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  <row Id="1" PostTypeId="1" AcceptedAnswerId="83" CreationDate="2020-04-28T18:44:35.860" Score="57" ViewCount="1710" Body="&lt;p&gt;For small molecules, NIST has a database of experimentally determined geometries &lt;a href=&quot;https://cccbdb.nist.gov/expgeom1x.asp&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, and &lt;em&gt;ab initio&lt;/em&gt; geometries &lt;a href=&quot;https://cccbdb.nist.gov/geom1x.asp&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I wonder if there is something similar for materials?&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-17T22:22:58.040" LastActivityDate="2021-01-07T17:25:31.120" Title="Is there a database where we can find previously determined geometries of materials?" Tags="|ab-initio-calculations|crystal-structure|databases|structure|experimental|" AnswerCount="7" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2" PostTypeId="1" AcceptedAnswerId="11" CreationDate="2020-04-28T18:49:11.420" Score="54" ViewCount="1520" Body="&lt;p&gt;It is understood that finding &quot;the&quot; universal functional is an NP-complete problem. However, progressively better functionals have been constructed decade after decade and fitted to more and more comprehensive datasets. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is the closest humans have achieved, to a universal functional?&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-20T00:28:45.107" LastActivityDate="2022-01-09T10:09:42.887" Title="What is the closest thing we have to &quot;the&quot; universal density functional?" Tags="|density-functional-theory|ab-initio-calculations|functional|" AnswerCount="5" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3" PostTypeId="1" AcceptedAnswerId="133" CreationDate="2020-04-28T19:03:08.227" Score="21" ViewCount="287" Body="&lt;p&gt;On &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;noreferrer&quot;&gt;basis set exchange&lt;/a&gt;, the only correlation consistent (cc)  basis sets for potassium, are relativistic (labelled by X2C). Very recently (I consider 2017 quite recent, because most Dunning basis sets date back to the late 1980s) the &lt;a href=&quot;http://www.grant-hill.group.shef.ac.uk/ccrepo/potassium/kbasis.php&quot; rel=&quot;noreferrer&quot;&gt;ccRepo&lt;/a&gt; has provided a basis set for potassium that &quot;was constructed by re-contracting the DK (relativistic Douglas-Kroll) set for a non-relativistic Hamiltonian&quot;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;I am curious why there was never any basis set for potassium that was originally contracted for a non-relativistic Hamiltonian?&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I understand that potassium is not a light element, however non-relativistic cc basis sets have existed all along for the elements all the way up to krypton, which is much heavier than potassium. Non-relativistic cc basis sets have even been made recently by the group of Angela Wilson, up to xenon, which is almost triple as heavy (so in some sense, triple as relativistic) as potassium.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-04-30T00:08:34.377" LastActivityDate="2020-08-07T21:17:29.613" Title="Why were no correlation consistent basis sets for potassium contracted for a non-relativistic Hamiltonian?" Tags="|relativistic|basis-sets|heavy-elements|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4" PostTypeId="5" CreationDate="2020-04-28T19:07:18.703" Score="0" Body="&lt;p&gt;Databases are widely used in material/molecular modeling. Common examples store input parameters for simulations (&lt;em&gt;e.g.&lt;/em&gt; system geometries, &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;electronic structure basis sets&lt;/a&gt;, &lt;a href=&quot;http://gaussian.com/scrf/?tabid=7&quot; rel=&quot;nofollow noreferrer&quot;&gt;solvent parameters&lt;/a&gt;), properties computed from prior calculations, and benchmark data on experimental systems. &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-29T11:29:59.987" LastActivityDate="2020-04-29T11:29:59.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5" PostTypeId="4" CreationDate="2020-04-28T19:07:18.703" Score="0" Body="For questions about finding and using databases of material and molecular properties." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-29T11:29:44.883" LastActivityDate="2020-04-29T11:29:44.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6" PostTypeId="2" ParentId="1" CreationDate="2020-04-28T19:11:22.400" Score="39" Body="&lt;p&gt;There is the &lt;strong&gt;Materials Project&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;https://materialsproject.org/&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the site:&#xA;&lt;em&gt;Harnessing the power of supercomputing and state of the art electronic structure methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials.&lt;/em&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the experimental view, there are databases like ICDD (&lt;a href=&quot;http://www.icdd.com/&quot; rel=&quot;noreferrer&quot;&gt;http://www.icdd.com/&lt;/a&gt;) with the x-ray crystallographic determined structures.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-04-28T19:11:22.400" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7" PostTypeId="1" AcceptedAnswerId="760" CreationDate="2020-04-28T19:17:27.477" Score="20" ViewCount="342" Body="&lt;p&gt;Diffuse functions are often added to basis sets using &quot;even-tempered&quot; exponents, or sometimes I have heard the phrase &quot;even tempering&quot;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.23931&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; by Jacek Koput, the author says &quot;the customary even-tempered exponents were calculated in this work by multiplying the exponent of the outermost primitive function of a given angular symmetry in the valence basis set by a factor of 0.4.&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The factor of 0.4 (or factors with a very similar value, such as 0.3) have been used in various other papers, but in my experience the factor is chosen without any detailed explanation. Is there any reason why the numerical factor should be specifically 0.4 (or similar)? &lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-04-30T00:55:05.427" LastActivityDate="2020-05-17T18:27:09.767" Title="When using the &quot;even tempered method&quot; for augmenting basis sets, what justification is there for the numerical factor which is used?" Tags="|basis-sets|ab-initio-calculations|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8" PostTypeId="2" ParentId="1" CreationDate="2020-04-28T19:24:08.823" Score="40" Body="&lt;p&gt;I agree with &lt;a href=&quot;https://materials.stackexchange.com/a/6/30&quot;&gt;the other answer&lt;/a&gt; but there are many other resources:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://crystallography.net/cod/&quot; rel=&quot;noreferrer&quot;&gt;Open Crystallographic Database&lt;/a&gt; which includes a large set of experimental crystal structures.&lt;/li&gt;&#xA;&lt;li&gt;There's a related &lt;a href=&quot;http://www.crystallography.net/tcod/&quot; rel=&quot;noreferrer&quot;&gt;Theoretical Crystallographic Open Database&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;For zeolites, there's the &lt;a href=&quot;http://www.iza-structure.org/databases/&quot; rel=&quot;noreferrer&quot;&gt;IZA Database&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;For MOFs, there's the &lt;a href=&quot;https://gregchung.github.io/CoRE-MOFs/&quot; rel=&quot;noreferrer&quot;&gt;CoRE MOF database&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://aflowlib.org&quot; rel=&quot;noreferrer&quot;&gt;Aflow&lt;/a&gt; also has a good repository&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://nomad-repository.eu&quot; rel=&quot;noreferrer&quot;&gt;NOMAD&lt;/a&gt; has a variety of materials data, including geometries&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-04-28T19:24:08.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9" PostTypeId="1" AcceptedAnswerId="557" CreationDate="2020-04-28T19:45:49.597" Score="36" ViewCount="1186" Body="&lt;p&gt;In terms of energy, how are van der Waals forces modelled (are there formulas/laws that govern these)?&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="5" LastEditDate="2020-05-14T21:15:39.723" LastActivityDate="2020-05-14T21:15:39.723" Title="In molecular mechanics, how are van der Waals forces modelled?" Tags="|molecular-dynamics|intermolecular-forces|molecular-mechanics|interatomic-potentials|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10" PostTypeId="2" ParentId="9" CreationDate="2020-04-28T19:49:25.800" Score="20" Body="&lt;p&gt;You are looking for &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;noreferrer&quot;&gt;Lennard-Jones potential&lt;/a&gt;. Basically, the interatomic interaction is modeled by this formula:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U(r) = 4 \epsilon \Bigg [ \Big ( \frac{\sigma}{r} \Big )^{12} - \Big ( \frac{\sigma}{r} \Big )^{6} \Bigg ]$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Particularly the term &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; in the above formula describes long-range attraction force based on van der Waals theory.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'll elaborate a bit more about my answer here. As Lucas said there is no universal model for capturing the behavior of van der Waals forces and you could generalize the Lennard-Jones potential as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U(r) = 4 \epsilon \Bigg [ \Big ( \frac{\sigma}{r} \Big )^{m} - \Big ( \frac{\sigma}{r} \Big )^{n} \Bigg ]$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you see, due to the fact that always molecular dynamics boxes are finite in terms of length, no matter how big is your box and how far you molecules are &lt;span class=&quot;math-container&quot;&gt;$U(r) \neq 0$&lt;/span&gt;. This causes a problem when you put a periodic boundary condition and the image of an atom interacts with itself, which is obviously incorrect. You could modify this Lennard-Jones potential and define a cut off value to reduce &lt;span class=&quot;math-container&quot;&gt;$U(r)$&lt;/span&gt; to zero for &lt;span class=&quot;math-container&quot;&gt;$r &amp;gt; r_{c}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$r_{c}$&lt;/span&gt; is the cut off radius, but still induces some other trouble due to non-continuity of force (first derivative of the potential). Another common model to capture van der Waals forces is called soft-potential, defined as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U(r) = D_{e} \Big( 1 - \exp{(-a(r-r_{e}))} \Big)^{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This potential comes from the solution of a quantum harmonic oscillator. &lt;span class=&quot;math-container&quot;&gt;$D_{e}$&lt;/span&gt; is the height of the potential well, and &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; controls its width. &lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-04-30T16:12:04.837" LastActivityDate="2020-04-30T16:12:04.837" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11" PostTypeId="2" ParentId="2" CreationDate="2020-04-28T19:51:01.910" Score="42" Body="&lt;p&gt;I think this question somewhat comes down to what &quot;camp&quot; of DFT progression you subscribe to. I should specify upfront that this summary is mainly centered around molecular systems, so some of the recommendations likely vary for materials where the computational workload can often be much greater.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One side really emphasizes accuracy with respect to experiment and is somewhat less concerned with the physical interpretation of the functional form. These groups make efforts to directly improve the accuracy of functionals with respect to experiment by extensive fitting and parameterization. Some functionals that fit into this category would be the &lt;a href=&quot;https://en.wikipedia.org/wiki/Minnesota_functionals&quot; rel=&quot;noreferrer&quot;&gt;Minnesota Functionals&lt;/a&gt; from the Truhlar group, as well the ωB97X and ωB97M functionals from the Head-Gordon group. Based on fairly extensive benchmarking (see this &lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;excellent paper&lt;/a&gt;), these functionals are tough to beat for a wide variety of energetic metrics and types of molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other side, the form of functionals is more physically motivated. This is done by ensuring the functional satisfies certain exact constraints of the &quot;universal functional&quot;. A prominent example of this type is the &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/1511/1511.01089.pdf&quot; rel=&quot;noreferrer&quot;&gt;SCAN functional&lt;/a&gt; from Perdew et al. While these types of functionals have not been able to achieve the same experimental accuracy as more heavily parameterized functionals, there is a chance that they are more robust and amenable to improvement, as they exactly match known properties of the &quot;universal functional&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So it depends in what you are interested. If you want the closest functional form to the &quot;universal functional&quot;, you would likely want something from the second camp. However, if your interest is in what will give you the best results for a wide range of complexes/materials right now, you will likely want to go with a functional that has been extensively parameterized on a large training set. &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-28T21:01:02.220" LastActivityDate="2020-04-28T21:01:02.220" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12" PostTypeId="1" AcceptedAnswerId="21" CreationDate="2020-04-28T19:57:37.250" Score="33" ViewCount="1871" Body="&lt;p&gt;In wavefunction methods the accuracy of the description of a system of electrons can be improved systematically starting from a reference, usually a Hartree-Fock wavefunction. This difference between the HF energy and the true non-relativistic energy is called (Coulomb) correlation energy and, as far as I know, it can be divided in, at least, two types: static correlation and dynamic correlation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Dynamic correlation can be described by perturbative methods or Coupled Cluster theory, while static correlation needs multi-reference descriptions. Although the definition of dynamic and static correlation can be ambiguous, in some cases the effects of static correlation can be &quot;separated&quot; from dynamic effects and it becomes important to know what correlated method is needed.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In DFT, however, it seems that the amount of dynamic correlation, introduced by the exchange-correlation (XC) potential, is unspecified. Moreover, Kohn-Sham orbitals are constructed such that they reproduce the real electron density, which means that KS orbitals account some correlation effects. Also, the KS exchange energy is based only on a &lt;em&gt;single&lt;/em&gt; determinant, thus, one can think that static effects are neglected. However, I'm not really sure about that sentence.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, the question is, &lt;strong&gt;what correlation effects are included in DFT?&lt;/strong&gt; &lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="63" LastEditDate="2020-04-29T22:44:35.350" LastActivityDate="2020-04-29T22:44:35.350" Title="What correlation effects are included in DFT?" Tags="|density-functional-theory|correlation-energy|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="13" PostTypeId="1" CreationDate="2020-04-28T20:14:57.480" Score="17" ViewCount="293" Body="&lt;p&gt;The FCIDUMP format is widely used for the communication of one- and two- body integrals. I wonder what formats are used for 1-/2-RDMs, which are important in many basis rotation or compression tasks.&lt;/p&gt;&#xA;&lt;p&gt;How is it done in the various mainstream software (MOLCAS, MOLDEN, etc.)?&lt;/p&gt;&#xA;" OwnerUserId="11" LastEditorUserId="5" LastEditDate="2020-09-03T02:43:07.647" LastActivityDate="2020-09-03T02:43:07.647" Title="How are one-/two- particle reduced density matrices printed in mainstream programs?" Tags="|software|molpro|fcidump|open-molcas|reduced-density-matrix|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="14" PostTypeId="5" CreationDate="2020-04-28T20:20:27.873" Score="0" Body="&lt;p&gt;Density Functional Theory is an electronic structure theory model developed by Pierre Hohenberg and Walter Kohn in the early 1960s. The so called Hohenberg-Kohn theorems show that:  &lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The ground state energy of an N-electron system is uniquely determined by its electron density &lt;/li&gt;&#xA;&lt;li&gt;There exists a functional of the ground state energy and the exact ground state electron density minimizes this functional. &lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;These theorems in principle allow the complicated problem of determining the 3N dimensional wavefunction of the system via the Schrodinger equation to be reduced to the problem of determining the 3 dimensional electron density that minimizes the energy functional.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Kohn-Sham (KS) DFT refers to a version of DFT in which the electrons are treated as noninteracting and moving within an effective potential. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The exact energy functional (in particular, the exchange-correlation portion of the KS potential) is not expressible analytically, so numerous approximate functionals have emerged.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="3" LastEditDate="2020-04-29T11:31:54.857" LastActivityDate="2020-04-29T11:31:54.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="15" PostTypeId="4" CreationDate="2020-04-28T20:20:27.873" Score="0" Body="For questions about simulations using Density Functional Theory" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-29T11:31:58.620" LastActivityDate="2020-04-29T11:31:58.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="16" PostTypeId="1" CreationDate="2020-04-28T20:23:51.000" Score="8" ViewCount="109" Body="&lt;p&gt;What are the main mathematical approaches to materials modeling? This can include both analytical (closed-form) and numerical techniques.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-04-28T20:50:33.383" LastActivityDate="2020-04-28T20:50:33.383" Title="What are the main mathematical approaches to materials modeling?" Tags="|density-functional-theory|molecular-mechanics|molecular-modeling|mathematical-modeling|" AnswerCount="0" CommentCount="4" ClosedDate="2020-04-30T00:59:29.947" ContentLicense="CC BY-SA 4.0" />
  <row Id="17" PostTypeId="1" CreationDate="2020-04-28T20:29:56.390" Score="27" ViewCount="609" Body="&lt;p&gt;What are the main computational frameworks used in materials modeling? Software packages can include those designed to run on both classical and quantum devices.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-04-28T21:27:05.960" LastActivityDate="2021-04-17T22:39:33.907" Title="What are the main computational frameworks used in materials modeling?" Tags="|computational-frameworks|software|" AnswerCount="4" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="18" PostTypeId="1" AcceptedAnswerId="25" CreationDate="2020-04-28T20:37:25.817" Score="30" ViewCount="637" Body="&lt;p&gt;I heard that machine learning techniques on materials use a large quantity of data to make predictions of a variety of features; for instance, a crystal structure. Data collected from empirical or high-level calculations could be used to correct DFT calculations for materials at, presumably, lower computational cost.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Basically, I would like to know what are the current advances made in machine learning methods applied to molecular systems or the design of materials.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="52" LastEditDate="2020-05-03T00:46:26.053" LastActivityDate="2023-09-12T12:46:56.187" Title="What is the current status of machine learning applied to materials or molecular systems?" Tags="|reference-request|machine-learning|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="19" PostTypeId="1" AcceptedAnswerId="22" CreationDate="2020-04-28T20:49:29.670" Score="27" ViewCount="581" Body="&lt;p&gt;We say a system has &lt;em&gt;multireference character&lt;/em&gt; if it is not well described at the SCF level by a single configuration/Slater determinant. Not accounting for this can lead to errors in post-SCF methods, which often rely on expansions of additional configurations generated from the SCF solution. It is fairly easy that this sort of error has occurred once a post-SCF solution has been constructed, but are there ways to predict this without performing a high level calculation?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would be interested in both heuristic methods (&lt;em&gt;e.g.&lt;/em&gt; compounds containing atom X or structure Y tend to have issues) as well as more quantitative approaches (&lt;em&gt;e.g.&lt;/em&gt; X property from a DFT calculation is a good diagnostic for multireference character).&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-04-30T10:47:44.460" Title="How to determine, a priori, whether a compound has multireference character?" Tags="|correlation-energy|electronic-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="20" PostTypeId="2" ParentId="2" CreationDate="2020-04-28T20:53:32.673" Score="18" Body="&lt;p&gt;I'm not entirely sure what you mean by &quot;universal&quot;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you mean a functional that can model a wide variety of materials with reasonable success, probably the closest we have are GGA functionals. They are not necessarily the most accurate, but they are used to regularly model metals and semiconductors. They get decent results, despite their known shortcomings (i.e. inaccurate band gaps). Hybrid functionals are increasingly becoming the norm, as we have fast computers that can deal with slow hybrid calculations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you mean a functional that is most accurate, there is no one functional that always works for every material. Presumably as you move up the DFT ladder, functionals get better. But this isn't always the case. For instance, hybrid functionals can get very different results for the same material. Some hybrid functionals may overestimate the band gap. Some underestimate. Some get the correct band gap. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My usual operating procedure is to look in the literature, see what has worked, and then use that as a jumping off point. &lt;/p&gt;&#xA;" OwnerUserId="38" LastActivityDate="2020-04-28T20:53:32.673" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="21" PostTypeId="2" ParentId="12" CreationDate="2020-04-28T20:58:15.227" Score="27" Body="&lt;p&gt;By definition all of them, because Density Functional Theory is in principle exact. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Becke states:&lt;sup&gt;[1]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Density-functional theory (DFT) is a subtle, seductive, provocative business. Its basic premise, that all the intricate motions and pair correlations in a many-electron system are somehow contained in the total electron density alone, is so compelling it can drive one mad.&lt;br&gt;&#xA;  [...]&lt;br&gt;&#xA;  Let us introduce the acronym DFA at this point for “density-functional approximation.” If you attend DFT meetings, you will know that Mel Levy often needs to remind us that DFT is exact. The failures we report at meetings and in papers are not failures of DFT, but failures of DFAs.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;DFT does model the exact electron density, hence all electron correlation. The problem becomes which of part of correlation is treated by the particular DFA, and how. Given the large number of approaches and parameterisations, this is probably too much to handle on this platform.&lt;sup&gt;[2]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you also state that the definition of dynamic and static correlation can be ambiguous, it is at first only really meaningful for wave-function based approaches. As you separate the electron density differently in DFA, you have even more ambiguity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You can see that in real life, when you calculate 'strongly-correlated' systems with DFT, and surprisingly they manage quite well, where wave-function based methods completely fail.&lt;br&gt;&#xA;Another point in favour of this is the broken symmetry approach often taken, see for example in the popular Orca input library: &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/dft/broken-symmetry-dft&quot; rel=&quot;noreferrer&quot;&gt;broken symmetry DFT&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Becke, A. D. Perspective: Fifty years of density-functional theory in chemical physics. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2014,&lt;/strong&gt; &lt;em&gt;140&lt;/em&gt; (18), 18A301. &lt;a href=&quot;https://doi.org/10.1063/1.4869598&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1063/1.4869598&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I have written a bit more about functionals, their shortcomings and advantages, etc. at Chemistry.se: &lt;a href=&quot;https://chemistry.stackexchange.com/q/27302/4945&quot;&gt;DFT Functional Selection Criteria&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="49" LastActivityDate="2020-04-28T20:58:15.227" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="22" PostTypeId="2" ParentId="19" CreationDate="2020-04-28T21:22:21.347" Score="20" Body="&lt;p&gt;This is not going to be a full answer, but maybe a starting point, a pointer to somewhat troubled systems. The general keyword here is &lt;strong&gt;degeneracy&lt;/strong&gt;. Whenever you have fewer electrons than fit in the degenerate orbitals, two things may happen: In the simple case the molecule will distort, see aromaticity and anti-aromaticity. In the complicated case, you guessed it, you'll have a multireference system. A popular example for this is the rotational barrier of ethene, where you have degenerate, but orthogonal orbitals at the 90° dihedral. Two electrons, two orbitals, forced singlet will lead to no solution. If you treat it with TCSCF (two-configuration SCF) you'll get a qualitative solution, similar for CAS[2,2], and even UHF.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So the short and very unsatisfactory answer is, whenever you see a high symmetry, you should be careful.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another obvious point is: anything with transition metals. Partially unoccupied d-orbitals will almost always need multi-reference treatment. In other words: &lt;a href=&quot;https://web.archive.org/web/20150909233705/http://esqc.ups-tlse.fr/11/lectures/ESQC-Neese-1-1x2.pdf&quot; rel=&quot;noreferrer&quot;&gt;Transition-metal chemistry is a graveyard for MP2 (large pdf via the Internet Archive))&lt;/a&gt;, dito in &lt;a href=&quot;https://books.google.de/books?id=qm5cCwAAQBAJ&amp;amp;pg=PT220&amp;amp;lpg=PT220&amp;amp;dq=Transition-metal+chemistry+is+a+graveyard+for+MP2&quot; rel=&quot;noreferrer&quot;&gt;Koch/Holthausen's DFT book&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;Some practical approaches:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate the fractional occupation number weighted electron density (FOD). This is fast and can be done at the semi-empirical level.&lt;sup&gt;[1]&lt;/sup&gt; I don't think there is a faster (practical) way of doing this. (&lt;em&gt;I cannot believe I forgot about this before.&lt;/em&gt;)&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A more conventional approach: UHF for an initial guess will give you approximate natural orbitals. You can use this to determine an active space, if you are so inclined.&lt;sup&gt;[2]&lt;/sup&gt; &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;UDFA and stability checks. Most Density Functional Methods are surprisingly robust about multi-reference character. If you run a calculation, then perform a stability analysis, which runs into a broken symmetry solution, you'll need to do multi-reference wave function methods.&lt;br&gt;&#xA;In general, performing a cheap method, will likely give you a HOMO-LUMO gap. When even your program of choice warns you about it being small, you might want to check for MR character.&lt;sup&gt;[3]&lt;/sup&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Obviously, your mileage may vary, and you need to check what is feasible for your system.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Resources:&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Original Paper: Grimme, S.; Hansen, A. A Practicable Real-Space Measure and Visualization of Static Electron-Correlation Effects. &lt;em&gt;Angew. Chem. Int. Ed.&lt;/em&gt; &lt;strong&gt;2015,&lt;/strong&gt; &lt;em&gt;54&lt;/em&gt; (42), 12308–12313. &lt;a href=&quot;https://doi.org/10.1002/anie.201501887&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/anie.201501887&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Please see on Chemistry.se: &lt;a href=&quot;https://chemistry.stackexchange.com/q/89470/4945&quot;&gt;Is there a reliable way to determine if a chemical system is more suited to be calculated using a multireference method instead of DFT?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Orca input library on FOD: &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/orbital-and-density-analysis/fod-analysis&quot; rel=&quot;noreferrer&quot;&gt;FOD analysis&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;xtb manual: &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/properties.html#fractional-occupation-density-fod-calculation&quot; rel=&quot;noreferrer&quot;&gt;Fractional Occupation Density Calculation&lt;/a&gt;, also see the repository on &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;See Chemistry.se for some more details: &lt;a href=&quot;https://chemistry.stackexchange.com/q/69929/4945&quot;&gt;Is it reasonable to use natural orbitals of an unrestricted HF calculation as a basis to start a CASSCF calculation for a radical&lt;/a&gt;  &lt;/li&gt;&#xA;&lt;li&gt;Some related questions on Chemistry.se (I know this gets old, but that's where the resources are.): &#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/q/49174/4945&quot;&gt;U- or RO-method for Singlet-Triplet Gap?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/q/55736/4945&quot;&gt;Calculating singlet-triplet gap and open-shell singlet character&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;this is also a bit related: &lt;a href=&quot;https://chemistry.stackexchange.com/q/34215/4945&quot;&gt;Similarities and Differences between Resonance and MCSCF treatments&lt;/a&gt;&lt;a href=&quot;https://doi.org/10.1002/anie.201501887&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Angew. Chem. Int. Ed.&lt;/em&gt; &lt;strong&gt;2015,&lt;/strong&gt; &lt;em&gt;54&lt;/em&gt; (42), 12308–12313&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="49" LastEditorUserId="49" LastEditDate="2020-04-30T10:47:44.460" LastActivityDate="2020-04-30T10:47:44.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="23" PostTypeId="2" ParentId="9" CreationDate="2020-04-28T21:46:13.997" Score="23" Body="&lt;p&gt;Additional to Alone Programmer's answer. The Lennard-Jones Potential (LJ 12-6) is the standard, but is not unique, in some cases the factor of 6 is changed to 8 to simulate better the hydrogen bonds. &#xA;Also, there is the Buckingham potential, where the repulsion part (&lt;span class=&quot;math-container&quot;&gt;$r^{12}$&lt;/span&gt; term) is modified to the exponential term. But the attractive long-range term (&lt;span class=&quot;math-container&quot;&gt;$r^{6}$&lt;/span&gt;) is the same.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;LJ 12-6 fits very well for the potential energy surface of a noble gas dimer. The epsilon term is the maximum depth of the curve, and sigma is the radius where the potential energy is zero (short distance). When the LJ is used to simulate the interaction of different atomic species, there is not a rule to determine the sigma and epsilon terms... and there are geometrical and arithmetic averages, using the values for the same-species interaction for each atom.&lt;/p&gt;&#xA;" OwnerUserId="61" LastEditorUserId="37" LastEditDate="2020-04-30T08:47:31.130" LastActivityDate="2020-04-30T08:47:31.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="24" PostTypeId="1" CreationDate="2020-04-28T22:11:11.937" Score="13" ViewCount="222" Body="&lt;p&gt;I was wondering if all the recent success of perovskite solar cells was accomplished purely experimentally or if there was some materials modeling aspect in it.&lt;/p&gt;&#xA;" OwnerUserId="42" LastEditorUserId="5" LastEditDate="2020-06-26T22:05:35.700" LastActivityDate="2020-08-14T14:49:56.767" Title="Has materials modeling made any specific contribution to the success of perovskite solar cells, or has it only been experimental?" Tags="|perovskites|solar-cells|materials-design|experimental|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="25" PostTypeId="2" ParentId="18" CreationDate="2020-04-28T22:26:14.283" Score="23" Body="&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Here is state of the art research:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Smith J.S. et al, &lt;em&gt;Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning&lt;/em&gt;, July 2019&lt;/strong&gt; &lt;a href=&quot;https://doi.org/10.1038/s41467-019-10827-4&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Nat. Commun.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;10&lt;/em&gt; (1), No. 2903&lt;/a&gt;, &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pubmed/31263102&quot; rel=&quot;noreferrer&quot;&gt;PMID: 31263102&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist's toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy but are computationally expensive and scale poorly to large systems, while classical force fields are cheap and scalable, but lack transferability to new systems. Machine learning can be used to achieve the best of both approaches. Here we train a general-purpose neural network potential that approaches CCSD(T)/CBS accuracy on benchmarks for reaction thermochemistry, isomerization, and drug-like molecular torsions. This is achieved by training a network to DFT data then using transfer learning techniques to retrain on a dataset of gold standard QM calculations (CCSD(T)/CBS) that optimally spans chemical space. The resulting potential is broadly applicable to materials science, biology, and chemistry, and billions of times faster than CCSD(T)/CBS calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Here's a nice review paper:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Dereinger, V.L. et. al., &lt;em&gt;Machine Learning Interatomic Potentials as Emerging Tools for Materials Science&lt;/em&gt;, Nov 2019&lt;/strong&gt; &lt;a href=&quot;https://doi.org/10.1002/adma.201902765&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Adv. Mater.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;31&lt;/em&gt; (46), 1902765&lt;/a&gt;, &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pubmed/31486179&quot; rel=&quot;noreferrer&quot;&gt;PMID: 31486179&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Atomic-scale modeling and understanding of materials have made remarkable progress, but they are still fundamentally limited by the large computational cost of explicit electronic-structure methods such as density-functional theory. This Progress Report shows how machine learning (ML) is currently enabling a new degree of realism in materials modeling: by &quot;learning&quot; electronic-structure data, ML-based interatomic potentials give access to atomistic simulations that reach similar accuracy levels but are orders of magnitude faster. A brief introduction to the new tools is given, and then, applications to some select problems in materials science are highlighted: phase-change materials for memory devices; nanoparticle catalysts; and carbon-based electrodes for chemical sensing, supercapacitors, and batteries. It is hoped that the present work will inspire the development and wider use of ML-based interatomic potentials in diverse areas of materials research.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;And here's a nice overview:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Mater &amp;amp; Coote, &lt;em&gt;Deep Learning in Chemistry&lt;/em&gt;, June, 2019&lt;/strong&gt; &lt;a href=&quot;https://doi.org/10.1021/acs.jcim.9b00266&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Inf. Model.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;59&lt;/em&gt; (6), 2545–2559&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in the data. Over the last eight years, its abilities have increasingly been applied to a wide variety of chemical challenges, from improving computational chemistry to drug and materials design and even synthesis planning. This review aims to explain the concepts of deep learning to chemists from any background and follows this with an overview of the diverse applications demonstrated in the literature. We hope that this will empower the broader chemical community to engage with this burgeoning field and foster the growing movement of deep learning accelerated chemistry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="36" LastEditorUserId="49" LastEditDate="2020-04-28T23:02:02.333" LastActivityDate="2020-04-28T23:02:02.333" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="26" PostTypeId="1" CreationDate="2020-04-28T22:33:05.007" Score="17" ViewCount="111" Body="&lt;p&gt;There is a huge hype on perovskites and more specifically on their applications in solar cell technologies. We now know that perovskites have a lot of unique properties (high-absorption coefficient, long-range ambipolar charge transport, low exciton-binding energy, high dielectric constant, ferroelectric properties (&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B9780128129159000071&quot; rel=&quot;noreferrer&quot;&gt;source&lt;/a&gt;)) that may deem them interesting for a variety of optoelectronic applications.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is how did all of this hype get started?&lt;/p&gt;&#xA;" OwnerUserId="42" LastEditorUserId="118" LastEditDate="2020-04-29T15:22:23.670" LastActivityDate="2020-05-04T18:16:23.253" Title="What specifically was it, that helped perovskites become so popular?" Tags="|perovskites|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="27" PostTypeId="1" AcceptedAnswerId="29" CreationDate="2020-04-28T23:28:59.813" Score="20" ViewCount="241" Body="&lt;p&gt;It's fairly routine to calculate absorption of single molecules, essentially this can be done by calculating the excited-state wavefunctions and the oscillator strengths between the states. For example, using TD-DFT or configuration interaction methods. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However nanoparticles behave much differently, from what I understand the electrons behave more like a particle in a box. The size and shape of the particle directly controls the optical properties. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What type of software can be used to model optical properties of nanoparticles and how do these approaches differ from molecules? &lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="189" LastEditDate="2020-05-04T12:18:29.760" LastActivityDate="2020-05-31T23:44:54.407" Title="What software are used to model the optical behavior of metallic nanoparticles?" Tags="|software|nanoparticles|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="28" PostTypeId="2" ParentId="1" CreationDate="2020-04-29T00:14:21.213" Score="24" Body="&lt;p&gt;In addition to above recommendations, I also use American Mineralogist Crystal Structure Database. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://rruff.geo.arizona.edu/AMS/amcsd.php&quot; rel=&quot;noreferrer&quot;&gt;http://rruff.geo.arizona.edu/AMS/amcsd.php&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The good thing about this place is that you can check the publications related to a specific geometry. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I usually use AMCSD and Materialsproject. &lt;/p&gt;&#xA;" OwnerUserId="74" LastEditorUserId="5" LastEditDate="2020-04-29T11:29:18.970" LastActivityDate="2020-04-29T11:29:18.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="29" PostTypeId="2" ParentId="27" CreationDate="2020-04-29T01:28:24.157" Score="12" Body="&lt;p&gt;There are several DFT based commercial or open source softwares that could be used to simulate the optical properties of nanomaterials, particularly metallic nanoparticles. Basically, what you are looking for is calculating the susceptibility tensor from Kubo-Greenwood relation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\chi_{ij}(\omega) = \frac{e^{2}}{\hbar m_{e}^{2} V} \sum_{n,m,\mathbf{k}} \frac{f_{m,\mathbf{k}} - f_{n,\mathbf{k}}}{\omega_{nm}^{2}(\mathbf{k}) (\omega_{nm}(\mathbf{k})-\omega-i\frac{\Gamma}{\hbar})}p_{nm}^{i}(\mathbf{k})p_{mn}^{j}(\mathbf{k})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$p_{nm}^{i}(\mathbf{k}) = \langle n\mathbf{k} | \mathbf{p}^{i} | m\mathbf{k}\rangle$&lt;/span&gt; is i-th component of the momentum operator between states n and m. &lt;span class=&quot;math-container&quot;&gt;$m_{e}$&lt;/span&gt; is the electron mass, &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt; is electron charge, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the volume, &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; the energy broadening, &lt;span class=&quot;math-container&quot;&gt;$\hbar\omega_{nm}(\mathbf{k})= E_{n}(\mathbf{k}) - E_{m}(\mathbf{k})$&lt;/span&gt;, and finally &lt;span class=&quot;math-container&quot;&gt;$f_{n,\mathbf{k}}$&lt;/span&gt; is the Fermi function evaluated at the band energy of &lt;span class=&quot;math-container&quot;&gt;$E_{n}(\mathbf{k})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Relative dielectric constant (&lt;span class=&quot;math-container&quot;&gt;$\epsilon_{r}$&lt;/span&gt;), polarizability (&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;), and optical conductivity (&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;) are related to susceptibility as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon_{r}(\omega) = 1 + \chi(\omega)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\alpha(\omega) = V \epsilon_{0} \chi(\omega)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sigma(\omega) = -i \omega \epsilon_{0} \chi(\omega)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, the refractve indices are derived from relative dielectric constant (&lt;span class=&quot;math-container&quot;&gt;$\epsilon_{r}$&lt;/span&gt;) as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$n(\omega) + i\kappa(\omega) = \sqrt{\epsilon_{r}(\omega)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h1&gt;QuantumATK&lt;/h1&gt;&#xA;&lt;p&gt;An example of commercial software that could be used to extract these optical properties for metallic nanoparticles is &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;noreferrer&quot;&gt;QuantumATK&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-31T23:44:54.407" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="30" PostTypeId="1" CreationDate="2020-04-29T03:28:28.687" Score="12" ViewCount="104" Body="&lt;p&gt;I would like to build a &lt;a href=&quot;https://en.wikipedia.org/wiki/Nucleation&quot; rel=&quot;noreferrer&quot;&gt;nucleation&lt;/a&gt; model for Ti-6Al-4V by finding coefficients for the &lt;a href=&quot;https://en.wikipedia.org/wiki/Avrami_equation&quot; rel=&quot;noreferrer&quot;&gt;Avrami equation&lt;/a&gt;. Is it possible to estimate these coefficients (or find approximate error bounds for them) using molecular dynamic simulations?&lt;/p&gt;&#xA;" OwnerUserId="79" LastEditorUserId="7" LastEditDate="2020-06-26T21:44:09.163" LastActivityDate="2020-06-26T21:44:09.163" Title="Is it possible to parametize a nucleation model from molecular dynamics simulation?" Tags="|molecular-dynamics|nucleation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="31" PostTypeId="2" ParentId="17" CreationDate="2020-04-29T03:48:08.087" Score="23" Body="&lt;h1&gt;Electronic Structure Theory&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Much of the behavior we observe from molecules/materials arises from electronic interactions. These interactions are fundamentally quantum mechanical as are most of the approaches used to model them.&lt;/p&gt;&#xA;&lt;p&gt;To study electronic properties of a system, we typically solve some approximation of the electronic time in/dependent Schrodinger equation: &lt;span class=&quot;math-container&quot;&gt;\begin{equation}E\Psi=H\Psi\tag{1}\end{equation}&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}i\hbar\frac{d\Psi}{dt}=H\Psi\tag{2}\end{equation}&lt;/span&gt;&#xA;The wavefunction and energy allow a whole host of other properties to be determined, including charge transfer rates and various polarizabilities (along with their associated spectroscopic signals).&lt;/p&gt;&#xA;&lt;p&gt;The difficulty of solving the Schrodinger equation exactly has led to the development of a number of approximate schemes. Two commonly encountered types of approximations are wavefunction based methods, which build on top of the simple &lt;a href=&quot;https://en.wikipedia.org/wiki/Hartree%E2%80%93Fock_method&quot; rel=&quot;noreferrer&quot;&gt;Hartree-Fock&lt;/a&gt;, and &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;Density Functional Theory&lt;/a&gt;(DFT), which reframes the problem of solving for the system wavefunction that satisfies the Schrodinger equation to instead solving for the electron density that minimizes a particular energy functional.&lt;/p&gt;&#xA;&lt;p&gt;These approximations vary in computational complexity, which has led to varied use depending on the field. In molecular sciences, approaches such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Multi-configurational_self-consistent_field&quot; rel=&quot;noreferrer&quot;&gt;MCSCF&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Coupled_cluster&quot; rel=&quot;noreferrer&quot;&gt;Coupled Cluster&lt;/a&gt; are widely used due to their accuracy and clear direction for systematic improvement. For larger materials however, these methods are generally precluded by their high cost and so more economical approaches like DFT are far more common.&lt;/p&gt;&#xA;&lt;p&gt;There are number of software packages that have been developed to perform these calculations, each with a different emphasis (e.g. performance, number of features, ease of use/development, molecules vs materials, free vs proprietary). On the molecular side, &lt;a href=&quot;http://gaussian.com/&quot; rel=&quot;noreferrer&quot;&gt;Gaussian&lt;/a&gt;, &lt;a href=&quot;http://www.q-chem.com/&quot; rel=&quot;noreferrer&quot;&gt;Q-Chem&lt;/a&gt;, &lt;a href=&quot;http://www.nwchem-sw.org/index.php/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;NWChem&lt;/a&gt;, &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/&quot; rel=&quot;noreferrer&quot;&gt;GAMESS&lt;/a&gt;, and &lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt; are notable examples. For materials, &lt;a href=&quot;https://www.vasp.at/&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt;, &lt;a href=&quot;http://www.quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt;, &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt;&#xA;, and &lt;a href=&quot;https://www.cp2k.org/&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt; are more commonly used (among many other &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;electronic structure packages&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-01T04:20:01.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="32" PostTypeId="2" ParentId="30" CreationDate="2020-04-29T03:52:50.873" Score="9" Body="&lt;p&gt;You could use molecular dynamics simulation by assuming the &lt;a href=&quot;https://en.wikipedia.org/wiki/Embedded_atom_model&quot; rel=&quot;noreferrer&quot;&gt;Embedded Atom Model (EAM)&lt;/a&gt; potential for modeling their interatomic interaction of Ti, Al, and V atoms. You could define a completely random configuration of these atoms by the correct atomic ratio to define the Ti-6Al-4V alloy and then track the grain boundaries and estimate the grain size to extract the kinetic of your system (i.e. grain size vs. time) and fit the Avrami equation to this extracted kinetic from molecular dynamics to extract the coefficients. Find more information in my recent article &lt;a href=&quot;https://arxiv.org/abs/1907.01461&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. &lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-29T03:52:50.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="33" PostTypeId="5" CreationDate="2020-04-29T03:54:22.923" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-04-29T03:54:22.923" LastActivityDate="2020-04-29T03:54:22.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="34" PostTypeId="4" CreationDate="2020-04-29T03:54:22.923" Score="0" Body="For questions related to the use of machine learning techniques (neural networks, support vector machines, Gaussian process regression, etc) to study material or molecular properties." OwnerUserId="7" LastEditorUserId="10" LastEditDate="2020-05-01T10:00:56.307" LastActivityDate="2020-05-01T10:00:56.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="35" PostTypeId="1" CreationDate="2020-04-29T03:55:12.380" Score="16" ViewCount="171" Body="&lt;p&gt;I have some alloy microstructure images, showing elongated grains (darker colours) and the grain boundaries (lighter colours). If I take the Fourier transform of the image, there are directional bands in the Fourier image.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there a relationship between the angle of these bands in the Fourier image and the orientation of the grain boundaries in the real space image?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another observation is that if high frequencies are removed, and the inverse Fourier transform is taken, a significant amount of noise is removed, and I am mostly left with the grain boundaries of the microstructure.  Is there any other kind of useful information that can be extracted from the Fourier image?&lt;/p&gt;&#xA;" OwnerUserId="79" LastEditorUserId="5" LastEditDate="2020-07-04T13:41:49.060" LastActivityDate="2020-10-13T21:10:56.217" Title="What kind of information can be extracted from alloy microstructure images converted to Fourier space?" Tags="|grain-boundaries|alloys|fourier-transform|microstructure|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="36" PostTypeId="5" CreationDate="2020-04-29T03:56:33.147" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-04-29T03:56:33.147" LastActivityDate="2020-04-29T03:56:33.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="37" PostTypeId="4" CreationDate="2020-04-29T03:56:33.147" Score="0" Body="For questions about matter modeling software." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2022-07-31T23:10:23.270" LastActivityDate="2022-07-31T23:10:23.270" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="38" PostTypeId="5" CreationDate="2020-04-29T03:57:57.997" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-04-29T03:57:57.997" LastActivityDate="2020-04-29T03:57:57.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="39" PostTypeId="4" CreationDate="2020-04-29T03:57:57.997" Score="0" Body="For questions related to the use of or theory behind classical or ab initio molecular dynamics. " OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-02T18:27:21.260" LastActivityDate="2020-05-02T18:27:21.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="40" PostTypeId="2" ParentId="19" CreationDate="2020-04-29T05:08:48.963" Score="15" Body="&lt;p&gt;As Martin has said a practical way to decide if a molecule requires multi-reference treatment is to calculate the unrestricted Hartree Fock natural orbitals.&lt;sup&gt;[1]&lt;/sup&gt; Significant fractional occupancy of a UHF natural orbital indicates that the orbital should be included in the active space.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For a nonorthogonal finite basis set, they are given as&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{S}(\mathbf{D_\alpha+\mathbf{D_\beta}})\mathbf{S}\mathbf{C} = \mathbf{S}\mathbf{C}\mathbf{n},$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}$&lt;/span&gt; is the overlap matrix, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{D}_\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{D}_\beta$&lt;/span&gt; are the reduced first order density matrices for the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spins, respectively, the columns of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt; contain the coefficients of the natural orbitals, and the diagonal matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{n}$&lt;/span&gt; holds the occupation numbers. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Specifically wavefunction with significant fractional occupancy (roughly between 0.02 and 1.98) should constitute the active space for static (non-dynamical) correlation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, this can be performed in Molpro as &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;***, HF&#xA;symmetry,nosym &#xA;memory,400,m&#xA;orient,noorient&#xA;&#xA;basis=6-31G**&#xA;&#xA;geometry = {&#xA;N 0 0 0&#xA;O 0 0 1.75&#xA;}&#xA;&#xA;{UHF;save,2101.2}&#xA;{matrop&#xA;load,D,Den&#xA;load,S&#xA;natorb,Cnat,D&#xA;mult,SC,S,Cnat&#xA;tran,D_nat,D,SC  ! = SC' D SC&#xA;prid,D_nat&#xA;save,Cnat,2150.2&#xA;}&#xA;{put,molden,orbitals.gmolden;orbital,2101.2}&#xA;{put,molden,check.gmolden;orbital,2150.2}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Molden will automatically print the occupations in the orbital dump (2101.2) but the &lt;code&gt;matrop&lt;/code&gt; can be also used to solve the eigenvalue problem manually&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The result for example here is &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;   1.99999995   1.99999988   1.99987846   1.99937413   1.99796035   1.96525179   1.96022720   1.00000000   0.03977280   0.03474821   0.00203965   0.00062587   0.00012154   0.00000012   0.00000005   0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000  -0.00000000   0.00000000   0.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Which is in agreement with reference [1].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(If you do plan to do multi-reference however, do never use Hartree-Fock orbitals. &lt;strong&gt;They are the worst!&lt;/strong&gt; Use DFT orbitals as a starting place.) &lt;/p&gt;&#xA;&#xA;&lt;h2&gt;References:&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pulay, P.; Hamilton, T. P. UHF natural orbitals for defining and starting MC‐SCF calculations. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;1988,&lt;/strong&gt; &lt;em&gt;88&lt;/em&gt; (8), 4926–4933. &lt;a href=&quot;https://doi.org/10.1063/1.454704&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1063/1.454704&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="49" LastEditDate="2020-04-29T14:50:01.587" LastActivityDate="2020-04-29T14:50:01.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="41" PostTypeId="1" CreationDate="2020-04-29T06:13:10.503" Score="22" ViewCount="231" Body="&lt;p&gt;Materials Modeling helps give theoretical insight into the working of various materials and in turn helps enhance the working of these materials. But are there examples of discovery of new materials which was a direct consequence of modeling of materials? The example(s) may include materials with applications in any field.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2020-05-26T13:51:22.503" Title="Examples for results obtained from modeling materials having had a direct impact in discovery of new materials" Tags="|reference-request|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="42" PostTypeId="2" ParentId="1" CreationDate="2020-04-29T06:28:38.580" Score="26" Body="&lt;p&gt;Depending on what kind of materials looking for the following crystallographic databases can be relevant, too (unfortunately, for a cost):&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Inorganic Crystal Structure Database (ICSD) by Karlsruhe University:&#xA;&lt;a href=&quot;https://icsd.products.fiz-karlsruhe.de/&quot; rel=&quot;noreferrer&quot;&gt;https://icsd.products.fiz-karlsruhe.de/&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;ICSD by FIZ/NIST: &lt;a href=&quot;https://icsd.nist.gov/&quot; rel=&quot;noreferrer&quot;&gt;https://icsd.nist.gov/&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Cambridge Crystal Data Centre (CCDC):&#xA;&lt;a href=&quot;https://www.ccdc.cam.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;https://www.ccdc.cam.ac.uk/&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="91" LastActivityDate="2020-04-29T06:28:38.580" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="43" PostTypeId="1" CreationDate="2020-04-29T10:52:58.813" Score="14" ViewCount="223" Body="&lt;p&gt;To build a model using the &lt;a href=&quot;https://en.wikipedia.org/wiki/CALPHAD&quot; rel=&quot;noreferrer&quot;&gt;CALPHAD&lt;/a&gt; approach, i.e. &lt;a href=&quot;https://en.wikipedia.org/wiki/Gibbs_free_energy&quot; rel=&quot;noreferrer&quot;&gt;Gibbs free energy&lt;/a&gt; as a function of composition and temperature, typically taking the form of a Redlich-Kister polynomial, what kind of thermodynamic data needs to be collected from experiment (or from first principles calculations)?&lt;/p&gt;&#xA;" OwnerUserId="79" LastEditorUserId="5" LastEditDate="2020-07-22T02:36:01.847" LastActivityDate="2020-11-24T14:43:13.197" Title="What thermodynamic data is collected in order to build a CALPHAD model?" Tags="|gibbs-free-energy|thermodynamics|calphad|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="44" PostTypeId="1" CreationDate="2020-04-29T11:26:35.750" Score="17" ViewCount="191" Body="&lt;p&gt;I wish to calculate solution-phase dielectric constants (required for a Monte-Carlo model) for CoCl&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and TaS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; dissolved in DMF.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is it possible to estimate these constants from the solid-state values, or to obtain them from first-principles / molecular dynamics calculations?&lt;/p&gt;&#xA;" OwnerUserId="79" LastEditorUserId="5" LastEditDate="2020-07-22T02:36:38.703" LastActivityDate="2022-01-21T05:29:25.217" Title="Is there a way to obtain solution-phase dielectric constants?" Tags="|molecular-dynamics|transition-metals|dielectric-constants|solvation|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="45" PostTypeId="5" CreationDate="2020-04-29T12:42:37.820" Score="0" Body="&lt;p&gt;This tag is for questions looking for a single specific, or a small number of (citable) references. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Questions of the form &quot;What paper/book reported X?&quot;, &quot;Where can I find the original publication of X?&quot;, or &quot;Where can I find popular applications of X?&quot; are reference requests. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Valid answers should include a complete citation, e.g.:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Author(s), Initial(s): Year of publication, Title, Edition, Publisher, Place of Publication. (ISBN, URL if available)&lt;/li&gt;&#xA;&lt;li&gt;Author(s), Initial(s), Journal name &lt;strong&gt;Year of publication&lt;/strong&gt; &lt;em&gt;Volume number&lt;/em&gt; (Issue or part number), first (and last page) numbers (Title, DOI, URL if availabile)&lt;/li&gt;&#xA;&lt;li&gt;...&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt;(adapted from the &lt;a href=&quot;https://chemistry.stackexchange.com/tags/reference-request/info&quot;&gt;Chemistry.SE tag wiki&lt;/a&gt;)&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="118" LastEditorUserId="118" LastEditDate="2020-04-29T15:22:08.613" LastActivityDate="2020-04-29T15:22:08.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="46" PostTypeId="4" CreationDate="2020-04-29T12:42:37.820" Score="0" Body="This tag is for questions looking for a single specific, or a small number of (citable) references." OwnerUserId="118" LastEditorUserId="118" LastEditDate="2020-04-29T15:21:54.183" LastActivityDate="2020-04-29T15:21:54.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="47" PostTypeId="1" CreationDate="2020-04-29T13:30:00.370" Score="18" ViewCount="355" Body="&lt;p&gt;A lot of atomistic machine learning deals with correctly describing atomic neighborhood environments by vectors or fingerprints (see, e.g. &lt;a href=&quot;https://doi.org/10.1063/1.5055772&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; 149, 244102 (&lt;strong&gt;2018&lt;/strong&gt;)&lt;/a&gt;, &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.87.184115&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Phys. Rev. B&lt;/em&gt; 87, 184115 (&lt;strong&gt;2013&lt;/strong&gt;)&lt;/a&gt;), before feeding those descriptions to neural networks, kernel ridge regressors or other algorithms&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So the question is: &lt;strong&gt;what is the current status of local atomic environment descriptors for machine learning?&lt;/strong&gt;&#xA;Specifically, I want to know what makes a good descriptor and if there are any classification to them (i.e., what makes them different?).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(This question is complimentary to &lt;a href=&quot;https://materials.stackexchange.com/q/18/63&quot;&gt;&quot;What is the current status of machine learning applied to materials or molecular systems?&quot;&lt;/a&gt;.)&lt;/p&gt;&#xA;" OwnerUserId="63" LastActivityDate="2020-04-30T03:15:00.543" Title="What is the state of the art in terms of local atomic environment descriptors for machine learning?" Tags="|reference-request|machine-learning|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="48" PostTypeId="1" CreationDate="2020-04-29T13:55:43.337" Score="19" ViewCount="576" Body="&lt;p&gt;I think we have to calculate total energies using different FM, AFM configurations and solve a set of linear equations. How to arrive at the set of equations for any given structure?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;An example from the literature: &lt;a href=&quot;https://doi.org/10.1016/j.ssc.2009.01.030&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Solid State Communications&lt;/em&gt; &lt;strong&gt;2009&lt;/strong&gt;, 149 (15–16), 602–604&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="63" LastEditDate="2020-04-30T02:31:38.047" LastActivityDate="2023-01-31T16:50:15.133" Title="How to evaluate spin exchange parameters of a magnetic material using DFT?" Tags="|density-functional-theory|magnetism|spin-exchange|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="49" PostTypeId="1" CreationDate="2020-04-29T14:15:48.443" Score="19" ViewCount="137" Body="&lt;p&gt;Activity cliffs are defined as pairs of similar compounds with substantial differences in activity (&lt;a href=&quot;https://doi.org/10.1007/s11030-015-9609-z&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Molecular Diversity&lt;/em&gt;, 19, 1021–1035 (&lt;strong&gt;2015&lt;/strong&gt;)&lt;/a&gt;). Are there computational tools for the identification of activity cliffs between two analog compounds? This paper lists chemotypes that have a high propensity to induce activity cliff. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kT3Zf.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kT3Zf.gif&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="52" LastEditDate="2020-06-02T15:24:36.060" LastActivityDate="2020-06-02T15:24:36.060" Title="Computational tool for identification of activity cliff" Tags="|molecular-modeling|from-chem-se|qsar|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="50" PostTypeId="1" AcceptedAnswerId="86" CreationDate="2020-04-29T14:25:39.347" Score="27" ViewCount="748" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Extended_H%C3%BCckel_method&quot; rel=&quot;noreferrer&quot;&gt;extended Hückel method&lt;/a&gt; (EHM) proved to be very useful through time, but there are better and affordable models today. One interesting thing about the model is the independence of the Hamiltonian with respect to the (molecular) orbital coefficients, which allows solutions to be calculated in a single diagonalization:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_{ij} = K S_{ij} \frac{H_{ii} + H_{jj}}{2},$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; being the calculated &lt;a href=&quot;https://en.wikipedia.org/wiki/Orbital_overlap&quot; rel=&quot;noreferrer&quot;&gt;overlap matrix&lt;/a&gt; and the diagonal elements &lt;span class=&quot;math-container&quot;&gt;$H_{ii}$&lt;/span&gt; taken as model parameters.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The question is &lt;strong&gt;which fields still use the extended Hückel model today?&lt;/strong&gt; Why and how? Does the EHM still fill a gap?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am specifically looking for fields where it is the main method and how the shortcomings of EHM have been addressed.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="5" LastEditDate="2021-02-18T22:46:20.493" LastActivityDate="2021-02-18T22:46:20.493" Title="Where is the extended Hückel method (EHM) still used today?" Tags="|reference-request|molecular-modeling|quantum-chemistry|model-hamiltonians|semi-empirical-method|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="51" PostTypeId="1" AcceptedAnswerId="1287" CreationDate="2020-04-29T14:51:49.103" Score="24" ViewCount="250" Body="&lt;p&gt;Many machine learning attempts in atomistic applications (see &lt;a href=&quot;https://materials.stackexchange.com/a/25/63&quot;&gt;this answer&lt;/a&gt;) seem to parameterize models on calculated data (i.e., CCSD(T), DFT, etc.). This approach suggests some automatic procedure for &lt;a href=&quot;https://en.wikipedia.org/wiki/Active_learning_(machine_learning)&quot; rel=&quot;noreferrer&quot;&gt;active machine learning&lt;/a&gt; in this context.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So the question is: &lt;strong&gt;what is the current status of active machine learning methods for atomistic applications?&lt;/strong&gt;&#xA;Specifically, I want to know which algorithms are more appropriate for chemical problems.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="5" LastEditDate="2020-06-12T22:38:33.633" LastActivityDate="2020-06-13T01:24:21.037" Title="What are some examples of active learning methods used in atomistic machine learning?" Tags="|reference-request|machine-learning|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="52" PostTypeId="2" ParentId="44" CreationDate="2020-04-29T14:52:32.683" Score="13" Body="&lt;p&gt;It's possible to estimate solution-phase dielectric constant from a molecular dynamics simulation using this formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon_{r} = 1 + \frac{4\pi}{3Vk_{B}T}(\langle \mathbf{P}^{2} \rangle - \langle \mathbf{P} \rangle^{2})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the volume, &lt;span class=&quot;math-container&quot;&gt;$k_{B}$&lt;/span&gt; is Boltzmann's constant, &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is temperature, and &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the dipole moment defined as: &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P} = \sum_{i} \vec{\mu}_{i}$&lt;/span&gt; the summation of molecular dipole moments.&lt;/p&gt;&#xA;&lt;p&gt;In the absence of any external electric field (which I assume is the case here), from electrostatics, you have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{P}(\mathbf{r}) = \chi \int_{\Omega} \mathbf{T}(\mathbf{r}-\mathbf{r}^{'})\cdot \mathbf{P}(\mathbf{r}^{'}) d^{3} \mathbf{r}^{'}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; is the susceptibility, which is unknown here. Also, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{T}$&lt;/span&gt; is the dipole-dipole tensor defined as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$T_{ij} =&#xA;\frac{\partial^{2}}{\partial x_{i}\partial x_{j}}(-\ln(r))$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now if you replace the integral with a summation and replace &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P}(\mathbf{r})$&lt;/span&gt; with the discretized dipole moment at molecular locations shown as &lt;span class=&quot;math-container&quot;&gt;$\mathsf{P}$&lt;/span&gt; and the discretized dipole-dipole tensor (matrix &lt;span class=&quot;math-container&quot;&gt;$\mathsf{T}$&lt;/span&gt;), you have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathsf{P} = \chi \mathsf{T} \cdot \mathsf{P}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathsf{T} \cdot \mathsf{P} = \frac{1}{\chi} \mathsf{P}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is an eigenvalue problem where you know dipole-dipole tensor &lt;span class=&quot;math-container&quot;&gt;$\mathsf{T}$&lt;/span&gt;, while the eigenvector (dipole moment &lt;span class=&quot;math-container&quot;&gt;$\mathsf{P}$&lt;/span&gt;) and eigenvalue (susceptibility &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt;) are unknowns. You can solve this eigenvalue problem for your system and then you'll get the dielectric constant by estimating the fluctuation of dipole moment.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2022-01-21T05:29:25.217" LastActivityDate="2022-01-21T05:29:25.217" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="53" PostTypeId="2" ParentId="41" CreationDate="2020-04-29T14:56:48.853" Score="18" Body="&lt;p&gt;A few years ago, I was fascinated by the news of the discovery of a new Carbon allotrope based on first-principle simulations by using USPEX software described &lt;a href=&quot;https://uspex-team.org/en/research/materials&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Or particularly this article:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Zhu Q., Oganov A.R., Salvado M., Pertierra P., Lyakhov A.O. (2011). Denser than diamond:ab initio search for superdense carbon allotropes. Phys. Rev. B83, 193410&lt;/strong&gt;, &lt;a href=&quot;https://uspex-team.org/static/file/Zhu-carbon-2011.pdf&quot; rel=&quot;noreferrer&quot;&gt;download here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I promised to elaborate a bit more on my answer here. As I said in my comments after a few years later, this new Carbon allotrope is synthesized in the lab, which is truly fascinating how a theoretically predicted material structure, is synthesized by experimentalists (see here: &lt;a href=&quot;https://elementy.ru/novosti_nauki/431105&quot; rel=&quot;noreferrer&quot;&gt;https://elementy.ru/novosti_nauki/431105&lt;/a&gt; and sorry for the Russian language only).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are several other examples of discovering new materials for specific applications of batteries or fuel cells are provided &lt;a href=&quot;https://uspex-team.org/en/research/materials&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, that shows how quantum mechanical simulations combined with machine-learning methods could be used to tailor materials structure for a new application and developing new materials properties based on that.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-04-30T16:15:37.903" LastActivityDate="2020-04-30T16:15:37.903" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="54" PostTypeId="5" CreationDate="2020-04-29T15:07:37.520" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-04-29T15:07:37.520" LastActivityDate="2020-04-29T15:07:37.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="55" PostTypeId="4" CreationDate="2020-04-29T15:07:37.520" Score="0" Body="For questions about methods (typically in electronic structure theory) that use experimental parameters as part of their formulation" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-29T15:22:14.727" LastActivityDate="2020-04-29T15:22:14.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="56" PostTypeId="2" ParentId="43" CreationDate="2020-04-29T15:09:40.953" Score="11" Body="&lt;p&gt;Basically you need to find &lt;span class=&quot;math-container&quot;&gt;$L_{ij}^{m}$&lt;/span&gt; coefficients in the Redlich-Kister polynomials from DFT calculations, related to temperature as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$L_{ij}^{m} = a_{ij}^{m} + b_{ij}^{m} T + c_{ij}^{m} T \ln(T) + d_{ij}^{m} T^{2} + e_{ij}^{m} T^{3} + \frac{f_{ij}^{m}}{T}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Typically you need just the values for &lt;span class=&quot;math-container&quot;&gt;$m \leq 2$&lt;/span&gt;. I think this is a good reference for the data infrastructure that is needed for CALPHAD simulations: &lt;a href=&quot;https://link.springer.com/content/pdf/10.1186/2193-9772-3-12.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://link.springer.com/content/pdf/10.1186/2193-9772-3-12.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-29T15:09:40.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="57" PostTypeId="2" ParentId="50" CreationDate="2020-04-29T15:13:09.453" Score="14" Body="&lt;p&gt;I know of at least one place, where it is relatively common to use the extended Hückel theory in practise: in generating initial guess orbitals for further electronic structure calculations.&lt;br&gt;&#xA;The most popular example I can think of is Turbomole, see its &lt;a href=&quot;https://www.turbomole.org/wp-content/uploads/2019/10/Turbomole_Manual_7-4.pdf&quot; rel=&quot;noreferrer&quot;&gt;manual (pdf, chapter 4.3, p. 75)&lt;/a&gt;. They claim that the starting vectors are better than a core Hamiltonian guess, when no other starting vectors are available.&lt;/p&gt;&#xA;" OwnerUserId="49" LastActivityDate="2020-04-29T15:13:09.453" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="58" PostTypeId="2" ParentId="50" CreationDate="2020-04-29T15:56:00.223" Score="18" Body="&lt;p&gt;One area where the extended-Huckel method continues to see use is to form the initial guess for an SCF calculation or even just a more accurate semi-empirical method. While most electronic structures packages use the Superposition of Atomic Densities (SAD) guess as the default, the option is available in almost all of them and Psi4 uses it as the default for open shell calculations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A fairly recent paper &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt; actually benchmarked the performance of various initial guesses. They developed a variant of the Huckel guess that uses a SAD like process to generate matrix elements in the basis being used, rather using a minimal basis and experimental ionization potentials for the diagonal elements. They found that this approach was more robust than the SAD guess alone and was very easy to implement on top of it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For an example where EH is the main method, a recent Scientific Reports paper &lt;a href=&quot;https://doi.org/10.1038/s41598-018-28864-2&quot; rel=&quot;noreferrer&quot;&gt;[2]&lt;/a&gt; looked at how extended Huckel tight-binding could used for screening of electronic materials. By tuning the input parameters with a test set of DFT calculations, they were able to produce near DFT quality band structures at a fraction of the cost.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In general, it would seem that a good number of the issues with the Huckel method can be addressed by not using fixed parameters, whether that means calculating them cheaply on the fly or calibrating them using a test set of interest. But also, its important to recognize the methods limitations and work with them rather than try to fight them too much; the approaches I have mentioned basically use EHM as either preprocessing or screening rather than taking the results at face value. The accuracy of the method will always be limited and the speed of the method is really what makes it valuable.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Susi Lehtola Journal of Chemical Theory and Computation 2019 15 (3), 1593-1604 DOI: 10.1021/acs.jctc.8b01089 &lt;/li&gt;&#xA;&lt;li&gt;Grabill, L.P., Berger, R.F. Calibrating the Extended Hückel Method to Quantitatively Screen the Electronic Properties of Materials. Sci Rep 8, 10530 (2018). DOI: 10.1038/s41598-018-28864-2&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-07T19:25:50.293" LastActivityDate="2020-05-07T19:25:50.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="59" PostTypeId="2" ParentId="41" CreationDate="2020-04-29T15:59:33.903" Score="15" Body="&lt;p&gt;This answer is adopted from the book &lt;a href=&quot;https://books.google.co.in/books?id=FzOTAwAAQBAJ&amp;amp;printsec=frontcover&amp;amp;source=gbs_ge_summary_r&amp;amp;cad=0#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;Materials Modelling Using Density Functional Theory: Properties and Predictions&lt;/a&gt; by Feliciano Giustino&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/nmat1752&quot; rel=&quot;noreferrer&quot;&gt;Greeley et al. (2006)&lt;/a&gt; searched for potential replacements for Pt as catalyst in hydrogen production using DFT calculations. One of the most promising alloy was an hypothetical material &lt;strong&gt;BiPt&lt;/strong&gt;. The material was synthesized later in lab and as predicted from the DFT calculations, the measured catalytic activity of this new compound turned out to be superior to that of pure Pt.&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-04-29T16:14:40.077" LastActivityDate="2020-04-29T16:14:40.077" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="60" PostTypeId="5" CreationDate="2020-04-29T16:19:41.747" Score="0" Body="&lt;p&gt;For N-electron systems, the motion of any one electron is correlated with all the others due to instantaneous Coulombic interactions between them. In mean-field electronic structure techniques such as Hartree-Fock, these interactions are mostly neglected and each electron interacts with the average field produced by its neighbors. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The effect of this correlation can be reintroduced, either through higher level corrections to the Hartree-Fock approach &lt;a href=&quot;https://en.wikipedia.org/wiki/Post%E2%80%93Hartree%E2%80%93Fock&quot; rel=&quot;nofollow noreferrer&quot;&gt;Post-HF&lt;/a&gt; or through an exchange-correlation functional in Density Functional Theory approximations. The corrected energy with these factors introduced is referred to as the correlation energy.  &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-01T15:58:26.020" LastActivityDate="2020-05-01T15:58:26.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="61" PostTypeId="4" CreationDate="2020-04-29T16:19:41.747" Score="0" Body="For questions related to energy arising from the correlated motion of electrons. For wavefunction based methods, this is typically taken to be the difference between the true energy and the Hartree-Fock energy" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-04-29T17:45:45.840" LastActivityDate="2020-04-29T17:45:45.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="62" PostTypeId="1" AcceptedAnswerId="845" CreationDate="2020-04-29T16:36:34.730" Score="18" ViewCount="383" Body="&lt;p&gt;Do any freely available or proprietary electronic structure packages explicitly compute two-electron exchange correlation integrals?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have found a few derivations to calculate excited state properties/spectroscopic observables using DFT,&lt;sup&gt;[1]&lt;/sup&gt; and they tend to write expressions including integrals of the form &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle\mu\nu|w|\lambda\sigma\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$w$&lt;/span&gt; is the exchange-correlation kernel. However, I have yet to find a package that specifically generates these integrals. It seems that in general they do some sort of prior contraction with the density to avoid the need to generate these terms explicitly when calculating response properties. However, I had wanted to make a small standalone script that used these quantities. Its presumably much less efficient than the approach used in these packages, but the implementation is much clearer for me. Are there any packages that have an existing option to do this? Or is it something that would require some modification of either these packages themselves or some existing API?&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;S. Hirata, M. Head-Gordon, R.J. Bartlett &lt;strong&gt;Configuration interaction singles, time-dependent Hartree–Fock,&#xA;and time-dependent density functional theory for the electronic&#xA;excited states of extended systems&lt;/strong&gt; &lt;em&gt;J. Chem. Phys.&lt;/em&gt; 111, 10774 (1999); &lt;a href=&quot;https://doi.org/10.1063/1.480443&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1063/1.480443&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-02T15:31:28.280" LastActivityDate="2020-06-02T15:31:28.280" Title="Exchange-Correlation Two-Electron Integrals" Tags="|density-functional-theory|integrals|from-chem-se|response-theory|psi4|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="63" PostTypeId="1" CreationDate="2020-04-29T17:49:52.993" Score="24" ViewCount="459" Body="&lt;p&gt;There are many different dispersion corrections out there. The most famous is D3 &lt;a href=&quot;https://doi.org/10.1063/1.3382344&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt; (and the new D4 &lt;a href=&quot;https://doi.org/10.1063/1.4993215&quot; rel=&quot;nofollow noreferrer&quot;&gt;[2]&lt;/a&gt;), but there's probably other approaches too. The dispersion energy can be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{\textrm{disp}} = -\sum_{ij}\sum_{6,8,10,\cdot \cdot  }\frac{C_n^{ij}f^{(n)}_{\textrm{damp}}(r)}{r^n},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the &lt;span class=&quot;math-container&quot;&gt;$C^{ij}_n$&lt;/span&gt; coefficients are calculated differently depending on whether using D3 or D4, and the damping function &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; can take on various forms.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the other ways of calculating &lt;span class=&quot;math-container&quot;&gt;$C^{ij}_n$&lt;/span&gt;?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&#xA;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://doi.org/10.1063/1.3382344&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; 132, 154104 (&lt;strong&gt;2010&lt;/strong&gt;)&lt;/a&gt;&lt;br&gt;&#xA;[2] &lt;a href=&quot;https://doi.org/10.1063/1.4993215&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; 147, 034112 (&lt;strong&gt;2017&lt;/strong&gt;)&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;P.S. For further discussion and overview, see &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemrev.5b00533&quot; rel=&quot;nofollow noreferrer&quot;&gt;Grimme's&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.6b00446&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tkatchenko's&lt;/a&gt; review papers.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="5" LastEditDate="2020-07-30T20:00:10.653" LastActivityDate="2020-07-30T20:55:27.993" Title="What are the different ways of calculating dispersion constants?" Tags="|density-functional-theory|reference-request|intermolecular-forces|dispersion-correction|one-topic-per-answer|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="64" PostTypeId="1" AcceptedAnswerId="79" CreationDate="2020-04-29T19:28:12.070" Score="25" ViewCount="392" Body="&lt;p&gt;Similar to how a molecular orbital, also known as a 1-electron wavefunction, can be represented with a linear combination of  “basis” functions, e.g., atomic orbitals (LCAO):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Phi(\mathbf{r})=\sum_i^N c_i \phi(r).$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A multi-electron wavefunction can be represented with a linear combination of multi-electron basis functions, also known as determinants, or electron configurations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yv5ug.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yv5ug.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the limit of all possible excited-determinants the solution is exact. The excited-electronic configurations describe both static electronic and dynamic electronic correlation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, the main challenge in solving this problem is that the number of determinants scales combinatorially. For even small molecules (e.g. &gt;4 heavy atoms) and modest basis functions this problem is intractable. To make matters worse, solving for the coefficients &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; requires diagonalizing the Hamiltonian, which scales as &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are some of the best approaches, generally speaking, for working around this problem (within the confines of configuration interaction approaches) while still capturing most of the static and dynamic electronic correlation? &lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="49" LastEditDate="2020-05-10T16:54:32.987" LastActivityDate="2021-08-13T13:29:37.817" Title="How to overcome the exponential wall encountered in full configurational interaction methods?" Tags="|electronic-structure|wavefunctions|configuration-interaction|ab-initio-calculations|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="65" PostTypeId="1" CreationDate="2020-04-29T19:50:00.760" Score="16" ViewCount="174" Body="&lt;p&gt;For an ordered crystal, we generally converge the k-mesh resolution for a primitive cell or other smaller supercells. We then use this resolution for any other size of the supercell for the same material. Can we do the same with special quasi-random structures, given that they are disordered? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I've noticed that on doing spin-polarised relaxation for various SQS of different sizes of a magnetic material, they each might turn out to have different magnetic moments. That is inconsistent, though I don't know if this is the case with any magnetic material.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I thought since SQS are disordered, the local atomic arrangement/ environment shall be different for different SQS, both, of the same and different sizes. This might lead to different magnetic moments. What is your understanding of the topic?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also, can we establish a standard method on the convergence of k-mesh resolution for SQS?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-04-29T20:20:17.843" LastActivityDate="2020-04-29T20:20:17.843" Title="k-points convergence for special quasirandom structures (SQS) of the same material containing different # of atoms" Tags="|density-functional-theory|ab-initio-calculations|special-quasirandom-structures|k-points|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="66" PostTypeId="2" ParentId="65" CreationDate="2020-04-29T20:07:18.417" Score="9" Body="&lt;p&gt;Very good question.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I think that when you select one of the many different disordered structures as been a representative one, that structure is not disordered anymore, it is an structure as any other. Following this, I think that the convergence test can be done in a similar way that for any other primitive cell.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The problem of course, is when you decide to calculate for several disordered structures. In this case, one convergence study may not work for all the structures.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The big problem is how to select the &lt;em&gt;best&lt;/em&gt; structure among all the possible disordered.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-04-29T20:07:18.417" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="67" PostTypeId="2" ParentId="41" CreationDate="2020-04-29T20:13:41.573" Score="10" Body="&lt;p&gt;I strongly recommend to follow the work of prof. Oganov and the use of the software USPEX.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Take a look at the site: &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://uspex-team.org/en&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the above link, there is the information about the USPEX package, what it is capable to do, how it does what it does, etc. Also, there is a list of publications (including two books), all related to Materials Modeling.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-26T13:51:22.503" LastActivityDate="2020-05-26T13:51:22.503" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="68" PostTypeId="1" AcceptedAnswerId="120" CreationDate="2020-04-29T20:28:43.767" Score="20" ViewCount="407" Body="&lt;p&gt;Plane-wave basis sets are useful in the calculation of periodic systems and can be used in combination with pseudopotentials. However, when dealing with surfaces the system is no longer periodic in, at least, one dimension. Moreover, in modeling adsorption processes, it is necessary to include a surface and the molecule attached with a suitable basis set.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As far as I know, a plane-wave basis set should be expanded over the whole simulation box and the periodicity in three dimensions is required. However, some studies on adsorption were made using this type of basis (for instance, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp811381d&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Phys. Chem. &lt;strong&gt;2009&lt;/strong&gt;, 113, 9256-9274&lt;/em&gt;&lt;/a&gt;), although the periodicity is broken. At first glance, it seems like a localized basis set is better for surfaces with molecules attached.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Are plane-waves basis sets really useful for surfaces or adsorption processes? &lt;/li&gt;&#xA;&lt;li&gt;What advantages (if there are) have plane-waves over localized basis sets in modeling surfaces?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="10" LastEditorUserId="5" LastEditDate="2020-04-29T20:36:31.837" LastActivityDate="2020-04-30T23:43:53.543" Title="Are plane-wave basis sets reliable for modeling adsorption processes?" Tags="|basis-sets|surfaces|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="69" PostTypeId="1" AcceptedAnswerId="770" CreationDate="2020-04-29T20:36:30.943" Score="13" ViewCount="554" Body="&lt;p&gt;This is a doubt regarding the usage of various forcefields together in MD simulation of hydrates. For Eg., we use TIP4P/ice for water molecules, OPLS-UA for methane and EPM2 for carbon dioxide and so on. How exactly does GROMACS work in this scenario? Can it work with different functional forms or is it just different parameters for the same functional form? Because, in the GROMACS topology or .itp file, we sometimes use different numbers for different functional forms for different molecules under one same directive.(Eg: func 1 for OPLS for one molecule and func 2 for GROMOS for some other molecule under the same 'bonds' directive)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Majority of the research work in Molecular dynamics simulations of hydrates is done with such combinations. For example, &lt;a href=&quot;https://www.researchgate.net/deref/https%3A%2F%2Fpubs.rsc.org%2Fen%2Fcontent%2Farticlelanding%2F2012%2FEE%2Fc2ee21189k%23!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; uses such different forcefields for different molecules in one simulation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also &lt;a href=&quot;https://www.researchgate.net/post/How_to_use_two_kinds_of_forcefield_in_Gromacs_at_the_same_time&quot; rel=&quot;noreferrer&quot;&gt;in this link&lt;/a&gt;, Justin clearly dismisses the idea of using different forcefields together.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It will be helpful if you can clear this confusion. Is there a way to check the functional form of the forcefields that is being used to calculate, in this software? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thanks and Regards&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2020-05-03T18:52:42.190" LastActivityDate="2020-05-17T20:39:59.097" Title="How to find out the total functional form of the forcefield that is being used for a current simulation in GROMACS?" Tags="|software|molecular-dynamics|gromacs|forcefields|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="70" PostTypeId="1" AcceptedAnswerId="75" CreationDate="2020-04-29T20:39:07.000" Score="40" ViewCount="1706" Body="&lt;p&gt;&lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;noreferrer&quot;&gt;Lejaeghere et. al&lt;/a&gt;  studied reproducibility of DFT codes (softwares) by comparing 15 different codes employing 40 different potentials. The study concluded that most codes agree very well, with pairwise differences that are comparable to those between different high-precision experiments.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Why do we have so many different codes? Are they redundant?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-14T05:33:09.543" LastActivityDate="2020-08-28T08:36:25.297" Title="Why do we have so many DFT codes (softwares)? Are they redundant?" Tags="|software|density-functional-theory|" AnswerCount="5" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="75" PostTypeId="2" ParentId="70" CreationDate="2020-04-29T21:19:12.730" Score="39" Body="&lt;p&gt;There are many reasons why so many different scientific packages have been developed&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;These packages were developed by individual researchers who were in competition with each other and also work mostly independently. It was natural that different packages sprung out of different regions (e.g. NWChem stands for NorthWest Chem, because it’s based at Pacific Northwest National Lab (PNNL)) and for different purposes or specialties (e.g. Molpro for excited-states). Also remember that this was before version control or the idea of open-access was a thing, so sharing code was not so easy. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The opportunity to make money with the software was also a huge draw and further enticed people to start there own company, or in contrast distance themselves from the company because of their own personal beliefs. For example, the company Gaussian has a well known history of &lt;a href=&quot;https://en.wikipedia.org/wiki/Gaussian_(software)&quot; rel=&quot;noreferrer&quot;&gt;controversy&lt;/a&gt; with some scientists over how the company was ran (perhaps even with the founder of Gaussian itself, John Pople). &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Despite the code similarity most scientific software is very poorly managed because the developers work independently and are not computer programmers. So in many cases, people wanted to start something fresh in an attempt to make it better, or easier for them to write their own custom code. Again, open-access and object oriented programming is fairly recent. A great example of a software package that was developed to make reading and improving the code is &lt;a href=&quot;http://openmm.org/&quot; rel=&quot;noreferrer&quot;&gt;OpenMM&lt;/a&gt;. And because of this, OpenMM now has superior GPU kernels and object oriented design making it one of the best and fastest codes for molecular dynamics today.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There is also a difference in preferred languages. Historically scientific software was written in Fortran. Then people started using C/C++. Nowadays people are even using python!&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;It is my opinion that all types of codes should be continued to be developed independently but hopefully they follow good coding practices like object-oriented programming. If that is the case then it's easy to mix and match code from different developers. &lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-25T17:45:30.530" LastActivityDate="2020-05-25T17:45:30.530" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="77" PostTypeId="5" CreationDate="2020-04-29T22:46:49.790" Score="0" Body="&lt;p&gt;Density Functional Theory is an electronic structure theory model developed by Pierre Hohenberg and Walter Kohn in the early 1960s. The so called Hohenberg-Kohn theorems show that (1) The ground state energy of an N-electron system is uniquely determined by its electron density (2) There exists a functional of the ground state energy and the exact ground state electron density minimizes this functional.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These theorems in principle allow the complicated problem of determining the 3N dimensional wavefunction of the system via the Schrodinger equation to be reduced to the problem of determining the 3 dimensional electron density that minimizes the energy functional.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Kohn-Sham (KS) DFT refers to a version of DFT in which the electrons are treated as noninteracting and moving within an effective potential.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The exact energy functional (in particular, the exchange-correlation portion of the KS potential) is not expressible analytically, so numerous approximate functionals have emerged&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-03T00:11:38.983" LastActivityDate="2020-05-03T00:11:38.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="78" PostTypeId="4" CreationDate="2020-04-29T22:46:49.790" Score="0" Body="For questions about simulations using Density Functional Theory." OwnerUserId="10" LastEditorUserId="10" LastEditDate="2020-04-30T09:22:51.127" LastActivityDate="2020-04-30T09:22:51.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="79" PostTypeId="2" ParentId="64" CreationDate="2020-04-29T22:57:47.650" Score="15" Body="&lt;p&gt;It is hard to claim that any FCI code overcomes the exponential wall, especially for strongly correlated systems.&#xA;There are many algorithms, e.g. CDFCI, HCI, FCIQMC, ACI, etc., which significantly reduce the computational cost of direct FCI calculations and represent wavefunctions by sparse vectors. However, in my opinion, all of them only reduce the prefactor and none of them overcome the exponential wall.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;DMRG is another method using a different ansatz. The scaling is indeed polynomial for weakly correlated systems (when it's possible to use small bandwidth). However, for strongly correlated systems, the scaling is difficult to say.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another possible attempt is to rotate the molecular orbitals, like CASSCF, OptOrbFCI, etc. However, full accuracy of these methods is not expected if the orbital truncation is aggressive.&lt;/p&gt;&#xA;" OwnerUserId="11" LastEditorUserId="5" LastEditDate="2020-04-29T23:02:30.503" LastActivityDate="2020-04-29T23:02:30.503" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="80" PostTypeId="2" ParentId="69" CreationDate="2020-04-30T00:20:00.023" Score="10" Body="&lt;p&gt;I am not a GROMACS user, but have used it once or twice during my course. As far as I can remember and understand, it is common to use different force field in MD if one simulate something solvated in something, e.g. formaldehyde (OPLSAA force field) in water (SPC,TIP3P, etc.). I guess we can also do that in GROMACS, but I do not really know how to specify this in the topology file (I remember that there must be directory which lists available force fields and how to call them in the topology file). There must be some discussions already in the mailing list of GROMACS (&lt;a href=&quot;http://www.gromacs.org/Support/Mailing_Lists&quot; rel=&quot;noreferrer&quot;&gt;http://www.gromacs.org/Support/Mailing_Lists&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For other processes, such as the interaction between organic molecule and DNA, I do not think that you can mix the force fields, e.g. using MM-type for organic molecule and AMBER for DNA. One reason that I can think of is because those force fields are parameterised differently and you might need to do validation too, which I am not really sure how to do that. Also, you cannot mix up force fields for MD and coarse grain.&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="159" LastEditDate="2020-04-30T00:25:41.650" LastActivityDate="2020-04-30T00:25:41.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="81" PostTypeId="2" ParentId="47" CreationDate="2020-04-30T02:26:59.630" Score="16" Body="&lt;p&gt;If you are familiar with the &lt;a href=&quot;https://doi.org/10.1063/1.3553717&quot; rel=&quot;noreferrer&quot;&gt;Behler-Parrinello symmetry functions&lt;/a&gt; implemented in AMP, you may be interested in seeing how they compare to other atom-centered representations in terms of speed and accuracy. Marcel F. Langer, Alex Goeßmann, and Matthias Rupp have recently released &lt;a href=&quot;https://arxiv.org/abs/2003.12081&quot; rel=&quot;noreferrer&quot;&gt;their benchmarking&lt;/a&gt; &lt;a href=&quot;https://github.com/sirmarcel/cmlkit&quot; rel=&quot;noreferrer&quot;&gt;efforts&lt;/a&gt; including the symmetry functions, the &lt;a href=&quot;https://arxiv.org/abs/1704.06439&quot; rel=&quot;noreferrer&quot;&gt;Many-body Tensor Representation&lt;/a&gt;, and the &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.87.184115&quot; rel=&quot;noreferrer&quot;&gt;Smooth Overlap of Atomic Positions representation&lt;/a&gt;. Their work also includes concise summaries of other representations to get you up to speed as well as &lt;strong&gt;what exactly makes a good representation&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Invariance to rotations, translations, and permutations&lt;/li&gt;&#xA;&lt;li&gt;Uniqueness: &quot;Systems with identical representations that differ in property&#xA;introduce errors&quot;&lt;/li&gt;&#xA;&lt;li&gt;Continuity/Differentiability &lt;/li&gt;&#xA;&lt;li&gt;Computational efficiency&lt;/li&gt;&#xA;&lt;li&gt;Structure (e.g constant size)&lt;/li&gt;&#xA;&lt;li&gt;Generality, &quot; in the sense of being able to encode any&#xA;atomistic system&quot;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What distinguishes many representations is the choice of their basis set&lt;/strong&gt; when encoding physical distances and angles into machine-learning inputs. Where the Behler-Parrinello symmetry functions use Gaussian functions, the &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.96.014112&quot; rel=&quot;noreferrer&quot;&gt;Artrith-Urban-Ceder descriptor&lt;/a&gt; uses Chebyshev polynomials. The Many-Body Tensor Representation uses a real-space basis, while the Smooth Overlap of Atomic Positions uses spherical harmonics. Michele Ceriotti's group has released &lt;a href=&quot;https://arxiv.org/pdf/1807.00408.pdf&quot; rel=&quot;noreferrer&quot;&gt;an excellent paper&lt;/a&gt; connecting these atom-centered representations with a general mathematical formulism.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Dr. Ceriotti is also on a paper with Gabor Csanyi where they have extensively investigated the topic of uniqueness. &lt;a href=&quot;https://arxiv.org/pdf/2001.11696.pdf&quot; rel=&quot;noreferrer&quot;&gt;The paper&lt;/a&gt; &lt;strong&gt;highlights the limitations of using representations that stop at 3-body terms&lt;/strong&gt; (i.e distances and angles).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While invariance and equivariance might be handled by the representation, there are several groups working on finding &lt;a href=&quot;https://blondegeek.github.io/e3nn_tutorial/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;ways to handle equivariance directly with the model architecture&lt;/strong&gt;&lt;/a&gt;. As far as I understand, this is especially necessary when learning tensorial properties rather than scalar properties like energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As Greg alluded to, there have also been efforts to create &lt;strong&gt;machine learning frameworks where atomic representations can be learned and tuned automatically&lt;/strong&gt;. Schnet (or &lt;a href=&quot;https://schnetpack.readthedocs.io/en/stable/&quot; rel=&quot;noreferrer&quot;&gt;Schnetpack&lt;/a&gt;) is a framework that uses continuous-filter convolutional neural networks to do so.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I recommend watching these lectures from the recent Institute for Pure and Applied Mathematics program on &quot;Machine Learning for Physics and the Physics of Learning&quot;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Richard G. Hennig: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=16352&amp;amp;pcode=MLPWS1&quot; rel=&quot;noreferrer&quot;&gt;Machine-learning for materials and physics discovery through symbolic regression and kernel methods&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Tess Smidt: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=16346&amp;amp;pcode=MLPWS1&quot; rel=&quot;noreferrer&quot;&gt;Euclidean Neural Networks* for Emulating Ab Initio Calculations and Generating Atomic Geometries *also called Tensor Field Networks and 3D Steerable CNNs&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Anatole von Lilienfeld: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=15761&amp;amp;pcode=MLPWS2&quot; rel=&quot;noreferrer&quot;&gt;Quantum Machine Learning&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Michele Ceriotti: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=15817&amp;amp;pcode=MLPWS4&quot; rel=&quot;noreferrer&quot;&gt;Machine learning for atomic and molecular simulations&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Matthias Rupp: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=15782&amp;amp;pcode=MLPWS4&quot; rel=&quot;noreferrer&quot;&gt;How to assess scientific machine learning models? Prediction errors and predictive uncertainty quantification&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Gabor Csanyi: &lt;a href=&quot;http://www.ipam.ucla.edu/abstract/?tid=15837&amp;amp;pcode=MLPWS4&quot; rel=&quot;noreferrer&quot;&gt;Representation and regression problems for molecular structure and dynamics&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="166" LastEditorUserId="166" LastEditDate="2020-04-30T03:15:00.543" LastActivityDate="2020-04-30T03:15:00.543" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="83" PostTypeId="2" ParentId="1" CreationDate="2020-04-30T02:51:08.057" Score="31" Body="&lt;p&gt;&lt;a href=&quot;http://www.2dmatpedia.org/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2DMatPedia&lt;/strong&gt;&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;An open computational database of two-dimensional materials. A large dataset of 2D materials, with more than 6,000 monolayer structures, obtained from both top-down and bottom-up discovery procedures&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/dashboard/ptable&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2D structures and layered materials&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Results from screening all known 3D crystal structures finding those that can be computationally exfoliated producing 2D materials candidates. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.2dmatpedia.org/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;TopoMat database&lt;/strong&gt;&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/dashboard/ptable&quot; rel=&quot;noreferrer&quot;&gt;database&lt;/a&gt; contains the results of high-throughput first-principles screening of known crystal structures for topological materials (topological insulators, Dirac and Weyl semimetals, etc.).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I recently came across the publication &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/advs.201900808&quot; rel=&quot;noreferrer&quot;&gt;Data‐Driven Materials Science: Status, Challenges and Perspectives&lt;/a&gt; by Himanen et. al featuring this list of current major materials data infrastructures.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oebL5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oebL5.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5f9o3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5f9o3.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/NeN1I.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NeN1I.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Himanen, Lauri, et al. &quot;Data‐Driven Materials Science: Status, Challenges, and Perspectives.&quot; Advanced Science 6.21 (2019): 1900808.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-15T17:19:47.653" LastActivityDate="2020-05-15T17:19:47.653" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="84" PostTypeId="2" ParentId="7" CreationDate="2020-04-30T04:33:46.477" Score="8" Body="&lt;p&gt;I'm not completely satisfied with this answer, but I think it is worth including here what I have for now.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Going back to the original papers that defined the various aug-cc-pVXZ basis sets, the even-tempered exponents of the diffuse functions are obtained by an optimization to fit CI calculations for those atoms. The functions &lt;span class=&quot;math-container&quot;&gt;$\{\zeta_i\}$&lt;/span&gt; are obtained as &lt;span class=&quot;math-container&quot;&gt;$$\zeta_i=\alpha\beta^{i-1},i=1,2,3,...,N$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; are optimized. These optimizations all produced &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; values right around 0.3-0.4. I would be surprised if this was entirely coincidental, but its difficult to parse the physical meaning of this value due to it stemming from a nonlinear optimization of a complicated function. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As to your paper, I think people have caught on to the recurrence of this value and so for the case considered (creating aug-cc-pV8Z diffuse functions), rather than going through an additional complicated optimization, one can just choose heuristically reasonable values for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; to arrive at a result sufficient enough for their purposes. &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-04-30T04:38:01.177" LastActivityDate="2020-04-30T04:38:01.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="85" PostTypeId="1" CreationDate="2020-04-30T04:36:04.353" Score="18" ViewCount="235" Body="&lt;p&gt;I wonder if all DFT codes are based on the Kohn-Sham formalism?.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If other methods are available, what are their scopes?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-04-30T05:10:14.320" LastActivityDate="2020-04-30T16:34:37.490" Title="Is there any relevant DFT formalism apart from the Kohn-Sham approach?" Tags="|density-functional-theory|kohn-sham|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="86" PostTypeId="2" ParentId="50" CreationDate="2020-04-30T07:34:22.290" Score="32" Body="&lt;p&gt;In an era of &lt;em&gt;ab initio&lt;/em&gt; methods and many-body methods like the &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt;, there is not too much room for methods like the extended Hückel model to be the &lt;em&gt;main&lt;/em&gt; method in any particular field of materials modeling. However, the method is still very much appreciated by the solid-state community particularly for it's accessibility. It is especially popular with those fond of Tight-Binding variants. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The extended Hückel model is an effective Hamiltonian that is used to approximate the Schrödinger eq. by making use of the variational theorem and the linear combination of atomic orbitals (&lt;strong&gt;LCAO&lt;/strong&gt;). The key is to solve a set of linear Hückel equations of form &#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;  \sum_{i,j}\left({H}_{ij} - \epsilon_\alpha S_{ij}\right) C_{ij} &amp;amp;= 0, &amp;amp;&#xA;  \text{with } i,j &amp;amp;= 1, 2, 3, \dots \tag{1}\label{eq:huckel}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The diagonal elements of &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; are taken to be equal to the ionization energy of an electron in the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th valence &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; of the isolated atom in the appropriate state, i.e. Valence State Ionization Potential (VSIP), expressed as &lt;span class=&quot;math-container&quot;&gt;$H_{ii}  = - VSIP(\phi_{j})=\epsilon_\mathrm{onsite}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The off-diagonal elements of &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; are evaluated according to a modified Wolfsberg-Helmholtz relation, as mentioned by Felipe:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H_{ij} = \mathcal{K} S_{ij} \left(\frac{H_{ii} + H_{jj}}{2}\right),&#xA;\tag{2}\label{eq:Hij}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; is the matrix of overlap integrals, &lt;span class=&quot;math-container&quot;&gt;$S_{ij} = \langle \phi_{i}\vert \phi_{j} \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;So... who is using it and how?&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;As mentioned by Felipe, the eH-TB method is fairly easy to work with and Tyberius highlighted that it's speed is primarily what gives it value. Hence, many researchers often write in-house codes for their research projects,&lt;sup&gt;[1]&lt;/sup&gt; or build on community codes. Actually, my first formal encounter with materials modeling was learning the extended Hückel Tight-Binding method!&lt;sup&gt;[2]&lt;/sup&gt; I carried out a project under Prof. Donald H. Galván, who worked directly with Roald Hoffmann a couple years ago. When I began the project, I had no experience or knowledge of Quantum Mechanics or Solid State Physics, and worked with a modified version of the &lt;a href=&quot;http://yaehmop.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;YAeHMOP&lt;/a&gt; code written by Greg Landrum, but that experience prepared me to really make sense of band theory and materials form an orbital perspective.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The method is a very good starting point for students interested in electronic structure theory, whether it be modeling of development. Therefore, it is a useful tool in the classroom. Recently, YaEHMOP was merged with the Avogadro molecular editor and visualizer to serve as a simple way for undergraduate quantum theory students to model band structures, Density of States (DOS) and Crystal Orbital Hamilton Population (COHP) using their personal computer. The authors published this in &lt;em&gt;&quot;Journal of Chemical Education&quot;&lt;/em&gt;.&lt;sup&gt;[3]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It is also implemented in the &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk/atomic-scale-modeling/products.html&quot; rel=&quot;noreferrer&quot;&gt;Quantum ATK&lt;/a&gt; platform for both academic research and materials development. In research, the method is often used to model the ground state and transport properties of systems of sized prohibitive by other methods (e.g. Carbon Nanotubes),&lt;sup&gt;[4]&lt;/sup&gt; as a first-approximations to study a system's properties or model a material with an effective &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; to study physics that may not be accessible by traditional DFT. An example of this, is the work of A.S. Martins on the Hyper-Honeycomb lattice in &lt;em&gt;J.Phys. Chem. C.&lt;/em&gt;&lt;sup&gt;[5]&lt;/sup&gt; and on 2D materials with defects.&lt;sup&gt;[6]&lt;/sup&gt; The method is still trusted enough to model the electronic structure in support of experimentally achieved materials.&lt;sup&gt;[7]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Recently, the Extended Hückel Hamiltonian has also found a home in quantum dynamics and charge transfer simulations.&lt;sup&gt;[8, 9, 10, 11]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It is still inspiring new TB models,&lt;sup&gt;[12]&lt;/sup&gt; and the derivation of paper-and-pencil LCAO models help to understand complex materials. Last year, a LCAO model was proposed for double halide perovskites.&lt;sup&gt;[13]&lt;/sup&gt; Additionally, due to its qualitative predictive power and speed, there are efforts to improve through Machine Learning.&lt;sup&gt;[14]&lt;/sup&gt; Lastly, the eH is key ingredient in the novel GFNx-TB method.&lt;sup&gt;[15]&lt;/sup&gt;  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As seen, the extended Hückel method continues to play a strong role in quantum chemistry and materials modeling, though not in the same way it did in the twentieth century. Currently, I am not sure if it is the &quot;standard&quot; method of anything, but the model itself can teach us a lot about band theory at a qualitative level and that is useful for many things. If I were to give it three solid applications today, they would be:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Education in band theory &lt;/li&gt;&#xA;&lt;li&gt;Method development in Quantum Chemistry&lt;/li&gt;&#xA;&lt;li&gt;Transport simulations&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;El Khatib, M.; Evangelisti, S.; Leininger, T.; Bendazzoli, G. L. A theoretical study of closed polyacene structures. &lt;em&gt;Phys. Chem. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2012,&lt;/strong&gt; &lt;em&gt;14&lt;/em&gt; (45), 15666. &lt;a href=&quot;https://doi.org/10.1039/C2CP42144E&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1039/C2CP42144E&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Palos, E. I.; Paez, J. I.; Reyes-Serrato, A.; Galván, D. H. Electronic structure calculations for rhenium carbonitride: an extended Hückel tight-binding study. &lt;em&gt;Phys. Scr.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;93&lt;/em&gt; (11), 115801. &lt;a href=&quot;https://doi.org/10.1088/1402-4896/aae14c&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1088/1402-4896/aae14c&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Avery, P.; Ludowieg, H.; Autschbach, J.; Zurek, E. Extended Hückel Calculations on Solids Using the Avogadro Molecular Editor and Visualizer. &lt;em&gt;J. Chem. Educ.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;95&lt;/em&gt; (2), 331–337. &lt;a href=&quot;https://doi.org/10.1021/acs.jchemed.7b00698&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jchemed.7b00698&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Zienert, A.; Schuster, J.; Gessner, T. Extended Hückel Theory for Carbon Nanotubes: Band Structure and Transport Properties. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2013,&lt;/strong&gt; &lt;em&gt;117&lt;/em&gt; (17), 3650–3654. &lt;a href=&quot;https://doi.org/10.1021/jp312586j&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/jp312586j&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Veríssimo-Alves, M.; Amorim, R. G.; Martins, A. S. Anisotropic Electronic Structure and Transport Properties of the H-0 Hyperhoneycomb Lattice. &lt;em&gt;J. Phys. Chem. C&lt;/em&gt; &lt;strong&gt;2017,&lt;/strong&gt; &lt;em&gt;121&lt;/em&gt; (3), 1928–1933. &lt;a href=&quot;https://doi.org/10.1021/acs.jpcc.6b10336&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jpcc.6b10336&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Martins, A. d. S.; Veríssimo-Alves, M. Group-IV nanosheets with vacancies: a tight-binding extended Hückel study. &lt;em&gt;J. Phys.: Condens. Matter&lt;/em&gt; &lt;strong&gt;2014,&lt;/strong&gt; &lt;em&gt;26&lt;/em&gt; (36), 365501. &lt;a href=&quot;https://doi.org/10.1088/0953-8984/26/36/365501&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1088/0953-8984/26/36/365501&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Zhak, O.; Zdorov, T.; Levytskyy, V.; Babizhetskyy, V.; Zheng, C.; Isnard, O. Ternary antimonides Ln2Pd9Sb3 (Ln = La, Ce, Nd, Pr, and Sm): Crystal, electronic structure, and magnetic properties. &lt;em&gt;J. Alloys Compd.&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;815,&lt;/em&gt; 152428. &lt;a href=&quot;https://doi.org/10.1016/j.jallcom.2019.152428&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1016/j.jallcom.2019.152428&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Tsuji, Y.; Estrada, E. Influence of long-range interactions on quantum interference in molecular conduction. A tight-binding (Hückel) approach. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;150&lt;/em&gt; (20), 204123. &lt;a href=&quot;https://doi.org/10.1063/1.5097330&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1063/1.5097330&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Sato, K.; Pradhan, E.; Asahi, R.; Akimov, A. V. Charge transfer dynamics at the boron subphthalocyanine chloride/C60 interface: non-adiabatic dynamics study with Libra-X. &lt;em&gt;Phys. Chem. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;20&lt;/em&gt; (39), 25275–25294. &lt;a href=&quot;https://doi.org/10.1039/C8CP03841D&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1039/C8CP03841D&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Li, W.; Ren, W.; Chen, Z.; Lu, T.; Deng, L.; Tang, J.; Zhang, X.; Wang, L.; Bai, F. Theoretical design of porphyrin dyes with electron-deficit heterocycles towards near-IR light sensitization in dye-sensitized solar cells. &lt;em&gt;Sol. 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Jpn.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;87&lt;/em&gt; (6), 064802. &lt;a href=&quot;https://doi.org/10.7566/JPSJ.87.064802&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.7566/JPSJ.87.064802&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Slavney, A. H.; Connor, B. A.; Leppert, L.; Karunadasa, H. I. A pencil-and-paper method for elucidating halide double perovskite band structures. &lt;em&gt;Chem. Sci.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;10&lt;/em&gt; (48), 11041–11053. &lt;a href=&quot;https://doi.org/10.1039/C9SC03219C&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1039/C9SC03219C&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Tetiana Zubatyuk, Ben Nebgen, Nicholas Lubbers, Justin S. Smith, Roman Zubatyuk, Guoqing Zhou, Christopher Koh, Kipton Barros, Olexandr Isayev, Sergei Tretiak. Machine Learned Hückel Theory: Interfacing Physics and Deep Neural Networks. arXiv:&lt;a href=&quot;https://arxiv.org/abs/1909.12963&quot; rel=&quot;noreferrer&quot;&gt;1909.12963&lt;/a&gt; &lt;strong&gt;[cond-mat.dis-nn]&lt;/strong&gt; &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Bannwarth, C.; Ehlert, S.; Grimme, S. GFN2-xTB—An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method with Multipole Electrostatics and Density-Dependent Dispersion Contributions. &lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;15&lt;/em&gt; (3), 1652–1671. &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01176&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jctc.8b01176&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="175" LastEditorUserId="49" LastEditDate="2020-04-30T16:29:40.480" LastActivityDate="2020-04-30T16:29:40.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="87" PostTypeId="1" AcceptedAnswerId="88" CreationDate="2020-04-30T07:53:02.963" Score="19" ViewCount="317" Body="&lt;p&gt;I've seen many papers analyzing reaction pathway using a small basis set like 6-31G* for all optimization steps and later single point calculations in bigger one (like 6-311++G**).&#xA;What is the correct sequence of jobs for TS search in such a case?&#xA;Should it be:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Frequency (6-31G*)&lt;/li&gt;&#xA;&lt;li&gt;TS_search (6-31G*)&lt;/li&gt;&#xA;&lt;li&gt;Single Point Energy (6-311++G**)&lt;/li&gt;&#xA;&lt;li&gt;Frequency (6-311++G**)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Frequency (6-31G*)&lt;/li&gt;&#xA;&lt;li&gt;TS_search (6-31G*)&lt;/li&gt;&#xA;&lt;li&gt;Frequency (6-31G*)&lt;/li&gt;&#xA;&lt;li&gt;Single point Energy (6-311++G**)&lt;/li&gt;&#xA;&lt;li&gt;Frequency (6-311++G**)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="7" LastEditDate="2022-02-12T14:02:21.657" LastActivityDate="2022-02-13T17:57:17.527" Title="Correct jobs sequence for transition-state (TS) search" Tags="|quantum-chemistry|transition-state|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="88" PostTypeId="2" ParentId="87" CreationDate="2020-04-30T08:03:04.090" Score="11" Body="&lt;p&gt;J1 Freq (6-31G*); J2 TS_search (6-31G*); J3 Freq (6-31G*);&lt;/p&gt;&#xA;&#xA;&lt;p&gt;is good because it let's you optimize the saddle point and then get the thermodynamic data &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the single-point correction don't recalculate the frequencies because the thermodynamic corrections won't change much anyway. You can also include implicit solvent in J4. &lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-04-30T08:03:04.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="89" PostTypeId="1" AcceptedAnswerId="1296" CreationDate="2020-04-30T08:13:14.337" Score="19" ViewCount="2501" Body="&lt;p&gt;When proposing or predicting new materials, whether in the bulk or in two dimensions, it is important to discuss the stability of the system. This is usually done through thermodynamics and(or) lattice dynamics. A feasible way to determine the dynamical stability of a material is by modeling its phonon band structure. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I see that two popular methods of modeling the phonon band structure are:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(a) the frozen phonon / finite displacement method (as implemented in &lt;code&gt;phonopy&lt;/code&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(b) Linear Response Theory / Density Functional Perturbation Theory (as implemented in &lt;code&gt;Quantum ESPRESSO&lt;/code&gt; (&lt;code&gt;ph.x&lt;/code&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are the two methods equivalent or is one more reliable/accurate than the other, and if so, why?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-06-12T23:12:57.183" LastActivityDate="2020-06-14T09:54:22.650" Title="Are there differences in accuracy and reliability between the frozen phonon method and Density Functional Perturbation Theory?" Tags="|density-functional-theory|band-structure|phonons|phonopy|dfpt|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="90" PostTypeId="1" CreationDate="2020-04-30T08:40:22.017" Score="21" ViewCount="1035" Body="&lt;p&gt;Given that most of the available codes for performing DFT calculations work with periodic boundary conditions, there are tools like &lt;code&gt;mcsqs&lt;/code&gt; as a part of the Alloy Theoretic Automated Toolkit (&lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;noreferrer&quot;&gt;ATAT&lt;/a&gt;) that enable generation of SQS for modelling materials with configurational disorder. Inherently, these methods of generating SQS rely on the periodicity of the supercell in all directions while generating the SQS. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In simulations where we explicitly reduce the effect of the periodic images in one or more dimensions (like when modelling surfaces), what are the points to keep in mind to ensure that the SQS are generated and used correctly?  &lt;/p&gt;&#xA;" OwnerUserId="22" LastEditorUserId="5" LastEditDate="2021-03-15T23:03:12.027" LastActivityDate="2021-03-15T23:03:12.027" Title="Generating special quasirandom structures (SQS) for surface calculations?" Tags="|ab-initio-calculations|surfaces|special-quasirandom-structures|alloy-theoretic-automated-toolkit|radial-distribution-function|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="91" PostTypeId="2" ParentId="87" CreationDate="2020-04-30T10:24:26.600" Score="20" Body="&lt;p&gt;A common and not quite unreasonable approach is to do molecular structure optimisations at a low level, establish the path(s) at this level, and obtain better energies at a higher level. It really depends on what you need and what you can afford. However, there are plenty of things to consider, and doing this approach without checking may lead to wrong conclusions.&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;ol&gt;&#xA;  &lt;li&gt;Freq (6-31G*) &lt;/li&gt;&#xA;  &lt;li&gt;TS_search (6-31G*) &lt;/li&gt;&#xA;  &lt;li&gt;SP (6-311++G**) &lt;/li&gt;&#xA;  &lt;li&gt;Freq (6-311++G**)&lt;/li&gt;&#xA;  &lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\strut{}$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;ol&gt;&#xA;  &lt;li&gt;Freq (6-31G*)&lt;/li&gt;&#xA;  &lt;li&gt;TS_search (6-31G*)&lt;/li&gt;&#xA;  &lt;li&gt;Freq (6-31G*)&lt;/li&gt;&#xA;  &lt;li&gt;SP (6-311++G**)&lt;/li&gt;&#xA;  &lt;li&gt;Freq (6-311++G**)?&lt;/li&gt;&#xA;  &lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Both approaches are basically the same, at least for the transition state,  because 2 will include frequencies, otherwise you will not find the TS.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore 1, 2, 2 + Freq. is fine; 4 (top) or 5 (bottom) is wrong and will almost certainly lead to less accurate energies.&lt;br&gt;&#xA;I also generally consider Pople basis sets outdated and underperforming, and especially inconsistent for any interpolation. Use something more reasonable, there are plenty of options. For DFT I recommend the def2-XVZP family as it is available in most QC packages. See the incredible &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.basissetexchange.org/&lt;/a&gt; for an extensive list and file formats.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Back to the job 5 problem. With a frequency calculation you are almost always employing the harmonic approximation. Therefore the obtained modes are only meaningful, if they are computed as the same level of theory as the optimised structure. A valid approach, however, is to recompute energies at a higher level and add thermal corrections from the optimisation at a lower level.&lt;br&gt;&#xA;For example, in generic terms Density Functional Approximation (DFA), Split Valence Basis Set (SVBS), X-tuple Zeta Basis Set (X &gt; 2, XZBS):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\small&#xA;\begin{array}{llcc}&#xA;  \text{Optimisation:}     &amp;amp; \text{DFA/SVBS} &amp;amp; \leadsto &amp;amp; E_\mathrm{el, SV}\\&#xA;  \text{Anal. 2nd deriv.:} &amp;amp; \text{DFA/SVBS} &amp;amp; \leadsto &amp;amp; &#xA;    E_\mathrm{ZPE, SV}, \dots, &#xA;    H_{\mathrm{corr., SV}, T}, G_{\mathrm{corr., SV}, T}\\\hline&#xA;  \mathrm{Sum_{SV}}               &amp;amp;                 &amp;amp;          &amp;amp;&#xA;    E_\mathrm{o, SV}, \dots, H_{\mathrm{SV}, T}, G_{\mathrm{SV}, T}\\[2ex]&#xA;  \text{Single Point}      &amp;amp; \text{DFA/3ZBS//SVBS} &amp;amp; \leadsto &amp;amp; &#xA;    E_\mathrm{el, 3Z}\\\hline&#xA;  \text{Final Energies}    &amp;amp; \text{as DFA/3ZBS//SVBS} &amp;amp; &amp;amp;&#xA;    \begin{align}&#xA;      E_\mathrm{o, 3Z/SV}   &amp;amp;= E_\mathrm{el, 3Z} + E_\mathrm{ZPE, SV}\\&#xA;        \vdots\\&#xA;      H_{\mathrm{3Z/SV}, T} &amp;amp;= E_\mathrm{el, 3Z} + H_{\mathrm{corr., SV}, T}\\&#xA;      G_{\mathrm{3Z/SV}, T} &amp;amp;= E_\mathrm{el, 3Z} + G_{\mathrm{corr., SV}, T}&#xA;    \end{align}\\\hline\hline&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;Some more practical tipps:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are also a couple of modern tricks that may help you avoid blind guessing, and also avoid expensive calculations. The escalation scheme of above is probably already more than 20 years old. Thankfully not only our computers, but also our methodology has greatly improved. State of the art DFA from the last millenia can now run in a tiny fraction of the time. A consequence of that is treating larger systems is becoming increasingly popular. Unfortunately, the art of doing calculations efficiently has suffered from this. Here are a few tips, I hope you will consider for the future:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Approximate wherever you can to generate starting structures&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Minimise conformational space, replace large moieties with methyl groups when possible. Especially isopropyl groups can be troublesome, or cyclohexyl groups and derivatives. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use cheap methodology. Semi-empirics has made a huge comeback, and it is fast and quite reliable nowadays. I cannot recommend xTB enough, see &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;.  &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Check the conformational space at that level. You don't want to be stuck with a guess, which is a high energy structure and not realise it.  &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use cheap pure DFA as workhorses (workhorse functional = WhF). Popular examples are BP86, PBE, M06L (or newer), TPSS. If your QC package can handle it, use density fitting (DF) or similarly  the Resolution of the Identity approximation (RI).  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For DFA, always use a large grid; it will cost more, but lead to faster convergence. Similarly, you always want to emplay tight criteria for the density. However, you can play with loose optimisation criteria. A loosely converged structure is always a better guess than a constructed structure.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Use these structures and validate/calibrate them against other functionals; again some popular examples are PBE0, M06 (or newer), TPSSh, B3LYP (and other derivatives). You don't want to have done all the work just to realise the one functional you have picked as a workhorse, produces significantly other results than the others.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimise key intermediates first. This will help you find the transition states, as you have reasonable approximations for bond lengths etc.&lt;br&gt;&#xA;Gaussian has a method called QST2/3, which will try to automatically compute a TS between two minima. Sure, the calculations are a bit more extensive, but you might find the TS at the first try, and not have blindly guess. You can or even should do that with semi-empirics, too.&lt;br&gt;&#xA;In many other packages (obviously not Gaussian) you have nudged elastic band methods. Use them with semi-empirics. For example &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/geometry-optimizations/tutorial-neb-calculations&quot; rel=&quot;noreferrer&quot;&gt;Orca (tutorial from the input library)&lt;/a&gt; can be coupled with xtb and provide a very reasonable guess for a TS within the hour.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;At this stage you'll probably have &lt;span class=&quot;math-container&quot;&gt;$\ce{A -&amp;gt; [AB]^\dagger -&amp;gt; B}$&lt;/span&gt;, etc. optimised at your WhF/SVBS level of theory. &lt;strong&gt;Validate!&lt;/strong&gt; Then run higher level calculations with larger basis sets. Make sure your paths are well connected and make sense; run intrinsic reaction coordinate analyses, or other displacement algorithms.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Validate, again. Yes I know this sounds like a broken record, but you want to justify your results. Obviously, your mileage may vary, so tailor this to your applications. You may want to reoptimise the key steps of your path, check for deviations in structure and whether the energies hold. If you calculate catalytic cycles, I recommend reading about the energy span model.&lt;sup&gt;[1]&lt;/sup&gt; &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you can afford it (and want to make double-dead sure), also validate against wave-function based methods, e.g. MP2, DLPNO-CC, CCSD-F12, etc..&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Kozuch, S.; Shaik, S. How to Conceptualize Catalytic Cycles? The Energetic Span Model. &lt;em&gt;Acc. Chem. Res.&lt;/em&gt; &lt;strong&gt;2011,&lt;/strong&gt; &lt;em&gt;44&lt;/em&gt; (2), 101–110. &lt;a href=&quot;https://doi.org/10.1021/ar1000956&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/ar1000956&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="49" LastEditorUserId="7" LastEditDate="2020-04-30T13:49:45.450" LastActivityDate="2020-04-30T13:49:45.450" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="92" PostTypeId="5" CreationDate="2020-04-30T11:30:23.197" Score="0" Body="&lt;blockquote&gt;&#xA;  &lt;h2&gt;Quantitative structure–activity relationship (QSAR)&lt;/h2&gt;&#xA;  &#xA;  &lt;p&gt;QSAR is a technique that tries to predict the activity, reactivity, and properties of an unknown set of molecules based on analysis of an equation connecting the structures of molecules to their respective measured activity and property.&lt;/p&gt;&#xA;  &#xA;  &lt;p&gt;From: In Vitro Toxicology, 2018 (quoted from &lt;a href=&quot;https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/quantitative-structure-activity-relationship&quot; rel=&quot;nofollow noreferrer&quot;&gt;Science Direct&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;h2&gt;Quantitative structure–activity relationship (QSAR) &lt;em&gt;in drug design&lt;/em&gt;&lt;/h2&gt;&#xA;  &#xA;  &lt;p&gt;Quantitative structure–activity relationships (QSAR) are mathematical relationships linking chemical structure and pharmacological activity in a quantitative manner for a series of compounds. Methods which can be used in QSAR include various regression and pattern recognition techniques.&lt;br&gt;&#xA;  QSAR is often taken to be equivalent to chemometrics or multivariate statistical data analysis. It is sometimes used in a more limited sense as equivalent to Hansch analysis. QSAR is a subset of the more general term SPC.&lt;/p&gt;&#xA;  &#xA;  &lt;p&gt;(quoted from: &lt;a href=&quot;https://doi.org/10.1351/goldbook.QT06977&quot; rel=&quot;nofollow noreferrer&quot;&gt;IUPAC Gold book, DOI: 10.1351/goldbook.QT06977&lt;/a&gt;)&lt;/p&gt;&#xA;  &#xA;  &lt;h2&gt;Quantitative structure–activity relationships (QSAR)&lt;/h2&gt;&#xA;  &#xA;  &lt;p&gt;The building of structure–biological activity models by using regression analysis with physicochemical constants, indicator variables or theoretical calculations. The term has been extended by some authors to include chemical reactivity, i.e. activity is regarded as synonymous with reactivity. This extension is, however, discouraged.&#xA;  See also: correlation analysis&lt;/p&gt;&#xA;  &#xA;  &lt;p&gt;(quoted from: &lt;a href=&quot;https://doi.org/10.1351/goldbook.Q04981&quot; rel=&quot;nofollow noreferrer&quot;&gt;IUPAC Gold book, DOI: 10.1351/goldbook.Q04981&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="49" LastEditorUserId="49" LastEditDate="2020-05-01T14:25:32.760" LastActivityDate="2020-05-01T14:25:32.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="93" PostTypeId="4" CreationDate="2020-04-30T11:30:23.197" Score="0" Body="Quantitative structure–activity relationship (QSAR) is a regression technique to predict the properties, activity, and reactivity of unknown molecules based on molecules where these are known." OwnerUserId="49" LastEditorUserId="49" LastEditDate="2020-05-01T14:25:37.907" LastActivityDate="2020-05-01T14:25:37.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="95" PostTypeId="1" CreationDate="2020-04-30T13:24:47.130" Score="5" ViewCount="242" Body="&lt;p&gt;We face a reality that we have many codes to do matter modeling simulations (as described &lt;a href=&quot;https://materials.stackexchange.com/questions/70/why-do-we-have-so-many-dft-codes-softwares-are-they-redundant-if-not-what-ma&quot;&gt;here&lt;/a&gt;). This is good. But, how good is it, really? For any beginner in computational modeling it is very difficult to choose a code with which to start modeling. Also, as these codes don't talk to each other, it is also hard to move between them.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-09-09T18:26:09.240" LastActivityDate="2021-09-05T17:51:43.950" Title="More matter modeling codes or better codes?" Tags="|software|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="96" PostTypeId="2" ParentId="95" CreationDate="2020-04-30T14:00:01.193" Score="12" Body="&lt;p&gt;If you put aside the commercial software like QuantumWise, Materials Studio, Schrodinger that are well-known materials modeling tools and are designed in a very general fashion, other open-source codes in this field more or less are designed for a specific purpose. It's true that LAMMPS, for example, is a general molecular dynamics simulation library, but most of the computational materials scientists that I know, choose their code or software based on literature review and what is the well-known application of that particular software. As I said LAMMPS, for example, is a general molecular dynamics software, but most of the people that I know which work in designing polymers/bio-polymers use GROMACS, not LAMMPS because it has suitable force-fields for that specific area of research and you don't need to reinvent the wheel from scratch. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;This was just an example to show how people choose their research software and I hope it helps you.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-30T14:00:01.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="97" PostTypeId="1" CreationDate="2020-04-30T14:05:47.687" Score="26" ViewCount="229" Body="&lt;p&gt;Let's assume I have already relaxed a molecular structure for a non-trivial molecule and obtained a geometry that is close to the one resulting from X-ray crystallography. This can be achieved in a number of ways, e.g. trivially (relaxation in vacuum) if the molecule is not feeling a significant distortion from its environment, or with ad-hoc tricks such as surrounding it with a frozen local environment. In any case, I have access to a set of vibrational normal modes, that, in a first approximation and for my purposes, may resemble the actual vibrations of the molecules in the crystal.&#xA;&lt;em&gt;This can be done with a variety of packages, let's say we are using Gaussian&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Independently, we have information on the phonon spectrum.&#xA;&lt;em&gt;Again, this can be done with a variety of packages, let's say we are using Quantum Espresso&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The question is: &lt;strong&gt;is there a good procedure to map (or, at least, to relate) the molecular normal modes with the lattice phonons?&lt;/strong&gt; In particular I'm interested in complicated (C1 symmetry) molecules, so any way that does not require relying on symmetry arguments would be preferred.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To put the question into perspective: the goal would be &lt;em&gt;to facilitate the molecular design of systems with improved properties&lt;/em&gt;. Designing and obtaining molecules is hard enough as it is, but designing specific crystal packings is adding a layer of complexity, hence the utility of projecting (most of) the key behavior into the single molecule level, whenever it is possible. &lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="7" LastEditDate="2020-05-18T20:45:59.413" LastActivityDate="2020-05-22T12:30:42.043" Title="How to map molecular vibrations into lattice phonons?" Tags="|crystal-structure|vibrations|phonons|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="98" PostTypeId="2" ParentId="90" CreationDate="2020-04-30T14:34:56.883" Score="10" Body="&lt;p&gt;First of all, it's better to define the terms here because probably not all the people here are familiar with SQS right away. SQS is an abbreviation for special quasirandom structures. The illuminating reference here is the work of &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.65.353&quot; rel=&quot;noreferrer&quot;&gt;Zunger et. al.&lt;/a&gt; that basically show you that the most relevant parameter to consider when you want if SQS truly resembles a random alloy or not is &lt;strong&gt;radial distribution function&lt;/strong&gt; that basically tells you how the atoms are distributed in the space.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-30T14:34:56.883" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="99" PostTypeId="1" AcceptedAnswerId="115" CreationDate="2020-04-30T15:48:36.873" Score="17" ViewCount="147" Body="&lt;p&gt;The estimates for partial atomic charges start with the very simple Mulliken analysis, which we all study in class, but which is known to be very limited. Beyond this, there is a range of computational methodologies to estimate partial charges; Gaussian for example has multiple options for generating electrostatic &quot;potential-derived&quot; charges. Each method is based on a different theoretical framework with different assumptions, so they are not equivalent.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm interested in the simulation of the crystal field (CF) effects (a) in transition metal ions and/or (b) in rare earth (lanthanide) ions via electrostatic models. Any modelling that does not explicitly consider covalent effects is going to be limited to some extent.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: &lt;strong&gt;what software and what software and method would be the most adequate to estimate partial atomic charges for the purposes of a electrostatic simulation of the crystal field effects&lt;/strong&gt; ?&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="52" LastEditDate="2020-05-03T00:48:22.503" LastActivityDate="2020-05-03T00:48:22.503" Title="Best partial atomic charges estimate for crystal field purposes?" Tags="|magnetism|electrostatic|lanthanide|crystal-field|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="100" PostTypeId="1" AcceptedAnswerId="108" CreationDate="2020-04-30T15:57:42.390" Score="18" ViewCount="602" Body="&lt;p&gt;Some tools allow for a relatively inexpensive analysis of crystal field effects in metal complexes, starting from the coordination sphere. Additionally, there are multiple sources of crystal structures that, to a certain level, can be accessed following automated computational procedures. An example of the latter would be the Cambridge Structural Database (CSD) of  the Cambridge Crystallographic Data Centre (CCDC).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is:&#xA;&lt;strong&gt;Given a large series of crystal structures&lt;/strong&gt; in any given standard form (e.g. xyz, pdb, cif...), &lt;strong&gt;is there a tool to automatically extract the coordination sphere of a certain metal ion&lt;/strong&gt; with minimal user intevention?&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="5" LastEditDate="2020-05-09T20:45:22.767" LastActivityDate="2020-05-09T20:45:22.767" Title="Extract coordination sphere from crystal structure" Tags="|crystal-structure|ccdc|coordination|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="101" PostTypeId="2" ParentId="100" CreationDate="2020-04-30T16:22:18.547" Score="4" Body="&lt;p&gt;I don't think there is a predefined tool right away or at least I'm not aware of that, but this problem seems a pretty easy task to do with TCL in VMD (Visual Molecular Dynamics) software. Basically you want to find the ligands that are attached to metal atom in your molecule. As you know all the molecular formats such as xyz or pdb, lists the atoms, and then list the connectivity of atoms for forming the bonds. It's just a search task in your connectivity matrix (list of bonds) to find rows that contain the id of metal atom. Let's say you have this connectivity matrix for three atoms of M (metal atom), A, B:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;M - A&#xA;A - B&#xA;B - M&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;So your search should identify the &lt;code&gt;M - A&lt;/code&gt; and &lt;code&gt;B - M&lt;/code&gt; by checking that if one of the two members in each row is equal to M or not. I hope it helps you to find such tool or at least develop your own to do this job for you.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-30T16:22:18.547" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="102" PostTypeId="2" ParentId="85" CreationDate="2020-04-30T16:26:55.253" Score="12" Body="&lt;p&gt;Orbital-Free Density Functional Theory (OFDFT) is, as the name suggests, an attempt to work with DFT without using the Kohn-Sham (KSDFT) approach of expressing the density as a sum of non-interacting orbital densities. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the KS formulation, the kinetic energy functional explicitly depends on the choice of orbitals, whereas in principle the true energy functional should only depend on the overall density. The trade-off is that the KS kinetic energy functional has a well defined simple form, with all the many body effects describing the system being compressed into the exchange-correlation functional. For OFDFT, both the kinetic energy and exchange correlation functionals are undetermined and must be approximated in some way.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So why would one want to use OFDFT if its less easily defined and presumably less accurate? The main benefit is in the reduced scaling; while KSDFT generally scales cubically with the number of orbitals due to the need to perform a diagonalization, OFDFT scales linearly with system size. This obviously offers a huge potential benefit for studying large systems. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A fairly nice, practical tutorial for using OFDFT is given on the &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorials/ofdft/ofdft.html&quot; rel=&quot;noreferrer&quot;&gt;GPAW website&lt;/a&gt; and a more in depth description of their implementation is given &lt;a href=&quot;https://arxiv.org/pdf/1408.4701.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-04-30T16:26:55.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="103" PostTypeId="2" ParentId="85" CreationDate="2020-04-30T16:34:37.490" Score="14" Body="&lt;p&gt;At least I was able to find three other forms of DFT listed as:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.165118&quot; rel=&quot;noreferrer&quot;&gt;Lattice density-functional theory&lt;/a&gt;: It's suitable for modeling the lattice gas, binary liquid solutions, order-disorder phase transformations.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Orbital-free_density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;Orbital-free density functional theory&lt;/a&gt;: It's less accurate than KS but it's much faster.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Strictly-Correlated-Electrons_density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;Strictly-Correlated-Electrons density functional theory&lt;/a&gt;: It's an alternative to KS for strongly-correlated systems. In contrast to KS, when you start from a set of non-interacting electrons and you could calculate their kinetics energy exactly, and then approximate the interaction through exchange-correlation energy, in SCE DFT, you start from an infinite electronic correlation and zero kinetics energy.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-04-30T16:34:37.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="104" PostTypeId="2" ParentId="48" CreationDate="2020-04-30T16:39:00.537" Score="13" Body="&lt;p&gt;First of all, you need to be familiar with &lt;strong&gt;models for magnetic exchange&lt;/strong&gt;. Two important examples are &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_Heisenberg_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;Heisenberg&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Ising_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ising&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;Depending on the system you are studying, you will be using one of these. Typically, for very anisotropic spins with a very well defined axis for the spin projection, you should use the Ising model, which is simpler. On the other hand, more isotropic spins will require a Heisenberg model.&lt;/p&gt;&#xA;&lt;p&gt;These models will give you the energy difference per ion pair between the parallel and antiparallel configuration. Your calculation, for extended solids, will typically give you energies for different spin alignings in a fragment of the crystal containing several magnetic ions. The energies of the fragments will therefore differ in a larger value than the magnetic exchange parameter; you need to adjust the energies accordingly. This can be as simple as a linear factor.&lt;/p&gt;&#xA;&lt;p&gt;In the example you provide, the set of equations arises because there are different (super)exchange interaction pathways, that present different strenghts. These need to be estimated independently, and this is why you need more than two energies to extract the needed information univocally.&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="4232" LastEditDate="2021-10-28T03:54:38.007" LastActivityDate="2021-10-28T03:54:38.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="105" PostTypeId="1" AcceptedAnswerId="1216" CreationDate="2020-04-30T17:27:31.260" Score="21" ViewCount="105" Body="&lt;p&gt;Is diffusion/variational quantum Monte Carlo applicable to the calculation of the athermal (zero temperature, no zero point energy) equation of state of metals including electronic correlation? For instance, would it work to compute the total free energy (again, at &lt;span class=&quot;math-container&quot;&gt;$\pu{0}{K}$&lt;/span&gt;) of gold versus its unit cell volume?&lt;/p&gt;&#xA;" OwnerUserId="205" LastEditorUserId="7" LastEditDate="2020-05-18T19:56:50.733" LastActivityDate="2020-06-07T07:45:46.827" Title="QMC calculation of the equation of state of metals" Tags="|quantum-monte-carlo|variational-principle|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="106" PostTypeId="5" CreationDate="2020-04-30T17:43:04.550" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-04-30T17:43:04.550" LastActivityDate="2020-04-30T17:43:04.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="107" PostTypeId="4" CreationDate="2020-04-30T17:43:04.550" Score="0" Body="For questions about modeling materials containing lanthanide elements (atomic numbers 57-71)" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-01T10:00:51.827" LastActivityDate="2020-05-01T10:00:51.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="108" PostTypeId="2" ParentId="100" CreationDate="2020-04-30T18:36:46.617" Score="14" Body="&lt;p&gt;Yes, there is! &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt; is ideally suited for this task. Specifically, I highly recommend the &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.local_env.html&quot; rel=&quot;noreferrer&quot;&gt;local environment module&lt;/a&gt;. Given a CIF, you can calculate the coordination environment around a given atom index using the following Python code. Here, the &lt;code&gt;CrystalNN&lt;/code&gt; algorithm is used, but you can find many other approaches &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.local_env.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; that you should consider. Simply swap out the &lt;code&gt;nn_object&lt;/code&gt; line.&lt;/p&gt;&#xA;&#xA;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import pymatgen as pm&#xA;from pymatgen.analysis.local_env import CrystalNN&#xA;p = '/path/to/cif' #path to CIF file&#xA;site_idx = 0 #index of atom to get coordination environment&#xA;structure = pm.Structure.from_file(p) #read in CIF as Pymatgen Structure&#xA;nn_object = CrystalNN() #initialize class&#xA;neighbors = nn_object.get_nn_info(structure,site_idx) #get NN info&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;An example output for &lt;code&gt;neighbors&lt;/code&gt; would look something like the following, which is a list containing all the coordinating atoms and their distances, the nearest image, and the site index. Other methods, such as &lt;code&gt;VoronoiNN&lt;/code&gt;, will provide additional information.&lt;/p&gt;&#xA;&#xA;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;[{'site': PeriodicSite: O (3.2910, 2.0794, 0.9655) [0.4692, 0.2958, 0.2602], 'image': (0, 0, 0), 'weight': 1, 'site_index': 25}, {'site': PeriodicSite: C (4.9976, 0.0907, 2.7314) [0.7612, 0.0129, 0.5053], 'image': (0, 0, 0), 'weight': 1, 'site_index': 35}]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Of course, there are simpler approaches that are just based off a fixed cutoff distance (in Pymatgen, that could be done with &lt;code&gt;pymatgen.core.structure.get_neighbors()&lt;/code&gt; or in the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; with the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/neighborlist.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ase.neighborlist&lt;/code&gt; tool&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-04-30T18:45:49.003" LastActivityDate="2020-04-30T18:45:49.003" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="109" PostTypeId="1" AcceptedAnswerId="1148" CreationDate="2020-04-30T19:00:37.073" Score="29" ViewCount="3479" Body="&lt;p&gt;It is known that neither LDA or GGA correctly account for the strong on-site Coulomb interaction of localized electrons&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorials/hubbardu/hubbardu.html&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;. A cost-effective way of correcting this is by using a Hubbard-like term &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;. In literature, I have often found that &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is introduced as an empirical parameter, taken from previous computational studies or experiments. Alternatively, I have seen studies where various values for &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; are used (typically between 2 and 5 eV). Neither of these methods seem too convinving. &#xA;Is there a standard and reliable manner of determining the (best) value for &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="88" LastEditDate="2020-05-27T15:34:23.647" LastActivityDate="2020-05-31T04:47:52.117" Title="What is the appropriate way of determining a value for the Hubbard-like potential U for LDA+U / GGA+U calculations?" Tags="|density-functional-theory|intermolecular-forces|hubbard-model|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="110" PostTypeId="1" CreationDate="2020-04-30T19:08:27.933" Score="31" ViewCount="748" Body="&lt;p&gt;I'm a noob with zero knowledge of the subject. Materials Modeling is so specialized that it's not even on Wikipedia yet. Help orient a newcomer. What do you use it for? Can you use it to model materials for a bulletproof t-shirt, a superior mask to protect against COVID-19, a flux capacitor?&lt;/p&gt;&#xA;" OwnerUserId="209" LastEditorUserId="5" LastEditDate="2021-11-30T22:00:13.007" LastActivityDate="2021-11-30T22:00:13.007" Title="What is Materials Modeling?" Tags="|terminology|materials-design|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="111" PostTypeId="1" CreationDate="2020-04-30T19:44:08.287" Score="18" ViewCount="1046" Body="&lt;p&gt;I would like to calculate the chemical potential of elements having different environmental condition (rich or poor) using VASP. How is this accomplished?&lt;/p&gt;&#xA;" OwnerUserId="211" LastEditorUserId="5" LastEditDate="2020-04-30T19:49:52.537" LastActivityDate="2020-05-01T04:22:55.783" Title="In VASP, how is the chemical potential of elements calculated?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="112" PostTypeId="2" ParentId="109" CreationDate="2020-04-30T19:48:59.650" Score="18" Body="&lt;p&gt;You can calculate &lt;em&gt;U&lt;/em&gt; in an &lt;em&gt;ab initio&lt;/em&gt; way via linear response theory, for instance. See an example &lt;a href=&quot;http://hjkgrp.mit.edu/content/calculating-hubbard-u&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. However, there is no guarantee that a linear response &lt;em&gt;U&lt;/em&gt; value is empirically ideal. That is part of the reason why, in practice, many people invoke some empirical &lt;em&gt;U&lt;/em&gt; term and hope that it holds reasonably well for their system (especially compared to &lt;em&gt;U&lt;/em&gt; = 0 eV). In the case of using a range of &lt;em&gt;U&lt;/em&gt; values, the goal is usually to put some sort of lower and upper bound on the computed property of interest, since the ideal &lt;em&gt;U&lt;/em&gt; value is not known.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-04-30T19:48:59.650" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="113" PostTypeId="1" CreationDate="2020-04-30T20:09:14.007" Score="26" ViewCount="1028" Body="&lt;p&gt;Some properties of transition metal compounds can be influenced by static correlation, relativistic effects, and, in some cases, close-lying electronic states could result in difficulties in SCF convergence. All these complications influence geometry optimizations and, hence, the accuracy of the obtained results.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Considering a usual Kohn-Sham DFT calculation of a TM compound with organic ligands:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;What functionals gives accurate equilibrium geometries, compared to high-level calculations or experimental ones?&lt;/li&gt;&#xA;&lt;li&gt;What functionals are accurate for electronic and bonding properties?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I'm not asking for a specific functional, but some guidelines on which are better for those purposes.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="5" LastEditDate="2020-05-30T21:08:03.530" LastActivityDate="2020-05-31T09:52:11.480" Title="What are the best functionals for transition metal compounds?" Tags="|density-functional-theory|functional|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="114" PostTypeId="2" ParentId="110" CreationDate="2020-04-30T20:25:12.437" Score="21" Body="&lt;p&gt;I'm just as curious of a user here as you, but I was able to find that a &lt;a href=&quot;https://en.wikipedia.org/wiki/Computational_materials_science&quot; rel=&quot;noreferrer&quot;&gt;Materials Modeling Wikipedia page&lt;/a&gt; does in fact exist. :)&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&lt;strong&gt;Computational materials science and engineering&lt;/strong&gt; uses modeling,&#xA;  simulation, theory, and informatics to understand materials. Main&#xA;  goals include discovering new materials, determining material behavior&#xA;  and mechanisms, explaining experiments, and exploring materials&#xA;  theories. It is analogous to computational chemistry and computational&#xA;  biology as an increasingly important subfield of materials science.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="29" LastEditorUserId="29" LastEditDate="2020-05-01T07:59:44.480" LastActivityDate="2020-05-01T07:59:44.480" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="115" PostTypeId="2" ParentId="99" CreationDate="2020-04-30T20:52:29.813" Score="15" Body="&lt;p&gt;There are a few recent atomic partial charge schemes that are useful.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You mentioned the electrostatic fitting schemes. These seek to best match the electrostatic potential of the molecule / system, but wouldn't be ideal for your situation. They have problems fitting charges on &quot;buried atoms&quot; such as the metal center of your complex, because they have little effect on the outer electrostatic potential (i.e. all your ligands surround the metal, so it's hard to separate the charge on the metal and the charges on the ligands).&lt;/li&gt;&#xA;&lt;li&gt;Atomic orbital partioning (e.g. Mulliken, NAO, etc.). These methods use atomic orbitals, but are often sensitive to basis set effects. &lt;/li&gt;&#xA;&lt;li&gt;Hirschfeld / Atoms in Molecules (AIM) analysis. These methods seek to partition the electron density to produce charges. Consequently, they'll have little problem with your metal complex. Several schemes exist depending on the program you use, but the open source &lt;a href=&quot;https://theochem.github.io/horton/2.1.1/user_postproc_aim.html&quot; rel=&quot;noreferrer&quot;&gt;Horton package&lt;/a&gt; can derive most by post-processing.&lt;/li&gt;&#xA;&lt;li&gt;A comment above suggests &lt;a href=&quot;https://doi.org/10.1039/C6RA04656H&quot; rel=&quot;noreferrer&quot;&gt;Thomas Manz's DDEC6 scheme&lt;/a&gt;. This has been fairly robust over the last few years although has fewer proponents than Hirshfeld / IBS approaches - possibly because Chargemol is currently the only program with an implementation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Incidentally, there's an excellent review article &lt;a href=&quot;https://doi.org/10.1002/cphc.202000040&quot; rel=&quot;noreferrer&quot;&gt;&quot;The Atomic Partial Charges Arboretum: Trying to See the Forest for the Trees&quot;&lt;/a&gt; that may provide useful context.&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;In all, no single charge distribution tells the whole story, but a&#xA;  trio of well‐defined ones – i.e., one representative each of the three&#xA;  major classes of Corminboeuf and coworkers – should be able to cover&#xA;  most aspects of it.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;The three classes mentioned include electrostatic fitting, atomic orbital partitioning, and electron density partitioning.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For your purpose, I'd highly advocate some type of electron density partitioning - these methods are resistant to basis set effects and won't have issues with buried metal centers in your molecules.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2020-04-30T20:57:34.870" LastActivityDate="2020-04-30T20:57:34.870" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="116" PostTypeId="1" CreationDate="2020-04-30T21:10:17.550" Score="16" ViewCount="133" Body="&lt;p&gt;I want to adsorb atomic oxygen on a slab surface. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The adsorption energy I am calculating is around -10 eV. Which seems higher to me than I expected. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is this: Is this value reasonable or is there some issue in my calculation?&lt;/p&gt;&#xA;" OwnerUserId="219" LastEditorUserId="5" LastEditDate="2020-04-30T21:13:35.193" LastActivityDate="2021-06-29T18:50:13.593" Title="The upper limit for the atomic adsorption energy value on a slab surface?" Tags="|density-functional-theory|surfaces|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="117" PostTypeId="2" ParentId="113" CreationDate="2020-04-30T21:12:58.603" Score="9" Body="&lt;p&gt;I think for transition metals the best functionals would be MS1-D3(0), ωB97M-V, ωB97X-V, MN15, and B97M-r based on the information from the review article-&lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="220" LastEditorUserId="220" LastEditDate="2020-05-01T22:14:27.847" LastActivityDate="2020-05-01T22:14:27.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="118" PostTypeId="2" ParentId="116" CreationDate="2020-04-30T21:18:52.763" Score="11" Body="&lt;p&gt;To address the question in the title, I went to &lt;a href=&quot;https://www.catalysis-hub.org/energies&quot; rel=&quot;noreferrer&quot;&gt;Catalysis-Hub&lt;/a&gt; and sorted the computed energies from most exothermic to most endothermic. Ignoring the C (g) entries adsorbing onto surfaces (which have computed adsorption energies around -7 eV), the most exothermic entry is &lt;span class=&quot;math-container&quot;&gt;$\mathrm{I_{2}\ (g)} + 2* \rightarrow 2 \mathrm{I}^*$&lt;/span&gt; on a Pt(111) surface with a value of -3.49 eV with the SCAN functional. This definitely seems very exothermic to me.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Anyway, for what you're actually asking, -10 eV sounds far too exothermic. It is almost certainly unreasonable. Perhaps your surface structure rearranged upon adsorption, there is some algebra error, some settings were changed, or a spin state was not correctly accounted for.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-04-30T21:22:45.560" LastActivityDate="2020-04-30T21:22:45.560" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="119" PostTypeId="1" AcceptedAnswerId="3734" CreationDate="2020-04-30T22:08:40.943" Score="31" ViewCount="516" Body="&lt;p&gt;In answering another question here (&lt;a href=&quot;https://materials.stackexchange.com/q/85/7&quot;&gt;Is there any relevant DFT formalism apart from the Kohn-Sham approach?&lt;/a&gt;), I came across numerous statements that Orbital-Free DFT should scale linearly with system size. From the &lt;a href=&quot;https://arxiv.org/pdf/1408.4701.pdf&quot; rel=&quot;noreferrer&quot;&gt;implementation details&lt;/a&gt; in GPAW, this seems to be a result of using the same machinery as for a typical Kohn-Sham DFT calculation, but with only a single &quot;orbital&quot; (actually the square root of the density). But from the other statements, there seems to be a more fundamental physical reason why we would expect orbital free DFT to scale linearly with system size. Why should orbital free DFT be linearly scaling and by what metric for system size (since KS DFT is usually said to scale cubically with the number of orbitals)? &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-21T20:06:58.660" LastActivityDate="2020-11-13T02:05:04.210" Title="Why does orbital-free DFT scale linearly with system size?" Tags="|density-functional-theory|electronic-structure|gpaw|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="120" PostTypeId="2" ParentId="68" CreationDate="2020-04-30T23:30:29.460" Score="13" Body="&lt;p&gt;In the example you highlighted and indeed in most plane-wave DFT codes, there is periodicity in all three dimensions including for surface slab calculations. In the case of a surface slab, vacuum space is commonly added in the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; dimension. The vacuum space is there so that an adsorbate can bind of course, but it's also there because of the boundary conditions. A vacuum space ensures that the adsorbate-slab complex does not interact with itself over the periodic boundary, provided the vacuum space is large enough. In this way, you're modeling what is effectively a 2D system while still having 3D periodic boundary conditions as part of the DFT calculation. If an interactive example would be helpful, I recommend John Kitchin's &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.html&quot; rel=&quot;noreferrer&quot;&gt;DFT ebook&lt;/a&gt;, specifically Section 5.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The answer to both your questions is actually, for the most part, one in the same. The reason plane-wave basis sets are so useful is how well they lend themselves to periodic DFT calculations. In this case, you can represent a crystalline or bulk system with much fewer atoms than you would be able to do if you relied on a Gaussian basis set. A given metal might have a primitive unit cell of only a few atoms, whereas modeling the same metal with the same degree of accuracy without finite boundary conditions might require several hundred atoms to prevent edge effects and ensure the system is large enough. A localized, Gaussian basis set is not inherently better than a plane-wave basis set. The latter, however, is naturally better suited for adsorption problems in general. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As a side-note, because it can be helpful for to visualize orbitals in a Gaussian basis set, there are several algorithms that project plane-wave bands to Gaussian type orbitals, such as the &lt;a href=&quot;https://github.com/jrschmidt2/periodic-NBO&quot; rel=&quot;noreferrer&quot;&gt;periodic NBO code&lt;/a&gt; of Dunnington and Schmidt. This is mostly for gaining insight into the electronic structure of the chemical process, rather than a question of accuracy.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-04-30T23:43:53.543" LastActivityDate="2020-04-30T23:43:53.543" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="121" PostTypeId="1" CreationDate="2020-04-30T23:43:51.080" Score="18" ViewCount="743" Body="&lt;p&gt;I am interested to generate some configurations from MD simulations which include the presence of strong magnetic field. Does anyone know any software that has some functionality to do this?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="5" LastEditDate="2020-07-02T01:13:43.483" LastActivityDate="2020-07-03T18:41:09.993" Title="Does anyone know any software for MD simulation which include the effect of magnetic field?" Tags="|software|molecular-dynamics|lammps|gromacs|magnetic-field|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="122" PostTypeId="2" ParentId="109" CreationDate="2020-04-30T23:45:54.397" Score="15" Body="&lt;p&gt;The answer is based on &lt;strong&gt;Chapter 1 - The DFT+U: Approaches, Accuracy, and Applications&lt;/strong&gt; from the book &lt;a href=&quot;https://books.google.co.in/books?id=d2iQDwAAQBAJ&amp;amp;printsec=frontcover#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;Density Functional Calculations: Recent Progresses of Theory and Application&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For practical implementation of DFT+U, the strength of the on-site interactions is described by a couple of parameters: the on-site Coulomb term U and the site exchange term J. These parameters “U and J” can be extracted from ab initio calculations, but usually are obtained semi-empirically. The implementation of the DFT+U requires a clear understanding of the approximations it is based on and a precise evaluation of the conditions under which it can be expected to provide accurate quantitative predictions&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Different procedures have been addressed to determine the Hubbard U from first principles. In these procedures, the U parameter can generally be calculated using a self-consistent and basis set in an independent way. For each atom, the U value is found to be dependent on the material specific parameters, including its position in the lattice and the structural and magnetic properties of the crystal, and also dependent on the localized basis set employed to describe the on-site occupation in the Hubbard functional. Most programs these days use the method presented by Cococcioni et al., where the values of U can be determined through a linear response method, in which the response of the occupation of localized states to a small perturbation of the local potential is calculated. The U is self-consistently determined, which is fully consistent with the definition of the DFT+U Hamiltonian, making this approach for the potential calculations fully ab initio.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The U value is not known and practically is often tuned semi-empirically to make a good agreement with experimental or higher level computational results. However, the semi-empirical way of evaluating the U parameter fails to capture its dependence on the volume, structure, or the magnetic phase of the crystal, and also does not permit the capturing of changes in the on-site electronic interaction under changing physical conditions, such as chemical reactions. Despite the limitations of choosing the U value semiempirically for systems, where variations of on-site electronic interactions are present, it is found to be the most common practice used in literature, where the value of U is usually compared to the experimental bandgap.The semi-empirical tuning is found to be the most common practice employed by researchers due to the significant computational cost of ab initio calculations that U can have, and also, the computed U is not necessarily being better than the empirical ones. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A review on different values of U (ranging from -2 eV to 10 eV ) used for different materials are also available in the chapter&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-04-30T23:51:46.057" LastActivityDate="2020-04-30T23:51:46.057" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="123" PostTypeId="1" CreationDate="2020-05-01T00:22:26.710" Score="20" ViewCount="1711" Body="&lt;p&gt;Please mention good online video lectures on theoretical foundations and practical implementation of DFT.&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="52" LastEditDate="2020-05-03T01:16:42.943" LastActivityDate="2020-05-04T14:21:00.033" Title="Are there any online course/video lectures available on Density functional theory?" Tags="|density-functional-theory|reference-request|" AnswerCount="3" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="124" PostTypeId="2" ParentId="123" CreationDate="2020-05-01T00:22:26.710" Score="14" Body="&lt;p&gt;&lt;strong&gt;1. &lt;a href=&quot;http://compmatphys.epotentia.com/&quot; rel=&quot;noreferrer&quot;&gt;Online course on Computational Materials Physics&lt;/a&gt; by &lt;a href=&quot;https://molmod.ugent.be/members/stefaan-cottenier&quot; rel=&quot;noreferrer&quot;&gt;Prof. Stefaan Cottenier&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;All content is offered via prerecorded videos. Each video comes with a task, and after submitting the task there is in many cases either automated feedback or peer feedback. At any other time of the year, you can still study this course in a self-paced way. There is the opportunity to be part of a team to work on a project. The course is free of cost and open to anyone. Emphasis is on conceptual understanding and hands-on training, not on mathematical theory.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;2. &lt;a href=&quot;https://www.paradim.org/cu_ss_2018&quot; rel=&quot;noreferrer&quot;&gt;An Introduction to Density Functional Theory for Experimentalists&lt;/a&gt; by &lt;a href=&quot;https://www.oden.utexas.edu/people/1669/&quot; rel=&quot;noreferrer&quot;&gt;Prof. Feliciano Giustino&lt;/a&gt; during DFT Summer School 2018 at Cornell University&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The goal of this Summer School is to introduce experimentalists to density-functional theory calculations and first-principles materials modelling. This course answers the basic questions: “Can DFT help me with my experimental problem? Which  materials  properties  can  be predicted  and  how reliable are the results? How difficult would it be to run the calculation that I need? Can I do this on my own or I better seek for help from the theory group next door?”. By the end of the school the participants will be able to perform basic DFT calculations in complete autonomy, and will have a better understanding of the current literature on atomistic modelling using DFT. The course is articulated along three parallel tracks: theory lectures, practical lectures, and hands-on sessions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;3. &lt;a href=&quot;https://www.materialscloud.org/learn/sections/lfYatW/hpc-and-high-throughput-materials-modeling-ictp-trieste-2017&quot; rel=&quot;noreferrer&quot;&gt;Advanced Workshop on High-Performance &amp;amp; High-Throughput Materials Simulations using Quantum ESPRESSO | (smr 3102), Trieste, January 16 - 31, 2017&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-03T14:08:46.537" LastActivityDate="2020-05-03T14:08:46.537" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="125" PostTypeId="2" ParentId="121" CreationDate="2020-05-01T00:35:29.093" Score="5" Body="&lt;p&gt;I think that there isn't one. As the cause of the magnetic properties are the electrons, and no MD codes consider the electrons, they are unable to simulate magnetism.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-01T00:35:29.093" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="126" PostTypeId="2" ParentId="110" CreationDate="2020-05-01T00:57:36.553" Score="17" Body="&lt;p&gt;Answering your last questions: yes, yes and yes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One thing to consider is which approach do you want/need to use. You can use an atomistic approach where you simulate/model the properties and the material starting from the atomic structure of it (an input file with the list of atoms and its coordinates). The other approach is to use your material as a continuous medium and use its mechanical and optical experimental properties.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the atomistic approach, take a look at this &lt;a href=&quot;https://materials.stackexchange.com/questions/17/what-are-the-main-computational-frameworks-used-in-materials-modeling&quot;&gt;post&lt;/a&gt;.&#xA;How to simulate continuous materials, I recommend to take a look at the &lt;a href=&quot;https://www.comsol.com/&quot; rel=&quot;noreferrer&quot;&gt;COMSOL Multiphysics&lt;/a&gt; software (I'm in love with this, it is marvelous).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-01T05:18:02.473" LastActivityDate="2020-05-01T05:18:02.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="127" PostTypeId="1" CreationDate="2020-05-01T01:14:21.223" Score="19" ViewCount="1161" Body="&lt;p&gt;Many DFT codes use pseudopotentials (for the core electrons) and basis set functions (for the valence electrons) in order to solve the Schrodinger equation. This because simulates each electron wavefunction is very costly.&lt;/p&gt;&#xA;&lt;p&gt;I found works where the authors generate the pseudopotentials dividing the core electrons in electrons from the inner core and electrons for the external core (called semi-core). These semi-core electrons were also considered as &amp;quot;valence&amp;quot; electrons.&lt;/p&gt;&#xA;&lt;p&gt;When should I include semi-core electrons in DFT calculations?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="142" LastEditDate="2021-02-22T16:31:44.880" LastActivityDate="2021-02-22T16:34:49.770" Title="When should I include semi-core electrons in DFT calculations?" Tags="|density-functional-theory|pseudopotentials|relativistic|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="128" PostTypeId="2" ParentId="17" CreationDate="2020-05-01T02:01:20.667" Score="19" Body="&lt;h1&gt;Monte Carlo&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;In this case there is no one answer, and perhaps no individual best suited to write the full list. I can contribute few words about &lt;em&gt;Monte Carlo methods.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is Monte Carlo?&lt;/strong&gt; Monte Carlo (MC) is a name that refers to a broad range of computational techniques that rely on random numbers. MC is very broadly applicable anywhere you need to do a high-dimensional integral or sum, so it is widely used in fields like finance and even election forecasting (like Nate Silver's fivethiryeight), as well as the physical sciences.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Classical Monte Carlo:&lt;/strong&gt; Classical Monte Carlo is capable (in general) of describing any equilibrium statistical mechanical system. It works by stochastically sampling the Boltzmann distribution. Basically, it works by starting with an state, proposing updates to that state, accepting those updates with some probability (which satisfies the detailed balance condition). In practice, it is usually used with simplified models like the Ising model, or hard core spheres, rather than directly simulating atoms and electrons.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Quantum Monte Carlo:&lt;/strong&gt; Quantum Monte Carlo (QMC) is done by mapping a quantum problem onto an equivalent classical ensemble in a manner that sometimes looks like a path integral. One you have the corresponding classical ensemble then you can use classical Monte Carlo to study it. Similar to classical MC, QMC is typically used for simplified models, like the Heisenberg model, which can be instructive for how physical materials work.&lt;/p&gt;&#xA;&lt;p&gt;QMC has one major flaw: &lt;strong&gt;the sign problem.&lt;/strong&gt; When converting from a quantum to a classical ensemble, sometimes you end up with negative probabilities. This means that the sampled states tend to cancel each other out, so in most cases you cannot do anything useful with QMC when there is a sign problem. Systems that usually have sign problems include anything with mobile fermions in &lt;span class=&quot;math-container&quot;&gt;$d&amp;gt;1$&lt;/span&gt; and systems with frustrated spin interactions (like the triangular Heisenberg antiferromagnet).&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-04-17T22:39:33.907" LastActivityDate="2021-04-17T22:39:33.907" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="129" PostTypeId="1" AcceptedAnswerId="1101" CreationDate="2020-05-01T02:16:10.740" Score="15" ViewCount="413" Body="&lt;p&gt;I've been writing a manuscript about the breakdown of ergodicity in single spin flip Metropolis algorithm Monte Carlo &lt;a href=&quot;https://arxiv.org/abs/2001.09268&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:2001.09268&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The definition I have been using is: a Markov process is ergodic if any state &lt;span class=&quot;math-container&quot;&gt;$x'$&lt;/span&gt; can be reached from any state &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; in a finite number of steps. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore, if the number of steps required diverges rapidly with system size, the simulation has lost ergodicity. Is that a correct interpretation? Are there competing definitions? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Ideally I would like to get a citeable source that that I can use to defend my definition. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-11-20T22:48:38.263" LastActivityDate="2020-11-20T22:48:38.263" Title="What is the definition of ergodicity in Monte Carlo?" Tags="|reference-request|monte-carlo|ergodicity|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="130" PostTypeId="2" ParentId="123" CreationDate="2020-05-01T02:37:37.037" Score="14" Body="&lt;p&gt;Thomas has listed some great resources. Let me add some more, mostly materials science-related ones:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;NOMAD has regular workshops, &quot;Hands-on DFT and beyond&quot;, and the recordings from 2017, Berlin are uploaded to Youtube: &lt;a href=&quot;https://www.youtube.com/playlist?list=PLbgFiRV2JFy-VQ3D6cJjn5jkXmAsjQPiT&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/playlist?list=PLbgFiRV2JFy-VQ3D6cJjn5jkXmAsjQPiT&lt;/a&gt;&#xA;Slides of the more recent workshops can be found&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Barcelona (2019): &lt;a href=&quot;https://th.fhi-berlin.mpg.de/meetings/dft-workshop-2019/index.php?n=Meeting.Program&quot; rel=&quot;noreferrer&quot;&gt;https://th.fhi-berlin.mpg.de/meetings/dft-workshop-2019/index.php?n=Meeting.Program&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Peking (2018): &lt;a href=&quot;https://th.fhi-berlin.mpg.de/sitesub/meetings/dft-workshop-2018/index.php?n=Meeting.Program&quot; rel=&quot;noreferrer&quot;&gt;https://th.fhi-berlin.mpg.de/sitesub/meetings/dft-workshop-2018/index.php?n=Meeting.Program&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Kieron Burke has several good links on his lab page, including a CECAM lecture series from 2017, &quot;Teaching the Theory in Density Functional Theory&quot;  (&lt;a href=&quot;https://www.youtube.com/channel/UCfLssAro7SMxgaeKTNFFeeA/feed&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/channel/UCfLssAro7SMxgaeKTNFFeeA/feed&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Burke group page: &lt;a href=&quot;https://dft.uci.edu/learnDFT.php&quot; rel=&quot;noreferrer&quot;&gt;https://dft.uci.edu/learnDFT.php&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="91" LastActivityDate="2020-05-01T02:37:37.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="131" PostTypeId="1" CreationDate="2020-05-01T02:54:06.483" Score="27" ViewCount="195" Body="&lt;p&gt;In quantum chemistry, coupled-cluster methods, especially CCSD(T), with complete basis set extrapolation are often considered a &quot;gold-standard&quot; for closed-shell molecules. This means that we consider them as accurate as experimental results. While there are some debates about whether if we should consider them gold-standards, that is beside the point.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is if there is any similar method when we study periodic (1D-3D) materials? Should we \ can we consider eg quantum MC methods such?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Edit:&#xA;As it was pointed out in the comments, different properties require different methods, scale, etc. For simplicity I would like to limit the question to ground state energy. &lt;/p&gt;&#xA;" OwnerUserId="91" LastEditorUserId="5" LastEditDate="2020-05-06T04:17:49.923" LastActivityDate="2020-05-08T04:49:18.853" Title="Is there a &quot;gold standard&quot; method in materials modeling for obtaining ground state energy?" Tags="|quantum-monte-carlo|coupled-cluster|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="132" PostTypeId="1" AcceptedAnswerId="148" CreationDate="2020-05-01T03:09:47.573" Score="17" ViewCount="1308" Body="&lt;p&gt;I am looking for computational tools that can be used to automatize the generation surface slab models of latices of oxides, layered oxides, perovskites etc. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have found a promising Python package, ASE (Atomic Simulation Environment, &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/index.html&lt;/a&gt;), however, going through their examples ASE seems to be designed for simple systems, like metal lattices. Maybe I am wrong, but cutting perovskites cells for slabs through given atoms seems to be a difficult task with &lt;em&gt;ase.lattice&lt;/em&gt;.      &lt;/p&gt;&#xA;" OwnerUserId="91" LastEditorUserId="88" LastEditDate="2020-08-05T21:28:01.977" LastActivityDate="2020-08-05T21:28:01.977" Title="Computational tools for automatic creation of surface slab models of complex systems" Tags="|software|surfaces|atomic-simulation-environment|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="133" PostTypeId="2" ParentId="3" CreationDate="2020-05-01T03:35:35.893" Score="12" Body="&lt;p&gt;The answer in part is that not all the elements up through &lt;span class=&quot;math-container&quot;&gt;$\ce{Xe}$&lt;/span&gt; have (or had until fairly recently) a nonrelativistic correlation consistent basis set. Specifically, the alkali and alkaline earth elements (columns 1 and 2 of the periodic table) have been much slower to get nonrelativistic basis sets. The cc-pVnZ basis sets for &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}, \text{ }\ce{Be}, \text{ }\ce{Na}, \text{ and } \ce{Mg}$&lt;/span&gt; were only published in 2011.&lt;sup&gt;[1]&lt;/sup&gt; As you mentioned, &lt;span class=&quot;math-container&quot;&gt;$\ce{K}$&lt;/span&gt; was very recent, but &lt;span class=&quot;math-container&quot;&gt;$\ce{Ca}$&lt;/span&gt; only got cc-pVnZ basis sets in 2002.&lt;sup&gt;[2]&lt;/sup&gt; Neither &lt;span class=&quot;math-container&quot;&gt;$\ce{Rb}$&lt;/span&gt; nor &lt;span class=&quot;math-container&quot;&gt;$\ce{Sr}$&lt;/span&gt; have a nonrelativistic cc-basis set. This discrepancy was mentioned in a recent article&lt;sup&gt;[3]&lt;/sup&gt; that defined relativistic cc-basis for the alkali and alkaline earth metals, it was not further explained.&lt;/p&gt;&#xA;&lt;p&gt;As to why these took so long, it may just have been a lack of interest in these atoms. Both the p-block and transition metal elements are widely studied in chemistry, but the alkali and alkaline earth metals have generally not been as studied (at least, not in contexts requiring insight from electronic structure theory). The previously discussed &lt;span class=&quot;math-container&quot;&gt;$\ce{Ca}$&lt;/span&gt; basis was made specifically so they could better characterize the potential energy surface of a compound that had seen limited experimental or theoretical interest. So it doesn't seem to be due to any inherent difficulty in making basis sets for these atoms. Rather they seemed to just hold off until there enough potential applications to warrant it.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;p&gt;[1] Prascher, B.P., Woon, D.E., Peterson, K.A. et al. Gaussian basis sets for use in correlated molecular calculations. VII. Valence, core-valence, and scalar relativistic basis sets for Li, Be, Na, and Mg. &lt;em&gt;Theor Chem Acc&lt;/em&gt; 128, 69–82 (&lt;strong&gt;2011&lt;/strong&gt;). &lt;a href=&quot;https://doi.org/10.1007/s00214-010-0764-0&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1007/s00214-010-0764-0&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] Koput, J. &amp;amp; Peterson K.A. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2002&lt;/strong&gt;, &lt;em&gt;106&lt;/em&gt;, 41, 9595-9599 &lt;a href=&quot;https://doi.org/10.1021/jp026283u&quot; rel=&quot;noreferrer&quot;&gt;DOI:10.1021/jp026283u&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[3] Hill, J.G. &amp;amp;  Peterson K.A. Gaussian basis sets for use in correlated molecular calculations. XI. Pseudopotential-based and all-electron relativistic basis sets for alkali metal (K–Fr) and alkaline earth (Ca–Ra) elements&#xA;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; 147, 244106 (&lt;strong&gt;2017&lt;/strong&gt;); &lt;a href=&quot;https://doi.org/10.1063/1.5010587&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1063/1.5010587&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-01T03:35:35.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="134" PostTypeId="5" CreationDate="2020-05-01T03:42:30.497" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-01T03:42:30.497" LastActivityDate="2020-05-01T03:42:30.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="135" PostTypeId="4" CreationDate="2020-05-01T03:42:30.497" Score="0" Body="For questions related to Monte Carlo methods, which solve deterministic numerical problems via a probabilistic sampling approach." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-07T08:15:02.317" LastActivityDate="2020-05-07T08:15:02.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="136" PostTypeId="1" CreationDate="2020-05-01T03:47:06.283" Score="33" ViewCount="495" Body="&lt;p&gt;&lt;a href=&quot;https://or.stackexchange.com/&quot;&gt;Operations Research&lt;/a&gt; is a field of mathematics in which &lt;strong&gt;optimal or near-optimal solutions are sought for complicated problems.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the modeling of materials, we often optimize Ising models, in which the discrete variables on &lt;span class=&quot;math-container&quot;&gt;$\{-1,1\}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\{0,1\}$&lt;/span&gt; represent&#xA;&lt;em&gt;&lt;strong&gt;spin-up&lt;/strong&gt;&lt;/em&gt; particles (&lt;span class=&quot;math-container&quot;&gt;$\,\uparrow\,$&lt;/span&gt;) and &lt;em&gt;&lt;strong&gt;spin-down&lt;/strong&gt;&lt;/em&gt; particles (&lt;span class=&quot;math-container&quot;&gt;$\,\downarrow\,$&lt;/span&gt;), and we seek the optimal configuration of spins that minimizes the energy (&lt;em&gt;i.e.&lt;/em&gt; the ground state of the system). The lowest-energy configuration can vary greatly, depending on the couplings between the spins, and this can give rise to different types of &lt;strong&gt;magnetism&lt;/strong&gt; in the materials, such as &lt;em&gt;ferromagnetism&lt;/em&gt;: &lt;img src=&quot;https://i.stack.imgur.com/bBIor.png&quot; width=&quot;20&quot;&gt;, &lt;em&gt;anti-ferromagnetism&lt;/em&gt;:&#xA;&lt;img src=&quot;https://i.stack.imgur.com/MnVB1.png&quot; width=&quot;30&quot;&gt;, or one of &lt;em&gt;many&lt;/em&gt; other types of &lt;em&gt;phases&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;2001&lt;/strong&gt; book &lt;a href=&quot;http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.382.8505&amp;amp;rep=rep1&amp;amp;type=pdf&quot; rel=&quot;noreferrer&quot;&gt;Optimization Algorithms in Physics&lt;/a&gt; by &lt;a href=&quot;https://scholar.google.com/citations?user=bNlwNPYAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;Alex Hartmann&lt;/a&gt; and &lt;a href=&quot;https://scholar.google.com/citations?user=7koADWYAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;Heiko Rieger&lt;/a&gt; claims in the introduction to be a &amp;quot;unique&amp;quot; book in cross-pollinating algorithms that are popular in operations research, with algorithms and applications in physics. For example, they mention &lt;em&gt;&lt;strong&gt;simulated annealing&lt;/strong&gt;&lt;/em&gt;, which was born in the physics community, but is now used by mathematicians to optimize non-physics problems such as optimizations in graph-cut problems or in finance, and &lt;em&gt;&lt;strong&gt;parallel tempering&lt;/strong&gt;&lt;/em&gt; which was introduced in a physics journal in 1986 and implemented in GROMACS, LAMMPS, CHARMM, and AMBER (materials modeling software), but was used for &amp;quot;maximum likelihood&amp;quot; problems by statistician C.J. Geyer &lt;a href=&quot;http://www.stat.umn.edu/geyer/thesis/&quot; rel=&quot;noreferrer&quot;&gt;in 1991&lt;/a&gt;. However, they also mention the &amp;quot;blossom algorithm&amp;quot; of computer scientist Jack Edmonds, which helps to solve Ising problems very efficiently when restricted to certain scenarios with &lt;em&gt;planar&lt;/em&gt; spin configurations.&lt;/p&gt;&#xA;&lt;p&gt;While this book might indeed have been the first book to bring so much from the operations research community into the materials modeling context, and &lt;em&gt;vice versa&lt;/em&gt;, most of the references are from much earlier. This got me curious to find out, &lt;em&gt;when did the separately growing operations research community start adopting Ising-optimization methods from the physics community and vice versa?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I found a book from one decade earlier, called &amp;quot;&lt;a href=&quot;https://books.google.ca/books?id=aWWSbE-eSwEC&amp;amp;source=gbs_book_similarbooks&quot; rel=&quot;noreferrer&quot;&gt;Spin glasses and related problems&lt;/a&gt;&amp;quot; (&lt;strong&gt;1991&lt;/strong&gt;).&lt;br&gt;&#xA;But then I found proceedings of a colloquium on &lt;a href=&quot;https://books.google.ca/books?id=s6zvAAAAMAAJ&amp;amp;source=gbs_similarbooks&quot; rel=&quot;noreferrer&quot;&gt;Spin Glasses, Optimization and Neural Networks&lt;/a&gt; (&lt;strong&gt;1986&lt;/strong&gt;).&lt;br&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;However the mathematical optimization literature about developments such as Jack Edmond's blossom algorithm (&lt;strong&gt;1961&lt;/strong&gt;), makes no mention of Ising models (which &lt;a href=&quot;https://link.springer.com/article/10.1007%2FBF02980577&quot; rel=&quot;noreferrer&quot;&gt;physicists were trying to optimize since the &lt;strong&gt;1920s&lt;/strong&gt;&lt;/a&gt;) or simulated annealing type algorithms which Metropolis &lt;em&gt;et al.&lt;/em&gt; published in &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1699114&quot; rel=&quot;noreferrer&quot;&gt;Journal of Chemical Physics in &lt;strong&gt;1953&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Between &lt;em&gt;circa&lt;/em&gt; 1961 and 1986, these two communities somehow learned about each other, and I am curious to know which paper or conference might get credit for it?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-24T22:47:36.043" LastActivityDate="2023-12-07T02:07:05.910" Title="Where/when did the fields of Operations Research and Spin Physics or Molecular Dynamics begin to cross-pollinate?" Tags="|condensed-matter|model-hamiltonians|optimization|ising-model|history|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="137" PostTypeId="2" ParentId="49" CreationDate="2020-05-01T03:54:13.527" Score="14" Body="&lt;p&gt;A 2015 paper &lt;sup&gt;[1]&lt;/sup&gt; looked at the ability to predict activity cliffs structurally using docking models that could combine experimental and computational information about the conformation of the receptor and/or binding molecule. They found that they could achieve reasonable prediction accuracy and planned to implement further improvements to make a more robust predictor model.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1] J. Husby, G. Bottegoni, Irina Kufareva, Ruben Abagyan, Andrea Cavalli, &lt;em&gt;J. Chem. Inf. Model.&lt;/em&gt; &lt;strong&gt;2015&lt;/strong&gt;, 55, 5, 1062-1076 &lt;a href=&quot;https://doi.org/10.1021/ci500742b&quot; rel=&quot;noreferrer&quot;&gt;DOI:10.1021/ci500742b&lt;/a&gt; (Also freely available &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4553268/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-05-01T03:54:13.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="138" PostTypeId="2" ParentId="111" CreationDate="2020-05-01T04:22:55.783" Score="10" Body="&lt;p&gt;The chemical potential in VASP or any other computational chemistry software is calculated based on the theory of chemical potential relation to Helmholtz energy functional as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu_{i} = \Bigg(\frac{\partial F(V,T,N_{1},N_{2},...,N_{i}...,N_{n})}{\partial N_{i}}\Bigg)_{V,T,N_{j \neq i}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You can approximate the above equation up to first order as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu_{i} \simeq F(V,T,N_{i}+1,N_{j \neq i}) - F(V,T,N_{i},N_{j \neq i})$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here we omitted the terms of &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}\Big( \frac{\partial^{2} F}{\partial N_{i}^{2}} \Big)$&lt;/span&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I call &lt;span class=&quot;math-container&quot;&gt;$F(V,T,N_{i}+1,N_{j \neq i}) - F(V,T,N_{i},N_{j \neq i}) = \Delta F_{N_{i} \rightarrow N_{i}+1}$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, you have:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu_{i} = \Delta F_{N_{i} \rightarrow N_{i}+1} = \mu_{\text{XC}}^{i}+\mu_{\text{ideal}}^{i}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\mu^{i}_{\text{ideal}}$&lt;/span&gt; is the chemical potential of the ideal gas and &lt;span class=&quot;math-container&quot;&gt;$\mu^{i}_{\text{XC}}$&lt;/span&gt; is the chemical potential of exchange-correlation. The ideal gas chemical potential is trivial:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu^{i}_{\text{ideal}} = -k_{B}T\ln{\Bigg( \frac{V}{\Lambda^{3} (N_{i}+1)}\Bigg)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt; is the Broglie wavelength: &lt;span class=&quot;math-container&quot;&gt;$\Lambda = \sqrt{\frac{2\pi\hbar^{2}}{mk_{B}T}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The exchange-correlation chemical potential is calculated as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu^{i}_{\text{XC}} = -k_{B}T \ln{\Bigg ( \frac{1}{V} \frac{\int \exp{\Big(-\frac{U(\mathbf{r}^{N_{i}+1})}{k_{B}T}\Big)} d^{3}\mathbf{r}^{N_{i}+1}}{\int \exp{\Big(-\frac{U(\mathbf{r}^{N_{i}})}{k_{B}T}\Big)} d^{3}\mathbf{r}^{N_{i}}} \Bigg )}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Or in ensemble form:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mu^{i}_{\text{XC}} = -k_{B}T \ln{\Bigg ( \frac{1}{V} \Bigg \langle \int \exp{\Big( -\frac{\Delta U_{N_{i} \rightarrow N_{i}+1}}{k_{B}T} \Big)} d^{3}\mathbf{r}^{N_{i}+1} \Bigg \rangle \Bigg )}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-01T04:22:55.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="139" PostTypeId="1" AcceptedAnswerId="1288" CreationDate="2020-05-01T06:26:49.233" Score="23" ViewCount="1272" Body="&lt;p&gt;I've often had this problem: I have a model that has a phase transition in it, but I don't know what universality class it falls into or what the universality class is &lt;em&gt;called&lt;/em&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there anywhere on the web where there is a big list of all the classes and examples of each (hopefully with critical exponents as well)?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;For example:&lt;/strong&gt;&lt;br&gt;&#xA;Name: 2D Ising Model&lt;br&gt;&#xA;Symmetry: Z&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;br&gt;&#xA;Dimension: 2&lt;br&gt;&#xA;Other examples:  liquid-gas transition, etc&lt;br&gt;&#xA;Critical exponents: ...   &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-06-12T23:21:32.547" LastActivityDate="2020-07-27T17:30:18.027" Title="Is there a list of all universality classes for phase transitions with examples of each?" Tags="|reference-request|condensed-matter|model-hamiltonians|databases|phase-transitions|" AnswerCount="2" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="140" PostTypeId="1" AcceptedAnswerId="145" CreationDate="2020-05-01T06:59:29.737" Score="14" ViewCount="123" Body="&lt;p&gt;Is there any first principle method available to study phase transitions at the critical region for &lt;a href=&quot;https://en.wikipedia.org/wiki/Ferromagnetism&quot; rel=&quot;noreferrer&quot;&gt;ferromagnetism&lt;/a&gt; (FM) or &lt;a href=&quot;https://en.wikipedia.org/wiki/Antiferromagnetism&quot; rel=&quot;noreferrer&quot;&gt;antiferromagnetism&lt;/a&gt; (AFM)?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-01T19:50:00.940" LastActivityDate="2020-05-01T19:50:00.940" Title="How to model phase transitions at critical regions in a magnetic system?" Tags="|electronic-structure|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="141" PostTypeId="1" CreationDate="2020-05-01T08:31:46.717" Score="20" ViewCount="181" Body="&lt;p&gt;What type of education is appropriate for people interested in Materials Modeling?  Obviously, the more education, the better.  I'm sure a PhD in physics, another in chemistry, topped off with one in structural engineering will help.  But most people will not choose to pursue that much education.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is a good baseline education for people interested in Materials Modeling?&lt;/p&gt;&#xA;" OwnerUserId="174" LastEditorUserId="7" LastEditDate="2021-07-09T17:09:23.407" LastActivityDate="2021-07-09T17:09:23.407" Title="What type of education is appropriate for people interested in Materials Modeling?" Tags="|reference-request|education|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="142" PostTypeId="1" AcceptedAnswerId="146" CreationDate="2020-05-01T11:26:09.213" Score="24" ViewCount="2089" Body="&lt;p&gt;I remember that 20+ years ago we used a program called Powder Cell to calculate diffraction patterns from models of materials (for example, to compare it with experimental data from powder diffraction).&#xA;I just fired this program up under wine and it still works:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/enoJ6.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/enoJ6.png&quot; alt=&quot;Powder Cell screenshot&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are modern alternatives?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note: this program takes description of a unit cell (atoms and unit cell parameters) and produces indexed pattern.&#xA;This is different than using the Debye scattering formula to calculate diffraction pattern of any set of atoms, but without Miller indices.  &lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="88" LastEditDate="2020-07-30T20:38:59.430" LastActivityDate="2022-12-09T15:52:36.967" Title="How to calculate diffraction pattern from a model of unit cell?" Tags="|software|vesta|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="143" PostTypeId="2" ParentId="141" CreationDate="2020-05-01T11:41:50.610" Score="19" Body="&lt;p&gt;As evident from the name, Materials Modelling (or Computational Materials Science as it is sometimes called) lies at the intersection of materials science and computational engineering. To answer this question, the level of education required depends entirely on what one intends to do with materials modelling.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Materials science is quite interdisciplinary, and it is possible to work on different aspects of materials modelling (like the application of existing models/software to new materials/problems, building new models/software etc.). If one is interested in doing research in the field of materials modelling, typically, it is possible to start participating in research while pursuing an undergraduate degree in a related discipline. So, the undergraduate major could be materials science/engineering itself, physics, chemistry, chemical engineering, mechanical engineering, mathematics, computer science, the list cannot be exhaustive. Also, one can work on a materials modelling problem for their PhD while being officially affiliated to any of these disciplines. So, one often pursues some form of education while already working with materials modelling, and then continues to work in the field.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If the question intended to know of any prerequisites to start doing materials modelling, then the answer could be some understanding of materials behaviour, and the ability to use computational tools to solve problems (which can also be learnt as one starts). The book &lt;a href=&quot;https://www.cambridge.org/in/academic/subjects/engineering/materials-science/introduction-computational-materials-science-fundamentals-applications?format=HB&quot; rel=&quot;noreferrer&quot;&gt;Introduction to Computational Materials Science&lt;/a&gt; by Prof. Richard LeSar is an accessible starting point.&lt;/p&gt;&#xA;" OwnerUserId="22" LastActivityDate="2020-05-01T11:41:50.610" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="144" PostTypeId="2" ParentId="141" CreationDate="2020-05-01T13:50:20.087" Score="15" Body="&lt;p&gt;I think that it is not the education &lt;em&gt;per se&lt;/em&gt; (a Masters or PhD in Physics or Chemistry, for example), but the set of disciplines you take that will help you to better understand and work in the Materials Modeling area.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Courses like &lt;a href=&quot;https://en.wikipedia.org/wiki/Classical_mechanics&quot; rel=&quot;noreferrer&quot;&gt;Classical Mechanics&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Electromagnetism&quot; rel=&quot;noreferrer&quot;&gt;Electromagnetism&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_mechanics&quot; rel=&quot;noreferrer&quot;&gt;Quantum Mechanics&lt;/a&gt;,  &lt;a href=&quot;https://en.wikipedia.org/wiki/Statistical_mechanics&quot; rel=&quot;noreferrer&quot;&gt;Statistical Mechanics&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Solid_state_physics&quot; rel=&quot;noreferrer&quot;&gt;Solid State Physics&lt;/a&gt; are fundamental.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also, courses in programming languages are helpful.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-01T14:39:05.173" LastActivityDate="2020-05-01T14:39:05.173" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="145" PostTypeId="2" ParentId="140" CreationDate="2020-05-01T14:43:49.653" Score="4" Body="&lt;p&gt;Yes, this topic is pretty mature I believe to FM and AFM by using quantum mechanics and specifically density functional theory. More specifically, the mean-field theory and Ising directions are essential to calculate phase transition temperature in ferromagnetic or anti-ferromagnetic materials. I'm not going to go through all the mathematical details here, which is beyond the scope of this SE I believe, but you could find the more solid theoretical background of this topic from outstanding work of &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0305-4608/15/6/018/pdf&quot; rel=&quot;noreferrer&quot;&gt;Gyorffy et. al.&lt;/a&gt; that described how one could construct a self-consistent model based on Pauli equation and derive the magnetic momentum field from first-principle calculations. &lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-01T14:43:49.653" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="146" PostTypeId="2" ParentId="142" CreationDate="2020-05-01T14:50:20.840" Score="20" Body="&lt;p&gt;Perhaps the easiest solution is to use &lt;a href=&quot;http://jp-minerals.org/vesta/en/&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt;, which can read in a CIF (and many other crystalline structure formats) and produce a powder diffraction pattern (&quot;Utilities&quot; &gt; &quot;Powder Diffraction Pattern&quot;). Behind the scenes, VESTA is using &lt;a href=&quot;http://fujioizumi.verse.jp/download/download_Eng.html&quot; rel=&quot;noreferrer&quot;&gt;RIETAN-FP&lt;/a&gt; to do the calculation, which has a standalone version to download if you wanted.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/qAExS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qAExS.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&#xA;Another way you could do this, especially for those who have to do this for many structures and don't mind using Python, is with the &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.diffraction.xrd.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;xrd module&lt;/code&gt;&lt;/a&gt; in &lt;a href=&quot;https://pymatgen.org/index.html&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt;, which provides a bit more flexibility. This could be done as shown below:&lt;/p&gt;&#xA;&#xA;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import pymatgen as pm&#xA;from pymatgen.analysis.diffraction.xrd import XRDCalculator&#xA;p = '/path/to/my.cif' #path to CIF&#xA;structure = pm.Structure.from_file(p) #read in structure&#xA;xrd = XRDCalculator() #initiate XRD calculator (can specify various options here)&#xA;pattern = xrd.get_pattern(structure)&#xA;print(pattern)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-01T15:59:54.223" LastActivityDate="2020-05-01T15:59:54.223" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="147" PostTypeId="2" ParentId="142" CreationDate="2020-05-01T14:50:39.617" Score="6" Body="&lt;p&gt;You are looking for the calculation of &lt;a href=&quot;https://en.wikipedia.org/wiki/Structure_factor&quot; rel=&quot;noreferrer&quot;&gt;structure factor&lt;/a&gt;. Basically the X-Ray spectra could be calculated as Fourier transform of your crystal lattice and the Intensity (&lt;span class=&quot;math-container&quot;&gt;$I(\mathbf{q})$&lt;/span&gt;) could be estimated as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$I(\mathbf{q}) = f^{2} \sum_{i=1}^{N} \exp{(-i \mathbf{q} \cdot \mathbf{R}_{i})}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Basically, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; is the scattering vector and the X-Ray spectra would be a 3D field in Fourier space but because you have other knowledge about your crystal structure, you could just plot &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; versus &lt;span class=&quot;math-container&quot;&gt;$2\theta$&lt;/span&gt; the angle of scattering vector and you would get your X-Ray spectra.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-01T14:50:39.617" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="148" PostTypeId="2" ParentId="132" CreationDate="2020-05-01T15:55:30.043" Score="15" Body="&lt;p&gt;I &lt;em&gt;highly&lt;/em&gt; recommend using &lt;code&gt;pymatgen&lt;/code&gt; for this.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I coded a surface slab generator for Avogadro and in addition to being slow (since it generates a supercell before carving up the slab) it has a variety of weird hard-to-debug issues.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There's a nice example of cutting &lt;span class=&quot;math-container&quot;&gt;$\ce{LiFePO4}$&lt;/span&gt; &lt;a href=&quot;https://matgenb.materialsvirtuallab.org/2017/04/03/Slab-generation-and-Wulff-shape.html&quot; rel=&quot;noreferrer&quot;&gt;online from materialsvirtuallab.org&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;# Import the neccesary tools to generate surfaces&#xA;from pymatgen.core.surface import SlabGenerator, generate_all_slabs, Structure, Lattice&#xA;# .. [ other parts of the page omitted ]&#xA;# Lets try something a little more complicated, say LiFePO4&#xA;from pymatgen.util.testing import PymatgenTest&#xA;# Get the LiFePO4 structure&#xA;LiFePO4 = PymatgenTest.get_structure(&quot;LiFePO4&quot;) &#xA;&#xA;# Let's add some oxidation states to LiFePO4, this will be &#xA;# important when we want to take surface polarity into consideration&#xA;LiFePO4.add_oxidation_state_by_element({&quot;Fe&quot;: 2, &quot;Li&quot;: 1, &quot;P&quot;: 5, &quot;O&quot;: -2})&#xA;slabgen = SlabGenerator(LiFePO4, (0,0,1), 10, 10)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;I've done a variety of slabs with &lt;code&gt;pymatgen&lt;/code&gt; and they look fairly good. The core algorithm was published: &quot;Efficient creation and convergence of surface slabs&quot; &lt;a href=&quot;http://dx.doi.org/10.1016/j.susc.2013.05.016&quot; rel=&quot;noreferrer&quot;&gt;Surface Science 617 (2013) 53–59&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The method is fairly widely used, including non-trivial results:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1038/sdata.2016.80&quot; rel=&quot;noreferrer&quot;&gt;Surface energies of elemental crystals&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1016/j.susc.2017.11.007&quot; rel=&quot;noreferrer&quot;&gt;A topological screening heuristic for low-energy, high-index surfaces&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-01T15:55:30.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="149" PostTypeId="2" ParentId="70" CreationDate="2020-05-01T16:49:32.633" Score="23" Body="&lt;p&gt;Another thing not mentioned yet is that there are, broadly speaking, two camps of codes: those that are primarily meant for periodic (often but not exclusively plane-wave) DFT (VASP, Quantum Espresso, etc.), and those that are primarily meant for finite systems like molecules (e.g. Gaussian, ORCA). Also, there are different algorithms in each package, some of which may better suit a given user. There's also a number of packages recently that are meant to be open-source (or at least free) alternatives of paid packages that have dominated the field.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-01T16:49:32.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="150" PostTypeId="5" CreationDate="2020-05-01T16:57:40.157" Score="0" Body="&lt;p&gt;In linear algebra, a basis B is a set of vectors in a vector space V for which every element of V can be written as a linear combination of elements of B. This concept is used in quantum electronic structure theory to express the wavefunction as a linear combination of simpler functions.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The choice of functions to use can vary based on the application, with Gaussians basis sets being useful for studying molecular/localized interactions and plane wave basis sets seeing use for studying extended structures and materials. While the functions used can be optimized on fly for a given system, it is more often the case that predetermined functions are used that have been optimized for use with particular constituent atoms or moieties. These are available both within most electronic structure programs, as well as in online repositories (e.g. &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Basis Set Exchange&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the language of materials modeling, a complete basis is the analog of the mathematical definition of a basis. For materials and molecules, a complete basis would need to be effectively infinite in size, so in practice finite sized &quot;basis sets&quot; are used which only span a subspace of the whole possible space of wavefunction solutions. The quality of the resulting wavefunction is dependent on how large/close to complete the basis set is.  &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-01T18:26:49.933" LastActivityDate="2020-05-01T18:26:49.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="151" PostTypeId="4" CreationDate="2020-05-01T16:57:40.157" Score="0" Body="For questions about the usage and construction of electronic structure basis sets. " OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-01T18:26:54.057" LastActivityDate="2020-05-01T18:26:54.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="152" PostTypeId="5" CreationDate="2020-05-01T17:20:00.560" Score="0" Body="&lt;p&gt;The Vienna &lt;em&gt;ab initio&lt;/em&gt; Simulation Package (VASP) is a computer program for atomic scale materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics, from first principles.&lt;/p&gt;&#xA;&lt;p&gt;VASP computes an approximate solution to the many-body Schrödinger equation, either within density functional theory (DFT), solving the Kohn-Sham equations, or within the Hartree-Fock (HF) approximation, solving the Roothaan equations. Hybrid functionals that mix the Hartree-Fock approach with density functional theory are implemented as well. Furthermore, Green’s functions methods (GW quasiparticles, and ACFDT-RPA) and many-body perturbation theory (2nd-order Møller-Plesset) are available in VASP.&lt;/p&gt;&#xA;&lt;p&gt;In VASP, central quantities, like the one-electron orbitals, the electronic charge density, and the local potential are expressed in plane wave basis sets. The interactions between the electrons and ions are described using norm-conserving or ultrasoft pseudopotentials, or the projector-augmented-wave method.&lt;/p&gt;&#xA;&lt;p&gt;To determine the electronic groundstate, VASP makes use of efficient iterative matrix diagonalisation techniques, like the residual minimisation method with direct inversion of the iterative subspace (RMM-DIIS) or blocked Davidson algorithms. These are coupled to highly efficient Broyden and Pulay density mixing schemes to speed up the self-consistency cycle.&lt;/p&gt;&#xA;&lt;p&gt;Description source: &lt;a href=&quot;https://www.vasp.at/about/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/about/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2023-02-15T14:13:20.807" LastActivityDate="2023-02-15T14:13:20.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="153" PostTypeId="4" CreationDate="2020-05-01T17:20:00.560" Score="0" Body="Questions about or related to the Vienna ab-initio Simulation Package (VASP)." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2023-02-15T14:12:51.930" LastActivityDate="2023-02-15T14:12:51.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="154" PostTypeId="1" AcceptedAnswerId="1470" CreationDate="2020-05-01T18:15:27.453" Score="18" ViewCount="589" Body="&lt;p&gt;When modeling solid-state materials and particularly semiconductors, one must go beyond LDA and GGA. One alternative is to use hybrid functionals or the &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt; method. However, this can be very prohibitive for certain systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A popular alternative is to use the Tran-Blaha modified Becke-Johnson potential&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.226401&quot; rel=&quot;noreferrer&quot;&gt; [Phys. Rev. Lett. &lt;strong&gt;102&lt;/strong&gt;, 226401 (2009)]&lt;/a&gt;, &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\mathbf{v}_{x,\sigma}^{TB-mBJ}(\textbf{r})=c \mathbf{v}_{x,\sigma}^{BR}(\textbf{r}) + (3c-2)\frac{1}{\pi}\sqrt{\frac{5}{12}}\sqrt{\frac{2t_\sigma(\textbf{r})}{\rho_\sigma(\textbf{r})}}&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\rho_\sigma$&lt;/span&gt; is the electronic density, &lt;span class=&quot;math-container&quot;&gt;$t_\sigma$&lt;/span&gt; is the kinetic energy density and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_{x,\sigma}^{BR}(\textbf{r})$&lt;/span&gt; is the original Becke-Roussel potential.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The authors propose the TB-mBJ (aka TB09) potential and implement it in Wien2K,a code based on the Augmented Planewave + local orbitals [APW+lo] method. Wien2K is an &quot;all electron code&quot;. Over the years, most papers I have read that &lt;em&gt;use&lt;/em&gt; the TB&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How trustworthy is TB-mBJ (a.k.a. TB09) and how is it seen by the community &lt;em&gt;today&lt;/em&gt;? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Does it yield accurate results with pseudo-potential codes like Quantum ESPRESSO or VASP? Are there any references that study the performance of TB-mBJ accross codes and basis sets?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="52" LastEditDate="2020-05-03T00:41:45.393" LastActivityDate="2020-07-05T23:02:44.293" Title="How trustworthy is the Tran-Blaha modified Becke-Johnson potential and how does it perform across basis sets?" Tags="|density-functional-theory|basis-sets|" AnswerCount="3" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="155" PostTypeId="2" ParentId="17" CreationDate="2020-05-01T18:43:46.007" Score="9" Body="&lt;p&gt;Here is a list of molecular/chemistry/materials modeling software packages designed to run on classical computers:&#xA;VASP, MOLCAS, CFOUR, GAUSSIAN, LAMMPS, CP2K, DIRAC, Turbomole, MOLPRO, ORCA, MRCC, ADF, PySCF, PSI4, DALTON, QuantumEspresso, QChem, CASTEP, CPMD, ABINT, DFTB+, ABAQUS, OpenBabel, Amber, CHARMM, GAMESS, Gromacs, NAMD, Omnia, OpenCalphad, OpenMM, AVOGADRO, DFTK, NECI, Newton-X and pyquante2.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is a list of molecular/chemistry/materials software packages designed to run on quantum computers:&#xA;CUSP, FermLib, Microsoft QDK, NWChem, OpenQEMIST, QISkit, OpenFermion, Orquestra, and PennyLane.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There may be others - feel free to add.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-01T19:00:51.073" LastActivityDate="2020-05-01T19:00:51.073" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="156" PostTypeId="1" AcceptedAnswerId="161" CreationDate="2020-05-01T18:51:09.207" Score="23" ViewCount="965" Body="&lt;p&gt;I have only done quantum mechanical computations using non-periodic wavefunctions. I'd like to try to periodic-wavefunction density functional theory. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Quantum ESPRESSO seems like a good package because it's open-source. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Can some one help me get started by providing me some tips or an input file? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, I'd like to reproduce these calculation details:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The crystal structures of HC1 and HC2 were optimized using PBE-D2 as implemented in&#xA;  Quantum ESPRESSO. The plane- wave cutoff was 30 Ry, and the k-point&#xA;  meshes were 2 × 3 × 2 and 2 × 2 × 1 respectively, in accordance with&#xA;  the shapes of the unit cells&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-06-12T03:16:41.893" LastActivityDate="2020-06-12T03:16:41.893" Title="How to do periodic DFT calculations using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|periodic-system|space-groups|plane-waves|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="157" PostTypeId="1" AcceptedAnswerId="159" CreationDate="2020-05-01T18:55:25.920" Score="27" ViewCount="692" Body="&lt;p&gt;There are many open databases and projects that allow you to access computed crystal structures of experimentally known compounds, registered in the Inorganic Crystal Structure Database (ICSD). These structures are usually then studied using a given materials modeling method, e.g. DFT.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are there any methods and codes available to predict completely new materials, their crystal structures and properties with no experimental references? &lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-05-09T20:45:36.103" LastActivityDate="2020-06-29T01:19:03.903" Title="Available methods and codes for materials discovery / crystal structure prediction?" Tags="|density-functional-theory|reference-request|crystal-structure|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="158" PostTypeId="1" AcceptedAnswerId="900" CreationDate="2020-05-01T19:03:30.793" Score="17" ViewCount="425" Body="&lt;p&gt;When finding nuclear forces for the true electronic wavefunction, thanks to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hellmann%E2%80%93Feynman_theorem&quot; rel=&quot;noreferrer&quot;&gt;Hellmann-Feynman theorem&lt;/a&gt; we only need to consider explicit derivatives with respect to the nuclear coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;: &#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\frac{dE}{d\mathbf{R}}=\left\langle\Psi\left|\frac{dH}{d\mathbf{R}}\right|\Psi\right\rangle+E\frac{d}{d\mathbf{R}}\left\langle\Psi\left|\right.\Psi\right\rangle=\left\langle\Psi\left|\frac{dH}{d\mathbf{R}}\right|\Psi\right\rangle&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The 2nd term cancels as the overlap of the wavefunction with itself is constant (1 if normalized) and so the derivative is 0.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For approximate methods, this second term (the Pulay force or stress) does not generally go away, as the wavefunction is not an eigenfunction of the true Hamiltonian. For variational methods, these forces are said to go away in the limit of a complete basis. What is it about the complete basis limit that removes the Pulay forces for a variational method?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-01T19:09:47.383" LastActivityDate="2022-10-15T14:28:32.080" Title="How does a complete basis set remove Pulay forces/stress?" Tags="|basis-sets|stress-strain|variational-principle|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="159" PostTypeId="2" ParentId="157" CreationDate="2020-05-01T19:14:50.460" Score="22" Body="&lt;p&gt;Yes, there are! One early example that's still in use today is &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;noreferrer&quot;&gt;the Universal Structure Predictor: Evolutionary Xtallography (USPEX) method&lt;/a&gt;. You can find many &quot;success cases&quot; on their website if you're curious. The &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.1.063802&quot; rel=&quot;noreferrer&quot;&gt;First-Principles-Assisted Structure Solution (FPASS)&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.1.063802&quot; rel=&quot;noreferrer&quot;&gt;Prototype Electrostatic Ground States (PEGS)&lt;/a&gt; methods are a couple of other codes used for structure prediction. Then there are many that are specific to a given application area. For instance, to predict the structures of metal-organic frameworks from specified molecular building blocks, there is the &lt;a href=&quot;https://github.com/tobacco-mofs/tobacco_3.0&quot; rel=&quot;noreferrer&quot;&gt;Topologically Based Crystal Constructor (ToBaCCo)&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Each code out there works differently. Some try to use brute-force approaches while accounting for material-specific design principles. The lowest energy structure is then often take. You could imagine taking such structures from the &lt;a href=&quot;http://oqmd.org/&quot; rel=&quot;noreferrer&quot;&gt;Open Quantum Materials Database&lt;/a&gt;, for instance. Other methods use evolutionary algorithms, as summarized in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ar1001318&quot; rel=&quot;noreferrer&quot;&gt;this review&lt;/a&gt;. More recently, these crystal structure prediction algorithms are taking advantage of machine learning and artificial intelligence for the design and prediction of crystals with tailored properties for a given application of interest, such as &lt;a href=&quot;https://chemrxiv.org/articles/Inverse_Design_of_Nanoporous_Crystalline_Reticular_Materials_with_Deep_Generative_Models/12186681&quot; rel=&quot;noreferrer&quot;&gt;a material&lt;/a&gt; that can separate &lt;span class=&quot;math-container&quot;&gt;$\mathrm{CO}_{2}$&lt;/span&gt; from natural gas.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are several reviews on the topic you may be interested in: &lt;a href=&quot;https://pubs.rsc.org/en/content/ebook/978-1-78262-961-0&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9783527632831&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;, &lt;a href=&quot;https://link.springer.com/book/10.1007%2F978-3-319-05774-3&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-01T19:40:12.410" LastActivityDate="2020-05-01T19:40:12.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="160" PostTypeId="1" AcceptedAnswerId="489" CreationDate="2020-05-01T19:17:34.440" Score="16" ViewCount="307" Body="&lt;p&gt;In periodic systems plane-wave basis functions are often used. In a previous question on this site it was questioned if &lt;a href=&quot;https://materials.stackexchange.com/questions/68/are-plane-wave-basis-sets-reliable-for-modeling-adsorption-processes&quot;&gt;plane-wave basis-sets are reliable for modeling adsorption-processes&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The answer to that question was ultimately &quot;yes&quot; they are good and appropriate for adsorption process.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, Gaussian based wavefunction theories are still far ahead of plane-wave theories in key areas like excited-states. For example, it is not possible, as far as I know, to do plane-wave based &quot;configuration interaction&quot; calculations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Accurately calculating excited-states is important because molecular crystals have much different photonic properties. For example, molecular crystals can display aggregation induced emission, increased oscillator strengths and emission wavelength shifts. All very relevant and impossible to capture with the single molecule. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore, what are some of the methods to model excited-states in molecular crystals? &lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-05-09T20:44:02.727" LastActivityDate="2020-05-09T20:44:02.727" Title="What methods can be used to calculate excited-states in molecular crystals?" Tags="|basis-sets|ab-initio-calculations|excited-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="161" PostTypeId="2" ParentId="156" CreationDate="2020-05-01T19:25:16.727" Score="17" Body="&lt;p&gt;Unlike non-periodical DFT codes, Quantum ESPRESSO uses planewave basis sets and pseudopotentials. There are many ways of writing your input file, and it all depends on &lt;em&gt;what&lt;/em&gt; information you have or &lt;em&gt;what&lt;/em&gt; you want to learn. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is the skeleton of your input file: &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;===============================================================================&#xA;&#xA;&amp;amp;CONTROL&#xA;  ...&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ...&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;  ...&#xA;/&#xA;&#xA;[ &amp;amp;IONS&#xA;  ...&#xA; / ]&#xA;&#xA;[ &amp;amp;CELL&#xA;  ...&#xA; / ]&#xA;&#xA;ATOMIC_SPECIES&#xA; X  Mass_X  PseudoPot_X&#xA; Y  Mass_Y  PseudoPot_Y&#xA; Z  Mass_Z  PseudoPot_Z&#xA;&#xA;ATOMIC_POSITIONS { alat | bohr | crystal | angstrom | crystal_sg }&#xA;  X 0.0  0.0  0.0  {if_pos(1) if_pos(2) if_pos(3)}&#xA;  Y 0.5  0.0  0.0&#xA;  Z O.0  0.2  0.2&#xA;&#xA;K_POINTS { tpiba | automatic | crystal | gamma | tpiba_b | crystal_b | tpiba_c | crystal_c }&#xA;if (gamma)&#xA;   nothing to read&#xA;if (automatic)&#xA;   nk1, nk2, nk3, k1, k2, k3&#xA;if (not automatic)&#xA;   nks&#xA;   xk_x, xk_y, xk_z,  wk&#xA;if (tpipa_b or crystal_b in a 'bands' calculation) see Doc/brillouin_zones.pdf&#xA;&#xA;[ CELL_PARAMETERS { alat | bohr | angstrom }&#xA;   v1(1) v1(2) v1(3)&#xA;   v2(1) v2(2) v2(3)&#xA;   v3(1) v3(2) v3(3) ]&#xA;&#xA;[ OCCUPATIONS&#xA;   f_inp1(1)  f_inp1(2)  f_inp1(3) ... f_inp1(10)&#xA;   f_inp1(11) f_inp1(12) ... f_inp1(nbnd)&#xA; [ f_inp2(1)  f_inp2(2)  f_inp2(3) ... f_inp2(10)&#xA;   f_inp2(11) f_inp2(12) ... f_inp2(nbnd) ] ]&#xA;&#xA;[ CONSTRAINTS&#xA;   nconstr  { constr_tol }&#xA;   constr_type(.)   constr(1,.)   constr(2,.) [ constr(3,.)   constr(4,.) ] { constr_target(.) } ]&#xA;&#xA;[ ATOMIC_FORCES&#xA;   label_1 Fx(1) Fy(1) Fz(1)&#xA;   .....&#xA;   label_n Fx(n) Fy(n) Fz(n) ]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;To start off, you will be &quot;filling in the blanks&quot; with the information found &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, select &quot;relax&quot; to relax atomic positions within the unit cell. You will be able to define your structure by space group no., lattice constants &lt;span class=&quot;math-container&quot;&gt;$a,b,c$&lt;/span&gt;, or by the primitive vectors in &lt;code&gt;&amp;amp;CELL_PARAMETERS&lt;/code&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; card is the most important. This is where you will define your cell dimensions, your energy cutoff, any corrections such as &lt;code&gt;vdw_corr&lt;/code&gt; (e.g. Grimme-D2,D3) and you can call hybrid functionals &lt;code&gt;via input_dft&lt;/code&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Next, you will need to get your pseudopotentials. The Quantum ESPRESSO website has a library of pseudopotentials developed by Andrea Dal Corso. These are the default, plug-and-play pseudopotentials you can use instead of generating your own. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here are three places where you can get good pseudopotentials:&#xA;The PSLIBRARY by A. Dal Corso is &lt;a href=&quot;https://dalcorso.github.io/pslibrary/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. There you will find Ultrasoft and PAW pseudopotentials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Standard Solid State Pseudopotential library in MaterialsCloud is &lt;a href=&quot;https://www.materialscloud.org/discover/sssp/table/efficiency&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;http://www.pseudo-dojo.org/&quot; rel=&quot;noreferrer&quot;&gt;Pseudo Dojo&lt;/a&gt; is also gaining popularity. There, you might be limited for now, to Norm-conserving or PAW pseudopotentials depending on the species.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Everything else is relatively straight forward and easy to work with. Once you define your system. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the example you provide, they used&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;K_POINTS automatic &#xA;2 3 2 0 0 0&lt;/code&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;to generate that first mesh. This is very loose. You will need a much denser grid to study properties, but this should be good enough to get you started! Hope this helps. To visualize your system directly from your input, many use &lt;a href=&quot;http://www.xcrysden.org/&quot; rel=&quot;noreferrer&quot;&gt;XCrysDen&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="189" LastEditDate="2020-05-06T13:43:49.593" LastActivityDate="2020-05-06T13:43:49.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="162" PostTypeId="1" CreationDate="2020-05-01T19:52:11.550" Score="21" ViewCount="179" Body="&lt;p&gt;High-throughput computational screening, inverse materials design, and advances in machine learning have really accelerated the pace in which we can identify novel materials for a wide range of applications, at least in an academic setting. What are some examples where the proposed material, or a clear variant of it, has been developed and used in the industry?&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-01-03T07:35:33.540" Title="What are some materials discovered from first-principles calculations that ended up being incorporated in a commercial product?" Tags="|density-functional-theory|ab-initio-calculations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="163" PostTypeId="1" AcceptedAnswerId="3739" CreationDate="2020-05-01T20:06:14.597" Score="35" ViewCount="1721" Body="&lt;p&gt;Most periodic density functional theory (DFT) codes use plane-wave basis sets in conjunction with three-dimensional periodic boundary conditions. In contrast, for molecular systems of finite size, Gaussian basis sets are often used. The former are quite efficient for periodic systems, but more expensive methods such as hybrid functionals become intractable for large system sizes. The latter is well-suited for finite clusters but rarely is appropriate for periodic systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.cp2k.org/&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt; uses a mixed Gaussian and plane-wave approach (GAPW) for periodic systems. &lt;a href=&quot;https://www.crystal.unito.it/index.php&quot; rel=&quot;noreferrer&quot;&gt;Crystal&lt;/a&gt; models periodic systems using atom-centered Gaussian functions. &lt;a href=&quot;https://parsec.oden.utexas.edu/&quot; rel=&quot;noreferrer&quot;&gt;PARSEC&lt;/a&gt; expresses wavefunctions in real space, avoiding explicit basis sets.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are some positives and negatives of these alternate approaches, when compared to more conventional periodic DFT packages? &lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2020-05-05T15:41:09.173" LastActivityDate="2020-11-13T01:44:04.323" Title="What are the positives and negatives of periodic DFT codes that don't use plane-wave basis sets?" Tags="|density-functional-theory|software|ab-initio-calculations|basis-sets|periodic-system|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="164" PostTypeId="2" ParentId="162" CreationDate="2020-05-01T20:16:32.723" Score="9" Body="&lt;p&gt;When you go to the industrial environment, it becomes really difficult to obtain published results due to the fact that if a company finds breakthrough new materials, why they should share it with the public, while they could commercialize it?&lt;/p&gt;&#xA;&lt;p&gt;I found an example of a company, called &lt;a href=&quot;https://exabyte.io/#case-study&quot; rel=&quot;nofollow noreferrer&quot;&gt;ExaByte&lt;/a&gt; that works on a material discovery platform and collaborate with universities and other companies to help them find novel materials for specific applications. I came across this &lt;a href=&quot;https://exabyte.docsend.com/view/syitiek&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt; that is related to the discovery of new metallic alloys for automotive and aerospace applications. You won't find many details, but overall they studied the stability of new metallic alloys based on enthalpy of formation values extracted from simulations that helped them to develop these new metallic alloys. I hope it helps here.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="697" LastEditDate="2021-01-03T07:35:33.540" LastActivityDate="2021-01-03T07:35:33.540" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="166" PostTypeId="1" AcceptedAnswerId="168" CreationDate="2020-05-01T20:21:20.233" Score="26" ViewCount="1205" Body="&lt;p&gt;Quantum-chemical calculations are quite expensive with a cost that scales greatly with the number of atoms in the system. What is the largest material that has been modeled using density functional theory (DFT), by number of atoms?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Edit: For the purposes of intellectual curiosity, please feel free to answer with unusually &quot;large&quot; DFT calculations even if it's not &lt;em&gt;the largest&lt;/em&gt;. &lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2020-05-02T02:40:30.887" LastActivityDate="2020-06-01T17:55:47.037" Title="What is the largest material that has been studied using density functional theory?" Tags="|density-functional-theory|ab-initio-calculations|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="167" PostTypeId="2" ParentId="166" CreationDate="2020-05-01T20:22:45.300" Score="11" Body="&lt;p&gt;In 2011, the electronic states of a silicon nanowire with 107,292 atoms was modeled using 6,144 cores over a ~24 hour runtime, as discussed &lt;a href=&quot;https://dl.acm.org/doi/10.1145/2063384.2063386&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I'm not sure of any larger example than this one, although one may exist.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-01T20:22:45.300" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="168" PostTypeId="2" ParentId="166" CreationDate="2020-05-01T20:39:56.437" Score="22" Body="&lt;p&gt;I know of several papers over the million-atom mark:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2,097,152 atoms &lt;a href=&quot;https://doi.org/10.1088/0953-8984/22/7/074207&quot; rel=&quot;noreferrer&quot;&gt;&quot;Calculations for millions of atoms with density functional theory: linear scaling shows its potential&quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;1,012,500 atoms using linear-scaling orbital-free DFT: &lt;a href=&quot;https://doi.org/10.1016/j.cplett.2009.04.059&quot; rel=&quot;noreferrer&quot;&gt;&quot;Accurate simulations of metals at the mesoscale: Explicit treatment of 1 million atoms with quantum mechanics&quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://hdl.handle.net/1842/6543&quot; rel=&quot;noreferrer&quot;&gt;&quot;Million Atom KS-DFT with CP2K&quot;&lt;/a&gt; (not clear if it actually happened)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastEditorUserId="142" LastEditDate="2020-06-01T17:55:47.037" LastActivityDate="2020-06-01T17:55:47.037" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="169" PostTypeId="1" AcceptedAnswerId="235" CreationDate="2020-05-01T21:52:15.230" Score="23" ViewCount="272" Body="&lt;p&gt;For many applications with heavy metals, pseudopotentials can be used to include some amount of relativistic effects. But for what sort of systems does it become necessary to actually use a relativistic method (e.g Dirac Hartree Fock)? Is this there active research into material modeling with a relativistic formalism?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="52" LastEditDate="2020-05-02T20:22:56.227" LastActivityDate="2020-05-02T20:58:27.103" Title="When do relativistic effects need to be explicitly included?" Tags="|electronic-structure|relativistic|pseudopotentials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="170" PostTypeId="1" AcceptedAnswerId="172" CreationDate="2020-05-01T22:25:12.820" Score="28" ViewCount="1665" Body="&lt;p&gt;I know that parallelization is an important factor, however, I wanted to know if there are any other methods of reducing computing time when dealing with large systems without sacrificing accuracy. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="204" LastActivityDate="2023-07-20T04:39:10.897" Title="What are good ways to reduce computing time when working with large systems in VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="171" PostTypeId="1" CreationDate="2020-05-01T22:27:08.823" Score="10" ViewCount="102" Body="&lt;p&gt;Could you list any programs that can do non-orthogonal CI please?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="5" LastEditDate="2020-05-01T22:47:41.157" LastActivityDate="2020-06-11T07:36:04.867" Title="Are there any programs that can do non-orthogonal CI?" Tags="|configuration-interaction|nonorthogonal-ci|valence-bond-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="172" PostTypeId="2" ParentId="170" CreationDate="2020-05-01T23:20:57.390" Score="26" Body="&lt;p&gt;There isn't a single correct answer to this question, and it depends on what is slow, what kind of material you are modeling, and what you are trying to calculate. This answer is mostly going to be partially copied from my blog post &lt;a href=&quot;https://sites.tufts.edu/andrewrosen/density-functional-theory/vasp/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Geometry Optimizations&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Don’t waste your time using super high-accuracy settings on a structure far from the local minimum. Do an initial optimization with “looser” settings (e.g. gamma-point only for the k-point grid, 400 eV cutoff if relaxing the atomic positions) and then incrementally refine it with the desired (but more computationally expensive) parameters. The one exception to this general comment is that, when performing geometry optimizations that involve changes in the cell shape and/or volume, always ensure that ENCUT &gt; 1.3*ENMAX to prevent Pulay stresses. You don't want to cheapen out on this. But on the whole, you often don't need to use your &quot;production-quality&quot; settings for the full duration of a given structure relaxation.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When performing a full optimization of atomic positions and cell shape/volume, I generally recommend to do this in stages. It is often wise to start with a relaxation of the atomic positions (ISIF=2) followed by a full volume relaxation (ISIF=3). This will also significantly reduce the chance of running into convergence issues.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Whenever you can, restart from a converged wavefunction (i.e. the WAVECAR). The WAVECARs are not transferable between the gamma-point only and standard versions of VASP, but otherwise you should try to restart from them when possible to make the SCF converge quicker on a restart.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The first step in a geometry optimization will generally have the highest number of SCF iterations. It is okay if those first few steps do not converge electronically within the limits of NELM (maximum number of SCF iterations). In fact, it is better to have the first step reach NELM instead of running for many hundreds of SCF iterations.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Electronic Energy Convergence&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;For insulating materials (or when using meta-GGA functionals), SCF convergence is greatly accelerated by using ALGO=All. This has the added benefit that you don’t have to worry about any of the mixing tags. A word of caution though -- some compilations of VASP do not play well with the ALGO=All flag for some reason and stall after a few SCF iterations, so just give it a go and see.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If dealing with large systems, use LREAL=Auto to speed up the calculations. You may want to switch this back to LREAL=False at the end though to ensure your energies are high-quality.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Choice of Geometry Optimization Algorithms&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In terms of efficiency and robustness in an optimization algorithm for finding local minima, I generally recommend starting with the conjugate gradient (CG) algorithm (IBRION=2) because it is very robust and you do not have to worry about tweaking POTIM. However, in large, flexible materials with many degrees of freedom, the CG optimization algorithm oftentimes results in a bracketing error once it gets relatively close to the local minimum (search for &lt;code&gt;ZBRENT: fatal error in bracketing&lt;/code&gt; in the standard output file). This occurs because the potential energy surface is very flat, and the CG algorithm implemented in VASP is based on the energy differences. One option to fix this is to use FIRE as implemented with &lt;a href=&quot;http://theory.cm.utexas.edu/vtsttools/&quot; rel=&quot;noreferrer&quot;&gt;VTST&lt;/a&gt; (IBRION=3, IOPT=7). &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.170201&quot; rel=&quot;noreferrer&quot;&gt;It should get you to that local minimum quicker&lt;/a&gt;, particularly when the potential energy surface is quite flat.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Generally, for nudged elastic band (NEB) calculations and the climbing image variant (CI-NEB), I have found that the the L-BFGS algorithm (IOPT=1) implemented in VTST is often the fastest. For the dimer method, the force-based CG method in VTST (IOPT=2) is recommended. However, if you are having trouble in either case, I suggest switching to the FIRE algorithm (IOPT=7) with the default settings. It is a bit slower, but it is especially useful in troublesome cases of convergence.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Parallel Performance&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Whenever feasible, take advantage of the gamma-point only VASP executable, as it runs up to 1.5 times faster than the standard executable.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Try tweaking the NCORE or NPAR flags to adjust the scaling performance. The optimal value for NCORE strongly varies based on the computing environment. I generally use NCORE=cpus-per-node or NCORE=cpus-per-node/2 as a first guess.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-01T23:31:19.837" LastActivityDate="2020-05-01T23:31:19.837" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="173" PostTypeId="2" ParentId="166" CreationDate="2020-05-02T00:01:58.670" Score="26" Body="&lt;p&gt;Here is a DFT simulation of a &lt;strong&gt;&lt;em&gt;virus&lt;/em&gt;&lt;/strong&gt;, in solution!&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&quot;&lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jctc.6b00398&quot; rel=&quot;noreferrer&quot;&gt;Combining Linear-Scaling DFT with Subsystem DFT in&#xA;Born-Oppenheimer and Ehrenfest Molecular Dynamics&#xA;simulations: from Molecules to a Virus in Solution.&lt;/a&gt;&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iyf4j.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iyf4j.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But I like the way Frank Neese (lead author of ORCA) described his coupled cluster calculation of a protein: &quot;this is what I call quantum mechanical weightlifting .. it's when we are only doing the calculation because we want to see who can lift the most.&quot; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Bear in mind that if all we cared about was &quot;quantum mechanical weightlifting&quot; competitions, those records from 2010 could have been broken several times by people making more and more approximations and using more and more hardware. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My preferred criteria when evaluating things like this, is that the calculation was a necessary part of predicting something that was later shown to be true in an experiment, or was necessary to reach agreement with experiment, or was crucial in the correct analysis of an experiment, or something along those lines. But I still also do love seeing these &quot;quantum mechanical weightlifting&quot; records being broken either way, and therefore I do love questions like these!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="142" LastEditDate="2020-06-01T17:53:48.123" LastActivityDate="2020-06-01T17:53:48.123" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="174" PostTypeId="1" CreationDate="2020-05-02T00:04:05.263" Score="30" ViewCount="1840" Body="&lt;p&gt;We use the Born-Oppenheimer approximation in both Hartree-Fock method and DFT. What are the problems where we cannot use this approximations.&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="49" LastEditDate="2020-05-02T21:28:57.923" LastActivityDate="2020-05-13T15:08:46.710" Title="What are the situations/problems where Born-Oppenheimer approximation is invalid?" Tags="|quantum-mechanics|born-oppenheimer-approximation|" AnswerCount="5" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="175" PostTypeId="1" AcceptedAnswerId="196" CreationDate="2020-05-02T00:12:38.877" Score="14" ViewCount="173" Body="&lt;p&gt;In line with &lt;a href=&quot;https://materials.stackexchange.com/q/113/10&quot;&gt;this question&lt;/a&gt;, I'm looking for suitable functionals for transition metal compounds with organic ligands to predict NMR spectra. Also, I'd like some guidelines about how to choose functionals for this type of calculations.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="5" LastEditDate="2020-05-17T00:04:21.740" LastActivityDate="2020-05-17T00:04:21.740" Title="Appropriate functionals for prediction of NMR spectra of transition metal compounds" Tags="|density-functional-theory|cdft|bdft|transition-metals|nuclear-magnetic-resonance|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="176" PostTypeId="1" AcceptedAnswerId="306" CreationDate="2020-05-02T00:26:10.433" Score="17" ViewCount="520" Body="&lt;p&gt;&lt;strong&gt;Related question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1322/5&quot;&gt;Mathematical expression of SCAN (Strongly Constrained and Appropriately Normed) constraints in DFT&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The SCAN (strongly-constrained and appropriately-normed) meta-GGA constructed in 2015 is the most promising metaGGA which respects all 17 known exact constraints that a meta-GGA can satisfy. What are these constraints? What's the significance?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2021-04-26T01:21:22.377" LastActivityDate="2021-04-26T01:21:22.377" Title="The SCAN meta-GGA respects all 17 known exact constraints that a meta-GGA can satisfy. What are these constraints? What's the significance?" Tags="|density-functional-theory|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="177" PostTypeId="1" AcceptedAnswerId="1045" CreationDate="2020-05-02T01:10:06.013" Score="17" ViewCount="853" Body="&lt;p&gt;Effective Hamiltonian approaches such as the Tight-Binding method played a central role in the reconciliation between chemistry and in physics in the solid state. A classical and complete treatment of the method is found in Walter A. Harrison's book &lt;em&gt;&quot;Elementary Electronic Structure&quot;&lt;/em&gt; (an update to his prior text &lt;em&gt;&quot;Electronic Structure and the Properties of Solids: The physics of the chemical bond&quot;&lt;/em&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Tight-binding models continue to play a central role in condensed&#xA;   matter and materials physics. As they require certain model&#xA;   parameters, I ask:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Is it possible to construct a Tight-binding model using Density Functional &#xA;Theory or another &lt;em&gt;ab initio&lt;/em&gt; method as a starting point?&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;How is this achieved? Are there available codes that aid in this process?&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="175" LastEditorUserId="36" LastEditDate="2020-05-22T18:57:58.710" LastActivityDate="2020-05-23T05:11:07.807" Title="How to construct a Tight-Binding Hamiltonian from first-principles computations?" Tags="|density-functional-theory|model-hamiltonians|effective-hamiltonian|tight-binding|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="178" PostTypeId="1" CreationDate="2020-05-02T01:58:39.313" Score="23" ViewCount="715" Body="&lt;p&gt;This is parallel to the analogous question about the largest DFT calculation: &lt;a href=&quot;https://materials.stackexchange.com/questions/166/what-is-the-largest-material-that-has-been-studied-using-density-functional-theo&quot;&gt;What is the largest material that has been studied using density functional theory?&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I assume we allow high performance computing (e.g local correlation, sparsity, parallelization, etc).&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-26T19:39:51.453" LastActivityDate="2024-03-07T18:19:56.570" Title="What is the largest system that has been studied by the coupled cluster method?" Tags="|electronic-structure|coupled-cluster|orca|mrcc|nwchem|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="179" PostTypeId="1" AcceptedAnswerId="237" CreationDate="2020-05-02T02:06:00.073" Score="23" ViewCount="705" Body="&lt;p&gt;If I have a CIF that is P1, is there a (preferably free) code that can map the structure to some user-specified space group? I know that there are ways to do similar things with molecular systems. For instance, &lt;a href=&quot;http://www.chemcraftprog.com/&quot; rel=&quot;noreferrer&quot;&gt;ChemCraft&lt;/a&gt; has an option to detect the nearest point group and then apply it to the molecule. I'd like to do the same for a crystalline structure given a space group.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2020-05-09T20:45:09.647" LastActivityDate="2020-09-10T02:41:06.687" Title="Enforce a space group on a given crystal structure" Tags="|software|space-groups|crystal-structure|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="180" PostTypeId="2" ParentId="156" CreationDate="2020-05-02T03:32:33.907" Score="12" Body="&lt;p&gt;Regarding input file format, check this website: &#xA;&lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;noreferrer&quot;&gt;https://www.materialscloud.org/work/tools/qeinputgenerator&lt;/a&gt;&#xA;Format from this website will provide you a &lt;strong&gt;starting point&lt;/strong&gt;. But please remind that the result from this website IS NOT the ultimate solution and please do NOT regard the result from here as the &quot;OK-button&quot; solution. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;It seems that the example in your question already provided all conditions. However, in reality, you will need to run a lot of test runs to figure out the optimal conditions for cutoff energy values, k-point, and etc conditions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For pseudopotentials, I usually use QE homepage: &#xA;&lt;a href=&quot;https://www.quantum-espresso.org/pseudopotentials&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/pseudopotentials&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also check out QE homepage for additional information, such as: &#xA;&lt;a href=&quot;https://www.quantum-espresso.org/resources/tools&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/resources/tools&lt;/a&gt;&#xA;and&#xA;&lt;a href=&quot;https://www.quantum-espresso.org/resources/tutorials&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/resources/tutorials&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="74" LastActivityDate="2020-05-02T03:32:33.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="181" PostTypeId="1" AcceptedAnswerId="863" CreationDate="2020-05-02T03:44:30.873" Score="36" ViewCount="940" Body="&lt;p&gt;I know the general question of machine learning in computational chemistry has been already raised here: &lt;a href=&quot;https://materials.stackexchange.com/q/18&quot;&gt;What is the current status of machine learning applied to materials or molecular systems?&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, still, I'm curious, what are the pros and cons of ML force fields for MD simulations.   &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Classical empirical potential models are fast but they are incorrect or cannot predict specific chemistry and bond formation/dissociation. Reactive potentials have some accuracy (depending on parameters) but they are slow. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Then... where is the position of ML potentials? Are they accurate? Or fast? Or both? I read some papers by Podryabinkin &lt;em&gt;et. al.&lt;/em&gt;&lt;sup&gt;[1]&lt;/sup&gt; and by Deringer &lt;em&gt;et al.&lt;/em&gt;.&lt;sup&gt;[2]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, as a person who never tried ML potentials before, it is really hard to judge or feel the state of the ML force field. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, if anyone tried various interatomic potentials including ML force fields (in Gromacs or Lammps or any platforms) may I ask how much accurate/fast are they, and what is the advantage/disadvantage of ML force field? Is this easy/hard to learn, or easy/hard to get &quot;good parameter&quot;, etc.. &lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Podryabinkin, E. V.; Tikhonov, E. V.; Shapeev, A. V.; Oganov, A. R. Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning. &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;99&lt;/em&gt; (6), No. 064114. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.99.064114&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.99.064114&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Deringer, V. L.; Caro, M. A.; Csányi, G. Machine Learning Interatomic Potentials as Emerging Tools for Materials Science. &lt;em&gt;Adv. Mater.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;31&lt;/em&gt; (46), 1902765. &lt;a href=&quot;https://doi.org/10.1002/adma.201902765&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/adma.201902765&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="74" LastEditorUserId="49" LastEditDate="2020-05-10T23:06:55.233" LastActivityDate="2020-07-02T17:12:00.363" Title="Machine learning interatomic potentials for molecular dynamic simulations: are they good?" Tags="|machine-learning|molecular-dynamics|forcefields|interatomic-potentials|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="182" PostTypeId="2" ParentId="178" CreationDate="2020-05-02T04:01:36.643" Score="22" Body="&lt;h1&gt;ORCA&lt;/h1&gt;&#xA;&lt;p&gt;The local pair-natural orbital (DLPNO) based coupled cluster method have been managed to investigate large organic molecule and small proteins (linear C150H302 (452 atoms, &amp;gt;8800 basis functions) , Crambin with 644 atoms, and more than 6400 basis functions ,C350H902 (&amp;gt;1000 atoms, &amp;gt; 20000 basis functions)).&lt;/p&gt;&#xA;&lt;p&gt;Riplinger, C., Sandhoefer, B., Hansen, A., &amp;amp; Neese, F. (2013). Natural triple excitations in local coupled cluster calculations with pair natural orbitals. The Journal of chemical physics, 139(13), 134101.&lt;/p&gt;&#xA;&lt;p&gt;Riplinger, C., Pinski, P., Becker, U., Valeev, E. F., &amp;amp; Neese, F. (2016). Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. II. Linear scaling domain based pair natural orbital coupled cluster theory. The Journal of chemical physics, 144(2), 024109.&lt;/p&gt;&#xA;&lt;p&gt;In recent years, considerable amount of effort has been made on developing linear scaling coupled cluster methods. These methods have been implemented in the electronic structure package ORCA which is developed by Max Planck Institute, Germany.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-26T19:38:53.593" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="183" PostTypeId="2" ParentId="179" CreationDate="2020-05-02T04:03:31.343" Score="25" Body="&lt;p&gt;While there are undoubtedly other programs that do this, it's fairly easy to do in Avogadro.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I start with a calculation on hexagonal SiC. As mentioned, it starts as &lt;span class=&quot;math-container&quot;&gt;$P_1$&lt;/span&gt;:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hc9ASm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hc9ASm.png&quot; alt=&quot;triclinic setting of a non-ideal SiC unit cell&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Go to Crystallography -&gt; Space Group -&gt; Perceive Space Group&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JEZeHm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JEZeHm.png&quot; alt=&quot;Avogadro menu item for Perceive Space Group...&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The unit cell should update, including symmetrization if needed&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5qUKwm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5qUKwm.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-02T04:03:31.343" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="184" PostTypeId="2" ParentId="156" CreationDate="2020-05-02T04:41:13.913" Score="13" Body="&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;You can start with following this &lt;a href=&quot;http://www.iiserpune.ac.in/~smr2626/talks-presentations.html&quot; rel=&quot;noreferrer&quot;&gt;Quantum Espresso Tutorial&lt;/a&gt;. The tutorial includes &lt;strong&gt;Hands On: scf, Energy bands, eqn of state, Geometry, cell optimization, Magnetism, DFT + U, CPMD, TDDFT, GW, Phonos, Berry Phases, IR and Raman&lt;/strong&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You can also follow &lt;a href=&quot;http://www.compmatphys.org/&quot; rel=&quot;noreferrer&quot;&gt;Open online course on DFT&lt;/a&gt;, with simultaneous hands-on training on Quantum ESPRESSO. Available at any time for self-paced study. Yearly supervised edition from September to December.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-02T12:27:40.317" LastActivityDate="2020-05-02T12:27:40.317" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="185" PostTypeId="1" AcceptedAnswerId="187" CreationDate="2020-05-02T07:06:20.803" Score="20" ViewCount="437" Body="&lt;p&gt;In my spare time, I have been studying and analysing continued fractions. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I was having a conversation with someone on Discord in a Mathematics server and he was telling me that continued fractions can be related to quantum physics. He didn't go into it too much and the concept he was describing seemed a little vague to me. I am aware that Pincherle's theorem&lt;sup&gt;[1]&lt;/sup&gt; asserts there is an intimate relationship with three-term recurrence relations of the form &lt;span class=&quot;math-container&quot;&gt;$x_{n+1}=b_nx_n+a_nx_{n-1}$&lt;/span&gt; and continued fractions, more accurately with their partial convergents, given that this recurrence relation has a minimum if a related cfrac converges. But I am not quite the physicist myself to compare physics with the properties of cfracs.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Although I can go on Google and do some research on this, I figured it might serve useful to have a post on this in this beta community, but I do apologise if it is too broad or open-ended and thus upsets any regulations here.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Any thoughts on this?&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;[1] Pincherle, S. (1894). Delle funzioni ipergeometriche e di varie questioni ad esse attinenti. &lt;em&gt;Giorn. Mat. Battaglini&lt;/em&gt;. 32:209–29&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2] Parusnikov, V. I. A Generalization of Pincherle's Theorem to k-Term Recursion Relations. &lt;em&gt;Math Notes&lt;/em&gt; &lt;strong&gt;2005,&lt;/strong&gt; &lt;em&gt;78&lt;/em&gt; (5-6), 827–840. &lt;a href=&quot;https://doi.org/10.1007/s11006-005-0188-7&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1007/s11006-005-0188-7&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="246" LastEditorUserId="5" LastEditDate="2020-06-01T16:59:12.310" LastActivityDate="2020-08-01T00:01:34.877" Title="How are continued fractions related to quantum materials?" Tags="|mathematical-modeling|quantum-mechanics|soft-question|" AnswerCount="3" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="186" PostTypeId="2" ParentId="185" CreationDate="2020-05-02T07:49:17.513" Score="14" Body="&lt;p&gt;You may take a look at the &lt;a href=&quot;https://en.wikipedia.org/wiki/Method_of_continued_fractions&quot; rel=&quot;noreferrer&quot;&gt;Method of Continued Fractions&lt;/a&gt; used in quantum scattering theory&amp;mdash;this was only &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.28.2151&quot; rel=&quot;noreferrer&quot;&gt;formed in 1983&lt;/a&gt;&lt;sup&gt;1&lt;/sup&gt; so is rather recent. Related is the PhD thesis by &lt;a href=&quot;https://arxiv.org/pdf/quant-ph/0101040.pdf&quot; rel=&quot;noreferrer&quot;&gt;Kónya (2000)&lt;/a&gt;&lt;sup&gt;2&lt;/sup&gt;; §3.3 onwards. &lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; Reference &lt;/sub&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; [1] Horáček, J., Sasakawa, T. (1983). Method of continued fractions with application to atomic physics. &lt;em&gt;Physical Review A.&lt;/em&gt; 28(4):2151–2156. &lt;/sub&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; [2] Kónya, B. (2000). Continued fraction representation of quantum mechanical Green's operators. PhD thesis. arXiv:0101040 [quant-ph]. &lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="35" LastEditDate="2020-05-02T08:00:34.070" LastActivityDate="2020-05-02T08:00:34.070" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="187" PostTypeId="2" ParentId="185" CreationDate="2020-05-02T07:55:21.120" Score="15" Body="&lt;p&gt;In the paper &amp;quot;&lt;a href=&quot;https://academic.oup.com/ptp/article/34/3/399/1943170&quot; rel=&quot;nofollow noreferrer&quot;&gt;A Continued-Fraction Representation of the Time-Correlation Functions&lt;/a&gt;&amp;quot;, generalized susceptibilities and transport coefficients for materials are obtained using a continued-fraction expansion of the Laplace transform of the time-correlation functions.&lt;/p&gt;&#xA;&lt;p&gt;This was the precursor to what is now called the &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Hierarchical_equations_of_motion&quot; rel=&quot;nofollow noreferrer&quot;&gt;hierarchical equations of motion&lt;/a&gt;&amp;quot; which are used to study the dynamics of a quantum system (such as an electron) coupled to a bosonic bath (for example the vibrations of the lattice in a GaAs semi-conductor quantum dot). This area is called &amp;quot;dissipative quantum dynamics&amp;quot; or &amp;quot;open quantum systems&amp;quot; and is used to study for example, the decoherence of qubits in solid-state quantum computers.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-01T00:01:34.877" LastActivityDate="2020-08-01T00:01:34.877" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="188" PostTypeId="1" AcceptedAnswerId="1049" CreationDate="2020-05-02T08:58:14.117" Score="17" ViewCount="107" Body="&lt;p&gt;Optically active materials, and particularly metals can be described fairly well with Classical Electrodynamics. For example, interfaces can be modeled using the Drude model, and for spherical particles we have Mie theory. This is valid for large systems (for example microns in depth or diameter). However, as systems become smaller, microscopic quantum effects can play an important role in the description of the electrodynamics. These effects are commonly known as &lt;a href=&quot;https://www.nature.com/articles/nphys2615&quot; rel=&quot;noreferrer&quot;&gt;&quot;Quantum Confinement Effects&lt;/a&gt;&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A classic and illustrative example of change in optical activity as a function of size is in silver and gold nanoparticles. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the completely classical regime, Finite Difference Time Domain (&lt;a href=&quot;https://en.wikipedia.org/wiki/Finite-difference_time-domain_method&quot; rel=&quot;noreferrer&quot;&gt;FDTD&lt;/a&gt;) simulations are used for electrodynamic simulations. Is it possible to use FDTD for simulating mesoscopic structures (nanostructures) where quantum size effects matter? What is the limit in size that can accurately be described by classical electrodynamics for a gold nanoparticle?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What methods are there available to model quantum-confinement effects in nanostructures of different sizes?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-05-18T04:42:56.030" LastActivityDate="2020-05-23T16:35:49.890" Title="How do you model quantum-confinement effects in optically active (e.g. plasmonic) mesoscopic structures?" Tags="|plasmonics|mesoscopic-physics|nanostructures|semiclassical|quantum-size-effects|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="189" PostTypeId="1" AcceptedAnswerId="193" CreationDate="2020-05-02T09:16:11.133" Score="19" ViewCount="157" Body="&lt;p&gt;High-Throughput materials modeling based on Density Functional Theory has become very popular recently. If, for example, we search &lt;a href=&quot;https://scholar.google.com/scholar?q=High-Throughput%20perovskites&amp;amp;hl=en&amp;amp;as_sdt=0,5&quot; rel=&quot;noreferrer&quot;&gt;&quot;High-Throughput Perovskites&quot;&lt;/a&gt; in Google Scholar, we get over ~14,000 results. Not all are computational and not all are peer-reviewed publications but it shows just how important High Performance Computing is in current materials research. Needless to say, &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;The Materials Project&lt;/a&gt; and &lt;a href=&quot;http://aflowlib.org/&quot; rel=&quot;noreferrer&quot;&gt;AFLOW&lt;/a&gt; are big players in the High-Throughput Materials Simulation game. There is even a &lt;a href=&quot;https://www.topologicalquantumchemistry.org/#/&quot; rel=&quot;noreferrer&quot;&gt;database&lt;/a&gt; for Topological Insulators and Weyl Semimetals&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However I am not aware of a database or High-Throughput study that is completely focused on the discovery of high &lt;span class=&quot;math-container&quot;&gt;$T_C$&lt;/span&gt; superconductors. Can anyone point me toward some references? Are there any studies of this kind at all?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="7" LastEditDate="2020-06-15T18:58:59.003" LastActivityDate="2020-06-15T18:58:59.003" Title="Are there any High-Throughput studies that aim to discover High Tc superconductors?" Tags="|density-functional-theory|reference-request|high-performance-computing|materials-informatics|superconductivity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="190" PostTypeId="1" AcceptedAnswerId="194" CreationDate="2020-05-02T10:30:07.563" Score="17" ViewCount="545" Body="&lt;p&gt;Many abbreviations are used in Materials Modelling. For example, we have DFT (density functional theory/discrete Fourier transform), TST (transition state theory) and MD (molecular dynamics).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Which abbreviations are commonly used in Materials Modelling?&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; This question was taken from the similar &lt;a href=&quot;https://or.stackexchange.com/questions/865/what-are-common-and-not-so-common-abbreviations-in-operations-research&quot;&gt;What are common and not so common abbreviations in Operations Research?&lt;/a&gt; on OR.SE. &lt;/sub&gt; &lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="5" LastEditDate="2020-06-03T23:51:30.380" LastActivityDate="2023-04-05T14:08:54.367" Title="What are the common acronyms in Materials Modelling?" Tags="|terminology|one-topic-per-answer|" AnswerCount="6" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="191" PostTypeId="1" AcceptedAnswerId="195" CreationDate="2020-05-02T11:00:43.973" Score="15" ViewCount="112" Body="&lt;p&gt;I am aware that the &lt;a href=&quot;https://en.wikipedia.org/wiki/Potts_model&quot; rel=&quot;noreferrer&quot;&gt;Potts Model&lt;/a&gt; can be used to simulate grain growth, and that &lt;a href=&quot;https://en.wikipedia.org/wiki/Phase-field_model&quot; rel=&quot;noreferrer&quot;&gt;Phase Field Models&lt;/a&gt; have also been very successful. What are the advantages and limitations of these models? What are the other modelling techniques that can be used to simulate microstructure evolution?&lt;/p&gt;&#xA;" OwnerUserId="22" LastActivityDate="2020-05-02T16:48:21.823" Title="What are the modelling techniques that can be used for simulating microstructure evolution in materials?" Tags="|reference-request|monte-carlo|mathematical-modeling|phase-field-modeling|microstructure-evolution|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="192" PostTypeId="2" ParentId="171" CreationDate="2020-05-02T12:43:04.970" Score="7" Body="&lt;p&gt;To start with, we do have:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;LUCIA, a Correlation Program, 2019, developed by Kähler and Olsen. &lt;a href=&quot;http://doi.org/10.1063/1.4999218&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nonorthogonal internally contracted multi-configurational perturbation theory&lt;/a&gt; and &lt;a href=&quot;http://doi.org/10.1063/1.5049706&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dynamic correlation for nonorthogonal reference states&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://manual.q-chem.com/5.2/Ch7.S4.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Q-CHEM&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://gronor.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;GronOR&lt;/a&gt;: Massively parallel and GPU- accelerated non-orthogonal configuration interaction for large molecular systems.&lt;/li&gt;&#xA;&lt;li&gt;TURTLE, an Ab ignition VB/VBSCF Program, 1988-2000, developed by J. Verbeek, J. H. Langenberg, C. P. Byrman, F. Dijkstra, and J. H. van Lenthe.&lt;/li&gt;&#xA;&lt;li&gt;... continue the list ...&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="159" LastEditorUserId="142" LastEditDate="2020-06-11T07:36:04.867" LastActivityDate="2020-06-11T07:36:04.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="193" PostTypeId="2" ParentId="189" CreationDate="2020-05-02T14:36:37.687" Score="18" Body="&lt;p&gt;There are several such studies, particularly focusing on the machine-learning of critical temperatures.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1038/s41524-018-0085-8&quot; rel=&quot;noreferrer&quot;&gt;&quot;Machine learning modeling of superconducting critical temperature&quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.7567/1882-0786/ab2922&quot; rel=&quot;noreferrer&quot;&gt;&quot;An acceleration search method of higher T c superconductors by a machine learning algorithm&quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1039/C8ME00012C&quot; rel=&quot;noreferrer&quot;&gt;&quot;Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery&quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;They all rely on the &lt;a href=&quot;https://supercon.nims.go.jp/index_en.html&quot; rel=&quot;noreferrer&quot;&gt;&quot;Supercon&quot;&lt;/a&gt; database of ~12,000 critical temperatures, which has also been extracted as supporting information for the first paper to &lt;a href=&quot;https://github.com/vstanev1/Supercon&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In general, the ML methods offer suggestions for new compositions, but I'm not sure if any have yet been attempted.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-02T14:36:37.687" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="194" PostTypeId="2" ParentId="190" CreationDate="2020-05-02T16:02:11.930" Score="25" Body=" &#xA;&lt;p&gt;I will start with acronyms for coupled-cluster, and someone else might answer with acronyms for &lt;strong&gt;basis sets&lt;/strong&gt; or for &lt;strong&gt;functionals&lt;/strong&gt; or for &lt;strong&gt;many body perturbation theory&lt;/strong&gt; or for &lt;strong&gt;composite approaches&lt;/strong&gt; or for different &lt;strong&gt;types of SCF&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h1&gt;Coupled Cluster acronyms&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;CCSD, CCSDT, CCSDTQ&lt;/strong&gt;, ... (coupled cluster with singles, doubles, triples, quadrtuples, etc.)&lt;br&gt;&#xA;&lt;strong&gt;CCSD(T), CCSDT(Q)&lt;/strong&gt;, ... (coupled cluster with perturbative triples, quadruples, pentuples, etc.)&lt;br&gt;&#xA;&lt;strong&gt;EOM-CCSD, EOM-CCSDT&lt;/strong&gt;, ... (equation of motion coupled cluster, w/ singles, doubles, etc.)&lt;br&gt;&#xA;&lt;strong&gt;STEOM-CCSD&lt;/strong&gt;, ... (similarity transformed equation of motion coupled cluster, w/ singles, etc.)&lt;br&gt;&#xA;&lt;strong&gt;LR-CCSD, LR-CCSDT&lt;/strong&gt;, ... (linear response coupled cluster, a synonym for EOM-CC)&lt;br&gt;&#xA;&lt;strong&gt;CC2, CC3, CC4, CC5&lt;/strong&gt;, ... (second, third, fourth, fifth-order coupled-cluster, etc.)&lt;br&gt;&#xA;&lt;strong&gt;SCS-CC2, SCS-CC3&lt;/strong&gt;, ... (spin-component scaled second, third, fourth, coupled-cluster, etc.)&lt;br&gt;&#xA;&lt;strong&gt;SOS-CC2, SOS-CC3&lt;/strong&gt;, ... (scaled opposite-spin second, third, fourth, coupled-cluster, etc.)&lt;br&gt;&#xA;&lt;strong&gt;BCCD, BCCDT, BCCDTQ&lt;/strong&gt;, ... (Brueckner coupled cluster with doubles, triples, etc.)&lt;br&gt;&#xA;&lt;strong&gt;Mk-MRCCSD, Mk-MRCCSDT&lt;/strong&gt;, ... (state-specific Mukherjee multireference coupled-cluster)&#xA;&lt;strong&gt;pCCSD, pCCSDT, pCCSDTQ&lt;/strong&gt;, ... (parameterized coupled cluster with singles, doubles, etc.)&#xA;&lt;strong&gt;TCCSD,TCCSDT,TCCSDDTQ&lt;/strong&gt;, .. (tailored coupled cluster with singles, doubles, triples, etc.)&lt;br&gt;&#xA;&lt;strong&gt;CVS-EOM-CC&lt;/strong&gt;, .. (core-valence separated equation-of-motion coupled-cluster)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;RCCSD&lt;/strong&gt;: partially spin-restricted coupled cluster &lt;br&gt;&#xA;&lt;strong&gt;UCCSD&lt;/strong&gt;: spin-unrestricted coupled cluster, or unitary coupled cluster&lt;br&gt;&#xA;&lt;strong&gt;RDCSD&lt;/strong&gt;: partially spin-restricted distinguishable coupled cluster&lt;br&gt;&#xA;&lt;strong&gt;UDCSD&lt;/strong&gt;: spin-urestricted distinguishable coupled cluster&lt;br&gt;&#xA;&lt;strong&gt;pCCD&lt;/strong&gt;: pair coupled cluster with doubles (sometimes called &lt;strong&gt;AP1RoG&lt;/strong&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;CCSD-F12, EOM-CCSD-F12&lt;/strong&gt;: coupled cluster, or EOM coupled cluster, with F12 correction.&lt;br&gt;&#xA;&lt;strong&gt;RI-CC2&lt;/strong&gt;: coupled cluster, with the resolution of the identity approximation for the integrals.&lt;br&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-08T21:14:17.790" LastActivityDate="2020-08-08T21:14:17.790" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="195" PostTypeId="2" ParentId="191" CreationDate="2020-05-02T16:48:21.823" Score="13" Body="&lt;p&gt;I could list the models that could be used for microstructural modeling as:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Phase-Field&lt;/strong&gt;: It is constructed based on non-equilibrium thermodynamics and Onsager reciprocal relations to derive a functional for Gibbs free energy and then find the order variables (i.e. phase-field variable to describe the fraction of phases, concentration, temperature, stresses, etc.). This method will give you a PDE that needs to be solved numerically with finite difference or finite element. The advantage with phase-field is that you have solid theory to capture phase transformations (e.g. grain growth) by using thermodynamics, but the disadvantage is that it is computationally expensive usually for real systems and you need a parallelized code with MPI or GPU to have a reasonable computational performance.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Stochastic or Monte-Carlo&lt;/strong&gt;: In this method you model the phase transformation in your material by calculating its Gibbs free energy and then calculate probability density function to decide if this transformation is going to happen or not. Note that stochastic is much more simpler than Monte-Carlo method. Basically in your random-walk trial you just try one time for comparing the generated random number with the probability drawn from your probability density function, but in Monte-Carlo you need to repeat this try even in your first move for certain times to make sure it's the most probable way for your system to go. The advantage is that it's much more simpler to code and it's much more faster than phase-field, but you would have lots of difficulties to capture complex phase transformation phenomena in your real systems.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Molecular Dynamics&lt;/strong&gt;: It's possible to simulate the grain growth or other phase-transformation problems with molecular dynamics. In fact, you need to define the interatomic potential (i.e. in case of metallic systems, it's simple: just choose EAM (Embedded Atom Method)) and the temperature of your system and then you need to track the time-evolution of your system and identify the interesting regions such as crystallized grains, etc. The advantage here is that you could approach complex systems with much more confidence because here molecular dynamics acts like a pseudo first-principle method for studying microstructures and phase transformations, but the challenge or disadvantage is that the molecular dynamics is usually computationally expensive and also the phase-transformation phenomena are considered &lt;em&gt;rare-events&lt;/em&gt; which means you need to run your simulation for long-time at least based on diffusion time calculated from your diffusion coefficient to see a phase-transformation, which again adds more burden on computationally expensive molecular dynamics.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Potts Models or Ising Models&lt;/strong&gt;: This model is similar to stochastic and Monte-Carlo method but you need to define the Hamiltonian of the system (instead of defining the Gibbs free energy) based on mechanics of your system and then solve it semi-deterministic to find the state of your system and study the phase-transformation in your material. The advantage is that the coding is much simpler than phase-field for example and as a result, it's much faster than phase-field, but you would have lots of difficulties defining the Hamiltonian of your system for real case applications besides toy models available in books.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;If you are looking for practical sides and want some suggestion for practical softwares or codes, feel free to open a new question to discuss the suitable codes or softwares for each of these methods mentioned above.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-02T16:48:21.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="196" PostTypeId="2" ParentId="175" CreationDate="2020-05-02T18:01:57.050" Score="9" Body="&lt;p&gt;I haven't had much experience with calculating chemical shifts, but I do have experience calculating J-coupling between P atoms on metal complexes. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;From this, I know that for chemical shifts and J-coupling calcs may require the use of specialized basis sets since most energy optimized basis sets (i.e. pople, dunning, karlsruhe) do not have an appropriate description of the core electrons for accuracy in nuclear calculations. I don't have experience with basis sets that are developed for chemical shifts, but this paper may be of use (although it only looks at 31P shifts): &lt;a href=&quot;https://dx.doi.org/10.1021/acs.organomet.0c00127&quot; rel=&quot;noreferrer&quot;&gt;https://dx.doi.org/10.1021/acs.organomet.0c00127&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I know that for 13C and 1H chemical shifts, the hybrid GGA functionals WPO4 and WCO4 were developed by Cramer for small organic compounds (ref to the original paper: &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/ct6001016&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/pdf/10.1021/ct6001016&lt;/a&gt; ) and are available by default on many quantum chemical computing programs - the paper cited also discusses the performance and shortcomings of other functionals, so that may help guide you if WPO4/WCO4 are not appropriate for your system. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also the GGA functionals KT1, KT2, and KT3 were developed for the nuclear shielding constants of non-H atoms and could be useful to you too (ref to the original KT paper: &lt;a href=&quot;https://doi.org/10.1063/1.1590634&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1063/1.1590634&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="254" LastActivityDate="2020-05-02T18:01:57.050" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="197" PostTypeId="5" CreationDate="2020-05-02T18:09:37.307" Score="0" Body="" OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-03T01:57:02.107" LastActivityDate="2020-05-03T01:57:02.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="198" PostTypeId="4" CreationDate="2020-05-02T18:09:37.307" Score="0" Body="For questions about ab-initio (first principle) calculations." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-02T18:55:44.677" LastActivityDate="2020-05-02T18:55:44.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="199" PostTypeId="5" CreationDate="2020-05-02T18:33:08.663" Score="0" Body="&lt;p&gt;For more information about phonopy, you can look at the &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;program's website&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2021-07-19T14:18:33.450" LastActivityDate="2021-07-19T14:18:33.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="200" PostTypeId="4" CreationDate="2020-05-02T18:33:08.663" Score="0" Body="Tag this when using the phonopy package for phonon calculations at harmonic and quasi-harmonic levels." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:12:23.397" LastActivityDate="2020-05-03T00:12:23.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="201" PostTypeId="5" CreationDate="2020-05-02T18:38:05.137" Score="0" Body="" OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-15T16:41:58.647" LastActivityDate="2020-05-15T16:41:58.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="202" PostTypeId="4" CreationDate="2020-05-02T18:38:05.137" Score="0" Body="For questions concerning electronic structure concepts and calculations." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-15T16:41:58.647" LastActivityDate="2020-05-15T16:41:58.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="203" PostTypeId="5" CreationDate="2020-05-02T18:39:08.557" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:39:08.557" LastActivityDate="2020-05-02T18:39:08.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="204" PostTypeId="4" CreationDate="2020-05-02T18:39:08.557" Score="0" Body="GROMACS software package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. Primarily designed for biochemical molecules like proteins, lipids and nucleic acids." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-02T18:55:12.677" LastActivityDate="2020-05-02T18:55:12.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="205" PostTypeId="5" CreationDate="2020-05-02T18:40:25.113" Score="0" Body="&lt;p&gt;For questions about magnetic systems and materials&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-02T18:55:18.910" LastActivityDate="2020-05-02T18:55:18.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="206" PostTypeId="4" CreationDate="2020-05-02T18:40:25.113" Score="0" Body="For questions about magnetic systems and materials" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-02T18:55:32.470" LastActivityDate="2020-05-02T18:55:32.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="207" PostTypeId="5" CreationDate="2020-05-02T18:43:12.640" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:43:12.640" LastActivityDate="2020-05-02T18:43:12.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="208" PostTypeId="4" CreationDate="2020-05-02T18:43:12.640" Score="0" Body="Refers to a mathematical description of a quantum state of a system." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:29:38.697" LastActivityDate="2020-05-03T00:29:38.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="209" PostTypeId="5" CreationDate="2020-05-02T18:44:45.923" Score="0" Body="&lt;p&gt;For questions around the modeling and description of materials surfaces i.e. crystal surfaces and slabs. &lt;strong&gt;Not for use in describing general surfaces like potential energy surfaces.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="52" LastEditDate="2020-06-29T05:25:55.667" LastActivityDate="2020-06-29T05:25:55.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="210" PostTypeId="4" CreationDate="2020-05-02T18:44:45.923" Score="0" Body="For questions around the modeling and description of materials surfaces" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-02T18:55:36.957" LastActivityDate="2020-05-02T18:55:36.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="211" PostTypeId="5" CreationDate="2020-05-02T18:47:02.073" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:47:02.073" LastActivityDate="2020-05-02T18:47:02.073" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="212" PostTypeId="4" CreationDate="2020-05-02T18:47:02.073" Score="0" Body="A class of theory  to explain chemical bonding. This focuses on how the atomic orbitals  of the dissociated atoms combine to give individual chemical bonds when a molecule is formed. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:12:36.987" LastActivityDate="2020-05-03T00:12:36.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="213" PostTypeId="5" CreationDate="2020-05-02T18:53:17.427" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:53:17.427" LastActivityDate="2020-05-02T18:53:17.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="214" PostTypeId="4" CreationDate="2020-05-02T18:53:17.427" Score="0" Body="For questions regarding crystal and molecular structure of materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-02T20:23:48.887" LastActivityDate="2020-05-02T20:23:48.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="215" PostTypeId="5" CreationDate="2020-05-02T18:53:17.967" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:53:17.967" LastActivityDate="2020-05-02T18:53:17.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="216" PostTypeId="4" CreationDate="2020-05-02T18:53:17.967" Score="0" Body="For questions referring to the degeneracies of electron orbital states, usually d or f orbitals, due to a static electric field produced by a surrounding charge distribution (anion neighbors)." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-02T19:06:41.917" LastActivityDate="2020-05-02T19:06:41.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="217" PostTypeId="5" CreationDate="2020-05-02T18:59:46.797" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T18:59:46.797" LastActivityDate="2020-05-02T18:59:46.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="218" PostTypeId="4" CreationDate="2020-05-02T18:59:46.797" Score="0" Body="Refers to the approximation of core electrons by effective potentials. Used in plane-wave and Gaussian based theories." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:12:47.127" LastActivityDate="2020-05-03T00:12:47.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="219" PostTypeId="5" CreationDate="2020-05-02T19:00:57.263" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:00:57.263" LastActivityDate="2020-05-02T19:00:57.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="220" PostTypeId="4" CreationDate="2020-05-02T19:00:57.263" Score="0" Body="Refers to the modeling of molecular systems with classical mechanics (e.g. Hooke's Law). " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:30:38.640" LastActivityDate="2020-05-03T00:30:38.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="221" PostTypeId="5" CreationDate="2020-05-02T19:02:43.873" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:02:43.873" LastActivityDate="2020-05-02T19:02:43.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="222" PostTypeId="4" CreationDate="2020-05-02T19:02:43.873" Score="0" Body="Refers to the mathematical model of ferromagnetism in statistical mechanics. The model consists of discrete variables that represent magnetic dipole moments of atomic &quot;spins&quot; that can be in one of two states (+1 or −1)." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T01:56:34.577" LastActivityDate="2020-05-03T01:56:34.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="223" PostTypeId="5" CreationDate="2020-05-02T19:04:03.250" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:04:03.250" LastActivityDate="2020-05-02T19:04:03.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="224" PostTypeId="4" CreationDate="2020-05-02T19:04:03.250" Score="0" Body="Refers to the nuclear geometry optimization of first-order saddle points." OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T01:56:56.207" LastActivityDate="2020-05-03T01:56:56.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="225" PostTypeId="5" CreationDate="2020-05-02T19:05:10.983" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:05:10.983" LastActivityDate="2020-05-02T19:05:10.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="226" PostTypeId="4" CreationDate="2020-05-02T19:05:10.983" Score="0" Body="Refers to the branch of mechanics that deals with the mathematical description of the motion and interaction of subatomic particles, in particular electrons. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:29:19.700" LastActivityDate="2020-05-03T00:29:19.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="227" PostTypeId="5" CreationDate="2020-05-02T19:07:24.907" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:07:24.907" LastActivityDate="2020-05-02T19:07:24.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="228" PostTypeId="4" CreationDate="2020-05-02T19:07:24.907" Score="0" Body="Refers to a model which is treated as infinitely repeating, for example so as to use plane-wave basis functions and capture long-range electrostatic interactions. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:30:28.460" LastActivityDate="2020-05-03T00:30:28.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="229" PostTypeId="5" CreationDate="2020-05-02T19:09:52.357" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:09:52.357" LastActivityDate="2020-05-02T19:09:52.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="230" PostTypeId="4" CreationDate="2020-05-02T19:09:52.357" Score="0" Body="Refers to forces that mediate interaction between molecules, including forces of attraction or repulsion which act between molecules and other types of neighboring particles, e.g. atoms or ions. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:28:57.747" LastActivityDate="2020-05-03T00:28:57.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="231" PostTypeId="5" CreationDate="2020-05-02T19:12:40.847" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:12:40.847" LastActivityDate="2020-05-02T19:12:40.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="232" PostTypeId="4" CreationDate="2020-05-02T19:12:40.847" Score="0" Body="Refers to the thermodynamic quantity representing both enthalpy and entropy factors. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:29:44.520" LastActivityDate="2020-05-03T00:29:44.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="233" PostTypeId="5" CreationDate="2020-05-02T19:21:19.790" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T19:21:19.790" LastActivityDate="2020-05-02T19:21:19.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="234" PostTypeId="4" CreationDate="2020-05-02T19:21:19.790" Score="0" Body="Refers to an atom or molecule with an electronic configuration in a higher than normal energy state than it's ground-state. The excited-state may relax radiatively or non-radiatively. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:30:18.867" LastActivityDate="2020-05-03T00:30:18.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="235" PostTypeId="2" ParentId="169" CreationDate="2020-05-02T20:08:10.183" Score="15" Body="&lt;p&gt;When to include relativistic corrections or modeling of any kind in computational methods is a rather complex one. Full Dirac methods as you asked about (DHF) recapture two important factors, so called scalar relativistic effects, and spin effects. I'll elaborate on each and when including them is important.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Scalar Relativistic Effects&lt;/strong&gt; - This largely describes the so called &quot;mass/velocity&quot; relationship. You may be familiar that as a massive object moves with great velocity it gains mass (so that its velocity can never truly reach or surpass the speed of light). In the case of the electron, its effective velocity is a function of &lt;span class=&quot;math-container&quot;&gt;$Z_\text{eff}$&lt;/span&gt; (in atomic units &lt;span class=&quot;math-container&quot;&gt;$Z_\text{eff}/c \approx v$&lt;/span&gt; or for say hydrogen &lt;span class=&quot;math-container&quot;&gt;$1/137 = 0.007c$&lt;/span&gt;). This is why psuedo-potentials can easily approximate  this effect, generally the largest &lt;span class=&quot;math-container&quot;&gt;$Z_\text{eff}$&lt;/span&gt; is for electrons near the core (1s 2s 2p etc.) but valence electrons experience only a small percentage of the &lt;span class=&quot;math-container&quot;&gt;$Z_\text{eff}$&lt;/span&gt; due to screening. The caveat is you may realize is that d and f orbitals experience much less screening, but are valence orbitals for the transition metals, lanthanides, and actinides. For lighter transition metals the effect is still minor but by Actinides especially, valence electrons can be moving &lt;span class=&quot;math-container&quot;&gt;$0.3-0.5c$&lt;/span&gt;. However, once your valence becomes a p or s again, you no longer have such a significant valence effect. Thus, lead can be fine with a pseudo-potential, where uranium would not be.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR : If you're worried about scalar relativistic effects you're looking at lanthanides and actinides&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Spin effects&lt;/strong&gt; - (this relates to the Pauli principle and electrons having spin&lt;span class=&quot;math-container&quot;&gt;$= \pm 1/2$&lt;/span&gt;). This is a much more complicated issue. Since spin effects are proportional to total atomic spin (or molecular) it depends on the charge and occupancy of your species. For example, molecular oxygen (ground state triplet) has very large spin effects (on the order of 0.5-1.0 kcal/mol), yet molecular nitrogen has almost none. Conversely, Ni(II) (ground state triplet) has abnormally small spin effects, even though it has a similar total spin, the considerations of the orbitals themselves also plays a role. Here is where computational chemists generally start to use (the often reviled) heuristic considerations. In the case of worrisome spin effects, you should either rely on experimental evidence that they are important or otherwise do extensive research to determine if they might play a role. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR: Spin effects are a guessing game, but if this is your area of research, endeavor to be an expert on which things have large spin effects in general.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Finally, materials modeling with relativity! The main consideration here is that DHF and other relativistic methods are QM methods with worse (roughly squared of the base scaling of a non-relativistic method, e.g. DHF is &lt;span class=&quot;math-container&quot;&gt;$O(N^{4-6})$&lt;/span&gt; since HF is &lt;span class=&quot;math-container&quot;&gt;$O(N^{2-3})$&lt;/span&gt; on most computers, though a book might tell you HF is formally &lt;span class=&quot;math-container&quot;&gt;$O(N^4)$&lt;/span&gt;, with computational tricks it's cheaper than that) scaling. Since materials modeling with QM methods is (to my knowledge) still in its adolescence, this makes full or even partial relativistic materials modeling more or less cutting edge science.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR : Send me a copy of your publication if you manage to figure out relativistic materials modeling on a non-super computer.&lt;/strong&gt;     &lt;/p&gt;&#xA;" OwnerUserId="256" LastEditorUserId="7" LastEditDate="2020-05-02T20:58:27.103" LastActivityDate="2020-05-02T20:58:27.103" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="236" PostTypeId="2" ParentId="175" CreationDate="2020-05-02T20:11:51.390" Score="5" Body="&lt;p&gt;I do not have much experience with DFT, but have been digging into DFT in strong fields the last couple of months. The investigation of magnetic properties such as NMR shielding constant and the magnetisability in the context of DFT rely on an explicit dependence on the magnetic field. Magnetic-field DFT, known as BDFT (J. Chem. Theory Comput. 2017, 13, 9, 4089-4100) and current DFT (CDFT, J. Chem. Theory Comput. 2015, 11, 4169−4181) are alternatives to the the standard DFT, where it was shown that cTPSS functional gives modest improvements over GGA level functionals such as PBE.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Hence, you might try to use cTPSS functional and its hybrid forms, i.e. Hybrid-cTPSS (10% HF exchange is added) and Range-separated cTPSS.&lt;/p&gt;&#xA;" OwnerUserId="159" LastActivityDate="2020-05-02T20:11:51.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="237" PostTypeId="2" ParentId="179" CreationDate="2020-05-02T20:58:02.563" Score="13" Body="&lt;p&gt;This can be done using &lt;a href=&quot;https://pymol.org/2/&quot; rel=&quot;noreferrer&quot;&gt;PyMOL&lt;/a&gt; (which, while not free for general use, does have a free student license) via the &lt;code&gt;set_symmetry&lt;/code&gt; argument, as documented &lt;a href=&quot;https://pymolwiki.org/index.php/Set_Symmetry&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. This allows for a user-specified spacegroup and will update the CIF to match.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-02T20:58:02.563" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="238" PostTypeId="5" CreationDate="2020-05-02T21:57:24.897" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T21:57:24.897" LastActivityDate="2020-05-02T21:57:24.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="239" PostTypeId="4" CreationDate="2020-05-02T21:57:24.897" Score="0" Body="Questions relating to functionals in materials science." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:56:26.277" LastActivityDate="2020-05-03T01:56:26.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="240" PostTypeId="5" CreationDate="2020-05-02T21:59:43.853" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T21:59:43.853" LastActivityDate="2020-05-02T21:59:43.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="241" PostTypeId="4" CreationDate="2020-05-02T21:59:43.853" Score="0" Body="Soft questions are for general overview questions." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T00:29:03.167" LastActivityDate="2020-05-03T00:29:03.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="242" PostTypeId="5" CreationDate="2020-05-02T22:02:12.063" Score="0" Body="&lt;p&gt;Phonons are the quasiparticles associated with atomic motion within the harmonic approximation.&lt;/p&gt;&#xA;&lt;p&gt;In the harmonic approximation, the motion of atoms is described locally, taking into account quadratic terms only in the expansion of the total energy around the equilibrium position of atoms. These quadratic terms are typically calculated using finite difference methods (using supercells), or, in the context of density functional theory, linear response methods (density functional perturbation theory).&lt;/p&gt;&#xA;&lt;p&gt;Phonons are described by the relation between their energy (frequency) and their momentum (wave vector). These phonon dispersions capture information such as the speed of sound in a material (slope of acoustic modes) or the spectra observed in infrared and Raman experiments.&lt;/p&gt;&#xA;&lt;p&gt;Phonons also form the building blocks for theories such as those of anharmonic lattice dynamics (to capture phonon-phonon interactions) or electron-phonon coupling (with applications in superconductivity and transport).&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-13T15:32:38.633" LastActivityDate="2020-07-13T15:32:38.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="243" PostTypeId="4" CreationDate="2020-05-02T22:02:12.063" Score="0" Body="Questions related to phonons as applicable to the field of materials science." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T00:13:24.217" LastActivityDate="2020-05-03T00:13:24.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="244" PostTypeId="5" CreationDate="2020-05-02T22:03:06.813" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:03:06.813" LastActivityDate="2020-05-02T22:03:06.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="245" PostTypeId="4" CreationDate="2020-05-02T22:03:06.813" Score="0" Body="Questions related to forcefield development and use in matter modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-02T15:55:53.193" LastActivityDate="2020-07-02T15:55:53.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="246" PostTypeId="5" CreationDate="2020-05-02T22:06:02.227" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:06:02.227" LastActivityDate="2020-05-02T22:06:02.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="247" PostTypeId="4" CreationDate="2020-05-02T22:06:02.227" Score="0" Body="Questions to do with configuration interaction theory and applications." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:11:30.343" LastActivityDate="2020-05-03T01:11:30.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="248" PostTypeId="5" CreationDate="2020-05-02T22:07:21.267" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:07:21.267" LastActivityDate="2020-05-02T22:07:21.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="249" PostTypeId="4" CreationDate="2020-05-02T22:07:21.267" Score="0" Body="Questions associated with relativistic concepts and methods in materials science." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T00:29:53.637" LastActivityDate="2020-05-03T00:29:53.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="250" PostTypeId="5" CreationDate="2020-05-02T22:08:13.583" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:08:13.583" LastActivityDate="2020-05-02T22:08:13.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="251" PostTypeId="4" CreationDate="2020-05-02T22:08:13.583" Score="0" Body="Questions related with quantum Monte Carlo methods." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T00:11:47.197" LastActivityDate="2020-05-03T00:11:47.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="252" PostTypeId="5" CreationDate="2020-05-02T22:09:39.433" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:09:39.433" LastActivityDate="2020-05-02T22:09:39.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="253" PostTypeId="4" CreationDate="2020-05-02T22:09:39.433" Score="0" Body="Please use the &quot;software&quot; tag instead." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-05T20:08:23.467" LastActivityDate="2020-05-05T20:08:23.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="254" PostTypeId="5" CreationDate="2020-05-02T22:12:51.997" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:12:51.997" LastActivityDate="2020-05-02T22:12:51.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="255" PostTypeId="4" CreationDate="2020-05-02T22:12:51.997" Score="0" Body="Questions to do with molecular modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-06-26T21:53:15.247" LastActivityDate="2020-06-26T21:53:15.247" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="256" PostTypeId="5" CreationDate="2020-05-02T22:14:02.097" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:14:02.097" LastActivityDate="2020-05-02T22:14:02.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="257" PostTypeId="4" CreationDate="2020-05-02T22:14:02.097" Score="0" Body="Questions related to mathematical modeling of materials systems." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T00:11:35.077" LastActivityDate="2020-05-03T00:11:35.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="258" PostTypeId="5" CreationDate="2020-05-02T22:15:08.407" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-02T22:15:08.407" LastActivityDate="2020-05-02T22:15:08.407" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="259" PostTypeId="4" CreationDate="2020-05-02T22:15:08.407" Score="0" Body="Questions related to special quasi-random structures." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:11:26.163" LastActivityDate="2020-05-03T01:11:26.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="260" PostTypeId="5" CreationDate="2020-05-02T22:26:12.913" Score="0" Body="&lt;p&gt;Perovskite is a calcium titanium oxide mineral composed of calcium titanate. Its name is also applied to the class of compounds which have the same type of crystal structure as CaTiO₃, known as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Perovskite_(structure)&quot; rel=&quot;nofollow noreferrer&quot;&gt;perovskite structure&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-05-14T16:40:50.640" LastActivityDate="2020-05-14T16:40:50.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="261" PostTypeId="4" CreationDate="2020-05-02T22:26:12.913" Score="0" Body="For questions about the perovskite class of compounds (ABX₃ formula with crystal structure of CaTiO₃). " OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-05-14T16:40:50.640" LastActivityDate="2020-05-14T16:40:50.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="262" PostTypeId="1" CreationDate="2020-05-02T23:37:22.577" Score="12" ViewCount="95" Body="&lt;p&gt;Here I assume that conventional superconductors refer to materials that undergo a superconducting transition at low temperature as described by the Bardeen-Cooper-Schrieffer theory (BCS). For those materials the effective attractive electron-electron interaction is mediated by phonons. How accurately can the superconducting transition temperature be computed from ab initio methods and what are the factors that limit the accuracy of those methods?&lt;/p&gt;&#xA;" OwnerUserId="215" LastEditorUserId="5" LastEditDate="2020-05-02T23:49:46.430" LastActivityDate="2020-05-03T06:20:03.957" Title="What limits the accuracy of ab initio methods in predicting the transition temperature of conventional superconductors?" Tags="|ab-initio-calculations|superconductivity|transition-temperature|bcs-theory|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="263" PostTypeId="1" CreationDate="2020-05-02T23:44:16.100" Score="17" ViewCount="135" Body="&lt;p&gt;Current ab initio methods may not be able to predict the electronic transport properties of cuprate superconductors but can they be used to predict their crystal structure?&#xA;Furthermore those materials are typically polycrystalline and tend to brittle, can ab initio methods predict the details of those properties?&lt;/p&gt;&#xA;" OwnerUserId="215" LastEditorUserId="189" LastEditDate="2020-05-05T13:28:35.183" LastActivityDate="2020-06-27T22:09:43.550" Title="Can ab initio crystal structure methods predict the structure of cuprates from their stoichiometry and quantify the brittleness of those materials?" Tags="|ab-initio-calculations|superconductivity|mechanical-properties|cuprates|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="264" PostTypeId="2" ParentId="174" CreationDate="2020-05-02T23:48:30.607" Score="19" Body="&lt;h2&gt;&lt;strong&gt;TL;DR conical intersections, and polarons. Or any other case when the velocity of the nuclei is faster than the electrons can respond nearly instantaneous&lt;/strong&gt;&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;The long answer requires  a lot of mathematics!&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;h2&gt;&lt;strong&gt;The Mathematical derivation&lt;/strong&gt;&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;The total nuclear and electronic Hamiltonian can be written as &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat{H} = \hat{T}_N + \hat{T}_e +\hat{V}_{ee} + \hat{V}_{NN} + \hat{V}_{eN}$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(\hat{T}_N + \hat{T}_e +\hat{V}_{ee} + \hat{V}_{NN} + \hat{V}_{eN})\Psi = E\Psi $&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where N are the nuclei and e are the electrons. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The BO approximation starts by asking what happens if we we &lt;em&gt;freeze&lt;/em&gt; the nuclei at position  &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_0$&lt;/span&gt; and take &lt;span class=&quot;math-container&quot;&gt;$\Phi(\mathbf{r})\chi(\mathbf{R}_0)$&lt;/span&gt; as an ansatz of the total &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is mathematically much easier to solve because nuclear and electronic wavefunctions can be solved seperately. As we will see below, this is a good approximation in most situations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;First separating the electronic component we have&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(\hat{T}_e  +\hat{V}_{ee} + \hat{V}_{NN} + \hat{V}_{eN})\Phi_k(\mathbf{r};\mathbf{R}_0) = E_{el,k}\Phi_k(\mathbf{r};\mathbf{R}_0) $&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Combining this with the total Hamiltonian and the ansatz &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$[\hat{T}_{N} + E_{el,k}]\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R) = E\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R)$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Rearranging, &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\frac{\hat{T}_{N}\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R)}{\Phi_k(\mathbf{r};\mathbf{R}_0)} +E_{el,k}\chi(R)  = E\chi(R)$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now here is the technical &lt;strong&gt;BO approximation:&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat{T}_{N}\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R)\approx \Phi_k(\mathbf{r};\mathbf{R}_0)\hat{T}_{N}\chi(R)$&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Essentially this says that the kinetic energy of the nuclei doesn't affect the electronic states. Therefore, the nuclear wavefunction can be solved separately&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$[\hat{T}_{N} + E_{el,k}]\chi(R) = E\chi(R)$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thus under the BO approx., &lt;span class=&quot;math-container&quot;&gt;$\chi(\mathbf{R})$&lt;/span&gt; Is solved by solving a nuclear Schrodinger equation where the potential is given by &lt;span class=&quot;math-container&quot;&gt;$E_{el}$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;h2&gt;But why is the B.O. approximation justified?&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;The nuclear kinetic energy operators are derivatives with respect to the nuclei&#xA;&lt;span class=&quot;math-container&quot;&gt;$\hat{T}_{N}\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R)=-\sum_{l=1}^{N_a}\frac{1}{2M_l}\nabla_l^2[\Phi_k(\mathbf{r};\mathbf{R}_0)\chi(R)]$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now doing some painful differentiation this equals&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$-\sum_{l=1}^{N_a}\frac{1}{2M_l} \Phi_k(\mathbf{r};\mathbf{R}_0) \nabla_l^2\chi(\mathbf{r}) - \sum_{l=1}^{N_a}\frac{1}{2M_l}\chi(\mathbf{r})\nabla_l^2\Phi_k(\mathbf{r};\mathbf{R}_0) - \sum_{l=1}^{N_a}\frac{1}{M_l}[\nabla_l\chi(\mathbf{R})][\nabla_l \Phi_k(\mathbf{r};\mathbf{R}_0)  ]$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The BO approx. amounts to assuming that the last two terms on the right hand side are negligible because&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\frac{1}{M_l}[\nabla_l\chi(\mathbf{R})][\nabla_l \Phi_k(\mathbf{r};\mathbf{R}_0)]\approx \frac{1}{2M_l}\chi(\mathbf{R})\nabla_l^2 \Phi_k(\mathbf{r};\mathbf{R}_0) ≪ \frac{1}{2M_e}\chi(\mathbf{R})\nabla_e^2 \Phi_k(\mathbf{r};\mathbf{R}_0) $&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;which is in turn because &#xA;&lt;span class=&quot;math-container&quot;&gt;$\nabla_r \Phi_k (r;R)≈∇_e Φ_k (r;R)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m_e≪M_l$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In other words, because  the mass of an electron is much less than the mass of a nuclei it moves slower and the nuclei can be considered stationary with respect to the motion of the electron. Whew!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, this reveals something &lt;strong&gt;VERY&lt;/strong&gt; interesting. As we can see, it tells us that we can expect breakdown of the BO approximation any time the nuclear derivative of the electronic wavefunction changes rapidly. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example in a &lt;a href=&quot;https://en.wikipedia.org/wiki/Conical_intersection&quot; rel=&quot;noreferrer&quot;&gt;conical intersection&lt;/a&gt;!!!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you can see the electronic wavefunction changes rapidly with nuclear coordinates and it actually has a discontinuity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uo3dU.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uo3dU.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Polarons are another example which have breakdown of the BO approximation and that's simply because the nuclei and electron are so far apart that the electrons cannot respond fast enough to the nuclei.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-03T00:02:01.823" LastActivityDate="2020-05-03T00:02:01.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="265" PostTypeId="1" CreationDate="2020-05-02T23:59:58.983" Score="16" ViewCount="634" Body="&lt;p&gt;It is well known that LDA/GGA often underestimates band gaps. So I wonder if there are any cases where LDA/GGA overestimates the band gap? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In these cases, what is the reason?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="52" LastEditDate="2020-05-03T00:40:57.240" LastActivityDate="2020-05-03T01:39:45.173" Title="Are there any cases where LDA/GGA overestimates band gaps? If so what is the reason?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="266" PostTypeId="1" CreationDate="2020-05-03T00:05:26.300" Score="19" ViewCount="5961" Body="&lt;p&gt;There are many GGA functionals like PW91, PBE, and BLYP. However the most popular functional is the PBE. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is the reason PBE functional so popular?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="52" LastEditDate="2020-05-03T00:40:28.247" LastActivityDate="2020-05-05T08:20:14.530" Title="What makes PBE the most preferred functional over other GGA functionals?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="267" PostTypeId="1" CreationDate="2020-05-03T00:33:14.577" Score="21" ViewCount="279" Body="&lt;p&gt;In the time-dependent Kohn-Sham formalism the effective potential on electrons is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ v_s[\rho(\mathbf{r},t)]=v(\mathbf{r},t)+v_H(\mathbf{r},t)+v_{xc}[\rho(\mathbf{r},t)] $$&lt;/span&gt;&#xA;where, &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r},t)$&lt;/span&gt; is the external TD potential, &lt;span class=&quot;math-container&quot;&gt;$v_H(\mathbf{r},t)$&lt;/span&gt; is the TD Hartree potential and &lt;span class=&quot;math-container&quot;&gt;$v_{xc}[\rho(\mathbf{r},t)]$&lt;/span&gt; is the TD exchange-correlation potential. To get accurate results, we need to find a good approximation to &lt;span class=&quot;math-container&quot;&gt;$v_{xc}$&lt;/span&gt; and a common starting point is the adiabatic approximation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ v_{xc}[\rho(\mathbf{r},t)]= \left.v_{xc}[\rho_0(\mathbf{r})]\right|_{\rho_0(\mathbf{r})=\rho(\mathbf{r},t)} $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$v_{xc}[\rho_0(\mathbf{r})]$&lt;/span&gt; is the static XC potential. As said in Ullrich's TDDFT book,&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;this approximation means that &lt;span class=&quot;math-container&quot;&gt;$v_{xc}[\rho(\mathbf{r},t)]$&lt;/span&gt; becomes exact in the limit where the adiabatic theorem of quantum mechanics applies, i.e., a physical system remains in its instantaneous eigenstate if a perturbation that is acting on it is slow enough.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What is the time scale on which the adiabatic approximation works?&lt;/strong&gt; In other words, &lt;strong&gt;when is this approximation valid?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="85" LastEditDate="2020-05-28T07:43:29.357" LastActivityDate="2022-06-15T09:38:54.500" Title="Validity of adiabatic approximation in TDDFT" Tags="|td-dft|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="268" PostTypeId="2" ParentId="265" CreationDate="2020-05-03T01:24:22.007" Score="13" Body="&lt;p&gt;First, it's worth noting that DFT with both LDA or GGA &lt;strong&gt;underestimate&lt;/strong&gt; band gap and not overestimate it usually. In extreme cases, it predicts that your compound is metal (i.e. no band gap at all)!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The reason is that there is a discontinuity in the derivative of energy with respect to number of electrons. Both LDA and GGA suffers from this problem. One example is band gap of &lt;span class=&quot;math-container&quot;&gt;$\text{La}_{2}\text{CuO}_{4}$&lt;/span&gt; a high temperature superconductor with band gap of 2 eV but LDA, PBE, and PW91 predict it as a metal! ref: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.63.144510&quot; rel=&quot;noreferrer&quot;&gt;Perry et. al.&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More reads here:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.worldscientific.com/doi/10.1142/S0218625X07009499&quot; rel=&quot;noreferrer&quot;&gt;Yakovkin and Dowben&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jz101565j&quot; rel=&quot;noreferrer&quot;&gt;Xiao et. al.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;: If you are looking for a case that DFT with GGA or LDA overestimate the band gap and if you consider PBE (Perdew–Burke-Ernzerhof) exchange-correlation as a part of GGA, yes there are couple of examples that band gap is overestimated for compounds of &lt;span class=&quot;math-container&quot;&gt;$\text{PbSe}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\text{Bi}_{2}\text{Se}_{3}$&lt;/span&gt; because there is a strong spin-orbit coupling in these compounds with small band gap&lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.5b02870&quot; rel=&quot;noreferrer&quot;&gt;4&lt;/a&gt;. &lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-05-03T01:39:45.173" LastActivityDate="2020-05-03T01:39:45.173" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="269" PostTypeId="5" CreationDate="2020-05-03T01:29:13.300" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:29:13.300" LastActivityDate="2020-05-03T01:29:13.300" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="270" PostTypeId="4" CreationDate="2020-05-03T01:29:13.300" Score="0" Body="Questions related to molecular dynamics and molecular modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:56:20.647" LastActivityDate="2020-05-03T01:56:20.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
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  <row Id="272" PostTypeId="4" CreationDate="2020-05-03T01:31:43.190" Score="0" Body="For questions related to superconductivity in materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:56:29.017" LastActivityDate="2020-05-03T01:56:29.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="273" PostTypeId="5" CreationDate="2020-05-03T01:34:27.980" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:34:27.980" LastActivityDate="2020-05-03T01:34:27.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="274" PostTypeId="4" CreationDate="2020-05-03T01:34:27.980" Score="0" Body="For questions related to the history of materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T01:56:31.773" LastActivityDate="2020-05-03T01:56:31.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="275" PostTypeId="5" CreationDate="2020-05-03T01:36:59.547" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:36:59.547" LastActivityDate="2020-05-03T01:36:59.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="276" PostTypeId="4" CreationDate="2020-05-03T01:36:59.547" Score="0" Body="For questions related to theory or application of optimization techniques in matter modeling. If your question is about a specific type of optimization like geometry optimization, we have the &quot;geometry-optimization&quot; and &quot;geometry&quot; tags. Another related tag is the &quot;numerical-convergence&quot; tag." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2021-10-11T17:44:21.170" LastActivityDate="2021-10-11T17:44:21.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="277" PostTypeId="5" CreationDate="2020-05-03T01:38:29.957" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:38:29.957" LastActivityDate="2020-05-03T01:38:29.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="278" PostTypeId="4" CreationDate="2020-05-03T01:38:29.957" Score="0" Body="For all matters related to condensed matter physics." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T12:49:34.267" LastActivityDate="2020-05-03T12:49:34.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="279" PostTypeId="5" CreationDate="2020-05-03T01:39:08.457" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:39:08.457" LastActivityDate="2020-05-03T01:39:08.457" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="280" PostTypeId="4" CreationDate="2020-05-03T01:39:08.457" Score="0" Body="Questions related to phase transitions in matter." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T02:26:36.767" LastActivityDate="2020-05-03T02:26:36.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="281" PostTypeId="5" CreationDate="2020-05-03T01:40:27.597" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:40:27.597" LastActivityDate="2020-05-03T01:40:27.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="282" PostTypeId="4" CreationDate="2020-05-03T01:40:27.597" Score="0" Body="Questions related to universality classes of phase transitions." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T21:30:13.883" LastActivityDate="2020-05-03T21:30:13.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="283" PostTypeId="5" CreationDate="2020-05-03T01:42:18.333" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:42:18.333" LastActivityDate="2020-05-03T01:42:18.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="284" PostTypeId="4" CreationDate="2020-05-03T01:42:18.333" Score="0" Body="Questions concerning educational background in relation to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T02:56:56.523" LastActivityDate="2020-05-03T02:56:56.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="285" PostTypeId="5" CreationDate="2020-05-03T01:44:15.943" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:44:15.943" LastActivityDate="2020-05-03T01:44:15.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="286" PostTypeId="4" CreationDate="2020-05-03T01:44:15.943" Score="0" Body="Questions related to the coordination sphere." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T16:44:54.017" LastActivityDate="2020-05-03T16:44:54.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="287" PostTypeId="5" CreationDate="2020-05-03T01:47:29.507" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:47:29.507" LastActivityDate="2020-05-03T01:47:29.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="288" PostTypeId="4" CreationDate="2020-05-03T01:47:29.507" Score="0" Body="Questions concerning the various electrostatic models of materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T02:04:25.930" LastActivityDate="2020-05-03T02:04:25.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="289" PostTypeId="2" ParentId="267" CreationDate="2020-05-03T01:48:58.863" Score="8" Body="&lt;p&gt;The time scale is related to time derivative of the kinetic energy of electrons defined as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$T(t) = \sum_{i} \int |\nabla \phi_{i}(\mathbf{r},t)|^{2} d^{3} \mathbf{r}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You have this for time-derivative of the kinetic energy:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{d T(t)}{d t} \simeq \frac{T(t=0)}{\tau}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the relaxation time for kinetic energy in the order of period associated with the lowest excitation energy of the system.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-05-03T01:58:03.877" LastActivityDate="2020-05-03T01:58:03.877" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="290" PostTypeId="5" CreationDate="2020-05-03T01:52:06.520" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:52:06.520" LastActivityDate="2020-05-03T01:52:06.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="291" PostTypeId="4" CreationDate="2020-05-03T01:52:06.520" Score="0" Body="Questions related to the heavier elements in the periodic table wrt materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T16:44:44.650" LastActivityDate="2020-05-03T16:44:44.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="292" PostTypeId="5" CreationDate="2020-05-03T01:54:15.063" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:54:15.063" LastActivityDate="2020-05-03T01:54:15.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="293" PostTypeId="4" CreationDate="2020-05-03T01:54:15.063" Score="0" Body="Questions related to the  Kohn-Sham approach to DFT." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T02:26:44.517" LastActivityDate="2020-05-03T02:26:44.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="294" PostTypeId="5" CreationDate="2020-05-03T01:58:38.593" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T01:58:38.593" LastActivityDate="2020-05-03T01:58:38.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="295" PostTypeId="4" CreationDate="2020-05-03T01:58:38.593" Score="0" Body="Questions related to Density Functional Perturbation Theory." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T02:27:00.287" LastActivityDate="2020-05-03T02:27:00.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="296" PostTypeId="5" CreationDate="2020-05-03T02:01:22.487" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T02:01:22.487" LastActivityDate="2020-05-03T02:01:22.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="297" PostTypeId="4" CreationDate="2020-05-03T02:01:22.487" Score="0" Body="For questions regarding the quasi-harmonic-approximation." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-03T03:29:03.933" LastActivityDate="2020-05-03T03:29:03.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="298" PostTypeId="5" CreationDate="2020-05-03T02:05:37.880" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T02:05:37.880" LastActivityDate="2020-05-03T02:05:37.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="299" PostTypeId="4" CreationDate="2020-05-03T02:05:37.880" Score="0" Body="Questions concerning molecular and solid vibrational modes." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-05-06T17:28:47.317" LastActivityDate="2020-05-06T17:28:47.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="300" PostTypeId="5" CreationDate="2020-05-03T02:10:28.347" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T02:10:28.347" LastActivityDate="2020-05-03T02:10:28.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="301" PostTypeId="4" CreationDate="2020-05-03T02:10:28.347" Score="0" Body="Questions related to vibrational entropy of lattice materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T00:01:41.513" LastActivityDate="2020-05-04T00:01:41.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="302" PostTypeId="5" CreationDate="2020-05-03T02:11:14.580" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T02:11:14.580" LastActivityDate="2020-05-03T02:11:14.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="303" PostTypeId="4" CreationDate="2020-05-03T02:11:14.580" Score="0" Body="Questions related to the heat capacity of materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T00:02:07.440" LastActivityDate="2020-05-04T00:02:07.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="304" PostTypeId="2" ParentId="263" CreationDate="2020-05-03T04:07:33.143" Score="8" Body="&lt;p&gt;Yes, indeed it's done by using plane-wave ultrasoft pseudo-potential technique and GGA exchange-correlation. See here: &lt;a href=&quot;https://www.tandfonline.com/doi/pdf/10.1080/23311940.2016.1231361?needAccess=true&quot; rel=&quot;noreferrer&quot;&gt;https://www.tandfonline.com/doi/pdf/10.1080/23311940.2016.1231361?needAccess=true&lt;/a&gt; . Particularly in this paper authors were able to calculate mechanical properties of Barium cuprate (&lt;span class=&quot;math-container&quot;&gt;$\text{BaCuO}_{2}$&lt;/span&gt;) superconductor and they find indeed it's brittle based on the definition of &lt;span class=&quot;math-container&quot;&gt;$\frac{G}{B} &amp;gt; 0.5$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; is shear modulus and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; is the bulk modulus both of them calculated from DFT.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-03T04:07:33.143" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="305" PostTypeId="1" AcceptedAnswerId="2366" CreationDate="2020-05-03T04:59:49.423" Score="17" ViewCount="261" Body="&lt;p&gt;Many reactivity descriptors can be obtained from ground state (or static) DFT as energy derivatives respect to the number of electrons, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, and the external potential, &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt;, like chemical potential, &lt;span class=&quot;math-container&quot;&gt;$\mu=\left(\frac{\partial E}{\partial N}\right)_{v(\mathbf{r})}$&lt;/span&gt;, global hardness, &lt;span class=&quot;math-container&quot;&gt;$\eta=\left(\frac{\partial^2 E}{\partial N^2}\right)_{v(\mathbf{r})}$&lt;/span&gt;, Fukui function, &lt;span class=&quot;math-container&quot;&gt;$f(\mathbf{r})=\left(\frac{\partial^2 E}{\partial N\delta v(\mathbf{r})}\right)=\left(\frac{\partial\rho(\mathbf{r})}{\partial N}\right)_{v(\mathbf{r})}$&lt;/span&gt; and the linear response function, &lt;span class=&quot;math-container&quot;&gt;$\chi(\mathbf{r},\mathbf{r}')=\left(\frac{\delta^2 E}{\delta v(\mathbf{r})\delta v(\mathbf{r}')}\right)_N=\left(\frac{\delta\rho(\mathbf{r})}{\delta v(\mathbf{r}')}\right)_N$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My question is about the time-dependent regime. For instance, in the definition of &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; the derivatives are with &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt; constant, however, in TDDFT the external potential changes with time. Also, for &lt;span class=&quot;math-container&quot;&gt;$f(\mathbf{r})$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\chi(\mathbf{r},\mathbf{r}')$&lt;/span&gt;, the derivatives should be, presumably, respect to &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r},t)$&lt;/span&gt;, i.e., they evolve in time. The latter interpretation seems rather evident because the electrons are subject to a time-dependent potential and, thus, the electron density changes with time and also its derivatives.&lt;/p&gt;&#xA;&lt;p&gt;Considering that local properties could change through a, for instance, chemical reaction, I suppose that knowing the time evolution of Fukui functions or the linear response function should give some insight about what is happening, from another perspective. But this topic doesn't seems to be very attractive due to the short literature that exist and I don't understand the reason.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can these descriptors be calculated in a time-dependent scheme? Do global descriptors (&lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt;) need a redefinition? Is there a problem with TD reactivity indices in general?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="10" LastEditDate="2020-09-10T13:48:12.833" LastActivityDate="2020-09-25T00:31:52.330" Title="How can reactivity indices be calculated in a time-dependent scheme?" Tags="|density-functional-theory|td-dft|conceptual-dft|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="306" PostTypeId="2" ParentId="176" CreationDate="2020-05-03T06:09:16.727" Score="9" Body="&lt;p&gt;I list these 17 constraints directly from 2015 &lt;a href=&quot;https://journals.aps.org/prl/supplemental/10.1103/PhysRevLett.115.036402/SCAN_Sup.pdf&quot; rel=&quot;noreferrer&quot;&gt;Sun et. al. paper&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For exchange potential:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Negativity.&lt;/li&gt;&#xA;&lt;li&gt;Spin-scaling.&lt;/li&gt;&#xA;&lt;li&gt;Uniform density scaling.&lt;/li&gt;&#xA;&lt;li&gt;Fourth-order gradient expansion.&lt;/li&gt;&#xA;&lt;li&gt;Non-uniform density scaling.&lt;/li&gt;&#xA;&lt;li&gt;Tight bounds for two-electron densities.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;For correlation potential:&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;7&quot;&gt;&#xA;&lt;li&gt;Non-positivity.&lt;/li&gt;&#xA;&lt;li&gt;Second-order gradient expansion.&lt;/li&gt;&#xA;&lt;li&gt;Uniform density scaling to the high-density limit.&lt;/li&gt;&#xA;&lt;li&gt;Uniform density scaling to the low-density limit.&lt;/li&gt;&#xA;&lt;li&gt;Zero correlation energy for any one-electron spin-polarized density.&lt;/li&gt;&#xA;&lt;li&gt;Non-uniform density scaling.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;For both exchange and correlation potentials:&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;13&quot;&gt;&#xA;&lt;li&gt;Size extensively.&lt;/li&gt;&#xA;&lt;li&gt;General Lieb-Oxford bound.&lt;/li&gt;&#xA;&lt;li&gt;Weak dependence upon relative spin polarization in the low-density limit.&lt;/li&gt;&#xA;&lt;li&gt;Static linear response of the uniform electron gas.&lt;/li&gt;&#xA;&lt;li&gt;Lieb-Oxford bound for two-electron densities.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Some of these conditions are based on properties of exact &lt;span class=&quot;math-container&quot;&gt;$E_{\text{XC}}[n(\mathbf{r})]$&lt;/span&gt; for example we know that correlation potential should be self-correlation free for one-electron (constraint 11), etc. Keep in mind that there are infinitely many ways to satisfy these conditions and it's not guaranteed if an exchange-correlation model satisfies these constraints, it's suitable for all applications.   &lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-05-03T06:15:12.197" LastActivityDate="2020-05-03T06:15:12.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="307" PostTypeId="2" ParentId="262" CreationDate="2020-05-03T06:20:03.957" Score="1" Body="&lt;p&gt;I am not an expert in superconductivity but I believe that the crucial interaction that dictate the conventional superconductivity is the phonon-electron interaction which in the language of quantum chemistry can be regarded as a non-adiabatic nuclear dynamics which is beyond Bohr-Oppenheimer approximation. And I do not think conventional electronic calculations incorporate this effect.&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2020-05-03T06:20:03.957" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="308" PostTypeId="1" AcceptedAnswerId="681" CreationDate="2020-05-03T06:29:17.783" Score="19" ViewCount="743" Body="&lt;p&gt;Since the effect of spin-orbit coupling plays an important role in many transition metal complexes, what are the common methods to incorporate the effect of spin-orbit coupling?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="49" LastEditDate="2020-05-10T22:56:07.930" LastActivityDate="2020-06-09T06:23:43.547" Title="How to incorporate the effect of spin-orbit coupling in electronic structure calculation" Tags="|electronic-structure|relativistic|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="309" PostTypeId="1" CreationDate="2020-05-03T06:34:26.543" Score="3" ViewCount="56" Body="&lt;p&gt;For electron with large kinetic energy, one needs to introduce Dirac equation for relativistic correction. In what type of systems these relativistic effects is non-negligible? &lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="37" LastEditDate="2020-05-03T06:49:02.680" LastActivityDate="2020-05-03T06:49:02.680" Title="In what kind of system, relativistic effect is non-negligible?" Tags="|electronic-structure|" AnswerCount="0" CommentCount="2" ClosedDate="2020-05-03T13:33:57.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="310" PostTypeId="2" ParentId="127" CreationDate="2020-05-03T09:01:26.420" Score="9" Body="&lt;p&gt;I am quoting from the book &lt;a href=&quot;https://books.google.co.in/books?id=FzOTAwAAQBAJ&amp;amp;printsec=frontcover&amp;amp;source=gbs_ge_summary_r&amp;amp;cad=0#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;Materials Modelling Using Density Functional Theory: Properties and Predictions&lt;/a&gt; by Feliciano Giustino&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;How do we decide which wavefunctions should be considered ‘core’ and which ones ‘valence’ states? As a rule of thumb, in the context of DFT calculations the ‘valence’ corresponds to the outermost shell of the atom in the periodic table; for example, for tungsten we would have 6s&lt;sup&gt;2&lt;/sup&gt;5d&lt;sup&gt;4&lt;/sup&gt;. However, there are cases where one might need to include more electronic states in the set of ‘valence electrons’. &lt;strong&gt;For example, in the case of bismuth it is important to describe on an equal footing both the nominal valence shell, 6s&lt;sup&gt;2&lt;/sup&gt;6p&lt;sup&gt;3&lt;/sup&gt; , and the ‘semi-core’ shell, 5d&lt;sup&gt;10&lt;/sup&gt;&lt;/strong&gt;. In practice the distinction between core and valence is not a strict one, and depends on the level of accuracy that one is trying to achieve. &lt;strong&gt;When in doubt, an inspection of the spatial extent of all the atomic wavefunctions  represents the first point of call for identifying core and valence states.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-05-03T09:01:26.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="311" PostTypeId="2" ParentId="263" CreationDate="2020-05-03T10:28:17.847" Score="12" Body="&lt;p&gt;Check the &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX method&lt;/a&gt; which is mainly a crystal structure prediction code. It uses the &lt;a href=&quot;https://towardsdatascience.com/introduction-to-evolutionary-algorithms-a8594b484ac&quot; rel=&quot;nofollow noreferrer&quot;&gt;evolutionary algorithm&lt;/a&gt; to find the global minimum on the potential energy surface of a material, thereby predicting its crystal structure in the equilibrium state. It works with even a bare-minimum input like the composition of the material.&lt;/p&gt;&#xA;&lt;p&gt;This &lt;a href=&quot;https://search.proquest.com/openview/e9b07b5b5014ab5672328c628c6e3412/1?pq-origsite=gscholar&amp;amp;cbl=18750&amp;amp;diss=y&quot; rel=&quot;nofollow noreferrer&quot;&gt;dissertation&lt;/a&gt; (&lt;code&gt;Esfahani, M.M.D., 2017. Novel Superconducting Phases of Materials under Pressure by Evolutionary Algorithm USPEX (Doctoral dissertation, State University of New York at Stony Brook)&lt;/code&gt;) seems useful.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-06-27T22:09:43.550" LastActivityDate="2020-06-27T22:09:43.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="312" PostTypeId="1" CreationDate="2020-05-03T10:57:40.940" Score="17" ViewCount="387" Body="&lt;p&gt;Following the &lt;a href=&quot;https://materials.stackexchange.com/questions/175/appropriate-functionals-for-prediction-of-nmr-spectra-of-transition-metal-compou&quot;&gt;previous&lt;/a&gt; discussion on DFT in strong fields, I would like to ask about the difference between those two alternatives (BDFT and CDFT). By CDFT I do not mean (constrained DFT, but current DFT). The mathematical background of these two can be found in:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Vignale, et al., Density-functional theory in strong magnetic fields, Phys. Rev. Lett. 1987, 59, 2360.&lt;/li&gt;&#xA;&lt;li&gt;Grayce, et al., Magnetic-field density functional theory, Phys. Rev. A, 1994, 50, 3089.&lt;/li&gt;&#xA;&lt;li&gt;Tellgren, et al., Choice of basic variables in current-density functional theory, Phys. Rev. A 2012, 86, 062506.&lt;/li&gt;&#xA;&lt;li&gt;Bates, et al., Harnessing the meta-generalised gradient approximation for time-dependent density functional theory, J. Chem. Phys. 2012, 137, 164105.&lt;/li&gt;&#xA;&lt;li&gt;Furness, et al., Current density functional theory using meta-generalised gradient exchange-correlation functionals, J. Comp. Theory Comput. 2015, 11, 4169.&lt;/li&gt;&#xA;&lt;li&gt;Reimann, et al., Magnetic-field density functional theory (BDFT): Lessons from the adiabatic connection, J. Comp. Theory Comput. 2017, 13, 4089.&lt;/li&gt;&#xA;&lt;li&gt;Reimann, et al., Kohn-Sham energy decomposition for molecules in a magnetic field, Mol. Phys. 2018.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To summarise, Kohn-Sham CDFT has the advantages that it is universal (can be applied for any magnetic field / vector potential &lt;strong&gt;A&lt;/strong&gt;), a non-perturbative implementation can be applied to arbitrary field strengths, and functionals can be generated from existing meta-GGAs. However, functional dependence on the physical current, &lt;strong&gt;j&lt;/strong&gt;_p is not widely studied, hence, new functionals are required.&lt;/p&gt;&#xA;&lt;p&gt;What about the advantages (and differences) of BDFT?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="5" LastEditDate="2020-06-20T16:13:37.720" LastActivityDate="2020-07-05T12:35:43.037" Title="What is the difference between BDFT and CDFT (magnetic-field DFT and current DFT)?" Tags="|density-functional-theory|reference-request|magnetic-field|cdft|bdft|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="313" PostTypeId="2" ParentId="308" CreationDate="2020-05-03T11:09:15.910" Score="18" Body="&lt;p&gt;The inclusion of spin-orbit coupling in electronic structure calculations is done by including the interaction between the electron-spin and the orbital angular momentum in the Hamiltonian. Such interaction is described according to the spin-orbit Hamiltonian defined as follows,&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}_\mathrm{SO} = \frac{1}{2m_\mathrm{e}\mathrm{c}^2} \frac{1}{r} \left( \frac{\partial{V}}{\partial{r}} \right) \hat{L} \cdot \hat{S}, &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the Coulombic potential of the electron in the field of the atom. &lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="49" LastEditDate="2020-05-10T22:57:29.033" LastActivityDate="2020-05-10T22:57:29.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="314" PostTypeId="1" AcceptedAnswerId="319" CreationDate="2020-05-03T11:14:44.193" Score="12" ViewCount="245" Body="&lt;p&gt;I have downloaded POSCAR file for &quot;WS2&quot; from &quot;materials project website&quot;. I want to do lattice optimization, draw &quot;Energy versus lattice parameters&quot; curves, and calculate Bulk modulus through Birch–Murnaghan equation of state.&#xA;So, could you please show how to do that, and if there is a script that I can rely on ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="85" LastEditDate="2020-05-03T16:41:02.690" LastActivityDate="2020-05-03T16:48:36.143" Title="Hexagonal lattice optimization" Tags="|density-functional-theory|vasp|optimization|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="315" PostTypeId="1" AcceptedAnswerId="323" CreationDate="2020-05-03T14:03:04.380" Score="18" ViewCount="1510" Body="&lt;p&gt;How would one obtain the phonon dispersion curve from a molecular dynamics simulation trajectory? What are the steps involved? Are there any packages that does this? If so, please mention them.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2022-06-03T12:29:47.373" Title="Computing phonon dispersion from molecular dynamics simulations?" Tags="|software|molecular-dynamics|phonons|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="316" PostTypeId="1" CreationDate="2020-05-03T14:45:18.303" Score="16" ViewCount="788" Body="&lt;p&gt;Any time you start a new DFT calculation, it is recommended to do a convergence test. The parameters to include in the tests vary depending on the DFT implementation, i.e. plane-waves, Gaussian basis set, numerical orbitals, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The idea is to choose a property, in general the energy of the system, and then vary a parameter in order to obtain the property that converges to a value (attaining a plateau).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The usual parameters used in convergence tests are mesh cut-off, k-points, energy cut-off, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Using bad parameters, in general, gave bad results.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: if I achieve convergence for a system A formed by atoms X, Y, and Z, do I need to repeat the convergence test for a new system, B, formed by the same atoms or I just could use the same parameters for system A?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-03T17:17:33.023" LastActivityDate="2020-05-13T13:20:31.093" Title="In DFT, if I complete a convergence test once, then want to study a different system with the same atoms, do I have to do a new convergence test?" Tags="|density-functional-theory|convergence-test|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="317" PostTypeId="1" CreationDate="2020-05-03T14:57:34.287" Score="13" ViewCount="992" Body="&lt;p&gt;As I pointed out in the other question &lt;a href=&quot;https://materials.stackexchange.com/questions/316/convergence-test-i-same-atoms-and-different-structures&quot;&gt;Convergence test I: same atoms and different structures&lt;/a&gt;, each time you start a DFT calculation you need to do a convergence test.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Normally, we use the system energy, but this energy &lt;em&gt;per se&lt;/em&gt;, is meaningless.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The question now is: What is the adequate property to do the convergence test? Should we use another calculated property instead of the system energy?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="36" LastEditDate="2020-05-03T17:54:33.417" LastActivityDate="2020-05-03T17:57:05.437" Title="Which property should be used for a DFT convergence test? Is energy always the best, or should convergence be tested for a different property?" Tags="|density-functional-theory|convergence-test|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="318" PostTypeId="1" AcceptedAnswerId="361" CreationDate="2020-05-03T15:33:17.217" Score="31" ViewCount="1870" Body="&lt;p&gt;At first I posted &lt;a href=&quot;https://chemistry.stackexchange.com/q/130712/89908&quot;&gt;this question&lt;/a&gt; in chemistry.stackexchange.com, before materials.stackexchange.com was launched in beta. As it went unaswered, I'm giving a try here.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have some calculations results I runned previously using Pople's basis sets, mostly 6-311+G(d), under Gaussian09. These days I read some texts on Frank Jensen's family of polarization consistent, segmented basis sets, optimized for DFT (pcseg-0, pcseg-1, pcseg-2, pcseg-3, pcseg-4 and the respective augmented versions). Now I'm thinking about trying to reproduce my results using Jensen's basis set family and Gamess-US.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Said that, I'm not sure about the correspondence between the two sets. I understand in Pople's basis sets, for light elements (first 3 periods of the periodic table) it's common to see people using double zeta(DZ) 3-21G for rough calculations, and either double zeta 6-31G or triple zeta(TZ) 6-311G for more precise work. Both 6-31G and 6-311G can have up to two polarization functions (or none) and up to two diffuse functions (or none) associated, resulting in 2x3x3 = 12 combinations between them (not counting heavier elements, that would require f polarization orbitals). In the table 5 of &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119356059.ch3&quot; rel=&quot;noreferrer&quot;&gt;Nagy, Balazs, and Frank Jensen. “Basis Sets in Quantum Chemistry.” Reviews in Computational Chemistry (2017): 93–150. Print.&lt;/a&gt;, they group together 3-21G and pcseg-0; 6-31G(d), cc-pVDZ and pcseg-1; and 6-311G(2df), cc-pVTZ and pcseg-2. So I assume each basis set inside these 3 groups to be equivalent (but not sure). As pcseg-2 is the only triple zeta option, despite already falling in the range of f-polarized basis, I suppose that, to map these 12 Pople's basis into the respective Jensen's basis, I need some combination between pcseg-0, pcseg-1, pcseg-2, aug-pcseg-0, aug-pcseg-1 and aug-pcseg-2 over H and heavier atoms (6x6 = 36 possibilities). For me it's not trivial to choose which of the 36 Jensen's possibilities in this range best match the 12 Pople's ones not explicitly cited on the paper. My guess at the closest mapping between the 2 sets is as follow:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;Type    POPLE's         DUNNING     JENSEN'S CLOSEST&#xA;DZ      3-21G                       pcseg-0 on all atoms?&#xA;DZ      6-31G                       ?&#xA;DZP     6-31G(d)        cc-PVDZ     pcseg-0 on H, pcseg-1 on heavier?&#xA;DZP     6-31+G(d)                   pcseg-0 on H, aug-pcseg-1 on heavier?                   &#xA;DZP     6-31G(d,p)                  pcseg-1 on H, pcseg-1 on heavier?&#xA;DZP     6-31+G(d,p)                 pcseg-1 on H, aug-pcseg-1 on heavier?&#xA;DZP     6-31++G(d,p)                aug-pcseg-1 on H, aug-pcseg-1 on heavier?&#xA;TZ      6-311G                      ?&#xA;TZ      6-311+G                     ?&#xA;TZP     6-311+G(d)                  pcseg-0 on H, aug-pcseg-2 on heavier?&#xA;TZP     6-311G(d,p)                 pcseg-1 on H, pcseg-2 on heavier?                 &#xA;TZP     6-311+G(d,p)                pcseg-1 on H, aug-pcseg-2 on heavier?&#xA;TZP     6-311++G(d,p)               aug-pcseg-1 on H, aug-pcseg-2 on heavier?&#xA;TZP     6-311G(2df)     cc-PVTZ     pcseg-2 on all&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Is my reasoning sound and the proposed equivalence table correct, or did I get it all wrong? If wrong, could somebody please give the correct mapping from Pople's traditional basis sets to Jensen's optimized ones?&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-06-01T15:28:06.507" LastActivityDate="2020-12-07T18:34:22.923" Title="Approximate equivalence table between Pople's basis sets and Jensen's DFT optimized polarization consistent basis sets (pcseg-n)" Tags="|density-functional-theory|basis-sets|computational-chemistry|quantum-chemistry|from-chem-se|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="319" PostTypeId="2" ParentId="314" CreationDate="2020-05-03T16:19:11.503" Score="9" Body="&lt;p&gt;This can be readily done using the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/eos/eos.html&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; (ASE), if you are comfortable with Python. A tutorial for this exact purpose is described &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/eos/eos.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Another example using ASE can be found in Section 4.3 of Kitchin's &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.html#orgheadline23&quot; rel=&quot;noreferrer&quot;&gt;&quot;Modeling materials using density functional theory&quot;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-03T16:48:36.143" LastActivityDate="2020-05-03T16:48:36.143" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="320" PostTypeId="2" ParentId="317" CreationDate="2020-05-03T16:25:06.230" Score="11" Body="&lt;p&gt;The question you should be asking yourself is: what properties do I want to compute? You, naturally, want to make sure that property is converged. For instance, if you wish to compute the band gap, then it makes more sense to confirm that your band gap is converged with your given settings. The band gap could very well be more (or less) sensitive to a given parameter than the absolute energy, in which case your convergence test on the absolute energy may not translate well for the property of interest. There is no inherent reason to do a convergence test on the absolute energy -- it is just a commonly computed property and generally will indicate that other properties are well-converged, but that's certainly not a guarantee. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As an aside, there may be cases where converging the absolute energy is recommended but not required. If you are computing a reaction energy or any other energy for that matter, what you are often reporting is an &lt;em&gt;energy difference&lt;/em&gt;. In many cases, there is significant cancellation of error that occurs, which means that the energy difference will often converge faster than the absolute energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Interestingly enough, there are even subtle cases with certain codes where it is impossible to converge the absolute energy. I found this to be the case in VASP when using the &lt;code&gt;LASPH&lt;/code&gt; &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LASPH&quot; rel=&quot;noreferrer&quot;&gt;flag&lt;/a&gt;, which determines whether to include non-spherical contributions related to the gradient of the density in the projector-augmented wave spheres. When enabling &lt;code&gt;LASPH&lt;/code&gt;, the absolute energy never converges with respect to increasing plane-wave kinetic energy cutoff because the non-spherical contribution is always changing. In this case, the only option is to check that an energy difference is converged.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-03T16:43:15.593" LastActivityDate="2020-05-03T16:43:15.593" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="321" PostTypeId="2" ParentId="317" CreationDate="2020-05-03T16:26:16.133" Score="7" Body="&lt;p&gt;The hydrostatic pressure on a given unit cell is an experimentally observable property very sensitive to numerical precision. If this property is converged many other less sensitive properties will be converged too. Hence checking for convergence of pressure will be a better bet to make sure that other properties are also converged&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://compmatphys.epotentia.com/wp-content/uploads/2020/04/project_03b_convergence-testing_no-GUI.pdf&quot; rel=&quot;noreferrer&quot;&gt;Reference&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://compmatphys.epotentia.com/&quot; rel=&quot;noreferrer&quot;&gt;Source&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="36" LastEditDate="2020-05-03T17:57:05.437" LastActivityDate="2020-05-03T17:57:05.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="322" PostTypeId="2" ParentId="316" CreationDate="2020-05-03T16:39:33.523" Score="12" Body="&lt;p&gt;As you might expect, the answer is: it depends. It really boils down to how different the two systems are. There are obvious cases where the settings will &lt;em&gt;not&lt;/em&gt; transfer between two systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The trivial example (at least for plane-wave, periodic DFT) is to consider System A as having the same elements as System B, but the former is a &lt;span class=&quot;math-container&quot;&gt;$10\times10\times10$&lt;/span&gt; unit cell of the latter. In this case, the number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points required to achieve convergence in System B is going to be much higher than that of System A, and a convergence test in terms of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points on System A will not be appropriate for System B.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To get around this, you can check to see what the ideal &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points per (reciprocal) atom is for System A and then use that same value for System B. In this case, the number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points would be adjusted by the number of atoms in the system. For instance, in &lt;a href=&quot;https://pymatgen.org/pymatgen.io.vasp.inputs.html#pymatgen.io.vasp.inputs.Kpoints.automatic_density&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt;'s &lt;code&gt;automatic_density()&lt;/code&gt; function, you could tweak &lt;code&gt;kppa&lt;/code&gt; for one system and then see if that works well for another. Same thing for the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point generator from the &lt;a href=&quot;http://muellergroup.jhu.edu/K-Points.html&quot; rel=&quot;noreferrer&quot;&gt;Mueller group&lt;/a&gt;, where &lt;code&gt;KPPRA&lt;/code&gt; is one of the key input arguments. So, in this example, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points per number of atoms will likely lead to transferable convergence between systems of different sizes, but the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points themselves will likely not.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you specifically meant both the same types of atoms and the same number of atoms per cell, the above answer still holds. What if one system has a really small lattice constant whereas the other system does not? You'll need more &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points along the small lattice constant dimension. Most &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point generation codes will account for this in determining how to distribute the given &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; and &lt;a href=&quot;http://oqmd.org/&quot; rel=&quot;noreferrer&quot;&gt;Open Quantum Materials Database&lt;/a&gt; both rely on the assumption that, generally speaking, the used parameters will be appropriate for many of the materials under investigation. You can see several examples of this evaluation in the 2011 &lt;em&gt;Comput. Mater. Sci&lt;/em&gt; paper by &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0927025611001133&quot; rel=&quot;noreferrer&quot;&gt;Jain and coworkers&lt;/a&gt;. Of course, there's no guarantee that a given plane-wave kinetic energy cutoff, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid, and so on will be applicable to all materials, so it helps to be a bit conservative in your choice.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-03T16:59:20.327" LastActivityDate="2020-05-03T16:59:20.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="323" PostTypeId="2" ParentId="315" CreationDate="2020-05-03T17:26:59.267" Score="15" Body="&lt;p&gt;You are basically looking for finding phonon frequencies with respect to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; the scattering vector in reciprocal space. From fluctuation-dissipation theory, the force constants of the system in the reciprocal space is given by:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Phi_{k\alpha,k^{'}\beta}(\mathbf{q}) = k_{B}T \mathbf{G}^{-1}_{k\alpha,k^{'}\beta}(\mathbf{q})$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{G}$&lt;/span&gt; is the green function defined as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{G}_{k\alpha,k^{'}\beta}(\mathbf{q}) = \langle \mathbf{u}_{k\alpha}(\mathbf{q}) \cdot \mathbf{u}_{k^{'}\beta}^{*}(\mathbf{q}) \rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle...\rangle$&lt;/span&gt; is the ensemble average and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_{k\alpha}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; component of atomic displacement for &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-th atom:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{u}_{k\alpha}(\mathbf{q}) = \sum_{\ell}\mathbf{u}_{k\alpha}^{\ell}\exp{(i\mathbf{q}\cdot \mathbf{r}_{\ell})}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;We could calculate Green function based on the instantaneous position of atoms (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;) and their ensemble average as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{G}_{k\alpha,k^{'}\beta}(\mathbf{q}) = \langle \mathbf{R}_{k\alpha}(\mathbf{q}) \cdot \mathbf{R}^{*}_{k^{'}\beta}(\mathbf{q})\rangle - \langle \mathbf{R}\rangle_{k\alpha} (\mathbf{q}) \cdot \langle \mathbf{R} \rangle^{*}_{k^{'}\beta}(\mathbf{q})$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now the dynamical matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{D}$&lt;/span&gt; is calculated as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{D}_{k\alpha,k^{'}\beta}(\mathbf{q}) = (m_{k}m_{k^{'}})^{-\frac{1}{2}} \Phi_{k\alpha,k^{'}\beta}(\mathbf{q})$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The eigenvalues of this matrix are phonon frequencies at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; and if you plot them versus &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; you would get the phonon dispersion curve. This is done in LAMMPS by using &lt;code&gt;fix phonon&lt;/code&gt; command.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-03T17:26:59.267" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="324" PostTypeId="1" AcceptedAnswerId="325" CreationDate="2020-05-03T19:09:17.890" Score="19" ViewCount="428" Body="&lt;p&gt;Now a days, due to some &lt;em&gt;publish-or-perish&lt;/em&gt; politics that gives place to many cases of plagiarism and fake data/results, some journals are asking to submit (and share) the data used in the research. In this way, not only the referees can take a careful look to the data but also any reader can use it and reproduce your results.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Following this idea, the &lt;a href=&quot;https://zenodo.org/&quot; rel=&quot;noreferrer&quot;&gt;Zenodo&lt;/a&gt; server (built and operated by CERN) permit the storage of your research data.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I wonder what other options exist and what advantages they have over Zenodo?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2020-06-15T18:59:46.607" LastActivityDate="2020-06-15T18:59:46.607" Title="What are some servers that are able to host and share our research data?" Tags="|open-source|databases|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="325" PostTypeId="2" ParentId="324" CreationDate="2020-05-03T19:56:38.917" Score="19" Body="&lt;p&gt;First, there are general-use repositories that are not specific to materials modeling.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://zenodo.org/&quot; rel=&quot;noreferrer&quot;&gt;Zenodo&lt;/a&gt;. Like several other approaches, each project gets a permanent DOI associated with it, and new versions can be uploaded with the same unique parent DOI for the project and version-specific DOI. One major upside of Zenodo is that it is managed by CERN, which is likely to be around for a while. They also &lt;a href=&quot;https://help.zenodo.org/&quot; rel=&quot;noreferrer&quot;&gt;guarantee&lt;/a&gt; that should operations be ceased, they will transfer all data to a separate repository. Since the DOI is static but what it links to can be changed, this does not impact the findability of the data. One downside is that there is currently a 50 GB per-record file size limit, which may not be suitable for large-scale materials modeling.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://figshare.com/&quot; rel=&quot;noreferrer&quot;&gt;Figshare&lt;/a&gt;. It operates in a very similar way with regards to have project- and version-specific DOIs, although they make no public claims about how they will ensure the longevity of the data. One major benefit of Figshare compared to Zenodo is that there are no project-specific file size limits (there is just a 5 TB limit on a per-file basis). Otherwise, the two platforms are very similar aside from user-interface.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://datadryad.org/stash&quot; rel=&quot;noreferrer&quot;&gt;Dryad&lt;/a&gt;. Also operates similarly as the above but specifically has partnered with various publishers, such as Wiley, RSC, and PLOS so there are some ease-of-use features if you're submitting a manuscript to one of those journals and wish to also deposit the data.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Of course, there are other field-agnostic platforms to host data, such as on &lt;a href=&quot;https://github.com/&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt; or &lt;a href=&quot;https://about.gitlab.com/&quot; rel=&quot;noreferrer&quot;&gt;GitLab&lt;/a&gt; or &lt;a href=&quot;https://bitbucket.org/product&quot; rel=&quot;noreferrer&quot;&gt;Bit-bucket&lt;/a&gt;, but in my opinion these are not suitable for ensuring the longevity of data. The repositories can be deleted at any time, and there is no associated DOI.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Then there are topic-specific platforms. For materials modeling in particular, some big names are:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.iochem-bd.org/&quot; rel=&quot;noreferrer&quot;&gt;ioChem-BD&lt;/a&gt;. This platform is meant for hosting computational chemistry results. Each data repository gets a DOI. You can read more about it in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ci500593j&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, although it is slightly outdated now. There is also this &lt;a href=&quot;https://www.nature.com/articles/s41929-018-0176-4&quot; rel=&quot;noreferrer&quot;&gt;perspective&lt;/a&gt; on hosting data for catalysis research, written by the folks of ioChem-BD.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://qcarchive.molssi.org/&quot; rel=&quot;noreferrer&quot;&gt;QCArchive&lt;/a&gt;. This is a repository fulfilling a similar niche as ioChem-BD, hosting data for computational chemistry simulations and making sure the data is findable while also providing interactive data visualizations. This is mainly meant for molecules. You can read more about the QCArchive in &lt;a href=&quot;https://chemrxiv.org/articles/The_MolSSI_QCArchive_Project_An_Open-Source_Platform_to_Compute_Organize_and_Share_Quantum_Chemistry_Data/11908356/1&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://nomad-repository.eu/&quot; rel=&quot;noreferrer&quot;&gt;NOMAD repository&lt;/a&gt;. This repository is also specifically suited for materials modeling (less so for computational chemistry). Once again, all projects get a DOI, and there is an API that can be used to interface with the data hosted on NOMAD. One subtle benefit of repositories like this is that they take care of issues you might not have thought of when hosting files for a given materials modeling code. For instance, it is against copyright to share VASP's pseudopotential files, but the NOMAD repository will automatically remove those (while storing the key information about what pseudopotentials you used) upon upload. You can read more about NOMAD in &lt;a href=&quot;https://www.cambridge.org/core/journals/mrs-bulletin/article/nomad-the-fair-concept-for-big-datadriven-materials-science/1EEF321F62D41997CA16AD367B74C4B0&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.materialscloud.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud&lt;/a&gt;. This is a platform that is specific to materials modeling, but unlike ioChem-BD and NOMAD, it is not specifically focused on quantum-chemical calculations. You can read more about the Materials Cloud in &lt;a href=&quot;https://arxiv.org/abs/2003.12510&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. One of the main distinguishing factors of the Materials Cloud is that it also focuses on making sure the workflows themselves are reproducible.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.catalysis-hub.org/&quot; rel=&quot;noreferrer&quot;&gt;Catalysis-Hub&lt;/a&gt;. This is a data repository specific to quantum-chemical calculations related to catalysis and surface science. You can read more about Catalysis-Hub in &lt;a href=&quot;https://www.nature.com/articles/s41597-019-0081-y&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;The main benefits of using a platform specific to computational chemistry or materials modeling is that they often make it easy to find other data or carry out meta-analyses, which are not practical on broader repositories like Zenodo or Figshare. In other words, they make your data more re-useable. They also are constructed to deal with common input/output file formats, oftentimes parsing the results automatically and displaying them in an intuitive way. This is also in contrast with more general data-hosting platforms, which effectively are just ways to host files as-is with some degree of longevity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The main disadvantage in using a materials modeling-specific platform is that it may require more work to set up. You could, in principle, just dump all your files on a repository like Zenodo or Figshare. That doesn't mean they'll be easily findable and it's not necessarily advisable, but you could do it and it'd require little time on your part. In contrast, materials modeling-specific repositories are trying to make sure the data is consistently structured and readily accessible, so it will require a little bit more organizing time for the person uploading the data. Personally, I think that is a price worth paying.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-04T02:07:17.427" LastActivityDate="2020-05-04T02:07:17.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="326" PostTypeId="1" AcceptedAnswerId="1294" CreationDate="2020-05-03T20:42:37.450" Score="20" ViewCount="653" Body="&lt;p&gt;I use the codes &lt;code&gt;phonopy&lt;/code&gt; and &lt;code&gt;phonopy-qha&lt;/code&gt; for phonon dispersion studies. &lt;code&gt;phonopy-qha&lt;/code&gt; gives quite a lot of information about the material: bulk modulus vs temperature, Gibbs energy vs temperature, etc.&lt;/p&gt;&#xA;&lt;p&gt;I was curious about the information that goes into calculating these properties. Since it diagonalizes the dynamical matrix and gets phonon frequencies, I assume we have no information about electronic properties in the output.&lt;/p&gt;&#xA;&lt;p&gt;To be specific, in the Gibbs energy that &lt;code&gt;phonopy-qha&lt;/code&gt; calculates, other than the vibrational entropy contribution,  would it have any other contribution? What about enthalpy contribution, and would it consider the zero-point kinetic energy of ions (by virtue of Heisenberg's uncertainty principle) in that?&lt;/p&gt;&#xA;&lt;p&gt;Edit: I realised it does account for the electronic energy (DFT calculated energy) as well. &lt;strong&gt;What else is included other than phonon vibrations and electronic energy?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-12T22:50:55.647" LastActivityDate="2020-12-12T22:50:55.647" Title="What do phonon dispersion (or lattice dynamics) studies include?" Tags="|gibbs-free-energy|phonopy|quasi-harmonic-approximation|phonon-dispersion|lattice-dynamics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="327" PostTypeId="5" CreationDate="2020-05-03T20:52:06.263" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T20:52:06.263" LastActivityDate="2020-05-03T20:52:06.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="328" PostTypeId="4" CreationDate="2020-05-03T20:52:06.263" Score="0" Body="For questions related to simulating the effects of magnetic fields." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-02T15:59:33.940" LastActivityDate="2020-07-02T15:59:33.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="329" PostTypeId="1" AcceptedAnswerId="394" CreationDate="2020-05-03T22:00:22.980" Score="28" ViewCount="283" Body="&lt;p&gt;The NREL solar cell efficiency chart tracks the efficiency of research-level photovoltaics since 1976, and the most up-to-date version is presented below (it was updated in April 2020). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;3-J (3-junction) solar cells have seen a steady improvement in efficiency from about 33% in 1999 to 44.4% in 2013, at which point no further research seems to have been done on 3-J solar cells (according to the NREL chart at least). At around the same time, the company Soitec put 4-J cells on the map, the fist one having an efficiency of 44%, followed by a &lt;strong&gt;&lt;em&gt;steady&lt;/em&gt;&lt;/strong&gt; increase in efficiency up to 47.1% in 2015. When I say &quot;steady&quot; increase, I mean that the slope we see in the curve for 4-J cells is roughly the same as the slope we see for the 3-J cells from 1999 to 2013, which was &lt;strong&gt;&lt;em&gt;excellent&lt;/em&gt;&lt;/strong&gt; progress in increasing solar cell efficiency.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;But suddenly it stopped.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;No new reports of progress with 4-J solar cells have been put on the map since 2015. &lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;No 5-J concentrator solar cells have been put on the map &lt;strong&gt;at all.&lt;/em&gt;&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;One 6-J concentrator solar cell was reported by NREL in the summer of 2019, which was the first 4+ junction concentrator cell reported in 4 years.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What happened?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/asBjr.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/asBjr.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&#xA;&lt;sup&gt;Source: &lt;a href=&quot;https://www.nrel.gov/pv/cell-efficiency.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.nrel.gov/pv/cell-efficiency.html&lt;/a&gt;&lt;/sup&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-04T23:32:18.537" LastActivityDate="2020-05-05T03:12:03.607" Title="What has caused this apparent stagnancy, in the development of more efficient solar cells?" Tags="|solar-cells|multi-junction-photovoltaics|energy-conversion|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="330" PostTypeId="1" AcceptedAnswerId="977" CreationDate="2020-05-03T22:18:00.373" Score="15" ViewCount="122" Body="&lt;p&gt;In general (at least for molecular calculations) basis sets and DFT functionals are fit to some high level calculation or experimental energy. It is speculated that an accurate energy will result in an accurate wavefunction and thus accurate properties, but this is not guaranteed. There have been papers looking at how different functionals perform at &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.7b01252&quot; rel=&quot;nofollow noreferrer&quot;&gt;computing properties&lt;/a&gt; as well as basis sets optimized to compute particular &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.23347&quot; rel=&quot;nofollow noreferrer&quot;&gt;nonenergetic properties&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are there any functionals/basis sets optimized to calculate bulk material properties rather than the energy? Say polarizablity or refractive index (I'm not certain what properties would be of most interest to material scientists in general, as I have more of a molecular chemistry background).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To clarify, I'm not necessarily interested in functionals that were intended to be better for some property, but were still fit using minimization of error in the energy as a criteria. I'm hoping to find cases where the fitting was done explicitly to minimize the error of some property within a test set, rather than cases where the functional was implicitly improved by, for example, using a different test set.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-20T16:07:10.487" LastActivityDate="2020-05-21T11:56:16.857" Title="Functionals/basis sets optimized with respect to properties?" Tags="|density-functional-theory|basis-sets|condensed-matter|functional|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="331" PostTypeId="5" CreationDate="2020-05-03T23:52:46.263" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T23:52:46.263" LastActivityDate="2020-05-03T23:52:46.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="332" PostTypeId="4" CreationDate="2020-05-03T23:52:46.263" Score="0" Body="Questions related to the open source materials modeling framework, Quantum Espresso." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-15T16:41:39.533" LastActivityDate="2020-05-15T16:41:39.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="333" PostTypeId="5" CreationDate="2020-05-03T23:58:20.430" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-03T23:58:20.430" LastActivityDate="2020-05-03T23:58:20.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="334" PostTypeId="4" CreationDate="2020-05-03T23:58:20.430" Score="0" Body="Questions related to the core electrons in the electronic structure." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T00:11:06.297" LastActivityDate="2020-05-04T00:11:06.297" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="335" PostTypeId="5" CreationDate="2020-05-04T00:00:53.277" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T00:00:53.277" LastActivityDate="2020-05-04T00:00:53.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="336" PostTypeId="4" CreationDate="2020-05-04T00:00:53.277" Score="0" Body="Questions related to the semi-core electrons in the electronic structure." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T00:11:08.843" LastActivityDate="2020-05-04T00:11:08.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="337" PostTypeId="1" CreationDate="2020-05-04T01:48:17.550" Score="13" ViewCount="166" Body="&lt;p&gt;The mechanical, chemical, and electronic properties of materials change depending on the scale at which we are measuring.&#xA;Scales typically range from the nano to micro to macro levels. My question is, what frameworks have people found particularly useful for the mesoscopic scale of materials modeling, i.e., the level between micro and macro. A related question can be found here: &lt;a href=&quot;https://materials.stackexchange.com/questions/17/what-are-the-main-computational-frameworks-used-in-materials-modeling&quot;&gt;What are the main computational frameworks used in materials modeling?&lt;/a&gt; &lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-05-06T16:34:11.120" LastActivityDate="2020-07-21T15:04:41.997" Title="Frameworks for materials modeling at the mesoscopic scale" Tags="|computational-frameworks|mesoscopic-physics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="338" PostTypeId="2" ParentId="174" CreationDate="2020-05-04T01:55:46.767" Score="8" Body="&lt;p&gt;The first answer is most relevant to materials modeling, but I also want to chip in that Born-Oppenheimer is more than just a kinetic assumption, it also assumes nuclei are point charges. This is especially important for actinides and super heavy elements where nuclei become not only much larger relative to the electron cloud but also more ovoid with unequal charge distribution in space. This can play a role in chemical properties related to spin effects as the dipole moment of the nuclei are much different than what Born-Oppenheimer would tell you.&lt;/p&gt;&#xA;" OwnerUserId="256" LastActivityDate="2020-05-04T01:55:46.767" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="339" PostTypeId="2" ParentId="337" CreationDate="2020-05-04T02:07:43.980" Score="13" Body="&lt;p&gt;I assume when you are asking about &lt;strong&gt;mesoscopic modeling&lt;/strong&gt; you are looking for a scale higher than molecular dynamics and quantum mechanical simulations and a scale smaller than macroscopic finite element or finite volume modeling that typically mechanical engineers do for designing for example aircraft, reactors, etc. In this regime of mesoscopic modeling, typically two different approaches are famous:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Dissipative_particle_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Dissipative Particle Dynamics (DPD)&lt;/strong&gt;&lt;/a&gt;: This method is nothing but just a coarse-grained molecular dynamics. It starts from coarse-graining of big molecular structures such as proteins or polymers into some beads that represent the structure of your material and then solves it by conventional molecular dynamics methods. The only difference is that in DPD the force fields represent the interaction of &lt;strong&gt;beads&lt;/strong&gt;, not atoms in your structure and that's the challenging part to develop a coarse-grain model that could capture the properties of a large-scale molecular dynamics accurately and be much faster as well. So, overall, you coarse-grain your structure into beads, and then you solve it with methods similar to molecular dynamics to have a more efficient and cheaper computation in comparison to conventional molecular dynamics simulation.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Lattice_Boltzmann_methods&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Lattice Boltzmann Method (LBM)&lt;/strong&gt;&lt;/a&gt;: I believe you know about computational fluid dynamics that mechanical engineers use for designing channels, aircraft, etc. to model the movement of fluids. Lattice Boltzmann method is similar to computational fluid dynamics method to capture the hydrodynamics of fluids but it comes from Boltzmann equation and kinetics theory as well as non-equilibrium thermodynamics instead of solving macroscopic Navier-Stokes equation. In the end, you solve Navier-Stokes equation but with a completely different approach. Here again, you coarse-grain your material into some particles or beads that contain a pre-defined number of atoms and then track their probability distribution function &lt;strong&gt;deterministically&lt;/strong&gt; by using Maxwell-Boltzmann probability distribution and then calculate the hydrodynamics parameters (e.g. density, momentum, stress, energy, temperature, etc.) by taking ensemble average. The advantage in comparison to macroscopic computational fluid dynamics approaches is that you have a solid physical theory to capture complex phenomena easily such as the interaction of multi-component or multiphase fluids and materials and it is straightforward to couple this LBM approach with a coarse-grained molecular dynamics method (e.g. DPD) to for example study the hydrodynamics of polymeric solution where you capture the fluid movement of the solution with LBM and the movement of polymer chain with DPD or coarse-grained molecular dynamics.  &lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Of course, you could consider other methods such as Monte-Carlo or Phase-Field as well in the mesoscopic regime (note that Phase-Field could be coupled with LBM usually) to capture the microstructure of materials or fluids.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;: Definition of DPD beads, PCL is grouped into P beads, MDI is grouped into M beads, and BDO is grouped into B beads for example:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FVZuv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FVZuv.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://www.researchgate.net/publication/304809071_Revealing_the_morphological_architecture_of_a_shape_memory_polyurethane_by_simulation&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hu et. al., Revealing the morphological architecture of a shape memory polyurethane by simulation, Scientific Reports 6:29180 · July 2016.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-05-04T14:22:54.337" LastActivityDate="2020-05-04T14:22:54.337" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="340" PostTypeId="1" CreationDate="2020-05-04T02:38:30.670" Score="20" ViewCount="295" Body="&lt;p&gt;Several years ago, I became familiar with &lt;a href=&quot;https://nanohub.org/&quot; rel=&quot;noreferrer&quot;&gt;nanoHUB&lt;/a&gt; for accessing open-source codes and software specifically for computational materials science at the nano-scale as well as &lt;a href=&quot;https://pages.nist.gov/pfhub/&quot; rel=&quot;noreferrer&quot;&gt;PFHub&lt;/a&gt; that gives you access to phase-field and microstructural modeling codes and software. Both of these hubs are open-source and you could use other codes or share your own code there. I'm wondering if there is a more complete list of similar hubs specifically for computational materials science (for a whole range of materials modeling from atomistic, quantum mechanics, molecular dynamics to mesoscopic and even macroscopic modeling) including these two that I know. I really appreciate any recommendations or suggestions here.&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="7" LastEditDate="2020-05-20T16:08:11.020" LastActivityDate="2020-05-21T03:39:26.897" Title="Is there any complete list of open source hubs specifically designed for materials modeling and computational materials science?" Tags="|databases|open-source|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="341" PostTypeId="5" CreationDate="2020-05-04T02:46:55.310" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T02:46:55.310" LastActivityDate="2020-05-04T02:46:55.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="342" PostTypeId="4" CreationDate="2020-05-04T02:46:55.310" Score="0" Body="Physics at the mesoscopic scale which lies between the nano and micro scales." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T03:30:14.373" LastActivityDate="2020-05-04T03:30:14.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="343" PostTypeId="5" CreationDate="2020-05-04T02:48:10.840" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T02:48:10.840" LastActivityDate="2020-05-04T02:48:10.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="344" PostTypeId="4" CreationDate="2020-05-04T02:48:10.840" Score="0" Body="Questions related to computational frameworks, aka software packages or libraries. Can be open or closed source." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-05T17:30:13.770" LastActivityDate="2020-05-05T17:30:13.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="345" PostTypeId="1" AcceptedAnswerId="348" CreationDate="2020-05-04T02:48:46.230" Score="22" ViewCount="269" Body="&lt;p&gt;The &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; and other materials databases have a nice periodic table on their home page that allows you to search for compounds. For some materials, they give an empirical &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; value used to model the bandstructure, and a reference to the paper. However, this information is available for a limited amount of materials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there a databse or repository where one can find &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; values obtained by experiment or determined &lt;em&gt;ab-initio&lt;/em&gt; for metals across the periodic table? &lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="88" LastEditDate="2020-05-27T15:35:05.800" LastActivityDate="2020-05-27T15:35:05.800" Title="Database or repository with values for the Hubbard potential U?" Tags="|density-functional-theory|reference-request|databases|dft-u|hubbard-model|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="347" PostTypeId="1" AcceptedAnswerId="419" CreationDate="2020-05-04T03:11:28.787" Score="32" ViewCount="1132" Body="&lt;p&gt;Most of the conventional DFT codes or software use LDA, GGA, meta-GGA, PBE, etc. exchange-correlation functionals, but I'm wondering if there is any DFT code or software that uses the new generation of exchange-correlation functionals called &lt;strong&gt;Exact Exchange-Correlation Potentials&lt;/strong&gt;? Particularly, I recently came across the exact Hartree-Fock exchange energy functional and potential that neglects the correlation and defined as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{X}[n] = -\frac{1}{2}\sum_{i,j} \int d^{3}\mathbf{r} d^{3}\mathbf{r}^{'} \frac{\phi^{*}_{i}(\mathbf{r})\phi_{j}^{*}(\mathbf{r}^{'})\phi_{j}(\mathbf{r})\phi_{i}(\mathbf{r}^{'})}{|\mathbf{r}-\mathbf{r}^{'}|}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_{X}[n]=\frac{\delta E_{X}[n]}{\delta n(\mathbf{r})}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;and I see that this exact exchange-energy functional is able to calculate magnetic moment of &lt;span class=&quot;math-container&quot;&gt;$\text{FeAl}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\text{Ni}_{3}\text{Ga}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\text{Ni}_{3}\text{Al}$&lt;/span&gt; with much higher accuracy in comparison to FP-LDA for example described &lt;a href=&quot;http://arxiv.org/abs/cond-mat/0501258&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. So my question is: Are these sort of exact exchange-correlation energy functionals incorporated into open-source DFT codes and are they worth using in comparison to conventional XC potentials due to the fact they seem to be more complicated and more difficult to implement? Also, when we say these are &lt;strong&gt;exact&lt;/strong&gt; exchange-correlation energy functionals, what do we mean by exact? The purpose is that there is no approximation here or something else?&lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="36" LastEditDate="2020-05-22T19:23:01.057" LastActivityDate="2020-05-22T19:23:01.057" Title="Is there any DFT code or software that has the option to use this exact exchange-correlation energy functional?" Tags="|density-functional-theory|gpaw|exchange-correlation|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="348" PostTypeId="2" ParentId="345" CreationDate="2020-05-04T04:29:13.123" Score="17" Body="&lt;p&gt;Unfortunately, I don't believe such a resource exists. One should keep in mind that it's not just a matter of a single U value for every metal, of course. The &quot;best&quot; empirical U value will depend on the property of interest. Perhaps more problematic, not every metal environment is made equal. Different oxidation states, coordination environments, and overall electronic structures will inevitably influence the empirically ideal U value as well as any &lt;em&gt;ab initio&lt;/em&gt; U value, making it hard to have a one-value-fits-all approach for a given metal.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This variety and application-specific nature is probably the major reason why such a database doesn't exist right now, to the best of my knowledge. That being said, I think it would be an amazing resource if such a database did exist, even if there were a variety of U values categorized by material and property.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Beyond the band structures, it's worth mentioning that a commonly used set of U values are those taken from &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.73.195107&quot; rel=&quot;noreferrer&quot;&gt;this work&lt;/a&gt; by Ceder and coworkers to reproduce the oxidation energies of transition metal oxides. This is what is used throughout the &lt;a href=&quot;http://oqmd.org/documentation/vasp&quot; rel=&quot;noreferrer&quot;&gt;Open Quantum Materials Database&lt;/a&gt; to try and achieve more accurate formation energies.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-04T05:06:14.553" LastActivityDate="2020-05-04T05:06:14.553" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="349" PostTypeId="5" CreationDate="2020-05-04T04:41:39.740" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T04:41:39.740" LastActivityDate="2020-05-04T04:41:39.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="350" PostTypeId="4" CreationDate="2020-05-04T04:41:39.740" Score="0" Body="For questions related to variational methods in matter modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-06-26T21:54:32.327" LastActivityDate="2020-06-26T21:54:32.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="351" PostTypeId="5" CreationDate="2020-05-04T04:43:57.913" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T04:43:57.913" LastActivityDate="2020-05-04T04:43:57.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="352" PostTypeId="4" CreationDate="2020-05-04T04:43:57.913" Score="0" Body="Questions related to the physical quantities of stress and strain in materials systems." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T05:26:44.080" LastActivityDate="2020-05-04T05:26:44.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="353" PostTypeId="5" CreationDate="2020-05-04T04:47:37.847" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T04:47:37.847" LastActivityDate="2020-05-04T04:47:37.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="354" PostTypeId="4" CreationDate="2020-05-04T04:47:37.847" Score="0" Body="Questions related to nanoparticles. A nanoparticle is usually defined as a particle of matter that is between 1 and 100 nanometres in diameter." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T05:26:58.100" LastActivityDate="2020-05-04T05:26:58.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="355" PostTypeId="1" CreationDate="2020-05-04T04:52:26.807" Score="19" ViewCount="112" Body="&lt;p&gt;Most, if not all, material systems are multiscale in nature that are described by different physics at different length and time scales, ranging from density functional theory (DFT) to phase field modeling to finite element analysis.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How are these different levels of theory/model coupled across length and time scales?&lt;/p&gt;&#xA;" OwnerUserId="189" LastActivityDate="2020-05-04T05:09:26.137" Title="What are some common techniques for building multiscale models for materials?" Tags="|density-functional-theory|phase-field-modeling|multiscale-modeling|finite-element-analysis|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="356" PostTypeId="5" CreationDate="2020-05-04T04:52:42.670" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T04:52:42.670" LastActivityDate="2020-05-04T04:52:42.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="357" PostTypeId="4" CreationDate="2020-05-04T04:52:42.670" Score="0" Body="For questions related to the Fourier Transform." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-04T05:27:01.813" LastActivityDate="2020-05-04T05:27:01.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="358" PostTypeId="2" ParentId="355" CreationDate="2020-05-04T05:08:53.727" Score="13" Body="&lt;p&gt;One example of multi-scale modeling in materials modeling is &lt;a href=&quot;https://en.wikipedia.org/wiki/Coarse-grained_modeling&quot; rel=&quot;noreferrer&quot;&gt;coarse-grain modeling&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In these examples larger systems can be studied in a more efficient way by treating clusters of atoms, often monomers or residues of a polymer as a single structure or &quot;bead&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Each bead is parameterized to capture the feature of the underlying atoms, for example polarity and steric bulk. Thus the  material properties of the smaller atomic level affect the larger level. &lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-05-04T05:08:53.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="359" PostTypeId="2" ParentId="355" CreationDate="2020-05-04T05:09:26.137" Score="13" Body="&lt;p&gt;I would limit my answer to the situation where you have only two scales in your system. For more complicated problems, it's easy to generalize the concept provided here. Usually, the computational technique that works with the smallest scale in your system sends information to the higher-level scale back and forth. For example, let's say you want to simulate the mechanical properties of nanomaterials by using multiscale approach when you want to use molecular dynamics to extract the material behavior (i.e. the relation between stress and strain) and then use the finite element to get that information from the molecular dynamics and use it in defining the governing equation of your larger-scale simulation. Basically, here molecular dynamics calculate forces between atoms or molecules in your system for complex materials when you don't have a clear material model to describe its behavior and then finite element take this information and send back the updated stress/strain values to the molecular dynamics and you repeat this loop.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another example is about coupling molecular dynamics and DFT. One of the challenges in molecular dynamics is finding suitable force-fields for complex materials like polymers or proteins. Here, DFT could act as a really accurate but computationally expensive tool find the forces from quantum mechanical simulation and molecular dynamics would be able to use this DFT extracted force-field and update the position of atoms (keep in mind the effect of electrons-nuclei is neglected due to the fact that electrons are much faster than nuclei and the electronic orbital reaches equilibrium so fast in comparison to atomic displacement time scale) and then you repeat the DFT to update the force-field and you repeat this loop.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now we could couple the whole range physical model for combining these two examples and doing DFT to extract force-field and then feed it to molecular dynamics to extract the behavior of material and then feed the information from molecular dynamics to finite element to update the macroscopic stress/strain and displacement, though this approach seems really computationally demanding.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-04T05:09:26.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="360" PostTypeId="1" AcceptedAnswerId="567" CreationDate="2020-05-04T05:22:44.193" Score="23" ViewCount="421" Body="&lt;p&gt;As pointed out in a &lt;a href=&quot;https://materials.stackexchange.com/questions/316/in-dft-if-i-complete-a-convergence-test-once-then-want-to-study-a-different-sy&quot;&gt;previous question&lt;/a&gt; each time you start a new DFT calculation, it is recommended to do a convergence test. If I am studying a system using different exchange correlation functional approximations like GGA, meta-GGA, hybrid, DFT+U, should I explicitly check for convergence for each method?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How do people approach this in real life calculations? If I am doing a calculation, am I expected to check convergence for each method? Alternatively, if I find a similar work in literature, is it understood that the authors have checked for convergence explicitly for every method?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-14T05:29:25.640" LastActivityDate="2020-05-14T05:29:25.640" Title="In DFT, while studying a system using different exchange-correlation functional approximations, are we expected to check convergence for each method?" Tags="|density-functional-theory|convergence-test|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="361" PostTypeId="2" ParentId="318" CreationDate="2020-05-04T06:03:01.420" Score="36" Body="&lt;p&gt;Disclaimer and warning: long and likely biased answer.&lt;/p&gt;&#xA;&lt;p&gt;Background: The Pople style basis sets were defined almost 50 years ago. The 6-31G was designed for HF calculations, the 6-311G for MP2 calculations. For computational efficiency reasons, the s- and p-exponents were constrained to be identical. Polarization functions were defined for 1d, 2d, 3d and 1f. Calculations for anions lead to the augmentation with diffuse s- and p-functions, denoted with +.&lt;/p&gt;&#xA;&lt;p&gt;The seminal work of Dunning leading to the cc-pVnZ family of basis sets introduced the concept of balancing errors as a basis set design element. The key feature is that a balanced basis set typically has one less (contracted) function for each step up in angular momentum, and the highest angular momentum function included thus defines the basis set quality. This is by modern notation often called the cardinal number X. By this standard, only the Pople style basis sets 6-31G(d,p) and 6-311G(2d1f,2p1d) are balanced, and combinations such as 6-31G(2d,2p) or 6-311G(d,p) should not be used. Similarly, using the unpolarized 6-31G and 6-311G does not make sense, as the lack of polarization functions completely dominates the error. It has been argued that the 6-311G is really only of double-zeta quality, in which case 6-311G(d,p) could be considered as a marginally improved version of 6-31G(d,p).&lt;/p&gt;&#xA;&lt;p&gt;The cc-pVnZ basis sets have been optimized to describe electron correlation, while the polarization consistent (pc) basis sets have been optimized towards DFT methods. The difference in basis set convergence for wave function electron correlation and DFT methods (&lt;span class=&quot;math-container&quot;&gt;$X^{-3}$&lt;/span&gt; vs. &lt;span class=&quot;math-container&quot;&gt;$\exp(-X^{1/2}$&lt;/span&gt;)) makes the optimum composition and exponents (slightly) different. The most recent version of the pc has been defined with a segmented contraction (pcseg), which improves the computational efficiency significantly in most program packages. The following assumes that the method is DFT or HF, for highly correlated wave function methods, the cc-pVnZ are likely the best choice.&lt;/p&gt;&#xA;&lt;p&gt;Now for the questions raised (basis set errors taken from &lt;a href=&quot;https://doi.org/10.1021/ct401026a&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt; using DFT):&lt;/p&gt;&#xA;&lt;p&gt;The 6-31G(d,p) is formally of the same cardinal quality as pcseg-1. The basis set error relative to the basis set limit, however, is roughly a factor of 3 lower for the pcseg-1.&lt;/p&gt;&#xA;&lt;p&gt;The 6-311G(2d1f,2p1d) is formally of the same cardinal quality as pcseg-2. The basis set error relative to the basis set limit, however, is roughly a factor of 5 lower for the pcseg-2. The pcseg-1 also gives lower basis set errors than 6-311G(2d1f,2p1d), by roughly a factor of 2, which as mentioned above, suggests that the 6-311G is not of triple zeta quality.&lt;/p&gt;&#xA;&lt;p&gt;The pcseg-1 gives lower basis set errors than any of the Pople type combinations, and the basis set error is consistent for all atoms H-Kr.&lt;/p&gt;&#xA;&lt;p&gt;The computational efficiency depends on the molecule and the program package used, but the computational time using 6-31G(d,p) or pcseg-1 is usually very similar, but see the comment regarding hydrogen below.&lt;/p&gt;&#xA;&lt;p&gt;Diffuse augmentation leads to 6-31+G(d) and aug-pcseg-1. The aug-pcseg-1 for non-H atoms has diffuse s-, p- and d-function, while 6-31+G(d) only has diffuse s- and p-functions. Diffuse d-functions have a minor influence on energetics for e.g. anions, but they vastly improve the performance for e.g. dipole moments and polarizabilities.&lt;/p&gt;&#xA;&lt;p&gt;Hydrogen atoms often play a ‘spectator’ role in molecules but often accounts for roughly half of the atoms, and they are for computational efficiency reasons therefore often described by a (slightly) lower quality basis set. The 6-31G(d) thus do not include polarization functions on hydrogen, while the pcseg-1 does by default, again based on balancing errors. 6-31G(d) is thus equivalent to pcseg-1 for non-H, but requires removing the p-function for H. Alternatively, one could use the pcseg-0 for H, which would be equivalent to using the 3-21G in the Pople family. Similarly, one often only includes diffuse functions on non-hydrogen atoms.&lt;/p&gt;&#xA;&lt;p&gt;The updated Table:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Type&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Pople/Dunning&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Jensen (closest)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;3-21G&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;pcseg-0 (all atoms)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31G&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1 polarization removed)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31G(d)/cc-pVDZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1 polarization removed)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31+G(d)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1 no polarization or pcseg-0)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;pcseg-1 (all atoms)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31+G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;DZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-31++G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;aug-pcseg-1 (all atoms)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311G(2df)/cc-pVTZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (pcseg-2), H (pcseg-2 no polarization)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;The following combinations are really inconsistent and not truly of TZP quality. They should generally be avoided, but if viewed as being of double zeta quality, rather than triple zeta quality, then:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Type&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Pople/Dunning&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Jensen (closest)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311G&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;pcseg-1 (all polarization removed)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZ&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311+G&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1 polarization removed)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311+G(d)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1 polarization removed)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;pcseg-1 (all atoms)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311+G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;non-H (aug-pcseg-1), H (pcseg-1)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;TZP&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6-311++G(d,p)&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;aug-pcseg-1 (all atoms)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;The above is for second-row elements (Li-Ne). The 6-311G is not defined for third-row (Na-Ar) atoms, and the 6-31G for transition metals is, in my opinion, a poor choice.&lt;/p&gt;&#xA;&lt;p&gt;The goal of the cc and pc basis sets is to approach the complete basis set limit in a fast, systematic and monotonic fashion. The computational method, however, in most cases also have inherent errors, and method and basis set errors may be in different directions. As mentioned in the question, one can easily design ~50 Pople style basis set combinations, and if combined with ~50 DFT methods, one has 2500 different computational models. Testing these against a (limited) set of reference data will almost certainly identify ‘magic’ combinations where basis set and method errors to some extend cancel each other and lead to a low error relative to the reference data. For this to work, it is necessary that one can introduce significant (and different) basis set errors, and this is where unbalanced basis sets come into play. &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b00477&quot; rel=&quot;noreferrer&quot;&gt;[2]&lt;/a&gt; gives an illustration of such method and basis set error compensation.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;F. Jensen J. Chem. Theory Comput. 2014, 10, 3, 1074-1085 DOI: 10.1021/ct401026a&lt;/li&gt;&#xA;&lt;li&gt;F. Jensen J. Chem. Theory Comput. 2018, 14, 9, 4651-4661 DOI: 10.1021/acs.jctc.8b00477&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="279" LastEditorUserId="5" LastEditDate="2020-12-07T18:34:22.923" LastActivityDate="2020-12-07T18:34:22.923" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="362" PostTypeId="2" ParentId="131" CreationDate="2020-05-04T07:09:12.500" Score="6" Body="&lt;p&gt;I think the answer is probably: yes, but not just one. Or no, if you want to be very strict. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Depending on the type of system you are studying, different methods may work better or worse and it may not always be obvious why. There is probably not one method that will work best generically. &lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;For quantum spin systems in &lt;span class=&quot;math-container&quot;&gt;$d\geq 2$&lt;/span&gt; (lattice Hamiltonians with interactions of the form &lt;span class=&quot;math-container&quot;&gt;$\vec S_i \cdot \vec S_j$&lt;/span&gt;), the &lt;em&gt;gold standard&lt;/em&gt; is quantum Monte Carlo (QMC), with the specific method depending on the specific nature of the material, question. For example, if you wanted to know the transition temperature for the AFM ground state for a 3D Heisenberg model, the gold standard would be Stochastic Series Expansion QMC (SSE) &lt;a href=&quot;https://arxiv.org/abs/1909.10591&quot; rel=&quot;nofollow noreferrer&quot;&gt;see arXiv&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For lattice Hamiltonians in 1D, the gold standard is matrix product state methods, like &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_matrix_renormalization_group&quot; rel=&quot;nofollow noreferrer&quot;&gt;DMRG&lt;/a&gt;. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-08T04:49:18.853" LastActivityDate="2020-05-08T04:49:18.853" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="363" PostTypeId="1" CreationDate="2020-05-04T09:08:17.427" Score="13" ViewCount="148" Body="&lt;p&gt;&lt;strong&gt;Ion drift-diffusion&lt;/strong&gt; under the effect of an external electric field is a phenomenon with a huge relevancy in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.201201471&quot; rel=&quot;nofollow noreferrer&quot;&gt;light emitting devices&lt;/a&gt;, &lt;a href=&quot;https://www.nature.com/articles/ncomms15448&quot; rel=&quot;nofollow noreferrer&quot;&gt;neuromorphic architectures&lt;/a&gt; and in general &lt;a href=&quot;https://science.sciencemag.org/content/364/6437/233.summary&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular electronics&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Up to now, the most advanced approaches considered two steady-state operative models: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.57.12951&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electrodynamical model (ED)&lt;/a&gt; and &lt;a href=&quot;https://www.nature.com/articles/nmat2623&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electrochemical Doping model (ECD)&lt;/a&gt;. But the key point to solve the resulting set of Partial differential equations is related to their &lt;strong&gt;non-linearity&lt;/strong&gt; and &lt;strong&gt;time-dependence&lt;/strong&gt;. These set include Drift and Diffusion equations for each type of carriers (ions, electrons and holes)  and Poisson equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}{\delta{n_e} \over \delta{t}} &amp;amp;= \mu_{e} \left[{kT \over e} \nabla^2n_e - n_e \nabla^2 \phi- (\nabla n_e)(\nabla \phi)\right] -k_{eh}n_en_h\tag{1}\\{\delta{n_h} \over \delta{t}} &amp;amp;= \mu_{h} \left[{kT \over e}\nabla^2n_h - n_h \nabla^2 \phi- (\nabla n_h)(\nabla \phi)\right] -k_{eh}n_en_h\tag{2}\\{\delta{n_a} \over \delta{t}} &amp;amp;= \mu_{a} \left[{kT \over e} \nabla^2n_a - n_a \nabla^2 \phi- (\nabla n_a)(\nabla \phi)\right]\tag{3}\\{\delta{n_c} \over \delta{t}} &amp;amp;= \mu_{c} \left[{kT \over e} \nabla^2n_c - n_c \nabla^2 \phi- (\nabla n_c)(\nabla \phi)\right]\tag{4}\\{\nabla^2 \phi} &amp;amp;= {-e \over \epsilon}  (n_h + n_c -n_e -n_a)\tag{5}\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is related to programmable solving methods for highly non-linear PDEs. Even in the case that we have the algebraic expression of the PDEs, which methodologies are powerful enough to deal with such a complicated problem?&lt;/p&gt;&#xA;" OwnerUserId="290" LastEditorUserId="5" LastEditDate="2020-12-28T02:07:03.243" LastActivityDate="2020-12-28T02:07:03.243" Title="Modelling ion Drift-Diffusion under an external electric potential, convergency in PDE?" Tags="|mathematical-modeling|partial-differential-equations|ion-dynamics|electric-field|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="364" PostTypeId="1" AcceptedAnswerId="383" CreationDate="2020-05-04T09:17:23.747" Score="21" ViewCount="1754" Body="&lt;p&gt;I am aware of &lt;a href=&quot;https://romerogroup.github.io/pyprocar/&quot; rel=&quot;noreferrer&quot;&gt;pyPROCAR&lt;/a&gt; and &lt;a href=&quot;http://vaspkit.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT&lt;/a&gt;. Are there any other tools supporting VASP&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-08-05T21:31:08.987" LastActivityDate="2020-08-05T21:31:08.987" Title="What are the pre/post processing tools available for VASP?" Tags="|density-functional-theory|vasp|atomic-simulation-environment|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="365" PostTypeId="1" CreationDate="2020-05-04T10:08:12.227" Score="39" ViewCount="3394" Body="&lt;p&gt;What is a good programming language for matter (e.g. molecular or materials) modeling?&lt;/p&gt;&#xA;&lt;p&gt;Since this is a broad field, I don't expect there to be only one answer.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-11-03T03:35:12.207" LastActivityDate="2023-07-03T15:38:01.643" Title="What is a good programming language for matter modeling?" Tags="|software|one-topic-per-answer|high-performance-computing|python|" AnswerCount="13" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="366" PostTypeId="1" AcceptedAnswerId="369" CreationDate="2020-05-04T10:08:53.483" Score="13" ViewCount="202" Body="&lt;p&gt;The basis of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kohn_anomaly&quot; rel=&quot;noreferrer&quot;&gt;Kohn anomaly&lt;/a&gt; is that a logarithmic singularity at &lt;span class=&quot;math-container&quot;&gt;$q=2k_\rm F$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$k_\rm F$&lt;/span&gt; is the radius of the Fermi sphere) causes extreme fluctuations of the dielectric function about that point.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm interested in how that is derived, but I could not find anything in &lt;a href=&quot;https://en.wikipedia.org/wiki/Lindhard_theory&quot; rel=&quot;noreferrer&quot;&gt;Lindhard theory&lt;/a&gt; which the Wikipedia article (linked above) points to.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there literature that details a proof of this result?&lt;/p&gt;&#xA;" OwnerUserId="35" LastActivityDate="2020-05-04T18:53:56.150" Title="Derivation of logarithmic singularity that causes the Kohn anomaly" Tags="|reference-request|lindhard-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="367" PostTypeId="2" ParentId="365" CreationDate="2020-05-04T10:21:03.053" Score="24" Body="&lt;h2&gt;It depends on what you want to do&lt;/h2&gt;&#xA;&lt;p&gt;I'll go first. For context: I do mostly Monte Carlo simulations, especially quantum Monte Carlo. My work has focused on spin systems, using techniques like the Metropolis Algorithm and stochastic series expansion QMC.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For Writing Simulations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In my field there are few software packages available and the algorithms are sufficiently simple that most people write their own code from scratch. Especially for Monte Carlo, serial performance is key, memory is rarely an issue, so most people use fast, compiled languages like &lt;strong&gt;C/C++&lt;/strong&gt; or &lt;strong&gt;Fortran&lt;/strong&gt;. Interpreted languages like python are often too slow for intense computations, but people do use hybrid solutions where the expensive calculations are written in C and called from python, which can be a good option.&lt;/p&gt;&#xA;&lt;p&gt;C/C++ are great general purpose languages that you might want to learn for a whole host of reasons, and when properly optimized, they are very fast.&lt;/p&gt;&#xA;&lt;p&gt;Fortran is less sophisticated than C/C++, but it is designed for writing simulations, so stuff like complex numbers, exponential and power functions are native. It's also very fast. In my experience, it's basically impossible to write slow Fortran code.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For Data Processing/Plotting:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;After the simulations are done, you need post-processing programs to perform averages, calculate derived quantities and make figures. Here, speed is not important, so most people use an interpreted language. I personally use &lt;strong&gt;MATLAB&lt;/strong&gt; (and it's GNU clone, &lt;strong&gt;Octave&lt;/strong&gt;) for post-processing and plotting. MATLAB is commercial software, so the documentation is great and it works reliably on all sorts of machines. I can write scripts to fully automate plotting and they work reliably for years. The (literal) price you pay is that you have to buy a license or use one provided by your institution. Matlab can be pretty expensive.&lt;/p&gt;&#xA;&lt;p&gt;If you're starting from scratch, it's probably a better idea to learn &lt;strong&gt;python.&lt;/strong&gt; Python is a powerful, flexible language and it has a billion packages that make it pretty easy to get started on anything. There are a lot of resources for learning python and, unlike Matlab, it's &lt;em&gt;free&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-06-25T00:45:36.300" LastActivityDate="2020-06-25T00:45:36.300" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="368" PostTypeId="2" ParentId="365" CreationDate="2020-05-04T10:28:17.080" Score="32" Body="&lt;h1&gt;Fortran&lt;/h1&gt;&#xA;&lt;p&gt;A large part of materials modelling involves density functional theory and molecular mechanics. From &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;this compilation&lt;/a&gt; of quantum chemistry software, the most widely used programming language seems to be &lt;a href=&quot;https://en.wikipedia.org/wiki/Fortran&quot; rel=&quot;noreferrer&quot;&gt;Fortran&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Indeed, the popular packages VASP (commercial), Quantum Espresso and Siesta (both free) all use this language.&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-21T21:14:40.107" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="369" PostTypeId="2" ParentId="366" CreationDate="2020-05-04T11:19:38.480" Score="10" Body="&lt;p&gt;A derivation of the Lindhard formula and the emerging Kohn anomaly can be found in J. M. Ziman's &lt;em&gt;Principles of the Theory of Solids&lt;/em&gt; (&lt;a href=&quot;https://doi.org/10.1017/CBO9781139644075.007&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chapter 5: Electron-Electron Interaction&lt;/a&gt;&lt;sup&gt;1&lt;/sup&gt;). Equation (5.16) from the cited book gives a general formula for the dielectric constant. The Kohn anomaly (shown in equation (5.36) in Ziman) is a consequence of the free-electrons model approximating (5.16) at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; Kelvin. Here is what Ziman writes in Chapter 5.4:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;If we wish to study screening at short distances we need to evaluate the sum  (5.16) for large values of &lt;span class=&quot;math-container&quot;&gt;$\bf q$&lt;/span&gt;. This depends on the detailed structure of the energy surfaces &lt;span class=&quot;math-container&quot;&gt;$\mathcal E(k)$&lt;/span&gt;. For our &lt;strong&gt;free-electron model at absolute zero&lt;/strong&gt; it is not very difficult to evaluate the sum by a straightforward integration  over &lt;span class=&quot;math-container&quot;&gt;$\bf k$&lt;/span&gt;-space. The result is as follows: &lt;span class=&quot;math-container&quot;&gt;$$\epsilon({\bf q},0)=1+\frac{4\pi{\boldsymbol e}^2}{q^2}\frac n{\frac23\mathcal E_F}\left\{\frac12+\frac{4k_F^2-q^2}{8k_Fq^2}\ln\left|\frac{2k_F+q}{2k_F-q}\right|\right\}\tag{5.36},$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$k_F$&lt;/span&gt; is the radius of the Fermi sphere.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; Reference &lt;/sub&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; [1] Ziman, J. (1972). Electron-Electron Interaction. In &lt;em&gt;Principles of the Theory of Solids&lt;/em&gt; (pp. 146-170). Cambridge: Cambridge University Press. doi:10.1017/CBO9781139644075.007 &lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="99" LastEditorUserId="35" LastEditDate="2020-05-04T18:53:56.150" LastActivityDate="2020-05-04T18:53:56.150" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="370" PostTypeId="2" ParentId="365" CreationDate="2020-05-04T12:54:25.770" Score="15" Body="&lt;h1&gt;Compiled Languages&lt;/h1&gt;&#xA;&lt;p&gt;Since all simulations are CPU and memory consuming, I recommend to not use interpreted language like Java, Julia*, Python, etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Compiled languages are converted directly into machine code that the processor can execute. As a result, they tend to be faster and more efficient to execute than interpreted languages. They also give the developer more control over hardware aspects, like memory management and CPU usage.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;More information about the advantages/disadvantages can be read &lt;a href=&quot;https://www.freecodecamp.org/news/compiled-versus-interpreted-languages/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;*&lt;em&gt;Julia is not an interpreted language but uses just-in-time (JIT) compilation, implemented using &lt;a href=&quot;https://en.wikipedia.org/wiki/LLVM&quot; rel=&quot;nofollow noreferrer&quot;&gt;LLVM&lt;/a&gt;. See a &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/401/63&quot;&gt;related answer&lt;/a&gt;.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="63" LastEditDate="2023-07-03T15:38:01.643" LastActivityDate="2023-07-03T15:38:01.643" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="371" PostTypeId="2" ParentId="363" CreationDate="2020-05-04T13:16:25.323" Score="6" Body="&lt;p&gt;These PDEs are typical diffusion-drift PDEs that arise in a huge number of fields (including my field, which is electrochemistry) and are routinely solved using any numerical method of your choice, e.g. finite difference method and finite element method, in both open-source and commercial software. Nonlinearities are generally not an issue in my experience because we have access to very sophisticated time integrators and adaptive meshing.&lt;/p&gt;&#xA;" OwnerUserId="189" LastActivityDate="2020-05-04T13:16:25.323" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="372" PostTypeId="1" AcceptedAnswerId="596" CreationDate="2020-05-04T13:19:38.627" Score="20" ViewCount="344" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Spin_crossover&quot; rel=&quot;nofollow noreferrer&quot;&gt;Spin Crossover (SCO) complexes&lt;/a&gt; are a particular type of molecular entities which are usually formed by a metal ion (general &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe(II)}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\ce{Co(III)}$&lt;/span&gt;) complexed by several ligands with donor N atoms. The &lt;em&gt;d&lt;/em&gt; orbitals splitting (&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; or 10Dq) produced in certain octahedral coordination geometries allows two spin configurations which are metastable and accesible with a stimuli such as temperature, light, pressure and electric field among others, producing a well-known hysteretic behavior.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pXlvg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pXlvg.png&quot; alt=&quot;Metal d orbitals splitting under a octahedral ligand field&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, the relative energies of HS and LS in a SCO complex are extremely difficult to tackle in a DFT molecular calculation. Although some elaborated approaches have been considered, such as considering the effect of the &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.24676&quot; rel=&quot;nofollow noreferrer&quot;&gt;dipolar interactions&lt;/a&gt; or using &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.inorgchem.8b01821&quot; rel=&quot;nofollow noreferrer&quot;&gt;intrincated exchange-interaction funcionals&lt;/a&gt;, no evident recipe has been proposed to correctly simulate such materials.&lt;/p&gt;&#xA;&lt;p&gt;In example, in the previous work by Cirera et al., they presented a selection of SCO complexes and calculated an estimation of the transition temperature by using Gibbs free energy expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\Delta G = \Delta H - T\Delta S $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since at equilibrium, &lt;span class=&quot;math-container&quot;&gt;$\Delta G$&lt;/span&gt; vanishes, the transition temperature (&lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt;) is determined by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}T_{1/2} =  {{\Delta H} \over {\Delta S}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From this equation (more details on the article), the key contribution to obtain the transition temperature is the enthalpy difference between the high and low spin state, which can be computed using DFT.&lt;/p&gt;&#xA;&lt;p&gt;To illustrate the complexity of this procedure, I have chosen the molecule &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe(SCN)_2(Phen)_2}$&lt;/span&gt;, considered the Droshophila of SCO materials, which has been modeled with TPSSh Funcional. The results obtained are:&lt;/p&gt;&#xA;&lt;p&gt;Experimental &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; = 176.5 K&lt;/p&gt;&#xA;&lt;p&gt;Theoretical (TPSSh Functional) &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; = 454 K (basis set 1) and 237 K (basis set 2)&lt;/p&gt;&#xA;&lt;p&gt;As can be easily seen, we are still far from the accurate result.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&#xA;Up to now, which is the most correct way of simulating the SCO transition? How realistic is it to reproduce the hysteresis on the magnetization properties in a temperature sweep?&lt;/p&gt;&#xA;" OwnerUserId="290" LastEditorUserId="5" LastEditDate="2021-03-16T22:26:01.420" LastActivityDate="2021-03-16T22:26:01.420" Title="Calculation of the relative energies in a Spin Crossover material" Tags="|magnetism|metal-complexes|spin-crossover-complexes|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="373" PostTypeId="5" CreationDate="2020-05-04T13:44:02.210" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-04T13:44:02.210" LastActivityDate="2020-05-04T13:44:02.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="374" PostTypeId="4" CreationDate="2020-05-04T13:44:02.210" Score="0" Body="Questions relating to convergence testing methods in matter modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-06-26T21:53:01.317" LastActivityDate="2020-06-26T21:53:01.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="375" PostTypeId="2" ParentId="123" CreationDate="2020-05-04T14:21:00.033" Score="9" Body="&lt;p&gt;I have found some interesting lectures about DFT in general that could be useful for you:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/playlist?list=PLbgFiRV2JFy-VQ3D6cJjn5jkXmAsjQPiT&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2017 Hands-on Workshop Density-Functional Theory and Beyond&lt;/strong&gt;&lt;/a&gt;  - Humboldt University Berlin, Germany.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/channel/UCfLssAro7SMxgaeKTNFFeeA/feed&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Teaching the Theory in Density Functional Theory&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.ipam.ucla.edu/programs/summer-schools/putting-the-theory-back-in-density-functional-theory/?tab=schedule&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Putting the Theory Back in Density Functional Theory&lt;/strong&gt;&lt;/a&gt; - Institute for Pure &amp;amp; Applied Mathematics (UCLA)&lt;/p&gt;&#xA;" OwnerUserId="290" LastActivityDate="2020-05-04T14:21:00.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="376" PostTypeId="2" ParentId="43" CreationDate="2020-05-04T15:22:10.980" Score="13" Body="&lt;p&gt;I concur with the answer by Alone programmer, but his answer only gives half the story. The coefficients or the model parameters come into the picture later and are actually obtained by optimization of both the experimentally obtained and theoretically calculated data. Here I will discuss the experimental data since the DFT part has already been discussed. The experimental data can be basically classified into three categories:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Structural (Crystallographic): this helps in selecting the Gibbs energy models&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Constitutional: for example, tie-line, invariant points, special points, phase boundaries, phase amounts, etcetera. These can be obtained through suitable experiments.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Thermochemical: for example, enthalpy, activity, heat capacity, etcetera. This data actually serves as constraints during the optimization of the model parameters since using only the constitutional data will make the calculation of model parameters difficult as many solutions are possible without using constraints.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Hope this helps. &lt;/p&gt;&#xA;" OwnerUserId="301" LastActivityDate="2020-05-04T15:22:10.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="377" PostTypeId="1" CreationDate="2020-05-04T16:59:58.260" Score="13" ViewCount="679" Body="&lt;p&gt;Reading some Gaussian related documents (inputs, manuals, books), I found the possibility to setup periodic boundary conditions (PBC) in Gaussian. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As Gaussian is developed only for molecular systems (that are not periodic by nature), what does this mean? How is it useful?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-04T17:48:13.763" LastActivityDate="2020-05-04T18:21:22.567" Title="What is the meaning of periodic boundary condition for molecular systems?" Tags="|gaussian|periodic-boundary-conditions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="378" PostTypeId="1" AcceptedAnswerId="406" CreationDate="2020-05-04T17:36:46.413" Score="13" ViewCount="1390" Body="&lt;p&gt;There are many problems where we want to calculate the binding energy between two systems.&lt;/p&gt;&#xA;&lt;p&gt;Normally, we have a system A, adsorbent (a surface, a nanotube, a protein, etc.), that interact with a system B, adsorbate (atoms, ions, molecules, etc.). The procedure is to calculate the energy of both systems separately &lt;span class=&quot;math-container&quot;&gt;$E_\text{A}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$E_\text{B}$&lt;/span&gt; and to calculate the energy of the complex &lt;span class=&quot;math-container&quot;&gt;$E_{\text{AB}}$&lt;/span&gt;, then the binding energy can be calculated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{\text{bind}} = E_{\text{AB}} - E_\text{A} + E_\text{B}&#xA;\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In case DFT calculations using basis set, we also need to apply the basis set superposition error (BSSE) correction (&lt;a href=&quot;https://doi.org/10.1080/00268977000101561&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Physics, 1970, VOL. 19, NO. 4, 553-566&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The question is: what are the fundamentals of equation (1)?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="730" LastEditDate="2020-06-21T07:40:16.763" LastActivityDate="2020-06-21T07:40:16.763" Title="What are the scientific justifications of the binding energy equation?" Tags="|density-functional-theory|basis-sets|binding-energy|basis-set-superposition-error|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="379" PostTypeId="2" ParentId="17" CreationDate="2020-05-04T17:56:04.780" Score="14" Body="&lt;h1&gt;Force fields&lt;/h1&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;These calculations are based on interatomic potentials and lattice energy&#xA;minimization.&lt;/p&gt;&#xA;&lt;p&gt;As an example, lets take the DREIDING force field. This force&#xA;field uses general force constants, and the parameters are defined for all&#xA;possible combinations of atoms (J. Phys. Chem. 1990, 94, 8897-8909).&lt;/p&gt;&#xA;&lt;p&gt;The total potential energy, &lt;span class=&quot;math-container&quot;&gt;$U_T$&lt;/span&gt;, of an arbitrary system can be written as the sum&#xA;of bonded interactions (&lt;span class=&quot;math-container&quot;&gt;$U_b$&lt;/span&gt;) and nonbonded interactions (&lt;span class=&quot;math-container&quot;&gt;$U_{nb}$&lt;/span&gt;):&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{UT}&#xA;U_T = U_b + U_{nb}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the DREIDING force field, the bonded&#xA;interactions consist of bond stretch between two atoms (&lt;span class=&quot;math-container&quot;&gt;$U_B$&lt;/span&gt;); bond--angle&#xA;bend between three atoms (&lt;span class=&quot;math-container&quot;&gt;$U_A$&lt;/span&gt;); dihedral torsion angle between four atoms&#xA;(&lt;span class=&quot;math-container&quot;&gt;$U_D$&lt;/span&gt;), and inversion term (&lt;span class=&quot;math-container&quot;&gt;$U_I$&lt;/span&gt;) (also between four atoms). The nonbonded&#xA;interactions consist of the van der Waals (dispersion) (&lt;span class=&quot;math-container&quot;&gt;$U_{vdW}$&lt;/span&gt;), the&#xA;electrostatic (&lt;span class=&quot;math-container&quot;&gt;$U_{Coul}$&lt;/span&gt;), and the hydrogen (&lt;span class=&quot;math-container&quot;&gt;$U_H$&lt;/span&gt;) interactions, respectively.&lt;/p&gt;&#xA;&lt;p&gt;The bond stretch interactions, &lt;span class=&quot;math-container&quot;&gt;$U_B$&lt;/span&gt;, is described as a simple harmonic&#xA;oscillator:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_B}&#xA;  U_B = (1/2)k_e\left(R - R_e\right)^2&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$k_e$&lt;/span&gt; represents the intensity of the bond, and &lt;span class=&quot;math-container&quot;&gt;$R_e$&lt;/span&gt; the equilibrium&#xA;distance between the two bonded atoms.&lt;/p&gt;&#xA;&lt;p&gt;The bond--angle bend, &lt;span class=&quot;math-container&quot;&gt;$U_A$&lt;/span&gt;, between atoms &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is taken as an&#xA;harmonic cosine:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_A}&#xA;  U_A = (1/2)C_{IJK}\left[\cos\theta_{IJK}-\cos\theta^{0}_{J}\right]^2&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\theta_{IJK}$&lt;/span&gt; is the angle between bonds &lt;span class=&quot;math-container&quot;&gt;$IJ$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$JK$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$\theta_{j}^{0}$&lt;/span&gt; is the equilibrium angle, and &lt;span class=&quot;math-container&quot;&gt;$C_{IJK}$&lt;/span&gt; is related to the&#xA;force constant &lt;span class=&quot;math-container&quot;&gt;$k_{IJK}$&lt;/span&gt; as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{angulocte}&#xA;  C_{IJK}=\frac{k_{IJK}}{(\sin\theta^{0}_{J})^2}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The torsion interaction, &lt;span class=&quot;math-container&quot;&gt;$U_D$&lt;/span&gt;, for two bonds &lt;span class=&quot;math-container&quot;&gt;$IJ$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$KL$&lt;/span&gt; connected by a&#xA;common bond &lt;span class=&quot;math-container&quot;&gt;$JK$&lt;/span&gt; has the following form:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_D}&#xA;  U_D = (1/2)V_{JK}\left\{1-\cos[n_{JK}(\varphi-\varphi^{0}_{JK})]\right\}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$V_{JK}$&lt;/span&gt; is the barrier potential, &lt;span class=&quot;math-container&quot;&gt;$n_{JK}$&lt;/span&gt; is the periodicity,&#xA;&lt;span class=&quot;math-container&quot;&gt;$\varphi$&lt;/span&gt; is the dihedral angle between &lt;span class=&quot;math-container&quot;&gt;$IJK$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$JKL$&lt;/span&gt; planes, and&#xA;&lt;span class=&quot;math-container&quot;&gt;$\varphi^{0}_{JK}$&lt;/span&gt; is the equilibrium angle.&lt;/p&gt;&#xA;&lt;p&gt;The last term included in the bonded interactions is the inversion term,&#xA;&lt;span class=&quot;math-container&quot;&gt;$U_I$&lt;/span&gt;. This term describes how easy or difficult it is to keep all bonds in&#xA;the same plane:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_I}&#xA;  U_I = (1/2)k_{inv}\left(\Psi-\Psi_{0}\right)^2.&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; is the angle between bond &lt;span class=&quot;math-container&quot;&gt;$IL$&lt;/span&gt; and plane &lt;span class=&quot;math-container&quot;&gt;$JIK$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Psi_{0}$&lt;/span&gt; is&#xA;defined in such a way that its value is zero for a planar molecule.&lt;/p&gt;&#xA;&lt;p&gt;The nonbonded interactions are not calculated for atoms involved in bonded or&#xA;angle interactions (bond--angle bend and dihedral torsion angle).&lt;/p&gt;&#xA;&lt;p&gt;The interaction between two neutral atoms, &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;, which present nonzero&#xA;dipole moment results in an attractive force, known as van der Waals force.&#xA;As the atoms approach one each other, Coulombian repulsion forces arise due&#xA;to charges of the same signal. The &lt;span class=&quot;math-container&quot;&gt;$12-6$&lt;/span&gt; Lennard-Jones' potential energy,&#xA;&lt;span class=&quot;math-container&quot;&gt;$U_{vdW}$&lt;/span&gt;, brings a good description of these two characteristics, repulsive&#xA;and attractive:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_vdW}&#xA;  U_{vdW} = \frac{A}{R^{12}_{IJ}}-\frac{B}{R^{6}_{IJ}}&#xA;\end{equation}&lt;/span&gt;&#xA;where the first term represents the repulsive and the second one the&#xA;attractive interaction, respectively.  The &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; parameters depends on&#xA;the two atoms types, and &lt;span class=&quot;math-container&quot;&gt;$R_{IJ}$&lt;/span&gt; is the distance between atoms &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The nonbonded electrostatic interaction, &lt;span class=&quot;math-container&quot;&gt;$U_{Coul}$&lt;/span&gt;, takes the form proposed&#xA;by Coulomb:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_Coul}&#xA;  U_{Coul} = C \frac{Q_I Q_J}{\varepsilon R_{IJ}}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is a constant (used to do conversion between energy units), &lt;span class=&quot;math-container&quot;&gt;$Q_I$&lt;/span&gt;&#xA;and &lt;span class=&quot;math-container&quot;&gt;$Q_J$&lt;/span&gt; are the atomic charges, &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt; is the dielectric constant,&#xA;and &lt;span class=&quot;math-container&quot;&gt;$R_{IJ}$&lt;/span&gt; is the distance between atoms &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The last nonbonded interaction took into account is the hydrogen interaction,&#xA;&lt;span class=&quot;math-container&quot;&gt;$U_H$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{U_H}&#xA;U_H = D_H\left[5\left(\frac{R_H}{R_{DA}}\right)^{12}-6\left(\frac{R_H}{R_{DA}}\right)^{10}\right]\cos^{4}(\theta_{DHA}).&#xA;\end{equation}&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$\theta_{DHA}$&lt;/span&gt; is the angle between the hydrogen donor&#xA;atom &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;, the hydrogen &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and the hydrogen acceptor atom &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;; &lt;span class=&quot;math-container&quot;&gt;$R_{DA}$&lt;/span&gt; is&#xA;the distance between the donor &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; and acceptor &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; atoms. The parameters&#xA;&lt;span class=&quot;math-container&quot;&gt;$D_H$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R_H$&lt;/span&gt; depends on the conversion for assigning charges.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example software: GULP&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://gulp.curtin.edu.au/gulp/&quot; rel=&quot;noreferrer&quot;&gt;GULP&lt;/a&gt; is a program for performing a variety of types of simulation on materials using boundary conditions of 0-D (molecules and clusters), 1-D (polymers), 2-D (surfaces, slabs and grain boundaries), or 3-D (periodic solids). The focus of the code is on analytical solutions, through the use of lattice dynamics, where possible, rather than on molecular dynamics. A variety of force fields can be used within GULP spanning the shell model for ionic materials, molecular mechanics for organic systems, the embedded atom model for metals and the reactive REBO potential for hydrocarbons. Analytic derivatives are included up to at least second order for most force fields, and to third order for many.&lt;/p&gt;&#xA;&lt;p&gt;It had implemented different potential models: two-body (Buckingham, Buckingham four range, Lennard-Jones, Morse, etc.); three-body (Three-body harmonic, Axilrod-Teller, Urey-Bradley, etc.); four-body (Four-body torsional, ESFF torsional, UFF4, etc.); Many-body (Embedded Atom Method, Tersoff, REBO, ReaxFF, etc.).&lt;/p&gt;&#xA;&lt;p&gt;General overview (systems, calculated properties, etc.) can be read &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/overview.cfm&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-04T18:05:48.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="380" PostTypeId="2" ParentId="26" CreationDate="2020-05-04T18:14:13.323" Score="7" Body="&lt;p&gt;While I can't speak to the specific interest of solar cells, Perovskite is the primary ore source for Titanium. Owing to the fact that alloys of Titanium played a critical role in modernization of weapons technologies that occurred during the cold war period, there was a LOT of research money into titanium projects during the 1970s to early 1990s. For instance, the hull of the SR-71 blackbird is a special titanium alloy that allows it to fly at MACH 3 and at &gt;100,000 ft (also while its top secret there's some evidence that radar deflecting paints have titanium in them). As such, defense money in  the US and former CCCP was pouring into anything even remotely titanium related (analogous to Machine Learning stuff today). I'd imagine once people found out that perovskite was actually decent for the solar cell stuff that created a reinforcing effect, where grant writers and readers both bought into giving money to this subset of solar cell research, as it was established science.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;TL;DR: If I was a solar cell research a couple decades ago, I'd write a perovskite related grant to get a lot of money, and everything snowballed from that.&lt;/p&gt;&#xA;" OwnerUserId="256" LastEditorUserId="5" LastEditDate="2020-05-04T18:16:23.253" LastActivityDate="2020-05-04T18:16:23.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="381" PostTypeId="2" ParentId="377" CreationDate="2020-05-04T18:21:22.567" Score="11" Body="&lt;p&gt;A periodic boundary condition creates a box around your molecule (or surface) and then treats the molecule leaving the box on the right side as entering the box from the left. This is particularly useful for surfaces as otherwise the atoms at the edges (but not on top where you'd be exposed to a solvent) would otherwise degrade into open space. This preserves the physicality of a surface extending to a much larger size than is computationally feasible.&lt;/p&gt;&#xA;" OwnerUserId="256" LastActivityDate="2020-05-04T18:21:22.567" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="382" PostTypeId="1" CreationDate="2020-05-04T18:29:40.327" Score="21" ViewCount="1144" Body="&lt;p&gt;What methods and tools are used for building models of grain boundaries?&lt;br&gt;&#xA;I mean initial models that are then optimized using molecular dynamics potentials or a different methods.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;When I was involved in such things 10-15 years ago we were writing own codes to generate starting structures. Both big systems that emulated nano-sized policrystals&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/16s8t.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/16s8t.png&quot; alt=&quot;policrystal&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;and small bicrystals to analyze particular boundary types&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wNvSW.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wNvSW.png&quot; alt=&quot;bicrystal&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(I added pictures to clarify what type of things I'm writing about)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I wonder what tools (if any) are used nowadays?&lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="5" LastEditDate="2020-05-06T04:16:45.770" LastActivityDate="2020-05-07T21:32:07.337" Title="What tools are used for the preparation of grain boundary models?" Tags="|software|grain-boundaries|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="383" PostTypeId="2" ParentId="364" CreationDate="2020-05-04T18:30:49.783" Score="16" Body="&lt;p&gt;The &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; (ASE) is a pretty big name missing from your list. It can read in a variety of VASP-generated output files and do several post-processing analyses. More importantly, it can be used to set up calculations and even run them using its &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/calculators/vasp.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;Vasp()&lt;/code&gt; calculator&lt;/a&gt;, provided you link it to a VASP executable. You can read more about ASE in &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/aa680e/meta&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt; also has several pre- and post-processing tools that work with VASP, although you cannot as easily launch calculations from the tool like you can with ASE. Pymatgen is a more general platform meant for materials analysis, but there are indeed several &lt;a href=&quot;https://pymatgen.org/pymatgen.io.vasp.html&quot; rel=&quot;noreferrer&quot;&gt;VASP utilities&lt;/a&gt;. You can read more about Pymatgen in &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0927025612006295&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are also the highly popular &lt;a href=&quot;https://theory.cm.utexas.edu/vtsttools/scripts.html&quot; rel=&quot;noreferrer&quot;&gt;VTST Tools scripts&lt;/a&gt;, which can be used to parse output files for various properties and set up transition state calculations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;And then there are countless short scripts scattered around the Internet for various use-cases, such as those of &lt;a href=&quot;https://www.nsc.liu.se/~pla/vasptools/&quot; rel=&quot;noreferrer&quot;&gt;Peter Larsson&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Of course, this excludes the many dozens of GUI-based programs that can parse VASP output files, such as those listed &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_molecular_graphics_systems&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-04T18:30:49.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="384" PostTypeId="1" CreationDate="2020-05-04T18:39:11.750" Score="13" ViewCount="98" Body="&lt;p&gt;Nonorthogonal configuration interaction is known to be a computationally inefficient approach. Recently, there has been a number of developments that have been done to improve the efficiency of calculations using nonorthogonal orbitals, as mentioned in &lt;a href=&quot;https://materials.stackexchange.com/questions/171/are-there-any-programs-that-can-do-non-orthogonal-ci/192#192&quot;&gt;this question&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: In which situations or problems does this method  outperform the 'standard' method which uses orthogonal orbitals?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="7" LastEditDate="2020-05-06T16:44:43.080" LastActivityDate="2020-06-10T14:36:35.970" Title="In which situations/problems, does one need to employ the nonorthogonal configuration interaction method?" Tags="|quantum-chemistry|nonorthogonal-ci|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="385" PostTypeId="1" AcceptedAnswerId="1488" CreationDate="2020-05-04T19:38:24.957" Score="22" ViewCount="252" Body="&lt;p&gt;Are there good benchmarks available for testing homemade Ewald summation code?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Optimally it would be very nice if there was several types of systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;NIST has a very nice benchmark for energies of SPC/E water configurations &lt;a href=&quot;https://www.nist.gov/mml/csd/chemical-informatics-research-group/spce-water-reference-calculations-10a-cutoff&quot; rel=&quot;noreferrer&quot;&gt;NIST SPCE&lt;/a&gt; made up of 100, 200, 300, 750 water molecules and breaks the energy down into LJ, LJ long range correction, Ewald real, Ewald recipricol, Ewald self, Ewald intra.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, it would be nice to also test Forces and pressure as well. It would also be nice to do this for flexible molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While it is possible to generate a configuration in an open source package like Gromacs for instance, I am hesitant because there are so many unseen variables. The NIST data is very clear on what their parameters were and it takes no digging to ensure you use the same protocol. It doesn't help that it is well known that different packages, when given the same input parameters return different results, even if slightly different. A simple, purpose made testing code/database would be nice.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2020-05-06T04:19:53.447" LastActivityDate="2020-07-08T16:55:23.783" Title="Benchmarking data for Ewald summation algorithms" Tags="|intermolecular-forces|forcefields|electrostatic|ewald-summation|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="386" PostTypeId="2" ParentId="2" CreationDate="2020-05-04T21:06:44.650" Score="16" Body="&lt;p&gt;This paper published by Bikash Kanungo, Paul M. Zimmerman &amp;amp; Vikram Gavini provide an interesting solution to getting closer to a &quot;universal functional&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41467-019-12467-0&quot; rel=&quot;noreferrer&quot;&gt;Exact exchange-correlation potentials from ground-state electron densities&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;They have mapped very accurate electronic densities from &lt;em&gt;ab initio&lt;/em&gt; full configuration interaction methods onto an exact exchange correlation functional. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The author's call this inverse DFT since it is going from electron densities to exchange potentials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Specifically the authors believe the&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;inverse DFT problem to be instrumental in generating &lt;span class=&quot;math-container&quot;&gt;${\rho(i),v(i)_{xc}}$&lt;/span&gt;&#xA;  pairs, using &lt;span class=&quot;math-container&quot;&gt;$\rho(i)$&lt;/span&gt;’s from correlated ab-initio calculations.&#xA;  Subsequently, these can be used as training data to model &lt;span class=&quot;math-container&quot;&gt;$v_{xc}[\rho]$&lt;/span&gt;&#xA;  through machine-learning algorithms which are designed to preserve the&#xA;  functional derivative requirement on vxc[ρ]. Furthermore, the xc&#xA;  energy (&lt;span class=&quot;math-container&quot;&gt;$E_{xc}[\rho]$&lt;/span&gt;) can be directly evaluated through line integration on&#xA;  &lt;span class=&quot;math-container&quot;&gt;$v_{xc}[\rho]$&lt;/span&gt;.&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;So maybe sometime soon we can expect a &quot;Universal&quot; DFT exchange functional which is born from exact ab-initio computations and an inverse-DFT generated functional.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-05T04:45:48.200" LastActivityDate="2020-05-05T04:45:48.200" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="387" PostTypeId="1" AcceptedAnswerId="1092" CreationDate="2020-05-04T21:27:25.113" Score="19" ViewCount="994" Body="&lt;p&gt;From what I understand, one major issue in modeling charged point defects in materials is the existence of artificial interactions between charged defects and their periodic images. Even when using large supercells, as is typical when modeling uncharged point defects, the problem persists.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the past, I briefly used the &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2018.01.004&quot; rel=&quot;noreferrer&quot;&gt;PyCDT&lt;/a&gt; &lt;a href=&quot;https://bitbucket.org/mbkumar/pycdt/src/master/&quot; rel=&quot;noreferrer&quot;&gt;Python package&lt;/a&gt;, which uses &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.102.016402&quot; rel=&quot;noreferrer&quot;&gt;sxdefectalign&lt;/a&gt;, and VASP to calculate the formation energies of charged point defects. Besides using plane-wave DFT and the correction scheme in sxdefectalign, are there other approaches to modeling charged defects that might trade speed for accuracy or vice-versa? What other challenges are associated with modeling charged defects?&lt;/p&gt;&#xA;" OwnerUserId="166" LastActivityDate="2020-05-27T21:34:14.900" Title="What are some approaches to modeling charged point defects in materials?" Tags="|density-functional-theory|defects|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="388" PostTypeId="1" CreationDate="2020-05-04T21:35:57.523" Score="14" ViewCount="604" Body="&lt;p&gt;I wonder if there are any books or resources to start learning Materials modelling using methods&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;density functional theory&lt;/li&gt;&#xA;&lt;li&gt;quantum monte carlo&lt;/li&gt;&#xA;&lt;li&gt;molecular dynamics&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="46" LastEditorUserId="88" LastEditDate="2020-05-21T13:36:54.250" LastActivityDate="2021-06-24T17:46:11.310" Title="What are good resources to learn Materials Modeling?" Tags="|density-functional-theory|reference-request|molecular-dynamics|quantum-monte-carlo|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="389" PostTypeId="2" ParentId="176" CreationDate="2020-05-04T23:03:21.453" Score="4" Body="&lt;p&gt;This is more of supplement to Alone Programmer's answer to expand a bit more on the significance of meeting these constraints.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These constraints allow the SCAN functional to reproduce the results of the true density functional for simplified model system. This agreement suggests that the form of the functional is more physically consistent than a functional that does not follow these constraints. In principle, agreeing with the true density functional should make SCAN more robust than other functionals and better able to describe systems that it wasn't specifically parameterized for.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-05-04T23:03:21.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="390" PostTypeId="2" ParentId="388" CreationDate="2020-05-05T00:51:32.003" Score="18" Body="&lt;ol&gt;&#xA;&lt;li&gt;I would recommend to start with &lt;a href=&quot;http://Computational%20Materials%20Science:%20An%20Introduction,%20Second%20Edition%20By%20June%20Gunn%20Lee&quot; rel=&quot;noreferrer&quot;&gt;Computational Materials Science: An Introduction&lt;/a&gt; by June Gunn Lee, The book starts from the basics and covers Molecular Dynamics and DFT featuring DFT exercises using VASP, Quantum Espresso and Medea-VASP. It is undergraduate level introduction to the subject&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Pwiov.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Pwiov.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://books.google.co.in/books?id=FzOTAwAAQBAJ&amp;amp;printsec=frontcover&amp;amp;dq=Materials%20Modelling%20using%20Density%20Functional%20Theory&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=0ahUKEwiHyL7svZvpAhXBF3IKHRdDDlMQ6AEIJzAA#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;Materials Modelling Using Density Functional Theory: Properties and Predictions&lt;/a&gt; By Feliciano Giustino is good book to start learning DFT. It is a undergraduate/graduate level book. As a bonus you can also find video lectures &#xA;on &lt;a href=&quot;https://www.paradim.org/cu_ss_2018&quot; rel=&quot;noreferrer&quot;&gt;An Introduction to Density Functional Theory for Experimentalists&lt;/a&gt; by Prof. Feliciano Giustino during DFT Summer School 2018 at Cornell University&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gsxn6.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gsxn6.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-05-05T00:51:32.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="391" PostTypeId="1" AcceptedAnswerId="1489" CreationDate="2020-05-05T01:05:05.963" Score="17" ViewCount="1216" Body="&lt;p&gt;I have used the modified Becke-Johnson (mBJ) exchange potential before, as it was developed and implemented in Wien2K by Fabien Tran and Peter Blaha (&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.226401&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;). In 2013, Éric Germaneau &lt;em&gt;et al.&lt;/em&gt; implemented mBJ in Quantum ESPRESSO, where it is called 'TB09' (&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513000775?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;). Here, I will refer to this meta-GGA as TB09 as it is implemented in Quantum ESPRESSO.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As I understand it, once the Libxc library is installed, the TB09 potential can be called simply by &lt;code&gt;input_dft= 'sla+pw+tb09+tb09'&lt;/code&gt; or &lt;code&gt;input_dft = 'TB09'&lt;/code&gt;. Another note, is that the TB09 potential was defined with LDA correlation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, I have been &lt;em&gt;trying&lt;/em&gt; to run an scf computation using TB09, with norm-conserving LDA scalar-relativistic pseudopotentials. I have not been successful with this computation, and I have tried before with GGA (PBE and PBEsol), norm-conserving and ultra-soft pseudopotentials. I have tried changing the diagonalization method, from the default Davidson to Conjugate-Gradient (cg). I have also tried changing the smearing, mixing mode, and other parameters.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;I have had zero success with the TB09 potential in Quantum ESPRESSO.&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Specifically, I get the good ol' &lt;code&gt;problems computing cholesky&lt;/code&gt; error, although the structure was fully optimized previously with PBEsol.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have modeled the band structure of a this given material with GGA using Quantum ESPRESSO, reproduced the results with the APW+lo method in Wien2K (PBEsol) and then modeled the band structure with mBJ in Wien2K without any issues.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Is there something I am failing to consider? Are there problems in general with the TB09 potential in Quantum ESPRESSO?&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A benefit and motivation to get this right using QE is that it is open source as opposed to Wien2K and VASP. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Happy to share my input file if willing to help.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;References: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;1 : F. Tran and P. Blaha. (2009). &lt;em&gt;Phys. Rev. Lett.&lt;/em&gt; &lt;strong&gt;102&lt;/strong&gt;, 226401  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;2: É. Germaneau &lt;em&gt;et al&lt;/em&gt;. (2013). &lt;em&gt;Comput. Phys. Commun.&lt;/em&gt; &lt;strong&gt;184&lt;/strong&gt; 1697–1700&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-06-30T04:47:39.630" LastActivityDate="2020-07-09T06:23:10.157" Title="Are there problems with the Tran-Blaha modified Becke-Johnson potential (mBJ, a.k.a. TB09) in Quantum ESPRESSO?" Tags="|density-functional-theory|software|vasp|quantum-espresso|functional|" AnswerCount="1" CommentCount="10" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="392" PostTypeId="1" CreationDate="2020-05-05T01:43:56.547" Score="43" ViewCount="2473" Body="&lt;p&gt;In the book &lt;a href=&quot;https://books.google.co.in/books?id=FzOTAwAAQBAJ&amp;amp;printsec=frontcover&amp;amp;dq=Materials%20Modelling%20using%20Density%20Functional%20Theory&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=0ahUKEwiHyL7svZvpAhXBF3IKHRdDDlMQ6AEIJzAA#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;Materials Modelling Using Density Functional Theory: Properties and Predictions&lt;/a&gt; by Feliciano Giustino, a timeline of milestones in DFT was given for achievements between 1964 and 1996:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\small\begin{array}{|c|c|c|} \hline&#xA;\textbf{Year} &amp;amp; \textbf{Milestone} &amp;amp; \textbf{Researchers} \\ \hline&#xA;1964, 1965 &amp;amp; \text{HK Theorem/KS Formulation} &amp;amp; \text{Kohn, Hohenberg, Sham}  \\  &#xA;1972, 1973 &amp;amp; \text{Relativistic DFT} &amp;amp; \text{von Barth/Hedin, Rajapol/Callway} \\  &#xA;1980, 1981 &amp;amp; \text{Local Density Approximiation(LDA)} &amp;amp;\text{Ceperley/Alder, Perdew/Zunger} \\&#xA;1984 &amp;amp; \text{TDDFT} &amp;amp; \text{Runge, Gross}  \\&#xA;1985 &amp;amp; \text{First Principles MD} &amp;amp; \text{Carr, Parrinello}   \\  &#xA;1986 &amp;amp; \text{Quasiparticle Corrections} &amp;amp; \text{Hybertsen, Louie} \\  &#xA;1987 &amp;amp; \text{Density Functional Perturbation Theory} &amp;amp; \text{Baroni, Giannozzi, Testa}  \\  &#xA;1988, 1993 &amp;amp; \text{Toward Chemical Accuracy} &amp;amp; \text{Lee/Yang/Parr (1988), Becke (1993)} \\&#xA;1991 &amp;amp; \text{Hubbard Correction} &amp;amp; \text{Anisimov, Zaanen, Andersen} \\&#xA;1992, 1996 &amp;amp; \text{Generalized Gradient Approximation} &amp;amp; \text{Perdew/Burke/Ernzerhof} \\&#xA;\hline&#xA;\end{array}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Has there been any milestone after 1996, or not included in the above list?&lt;/strong&gt; &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Please limit each answer to one milestone!&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Since there's now so many answers that it takes a very long time to scroll down to a specific one, I Have created links for the milestones that have already been explained in an answer:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1173/5&quot;&gt;1993 (Becke) Hybrid Functionals&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1284/5&quot;&gt;1995 (Casida) TD-DFRT&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1188/5&quot;&gt;2004 (Yanai &lt;em&gt;et al.&lt;/em&gt;) Range separation&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1212/5&quot;&gt;2005 (Bartlett) &lt;em&gt;ab initio&lt;/em&gt; DFT&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;2006 (Grimme) Double Hybrids&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1227/5&quot;&gt;2007 (Becke-Johnson) Dispersion correction&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1260/5&quot;&gt;2013 (Kim &lt;em&gt;et al.&lt;/em&gt;) Density-corrected DFT&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1192/5&quot;&gt;2015 (Sun &lt;em&gt;et al.&lt;/em&gt;) SCAN functional&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-12T22:17:12.367" LastActivityDate="2021-06-19T18:28:29.770" Title="What are some recent developments in density functional theory?" Tags="|density-functional-theory|functional|one-topic-per-answer|algorithms|history|" AnswerCount="16" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="393" PostTypeId="1" CreationDate="2020-05-05T01:57:20.413" Score="13" ViewCount="1241" Body="&lt;p&gt;DFT codes like Siesta, QuantumATK, Questaal, and Smeagol having localized basis sets have NEGF implementations available. But not in plane wave codes like VASP and Quantum Espresso. Why is it so?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-05-05T04:03:11.777" LastActivityDate="2020-09-15T15:05:48.460" Title="Why is the Nonequilibrium Green’s function (NEGF) method for quantum transport not implemented in plane wave codes like VASP and Quantum Espresso?" Tags="|density-functional-theory|vasp|quantum-espresso|greens-functions|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="394" PostTypeId="2" ParentId="329" CreationDate="2020-05-05T03:12:03.607" Score="16" Body="&lt;p&gt;I suspect it's a combination of three factors:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;First, there's a fundamental limit of the efficiency of solar cells.  A solar cell is effectively a heat engine that uses the 6000K Sun as the heat source and the Earth's ~300K ambient temperature as the heat sink.  Given that, the efficiency of a &quot;perfect&quot; solar cell tops out at around 95% for an infinite-sized Sun, or 69% for the Sun as it actually appears in the sky.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Second, increasing the junction count produces diminishing returns.  You mention that the slope of four-junction cells follows the trend of three-junction cells -- in contrast, changing from single-junction to two-junction, and two-junction to three-junction cells both produced an immediate jump in efficiency.  Yes, you get more efficiency by adding more junctions, but each additional junction requires more effort for less improvement.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;And third, solar panels are a reasonably mature commercialized technology.  Efficiency is &quot;good enough&quot;, and research effort is directed more towards making cheaper cells than making efficient cells.  Most users, if they need more power, can just put up a bigger array, they don't need a more-efficient one.&lt;/p&gt;&#xA;" OwnerUserId="53" LastActivityDate="2020-05-05T03:12:03.607" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="395" PostTypeId="2" ParentId="382" CreationDate="2020-05-05T04:33:54.383" Score="13" Body="&lt;p&gt;If you are looking for generating synthesized microstructures for using it in Phase-Field simulation, the best choice is &lt;a href=&quot;http://dream3d.bluequartz.net/&quot; rel=&quot;noreferrer&quot;&gt;Dream 3D&lt;/a&gt;, where you can control the distribution of grains and their crystallographic orientations:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JImvs.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JImvs.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you are looking for a framework to generate synthesized polycrystalline structures for molecular dynamics simulation, the best tool is &lt;a href=&quot;https://atomsk.univ-lille.fr/&quot; rel=&quot;noreferrer&quot;&gt;Atomsk&lt;/a&gt;, that is compatible with LAMMPS, DL_POLY, VASP, QuantumEspresso, SIESTA, etc.:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WIXtc.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WIXtc.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-05T04:33:54.383" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="396" PostTypeId="2" ParentId="393" CreationDate="2020-05-05T04:44:48.423" Score="10" Body="&lt;p&gt;I quote from Derek Stewart that gave the answer &lt;a href=&quot;https://www.researchgate.net/post/How_to_implement_nonequilibrium_Greens_function_NEGF_method_in_VASP&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Since VASP relies on a non-localized basis set (plane waves), it is not possible to implement a non-equilibrium Green's function approach directly. The NEGF approach can be easily expressed using a localized basis set where you can define local Hamiltonians and local Green's Functions. In the transmission function for a device with N layers, you have terms, &lt;span class=&quot;math-container&quot;&gt;$G^R_{1N}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$G^{A}_{N1}$&lt;/span&gt;, which you can think of as a measure of the ability for electrons to travel between layer 1 to layer N. This spatial information falls out naturally with a localized basis set. This is why codes like Siesta, QuantumATK, Questaal, and Smeagol all use localized basis sets for their NEGF codes.&lt;/p&gt;&#xA;&lt;p&gt;For plane wave codes like VASP, you have two options for calculating electronic transport. You can calculate the zero bias transmission of electrons using the scattering approach of Choi and Ihm (Phys. Rev. B, 59, 2267, 1999). Smogunov and Dal Corso did a nice job implementing this in the PWCOND code for Quantum Espresso (see Phys. Rev. B, 70, 045417 (2014)). However, I am not sure if this approach can be used at finite bias. The other route is to run the plane wave calculation and then map your results to a localized basis set using Wannier functions or some other tight-binding representation. This is done in the code WanT. However, with this route, you are always stuck with a two step process and you have to be careful that your mapping to the localized basis set is correct. So in the end, you may be better off going with a localized basis code for your transport calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="37" LastEditorUserId="1218" LastEditDate="2020-09-15T15:05:48.460" LastActivityDate="2020-09-15T15:05:48.460" CommentCount="5" CommunityOwnedDate="2020-09-15T16:22:47.353" ContentLicense="CC BY-SA 4.0" />
  <row Id="397" PostTypeId="2" ParentId="365" CreationDate="2020-05-05T05:09:28.433" Score="24" Body="&lt;h1&gt;Python&lt;/h1&gt;&#xA;&lt;p&gt;@taciteloquence has already mentioned Python for data analysis and visualization, but let me add one more angle: automation.&lt;/p&gt;&#xA;&lt;p&gt;Simulation nowadays often means high-throughput, automated simulation. Not only for large scale projects, like Materials Project but also individual projects where large amounts of data generated for screening properties, screeing different geometries, generating data files for machine learning, ABC approaches etc.. For building workflows (eg with automate) or examining the generated databases, Python is good language.&lt;/p&gt;&#xA;" OwnerUserId="91" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-21T21:16:43.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="398" PostTypeId="1" CreationDate="2020-05-05T05:21:49.700" Score="19" ViewCount="202" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Heterogeneous_catalysis&quot; rel=&quot;noreferrer&quot;&gt;Heterogeneous catalysis&lt;/a&gt; is known to be very important:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Approximately 35% of the world's GDP is influenced by catalysis. The production of 90% of chemicals (by volume) is assisted by solid catalysts.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;What considerations go into a model of these types of reactions? For example, how would one generally go about modeling surface catalysis (e.g. software/algorithms)? &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Besides software what considerations should be taken into account that are different from homogeneous catalysis?&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="52" LastEditorUserId="189" LastEditDate="2020-05-05T14:09:35.860" LastActivityDate="2020-08-29T17:48:24.033" Title="How to model heterogeneous catalysis?" Tags="|surfaces|catalysis|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="399" PostTypeId="2" ParentId="27" CreationDate="2020-05-05T05:33:32.917" Score="8" Body="&lt;h1&gt;DDSCAT&lt;/h1&gt;&#xA;&lt;p&gt;You can use &lt;a href=&quot;http://ddscat.wikidot.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;the DDSCAT (Discrete Dipole Scattering) package&lt;/a&gt; for nanoparticles &amp;gt;5 nm. Many of the optical properties of nanoparticles (absorption, scattering, extinction coefficient) can be solved via classic electrodynamics, i.e. solving the Maxwell Equations when light interacts with a nano-sized object with no quantum packages necessary. To determine the optical properties of nanomaterials classically, the most rigorous approach is solving Maxwell's Equations analytically via Mie Theory (&lt;a href=&quot;https://pure.tue.nl/ws/portalfiles/portal/69570032/Bertens_MWMC_2015.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;see section 2.2 of Bertens&lt;/a&gt;). However, exact analytical solutions to the scattering problem only exist for a limited number of geometries (sphere, cylinder, etc.). The DDSCAT package approximates a continuous object utilizing a series of point dipoles on a 3D lattice, of which a direct solution to Maxwell's Equations can readily be solved.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/dHmNq.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dHmNq.jpg&quot; alt=&quot;sphere converted to point dipoles&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The image above shows an example of point dipoles constructed for input into DDSCAT (Draine, 1988). In addition to the point geometry, to run DDSCAT, the complex polarizability of the material and an 'effective' radius must be provided. The complex polarizability of materials like gold, silver, etc. can be found readily online. The effective radius of an object is solved by determining the total volume of your object, then solving for radius as if the object were spherical (V&lt;sub&gt;obj&lt;/sub&gt; = 4/3r&lt;sub&gt;eff&lt;/sub&gt;&lt;sup&gt;3&lt;/sup&gt;).&lt;/p&gt;&#xA;" OwnerUserId="69" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-31T23:44:01.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="400" PostTypeId="2" ParentId="365" CreationDate="2020-05-05T06:04:34.490" Score="19" Body="&lt;h1&gt;Python&lt;/h1&gt;&#xA;&lt;p&gt;Python is definitely a good language for scientific calculation.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The syntax is very simple. It is not hard to implement some novel method and conduct preliminary tests.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The library is abundant. One could almost do everything in python. There are many open source libraries in python that implement a variety of libraries of scientific computing and data analysis.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It is not hard to build interface with other languages. One drawback of python is its low efficiency. While there are many ways to build interface to other languages(e.g. to build python-c interface, one could use Cython (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1385/63&quot;&gt;relevant answer&lt;/a&gt;) or cprofile):&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="141" LastEditorUserId="63" LastEditDate="2023-07-03T15:32:45.653" LastActivityDate="2023-07-03T15:32:45.653" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="401" PostTypeId="2" ParentId="365" CreationDate="2020-05-05T07:25:44.220" Score="33" Body="&lt;h1&gt;Julia&lt;/h1&gt;&#xA;&lt;p&gt;The answers above allude to what some call the &amp;quot;two-language problem&amp;quot;. In materials science it takes the form of writing your code in Fortran for speed, and writing an interface to it in Python for sanity and interactivity. Fortran will not go away any time soon due to the massive amount of legacy code available. For new codes, there is a new option: &lt;strong&gt;Julia&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;With a little bit of care (follow a few simple rules given in the &amp;quot;performance tips&amp;quot; section of the manual), one can easily mix Python-style high-level code and Fortran-style tight inner loops. Julia is easily interoperable with other languages, and reuse existing libraries (the Python interface, in particular, being particularly seamless). Coupled with a very good native ecosystem for numerical computing (unlike Python which is forced to hack together a core language not designed for numerics and NumPy), this makes it a particularly appealing language to use.&lt;/p&gt;&#xA;&lt;p&gt;At least that has been our experience developing DFTK (&lt;a href=&quot;https://github.com//JuliaMolSim/DFTK.jl/&quot; rel=&quot;noreferrer&quot;&gt;https://github.com//JuliaMolSim/DFTK.jl/&lt;/a&gt;), a plane-wave DFT code built from scratch. The code is about one year old, ~4k LOC, and covers the basics of such codes. Had we chosen Fortran for this task, we'd still be writing the input file parser and makefile (I'm only partly joking).&lt;/p&gt;&#xA;" OwnerUserId="316" LastEditorUserId="24" LastEditDate="2020-06-25T00:28:50.877" LastActivityDate="2020-06-25T00:28:50.877" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="402" PostTypeId="2" ParentId="266" CreationDate="2020-05-05T08:20:14.530" Score="14" Body="&lt;p&gt;Here is an introduction to DFT functionals: &lt;a href=&quot;https://dft.uci.edu/pubs/RCFB08.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://dft.uci.edu/pubs/RCFB08.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In short, the Perdew-Burke-Ernzerhof (PBE) functional is very popular because it is a non-empirical functional with reasonable accuracy over a wide range of systems. While PBE is typically not the most accurate GGA (generalized gradient approximation) functional for a given system, it usually is not too far off either. Empirical functionals offer better accuracy for systems they are parametrized for, e.g. &quot;BLYP has smaller errors for main-group organic molecule energetics&quot;, but fail in others.&lt;/p&gt;&#xA;" OwnerUserId="295" LastActivityDate="2020-05-05T08:20:14.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="403" PostTypeId="1" AcceptedAnswerId="405" CreationDate="2020-05-05T10:56:44.710" Score="15" ViewCount="308" Body="&lt;p&gt;Density Functional Theory based codes evaluate quite successfully intramolecular forces responsible of the atomic bonding. Within this technique one is able to obtain molecular relaxed structures that match almost perfectly the &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2012/dt/c2dt12232d#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;experimentally measured geometry.&lt;/a&gt; This is particularly true for very diluted single molecule structures in which the intermolecular interactions are almost negligible. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question arises regarding the non-covalent &lt;a href=&quot;https://en.wikipedia.org/wiki/Intermolecular_force&quot; rel=&quot;noreferrer&quot;&gt;intermolecular interactions&lt;/a&gt; appearing in molecular solids (Hydrogen bonding, ion-dipole forces, dipolar (and quadrupolar) interaction, van der Waals interaction, London forces, among others).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is the correct formulation of DFT to include such forces in the calculation thus producing an adequate result in structural modeling of new molecular materials?&lt;/p&gt;&#xA;" OwnerUserId="290" LastActivityDate="2020-05-05T12:38:51.877" Title="DFT modeling intermolecular interactions" Tags="|density-functional-theory|intermolecular-forces|molecular-modeling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="404" PostTypeId="1" CreationDate="2020-05-05T11:58:32.080" Score="23" ViewCount="588" Body="&lt;p&gt;Materials modeling is very computationally intensive and first-principles simulation of a real system of reasonable size typically involves the use of classical supercomputers.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How can quantum computing accelerate materials modeling? Are there differences in how quantum computing can be used to accelerate wavefunction vs. density functional methods?&lt;/p&gt;&#xA;" OwnerUserId="189" LastActivityDate="2020-05-14T03:30:31.377" Title="How can quantum computing accelerate materials modeling?" Tags="|electronic-structure|quantum-chemistry|quantum-computing|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="405" PostTypeId="2" ParentId="403" CreationDate="2020-05-05T12:38:51.877" Score="9" Body="&lt;p&gt;They are included in long range type functionals. Here are some references:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.20495&quot; rel=&quot;noreferrer&quot;&gt;S. Grimme, Semiempirical GGA-type density functional constructed with a long-range dispersion correction, J. Comput. Chem. 27 (2006) 1787.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.92.246401&quot; rel=&quot;noreferrer&quot;&gt;M. Dion, H. Rydberg, E. Schroder, D. Langreth, B. Lundqvist, Van der Waals&#xA;density functional for general geometries, Phys. Rev. Lett. 92 (2004) 246401.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.096102&quot; rel=&quot;noreferrer&quot;&gt;G. Roman-Perez, J.M. Soler, Efficient implementation of a van der Waals&#xA;density functional: application to double-wall carbon nanotubes, Phys. Rev.&#xA;Lett. 103 (2009) 096102.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/22/2/022201&quot; rel=&quot;noreferrer&quot;&gt;J. Klimes, D.R. Bowler, A. Michaelides, Chemical accuracy for the van der Waals&#xA;density functional, J. Phys. Condens. Matter 22 (2010) 022201.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.081101&quot; rel=&quot;noreferrer&quot;&gt;K. Lee, Eamonn D. Murray, L. Kong, B.I. Lundqvist, D.C. Langreth, Higher-accuracy van der Waals density functional, Phys. Rev. B 82 (2010) 081101.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/24/7/073201&quot; rel=&quot;noreferrer&quot;&gt;J.F. Dobson, T. Gould, Calculation of dispersion energies, J. Phys. Condens.&#xA;Matter 24 (2012) 073201.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/24/42/424211&quot; rel=&quot;noreferrer&quot;&gt;D.-L. Chen, W.A. Al-Saidi, J.K. Johnson, The role of van der Waals interactions&#xA;in the adsorption of noble gases on metal surfaces, J. Phys. Condens. Matter 24&#xA;(2012) 424211.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-05T12:38:51.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="406" PostTypeId="2" ParentId="378" CreationDate="2020-05-05T13:43:42.273" Score="15" Body="&lt;p&gt;The justification is simple and comes from a very fundamental law of thermodynamics: Internal energy is a complete differential form and is independent of intermediate states and only depends on start and final states: &lt;span class=&quot;math-container&quot;&gt;$$\Delta U = U_{2} - U_{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In your case: &lt;span class=&quot;math-container&quot;&gt;$U_{2} = E_{AB}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$U_{1} = E_{A} + E_{B}$&lt;/span&gt; and if &lt;span class=&quot;math-container&quot;&gt;$\Delta U$&lt;/span&gt; or binding energy &lt;span class=&quot;math-container&quot;&gt;$E_{\text{binding}}$&lt;/span&gt; is positive, it means the start state is thermodynamically preferred but if &lt;span class=&quot;math-container&quot;&gt;$\Delta U$&lt;/span&gt; is negative, it means the binding state is thermodynamically preferred. You can generalize it to more complex systems with more than two reacting systems or components.&lt;/p&gt;&#xA;" OwnerUserId="37" LastActivityDate="2020-05-05T13:43:42.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="407" PostTypeId="1" AcceptedAnswerId="409" CreationDate="2020-05-05T13:45:02.890" Score="19" ViewCount="2023" Body="&lt;p&gt;I tried to recover a .CIF file (Crystallographic Information File) with the crystal structure for the compound discussed in a paper by Reuter &lt;em&gt;et. al.&lt;/em&gt;&lt;sup&gt;[1]&lt;/sup&gt;, strontium hydroxide octahydrate - &lt;span class=&quot;math-container&quot;&gt;$\ce{Sr(OH)2·8H2O}$&lt;/span&gt; - from Cambridge Crystallographic Data Centre (CCDC), but couldn't find it. The paper itself has tables with information recovered from x-ray diffraction data, as shown below.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/n6K6a.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/n6K6a.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JjL5W.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JjL5W.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there any free software or open source tool where I can just type the data from these tables to assemble a crystal structure like the ones I'm used to download from the database? How can I do it?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I posted &lt;a href=&quot;https://chemistry.stackexchange.com/q/132937/89908&quot;&gt;this question&lt;/a&gt; in chemistry.stackexchange at first, before materials.stackexchange entered beta. As it went unanswered, I'm giving it a try here.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Reuter, H.; Kamaha, S.; Zerzouf, O. Hydrogen Bonds in the Crystal Structure of Strontium Hydroxide Octahydrate Sr(OH)2 · 8H2O. &lt;em&gt;Zeitschrift für Naturforschung B&lt;/em&gt; &lt;strong&gt;2007,&lt;/strong&gt; &lt;em&gt;62&lt;/em&gt; (2), 215–219. &lt;a href=&quot;https://doi.org/10.1515/znb-2007-0212&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1515/znb-2007-0212&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="243" LastEditorUserId="88" LastEditDate="2020-07-30T20:40:02.003" LastActivityDate="2020-07-30T20:40:02.003" Title="How can I create a .CIF file from x-ray diffraction data in a paper, for compound not found in crystallographic database" Tags="|crystal-structure|open-source|space-groups|cif|vesta|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="408" PostTypeId="1" CreationDate="2020-05-05T13:52:18.837" Score="10" ViewCount="100" Body="&lt;p&gt;Since materials modelling is made possible primarily because of the availability of mathematical models, are there any resources that provide a mathematics heavy picture of materials behaviour?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am interesting in finding out if there are any courses or textbooks that have incorporated mathematics and simple computational modelling as a part of introducing concepts from areas like physical metallurgy, materials thermodynamics, environmental degradation of materials, solid state physics etc. at the undergraduate level.&lt;/p&gt;&#xA;" OwnerUserId="22" LastActivityDate="2020-05-15T14:28:45.783" Title="What mathematics/computation heavy resources are available for understanding materials behaviour?" Tags="|mathematical-modeling|education|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="409" PostTypeId="2" ParentId="407" CreationDate="2020-05-05T14:13:42.167" Score="17" Body="&lt;p&gt;You can use the free software &lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt; for creating a new structure by following steps&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;From the file menu choose New structure&lt;/li&gt;&#xA;&lt;li&gt;Go to Unit cell panel and choose the space group of the structure&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bdVJS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bdVJS.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Enter the lattice parameters in the same panel&lt;/li&gt;&#xA;&lt;li&gt;Change to Structure parameters panel and enter x,y,z and U&lt;sub&gt;eq&lt;/sub&gt; of each atom one by one&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SjkWN.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SjkWN.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;Save the structure and after verifying that the wyckoff positions displayed by the software matches with that of the publication, you can export it to cif.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-05T15:10:15.350" LastActivityDate="2020-05-05T15:10:15.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="410" PostTypeId="2" ParentId="404" CreationDate="2020-05-05T14:38:34.077" Score="18" Body="&lt;p&gt;Quantum computers provide the possibility of simulating systems that are so mathematically complex that classical computers cannot practically be used. The difficulty comes from the fact that the electrical properties of materials, and other chemical systems, are governed by the laws of many body quantum mechanics, which contain equations that are extremely hard to solve with classical computers. The calculations are essentially intractable, taking the age of the universe, or longer, to solve. A quantum computer doesn’t have this problem - by definition the qubits already know how to follow the laws of quantum physics - see the classic paper, &lt;a href=&quot;https://www.academia.edu/25883393/Richard_Feynman_Simulating_Physics_with_Computers&quot; rel=&quot;noreferrer&quot;&gt;Feynman, R., &lt;em&gt;Simulating Physics with Computers&lt;/em&gt;, 1982, Int J. Phys.&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In current quantum computers, aka noisy intermediate-scale quantum (NISQ) devices, the noise can actually be a feature when it comes to modeling chemical systems - see &lt;a href=&quot;https://www.wired.com/story/opinion-noisy-quantum-computers-chemistry-problems/&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Noisy Quantum Computers Could Be Good for Chemistry Problems&lt;/em&gt;, Wired, April 2019&lt;/a&gt;. Some further research in this direction is given in the following papers.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41534-020-0259-3&quot; rel=&quot;noreferrer&quot;&gt;Nam, Y. et al, &lt;em&gt;Ground-state energy estimation of the water molecule on a trapped-ion quantum computer&lt;/em&gt;, Nature, npj Quantum Information, April 3, 2020, 6, 33&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.pnas.org/content/114/29/7555&quot; rel=&quot;noreferrer&quot;&gt;Reiher M. et al, &lt;em&gt;Elucidating reaction mechanisms on quantum computers&lt;/em&gt;, PNAS, July 18, 2017, 114(29) 7555-7560&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1809.00058&quot; rel=&quot;noreferrer&quot;&gt;Rivera, N. et al, &lt;em&gt;Ab initio calculation of phonon polaritons in silicon carbide and boron nitride&lt;/em&gt;, Aug 31, 2018&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From a practical standpoint, we are still in the very early stages of developing quantum computers, however, and further research is needed to solve significant challenges, including creating systems with many more qubits, improving qubit performance, and developing software languages and frameworks for quantum computers. For more information see the NSF report &lt;a href=&quot;https://arxiv.org/pdf/1706.05413.pdf&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Quantum Information and Computation for Chemistry&lt;/em&gt;, NSF Workshop Report, June 20, 2017&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A &lt;a href=&quot;https://www.mckinsey.com/industries/chemicals/our-insights/the-next-big-thing-quantum-computings-potential-impact-on-chemicals?cid=soc-web&quot; rel=&quot;noreferrer&quot;&gt;recent report by McKinsey&lt;/a&gt; gives a higher level market overview of the field.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-05T17:05:27.077" LastActivityDate="2020-05-05T17:05:27.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="411" PostTypeId="1" AcceptedAnswerId="1507" CreationDate="2020-05-05T15:39:09.553" Score="17" ViewCount="802" Body="&lt;p&gt;Said software is useful when you need to assign the peaks in vibrational spectra to different vibrational modes found in a hessian calculation for a given molecule, as described in &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1386142513005891&quot; rel=&quot;noreferrer&quot;&gt;Jamróz, Michał H. “Vibrational Energy Distribution Analysis (VEDA): Scopes and Limitations”. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, vol. 114, outubro de 2013, p. 220–30. ScienceDirect, doi:10.1016/j.saa.2013.05.096.&lt;/a&gt; It's becoming popular, the paper has nearly 450 citations as of april 2020, but it has some downsides for me:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Despite being a freeware that can be downloaded from &lt;a href=&quot;https://smmg.pl/software/veda&quot; rel=&quot;noreferrer&quot;&gt;their site&lt;/a&gt; by anyone, it's not &lt;a href=&quot;https://en.wikipedia.org/wiki/The_Free_Software_Definition&quot; rel=&quot;noreferrer&quot;&gt;free software&lt;/a&gt;, or at least open source, and it's windows-only;&lt;/li&gt;&#xA;&lt;li&gt;Doesn't support people using free tools like &lt;a href=&quot;https://en.wikipedia.org/wiki/GAMESS_(US)&quot; rel=&quot;noreferrer&quot;&gt;Gamess-US&lt;/a&gt; or &lt;a href=&quot;https://en.wikipedia.org/wiki/PSI_(computational_chemistry)&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt;, only accepting Gaussian output files as its input, a paid and very expensive quantum chemistry software;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;So I did some research for alternatives that could avoid these downsides. Among the citations to the VEDA paper, I've found what seems to be a alternative approach to solve the same problem, as described in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.8b00439&quot; rel=&quot;noreferrer&quot;&gt;Teixeira, Filipe, e M. Natália D. S. Cordeiro. “Improving Vibrational Mode Interpretation Using Bayesian Regression”. Journal of Chemical Theory and Computation, vol. 15, no 1, janeiro de 2019, p. 456–70. ACS Publications, doi:10.1021/acs.jctc.8b00439.&lt;/a&gt; Their software, called vibAnalysis, is open source, and available from a &lt;a href=&quot;https://github.com/teixeirafilipe/vibAnalysis&quot; rel=&quot;noreferrer&quot;&gt;GitHub repository&lt;/a&gt;. It doesn't support Gamess-US or Psi4, but at least supports &lt;a href=&quot;https://en.wikipedia.org/wiki/ORCA_(quantum_chemistry_program)&quot; rel=&quot;noreferrer&quot;&gt;ORCA&lt;/a&gt;, which is free for academics, besides Gaussian.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I wonder if there are other alternatives I have missed in my research, specially if they run on linux and work with Gamess-US or Psi4. If somebody here could provide some guidance, I'd be grateful. I posted &lt;a href=&quot;https://chemistry.stackexchange.com/q/132170/89908&quot;&gt;this question&lt;/a&gt; in chemistry.stackexchange at first, before materials.stackexchange entered beta. As it went unanswered, I'm giving it a try here.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="7" LastEditDate="2020-07-10T18:50:52.130" LastActivityDate="2021-01-12T15:03:19.630" Title="Alternatives to VEDA 4 vibrational energy distribution analysis software?" Tags="|software|vibrations|from-chem-se|psi4|gamess|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="412" PostTypeId="2" ParentId="365" CreationDate="2020-05-05T15:47:52.263" Score="24" Body="&lt;h1&gt;Julia&lt;/h1&gt;&#xA;&lt;p&gt;Okay, I have to add Julia.&lt;/p&gt;&#xA;&lt;p&gt;Everyone is saying Fortran or Python, and I love them both, but they both have issues. Fortran is easy for a compiled language to write, but I still have &lt;code&gt;SIGSEGV&lt;/code&gt; burned into my retinas. Python is fast to write, but very slow. Learning how to cleverly make python fast (and it is still not all that fast) takes more time and skill than learning Fortran.&lt;/p&gt;&#xA;&lt;p&gt;I will say, for Quantum Mechanical calculation, there are many Numpy libraries that essentially do the hard parts in C/C++/Fortran, so I will not complain about using python for Quantum Mechanics. However, if you think you as a beginner are going to write fast Python code... forget about it. You need to learn Python, as well as all of the specializations in Numpy and Scipy.&lt;/p&gt;&#xA;&lt;p&gt;However, for atomistic simulation (molecular mechanics), there is only brute force for loops. Vectorization only gets you so much, and Python drives me crazy here.&lt;/p&gt;&#xA;&lt;p&gt;Julia however is as easy to write as Python, as pleasant to write as Python, and, so long as you follow some simple rules, such as making sure you do not change a variables type accidently, as fast as Fortran. There are built in standard tools for helping with this such as &lt;code&gt;@code_warntype&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The only downside to Julia is that the bandwagon picked Python. However, that is changing. Julia is on the rise.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If you want to write a prototype, which then turns out to be just as fast as a compiled language (because it is) choose Julia.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2020-11-24T20:38:07.397" LastActivityDate="2020-11-24T20:38:07.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="413" PostTypeId="2" ParentId="407" CreationDate="2020-05-05T16:05:34.193" Score="8" Body="&lt;p&gt;The journal requires that the data is deposited in CCDC, ICSD or CRYSTMET.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This one was apparently deposited in ICDC with the depository number CSD-417100 (the number is given in the paper, I don't have access to the database).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you also don't have access to ICDC write an e-mail to the author asking for the CIF file. Most academics are happy to answer such requests.&lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="5" LastEditDate="2020-05-05T16:13:52.620" LastActivityDate="2020-05-05T16:13:52.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="414" PostTypeId="1" CreationDate="2020-05-05T17:31:51.697" Score="34" ViewCount="1465" Body="&lt;p&gt;Among free software packages, which one has robust CASSCF functionality? The FCI solver can be implemented in either way, e.g., direct solver, DMRG, etc.&lt;/p&gt;&#xA;" OwnerUserId="11" LastEditorUserId="5" LastEditDate="2021-03-12T20:28:30.200" LastActivityDate="2021-05-31T18:05:45.010" Title="Is there a free package with robust CASSCF functionality?" Tags="|software|one-topic-per-answer|software-recommendations|casscf|open-molcas|" AnswerCount="9" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="415" PostTypeId="2" ParentId="119" CreationDate="2020-05-05T17:49:56.937" Score="15" Body="&lt;p&gt;There is linear scaling DFT, where you use density matrix as your object throughout SCF iterations instead of the wavefunctions. The linear scaling comes from the sparsity assumption/truncation on the density matrix. Usually, the wavefunctions are dense vectors, and any eigensolver results in cubic scaling with respect to the number of electrons/bases. However, if the density matrix is truncated to a sparse matrix with linear scaling sparsity (w.r.t. number of electrons), then the linear eigensolver in SCF iteration can be implemented through a density filtering method. The main operation in the density filtering method is multiplying the Hamiltonian operator to the density matrix, which scales linearly. Therefore, in the end, the overall cost for the DFT scales linearly.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Regarding the sparsity of density matrix, it can be related to Wannier function, which is localized molecular orbital of crystalline system. The Wannier function is much sparser than the wavefunction (theoretical understanding is available for gaped systems). In DFT calculation,  Wannier function can be constructed through rotating (transforming) your wavefunctions. Since Wannier function decays exponentially, it can be well approximated by a truncated function with constant size support. On the other hand, the density matrix (the product of wavefucntions) equals to the product of Wannier functions (two rotation matrices in the middle cancel with each other). Hence the density matrix is sparse and the sparsity scales linearly with respect to the number of electrons.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am not familiar with OFDFT. Since OFDFT also uses the density matrix as the object, I guess the linear scaling argument is due to the similar reason above.&lt;/p&gt;&#xA;" OwnerUserId="11" LastEditorUserId="11" LastEditDate="2020-05-06T20:28:50.700" LastActivityDate="2020-05-06T20:28:50.700" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="416" PostTypeId="1" CreationDate="2020-05-05T18:16:45.387" Score="19" ViewCount="380" Body="&lt;p&gt;Motivated by the ongoing COVID-19 pandemic, I am wondering how established density functional theory (DFT) is as a tool/technique in drug design.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Drug molecules come in a wide range of sizes from small molecules (e.g. aspirin) to proteins (biologics) that have complicated intramolecular and intermolecular interactions in a physiological environment, which is often highly concentrated. Is DFT a commonly used tool/technique in drug design? Or is DFT too expensive and inaccurate for us to perform first-principles prediction of drug properties?&lt;/p&gt;&#xA;" OwnerUserId="189" LastActivityDate="2020-05-07T15:27:46.617" Title="How established is density functional theory as a tool in drug design?" Tags="|density-functional-theory|drug-design|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="417" PostTypeId="2" ParentId="414" CreationDate="2020-05-05T21:11:08.423" Score="18" Body="&lt;h2&gt;PySCF&lt;/h2&gt;&#xA;&lt;p&gt;Personally I would use &lt;a href=&quot;https://sunqm.github.io/pyscf/&quot; rel=&quot;noreferrer&quot;&gt;pyscf&lt;/a&gt;, its not the most efficient or user friendly but it's free.&lt;/p&gt;&#xA;" OwnerUserId="256" LastEditorUserId="5" LastEditDate="2020-09-08T16:35:14.157" LastActivityDate="2020-09-08T16:35:14.157" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="418" PostTypeId="2" ParentId="398" CreationDate="2020-05-05T21:25:25.590" Score="8" Body="&lt;p&gt;I did some work during my rotation in the Brooks group  on surfaces that could act as abiogenesis sources (self-sustaining chemical reactions that become living organisms). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Key considerations for Heterogeneous catalysis are:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The timescales of your reaction, in our case it was a 24hr high pressure/temperature reaction so we required a driving force to have an initiation event. This isn't uncommon, but generally you want a surface that reacts faster than that.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Crystal cuts, also called Miller Indices, generally have to be investigated thoroughly. Essentially the angle of a cut through a unit cell is entirely up to chance, so a 001 crystal surface may react differently than a 010 or 110 etc. As a result you have to do some research of the common fracture angles for your surface and generate them as unique catalyst surfaces.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Solvation almost always has to be explicit to get a realistic reaction behavior. But oftentimes you'll add some type of force or implicit solvent on top to contain the top of your surface. This is especially important with the periodic boundary conditions that are typically used, so that your molecules don't interact with the bottom of the crystal which is normally buried.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Additionally how deep you layer your surface can matter. Many crystals at the atomic level can &quot;breathe&quot; up to 3 or 4 layers deep (some iron minerals can react even farther) so you'll want to have at least enough layers for the full reaction space, and some below. However, you can freeze portions of your surface to avoid additional calculation expenses.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;For software we used VASP and TBDFT with periodic boundary conditions with explicit waters. So those are the most familiar to me and the ones I would recommend&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For input files I found Avogadro has the most user friendly for generating input files for VASP and TBDFT, however VESTA is another freely available package for opening CIF files and generating computation inputs.&lt;/p&gt;&#xA;" OwnerUserId="256" LastEditorUserId="118" LastEditDate="2020-05-09T23:43:46.783" LastActivityDate="2020-05-09T23:43:46.783" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="419" PostTypeId="2" ParentId="347" CreationDate="2020-05-05T22:04:36.580" Score="38" Body="&lt;p&gt;Below is a summary of what I have found:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;hr&gt;&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;What is meant by &quot;Exact exchange&quot;&lt;span class=&quot;math-container&quot;&gt;$\,$&lt;/span&gt;?&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;The question mentions the following (in order of how they were presented in the question):&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact exchange-correlation potential&lt;/strong&gt; (used in &lt;a href=&quot;https://www.nature.com/articles/s41467-019-12467-0&quot; rel=&quot;noreferrer&quot;&gt;this 2019 paper in Nature Communications&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact Hartree-Fock exchange energy functional&lt;/strong&gt; (&lt;a href=&quot;https://www.google.ca/search?q=&amp;quot;exact+Hartree-Fock+exchange+energy+functional&amp;quot;&quot; rel=&quot;noreferrer&quot;&gt;only 4 results&lt;/a&gt;, 3 from the same authors).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact exchange-energy functional&lt;/strong&gt; (wording that's been used &lt;a href=&quot;https://en.wikipedia.org/wiki/Hybrid_functional&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for  hybrid functionals).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact exchange-correlation energy functional&lt;/strong&gt; (&lt;em&gt;finding it is often thought to be impossible&lt;/em&gt;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;However, I was indeed able to find the equations you gave, in &lt;a href=&quot;http://www1.mpi-halle.mpg.de/~sharma/talks/vienna.pdf&quot; rel=&quot;noreferrer&quot;&gt;these lecture slides&lt;/a&gt;!&lt;/em&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;This leads to more terms:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact Exchange in Density Functional Theory&lt;/strong&gt; (is the title of the talk).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact Exchange Density Functional theory&lt;/strong&gt; (in title of the paper you linked, by same author).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Exact exchange (EXX) method&lt;/strong&gt; (this is what the paper you mentined, by, uses).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Your quote &quot;this exact exchange-energy functional is able to calculate...&quot; refers to the &lt;strong&gt;EXX method&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;h1&gt;What was meant by &quot;EXX method&quot; in the linked paper?&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;Unfortunately I have come to learn that the authors of the paper you mentioned, did not cite the original EXX papers when they mentioned EXX: &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;In this work we deploy the EXact eXchange (EXX) method, implemented within an all-electron full-potential code EXITING [8]&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;or anywhere in the paper, or the aforementioned talk. Instead the paper cited a code called &quot;EXITING&quot; which is actually a mis-spelling of their &lt;a href=&quot;http://www.exciting.physics.at/tasks/t2.shtml#m13&quot; rel=&quot;noreferrer&quot;&gt;unavailable code&lt;/a&gt; called EXCITING. The aforementioned lecture slides end with a page saying that the &quot;code is available&quot; over &lt;a href=&quot;https://physik.kfunigraz.ac.at/%E2%88%BCkde/secret%20garden/exciting.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, but that link leads to a 404 error. They mentioned that they had recently developed the EXX equations for their magnets, with a reference to &lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0510800v1.pdf&quot; rel=&quot;noreferrer&quot;&gt;this pre-print&lt;/a&gt; which after adding 1 new author and moving Hardy Gross from 3rd last author to last author, &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0510800&quot; rel=&quot;noreferrer&quot;&gt;got published 2 years later in PRL&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since the paper you mentioned was never cited, and didn't land in any journal, but refers to a paper which landed in PRL two years later, involving all-but-one of the same authors, I was curious to see how far apart these papers were written. This lead me to find out that the paper you linked was v3 of a paper whose v1 (which had &lt;em&gt;even fewer&lt;/em&gt; authors) was actually put on arXiv 10 months before v1 of the other one. That paper actually did cite some earlier EXX papers (indicating that the authors were aware of them when they posted later versions without citation).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Summary of this section:&lt;/em&gt;&lt;/strong&gt; The authors of the linked paper posted v1 of a 4-page PRL-style paper on arXiv in January 2005 with 4 authors, added 2 authors for v2 in June, removed 1 author and added 3 more (including a very famous one) for v1 of a different 4-page PRL-style paper in October (which was eventually published in PRL in March 2007 after adding 1 more author and moving the most famous one to the end position), while a v3 of the first paper was posted 1 month later never landed in a journal and never got cited. The EXCITING code is also not available at exciting.physics.at, nor at the link mentioned in the talk.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;hr&gt;&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;So where did the term &quot;EXX method&quot; originate?&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;At first I thought the EXX method was invented by the authors of the linked paper (hours before I tracked down v1 which did cite some earlier papers), but something smelled fishy so I looked in other places.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;http://cmt.dur.ac.uk/sjc/thesis_mcg/node67.html&quot; rel=&quot;noreferrer&quot;&gt;2006 PhD thesis of Michael Gibson&lt;/a&gt; of the reputable Durham University says in the &lt;strong&gt;&lt;em&gt;abstract:&lt;/em&gt;&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;We then describe our computational implementation of advanced density&#xA;  functionals, including screened exchange (sX-LDA), Hartree-Fock (HF),&#xA;  and exact exchange (EXX), within an efficient, fully parallel, plane&#xA;  wave code.&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Since this person's PhD thesis was on this, let's proceed. He calls it the &quot;&lt;strong&gt;exact exchange (EXX) functional&lt;/strong&gt;&quot; and cites 3 papers: one was published in 1996, another in 1997 with the same author plus 2 more, and the last in 1999 with the same authors plus 1 more.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;strong&gt;1996&lt;/strong&gt; paper does not use the term EXX, but mentions a &quot;recently introduced exact formal KS procedure&quot; in the abstract, with a reference to a paper from 2 years earlier, involving the same author.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;1997&lt;/strong&gt; paper (published in PRL) begins the abstract with &quot;A new Kohn-Sham method that treats exchange interactions within density functional theory&#xA;exactly&quot; followed later by &quot;In this Letter, we present an &lt;em&gt;exact&lt;/em&gt; determination of the KS exchange potential&quot; (Italic font on the word &quot;exact&quot; was theirs). The third paragraph ends with &quot;The&#xA;present exact exchange formalism, that we abbreviate by EXX, eliminates these divergencies exactly.&quot; &lt;strong&gt;So this must be where EXX comes from right?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;For some reason I also looked at the &lt;strong&gt;1999&lt;/strong&gt; paper, which says &quot;We have developed a scheme—termed the exact exchange (EXX) method [31]&quot; which points not to the 1997 paper where they claim to have come up with the term EXX, but to a &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.50.14816&quot; rel=&quot;noreferrer&quot;&gt;1994 paper&lt;/a&gt; by a Japanese author entirely independent of any of the Germany-based authors of this 1994-1999 series.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;1994&lt;/strong&gt; paper indeed uses the term EXX, but they openly admit that it's an old concept and it's been called that in the past: &quot;In this paper, we present a method of DF band calculation using the so-called exact exchange (EXX) potential&#xA;[the exact Kohn-Sham (KS) density-functional exchange potential] (Ref. 5)&quot; where Ref 5 is a &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.28.1809&quot; rel=&quot;noreferrer&quot;&gt;1983 paper currently with 1330 citations&lt;/a&gt;. Elsewhere they also mention that a &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.14.36&quot; rel=&quot;noreferrer&quot;&gt;1976 paper currently with 1328 citations&lt;/a&gt; used &quot;the EXX-only method&quot;.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;1983&lt;/strong&gt; paper uses the word &quot;exact&quot; 103 times, but never the acronym EXX.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;1976&lt;/strong&gt; paper doesn't make any reference to EXX or even DFT in general, but a &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0092640X78900190&quot; rel=&quot;noreferrer&quot;&gt;1978 paper&lt;/a&gt; involving one of the authors, does put the 1976 paper into the context of the Thomas-Fermi model and the language of energy functionals. &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Summary of this section:&lt;/em&gt;&lt;/strong&gt; I only started doing research on this about 5 hours ago, and only to try to answer this question, but the earliest use of the acronym EXX I could find was in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.50.14816&quot; rel=&quot;noreferrer&quot;&gt;this 1994 paper&lt;/a&gt; by Kotani which credits &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0092640X78900190&quot; rel=&quot;noreferrer&quot;&gt;this 1978 paper&lt;/a&gt; as using what the 1994 author calls &quot;the EXX-only method&quot; and &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.28.1809&quot; rel=&quot;noreferrer&quot;&gt;this 1983 paper&lt;/a&gt; when mentioning the EXX potential for the first time. &lt;strong&gt;The &quot;EXX method&quot; has some roots in the 1976 and 1983 papers but the phrase seems to have emerged some time between 1983 and 1994&lt;/strong&gt;. Görling and co-workers seem to have improved on the work of Kotani (though they don't phrase it that way) from 1994-1999, and they call this improvement &quot;the EXX method&quot;, and &lt;strong&gt;a version of this catered to specific magnetic problems is what was used in the 2005-2007 paper of Sharma &lt;em&gt;et al.&lt;/em&gt; linked in the question.&lt;/strong&gt; The Görling  &lt;em&gt;et al.&lt;/em&gt; and Sharma &lt;em&gt;et al.&lt;/em&gt; papers each gave me the impression that they invented the EXX method, but if dug deeply enough it's possible to find Kotani's paper buried in the bibliography (except in the present version of the linked Sharma paper, which doesn't cite any previous EXX paper).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;hr&gt;&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;Is there any software that offers &quot;EXX&quot; functionals?&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;GPAW has &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/xc/exx.html&quot; rel=&quot;noreferrer&quot;&gt;two implementations of EXX&lt;/a&gt; but your mileage may vary (their EXX might not mean the same as your EXX). They also did not provide a reference for the EXX functional that they implemented (but this does not surprise me as I have now spent almost 6 hours on this and 6 hours was perhaps not enough): &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Nt2yh.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Nt2yh.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;h1&gt;Conclusion&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;You asked if the EXX method is:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;worth to use in comparison to conventional XC potentials&quot;?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&quot;Exact&quot; seems to be a buzz word that was used 103 times in the aforementioned 1983 paper, when in fact nothing is &lt;em&gt;truly&lt;/em&gt; exact other than the &quot;grand unified theory&quot; (which doesn't yet exist and may never exist). At least two groups of authors seem to have misleadingly claimed to invent exact-exchange methods, one group in the 1990s and one group in the 2000s, but the paper you linked which claimed higher accuracy compared to FP-LDA never survived peer review, has never been cited, and was performed with software that is unavailable.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I therefore see no evidence yet that the EXX method you linked to is actually better than the conventional XC methods you mention. DFT is a highly approximate method anyway, and nothing is exact. DFT is notorious for sometimes giving good results for the wrong reasons, so one single paper showing a better accuracy than one other paper, does not convince me that any method is better in general. However I am not a DFT expert: I am just someone who accidentally tried to answer this question because I wanted to clear up the &quot;unanswered&quot; queue, and 6 hours ago I thought the answer would be easy!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-06T23:42:58.010" LastActivityDate="2020-05-06T23:42:58.010" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="420" PostTypeId="2" ParentId="414" CreationDate="2020-05-05T22:21:06.387" Score="29" Body="&lt;h2&gt;ORCA&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.orcasoftware.de/tutorials/index.html&quot; rel=&quot;noreferrer&quot;&gt;ORCA&lt;/a&gt; (&lt;a href=&quot;https://orcaforum.kofo.mpg.de/index.php&quot; rel=&quot;noreferrer&quot;&gt;forum&lt;/a&gt;). It is fully featured, efficient, and free for academics. The input is straightforward:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# CASSCF(2,4) example from the manual,&#xA;# section 8.1.7.2, page 108&#xA;&#xA;! TZVPP TightSCF&#xA;&#xA;%casscf&#xA;  nel 2&#xA;  norb 4&#xA;end&#xA;&#xA;* xyz 0 1&#xA;Be 0 0 0&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Some resources for CASSCF:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;General functionality is reported in &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/cas-calculations&quot; rel=&quot;noreferrer&quot;&gt;this tutorial&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;A tutorial dedicated exclusively to &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/cas-calculations/tutorial-active-space-selection&quot; rel=&quot;noreferrer&quot;&gt;dealing with the active space in ORCA&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;A &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/?view=detail&amp;amp;df_id=23&quot; rel=&quot;noreferrer&quot;&gt;90-page document&lt;/a&gt; from the developers entirely dedicated to CASSCF (free registration required). (This can be found in the &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/&quot; rel=&quot;noreferrer&quot;&gt;Downloads section&lt;/a&gt; of the &lt;a href=&quot;https://orcaforum.kofo.mpg.de/index.php&quot; rel=&quot;noreferrer&quot;&gt;ORCA Forum&lt;/a&gt; under &amp;quot;CASSCF Tutorial&amp;quot;.)&lt;/li&gt;&#xA;&lt;li&gt;The &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/?view=detail&amp;amp;df_id=80&quot; rel=&quot;noreferrer&quot;&gt;ORCA manual&lt;/a&gt; (free registration required). See section 8.1.7 (page 107) for CASSCF, NEVPT2, and DMRG. (This can be found in the &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/&quot; rel=&quot;noreferrer&quot;&gt;Downloads section&lt;/a&gt; of the &lt;a href=&quot;https://orcaforum.kofo.mpg.de/index.php&quot; rel=&quot;noreferrer&quot;&gt;ORCA Forum&lt;/a&gt; under &amp;quot;ORCA Manuals&amp;quot;.)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="63" LastEditorUserId="5" LastEditDate="2020-09-08T16:35:20.210" LastActivityDate="2020-09-08T16:35:20.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="421" PostTypeId="2" ParentId="414" CreationDate="2020-05-05T22:46:49.420" Score="40" Body="&lt;h2&gt;OpenMOLCAS&lt;/h2&gt;&#xA;&lt;p&gt;I'm surprised that the other two answers were given without yet any mention of OpenMOLCAS yet! &lt;br&gt;&#xA;There is a recent paper&lt;sup&gt;[1]&lt;/sup&gt; about it for which I happen to be one of the many co-authors.&lt;/p&gt;&#xA;&lt;p&gt;MOLCAS has the quality of a commercial software like MOLPRO, since it was a commercial software that people paid big money for since the 1980s, but recently an open source branch called OpenMOLCAS was made freely available.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, (Open)MOLCAS is the only program with CAS in its name, suggesting that it caters well to CASSCF calculations. Indeed, it originated in the 1980s in the group of Björn Roos, and Roos in fact &lt;a href=&quot;http://www.molcas.org/roos.html&quot; rel=&quot;noreferrer&quot;&gt;described the CASSCF method in the year 1980&lt;/a&gt;  and later in the same decade developed the CASPT2 method.&lt;/p&gt;&#xA;&lt;p&gt;CASSCF, RASSCF, and GASSCF are all implemented well in OpenMOLCAS, as it is used mainly by people who specialize in active-space calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.jctc.9b00532&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;15&lt;/em&gt; (11), 5925–5964&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-08T16:35:25.813" LastActivityDate="2020-09-08T16:35:25.813" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="422" PostTypeId="1" AcceptedAnswerId="424" CreationDate="2020-05-06T01:40:03.213" Score="16" ViewCount="537" Body="&lt;p&gt;I would appreciate if someone could recommend me good review literature on the density matrix renormalization group (DMRG) method, especially for magnetic systems.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-06T02:17:48.890" LastActivityDate="2020-06-30T16:36:18.193" Title="Is there any good review paper on the density matrix renormalization group (DMRG) method?" Tags="|reference-request|magnetism|dmrg|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="423" PostTypeId="1" CreationDate="2020-05-06T02:06:35.480" Score="-8" ViewCount="350" Body="&lt;p&gt;A biomaterials question this time. How are quantum computers being used in drug discovery and design? &lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="88" LastEditDate="2020-05-07T03:02:06.467" LastActivityDate="2020-05-07T03:02:06.467" Title="How are quantum computers being used in drug design?" Tags="|quantum-computing|drug-design|biomaterials|" AnswerCount="2" CommentCount="3" ClosedDate="2020-05-06T16:30:25.260" ContentLicense="CC BY-SA 4.0" />
  <row Id="424" PostTypeId="2" ParentId="422" CreationDate="2020-05-06T02:16:26.357" Score="24" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0303557&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2003&lt;/strong&gt;: Book chapter &lt;/a&gt; by Karen Hallberg.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0409292&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2004&lt;/strong&gt;: Reviews of Modern Physics&lt;/a&gt; by Ulrich Schollwoeck (2818 current citations).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tandfonline.com/doi/abs/10.1080/00018730600766432&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2006&lt;/strong&gt;: Advances in Physics&lt;/a&gt; by Karen Hallberg.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0603842&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2008&lt;/strong&gt;: JCTN:&lt;/a&gt; by Gabriele De Chiara and co-workers.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.annualreviews.org/doi/abs/10.1146/annurev-physchem-032210-103338&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2011&lt;/strong&gt;: ARPC:&lt;/a&gt; by Garnet Chan and Sandeep Sharma (426 current citations).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1407.2040&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2014&lt;/strong&gt;: The European Physical Journal D&lt;/a&gt; by Sebastian Wouters and Dimitri Van Neck.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.24808&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2014&lt;/strong&gt;: IJQC&lt;/a&gt; by Takeshi Yanai and co-workers.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4905329&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;2015&lt;/strong&gt;: JCP&lt;/a&gt; by Roberto Olivares-Amaya and co-workers.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;There is also &lt;a href=&quot;http://quattro.phys.sci.kobe-u.ac.jp/dmrg.html&quot; rel=&quot;noreferrer&quot;&gt;this website&lt;/a&gt; which attempts (seemingly very successfully!) to track every DMRG, MPS, TPS, MERA, and/or general Tensor Network paper &lt;em&gt;ever&lt;/em&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-29T19:57:04.060" LastActivityDate="2020-06-29T19:57:04.060" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="425" PostTypeId="2" ParentId="423" CreationDate="2020-05-06T02:20:05.727" Score="15" Body="&lt;blockquote&gt;&#xA;  &lt;p&gt;How are quantum computers being used in drug design?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;They are not. &lt;br&gt;&#xA;Because useful quantum computers do not exist yet.&lt;br&gt;&#xA;Ask again in a couple decades :)&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-05-06T02:20:05.727" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="426" PostTypeId="1" CreationDate="2020-05-06T02:56:32.090" Score="13" ViewCount="132" Body="&lt;p&gt;If I construct a crystal structure using lattice parameters and atomic coordinates as mentioned in a &lt;a href=&quot;https://materials.stackexchange.com/questions/407/how-can-i-create-a-cif-file-from-x-ray-diffraction-data-in-a-paper-for-compoun&quot;&gt;previous post&lt;/a&gt;, what difference does it make if I  omit (or enter wrong parameters) for the displacement parameters U or B?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How relevant are these displacement parameters while modelling the material? &lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-05-09T20:46:24.457" LastActivityDate="2020-06-12T13:25:42.627" Title="How relevant are the displacement parameters in a crystal structure for materials modelling?" Tags="|crystal-structure|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="427" PostTypeId="2" ParentId="423" CreationDate="2020-05-06T05:36:37.507" Score="-6" Body="&lt;p&gt;I actually found this reference, which is pretty helpful.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Quantum computing has rapidly advanced in recent years due to substantial development in both hardware and algorithms. These advances are carrying quantum computers closer to their impending commercial utility. Drug discovery is a promising area of application that will find a number of uses for these new machines. As a prominent example, quantum simulation will enable faster and more accurate characterizations of molecular systems than existing quantum chemistry methods. Furthermore, algorithmic developments in quantum machine learning offer interesting alternatives to classical machine learning techniques, which may also be useful for the biochemical efforts involved in early phases of drug discovery. Meanwhile, quantum hardware is scaling up rapidly into a regime where an exact simulation is difficult even using the world’s largest supercomputers. We review how these recent advances can shift the paradigm with which one thinks about drug discovery, focusing on both the promises and caveats associated with each development. In particular, we highlight how hybrid quantum-classical approaches to quantum simulation and quantum machine learning could yield substantial progress using noisy-intermediate scale quantum devices, whereas fault-tolerant, error-corrected quantum computers are still in their development phase.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://ieeexplore.ieee.org/document/8585034&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;&lt;em&gt;Potential of quantum computing for drug discovery&lt;/em&gt;&lt;/strong&gt;, IBM Journal of Research and Development, 62(6), Nov 2018.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="36" LastActivityDate="2020-05-06T05:36:37.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="428" PostTypeId="1" AcceptedAnswerId="1834" CreationDate="2020-05-06T08:00:50.310" Score="17" ViewCount="271" Body="&lt;p&gt;In a DFT standard calculation of a solid 3D material (i.e. bulk metal), one of the properties that can be obtained is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fermi_level&quot; rel=&quot;noreferrer&quot;&gt;Fermi level &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt;.&lt;/a&gt; This feature is related with the required work to add an electron to this material. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In organic electronics, one possible utility of that value is to extract information about the charge-transfer properties of such material when it is contacted by a single molecule or even a molecular layer (organic semiconductor), thus obtaining the &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.201606901&quot; rel=&quot;noreferrer&quot;&gt;interfacial properties of the complete junction.&lt;/a&gt; As the orbitals of both entities tend to hybridize, the properties of the modified surface can be radically different from those of the initial isolated materials. This is particularly critical when either or both of the materials are magnetic, in which case it is called &lt;a href=&quot;https://www.nature.com/articles/nphys1714&quot; rel=&quot;noreferrer&quot;&gt;Spinterface.&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xnxV1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xnxV1.png&quot; alt=&quot;Spin-dependent hybridization in a spinterface&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In this context, some question arises. Which is the most adequate way of calculating a molecular surface on top of a metal? How to account on rearrangement of atomic positions, image-charge properties and orbital hybridization? and last but not least, How to model a descriptive molecular surface in which different molecules can be arranged in different positions?&lt;/p&gt;&#xA;" OwnerUserId="290" LastEditorUserId="5" LastEditDate="2020-07-04T13:59:06.967" LastActivityDate="2020-07-29T01:21:31.523" Title="Fermi level change in surfaces with adsorbed molecules" Tags="|molecular-modeling|surfaces|molecular-interactions|adsorption|metals|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="429" PostTypeId="2" ParentId="64" CreationDate="2020-05-06T08:59:05.447" Score="8" Body="&lt;p&gt;Not all determinants contribute significant correlation, especially configurations for excitations of multiple electrons to higher energy orbitals, which is the basis for CAS methods; i.e. only choose the “important” orbitals in which to perform FCI. Doing so works acceptably for weakly correlated systems, but since FCI is still performed within the active space, as more orbitals are required to maintain an accurate description of electronic structure, the exponential growth once again becomes a problem. The only way to circumvent this is by excluding insignificant determinants, often for higher-level excitations, upon expansion of the active space. To my understanding, this approach is present to some extent in HCI, QMC, DMRG, and other algorithms, but each experiences their own problems with strongly correlated systems.&lt;/p&gt;&#xA;&lt;p&gt;An emerging strategy that considers the entire orbital space with the means to systematically capture correlation without performing excessive excitations is the application of the Method of Increments to FCI (iFCI). This algorithm achieves polynomial scaling at low-order increments (up to n~4), where the FCI problem is broken up into portions to be solved individually. Of course, higher expansions are required for more strongly correlated systems, which again potentially encroaches on the problem of exponential scaling. However, utilizing the entire space to find the most strongly correlating orbital spaces without excessively including high-level excitations shows promise for approaching FCI-level accuracy without the intractable cost.&lt;/p&gt;&#xA;&lt;p&gt;Reference: &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.0c07624&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.0c07624&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="328" LastEditorUserId="786" LastEditDate="2021-08-13T13:29:37.817" LastActivityDate="2021-08-13T13:29:37.817" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="430" PostTypeId="2" ParentId="382" CreationDate="2020-05-06T09:10:36.080" Score="7" Body="&lt;p&gt;Alone Programmer's &lt;a href=&quot;https://materials.stackexchange.com/a/395/22&quot;&gt;answer&lt;/a&gt; already mentions ways to generate polycrystalline microstructure. To add to that, it is possible to generate models of bi-crystals to analyse particular grain boundaries directly using LAMMPS. &lt;a href=&quot;https://icme.hpc.msstate.edu/mediawiki/index.php/Grain_boundary_generation&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a detailed wiki on how to generate such models.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Apart from this, there was a Java based applet called &lt;a href=&quot;https://www.jstage.jst.go.jp/article/matertrans/47/11/47_11_2706/_article&quot; rel=&quot;noreferrer&quot;&gt;GBStudio&lt;/a&gt; that made generating grain boundary models very simple. Unfortunately, this tool seems to be no longer available.&lt;/p&gt;&#xA;" OwnerUserId="22" LastActivityDate="2020-05-06T09:10:36.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="431" PostTypeId="1" CreationDate="2020-05-06T12:56:44.837" Score="17" ViewCount="743" Body="&lt;p&gt;It looks to me to that many of the things one would do within the framework of density functional theory (DFT) ultimately boil down to solving a generalized eigenvalue problem &lt;span class=&quot;math-container&quot;&gt;$Av = \lambda Bv$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; are matrices, &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is the eigenvalue and &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; is the corresponding generalized eigenvector.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are the core numerical routines used in DFT, besides solving generalized eigenvalue problems? What about optimization routines?&lt;/p&gt;&#xA;" OwnerUserId="189" LastActivityDate="2020-05-18T09:04:29.963" Title="What are the core numerical routines used in density functional theory?" Tags="|density-functional-theory|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="432" PostTypeId="1" CreationDate="2020-05-06T12:58:16.873" Score="18" ViewCount="2049" Body="&lt;p&gt;Wikipedia says&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;A semimetal is a material with a very small overlap between the bottom of the conduction band and the top of the valence band. &lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;How small/unique the overlap should be so that we can classify a material as a semi-metal?&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-09-16T01:22:07.263" Title="How to identify a semi-metal from the band structure?" Tags="|electronic-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="433" PostTypeId="5" CreationDate="2020-05-06T16:40:19.140" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-06T16:40:19.140" LastActivityDate="2020-05-06T16:40:19.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="434" PostTypeId="4" CreationDate="2020-05-06T16:40:19.140" Score="0" Body="For questions related to the Cambridge Structural Database, a repository of &quot;small-molecule organic and metal-organic crystal structures&quot;." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-06T17:28:39.140" LastActivityDate="2020-05-06T17:28:39.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="435" PostTypeId="5" CreationDate="2020-05-06T16:44:08.863" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-06T16:44:08.863" LastActivityDate="2020-05-06T16:44:08.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="436" PostTypeId="4" CreationDate="2020-05-06T16:44:08.863" Score="0" Body="For questions about correcting basis set superposition errors (BSSE), which tend to occur when evaluating binding energies." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-06T17:28:52.967" LastActivityDate="2020-05-06T17:28:52.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="437" PostTypeId="1" AcceptedAnswerId="442" CreationDate="2020-05-06T18:59:31.983" Score="19" ViewCount="352" Body="&lt;p&gt;I want to make a pet project in cheminformatics and I need to hear from the community about the actual challenges in chemistry that might be resolved with a digital solution.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I've been working in this field a long time ago and want to get fresh opinions about the most current issues in chemistry.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I understand that the most obvious issues are already covered by some solutions, which is why I need your advice. Mostly interested in organic chemistry but will gladly review all the ideas.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It will be a solo project so it's nothing monumental but still, I would like to do something that will have real value for chemists.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I will appreciate any ideas.&lt;/p&gt;&#xA;" OwnerUserId="330" LastEditorUserId="7" LastEditDate="2020-05-06T19:20:08.553" LastActivityDate="2020-05-09T21:16:29.323" Title="What software is needed in chemoinformatics or materials modeling, that a solo programmer could work on?" Tags="|software|molecular-modeling|databases|computational-chemistry|" AnswerCount="3" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="438" PostTypeId="2" ParentId="431" CreationDate="2020-05-06T20:48:36.663" Score="15" Body="&lt;p&gt;DFT is a nonlinear eigenvalue problem. In the community of chemistry and material science, it is almost always solved via the self-consistent-field method (SCF).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If the DFT is solved on the level of GGA or LDA (referring to Jacob's Ladder), then, within each SCF iteration, the most expensive numerical routine is indeed (generalized) eigenvalue problem. In addition to the linear (generalized) eigenvalue problem, the density/orbital mixing also involves cubic scaling numerical routines. To my knowledge, they are still much cheaper than the eigensolver.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, if you further move upon Jacob's ladder to hybrid-functionals or above, then you will encounter numerical routines of much higher order scaling than the eigensolver. In practice, some approximation and numerical tricks can be used to reduce the computational cost of hybrid-functional to the same level as eigensolver. Hence the discussion is more complicated in this case.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Jumping out of the chemistry and material science community, some mathematicians have tried to solve the nonlinear eigenvalue problem directly from an optimization point of view and not uses SCF+mixing. These methods have only been applied to LDA-level functionals. Hence the core numerical routine varies from method to method.&lt;/p&gt;&#xA;" OwnerUserId="11" LastActivityDate="2020-05-06T20:48:36.663" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="439" PostTypeId="2" ParentId="437" CreationDate="2020-05-06T20:50:36.230" Score="14" Body="&lt;h2&gt;&lt;a href=&quot;https://github.com/openbabel/openbabel&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenBabel&lt;/a&gt;&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;And the related Pybel are excellent platforms for starting a project because they have well written C++ and python APIs, and are specifically designed for &lt;a href=&quot;http://openbabel.org/wiki/Cheminformatics_101&quot; rel=&quot;nofollow noreferrer&quot;&gt;cheminformatics 101&lt;/a&gt;. For example, cheminformatics involves&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Storing a Molecule in various formats (e.g. smiles, twirlymol, 2d, xyz, etc)&lt;/li&gt;&#xA;&lt;li&gt;Finding exact molecule &lt;/li&gt;&#xA;&lt;li&gt;Substructure search&lt;/li&gt;&#xA;&lt;li&gt;Similarity search&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;A typical workflow could involve creating a 3D molecule from a smiles string, performing a conformation search, and searching a database for matches/machine learning.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Perhaps Geoff Hutchinson, who is a user on this site, or the other developers on GitHub can provide more specific details about how you can contribute. &#xA;Also, the &lt;a href=&quot;https://baoilleach.blogspot.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Noel O'Blo&lt;/a&gt;g has a lot of information on smaller things you can do to help. For example, not all the work needs to be in the &quot;back end&quot;. Simpler scripts which could be written by a single user could be quite useful. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;AND GEOFF HAS ANSWERED! See that answer for a more complete description of ways to contribute the field of cheminformatics.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Finally, to add to the list of ways to contribute. I found this list of curated &lt;a href=&quot;https://github.com/hsiaoyi0504/awesome-cheminformatics&quot; rel=&quot;nofollow noreferrer&quot;&gt;cheminformatics software&lt;/a&gt; you can peruse.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-09T21:16:29.323" LastActivityDate="2020-05-09T21:16:29.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="440" PostTypeId="2" ParentId="437" CreationDate="2020-05-06T22:29:25.197" Score="9" Body="&lt;p&gt;When writing some simple Python script in &lt;a href=&quot;https://en.wikipedia.org/wiki/Spyder_(software)&quot; rel=&quot;noreferrer&quot;&gt;Spyder&lt;/a&gt; code editor, I always feel envious of computer science people every time its &lt;a href=&quot;https://en.wikipedia.org/wiki/Lint_(software)&quot; rel=&quot;noreferrer&quot;&gt;linting tool&lt;/a&gt; points some silly mistake I do, for example, forgetting a &quot;:&quot; in the end of a function definition, or using a &quot;=&quot; instead of &quot;==&quot; in a logic expression. I think myself, why can't we have such nice things in computational chemistry too. Why so much pain?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It's very unpleasant when you're starting your career as a aspiring computational chemist, and you find yourself losing a lot of time, in anger and frustration, just because your input file doesn't run, and you're left only with some cryptic error message to figure out the problem. Sometimes a silly mistake, a single missing blank line, or a typo somewhere can make you lose hours. If you search the web, you will find countless people asking for help with problems like these, see for example  &lt;a href=&quot;https://chemistry.stackexchange.com/q/73001/89908&quot;&gt;Gaussian Error: Zero Point Energy Calculation on Fluoroform fails&lt;/a&gt; or &lt;a href=&quot;https://chemistry.stackexchange.com/q/111258/89908&quot;&gt;Gaussian syntax error on the input line&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Every time you have to figure out how to use a new tool, is the same history, the same pain, and there are dozens to learn. Sometimes you find some kind soul to help you in questions like these, but sometimes you just receive some nasty answers that amount to &lt;a href=&quot;https://en.wikipedia.org/wiki/RTFM&quot; rel=&quot;noreferrer&quot;&gt;RTFM&lt;/a&gt;, probably because somebody heard the same question 1000 times before and got tired.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I think a simple text editor with &lt;a href=&quot;https://en.wikipedia.org/wiki/Syntax_highlighting&quot; rel=&quot;noreferrer&quot;&gt;syntax highlighting&lt;/a&gt; and something akin to linting for quantum chemistry input files would go a long way into alleviating this problem.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I wonder why have we no such tools already. It's like the if the wheel have not been invented yet. Perhaps the default in the field is stick to the &lt;a href=&quot;https://www.quora.com/What-is-Alan-Kay%E2%80%99s-opinion-of-Assembly-and-mainstream-programming-languages-like-Google-Go&quot; rel=&quot;noreferrer&quot;&gt;von Neumann approach&lt;/a&gt; and just withstand it until you became a paid professor, then you can lose your students time instead of yours. Why worry about &lt;a href=&quot;https://en.wikipedia.org/wiki/Human_factors_and_ergonomics&quot; rel=&quot;noreferrer&quot;&gt;ergonomics&lt;/a&gt;, with so much cheap labor? Just let them bang their heads in the keyboard until it works, while we enjoy reading our papers.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MkTfW.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MkTfW.gif&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2020-05-06T22:29:25.197" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="441" PostTypeId="1" CreationDate="2020-05-06T22:31:21.343" Score="19" ViewCount="514" Body="&lt;p&gt;I'm doing some post-processing using the vibrational modes of a molecule to solve a linear system of equations, but I believe I need all the modes in order to have a single, well-determined solution. I'm doing this with Gaussian and their &lt;a href=&quot;http://gaussian.com/vib/&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt; lays out how they form these modes, but I have yet to find an option to actually print them and since they are doing it already internally and I'm reading the other modes from output files, I'd rather not repeat the process if I don't have to.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to get Gaussian (or any electronic structure program) to print the coordinates of the translational/rotational modes to the log or some output file? Alternatively, can I easily generate translational/rotational modes given the vibrational modes?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-16T15:09:45.400" LastActivityDate="2020-07-16T15:09:45.400" Title="Retrieving Translational and Rotational Modes" Tags="|vibrations|gaussian|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="442" PostTypeId="2" ParentId="437" CreationDate="2020-05-07T03:52:09.527" Score="19" Body="&lt;p&gt;Disclaimer: I'm the lead developer of &lt;a href=&quot;https://openbabel.org/&quot; rel=&quot;noreferrer&quot;&gt;Open Babel&lt;/a&gt; and &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; - and currently mentoring Google Summer of Code projects.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The biggest question is more &quot;what kind of topics&quot; interest you and/or what kind of skills you want to learn. Data Science? Informatics? Visualization? Reaction Prediction? QSAR? etc. That would help you refine the possible projects to pursue. Maybe it's a particular programming language or skill? (I usually have my students learn Python through some mini projects relevant to their research.) Maybe it's ways to automate computational or experimental tasks.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Generally open source projects have open lists of bugs, feature requests, etc., often some marked &quot;help wanted&quot; or &quot;good first issue.&quot; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;More involved projects are posted in various places. For example, the &quot;Open Chemistry&quot; mentoring organization for Google Summer of code has this year's &lt;a href=&quot;https://wiki.openchemistry.org/GSoC_Ideas_2020&quot; rel=&quot;noreferrer&quot;&gt;project ideas&lt;/a&gt; for a wide range of topics.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So &lt;em&gt;welcome&lt;/em&gt; - there's lots to do. My suggestion as someone who's helped get many people up to speed with contributing to open source chemistry:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Think about topics or skills that matter to you. There are a huge number of projects and you're most likely to make useful contributions if you're enthusiastic about it.&lt;/li&gt;&#xA;&lt;li&gt;Find a project or two that seems like a good fit. Check out their code, webpages, project pages, etc. Are there good starting points? If not, submit an issue or contact the e-mail list, discussion forum, etc. Chances are good that they'll welcome new contributors.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;If you're not sure, you can always reach out to projects like RDKit, Open Babel, MDTraj, and other larger projects. There's also an excellent review article on &lt;a href=&quot;https://opensourcemolecularmodeling.github.io&quot; rel=&quot;noreferrer&quot;&gt;&quot;Open Source Molecular Modeling&quot;&lt;/a&gt; - originally &lt;a href=&quot;https://doi.org/10.1016/j.jmgm.2016.07.008&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Journal of Molecular Graphics and Modelling&lt;/em&gt; (2016)&lt;/a&gt; that lists tons of projects across multiple topics.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-07T03:52:09.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="443" PostTypeId="2" ParentId="441" CreationDate="2020-05-07T05:02:30.487" Score="18" Body="&lt;p&gt;I've never done this myself, and there may be other approaches, but one possible detailed answer seems to be provided by the Gaussian webpage. For stability reasons, you can find this page via &lt;a href=&quot;https://web.archive.org/web/20191229092611/https://gaussian.com/vib/&quot; rel=&quot;noreferrer&quot;&gt;the Internet Archive&lt;/a&gt; (&lt;a href=&quot;https://web.archive.org/web/20171013014851/http://gaussian.com/wp-content/uploads/dl/vib.pdf&quot; rel=&quot;noreferrer&quot;&gt;pdf&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In particular, you may want to jump to the sections&#xA;&quot;&lt;em&gt;Determine the principal axes of inertia&lt;/em&gt;&quot;&#xA;and&#xA;&quot;&lt;em&gt;Generate coordinates in the rotating and translating frame&lt;/em&gt;&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For convenience, let me copy the procedure here. In short, you want to:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;translate the center of mass to the origin (trivial)&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;calculate the moments of inertia (the diagonal elements) and the products of inertia (off diagonal elements) of the moment of inertia tensor &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;obtain the translational vectors by normalizing the corresponding coordinate axis with the factor &lt;span class=&quot;math-container&quot;&gt;$\sqrt{m_i}$&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;obtain the (infinitesimal) rotational vectors by a slightly more convoluted formula:&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;D_{4,j,i} &amp;amp;= ((P_y)_i X_{j,3} - (P_z)_i X_{j,2})/\sqrt{m_i}\\&#xA;D_{5,j,i} &amp;amp;= ((P_z)_i X_{j,1} - (P_x)_i X_{j,3})/\sqrt{m_i}\\&#xA;D_{6,j,i} &amp;amp;= ((P_x)_i X_{j,2} - (P_y)_i X_{j,1})/\sqrt{m_i}&#xA;\end{align}&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$j = x, y, z$&lt;/span&gt;; &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is over all atoms and &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the dot product of &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; (the coordinates of the atoms with respect to the center of mass) and the corresponding row of &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt;, the matrix used to diagonalize the moment of inertia tensor &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The next step is to normalize these vectors: the vector is normalized using the reciprocal square root of the scalar product.&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="49" LastEditDate="2020-05-10T16:46:04.203" LastActivityDate="2020-05-10T16:46:04.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="444" PostTypeId="1" CreationDate="2020-05-07T05:22:59.237" Score="16" ViewCount="48" Body="&lt;p&gt;&lt;em&gt;This is a particular aspect I'm interested in, from the more generic question&lt;/em&gt;&#xA;&quot;&lt;strong&gt;Does the thermal evolution of chemical structures critically affect the validity of the calculated physical properties?&lt;/strong&gt;&quot;. &lt;em&gt;Generic, as well as particular answers will be welcomed.&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Materials modelling is commonly performed starting from the single-crystal X-ray crystallography, whenever it is available. Theoretically determined structures are compared with this reference structure to assess the validity of the chosen method to estimate the physical property under study. A conceptual problem with this approach is that the theoretical structure corresponds to the bottom of the potential energy well, while the experimental structure is often determined at relatively high temperatures (e.g. 100 K or even 300 K). This means that we have experimental access to the thermally averaged coordinates, which may or may not coincide with the low-temperature energy minimum. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A related conceptual problem is that the higher temperature properties are often estimated from this bottom-of-the-well theoretical structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While it seems clear that there is a fundamental conceptual problem with this approach, since it implicitly assumes that the low temperature structure and the high temperature structures are the same, my question is how serious this problem is, in practice? How much of an error is expected to be introduced by this approximation?&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2020-06-12T13:23:39.127" Title="Does the thermal evolution of molecular structures critically affect the validity of the calculated magnetic anisotropy?" Tags="|magnetism|temperature|thermal|structure|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="445" PostTypeId="2" ParentId="432" CreationDate="2020-05-07T06:41:27.580" Score="16" Body="&lt;p&gt;A rigorous definition of a semimetal can for example be found in the mathematical literature (e.g. this paper: &lt;a href=&quot;https://arxiv.org/abs/2002.01990v1&quot; rel=&quot;noreferrer&quot;&gt;arXiv:2002.01990v1&lt;/a&gt; &lt;strong&gt;[math-ph]&lt;/strong&gt;, &lt;a href=&quot;https://arxiv.org/pdf/2002.01990.pdf&quot; rel=&quot;noreferrer&quot;&gt;pdf version&lt;/a&gt;, assumption 2.5). The basic idea is that the Fermi surface, i.e. the union of points where occupied an unoccupied bands meet, consists exactly of isolated points, the Dirac points. These points are what is called &quot;conical&quot;, meaning that you can make a linear approximation of the bands around them, such that the upper (unoccupied) and lower (occupied) bands looks like a double cone.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So essentially the overlap should consist exactly of isolated points and the bands further clearly separate at the point in the form of a cone.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="49" LastEditDate="2020-05-10T16:49:31.263" LastActivityDate="2020-05-10T16:49:31.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="446" PostTypeId="5" CreationDate="2020-05-07T07:29:58.260" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-07T07:29:58.260" LastActivityDate="2020-05-07T07:29:58.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="447" PostTypeId="4" CreationDate="2020-05-07T07:29:58.260" Score="0" Body="For questions about computational chemistry." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-07T09:50:30.270" LastActivityDate="2020-05-07T09:50:30.270" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="448" PostTypeId="5" CreationDate="2020-05-07T07:30:32.190" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-07T07:30:32.190" LastActivityDate="2020-05-07T07:30:32.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="449" PostTypeId="4" CreationDate="2020-05-07T07:30:32.190" Score="0" Body="For questions about quantum chemistry." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-07T09:50:27.417" LastActivityDate="2020-05-07T09:50:27.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="450" PostTypeId="5" CreationDate="2020-05-07T07:31:48.090" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-07T07:31:48.090" LastActivityDate="2020-05-07T07:31:48.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="451" PostTypeId="4" CreationDate="2020-05-07T07:31:48.090" Score="0" Body="For questions about group theory and applications of symmetry groups of a configuration space." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-07T09:50:33.770" LastActivityDate="2020-05-07T09:50:33.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="452" PostTypeId="2" ParentId="414" CreationDate="2020-05-07T08:09:56.767" Score="16" Body="&lt;h2&gt;NWChem&lt;/h2&gt;&#xA;&lt;p&gt;NWChem is a commonly use quantum chemistry software package with &lt;a href=&quot;https://github.com/nwchemgit/nwchem/wiki/Multiconfiguration_SCF&quot; rel=&quot;noreferrer&quot;&gt;CASSCF&lt;/a&gt; included.&lt;/p&gt;&#xA;&lt;p&gt;NWChem is free, as in both free coffee and free speech.  It is under &lt;a href=&quot;https://opensource.org/licenses/ecl2.php&quot; rel=&quot;noreferrer&quot;&gt;ECL-2.0&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It is written in FORTRAN (in case you want to do some development).&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="5" LastEditDate="2020-09-08T16:35:09.920" LastActivityDate="2020-09-08T16:35:09.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="453" PostTypeId="2" ParentId="416" CreationDate="2020-05-07T14:07:04.810" Score="8" Body="&lt;p&gt;There are two parameters that are important in such a question: the number of molecules and the size of the systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are some approach used to test a molecule. One is using databases with thousand of molecules. One example of such database is &lt;a href=&quot;http://zinc.docking.org/&quot; rel=&quot;noreferrer&quot;&gt;Zinc&lt;/a&gt; that have 230M 3D structures that can be downloaded and freely used. The other approach is the combinatorial chemistry. One technique is the &lt;em&gt;de novo&lt;/em&gt; design. Using this technique against one target, you can generate more than 2.5M molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As many drugs act inhibiting a protein, a single system will have thousand of atoms.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With all the above in mind, for example, if you want to test molecules against one of the proteins related to COVID-19, you will be dealing with thousand of molecules, which means thousand/million of atoms.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Such huge system are intractable using DFT (even with approaches like &lt;a href=&quot;https://en.wikipedia.org/wiki/Fragment_molecular_orbital&quot; rel=&quot;noreferrer&quot;&gt;Fragment Molecular Orbitals&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, the solution is to use simple methods like Molecular Mechanics and Molecular Dynamics that use forcefields making the calculations faster.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="189" LastEditDate="2020-05-07T15:27:46.617" LastActivityDate="2020-05-07T15:27:46.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="454" PostTypeId="1" CreationDate="2020-05-07T14:11:18.823" Score="13" ViewCount="107" Body="&lt;p&gt;According to &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.17.1133&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mermin-Wagner theorem&lt;/a&gt; ferro/antiferromagnetic ordering cannot occur in ideal one dimensional systems. However there exists &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.014410&quot; rel=&quot;nofollow noreferrer&quot;&gt;quasi-one-dimensional ferromagnetic materials&lt;/a&gt; attributing its long range magnetic order stability to magnetic anisotropy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question : How does magnetic anisotropy cause stable long range magnetic ordering in quasi-one-dimensional solids?  &lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="198" LastEditDate="2020-05-08T05:17:08.410" LastActivityDate="2020-05-08T05:17:08.410" Title="How does magnetic anisotropy cause stable long range magnetic ordering in quasi-one-dimensional solids?" Tags="|magnetism|one-dimension|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="455" PostTypeId="2" ParentId="454" CreationDate="2020-05-07T14:42:50.287" Score="9" Body="&lt;p&gt;At least in the example you picked up to illustrate your question, the key to the answer might be here:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&quot;&lt;em&gt;The a axis, perpendicular to the chains in the structure, is the magnetic easy axis, while the chain axis direction, along b, is the hard axis.&lt;/em&gt;&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This means that the effectively infinite magnetic moments corresponding to each infinite one-dimensional chain are in a good situation to achieve an (dipolar) Ising-type ferromagnetic coupling between each other, especially among neighbouring and nearest-neighbouring ones.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To complete the answer we need to consider how the situation would change for perfectly isotropic one-dimensional ferromagnetic chains. In that case, the total spin of each chain would be free to point in any direction. Without geometric restrictions, one can think that the magnetic energy would either be minimized by closing the magnetic field lines locally, or so weak that moments effectively are oriented randomly, with no long-range order, like in a paramagnet.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As complementary readings to understand the role of through-space interactions between magnetic dipoles, I recommend the case of dipolar Ising ferromagnet LiHoF&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;. In this very anisotropic material, magnetic order can be achieved at low temperatures, even though the spins are zero-dimensional, in the sense that both direct exchange and superexchange between nearest neighbours are negligible. There are maybe hundreds of studies on this system; let me pick this one and we'll go back and edit the answer if this particular example seems useless:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/pdf/0903.1603.pdf&quot; rel=&quot;noreferrer&quot;&gt;The ferromagnetic transition and domain structure in LiHoF&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2020-05-07T14:42:50.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="456" PostTypeId="5" CreationDate="2020-05-07T16:46:33.670" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-07T16:46:33.670" LastActivityDate="2020-05-07T16:46:33.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="457" PostTypeId="4" CreationDate="2020-05-07T16:46:33.670" Score="0" Body="For questions about modeling of interfaces between crystalline structures." OwnerUserId="126" LastEditorUserId="126" LastEditDate="2020-05-07T18:28:15.133" LastActivityDate="2020-05-07T18:28:15.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="458" PostTypeId="1" AcceptedAnswerId="460" CreationDate="2020-05-07T18:11:21.080" Score="16" ViewCount="329" Body="&lt;p&gt;My understanding is that geometry relaxation (i.e. letting the nuclei follow the force gradients of the PES until they reach local minima) should usually be performed in order to get the correct molecular or material energies from electronic structure calculations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are there times when doing so would actually give an incorrect/inaccurate answer?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One example that I can think of (which may be incorrect) would be when trying to study molecular ionization by an applied electric field. That is, the electronic dynamics may be so fast that the nuclei would not have the time to respond to the forces before the electron actually leaves the molecule. Thus, to get an accurate understanding of the electron dynamics, you should not let the nuclei relax. To get the final, post-ionization molecular energy, though, you would want to let the nuclei relax again.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are there other, less clear, situations?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="7" LastEditDate="2020-05-15T18:42:57.107" LastActivityDate="2020-05-15T18:42:57.107" Title="When should geometry relaxation not be performed?" Tags="|electronic-structure|born-oppenheimer-approximation|structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="459" PostTypeId="1" AcceptedAnswerId="463" CreationDate="2020-05-07T18:40:46.263" Score="22" ViewCount="168" Body="&lt;p&gt;I'm interested in looking at current flow across a nanoscale junction, specifically a pair of electrodes linked by a molecular bridge. How is this sort of problem typically approached?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm vaguely familiar with the idea of using Green's functions for this purpose, but don't know much in detail beyond that. In terms of the device, is it more common to treat the electrodes as a large cluster or employ periodic boundary conditions for the whole system?&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-05-08T09:53:57.287" Title="How are charge transfer processes modeled in materials?" Tags="|periodic-system|charge-transfer|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="460" PostTypeId="2" ParentId="458" CreationDate="2020-05-07T19:35:53.257" Score="18" Body="&lt;p&gt;Geometry optimization corresponds to a system in equilibrium. It is the &quot;average&quot; position of a molecule vibrating in a well. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, there are many cases where the system  is  &quot;non-equilibrium&quot; which are important to model. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, photochemistry can involve important non-equilibrium processes. &#xA;In photochemistry, relaxation to the ground-state can involve passage through the crossing seam between potential energy surface. At each point in this crossing is a so called &quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Conical_intersection&quot; rel=&quot;noreferrer&quot;&gt;Conical intersection&lt;/a&gt;&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WvOwy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WvOwy.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The dimensions of the seam space is &lt;span class=&quot;math-container&quot;&gt;$3N-2$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$3N-8$&lt;/span&gt; when excluding translations and rotations) which means that there is a lot of places where the molecule can decay to the ground-state. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If there is no local excited-state minimum, then the reactant will simply roll down hill and hit a &quot;tree in the forest&quot; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eUrsO.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eUrsO.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This however, has not stopped computational chemists from employing equilibrium principles to photochemistry by optimizing the &quot;Minimum Energy Conical Intersections&quot;. However, the value in MECI is more qualitative than quantitative. Sometimes they work sometimes they don't!&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-05-07T19:35:53.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="461" PostTypeId="1" AcceptedAnswerId="482" CreationDate="2020-05-07T21:18:54.840" Score="16" ViewCount="313" Body="&lt;p&gt;Does anyone know a tool or a server that can generate the node coordinates for different tiles?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would like to create 2D materials based in some periodic tiles like the ones in the image below:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ya7Zb.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ya7Zb.gif&quot; alt=&quot;The 14 Different Types of Convex Pentagons that Tile the Plane&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More info about tiles: &lt;a href=&quot;https://www.jaapsch.net/tilings/&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;http://www.mathpuzzle.com/tilepent.html&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Pentagonal_tiling&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-08T04:38:42.260" LastActivityDate="2020-05-08T23:37:27.863" Title="Where can I find a tool or server to generate tiles nodes cordinates?" Tags="|software|tiles|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="462" PostTypeId="2" ParentId="382" CreationDate="2020-05-07T21:32:07.337" Score="4" Body="&lt;p&gt;In 2008 I wrote a Python script to generate bicrystal models in a PBC box.&lt;br&gt;&#xA;Since the boundary is periodic (due to PBC), it's always a coincidence site lattice (CSL) boundary.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/h8AbF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/h8AbF.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The script is in repository named &lt;a href=&quot;https://github.com/wojdyr/gosam&quot; rel=&quot;nofollow noreferrer&quot;&gt;gosam&lt;/a&gt;&#xA;and is &lt;a href=&quot;https://github.com/wojdyr/gosam/wiki#bicrystalpy&quot; rel=&quot;nofollow noreferrer&quot;&gt;documented here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The math was based on H. Grimmer's paper &lt;a href=&quot;https://doi.org/10.1107/S0108767384000246&quot; rel=&quot;nofollow noreferrer&quot;&gt;&quot;The generating function for coincidence site lattices in the cubic system&quot;&lt;/a&gt;,&#xA;so it works only for cubic lattices.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From time to time (maybe once every two years) I get a question from someone trying to use this script. Unfortunately, I don't remember much and I can only answer simple questions.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2020-05-07T21:32:07.337" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="463" PostTypeId="2" ParentId="459" CreationDate="2020-05-07T21:36:39.457" Score="18" Body="&lt;p&gt;Here is a paper reviewing charge transport in molecular junctions: J. Chem. Phys. 148, 030901 (2018), &lt;a href=&quot;http://dx.doi.org/10.1063/1.5003306&quot; rel=&quot;noreferrer&quot;&gt;http://dx.doi.org/10.1063/1.5003306&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A typical way to treat such a problem is to couple the Non-equilibrium Green's function (NEGF) formalism with density-functional-theory (DFT), short NEGF-DFT. You need to solve&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;(E-H-\Sigma^{R,B}(E))\cdot G^R(E) = I,&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G^\lessgtr(E) = G^R(E)\cdot\Sigma^{\lessgtr,B}(E)\cdot G^A(E),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the electron energy, &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; the Hamiltonian obtained from DFT, &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; are Green's functions, &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; are self-energies and &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; is the identity matrix. The superscripts denote the retarded, advances, lesser and greater &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt;. The self-energies come from the open boundary conditions (OBC) and couple the device region perturbatively to the leads. These semi-infinite leads are essentially a periodic continuation of the electronic structure of the electrodes. The OBC enable particles to enter and leave the simulation domain. Once the equations are solved for all energies of interest, obeservable quantities such as the current and charge density are computed from the &lt;span class=&quot;math-container&quot;&gt;$G^\lessgtr(E)$&lt;/span&gt;. Injecting charge into the device will affect the potential and therefore also the Hamiltonian. This creates a dependence of DFT on NEGF and vice-versa, which needs to be resolved self-consistently.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A detailed review of NEGF-DFT can be found here:&#xA;Proceedings of the IEEE, vol. 101, no. 2, pp. 518-530, Feb. 2013, &lt;a href=&quot;http://dx.doi.org/10.1109/JPROC.2012.2197810&quot; rel=&quot;noreferrer&quot;&gt;http://dx.doi.org/10.1109/JPROC.2012.2197810&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;NEGF-DFT can also treat thermal transport, and coupled electro-thermal transport though the latter comes at considerable computational cost. In the presence of strong electron-electron or electron-phonon coupling NEGF can break down and more sophisticated but also far more costly simulations are needed such as the hierarchical quantum master equation (HQME) framework [C. Schinabeck, R. Härtle, and M. Thoss, Phys. Rev. B 94, 201407(R) (2016)].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;EDIT 2&lt;/strong&gt;: The Hamiltonian, &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; depend on the electron momentum &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. If there is periodicity in the transverse directions, these equations have to be solved for multiple &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-vectors.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;EDIT 3&lt;/strong&gt;: more on OBC&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Hamiltonian has the following form (requires a localized basis and correct ordering of the atoms):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \begin{pmatrix}&#xA;%       \ddots &amp;amp; &amp;amp; &amp;amp;  \\[0.2em]&#xA;       H_{11} &amp;amp; H_{12} &amp;amp; &amp;amp; \\[0.2em]&#xA;       H_{21} &amp;amp; H_{22} &amp;amp; H_{23} &amp;amp; \\[0.2em]&#xA;       &amp;amp; H_{32} &amp;amp; H_{33} &amp;amp; \ddots  \\[0.2em]&#xA;       &amp;amp; &amp;amp; \ddots &amp;amp; \ddots \\[0.2em]&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;The &lt;span class=&quot;math-container&quot;&gt;$H_{nn}$&lt;/span&gt; are matrices corresponding to slabs sorted along the transport axis. Plug this into the stationary Schrödinger equation &lt;span class=&quot;math-container&quot;&gt;$ (IE-H)\Psi = 0$&lt;/span&gt;&#xA;to find&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(IE-H_{nn})\Psi_n - H_{nn+1}\Psi_{n+1} - H_{nn-1}\Psi_{n-1}=0,$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Psi_n$&lt;/span&gt; is the wave function in the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-th slab. Assuming that the electrode material is periodically continued, we know that &lt;span class=&quot;math-container&quot;&gt;$H_{11}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$H_{12}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$H_{21}$&lt;/span&gt; should be repeated, i.e. &lt;span class=&quot;math-container&quot;&gt;$H_{00}=H_{11}$&lt;/span&gt; etc. If the potential is homogeneous a plane-wave ansatz can be used for &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; to compute &lt;span class=&quot;math-container&quot;&gt;$\Sigma_{11}$&lt;/span&gt;, which contains the &quot;impact&quot; the lead &lt;span class=&quot;math-container&quot;&gt;$H_{00}$&lt;/span&gt; has on &lt;span class=&quot;math-container&quot;&gt;$H_{11}$&lt;/span&gt;. This &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; is the self-energy in the NEGF equations. A thorough derivation can be found in [Phys. Rev. B 74, 205323 (2006)] &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.74.205323&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.74.205323&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The content of &lt;span class=&quot;math-container&quot;&gt;$H_{nn}$&lt;/span&gt; depends on the electronic structure in the transverse directions. It will be different in the case of a nanowire without periodicity than in a 2D material or in bulk. But the tri-diagonal structure of the Hamiltonain remains the same in all cases. Therefore, the procedure to obtain the boundary self-energy is the same.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Edit: typo&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="295" LastEditDate="2020-05-07T23:33:56.063" LastActivityDate="2020-05-07T23:33:56.063" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="464" PostTypeId="1" CreationDate="2020-05-08T02:46:20.400" Score="12" ViewCount="73" Body="&lt;p&gt;I am interested in modeling heterostructures using DFT. What are some good references to start learning?&lt;/p&gt;&#xA;" OwnerUserId="204" LastEditorUserId="5" LastEditDate="2020-05-08T04:38:13.520" LastActivityDate="2020-05-08T04:38:13.520" Title="What are good references to learn how to model heterostructures using DFT?" Tags="|density-functional-theory|reference-request|heterostructures|" AnswerCount="0" CommentCount="3" ClosedDate="2020-05-11T05:41:10.610" ContentLicense="CC BY-SA 4.0" />
  <row Id="465" PostTypeId="2" ParentId="454" CreationDate="2020-05-08T05:09:26.657" Score="5" Body="&lt;p&gt;I have not read the paper your linked to in detail, but I can offer some general answers to your questions. &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;...there exists &lt;strong&gt;quasi&lt;/strong&gt;-one-dimensional ferromagnetic materials attributing its long range magnetic order stability to magnetic &lt;strong&gt;anisotropy&lt;/strong&gt;...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;(emphasis added)&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;We're talking about &lt;strong&gt;quasi&lt;/strong&gt;-1D materials. Usually this means that it's a 3D crystal structure, but the strongest interactions along one direction. You can picture it like a bunch of spin chains arranged in a plane. At high temperatures, the interactions between the chains are negligible, but at low temperatures, those interactions can matter. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Anisotropy&lt;/strong&gt;: The Heisenberg Model has full &lt;em&gt;continuous&lt;/em&gt; 3D rotational symmetry, but the Ising model has &lt;em&gt;discrete&lt;/em&gt; 2-fold (&lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt;) symmetry. You can imagine a continuum between these two extremes: &#xA;&lt;span class=&quot;math-container&quot;&gt;$$ H = -J\sum \limits_i \left[ g S^z_i S^z_{i+1} + (1-g)(S^x_i S^x_{i+1}+S^y_i S^y_{i+1}) \right] $$&lt;/span&gt;&#xA;For &lt;span class=&quot;math-container&quot;&gt;$g=1$&lt;/span&gt;, it's the Ising model, for &lt;span class=&quot;math-container&quot;&gt;$g=0$&lt;/span&gt;, it's an XY model, and for &lt;span class=&quot;math-container&quot;&gt;$g=1/2$&lt;/span&gt; it's the Heisenberg model. An easy-axis ferromagnet (&lt;span class=&quot;math-container&quot;&gt;$1/2 &amp;lt; g &amp;lt;1$&lt;/span&gt;) prefers to order along the z-axis, so it acts a bit more like an Ising model. Therefore, you only have to break a discrete symmetry (glossing over some more subleties). &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;Long-range interactions: magnetic moments in materials might have some longer-range interactions, in which case Mermin-Wagner doesn't apply. &lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-08T05:09:26.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="466" PostTypeId="2" ParentId="459" CreationDate="2020-05-08T05:17:44.697" Score="8" Body="&lt;p&gt;Here's another approach for strongly correlated systems: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.73.195304&quot; rel=&quot;noreferrer&quot;&gt;Al-Hassanieh &lt;em&gt;et al.&lt;/em&gt; Phys. Rev. B &lt;strong&gt;73&lt;/strong&gt; 195304 2006&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In this case, they use time-dependent DMRG. They treat the wire as a chain of sites occupied by spinless Fermions and the junction as an impurity in the wire. They can't observe a steady state current because their system has hard boundaries (the wires just end). The current therefore 'bounces off' the boundary and goes back the other way and then sloshes back and forth. With long enough leads, the middle of a slosh looks like the steady state result. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-08T09:53:57.287" LastActivityDate="2020-05-08T09:53:57.287" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="467" PostTypeId="1" AcceptedAnswerId="470" CreationDate="2020-05-08T07:34:41.813" Score="34" ViewCount="12517" Body="&lt;p&gt;I use &lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt; mostly for crystal structure visualizations.&lt;/p&gt;&#xA;&lt;p&gt;What other options are available?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2021-03-09T16:20:11.097" LastActivityDate="2023-10-19T23:01:30.730" Title="What are the freely available crystal-structure visualization softwares?" Tags="|software|crystal-structure|vesta|atomic-simulation-environment|" AnswerCount="20" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="468" PostTypeId="2" ParentId="467" CreationDate="2020-05-08T07:45:07.637" Score="22" Body="&lt;h2&gt;OVITO&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ovito.org&quot; rel=&quot;noreferrer&quot;&gt;OVITO&lt;/a&gt; is a great tool for visualising supercells and simulation cells with a large number of atoms. There are plenty of modifications available that facilitate analysis, and it also has a Python interface for those who would like to work with scripts.&lt;/p&gt;&#xA;" OwnerUserId="22" LastEditorUserId="5" LastEditDate="2020-11-10T04:55:47.003" LastActivityDate="2020-11-10T04:55:47.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="469" PostTypeId="2" ParentId="467" CreationDate="2020-05-08T08:00:19.750" Score="23" Body="&lt;h2&gt;pymatgen &amp;amp; ASE&lt;/h2&gt;&#xA;&lt;p&gt;I'm a big fan of simplicity and integration in my python-based and Julia-based workflow.&lt;/p&gt;&#xA;&lt;p&gt;Therefore I typically directly use the visualisation features from &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pymatgen&lt;/a&gt;, such as &lt;a href=&quot;https://pymatgen.org/pymatgen.vis.html#module-pymatgen.vis.structure_vtk&quot; rel=&quot;nofollow noreferrer&quot;&gt;pymatgen.vis.structure_vtk&lt;/a&gt;, and &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE&lt;/a&gt;, for example &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/visualize/visualize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ase.visualize&lt;/a&gt;. Mostly I use them anyway to build up my problem. They have some features for analysing results as well, but those I have not used so far.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="671" LastEditDate="2023-10-19T23:01:30.730" LastActivityDate="2023-10-19T23:01:30.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="470" PostTypeId="2" ParentId="467" CreationDate="2020-05-08T08:02:46.240" Score="31" Body="&lt;h2&gt;ASE&lt;/h2&gt;&#xA;&lt;p&gt;The Atomic Simulation Environment (ASE) has visualization capabilities. It is a python environment that allows direct interaction with a lot of atomistic simulation tools.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Visual Molecular Dynamics (VMD) and XCrySDen are the two tools I personally work with the most time. They produce nice graphics and can visualize densities etc. VMD also has rendering capabilites by invoking e.g. PovRay.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ks.uiuc.edu/Research/vmd/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.xcrysden.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.xcrysden.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Visualization Toolkit (VTK) and its graphical interface ParaView are capable of rendering truly stunning images and animations but have a rather steep learning curve.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://vtk.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://vtk.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.paraview.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.paraview.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am sure there are a lot more options than this though.&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="24" LastEditDate="2022-10-03T17:32:36.133" LastActivityDate="2022-10-03T17:32:36.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="471" PostTypeId="2" ParentId="467" CreationDate="2020-05-08T13:54:38.407" Score="20" Body="&lt;h2&gt;OlexSys Olex2&lt;/h2&gt;&#xA;&lt;p&gt;For some applications there exists a elegant software called &lt;a href=&quot;https://www.olexsys.org/Software&quot; rel=&quot;noreferrer&quot;&gt;Olex2&lt;/a&gt; which matches most of the crystallographic requirements of dealing with large systems like metal–organic frameworks.&lt;/p&gt;&#xA;" OwnerUserId="290" LastEditorUserId="724" LastEditDate="2021-01-24T20:29:33.257" LastActivityDate="2021-01-24T20:29:33.257" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="472" PostTypeId="2" ParentId="467" CreationDate="2020-05-08T15:55:08.077" Score="20" Body="&lt;h2&gt;AtomEye&lt;/h2&gt;&#xA;&lt;p&gt;My favorite for working with inorganic crystals. But I moved to biomolecules several years ago, so I don't know how it compares with newer programs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://li.mit.edu/Archive/Graphics/A/&quot; rel=&quot;noreferrer&quot;&gt;AtomEye&lt;/a&gt; has no menu. It is driven by pressing keys on keyboard. Mouse can be used for rotation, selection, etc, but surprisingly many things can be done with keyboard only.&lt;/p&gt;&#xA;&lt;p&gt;It could handle millions of atoms from large-scale MD simulations, although I mostly used it for smaller configurations. AtomEye assumes that the system is under periodic boundary conditions (PBC) in a parallelepiped box. It's possible to shift the system under PBC (shift+mouse drag) - any atom can be moved to the middle of the PBC box. This was a useful feature I haven't seen in other programs.&lt;/p&gt;&#xA;&lt;p&gt;Built-in coloring options were also nice - one can switch with a key press to coloring by coordination number or by sheer strain.&lt;/p&gt;&#xA;&lt;p&gt;I don't have data at hand to make a nice screenshot. Looking into disk backup I found these pictures of SiC that were made with AtomEye:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zdT2y.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zdT2y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="5" LastEditDate="2020-07-30T20:38:01.390" LastActivityDate="2020-07-30T20:38:01.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="473" PostTypeId="1" CreationDate="2020-05-08T17:20:37.167" Score="15" ViewCount="328" Body="&lt;p&gt;I will setup a single point energy calculation using Gaussian for a system containing atoms of B-N-Ni, B-N-Pb and B-N-Cd. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The system are slabs of boron-nitride &lt;a href=&quot;https://doi.org/10.1016/bs.semsem.2016.04.004&quot; rel=&quot;noreferrer&quot;&gt;[1&lt;/a&gt;,&lt;a href=&quot;https://en.wikipedia.org/wiki/Boron_nitride&quot; rel=&quot;noreferrer&quot;&gt;2]&lt;/a&gt; interacting with those metals.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am interested in the electronic wavefunction analysis of the three systems. Specifically, topology analysis for any real space function, such as electron density. The determination of critical points (CPs), topology paths and interbasin surfaces together with population analysis using different schemes (Hirshfeld, ADCH, RESP, etc.) all using the software &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I need two suggestions:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;A functional;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A good basis set I can use for the three systems.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Here &lt;em&gt;good&lt;/em&gt; means that the obtained wavefunction are reliable to be used in such type and analysis given valid results.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(As I will compare the results, I will need the same type of basis sets for all three.)&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-15T00:57:12.363" LastActivityDate="2020-06-15T09:06:29.987" Title="What are good basis sets and functionals for Ni, Cd and Pb?" Tags="|density-functional-theory|basis-sets|functional|gaussian|transition-metals|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="474" PostTypeId="1" CreationDate="2020-05-08T19:32:07.640" Score="13" ViewCount="559" Body="&lt;p&gt;All the tutorials I see online for creating a molecular model are either for small molecules or for crystal systems. I can't seem to figure out how to create a model for a core-shell nanoparticle. Is this doable in VESTA? Or do I have to use something else? Can someone give me directions on how I could learn this?&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="126" LastEditDate="2020-05-09T12:38:28.470" LastActivityDate="2020-05-09T15:11:37.693" Title="How may I create a CIF for a core-shell nanostructure? Is it possible in VESTA, or elsewhere?" Tags="|software|nanoparticles|vesta|cif|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="475" PostTypeId="2" ParentId="474" CreationDate="2020-05-08T20:05:24.610" Score="11" Body="&lt;p&gt;Well, to answer properly this question first we would need a clarification about the nature of the CIF file. This type of file is Crystallographic Information File, which means that it is devoted to periodic, crystalline, and symmetric materials. In my opinion a core-shell nanostructure (CNS) is not fullfilling this requirements.&#xA;In particular, the symmetry and periodicity of a crystalline solid is necessarily different from the discrete nature of such nanostructure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Remember that, contrary to a molecular crystal in which you can extract the geometrical structure of a single entitie, it is not possible to do so in a CSN.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you want to obtain a XYZ file with the positions of the atoms, that is a different point and , as far as I know, it should be handmade.&lt;/p&gt;&#xA;" OwnerUserId="290" LastActivityDate="2020-05-08T20:05:24.610" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="476" PostTypeId="5" CreationDate="2020-05-08T20:32:45.647" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-08T20:32:45.647" LastActivityDate="2020-05-08T20:32:45.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="477" PostTypeId="4" CreationDate="2020-05-08T20:32:45.647" Score="0" Body="For questions related to the Coupled Cluster electronic structure method." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-09T02:42:55.710" LastActivityDate="2020-05-09T02:42:55.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="478" PostTypeId="5" CreationDate="2020-05-08T20:46:35.640" Score="0" Body="&lt;p&gt;Gaussian is an electronic structure package initially developed in the 1970s by John Pople's research group at Carnegie-Mellon. Since then, the program has expanded dramatically, offering a wide range of different methods (e.g. DFT, CASSCF, Coupled Cluster, Moeller-Plesset-n), properties (e.g. NMR, ECD/VCD, Optical Activity, UV-Vis, (hyper)-polarizabilities), and technical capabilities (e.g. multicore/processor, GPU, Gaussview visualization). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For more info, see the latest version of the software, &lt;a href=&quot;http://gaussian.com/g16main/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian 16&lt;/a&gt; &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-08T21:21:22.870" LastActivityDate="2020-05-08T21:21:22.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="479" PostTypeId="4" CreationDate="2020-05-08T20:46:35.640" Score="0" Body="For questions related to the Gaussian electronic structure program" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-09T02:42:47.187" LastActivityDate="2020-05-09T02:42:47.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="480" PostTypeId="5" CreationDate="2020-05-08T22:03:39.427" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-08T22:03:39.427" LastActivityDate="2020-05-08T22:03:39.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="481" PostTypeId="4" CreationDate="2020-05-08T22:03:39.427" Score="0" Body="Please use the full-configuration-interaction tag instead." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-08T22:03:39.427" LastActivityDate="2020-05-08T22:03:39.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="482" PostTypeId="2" ParentId="461" CreationDate="2020-05-08T23:37:27.863" Score="12" Body="&lt;p&gt;You're looking for the &lt;a href=&quot;http://rcsr.anu.edu.au/about&quot; rel=&quot;noreferrer&quot;&gt;Reticular Chemistry Structure Resource&lt;/a&gt;. The website has 3D, 2D, 1D, and 0D nets / tilings.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;At the moment, there are &lt;a href=&quot;http://rcsr.anu.edu.au/layers&quot; rel=&quot;noreferrer&quot;&gt;200 2D layers&lt;/a&gt;. You can filter by numbers of vertices, coordination numbers, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are some resources associated with the &lt;a href=&quot;http://gavrog.org&quot; rel=&quot;noreferrer&quot;&gt;Gavrog / Systre&lt;/a&gt; project for analyzing tilings as well.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These tilings are focused generally on &quot;things that exist&quot;, while some of your tilings seem a bit abstract. For those, I'd suggest using image analysis software or something like &lt;a href=&quot;https://scikit-image.org&quot; rel=&quot;noreferrer&quot;&gt;scikit-image&lt;/a&gt; in Python to find the intersections and derive the coordinates yourself (e.g., using a &lt;a href=&quot;https://scikit-image.org/docs/dev/auto_examples/edges/plot_line_hough_transform.html&quot; rel=&quot;noreferrer&quot;&gt;Hough transform&lt;/a&gt; or contour-finding).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-08T23:37:27.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="483" PostTypeId="1" CreationDate="2020-05-09T02:50:28.500" Score="16" ViewCount="518" Body="&lt;p&gt;T-zero temperature is the temperature at which the Gibbs energies of two phases are equal. Here, I wish to find the temperature at which FCC and BCC have same Gibbs energy. Thermo-Calc console mode has an in-built function to calculate t-zero. However, if I manually do the calculation in TC-Python the results are different.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;from tc_python import *&#xA;w_c=0.008&#xA;with TCPython() as start:&#xA;    # create and configure a single equilibrium calculation&#xA;    calc_result = (&#xA;        start&#xA;            .set_cache_folder(os.path.basename(__file__) + &amp;quot;_cache&amp;quot;)&#xA;            .select_database_and_elements(&amp;quot;TCFE6&amp;quot;, [&amp;quot;Fe&amp;quot;,&amp;quot;C&amp;quot;])&#xA;            .get_system()&#xA;            .with_single_equilibrium_calculation()&#xA;            .disable_global_minimization()&#xA;            .set_condition(ThermodynamicQuantity.mass_fraction_of_a_component(&amp;quot;C&amp;quot;), w_c)&#xA;    )&#xA;    step=2000&#xA;    for temp in np.linspace(500,1200,step):&#xA;        calc = (&#xA;            calc_result&#xA;            .set_condition(ThermodynamicQuantity.temperature(),temp)&#xA;            .calculate()&#xA;        )&#xA;        &#xA;        gf = abs(calc.get_value_of('GM(FCC_A1)'))&#xA;        gb = abs(calc.get_value_of('GM(BCC_A2)'))&#xA;        if(abs(gf-gb)&amp;lt;=1):&#xA;            print(temp,gf,gb)&#xA;            break&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There was no temperature that satisfied this criteria. However, in console mode  (adv-options t-zero bcc_A2 fcc_A1 )I got 784.79 K. If I use run_poly_command also, I get the set-temperature (473 K) and not t-zero temperature.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from tc_python import *&#xA;w_c=0.008&#xA;with TCPython() as start:&#xA;    # create and configure a single equilibrium calculation&#xA;    calc_result = (&#xA;        start&#xA;            .set_cache_folder(os.path.basename(__file__) + &amp;quot;_cache&amp;quot;)&#xA;            .select_database_and_elements(&amp;quot;TCFE6&amp;quot;, [&amp;quot;Fe&amp;quot;,&amp;quot;C&amp;quot;])&#xA;            .get_system()&#xA;            .with_single_equilibrium_calculation()&#xA;            .disable_global_minimization()&#xA;            .set_condition(ThermodynamicQuantity.mass_fraction_of_a_component(&amp;quot;C&amp;quot;), w_c)&#xA;            .set_condition(ThermodynamicQuantity.temperature(),473)&#xA;    )&#xA;    calc=calc_result.run_poly_command('adv t-zero bcc_a2 fcc_a1').calculate()&#xA;    print(calc.get_value_of('T'))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What command should be used to get t-zero temperature in TC-Python?&lt;/p&gt;&#xA;" OwnerUserId="354" LastEditorUserId="354" LastEditDate="2020-07-07T07:30:07.253" LastActivityDate="2020-10-20T16:06:27.523" Title="How to calculate t-zero temperature using Thermo-Calc- Python (TCPython) for multiple alloys?" Tags="|software|thermodynamics|thermo-calc|python|alloys|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="484" PostTypeId="1" CreationDate="2020-05-09T09:25:58.680" Score="9" ViewCount="142" Body="&lt;p&gt;I wonder if anyone might save me several clicks and hours of scrolling and point me to a good recent survey/book on materials informatics to get me acquainted with the field?&lt;/p&gt;&#xA;" OwnerUserId="84" LastEditorUserId="5" LastEditDate="2020-05-09T17:12:25.690" LastActivityDate="2020-06-12T01:13:24.607" Title="Is there any recent beginner's reference on materials informatics?" Tags="|reference-request|materials-informatics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="485" PostTypeId="5" CreationDate="2020-05-09T13:32:53.167" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-09T13:32:53.167" LastActivityDate="2020-05-09T13:32:53.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="486" PostTypeId="4" CreationDate="2020-05-09T13:32:53.167" Score="0" Body="For questions about the use of Crystallographic Information File – file format used in structural sciences." OwnerUserId="126" LastEditorUserId="126" LastEditDate="2020-05-09T23:43:24.480" LastActivityDate="2020-05-09T23:43:24.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="487" PostTypeId="2" ParentId="474" CreationDate="2020-05-09T15:11:37.693" Score="8" Body="&lt;p&gt;Two things are mixed in the question.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;How to create atomistic model of a core-shell nanoparticle?&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;Are both the core and the shell assumed to be crystalline?&lt;br&gt;&#xA;Most likely you will need is to write a small program that generates the required configuration by calculating atomic positions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You can create the first approximation of a (uniform) nanoparticle&#xA;by cutting out a desired shape from a crystal. Sphere is easy to calculate.&#xA;But it's known that some crystal surfaces have lower energy than others (Wulff construction), so polyhedron can be more realistic. &#xA;You can also cut out a shell, but I imagine the structure of the core-shell interface will be non-trivial.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A decade ago I was part of a group that used &quot;core-shell&quot; models, but both core and shell were from the same material, the structure just varied slightly. So that was easier.&#xA;I used a Python script documented here:&lt;br&gt;&#xA;&lt;a href=&quot;https://github.com/wojdyr/gosam/wiki#graingenpy&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/wojdyr/gosam/wiki#graingenpy&lt;/a&gt;&lt;br&gt;&#xA;to generate initial models. The script was modified every time we tried some new idea.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Px5F7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Px5F7.png&quot; alt=&quot;SiC nanoparticle model&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;How to put atomistic model into a CIF file?&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;Do you mean a CIF as it is used in small-molecule crystallography (SMX)?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In general, CIF format is like JSON or XML, it can store anything.&#xA;But in practice it is used only for a few things, so usually it's clear from the context what is meant by CIF. In SMX it's description of a model plus information about experiment and refinement. In MX (M=macromolecular) it's either refinement restraints or a model (mmCIF). Or structure factors. I see that here it must be about coordinates, but we still have two options:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;in SMX fractional coordinates are stored - &lt;em&gt;x&lt;/em&gt; has tag &lt;code&gt;_atom_site_fract_x&lt;/code&gt;,&lt;/li&gt;&#xA;&lt;li&gt;in MX orthogonal coordinates are stored - &lt;em&gt;x&lt;/em&gt; has tag &lt;code&gt;_atom_site.Cartn_x&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Anyway, converting between file formats is the easiest part.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2020-05-09T15:11:37.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="488" PostTypeId="1" AcceptedAnswerId="519" CreationDate="2020-05-09T15:33:25.447" Score="20" ViewCount="2468" Body="&lt;p&gt;We come across many file formats like CIF, XYZ, PDB, INS, cc1, p1, POSCAR, FDF, struct etc. Why do we have so many file formats to store crystal structure information? Are they redundant? Can someone give a historical perspective and advantages/disadvantages of these file formats?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="126" LastEditDate="2020-05-12T14:39:19.970" LastActivityDate="2020-05-12T14:39:19.970" Title="What are the differences between crystal structure file formats like CIF, XYZ, PDB etc.?" Tags="|crystal-structure|cif|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="489" PostTypeId="2" ParentId="160" CreationDate="2020-05-09T19:45:03.073" Score="14" Body="&lt;p&gt;There's two facets to this question:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;What methods can be used for excited states in crystals?&lt;/strong&gt; (the title, and final sentence)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;What methods can be used for excited states with plane waves?&lt;/strong&gt; (paragraphs 1 and 3)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;I will begin by answering the second question, which is in some sense grounded by this assumption:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;it is not possible, as far as I know, to do plane-wave based&#xA;  &quot;configuration interaction&quot; calculations.&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;While CI calculations on plane-wave basis sets are rare, there are in fact examples, and while &lt;a href=&quot;https://www.nature.com/articles/nature11770?platform=oscar&amp;amp;draft=collection&quot; rel=&quot;noreferrer&quot;&gt;this Nature paper&lt;/a&gt;  might not be the only example, it is the one with which I'm most familiar. Here is a quote from the paper (emphasis on the plane wave part was added by me):&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;The determinants in this work are composed from antisymmetrized&#xA;  products of one-electron orbitals obtained from a prior Hartree–Fock&#xA;  calculation in a large &lt;strong&gt;&lt;em&gt;basis of periodic plane waves&lt;/em&gt;&lt;/strong&gt; within the&#xA;  framework of the projector-augmented wave method, as implemented in&#xA;  VASP.&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Since that quote was talking about FCIQMC, I will provide &lt;a href=&quot;https://arxiv.org/abs/1508.04680&quot; rel=&quot;noreferrer&quot;&gt;a reference&lt;/a&gt; for how FCIQMC can treat excited states quite straightforwardly, but you might agree that if FCIQMC can be used with plane waves, then other CI approaches (along with excited-state extensions) can too. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Nature paper also shows results for solids, using MP2 and coupled-cluster, which have excited-state extensions such as EOM-CC (a.k.a. LR-CC), STEOM-CC and Fock-Space CC. On the topic of coupled-cluster, I will also say that two of the same authors from the Nature paper, also describe a &quot;pseudized Gaussian&quot; approach for treating periodic systems, in &lt;a href=&quot;https://arxiv.org/abs/1603.06457&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. Pseudized Gaussians were used in numerous papers which treat periodic systems with coupled cluster, many of them references in &lt;a href=&quot;https://arxiv.org/abs/2004.06424&quot; rel=&quot;noreferrer&quot;&gt;this recent review article&lt;/a&gt; on coupled cluster for materials science.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This conveniently allows me to transition into answering the first of the two questions listed at the top of this answer, which is the one which doesn't mention plane wave sets explicitly. Indeed excited state coupled cluster calculations have been done using Gaussians, for example in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.7b00049&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; in which the opening line of the abstract is:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;We present the results of Gaussian-based ground-state and&#xA;  excited-state equation-of-motion coupled-cluster theory with single&#xA;  and double excitations for three-dimensional solids.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;One of the authors of that paper also published an earlier &lt;a href=&quot;https://science.sciencemag.org/content/345/6197/640.figures-only&quot; rel=&quot;noreferrer&quot;&gt;paper in Science&lt;/a&gt; on crystalline benzene, which uses not only coupled-cluster but also DMRG with Dunning basis sets.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; In addition to TDDFT or other approaches to DFT involving excited states, and the methods based on the GW approximation and the Bethe-Salpeter equation, which Geoff said in the comment he might elaborate more on, DMRG, CI, CC, and their excited-state extensions can be used for plane waves, pseudized Gaussians, or even pure Gaussians, even for periodic systems.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-05-09T19:45:03.073" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="490" PostTypeId="2" ParentId="414" CreationDate="2020-05-09T21:07:23.863" Score="14" Body="&lt;h2&gt;BAGEL&lt;/h2&gt;&#xA;&lt;p&gt;The code is available through GitHub&lt;sup&gt;[1]&lt;/sup&gt; and has been described in WIRES.&lt;sup&gt;[2]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;The main advantages of BAGEL is that it has &lt;s&gt; better memory and parallelization than MOLPRO. For example, MOLPRO (not Free) is restricted to 32 active orbitals. While not a problem for CASSCF, this will severely affect your ability to do CASPT2 calculations.&lt;/s&gt;  (they have fixed this problem in 2012 and it requires the use of rs2c keyword)&lt;/p&gt;&#xA;&lt;p&gt;BAGEL also has the added advantage of being able to calculate CASPT2 non-adiabatic couplings.&lt;/p&gt;&#xA;&lt;p&gt;I should warn, however, that the developers specifically say&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;BAGEL is intended for use in parallel environments with a large amount&lt;br /&gt;&#xA;of distributed memory (e.g., hence there is no disk interface).   We&#xA;are NOT going to optimize BAGEL for a stand-alone workstation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is good news if you are working on a cluster since that means your calculation will run faster, but is bad news if you're working on a smaller scale.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Project on GitHub: &lt;a href=&quot;https://github.com/nubakery/bagel&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/nubakery/bagel&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Shiozaki, T. BAGEL: Brilliantly Advanced General Electronic‐structure Library. &lt;em&gt;WIREs Comput. Mol. Sci.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;8&lt;/em&gt; (1). &lt;a href=&quot;https://doi.org/10.1002/wcms.1331&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/wcms.1331&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-09-08T16:35:04.703" LastActivityDate="2020-09-08T16:35:04.703" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="491" PostTypeId="5" CreationDate="2020-05-09T23:07:35.253" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-09T23:07:35.253" LastActivityDate="2020-05-09T23:07:35.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="492" PostTypeId="4" CreationDate="2020-05-09T23:07:35.253" Score="0" Body="For questions about crystal structure." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-09T23:07:35.253" LastActivityDate="2020-05-09T23:07:35.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="493" PostTypeId="1" CreationDate="2020-05-10T08:48:10.067" Score="8" ViewCount="82" Body="&lt;p&gt;Acid attack in concrete is a problem in sewage structures. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The phases degrade with the pH change at different pH values. The conditions in sewers is complex: The presence of a combination of acids, temperature variation, flow velocity changes, and the effects of bacteria make its study very complicated.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What techniques are used to model the degradation of concrete?&lt;/p&gt;&#xA;" OwnerUserId="380" LastEditorUserId="5" LastEditDate="2020-06-15T01:18:01.163" LastActivityDate="2020-06-15T01:18:01.163" Title="How is the phase degradation of concrete modeled?" Tags="|phase-transitions|macroscopic-materials|materials-engineering|" AnswerCount="0" CommentCount="2" ClosedDate="2020-07-06T14:26:44.167" ContentLicense="CC BY-SA 4.0" />
  <row Id="494" PostTypeId="2" ParentId="431" CreationDate="2020-05-10T09:03:34.633" Score="12" Body="&lt;p&gt;The answer to your question depends a little on the context you are talking about, most importantly the type of basis function you use. As I will describe especially this aspect crucially influences the mathematical structure of the problem you try to solve.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;Structure of Kohn-Sham&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;Being a bit sloppy on the mathematical details (for more see e.g. section 4.6 of &lt;a href=&quot;https://michael-herbst.com/publications/2018.05_phd_corrected.pdf&quot; rel=&quot;noreferrer&quot;&gt;my thesis&lt;/a&gt; Kohn-Sham DFT and related problems such as Hartree-Fock are concerned with solving the following minimisation problem&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \min_{\varphi_i}\left( E[\{\varphi_i\}_i] \right) \quad \text{under the constraint} \quad \int \varphi_i(r) \varphi_j(r) \text{d}r = \delta_{ij} $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where one seeks to find the minimising set of orthonormal orbitals for the Kohn-Sham functional &lt;span class=&quot;math-container&quot;&gt;$E[\{\varphi_i\}_i]$&lt;/span&gt;. Its precise form depends, for example, on the type of exchange-correlation functional employed.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now finding the minimum of this problem means as usual that we need to take the functional derivative of that equation and set it to zero. The resulting Euler-Lagrange equations are the famous Kohn-Sham equations&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{F}[\{\varphi_i\}_i] \varphi_i = \epsilon_i \varphi_i $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;involving the orbital-dependent Kohn-Sham operator &lt;span class=&quot;math-container&quot;&gt;$\hat{F}[\{\varphi_i\}_i]$&lt;/span&gt;. Notice that we are still in the infinite-dimensional regime of functions and operators at this point and notice further that &lt;span class=&quot;math-container&quot;&gt;$\hat{F}$&lt;/span&gt; is actually the derivative of the energy functional with respect to the orbitals.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;Self-consistent field&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;As Yingzhou Li already mentioned there are two ways to tackle this problem. The most common approach is the self-consistent field (SCF) procedure, where our angle of attack is the second equation. Introducing a basis the spectral problem of the operator becomes a generalised matrix eigenvalue problem&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ F[\{v_i\}_i] v_i = \epsilon_i S v_i. $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; depends on the eigenvectors &lt;span class=&quot;math-container&quot;&gt;$\{v_i\}_i$&lt;/span&gt;, the procedure is to first guess some &lt;span class=&quot;math-container&quot;&gt;$\{v_i\}_i$&lt;/span&gt;, build an initial &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;, diagonalise it to get new &lt;span class=&quot;math-container&quot;&gt;$\{v_i\}_i$&lt;/span&gt; and repeat until convergence. Because the diagonalisation is done many times (order of 20 to 50) for a single ground-state DFT calculation this is where most time is spent. I should mention that I am glossing over details here. In practice you never follow this simple procedure but additional measures like &quot;mixing&quot;, &quot;damping&quot; or various forms of preconditioning are employed, but they are not the time-dependent steps.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The structure of &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; depend on the basis you employ. If your basis is orthogonal (like properly normalised plane-waves) than &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is just the identity and can be dropped and you get a standard eigenvalue problem. If you use for example Gaussians, than &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; needs to be kept. Also for plane waves you typically need lots of them, say like 1 million or more, whereas for Gaussians typically large bases are around 1000 functions. On the other hand the matrices &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; for Gaussians are pretty densely populated, whereas for plane-wave-discretised problems &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is very sparse and contains many zeros. (I am focusing on Gaussians versus plane waves here, but the picture is similar for other types of bases).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It is easy to imagine that storing a &lt;span class=&quot;math-container&quot;&gt;$10^6$&lt;/span&gt; times &lt;span class=&quot;math-container&quot;&gt;$10^6$&lt;/span&gt; matrix in memory is going to be a problem, whereas storing a &lt;span class=&quot;math-container&quot;&gt;$1000$&lt;/span&gt; times &lt;span class=&quot;math-container&quot;&gt;$1000$&lt;/span&gt; matrix is completely fine. As a result one usually does not use the same diagonalisation procedures for both type of basis sets: For Gaussians one assembles the matrix and uses a dense diagonalisation procedure from LAPACK, whereas for plane-waves one uses iterative methods like Davidson or LOBPCG, where the key step is to be able to apply &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;.&#xA;That is form matrix-vector products &lt;span class=&quot;math-container&quot;&gt;$F x$&lt;/span&gt; for trial eigenvectors &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; that come up during the iterative procedure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To summarise: For an SCF-based approach for Gaussians building &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is the key step, which primarily involves the computation of the two-electron integrals as the most expensive constituent of &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;. For plane waves, however, the application of &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is most crucial. Here the most costly steps is the computation of fast-fourier transforms, which are needed to transform between Fourier space (the space in which the elements of &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; live) and real space (the space in which the potential is usually stored).&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;Direct minimisation&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;The second approach to tackle Kohn-Sham is not to use a self-consistent field procedure, but instead to directly tackle the minimisation problem I mentioned first. For this one typically uses Newton or Quasi-Newton minimisation procedures to directly minimise the energy by varying the input orbitals (hence the name). These algorithms all require the derivative of the energy wrt. the variations, hence again &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;. But similar to iterative diagonalisations &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; only needs to be applied during the Newton minimsation. Therefore these procedures can be used both for Gaussian as well as plane-wave basis sets and the most costly step is, as before, building &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; or the application of it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Regarding what Yingzhou Li said, there is no limit to using direct minimisation LDA I am aware of. In fact in &lt;a href=&quot;https://dftk.org&quot; rel=&quot;noreferrer&quot;&gt;DFTK&lt;/a&gt; we can easily do direct minimisation for both LDA and GGA functionals and I do not immediately see a reason why an extension to hybrids would not be possible, but we never tried it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It should be said, however, that some restrictions do apply to direct minimisation. In the typical implementations it is assumed that only the orbitals need to be optimised and not the occupation numbers. For systems with zero or small gaps (such as metals) direct minimisation is therefore not suitable.&lt;/p&gt;&#xA;" OwnerUserId="327" LastActivityDate="2020-05-10T09:03:34.633" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="495" PostTypeId="1" CreationDate="2020-05-10T16:49:47.733" Score="23" ViewCount="1892" Body="&lt;p&gt;In a recent article by Woods &lt;em&gt;et. al.&lt;/em&gt;&lt;sup&gt;[1]&lt;/sup&gt; a couple of methods for converging ground-state Kohn-Sham DFT calculations are reviewed and compared. In their test suite they give plenty of examples for badly convergent cases for self-consistent field calculations. Taking a look at their examples it seems that mainly isolated atoms, large cells, slabs and unusual spin systems that cause trouble with convergence.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am wondering what the experience of the community are with respect to cases where standard approaches (e.g. Kerker mixing, some temperature) fail. Did you encounter systems where you had a tough time? What type / class of system were they? What are common approaches to circumvent the problem or improve convergence?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My interest mainly concerns with &lt;em&gt;numerical&lt;/em&gt; convergence problems in the self-consistent field procedure itself. So when one would expect Kohn-Sham DFT to be a sensible model for a particular system, making the SCF problem well-posed, but still the SCF fails to converge (like e.g. the slab of Gold they mention in the cited paper).&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Woods, N. D.; Payne, M. C.; Hasnip, P. J. Computing the self-consistent field in Kohn–Sham density functional theory. &lt;em&gt;J. Phys.: Condens. Matter&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;31&lt;/em&gt; (45), 453001. &lt;a href=&quot;https://doi.org/10.1088/1361-648X/ab31c0&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1088/1361-648X/ab31c0&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="327" LastEditorUserId="5" LastEditDate="2020-05-21T20:07:20.347" LastActivityDate="2020-05-23T01:24:50.783" Title="Difficult cases for converging Kohn-Sham SCF calculations" Tags="|density-functional-theory|self-consistent-field|numerical-convergence|gpaw|" AnswerCount="4" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="496" PostTypeId="5" CreationDate="2020-05-10T17:01:25.643" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Density_matrix_renormalization_group&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia&lt;/a&gt; on the density matrix renormalization group (DMRG) method:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The &lt;strong&gt;density matrix renormalization group (DMRG)&lt;/strong&gt; is a numerical variational technique devised to obtain the low-energy physics of quantum many-body systems with high accuracy. As a variational method, DMRG is an efficient algorithm that attempts to find the lowest-energy matrix product state wavefunction of a Hamiltonian. It was invented in 1992 by Steven R. White and it is nowadays the most efficient method for 1-dimensional systems.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="49" LastEditorUserId="49" LastEditDate="2020-05-10T21:15:31.063" LastActivityDate="2020-05-10T21:15:31.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="497" PostTypeId="4" CreationDate="2020-05-10T17:01:25.643" Score="0" Body="Use this tag for questions about the density matrix renormalization group (DMRG) method." OwnerUserId="49" LastEditorUserId="49" LastEditDate="2020-05-10T21:15:33.850" LastActivityDate="2020-05-10T21:15:33.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="498" PostTypeId="1" AcceptedAnswerId="514" CreationDate="2020-05-10T17:05:31.963" Score="43" ViewCount="7641" Body="&lt;p&gt;Choosing too small of a timestep leads to an unrealistic simulation time, whereas too big of a timestep leads to the system not being represented correctly (or, in the case of an algorithm like &lt;a href=&quot;https://en.wikipedia.org/wiki/Constraint_(computational_chemistry)#The_SHAKE_algorithm&quot; rel=&quot;noreferrer&quot;&gt;SHAKE&lt;/a&gt;, a SHAKE failure). Given a molecular system to be integrated in time, what are bases on which to decide what value of the time step is ideal? What can be used to assert that the choice is the correct one?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example for hyperbolic partial differential equations, there is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Courant%E2%80%93Friedrichs%E2%80%93Lewy_condition&quot; rel=&quot;noreferrer&quot;&gt;Courant-Friedrichts-Lewy&lt;/a&gt; condition which aids in deciding the necessary timestep size in order to get convergence. Is there an equivalent for the equations of motion in molecular dynamics?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2020-05-10T20:37:30.120" LastActivityDate="2021-09-04T08:00:13.773" Title="How should one choose the time step in a molecular dynamics integration?" Tags="|molecular-dynamics|numerical-convergence|" AnswerCount="4" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="499" PostTypeId="1" AcceptedAnswerId="1133" CreationDate="2020-05-10T19:29:35.180" Score="15" ViewCount="860" Body="&lt;p&gt;Before performing Molecular Dynamics on a co-polymer that doesn't have a ready-to-use structure anywhere, the monomer fragment was built in Avogadro software with 0 net charge, B3LYP theory and 6-31G(d) basis set with a multiplicity of 1, being the parameters used for an optimization in Gaussian. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are the parameters that I should look out for, in the Gaussian output, to know that the structure has been optimised for use in MD?&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2020-05-30T03:53:12.763" LastActivityDate="2022-07-18T14:59:21.237" Title="What are the parameters that need to be calculated to design the structure of a molecule?" Tags="|molecular-dynamics|gaussian|structure|polymers|avogadro|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="500" PostTypeId="1" AcceptedAnswerId="837" CreationDate="2020-05-10T20:07:11.127" Score="15" ViewCount="603" Body="&lt;p&gt;The SCF is an iterative procedure to produce the ground state energy and wavefunction for Hartree-Fock, MCSCF, and DFT. Due to the iteration, one needs to establish convergence criteria. Depending on the program used, the default criteria could be just the change in energy (ORCA), the RMS/max change in the density (Gaussian, Q-Chem), or a combination of both (Psi4). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would think you would always want to use both the energy and density in the convergence criteria. Since you need to compute both anyways, it should negligibly increase the cost to check both and would give more information about convergence than either energy/density alone. What would be the advantage of not including the  energy or density in the SCF convergence criteria?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-10T20:36:51.320" LastActivityDate="2020-05-20T22:03:18.127" Title="Convergence by energy and/or density?" Tags="|molecular-modeling|self-consistent-field|numerical-convergence|" AnswerCount="2" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="501" PostTypeId="1" AcceptedAnswerId="503" CreationDate="2020-05-11T07:27:10.313" Score="31" ViewCount="1071" Body="&lt;p&gt;What are the main uses and applications of Julia in matter modeling?&lt;/p&gt;&#xA;&lt;p&gt;Python for example is used in many codes, not to mention workflow automation and data processing.&lt;/p&gt;&#xA;&lt;p&gt;Are there any available codes or publications out there that are based mainly on the Julia programming language?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2021-06-26T18:40:08.270" LastActivityDate="2021-06-26T18:40:08.270" Title="How is Julia used in matter modeling?" Tags="|software|reference-request|python|julia|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="502" PostTypeId="1" AcceptedAnswerId="842" CreationDate="2020-05-11T10:08:11.953" Score="16" ViewCount="434" Body="&lt;p&gt;In the same aspect as some of my previous questions, I am interested in modeling molecules on different surfaces and to study the interfacial effect on them.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One of the most important problems that one can face in such aspect is how to create an initial guess of randomly oriented and distributed molecules over the material surface.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While it is relatively easy to calculate a single molecule on a surface and, if necessary, use Periodic Boundary Conditions to replicate such unit in the material plane, I am not aware in what is the best option to create a much denser 'packing' in a randomized distribution.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Any idea about software or methodology to set this initial structure?&lt;/p&gt;&#xA;" OwnerUserId="290" LastActivityDate="2023-05-09T09:57:23.313" Title="How to model a random distribution of molecules attached to a surface?" Tags="|molecular-modeling|surfaces|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="503" PostTypeId="2" ParentId="501" CreationDate="2020-05-11T10:37:37.480" Score="36" Body="&lt;p&gt;(Disclaimer: As one of the main authors of a Julia-based DFT code, &lt;a href=&quot;https://dftk.org&quot; rel=&quot;noreferrer&quot;&gt;DFTK&lt;/a&gt;, my opinion is definitely biased)&lt;/p&gt;&#xA;&lt;p&gt;The community of people employing Julia for materials modelling is still small, but a couple of programs exist. Probably a good overview gives &lt;a href=&quot;https://github.com/svaksha/Julia.jl/blob/master/Chemistry.md#simulation-methods&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/svaksha/Julia.jl/blob/master/Chemistry.md&lt;/a&gt;. Many projects have only started within the last year, but still show a sizeable set of features, indicating the great potential of Julia for this field. Regarding the workflow, there are not that many packages, but you can just use from python what you need. I'll try to summarise:&lt;/p&gt;&#xA;&lt;h1&gt;Uses of Julia and its design&lt;/h1&gt;&#xA;&lt;p&gt;Julia solves very elegantly what is commonly known as the two-language problem. In computational science one wants to be fast when crunching the numbers (traditionally calling for a language like Fortran, C and C++) and flexible when building models or simulation workflows (calling traditionally for something like python).&lt;/p&gt;&#xA;&lt;p&gt;This by itself has the trouble that people (read: PhD students) need to actually learn two languages to be able to develop the code, but let's argue this is not a problem in practice. Still, we are faced with making the decision at which point to make the cut between the languages. Where this cut point should be placed is less obvious than it might sound if you keep in mind that materials science is an interdisciplinary field with people from maths, physics, chemistry, computer science, ... working on the same sort of problems, but at very different levels. While for a practitioner all the hairy details SCF algorithm, say, are not so important and can be easily shuffled under the carpet of heavy C or Fortran code, mathematicians actually want to modify exactly those to improve mixing schemes or preconditioning and so on. So for a mathematician this should be high-level python to productively do research, but if one does this, it has too much of a performance impact for large-scale practical calculations to be feasible.&lt;/p&gt;&#xA;&lt;p&gt;Here Julia is for the rescue, since as commonly quoted it &lt;em&gt;looks like Python, feels like Lisp, runs like Fortran&lt;/em&gt;. What this is supposed to mean is that writing Julia code is very similar to Python including hairy parts such as linear algebra. It has stronger type systems and structures similar to functional languages like Lisp&#xA;and in the end really is as fast as Fortran or C. The reason is that even though it is a high-level language it has &amp;quot;close to the metal&amp;quot; constructs that allow you to directly influence aspects such as vectorisation, parallelisation and so on. The advantage over a two language solution is, however, that you can introduce them step by step once the first version of the code has been written without rewriting it in another language. So first you get things done, then you get them done fast.&#xA;For any new project in materials modeling, whether you right now think it is performance-critical or not, I think Julia is therefore the perfect language.&lt;/p&gt;&#xA;&lt;h1&gt;Materials-related Julia projects&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/JuliaMolSim&quot; rel=&quot;noreferrer&quot;&gt;JuliaMolSim&lt;/a&gt;: Github organisation for molecular simulation in Julia, packages such as:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/JuliaMolSim/ASE.jl&quot; rel=&quot;noreferrer&quot;&gt;ASE.jl&lt;/a&gt;: (Incomplete) Julia bindings for ASE.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://dftk.org&quot; rel=&quot;noreferrer&quot;&gt;DFTK.jl&lt;/a&gt;:  Flexible Julia code for plane-wave density-functional theory (DFT) and related models. LDA and GGA functionals are supported. Ground-state calculations only for now. Less than 5k lines of code and very hackable. Designed also for mathematical work in the field. Can be used directly from ASE as a calculator using &lt;a href=&quot;https://github.com/mfherbst/asedftk&quot; rel=&quot;noreferrer&quot;&gt;asedftk&lt;/a&gt;. Still experimental, but any feedback welcome!&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/JuliaMolSim/JuLIP.jl&quot; rel=&quot;noreferrer&quot;&gt;JuLIP.jl&lt;/a&gt;: Julia Library for Interatomic Potentials. Can be used to rapidly build and test interatomic potentials for defects etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/jgreener64/Molly.jl&quot; rel=&quot;noreferrer&quot;&gt;Molly.jl&lt;/a&gt;: Proof of concept molecular-dynamics package in Julia.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/SimonEnsemble/PorousMaterials.jl&quot; rel=&quot;noreferrer&quot;&gt;PorousMaterials.jl&lt;/a&gt;: Julia package for modelling adsorption on porous crystals using Monte Carlo methods.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/pablosanjose/Quantica.jl&quot; rel=&quot;noreferrer&quot;&gt;Quantica.jl&lt;/a&gt;: Julia package for building generic tight-binding models and computing various properties from it.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/BBN-Q/QSimulator.jl&quot; rel=&quot;noreferrer&quot;&gt;QSimlator.jl&lt;/a&gt;: Package for Unitary and Lindbladian evolution in Julia.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/vonDonnerstein/QuantumLab.jl&quot; rel=&quot;noreferrer&quot;&gt;QuantumLab.jl&lt;/a&gt;: Experimental package for more molecular quantum chemistry (roadmap is similar to pyscf)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Workflow&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For managing a scientific project &lt;a href=&quot;https://github.com/JuliaDynamics/DrWatson.jl&quot; rel=&quot;noreferrer&quot;&gt;DrWatson.jl&lt;/a&gt; is extremely helpful.&lt;/li&gt;&#xA;&lt;li&gt;The pandas equivalent of Julia is &lt;a href=&quot;https://github.com/JuliaData/DataFrames.jl&quot; rel=&quot;noreferrer&quot;&gt;DataFrames.jl&lt;/a&gt;. You can also directly use &lt;a href=&quot;https://github.com/JuliaIO/HDF5.jl&quot; rel=&quot;noreferrer&quot;&gt;HDF5.jl&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Plotting can be done in &lt;a href=&quot;https://github.com/JuliaPlots/Plots.jl&quot; rel=&quot;noreferrer&quot;&gt;Plots.jl&lt;/a&gt; or matplotlib via &lt;a href=&quot;https://github.com/JuliaPy/PyPlot.jl&quot; rel=&quot;noreferrer&quot;&gt;PyPlot.jl&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Actually you can integrate &lt;em&gt;any&lt;/em&gt; python or R package into a Julia script using packages such as &lt;a href=&quot;https://github.com/JuliaPy/PyCall.jl&quot; rel=&quot;noreferrer&quot;&gt;PyCall.jl&lt;/a&gt; or &lt;a href=&quot;https://github.com/JuliaInterop/RCall.jl&quot; rel=&quot;noreferrer&quot;&gt;RCall.jl&lt;/a&gt;. For python this integration is two-way, so calling Julia from python is a piece of cake. You can even &lt;code&gt;pip install julia&lt;/code&gt;. This is what we use in DFTK to do our lattice and Brillouin zone setup  using &lt;code&gt;spglib&lt;/code&gt; and &lt;code&gt;pymatgen&lt;/code&gt; or import &lt;code&gt;ase.Atoms&lt;/code&gt; into our datastructures.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Publications&lt;/h1&gt;&#xA;&lt;p&gt;Not that many I am aware of. We have recently published a few things with DFTK, but they are not so much related to modelling.&lt;/p&gt;&#xA;&lt;p&gt;In 2019, &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2019.01.012&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;A fresh computational approach to atomic structures, processes and cascades&amp;quot;&lt;/a&gt; was published in &lt;em&gt;Computer Physics Communications&lt;/em&gt;, which presents &lt;em&gt;a fresh concept and implementation of (relativistic) atomic structure theory that supports the computation of interaction amplitudes, properties&lt;/em&gt;, etc., which are implemented in &lt;a href=&quot;https://github.com/OpenJAC/JAC.jl&quot; rel=&quot;noreferrer&quot;&gt;JAC.jl&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Recently,(May 2020) &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2020.107372&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;PWDFT.jl: A Julia package for electronic structure calculation using density functional theory and plane wave basis&amp;quot;&lt;/a&gt; was published in &lt;em&gt;Computer Physics Communications&lt;/em&gt; based on the &lt;a href=&quot;https://github.com/f-fathurrahman/PWDFT.jl&quot; rel=&quot;noreferrer&quot;&gt;PWDFT.jl&lt;/a&gt; package.&lt;/p&gt;&#xA;&lt;p&gt;Also in 2020, the paper &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c00337&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;A New Kid on the Block: Application of Julia to Hartree–Fock Calculations&amp;quot;&lt;/a&gt; was published in the &lt;em&gt;Journal of Chemical Theory and Computation&lt;/em&gt; decribing &lt;a href=&quot;https://github.com/davpoolechem/JuliaChem.jl&quot; rel=&quot;noreferrer&quot;&gt;JuliaChem&lt;/a&gt;, a novel quantum chemistry software designed to take advantage of Julia as much as possible.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="85" LastEditDate="2021-06-26T13:03:49.170" LastActivityDate="2021-06-26T13:03:49.170" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="504" PostTypeId="1" AcceptedAnswerId="935" CreationDate="2020-05-11T11:54:23.697" Score="14" ViewCount="120" Body="&lt;p&gt;While performing molecular dynamics simulations on a co-polymer, how long should the minimum size of the polymer be, to replicate the experimental properties with a reasonable error?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Within this length, are there any standards to be followed for the order of the monomers (for example, -A-A-B-A-B- or any random arrangement), with a given composition of the total ratio A:B ? &lt;/p&gt;&#xA;" OwnerUserId="148" LastActivityDate="2020-07-27T09:05:42.213" Title="How can I decide on the order of different monomers in a co-polymer?" Tags="|molecular-dynamics|gromacs|polymers|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="505" PostTypeId="1" CreationDate="2020-05-11T12:06:31.373" Score="16" ViewCount="99" Body="&lt;p&gt;Characterizing surface properties is important for understanding how proteins execute their function by interacting with other molecules. This includes characterizing cavities.  Perhaps the simplest characteristic measure of a cavity is its volume. The definition of a this volume requires use of a probe. Starting from a set of surface residues accessible to the probe, the cavity volume is defined as a connected volume enclosed by the protein surface and a plane whose intersection with the protein surface defines the outer edge of the enclosing protein surface. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is a computationally simple (as in ideally &quot;canned&quot;, &quot;requiring minimal user input&quot; - a pdb file and probe radius, and perhaps a residue to start searching - and &quot;open-source&quot;) way for computation of the volume, probe-accessible surface area, and probe-accessible residues/atoms in such enclosed cavities? Example: assume I want to analyze these basic properties for the volume enclosed by a chaperone such as &lt;a href=&quot;https://en.wikipedia.org/wiki/GroEL&quot; rel=&quot;noreferrer&quot;&gt;GroEL&lt;/a&gt;. A &lt;a href=&quot;https://www.google.com/search?client=firefox-b-d&amp;amp;q=protein%20cavity%20modeling&quot; rel=&quot;noreferrer&quot;&gt;quick web search&lt;/a&gt; turns up a long list of software programs to explore cavities in proteins including CavVis, CavBench, CAVER, and CavityPlus, to name a few, but I am not familiar with many of these, and lack resources for an exhaustive exploration. What would be appropriate software for the task I am interested in? &lt;/p&gt;&#xA;" OwnerUserId="120" LastEditorUserId="7" LastEditDate="2020-05-20T16:09:33.633" LastActivityDate="2020-05-20T16:09:33.633" Title="Protein cavities - methodological starting point for basic characterization" Tags="|molecular-modeling|surfaces|open-source|molecular-interactions|biomaterials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="506" PostTypeId="2" ParentId="360" CreationDate="2020-05-11T13:57:29.620" Score="7" Body="&lt;p&gt;I don't know if I can give you a definitive response, but I would like to give you some clues based on my experience working with DFT, with Quantum ESPRESSO to be more specific.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As a thumb rule, I guess some parameters should be converged &lt;em&gt;a priori&lt;/em&gt;. Among them are the energy cutoff and k-points sampling. Those are significant parameters to take care of. Since we are dealing with numeric methods, we are not able to integrate up to infinity, therefore cuts are needed. Here I'm not talking about the comparison between different exchange-correlation approximations, but about the chosen functional against itself. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thus, at the beginning of a new simulation, I think it to be necessary to ensure the integrations are converged prior to comparing results between functionals.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To finish it up, I would like to recommend a &lt;a href=&quot;https://www.materialscloud.org/learn/sections/spVa3j/fireside-chats-for-lockdown-times&quot; rel=&quot;noreferrer&quot;&gt;series of talks&lt;/a&gt; given by Dr. Nicola Marzari, head of the Quantum ESPRESSO developers. He describes in detail the implementation of plane wave-based DFT, indicating the important aspects to be taken into account.&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-11T14:16:33.033" LastActivityDate="2020-05-11T14:16:33.033" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="507" PostTypeId="1" CreationDate="2020-05-11T14:19:41.090" Score="20" ViewCount="184" Body="&lt;p&gt;After obtaining the Kohn-Sham orbitals from a plane-wave-based self-consistent-field calculation, the dipole matrix elements could be calculated in order to determine electro-optical properties such as the dieletric response of the material. For instance, Quantum ESPRESSO has two different approaches to accomplish it, namely the epsilon.x program, and TDDFPT (time-dependent density functional perturbation theory) with the turbo_eels.x program. The first one does not take into account electron-electron interaction, the latter does. Both of them are very time consuming and sometimes don't converge at all. It has been shown that such interaction is relevant for molecules (small ones, at least). What about periodic crystals, should I be concerned about it?  &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-30T21:50:37.930" LastActivityDate="2020-06-11T20:05:31.733" Title="What is the importance of electron interaction on dielectric response of crystals?" Tags="|density-functional-theory|quantum-espresso|condensed-matter|td-dft|dfpt|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="508" PostTypeId="1" CreationDate="2020-05-11T14:30:43.257" Score="17" ViewCount="358" Body="&lt;p&gt;Crystallographic Information Files (CIF) are, in general, obtained from experimental measurements. Since the information originated from real samples, is it mandatory to relax the structure in order to determine &quot;better&quot; atoms positions and &quot;better&quot; cell parameters? &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-11T15:42:37.287" LastActivityDate="2020-05-11T16:25:25.383" Title="Is it necessary to optimize structures obtained from a cif file?" Tags="|crystal-structure|optimization|cif|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="509" PostTypeId="2" ParentId="505" CreationDate="2020-05-11T15:26:10.517" Score="11" Body="&lt;p&gt;The identification of cavities, for drug design, is beyond the geometric characterization (aka volume). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The server and individual software, beside the geometrical cavity determination, characterize them following their functionality and extent of solvent exposure, what sites are suitable for occupancy by hydrophobic groups or by ligand hydrogen-bond donors, acceptors, or metal-binding functionality, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Usually, a parameter called &lt;em&gt;druggability&lt;/em&gt; is used to score/classify each cavity found.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The reference below can give you a starting point about this type of analysis:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Halgren, T., &quot;Identifying and Characterizing Binding Sites and Assessing Druggability,&quot; &lt;a href=&quot;https://doi.org/10.1021/ci800324m&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Inf. Model., 2009, 49, 377–389&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Halgren, T., &quot;New Method for Fast and Accurate Binding-site Identification and Analysis,&quot; &lt;a href=&quot;https://doi.org/10.1111/j.1747-0285.2007.00483.x&quot; rel=&quot;noreferrer&quot;&gt;Chem. Biol. Drug Des., 2007, 69, 146–148.&lt;/a&gt; &lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-11T15:26:10.517" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="510" PostTypeId="1" CreationDate="2020-05-11T15:28:06.660" Score="8" ViewCount="75" Body="&lt;p&gt;Because of its size, for example a protein can not be modelled from the quantum chemical basis in a reasonable amount ot time without approximations. A hydrogen atom though can, manually even. &#xA;Where is the boundary between those, where approximations become necessary for the results to be sensible while taking a managable amount of time for the calculations to converge?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I suppose this question is dependent on parameters, such as what computer power is available and what is considered tolerable amount of time for the calculations. Let's say one year computation on &lt;a href=&quot;https://en.wikipedia.org/wiki/Piz_Daint_(supercomputer)&quot; rel=&quot;noreferrer&quot;&gt;Piz Daint&lt;/a&gt;, but feel free to choose the parameters to your liking.&lt;/p&gt;&#xA;" OwnerUserId="108" LastActivityDate="2020-05-12T04:01:58.140" Title="What chemical systems can be modelled without the use of approximations?" Tags="|computational-chemistry|" AnswerCount="1" CommentCount="7" ClosedDate="2020-05-12T06:39:07.317" ContentLicense="CC BY-SA 4.0" />
  <row Id="511" PostTypeId="2" ParentId="508" CreationDate="2020-05-11T15:31:09.827" Score="18" Body="&lt;p&gt;It depends somewhat on the properties you are interested in. Meaningful vibrational modes, for example, require that your geometry is an energy minimum for the method you are using. Since the experimental structure is unlikely to be energy minimum for an arbitrary electronic structure method, you should optimize starting from the experimental structure. Its also important to consider whether you can properly account for temperature effects computationally. This can be challenging for electronic structure techniques, but even classical dynamics can have issues. There can be disparities between the phase diagram of your computational approach and the experimental phase diagram.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, for properties where it is not crucial to be at an energy minimum, it would likely produce better agreement with experiment to use the experimental geometry. For example, while methods to determine electronic absorption or linear/circular birefringence do require finding a stationary electronic state, these properties are still meaningful away from a nuclear minimum. Birefringence in particular is very sensitive to the electronic configuration and so its important that your simulation and experimental geometry match; otherwise, if there are errors, its difficult to determine whether they stem from deficiencies in the property calculation itself or from deviation between the geometries. &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-11T16:25:25.383" LastActivityDate="2020-05-11T16:25:25.383" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="512" PostTypeId="2" ParentId="508" CreationDate="2020-05-11T15:47:49.757" Score="12" Body="&lt;p&gt;This is a very intriguing question.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'll answer assuming that your CIF is formed by a molecule-based crystal.&#xA;The structure in such CIF has been obtained usually by the &lt;a href=&quot;https://www.sciencedirect.com/topics/materials-science/x-ray-diffraction&quot; rel=&quot;noreferrer&quot;&gt;X-ray diffraction technique&lt;/a&gt;. With it, you can obtain a single cell that, repeated in the 3 spatial directions, forms the total crystal structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Considering this, if you isolate just one molecule and perform the structural relaxation, you may obtain a structure that may be far from the original crystal. This makes the necessary standard procedure of obtaining the minimum energy structure invalid, for example, to obtain the vibration frequencies of the molecule in the crystal. In this &lt;a href=&quot;https://arxiv.org/abs/1512.05690&quot; rel=&quot;noreferrer&quot;&gt;work&lt;/a&gt;, Escalera-Moreno, explained the detailed procedure they followed to select the initial structure where the vibrations were calculated. I think it may be useful for you to take a look at it.&lt;/p&gt;&#xA;" OwnerUserId="290" LastActivityDate="2020-05-11T15:47:49.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="513" PostTypeId="1" CreationDate="2020-05-11T17:24:49.693" Score="17" ViewCount="350" Body="&lt;p&gt;Four years ago, the Nobel Prize in physics was awarded for &quot;for theoretical discoveries of topological phase transitions and topological phases of matter.&quot; In line with this, I heard of topological insulators, a new material with the strange property of having an insulating bulk with a conductor surface, having a great interest because they could be useful for many future applications in electronics and quantum computation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would like to know what is a topological insulator from a theoretical point of view, i.e., how to recognize one from its band structure and how is the property of bulk-insulator/surface-conductor explained from first principles (at least conceptually).&lt;/p&gt;&#xA;" OwnerUserId="10" LastActivityDate="2020-05-12T03:53:04.827" Title="What exactly is a topological insulator and how to recognize one from band structure?" Tags="|condensed-matter|topological-insulators|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="514" PostTypeId="2" ParentId="498" CreationDate="2020-05-11T18:43:50.750" Score="31" Body="&lt;h2&gt;The Rule&lt;/h2&gt;&#xA;&lt;p&gt;The timestep should be less than the period of the fastest vibration by at least 2. In signal processing this is known as &lt;a href=&quot;https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem&quot; rel=&quot;noreferrer&quot;&gt;Nyquist's theorem.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If a function&#xA;&lt;span class=&quot;math-container&quot;&gt;${\displaystyle x(t)}$&lt;/span&gt;&#xA;contains no frequencies higher than B hertz, it is completely determined by giving its ordinates at a series of points spaced &lt;span class=&quot;math-container&quot;&gt;${\displaystyle 1/(2B)}$&lt;/span&gt;  seconds apart.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The frequency of a C-H bond is around 3000 &lt;span class=&quot;math-container&quot;&gt;$cm^{-1}$&lt;/span&gt;. Converting to Hertz this is about 8.99e+13 &lt;span class=&quot;math-container&quot;&gt;$Hz$&lt;/span&gt; or a period of 11 femtoseconds.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, we need a timestep of at least 5 fs but the integrator also introduces some error.&lt;/p&gt;&#xA;&lt;p&gt;However, even when doing SHAKE (which removes most of the high-frequency vibrations) &lt;strong&gt;most MD stick with a 2 fs timestep&lt;/strong&gt;. For example, see this &lt;a href=&quot;https://www.charmm.org/ubbthreads/ubbthreads.php?ubb=showflat&amp;amp;Number=10000&quot; rel=&quot;noreferrer&quot;&gt;CHARMM post&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h2&gt;So how do we check?&lt;/h2&gt;&#xA;&lt;p&gt;One way you can check if the timestep is okay is to check if there is any drift in a constant energy simulation (NVE). If there is that can mean that the integrator is not behaving time-reversibly. I ran the following with a time-step of 3 fs and no shake and the energy looks constant&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0kGke.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0kGke.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried to sequentially increase the time-step to demonstrate the drift. However, the energy apparently deviated so fast from constant energy that the energy blew up and OpenMM complained ( this happened at a timestep of 4 fs)&lt;/p&gt;&#xA;&lt;p&gt;Lastly, I wanted to update this post with this excellent &lt;a href=&quot;https://doi.org/10.1016/j.phpro.2014.06.027&quot; rel=&quot;noreferrer&quot;&gt;open-access document:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In that document they give excellent advice on the choice of the time step:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;fluctuations of about 1 part in 5000 of the total system energy per&#xA;twenty time steps are acceptable&lt;/li&gt;&#xA;&lt;li&gt;time step size is about 0.0333&#xA;to 0.01 of the smallest vibrational period in the simulation&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="52" LastEditorUserId="1179" LastEditDate="2021-09-03T15:53:44.383" LastActivityDate="2021-09-03T15:53:44.383" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="517" PostTypeId="2" ParentId="174" CreationDate="2020-05-11T21:45:20.770" Score="18" Body="&lt;p&gt;Adding to the answer given by Cody Aldaz, there are many situations in chemistry when the Born-Oppenheimer approximation (BOA) breaks down, conical intersection is just one of them! In fact, the electronic states do not necessarily have to cross/intersect each other for BOA to be invalid. A classic example of this is given by what is famously known as &quot;avoided crossing&quot;. The general term for phenomena when the BOA breaks down is referred to as &quot;non-adiabatic processes&quot;. The entire field of photochemistry is filled with examples of non-adiabatic processes. Some examples include &lt;strong&gt;internal conversion&lt;/strong&gt; and &lt;strong&gt;singlet fission&lt;/strong&gt;. The former is even responsible for our vision!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From a quantum chemistry point of view, this is very common when one computes excited states (in order to model the above mentioned photochemical processes). You mentioned about Hartree-Fock and DFT. Well, they are single-reference methods to compute ground state energies. For excited state problems, when BOA is no longer valid, one will have to resort to multi-reference methods such as MRCI or EOM-CC. In addition to computing the excitation energies, these methods then allow to compute the &quot;coupling&quot; between different electronic states, precisely the terms that have been neglected in the derivation of BOA.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In short, most excited state problems such as vibronic spectroscopy, charge transfer, photochemistry, singlet fission, and many others will require going beyond Born-Oppenheimer approximation!&lt;/p&gt;&#xA;" OwnerUserId="393" LastActivityDate="2020-05-11T21:45:20.770" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="518" PostTypeId="1" CreationDate="2020-05-11T21:55:41.590" Score="19" ViewCount="3335" Body="&lt;p&gt;&lt;strong&gt;Note added afterwards: This question also has excellent answers on the Chemistry Stack Exchange: &lt;a href=&quot;https://chemistry.stackexchange.com/q/33764/27342&quot;&gt;Is density functional theory an ab initio method?&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;I have very little experience with DFT, but coming from more of a coupled-cluster background, where the improvements are &amp;quot;systematic&amp;quot;, to me it seems that the choice of functional in DFT is somewhat trial-and-error based and also problem specific, perhaps requiring &amp;quot;chemical intuition&amp;quot;. Therefore, can DFT truly be considered an ab initio method?&lt;/p&gt;&#xA;" OwnerUserId="393" LastEditorUserId="5" LastEditDate="2021-02-09T22:18:11.357" LastActivityDate="2021-02-09T22:18:11.357" Title="Can DFT be considered an ab initio method?" Tags="|density-functional-theory|electronic-structure|ab-initio-calculations|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="519" PostTypeId="2" ParentId="488" CreationDate="2020-05-11T22:56:33.793" Score="22" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/XYZ_file_format&quot; rel=&quot;noreferrer&quot;&gt;XYZ&lt;/a&gt; format provides a list of atoms with minimal content: element and coordinates. This is often not sufficient, so people need other formats. In particular, XYZ cannot describe a crystal -- it doesn't include unit cell parameters.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The PDB format was designed with proteins and nucleic acids is mind.&#xA;The format is old (from 1970's) and popular, so sometimes it's used even for inorganic materials, but it's well fitted only for systems with the model&gt;chain&gt;residue&gt;atom hierarchy.&#xA;Additionally, the fixed column format imposes limitations: residue name&#xA;can have up to 3 characters, chain name only a single character,&#xA;atom number - 5 digits.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The CIF format is a narrowed down derivative of a format called STAR.&#xA;Both are used only in structural sciences,&#xA;although they provide a general syntax for storing any data,&#xA;similarly to XML, JSON, YAML, TOML, etc (and CIF is older than XML!).&#xA;Usually, CIF is used together with a dictionary (think XML schema).&#xA;It was first used in the small molecule world.&#xA;About 20 years ago it was adapted to be the successor of the PDB format, called mmCIF. mmCIF uses CIF 1.1 syntax with a different dictionary.&#xA;One visible difference is that mmCIF has dots in tags (&lt;code&gt;_cell.length_a&lt;/code&gt; instead of &lt;code&gt;_cell_length_a&lt;/code&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Some software developers designed own file formats for their programs.&#xA;So we also have a number of software-specific formats. This is a natural thing.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2020-05-11T22:56:33.793" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="520" PostTypeId="2" ParentId="378" CreationDate="2020-05-12T00:02:57.620" Score="9" Body="&lt;p&gt;In general, a system composed of &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; interacting subsystems have a potential energy at a specific configuration of its parts. For instance, a system of &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; nuclei and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons can be separated into interacting subsystems with internal geometries, having &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{R}_A\}$&lt;/span&gt; as nuclear positions for subsystem &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt; electrons, &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{R}_B\}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N_B$&lt;/span&gt; for subsystem &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, and so on. With all the remainder coordinates accounting for the distance between these subsystems, we can write:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{R}=\mathbf{R}_{\text{int}}+\mathbf{R}_{\text{ext}}=\sum_{A}^{K}\left[\sum_{a\in A}\left(\mathbf{R}_a+\sum_{b\in B}\mathbf{R}_{ba}\right)\right]&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_a$&lt;/span&gt; is the position of a nucleus &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; within the subsystem &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; (internal coordinates) and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_{ba}$&lt;/span&gt; is the distance vector from a nucleus &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; in the subsystem &lt;span class=&quot;math-container&quot;&gt;$B\neq A$&lt;/span&gt; to the nucleus &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;According to this, we can write the total energy of the complex as one-system terms, two-system terms, and so on.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E(\{\mathbf{R}\})=\sum_{A}^{K}E_A(\{\mathbf{R}_A\})+\frac{1}{2}\sum_{A}^{K}\sum_{B\neq A}^{K}E_{AB}(\{\mathbf{R}_B-\mathbf{R}_A\})+\dots&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where the energy is adjusted to zero (subtracting the energy of the isolated subsystems from &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;) at infinite separation of the subsystems. Then, we can define a potential energy of interaction between the subsystems as&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta E(\{\mathbf{R}\})=E(\{\mathbf{R}\})-\sum_{A}^{K}E_A(\mathbf{R}_A)=\frac{1}{2}\sum_{A}^{K}\sum_{B\neq A}^{K}E_{AB}(\{\mathbf{R}_B-\mathbf{R}_A\})+\dots&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, this interaction energy can be calculated at any &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{R}\}$&lt;/span&gt;, however, most of the time we want to calculate the interaction energy at optimized geometries &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{R}^{\text{(opt)}}\}$&lt;/span&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta E=E(\{\mathbf{R}^{\text{(opt)}}\})-\sum_{A}^{K}E_A(\mathbf{R}^{\text{(opt)}}_A)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;and this happen to be the binding energy with respect to a specific dissociation route from equilibrium.&lt;/p&gt;&#xA;" OwnerUserId="10" LastActivityDate="2020-05-12T00:02:57.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="521" PostTypeId="2" ParentId="518" CreationDate="2020-05-12T00:20:27.657" Score="4" Body="&lt;p&gt;In principle, DFT is exact, so it's an ab initio method. However, because we don't have an universal functional and work only with approximated functionals, we have to know a priori what functional performs well with our system in study and also compare results with experiment or high-level wavefunction methods. Then, we could say that is a &lt;em&gt;&quot;semi-empirical&quot;&lt;/em&gt; approach, but some could argue with that name.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More information in related posts in &lt;a href=&quot;https://chemistry.stackexchange.com/a/33766/32355&quot;&gt;ChemSE&lt;/a&gt; and &lt;a href=&quot;https://materials.stackexchange.com/a/21/10&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="10" LastEditDate="2020-05-12T02:26:32.103" LastActivityDate="2020-05-12T02:26:32.103" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="522" PostTypeId="2" ParentId="518" CreationDate="2020-05-12T03:42:58.387" Score="9" Body="&lt;p&gt;This is a good question. The term &lt;em&gt;ab initio&lt;/em&gt; &lt;strong&gt;literally&lt;/strong&gt; means 'from the beginning,' &quot;implying that the only inputs into an ab initio calculation are physical constants.&quot; (&lt;a href=&quot;https://en.wikipedia.org/wiki/Ab_initio_quantum_chemistry_methods&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, this term is often used to describe methods that involve empirical approximations (like LDA, GGA) or derived quantities (like pseudopotentials). And DFT is commonly referred to as an &lt;em&gt;ab initio&lt;/em&gt; method, including on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;DFT Wikipedia entry&lt;/a&gt;: &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;In the context of computational materials science, ab initio (from first principles) DFT calculations allow the prediction and calculation of material behaviour on the basis of quantum mechanical considerations, without requiring higher-order parameters such as fundamental material properties. In contemporary DFT techniques the electronic structure is evaluated using a potential acting on the system’s electrons. &lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;There are techniques, like quantum Monte Carlo, or directly solving the Schrodinger equation, that are truly &lt;em&gt;from first principles&lt;/em&gt;, but these techniques are so computationally expensive that they are rarely useful for modelling an actual material at any scale, and are also rarely referred to as &lt;em&gt;ab initio&lt;/em&gt;. DFT is &lt;em&gt;ab initio&lt;/em&gt; relative to other more empirical methods like molecular mechanics. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-12T03:42:58.387" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="523" PostTypeId="2" ParentId="513" CreationDate="2020-05-12T03:53:04.827" Score="9" Body="&lt;p&gt;The &lt;em&gt;bulk&lt;/em&gt; band structure of a topological insulator would look just like any other insulator, with the Fermi level in the gap between the valence and conduction bands. If your band structure includes the surface states, then you would see some states in the gap that cross the Fermi level. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There's an example on &lt;a href=&quot;https://en.wikipedia.org/wiki/Topological_insulator&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt;: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NJ6YJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NJ6YJ.png&quot; alt=&quot;An idealized band structure for a topological insulator. The Fermi level falls within the bulk band gap which is traversed by topologically-protected spin-textured Dirac surface states.&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;An idealized band structure for a topological insulator. The Fermi level falls within the bulk band gap which is traversed by topologically-protected spin-textured Dirac surface states. By &lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Topological_insulator_band_structure.svg&quot; rel=&quot;noreferrer&quot;&gt;A13ean&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As far as whether those surface states will appear in a experimental measurement of the band structure, I am not sure. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-12T03:53:04.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="524" PostTypeId="2" ParentId="510" CreationDate="2020-05-12T04:01:58.140" Score="5" Body="&lt;p&gt;Very small. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The problem is, that for there to be no approximations, you must be solving the full many-body Hamiltonian for all particles. That means to solve just O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; you have six electrons and one nucleus. Even using the Born-Oppenheimer approximation, that leaves you with an eigenvalue problem for 16 3D vectors. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;To take a simpler case (with a discrete Hilbert space), say you want to solve the 1D &lt;span class=&quot;math-container&quot;&gt;$S=1/2$&lt;/span&gt; Heisenberg model, that's a simple spin chain with &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; sites. Each site has two possible states, so the Hilbert space for the whole chain is &lt;span class=&quot;math-container&quot;&gt;$2^L$&lt;/span&gt;. Right now the maximum length of the chain that can be treated without approximations is about 40 sites. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-12T04:01:58.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="525" PostTypeId="1" AcceptedAnswerId="951" CreationDate="2020-05-12T04:08:09.917" Score="25" ViewCount="523" Body="&lt;p&gt;I use the antiferromagnetic Heisenberg model all the time: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ H = J \sum \limits_{\langle i,j \rangle} \vec S_i \cdot \vec S_j$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are some examples of materials that are well-described by this model in &lt;strong&gt;3D&lt;/strong&gt;? What about in &lt;strong&gt;1D&lt;/strong&gt; and &lt;strong&gt;2D&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-05-14T04:21:59.870" LastActivityDate="2020-05-21T00:13:28.767" Title="What are examples of materials that closely correspond to the Heisenberg model?" Tags="|magnetism|one-dimension|model-hamiltonians|spin-models|heisenberg-model|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="526" PostTypeId="1" AcceptedAnswerId="550" CreationDate="2020-05-12T05:12:07.487" Score="29" ViewCount="2103" Body="&lt;p&gt;Every method has its strengths and weaknesses. For instance, a strength of DFT is that is has HF like speeds, but can also account for electron-correlation and this is a pretty big feature since methods that account for electron correlation typically either require more than 1 Slater determinant (Configuration Interaction, Coupled Cluster etc.), or involve expensive perturbation about a HF reference system (Many Body Perturbation Theories).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A result of DFT being so pound-for-pound good is that its popularity is soaring.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Given the relative ease in which a DFT calcualtion can be performed, this makes it perfect for &quot;turning the crank&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are however instances where DFT fails or has caveats.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;What are the systems/phenomena/caveats users should be aware of when modelling materials with DFT?&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;For instance, one caveat I know of is that because of the complexity of the exchange/correlation functionals, they must be numerically integrated. This means a grid-size must be set, and while programs such as Gaussian allow the user to set the grid-size, generally, a default grid-size is used unbeknownst to the novice user.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-05-12T06:22:47.560" LastActivityDate="2020-06-08T21:35:23.990" Title="When and Why does Density Functional Theory (DFT) fail?" Tags="|density-functional-theory|quantum-chemistry|electron-correlation|" AnswerCount="5" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="527" PostTypeId="1" CreationDate="2020-05-12T05:52:36.340" Score="12" ViewCount="184" Body="&lt;p&gt;A technique for deducing arrangements of atoms on crystal surfaces is &lt;a href=&quot;https://en.wikipedia.org/wiki/Low-energy_electron_diffraction&quot; rel=&quot;nofollow noreferrer&quot;&gt;Low Energy Electron Diffraction&lt;/a&gt; or LEED.&lt;/p&gt;&#xA;&lt;p&gt;For a flat crystal surface aligned to a low-order plane with perhaps a 2D periodic overlayer, the directions of the diffracted spots can generally be reproduced from the electron beam momentum and the reciprocal vectors at the surfaces, but the intensities are a challenge to simulate because low energy electrons interact strongly with each atom and really with individual electrons within each atom.&lt;/p&gt;&#xA;&lt;p&gt;Nonetheless a very helpful level of agreement between simulated and measured intensity versus incident electron energy curves (or I/V curves) has led to solutions for a large number of complex surface constructions.&lt;/p&gt;&#xA;&lt;p&gt;From what I understand these self-consistent &lt;a href=&quot;https://en.wikipedia.org/wiki/Low-energy_electron_diffraction#Dynamical_LEED_calculations&quot; rel=&quot;nofollow noreferrer&quot;&gt;dynamical diffraction simulations&lt;/a&gt; are based on models for:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the physical locations of each atom within the unit cells of the bulk and of the 2D overlayer&lt;/li&gt;&#xA;&lt;li&gt;the geometry of the orientations of these, and spacings between layers near the surface&lt;/li&gt;&#xA;&lt;li&gt;the amplitude and phase shift of electron waves at a given energy passing through and scattered by each atom&lt;/li&gt;&#xA;&lt;li&gt;the &amp;quot;internal energy&amp;quot; of the electron as a function of depth, which for say a 50 eV electron can be another 10 eV or so&lt;/li&gt;&#xA;&lt;li&gt;the way the scattered waves add and produce back-diffracted intensities&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'm currently reading about this kind of simulation in hopes of doing it myself, but I'm overwhelmed by the apparent complexity. One reason for this may be that there is a lot of literature on this from an earlier time when the topic was hot but computers were relatively slow, so a lot of work went into optimization of the algorithms for best performance rather than simplicity of approach.&lt;/p&gt;&#xA;&lt;p&gt;For example in the beginning of Chapter 6 of the book &lt;a href=&quot;https://www.springer.com/gp/book/9783642827235&quot; rel=&quot;nofollow noreferrer&quot;&gt;Low-Energy Electron Diffraction; Experiment, Theory and Surface Structure Determination&lt;/a&gt; by Van Hove, M. A., Weinberg, W. H. and Chan, C. -M. 1986, Springer-Verlag the authors write:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...Thus, the more complicated structures investigated in recent years yield costs on the order of US \$ 100 to \$ 500 per structure. As a result, a complete structural analysis in the three quoted situations could cost in practice approximately US \$ 50, \$ 500 and \$ 2,000 to \$ 10,000, respectively.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have a hunch that 34 years later I could potentially do these on my laptop, &lt;em&gt;if only I could figure out how!&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; As my first question here I'd like to ask for an overview description of how self-consistent dynamical diffraction simulations are done, along the lines of my guess in bulleted items above but perhaps with a little more insight. I understand that there may be more than one way to do this calculation, the applications I'm interested in are inorganic adlayers on metal crystal surfaces in coincident lattice configurations.&lt;/p&gt;&#xA;&lt;p&gt;From Math SE:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://math.stackexchange.com/q/3705547/284619&quot;&gt;Determining if a coincident point in a pair of rotated hexagonal lattices is closest to the origin&lt;/a&gt; &lt;em&gt;&lt;strong&gt;currently has &lt;code&gt;+200&lt;/code&gt; bounty!&lt;/strong&gt;&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://math.stackexchange.com/q/3669788/284619&quot;&gt;How should I restrict the points considered in each hexagonal lattice to correctly count all unique near-coincident lattices? Part II (finite sizes)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://math.stackexchange.com/q/3669461/284619&quot;&gt;How should I restrict the points considered in each hexagonal lattice to correctly count all unique near-coincident lattices?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oTkoY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oTkoYm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; click for larger&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2020-08-08T16:41:00.747" LastActivityDate="2020-08-08T16:41:00.747" Title="Overview of how self-consistent dynamical low-energy electron diffraction simulations are performed" Tags="|crystal-structure|crystallography|diffraction|electron-diffraction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="528" PostTypeId="1" CreationDate="2020-05-12T06:13:19.457" Score="17" ViewCount="225" Body="&lt;p&gt;I'm not sure if this will be considered on-topic, let's see what happens. I've &lt;a href=&quot;https://physics.stackexchange.com/q/539969/83380&quot;&gt;asked this previously&lt;/a&gt; in Physics SE and it was closed as needing focus. It is now past 30 days and too late to consider migration.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;note that&lt;/strong&gt; I'm asking about how to treat the atoms and phonons in the wall and how these affect the scattering, not about simulating the subsequent free motion in the box.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;For example Singh et al. (2009) J. App. Phys. 106, 024314 &lt;a href=&quot;https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1022&amp;amp;context=prism&quot; rel=&quot;noreferrer&quot;&gt;Modeling of subcontinuum thermal transport across semiconductor-gasinterfaces&lt;/a&gt; seems to address this using a Boltzman distribution for the gas atoms in the vacuum &lt;em&gt;and for phonons in the wall material&lt;/em&gt; rather than simulating individual atoms of the walls. However I can’t see how to apply that microscopically on a per-collision basis without estimating how many phonons are involved; is it one phonon on average? More? Less?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Figures at the end of &lt;a href=&quot;https://www.osti.gov/servlets/purl/4419031&quot; rel=&quot;noreferrer&quot;&gt;The Interaction of Molecular Beams with Solid Surfaces&lt;/a&gt; show that the spread in angles of atoms incident at 45 degrees does get wider with increased surface temperature, but there is no information on changes in kinetic energy, but Wikipedia's &lt;a href=&quot;https://en.wikipedia.org/wiki/Helium_atom_scattering#Inelastic_measurements&quot; rel=&quot;noreferrer&quot;&gt;Helium atom scattering; Inelastic measurements&lt;/a&gt; suggests that interactions with phonons can lead to a much more complicated picture.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; I'm writing a simple Monte-Carlo simulation for an ultra-high vacuum chamber. I'll initially distribute atoms randomly in position and direction and with speeds derived from a &lt;a href=&quot;https://en.wikipedia.org/wiki/Maxwell%E2%80%93Boltzmann_distribution&quot; rel=&quot;noreferrer&quot;&gt;Maxwell-Boltzmann&lt;/a&gt; distribution. At one end there is a tube of variable length; once a particle passes the far end of it it will be considered &quot;pumped&quot; and no longer tracked. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The idea is to address the effect of a long narrow tube between the chamber and the pump on the effective pumping speed.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'll assume a monatomic gas with no internal degrees of freedom.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; I can introduce the effect of wall roughness by randomly varying the microscopic surface normal from the macroscopic normal at each collision, but I can't think of a way to handle the random momentum transfer effects due to thermal vibrations of the atoms in the wall. These can both change the kinetic energy and the direction of scattering.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What would be a simple, first principles way to introduce it?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I can imagine treating the atom in the wall as a free particle with a similar thermal distribution of speed and direction, but the atoms of the wall are not free, they're constrained by bonds to adjacent atoms. &lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2020-05-13T01:15:23.420" LastActivityDate="2020-05-30T00:05:53.320" Title="How to simulate atomic scattering from solid walls at finite temperature for a particles in a box simulation?" Tags="|phonons|monte-carlo|temperature|transport|scattering|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="529" PostTypeId="2" ParentId="526" CreationDate="2020-05-12T07:16:16.993" Score="4" Body="&lt;p&gt;DFT can break down (like all numerical methods) if you want to model a too-large or too-complicated system. This is especially relevant if you want to study impurities, where periodic boundary conditions are less helpful. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The exchange correlation functionals are a key weakness for DFT, since they are empirical approximations. Therefore the method may encounter trouble when trying to model materials where electron-electron correlations are very important. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-12T07:16:16.993" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="530" PostTypeId="1" AcceptedAnswerId="552" CreationDate="2020-05-12T08:22:08.553" Score="15" ViewCount="183" Body="&lt;p&gt;Within  &lt;a href=&quot;https://en.wikipedia.org/wiki/Born%E2%80%93Oppenheimer_approximation&quot; rel=&quot;noreferrer&quot;&gt;Born-Oppenheimer approximation&lt;/a&gt;, the motion of atomic nuclei are considered as being separated from the electrons movement. Although in general this approximation is valid for a high number of cases, for some particular problems like Vibro-electronic (Vibronic) interaction one should prepare its calculations beyond it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The vibronic interaction have been deeply studied since the decade of 1980's and even earlier. This phenomena assumes that the electron transition (usually a intramolecular charge transfer in a mixed valence system), is mediated by the vibrations of the nuclei. In this regard, the contributions of &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ja00478a011&quot; rel=&quot;noreferrer&quot;&gt;Piepho, Krausz and Schatz&lt;/a&gt; and later by &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ja00227a007&quot; rel=&quot;noreferrer&quot;&gt;Piepho&lt;/a&gt; herself introduced a mathematical model for dealing with this problem in low nuclearity complexes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: Is there any methodology which can explicitly calculate the electro-vibrational levels in a molecule beyond Born-Oppenheimer approximation?&lt;/p&gt;&#xA;" OwnerUserId="290" LastEditorUserId="7" LastEditDate="2020-05-14T16:46:20.087" LastActivityDate="2020-05-14T16:46:20.087" Title="Modeling vibronic interaction beyond Born-Oppenheimer" Tags="|molecular-modeling|molecular-dynamics|born-oppenheimer-approximation|vibronic-interaction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="531" PostTypeId="1" AcceptedAnswerId="1319" CreationDate="2020-05-12T12:03:10.593" Score="14" ViewCount="2005" Body="&lt;p&gt;Gaussian 16 claims to have an external tool to calculate sigma-profile COSMO/RS (Klamt) &lt;a href=&quot;https://gaussian.com/g16glance/&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;. In the support website, there is a SCRF flag for COSMORS &lt;a href=&quot;https://gaussian.com/overlay3/&quot; rel=&quot;noreferrer&quot;&gt;[2]&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How do I calculate sigma-profile using Gaussian 16 and COSMO/RS?&#xA;Are there any examples available?&lt;/p&gt;&#xA;" OwnerUserId="397" LastEditorUserId="7" LastEditDate="2020-05-14T16:45:33.173" LastActivityDate="2020-06-16T18:28:49.910" Title="How to calculate sigma-profile using COSMO/RS and Gaussian 16?" Tags="|gaussian|solvation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="532" PostTypeId="1" AcceptedAnswerId="547" CreationDate="2020-05-12T15:25:05.267" Score="23" ViewCount="747" Body="&lt;p&gt;The Gaussian function &lt;span class=&quot;math-container&quot;&gt;$\propto\exp((x-a)^2/b)$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$b&amp;gt;0$&lt;/span&gt; is one of the most common functions used in molecular modelling (e.g. Gaussian type orbitals).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are some examples of applications of functions (in the literature) used other than the Gaussian in molecular modelling, and are there explanations as to why those are preferred over the Gaussian?&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="5" LastEditDate="2020-05-12T21:53:03.420" LastActivityDate="2020-08-13T10:53:21.137" Title="What functions other than Gaussians are used for orbital basis sets?" Tags="|reference-request|molecular-modeling|basis-sets|" AnswerCount="5" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="533" PostTypeId="2" ParentId="526" CreationDate="2020-05-12T16:29:07.030" Score="21" Body="&lt;p&gt;It is very important to differentiate between &lt;strong&gt;Density Functional Theory (DFT)&lt;/strong&gt; and &lt;strong&gt;Density Functional Approximation (DFA)&lt;/strong&gt;. DFT is an exact theory and if we know the exact formulation for exchange-correlation functional, we should get the exact solution. However we don't have the exact formulation and hence we choose different approximations for it, essentially making it a DFA. And the failures are that of DFA and not DFT.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Quoting Becke [1]&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&lt;em&gt;Let us introduce the acronym DFA at this point for “density-functional approximation.” If you attend DFT meetings, you will know that Mel Levy often needs to remind us that DFT is exact. The failures we report at meetings and in papers are not failures of DFT, but failures of DFAs.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;The known failures of DFAs like the lack of long-range correlation or dispersion interactions and the spurious self-interaction error are addressed by specialized developments for specialized materials (DFT+U, DFT+vdW).[2]&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Becke, Axel D. &quot;Perspective: Fifty years of density-functional theory in chemical physics.&quot; The Journal of chemical physics 140.18 (2014): 18A301.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Maurer, Reinhard J., Christoph Freysoldt, Anthony M. Reilly, Jan Gerit Brandenburg, Oliver T. Hofmann, Torbjörn Björkman, Sébastien Lebègue, and Alexandre Tkatchenko. &quot;Advances in density-functional calculations for materials modeling.&quot; Annual Review of Materials Research 49 (2019): 1-30.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-12T16:58:28.527" LastActivityDate="2020-05-12T16:58:28.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="534" PostTypeId="1" AcceptedAnswerId="1358" CreationDate="2020-05-12T18:07:50.727" Score="20" ViewCount="157" Body="&lt;p&gt;From a physics point of view, there is an effective (approximation to second-order coupling Jaynes-Cummings) Hamiltonian of the form [1]&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H=\sum_j\omega_j(t)\sigma_j^z+\sum_{\langle i,j\rangle}J_{ij}(t)(\sigma_i^+\sigma_j^- + \text{h.c.}) &#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$J_{ij}(t)$&lt;/span&gt; is tunable, meaning that it can always be tuned continuously w.r.t. a parameter (such as capacitance in superconducting circuits). &lt;span class=&quot;math-container&quot;&gt;$\langle i,j\rangle$&lt;/span&gt; denotes the sum over adjacent spin-1/2's that are coupled to each other. We may assumed ferromagnetic or anti-ferromagnetic configuration. But my focus shall be in just the functional form of the Hamiltonian. This coupling Hamiltonian actually resembles the &lt;span class=&quot;math-container&quot;&gt;$XY$&lt;/span&gt; model&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H_{XY}=\sum_{\langle i,j\rangle}2J_{ij}(\sigma_i^+\sigma_j^- + \text{h.c.})=\sum_{\langle i,j\rangle}J_{ij}(\sigma_i^x\sigma_j^x +\sigma_i^y\sigma_j^y)&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$J_{ij}$&lt;/span&gt; are fixed in experiment, not tunable. My aim is to see the purely material implementation for the same where we have some tunable parameter to control and we can selectively and dynamically choose each &lt;span class=&quot;math-container&quot;&gt;$J_{ij}$&lt;/span&gt; for the coupling for each pair.&#xA;Please suggest such materials or theoretical models for such materials if they exist or are proposed.&lt;/p&gt;&#xA;&lt;p&gt;[1] Fei Yan,  Philip Krantz,  Youngkyu Sung,  Morten Kjaergaard,  Daniel L. Campbell,  Terry P. Orlando, Simon Gustavsson, and William D. Oliver.  &lt;a href=&quot;https://journals.aps.org/prapplied/abstract/10.1103/PhysRevApplied.10.054062%5D&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates&lt;/a&gt;. Phys. Rev. Applied, 10:054062, Nov 2018.&lt;/p&gt;&#xA;" OwnerUserId="287" LastEditorUserId="5" LastEditDate="2020-06-20T19:36:12.007" LastActivityDate="2020-06-21T01:17:46.503" Title="What class of materials are closest to realizing the tunable coupling Hamiltonian?" Tags="|condensed-matter|model-hamiltonians|quantum-computing|superconductivity|solid-state-physics|" AnswerCount="1" CommentCount="9" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="535" PostTypeId="1" AcceptedAnswerId="549" CreationDate="2020-05-12T18:50:23.120" Score="15" ViewCount="154" Body="&lt;p&gt;Multi-layer Multi-configuration time-dependent Hartree (ML-MCTDH) is a method widely used for simulation of vibrationally resolved electronic spectra that incorporate the coupling between vibrational modes and the electronic structure of the system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is the largest system that has been  simulated using ML-MCTDH, recorded in literature?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-13T01:04:08.137" LastActivityDate="2020-05-13T01:46:39.180" Title="What is the largest system for which vibrationally resolved electronic spectra have been simulated using ML-MCTDH?" Tags="|reference-request|electronic-structure|molecular-modeling|vibrations|mctdh|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="536" PostTypeId="1" CreationDate="2020-05-12T19:37:55.957" Score="16" ViewCount="83" Body="&lt;p&gt;I wonder if there are any books or resources that may address one or more of the following questions:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What kinds of defects are important for topology? Especially crystallographic defects.&lt;/li&gt;&#xA;&lt;li&gt;How do they relate to the defect topological dimension?&lt;/li&gt;&#xA;&lt;li&gt;How do they change in different crystal dimensions?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="287" LastEditorUserId="5" LastEditDate="2020-05-12T21:37:27.503" LastActivityDate="2020-05-20T12:03:33.037" Title="What are good resources to study crystallographic defects in different dimensional systems and their topological dimensionality?" Tags="|reference-request|crystal-structure|condensed-matter|defects|topological-insulators|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="537" PostTypeId="2" ParentId="501" CreationDate="2020-05-12T19:39:34.047" Score="9" Body="&lt;p&gt;And of course, there is Lattices.jl, for defining lattices in Julia. Please note that this package is still in the very early stages of exploring a potential Julian interface for lattices, and should be used with discretion.&#xA;&lt;a href=&quot;https://juliaphysics.github.io/Lattices.jl/latest/&quot; rel=&quot;noreferrer&quot;&gt;https://juliaphysics.github.io/Lattices.jl/latest/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="36" LastActivityDate="2020-05-12T19:39:34.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="538" PostTypeId="2" ParentId="535" CreationDate="2020-05-12T20:35:43.103" Score="8" Body="&lt;p&gt;The developers of MCTDH from Heidelberg reported in the year 2000 &lt;sup&gt;[1]&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The largest system treated with MCTDH to date is the pyrazine&#xA;  molecule, where all 24 (!) vibrational modes were accounted for. The&#xA;  particular representation of the MCTDH wavefunction requires special&#xA;  techniques for generating an initial wavepacket and for analysing the&#xA;  propagated wavefunction&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;However, this is almost certainly outdated (20 years old). I'm just posting this here to get the ball rolling in case anyone else knows better. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;M.H.Beck, A.Jäckle, G.A.Worth, H.-D.Meyer, The multiconfiguration time-dependent Hartree (MCTDH) method: a highly efficient algorithm for propagating wavepackets, &lt;em&gt;Physics Reports&lt;/em&gt;, &lt;strong&gt;2000&lt;/strong&gt;, 324 &lt;a href=&quot;http://dx.doi.org/10.1016/S0370-1573(99)00047-2&quot; rel=&quot;noreferrer&quot;&gt;DOI:10.1016/S0370-1573(99)00047-2&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-05-12T20:35:43.103" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="539" PostTypeId="5" CreationDate="2020-05-12T20:41:02.513" Score="0" Body="&lt;p&gt;Python is a general purpose programming language developed by Guido van Rossum. While not designed with a heavy computational emphasis, its ease of use led it to become popular among computational scientists. For scientific applications, the language is very easy to use for prototyping due to the wide array of easy to use math and data processing modules (e.g. Numpy, Scipy, Pandas, Matplotlib, Tensorflow).&lt;/p&gt;&#xA;&lt;p&gt;Some prominent material simulation packages developed in Python include &lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Psi4&lt;/a&gt;, &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymatgen&lt;/a&gt;, &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;, and &lt;a href=&quot;http://pyscf.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2023-02-24T15:00:38.230" LastActivityDate="2023-02-24T15:00:38.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="540" PostTypeId="4" CreationDate="2020-05-12T20:41:02.513" Score="0" Body="Questions about or related to Matter Modeling with Python or Python's relationship to Matter Modeling." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2023-02-24T15:00:18.497" LastActivityDate="2023-02-24T15:00:18.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="541" PostTypeId="5" CreationDate="2020-05-12T23:52:41.520" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:52:41.520" LastActivityDate="2020-05-12T23:52:41.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="542" PostTypeId="4" CreationDate="2020-05-12T23:52:41.520" Score="0" Body="For questions about the concept of temperature in molecular or materials modeling, or about applications in which temperature plays an important role." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:52:41.520" LastActivityDate="2020-05-12T23:52:41.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="543" PostTypeId="5" CreationDate="2020-05-12T23:53:29.703" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:53:29.703" LastActivityDate="2020-05-12T23:53:29.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="544" PostTypeId="4" CreationDate="2020-05-12T23:53:29.703" Score="0" Body="For questions about numerical convergence in molecular and materials modeling questions." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:53:29.703" LastActivityDate="2020-05-12T23:53:29.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="545" PostTypeId="5" CreationDate="2020-05-12T23:54:08.800" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:54:08.800" LastActivityDate="2020-05-12T23:54:08.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="546" PostTypeId="4" CreationDate="2020-05-12T23:54:08.800" Score="0" Body="For questions about the software AVOGADRO." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-12T23:54:08.800" LastActivityDate="2020-05-12T23:54:08.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="547" PostTypeId="2" ParentId="532" CreationDate="2020-05-13T00:25:12.253" Score="17" Body="&lt;p&gt;There are two considerations guiding the choice a basis for orbital expansion:&#xA;1. Compactness;&#xA;2. Efficiency of computations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are two common choices for basis functions (A) &lt;strong&gt;Gaussians&lt;/strong&gt; and (B) &lt;strong&gt;Plane waves&lt;/strong&gt;.&#xA;Both of those allow for the most efficient way to evaluate the integrals needed to construct the Fock matrix (i.e. second derivative for kinetic energy, nuclear-electron attraction and electron-electron repulsion)  - &lt;strong&gt;analytically&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(A) Gaussians is by far the most popular set for &lt;strong&gt;localized&lt;/strong&gt; systems (e.g. molecules). The reason is because Gaussian functions are themselves localized and thus they can be used to compactly represent electron density localized around nuclei (i.e. you don't need too many Gaussian functions to do this). Plane waves resolve all of the simulation volume with equal accuracy, so a large part of the computational effort is wasted on (nearly) empty space.&#xA;(B) Plane waves are much more popular for computations on &lt;strong&gt;periodic&lt;/strong&gt; (condensed matter) systems (e.g. crystal structures). They enable even more efficient computations, since (unlike Gaussians) they are &lt;strong&gt;orthonormal&lt;/strong&gt; and so there is no need to compute the overlap matrix S.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In practice, the sharp features (like the cusp near the nucleus) are still tough for the plane waves. This problem is circumvented by using the pseudopotentials, which smooth out the sharp features.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another good reason to use either Gaussian or plane wave basis sets is that a lot of work has been done for you to develop really good Gaussian contractions and pseudopotentials. For a typical system there is no need to reinvent the wheel. That said, better basis sets are sought after and situationally (e.g. for a strange system) a different basis set could be much better.&lt;/p&gt;&#xA;" OwnerUserId="349" LastActivityDate="2020-05-13T00:25:12.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="548" PostTypeId="1" CreationDate="2020-05-13T00:34:46.123" Score="19" ViewCount="229" Body="&lt;p&gt;Quoting Becke [1]&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&lt;em&gt;Density-functional theory (DFT) is a subtle, seductive, provocative business. Its basic premise, that all the intricate motions and pair correlations in a many-electron system are somehow contained in the total electron density alone, is so compelling it can drive one mad&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;How do you convince yourself that all the intricate motions and pair correlations in a many-electron system are somehow contained in the total electron density alone?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;PS: I am not looking for proofs for Hohenberg-Kohn theorems. More like a physical/intuitive picture&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Becke, Axel D. &quot;Perspective: Fifty years of density-functional theory in chemical physics.&quot; The Journal of chemical physics 140.18 (2014): 18A301.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-13T20:59:24.343" LastActivityDate="2020-09-20T12:50:40.917" Title="Physical/Intuitive picture for DFT that all motions and pair correlations in a many-electron system are contained in the total electron density alone" Tags="|density-functional-theory|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="549" PostTypeId="2" ParentId="535" CreationDate="2020-05-13T00:55:31.890" Score="9" Body="&lt;p&gt;When you say MCTDH, I am assuming you mean the vanilla MCTDH without employing the multi-layer structure. In which case 24 modes seem to be the best known result (higher modes can be done, I have tried things myself with more than 24 modes, but they are unpublished results!) However, the true power of MCTDH comes with ML-MCTDH, which is sort of adding another layer of MCTDH on top of MCTDH and so on (think tensor networks).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With ML-MCTDH, for isolated gas phase molecules, photoelectron spectra have been simulated for naphthalene (&lt;strong&gt;48D&lt;/strong&gt;) and anthracene (&lt;strong&gt;66D&lt;/strong&gt;)! [&lt;em&gt;J. Chem. Phys.&lt;/em&gt;, &lt;strong&gt;138&lt;/strong&gt;, 014313 (2013)]&lt;/p&gt;&#xA;" OwnerUserId="393" LastEditorUserId="393" LastEditDate="2020-05-13T01:46:39.180" LastActivityDate="2020-05-13T01:46:39.180" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="550" PostTypeId="2" ParentId="526" CreationDate="2020-05-13T01:07:48.843" Score="22" Body="&lt;p&gt;First, a word of caution: it is hard to generalize since there are so many different approximations to the exact exchange-correlation functional. Nonetheless, in my opinion:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The biggest weakness of all existing (and arguably all plausible) implementations of DFT is their &lt;strong&gt;limited predictive power&lt;/strong&gt;. In practice, this means that you need to know a lot about your system to choose the right method (functional) and you can only sort of trust the answer (as evidenced by the variety of answers you get when using different functionals). More precisely, your degree of confidence decreases as you move to more &quot;weird&quot; systems, that are not usually used to inform the construction of the exchange-correlation functionals.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Density functionals are &lt;strong&gt;not systematically improvable&lt;/strong&gt;. There is no guarantee that using the density functionals higher up on the Jakob's ladder will give a more accurate answer. This is fundamentally different from the coupled-cluster or configuration interaction approaches. For a recent long-read review check out  &lt;a href=&quot;https://doi.org/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;this work from Martin Head-Gordon group&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally, the &lt;strong&gt;grid convergence&lt;/strong&gt; you mentioned is a big issue for an average user that is treating DFT implementations as black-box methods. &lt;a href=&quot;https://chemrxiv.org/articles/Popular_Integration_Grids_Can_Result_in_Large_Errors_in_DFT-Computed_Free_Energies/8864204/5&quot; rel=&quot;noreferrer&quot;&gt;Steven Wheeler has explored this recently&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="349" LastActivityDate="2020-05-13T01:07:48.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="551" PostTypeId="1" CreationDate="2020-05-13T01:21:07.850" Score="12" ViewCount="215" Body="&lt;p&gt;I've just found this &lt;a href=&quot;https://doi.org/10.1063/1.4900629&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; (&lt;a href=&quot;https://doi.org/10.1063/1.4900629&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 141, 174106 (&lt;strong&gt;2014&lt;/strong&gt;)&lt;/a&gt;) that deals with the translational and rotational entropies in solution. The method is promising but, unfortunately, requires a modification in the frequency calculation that is not readily available on most quantum chemistry packages.&lt;/p&gt;&#xA;&lt;p&gt;As such, my question is &lt;strong&gt;which methods &lt;em&gt;explicitly&lt;/em&gt; calculate solvation contributions to free energies and how do they compare?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;They naturally have something to do with a polarizable continuum (&lt;a href=&quot;https://doi.org/10.1021/jp9716997&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A &lt;strong&gt;1998&lt;/strong&gt;, 102, 11, 1995-2001&lt;/a&gt;), but which methods go beyond pure electrostatic/cavity/dispersion energies and deal with free energy in terms of entropies and enthalpies (as in the rigid rotor-harmonic oscillator approximation)? (I would rather avoid purely parameterized corrections as in, e.g., &lt;a href=&quot;https://doi.org/10.1021/jp810292n&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. B &lt;strong&gt;2009&lt;/strong&gt;, 113, 18, 6378-6396&lt;/a&gt;.)&lt;/p&gt;&#xA;&lt;h1&gt;The problem of entropy&lt;/h1&gt;&#xA;&lt;p&gt;In terms of free energy contributions, one particularly significant contribution is entropy. Are there any readily available methods/theories for the rotational and translational contributions to enthalpy and entropy of solutes?&lt;/p&gt;&#xA;&lt;p&gt;I am particularly interested in the fact that current successful methods (SMD, PCM, etc.) seem to adjust &lt;em&gt;electronic energies&lt;/em&gt; using &lt;em&gt;free energy&lt;/em&gt; terms, such as CPCM (which explicitly uses an equation derived by Pierotti from the hard-sphere theory for calculating the cavity free energy, &lt;a href=&quot;https://doi.org/10.1021/jp9716997&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A &lt;strong&gt;1998&lt;/strong&gt;, 102, 11, 1995-2001&lt;/a&gt;), or SMD (which uses purely parameterized terms that certainly include entropic contributions). As such, their temperature dependence likely wrong (&lt;em&gt;or am I missing something?&lt;/em&gt;). This has been addressed in recent publications to some extent, such as in  &lt;a href=&quot;https://doi.org/10.1039/C9CY01285K&quot; rel=&quot;nofollow noreferrer&quot;&gt;Catal. Sci. Technol., &lt;strong&gt;2019&lt;/strong&gt;,9, 5433-5440&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/acscatal.9b01537&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACS Catal. &lt;strong&gt;2019&lt;/strong&gt;, 9, 8, 6803–6813&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="63" LastEditDate="2020-06-26T13:22:15.573" LastActivityDate="2020-08-16T15:17:01.097" Title="What are the methods for calculating solvation effects in free energies and how do they compare?" Tags="|gibbs-free-energy|thermodynamics|entropy|solvation|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="552" PostTypeId="2" ParentId="530" CreationDate="2020-05-13T01:32:09.733" Score="12" Body="&lt;p&gt;This is a good question. In order to go beyond Born-Oppenheimer approximation, one has to first make a choice of electronic basis - diabatic or adiabatic - in order to define the vibronic coupling (vibrational-electronic coupling). The adiabatic choice seems to be more practical since it is a well-defined basis (adiabatic states are eigenstates of the electronic Hamiltonian) and most quantum chemistry program make use of them anyway. So the &quot;only&quot; thing remains to compute is the non-adibatic coupling vectors (NADVEC) between different electronic states. These calculations are now possible with programs such as MOLPRO, COLUMBUS, CFOUR and others. Adiabatic basis is often used in conjunction with &quot;on-the-fly&quot; molecular dynamics methods such as the popular Surface Hopping scheme.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, most vibronic problems are actually studied using diabatic basis, and for good reason. While diabatic states are not unique (and NOT eigenstates of electronic Hamiltonian), they preserve the electronic character with the change in nuclear position and are therefore &quot;smoothly varying&quot;. Not only this has better mathematical properties (potential energy surface is always differentiable, unlike in adiabatic basis, where PES may have &quot;cusps&quot;), but also it has more &quot;chemical&quot; meaning. Think of diabatic states as the valence bond structures (like resonance structure of benzene!).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A large body of work has been done to model vibronic problems in diabatic basis. The most popular approach is the &quot;vibronic model Hamiltonian&quot; proposed by Koppel-Domcke-Cederbaum (KDC) in 1984 [1]. It remains a classic and is an excellent place to start for all things vibronic. Even today the linear variant of vibronic models (Linear Vibronic Model or commonly known as LVC) is used widely to model many different kind of processes. The parameters of the vibronic models can be obtained in many different ways, and the process of extracting these parameters is known as &quot;diabatization&quot;. Since diabatic states are not unique, many diabatization procedures have been proposed in the literature. However, this depends on the problem and is often also a matter of taste, and does not take away the power of vibronic model Hamiltonian ansatz!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;PS: Vibronic model Hamiltonian is also referred to as KDC Hamiltonian for obvious reasons!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;H. Köuppel, W. Domcke, L. S. Cederbaum, Multimode Molecular Dynamics Beyond the Born‐Oppenheimer Approximation, Advances in Chemical Physics, Volume 57, 1984. &lt;a href=&quot;https://doi.org/10.1002/9780470142813.ch2&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1002/9780470142813.ch2&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="393" LastEditorUserId="393" LastEditDate="2020-05-13T10:34:43.483" LastActivityDate="2020-05-13T10:34:43.483" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="553" PostTypeId="2" ParentId="174" CreationDate="2020-05-13T01:45:25.327" Score="9" Body="&lt;p&gt;In addition to the classic examples of where non-adiabatic effects are important, the Born-Oppenheimer approximation cannot be taken for granted in the electronic structure computations of small chemical systems, where &lt;strong&gt;high-accuracy&lt;/strong&gt; is needed (e.g. &lt;a href=&quot;http://aip.scitation.org/doi/10.1063/1.1540626&quot; rel=&quot;noreferrer&quot;&gt;isotope dependence of molecular properties, high-resolution rovibrational spectroscopy, and quantum nuclear dynamics&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In some cases, a (relatively) easy fix is possible - &lt;a href=&quot;http://aip.scitation.org/doi/10.1063/1.2356465&quot; rel=&quot;noreferrer&quot;&gt;DBOC (diagonal Born-Oppenheimer correction)&lt;/a&gt;, which is to take into account first-order correction only. Otherwise, non-adiabatic effects need to be taken into account (e.g. &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp0032513&quot; rel=&quot;noreferrer&quot;&gt;here is such a calculation for water&lt;/a&gt;). &lt;/p&gt;&#xA;" OwnerUserId="349" LastEditorUserId="5" LastEditDate="2020-05-13T03:36:39.017" LastActivityDate="2020-05-13T03:36:39.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="554" PostTypeId="1" AcceptedAnswerId="555" CreationDate="2020-05-13T02:07:09.740" Score="28" ViewCount="648" Body="&lt;p&gt;Taking into account the fact that the theory of quantum gravity does not exist and the QED calculations are not possible for most realistic chemical systems, what levels of accuracy can we expect from a theoretical calculation on simple (small) materials? Examples that come to mind are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Simplest molecular materials: &lt;span class=&quot;math-container&quot;&gt;$^3\ce{He}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$^4\ce{He}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H_2}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Simplest periodic systems, i.e. metallic &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="349" LastEditorUserId="5" LastEditDate="2020-09-18T15:59:26.747" LastActivityDate="2021-01-20T19:37:23.993" Title="How accurate are the most accurate calculations?" Tags="|molecular-modeling|periodic-system|full-configuration-interaction|atomic-physics|high-precision|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="555" PostTypeId="2" ParentId="554" CreationDate="2020-05-13T03:05:59.243" Score="29" Body="&lt;h2&gt;Exhibit 1: Ground state hyperfine splitting of the H atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;1420405751767(1) mHz (present most accurate experiment)&#xA;142045199        mHz (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The error in the theory is due to the difficulty in treating the nuclear structure (2 up quarks + 1 down).&lt;/p&gt;&#xA;&lt;h2&gt;Exhibit 2: Ground state hyperfine splitting of the muonium atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;4463302780(050) Hz (present most accurate experiment)&#xA;4463302880(550) Hz (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why does it agree so well? μ&lt;span class=&quot;math-container&quot;&gt;$^+$&lt;/span&gt; is a fundamental particle and therefore has no nuclear structure. QED is the correct theory for describing the interaction between pure electric charges (e&lt;span class=&quot;math-container&quot;&gt;$^-$&lt;/span&gt; and μ&lt;span class=&quot;math-container&quot;&gt;$^+$&lt;/span&gt;). The only QFD (quantum flavordynamics) needed is for the electro-weak interaction &lt;em&gt;between&lt;/em&gt; the particles (not for interactions within sub-nuclear particles), and QFD calculations were done &lt;a href=&quot;https://arxiv.org/abs/1502.03841&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; in anticipation of more accurate experiments to come.&lt;/p&gt;&#xA;&lt;h2&gt;Exhibit 3: Ground state hyperfine splitting of the He atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;6739701177(0016) Hz (present most accurate experiment)&#xA;6739699930(1700) Hz (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice how much harder it is when you add an electron.&lt;/p&gt;&#xA;&lt;h2&gt;Exhibit 5: &lt;span class=&quot;math-container&quot;&gt;$S\rightarrow P$&lt;/span&gt; transition in the Li atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;14903.632061014(5003) cm^-1 (present most accurate experiment)&#xA;14903.631765(0006670) cm^-1 (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Exhibit 6: Ionization energy of the Li atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;43487.15940(18) cm^-1 (present most accurate experiment)&#xA;43487.1590(080) cm^-1 (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Exhibit 7: Ionization energy of the Be atom:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;76192.64(0060) cm^-1 (present most accurate experiment)&#xA;76192.699(007) cm^-1 (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Notice that theory is 1 order of magnitude &lt;em&gt;more accurate&lt;/em&gt; than experiment!!!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Exhibit 8: Atomization energy of the H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;35999.582834(11) cm^-1 (present most accurate experiment)&#xA;35999.582820(26) cm^-1 (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://arxiv.org/pdf/1902.09471.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here for more info&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Exhibit 9: Fundamental vibration of the H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;4161.16632(18) cm^-1 (present most accurate experiment)&#xA;4161.16612(90) cm^-1 (present most accurate theory)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://arxiv.org/pdf/1304.6390.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here for HD and D&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-20T19:37:23.993" LastActivityDate="2021-01-20T19:37:23.993" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="556" PostTypeId="1" AcceptedAnswerId="570" CreationDate="2020-05-13T09:21:19.727" Score="15" ViewCount="191" Body="&lt;p&gt;In molecular dynamics, one typically integrates Newton's equation of motion, for example using a &lt;a href=&quot;https://en.wikipedia.org/wiki/Leapfrog_integration&quot; rel=&quot;noreferrer&quot;&gt;leap-frog algorithm&lt;/a&gt;. Are there chemical systems, for which an analytic integration is a viable alternative? Are there even simulation programs doing this?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2020-05-13T09:34:15.020" LastActivityDate="2020-05-13T16:26:55.373" Title="Can Newton's Equation of Motion be Integrated Analytically for Certain Chemical Systems?" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="557" PostTypeId="2" ParentId="9" CreationDate="2020-05-13T09:22:19.673" Score="20" Body="&lt;p&gt;First I will try to directly answer this question:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;In terms of energy, how are van der Waals forces modelled (are there&#xA;  formulas that govern these)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;The most common way to model the potential energy between two ground state (S-state) atoms that are far apart, is by the London dispersion formula:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V(r) = -\frac{C_6}{r^6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; depends on the dipole polarizabilities (&lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_2$&lt;/span&gt;) of the two atoms. One decent approximation is the Slater-Kirkwood formula:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C_6 \approx \frac{3}{2}\frac{I_1I_2}{I_1+I_2}\alpha_1\alpha_2$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$I_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$I_2$&lt;/span&gt; are the first ionization potentials of the atoms.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However the London dispersion potential is not the only one:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Casimir-Polder potential is used in the relativistic regime, and it's often closer to &lt;span class=&quot;math-container&quot;&gt;$C_7/r^7$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;The resonance dipole-dipole potential: &lt;span class=&quot;math-container&quot;&gt;$C_3/r^3$&lt;/span&gt; used between S-state and P-state atoms&lt;/li&gt;&#xA;&lt;li&gt;If one particle is charged you can get:  &lt;span class=&quot;math-container&quot;&gt;$C_4/r^4$&lt;/span&gt; as in &lt;a href=&quot;https://arxiv.org/pdf/1410.4895.pdf&quot; rel=&quot;noreferrer&quot;&gt;Eq. 2 of this paper of mine&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;In molecular mechanics, how are van der Waals forces modelled?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Most often the &lt;span class=&quot;math-container&quot;&gt;$C_6/r^6$&lt;/span&gt; formula is used, which is reasonable unless dealing with ions, or excited states, or extremely long-range (relativistic) situations. However this formula is for two particles that are very far apart, and we need a force to go the other way when particles are too close to each other, and that is where the 1924 Lennard-Jones potential enters (it has already been written by AloneProgrammer, but in a different way):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V(r) = \frac{C_{12}}{r^{12}}-\frac{C_6}{r^6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;While the &lt;span class=&quot;math-container&quot;&gt;$r^6$&lt;/span&gt; has rigorous theoretical foundations, the &lt;span class=&quot;math-container&quot;&gt;$r^{12}$&lt;/span&gt; does not&lt;/strong&gt;, but in molecular mechanics calculations, this function might need to be evaluated billions of times, so it is convenient that once you've calculated &lt;code&gt;temp=r^6&lt;/code&gt; in your computer program, you can just do &lt;code&gt;temp2=temp*temp&lt;/code&gt; to get &lt;span class=&quot;math-container&quot;&gt;$r^{12}$&lt;/span&gt;. This might sound crazy now, but the earliest computers were so slow that being able to reuse the calculation &lt;span class=&quot;math-container&quot;&gt;$r^6$&lt;/span&gt; in order to take a short cut to calculate &lt;span class=&quot;math-container&quot;&gt;$r^{12}$&lt;/span&gt;, actually made a big difference, and the most high-performance codes, even today, still use this short-cut.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;However, now we have to address the &lt;a href=&quot;https://materials.stackexchange.com/questions/9/in-molecular-mechanics-how-are-van-der-waals-forces-modelled#comment409_9&quot;&gt;comment of Charlie Crown&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;LJ and EXP6 are merely two of the most cliche ways. They are both very&#xA;  simple and easy to use, but neither is all that great. LJ is too steep&#xA;  at close distances and EXP6 is unphysical at small distances&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;This is exactly what I told you: &lt;span class=&quot;math-container&quot;&gt;$C_6/r^6$&lt;/span&gt; is only valid when the atoms are very far apart, and &lt;span class=&quot;math-container&quot;&gt;$C_{12}/r^{12}$&lt;/span&gt; has no physical foundation at all (it is simply convenient since &lt;span class=&quot;math-container&quot;&gt;$(r^6)^2=r^{12}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;AloneProgrammer gave the Morse potential (from 1929) which is actually really good when the atoms are closer together:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V(r) = D_e\left(1 - e^{\beta(r-r_e)}\right)^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt; is the inter-atomic distance at equilibrium, &lt;span class=&quot;math-container&quot;&gt;$D_e$&lt;/span&gt; is the &quot;Depth at equilibrium&quot; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; controls the shape. While this is good at short-range, it is bad at long-range, because if you work out the asymptotic behaviour as &lt;span class=&quot;math-container&quot;&gt;$r\rightarrow \infty$&lt;/span&gt; you will see that it decays exponentially, when in fact we know it should decay with an inverse-power (proportional to &lt;span class=&quot;math-container&quot;&gt;$1/r^6$&lt;/span&gt;), and exponentials behave very differently from inverse-power functions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;The solution is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential&quot; rel=&quot;noreferrer&quot;&gt;Morse/long-range function&lt;/a&gt; or MLR, which was introduced by &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3264688&quot; rel=&quot;noreferrer&quot;&gt;Bob LeRoy and myself in 2009&lt;/a&gt;&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;It looks exactly like the Morse potential when &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is close to &lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt; (when the system is close to equilibrium). But if you calculate the form of the function as &lt;span class=&quot;math-container&quot;&gt;$\lim\limits_{r\rightarrow \infty}$&lt;/span&gt;, you literally get &lt;span class=&quot;math-container&quot;&gt;$V(r) \rightarrow -u(r)$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$u(r)$&lt;/span&gt; can be anything you want: &lt;span class=&quot;math-container&quot;&gt;$C_6/r^6$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_3/r^3$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_4/r^4$&lt;/span&gt;, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Therefore the MLR potential is Morse-like near equilibrium, and LJ-like when far from equilibrium, which is exactly what Charlie Crown said was problematic if you use pure Morse or pure Lennard-Jones.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The MLR potential isn't used in mainstream molecular mechanics calculations, because evaluating the function would be slower than simply using the &lt;span class=&quot;math-container&quot;&gt;$(r^6)^2=r^{12}$&lt;/span&gt; trick (which makes calculations very fast when using the LJ potential). The MLR potential is more accurate though, and solves the problem of the LJ being wrong at equilibrium and the Morse being wrong when far from equilibrium, so it can give more accurate results. Often there's so many approximations going on in molecular mechanics that it doesn't hurt to use the LJ potential which both other answers mentioned already. The MLR tends to be used for high-precision spectroscopy more than for molecular mechanics, but it's an option if one wanted more accurate results.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="35" LastEditDate="2020-05-13T13:58:33.347" LastActivityDate="2020-05-13T13:58:33.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="558" PostTypeId="5" CreationDate="2020-05-13T09:35:55.907" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-13T09:35:55.907" LastActivityDate="2020-05-13T09:35:55.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="559" PostTypeId="4" CreationDate="2020-05-13T09:35:55.907" Score="0" Body="For 1- and 2-electron integrals in electronic structure calculations, before Hartree-Fock or some other type of self-consistent-field calculation, or the integral transformation which is done after HF or SCF." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-13T09:35:55.907" LastActivityDate="2020-05-13T09:35:55.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="560" PostTypeId="1" CreationDate="2020-05-13T11:08:06.130" Score="14" ViewCount="598" Body="&lt;p&gt;I am very interested in doing transport calculation with SIESTA. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My problem is that it is a little hard for me to understand and setup the input files to be used with TranSIESTA (the module that do the transmission and I-V curve simulations).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Do you know any software/server/GUI that can prepare such input? I am thinking in something in the same direction like Virtual NanoLab from the &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumATK&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is an &lt;a href=&quot;https://quantumwise.com/documents/manuals/ATK-12.8/VNLTutorial/index.html/chap.gnr.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt; of how the old Virtual NanoLab works.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note: I am involved in many other projects that demand huge amounts of time dedicated to them. That's why I am looking to speed up some things here.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2020-05-20T16:05:20.493" LastActivityDate="2021-03-22T09:08:00.207" Title="Is there a (free) GUI to setup transport calculations using SIESTA?" Tags="|software|siesta|transport|graphical-user-interface|open-source|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="561" PostTypeId="1" AcceptedAnswerId="974" CreationDate="2020-05-13T12:07:00.550" Score="30" ViewCount="6145" Body="&lt;p&gt;We know that both Quantum ESPRESSO and VASP can perform lots of different kinds of simulations of materials. But what can VASP do that Quantum ESPRESSO can not, and &lt;em&gt;vice-versa&lt;/em&gt;? &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-21T00:45:55.017" LastActivityDate="2020-05-21T12:51:51.280" Title="Quantum ESPRESSO vs VASP" Tags="|vasp|quantum-espresso|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="562" PostTypeId="1" CreationDate="2020-05-13T12:22:43.343" Score="19" ViewCount="469" Body="&lt;p&gt;What are the advantages and disadvantages in using special quasirandom structures (SQS) vs virtual-crystal approximation (VCA) to simulate electronic properties of disordered alloys?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You do not need to named &lt;strong&gt;&lt;em&gt;all&lt;/em&gt;&lt;/strong&gt; advantages and &lt;strong&gt;&lt;em&gt;all&lt;/em&gt;&lt;/strong&gt; disadvantages. Instead you can answer even if you know &lt;strong&gt;&lt;em&gt;one&lt;/em&gt;&lt;/strong&gt; advantage or &lt;strong&gt;&lt;em&gt;one&lt;/em&gt;&lt;/strong&gt; disadvantage of either package.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-15T15:59:18.700" LastActivityDate="2020-08-18T19:31:18.693" Title="Special quasirandom structures vs virtual crystal approach" Tags="|one-topic-per-answer|special-quasirandom-structures|alloys|virtual-crystal-approximation|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="563" PostTypeId="2" ParentId="404" CreationDate="2020-05-13T12:49:42.493" Score="15" Body="&lt;p&gt;Quantum computing has been extensively discussed as long as the first quantum computers have become a reality. As already pointed out, we are still at very early stages of such development. What we need to keep in mind is that a quantum computer needs a quantum computing algorithm. The latter can have few to no correlation with classical algorithms, such as the ones used in density functional theory for materials modeling.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The major advantage of using qubits (quantum bits) and quantum algorithms, against the classical ones, is that they are by essence fully parallelized since we are dealing with entangled states. Also, the sampling space grows with &lt;span class=&quot;math-container&quot;&gt;$2^n$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the number of qubits. That is the key: use the massive power of parallelism to perform tasks a classical (super)computer would suffer to do.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since materials modeling relies on dealing with complex systems with lots of interactions, quantum computing can be thought of as a tool we should take care of. The main obstacles nowadays are the lack of specific algorithms for material modeling. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are some efforts to adapt the classical algorithms, where the time-consuming parts such as the minimization problems are done by the quantum computer, and efforts to create new algorithms from scratch. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://qiskit.org/&quot; rel=&quot;noreferrer&quot;&gt;Qiskit&lt;/a&gt; from IBM is &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;an open-source quantum computing software development framework for leveraging today's quantum processors in research, education, and business.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;One of its components is the &lt;a href=&quot;https://github.com/Qiskit/qiskit-aqua#chemistry&quot; rel=&quot;noreferrer&quot;&gt;Qiskit AQUA&lt;/a&gt;. It is a &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;package contains the core cross-domain algorithms and supporting logic to run these on a quantum backend, whether a real device or simulator.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Aqua includes the Chemistry package, a specific library for quantum chemistry in (IBM's) quantum computers.&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The qiskit.chemistry package supports problems including ground state energy computations, excited states and dipole moments of molecule, both open and closed-shell.&#xA;  The code comprises chemistry drivers, which when provided with a molecular configuration will return one and two-body integrals as well as other data that is efficiently computed classically. This output data from a driver can then be used as input to the chemistry module that contains logic which is able to translate this into a form that is suitable for quantum algorithms. The conversion first creates a FermionicOperator which must then be mapped, e.g. by a Jordan Wigner mapping, to a qubit operator in readiness for the quantum computation.   &lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Therefore, this is still an open question. &lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-05-13T12:49:42.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="564" PostTypeId="2" ParentId="316" CreationDate="2020-05-13T13:20:31.093" Score="9" Body="&lt;p&gt;You should converge each calculation with respect to all the parameters; however, some parameters are relatively transferable between related systems. Let's consider the two main ones in a condensed-phase simulation:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Size of basis set&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Brillouin zone sampling (&quot;k-points&quot;) (Only relevant for periodic systems)&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;The basis set is largely dependent on the external potential (usually meaning the nuclear Coulomb or effective core/pseudopotential). Increasing the size of the basis set means describing shorter-wavelength variations of the wavefunction, and the wavefunction typically has the shortest oscillations near nuclei, where the nuclear potential is strong and changes sharply. However, the nuclear potential is so strong in these regions that the wavefunctions tend to be fairly insensitive to the chemical environment the atoms are in, so this is quite a transferable property between any simulations using the same nuclear potentials. (Note that this isn't quite the case if you also have localised bond-centred basis states, as that obviously depends on the bonding.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In contrast to basis sets, the quality of k-point sampling you need depends on the nature of the bands in the system, so is very sensitive to changes in chemistry, bonding, defects etc. k-point sampling is generally &lt;em&gt;not&lt;/em&gt; transferable between systems, even introducing a single vacancy can change the k-point sampling you need considerably. Since the k-points sample the Brillouin zone, the size of which depends on the real-space simulation cell, the appropriate quantity to consider is the k-point spacing (or, equivalently, k-point sampling density), rather than the number of k-points directly. You need smaller k-point spacing for systems with degenerate states at the Fermi-level (e.g. metals), in order to sample the Fermi surface well. The k-point spacing you need also interacts with any Fermi-level broadening you are using; the greater the Fermi-level broadening, the smoother the Fermi surface and so you can use a larger k-point spacing (i.e. fewer k-points).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For PAW and ultrasoft pseudopotentials there is often an auxiliary grid used to represent the hard &quot;augmentation&quot; charge, and this also should be converged. This is very similar to the basis set size, in that it is a property of the pseudopotential and transfers well to other systems with the same pseudopotentials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Finally, beware of relying on total energy as your sole property of interest when converging. Different chemical and materials properties can have very different convergence rates. Typically forces and stresses are more sensitive than total energies, and vibrational properties are even more sensitive, as are NMR chemical shifts. When converging with respect to basis set size, k-points etc. you should always focus on the property you're actually interested in or a reasonable proxy.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-05-13T13:20:31.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="565" PostTypeId="2" ParentId="560" CreationDate="2020-05-13T13:56:53.133" Score="14" Body="&lt;p&gt;They do not have an easy interface, however, there are some tutorials and examples that can be used, you can use as an input parameter:  &lt;a href=&quot;https://github.com/siesta-project/tutorials&quot; rel=&quot;noreferrer&quot;&gt;github.com/siesta-project/tutorials&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The input file is in .fdf, you can try to generate only the structure through nanolab&gt; 2015 with commercial or academic version.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But the calculator will always be set manually, with the flags themselves.&lt;/p&gt;&#xA;" OwnerUserId="404" LastEditorUserId="49" LastEditDate="2020-05-15T17:04:40.647" LastActivityDate="2020-05-15T17:04:40.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="567" PostTypeId="2" ParentId="360" CreationDate="2020-05-13T14:12:39.657" Score="12" Body="&lt;p&gt;The short answer is &quot;yes&quot; you should check, however this is not as arduous as it might appear at first. Your initial convergence calculations will be fairly exhaustive, sweeping over a large range of basis set size, Brillouin zone sampling etc. but when you change exchange-correlation functional you only need to check that your previously determined parameters were sufficient.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As an example, if I were to use a plane-wave pseudopotential DFT program I might start with LDA and converge the plane-wave cut-off by looking at cut-off energies of 300 eV, 400 eV, 500 eV... 1200 eV, and perhaps decide to use 600 eV. If I then change to PBE, I would start at 600 eV and check that this is reasonable by either comparing dE_total/dlog(E_cutoff) with the LDA one, or looking at 700 eV and perhaps 800 eV (comparing the trend to the corresponding trend with LDA). This is much quicker and easier than the original convergence check, since we know roughly what we expect the answer to be and how everything should vary.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The natural follow-on question is &lt;em&gt;why&lt;/em&gt; the convergence might depend on the choice of exchange-correlation functional. The principal answer to this is the self-interaction error: the Hartree term in the Kohn-Sham equations is the Coulomb repulsion between the  electron density at a point and the electron density at another point, but at each of these points some of this electron density was due to the same particle, which means that a particle repels itself! This is called self-interaction, and is completely incorrect. The &quot;true&quot; exchange-correlation functional would remove this spurious self-interaction but, since we don't have this wondrous functional at present, we must make do with approximations to it. These approximations vary considerably as to how much they mitigate the effect of self-interaction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If we focus on the two main considerations of basis set size and Brillouin zone/k-point sampling (for periodic systems) then we can see what difference we expect from the self-interaction error.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The appropriate basis set size usually depends primarily on the states near the nuclei. A large self-interaction leads to spurious delocalisation of states with high electron density, particularly &quot;shallow core&quot; states such as atomic d- and f-states. This can change the size of basis needed to describe the states accurately. If you are using pseudopotentials, then there is an additional effect: when you change the functional you also change the pseudopotential, and this may require more basis sets. This is particularly true in my experience if you're using functionals with some Fock exchange, as the pseudopotential generation in this case is rather difficult and the resultant potentials tend to be rather hard.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Brillouin zone sampling depends on the bonding in your system so you may not expect this to be strongly dependent on the exchange-correlation functional, but this is not always true. One of the clearest examples might be transition metal oxides, e.g. NiO, which is strongly affected by the self-interaction error in the Ni d-states. LDA predicts that NiO is a non-magnetic metal (due to self-interaction error), so an exhaustive convergence check would conclude you need a high k-point sampling, but do not need to worry about spin (collinear or non-collinear); however, changing to PBE removes just enough of the self-interaction to open up a small band gap and make NiO an antiferromagnetic insulator, meaning that you do not need as high a k-point sampling but you do need to consider the spin density (at least at the collinear level). The antiferromagnetic insulating state would also be obtained with a modest Hubbard U, even with LDA, on the Ni d-states, and/or a proportion of Fock or screened-Fock exchange (which removes this self-interaction directly).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-05-13T14:12:39.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="568" PostTypeId="1" CreationDate="2020-05-13T14:27:53.853" Score="16" ViewCount="474" Body="&lt;p&gt;When designing molecules or materials (as drug carriers) in drug design, one important properties is the system solubility.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are there any software that using ab intio/DFT methods can be used to simulate molecular solubility?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-13T16:48:06.107" LastActivityDate="2020-05-17T20:11:37.257" Title="Are there any ab intio/DFT methods to simulate solubility?" Tags="|density-functional-theory|ab-initio-calculations|solubility|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="569" PostTypeId="2" ParentId="174" CreationDate="2020-05-13T15:08:46.710" Score="10" Body="&lt;p&gt;The Born-Oppenheimer approximation comprises two different approximations:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Adiabatic separation of electron and nuclear coordinates&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Semi-classical approximation for nuclei&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Previous answers have already addressed (1). I would also like to add that although it neglects electron-phonon coupling, this can be added back in using density functional perturbation theory (DFPT).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The semi-classical approximation (2) can also cause some issues, particularly for light nuclei where quantum delocalisation, zero-point energy etc. are an issue. These quantum effects can be added back, for example using path-integral dynamics (esp. suitable for bosons), DFPT or vibrational SCF, or the light nuclei can be treated in an explicit quantum mechanical treatment (e.g. the double adiabatic separation). As well as systems with light nuclei, there are also experimental techniques where these issues are vital, e.g. muon spectroscopy, where the muons can be treated as very low-mass nuclei.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-05-13T15:08:46.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="570" PostTypeId="2" ParentId="556" CreationDate="2020-05-13T16:26:55.373" Score="12" Body="&lt;p&gt;Analytic integration is only possible for the &lt;strong&gt;simplest potentials&lt;/strong&gt; (a lot of them are covered in the introductory quantum mechanics course). Thus, this is only possible if the model for the process is simple enough that the &lt;strong&gt;motion decouples&lt;/strong&gt; into a series of uncoupled harmonic oscillators, rigid rotors, spins and central potentials. As you can imagine, this is not at all a typical situation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If this happens, however, no simulation program is needed as the dynamics is analytic.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As an aside: it is fairly common to &lt;strong&gt;decompose the dynamics into parts&lt;/strong&gt;, that can be solved analytically and then obtain numerically exact answers to parts of your dynamics (e.g. the leap-frog algorithm you cited is an example of that with the free particle sub-step being obtained exactly - of course the error is then buried in the Trotter splitting). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The examples that come to mind from my personal experience are the ring-polymer molecular dynamics (&lt;strong&gt;RPMD&lt;/strong&gt;) simulations, where the free ring-polymer evolution sub-step is a collection of uncoupled harmonic oscillators, that can be integrated analytically. &lt;a href=&quot;http://aip.scitation.org/doi/10.1063/1.3489925&quot; rel=&quot;noreferrer&quot;&gt;The algorithm is well-described in section IIB of this paper.&lt;/a&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Shameless self-advertising: It turns out that this is a good, but not the best way to do it. Instead, one should &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5120282&quot; rel=&quot;noreferrer&quot;&gt;integrate the approximation of the free ring-polymer dynamics exactly&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="349" LastActivityDate="2020-05-13T16:26:55.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="571" PostTypeId="2" ParentId="560" CreationDate="2020-05-13T16:37:51.523" Score="13" Body="&lt;p&gt;This is not the exact response to your question, but I would like to present a very good youtube channel &lt;a href=&quot;https://www.youtube.com/channel/UCgQPek4ZSo_yL7wEjIhxvfA&quot; rel=&quot;noreferrer&quot;&gt;QuantumNerd&lt;/a&gt;. Its content is vast and interesting, concerning materials simulation. Recently, he posted a &lt;a href=&quot;https://www.youtube.com/watch?v=S2e1TWx6DHs&quot; rel=&quot;noreferrer&quot;&gt;video&lt;/a&gt; about a project of making multi-platform GUI for Quantum ESPRESSO, he mentioned though the possibility of growing the project to other DFT engines. &lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-05-13T16:37:51.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="572" PostTypeId="2" ParentId="548" CreationDate="2020-05-13T17:17:31.860" Score="3" Body="&lt;p&gt;I really don't think that I have to be convinced in any conceptual/philosophical way.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As we are dealing with Science, and in this particular case, Exact Science, whenever the method reproduce the experimental properties, it is good enough. If also, it is capable to predict the properties/existence of new materials, is better. As soon as it fails (like &quot;old&quot; functionals used to simulate the interaction of graphene sheets), new methods (in this case, new functionals) are developed.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-13T17:17:31.860" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="573" PostTypeId="1" CreationDate="2020-05-13T18:16:56.727" Score="11" ViewCount="60" Body="&lt;p&gt;When a material forms a crack (say, for example, a disk that is getting old, or a fresh bread where force is applied to), on the microscopic/atomic level, atomic bonds break and forces are overcome. What computational methods are there to simulate such behaviour?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2020-05-13T21:58:26.523" LastActivityDate="2020-05-13T22:55:32.360" Title="What methods are there to simulate microscopic cracking of materials?" Tags="|reference-request|macroscopic-materials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="574" PostTypeId="2" ParentId="532" CreationDate="2020-05-13T18:34:50.977" Score="16" Body="&lt;p&gt;I would like to expand on Roman Korol's answer a bit. He already lists GTO's and plane waves as they are the most common kind of basis functions. These are characteristic for the underlying models by which they are motivated.&#xA;GTO's approximate the solutions to the hydrogen atom and are thus atom centered functions used for molecules. Plane waves on the other hand derive from the (nearly) free electron gas in a lattice and as such are suited for periodic systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are, however, some lesser used types of basis functions.&#xA;The ADF suite uses Slater type orbitals. While the idea of GTOs and STOs is of course similar, I would list them separately as their treatment in the code is quite different and, supposedly, they yield more accurate results. The reason GTOs are more commonly used is that for Gaussians you can exploit the Gaussian product theorem to evaluate the molecular integrals. It states (roughly) that the product of two Gaussians is another Gaussian centered between the two original ones. This can be used to get closed expressions for the integrals and calculating them becomes a matter of using recurrence relations. STOs are less convenient and the integrals have to be computed numerically.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The other type of basis functions I have seen are wavelets. These functions strike a balance between localization in real space (like GTOs) and in momentum space (like plane waves). They are used in the BigDFT program, but I am not very familiar with their properties.&lt;/p&gt;&#xA;" OwnerUserId="406" LastEditorUserId="35" LastEditDate="2020-05-13T18:48:45.967" LastActivityDate="2020-05-13T18:48:45.967" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="575" PostTypeId="2" ParentId="414" CreationDate="2020-05-13T19:43:12.680" Score="8" Body="&lt;h2&gt;Columbus&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.univie.ac.at/columbus/&quot; rel=&quot;noreferrer&quot;&gt;Columbus&lt;/a&gt; is an alternative package for CASSCF and other multireference methods. There is a free and open-source distribution. It is a bit old fashioned but still widely used.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Newest Reference&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;H. Lischka, R. Shepard, T. Müller, P. G. Szalay, R. M. Pitzer, A. J. A. Aquino, M. M. A. do Nascimento, M. Barbatti, L. T. Belcher, J.-P. Blaudeau, et al., J. Chem. Phys. 2020, 152, 134110. DOI: &lt;a href=&quot;https://dx.doi.org/10.1063/1.5144267&quot; rel=&quot;noreferrer&quot;&gt;10.1063/1.5144267&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="115" LastEditorUserId="5" LastEditDate="2020-09-08T16:34:57.773" LastActivityDate="2020-09-08T16:34:57.773" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="576" PostTypeId="1" CreationDate="2020-05-13T20:09:17.297" Score="19" ViewCount="131" Body="&lt;p&gt;I am working on adding a charge polarization model into my own research and have been exploring a few approaches. One of the most attractive options is the Bond Capacity (&lt;em&gt;BC herein&lt;/em&gt;) model of Paolo and Jensen (&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.8b01215&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jctc.8b01215&lt;/a&gt;). Alas, there is no example implementation available and though it has been added to Tinker-HP (&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00721&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jctc.9b00721&lt;/a&gt;) the version that might contain it has yet to see a release. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have been prototyping my own implementation, but I have ran into some roadblocks when trying to reproduce results in the paper. The primary issue is a lack of information regarding the model's parameterization and handling of integrals. I understand the questions are narrow, but I'm taking a shot in the dark and looking for any valuable insights. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I will briefly highlight the purpose and key equations to save you from reading the paper. I should note, the BC model was designed to describe molecular polarization and polarizabilities using fluctuating charges. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now for the equations. I am going to presume we are working with a neutral system of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms acting under the influence of an external electric field &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;. In the BC model, the electrostatic potential for atom &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$V_i$&lt;/span&gt;, is the sum of the intrinsic potential of atomic electronegativity (&lt;span class=&quot;math-container&quot;&gt;$\chi_i$&lt;/span&gt;), the cumulative external potential of neighboring atoms (&lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt;), and the potential due to the external field (&lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt;). The amount of charge that is transferred between a pair of atoms &lt;span class=&quot;math-container&quot;&gt;$p_{ij}$&lt;/span&gt; is taken to be proportional to a pair capacity &lt;span class=&quot;math-container&quot;&gt;$\xi_{ij}$&lt;/span&gt; and the difference in electrostatic potential for the atoms: &lt;span class=&quot;math-container&quot;&gt;$$p_{ij} = \xi_{ij}(V_i - V_j) \\ p_{ij} = \xi_{ij}\left[(\chi_i+\phi_i+\psi_i)-(\chi_j+\phi_j+\psi_j)\right]$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This pair capacity parameter is geometry dependent and is defined as: &lt;span class=&quot;math-container&quot;&gt;$$\xi_{ij}(R_{ij}) = \xi_{ij}^{0} g(R_{ij}) = \xi_{ij}^{0} \left(\frac{1-S_{ij}}{R_{ij}}\right)$$&lt;/span&gt; Where &lt;span class=&quot;math-container&quot;&gt;$\xi_{ij}^{0}$&lt;/span&gt; is pair capacity at equilibrium geometry and &lt;span class=&quot;math-container&quot;&gt;$g(R_{ij})$&lt;/span&gt; is an attenuation function that is one at equilibrium and decays to zero as inter atomic distance grows. &lt;strong&gt;This&lt;/strong&gt; is where my first two questions come in. In the paper, they choose the overlap between Slater orbitals (&lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt;) as part of the attenuation function.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;By chance, does anyone have any idea if they are using STOs with angular momenta greater than &lt;span class=&quot;math-container&quot;&gt;$l=0$&lt;/span&gt; to evaluate the overlap of atoms?&lt;/strong&gt; &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In similar models, only one s Slater type orbital is used per atom. I presume the same in my implementation and evaluate the overlap using equations (5) and (6) from (&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/epdf/10.1002/qua.560210612&quot; rel=&quot;noreferrer&quot;&gt;DOI:10.1002/qua.560210612&lt;/a&gt;). Though, this form is not analytically derived. &lt;strong&gt;Does anyone have a reference that gives an exact form for the two-centered overlap of S-type slater orbitals?&lt;/strong&gt;    &lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Okay moving forward, the total charge on any atom &lt;span class=&quot;math-container&quot;&gt;$Q_i$&lt;/span&gt; due to the aforementioned electrostatic potential components can be determined via, &lt;span class=&quot;math-container&quot;&gt;$$Q_i = \sum_j^N -\xi_{ij}(V_i - V_j)$$&lt;/span&gt; thus the charge on every atom in the system can summarized in the matrix form, &lt;span class=&quot;math-container&quot;&gt;$$\textbf{Q}=-\textbf{CV}$$&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\textbf{C}$&lt;/span&gt; is symmetric (&lt;span class=&quot;math-container&quot;&gt;$\xi_{ij}=\xi_{ji}$&lt;/span&gt;) and contains negative pair capacities of atoms on the off-diagonal and the diagonal is a sum of these pair capacities in the corresponding column or row, &lt;span class=&quot;math-container&quot;&gt;$\xi_{ii} = \sum_{k\neq j}^N \xi_{ik}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\textbf{V}$&lt;/span&gt; is a vector of the atomic electrostatic potentials defined above.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The components of &lt;span class=&quot;math-container&quot;&gt;$\textbf{V}$&lt;/span&gt; should be defined briefly. To determine the polarization potential of atom &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; due to its neighbors, &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt;, you must evaluate a Coulomb interaction, (&lt;span class=&quot;math-container&quot;&gt;$J_{ik}$&lt;/span&gt;), with a similar form to &lt;span class=&quot;math-container&quot;&gt;$\xi_{ij}(R_{ij})$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$$\phi_{i}=\sum_{k=1}^{N} J_{ik} Q_{k}=\sum_{k \neq i}^{N} \frac{1-S_{i k}}{R_{ik}} Q_{k}+J_{ii} Q_{i} \\ \boldsymbol{\phi = JQ}$$&lt;/span&gt;&#xA;Where again the overlap between Slater orbitals (&lt;span class=&quot;math-container&quot;&gt;$S_{ik}$&lt;/span&gt;) attenuation function is applied. Meanwhile, the intrinsic potential of atomic electronegativity, &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\chi}$&lt;/span&gt;, is taken to be a vector of free parameters. The potential due to the external electric field has it's usual definition &#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi_i = \sum_{\sigma=x,y,z}R_{i \sigma}F_{\sigma} \\ \boldsymbol{\psi = R^TF}$$&lt;/span&gt; &#xA;where &lt;span class=&quot;math-container&quot;&gt;$\textbf{R}$&lt;/span&gt; is a (N,3) matrix of atomic positions and &lt;span class=&quot;math-container&quot;&gt;$\textbf{F}$&lt;/span&gt; is the electric field vector. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Combining the above equations and performing some rearrangements allows one to define the 3x3 molecular polarizability tensor as, &lt;span class=&quot;math-container&quot;&gt;$$\boldsymbol{\alpha = R^T\left( I + CJ \right)^{-1}CR}$$&lt;/span&gt; where all &lt;span class=&quot;math-container&quot;&gt;$\textbf{I}$&lt;/span&gt; is the identity matrix and all other terms have been defined above. This brings me to my final question:&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;The authors are using an, &quot;in house,&quot; code to perform the fitting of their parameters to reproduce ab initio polarizabilities. I have no way of knowing what routines they are using. &lt;strong&gt;I am trying to determine what STO exponential constants &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; and electronegativities &lt;span class=&quot;math-container&quot;&gt;$\chi_i$&lt;/span&gt; were used to attain their results. I am currently using scipy's &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.least_squares.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;least_squares&lt;/code&gt;&lt;/a&gt; to optimize these parameters via minimizing the residuals between the components of my polarizability matrix and theirs (iteratively of course). I am not a statistician nor a fitting expert. Since this is just a system of equations, does anyone know of a better way of fitting the parameters to ab initio data in python or C++?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I apologize for the long winded post, but these details have been vexing for a while now and I'm getting tired of perusing Google for answers. If you made it this far, thanks for reading.&lt;/p&gt;&#xA;" OwnerUserId="346" LastEditorUserId="5" LastEditDate="2020-05-15T17:38:40.360" LastActivityDate="2020-05-15T17:38:40.360" Title="How is Poier and Jensen's Bond Capacity Model Parameterized and Optimized?" Tags="|quantum-mechanics|charge-transfer|charge-polarization-model|polarizability|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="577" PostTypeId="2" ParentId="573" CreationDate="2020-05-13T21:19:59.387" Score="8" Body="&lt;p&gt;The package &lt;a href=&quot;https://lammps.sandia.gov/index.html&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt;, that implements Molecular Dynamics, has an example of a crack propagating in a 2D solid. &lt;a href=&quot;https://lammps.sandia.gov/inputs/in.crack.txt&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is the input they used. A complete mpeg video of the result can be downloaded by clicking &lt;a href=&quot;https://lammps.sandia.gov/movies/crack.mpg&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, which shows the crack propagation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hcD3d.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hcD3d.gif&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="52" LastEditDate="2020-05-13T22:55:32.360" LastActivityDate="2020-05-13T22:55:32.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="578" PostTypeId="2" ParentId="70" CreationDate="2020-05-14T01:27:05.217" Score="27" Body="&lt;p&gt;There are many reasons why we have so many different density functional theory programs, and it would be nigh on impossible to give a full answer encompassing all of them. A brief, select few:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Scientific reasons, because you need something that can handle some very specific physics or chemistry accurately and efficiently. At a simple level it might be that a particular basis set is most appropriate for the task you want, but there are many other considerations. You might want to treat solvation as an integral part of the problem (e.g. &lt;a href=&quot;http://jdftx.org/1.3.0/&quot; rel=&quot;noreferrer&quot;&gt;JDFTx&lt;/a&gt;), or not use the Born-Oppenheimer approximation etc.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Technical reasons, for example you really need methods which are efficient on some very particular hardware (e.g. with extreme parallelism, or accelerators, or very long vector machines), or are written in a particular language in order to integrate with some other software or workflow.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Philosophical design reasons. Perhaps you want a single program which can do all the kinds of calculations you want, or perhaps you prefer a suite of smaller, more specialised programs. Maybe you want something you can rapidly prototype new methods in and don't care about performance or features.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Personal reasons. Perhaps you want some software to your name to enhance your career, or perhaps you fell out with the authors of the &quot;usual&quot; choice (or vice versa). Perhaps your intended use of the software isn't compatible with the licence of the usual programs, e.g. because you're doing research which is commercial or classified. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Inertia. Now that we have all of these different programs, what is the incentive for developer communities to merge and settle on one particular software and approach? &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Pedagogical reasons, for example someone wants to really understand how the theory and algorithms work. Many of my own PhD students write their own density functional theory program for this reason, though these are not used for real applications.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It isn't very hard! Writing a very basic, full-potential, all-electron density functional theory program is relatively straightforward. It will not be fast or scalable, nor will it compute very much -- probably just the ground state energy, density and Kohn-Sham states -- but it will work.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Finally, I'd like to note that having several implementations, even when they make the same major design choices (e.g. basis set; wavefunction or Green's function approaches), gives some competition, and this can be healthy. The &lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;noreferrer&quot;&gt;Science paper&lt;/a&gt; referenced in the question demonstrates the benefit of this: the good agreement between the programs has not always been there, indeed it is partly due to the work behind this paper that the programs do agree so well; when we found an outlier in our tests, we worked hard to understand why and fix any issues. Reproducibility is a serious issue in research, and the ability to apply two (or more) completely independent implementations of the theory to a scientific problem is extremely valuable.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another benefit of competition is that developers don't generally like it when a different program can do something theirs can't, or is faster, or scales better or... so competition can lead to improvements for everyone.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So in summary: there are lots of reasons why people write their own programs. Having a variety of design choices is good, but even having several implementations with similar design choices is healthy. Are there &quot;too many&quot; implementations? Possibly, but the &quot;ideal&quot; number of implementations is more than one or two.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-05-14T01:27:05.217" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="579" PostTypeId="5" CreationDate="2020-05-14T03:15:25.783" Score="0" Body="" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-05-14T03:15:25.783" LastActivityDate="2020-05-14T03:15:25.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="580" PostTypeId="4" CreationDate="2020-05-14T03:15:25.783" Score="0" Body="For questions regarding Graphical User Interfaces used in matter modeling" OwnerUserId="88" LastEditorUserId="7" LastEditDate="2020-06-26T21:49:57.967" LastActivityDate="2020-06-26T21:49:57.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="581" PostTypeId="2" ParentId="404" CreationDate="2020-05-14T03:30:31.377" Score="13" Body="&lt;p&gt;Quantum computers potentially could provide a far more efficient way to solve the electronic structure problem: finding the ground state energy (or other properties) of electrons in a compound.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The most prominent quantum algorithms for this purpose are the Phase Estimation Algorithm (PEA) and the Variational Quantum Eigensolver (VQE). While PEA offers the potential for dramatic speedups over classical methods, it requires very high fidelity qubits. VQE in contrast is more tolerant of device error.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Recent advances in superconducting and ion-trap quantum computers have allowed for the experimental realization of both of these algorithms by &lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.031007&quot; rel=&quot;noreferrer&quot;&gt;Google&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1805.04492&quot; rel=&quot;noreferrer&quot;&gt;IBM&lt;/a&gt;, &lt;a href=&quot;https://www.nature.com/articles/s41534-020-0259-3&quot; rel=&quot;noreferrer&quot;&gt;IonQ&lt;/a&gt;, and others using Noisy Intermediate-Scale Quantum (NISQ) devices. (However these experiments have been limited to simulations of small molecules and small active spaces.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note that both VQE and PEA are wavefunction approaches in the sense that the quantum computer is used to prepare a state that corresponds to the state of the electrons in the compound. For more details, I would recommend the review article &lt;a href=&quot;https://arxiv.org/abs/1812.09976&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Quantum Chemistry in the Age of Quantum Computing&lt;/em&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Additionally, there are potential applications for quantum computers in materials modeling besides electronic structure simulation. For example, some quantum algorithms may accelerate the &lt;a href=&quot;https://royalsocietypublishing.org/doi/full/10.1098/rspa.2015.0301&quot; rel=&quot;noreferrer&quot;&gt;computation of thermodynamic properties of classical lattice Hamiltonians&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="408" LastActivityDate="2020-05-14T03:30:31.377" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="582" PostTypeId="2" ParentId="548" CreationDate="2020-05-14T04:13:15.590" Score="13" Body="&lt;p&gt;It's completely legitimate to want a physical intuition for something that is proved mathematically. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;One &lt;strong&gt;very&lt;/strong&gt; hand-wavy argument is just to say that the electron density in the ground state has to reflect the effects of all of those electron-electron correlations, interactions, exchange. After all, the electron density definitely depends on the interactions between electrons, but that doesn't mean we need to know all the details of how the electrons are actually interacting. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are often macroscopic/thermodynamic quantities that include the effects of all sorts of more complicated microscopic interactions. For example, the Young's modulus of a solid allows us to accurately predict the stress/strain relationship without having to know anything about the microscopic rules that cause the Young's modulus to take it's specific value. the Another example would be an effective electron mass in solid state physics. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-14T04:13:15.590" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="583" PostTypeId="2" ParentId="576" CreationDate="2020-05-14T07:48:42.980" Score="15" Body="&lt;p&gt;The specific questions:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Only &lt;span class=&quot;math-container&quot;&gt;$l = 0$&lt;/span&gt; overlaps are (currently) considered, in the spirit of atoms being represented by (only) a spherical charge distribution (point charges).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The overlap/attenuation function for the bond capacities is very (!) preliminary. It should be designed to reflect the actual physics, and this is work in progress. However, any reasonable function that models how the bonding decays as a function of distance should at least give a fair model. The same holds for the Coulomb screening function. In the paper, it was taken to be the same as the screening function for the bond capacity, but one could (and should) considered these to have different functional forms. We opted for the simple solution of using the overlap calculated using the s-functions of the STO-3G basis set. This involves only overlap of s-type Gaussian functions which is trivial to calculate.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;We used a Newton-Raphson optimizer with numerical gradients, a piece of code that had been developed for another purpose, and could easily be modified to do the job. We assigned the bond capacities from calculated polarizabilities, and then fitted the electronegativity parameters to give the desired atomic charges. One also need to assign the atomic Coulomb self-interaction (aka hardness) parameters to give the desired polarization response.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;As inferred from the above, the parameterization of the BC model is currently very rudimentary, and there is certainly room for refinements, but it does have some fundamental features that look attractive.&lt;/p&gt;&#xA;" OwnerUserId="279" LastEditorUserId="49" LastEditDate="2020-05-15T17:26:49.400" LastActivityDate="2020-05-15T17:26:49.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="584" PostTypeId="1" CreationDate="2020-05-14T11:33:28.210" Score="19" ViewCount="391" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;There is an ever-growing list of freeware and open-source software for solid-state physics and quantum chemistry&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;But many commercial programs still thrive, even in 2020, and their cost can be in the thousands of pounds/dollars. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am curious to know what mainstream calculations still cannot be done for free? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For each answer, please list one method that is implemented in commercial software but not any freeware, and a reference to a paper that used this commercial method, where the authors of the paper are not involved in any way with the commercial software.&lt;/p&gt;&#xA;" OwnerUserId="412" LastEditorUserId="5" LastEditDate="2020-05-16T02:22:15.190" LastActivityDate="2020-05-21T11:41:57.617" Title="What significant matter modelling methods are implemented in commercial software, for which there is no freeware alternative?" Tags="|software|condensed-matter|quantum-chemistry|molpro|q-chem|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="585" PostTypeId="2" ParentId="532" CreationDate="2020-05-14T15:46:23.230" Score="13" Body="&lt;p&gt;Another slightly less commonly seen basis are the &lt;a href=&quot;https://en.wikipedia.org/wiki/Sinc_function&quot; rel=&quot;noreferrer&quot;&gt;sinc functions&lt;/a&gt;, which are related to plane waves, but come at the problem from the perspective of a position, rather than momentum, space. They are delocalized functions, but sharply peaked at their center point and zero valued at the centers of other sinc functions, effectively partitioning space into a grid.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These have seen use in the Discrete Variable Representation method [&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.462100&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;], which has the potential energy matrix elements being defined only at grid points and kinetic energy elements being defined by an infinite order finite difference for the second derivative.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Sinc functions have been mixed with localized functions like Gaussians [&lt;a href=&quot;https://doi.org/10.1063/1.4928577&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;] to try to combine the best parts, similar to the wavelets mentioned in Fuzzy's answer. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the ONETEP program [&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1839852&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;], periodic sinc functions are used as a basis to form nonorthogonal generalized Wannier functions (NGWFs), which are in turn optimized over a localization sphere during the calculation. The localization of these NGWFs allows for linear scaling DFT calculations, as it makes apparent the exponential decay of the density matrix.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;D. T. Colbert and W. H. Miller J. Chem. Phys. 96 (3), 1992 DOI: 10.1063/1.462100&lt;/li&gt;&#xA;&lt;li&gt;Jonathan L. Jerke, Young Lee, and C. J. Tymczak J. Chem. Phys. 143, 064108 (2015); DOI: 10.1063/1.4928577&lt;/li&gt;&#xA;&lt;li&gt;Chris-Kriton Skylaris, Peter D. Haynes, Arash A. Mostofi, and Mike C. Payne J. Chem. Phys. 122, 084119 (2005); DOI: 10.1063/1.1839852&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-05-14T15:46:23.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="586" PostTypeId="5" CreationDate="2020-05-14T16:33:59.887" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:33:59.887" LastActivityDate="2020-05-14T16:33:59.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="587" PostTypeId="4" CreationDate="2020-05-14T16:33:59.887" Score="0" Body="For questions related to the use of materials model in drug design. Examples include simulations of docking, ligand binding, and molecular dynamics of biological species." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:33:59.887" LastActivityDate="2020-05-14T16:33:59.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="588" PostTypeId="5" CreationDate="2020-05-14T16:37:02.323" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:37:02.323" LastActivityDate="2020-05-14T16:37:02.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="589" PostTypeId="4" CreationDate="2020-05-14T16:37:02.323" Score="0" Body="For questions about modeling material defects (e.g. vacancies, interstitial/substitutional impurities, topological defects)." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:37:02.323" LastActivityDate="2020-05-14T16:37:02.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="590" PostTypeId="5" CreationDate="2020-05-14T16:41:38.260" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:41:38.260" LastActivityDate="2020-05-14T16:41:38.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="591" PostTypeId="4" CreationDate="2020-05-14T16:41:38.260" Score="0" Body="For questions about how quantum computing algorithms/technology can be applied to problems of materials modeling." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:41:38.260" LastActivityDate="2020-05-14T16:41:38.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="592" PostTypeId="5" CreationDate="2020-05-14T16:43:56.413" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:43:56.413" LastActivityDate="2020-05-14T16:43:56.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="593" PostTypeId="4" CreationDate="2020-05-14T16:43:56.413" Score="0" Body="For questions about modeling topological insulators (materials which are insulating in the bulk, but have conductive surface states due to specific topology of their band structure)." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:43:56.413" LastActivityDate="2020-05-14T16:43:56.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="594" PostTypeId="5" CreationDate="2020-05-14T16:51:55.993" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:51:55.993" LastActivityDate="2020-05-14T16:51:55.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="595" PostTypeId="4" CreationDate="2020-05-14T16:51:55.993" Score="0" Body="For questions related to Response Theory, the behavior of materials in response to external stimuli. Linear response and sum-over-states approaches to computing polarizabilities/spectroscopic observables." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-14T16:51:55.993" LastActivityDate="2020-05-14T16:51:55.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="596" PostTypeId="2" ParentId="372" CreationDate="2020-05-14T19:03:11.763" Score="10" Body="&lt;p&gt;The question highlights the difficulty in calculating an &lt;em&gt;ab initio&lt;/em&gt; value for &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; for a molecule like &lt;span class=&quot;math-container&quot;&gt;$\textrm{Fe(Phen)}_2\textrm{(SCN)}_2$&lt;/span&gt;, and specifically the fact that a highly cited 2018 paper predicts values that are between 60K and 278K higher than the experimental value of 176.5K.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The paper highlights a major danger of using DFT, and in using theory to try to predict something that is out of reach with today's computing technology and algorithms.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The paper uses many approximations to calculate &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; for a molecule. They begin with the approximation that it can be calculated as follows:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}T_{1/2} &amp;amp;= \frac{\Delta H}{\Delta S} \\  &amp;amp;\approx  \frac{\Delta E_\textrm{electronic}+\Delta E_\textrm{vibrational}}{\Delta S},&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where only &lt;span class=&quot;math-container&quot;&gt;$\Delta E_\textrm{electronic}$&lt;/span&gt; is attempted accurately because they claim near their Eq. 3 that &quot;the harmonic approximation&quot; is good enough for &lt;span class=&quot;math-container&quot;&gt;$\Delta E_\textrm{vibrational}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Delta S$&lt;/span&gt; (see their Eq. 8 for more details). In general if you want to calculate &lt;span class=&quot;math-container&quot;&gt;$\Delta S$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt; &lt;em&gt;ab initio&lt;/em&gt;, resources that might help you are  &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp981195o&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; for &lt;span class=&quot;math-container&quot;&gt;$\Delta S$&lt;/span&gt;, and &lt;a href=&quot;https://cccbdb.nist.gov/enthformation.asp&quot; rel=&quot;noreferrer&quot;&gt;this step-by-step guide&lt;/a&gt; for &lt;span class=&quot;math-container&quot;&gt;$\Delta S$&lt;/span&gt;, but as the authors claim that the harmonic approximation is good enough for everything except &lt;span class=&quot;math-container&quot;&gt;$\Delta E_\textrm{electronic}$&lt;/span&gt;, let's zoom into how &lt;span class=&quot;math-container&quot;&gt;$\Delta E_\textrm{electronic}$&lt;/span&gt; is calculated.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The system mentioned in the question is labelled S11 in the table below, and you can see that with 8 different functionals, values for the HS vs LS energy gap vary from -14.6 to +9.6 kcal/mol (&lt;strong&gt;&lt;em&gt;a 25 kcal/mol range for a number estimated to be at most 15 kcal/mol in magnitude&lt;/em&gt;&lt;/strong&gt;), with only 3 out of 8 functionals even giving the correct sign. For reference, the term &quot;chemical accuracy&quot; means an accuracy of +/- 1 kcal/mol. As someone who mainly works in the &quot;high-precision &lt;em&gt;ab initio&lt;/em&gt;&quot; field, I would stop right here and start working on a different project, however the brave scientists noticed that the TPSSh functional predicted the sign correctly for all 20 systems:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yPooM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yPooM.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I lack experience with DFT, so I personally would try to develop more experience to decide how significant it is to me that one functional is getting all the signs correctly (I think I personally would try more functionals until I find another one that gets all signs correctly, and then compare the magnitudes, since what i see in the table indicates that the magnitudes vary wildly from what people call &quot;chemical precision&quot;). However the authors have more experience with DFT than me, and they have decided to use the TPSSh functional for the rest of their calculations. The &lt;span class=&quot;math-container&quot;&gt;$\Delta E_\textrm{electronic}$&lt;/span&gt; could have been 1/3 of what it was for TPSSh if they used B3LYP* instead, and could have been the opposite sign and almost 2x larger in magnitude if they used M06 (which I understand is reputed to be good for transition-metal containing systems like the system in question), so you can see that we can get a very wide range of &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; values if we wish.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;After deciding that the TPSSh functional was the only one that got the signs correctly for all 20 systems studied in the above table, they increased the size of the basis set from what they call BS1 to what they call BS2.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Your question notes that there is a 217K difference between the result obtained with BS2 vs BS1, a different 2 times larger than the amount needed to boil water.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Furthermore, the difference between the two basis sets is really not very big:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;BS1 = QZVP for the Fe atom and TZV for all other atoms&lt;/li&gt;&#xA;&lt;li&gt;BS2 = TZVP for all atoms (this may have been a typo, since it would be strange that they choose not to use QZVP for the Fe atom in the bigger basis set, but maybe that would make the overall basis set too big, but I find that hard to believe and it doesn't matter much because it's just one of the dozens of overall atoms).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;This tiny difference in the basis set (keeping &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; the same but just increasing polarization functions, and perhaps also reducing &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; for the Fe atom) caused a difference of 217K in &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt;, so again I would probably &lt;strong&gt;&lt;em&gt;stop here and try to do a basis set convergence study&lt;/em&gt;&lt;/strong&gt; (for example, looking at cc-pVDZ, cc-pVTZ, and an extrapolation, and comparing it with another 2Z/3Z extrapolation). Personally I probably would have tried to study 5 molecules more thoroughly (with a basis set convergence study and more supporting evidence for my choice of functional) rather than 20 molecules the way they did, but I also do not work in this field and cannot fully appreciate the motivations behind the study.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;So how can the prediction for &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt; be calculated more accurately? I would recommend the following things:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;This study showed that a minor difference in basis set resulted in a 217K change in &lt;span class=&quot;math-container&quot;&gt;$T_{1/2}$&lt;/span&gt;, so I would do a basis set extrapolation with at least two different basis set series and see if there is some reasonable number on which the different series agree. If the basis set extrapolations give numbers that are vastly different, and I cannot afford to use a larger basis set or to incorporate explicit correlation through something like an F12 method, then there is no shame in saying that the problem has defeated me. With so many atoms, it is understood that the complete basis set is not approachable easily (if at all).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This study shows that different functionals give vastly different results. The number of atoms is rather large, but not out of reach for CCSD and CCSD(T). Transition metal systems can be challenging, especially for multi-reference spin states, but this system does not look &lt;em&gt;impossible&lt;/em&gt; for coupled cluster. A comparison between MP2, CCSD, and CCSD(T) may show energies that are closer together than the different functionals used in this paper, and the agreement between CCSD and CCSD(T) can be an inidication of the overall accuracy of the calculation. Another option would be CASSCF, RASSCF or GASSCF and CASPT2/RASPT2 with &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b00532&quot; rel=&quot;noreferrer&quot;&gt;OpenMOLCAS&lt;/a&gt;, which may allow for better accuracy but will cost more human time since these are not black box methods.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The DKH relativistic treatment in the paper is most likely okay, but for the same cost they could have done X2C which is equivalent to &quot;infinite order DKH&quot;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-05-14T19:03:11.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="597" PostTypeId="1" AcceptedAnswerId="598" CreationDate="2020-05-14T19:42:22.120" Score="9" ViewCount="223" Body="&lt;p&gt;I have tried to calculate state-averaged gradients with MOLPRO using the default basis set &lt;code&gt;cc-pvdz&lt;/code&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, I was met with the error message:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;1PROGRAM * FORCE (Gradient of the energy)&#xA; SA-MCSCF information from    5101.1&#xA; Orbitals from record         2140.2&#xA; Number of closed-shell orbitals: 29 ( 29 )&#xA; Number of active orbitals:       12 ( 12 )&#xA; Number of occupied orbitals:     41 ( 41 )&#xA; Number of electrons= 72     Singlet     Space symmetry=1      Wavefunction type: SA-MCSCF&#xA; GENERAL BASIS CONTRACTION NOT IMPLEMENTED IN CADPAC GRADIENTS&#xA; Please try with segmented basis set&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Can MOLPRO really not calculate excited-state gradients with cc-pvdz?? &lt;strong&gt;&lt;em&gt;That's the default basis-set and the correlation consistent basis set.&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The gradient does work with the Pople basis sets, however. I'm wondering if this is something that I'm doing wrong or is intrinsic to this version of MOLPRO (2012.1)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Bonus question&lt;/strong&gt;: what does the error message mean general basis set contraction? I didn't consider Pople and correlation consistent basis functions much different.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-03-16T22:25:29.573" LastActivityDate="2021-03-16T22:25:29.573" Title="Can MOLPRO (2012) calculate SA-CASSCF gradients with cc-pVDZ?" Tags="|molpro|casscf|multi-reference|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="598" PostTypeId="2" ParentId="597" CreationDate="2020-05-14T20:44:48.050" Score="11" Body="&lt;p&gt;The &lt;a href=&quot;https://www.molpro.net/info/2012.1/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOLPRO 2012.1 manual&lt;/a&gt; is no longer online, although there is &lt;a href=&quot;https://web.archive.org/web/20130212102902/https://www.molpro.net/info/2012.1/doc/manual/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;an archive of at least some of the pages&lt;/a&gt; and you can try your luck for finding the pages you want on the archive, but it might not be necessary since the 2019 manual seems to answer your question.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;MOLPRO has &lt;a href=&quot;https://www.molpro.net/info/release/doc/manual/node524.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;3 different programs&lt;/a&gt; for calculating gradients: CADPAC, ALASKA/SEWARD, and AIC.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The 2019 manual  clearly says &quot;CADPAC does not work with generally contracted basis functions&quot; and &lt;strong&gt;this is the error you got in your 2012 version (i.e. the functionality was not there then, and it's not here now)&lt;/strong&gt;. To do gradients with CADPAC, you need to use a basis set with a segmented contraction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;AIC does do gradients for SA-MCSCF, but it seems to be meant for use with density-fitting: &quot;This program is used for computing gradients for the DF-MP2, DF-LMP2, DF-CCSD, DF-CCSD(T), DF-MP2-F12, DF-CCSD-F12, DF-CCSD(T)-F12, state averaged DF-MCSCF, and DF-CASPT2 methods&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.molpro.net/info/release/doc/manual/node530.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;The option you want to use for SA-MCSCF gradients with &lt;strong&gt;&lt;em&gt;generally contracted&lt;/em&gt;&lt;/strong&gt; basis sets is SEWARD&lt;/a&gt;: &quot;SA-MCSCF gradients can be computed using segmented or generally contracted basis sets using SEWARD and the RS2 gradient program.&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The MOLPRO 2012.1 manual makes no reference to AIC, and while it does refer to RS2, I was not able to find the above detailed description about the various programs that do gradients for SA-MCSCF. Functionality might have been added for MOLPRO 2015 and later, in which case your best options are either: &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;get the &lt;a href=&quot;https://www.molpro.net/info/request_trial_licence?portal=visitor&amp;amp;choice=Free+trial&quot; rel=&quot;nofollow noreferrer&quot;&gt;30-day free-trial of MOLPRO 2019&lt;/a&gt; to get you through this paper, &lt;/li&gt;&#xA;&lt;li&gt;do gradients by finite differences (which I don't recommend),&lt;/li&gt;&#xA;&lt;li&gt;do not do gradients, instead just optimize the geometry manually,&lt;/li&gt;&#xA;&lt;li&gt;use a basis set with segmented contraction,&lt;/li&gt;&#xA;&lt;li&gt;for cc-pVDZ, you can also uncontract the basis set and CADPAC may actually be able to do the gradients.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-15T01:34:06.267" LastActivityDate="2020-05-15T01:34:06.267" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="599" PostTypeId="5" CreationDate="2020-05-14T20:48:19.377" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T20:48:19.377" LastActivityDate="2020-05-14T20:48:19.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="600" PostTypeId="4" CreationDate="2020-05-14T20:48:19.377" Score="0" Body="For questions related to the Born-Oppenheimer approximation in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:55.227" LastActivityDate="2020-05-15T04:18:55.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="601" PostTypeId="5" CreationDate="2020-05-14T20:53:25.273" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T20:53:25.273" LastActivityDate="2020-05-14T20:53:25.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="602" PostTypeId="4" CreationDate="2020-05-14T20:53:25.273" Score="0" Body="Questions related to molecular interactions when calculating quantities in materials science." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T11:40:23.227" LastActivityDate="2020-05-15T11:40:23.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="603" PostTypeId="5" CreationDate="2020-05-14T20:54:17.950" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T20:54:17.950" LastActivityDate="2020-05-14T20:54:17.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="604" PostTypeId="4" CreationDate="2020-05-14T20:54:17.950" Score="0" Body="Questions relating to biomaterials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:19:04.740" LastActivityDate="2020-05-15T04:19:04.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="605" PostTypeId="1" CreationDate="2020-05-14T21:15:48.117" Score="13" ViewCount="175" Body="&lt;p&gt;I want to study the interaction of a given surface with some molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How should I prepare the surface for that kind of simulation?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;By prepare the surface I mean how many atom layers, how many of them should be frozen, how to passivate the surface (if it is needed), etc.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-16T13:14:41.513" LastActivityDate="2020-06-16T15:33:38.057" Title="What are the steps to prepare a surface for molecular adsorption simulations on it?" Tags="|molecular-modeling|surfaces|molecular-interactions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="606" PostTypeId="1" CreationDate="2020-05-14T21:25:45.257" Score="7" ViewCount="525" Body="&lt;p&gt;I want to study the interaction of a surface with some molecules (green house effect gases).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To obtain the binding energy, the procedure is to calculate the energy of both systems separately &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{surface}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{gas}$&lt;/span&gt;, and to calculate the energy of the complex &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{surface+gas}$&lt;/span&gt;. Then, the binding energy can be calculated as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_\mathrm{bind} &#xA;  = E_\mathrm{surface+gas} - E_\mathrm{surface} - E_\mathrm{gas}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: how to calculate the energy of a surface for the terms &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{surface}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{surface+gas}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="22" LastEditDate="2020-05-15T18:51:10.937" LastActivityDate="2020-05-15T19:20:59.663" Title="How to calculate the energy of a surface?" Tags="|surfaces|molecular-interactions|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="607" PostTypeId="1" AcceptedAnswerId="1291" CreationDate="2020-05-14T21:59:16.590" Score="19" ViewCount="708" Body="&lt;p&gt;A few years back, I performed a few calculations of metallic slabs using VASP and the Atomic Simulation Environment (ASE). I'm by no means an expert, but I noticed that the calculations were very CPU intensive e.g. ~24 cpu-hours (in parallel) to get a single energy point and gradient calculation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Considering the size of the system this makes sense, however, I'm wondering, have graphics processing units (GPUs) changed this scenario much? Is the use of GPUs becoming more popular in plane-wave DFT? &lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-05-21T20:08:04.963" LastActivityDate="2020-06-13T10:33:32.870" Title="What is the status of graphics processing units in plane-wave DFT?" Tags="|density-functional-theory|vasp|periodic-system|graphical-processing-unit|gpaw|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="608" PostTypeId="5" CreationDate="2020-05-14T22:23:21.860" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:23:21.860" LastActivityDate="2020-05-14T22:23:21.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="609" PostTypeId="4" CreationDate="2020-05-14T22:23:21.860" Score="0" Body="Question relating to structure in materials modeling. Can be on any scale." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T09:07:45.513" LastActivityDate="2020-05-15T09:07:45.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="610" PostTypeId="5" CreationDate="2020-05-14T22:25:50.050" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:25:50.050" LastActivityDate="2020-05-14T22:25:50.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="611" PostTypeId="4" CreationDate="2020-05-14T22:25:50.050" Score="0" Body="Questions examining the various types of Hamiltonian models that are used in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:19:07.057" LastActivityDate="2020-05-15T04:19:07.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="612" PostTypeId="5" CreationDate="2020-05-14T22:26:43.960" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:26:43.960" LastActivityDate="2020-05-14T22:26:43.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="613" PostTypeId="4" CreationDate="2020-05-14T22:26:43.960" Score="0" Body="Questions related to materials modeling at the macroscopic scale." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:29.923" LastActivityDate="2020-05-15T04:18:29.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="614" PostTypeId="5" CreationDate="2020-05-14T22:28:09.230" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:28:09.230" LastActivityDate="2020-05-14T22:28:09.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="615" PostTypeId="4" CreationDate="2020-05-14T22:28:09.230" Score="0" Body="Questions related to the various types of interatomic potentials that are used in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:19.170" LastActivityDate="2020-05-15T04:18:19.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="616" PostTypeId="5" CreationDate="2020-05-14T22:28:46.353" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:28:46.353" LastActivityDate="2020-05-14T22:28:46.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="617" PostTypeId="4" CreationDate="2020-05-14T22:28:46.353" Score="0" Body="Questions related to alloys." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:37.460" LastActivityDate="2020-05-15T04:18:37.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="618" PostTypeId="5" CreationDate="2020-05-14T22:29:47.377" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:29:47.377" LastActivityDate="2020-05-14T22:29:47.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="619" PostTypeId="4" CreationDate="2020-05-14T22:29:47.377" Score="0" Body="Questions related to polymers. " OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:33.807" LastActivityDate="2020-05-15T05:06:33.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="620" PostTypeId="5" CreationDate="2020-05-14T22:30:57.440" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:30:57.440" LastActivityDate="2020-05-14T22:30:57.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="621" PostTypeId="4" CreationDate="2020-05-14T22:30:57.440" Score="0" Body="Questions concerned with thermodynamics as related to systems in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:27.063" LastActivityDate="2020-05-15T04:18:27.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="622" PostTypeId="5" CreationDate="2020-05-14T22:31:35.203" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:31:35.203" LastActivityDate="2020-05-14T22:31:35.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="623" PostTypeId="4" CreationDate="2020-05-14T22:31:35.203" Score="0" Body="Questions related to the thermal properties of materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:18:45.227" LastActivityDate="2020-05-15T04:18:45.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="624" PostTypeId="5" CreationDate="2020-05-14T22:32:50.920" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:32:50.920" LastActivityDate="2020-05-14T22:32:50.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="625" PostTypeId="4" CreationDate="2020-05-14T22:32:50.920" Score="0" Body="Questions related to Green's functions and their role in matter modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-02T16:13:39.633" LastActivityDate="2020-07-02T16:13:39.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="626" PostTypeId="5" CreationDate="2020-05-14T22:33:32.780" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:33:32.780" LastActivityDate="2020-05-14T22:33:32.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="627" PostTypeId="4" CreationDate="2020-05-14T22:33:32.780" Score="0" Body="Questions related to the semiclassical modeling of materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:46.067" LastActivityDate="2020-05-15T05:06:46.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="628" PostTypeId="5" CreationDate="2020-05-14T22:34:29.647" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:34:29.647" LastActivityDate="2020-05-14T22:34:29.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="629" PostTypeId="4" CreationDate="2020-05-14T22:34:29.647" Score="0" Body="Questions related to nanostructures in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:27.497" LastActivityDate="2020-05-15T05:06:27.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="630" PostTypeId="5" CreationDate="2020-05-14T22:35:36.533" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:35:36.533" LastActivityDate="2020-05-14T22:35:36.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="631" PostTypeId="4" CreationDate="2020-05-14T22:35:36.533" Score="0" Body="Questions focusing on effective Hamiltonians and their application to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:31.087" LastActivityDate="2020-05-15T05:06:31.087" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="632" PostTypeId="5" CreationDate="2020-05-14T22:36:17.943" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:36:17.943" LastActivityDate="2020-05-14T22:36:17.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="633" PostTypeId="4" CreationDate="2020-05-14T22:36:17.943" Score="0" Body="Questions concerning high performance computing (HPC)." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2021-11-23T19:27:15.627" LastActivityDate="2021-11-23T19:27:15.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="634" PostTypeId="5" CreationDate="2020-05-14T22:37:29.873" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:37:29.873" LastActivityDate="2020-05-14T22:37:29.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="635" PostTypeId="4" CreationDate="2020-05-14T22:37:29.873" Score="0" Body="Questions pertaining to electric fields wrt materials modeling. " OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:43.250" LastActivityDate="2020-05-15T05:06:43.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="636" PostTypeId="5" CreationDate="2020-05-14T22:39:00.043" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:39:00.043" LastActivityDate="2020-05-14T22:39:00.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="637" PostTypeId="4" CreationDate="2020-05-14T22:39:00.043" Score="0" Body="Questions pertaining to multiscale phenomena in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:06:23.810" LastActivityDate="2020-05-15T05:06:23.810" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="638" PostTypeId="5" CreationDate="2020-05-14T22:40:10.537" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:40:10.537" LastActivityDate="2020-05-14T22:40:10.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="639" PostTypeId="4" CreationDate="2020-05-14T22:40:10.537" Score="0" Body="Questions on finite element methods as they pertain to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T04:19:02.303" LastActivityDate="2020-05-15T04:19:02.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="640" PostTypeId="5" CreationDate="2020-05-14T22:41:36.950" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-14T22:41:36.950" LastActivityDate="2020-05-14T22:41:36.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="641" PostTypeId="4" CreationDate="2020-05-14T22:41:36.950" Score="0" Body="Questions on dielectric constants as they relate to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-15T05:07:04.483" LastActivityDate="2020-05-15T05:07:04.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="642" PostTypeId="2" ParentId="467" CreationDate="2020-05-15T01:14:04.567" Score="20" Body="&lt;h2&gt;Jmol&lt;/h2&gt;&#xA;&lt;p&gt;For visualisation there's also a standalone Java application &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;Jmol&lt;/a&gt;, which has a GUI and a more powerful command-line &amp;quot;console&amp;quot;. I particularly like it for quickly visualising vibrational modes. However, it lacks tools to construct a simulation cell, unlike some of the other options people have mentioned.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="724" LastEditDate="2021-01-24T20:29:18.693" LastActivityDate="2021-01-24T20:29:18.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="643" PostTypeId="1" CreationDate="2020-05-15T02:09:53.717" Score="10" ViewCount="1945" Body="&lt;p&gt;To my understanding, they both refer to circular symmetry. I know U(1) is the complex plane, and I think O(2) is real numbers. I have seen them used more or less interchangably, but is there actually some subtle difference or are they just two ways to say the same thing? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm specifically interested about this question as it applies to phase transitions in materials, specifically with BKT-like transitions. It seems people use U(1) and O(2) interchangeably to describe a BKT transition. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-05-18T04:59:32.053" LastActivityDate="2020-05-18T19:55:22.070" Title="What is the difference between U(1) and O(2) symmetry?" Tags="|condensed-matter|symmetry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="644" PostTypeId="2" ParentId="498" CreationDate="2020-05-15T02:13:23.457" Score="17" Body="&lt;p&gt;The Nyquist sampling theorem states that the time step must be half or less of the period of the quickest dynamics. This is the absolute maximum time step that can capture the quickest dynamics at all, and it is usually recommended to choose a much smaller time step (often chosen to be between 0.1 and 0.2 of the shortest period).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Typical time steps range from 0.25 fs for systems with light nuclei (such as hydrogen), to 2 fs or greater for systems with more massive nuclei. (NB for quantum nuclear dynamics, e.g. using path-integrals, you may need even shorter time steps for light nuclei, especially at low temperatures.) &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In order to work out how reasonable your time step is, it is common to monitor the appropriate &quot;conserved quantity&quot; over the course of a short simulation. The relevant &quot;conserved quantity&quot; depends on the ensemble used for the dynamics; for NVE it is simply the total energy, but for NVT, NPH etc. there are extra terms from the thermostat and barostat. Whatever the appropriate quantity is, it is &lt;em&gt;conserved&lt;/em&gt; in the ideal dynamics, so monitoring the numerical drift in this quantity is a good indicator of the error in your dynamics. A reasonable rule of thumb is that the long-term drift in the &quot;conserved quantity&quot; should be less than 10 meV/atom/ps for qualitative results, and 1 meV/atom/ps for &quot;publishable&quot; results.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The time step alone is not sufficient in order to determine the accuracy of a molecular dynamics calculation. There are three other considerations which come to mind:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The time-integration algorithm. It is very important that your integration algorithm is &lt;em&gt;symplectic&lt;/em&gt;, which essentially means it is time-reversible (energy conservation is directly related to the time-reversal symmetry of the physical laws). If you use a non-symplectic integrator then you will need a much shorter time step, even if the integrator is supposedly more accurate (e.g. high-order predictor-corrector methods). Velocity-Verlet is probably the most common method used, and is symplectic.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are doing &lt;em&gt;ab initio&lt;/em&gt; dynamics, then the energy and forces are computed from an iterative solution to the quantum mechanical equations. Because the solutions are not converged perfectly there is numerical noise in the energies and forces, and this will cause additional drift in the conserved quantities.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Again, for &lt;em&gt;ab initio&lt;/em&gt; dynamics it is common to accelerate the iterative solution of the quantum mechanical equations by extrapolating the wavefunction, density etc. from the previous time step to the present time step. Many of these extrapolation schemes are not time-reversible, which breaks the overall symplecticity of the method, causing a greater drift in the conserved quantity and necessitating a smaller time step. This has been addressed by methods such as &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.123001&quot; rel=&quot;noreferrer&quot;&gt;extended-Lagrangian dynamics&lt;/a&gt;, where the wavefunction and density degrees of freedom are also propagated with a symplectic algorithm.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-05-15T02:13:23.457" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="645" PostTypeId="1" CreationDate="2020-05-15T02:39:34.577" Score="16" ViewCount="110" Body="&lt;p&gt;The &lt;strong&gt;sign problem&lt;/strong&gt; is a huge limitation of QMC, but it's not easy to tell by looking at a Hamiltonian if it has the sign problem. Often there will be some clever transformation that allows you to avoid the sign problem. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there somewhere that a database of models with known sign-problem-free implementations are listed? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Example of a nontrivial avoidance of the sign problem: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The antiferromagnetic Heisenberg Model is:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H = J \sum \limits_{\langle i,j \rangle} \vec S_i \cdot \vec S_j = J \sum \limits_{\langle i,j \rangle} [ S^z_i S^z_j + \frac{1}{2} ( S^+_i S^-_j + S^-_i S^+_j ) ] $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you naively implement the stochastic series exchange QMC, you will get a sign problem, but that can be avoided on bipartite lattices by adding a constant offset and doing a &lt;em&gt;sublattice rotation&lt;/em&gt; &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1101.3281, p. 144&lt;/a&gt; (&lt;a href=&quot;https://doi.org/10.1063/1.3518900&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;AIP Conference Proceedings&lt;/em&gt; &lt;strong&gt;2010&lt;/strong&gt;, 1297, 135&lt;/a&gt;). This is all pretty simple mathematically, but it is not trivial to figure out in the first place, and it would be easy to imagine encountering the apparent sign problem and simply giving up. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;And even more nontrivial example is a method for avoiding the sign problem in this antiferromagnetic Heisenberg model with random ferromagnetic bonds: &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.50.15803&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;1994,&lt;/strong&gt; &lt;em&gt;50&lt;/em&gt; (21), 15803–15807&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Addition:&lt;/strong&gt; if there is no such list, what are some examples of sign-problem that have solutions like this? &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-18T04:12:44.160" LastActivityDate="2020-05-18T04:12:44.160" Title="Is there a list of models that do and do not have the QMC sign problem?" Tags="|quantum-monte-carlo|spin-models|model-hamiltonians|sign-problem|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="646" PostTypeId="1" AcceptedAnswerId="653" CreationDate="2020-05-15T03:17:20.340" Score="17" ViewCount="145" Body="&lt;p&gt;A lot of materials electronic structure research focuses on periodic structures like polymers, nanotubes/sheets, Metal Organic Frameworks (MOFs) and crystals, which makes them amenable to PBC calculations and delocalized basis sets. If the periodicity is broken, say by some kind of defect site, a composite approach might be required where one still does a PBC calculation of the idealized bulk, but does a cluster calculation of the defect.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But how is the problem of modeling an explicitly aperiodic bulk structure like amorphous silica addressed? It does not seem to be as easy to form a composite model, as it is not just a small perturbation on an otherwise periodic structure.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T14:16:55.337" LastActivityDate="2020-05-17T01:22:35.580" Title="What approaches are employed to treat amorphous materials?" Tags="|electronic-structure|amorphous-materials|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="647" PostTypeId="1" AcceptedAnswerId="1504" CreationDate="2020-05-15T03:44:09.820" Score="12" ViewCount="151" Body="&lt;p&gt;Hybrid density functionals with screened Hartree-Fock exchange at long range have become popular for modeling solids. I'm curious as to what the reasoning is behind this functional form. I understand that exchange interactions are expensive to compute and so eliminating long range ones can help to maintain low scaling for larger systems. My initial intuition would say that screening these interactions would reduce the accuracy, but I have heard that full exchange at long range is actually unphysical. What makes long range exchange incorrect for solids?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:31:20.390" LastActivityDate="2020-07-14T18:16:18.363" Title="Justification for use of Screened Functionals" Tags="|density-functional-theory|functional|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="648" PostTypeId="2" ParentId="607" CreationDate="2020-05-15T06:52:51.160" Score="12" Body="&lt;p&gt;I can't say much about the popularity of GPUs in practical calculations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From a development point of view the speedups that can be expected from GPUs in plane-wave DFT are only moderate, probably around 2 to 3, maybe 7 if you are optimistic. See for example the paper describing the VASP implementation [1] or &#xA;&lt;a href=&quot;https://stackoverflow.com/questions/8158632/is-it-worth-offloading-fft-computation-to-an-embedded-gpu&quot;&gt;this stackoverflow question&lt;/a&gt; illustrating speedups of 2 to 3 for the key computational step in plane-wave FFT, namely the fast-fourier transfrom (FFT).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This might not sound so bad, but keep in mind the extra requirements in computational power, which is also &lt;a href=&quot;https://www.karlrupp.net/2013/06/cpu-gpu-and-mic-hardware-characteristics-over-time/&quot; rel=&quot;noreferrer&quot;&gt;about a factor of 2 or higher&lt;/a&gt;, the price of the GPU (on top of a CPU you need anyway!) and the added complexity inside the code, which might well prevent the implementation of other faster algorithms in the future. With that in mind, I would say GPUs have potential for large-scale cutting edge calculations, but are not able to change the picture much over CPUs for the type of calculations you describe (a few days or less): You might as well buy another CPU rack and just use that on top.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;[1] S. Maintz, B. Eck, R. Dronskowski. &lt;em&gt;Speeding up plane-wave electronic-structure calculations using graphics-processing units&lt;/em&gt;, Comp. Phys. Comm. &lt;strong&gt;7&lt;/strong&gt;, 1421 (2011) DOI &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2011.03.010&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2011.03.010&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="327" LastActivityDate="2020-05-15T06:52:51.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="649" PostTypeId="1" CreationDate="2020-05-15T08:00:28.893" Score="14" ViewCount="229" Body="&lt;p&gt;What are the best possible methods and available software to compute the spin-state energetics of transition metal complexes?&lt;/p&gt;&#xA;" OwnerUserId="441" LastEditorUserId="5" LastEditDate="2020-12-02T19:42:35.500" LastActivityDate="2020-12-02T19:42:35.500" Title="Spin State of Transition Metal complex" Tags="|molecular-modeling|transition-metals|spin|metal-complexes|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="650" PostTypeId="2" ParentId="649" CreationDate="2020-05-15T08:22:46.310" Score="8" Body="&lt;p&gt;There's probably no answer to this question. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Best possible method? In general, just build up reasonable structures (don't tunnel vision into one), find their local minima on the given spin-states and just compare their energetics. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The best level of theory is also not really defined. One might say DFT, but I personally do not really trust DFT in general for problems like these. CCSD(T) could be performed, depending on your computational resources (remember, you need to optimize too, which you can probably do on MP2 level in this case and hope for the best), but don't be fooled into thinking CCSD(T) is the golden standard method. It is only the golden standard for large enough basis sets, which could also be an issue with transition metal complexes. Also for heavier elements, you might need to add spin-orbit corrections. Even worse: if the spin states (or just normal electronic states) are not separate enough, you really need a multireference method. Then we should be talking about MRCI, which is extremely complicated, and again, no general answer on how to do it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As to what code to use, you have a plethora to choose from. Apart from the big names like Gaussian or Q-Chem, you might look into FHI-AIMS for the numerical basis set efficiency - however, this code really only is for DFT, which I would not suggest here. ORCA seems to do excellent on problems on this, and it also has a DMRG method built in, so I strongly suggest ORCA here. Molpro can also be considered for the extremely reliable spin-orbit coupling methods available. But for a general CCSD(T) calculation, I'd stick with the good old Gaussian, as that is, in my experience, the most reliable.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastActivityDate="2020-05-15T08:22:46.310" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="651" PostTypeId="2" ParentId="649" CreationDate="2020-05-15T09:51:40.443" Score="10" Body="&lt;p&gt;For computing the spin-state in a metal complex there are many methods available. I'll focus in DFT as one of the most used methodologies.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In a single atom cluster (sometimes described as mononuclear complexes), DFT offers good results compared with wave-function multideterminantal methods.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, if the complex is formed by two or more metallic centers, DFT has real troubles while finding the energy of antiferromagnetically coupled states. One of the most used approximations about this is the 'broken-symmetry' approach which permits to calculate the single determinant energy of a certain state. Nice reviews on this about metallic complexes are by Ruiz &lt;em&gt;et. al.&lt;/em&gt;.&lt;sup&gt;[1, 2]&lt;/sup&gt; With this approach it is possible to somehow approximate the value of the magnetic exchange coupling that finally determines the relative energies of the different spin states, but one should be really careful concerning which particular expression is using for it.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ruiz, E.; Cano, J.; Alvarez, S.; Alemany, P. Broken symmetry approach to calculation of exchange coupling constants for homobinuclear and heterobinuclear transition metal complexes. &lt;em&gt;J. Comput. Chem.&lt;/em&gt; &lt;strong&gt;1999,&lt;/strong&gt; &lt;em&gt;20&lt;/em&gt; (13), 1391–1400. &lt;a href=&quot;https://doi.org/10.1002/(SICI)1096-987X(199910)20:13%3C1391::AID-JCC6%3E3.0.CO;2-J&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/(SICI)1096-987X(199910)20:13%3C1391::AID-JCC6%3E3.0.CO;2-J&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Ruiz, E.; Rodríguez-Fortea, A.; Cano, J.; Alvarez, S.; Alemany, P. About the calculation of exchange coupling constants in polynuclear transition metal complexes. &lt;em&gt;J. Comput. Chem.&lt;/em&gt; &lt;strong&gt;2003,&lt;/strong&gt; &lt;em&gt;24&lt;/em&gt; (8), 982–989. &lt;a href=&quot;https://doi.org/10.1002/jcc.10257&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/jcc.10257&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="290" LastEditorUserId="49" LastEditDate="2020-05-15T10:21:33.640" LastActivityDate="2020-05-15T10:21:33.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="652" PostTypeId="2" ParentId="607" CreationDate="2020-05-15T13:57:37.550" Score="10" Body="&lt;p&gt;While I can't comment on concrete speed-ups as I'm not very familiar with GPU programming itself, I would like to point out that most of the computing time is spent in FFT and GEMM (matrix matrix multipicaltions) calls. A friend of mine tested this for the GPAW code where those two thing accounted for &gt; 70 % of the CPU time. I imagine it is similar for other programs.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In principle, speeding up these functions should result in a significant overall performance increase. That said, additions/changes to the core functionality of popular programs like VASP can yield underwhelming results. An example for that would be the k-point parallelism in VASP that shows extreme data redundancy. &lt;/p&gt;&#xA;" OwnerUserId="406" LastActivityDate="2020-05-15T13:57:37.550" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="653" PostTypeId="2" ParentId="646" CreationDate="2020-05-15T14:15:58.623" Score="12" Body="&lt;p&gt;Creating amorphous structures is non-trivial and always rather expensive. Generally you are using large supercells such that you can achieve mid-range disorder. That means, since the cell is still periodic, you cannot truly achieve the long range disorder of amorphous materials, but in a medium range (&gt; the unit cell volume) you can. As such, we some times speak of pseudo-amorphicity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;After you created the starting structure the general procedure is to quenching an ab-initio MD simulation. The principle is very similar to creating amorphous aterails in the lab: heat up a crystaline sample and then rapidly cool it down.&#xA;This procedure is discussed at length in&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Molecular Dynamics Simulations of Disordered Materials: From Network Glasses to Phase-Change Memory Alloys&lt;/em&gt; by C. Massobrio et. al.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Recently people have started experimenting with evolutionary structure generation programs like USPEX to create amorphous structures, but as far as I am aware the jury is still out on the prospects of that.&lt;/p&gt;&#xA;" OwnerUserId="406" LastEditorUserId="36" LastEditDate="2020-05-16T13:28:52.370" LastActivityDate="2020-05-16T13:28:52.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="654" PostTypeId="2" ParentId="408" CreationDate="2020-05-15T14:28:45.783" Score="2" Body="&lt;p&gt;I think that material modeling is made possible primarily due to physical models instead of mathematical/computational ones. A mathematical/computational model, &lt;em&gt;per se&lt;/em&gt;, don't have any information/interpretation about the system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Once the physics behind the process/phenomenon is understood, it is modeled using tools like mathematics, as needed.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Normally, in the Physics courses are disciplines dedicate to the mathematical tools useful in Physics called Mathematical Physics. In the &lt;a href=&quot;https://www.google.com/search?tbm=bks&amp;amp;q=mathematical%20physics&amp;amp;oq=mathematical%20&quot; rel=&quot;nofollow noreferrer&quot;&gt;Google Books&lt;/a&gt; resource you can find many books with this subject, for example.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-15T14:28:45.783" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="655" PostTypeId="2" ParentId="132" CreationDate="2020-05-15T14:45:46.013" Score="5" Body="&lt;p&gt;Also, you can use &lt;a href=&quot;https://atomsk.univ-lille.fr/index.php&quot; rel=&quot;noreferrer&quot;&gt;Atomsk&lt;/a&gt; and &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/src/master/&quot; rel=&quot;noreferrer&quot;&gt;Nanocut&lt;/a&gt;. Both are free.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Atomsk info (from the site):&#xA;&lt;em&gt;A free, Open Source command-line program dedicated to the creation, manipulation, and conversion of data files for atomic-scale simulations.&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&quot;Atomsk: A tool for manipulating and converting atomic data files&quot;&#xA;Pierre Hirel, Comput. Phys. Comm. 197 (2015) 212-219&#xA;doi:10.1016/j.cpc.2015.07.012&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nanocut info (form the site):&#xA;&lt;em&gt;Nanocut is a program designed to cut out various objects from three dimensional crystal structures. It is aimed to be helpful when creating geometry input for atomistic simulations. Currently it can create following objects:&#xA;    Spherical cluster&#xA;    Polyhedral cluster&#xA;    Cylindrical cluster&#xA;    Spherical wire (1D periodic)&#xA;    Polyhedral wire (1D periodic)&#xA;    Plain slab (2D periodic)&#xA;    Supercells (3D periodic)&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-15T14:45:46.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="656" PostTypeId="1" AcceptedAnswerId="1146" CreationDate="2020-05-15T16:07:15.347" Score="14" ViewCount="180" Body="&lt;p&gt;Expanding the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron wavefunction in terms of Slater determinants (as in CI and CC theory) could lead to a very slow convergence to its basis set limit because such expansions can't give an accurate representation of the electron-electron cusps. As noted by &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/cr200168z&quot; rel=&quot;noreferrer&quot;&gt;Slater (and Hylleraas)&lt;/a&gt;, going beyond determinants, including the interelectronic distance explicitly, can improve this.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This idea was exploited by Hylleraas and he wrote the wavefunction as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Psi=e^{-\zeta(r_1+r_2)}\sum_{i=1}^{N}c_i(r_1+r_2)^{l_i}(r_1-r_2)^{2m_i}(r_{12})^{n_i},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; is the distance of electron &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; from the nucleus and &lt;span class=&quot;math-container&quot;&gt;$r_{12}$&lt;/span&gt; is the distance between two electrons. For the helium, he found that a 308-term expansion gives an accuracy within &lt;span class=&quot;math-container&quot;&gt;$10^{-9}$&lt;/span&gt; Hartree (!).&#xA;However, in Jensen's Introduction to Computational Chemistry (2007 edition) it says that Hylleraas type wavefunctions are impractical for more than &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$4$&lt;/span&gt; electrons. However, there have been a lot of development in computational methods in the last &lt;span class=&quot;math-container&quot;&gt;$13$&lt;/span&gt; years (improvement in parallel processing, GPUs, etc..), so, this can't be that bad.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Furthermore, in 1960, Boys and Singer found that functions that are product of Gaussian orbital and factors of the type &lt;span class=&quot;math-container&quot;&gt;$e^{-a r_{ij}^2}$&lt;/span&gt; generate relatively simple integrals to calculate. But, in Piela's Ideas of Quantum Chemistry (2006) it says that the area of application of this method is relatively small due to computational reasons too.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What are the current practical limitations of explicitly correlated methods? What is the largest system that has been studied using explictly correlated methods?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="10" LastEditDate="2020-05-30T06:46:23.410" LastActivityDate="2020-05-30T19:01:57.140" Title="What are the computational limits of explicitly correlated methods?" Tags="|electronic-structure|electron-correlation|explicitly-correlated-methods|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="657" PostTypeId="1" CreationDate="2020-05-15T16:59:35.447" Score="13" ViewCount="2690" Body="&lt;p&gt;One of the properties used in Solid State Physics, and specially in semiconductor physics, is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;noreferrer&quot;&gt;effective mass&lt;/a&gt;. It can be calculated from the energy dispersion relationship. The simple form, for parabolic bands, is:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E(\vec{k}) = E_0 + \frac{\hbar^2\vec{k}^2}{2m^*}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there a tool/script that can extract the effective mass from DFT band calculations done by software like &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt; and/or &lt;a href=&quot;http://quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt;?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-16T17:25:24.217" LastActivityDate="2020-05-16T21:43:05.393" Title="How to calculate the effective mass from DFT band calculations?" Tags="|density-functional-theory|quantum-espresso|siesta|effective-mass|energy-dispersion|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="658" PostTypeId="1" CreationDate="2020-05-15T17:32:40.647" Score="7" ViewCount="1786" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Photoluminescence&quot; rel=&quot;nofollow noreferrer&quot;&gt;Photoluminescence&lt;/a&gt; (PL) spectrum is one of the experimental observable used, among other things, to have an accurate idea about the material band structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It can be calculated using the band structure and wavefunctions together with the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fermi%27s_golden_rule&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fermi's golden rule&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there any tool  or script to estimate the PL spectra from DFT calculations using software like &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SIESTA&lt;/a&gt; and/or &lt;a href=&quot;http://quantum-espresso.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt;?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FKSZL.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FKSZL.gif&quot; alt=&quot;By BlyumJ - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=64937770&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-18T12:56:05.167" LastActivityDate="2020-05-18T12:56:05.167" Title="How to calculate the photoluminescence spectrum from DFT band calculations?" Tags="|software|quantum-espresso|siesta|photoluminescence|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="659" PostTypeId="1" AcceptedAnswerId="1509" CreationDate="2020-05-15T18:06:55.557" Score="15" ViewCount="706" Body="&lt;p&gt;Heisenberg model&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}=-\sum_{\langle i j\rangle}J\hat{S}_i\hat{S}_j$$&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;And in its simplified version, the Ising model&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}=-\sum_{\langle ij\rangle}J\hat{S}_i^z\hat{S}_j^z$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;are widely applied in the field of condensed matter to understand magnetic systems. For example, there is classical spin wave approach and Bloch &lt;span class=&quot;math-container&quot;&gt;$T^{\frac{3}{2}}$&lt;/span&gt; law. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are also many computational methods available to diagonalize the Heisenberg effective model Hamiltonian (e.g. renormalization group method , quantum Monte Carlo, etc).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, is the Heisenberg model Hamiltonian good enough to study magnetic system? As the assumption of these type of Hamiltonian is that the electrons are localized on each site (unit cell) and thus no charge transfer states are allowed. What's more, the exchange integrals in these Heisenberg model are to some extent semi-empirical and could only be determined through experiments.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While on the other hand, in modern quantum chemistry ab initio Hamiltonian is introduced to study the electronic structure of molecular systems. By introducing certain basis sets and Slater determinants, all matrix elements in the Hamiltonian of electronic structure could be evaluated merely via first principle (of course some additional constants are required e.g. Planck constant, speed of light, etc).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is, how is the performance of the Heisenberg Hamiltonian compares to a first principle Hamiltonian? What are the pros and cons?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-15T19:05:26.397" LastActivityDate="2020-07-12T22:06:04.840" Title="Is Heisenberg model or in its simplier form Ising model a good approximation to study magnetic systems?" Tags="|electronic-structure|magnetism|model-hamiltonians|ising-model|heisenberg-model|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="660" PostTypeId="5" CreationDate="2020-05-15T18:33:31.720" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:33:31.720" LastActivityDate="2020-05-15T18:33:31.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="661" PostTypeId="4" CreationDate="2020-05-15T18:33:31.720" Score="0" Body="For questions about the design and use of specific exchange-correlation density functionals" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:33:31.720" LastActivityDate="2020-05-15T18:33:31.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="662" PostTypeId="5" CreationDate="2020-05-15T18:37:01.210" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:37:01.210" LastActivityDate="2020-05-15T18:37:01.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="663" PostTypeId="4" CreationDate="2020-05-15T18:37:01.210" Score="0" Body="For questions about using the SIESTA (Spanish Initiative for Electronic Simulations with Thousands of Atoms) electronic structure program." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-07-31T19:23:32.920" LastActivityDate="2020-07-31T19:23:32.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="664" PostTypeId="5" CreationDate="2020-05-15T18:43:44.787" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:43:44.787" LastActivityDate="2020-05-15T18:43:44.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="665" PostTypeId="4" CreationDate="2020-05-15T18:43:44.787" Score="0" Body="For questions about charge transfer processes in materials and molecules" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:43:44.787" LastActivityDate="2020-05-15T18:43:44.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="666" PostTypeId="5" CreationDate="2020-05-15T18:44:59.803" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:44:59.803" LastActivityDate="2020-05-15T18:44:59.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="667" PostTypeId="4" CreationDate="2020-05-15T18:44:59.803" Score="0" Body="For questions about performing Complete Active Space Self Consistent Field calculations" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:44:59.803" LastActivityDate="2020-05-15T18:44:59.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="668" PostTypeId="5" CreationDate="2020-05-15T18:48:11.187" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:48:11.187" LastActivityDate="2020-05-15T18:48:11.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="669" PostTypeId="4" CreationDate="2020-05-15T18:48:11.187" Score="0" Body="For questions related to performing calculation using the self consistent field (SCF) algorithm, for example Hartree-Fock and Kohn-Sham Density Functional Theory." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:48:11.187" LastActivityDate="2020-05-15T18:48:11.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="670" PostTypeId="5" CreationDate="2020-05-15T18:49:04.497" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:49:04.497" LastActivityDate="2020-05-15T18:49:04.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="671" PostTypeId="4" CreationDate="2020-05-15T18:49:04.497" Score="0" Body="For questions about methods to model solvation effects in simulation." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-15T18:49:04.497" LastActivityDate="2020-05-15T18:49:04.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="672" PostTypeId="2" ParentId="606" CreationDate="2020-05-15T19:20:59.663" Score="6" Body="&lt;p&gt;For calculating the energy of a surface, we need to split the contribution of the surface and the contribution of the bulk to the total energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_\mathrm{total} = E_\mathrm{surface} + E_\mathrm{bulk}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The term &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{total}$&lt;/span&gt; is obtained from a calculation on a simulation cell that models the surface (let this be Calculation 1). The term &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{bulk}$&lt;/span&gt; is obtained from a calculation that only contains the material in bulk (let this be Calculation 2). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since the simulation cells are different, we must normalise the contribution of the energy. This is usually done by dividing the calculated energy by the number of atoms (or formula units) in the simulation cell. If &lt;span class=&quot;math-container&quot;&gt;$n_2$&lt;/span&gt; is the number of atoms (or formula units) in the simulation cell in Calculation 2, the energy contribution per atom (or formula unit) be &#xA;&lt;span class=&quot;math-container&quot;&gt;$$E'_\mathrm{bulk} = \frac{E_\mathrm{bulk}}{n_2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, we can subtract the contribution of the bulk and obtain the surface contribution. If &lt;span class=&quot;math-container&quot;&gt;$n_1$&lt;/span&gt; is the number of atoms (or formula units) in the simulation cell in Calculation 1 (see point 1 below), the surface contribution will be:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_\mathrm{surface} = E_\mathrm{total} - n_1 E'_\mathrm{bulk}$$&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Surface energy is also usually normalised with the area. Hence, if &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is the area of the surface (see point 2 below), the final expression will become&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E'_\mathrm{surface} = \frac{1}{A} \left( E_\mathrm{total} - n_1 E'_\mathrm{bulk} \right)$$&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Points to note&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Even though some of the atoms in Calculation 1 are part of the &quot;surface&quot;, we must still include them in &lt;span class=&quot;math-container&quot;&gt;$n_1$&lt;/span&gt; while calculating the &lt;em&gt;bulk&lt;/em&gt; contribution because the surface energy is defined as the &lt;em&gt;excess&lt;/em&gt; energy due to a surface. So the energy in the bulk is simply the &lt;em&gt;reference&lt;/em&gt; energy using which we calculate the contribution of the surface.&lt;/li&gt;&#xA;&lt;li&gt;When slab models are used to model the surface, and if the energy calculations use periodic boundary conditions, then the contribution to area &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; will actually be 2 times the area of one surface.&lt;/li&gt;&#xA;&lt;li&gt;The only input we need here is the energy, so irrespective of what atomistic modelling method we use to calculate the energy, this procedure can be used to get the surface energy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="22" LastActivityDate="2020-05-15T19:20:59.663" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="673" PostTypeId="1" AcceptedAnswerId="674" CreationDate="2020-05-15T19:32:22.910" Score="10" ViewCount="198" Body="&lt;p&gt;I am trying to swap orbitals for a high-spin iron(IV) complex. The orbitals that correspond to the iron are not in any of the SOMOs. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am using the pDynamo QM/MM program, which is an interface for CHARMM and ORCA. Does anyone know the correct formatting to swap orbitals?&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="510" LastEditDate="2020-05-17T23:20:32.657" LastActivityDate="2020-05-17T23:20:32.657" Title="How to swap orbitals in ORCA?" Tags="|software|orca|pdynamo|charmm|qmmm|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="674" PostTypeId="2" ParentId="673" CreationDate="2020-05-15T19:36:59.827" Score="9" Body="&lt;p&gt;I figured out the correct formatting. The section defining the QM needs to have the &lt;code&gt;MORead&lt;/code&gt; option, the &lt;code&gt;%moinp&lt;/code&gt; section, and the &lt;code&gt;%scf&lt;/code&gt; section. Example:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;!B3LYP 6-31G* Slowconv MOREAD&#xA;*xyz 0 3&#xA;...&#xA;*&#xA;&#xA;%moinp &quot;01.ethylene.gbw&quot;&#xA; %scf&#xA;  rotate {7, 8, 90, 0, 0}&#xA; end&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="510" LastEditorUserId="52" LastEditDate="2020-05-15T19:38:36.487" LastActivityDate="2020-05-15T19:38:36.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="675" PostTypeId="1" AcceptedAnswerId="676" CreationDate="2020-05-15T19:38:45.560" Score="7" ViewCount="120" Body="&lt;p&gt;Does anyone know how to localize orbitals in pDynamo (CHARMM/ORCA interface). I am trying to identify the correct orbitals to swap for my high-spin iron(IV) system. &lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="510" LastEditDate="2020-05-17T23:20:01.963" LastActivityDate="2020-05-17T23:20:01.963" Title="How to localize orbitals in pDynamo (CHARMM/ORCA interface)?" Tags="|software|orca|pdynamo|charmm|qmmm|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="676" PostTypeId="2" ParentId="675" CreationDate="2020-05-15T19:41:31.890" Score="3" Body="&lt;p&gt;I found the most consistent way to localize orbitals. Use the orca_loc extension. You must create and input file where define the localization method (PM, Boys, ...), and the orbitals you want to localize. To run it: orca_loc name.inp -i&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-05-15T19:41:31.890" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="677" PostTypeId="2" ParentId="645" CreationDate="2020-05-15T20:11:23.147" Score="11" Body="&lt;p&gt;The general problem of determining whether a Hamiltonian can be transformed into &quot;stoquastic&quot; (i.e. sign-problem-free) form by local transformations is NP-hard:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1906.08800&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1906.08800&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1802.03408&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1802.03408&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, there are lots of individual Hamiltonians for which people have figured out clever tricks to bring them into stoquastic form, as the question asker has noted. Unfortunately, I am not aware of any place that these have been systematically aggregated.&lt;/p&gt;&#xA;" OwnerUserId="513" LastActivityDate="2020-05-15T20:11:23.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="678" PostTypeId="2" ParentId="365" CreationDate="2020-05-15T20:20:01.487" Score="20" Body="&lt;h2&gt;It depends on what you want to do&lt;/h2&gt;&#xA;&lt;p&gt;It depends on what you want to do. As a couple of others have pointed out, many of the computer programs used in computational chemistry and theoretical solid state physics are written in Fortran. However, &lt;em&gt;that does not imply that you should learn Fortran&lt;/em&gt; and it does not mean that Fortran is the best language for materials modelling.&lt;/p&gt;&#xA;&lt;p&gt;Even if you are concerned with writing serious code for a DFT/MD code. Consider that languages like &lt;strong&gt;Python&lt;/strong&gt; and &lt;strong&gt;Julia&lt;/strong&gt; are very easy to pick up. If you want to get to learn the theory and spend less time thinking about the implementation (as beginners should), it's hard to beat these languages. The other advantage that python has is that it has by far the best ecosystem surrounding modelling programs. The atomic simulation environment (ASE) has very significantly improved my productivity when working with programs like VASP.&lt;/p&gt;&#xA;&lt;p&gt;That said, it doesn't mean that you cannot use python to contribute to serious DFT codes. the best example would be GPAW:&lt;/p&gt;&#xA;&lt;p&gt;developing a DFT program takes a lot of time and when competitors had a headstart of decades you need ot catch up. ~80 % of GPAW are written in python and the very performance critcal parts are written in C. This allows them to regularly ship new versions with significant amounts of new features.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore python can be made very fast via numba, cython (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1385/63&quot;&gt;relevant answer&lt;/a&gt;) or pybind11, but it has some pitfalls. It is not as easy to implement complicated &lt;em&gt;and&lt;/em&gt; performant, data structures in Python as it is in &lt;strong&gt;C++&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It should be noted that I am &lt;em&gt;not&lt;/em&gt; saying you shouldn't learn &lt;strong&gt;Fortran&lt;/strong&gt;. It is a perfectly good choice for a high performance computing language. The big problems Fortran has are that it lacks essential features of modern programming languages, like a package manager and the fact that there are essentially only very large projects. Therefore, it can be difficult to progress after you get the basics down. There are no medium sized projects one could contribute to. There are some recents efforts  to make Fortran more popular again, namely &lt;a href=&quot;https://fortran-lang.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://fortran-lang.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;At the end of the day, it depends on what you make of these languges as any of them are fine to learn.&lt;/p&gt;&#xA;" OwnerUserId="406" LastEditorUserId="63" LastEditDate="2023-07-03T15:32:10.853" LastActivityDate="2023-07-03T15:32:10.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="679" PostTypeId="2" ParentId="495" CreationDate="2020-05-15T20:24:56.140" Score="13" Body="&lt;p&gt;A few materials/simulation boxes I've had some proper trouble with:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;HSE06 + noncollinear magnetism + antiferromagnetism, Vasp noncollinear:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This was a strongly antiferro material (4 Fe atoms, in an up-down-up-down configuration).&lt;/li&gt;&#xA;&lt;li&gt;HSE06 is apparently difficult to converge anyway.&lt;/li&gt;&#xA;&lt;li&gt;Noncollinear magnetism/antiferromagnetism apparently creates problems for any charge density/spin density mixer (or so I've been told/seen). But this was quite bad.&lt;/li&gt;&#xA;&lt;li&gt;Solved with: AMIX = 0.01, BMIX=1e-5, AMIX_MAG=0.01, BMIX_MAG=1e-5, Methfessel-Paxton order 1 smearing of 0.2 eV. Davidson solver (ALGO=Fast). It took ~160 SCF steps, but it &lt;em&gt;did&lt;/em&gt; converge.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Cell with really different a, b, c, GPAW, PW mode:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This was a much simpler, spin-paired, metallic system. However, the&#xA;cell was 5.8 x 5.0 x ~70 angstroms.&lt;/li&gt;&#xA;&lt;li&gt;This happens in general when a cell is really elongated along a particular axis/in general has a very 'non-cubic' shape.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.64.121101&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt;, which I believe is the reference for Quantum Espresso's 'local-TF' charge-density mixing explains (I think) why this happens. Turns out that really large lattice vector (or in general a very 'non-cubic' cell) ill-conditions the charge-mixing problem. This is the precise problem that is addressed in the paper.&lt;/li&gt;&#xA;&lt;li&gt;Since GPAW does not implement the 'local-TF' mixing yet, I solved this by using &lt;code&gt;mixer=Mixer(beta=0.01)&lt;/code&gt;. The convergence is very slow, but again, it &lt;em&gt;did&lt;/em&gt; converge.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A colleague and I discussed the convergence of a (possibly antiferromagnetic) nickel compound (that's about as much I know), Vasp. I don't have many details on this other than it was a similar pain as case #1 above. It took a lot of work and mostly just turning down AMIX and AMIX_MAG.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I recently saw another person attempting to converge a single Ni atom in a box (GPAW, LCAO mode), with magnetic moment set by Hund's rule, and I think the thing actually converged density to a log10-error of &amp;lt; -2.4 (you want to aim for &amp;lt; -4.0). To converge further, they proceeded with a Fermi-Dirac smearing of... 0.5 eV. This was one of the more extreme cases I've seen.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I will keep updating this answer as I see/find more pathological cases, but these are what I have so far.&lt;/p&gt;&#xA;" OwnerUserId="512" LastEditorUserId="512" LastEditDate="2020-05-16T05:46:59.090" LastActivityDate="2020-05-16T05:46:59.090" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="680" PostTypeId="2" ParentId="119" CreationDate="2020-05-16T02:19:40.937" Score="6" Body="&lt;p&gt;For linear scaling both Hamiltonian matrix (&lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;) and density matrix (&lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;) need to be sparse. If either &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; are dense, then the resulting scaling is quadratic &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt;. When both &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; are dense, then the scaling is cubic &lt;span class=&quot;math-container&quot;&gt;$O(N^3)$&lt;/span&gt;. As mentioned above the underlying computational cost is determined by matrix-matrix multiplication.&#xA;For example, to calculate &lt;span class=&quot;math-container&quot;&gt;$C = A * B$&lt;/span&gt; we note that one has to find &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; elements of &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; and each element of &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; requires &lt;span class=&quot;math-container&quot;&gt;$2N$&lt;/span&gt; operations:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C(i,j) = \sum_{k=1}^N  A(i,k) * B(k,j)$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The reduction from cubic to quadratic or linear comes from the assumption that  &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and/or &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; are not dense and so the summation is reduced to some &quot;fixed&quot; number of elements smaller than N or perhaps the structure of C fixes the number of elements. Hence, not all &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; elements are required to be calculated. For interesting problems of materials science, physics, chemistry, it is very difficult to achieve linear scaling because, depending on the choice of basis set representation, one matrix can be dense which kills  linear scaling. Typically, localized orbital basis sets are most promising because they lead to dense Hamiltonian, but for metallic systems the Density matrix becomes delocalized  and dense. You can switch to delocalized orbitals in hope to get sparse density matrix but you will get delocalized, dense hamiltonian matrix.  In practice the linear scaling is only achieved in the so called &quot;biological systems&quot; (such as a box of waters) in which wide band gap leads  to sparse density and hamiltonian matrices. There is a  good paper on this topic: Stefan Godecker, Rev. Mod. Phys.  1998.&lt;/p&gt;&#xA;" OwnerUserId="519" LastEditorUserId="88" LastEditDate="2020-05-16T07:08:00.837" LastActivityDate="2020-05-16T07:08:00.837" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="681" PostTypeId="2" ParentId="308" CreationDate="2020-05-16T03:16:05.647" Score="16" Body="&lt;p&gt;Basically there are two kinds of approaches which may be found in many text books, L-S coupling and j-j coupling.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;L-S coupling means that scalar electronic states (e.g. atomic L-S states and linear molecular Lambda-S states) are calculated first, and then the SO matrix is constructed with the help of 1-e (and optional 2-e) SO integrals. After diagonalizaion, energies of spinor states (atomic J levels and linear Omega states) may be obtained. Most of Q.C. programs like Molpro, Molcas, Orca, and Gamess do SOC in this way.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In j-j coupling, orbitals and spins are combined into spinors (atomic j and linear omega) at the very beginning, so there are no orbitals and scalar electronic states any more. The most representative program is Dirac. In addition, some Q.C. programs can do two-component HF/DFT only, including NWchem (sodft), Turbomole, Gaussian (int=dkh4), and so on. ADF can do j-j coupling DFT also (spinorbit zora), whereas L-S coupling DFT has to be performed through TDDFT.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the perspective of methodology, in addition to L-S coupling and j-j coupling, there are also some intermediate approaches, which do scalar SCF/MCSCF calculatons first but SOC calculations at the post-HF/MCSCF stage. The programs I can think of are Columbus (soci), Cfour (ccsdso), and (maybe) Nooijen's STEOM-CC which is integrated in Orca.&lt;/p&gt;&#xA;" OwnerUserId="521" LastActivityDate="2020-05-16T03:16:05.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="682" PostTypeId="1" AcceptedAnswerId="695" CreationDate="2020-05-16T04:26:41.117" Score="10" ViewCount="378" Body="&lt;p&gt;The efficiency &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; of a parallel calculation is defined as &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E &amp;amp;= \frac{S}{N}, &amp;amp; S &amp;amp;= \frac{T_1}{T_N},&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the speedup and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of workers, and &lt;span class=&quot;math-container&quot;&gt;$T_{1/N}$&lt;/span&gt; is the time for one core, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; cores, respectively.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;By definition the efficiency of a parallel calculation should never be able to exceed 1.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Considering this, I came upon an interesting result in Q-Chem when I was benchmarking the two parallel options: the OpenMP threaded options (-nt) and the message passing interface option (-np) &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/V7x0y.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/V7x0y.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;As can be seen, I am getting an efficiency greater than 1 for -nt processes!&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;All calculations were done with &lt;code&gt;qchem/feb2019/env_intel_2018_parallel&lt;/code&gt; version and were run on the same compute node.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The number of SCF cycles are identical between the two calculations, but the energy and DIIS error is not exactly the same:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The 1 process calculations:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;Cycle       Energy         DIIS Error&#xA; ---------------------------------------&#xA;14    -690.0167217745      3.47E-07 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;the 4,8, etc. calculation process:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;Cycle       Energy         DIIS Error&#xA;---------------------------------------&#xA;14    -690.0167223190      3.49E-07&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Is there an explanation? &lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-05-16T22:11:24.793" LastActivityDate="2020-05-16T22:11:24.793" Title="Why is Q-Chem producing a parallel efficiency greater than 1?" Tags="|q-chem|high-performance-computing|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="683" PostTypeId="1" CreationDate="2020-05-16T05:19:03.583" Score="16" ViewCount="407" Body="&lt;p&gt;My question is specifically related to the molecular energies of Kohn-Sham DFT:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Do eigenvalues in KS-DFT mean anything?&lt;/strong&gt; &lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-05-16T15:09:49.323" LastActivityDate="2020-06-06T19:42:46.470" Title="Do eigenvalues in DFT mean anything?" Tags="|density-functional-theory|kohn-sham|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="684" PostTypeId="2" ParentId="682" CreationDate="2020-05-16T06:07:12.117" Score="9" Body="&lt;p&gt;While I am not completely familiar with all the details in Q-Chem's SCFs, I am aware that there are in fact multiple SCF implementations and multiple implementations for computing two-electron integrals in Q-Chem.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I could therefore imagine that &lt;code&gt;-nt&lt;/code&gt; and &lt;code&gt;-np&lt;/code&gt; triggers different code branches (for all cases but 1 thread, where the same is used). This explains why there is the sudden jump from 1 to 2 for the&lt;code&gt;-nt&lt;/code&gt; plot, but otherwise similar slopes as you increase &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another point to note is that efficiencies beyond &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; are actually possible. This can happen because a couple of reasons. One is that increasing the number of CPUs makes in total also more CPU cache available (which is faster to access than RAM) and overall may change the balance between how much is computed and how much is stored. Since for  modern systems an access to RAM well equals a few thousand FLOPs, this can lead to a gain in performance. Therefore for small problem sizes it can happen that this so-called superlinear speedup makes the parallel efficiency go beyond &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; (see also &lt;a href=&quot;https://cs.stackexchange.com/questions/55433/what-is-meant-by-superlinear-speedup-is-it-possible-to-have-superlinear-speedup&quot;&gt;this computer science thread&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While this could be what happens here, the distinct jump from &lt;span class=&quot;math-container&quot;&gt;$N = 1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$N = 2$&lt;/span&gt; makes me suspect that the observed behaviour is just an artifact of the code used at &lt;span class=&quot;math-container&quot;&gt;$N = 1$&lt;/span&gt; being a lot worse than the code for the &lt;code&gt;-nt&lt;/code&gt; branch.&lt;/p&gt;&#xA;" OwnerUserId="327" LastActivityDate="2020-05-16T06:07:12.117" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="685" PostTypeId="2" ParentId="365" CreationDate="2020-05-16T10:18:49.510" Score="20" Body="&lt;h2&gt;It depends on what you want to do&lt;/h2&gt;&#xA;&lt;p&gt;I think one major question that needs to be asked is &amp;quot;What do you want to do?&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Develop new quantum chemistry codes? Use them more efficiently? Automate data processing? User @taciteloquence Has given a good answer I think.&#xA;Many legacy codes are written in Fortran - newer codes will be typically written in C or C++. I believe there is also a Python project as well as a toolkit tying &amp;quot;things&amp;quot; together written in Python (The Atomic Simulation Environment). So as little as I personally like Python, it is used in the field.&lt;/p&gt;&#xA;&lt;p&gt;To process data, you have two main approaches: Deal with the binary files or deal with the text files.&#xA;I have myself written C++ code to extract and process data from text files.&lt;/p&gt;&#xA;&lt;p&gt;If you have numerical data, it can be processed well in R. I actually started with a mix of C++ and R for extraction and processing but then gravitated to C++ only as it was faster (and I also ended up improving a lot of the underlying workflow structure). Still, I suspect my code &amp;quot;died&amp;quot; when I finished the PostDoc...&lt;/p&gt;&#xA;&lt;p&gt;Another code I wrote (which lead to a recently published paper by a PhD student) was a C++ implementation of solvation models that existed in Fortran already. Why? It enabled &amp;quot;us&amp;quot; to optimise a model and the use of RAM for storing data lead to very significant performance increase. Oh, and I wrote the code to work with ORCA output.&#xA;But in the end, your choice of post-processing language is effectively personal. Use what you like - what your colleagues can use. Be it C++, R, etc.&#xA;For computation-heavy tasks, compiled languages will typically give better performance that interpreted languages. R? Lovely plot and data post processing, but loops are much slower than in C++ and the data structure is limited compared to structs/classes in C++.&#xA;So basically, chose based on interest and maybe based on what the people around you use (with some qualifiers - I would argue that Excel should in many cases not be used...).&lt;/p&gt;&#xA;&lt;p&gt;Something that wasn't touched upon by others: Automation.&#xA;Learn some Bash (or another shell of your choice). My paper on fitting regression coefficients? I built the xyz geometries by hand, but then just ran the calculations using scripts. I did NOT write the input files with the methods by hand.&#xA;A good scripting language will allow you to automate many mundane tasks. Once upon a time I used to write job scheduler scripts by hand... Nowadays I create a script to submit the job which I can call. I spend time figuring it out once but afterwards do not wear out my patience with menial tasks.&#xA;So definitely look into scripting.&lt;/p&gt;&#xA;&lt;p&gt;Though automation can also use more classical programming languages. If you have a set series of steps you wish to carry out. Let me given a rough example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You run a large number of quantum chemistry calculations (optimisations and frequencies).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You use bash to extract the location of all text files&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You hand the list of file paths to a C++ code that extracts the desired data from the output files into a database. This can include further tasks such as identifying non-converged geometries, transition states, etc.&#xA;Your limitation for many data-processing tasks is often your own competency.&#xA;And the best way to get better at it, is to gain experience.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For those interested in the papers I mentioned, I leave you with the DOIs. - In terms of tools, I was using bash, C++ and R.&lt;/p&gt;&#xA;&lt;p&gt;10.1016/j.fluid.2020.112614&lt;/p&gt;&#xA;&lt;p&gt;10.1002/jcc.25763&lt;/p&gt;&#xA;" OwnerUserId="540" LastEditorUserId="540" LastEditDate="2020-06-25T07:50:33.683" LastActivityDate="2020-06-25T07:50:33.683" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="686" PostTypeId="1" CreationDate="2020-05-16T16:11:04.283" Score="12" ViewCount="132" Body="&lt;p&gt;One of the key pillars of scientific method is the reproducibility of scientific results. A 2016 survey by &lt;a href=&quot;https://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970&quot; rel=&quot;noreferrer&quot;&gt;Nature&lt;/a&gt; revealed that many fields in science  suffer from &lt;em&gt;reproducibility crisis&lt;/em&gt;. Lejaeghere et. al&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; studied &lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;noreferrer&quot;&gt;Reproducibility in density functional theory calculations of solids&lt;/a&gt; by calculating equation-of-state data for four classes of DFT implementations, totaling 40 methods. They found that most codes agree very well, with pairwise differences that are comparable to those between different high-precision experiments. However the study was limited to the equation of state calculation and a few materials only.&lt;/p&gt;&#xA;&lt;p&gt;Question: How reproducible are results from materials modelling? Are there any famous results which could not be reproduced?&lt;/p&gt;&#xA;&lt;p&gt;References&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Lejaeghere, Kurt, et al. &amp;quot;Reproducibility in density functional theory calculations of solids.&amp;quot; Science 351.6280 (2016): aad3000.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-10-24T23:59:44.290" Title="How reproducible are results from materials modelling? Are there any notable results which could not be reproduced?" Tags="|density-functional-theory|reference-request|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="687" PostTypeId="2" ParentId="657" CreationDate="2020-05-16T16:36:18.980" Score="10" Body="&lt;p&gt;If VASP is a possibility, then check out this very nice python package by Lucy Whalley: &lt;a href=&quot;https://github.com/lucydot/effmass&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/lucydot/effmass&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Associated paper is Phys. Rev. B 99, 085207 or via &lt;a href=&quot;https://arxiv.org/pdf/1811.02281.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/pdf/1811.02281.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="559" LastActivityDate="2020-05-16T16:36:18.980" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="688" PostTypeId="1" AcceptedAnswerId="1503" CreationDate="2020-05-16T16:45:03.143" Score="9" ViewCount="75" Body="&lt;p&gt;Hybrid DFT methods, where the functional is supplemented with Hartree-Fock exchange, have become increasingly popular due to their low cost and decent accuracy. Double hybrids, which mix in an  MP2 contribution, have also been developed as a way to improve the accuracy. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Has this idea been extended to other Post-SCF methods? For example, one could consider doing coupled cluster or configuration interaction calculations where a DFT wavefunction is used as the primary configuration. If not, is there a major hurdle, technical or theoretical, that prevents this from being done?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-16T17:24:53.760" LastActivityDate="2020-07-10T14:44:00.033" Title="Extended Hybrid Methods" Tags="|density-functional-theory|kohn-sham|coupled-cluster|configuration-interaction|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="689" PostTypeId="1" CreationDate="2020-05-16T16:52:24.517" Score="17" ViewCount="570" Body="&lt;p&gt;In [1], starting with the bosonic Hamiltonian (Eqn. 1) for the dice lattice model with half flux density (with Ahronov-Bohm phases incorporated),&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H=-t\sum_{\langle j,\mu\rangle}(a^\dagger_\mu a_je^{iA_{\mu j}}+\text{h.c.})+\frac{U_\Delta}{2}\sum_{\mu \in \Delta,\nabla}a^\dagger_\mu a_\mu(a^\dagger_\mu a_\mu-1)+\frac{U_*}{2}\sum_{j\in *}a^\dagger_j a_j(a^\dagger_j a_j-1)&#xA;\end{equation}&lt;/span&gt;&#xA;where the form of the Hamiltonian is well understood (which is what we care for, in this question). Let the constants involved be arbitrarily chosen with main focus on the functional form of the operators involved. Single particle spectrum can be easily deduced from the above Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;Further, the authors, in the special regime &lt;span class=&quot;math-container&quot;&gt;$nU_{*/\Delta}/t\ll 1$&lt;/span&gt;, make the lowest flat band approximation leading to the Hamiltonian (Eqn. 2),&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H_{\text{proj}}=\gamma_1\sum_i n_i(n_i-1)+\gamma_2\sum_{\langle i,j \rangle}[n_in_j+(c^\dagger)^2c_j^2+(c_j^\dagger)^2c_i^2]+\gamma_3\sum_{\Delta(i,j,k)}[\sigma^{ij}_{kk}c^\dagger_ic^\dagger_jc_k^2+\sigma^{ik}_{jk}c^\dagger_ic_jn_k+\text{h.c.}]&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\gamma_i$&lt;/span&gt; are some specially chosen numbers and &lt;span class=&quot;math-container&quot;&gt;$n_{\lambda}=a^\dagger_\lambda a_\lambda$&lt;/span&gt; is the number operator for that mode. &lt;span class=&quot;math-container&quot;&gt;$\sigma^{qr}_{st}=\exp [i(A_{q\mu}+A_{r\mu}+A_{\mu s}+A_{\mu t})]$&lt;/span&gt; are the phase factors. This projected Hamiltonan works perfectly fine for the lowest flat-band dynamics but it is not proved how to arrive at it by a projection action. However, by construction it works well enough. Again, we shall only focus on the functional form of the Hamiltonian. My questions are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How to take the lowest band, especially lowest flat-band projection, of a given Hamiltonian in general? I am looking for a matrix projector method.&lt;/li&gt;&#xA;&lt;li&gt;How to show the above with respect to the given research in [1]?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;[1] G. Moller, N. R. Cooper. &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevLett.108.045306&quot; rel=&quot;noreferrer&quot;&gt;Correlated Phases of Bosons in the Flat Lowest Band of the Dice Lattice&lt;/a&gt;.Phys. Rev. Lett. 108 (4), 045306. Jan, 2012.&lt;/p&gt;&#xA;" OwnerUserId="287" LastEditorUserId="7" LastEditDate="2020-07-11T01:32:49.297" LastActivityDate="2021-11-17T23:32:28.590" Title="How to find the projected Hamiltonian for lowest flat-band in general?" Tags="|condensed-matter|model-hamiltonians|effective-hamiltonian|dice-lattice|band-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="690" PostTypeId="1" CreationDate="2020-05-16T17:14:08.043" Score="13" ViewCount="202" Body="&lt;p&gt;This question came to mind while writing another question here  &lt;a href=&quot;https://materials.stackexchange.com/questions/688/extended-hybrid-methods&quot;&gt;Extended Hybrid Methods&lt;/a&gt;, but I felt it was distinct enough to ask separately.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In double hybrids DFT methods, you essentially perform a hybrid DFT calculation (DFT plus Hartree-Fock exchange) and then perform an MP2 calculation using the orbitals from the hybrid calculation. The energies from both these calculations are weighted and combined to give a final energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm curious about this last step; beyond fitting, are there heuristics that can be used to set the correlation coefficient for a particular type of problem? Obviously there is no exact answer for picking how much correlation comes the DFT part and how much from MP2, but what sort of considerations go into that decision? I know for regular hybrids different ratios of exchange are chosen depending on the problem they hope to address with that functional. For example, the original PBE0 paper makes an argument based on perturbation theory that ~1/4 HF exchange should be the best for atomization energies. I was wondering if there were similar physical rationale for setting the correlation ratio for double hybrids.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-04T04:04:26.117" LastActivityDate="2020-06-10T21:50:44.383" Title="Physically motivated double hybrid DFT?" Tags="|density-functional-theory|kohn-sham|correlation-energy|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="691" PostTypeId="1" AcceptedAnswerId="830" CreationDate="2020-05-16T18:00:58.750" Score="8" ViewCount="190" Body="&lt;p&gt;&lt;a href=&quot;https://materials.stackexchange.com/a/596/5&quot;&gt;This answer&lt;/a&gt; refers to a paper that calculates &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\textrm{electronic}} + \Delta E_{\textrm{vibrational}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, what if I had enough computing power, and I wanted to get the &lt;strong&gt;exact&lt;/strong&gt; value for &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt;: Would I include a &quot;rotational&quot; term too? What about &quot;torsional&quot; or even fine-structure?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are all the terms that would be included, if we had enough computing power and desired the accuracy?&lt;/p&gt;&#xA;" OwnerUserId="29" LastEditorUserId="181" LastEditDate="2020-05-18T06:13:59.073" LastActivityDate="2020-05-18T06:20:01.210" Title="What contributes to the total enthalpy of a system?" Tags="|thermodynamics|statistical-thermodynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="692" PostTypeId="1" AcceptedAnswerId="758" CreationDate="2020-05-16T18:07:08.710" Score="9" ViewCount="523" Body="&lt;p&gt;Similar to &lt;a href=&quot;https://materials.stackexchange.com/questions/414/is-there-a-free-package-with-robust-casscf-functionality&quot;&gt;this question&lt;/a&gt; which asks for each answer to provide one software that can do CASSCF: I am interested in software that can do integrals, SCF (Hartree-Fock), and the integral transformation, with more than one CPU. &lt;strong&gt;Do any of these programs allow also for use with more than one node?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The software can be commercial or open-source.&lt;/p&gt;&#xA;" OwnerUserId="29" LastEditorUserId="5" LastEditDate="2021-02-05T18:46:51.630" LastActivityDate="2021-02-05T21:05:12.967" Title="What programs can do electron integrals and SCF calculations with more than one CPU?" Tags="|software|one-topic-per-answer|high-performance-computing|self-consistent-field|integrals|" AnswerCount="4" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="693" PostTypeId="1" CreationDate="2020-05-16T18:16:13.680" Score="17" ViewCount="925" Body="&lt;p&gt;I have heard that TURBOMOLE works extremely fast (even compared to MOLPRO) with def2 basis sets, but is slow if Dunning basis sets are used.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is it about def2 basis sets that allows calculations to be so fast in TURBOMOLE, and why is this unique to def2 basis sets? Why can't we get similar speed with Dunning basis sets?&lt;/p&gt;&#xA;" OwnerUserId="29" LastActivityDate="2021-01-28T11:51:01.907" Title="Understanding the difference between Dunning and Karlsruhe basis sets" Tags="|basis-sets|molpro|turbomole|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="694" PostTypeId="2" ParentId="658" CreationDate="2020-05-16T20:52:13.090" Score="7" Body="&lt;p&gt;Nice question!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My answer will be based on the optical response that can be obtained with the Quantum ESPRESSO package, not the Photoluminescence specifically, but the responses can be correlated. The absorption spectrum can be correlated to the photoluminescence one since it preserves the selection rules from inter and intra-band transitions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Quantum ESPRESSO has two ways for evaluating optical properties: the codes epsilon.x and turbo_eels.x. The former evaluates the frequency-dependent dielectric function, returning its real (&lt;span class=&quot;math-container&quot;&gt;$\epsilon_1$&lt;/span&gt;) and imaginary (&lt;span class=&quot;math-container&quot;&gt;$\epsilon_2$&lt;/span&gt;) parts. The latter also returns the dielectric function together with the frequency-dependent susceptibility (&lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt;) and the imaginary part of the inverse of the complex dielectric function (&lt;span class=&quot;math-container&quot;&gt;$Im(\epsilon^{-1})$&lt;/span&gt;), which is related to inelastic X-ray spectroscopy (IXS) and to electron energy loss spectroscopy (EELS).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the dielectric function, the absorption spectrum can be obtained by evaluating the real (&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) and imaginary (&lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;) parts of the refractive index  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$n(\hbar\omega)=\left[ \frac{1}{2}\left(\left(\epsilon_1^2 +\epsilon_2^2  \right)^{\frac{1}{2}}  + \epsilon_1\right)\right]^{\frac{1}{2}}$&lt;/span&gt;,&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$k(\hbar\omega)=\left[ \frac{1}{2}\left(\left(\epsilon_1^2 +\epsilon_2^2  \right)^{\frac{1}{2}}  - \epsilon_1\right)\right]^{\frac{1}{2}}$&lt;/span&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha(\hbar\omega)= \frac{2\omega}{c}k$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The epsilon.x code requires the &lt;em&gt;self-consistent field&lt;/em&gt; (SCF) calculation to be performed with Norm-conserving pseudopotentials (it is not implemented for Ultrasoft ones), with very-well converged ground stated energy, with thresholds bellow &lt;span class=&quot;math-container&quot;&gt;$10^{-10}$&lt;/span&gt;Ry. For metals, due to the occupations of the bands, a &quot;fake-temperature&quot; like smearing parameter is required and the dielectric response presents a weak-dependence on it and should be optimized. The epsilon.x code does not takes into account electron-electron interaction, which can shift the optical response.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The turbo_eels.x code, though, takes into account electron-electron interaction and can be used with Ultrasoft-pseudopotentials, requiring minor plane-waves cut off. However, the dielectric response should be optimized against the k-points sampling and the number of iterations. It is based on the optical or electronic transferred momentum &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt;, allowing for &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;-dependent responses (where &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; is the incidence angle) such as the reflectivity&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$R(\hbar\omega)=\frac{(n_0 - n)^2 + k^2}{(n_0 + n)^2 + k^2}$&lt;/span&gt;,&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$n_0$&lt;/span&gt; is the refractive index of the incident medium.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As a final note, &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S163107050800128X&quot; rel=&quot;noreferrer&quot;&gt;this reference&lt;/a&gt; shows the results of luminescence and absorption responses for silicon using Quantum ESPRESSO.&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="389" LastEditDate="2020-05-16T21:04:35.833" LastActivityDate="2020-05-16T21:04:35.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="695" PostTypeId="2" ParentId="682" CreationDate="2020-05-16T21:03:06.557" Score="8" Body="&lt;p&gt;Yes, this is correct explanation. There are three SCF codes and two integral libraries and which ones are executed depends on the job parameters (single core, multicore, multi-node). If accurate scaling benchmarks are desired, I would use execution with 2 threads as the base. One should also pay attention to the current defaults re: integral and scf engines - these can change with updates. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The energy difference is smaller than the specified convergence threshold, so there is nothing to worry about. The differences smaller than convergence threshold are perfectly normal for different modes of execution.&lt;/p&gt;&#xA;" OwnerUserId="517" LastActivityDate="2020-05-16T21:03:06.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="696" PostTypeId="1" CreationDate="2020-05-16T21:19:55.903" Score="13" ViewCount="293" Body="&lt;p&gt;While DFT calculations are a key step in a simulation workflow, generally more steps are required to obtain a meaningful result. This can include pre/post-processing of results to e.g. compute additional properties, rerun a calculation with a different basis/geometry, or cut out a cluster from a larger structure. This processing often has to be repeated for many different simulations, almost like a cake-recipe. Therefore, making scripts is a mandatory short-cut. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, making them is, in general, a fairly time-consuming task. To my knowledge, there are paid tools like the Virtual Nanolab, with drag and drop options that facilitate the process. Are there free similar tools? Or at least is there a repository where we can post our own scripts and get scripts from other people?   &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="7" LastEditDate="2020-05-20T16:06:32.407" LastActivityDate="2020-06-01T11:48:22.937" Title="Is there a repository for DFT pre/postprocessing scripts?" Tags="|density-functional-theory|software|open-source|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="697" PostTypeId="2" ParentId="584" CreationDate="2020-05-16T21:23:37.037" Score="12" Body="&lt;p&gt;I think the way this question is asked is a little too simplistic. In order to execute a computational project, there is always more than one calculation required. Even if you are happy with the lowest level of theory (say, B3LYP/6-31G*), it does not mean that any package that lists B3LYP in the list of the available features would be useful. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Possible caveats:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The method is implemented, but the convergence is not robust. So your jobs fail because of poor underlying algorithms of SCF solvers;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The method is implemented, but the code is ineffective. You need to spend more compute resources, wait longer, and increase your carbon footprint (not a joke! Calculations use lots of electricity);&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The package claims the method exists, but the implementation is buggy and gives wrong numbers; &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You can compute energy, but there are no analytic gradients or frequencies;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You can compute energies and optimize structures, but there are no other features -- like various properties calculations that are needed for answering a research question. To give a few examples: Solvent effects, QM/MM capabilities, spin-orbit couplings, multipole moments, wave-function analysis, NMR, IR/Raman intensities. The list can go on forever. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;It takes many years to build and maintain a software package that is mature enough to be considered an adequate research tool. You may lose a lot of time and money by going after &quot;free stuff&quot;. &lt;/p&gt;&#xA;" OwnerUserId="517" LastEditorUserId="5" LastEditDate="2020-05-16T22:04:24.220" LastActivityDate="2020-05-16T22:04:24.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="698" PostTypeId="2" ParentId="657" CreationDate="2020-05-16T21:43:05.393" Score="7" Body="&lt;p&gt;Effective mass is related to the electronic band curvature along a specific direction across the momentum space. For semiconductors, in general, it is worth knowing the effective mass around the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; high-symmetry point (&lt;span class=&quot;math-container&quot;&gt;$\Gamma \equiv \vec k=(0,0,0)$&lt;/span&gt;), for both the highest occupied band (the valence band) and the lowest unoccupied band (the conduction band). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Being the effective mass the band curvature, it is proportional to the second derivative of the energy band with respect to the wave vector k. Another possibility is to fit the electronic band with the parabolic dispersion as shown in the question&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E(k) = E_0 + \frac{\hbar^2 k^2}{2m^*}$&lt;/span&gt;,&lt;/p&gt;&#xA;&#xA;&lt;p&gt;however, you should be aware of the system under simulation if it presents parabolic bands. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I know the &lt;em&gt;&lt;a href=&quot;https://docs.quantumwise.com/tutorials/effective_mass/effective_mass.html&quot; rel=&quot;noreferrer&quot;&gt;Virtual Nano Lab&lt;/a&gt;&lt;/em&gt; software does the calculation after plotting the band-structure. Apart from my own script (which is a very crude python program), I don't know about free alternatives.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-05-16T21:43:05.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="699" PostTypeId="2" ParentId="683" CreationDate="2020-05-16T21:53:30.403" Score="3" Body="&lt;p&gt;Direct answer: it means the energy of the KS lowest-energetic orbital minimized for a specific Exchange-Correlation functional. If eventually (I don't know how to verify!) the KS lowest-energetic orbital retrieves the system orbital, it means the ground state energy of the system. To my knowledge, we have to be interested in the changes in such energy, not its value. &lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-05-16T21:53:30.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="700" PostTypeId="1" AcceptedAnswerId="750" CreationDate="2020-05-16T22:10:25.837" Score="23" ViewCount="2577" Body="&lt;p&gt;In order to do DFT calculations of metallic alloys, the start point is a supercell, whose atoms are changed to match the desired stoichiometry. Gold and Silver, for example, both have FCC structure. In Quantum-ESPRESSO, we can both tell to the code the &lt;em&gt;Bravais lattice&lt;/em&gt; (&lt;em&gt;ibrav&lt;/em&gt; parameter) and specify only one atom position ( &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt; for an FCC cell ), or use a cubic lattice indicating four atoms positions ( &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)a$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0,0.25,0.25)a$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0.25,0,0.25)a$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$(0,0.25,0.25)a$&lt;/span&gt;, in terms of the lattice parameter &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;). In theory, the responses should be the same, and the GND energies are retrieved to be equal. However, the band structure for the four-atoms cell is way denser than the single-atom cell. Why does this occur? &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-16T23:16:26.780" LastActivityDate="2023-05-18T00:37:29.843" Title="Why is the band structure of a supercell more dense than for simple cell?" Tags="|density-functional-theory|quantum-espresso|periodic-system|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="701" PostTypeId="5" CreationDate="2020-05-16T22:19:35.967" Score="0" Body="&lt;p&gt;ORCA is a flexible, efficient and easy-to-use general purpose tool for quantum chemistry with specific emphasis on spectroscopic properties of open-shell molecules. It features a wide variety of standard quantum chemical methods ranging from semiempirical methods to DFT to single- and multireference correlated ab initio methods. It can also treat environmental and relativistic effects.&lt;/p&gt;&#xA;&lt;p&gt;Due to the user-friendly style, ORCA is considered to be a helpful tool not only for computational chemists, but also for chemists, physicists and biologists that are interested in developing the full information content of their experimental data with help of calculations.&lt;/p&gt;&#xA;&lt;p&gt;Description source: &lt;a href=&quot;https://www.kofo.mpg.de/en/research/service-departements/orca&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.kofo.mpg.de/en/research/service-departements/orca&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2020-07-09T17:48:32.667" LastActivityDate="2020-07-09T17:48:32.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="702" PostTypeId="4" CreationDate="2020-05-16T22:19:35.967" Score="0" Body="For questions about (or involving) the ORCA electronic-structure package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-16T22:19:35.967" LastActivityDate="2020-05-16T22:19:35.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="703" PostTypeId="5" CreationDate="2020-05-16T22:20:18.873" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-16T22:20:18.873" LastActivityDate="2020-05-16T22:20:18.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="704" PostTypeId="4" CreationDate="2020-05-16T22:20:18.873" Score="0" Body="For questions about (or involving) the MOLPRO electronic-structure package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-16T22:20:18.873" LastActivityDate="2020-05-16T22:20:18.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="705" PostTypeId="5" CreationDate="2020-05-16T23:09:14.997" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:09:14.997" LastActivityDate="2020-05-16T23:09:14.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="706" PostTypeId="4" CreationDate="2020-05-16T23:09:14.997" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:09:14.997" LastActivityDate="2020-05-16T23:09:14.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="707" PostTypeId="5" CreationDate="2020-05-16T23:10:27.633" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:10:27.633" LastActivityDate="2020-05-16T23:10:27.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="708" PostTypeId="4" CreationDate="2020-05-16T23:10:27.633" Score="0" Body="Questions related to corrections due to dispersion effects in matter modeling." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-06-26T21:57:02.543" LastActivityDate="2020-06-26T21:57:02.543" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="709" PostTypeId="5" CreationDate="2020-05-16T23:12:10.887" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:12:10.887" LastActivityDate="2020-05-16T23:12:10.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="710" PostTypeId="4" CreationDate="2020-05-16T23:12:10.887" Score="0" Body="Questions related to Bardeen–Cooper–Schrieffer theory of superconductivity in the context of materials modeling. " OwnerUserId="36" LastEditorUserId="88" LastEditDate="2020-05-17T03:27:00.847" LastActivityDate="2020-05-17T03:27:00.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="711" PostTypeId="5" CreationDate="2020-05-16T23:53:06.643" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory#Classical_density_functional_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Density_functional_theory#Classical_density_functional_theory&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2022-10-07T18:30:15.887" LastActivityDate="2022-10-07T18:30:15.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="712" PostTypeId="4" CreationDate="2020-05-16T23:53:06.643" Score="0" Body="For questions about CDFT (current DFT) or &quot;classical DFT&quot; even though they are unrelated." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2022-10-07T18:30:48.620" LastActivityDate="2022-10-07T18:30:48.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="713" PostTypeId="5" CreationDate="2020-05-16T23:54:40.807" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:54:40.807" LastActivityDate="2020-05-16T23:54:40.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="714" PostTypeId="4" CreationDate="2020-05-16T23:54:40.807" Score="0" Body="Questions related to Magnetic-Field Density-Functional Theory (BDFT)." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T00:19:24.007" LastActivityDate="2020-05-17T00:19:24.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="715" PostTypeId="5" CreationDate="2020-05-16T23:58:05.970" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-16T23:58:05.970" LastActivityDate="2020-05-16T23:58:05.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="716" PostTypeId="4" CreationDate="2020-05-16T23:58:05.970" Score="0" Body="Questions related to the lattice dynamics of solids." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T03:28:19.927" LastActivityDate="2020-05-17T03:28:19.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="717" PostTypeId="5" CreationDate="2020-05-17T00:09:27.623" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:09:27.623" LastActivityDate="2020-05-17T00:09:27.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="718" PostTypeId="4" CreationDate="2020-05-17T00:09:27.623" Score="0" Body="Questions relating to phonon dispersions - the relationship between the phonon frequency and its wave vector." OwnerUserId="36" LastEditorUserId="792" LastEditDate="2020-06-15T02:33:10.667" LastActivityDate="2020-06-15T02:33:10.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="719" PostTypeId="5" CreationDate="2020-05-17T00:22:24.043" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:22:24.043" LastActivityDate="2020-05-17T00:22:24.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="720" PostTypeId="4" CreationDate="2020-05-17T00:22:24.043" Score="0" Body="For questions about (or involving) reduced density matrices." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-17T01:16:03.047" LastActivityDate="2020-05-17T01:16:03.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="721" PostTypeId="5" CreationDate="2020-05-17T00:26:15.777" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:26:15.777" LastActivityDate="2020-05-17T00:26:15.777" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="722" PostTypeId="4" CreationDate="2020-05-17T00:26:15.777" Score="0" Body="Questions about the molecular simulation program CHARMM (Chemistry at HARvard Macromolecular Mechanics). CHARMM primarily targets biological systems including peptides and proteins, but also finds broad applications for inorganic materials with applications in materials design." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T07:01:24.583" LastActivityDate="2020-05-17T07:01:24.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="723" PostTypeId="5" CreationDate="2020-05-17T00:27:09.743" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:27:09.743" LastActivityDate="2020-05-17T00:27:09.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="724" PostTypeId="4" CreationDate="2020-05-17T00:27:09.743" Score="0" Body="Questions concerning NMR in relation to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T07:00:39.800" LastActivityDate="2020-05-17T07:00:39.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="725" PostTypeId="5" CreationDate="2020-05-17T00:28:02.817" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:28:02.817" LastActivityDate="2020-05-17T00:28:02.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="726" PostTypeId="4" CreationDate="2020-05-17T00:28:02.817" Score="0" Body="Questions concerning diffraction in materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T09:06:29.847" LastActivityDate="2020-05-17T09:06:29.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="727" PostTypeId="5" CreationDate="2020-05-17T00:31:04.427" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:31:04.427" LastActivityDate="2020-05-17T00:31:04.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="728" PostTypeId="4" CreationDate="2020-05-17T00:31:04.427" Score="0" Body="Questions about electron diffraction in materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T07:00:50.060" LastActivityDate="2020-05-17T07:00:50.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="729" PostTypeId="5" CreationDate="2020-05-17T00:31:48.463" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:31:48.463" LastActivityDate="2020-05-17T00:31:48.463" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="730" PostTypeId="4" CreationDate="2020-05-17T00:31:48.463" Score="0" Body="Questions regarding periodic boundary conditions in materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T03:27:13.923" LastActivityDate="2020-05-17T03:27:13.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="731" PostTypeId="5" CreationDate="2020-05-17T00:33:49.600" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T00:33:49.600" LastActivityDate="2020-05-17T00:33:49.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="732" PostTypeId="4" CreationDate="2020-05-17T00:33:49.600" Score="0" Body="Questions about cuprates. They are especially involved in high-temperature superconductivity." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-17T04:20:01.373" LastActivityDate="2020-05-17T04:20:01.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="733" PostTypeId="5" CreationDate="2020-05-17T01:06:38.617" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:06:38.617" LastActivityDate="2020-05-17T01:06:38.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="734" PostTypeId="4" CreationDate="2020-05-17T01:06:38.617" Score="0" Body="Questions related to DFT+U, where U is an extra term involving the Hubbard potential." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-12-30T14:46:40.657" LastActivityDate="2020-12-30T14:46:40.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="735" PostTypeId="5" CreationDate="2020-05-17T01:07:49.113" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:07:49.113" LastActivityDate="2020-05-17T01:07:49.113" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="736" PostTypeId="4" CreationDate="2020-05-17T01:07:49.113" Score="0" Body="Questions involving catalysis - the process of increasing the rate of a chemical reaction by adding a substance which is not consumed in the catalyzed reaction and can continue to act repeatedly." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T07:01:21.600" LastActivityDate="2020-05-17T07:01:21.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="737" PostTypeId="5" CreationDate="2020-05-17T01:08:27.837" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:08:27.837" LastActivityDate="2020-05-17T01:08:27.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="738" PostTypeId="4" CreationDate="2020-05-17T01:08:27.837" Score="0" Body="Questions related to spin models wrt materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T09:06:26.907" LastActivityDate="2020-05-17T09:06:26.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="739" PostTypeId="5" CreationDate="2020-05-17T01:12:56.147" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:12:56.147" LastActivityDate="2020-05-17T01:12:56.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="740" PostTypeId="4" CreationDate="2020-05-17T01:12:56.147" Score="0" Body="Questions related to the ab initio quantum chemistry software package Q-Chem. Q-Chem includes DFT/HF calculations as well as high level post-HF correlation methods." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T07:00:47.310" LastActivityDate="2020-05-17T07:00:47.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="741" PostTypeId="5" CreationDate="2020-05-17T01:18:34.647" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:18:34.647" LastActivityDate="2020-05-17T01:18:34.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="742" PostTypeId="4" CreationDate="2020-05-17T01:18:34.647" Score="0" Body="Questions relating to VESTA (Visualization for Electronic and Structural Analysis). VESTA is a 3D visualization program for structural models, electron/nuclear densities, and crystal morphologies." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-17T04:19:14.570" LastActivityDate="2020-05-17T04:19:14.570" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="743" PostTypeId="2" ParentId="646" CreationDate="2020-05-17T01:19:04.140" Score="7" Body="&lt;p&gt;A common approach for generating the starting model is the method of Wooten, Winer, and Weaire [1]. The WWW algorithm is a bond switching Monte Carlo approach: a Monte Carlo move is the exchange of two bonds, followed by a structural relaxation (either MD or MC of the newly connected structure). In the case of silicon, you would start from a large cell of diamond cubic Si, and go through a simulated annealing procedure. To generate a starting model of amorphous silica (SiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;), the completed model of amorphous Si can be decorated with oxygen atoms at the midpoints of the Si--Si bonds, then run through a structural relaxation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The quench-from-the-melt molecular dynamics approach has been rather successful; however, struggles more with a limited box size for the structural solution [2]. Regardless of approach, these starting structural solutions are compared against the pair distribution function (attained from a total scattering experiment) for verification. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the resulting models, &lt;em&gt;ab initio&lt;/em&gt; electronic structure methods can be used to calculate properties of interest. A modern use of these methods with amorphous metal-organic frameworks has been accomplished with zinc imidazolate [3].&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;F. Wooten, K. Winer, D. Weaire, &lt;em&gt;Phys. Rev. Lett.&lt;/em&gt; &lt;strong&gt;54&lt;/strong&gt;, 1392 (1985).&lt;/li&gt;&#xA;&lt;li&gt;A. Tilocca, &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;139&lt;/strong&gt;, 114501 (2013).&lt;/li&gt;&#xA;&lt;li&gt;P. Adhikari, &lt;em&gt;J. Phys. Chem. C&lt;/em&gt; &lt;strong&gt;120&lt;/strong&gt;, 15362 (2016).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="546" LastEditorUserId="5" LastEditDate="2020-05-17T01:22:35.580" LastActivityDate="2020-05-17T01:22:35.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="744" PostTypeId="5" CreationDate="2020-05-17T01:20:57.277" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T01:20:57.277" LastActivityDate="2020-05-17T01:20:57.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="745" PostTypeId="4" CreationDate="2020-05-17T01:20:57.277" Score="0" Body="Questions concerning crystallography, the science of determining the arrangement of atoms in crystalline solids." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-17T04:19:24.133" LastActivityDate="2020-05-17T04:19:24.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="747" PostTypeId="2" ParentId="607" CreationDate="2020-05-17T01:57:29.293" Score="9" Body="&lt;p&gt;I experienced&lt;sup&gt;[1]&lt;/sup&gt; about 5-10 times speedup with &lt;a href=&quot;https://gitlab.com/QEF/q-e-gpu/-/wikis/home&quot; rel=&quot;nofollow noreferrer&quot;&gt;GPU accelerated Quantum Espresso&lt;/a&gt; on Tesla V100 32 Gb compared with &lt;a href=&quot;https://ark.intel.com/content/www/us/en/ark/products/186604/intel-core-i7-9700k-processor-12m-cache-up-to-4-90-ghz.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Intel Core &lt;strong&gt;i7 9700K&lt;/strong&gt;&lt;/a&gt; processor with 8 cores and 32 Gb RAM. The above mentioned system's volume was about 125 cubic Angstroms, it had about 19 atoms, 5 k-points, &lt;code&gt;ecutwfc = 80 Ry&lt;/code&gt;, &lt;code&gt;ecutrho = 320 Ry&lt;/code&gt;. 24 SCF iterations took 54 seconds with GPU, and sadly I do not have timings for CPU-only calculations.&#xA;It took some efforts to build GPU version. It is still in beta version, but I didn't face any bugs. So it is reasonable to expect GPU acceleration in the nearest major release.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;References:&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Mikhail A. Syroeshkin et al. 2‐Carboxyethylgermanium sesquioxide as a promising anode material for Li‐ion batteries. &lt;em&gt;Chemistry Europe&lt;/em&gt;, &lt;strong&gt;2020&lt;/strong&gt;,&lt;a href=&quot;https://doi.org/10.1002/cssc.202000852&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1002/cssc.202000852&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="277" LastEditorUserId="52" LastEditDate="2020-05-17T21:31:35.250" LastActivityDate="2020-05-17T21:31:35.250" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="748" PostTypeId="2" ParentId="645" CreationDate="2020-05-17T02:51:59.627" Score="11" Body="&lt;p&gt;You can tell if a Hamiltonian is sign-free by looking at it in the form that it is handed to you. If the Hamiltonian is real and the off-diagonals are non-positive then it is Stoquastic (which is sign-free). Moreover, every Hamiltonian is sign-free if you don't care about the computational complexity of transforming it: In the basis that it is diagonal, the diagonal is real and all the off diagonals are zero and the Hamiltonian is Stoquastic and sign-free.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The issue often is, and that is what Stephen Jordan points out as well, that the Hamiltonian in the original form may not seem to be Stoquastic yet it might be if you do a small amount of work (say local transformations or an efficient poly-time algorithm). It is hard to decide whether a non-stoquastic looking Hamiltonian is Stoquastic IF one allows for some SMALL amount of computation to transform it.&lt;/p&gt;&#xA;" OwnerUserId="578" LastActivityDate="2020-05-17T02:51:59.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="749" PostTypeId="2" ParentId="696" CreationDate="2020-05-17T02:56:56.940" Score="14" Body="&lt;p&gt;There are numerous free tools that can do this with command-line based calls to the underlying codes, from the venerable 'make' to more modern alternatives like 'DoIt' and 'snakemake'. A lot of these 'workflow systems' seem to be used in the bioinformatics community.&#xA;For a visually-edited 'blocks and wires' approach, perhaps KNIME (assuming a free version is still available)? . You would most likely still have to write your own blocks though, unless the KNIME community has a repository of suitable DFT components.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You might want to also consider ASE (Atomic Simulation Environment)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="577" LastActivityDate="2020-05-17T02:56:56.940" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="750" PostTypeId="2" ParentId="700" CreationDate="2020-05-17T05:00:03.537" Score="25" Body="&lt;p&gt;What you are referring to is called &lt;em&gt;band folding&lt;/em&gt;.  Remember we are plotting the band structure in the reciprocal space. As  the  size  of  the  cell  in real space increases (eg: when you make a super cell), the first Brillouin zone in reciprocal space  shrinks  and  more  lines  populate  the  band  structure resulting from folding back of lines at the boundaries.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YAPpc.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YAPpc.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The figure&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; illustrates band folding in the super cell calculations: (a) band structure of a 2D one-band first- neighbor tight-binding model, (b) the same obtained from a 4x4 super-cell calculation, and (c) the same obtained from a 16x16 super-cell calculation. Panel (d) shows the DOS&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another figure&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt; to visualize band folding in 1D&#xA;&lt;a href=&quot;https://i.stack.imgur.com/FUSo7.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FUSo7.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;There are many tools available to &lt;em&gt;unfold&lt;/em&gt; the band structure.&lt;/strong&gt; Here I list a few&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/band-unfolding/bandup&quot; rel=&quot;noreferrer&quot;&gt;BandUP&lt;/a&gt;: Band Unfolding code for Plane-wave based calculations available for VASP, Quantum Espresso, ABINIT and CASTEP&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://romerogroup.github.io/pyprocar/unfold.html&quot; rel=&quot;noreferrer&quot;&gt;pyPROCAR&lt;/a&gt; offers a utility to unfold bands for VASP&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/ab6e8e&quot; rel=&quot;noreferrer&quot;&gt;Band unfolding made simple&lt;/a&gt;&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt; by May et. al implementation for SIESTA.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://bitbucket.org/bonfus/unfold-x/src/master/&quot; rel=&quot;noreferrer&quot;&gt;unfold-x&lt;/a&gt; Tool to unfold the band structure of a supercell DFT simulation to a larger Brillouin zone based on QuantumESPRESSO&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ku, Wei, Tom Berlijn, and Chi-Cheng Lee. &amp;quot;Unfolding first-principles band structures.&amp;quot; Physical review letters 104.21 (2010): 216401.&lt;/li&gt;&#xA;&lt;li&gt;Yang, Shuo-Ying, et al. &amp;quot;Symmetry demanded topological nodal-line materials.&amp;quot; Advances in Physics: X 3.1 (2018): 1414631.&lt;/li&gt;&#xA;&lt;li&gt;Mayo, Sara G., Felix Yndurain, and Jose M. Soler. &amp;quot;Band unfolding made simple.&amp;quot; Journal of Physics: Condensed Matter 32.20 (2020): 205902.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="6055" LastEditDate="2023-05-18T00:37:29.843" LastActivityDate="2023-05-18T00:37:29.843" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="751" PostTypeId="1" AcceptedAnswerId="777" CreationDate="2020-05-17T07:55:30.477" Score="23" ViewCount="1301" Body="&lt;p&gt;How does one introduce the possibility of breaking a bond in a molecule during MD simulation?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I only found the cases when we just introduce the harmonic potential &lt;span class=&quot;math-container&quot;&gt;$U_{ij} = \frac{1}{2}k(r_i - r_j)^2$&lt;/span&gt; for atoms in a molecule or introduce an additional equation restricting the length of a bond during simulaton.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nevertheless, it is still not clear for me how we can take into account the breaking bond result?&lt;/p&gt;&#xA;" OwnerUserId="584" LastEditorUserId="584" LastEditDate="2020-05-17T13:20:09.693" LastActivityDate="2020-05-23T02:10:54.307" Title="Simulating breaking bonds in molecular dynamics" Tags="|molecular-dynamics|intermolecular-forces|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="752" PostTypeId="2" ParentId="686" CreationDate="2020-05-17T07:55:57.627" Score="9" Body="&lt;p&gt;Yes, I can think of a few (non-famous) cases in the literature where results could not be reproduced, but this lack of reproducibility usually comes from omission of details about the computations in the original publications. If you do the same calculation with the same method, you should always get the same results, but if you don't know what exactly was originally calculated, you may get somewhat different results. For instance, for adsorption energies and activation energies of surface caculations, the super cell size matters, but it is not usually reported in the literature for some reason.&lt;/p&gt;&#xA;" OwnerUserId="583" LastActivityDate="2020-05-17T07:55:57.627" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="753" PostTypeId="2" ParentId="525" CreationDate="2020-05-17T08:10:55.500" Score="2" Body="&lt;p&gt;The Heisenberg formalism is often used to describe the interaction between molecules adsorbed on a surface (&lt;strong&gt;2D&lt;/strong&gt;) using a cluster expansion. This has nothing to do with magnetism, but the mathematical framework is suitable for this kind of problem. Please take a look at &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4840395&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nielsen et al. J. Chem. Phys. 139 (2013) 224706&lt;/a&gt;. The application of the Heisenberg formalism is shown in detail in the supplementary material.&lt;/p&gt;&#xA;" OwnerUserId="583" LastEditorUserId="583" LastEditDate="2020-05-17T12:52:09.887" LastActivityDate="2020-05-17T12:52:09.887" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="754" PostTypeId="2" ParentId="683" CreationDate="2020-05-17T08:13:16.737" Score="14" Body="&lt;p&gt;This is a very interesting question and to the best of my knowledge there is not yet a conclusive answer. As the chemistry stackexchange threads linked by @Tyberius already state Kohn-Sham orbital energies and Kohn-Sham orbitals are often used in the chemistry community to interpret computational findings, because empirically this works ok.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But there are problems. For example, there is no guarantee that the lowest-energy Kohn-Sham solution is actually the one in which the lowest-energy orbitals are occupied (i.e. there is no reason for the Aufbau principle to hold for Kohn-Sham). And there are counterexamples [1]. Additionally for neutral and negatively-charged systems, there is no reason for the existence of HOMO-LUMO excitations and in fact already for simple cases like Helium one can prove that they don't exist [2] (in this case for LDA). This is in contrast to for example the related Hartree-Fock problem, where there always has to be a HOMO-LUMO gap [3].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With there results in mind, I would say that in general it is far-fetched to directly give KS orbitals a physical meaning. But, people have made efforts to design specific functionals or schemes, which correct on top of the orbital energies based on arguments from the derivative discontinuity. These amount to give results in agreement with ionisation potentials or electron affinites [4] and therefore could suggest that there is more to it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So as always in physics, if you check your model applies with a higher-level theory, you might get away with using Kohn-Sham orbital energies and give them a physical interpretation, but there are definitely edge cases where this is not justified.&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;[1] Adi Makmal, Stephan Kümmel and Leeor Kronik Phys. Rev. A &lt;strong&gt;83&lt;/strong&gt;, 062512. DOI &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.83.062512&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRevA.83.062512&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2] Gero Friesecke, Benedikt Graswald arXiv:1907.00064 (&lt;a href=&quot;https://arxiv.org/pdf/1907.00064&quot; rel=&quot;noreferrer&quot;&gt;pdf&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[3] Volker Bach, Elliott H. Lieb, Michael Loss and Jan Philip Solovej&#xA;Phys. Rev. Lett. &lt;strong&gt;72&lt;/strong&gt;, 2981. DOI &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.72.2981&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRevLett.72.2981&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[4] Andrew M. Teale, Frank De Proft, and David J. Tozer J. Chem. Phys. &lt;strong&gt;129&lt;/strong&gt;, 044110 (2008). DOI &lt;a href=&quot;https://10.1063/1.2961035&quot; rel=&quot;noreferrer&quot;&gt;10.1063/1.2961035&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="327" LastActivityDate="2020-05-17T08:13:16.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="755" PostTypeId="2" ParentId="163" CreationDate="2020-05-17T08:29:34.867" Score="14" Body="&lt;p&gt;One important property of atom-centered basis sets is that electrons can only be localized on atoms. This is a problematic property when modeling solid systems with defects. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For instance, at a color center, an electron is localized at a vacancy site. How can you model this with atom-centered basis sets? You have place a ghost atom at the vacancy site, which means you place an empty basis set without nucleus at the vacancy, and only then an electron could localize there. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is an easy example, but I hope it illustrates that you have to put additional information into the calculation to get the correct result, while you do not need to provide this information in plane-wave DFT. And I cannot imagine how many details one could possibly miss this way when modeling a more complex material.&lt;/p&gt;&#xA;" OwnerUserId="583" LastEditorUserId="583" LastEditDate="2020-05-17T12:54:06.453" LastActivityDate="2020-05-17T12:54:06.453" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="756" PostTypeId="2" ParentId="525" CreationDate="2020-05-17T08:32:54.907" Score="4" Body="&lt;p&gt;Actual examples of &lt;strong&gt;2D&lt;/strong&gt; magnetic systems are &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acsnano.8b03472&quot; rel=&quot;nofollow noreferrer&quot;&gt;MXenes&lt;/a&gt; and &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2018/nr/c8nr08479c/unauth#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;metal-organic adsorption monolayers&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="277" LastActivityDate="2020-05-17T08:32:54.907" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="757" PostTypeId="1" CreationDate="2020-05-17T14:22:47.757" Score="13" ViewCount="833" Body="&lt;p&gt;How can I make a heterostructure or a heterojunction of ZnO/MgZnO for optimization with WIEN2k code?&lt;/p&gt;&#xA;" OwnerUserId="591" LastEditorUserId="24" LastEditDate="2020-05-30T11:49:02.363" LastActivityDate="2020-05-30T12:08:06.560" Title="How to make heterostructure/heterojunction structure?" Tags="|density-functional-theory|software|electronic-structure|wien2k|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="758" PostTypeId="2" ParentId="692" CreationDate="2020-05-17T18:04:41.897" Score="13" Body="&lt;h2&gt;Psi4 and PySCF&lt;/h2&gt;&#xA;&lt;p&gt;Psi4 and PySCF are free, open source programs that can do both parallel integrals and SCF. MPI parallellization is quite rare in quantum chemistry codes, since the algorithms don't tend to parallellize easily across nodes..&lt;/p&gt;&#xA;&lt;h2&gt;MPQC&lt;/h2&gt;&#xA;&lt;p&gt;If you really want to do massively parallel calculations, then the Massively Parallel Quantum Chemistry (MPQC) package is your choice. This is a program aimed for molecules and periodic solids that can also run massively parallel coupled-cluster calculations.&lt;/p&gt;&#xA;&lt;h2&gt;ORCA&lt;/h2&gt;&#xA;&lt;p&gt;The ORCA program is MPI parallel, allowing it to run in parallel both on shared-memory and distributed-memory setups.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2021-02-05T21:05:12.967" LastActivityDate="2021-02-05T21:05:12.967" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="759" PostTypeId="2" ParentId="163" CreationDate="2020-05-17T18:15:23.857" Score="17" Body="&lt;p&gt;The main positives:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;you can do all-electron calculations&lt;/li&gt;&#xA;&lt;li&gt;you don't need to set up pseudopotentials / PAWs&lt;/li&gt;&#xA;&lt;li&gt;you can study core properties&lt;/li&gt;&#xA;&lt;li&gt;you can use hybrid functionals cheaper / run post-HF calculations&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The negatives:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;basis set is geometry dependent, so you get superposition error&lt;/li&gt;&#xA;&lt;li&gt;it's harder to get results close to the complete basis set limit&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Either approach is bad for empty space: plane-waves have uniform precision everywhere, whereas atomic orbitals are localized. Other approaches like finite elements and multiresolution grids fare a lot better here; they can easily represent both core orbitals and empty space.&lt;/p&gt;&#xA;&lt;p&gt;edit: see also the answer with references here &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1944/142&quot;&gt;https://mattermodeling.stackexchange.com/a/1944/142&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-11-11T16:46:38.417" LastActivityDate="2020-11-11T16:46:38.417" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="760" PostTypeId="2" ParentId="7" CreationDate="2020-05-17T18:27:09.767" Score="4" Body="&lt;p&gt;Often it's the Stetson-Harrison method. Instead of multiplying, one often specifies the diffuse extrapolation by division. E.g. 0.4 corresponds to dividing the smallest exponent by 1/0.4 = 2.5. This is indeed in the usual ball park; a factor of 3 is quite commonly used.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The numerical value of the factor is related to the completeness of the basis set, which can be &quot;measured&quot;, see e.g. &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.23802&quot; rel=&quot;nofollow noreferrer&quot;&gt;my paper on completeness-optimization&lt;/a&gt; for a discussion. As the basis set becomes more and more complete, the spacing factor approaches the value 1.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If the basis set you are trying to augment has been optimized as even tempered, IMHO one should not change the spacing of the exponents, but rather re-use the even-tempered spacing of the optimized primitives. (I also used a similar scheme &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5144964&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T18:27:09.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="761" PostTypeId="2" ParentId="70" CreationDate="2020-05-17T18:35:28.947" Score="12" Body="&lt;p&gt;I would like to stress the importance of the choice of the numerical algorithm, which was briefly touched on above. The choice of the representation (plane waves, augmented plane-waves, finite elements, finite differences, multiresolution grids, or atomic orbitals: Slater-type orbitals, Gaussian-type orbitals, or numerical atomic orbitals) determines the algorithms one can use and the properties one can study; in addition with a given numerical representation one may have to choose between different styles of pseudopotentials. No code will cover all possibilities, since traditionally scientific software is not very modular and cleanly structured, and the different approaches may not have a lot of common ground infrastructure wise.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Fortunately, modularization has happened, and e.g. common ground has been established for the evaluation of density functionals which is now typically handled by a common purpose-built library.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T18:35:28.947" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="762" PostTypeId="2" ParentId="683" CreationDate="2020-05-17T18:47:33.717" Score="10" Body="&lt;p&gt;A few more papers to add to Michael's answer:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://pubs.acs.org/doi/abs/10.1021/ja9826892&quot; rel=&quot;noreferrer&quot;&gt;What Do the Kohn-Sham Orbitals and Eigenvalues Mean&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://linkinghub.elsevier.com/retrieve/pii/S0009261498003169&quot; rel=&quot;noreferrer&quot;&gt;Relationship of Kohn–Sham eigenvalues to excitation energies&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T18:47:33.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="763" PostTypeId="2" ParentId="751" CreationDate="2020-05-17T18:53:39.910" Score="11" Body="&lt;h2&gt;Very short answer: No, &lt;em&gt;classical&lt;/em&gt; molecular dynamics cannot break bonds.&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;The potential you showed is the most common form of bond, the harmonic potential a.k.a. Hookes law.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you have ever broken a bond in QM (calculated a dissociation curve), you know it is a bit tricky, you need to use &quot;unrestricted&quot; settings, meaning, that a given pair of electrons does not need share the same orbital. As an added point for accuracy at the risk of distraction... saying you need &quot;QM&quot; is a bit hand wavey, although, not wrong. For real accuracy in QM, you need more than one Slater determinant to approximate the wave function. Now this is somewhat besides the point, but it lets me show a picture hastily drawn in powerpoint, so don't judge...&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GF2SM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GF2SM.png&quot; alt=&quot;{I WILL INSERT IMAGE HERE: Just realized I am booted on Linux, need to boot on windows to use my classy powerpoint imagery}&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you can see, the potential has a minimum, and at that minimum, and for a small ways out from it, as you stretch or compress the bond from equilibrium (the minimum is the equilibrium energy/bond length) the form of the potential is pretty close to quadratic. SPOILER ALERT: this is why the potential you showed in your question is used. It is quadratic, and describes the bond energy fairly well, BUT, only close to the minimum. As you get further away the bond energy clearly is not well modeled by a harmonic potential (quadratic)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thus, if you try to break a bond with in classical MD, you will do a terrible job of accurately modelling it. QM can't even do it well without using un-Restricted or Restricted open shell approaches!&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;There is also the subtle point that the quadratic we use for bonds will never actually break. The energy will increase to infinity without &quot;breaking&quot;.&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;As I alluded to in my comment &quot;non-classical&quot; methods can be used, for instance ab-initio MD which incorporated QM, thus allowing the bond to break. Also, ReaxFF which is closer to a classical FF uses bond-orders rather than actual bonds to describe molecules. I am not experienced with either of these, so I simply mention them and supply these two links for your further reading if you are interested:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;ab-initio &lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_dynamics#Potentials_in_ab_initio_methods&quot; rel=&quot;noreferrer&quot;&gt;ab-initio Wiki&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;reaxFF &lt;a href=&quot;https://en.wikipedia.org/wiki/ReaxFF&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF Wiki&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-05-18T01:05:02.817" LastActivityDate="2020-05-18T01:05:02.817" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="764" PostTypeId="2" ParentId="495" CreationDate="2020-05-17T19:12:24.763" Score="10" Body="&lt;p&gt;This will be a long answer, so I will divide it in parts.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Woods paper&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A significant limitation of the Woods et al paper is that it excludes atomic-basis set calculations where convergence acceleration is much more powerful than in plane wave codes. Namely, the update schemes discussed in the article talk about just the input and output &lt;strong&gt;densities&lt;/strong&gt;, whereas if you can store and diagonalize the Kohn-Sham-Fock matrix, you can formulate much faster converging methods for the solution. Typical quantum chemistry codes extrapolate the Fock matrix, not the density. This method typically achieves convergence in a few dozen iterations.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Which spin state?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As far as I know, some solid-state codes determine the spin state on the fly. If you don't fix the spin multiplicity, this may contribute to convergence problems. A study of convergence problems should be run for a fixed spin state; one can always carry out separate calculations for each spin state.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What is &quot;Kohn-Sham&quot;?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I also have to point out that the notion of &quot;Kohn-Sham calculations&quot; is a bit ill-defined, since typical solid-state calculations are run at a finite temperature; I think this is typically referred to as Mermin-Kohn-Sham theory. Kohn-Sham to me means integer occupations. If you have a finite temperature, you get fractional occupations.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Fractional occupations&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, you often get convergence problems when you have solutions of different symmetries close together (which is why atoms and diatomic molecules are often challenging). The reason for the lack of convergence is that the occupations switch between the SCF cycles. In some cases you can even find that LUMO and HOMO swap places when you optimize the orbitals: you find that the LUMO is below the HOMO, you reoptimize the orbitals at this symmetry, and now you realize the new LUMO is below the new HOMO.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But, fractional occupations at the Fermi level are in principle allowed by the Aufbau scheme. Allowing fractional occupations helps in this case, and you get much better convergence.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, variational minimization of the energy with respect to &lt;strong&gt;both&lt;/strong&gt; the orbitals &lt;strong&gt;and&lt;/strong&gt; the fractional occupation numbers is very hard (which is why AFAIK almost nobody does it).&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Finite temperature&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The alternative is to use a smearing function, e.g. Fermi-Dirac occupations. Also in this case the occupation numbers depend on the orbital energies, which depend on the orbitals, which depend on the occupation numbers. Solving the coupling between these might also make calculations slowly convergent; I am not sure how tightly these are converged in solid state codes.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-05-17T19:34:21.510" LastActivityDate="2020-05-17T19:34:21.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="765" PostTypeId="2" ParentId="347" CreationDate="2020-05-17T19:14:31.147" Score="11" Body="&lt;p&gt;Whenever you see EXX, a warning flag should go up inside your head. It is never clear whether one means just using Hartree-Fock exchange in a DFT calculation, implying a generalized Kohn-Sham scheme with a fully non-local potential, or if one means an optimized effective potential approach in which the exact Hartree-Fock exchange energy is inverted to find a local exchange potential v(r) that is then used to calculate the orbitals. Most of chemistry uses the former approach, e.g. the (in)famous B3LYP functional, per Becke's 1993 proposal of mixing HF and DFT in 10.1063/1.464304.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the looks of it, in GPAW &quot;the implementation lacks an optimized effective potential&quot;, which I take to mean that it is using the former i.e. generalized Kohn-Sham approach with a non-local potential. In contrast, the paper by Städele et al is solving the optimized effective potential introduced by Talman in 1976 for the local potential. A famous approximate scheme to achieve an optimized effective potential was developed before this paper by Krieger, Li, and Iafrate; it might be the most popular approach. If I remember correctly, the differences between KLI and the real OEP are small.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T19:14:31.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="766" PostTypeId="2" ParentId="696" CreationDate="2020-05-17T19:31:44.107" Score="8" Body="&lt;p&gt;This hasn't fully developed to what you are looking for yet, but it seems to be moving in that direction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;https://esl.cecam.org/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;CECAM Electronic Structure Library&lt;/a&gt; is an attempt to define a modular Electronic Structure program. The goal is basically to have collection of small programs that cover specialized parts of a calculation and an API/core program that will facilitate communication between these parts. At the moment, it seems to mainly be at the stage of developing the core, but with that in place, I assume they will move to a greater focus on developing and collecting modules that work within this framework.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This fits into a general movement toward modularization, mentioned previously in an &lt;a href=&quot;https://materials.stackexchange.com/a/761/7&quot;&gt;answer here&lt;/a&gt;. A standard for communication is necessary for the sorts of scripts you are looking for to have any widespread utility. To take the example from your comment, while a program like Gaussian can run a compound job to perform a geometry optimization and then compute a single point energy with this new geometry with a higher level of theory/different basis set, a separate program would be need to pass this geometry to another program. A different program might be needed to do the same thing for another electronic structure package, but this could be avoided if they were built to follow a particular API to pass geometric information.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-17T19:40:59.880" LastActivityDate="2020-05-17T19:40:59.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="767" PostTypeId="2" ParentId="690" CreationDate="2020-05-17T19:49:21.377" Score="11" Body="&lt;p&gt;It's determined by fitting. You optimize the functional (i.e. the coefficients therein) to yield the lowest errors possible.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;See e.g. &lt;a href=&quot;https://doi.org/10.1063/1.5025226&quot; rel=&quot;noreferrer&quot;&gt;the wB97M(2) functional&lt;/a&gt; for an example of a recent double hybrid.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T19:49:21.377" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="768" PostTypeId="2" ParentId="693" CreationDate="2020-05-17T19:51:37.973" Score="7" Body="&lt;p&gt;What systems are you running? Turbomole is designed for basis sets employing segmented contractions (like the Karlsruhe sets are), whereas the Dunning sets are generally contracted.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While any code using segmented contractions &lt;em&gt;works&lt;/em&gt; also with generally contracted basis sets, it is horrendously slow for heavy atoms since primitive integrals are re-computed hundreds of times.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-17T19:51:37.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="769" PostTypeId="2" ParentId="568" CreationDate="2020-05-17T20:11:37.257" Score="5" Body="&lt;p&gt;From my personal experience if you want to abstract the question to one of solvation energy you can approximate the favorability of solvation. For instance if I were to run an implicit solvent calculation on a benzene with various implicit solvents (e.g. water, other benzene, ethanol etc.) and compare to unsolvated, I could compare the solvated energy to the unsolvated energy to see if and how favorable it is to dissolve. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;An explicit way of doing this would be to create for example a water box around your two of your molecule, and see if they get pushed together or pulled apart during a geometry optimization, though this would be more of a heuristic observation rather than a measurable effect.&lt;/p&gt;&#xA;" OwnerUserId="256" LastActivityDate="2020-05-17T20:11:37.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="770" PostTypeId="2" ParentId="69" CreationDate="2020-05-17T20:15:56.243" Score="8" Body="&lt;h3&gt;Short answer&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;I am a regular GROMACS user. I do not think you can just easily have the total functional form &quot;printed out&quot; from GROMACS. However, you can obtain it from the topology file (&lt;code&gt;top&lt;/code&gt; and &lt;code&gt;itp&lt;/code&gt;s) and the &lt;code&gt;mdp&lt;/code&gt; file. Let me elaborate a little below.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;h3&gt;Longer answer&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;The functional forms you are referring to in the GROMACS &lt;code&gt;top&lt;/code&gt;/&lt;code&gt;itp&lt;/code&gt; file are the ones used in &lt;strong&gt;bonded interactions&lt;/strong&gt; - bonds, angles, and (proper and improper) dihedrals - and they indeed may vary across force fields, mostly for historical reasons. For example, GROMOS uses cosine based angle potentials (see &lt;a href=&quot;http://manual.gromacs.org/documentation/2019/reference-manual/functions/bonded-interactions.html#bondpot&quot; rel=&quot;noreferrer&quot;&gt;GROMACS manual - bonded interactions&lt;/a&gt; for the functional form), while other force fields use harmonic angle potentials. Another example is OPLS using Fourier functions (&lt;a href=&quot;http://manual.gromacs.org/documentation/2019/reference-manual/functions/bonded-interactions.html#bondpot&quot; rel=&quot;noreferrer&quot;&gt;GROMACS manual - bonded interactions&lt;/a&gt; for the functional form) for proper dihedrals, while other force fields use other functions. However, most of this functional forms are very similar, or in some cases equivalent: for example, at least in the case of dihedrals, you can actually have the same dihedral potential expressed via a Fourier function or by a Ryckaert-Bellemans function. As you recognized, the functional form of a particular bonded interaction in GROMACS is defined in the &lt;code&gt;itp&lt;/code&gt; file by a functional form &quot;ID&quot; - called &lt;code&gt;function type&lt;/code&gt;: &lt;em&gt;i.e.&lt;/em&gt;, the func 1, func 2 you mentioned. &lt;a href=&quot;http://manual.gromacs.org/documentation/2019/reference-manual/topologies/topology-file-formats.html#tab-topfile2&quot; rel=&quot;noreferrer&quot;&gt;This Table&lt;/a&gt; from the GROMACS manual contains a complete list of the different functions available in GROMACS for the bonded terms, their &quot;itp ID&quot; (&lt;code&gt;function type&lt;/code&gt;), and the parameters each of them requires.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Besides bonded interactions, the total functional form is made up of a second part: the &lt;strong&gt;nonbonded interactions&lt;/strong&gt; (&lt;a href=&quot;http://manual.gromacs.org/documentation/2019/reference-manual/functions/nonbonded-interactions.html&quot; rel=&quot;noreferrer&quot;&gt;GROMACS manual - nonbonded interactions&lt;/a&gt;; see also, &lt;em&gt;e.g.&lt;/em&gt;, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.200502655&quot; rel=&quot;noreferrer&quot;&gt;van Gusteren et al&lt;/a&gt;). This part is possibly more relevant in the context of your sub-question about force field compatibility. In classical MD, nonbonded interactions most commonly means describing van der Waals and Coulomb interactions. However, it is in how such nonbonded terms are specifically treated which can make a big difference and renders force field mixing not recommendable (i.e., Justin's replies on Researchgate &lt;a href=&quot;https://www.researchgate.net/post/How_to_use_two_kinds_of_forcefield_in_Gromacs_at_the_same_time&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://www.researchgate.net/post/Is_is_a_valid_approach_to_mix_two_forcefields_in_a_molecular_dynamics_simulation&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) unless a proper &lt;em&gt;validation&lt;/em&gt; is carried out (see below). This is the case because, the specific force fields have been all parametrized with different nonbonded settings. What I refer to here is to the exact treatment of Lennard-Jones and Coulomb interactions. For example,  while the use of Lennard-Jones potential itself is pretty much ubiquitous, the scaling of the 1-4 interactions, &lt;em&gt;i.e.&lt;/em&gt;, the interactions between atom &lt;em&gt;i&lt;/em&gt; and atom &lt;em&gt;j&lt;/em&gt; which is 3 bonds away from &lt;em&gt;i&lt;/em&gt;, varies considerably across force fields, see, &lt;em&gt;e.g.&lt;/em&gt;, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jcim.8b00042&quot; rel=&quot;noreferrer&quot;&gt;Table 2 of S. Riniker&lt;/a&gt;. This difference (and others) impacts the overall functional form of the force field, and in turn the parameters which make up the force field. So, different force fields end up having different balances of Lennard-Jones and Coulomb interactions: &lt;em&gt;e.g.&lt;/em&gt;, some force fields have on average partial charges with larger magnitudes than others, and this usually means that the Lennard-Jones parameters will be somewhat less cohesive to compensate for that.&#xA;The paper of &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jcim.8b00042&quot; rel=&quot;noreferrer&quot;&gt;S. Riniker&lt;/a&gt; gives a detailed overview of the four major force fields historically developed for biomolecules - AMBER, CHARMM, GROMOS, OPLS -, their refinement over time, and all the different settings which come with that. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also note that, despite the fact that water models, such as &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.445869&quot; rel=&quot;noreferrer&quot;&gt;TIP3P&lt;/a&gt; or &lt;a href=&quot;https://link.springer.com/chapter/10.1007%2F978-94-015-7658-1_21&quot; rel=&quot;noreferrer&quot;&gt;SPC&lt;/a&gt;, can be considered a &quot;separate&quot; force field, they are compatible with certain force fields because such force fields have been developed using them. In other words, each force field chose to use a certain water model - possibly because they were the developers of that model - for their force field. The specific force field was then parametrized using that chosen water model, e.g., TIP3P for OPLS and SPC for GROMOS. This then means that you should use TIP3P with OPLS and SPC with GROMOS and not vice versa, etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A last note on the &lt;em&gt;validation&lt;/em&gt;: force fields have historically been validated in various ways, that is, by using different parametrization targets. For example, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.20090&quot; rel=&quot;noreferrer&quot;&gt;GROMOS 53A6&lt;/a&gt; relies primarily on solvation free energies, the coarse-grain &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp071097f&quot; rel=&quot;noreferrer&quot;&gt;Martini&lt;/a&gt; force field on free energies of transfer, etc. The chosen parametrization targets reflect the &quot;philosophy&quot; behind the force field, and tell you also about the domain of application of the force field. Now, this means that if you create a new molecule (a new &lt;code&gt;itp&lt;/code&gt; file) within that force field by following the guidelines (e.g., use a particular method to compute the partial charges, use the force field default atom type for the Lennard-Jones parameter of the aromatic atoms, etc.), the idea is that you get a molecule which is compatible with the force field and which, in principle, should give you, for example in the case of GROMOS, solvation free energies in agreement with experimental data. Now, you see that if you mix in topologies from different force fields, there's no guarantee that this is the case. Potentially, for a specific application, if you really need to mix in different force field, you should first carefully validate that properties which are relevant for your application and for that system are reproduced well (solvation free energy, mass density, etc.). But this is very application specific, and should be checked very carefully. Now, I think I should leave it here and not go much further off topic. :)&lt;/p&gt;&#xA;" OwnerUserId="536" LastActivityDate="2020-05-17T20:15:56.243" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="771" PostTypeId="1" CreationDate="2020-05-17T20:25:39.980" Score="17" ViewCount="754" Body="&lt;p&gt;I performed an HSE06 calculations using VASP and the calculated band gap is in good agreement with experiment. However the band is not smooth, with very sharp, zig-zag like features. How to improve the smoothness of the band structure?&lt;/p&gt;&#xA;" OwnerUserId="219" LastEditorUserId="7" LastEditDate="2020-05-17T20:41:38.720" LastActivityDate="2020-05-24T19:03:43.857" Title="How to ensure a smooth band structure?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="772" PostTypeId="2" ParentId="527" CreationDate="2020-05-17T20:26:30.713" Score="4" Body="&lt;p&gt;I have done computational fitting of LEED-IV in the past using an older code and, yes, you are correct. You can do these optimizations on a workstation now for small systems, although I don't recommend it. I ended up doing most of the calculations on a high-performance computer anyway (and you will do that as well for such a large system). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the system you are thinking about, however, I think the unit cell is very large and also low-symmetry, which is problematic because you will have many parameters that need to be optimized. As you are probably aware after you read the book chapter, fitting LEED-IV curves is nontrivial because of the complicated (and meaningless) structure of the I(V) curves and the resulting large number of local minima of the RP value. You will not (not even if you're lucky) achieve a useful agreement between your experimental data and your simulation unless you do at least some degree of fitting. Before you start this endeavor, you should critically assess whether the energy range and quality of your experimental data are even sufficient to fit the large number of parameters in your system. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Then, if you still want to do it, I suggest you don't write your own code. I suggest you find a specialist who has a code and ask to collaborate with them. I am sorry if this suggestion is out of place because you seem to be interested in the technical details, but there are already good codes for LEED-I(V) fitting and these codes are quite complex (I'm talking several 100k lines of code). You also mentioned the apparent complexity. Your impression is very correct. I just wanted to give some general LEED-I(V) advice and things to consider before you get into the details. You could potentially waste a lot of time on this kind of research question and never actually get anywhere, so you should think first if this is even doable.&lt;/p&gt;&#xA;" OwnerUserId="583" LastEditorUserId="583" LastEditDate="2020-05-17T20:38:15.077" LastActivityDate="2020-05-17T20:38:15.077" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="773" PostTypeId="5" CreationDate="2020-05-17T20:48:03.530" Score="0" Body="&lt;p&gt;From &lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Psi4 website&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;PSI4 is an open-source suite of ab initio quantum chemistry programs designed for efficient, high-accuracy simulations of a variety of molecular properties. It is very easy to use and has an optional Python interface.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-17T20:48:03.530" LastActivityDate="2020-05-17T20:48:03.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="774" PostTypeId="4" CreationDate="2020-05-17T20:48:03.530" Score="0" Body="For questions about using the Psi4 Quantum Chemistry Package." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-05-21T20:50:03.280" LastActivityDate="2020-05-21T20:50:03.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="775" PostTypeId="1" CreationDate="2020-05-17T21:11:31.620" Score="12" ViewCount="101" Body="&lt;p&gt;I am trying to setup QM/MM calculations with QChem using user-defined connectivity and MM parameters. But the official manual is not detailed about some options. Mostly I am interested in the procedure of accounting angles and torsions across QM/MM linkage. How it is usually calculated during QM/MM? And is there any additional keys in $rem section to control QM/MM job for QChem?&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="506" LastEditorUserId="5" LastEditDate="2020-05-18T01:03:24.403" LastActivityDate="2020-05-30T05:52:35.653" Title="Q-Chem QM/MM options" Tags="|q-chem|qmmm|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="776" PostTypeId="1" AcceptedAnswerId="848" CreationDate="2020-05-17T21:16:39.010" Score="12" ViewCount="242" Body="&lt;p&gt;Is there a rule-of-thumb for selecting a cutoff for the Morse potential in molecular dynamics simulation? For instance, is it typically some multiple of the equilibrium distance?&lt;/p&gt;&#xA;" OwnerUserId="599" LastActivityDate="2020-05-18T10:25:08.283" Title="Rule-of-thumb for Morse potential cutoff in molecular dynamics?" Tags="|molecular-modeling|molecular-dynamics|intermolecular-forces|molecular-interactions|molecular-mechanics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="777" PostTypeId="2" ParentId="751" CreationDate="2020-05-17T21:17:16.463" Score="14" Body="&lt;p&gt;The quadratic potential is the simplest possible model for a bond. You can derive it by considering the Taylor expansion of the potential around the natural bond length&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V(r - r_0) = V(r_0) + \frac{d V(r_0)}{d r} (r - r_0) + \frac{1}{2} \frac{d^2 V}{dr^2} (r - r_0)^2$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The constant term can be set to 0 since it does not contribute to the force and just sets the 0 point of your energy scale. The linear term is 0, because you are at a stationary point [1].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;That leaves you with&#xA;&lt;span class=&quot;math-container&quot;&gt;$V(r - r_0) = \frac{1}{2} \frac{d^2 V}{dr^2} (r - r_0)^2$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If we require the second derivative to be constant, we have recovered the harmonic potential.&#xA;As @Charlie Crown illustrated, this force resulting from this potential does not go to 0 at infinity, while the Morse potential does. You can of course take a polynomial of higher order than two, but not every order is suitable. A third order polynomial results in a potential that (typically) goes to negative infinity at large &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, so instead a quartic potential is some times used. It has the advantage of being slightly &quot;wider&quot; than the quadratic one. That said, a completely unrelated reason why none of these can simulate bond breaking/formation is that the implementation requires explicit declaration of which atoms should interact via the stretching potential.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Still, at large &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; both differ significantly from the Morse potential. &lt;em&gt;Why then is the Morse potential not used?&lt;/em&gt;&#xA;The restoring force for large &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is very low in case of the Morse potential, hence it takes longer for the bond length to return to the equilibrium position. The quadratic potential describes the potential well for displacements close to equilibrium and for moderate temperatures, this is the part of the potential you care about.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Obviously that still leaves the question of how to simulate bond breaking in a force field. ReaxFF assumes that the bond order of a pair of atoms can be determined from the interatomic distance alone. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oJQ60.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oJQ60.png&quot; alt=&quot;Bond order C-C distance dependence&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(qualitative recreation from [2])&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The sigma, pi and double pi bonds contribute increasingly to the overall bond order (max individual bond order is 1) as the atoms get closer together. For simplicity I am leaving out the corrections made to the overall bond order necessitated by overcoordination.&#xA;The bond stretching potential takes the form of a modified Morse potential&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{Bond} = -D_e \cdot BO_{ij} \cdot \exp(p \cdot (1 - BO_{ij}^p))$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; is a bond specific parameter[2].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1]: Frank Jensen, &lt;em&gt;Introduction to Computational Chemistry&lt;/em&gt; Chap. 2&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2]: J. Phys. Chem. A 2001, 105, 9396-9409&lt;/p&gt;&#xA;" OwnerUserId="406" LastActivityDate="2020-05-17T21:17:16.463" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="778" PostTypeId="1" CreationDate="2020-05-17T21:20:27.707" Score="21" ViewCount="234" Body="&lt;p&gt;I'm doing some property calculations that depend on a sum of derivatives of some quantity with respect to normal vibrational modes. I was hoping to find some physical intuition relating the type of mode to its property contribution, but there isn't an obvious connection in the normal mode basis.&lt;/p&gt;&#xA;&lt;p&gt;I decided to try converting to a different mode basis to see if there is a more obvious connection. I'm able to convert the modes using a unitary transformation, but I can't seem to convert derivatives to the new basis properly (the unitary transformed derivatives don't match numerical derivatives along the transformed modes).&lt;/p&gt;&#xA;&lt;p&gt;I asked separately &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/928/discrepancy-between-numerical-and-transformed-derivatives&quot;&gt;here&lt;/a&gt; about any errors with my transformation method. For this question, I'm more curious if this already solved in an existing program?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there an electronic structure program that can perform derivatives with respect to vibrational modes and allows the user to define the modes?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-12-31T04:16:17.350" LastActivityDate="2022-02-24T16:55:18.753" Title="Is there a software that can do derivatives with respect to user defined vibrational modes?" Tags="|software|electronic-structure|software-recommendations|mathematical-modeling|vibrations|" AnswerCount="0" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="779" PostTypeId="1" CreationDate="2020-05-17T21:56:36.903" Score="10" ViewCount="113" Body="&lt;p&gt;I am trying to perform a QM/MM optimization in which my substrate is in the MM region. However when this happens there are significant changes to the geometry (undesired). I want to avoid fixing all atoms in place and having to constrain all distances/angles/diehedrals. Does anyone know how to select an index of atoms to constrain and which constraint might be best (using pDynamo)?&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="510" LastEditDate="2020-05-17T23:20:18.013" LastActivityDate="2020-06-19T21:38:55.303" Title="Constraining a set of atoms in the MM region using pDynamo (CHARMM/ORCA interface)" Tags="|software|orca|pdynamo|charmm|qmmm|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="780" PostTypeId="5" CreationDate="2020-05-17T23:05:51.987" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:05:51.987" LastActivityDate="2020-05-17T23:05:51.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="781" PostTypeId="4" CreationDate="2020-05-17T23:05:51.987" Score="0" Body="Questions about pDynamo. pDynamo is the open source program library for the simulation of molecular systems using quantum chemical (QC), molecular mechanical (MM) and hybrid QC/MM potential energy functions." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T03:42:50.860" LastActivityDate="2020-05-18T03:42:50.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="782" PostTypeId="5" CreationDate="2020-05-17T23:07:04.687" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:07:04.687" LastActivityDate="2020-05-17T23:07:04.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="783" PostTypeId="4" CreationDate="2020-05-17T23:07:04.687" Score="0" Body="Questions involving the modeling of systems in one dimension, such as 1D Ising models, 1D Hubbard models, or even carbon nanotubes." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-18T00:08:30.650" LastActivityDate="2020-05-18T00:08:30.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="784" PostTypeId="5" CreationDate="2020-05-17T23:25:53.840" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:25:53.840" LastActivityDate="2020-05-17T23:25:53.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="785" PostTypeId="4" CreationDate="2020-05-17T23:25:53.840" Score="0" Body="For questions about applying or developing QM/MM (quantum-mechanics/molecular-mechanics) hybrid models ." OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2020-06-29T19:18:46.413" LastActivityDate="2020-06-29T19:18:46.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="786" PostTypeId="5" CreationDate="2020-05-17T23:34:34.790" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:34:34.790" LastActivityDate="2020-05-17T23:34:34.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="787" PostTypeId="4" CreationDate="2020-05-17T23:34:34.790" Score="0" Body="Questions relating to the phase-field modeling of materials, which provides a means of simulating microstructure evolution at the mesoscale. " OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T00:19:13.720" LastActivityDate="2020-05-18T00:19:13.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="788" PostTypeId="5" CreationDate="2020-05-17T23:50:13.223" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:50:13.223" LastActivityDate="2020-05-17T23:50:13.223" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="789" PostTypeId="4" CreationDate="2020-05-17T23:50:13.223" Score="0" Body="For questions related to the non-orthogonal configuration interaction (NOCI) method in electronic structure theory. NOCI is a configuration interaction method where the basis in which one diagonalizes the Hamiltonian can be any Slater determinant, each of which may be non-orthogonal with the rest of the basis." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-18T00:09:46.710" LastActivityDate="2020-05-18T00:09:46.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="790" PostTypeId="5" CreationDate="2020-05-17T23:53:11.150" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:53:11.150" LastActivityDate="2020-05-17T23:53:11.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="791" PostTypeId="4" CreationDate="2020-05-17T23:53:11.150" Score="0" Body="Questions related to transport phenomena (e.g. charge transfer, heat conduction, molecular diffusion)." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-02T15:58:51.483" LastActivityDate="2020-07-02T15:58:51.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="792" PostTypeId="5" CreationDate="2020-05-17T23:55:26.630" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-17T23:55:26.630" LastActivityDate="2020-05-17T23:55:26.630" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="793" PostTypeId="4" CreationDate="2020-05-17T23:55:26.630" Score="0" Body="For questions related to the Heisenberg model Hamiltonian." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T00:07:07.097" LastActivityDate="2020-05-18T00:07:07.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="794" PostTypeId="5" CreationDate="2020-05-18T00:15:37.450" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T00:15:37.450" LastActivityDate="2020-05-18T00:15:37.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="795" PostTypeId="4" CreationDate="2020-05-18T00:15:37.450" Score="0" Body="For questions about the software WIEN2k." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T01:18:00.137" LastActivityDate="2020-05-18T01:18:00.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="796" PostTypeId="5" CreationDate="2020-05-18T00:50:32.010" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T00:50:32.010" LastActivityDate="2020-05-18T00:50:32.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="797" PostTypeId="4" CreationDate="2020-05-18T00:50:32.010" Score="0" Body="Questions concerning the software TURBOMOLE." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-18T01:16:46.087" LastActivityDate="2020-05-18T01:16:46.087" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="798" PostTypeId="5" CreationDate="2020-05-18T00:58:12.930" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T00:58:12.930" LastActivityDate="2020-05-18T00:58:12.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="799" PostTypeId="4" CreationDate="2020-05-18T00:58:12.930" Score="0" Body="Questions relating to transition metals." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-18T01:17:04.030" LastActivityDate="2020-05-18T01:17:04.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="800" PostTypeId="5" CreationDate="2020-05-18T01:02:22.483" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:02:22.483" LastActivityDate="2020-05-18T01:02:22.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="801" PostTypeId="4" CreationDate="2020-05-18T01:02:22.483" Score="0" Body="Questions relating to electron correlation - the interaction between electrons in the electronic structure of a quantum system. The correlation energy is a measure of how much the movement of one electron is influenced by the presence of all other electrons." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T05:30:28.110" LastActivityDate="2020-05-18T05:30:28.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="802" PostTypeId="5" CreationDate="2020-05-18T01:05:45.077" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:05:45.077" LastActivityDate="2020-05-18T01:05:45.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="803" PostTypeId="4" CreationDate="2020-05-18T01:05:45.077" Score="0" Body="Questions about the band structure of solids. Band theory forms the foundation of the understanding of all solid-state devices." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T05:30:41.553" LastActivityDate="2020-05-18T05:30:41.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="804" PostTypeId="5" CreationDate="2020-05-18T01:14:46.430" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:14:46.430" LastActivityDate="2020-05-18T01:14:46.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="805" PostTypeId="4" CreationDate="2020-05-18T01:14:46.430" Score="0" Body="Questions related to the dice lattice - a two dimensional lattice which has three sites in the unit cell." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T10:37:11.990" LastActivityDate="2020-05-18T10:37:11.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="806" PostTypeId="5" CreationDate="2020-05-18T01:22:10.307" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:22:10.307" LastActivityDate="2020-05-18T01:22:10.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="807" PostTypeId="4" CreationDate="2020-05-18T01:22:10.307" Score="0" Body="Questions related to photoluminescence, the phenomenon whereby light is emitted after electronic excitation by an incoming photon." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T03:44:24.240" LastActivityDate="2020-05-18T03:44:24.240" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="808" PostTypeId="5" CreationDate="2020-05-18T01:26:19.307" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:26:19.307" LastActivityDate="2020-05-18T01:26:19.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="809" PostTypeId="4" CreationDate="2020-05-18T01:26:19.307" Score="0" Body="Questions seeking clarification on the various terminology related to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T08:36:18.363" LastActivityDate="2020-05-18T08:36:18.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="810" PostTypeId="5" CreationDate="2020-05-18T01:28:22.820" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:28:22.820" LastActivityDate="2020-05-18T01:28:22.820" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="811" PostTypeId="4" CreationDate="2020-05-18T01:28:22.820" Score="0" Body="Questions related to scattering phenomena in materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T03:44:12.530" LastActivityDate="2020-05-18T03:44:12.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="812" PostTypeId="5" CreationDate="2020-05-18T01:30:55.860" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:30:55.860" LastActivityDate="2020-05-18T01:30:55.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="813" PostTypeId="4" CreationDate="2020-05-18T01:30:55.860" Score="0" Body="For questions about harmonic oscillators." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T03:13:24.767" LastActivityDate="2020-05-18T03:13:24.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="814" PostTypeId="5" CreationDate="2020-05-18T01:35:54.683" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:35:54.683" LastActivityDate="2020-05-18T01:35:54.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="815" PostTypeId="4" CreationDate="2020-05-18T01:35:54.683" Score="0" Body="Questions about the rigid rotor being used as a mechanical model of rotating systems." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T08:36:26.813" LastActivityDate="2020-05-18T08:36:26.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="816" PostTypeId="5" CreationDate="2020-05-18T01:42:01.583" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:42:01.583" LastActivityDate="2020-05-18T01:42:01.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="817" PostTypeId="4" CreationDate="2020-05-18T01:42:01.583" Score="0" Body="For questions about the open-source software OpenMOLCAS." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T03:15:55.263" LastActivityDate="2020-05-18T03:15:55.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="818" PostTypeId="5" CreationDate="2020-05-18T01:48:45.827" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:48:45.827" LastActivityDate="2020-05-18T01:48:45.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="819" PostTypeId="4" CreationDate="2020-05-18T01:48:45.827" Score="0" Body="For question about the software PySCF." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T03:12:41.937" LastActivityDate="2020-05-18T03:12:41.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="820" PostTypeId="5" CreationDate="2020-05-18T01:52:17.207" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:52:17.207" LastActivityDate="2020-05-18T01:52:17.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="821" PostTypeId="4" CreationDate="2020-05-18T01:52:17.207" Score="0" Body="For questions about GPUs (graphical processing units) in the context of designing and performing material simulations." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-05-19T16:27:14.607" LastActivityDate="2020-05-19T16:27:14.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="822" PostTypeId="5" CreationDate="2020-05-18T01:55:39.130" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:55:39.130" LastActivityDate="2020-05-18T01:55:39.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="823" PostTypeId="4" CreationDate="2020-05-18T01:55:39.130" Score="0" Body="Questions pertaining to the use of PDEs to model molecular and material processes" OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-02T16:16:33.540" LastActivityDate="2020-07-02T16:16:33.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="824" PostTypeId="5" CreationDate="2020-05-18T01:57:01.873" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:57:01.873" LastActivityDate="2020-05-18T01:57:01.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="825" PostTypeId="4" CreationDate="2020-05-18T01:57:01.873" Score="0" Body="Questions related to the use of periodic tiling in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T10:37:18.127" LastActivityDate="2020-05-18T10:37:18.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="826" PostTypeId="5" CreationDate="2020-05-18T01:57:46.340" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:57:46.340" LastActivityDate="2020-05-18T01:57:46.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="827" PostTypeId="4" CreationDate="2020-05-18T01:57:46.340" Score="0" Body="Questions about research data in relation to materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T08:36:12.563" LastActivityDate="2020-05-18T08:36:12.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="828" PostTypeId="5" CreationDate="2020-05-18T01:59:12.393" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T01:59:12.393" LastActivityDate="2020-05-18T01:59:12.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="829" PostTypeId="4" CreationDate="2020-05-18T01:59:12.393" Score="0" Body="Please instead use the tag [hubbard-model]." OwnerUserId="118" LastEditorUserId="118" LastEditDate="2020-05-26T18:37:18.063" LastActivityDate="2020-05-26T18:37:18.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="830" PostTypeId="2" ParentId="691" CreationDate="2020-05-18T05:58:06.280" Score="7" Body="&lt;h2&gt;Thermochemistry (for a single molecule, e.g., ideal gas) depends on the Temperature.&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;At T=0K thermochemistry is kind to us.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;At T = 0K &lt;span class=&quot;math-container&quot;&gt;$U = G = H$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is because H = U + PV, which for an ideal gas is H = U + RT, and T = 0K, and also, G = H-TS, and again, T = 0K so that cancels&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The only direct calculation a QM program is doing, that I am aware of, is calculating contributions to the Energy. And it only does energy calculations at T=0K.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;At T = 0K a QM calculation will give you &lt;span class=&quot;math-container&quot;&gt;$E_{\rm elec}$&lt;/span&gt;. It will also calculate the zero-point vibrational energy (ZPVE). You need to add this on. All other contributions to energy are zero. There are no rotations or translations at T=0K.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you want to do thermochemistry at a different temperature, you need to calculate the &lt;span class=&quot;math-container&quot;&gt;$\Delta U$&lt;/span&gt; between the energy at T=0K and the desired temperature,  and also, as will be seen, calculate the entropy. I say &quot;you&quot;, but I mean your QM program. In going to a different temperature you will need to consider&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta E = \Delta E_{\rm trans} + \Delta E_{\rm rotation} + \Delta E_{\rm vib} +\Delta E_{\rm others}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The first three are calculated using statistical thermodynamics. Specifically, statistical thermodynamics for ideal gases, which are actually solvable. Professor Christopher Cramer has a great online course covering how to calculate thermodynamic properties from the partition function &lt;a href=&quot;https://www.coursera.org/learn/statistical-thermodynamics&quot; rel=&quot;noreferrer&quot;&gt;Cramer's Coursera course&lt;/a&gt;. This Gaussian white paper covers how Gaussian does thermochemistry &lt;a href=&quot;https://gaussian.com/thermo/&quot; rel=&quot;noreferrer&quot;&gt;Gaussian Thermochemistry White Paper&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The take home is that you can calculate &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm trans}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm rotation}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm vib}$&lt;/span&gt;. A note  on &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm others}$&lt;/span&gt; this can contain many things, most notably nuclear contributions which we normally neglect, and excited state electronic energy, which is often neglected, but not necessarily wisely.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, also, from the same guiding principles of statistical thermodynamics we can calculate the entropy. So, we have in hand our &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;'s and our entropies, &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thermodynamics does the rest.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$H = U + PV$&lt;/span&gt; and since this is an ideal gas, we know PV = nRT, so we thus have&#xA;&lt;span class=&quot;math-container&quot;&gt;$\Delta H = \Delta U +nRT$&lt;/span&gt;. Typically &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; refers to internal energy in a macroscopic sense, and we use &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; to denote microscopic energy. I will use &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; rather than &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; for clarity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;We now have &lt;span class=&quot;math-container&quot;&gt;$\Delta H = \Delta E + nRT$&lt;/span&gt; where R is the gas constant and n is number of moles, and T is temperature. Presumably you know n, can look up R, and had a T in mind when you did the QM computer experiment. So we have H now, at any temperature, for our single molecule, which, by fiat, is an ideal gas molecule.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The last thing usually of interest is the Gibbs free energy. It is certainly my favorite.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Again, thermodynamics has a relation which is G = H-TS. Remember, we calculated our &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;'s earlier and also our entropy S, and we know T, and we just calculated &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt;, so we can plug and chug to get &lt;span class=&quot;math-container&quot;&gt;$\Delta G$&lt;/span&gt; since we know &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt;, T and S at this point.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Worthwhile notes&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;it is useful to know that &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm trans} = \frac{3RT}{2}$&lt;/span&gt; and, this applies to a proton (among other things)! often in proton affinity REACTIONS, a magical 5/2RT appears and people just accept it. it is because a proton does not have rotation, it is a single nuclei, nor does it vibrate, it only has a translational contrabution to the &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; between two temperatures,presumably T=0K and your goal. I am not quite done. And this may be useful. Proton affinity is calculated as an Enthalpy - hence, the relevance to your question. So the proton affinity (enthalpy) must account for the &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\rm trans}$&lt;/span&gt; of the proton is 3/2 RT, but Enthalpy is E + nRT, here n = 1, so the magic 5/2RT that appears is due to the 3/2RT from energy, and the RT to go from E to H. i.e., &lt;span class=&quot;math-container&quot;&gt;$\Delta H = 3/2RT + RT = 5/2RT$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Probably overkill.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In this day and age, given the simplicity of a thermochemistry calculation, there should be no excuse for assuming &lt;span class=&quot;math-container&quot;&gt;$\Delta H = \Delta E$&lt;/span&gt; at any temperature other than T = 0K.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-05-18T06:20:01.210" LastActivityDate="2020-05-18T06:20:01.210" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="831" PostTypeId="1" AcceptedAnswerId="1724" CreationDate="2020-05-18T06:19:44.747" Score="16" ViewCount="187" Body="&lt;p&gt;I am studying several thermodynamics properties of crystalline iron oxides (&lt;span class=&quot;math-container&quot;&gt;$\ce{Fe3O4}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma-\ce{Fe2O3}$&lt;/span&gt;) in their solid phases by MD simulations. At the moment, I am facing many difficulties in simulating the nano particles. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The crystal structures I am using are coming from first principle simulations and interaction potential parametrisations (Buckingham potential for short range and Coulombic potentials for Long range) developed for bulk iron oxides. Clearly the modelling is properly working for bulk iron oxides. However, when applied to nano-particles, the nano-particles become amorphous at any temperature.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In my opinion, the lack of Coulombic contribution in the nano-system (for bulk, the contribution is large, as the simulation box is periodic in each dimension) is causing this behavior.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Has anyone ever faced such issue while studying crystalline nano-structures?&lt;/p&gt;&#xA;" OwnerUserId="605" LastEditorUserId="5" LastEditDate="2020-07-04T14:40:14.643" LastActivityDate="2020-07-26T20:05:55.483" Title="Why do interaction potential parametrizations of bulk systems not work for corresponding nano-systems?" Tags="|molecular-dynamics|lammps|interatomic-potentials|nanoparticles|gromacs|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="832" PostTypeId="1" AcceptedAnswerId="843" CreationDate="2020-05-18T06:39:01.007" Score="12" ViewCount="105" Body="&lt;p&gt;I'm currently responding to referees about a manuscript on the dynamics of the Ising model. I have been using the term &lt;strong&gt;nonequilibrium&lt;/strong&gt; to refer to any state that is not characteristic of the equilibrium distribution of that system. For example, the simulation gets stuck (due to the dynamics) in a state far from the ground state. Basically nonequilibrium = not equilibrium. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A referee complained that &lt;em&gt;nonequilibrium states&lt;/em&gt; are stationary states stabilized by some external driving force. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Who is right? And is there an authoritative definition that I could cite somewhere? &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-20T01:04:55.223" Title="In Monte Carlo: does nonequilibrium imply stationary state?" Tags="|monte-carlo|nonequilibrium|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="833" PostTypeId="1" AcceptedAnswerId="834" CreationDate="2020-05-18T06:41:38.920" Score="10" ViewCount="2675" Body="&lt;p&gt;Today I tried to get an access to Molden to install it and use for processing the results of my calculations. Unfortunately the ftp seems to be down or is it only my personal connection issues?&lt;br&gt;&lt;br&gt;&#xA;My additional question is foreseeing: Does molden work on the latest macOS Catalina (v. 10.15)?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="88" LastEditDate="2020-05-18T07:04:58.840" LastActivityDate="2021-12-15T06:31:42.190" Title="Molden installation on macOS?" Tags="|visualization-software|molden|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="834" PostTypeId="2" ParentId="833" CreationDate="2020-05-18T06:53:17.693" Score="13" Body="&lt;p&gt;I believe that these instructions from this YouTube video &lt;a href=&quot;https://www.youtube.com/watch?v=zvrfVNzb-zs&amp;amp;t=10s&quot; rel=&quot;noreferrer&quot;&gt;&quot;How to install Molden on Mac (OS X High Sierra)&quot;&lt;/a&gt; work well &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For some reason the &quot;ftp&quot; button on Molden's website is broken however, the &lt;code&gt;curl&lt;/code&gt; command works easily&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is a complete set of instructions from that video:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Install Homebrew:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;/usr/bin/ruby -e &quot;$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)&quot;&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Install Cask:&#xA;&lt;code&gt;brew install cask&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Install XQuartz:&#xA;&lt;code&gt;brew cask install xquartz&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Install complier:&#xA;&lt;code&gt;brew install gcc&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Change working directory to desktop:&#xA;&lt;code&gt;cd desktop&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Download Molden source code:&#xA;&lt;code&gt;curl ftp://ftp.cmbi.ru.nl/pub/molgraph/molden/molden5.7.tar.gz -o molden5.7.tar.gz&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Unpack downloaded file manually or use command:&#xA;&lt;code&gt;tar -xzf molden5.7.tar.gz&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Change working directory to molden5.7:&#xA;&lt;code&gt;cd molden5.7&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Compile Molden:&#xA;&lt;code&gt;make all&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Remove original files (optional):&#xA;&lt;code&gt;rm -r */*.o */*.c */*.f */*.h */*.bak&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Start Molden:&#xA;./molden&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(Optional) cop molden executable to ~/bin and make sure ~/bin is in $PATH&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Obviously skip installing Homebrew, Cask, XQuartz, gcc, if you don't need them!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-05-18T06:53:17.693" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="835" PostTypeId="1" AcceptedAnswerId="995" CreationDate="2020-05-18T07:02:18.200" Score="13" ViewCount="198" Body="&lt;p&gt;&lt;br&gt;&#xA;I'm looking for an advice how the best to set up the system and optimize a transition state with explicit solvent.&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I believe that solvent molecules are participating in the reaction  by specific solvation/coordination and assist in one of the reaction steps. Geometry optimization of the pre-reaction complex converged to a local minima of the system featuring solvent coordination on a different spot (hydrogen bonding). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I do not want to introduce too many solvent molecules, as solvent behavior is extremely dynamic.&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Could you, please, recommend possible ways to optimize TS with explicit solvent, or some literature as a reference? &lt;br&gt;&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="52" LastEditDate="2020-05-22T04:08:48.770" LastActivityDate="2020-05-22T04:48:34.247" Title="TS-search with explicit solvent" Tags="|reference-request|q-chem|transition-state|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="836" PostTypeId="1" CreationDate="2020-05-18T07:13:02.573" Score="17" ViewCount="1355" Body="&lt;p&gt;I am not able to understand the literature on how the &lt;strong&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.226401&quot; rel=&quot;noreferrer&quot;&gt;modified Becke-Johnson(MBJ)&lt;/a&gt;&lt;/strong&gt;&lt;span class=&quot;math-container&quot;&gt;$^{[1]}$&lt;/span&gt; potential gives an accurate bandgap. Can someone please help? Thank you. The formula for the potential can be found &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4798706?journalCode=jcp&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;span class=&quot;math-container&quot;&gt;$^{[2]}$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Tran, Fabien, and Peter Blaha. &quot;Accurate band gaps of semiconductors and insulators with a semilocal exchange-correlation potential.&quot; Physical review letters 102.22 (2009): 226401.&lt;/li&gt;&#xA;&lt;li&gt;Jiang, Hong. &quot;Band gaps from the Tran-Blaha modified Becke-Johnson approach: A systematic investigation.&quot; The Journal of chemical physics 138.13 (2013): 134115.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="606" LastEditorUserId="175" LastEditDate="2020-06-18T00:19:40.170" LastActivityDate="2020-06-18T00:19:40.170" Title="How does the mBJ potential give an accurate band gap as compared to LDA and GGA?" Tags="|density-functional-theory|vasp|quantum-espresso|band-structure|wien2k|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="837" PostTypeId="2" ParentId="500" CreationDate="2020-05-18T07:16:50.030" Score="7" Body="&lt;p&gt;Approaching the fixed-point problem an SCF solves from the direct minimisation (DM) point of view (for the relation of DM to SCF, see &lt;a href=&quot;https://materials.stackexchange.com/questions/431/what-are-the-core-numerical-routines-used-in-density-functional-theory/494#494&quot;&gt;my previous post&lt;/a&gt;, the key quantities to check for convergence are actually the total energy and it's derivative, i.e. the occupied-virtual block of the Fock / Kohn-Sham matrix. The latter is after all the gradient and that's what you want to drive to zero in a fixed point. In an SCF context you could theoretically do the same and to the best of my knowledge some codes like PySCF actually use these two criteria for convergence.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Of course there are other choices, which can be done and using the density works the same, since a zero density change implies a zero change in the Fock matrix and vice versa. From that point of view the density is kind of a substitute for checking convergence in the gradient, but of course not the same threshold can be used for both checks and tolerances need to be adjusted between them.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since clearly the gradient being zero is the whole aim of an SCF, I find it dubious to only check for convergence in the energy as it could accidentally stagnate without being at a fixed point. In turn if you check for the density / gradient change being zero you should be safe. However, as @Tyberius already pointed out, computing the energy is pretty much for free if you compute density and Fock matrix and therefore performing a check on the energy does not cost and shouldn't do harm either.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Talking about convergence speeds: In absolute numbers the energy always converges first, since it depends quadratically on the density (so &lt;strong&gt;error 1e-3 in the density usually translates to 1e-6 in the energy&lt;/strong&gt;). Therefore convergence criteria on energy should be the square of the convergence tolerance in the density / gradient. But notice that many codes are a bit sloppy here and do not print the norm of the density / gradient change in their outputs, but the norm squared, such that both numbers are again on the same scale (e.g. ABINIT does this). So one has to be a little careful when looking at the numbers presented from codes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Let me point out one last subtlety from a mathematical point of view. When checking the convergence in density / gradient one is faced with the problem that these quantities are vectors or matrices, but of course we want to check convergence in a number. So we need to take the norm of the difference. But which norm should we choose? Most codes to the best of my knowledge use the Frobenius or l2 norms (so just square the elements, add them up and take the square root), but this is just one choice. There are plenty of other norms, see the wikipedia articles on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lp_space&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lp norms&lt;/a&gt; and the &lt;a href=&quot;https://en.wikipedia.org/wiki/Matrix_norm&quot; rel=&quot;nofollow noreferrer&quot;&gt;matrix norms&lt;/a&gt; to get an idea. Which norm is the best one to choose depends a little on which property you are after in your calculation: Total energy, forces / gradients wrt. nuclear positions, partial charges etc, just because these ask different questions about the mathematical properties of the wavefunction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, the take-away from this is not that one should use a different norm depending on what property one is after. This is just impractical and also in calculations with their finite basis set sizes all norms are equivalent up to a constant. But this constant might not be small and usually depends on the size of the basis (it typically grows with larger bases). So depending on what property you are after in the end, the number of digits you can trust in the computed answer differs. For example, even if the density is converged to 6 digits in the Frobenius norm, the forces might only be correct to 5 and the partial charges to 4.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="5" LastEditDate="2020-05-20T22:03:18.127" LastActivityDate="2020-05-20T22:03:18.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="838" PostTypeId="1" CreationDate="2020-05-18T07:25:45.957" Score="16" ViewCount="150" Body="&lt;p&gt;Plenty of standard plane-wave codes are able to compute correlation energies on top of DFT solutions using the random-phase approximation (RPA). I was wondering what the typical capabilities are in terms of scaling (Default RPA is O(N^4), but approximations can lower it) and the largest systems the codes report to be treatable. I am most strongly focused on open-source codes.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="5" LastEditDate="2020-07-04T14:52:55.113" LastActivityDate="2020-07-21T22:16:15.713" Title="What are typical RPA capabilities of plane-wave codes?" Tags="|software|reference-request|high-performance-computing|open-source|random-phase-approximation|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="839" PostTypeId="5" CreationDate="2020-05-18T07:34:30.440" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T07:34:30.440" LastActivityDate="2020-05-18T07:34:30.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="840" PostTypeId="4" CreationDate="2020-05-18T07:34:30.440" Score="0" Body="Topics concerning the random-phase approximations (RPA)" OwnerUserId="327" LastEditorUserId="327" LastEditDate="2020-05-18T10:37:14.707" LastActivityDate="2020-05-18T10:37:14.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="841" PostTypeId="1" AcceptedAnswerId="1130" CreationDate="2020-05-18T08:00:38.047" Score="10" ViewCount="285" Body="&lt;p&gt;&lt;br&gt;&#xA;&lt;strong&gt;How to maximize the efficiency/time-to-solution of the calculations in Q-Chem on HPC clusters?&lt;/strong&gt;&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;MPI parallelization is supposed to improve time-to-solution as compared to OpenMP. The system I tested numerous times has 80 alpha and 80 beta electrons (requested basis set is 6-311+G(d,p), there are 158 shells and 462 basis functions). The job (geometry optimization followed by frequency calculation) was running on 16 cpus either on a single node:&lt;br&gt;&#xA;qchem -np 1 -nt 16 INPUT.inp OUTPUT.out&lt;br&gt;&lt;br&gt;&#xA;or on 4 nodes with 4 cpus in MPI fashion:&lt;br&gt;&#xA;qchem -np 4 -nt 4 INPUT.inp OUTPUT.out&lt;br&gt;&lt;br&gt;&#xA;Still, OpenMP works much faster. &lt;strong&gt;Am I wrong here? Should it be exactly like this?&lt;/strong&gt;&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I also tried hybrid MPI+OpenMP way. For that I added 'export OMP_NUM_THREADS=4' line to my SLURM script, but it still lost in time to OpenMP, but at least was after than MPI.&lt;br&gt;&lt;br&gt;&#xA;&lt;strong&gt;Is it possible to accelerate such calculations?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2020-05-30T03:23:49.710" LastActivityDate="2020-05-30T03:23:49.710" Title="When running DFT on Q-Chem with an HPC cluster, why is parallelization with OpenMP faster than with MPI?" Tags="|density-functional-theory|software|ab-initio-calculations|q-chem|high-performance-computing|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="842" PostTypeId="2" ParentId="502" CreationDate="2020-05-18T08:06:46.337" Score="9" Body="&lt;p&gt;As mentioned by @GeoffHutchison, &lt;a href=&quot;http://m3g.iqm.unicamp.br/packmol/home.shtml&quot; rel=&quot;noreferrer&quot;&gt;PACKMOL&lt;/a&gt; is probably the most used one for random dense packing of molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Sometimes this might however not suit your needs, e.g. if the shape you want to fit molecules into is not supported by PACKMOL or you want to achieve a certain distance. I achieved good results using the surface tools of &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;. Since it's Python you can create random positions with restraints you choose. Of course you will lack the automatic overlap prevention PACKMOL offers.&lt;/p&gt;&#xA;" OwnerUserId="607" LastActivityDate="2020-05-18T08:06:46.337" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="843" PostTypeId="2" ParentId="832" CreationDate="2020-05-18T08:57:29.933" Score="13" Body="&lt;p&gt;This is actually a tricky question. First your use of &quot;non equilibrium&quot; is incorrect. Without more information on your MC simulations, especially on the applied biases and simulation process, one cannot state if you are in an out-of-equilibrium (OOE) regime (not state) or not. The way you define it as a state far from the ground state can be a &quot;local&quot; equilibrium in which the system is trapped. This can be, for example, a glassy state obtained from quenching (and yes I know the definition of glass as OOE states is a blurred field). In such a case, the system does not need an external force to be kept far from the ground state (because of the energy barrier it needs a really long time to pass) and it is actually not &quot;out-of-equilibrium&quot; in a thermodynamic sense. It is just a very unlikely state of the equilibrium distribution that would eventually relax using standard techniques (in an infinitely long time, depending on your MC moves).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The referee's definition you give is related to the regime of your whole system. If your system is in a steady-state with a bias or a force which maintains it in such a state, then you are in a truly OOE regime. Removing the bias is supposed to let the system free to go back in an equilibrium state, even a local one (not especially the ground state).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I think you should refer clearly to the source of your unlikely configurations and clarify this point in your manuscript.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Sidenote: As an example, some MC simulations use a so-called &quot;local equilibrium&quot; technique to simulate OOE regimes at the atomic/spin level: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/037843719390463E&quot; rel=&quot;noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/037843719390463E&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="432" LastActivityDate="2020-05-18T08:57:29.933" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="844" PostTypeId="2" ParentId="431" CreationDate="2020-05-18T09:04:29.963" Score="2" Body="&lt;p&gt;Well, arguably the &lt;strong&gt;core numerical routine&lt;/strong&gt; in density functional theory is the evaluation of the exchange-correlation functional itself, and the evaluation by quadrature of the integrals where the exchange-correlation functional sits.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-18T09:04:29.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="845" PostTypeId="2" ParentId="62" CreationDate="2020-05-18T09:45:52.643" Score="9" Body="&lt;p&gt;I assume you're referring to eq 51 of the Hirata-Head-Gordon-Bartlett paper.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One should note that these are not two-electron integrals, since there is only one spatial position; these are rather weighted four-center one-electron integrals.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As always, the problem when you have four indices is that there is a &lt;strong&gt;huge&lt;/strong&gt; number of integrals that come out, and you might not have storage for them.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another issue is that the set of four-products is linearly dependent to a ridiculous degree. If you start out with a atomic basis set, in usual electron repulsion integrals you get basis function products. Most of these will be linearly dependent, and you get out a linearly growing number of independent functions (this is why the Cholesky decomposition is so powerful in repulsion integrals) and the rest &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; are linearly dependent.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, instead of basis function products, you have products of basis function products. Again, you only get a linearly growing number of independent functions, with a prefactor higher than in the two-electron case, meaning that the number of linearly dependent functions grows as &lt;span class=&quot;math-container&quot;&gt;$O(N^4)$&lt;/span&gt;. So, you'd like to get a large number of integrals that are mostly linearly dependent.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Other than this issue, there's nothing that would prevent you from evaluating the integrals in the same way as is done in the paper. That is, you just need numerical quadrature to do it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you had an optimized version of the procedure, one could extract the integrals by &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; calls to eq (54). But this is going to be so costly that I doubt that you could do it in anything except the smallest basis set...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="7" LastEditDate="2020-05-18T16:13:36.650" LastActivityDate="2020-05-18T16:13:36.650" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="846" PostTypeId="2" ParentId="500" CreationDate="2020-05-18T09:59:16.580" Score="3" Body="&lt;p&gt;Note that Q-Chem and Psi4 are not actually measuring the change in the density, but rather the orbital gradient. There is a subtle difference: no change in the density does not mean the energy has been minimized, but if the orbital gradient is zero you're mathematically certain to be at an extremal point, which can be either a local minimum or a saddle-point solution.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-18T09:59:16.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="847" PostTypeId="1" AcceptedAnswerId="908" CreationDate="2020-05-18T10:08:39.757" Score="14" ViewCount="1390" Body="&lt;p&gt;I have calculated elastic constants for Si, GaAs, and GaN using LDA and GGA in VASP. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;LDA is giving better results than GGA for elastic constants. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there is a reason behind the good results by LDA in this case. Is there any reference I can read to understand why this is so? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I also found some reviews on this but I am not able to understand the explanation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Reviews:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Råsander, M., and M. A. Moram. &quot;On the accuracy of commonly used density functional approximations in determining the elastic constants of insulators and semiconductors.&quot; The Journal of chemical physics 143.14 (2015): 144104.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Van de Walle, A., and G. Ceder. &quot;Correcting overbinding in local-density-approximation calculations.&quot; Physical Review B 59.23 (1999): 14992.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="606" LastEditorUserId="606" LastEditDate="2020-06-17T12:02:46.657" LastActivityDate="2022-01-31T16:00:40.543" Title="Is LDA better than GGA for elastic constants?" Tags="|density-functional-theory|vasp|functional|elastic-constants|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="848" PostTypeId="2" ParentId="776" CreationDate="2020-05-18T10:25:08.283" Score="7" Body="&lt;p&gt;Since you are referring to &quot;the Morse potential&quot;, I assume you mean to use it for modeling van der Waals interactions?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If not, please ignore this answer and consider updating your question to include what kind of potential you are modeling using the Morse potential.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If so, here is my answer:&#xA;There is a rule of thumb based on experience and a lot of previous studies, but not based on equilibrium distance as far as I am informed.&#xA;Most of the times people use cutoff values of around 10-12Å nowadays.&#xA;If you want to be rigorous you can test your cutoff with the system you want to study, it will greatly depend on the type of system you are studying.&#xA;Check out the paper of &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00586&quot; rel=&quot;noreferrer&quot;&gt;Jablonka et al.&lt;/a&gt; for some insight into the problem of cutting the vdW potential. When necessary and available you might want to consider using tail corrections to smooth out the error introduced by cutting the potential.&#xA;You will also find in there, that the influence of the cutoff on forces is however negligible. So if you are not analyzing energies but movement, the errors due to the cutoff are not that important.&lt;/p&gt;&#xA;" OwnerUserId="607" LastActivityDate="2020-05-18T10:25:08.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="849" PostTypeId="5" CreationDate="2020-05-18T12:05:54.493" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T12:05:54.493" LastActivityDate="2020-05-18T12:05:54.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="850" PostTypeId="4" CreationDate="2020-05-18T12:05:54.493" Score="0" Body="Questions about corrections to the potential due to electron-electron interactions." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T13:10:55.140" LastActivityDate="2020-05-18T13:10:55.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="851" PostTypeId="5" CreationDate="2020-05-18T12:15:56.717" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T12:15:56.717" LastActivityDate="2020-05-18T12:15:56.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="852" PostTypeId="4" CreationDate="2020-05-18T12:15:56.717" Score="0" Body="Questions regarding the various types of visualization software for materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T13:41:24.960" LastActivityDate="2020-05-18T13:41:24.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="853" PostTypeId="5" CreationDate="2020-05-18T12:35:54.067" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T12:35:54.067" LastActivityDate="2020-05-18T12:35:54.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="854" PostTypeId="4" CreationDate="2020-05-18T12:35:54.067" Score="0" Body="For questions concerning Molden, a molecular and electronic structure visualization program." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-18T13:10:38.580" LastActivityDate="2020-05-18T13:10:38.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="855" PostTypeId="1" CreationDate="2020-05-18T12:44:28.340" Score="8" ViewCount="215" Body="&lt;p&gt;Many DFT codes use pseudopotentials to represent the electron-ion interaction (as do most plane-wave codes and in contrast to so-called &quot;all-electron&quot; programs). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are several &lt;a href=&quot;https://www.nnin.org/search/node/pseudopotential&quot; rel=&quot;noreferrer&quot;&gt;resources&lt;/a&gt; on the web to generate pseudopotentials in different formats and for different DFT codes. One of them is the program &lt;a href=&quot;http://bohr.inesc-mn.pt/~jlm/pseudo.html&quot; rel=&quot;noreferrer&quot;&gt;ATOM&lt;/a&gt;. Bellow is an example ot the ATOM input file for carbon.&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;       pg                  -- file generated from C ps file&#xA;        tm2&#xA;    C   ca &#xA;     0.000     0.000     0.000     0.000     0.000     0.000&#xA;    1    4&#xA;    2    0     2.000     0.000    #2s&#xA;    2    1     2.000     0.000    #2p&#xA;    3    2     0.000     0.000    #3d&#xA;    4    3     0.000     0.000    #4f&#xA;   1.56000   1.56000   1.56000   1.56000   0.00000   0.00000&#xA;&#xA;#23456789012345678901234567890123456789012345678901234567890      Ruler&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;My question is: how to generate a pseudopotential for a cation/anion?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="389" LastEditDate="2020-05-18T13:21:44.183" LastActivityDate="2020-05-19T14:22:18.640" Title="How to generate a pseudopotential for a cation/anion?" Tags="|density-functional-theory|pseudopotentials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="857" PostTypeId="1" CreationDate="2020-05-18T13:39:32.963" Score="17" ViewCount="449" Body="&lt;p&gt;What is a good open source software for calculating the rotational and translational entropy of molecules?  The National Institute of Standards and Technology does not provide standard molar entropy for all molecules.&lt;/p&gt;&#xA;" OwnerUserId="619" LastEditorUserId="24" LastEditDate="2020-07-03T21:41:05.647" LastActivityDate="2020-07-04T14:32:31.520" Title="Are there any open source software for calculating the rotational and translational entropy of molecules?" Tags="|software|molecular-modeling|open-source|entropy|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="858" PostTypeId="1" CreationDate="2020-05-18T13:40:47.807" Score="9" ViewCount="218" Body="&lt;p&gt;Which VASP output energy, after sigma -&gt; 0 or before, do you use when combining with zero point energy and vibrational entropy obtained via vtst tools?  (Vtst tools provide the vibrational frequencies from which zero point energy and vibrational entropy are calculated.)&lt;/p&gt;&#xA;" OwnerUserId="619" LastEditorUserId="5" LastEditDate="2020-05-18T17:06:12.550" LastActivityDate="2020-05-18T17:06:12.550" Title="VASP output energy" Tags="|vasp|gibbs-free-energy|entropy|zero-point-energy|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="859" PostTypeId="1" AcceptedAnswerId="906" CreationDate="2020-05-18T13:49:27.633" Score="12" ViewCount="1122" Body="&lt;p&gt;Currently, I did a Monte Carlo simulation with the local update and Wolff cluster updated in 2D classical Ising model. I use the autocorrelation function to compare 2 different algorithm in critical temperature (T ~ 2.269). That's what I got.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/6Bnja.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6Bnja.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&#xA;Is it correct? The local updated algorithm didn't show the exponential decay in the beginning. And it will become negative as it pass through 0. What I expect is that it has an exponential decay in the beginning and fluctuate around 0 once the sample become decorrelated. The equation I used to evaluate the autocorrelation function is &lt;span class=&quot;math-container&quot;&gt;$$A(\tau)=\frac{\langle Q_kQ_{k+\tau}\rangle-\langle Q_k\rangle^2}{\langle Q_k^2\rangle-\langle Q_k\rangle^2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="35" LastEditDate="2020-05-27T09:40:24.777" LastActivityDate="2020-05-27T11:36:13.377" Title="Autocorrelation function problem in Monte Carlo simulation of 2D Ising model" Tags="|model-hamiltonians|monte-carlo|ising-model|quantum-monte-carlo|spin-models|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="860" PostTypeId="2" ParentId="857" CreationDate="2020-05-18T14:05:11.600" Score="14" Body="&lt;h2&gt;ASE: Thermochemistry module&lt;/h2&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;thermochemistry module of ASE&lt;/a&gt; is able to calculate these for you.&lt;/p&gt;&#xA;" OwnerUserId="607" LastEditorUserId="5" LastEditDate="2020-07-04T14:31:30.013" LastActivityDate="2020-07-04T14:31:30.013" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="861" PostTypeId="1" CreationDate="2020-05-18T15:12:05.067" Score="13" ViewCount="697" Body="&lt;p&gt;Quantum ESPRESSO presents several levels of &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node18.html&quot; rel=&quot;noreferrer&quot;&gt;parallelization&lt;/a&gt;, including worlds, images, polls, and so on. However, there is a very intricate (and not clear to me) relationship between k-point sampling, the number of atoms in the cell, and how the parallel tasks are distributed.  The parallelization can turn a calculation very quick or very slow depending on the right or wrong choice of parameters. Is there a comprehensive manual or &quot;rule&quot; to decide on how to pick the right parameters for a parallel run?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-05-18T15:14:50.593" LastActivityDate="2020-05-21T03:28:39.407" Title="Parallelization levels on Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="862" PostTypeId="1" CreationDate="2020-05-18T15:29:04.583" Score="16" ViewCount="1321" Body="&lt;p&gt;The power of computation required to perform a DFT calculation increases with the size of the system. Therefore, for some systems, is mandatory to use high-performance-computers, clusters, and grids. One of the main ingredients in their administration is a job scheduler. There are some possibilities, such as &lt;a href=&quot;https://slurm.schedmd.com/documentation.html&quot; rel=&quot;noreferrer&quot;&gt;Slurm&lt;/a&gt; and &lt;a href=&quot;https://flux.ly/flux-demo?utm_source=google_ads&amp;amp;utm_medium=ppc&amp;amp;utm_campaign=demo_cta&amp;amp;gclid=CjwKCAjw5Ij2BRBdEiwA0Frc9dw0CdzuU6E62NgIZSe6OpuygQxFJ3MUjhwLUJBPuqqv_rY1xWxFSxoC-esQAvD_BwE&quot; rel=&quot;noreferrer&quot;&gt;PBS&lt;/a&gt; but the configuration is not a simple and intuitive task, even with some tutorials spread on-line. Are there alternatives to more &quot;user-friendly&quot; schedulers, capable to perform basic queue administration?   &lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="7" LastEditDate="2021-07-30T20:13:48.203" LastActivityDate="2021-07-30T20:13:48.203" Title="Job scheduler alternatives" Tags="|high-performance-computing|job-scheduler|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="863" PostTypeId="2" ParentId="181" CreationDate="2020-05-18T15:35:09.503" Score="17" Body="&lt;p&gt;(Expanding my comment into an answer)&#xA;When ML-based forcefields are compared to classical forcefield directly, I think we miss the most important points. ML-based models have several advantages:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;They do not need an &lt;em&gt;a priori&lt;/em&gt; &quot;correct&quot; description of the system, nor are they limited by the applicability of specific theories to your system. Classical force fields are very sophisticated for problems like biological molecules or water simulation, but once you start simulating transition metal compounds or their oxides, suddenly you have to invent new types of forcefields. ML-based models are flexible; you do not have to invent it every single time. Also, they are flexible in the sense that their accuracy is not limited by the model you choose: it is possible to improve their accuracy by training them on more data.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Therefore, theoretically, one can reach CCSD(T) or whatever level of accuracy if enough data is previously collected &lt;a href=&quot;https://doi.org/10.1038/s41467-019-10827-4&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;We generally know (and measure) the errors. It is not really a theoretical limitation, but as far as I know, MM software like Gromacs or NAMD is not telling you when your system is far from the training set. &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Why is it important?&#xA;We can do things like new forcefields on the fly: one can start an MD simulation with DFT, and parallel train a forcefield. Continue the simulation with ML-forcefield and calculate DFT only when something new is happening (a structure that is far from the training set)&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Machine_learning_force_field:_Theory&quot; rel=&quot;noreferrer&quot;&gt;[2]&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are they slow compared to a GROMACS force field? Yes.&#xA;But it is mostly irrelevant in cases where there is no classic force field at all or where more accuracy is needed or when you speed up a QM-MD simulation x100...0(?) times.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Smith, J.S., Nebgen, B.T., Zubatyuk, R. et al. &quot;Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.&quot; Nat Commun 10, 2903 (2019). DOI: 10.1038/s41467-019-10827-4&lt;/li&gt;&#xA;&lt;li&gt;Vasp.at. 2020. Machine Learning Force Field: Theory - Vaspwiki. [online] Available at: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Machine_learning_force_field:_Theory&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Machine_learning_force_field:_Theory&lt;/a&gt; [Accessed 18 May 2020]&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="91" LastEditorUserId="7" LastEditDate="2020-05-18T15:58:33.343" LastActivityDate="2020-05-18T15:58:33.343" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="864" PostTypeId="2" ParentId="858" CreationDate="2020-05-18T15:35:26.903" Score="8" Body="&lt;p&gt;Always use the energy after extrapolation back to 0 K. The energy before the extrapolation is just from your smearing method and is a fictitious value. &lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-18T15:35:26.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="865" PostTypeId="5" CreationDate="2020-05-18T15:40:57.900" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T15:40:57.900" LastActivityDate="2020-05-18T15:40:57.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="866" PostTypeId="4" CreationDate="2020-05-18T15:40:57.900" Score="0" Body="Topic concerning job scheduling and queue management software on high-performance clusters." OwnerUserId="327" LastEditorUserId="327" LastEditDate="2020-05-18T16:02:21.633" LastActivityDate="2020-05-18T16:02:21.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="867" PostTypeId="5" CreationDate="2020-05-18T15:41:35.083" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T15:41:35.083" LastActivityDate="2020-05-18T15:41:35.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="868" PostTypeId="4" CreationDate="2020-05-18T15:41:35.083" Score="0" Body="Questions concerning the slurm queue management system." OwnerUserId="327" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:33.970" LastActivityDate="2020-05-21T22:08:33.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="869" PostTypeId="5" CreationDate="2020-05-18T15:41:52.780" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T15:41:52.780" LastActivityDate="2020-05-18T15:41:52.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="870" PostTypeId="4" CreationDate="2020-05-18T15:41:52.780" Score="0" Body="Question concerning the Portable Batch System (PBS) queue management system." OwnerUserId="327" LastEditorUserId="7" LastEditDate="2020-05-18T16:02:07.187" LastActivityDate="2020-05-18T16:02:07.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="871" PostTypeId="1" AcceptedAnswerId="874" CreationDate="2020-05-18T17:54:53.497" Score="12" ViewCount="4415" Body="&lt;p&gt;I did a docking job and got a score of -5.69 kcal/mol and a value for MM-GBSA of -60 kcal/mol. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I should analyze these results for my thesis but do not know how to comment on them. Does anyone have any insight about what this number might mean?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also on interactions, I wonder what can be said? Are there plots of the data that would be appropriate to include? &lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="24" LastEditDate="2020-05-18T20:54:44.093" LastActivityDate="2020-06-18T13:39:41.047" Title="How I can analyze and present docking results?" Tags="|binding-energy|docking|glide|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="872" PostTypeId="1" AcceptedAnswerId="876" CreationDate="2020-05-18T18:11:40.183" Score="4" ViewCount="49" Body="&lt;p&gt;I am trying to implement a tether restraint in the MM region of my QM/MM calculation using pDynamo (CHARMM/ORCA interface). I need to define the origin as a Vector3. Does anyone know how to do this?&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-05-18T20:11:03.993" Title="Defining coordinates using Vector3" Tags="|software|orca|pdynamo|charmm|qmmm|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="873" PostTypeId="2" ParentId="871" CreationDate="2020-05-18T18:18:04.390" Score="8" Body="&lt;p&gt;Docking results can be analyzed in a number of ways by looking at various geometric parameters, such as a distances, angles and dihedrals. These are then typically compared against &quot;ideal&quot; values, such as a those at the transition state. Graphs typically contain a parameter on each axis with the results and ideal points plotted. Interactions can mean various things, such as H-bonds and pi-interactions. &lt;em&gt;Comment made before revisions to initial question&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="510" LastEditDate="2020-05-18T18:56:10.790" LastActivityDate="2020-05-18T18:56:10.790" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="874" PostTypeId="2" ParentId="871" CreationDate="2020-05-18T18:41:33.447" Score="13" Body="&lt;p&gt;You can analyze your docking results in two ways.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;First way is looking for the score function your program uses. For some score functions, lower value indicates better interactions and for others, higher values indicate better interactions. Also,, look for the decomposition of the score. Normally, the score is composed by different type of interaction/penalties like Coulomb electrostatic interaction, van der Waals interaction, H-bond interaction, etc. This partition scheme will help you to understand which is the main mechanism of interaction between your ligand and the protein.&#xA;&lt;strong&gt;This should be the main way to get conclusions about how the interaction occurs.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The second way is by visually inspecting the 2D Interaction diagram. To produce those diagrams, you need to use another software like &lt;a href=&quot;https://www.schrodinger.com/maestro&quot; rel=&quot;noreferrer&quot;&gt;Maestro&lt;/a&gt;, &lt;a href=&quot;https://www.ebi.ac.uk/thornton-srv/software/LigPlus/&quot; rel=&quot;noreferrer&quot;&gt;LigPlot+&lt;/a&gt;, &lt;a href=&quot;http://www.pegase-biosciences.com/leview-ligand-environment-viewer/&quot; rel=&quot;noreferrer&quot;&gt;LeView&lt;/a&gt;,  &lt;a href=&quot;https://www.zbh.uni-hamburg.de/en/forschung/amd/server/poseview.html&quot; rel=&quot;noreferrer&quot;&gt;PoseView&lt;/a&gt;, and &#xA;&lt;a href=&quot;https://projects.biotec.tu-dresden.de/plip-web/plip&quot; rel=&quot;noreferrer&quot;&gt;Protein-Ligand Interaction Profiler&lt;/a&gt; just to cite a few.&#xA;&lt;strong&gt;Not all the relevant information about the interactions is shown in this 2D diagrams.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-18T18:41:33.447" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="875" PostTypeId="2" ParentId="643" CreationDate="2020-05-18T19:55:22.070" Score="8" Body="&lt;p&gt;The 1-dimensional unitary group U(1) simply corresponds to all complex numbers with a modulus of 1. This is isomorphic to the special orthogonal group SO(2), which corresponds to all real 2x2 rotation matrices. This is the case because because any element of U(1) is uniquely defined by its complex phase (going from 0 to 2pi) and this can be mapped uniquely onto the rotation angle in SO(2).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;SO(2) is a subgroup of the orthogonal group O(2). O(2) also contains the improper rotations. As a consequence O(2) should be seen as a &quot;larger&quot; group than U(1), I would say.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-05-18T19:55:22.070" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="876" PostTypeId="2" ParentId="872" CreationDate="2020-05-18T19:58:13.667" Score="5" Body="&lt;p&gt;In pdynamo 3.0.9&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A &lt;code&gt;vector3&lt;/code&gt; can be defined by importing from &lt;code&gt;Geometry&lt;/code&gt; module. For example, &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;center = Vector3.Null ( )&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It looks like a vector3 is just 3 element vector. Not really sure but here is what I found in &lt;code&gt;pScientific/Symmetry/PointGroupFinder.py&lt;/code&gt; file &lt;/p&gt;&#xA;&#xA;&lt;p&gt;You will need to get the center of mass however by looping over each atom in the geometry&#xA;e.g. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$X_i = \displaystyle\sum_a^{N_a} m_a x_{ia}/M $&lt;/span&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Which could be done in python like &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;np.sum([xyz[i,:]*atomic_masses[i]/M for i in range(self.natoms)],axis=0)&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, you are going to want to use an explicit for loop and loop over the &lt;code&gt;coordinates3&lt;/code&gt; of your geometry. Furthermore, you're gonna need the masses.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It looks like that's stored in &lt;code&gt;system.atoms&lt;/code&gt; e.g. &lt;code&gt;atom.mass&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But that's a separate problem. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There may be a simple trick to do this but I'm not that familiar with pDynamo!&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-18T20:11:03.993" LastActivityDate="2020-05-18T20:11:03.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="877" PostTypeId="1" AcceptedAnswerId="1135" CreationDate="2020-05-18T20:09:30.197" Score="14" ViewCount="136" Body="&lt;p&gt;I've been trying to learn about Green's function in the context of computational chemistry by reading Szabo and Ostlund's &lt;a href=&quot;https://play.google.com/store/books/details?id=KQ3DAgAAQBAJ&amp;amp;source=productsearch&amp;amp;utm_source=HA_Desktop_US&amp;amp;utm_medium=SEM&amp;amp;utm_campaign=PLA&amp;amp;pcampaignid=MKTAD0930BO1&amp;amp;gclid=Cj0KCQiAuZXQBRDKARIsAMwpUeQOSUb5s8bZi79Iiskp1cEbWAvuOc0_FXxmuAR6-wkOg6_l5ZVNZv0aAlmuEALw_wcB&amp;amp;gclsrc=aw.ds&amp;amp;dclid=CO2h9JG5tNcCFQK7Twodf-gBig&quot; rel=&quot;nofollow noreferrer&quot;&gt;Modern Quantum Chemistry&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I've reached a section about the one particle many body Green's function and I'm confused about an approximation the authors use to obtain the lowest order correction to the ionization potential/electron affinity. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;They write, in regards to solving the Dyson equation,&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\det\left[E\mathbf{1}-\epsilon_i-\mathbf{\Sigma}(E)\right]=0 \tag{7.42}$$&lt;/span&gt; &#xA;  When &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\Sigma}(E)=0$&lt;/span&gt;, the roots occur at &lt;span class=&quot;math-container&quot;&gt;$\mathbb{\epsilon}_i$&lt;/span&gt;'s. To find the lowest order correction to these Koopman's theorem results, let us ignore the off-diagonal elements of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\Sigma}(E)$&lt;/span&gt;. Then Eq. (&lt;span class=&quot;math-container&quot;&gt;$7.42$&lt;/span&gt;) simplifies to &lt;span class=&quot;math-container&quot;&gt;$$\prod_i(E-\epsilon_i-\Sigma_{ii}(E))\tag{7.43}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt; are orbital energies and &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the self-energy. What I don't understand is, &lt;em&gt;what justifies ignoring the off diagonal elements&lt;/em&gt;? Or rather, &lt;em&gt;what error is introduced by this approximation&lt;/em&gt;? I would think the lowest order correction would take the entire second order self energy, including off-diagonal elements.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;They actually later show the results of some example calculations and have results for just the diagonal, second order self energy and the full matrix second order result. &lt;em&gt;Is there something about the self energy that makes taking just the diagonal reasonable&lt;/em&gt;?&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-30T02:27:53.013" LastActivityDate="2020-05-30T07:06:42.997" Title="Approximation of Dyson's Equation" Tags="|electronic-structure|greens-functions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="878" PostTypeId="1" CreationDate="2020-05-18T20:11:23.707" Score="16" ViewCount="223" Body="&lt;p&gt;I was wondering what tools there are for visualising aromaticity and anti-aromaticity in molecules, to what quantum chemistry programs they are interfaced, and what other relevant features they have.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So far, I found:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.otto-diels-institut.de/herges/pages_en/projects_acid.html&quot; rel=&quot;noreferrer&quot;&gt;ACID&lt;/a&gt;, which is interfaced only to Gaussian. This seems to be a very popular tool but has a rather rigid workflow.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://gimic.readthedocs.io/&quot; rel=&quot;noreferrer&quot;&gt;GIMIC&lt;/a&gt; interfaced to a number of different programs. This seems to be more flexible but also a bit harder to use.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="115" LastEditorUserId="5" LastEditDate="2020-05-18T20:16:26.220" LastActivityDate="2021-01-26T19:39:43.470" Title="Methods for visualising aromaticity" Tags="|software|electronic-structure|molecular-modeling|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="879" PostTypeId="1" CreationDate="2020-05-18T20:24:43.593" Score="18" ViewCount="415" Body="&lt;p&gt;I'm trying to set up iQmol as a tool to submit calculations to Q-Chem on our lab machines to make access to it easier for OChem students. Unfortunately, it is not working properly &amp;quot;from the box&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;By default, when one creates a local server in iQmol it uses the csh shell environment and it looks like I only need to adjust Q-Chem environment:&lt;br&gt;&lt;a href=&quot;https://i.stack.imgur.com/8QeqX.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8QeqX.png&quot; alt=&quot;local_server_settings&quot; /&gt;&lt;/a&gt;&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;These settings nicely work for HF calculations, but when I try to use DFT I have a significant issue: SP or Optimization calculations go fine, but when Frequency calculation is added as a job, the calculation fails at the step &lt;code&gt;&amp;quot;Calculating analytic Hessian of the SCF energy&amp;quot;.&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the case of H&lt;sub&gt;2&lt;/sub&gt; molecule I stops like this:&lt;br&gt;&#xA;&lt;code&gt;Polarizability Matrix (a.u.)&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;            1           2           3&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;    1   0.0000000   0.0000000   0.0000000&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;    2   0.0000000   0.0000000   0.0000000&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;    3   0.0000000   0.0000000  -6.3752744&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt; Calculating analytic Hessian of the SCF energy&lt;/code&gt;&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;It also gives an error message:&lt;br&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/wRpUJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wRpUJ.png&quot; alt=&quot;error_message&quot; /&gt;&lt;/a&gt;&lt;br&gt;&#xA;and the scratch folder for the job is not cleared after the job.&lt;/p&gt;&#xA;&lt;p&gt;The input file is not the issue, as the same file can be submitted using the terminal and the calculation finishes successfully. It does not seem to be a memory issue, as specification of MEM_TOTAL and MEM_STATIC does not solve the problem. I thought that there might be a problem in server settings, but I can't figure out what exactly happened.&lt;/p&gt;&#xA;&lt;p&gt;I will very much appreciate any suggestion and advice!&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2020-10-06T14:06:52.667" LastActivityDate="2021-04-21T02:47:52.707" Title="How to set up a local server for iQmol on macOS?" Tags="|software|visualization-software|q-chem|iqmol|apple-operating-system|" AnswerCount="1" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="880" PostTypeId="2" ParentId="862" CreationDate="2020-05-18T20:24:44.407" Score="15" Body="&lt;p&gt;This depends on what you want to do:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you have any kind of distributed computing (this might be 5 PCs in a lab with a central node), you will not be able to avoid using a scheduler to distribute jobs.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Running jobs locally, people have written &quot;first come first served&quot; schedulers in for example bash. However I would suggest that this is not the best choice.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Even for just your local usage, setting up a scheduler is the better way to go. (I have done this in the past using slurm. I also remember using the SunGrid Scheduler but I don't think I configured it... Or maybe I did and then it died in an Upgrade and was replaced by SLURM?)&#xA;For example using a scheduler allows you to dedicate only a part of the available CPU resources to computations while retaining some resources for day-to day tasks. Especially with today's multi-core CPUs, this is an enticing proposition.&#xA;Schedulers can also be more clever than a first come first served algorithm, slipping in smaller jobs while a large calculation awaits its execution which a simple shell script will typically no do.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It turns out that for a local installation, SLURM is really not that bad in terms of configuration. The biggest issue is that you (in my past experience pre-2018/19 I have not set it up since) &lt;strong&gt;cannot&lt;/strong&gt; use the loopback IP or localhost for the calculation node. Thus you are &lt;strong&gt;obliged&lt;/strong&gt; to assign a &lt;strong&gt;static IP address&lt;/strong&gt; (in the router) or to &lt;strong&gt;update the DHCP assigned IP-address in the config file when it changes&lt;/strong&gt; in addition to using a specific host name for your PC.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another advice is to install SLURM from the repository of your Linux distribution - this will ensure the correct dependencies are included.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A major simplification on a &quot;personal&quot; computer is, that you can assume that resource demands will be honest. -&gt; So while the scheduler takes the requested resources into account, there is no need to monitor resource usage.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the details of the configuration I will point at the documentation as this is eventually the only up-to date source:&#xA;&lt;a href=&quot;https://slurm.schedmd.com&quot; rel=&quot;noreferrer&quot;&gt;https://slurm.schedmd.com&lt;/a&gt;&#xA;(There was a funny bug about 3 years ago in how threads and processor cores were handled between openSUSE and Ubuntu which was not identical which made some parameter choices non-intuitive...)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another quick PS: SLURM offer a config tool in the form of a website to generate a configuration file. I believe it is also installed with the scheduler, the online version is here: &lt;a href=&quot;https://slurm.schedmd.com/configurator.html&quot; rel=&quot;noreferrer&quot;&gt;https://slurm.schedmd.com/configurator.html&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the end, every IT tool will seem daunting at first until the language used becomes clear. Setting up a scheduler may seem daunting at first, but once the process is clear, it is not actually a difficult task to execute.&#xA;(Balancing user shares and fair scheduling is yet another topic...)&#xA;There also isn't going to be a major difference between different scheduler as they invariably need to carry out similar task. The scheduler needs to know what resources are available on the computer node and where they are. - The computer node and head node can be the same. Thus the differences in the configuration are in the end cosmetic.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Selecting a scheduler which is widely used is insofar advisable as support is not likely to disappear soon. I used a cluster that employed the Sun Grid Scheduler (SGE) which no longer exists. There is a spiritual successor, called Son of Grid Engine (SGE) but it might not be non-trivial to run on a modern Linux-Distribution. (Icon libraries, other libraries.)&#xA;Selecting a mainstream scheduler such as SLURM or PBS (same syntax as SGE in the submission scripts, thanks for the comment pointing it out) will mean that you are familiar with a standard tool.&#xA;I.e. If you bring along experience with a standard scheduler, this is valuable to others both from being able to use established systems elsewhere to helping new users.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the warning side: Be careful that you make good use of your resources. I used to run calculations on an old AMD PC that had a total of 48 CPU cores but only one internal harddrive... - It turned out that running many jobs in parallel was slower than running then with more threads per job in fewer jobs, even leaving parts of the CPU unused due to the I/O bottleneck. &#xA;To get the best performance, you will need to actually determine what kind of calculation you wish to carry out and what bottlenecks your work will hit. For example, I used a code that even with DFT used temporary files in the calculations. And then the DLPNO-CCSD(T) calculations wrote large temporary files that had a huge I/O impact... - Of course minimising the number of parallel jobs was important in this case.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;PS: I anybody wants to turn this into a Wiki and update it, let me know and I'll tick the box. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I hope this slightly rambly post helps.&lt;/p&gt;&#xA;" OwnerUserId="540" LastActivityDate="2020-05-18T20:24:44.407" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="881" PostTypeId="1" AcceptedAnswerId="899" CreationDate="2020-05-18T20:33:21.563" Score="20" ViewCount="159" Body="&lt;p&gt;Quantum Monte Carlo simulations are often performed with very modest lattice sizes (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.96.035129&quot; rel=&quot;noreferrer&quot;&gt;such as&lt;/a&gt; [&lt;a href=&quot;https://journals.aps.org/prb/pdf/10.1103/PhysRevB.96.035129?casa_token=yZdAejuhHagAAAAA%3AGDpAOW46hZvGnqthfK2Y9g-OzI1z53kS-EqD3GPJce9OzNWG5Wg3hvoSH9OIbQ9c1OdttL_F1kl7&quot; rel=&quot;noreferrer&quot;&gt;e-print&lt;/a&gt;], &lt;span class=&quot;math-container&quot;&gt;$64$&lt;/span&gt; sites), due to their computational cost increasing exponentially with the system volume; while classic Monte Carlo simulations usually require much larger lattice sizes, even when making use of finite-size analysis.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Why are these small lattices enough for obtaining physically meaningful results for quantum systems? Is it simply a case of &quot;we take what we can get&quot;, or is there some intrinsically quantum mechanism in action&lt;sup&gt;[1]&lt;/sup&gt;?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1]&lt;sub&gt; Such as a symmetry-breaking magnetic field removing degeneracies for free electrons in a tight binding approximation. Ref.: NIC Series Vol. 10 (&lt;a href=&quot;http://www.john-von-neumann-institut.de/nic/EN/Publications/NICSeries/nic-series-1-10.html?nn=1487798&quot; rel=&quot;noreferrer&quot;&gt;ISBN 3-00-009057-6&lt;/a&gt;) (&lt;a href=&quot;https://juser.fz-juelich.de/record/24560/files/NIC-Band-10.pdf&quot; rel=&quot;noreferrer&quot;&gt;pdf 1&lt;/a&gt;, &lt;a href=&quot;https://core.ac.uk/download/pdf/35009945.pdf&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;), page 131.&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="625" LastEditorUserId="625" LastEditDate="2020-05-19T12:01:45.543" LastActivityDate="2020-05-21T02:24:31.753" Title="How can very small lattices be sufficient for Quantum Monte Carlo simulations?" Tags="|monte-carlo|quantum-monte-carlo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="882" PostTypeId="2" ParentId="878" CreationDate="2020-05-18T20:45:31.173" Score="13" Body="&lt;h1&gt;Multiwfn&lt;/h1&gt;&#xA;&lt;p&gt;The software &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt; can calculated four aromaticity indices, namely FLU, FLU-pi, PDI and information-theoretic index.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Multiwfn can perform wavefunction analyses based on outputted file of almost all well-known quantum chemistry programs, such as Gaussian, ORCA, GAMESS-US, Molpro, NWChem, Dalton, xtb, PSI4, Molcas, Q-Chem, MRCC, deMon2k, Firefly, CFour, Turbomole&lt;/em&gt; [&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;]&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-31T23:36:03.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="883" PostTypeId="1" AcceptedAnswerId="918" CreationDate="2020-05-18T20:46:47.060" Score="19" ViewCount="4294" Body="&lt;p&gt;A few years ago there was a significant difference between CPUs and GPUs for performing calculations. It was quite clear when to go for a CPU or a GPU. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Today there are GPUs with a very large number of cores and threads. I was away from the subject for a while.  Is there still such a marked difference?  Or can a CPU reasonably well replace a GPU in, say, molecular dynamics? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where should one put the money?&lt;/p&gt;&#xA;" OwnerUserId="522" LastEditorUserId="5" LastEditDate="2020-05-20T16:58:57.877" LastActivityDate="2020-05-20T16:58:57.877" Title="Should I buy a CPU or a GPU for doing calculations?" Tags="|high-performance-computing|graphical-processing-unit|" AnswerCount="4" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="884" PostTypeId="1" CreationDate="2020-05-18T21:02:24.567" Score="5" ViewCount="54" Body="&lt;p&gt;A common situation is that researches move slightly from their expertise area. In those cases, the tutorials for beginners are not suitable. A common doubt is &amp;quot;This is reasonable, I am sure but: will the reviewers complain?&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;For example, when choosing a functional for DFT, or a basis set for an &lt;em&gt;ab initio&lt;/em&gt; calculation, there are safe choices which are not the best ones in terms of accuracy/efficiency. Sometimes other choices require to give more detail and justification.&lt;/p&gt;&#xA;&lt;p&gt;Taking the above in mind: what are key points to move from gas phase to surfaces? Programs, methods, number of layers below the surface, levels of accuracy, etc.&lt;/p&gt;&#xA;" OwnerUserId="522" LastEditorUserId="5" LastEditDate="2021-01-24T23:23:11.980" LastActivityDate="2021-01-24T23:23:11.980" Title="Key points for studying surfaces intended for researchers on gas phase" Tags="|surfaces|" AnswerCount="0" CommentCount="3" ClosedDate="2020-05-19T15:57:50.173" ContentLicense="CC BY-SA 4.0" />
  <row Id="885" PostTypeId="1" CreationDate="2020-05-18T21:21:02.547" Score="20" ViewCount="1516" Body="&lt;p&gt;Ultrasoft pseudopotential (USPP), in general, requires a lower energy-cutoff to the plane waves when compared to Norm-Conserving ones (NC). On the other hand (at least with Quantum ESPRESSO) the charge-density cutoff should be bigger for the USPP, where it is always kept 4 times the energy cutoff for the NC. Apart from that, which other characteristics should be taken into account when choosing the pseudopotential? Are there specific properties more or less sensitive to one or another?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="142" LastEditDate="2020-05-23T13:38:47.127" LastActivityDate="2020-05-26T19:38:47.783" Title="Norm-Conserving or Ultrasoft, which pseudopotential to choose?" Tags="|density-functional-theory|quantum-espresso|pseudopotentials|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="886" PostTypeId="5" CreationDate="2020-05-18T21:32:30.587" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T21:32:30.587" LastActivityDate="2020-05-18T21:32:30.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="887" PostTypeId="4" CreationDate="2020-05-18T21:32:30.587" Score="0" Body="Questions relating to entropy. The entropy S, of a physical system, is related to the number of possible microscopic configurations of that system. It is also a measure of disorder in a physical system." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-05-18T22:33:47.163" LastActivityDate="2020-05-18T22:33:47.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="888" PostTypeId="5" CreationDate="2020-05-18T21:36:12.030" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-18T21:36:12.030" LastActivityDate="2020-05-18T21:36:12.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="889" PostTypeId="4" CreationDate="2020-05-18T21:36:12.030" Score="0" Body="Questions related to the binding energy of a system, i.e., the amount of energy required to separate a particle from a system of particles or to disperse all the particles of the system, especially as it pertains to the atoms and ions bound together in crystals." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T00:57:45.470" LastActivityDate="2020-05-19T00:57:45.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="890" PostTypeId="1" AcceptedAnswerId="1047" CreationDate="2020-05-18T22:03:06.250" Score="20" ViewCount="213" Body="&lt;p&gt;I was wondering what goes into the consideration of choosing the frequency to attempt swaps for replica exchange? &lt;a href=&quot;https://doi.org/10.1063/1.2816560&quot; rel=&quot;noreferrer&quot;&gt;D. Sindhikara, 2008&lt;/a&gt; proposes the faster the better, but this goes against the view that you should allow the systems to relax to their new conditions.&lt;/p&gt;&#xA;" OwnerUserId="636" LastEditorUserId="5" LastEditDate="2020-05-18T22:32:15.913" LastActivityDate="2020-05-23T13:11:44.503" Title="How to choose replica exchange interval?" Tags="|molecular-dynamics|enhanced-sampling|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="891" PostTypeId="1" AcceptedAnswerId="1118" CreationDate="2020-05-18T23:27:13.777" Score="14" ViewCount="343" Body="&lt;p&gt;In Jensen's Introduction to Computational Chemistry it says that the total non-relativistic Hamiltonian operator, transformed to the center of mass system, can be written, in atomic units, as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{H}=\hat{T}_N+\hat{H}_e+\hat{H}_{mp} $$&lt;/span&gt; &#xA;where &lt;span class=&quot;math-container&quot;&gt;$\hat{T}_N$&lt;/span&gt; is the kinetic energy of the nuclei, &lt;span class=&quot;math-container&quot;&gt;$\hat{H}_e$&lt;/span&gt; is the electronic Hamiltonian, and &lt;span class=&quot;math-container&quot;&gt;$\hat{H}_{mp}$&lt;/span&gt; is the mass polarization term, written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{H}_{mp}=-\frac{1}{2M_{tot}}\left(\sum_{i}^{N_{elec}}\nabla_i\right)^2$$&lt;/span&gt;&#xA;It happens that I did the transformation step-by-step and found that the mass polarization term should be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{H}_{mp}=-\frac{1}{2M_{tot}}\sum_{i}^{N_{elec}}\sum_{j\neq i}^{N_{elec}}\nabla_i\cdot\nabla_j $$&lt;/span&gt;&#xA;So, my first question is, why the textbook consider the case where &lt;span class=&quot;math-container&quot;&gt;$j=i$&lt;/span&gt; to be the only one? This is also strange, because in my derivation I only found mixed &lt;span class=&quot;math-container&quot;&gt;$j\neq i$&lt;/span&gt; terms. To be sure about this I tried with a three particle Hamiltonian and got the same. No terms with &lt;span class=&quot;math-container&quot;&gt;$j=i$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The other question is, if this term arises because it is not possible to separate the center of mass motion from the internal motion, then, how important is the contribution of mass polarization relative to non-adiabatic coupling elements (beyond Born-Oppenheimer approximation)?&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="36" LastEditDate="2020-05-19T12:13:29.360" LastActivityDate="2020-05-28T21:56:48.267" Title="On mass polarization terms" Tags="|quantum-mechanics|relativistic|non-adiabatic|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="893" PostTypeId="5" CreationDate="2020-05-19T01:53:07.443" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T01:53:07.443" LastActivityDate="2020-05-19T01:53:07.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="894" PostTypeId="4" CreationDate="2020-05-19T01:53:07.443" Score="0" Body="Questions regarding k-points in crystal geometric settings." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T06:10:22.353" LastActivityDate="2020-05-19T06:10:22.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="895" PostTypeId="5" CreationDate="2020-05-19T04:47:13.690" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T04:47:13.690" LastActivityDate="2020-05-19T04:47:13.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="896" PostTypeId="4" CreationDate="2020-05-19T04:47:13.690" Score="0" Body="Questions related to microstructures in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T13:20:56.267" LastActivityDate="2020-05-19T13:20:56.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="897" PostTypeId="2" ParentId="883" CreationDate="2020-05-19T05:45:59.893" Score="12" Body="&lt;p&gt;It depends a lot on your application. All problems can be solved on a CPU, &lt;strong&gt;some&lt;/strong&gt; problems can be solved much faster on a GPU. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;One thing to consider is the effort required to write your code. If you're writing your own code from scratch, adapting it for the GPU can be a lot of work, and potentially for little to no reward. On the other hand, if you're using software packages or certain libraries, enabling GPU support might be as simple as checking a box. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are you talking about configuring your own personal/work computer? How much do you plan on running your code on your machine itself (rather than a cluster, or dedicated workstation). If you're going to be running your code on a cluster, the amount of simulation you can get done on your personal machine won't matter much. In that case, you might want just enough CPU and GPU to do development and short tests. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="36" LastEditDate="2020-05-19T12:27:08.747" LastActivityDate="2020-05-19T12:27:08.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="898" PostTypeId="2" ParentId="890" CreationDate="2020-05-19T05:50:22.820" Score="8" Body="&lt;p&gt;As with many such hyperparameters, there is no hard and fast rule and you will probably have to do some testing to see what is best. The swap attempts may come with substantial overhead, which might be something to consider as well. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Disclaimer:&lt;/em&gt; my experience with replica exchange comes from quantum Monte Carlo, not MD. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-19T05:50:22.820" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="899" PostTypeId="2" ParentId="881" CreationDate="2020-05-19T06:07:07.130" Score="10" Body="&lt;p&gt;I think you are correct that there is an aspect of &quot;take what you can get&quot; to the sizes that are typically used in numerical methods. Even with finite size scaling (FSS), you usually try to go to the largest size that is practical with your computational resources. Case in point: people do finite size scaling with &lt;em&gt;extremely&lt;/em&gt; small sizes for exact diagonalization calculations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;It's worth noting that the finite size effects are themselves interesting and often &lt;a href=&quot;https://arxiv.org/abs/1603.04359&quot; rel=&quot;nofollow noreferrer&quot;&gt;contain important physical quantities&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There is one more specifically-quantum feature to consider: the finite size gap and the size-temperature tradeoff. In finite-size quantum systems, even gapless quantities have a finite-size gap &lt;span class=&quot;math-container&quot;&gt;$\Delta \propto 1/L$&lt;/span&gt; (basically because &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; becomes the maximum wavelength). This gap contributes directly to the finite-size effects, but also separates the &quot;finite-size zero-temperature&quot; and &quot;finite-temperature large-size&quot; regimes:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;When &lt;span class=&quot;math-container&quot;&gt;$\beta \Delta \gg 1$&lt;/span&gt;, then effectively the temperature is zero, because all the excited states, even the 'gapless' ones, are suppressed. &lt;/li&gt;&#xA;&lt;li&gt;When &lt;span class=&quot;math-container&quot;&gt;$\beta \Delta \ll 1$&lt;/span&gt;, the finite size effects are weaker because the system 'can't see' the finite-size gap.  &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;The &lt;strong&gt;computational cost&lt;/strong&gt; of QMC (at least the form I use, SSE) roughly scales like &lt;span class=&quot;math-container&quot;&gt;$\beta L^d$&lt;/span&gt;. Because of this finite-size gap, you need &lt;span class=&quot;math-container&quot;&gt;$\beta \propto L$&lt;/span&gt; to maintain the same `effective' temperature as you go to larger and larger sizes. As a result, zero-temperature properties are &lt;strong&gt;much&lt;/strong&gt; easier to access for small sizes (with a large gap, and not-too-low &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; requirement). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you want to avoid finite-size effects, then you want to &lt;strong&gt;avoid&lt;/strong&gt; low temperatures so you aren't detecting this finite-size gap. (Or you need a large system so &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; is small).  &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-21T02:24:31.753" LastActivityDate="2020-05-21T02:24:31.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="900" PostTypeId="2" ParentId="158" CreationDate="2020-05-19T11:59:19.077" Score="12" Body="&lt;p&gt;I think a good way to see this is to simplify the stage a little. Imagine we want to solve the Schrödinger equation for a Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;. For this we take a very simple basis, namely just two real-valued functions &lt;span class=&quot;math-container&quot;&gt;$\{f_1, f_2\}$&lt;/span&gt;. If we variationally optimise the trial wavefunction from this basis, we are presented with an approximation to the ground state in the linear combination &lt;span class=&quot;math-container&quot;&gt;$ \Psi = c_1 f_1 + c_2 f_2$&lt;/span&gt;&#xA;and some corresponding approximate energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;. Since we are variational, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ 0 = \frac{dE}{dc_1} = 2 \left\langle \Psi \middle| H \frac{d\Psi}{dc_1} \right\rangle = 2 \left\langle \Psi \middle| H f_1 \right\rangle$$&lt;/span&gt;&#xA;and similarly &lt;span class=&quot;math-container&quot;&gt;$0 = \left\langle \Psi \middle| H f_2 \right\rangle$&lt;/span&gt;.&#xA;Now the derivative of the energy wrt. positions can be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\frac{dE}{d\mathbf{R}}=\left\langle\Psi \middle|\frac{dH}{d\mathbf{R}}\Psi\right\rangle&#xA;+ 2 \left\langle \Psi \middle| H \frac{d\Psi}{d\mathbf{R}} \right\rangle&#xA;\end{equation}&lt;/span&gt;&#xA;with the second term being the Pulay forces of interest for us. Consider as an example the derivative wrt. &lt;span class=&quot;math-container&quot;&gt;$R_1$&lt;/span&gt;. Its Pulay term is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \left\langle \Psi \middle| H \left( c_1 \frac{df_1}{dR_1} + c_2 \frac{df_2}{dR_1} \right)\right\rangle. $$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;When is this term zero? Either when both the derivative of &lt;span class=&quot;math-container&quot;&gt;$f_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_2$&lt;/span&gt; wrt. &lt;span class=&quot;math-container&quot;&gt;$R_1$&lt;/span&gt; are zero, i.e. if the &lt;strong&gt;basis functions&lt;/strong&gt; by itself is &lt;strong&gt;independent of atomic positions&lt;/strong&gt;. This is the case for example for plane waves or generally all basis sets which are not atom-centred. The other option is if the &lt;strong&gt;derivatives&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$\frac{df_1}{dR_1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\frac{df_2}{dR_1}$&lt;/span&gt; are itself basis functions or &lt;strong&gt;can be exactly represented by the basis&lt;/strong&gt;. To see what happens then, assume this was the case. We could write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{df_1}{dR_1} = k_{11} f_1 + k_{12} f_2 \quad\text{and}\quad \frac{df_2}{dR_1} = k_{21} f_1 + k_{22} f_2$$&lt;/span&gt;&#xA;for appropriate constants and obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;&amp;amp;\hspace{-30pt}\left\langle \Psi \middle| H \left[ (c_1k_{11} + c_2k_{21}) f_1 + (c_1k_{12} + c_2k_{22}) f_2 \right]\right\rangle \\&#xA;&amp;amp;= (c_1k_{11} + c_2k_{21}) \left\langle \Psi \middle| H  f_1 \right\rangle + (c_1k_{12} + c_2k_{22}) \left\langle \Psi \middle| H  f_2 \right\rangle \\&#xA;&amp;amp;= 0&#xA;\end{align}&lt;/span&gt;&#xA;due to the first expressions we derived.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A &lt;strong&gt;complete basis&lt;/strong&gt; set is just a special case of our argument where by definition &lt;strong&gt;all derivatives&lt;/strong&gt; of basis functions &lt;strong&gt;can be represented&lt;/strong&gt; by the basis itself, thus giving net zero Pulay forces.&lt;/p&gt;&#xA;" OwnerUserId="327" LastActivityDate="2020-05-19T11:59:19.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="901" PostTypeId="1" CreationDate="2020-05-19T12:22:44.603" Score="21" ViewCount="1812" Body="&lt;p&gt;&lt;strong&gt;I am studying the interaction of a metal with a nanostructure&lt;/strong&gt;. As we can not trust graphical software about the bond formation, I decided to analyze them using the software &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It happens that there is a Zoo of several theories about &lt;strong&gt;how to calculate the bond orders&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Mayer bond order analysis (Chem. Phys. Lett, 97, 270 (1983))&lt;/li&gt;&#xA;&lt;li&gt;Standard multi-center bond order (Struct. Chem., 1, 423 (1990))&lt;/li&gt;&#xA;&lt;li&gt;Multi-center bond order in natural atomic orbital (NAO) basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1469/5&quot;&gt;Wiberg bond order&lt;/a&gt; analysis in Löwdin orthogonalized basis (Tetrahedron, 24, 1083 (1968), J. Mol. Struct. (THEOCHEM), 870, 1 (2008))&lt;/li&gt;&#xA;&lt;li&gt;Mulliken bond order analysis&lt;/li&gt;&#xA;&lt;li&gt;Orbital occupancy-perturbed Mayer bond order (J. Chem. Theory&#xA;Comput., 8, 908 (2012))&lt;/li&gt;&#xA;&lt;li&gt;Fuzzy bond order (Chem. Phys. Lett., 383, 368 (2004))&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1508/5&quot;&gt;Laplacian bond order&lt;/a&gt; (J. Phys. Chem. A, 117, 3100 (2013))&lt;/li&gt;&#xA;&lt;li&gt;Intrinsic bond strength index (J. Phys. Chem. A, 124, 1850 (2020))&lt;/li&gt;&#xA;&lt;li&gt;AV1245 index (approximate multi-center bond order for large&#xA;rings) (Phys. Chem. Chem. Phys., 18, 11839 (2016))&lt;/li&gt;&#xA;&lt;li&gt;DDEC6 atomic population analysis (RSC Adv. 7, 45552 (2017))&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;What method/theory do you suggest to be used?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-08-02T19:07:32.913" LastActivityDate="2020-09-20T17:18:22.917" Title="What are the types of bond orders?" Tags="|one-topic-per-answer|valence-bond-theory|nanostructures|conceptual-dft|" AnswerCount="4" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="902" PostTypeId="1" CreationDate="2020-05-19T12:40:30.970" Score="13" ViewCount="211" Body="&lt;p&gt;In Semiconductor Physics, one of the main parameters of interest is the band gap. It is known that, in DFT, there are functionals that underestimate it. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I came across the &lt;a href=&quot;http://openmopac.net/&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt; program, a semi-empirical quantum chemistry program based on Dewar and Thiel's NDDO approximation, that have two utilities to work with periodical system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The picture bellow shows the bands calculated for &lt;span class=&quot;math-container&quot;&gt;$\ce{TiO2}$&lt;/span&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/4PYsI.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4PYsI.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The problem is that, as MOPAC is not for periodic systems, it is a little difficult to calculate the bands with it (it is mandatory to leave the calculations windows open and you can not move the mouse). But, the gap was in agreement with the experimental value :).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there any other software with semiempirical methods available to calculate the electronic structure of periodical systems?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-11T21:35:47.340" LastActivityDate="2020-06-11T21:35:47.340" Title="Semi-empirical software for bands calculations" Tags="|software|band-structure|one-topic-per-answer|semi-empirical-method|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="903" PostTypeId="2" ParentId="883" CreationDate="2020-05-19T13:50:33.853" Score="2" Body="&lt;p&gt;So long as your calculations are parallelizable, using GPU's should provide significant speedup over just using CPU's alone. Nvidia last week at their GTC conference announced their new A100 GPU, which provides up to 20X speedup over its predecessor, the Volta V100. &lt;a href=&quot;https://siliconangle.com/2020/05/14/nvidia-debuts-a100-powerful-graphics-processor-yet/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nvidia debuts the A100, its most powerful graphics processor yet&lt;/a&gt;. Each A100 can deliver up to 600 Teraflops of performance. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;A new DGX server with 8 A100's, while delivering 5PetaFlops performance (which is equivalent to the performance of the world's largest supercomputer a few years ago), will set you back around $200k. While this can be out of the price range of a lot of (but not all) academic labs, a cost-effective option could be a pay-as-you-go machine instance on AWS, or another cloud provider such as GCP or Azure. An example of a relevant deep learning AMI can be found &lt;a href=&quot;https://aws.amazon.com/marketplace/pp/B07Y43P7X5&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T16:18:23.677" LastActivityDate="2020-05-19T16:18:23.677" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="904" PostTypeId="2" ParentId="883" CreationDate="2020-05-19T14:16:58.730" Score="11" Body="&lt;p&gt;Generally, CPUs give you the best bang for buck. While GPUs are promising, support for them is lacking in many codes. Moreover, even if some codes do support GPUs, the speedups are embarassingly small. Good GPUs are quite expensive: e.g. NVidia cards cost several thousands of dollars, and to get the best efficiency one might need several of them. For this price you can just get more CPUs.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, short answer: check first if the program you want to run supports GPUs, and what is the speedup for a representative calculation. (Note that the published numbers may not match your use case!) Then, do the math: is spending money on a GPU worth it?&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-19T14:16:58.730" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="905" PostTypeId="2" ParentId="855" CreationDate="2020-05-19T14:22:18.640" Score="6" Body="&lt;p&gt;Why would you want to generate a pseudopotential for a cation/anion? The pseudopotential is only for the inner core electrons. The only case where you'd want to do this is when the charge state of the system is so extreme that the inner shells are disturbed as well. (Also note that anions are ill-described by DFT so setting up an anion pseudopotential would be problematic.)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-19T14:22:18.640" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="906" PostTypeId="2" ParentId="859" CreationDate="2020-05-19T14:57:10.220" Score="10" Body="&lt;p&gt;First, some general remarks:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The measurements should be made after the system has &lt;em&gt;equilibrated&lt;/em&gt;, i.e., a large number of the first iterations should be discarded before the analysis.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;They should also be &lt;em&gt;averaged&lt;/em&gt; over a number of runs, in order to reduce noise.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This plot is better appreciated with a log scale in the vertical axis.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Later on, it's important to consider different system sizes. See &lt;em&gt;finite-size analysis&lt;/em&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Local updates perform very poorly (see taciteloquence's &lt;a href=&quot;https://materials.stackexchange.com/a/1099/625&quot;&gt;answer&lt;/a&gt;) at the critical temperature - so the general relative behavior of both curves seems fine enough.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;With respect to   &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;it will become negative as it pass through 0&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;if it's a robust trend, there seems to be something wrong - you can check a good source such as &lt;a href=&quot;https://doi.org/10.1142/9789814417891_0003&quot; rel=&quot;nofollow noreferrer&quot;&gt;Janke's book&lt;/a&gt; (especially &lt;a href=&quot;https://www.physik.uni-leipzig.de/~janke/Paper/lviv-ising-lecture-janke.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chap. 3 [pdf]&lt;/a&gt;), Sandvik &lt;a href=&quot;http://physics.bu.edu/~py502/lectures5/mc.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;notes&lt;/a&gt;, or &lt;a href=&quot;https://physics.stackexchange.com/q/312431/75633&quot;&gt;this question&lt;/a&gt; in Physics SE.&lt;/p&gt;&#xA;" OwnerUserId="625" LastEditorUserId="625" LastEditDate="2020-05-27T11:36:13.377" LastActivityDate="2020-05-27T11:36:13.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="907" PostTypeId="1" AcceptedAnswerId="1490" CreationDate="2020-05-19T15:13:21.050" Score="15" ViewCount="210" Body="&lt;p&gt;Similar to &lt;a href=&quot;https://en.wikipedia.org/wiki/Spintronics&quot; rel=&quot;nofollow noreferrer&quot;&gt;spintronics&lt;/a&gt;, which attempts to use electron spin polarization as the bits (or possibly qubits) in a logic device, &lt;a href=&quot;https://en.wikipedia.org/wiki/Valleytronics&quot; rel=&quot;nofollow noreferrer&quot;&gt;valleytronics&lt;/a&gt; attempts to use a combination of the spin and &amp;quot;valleys&amp;quot; in the electronic band structure with different crystal momentum.&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://www.physics.hku.hk/%7Ewangyao/valley_spin3d.png&quot; alt=&quot;Spin Valley Diagram&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;While this field is still in its infancy, &lt;strong&gt;has their been any development of computational tools specifically to address this problem?&lt;/strong&gt; I'm thinking along the lines of an automated procedure to detect and assess possible valley sites in the band structure of various compounds. However, &lt;strong&gt;I would be curious to see any such tools designed with valleytronics in mind.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-06-30T05:21:40.470" LastActivityDate="2020-07-09T06:57:49.897" Title="Tools for Valleytronic Research" Tags="|band-structure|valleytronics|spintronics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="908" PostTypeId="2" ParentId="847" CreationDate="2020-05-19T15:57:32.080" Score="18" Body="&lt;p&gt;I don't think you will find a reference showing that LDAs are better than GGAs for computing elastic constants. More specifically, I don't think a paper could reasonably offer an explanation of why LDA does better than GGA for any specific case.&lt;/p&gt;&#xA;&lt;p&gt;In principle, a GGA is more physically consistent than an LDA, as we know that the true exchange-correlation functional of DFT should depend on the gradient of the density. In practice, DFT functionals are typically parameterized to minimize errors in the energy for test set of molecules/compounds. Due to the approximate nature of the functional used in practice, there will always be cases where the &amp;quot;inferior&amp;quot; functional does better simply due to coincidental cancellation of error. There might be classes of compounds/problems where the source of this cancellation can be determined and a rigorous explanation of the good performance of the &amp;quot;inferior&amp;quot; functional can be formulated, but this is rare and generally very challenging.&lt;/p&gt;&#xA;&lt;p&gt;You are looking at a small selection of materials with fairly different properties (e.g. different crystal structure), so its unlikely that there is some clear, common factor that is making LDA better for these cases. A paper in the Journal of Computational Material Science&lt;sup&gt;[1]&lt;/sup&gt; found that for cubic crystal, there were cases where LDA produced better elastic constants and there were cases where it was much worse than GGA.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Jamal, M.; Jalali Asadabadi, S.; Ahmad, I.; Rahnamaye Aliabad, H. Elastic constants of cubic crystals. &lt;em&gt;Computational Materials Science&lt;/em&gt; &lt;strong&gt;2014,&lt;/strong&gt; &lt;em&gt;95,&lt;/em&gt; 592–599. &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2014.08.027&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1016/j.commatsci.2014.08.027&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-01-31T16:00:40.543" LastActivityDate="2022-01-31T16:00:40.543" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="909" PostTypeId="1" AcceptedAnswerId="1546" CreationDate="2020-05-19T15:59:49.120" Score="32" ViewCount="8248" Body="&lt;p&gt;Band inversion is a key ingredient of a topologically nontrivial material&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;. What is band inversion? How to recognize it in a band structure? What conclusions can I infer if I observe band inversion in a material?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Zhiyong Zhu, Yingchun Cheng, and Udo Schwingenschlögl. &quot;Band inversion mechanism in topological insulators: A guideline for materials design.&quot; &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.85.235401&quot; rel=&quot;noreferrer&quot;&gt;Physical Review B &lt;strong&gt;85&lt;/strong&gt; 235401 (2012)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="792" LastEditDate="2020-07-18T09:15:51.447" LastActivityDate="2022-03-22T14:42:18.410" Title="What is band inversion and how to recognize it in band structure?" Tags="|band-structure|materials-design|topological-insulators|berry-phase|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="910" PostTypeId="5" CreationDate="2020-05-19T16:31:58.397" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:31:58.397" LastActivityDate="2020-05-19T16:31:58.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="911" PostTypeId="4" CreationDate="2020-05-19T16:31:58.397" Score="0" Body="For questions about determining/optimizing transitions states of chemical reactions" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:31:58.397" LastActivityDate="2020-05-19T16:31:58.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="912" PostTypeId="5" CreationDate="2020-05-19T16:34:04.793" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:34:04.793" LastActivityDate="2020-05-19T16:34:04.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="913" PostTypeId="4" CreationDate="2020-05-19T16:34:04.793" Score="0" Body="For questions about the Multi-configuration time-dependent Hartree (MCTDH) method" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:34:04.793" LastActivityDate="2020-05-19T16:34:04.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="914" PostTypeId="5" CreationDate="2020-05-19T16:35:23.890" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:35:23.890" LastActivityDate="2020-05-19T16:35:23.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="915" PostTypeId="4" CreationDate="2020-05-19T16:35:23.890" Score="0" Body="For questions about modeling aperiodic bulk structures" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-19T16:35:23.890" LastActivityDate="2020-05-19T16:35:23.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="916" PostTypeId="5" CreationDate="2020-05-19T16:43:51.927" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T16:43:51.927" LastActivityDate="2020-05-19T16:43:51.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="917" PostTypeId="4" CreationDate="2020-05-19T16:43:51.927" Score="0" Body="Questions concerning molecules and molecular interactions within the discipline of materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T17:13:30.713" LastActivityDate="2020-05-19T17:13:30.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="918" PostTypeId="2" ParentId="883" CreationDate="2020-05-19T16:48:07.047" Score="16" Body="&lt;p&gt;As other answers have mentioned, it depends a lot on the workload and the availability of GPU-acceleration for the codes you use (or write). In principal, there are multiple platforms, but in practical use right now, Nvidia CUDA has the best performance and largest use.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nvidia offers a &lt;a href=&quot;https://www.nvidia.com/en-us/gpu-accelerated-applications/&quot; rel=&quot;noreferrer&quot;&gt;GPU Application directory&lt;/a&gt; - listing existing codes with CUDA availability.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Many molecular dynamics codes are already GPU-enabled and show huge speedups over CPU versions (e.g., &lt;a href=&quot;https://developer.nvidia.com/hpc-application-performance&quot; rel=&quot;noreferrer&quot;&gt;https://developer.nvidia.com/hpc-application-performance&lt;/a&gt;). This includes LAMMPS, AMBER, GROMACS, NAMD.. pretty much everything. Speedup varies, but I've often seen 20x-100x show up.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Fewer quantum codes are GPU-enabled with mixed results, largely dependent on how much work has gone into writing GPU versions of the code. These include VASP, Quantum Espresso, CP2k, Abinit, BigDFT, Gaussian, GAMESS, etc. I've seen some good benchmarks for commercial GPU acceleration of &lt;a href=&quot;https://www.brianqc.com&quot; rel=&quot;noreferrer&quot;&gt;Q-Chem called BrianQC&lt;/a&gt; and &lt;a href=&quot;http://www.petachem.com/performance.html&quot; rel=&quot;noreferrer&quot;&gt;Terachem&lt;/a&gt; but these are not widely deployed. On codes like Quantum Espresso and VASP, even Nvidia is &lt;a href=&quot;https://developer.nvidia.com/hpc-application-performance&quot; rel=&quot;noreferrer&quot;&gt;quoting a 10-20x speedup&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;For machine learning, speedup can be much, much more dramatic if your workload can be stored on the GPU. Data Center GPUs can be 16GB to 32GB in the Tesla V100 cards, and now 40GB in the A100 cards, although there's some overhead (i.e. you don't get to use all of that for your data and model).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-19T16:48:07.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="919" PostTypeId="5" CreationDate="2020-05-19T16:51:06.640" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T16:51:06.640" LastActivityDate="2020-05-19T16:51:06.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="920" PostTypeId="4" CreationDate="2020-05-19T16:51:06.640" Score="0" Body="For questions concerning CALPHAD (CALculation of PHAse Diagrams), a methodology introduced in the 1960s by Larry Kaufman." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T17:13:19.433" LastActivityDate="2020-05-19T17:13:19.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="921" PostTypeId="2" ParentId="857" CreationDate="2020-05-19T17:02:11.043" Score="12" Body="&lt;p&gt;Any quantum chemical program should calculate these for you as part of a vibrational calculation. Generally, the vibrational, rotational, and translational entropies will be given.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The critical task is to start with an &lt;strong&gt;optimized&lt;/strong&gt; geometry with a good method - and ideally some level of conformer search (i.e., to make sure you have a low-energy conformer).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The rotational entropy derives from the moments of inertia, through the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rotational_partition_function&quot; rel=&quot;nofollow noreferrer&quot;&gt;rotational partition function&lt;/a&gt; as well as any symmetry of the molecule. So you'll want to make sure you have a fairly accurate geometry, optimized using that particular method, to get accurate moments of inertia.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here's an example using the &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;xtb&lt;/code&gt;&lt;/a&gt; program - I'm analyzing these for a paper:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;       temp. (K)  partition function   enthalpy   heat capacity  entropy&#xA;                                   cal/mol     cal/K/mol   cal/K/mol   J/K/mol&#xA; 298.15  VIB  0.350E+07            10585.483     74.558     62.428&#xA;         ROT  0.115E+08              888.752      2.981     35.294&#xA;         INT  0.404E+14            11474.235     77.539     97.722&#xA;         TR   0.626E+28             1481.254      4.968     43.410&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Here you want the VIB, ROT, and TR entropies for the vibrational, rotational, and translational entropy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Any molecular quantum program that I've used will spit these out after performing a vibrational calculation. The format of the output varies, though.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2020-05-26T12:35:58.957" LastActivityDate="2020-05-26T12:35:58.957" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="922" PostTypeId="5" CreationDate="2020-05-19T17:02:37.850" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T17:02:37.850" LastActivityDate="2020-05-19T17:02:37.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="923" PostTypeId="4" CreationDate="2020-05-19T17:02:37.850" Score="0" Body="Questions about the Glide molecular docking software. " OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-19T17:13:23.797" LastActivityDate="2020-05-19T17:13:23.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="924" PostTypeId="1" AcceptedAnswerId="932" CreationDate="2020-05-19T18:31:52.740" Score="13" ViewCount="644" Body="&lt;p&gt;Does anyone know how to export a calculated Raman spectrum (my calculation was performed in Q-Chem) as a data-file, which can be used to plot the profile of a Gaussian-shape spectrum (in origin, excel, etc.), rathe than centroid data points?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2020-05-20T17:07:40.063" LastActivityDate="2020-05-20T17:07:40.063" Title="How to export a calculated Raman spectrum in Q-Chem, as a Gaussian profile?" Tags="|software|q-chem|spectroscopy|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="925" PostTypeId="1" CreationDate="2020-05-19T20:58:51.027" Score="19" ViewCount="298" Body="&lt;p&gt;With the advent of more computational power than ever in the recent years, interest in &lt;em&gt;in silico&lt;/em&gt; design of interesting compounds has grown as well. I am wondering about the state of the art for the case of designing novel materials:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What methods are commonly used (DFT, semi-empirical, more / less expensive)?&lt;/li&gt;&#xA;&lt;li&gt;What size of lattices is one able to treat in high-througput screening approaches?&lt;/li&gt;&#xA;&lt;li&gt;What is the effort in terms of runtime one needs to put in?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="327" LastEditorUserId="7" LastEditDate="2020-06-15T18:58:28.037" LastActivityDate="2022-01-18T19:00:01.247" Title="State of the art in computational materials design" Tags="|density-functional-theory|reference-request|semi-empirical-method|materials-informatics|materials-design|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="926" PostTypeId="5" CreationDate="2020-05-19T21:01:09.993" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-19T21:01:09.993" LastActivityDate="2020-05-19T21:01:09.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="927" PostTypeId="4" CreationDate="2020-05-19T21:01:09.993" Score="0" Body="For questions related to the use of modelling in materials design. Examples include high-throughput calculations to scan for candidates improving macroscopic properties over reference materials." OwnerUserId="327" LastEditorUserId="327" LastEditDate="2020-05-20T02:15:17.537" LastActivityDate="2020-05-20T02:15:17.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="928" PostTypeId="1" CreationDate="2020-05-19T21:31:29.183" Score="18" ViewCount="182" Body="&lt;p&gt;This is related to a prior question of mine &lt;a href=&quot;https://materials.stackexchange.com/questions/778/derivatives-with-respect-to-user-defined-vibrational-modes&quot;&gt;Derivatives with respect to user defined vibrational modes&lt;/a&gt;. While that one focuses on potential software to use for derivatives with respect to normal modes, I want to present the actual problem that led me to that.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have the derivatives of some property &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; with respect to the &lt;span class=&quot;math-container&quot;&gt;$3N-6=M$&lt;/span&gt; normal vibrational modes &lt;span class=&quot;math-container&quot;&gt;$\big\{Q_i\big\}$&lt;/span&gt; of a molecule. I wanted to convert these modes to a local mode basis to more directly relate these derivatives to functional groups of the molecule. Conversion of the modes to a local basis can done by a simple unitary transformation &lt;a href=&quot;https://doi.org/10.1063/1.3077690&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{Q}'=\mathbf{QU}$$&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt; is a &lt;span class=&quot;math-container&quot;&gt;$3N\times M$&lt;/span&gt; matrix of the normal modes, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{U}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$M\times M$&lt;/span&gt; unitary matrix defined via an iterative process described in the linked paper, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q'}$&lt;/span&gt; is a matrix of the normal modes. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;With the modes transformed, I also want derivatives in this local mode basis. I have two ways of doing this:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Transform the original derivatives: &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial P}{\partial Q_i'}=\sum_jU_{ji}\frac{\partial P}{\partial Q_i}$&lt;/span&gt; where the derivatives are arranged as column vectors.&lt;/li&gt;&#xA;&lt;li&gt;Compute numerical derivatives along the new mode: &lt;span class=&quot;math-container&quot;&gt;$\frac{P(X+hQ_i')-P(X)}{h|Q_i'|}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; is the initial molecule geometry.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;However, the transformed derivatives and the numerical derivatives of the local modes do not seem to match. If I test my procedure on the normal modes, the numerical derivatives agree with the ones I get from Gaussian. I'm concerned that perhaps I have something mixed up with removing/keeping the mass weighting of the modes (Gaussian fiddles with the coordinate representation a lot during &lt;a href=&quot;http://gaussian.com/vib/&quot; rel=&quot;noreferrer&quot;&gt;vibrational analysis&lt;/a&gt;). Is there something obviously wrong with the procedure I have outlined above?  Can I transform mass-weighted normal modes properly or do I need to ensure they are in cartesian coordinates before performing the transformation?&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Jacob, C.R &amp;amp; Reiher, M. J. Chem. Phys. 130, 084106 (2009); DOI: &lt;a href=&quot;https://doi.org/10.1063/1.3077690&quot; rel=&quot;noreferrer&quot;&gt;10.1063/1.3077690&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-21T03:30:43.850" LastActivityDate="2020-06-29T22:51:39.533" Title="Discrepancy between numerical and transformed derivatives" Tags="|gaussian|vibrations|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="929" PostTypeId="2" ParentId="857" CreationDate="2020-05-19T22:47:22.060" Score="9" Body="&lt;h2&gt;Psi4 and NWChem&lt;/h2&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;For open source software to perform this task, I can think of Psi4. It's probably the easiest to download/install and get going. It has the usual computational chemistry methods along with ab-initio/SAPT methods.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Some details can be found here:&#xA;psi4: &lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.psicode.org/&lt;/a&gt;&#xA;psi4 thermochemistry: &lt;a href=&quot;http://www.psicode.org/psi4manual/master/thermo.html#examples&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.psicode.org/psi4manual/master/thermo.html#examples&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;And of course, there is the beautiful open source NWChem - which is actively developed at PNNL! It can do all sorts of calculations like Gaussian. See for more details: &lt;a href=&quot;https://nwchemgit.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://nwchemgit.github.io/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="664" LastEditorUserId="5" LastEditDate="2020-07-04T14:32:21.513" LastActivityDate="2020-07-04T14:32:21.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="930" PostTypeId="1" AcceptedAnswerId="945" CreationDate="2020-05-19T23:06:44.983" Score="12" ViewCount="462" Body="&lt;p&gt;I am looking for real data that concludes that implicit solvent models are definitively better than explicit solvent models for solvation free energy calculations. The motivation is a lovely reviewer who has said this. Evidence that they are not statistically different is also valid.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="7" LastEditDate="2020-06-25T21:34:21.440" LastActivityDate="2020-06-25T21:34:21.440" Title="Is there any definitive evidence that implicit solvation methods are more accurate than explicit solvation methods for free energy calculations?" Tags="|free-energy|explicit-solvent|implicit-solvent|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="931" PostTypeId="2" ParentId="885" CreationDate="2020-05-19T23:10:09.427" Score="8" Body="&lt;p&gt;The short answer is DEPENDS on your system and property of interest you are after (among other things). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Anyway, I see the order of physical basis/complexity increasing as NC --&gt; USPP --&gt; PAW. But I may be wrong here. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, you should look at &lt;a href=&quot;https://www.vasp.at/vasp-workshop/pseudopp2.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/vasp-workshop/pseudopp2.pdf&lt;/a&gt; and the original USPP paper by Vanderbilt &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.41.7892&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.41.7892&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="664" LastEditorUserId="389" LastEditDate="2020-05-26T19:38:47.783" LastActivityDate="2020-05-26T19:38:47.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="932" PostTypeId="2" ParentId="924" CreationDate="2020-05-19T23:55:13.440" Score="14" Body="&lt;p&gt;I wrote the following simple Python function that allows one to use any distribution from &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/stats.html#continuous-distributions&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;scipy.stats&lt;/code&gt;&lt;/a&gt; for peak broadening (the &lt;code&gt;scale&lt;/code&gt; parameter determines how broad peaks will be):&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from scipy.stats import cauchy, norm&#xA;&#xA;&#xA;def broaden_spectrum(x, x0, y0, distribution=&quot;gaussian&quot;, scale=1.0, &#xA;                     fit_points=True, *args, **kwargs):&#xA;    if distribution in {&quot;gaussian&quot;, &quot;norm&quot;}:&#xA;        distribution = norm&#xA;    elif distribution in {&quot;lorentzian&quot;, &quot;cauchy&quot;}:&#xA;        distribution = cauchy&#xA;&#xA;    s = np.sum([yp * distribution.pdf(x, xp, scale=scale, *args, **kwargs)&#xA;                for xp, yp in zip(x0, y0)], axis=0)&#xA;&#xA;    if fit_points:&#xA;        s_max = np.max(s)&#xA;        if s_max == 0.0:&#xA;            s_max = 1.0&#xA;        return s * np.max(y0) / s_max&#xA;    return s&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;As &lt;a href=&quot;https://materials.stackexchange.com/questions/924/export-calculated-raman-spectrum-as-gaussian-profile#comment931_924&quot;&gt;Geoff Hutchison mentioned&lt;/a&gt;, you can use cclib to read your logfile:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import cclib&#xA;&#xA;&#xA;data = cclib.ccopen(&quot;data/2-propanol.out&quot;).parse()&#xA;x = np.linspace(data.vibfreqs.min() - 100.,&#xA;                data.vibfreqs.max() + 100., num=1000)&#xA;y = broaden_spectrum(x, data.vibfreqs, data.vibirs, scale=40.)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Plotting is easy:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import matplotlib.pyplot as plt&#xA;&#xA;&#xA;plt.plot(x, y)&#xA;plt.gca().invert_xaxis()&#xA;plt.gca().invert_yaxis()&#xA;plt.ylabel(&quot;Absorbance (arb. unit.)&quot;)&#xA;plt.xlabel(&quot;Wavenumber (cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;)&quot;)&#xA;plt.title(&quot;Predicted IR spectrum of 2-propanol at revPBE-D4-gCP/def2-SVP&quot;)&#xA;plt.savefig(&quot;ir-spectrum.png&quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YkWnC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YkWnC.png&quot; alt=&quot;Predicted IR spectrum of 2-propanol at revPBE-D4-gCP/def2-SVP&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is easily customizable and the &lt;code&gt;broaden_spectrum&lt;/code&gt; function works for all kinds of spectra.&lt;/p&gt;&#xA;" OwnerUserId="63" LastActivityDate="2020-05-19T23:55:13.440" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="933" PostTypeId="2" ParentId="832" CreationDate="2020-05-20T01:04:55.223" Score="6" Body="&lt;p&gt;No, nonequilibrium doesn't imply stationarity, but, at the sime time, using &quot;nonequilibrium state&quot; to denote those local energy minima can indeed be confusing, as it might seem to refer to &lt;a href=&quot;https://en.wikipedia.org/wiki/Non-equilibrium_thermodynamics&quot; rel=&quot;noreferrer&quot;&gt;nonequilibrium &lt;em&gt;steady&lt;/em&gt; states&lt;/a&gt;, which is what your referee is probably getting to.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One possible name for these local minima (besides &quot;local minima&quot;) could be &quot;non-equilibrated states&quot; or even &quot;non-asymptotic states&quot;, but I don't think that's standard, so if used it should be defined.&lt;/p&gt;&#xA;" OwnerUserId="625" LastActivityDate="2020-05-20T01:04:55.223" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="934" PostTypeId="2" ParentId="924" CreationDate="2020-05-20T04:51:52.407" Score="11" Body="&lt;p&gt;Many thanks to &lt;a href=&quot;https://materials.stackexchange.com/users/63/felipe-s-s-schneider&quot;&gt;Felipe&lt;/a&gt;, &lt;a href=&quot;https://materials.stackexchange.com/q/932&quot;&gt;the code&lt;/a&gt; is very useful! I know this is just a simple editing, but this is how I adjusted part of the code for Raman spectra:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import cclib&#xA;&#xA;&#xA;data = cclib.ccopen(&quot;molecule.out&quot;).parse()&#xA;x = np.linspace(data.vibfreqs.min() - 100.,&#xA;                data.vibfreqs.max() + 100., num=1000)&#xA;y = broaden_spectrum(x, data.vibfreqs, data.vibramans, scale=10.)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;And also this will save a .csv which can be used for further data processing:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;import matplotlib.pyplot as plt&#xA;import pandas as pd&#xA;&#xA;&#xA;plt.plot(x, y)&#xA;plt.ylabel(&quot;Intensity (a.u.)&quot;)&#xA;plt.xlabel(&quot;Raman Shift (cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;)&quot;)&#xA;plt.title(&quot;Predicted Raman spectrum of molecule at B3LYP/6-311++G**&quot;)&#xA;plt.savefig(&quot;Raman_gauss.pdf&quot;, dpi=300, bbox_inches='tight')&#xA;&#xA;&#xA;dataframe = pd.DataFrame({'x': x,&#xA;                          'y':y})&#xA;dataframe.to_csv(&quot;Raman_spectrum.csv&quot;, index=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;I'm sure this has multiple options for customization, but I though it might be useful.&lt;/p&gt;&#xA;" OwnerUserId="184" LastActivityDate="2020-05-20T04:51:52.407" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="935" PostTypeId="2" ParentId="504" CreationDate="2020-05-20T06:56:28.710" Score="8" Body="&lt;p&gt;This is a question that cannot have a &amp;quot;right&amp;quot; answer. As mentioned in the comments, the answer would depend on the experimental system and on the specific properties you want to reproduce.&lt;/p&gt;&#xA;&lt;p&gt;Since most experimental systems are in what is known as the &amp;quot;scaling regime&amp;quot; you probably need long polymers to begin with (I commented on the issue &lt;a href=&quot;https://physics.stackexchange.com/questions/401555/finite-size-effect/401563#401563&quot;&gt;elsewhere&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;In addition to the length, when dealing with co-polymers the effect of the sequence can be dramatic, and hence you need to be extra-careful when choosing it. &lt;a href=&quot;https://doi.org/10.1063/1.5141095&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; is a recent (open access) paper that shows the phase behaviour of short-ish (20 beads) co-polymers with different sequences. It also includes examples of polymers having the same AB composition but different arrangements. As you can see, different arrangements can give raise to sensibly different macroscopic behaviours.&lt;/p&gt;&#xA;" OwnerUserId="674" LastEditorUserId="674" LastEditDate="2020-07-27T09:05:42.213" LastActivityDate="2020-07-27T09:05:42.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="936" PostTypeId="2" ParentId="930" CreationDate="2020-05-20T07:09:53.463" Score="10" Body="&lt;p&gt;From what I have read, the performance of implicit models depends on a combination of the method used (Poisson-Boltzmann vs. Generalized-Born vs. another analytical method); and the size, shape, and species of the solute (ie: protein vs. ion). I think the best way to answer this would be to search for prior work on different solvation methods  applied to the solute of interest (or a highly-similar one).&lt;/p&gt;&#xA;" OwnerUserId="599" LastActivityDate="2020-05-20T07:09:53.463" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="937" PostTypeId="2" ParentId="925" CreationDate="2020-05-20T07:53:31.073" Score="18" Body="&lt;p&gt;After a little research I found a great article [1], which provides a good overview to what I asked above in Figure 2. Summarising in a table:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Method&lt;/th&gt;&#xA;&lt;th&gt;effort&lt;/th&gt;&#xA;&lt;th&gt;reliability&lt;/th&gt;&#xA;&lt;th&gt;system size&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Interatomic potentials&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;high/low*&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^8$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Linear-scaling DFT&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;medium-high&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^6$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Tight binding&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;medium-high&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^6$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;LDA DFT&lt;/td&gt;&#xA;&lt;td&gt;low&lt;/td&gt;&#xA;&lt;td&gt;medium-low&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^3$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;GGA DFT&lt;/td&gt;&#xA;&lt;td&gt;low&lt;/td&gt;&#xA;&lt;td&gt;medium&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^3$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;GGA+U DFT&lt;/td&gt;&#xA;&lt;td&gt;low&lt;/td&gt;&#xA;&lt;td&gt;medium-high&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^3$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Hybrid DFT&lt;/td&gt;&#xA;&lt;td&gt;low&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;GW&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;high&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$10^1$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;* high for geometries and energetics, but low for excited states&#xA;or the dielectric function&lt;/p&gt;&#xA;&lt;p&gt;where &lt;em&gt;effort&lt;/em&gt; refers to the manual effort from the researcher, &lt;em&gt;reliability&lt;/em&gt; gives the reliability of the method and &lt;em&gt;system size&lt;/em&gt; is the typical system size in the number of atoms. In the table I am providing a condensed (and maybe biased) overview, focusing on properties such as geometry, energetics, dielectric function, excited states or bandgap. See [1] for the full details.&lt;/p&gt;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&lt;p&gt;[1] K. T. Butler, J. M. Frost, J. M. Skelton, K. L. Svane and&#xA;A. Walsh. &lt;em&gt;Chem. Soc. Rev.&lt;/em&gt;, 2016, &lt;strong&gt;45&lt;/strong&gt;, 6138. DOI &lt;a href=&quot;https://doi.org/10.1039/c5cs00841g&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1039/c5cs00841g&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="7" LastEditDate="2022-01-18T19:00:01.247" LastActivityDate="2022-01-18T19:00:01.247" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="938" PostTypeId="1" AcceptedAnswerId="939" CreationDate="2020-05-20T09:44:00.733" Score="6" ViewCount="253" Body="&lt;p&gt;I am a theoretical physicist, so I am not very familiar with chemical names. The material I am interested in is &lt;span class=&quot;math-container&quot;&gt;$\ce{\alpha-NaMnO2}$&lt;/span&gt;. Would that be pronounced &lt;em&gt;alpha sodium manganese dioxide&lt;/em&gt;? Is it important to say the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If it's relevant, I'm talking about &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.124.197203&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Phys. Rev. Lett.&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;124&lt;/em&gt; (19), No. 197203&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Apologies if this is a trivial question, I tried looking up the answer, it may just be that I am not using the correct search terms.&lt;/em&gt; &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-20T23:49:48.673" LastActivityDate="2021-07-14T20:01:57.043" Title="How is the material $\ce{\alpha-NaMnO2}$ pronounced?" Tags="|magnetism|terminology|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="939" PostTypeId="2" ParentId="938" CreationDate="2020-05-20T10:25:48.590" Score="10" Body="&lt;p&gt;The anions of the form &lt;span class=&quot;math-container&quot;&gt;$\ce{MnO_x^y-}$&lt;/span&gt; are referred to as manganates (see &lt;a href=&quot;https://en.wikipedia.org/wiki/Manganate&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt;). I'm not sure if there might be a &quot;special&quot; name for &lt;span class=&quot;math-container&quot;&gt;$\ce{MnO2^-}$&lt;/span&gt; specifically (that's the species you have here) because I never encountered this anion in my lab times, but given that &lt;span class=&quot;math-container&quot;&gt;$\ce{MnO4^2-}$&lt;/span&gt; are the &quot;normal&quot; manganates and &lt;span class=&quot;math-container&quot;&gt;$\ce{MnO4^-}$&lt;/span&gt; the permanganates, I think manganate would be the term used here as well.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now to distinguish the ambiguity in &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; you usually add the oxidation state of the central metal (in this case manganese) in the form of roman numbers. Since actually the same stoichiometric formula (&lt;span class=&quot;math-container&quot;&gt;$\ce{NaMnO2}$&lt;/span&gt;) could give rise to different stable crystal structures (depending on external conditions) one uses the greek letter to distinguish between these different structures. So, yes, to be precise the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is needed and I would call the compound &lt;strong&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-Sodium-manganate(III)&lt;/strong&gt; pronounced &quot;alpha sodium manganate three&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But in day to day conversations one would rarely use the full thing if it is clear from context. First thing usually the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is dropped and next the (III). So taking to a lab colleague, where it is clear you can just say Sodium manganate. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Update:&lt;/strong&gt; I just saw that the &lt;a href=&quot;https://materialsproject.org/materials/mp-18957/&quot; rel=&quot;noreferrer&quot;&gt;materialsproject&lt;/a&gt; has something on your compound under ID mp-18957, where they tagged it as &lt;code&gt;Sodium manganese(III) oxide&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="327" LastEditorUserId="49" LastEditDate="2020-05-20T12:38:18.073" LastActivityDate="2020-05-20T12:38:18.073" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="940" PostTypeId="5" CreationDate="2020-05-20T11:13:26.893" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-20T11:13:26.893" LastActivityDate="2020-05-20T11:13:26.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="941" PostTypeId="4" CreationDate="2020-05-20T11:13:26.893" Score="0" Body="For questions about materials modelling software written in the Julia programming language. Focus should be on the Julia ecosystem and interfacing or using Julia packages for modelling workflows, not general debugging. " OwnerUserId="327" LastEditorUserId="327" LastEditDate="2020-05-20T14:54:50.913" LastActivityDate="2020-05-20T14:54:50.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="942" PostTypeId="2" ParentId="885" CreationDate="2020-05-20T11:55:58.400" Score="18" Body="&lt;p&gt;Three criteria to consider are&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Performance and size of basis set&lt;/strong&gt; &#xA;USPPs generally require a lower plane-wave cut-off and smaller basis, but a larger density grid. However performance may not be straightforwardly related to cut off as there are additional terms to compute which may have a significant computational cost.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Accuracy&lt;/strong&gt;&#xA;USPPs usually have 2 (or more) projectors per angular momentum state, which linearizes the energy. Traditional Troullier-Martins and Rappe/Cambridge NCPs had only one and were consequently less accurate. Do beware of older generations of NCPs for this reason, but recent multi-projector NCPs, nowadays known as &quot;Optimized Norm-Consetving Vanderbilt&quot; are nearly as accurate as USPs.  See the &lt;a href=&quot;https://molmod.ugent.be/deltacodesdft&quot; rel=&quot;noreferrer&quot;&gt;Delta project website &lt;/a&gt; for some examples.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Implementation restrictions and constraints&lt;/strong&gt;&#xA;Some functionality may be implemented only for NCPs, so USPs may not be used.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="498" LastActivityDate="2020-05-20T11:55:58.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="943" PostTypeId="2" ParentId="536" CreationDate="2020-05-20T12:03:33.037" Score="6" Body="&lt;p&gt;Arkadiy Simonov and Andrew Goodwin have a nice review out on the arXiv regarding designing disorder into materials, that can elicit unique topological states [1], and there is are some older reviews discussing specifically crystallography [2,3]. For a more robust mathematical treatment, this paper focuses on abstraction with a set of good physical examples [4].&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1912.00366&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1912.00366&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/nature14453&quot; rel=&quot;noreferrer&quot;&gt;D. A. Keen, A. L. Goodwin, &lt;em&gt;Nature&lt;/em&gt; &lt;strong&gt;521&lt;/strong&gt;, 303–309 (2015).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/0889311X.2015.1046853&quot; rel=&quot;noreferrer&quot;&gt;T. R. Welberry, T. Weber&#xA;&lt;em&gt;Crystallography Reviews&lt;/em&gt;  &lt;strong&gt;22&lt;/strong&gt;,  2-78  (2016)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://link.aps.org/doi/10.1103/RevModPhys.51.591&quot; rel=&quot;noreferrer&quot;&gt;N. D. Mermin, &lt;em&gt;Rev. Mod. Phys.&lt;/em&gt;  &lt;strong&gt;51&lt;/strong&gt;,  591-648 (1979).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="546" LastActivityDate="2020-05-20T12:03:33.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="944" PostTypeId="2" ParentId="132" CreationDate="2020-05-20T12:18:40.947" Score="8" Body="&lt;p&gt;I have used ASE to create slaps of complex, anisotropic materials in the past. However, &lt;code&gt;ase.lattice&lt;/code&gt; is not for creating slabs, it's a module containing functions for creating three dimensional Bravais lattices. Some functions you could use are &lt;code&gt;ase.build.surface&lt;/code&gt; or &lt;code&gt;ase.build.cut&lt;/code&gt; (for lower level control).&#xA;Examples:&lt;/p&gt;&#xA;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase.build import surface&#xA;s1 = surface('Au', (2, 1, 1), 9)&#xA;s1.center(vacuum=10, axis=2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Creates a gold (211) slap with 9 layers&lt;/p&gt;&#xA;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import ase&#xA;from ase.spacegroup import crystal&#xA;&#xA;a = 4.05&#xA;aluminium = crystal('Al', [(0,0,0)], spacegroup=225,&#xA;                    cellpar=[a, a, a, 90, 90, 90])&#xA;&#xA;al111 = cut(aluminium, (1,-1,0), (0,1,-1), nlayers=3)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Cut allows for finer control as you are specifying vectors (or atoms indices) that define a triangle in the plane you are cutting.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;ASE is great for automization in general as it offers calculator interfaces to programs like VASP and I highly recommend it. I am not too familiar with pymatgen, but it seems to provide many similar features. Either is probably fine.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Resources:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html?highlight=cut#ase.build.surface&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html?highlight=cut#ase.build.surface&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2] &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html?highlight=cut#ase.build.cut&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html?highlight=cut#ase.build.cut&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="406" LastActivityDate="2020-05-20T12:18:40.947" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="945" PostTypeId="2" ParentId="930" CreationDate="2020-05-20T15:30:26.307" Score="13" Body="&lt;p&gt;In principle, you would expect the exact &lt;em&gt;opposite&lt;/em&gt; (i.e. explicit better than implicit) simply because an explicit model more closely matches the reality of molecules interacting with other molecules rather than some sort of continuum.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In practice, you generally can't achieve full explicit solvation or even a single solvation shell and are limited to working with only a few solvent molecules. While this does allow you to treat some of the specific solute-solvent interactions, the ad-hoc inclusion of some interactions and not others can be problematic. This could potentially lead to a more uniform implicit model performing better for some systems (or all systems if you aren't careful about the arrangement of solvent molecules, conformational averaging, etc). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, the general consensus in the literature seems to be that, when they can be done, explicit models are the way to go. This 2017 JCTC paper [&lt;a href=&quot;https://doi.org/10.1021/acs.jctc.7b00169&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;] comparing implicit, explicit, and experimental solvation free energies of organic molecules in organic solvent might be of interest to you. They found that all the implicit models they tested were in worse agreement with experiment than an explicit model, in some cases substantially worse.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;J. Zhang, H. Zhang, T. Wu, Q. Wang, and D. van der Spoel J. Chem. Theory Comput. 2017, 13, 3, 1034–1043 DOI: &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.7b00169&quot; rel=&quot;noreferrer&quot;&gt;10.1021/acs.jctc.7b00169&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="97" LastEditDate="2020-05-21T02:39:26.457" LastActivityDate="2020-05-21T02:39:26.457" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="946" PostTypeId="5" CreationDate="2020-05-20T16:12:29.720" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-20T16:12:29.720" LastActivityDate="2020-05-20T16:12:29.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="947" PostTypeId="4" CreationDate="2020-05-20T16:12:29.720" Score="0" Body="For questions seeking open source software or databases to solve a modeling problem. " OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-20T22:09:03.003" LastActivityDate="2020-05-20T22:09:03.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="948" PostTypeId="2" ParentId="696" CreationDate="2020-05-20T16:27:57.180" Score="6" Body="&lt;p&gt;The problem here is that each package has its own files formats, so, each of them exports the data in a particular way (sometimes even in binary format). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;That's make having a repository for general scripts a hard task. Also, many of the scripts are due to the efforts of individual researchers.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, just very recently a common file format for pseudopotentials was developed (or added to &lt;a href=&quot;https://departments.icmab.es/leem/siesta/Pseudopotentials/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SIESTA&lt;/a&gt;), the &lt;a href=&quot;https://esl.cecam.org/PSML&quot; rel=&quot;nofollow noreferrer&quot;&gt;PSML&lt;/a&gt;. From the PSML developers site about the different formats:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;This leads to practical problems, not only of programming, but of interoperability and reproducibility, which depend on spelling out quite a number of details which are not well represented for all codes in existing formats.&lt;/em&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Years ago, I tested the &lt;a href=&quot;https://www.3dsbiovia.com/products/collaborative-science/biovia-materials-studio/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Material Studio&lt;/a&gt; suite from Biovia. It consist in one interface for many software like CASTEP, GAUSSIAN, DMOL3, FORCITE, GULP, DFTB+ and many others. The suite uses only one file format that converts &lt;em&gt;on the fly&lt;/em&gt; among the tools.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-01T11:48:22.937" LastActivityDate="2020-06-01T11:48:22.937" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="949" PostTypeId="2" ParentId="340" CreationDate="2020-05-20T17:29:42.250" Score="11" Body="&lt;p&gt;The &lt;a href=&quot;https://materials.registry.nist.gov/&quot; rel=&quot;noreferrer&quot;&gt;NIST Materials Resource Registry&lt;/a&gt; is not limited to computational resources, but refers to many of the codes you're looking for. Searching for &quot;hub&quot; only turns up two listings, both of which are tied to nanoHUB and Purdue.&lt;/p&gt;&#xA;" OwnerUserId="680" LastActivityDate="2020-05-20T17:29:42.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="950" PostTypeId="1" CreationDate="2020-05-20T18:16:03.453" Score="14" ViewCount="106" Body="&lt;p&gt;I am trying to learn best practices for force matching ab initio molecular dynamics (AIMD) data with nonlinear least-squares minimization to generate interatomic potentials for use in classical MD.&lt;/p&gt;&#xA;&lt;p&gt;I understand the concepts of selecting appropriate reference structures (for the expected classical MD behavior) and fitting to physically-justified functional forms. However, the art of selecting the right weighting factors, the right amount of reference structures, and judging if a set of potential parameters are fit properly appears to be highly open-ended problem with no single solution.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I was wondering if anyone knows of good resources (or has any advice) on gaining mastery and judgment over this process.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="599" LastEditorUserId="7" LastEditDate="2020-07-11T01:22:33.897" LastActivityDate="2020-07-11T01:22:33.897" Title="Generating interatomic potentials via force matching" Tags="|reference-request|molecular-dynamics|ab-initio-calculations|forcefields|interatomic-potentials|" AnswerCount="0" CommentCount="4" ClosedDate="2021-06-09T19:06:20.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="951" PostTypeId="2" ParentId="525" CreationDate="2020-05-21T00:13:28.767" Score="8" Body="&lt;h2&gt;1D&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;A famous example of a nearly ideal spin-&lt;span class=&quot;math-container&quot;&gt;$1/2$&lt;/span&gt; isotropic Heisenberg antiferromagnetic chain (1D) system is copper pyrazine dinitrate [Cu(C&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;)(NO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;], which was discussed in Hammar et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.59.1008&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;59&lt;/strong&gt;, 1008 (1999)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/9809068&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;]. Another excellent realizations include KCuF&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, which has stronger (but still low) interchain coupling, and orders at low temperatures. However, the spectrum of magnetic excitations above &lt;span class=&quot;math-container&quot;&gt;$\sim J/10$&lt;/span&gt; matches DMRG and Bethe Ansatz calculations very closely. See e.g. Lake et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.111.137205&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. Lett. &lt;strong&gt;111&lt;/strong&gt;, 137205 (2013)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/1307.4071&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;]. A third example is CuSO&lt;span class=&quot;math-container&quot;&gt;$_4\cdot 5$&lt;/span&gt;D&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O, see Mourigal et al. &lt;a href=&quot;https://www.nature.com/articles/nphys2652&quot; rel=&quot;noreferrer&quot;&gt;Nature Physics &lt;strong&gt;9&lt;/strong&gt;, 435 (2013)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/1306.4678&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$S=1$&lt;/span&gt; the materials I'm aware of seem to have some degree of single-ion anisotropy. The most well-known one is probably NENP [Ni(C&lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_8$&lt;/span&gt;N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;NO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;(ClO$_4)], as studied in e.g. Avenel et al. &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.46.8655&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;46&lt;/strong&gt;, 8655 (1992)&lt;/a&gt;. Earlier this year a molecular coordination complex was introduced and claimed to be one of the most ideal realizations yet, see Williams et al. &lt;a href=&quot;https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.2.013082&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. Research &lt;strong&gt;2&lt;/strong&gt;, 013082 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are some higher-spin realizations too, but I'm not sure which are good examples, and which aren't.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;2D&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;For higher dimensions the lattice geometry really needs to be specified. I will here assume you are interested in simple lattices, and not some geometrically frustrated one (though there is a fascinating literature on e.g. triangular, kagome lattices in the pursuit of quantum spin liquids). Spin-&lt;span class=&quot;math-container&quot;&gt;$1/2$&lt;/span&gt; examples on the square lattice include&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;La&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;CuO&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;, see e.g. the review Manousakis &lt;a href=&quot;https://doi.org/10.1103/RevModPhys.63.1&quot; rel=&quot;noreferrer&quot;&gt;Rev. Mod. Phys. &lt;strong&gt;63&lt;/strong&gt;, 1 (1991)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Sr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;CuO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;Cl&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, see Greven et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.72.1096&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. Lett. &lt;strong&gt;72&lt;/strong&gt;, 1096 (1994)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;certain organic compounds, see Woodward et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.65.144412&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;65&lt;/strong&gt;, 144412 (2002)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0107483&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;An &lt;span class=&quot;math-container&quot;&gt;$S=5/2$&lt;/span&gt; example is found in Rb&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;MnF&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;, see Huberman et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.72.014413&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;72&lt;/strong&gt;, 014413 (2005)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0504684&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;].&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;3D&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;I don't know too much about the 3D systems, but the two best realizations of nearest-neighbor only Heisenberg models I'm aware of are&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;span class=&quot;math-container&quot;&gt;$S=5/2$&lt;/span&gt; simple cubic lattice compound RbMnF&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, see e.g. Coldea et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.57.5281&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;57&lt;/strong&gt;, 5281 (1998)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;KMnF&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; see eg. Salazar et al. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.75.224428&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;75&lt;/strong&gt;, 224428 (2007)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/1001.3572&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;]. There are also the related KCoF&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; and KNiF&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; discussed in e.g. Oleaga et al. &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0925838815000328&quot; rel=&quot;noreferrer&quot;&gt;J. Alloys and Compounds &lt;strong&gt;629&lt;/strong&gt;, 178 (2015)&lt;/a&gt; [&lt;a href=&quot;http://www.ehu.eus/photothermal/JAlloysCompounds2015.pdf&quot; rel=&quot;noreferrer&quot;&gt;non-paywall link&lt;/a&gt;].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-05-21T00:13:28.767" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="952" PostTypeId="2" ParentId="561" CreationDate="2020-05-21T01:59:20.963" Score="28" Body="&lt;p&gt;I will try my best to delineate the differences between VASP and Quantum Espresso, specifically, how one has an edge over the other in certain aspects. I will &lt;em&gt;not&lt;/em&gt; try to explain the similarities between the codes because the original post is not concerned with it. I will also &lt;em&gt;not&lt;/em&gt; focus on integration of these softwares with GPUs etc as it is not my area of expertise. I will however, state two common denominators between the two codes (if it helps comparison with other ab-initio packages) - The use of a plane-wave basis set and the fact that they rely on periodic boundary conditions.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Pseudopotentials : VASP by default uses Projector-augmented wave (PAW) Pseudopotentials. These PPs are very well tested and have much lower cutoffs than typical Norm-conserving pseudopotentials (NCPPs) used in Quantum Espresso. Without practically any loss in accuracy, VASP is usually much quicker than QE for Kohn-Sham DFT calculations. Meanwhile, QE by itself doesn't provide PPs for calculations. They do refer good resources that enable implementations of NCPPs, PAWs, USPPs (ultra-soft) etc. I believe that VASP also has some USPP support, but these were historically inaccurate. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Community: QE is open-sourced and has a much more responsive, active user community (Refer: &lt;a href=&quot;https://www.quantum-espresso.org/forum&quot; rel=&quot;noreferrer&quot;&gt;quantum espresso user forums&lt;/a&gt;). Their mailing archives date back to more than a decade, hence it is much easier to diagnose any problems in your calculations in QE.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Hybrid functional calculations: It is well known that Kohn-Sham DFT underestimates bandgap. Many hybrid functionals are available in a variety of ab-initio softwares. From my personal experience,I have found that implementation of the hybrid functionals (HSE, in particular) is easier in VASP. QE does have some tutorials on implementing hybrid functionals but I've found it harder to implement with increasing complexity of the system - Also, HSE calculations on QE incur so  much more computing time - typically 100x(time taken for non-hybrid calculations). If you want to calculate band structures, it gets even more complicated because you need to generate Maximally Localized Wannier functions (MLWFs). The MLWF code is well optimized for QE but its implementation is difficult unless you know exactly what you are doing. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I've found that VASP provides a lot more options when it boils down to certain nuances. For example, QE doesn't let you calculate the dipole matrix element (crucial for studying optical transitions) if you include the hubbard 'U' or Spin-orbit coupling. VASP can do both. Also, in QE, you cannot calculate the forces in relaxation procedures if you include the hubbard 'U'. But I do have to remind you that you could technically modify the QE code to serve these purposes. Although, this is very difficult to do unless you know the exact physics behind it and also have a sound grasp of coding it.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I've found VASP to be more user-friendly in certain situations. Although QE has descriptions of its various executable files, some outputs generated can be off-putting and very hard to read, to a new user. For example, the dipole matrix elements (from Fermi's golden rule) printed in QE are very hard to read for a beginner. I personally had to go back to the code of the executable file and decrypt in which order the bands were printed in the output. Again, the user forums for QE are very helpful, but my point circles back to better documentation and interface available in VASP.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Implementation of the Hubbard 'U': In QE the projections are done on ortho-atomic orbitals while in VASP, it is done on beta projector functions. This is to point out that there are subtleties between the two codes that do not unequivocally tell you which one is 'better'.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Implementation of Spin-orbit coupling (SOC): In QE, only non-collinear spin-orbit coupling calculations are permitted which is not the case in VASP.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Although one typically doesn't use VASP or QE for post-Hartree Fock processes (chemists typically turn to softwares like Gaussian), VASP has this provision whereas QE does not.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;In conclusion, there is no stand-out software that is 'better' than the rest. VASP and QE along with other ab-initio softwares are not fundamentally disparate. If one were to set out to learn ab-initio modeling, I would suggest weighing out the myriad factors. &lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="689" LastEditDate="2020-05-21T12:51:51.280" LastActivityDate="2020-05-21T12:51:51.280" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="953" PostTypeId="1" AcceptedAnswerId="1984" CreationDate="2020-05-21T02:53:43.563" Score="23" ViewCount="210" Body="&lt;p&gt;Dunning's basis set families (such as cc-pV&lt;strong&gt;X&lt;/strong&gt;Z and aug-cc-pCV&lt;strong&gt;X&lt;/strong&gt;Z) were not optimized to give the lowest variational energy for a given number of orbitals. For example the S-type orbitals are optimized, then held fixed while P-type orbitals are optimized, then the S-type and P-type orbitals are both held fixed while the D-type orbitals are optimized, and so on. Likewise when the &quot;tight&quot; functions of the CV correction are optimized to create an cc-pCV&lt;strong&gt;X&lt;/strong&gt;Z basis set, the exponents of the cc-pV&lt;strong&gt;X&lt;/strong&gt;Z basis set are held fixed. &lt;strong&gt;When holding some parameters fixed during the optimization, one will not get the absolute optimal outcome possible for a given number of parameters.&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Furthermore, the Dunning basis set sequence is constructed in such a way that when increasing the &lt;strong&gt;X&lt;/strong&gt; in cc-pV&lt;strong&gt;X&lt;/strong&gt;Z by one, a fixed number of new orbitals are added: for example when going from &lt;strong&gt;X&lt;/strong&gt;=3 to &lt;strong&gt;X&lt;/strong&gt;=4 (TZ to QZ) for some second row atom, there will be one new G-type exponent, one new F-type exponent, one new D-type exponent, and so on; &lt;em&gt;but&lt;/em&gt; it's possible that a lower variational energy would be obtained with the same number of orbitals if we were to avoid adding the G-type function and instead invest in more P-type functions. &lt;strong&gt;This is because the goal of Dunning's basis set sequences, is to construct them in a &lt;em&gt;systematic&lt;/em&gt; manner so that there will be a smooth extrapolation to the CBS (complete basis set) limit for some actual property (e.g. energy difference),&lt;/strong&gt; whether or not a lower total energy for a particular X value could be obtained by adding more exponents for one type of orbital than another.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Which basis set families are constructed simply to get the lowest variational energy for a given number of orbitals, regardless of the ability to extrapolate well or the ability to optimize the exponents in a systematic way?&lt;/em&gt;&lt;/strong&gt; I appreciate that this: &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;will be &lt;em&gt;much&lt;/em&gt; more costly than holding some exponents fixed while optimizing others, and that&lt;/li&gt;&#xA;&lt;li&gt;total energies might be improved at the expense of actual properties (like ionization energies or atomization energies) being worsened, and that&lt;/li&gt;&#xA;&lt;li&gt;extrapolations to the CBS limit will not be as smooth,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;but I'm curious to know what exists!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;For the purposes of this question, I am interested in one-particle basis set families, so not ECGs (explicitly correlated Gaussians) for example. You may choose to answer by giving just one basis set family in one answer, or by giving all examples you know in one answer.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T14:13:02.060" LastActivityDate="2020-08-13T16:32:22.823" Title="Which basis set families were optimized to give the lowest possible variational energy for a given number of orbitals?" Tags="|reference-request|ab-initio-calculations|basis-sets|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="954" PostTypeId="5" CreationDate="2020-05-21T03:17:59.460" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:17:59.460" LastActivityDate="2020-05-21T03:17:59.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="955" PostTypeId="4" CreationDate="2020-05-21T03:17:59.460" Score="0" Body="Questions about nucleation -  the first step in the formation of either a new thermodynamic phase or a new structure via self-assembly or self-organization." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T06:48:53.290" LastActivityDate="2020-05-21T06:48:53.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="956" PostTypeId="5" CreationDate="2020-05-21T03:26:10.863" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:26:10.863" LastActivityDate="2020-05-21T03:26:10.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="957" PostTypeId="4" CreationDate="2020-05-21T03:26:10.863" Score="0" Body="Questions regarding spin-exchange - an interaction that preserves the total angular momentum of the system but may allow other aspects of the system to change." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T06:47:10.310" LastActivityDate="2020-05-21T06:47:10.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="958" PostTypeId="2" ParentId="930" CreationDate="2020-05-21T03:26:32.823" Score="8" Body="&lt;p&gt;Highly depends on what your system of interest is. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;(i) For molecular and ionic systems, check papers by Chris Cramer and Donald Truhlar. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;(ii) Another paper of interest for heterogeneous catalysis could be the below paper. Basically for nonpolar/weakly polar solute implicit solvation is pretty good. However, the solvation energies can start to deviate for polar solutes (especially when solute can form H bonds with water). Well, the deviation here is based on comparison with explicit solvation, which in themselves can be wrong. So, one of the biggest problems is lack of experimental standards - I believe the closest water adsorption on heterogeneous surface experiments are calorimetric experiments by Charlie Campbell in U Washington(?). I think they did experiments on dissociated water adsorption on Pt(111). I can dig it up if you are interested in it. &#xA;&lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cphc.201700162&quot; rel=&quot;noreferrer&quot;&gt;https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cphc.201700162&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-05-21T03:26:32.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="959" PostTypeId="2" ParentId="861" CreationDate="2020-05-21T03:28:39.407" Score="8" Body="&lt;p&gt;I don't think there is a universal rule for the number of 'cores' or 'threads' that you request in your parallel calculation. In my opinion, the only parameter you need to look out for, is the number of K points. If you are sampling more than one K-point, you can get clever and use &lt;em&gt;npool = no. of nodes&lt;/em&gt;. I would recommend that you keep the 'npool' tag to be a divisor of the number of K points. For example, if your K-point mesh is 12x12x1, you can use ' -npool 6 ' where 6 is the number of nodes/cores that you are using. But the parallelism process is pretty clever, so even if you use a number that is not a divisor, the calculation should run just fine. In that case, it does occasionally terminate abruptly, from my experience. You can take a look at the exact syntax for this in the documentation for pw.x on QE. What npool does is it basically splits the K-points evenly between the nodes and this speeds up your calculation significantly. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In conclusion, the parallelization process on QE is very clever. I would suggest you use a good amount of computing resources available for calculations without worrying much about the parallelism. If you are using more than 1 K-point, I would heavily recommend you check out 'npool' - It makes life so much more easier.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-05-21T03:28:39.407" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="960" PostTypeId="5" CreationDate="2020-05-21T03:31:02.413" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:31:02.413" LastActivityDate="2020-05-21T03:31:02.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="961" PostTypeId="4" CreationDate="2020-05-21T03:31:02.413" Score="0" Body="For questions about systems involving the element titanium." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:42.570" LastActivityDate="2020-05-21T22:08:42.570" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="962" PostTypeId="5" CreationDate="2020-05-21T03:36:29.967" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:36:29.967" LastActivityDate="2020-05-21T03:36:29.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="963" PostTypeId="4" CreationDate="2020-05-21T03:36:29.967" Score="0" Body="Questions concerning Ewald summation, used for calculating long-range interactions in computational chemistry. " OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T06:48:33.320" LastActivityDate="2020-05-21T06:48:33.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="964" PostTypeId="2" ParentId="340" CreationDate="2020-05-21T03:39:26.897" Score="4" Body="&lt;p&gt;I am not sure if I understand the meaning of hubs here. But below are some listing of databases with/without abilities to calculate/lookup materials properties.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;MaterialsProject.org&#xA;Crystallography Open Database (COD)&#xA;AFLOW (&lt;a href=&quot;http://www.aflowlib.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.aflowlib.org/&lt;/a&gt;)&#xA;Nomad (NOMADnomad-coe.eu)&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-05-21T03:39:26.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="965" PostTypeId="5" CreationDate="2020-05-21T03:39:36.903" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:39:36.903" LastActivityDate="2020-05-21T03:39:36.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="966" PostTypeId="4" CreationDate="2020-05-21T03:39:36.903" Score="0" Body="Questions related to ion dynamics within materials." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T14:22:26.517" LastActivityDate="2020-05-21T14:22:26.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="967" PostTypeId="5" CreationDate="2020-05-21T03:52:13.230" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:52:13.230" LastActivityDate="2020-05-21T03:52:13.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="968" PostTypeId="4" CreationDate="2020-05-21T03:52:13.230" Score="0" Body="Questions related to Lindhard theory, a method of calculating the effects of electric field screening by electrons in a solid." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T06:48:22.353" LastActivityDate="2020-05-21T06:48:22.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="969" PostTypeId="2" ParentId="925" CreationDate="2020-05-21T03:54:25.180" Score="11" Body="&lt;p&gt;I am sure there are A LOT of authors publishing papers to answer this very question. Mainly because the theories employed have face a paradigm since &quot;one-size-doesn't-fit-all&quot;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here are the variables that affect this use of a certain method:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(i) Molecular models or periodic solids&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(ii) Chemical Accuracy (energies with accuracy of &amp;lt; 1kcal/mol) - e.g. in polymorph stability such as crystal structure prediction or molecular solids&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(iii) Electronic structure (band gap/density of states/ band structure/excitonic effects) can be calculated using PBE+U (or PBE+D3+U) that is Fast vs Hybrid (PBE0/HSE06/etc.) or quasiparticle GW calculations that can be quite slow&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A good read on theoretical comparisons: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;(i) Philosophical+technical: &lt;a href=&quot;https://science.sciencemag.org/content/355/6320/49/tab-figures-data&quot; rel=&quot;noreferrer&quot;&gt;https://science.sciencemag.org/content/355/6320/49/tab-figures-data&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(ii) Technical benchmarking of a recent density functional across various model solids: &lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041005&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041005&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-05-21T03:54:25.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="970" PostTypeId="5" CreationDate="2020-05-21T03:57:46.533" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T03:57:46.533" LastActivityDate="2020-05-21T03:57:46.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="971" PostTypeId="4" CreationDate="2020-05-21T03:57:46.533" Score="0" Body="Questions regarding metal complexes - compounds of metal ions coordinated by ligands." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T14:22:28.997" LastActivityDate="2020-05-21T14:22:28.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="972" PostTypeId="5" CreationDate="2020-05-21T04:03:40.297" Score="0" Body="&lt;p&gt;Thermo-Calc Software: &lt;a href=&quot;https://thermocalc.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://thermocalc.com/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2023-12-08T16:53:25.297" LastActivityDate="2023-12-08T16:53:25.297" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="973" PostTypeId="4" CreationDate="2020-05-21T04:03:40.297" Score="0" Body="Questions concerning the Thermo-Calc software package." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-21T06:48:46.160" LastActivityDate="2020-05-21T06:48:46.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="974" PostTypeId="2" ParentId="561" CreationDate="2020-05-21T06:01:41.583" Score="21" Body="&lt;p&gt;There is another (good) answer, and since I can't comment yet I will add a few things, possibly from a different perspective as someone who uses QE more often.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In general, QE is a free (GPL 2.0), open source code, and that comes with some advantages. New methods can be implemented relatively quickly. If you will be using DFT+U, QE has hp.x, for calculating Hubbard U values from first principles using density functional perturbation theory (see Phys. Rev. B 98, 085127). To my knowledge VASP does not have this capability. And QE DOES implement forces and stresses using DFT+U when using the &quot;simplified&quot; rotationally-invariant formulation (which is default), but you are limited in the choice of orbital for the projection to either atomic wavefunctions or the pseudopotential projectors. In general though, you are not limited to ortho-atomic orbitals--there are a few options, and you can also provide your own generated wavefunction files (i.e. from Wannier codes) for the projection.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;QE also has some interesting methods for boundary conditions and periodicity, such as using the effective screening method (Phys. Rev. B 73, 115407) for polarized/charged slab calculations. Again, to the best of my knowledge, VASP can only apply dipole corrections in this case (which QE can also do).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The advantages of VASP that stick out the most to me are the handling of hybrid functional calculations, and slightly fewer restrictions on the types of calculations you can do (though not true with simplified DFT+U, there are indeed situations in QE where you don't have forces or stresses implemented yet). It's been reported that VASP shows better scaling for parallel computation but this may just be in systems with many electrons, and was on a much older version of QE (and may no longer be true). QE is also improving its treatment of hybrid functionals (the speedup from the ACE algorithm is significant, and finally ultrasoft and PAW pseudopotentials can be used). I would not say that in general, VASP is faster, though it may be in some particular cases.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'll finish by just quickly mentioning pseudopotentials. Techically this isn't something one code can do that the other can't, but I thought this is important to clarify. It is true that VASP uses PAW by default, and has a fairly well-tested set of pseudopotentials for most elements. However, while QE doesn't include pseudopotentials by default, I would not say that most users typically use &quot;slow&quot; norm-conserving pseudopotentials, nor is the situation some &quot;wild west&quot; of unreliability. A widely used set (PSLibrary) comes in both PAW and ultrasoft versions. The Materials Cloud project has compiled a set of pseudopotentials from many sources to give the lowest errors vs. all-electron calculations, while prioritizing either efficiency (lower cutoffs) or accuracy. And new &quot;ONCV&quot; norm-conserving pseudopotentials (Phys. Rev. B 88, 08511) are almost as soft as ultrasoft and PAW (see pseudo-dojo.org).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If I were deciding which code to use, it would strongly depend on what specific types of calculation I want to do, though I admit both codes have a lot of capabilities and its quite difficult to keep track of everything. Sometimes the professor or research group you work in is simply more familiar with a certain code, so you use that!&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-21T06:17:02.413" LastActivityDate="2020-05-21T06:17:02.413" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="975" PostTypeId="1" CreationDate="2020-05-21T06:45:46.297" Score="11" ViewCount="87" Body="&lt;p&gt;I have multiple Q-Chem output files for TS search starting and finishing with frequency calculations (two sets of calculated IR data in total). To parse and plot spectra  I use &lt;a href=&quot;https://cclib.github.io/contents.html&quot; rel=&quot;noreferrer&quot;&gt;cclib&lt;/a&gt; and a &lt;a href=&quot;https://materials.stackexchange.com/questions/924/how-to-export-a-calculated-raman-spectrum-in-q-chem-as-a-gaussian-profile&quot;&gt;script&lt;/a&gt; discussed recently. But when cclib parses output, it combines both frequency calculations. Is there a way to parse only one (the second) selectively? &lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="52" LastEditDate="2020-05-21T07:12:56.707" LastActivityDate="2020-05-22T12:07:01.243" Title="Parse linked frequency calculations with cclib" Tags="|q-chem|cclib|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="976" PostTypeId="2" ParentId="584" CreationDate="2020-05-21T11:41:57.617" Score="8" Body="&lt;p&gt;One can also pose the opposite question, which may be more interesting: what significant matter modelling methods are implemented in open source software, for which there is no commercial alternative? Anna's answer above had a lot of important considerations, but also this reverse question is important to keep in mind; commercial software is not always free of shortcomings, either!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The thing about modern open source development is that new features may spread very easily from one code to another. The KISS (keep it simple, stupid!) principle familiar for a long time in computer science and UNIX systems is gaining traction in science, too: code development is moving to small, modular projects focused on solving a defined problem as well as possible. When the implementation is separated from the interface, the pieces are easy to interface to various codes, and the improvements made within the module spread quickly to all the programs interfaced with the module.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But, many of these open source projects have also been interfaced by big commercial programs; this is only possible if the license is permissive enough. Some examples of are libxc (Mozilla Public License) and libecpint (MIT license), which despite being open source are bundled with major commercial programs to offer core functionalities.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-21T11:41:57.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="977" PostTypeId="2" ParentId="330" CreationDate="2020-05-21T11:56:16.857" Score="5" Body="&lt;p&gt;On the basis set side, e.g. completeness-optimized basis sets are usually optimized for properties, there's a bunch of papers on them for magnetic properties from Juha Vaara's group; I've also published a few. One could also mention the augmented Karlsruhe sets which are optimized for polarizabilities instead of the description of anions, as well as Sadlej's basis sets which are also aimed for electric properties.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the DFT side, hundreds of functionals have been proposed, and several semiempirical ones are fit for properties. E.g. the Keal-Tozer functionals KT1, KT2, KT3, B97-2, and B97-3 are optimized for NMR shieldings. There are also functionals fitted to band gaps.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-21T11:56:16.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="978" PostTypeId="2" ParentId="862" CreationDate="2020-05-21T14:04:18.870" Score="10" Body="&lt;p&gt;I fully endorse @DetlevCM's advocacy for using &quot;proper&quot; job schedulers, but for comparison, there are some tools geared toward intensive DFT runs that might be more approachable for your application:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Materials Project's &lt;a href=&quot;https://materialsproject.github.io/fireworks/&quot; rel=&quot;nofollow noreferrer&quot;&gt;FireWorks&lt;/a&gt; is a &quot;code for defining, managing, and executing workflows&quot;. It looks like it sits on top of schedulers like SLURM, but may be more approachable.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.oqmd.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;OQMD&lt;/a&gt; from the Wolverton group at Northwestern includes facilities for &quot;automating density-functional calculations&quot;. I don't know how generalizable those facilities are.&lt;/li&gt;&#xA;&lt;li&gt;NIST's &lt;a href=&quot;https://jarvis.nist.gov/&quot; rel=&quot;nofollow noreferrer&quot;&gt;JARVIS&lt;/a&gt; &quot;is a repository designed to automate materials discovery using classical force-field, density functional theory, machine learning calculations and experiments&quot;. I'm not sure how adaptable its internal scripting and workflow is to other applications.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://signac.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;signac&lt;/a&gt; from the Glotzer group at UMich has workflow and data pipelining capabilities. Their applications are MD-centric, but my impression of signac is that it's more general.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="680" LastEditorUserId="680" LastEditDate="2020-05-26T14:41:34.877" LastActivityDate="2020-05-26T14:41:34.877" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="979" PostTypeId="5" CreationDate="2020-05-21T16:14:06.060" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T16:14:06.060" LastActivityDate="2020-05-21T16:14:06.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="980" PostTypeId="4" CreationDate="2020-05-21T16:14:06.060" Score="0" Body="For questions about cclib, an open source Python library for parsing and interpreting the results of various computational chemistry packages." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:28.890" LastActivityDate="2020-05-21T22:08:28.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="981" PostTypeId="2" ParentId="692" CreationDate="2020-05-21T18:39:10.537" Score="7" Body="&lt;h2&gt;MRCC&lt;/h2&gt;&#xA;&lt;p&gt;There are more programs with parallel SCF capability, but it is quite hard to scale SCF (with HF exchange) to large number of cores. MRCC indeed has a recent hybrid multi-node (MPI) &amp;amp; multi-threaded (OpenMP) parallel HF/hybrid DFT code relying on an integral direct density fitting algorithm, but you should not expect great scaling above few hundred cores, depending on system size. GPUs are not supported there. It is however free for academics, open source, and for large systems (cca. 100+ atoms in 3D) the HF exchange can be further accelerated via local approximations. Largest (local) HF calc I performed with it had about 1000 atoms and 50000 atomic orbitals.&lt;/p&gt;&#xA;&lt;p&gt;More details:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.mrcc.hu/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.mrcc.hu/index.php&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;J. Chem. Phys. 152, 074107 (2020); &lt;a href=&quot;https://doi.org/10.1063/1.5142048&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.5142048&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="317" LastEditorUserId="5" LastEditDate="2021-02-05T21:04:02.923" LastActivityDate="2021-02-05T21:04:02.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="982" PostTypeId="5" CreationDate="2020-05-21T20:11:15.827" Score="0" Body="&lt;p&gt;General features of the GPAW code are described in more detail at: &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/gpaw/&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2021-11-10T18:17:16.263" LastActivityDate="2021-11-10T18:17:16.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="983" PostTypeId="4" CreationDate="2020-05-21T20:11:15.827" Score="0" Body="For questions about GPAW, a Python based DFT code based on the projector-augmented-wave (PAW) &#xD;&#xA;method and the atomic simulation environment (ASE)" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-11-10T18:17:16.263" LastActivityDate="2021-11-10T18:17:16.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="984" PostTypeId="5" CreationDate="2020-05-21T20:15:15.370" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T20:15:15.370" LastActivityDate="2020-05-21T20:15:15.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="985" PostTypeId="4" CreationDate="2020-05-21T20:15:15.370" Score="0" Body="For questions about FCI (full configuration interaction) calculations." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:45.790" LastActivityDate="2020-05-21T22:08:45.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="986" PostTypeId="5" CreationDate="2020-05-21T20:15:50.450" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T20:15:50.450" LastActivityDate="2020-05-21T20:15:50.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="987" PostTypeId="4" CreationDate="2020-05-21T20:15:50.450" Score="0" Body="For questions about or related to spectroscopy." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-18T16:56:59.440" LastActivityDate="2023-02-18T16:56:59.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="988" PostTypeId="5" CreationDate="2020-05-21T20:16:27.590" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T20:16:27.590" LastActivityDate="2020-05-21T20:16:27.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="989" PostTypeId="4" CreationDate="2020-05-21T20:16:27.590" Score="0" Body="For questions about the extended Hückel method." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:48.937" LastActivityDate="2020-05-21T22:08:48.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="990" PostTypeId="5" CreationDate="2020-05-21T20:16:54.197" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T20:16:54.197" LastActivityDate="2020-05-21T20:16:54.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="991" PostTypeId="4" CreationDate="2020-05-21T20:16:54.197" Score="0" Body="For questions about heterostructures." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:23.727" LastActivityDate="2020-05-21T22:08:23.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="992" PostTypeId="5" CreationDate="2020-05-21T20:17:23.657" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-21T20:17:23.657" LastActivityDate="2020-05-21T20:17:23.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="993" PostTypeId="4" CreationDate="2020-05-21T20:17:23.657" Score="0" Body="For questions about solar cells." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-21T22:08:56.400" LastActivityDate="2020-05-21T22:08:56.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="994" PostTypeId="1" CreationDate="2020-05-21T20:34:19.010" Score="19" ViewCount="338" Body="&lt;p&gt;I am curious to find references for when is it TRUE that the error cancellation in approximate methods like DFT/MP2/etc. are valid and when they fall apart.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example: My understanding is (please argue against if you don't agree) that if an approximate method only captures interactions say X, Y, and Z (x/y/z could be lets say pairwise dispersion, hydrogen bonding, aromatic interaction), then the error cancellation would be valid across all the molecular systems that have X, Y, and Z interactions. However, let's say in reality (i.e. true physical interacting picture) there is X, Y, Z, and A (where A might be say many body dispersion or exact exchange), then is it true that the error cancellation of a method correctly capturing X, Y, and Z will not be valid for systems with X, Y, Z, A. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Mathematically, for say the energies of molecules 1 and 2, is the following true:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(X1 + Y1 + Z1) - (X2 + Y2 + Z2) is the same as (X1 + Y1 + Z1 + A1) - (X2 + Y2 + Z2 + A2)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where Xi,Yi/etc. may just be energy contributions of pairwise dispersion/hydrogen bonding/etc. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Papers supporting or arguing against error cancellation are all appreciated! &lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-06-25T03:45:13.017" Title="Cancellation of Errors in density functional approximations or any wavefunction based methods" Tags="|density-functional-theory|error-cancellation|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="995" PostTypeId="2" ParentId="835" CreationDate="2020-05-22T04:48:34.247" Score="7" Body="&lt;p&gt;Explicit solvent can be of importance, like you mention, whenever strong coordination or hydrogen bonding is involved. For example, transition metals often coordinate to solvent and not including them in the calculation would give very poor results. Similarly hydrogen bonding can affect the electrostatics and result in poor properties like reaction paths, pKa, etc. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are generally two ways to introduce explicit solvent into a simulation:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Introduce one or two explicit solvent model in the areas of strong coordination, and use an implicit solvent model for the remaining interactions. &lt;/li&gt;&#xA;&lt;li&gt;Treat all of the solvent explitly, for example with QM/MM. Normally, this involves running some molecular dynamics with periodic boundary conditions, and then optimizing transition states for several snapshots of the dynamics. However, this method introduces so many degrees of freedom that it's no longer possible to apply the harmonic approximation to calculate entropy, and it's difficult to gather enough statistics. An example of this can be found in Houk's Solvent perturbed transition state calculations &lt;sup&gt;[1]&lt;/sup&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Since you don't want to do the latter (I also would not recommend this for a first pass either). Your best bet is to try to coordinate a few solvent and optimize.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;Finally, any time you are dealing with intermolecular systems (e.g. reactant and one or more solvent molecules) I recommend the &lt;strong&gt;translation and rotation internal coordinate system (TRIC&lt;/strong&gt;)&lt;sup&gt;[2]&lt;/sup&gt;. This coordinate system is similar to the very popular Delocalized Internal Coordinate (DLC) system but is superior for intermolecular optimization.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This can be accomplished via the package Geometric &lt;sup&gt;[3]&lt;/sup&gt;, but since you are already using pyGSM, this can also be accomplished with a pyGSM script&lt;sup&gt;[4]&lt;/sup&gt;. I've attached the optimization script below. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Yang, Z., Doubleday, C. &amp;amp; Houk, K. N. QM/MM Protocol for Direct Molecular Dynamics of Chemical Reactions in Solution: The Water-Accelerated Diels-Alder Reaction. J. Chem. Theory Comput. 11, 5606–5612 (&lt;strong&gt;2015&lt;/strong&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Wang, L. P. &amp;amp; Song, C. Geometry optimization made simple with&#xA;translation and rotation coordinates. J. Chem. Phys. &lt;strong&gt;144&lt;/strong&gt;, 214108&#xA;(2016)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/leeping/geomeTRIC&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/leeping/geomeTRIC&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/ZimmermanGroup/pyGSM&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/ZimmermanGroup/pyGSM&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;from pygsm.level_of_theories.qchem import QChem&#xA;from pygsm.potential_energy_surfaces import PES&#xA;from pygsm.optimizers import *&#xA;from pygsm.wrappers import Molecule&#xA;from pygsm.utilities import *&#xA;from coordinate_systems import Topology,PrimitiveInternalCoordinates,DelocalizedInternalCoordinates&#xA;&#xA;def main():&#xA;&#xA;    geom = manage_xyz.read_xyz(&quot;geom.xyz&quot;)&#xA;    xyz = manage_xyz.xyz_to_np(geom)&#xA;&#xA;    nifty.printcool(&quot; Building the LOT&quot;)&#xA;    lot = QChem.from_options(&#xA;            lot_inp_file=&quot;qstart&quot;, # a Q-Chem input file with only the &lt;span class=&quot;math-container&quot;&gt;$rem$&lt;/span&gt; arguments&#xA;            geom=geom,&#xA;            )&#xA;&#xA;    nifty.printcool(&quot; Building the PES&quot;)&#xA;    pes = PES.from_options(&#xA;            lot=lot,&#xA;            ad_idx=0,&#xA;            multiplicity=1,  # your system multiplicity&#xA;            )&#xA;&#xA;    nifty.printcool(&quot;Building the topology&quot;)&#xA;    atom_symbols  = manage_xyz.get_atoms(geom)&#xA;    ELEMENT_TABLE = elements.ElementData()&#xA;    atoms = [ELEMENT_TABLE.from_symbol(atom) for atom in atom_symbols]&#xA;    top = Topology.build_topology(xyz,atoms)&#xA;&#xA;    nifty.printcool(&quot;Building Primitive Internal Coordinates&quot;)&#xA;    p1 = PrimitiveInternalCoordinates.from_options(&#xA;            xyz=xyz,&#xA;            atoms=atoms,&#xA;            addtr=True,    # Adding translations and rotations!&#xA;            topology=top,&#xA;            )&#xA;&#xA;    nifty.printcool(&quot;Building Delocalized Internal Coordinates&quot;)&#xA;    coord_obj1 = DelocalizedInternalCoordinates.from_options(&#xA;            xyz=xyz,&#xA;            atoms=atoms,&#xA;            addtr = True,  # Adding translations and rotations!&#xA;            primitives=p1,&#xA;            )&#xA;&#xA;    nifty.printcool(&quot;Building Molecule&quot;)&#xA;    reactant = Molecule.from_options(&#xA;            geom=geom,&#xA;            PES=pes,&#xA;            coord_obj = coord_obj1,&#xA;            Form_Hessian=True,&#xA;            )&#xA;&#xA;    print(&quot; Done creating molecule&quot;)&#xA;    optimizer =  eigenvector_follow.from_options(Linesearch='backtrack',OPTTHRESH=0.0005,DMAX=0.5,abs_max_step=0.5,conv_Ediff=0.1)&#xA;&#xA;    print(&quot;initial energy is {:5.4f}&quot;.format(reactant.energy))&#xA;    geoms,energies = optimizer.optimize(&#xA;            molecule=reactant,&#xA;            refE=reactant.energy,&#xA;            opt_steps=500,&#xA;            verbose=True,&#xA;            )&#xA;&#xA;    print(&quot;Final energy is {:5.4f}&quot;.format(reactant.energy))&#xA;    manage_xyz.write_xyzs_w_comments('output.xyz',geoms,energies,scale=1.)&#xA;    manage_xyz.write_xyz('minimized.xyz',geoms[-1],energies[-1],scale=1.)&#xA;&#xA;if __name__=='__main__':&#xA;    main()&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-05-22T04:48:34.247" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="996" PostTypeId="5" CreationDate="2020-05-22T05:29:35.757" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T05:29:35.757" LastActivityDate="2020-05-22T05:29:35.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="997" PostTypeId="4" CreationDate="2020-05-22T05:29:35.757" Score="0" Body="For questions about (or involving) the MRCC electronic structure software package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-22T15:59:28.097" LastActivityDate="2020-05-22T15:59:28.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="998" PostTypeId="5" CreationDate="2020-05-22T05:30:27.290" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T05:30:27.290" LastActivityDate="2020-05-22T05:30:27.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="999" PostTypeId="4" CreationDate="2020-05-22T05:30:27.290" Score="0" Body="For questions about the phenomenon of error cancellation." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-22T19:19:04.700" LastActivityDate="2020-05-22T19:19:04.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1000" PostTypeId="2" ParentId="495" CreationDate="2020-05-22T05:53:23.523" Score="5" Body="&lt;p&gt;Here's some calculations I had some problems with:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;LaFeO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; on LaAlO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; with an adsorbed O atom. &lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}\times\sqrt{2}$&lt;/span&gt; perovskite cell in the x-y direction. 5 layers of LaAlO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (alternating LaO - AlO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; - LaO etc.) with 3 layers of LaFeO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; on top. The bottom 3 layers of LaAlO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; are fixed. Anti-ferromagnetic order on the Fe atoms. Around 450 electrons or so. I used Quantum Espresso 6.1.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Things I played with to get convergence:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;trying a dipole correction OR the effective screening medium method&lt;/li&gt;&#xA;&lt;li&gt;changing the amount of vacuum in the unit cell &lt;em&gt;z&lt;/em&gt; direction (usually 16-20 Å)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;mixing_mode = 'local-TF'&lt;/code&gt; with varying number of iterations (&lt;code&gt;mixing_dim&lt;/code&gt; of 8, 10, 12)&lt;/li&gt;&#xA;&lt;li&gt;lowered &lt;code&gt;mixing_beta&lt;/code&gt; (~0.2)&lt;/li&gt;&#xA;&lt;li&gt;removing random atomic orbitals from the initial charge density guess (&lt;code&gt;startingwfc = 'atomic'&lt;/code&gt; instead of &lt;code&gt;'atomic+random'&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;different pseudopotential (sometimes pseudopotentials that behaved extremely similarly during early testing could result in very subtle and fickle changes in the tendency to converge)&lt;/li&gt;&#xA;&lt;li&gt;slightly perturbing atomic positions (during relaxation, sometimes things would converge for many steps, then you arrive at a certain geometry that throws a wrench in scf convergence). I used &lt;code&gt;scf_must_converge = .false.&lt;/code&gt; here.&lt;/li&gt;&#xA;&lt;li&gt;I also tried using a fork of QE by Satomichi Nishihara, who implemented RMM-DIIS diagonalization and SR1-BFGS relaxation algorithms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Eventually some combination of the above worked. What a pain!&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-22T06:07:18.503" LastActivityDate="2020-05-22T06:07:18.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1001" PostTypeId="2" ParentId="975" CreationDate="2020-05-22T12:07:01.243" Score="6" Body="&lt;p&gt;I think the easiest way to parse multiple-job files from Q-Chem is if you just manually split the output file into the parts that pertain to the individual jobs. Just locate where the first job ends and the second one starts and save the output in individual files. If you have lots of those jobs to split, then I am sure this could be done with the &lt;code&gt;head&lt;/code&gt; and &lt;code&gt;tail&lt;/code&gt; commands.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-05-22T12:07:01.243" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1002" PostTypeId="2" ParentId="97" CreationDate="2020-05-22T12:12:30.130" Score="9" Body="&lt;p&gt;If you index the molecule and the atoms in the crystallographic unit cell the same, you could extract the displacement from the phonon eigenvectors and the displacement from the normal modes. By projecting each normal mode displacement onto each phonon displacement, you can get a qualitative relationship between a molecular deformation and a lattice vibration. This could be readily visualized in a heat map. I can't think of any quantitative relationship; however, this offers a quantitative view on relating favorable deformations between a given crystal polymorph and molecule.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Details of the displacement and eigenvectors are here:&#xA;Dove, M. T. &lt;em&gt;Structure and Dynamics: An Atomic View of Materials&lt;/em&gt; (2002)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;with a more thorough work on phonons here: &#xA;Dove, M. T. &lt;em&gt;Introduction to Lattice Dynamics&lt;/em&gt; (1993).&lt;/p&gt;&#xA;" OwnerUserId="546" LastEditorUserId="546" LastEditDate="2020-05-22T12:30:42.043" LastActivityDate="2020-05-22T12:30:42.043" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1003" PostTypeId="1" CreationDate="2020-05-22T12:44:11.320" Score="12" ViewCount="328" Body="&lt;p&gt;A newish area of interactions between quantum Monte Carlo (QMC) and experiments is in spin spectra. Recent improvements in stochastic analytic continuation have made it much easier to compare/extract the dynamical spin structure factor, which corresponds to the results of inelastic neutron scattering experiments.&lt;/p&gt;&#xA;&lt;p&gt;Example of QMC spin structure factor: &lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.7.041072&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. X &lt;strong&gt;7&lt;/strong&gt;, 041072 (2017)&lt;/a&gt;&lt;br /&gt;&#xA;Example of neutron scattering measurements: &lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.7.041072&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. Lett. &lt;strong&gt;124&lt;/strong&gt;, 197203 (2020)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My problem is that I don't have a good intuition for &lt;strong&gt;interpreting&lt;/strong&gt; these spectra. They represent a complex quantity that includes density of states, dispersion relations, gaps, and finite-temperature effects with a layer of noise on top.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How to identify important features from the experiments avoid getting confused by artifacts?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-12-31T04:07:48.003" LastActivityDate="2020-12-31T04:07:48.003" Title="How to understand dynamical spin structure factor?" Tags="|quantum-monte-carlo|neutron-scattering|" AnswerCount="0" CommentCount="4" ClosedDate="2021-01-01T17:58:38.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="1004" PostTypeId="1" CreationDate="2020-05-22T13:05:28.240" Score="12" ViewCount="372" Body="&lt;p&gt;The binding interaction energy during the adsorption of system B on system A can give an idea if the interaction is favorable (negative value) or unfavorable (positive value). Also, the absolute value represents the strength of the interaction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To determine the binding energy, the procedure is to calculate the energy of both systems separately &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; and the energy of the complex &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt;, then the binding energy can be calculated as:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{bind} = E_{AB} - E_A + E_B$&lt;/span&gt;.........   (1)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(the justification to do this is &lt;a href=&quot;https://materials.stackexchange.com/a/406/24&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, let suppose that I want to heat the complex to detach the system B from the surface of system A.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How to have an estimate of the temperature needed to do that? The only idea that come to my mind  is to use the rule of three with the association that 300K correspond to 25meV (via &lt;span class=&quot;math-container&quot;&gt;$k_BT$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt; being the Boltzmann constant).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-25T13:06:01.870" LastActivityDate="2020-06-29T21:06:44.347" Title="Converting adsorption binding energy to absolute temperature" Tags="|binding-energy|temperature|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1005" PostTypeId="2" ParentId="1004" CreationDate="2020-05-22T17:04:14.303" Score="14" Body="&lt;p&gt;If I want to break a Li&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule (&lt;em&gt;i.e.&lt;/em&gt; remove atom A from atom B), one way to do it is by shining a laser on it such that the frequency (&lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt;) or energy (&lt;span class=&quot;math-container&quot;&gt;$h\nu$&lt;/span&gt;) corresponds to the difference between the energy at &lt;span class=&quot;math-container&quot;&gt;$v=0$&lt;/span&gt; (if the molecule starts in the ground state) and the dissociation asymptote in this picture (generated based on &lt;strong&gt;[1,2]&lt;/strong&gt;):&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/gjN9L.png&quot; width=&quot;600&quot;&gt;&#xA;&lt;p&gt;I think the question asks: What if we don't have a laser but we have some other way of turning up the temperature? &lt;strong&gt;How high would the temperature need to be, to break the molecule?&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I think that quantum mechanics tells us that even if we raise the system to a very high temperature, there is still no guarantee that the particles will separate, but we can estimate the temperature at which the dissociation happens with probability &amp;gt; 99%. One way to see the probability for a system with Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; to be in a particular state, is to use the formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\rho = \frac{e^{-\beta H}}{\textrm{tr}\left(e^{-\beta H}\right)},~~~~~~~~\beta\equiv \frac{1}{k_BT}.&#xA;\tag{1}&#xA;\label{eq:boltzmann}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the density matrix and the diagonal elements of it give the probabilities &lt;span class=&quot;math-container&quot;&gt;$p_i$&lt;/span&gt; of finding the system in state &lt;span class=&quot;math-container&quot;&gt;$|i\rangle$&lt;/span&gt;. There is an infinite number of possible states for this system: 10 of them are shown in the above diagram (&lt;span class=&quot;math-container&quot;&gt;$v=$&lt;/span&gt; 0 to 9), but there's also a &amp;quot;continuum&amp;quot; of states above the dissociation asymptote, and &lt;strong&gt;these&lt;/strong&gt; are the ones we want, because these are the states that correspond to atom A being removed from atom B. If we sum/integrate the probabilities &lt;span class=&quot;math-container&quot;&gt;$p_i$&lt;/span&gt; over all states that correspond to a dissociation, we can get the total probability &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; of successfully breaking the bond at temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;. &lt;strong&gt;Then, all we have to do is find the value of &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; such that &lt;span class=&quot;math-container&quot;&gt;$P&amp;gt;99\%$&lt;/span&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now if we are not dealing with Li&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; but instead with a complicated system AB, and we want to know the probability of detaching a sub-system (A) from the rest of the complex (B), the potential energy surface may look more complicated than the one in the above figure (maybe we don't just have an internuclear distance &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; but we also have have angles), so the Hamiltonian will be more complicated, but Eq.  \eqref{eq:boltzmann} can still be used to get the probabilities of the dissociated states .&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;br&gt;&#xA;[1] N. Dattani and R. J. Le Roy, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Journal of Molecular&#xA;Spectroscopy.&lt;/em&gt; &lt;strong&gt;268&lt;/strong&gt;, 199&lt;/a&gt; (2011).&lt;br&gt;&#xA;[2] M. Semczuk, X. Li, W. Gunton, M. Haw, N. Dattani,&#xA;J. Witz, A. K. Mills, D. J. Jones, and K. W. Madison, &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.87.052505&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Physical Review A.&lt;/em&gt; &lt;strong&gt;87&lt;/strong&gt;, 052505&lt;/a&gt; (2013).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-29T21:06:44.347" LastActivityDate="2020-06-29T21:06:44.347" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1006" PostTypeId="5" CreationDate="2020-05-22T18:53:24.317" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T18:53:24.317" LastActivityDate="2020-05-22T18:53:24.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1007" PostTypeId="4" CreationDate="2020-05-22T18:53:24.317" Score="0" Body="For questions relating to effects that only appear at the quantum scale." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T19:33:47.983" LastActivityDate="2020-05-22T19:33:47.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1008" PostTypeId="5" CreationDate="2020-05-22T18:55:46.467" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T18:55:46.467" LastActivityDate="2020-05-22T18:55:46.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1009" PostTypeId="4" CreationDate="2020-05-22T18:55:46.467" Score="0" Body="Questions relating to microstructure modeling and dynamics." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T20:52:42.617" LastActivityDate="2020-05-22T20:52:42.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1010" PostTypeId="5" CreationDate="2020-05-22T19:01:58.040" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:01:58.040" LastActivityDate="2020-05-22T19:01:58.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1011" PostTypeId="4" CreationDate="2020-05-22T19:01:58.040" Score="0" Body="Questions related to the tight binding method in materials science." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T19:18:55.703" LastActivityDate="2020-05-22T19:18:55.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1012" PostTypeId="5" CreationDate="2020-05-22T19:04:02.633" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:04:02.633" LastActivityDate="2020-05-22T19:04:02.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1013" PostTypeId="4" CreationDate="2020-05-22T19:04:02.633" Score="0" Body="Questions about quantum plasmonics, which concerns the quantum properties of light and its interaction with matter at the nanoscale." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T20:44:40.720" LastActivityDate="2020-05-22T20:44:40.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1014" PostTypeId="5" CreationDate="2020-05-22T19:07:49.797" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:07:49.797" LastActivityDate="2020-05-22T19:07:49.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1015" PostTypeId="4" CreationDate="2020-05-22T19:07:49.797" Score="0" Body="Questions about transition temperature, i.e., the temperature at which a substance acquires or loses a distinctive property, in particular superconductivity." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T19:33:43.133" LastActivityDate="2020-05-22T19:33:43.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1016" PostTypeId="5" CreationDate="2020-05-22T19:09:42.523" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:09:42.523" LastActivityDate="2020-05-22T19:09:42.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1017" PostTypeId="4" CreationDate="2020-05-22T19:09:42.523" Score="0" Body="Questions relating to simulating the mechanical properties of materials." OwnerUserId="36" LastEditorUserId="7" LastEditDate="2020-07-06T19:42:10.070" LastActivityDate="2020-07-06T19:42:10.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1018" PostTypeId="5" CreationDate="2020-05-22T19:17:41.923" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:17:41.923" LastActivityDate="2020-05-22T19:17:41.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1019" PostTypeId="4" CreationDate="2020-05-22T19:17:41.923" Score="0" Body="Questions regarding multi-junction photovoltaic cells." OwnerUserId="36" LastEditorUserId="5" LastEditDate="2020-05-23T17:11:53.857" LastActivityDate="2020-05-23T17:11:53.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1020" PostTypeId="5" CreationDate="2020-05-22T19:18:36.233" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:18:36.233" LastActivityDate="2020-05-22T19:18:36.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1021" PostTypeId="4" CreationDate="2020-05-22T19:18:36.233" Score="0" Body="Questions related to energy conversion in systems such as solar cells." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-22T19:33:50.257" LastActivityDate="2020-05-22T19:33:50.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1022" PostTypeId="5" CreationDate="2020-05-22T19:25:41.650" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-22T19:25:41.650" LastActivityDate="2020-05-22T19:25:41.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1023" PostTypeId="4" CreationDate="2020-05-22T19:25:41.650" Score="0" Body="Questions concerning exchange-correlation terms in materials modeling calculations." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-23T02:45:31.833" LastActivityDate="2020-05-23T02:45:31.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1024" PostTypeId="2" ParentId="495" CreationDate="2020-05-22T21:42:42.343" Score="6" Body="&lt;p&gt;It is well-established that it can be quite difficult to converge the SCF for certain (hybrid) meta-GGA functionals compared to their (hybrid) GGA counterparts. This is especially true for plane-wave periodic DFT and is most often the case with many of the popular Minnesota functionals. In large part because of this reason, a &lt;a href=&quot;https://www.pnas.org/content/114/32/8487&quot; rel=&quot;nofollow noreferrer&quot;&gt;revised version of M06-L&lt;/a&gt; functional was developed. Anecdotally, I have studied several systems in VASP where it is near-impossible to get the SCF to converge with M06-L unless starting from the PBE wavefunction. Generally, there are also algorithmic tricks that can be used to help the convergence of meta-GGA functionals though. In VASP, using a pre-conditioned conjugate gradient algorithm (&lt;code&gt;algo=All&lt;/code&gt;) is found to greatly improve convergence compared to the other commonly used algorithms. This is discussed in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/METAGGA&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP wiki&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This may seem to silly, but it is also worth mentioning that a very common case of the SCF converging poorly is when your system isn't appropriately set up! I have personally encountered many scenarios where the SCF is extremely difficult to converge, only to find out the crystal structure I took from a database was missing an atom or ion such that the system was no longer charge-neutral. Of course, this is somewhat of an artificial scenario, but if you run into such troubles, it is one worth considering.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the purposes of this discussion, I'd also like to add cases where the SCF is converged &lt;em&gt;but not necessarily to the ground state solution&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One very tricky case is related to spin. For a given spin multiplicity (i.e. net magnetic moment), there are some systems where there can be multiple relatively low-lying arrangements of electrons. You can fix the net spin multiplicity, but there's no guarantee you converge to the lowest energy arrangement of electrons at that spin multiplicity. In these cases, the user must provide an initial guess for the individual magnetic moments and hope the SCF converges to the desired electronic state. Occasionally, it can be very difficult to converge to the lowest energy state even if the next lowest electron configuration is several tens of kJ/mol higher in energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another scenario is with DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, which can have multiple self-consistent solutions of different energies. There are several cases regarding bulk oxides where the SCF converges to a solution that is not the ground state, such as for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{UO_{2}}$&lt;/span&gt; in the fluorite structure. &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.195128&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; is a discussion on how to get around that.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-05-23T01:24:50.783" LastActivityDate="2020-05-23T01:24:50.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1025" PostTypeId="1" AcceptedAnswerId="1352" CreationDate="2020-05-23T00:19:56.297" Score="16" ViewCount="1039" Body="&lt;p&gt;An experimental colleague asked me how hard it would be to calculate homolytic bond-dissociation energies for different phosphonates which are involved in a &lt;a href=&quot;https://en.wikipedia.org/wiki/Hydrophosphination&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hydrophosphination&lt;/a&gt;.  The compounds include aryl and alkyl phosphonates (R2P=O), and the oxygen can be replaced with BH3 (R2P-BH3).&lt;/p&gt;&#xA;&lt;p&gt;Maybe I'm overthinking this but isn't it difficult to calculate BDE because at the dissociation limit the &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma^*$&lt;/span&gt; become degenerate, and more than one electronic configuration can describe the system (multi-configurational), e.g. &lt;span class=&quot;math-container&quot;&gt;$(\sigma)^2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(\sigma^*)^2$&lt;/span&gt;? Therefore, the correct wavefunction  should be sufficiently flexible to treat both configurations on the same footing, which single-references like Hartree-Fock, and DFT cannot. However, multi-configuration techniques like CASPT2/CASSCF are complicated and I'd probably not be able to easily instruct a colleague how to use them easily.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Besides CASPT2/CASSCF, what other methods for calculating homolytic BDEs are good and are fairly &amp;quot;black-box&amp;quot;?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;They just want a trend, so the absolute value doesn't matter as long as the model is useful for getting relative trends correct. Blackbox methods like DFT are preferred.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-06-19T15:40:58.103" LastActivityDate="2020-06-26T19:59:28.333" Title="How to calculate homolytic bond dissociation energies?" Tags="|density-functional-theory|q-chem|molpro|mrcc|" AnswerCount="3" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="1026" PostTypeId="2" ParentId="751" CreationDate="2020-05-23T02:10:54.307" Score="4" Body="&lt;p&gt;You can do something with Lennard-Jones potentials instead of harmonic ones. I know this has been done for Coarse-Grained MD simulations using Go-Martini models as in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00986&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00986&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now this needs more testing, I have done some force-probe simulations with it but nothing too serious.&lt;/p&gt;&#xA;" OwnerUserId="484" LastActivityDate="2020-05-23T02:10:54.307" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1027" PostTypeId="5" CreationDate="2020-05-23T02:15:12.473" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T02:15:12.473" LastActivityDate="2020-05-23T02:15:12.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1028" PostTypeId="4" CreationDate="2020-05-23T02:15:12.473" Score="0" Body="For questions about (or involving) inelastic or elastic neutron scattering." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-23T13:40:20.587" LastActivityDate="2020-05-23T13:40:20.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1029" PostTypeId="5" CreationDate="2020-05-23T02:49:46.343" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T02:49:46.343" LastActivityDate="2020-05-23T02:49:46.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1030" PostTypeId="4" CreationDate="2020-05-23T02:49:46.343" Score="0" Body="Questions relating to the discipline of statistical thermodynamics." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-23T07:07:41.620" LastActivityDate="2020-05-23T07:07:41.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1031" PostTypeId="5" CreationDate="2020-05-23T02:52:09.113" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T02:52:09.113" LastActivityDate="2020-05-23T02:52:09.113" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1032" PostTypeId="4" CreationDate="2020-05-23T02:52:09.113" Score="0" Body="Questions relating to symmetries and symmetry groups encountered in materials modeling." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-23T07:08:43.517" LastActivityDate="2020-05-23T07:08:43.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1033" PostTypeId="5" CreationDate="2020-05-23T03:07:40.823" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:07:40.823" LastActivityDate="2020-05-23T03:07:40.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1034" PostTypeId="4" CreationDate="2020-05-23T03:07:40.823" Score="0" Body="Questions about the sign-problem in Monte Carlo calculations, and related topics." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-09-12T23:46:43.687" LastActivityDate="2020-09-12T23:46:43.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1035" PostTypeId="5" CreationDate="2020-05-23T03:14:18.843" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:14:18.843" LastActivityDate="2020-05-23T03:14:18.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1036" PostTypeId="4" CreationDate="2020-05-23T03:14:18.843" Score="0" Body="Questions about or related to out-of-equilibrium simulations." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2021-12-27T23:44:46.250" LastActivityDate="2021-12-27T23:44:46.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1037" PostTypeId="5" CreationDate="2020-05-23T03:20:50.380" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:20:50.380" LastActivityDate="2020-05-23T03:20:50.380" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1038" PostTypeId="4" CreationDate="2020-05-23T03:20:50.380" Score="0" Body="questions concerning docking - a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-23T07:08:37.227" LastActivityDate="2020-05-23T07:08:37.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1039" PostTypeId="5" CreationDate="2020-05-23T03:22:57.267" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:22:57.267" LastActivityDate="2020-05-23T03:22:57.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1040" PostTypeId="4" CreationDate="2020-05-23T03:22:57.267" Score="0" Body="Questions about free energy." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2021-05-02T20:39:11.807" LastActivityDate="2021-05-02T20:39:11.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1041" PostTypeId="5" CreationDate="2020-05-23T03:27:52.747" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:27:52.747" LastActivityDate="2020-05-23T03:27:52.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1042" PostTypeId="4" CreationDate="2020-05-23T03:27:52.747" Score="0" Body="For questions about modeling spintronic (spin+electronic) properties of devices" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2020-07-16T17:18:06.827" LastActivityDate="2020-07-16T17:18:06.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1043" PostTypeId="5" CreationDate="2020-05-23T03:31:37.193" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-23T03:31:37.193" LastActivityDate="2020-05-23T03:31:37.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1044" PostTypeId="4" CreationDate="2020-05-23T03:31:37.193" Score="0" Body="Questions relating to spin-state phenomena and calculations." OwnerUserId="36" LastEditorUserId="36" LastEditDate="2020-05-23T14:06:18.850" LastActivityDate="2020-05-23T14:06:18.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1045" PostTypeId="2" ParentId="177" CreationDate="2020-05-23T04:47:06.313" Score="10" Body="&lt;p&gt;Yes! It is definitely possible and it is useful for calculating other things like electronic transport and first-principles values of Hubbard U (i.e. the &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevX.5.011006&quot; rel=&quot;noreferrer&quot;&gt;ACBN0 method&lt;/a&gt;, which I have used a bit). Some good papers to read are from Prof. Marco Buongiorno Nardelli's group at UNT:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;L. A. Agapito, A. Ferretti, A. Calzolari, S. Curtarolo, and M. Buongiorno Nardelli, &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.88.165127&quot; rel=&quot;noreferrer&quot;&gt;Physical Review B 88, 165127 (2013)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;L. A. Agapito, M. Fornari, D. Ceresoli, A. Ferretti, S. Curtarolo, and M. Buongiorno Nardelli, &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.93.125137&quot; rel=&quot;noreferrer&quot;&gt;Physical Review B 93, 125137 (2016)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;L. A. Agapito, S. Ismail-Beigi, S. Curtarolo, M. Fornari, and M. Buongiorno Nardelli, &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.93.035104&quot; rel=&quot;noreferrer&quot;&gt;Physical Review B 93, 035104 (2016)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;P. D’Amico, L. Agapito, A. Catellani, A. Ruini, S. Curtarolo, M. Fornari, M. Buongiorno Nardelli, and A. Calzolari, &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.94.165166&quot; rel=&quot;noreferrer&quot;&gt;Physical Review B 94, 165166 (2016)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;The basic idea is that you take the Kohn-Sham (K-S) orbitals and project them on the atomic orbitals you want to use in your tight-binding model. A convenient choice is the pseudo-atomic orbitals present in most pseudopotential files. Some difficulties can arise, especially in projecting empty conduction band states onto the atomic orbitals, since they are not as well-described by this basis. The method from these authors filters out K-S orbitals that have a low projectability on the localized basis. These get replaced in the Hamiltonian as zero eigenvalues. Another step is actually &quot;shifting&quot; these eigenvalues to a non-zero energy to avoid interfering with &quot;real&quot; bands in the energy range of interest.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I believe the code WanT (&lt;a href=&quot;http://www.wannier-transport.org/&quot; rel=&quot;noreferrer&quot;&gt;Wannier-Transport&lt;/a&gt;) can do this with Quantum Espresso, though it might not be an &quot;official&quot; feature. You can probably look through the source code to find the relevant methods. I think the code will output a &quot;prefix.ham&quot; file for the TB Hamiltonian.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More recent related codes to look at would be &lt;a href=&quot;http://aflowlib.org/src/paoflow/&quot; rel=&quot;noreferrer&quot;&gt;PAOFLOW&lt;/a&gt; and &lt;a href=&quot;http://aflowlib.org/src/aflowpi/&quot; rel=&quot;noreferrer&quot;&gt;AFLOW&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;&lt;/a&gt; from the AFlow consortium. &lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-23T05:11:07.807" LastActivityDate="2020-05-23T05:11:07.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1046" PostTypeId="1" CreationDate="2020-05-23T09:43:52.267" Score="20" ViewCount="1970" Body="&lt;p&gt;I am a beginner in DFT. Please suggest me some good material to understand the basics. &lt;/p&gt;&#xA;" OwnerUserId="606" LastEditorUserId="5" LastEditDate="2020-05-23T15:23:54.793" LastActivityDate="2020-05-30T04:33:18.043" Title="I am a beginner in DFT. What are some resources that could help me to learn the basics?" Tags="|density-functional-theory|reference-request|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1047" PostTypeId="2" ParentId="890" CreationDate="2020-05-23T13:11:44.503" Score="9" Body="&lt;p&gt;The sampling enhancement in replica exchange (REMD) comes completely from transitions between your different distributions, so the more transitions you attempt, the faster you will achieve equilibrium between all your different distributions. However, MD doesn't start generating locally decorrelated samples before ~1-10 ps of sampling (the true number will depend on the nature of the system and the topology of the local minimum you are exploring), so below this timescale you are very unlikely to observe any transitions of interest, even in your most &quot;mobile&quot; replica. Your samples are never completely decorrelated in the global sense, however, but this is something we accept and is the reason we use REMD in the first place.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore, any swap attempts after less time than your decorrelation time are still &quot;correct&quot; in the sense that they will converge to the right distributions but they are very unlikely to provide any increase in sampling quality (remember that the only transitions of interest are the ones that won't occur in the replica of interest in that timescale). And as was already stated, swaps need energy evaluations, which need CPU time / computational overhead and if you attempt swaps below your decorrelation time, while not technically wrong, you are quite literally wasting your time. If that computational overhead was not needed, there wouldn't be any reason not to run swaps at each timestep - there would be nothing to lose by doing that.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So I would say anything between 1-10 ps is fair game in the sense that in order to obtain the optimal parameter, you need to have knowledge which you can only obtain by running enhanced sampling in the first place! This agrees with the idea of &quot;relaxation&quot;, which actually just means that you obtain a typical sample around your local minimum which has no local memory of the previous sample. Again, global memory is still there, so &quot;relaxation&quot; (and &quot;local&quot;) is fundamentally a vague and timescale-dependent term - the space you sample locally within 1 ps is much more narrow than the space you sample within 1 ms.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-05-23T13:11:44.503" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1048" PostTypeId="2" ParentId="836" CreationDate="2020-05-23T14:12:13.253" Score="11" Body="&lt;h1&gt;Model potentials for exchange:&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;Exchange-correlation potentials like mBJ and GLLBSC have model orbital-dependent corrections included in the form of the functional. I'll first try to get the fundamental motivation across using GLLBSC as an example, and then attempt to go into how mBJ does this.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;GLLB/SC:&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;In the case of the &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.51.1944&quot; rel=&quot;noreferrer&quot;&gt;GLLB work&lt;/a&gt;, the authors used a model exchange potential near the core region to represent the stepped structure of the short-range exchange potential. It is my understanding that this short-ranged stepped structured is challenging to reproduce using (semi)local approximations such as the LDA or the variety of GGA available. It appears that given a somewhat accurate description of the long-range tail of the exchange hole, the short range stepped structure can be approximated. This is so far my understanding.The approach has been improved to include a description for correlation: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.115106&quot; rel=&quot;noreferrer&quot;&gt;GLLBSC&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;mBJ:&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;In the work linked, equation 1 has a term &lt;span class=&quot;math-container&quot;&gt;$t_{\sigma}$&lt;/span&gt; which is the KE density of the (KS) wavefunctions. This is your orbital-dependence. The &lt;span class=&quot;math-container&quot;&gt;$\rho_{\sigma}$&lt;/span&gt; term does not have an orbital dependence. There are two remaining free parameters, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, which the authors choose these values that provide accurate gaps for a (not too large) list of solids. Whether this procedure for deciding these two parameters is valid for a larger range of solids can only be answered by extensive testing of the functional's performance. But the key point is this: The improved description of the fundamental gap comes in both of these approaches from a &lt;strong&gt;model potential used for the short-range part of the exchange potential&lt;/strong&gt; instead of doing an exact-exchange or a GW calculation out. The gap is improved since the effect of exact-exchange that LDA/GGAs cannot describe quite well is described using a model orbital-dependent quantity. The benefit lies in the use of semilocal quantities, which prevent large numbers of Poisson equation solutions/other general calculations, as in the case of HSE/GW/any other exact-exchange-including approach.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;In summary:&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;The short-range part of the exchange potential has an improved description using (to the  best of my knowledge, orbital-dependent) model potentials as compared to LDA/GGAs.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note that in both the above cases, the common theme is the presence of orbital-dependent model corrections. These corrections may have free parameters (both of the above approaches do), and these free parameters need to be pinned down with some motivation. It can either be to recover well-known limits (GLLB), or to optimize against a test set of known observables (gaps in Table 1 in the case of mBJ or TB09, whichever name one prefers).&lt;/p&gt;&#xA;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Gritsenko, O., van Leeuwen, R., van Lenthe, E., &amp;amp; Baerends, E. J. (1995). Self-consistent approximation to the Kohn-Sham exchange potential. Physical Review A, 51(3), 1944.&lt;/li&gt;&#xA;&lt;li&gt;Kuisma, M., Ojanen, J., Enkovaara, J., &amp;amp; Rantala, T. T. (2010). Kohn-Sham potential with discontinuity for band gap materials. Physical Review B, 82(11), 115106.&lt;/li&gt;&#xA;&lt;li&gt;Tran, F., &amp;amp; Blaha, P. (2009). Accurate band gaps of semiconductors and insulators with a semilocal exchange-correlation potential. Physical review letters, 102(22), 226401.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="512" LastEditorUserId="512" LastEditDate="2020-05-23T18:05:02.153" LastActivityDate="2020-05-23T18:05:02.153" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1049" PostTypeId="2" ParentId="188" CreationDate="2020-05-23T16:35:49.890" Score="3" Body="&lt;ol&gt;&#xA;&lt;li&gt;How do you model quantum-confinement effects in optically active (e.g. plasmonic) mesoscopic structures?&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There should be a Comsol module that corresponds to &lt;a href=&quot;https://arxiv.org/abs/1901.03988&quot; rel=&quot;nofollow noreferrer&quot;&gt;this work&lt;/a&gt;, since it's mentioned that they implement the theory using that.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Is it possible to use FDTD for simulating mesoscopic structures (nanostructures) where quantum size effects matter?&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I'm not 100% sure, but it would likely be an immense pain. Modeling spatial dispersion (nonlocal dielectric response, &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;-dependent dielectric function, it has many names) involves different wavevectors of light experiencing different dielectric functions. I'm not sure how this can be implemented in a real-space, method such as FDTD since it involves a full convolution of your nonlocal (but still short-ranged) involved of the dielectric function. At the very least, this suggests to be at that every time step, you would have to Fourier transform your fields, use the convolution theorem to model the action of a nonlocal dielectric function on the incoming E fields, then FT back to get your real-space grid so you can then time-step to the next (there may be subtleties here too that I'm completely missing out).&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What is the limit in size that can accurately be described by classical electrodynamics for a gold nanoparticle?&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Sizes above 5-20 nanometers, generally, depending on your required accuracy&lt;/strong&gt;. This number is a bit contested, but roughly around here is when you'll notice simple Mie theory using step-function-dielectric models of spheres and core-shells start to break down compared to experiment. I recommend &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/037015738490098X&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1901.03988&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, and &lt;a href=&quot;https://arxiv.org/abs/1904.09279&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; for an intuition into the length scales where these nonlocal quantum confinement/electron spill-out effects become important.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What methods are there available to model quantum-confinement effects in nanostructures of different sizes?&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This is a bit open-ended, since the question arises: What is your intended observable? There are beautiful applications of &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl0622404&quot; rel=&quot;nofollow noreferrer&quot;&gt;simple models&lt;/a&gt; to model excitons in core-shell quantum dots in the weak confinement limit (small nanoparticles, ~10-30 nm in diameter). In these regimes, your exciton ends up behaving like a particle in a finite well, a finite amount of energy greater than the optical gap, since the first available state is raised due to the finite extent of the dot.&lt;/li&gt;&#xA;&lt;li&gt;For plasmonics, you can try &lt;strong&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/tddft/lcaotddft.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;LCAO-based TDDFT&lt;/a&gt;&lt;/strong&gt; where you can make gold nanoparticles, etc (careful of the number of atoms, this is LCAO, but it's still DFT, don't get too crazy unless you have a supercomputer at your disposal) or other finite structures and attempt to have a go. The (many) subtleties of LCAO-TDDFT apply to this, so if you're not familiar with this method, it may take a bit to get an intuition for whether a calculation's results are physically meaningful or not.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="512" LastActivityDate="2020-05-23T16:35:49.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1050" PostTypeId="2" ParentId="1046" CreationDate="2020-05-23T17:49:44.127" Score="18" Body="&lt;p&gt;Assuming you are interested in pursuing plane-wave periodic DFT, there is a clear best answer in my opinion and that's &lt;a href=&quot;https://www.wiley.com/en-us/Density+Functional+Theory%3A+A+Practical+Introduction-p-9780470373170&quot; rel=&quot;noreferrer&quot;&gt;&quot;Density Functional Theory: A Practical Introduction&quot;&lt;/a&gt; by Sholl and Steckel. For a relatively complex topic, they truly manage to accomplish the goal of making this a &lt;em&gt;practical&lt;/em&gt; introduction. As they say in the intro, &quot;you don't need to learn how to build a car to learn how to drive from Point A to Point B&quot;, and I think that mentality helps a lot with getting started with DFT. It still has enough detail to make it not overly superficial though.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you're using VASP, I also recommend &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.html&quot; rel=&quot;noreferrer&quot;&gt;&quot;Modeling materials using density functional theory&quot;&lt;/a&gt; by Kitchin. It's a useful hands-on resource for learning how to use VASP, particularly through the useful program the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-05-23T17:49:44.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1051" PostTypeId="1" AcceptedAnswerId="1811" CreationDate="2020-05-23T18:39:55.630" Score="20" ViewCount="525" Body="&lt;p&gt;I have a little problem concerning hexagonal volume fitting using VASP.&#xA;I have followed these steps:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Relax the structure from a given volume using &lt;code&gt;ISIF =4&lt;/code&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Copy CONTCAR to POSCAR and relax it again&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Run with &lt;code&gt;ISMEAR = -5&lt;/code&gt; and without relaxation&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Repeat for different volumes (+10% +5% 0% -5% -10%)&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use your script for EOS fitting.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;It worked successfully with cubic systems. But for a hexagonal system (e.g. Carbon), I got the figure below. I don't know why I always get wrong results for the first volume point. Even with 7 volume points the first point always wrong.&lt;a href=&quot;https://i.stack.imgur.com/x6hYC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x6hYC.png&quot; alt=&quot;Equation of state fitting&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="7" LastEditDate="2020-06-26T21:46:15.873" LastActivityDate="2020-07-28T13:14:28.850" Title="Hexagonal lattice volume EOS fit" Tags="|density-functional-theory|software|vasp|" AnswerCount="3" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1053" PostTypeId="1" AcceptedAnswerId="1055" CreationDate="2020-05-24T03:56:44.337" Score="28" ViewCount="2622" Body="&lt;p&gt;I just saw &lt;a href=&quot;https://materials.stackexchange.com/q/1046/201&quot;&gt;I am a beginner in Density Functional Theory. What are some resources that could help me to learn the basics?&lt;/a&gt; and it reminded me that few years ago I'd asked &lt;a href=&quot;https://chemistry.stackexchange.com/q/30933/16035&quot;&gt;How can I calculate the charge distribution of a water molecule?&lt;/a&gt; in Chemistry SE.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There is some excellent advice there, but at the time I'd realized I couldn't just install a python package and type &quot;Calculate H2O&quot; so I shelved it at the time. Now there is Materials Modeling SE!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In addition to reading the material recommended in answers to the resources question linked above, I'd like to run an example and getting the electron density of a water molecule still captures my interest.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What would be a simple approach be, and by simple I mean a python package that can be used with an Anaconda Python 3 installation and run without a large number of additional dependencies that might be complicated to install?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The process should be instructive but the results do not have to be particularly accurate; I've chosen the water molecule to get my feet wet and get a better feeling for how these calculates are actually done procedurally.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If there is an OS aspect to this I'd prefer to do this on MacOS but I have access to Windows machines. I know that these can be computationally intensive once one gets going and so I may need to find more hardware resources later on.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2021-03-12T20:25:34.127" LastActivityDate="2021-03-12T20:25:34.127" Title="How to &quot;get my feet wet&quot; in Density Functional Theory by simulating a water molecule using Python" Tags="|density-functional-theory|one-topic-per-answer|software-recommendations|python|from-chem-se|" AnswerCount="3" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1054" PostTypeId="2" ParentId="1053" CreationDate="2020-05-24T04:20:18.267" Score="16" Body="&lt;p&gt;If you're set on using Python here are some options. I haven't used these codes so I can't speak to their ease of use.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;PyQyante&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://pyquante.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;PyQuante&lt;/a&gt; is a suite of programs that can not only do DFT but also Hartree-Fock, MP2, and more. Certain parts of the code are written in C for speed. A package can be &lt;a href=&quot;https://sourceforge.net/projects/pyquante/&quot; rel=&quot;noreferrer&quot;&gt;downloaded&lt;/a&gt; and then &lt;a href=&quot;http://pyquante.sourceforge.net/#download-and-installation&quot; rel=&quot;noreferrer&quot;&gt;installed&lt;/a&gt; with Python, but a newer version, &lt;a href=&quot;https://github.com/rpmuller/pyquante2&quot; rel=&quot;noreferrer&quot;&gt;PyQuante2&lt;/a&gt;, can simply be installed with conda. It typically only requires Numpy, but some other packages are recommended in certain situations (see the previous install link).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On Windows:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;conda install -c rpmuller pyquante2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;On Linux/Mac:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;conda install -c rpmuller pyquante2_pure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;h2&gt;Psi&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;Psi&lt;/a&gt; is also package that includes a lot of quantum chemistry methods beyond DFT.  The front end uses Python but underlying code uses C and C++. It can be &lt;a href=&quot;http://psicode.org/psi4manual/master/build_planning.html&quot; rel=&quot;noreferrer&quot;&gt;compiled&lt;/a&gt; from source code, but binaries can be &lt;a href=&quot;http://psicode.org/psi4manual/master/conda.html&quot; rel=&quot;noreferrer&quot;&gt;installed&lt;/a&gt; either by using provided install scripts or by using conda (it's recommended to create a new environment):&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;conda create --name psi4env python=3.6 psi4 psi4-rt -c psi4/label/dev -c psi4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Psi requires a fairly large number of dependencies but they are taken care of by conda if you install by that route. &lt;/p&gt;&#xA;&#xA;&lt;h2&gt;PySCF&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/pyscf/pyscf&quot; rel=&quot;noreferrer&quot;&gt;PySCF&lt;/a&gt; is another Python-based suite of programs. Some additional documentation is available &lt;a href=&quot;https://sunqm.github.io/pyscf/overview.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. It can support finite and periodic systems and has a fairly extensive list of &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/FEATURES&quot; rel=&quot;noreferrer&quot;&gt;features&lt;/a&gt;. If you build it yourself, you will require&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;CMake 2.8+&lt;/li&gt;&#xA;&lt;li&gt;Numpy 1.8.0+&lt;/li&gt;&#xA;&lt;li&gt;Scipy 0.10+ (0.12.0+ for python 3.4-3.8)&lt;/li&gt;&#xA;&lt;li&gt;h5py 2.3.0+ (also HDF5 1.8.4+)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;But this is made simpler if you just use conda:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;conda install -c pyscf pyscf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;h2&gt;Other options&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;If you are interested, it might be worthwhile to look into &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;other codes&lt;/a&gt;, and if they are open-source, try compiling them on your Mac. Quantum Espresso should compile pretty easily, I've done it on my Windows PC via Cygwin and Windows Subsystem for Linux (it's also been installed on at least one smartphone and Playstation 3).&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-24T06:37:28.797" LastActivityDate="2020-05-24T06:37:28.797" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1055" PostTypeId="2" ParentId="1053" CreationDate="2020-05-24T04:28:32.157" Score="16" Body="&lt;h1&gt;SlowQuant&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;In your question from 2015, you mentioned PyQuante and PySCF, but I saw no mention of &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;SlowQuant&lt;/a&gt; in the question or in the multiple answers. I see that while writing this, someone else answered, with mentions of PyQuante, PySCF, and Psi4 again. Still no mention of SlowQuant.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The author of SlowQuant has described the program this way (emphasis mine):&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;SlowQuant is a molecular quantum chemistry program written in python.&#xA;  &lt;strong&gt;Even the computational demanding parts are written in python&lt;/strong&gt;, so it&#xA;  lacks speed, thus the name SlowQuant. &lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Right below that he gives the command for running it on  the water molecule (click to get input files):&lt;br&gt; &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;python SlowQuant.py &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/Examples.html#example-input-files&quot; rel=&quot;noreferrer&quot;&gt;H2O.csv&lt;/a&gt;&#xA;  &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/illustrativecalc.html#scf-with-and-without-diis&quot; rel=&quot;noreferrer&quot;&gt;setting.csv&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Dependencies:&lt;/strong&gt;&lt;br&gt;&#xA; - Python 3.5 or above&lt;br&gt;&#xA; - numpy 1.13.1&lt;br&gt;&#xA; - scipy 0.19.1&lt;br&gt;&#xA; - numba 0.34.0&lt;br&gt;&#xA; - cython 0.25.2&lt;br&gt;&#xA; - gcc 5.4.0&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you can see, even SlowQuant requires the GCC compilers, presumably because it uses Cython which is for turning Python code into faster running C code (&lt;strong&gt;maybe this program is not so slow after all?&lt;/strong&gt;).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-24T04:58:56.487" LastActivityDate="2020-05-24T04:58:56.487" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="1056" PostTypeId="1" AcceptedAnswerId="1057" CreationDate="2020-05-24T05:10:19.643" Score="39" ViewCount="11315" Body="&lt;p&gt;I am a DFT user and at some point in the future, I would like to write my own DFT code in Python to help gain a deeper understanding of DFT. As mentioned in a &lt;a href=&quot;https://materials.stackexchange.com/a/578/88&quot;&gt;previous answer&lt;/a&gt; people have written their own DFT codes to understand more deeply how the theory and algorithms work. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Where do I start? What are the important aspects I should consider?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-05-24T17:26:26.477" LastActivityDate="2020-08-27T20:08:53.817" Title="How to write my own density functional theory (DFT) code in Python?" Tags="|density-functional-theory|software|python|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1057" PostTypeId="2" ParentId="1056" CreationDate="2020-05-24T08:53:42.220" Score="40" Body="&lt;p&gt;Understanding, deriving, writing, testing and debugging an ab initio code can be a lenghty and tedious task. I'd like to provide a starting point for you here. If you just to it for pedagocial reasons, it might be advisable to start with the atomic problem and try to solve it with DFT. The effort for that is not too big, but it covers nearly all the nesseary physical principles to understand how one arrives at total energies and electron densities. With such a program, you can predict for example, energy levels of a certain element. Also, If you want to extend your program to treat crystalline material i. e., the written routines for the atomic problem will be of fundamental use. Core states are essential calculated like this.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The following websites provide some beginner-friendly introduction to the topic of simple DFT calculations of atoms.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[1]: &lt;a href=&quot;https://github.com/certik/dftatom&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/certik/dftatom&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;[2]: &lt;a href=&quot;https://github.com/theochem/tinydft&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/theochem/tinydft&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;[3]: &lt;a href=&quot;https://compphys.go.ro/dft-for-an-atom/&quot; rel=&quot;noreferrer&quot;&gt;https://compphys.go.ro/dft-for-an-atom/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;[4]: &lt;a href=&quot;https://www.theoretical-physics.com/&quot; rel=&quot;noreferrer&quot;&gt;https://www.theoretical-physics.com/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;I want to list down some the steps that are nessary for a simple solver written in python.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Setting up the equations&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The starting point is the Kohn–Sham equation, which is the one-electron Schrödinger-like equation of a fictitious system of non-interacting particles. If you take the Born-Oppenheimer approximation into account and assume that the Kohn-Sham potential is radial symmetric, the task reduces to solve the radial part of the Kohn-Sham equation under some restrictions. Basically, you need to construct a solver that calculates the radial wave function and the eigenenergy for a given Kohn-Sham potential. For this you will need a shooting method similar to [1]. Basically, one solves the an inital value problem starting from &lt;span class=&quot;math-container&quot;&gt;$r=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r=\infty$&lt;/span&gt; and change the energy till the solution matches at some point.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Calculating the Kohn-Sham potential&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The effective Kohn-Sham potential is the sum of the core contributions (&lt;span class=&quot;math-container&quot;&gt;$1/r$&lt;/span&gt; coloumb potential), the exchange-correlation (input here is the electron density) and the Hartree potential. In order to get the Hartree potential, you will need to solve the radial Poisson equation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In order to set up a self-consistent cycle, you will need to calculate the poisson equation, which can be treaten as an inital value problem or also as an boundary value problem.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Remark to computational efficency in Python&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The computational effort is considerable for bigger atoms. You might want to take a look some acceleration methods for Python like Numba.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;http://numba.pydata.org/&quot; rel=&quot;noreferrer&quot;&gt;http://numba.pydata.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="717" LastEditorUserId="717" LastEditDate="2020-05-26T07:29:49.370" LastActivityDate="2020-05-26T07:29:49.370" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1058" PostTypeId="1" AcceptedAnswerId="1199" CreationDate="2020-05-24T11:57:24.173" Score="18" ViewCount="1580" Body="&lt;p&gt;I'm new to DFT. I want to make use of the GTH pseudopotential.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am trying to understand how this potential works. I read the article &quot;Separable dual-space Gaussian pseudopotentials&quot; by S. Goedecker, M. Teter, and J. Hutter.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It indicates that the potential consists of two parts: local and nonlocal. There is an exponential parameter &lt;span class=&quot;math-container&quot;&gt;$r_{loc}$&lt;/span&gt; in the local potential. This parameter denotes the range of the Gaussian ionic charge distribution.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is meant by this in terms of physical quantities? Does it mean that at distances exceeding &lt;span class=&quot;math-container&quot;&gt;$r_{loc}$&lt;/span&gt;, the non-local part of the potential begins to prevail? As the non-local part of the potential does not contain the parameter &lt;span class=&quot;math-container&quot;&gt;$r_{loc}$&lt;/span&gt; at all. How is &lt;span class=&quot;math-container&quot;&gt;$r_{loc}$&lt;/span&gt; determined in practice?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/e2lp1.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e2lp1.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aF1jd.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aF1jd.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Can anyone please explain the purpose of the parameter &lt;span class=&quot;math-container&quot;&gt;$r_{loc}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="663" LastEditorUserId="52" LastEditDate="2020-06-02T15:27:12.887" LastActivityDate="2020-06-05T12:52:18.090" Title="Understanding the GTH Pseudopotential" Tags="|density-functional-theory|pseudopotentials|from-chem-se|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1059" PostTypeId="2" ParentId="1056" CreationDate="2020-05-24T13:25:50.020" Score="17" Body="&lt;p&gt;&lt;strong&gt;For molecular DFT, there are definitely several tutorials around for major pieces.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;http://psicode.org&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt; code has a set of Jupyter notebooks called &lt;a href=&quot;https://github.com/psi4/psi4numpy&quot; rel=&quot;noreferrer&quot;&gt;Psi4Numpy&lt;/a&gt;, working through each element of a quantum chemical program.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This includes:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/psi4/psi4numpy/tree/master/Self-Consistent-Field&quot; rel=&quot;noreferrer&quot;&gt;Self-Consistent Field&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/psi4/psi4numpy/tree/master/Tutorials/04_Density_Functional_Theory&quot; rel=&quot;noreferrer&quot;&gt;DFT grids, LDA, GGA, metaGGA&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/psi4/psi4numpy/blob/master/Tutorials/11_Integrals/11a_1e_Integrals.ipynb&quot; rel=&quot;noreferrer&quot;&gt;One electron integrals&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;There are a variety of other tutorials for response properties, geometry optimization, etc. Certainly you can work through much using the tutorials, particularly if you build off of Psi4 for &quot;missing pieces.&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Moreover, most (almost all?) functionals have been implemented as part of &lt;a href=&quot;https://www.tddft.org/programs/libxc/&quot; rel=&quot;noreferrer&quot;&gt;libxc&lt;/a&gt; which also has an example of calculating the XC energy for &lt;a href=&quot;https://www.tddft.org/programs/libxc/manual/&quot; rel=&quot;noreferrer&quot;&gt;varying density&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-24T13:25:50.020" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1060" PostTypeId="1" CreationDate="2020-05-24T16:40:33.403" Score="15" ViewCount="312" Body="&lt;p&gt;I've simulated the dielectric constants using the LEPSILON = .TRUE. tag and the PBE GPAW potentials. A collegue mentioned that for accurate results norm conserving pseudo-potentials are the way to go. I have two problems/questions now&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Why would norm conserving potentials be better? I could not find any source verifying this.&lt;/li&gt;&#xA;&lt;li&gt;How can I get the norm conserving potentials. I could not find them on the VASP download site anymore.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="250" LastEditorUserId="5" LastEditDate="2020-08-07T17:52:38.693" LastActivityDate="2020-08-07T17:52:38.693" Title="VASP Dielectric constants: What potential to use?" Tags="|vasp|pseudopotentials|dichalcogenides|dielectric-constants|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1062" PostTypeId="2" ParentId="771" CreationDate="2020-05-24T18:18:28.683" Score="6" Body="&lt;p&gt;Normally, this could happen due to several issues:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;discontinuity in the k-path you selected to calculate the band structure,&lt;/li&gt;&#xA;&lt;li&gt;low number of points in each interval,&lt;/li&gt;&#xA;&lt;li&gt;bad convergence parameters. &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-24T19:03:43.857" LastActivityDate="2020-05-24T19:03:43.857" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1063" PostTypeId="1" CreationDate="2020-05-24T19:00:03.703" Score="14" ViewCount="797" Body="&lt;p&gt;In general, the &lt;a href=&quot;https://www.iucr.org/resources/cif&quot; rel=&quot;nofollow noreferrer&quot;&gt;CIF&lt;/a&gt; file with the crystal structure uses &lt;a href=&quot;https://en.wikipedia.org/wiki/Fractional_coordinates&quot; rel=&quot;nofollow noreferrer&quot;&gt;fractional coordinates&lt;/a&gt; for setting the atoms positions. In this type of coordinates, the atom positions are relative to the cell parameters. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another way to setting up the atom positions is to use Cartesian coordinates. In this type of coordinate, the atoms have absolute positions, i.e., don't depend on cell parameters.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In many DFT codes, you can use both type of coordinates to represent your system in the input files.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question: is there any performance difference in using one type over the other one?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;PS: in general, I work with systems where I have to add a vacuum region that, &lt;em&gt;a priori&lt;/em&gt;, I don't know how big will be, so, I use Cartesian coordinates. &lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="118" LastEditDate="2020-05-25T11:50:56.870" LastActivityDate="2020-05-26T15:02:17.810" Title="Is there a performance difference when using fractional coordinates instead of Cartesian coordinates?" Tags="|density-functional-theory|crystal-structure|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1064" PostTypeId="1" CreationDate="2020-05-24T19:47:39.573" Score="15" ViewCount="1198" Body="&lt;p&gt;I’m doing CCSD(T) calculations (for both transition and ground state geometries) on a series of small molecules in Gaussian09. Several similar calculations terminated without any problems but one TS calculation and one ground state calculation gave me this error after about 20 minutes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;HESSIAN DOES NOT HAVE THE DESIRED LOCAL STRUCTURE&#xA; TAKING P-RFO STEP&#xA; SEARCHING FOR LAMDA THAT MAXIMIZES ALONG THE LOWEST MODE&#xA; VALUE TAKEN    LAMDA=   3.41177479&#xA; SEARCHING FOR LAMDA THAT MINIMIZES ALONG ALL OTHER MODES&#xA; UNABLE TO DETERMINE LAMDA IN FmD114&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Without these remaining calculations, several months’ worth of work is incomplete. I will appreciate any suggestions. I’ve searched a lot of chemistry forums, but nobody seems to know the solution.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here’s my route section for the TS calculation:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;#p opt=(ts,z-matrix,noeigentest) freq=noraman rccsd(t)/genecp nosymm maxdisk=15950MB&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Route section for the ground state calculation:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;code&gt;#p opt=(z-matrix,noeigentest) freq=noraman rccsd(t)/genecp maxdisk=15950MB&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="723" LastEditorUserId="723" LastEditDate="2020-06-05T13:23:56.260" LastActivityDate="2020-06-29T19:15:38.613" Title="CCSD(T) Transition State and Ground State Calculations in Gaussian09: &quot;Unable to Determine Lambda&quot;?" Tags="|gaussian|coupled-cluster|computational-chemistry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1065" PostTypeId="2" ParentId="1064" CreationDate="2020-05-24T20:59:07.320" Score="11" Body="&lt;p&gt;It's not a descriptive error message, but this occurs when you reach the max number of iterations for the Eigenvector Following (EF) algorithm and still haven't converged a lambda. While Gaussian uses a different approach (the Berny Algorithm) for methods which have analytical gradients, CCSD(T) is one of the few methods for which these still aren't implemented, so it has to use EF to find minima/saddle points.&lt;/p&gt;&#xA;&lt;p&gt;This &lt;a href=&quot;https://www.q-chem.com/qchem-website/manual/qchem43_manual/sect-ef.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt; gives a mathematical description of the algorithm showing what lambda means in this context (note, the page is for QChem, but the underlying algorithm should be more or less the same in both programs).&lt;/p&gt;&#xA;&lt;p&gt;There is probably a more in depth solution to your problem, and it would probably require a bit more knowledge about your system. However, for now you can try adding &lt;code&gt;iop(1/6=N)&lt;/code&gt; to allow it to try more iterations (&lt;a href=&quot;https://gaussian.com/overlay1/&quot; rel=&quot;nofollow noreferrer&quot;&gt;see here&lt;/a&gt;) There might be an iteration count somewhere in your output, but otherwise the default number of steps can't go higher than 40 regardless of system size, so maybe set N to something &amp;gt;40.&lt;/p&gt;&#xA;&lt;p&gt;Also, if you haven't already, try to find your minima/saddle point with a lower level of theory first (e.g. DFT, MP2, CCSD) and use this as your starting geometry.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="52" LastEditDate="2020-06-29T19:15:38.613" LastActivityDate="2020-06-29T19:15:38.613" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1066" PostTypeId="2" ParentId="1063" CreationDate="2020-05-24T21:08:40.357" Score="11" Body="&lt;p&gt;&lt;strong&gt;Warning possible pseudoanswer:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm unfamiliar with this exactly but my gut feeling is fractional coordinates are better because they represent the physical crystal more intuitively than Cartesians. I couldn't find an exact paper on a comparison between Cartesians and fractional coordinates. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, the following lists some tangential evidence that fractional coordinates are better:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;This&#xA;&lt;a href=&quot;http://www.theochem.unito.it/crystal_tuto/mssc2013_cd/tutorials/optgeom/opt_tut.html&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;&#xA;has exercises to compare redundant and fractional coordinate&#xA;optimization. It's worthwhile to note that they don't even mention&#xA;Cartesian optimization as an option suggesting that it's not a very&#xA;popular option in this package. Other ab initio packages for periodic systems also use fractional coordinates more frequently than Cartesian coordinates (e.g. VASP). &lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Any time you can cast the optimization problem into a coordinate system that&#xA;makes more physical sense than it can be incredibly beneficial. For example delocalized  internal coordinates and redundant internal coordinates are much more efficient for molecular optimization than Cartesian coordinates because they represent molecules better (e.g. both of these coordinate systems are made using bonds, angles and torsions -- chemical concepts).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This work &lt;sup&gt;[1]&lt;/sup&gt; combines fractional coordinates with delocalized coordinates and saw 2-10 x less iterations than pure Cartesians. However, it's unclear exactly where the performance boost came from delocalized coordinates or fractional coordinates or some combination of both. Nevertheless, very cool!&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&#xA;[1] Bučko, T., Hafner, J. &amp;amp; Ángyán, J. G. Geometry optimization of periodic systems using internal coordinates. J. Chem. Phys. 122, (2005).&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-24T21:31:42.137" LastActivityDate="2020-05-24T21:31:42.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1067" PostTypeId="1" AcceptedAnswerId="1068" CreationDate="2020-05-24T21:38:07.887" Score="15" ViewCount="1247" Body="&lt;p&gt;I'm just now starting to use the program &lt;a href=&quot;https://www.cp2k.org/&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt;, and I am having trouble understanding the difference between the &lt;code&gt;optimizer&lt;/code&gt; options (CG, BFGS, LBFGS). I have seen what they have written on their website, but it didn't help me much since I have no idea what the optimizer is. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If possible could someone also explain to me what relation the optimizer has to the DFT functional and basis set selected when doing a geometry optimization of a single molecule vs a crystal structure?&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-05-24T22:21:05.807" LastActivityDate="2020-05-25T00:54:55.977" Title="What exactly is the &quot;Optimizer&quot; in CP2K geometry optimization?" Tags="|optimization|cp2k|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1068" PostTypeId="2" ParentId="1067" CreationDate="2020-05-24T22:01:38.543" Score="16" Body="&lt;p&gt;The question says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I am having trouble understanding the difference between the&#xA;optimizer options (CG, BFGS, LBFGS).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;These are three optimization algorithms that evidently are implemented in CP2K for geometry optimization. Maybe the documentation should have said &amp;quot;optimization algorithm&amp;quot; instead of &amp;quot;optimizer&amp;quot;, to make this more clear:&lt;/p&gt;&#xA;&lt;h2&gt;CG: &lt;a href=&quot;https://en.wikipedia.org/wiki/Conjugate_gradient_method&quot; rel=&quot;noreferrer&quot;&gt;Conjugate Gradient method&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;h2&gt;BFGS: &lt;a href=&quot;https://en.wikipedia.org/wiki/Broyden%E2%80%93Fletcher%E2%80%93Goldfarb%E2%80%93Shanno_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;h2&gt;LBFGS: &lt;a href=&quot;https://en.wikipedia.org/wiki/Limited-memory_BFGS&quot; rel=&quot;noreferrer&quot;&gt;Limited Memory BFGS&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;As for the second part of the question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If possible could someone also explain to me what relation the&#xA;optimizer has to the DFT Functional and Basis Set selected when doing&#xA;a geometry optimization of a single molecule vs a crystal structure.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Essentially the DFT functional and basis set choice have no rigorous connection to the choice of optimization algorithm. The reason why more than one optimization algorithm is offered, is because some optimization problems are better solved by some algorithms than others. This would usually have much more to do with the shape of the energy surface that is being optimized, than the choice of functional or basis set. The optimization algorithm (&amp;quot;optimizer&amp;quot;) that is best for a landscape with thousands of equal-value local minima, might not be the best algorithm for a more smooth surface which could be optimized much faster with a simpler algorithm.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since CP2K has only these three methods implemented, I would recommend BFGS (the most efficient optimizer) if you have enough RAM and time, CG if the system gets a bit larger and too demanding for BFGS, and LBFGS if the system is very large.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-25T00:54:55.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1069" PostTypeId="2" ParentId="1067" CreationDate="2020-05-24T22:28:22.050" Score="14" Body="&lt;p&gt;&lt;strong&gt;Optimizer&lt;/strong&gt; refers to the algorithm used for finding the minimum of a function. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;In this specific case the optimizer is referring to &quot;geometry optimization&quot; which seeks to find the local minimum of the potential energy surface. However, optimizers can also be used in other areas in DFT, for example, to optimize the wavefunction. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Below I will give a brief overview of the three optimizers that you listed:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;CG stands for conjugate gradient, however before describing CG it's easier to first describe &quot;steepest descent&quot;. In steepest descent you follow the negative of energy nuclear gradient (&lt;span class=&quot;math-container&quot;&gt;$-\displaystyle{dE/d\mathbf{x}}$&lt;/span&gt;) downhill to the minimum along that direction using a linesearch algorithm, and repeat this until reaching the local minimum. Because in each prior step you followed a direction to the minimum the subsequent step is by definition orthogonal (perpendicular) to the prior step, but is not orthogonal to a direction searched two steps ago (see figure).Therefore SD is inefficient near the minimum and sometimes oscillates near the solution&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HG5vv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HG5vv.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;However, note that if the potential energy surface was perfectly circular, instead of elliptical the solution would happen in two steps (N steps for N dimensions).   CG takes advantage of this observation by introducing the concept of &quot;conjugate orthogonality&quot; -- essentially it stretches the vectors to become orthogonal in some new space which is perfectly spherical therefore the solution can again happen in N steps. This however assumes that the PES is perfectly Harmonic and we know it's analytic quadratic form (&lt;span class=&quot;math-container&quot;&gt;$f(x) = 1/2x^TAx + bx +c$&lt;/span&gt;) -- which we do not! Therefore, we aren't guaranteed that all steps will be conjugate orthogonal to all other steps, or that the solution will converge in N steps. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4GO5S.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4GO5S.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;In part 1 it was revealed that CG would converge in N steps if we knew the analytical form of the PES which we don't and this significantly reduces its performance. BFGS and L-BFGS are algorithms that introduce the concept of the local quadratic approximation &lt;span class=&quot;math-container&quot;&gt;$E(x) = E(x_0) + g^T\Delta X + 1/2\Delta x^T H_0\Delta X$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; is the Hessian (&lt;span class=&quot;math-container&quot;&gt;$d^2 E/dx^2)$&lt;/span&gt;. This is better because we can now gain a better picture of the PES by including local curvature information. However, the Hessian is an expensive quantity to calculate and is typically approximated. The BFGS and L-BFGS algorithms are methods to update this approximate Hessian so that it improves over time, therefore accelerating the optimization. The main difference is that L-BFGS is less memory intensive and should be used if the system is large. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;See these references for more information on optimization &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;An Introduction to the Conjugate Gradient Method Without the Agonizing Pain Edition 1/4 By Jonathan Richard Shewchuk&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Schlegel, H. B. Geometry optimization. Wiley Interdiscip. Rev. Comput. Mol. Sci. 1, 790–809 (2011).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-24T22:47:28.907" LastActivityDate="2020-05-24T22:47:28.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1070" PostTypeId="1" AcceptedAnswerId="1073" CreationDate="2020-05-25T02:16:31.413" Score="26" ViewCount="2625" Body="&lt;p&gt;The &amp;quot;curse of dimensionality&amp;quot; is an ubiquitous issue arising in both electronic structure and quantum molecular dynamics, which refers to the exponential scaling of computational cost with the number of degrees of freedom of the systems of interest.&lt;/p&gt;&#xA;&lt;p&gt;This problem is manifested in many applications of computational studies (e.g. determining transition states of chemical reactions, geometry optimization of large molecular systems, simulating spectra of molecular systems, etc). The &amp;quot;curse of dimensionality&amp;quot; dramatically restricts the practical size of systems that can be studied computationally.&lt;/p&gt;&#xA;&lt;p&gt;Assuming that only classical computers are available, what are the &amp;quot;smart algorithms&amp;quot; that have been devised to partially solve this &amp;quot;curse of dimensionality&amp;quot; problem and make the subset of the full problem be close to linear scaling?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="7" LastEditDate="2020-07-02T15:46:26.753" LastActivityDate="2020-07-02T15:46:26.753" Title="What are the &quot;smart algorithms&quot; applied to solve the &quot;curse of dimensionality&quot;?" Tags="|molecular-dynamics|electronic-structure|computational-chemistry|quantum-chemistry|algorithms|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1071" PostTypeId="2" ParentId="862" CreationDate="2020-05-25T07:03:19.220" Score="6" Body="&lt;p&gt;One of my colleagues uses a very hacky solution to this. I don't recommend using it, but I can imagine it being useful in certain narrow applications, so I'll post it here anyways. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Let's call this person Alex. Alex is a PI and admin for a cluster used by a small research group. The cluster has a normal queuing system, but unlike most clusters, it is not set up to kill jobs running outside the queue on the compute nodes. Instead, it just sets them to &lt;code&gt;nice -19&lt;/code&gt;. Alex has a lot of &lt;strong&gt;very long&lt;/strong&gt; (months+) low-memory, low-priority simulations. Instead of running them through the queue, they log onto a not-too-busy node and start their jobs manually. They don't keep track of where any particular job is running. The jobs regularly check a text file that has a flag in it, to kill that job they just edit that file to have the 'kill' flag. &lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Advantages of this system:&lt;/h2&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Since jobs are run with &lt;code&gt;nice -19&lt;/code&gt; priority, if the queue starts a job on that node, the job is effectively paused until the node frees up again (although it will run in the background when there are spare cycles). &lt;/li&gt;&#xA;&lt;li&gt;This allows for &lt;strong&gt;super&lt;/strong&gt; long simulations without tying up the queue or preventing anyone else from running jobs. &lt;/li&gt;&#xA;&lt;li&gt;It's basically like a slow cooker. &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;h2&gt;Disadvantages:&lt;/h2&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Complicated and labor-intensive to maintain and keep track of all the running jobs, know how to turn them off, etc. &lt;/li&gt;&#xA;&lt;li&gt;Only sustainable for one person to do this on a given system (and really only when that person is in charge). &lt;/li&gt;&#xA;&lt;li&gt;Also really only makes sense for low-memory simulations where you &lt;strong&gt;really&lt;/strong&gt; don't care when you get the final result. &lt;/li&gt;&#xA;&lt;li&gt;Probably has other weird side effects. It's easy to lose track of your running jobs or not know which is which. &lt;/li&gt;&#xA;&lt;li&gt;Seriously &lt;strong&gt;don't do this.&lt;/strong&gt; &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-25T07:03:19.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1072" PostTypeId="2" ParentId="1004" CreationDate="2020-05-25T07:09:51.007" Score="8" Body="&lt;p&gt;A more approximate but sometimes easier approach than the one of &lt;a href=&quot;https://materials.stackexchange.com/a/1005/607&quot;&gt;Nike Dattani&lt;/a&gt; might be to calculate an artificial reaction coordinate of separating the two systems. This can be done manually or by employing some accelerated MD technique, e.g. metadynamics. The latter would even allow you to map the free energy along this path and thereby give you an estimate of the free energy barrier. You could then use your initial idea to directly translate this barrier to a temperature.&lt;/p&gt;&#xA;" OwnerUserId="607" LastActivityDate="2020-05-25T07:09:51.007" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1073" PostTypeId="2" ParentId="1070" CreationDate="2020-05-25T07:33:59.400" Score="25" Body="&lt;p&gt;This is a very broad question, so I am going to give a very brief overview of typical exponentially-scaling problems. I am not an expert in most of these areas, so any suggestions or improvements will be welcome.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Solving the Schrödinger equation&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In order to solve the Schrödinger equation numerically, you need to diagonalise a rank &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; tensor -- as you can see, a pretty impossible operation not only in terms of CPU power, but also in terms of memory. The main problem in fact is that the wavefunction has to be antisymmetric with respect to all electrons, which is the main reason for combinatorial explosion. An alternative way is to expand the wavefunction as a multivariable Taylor series of antisymmetric functions (determinants), and if you were to do it exactly (full configuration interaction), it also scales exponentially. So at this point you can either solve the equation by ignoring most of the correlation between different degrees of freedom (Hartree-Fock, Moller-Plesset perturbation theory, truncated configuration interaction), project the &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt;-dimensional problem onto a 3-dimensional one, where the exact solution is unknown, but able to be approximated (density functional theory), or solve the correlated problem exactly for an idealised approximate infinite sum (coupled cluster theory). Another way to solve the equation is to convert it to a sampling problem (diffusion quantum Monte Carlo), which is exact for bosons, but needs an approximation for fermions (fixed node approximation), so that it doesn't scale exponentially. There is a lot of literature on making a lot of the above methods linear-scaling using clever approximations or making the formally exact full configuration interaction method more efficient (full configuration interaction quantum Monte Carlo), but in general, the more computational time you throw in, the larger the class of problems your method can tackle and some of the above approximations are better (and slower) than others.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Exploring potential energy surfaces&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is related to the sampling problem which I will address later. Here you convert a &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt;-dimensional sampling problem into a 1, 2 or 3-dimensional one, where you only care about particular nonlinear degrees of freedom (reaction coordinates, collective variables). This gets rid of the exponential scaling, but also needs a certain knowledge of the best/relevant collective variables, which are typically unknown. So this approach is similar in spirit to density functional theory - you convert your problem into a simple one, for which you don't know the exact method and you have to make an educated guess. In terms of sampling nuclear quantum effects, the problem is particularly badly scaling and common methods to estimate typical correlation functions/constants of interest is to either approximate them as simpler classical problems (semi-classical transition state theory), or to convert them into a sampling problem (ring polymer molecular dynamics). The latter is very similar in spirit to diffusion Monte Carlo for electronic structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Geometry optimisation&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As with all optimisation algorithms, finding a global minimum is an exponentially scaling problem, so to my knowledge, most minimisation algorithms in computational chemistry provide local minima, which scale much better but are also more approximate. In classical computational chemistry you could afford to go one step further and explore much wider conformational space by heating your system up and slowly cooling it down to find some other better minima (simulated annealing). However, as you can see, the result you obtain from this will be highly dependent on chance and convergence will still be exponentially scaling -- there is no way around this.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Sampling&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is one of the biggest unsolved problems in classical computational chemistry. As usual, local sampling is straightforward and typically scales as &lt;span class=&quot;math-container&quot;&gt;$3N\log 3N$&lt;/span&gt; (Markov chain Monte Carlo, leapfrog/any other integrator), whereas enhanced sampling either resorts to using collective variables (metadynamics, umbrella sampling) or providing &quot;locally global&quot; sampling, by smoothening kinetic barriers (replica exchange, sequential Monte Carlo). Now, kinetic barriers slow down local sampling exponentially, but the above methods smoothen these linearly, resulting in cheaper locally enhanced sampling. However, there is no free lunch and global convergence will still be exponential, no matter what you do (e.g. protein folding problem).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Partition function calculation&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The partition function is a &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt;-dimensional integral (I am going to focus on the classical case, as the quantum one is even more difficult). One way is to try to estimate the partition function (nested sampling, sequential monte carlo), where your convergence will typically scale exponentially but still much, much more efficient than regular quadrature (see exact diagonalisation of the Schrödinger equation, similar problem). This is very difficult, so we typically only try to calculate ratios of partition functions, which are much more nicely behaved. In these cases you can convert the integration problem into a sampling problem (free energy perturbation, thermodynamic integration, nonequilibrium free energy perturbation) and all above sampling issues still apply, so you never really escape the curse of dimensionality, but you get some sort of local convergence, which is still better than nothing :)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So in conclusion, there is no free lunch in computational chemistry and there are various classes of approximations suitable for different problems and in general, the better scaling your problem is, the more approximate and less applicable in general it is. In terms of &quot;best value&quot; nearly exact methods, my vote is on path integral methods (diffusion Monte Carlo, ring polymer molecular dynamics, sequential Monte Carlo), which convert the exponentially scaling problems into polynomially scaling ones (but still with convergence problems) -- although not perfect, at least you won't need all the atoms of the universe to run these &lt;em&gt;and&lt;/em&gt; you won't need to know the answer to get the answer, which is sadly an overwhelming problem in many subfields of computational chemistry.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-05-25T07:33:59.400" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1074" PostTypeId="2" ParentId="1070" CreationDate="2020-05-25T09:49:04.177" Score="12" Body="&lt;p&gt;The curse of dimensionality is indeed a huge problem in quantum chemistry, since the possible ways N electrons can occupy K orbitals is a binning problem whose computational cost grows &lt;strong&gt;factorially&lt;/strong&gt; (almost as fast as x^x!) with the size of the system. Moreover, for accurate results you need K&gt;&gt;N in order to account for the so-called dynamical correlation, highlighting the computational challenge of the problem.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A huge breakthrough to the curse of dimensionality was proposed by Walter Kohn: instead of the exponentially difficult problem of describing the anti-symmetric wave function, &lt;strong&gt;density functional theory&lt;/strong&gt; (DFT) shows that it is enough to describe just the electron density n(&lt;strong&gt;r&lt;/strong&gt;), which is just a scalar function. The only problem is that we don't know the exact exchange-correlation functional, which describes how the movement of the electrons is correlated. Still, DFT has been hugely successful in both chemistry and materials science, since in many cases it yields sufficiently accurate results. You can also make DFT linear scaling, if you are smart about the algorithm; however, as far as I am aware, many people are still using the polynomially scaling O(N^3) algorithms since for many systems the lower-order terms are still dominating the cost...&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The main problem with DFT is that you don't know the accuracy &lt;em&gt;a priori&lt;/em&gt;, and DFT doesn't allow a systematic approach to the exact solution. Wave function based methods to the rescue! It turns out that by being smart, in many cases you can avoid the exponential scaling of exact wave function theory. The exact solution is given by diagonalizing the Hamiltonian in the basis of the possible electronic configurations (given by distributing the N electrons into K orbitals, or the K choose N problem); the size of this Hamiltonian is then (K choose N) x (K choose N) although it is extremely sparse. This is known in chemistry as the &lt;em&gt;configuration interaction problem&lt;/em&gt;, and in physics as &lt;em&gt;exact diagonalization&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The problem is extremely hard even for K=N. &#xA;For example, the 16 electrons in 16 orbitals problem, or (16e,16o), if you are looking at the singlet state you have 8 spin-up and 8 spin-down electrons, yielding (16 choose 8)^2 = 165 million possible configurations. If you go to (18e,18o), you get 2.4 billion configurations. (20e,20o) has 34 billion configurations. (22e,22o) has 500 billion configurations. (24e,24o) has 73 trillion configurations. The (18e,18o) is still practical on a desktop computer, but the (24e,24o) is extremely hard even with a huge supercomputer.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;strong&gt;coupled-cluster method&lt;/strong&gt; re-expresses the problem with an exponential ansatz, which yields a much more rapidly converging expansion for the wave function; you go down from exponential scaling to polynomial cost - assuming that you don't need to include all possible &quot;excitations&quot;. The &quot;gold standard&quot; of quantum chemistry, the CCSD(T) method, scales as O(N^7). It's not cheap, but it yields amazingly accurate results for well-behaved molecules. The &lt;strong&gt;density matrix renormalization group&lt;/strong&gt; could also be mentioned here; it is polynomially scaling for &quot;easy&quot; systems, but reduces to exponential scaling for hard ones....&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-05-26T14:40:03.043" LastActivityDate="2020-05-26T14:40:03.043" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1075" PostTypeId="1" AcceptedAnswerId="1076" CreationDate="2020-05-25T13:30:14.360" Score="14" ViewCount="664" Body="&lt;p&gt;So I am aware that many quantum chemical codes are able to add external fields to molecular calculations (for example to calculate polarizabilities). I also know that in some (eg. Orca) you have some control over the applied field, for example the strength. I am also aware that for example in Molpro, you can apply multiple fields at once, and set the direction of these fields with respect to another. However what I really want to do is apply electric field along a specific chemical bond, and I have not been able to do this yet, since most, if not all codes first align the molecule along the axes of inertia and apply the field after that. Is there an ab initio, or maybe a DFT code that is able to add an electric field along a molecule?&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastActivityDate="2020-05-29T21:12:00.747" Title="How to calculate energy of a molecule in an aligned electric field?" Tags="|density-functional-theory|electronic-structure|ab-initio-calculations|response-theory|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1076" PostTypeId="2" ParentId="1075" CreationDate="2020-05-25T14:49:15.497" Score="17" Body="&lt;p&gt;Aligning a molecule to a particular frame of reference (e.g., with the z-axis along a particular bond) is part of &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; for this reason:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In Avogadro 1.x, there's an &lt;a href=&quot;https://avogadro.cc/docs/tools/align-tool/&quot; rel=&quot;noreferrer&quot;&gt;align tool&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You click one atom that will be set to the origin&lt;/li&gt;&#xA;&lt;li&gt;You click another atom that will be projected along the x, y, or z-axis&lt;/li&gt;&#xA;&lt;li&gt;You click 'align' and the molecular coordinates will be translated and rotated accordingly.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;You will then need to set the program to avoid changing the molecular frame of reference:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In Gaussian, the keyword is &lt;code&gt;NoSymm&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;In Q-Chem, the keyword is &lt;code&gt;SYM_IGNORE&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-25T14:49:15.497" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1077" PostTypeId="2" ParentId="1056" CreationDate="2020-05-25T15:01:00.457" Score="8" Body="&lt;p&gt;I think this is an ambitious task. I  suggest you to divide the writing DFT program into two subproblems: &lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Writing an integration library for 1e and 2e electronic integrals. &lt;/li&gt;&#xA;&lt;li&gt;Construct a SCF procedure. &lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;The first part of the task is hard you might start from calling existing integration library and write an SCF code on your own. And also you could consider two aspect: how to write an correct code and how to implement it efficiently. Good luck!&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="30" LastEditDate="2020-05-25T23:59:04.737" LastActivityDate="2020-05-25T23:59:04.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1078" PostTypeId="1" AcceptedAnswerId="1080" CreationDate="2020-05-25T17:10:54.950" Score="16" ViewCount="1386" Body="&lt;p&gt;A lot of codes can do Quantum Mechanics/ Molecular Mechanics (QM/MM), and I am not naively asking if there is a program that can do QM/MM.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What I am interested in is a program that is purely QM/MM meaning that it is &lt;strong&gt;&lt;em&gt;designed and optimized&lt;/em&gt;&lt;/strong&gt; specifically for this purpose. QM/MM is not an after-thought addon much like many codes that do DFT just do some ad-hoc alterations to their HF algorithm.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would like to also highlight in the last sentence the words &quot;designed and optimized&quot; to clarify my intent. Gaussian can do QM obviously, and it can also now do MM, but in all honesty, I would not say it is designed for QM/MM, and I don't think you can even say it is an optimized program for QM. After 4-6 cpu's, you gain very little out of Gaussian in terms of parallelism. I would not say Atomic Simulation Environment (ASE) qualifies either, it simply pairs things together.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am looking for the apex predator of QM/MM codes.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-06-04T17:58:58.517" LastActivityDate="2020-09-05T01:51:50.320" Title="Is there any software that is optimized specifically for QM/MM?" Tags="|software|qmmm|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1079" PostTypeId="2" ParentId="178" CreationDate="2020-05-25T18:02:03.610" Score="11" Body="&lt;p&gt;I’ll expand on this later but here is the abbreviated version.&lt;/p&gt;&#xA;&lt;h1&gt;CTF&lt;/h1&gt;&#xA;&lt;p&gt;The CTF code can do very large iterative CCSD and CCSDT using a dense spin-orbital formalism.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;CCSD up to 55 (50) water molecules with cc-pVDZ&lt;/em&gt;&#xA;&lt;a href=&quot;http://solomonik.cs.illinois.edu/talks/molssi-monterey-may-2017.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://solomonik.cs.illinois.edu/talks/molssi-monterey-may-2017.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The 8-water CCSDT problem in Table 3 took 15 minutes on 1024 nodes of BG/Q and 21 minutes on 256 nodes of Edison. The strong scalability achievable for this problem is significantly better on Edison, increasing the number of nodes by four, BG/Q performs such a CCSDT iteration (using 4096 nodes) in 9 minutes while Edison computes it (using 1024 nodes) in 6 minutes.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;“A massively parallel tensor contraction framework for coupled-cluster computations”&#xA;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S074373151400104X&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/abs/pii/S074373151400104X&lt;/a&gt;&#xA;&lt;a href=&quot;https://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-143.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-143.pdf&lt;/a&gt;&#xA;&lt;a href=&quot;https://apps.dtic.mil/dtic/tr/fulltext/u2/a614387.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://apps.dtic.mil/dtic/tr/fulltext/u2/a614387.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;NWChem&lt;/h1&gt;&#xA;&lt;p&gt;If nothing else, this shows how real the N^7 cost of CCSD(T) is. In 2005, ~80 electrons in ~1400 orbitals hit 6 TF/s. In 2019, ~220 electrons in ~1800 orbitals hit 9 PF/s with the same code. This is the same code running at similar efficiency, albeit for an order-of-magnitude less time, more than a decade later. 2.7^3 is not a small number...&lt;/p&gt;&#xA;&lt;p&gt;The largest semidirect CCSD(T) using NWChem is CCSD(T) with 216 electrons / 1,776 basis functions (cc-pVTZ basis set), which achieved more than 9 petaflop/s on NERSC Cori (KNL). This is work led by PNNL to which I made a small software contribution.&lt;/p&gt;&#xA;&lt;p&gt;This was the largest CCSD(T) calculation of its time (2005):&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;All of the calculations were performed with the NWChem suite of&#xA;programs and Ecce (Extensible Computational Chemistry Environment), a&#xA;problem-solving environment. The calculations&#xA;were done on a massively parallel HP Linux cluster with Itanium-2&#xA;processors. The largest calculation performed was the CCSD(T)&#xA;calculation on octane with 1468 basis functions (the aug-cc-pVQZ basis&#xA;set). The perturbative triples (T) for octane took 23 h on 1400&#xA;processors, yielding 75% CPU efficiency and a sustained performance of&#xA;6.3 TFlops. Fourteen iterations were required for convergence of the&#xA;CCSD, which took approximately 43 h on 600 processors.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;J. Phys. Chem. A, 109 (31), 6934 -6938, 2005 - &lt;a href=&quot;https://doi.org/10.1021/jp044564r&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jp044564r&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="70" LastEditorUserId="70" LastEditDate="2024-03-07T18:19:56.570" LastActivityDate="2024-03-07T18:19:56.570" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1080" PostTypeId="2" ParentId="1078" CreationDate="2020-05-25T19:58:25.563" Score="12" Body="&lt;h1&gt;pDynamo&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://sites.google.com/site/pdynamomodeling/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pDynamo&lt;/a&gt; is a program developed by Martin Field, and is a CHARMM/ORCA interface. There is a &lt;a href=&quot;https://sites.google.com/site/pdynamowiki/&quot; rel=&quot;nofollow noreferrer&quot;&gt;wiki&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Here is the first line from the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct800092p&quot; rel=&quot;nofollow noreferrer&quot;&gt;abstract&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The pDynamo program has been developed for the simulation of molecular systems using hybrid quantum chemical (QC) and molecular mechanical (MM) potentials.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There is also a PyMol plugin named &lt;a href=&quot;https://sites.google.com/site/gtkdynamo/home&quot; rel=&quot;nofollow noreferrer&quot;&gt;EasyHybrid&lt;/a&gt;. Though I do not have experience with this program.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;Field, M. J. The pDynamo Program for Molecular Simulations using Hybrid Quantum Chemical and Molecular Mechanical Potentials &lt;em&gt;J. Chem. Theory Comput. Chem.&lt;/em&gt; &lt;strong&gt;2008&lt;/strong&gt;, &lt;em&gt;4&lt;/em&gt;, 1151-1161.&lt;/p&gt;&#xA;&lt;p&gt;Bachega, J. F. R.; Timmers, L. F. S. M.; Assirati, L.; Bachega, L. B.; Field, M. J.; Wymore, T. GTKDynamo: A PyMOL plug‐in for QC/MM hybrid potential simulations. &lt;em&gt;J. Computer. Chem.&lt;/em&gt; &lt;strong&gt;2013&lt;/strong&gt;, &lt;em&gt;34&lt;/em&gt;, 2190-2196.&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-31T23:36:40.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1082" PostTypeId="1" CreationDate="2020-05-26T07:50:31.620" Score="14" ViewCount="103" Body="&lt;p&gt;I am a condensed matter theorist and I mostly use quantum Monte Carlo methods. I use models like the Heisenberg model, an represent an extreme simplification of real materials to just localized spin degrees of freedom (no electrons, orbitals, etc). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;strong&gt;advantage&lt;/strong&gt; of this extreme simplification is it allows much more precise studies of the underlying physics. The &lt;strong&gt;disadvantage&lt;/strong&gt; is that it can be difficult to make direct connections to experiments. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I know very little about how &lt;em&gt;ab initio&lt;/em&gt; methods work and even less about how they treat magnetism. I would like to have a better sense of the capabilities of these methods. &lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is it possible to model strong magnetic correlations or magnetic phase transitions? &lt;/li&gt;&#xA;&lt;li&gt;Can &lt;em&gt;ab initio&lt;/em&gt; methods be used to calculate exchange parameters (like the Heisenberg &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;)? &lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-27T10:46:19.383" LastActivityDate="2020-05-27T17:35:41.793" Title="How accurately are magnetic effects treated in *ab initio* methods?" Tags="|ab-initio-calculations|magnetism|quantum-monte-carlo|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1083" PostTypeId="1" CreationDate="2020-05-26T08:50:47.287" Score="18" ViewCount="900" Body="&lt;p&gt;I am trying to simulate the Zinc oxide bulk structure (periodic) at constant pressure(0.0 ~ 20.0 GPa) to observe phase transition with LAMMPS.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, I approached a problem that the &lt;strong&gt;&lt;em&gt;fluctuating pressure&lt;/em&gt;&lt;/strong&gt; in each step of optimisation and importantly the final step of the optimisation &lt;strong&gt;&lt;em&gt;does not have the value of pressure that I set&lt;/em&gt;&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;*5th-edit: the problem is solved *&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;The last step of the pressure is not the exact the pressure that I set for which presumably a form of showing residual force of minimisation. Basically, it went down to the basin but not exactly the lowest point of the basin with a certain tolerance.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Primarily the calculation went wrong because I have used wrongly formatted structure data in the read_data command. The wrong data file was produced by three different software... which was very unlucky...&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;I sincerely apologise for the question as I made many people confused.&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is my input:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;units       metal&#xA;atom_style  charge&#xA;dimension   3&#xA;boundary    p p p&#xA;&#xA;#box tilt large                          # allow lammps to have large tilt facotr (xy yz xz)&#xA;read_data       data.3_iso0.0&#xA;#replicate       3 3 3&#xA;&#xA;pair_style  comb3 polar_off&#xA;pair_coeff  * * ./lammps_ip Zn O&#xA;&#xA;neighbor        2.0 bin&#xA;neigh_modify every 1 delay 0 check yes&#xA;&#xA;set type 1    charge  2.0  # Zn&#xA;set type 2    charge -2.0  # O&#xA;&#xA;##############################################################&#xA;#                   type of output data                      #&#xA;##############################################################&#xA;&#xA;fix             1 all qeq/comb 2 0.00003 file fq.out&#xA;fix             2 all box/relax iso 0.0                 # Pressure = unit [bars], 1 GPa = 10,000 bars, Constant pressure&#xA;&#xA;&#xA;thermo          1&#xA;thermo_style    custom step press temp enthalpy etotal pe ke evdwl ecoul cella cellb cellc cellalpha cellbeta cellgamma&#xA;&#xA;#min_style cg&#xA;minimize 0 0.0 10000 10000&#xA;min_modify line quadratic&#xA;&#xA;write_data data.*        #produce file for &quot;read_data&quot; command&#xA;print &quot; All done &quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;The corresponding output data is:&#xA;&lt;code&gt;Step    Press       c_1          v_press      Temp    v_etot     v_relax     TotEng     PotEng     KinEng&lt;/code&gt;&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;    1157   -186.71231   -186.71231   -186.71231            0  -2.9709191            0   -2.9709191   -2.9709191            0&#xA;    1158    -128.7401    -128.7401    -128.7401            0   -2.9709192            0   -2.9709192   -2.9709192            0&#xA;    1159   -124.22057   -124.22057   -124.22057            0   -2.9709192            0   -2.9709192   -2.9709192            0&#xA; Loop time of 464.543 on 1 procs for 1159 steps with 216 atoms&#xA;&#xA; 99.9% CPU use with 1 MPI tasks x 1 OpenMP threads&#xA;&#xA; Minimization stats:&#xA;   Stopping criterion = linesearch alpha is zero&#xA;   Energy initial, next-to-last, final =&#xA;         -2.25448773082     -2.97091924357     -2.97091924466&#xA;   Force two-norm initial, final = 351.736 2.00988&#xA;   Force max component initial, final = 342.312 0.805865&#xA;   Final line search alpha, max atom move = 4.67711e-07 3.76912e-07&#xA;   Iterations, force evaluations = 1159 1175&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="748" LastEditorUserId="748" LastEditDate="2020-06-12T14:48:01.173" LastActivityDate="2020-06-12T14:48:01.173" Title="How to optimize zinc oxide bulk structure at certain pressure with LAMMPS" Tags="|molecular-modeling|molecular-dynamics|interatomic-potentials|lammps|" AnswerCount="1" CommentCount="17" ContentLicense="CC BY-SA 4.0" />
  <row Id="1084" PostTypeId="1" AcceptedAnswerId="1085" CreationDate="2020-05-26T09:53:27.590" Score="8" ViewCount="405" Body="&lt;p&gt;It is possible to use different types of thermostats in CP2K by specifying them in the corresponding section of the input as mentioned &lt;a href=&quot;https://manual.cp2k.org/cp2k-7_1-branch/CP2K_INPUT/MOTION/MD/THERMOSTAT.html#TYPE&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. But there is no mention of specifying the barostat type in the &lt;a href=&quot;https://manual.cp2k.org/cp2k-7_1-branch/CP2K_INPUT/MOTION/MD/BAROSTAT.html&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt;. And I couldn't find any mention of the type of barostat being used in CP2K for NPT simulations. So is it possible to use the Parrinello-Rahman barostat for NPT simulations in CP2K?&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2020-05-26T10:42:29.700" Title="Is it possible to use the Parrinello-Rahman barostat for NPT simulations in CP2K?" Tags="|molecular-dynamics|cp2k|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1085" PostTypeId="2" ParentId="1084" CreationDate="2020-05-26T10:22:23.323" Score="10" Body="&lt;p&gt;The barostat used by CP2K is the one developped by Glenn J. Martyna et al. &lt;a href=&quot;https://doi.org/10.1063/1.467468&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 101, 4177 (1994)&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Parrinello-Rahman barostat is not implemented in CP2K.&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="85" LastEditDate="2020-05-26T10:42:29.700" LastActivityDate="2020-05-26T10:42:29.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1086" PostTypeId="1" CreationDate="2020-05-26T13:49:37.343" Score="14" ViewCount="5422" Body="&lt;p&gt;A &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;noreferrer&quot;&gt;Brillouin zone&lt;/a&gt; is defined as a Wigner~Secitz primitive cell in the reciprocal lattice &lt;sup&gt;[1,2]&lt;/sup&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The construction of the first Brillouin zone for two different 2D lattices are shown below:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IGyQC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IGyQC.png&quot; alt=&quot;First Brillouin zone for a 2D lattice&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The construction procedure for 3D lattices is basically the same as for 2D lattices. In the image below, the first Brillouin zone of FCC lattice, a truncated octahedron, showing symmetry labels for high symmetry lines and points are shown:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7hLW7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7hLW7.png&quot; alt=&quot;First Brillouin zone of FCC lattice&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is: how the labels of the high symmetry points are defined and associated with the vertices, edges, faces and lines of the surface?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1] Ashcroft, Neil W. &amp;amp; Mermin, N. David, Solid State Physics&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2] Kittel, Charles, Introduction to Solid State Physics&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-05-27T11:16:34.407" LastActivityDate="2023-10-24T04:42:51.450" Title="Labeling of high symmetry points in Brillouin zone" Tags="|crystallography|brillouin-zone|solid-state-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1087" PostTypeId="1" CreationDate="2020-05-26T14:15:26.080" Score="8" ViewCount="1368" Body="&lt;p&gt;There are several &lt;a href=&quot;http://lampx.tugraz.at/~hadley/ss2/fermisurface/2d_fermisurface/2dBz.php&quot; rel=&quot;noreferrer&quot;&gt;pages&lt;/a&gt; where you can find scripts/simulations to generate the first Brillouin zone for square and hexagonal 2D lattices.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I wonder if there is a tool to generate the Brillouin for other 2D lattices like the tiles presented &lt;a href=&quot;https://materials.stackexchange.com/q/461&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;http://rcsr.anu.edu.au/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;PS: I am aware that not all the tiles can be used to represent a 2D lattice as they don't fill the space (area).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-13T01:33:04.393" LastActivityDate="2020-06-13T05:17:00.030" Title="2D Brillouin zone generator" Tags="|software|condensed-matter|brillouin-zone|2d-lattice|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1088" PostTypeId="2" ParentId="1046" CreationDate="2020-05-26T14:16:14.767" Score="8" Body="&lt;p&gt;I think to answer the question, one needs to ask another, what part of DFT?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The world of research around quantum chemistry (DFT) but also say coupled cluster simulations or Møller Plesset perturbations can be broken into four main groups:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;method developers&lt;/li&gt;&#xA;&lt;li&gt;basis set developers&lt;/li&gt;&#xA;&lt;li&gt;code developers&lt;/li&gt;&#xA;&lt;li&gt;users&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;To develop methods or basis sets, you should have a deep understanding of the underlying mathematics. To use it you can be &quot;just a user&quot; depending on what you wish to achieve.&#xA;If you develop codes, understanding the mathematics surely helps, but you could equally take published materials as given. Typically there are overlaps - and people who are capable of developing methods and basis sets have a deeper understanding that allows them to be &quot;better&quot; users.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Now I am going to assume you mainly want to use DFT:&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I studied maths before I ended up working with computational chemistry (and since have been doing &quot;other&quot; things).&#xA;At the time, &quot;we&quot; had Gaussian at the university. While it has its quirks/troubles it is widely known. And for all the faults present in Gaussian (e.g. lack of stability), the book&#xA;&quot;&lt;strong&gt;Exploring Chemistry with Electronic Structure Methods, James B. Foresman, AEleen Frisch, Gaussian, Inc Gaussian, Inc., 1996&lt;/strong&gt;&quot; is an excellent basic introduction to the subject. (This is the 2nd edition and many computer related observations are outdated. However there is a newer revision.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Having said that, I would highly recommend the use of ORCA for quantum chemistry calculations. Besides being more stable, the output is significantly more user friendly. (And I moved to ORCA in subsequent work, some of which would not have been possible without ORCA.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A more general and in depth book on the subject would be:&#xA;&quot;&lt;strong&gt;Essentials of Computational Chemistry: Theories and Models, Christopher J. Cramer, Wiley, 2004&lt;/strong&gt;&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A colleague's suggestion at some point:&#xA;&quot;&lt;strong&gt;Introduction to Computational Chemistry, Introduction to Computational Chemistry, Frank Jensen, John Wiley &amp;amp; Sons, 2013&lt;/strong&gt;&quot;&#xA;This book deals less with the &quot;hands on&quot; of using computational chemistry methods, but delves into the depths of the key underlying theory. If you intend to understand the underlying mathematics better, this would be surely an interesting book to read.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;And finally, my favourite Quantum Chemistry Software comes with extensive documentation and tutorials, it is called ORCA.&#xA;If you are interested in the details of the implementation, the ORCA manual is ever expanding. &#xA;&quot;&lt;strong&gt;ORCA - An abinitio, DFT and semiempirical SCF-MO package, Frank Neese, Frank Wennmohs, and many others&lt;/strong&gt;&quot;&#xA;It is available from the ORCA forum, though google will turn up an older version:&#xA;&lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/portal&quot; rel=&quot;noreferrer&quot;&gt;https://orcaforum.kofo.mpg.de/app.php/portal&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;And just for using ORCA, the ORCA Input Library, which is an independent site by a researcher who worked with the developers, is highly recommended too:&#xA;&lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/&quot; rel=&quot;noreferrer&quot;&gt;https://sites.google.com/site/orcainputlibrary/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="540" LastEditorUserId="540" LastEditDate="2020-05-26T16:48:47.057" LastActivityDate="2020-05-26T16:48:47.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1089" PostTypeId="2" ParentId="178" CreationDate="2020-05-26T14:52:05.317" Score="10" Body="&lt;p&gt;Localized natural orbitals methods allow tackling huge system sizes; some links were already given above. Of course, the accuracy remains sometimes a question in such methods: the methods rely on thresholds, which may not have always been converged! So you should keep in mind that these are not black-box tools like conventional coupled-cluster theory.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The biggest calculation I remember seeing is the monstrous 1023-atom, 44712-atomic-orbital LNO-CCSD(T)/def2-QZVP calculation on a lipid transfer protein by Nagy and Kállay in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00511&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 2019, 15, 10, 5275–5298&lt;/a&gt; which they claim took just 18 days on 6 cores; this system is many times larger than the examples given so far.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-26T14:52:05.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1090" PostTypeId="2" ParentId="1063" CreationDate="2020-05-26T15:02:17.810" Score="11" Body="&lt;p&gt;If the question is how the file format and storage of the coordinates in that file format affects the performance – it doesn't.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, the internal representation of atoms in a program can affect the performance, so the author of the program probably designed it carefully.&#xA;Calculation of distances between atoms or angles is better done in Cartesian (orthogonal) coordinates. Finding symmetry mates of atoms – in fractional.&#xA;Classical molecular dynamics program would probably store Cartesian coordinates. I don't know about DFT.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If the program uses internally Cartesian coordinates and the input file has fractional ones, it must convert them. But the cost of such conversion is negligible. It's much faster than reading and parsing the input CIF file.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To elaborate more, conversion to fractional coordinates (called sometimes &lt;em&gt;fractionalization&lt;/em&gt;) can be implemented as multiplication by 3x3 matrix (called &lt;em&gt;fractionalization matrix&lt;/em&gt;). Conversion in the other direction – as multiplication by &lt;em&gt;orthogonalization matrix&lt;/em&gt; (inverse of the fractionalization matrix).&#xA;The matrices are calculated from the unit cell parameters.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2020-05-26T15:02:17.810" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1091" PostTypeId="2" ParentId="1075" CreationDate="2020-05-26T15:08:05.673" Score="3" Body="&lt;p&gt;I would agree that the best approach is to align your molecule in a way where your desired field is along one of the Cartesian axes. However, you can specify the direction/magnitude of the applied field using Gaussian. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;While the typical way of specifying a field &lt;code&gt;Field=M+/-N&lt;/code&gt; only allows you to specify a multipole &lt;code&gt;M&lt;/code&gt; and a magnitude &lt;code&gt;N*.0001&lt;/code&gt; a.u., you can give specify a particular direction of the field, along with higher multipole fields, at the end of the input file using &lt;code&gt;iop(3/14=-6)&lt;/code&gt;. Keep in mind that the magnitude of the components you enter is not scaled,  unlike the &lt;code&gt;Field&lt;/code&gt; keyword.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Example input file, specifying a dipole field along (1,0,1):&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;#p hf/sto-3g iop(3/14=-6) nosymm&#xA;&#xA;Dipole field in x and z directions&#xA;&#xA;0 1&#xA;N 0.0 0.0 -0.549&#xA;N 0.0 0.0 0.549&#xA;&#xA;!Specify coordinates of field&#xA;!Can give up to 34 values (3 dipole/field, &#xA;!6 quadrupole/field gradient, 10 octupole/field 2nd deriv, &#xA;!15 hexapole/field 3rd deriv) &#xA;1.0 0.0 1.0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-05-29T21:12:00.747" LastActivityDate="2020-05-29T21:12:00.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1092" PostTypeId="2" ParentId="387" CreationDate="2020-05-26T16:21:56.803" Score="17" Body="&lt;p&gt;This is an important question that isn't answered yet, and I've been doing some work with charged defects recently so I'll attempt an answer--though I readily admit I am not really an expert (&lt;em&gt;i.e.&lt;/em&gt; I don't work on developing these correction approaches). I'm not familiar with many approaches apart from DFT, so I'll limit my answer to that area.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In DFT at least, a charged cell is compensated by a uniform jellium background of equal and opposite charge, to keep the energy finite. The problem is that the long-range potential of the charged defect in this medium decays very slowly, as you mentioned. It depends on the defect and the dielectric properties of the material under study, but can be significant (on the order of eV). So something needs to be done to correct for this spurious interaction. There are also several potential-alignment terms that come into play when calculating energy differences between different systems. A good place to start reading is references &lt;a href=&quot;https://link.aps.org/doi/10.1103/RevModPhys.86.253&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; and &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.86.045112&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt; below. I'll keep this answer less theoretical since the references do a much better job of explaining. I'll summarize the concepts quickly and mention some practical issues.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One approach you may have heard of is the Makov-Payne correction, which was derived based on a Madelung-type sum in a cubic cell. I haven't used this correction but I understand it can be quite inaccurate in realistic systems, typically overcorrecting &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0921452611007812&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;. In the situations I've encountered it, it's also been limited to systems with cubic symmetry, though I'm not sure if this is always the case.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Freysoldt's scheme is a common approach. The basic idea is that you use a simple model to describe the defect's charge, such that you can calculate it's isolated energy interacting with the jellium background, as well as the energy of a periodic system that is interacting with it's images, using Poisson's equation. If you align the potential of your model with the DFT calculations, you can use the difference between the isolated and periodic energies of your model as a correction term. There is also related correction by Kumegai and Oba &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.89.195205&quot; rel=&quot;noreferrer&quot;&gt;4&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The third correction I've seen is from Lany and Zunger, which goes beyond the Makov-Payne correction by using DFT-calculated difference in charge between a charged and neutral defect to calculate a higher-order term in the correction. I have the least amount of experience with this method.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;When it comes down to implementing these schemes I have the most experience with the Freysoldt method. I have used &lt;a href=&quot;https://sxrepo.mpie.de/&quot; rel=&quot;noreferrer&quot;&gt;sxdefectalign&lt;/a&gt; and &lt;a href=&quot;http://www.physics.iisc.ernet.in/~mjain/pages/software.html&quot; rel=&quot;noreferrer&quot;&gt;CoFFEE&lt;/a&gt;. One thing I learned early on was that all the nice plots in the papers and code examples are typically &lt;em&gt;unrelaxed&lt;/em&gt; calculations where the atomic positions are the same in all the calculations. This makes differences in potentials smooth and easy to analyze. When you want an accurate formation energy you need to allow the system to relax; the differences in the atomic positions of the different calculations (pristine vs. defect) cause significant variation in the potential. You typically need to do some smoothing or averaging, which can be challenging to get right.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I've also encountered challenges when using these codes with cells that have non-orthogonal lattice vectors (e.g. monoclinic). Planar averaging and model calculations can be especially difficult. It can be hard to determine if you're doing something wrong or if there is a bug in the code somewhere. You need to do a lot of experimenting.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are other codes that automate the process more. You mentioned &lt;a href=&quot;https://bitbucket.org/mbkumar/pycdt/src/master/&quot; rel=&quot;noreferrer&quot;&gt;PyCDT&lt;/a&gt;; &lt;a href=&quot;https://github.com/PyDEF2/PyDEF-2.0&quot; rel=&quot;noreferrer&quot;&gt;PyDEF&lt;/a&gt; and &lt;a href=&quot;https://github.com/pylada/pylada-defects&quot; rel=&quot;noreferrer&quot;&gt;Pylada&lt;/a&gt; are also interesting, but these three only really support VASP at the moment. I know PyCDT has a wrapper for sxdefectalign, but I thought they had a separate module for performing the calculation without sxdefectalign. &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt; can perform various corrections taken from the PyCDT code, but I haven't had much time to spend with it yet. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm always interested to hear if there are other approaches and codes out there.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://link.aps.org/doi/10.1103/RevModPhys.86.253&quot; rel=&quot;noreferrer&quot;&gt;C. Freysoldt &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;Rev. Mod. Phys.&lt;/em&gt; &lt;strong&gt;86&lt;/strong&gt;, 253&#xA;(2014)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.86.045112&quot; rel=&quot;noreferrer&quot;&gt;H.-P. Komsa, T. T. Rantala, and A. Pasquarello, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;86&lt;/strong&gt;,&#xA;045112 (2012)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0921452611007812&quot; rel=&quot;noreferrer&quot;&gt;H.-P. Komsa, T. Rantala, and A. Pasquarello, &lt;em&gt;Physica B: Condensed Matter&lt;/em&gt; &lt;strong&gt;407&lt;/strong&gt;, 3063 (2012)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.89.195205&quot; rel=&quot;noreferrer&quot;&gt;Y. Kumagai and F. Oba, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;89&lt;/strong&gt;, 195205 (2014)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-27T21:34:14.900" LastActivityDate="2020-05-27T21:34:14.900" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1093" PostTypeId="2" ParentId="1086" CreationDate="2020-05-26T17:48:19.033" Score="12" Body="&lt;p&gt;I think the naming conventions are standardized and people computing band structures employ them directly. I will break down the high-symmetry points for a 2-D brillouin zone and post very good references for you to explore 3-D BZs. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Take a rectangular Brillouin zone as the one depicted below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Iatur.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Iatur.png&quot; alt=&quot;K-points path in rectangular Brillouin zone&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The center of the brillouin zone is unequivocally marked as &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;. For the other high-symmetry points, it's easy to reconcile in this case - 'X' and 'Y' just represent points on the rectangle along &lt;span class=&quot;math-container&quot;&gt;$ k_x $&lt;/span&gt; an &lt;span class=&quot;math-container&quot;&gt;$ k_y $&lt;/span&gt;. 'S' is the other high-symmetry point on the corner of the rectangle, an intermediate point in the &lt;span class=&quot;math-container&quot;&gt;$ \Gamma $&lt;/span&gt; - X - S - Y - &lt;span class=&quot;math-container&quot;&gt;$ \Gamma $&lt;/span&gt; path.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For a very comprehensive treatment of 3-D brillouin zones, refer to &lt;a href=&quot;https://arxiv.org/pdf/1004.2974.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. In 3-D brillouin zones, you will encounter more high-symmetry points - &lt;span class=&quot;math-container&quot;&gt;$ \Gamma $&lt;/span&gt; will still refer to the center of the BZ and points like 'M' refer to mid-points i.e. &lt;span class=&quot;math-container&quot;&gt;$ k/2 $&lt;/span&gt; .&#xA;If you just want to find the high-symmetry points, I've found &lt;a href=&quot;https://msu.edu/~dodat/files/Brillouin_zone.pdf&quot; rel=&quot;noreferrer&quot;&gt;this table very helpful&lt;/a&gt;. It directly gives you the high-symmetry points and their coordinates.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://i.stack.imgur.com/Iatur.png&quot; rel=&quot;noreferrer&quot;&gt;https://i.stack.imgur.com/Iatur.png&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/pdf/1004.2974.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/pdf/1004.2974.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://msu.edu/~dodat/files/Brillouin_zone.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://msu.edu/~dodat/files/Brillouin_zone.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-05-26T17:48:19.033" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1094" PostTypeId="1" CreationDate="2020-05-26T17:58:06.967" Score="12" ViewCount="157" Body="&lt;p&gt;When performing electronic structure calculations on a molecule, one can surround it with point charges to mimic a solvent environment, and lend polarization effects. There is a bit of a caveat unfortunately.&lt;/p&gt;&#xA;&lt;p&gt;If diffuse functions are used, there is a risk that the point charges surrounding the &amp;quot;cavity&amp;quot; that the molecule of interest is in, will lead to distortion of the electron density i.e., the electron density will(may) migrate towards the point charges in an unphysical manner.&lt;/p&gt;&#xA;&lt;p&gt;This is unfortunate, but, not too big of a deal for neutral and cation species which are not reliant on diffuse functions (just don't use them). However, anions really should be done with diffuse functions to account for the loose electron. This applies to anything where electron density will not be as tight around nuclei, i.e., excited states.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a ready solution to this problem of charge migration?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This also applies when using implicit solvents as well, the tessellated surface of the cavity can lead to unphysical migration of the solute's electron density towards the cavity surface.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-07-27T12:13:51.967" LastActivityDate="2021-07-27T16:52:52.120" Title="Avoiding charge-migration in electronic structure calculations with solvent-like environments" Tags="|electronic-structure|basis-sets|implicit-solvent|charge-polarization-model|explicit-solvent|" AnswerCount="2" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="1095" PostTypeId="5" CreationDate="2020-05-27T02:36:02.293" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-27T02:36:02.293" LastActivityDate="2020-05-27T02:36:02.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1096" PostTypeId="4" CreationDate="2020-05-27T02:36:02.293" Score="0" Body="For questions about (or related to) the software LAMMPS." OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2020-06-03T20:08:20.867" LastActivityDate="2020-06-03T20:08:20.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1097" PostTypeId="1" CreationDate="2020-05-27T04:14:46.420" Score="9" ViewCount="122" Body="&lt;p&gt;Big O notation is commonly seen in the papers on novel computational methods. However, only a few of them include rigorous analysis of the algorithm. Is there any literature that summarizes current prevalent computational chemistry algorithm of density functional theory, coupled cluster, density matrix renormalization group and quantum monte carlo and gives analysis of their big O notations? &lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="141" LastEditDate="2020-05-27T05:56:36.367" LastActivityDate="2020-05-27T05:56:36.367" Title="Is there any literature that systematically analyzes current quantum chemistry algorithms using Big O notation for time and memory cost?" Tags="|reference-request|molecular-modeling|computational-chemistry|algorithms|" AnswerCount="0" CommentCount="8" ClosedDate="2020-06-02T03:11:12.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="1098" PostTypeId="1" CreationDate="2020-05-27T06:10:17.393" Score="15" ViewCount="117" Body="&lt;p&gt;It is often assumed in cheminformatics that molecules with similar physical structure tend to have similar chemical properties &lt;a href=&quot;https://doi.org/10.1145/2366316.2366334&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Based on this, our group has used discrete graphs as a model for the physical structure of molecules &lt;a href=&quot;https://arxiv.org/abs/2004.08381&quot; rel=&quot;nofollow noreferrer&quot;&gt;[2]&lt;/a&gt;&lt;a href=&quot;https://arxiv.org/abs/2004.06367&quot; rel=&quot;nofollow noreferrer&quot;&gt;[3]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What other types of molecular models are out there?  My interest is mainly simple, discrete models, but I'm hoping to find something that offers more insight than the nodes and edges of discrete graph models.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Joerg Kurt Wegner, Aaron Sterling, Rajarshi Guha, Andreas Bender, Jean-Loup Faulon, Janna Hastings, Noel O’Boyle, John Overington, Herman Van Vlijmen, and Egon Willighagen. 2012. Cheminformatics. Commun. ACM 55, 11 (November 2012), 65–75. DOI: 10.1145/2366316.2366334&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Kyousuke Yamashita, Ryuji Masui, Xiang Zhou, Chenxi Wang, Aleksandar Shurbevski, Hiroshi Nagamochi, &amp;amp; Tatsuya Akutsu. (2020). Enumerating Chemical Graphs with Two Disjoint Cycles Satisfying Given Path Frequency Specifications. arXiv: 2004.08381 [cs.DS]&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Yuui Tamura, Yuhei Nishiyama, Chenxi Wang, Yanming Sun, Aleksandar Shurbevski, Hiroshi Nagamochi, &amp;amp; Tatsuya Akutsu. (2020). Enumerating Chemical Graphs with Mono-block 2-Augmented Tree Structure from Given Upper and Lower Bounds on Path Frequencies. arXiv: 2004.06367 [cs.DS]&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="84" LastEditorUserId="7" LastEditDate="2020-06-29T19:15:06.907" LastActivityDate="2020-07-09T15:32:54.910" Title="Types of Discrete molecular models" Tags="|reference-request|molecular-modeling|mathematical-modeling|chemoinformatics|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1099" PostTypeId="2" ParentId="859" CreationDate="2020-05-27T08:14:05.917" Score="8" Body="&lt;p&gt;@stafusa's answer is great, but there is a specific phenomenon you are encountering here called &lt;strong&gt;critical slowing down&lt;/strong&gt;, which is especially bad for the single-spin-flip Metropolis Algorithm. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Near the critical point, the typical cluster size diverges. For the single-spin-flip algorithm, it's really hard to flip these huge clusters, so the autocorrelation time can increase dramatically. Cluster algorithms sidestep this issue by flipping big groups of spins at once. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What you are seeing for the local updates is an exponential decay with a &lt;em&gt;really&lt;/em&gt; long time constant, which causes it to look linear. To see an exponential decay in the autocorrelations for the local updates, try moving away from &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;To learn more you can take a look at &quot;Overcoming critical slowing down&quot;, Gould and Tobochnik, &lt;a href=&quot;https://doi.org/10.1063/1.4822858&quot; rel=&quot;noreferrer&quot;&gt;Computers in Physics &lt;strong&gt;3&lt;/strong&gt;, 82 (1989)&lt;/a&gt;. Or you can look at p. 79 of &quot;Monte Carlo Methods in Statistical Physics&quot; by &lt;a href=&quot;https://books.google.com.tw/books/about/Monte_Carlo_Methods_in_Statistical_Physi.html?id=J5aLdDN4uFwC&amp;amp;redir_esc=y&quot; rel=&quot;noreferrer&quot;&gt;Newman and Barkema.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-05-27T08:14:05.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1100" PostTypeId="2" ParentId="528" CreationDate="2020-05-27T10:43:39.777" Score="5" Body="&lt;p&gt;Since no one has responded with expertise, I'll attempt a speculative answer here. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;To my mind, the simplest model of the atoms on the surface of the walls would be an ensemble of independent classical 3D harmonic oscillators at some temperatures &lt;span class=&quot;math-container&quot;&gt;$T_{\rm wall}$&lt;/span&gt;. That would be pretty easy to describe from a numerical standpoint, since their velocity could be described by the Boltzmann distribution. Then you could treat the collisions with the wall with classical energy/momentum conservation. This would still allow transfer of momentum and energy between the walls and gas. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Caveat:&lt;/strong&gt; Treating the wall as independent harmonic oscillators like this will mean that your simulation does &lt;strong&gt;not&lt;/strong&gt; conserve energy, since the walls will acts as a thermal bath. In practice, this is probably a good thing since the temperature of the walls will be set by the room temperature or any heating you do. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-05-28T02:22:00.507" LastActivityDate="2020-05-28T02:22:00.507" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1101" PostTypeId="2" ParentId="129" CreationDate="2020-05-27T13:57:52.793" Score="9" Body="&lt;p&gt;Your definition is alright, and a citable reference is Landau and Binder's &lt;em&gt;A Guide to Monte Carlo Simulations in Statistical Physics&lt;/em&gt; which &lt;a href=&quot;https://books.google.de/books?id=CVreBAAAQBAJ&amp;amp;lpg=PA27&amp;amp;ots=RxBqYbF4Vi&amp;amp;dq=Ergodicity%20in%20physics%20and%20Monte%20Carlo%20simulations&amp;amp;pg=PA27#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;says&lt;/a&gt; (Sec. 2.1.3):&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;The principle of ergodicity states that all possible configurations of the system should be attainable.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;The usual definition of ergodicity, both in mathematics and physics, is that the &lt;em&gt;ensemble&lt;/em&gt; and &lt;em&gt;time&lt;/em&gt; averages should be the same in an ergodic system -- and in Monte Carlo simulations it's not different, &lt;em&gt;except&lt;/em&gt; that one is often concerned with ergodicity which can be observed in practice. This is made very clear in another book by Binder, &quot;Monte Carlo Simulation in Statistical Physics: An Introduction&quot;, which &lt;a href=&quot;https://books.google.de/books?id=6J0R0s-uZbkC&amp;amp;lpg=PA30&amp;amp;ots=X5cO5kkf6O&amp;amp;dq=Ergodicity%20in%20physics%20and%20Monte%20Carlo%20simulations&amp;amp;pg=PA30#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;explains&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;In practice one may find an apparent &quot;breaking of ergodicity&quot; even for systems which are ergodic, if the &quot;time&quot; over which the averaging is extended is not long enough, i.e., less than the so-called &quot;ergodic time&quot; &lt;span class=&quot;math-container&quot;&gt;$\tau_e$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Which then continues:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;There is no general rule about whether this happens or not, it really depends on the details of the algorithm.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;It's also important to remember that in practice we perform simultaneously an ensemble average over the time average: where the ensemble average isn't done directly over the phase space, but comes from considering different realizations of the system (say, in the disordered case), different runs (with distinct random seeds), or different initial conditions. This is also detailed in the references above.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another possibly interesting reference is the &lt;a href=&quot;https://doi.org/10.1103/PhysRevE.62.7445&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; &quot;Approach to ergodicity in Monte Carlo simulations&quot; (&lt;a href=&quot;https://journals.aps.org/pre/pdf/10.1103/PhysRevE.62.7445?casa_token=fl_MDLBKKnQAAAAA%3AG1cQjNyelWMSJmHMyCS_tsHe2unXMn0tkzCBvDwRW4V49scoUGPH17t5cZgRv6Xz2w5q_BY6Eq0L&quot; rel=&quot;noreferrer&quot;&gt;e-print&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="625" LastActivityDate="2020-05-27T13:57:52.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1102" PostTypeId="2" ParentId="1082" CreationDate="2020-05-27T17:35:41.793" Score="9" Body="&lt;p&gt;It is an example where representative of different fields would give you very different answers. I do not want to pretend my answer would be by anyway complete.&#xA;Short answer: yes. And the devil, as always, is in the details.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Since we can solve Schrodinger and Dirac equations arbitrary accuracy (see eg Nakatsuji's work, &lt;a href=&quot;http://qcri.or.jp/~nakatsuji/nakatsuji.htm&quot; rel=&quot;noreferrer&quot;&gt;http://qcri.or.jp/~nakatsuji/nakatsuji.htm&lt;/a&gt;), technically speaking we can solve any quantum mechanical problem if we have enough computational power, so it is a YES. The question is always what accuracy and what cost...&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;OK, I guess you meant for systems comparable to the size of the model you run. Then most probably NO. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You are asking about strong magnetic correlation and magnetic phase transitions. This is far from my field, but it sounds more like a statistical mechanical problem, not a quantum mechanical problem. But I leave this to others.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What can we solve? You are asking about e.g J, J is not an observable but a model parameter in your model. What ab initio and DFT methods can calculate (estimate) is the energy of different spin configurations, and then you can fit it with whatever assumption about the spin-Hamiltonian you want. In the molecular field, it is fairly common in the last decade(s?) to estimate magnetic coupling between metal ions e.g. in catalysts or metalloenzyme active centers. Even methods like DFT can be used to calculate J (through broken symmetry approach) leading to surprisingly accurate results for many systems. Packages like Orca even have keywords to create broken symmetry wavefunctions. If you want more accurate methods, you need something that represents better the multireference character of different spin configurations (eg CASSCF, CASPT2, MR-SAC), but the basic idea is the same. The problem with these methods that they generally scale horribly with the size of the spin system.  &lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="91" LastActivityDate="2020-05-27T17:35:41.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1103" PostTypeId="1" AcceptedAnswerId="1111" CreationDate="2020-05-27T17:36:27.597" Score="24" ViewCount="11132" Body="&lt;p&gt;The codes for quantum mechanical calculations make heavy use of linear algebra, and it seems most of them delegate this task to time-tested and highly optimized libraries, instead of trying to deploy their own. There is a plethora of options. For example, when we install Gamess-US in Ubuntu GNU/Linux, several options are listed, both proprietary and free / open source software:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pCx9x.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pCx9x.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the past I used ATLAS, and then MKL, as we are nudged towards it by the (very fast) qualifier given in the install screen. But then I was doing some research on it, and found this information on its &lt;a href=&quot;https://en.wikipedia.org/wiki/Math_Kernel_Library&quot; rel=&quot;noreferrer&quot;&gt;wikipedia page&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Intel MKL and other programs generated by the Intel C++ Compiler improve performance with a technique called function multi-versioning: a function is compiled or written for many of the x86 instruction set extensions, and at run-time a &quot;master function&quot; uses the CPUID instruction to select a version most appropriate for the current CPU. However, as long as the master function detects a non-Intel CPU, it almost always chooses the most basic (and slowest) function to use, regardless of what instruction sets the CPU claims to support. This has netted the system a nickname of &quot;cripple AMD&quot; routine since 2009.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;This got me a bit worried, as I'm trying to do a Gamess-US install in a machine with a &lt;a href=&quot;https://en.wikipedia.org/wiki/Zen_(microarchitecture)&quot; rel=&quot;noreferrer&quot;&gt;Ryzen&lt;/a&gt; processor, and so I'm afraid I will get a crippled install if I use intel MKL. Given the number of remaining choices, without a clear idea of relative performance between them, I got some &lt;a href=&quot;https://en.wikipedia.org/wiki/Analysis_paralysis&quot; rel=&quot;noreferrer&quot;&gt;analysis paralysis&lt;/a&gt;. The obvious alternative would be one of AMD, but in absence of a substantial speed advantage, I could as well use a open source one, as I try to favor free software whenever I can.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If someone more experienced could give some advice on this problem, I would be grateful. How does the several linear algebra libraries compare to each other, on the workloads typical of materials modeling? Is there a big difference from one to other, or they are all optimized to such degree that doesn't matter much which one is used. Is there one with good overall performance over a variety of hardware, not biased against alternative hardware like the MKL seems to be?&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-05-27T17:52:45.680" LastActivityDate="2020-12-02T08:31:38.533" Title="Since MKL is not optimized for AMD hardware, should I use a math library specific to AMD, or would an open-source one be just as good?" Tags="|software|quantum-chemistry|open-source|high-performance-computing|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1104" PostTypeId="1" AcceptedAnswerId="1257" CreationDate="2020-05-27T19:39:12.190" Score="10" ViewCount="252" Body="&lt;p&gt;Time-dependent density functional theory (TD-DFT) is considered to be more efficient (in terms of its accuracy/speed ratio) than alternatives such as the approximate coupled-cluster singles and doubles (CC2), even with resolution of identity which together forms RI-CC2&lt;sup&gt;&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4642227/&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;&lt;/sup&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.researchgate.net/publication/23232429_Theoretical_study_on_oligothiophene_N-succinimidyl_esters_Size_and_push-pull_effects&quot; rel=&quot;nofollow noreferrer&quot;&gt;Piacenza &lt;em&gt;et al.&lt;/em&gt; (2008)&lt;/a&gt;&lt;sup&gt;2&lt;/sup&gt; highlight that one drawback of TD-DFT is that &quot;for larger conjugated systems the &lt;span class=&quot;math-container&quot;&gt;$\sigma\to\pi^\ast$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\pi\to\pi^\ast$&lt;/span&gt; transitions can become significantly wrong when calculated with TD-DFT&quot; and so for such systems RI-CC2 should be used despite its taking slower.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;However, is it always the case that for small(er) systems that RI-CC2 need not be used as TD-DFT can provide sufficient accuracy, and if not what is an example where the former prevails?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; References &lt;/sub&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; [1] Jacquemin, D. &lt;em&gt;et al.&lt;/em&gt; (2015). 0–0 Energies Using Hybrid Schemes: Benchmarks of TD-DFT, CIS(D), ADC(2), CC2, and BSE/GW formalisms for 80 Real-Life Compounds. &lt;em&gt;J Chem Theory Comput.&lt;/em&gt; 11(11):5340–5359.&lt;/sub&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;sub&gt; [2] Piacenza, M., Zambianchi, M., Barbarella, G. &lt;em&gt;et al.&lt;/em&gt; (2008). Theoretical study on oligothiophene N-succinimidyl esters: size and push–pull effects. &lt;em&gt;Physical Chemistry Chemical Physics.&lt;/em&gt; 10(35):5363-5373.&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="35" LastEditDate="2020-06-09T14:47:22.233" LastActivityDate="2020-06-10T22:07:11.253" Title="Is there an example where TD-DFT fails to provide sufficient accuracy for a small system, where RI-CC2 is sufficient?" Tags="|ab-initio-calculations|td-dft|excited-states|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1105" PostTypeId="1" CreationDate="2020-05-27T22:26:52.870" Score="13" ViewCount="367" Body="&lt;p&gt;I realize that the more ordered the supercell is, the lower the number of displacements. Perhaps, we could say the same with respect to symmetry.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there anything that can be done to reduce the number of displacements required to be studied, like maybe some way to circumvent the need to study all possible displacements?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-05-27T22:37:39.860" LastActivityDate="2020-06-09T11:12:59.083" Title="Can we do anything to reduce the number of displacements in a frozen phonon lattice dynamics study?" Tags="|phonons|phonopy|phonon-dispersion|lattice-dynamics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1106" PostTypeId="1" AcceptedAnswerId="1108" CreationDate="2020-05-27T23:59:47.420" Score="11" ViewCount="250" Body="&lt;p&gt;I've been doing some calculations for a water molecule, with a big uncontracted basis set: For oxygen I am using aug-cc-pV9Z supplemented with the &quot;tight&quot; functions from cc-pCV7Z. The s-type exponents are listed below, with all numbers up to 0.04456 constituting the s-type exponents of aug-cc-pV9Z, and the rest of the numbers constituting the &quot;tight&quot; s-type exponents of the CV7Z correction:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;14977011.0 2218105.60 497972.050 136123.290 42655.7170 15004.6890 5776.15000 2375.75410 1017.44250 448.248580 203.162260 94.8087090 45.4553660 22.3219240 11.1990240 5.70236100 2.88556500 1.45704800 0.72489200 0.36172700 0.18245000 0.90164000E-01 0.04456 496.301272333 283.450755017 161.886207025 92.4574853342 52.8049100131 30.1582777362&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;After several hours of calculating integrals, I was told by the program that there were two near-linear-dependencies (determined by noticing that two eigenvalues of the overlap matrix were smaller than the default tolerance). The corresponding eigenvectors were removed automatically by the program, and my Hartree-Fock energy was higher than what it was, for the much smaller: aug-cc-pV9Z basis set (without the extra &quot;tight&quot; functions).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I decided to try to manually remove two basis functions to avoid any issue of near-linear-dependencies. &lt;strong&gt;But which ones should be removed?&lt;/strong&gt; &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I could plot all of the functions and see which ones look the most similar, but it would be tedious, and &lt;strong&gt;I do not know of any measure to determine which pairs of functions are most similar for this purpose, so I would merely be attempting to eye-ball it.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I suppose I could remove all of the exponents except for the ones that I think might lead to linear dependencies (based on the exponents being similar in magnitude), and then calculate the overlap matrix (which would be very fast since I would only have 4 functions in my basis set), and see if the small eigenvalues (near-linear-dependencies) still appear?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The two exponents most similar to each other are unsurprisingly, the two most diffuse functions:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;0.90164000 0.04456 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;but they surely won't lead to any problems, since they exist in the uncontracted aug-cc-pV9Z basis set, which does not lead to any issues.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So next I looked at the exponents that were most similar to each other percentage-wise:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;94.8087090 92.4574853342&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;and it sure turned out that this &lt;em&gt;guess&lt;/em&gt; was correct! The overlap matrix after removing one of them, now only had one eigenvalue that was too small (instead of two!). I then &lt;em&gt;guessed&lt;/em&gt; to remove a function from the following second pair, which was the next closest to each other percentage-wise: &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;45.4553660 52.8049100131&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;and miraculously, the overlap matrix now had no eigenvalues below the tolerance (i.e. no near-linear-dependencies!), and the Hartree-Fock energy was lower than what I obtained with a vanilla uncontracted aug-cc-pV9Z (as expected).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Is it always safe to just look for the N pairs of exponents that are most similar to each other percentage-wise, and remove one from each pair, to cure N overly low eigenvalues?&lt;/strong&gt; If so, why is it that none of the mainstream electronic structure packages have been able to implement an &lt;em&gt;a priori&lt;/em&gt; test to &quot;predict&quot; near-linear-dependencies before spending several hours doing the integrals? I suppose when the geometry gets much more complicated, so will the procedure for predicting near-linear-dependencies in advance, but for diatomics and triatomics like water, is there ever a case in which the guessing procedure I used here fails?  &lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-28T00:33:25.113" LastActivityDate="2020-05-28T07:27:02.540" Title="Predicting linear dependencies in a basis set in advance of calculating any integrals" Tags="|basis-sets|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1107" PostTypeId="2" ParentId="1060" CreationDate="2020-05-28T00:09:58.503" Score="6" Body="&lt;p&gt;I don't think there is a consensus of norm conserving PP being more accurate. There are some references I am aware of which have calculated dielectric tensor using NC-PP, but without justification though:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Yu, E. K.; Stewart, D. A.; Tiwari, S. Ab Initio Study of Polarizability and Induced Charge Densities in Multilayer Graphene Films. Phys. Rev. B - Condens. Matter Mater. Phys. 2008, 77 (19), 1–8.&lt;/li&gt;&#xA;&lt;li&gt;Kumar, P.; Bhadoria, B. S.; Kumar, S.; Bhowmick, S.; Chauhan, Y. S.; Agarwal, A. Thickness and Electric-Field-Dependent Polarizability and Dielectric Constant in Phosphorene. Phys. Rev. B 2016, 93 (19), 1–8.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;But then I have seen often (and performed calculations myself) PAW-based methods in VASP used for calculating the dielectric tensor. Here is a reference for you to dig deeper: &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Laturia, A.; Van de Put, M. L.; Vandenberghe, W. G. Dielectric Properties of Hexagonal Boron Nitride and Transition Metal Dichalcogenides: From Monolayer to Bulk. npj 2D Mater. Appl. 2018, 2 (1), 6.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;One way to validate your method is to compare polarizabilities (related to dielectric constant) with more accurate methods such as polarizability calculations using maximally localized Wannier functions - see below for some insights:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Pan, D.; Govoni, M.; Galli, G. Dielectric Properties of Condensed Systems Composed of Fragments. J. Chem. Phys. 2018, 149 (5), 051101.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-05-28T00:09:58.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1108" PostTypeId="2" ParentId="1106" CreationDate="2020-05-28T07:27:02.540" Score="10" Body="&lt;p&gt;You might be interested to know that I've recently presented a general solution to this problem in &lt;a href=&quot;https://doi.org/10.1063/1.5139948&quot; rel=&quot;noreferrer&quot;&gt;Curing basis set overcompleteness with pivoted Cholesky decompositions, J. Chem. Phys. 151, 241102 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The method is amazingly versatile, it also works if you have nuclei that are &quot;unphysically&quot; close to each other as I showed in &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.101.032504&quot; rel=&quot;noreferrer&quot;&gt;Accurate reproduction of strongly repulsive interatomic potentials, Phys. Rev. A 101, 032504 (2020)&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As pointed out in &lt;a href=&quot;https://doi.org/10.1063/1.5139948&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, the method can be implemented in two ways: you can either modify the usual orthonormalization routine, in which case your program might still waste a lot of time computing integrals that don't even appear in the calculation, or you can use the method to generate a customized basis set for the system you want to study by completely removing all shells that don't appear in the calculation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As in the note in &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.101.032504&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;, the only thing you need to implement this method is the overlap matrix, which is very cheap to compute. Implementations of the method are presently available in my ERKALE code, as well as Psi4 and PySCF.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-28T07:27:02.540" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1109" PostTypeId="5" CreationDate="2020-05-28T07:32:50.147" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-05-28T07:32:50.147" LastActivityDate="2020-05-28T07:32:50.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1110" PostTypeId="4" CreationDate="2020-05-28T07:32:50.147" Score="0" Body="For questions related to time-dependent density functional theory." OwnerUserId="35" LastEditorUserId="35" LastEditDate="2020-05-30T15:58:36.207" LastActivityDate="2020-05-30T15:58:36.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1111" PostTypeId="2" ParentId="1103" CreationDate="2020-05-28T07:39:40.347" Score="17" Body="&lt;p&gt;OpenBLAS is a free, open-source BLAS library that has fast support for even recent processors. (It is based on the earlier, famous GotoBLAS library which became obsolete years ago.) OpenBLAS is also multi-platform: in addition to x86 and x86_64 it also supports other architectures like ARM and PowerPC. OpenBLAS also has runtime CPU detection; if you compile it in, the resulting library supports all processors and picks the best kernel at runtime.&lt;/p&gt;&#xA;&lt;p&gt;IIRC OpenBLAS is as fast (sometimes has been even faster!) as MKL on some Intel processors; I don't think I've seen benchmarks on AMD hardware. But, the nice thing about OpenBLAS is that it's free, so it typically comes built-in your linux distribution. E.g. OpenBLAS has been available on Fedora and Red Hat Enterprise for a few years now (courtesy of yours truly), and to use it you just need to install the package&lt;/p&gt;&#xA;&lt;h3&gt;yum install openblas-devel&lt;/h3&gt;&#xA;&lt;p&gt;and then link to the flavor you want: on Fedora/Red Hat the available variants are&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblas&lt;/code&gt; sequential library with 4-byte integers&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblaso&lt;/code&gt; OpenMP parallel library with 4-byte integers&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblasp&lt;/code&gt; pthreads parallel library with 4-byte integers&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblas64&lt;/code&gt; sequential library with 8-byte integers&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblaso64&lt;/code&gt; OpenMP parallel library with 8-byte integers&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;libopenblasp64&lt;/code&gt; pthreads parallel library with 8-byte integers&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-09-07T20:57:43.830" LastActivityDate="2020-09-07T20:57:43.830" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1112" PostTypeId="1" AcceptedAnswerId="1124" CreationDate="2020-05-28T08:50:29.103" Score="14" ViewCount="184" Body="&lt;p&gt;According to my knowledge, each computational chemistry code optimizes a molecule keeping the input orientation of the molecule. The population and spectral analysis is performed on the optimized geometry.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My Question is, if a molecule is slightly different from a perfect point group representation in Cartesian coordinates(i.e tilted from perfect Cartesian planes), will there be any consequence? &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If so, how much difference can we expect in the molecular properties like ml-resolved partial occupation, spectral data, molecular orbital coefficients, Molecular orbital plots, electron density and it's plots, spin moments?&lt;/p&gt;&#xA;" OwnerUserId="765" LastEditorUserId="765" LastEditDate="2020-05-28T18:39:35.643" LastActivityDate="2020-05-29T09:13:39.673" Title="What is the impact of the orientation of a molecule in cartesian coordinates to molecular properties?" Tags="|molecular-modeling|computational-chemistry|spectroscopy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1113" PostTypeId="1" CreationDate="2020-05-28T15:08:20.897" Score="16" ViewCount="648" Body="&lt;p&gt;I'm new to DFT. I'm trying to figure out how projected density of states (PDOS) is built in solid state physics software package.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I understand the basics of the density functional theory method: each orbital of each substance is described by basis functions, the concept of electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is introduced and there is a one-to-one correspondence between the wave functions and the introduced electron density. However, I do not fully understand the principles of computer calculations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;According to the initial position of the atoms, the initial value of &lt;span class=&quot;math-container&quot;&gt;$\rho_0$&lt;/span&gt; is specified. The pseudopotential and the exchange-correlation potential are set. Then the Kohn-Sham equations are solved, where &lt;span class=&quot;math-container&quot;&gt;$\rho_0$&lt;/span&gt; is specified as the initial approximation, until the next value of &lt;span class=&quot;math-container&quot;&gt;$\rho_{i+1}$&lt;/span&gt; differs from the previous &lt;span class=&quot;math-container&quot;&gt;$\rho_i$&lt;/span&gt; by the allowable error &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How is the PDOS determined further? Indeed, in the compound there are common orbitals, as the algorithm determines from the electron density a specification of the electrons (&lt;span class=&quot;math-container&quot;&gt;$s, p ,d, f$&lt;/span&gt;) and the energy that they can occupy? (How is the PDOS determined for each individual kind, if the orbitals are common?)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Perhaps I do not fully understand the principles of DFT itself, please explain.&lt;/p&gt;&#xA;" OwnerUserId="663" LastEditorUserId="663" LastEditDate="2020-06-02T21:15:44.313" LastActivityDate="2020-06-02T21:15:44.313" Title="How the projected density of states is built" Tags="|density-functional-theory|computational-chemistry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1114" PostTypeId="1" CreationDate="2020-05-28T15:27:32.053" Score="17" ViewCount="1480" Body="&lt;p&gt;I am not able to understand the math of this. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;After taking the Slater determinant as a wavefunction in Hartree-Fock, does the procedure to find wavefunctions remain the same as in the Hartree method i.e. the self-consistent method, or does it change? &lt;/p&gt;&#xA;" OwnerUserId="606" LastEditorUserId="5" LastEditDate="2020-05-28T17:39:13.803" LastActivityDate="2020-06-08T10:00:28.817" Title="How does the Hartree-Fock method improve on Hartree after considering the wavefunction that takes the anti-symmetry property into account?" Tags="|self-consistent-field|hartree-fock|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1115" PostTypeId="2" ParentId="1114" CreationDate="2020-05-28T15:39:53.553" Score="21" Body="&lt;p&gt;Both Hartree and Hartree-Fock have a self-consistent field method, as does density functional theory, too; the difference is just that Hartree theory uses a bosonic wave function (symmetric with interchange of particles), while Hartree-Fock uses a fermionic wave function i.e. a Slater determinant that is the correct one for electrons.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In both cases, the self-consistent field method is obtained by the calculus of variations, which gives you a condition for achieving an extremum of the energy functional; e.g. in finite-basis Hartree-Fock, this is the Roothaan equation FC = SCE that gives you the one-particle states. (Note that the extremum does not have to be a minimum, it can also be a saddle point!)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Because the Hamiltonian is a two-particle operator, the potential the electrons move in is dependent on the movement of the electrons, or F = F(C). This means that you have to find a self-consistent solution. It turns out that the Roothaan procedure of solving FC=SCE for C and recomputing F=F(C) usually does not converge, and you have to stabilize the iterations e.g. by damping or extrapolation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is discussed in several textbooks, as well as &lt;a href=&quot;https://www.mdpi.com/1420-3049/25/5/1218&quot; rel=&quot;noreferrer&quot;&gt;our recent overview&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Edit: as is pointed out by André below, the Hartree method actually is inconsistent: the proper bosonic wave function is indistinguishable, whereas the Hartree method places specific particles on specific orbitals. A proper bosonic model would have a Fock matrix similar to Hartree-Fock; the difference is just that the exchange term would have a plus sign instead of a minus sign as in Hartree-Fock. For bosonic systems one often uses the Gross-Pitaevskii model where all the particles occupy the lowest orbital (exclusion principle is only for fermions).&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-06-08T10:00:28.817" LastActivityDate="2020-06-08T10:00:28.817" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1116" PostTypeId="1" AcceptedAnswerId="1158" CreationDate="2020-05-28T16:48:13.953" Score="11" ViewCount="108" Body="&lt;p&gt;I'm wondering if it is possible to simulate the chemical changes materials undergo when exposed to ionizing radiation for a finite period of time with Molecular Dynamics (MD) software. In principal this could be done with a few steps, although I'm not sure if these are implementable in current existing MD software.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Give certain molecules in the track of the radiation (use another software to find out which molecules these are) an increased energy prior to the run. &lt;/li&gt;&#xA;&lt;li&gt;Produce dissociation of bonds in the molecules with larger energy. &lt;/li&gt;&#xA;&lt;li&gt;Diffuse the dissociated species into the bulk.&lt;/li&gt;&#xA;&lt;li&gt;Simulate the recombination of dissociated species with non-dissociated species.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I understand these steps may not be things that MD alone can do, but I'm not sure how else to effectively simulate such a process. I would be open to suggestions that require running simulation of different steps in different software packages. I decided to ask this here since I saw previously a post about calculating homolytic bond-dissociation energies and thought to myself; if that can be done then maybe this can give me a way to identify what bond-dissociations would happen during energy deposition via radiation, then maybe MD could simulate diffusion and recombination by simply minimizing the energy.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Ultimately, I was at a loss for how to do any of this and would greatly appreciate any suggestions.  &lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-05-28T17:38:00.623" LastActivityDate="2020-06-01T10:30:03.053" Title="Can you model Radiation Chemistry with existing MD software?" Tags="|software|molecular-dynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1117" PostTypeId="1" CreationDate="2020-05-28T20:06:50.963" Score="12" ViewCount="268" Body="&lt;p&gt;We know that there is convergence issue of DFT method on study real molecular system. It would be conducive if people could pre-determine if the SCF procedure is converge analytically before starting the calculation.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-05-28T20:17:32.877" LastActivityDate="2020-06-02T14:43:48.617" Title="What is the mathematical condition that ensure that the self-consistent field (SCF) procedure must converge?" Tags="|density-functional-theory|electronic-structure|self-consistent-field|numerical-convergence|hartree-fock|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1118" PostTypeId="2" ParentId="891" CreationDate="2020-05-28T21:56:48.267" Score="6" Body="&lt;p&gt;You may find derivation of eqs.120-124 in these notes &lt;a href=&quot;https://arxiv.org/pdf/1601.04735.pdf&quot; rel=&quot;noreferrer&quot;&gt;Normal modes. The true story.&lt;/a&gt; helpful in revising your derivation. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Answering the other question: centre-of-mass can always be separated by the choice of centre-of-mass coordinates (cf. eq. 109-118) in &lt;a href=&quot;https://arxiv.org/pdf/1601.04735.pdf&quot; rel=&quot;noreferrer&quot;&gt;Normal modes. The true story.&lt;/a&gt;. &#xA;In almost all nuclear motion calculations the mass-polarisation term can be neglected: it is generally no bigger than finite-nuclei size effects or lowest order QED corrections. &lt;/p&gt;&#xA;" OwnerUserId="99" LastActivityDate="2020-05-28T21:56:48.267" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1119" PostTypeId="1" AcceptedAnswerId="1120" CreationDate="2020-05-29T00:48:55.497" Score="18" ViewCount="1890" Body="&lt;p&gt;In Kohn-Sham DFT calculations, Van der Waals corrections are often implemented in the structure optimization calculations because the typical functionals such as LDA and GGA are found to not treat long-range dispersion forces faithfully. But even in the context of Van der Waals corrections, there are some options such as the DFT-D and DFT-D3 schemes (refer &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm592&quot; rel=&quot;noreferrer&quot;&gt;quantum espresso's documentation - under 'vdw-corr' tag&lt;/a&gt;). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;What is the difference between these two corrections? Also, is it possible to conclude which one is more suited for a certain application?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-05-30T07:00:21.420" LastActivityDate="2020-05-30T07:00:21.420" Title="Difference between Van der Waals (DFT-D and DFT-D3) corrections in ab-initio calculations" Tags="|density-functional-theory|kohn-sham|dispersion-correction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1120" PostTypeId="2" ParentId="1119" CreationDate="2020-05-29T05:03:56.813" Score="21" Body="&lt;p&gt;As you mention, there are &lt;strong&gt;many&lt;/strong&gt; empirical dispersion corrections for density functional theory.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Generally, the term &quot;DFT-D&quot; refers to a generic dispersion-corrected density functional calculation, regardless of the specific method used for the dispersion correction used.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The D3 dispersion model is a specific dispersion correction method and is now something of a family, started by Grimme's 2010 article:&#xA;&quot;A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu&quot; &lt;a href=&quot;https://doi.org/10.1063/1.3382344&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; 132, 154104 (2010)&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In most cases, it's recommended to use Becke-Johnson damping - D3BJ:&#xA;&lt;a href=&quot;https://doi.org/10.1002/jcc.21759&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Comput. Chem.&lt;/em&gt;, 32: 1456-1465 (2011)&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There have been a few efforts to improve these:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;D3M - &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.6b00780&quot; rel=&quot;noreferrer&quot;&gt;J. Phys. Chem. Lett. 2016, 7, 12, 2197–2203&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;D3(op) - &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.7b00176&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 2017, 13, 5, 2043–2052&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;D4 - &lt;a href=&quot;https://doi.org/10.1063/1.5090222&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 150, 154122 (2019)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;There are a &lt;em&gt;wide&lt;/em&gt; variety of other methods, particularly those working to add many-body dispersion. Grimme wrote a review, although obviously it's been an active field:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&quot;Dispersion-Corrected Mean-Field Electronic Structure Methods&quot; &lt;a href=&quot;https://doi.org/10.1021/acs.chemrev.5b00533&quot; rel=&quot;noreferrer&quot;&gt;Chem. Rev. 2016, 116, 9, 5105–5154&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-29T05:03:56.813" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1121" PostTypeId="2" ParentId="1113" CreationDate="2020-05-29T07:07:40.443" Score="15" Body="&lt;p&gt;&lt;em&gt;Disclaimer&lt;/em&gt;: This answer would have been better placed in a comment but since I have just joined the community I cannot write comments. Ironically, I was tipped about this community after answering a very related question in Physics SE to which I dare giving a &lt;a href=&quot;https://physics.stackexchange.com/a/555227/262951&quot;&gt;link&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The short answer here is that projected DOS is a somewhat ambiguous construction in the context of solid-state systems. What is often done in practice is that one chooses some basis set of functions localized at atomic sites and having well-defined orbital character [that is, the functions are of the form &lt;span class=&quot;math-container&quot;&gt;$\chi_l(r) Y_{lm}(\hat{\mathbf{r}})$&lt;/span&gt;] and calculates the overlap of Kohn-Sham wavefunctions with these localized functions. Summing these overlaps over bands and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points weighted by occupation numbers (Fermi weights) one gets the occupancy of local states associated with a given atom. For a PDOS as function of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; one just multiplies the summation terms by band partial DOS, &lt;span class=&quot;math-container&quot;&gt;$\Im [1 / (E + i\delta + \mu - \varepsilon_{\nu\mathbf{k}})]$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; being the Fermi level, &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{\nu\mathbf{k}}$&lt;/span&gt; Kohn-Sham eigenenergies, and &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; a smearing factor.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In many cases, projected DOS does not even have to be properly normalized (because, again, there is no unique procedure to do this) and it can be constructed by choosing very simple local basis functions, such as, e.g., &lt;span class=&quot;math-container&quot;&gt;$\Theta(a - r) Y_{lm}(\hat{\mathbf{r}})$&lt;/span&gt; (so-called &quot;theta-projectors&quot;), where &lt;span class=&quot;math-container&quot;&gt;$\Theta(a - r)$&lt;/span&gt; simply cuts out a spherical region of radius &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; around an atom.&lt;/p&gt;&#xA;" OwnerUserId="772" LastActivityDate="2020-05-29T07:07:40.443" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1122" PostTypeId="1" CreationDate="2020-05-29T07:42:00.273" Score="19" ViewCount="2279" Body="&lt;p&gt;So one big problem I experience in doing calculations with Quantum ESPRESSO is that many calculations require a lot of computing power: you need large RAM capacities and powerful processors especially when there are many atoms in a solid state model and the computation requires a dense k-point grid. It becomes really impractical for a desktop setup at some point.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Some peers of mine from the computer science department of our university said that since we don't have an HPC here (I'm from a 3rd world country), what they do is they run their programs (which they wrote themselves) in free cloud computing services such as the Google Colab.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is this: Is there a way to run Quantum Espresso on Google Colab?&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="5" LastEditDate="2021-04-28T01:52:04.547" LastActivityDate="2021-04-28T01:52:04.547" Title="Running Quantum ESPRESSO calculations in Google Colab" Tags="|quantum-espresso|high-performance-computing|k-points|cloud-computing|" AnswerCount="3" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="1123" PostTypeId="2" ParentId="1117" CreationDate="2020-05-29T09:03:44.977" Score="12" Body="&lt;p&gt;This question is a bit ill-defined: what do you mean by &quot;the self-consistent field procedure&quot;? If you mean the original Roothaan procedure, then the question makes sense, but it is uninteresting: nobody uses the Roothaan procedure, since it usually doesn't converge, and you need to do something smarter like use damping or other convergence acceleration schemes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But, these are &lt;em&gt;different&lt;/em&gt; methods, and now you would have to study each of them separately.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Still, it is possible to make any self-consistent field calculation converge simply by switching from iterative diagonalization to direct energy minimization. Here, you rewrite the problem in terms of iterative orbital rotations, and what you get is the minimization of a scalar function f(theta) in Cartesian space, which is a well-understood problem in numerical analysis. There are methods for minimization without gradients (e.g. the Nelder-Mead &quot;amoeba&quot; method), with gradients (e.g. steepest descent and conjugate gradients, and preconditioned versions thereof), and with Hessians (e.g. Newton-Raphson and trust region methods). These methods are proven to always converge to an extremum, and you'll just need to check whether you're at a local minimum or not just as if you use some kind of iterative diagonalization.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For details, you can refer to our recent open access overview paper: &lt;a href=&quot;https://doi.org/10.3390/molecules25051218&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Molecules&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;25&lt;/em&gt; (5), 1218&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="49" LastEditDate="2020-05-29T10:11:41.893" LastActivityDate="2020-05-29T10:11:41.893" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1124" PostTypeId="2" ParentId="1112" CreationDate="2020-05-29T09:13:39.673" Score="10" Body="&lt;p&gt;Actually, quantum chemistry codes tend to reorient molecules to make calculations more reproducible, since as was already mentioned in a comment above, the use of quadrature makes density functional calculations somewhat dependent on the absolute orientation of the molecule, see e.g. &lt;a href=&quot;https://rsc.anu.edu.au/~pgill/papers/038SG1.pdf&quot; rel=&quot;noreferrer&quot;&gt;the paper by Gill, Johnson, and Pople&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As to the second part of your question, if a molecule is slightly different from a perfect point group representation, this will affect its symmetries that may have repercussions onto observables due to e.g. &lt;a href=&quot;https://en.wikipedia.org/wiki/Jahn%E2%80%93Teller_effect&quot; rel=&quot;noreferrer&quot;&gt;the Jahn-Teller effect&lt;/a&gt;. Quantum chemistry codes usually employ the symmetry of the molecule to speed up calculations, but if you choose a too high level of  symmetry, you might not get the correct solution!&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-29T09:13:39.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1125" PostTypeId="1" AcceptedAnswerId="1137" CreationDate="2020-05-29T18:00:22.823" Score="20" ViewCount="1013" Body="&lt;p&gt;Does anyone have any knowledge or direction for creating a homemade &lt;a href=&quot;https://en.wikipedia.org/wiki/Beowulf_cluster&quot; rel=&quot;noreferrer&quot;&gt;Beowolf cluster&lt;/a&gt; for materials modeling?I would like to be able to run my own &amp;quot;hobby&amp;quot; simulations at home, so a low energy, low capital investment is what I seek.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Raspberry_Pi&quot; rel=&quot;noreferrer&quot;&gt;Raspberry Pi&lt;/a&gt; and &lt;a href=&quot;https://www.hardkernel.com/shop/odroid-mc1-my-cluster-one-with-32-cpu-cores-and-8gb-dram/&quot; rel=&quot;noreferrer&quot;&gt;ODroid&lt;/a&gt; use small, cheap, low energy single board computers (SBC) that can be stacked into a cluster. A demonstration cluster was made in 2013 in the UK &lt;a href=&quot;http://www.southampton.ac.uk/%7Esjc/raspberrypi/&quot; rel=&quot;noreferrer&quot;&gt;Raspberry Pi demonstration cluster&lt;/a&gt;. I have not found examples of molecular simulation being applied to these clusters (GROMACS or GAMESS type applications). My concern is that they may not be able to handle long term simulations?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there any recent examples of these SBC clusters handling prolonged workload, and in particular, are there examples of molecular simulations being successful?&lt;/strong&gt; I have tried reaching out to the SBC community, however, molecular dynamics and quantum chemistry gets me blank stares.&lt;/p&gt;&#xA;&lt;p&gt;I just found this paper comparing the ODroid-MC1 to supercomputer cluster CPU's. The Odroid-MC1 is a 32 cpu cluster for \$220, and the CPU's compared against retail at \$9000+. The test problem was solving Lattice-Boltzmann flow computations. &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0167739X18322015&quot; rel=&quot;noreferrer&quot;&gt;They found&lt;/a&gt; that ODroid-MC1 was only 4 times slower, and this was largely due to its use of 32-bit ARMv7. It can therefore likely be expected that using 64-bit ARMv8 and newer would make ODroid-MC1 very competitive, and incredibly cheap. ODroid consistently beats raspberry pi for speed.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="7" LastEditDate="2020-06-25T21:20:48.770" LastActivityDate="2021-12-09T06:45:03.943" Title="Materials Modeling with Raspberry Pi?" Tags="|molecular-modeling|quantum-chemistry|high-performance-computing|" AnswerCount="3" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="1126" PostTypeId="1" AcceptedAnswerId="1128" CreationDate="2020-05-29T22:31:47.550" Score="14" ViewCount="621" Body="&lt;p&gt;This might be a stupid question but to what extent will the initial configuration of a bulk phase geometry optimization calculation affect the final geometry? Most places say to start with experimental data but if there isn't any then is there a next best way of starting?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Would populating your initial configuration with a molecule repeated along the x y and z directions yield a different final geometry than populating it with molecules in random locations? or will this only effect the run time?&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-05-30T15:20:07.670" LastActivityDate="2020-05-30T16:03:57.170" Title="How much does the initial geometry affect the final geometry in optimization calculations?" Tags="|condensed-matter|optimization|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1127" PostTypeId="2" ParentId="1114" CreationDate="2020-05-29T23:21:47.870" Score="16" Body="&lt;p&gt;The procedure to find the Hartree equations and the Hartree-Fock equations is very similar, we have to minimize the expectation value of the Hamiltonian under the orthonormalization constraint. However, both methods differ in the form of the wavefunction.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Hartree Method&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;In the Hartree method, the total wavefunction is a Hartree product:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Phi(\mathbf{r}_1,\mathbf{r}_2,\dots,\mathbf{r}_N)=\prod_{i=1}^{N}\phi_i(\mathbf{r}_i)&#xA;$$&lt;/span&gt;&#xA;The constraint is the normalization of every orbital, so then, we can construct the functional:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;L[\{\phi_i,\phi_i^*\}]=\langle\hat{H}\rangle-\sum_{i=1}^{N}\varepsilon_i\left(\langle\phi_i|\phi_i\rangle-1\right)&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_i$&lt;/span&gt; are Lagrange multipliers. Now, the expectation value of the Hamiltonian is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{aligned}&#xA;\langle\hat{H}\rangle&amp;amp;=\sum_{i=1}^{N}\langle\phi_i|\frac{-\nabla_i^2}{2}-\frac{Z}{r_i}|\phi_i\rangle\left(\prod_{j\neq i}^{N}\langle\phi_j|\phi_j\rangle\right)+\frac{1}{2}\sum_{i=1}^{N}\sum_{j\neq i}^{N}\langle\phi_i\phi_j|r_{ij}^{-1}|\phi_i\phi_j\rangle\left(\prod_{k\neq i,j}^{N}\langle\phi_k|\phi_k\rangle\right) \\&#xA;&amp;amp;=\sum_{i=1}^{N}h_{ii}+\frac{1}{2}\sum_{i=1}^{N}\sum_{j\neq i}^{N}J_{ij}&#xA;\end{aligned}&#xA;$$&lt;/span&gt;&#xA;The functional &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; depends on the set of all the &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; and its complex conjugates, so we can vary either of them arbitrarily. For instance, a variation in a &lt;span class=&quot;math-container&quot;&gt;$\phi_k^*$&lt;/span&gt; can be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;L[\phi_1,\phi_1^*,\dots,\phi_k,\phi_k^*+\lambda\delta\phi_k^*,\dots,\phi_N,\phi_N^*]\equiv L[\phi_k^*+\lambda\delta\phi_k^*]&#xA;$$&lt;/span&gt;&#xA;and the difference between the original functional and this is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;L[\phi_k^*+\lambda\delta\phi_k^*]-L[\{\phi_i,\phi_i^*\}]=\lambda\left(\langle\delta\phi_k|\frac{-\nabla_k^2}{2}-\frac{Z}{r_k}|\phi_k\rangle+\sum_{j\neq i}^{N}\langle\delta\phi_k\phi_j|r_{kj}^{-1}|\phi_k\phi_j\rangle-\varepsilon_k\langle\delta\phi_k|\phi_k\rangle\right)&#xA;$$&lt;/span&gt;&#xA;Dividing by &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; and taking the limit where &lt;span class=&quot;math-container&quot;&gt;$\lambda\to 0$&lt;/span&gt;, we have that an extremum of the functional gives the Hartree equations (in summary, we look for &lt;span class=&quot;math-container&quot;&gt;$\delta L/\delta\phi_k^*=0$&lt;/span&gt;):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(\frac{-\nabla_k^2}{2}-\frac{Z}{r_k}+\sum_{j\neq k}^{N}\int\frac{|\phi_j(\mathbf{r}_j)|^2}{r_{jk}}d\mathbf{r}_j\right)\phi_k(\mathbf{r}_k)=\varepsilon_k\phi_k(\mathbf{r}_k)&#xA;$$&lt;/span&gt;&#xA;In short, the total energy can be written in terms of the orbital energies &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_i$&lt;/span&gt; as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_H=\sum_{i=1}^{N}\varepsilon_i-\frac{1}{2}\sum_{i=1}^{N}\sum_{j\neq i}^{N}J_{ij}&#xA;$$&lt;/span&gt;&#xA;The problem of the Hartree method is that the wavefunction is not antisymmetric with respect to the exchange of particles and, more fundamentally, it doesn't consider the electrons as indistinguishable particles. Also, in the original formulation, it doesn't consider spin.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Hartree-Fock Method&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;We can fix these problems by using an Slater determinant as a wavefunction. Now, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Psi(\mathbf{x}_1,\dots,\mathbf{x}_N)=\frac{1}{\sqrt{N!}}\sum_{n=1}^{N!}(-1)^{n_p}\hat{P}_n(\psi_i(\mathbf{x}_1),\psi_j(\mathbf{x}_2)\dots\psi_k(\mathbf{x}_N)),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\hat{P}_n$&lt;/span&gt; is the permutation operator, &lt;span class=&quot;math-container&quot;&gt;$n_p$&lt;/span&gt; is the number of required transpositions to get an specific permutation, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}_i$&lt;/span&gt; are spatial and spin coordinates.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, we construct the functional for this situation, with &lt;span class=&quot;math-container&quot;&gt;$\langle\hat{H}\rangle=\sum_{i=1}^{N}h_{ii}+\frac{1}{2}\sum_{i=1}^{N}\sum_{j\neq i}^{N}J_{ij}-K_{ij}$&lt;/span&gt; and the orthonormality condition of the orbitals.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;L[\{\psi_i,\psi_i^*\}]=\langle\hat{H}\rangle-\sum_{i=1}^{N}\sum_{j=1}^{N}\varepsilon_{ij}\left(\langle\psi_i|\psi_j\rangle-\delta_{ij}\right)&#xA;$$&lt;/span&gt;&#xA;Briefly, using the same method we get to the Hartree-Fock equations&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(\frac{-\nabla_k^2}{2}-\frac{Z}{r_k}+\sum_{j\neq k}^{N}\int\frac{|\psi_j(\mathbf{x}_j)|^2}{r_{jk}}d\mathbf{x}_j-\int\frac{\psi_j^*(\mathbf{x}_j)\hat{P}_{kj}\psi_j(\mathbf{x}_j)}{r_{kj}}d\mathbf{x}_j\right)\psi_k(\mathbf{x}_k)=\sum_{j=1}^{N}\varepsilon_{kj}\psi_j(\mathbf{x}_k)&#xA;$$&lt;/span&gt;&#xA;Finally, doing an unitary transformation we get the canonical form of the HF equations and the total energy in terms of the spin-orbitals is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{HF}=\sum_{i=1}^{N}\varepsilon_i-\frac{1}{2}\sum_{i=1}^{N}\sum_{j\neq i}^{N}J_{ij}-K_{ij}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Final Remarks&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;As you see, the method for finding an extremum of the energy with respect of the orbitals with the constraint of orthonormalization is similar. However, considering an Slater determinant instead of a Hartree product improves a lot the results in terms of physical significance and numerical accuracy. An Slater determinant considers that the electrons are antisymmetric with respect to exchange of coordinates and they are indistinguishable particles. Moreover, we have another term involved in the energy: the exchange integral, which is always positive and lowers the energy when it's not zero. In a pseudo-classical interpretation of the determinantal energies (as Szabo &amp;amp; Ostlund called in their book) we see that exchange terms arise only when we have electrons with the same spin, but, obviously, in different spin-orbitals.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="10" LastEditDate="2020-06-07T22:23:35.120" LastActivityDate="2020-06-07T22:23:35.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1128" PostTypeId="2" ParentId="1126" CreationDate="2020-05-29T23:33:54.353" Score="15" Body="&lt;h2&gt;Alot&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;Optimizations are all about finding the minimum in something. Typically in geometry optimization, it is about finding the minimum in energy. At a minimum the derivative of energy with respect to changing position should be zero, or better put, the jacobian should be positive definite.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Your question is about bulk systems, however, single molecules are problematic enough.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;A single molecule by itself&lt;/strong&gt; can take on many different conformations, each with a different energy. Given a starting configuration, a geometry optimization changes atomic coordinates to minimize energy. In practice, this usually means you find the nearest local minimum.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;It is therefore important, and often ignored, to do a conformer search for a single molecule and find the lowest energy conformer prior to doing a geometry optimization. I can't stress the importance of conformer searches enough.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Now&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;You are interested in a system of many molecules&lt;/strong&gt;. For a single molecule the actual x,y,z position does not really matter. For a system of them however it does. Each molecule will relax to some conformer, possibly not the best one, and they will relax to certain orientations and centers of mass x,y,z most likely not the best ones, but representing the nearest local minimum in energy from the initial starting guess.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Finding a best geometry for a single molecule is tough, I would say, currently, it is impossible for a bulk system, you find the best one that you can, and live with it.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You can of course generate many initial guesses and take the lowest energy final geometry. You can try simulated annealing techniques, you can try all sorts of numerical methods really, but, finding the global minumum is an unsolved problem for an N-body problem such as a bulk phase of molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Courtesy of Andrew Rosen&lt;/strong&gt;, this &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.8b12230&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; has a nice example of zeolite structures depending on initial configuration.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-05-30T05:14:31.380" LastActivityDate="2020-05-30T05:14:31.380" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1129" PostTypeId="2" ParentId="528" CreationDate="2020-05-29T23:45:41.597" Score="7" Body="&lt;p&gt;Whatever scattering mechanism you choose must respect detailed balance &lt;em&gt;in equilibrium&lt;/em&gt;: on average, the number of particles hitting a patch of the wall at a given angle and velocity must equal the number of particles reflected at the same angle and velocity. If this were not the case, the system would not be in equilibrium.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are numerous ways to do this including&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Have each particle scatter specularly.&lt;/li&gt;&#xA;&lt;li&gt;Have each particle that hits the wall keep its energy but choose a random direction from a cosine distribution. (Depending on the context, this is known as &lt;a href=&quot;https://en.wikipedia.org/wiki/Lambert%27s_cosine_law&quot; rel=&quot;noreferrer&quot;&gt;Lambert's cosine law&lt;/a&gt; or the Knudsen cosine law.) This is diffuse scattering.&lt;/li&gt;&#xA;&lt;li&gt;Randomize the energy as well by drawing a new energy from the Maxwell-Boltzmann distribution.*&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;These methods have different meanings. The first means that the surface is perfectly smooth and doesn't transfer energy. The second means that the surface is so rough that all knowledge about the particles previous direction is lost. The third means the surface thermalizes the particle, so knowledge about the previous energy is also lost.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are many variations on this. For example, a particle could scatter specularly with some probability p and scatter diffusely with probability 1-p. This indicates that the surface is somewhere between perfectly smooth and super rough.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, your system is not in equilibrium, but you still should choose a method that respects detailed balance in equilibrium. I'm guessing that the inside of the vacuum chamber is relatively smooth. I'm also guessing that the walls of the chamber won't do much to thermalize the chamber on each collision. (Think about a small gas cylinder with cold air in it. The atoms hit the walls a gazillion times a second, but it still takes a while for the air to warm up. So, individual collisions don't cause much thermalization.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You could probably do something like reflect specularly with a large probability, reflect diffusely with a smaller probability, and thermalize with a very small probability. (You could do a back-of-the envelope calculation for how many collisions it takes to thermalize a gas particle on average.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, none of these are first-principles methods, but I don't think that first-principles methods are meaningful unless you know the properties of the chamber walls in great detail. It sounds like that's not the case, so I'd use a simpler model and be done with it. I'm sure that simulations used for real-world engineering generally don't use first principle approaches.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;* This is surprisingly easy to do wrong. The methods I mentioned are all also used to model electromagnetic radiation. In particular, the third method is basically blackbody radiation with gas molecules instead of light. So, you can get a good reference on how to do this with light (e.g. &lt;em&gt;Radiative Heat Transfer&lt;/em&gt; by Michael Modest) and just substitute a Maxwell-Boltzmann distribution for gas particles wherever you see a Bose-Einstein distribution for photons. I'm sure there are good books on gas flows too, but I'm not familiar with them.&lt;/p&gt;&#xA;" OwnerUserId="778" LastEditorUserId="778" LastEditDate="2020-05-30T00:05:53.320" LastActivityDate="2020-05-30T00:05:53.320" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1130" PostTypeId="2" ParentId="841" CreationDate="2020-05-30T03:22:09.800" Score="4" Body="&lt;p&gt;&lt;strong&gt;I am not at all surprised that using 16 cores on one node with OpenMP is faster than using 16 cores spread across 4 different computers (nodes).&lt;/strong&gt; The 16 cores on a single node are usually part of the same &quot;chip&quot; and are definitely attached to the same motherboard. The 16 cores spread across 4 computers will not be able to communicate with each other nearly as quickly as if they were in the same chip or on the same motherboard.&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Is it possible to accelerate such calculations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Since for this calculation, OpenMP on a single node gave the fastest results out of the three experiments you did, to acceleration your results, I suggest you try to use more OpenMP cores on a single node (I would be surprised if your HPC cluster has nodes with only 16 cores, because for the last several years, most HPC nodes have 24, 32, or 40 cores.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you still want faster results, you can add a second node. This will allow you to double your total number of cores, but please do not expect the speed to be twice as fast as when you used 1 node, because there can be overhead due to the fact that you are now using two separate computers with two separate motherboards (connected by Omni-Path, or InfiniBand, or even an Ethernet cable in some rare cases!). If you have two calculations like this to do, I recommend that you run each of them on a separate node with maximum OpenMP parallelization, rather than to run one calculation on two nodes, and then the other calculation on the same two nodes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;So when should you use MPI?&lt;/strong&gt; Two examples of when I'd recommend MPI are:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When a single node does not have enough RAM for the calculation, you can use &quot;distributed memory&quot; meaning that data needed for the calculation can be spread across multiple nodes to give you sufficient RAM to store all the required data. This is probably not your case, because while 462 spatial orbitals is a &lt;em&gt;fairly&lt;/em&gt; large amount, the integrals will indeed be manageable on a single node on most HPC cluster built any time in the last several years.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When the algorithm you are using is &quot;embarrassingly parallel&quot;, meaning that there is essentially no communication needed between the nodes, so doubling the number of nodes will in fact nearly double the overall speed of the calculation. This is the case for FCIQMC, but not so much for the SCF in DFT (which is what you're doing, and is probably why your use of MPI is slowing you down in comparison to using OpenMP with the same number of total cores).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-05-30T03:22:09.800" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1131" PostTypeId="2" ParentId="775" CreationDate="2020-05-30T04:07:02.390" Score="3" Body="&lt;p&gt;The &lt;a href=&quot;https://manual.q-chem.com/5.2/Ch12.S3.SS1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Q-Chem manual edition 5.2&lt;/a&gt; is much better at describing QM/MM&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, to answer your main question there are no angles and torsions across a link atom. The link atom is a fictitious hydrogen that is added when you break the QM and MM region at a bond. This is done to maintain the proper valency/avoid dangling bonds in the QM region. The MM region is also affected in some methods, for example in additive QM/MM schemes the fractional charge that occurs due to partitioning the system into QM and MM regions is smeared out amongst the remaining MM atoms. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Q-Chem automatically insert the link atoms depending on the definitions of the QM and MM regions.&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Link atoms for the ONIOM model and YinYang atoms for the Janus model are not&#xA;  specified in the $qm_atoms section, as these are inserted&#xA;  automatically whenever a bond connects a QM atom and an MM atom.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Note however, that this only works if the linked atom is a carbon.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-05-30T05:52:35.653" LastActivityDate="2020-05-30T05:52:35.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1132" PostTypeId="2" ParentId="392" CreationDate="2020-05-30T06:17:08.583" Score="29" Body="&lt;h1&gt;2006 (Grimme): Double hybrid functionals&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;The timeline of milestones you have given, includes a hybrid functional called B3LYP, which mixes a Hartree-Fock exchange functional with a GGA exchange-functional. &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.2148954?journalCode=jcp&quot; rel=&quot;noreferrer&quot;&gt;In 2006&lt;/a&gt;, Stefan Grimme introduced what later became known as &quot;double hybrid functionals&quot;, which not only mix the Hartree-Fock exchange functional with a GGA exchange-correlation functional, but also a many-body perturbation theory correction:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;E_{\textrm{xc}}=\left(1-a_\textrm{x}\right)E_\textrm{x}^{\textrm{GGA}} + a_\textrm{x}E_\textrm{x}^{\textrm{HF}} + bE_\textrm{c}^{\textrm{GGA}} + cE_\textrm{c}^{\textrm{MBPT}}.&#xA;\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For the MBPT correction, Grimme used MP2 with the Kohn-Sham orbitals and single-excitations neglected. He tried various double hybrids, and the one that he finally recommended was obtained after setting b=1-c, and then using the Becke-88 functional for &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{x}^{\textrm{HF}}$&lt;/span&gt; and the LYP functional for &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{c}^{\textrm{GGA}}$&lt;/span&gt;. He called this new functional &lt;strong&gt;B2PLYP&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;By 2011 there existed several different double hybrid functionals made by various other groups, and &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2011/cp/c0cp02984j/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;Goerigk and Grimme created&lt;/a&gt; an enormous dataset by combining 30 test sets, containing a grand total of 841 relative energies involving 1218 total energies, and compared the performance of 47 functionals (2 LDA, 14 GGA, 3 meta-GGA, 23 Hybrid, 5 Double Hybrid) on this test suite. &lt;strong&gt;Double hybrids were by far the most accurate family of functionals, with an estimated average error of only 1.8 kcal/mol:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;img src=&quot;https://i.stack.imgur.com/mpIgV.png&quot; width=&quot;400&quot;&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-05-30T15:12:13.330" LastActivityDate="2020-05-30T15:12:13.330" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1133" PostTypeId="2" ParentId="499" CreationDate="2020-05-30T06:20:35.357" Score="17" Body="&lt;h2&gt;Ah, yes, the fun of force-field building.&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;For the answer to a simple geometry optimization, see I. Camps response below.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Skip to the end if you want what is a more general answer to building an entire force-field. Read the whole thing if you want some insight into force-fields, particularly partial charges.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;First, doing an electronic structure calculation (in your example you suggest using B3LYP/6-31G(d)) unsurprisingly gives you an electron density. Perhaps interestingly, it does not give you partial charges.&lt;/p&gt;&#xA;&lt;h2&gt;Partial charges are not real&lt;/h2&gt;&#xA;&lt;p&gt;There is no way to actually calculate a partial charge since they are not real observables. However, given an electron density, you can apply a protocol, to calculate partial charges that represent the given electron density according to some principle.&lt;/p&gt;&#xA;&lt;p&gt;For the record B3LYP/6-31G(d) is typically used with Restrained Electrostatic Potential (RESP) partial charges, however, more frequently, HF/6-31G* is used. Further, this is the default method for the older AMBER forcefields, as well as the General AMBER Force-Field, although other Force-fields use it.&lt;/p&gt;&#xA;&lt;p&gt;It is my opinion that RESP using HF or B3LYP with 6-31G* (additional note,  6-31G* is the same as 6-31G(d)) is a terrible choice.&lt;/p&gt;&#xA;&lt;p&gt;If you are using RESP, then your electronic structure calculation only calculates the electron density, and another program must calculate the RESP partial charges. Gaussian will output ESP (not restrained) partial charges, that usually, are identical.&lt;/p&gt;&#xA;&lt;p&gt;One problem with RESP when using B3LYP/6-31G(d), is that it adds polarization effects implicitly. What I mean is that you just did a calculation for the electron density of the molecule in a vacuum, and calculated partial charges from this density. However, this density by no means should be useful if you put your molecule in a liquid. In a liquid, the neighboring molecules will polarize each other, and a molecules electron density will distort from the density in a vacuum. However, &lt;strong&gt;B3LYP/6-31G* is so terribly bad&lt;/strong&gt; its vacuum calculations actually somewhat polarize the molecule. Unfortunately, it does it almost randomly, ranging from underpolarizing, to overpolarizing by 35% &lt;a href=&quot;https://chemrxiv.org/articles/Benchmarking_Electronic_Structure_Methods_for_Accurate_Fixed-Charge_Electrostatic_Models/9985079/2&quot; rel=&quot;nofollow noreferrer&quot;&gt;Paper to read&lt;/a&gt;. RESP using HF or B3LYP with 6-31G(d) is so bad, it is actually by fluke useful, in an average way, but messes up alot.&lt;/p&gt;&#xA;&lt;p&gt;RESP is from the 1990's. It used to take time to calculate electron densities back then, so they made a parameterized model AM1-BCC which uses a even worse semiempirically derived electron density to calculate Mulliken partial charges, and then adds corrections to them in an attempt to match RESP using HF/6-31G*. This is faster to calculate, but again, not that great, it often fails and really, you can't expect it to work outside of its training set.&lt;/p&gt;&#xA;&lt;p&gt;Important point here though, RESP partial charges are derived by starting with an initial guess for the partial charges, and then calculating the electrostatic potential of the molecule using the partial charges. You also calculate it from the QM software. You then change the partial charges until the forcefields electrostatic potential is as close as possible to the QM's &amp;quot;correct&amp;quot; electrostatic potential. Other methods exist however, and Mulliken is one, where for brevity, you &amp;quot;partition&amp;quot; the electron density to each atom. This is a much more intuitive method that doesn't not rely on opptimization. However, Mulliken charges are usually only qualitatively useful.&lt;/p&gt;&#xA;&lt;p&gt;More advanced methods such as the Hirshfeld familes &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct200866d&quot; rel=&quot;nofollow noreferrer&quot;&gt;CM5&lt;/a&gt;, &lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2016/ra/c6ra04656h&quot; rel=&quot;nofollow noreferrer&quot;&gt;DDEC6&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00456&quot; rel=&quot;nofollow noreferrer&quot;&gt;MBIS&lt;/a&gt; exist and in my opinion are far superior to RESP. I do not say superior to AM1-BCC because AM1-BCC is nothing but parameters, it is not a &amp;quot;method&amp;quot;.&lt;/p&gt;&#xA;&lt;h2&gt;Why don't we use these better methods?&lt;/h2&gt;&#xA;&lt;p&gt;Hopefully we will in the future, unfortunately partial charges are only part of a force-field, and if you change the charges, you should really change the other parts too.&lt;/p&gt;&#xA;&lt;p&gt;This is most clear with Lennard-Jones parameters, which is typically fit to experimental data for the given partial charge method. It is thus, alot of work to refit all of the LJ parameters (and torsions as well) for a new charge method. But, this is slowly happening.&lt;/p&gt;&#xA;&lt;h2&gt;Building a Force-Field in Practice&lt;/h2&gt;&#xA;&lt;p&gt;To directly answer your question now, Force-fields take a lot of work. If you are making one from scratch you need to&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Generate partial charges&lt;/li&gt;&#xA;&lt;li&gt;Calculate bond parameters&lt;/li&gt;&#xA;&lt;li&gt;calculate angle parameters&lt;/li&gt;&#xA;&lt;li&gt;Calculate torsion parameters&lt;/li&gt;&#xA;&lt;li&gt;Calculate (fit to data) Lennard-Joes parameters&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This is a ridiculous amount of work. And, Gaussian does not do this at a push of a button. Each item is progressively more work and its own task. If you do this however, I would strongly recommend ditching the B3LYp/6-31G(d) electronic structure calculation and the presumably RESP or AM1-BCC partial charges that follow. Use better methods. i.e., use &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D/DEF2TZVP for instance for the electronic structure calculation, and then use CM5/DDEC6 or MBIS for the partial charges. I recommend MBIS.&lt;/p&gt;&#xA;&lt;p&gt;But, what I recommend even more is to not make your own force-field if this is your first time. There are many ready to go toolkits that will make one for you.&lt;/p&gt;&#xA;&lt;p&gt;For polymers I would recommend either GAFF or OPLS.&lt;/p&gt;&#xA;&lt;p&gt;Here is a link to &lt;a href=&quot;http://ambermd.org/antechamber/gaff.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GAFF&lt;/a&gt;. It will use AM1-BCC be default, but the other parameters are fit to it, so it will be decent for you. Follow their instructions.&lt;/p&gt;&#xA;&lt;p&gt;Or, OPLS has a easy to use webserver that will whip up a force-field for you for almost any program you want to use found &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. They use empirically scaled CM1 partial charges - a faster(presumably), older version of CM5. It has some options, but basically, you just upload a structure in a pdb or mol2 file, and it will give you back an entire force-field for your molecule.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-07-18T14:59:21.237" LastActivityDate="2022-07-18T14:59:21.237" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1134" PostTypeId="1" AcceptedAnswerId="1423" CreationDate="2020-05-30T06:55:01.390" Score="12" ViewCount="300" Body="&lt;p&gt;Electron correlation methods based on an expansion of the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron wavefunction in terms of Slater determinants have a slow basis set convergence. Moreover, explicitly correlated methods (such as R12 or F12) provides a better description of the Coulomb holes of the wavefunction, that is, they give an accurate representation of the electron-electron cusps, and, thus, its basis set convergence is faster.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Although this sounds good, I understand that treating with geminals can be more difficult that the current orbital methods, making expensive computationally the use of explicitly correlated methods. For instance, the energy of a CI calculation with an R12 wavefunction is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E=\langle\Psi_{R12}|\hat{H}|\Psi_{R12}\rangle,&#xA;$$&lt;/span&gt;&#xA;and the matrix elements needed involve three- and four-electron integrals (that can be &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.459921&quot; rel=&quot;noreferrer&quot;&gt;very difficult without approximations&lt;/a&gt;). Also, F12 methods are based on this kind of methods aiming for application to larger systems and it can be combined with other correlated methods, for instance CCSD-F12, CASPT2-F12 and MRCI-F12.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In general terms, what are the practical limitations of R12 or F12 methods?&lt;/p&gt;&#xA;" OwnerUserId="10" LastActivityDate="2020-06-29T23:20:58.987" Title="What are the practical limitations of R12/F12 methods?" Tags="|electronic-structure|electron-correlation|explicitly-correlated-methods|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1135" PostTypeId="2" ParentId="877" CreationDate="2020-05-30T07:06:42.997" Score="4" Body="&lt;p&gt;I think the justification is just that this is the simplest approach, since &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is a scalar and &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\epsilon}$&lt;/span&gt; is a vector. If you only take the diagonal part of &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt;, you see that the secular determinant vanishes whenever &lt;span class=&quot;math-container&quot;&gt;$E = \epsilon_i + \Sigma_{ii}$&lt;/span&gt;. If you included the off-diagonal elements, you would essentially have to diagonalize &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\Sigma}$&lt;/span&gt; and you would lose this nice simple interpretation...&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-30T07:06:42.997" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1136" PostTypeId="2" ParentId="656" CreationDate="2020-05-30T07:24:48.003" Score="7" Body="&lt;p&gt;Hylleraas' method is special to the case of the helium atom; note that the equation only has a single nucleus. When you go to more electrons, you get more and more interelectronic distances in your wave function ansatz, which will blow up the scaling; this is why the method is impractical for several electrons. (Also, I think you would need several expansion parameters &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; to get an accurate result!)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$r_{12}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_{12}$&lt;/span&gt; methods are indeed inspired by Hylleraas' technique, but instead of aiming for the &lt;em&gt;exact&lt;/em&gt; (i.e. FCI/CBS) energy their target is simpler: accelerate the basis set convergence for your approximate post-HF method like MP2. I would not say these methods are only rarely applied; you do see them quite often in e.g. benchmark studies. A rule of thumb you often hear is that these methods allow you to get one cardinal number more accurate results in your basis set, e.g. triple-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; results for a double-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; basis set, and quadruple-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; results for a triple-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; basis set. Since post-HF methods often have a steep scaling in the number of virtual orbitals (e.g. &lt;span class=&quot;math-container&quot;&gt;$O(v^4)$&lt;/span&gt; for CCSD), this speedup can become important when you want to push the limits...&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-30T07:24:48.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1137" PostTypeId="2" ParentId="1125" CreationDate="2020-05-30T07:59:07.237" Score="22" Body="&lt;p&gt;Raspberry Pi clusters are okay for studying networked systems and job schedulers, but bad for any real calculations. There are several problems: there's very little memory per CPU, the interconnect is slow, having local disk is hard... but worst of all, the bang per buck is very low, see e.g. &lt;a href=&quot;https://www.phoronix.com/scan.php?page=article&amp;amp;item=raspberry-pi-burst&amp;amp;num=6&quot; rel=&quot;noreferrer&quot;&gt;a Phoronix benchmark&lt;/a&gt;.&#xA;So, in summary: Intel/AMD is still cheaper for running actual calculations, but a Raspberry Pi cluster is quite cheap to set up so it could serve as a toy / test system.&lt;/p&gt;&#xA;&lt;p&gt;More powerful ARM workstations that are actually designed for running calculations (many CPUs, large memory, local storage) could be a game changer, but these are still not common.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I've just benchmarked a Raspberry Pi 4. According to linpack, it's about the same speed as a cheap celeron laptop; however, it's terribly slow in desktop use. Both are at least 10 times less powerful than my work laptop; I'd estimate that the raspberry pis are at least 3-4 times more expensive per gflop than good PCs at the moment.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-06-16T04:05:00.587" LastActivityDate="2021-06-16T04:05:00.587" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1138" PostTypeId="2" ParentId="499" CreationDate="2020-05-30T11:34:34.900" Score="10" Body="&lt;p&gt;All Gaussian jobs when completed without any error, will have, at the end of the output file, a phrase/thought/quote from someone famous. It is kind off an easteregg. My latest Gaussian successful job finished with this quote:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;THERE IS NO SCIENCE WITHOUT FANCY, NOR ART WITHOUT FACTS.&#xA;     -- VLADIMIR NABAKOV&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Anyway, answering your second question:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;What are the parameters that I should look out for, in the Gaussian output, to know that the structure has been optimised for use in MD?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;If a successfully optimization has being reached, you will have the direct information below in your output file.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Just a remainder: the full optimization will depends on two parameters, the number of steps in the geometry moves and the threshold on the energy for the self consistent field (SCF).        &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;     Item               Value     Threshold  Converged?&#xA;     Maximum Force            0.000022     0.000450     YES&#xA;     RMS     Force            0.000003     0.000300     YES&#xA;     Maximum Displacement     0.001224     0.001800     YES&#xA;     RMS     Displacement     0.000305     0.001200     YES&#xA; Predicted change in Energy=-4.458789D-09&#xA; Optimization completed.&#xA;    -- Stationary point found.&#xA;                           ----------------------------&#xA;                           !   Optimized Parameters   !&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;For your first question:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;What are the parameters that need to be calculated to design the structure of a molecule?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;The &lt;a href=&quot;https://materials.stackexchange.com/a/1133/24&quot;&gt;answer&lt;/a&gt; from @CharlieCrown is pretty much what you need to do/know.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-05-30T19:10:12.430" LastActivityDate="2020-05-30T19:10:12.430" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1139" PostTypeId="1" AcceptedAnswerId="1149" CreationDate="2020-05-30T11:42:31.867" Score="14" ViewCount="206" Body="&lt;p&gt;Assume that we have a cube file that contains &lt;code&gt;Ni * Nj * Nk&lt;/code&gt; points, and an origin at &lt;code&gt;0, 0, 0&lt;/code&gt;, where are the data points actually located?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Let's say the grid spacing along each direction is &lt;code&gt;di, dj, dk&lt;/code&gt; in crystal coordinates (so &lt;code&gt;di = 1 / (Ni - 1)&lt;/code&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Are the data points located at &lt;code&gt;0, di, 2 * di, ..., ... Nx * di&lt;/code&gt; or &lt;code&gt;0.5 * di, 1.5 * di, ..., (Nx + 0.5) * di&lt;/code&gt; (and correspondingly for other axes)? Meaning, is the sampled data &lt;strong&gt;at&lt;/strong&gt; the origin and corresponding gridpoints, or are they &lt;strong&gt;between&lt;/strong&gt; the gridpoints, similar to a mean value for &lt;strong&gt;voxels&lt;/strong&gt;?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt; (that may be useful, but don't answer the question above definitively):&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://paulbourke.net/dataformats/cube/&quot; rel=&quot;noreferrer&quot;&gt;http://paulbourke.net/dataformats/cube/&lt;/a&gt; A good exposition about the cube file format.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/io/cube.py#L69&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/blob/master/ase/io/cube.py#L69&lt;/a&gt; ASE's cube file reader.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://h5cube-spec.readthedocs.io/en/latest/cubeformat.html&quot; rel=&quot;noreferrer&quot;&gt;https://h5cube-spec.readthedocs.io/en/latest/cubeformat.html&lt;/a&gt; Another attempt at the specs of the cube file format.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="512" LastEditorUserId="5" LastEditDate="2020-05-30T14:46:33.183" LastActivityDate="2020-05-31T09:43:51.623" Title="What is the precise location of the grid points/voxels in a Gaussian .cube file?" Tags="|software|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1140" PostTypeId="2" ParentId="757" CreationDate="2020-05-30T12:08:06.560" Score="4" Body="&lt;p&gt;You can start from the experimental CIFs for each structure ZnO and MgZnO.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Then, using a software that allows you to manipulate the structures, you can generate a supercell, make cuts and convert the symmetry crystal to a molecular system. You will end with two data files, one for each system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Using the same software you can create a new system using both the data files from the previous step.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I know, for sure, that &lt;a href=&quot;https://www.3dsbiovia.com/products/collaborative-science/biovia-materials-studio/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Material Studio&lt;/a&gt; and &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumATK&lt;/a&gt; can do this task (but they are too expensive to buy just for that). &lt;a href=&quot;https://atomsk.univ-lille.fr/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomsk&lt;/a&gt;, &lt;a href=&quot;https://sourceforge.net/projects/cif2cell/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CIF2Cell&lt;/a&gt;, and &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/src/master/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nanocut&lt;/a&gt; can help to generate the final data files with the supercells.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A note: if using the final structure for DFT calculation, it will not work as a heterostrucure/heterojuntion. It will be seeing  by WEIN2k (or any other code) as a single structure. To study as a heterostrucure/heterojuntion you can determine the electronic properties of each system, and them, using the band off set theory, simulate the band structure for the heterostrucure/heterojuntion.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-05-30T12:08:06.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1141" PostTypeId="1" CreationDate="2020-05-30T13:00:04.913" Score="15" ViewCount="941" Body="&lt;h2&gt;&lt;strong&gt;Introduction&lt;/strong&gt;&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;It is know that the entropy of a system can be calculated using the formula (1):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{eq:entropy_Boltz}&#xA;S = {k_B}\ln \Omega\tag1&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt; is the Boltzmann constant, &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; is the number of microstates&#xA;of the system and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is its entropy. This equation is one of the fundamental&#xA;equations of Statistical Mechanics. Since &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; represents the number of&#xA;microstates of the system, the more microstates, the greater the disorder of&#xA;the system and therefore, the greater the entropy. One of the problems in&#xA;using equation \eqref{eq:entropy_Boltz} is the need to know the number of&#xA;microstates of the system. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Instead of expression \eqref{eq:entropy_Boltz}, Oganov and Valle &lt;sup&gt;[1]&lt;/sup&gt; proposed an expression for the&#xA;calculation of a quasi-entropy representing the structure disorder for a crystal:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{eq:quasi-entropy}&#xA;S_{str} =  - \sum\limits_A {\frac{{{N_A}}}{N}}\left\langle\ln (1 -&#xA;{F_{{A_i}{A_j}}})\right\rangle&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; represents the chemical species in the structure, &lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt; is the&#xA;number of atoms of the chemical species &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the total number of&#xA;atoms, and &lt;span class=&quot;math-container&quot;&gt;$F_{{A_i}{A_j}}$&lt;/span&gt; is the distance between the fingerprints of sites&#xA;&lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; of the chemical species &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;. The fingerprints of each structure&#xA;can be calculated as&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\label{eq:fingerprints}&#xA;{F_{{A_i}B}} =  - \sum\limits_{{B_j}} {\left\{ {\frac{{\delta (R - {R_{ij}})}}{{4\pi {R_{ij}}^2({N_B}/V)\Delta }}} \right\}}  - 1&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is a parameter representing the maximum distance between atoms,&#xA;&lt;span class=&quot;math-container&quot;&gt;$R_{ij}$&lt;/span&gt; is the distance between the sites &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$N_B$&lt;/span&gt; is the number&#xA;of atoms of the chemical species &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the volume of the structure, and&#xA;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; is another parameter associated with the distance between pairs of&#xA;structures &lt;sup&gt;[1]&lt;/sup&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Using this for molecules imply you have to create a pseudo crystal with your system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the other hand, the entropy associated with of bit string can be calculated using the &lt;a href=&quot;https://en.wiktionary.org/wiki/Shannon_entropy&quot; rel=&quot;noreferrer&quot;&gt;Shannon Entropy&lt;/a&gt;. A modification of it was proposed by Grenville J. Croll and called BiEntropy &lt;sup&gt;[2]&lt;/sup&gt;. In this case, it is necessary to use binary fingerprints of molecules.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;The problem&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My systems consist on randomly decorate a nanostructure with organic groups like &lt;span class=&quot;math-container&quot;&gt;$\ce{-OH}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{-COOH}$&lt;/span&gt;, then select one (using the entropy as criteria) and run the calculations with it (&lt;a href=&quot;https://doi.org/10.1016/j.apsusc.2017.07.162&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; is an example of the type of system I am talking about).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Is there a way to calculate the conformational (disorder) entropy of a molecule?&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1] A.R. Oganov, M. Valle, How to quantify energy landscapes of solids, &lt;a href=&quot;https://doi.org/10.1063/1.3079326&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 130 (2009) 104504&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[2] G.J. Croll, BiEntropy - The Approximate Entropy of a Finite Binary String, &lt;a href=&quot;https://arxiv.org/abs/1305.0954&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1305.0954 [cs.OH]&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="35" LastEditDate="2020-05-30T13:32:08.510" LastActivityDate="2020-05-30T14:15:13.310" Title="How to calculate the conformational entropy of a molecule?" Tags="|entropy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1142" PostTypeId="2" ParentId="1141" CreationDate="2020-05-30T14:15:13.310" Score="10" Body="&lt;p&gt;&lt;strong&gt;tldr, Extensively sample the potential energy surface of the molecule, then Boltzmann-weight the relative energies. The CREST tool is useful.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nice to see this question as I'm writing / editing a paper on the conformational entropy of molecules.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There's already a question about the &lt;a href=&quot;https://materials.stackexchange.com/a/921/30&quot;&gt;translational and rotational entropy&lt;/a&gt; of molecules. For those, you optimize a geometry, then calculate from the molecular mass and moments of inertia.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Similarly, one gets the vibrational entropy under the rigid rotor approximation by calculating the vibrational modes from the Hessian and thus the vibrational partition function.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These procedures, though, start from one conformer geometry. For any molecule with conformational degrees of freedom, there are likely to be multiple minima.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In principal, you could run molecular dynamics (even &lt;em&gt;ab initio&lt;/em&gt; MD) for a long time, collect all the geometries, and Boltzmann weight the relative energies. Unfortunately, there's no guarantee that &quot;a long time&quot; is enough to capture all the thermally-accessible minima.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There are a few more practical methods at the moment:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Generate an extensive number of conformers using your favorite tool, e.g. &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/3DStructureGen/multipleconformers.html&quot; rel=&quot;noreferrer&quot;&gt;confab&lt;/a&gt; or &lt;a href=&quot;https://doi.org/10.1021/acs.jcim.5b00654&quot; rel=&quot;noreferrer&quot;&gt;ETKDG-RDKit&lt;/a&gt; etc. then use QM to minimize and rank relative energies.&lt;/li&gt;&#xA;&lt;li&gt;Use Grimme's &lt;a href=&quot;https://github.com/grimme-lab/crest&quot; rel=&quot;noreferrer&quot;&gt;CREST program&lt;/a&gt; &lt;a href=&quot;https://doi.org/10.1039/C9CP06869D&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Phys. Chem. Chem. Phys.&lt;/em&gt;, &lt;strong&gt;2020&lt;/strong&gt;, 22, 7169-7192.&lt;/a&gt; to sample using an iterative meta-dynamics method using the GFN1 / GFN2 semiempirical methods.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;The latter will directly calculate conformational entropies of the resulting ensemble through Boltzmann weighting and degeneracies.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, you might get output like this:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;T /K                                  :   298.15&#xA;E lowest                              :   -43.34438&#xA;ensemble average energy (kcal)        :    0.028&#xA;ensemble entropy (J/mol K, cal/mol K) :   13.834    3.306&#xA;ensemble free energy (kcal/mol)       :   -0.986&#xA;population of lowest in %             :   79.407&#xA; number of unique conformers for further calc            3&#xA;   1       0.000&#xA;   2       0.006&#xA;   3       2.879&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;CREST is time-consuming, and in principal, you should also use QM minimization and re-ranking relative energies.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-05-30T14:15:13.310" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1143" PostTypeId="2" ParentId="1126" CreationDate="2020-05-30T16:03:57.170" Score="9" Body="&lt;p&gt;I won't go over what Charlie Crown already described in his answer, but if you don't have experimental data, you can try starting off with the experimental structure of a similar compound that has the same crystal structure (i.e. ZrO2 and HfO2). If there are several options, try them and choose the relaxation that gives you the lowest energy. Just to add a quick anecdote, I've relaxed a single adsorbate atom on top of a slab structure, and the initial position had a very strong effect on the final relaxed position of both the adsorbate atom and the elastic distortions beneath the adsorbate. Try multiple arrangements!&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-05-30T16:03:57.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1144" PostTypeId="1" AcceptedAnswerId="1145" CreationDate="2020-05-30T16:59:01.167" Score="10" ViewCount="1435" Body="&lt;p&gt;I'm new to DFT.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Does the DFT take into account the spin-orbit interaction?&#xA;On the one hand, this is a relativistic effect, perhaps DFT does not take it into account.&#xA;However, on the other hand, I read that DFT is an extremely accurate method and the error of this method lies only in the inaccuracy of the exchange-correlation potential.&lt;/p&gt;&#xA;" OwnerUserId="663" LastEditorUserId="5" LastEditDate="2020-05-30T18:03:05.737" LastActivityDate="2020-11-12T16:18:59.333" Title="Spin–orbit interaction with DFT" Tags="|density-functional-theory|relativistic|spin-orbit-coupling|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1145" PostTypeId="2" ParentId="1144" CreationDate="2020-05-30T18:01:53.923" Score="15" Body="&lt;p&gt;There are options to include spin-orbit coupling in DFT. In general, there are two ways to do it:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Solve Dirac's relativistic equation for the electrons&lt;/li&gt;&#xA;&lt;li&gt;Incorporate relativistic effects through the Pseudopotential&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Most DFT codes employ (2) as it is easier. There are well tested and readily available 'fully-relativistic' pseudopotentials for LDA and GGA available now.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the second part of the question, it depends on what you want to calculate.  KS-DFT for example, cannot predict optical properties faithfully since it is a strictly ground-state method. In fact, the accuracy of DFT is more nuanced than you think - It depends on a variety of factors including the exchange functional used. One functional is not unequivocally better than another - Check &lt;a href=&quot;https://materials.stackexchange.com/questions/847/is-lda-better-than-gga-for-lattice-constants&quot;&gt;this post&lt;/a&gt; for a comparison of LDA vs GGA in the context of elastic constants. Another example I can think of is in the context of highly-correlated materials. Kohn-Sham DFT predicts some transition-metal oxides such as FeO and ZnO incorrectly as metals. The inclusion of a modest Hubbard 'U' faithfully treats the highly localized 'd' orbitals in these materials, opening up a band gap. The properties predicted in this 'LDA(or GGA)+U' scheme are found to agree well with experiments.&lt;/p&gt;&#xA;&lt;p&gt;The most commonly used exchange functionals such as LDA and GGA are very well known to underestimate electronic band gap due to a spurious self-interaction in partially occupied orbitals that is not exactly cancelled out by the terms in the exchange correlation functional. This causes occupied bands to over-delocalize, and push them up in energy, hence reducing band gap. To get an accurate band gap, you would need to do the actual quasiparticle calculation - via the GW-BSE method. However, various 'hybrid' functionals have been developed in the past years to give a more reliable estimate of the band gap. However these methods are semi-empirical, and hence strictly speaking, you don't know what band gap it gives you.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="403" LastEditDate="2020-11-12T16:18:59.333" LastActivityDate="2020-11-12T16:18:59.333" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1146" PostTypeId="2" ParentId="656" CreationDate="2020-05-30T19:01:57.140" Score="6" Body="&lt;p&gt;Hylleraas wavefunctions tend only to be used for systems with up to 3 electrons. The reason for this is because the integrals have only been worked out analytically for up to 3 electrons, and they would be far too slow to do numerically. People have talked about using Hylleraas wavefunctions for 4 electrons, but when you ask them to show you results on real systems (for example the Be atom), the results are &lt;strong&gt;at least 12 orders of magnitude worse&lt;/strong&gt; than what we have achieved for 3 electron systems, and about 4 orders of magnitude worse than what is achieved with methods based on non-Hylleraas wavefunctions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Specifically, from Table I of &lt;a href=&quot;https://github.com/HPQC-LABS/Carbon/blob/master/C.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper of mine on the carbon atom&lt;/a&gt;, you can see that the state-of-the art lowest variational energy for Be, is not obtained using a Hylleraas wavefunction but with an &quot;explicitly correlated Gaussian&quot;. Nakatsuji has used Hylleraas-like wavefunctions for Be, but to the best of my knowledge, never achieved the correct energy to micro-Hartree precision, whereas explicitly correlated Gaussians have managed to achieve nano-Hartree precision almost a decade ago. Part of Table I from that paper is repeated here:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{c l l l}&#xA;\textrm{He} &amp;amp;  -2.903 724 377 034 119 598 311 159 245 194 404 446 696 925 309 838  &amp;amp; \textrm{Hylleraas-Log} &amp;amp; (2006)\\&#xA;\textrm{Li} &amp;amp;  -7.478 060 323 910 134 843 &amp;amp; \textrm{Hylleraas} &amp;amp; (2017)\\&#xA;\textrm{Be} &amp;amp;  -14.667 3564949 &amp;amp; \textrm{ECG} &amp;amp; (2013)\\&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;So while it is theoretically possible to use a 4-electron Hylleraas wavefunction, the necessary integrals have not yet been worked out analytically, and therefore no one has achieved any 4-electron energy to better accuracy than achieved using other methods (such as ECGs).&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So now you may ask what the largest system is, that has been treated successfully using ECGs? ECGs have the advantage that the integrals can be calculated analytically. Unfortunately the answer is still &lt;strong&gt;5 electrons&lt;/strong&gt;, which was done by Puchalski &lt;em&gt;et al.&lt;/em&gt; (the same author that did the Be atom in 2013) in 2015. I spoke to Puchalski many times about this, and while he did actually do some calculations on the 6-electron carbon atom, he did not obtain any results that he found to be worth publishing, although my 2018 paper on the carbon atom linked above (which used an aug-cc-pCV8Z basis set) inspired him to consider returning to the carbon atom project and publish something better than what I achieved (but that has not been completed yet). There has indeed been a 2019 paper which calculated the energy of the carbon atom using ECGs, but it did not achieve an energy lower than mine with the non-explicitly correlated aug-cc-pCV8Z basis set. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nakatsuji has used Hylleraas-type wavefunctions for much larger numbers of electrons, but to the best of my knowledge, the results are not state-of-the-art for any of those systems.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Summary:&lt;/h2&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Explicitly correlated &lt;strong&gt;Hylleraas&lt;/strong&gt; wavefunctions have achieved state-of-the art energies up to 3e.&lt;/li&gt;&#xA;&lt;li&gt;Explicitly correlated &lt;strong&gt;Gaussian&lt;/strong&gt; wavefunctions have achieved state-of-the art energies up to 5e.&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;However ECGs will likely soon achieve state-of-the-art energies for 6e&lt;span class=&quot;math-container&quot;&gt;$^-$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;ECGs will &lt;em&gt;not&lt;/em&gt; likely achieve state-of-the-art energies for 7e&lt;span class=&quot;math-container&quot;&gt;$^-$&lt;/span&gt; for several more years without a breakthrough change in the algorithm or hardware.&lt;/li&gt;&#xA;&lt;/ul&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Explcitly correlated wavefunctions do not tend to benefit from &lt;em&gt;error cancellation&lt;/em&gt; as much as traditional single-particle basis sets like those from the Dunning family. Dunning prevails.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-05-30T19:01:57.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1147" PostTypeId="1" AcceptedAnswerId="1191" CreationDate="2020-05-30T21:56:32.317" Score="25" ViewCount="723" Body="&lt;p&gt;In classical density functional theory, one traditionally calculates the chemical potential by taking the variational derivative,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\mu_{i} = \frac{\delta F}{\delta \rho_{i}}\tag{1}&#xA;\end{equation}&lt;/span&gt;&#xA;of the Helmholtz free energy&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;F[\rho] = \int d\textbf{r} f(\rho, \nabla \rho, ...) \textrm{.}\tag{2}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, this is not directly analogous to the chemical potential in classical thermodynamics. In the latter theory, the chemical potential is defined as a partial derivative with respect to the number of moles,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\hat{\mu}_{i} = \frac{\partial A}{\partial n_{i}}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is the homogeneous Helmholtz free energy analogous to &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;.&#xA;Importantly, &lt;span class=&quot;math-container&quot;&gt;$n_{i}$&lt;/span&gt; is an &lt;em&gt;extensive&lt;/em&gt; quantity (e.g. &lt;span class=&quot;math-container&quot;&gt;$n_{i} = \rho_{i} V$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the system volume). This means that &lt;span class=&quot;math-container&quot;&gt;$\mu_{i}$&lt;/span&gt;, defined in DFT is actually analogous to the derivative&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\mu_{i} = \frac{\partial A}{\partial \rho_{i}}\tag{3}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How then does one obtain the actual analogue,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\hat{\mu}_{i} = \frac{\delta F}{\delta n_{i}}\tag{4}&#xA;\end{equation}&lt;/span&gt;&#xA;to the traditional chemical potential?&#xA;Is this generalization correct? If so, how does one go about computing such a quantity when the number of moles &lt;span class=&quot;math-container&quot;&gt;$n_{i}$&lt;/span&gt; is now itself a functional of the density,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;n_{i} = \int d\textbf{r} \rho_{i}(\textbf{r})\tag{5}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Aside:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is clear that &lt;span class=&quot;math-container&quot;&gt;$\partial A/\partial \rho_{i}$&lt;/span&gt; is related to the difference between chemical potentials for an incompressible, multicomponent system, e.g. &lt;a href=&quot;http://dx.doi.org/10.1103/PhysRevE.83.061602&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dx.doi.org/10.1103/PhysRevE.83.061602&lt;/a&gt;. Because of this, it is sometimes called an &amp;quot;exchange&amp;quot; chemical potential, e.g. &lt;a href=&quot;https://doi.org/10.1039/C6SM02839J&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1039/C6SM02839J&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;There is also a connection between the exchange chemical potentials and the osmotic pressure, &lt;span class=&quot;math-container&quot;&gt;$\pi = \partial A/\partial V$&lt;/span&gt;. It is not clear to me how one can calculate the osmotic pressure from a functional either, since it is also an extensive quantity.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Related:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://math.stackexchange.com/q/3016507/&quot;&gt;https://math.stackexchange.com/q/3016507/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://math.stackexchange.com/q/3697883/&quot;&gt;https://math.stackexchange.com/q/3697883/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="780" LastEditorUserId="5" LastEditDate="2020-12-28T02:05:21.983" LastActivityDate="2020-12-28T02:05:21.983" Title="How do you calculate the &quot;true&quot; chemical potential in classical density functional theory?" Tags="|density-functional-theory|mathematical-modeling|statistical-thermodynamics|variational-principle|from-phys-se|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1148" PostTypeId="2" ParentId="109" CreationDate="2020-05-30T22:12:24.230" Score="25" Body="&lt;p&gt;This is a bit late, but I would say the short answer to your direct question is: technically no, there is no &quot;standard&quot; reliable way, since there are several approaches to determining &lt;em&gt;U&lt;/em&gt; self-consistently from first principles. By self-consistently I mean a first-principles &lt;em&gt;U&lt;/em&gt; is calculated, which when applied changes the electronic structure, so a new &lt;em&gt;U&lt;/em&gt; is calculated and applied, and so on, until the value of &lt;em&gt;U&lt;/em&gt; has converged. However, these methods are each fairly reliable and often give similar results. This is an area I've worked in a bit so I'll summarize a few methods here, some ongoing work in this area, some resources for further reading and practical application, and some recommended practices. This is in the context of my experience in solid-state periodic DFT but in principle it should apply to any DFT calculation where these methods are possible and appropriate.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;1. Hubbard &lt;em&gt;U&lt;/em&gt; and Determination of &lt;em&gt;U&lt;/em&gt; from First-Principles&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;a. Basic Concepts&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The basic idea of DFT+&lt;em&gt;U&lt;/em&gt; is that we are &lt;em&gt;replacing&lt;/em&gt; the treatment of some of the charge density with a Hubbard correction term, where otherwise it would be treated by the chosen DFT exchange-correlation (XC) functional. This correction, in practice, is usually a screened Hartree-Fock-like term as opposed to being more reminiscent of the actual Hubbard model. A double-counting term is subtracted to remove the estimated contribution from the original XC functional. However, this term is not uniquely defined, so the choice of double-counting correction will affect the results. Most calculations use a fully-localized limit, most appropriate for strongly localized states.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;DFT+&lt;em&gt;U&lt;/em&gt; has the effect of introducing discontinuity in the total energy as a function of electrons added to the system--the rationale behind why it can improve the prediction of band gaps (if this is unclear, read on the band gap problem in DFT). In fact, the value of &lt;em&gt;U&lt;/em&gt; can be defined in terms of this unphysical curvature present in LDA and GGA. A more intuitive interpretation of DFT+&lt;em&gt;U&lt;/em&gt; can be illustrated by the form of the rotationally-invariant &quot;simplified&quot; correction (reducing explicit &lt;em&gt;U&lt;/em&gt; and &lt;em&gt;J&lt;/em&gt; terms to an effective &lt;span class=&quot;math-container&quot;&gt;$U_{\text{eff}}=U-J$&lt;/span&gt;) developed by &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.57.1505&quot; rel=&quot;noreferrer&quot;&gt;Dudarev &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; and &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.71.035105&quot; rel=&quot;noreferrer&quot;&gt;Cococcioni &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt;, where the Hubbard energy is minimized when orbitals in the Hubbard manifold are either completely &lt;em&gt;full&lt;/em&gt; or &lt;em&gt;empty&lt;/em&gt;, i.e. no partial occupations due to hybridization. This means there is a tendency to decrease delocalization in the calculation (compensating for how GGA, for example, tends to over-delocalize).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A more recent development is &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/22/5/055602&quot; rel=&quot;noreferrer&quot;&gt;DFT+&lt;em&gt;U&lt;/em&gt;+&lt;em&gt;V&lt;/em&gt;&lt;/a&gt;, which includes inter-site interaction &lt;em&gt;V&lt;/em&gt; and can improve the description of covalently-bonded materials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I recommend reading this &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.24521&quot; rel=&quot;noreferrer&quot;&gt;excellent review article&lt;/a&gt; by Himmetoglu &lt;em&gt;et al.&lt;/em&gt; for an overview of DFT+&lt;em&gt;U&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;b. Constrained Random Phase Approximation&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The constrained random phase approximation (cRPA), developed by &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.70.195104&quot; rel=&quot;noreferrer&quot;&gt;Aryasetiawan &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt;, is used to find a frequency-dependent &lt;em&gt;U&lt;/em&gt; that can be used in DFT+DMFT, but in the static limit it can be used in DFT+&lt;em&gt;U&lt;/em&gt;. Essentially, once you have chosen how to define the localized and delocalized states for your system, the Coulomb interaction between the localized states is calculated while including screening effects from the delocalized states. The &quot;constrained&quot; comes from the fact that only the Hartree term is used to calculate the dielectric function used for screening, for simplicity (as opposed to both Hartree and exchange-correlation). I personally have not used cRPA to calculate values of &lt;em&gt;U&lt;/em&gt;, so check the reference paper and its citations for further reading on the topic.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;c. Linear Response&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The linear response method by &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.71.035105&quot; rel=&quot;noreferrer&quot;&gt;Cococcioni &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; defines &lt;em&gt;U&lt;/em&gt; such that when applied the unphysical curvature in the total energy vs. the number of electrons present in the system is eliminated. In exact DFT this is a piecewise-continuous linear function, while in approximate LDA and GGA DFT it is a smooth curved function. &lt;em&gt;Constrained&lt;/em&gt; DFT was an approach to correct this by varying the Hubbard orbital occupations, and determining the corresponding change in energy. Linear response approaches this in a more convenient way for most DFT codes, by applying a varying perturbative potential and then measuring the resulting change in occupation. Once this is done for several perturbations, &lt;em&gt;U&lt;/em&gt; can be calculated (see resources section for how to do this). This approach typically requires &lt;em&gt;U&lt;/em&gt; to be calculated in a supercell, to prevent the Hubbard states from being affected by periodic images of the perturbation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;d. Density Functional Perturbation Theory&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A very nice recent development in the calculation of &lt;em&gt;U&lt;/em&gt; is from &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.98.085127&quot; rel=&quot;noreferrer&quot;&gt;Timrov, Mazari and Cococcioni&lt;/a&gt;. They reformulate the linear response method from a single perturbation in a supercell to a sum of perturbations in the primitive cell. I'm not as familiar with the theory here, but it's implemented in the new hp.x code included with Quantum Espresso. Very interesting.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;d. ACBN0&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.5.011006&quot; rel=&quot;noreferrer&quot;&gt;ACBN0&lt;/a&gt; (named for the authors) takes inspiration from previous work by &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.76.155123&quot; rel=&quot;noreferrer&quot;&gt;Mosey and Carter&lt;/a&gt;, and explicitly calculates &lt;em&gt;U&lt;/em&gt; from a Hartree-Fock-like interaction between the Hubbard orbitals of interest. Some screening-like reduction of the interaction is introduced by renormalizing the occupations of the Kohn-Sham orbitals according to their projectability on the Hubbard basis--so less-localized states should have a drastically reduced magnitude of &lt;em&gt;U&lt;/em&gt;. This method also allows calculation of many site-dependent &lt;em&gt;U&lt;/em&gt; values from a single scf calculation. In theory this can be incorporated into the self-consistency loop of the DFT calculation, but current implementations are a post-processing step. It can be used in the &lt;a href=&quot;http://aflowlib.org/src/paoflow/&quot; rel=&quot;noreferrer&quot;&gt;PAOFLOW&lt;/a&gt; and &lt;a href=&quot;http://aflowlib.org/src/aflowpi/index.html&quot; rel=&quot;noreferrer&quot;&gt;AFLOW&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;&lt;/a&gt; codes. It's also been &lt;a href=&quot;http://arxiv.org/abs/1911.10813&quot; rel=&quot;noreferrer&quot;&gt;recently demonstrated&lt;/a&gt; with DFT+&lt;em&gt;U&lt;/em&gt;+&lt;em&gt;V&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;2. Resources&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;a. References for Implementations of Hubbard &lt;em&gt;U&lt;/em&gt; Corrections&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.52.R5467&quot; rel=&quot;noreferrer&quot;&gt;Rotationally-invariant implementation with explicit &lt;em&gt;U&lt;/em&gt; and &lt;em&gt;J&lt;/em&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.57.1505&quot; rel=&quot;noreferrer&quot;&gt;Simplified rotationally-invariant scheme (&lt;span class=&quot;math-container&quot;&gt;$U_{\text{eff}}$&lt;/span&gt;)&lt;/a&gt; (also &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.71.035105&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.115108&quot; rel=&quot;noreferrer&quot;&gt;Simplified scheme re-introducing explicit &lt;em&gt;J&lt;/em&gt; term&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;b. Future Possibilities&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;A limitation of the simplified implementations of DFT+&lt;em&gt;U&lt;/em&gt; is that the Hubbard orbitals are treated in a way that assumes some spherical symmetry (i.e. very close to true atomic orbitals). In compounds that have significant crystal field splitting this is not technically appropriate. Some early work used different &lt;em&gt;U&lt;/em&gt; values for &lt;span class=&quot;math-container&quot;&gt;$t_{2g}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$e_{g}$&lt;/span&gt; electrons in perovskite oxides, for example. The exchange term &lt;em&gt;J&lt;/em&gt; is also treated in an average way, which worsens treatment of materials where the localization depends on Hund's rule magnetism. It could be very interesting to determine &lt;em&gt;U&lt;/em&gt;, &lt;em&gt;J&lt;/em&gt; and &lt;em&gt;V&lt;/em&gt; for specific subsets of the Hubbard orbitals. This may provide better treatment of orbitally-ordered materials, or materials where some of the &lt;em&gt;d&lt;/em&gt; electrons form an itinerant band (and should have a much smaller &lt;em&gt;U&lt;/em&gt; value than the localized states, and may also participate in screening).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;c. Practical Information/Tutorials&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Prof. Heather Kulik at MIT has some nice tutorials and slides on DFT+U:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://hjkgrp.mit.edu/content/review-dftu&quot; rel=&quot;noreferrer&quot;&gt;Intro to DFT+&lt;em&gt;U&lt;/em&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://hjkgrp.mit.edu/content/calculating-hubbard-u&quot; rel=&quot;noreferrer&quot;&gt;Calculating Hubbard &lt;em&gt;U&lt;/em&gt;&lt;/a&gt;, &lt;a href=&quot;http://hjkgrp.mit.edu/content/hubbard-u-multiple-sites&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;U&lt;/em&gt; for multiple sites&lt;/a&gt;, &lt;a href=&quot;http://hjkgrp.mit.edu/content/calculating-hubbard-u-periodic-systems&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;U&lt;/em&gt; for periodic systems&lt;/a&gt;, &lt;a href=&quot;http://hjkgrp.mit.edu/content/readers-choice-dftu&quot; rel=&quot;noreferrer&quot;&gt;calculating &lt;em&gt;U&lt;/em&gt; and &lt;em&gt;J&lt;/em&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://hjkgrp.mit.edu/content/troubleshooting-common-problems-dftu&quot; rel=&quot;noreferrer&quot;&gt;Troubleshooting common problems&lt;/a&gt;, &lt;a href=&quot;http://hjkgrp.mit.edu/content/right-hubbard-u-any-element&quot; rel=&quot;noreferrer&quot;&gt;the right &lt;em&gt;U&lt;/em&gt; for any element&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://hjkgrp.mit.edu/content/including-hubbard-u-variations-dftur&quot; rel=&quot;noreferrer&quot;&gt;Including Hubbard &lt;em&gt;U&lt;/em&gt; variations with DFT+&lt;em&gt;U&lt;/em&gt;(&lt;strong&gt;R&lt;/strong&gt;)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;h2&gt;3. Recommended Practices&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Values of &lt;em&gt;U&lt;/em&gt; are in general &lt;em&gt;non-transferable&lt;/em&gt;. It is poor practice to take a literature value of &lt;em&gt;U&lt;/em&gt; when the work does not use the same functional, DFT+&lt;em&gt;U&lt;/em&gt; implementation, material (especially drastically different chemical environments), Hubbard basis, or even pseudopotential that you are using. This is especially true for values of &lt;em&gt;U&lt;/em&gt; chosen empirically for a different property than the one you're studying.&lt;/li&gt;&#xA;&lt;li&gt;Calculate &lt;em&gt;U&lt;/em&gt; self-consistently whenever possible. It's becoming easier and easier to do this.&lt;/li&gt;&#xA;&lt;li&gt;Think carefully about which atoms and states you want to apply &lt;em&gt;U&lt;/em&gt; to. It's sometimes useful to apply &lt;em&gt;U&lt;/em&gt; to oxygen &lt;em&gt;p&lt;/em&gt; states in addition to metal &lt;em&gt;d&lt;/em&gt; states in oxides, for example.&lt;/li&gt;&#xA;&lt;li&gt;DFT+&lt;em&gt;U&lt;/em&gt; often introduces local minima in the energy, related to the occupations of your Hubbard atom states. This seems especially pronounced in spin-polarized calculations. Manually setting the starting occupation matrix to what you are trying to study can help converge to the appropriate energy minimum. This is useful when trying to study different possible spin states on a metal cation, for example. It can also help speed up convergence, in my experience.&lt;/li&gt;&#xA;&lt;li&gt;If you are choosing &lt;em&gt;U&lt;/em&gt; empirically, think about whether you are getting the &quot;right&quot; answer for the wrong reason. Band gaps can be correct at the expense of a realistic picture of electronic structure, not to mention other quantities like lattice parameters, formation enthalpy, etc. Compare your calculations with higher levels of theory in the literature when possible. &lt;/li&gt;&#xA;&lt;li&gt;Current DFT+&lt;em&gt;U&lt;/em&gt; implementations are not, to my knowledge, variational with respect to the total energy. So the optimal value of &lt;em&gt;U&lt;/em&gt; will not typically result in the lowest calculated total energy. To make comparisons between different calculations, you need to be using the same values of &lt;em&gt;U&lt;/em&gt; in both calculations--unless you specifically account for the change in the energy surface with respect to &lt;em&gt;U&lt;/em&gt; (as in &lt;a href=&quot;https://scitation.aip.org/content/aip/journal/jcp/135/19/10.1063/1.3660353&quot; rel=&quot;noreferrer&quot;&gt;DFT+&lt;em&gt;U&lt;/em&gt;(&lt;strong&gt;R&lt;/strong&gt;)&lt;/a&gt; or &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.4916823&quot; rel=&quot;noreferrer&quot;&gt;DFT+&lt;em&gt;U&lt;/em&gt;(V)&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-05-31T04:47:52.117" LastActivityDate="2020-05-31T04:47:52.117" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1149" PostTypeId="2" ParentId="1139" CreationDate="2020-05-31T09:43:51.623" Score="10" Body="&lt;p&gt;The canonical source is probably &lt;a href=&quot;https://gaussian.com/cubegen/&quot; rel=&quot;noreferrer&quot;&gt;Gaussian's user documentation&lt;/a&gt; according to which the cube file defines an initial point &lt;span class=&quot;math-container&quot;&gt;$(x_0, y_0, z_0)$&lt;/span&gt;, as well as three step directions &lt;span class=&quot;math-container&quot;&gt;$(x_i, y_i, z_i)$&lt;/span&gt; and the corresponding number of steps &lt;span class=&quot;math-container&quot;&gt;$N_i$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$i=1,2,3$&lt;/span&gt;. The data are computed &lt;em&gt;at&lt;/em&gt; the gridpoints, since averaging would make grid data evaluation much more costly, and at the limit of an infinitely fine grid the two results coincide.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-31T09:43:51.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1150" PostTypeId="2" ParentId="113" CreationDate="2020-05-31T09:52:11.480" Score="11" Body="&lt;p&gt;The general question on the accuracy of density functionals for transition metal compounds is highly ambigious due to the effect of static correlation, for which there is no solution at the moment.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As to the simpler question on well-behaving TM compounds with organic ligands, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.9b01546&quot; rel=&quot;noreferrer&quot;&gt;a benchmark study on transition metal reaction barrier heights&lt;/a&gt; found that Head-Gordon's recent functionals are excellent choices, with revTPSS0-D4 also faring well.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-05-31T09:52:11.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1151" PostTypeId="1" AcceptedAnswerId="1239" CreationDate="2020-05-31T18:07:19.333" Score="15" ViewCount="390" Body="&lt;p&gt;I've read in some texts that GW-BSE quasiparticle calculations have only been implemented on Norm-conserving Pseudopotentials (and not Ultra-soft or PAW PPs). Is there a conceptual reason for this? I can't seem to locate a reliable source but &lt;a href=&quot;https://www.attaccalite.com/reasonable-parameters-for-yambo-calculations/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here it is mentioned&lt;/a&gt; that the YAMBO code (used for GW-BSE in conjunction with Quantum Espresso) can only support NCPPs.&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-06-09T04:08:12.893" LastActivityDate="2020-06-09T16:17:40.387" Title="Can GW-BSE quasiparticle calculations only be run on norm-conserving pseudopotentials (NCPPs)? If so, why not?" Tags="|quantum-espresso|pseudopotentials|gpaw|yambo|gw-bse|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1152" PostTypeId="2" ParentId="902" CreationDate="2020-05-31T18:22:29.470" Score="8" Body="&lt;h1&gt;DFTB+&lt;/h1&gt;&#xA;&lt;p&gt;One option is DFTB+. It is free, open source, has been around for more than a couple years now, and has a fairly big community.&lt;/p&gt;&#xA;&lt;p&gt;You are also very lucky, since your question is about the band structure of TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and the &lt;a href=&quot;https://dftbplus-recipes.readthedocs.io/en/stable/basics/bandstruct.html&quot; rel=&quot;noreferrer&quot;&gt;sample input&lt;/a&gt; that DFTB+ provides for band structure calculations is for... TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; :)&lt;/p&gt;&#xA;&lt;p&gt;The following might also be useful:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://dftbplus-recipes.readthedocs.io/en/stable/index.html&quot; rel=&quot;noreferrer&quot;&gt;DFTB+ documentation&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/dftbplus&quot; rel=&quot;noreferrer&quot;&gt;DFTB+ GitHub Organization&lt;/a&gt; (includes links to the Git repositories for the  DFTB+ software, documentation, developer guide, and many other things).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.dftbplus.org/&quot; rel=&quot;noreferrer&quot;&gt;DFTB+ website&lt;/a&gt; (includes a &lt;a href=&quot;http://www.dftbplus.org/about-dftb/features/&quot; rel=&quot;noreferrer&quot;&gt;list of features&lt;/a&gt;, &lt;a href=&quot;http://www.dftbplus.org/download/deprecated/&quot; rel=&quot;noreferrer&quot;&gt;pages for previous versions&lt;/a&gt;, and &lt;a href=&quot;http://www.dftbplus.org/contact-support/&quot; rel=&quot;noreferrer&quot;&gt;ways to contact the community&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5143190&quot; rel=&quot;noreferrer&quot;&gt;Recent paper in the 2020 JCP Special Issue on software&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-05-31T18:22:29.470" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1153" PostTypeId="2" ParentId="1122" CreationDate="2020-06-01T01:47:16.150" Score="15" Body="&lt;p&gt;A little background on why I asked this question: &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have a desktop PC with an AMD Ryzen 5 processor, 4 cores 8 logical threads and 32GB DDR4 RAM. I'm trying to do DFT-GGA calculations on a 2D Xene with hydrogen atoms adsorbed at the surface. I'm using a 4x4 supercell as a model for a total of 32 atoms (16 for X and 16 for H). Without spin-orbit coupling (SOC), the total dynamically allocated RAM required for relaxation and SCF calculations is somewhere in the range of 4-6 GB. When I try to account for SOC, the memory required jumps to around 20 GB, so I'm guessing performing phonon or band calculations would require much much more than 30 GB, and enlarging the cell to 5x5 or 6x6 would require an even greater memory capacity. Not to mention, it would also require more processing power to finish the calculations at a decent amount of time. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;So I checked out Google Colab some more, after seeing the replies to this question. While it looks really possible to install an executable like Quantum Espresso into Google Colab, the free RAM can be boosted only up to 25 GB, which is in my opinion, less RAM than what I would need. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Update/Edit: I actually also found a page which seems to walk you through how to do it: &lt;a href=&quot;https://qiita.com/cometscome_phys/items/a31ab8a4a4f7217a70ff&quot; rel=&quot;noreferrer&quot;&gt;https://qiita.com/cometscome_phys/items/a31ab8a4a4f7217a70ff&lt;/a&gt;. It's in Japanese so I don't understand everything it says but I get the basic gist.&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="347" LastEditDate="2020-06-01T02:06:04.037" LastActivityDate="2020-06-01T02:06:04.037" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1154" PostTypeId="1" AcceptedAnswerId="1155" CreationDate="2020-06-01T06:53:16.667" Score="12" ViewCount="618" Body="&lt;p&gt;As per @user1271772 's suggestion I am asking &lt;a href=&quot;https://chemistry.stackexchange.com/questions/134515/two-electron-integrals-between-1s-sto&quot;&gt;this&lt;/a&gt; question here again.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;I am trying to understand SCF cycle by trying to code up solved example from Quantum Chemistry by Levine (page 443, 5th edition). The problem is stated as:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Do an SCF calculation for the helium-atom ground state using basis set of two 1s STOs with exponent &lt;span class=&quot;math-container&quot;&gt;$\zeta_1$&lt;/span&gt; = 1.45 and &lt;span class=&quot;math-container&quot;&gt;$\zeta_2$&lt;/span&gt;=2.91. [Ref: Roetti and Clementi J. Chem. Phys., 60, 4725 1974]&#xA;  &lt;span class=&quot;math-container&quot;&gt;$\chi_1 = 2\zeta_1^{3/2}e^{-\zeta_1 r}Y^0_0$&lt;/span&gt;, and  &lt;span class=&quot;math-container&quot;&gt;$\chi_2 = 2\zeta_2^{3/2}e^{-\zeta_2 r}Y^0_0$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;One electron integrals are straight forward and I was able to get the correct answer, however I still can't get correct values for two election integral, lets say &lt;code&gt;(11|11)&lt;/code&gt;. Below is my attempt in Octave&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;clear all;&#xA;N=2000;&#xA;zeta1 = 1.45;&#xA;zeta2 = 2.91;&#xA;&#xA;r = linspace(0.000001,10,N)';&#xA;dr = r(2)-r(1);&#xA;chi = @(zetad,x) (2*zetad.^(3/2))*exp(-zetad*x).*x;&#xA;chichi = 0;&#xA;for i =1:N&#xA;    chichi = chichi + dr*(chi(zeta1,r(i))*chi(zeta1,r(i))*chi(zeta1,r')*(chi(zeta1,r)./((r(i)-r) + 0.000001)));&#xA;end&#xA;chichi*dr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;However my values are way off in this case. Can anyone please shed a light on it? Value of &lt;code&gt;(11|11) = 5/8 zeta1 = 0.9062&lt;/code&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Two electron integrals are defined in the Levine book as :&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;(rs|tu) = \int \int \frac{\chi^*_r(1)\chi_s(1)\chi_t^*(2)\chi_u(2)}{r_{12}} dv_1dv_2&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;user @TAR86 from the Chemistry SE suggested that&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;You replaced the 6-fold integration by one in spherical coordinates. Not sure if that can work as easily as you wrote it&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;But I was thinking as the function have no angular dependence, at least in above case, its integral should be really straight forward.&lt;/p&gt;&#xA;" OwnerUserId="785" LastEditorUserId="5" LastEditDate="2020-06-01T15:27:08.407" LastActivityDate="2020-06-01T15:27:08.407" Title="One-center two-electron integrals between 1s STO" Tags="|computational-chemistry|self-consistent-field|integrals|hartree-fock|from-chem-se|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1155" PostTypeId="2" ParentId="1154" CreationDate="2020-06-01T07:55:53.080" Score="13" Body="&lt;p&gt;Your Octave code is trying to do the integral by quadrature, which makes very little sense since it will have a huge problems with the cusp.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since this is a one-center problem, the best approach is to use the Legendre expansion for &lt;span class=&quot;math-container&quot;&gt;$|r_1-r_2|^{-1}$&lt;/span&gt;, which decomposes the interaction into a radial part and an angular part: &lt;span class=&quot;math-container&quot;&gt;$r_{12}^{-1} = \frac {4\pi} {r_&amp;gt;} \sum_{L=0}^\infty \frac 1 {2L+1} \left( \frac {r_&amp;lt;} {r_&amp;gt;} \right)^L \sum_{M=-L}^L Y_L^M (\Omega_1) (Y_L^M (\Omega_2))^*$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You only have &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; orbitals; this means that the angular parts are trivial and only a single term drops out; you're left with the radial integral&#xA;&lt;span class=&quot;math-container&quot;&gt;$\int_0^\infty {\rm d}r r^2 \int_0^\infty {\rm d}r' {r'}^2 \chi_r(r) \chi_s(r) \chi_t(r') \chi_u(r') r_&amp;gt;^{-1} $&lt;/span&gt;&#xA;that you can solve by standard techniques i.e. dividing the integration in two parts for &lt;span class=&quot;math-container&quot;&gt;$r'\leq r$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r'&amp;gt;r$&lt;/span&gt; and then evaluating these integrals separately.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This trick is also what makes fully numerical calculations possible on atoms, see e.g. my recent review in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int J Quantum Chem 119, 19, e25968&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/1902.01431&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1902.01431&lt;/a&gt;) and the application to finite-element calculations on atoms in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.25945&quot; rel=&quot;noreferrer&quot;&gt;Int J Quantum Chem 119, 19, e25945&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/1810.11651&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1810.11651&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-06-01T14:02:18.683" LastActivityDate="2020-06-01T14:02:18.683" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1156" PostTypeId="2" ParentId="1154" CreationDate="2020-06-01T08:23:44.457" Score="9" Body="&lt;p&gt;This can be solved analytically, a complete solution can be found &lt;a href=&quot;http://farside.ph.utexas.edu/teaching/qmech/Quantum/node128.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To refrain from rewriting the entire derivation I will only say that you need to integrate over all 3 dimensional degrees of freedom for both electrons, so TAR86 is correct.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the derivation at the link, the distance between the electrons (&lt;span class=&quot;math-container&quot;&gt;$\mid r_1 - r_2 \mid \equiv r_{12}$&lt;/span&gt;) is better represented in polar coordinates (equation 1196).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Going through the algebra and calculus one can then end up with the correct solution for the Coulomb integral, -5/2 E0. &lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-06-01T08:23:44.457" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1157" PostTypeId="2" ParentId="1125" CreationDate="2020-06-01T10:24:27.573" Score="11" Body="&lt;p&gt;@Susi already provided an excellent answer. I just want to add that for most applications in materials modeling, there is a relatively high overhead for parallelization. Basically, breaking up a problem into smaller and smaller pieces means that you are spending more and more time on communication between the nodes, etc. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Basically, you usually still want individual cores that are pretty fast. If you want to build a cheap hobby cluster yourself, the best option may be to try to get used hardware. A old desktop-class CPU can still be quite useful. Older server-grade stuff could also be really cheap since businesses might essentially be throwing them away. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;You could also try to use &lt;em&gt;diskless nodes&lt;/em&gt;. Finally, the nodes don't need to have full cases, nor do you need proper CPU racks. I know people who have essentially put a &lt;a href=&quot;http://physics.bu.edu/~sandvik/clusters.html&quot; rel=&quot;noreferrer&quot;&gt;bunch of motherboards on cheap wire racks and hooked them all up.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-06-01T10:24:27.573" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1158" PostTypeId="2" ParentId="1116" CreationDate="2020-06-01T10:30:03.053" Score="4" Body="&lt;p&gt;&lt;strong&gt;Speculation:&lt;/strong&gt; If there are not predefined routines in MD for this, you might be able to get some pretty useful results by equilibrating the molecule as usual and then just manually (for example) removing an electron to simulate the molecule being ionized. This may not be super physically realistic, but it might get you some of the answers you need. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-06-01T10:30:03.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1159" PostTypeId="1" CreationDate="2020-06-01T12:50:09.450" Score="1" ViewCount="116" Body="&lt;p&gt;This questions is not directly related to &lt;em&gt;Matter Modeling&lt;/em&gt;, but it is related with the way we share/publish our research.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Let suppose that someone deposited a manuscript in a preprint server.&#xA;Then, he/she send the same manuscript to a Journal and it is accepted. In many journals you have to sign a copyright transfer given the journal the publication/reproduction rights over the whole manuscript (text and images).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, I, as a reader, get access to both, the preprint and the final published paper.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The question is: Can I just use any of the images from the work in my own paper (just as reference, comparison, etc.) citing the source? Isn't there a superposition of rights?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2020-06-26T21:48:50.880" LastActivityDate="2020-06-26T21:48:50.880" Title="Copyright war: preprint servers vs journals transfer" Tags="|education|" AnswerCount="2" CommentCount="4" ClosedDate="2020-06-02T12:18:00.840" ContentLicense="CC BY-SA 4.0" />
  <row Id="1160" PostTypeId="2" ParentId="1159" CreationDate="2020-06-01T13:57:18.193" Score="4" Body="&lt;p&gt;Depending on the license of the preprint you can use the figures from there, yes. Make sure you have checked the corresponding license and the things you need to do when reusing it (most of the times giving appropriate reference and license notes).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note that the final article of the journal might include some edited version of the images (review process), so no guarantee that they are the same. But also remember that the authors might be happier if you cite their final paper, since it will more likely increase their &quot;impact&quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you want to make use of the &quot;more free&quot; license of the preprint, you could also just put two references, one for the image and one for the journal article. Then everybody is happy.&lt;/p&gt;&#xA;" OwnerUserId="607" LastActivityDate="2020-06-01T13:57:18.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1161" PostTypeId="1" AcceptedAnswerId="1200" CreationDate="2020-06-01T15:06:24.020" Score="14" ViewCount="630" Body="&lt;p&gt;&lt;a href=&quot;https://sourceforge.net/p/lammps/mailman/message/30731504/&quot; rel=&quot;noreferrer&quot;&gt;In 2013 it was stated that v8.8 of DYNAMO was the version mostly used&lt;/a&gt; for the last 10-12 years.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However I am struggling to find the code repository. It was developed by the LAMMPS developers and is used to mix eam potentials. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;DYNAMO was available on sourceforge.net, but now it seems to have been removed. Where can I get access to the repository?&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="7" LastEditDate="2020-06-15T19:00:43.637" LastActivityDate="2021-06-14T14:41:09.167" Title="Is the DYNAMO code developed by LAMMPS still available?" Tags="|software|reference-request|lammps|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1162" PostTypeId="2" ParentId="1161" CreationDate="2020-06-01T18:41:23.780" Score="14" Body="&lt;p&gt;There is a page on the &lt;a href=&quot;https://www.sandia.gov/%7Esjplimp/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sandia labs website&lt;/a&gt; that includes download links for all the software developed by Steve Plimpton. It sounds as if he reimplemented all the functionality of DYNAMO into a program called ParaDyn (the para denoting that it was modified to run in parallel).&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, the site makes it sound as though &lt;em&gt;almost all&lt;/em&gt; the features of DYNAMO have also already been incorporated into LAMMPS and are even faster than in ParaDyn. So you may just be able to use LAMMPS instead.&lt;/p&gt;&#xA;&lt;p&gt;If you really do need DYNAMO, I would suggest contacting &lt;a href=&quot;https://www.clemson.edu/science/departments/physics-astro/people/daw.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Murray Daw&lt;/a&gt; or &lt;a href=&quot;https://www.sandia.gov/cgi-bin/emplloc?ename=foiles&quot; rel=&quot;nofollow noreferrer&quot;&gt;Stephen Foiles&lt;/a&gt; who originally developed the program and may know what has become of it.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-14T14:41:09.167" LastActivityDate="2021-06-14T14:41:09.167" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1163" PostTypeId="5" CreationDate="2020-06-01T22:55:37.247" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-01T22:55:37.247" LastActivityDate="2020-06-01T22:55:37.247" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1164" PostTypeId="4" CreationDate="2020-06-01T22:55:37.247" Score="0" Body="For any questions about (or related to) the Hartree-Fock method." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-01T22:55:37.247" LastActivityDate="2020-06-01T22:55:37.247" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1165" PostTypeId="2" ParentId="1159" CreationDate="2020-06-02T04:07:28.063" Score="5" Body="&lt;p&gt;According &lt;a href=&quot;https://library.bu.edu/ld.php?content_id=30310050&quot; rel=&quot;noreferrer&quot;&gt;this guidance&lt;/a&gt; from the Boston University library: &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;Copying up to three figures from any one source is considered fair use. &lt;a href=&quot;https://library.bu.edu/ld.php?content_id=30310050&quot; rel=&quot;noreferrer&quot;&gt;direct link, see p. 14&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;If you want to play it extra safe (fair use is often a gray area) the publisher will probably have a link on the article listing for something like &quot;reuse and permissions&quot;, where you can get permission to reprint a figure (or text, etc). Anything covered by fair use should have a $0 licensing fee (and you can probably get some document from them specifying the permission to reprint). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;You will also want to look into the policies of the journal you will be submitting to. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also: there may be more generous policies if you want to reprint figures from your own papers. &lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-06-02T04:07:28.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1166" PostTypeId="1" CreationDate="2020-06-02T04:27:16.830" Score="9" ViewCount="1272" Body="&lt;p&gt;For systems with periodic boundary condition , plane wave basis is usually adopted. While for molecular systems, gaussian basis set is normally adopted. For periodic systems, the gaussian basis is transformed from real lattice space to momentum space (or k space) through Bloch function. My question is that what is the advantage of the plane wave basis? And a relevant question is that how to determine the number of k points required to converge the energy and density matrix for a periodic system?&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2020-06-02T16:26:41.177" Title="What are the advantages of plane wave basis?" Tags="|basis-sets|" AnswerCount="2" CommentCount="1" ClosedDate="2020-06-02T20:49:25.657" ContentLicense="CC BY-SA 4.0" />
  <row Id="1167" PostTypeId="2" ParentId="1166" CreationDate="2020-06-02T07:27:54.413" Score="11" Body="&lt;p&gt;In my opinion a solid, brief overview of DFT is given here.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.archer.ac.uk/training/course-material/2014/04/PMMP_UCL/Slides/castep_1.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://www.archer.ac.uk/training/course-material/2014/04/PMMP_UCL/Slides/castep_1.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The pro/cons of plane waves and other basis sets are discussed and I will &#xA;list them here in case the link goes dead.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Pros:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Fourier coefficients stored in regular grid.&lt;/li&gt;&#xA;&lt;li&gt;Efficient FFT algorithms between r- and G-space representation.&lt;/li&gt;&#xA;&lt;li&gt;O(N^2) scaling on CPU&lt;/li&gt;&#xA;&lt;li&gt;Complete and orthonormal basis set.&lt;/li&gt;&#xA;&lt;li&gt;Not atom-centered -&gt; unbiased.&lt;/li&gt;&#xA;&lt;li&gt;Systematically improvable by increasing the cut-off of the Fourier coefficients.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Cons:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Large set of basis coefficients. Hamiltonian cannot be stored.&lt;/li&gt;&#xA;&lt;li&gt;Sharp nodes of wave functions of core electrons are very expensive. Need pseudo-potential.&lt;/li&gt;&#xA;&lt;li&gt;Vacuum as expensive as atoms.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="250" LastEditorUserId="250" LastEditDate="2020-06-02T08:43:23.000" LastActivityDate="2020-06-02T08:43:23.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1169" PostTypeId="2" ParentId="1117" CreationDate="2020-06-02T14:25:28.533" Score="8" Body="&lt;p&gt;If by &quot;the SCF method&quot; you mean the simple SCF, the answer is: no, usually it does not converge (unless the problem is very simple; basically the gap is huge, so that the system does not respond very much to potentials). The &lt;em&gt;damped&lt;/em&gt; SCF problem on the other hand does converge, for damping parameters small enough (unless you run into fractional occupations). The trouble is that it's not trivial to find out &lt;em&gt;a priori&lt;/em&gt; what is a good damping parameter, so you have to couple that with a globalization strategy (like line searches). A good review paper is &lt;a href=&quot;https://arxiv.org/abs/1905.02332&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1905.02332&lt;/a&gt;, and for technical aspects about SCF/DM convergence I will shamelessly cite a recent preprint of mine: &lt;a href=&quot;https://arxiv.org/abs/2004.09088&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/2004.09088&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="316" LastEditorUserId="5" LastEditDate="2020-06-02T14:43:48.617" LastActivityDate="2020-06-02T14:43:48.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1170" PostTypeId="5" CreationDate="2020-06-02T15:32:47.620" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-06-02T15:32:47.620" LastActivityDate="2020-06-02T15:32:47.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1171" PostTypeId="4" CreationDate="2020-06-02T15:32:47.620" Score="0" Body="Questions that were first asked on Chemistry Stack Exchange. " OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-05-02T20:26:37.463" LastActivityDate="2021-05-02T20:26:37.463" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1172" PostTypeId="2" ParentId="1166" CreationDate="2020-06-02T16:15:42.800" Score="2" Body="&lt;p&gt;@Susi Lehtola&#xA;Thanks for sharing the link. I agree that the linked question is more or less the same as the question here. However, I think most of the answers is limited to DFT. I know there are electronic packages that could do calculation for periodic systems with &lt;strong&gt;coupled cluster method&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Like PySCF:&#xA; &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.7b00049?casa_token=okpTgl35nWYAAAAA:OcmfSpa8IpK_P8PCgfmCbDfVbLAZ-ILEuZoTdkMvPTUzhqhr7yvBrVejAg998vDoyHf-zzTmm95qZRaq&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.7b00049?casa_token=okpTgl35nWYAAAAA:OcmfSpa8IpK_P8PCgfmCbDfVbLAZ-ILEuZoTdkMvPTUzhqhr7yvBrVejAg998vDoyHf-zzTmm95qZRaq&lt;/a&gt;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For simplified model Hamiltonian, conventional solid state physicist also developed second quantization techniques in momentum space.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Like classical &lt;strong&gt;spin wave approach&lt;/strong&gt; for ferromagnetism &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.102.1217&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/pr/abstract/10.1103/PhysRev.102.1217&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also more recently, &lt;strong&gt;quantum monte carlo&lt;/strong&gt; approach is developed to study Hubbard model&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1811.03607&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/1811.03607&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;All these method adopt a plane-wave basis. I think in the real lattice space, effect of delocalization might not be well captured. But these effect might only consequential for same special system (correspond to long wave length limit in k space). For normal systems, the interaction might be decay within first few nearest neighbours (especially for ground state).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My question is that how is the performance of the plane-wave basis for these post-Hartree-Fock approaches?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="141" LastEditDate="2020-06-02T16:26:41.177" LastActivityDate="2020-06-02T16:26:41.177" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1173" PostTypeId="2" ParentId="392" CreationDate="2020-06-02T17:10:08.657" Score="19" Body="&lt;h1&gt;1993 (Becke): Hybrid Functionals&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;Axel D. Becke &lt;a href=&quot;https://doi.org/10.1063/1.464304&quot; rel=&quot;noreferrer&quot;&gt;introduced&lt;/a&gt; the adiabatic-connection model, which allows for mixing of DFT exchange and Fock-like exchange via the formula&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{\text{x}} = a \cdot E^{\text{HF}}_x + b \cdot E^{\text{GGA}}_x&#xA;$$&lt;/span&gt;&#xA;to obtain the exchange part of the exchange-correlation energy. Typically, one imposes &lt;span class=&quot;math-container&quot;&gt;$a+b = 1$&lt;/span&gt;, but some authors have sometimes abandoned the summation to &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; or introduced exchange from the local density approximation (LDA a.k.a. Slater-Exchange) to the mix (B3LYP falls into this category).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Hybrids show improved performance over GGAs and meta-GGAs for the HOMO-LUMO gap, thermochemistry and excited states via time-dependent DFT. Especially for the latter, mixing parameters that are dependent on the electron-electron distance have yielded good results, leading to &quot;long-range corrected&quot; or &quot;range-separated&quot; hybrid functionals such as LC-PBE.&#xA;&lt;hr&gt;&#xA;&lt;sup&gt;Technically, this is not more recent than 1996. Given the impact of hybrid functionals, I think it is proper to list this milestone regardless.&lt;/sup&gt;&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-06-03T17:32:06.633" LastActivityDate="2020-06-03T17:32:06.633" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1174" PostTypeId="2" ParentId="190" CreationDate="2020-06-02T20:26:12.377" Score="13" Body="&lt;h1&gt;Basis Sets&lt;/h1&gt;&#xA;&lt;p&gt;Throughout, I use square brackets to denote additional options that can be included, but are not required.&lt;/p&gt;&#xA;&lt;h3&gt;Slater:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;STO-nG: Slater Type Orbitals represented by a function of n contracted Gaussian functions&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;STO-nG*: Polarized version of STO-nG&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ones that you can commonly find:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;STO-2G&lt;/li&gt;&#xA;&lt;li&gt;STO-3G&lt;/li&gt;&#xA;&lt;li&gt;STO-4G&lt;/li&gt;&#xA;&lt;li&gt;STO-6G&lt;/li&gt;&#xA;&lt;li&gt;STO-3G*&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Pople:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;X-YZG: Split valence double zeta basis functions, where each core orbital is represented by a contracted function on X primitive Gaussians and each valence orbital is represented by two contracted functions with Y and Z primitive Gaussians. Can be extended up to quadruple zeta (e.g. X-YZWVG)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;X-YZG*[*]: Polarization functions on heavy atoms [and hydrogen]. Also written X-YZG(d) [X-YZG(d,p)]&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;X-YZ+[+]G: Diffuse functions on heavy atoms [and hydrogen]&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Basis_set_(chemistry)&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ones that you can commonly find&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;3-21G&lt;/li&gt;&#xA;&lt;li&gt;3-21G*&lt;/li&gt;&#xA;&lt;li&gt;3-21G**&lt;/li&gt;&#xA;&lt;li&gt;3-21+G&lt;/li&gt;&#xA;&lt;li&gt;3-21++G&lt;/li&gt;&#xA;&lt;li&gt;3-21+G*&lt;/li&gt;&#xA;&lt;li&gt;3-21+G**&lt;/li&gt;&#xA;&lt;li&gt;4-21G&lt;/li&gt;&#xA;&lt;li&gt;4-31G&lt;/li&gt;&#xA;&lt;li&gt;6-21G&lt;/li&gt;&#xA;&lt;li&gt;6-31G&lt;/li&gt;&#xA;&lt;li&gt;6-31G*&lt;/li&gt;&#xA;&lt;li&gt;6-31+G*&lt;/li&gt;&#xA;&lt;li&gt;6-31G(3df, 3pd)&lt;/li&gt;&#xA;&lt;li&gt;6-311G&lt;/li&gt;&#xA;&lt;li&gt;6-311G*&lt;/li&gt;&#xA;&lt;li&gt;6-311+G*&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Correlation-Consistent/Dunning:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;[d/t/q]-[aug]-cc-pVXZ: [doubly/triply/quadruply]-[Augmented with diffuse functions] Correlation Consistent Polarized Valence (Double,Triple, Quadruple,...) Zeta&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-p[w]CVXZ: Correlation Consistent Polarized [weighted] Core-Valence (Double,Triple, Quadruple,...) Zeta&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-pV(X+d)Z: Additional tight d-functions added for second and later row elements.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-pVXZ-PP: With Pseudopotentials&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-pVXZ-DK: Relativistic Douglas-Kroll contraction&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-pVXZ-X2C: Relativistic Exact 2-Component contraction&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;cc-pVXZ-F12: Reoptimized for better convergence with F12 explicitly correlated methods&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;[jul,jun,may,apr]-cc-pVXZ: Calendar basis set variations. Relative to Aug, Jul removes diffuse functions from H and He. Jun, May, and Apr remove the one, two, and three highest angluar momentum diffuse functions, respectively, from all atoms.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Karlsruhe&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;def2-XVP[P][D]: Reoptimized Turbomole Basis Functions (def2=default 2). (Single, Double, Triple,...) Valence Polarization [Additional set of Polarization] [Set of Diffuse functions]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ones that you can commonly find:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;def2-SV(P)&lt;/li&gt;&#xA;&lt;li&gt;def2-SVP&lt;/li&gt;&#xA;&lt;li&gt;def2-SVPD&lt;/li&gt;&#xA;&lt;li&gt;def2-TZVP&lt;/li&gt;&#xA;&lt;li&gt;def2-TZVPD&lt;/li&gt;&#xA;&lt;li&gt;def2-TZVPP&lt;/li&gt;&#xA;&lt;li&gt;def2-TZVPPD&lt;/li&gt;&#xA;&lt;li&gt;def2-QZVP&lt;/li&gt;&#xA;&lt;li&gt;def2-QZVPD&lt;/li&gt;&#xA;&lt;li&gt;def2-QZVPP&lt;/li&gt;&#xA;&lt;li&gt;def2-QZVPPD&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Polarization-Consistent/Jensen&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[aug]pc[seg]-n: [Augmented with Diffuse functions] Polarization consistent [segmented contraction]. n denotes how much higher in angular momentum the polarization functions are compared to the isolated atom.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Miscellaneous&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ANO: Atomic Natural Orbitals&lt;/li&gt;&#xA;&lt;li&gt;ECP: Effective Core Potential&lt;/li&gt;&#xA;&lt;li&gt;LanL2DZ: Los Alamos National Lab Double Zeta (double zeta for small atoms, Los Alamos ECP after Na).&lt;/li&gt;&#xA;&lt;li&gt;BSSE: Basis Set Superposition Error&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;To Be Continued&lt;/h3&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2023-04-02T02:18:32.420" LastActivityDate="2023-04-02T02:18:32.420" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1175" PostTypeId="1" CreationDate="2020-06-02T23:07:06.907" Score="15" ViewCount="996" Body="&lt;p&gt;When working with libraries of thousand of molecules or with &lt;em&gt;de novo&lt;/em&gt; design (using combinatorial chemistry), it is usual to filter the libraries using as a criterion the molecular similarity.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Tanimoto coefficient&lt;sup&gt;&lt;a href=&quot;https://doi.org/10.1186/s13321-015-0069-3&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;&lt;/sup&gt; for fingerprint-based similarity calculations is one of the must used coefficient. In order to use it, it is necessary to first, calculate the fingerprint of each molecule in the library. The problem now, is to define which fingerprint to use. Software like &lt;a href=&quot;https://openbabel.org/&quot; rel=&quot;noreferrer&quot;&gt;OpenBabel&lt;/a&gt; is able to compute 4 different fingerprints whereas software like &lt;a href=&quot;http://projects.scbdd.com/pybiomed.html&quot; rel=&quot;noreferrer&quot;&gt;PyBioMed&lt;/a&gt; can calculate 19.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The problem now is: how to choose the &lt;em&gt;best&lt;/em&gt; fingerprints to characterize the molecular library?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Note: By &lt;em&gt;best&lt;/em&gt;, I am inclined to think in a fingerprint sensible to minimum modifications in the the molecule structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1186/s13321-015-0069-3&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? D. Bajusz, A. Rácz and K. Héberger.  Cheminform 7, 20 (2015). &lt;a href=&quot;https://doi.org/10.1186/s13321-015-0069-3&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1186/s13321-015-0069-3&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2020-06-26T21:58:25.443" LastActivityDate="2020-06-26T21:58:25.443" Title="What are the best fingerprints to characterize molecules?" Tags="|materials-informatics|chemoinformatics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1176" PostTypeId="1" AcceptedAnswerId="1196" CreationDate="2020-06-03T06:35:06.257" Score="22" ViewCount="11331" Body="&lt;p&gt;I am currently trying to figure out how to compute band structures for my system, using the hybrid functional HSE06. I'm doing this on Quantum Espresso. As I understand, there are a handful of ways to do this:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;1) Generate maximally localized wannier functions (MLWFs) with the HSE functional turned on&lt;/p&gt;&#xA;&#xA;&lt;p&gt;2) The 'fake scf' procedure: This is similar to what is listed in Vaspwiki(&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&quot; rel=&quot;noreferrer&quot;&gt;here)&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;3) Generate scf data for a coarse 'q' mesh (of the Fock operator) and then interpolate these bands using softwares like BoltztraP2.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am not familiar with the Wannier module on Quantum ESPRESSO, hence option (1) is sort of last resort for me, since Wannier takes some time to learn.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The 'fake scf' procedure doesn't seem to work. The k-point mesh for my original calculation (my system is a bilayer TMD - Transition metal dichalcogenide) is 12x9x1. I tried using a commensurate 'q' grid and tried the 'fake scf' procedure, but I couldn't get it to work.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;I would be grateful if anyone could help me figure out how to compute these bandstructures - either through one of the methods I mentioned, or any easy method as you see fit.&lt;/strong&gt; I would like to add that I have access to considerable computational resources, so doing expensive calculations should not be much of an issue. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also, I would like to say that I am open to methods that use other softwares - including VASP or CASTEP. I have both licenses (CASTEP through Materials Studio). But things can get a little tricky here because VASP for example, uses a different implementation of the Hubbard 'U' and it would corrupt my results if I port my QE input to VASP to calculate the band-structures.&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-08-07T17:52:48.593" LastActivityDate="2021-02-06T19:07:19.847" Title="Calculating HSE06 band structures on Quantum ESPRESSO" Tags="|density-functional-theory|software|band-structure|quantum-espresso|dichalcogenides|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1178" PostTypeId="1" AcceptedAnswerId="1180" CreationDate="2020-06-03T09:26:56.580" Score="9" ViewCount="156" Body="&lt;p&gt;In other works and from the paper: &lt;a href=&quot;https://arxiv.org/pdf/2002.07901.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Scaling Up Electronic Structure Calculations on Quantum Computers: The Frozen Natural Orbital Based Method of Increments&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I have seen that the corrected CCSD correlation energy &lt;span class=&quot;math-container&quot;&gt;$E_{c}^{\text{CCSD}}(\text{corrected})$&lt;/span&gt; is calculated from a CCSD computation of the truncated virtual space correlation energy &lt;span class=&quot;math-container&quot;&gt;$E_{c}^{\text{FNO(CCSD})}$&lt;/span&gt;, which is added to a MPBT2 correction term &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{c}^{\text{MPBT(2)}}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{c}^{\text{CCSD}}(\text{corrected}) = E_{c}^{\text{FNO(CCSD)}} + \Delta E_{c}^{\text{MPBT(2)}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The correction term is the MBPT(2) correlation energy in the full molecular orbital space minus the MBPT(2) correlation energy in the truncated frozen natural orbital (FNO) space :&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_{c}^{\text{MPBT(2)}} = E_{c}^{\text{FNO(MPBT(2))}} - E_{c}^{\text{FNO(MPBT(2))}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;This strikes me as combining two different levels of theory. Why is this acceptable?&lt;/p&gt;&#xA;&lt;p&gt;Here, I have interpreted the equations as: The correlation energy of the occupied block is given by &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{c}^{\text{MPBT(2)}}$&lt;/span&gt; at the MPBT(2) level, which is added to the correlation energy of the truncated FNO block &lt;span class=&quot;math-container&quot;&gt;$E_{c}^{\text{FNO(CCSD)}}$&lt;/span&gt; at the CCSD level.&lt;/p&gt;&#xA;&lt;p&gt;To assist in my learning, I may have misinterpreted what is meant by frozen natural orbitals (FNOs). The &lt;a href=&quot;https://arxiv.org/pdf/2002.07901.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; states that FNOs are &lt;em&gt;transformed and ranked virtual molecular orbitals&lt;/em&gt;, which enable one to truncate the virtual space. Therefore, are the orbitals in the truncated frozen natural orbital (FNO) space from which &lt;span class=&quot;math-container&quot;&gt;$E_{c}^{\text{FNO(MPBT(2))}}$&lt;/span&gt; is calculated actually the remaining active virtual orbitals after truncation?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="7" LastEditDate="2021-11-10T19:08:49.853" LastActivityDate="2021-11-10T19:08:49.853" Title="The correlation energy from frozen natural orbtials (FNOs) using CCSD and MPBT(2)?" Tags="|quantum-chemistry|computational-chemistry|coupled-cluster|quantum-computing|many-body-perturbation-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1179" PostTypeId="2" ParentId="1175" CreationDate="2020-06-03T12:56:20.403" Score="5" Body="&lt;p&gt;I don't think there is an universal answer: the fingerprint is probably highly property dependent, since there is no single property that fully characterizes a molecule. (This is also the likely reason for there being dozens of different definitions for fingerprints; the same situation exists in partial charge analysis that lack a unique definition.)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-03T12:56:20.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1180" PostTypeId="2" ParentId="1178" CreationDate="2020-06-03T13:03:04.860" Score="6" Body="&lt;p&gt;The idea in the FNO method is to do a MP2 calculation for the one-particle density matrix and diagonalize it to get the natural orbitals (NOs) and natural orbital occupation numbers (NOONs).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So, starting from (usually) a Hartree-Fock reference wave function, you figure out which orbitals are the most strongly correlated, and which ones yield only small contributions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The next step is that you take the most strongly correlated NOs, and run CCSD in that orbital space; truncating the virtual space saves you a lot since CCSD has a &lt;span class=&quot;math-container&quot;&gt;$v^4$&lt;/span&gt; term.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Why does the scheme work so well? This is a good question, which arises also with composite methods like G-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; theories and more modern versions like W-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; theories. It just does :D&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The main point is that the error in the approximation is controllable by the NOON cutoff value. If you use a small cutoff (note that MP2 NOONs can also be negative - in which cases the scheme is probably unreliable!), you should be very close to the full CCSD energy.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-03T13:03:04.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1181" PostTypeId="5" CreationDate="2020-06-03T20:04:22.767" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:04:22.767" LastActivityDate="2020-06-03T20:04:22.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1182" PostTypeId="4" CreationDate="2020-06-03T20:04:22.767" Score="0" Body="For questions about (or related to) the Hubbard model." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:04:22.767" LastActivityDate="2020-06-03T20:04:22.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1183" PostTypeId="5" CreationDate="2020-06-03T20:07:35.620" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:07:35.620" LastActivityDate="2020-06-03T20:07:35.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1184" PostTypeId="4" CreationDate="2020-06-03T20:07:35.620" Score="0" Body="For questions about (or related to) electronic structure methods in which electrons are explicitly correlated in their representation within the overall wavefunction. Examples include explicitly correlated Hylleraas wavefunctions and similar. Related methods such as R12 and F12 methods which add explicitly correlated geminals into non-explicitly correlated basis sets, are also on topic." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:07:35.620" LastActivityDate="2020-06-03T20:07:35.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1185" PostTypeId="5" CreationDate="2020-06-03T20:08:00.110" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:08:00.110" LastActivityDate="2020-06-03T20:08:00.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1186" PostTypeId="4" CreationDate="2020-06-03T20:08:00.110" Score="0" Body="For questions about (or related to) the software CP2K." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-03T20:08:00.110" LastActivityDate="2020-06-03T20:08:00.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1187" PostTypeId="2" ParentId="1175" CreationDate="2020-06-04T02:02:40.577" Score="12" Body="&lt;p&gt;&lt;strong&gt;tldr; There is not necessarily a &quot;best&quot; fingerprint method because there are &lt;em&gt;many&lt;/em&gt;, many ways to generate fingerprints. ECFP4 or ECFP6 with &gt;2048 bits is usually decent.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Generally speaking, a fingerprint is some large vector, typically binary, used for similarity-based screening and more recently machine learning. The elements of the fingerprint are some type of chemical descriptor.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Some recent reviews:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1016/j.drudis.2018.05.010&quot; rel=&quot;noreferrer&quot;&gt;&quot;Machine learning in chemoinformatics and drug discovery&quot; &lt;em&gt;Drug Discovery Today&lt;/em&gt; 2018, v. 23, August pp. 1538-1546&#xA;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1007/978-1-60761-839-3_5&quot; rel=&quot;noreferrer&quot;&gt;&quot;Similarity Searching Using 2D Structural Fingerprints&quot; &lt;em&gt;Methods Mol Biol.&lt;/em&gt; 2011 v. 672 pp. 133-58.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;IMHO, there are a few general categories:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Structural pattern fingerprints (e.g. MACCS) - sets of functional group patterns (e.g. alkyl chains, aromatic rings, ketones, ..) one bit or count per functional group in the fingerprint.&lt;/li&gt;&#xA;&lt;li&gt;Daylight-style linear fingerprints - take the atom, and it's linear neighbors&lt;/li&gt;&#xA;&lt;li&gt;Circular-style fingerprints (e.g. ECFP) - generating a radius or diameter around the neighbors of an atom. Like the linear fingerprints, these can essentially generate an infinite number of patterns, so it's hashed to a fixed bit vector&lt;/li&gt;&#xA;&lt;li&gt;3D property fingerprints - interatomic distances, surfaces, electrostatic fields, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;There are countless new fingerprint schemes produced each year, e.g.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&quot;Neural Fingerprints&quot; &lt;a href=&quot;https://github.com/HIPS/neural-fingerprint&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/HIPS/neural-fingerprint&lt;/a&gt; - convolutional neural networks to design the best fingerprints for a particular property set&lt;/li&gt;&#xA;&lt;li&gt;MinHash fingerprints &lt;a href=&quot;https://github.com/reymond-group/mhfp&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/reymond-group/mhfp&lt;/a&gt; - a better hashing scheme for the high-dimensional ECFP-style circular fingerprint&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Open Babel can compute a few pattern-style fingerprints (FP3, FP4, and MACCS), the Daylight-style linear FP2 fingerprint, and a variety of ECFP circular fingerprint styles, e.g. ECFP4.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;RDKit can generate a whole pile of fingerprints too: &lt;a href=&quot;http://rdkit.org/docs/GettingStartedInPython.html#fingerprinting-and-molecular-similarity&quot; rel=&quot;noreferrer&quot;&gt;http://rdkit.org/docs/GettingStartedInPython.html#fingerprinting-and-molecular-similarity&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You might say, but is there a good place to start? The Morgan circular / ECFP fingerprints are really good, especially with a fairly large bit vector (e.g. 2048 bits per molecule) to hash.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-06-04T02:02:40.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1188" PostTypeId="2" ParentId="392" CreationDate="2020-06-04T03:30:24.910" Score="20" Body="&lt;h1&gt;2004 (Yanai &lt;em&gt;et al.&lt;/em&gt;): Range separation&lt;/h1&gt;&#xA;&lt;p&gt;Often, the source of DFT improvement comes from Hartree-Fock as is also obvious from the answer involving double hybrid functionals. So too it is with &lt;strong&gt;range-separation&lt;/strong&gt;. The electron-electron Coulomb operator for the exchange contribution is separated into a short and long range contribution.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \frac{1}{r} = \frac{1-\text{erf}(\omega r)}{r} + \frac{\text{erf}(\omega r)}{r}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\text{erf}$&lt;/span&gt; is the standard error function. The &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; parameter determines when to switch from using the short range part to the long range part. In this strategy the short range contribution is calculated using a density functional, and the long range contribution is calculated using HF. HF is good at this. What HF is not good at is correlation, but, there is a different functional for that. Right now, we are improving the electron-electron calculation.&lt;/p&gt;&#xA;&lt;p&gt;The long range contribution from HF helps ensure that DFT overlocalization of charge separation is removed - notably yielding much improved excitation energies for charge-transfer states. &lt;strong&gt;Overall: Range-separation helps solve self-interaction errors and improves excitation energies among other benefits.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1] T. Yanai, D.P. Tew and N.C. Handy, Chemical Physics Letters, 393, (1-3), 51-57 (2004)&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="181" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-13T16:34:43.267" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1190" PostTypeId="2" ParentId="690" CreationDate="2020-06-04T06:02:35.240" Score="6" Body="&lt;p&gt;Let's define the energy obtained by a double-hybrid as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E^\text{DHDF}_\text{xc} = a \cdot E^\text{exact}_\text{x} + b \cdot E^\text{(m)GGA}_\text{x} + c \cdot E^\text{(m)GGA}_\text{c} + d \cdot E^{\text{PT2}}_\text{c}&#xA;$$&lt;/span&gt;&#xA;where the weighted summands are the energy contribution of exact/Fock exchange, the (meta)-GGA DFT exchange energy, the (meta)-GGA DFT correlation energy, and the second-order perturbative correction&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Many researchers are of the opinion that the coefficients for exchange and correlation should sum to unity, respectively:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;a + b = 1 \\&#xA;c + d = 1&#xA;$$&lt;/span&gt;&#xA;which seems valid as long as the functionals reproduce some exactly known values, such as for the uniform electron gas.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Some researchers have suggested that there is a relationship between &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;, as well:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA; a^n = d&#xA;$$&lt;/span&gt;&#xA;where it is a matter of debate whether the exponent &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; should be &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt;. For proponents of &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt;, see &lt;a href=&quot;https://doi.org/10.1063/1.3604569&quot; rel=&quot;noreferrer&quot;&gt;work by Brémond and Adamo)&lt;/a&gt; wherein they claim to have found a parameter-free double-hybrid by using &lt;span class=&quot;math-container&quot;&gt;$a = 0.5$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d = 0.125$&lt;/span&gt; and the PBE functional. &lt;a href=&quot;https://doi.org/10.1063/1.3544215&quot; rel=&quot;noreferrer&quot;&gt;Sharkas, Toulouse, Savin&lt;/a&gt; suggested &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; instead. Note that the first double-hybrid functional, B2PLYP, leans towards &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$a = 0.53$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d = 0.27$&lt;/span&gt; (though it was largely fitted).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;So while there is a large amount of fitting going on, and most of the most successful DHDFs have been found this way, attempts to find a physical motivation exist.&lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; Some people say that it's not exactly MP2 because that would start from HF orbitals.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-06-04T06:02:35.240" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1191" PostTypeId="2" ParentId="1147" CreationDate="2020-06-04T10:12:57.787" Score="12" Body="&lt;p&gt;Seeing that this question has gathered attention but no replies, I will give it a stab. Note that I am not an expert on DFT &lt;em&gt;or&lt;/em&gt; functional calculus, so take this with a grain of salt. As usual, suggestions to the post will be welcome!&lt;/p&gt;&#xA;&lt;p&gt;Using an approach I saw &lt;a href=&quot;https://math.stackexchange.com/questions/235769/is-there-a-chain-rule-for-functional-derivatives&quot;&gt;here&lt;/a&gt;, we can use a chain rule and obtain the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta F[\rho(\boldsymbol{r})]}{\delta n_i[\rho_i(\boldsymbol{r})]} = \int \frac{\frac{\delta F[\rho(\boldsymbol{r})]}{\delta \rho(\boldsymbol{r})}}{\frac{\delta n_i[\rho_i(\boldsymbol{r})]}{\delta \rho(\boldsymbol{r})}} d\boldsymbol{r} = \int \frac{\frac{\delta F[\rho(\boldsymbol{r})]}{\delta \rho_i(\boldsymbol{r})}}{\frac{\delta n_i[\rho_i(\boldsymbol{r})]}{\delta \rho_i(\boldsymbol{r})}} d\boldsymbol{r}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the last equality stems from the fact that the integrand will vanish for any &lt;span class=&quot;math-container&quot;&gt;$\rho_k, k\neq i$&lt;/span&gt;. It is straightforward to see that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta n_i[\rho_i(\boldsymbol{r})]}{\delta \rho_i(\boldsymbol{r})} = 1\tag{2}$$&lt;/span&gt; so the above integral reduces to:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta F[\rho(\boldsymbol{r})]}{\delta n_i[\rho_i(\boldsymbol{r})]} = \int \frac{\delta F[\rho(\boldsymbol{r})]}{\delta \rho_i(\boldsymbol{r})} d\boldsymbol{r}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is what I assume you mean by writing &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial F}{\partial \rho_i}$&lt;/span&gt;, since this will be a function of &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{r}$&lt;/span&gt;, unless you integrate over it, and coordinate-dependent chemical potentials don't make much sense to me! Also, note that the functional derivative is only equal to &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial f}{\partial \rho_i}$&lt;/span&gt; if your free energy functional doesn't depend on any derivatives of the density. In this case, you will need higher-order terms as well.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I will give the osmotic pressure a try as well, but this will definitely need to be checked for some non-obvious errors. Use at your own discretion.&lt;/p&gt;&#xA;&lt;p&gt;You can express &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta F[\rho(\boldsymbol{r})]}{\delta V}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta F[\rho(\boldsymbol{sr})]}{\delta s^3}\Big|_{s=1} = \frac{1}{3s^2}\frac{\delta F[\rho(s\boldsymbol{r})]}{\delta s}\Big|_{s=1}$&lt;/span&gt; for some scaling factor &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;. In this case, the chain rule tells us that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\frac{1}{3s^2}\frac{\delta F[\rho(s\boldsymbol{r})]}{\delta s}\Bigg|_{s=1} &amp;amp;= \frac{1}{3s^2} \int \frac{\delta F[\rho(s\boldsymbol{r})]}{\delta \rho(s\boldsymbol r)} \frac{\partial \rho(s\boldsymbol{r})}{\partial s} d(s\boldsymbol{r})\Bigg|_{s=1}\tag{4}\\ &amp;amp;= \frac{1}{3} \int \frac{\delta F[\rho(\boldsymbol{r})]}{\delta \rho(\boldsymbol{r})} (\nabla\rho(\boldsymbol{r})\cdot\boldsymbol{r}) d\boldsymbol{r}\tag{5}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="5" LastEditDate="2020-12-28T02:01:49.970" LastActivityDate="2020-12-28T02:01:49.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1192" PostTypeId="2" ParentId="392" CreationDate="2020-06-04T11:24:17.273" Score="27" Body="&lt;h1&gt;2015 (Sun &lt;em&gt;et al.&lt;/em&gt;): SCAN functional&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.115.036402&quot; rel=&quot;noreferrer&quot;&gt;The SCAN meta-GGA functional&lt;/a&gt; is an extension of the popular PBE GGA [1] and the TPSS [2] and revTPSS [3] meta-GGAs, SCAN adheres to all 17 known exact XC constraints and is constructed to be almost exact for the noble gasses and jellium surfaces. Early evidence suggests that SCAN is more accurate than and of comparable efficiency to the aforementioned GGAs for crystal structure prediction [4-5], ab initio thermodynamics [6-7], and computational catalysis [8].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[1] J. P. Perdew, K. Burke, and M. Ernzerhof,Phys. Rev. Lett.77, 3865 (1996).&lt;br&gt;&#xA;[2] J. Tao, J. P. Perdew, V. N. Staroverov, and G. E. Scuseria,Phys. Rev. Lett.91, 146401 (2003).&lt;br&gt;&#xA;[3] J. P. Perdew, A. Ruzsinszky, G. I. Csonka, L. A. Constantin,and J. Sun,Phys. Rev. Lett.103, 026403 (2009).&lt;br&gt;&#xA;[4] H. Peng, Z.H. Yang, J.P. Perdew, and J. Sun, Phys. Rev. X 6, 041005 (2016).&lt;br&gt;&#xA;[5] J.H. Yang, D.A. Kitchaev, and G. Ceder, Phys. Rev. B 100, 035132 (2019).&lt;br&gt;&#xA;[6] E.B. Isaacs and C. Wolverton, Phys. Rev. Mater. 2, 063801 (2018).&lt;br&gt;&#xA;[7] Y. Zhang, D.A. Kitchaev, J. Yang, T. Chen, S.T. Dacek, R.A. Sarmiento-Pérez, M.A.L. Marques, H. Peng, G. Ceder, J.P. Perdew, and J. Sun, Npj Comput. Mater. 4, 9 (2018).&lt;br&gt;&#xA;[8] G. Sai Gautam and E.A. Carter, Phys. Rev. Mater. 2, 1 (2018).&lt;/p&gt;&#xA;" OwnerUserId="801" LastEditorUserId="5" LastEditDate="2020-06-11T01:36:11.713" LastActivityDate="2020-06-11T01:36:11.713" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1193" PostTypeId="1" AcceptedAnswerId="1483" CreationDate="2020-06-04T15:43:09.127" Score="19" ViewCount="1374" Body="&lt;p&gt;I have a supercell that has 12 layers, each with four atoms. I want to generate an SQS with local ordering at layer numbers 6, 7 and 8. Rest of the layers should be disordered.&lt;br&gt;&#xA;I followed the procedure &lt;a href=&quot;http://cniu.me/2017/08/05/SQS.html&quot; rel=&quot;noreferrer&quot;&gt;&quot;How to use SQS for disordered materials.&quot;&#xA;&lt;/a&gt; but I get the following error:  &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;Impossible to match point correlations due to incompatible supercell size.  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;The input code (I am considering only the pairs):&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;mcsqs -2=4&#xA;mcsqs -rc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;The &lt;code&gt;rndstr.in&lt;/code&gt; file(A,B,C,D can be any metallic element):&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;6.92820300      0.00000000      0.00000000&#xA;2.30940100      6.53197300      0.00000000&#xA;0.00000000      0.00000000  33.94112500&#xA;1   0   0&#xA;0   1   0&#xA;0   0   1&#xA;1   0.5 1   A=.25,B=.25,C=.25,D=.25&#xA;1   1   1   A=.25,B=.25,C=.25,D=.25&#xA;0.5 1   1   A=.25,B=.25,C=.25,D=.25&#xA;0.5 0.5 1   A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.25    0.916667    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.25    0.916667    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.75    0.916667    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.75    0.916667    A=.25,B=.25,C=.25,D=.25&#xA;1   1   0.833333    A=.25,B=.25,C=.25,D=.25&#xA;1   0.5 0.833333    A=.25,B=.25,C=.25,D=.25&#xA;0.5 1   0.833333    A=.25,B=.25,C=.25,D=.25&#xA;0.5 0.5 0.833333    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.25    0.75    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.75    0.75    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.25    0.75    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.75    0.75    A=.25,B=.25,C=.25,D=.25&#xA;0.5 0.5 0.666667    A=.25,B=.25,C=.25,D=.25&#xA;0.5 1   0.666667    A=.25,B=.25,C=.25,D=.25&#xA;1   1   0.666667    A=.25,B=.25,C=.25,D=.25&#xA;1   0.5 0.666667    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.25    0.583333    B&#xA;0.75    0.25    0.583333    C&#xA;0.75    0.75    0.583333    C&#xA;0.25    0.75    0.583333    D&#xA;1   1   0.5 B&#xA;1   0.5 0.5 C&#xA;0.5 1   0.5 D&#xA;0.5 0.5 0.5 A&#xA;0.25    0.75    0.416667    B&#xA;0.25    0.25    0.416667    D&#xA;0.75    0.75    0.416667    A&#xA;0.75    0.25    0.416667    A&#xA;0.5 0.5 0.333333    A=.25,B=.25,C=.25,D=.25&#xA;0.5 1   0.333333    A=.25,B=.25,C=.25,D=.25&#xA;1   1   0.333333    A=.25,B=.25,C=.25,D=.25&#xA;1   0.5 0.333333    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.25    0.25    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.75    0.25    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.25    0.25    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.75    0.25    A=.25,B=.25,C=.25,D=.25&#xA;0.5 0.5 0.166667    A=.25,B=.25,C=.25,D=.25&#xA;0.5 1   0.166667    A=.25,B=.25,C=.25,D=.25&#xA;1   0.5 0.166667    A=.25,B=.25,C=.25,D=.25&#xA;1   1   0.166667    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.75    0.083333    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.75    0.083333    A=.25,B=.25,C=.25,D=.25&#xA;0.75    0.25    0.083333    A=.25,B=.25,C=.25,D=.25&#xA;0.25    0.25    0.083333    A=.25,B=.25,C=.25,D=.25&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Please suggest if I am doing something wrong, or is there anything else further which I need to specify to the ATAT MCSQS code?&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="5" LastEditDate="2020-12-12T03:07:30.977" LastActivityDate="2020-12-12T03:07:30.977" Title="How to calculate Special Quasirandom Structure with local ordering?" Tags="|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1194" PostTypeId="5" CreationDate="2020-06-04T16:44:41.673" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-04T16:44:41.673" LastActivityDate="2020-06-04T16:44:41.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1195" PostTypeId="4" CreationDate="2020-06-04T16:44:41.673" Score="0" Body="For questions about (or related to) the Alloy Theoretic Automated Toolkit." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-04T16:44:41.673" LastActivityDate="2020-06-04T16:44:41.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1196" PostTypeId="2" ParentId="1176" CreationDate="2020-06-04T17:02:48.060" Score="23" Body="&lt;p&gt;I have seen all the methods you mentioned but have only done one myself; I'll explain here how to use Wannier90 in conjunction with Quantum Espresso to get band structures for hybrid functional calculations. It does take a bit of time to learn, but not very long! You can learn the basics and do some first calculations in an afternoon. There are subtleties of course that I won't get into, and if you have specific issues you should probably ask another question or send a message to the Wannier90 mailing list.&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Initial Checklist&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Compile and install &lt;a href=&quot;http://www.wannier.org/&quot; rel=&quot;noreferrer&quot;&gt;Wannier90&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are using QE &amp;lt;= 6.0, you will need to replace the qe/PP/src/pw2wannier90.f90 file with one provided in the Wannier90 tarball, and recompile QE. Otherwise, make sure you have a working compiled version of QE. Newer versions will typically be better for hybrid functional calculations (pairwise band parallelization, ACE algorithm, support for ultrasoft &amp;amp; PAW...)&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This method requires commensurate k-point grids between QE and Wannier90. Certain  k-point meshes may cause issues in Wannier90 when identifiying nearest neighbors, etc.  It's recommended that you prepare a manual k-point grid with the utility located in wannier90/utility/kmesh.pl and use it in your QE calculation. Wannier90 does not recognize k-point symmetry, so it is a good idea to disable symmetry in your hybrid calculation with &lt;code&gt;nosym = .true&lt;/code&gt; and &lt;code&gt;noinv = .true.&lt;/code&gt; in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; block, along with the aforementioned manual k-points at the highest density you can afford, with corresponding q-point grid (as an aside, this type of grid is always needed for Wannier90, but normally you use this full grid with an nscf calculation after your automatic grid scf calculation when not using hybrid functionals, to reduce computational cost). I will leave it to you to determine what you need in terms of k- and q-point densities for your specific calculation.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The input files you need at the beginning are: DFT input for QE, Wannier90 input file (.win), and a pw2wan input file. Here are some I used for a very quick (probably unconverged) calculation I did on my desktop, just using bulk silicon. In the interest of time I used automatic projections with the SCDM method and default values, you should read up on this and decide how you should proceed in your own calculation (manual projections require the &lt;code&gt;begin projections&lt;/code&gt; block in Wannier90 input--read the user guide for more info). It can affect the band structure significantly.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;QE input file: silicon.in&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;control&#xA;    calculation = 'scf'&#xA;    restart_mode='from_scratch',&#xA;    prefix='Si-HSE',&#xA;    pseudo_dir = './',&#xA;    outdir='./TMP_DIR/'&#xA; /&#xA; &amp;amp;system    &#xA;    ibrav=  2, celldm(1) =10.20, nat=  2, ntyp= 1,&#xA;    ecutwfc =30.0,  nbnd = 8,&#xA;    input_dft='hse', nqx1 = 1, nqx2 = 1, nqx3 = 1, &#xA;    x_gamma_extrapolation = .true.,&#xA;    exxdiv_treatment = 'gygi-baldereschi',&#xA;    nosym = .true., noinv = .true&#xA; /&#xA; &amp;amp;electrons&#xA;    mixing_beta = 0.7&#xA; /&#xA;ATOMIC_SPECIES&#xA; Si  28.086  Si_ONCV_PBE-1.1.upf&#xA;ATOMIC_POSITIONS alat&#xA; Si 0.00 0.00 0.00 &#xA; Si 0.25 0.25 0.25 &#xA;K_POINTS crystal&#xA;8&#xA;  0.00000000  0.00000000  0.00000000  1.250000e-01&#xA;  0.00000000  0.00000000  0.50000000  1.250000e-01&#xA;  0.00000000  0.50000000  0.00000000  1.250000e-01&#xA;  0.00000000  0.50000000  0.50000000  1.250000e-01&#xA;  0.50000000  0.00000000  0.00000000  1.250000e-01&#xA;  0.50000000  0.00000000  0.50000000  1.250000e-01&#xA;  0.50000000  0.50000000  0.00000000  1.250000e-01&#xA;  0.50000000  0.50000000  0.50000000  1.250000e-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Wannier90 input file: silicon.win&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;! Silicon HSE 1&#xA; num_wann    = 8&#xA; num_bands   = 8&#xA; num_iter    = 20&#xA; kmesh_tol   = 0.0000001&#xA; auto_projections = .true.&#xA;&#xA;! Use as much precision as you can (at least 6 decimals) to prevent issues with matching to QE output&#xA;Begin Unit_Cell_Cart&#xA;-2.698804 0.0000 2.698804&#xA; 0.0000 2.698804 2.698804&#xA;-2.698804 2.698804 0.0000&#xA;End Unit_Cell_Cart&#xA;&#xA;begin atoms_frac&#xA;Si 0.00  0.00  0.00&#xA;Si 0.25  0.25  0.25&#xA;end atoms_frac&#xA;&#xA;!begin projections&#xA;!Si:sp3&#xA;!end projections&#xA;&#xA;! To plot the WF interpolated bandstructure&#xA;bands_plot       = .true.&#xA;bands_num_points = 200&#xA;&#xA;begin kpoint_path&#xA;L 0.50000  0.50000 0.5000 G 0.00000  0.00000 0.0000&#xA;G 0.00000  0.00000 0.0000 X 0.50000  0.00000 0.5000&#xA;X 0.50000 -0.50000 0.0000 K 0.37500 -0.37500 0.0000&#xA;K 0.37500 -0.37500 0.0000 G 0.00000  0.00000 0.0000&#xA;end kpoint_path&#xA;&#xA;! KPOINTS&#xA;&#xA;mp_grid : 2 2 2&#xA;&#xA;begin kpoints&#xA;0.0 0.0 0.0&#xA;0.0 0.0 0.5&#xA;0.0 0.5 0.0&#xA;0.0 0.5 0.5&#xA;0.5 0.0 0.0&#xA;0.5 0.0 0.5&#xA;0.5 0.5 0.0&#xA;0.5 0.5 0.5&#xA;end kpoints&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;pw2wannier90 input file: silicon.pw2wan&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA; prefix = 'Si-HSE'&#xA; outdir = './TMP_DIR'&#xA; seedname = 'silicon'&#xA; scdm_proj = .true.&#xA; scdm_entanglement = 'isolated'&#xA; scdm_mu = 0.0&#xA; scdm_sigma = 1.0&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;h2&gt;Calculation Procedure&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Run Wannier90 to generate some needed files, with the postprocessing option: &lt;code&gt;$ wannier90 -pp silicon&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Run your QE hybrid functional calculation (obviously use the correct mpi commands for your system when running in parallel): &lt;code&gt;$ pw.x -inp silicon.in &amp;gt; silicon.out&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Run pw2wannier: &lt;code&gt;$ pathtoqe/PP/src/pw2wannier.x -inp silicon.pw2wan&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Run Wannier90 again to do the calculation and get band structure: &lt;code&gt;$ wannier90 silicon&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Doing the above I got this band structure. It obviously has some problems (some bands jumping up above the VBM) but the gap is larger than PBE and I did this with a very sparse grid, and no optimization of any options.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AlgQ1.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AlgQ1.jpg&quot; alt=&quot;silicon band structure&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-06-04T17:05:49.997" LastActivityDate="2020-06-04T17:05:49.997" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1197" PostTypeId="1" CreationDate="2020-06-04T19:39:32.290" Score="17" ViewCount="132" Body="&lt;p&gt;I'm seeking references/benchmarks for transition state geometries of reactions in condensed phases like crystals, zeolites, or surfaces. Basically the system just needs to be considered big, yet ordered. I'm avoiding solution phase because those are too disordered to reproduce easily. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Does anyone have any suggestions or ways to find such examples?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm open to any benchmarks which use DFT planewave basis or QM/MM, and DFT tight binding. &lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-08-12T03:06:58.070" Title="Benchmark transition state geometries in condensed phases" Tags="|reference-request|qmmm|transition-state|tight-binding|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1198" PostTypeId="2" ParentId="1078" CreationDate="2020-06-04T20:26:20.817" Score="6" Body="&lt;h2&gt;TeraChem&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;QM/MM is not computationally more intensive than regular QM. In mechanical embedding the MM region is essentially free because it's just simple harmonic oscillators. In electrostatic embedding the MM region polarizes the charges of the QM region via the nuclear potential. As long as the external charge doesn't cause any SCF convergence issue the difference in speed between QM and QM/MM should be negligible. Therefore, there is no room to specifically design algorithms around this issue. Instead, I think the main issue is interface. Because molecular mechanics and quantum mechanics were once independent, the interface between good QM and MM codes is not always great.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Nevertheless, I consider &lt;strong&gt;&lt;a href=&quot;http://petachem.com/performance.html&quot; rel=&quot;noreferrer&quot;&gt;TeraChem&lt;/a&gt;&lt;/strong&gt; the &lt;em&gt;apex predator&lt;/em&gt; of gaussian type orbital theories (DFT, HF, CI CASSCF). TeraChem also has a good and efficient QM/MM interface via Amber&lt;sup&gt;&lt;a href=&quot;https://i.stack.imgur.com/SxIXJ.png&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here are some benchmark results from their website&lt;sup&gt;&lt;a href=&quot;https://i.stack.imgur.com/SxIXJ.png&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;&lt;/sup&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SxIXJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SxIXJ.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In comparison the times for the B3LYP/6-31G* using GAMMES on a single Intel Xeon X5680 3.33GHz CPU core* are&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;Taxol    Valinomycin   Olestra&#xA;10.6 min  22.6 min   3.6 hours&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;*It's unclear what type of CPU the GPU study used, however&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More benchmarks can be found in the original publication&lt;sup&gt;[3]&lt;/sup&gt;. The speedups increase with system size, but you can generally expect about 4x speedup for smaller systems and up to 200x for larger systems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The code has also been efficiently parallelized with GPUs for multi-reference calculations like CASSCF &lt;sup&gt;[4]&lt;/sup&gt; and is very efficient. In that paper the authors claim that theu've performed the largest CASSCF calculation in terms of total number of atoms by greater than an order of magnitude  (e.g. CAS(2,2) on 1000 waters or something like that).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In my experience with TeraChem, I feel as if one to two GPUs (GTX-980 or GTX-1080s) are about as good as 16-28 CPUs for your typically application. In your typical dense GPU cluster there is usually 5-8 GPU slots so your looking at getting some pretty serious computational power. &lt;/p&gt;&#xA;&#xA;&lt;hr&gt;&#xA;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Isborn, C. M., Götz, A. W., Clark, M. A., Walker, R. C. &amp;amp; Martínez, T. J. Electronic absorption spectra from MM and ab initio QM/MM molecular dynamics: Environmental effects on the absorption spectrum of photoactive yellow protein. J. Chem. Theory Comput. 8, 5092–5106 (2012).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://petachem.com/performance.html&quot; rel=&quot;noreferrer&quot;&gt;http://petachem.com/performance.html&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ufimtsev, I. S. &amp;amp; Martinez, T. J. Quantum chemistry on graphical processing units. 3. Analytical energy gradients, geometry optimization, and first principles molecular dynamics. J. Chem. Theory Comput. 5, 2619–2628 (2009).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;An atomic orbital-based formulation of the complete active space self-consistent field method on graphical processing units. J. Chem. Phys. 142, (2015).&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-06-04T20:52:56.277" LastActivityDate="2020-06-04T20:52:56.277" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1199" PostTypeId="2" ParentId="1058" CreationDate="2020-06-05T12:42:46.073" Score="12" Body="&lt;p&gt;Great question, will allow me to advertize our newly-released DFT code :](&lt;a href=&quot;https://github.com/JuliaMolSim/DFTK.jl/&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/JuliaMolSim/DFTK.jl/&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The rloc parameter is the characteristic distance at which the pseudopotential acts. At distances bigger than rloc, the potential starts to behave like a Coulomb potential. Note that the nonlocal potential also has a characteristic size, though. Generally speaking, the largest rloc the better for numerical purposes (because the potential is less sharp around the nuclei). It can vary a lot from element to element, as the following Julia script shows:&#xA;(edit: with corresponding Coulomb potential, following Michael's suggestion)&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;using DFTK&#xA;using PyPlot&#xA;&#xA;x = range(0, 2, length=10000)&#xA;for pseudo in (&quot;Si-q4&quot;, &quot;O-q6&quot;, &quot;H-q1&quot;)&#xA;    psp = load_psp(&quot;hgh/lda/$(pseudo)&quot;)&#xA;    p, = plot(x, DFTK.eval_psp_local_real.(Ref(psp), x), label=pseudo, lw=3)&#xA;    q = parse(Int, pseudo[end])&#xA;    plot(x, -q ./ x, color=p.get_color(), linestyle=&quot;-.&quot;)&#xA;    axvline(psp.rloc, color=p.get_color(), lw=2)&#xA;    xlabel(&quot;r (Bohr)&quot;)&#xA;end&#xA;ylim([-40, 0])&#xA;legend()&#xA;&#xA;println.([(psp.identifier, load_psp(psp.identifier).rloc) for psp in DFTK.list_psp(family=&quot;hgh&quot;, functional=&quot;lda&quot;)])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/G0LeS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/G0LeS.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="316" LastEditorUserId="316" LastEditDate="2020-06-05T12:52:18.090" LastActivityDate="2020-06-05T12:52:18.090" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1200" PostTypeId="2" ParentId="1161" CreationDate="2020-06-05T14:42:18.177" Score="16" Body="&lt;p&gt;This is Steve Plimpton. So far as I know there&#xA;is no official DYNAMO website or download location.&#xA;The code long pre-dates the popularity of source code &quot;repositories&quot;.  It&#xA;was developed by Daw and Foiles (mentioned in the thread),&#xA;two or the originators of EAM potentials.&#xA;That said, I do have a tarball I can send you &#xA;if you contact me via my work email - I'm at Sandia Labs.&#xA;I'm not sure what DYNAMO version it is.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As was mentioned, we put many DYNAMO features&#xA;into ParaDyn which we wrote to allow EAM models&#xA;to run in parallel, but that was in the 1990s&#xA;and DYNAMO may have evolved since then.  And as was&#xA;also said, the parallel LAMMPS MD code includes the&#xA;original EAM (a la DYNAMO) and a variety of EAM&#xA;variants, including MEAM (modified EAM) and some&#xA;angular-dependent versions.  LAMMPS is actively supported&#xA;and has its own mail list where you can ask further questions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Hope that helps,&#xA;Steve&lt;/p&gt;&#xA;" OwnerUserId="804" LastEditorUserId="5" LastEditDate="2020-06-05T15:20:24.663" LastActivityDate="2020-06-05T15:20:24.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1201" PostTypeId="2" ParentId="1161" CreationDate="2020-06-05T14:47:38.117" Score="10" Body="&lt;p&gt;I should also mention that there are several repositories on the web of interatomic potentials, which include many, many EAM files&#xA;for different materials.  These are the files that a code like DYNAMO&#xA;or LAMMPS reads in, with tabulated values for the EAM functionals, not code implementations of the EAM equations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This doc page in the LAMMPS manual, lists several of them:&#xA;&lt;a href=&quot;https://lammps.sandia.gov/doc/pair_eam.html&quot; rel=&quot;noreferrer&quot;&gt;https://lammps.sandia.gov/doc/pair_eam.html&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The last one on the list for the OpenKIM project, is a good place to start.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Steve&lt;/p&gt;&#xA;" OwnerUserId="804" LastEditorUserId="5" LastEditDate="2020-06-05T15:21:51.660" LastActivityDate="2020-06-05T15:21:51.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1202" PostTypeId="1" AcceptedAnswerId="1204" CreationDate="2020-06-05T18:39:23.810" Score="16" ViewCount="636" Body="&lt;p&gt;It is very well known that Kohn-Sham DFT underestimates bandgap. To get an accurate estimate of the bandgap, people often turn to Hybrid functionals (if they don't want to perform the actual quasiparticle calculation). I understand how the Hybrid functional, say for example, HSE works. It is an admixture (of a specific ratio) of Hartree Fock and KS-DFT. This can give a more reliable estimate of the bandgap in most cases. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;But my question is as follows. Often, people perform KS-DFT calculations to study the electronic properties, the optical selection rules etc. Then, they just calculate the bandstructure with the hybrid functional turned on, to get a more agreeable bandgap. Does this mean the character of the bands is unchanged between KS-DFT and HSE? Is the electronic band gap the only thing that changes between these two calculations? In this context, I've come across a term called 'rigid shift' which just shifts the Hamiltonian without changing the wavefunctions. Is 'rigid shift' relevant here?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-06-05T22:06:56.270" LastActivityDate="2020-06-07T08:12:12.457" Title="Is the electronic band gap the only thing that is affected, when switching from standard KS-DFT to Hybrid functionals?" Tags="|density-functional-theory|functional|kohn-sham|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1203" PostTypeId="1" CreationDate="2020-06-05T20:56:22.420" Score="8" ViewCount="1809" Body="&lt;p&gt;I came across the band structure colored as bellow&lt;sup&gt;1&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EBGr8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EBGr8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, each band was colored depending of the atom contribution to each band.&lt;/p&gt;&#xA;&lt;p&gt;Googling, I found it was done using the concept of &lt;em&gt;fat&lt;/em&gt; bands. The definition of the it is&lt;sup&gt;2&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The fat bands &lt;span class=&quot;math-container&quot;&gt;${F_{i,n,\sigma ,\vec k}}$&lt;/span&gt; are the periodic equivalent of the Mulliken population. They are defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$${F_{i,n,\sigma ,\vec k}} = \sum\limits_j {{C_{i,n,\sigma ,\vec k}}{C_{j,n,\sigma ,\vec k}}{S_{i,j,\vec k}}}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;${{C_{i,n,\sigma ,\vec k}}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S_{i,j,\vec k}$&lt;/span&gt; are the orbital coefficients and the overlap matrix elements respectively. The indices &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; denote basis functions, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the band index, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is the spin index and &lt;span class=&quot;math-container&quot;&gt;$\vec k$&lt;/span&gt; is a reciprocal vector in the Brillouin zone.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I understand is that now there is a projection/identification of the contribution of each atom (orbital) one each band.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;why &lt;em&gt;fat&lt;/em&gt; bands? Is there other meaning/undestanding for them?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;1 Chen Gong, et al., Band Structure Engineering by Alloying for Photonics, Advanced Optical Material, &lt;strong&gt;6&lt;/strong&gt;, 1800218 (2018). &lt;a href=&quot;http://dx.doi.org/10.1002/adom.201800218&quot; rel=&quot;nofollow noreferrer&quot;&gt;dx.doi.org/10.1002/adom.201800218&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;2 &lt;a href=&quot;https://www.scm.com/doc/BAND/Analysis/Band_Structure.html#definition-of-the-fat-bands&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.scm.com/doc/BAND/Analysis/Band_Structure.html#definition-of-the-fat-bands&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-28T00:38:40.367" LastActivityDate="2020-07-28T03:34:18.127" Title="What is the meaning of fat bands?" Tags="|band-structure|terminology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1204" PostTypeId="2" ParentId="1202" CreationDate="2020-06-06T02:44:45.427" Score="11" Body="&lt;p&gt;The band gap problem in DFT is not just due to approximate exchange-correlation functionals--it is a reflection of the fact that the Kohn-Sham (K-S) orbitals are a mathematical construction of a non-physical, non-interacting system of electrons that yields the true ground state charge density of the real many-body system. In exact DFT, the derivative of the total energy vs. number of electrons added to the system is piece-wise continuous, linear for fractional numbers added and with a discontinuity at each integer number of electrons. This discontinuity is a significant contribution to the difference between the true gap and the K-S gap. Hybrid functionals improve the treatment of band gaps because they incorporate part of the derivative discontinuity into the K-S eigenvalue gap (DFT+U also does this). You can read up on many papers on this subject. A lot of fundamental work was done in this area by Sham, Perdew, Burke, Cohen, Levy and others. I've included a short bibliography. This is definitely not the same as &quot;rigid shift&quot; or &quot;scissor operator&quot; which you mentioned.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Hybrid functionals can definitely change the character of the bands. At the end of the day you are still removing some of the spurious self-interaction of DFT exchange functionals. This should also give energies (e.g. formation energy, adsorption energy, etc.) that are more accurate, especially when dealing with systems that have more localized states that exacerbate the self-interaction issue. This is in fact the original intention of hybrid functionals: to correct the self-interaction present in DFT approximate exchange and get better predictions of the thermochemical properties of molecules. It's worth reading Becke's original hybrid functional paper.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;That being said, I'm sometimes surprised by how little the general picture changes sometimes. One nice paper to illustrate this is &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.86.235117&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; by He and Franchini, which studies first-row transition metal perovskites with HSE. HSE can help split up manifolds that are normally tangled together in PBE, but the general picture of bonding stays pretty similar overall. This is in contrast to using DFT+U empirically and just fitting to a desired quantity, which can also change the bonding character significantly. Of course, in materials where self-interaction error is very large, or in some more exotic situations like orbital ordering, etc. HSE can still have a big impact on the electronic structure (see the He and Franchini paper sections on LaTiO3 or LaVO3 as opposed to LaScO3, or LaFeO3-- the electronic structures are significantly different with HSE vs. PBE in the former cases, and not as much in the latter with the exception of the gap).&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Perdew, J. P., Parr, R. G., Levy, M. &amp;amp; Balduz, J. L. Density-Functional Theory for Fractional Particle Number: Derivative Discontinuities of the Energy. Phys. Rev. Lett. 49, 1691–1694 (1982).&lt;/li&gt;&#xA;&lt;li&gt;Perdew, J. &amp;amp; Levy, M. Physical Content of the Exact Kohn-Sham Orbital Energies: Band Gaps and Derivative Discontinuities. Physical Review Letters 51, 1884–1887 (1983).&lt;/li&gt;&#xA;&lt;li&gt;Sham, L. &amp;amp; Schlüter, M. Density-functional theory of the band gap. Physical Review B 32, 3883–3889 (1985).&lt;/li&gt;&#xA;&lt;li&gt;Lannoo, M., Schlüter, M. &amp;amp; Sham, L. Calculation of the Kohn-Sham potential and its discontinuity for a model-semiconductor. Physical Review B 32, 3890–3899 (1985).&lt;/li&gt;&#xA;&lt;li&gt;Perdew, J. P. Density functional theory and the band gap problem. International Journal of Quantum Chemistry 28, 497–523 (1986).&lt;/li&gt;&#xA;&lt;li&gt;Becke, A. D. A new mixing of Hartree–Fock and local density‐functional theories. The Journal of Chemical Physics 98, 1372–1377 (1993).&lt;/li&gt;&#xA;&lt;li&gt;Seidl, A., Görling, A., Vogl, P., Majewski, J. A. &amp;amp; Levy, M. Generalized Kohn-Sham schemes and the band-gap problem. Physical Review B 53, 3764–3774 (1996).&lt;/li&gt;&#xA;&lt;li&gt;Perdew, J. P., Ernzerhof, M. &amp;amp; Burke, K. Rationale for mixing exact exchange with density functional approximations. The Journal of Chemical Physics 105, 9982 (1996).&lt;/li&gt;&#xA;&lt;li&gt;Cohen, A. J., Mori-Sánchez, P. &amp;amp; Yang, W. Fractional charge perspective on the band gap in density-functional theory. Phys. Rev. B 77, 115123 (2008).&lt;/li&gt;&#xA;&lt;li&gt;Yang, W., Cohen, A. J. &amp;amp; Mori-Sánchez, P. Derivative discontinuity, bandgap and lowest unoccupied molecular orbital in density functional theory. The Journal of Chemical Physics 136, 204111 (2012).&lt;/li&gt;&#xA;&lt;li&gt;Mori-Sánchez, P. &amp;amp; J. Cohen, A. The derivative discontinuity of the exchange–correlation functional. Physical Chemistry Chemical Physics 16, 14378–14387 (2014).&lt;/li&gt;&#xA;&lt;li&gt;Himmetoglu, B., Floris, A., de Gironcoli, S. &amp;amp; Cococcioni, M. Hubbard-corrected DFT energy functionals: The LDA+U description of correlated systems. International Journal of Quantum Chemistry 114, 14–49 (2014).&lt;/li&gt;&#xA;&lt;li&gt;Perdew, J. P. et al. Understanding band gaps of solids in generalized Kohn–Sham theory. Proceedings of the National Academy of Sciences 114, 2801–2806 (2017).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-06-06T03:20:24.737" LastActivityDate="2020-06-06T03:20:24.737" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1206" PostTypeId="1" CreationDate="2020-06-06T13:05:42.083" Score="12" ViewCount="563" Body="&lt;p&gt;I'm a beginner at DFT calculations with VASP software. I use it to calculate the band structure of graphene and I obtain the following result:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/qwmWy.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qwmWy.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;I used it to calculate the band structure of graphene with the tight binding method by hand. It should not be squeezed on the right hand side of the Dirac cone in the Fermi level as shown in the figure. How can I explain this phenomenon? My question might be very stupid. Is it from the effect of another orbital that I didn't take into account when I use tight binding method?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2020-07-25T19:21:08.647" LastActivityDate="2020-07-25T19:21:08.647" Title="DFT vs tight-binding solutions for a Dirac cone in graphene: Why is the DFT version squeezed?" Tags="|density-functional-theory|vasp|band-structure|tight-binding|graphene|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1207" PostTypeId="1" CreationDate="2020-06-06T14:56:15.613" Score="10" ViewCount="568" Body="&lt;p&gt;How can an MM-GBSA(molecular mechanics energies combined with generalized Born and surface area continuum solvation) calculation be done from an induced fit docking (IFD) output?&#xA;I performed an IFD and now I would like to run an MM-GBSA calculation, but when I try to start it, I get a warning message that says: &#xA;The ligand contains more than 300 atoms and the output is very big.&#xA;Could you please explain what I have to do for performing this calculation?&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="243" LastEditDate="2020-06-06T18:24:32.587" LastActivityDate="2020-06-06T19:25:48.020" Title="MM-GBSA from Induced Fit Docking on Maestro" Tags="|software|gibbs-free-energy|docking|schrodinger-software|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1210" PostTypeId="2" ParentId="1207" CreationDate="2020-06-06T19:17:52.480" Score="6" Body="&lt;p&gt;The Prime MM-GBSA panel is bellow. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you can see, the first section is about choosing the structures to calculate the MM-GBSA energy.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The marked option works only for pose viewer files. IFD don't create this kind of file. If you want to use it, you need to work with some scripts/export in order to convert a &lt;em&gt;mae&lt;/em&gt; (or &lt;em&gt;maegz&lt;/em&gt;) file into a &lt;em&gt;.pv.mae&lt;/em&gt; (or &lt;em&gt;.pv.maegz&lt;/em&gt;) file and then use this option.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The second option is to separate the complex into two structure files: one for the protein and one for the ligand. Again, you can do this using the table or using the scripts. &lt;strong&gt;Here you have to be careful to not exchange the files (selecting the receptor file in the ligand selection will give you an error about the number of atoms).&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PF0au.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PF0au.jpg&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-06T19:25:48.020" LastActivityDate="2020-06-06T19:25:48.020" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1211" PostTypeId="2" ParentId="683" CreationDate="2020-06-06T19:42:46.470" Score="4" Body="&lt;p&gt;JCP article titled &quot;Increasing the applicability of density functional theory. III. Do consistent Kohn-Sham density functional methods exist?&quot;  provides  Provide non-traditional view on KS eigenvalues. &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4755818.&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/abs/10.1063/1.4755818&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;If one construct KS potential paying attention of xc potential that is KS eigenvalues of all occupied orbitals should be a good approximation of ionization energies one manage to construct a single correlated particle theory. As a consequence one can observe consistent behaviour in DFT results as shown in this JCP article &quot;Increasing the applicability of density functional theory. IV. Consequences of ionization-potential improved exchange-correlation potentials&quot; &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4871409&quot; rel=&quot;nofollow noreferrer&quot;&gt; https://aip.scitation.org/doi/abs/10.1063/1.4871409&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="322" LastActivityDate="2020-06-06T19:42:46.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1212" PostTypeId="2" ParentId="392" CreationDate="2020-06-06T20:08:20.263" Score="13" Body="&lt;h1&gt;2005 (Bartlett): &lt;em&gt;ab initio&lt;/em&gt; DFT&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;Basically one takes the xc functional from a wave function approach such as MBPT(2), CC, etc. and constructs an xc potential from them using density conditions or a functional derivatives approach. Summary of developments is best captured in the following article: &quot;&lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.5116338&quot; rel=&quot;noreferrer&quot;&gt;Adventures in DFT by a wave function theorist&lt;/a&gt;.&quot;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Details on how to construct a local exchange potential from the HF exchange energy can found in the following article: &quot;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.83.5455&quot; rel=&quot;noreferrer&quot;&gt;Exact exchange treatment for molecules in finite-basis-set Kohn-Sham theory&lt;/a&gt;,&quot; while details about constructing the correlation potential from MBPT(2) energy can be found in the article title &quot;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.1904585&quot; rel=&quot;noreferrer&quot;&gt;Ab initio density functional theory: The best of both worlds?&lt;/a&gt;&quot; &lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-06-11T01:35:57.770" LastActivityDate="2020-06-11T01:35:57.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1213" PostTypeId="2" ParentId="526" CreationDate="2020-06-07T02:40:21.533" Score="10" Body="&lt;p&gt;&lt;strong&gt;DFT is single effective correlated particle theory&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Problems that can be described by single determinant theory DFT in principle should able to provide a good description given that exact form of xc functional is known. It is not the problem of DFT that it fails. Failure is due to approximate nature of xc functional. One should in KS-DFT (one that uses explicit density dependent form of xc), non-local potential is approximated my local form, it might work certain problems not for other problems. That is why optimized amount of non-local (HF) exchange help address some problem. Please have a look at article titled &quot;Increasing the applicability of density functional theory. III. Do consistent Kohn-Sham density functional methods exist?&quot; &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4755818&quot; rel=&quot;noreferrer&quot;&gt;https://aip.scitation.org/doi/abs/10.1063/1.4755818&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-06-08T21:35:23.990" LastActivityDate="2020-06-08T21:35:23.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1214" PostTypeId="2" ParentId="63" CreationDate="2020-06-07T03:20:37.753" Score="9" Body="&lt;h1&gt;2007 (Becke &amp;amp; Johnson): XDM&lt;/h1&gt;&#xA;&lt;p&gt;XDM stands for &amp;quot;exchange-hole dipole moment&amp;quot; which is a model &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.2795701&quot; rel=&quot;noreferrer&quot;&gt;introduced by Becke and Johnson in 2007&lt;/a&gt; for calculating dispersion constants. The formulas are as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}&#xA;\!\!\!\!\!\!\!\!C_6    &amp;amp;= \frac{\alpha_i\alpha_j}{\mathcal{M}_i\alpha_j + \mathcal{M}_j\alpha_i} \mathcal{M}_i\mathcal{M}_j           \tag{1}\label{eq1} \\&#xA;\!\!\!\!\!\!\!\!C_8    &amp;amp;=   \frac{\alpha_i\alpha_j}{\mathcal{M}_i\alpha_j + \mathcal{M}_j\alpha_i}\left(\frac{3}{2}\mathcal{M}_{1i}\mathcal{M}_{2j} + \frac{3}{2}\mathcal{M}_{2i}\mathcal{M}_{1j}\right)            \tag{2}\label{eq2}\\&#xA;\!\!\!\!\!\!\!\!C_{10} &amp;amp;=   \frac{\alpha_i\alpha_j}{\mathcal{M}_i\alpha_j + \mathcal{M}_j\alpha_i}\left(\frac{10}{5}\mathcal{M}_{1j}\mathcal{M}_{3j} + \frac{10}{5}\mathcal{M}_{3i} \mathcal{M}_{1j} + \frac{21}{5}\mathcal{M}_{2i} \mathcal{M}_{2j} \right), \tag{3}\label{eq3}&#xA;\end{align}$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where for the system &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;: the dipole polarizability is &lt;span class=&quot;math-container&quot;&gt;$\alpha_{x}$&lt;/span&gt; and the &lt;span class=&quot;math-container&quot;&gt;$l^{\textrm{th}}$&lt;/span&gt; multi-pole moment is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{M_{lx}}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$l=1,2,3$&lt;/span&gt; correspond to the dipole, quadrupole, and octupole moments respectively.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-07T03:20:37.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1215" PostTypeId="1" CreationDate="2020-06-07T06:37:11.197" Score="22" ViewCount="3808" Body="&lt;p&gt;Is there a Windows-based molecular dynamics simulation software which is easy to use?&lt;/p&gt;&#xA;" OwnerUserId="813" LastEditorUserId="5" LastEditDate="2021-03-12T20:27:39.383" LastActivityDate="2022-12-12T12:35:29.987" Title="What software is available to do molecular dynamics on Windows?" Tags="|software|molecular-dynamics|one-topic-per-answer|software-recommendations|" AnswerCount="6" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1216" PostTypeId="2" ParentId="105" CreationDate="2020-06-07T07:45:46.827" Score="9" Body="&lt;p&gt;Given that variational quantum Monte Carlo (VQMC) is specifically for calculating ground state properties, it shouldn't have any problem with finding the &lt;span class=&quot;math-container&quot;&gt;$T=0$&lt;/span&gt; energy. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;It may be difficult to do a material as complicated as gold, but I'm not an expert in this field by any means. This article discusses structural optimization with VQMC: &#xA;&lt;a href=&quot;https://doi.org/10.1063/1.466885&quot; rel=&quot;noreferrer&quot;&gt;S. Tanaka J. Chem. Phys. &lt;strong&gt;100&lt;/strong&gt;, 7416 (1994)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-06-07T07:45:46.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1217" PostTypeId="2" ParentId="1202" CreationDate="2020-06-07T08:12:12.457" Score="7" Body="&lt;p&gt;To add to the comprehensive answer by Kevin J. M., an example of a class of systems in which the use of a hybrid functional can lead to radically different band structure characteristics compared to a semilocal DFT, is in the area of topological materials. In this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.041109&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; the authors show that semilocal DFT incorrectly predicts whether a material is topologically ordered or not (which in this case essentially depends on the &quot;ordering&quot; of the bands), when compared to a quasiparticle &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt; approach. They also include calculations with the hybrid HSE06 functional, and find that in most cases (but there are a few exceptions), the hybrid agrees with the quasiparticle approach, and therefore predicts a different topological order to that predicted by the semilocal DFT. This is an example in which a simple &quot;rigid shift&quot; would fail.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-07T08:12:12.457" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1218" PostTypeId="2" ParentId="1215" CreationDate="2020-06-07T11:08:50.567" Score="17" Body="&lt;h2&gt;LAMMPS&lt;/h2&gt;&#xA;&lt;p&gt;LAMMPS provides pre-compiled Windows binaries. You can download them &lt;a href=&quot;http://packages.lammps.org/windows.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="674" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-07T12:56:47.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1219" PostTypeId="2" ParentId="1206" CreationDate="2020-06-07T12:41:14.663" Score="11" Body="&lt;p&gt;Oh! I found the answer already. Since I'm doing the calculation along the High symmetry point. Im doing the calculation along G -&gt; K -&gt; M -&gt; G, that's why the right hand sides show such phenomena. In tight binding I plot the band along G -&gt; K -&gt; G. I try to reproduce the band along this direction, it matched with the tight binding solution. Thanks guys. It's my mistake.&lt;/p&gt;&#xA;" OwnerUserId="621" LastActivityDate="2020-06-07T12:41:14.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1220" PostTypeId="2" ParentId="1215" CreationDate="2020-06-07T13:43:00.957" Score="8" Body="&lt;h2&gt;Run any Linux program from Windows using Cygwin&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;If you really need running Molecular Dynamics on Windows, you can use &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Cygwin&quot; rel=&quot;noreferrer&quot;&gt;Cygwin&lt;/a&gt; and port your code from Linux to Windows. Using this, you can test some on them and select which one is easier for you (as it is a personal issue).&#xA;Be aware that their performance will be drastically affected as Linux is more efficient running jobs (distributing among cores and using memory) than Windows.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-06-11T21:14:05.783" LastActivityDate="2020-06-11T21:14:05.783" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="1221" PostTypeId="2" ParentId="1215" CreationDate="2020-06-07T14:38:05.697" Score="12" Body="&lt;h2&gt;OpenMM&lt;/h2&gt;&#xA;&lt;p&gt;OpenMM is a highly efficient molecular dynamics package which can run via Python. Therefore, any way you normally run python can work. For example, via a Jupyter (Ipython) notebook, via a python GUI, Window's PowerShell,  Window's subsystem for Linux, etc.&lt;/p&gt;&#xA;&lt;p&gt;You can download OpenMM via the python manager &lt;a href=&quot;https://anaconda.org/omnia/openmm&quot; rel=&quot;noreferrer&quot;&gt;Anaconda&lt;/a&gt;, which makes it very easy to install. For example,&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;conda install -c omnia openmm&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;OpenMM, however, is not an input/output type of program but is directed completely through python code. This is also known as an Application Programming Interface (API).&lt;/p&gt;&#xA;&lt;p&gt;This is good because you know exactly what is going on and have more finer control. But that also does require you know what you're doing more. There are several code bases out there that attempt to create easier &amp;quot;wrappers&amp;quot; around the python. For example, see&#xA;&lt;a href=&quot;https://github.com/leeping/OpenMM-MD&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/leeping/OpenMM-MD&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-07T15:04:00.440" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1222" PostTypeId="2" ParentId="1215" CreationDate="2020-06-07T16:05:08.193" Score="13" Body="&lt;h2&gt;GROMACS&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;Instructions for installing GROMACS on Windows (even if you don't want to use Cygwin!) are &lt;a href=&quot;http://www.gromacs.org/Documentation_of_outdated_versions/Installation_Instructions_4.5/Windows&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free, and open-source.&lt;/li&gt;&#xA;&lt;li&gt;Long history: First released in 1991, based on an earlier program called GROMOS from 1978.&lt;/li&gt;&#xA;&lt;li&gt;Under very active development: For many codes, the majority of the development was done years or decades ago, &lt;a href=&quot;https://github.com/gromacs/gromacs/graphs/contributors&quot; rel=&quot;noreferrer&quot;&gt;but the development of GROMACS seems only to have grown&lt;/a&gt;, not waned. Last year (2019) seems to have been the most active year of development so far! &lt;/li&gt;&#xA;&lt;li&gt;Since the very beginning (decades ago), it was designed to run in parallel (i.e. fast). It now also supports GPUs.&lt;/li&gt;&#xA;&lt;li&gt;According to Steve Plimpton, &lt;a href=&quot;https://lammps.sandia.gov/threads/msg05362.html&quot; rel=&quot;noreferrer&quot;&gt;a fator of 2x speed-up in GROMACS compared to LAMMPS is &quot;not surprising&quot;&lt;/a&gt; because GROMACS has pairwise interactions implemented in assembly code. &lt;strong&gt;Therefore GROMACS might be the &lt;em&gt;fastest&lt;/em&gt; free MD code.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is primarily a classical MD code, so quantum effects are not the focus. QM/MM is possible, but seems to involve interfaces with other codes such as GAMESS, GAUSSIAN, or CPMD. Codes like DFTB+ and BigDFT might be better when quantum effects are important.&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;On &lt;a href=&quot;http://www.gromacs.org/About_Gromacs&quot; rel=&quot;noreferrer&quot;&gt;their own website&lt;/a&gt;, they say:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;&quot;It is primarily designed for biochemical molecules like proteins,&#xA;  lipids and nucleic acids that have a lot of complicated bonded&#xA;  interactions, but [...] many groups are also using it for research on non-biological systems, e.g. polymers.&quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;So it's certainly possible to run GROMACS for non-biological systems, but it's not their focus.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="536" LastEditDate="2020-06-07T16:48:15.613" LastActivityDate="2020-06-07T16:48:15.613" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1223" PostTypeId="2" ParentId="526" CreationDate="2020-06-08T10:06:44.443" Score="13" Body="&lt;p&gt;Known failures of density functional approximations (DFAs) include anions, charge transfer systems and point defects (e.g. vacancy states). These are mainly due to self-interaction error, which can be mitigated to some level with hybrid functionals and range-separated hybrids.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;DFAs are also generally unreliable for systems with strong correlation, like many transition metal complexes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;These are problems also when the calculations are done correctly, i.e. at the complete basis set limit. (The quality of the results at any level of theory will suffer enormously if there are coarse errors in the computational paradigm, e.g. insufficient basis set, insufficient quadrature, insufficient k point sampling, etc.)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-08T10:06:44.443" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1224" PostTypeId="1" AcceptedAnswerId="1248" CreationDate="2020-06-08T16:05:14.170" Score="27" ViewCount="4849" Body="&lt;p&gt;In some science fields there are efforts to provide customized distributions, so you can get a productive environment with minimum set-up overhead. For example, in high energy particle physics, we have &lt;a href=&quot;https://www.scientificlinux.org/&quot; rel=&quot;noreferrer&quot;&gt;Scientific Linux&lt;/a&gt;, in mathematics we have &lt;a href=&quot;http://www.mathlibre.org/&quot; rel=&quot;noreferrer&quot;&gt;MathLibre&lt;/a&gt;, and in cybersecurity research we have &lt;a href=&quot;https://www.kali.org/&quot; rel=&quot;noreferrer&quot;&gt;Kali Linux&lt;/a&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Is there any effort like these for materials modeling?&lt;/strong&gt; If not, which Linux distributions come the closest?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;Please list only one Linux distribution per answer!&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-09-07T20:58:40.863" LastActivityDate="2021-05-20T22:26:12.763" Title="Which Linux distribution is best for Matter Modeling?" Tags="|software|one-topic-per-answer|high-performance-computing|open-source|matter-modeling-specific-technology|" AnswerCount="9" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1225" PostTypeId="6" CreationDate="2020-06-08T20:42:04.437" Score="0" Body="&lt;p&gt;My name is &lt;a href=&quot;http://pessoas.unifal-mg.edu.br/camps/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ihosvany  Camps&lt;/a&gt;. I'm Cuban-Brazilian living in Brazil and working as an Associate Professor at &lt;a href=&quot;https://www.unifal-mg.edu.br/portal/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Federal University of Alfenas&lt;/a&gt;, Brazil. I own a PhD in Condensed Matter physics. My research is focused in Computational Modeling applied to condensed matter, drug design and pharmaceutical polymorphism.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I had already used molecular mechanic, semi-empiric, &lt;em&gt;ab initio&lt;/em&gt; and DFT methods to study the electronic and transport properties of nanostructures and nanodevices; &lt;em&gt;de novo&lt;/em&gt; drug design; molecular docking; fragment based drug design; and theoretical crystal structure predictions among other modeling techniques.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am making my name available to the community in order to participate in the selection of moderators. I will continue putting all &lt;a href=&quot;https://orcid.org/0000-0001-5898-1313&quot; rel=&quot;nofollow noreferrer&quot;&gt;my experience&lt;/a&gt;, my time and my effort to the well functioning and growth of the forum.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thank you very much.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Regards,&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Camps&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-09T12:10:08.993" LastActivityDate="2020-06-09T12:10:08.993" CommentCount="4" CommunityOwnedDate="2020-06-08T20:42:04.437" ContentLicense="CC BY-SA 4.0" />
  <row Id="1226" PostTypeId="2" ParentId="1224" CreationDate="2020-06-08T20:51:51.697" Score="15" Body="&lt;h2&gt;CAELinux&lt;/h2&gt;&#xA;&lt;p&gt;(to simulate continuous material)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.caelinux.com/CMS3/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CAELinux's official page states:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Based on the open-source CAD/CAM software such as Freecad, LibreCAD, PyCAM and Slic3r and CAE softwares like Salomé, Code_Aster, Code_Saturne, Calculix, OpenFOAM and Elmer , you can design  your CAD geometry, &lt;em&gt;&lt;strong&gt;perform multiphysics simulations&lt;/strong&gt;&lt;/em&gt; to optimize your design, generate G-code for prototyping with 3D printing &amp;amp; milling, and even develop your own PCBs &amp;amp; microcontroller based electronic circuits for automation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastEditorUserId="3" LastEditDate="2020-07-23T11:36:00.543" LastActivityDate="2020-07-23T11:36:00.543" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1227" PostTypeId="2" ParentId="392" CreationDate="2020-06-08T23:23:12.827" Score="22" Body="&lt;h1&gt;Dispersion corrected methods (2007/2010)&lt;/h1&gt;&#xA;&lt;p&gt;Lots of answers already, I would say the main ones are covered. However, in the spirit of the question, I don't think anyone has done dispersion corrections yet. So,&lt;/p&gt;&#xA;&lt;p&gt;There are many levels of Dispersion corrected methods, but I would say the most common is from Grimme et al. in 2010 (&lt;a href=&quot;http://dns2.asia.edu.tw/%7Eysho/YSHO-English/1000%20WC/PDF/J%20Che%20Phy132,%20154104.pdf&quot; rel=&quot;noreferrer&quot;&gt;Grimme et. al. 2010 paper.&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;The energy correction is calculated as (taken from Frank Jensen's textbook)&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;   \Delta E_{\rm disp} = -\sum_{n=6} s_n \sum_{\rm AB} \frac{C_n^{\rm AB}}{R_{\rm AB}^n}f_{\rm damp}(R_{\rm AB})&#xA;\end{equation}&lt;/span&gt;&#xA;Further variations can also account for higher order &lt;span class=&quot;math-container&quot;&gt;$R^n$&lt;/span&gt; dependance.&lt;/p&gt;&#xA;&lt;p&gt;Becke &amp;amp; Johnson have also done work on more physics based corrections, more can be found at a different &lt;a href=&quot;https://materials.stackexchange.com/questions/63/what-are-the-different-ways-of-calculating-dispersion-constants&quot;&gt;question, here.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="740" LastEditorUserId="5" LastEditDate="2020-10-10T21:57:14.393" LastActivityDate="2020-10-10T21:57:14.393" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1228" PostTypeId="1" AcceptedAnswerId="1235" CreationDate="2020-06-09T03:34:44.557" Score="28" ViewCount="2442" Body="&lt;p&gt;Kohn-Sham DFT appears to be so popular even though it is strictly a ground-state method - all calculations are done at 0 K. How then, is it so popular when describing materials that have real-life applications (possibly at room temperatures, or much higher temperatures)? Or am I mistakenly deeming KS-DFT to be too popular when there are other more suitable methods like TD-DFT, GW-BSE etc?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-06-09T03:50:32.083" LastActivityDate="2020-06-10T13:56:56.930" Title="Given that Kohn-Sham DFT is strictly a ground-state method (at 0 K), how is it sufficient to describe materials in real-life applications?" Tags="|density-functional-theory|kohn-sham|td-dft|gw-bse|greens-functions|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1229" PostTypeId="2" ParentId="1228" CreationDate="2020-06-09T04:09:20.140" Score="23" Body="&lt;p&gt;You are correct that KS-DFT, strictly speaking, involves calculations of a potential energy surface at 0 K. However, if you accept that the density functional approximation you are using is sufficiently accurate, it is not too difficult of a stretch to go from 0 K to finite temperature conditions for an application of interest. The key assumption is that the potential energy surface itself does not significantly change from 0 K to finite temperature. Admittedly, I don't know of many examples of molecules or materials where this has been shown not to hold, but there are surely some I'm not aware of. As a side-note, I have read that for very hot, dense matter, there is a need to account for thermal (i.e. entropic) effects on the exchange-correlation energy, and this has led to some developments in thermal DFT (e.g. as discussed &lt;a href=&quot;https://arxiv.org/pdf/1701.00873.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;). Otherwise, is a very common assumption that the 0 K potential energy surface is relatively unchanged.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With knowledge of the 0 K structures and vibrational modes, you have essentially everything you need to compute thermochemical quantities at finite temperature. It's simply a matter of computing the relevant translational, rotational, vibrational, and electronic partition functions. There are several assumptions that go into each one of these components (e.g. ideal gas approximation, rigid rotor approximation, particle-in-a-box approximation, harmonic oscillator approximation), but that has relatively little to do with the fact that KS-DFT is at 0 K and more that you need some way to express the partition functions. There are countless references on this topic to choose from. For molecular systems, Chris Cramer's &quot;Essentials of Computational Chemistry: Theories and Models&quot; does a great job. For periodic DFT calculations, you may find the thermochemistry summary on the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html&quot; rel=&quot;noreferrer&quot;&gt;ASE webpage&lt;/a&gt; to be helpful. I have also put together a series of notes covering this topic on my website &lt;a href=&quot;http://sites.tufts.edu/andrewrosen/density-functional-theory/qm-thermo-kinetics/&quot; rel=&quot;noreferrer&quot;&gt;Rosen Review&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also, it's not as if TD-DFT isn't widely used. It's the method of choice for computing excited states, which could be useful for predicting UV-Vis or X-ray absorption spectra. To the best of my knowledge, the main use-case for TD-DFT is because KS-DFT is a ground state theory, not because KS-DFT is strictly true at 0 K.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Edit: Please see the comments by ProfM, which clarify and expand upon my answer. &lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-06-09T14:17:30.967" LastActivityDate="2020-06-09T14:17:30.967" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1230" PostTypeId="1" CreationDate="2020-06-09T04:33:04.713" Score="17" ViewCount="1406" Body="&lt;p&gt;Hartree-Fock density is free of self-interaction but lacks electron correlation effects, while the density from KS-DFT (using an xc functional or potential, both which are explicitly density-dependent and gradient-dependent) suffers from self-interaction errors but does incorporate electron correlation effects. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;When is the HF density better, and when is the KS density better?&lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="10" LastEditDate="2020-06-09T17:49:05.370" LastActivityDate="2020-06-09T17:49:05.370" Title="Hartree-Fock density vs Kohn-Sham density" Tags="|density-functional-theory|kohn-sham|hartree-fock|self-interaction|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1231" PostTypeId="2" ParentId="1215" CreationDate="2020-06-09T04:45:49.253" Score="13" Body="&lt;h2&gt;Run any Linux program on WSL (Windows Subsystem for Linux)&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;One interesting alternative is using the Windows Subsystem for Linux (more info at: &lt;a href=&quot;https://docs.microsoft.com/en-us/windows/wsl/install-win10&quot; rel=&quot;noreferrer&quot;&gt;https://docs.microsoft.com/en-us/windows/wsl/install-win10&lt;/a&gt; ). I know of successful cases where this has been used to install GROMACS (recent versions). I don't have a reason to believe it wouldn't work for other MD software as well. It also has a way of using the GPU with CUDA as in &lt;a href=&quot;https://developer.nvidia.com/cuda/wsl&quot; rel=&quot;noreferrer&quot;&gt;https://developer.nvidia.com/cuda/wsl&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Definitely something worth trying, it should be easy enough and we all know how Cygwin can be a pain to setup sometimes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This would've been a comment if I had enough votes to comment :).&lt;/p&gt;&#xA;" OwnerUserId="484" LastEditorUserId="5" LastEditDate="2020-06-11T21:12:23.737" LastActivityDate="2020-06-11T21:12:23.737" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1232" PostTypeId="2" ParentId="1224" CreationDate="2020-06-09T04:52:48.823" Score="30" Body="&lt;p&gt;There isn't a silver bullet for this, so in my humble opinion there isn't a &quot;best&quot; Linux distribution for this. Just as Kali is not &quot;the best&quot; for security and Scientific Linux is also not advertised as the &quot;best&quot; for HEP. They are just good enough alternatives that tackle some issues that may seem helpful for many users, such as including many things and not having to install them by hand.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Personally, I tend to use popular big distributions, that I know are well documented and won't cease to exist anytime soon. Any Linux distribution could be used for Matter Modelling. The features of the software and tools for Modelling are independent of the choice of distribution (in general). Also take into account that a lot of Matter Modelling involves generic tools that are not specific for the area (shell, modern python versions, up-to-date BLAS libraries, etc.).&lt;/p&gt;&#xA;" OwnerUserId="484" LastActivityDate="2020-06-09T04:52:48.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1233" PostTypeId="2" ParentId="308" CreationDate="2020-06-09T06:11:22.440" Score="5" Body="&lt;p&gt;Spin-orbit coupling effect can be included in electronic structure calculations using variational methods such as fully relativistic four-component Dirac HF or KS approach, or two-component approaches such as ZORA, X2C, DKH etc. Spin-orbit coupling effect can also be included as a perturbative correction. &lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-06-09T06:23:43.547" LastActivityDate="2020-06-09T06:23:43.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1234" PostTypeId="2" ParentId="1230" CreationDate="2020-06-09T06:57:06.403" Score="8" Body="&lt;p&gt;I guess this will go in the answer slot, it is a bit long for a comment.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;DFT typically has quite a bit less spin contamination than HF (attributed to the inclusion of correlation).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;One issue however is that DFT tends to favor electron delocalization, and conveniently HF tends to the opposite. This is part of why hybrid DFT methods get improvements, the over/under electron delocalization is &quot;averaged out&quot;. Hybrids also benefit from the HF exchange not suffering from self-interaction, however, range separation methods also correct for self-interaction errors if you don't want to use a hybrid (or apply range-separation to a hybrid for more of a win).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In Hartree-Fock virtual orbitals are akin to electron affinity(determined in the field of N electrons), whereas in DFT they are akin to exciting an electron(determined in a field of N-1 electrons).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Actually saying when HF is better or worse than DFT seems quite difficult to me since you must say what functional you are comparing HF to. There are many ways to fix-up a given DFT functional to overcome deficiencies, two well known corrections being range-separation and dispersion corrections.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;To give some sort of summary to what I have said, hopefully others will be more prolific in their answers my instincts say that &lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Summary&lt;/h2&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;HF would possibly be better for electron affinity when using a frozen orbital assumption (assuming a low quality bare-bones DFT functional).&lt;/li&gt;&#xA;&lt;li&gt;DFT provides a better density for systems where spin-contamination is an issue.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I look forward to more answers on this one.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2020-06-09T06:57:06.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1235" PostTypeId="2" ParentId="1228" CreationDate="2020-06-09T07:45:00.877" Score="28" Body="&lt;p&gt;These are a few extra points to complement Andrew Rosen's comprehensive response:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;To be absolutely clear, typical DFT calculations are &lt;em&gt;not&lt;/em&gt; performed at 0K, a better description of what happens is that they are performed &quot;for a static crystal&quot;. Static crystal means that the atoms are fixed at their crystallographic positions (which is what a typical DFT calculation does), but this situation is different from 0K. Even at 0K, the atomic nuclei move due to quantum zero-point motion (also called quantum fluctuations). This quantum zero-point motion is very small for compounds containing heavy elements, which means that in these cases &quot;0K&quot; and &quot;static crystal&quot; are almost the same and many people use the terms interchangeably. However, quantum zero-point motion can be very large for light elements, for example in solid hydrogen (the lightest of all compounds) it dominates even at room temperature. To perform a calculation at 0K (as opposed to a static crystal calculation), the strategy that Andrew Rosen proposed would still work if you use quantum statistics. For example, solving the vibrational problem within the harmonic approximation at the quantum mechanical level with give you the zero-point energy as the ground state of a quantum harmonic oscillator. A good reference for hydrogen is this &lt;a href=&quot;https://link.aps.org/doi/10.1103/RevModPhys.84.1607&quot; rel=&quot;noreferrer&quot;&gt;review article&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Although Andrew Rosen is correct in that the potential energy surface is largely temperature independent, there are a few situations in which the potential energy surface does vary significantly with temperature. An example of this is provided by many perovskite crystals (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{BaTiO_3}$&lt;/span&gt;), which undergo a series of temperature-induced structural phase transitions. For example, at very high temperatures the structure is cubic, and this structure sits at a minimum of the potential &lt;em&gt;free&lt;/em&gt; energy surface. However, if you calculated the potential energy surface (instead of the free energy surface), then it has a double-well shape and the cubic structure is at the saddle point, so the structure will lower its energy by distorting and going to one of the minima. This is precisely what happens at low temperatures because the corresponding free energy surface acquires a double-well shape, and the system undergoes a structural phase transition. A good early DFT reference for this is this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.52.6301&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;As already pointed out by others, the differences between DFT and TDDFT or &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt;-BSE are not related to the inclusion or exclusion of temperature. In this language, both TDDFT and &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt;-BSE have no temperature for the behaviour of the nuclei, and you could incoporate it in a similar fashion to what Andrew Rosen described for DFT.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastEditorUserId="7" LastEditDate="2020-06-09T14:31:58.007" LastActivityDate="2020-06-09T14:31:58.007" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1236" PostTypeId="2" ParentId="1230" CreationDate="2020-06-09T08:23:44.333" Score="15" Body="&lt;p&gt;Kieron Burke and co-workers have shown that in many cases one can get better results by using the HF density as input to a DFT-XC evaluation of the energy, as opposed to using the DFT-XC to generate a self-consistent density. This has been termed density-driven error, as opposed to functional-error. SE is especially problematic in cases where an electron is weakly bound, as in many (most) anions. Even small SE in these cases may lead to an unbound electron, as is visible by a positive HOMO energy. Any standard basis set, however, will not allow the electron to escape, and thus produces an energy corresponding to the DFT-XC evaluated on an artificially constrained density. This leads to the energy being sensitive to the size of the basis set, especially including more and more diffuse functions will lead to an energy drift.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2020-06-09T08:23:44.333" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1237" PostTypeId="2" ParentId="1105" CreationDate="2020-06-09T10:07:48.630" Score="6" Body="&lt;p&gt;You can (should) use symmetry to reduce the number of displacements needed to construct the matrix of force constants. A nice pratical description of how to do this can be found in the description of the &lt;a href=&quot;http://www.homepages.ucl.ac.uk/~ucfbdxa/phon/node4.html&quot; rel=&quot;noreferrer&quot;&gt;PHON&lt;/a&gt; package by Dario Alfè. In short: if you have the force constants for displacing a given atom, and when you apply the symmetry operations of the crystal this atom is mapped to a second atom, then you can build the corresponding force constants for the second atom without having to calculate them explicitly, simply by using the symmetry transformation rules.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-09T10:07:48.630" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1238" PostTypeId="2" ParentId="1105" CreationDate="2020-06-09T11:12:59.083" Score="7" Body="&lt;p&gt;ProfM's answer gets the core idea perfectly right: Symmetry really is your best friend here. However, symmetry analysis is often &lt;em&gt;quite&lt;/em&gt; involved, especially for larger unit cells.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I recently discovered the &lt;a href=&quot;https://hiphive.materialsmodeling.org/background/index.html&quot; rel=&quot;noreferrer&quot;&gt;hiPhive&lt;/a&gt; package, which uses statistical fits (forces from random displacements fit to a force-constant potential), combined with with symmetry analysis (from spglib), to create a sparse representation of your potential energy surface.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm still learning the package myself, so I cannot go into much more detail, but the idea behind the package, very coarsely, is:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Create a few supercells with random atomic displacements. The magnitude of the displacements may be small (~0.01 Angstroms) if you want purely harmonic phonons, or can be larger (~0.2 Angstroms) if you want the anharmonic force-constants too (for thermal conductivity, etc).&lt;/li&gt;&#xA;&lt;li&gt;Once the forces have been calculated for a fair number of disordered supercells (this is the most time-consuming part, since your forces are typically being calculated by a DFT code, and you may end up with ~500-600+ atoms), you can then proceed to use the hiPhive to generate a force-constant potential. There are tutorials on the website as well as the the method paper about what parameters to check for convergence, what controls convergence, etc.&lt;/li&gt;&#xA;&lt;li&gt;Once you have your force-constant potential (fcp), you can then use Phono3py or any other code that can generate/use force-constants, to get your dynamical properties of choice.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;There is absolutely the question where convergence for a statistical/least-squares process is subtle, but the method paper (linked below) goes into at least some detail about the procedures to follow for a meaningful result from your calculations.&lt;/p&gt;&#xA;&#xA;&lt;h1&gt;References:&lt;/h1&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adts.201800184&quot; rel=&quot;noreferrer&quot;&gt;The Hiphive Package for the Extraction of High‐Order Force Constants by Machine Learning&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="512" LastActivityDate="2020-06-09T11:12:59.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1239" PostTypeId="2" ParentId="1151" CreationDate="2020-06-09T11:22:42.430" Score="8" Body="&lt;p&gt;The GPAW code can do GW/BSE and it uses purely PAW potentials. So it's absolutely possible to do GW/BSE with PAW sets. The &lt;em&gt;involvement&lt;/em&gt; for the implementation, however, is another topic. From Kevin J. M.'s answer, the primary block is fairly clear: PAWs are quite involved to implement. Doing all of the atom-centered corrections and then getting them onto your regular grid requires a focused effort to do, and is perhaps not the highest priority of many codes out there (somewhat understandably so, but PAW &lt;em&gt;does&lt;/em&gt; allow very low PW cutoffs...).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In case you're interested, the tutorials for GW/BSE in the GPAW code are as follows:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorials/gw_tutorial/gw_tutorial.html&quot; rel=&quot;noreferrer&quot;&gt;GW&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorials/bse_tutorial/bse_tutorial.html&quot; rel=&quot;noreferrer&quot;&gt;BSE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I'm fairly confident that Abinit also supports PAW potentials + GW/BSE as well. I think the key point is always how much the PAW methodology is prioritized by the code's developers.&lt;/p&gt;&#xA;" OwnerUserId="512" LastEditorUserId="512" LastEditDate="2020-06-09T16:17:40.387" LastActivityDate="2020-06-09T16:17:40.387" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1240" PostTypeId="1" AcceptedAnswerId="1241" CreationDate="2020-06-09T15:25:53.260" Score="11" ViewCount="316" Body="&lt;p&gt;I am studying a material which was first discovered in the early 1960s. It was reported then that it crystallized in the hexagonal &lt;span class=&quot;math-container&quot;&gt;$P6_3/mmc$&lt;/span&gt; space group. Recently the material was synthesized again and found that it posses &lt;span class=&quot;math-container&quot;&gt;$P6_3mc$&lt;/span&gt; symmetry. My own DFT calculations and another published work find that the latter structure is more stable. Hence during the review of my work, the reviewer mentioned the original &lt;span class=&quot;math-container&quot;&gt;$P6_3/mmc$&lt;/span&gt; structure as &lt;em&gt;hypothetical&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;How can the structure be called &lt;em&gt;hypothetical&lt;/em&gt; if it was reported from experiments and corroborated by others?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Also in general, if an earlier experiment identifies a material with a crystal type and later its found (experiment and theory) that the material crystallizes with a different structure, is the original structure invalid?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="118" LastEditDate="2020-06-10T21:35:49.857" LastActivityDate="2020-06-10T21:35:49.857" Title="Is the original structure invalid if it's found later that the material crystallises with a slightly different space group symmetry?" Tags="|crystal-structure|space-groups|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1241" PostTypeId="2" ParentId="1240" CreationDate="2020-06-09T16:26:53.640" Score="15" Body="&lt;p&gt;Let's imagine we have two different structures for the same compound, and that structure 1 has the lower energy and structure 2 has the higher energy. If you consider the potential energy surface of all potential atomic configurations, then each of these structures sits at a local minimum, and the minimum associated with structure 1 is lower in energy than the minimum associated with structure 2. I am also going to assume, for simplicity, that structure 1 is the global minimum, so it is the ground state structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What does this mean regarding the experimental synthesis of these structures? Structure 1, which is the global minimum, is the most stable structure. What this means is that it will typically be easier to synthesize, and if you wait long enough, any structure of that compound will eventually turn into structure 1. However, it may still possible to synthesize structure 2 experimentally. Depending on your synthesis route, you can create structure 2, which is then &quot;stuck&quot; in that minimum and, even though the minimum of structure 1 is lower in energy, there is an energy barrier to get there. A very famous example of this is carbon structures. The ground state structure of carbon is graphite (my structure 1), but you can also find diamond (my structure 2). In this case, diamond is synthesized at high pressures (where it is actually the lowest energy structure), and then releasing pressure leaves it stuck at its local minimum of energy. Even though diamond is not the lowest energy structure at ambient pressure, it is a structure that carbon can adopt.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What does all this mean for your question? I guess there could be two things going on here:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Both structures can be synthesized. The old experiment happened to synthesize a higher energy but locally stable structure (think diamond), and the new experiment has synthesized the true ground state (think graphite). In this case, I would not call any of the two structures hypothetical, as they have both been confirmed experimentally.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Another option that always needs to be considered is that one of the experiments is wrong. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-09T16:26:53.640" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1242" PostTypeId="2" ParentId="1240" CreationDate="2020-06-09T16:56:43.883" Score="8" Body="&lt;p&gt;Sometime the experiments can also be interpreted incorrectly. Namely, not all kinds of experiments are unambiguous; some require computational modeling to extract the structure.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;That is, even if the experiment were done correctly, the assignment can still be wrong if the interpretation is not correct.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(I'm not sure this applies to crystal structure modeling; if you have e.g. x-ray diffraction spectra the interpretation is quite straightforward. However, if your material contains hydrogens, x-ray diffraction spectroscopy can't usually locate the hydrogens and so your interpretations may again be limited. A full characterization tends to require both x-ray and neutron diffraction spectra.)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-09T16:56:43.883" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1243" PostTypeId="1" AcceptedAnswerId="1247" CreationDate="2020-06-09T17:35:05.553" Score="15" ViewCount="2368" Body="&lt;p&gt;I am trying to input various charge states of various transition metal ion species into DFT calculations. The program requires an input of  &lt;strong&gt;multiplicity = 2*(total spin) + 1&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have an undergraduate-level understanding of chemistry, up to the point where I understand orbital filling (1s,2s,2p,...) for a given element and its ion of varying charge state.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, I am having a difficult time understanding how to get the total spin and/or multiplicity for each ion. Does anyone have recommendations where I can find an explanation for how to do this? Would these values be tabulated somewhere?&lt;/p&gt;&#xA;" OwnerUserId="599" LastActivityDate="2022-02-24T20:13:38.750" Title="Total spin and/or multiplicity for transition metal ions?" Tags="|density-functional-theory|electronic-structure|quantum-chemistry|transition-metals|spin-orbit-coupling|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1244" PostTypeId="2" ParentId="1224" CreationDate="2020-06-09T18:30:41.557" Score="16" Body="&lt;p&gt;Scientific Linux is a rebuild of Red Hat Enterprise Linux. It started out before the CentOS project really took off. Nowadays CentOS is officially supported by Red Hat, but Scientific Linux still exists on its own.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since both CentOS and Scientific Linux are just rebuilds of RHEL, all three should be binary compatible, and you should be able to use the same software repositories for all three.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Fedora project is where development of RHEL happens, and the Fedora project also ships software for RHEL releases that haven't been included in the official Red Hat package selection. There is a fair number of matter modeling packages in the Fedora Extra Packages for Enterprise Linux (EPEL) repositories.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, the problem with RHEL is that since the distribution is &quot;stable&quot;, with the current pace of development the system packages quickly become outdated. The widest and most up to date selection is within Fedora, which aims at a new stable release every 6 months.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;IMNSHO there are only two distributions that can be considered at earnest for general usage: Debian/Ubuntu, and Fedora/Red Hat (and its clones like Scientific Linux and CentOS), since they are the most widely used and offer by far the widest software selections. (Knoppix is a live CD version of Debian.)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In my personal experience the Debian world tends to lag a bit behind, but it should be noted I am not impartial: I've been packaging for Fedora/Red Hat for over a decade, by addressing any deficiencies wherever I've noticed them; this is why my needs are best served by Fedora and Red Hat.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In any case, the situation dependends highly on the package and its maintainer. If the distribution has a contributor who needs package X for their interests, it's highly likely that the distribution's package X is up to date and includes all features. If not, then it might be that X is not included in the distro, or that the version of X is super old...&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-09T18:30:41.557" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1245" PostTypeId="2" ParentId="1243" CreationDate="2020-06-09T20:28:05.417" Score="9" Body="&lt;p&gt;If you're studying transition metal complexes, in short, there is no simple way to know except for to try the relevant physically plausible spin multiplicities and take the lowest energy solution as the ground state. For instance, an Fe(II) complex can have up to 4 unpaired electrons since it is &lt;span class=&quot;math-container&quot;&gt;$3d^6$&lt;/span&gt;. This is what we call the high-spin state and would be &lt;span class=&quot;math-container&quot;&gt;$2S+1=5$&lt;/span&gt;. However, you could also have 2 unpaired electrons for an intermediate spin state of &lt;span class=&quot;math-container&quot;&gt;$2S+1=3$&lt;/span&gt; or 0 unpaired electrons for a low-spin state of &lt;span class=&quot;math-container&quot;&gt;$2S+1=1$&lt;/span&gt;. The only way to know for which is best for your system is to optimize the geometries of all three structures and compare their relative energies. If you refer to any standard inorganic chemistry text, you will likely find various sections devoted to comparing high- vs. low-spin complexes so you can gain an intuition for which is likely to be the ground state for your system, but best-practice is to try all relevant spin states. Note that the density functional you choose will greatly influence the spin splitting energies, so you should be sure to use an appropriate level of theory for your problem.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="-1" LastEditDate="2022-02-24T20:13:38.750" LastActivityDate="2022-02-24T20:13:38.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1246" PostTypeId="2" ParentId="1083" CreationDate="2020-06-09T21:27:16.377" Score="5" Body="&lt;blockquote&gt;&#xA;  &lt;p&gt;However, I am not clear which command have to be used to optimise the structure at a certain pressure to have the constant pressure at the final step.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;For this you need to perform a time integration from the Isobaric Isothermal (&lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt;) ensemble. Essentially performing these dynamics, you equilibrate the systems at certain &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;. In LAMMPS documentation you can find the necessary commands for &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt; simulation. A very generic example is given below.&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;fix 1 all npt temp 300.0 300.0 &lt;span class=&quot;math-container&quot;&gt;$(100.0*dt) iso 0.0 0.0 $&lt;/span&gt;(1000.0*dt)&#xA;run 1000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;After equilibration, plot &lt;span class=&quot;math-container&quot;&gt;$E(timestep)$&lt;/span&gt;. If the slope becomes zero, your system is properly equilibrated at that &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, if you plot the &lt;span class=&quot;math-container&quot;&gt;$P(timestep)$&lt;/span&gt; after equilibration, it should always fluctuate around Final &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; as per your input.&lt;/p&gt;&#xA;" OwnerUserId="605" LastActivityDate="2020-06-09T21:27:16.377" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1247" PostTypeId="2" ParentId="1243" CreationDate="2020-06-09T22:20:17.030" Score="20" Body="&lt;p&gt;Even for the simplest transition metal diatomic molecules, the most reliable way to know the ground-state spin configuration is often by doing experiments. I will give an example where it's easy to correctly determine the ground state spin configuration, and then an example where it has remained impossible as of the year 2020.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Cr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/strong&gt;: Here we can accurately guess the ground-state spin configuration of the molecule with your undergrad-level knowledge about orbital filling: Each Cr atom has 1 lone 4s electron and 5 lone 3d electrons, and when two Cr atoms come together we will get a bonding of the 2 lone 4s electrons, and the 10 lone 3d electrons, which results in the famous sextuple bond with all 12 orbitals that used to be half-filled, now being doubly-occupied, leaving zero unpaired electrons and a spin-multiplicity of 1. This singlet state turns out to be the correct ground-state configuration as far as we know.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Fe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/strong&gt;: In this case the idea of just bonding together every half-filled atomic orbital to create doubly-occupied (spin-0) molecular orbitals, predicts a configuration that disagrees with the present best experiments (we even know this from molecules as simple as O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; whose ground state is a triplet). Even wet-lab experiments have not yet been able to confirm unanimously the ground-state of Fe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;: It is either &lt;span class=&quot;math-container&quot;&gt;$^7 \Delta_u$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$^9 \Sigma_g^-$&lt;/span&gt; (good luck even arriving at those 2 final candidates using theory alone!).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;While doing the research to write this answer about the ambiguity of the ground spin-state of Fe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, I found that the 2015 paper &quot;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4922793&quot; rel=&quot;noreferrer&quot;&gt;Fe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;: As simple as a Herculean labour.&lt;/a&gt;&quot; gives a good history of the pursuit to find the ground spin-state of Fe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, which I have tried to summarize &lt;em&gt;even more&lt;/em&gt; compactly here:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{cccc}&#xA;\text{Year} &amp;amp; \text{First author}&amp;amp; \text{Type} &amp;amp; \text{Ground state}\\&#xA;\hline&#xA;1975 &amp;amp; \text{Montano} &amp;amp; \text{Experimental} &amp;amp; \text{No conclusion}\\&#xA;1982 &amp;amp; \text{Shim} &amp;amp;  \text{Computational} &amp;amp; ^7\Delta_u\\&#xA;1983 &amp;amp; \text{Nagarathna} &amp;amp; \text{Experimental} &amp;amp; ^7\Sigma_g \\&#xA;1984 &amp;amp; \text{Baumann} &amp;amp; \text{Experimental} &amp;amp;  ^7\Delta \\&#xA;1988 &amp;amp; \text{Tomonari} &amp;amp; \text{Computational} &amp;amp; ^7\Delta_u\\&#xA;2002 &amp;amp; \text{Huebner} &amp;amp; \text{Computational} &amp;amp; ^9\Sigma_g^- \\&#xA;2003 &amp;amp; \text{Bauschlicher } &amp;amp; \text{Computational} &amp;amp; ^9\Sigma_g^- \\&#xA;2003 &amp;amp; \text{Bauschlicher } &amp;amp; \text{Combined} &amp;amp; ^7\Delta_u \\&#xA;2009 &amp;amp; \text{Casula} &amp;amp; \text{Computational} &amp;amp; ^7\Delta_u \\&#xA;2011 &amp;amp; \text{Angeli} &amp;amp; \text{Computational} &amp;amp; ^9\Sigma_g^-  \\&#xA;2014 &amp;amp; \text{Hoyer} &amp;amp; \text{Computational} &amp;amp; ^9\Sigma_g^-  \\&#xA;2015 &amp;amp; \text{Kalemos} &amp;amp; \text{Computational} &amp;amp; \text{No conclusion}\\&#xA;\hline&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; You cannot always know the ground state spin-multiplicity, even of some simple transition-metal diatomics, without doing careful experiments (either in a wet-lab, or on a computer). If you're dealing with a much larger system (which I assume is the case for you, because you mentioned ligands), perhaps you can try DFT with various functionals and various basis sets and see if there is one spin-symmetry that is always coming up as having the lowest energy.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-09T22:27:09.790" LastActivityDate="2020-06-09T22:27:09.790" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1248" PostTypeId="2" ParentId="1224" CreationDate="2020-06-10T02:15:18.227" Score="18" Body="&lt;h2&gt;Fedora&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://materials.stackexchange.com/a/1244/5&quot;&gt;Susi Lehtola's answer&lt;/a&gt; makes some good points, and I will elaborate on two of them:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Linux distributions mentioned in your question, which cater to specific communities (e.g. Scientific Linux for particle physics, MathLibre for math, Kali Linux for cybersecurity) are descendants of much more widely-known distributions, so they are not &lt;em&gt;acutely&lt;/em&gt; different from what a lot of people are already familiar with using. Susi mentioned that Scientific Linux is a descendant of Red Hat, and I'll add to that by saying that both MathLibre and Kali are direct descendants of KNOPPIX, which &lt;a href=&quot;https://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg&quot; rel=&quot;noreferrer&quot;&gt;descended from Debian&lt;/a&gt; between 2001-2002, a few years before Ubuntu descended from Debian. &lt;strong&gt;So of the three distributions you mentioned: 2 are very closely related to Debian/Ubuntu, and 1 is very closely related to RedHat/CentOS/Fedora&lt;/strong&gt;. This would likely also be the case with anything else catering specifically to matter modeling.&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;If the distribution has a contributor who needs package X for their interests, it's highly likely that the distribution's package X is up to date and includes all features.&amp;quot; In light of this, since &lt;a href=&quot;https://materials.stackexchange.com/questions/1103/since-mkl-is-not-optimized-for-amd-hardware-should-i-use-a-math-library-specifi#comment1231_1111&quot;&gt;Susi has been a packager for Fedora for over a decade&lt;/a&gt; and packaged OpenMOLCAS, PyQuante, Psi4, PySCF, linint, libxc, and whatever else (he can edit this if there's more!) for Fedora, then Matter Modelers might find Fedora/RedHat/CentOS to be convenient since so many of our workhorses have already been packaged for Fedora.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To focus this answer on just one Linux distribution, out of the Fedora/RedHat/CentOS family, &lt;strong&gt;I picked Fedora because&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;It's free.&lt;/strong&gt;  (Red Hat Enterprise Linux comes with official support, but costs money).&lt;/li&gt;&#xA;&lt;li&gt;It caters to desktop users. (CentOS is also free, but it caters more to servers, so it misses a lot of the packages for desktop use, so the Fedora user community is more likely to grow to a much larger size; Fedora also caters a bit to servers and cloud computing, so it's versatile in that way).&lt;/li&gt;&#xA;&lt;li&gt;It's updated frequently. (CentOS and RHEL are preferred for servers because they are very stable and well-tested, &lt;a href=&quot;https://www.reddit.com/r/Fedora/comments/9dwt9i/fedora_vs_centos/e5ks0vy/&quot; rel=&quot;noreferrer&quot;&gt;but this is accomplished by not updating the all the latest packages&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;The people I've met that use Fedora, are extremely enthusiastic about it (so the even if the number of users is not the biggest, the users love Fedora, will continue to promote and develop Fedora, and won't leave Fedora any time soon), and also very welcoming for others to joint the &lt;a href=&quot;https://fedoraproject.org/wiki/Join?fbclid=IwAR0dlLVrJ34i8IaQ6CKoJKm9HHsk_y8NuYq90UKKgtQK_9QqhmS1tj1IcK4#OS_Developer&quot; rel=&quot;noreferrer&quot;&gt;community&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;There's about &lt;a href=&quot;https://en.wikipedia.org/wiki/Fedora_(operating_system)&quot; rel=&quot;noreferrer&quot;&gt;1.5 million users, including the inventor of Linux: Linus Torvalds&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Drawbacks:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I mentioned Fedora because your comments suggested to me that you were looking for something for your personal computer. Most matter modeling calculations are done on servers though, and that's when CentOS is used more commonly, largely because it's more stable and tested than Fedora, and the latest fancy packages for which you would want Fedora on your desktop, are not usually needed on a server.&lt;/li&gt;&#xA;&lt;li&gt;As a desktop OS, Fedora still has a much smaller user community than Ubuntu which has an estimated 20 million users. Having too large a user community also leads to some disadvantages to Ubuntu, but &lt;a href=&quot;https://askubuntu.com/&quot;&gt;they have an entire StackExchange site of their own&lt;/a&gt;, so when troubleshooting you might get an answer faster, and also I personally have found it helpful when giving talks at other universities (using my own laptop) that people at the host university that needed to help me with something, or wanted to set me up to use their printer, were familiar with my Ubuntu OS.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-11T19:39:39.057" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="1249" PostTypeId="2" ParentId="1224" CreationDate="2020-06-10T02:45:23.463" Score="18" Body="&lt;h2&gt;Ubuntu&lt;/h2&gt;&#xA;&lt;p&gt;For your &lt;strong&gt;workstation&lt;/strong&gt; or &lt;strong&gt;laptop&lt;/strong&gt; the best linux distribution is &lt;strong&gt;Ubuntu.&lt;/strong&gt; Many of the recommendations here, like CentOS, are great for &lt;em&gt;servers&lt;/em&gt;, but you might also have a laptop or desktop computer that you use for developing your code and running simulations. Ubuntu has gone much further than other linux distributions in developing a consumer-grade user interface. It's the only linux distribution that comes close to being a user-friendly desktop operating system in the same way as Mac OS or Windows. It's broad user base also means that little things are more likely to work, like your wifi, or your laptop going to sleep when you close the lid.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-10T02:48:37.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1250" PostTypeId="1" AcceptedAnswerId="1251" CreationDate="2020-06-10T04:39:15.343" Score="15" ViewCount="290" Body="&lt;p&gt;When we calculate the band structure of certain material, we only have to calculate the value along the high symmetry point which enclose the Irreducible Brillouin Zone. Why the information lie in the IBZ is enough for us to know the information of entire BZ ? How to find the IBZ given a reciprocal lattice vector in K-space without checking the table? Is there any proof ? Ive google it, but they just give you the table without telling you how to find out these High symmetry point.&lt;/p&gt;&#xA;" OwnerUserId="621" LastActivityDate="2020-06-10T16:24:37.383" Title="conceptual problem about the energy band along the High symmetry point in the Brillouin zone" Tags="|band-structure|brillouin-zone|symmetry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1251" PostTypeId="2" ParentId="1250" CreationDate="2020-06-10T07:37:27.960" Score="11" Body="&lt;p&gt;I will try to outline this in simple terms. There are certainly more rigorous explanations.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The high-symmetry points in the Brillouin zone are those that remain physically identical when certain symmetry operations of the point-group are applied. Therefore, we notice that the first and higher derivatives of the dispersion relation have the same magnitude in directions that are mapped onto each other by these transformations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, in a 2D material, the dispersion relation is &lt;span class=&quot;math-container&quot;&gt;$\epsilon\left(k_x,k_y\right)$&lt;/span&gt; and we differentiate this with respect to a vector &lt;span class=&quot;math-container&quot;&gt;$\vec{k} = \vec{k}_x\sin{\alpha} + \vec{k}_y \cos{\alpha}$&lt;/span&gt; for multiple &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. The magnitude and sign of the derivative are a periodic function whose period is defined by the symmetry of the high-symmetry point. Thus, extrema tend to be a high-symmetry points.&lt;/p&gt;&#xA;" OwnerUserId="250" LastEditorUserId="5" LastEditDate="2020-06-10T16:24:37.383" LastActivityDate="2020-06-10T16:24:37.383" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1252" PostTypeId="2" ParentId="392" CreationDate="2020-06-10T12:36:42.420" Score="10" Body="&lt;p&gt;Most chemists' point of view could be condensed as follows:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Implementation of DFT in Gaussian&lt;/strong&gt; (Pople et al, 1992)&#xA;LDAs and GGAs were implemented in Gaussian 92/DFT by Pople, Gill and Johnson [Chem Phys Lett 199, 557 (1992)].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;DFT better than ab initio&lt;/strong&gt; (Johnson et al, 1993)&#xA;BLYP was found to yield more accurate equilibrium geometries, dipole moments, harmonic vibrational frequencies and atomization energies than ab initio methods, using the 6-31G* basis set [J Chem Phys 98, 5612 (1993)].&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;B3LYP&lt;/strong&gt; (Stephens et al, 1994)&#xA;The B3LYP functional was proposed based on Becke's earlier suggestion, where the correlation functional was just changed from PW91 to LYP.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This culminated in the infamous B3LYP/6-31G* model chemistry...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-06-11T01:38:55.863" LastActivityDate="2020-06-11T01:38:55.863" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1253" PostTypeId="2" ParentId="1228" CreationDate="2020-06-10T13:56:56.930" Score="12" Body="&lt;p&gt;Kohn-Sham DFT may only be rigorous at zero temperature, but at nonzero temperature, &#xA;Kohn-Sham-Mermin DFT is an equally rigorous replacement. There are two major differences&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Rather than deriving the orbital equations from a minimization of the energy, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, one &#xA;minimizes the &lt;em&gt;free&lt;/em&gt; energy &lt;span class=&quot;math-container&quot;&gt;$F = E - TS$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the entropy. A practical consequence &#xA;is that one needs approximate kinetic, exchange, and correlation functionals that are &#xA;functionals of both the density and the temperature. There are not very many of these out &#xA;there, and they are mainly used in high-density plasma physics contexts, rather than &#xA;conventional materials modeling.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When forming the density from the spin-orbitals, one must use proper finite-temeprature &#xA;occupations numbers, rather than just summing states whose energy is less than the chemical &#xA;potential (Fermi level). In practice, instead of evaluating the density as &lt;span class=&quot;math-container&quot;&gt;$$\rho(\vec r) = &#xA;\sum_{\epsilon &amp;lt; \mu} |\psi(\vec r; \epsilon)|^2$$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$\psi(\vec r; \epsilon)$&lt;/span&gt; is the &#xA;spin-orbital with eigenvalue &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;), one should instead evaluate &lt;span class=&quot;math-container&quot;&gt;$$\rho(\vec r) = &#xA;\sum_\epsilon n(\epsilon) |\psi(\vec r; \epsilon)|^2$$&lt;/span&gt;, where the sum runs over all &#xA;eigenvalues and &lt;span class=&quot;math-container&quot;&gt;$$n(\epsilon) = \frac{1}{1 + e^{(\epsilon-\mu)/kT}}$$&lt;/span&gt; is the Fermi-Dirac &#xA;occupation number. At zero temperature, &lt;span class=&quot;math-container&quot;&gt;$n(\epsilon)$&lt;/span&gt; becomes a step function at &#xA;&lt;span class=&quot;math-container&quot;&gt;$\epsilon=\mu$&lt;/span&gt;, and the usual density expression is recovered.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="839" LastActivityDate="2020-06-10T13:56:56.930" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1254" PostTypeId="2" ParentId="384" CreationDate="2020-06-10T14:36:35.970" Score="9" Body="&lt;p&gt;Non-orthogonal configuration interaction allows for a more intuitive interpretation in terms of molecular states with strict adiabatic character. While the orbital relaxation of individual states that leads to non-orthogonality can reduce the wavefunction expansion compared to orthogonal approaches, NOCI remains a computationally expensive method. But the method parallelizes very well, and the availability of large scale HPC systems allows application to larger molecular systems of interest. The method will not 'outperform' 'standard' orthogonal approaches computationally, but its strength is in the interpretation of the components in the wavefunction expansion. NOCI is useful in studies of materials and processes in which an accurate description of individual ground and excited states and their electronic coupling is important, e.g. in singlet fission materials.&lt;/p&gt;&#xA;" OwnerUserId="840" LastActivityDate="2020-06-10T14:36:35.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1255" PostTypeId="2" ParentId="154" CreationDate="2020-06-10T14:39:34.030" Score="3" Body="&lt;p&gt;I would like to state that I can't give you an answer to &lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;How trustworthy is TB-mBJ (a.k.a. TB09) and how is it seen by the community today?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;However, the &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513000775?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference&lt;/a&gt; presents the Quantum ESPRESSO's implementation of Meta GGA TB09, by extending the xc functionals of Libxc library in QE. There you will be able to find some useful benchmarks. &lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-06-10T14:39:34.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1256" PostTypeId="1" CreationDate="2020-06-10T18:19:06.993" Score="7" ViewCount="104" Body="&lt;p&gt;I am wondering whether or not &lt;strong&gt;&lt;em&gt;self-interaction error&lt;/em&gt;&lt;/strong&gt; and &lt;strong&gt;&lt;em&gt;integer-discontinuity&lt;/em&gt;&lt;/strong&gt; in Kohn-Sham density functionals, are related to each other?&lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-06-10T20:15:19.457" LastActivityDate="2020-06-11T11:23:16.390" Title="Is there a relation between self-interaction errors and integer-discontinuities in Kohn-Sham-DFT?" Tags="|density-functional-theory|kohn-sham|self-interaction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1257" PostTypeId="2" ParentId="1104" CreationDate="2020-06-10T21:21:11.997" Score="7" Body="&lt;p&gt;The question cites a 2008 paper about fairly large molecules (e.g. bithiophene N-succinimidyl esters), in which TD-DFT gave significantly wrong results, so the authors recommended RI-CC2. The question then asks if there's any example where TD-DFT was insufficient for a smaller system. After searching the literature, &lt;strong&gt;I have found &lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.1290013&quot; rel=&quot;noreferrer&quot;&gt;an example&lt;/a&gt; of a small molecule for which TD-DFT gave significantly worse results than RI-CC2: The molecule is C&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here I will make a condensed version of the relevant energies in their Table II:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{c c c c}&#xA;\text{State} &amp;amp; \text{TD-DFT} &amp;amp; \text{RI-CC2} &amp;amp; \text{Benchmark}\\&#xA;\hline&#xA;B_{1u} &amp;amp; 7.72 &amp;amp; 8.27 &amp;amp; 8.22\\&#xA;B_{1g} &amp;amp; 8.09 &amp;amp; 8.73 &amp;amp; 8.59\\&#xA;B_{3u} &amp;amp; 8.11 &amp;amp; 8.84 &amp;amp; 8.75\\&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here's some further explanations about the table:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;All energies are in eV.&lt;/li&gt;&#xA;&lt;li&gt;The benchmark was CC3, which the authors say they expect to be within about 0.1 eV of the exact truth (so whatever error is in these benchmarks, is negligible here).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;In every case&lt;/strong&gt; RI-CC2 was closer to the benchmark by more than 0.5 eV.&lt;/li&gt;&#xA;&lt;li&gt;The functional used for TD-DFT was B3LYP. According to &lt;a href=&quot;https://materials.stackexchange.com/a/1132/5&quot;&gt;this figure&lt;/a&gt; one might be able to get 1.5 kcal/mol better by using a double-hybrid such as B2PLYP, but that's only 0.065 eV, which is negligible compared to the fact that the table shows TD-DFT being more than 0.5 eV worse than RI-CC2 in every case.&lt;/li&gt;&#xA;&lt;li&gt;I have only included the first 3 states from Table II of the original paper, you're welcome to see the whole table, and the observations above remain the same (in fact the TD-DFT error becomes much worse for some of the other states.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;The bottom line is that if you have enough compute power available, coupled-cluster-based approaches will almost always beat DFT, except for multi-reference cases where coupled-cluster is known to fail, such as some molecules containing transition metals (where DFT can have an advantage, especially if the functionals are optimized for transition metal systems, such as some of the functionals that have come out of Don Truhlar's group).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-06-10T21:21:11.997" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1258" PostTypeId="2" ParentId="690" CreationDate="2020-06-10T21:50:44.383" Score="4" Body="&lt;p&gt;In most of double hybrid KS-DFT approaches, there is a disconnect between xc potential obtained from xc functional. As correlation corresponding to the MP2 part is not included in the self-consistent procedure. Thus one did not improve the KS density due to correlation functional of MP2. Parameters used in double-hybrid has no physical motivation except fitting to certain data. Physically motived way to construct double hybrid is described in paper titled &quot;Ionization potential optimized double-hybrid density functional approximations&quot; &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4962354&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/abs/10.1063/1.4962354&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="322" LastActivityDate="2020-06-10T21:50:44.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1259" PostTypeId="2" ParentId="1104" CreationDate="2020-06-10T21:59:46.307" Score="4" Body="&lt;p&gt;TD-DFT works best for valence-valence excitation energies, but does not very well for charge-transfer excitation (unless xc potentials are constructed to lower delocalization error). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Core-excitation energies are also not described will with TD-DFT. &lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2020-06-10T22:07:11.253" LastActivityDate="2020-06-10T22:07:11.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1260" PostTypeId="2" ParentId="392" CreationDate="2020-06-11T01:43:15.287" Score="23" Body="&lt;h1&gt;2013: Density-Corrected DFT (DC-DFT)&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;The goal of Density-Corrected DFT (DC-DFT) is not only to get better accuracy but also to understand and correct the true error in the functional approximation.[1,2]&#xA;In any approximate density functional, the DFT error is&#xA;&lt;span class=&quot;math-container&quot;&gt;$\Delta E = \tilde E[\tilde n] - E[n]$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; are exact functional and density while &lt;span class=&quot;math-container&quot;&gt;$\tilde {}$&lt;/span&gt; represents approximate counterpart. &#xA;Therefore, any density functional calculation has errors due to two causes: approximate functional and approximate density.&#xA;The true functional error is&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_F = \tilde E[n] - E[n] = \Delta E_{XC}[n]$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;and the remaining error is &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_D = \Delta E - \Delta E_F = \tilde E[\tilde n] - \tilde E[n]$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;called the density-driven error.&#xA;In most cases, &lt;span class=&quot;math-container&quot;&gt;$\Delta E_F$&lt;/span&gt; dominates &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; but, if DFT energy is density-sensitive, i.e., largely affected by density, &lt;span class=&quot;math-container&quot;&gt;$\Delta E_D$&lt;/span&gt; is non-negligible and worth examining.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There is no guarantee that the HF density is closer to the exact density than DFT self-consistent densities, but HF-DFT[5,6] (DFT energy evaluated on HF density) is probably one of the simplest and most practical ways to perform DC-DFT.&#xA;Moreover, HF-DFT has shown to provide better results than standard approximations for various density-sensitive cases that are not spin contaminated including electron affinities, potential energy curves, spin gaps for coordination compound, and noncovalent interactions.[3,4]&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;M.-C. Kim, E. Sim, K. Burke, Phys. Rev. Lett., 111, 073003 (2013) &lt;/li&gt;&#xA;&lt;li&gt;A. Wasserman, J. Nafziger, K. Jiang, M.-C. Kim, E. Sim, K. Burke, Annu. Rev. Phys. Chem., 68, 555 (2017)&lt;/li&gt;&#xA;&lt;li&gt;Y. Kim, S. Song, E. Sim, K. Burke, J. Phys. Chem. Lett., 10, 295 (2019)&lt;/li&gt;&#xA;&lt;li&gt;S. Vuckovic, S. Song, J. Kozlowski, E. Sim, K. Burke, J. Chem. Theo. Comp., 15, 6636 (2019)&lt;/li&gt;&#xA;&lt;li&gt;P. Verma, A. Perera, R. J. Bartlett CPL, 524, 10-15, 2012&lt;/li&gt;&#xA;&lt;li&gt;P.M.W. Gill, B.G. Johnson, J.A. Pople, M.J. Frisch, Int. J. Quant. Chem., 44,319 (1992)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="848" LastEditorUserId="848" LastEditDate="2020-06-13T02:58:25.020" LastActivityDate="2020-06-13T02:58:25.020" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1261" PostTypeId="1" CreationDate="2020-06-11T02:35:48.657" Score="2" ViewCount="105" Body="&lt;p&gt;This question is primarily targeted to individuals who are working in industries and in the field of materials modeling. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;em&gt;[Be ambiguous wherever required]&lt;/em&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(i) Please explain your role briefly&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(ii) the types of theoretical methods/softwares and calculations that you perform regularly&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(iii) How is the perception within your organization on these results.&lt;/p&gt;&#xA;" OwnerUserId="664" LastEditorUserId="7" LastEditDate="2021-07-09T17:08:41.103" LastActivityDate="2021-07-09T17:08:41.103" Title="Materials Modeling in Industry" Tags="|condensed-matter|" AnswerCount="0" CommentCount="4" ClosedDate="2020-06-11T06:17:46.713" ContentLicense="CC BY-SA 4.0" />
  <row Id="1262" PostTypeId="1" CreationDate="2020-06-11T03:14:53.147" Score="14" ViewCount="64" Body="&lt;p&gt;As we know, due to the current pandemic situation, people are getting more awake regarding hygiene and health. As such, there are many researches, both computational and experimental, within the health sector and mostly among the biologists and other related professions. However, as a computational materials scientist, I would like to find out if we could also do our part by applying our expertise in directly tackling these health issues too. &lt;p&gt;&#xA;Therefore, I would like to enquire any computational materials experts here if there is anyway to semi-quantify antibacterial/antimicrobial properties of a material in DFT without having to calculate or model biological system. For example, perhaps to utilize the electronic properties of a material, such as its valence or conduction band edge positions to gauge antibacterial effectiveness (by comparing magnitude of difference of redox potential of a particular redox process versus the band edges [just my postulation]), or perhaps other related approach.&lt;/p&gt;&#xA;" OwnerUserId="231" LastEditorUserId="5" LastEditDate="2020-06-11T13:49:43.810" LastActivityDate="2020-06-11T16:07:18.577" Title="Is there any way to semi-quantify antibacterial/antimicrobial properties of a material using DFT?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1263" PostTypeId="2" ParentId="190" CreationDate="2020-06-11T04:30:54.297" Score="14" Body="&lt;h1&gt;Density Functionals&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;LDA (LSDA):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;S: Slater (Dirac) exchange functional for a uniform electron gas.&lt;/li&gt;&#xA;&lt;li&gt;VWN: Vosko, Wilk, and Nusair 1980 correlation functional fitting the random phase approximation solution to the uniform electron gas.&lt;/li&gt;&#xA;&lt;li&gt;PL: Perdew and Wang 1992 local correlation functional (also known as PW or PW92).&lt;/li&gt;&#xA;&lt;li&gt;PZ81: Perdew-Zunger parameterization of the LSDA correlation energy from 1981.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;GGA:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;B88: Becke's 1988 exchange functional which includes Slater exchange and gradient corrections of the density.&lt;/li&gt;&#xA;&lt;li&gt;PBE: Exchange and Correlation functional of Perdew, Burke and Ernzerhof (1996).&lt;/li&gt;&#xA;&lt;li&gt;PW86: Perdew-Wang correlation functional from 1986 based on the PZ81 LSDA functional.&lt;/li&gt;&#xA;&lt;li&gt;PW91: Perdew-Wang correlation functional from 1991.&lt;/li&gt;&#xA;&lt;li&gt;LYP: Lee, Yang, Parr correlation functional which includes both local and non-local terms.&lt;/li&gt;&#xA;&lt;li&gt;BLYP: B88 exchange plus LYP correlation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;meta-GGA:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;SCAN: Strongly Constrained and Appropriately Normed density functional by Sun, Ruzsinszky and Perdew (2015).&lt;/li&gt;&#xA;&lt;li&gt;TPSS: Tao, Perdew, Staroverov, and Scuseria exchange and correlation functional.&lt;/li&gt;&#xA;&lt;li&gt;revTPSS: Revised TPSS functional.&lt;/li&gt;&#xA;&lt;li&gt;BR: Becke and Rousel exchange functional.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Hybrid or Hyper-GGA:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;TPSSh: Hybrid functional using the TPSS functionals.&lt;/li&gt;&#xA;&lt;li&gt;B3LYP: Becke three-parameter hybrid functional with VWN local correlation and LYP non-local correlation, Hartree-Fock exchange, B88 exchange and VWN exchange.&lt;/li&gt;&#xA;&lt;li&gt;B3P86: Same as B3LYP except that non-local correlation is provided by P86.&lt;/li&gt;&#xA;&lt;li&gt;B3PW91: Same as B3LYP except that non-local correlation is provided by PW91.&lt;/li&gt;&#xA;&lt;li&gt;O3LYP: Cohen and Handy's three parameter hybrid functional.&lt;/li&gt;&#xA;&lt;li&gt;PBE0: Adamo's reconstruction of PBE into a hybrid functional (1999).&lt;/li&gt;&#xA;&lt;li&gt;B97: Becke's 10-parameter density functional with &lt;span class=&quot;math-container&quot;&gt;$19.43\%$&lt;/span&gt; HF exchange.&lt;/li&gt;&#xA;&lt;li&gt;M06 class: parametrized hybrid functionals of Truhlar and Zhao (2008).&lt;/li&gt;&#xA;&lt;li&gt;HFLYP: &lt;span class=&quot;math-container&quot;&gt;$100\%$&lt;/span&gt; HF exchange plus LYP GGA correlation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Double Hybrid:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;B2PLYP: Grimme (2006) double hybrid functional built on the B88 exchange and LYP correlation functionals.&lt;/li&gt;&#xA;&lt;li&gt;PBE0-DH: Adamo et al. (2013) double hybrid functional built on the PBE0 functional.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Long-Range Corrected Hybrids:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97XD: Chai and Head-Gordon hybrid functional which includes empirical dispersion.&lt;/li&gt;&#xA;&lt;li&gt;CAM-B3LYP: Yanai, Tew and Head-Gordon version of B3LYP using the Coulomb-attenuating method.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;(This is a preliminary list for the moment, I'll be updating later.)&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-11T06:05:13.683" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1264" PostTypeId="2" ParentId="154" CreationDate="2020-06-11T07:34:24.903" Score="3" Body="&lt;p&gt;Anibal pointed out that the authors used a modified version of libxc; TB09 has actually been generally available in libxc since version 1.0.0, meaning that studies should be available in the literature.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Libxc is also supported interfaced to nowadays by over 30 programs relying on a variety of numerical approaches from plane waves to Gaussian basis sets and everything in-between, so it shouldn't be too difficult to assess the accuracy of TB09 if you have reliable reference data available.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-11T07:34:24.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1265" PostTypeId="2" ParentId="507" CreationDate="2020-06-11T11:23:07.080" Score="6" Body="&lt;p&gt;I think you should take care of all possible interactions to get close to the real picture. In periodic solids, there might be electron-hole interaction (solve BSE equation for it), el-phonon coupling, etc. Note that, QE epsilon.x is the lowest level of approximation for the solids (IPA) and it doesn't include any non-local part and local field effects. Moreover, you can incorporate the many-body effects in the solids using certain TDDFT kernels as well, like TDDFT-LRC (static and dynamic) and if you have solid with low electronic dielectric function and small lattice screening than the excitonic effects might play a big role even in the bulk systems, so you better solve BSE in those cases instead of RPA level of spectra. &#xA;I recommend to take your system into account carefully and then choose the right theory to apply.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Best of luck,&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Haseeb Ahmad.&lt;/p&gt;&#xA;" OwnerUserId="854" LastEditorUserId="854" LastEditDate="2020-06-11T20:05:31.733" LastActivityDate="2020-06-11T20:05:31.733" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1266" PostTypeId="2" ParentId="1256" CreationDate="2020-06-11T11:23:16.390" Score="4" Body="&lt;p&gt;Yes and no.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The exact functional should have a piecewise linear behavior in the number of electrons &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.49.1691&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. Lett. 49, 1691 (1982)&lt;/a&gt;, but this is not true for common density functional approximations, and self-interaction errors &lt;em&gt;do&lt;/em&gt; affect behavior at fractional electron numbers.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Now, if you apply the Perdew-Zunger self-interaction correction, then not only do you mitigate the one-electron self-interaction error (N.B. the correction is often problematic, see &lt;a href=&quot;https://doi.org/10.1016/bs.aamop.2015.06.004&quot; rel=&quot;nofollow noreferrer&quot;&gt;Adv. At., Mol., Opt. Phys. 64, 1 (2015)&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.6b00347&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 12, 3195 (2016)&lt;/a&gt;) but also introduce step-wise behavior in the functional due to the added term; orbital energies in PZ-SIC are often better than in Kohn-Sham DFT. There's also been a lot of work on the so-called Koopmans' compliant functionals by Marzari et al. &lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-11T11:23:16.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1267" PostTypeId="2" ParentId="1224" CreationDate="2020-06-11T15:40:36.940" Score="10" Body="&lt;h2&gt;VigyaanCD&lt;/h2&gt;&#xA;&#xA;&lt;p&gt;As a historic note, I found an example of a effort in this direction, in the past. A modified KNOPPIX targeted at molecular modeling with Gamess-US. It was called the &lt;a href=&quot;http://www.vigyaancd.org/&quot; rel=&quot;noreferrer&quot;&gt;VigyaanCD&lt;/a&gt;. Unfortunately it appears to be a defunct project by now. It was released in 2005 and I could not find any updates since then. The Gamess &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/windows.html&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt; has the following description:&lt;/p&gt;&#xA;&#xA;&lt;blockquote&gt;&#xA;  &lt;p&gt;GAMESS, Vigyaan CD (obsolete):&lt;/p&gt;&#xA;  &#xA;  &lt;p&gt;This is a bootable CD, containing a 2005-vintage version of GAMESS.&#xA;  This CD, from the Vigyaan project, is a live Linux CD containing all&#xA;  the required software to boot the computer, and run a standard, but&#xA;  now quite old, version of GAMESS, Avogadro-GMS, GTK-GAMESS and other&#xA;  useful software. Tutorials are also available on this CD. Note, this&#xA;  CD does not require compilation of GAMESS. More information about the&#xA;  CD can be found on the Vigyaan web site. If you encounter any problems&#xA;  with this CD, please do not send email to Mike or our Webmaster,&#xA;  instead send it to Pratul Agarwal.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&#xA;&lt;p&gt;Perhaps someone will bring it back from the dead, someday.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-06-11T15:42:38.653" LastActivityDate="2020-06-11T15:42:38.653" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1268" PostTypeId="2" ParentId="1262" CreationDate="2020-06-11T16:07:18.577" Score="5" Body="&lt;p&gt;While there are applications of density functional to biological systems and medical applications, there are far too many pathways possible for this to be currently useful.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;People do use DFT as part of docking or dynamics to predict the electrostatic potential of molecules - understanding how a compound might interact with a key protein or membrane.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Consider the possibilities for current disinfecting / antimicrobial cleaning. (I am not a biologist, so there are undoubtedly far more - ask at &lt;a href=&quot;https://biology.stackexchange.com/&quot;&gt;Bio SE&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Dissolve the cell membrane or viral capsid using alcohol or other solvents&lt;/li&gt;&#xA;&lt;li&gt;Denature key proteins&lt;/li&gt;&#xA;&lt;li&gt;Disrupt replication &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;etc.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I don't believe the mechanisms for silver or copper anti-microbial properties are fully understood. So when you combine multiple possible pathways with not-fully-understood pathways, it's extremely hard to apply computational modeling like DFT in useful ways.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-06-11T16:07:18.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1269" PostTypeId="1" CreationDate="2020-06-11T16:28:37.073" Score="13" ViewCount="932" Body="&lt;p&gt;I find the experiments to be relatively easy to explain to my young cousins (who are planning to take scientific reserach as a career option). I find the theoretical works, especially the ones which require highly involved computational tools (read DFT) to be a bit difficult to explain to these 16 somethings. They have a reasonably good understanding of the structure of the atom but nothing more than that.&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="5" LastEditDate="2020-06-11T20:37:22.997" LastActivityDate="2020-06-13T10:47:20.123" Title="How would you explain Density Functional Theory to a high school student?" Tags="|density-functional-theory|education|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1270" PostTypeId="2" ParentId="1269" CreationDate="2020-06-11T16:36:57.740" Score="10" Body="&lt;p&gt;I strongly recommend you to visit the site of the &lt;a href=&quot;http://chemistry.ncssm.edu/&quot; rel=&quot;noreferrer&quot;&gt;North Carolina High School Computational Chemistry Server&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;They have a project for teachers and high school students to learn molecular simulations using DFT, Molecular Mechanics and Semi-Empirical methods.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-11T16:36:57.740" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1271" PostTypeId="1" AcceptedAnswerId="1279" CreationDate="2020-06-11T19:23:41.603" Score="13" ViewCount="1420" Body="&lt;p&gt;I am using VASP package to model a material that has fractional site occupancies. An appropriate supercell (cif) was generated using &lt;code&gt;supercell&lt;/code&gt; package and converted to &lt;code&gt;POSCAR&lt;/code&gt; using VESTA. Then the structural relaxation was performed. Now I have the relaxed structure (&lt;code&gt;CONTCAR&lt;/code&gt;) and I want to analyze its space group. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I tried &lt;code&gt;pymatgen&lt;/code&gt;, but it doesn't seem to be working for fractional site occupant materials, because the original &lt;code&gt;POSCAR&lt;/code&gt; structure is &lt;code&gt;Pm-3m&lt;/code&gt;, however is identified as &lt;code&gt;P4/mmm&lt;/code&gt; by pymatgen.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Is there any other tool I can use to analyze such structures?&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="85" LastEditDate="2020-06-12T07:50:32.010" LastActivityDate="2020-09-03T18:27:54.993" Title="How to analyze the space group of a relaxed structure that has fractional site occupancies" Tags="|density-functional-theory|vasp|crystal-structure|space-groups|" AnswerCount="4" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1272" PostTypeId="2" ParentId="392" CreationDate="2020-06-11T19:57:42.250" Score="12" Body="&lt;p&gt;I would add some developments in TDDFT that came around 1996 and resonated only later such as:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;the Casida equation&lt;/strong&gt; (&lt;a href=&quot;https://www.worldscientific.com/doi/abs/10.1142/9789812830586_0005&quot; rel=&quot;noreferrer&quot;&gt;Casida 1995&lt;/a&gt;) that allows to calculate excitation energies and electronic spectra&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;the real-time TDDFT&lt;/strong&gt; (&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.54.4484&quot; rel=&quot;noreferrer&quot;&gt;Yabana &amp;amp; Bertsch 1996&lt;/a&gt;) a non-perturbative TDDFT technique in which the time-dependent Kohn–Sham equation is solved by direct propagation in time&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;the van Leeuwen theorem&lt;/strong&gt; (&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.82.3863&quot; rel=&quot;noreferrer&quot;&gt;van Leeuwen 1999&lt;/a&gt;) a generalization of the Runge–Gross theorem that also underpins the Kohn–Sham construction in TDDFT&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="544" LastActivityDate="2020-06-11T19:57:42.250" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1273" PostTypeId="2" ParentId="1269" CreationDate="2020-06-11T20:29:56.180" Score="2" Body="&lt;p&gt;In quantum mechanics state is represented by wave function while physical observables (such as energy, position, momentum etc) as operator. In quantum chemistry we are interested in obtaining energy of molecules, which is obtained as expectation value of the Hamiltonian. DFT is based on the realization that one does not need full information of the wave function as the Hamiltonian involves just one- and two- body operation in the process of evaluating the expectation value of the Hamiltonian, most of the degree of the freedom will integrate out. Thus one-particle and two-particle density will be suffice to obtain energy of the molecule. Two particle density can be written as a product of one-particle densities and a correlation function whose form is not know exactly but can be constructed using physical insights. &lt;/p&gt;&#xA;" OwnerUserId="322" LastActivityDate="2020-06-11T20:29:56.180" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1274" PostTypeId="2" ParentId="1271" CreationDate="2020-06-11T23:06:54.750" Score="5" Body="&lt;h3&gt;Bilbao Crystallographic Server&lt;/h3&gt;&#xA;&lt;p&gt;You can take a look at the &lt;a href=&quot;https://www.cryst.ehu.es/wiki/index.php/About_the_Bilbao_Crystallographic_Server&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bilbao Crystallographic Server&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It has several tools for symmetry and structure analysis in the Solid State Theory Applications section.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-09-03T18:27:12.100" LastActivityDate="2020-09-03T18:27:12.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1275" PostTypeId="2" ParentId="484" CreationDate="2020-06-11T23:36:12.217" Score="6" Body="&lt;p&gt;Here you can find some materials (article reviews &amp;amp; books) about Materials Informatics:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1063/1.4946894&quot; rel=&quot;nofollow noreferrer&quot;&gt;Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science.&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41524-017-0056-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;Machine learning in materials informatics: recent applications and prospects.&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.wiley.com/en-us/Materials+Informatics%3A+Methods%2C+Tools%2C+and+Applications-p-9783527341214&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Informatics: Methods, Tools, and Applications.&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/S1369-7021(05)71123-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials informatics&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/B978-0-12-394399-6.00001-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;Informatics for Materials Science and Engineering.Chapter 1 - Materials Informatics: An Introduction.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-12T01:13:24.607" LastActivityDate="2020-06-12T01:13:24.607" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1276" PostTypeId="2" ParentId="444" CreationDate="2020-06-11T23:49:04.300" Score="2" Body="&lt;p&gt;Not always the research pipeline is from experimental to theory. The group of Professor Artem Oganov had very &lt;a href=&quot;https://uspex-team.org/en/research/materials&quot; rel=&quot;nofollow noreferrer&quot;&gt;interesting results&lt;/a&gt; where they started predicting theoretical structures (at extreme conditions) and then synthetize them in the lab. to confirm the predictions. One of their results is about &lt;span class=&quot;math-container&quot;&gt;$Na_3Cl$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Na_2Cl$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Na_3Cl_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$NaCl_3$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$NaCl_7$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;About the errors to considered calculations at 0K for other temperatures, take a look at &lt;a href=&quot;https://materials.stackexchange.com/a/1229/24&quot;&gt;this&lt;/a&gt; answer this a similar question.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-12T13:23:39.127" LastActivityDate="2020-06-12T13:23:39.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1277" PostTypeId="2" ParentId="426" CreationDate="2020-06-12T00:03:50.920" Score="3" Body="&lt;p&gt;They can be relevant when comparing a geometry optimization with experimental data: how far the atoms &quot;went&quot;?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;(you can use both parameters if you want to constrain the atoms movement during a geometry optimization).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;But here we have two issues. The first one is related to the quality of the crystallographic data used to determine both parameters. If using powder x-ray crystallography, the data is least reliable as for single crystal x-ray diffraction.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The second one is that the obtaining of these parameters are valid only for a given, fixed crystal structure but, from the simulations you can get a phase transition where the atoms &quot;move&quot; more than the permitted values of U and B.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-12T13:25:42.627" LastActivityDate="2020-06-12T13:25:42.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1278" PostTypeId="6" CreationDate="2020-06-12T02:01:37.530" Score="0" Body="&lt;p&gt;I really enjoyed using this newborn forum dedicated to materials modeling and learned a lot as being a small part of this wonderful community.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;From the beginning of this forum, I tried my best to contribute in terms of answering the questions, reviewing the new posts, newly created tags, edits, etc. I have lots of other experiences in terms of moderating and contributing to similar other forums in StackExchange, such as Computational Science. I believe, if we work together, we could maintain and develop this community furthermore to become one of the main Q&amp;amp;A platforms for broader materials modeling community.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My main vision to be a moderator here in the Materials Modeling forum is to help people to develop a high-quality and inclusive community that a whole range of beginners to experts in this field could ask questions and receive high-quality answers. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I would do my best if I'll be selected to serve this community in order to bring more values into this materials modeling community by establishing a moderating plan to make sure the high-quality of answers and questions maintained while we make sure we are friendly and inclusive as much as possible. &lt;/p&gt;&#xA;" OwnerUserId="37" LastEditorUserId="37" LastEditDate="2020-06-12T02:01:37.530" LastActivityDate="2020-06-12T02:01:37.530" CommentCount="1" CommunityOwnedDate="2020-06-12T02:01:37.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="1279" PostTypeId="2" ParentId="1271" CreationDate="2020-06-12T06:38:32.013" Score="10" Body="&lt;h3&gt;ASE&lt;/h3&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE&lt;/a&gt; python package can find the space group of a structure using the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/_modules/ase/spacegroup/spacegroup.html#get_spacegroup&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;get_spacegroup&lt;/code&gt;&lt;/a&gt; function as follows.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import ase.io as io&#xA;from ase.spacegroup import get_spacegroup&#xA;&#xA;structure = io.read('path/to/POSCAR')&#xA;sp = get_spacegroup(structure,symprec=1e-5)&#xA;print(sp)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not sure as to whether it can deal with fractional occupancies, but it seems it can from the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/_modules/ase/spacegroup/spacegroup.html#Spacegroup&quot; rel=&quot;nofollow noreferrer&quot;&gt;source of the Spacegroup class&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="85" LastEditorUserId="5" LastEditDate="2020-09-03T18:27:54.993" LastActivityDate="2020-09-03T18:27:54.993" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1280" PostTypeId="2" ParentId="1271" CreationDate="2020-06-12T08:28:06.237" Score="9" Body="&lt;h3&gt;spg-lib&lt;/h3&gt;&#xA;&lt;p&gt;Another light-weight option is the spg-lib by Atsushi Togo and Isao Tanaka described &lt;a href=&quot;https://arxiv.org/abs/1808.01590&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; with multiple interfaces that can be found &lt;a href=&quot;https://spglib.github.io/spglib/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Especially, the tolerance parameters for the detection of symmetries are quite handy.&lt;/p&gt;&#xA;" OwnerUserId="250" LastEditorUserId="5" LastEditDate="2020-09-03T18:26:52.667" LastActivityDate="2020-09-03T18:26:52.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1281" PostTypeId="2" ParentId="1269" CreationDate="2020-06-12T10:05:54.620" Score="9" Body="&lt;p&gt;Explaining DFT even to a master's student is pretty hard... and to a high school student? Lol. In that case you're really restricted to a very ambiguous description. Unlike a master's student, they don't know (and you can't show them) what the exchange term is. Moreover, they don't (really) know what a wave function or state is.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Because of this, you're reduced to a very fuzzy and ambiguous explanation, so it would help a lot knowing what context you are working in. Mentioning DFT might even be counterproductive.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The single-particle Schrödinger isn't that hard, and can be understood in terms of the wave equation, e.g. by oscillations of a string. The problem is that if you want to also involve DFT, you need to explain &lt;em&gt;why&lt;/em&gt; you need it. This is due to the many-particle aspect: exchange and correlation. The first arises already with a single electron configuration (in addition to the classical Coulomb electrostatics you also get a term corresponding to interchange of the particles), while the latter arises from the fact that in reality many electron configurations contribute to the wave function simultaneously, and the number of possible configurations increases rapidly with system size.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;DFT constructs an effective independent particle approximation for this interacting system, and the exchange-correlation functional does the magic of mapping the systems to each other. Although we don't know what the exact functional is, hundreds of approximations have been developed for it, but the problem is that it's almost impossible to tell beforehand whether the approximate functionals are reliable for the system you want to study.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-06-13T10:47:20.123" LastActivityDate="2020-06-13T10:47:20.123" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1282" PostTypeId="6" CreationDate="2020-06-12T10:57:32.843" Score="0" Body="&lt;p&gt;I'm &lt;strong&gt;taciteloquence&lt;/strong&gt; and I'm nominating myself for moderator on the Materials Modeling Stack Exchange. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I'm a condensed matter physics postdoc specializing in both classical and quantum Monte Carlo methods for spin systems. I'm a founding member of this Stack Exchange group and I've really enjoying watching this community grow from a proposal to a large public beta.  &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Stack Exchange is unique among internet communities in that it rewards thoughtful questions and generous, helpful answers. As a user, I have done my best to contribute helpful and clear answers as well as interesting questions of my own. As a moderator, I would work to make sure the Materials Modeling Stack Exchange is an inclusive and kind community helps people get the answers they need. I have chosen to run in part because I think it would be useful to have a range of scientific specialties in the moderation team, and I am one of the relatively few Monte Carlo users in the forum. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;If you're wondering why I am not using my real name, I find it easier to both ask and answer questions honestly when I use a pseudonym. This is for my own privacy as well as the privacy of my real-life colleagues. &lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-06-12T10:57:32.843" LastActivityDate="2020-06-12T10:57:32.843" CommentCount="0" CommunityOwnedDate="2020-06-12T10:57:32.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="1283" PostTypeId="1" CreationDate="2020-06-12T13:37:39.570" Score="17" ViewCount="107" Body="&lt;p&gt;I'm trying to converge a dilute fcc alloy consisting of Cu and U, with the Uranium concentration at 0.01% and the lattice parameter of Cu, using Hubert Ebert's Spin Polarized Relativistic Korringa-Kohn-Rostoker (&lt;a href=&quot;https://www.ebert.cup.uni-muenchen.de/old/index.php?option=com_remository&amp;amp;Itemid=20&amp;amp;func=startdown&amp;amp;id=51&amp;amp;lang=de&quot; rel=&quot;nofollow noreferrer&quot;&gt;SPR-KKR&lt;/a&gt;) program.&lt;/p&gt;&#xA;&lt;p&gt;However it seems that after one iteration the energy of the lower limit of the semi-core states shoots above the upper energy limit of the core states. This problem only started to arise when I introduced the valence of the Cu and U atoms as parameters. I set the valence of U as 12 and the valence of Cu as 10, but have also tried 1 for the Cu valence. I have tried lowering the energy range of my calculation but that also doesn't seem to work, now I'm stuck and I'm not sure what other troubleshooting options to do.&lt;/p&gt;&#xA;" OwnerUserId="863" LastEditorUserId="5" LastEditDate="2020-08-27T15:56:54.177" LastActivityDate="2020-10-08T14:10:04.983" Title="Converging the potential of a dilute binary alloy system using the Coherent Potential Approximation. What troubleshooting options could I take?" Tags="|density-functional-theory|software|from-phys-se|relativistic|alloys|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1284" PostTypeId="2" ParentId="392" CreationDate="2020-06-12T15:41:26.330" Score="18" Body="&lt;h1&gt;1995 (Casida): TD-DFRT&lt;/h1&gt;&#xA;&lt;p&gt;Time-Dependent Density Functional Response Theory is a linear response formulation of TDDFT for the calculation of excitation energies and corresponding transition amplitudes, that in turn allows to evaluate electronic spectra of molecular and condensed matter systems.&lt;/p&gt;&#xA;&lt;p&gt;The time-dependent density functional theory (TDDFT) in the Kohn–Sham formalism is a set of differential equations for the time evolution of orbitals under the influence of an external field. However, in perturbation theory, TDDFT can be recast as an algebraic equation that describes the response in the frequency domain. Furthermore, instead of directly solving the response to an external field of particular frequency, one can calculate the resonant frequencies that correspond to the system's excitation energies (and to the poles of response functions).&lt;/p&gt;&#xA;&lt;p&gt;This is achieved by the Casida equation, whose most general form is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\pmatrix{A &amp;amp; B \\ -B^* &amp;amp; -A^* } \pmatrix{X_N \\ Y_N}&#xA;=&#xA;\omega_N \pmatrix{X_N \\ Y_N}&#xA;,&#xA;$$&lt;/span&gt;&#xA;where terms &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; are the Hessians (also called coupling matrices), &lt;span class=&quot;math-container&quot;&gt;$\omega_N$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-th excitation energy, and vectors &lt;span class=&quot;math-container&quot;&gt;$X_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_N$&lt;/span&gt; contain the corresponding transition amplitudes. The equation can be further simplified by considering the Tamm–Dancoff approximation (neglecting &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;) that can be added as a part of this direction of DFT development (&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0009261499011495&quot; rel=&quot;noreferrer&quot;&gt;Hirata &amp;amp; Head-Gordon 1999&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;For real orbitals and frequency-independent DFT kernel (part of the Hessian), the equation can alternatively be simplified by defining&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;CZ_N = \omega_N^2 Z_N&#xA;,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$C=(A-B)^{1/2}(A+B)(A-B)^{1/2}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Z_N=(A-B)^{1/2}(X_N-Y_N)$&lt;/span&gt;.&#xA;The Casida equation has the form of an eigenvalue equation with excitation energies being the eigenvalues.&lt;/p&gt;&#xA;&lt;p&gt;The equation was introduced by &lt;a href=&quot;https://www.worldscientific.com/doi/abs/10.1142/9789812830586_0005&quot; rel=&quot;noreferrer&quot;&gt;Casida in 1995&lt;/a&gt; and is now part of all major DFT codes and the primary DFT way of calculating excitation energies and excited state properties of wide range of systems.&lt;/p&gt;&#xA;" OwnerUserId="544" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-12T18:44:36.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1285" PostTypeId="1" AcceptedAnswerId="1290" CreationDate="2020-06-12T16:27:15.570" Score="18" ViewCount="1098" Body="&lt;p&gt;One way of predicting the thermodynamic stability of a DFT modelled structure is to calculate the energy above convex hull, which was used as the criterion in &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;The Materials Project&lt;/a&gt; database. For example, if I modelled the compound &lt;span class=&quot;math-container&quot;&gt;$\ce{BaSr(FeO3)2}$&lt;/span&gt;, I could compare its potential energy with that of the possible decompositions such as &lt;span class=&quot;math-container&quot;&gt;$\ce{SrFeO3}$&lt;/span&gt; &amp;amp; &lt;span class=&quot;math-container&quot;&gt;$\ce{BaFeO3}$&lt;/span&gt; and make a judgement on the stability. One might think this process is tedious because there can be several possible decompositions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another way of predicting thermodynamic stability at &lt;strong&gt;room temperature&lt;/strong&gt; is to perform molecular dynamic (MD) simulations&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/smtd.201900360&quot; rel=&quot;noreferrer&quot;&gt; [1]&lt;/a&gt;. VASP supports MD simulations (&lt;code&gt;IBRION=0&lt;/code&gt;) too.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;What are the other commonly used methods of predicting stability of new structures?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;[ 1 ]  Lu, S., Zhou, Q., Ma, L., Guo, Y., Wang, J., Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning. Small Methods 2019, 3, 1900360. &lt;a href=&quot;https://doi.org/10.1002/smtd.201900360&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1002/smtd.201900360&lt;/a&gt; &lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="5" LastEditDate="2020-06-13T01:59:26.480" LastActivityDate="2020-06-13T07:00:14.540" Title="What are the ways to ensure thermodynamic stability of a DFT modelled new structure?" Tags="|density-functional-theory|molecular-dynamics|vasp|thermodynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1286" PostTypeId="2" ParentId="18" CreationDate="2020-06-12T23:34:26.173" Score="14" Body="&lt;p&gt;Machine learning (ML) is rapidly gaining its popularity in the field of materials science due to its exceptional ability to learn from data to guide experimentalists, thus reducing traditional trial and error loops coupled with human intuition; as well as to replace time consuming &lt;em&gt;ab initio&lt;/em&gt; calculations. Of course, the foundation of ML is data (preferably large and of good quality). Currently, there are well organised and maintained experimental (&lt;a href=&quot;https://www.fiz-karlsruhe.de/en/produkte-und-dienstleistungen/inorganic-crystal-structure-database-icsd&quot; rel=&quot;noreferrer&quot;&gt;ICSD&lt;/a&gt;, &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-system/components/csd/&quot; rel=&quot;noreferrer&quot;&gt;CSD&lt;/a&gt;, &lt;a href=&quot;https://htem.nrel.gov/&quot; rel=&quot;noreferrer&quot;&gt;HTEM&lt;/a&gt;, etc.) and theoretical (&lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;MP&lt;/a&gt;, &lt;a href=&quot;http://www.aflowlib.org/&quot; rel=&quot;noreferrer&quot;&gt;AFLOW&lt;/a&gt;, &lt;a href=&quot;http://oqmd.org/&quot; rel=&quot;noreferrer&quot;&gt;OQMD&lt;/a&gt;, etc.) databases that power ML models, but it is not uncommon that researchers collect their own databases by &lt;a href=&quot;https://link.springer.com/article/10.1007/s11837-013-0755-4&quot; rel=&quot;noreferrer&quot;&gt;High-throughput Density Functional Theory&lt;/a&gt; calculations, &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0205-0&quot; rel=&quot;noreferrer&quot;&gt;High-throughput Experiments&lt;/a&gt; or screening the literature.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have highlighted several cases below where ML is applied in materials research. However, this is not an exhaustive list, meaning there is many more applications, and growing.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Structure-property prediction regression models [&lt;a href=&quot;http://Classification%20models%20to%20screen-down%20a%20large%20database%20to%20find%20candidate%20materials%20for%20a%20desired%20material%20class&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Classification models to screen-down a large database to find candidate materials for a desired material class [&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/smtd.201900360&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Classification/regression models for material characterisation (e.g. analyse space group using XRD data [&lt;a href=&quot;https://www.nature.com/articles/s41524-019-0196-x&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;])&lt;/li&gt;&#xA;&lt;li&gt;Natural language processing (NLP) models for automatic data extraction from literature&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00207&quot; rel=&quot;noreferrer&quot;&gt; [chemdataextractor]&lt;/a&gt;, capture materials knowledge by automatically reading Millions of papers [&lt;a href=&quot;https://www.nature.com/articles/s41586-019-1335-8&quot; rel=&quot;noreferrer&quot;&gt;4&lt;/a&gt;], future research trend prediction etc.&lt;/li&gt;&#xA;&lt;li&gt;Active learning and Bayesian optimisation to guide experiments [&lt;a href=&quot;https://www.nature.com/articles/s41467-018-03821-9&quot; rel=&quot;noreferrer&quot;&gt;5&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Material/molecule generation using reinforcement learning [&lt;a href=&quot;https://advances.sciencemag.org/content/4/7/eaap7885&quot; rel=&quot;noreferrer&quot;&gt;6&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Dimensionality reduction for data visualization [&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S092702561830716X&quot; rel=&quot;noreferrer&quot;&gt;7&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;I strongly recommend &lt;a href=&quot;https://www.nature.com/npjcompumats/&quot; rel=&quot;noreferrer&quot;&gt;NPJ Computational Materials&lt;/a&gt;, which is a well received, specialised journal in this field. Following are two good review papers I came across.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/s41524-019-0221-0#:~:text=Machine%20learning%20in%20materials%20science%20is%20mostly%20concerned%20with%20supervised,major%20challenges%20in%20material%20informatics.&quot; rel=&quot;noreferrer&quot;&gt;Recent advances and applications of machine learning in solid-state&#xA;materials science&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/s41586-018-0337-2&quot; rel=&quot;noreferrer&quot;&gt;Machine learning for molecular and materials science&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;You would also want to check out the tools below for high-throughput DFT calculations and analyses that are usually coupled with ML studies in computational materials science. &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; - open-source python library for materials analysis&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://materialsproject.github.io/fireworks/&quot; rel=&quot;noreferrer&quot;&gt;fireworks&lt;/a&gt; - open-source python package for managing&#xA;high-throughput workflows&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://atomate.org/&quot; rel=&quot;noreferrer&quot;&gt;atomate&lt;/a&gt; - python package built on top of pymatgen &amp;amp; fireworks&#xA;to execute workflows. It can be integrated with VASP which makes it&#xA;easier to run a series of VASP calculations using a few lines of&#xA;python code&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.aflowlib.org/aflow-ml/&quot; rel=&quot;noreferrer&quot;&gt;AFLOW ML&lt;/a&gt; - ML tool provided by AFLOW repository&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Finally, the true potential of Artificial Intelligence (AI) is yet to be explored in the field of materials science; and by the look of it, there is lot more opportunities. Some of you might have heard of &lt;a href=&quot;https://en.wikipedia.org/wiki/Generative_adversarial_network&quot; rel=&quot;noreferrer&quot;&gt;Generative Adversarial Networks&lt;/a&gt; (GANs) that were recently used to generate realistic images of people that do not exist in the world! Check out &lt;a href=&quot;https://github.com/NVlabs/stylegan&quot; rel=&quot;noreferrer&quot;&gt;StyleGAN&lt;/a&gt; by &lt;a href=&quot;https://www.nvidia.com/en-gb/&quot; rel=&quot;noreferrer&quot;&gt;NVIDIA&lt;/a&gt;. Who knows if these GANs or other generative AI models will be used to generate new synthesizable compounds!&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-06-12T23:34:26.173" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1287" PostTypeId="2" ParentId="51" CreationDate="2020-06-13T01:24:21.037" Score="12" Body="&lt;p&gt;Inverse designing of materials with known target properties is of great importance (to reduce time, labour, financial etc. costs) than the traditional way of materials design which is guided by human intuition, followed by trial and error loops (see figure below from &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0153-8&quot; rel=&quot;noreferrer&quot;&gt;Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design&lt;/a&gt;&#xA;). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Active learning optimization methods are generally used to iteratively guide experiments such that only a small number of promising experiments are carried out to discover new stable materials with target properties. During the iterative loop, the algorithm can learn from both successful and failed previous experiments to guide the next experiment. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;To formulate a simple example, imagine you want to discover new stable quaternary compound in the quaternary system &lt;span class=&quot;math-container&quot;&gt;$\ce{Ba - Sr - Mn - O}$&lt;/span&gt;. One would start the experiment from &lt;span class=&quot;math-container&quot;&gt;$\ce{BaSrMn2O6}$&lt;/span&gt;, and the active learning algorithm learns from the existing data and the success/failure of this experiment to guide the next &lt;em&gt;point&lt;/em&gt; to experiment in the quaternary system, such that smaller number of steps will be needed to reach convergence, which is to find a new stable compound. The same example can be reiterated to find new quaternary compound with target dielectric constant etc. It is specifically very useful when the compound search space is huge, but only very few experimental data is available on such compounds. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fTpJ3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fTpJ3.png&quot; alt=&quot;The trajectory of new materials discovery&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In theory, we want to find the design &lt;em&gt;x&lt;/em&gt;, that maximises a desired function &lt;em&gt;f(x)&lt;/em&gt;. Bayesian global optimisation (BGO) is a powerful algorithm used to search for extrema of objective functions which are costly and complex. BGO is applied in active learning to reach convergence. Describing BGO is beyond the scope of this answer and I suggest you look into &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0153-8&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; to understand the details. I also recommend the paper &lt;a href=&quot;https://www.nature.com/articles/s41467-018-03821-9&quot; rel=&quot;noreferrer&quot;&gt;Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning&lt;/a&gt; that deploys ML classification, regression and active learning techniques to discover new ferroelectric materials.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Finally, I have written an answer &lt;a href=&quot;https://materials.stackexchange.com/questions/18/what-is-the-current-status-of-machine-learning-applied-to-materials-or-molecular/1286#1286&quot;&gt;here&lt;/a&gt; describing the current trend of ML in materials science. Check that out too.&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-06-13T01:24:21.037" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1288" PostTypeId="2" ParentId="139" CreationDate="2020-06-13T02:49:23.040" Score="14" Body="&lt;p&gt;A locally interacting system displaying a continuous phase transition belongs to a universality class that is determined solely by the system symmetries and dimensionality.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Drawing from &lt;a href=&quot;https://en.wikipedia.org/wiki/Universality_class#List_of_critical_exponents&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia's list&lt;/a&gt; (itself mostly based on &lt;a href=&quot;https://doi.org/10.1103/RevModPhys.76.663&quot; rel=&quot;noreferrer&quot;&gt;Ódor's paper&lt;/a&gt;) and &lt;a href=&quot;https://physics.stackexchange.com/a/255632/75633&quot;&gt;this answer&lt;/a&gt; from Physics SE, here's a partial list of universality classes and critical exponents:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{| c | c | c c c c c c | c|}&#xA;\hline&#xA;\textbf{dim.} &amp;amp; \textbf{Symm.} &amp;amp;\alpha &amp;amp; \beta &amp;amp; \gamma &amp;amp; \delta &amp;amp; \nu &amp;amp; \eta &amp;amp; \textbf{class} \\&#xA; \hline \hline&#xA;\text{any} &amp;amp; \text{any} &amp;amp; 0 &amp;amp; 1/2 &amp;amp; 1 &amp;amp; 3 &amp;amp; 1/2 &amp;amp; 0 &amp;amp; \text{Mean field} \\\hline&#xA;2 &amp;amp; \text{Sym}_{2} &amp;amp; 0 &amp;amp; 1/8 &amp;amp; 7/4 &amp;amp; 15 &amp;amp; 1 &amp;amp; 1/4 &amp;amp;  \\&#xA;3 &amp;amp; \text{Sym}_{2} &amp;amp; 0.11007(7) &amp;amp; 0.32653(10) &amp;amp; 1.2373(2) &amp;amp; 4.7893(8) &amp;amp; 0.63012(16) &amp;amp; 0.03639(15) &amp;amp; \text{Ising} \\&#xA;4+ &amp;amp; \text{Sym}_{2} &amp;amp; 0 &amp;amp; 1/2 &amp;amp; 1 &amp;amp; 3 &amp;amp; 1/2 &amp;amp; 0 &amp;amp; \\\hline&#xA;2 &amp;amp; \text{Sym}_{3} &amp;amp; 1/3 &amp;amp; 1/9 &amp;amp; 13/9 &amp;amp; &amp;amp;  5/6 &amp;amp; &amp;amp; \text{3-state Potts} \\\hline&#xA;2 &amp;amp; \text{Sym}_{4} &amp;amp; 2/3 &amp;amp; 1/12 &amp;amp; 7/6 &amp;amp; &amp;amp;  2/3 &amp;amp; &amp;amp; \text{Ashkin-Teller (4-state Potts)} \\\hline&#xA;3 &amp;amp; {\mathcal {O}}(2) &amp;amp; −0.0146(8) &amp;amp; 0.3485(2) &amp;amp; 1.3177(5) &amp;amp; 4.780(2) &amp;amp; 0.67155(27) &amp;amp; 0.0380(4) &amp;amp; \text{XY} \\  \hline&#xA;3 &amp;amp; {\mathcal {O}}(3) &amp;amp; −0.12(1) &amp;amp; 0.366(2) &amp;amp; 1.395(5) &amp;amp; &amp;amp; 0.707(3) &amp;amp; 0.035(2) &amp;amp; \text{Heisenberg} \\\hline&#xA;1 &amp;amp; \mathbf{1} &amp;amp; &amp;amp; 0 &amp;amp; 1 &amp;amp; &amp;amp; 1 &amp;amp; &amp;amp; \\&#xA;2 &amp;amp; \mathbf{1} &amp;amp; −2/3 &amp;amp; 5/36 &amp;amp; 43/18 &amp;amp; 91/5 &amp;amp; 4/3 &amp;amp; 5/24 \\&#xA;3 &amp;amp; \mathbf{1} &amp;amp; −0.625(3) &amp;amp; 0.4181(8) &amp;amp; 1.793(3) &amp;amp; 5.29(6) &amp;amp; 0.87619(12) &amp;amp; 0.46(8) \text{ or } 0.59(9) &amp;amp; \text{Ordinary percolation} \\&#xA;4 &amp;amp; \mathbf{1} &amp;amp; −0.756(40) &amp;amp; 0.657(9) &amp;amp; 1.422(16) &amp;amp; &amp;amp; 0.689(10) &amp;amp; −0.0944(28) \\&#xA;5 &amp;amp; \mathbf{1} &amp;amp; &amp;amp; 0.830(10) &amp;amp; 1.185(5) &amp;amp; &amp;amp; 0.569(5) &amp;amp;  \\&#xA;6+ &amp;amp; \mathbf{1} &amp;amp; −1 &amp;amp; 1 &amp;amp; 1 &amp;amp; 2 &amp;amp; 1/2 &amp;amp; 0 \\&#xA;\hline&#xA;1 &amp;amp; \mathbf{1} &amp;amp; 0.159464(6) &amp;amp; 0.276486(8) &amp;amp; 2.277730(5) &amp;amp; 0.159464(6) &amp;amp; 1.096854(4) &amp;amp; 0.313686(8) &amp;amp;  \\&#xA;2 &amp;amp; \mathbf{1} &amp;amp; 0.451 &amp;amp; 0.536(3) &amp;amp; 1.60 &amp;amp; 0.451 &amp;amp; 0.733(8) &amp;amp; 0.230 &amp;amp; \text{Directed percolation}\\&#xA;3 &amp;amp; \mathbf{1} &amp;amp; 0.73 &amp;amp; 0.813(9) &amp;amp; 1.25 &amp;amp; 0.73 &amp;amp; 0.584(5) &amp;amp; 0.12 \\&#xA;4+ &amp;amp; \mathbf{1} &amp;amp; −1 &amp;amp; 1 &amp;amp; 1 &amp;amp; 2 &amp;amp; 1/2 &amp;amp; 0 \\&#xA;\hline&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{1}$&lt;/span&gt; denotes the &lt;a href=&quot;https://en.wikipedia.org/wiki/Trivial_group&quot; rel=&quot;noreferrer&quot;&gt;trivial group&lt;/a&gt;, &lt;span class=&quot;math-container&quot;&gt;$\text{Sym}_{n}$&lt;/span&gt; the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-th &lt;a href=&quot;https://en.wikipedia.org/wiki/Symmetric_group&quot; rel=&quot;noreferrer&quot;&gt;Symmetric group&lt;/a&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n)$&lt;/span&gt; the &lt;a href=&quot;https://en.wikipedia.org/wiki/Orthogonal_group&quot; rel=&quot;noreferrer&quot;&gt;Orthogonal group&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="625" LastEditorUserId="625" LastEditDate="2020-06-13T10:18:12.470" LastActivityDate="2020-06-13T10:18:12.470" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1289" PostTypeId="2" ParentId="1087" CreationDate="2020-06-13T05:02:41.003" Score="5" Body="&lt;p&gt;I didn't notice this before, but the link provided in the question can already be used to visualize any 2D Brillouin zone. Since you can define the ratio of b/a, and the angle between b and a, then you can define any 2D Bravais lattice. There are only &lt;a href=&quot;https://en.wikipedia.org/wiki/Bravais_lattice#In_2_dimensions&quot; rel=&quot;noreferrer&quot;&gt;5 possibilities&lt;/a&gt;. The &quot;hexagonal&quot; and &quot;square&quot; options are just there to conveniently show two of them.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Brillouin zone &lt;em&gt;only depends on the Bravais lattice vectors&lt;/em&gt;. Any additional complexity in the basis of this lattice (i.e. the specific arrangement of tiles) is irrelevant for the shape and size of the Brillouin zone. However, in real diffraction pattern measurements, the basis determines the &lt;em&gt;intensity&lt;/em&gt; of each point in the reciprocal lattice by the corresponding &lt;a href=&quot;https://en.wikipedia.org/wiki/Structure_factor&quot; rel=&quot;noreferrer&quot;&gt;structure factor&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I drew some of the possible Bravais lattice unit cells for the tile patterns included in the question:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/qhiKT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qhiKT.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-06-13T05:17:00.030" LastActivityDate="2020-06-13T05:17:00.030" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1290" PostTypeId="2" ParentId="1285" CreationDate="2020-06-13T07:00:14.540" Score="12" Body="&lt;p&gt;This is a tricky question and there is a whole area of research dedicated to solving it. The definition of the thermodynamically stable phase of a system is that occupying the &lt;em&gt;global&lt;/em&gt; minimum of the potential energy surface, or more precisely, the global minimum of the potential &lt;em&gt;free energy&lt;/em&gt; surface at the temperature of interest. Let me focus on solid phases, and divide the answer into two cases:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Elemental compounds. For compounds containig a single element, then the question simply becomes: what is the structure that has the lowest energy? As trivial as this question may sound, it has no general solution. In principle you should try all possible structures (with any number of atoms in the primitive cell) in all possible atomic arrangements to find the global minimum. This is a computational problem with exponential scaling, so it has no solution. Although there is no general answer, the past 15 years or so have seen great progress, with DFT-based &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_structure_prediction&quot; rel=&quot;noreferrer&quot;&gt;structure prediction methods&lt;/a&gt; using a variety of algorithms (stochastic, genetic, etc.) capable of exploring many structures and providing reasonable answers to the question posed. Despite the success of these methods, note that they do not provide a general solution: to give an example, structure searches are limited to about &lt;span class=&quot;math-container&quot;&gt;$100$&lt;/span&gt; atoms per cell, but it could very well be that the primitive cell of a material has &lt;span class=&quot;math-container&quot;&gt;$1000$&lt;/span&gt; atoms per cell, which means that the structure could never be found unless that many atoms are used in the simulation. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Non-elemental compounds. For compounds with more than one element, you need to add an extra degree of freedom to the search space: the stoichiometry of the compound. What you should do is the same structure searching in point 1, but now for every possible stoichiometry. Again, it may be that the correct stoichiometry is one you never try, so you would completely miss the thermodynamically stable structure in this case.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Up to this point, I have discussed the difficulties in scanning through all possible structures, arising from the extremely high dimensionality of the structural and composition spaces of materials. But let's imagine you have gone through the exercise of generating a range of candidate structures for your system. Then the next step is to figure out which one is the lowest (free) energy structure. The first step taken is typically to do a static lattice DFT calculation, which gives the electronic contribution to the energy. Then a finite temperature calculation is done to include the vibrational contribution to the energy at a given temperature. This calculation can be done either using the harmonic approximation to lattice dynamics (phonons), or a molecular dynamics simulation as you described. The former is fine at relatively low temperatures for most materials, and the latter necessary at higher temperatures when anharmonic vibrations become important. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;The free energies you get from these calculations allow you to decided which is the lowest energy of your elemental system (for example if you do this for carbon, you will find that graphite is the ground state as it has a lower energy than diamond), and it will also tell you the correct stoichiometry of a compound by building the corresponding Hull diagram (as you pointed out, this is being done in the Materials Project). To be precise, these calculations will tell you what the lowest free energy structure/compound is amongst those you try. However, remember that you can never be sure that you didn't miss a lower energy material in your initial searches.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;At this point the situation may look desperate. However, in practise it is many times possible to determine the actual thermodynamically stable structure. The obvious answer is that there may be experimental data. Even if there is only partial experimental data (for example no hydrogen positions, which are difficult to determine using X-rays), then these experiments can provide important constraints that can guide the theory and dramatically reduce the dimensionality of the search space, for example by providing the space group of the material. Finally, even if there is no data, many systems adopt relatively high-symmetry structures with relatively few atoms in the primitive cell. This makes the structure searches easier, as symmetry constraints reduce the dimensionality of the space being explored, and small primitive cells maximize the chances that you are exploring the correct number of atoms in the primitive cell. Indeed, structure prediction has been able to predict multiple structures that have subsequently been confirmed experimentally.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-13T07:00:14.540" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1291" PostTypeId="2" ParentId="607" CreationDate="2020-06-13T10:33:32.870" Score="5" Body="&lt;p&gt;I recently installed VASP GPU version provided by NVIDIA (&lt;a href=&quot;https://www.nsc.liu.se/~pla/blog/2015/11/16/vaspgpu/&quot; rel=&quot;noreferrer&quot;&gt;here's the installation tutorial&lt;/a&gt;) on my machine that has an RTX 2080 Ti GPU. GPU version was announced for &lt;code&gt;vasp-5.4.1&lt;/code&gt; and works fairly well for &lt;code&gt;vasp-5.4.4&lt;/code&gt; too. However, I have only managed to observe around 1.5x - 2x speedup when running VASP on the GPU compared to my &lt;code&gt;Intel(R) Core(TM) i7-8700 CPU&lt;/code&gt; with 12 cores. But there is definitely some degree of speedup. Maybe the GPU version of VASP is meant for more powerful (and expensive) double-precision GPUs such as &lt;code&gt;Titan V&lt;/code&gt; or &lt;code&gt;Tesla V100&lt;/code&gt;. While my GPU performs exceptionally well on running deep learning applications, I feel it can't keep up with its more powerful counterparts for VASP calculations. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Furthermore, I use &lt;a href=&quot;https://software.intel.com/content/www/us/en/develop/documentation/mpi-developer-reference-linux/top/command-reference/mpirun.html&quot; rel=&quot;noreferrer&quot;&gt;intel's mpi library&lt;/a&gt; to run VASP. Surprisingly, &lt;code&gt;mpirun -n 1 vasp_gpu&lt;/code&gt; is much faster than running on 2(or more) cores (&lt;code&gt;mpirun -n 2 vasp_gpu&lt;/code&gt;) even though more cores consumed more GPU memory. Using more cores is even slower than running solely on CPU with &lt;code&gt;vasp_std&lt;/code&gt;. I am currently investigating what's the reason for this and greatly appreciate if any other user with experience contribute to this answer. &lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-06-13T10:33:32.870" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1292" PostTypeId="2" ParentId="24" CreationDate="2020-06-13T11:29:55.957" Score="11" Body="&lt;p&gt;If you are looking for theoretical prediction of candidate perovskite solar cell materials; I have come across several papers that couple high-throughput density functional theory calculations along with machine learning for new material prediction. I haven't seen any solar cell compound discovery theoretical work that eventually validated their predictions through experiments though. However, this is not a result of an extensive search, so concluding &quot;materials modelling has not contributed to solar cell materials discovery&quot; is not right.&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Lu, S., Zhou, Q., Ma, L., Guo, Y., Wang, J., Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning. Small Methods 2019, 3, 1900360. &lt;a href=&quot;https://doi.org/10.1002/smtd.201900360&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1002/smtd.201900360&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Im, J., Lee, S., Ko, T. et al. Identifying Pb-free perovskites for solar cells by machine learning. npj Comput Mater 5, 37 (2019). &lt;a href=&quot;https://doi.org/10.1038/s41524-019-0177-0&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/s41524-019-0177-0&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Jacobs, R., Luo, G., Morgan, D., Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells. Adv. Funct. Mater. 2019, 29, 1804354. &lt;a href=&quot;https://doi.org/10.1002/adfm.201804354&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1002/adfm.201804354&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Choudhary et al. Accelerated Discovery of Efficient Solar Cell Materials Using Quantum and Machine-Learning Methods Chem. Mater. 2019, 31, 15, 5900–5908 Publication Date:July 17, 2019 &lt;a href=&quot;https://doi.org/10.1021/acs.chemmater.9b02166&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/acs.chemmater.9b02166&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;I did find machine learning ferroelectric perovskite modelling &lt;a href=&quot;https://www.nature.com/articles/s41467-018-03821-9&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; that validated predictions through experiments.&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="857" LastEditDate="2020-06-14T08:05:30.043" LastActivityDate="2020-06-14T08:05:30.043" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1293" PostTypeId="2" ParentId="1051" CreationDate="2020-06-13T15:07:12.053" Score="8" Body="&lt;p&gt;Normally this should follow a nice equation of state (Rose, Murnigham etc.). I'd say the curve looks okay: &lt;span class=&quot;math-container&quot;&gt;$35 \mathrm{A}^3$&lt;/span&gt; seems to be the questionable outlier.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;There is not enough information on the setup here, but I will give two thoughts anyway:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Has the k-point convergence been tested? &lt;/li&gt;&#xA;&lt;li&gt;HCP lattices require gamma centered k-point grids: &lt;a href=&quot;https://cms.mpi.univie.ac.at/vasp/vasp/hexagonal_lattices.html&quot; rel=&quot;noreferrer&quot;&gt;https://cms.mpi.univie.ac.at/vasp/vasp/hexagonal_lattices.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="868" LastEditorUserId="5" LastEditDate="2020-06-13T16:52:11.450" LastActivityDate="2020-06-13T16:52:11.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1294" PostTypeId="2" ParentId="326" CreationDate="2020-06-13T16:54:43.137" Score="12" Body="&lt;p&gt;TLDR: When you calculate phonons, you can describe electrons at different levels of theory, typically semilocal DFT, but also hybrids or dynamical mean-field theory. Phonons do include zero-point motion, as they are essentially a set of uncoupled quantum harmonic oscillators. Enthalpy can be calculated without reference to phonons, simply adding a PV term to the Hamiltonian. Gibbs free energy is calculated by adding a PV term to the phonon calculation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Longer answer: The starting point of any phonon calculation is the Born-Oppenheimer approximation, which allows you to separate the electron and nuclear degrees of freedom. After applying this Born-Oppenheimer approximation, you end up with two eigenvalue equations. The first one corresponds to the electrons, in which the nuclei occupy fixed positions and their coordinates only appear as parameters. This electronic eigenvalue equation is what DFT codes solve.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Your question refers to the second eigenvalue equation that results from the Born-Oppenheimer approximation, which is the nuclear equation. The Hamiltonian in this equation reads (in atomic units):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}=-\sum_i\frac{1}{2m_i}\nabla_i^2+V(\mathbf{R}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;in which the sum is the kinetic energy of the nuclei, and it runs over all nuclei &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; in the system, and the second term is the potential energy felt by the nuclei, in which &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}=(\mathbf{r}_1,\mathbf{r}_2,\ldots)$&lt;/span&gt; is a collective variable containing all individual nuclear coordinates &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{r}_i\}$&lt;/span&gt;. The value of this potential energy, typically called the potential energy surface, at a given collective nuclear coordinate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; is given by the electronic eigenvalue for the nuclei fixed at this coordinate. This means that, unlike the electronic equation solved in DFT for which you know the Hamiltonian, in the case of the equation for the nuclei, you don't even know the Hamiltonian, as you don't know what &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt; is. You first need to figure out what &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt; is, and to do this you need to solve the electronic equation &lt;strong&gt;many&lt;/strong&gt; times, once at each potential value of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;. This is clearly unfeasible, as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; spans a 3N dimensional space, where N is the number of atoms in your system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This is where the harmonic approximation that you mention comes in. For a material, we assume that the nuclei don't move much from their equilibrium positions. This is because they are relatively heavy (compared to the electrons), so rather than exploring the entire potential &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt;, they only explore this potential in the region near their equilibrium position, which corresponds to a minimum of &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt;. To proceed, I will make a change of coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_i=\mathbf{r}_i-\mathbf{r}_i^0$&lt;/span&gt;, to collective coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{U}$&lt;/span&gt; which are relative coordinates with respect to the equilibrium coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}^0$&lt;/span&gt;. In this way, equilibrium corresponds to &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{U}=0)$&lt;/span&gt;. In the harmonic approximation, we approximate this potential by a second-order Taylor expansion about equilibrium:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V(\mathbf{U})\simeq V(0)+\sum_{\alpha,\beta}\frac{\partial^2V}{\partial u_{\alpha}\partial u_{\beta} }u_{\alpha}u_{\beta}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the sum, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; are collective indices capturing the degrees of freedom of the 3N-dimensional energy surface (cell in the crystal, atoms in the basis, and Cartesian direction). To proceed, you replace this second-order approximation to the potential into the nuclear Hamiltonian I wrote above, and you can diagonalize it in terms of phonons. This second-order approximation works very well because, in terms of phonons, it essentially allows you to replace a 3N-dimensional potential with 3N 1-dimensional potentials, and the latter are much easier to calculate.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore, to go back to your question: all that goes into a phonon calculation are the second order derivatives of the potential energy surface &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt;. What information does this contain? As &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt; corresponds to the electronic energy at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;, then the level at which you treat the electrons affects &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt;. Typically, this is calculated using semi-local DFT (LDA, GGA), but there are a few studies that calculate &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt; using hybrid DFT, which is much more expensive but more accurate, or even other beyond-DFT methods like dynamical mean-field theory.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Once you solve the nuclear problem in terms of phonons, you can calculate the vibrational contribution at finite temperature to the Helmholtz free energy (TS term). In these calculations, the phonons &lt;strong&gt;do&lt;/strong&gt; have a zero-point contribution to the energy, as they are described by a set of uncoupled quantum harmonic oscillators.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For your other specific questions:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Enthalpy: for that you simply need to add a PV term to the Hamiltonian, so no need for phonons there. The calculations aren't any more expensive than a typical DFT calculation as PV is very cheap to evaluate.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Gibbs free energy: for this you need to add both PV and TS terms, you get the TS term from the Helmholtz free energy, and the PV term from the enthalpy.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-13T16:54:43.137" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1295" PostTypeId="2" ParentId="1051" CreationDate="2020-06-14T04:51:19.487" Score="7" Body="&lt;p&gt;There is little information in your question. It would be useful if you add your INCAR files. It seems to me that the problem could be in the fact that for such a cell there could be a “a free” parameter (c/a). So, you might be changing the volumen and the c/a ratio at the same time. Also, check that your are removing the density and wavefuncton files as a change in volumen changes the basis set&lt;/p&gt;&#xA;" OwnerUserId="262" LastActivityDate="2020-06-14T04:51:19.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1296" PostTypeId="2" ParentId="89" CreationDate="2020-06-14T09:54:22.650" Score="20" Body="&lt;p&gt;Short answer: Modern implementations of these two methods lead to similar accuracies.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Longer answer: The calculation of phonons requires the calculation of the Hessian of the potential energy surface &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{R})$&lt;/span&gt;, also known as the matrix of force constants:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial^2 V(\mathbf{R})}{\partial \mathbf{R}_i\partial\mathbf{R}_j}=-\frac{\partial \mathbf{F}_j}{\partial\mathbf{R}_i},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; is a collective coordinate of all atomic positions, &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; label atoms &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; in your system, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F}_j=-\partial V(\mathbf{R})/\partial\mathbf{R}_j$&lt;/span&gt; is the force felt when displacing atom &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Finite displacement.&lt;/strong&gt; This is what you call &quot;frozen phonon&quot;, and in this method you calculate the forces in DFT, and then calculate the derivative of the forces by finite difference methods. Therefore, the numerical approximation is that of approximating a derivative with a finite difference formula. In principle, you can make this calculation as accurate as you want by using increasingly accurate approximations to the numerical derivative, but in practice even low-order approximations lead to very accurate answers. The advantages of this method are that it is very simple to implement, and therefore it is in fact available using any underlying electronic structure method that can calculate forces, which includes semilocal DFT, hybrid DFT, or other non-DFT methods, like force fields or dynamical mean-field theory. The disadvantage of this method is that it requires the construction of supercells to capture long-wavelength phonons, which can make the calculations expensive. Most finite displacement codes use &quot;diagonal&quot; supercells, which lead to poor scaling, but the recently introduced &quot;nondiagonal&quot; supercells &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.184301&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; [disclaimer: I am a co-author of this work], significantly reduce the computational cost.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;DFPT.&lt;/strong&gt; In density functional perturbation theory, the calculation of the Hessian is specialized to DFT, and the second derivative of the energy is calculated as&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial^2 E}{\partial\lambda_i\lambda_j}=\int\frac{\partial^2V(\mathbf{r})}{\partial\lambda_i\lambda_j}n(\mathbf{r})d\mathbf{r}+\int\frac{\partial n(\mathbf{r})}{\partial\lambda_i}\frac{V(\mathbf{r})}{\partial\lambda_j}d\mathbf{r}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;This expression is general for parameters &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;, and in the case of phonons they simply become the atomic coordinate &lt;span class=&quot;math-container&quot;&gt;$\lambda_i=\mathbf{R}_i$&lt;/span&gt;. This expression requires the calculation of the derivative of the density, which in turn requires the derivative of the Kohn-Sham states. These terms can all be calculated within DFPT with the usual numerical approximations of finite basis sets, etc. Again, in practice, modern implementations are relatively easy to converge. The advantage of DFPT is that it does not require the construction of supercells, one can build a finite wave vector response within the primitive cell, so the computational cost is smaller than in the finite displacement method. The disadvantage of this method is that it is restricted to DFT (so no DMFT for example), and furthermore, the algorithmic implementation is not trivial, so it is only widely available for semilocal DFT (so no hybrid DFT either).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In summary, these two methods lead to comparable accuracies. If DFPT is available, then the calculations will be cheaper and DFPT should be the method of choice. However, DFPT is only widely available with semilocal DFT, which means that if you want phonons at the hybrid functional level, or using beyond-DFT methods, then you have to use the finite displacement method.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-14T09:54:22.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1297" PostTypeId="1" CreationDate="2020-06-14T21:08:05.497" Score="11" ViewCount="187" Body="&lt;p&gt;I have a series of molecules calculated (DFT PBE0-D3/def2-TZVP performed in Q-Chem) and I'm ready to plot PES (Potential Energy Surface). I had to increase the grid to get rid of small imaginary frequencies in frequency calculations.&lt;br&gt;&#xA;All calculations were performed with SMD(water) (Geometry Optimization and Frequency calculation), thus, numerical hessian calculation was performed. There are a lot of SCF energies from Frequency jobs that are lower in energy from the final value at &amp;quot;Optimizations converged&amp;quot; step. Does it mean that SCF energy for the &amp;quot;optimized geometry&amp;quot; should be adjusted?&lt;br&gt;&#xA;My question is which SCF energy is more correct to use to plot PES and further calculate enthalpy and Gibbs energy of the reactions?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="24" LastEditDate="2020-06-18T11:22:11.223" LastActivityDate="2020-06-18T11:37:31.250" Title="Which SCF energy to use to plot PES after calculations with SMD?" Tags="|q-chem|self-consistent-field|potential-energy-surface|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1298" PostTypeId="2" ParentId="1297" CreationDate="2020-06-14T21:46:08.510" Score="8" Body="&lt;p&gt;Generally you want to use the same settings when trying to combine results from different jobs. However, below is the general procedure that I have seen performed for a basic, publishable PES.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;1) Perform geometry optimization&lt;/p&gt;&#xA;&#xA;&lt;p&gt;2) Perform solvent/frequency calculations&lt;/p&gt;&#xA;&#xA;&lt;p&gt;3) Combine solvent energy and enthalpy (from frequency calculation &quot;Total Enthalp...&quot;)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;4) Use: ΔG = ΔH + TΔS&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With that in mind, use the optimized geometry for both the solvent and frequency calculations with the same settings (level of theory, basis set, grid, etc). &lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-06-14T21:46:08.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1299" PostTypeId="6" CreationDate="2020-06-15T02:32:31.610" Score="0" Body="&lt;p&gt;Hello, my name is Tyberius (Ty Balduf) and I'm a graduate student at the University of Kansas. I do computational chemistry research, specifically methods development for simulating chiral spectroscopy and charge transfer processes. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I think this site has the opportunity to become a great resource and hub for researchers across matter modeling disciplines. We already have a great core group of users, but there is plenty of room for the site to grow and develop. My hope is to play whatever small role I can in making that happen. &#xA;I have been an active participant on the SE network for a few years now (mainly Chem SE until now) and have learned a lot about mentoring new members, shaping community policy, and keeping a site running smoothly. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I see a moderator as being both a steward and representative for what the community wants; to be entrusted with the little details and maintenance work of keeping the site running day to day, but to ultimately be working to develop the site to fit the vision of the community.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://materials.meta.stackexchange.com/a/146/7&quot;&gt;My answers&lt;/a&gt; to the moderator questionnaire. &lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-15T19:06:49.397" LastActivityDate="2020-06-15T19:06:49.397" CommentCount="2" CommunityOwnedDate="2020-06-15T02:32:31.610" ContentLicense="CC BY-SA 4.0" />
  <row Id="1300" PostTypeId="2" ParentId="692" CreationDate="2020-06-15T05:32:28.763" Score="4" Body="&lt;h2&gt;NWChem&lt;/h2&gt;&#xA;&lt;p&gt;NWChem is an ideal package for massively parallel needs.&lt;/p&gt;&#xA;&lt;p&gt;JCP recently published a &lt;a href=&quot;https://aip.scitation.org/toc/jcp/collection/10.1063/jcp.2020.ESS2020.issue-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;collection of articles&lt;/a&gt; focused on the special topic &amp;quot;Electronic Structure Software&amp;quot;.&#xA;Not only NWCHem, GAMESS, and ACES4, but various other packages have the capability to do massively parallel calculations.&lt;/p&gt;&#xA;" OwnerUserId="322" LastEditorUserId="5" LastEditDate="2021-02-05T21:03:57.350" LastActivityDate="2021-02-05T21:03:57.350" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1301" PostTypeId="6" CreationDate="2020-06-15T07:14:44.950" Score="0" Body="&lt;p&gt;Whether we model molecules, atomic clusters, 2D-materials, bulk or mesoscale systems, we believe that computational science can be transcendental. For some, the task is to develop models and algorithms to solve an interesting problem with a desired efficacy. For others, it is to implement theory into software &amp;amp; push simulations forward. Finally, these are applied to discover and engineer real systems to solve world problems.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thus, it’s vital that there is a space in which all branches of matter-modeling converge and interact. &lt;strong&gt;My objective as a moderator would be to continue the efforts in maintaining an inclusive, multi- and interdisciplinary site.&lt;/strong&gt; To help solidify this as &lt;em&gt;THE&lt;/em&gt; forum of choice the field. This, by gaining the trust of novice and advanced members, ensuring that all Qs get the deserved attention &amp;amp; As of the highest quality. Additionally, I will communicate regularly with the community to ensure the site is headed in the right direction. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;My true college was SE, and I'm honored to be here NOW.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Thank you!&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;More on my commitment and experience &lt;a href=&quot;https://bit.ly/3fpVkOV&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, the CCMC &lt;a href=&quot;https://bit.ly/3d4PJMr&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="175" LastEditDate="2020-06-15T19:41:49.597" LastActivityDate="2020-06-15T19:41:49.597" CommentCount="4" CommunityOwnedDate="2020-06-15T07:14:44.950" ContentLicense="CC BY-SA 4.0" />
  <row Id="1302" PostTypeId="2" ParentId="1" CreationDate="2020-06-15T08:44:57.980" Score="18" Body="&lt;h3&gt;Awesome Materials Informatics&lt;/h3&gt;&#xA;&lt;p&gt;The community-edited &lt;a href=&quot;https://github.com/tilde-lab/awesome-materials-informatics&quot; rel=&quot;noreferrer&quot;&gt;awesome materials informatics list&lt;/a&gt; has a section on &amp;quot;machine-readable datasets&amp;quot;, many of which contain atomic structures of materials.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2020-08-15T12:38:00.053" LastActivityDate="2020-08-15T12:38:00.053" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1303" PostTypeId="2" ParentId="473" CreationDate="2020-06-15T09:06:29.987" Score="8" Body="&lt;p&gt;The Karlsruhe def2 basis sets cover most of the periodic table and are based on effective core potentials for relativistic effects; these are a good starting point for whatever you are interested in, and are also available built-in in Gaussian.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As to the functional, since you want to study slabs you probably want to use a pure functional since otherwise the calculations become horribly slow. PBE or TPSS would probably be safe bets.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-15T09:06:29.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1304" PostTypeId="6" CreationDate="2020-06-15T14:34:21.853" Score="0" Body="&lt;p&gt;I am Thomas, working as Assistant Professor in Physics in a college affiliated to the Mahatma Gandhi University, Kerala, India. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;My research interest is on density functional theory studies of low dimensional materials. I was part of CMS collaboration, CERN for a brief period and have research experience in the field of High Energy Physics also. I  teach Quantum Mechanics and Condensed Matter Physics at the Master's level.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I had to learn DFT by myself and hence I very much appreciate the value of this community. This is a wonderful place for learning and giving.  I believe that the scope of this SE is &lt;a href=&quot;https://materials.meta.stackexchange.com/a/103/88&quot;&gt;huge&lt;/a&gt; and we are just having a peek at the tip of the iceberg. &lt;strong&gt;My objective as a moderator is to see the site flourish the way the community desires and occasionally guide the community with gentle but firm interventions when deemed necessary.&lt;/strong&gt;  As I see it, the philosophy of &lt;a href=&quot;https://en.wikipedia.org/wiki/Ubuntu_philosophy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ubuntu&lt;/a&gt; should guide us, &lt;em&gt;I am because we are&lt;/em&gt;. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here are my &lt;a href=&quot;https://materials.meta.stackexchange.com/a/145/88&quot;&gt;answers&lt;/a&gt; to Election Questions&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-06-15T18:14:35.927" LastActivityDate="2020-06-15T18:14:35.927" CommentCount="0" CommunityOwnedDate="2020-06-15T14:34:21.853" ContentLicense="CC BY-SA 4.0" />
  <row Id="1305" PostTypeId="6" CreationDate="2020-06-15T15:15:22.303" Score="0" Body="&lt;h3&gt;TheSimpliFire&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;I would like to present my candidature as pro-tempore moderator. This was quite a challenging decision for me: having much experience in moderation on SE, I thought this would be a great opportunity to help out on this site, but I am a beginner in materials (though I have a strong mathematical and statistical background).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;However, I believe that being less knowledgeable in this area would not greatly impact on many moderation activities that I do. For example, I am very active in the &lt;a href=&quot;https://materials.stackexchange.com/review&quot;&gt;review queues&lt;/a&gt; as in my opinion they are some of the best ways to refine the quality of questions. In addition, I have been a &lt;a href=&quot;https://or.stackexchange.com/users/123/thesimplifire&quot;&gt;moderator on Operations Research SE&lt;/a&gt; for 8 months and an SE user for 3 years, so I have had much experience in tackling difficult scenarios and resolving disputes.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am available on this site for around 4 hours per day until September, where it will be around 2 hours from September as I'll be starting my PhD in Population Health Sciences at the University of Edinburgh.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://materials.meta.stackexchange.com/a/147/35&quot;&gt;Answers&lt;/a&gt; to the questionnaire.&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="35" LastEditDate="2020-06-15T19:41:28.350" LastActivityDate="2020-06-15T19:41:28.350" CommentCount="0" CommunityOwnedDate="2020-06-15T15:15:22.303" ContentLicense="CC BY-SA 4.0" />
  <row Id="1306" PostTypeId="5" CreationDate="2020-06-15T18:49:38.163" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-06-15T18:49:38.163" LastActivityDate="2020-06-15T18:49:38.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1307" PostTypeId="4" CreationDate="2020-06-15T18:49:38.163" Score="0" Body="Special tag for certain big-list questions. Answers should only go into detail about one specific topic related to the question. The original question will often present a template format for submitting answers." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-15T21:46:55.360" LastActivityDate="2020-06-15T21:46:55.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
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  <row Id="1309" PostTypeId="4" CreationDate="2020-06-15T18:54:08.077" Score="0" Body="For questions applying informatics techniques (data mining, high-throughput screening, specialized file formats) to materials research" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-15T21:46:38.740" LastActivityDate="2020-06-15T21:46:38.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
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  <row Id="1311" PostTypeId="4" CreationDate="2020-06-15T18:57:24.027" Score="0" Body="For questions about using implicit solvent models (e.g. Polarizable Continuum Method, Generalized Born, Conductor-like Screening Model)" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-15T21:46:42.030" LastActivityDate="2020-06-15T21:46:42.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1312" PostTypeId="5" CreationDate="2020-06-15T19:03:14.880" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-06-15T19:03:14.880" LastActivityDate="2020-06-15T19:03:14.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1313" PostTypeId="4" CreationDate="2020-06-15T19:03:14.880" Score="0" Body="For questions about the Vibrational Energy Distribution Analysis software package" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-15T21:47:01.093" LastActivityDate="2020-06-15T21:47:01.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1314" PostTypeId="1" CreationDate="2020-06-16T09:36:05.780" Score="13" ViewCount="2358" Body="&lt;p&gt;I have a 9 x 9 x 9 periodic crystal structure in .xyz format and I would like to change it to .cif file format.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Does anyone know how to convert the file?&lt;/strong&gt;&#xA;(e.g. 9 x 9 x 9 to unit cell then cif)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Pg5Iv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Pg5Iv.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="748" LastEditorUserId="35" LastEditDate="2020-06-16T12:38:47.723" LastActivityDate="2020-06-16T12:38:47.723" Title="9 x 9 x 9 periodic xyz file to cif file format" Tags="|crystal-structure|cif|visualization-software|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1315" PostTypeId="2" ParentId="1314" CreationDate="2020-06-16T10:59:53.300" Score="13" Body="&lt;p&gt;You can use for example &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; in python to do this. The tricky part of your question is to find a unit cell in step 2.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I outline the steps here:&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Read your xyz file into a pymatgen structure.&lt;/li&gt;&#xA;&lt;li&gt;Use the &lt;a href=&quot;https://pymatgen.org/pymatgen.symmetry.analyzer.html&quot; rel=&quot;noreferrer&quot;&gt;SpacegroupAnalyzer&lt;/a&gt; class to determine the unit cell.&lt;/li&gt;&#xA;&lt;li&gt;Write the cif file using the class &lt;a href=&quot;https://pymatgen.org/pymatgen.io.cif.html&quot; rel=&quot;noreferrer&quot;&gt;CifWriter&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="250" LastActivityDate="2020-06-16T10:59:53.300" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1316" PostTypeId="2" ParentId="1314" CreationDate="2020-06-16T11:11:24.200" Score="1" Body="&lt;p&gt;You can upload your .xyz file into &lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt;, then under the &lt;em&gt;Edit -&gt; Edit Data&lt;/em&gt;, you can find the Unit Cell option. Then you can export your data to a .cif format under the &lt;em&gt;File&lt;/em&gt; tab.&lt;/p&gt;&#xA;" OwnerUserId="35" LastActivityDate="2020-06-16T11:11:24.200" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1317" PostTypeId="2" ParentId="1314" CreationDate="2020-06-16T11:41:54.730" Score="3" Body="&lt;p&gt;There are probably quite a few software packages that automate this process. One I like to use is c2x, which provides support for structure files for multiple DFT packages (VASP, QE, Abinit, Castep, etc.) and visualization tools (VESTA, XCrysDen, JMol, etc.). You can download it from their website: &lt;a href=&quot;https://www.c2x.org.uk&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.c2x.org.uk&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-16T11:41:54.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1318" PostTypeId="2" ParentId="605" CreationDate="2020-06-16T14:54:48.563" Score="9" Body="&lt;p&gt;I'll try to outline an approach in plane-wave DFT. The main idea is to build up the system step-wise and reuse previous results as the number of atoms and therefore the computational burden will grow quickly.&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Lets start with the simulation using a bulk material with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms and assume the surface direction is orientated facing the z-axis. Make sure this cell is well relaxed.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Build a super cell (SC1) by repeating the cell along the z-direction &lt;span class=&quot;math-container&quot;&gt;$(2n+1)$&lt;/span&gt;-times that will have &lt;span class=&quot;math-container&quot;&gt;$(2n+1)N$&lt;/span&gt; atoms.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;An initial guess for the charge of the SC1 can be done by periodically repeating the charge from the first simulation. Eventually you need to interpolate this density such that it fits to the grid of the DFT simulation for SC1. In this simulations that atoms do not need to be relaxed as it's basically still bulk.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Now include a vacuum in the z-direction. Again an initial guess can be made from the charge density of the last simulation but the grid must be carefully adapted. Here, I would relax the first top and bottom layer and freeze all other layers, but only in z-direction. If they move a lot, make sure the vacuum included is sufficient. If so restart with relaxing 2 upper and bottom layer. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Once this is done make sure that the charge density in the middle layer is still bulk-like. If not, restart from step 2 with more layers.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;As we want to study the interaction with a molecule we need a wide enough cell in x and y-direction to avoid the molecule interact with its periodic replica. Thus we build a second super cell (SC2) by repeating the structure of the last simulation &lt;span class=&quot;math-container&quot;&gt;$n_x$&lt;/span&gt;-times in &lt;span class=&quot;math-container&quot;&gt;$x-$&lt;/span&gt; and and &lt;span class=&quot;math-container&quot;&gt;$n_y$&lt;/span&gt; times in &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;-direction. Again, reuse the charge density from the last simulation as we now have &lt;span class=&quot;math-container&quot;&gt;$(2n+1)n_x n_y N$&lt;/span&gt; atoms.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally, place your molecule close enough to one of the surface and relax only the atoms close to it.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&#xA;&lt;p&gt;Some practical hints in VASP,&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The python function &lt;code&gt;resample&lt;/code&gt; from &lt;code&gt;scipy.signal&lt;/code&gt; is quite useful to interpolate the charge density.&lt;/li&gt;&#xA;&lt;li&gt;Be aware of augmentation charges in VASP when extending your charge.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/NGXF&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;NGX&lt;/code&gt;&lt;/a&gt;, &lt;code&gt;NGY&lt;/code&gt; and &lt;code&gt;NGZ&lt;/code&gt; are the parameters that specify the real space grids.&lt;/li&gt;&#xA;&lt;li&gt;To analyse what is happening I would consider the potential that can be obtained with the Tag &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LVTOT&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;LVTOT = T&lt;/code&gt;&lt;/a&gt; and the differences with and without the molecule.&lt;/li&gt;&#xA;&lt;li&gt;The differences in charge density will tell further details about the interaction. So I would eventually simulate the molecule alone in SC2 and the compare to the situation including the surface.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="250" LastEditorUserId="250" LastEditDate="2020-06-16T15:33:38.057" LastActivityDate="2020-06-16T15:33:38.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1319" PostTypeId="2" ParentId="531" CreationDate="2020-06-16T15:10:46.420" Score="6" Body="&lt;p&gt;Gaussian itself doesn't have any way of computing sigma-profiles on its own. As you noticed, it has the &lt;code&gt;scrf=COSMORS&lt;/code&gt; keyword, but this just produces a file that is used by a dedicated program (e.g. &lt;a href=&quot;https://www.scm.com/doc/COSMO-RS/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;COSMO-RS&lt;/a&gt;, &lt;a href=&quot;http://www.cosmologic.de/products/cosmotherm.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;COSMOtherm&lt;/a&gt;).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;On the Gaussian side, it really is as straightforward as using that keyword. Here is a minimal example: &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;#p B88-VWN-P86/TZVP scrf=cosmors&#xA;&#xA;peroxide&#xA;&#xA;0 1&#xA;O  -0.22216884 -0.6214829  -0.08709297&#xA;H   0.09625091 -1.07514452  0.69674375&#xA;O   0.22216884  0.6214829  -0.08709297&#xA;H  -0.09625091  1.07514452  0.69674375&#xA;&#xA;h2o2.cosmo&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;This produces the necessary .cosmo file. Note the choice of functional and basis set is important, as COSMOtherm only ships parameter sets for certain combinations. In this case, you need to be sure the geometry is converged at this level of theory to use the BP_TZVP_C30_1701.ctd parameter file. If you can't converge it at that level of theory, you can use the SVP basis set and a different parameter file (BP_SVP_AM1_C30_1701.ctd). &lt;/p&gt;&#xA;&#xA;&lt;p&gt;I don't have access to either of the dedicated COSMO programs, but at least the input for COSMOtherm seems pretty straightforward. In an input file (name.inp), you would at minimum write: &lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;ctd=name.ctd&#xA;#Identifier&#xA;&#xA;f=name.cosmo&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;This would be run using &lt;code&gt;cosmotherm name.inp&lt;/code&gt; from the commandline.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-16T18:28:49.910" LastActivityDate="2020-06-16T18:28:49.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1320" PostTypeId="1" AcceptedAnswerId="1321" CreationDate="2020-06-16T18:32:32.293" Score="18" ViewCount="483" Body="&lt;p&gt;I was wondering if DFT (or specifically, LDA ?) can be exact in the limit of the homogeneous electron gas? In that case, shouldn't the self-interaction error perfectly cancel out? I realise that such a material might not exist, but in theory, is this true?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I am aware that nothing is perfectly exact without accounting for relativity, quantum electrodynamics, quantum gravity, etc. So by &lt;strong&gt;&lt;em&gt;exact&lt;/em&gt;&lt;/strong&gt; I just mean to say that the energy corresponding to this specific Hamiltonian is exact (meaning no self-interaction error):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4APkF.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4APkF.png&quot; alt=&quot;enter image description here&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-06-17T22:33:01.990" LastActivityDate="2021-05-20T01:41:49.020" Title="Can DFT be 'exact' in the limit of the uniform electron gas?" Tags="|density-functional-theory|self-interaction|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1321" PostTypeId="2" ParentId="1320" CreationDate="2020-06-16T20:27:08.487" Score="20" Body="&lt;p&gt;Let us represent the exact exchange-correlation (xc) energy as a sum of an exchange term (x) and a correlation term (c):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;E_{xc} = E_x + E_c~ .&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a uniform electron gas (UEG), we do have an exact expression for the exchange term:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;E_{x} = - \frac{3}{4}\left( \frac{3}{\pi} \right)^{1/3}\int\rho(\mathbf{r})^{4/3}\ \mathrm{d}\mathbf{r}\ ,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but the correlation term is only known in the unphysical &lt;strong&gt;limit of infinitely strong or infinitely weak correlation&lt;/strong&gt;, and for the &lt;strong&gt;spin-unpolarized case&lt;/strong&gt;. In the case of infinitely strong correlation and no spin polarization, we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{3}&#xA;E_{c} = A\ln(r_{s}) + B + C\ln(r_{s})r_{s} + Dr_{s},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in terms of the Wigner-Seitz radius, which I will give here for a 3D gas with a number density of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{4}&#xA;r_s = \left(\frac{3}{4\pi n}\right)^{1/3}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The expressions for &lt;span class=&quot;math-container&quot;&gt;$A,B,C$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; are not simple. For example, here is &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; (from a &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.106.364&quot; rel=&quot;noreferrer&quot;&gt;1956 paper&lt;/a&gt; by Gell-Mann and Brueckner) to second order in the logarithmic divergene and 4th order in perturbation theory:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{5}&#xA;C=\frac{2}{\pi^2}\left(1-\ln 2 \right)\left(\ \ln \left(\frac{256}{9\pi^{4}}  \right)^{1/3} - \frac{1}{2} + \frac{\int R(u)^2\ln R(u)\textrm{d}u}{\int R(u)^2\textrm{d}u } \right) + \delta,\\&#xA;\delta = \frac{3}{8\pi^5}\int\!\!\!\!\int\!\!\!\!\int \frac{\textrm{d}q\textrm{d}^3p_1\textrm{d}^3p_2}{q^2 + \textbf{q}\cdot \left( \textbf{p}_1 + \textbf{p}_2\right)} + \frac{6}{\pi^3}\int\!\!\!\! \int_0^1 \frac{R(u)^2}{q}\textrm{d}q \textrm{d}u.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The integrals area obtained by numerically, so they are not exact, but they can be made exact to within floating-point error if desired.&lt;/p&gt;&#xA;&lt;p&gt;For a spin-polarized UEG, further approximations are made, and for a UEG that is not in the infinitely strong (or infinitely weak) correlation limit, we again have to rely on approximations, such as the following: VWN (Vosko-Wilk-Nusair, 1980), PZ81 (Perdew-Zunger, 1981), CP (Cole-Perdew, 1982), PW92 (Perdew-Wang 1992), Chachiyo (2016).&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;I will now summarize the &lt;em&gt;&lt;strong&gt;current&lt;/strong&gt;&lt;/em&gt; limitations on &amp;quot;exact&amp;quot; xc-energy functionals for a uniform electron gas (UEG). The gas has to be:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;spin-unpolarized&lt;/li&gt;&#xA;&lt;li&gt;in the limit of infinitely strong correlation, or infinitely weak correlation&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Even in these cases, the expressions are not &lt;em&gt;entirely&lt;/em&gt; exact because:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;they involve truncating an expansion for a logarithmic divergence (to second order, in the above example, but I suppose if one &lt;em&gt;really&lt;/em&gt; wanted to, they could keep going until the sum of all remaining terms are deemed to not matter at machine precision),&lt;/li&gt;&#xA;&lt;li&gt;they involve truncating an perturbation theory expansion (to fourth order, in the above example, but machine precision can probably be achieved as in the above point),&lt;/li&gt;&#xA;&lt;li&gt;they involve numerical integrations, which also can in principle be done to within machine precision.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion&lt;/strong&gt;: In theory there exists some &lt;em&gt;&lt;strong&gt;exact&lt;/strong&gt;&lt;/em&gt; functional for the UEG, but until now  &lt;em&gt;&lt;strong&gt;we only know what it is for the special case just described, and even in this special case there are series that have to be truncated to get these formulas, and even after that, there's integrals that need to be done numerically.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-20T01:41:49.020" LastActivityDate="2021-05-20T01:41:49.020" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1322" PostTypeId="1" CreationDate="2020-06-17T16:43:25.963" Score="25" ViewCount="1305" Body="&lt;p&gt;(This question is originally posted on &lt;a href=&quot;https://physics.stackexchange.com/questions/559977/mathematical-expression-of-scan-strongly-constrained-and-appropriately-normed&quot;&gt;physics stackexchange&lt;/a&gt;, but someone suggested me to post on this site, so there you go)&lt;/p&gt;&#xA;&lt;p&gt;I'm compiling the mathematical expression of &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.036402&quot; rel=&quot;noreferrer&quot;&gt;SCAN&lt;/a&gt; (Strongly Constrained and Appropriately Normed) functionals' constraints, but apparently they are not very obvious from their paper (at least for me).&#xA;I have compiled some constraints from the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.036402&quot; rel=&quot;noreferrer&quot;&gt;SCAN paper&lt;/a&gt;, the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.77.3865&quot; rel=&quot;noreferrer&quot;&gt;PBE paper&lt;/a&gt;, and &lt;a href=&quot;http://mcc.illinois.edu/workshops/electronicstructure/2017/talks/ES_2017_Perdew.pdf&quot; rel=&quot;noreferrer&quot;&gt;Perdew's presentation&lt;/a&gt;, but some are missing (see the last line of this question).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;General form&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;E_{xc}[n] &amp;amp;= \int n \varepsilon_x^{unif}(n) F_{xc}(s,\alpha)\ \mathrm{d}\mathbf{r} \\&#xA;E_x[n] &amp;amp;= \int n \varepsilon_x^{unif}(n) F_x(s,\alpha)\ \mathrm{d}\mathbf{r} \\&#xA;E_c[n] &amp;amp;= \int n \varepsilon_x^{unif}(n) F_c(r_s,t,\zeta,\alpha)\ \mathrm{d}\mathbf{r} = \int n\left[\varepsilon_c^{unif} + H(r_s,t,\zeta,\alpha)\right]\ \mathrm{d}\mathbf{r} \\&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_x^{unif}(n) = -(3/4\pi)(3\pi^2n)^{1/3}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_c^{unif}$&lt;/span&gt; are obtained from &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.45.13244&quot; rel=&quot;noreferrer&quot;&gt;Perdew &amp;amp; Wang, 1992&lt;/a&gt; and the variables &lt;span class=&quot;math-container&quot;&gt;$s,\alpha, r_s,t,\zeta$&lt;/span&gt; are listed in SCAN's paper &lt;a href=&quot;https://journals.aps.org/prl/supplemental/10.1103/PhysRevLett.115.036402/SCAN_Sup.pdf&quot; rel=&quot;noreferrer&quot;&gt;supplementary material&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Exchange constraints&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Negativity&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_x(s,\alpha) &amp;gt; 0&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Spin-scaling&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_x[n_{\uparrow}, n_{\downarrow}] = \frac{1}{2}\left(E_x[2n_{\uparrow}] + E_x[2n_{\downarrow}]\right)&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Uniform density scaling&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_x[n_\gamma] = \gamma E_x[n]\mathrm{, where}\ n_\gamma(\mathbf{r}) = \gamma^3 n(\gamma \mathbf{r})&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Fourth order gradient expansion (the expression is from &lt;a href=&quot;http://mcc.illinois.edu/workshops/electronicstructure/2017/talks/ES_2017_Perdew.pdf&quot; rel=&quot;noreferrer&quot;&gt;Perdew's presentation&lt;/a&gt;)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{s\rightarrow 0, \alpha\rightarrow 1} F_x(s,\alpha) =  1 + \frac{10}{81}s^2 - \frac{1606}{18225} s^4 + \frac{511}{13500} s^2(1-\alpha) + \frac{5913}{405000}(1-\alpha)^2&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Non-uniform density scaling&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{s\rightarrow\infty}F_x(s,\alpha) \propto s^{-1/2}&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Tight lower bound for two electron densities&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_x(s,\alpha=0) \leq 1.174&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Correlation constraints&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;7&quot;&gt;&#xA;&lt;li&gt;Non-positivity&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_c(r_s,t,\zeta,\alpha) \geq 0&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Second order gradient expansion&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\lim_{t\rightarrow 0}H(r_s, \zeta, t, \alpha) &amp;amp;= \beta \phi^3  t^2 \\&#xA;\beta &amp;amp;\approx 0.066725&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Rapidly varying limit (using the term from PBE's paper, instead of from SCAN's paper, is it &amp;quot;&lt;em&gt;Uniform density scaling to the low density limit&lt;/em&gt;&amp;quot;?)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{t\rightarrow\infty}H(r_s, \zeta, t, \alpha) = -\varepsilon_c^{unif}&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Uniform density scaling to the high density limit&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;    \lim_{r_s\rightarrow 0}H(r_s, \zeta, t, \alpha) &amp;amp;= \gamma \phi^3\ln \left(t^2\right) \\&#xA;    \gamma &amp;amp;= \frac{1}{\pi} (1 - \ln 2)&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Zero correlation energy for one electron densities&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H(r_s, \zeta=1, t, \alpha=0) = -\varepsilon_c^{unif}&#xA;$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Finite non-uniform scaling limit (&lt;strong&gt;I don't know this&lt;/strong&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Exchange and correlation constraints&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;13&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Size extensivity (&lt;strong&gt;I don't know this&lt;/strong&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;General Lieb-Oxford bound&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{xc}(r_s, \zeta, t, \alpha) \leq 2.215&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Weak dependence upon relative spin polarization in  the low-density limit (&lt;strong&gt;I don't know this&lt;/strong&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Static linear  response of the uniform electron gas (&lt;strong&gt;I don't know this&lt;/strong&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Lieb-Oxford bound for two-electron densities&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{xc}(r_s, \zeta=0, t, \alpha=0) \leq 1.67&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Summary: What are the constraints for 12, 13, 15, 16? If you want, you can give one constraint in one answer.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="882" LastEditorUserId="5" LastEditDate="2022-01-04T00:02:20.953" LastActivityDate="2022-01-11T22:23:13.787" Title="Mathematical expression of SCAN (Strongly Constrained and Appropriately Normed) constraints in DFT" Tags="|density-functional-theory|one-topic-per-answer|from-phys-se|functional|history|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1323" PostTypeId="1" CreationDate="2020-06-17T19:00:26.760" Score="11" ViewCount="1788" Body="&lt;p&gt;Which quantum chemistry programs can compute natural bond orbitals (NBOs)? Which visualisation tools can I use subsequently to plot pictures of the NBOs?&lt;/p&gt;&#xA;" OwnerUserId="115" LastEditorUserId="5" LastEditDate="2020-06-17T19:44:10.340" LastActivityDate="2020-06-18T20:42:41.650" Title="Plotting of natural bond orbitals (NBOs)" Tags="|software|visualization-software|orbitals|" AnswerCount="5" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1324" PostTypeId="2" ParentId="1323" CreationDate="2020-06-17T19:43:11.520" Score="12" Body="&lt;h1&gt;NBO 7.0&lt;/h1&gt;&#xA;&lt;p&gt;The program &lt;a href=&quot;https://nbo6.chem.wisc.edu/index.htm&quot; rel=&quot;noreferrer&quot;&gt;NBO 7.0&lt;/a&gt; seems to be quite well maintained, with version 7.0.9 released fewer than 30 days ago.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://nbo6.chem.wisc.edu/affil_css.htm&quot; rel=&quot;noreferrer&quot;&gt;Has interfaces&lt;/a&gt; to ADF, DEMON2K, FIREFLY/PC-GAMESS, GAMESS(US), GAUSSIAN, JAGUAR/SCHROEDINGER, MOLCAS, MOLPRO, NWChem, ORCA, PQS, Psi4, QChem, SPARTAN, TeraChem, TURBOMOLE.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;At least 2 new releases were issued already in 2020, and at least 2 new releases issued in 2019, so it seems the developers are still active and constantly maintaining the code.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It has existed since 2001, so it is well established (probably not too many bugs).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;They have &lt;a href=&quot;https://nbo6.chem.wisc.edu/v_manual.htm&quot; rel=&quot;noreferrer&quot;&gt;NBOView&lt;/a&gt; for plotting and visualizing. There is also a plug-in for &lt;a href=&quot;https://nbo6.chem.wisc.edu/nbopro_adv.htm&quot; rel=&quot;noreferrer&quot;&gt;visualization with JMol&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;They have a detailed &lt;a href=&quot;https://nbo6.chem.wisc.edu/nboman.pdf&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt; available online.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It doesn't seem to have a presence on GitHub&lt;/li&gt;&#xA;&lt;li&gt;It is not free. The latest version &lt;a href=&quot;https://charge.wisc.edu/chemistry/order_nbo7.aspx&quot; rel=&quot;noreferrer&quot;&gt;seems to cost&lt;/a&gt; 100 USD or 30 USD as a plut-in to FIREFLY/PC-GAMESS.&lt;/li&gt;&#xA;&lt;li&gt;The interfaces to the software above, don't seem to be very up-to-date. For example the website says the MOLCAS interface is only to NBO3.0, not NBO7.0.&lt;/li&gt;&#xA;&lt;li&gt;The website seems old-fashioned.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-17T20:03:56.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1325" PostTypeId="1" CreationDate="2020-06-17T20:26:07.123" Score="6" ViewCount="148" Body="&lt;p&gt;I am interested to compute the conductivity properties of some molecular organic wires in SIESTA.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Since I am new in SIESTA, I would appreciate a guide for beginners to this field.&lt;/p&gt;&#xA;" OwnerUserId="883" LastEditorUserId="5" LastEditDate="2020-06-17T20:43:57.007" LastActivityDate="2020-06-17T21:00:57.310" Title="Conductivity Computations of Molecular Wires" Tags="|density-functional-theory|electronic-structure|molecular-modeling|siesta|transport|" AnswerCount="1" CommentCount="6" ClosedDate="2020-06-23T10:00:21.673" ContentLicense="CC BY-SA 4.0" />
  <row Id="1326" PostTypeId="2" ParentId="1325" CreationDate="2020-06-17T21:00:57.310" Score="2" Body="&lt;p&gt;I strongly suggest that you start from simple calculations instead going directly for transport calculations. Transport calculation in SIESTA are tricky: you have to define the electrodes, the main region,  run optimization calculations for each one, match all of them and finally, do the transport calculation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In the SIESTA page, you can find links for different &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/max-2017-bsc/Talks/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Siesta/TranSiesta School, Barcelona Supercomputing Center, May 23-26, 2017&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/ts-tb-2016-icn2/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TBtrans and TranSiesta Tutorial: Non-Equilibrium Green Functions, from Tight-Binding to Self-Consistency, Barcelona, 9-11 November 2016&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/tlv14/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Siesta/TranSiesta Tutorial, Tel Aviv, September 8-11, 2014&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-17T21:00:57.310" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1327" PostTypeId="2" ParentId="1323" CreationDate="2020-06-17T21:09:15.773" Score="3" Body="&lt;h1&gt;MOPAC&lt;/h1&gt;&#xA;&lt;p&gt;MOPAC (Molecular Orbital PACkage) is a semiempirical quantum chemistry program based on Dewar and Thiel's NDDO approximation.&lt;/p&gt;&#xA;&lt;p&gt;If you qualify for Academic not-for-profit use, request your password &lt;a href=&quot;http://openmopac.net/redirect_download_form.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Using the keyword &lt;em&gt;&lt;a href=&quot;http://openmopac.net/manual/localize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;local&lt;/a&gt;&lt;/em&gt;, you can calculate the localized orbitals are also known as Natural Bond Orbitals or NBO.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-17T21:09:15.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1328" PostTypeId="2" ParentId="1323" CreationDate="2020-06-17T21:14:06.343" Score="6" Body="&lt;h1&gt;Jmol&lt;/h1&gt;&#xA;&lt;p&gt;Jmol is a free, open source viewer of molecular structures useful for students, educators and researchers in chemistry, biochemistry and other fields dealing with molecular structure. It is cross-platform, running on Windows, Mac OS X, and Linux/Unix systems.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Jmol application is a standalone Java application that runs on the desktop.&lt;/li&gt;&#xA;&lt;li&gt;The JSmol is an object that can be integrated into web pages. It does not require Java, since it runs using just the browser's HTML5 and JavaScript engines..&lt;/li&gt;&#xA;&lt;li&gt;The JmolViewer is a development tool kit that can be integrated into other Java applications.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can download it from &lt;a href=&quot;http://jmol.sourceforge.net/download/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2020-06-18T08:37:33.217" LastActivityDate="2020-06-17T21:14:06.343" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1329" PostTypeId="2" ParentId="1322" CreationDate="2020-06-17T22:26:37.927" Score="17" Body="&lt;h2&gt;Constraint #13: Size-Extensivity&lt;/h2&gt;&#xA;&lt;p&gt;While the &lt;a href=&quot;https://en.wikipedia.org/wiki/Size_consistency_and_size_extensivity&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia page for size-consistency and size-extensivity&lt;/a&gt; gives a clear formula for the definition of size-consistency, unfortunately they did not give a definition of size-extensivity, so I had to look deeper into the reference that they provided. They say that size-extensivity was introduced by Bartlett, and they cite &lt;a href=&quot;https://www.annualreviews.org/doi/10.1146/annurev.pc.32.100181.002043&quot; rel=&quot;noreferrer&quot;&gt;this review paper of his from 1981&lt;/a&gt;, but this paper itself credits the following papers, which I have now looked at for the first time and summarized below:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(1955) &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.97.1353&quot; rel=&quot;noreferrer&quot;&gt;Keith Brueckner first recognized&lt;/a&gt; in his study of the uniform electron gas, that some terms in the energy obtained by Rayleigh-Schroedinger perturbation theory, incorrectly do not scale linearly with the number of electrons &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$N\rightarrow \infty $&lt;/span&gt;. He found a way to cancel out all of these spurious terms, up to fourth-order in the perturbation theory. These spurious terms are also the reason why CI (configuration interaction) converges slowly with respect to the number of excitations included. A year later, Brueckner published the paper with Gell-Mann that became the subject of &lt;a href=&quot;https://materials.stackexchange.com/a/1321/5&quot;&gt;my other answer here&lt;/a&gt;. He was one of the all-time greats, and lived to 90.&lt;/li&gt;&#xA;&lt;li&gt;(1957) &lt;a href=&quot;https://royalsocietypublishing.org/doi/10.1098/rspa.1957.0037&quot; rel=&quot;noreferrer&quot;&gt;Jeffrey Golstone proved&lt;/a&gt; the &amp;quot;linked-diagram theorem&amp;quot; which ensures that the spurious terms found by Brueckner, get cancelled out to &lt;em&gt;all&lt;/em&gt; orders in perturbation theory. Goldstone by the way, is one of the most influential physicists that's still alive! He's currently 85 and he was even a co-author on the quite recent paper that popularized Adiabatic Quantum Computing :)&lt;/li&gt;&#xA;&lt;li&gt;(1965) Bartlett's review paper says that Hans Primas was actually the one to first really emphasize this concept of having proper scaling. I don't know much about Primas, though I found that &lt;a href=&quot;https://en.wikipedia.org/wiki/Hans_Primas&quot; rel=&quot;noreferrer&quot;&gt;he survived to the age of 86&lt;/a&gt; :)&lt;/li&gt;&#xA;&lt;li&gt;(1971-1973) Wilfried Meyer used this concept of size-extensivity to justify the CEPA model. At the time, Meyer had just finished making the &lt;a href=&quot;https://materials.stackexchange.com/questions/tagged/molpro&quot;&gt;MOLPRO software&lt;/a&gt; in the 1960s, a software which is now more than 50 years later, maybe the most popular quantum chemistry software for fast high-accuracy calculations.&lt;/li&gt;&#xA;&lt;li&gt;(1978) &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/epdf/10.1002/qua.560140504&quot; rel=&quot;noreferrer&quot;&gt;Bartlett and Purvis used the term&lt;/a&gt;  &amp;quot;size-extensivity&amp;quot; here, so this is perhaps where the term was first introduced, but he uses it to describe what the 1955 and 1957 papers achieved.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;So what is size-extensivity?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;My reading of the above Bartlett papers tells me that &lt;strong&gt;for a homogenous system like an electron gas or a set of non-interacting He atoms, the energy should scale linearly with the number of particles&lt;/strong&gt; and that the concept can also be generalized to properties other than energy.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-29T02:40:33.930" LastActivityDate="2020-06-29T02:40:33.930" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1331" PostTypeId="1" CreationDate="2020-06-17T23:01:05.027" Score="18" ViewCount="587" Body="&lt;p&gt;Regarding the calculation of binding energy of molecular absorption on graphene, for which &lt;a href=&quot;https://materials.stackexchange.com/questions/378/what-are-the-scientific-justifications-of-the-binding-energy-equation&quot;&gt;this&lt;/a&gt; has been discussed before, the process of calculating &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt; is fairly straight forward, i.e., it is the single point energy of the relaxed complex AB. However, the calculation of &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; can be done in two ways: &lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Just extract A and B structures from the optimized structure of AB complex and calculate the single point energy of them. &lt;/p&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Relax the extracted A and B structures (from the optimized AB complex) again and then calculate the single point energy of them.&lt;/p&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Among these two methods, which method is more recommendable to use and why?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2020-06-17T23:14:27.557" LastActivityDate="2020-06-19T11:20:56.113" Title="Calculating binding energy between two systems" Tags="|density-functional-theory|vasp|quantum-espresso|binding-energy|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1332" PostTypeId="1" CreationDate="2020-06-18T08:04:19.493" Score="11" ViewCount="106" Body="&lt;p&gt;I have used Vanderbilt USPP for generating a pseudopotential that does not include the spin-orbit term. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;But I want to have the spin-orbit coupling term included in the pseudopotential, to do research on a van der Waal (VDW) hetero-structure of 2D materials. &lt;/p&gt;&#xA;&#xA;&lt;p&gt;How do I use Vanderbilt USPP to generate a pseudopotential including spin-orbit coupling? I'm working on the Mo atom.&lt;/p&gt;&#xA;" OwnerUserId="749" LastEditorUserId="24" LastEditDate="2020-06-18T10:34:27.233" LastActivityDate="2020-06-18T10:34:27.233" Title="How to generate relativistic pseudo-potential using Vanderbilt USPP that captures spin-orbit coupling?" Tags="|density-functional-theory|pseudopotentials|relativistic|spin-orbit-coupling|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1333" PostTypeId="2" ParentId="1331" CreationDate="2020-06-18T09:06:04.403" Score="12" Body="&lt;p&gt;The binding energy is defined in terms of the relaxed structures: it is the &lt;em&gt;minimum&lt;/em&gt; energy required to disassemble a system of particles into separate parts.&lt;/p&gt;&#xA;&lt;p&gt;Mathematically &lt;span class=&quot;math-container&quot;&gt;$E_{\rm bind} = E(A)+E(B)-E(AB)$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$E(A)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E(B)$&lt;/span&gt; are the energies of subsystems &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$E(AB)$&lt;/span&gt; is the energy of the compound system.&lt;/p&gt;&#xA;&lt;p&gt;Relaxing the structures of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; minimizes &lt;span class=&quot;math-container&quot;&gt;$E_{\rm bind}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-06-18T14:42:46.780" LastActivityDate="2020-06-18T14:42:46.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1334" PostTypeId="2" ParentId="1332" CreationDate="2020-06-18T10:34:03.140" Score="3" Body="&lt;p&gt;The spin-orbit effect is something that your code has to be able to do, it is not a property of the pseudopotential.&lt;/p&gt;&#xA;&lt;p&gt;Here you can find other discussions about it:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://materials.stackexchange.com/questions/308/how-to-incorporate-the-effect-of-spin-orbit-coupling-in-electronic-structure-cal&quot;&gt;How to incorporate the effect of spin-orbit coupling in electronic structure calculation&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://materials.stackexchange.com/questions/1144/spin-orbit-interaction-with-dft&quot;&gt;Spin–orbit interaction with DFT&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-18T10:34:03.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1335" PostTypeId="2" ParentId="1297" CreationDate="2020-06-18T11:37:31.250" Score="2" Body="&lt;p&gt;I really don't know the output structure of Q-Chem, but in SIESTA, we have the following information:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;siesta: Final energy (eV):&#xA;siesta:  Band Struct. =   -6333.862502&#xA;siesta:       Kinetic =   15927.632813&#xA;siesta:       Hartree =   72644.682988&#xA;siesta:       Eldau   =       0.000000&#xA;siesta:       Eso     =       0.000000&#xA;siesta:    Ext. field =       0.000000&#xA;siesta:       Enegf   =       0.000000&#xA;siesta:   Exch.-corr. =   -8639.068902&#xA;siesta:  Ion-electron = -159290.772952&#xA;siesta:       Ion-ion =   54887.144618&#xA;siesta:       Ekinion =       0.000000&#xA;siesta:         Total =  -24470.381434&#xA;siesta:         Fermi =      -3.153387&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, there is information about different types of energy, so, the energy to be used in the PES calculation should be the &lt;strong&gt;Total&lt;/strong&gt; energy, as it is the sum of all contributions.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-18T11:37:31.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1336" PostTypeId="2" ParentId="1322" CreationDate="2020-06-18T13:39:14.927" Score="6" Body="&lt;h2&gt;Constraints #9, #10, #12: Uniform and non-uniform density scaling limit&lt;/h2&gt;&#xA;&lt;p&gt;The uniform density scaling constraint is obtained by substituting the density into &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r}) \rightarrow n_\gamma (\mathbf{r})$&lt;/span&gt; which is defined by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n_\gamma(\mathbf{r}) = \gamma^3 n(\gamma\mathbf{r}).&#xA;$$&lt;/span&gt;&#xA;While the non-uniform density scaling is given as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;n^x_\gamma(x,y,z) &amp;amp;= \gamma n(\gamma x, y, z)\\&#xA;n^{xy}_{\gamma\gamma}(x,y,z) &amp;amp;= \gamma^2 n(\gamma x, \gamma y, z)&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Constraint #9: Uniform density scaling to the low density limit&lt;/h3&gt;&#xA;&lt;p&gt;[SCAN paper 1st paragraph page 3] &amp;quot;&lt;em&gt;It properly scales to ... zero like the exchange energy in the low-density limit&lt;/em&gt;&amp;quot;, so I guess what it says is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{\gamma\rightarrow 0}E_c[n_\gamma] = 0&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Constraint #10: Uniform density scaling to the high density limit&lt;/h3&gt;&#xA;&lt;p&gt;[SCAN paper 1st paragraph page 3] &amp;quot;&lt;em&gt;It properly scales to a finite negative value per electron under uniform density scaling to the high-density limit&lt;/em&gt;&amp;quot; which then cites the reference &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.43.4637&quot; rel=&quot;noreferrer&quot;&gt;Levy, 1990&lt;/a&gt; containing the mathematical expression (i.e. eq. 12),&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{\gamma\rightarrow\infty} E_c[n_\gamma] &amp;gt; -\infty&#xA;$$&lt;/span&gt;&#xA;The expression in the question is the implication of the equation above to make the correlation energy finite at limit &lt;span class=&quot;math-container&quot;&gt;$\gamma\rightarrow\infty$&lt;/span&gt;.&#xA;This is because the correlation energy for uniform electron gas scales with &lt;span class=&quot;math-container&quot;&gt;$\ln(r_s)$&lt;/span&gt; at this limit and can reach &lt;span class=&quot;math-container&quot;&gt;$-\infty$&lt;/span&gt;, therefore &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; should have the factor of &lt;span class=&quot;math-container&quot;&gt;$\ln(t^2)$&lt;/span&gt; to cancel this effect and keep the correlation energy finite at this limit.&lt;/p&gt;&#xA;&lt;h3&gt;Constraint #12: Finite non-uniform scaling limit&lt;/h3&gt;&#xA;&lt;p&gt;[SCAN paper 1st paragraph on page 3] &amp;quot;&lt;em&gt;Its correlation energy per electron is properly finite (but improperly zero) under nonuniform density scaling to the true two-dimensional limit&lt;/em&gt;&amp;quot;, referencing &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.43.4637&quot; rel=&quot;noreferrer&quot;&gt;Levy, 1990&lt;/a&gt; which contains in eq. 30 &amp;amp; 31:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\lim_{\gamma\rightarrow\infty}\gamma^{-1} E_c[n_{\gamma\gamma}^{xy}] &amp;amp;&amp;gt; -\infty \\&#xA;\lim_{\gamma\rightarrow 0}E_c[n_{\gamma}^x] &amp;amp;&amp;gt; -\infty&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="882" LastEditorUserId="882" LastEditDate="2020-06-18T14:12:35.600" LastActivityDate="2020-06-18T14:12:35.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1337" PostTypeId="2" ParentId="871" CreationDate="2020-06-18T13:39:41.047" Score="3" Body="&lt;p&gt;A good way to proceed is to use a control in your experiment as with modelling experiment in general.&#xA;You can, for example, use the co-crystalized ligand or a well-know inhibitor (something experimentally established with IC50 value for example) of your protein of interest. The values obtained with that ligand in your docking/MMGBSA calculations will serve as guide for comparison...&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2020-06-18T13:39:41.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1338" PostTypeId="1" CreationDate="2020-06-18T13:43:49.510" Score="8" ViewCount="352" Body="&lt;p&gt;Is it useful to energy minimize a docked pose before scoring it? I am speaking in the context of protein-ligand systems.&#xA;Does the energy obtained after minimization correlate better with experimental affinity?&lt;br /&gt;&#xA;Does someone have some published literature on that?&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2020-06-18T15:26:06.433" Title="Docked pose and energy minimization" Tags="|binding-energy|docking|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1339" PostTypeId="2" ParentId="1338" CreationDate="2020-06-18T14:13:11.353" Score="6" Body="&lt;p&gt;One  way these calculations are performed is using MD and implicit solvent calculations. The general procedure for these simulations are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Perform simulations and get frames&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Perform implicit solvent calculations on the complex, receptor, and ligand&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate docking energy from the three individual components&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Generally there is not an additional minimization that is performed as it could bias the sampling to a particular energy well. This would mean you could lose out on valuable information, such as why a pose is not favorable.&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-06-18T14:13:11.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1340" PostTypeId="2" ParentId="1322" CreationDate="2020-06-18T14:26:14.190" Score="1" Body="&lt;h2&gt;Constraint #15: Weak dependence upon relative spin polarization in  the low-density limit&lt;/h2&gt;&#xA;&lt;p&gt;[SCAN paper 2nd paragraph page 3] &amp;quot;&lt;em&gt;... in the low-density limit, where our &lt;span class=&quot;math-container&quot;&gt;$F_{xc}$&lt;/span&gt; properly shows a weak dependence on relative spin polarization&lt;/em&gt;&amp;quot;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lim_{r_s\rightarrow \infty} F_{xc}(r_s, \zeta_1, t, \alpha) \approx \lim_{r_s\rightarrow \infty} F_{xc}(r_s, \zeta_2, t, \alpha)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="882" LastActivityDate="2020-06-18T14:26:14.190" CommentCount="6" CommunityOwnedDate="2022-01-04T00:23:16.320" ContentLicense="CC BY-SA 4.0" />
  <row Id="1341" PostTypeId="1" AcceptedAnswerId="1345" CreationDate="2020-06-18T15:22:17.277" Score="12" ViewCount="436" Body="&lt;p&gt;I am working on modelling of a material that has partial/mixed site occupancies. For example consider the tetragonal (&lt;em&gt;P4mm&lt;/em&gt;) compound &lt;span class=&quot;math-container&quot;&gt;$\ce{(Ba_{0.67}Sr_{0.33})TiO3}$&lt;/span&gt;. Following is the atomic arrangement (visualised in VESTA) when looked along the &lt;em&gt;Z&lt;/em&gt; axis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x6tU6.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x6tU6.png&quot; alt=&quot;BST67&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;One of the ways to model such structures is to create a supercell. In this specific case a 3x1x1 supercell is sufficient. There could be many 3x1x1 supercell configurations, here is one of them with periodic boundary conditions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8fh2N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8fh2N.png&quot; alt=&quot;BST67 supercell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So my question is, does the atom arrangement in the real compound &lt;span class=&quot;math-container&quot;&gt;$\ce{(Ba_{0.67}Sr_{0.33})TiO3}$&lt;/span&gt; look something like this. If it does; after the structural relaxations the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ba}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Sr}$&lt;/span&gt; atoms (or &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; atoms) relax at slightly different x/y-coordinates. How do we merge such structures back to a single unit cell as shown in the first figure?&lt;/p&gt;&#xA;&lt;p&gt;Or could there be vacancies at the A-site keeping the ratio &lt;span class=&quot;math-container&quot;&gt;$\ce{Ba:Sr}$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$\ce{2:1}$&lt;/span&gt;. Or is it too complex to describe theoretically?&lt;/p&gt;&#xA;&lt;p&gt;I would greatly appreciate relevant references as well.&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-06-18T16:50:50.987" Title="How does the atomic arrangement look like in a compound that has partial/mixed site occupancies" Tags="|density-functional-theory|reference-request|crystal-structure|" AnswerCount="1" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1342" PostTypeId="2" ParentId="1338" CreationDate="2020-06-18T15:26:06.433" Score="2" Body="&lt;p&gt;Absolutely not.&lt;/p&gt;&#xA;&lt;p&gt;You only need that your input structure geometry is ok (no atomic clash, all valence ok, etc ).&lt;/p&gt;&#xA;&lt;p&gt;Using DFT or Molecular Dynamics to optimize the geometry pre docking is a waste of time.&lt;/p&gt;&#xA;&lt;p&gt;The justification to that is that every docking software will generate/search for a population of conformers, so, each conformer will be out of optimal geometry.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-18T15:26:06.433" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1343" PostTypeId="2" ParentId="1323" CreationDate="2020-06-18T15:46:45.160" Score="9" Body="&lt;h1&gt;Q-Chem + Jmol&lt;/h1&gt;&#xA;&lt;p&gt;The combination of Q-Chem and Jmol seems to work well (but is not yet well documented).&lt;/p&gt;&#xA;&lt;h2&gt;Q-Chem&lt;/h2&gt;&#xA;&lt;p&gt;In the Q-Chem input file one has to put&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;span class=&quot;math-container&quot;&gt;$rem&#xA;...&#xA;nbo    = 1&#xA;$&lt;/span&gt;end&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$nbo&#xA;PLOT&#xA;$&lt;/span&gt;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This calls the NBO program and writes out the information of interest to the files &lt;code&gt;$QCSCRATCH/FILE.[31-39]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;h2&gt;NBO&lt;/h2&gt;&#xA;&lt;p&gt;The content of the files written is&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.31&lt;/code&gt; Basis set information&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.32&lt;/code&gt; PNAOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.33&lt;/code&gt; NAOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.34&lt;/code&gt; PNHOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.35&lt;/code&gt; NHOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.36&lt;/code&gt; PNBOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.37&lt;/code&gt; NBOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.38&lt;/code&gt; PNLMOs in the AO basis&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;FILE.39&lt;/code&gt; NLMOs in the AO basis&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here, the letter P corresponds to the pre-orthogonal orbitals, which are suggested for visualisation (&lt;a href=&quot;https://dx.doi.org/10.1002/wcms.51&quot; rel=&quot;noreferrer&quot;&gt;WIREs, 2012, 2, 1&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h2&gt;Jmol&lt;/h2&gt;&#xA;&lt;p&gt;In Jmol, one can just open the file of interest. In the first instance this may be the pre-NBOs as contained in &lt;code&gt;FILE.36&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To automate the plotting of orbitals, one may use the &lt;code&gt;jmol_MOs.py&lt;/code&gt; wrapper supplied with &lt;a href=&quot;http://theodore-qc.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;TheoDORE&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="115" LastEditorUserId="115" LastEditDate="2020-06-18T15:57:33.100" LastActivityDate="2020-06-18T15:57:33.100" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1344" PostTypeId="2" ParentId="1331" CreationDate="2020-06-18T16:36:38.473" Score="10" Body="&lt;p&gt;As Susi notes, the rearrangements of the &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{B}$&lt;/span&gt;  fragments are a part of the binding process, and so it is natural to include this &amp;quot;rearrangement energy&amp;quot; into the overall binding energy. Starting with the fragments in the complex geometry would artificially increase the binding energy, as it would destabilize the initial fragments. So your second process is only one that gives the true binding energy.&lt;/p&gt;&#xA;&lt;p&gt;However, if you were interested in determining the &amp;quot;strength&amp;quot; of the binding site between &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{B}$&lt;/span&gt; rather than the energy of the overall binding process, you could use your first procedure. This quantity would be more useful if your goal was to determine how large a perturbation (e.g. temperature, energy of a photon) would be needed to cause dissociation. Regardless of the overall favorability of the unbinding process, the complex will need sufficient energy to overcome this barrier.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-19T11:20:56.113" LastActivityDate="2020-06-19T11:20:56.113" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1345" PostTypeId="2" ParentId="1341" CreationDate="2020-06-18T16:50:50.987" Score="11" Body="&lt;p&gt;When you get an experimental structure file that has partial occupations, as in your first figure, this implies that the occupations of the site do not have a periodic order (they are randomly occupied with probabilities determined by the occupation fractions of each ion). Otherwise, the ordering would be reflected in the symmetry of the unit cell, requiring it to be larger. Compare to something like the double perovskite &lt;span class=&quot;math-container&quot;&gt;$\textrm{PrBaCo}_{2}\textrm{O}_{6}$&lt;/span&gt;. The unit cell parameters in the partial occupations case reflect an average of the volume of material measured during the experiment.&lt;/p&gt;&#xA;&lt;p&gt;So to answer your first question: if there is no ordering in the real compounds, then no, your cell does not reflect the real material. When you go to your DFT cell, because the size of the cell is limited for computational reasons, you are necessarily introducing some periodic ordering to the A-site cations which may not be realistic. The distortions around the Sr that you mentioned prevent you from collapsing the unit cell down to an effective ABO3 perovskite structure.&lt;/p&gt;&#xA;&lt;p&gt;You can try to approximate the experimental structure using methods such as the special quasi-random structures (SQS) approach, where you generate a supercell with atomic arrangements that result in nearest-neighbor distributions that mimic those of a random structure. How well this works depends on whether you can use a sufficiently large cell. I have seen in the literature that when you are limited in the size of the cell you can accommodate, some researchers take several permutations of ionic ordering in the biggest cell they can manage, and take averages of the quantities of interest.&lt;/p&gt;&#xA;&lt;p&gt;I think there are other ways of approximating alloys and doped compounds, but since I'm not as familiar with them I'll leave it for others to answer.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-06-18T16:50:50.987" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1346" PostTypeId="2" ParentId="1323" CreationDate="2020-06-18T20:35:26.883" Score="10" Body="&lt;h1&gt;ADF&lt;/h1&gt;&#xA;&lt;p&gt;With the Amsterdam Modeling Suite you can calculate (ADF, DFTB) and plot NBOs in the graphical user interface within the same package.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.scm.com/doc/Tutorials/ADF/NMR_analysis_with_NLMO_and_NBO.html#nmr-analysis-with-nlmo-and-nbo&quot; rel=&quot;noreferrer&quot;&gt;Here's an example applied to NMR analysis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.scm.com/doc/Tutorials/Advanced/ADF_insight_tutorial_TDDFT_NBO.html&quot; rel=&quot;noreferrer&quot;&gt;Here's one applied to TDDFT UV/VIS, including NTOs and NBOs&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.scm.com/doc//Tutorials/ADF/QTAIM.html#benzene-qtaim-charge-analysis-and-nbos&quot; rel=&quot;noreferrer&quot;&gt;Here's one on NBO and other analysis / visualization (QTAIM)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You are welcome to have a &lt;a href=&quot;https://www.scm.com/free-trial&quot; rel=&quot;noreferrer&quot;&gt;Free Trial&lt;/a&gt;!&lt;/p&gt;&#xA;" OwnerUserId="468" LastEditorUserId="5" LastEditDate="2020-06-18T20:42:41.650" LastActivityDate="2020-06-18T20:42:41.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1347" PostTypeId="1" CreationDate="2020-06-18T21:08:29.777" Score="14" ViewCount="398" Body="&lt;p&gt;I am looking for a free software able to draw 3d micelle configuration like the figure attached.&lt;/p&gt;&#xA;&lt;p&gt;Any suggestion?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5pW0n.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5pW0n.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="890" LastEditorUserId="5" LastEditDate="2020-06-19T01:04:43.230" LastActivityDate="2020-07-04T00:04:57.217" Title="Software to draw 3d micelle configuration" Tags="|software|from-chem-se|visualization-software|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1348" PostTypeId="2" ParentId="1347" CreationDate="2020-06-18T22:45:28.610" Score="9" Body="&lt;p&gt;I found some software that can do this kind of work:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Rhino3d&lt;/li&gt;&#xA;&lt;li&gt;3ds Max&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="890" LastEditorUserId="5" LastEditDate="2020-07-04T00:04:57.217" LastActivityDate="2020-07-04T00:04:57.217" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1349" PostTypeId="2" ParentId="1025" CreationDate="2020-06-19T06:42:59.533" Score="8" Body="&lt;p&gt;BDEs are calculated by the below procedure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate initial energy&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Perform homolytic bond cleavage and separate fragments&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate energies of the fragments, add the energies together&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate BDE by comparing the fragment energies to the initial energy&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The level of theory and basis set is dependent on how accurate you want the results to be. B3LYP 6-311++G** is typically a good compromise between accuracy and speed for this system size.&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-06-19T06:42:59.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1350" PostTypeId="1" CreationDate="2020-06-19T16:28:02.893" Score="15" ViewCount="109" Body="&lt;p&gt;When looking at the structure of protein domains I notice many of them show a cleft-like structure in the same location (when aligned to each other). &lt;em&gt;&lt;strong&gt;What is a recommended way of characterizing these clefts?&lt;/strong&gt;&lt;/em&gt; Maybe some curvature measure? I want then to relate them with electrostatic potential so that I can correlate these clefts with some charge or electrostatic potential. Here I'm attaching an example of what I mean:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;                              &lt;img src=&quot;https://i.stack.imgur.com/Cc5ns.png&quot; alt=&quot;centered image&quot; /&gt;&#xA;&lt;/pre&gt;&#xA;" OwnerUserId="484" LastEditorUserId="5" LastEditDate="2020-06-19T17:24:59.053" LastActivityDate="2020-07-03T18:38:23.510" Title="How to characterize surface features in proteins?" Tags="|structure|biomaterials|proteins|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1352" PostTypeId="2" ParentId="1025" CreationDate="2020-06-19T20:32:14.060" Score="11" Body="&lt;h2&gt;Multi-reference or single-reference?&lt;/h2&gt;&#xA;&lt;p&gt;While it is appreciated that &lt;em&gt;&lt;strong&gt;near&lt;/strong&gt;&lt;/em&gt; dissociation there will be a near-degeneracy of orbitals, requiring a multi-reference treatment, fortunately we don't have to worry about this when calculating dissociation energies. For example, the N&lt;span class=&quot;math-container&quot;&gt;$_2%$&lt;/span&gt; molecule has profound multi-reference character as you approach the dissociation limit, which is why single-reference methods like CCSD(T) would fail miserably in calculating the &lt;em&gt;&lt;strong&gt;potential energy curve.&lt;/strong&gt;&lt;/em&gt; However you do not need the potential energy curve here, you just need a good energy of the overall molecule at its &lt;em&gt;single-reference&lt;/em&gt; equilibrium, and an &amp;quot;equally good&amp;quot; energy (hopefully with good error cancellation) for the &lt;em&gt;single-reference&lt;/em&gt; fragments after dissociation. &lt;strong&gt;Single-reference methods tend to describe such small aryl and alkyl phosphonates quite well at equilibrium.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Should you use DFT?&lt;/h2&gt;&#xA;&lt;p&gt;DFT (every single flavor) is notorious for giving bad results for computations outside of what the functional was optimized for. B3LYP can be used as a black-box, and is cheaper than most wavefunction based methods, but B3LYP is not likely going to calculate a dissociation energy correctly to within about 3 kcal/mol (see the figure &lt;a href=&quot;https://materials.stackexchange.com/a/1132/5&quot;&gt;here&lt;/a&gt;). If your dissociation energies are just a few kcal/mol, then your noise will be roughly the same size as your signal, and there's no easy way to systematically improve a B3LYP energy. For these reasons, if the system has only dozens of atoms, I would recommend wavefunction based methods, and I would resort to DFT for something like this only when reaching 100s of atoms.&lt;/p&gt;&#xA;&lt;p&gt;I asked a few times in the comments how many atoms we're dealing with, and after that all I have available to work with is that we have at most some (aryl)&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;P-BH&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; which has about 30 atoms if aryl=phenyl and about 40 atoms if aryl=naphthyl, and about 100 atoms if the aryl group is derived from heptacene. &lt;strong&gt;On the largest end of this spectrum, local-correlation wavefunction methods are still within reach, and on the lower end of this spectrum it is not too challenging to do without local-correlation techniques (meaning calculations would be even more black-box and more accurate).&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;What wavefunction based method should you use?&lt;/h2&gt;&#xA;&lt;p&gt;CCSD(T) is the ultimate &amp;quot;gold standard&amp;quot;, &lt;strong&gt;black-box&lt;/strong&gt;, method for molecules where it would not be too costly (such as your aryl phosphonates with only a few dozen atoms). You can even use the cc-pVDZ basis set without too big of a challenge, and your CCSD(T) calculations will &lt;em&gt;greatly&lt;/em&gt; benefit from error cancellation (the coupled-cluster and cc-pVDZ errors for the total bound molecule and for the fragments, will both have similar sources of error, which will be &lt;em&gt;eliminated&lt;/em&gt; when calculating the energy difference, resulting in dissociation energies that are much more accurate than you would otherwise imagine possible).&lt;/p&gt;&#xA;&lt;p&gt;Local-correlation coupled-cluster type techniques can be used if you need to deal with 100s of atoms:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;DLPNO-CCSD(T)&lt;/strong&gt; in ORCA might be the most famous, but compared to compared to the options I will give next, ORCA is extremely slow and less black-box in my opinion.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;PNO-LCCSD(T)&lt;/strong&gt; in MOLPRO is essentially the same type of thing but more accurate, and much faster (and you might agree that MOLPRO is easier to use). This is only in MOLPRO 2019 and later though (and MOLPRO is not free).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;LNO-CCSD(T)&lt;/strong&gt; in MRCC is essentially the same type of thing again, but might be the best option because:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;MRCC is free&lt;/strong&gt; (unlike MOLPRO).&lt;/li&gt;&#xA;&lt;li&gt;MRCC is very well-maintained (with frequent new releases, the latest being in 2020).&lt;/li&gt;&#xA;&lt;li&gt;MRCC is much easier to use (in my experience) than ORCA, and often even MOLPRO.&lt;/li&gt;&#xA;&lt;li&gt;The LNO-CCSD(T) method in MRCC is extremely well implemented: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00511&quot; rel=&quot;nofollow noreferrer&quot;&gt;It's been used with a QZ basis set for a system with 1023 atoms and 44,712 AOs&lt;/a&gt;. I think it's unlikely for other free programs to compete in both accuracy, speed, and ease-of-use.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-26T16:05:24.827" LastActivityDate="2020-06-26T16:05:24.827" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1353" PostTypeId="2" ParentId="779" CreationDate="2020-06-19T21:38:55.303" Score="7" Body="&lt;p&gt;To tether a set of atoms (index or fragment) in pDynamo, the below lines are needed (energy model can vary):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tethers = pM.SoftConstraintContainer ()&#xA;system.DefineSoftConstraints ( tethers )&#xA;&#xA;reference         = Clone ( system.coordinates3 )&#xA;tetherEnergyModel = SoftConstraintEnergyModelHarmonic ( 0.1 , 500.0 )&#xA;&#xA;NAME1 = &amp;quot;IronOH&amp;quot;&#xA;sele1          = Selection.FromIterable ( range(5024,5027) )&#xA;tethers[NAME1] = SoftConstraintMultipleTether ( sele1 , reference , tetherEnergyModel )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This particular constraint tethers the atoms in range 5024-5027 to 0.1 Å from the reference with a force constant of 500.0 kJ/mol.&lt;/p&gt;&#xA;&lt;p&gt;To have multiple ranges the below can be used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sele = Selection.FromIterable ( range(0,2878) + range(2896,3191) )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-06-19T21:38:55.303" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1354" PostTypeId="1" AcceptedAnswerId="1357" CreationDate="2020-06-19T23:06:36.213" Score="20" ViewCount="1213" Body="&lt;p&gt;I've found a page dedicated to quantum chemistry packages benchmarks, on GitHub, &lt;a href=&quot;https://github.com/PedroJSilva/qmspeedtest&quot; rel=&quot;noreferrer&quot;&gt;qmspeedtest&lt;/a&gt;. But most results there are several years old, and so probably outdated. Is there some place where we can find comparisons like these, but updated often, or at least more recently?&lt;/p&gt;&#xA;&lt;p&gt;I specified quantum chemistry in the question because I'm more interested in molecular systems, modeled with atom-centered gaussian function basis sets, for example. I have almost no familiarity with software that deals with periodic systems, plane-wave based. But I think it could be a good idea if someone with more familiarity with periodic systems opened a similar question for the respective packages.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-06-20T00:43:16.747" LastActivityDate="2020-10-22T22:11:46.903" Title="Is there a set of updated, comprehensive benchmarks for speed comparison between different quantum chemistry packages?" Tags="|software|molecular-modeling|high-performance-computing|quantum-chemistry|databases|" AnswerCount="4" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1355" PostTypeId="1" AcceptedAnswerId="1356" CreationDate="2020-06-20T01:27:14.010" Score="81" ViewCount="15473" Body="&lt;p&gt;Some time ago I've read this news article, &lt;a href=&quot;https://www.quantamagazine.org/mathematicians-discover-the-perfect-way-to-multiply-20190411/&quot; rel=&quot;noreferrer&quot;&gt;Mathematicians Discover the Perfect Way to Multiply&lt;/a&gt;, reporting a discovery published in 2019, where  Harvey and Hoeven[1] found a algorithm able to execute multiplication in &lt;span class=&quot;math-container&quot;&gt;$N \log N$&lt;/span&gt; steps. Compare with the &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; we are used to while doing multiplication by hand.&lt;/p&gt;&#xA;&lt;p&gt;That amused me, because I had no idea in Mathematics there was still open problems in basic arithmetic, something I took for granted, long ago settled knowledge, since childhood.&lt;/p&gt;&#xA;&lt;p&gt;Now I wonder, did this discovery help, or could help, materials modeling? Did a code developed somewhere for this purpose made use of it. A downside of the new algorithm is a set up phase where you need to put the numbers in a suitable form, so this initial effort is paid only for large numbers. My impression is that in matter modeling our algorithms are more about multiplying lots of small numbers fast, instead of some big numbers, so I guess the answer is probably no. But I'm not sure.&lt;/p&gt;&#xA;&lt;p&gt;If not, can someone explain in detail the impact of &lt;em&gt;any&lt;/em&gt; of the multiplication algorithms scaling better than &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt;, for some practical application?&lt;/p&gt;&#xA;&lt;p&gt;[1] David Harvey, Joris van der Hoeven. Integer multiplication in time O(n log n). 2019. &lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-02070778&quot; rel=&quot;noreferrer&quot;&gt;⟨hal-02070778⟩&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-06-22T03:04:01.773" LastActivityDate="2020-11-29T15:58:27.373" Title="Did the 2019 discovery of O(N log(N)) multiplication have a practical outcome?" Tags="|software|high-performance-computing|mathematical-modeling|history|algorithms|" AnswerCount="6" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1356" PostTypeId="2" ParentId="1355" CreationDate="2020-06-20T04:27:21.277" Score="85" Body="&lt;h1&gt;What are the state-of-the-art algorithms for long-integer multiplication?&lt;/h1&gt;&#xA;&lt;p&gt;First let me address the point you raised about the schoolbook algorithm having &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n^2)$&lt;/span&gt; scaling, by saying that this was not the state-of-the-art algorithm used in most matter modeling software. Below I give a brief overview:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(1960) Karatsuba multiplication. &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n^{1.58})$&lt;/span&gt;:&lt;/strong&gt; Faster than naive multiplication after &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; gets ~&lt;span class=&quot;math-container&quot;&gt;$10^{96}$&lt;/span&gt;.&lt;br&gt;&#xA;&lt;strong&gt;(1963-2005) Toom-Cook-Knuth. &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\cdot 2^{\sqrt{2\log n}}\log n)$&lt;/span&gt;:&lt;/strong&gt; Generalization of Karatsuba.&lt;br&gt;&#xA;&lt;strong&gt;(1971) Schönhage-Strassen. &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\log\log n)$&lt;/span&gt;:&lt;/strong&gt; Outperforms TCK after ~&lt;span class=&quot;math-container&quot;&gt;$10^{10000}$&lt;/span&gt;.&lt;br&gt;&#xA;&lt;strong&gt;(2007) &lt;strong&gt;Fürer.&lt;/strong&gt;  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{\mathcal{O}(\log^*n)})$&lt;/span&gt;:&lt;/strong&gt; Outperforms SS after ~&lt;span class=&quot;math-container&quot;&gt;$10^{10^{18}}$&lt;/span&gt;.&lt;br&gt;&#xA;&lt;strong&gt;(2015) &lt;strong&gt;Harvey &lt;em&gt;et al&lt;/em&gt;.&lt;/strong&gt;  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{3\log^*n})$&lt;/span&gt;:&lt;/strong&gt; Similar to Fürer's algorithm.&lt;br&gt;&#xA;&lt;strong&gt;(2015) &lt;strong&gt;Harvey &lt;em&gt;et al&lt;/em&gt;.&lt;/strong&gt;  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{2\log^*n})$&lt;/span&gt;:&lt;/strong&gt; Relies on conjectures not yet proven.&lt;br&gt;&#xA;&lt;strong&gt;(2016) Covanov-Thomé.  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{2\log^*n})$&lt;/span&gt;:&lt;/strong&gt; Relies on (different) conjectures not yet proven.&lt;br&gt;&#xA;&lt;strong&gt;(2018) Harvey &amp;amp; van der Hoeven.  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{2\log^*n})$&lt;/span&gt;:&lt;/strong&gt; Finally proven without conjectures.&lt;br&gt;&#xA;&lt;strong&gt;(2019) Harvey &amp;amp; van der Hoeven.  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n)$&lt;/span&gt;:&lt;/strong&gt; The algorithm mentioned in the paper you cited.&lt;/p&gt;&#xA;&lt;hr&gt;&lt;br&gt;&#xA;&lt;h1&gt;Which of these algorithms have practical consequences?&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Schönhage-Strassen&lt;/strong&gt;: &lt;a href=&quot;https://en.wikipedia.org/wiki/GNU_Multiple_Precision_Arithmetic_Library&quot; rel=&quot;noreferrer&quot;&gt;GNU multi-precision library&lt;/a&gt; uses it for #s with 33,000 to 150,000 digits.&lt;br&gt;&#xA;&lt;strong&gt;Toom-Cook&lt;/strong&gt;: is used for intermediate-sized numbers, basically until Schönhage-Strassen is used.&lt;br&gt;&#xA;&lt;strong&gt;Karatsuba&lt;/strong&gt;: is a specific case of Toom-Cook: not likely used for numbers smaller than &lt;span class=&quot;math-container&quot;&gt;$10^{96}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;hr&gt;&lt;br&gt;&#xA;&lt;h1&gt;So what are the consequences of the 2019 algorithm?&lt;/h1&gt;&#xA;&lt;p&gt;Likely nothing for the calculations we typically do. Schönhage and Strassen predicted very long ago that &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n)$&lt;/span&gt; would be the most efficient possible algorithm from a computational complexity point of view, and in 2019 the algorithm that achieves this predicted &amp;quot;lower bound&amp;quot; was found by Harvey and van der Hoeven. It is probably not implemented in any library, just as the 2018, 2016, 2015, and 2007 algorithms are also not implemented anywhere as far as I know. They are all beautiful mathematics papers which give theoretical scalings, but likely have no practical consequences.&lt;/p&gt;&#xA;&lt;p&gt;Do you ever multiply together integers with 96 digits? Typically in double-precision floating point arithmetic we multiply numbers with no more than 18 digits, and in quadruple-precision arithmetic (which is indeed used in matter modeling for things like numerical derivatives in variational energy calculations, but quite rarely) numbers have up to 36 digits, but it is unlikely that anyone in matter modeling is frequently multiplying numbers with 96 digits, so even the Karatsuba algorithm is in practice worse than the schoolbook &lt;span class=&quot;math-container&quot;&gt;$n^2$&lt;/span&gt; algorithm, due to Karatsuba involving extra shifts and additions as overhead. The Toom-Cook algorithms (such as Karatsuba) are useful in number theory, and in fact &lt;em&gt;we use them every day when we do e-banking or when we use GitHub involving RSA keys&lt;/em&gt;, since RSA numbers are hundreds or thousands of digits long. The Schönhage-Strassen is used mainly in number theory for things like calculating record numbers of digits in &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;, and for practical applications such as multiplying polynomials with huge coefficients.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; The 2019 algorithm for integer multiplication does not affect real-world applications.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-20T15:37:09.170" LastActivityDate="2020-06-20T15:37:09.170" CommentCount="24" ContentLicense="CC BY-SA 4.0" />
  <row Id="1357" PostTypeId="2" ParentId="1354" CreationDate="2020-06-20T09:06:15.387" Score="21" Body="&lt;p&gt;The problem is that this is a highly volatile question. In order to meaningfully benchmark programs, you have to use the exact same compiler flags (may require heavy hacking) and use the same algorithms and parameters (accuracy, cutoffs, quadrature grids, etc). But, if a program supports many kinds of algorithms, then each of them would have to be benchmarked. In contrast, qmspeedtest is  comparing apples to oranges; it is making no effort to actually ensure that the core algorithms and parameters are the same. It is for good reason that some programs explicitly ban publishing benchmark comparisons.&lt;/p&gt;&#xA;&lt;p&gt;If you still intend to proceed, a good benchmark should look at these two core questions first:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;speed of a single Fock build i.e. how quickly do you get a single-point energy from a given density&lt;/li&gt;&#xA;&lt;li&gt;speed of gradient evaluation i.e. how quickly do you evaluate forces from a converged wave function&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These are well-posed problems which are reproducible and where there is a single meaningful answer. This also means that the energy and Fock matrix / the nuclear gradient you get out from the benchmarks should agree numerically exactly between different codes. (You still do have several choices in the way to evaluate the final solution, e.g. density fitting, Cholesky decomposition, fast multipoles, etc, which may give different answers!)&lt;/p&gt;&#xA;&lt;p&gt;Now, running a full calculation also depends on these issues:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;cycles taken until SCF convergence i.e. how good is the default SCF guess and the default convergence accelerator for the system you're looking at&lt;/li&gt;&#xA;&lt;li&gt;steps taken until geometry optimization converges i.e. how sophisticated is the geometry optimizer (use of internal coordinates? empirical force constants / exact second derivatives?)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;While the first two issues, which are purely a question of speed, are somewhat important in practical applications, it is actually the latter two issues that in many cases are the most important for a workflow. If you're studying challenging molecules, you may face cases of poor SCF convergence, and this is where a flexible algorithm makes all the difference. You shouldn't care if program A solves an easy molecule in 5 steps while program B takes 7 steps to solve it, if for a challenging case program A takes 3000 steps but program B only 40. But, these issues are highly system dependent, and depend heavily on the algorithm. Using a second-order algorithm (e.g. trust region) yields more robust convergence, but even though the calculation now may converge in few steps they are much more expensive than with a simple gradient descent method; this is why you should compare apples to apples and use the exact same algorithms in all programs, and study a large variety of systems to try to cover a large sample of both &amp;quot;easy&amp;quot; and &amp;quot;difficult&amp;quot; cases.&lt;/p&gt;&#xA;&lt;p&gt;I would note last that speed is not everything. Also the ease of use of the program and its general availability are key questions in determining which tool to use. If program A is 3x faster than program B, but B is easier/safer to use, most people would opt for program B.&lt;/p&gt;&#xA;&lt;p&gt;Programs have also become more modular than before; this may also affect your choice: if it's easy to modify one program to do exactly what you want, it becomes your tool of choice even if it's not as fast as its competitors.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-06-21T07:03:58.787" LastActivityDate="2020-06-21T07:03:58.787" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1358" PostTypeId="2" ParentId="534" CreationDate="2020-06-21T01:17:46.503" Score="9" Body="&lt;h2&gt;Realizing this Hamiltonian in a natural material&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I cannot imagine a material in which all nearest-neighbor spin-spin interactions can be adjusted arbitrarily at the same time. Spin-spin couplings that are stronger when the spins are closer together, and weaker when the spins are farther apart, can be adjusted by moving the spins relative to each other; so if we have a 2D sheet of spins and we pull it from all four corners, all the spin-spin distances will get larger, and in that sense we might have &lt;span class=&quot;math-container&quot;&gt;$J_{ij}(t) = J_{ij}/t$&lt;/span&gt;, meaning that the coupling potential decreases linear as we do the stretching. &lt;em&gt;But not only will the couplings of the nearest neighbors be affected, but &lt;strong&gt;all&lt;/strong&gt; couplings will, since all distances change.&lt;/em&gt; There would also not be much control over the functions &lt;span class=&quot;math-container&quot;&gt;$J_{ij}(t)$&lt;/span&gt;. Perhaps we would have to change the couplings without changing relative distances, but in some other way, such as with a laser, but I don't know how this would happen (an NMR expert might).&lt;/li&gt;&#xA;&lt;li&gt;Any Hamiltonian with only Pauli operators is quite an approximation of real-world materials existing in nature. The electronic Hamiltonian of a material does not really resemble this Hamiltonian, but the nuclear Hamiltonian used in NMR studies might resemble it more closely (if spin-orbit coupling and other types of terms can be ignored, and &lt;em&gt;if the nuclear spins indeed are &lt;span class=&quot;math-container&quot;&gt;$\pm 1/2$&lt;/span&gt; like in the case of hydrogen atoms&lt;/em&gt;). Hopefully an NMR expert can give a better answer here.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;h2&gt;Realizing this Hamiltonian in an artificial material&lt;/h2&gt;&#xA;&lt;p&gt;Apart from the example in the paper you gave, the closest example I know is from a &lt;a href=&quot;https://journals.aps.org/prapplied/abstract/10.1103/PhysRevApplied.13.034037&quot; rel=&quot;noreferrer&quot;&gt;paper published&lt;/a&gt; fewer than 2 months before you asked this question. The Hamiltonian is given in the image I posted in &lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/4314/2293&quot;&gt;this question&lt;/a&gt;, where the time-dependent &amp;quot;driver&amp;quot; part is shown in a bit more general form in Eq. 3 of the paper I mentioned (whether viewing on arXiv or Physical Review, it's still Eq. 3). I will repeat the driver and &amp;quot;problem&amp;quot; Hamiltonians here for the case where the coupling in the driver and the problem Hamiltonians are chosen to be the same (which needs to be perfectly doable anyway):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{1}&#xA;H_{\rm{driver}} &amp;amp;= \sum_{i}\omega_i \sigma^x_i + \sum_{ij}J_{ij}\sigma_i^y\sigma_j^y \\&#xA;\tag{2}&#xA;H_{\rm{problem}} &amp;amp;= \sum_{ij}J_{ij}\sigma_i^z\sigma_j^z\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now assuming that the normal AQC driving is done, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{3}&#xA;H(t) &amp;amp; = (1-t)H_{\rm{driver}} + tH_{\rm{problem}} \\&#xA;\tag{4}&#xA;     &amp;amp; = \sum_{i}(1-t)\omega_i \sigma^x_i + \sum_{ij}(1-t)J_{ij}\sigma_i^y\sigma_j^y &#xA;+ \sum_{ij}tJ_{ij}\sigma_i^z\sigma_j^z\\&#xA;\tag{5}\label{similar}&#xA;     &amp;amp; =\sum_{i}\omega_i(t) \sigma^x_i + \sum_{ij}J_{ij}(t)\sigma_i^y\sigma_j^y &#xA;+ \sum_{ij}K_{ij}(t)\sigma_i^z\sigma_j^z,\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where I have defined:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{6}&#xA;\label{defineTimeDependence}&#xA;\omega_i(t) \equiv (1-t)\omega, &amp;amp; ~~~~~~J_{ij}(t)\equiv (1-t)J_{ij}, &amp;amp; K_{ij}(t)\equiv tJ_{ij}.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;When  &lt;span class=&quot;math-container&quot;&gt;$t=1/2$&lt;/span&gt;, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{7}&#xA;  H(t)  &amp;amp; =\sum_{i}\omega_i(t) \sigma^x_i + \sum_{ij}J_{ij}(t)\left(\sigma_i^y\sigma_j^y +&#xA;\sigma_i^z\sigma_j^z\right).\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now let's apply the unitary transormation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{8}&#xA;  H(t)  &amp;amp; =\sum_{i}\omega_i(t) \sigma^x_i + \sum_{ij}J_{ij}(t)\left(\sigma_i^y\sigma_j^y +&#xA;\sigma_i^z\sigma_j^z\right),\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is strikingly close to your Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{9}&#xA;  H(t)  &amp;amp; =\sum_{i}\omega_i(t) \sigma^z_i + \sum_{ij}J_{ij}(t)\left(\sigma_i^y\sigma_j^y +&#xA;\sigma_i^x\sigma_j^x\right).\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So the closest I could get was the same Hamiltonian except it's only precisely the same as yours when:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$t=1/2$&lt;/span&gt; holds true in my case (Eq. &lt;span class=&quot;math-container&quot;&gt;$\eqref{similar}$&lt;/span&gt; is quite similar for other values of &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; though).&lt;/li&gt;&#xA;&lt;li&gt;Eq. &lt;span class=&quot;math-container&quot;&gt;$\eqref{defineTimeDependence}$&lt;/span&gt; holds true in your case.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; is interchanged with &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the 2-spin case, if a material needs to behave like Eq. &lt;span class=&quot;math-container&quot;&gt;$\eqref{similar}$&lt;/span&gt;, it can work if it contains the following superconducting circuit with Josephson junctions represented by the x's (it looks only slightly different from the circuit &lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/4314/2293&quot;&gt;here&lt;/a&gt; maybe because this circuit is actually reported to be able to have linear &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; terms in addition to the linear &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; terms, but I've set those field strengths to 0 in my analysis, which is a perfectly fine thing to do):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Jiaca.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Jiaca.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-06-21T01:17:46.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1359" PostTypeId="1" AcceptedAnswerId="1436" CreationDate="2020-06-21T05:30:06.510" Score="16" ViewCount="789" Body="&lt;p&gt;I was reading on the implementation of Hubbard 'U' in Density Functional Theory. The Hubbard 'U' can be thought of as a parameter that accounts for the on-site electron-electron interactions in correlated materials.&lt;/p&gt;&#xA;&lt;p&gt;Meanwhile, the Hund's J, I'm given to believe is an exchange effect. Many texts mention the 'J' like &lt;a href=&quot;https://www.cond-mat.de/events/correl12/manuscripts/cococcioni.pdf&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt;. This kind of direct exchange comes from the antisymmetry nature of the many-body electron wavefunction. How can this kind of exchange be quantified by an energy value similar to the Hubbard 'U'? I believe in literature, this 'J' value is usually taken to be less than 20% of the U value. I have not found a conclusive reason for this, but what I am more concerned with, is how can you possibly quantify such a direct exchange?&lt;/p&gt;&#xA;&lt;p&gt;PS: I had cross-posted this question on Phys stack exch earlier but now realize that this forum might be more appropriate since the 'J' is frequently encountered in DFT+U calculations.&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-07-23T17:52:37.590" LastActivityDate="2020-12-31T04:12:45.890" Title="The Hund's J - Why can this be quantified?" Tags="|density-functional-theory|hubbard-model|from-phys-se|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1360" PostTypeId="1" AcceptedAnswerId="1363" CreationDate="2020-06-22T03:58:29.743" Score="17" ViewCount="652" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Graph_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;Graph theory&lt;/a&gt; was originally introduced in computer science to study data structure. Chemists also introduced graph theory to study the relation between structure and properties for molecular compounds.&lt;/p&gt;&#xA;&lt;p&gt;My questions:&#xA;&lt;strong&gt;What are the typical applications of &lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_graph_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemical graph theory&lt;/a&gt;? What are some recent breakthroughs?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="142" LastEditDate="2020-06-30T08:57:58.937" LastActivityDate="2020-07-01T03:19:06.027" Title="What are the applications of chemical graph theory?" Tags="|reference-request|computational-chemistry|mathematical-modeling|chemoinformatics|" AnswerCount="6" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1362" PostTypeId="2" ParentId="1355" CreationDate="2020-06-22T07:15:37.987" Score="35" Body="&lt;p&gt;This &lt;span class=&quot;math-container&quot;&gt;$O(n\ln n)$&lt;/span&gt; integer multiplication algorithm is a &lt;a href=&quot;https://en.wikipedia.org/wiki/Galactic_algorithm&quot; rel=&quot;noreferrer&quot;&gt;galactic algorithm&lt;/a&gt;, meaning that it won't be used despite being &amp;quot;of lower complexity&amp;quot; because it only becomes more efficient than existing algorithms for problems vastly larger than any relevant to us in practice. The problem is big-&lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; notation only tells us how the algorithm behaves for &lt;em&gt;sufficiently large&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, whereas values of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; that will come up in practice will see a much worse behaviour. Section 5 of &lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-02070778/document&quot; rel=&quot;noreferrer&quot;&gt;their paper&lt;/a&gt; explains:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In this section we present the main integer multiplication algorithm. We actually give a family of algorithms, parameterised by a dimension parameter &lt;span class=&quot;math-container&quot;&gt;$d\geqslant2$&lt;/span&gt;. Let &lt;span class=&quot;math-container&quot;&gt;$n_0 := 2^{d^{12}}\geqslant 2^{4096}$&lt;/span&gt;, and suppose that we wish to multiply integers with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; bits. For &lt;span class=&quot;math-container&quot;&gt;$n &amp;lt; n_0$&lt;/span&gt;, we may use any convenient base-case multiplication algorithm, such as the classical &lt;span class=&quot;math-container&quot;&gt;$O(n^2)$&lt;/span&gt; algorithm. For &lt;span class=&quot;math-container&quot;&gt;$n\geqslant n_0$&lt;/span&gt; we will describe a recursive algorithm that reduces the problem to a collection of multiplication problems of size roughly &lt;span class=&quot;math-container&quot;&gt;$n^{1/d}$&lt;/span&gt;. We will show that this algorithm achieves &lt;span class=&quot;math-container&quot;&gt;$M(n) = O(n\log n)$&lt;/span&gt;, provided that &lt;span class=&quot;math-container&quot;&gt;$d\geqslant1729$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In other words, it's only worth using the new algorithm to multiply numbers with at least &lt;span class=&quot;math-container&quot;&gt;$\geqslant2^{1729^{12}}$&lt;/span&gt; bits. (For integer multiplication, the problem size &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is how many bits the larger integer has, not the integer itself; but even this number would have to be so large for the algorithm to be worthwhile I'll find it useful to discuss &lt;em&gt;its&lt;/em&gt; number of digits, in base &lt;span class=&quot;math-container&quot;&gt;$10$&lt;/span&gt;.) This number of bits has more than &lt;span class=&quot;math-container&quot;&gt;$2\times 10^{38}$&lt;/span&gt; digits in base &lt;span class=&quot;math-container&quot;&gt;$10$&lt;/span&gt;. A computer using every subatomic particle in the observable universe to store one bit of data can only store a number of bits of data whose number of digits is well under &lt;span class=&quot;math-container&quot;&gt;$100$&lt;/span&gt;. So there's no chance anyone would ever have a machine capable of such multiplication regardless of algorithm. The paper notes that smaller problems should just be done with existing algorithms.&lt;/p&gt;&#xA;&lt;p&gt;Why does &lt;span class=&quot;math-container&quot;&gt;$1729$&lt;/span&gt; come up here? Because a &lt;span class=&quot;math-container&quot;&gt;$1729$&lt;/span&gt;-dimensional Fourier transform is used. I'm sure within a few years there will be a tweaked version that brings that number down, allowing smaller problems to be multiplied in &lt;span class=&quot;math-container&quot;&gt;$O(n\log n)$&lt;/span&gt; time. But even if we only require &lt;span class=&quot;math-container&quot;&gt;$d=2$&lt;/span&gt; so &lt;span class=&quot;math-container&quot;&gt;$n_0=2^{2^{12}}$&lt;/span&gt;, that's still a number with &lt;span class=&quot;math-container&quot;&gt;$1234$&lt;/span&gt; digits in base &lt;span class=&quot;math-container&quot;&gt;$10$&lt;/span&gt;, far more than the aforementioned &lt;span class=&quot;math-container&quot;&gt;$100$&lt;/span&gt;. For what it's worth, the paper sketches a route to using &lt;span class=&quot;math-container&quot;&gt;$d=8$&lt;/span&gt;, in which case &lt;span class=&quot;math-container&quot;&gt;$n_0$&lt;/span&gt; would have over &lt;span class=&quot;math-container&quot;&gt;$2\times10^{10}$&lt;/span&gt; digits.&lt;/p&gt;&#xA;&lt;p&gt;As my link to Wikipedia notes, other kinds of multiplication have also encountered galactic algorithms, such as &lt;a href=&quot;https://www.smbc-comics.com/comic/mathematicians&quot; rel=&quot;noreferrer&quot;&gt;gradual improvements&lt;/a&gt; to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Coppersmith%E2%80%93Winograd_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Coppersmith–Winograd algorithm&lt;/a&gt; for matrix multiplication.&lt;/p&gt;&#xA;" OwnerUserId="914" LastEditorUserId="914" LastEditDate="2020-06-22T17:26:56.067" LastActivityDate="2020-06-22T17:26:56.067" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1363" PostTypeId="2" ParentId="1360" CreationDate="2020-06-22T15:37:38.377" Score="13" Body="&lt;p&gt;This is a question that is answered by a straightforward literature search, here's e.g. two review papers from the 1980s:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abstract/10.1021/ci00047a033&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Inf. Comput. Sci. 25, 334 (1985)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abstract/10.1021/ed065p574&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Educ. 65, 574 (1988)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;as well as a more recent encyclopedia article &lt;a href=&quot;http://www.ivanciuc.org/Files/Reprints/ch_002.pdf&quot; rel=&quot;noreferrer&quot;&gt;Encyclopedia of Computational Chemistry 1998, pp. 1169-1190&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-22T15:37:38.377" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1364" PostTypeId="1" CreationDate="2020-06-22T17:12:18.010" Score="12" ViewCount="154" Body="&lt;p&gt;Please, how may one simulate a solid-solid interface that one can carry out adsorption studies from. I tried using virtual nanolab in Quantum ATK but didn't get a hand of it.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/YBk05.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YBk05.png&quot; alt=&quot;Image of two solid interfaces&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="220" LastEditorUserId="24" LastEditDate="2020-06-22T18:40:33.940" LastActivityDate="2020-07-14T12:37:18.207" Title="What are the steps to prepare a solid-solid interface for adsorption studies in plane-wave DFT?" Tags="|density-functional-theory|adsorption|solid-solid-interface|" AnswerCount="1" CommentCount="6" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1365" PostTypeId="2" ParentId="1350" CreationDate="2020-06-22T18:15:47.053" Score="6" Body="&lt;p&gt;Normally, if various proteins have the &amp;quot;same&amp;quot; cavities/clefts, this means that they are part of the same family and the amino acids that form the cavity are conserved.&lt;/p&gt;&#xA;&lt;p&gt;I really don't think that the electronic properties (charges and electrostatic potential surface) are directly related to the geometrical shape. Instead, they are related to the residues that are in the cavities, the protein protonation state, etc.&lt;/p&gt;&#xA;&lt;p&gt;Normally, the interest in protein cavities/clefs is related to their activity. So, we look for small molecules that bind to proteins in their cavities and change the protein state.&lt;/p&gt;&#xA;&lt;p&gt;Servers like &lt;a href=&quot;http://www.pkumdl.cn:8000/cavityplus/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;CavityPlus&lt;/a&gt;, for example, are focused on cavity detection and functional analysis whereas servers like &lt;a href=&quot;http://sts.bioe.uic.edu/castp/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASTp&lt;/a&gt;, are specialized in topological analysis of protein cavities.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="118" LastEditDate="2020-07-03T18:38:23.510" LastActivityDate="2020-07-03T18:38:23.510" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1366" PostTypeId="1" CreationDate="2020-06-23T00:40:51.707" Score="12" ViewCount="242" Body="&lt;p&gt;I am trying to compute the electrostatic potential profile from a distribution of point-charges that were output from an MD simulation. Does anyone know of ready-made Poisson solver packages that are suited for MD? (specifically: can handle an arbitrary distribution of charges, work in 3D, can handle different mesh spacings in different dimensions, and can handle periodic boundary conditions)&lt;/p&gt;&#xA;&lt;p&gt;I have done a lot of searching, but most of the solvers appear to be applicable to setups with 2D grids, equal mesh spacing in x and y, and non-periodic boundary conditions.&lt;/p&gt;&#xA;" OwnerUserId="599" LastActivityDate="2020-06-23T08:13:43.163" Title="3D Poisson equation solver for arbitrary charge distribution?" Tags="|molecular-dynamics|electrostatic|charge-transfer|potential-energy-surface|finite-element-analysis|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1367" PostTypeId="2" ParentId="1366" CreationDate="2020-06-23T08:13:43.163" Score="6" Body="&lt;p&gt;It would help to know what you need the potentials for, since this will affect the techniques that are necessary to evaluate the potential. Point charges are trivial, as the potential generated by each charge is just -Z/r; the trick is mostly how to make the evaluation efficient, this is achieved with methods like fast multipoles or particle mesh Ewald. (Continuous charge distributions are completely different animal since you don't need the solution to Poisson's equation &lt;em&gt;a priori&lt;/em&gt;.)&lt;/p&gt;&#xA;&lt;p&gt;However, evaluation of the Coulomb potential is a task that's handled by MD packages, since determining the non-bonded Coulomb interactions requires knowing the potential in the system. Since you got the structure from an MD simulation, maybe there's a way to extract the potential from the MD software package you used?&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-23T08:13:43.163" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1368" PostTypeId="1" AcceptedAnswerId="1377" CreationDate="2020-06-23T08:33:57.410" Score="12" ViewCount="800" Body="&lt;p&gt;I want to use the ONIOM keyword, like &lt;code&gt;oniom(ccsd(t)/avtz:m06/genEcp)&lt;/code&gt; or similar, in conjunction with &lt;code&gt;genecp&lt;/code&gt;. I want to use &lt;code&gt;genEcp&lt;/code&gt; in the low-layer, but I always get an error about L301, error in reading basis or pseudo in the end of input file.&lt;/p&gt;&#xA;&lt;p&gt;If change the sequence, like &lt;code&gt;oniom(m06/genEcp:ccsd(t)/avtz)&lt;/code&gt;, everything is OK, but that's not what I want and it is wrong both in theory and answer. Someone said it's a bug on &lt;a href=&quot;http://bbs.keinsci.com/thread-12386-1-1.html&quot; rel=&quot;noreferrer&quot;&gt;this chinese site&lt;/a&gt;, but I don't know how to avoid it.&lt;/p&gt;&#xA;&lt;p&gt;Also, the tests from g16, test1009.com test0369.com are OK. I tried the&#xA;&lt;code&gt;oniom(ccsd(t)/gen:m06/genecp)&lt;/code&gt; similar with test0369.com and failed.&lt;/p&gt;&#xA;&lt;p&gt;I think this is a severe bug, for one can repeat the error just by changing the keyword in the input below from &lt;code&gt;blyp&lt;/code&gt; to &lt;code&gt;b3lyp&lt;/code&gt;, or element from &lt;code&gt;Ti&lt;/code&gt; to &lt;code&gt;Ar&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p oniom(HF/gen:blyp/genecp)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He 0&#xA;sto-3g&#xA;****&#xA;Ti 0&#xA;lanl2dz&#xA;****&#xA;&#xA;Ti 0&#xA;lanl2dz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="938" LastEditorUserId="938" LastEditDate="2020-06-23T13:17:46.707" LastActivityDate="2020-06-24T17:05:48.860" Title="What is Gaussian16's read-file logic when using ONIOM with genecp?" Tags="|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1369" PostTypeId="1" CreationDate="2020-06-23T12:39:27.453" Score="13" ViewCount="965" Body="&lt;p&gt;I am working on DFT code having plane wave along xy axis and bspline in z direction. For calculating the properties of TMD materials, spin orbit coupling must be included but i did not find fully relativistic uspp pseudo-potentials of atoms that can be generated from vanderbilt code. Then I get it from Quantum Esspresso UPF format. but not able to parse it. I did not find it in web. can somebody help to convert it uspp format or any txt format so that i can extract parameters from it. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="749" LastActivityDate="2021-12-27T13:11:08.473" Title="How to convert Unified Pseudopotential Format (UPF) into Ultrasoft Pseudopotential (USPP) format?" Tags="|density-functional-theory|electronic-structure|condensed-matter|pseudopotentials|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1370" PostTypeId="2" ParentId="1360" CreationDate="2020-06-23T16:53:58.783" Score="9" Body="&lt;p&gt;Some recent work that comes to my mind is generation and analysis of fullerenes done by Peter Schwerdtfeger's group and described for example in&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.23278&quot; rel=&quot;noreferrer&quot;&gt;J. Comput. Chem. 34 1508 (2013)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/wcms.1207&quot; rel=&quot;noreferrer&quot;&gt;WIREs 5, 96 (2015)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="544" LastActivityDate="2020-06-23T16:53:58.783" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1371" PostTypeId="2" ParentId="1369" CreationDate="2020-06-23T17:49:21.860" Score="4" Body="&lt;p&gt;I really don't know any engine to convert between pseudopotential formats, but below you can find links to engines where you can generate pseudopotentials according to your own needs:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://tddft.org/programs/APE/&quot; rel=&quot;nofollow noreferrer&quot;&gt;APE-Atomic Pseudopotentials Engine&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://th.fhi-berlin.mpg.de/th/fhi98md/fhi98PP/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The fhi98PP pseudopotential program&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://opium.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Opium - pseudopotential generation project&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.physics.rutgers.edu/%7Edhv/uspp/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vanderbilt Ultra-Soft Pseudopotential Site&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/oncvpsp/oncvpsp&quot; rel=&quot;nofollow noreferrer&quot;&gt;Optimized norm-conserving Vanderbilt pseudopotentials&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.pseudo-dojo.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pseudo Dojo&lt;/a&gt; (&lt;a href=&quot;https://github.com/abinit/pseudo_dojo&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-12-27T13:11:08.473" LastActivityDate="2021-12-27T13:11:08.473" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1372" PostTypeId="2" ParentId="1369" CreationDate="2020-06-23T18:28:52.527" Score="10" Body="&lt;p&gt;USPP is not a format of pseudopotential. It is a &lt;strong&gt;type&lt;/strong&gt; of pseudopotential that enables you to work with lower cutoffs. On the other hand, upf is a popular file extension for pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;If your question is regarding the availability of fully relativistic Ultrasoft PPs, they aren't very popular but &lt;a href=&quot;https://dalcorso.github.io/pslibrary/&quot; rel=&quot;noreferrer&quot;&gt;PSLibrary&lt;/a&gt; offers that support.&lt;/p&gt;&#xA;&lt;p&gt;For Norm-conserving and Projector-augmented wave PPs, &lt;a href=&quot;http://www.pseudo-dojo.org/&quot; rel=&quot;noreferrer&quot;&gt;Pseudodojo&lt;/a&gt; is pretty reliable (for both relativistic and non-relativistic cases)&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-06-23T18:28:52.527" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1373" PostTypeId="2" ParentId="1355" CreationDate="2020-06-23T18:36:28.123" Score="24" Body="&lt;p&gt;To take a slight detour, we can also look at the progress of matrix multiplication algorithms. As mentioned in a few comments here, standard matrix multiplication is &lt;span class=&quot;math-container&quot;&gt;$O(n^{3})$&lt;/span&gt; and any exact method for a general matrix is going to require &lt;span class=&quot;math-container&quot;&gt;$O(n^{2})$&lt;/span&gt; operations just to process all the elements of initial matrices. Over the last 50 years, different methods have been developed to reduce the exponent, often denoted &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;. These could in principle be very useful for matter modeling, as a number of electronic structure and molecular dynamics methods rely on matrix multiplication and matrix operations which have been shown to scale the same (determinant, inversion, Gaussian elimination) or in a way expressible in terms of &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; (eigenvalues). &lt;/p&gt;&#xA;&lt;p&gt;The simplest such approach, and thus the most likely to be applied in practice, is the 1971 Strassen Algorithm, which has &lt;span class=&quot;math-container&quot;&gt;$O(n^{\log_2(7)})=O(n^{2.804...})$&lt;/span&gt; scaling. It achieves this by recursively breaking the initial matrices into 4 blocks and storing intermediate quantities such that you can perform 7, rather than the typical 8, block multiplications. &lt;/p&gt;&#xA;&lt;p&gt;Fairly recent studies suggest that the crossover point where it becomes more efficient than standard matrix multiplication is somewhere between &lt;span class=&quot;math-container&quot;&gt;$n=512$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n=1024$&lt;/span&gt; (the method works best with widths that are powers of two due the repeated splits into 4 blocks), which are not unreasonable sizes to encounter in a large molecular electronic structure calculation. In practice, the better scaling in general is traded for greater speed for specific cases by setting a threshold size below which the recursion is stopped and replaced with standard matrix multiplication. I don't know off hand of any program that actually uses this method, but it seems like it would be simple addition and could produce tangible speedups for larger systems.&lt;/p&gt;&#xA;&lt;p&gt;The last significant improvement was the 1990 Coopersmith-Winograd Algorithm, which scales as &lt;span class=&quot;math-container&quot;&gt;$O(n^{2.376...})$&lt;/span&gt;. The algorithm is much more complicated than the original Strassen algorithm; the proof of the scaling relates the rank of a particular trilinear form of tensor products to &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;. This complexity manifests in a very large prefactor, making the method much slower than the Strassen method or standard matrix multiplication. The impractically large matrices needed to reach the crossover threshold for these later approaches has led them to be referred to as galactic algorithms.&lt;/p&gt;&#xA;&lt;p&gt;These later approaches currently have no use in matter modeling (or really any practical application), but could have significance in the long run. While the current thread of research has focused on proving a lower bound for &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;, this work could provide the impetus for producing more practical algorithms by proving that better scaling than the standard algorithm is possible.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-25T02:24:40.400" LastActivityDate="2020-06-25T02:24:40.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1374" PostTypeId="2" ParentId="1360" CreationDate="2020-06-23T20:00:16.910" Score="8" Body="&lt;p&gt;This paper might be a good example: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2451929418300639&quot; rel=&quot;noreferrer&quot;&gt;Chem, 4, 390-398 (2018)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Quoting the authors: 'Computer autonomously designs chemical syntheses of medicinally relevant molecules'.&lt;/p&gt;&#xA;" OwnerUserId="99" LastActivityDate="2020-06-23T20:00:16.910" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1375" PostTypeId="2" ParentId="1360" CreationDate="2020-06-23T20:09:12.703" Score="9" Body="&lt;p&gt;Too many references for me to elaborate on, but here's a recent example I like: &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.9b01294&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals&amp;quot;&lt;/a&gt; in &lt;em&gt;Chemistry of Materials&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-06-23T20:09:12.703" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1376" PostTypeId="2" ParentId="1122" CreationDate="2020-06-24T15:07:48.790" Score="5" Body="&lt;p&gt;I am also looking for something like this. But to run a PWSCF calculation on google colab seems next to impossible.&lt;/p&gt;&#xA;&lt;p&gt;However, you should check this out: &lt;a href=&quot;https://github.com/jkitchin/dft-book-espresso&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/jkitchin/dft-book-espresso&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="943" LastActivityDate="2020-06-24T15:07:48.790" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1377" PostTypeId="2" ParentId="1368" CreationDate="2020-06-24T17:05:48.860" Score="8" Body="&lt;p&gt;I am not very well versed with ONIOM calculations, so I cannot really comment, whether my following examples are actually sensible, I just picked your example with different methods.&lt;br /&gt;&#xA;I think the biggest problem here is the lack of a real description of ONIOM for Gaussian, especially when it comes to defining general basis sets. Long story short, and if you don't like my rambling, check out &lt;code&gt;g16/tests/com/test0699.com&lt;/code&gt;.&#xA;In brief, if you use &lt;code&gt;oniom(x/genecp:y/genecp)&lt;/code&gt;, you'll need three complete sections of general basis sets: low-level real system, high-level model system, low-level model system.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As you have noticed something like &lt;code&gt;oniom(CCSD(T)/cc-pVTZ:M06/def2SVP)&lt;/code&gt; will run perfectly fine. There is nothing special about that, Gaussian uses all of its default implementations and files.&lt;br /&gt;&#xA;From what I understood, a two-layer calculation will first perform a low-level calculation on the real system, then the high-level calculation on the model system, then the low-level calculation on the model system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input 1&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(CCSD(T)/cc-pVTZ:M06/def2SVP)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The issue comes when specifying the general basis. If you want to specify a basis for the high level, it is still somewhat normal, so the above can be rewritten as following.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input 2&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(CCSD(T)/gen:M06/def2SVP)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He 0&#xA;cc-pVTZ&#xA;****&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So far so good, but what do you need to do to change the level for the lower layer? That is not quite as simple. Let's use the example and just switch it around.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input 3 (broken)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(CCSD(T)/cc-pVTZ:M06/gen)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He Ti 0&#xA;def2SVP&#xA;****&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It will run the low-level calculation on the system (RMO6/gen), then run the high-level calculation (CCSD(T)/cc-pVTZ), then abort with the error in 301:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;General basis read from cards:  (5D, 7F)  &#xA;End of file reading basis center. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It needs a general basis for the low-level calculation of the model system, if you add that, everything will work. Therefore, &lt;strong&gt;Input 1&lt;/strong&gt; can be rewritten as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input 3 (fixed)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(CCSD(T)/cc-pVTZ:M06/gen)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He Ti 0&#xA;def2SVP&#xA;****&#xA;&#xA;He 0&#xA;def2SVP&#xA;****&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From here on in it may be quite obvious what to do to run it with two different general basis sets. Simply specify them in the order as you would specify the charge: low-level real system (everything), high-level model system (layer H), low-level model system (layer H).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input 4&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(CCSD(T)/gen:M06/gen)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He Ti 0&#xA;def2SVP&#xA;****&#xA;&#xA;He 0&#xA;cc-pVTZ&#xA;****&#xA;&#xA;He 0&#xA;def2SVP&#xA;****&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, let's finish this with the ecp settings. Here it is especially important to keep track of the blank lines. Even though helium will not have an ECP, Gaussian will want to read that section. Since it is terminated by a blank line, at least that must be there. Otherwise you will get the following error in L301:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;EOF while reading ECP pointer card.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The following input should reproduce your example.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;#P TEST oniom(HF/genecp:BLYP/genecp)&#xA;&#xA;Title Card Required&#xA;&#xA;0 1&#xA; He                0    0.0 0.0 0.0 H&#xA; Ti                0    0.0 0.0 4.0 L&#xA;&#xA;He 0&#xA;STO-3G&#xA;****&#xA;Ti 0&#xA;LANL2DZ&#xA;****&#xA;&#xA;Ti 0&#xA;LANL2DZ&#xA;&#xA;He 0&#xA;def2SVP&#xA;****&#xA;&#xA;&#xA;He 0&#xA;STO-3G&#xA;****&#xA;&#xA;&#xA;!~eof&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I would say the bug is not in the code itself, but in the documentation.&lt;/p&gt;&#xA;" OwnerUserId="49" LastActivityDate="2020-06-24T17:05:48.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1378" PostTypeId="1" AcceptedAnswerId="1379" CreationDate="2020-06-24T18:07:03.287" Score="20" ViewCount="717" Body="&lt;p&gt;I am trying to model some materials with DFT, so I intended to start out with the structure. However, some texts that present XRD data, use a term called atomic positional parameter. I can't seem to figure out what this means. Here's an image from &lt;a href=&quot;https://www.researchgate.net/publication/244638749_Bis1a8b-dihydro11-2H2-2H-benzoacyclopropaccyclohepten-2-onehydrogenI_hexachloroantimonate_HC12H8D2O2SbCl6&quot; rel=&quot;noreferrer&quot;&gt;a paper&lt;/a&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/yRAIk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yRAIk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can someone help breakdown what format the coordinates are represented in ?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="770" LastEditDate="2020-06-24T18:50:07.573" LastActivityDate="2020-06-25T04:09:42.293" Title="Meaning of atomic positional parameters" Tags="|density-functional-theory|crystal-structure|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1379" PostTypeId="2" ParentId="1378" CreationDate="2020-06-24T22:42:19.330" Score="16" Body="&lt;p&gt;Above the table that you provided in the screenshot, is a caption that says what these numbers mean:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jo1Qx.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jo1Qx.png&quot; alt=&quot;Table header&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't blame you for coming here to ask this, because the notation (&lt;span class=&quot;math-container&quot;&gt;$\times 10^4$&lt;/span&gt;) can be confusing for someone that's not used to it (and I don't think it's taught in school, generally). But what it means is that numbers like 1383, which is the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;-coordinate (along the &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; axis of the unit cell) given for the 6th carbon atom, C(6), actually mean 0.1383. &lt;strong&gt;The number 1383(3) means (0.1383 +/- 0.0003).&lt;/strong&gt; Similarly, the &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; coordinates are actually fractional lengths along the &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; axes of the crystal unit cell.&lt;/p&gt;&#xA;&lt;p&gt;I also don't blame you if you're confused by what these numbers mean, because the table's caption says &amp;quot;atomic positional parameters&amp;quot; which seems (at least to me) as an unconventional way of saying &amp;quot;atomic coordinates&amp;quot;. At least a different part of the exact same paper describes this table as listing atomic coordinates though:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/2TrRQ.png&quot; width=&quot;400&quot;&gt;&#xA;&lt;p&gt;Table 2 also has the &amp;quot;internal coordinates&amp;quot; that you would use if your modeling program requires input in ZMAT format.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;In summary:&lt;/strong&gt; The table in your question corresponds to the fractional coordinates for the atoms with respect to the unit cell (although it also has uncertainties on each coordinate value). You mentioned in the comments that you're used to seeing exact fractions like 1/4 and 3/4, but in this case the molecule is not so simple like textbook lattice structures such as NaCl. So, when they are measured experimentally, they won't correspond to simple fractions and  will have an associated uncertainty.&lt;/p&gt;&#xA;&lt;p&gt;In the above case the fraction would be &lt;em&gt;approximately&lt;/em&gt; 1383/10000, but remember that there's an uncertainty, so in fractional form the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;-coordinate would actually be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{1383 \pm 3}{10000}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-25T03:18:59.387" LastActivityDate="2020-06-25T03:18:59.387" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1380" PostTypeId="1" AcceptedAnswerId="1383" CreationDate="2020-06-25T02:30:39.740" Score="15" ViewCount="5592" Body="&lt;p&gt;I have modeled a complex structure of a protein and a Carbon nano-cone (used as an indenter to the protein) using PACKMOL. The LAMMPS data file of the complex structure consists of 4 atom types (C O N S). But I constantly get an error saying &lt;em&gt;'Atoms lost'&lt;/em&gt; (I have tried with different potentials like ReaxFF, LJ, etc...). I know this means a few atoms have been blown off so far from the simulation box that they have been lost. LAMMPS mailing list archives all suggest for a bad geometry, but there is nothing I can do to modify the data file. Hence I really need some help with correcting the code(seen below). The main motive of the code is for the Carbon nano cone to indent the protein.&#xA;The code below is the code I have written for LJ potential.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# -------------- Initialisation -------------------#&#xA;&#xA;units           metal&#xA;boundary        p p p&#xA;atom_style      atomic&#xA;timestep        0.001&#xA;&#xA;read_data       SE_atomic.dat&#xA;mass    1 14.0067   #Nitrogen&#xA;mass    2 12.0107   #Carbon&#xA;mass    3 15.9940   #Oxygen&#xA;mass    4 32.0650   #Sulphur&#xA;&#xA;&#xA;#Substrate&#xA;&#xA;region           sars block INF INF INF INF INF 300 units box&#xA;group            sars region sars&#xA;&#xA;#Indenter&#xA;&#xA;region           top block INF INF INF INF 300 INF units box&#xA;group            top region top&#xA;&#xA;#Potentials&#xA;&#xA;&#xA;pair_style       lj/cut 2.5&#xA;&#xA;pair_coeff  1  1  0.0163859696   2.9565&#xA;pair_coeff  1  2  0.07146236771  3.1365&#xA;pair_coeff  1  3  0.07168744659  2.9165&#xA;pair_coeff  1  4  0.02856991424  2.8232&#xA;pair_coeff  2  2  0.12219124354  3.2615&#xA;pair_coeff  2  3  0.12257609881  3.0415&#xA;pair_coeff  2  4  0.04885079323  2.9482&#xA;pair_coeff  3  3  0.07146236771  3.1365&#xA;pair_coeff  3  4  0.07168744659  2.9165&#xA;pair_coeff  4  4  0.09181993247  3.0815&#xA;&#xA;&#xA;compute         peratom all pe/atom&#xA;neighbor        2.0 bin&#xA;neigh_modify delay 20 every 1 check yes page 500000 one 50000&#xA;&#xA;#Initialisation&#xA;&#xA;velocity all create 353 511124 rot yes mom yes&#xA;variable        t_step equal &amp;quot;step&amp;quot;&#xA;variable        t_temp equal &amp;quot;temp&amp;quot;&#xA;thermo          100&#xA;thermo_style    custom step press temp pe&#xA;&#xA;#Relaxation&#xA;&#xA;fix rigid sars addforce 0.0 0.0 0.0&#xA;fix relax top nvt temp 250 250 0.01&#xA;variable t equal 0.005&#xA;timestep ${t}&#xA;dump 1 all custom 500 equil.*.dump id type x y z fx fy fz&#xA;&#xA;run 3000&#xA;&#xA;&#xA;#Indentation&#xA;&#xA;fix 1 top addforce 0.0 -0.05 0.0&#xA;fix fix1 all nvt temp 250 250 0.01&#xA;dump 2 all custom 100 sars-Indent.*.dump id type x y z fx fy fz&#xA;&#xA;run 1000&#xA;&#xA;&#xA;print &amp;quot;All done&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This code is written for ReaxFF potential&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# -------------- Initialisation -------------------#&#xA;&#xA;units           metal&#xA;boundary        p p p&#xA;atom_style      charge&#xA;timestep        0.001&#xA;&#xA;read_data       SE_charge.dat&#xA;mass    1 14.0067   #Nitrogen&#xA;mass    2 12.0107   #Carbon&#xA;mass    3 15.9940   #Oxygen&#xA;mass    4 32.0650   #Sulphur&#xA;&#xA;&#xA;#Substrate&#xA;&#xA;region           sars block INF INF INF INF INF 300 units box&#xA;group            sars region sars&#xA;&#xA;#Indenter&#xA;&#xA;region           top block INF INF INF INF 300 INF units box&#xA;group            top region top&#xA;&#xA;#Potentials&#xA;&#xA;pair_style      reax/c NULL&#xA;pair_coeff      * * SARS.ff N C O S&#xA;compute         peratom all pe/atom&#xA;neighbor        0.5 bin&#xA;neigh_modify delay 20 every 1 check yes page 500000 one 50000&#xA;&#xA;#Initialisation&#xA;&#xA;velocity all create 353 511124 rot yes mom yes&#xA;variable        t_step equal &amp;quot;step&amp;quot;&#xA;variable        t_temp equal &amp;quot;temp&amp;quot;&#xA;thermo          100&#xA;thermo_style    custom step press temp pe&#xA;&#xA;#Relaxation&#xA;&#xA;fix rigid sars addforce 0.0 0.0 0.0&#xA;fix relax top nvt temp 250 250 0.01&#xA;fix charge all qeq/reax 1 0.0 10.0 1.0e-6 reax/c&#xA;variable t equal 0.005&#xA;timestep ${t}&#xA;dump 1 all custom 500 equil.*.dump id type x y z fx fy fz&#xA;&#xA;run 2000&#xA;&#xA;&#xA;#Indentation&#xA;&#xA;fix 1 top addforce 0.0 -0.05 0.0&#xA;fix fix1 all nvt temp 250 250 0.01&#xA;dump 2 all custom 100 sars-Indent.*.dump id type x y z fx fy fz&#xA;&#xA;run 1000&#xA;&#xA;&#xA;print &amp;quot;All done&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If anyone in the community can help regarding the same, it would be really helpful for me!&#xA;Cheers!&lt;/p&gt;&#xA;&lt;p&gt;I have uploaded &lt;a href=&quot;https://raw.githubusercontent.com/HPQC-LABS/QCBugs/master/Issue018/LAMMPS_datafile_LJ.txt&quot; rel=&quot;noreferrer&quot;&gt;my LAMMPS datafile for the LJ case&lt;/a&gt; and &lt;a href=&quot;https://raw.githubusercontent.com/HPQC-LABS/QCBugs/master/Issue018/LAMMPS_datafile_ReaxFF.txt&quot; rel=&quot;noreferrer&quot;&gt;my datafile for the ReaxFF case&lt;/a&gt;, and all data files, input files, and log files are located in &lt;a href=&quot;https://github.com/HPQC-LABS/QCBugs/tree/master/Issue018&quot; rel=&quot;noreferrer&quot;&gt;this folder&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="5" LastEditDate="2020-06-25T04:07:51.493" LastActivityDate="2020-06-26T10:16:17.973" Title="How to rectify the error &quot;Lost atoms: original 28437 current 3659&quot; in LAMMPS?" Tags="|molecular-modeling|molecular-dynamics|molecular-interactions|lammps|proteins|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="1381" PostTypeId="2" ParentId="994" CreationDate="2020-06-25T03:45:13.017" Score="9" Body="&lt;p&gt;I don't know if I can answer the exact question here, but I can hopefully start a discussion in the right direction.&lt;/p&gt;&#xA;&lt;p&gt;Error cancellation is pervasive throughout matter modeling, and in particular electronic structure calculations. Whenever we use an approximate method to predict, for example, the energy of some system, we are neglecting numerous possible interactions/factors that would be included in the exact formulation (e.g. the Schrodinger equation for nonrelativistic calculations). If the computed result is in good agreement with the exact result, what has happened is that the various error introduced by our approximation have effectively cancelled each other out. In this sense, the accuracy of approximate computational methods is entirely dependent on error cancellation. So asking when error cancellation holds for a given level of theory is essentially asking for when that method works at all.&lt;/p&gt;&#xA;&lt;p&gt;So we can easily determine extent of error cancellation provided we have some sort of exact reference. Not as simple is determining what are the main sources of a particular instance of error cancellation. Often this just takes the form of heuristics developed over time by applying different methods to different types of systems. In a few cases, efforts have been made to actually justify theoretically/mathematically why a method performs well/poorly on certain systems or for certain properties.&lt;/p&gt;&#xA;&lt;p&gt;A simple example is that Hartree-Fock can be used to predict surprisingly accurate ionization potentials (using Koopman's theorem) despite the simplicity of the method. The reason for this is that the calculation neglects both correlation energy and relaxation energy. Including correlation energy should stabilize the original molecule more than its ion, as the original molecule has more electrons to correlate. This would suggest that HF underestimates the ionization potential. However, allowing the orbitals of the ion to relax should stabilize it relative to the original molecule, which suggests that HF is overestimating the ionization potential. Since these two effects have opposite sign, neglecting them only introduces a small amount of error. (This argument is based on the one given in section 3.3 of Szabo and Ostlund's Modern Quantum Chemistry).&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-06-25T03:45:13.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1382" PostTypeId="2" ParentId="1378" CreationDate="2020-06-25T04:09:42.293" Score="9" Body="&lt;p&gt;These are in &lt;strong&gt;fractional coordinates&lt;/strong&gt;, which are coordinates with respect to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lattice_constant&quot; rel=&quot;noreferrer&quot;&gt;lattice axis&lt;/a&gt; commonly referred to as the a, b, and c axis. More specifically, a, b and c are the lengths of the cell edges, and the axis have angles &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; between them.&lt;/p&gt;&#xA;&lt;p&gt;Many matter modeling software can use either fractional coordinates or Cartesian coordinates but the conversion between them is straightforward.&#xA;.&lt;/p&gt;&#xA;&lt;p&gt;Here is a snippet adapted from &lt;a href=&quot;https://pymolwiki.org/index.php/Cart_to_frac&quot; rel=&quot;noreferrer&quot;&gt;https://pymolwiki.org/index.php/Cart_to_frac&lt;/a&gt; to convert Cartesians to fractional coordinates&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# (scaled) volume of the cell    &#xA;v = sqrt(1 -cos(alpha)*cos(alpha) - cos(beta)*cos(beta) - cos(gamma)*cos(gamma) + 2*cos(alpha)*cos(beta)*cos(gamma))&#xA;&#xA;tmat = numpy.matrix( [&#xA;[ 1.0 / a, -cos(gamma)/(a*sin(gamma)), (cos(alpha)*cos(gamma)-cos(beta)) / (a*v*sin(gamma))  ],&#xA;[ 0.0,     1.0 / (b*sin(gamma)),         (cos(beta) *cos(gamma)-cos(alpha))/ (b*v*sin(gamma))  ],&#xA;[ 0.0,     0.0,                        sin(gamma) / (c*v)                                    ] ])&#xA;&#xA;frac_coord = cart_coord * tmat.T    # CRA renamed for MMSE&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is a snippet adapted from I &lt;a href=&quot;https://gist.github.com/Bismarrck/a68da01f19b39320f78a&quot; rel=&quot;noreferrer&quot;&gt;https://gist.github.com/Bismarrck/a68da01f19b39320f78a&lt;/a&gt; to convert fractional coordinates to Cartesians:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cosa = np.cos(alpha)&#xA;sina = np.sin(alpha)&#xA;cosb = np.cos(beta)&#xA;sinb = np.sin(beta)&#xA;cosg = np.cos(gamma)&#xA;sing = np.sin(gamma)&#xA;volume = 1.0 - cosa**2.0 - cosb**2.0 - cosg**2.0 + 2.0 * cosa * cosb * cosg&#xA;volume = np.sqrt(volume)&#xA;r = np.zeros((3, 3))&#xA;r[0, 0] = a&#xA;r[0, 1] = b * cosg&#xA;r[0, 2] = c * cosb&#xA;r[1, 1] = b * sing&#xA;r[1, 2] = c * (cosa - cosb * cosg) / sing&#xA;r[2, 2] = c * volume / sing&#xA; &#xA;cart_coord = np.dot(r,frac_coord.T)   # CRA added this for MMSE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-06-25T04:09:42.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1383" PostTypeId="2" ParentId="1380" CreationDate="2020-06-25T08:33:50.490" Score="14" Body="&lt;p&gt;The &amp;quot;Lost atoms&amp;quot; error typically happens when huge forces blow up an MD calculation. This is also the problem here:&lt;/p&gt;&#xA;&lt;p&gt;The main issue are the units. The input parameters for reax force fields are given in &amp;quot;real&amp;quot; units by default. Unless they are converted real units have to be used in the lammps input file. Setting the units appropriately eliminates the &amp;quot;Lost atoms&amp;quot; error because the forces now have reasonable values.&lt;/p&gt;&#xA;&lt;p&gt;Two more (not directly related) issue are standing out: The &amp;quot;fix nvt&amp;quot; and the &amp;quot;region&amp;quot; commands. Unless explicitly unset a fix persists until the end of the simulation. Therefore,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix relax top nvt temp 250 250 0.01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix fix1 all nvt temp 250 250 0.01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;each apply a time integrator to all atoms in &amp;quot;top&amp;quot;. This will certainly lead to undesired results.&lt;/p&gt;&#xA;&lt;p&gt;The simulation box defined in &amp;quot;SE_charge.dat&amp;quot; only extends to 216, so the region top is always empty.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;region           top block INF INF INF INF 300 INF units box&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Therefore, the entire Relaxation block does nothing because the nvt time integrator is applies to 0 atoms.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR&lt;/strong&gt; With a few tweaks to the input file the simulation with the reaxFF is running. All I changed is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# The units for the parameters in reaxFF input decks are real&#xA;units           real                 # time is given in fs&#xA;&#xA;# Your simulation box only extends to 216.506012, setting 300 in the commands below leaves the region top empty. Set this value to something usefull&#xA;region           sars block INF INF INF INF INF 200 units box&#xA;region           top block INF INF INF INF 200 INF units box&#xA;&#xA;# adjust the time step to the new units&#xA;fix relax top nvt temp 250 250 100&#xA;variable t equal 1&#xA;&#xA;# use unfix to remove the nvt fix, otherwise you have two time integrators active!&#xA;unfix rigid&#xA;unfix relax&#xA;&#xA;# again adjust the time step&#xA;fix fix1 all nvt temp 250 250 100&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;EDIT:&#xA;The entire input file with changes is &lt;a href=&quot;https://github.com/ducryf/mattermodeling_se/blob/master/LAMMPS_input_ReaxFF.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="295" LastEditDate="2020-06-26T10:16:17.973" LastActivityDate="2020-06-26T10:16:17.973" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1384" PostTypeId="2" ParentId="1355" CreationDate="2020-06-25T10:49:53.050" Score="15" Body="&lt;h2&gt;Practical importance: compactifying explanations&lt;/h2&gt;&#xA;&lt;p&gt;It is widely believed that &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n \log n)$&lt;/span&gt;  is the best possible result, and therefore we no longer have to say &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n\log n\cdot 2^{2\log^*n})$&lt;/span&gt; every single time in every single paper in related fields, we can just say &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(n \log n)$&lt;/span&gt; every time now. Here is a related quote from Reddit:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The result is of extreme practical importance. Not for actually&#xA;multiplying integers (as usual with these algorithms it's probably not&#xA;faster than existing algorithms for integers that can be stored in the&#xA;observable universe), but for writing papers. It has always been a&#xA;hassle to write down the complexity of integer multiplication or&#xA;algorithms based on integer multiplication by introducing soft-O&#xA;notation, little-o exponents, epsilons greater than 0, or iterated&#xA;logarithms. From now on I can just write O(n log n) in my papers and&#xA;be done with it!&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;While this might not be the answer you're looking for, about practical impact on computations, it does in fact answer the question of &amp;quot;What is the practical value of this algorithm?&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="948" LastEditorUserId="5" LastEditDate="2020-06-25T15:40:03.400" LastActivityDate="2020-06-25T15:40:03.400" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1385" PostTypeId="2" ParentId="365" CreationDate="2020-06-25T16:15:11.850" Score="17" Body="&lt;h1&gt;Cython&lt;/h1&gt;&#xA;&lt;p&gt;There are currently two answers suggesting &lt;a href=&quot;https://www.python.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python&lt;/a&gt; (by &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/400/63&quot;&gt;Paulie Bao&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/397/63&quot;&gt;Greg&lt;/a&gt;). Python is a &lt;a href=&quot;https://en.wikipedia.org/wiki/High-level_programming_language&quot; rel=&quot;nofollow noreferrer&quot;&gt;high-level&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Interpreted_language&quot; rel=&quot;nofollow noreferrer&quot;&gt;interpreted&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Dynamic_programming_language&quot; rel=&quot;nofollow noreferrer&quot;&gt;dynamically typed&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Garbage_collection_(computer_science)&quot; rel=&quot;nofollow noreferrer&quot;&gt;garbage collected&lt;/a&gt;, and &lt;a href=&quot;https://en.wikipedia.org/wiki/General-purpose_programming_language&quot; rel=&quot;nofollow noreferrer&quot;&gt;general-purpose&lt;/a&gt; programming language. All this means is that you can have an actually working, readable piece of code in a considerably short amount of time and that this code can do pretty much anything (from &lt;a href=&quot;https://scikit-learn.org/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;machine learning&lt;/a&gt; to &lt;a href=&quot;https://cvxopt.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;convex optimization&lt;/a&gt; to &lt;a href=&quot;https://cclib.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;parsing computational chemistry logfiles&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;But coding faster does not mean fast code&lt;/em&gt;. This has been argued in other answers, particularly in the context of compiled (e.g. C/C++/Fortran/etc.) &lt;em&gt;versus&lt;/em&gt; interpreted languages (such as Python, see answers by &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/367/63&quot;&gt;taciteloquence&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/401/63&quot;&gt;Antoine Levitt&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/685/63&quot;&gt;DetlevCM&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/370/63&quot;&gt;Camps♦&lt;/a&gt;, etc.). Of course, you could try to avoid this discussion by using the many Python libraries that actually wrap C/C++/Fortran codes, such as &lt;a href=&quot;https://numpy.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NumPy&lt;/a&gt; or &lt;a href=&quot;https://www.scipy.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SciPy&lt;/a&gt;; this is probably fine for using Python as an (excellent) replacement for MATLAB/&lt;a href=&quot;https://www.gnu.org/software/octave/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Octave&lt;/a&gt; (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3680/63&quot;&gt;this answer&lt;/a&gt; as well), but this might not be enough. &lt;strong&gt;What if we could compile Python?&lt;/strong&gt; Better yet, what if we could only compile the bottlenecks?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://cython.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cython&lt;/a&gt; can be described as a C/C++-compiler for Python. You can either compile pure Python code (&lt;a href=&quot;https://cython.readthedocs.io/en/latest/src/quickstart/cythonize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;for which you can expect a 30-40% performance boost&lt;/a&gt;) or an annotated version of it (&lt;a href=&quot;https://notes-on-cython.readthedocs.io/en/latest/std_dev.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;for which you might not see a difference from pure C&lt;/a&gt;). The good thing is that the compiled modules are fully interoperable with the Python ecosystem.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="63" LastEditDate="2023-07-03T15:30:12.583" LastActivityDate="2023-07-03T15:30:12.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1386" PostTypeId="1" CreationDate="2020-06-25T20:20:48.993" Score="2" ViewCount="47" Body="&lt;p&gt;&lt;strong&gt;nano particle synthesis&lt;/strong&gt;&#xA;Anyone about nano particle synthesis by precipitation methods? what are the different precipitation methods?&lt;/p&gt;&#xA;" OwnerUserId="950" LastActivityDate="2020-06-25T20:20:48.993" Title="nanoparticle synthesis by precipitation methods" Tags="|nanoparticles|" AnswerCount="0" CommentCount="2" ClosedDate="2020-06-25T21:03:35.580" ContentLicense="CC BY-SA 4.0" />
  <row Id="1387" PostTypeId="7" CreationDate="2020-06-25T20:51:18.487" Score="0" Body="&lt;p&gt;&lt;b&gt;Matter Modeling Stack Exchange&lt;/b&gt; is a question and answer site for Matter Modelers: computational chemists, material scientists, particle physicists, data scientists, and anyone else who uses computational methods to study molecules and materials. It's built and run &lt;i&gt;by you&lt;/i&gt; as part of the &lt;a href=&quot;https://stackexchange.com&quot;&gt;Stack Exchange&lt;/a&gt; network of Q&amp;amp;A sites. With your help, we're working together to build a library of detailed answers to every question about the principles and software that make matter modeling possible.&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2020-06-25T20:51:18.487" LastActivityDate="2020-06-25T20:51:18.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1388" PostTypeId="2" ParentId="562" CreationDate="2020-06-25T20:53:08.013" Score="11" Body="&lt;p&gt;For VCA, as the construction is as simple as &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.7877&quot; rel=&quot;nofollow noreferrer&quot;&gt;averaging&lt;/a&gt; the potentials of atomic species, the main advantage is computational. This is in the sense that it is very simple to change the compositional ratio&#xA;of a solid solution by just changing how you average the potentials, instead of having to work with&#xA;supercells (as you would have to do with SQS or other approaches even for simple ratios).&lt;/p&gt;&#xA;&lt;p&gt;However, simply by doing this, you can imagine that the new potential will not be physical and neither the&#xA;calculations associated to it. To give some examples, properties which depend on the local&#xA;environment won't be correctly reproduced (e.g., the band gap in &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.57.3753&quot; rel=&quot;nofollow noreferrer&quot;&gt;GaAlAsN&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1063/1.119232&quot; rel=&quot;nofollow noreferrer&quot;&gt;GaPN and GaAsN&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Then, how is it that VCA has been shown to be successful for same cases? Well, it happens that for &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.7877&quot; rel=&quot;nofollow noreferrer&quot;&gt;some materials&lt;/a&gt;, the contributions of some atomic species are very similar to each other. Thus, averaging their potentials doesn't change the general properties (so much). Having said this, the real limitation of VCA is that it depends on how similar the parent atomic species are to each other.&lt;/p&gt;&#xA;" OwnerDisplayName="user249" LastEditorUserId="5" LastEditDate="2020-07-01T19:23:25.467" LastActivityDate="2020-07-01T19:23:25.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1389" PostTypeId="7" CreationDate="2020-06-25T20:56:04.180" Score="0" Body="&lt;ul&gt;&#xA;                            &lt;li&gt;Specific issues with developing or using modeling software&lt;/li&gt;&#xA;&lt;li&gt;Techniques for addressing a particular modeling problem&lt;/li&gt;&#xA;                            &lt;li&gt;Real problems or questions that you’ve encountered&lt;/li&gt;&#xA;                        &lt;/ul&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2020-06-25T20:56:04.180" LastActivityDate="2020-06-25T20:56:04.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1390" PostTypeId="7" CreationDate="2020-06-25T20:57:23.937" Score="0" Body="&lt;ul&gt;&#xA;                            &lt;li&gt;Questions without sufficient detail to give a helpful answer&lt;/li&gt;&#xA;                            &lt;li&gt;Questions that are entirely opinion-based&lt;/li&gt;&#xA;                            &lt;li&gt;Questions with too many possible answers or that would require an extremely long answer&lt;/li&gt;&#xA;                        &lt;/ul&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2020-06-25T20:57:23.937" LastActivityDate="2020-06-25T20:57:23.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1391" PostTypeId="1" CreationDate="2020-06-25T23:23:37.050" Score="14" ViewCount="896" Body="&lt;p&gt;I perform my calculations in Q-Chem and would like to make short movies of IR modes. As of now, I render them with IQmol, but I believe graphics properties (colors and resolution) can be much better. Yet, CYLView cannot understand Q-Chem outputs unfortunately.&lt;br&gt;&#xA;What visualization software can be used with a variety of atom/bond styles and adjustable resolution?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2020-06-26T13:37:58.770" LastActivityDate="2020-06-26T13:37:58.770" Title="What is the most user friendly software for frequency visualization rendering?" Tags="|software|q-chem|visualization-software|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1392" PostTypeId="2" ParentId="1391" CreationDate="2020-06-25T23:38:15.243" Score="9" Body="&lt;h1&gt;Jmol&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;Jmol&lt;/a&gt; package is able to do what you want. You can produce the animations below just using &lt;em&gt;point &amp;amp; click&lt;/em&gt; with your mouse.&lt;/p&gt;&#xA;&lt;p&gt;But you can also use its scripting capabilities to work with batch files, and make the process all automatic.&lt;/p&gt;&#xA;&lt;p&gt;As it is coded in Java, you can used in any operative system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www2.ess.ucla.edu/%7Eschauble/molecular_vibrations.htm&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; are some examples. Below the results for &lt;span class=&quot;math-container&quot;&gt;$CH_4$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$T_d$&lt;/span&gt; symmetry):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$o_1 = 3025.5\, cm^{-1}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$A_1$&lt;/span&gt; Symmetry)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pEmvB.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pEmvB.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$o_2 = 1582.7\, cm^{-1}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; Symmetry)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/L2udO.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/L2udO.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$o_3 = 3156.8\, cm^{-1}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$F_2$&lt;/span&gt; Symmetry)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GfPdq.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GfPdq.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$o_4 = 1367.4\, cm^{-1}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$F_2$&lt;/span&gt; Symmetry)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FmC1b.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FmC1b.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-06-26T12:17:30.973" LastActivityDate="2020-06-26T12:17:30.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1393" PostTypeId="2" ParentId="1391" CreationDate="2020-06-26T00:49:01.937" Score="13" Body="&lt;h2&gt;&lt;strong&gt;VMD Normal Mode Wizard&lt;/strong&gt;&lt;/h2&gt;&#xA;&lt;p&gt;If you're goal is to create high quality visualizations of vibrations I recommend VMD. It's highly customizable in terms of colors, resolution, and representation.&lt;/p&gt;&#xA;&lt;p&gt;The setup however, is a little bit painful as the normal mode (NMD) input file has to be specially prepared in atomic units and has a special format (see below).&lt;/p&gt;&#xA;&lt;p&gt;The official details can be found &lt;a href=&quot;http://www.ks.uiuc.edu/Research/vmd/plugins/nmwiz/&quot; rel=&quot;noreferrer&quot;&gt;here.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;One benefit however, is that the in addition to creating a movie which you can show in your presentation you can create static images like this which show the vibration vector&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VDn8B.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VDn8B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is my &amp;quot;NMD&amp;quot; file which was used in VMD to create this image.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;names C C C C H H H H H H C C C C H H H H H H&#xA;coordinates 0.419783 -0.742862 0.883452 -0.036356 0.490734 0.325996 0.251234 0.764637 -1.047649 0.039963 -0.211417 -2.131132 0.176898 -0.924957 1.920794 0.324685 -1.620253 0.262458 -0.109550 1.336747 0.988139 0.216590 1.797666 -1.352741 -0.135041 -1.246035 -1.916959 0.240780 0.062286 -3.148909 2.889548 1.383592 2.407869 2.645651 0.115596 2.054427 2.219184 -0.415514 0.727746 2.398198 0.407775 -0.493158 3.167189 1.622583 3.418802 2.857201 2.206403 1.717940 2.728662 -0.638593 2.822578 2.541096 -1.440669 0.600368 2.721145 1.425776 -0.398300 2.693411 -0.087720 -1.397883&#xA;mode 0.029 -0.016  0.006 0.018 0.034 -0.077  0.045 0.058 0.153 -0.012  -0.073  -0.082  -0.002  -0.001  0.000 -0.003  -0.001  0.001 0.003 0.001 0.000 -0.015  0.001 0.001 -0.002  0.002 -0.001  0.004 -0.002  0.001 0.000 -0.000  -0.001  0.003 0.000 -0.000  -0.027  -0.016  0.020 -0.050  0.018 -0.021  -0.000  0.000 -0.000  0.000 0.000 -0.000  -0.000  0.000 -0.000  0.004 0.000 0.001 0.004 -0.003  0.001 -0.000  -0.001  -0.002&#xA;mode 0.002 0.005 0.003 -0.028  -0.027  0.083 0.138 0.009 -0.050  -0.023  -0.011  -0.013  -0.002  0.001 -0.000  -0.000  0.000 -0.001  -0.003  -0.001  -0.000  -0.003  -0.001  0.001 -0.000  0.000 -0.000  0.001 0.000 0.001 -0.000  0.001 -0.000  -0.000  -0.002  -0.000  0.002 -0.002  0.005 -0.102  0.033 -0.036  0.000 -0.000  0.000 0.000 -0.000  -0.000  0.000 0.000 0.000 -0.000  -0.000  0.001 0.012 -0.003  0.003 0.008 -0.001  0.002&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-06-26T00:49:01.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1394" PostTypeId="1" AcceptedAnswerId="1398" CreationDate="2020-06-26T08:44:44.827" Score="40" ViewCount="2167" Body="&lt;p&gt;In Kohn's &lt;a href=&quot;https://www.nobelprize.org/uploads/2018/06/kohn-lecture.pdf&quot; rel=&quot;noreferrer&quot;&gt;Nobel Lecture&lt;/a&gt;, he claimed that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&amp;quot;In general the many-electron wave function &lt;span class=&quot;math-container&quot;&gt;$\Psi(\mathbf{r}_1,\ldots,\mathbf{r}_N)$&lt;/span&gt; for a system of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons is not a legitimate scientific concept, when &lt;span class=&quot;math-container&quot;&gt;$N\geq N_0$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$N_0\simeq10^3$&lt;/span&gt;.&amp;quot;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;He explains this in two ways: the first is that &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; cannot be calculated with sufficient accuracy, and the second that is cannot be stored with sufficient accuracy. As far as I understand, what he had in mind here was comparing traditional wave function methods in quantum chemistry (e.g. configuration interaction) with density functional theory, which is based on the density rather than the wave function.&lt;/p&gt;&#xA;&lt;p&gt;My question concerns Monte Carlo techniques. &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.33&quot; rel=&quot;noreferrer&quot;&gt;Quantum Monte Carlo&lt;/a&gt; and stochastic extensions to traditional quantum chemistry techniques, for example &lt;a href=&quot;https://www.nature.com/articles/nature11770?draft=collection&amp;amp;proof=true&quot; rel=&quot;noreferrer&quot;&gt;Full Configuration Interaction Quantum Monte Carlo&lt;/a&gt;, could be called wave function methods in that the central quantity is the wave function, and are being almost routinely used for very high accuracy solid state calculations with large &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;. Additionally, their nice scaling properties suggest that they will be able to exploit future parallel computer resources effectively.&lt;/p&gt;&#xA;&lt;p&gt;So the question is: how should we view quantum Monte Carlo techniques in view of Kohn's statement? Could we say that these techniques allow us to bypass the issue Kohn identified with wave functions by only &lt;em&gt;sampling&lt;/em&gt; the wave function rather than calculating/storing it?&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-06-26T23:24:49.273" LastActivityDate="2020-06-29T20:15:50.613" Title="Was Walter Kohn wrong about this?" Tags="|density-functional-theory|ab-initio-calculations|quantum-chemistry|quantum-monte-carlo|history|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1395" PostTypeId="2" ParentId="1360" CreationDate="2020-06-26T11:14:54.963" Score="11" Body="&lt;p&gt;I'd just briefly add that among other things, chemical graph theory is extensively used for computing so-called &amp;quot;molecular descriptors&amp;quot;, which are used to capture some &amp;quot;common properties&amp;quot; of a certain class of molecules.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9783527628766&quot; rel=&quot;noreferrer&quot;&gt;Todescini and Consonni, Molecular Descriptors for Chemoinformatics&lt;/a&gt;&#xA;already a bit dated, offers an extensive collection of 5000+ descriptors.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://dblp.uni-trier.de/pers/g/Gutman:Ivan.html&quot; rel=&quot;noreferrer&quot;&gt;Prof. Ivan Gutman's list of publications&lt;/a&gt;&#xA;would be a worthwhile reference collection.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="84" LastEditorUserId="84" LastEditDate="2020-06-29T01:23:22.957" LastActivityDate="2020-06-29T01:23:22.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1396" PostTypeId="2" ParentId="157" CreationDate="2020-06-26T13:35:32.857" Score="13" Body="&lt;h2&gt;stk (Supramolecular Toolkit)&lt;/h2&gt;&#xA;&lt;p&gt;Disclaimer: I am the author of stk.&lt;/p&gt;&#xA;&lt;p&gt;stk, &lt;a href=&quot;https://github.com/lukasturcani/stk&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/lukasturcani/stk&lt;/a&gt;, is an open-source Python library, which, among other things, is able to carry out automated material design through evolutionary algorithms.&lt;/p&gt;&#xA;&lt;p&gt;stk allows you to customize the evolutionary algorithms, by specifying your own mutation and crossover operations you want to use, which are appropriate for your material, but it also provides some default and built-in ones.&lt;/p&gt;&#xA;&lt;p&gt;The framework by which stk constructs materials is flexible and extendable, so you can define your own materials, if the built-in ones are not the ones you are interested in. At time of writing&#xA;organic cages, metal-organic cages, metal complexes, rotaxanes, macrocycles, covalent organic frameworks, linear polymers are all built-in. If you ask him, the author is also quite likely to add any materials you might be interested in, or if you file an issue on GitHub.&lt;/p&gt;&#xA;&lt;p&gt;stk also let's you deposit any calculated properties and constructed molecules into a MongoDB database for easy future retrieval.&lt;/p&gt;&#xA;&lt;p&gt;stk documentation, &lt;a href=&quot;https://stk.readthedocs.io/&quot; rel=&quot;noreferrer&quot;&gt;https://stk.readthedocs.io/&lt;/a&gt;, contains tutorials on how to run and customize the evolutionary algorithm.&lt;/p&gt;&#xA;&lt;p&gt;Note that stk does not include computational chemistry packages. Normally you will define a fitness function of the form&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def get_fitness_value(molecule):&#xA;&#xA;    # get fitness value somehow&#xA;    # for example, by using rdkit or ASE to get physical properties of the molecule&#xA;    # or writing the molecule to a file and then executing a computational chemistry package&#xA;    # and extracting the result&#xA;&#xA;    return the_calculated_fitness_value&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You would then execute the evolutionary algorithm in the following way&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import stk&#xA;import pymongo&#xA;&#xA;ea = stk.EvolutionaryAlgorithm(&#xA;    fitness_calculator=stk.FitnessFunction(get_fitness_value),&#xA;&#xA;    # Other options for the evolutionary algorithm go here, such&#xA;    # the mutation, crossover, selection operations you want to use&#xA;    # and the initial population&#xA;)&#xA;&#xA;# Using a MongoDB is optional, but very useful.&#xA;db = stk.ConstructedMoleculeMongoDb(pymongo.MongoClient())&#xA;&#xA;# Run the EA for 50 generations.&#xA;for gen_index, generation in enumerate(ea.get_generations(50)):&#xA;    # Do stuff with the molecules in the generation.&#xA;    for mol_index, molecule_record in enumerate(generation.get_molecule_records()):&#xA;        # Like putting them into a MongoDB database.&#xA;        db.put(molecule_record.get_molecule())&#xA;        # Or writing them to a file&#xA;        molecule_record.get_molecule().write(f'{gen_index}_{mol_index}.mol')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="956" LastEditorUserId="5" LastEditDate="2020-06-26T19:27:15.767" LastActivityDate="2020-06-26T19:27:15.767" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1397" PostTypeId="2" ParentId="157" CreationDate="2020-06-26T16:35:58.073" Score="8" Body="&lt;p&gt;Structure prediction involves two steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Propose candidate structures. This step is necessary to explore configuration space, and different codes use different strategies. Examples of methods that have been extensively used in the solid state include &lt;a href=&quot;https://www.mtg.msm.cam.ac.uk/Codes/AIRSS&quot; rel=&quot;noreferrer&quot;&gt;stochastic&lt;/a&gt;, &lt;a href=&quot;https://web.archive.org/web/20180201112504/http://uspex.stonybrook.edu/uspex.html&quot; rel=&quot;noreferrer&quot;&gt;evolutionary&lt;/a&gt;, or  &lt;a href=&quot;http://www.calypso.cn&quot; rel=&quot;noreferrer&quot;&gt;particle swarm&lt;/a&gt; algorithms to generate candidate structures. Features that can help when generating candidate structures include the use of symmetry, knowledge about the chemistry of the material (e.g. stoichiometry), or partial knowledge about the structure (e.g. lattice constants but no atomic positions). These features effectively reduce the high dimensionality of the configuration space that is being explored, thus greatly reducing the computational cost. However, even when absolutely nothing is known about a material, these methods can provide good candidate structures.&lt;/li&gt;&#xA;&lt;li&gt;Rank the candidate structures according to their energy. The thermodynamically stable structure of the system is the one with the lowest energy (or enthalpy at finite pressure, or Helmholtz free energy at finite temperature, or Gibbs free energy at finite pressure and temperature). In structure prediction, this problem is reduced to finding the lowest energy structure from the subset of candidate structures identified in the first step. Calculations are typically performed at the DFT level for solid state structure predictions, but of course can in principle be performed at any level of theory, with the only limitation being computational resources avaible (there may be &lt;em&gt;many&lt;/em&gt; candidate structures).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;How reliable are these methods? It is impossible to prove purely theoretically that a given structure is the ground state of a material. You could always have missed the real structure in your pool of candidate structures (e.g. due to computational limitations you may have searched for structures up to 100 atoms in the primitive cell, but the correct structure may have 200 atoms). This is why this is such a challenging problem. However, in practice structure prediction methods have been quite successful at predicting correct structures.&lt;/p&gt;&#xA;&lt;p&gt;For actual codes, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_structure_prediction&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia page&lt;/a&gt; has a reasonable list, and I would encourage everyone to add to the list.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-26T16:35:58.073" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1398" PostTypeId="2" ParentId="1394" CreationDate="2020-06-26T17:23:42.090" Score="39" Body="&lt;p&gt;Kohn is easily one of my favorite humans of all time, and he was a role model to whom I looked up in great admiration for most of my academic life; in fact before this site was created, I &lt;a href=&quot;https://area51.meta.stackexchange.com/a/31086/190792&quot;&gt;proposed&lt;/a&gt; that we name it after him.&lt;/p&gt;&#xA;&lt;p&gt;However I completely disagree with the sentence that you have quoted. Keep in mind that even though the Nobel Lecture was in 1999, Kohn was born in 1923, so I was not alive for much of his life, and I don't know what possible connotations might have surrounded the word &amp;quot;legitimate&amp;quot; back in those days; but certainly the way we use the word &amp;quot;legitimate&amp;quot; nowadays, and every dictionary definition of legitimate I've seen, would indicate that he might have been speaking in hyperbole.&lt;/p&gt;&#xA;&lt;p&gt;Let me address now, some of the specific matters in your question:&lt;/p&gt;&#xA;&lt;h2&gt;We have accurate wavefunctions for systems with far more than &lt;span class=&quot;math-container&quot;&gt;${\small N=10^3}$&lt;/span&gt;&lt;/h2&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1352/5&quot;&gt;this answer&lt;/a&gt; I recently mentioned that CCSD(T) with local orbital methods &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00511&quot; rel=&quot;noreferrer&quot;&gt;have calculated&lt;/a&gt; wavefunctions for systems with up to 1023 atoms; in this case it was a lipid transfer protein (PDB: 1N89) for which I'd estimate the number of electrons is about 10,000. Kohn may have written &lt;span class=&quot;math-container&quot;&gt;$N\simeq 10^3$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$N = 10^3$&lt;/span&gt;, but the &lt;em&gt;order of magnitude&lt;/em&gt; turned out to be wrong 20 years after that quote. Surely the order of magnitude will also increase again.&lt;/p&gt;&#xA;&lt;h2&gt;Accuracy&lt;/h2&gt;&#xA;&lt;p&gt;Energy differences with CCSD(T) or even LNO-CCSD(T) in the 4-zeta basis set that they used in the above example, are likely to be accurate to within 1.5 kcal/mol for a molecule like this, whereas &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;DFT is unlikely to give you anything with an error less than 4 kcal/mol&lt;/a&gt; unless you use hybrids (which by definition use wavefunctions). A good energy difference doesn't necessarily mean an accurate wavefunction, but&#xA;coupled cluster wavefunctions are not bad at all (otherwise you wouldn't be able to calculate accurate properties like polarizabilities).&lt;/p&gt;&#xA;&lt;h2&gt;Storage&lt;/h2&gt;&#xA;&lt;p&gt;The wavefunction in the above case is stored via cluster amplitudes, for which we can store billions (in fact trillions in the largest cases)&#xA;of them. Since cluster amplitudes appear in the argument of an exponential, we actually get CI coefficients for 100% of the non-zero determinants. So storage of a big wavefunction is no problem &lt;em&gt;&lt;strong&gt;when you use a compact representation&lt;/strong&gt;&lt;/em&gt;. Sure there will be a point at which classical computers can no longer accurately store quantum wavefunctions, but there will also be a point at which electron densities can't be stored either, so in that sense why not call the density &amp;quot;illegitimate&amp;quot; too? Furthermore, not being able to &amp;quot;store&amp;quot; the wavefunction is only a problem &lt;strong&gt;if using a classical storage device,&lt;/strong&gt; whereas if you use qubits instead of bits the statement no longer has legs.&lt;/p&gt;&#xA;&lt;h2&gt;Quantum Monte Carlo (QMC)&lt;/h2&gt;&#xA;&lt;p&gt;FCIQMC, VMC, DMC, AFQMC, and similar methods, are all wavefunction methods. They &lt;em&gt;&lt;strong&gt;are&lt;/strong&gt;&lt;/em&gt; wavefunctions methods, whereas you wrote that they &amp;quot;could be called wave function methods, in that...&amp;quot;. They do in fact manage to represent wavefunctions in huge Hilbert spaces, often by taking advantage of sparsity of the wavefunction, but using a &lt;em&gt;&lt;strong&gt;compact representation&lt;/strong&gt;&lt;/em&gt; as in the case of coupled cluster, means that you don't even need a &amp;quot;sparse&amp;quot; representation or a &amp;quot;stochastic sampling&amp;quot;, you can represent the whole wavefunction by storing only the argument of the exponential. I am not trying to take shine away from QMC; I say all this as a contributor to a major FCIQMC code, and having used FCIQMC in papers &lt;a href=&quot;https://ui.adsabs.harvard.edu/abs/2016isms.confETK07D/abstract&quot; rel=&quot;noreferrer&quot;&gt;with the inventor of FCIQMC&lt;/a&gt; and also &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4990673&quot; rel=&quot;noreferrer&quot;&gt;separately on my own&lt;/a&gt; and even on &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; I put on arXiv only two days ago. FCIQMC has its place as one of the best methods for ultra-high accuracy in large multi-reference systems, but it is not needed in the proof that Kohn's statement is wrong: coupled cluster can be very accurate on even bigger systems if they don't have too much multi-reference character.&lt;/p&gt;&#xA;&lt;h2&gt;Number of electrons is actually a &lt;em&gt;red herring&lt;/em&gt;&lt;/h2&gt;&#xA;&lt;p&gt;The problem with wavefunctions when using &lt;em&gt;classical computers&lt;/em&gt; has less to do with the number of electrons and more to do with its structure:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Bosonic wavefunctions&lt;/strong&gt; don't suffer from the fermionic sign-problem, so you can represent them with a Hartree product, and might be able to store a larger wavefunction than you can store a density! Kohn's statement is about electronic wavefunctions, but this bullet serves as a reminder that Kohn's argument is not so much about fundamental physics and ontology, than it is about &amp;quot;computability&amp;quot; (you probably already agreed with this, so this bullet is more for other people).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Fermionic wavefunctions involving only one determinant&lt;/strong&gt; (which can still be accurate for a very single-reference system) are very simple: instead of the &lt;span class=&quot;math-container&quot;&gt;$\binom{M}{N}$&lt;/span&gt; type scaling for the number of determinants in a full CI expansion, &lt;em&gt;you only have one term&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Fermionic wavefunctions involving many determinants but only static correlation&lt;/strong&gt;, can be represented by &lt;em&gt;matrix product states&lt;/em&gt; and calculated using the polynomially scaling DMRG.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Fermionic wavefunctions involving many determinants but only dynamic correlation&lt;/strong&gt;, can be represented by &lt;em&gt;coupled cluster ansatze&lt;/em&gt; which are also polynomially scaling.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Fermionic wavefunctions involving infinitely many determinants&lt;/strong&gt; can also be represented by a &lt;em&gt;compact representation&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The problem is more about how many digits you need for each of the CI coefficients. Then you quickly see that the computational complexity of &lt;span class=&quot;math-container&quot;&gt;$2^N$&lt;/span&gt; vs &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt; is irrelevant and what really matters is something more subtle, which is: how complicated is the wavefunction, not how many electrons are there.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;50 electrons in a CAS(50,50) is currently an absolutely &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5063376&quot; rel=&quot;noreferrer&quot;&gt;brutal calculation&lt;/a&gt; but 10,000 electrons in a CCSD(10000,44000) was done easily in the paper listed above. So there are cases where &lt;span class=&quot;math-container&quot;&gt;$N=50$&lt;/span&gt; electrons is harder than &lt;span class=&quot;math-container&quot;&gt;$N=10^4$&lt;/span&gt;, and in those highly multi-reference cases, good luck getting an accurate energy with a single-reference method like DFT!&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-06-29T20:15:50.613" LastActivityDate="2020-06-29T20:15:50.613" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1399" PostTypeId="2" ParentId="1025" CreationDate="2020-06-26T19:59:28.333" Score="6" Body="&lt;p&gt;One thing the other answers haven't mentioned is the zero point and thermal corrections to the BDE.&lt;/p&gt;&#xA;&lt;p&gt;As mentioned in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse_potential&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia Morse potential article&lt;/a&gt;, a geometry optimization will take you, by definition to the equilibrium bond length (&lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt;). If you use this as the low energy state, you're calculating &lt;span class=&quot;math-container&quot;&gt;$D_e$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VddPom.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VddPom.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The problem is that a quantum harmonic oscillator always has &lt;a href=&quot;https://en.wikipedia.org/wiki/Zero-point_energy&quot; rel=&quot;noreferrer&quot;&gt;zero point energy&lt;/a&gt; even at 0K. So a &lt;em&gt;better&lt;/em&gt; answer requires the zero-point vibrational energy. Usually a vibrational / frequency calculation will also produce the thermal corrections, e.g. to 300K since there will be some thermal occupation of higher vibrational levels.&lt;/p&gt;&#xA;&lt;p&gt;I've seen a few papers from groups that specialize in accurate thermochemistry, and their procedures are roughly:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Optimize the geometry, e.g. B3LYP-D3BJ / def2-TZVP&lt;/li&gt;&#xA;&lt;li&gt;Calculate vibrational levels (for ZVPE and thermal correction) at the same level&lt;/li&gt;&#xA;&lt;li&gt;Calculate the energies (bottom of the well) with DLPNO-CCSD(T) / def2-QZVP&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.jpca.7b03195&quot; rel=&quot;noreferrer&quot;&gt;Efficient DLPNO–CCSD(T)-Based Estimation of Formation Enthalpies …&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1002/jcc.25763&quot; rel=&quot;noreferrer&quot;&gt;Generalized Prediction of Enthalpies of Formation Using DLPNO‐CCSD(T) Ab Initio Calculations…&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You ned the optimized geometry and DLPNO-CCSD(T) energies for the molecule and fragments. In your case, where the fragments are also molecules (unlike the diatomic in the figures) you'll probably also want the ZPE and thermal correction of the fragments.&lt;/p&gt;&#xA;&lt;p&gt;I won't debate the merits of the various CCSD(T) schemes - I think &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1352/30&quot;&gt;Nike's answer&lt;/a&gt; already did that.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-06-26T19:59:28.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1400" PostTypeId="5" CreationDate="2020-06-26T21:55:12.047" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-26T21:55:12.047" LastActivityDate="2020-06-26T21:55:12.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1401" PostTypeId="4" CreationDate="2020-06-26T21:55:12.047" Score="0" Body="For questions about modeling proteins" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-26T21:55:12.047" LastActivityDate="2020-06-26T21:55:12.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1402" PostTypeId="5" CreationDate="2020-06-26T21:56:44.870" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-26T21:56:44.870" LastActivityDate="2020-06-26T21:56:44.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1403" PostTypeId="4" CreationDate="2020-06-26T21:56:44.870" Score="0" Body="Questions concerning the PBS queue management system." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-26T21:56:44.870" LastActivityDate="2020-06-26T21:56:44.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1404" PostTypeId="5" CreationDate="2020-06-26T22:03:40.903" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-06-26T22:03:40.903" LastActivityDate="2020-06-26T22:03:40.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1405" PostTypeId="4" CreationDate="2020-06-26T22:03:40.903" Score="0" Body="For questions about applying informatics techniques to study chemical systems." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-12-25T20:47:19.720" LastActivityDate="2021-12-25T20:47:19.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1406" PostTypeId="1" AcceptedAnswerId="1407" CreationDate="2020-06-27T03:09:08.657" Score="16" ViewCount="1120" Body="&lt;p&gt;I used VASP to do the band structure calculation on Graphene. Originally I would expect that the Dirac cone can be observed in the K point. If we watched qualitatively, we can see this behavior.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Q5cDp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Q5cDp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;But when I zoom in the region where the conduction band touches with the valences band, a bandgap can be observed as shown in the figure.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/v20li.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/v20li.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;That's weird because I've already adjusted my K point meshing to be an odd number and increase the number of meshing, it doesn't help. The upper band was still lifted.&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2020-06-27T03:34:55.867" LastActivityDate="2020-06-27T12:29:11.460" Title="Why is the band gap of graphene &quot;opened&quot; in this VASP calculation?" Tags="|density-functional-theory|vasp|band-structure|graphene|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1407" PostTypeId="2" ParentId="1406" CreationDate="2020-06-27T12:29:11.460" Score="14" Body="&lt;p&gt;The reason why graphene has Dirac points at K and &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt;K is because of a combination of time reversal and inversion symmetries. Therefore, if you impose these symmetries in your VASP calculation, there is no reason why there should be a gap at K. Even if you do not impose these symmetries explicitly, you should be able to get the degeneracy to very high accuracy (better than what you are showing) if you do a well converged calculation in terms of the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points that you are using to sample the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;So what could be going wrong? From the partial information that you provide, my best guess is that: (i) you don't include the symmetries in the calculation, (ii) the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid you are using for the self-consistent part of the calculation is not fine enough, and in particular it does not explicitly include the K point, and (iii) when you then do the non-self-consistent calculation to obtain the band structure along the high-symmetry lines, then you have very few points along the lines and the code simply naively interpolates between them to generate the plot.&lt;/p&gt;&#xA;&lt;p&gt;So what would I suggest you do? The first thing is to impose the relevant symmetries. The second is to make sure that the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point you are using in the self-consistent calculations is large enough, and in particular that it explicitly includes the K point, and (iii) that in the non-self-consistent calculation you include a large number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points along the high symmetry points near K.&lt;/p&gt;&#xA;&lt;p&gt;All of this is based on my interpretation of the partial information you provide.&lt;/p&gt;&#xA;&lt;p&gt;The discussion above is somewhat different if you included spin-orbit coupling. In that case, a gap develops at the K point in graphene, an observation that led to the field of &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.95.226801&quot; rel=&quot;noreferrer&quot;&gt;topological insulators&lt;/a&gt;. However, I don't think that this explains your results, because spin-orbit coupling in graphene is &lt;em&gt;very&lt;/em&gt; small, on the &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;eV scale, orders of magnitude smaller than what you are seeing. For this reason spin-orbit coupling can be neglected when doing calculations for graphene, so I imagine that this is what you are doing.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-06-27T12:29:11.460" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1408" PostTypeId="1" CreationDate="2020-06-27T15:28:02.990" Score="11" ViewCount="1084" Body="&lt;p&gt;I was trying to convert a crystal structure into a LAMMPS data file in Avogadro but whenever I type .lmpdat as an extension, it says &amp;quot;The file name is not valid&amp;quot;. Can you tell me any solution?&lt;/p&gt;&#xA;&lt;p&gt;i.e. I have also tried .lmp extension&lt;/p&gt;&#xA;&lt;p&gt;I have been following this tutorial:&#xA;&lt;a href=&quot;https://avogadro.cc/docs/extensions/lammps-input-for-water/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://avogadro.cc/docs/extensions/lammps-input-for-water/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="961" LastEditorUserId="961" LastEditDate="2020-07-12T05:35:39.333" LastActivityDate="2020-07-12T05:35:39.333" Title="How to convert a molecular structure made in Avogadro to a LAMMPS coordinate file?" Tags="|software|lammps|avogadro|" AnswerCount="0" CommentCount="10" ClosedDate="2020-07-11T19:15:59.193" ContentLicense="CC BY-SA 4.0" />
  <row Id="1409" PostTypeId="2" ParentId="1355" CreationDate="2020-06-27T21:23:42.897" Score="19" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Can someone explain in detail the impact of any of the multiplication algorithms scaling better than N&lt;sup&gt;2&lt;/sup&gt;, for some practical application?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;An actual application is right in front of our eyes: &lt;a href=&quot;https://en.wikipedia.org/wiki/Digital_signature&quot; rel=&quot;noreferrer&quot;&gt;digital signature&lt;/a&gt; using &lt;a href=&quot;https://en.wikipedia.org/wiki/RSA_(cryptosystem)&quot; rel=&quot;noreferrer&quot;&gt;RSA&lt;/a&gt;. If I click on the lock icon for the present page in my browser, then on the arrow on the right of &lt;em&gt;Connection secure&lt;/em&gt;, then &lt;em&gt;More Information&lt;/em&gt;, then &lt;em&gt;View Certificate&lt;/em&gt;, I see that the connection uses this RSA-2048 public key:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/e5G6h.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e5G6h.png&quot; alt=&quot;public key&quot; /&gt;&lt;/a&gt;&#xA;This means that at each new connection, the browser performs modular arithmetic with 2048-bit integers, that is 616-decimal digit integers.&lt;/p&gt;&#xA;&lt;p&gt;In order to authenticate the server (or, in a previous operation, to check its certificate, which must be done at least once on the first connection), it is computed A&lt;sup&gt;65537&lt;/sup&gt; mod M for the 2048-bit M in the picture, and A of the same size. Since 65537 = 2&lt;sup&gt;16&lt;/sup&gt;+1, that requires 17 modular multiplications. Each can be (and often is) performed by multiplying two 2048-bit integers into a 4096-bit integer, followed by modular reduction by way of an other multiplication of 2048-bit integers.&lt;/p&gt;&#xA;&lt;p&gt;That arithmetic is performed using &lt;em&gt;limbs&lt;/em&gt; (the equivalent of decimal digits) that typically are 32-bit (sometime 64-bit, or 16-bit on low-end mobile devices). It is thus performed multiplication of integers of width N = 64 limbs. With the schoolbook algorithm, each multiplication requires N&lt;sup&gt;2&lt;/sup&gt; multiplications of two limbs and additions of the result, each requiring in the order of 50 CPU clock cycles. At 1 GHz, we are talking 17×2×64×64×50×10&lt;sup&gt;-9&lt;/sup&gt; s that is ≈7 ms, which is not negligible because establishing an https connection (or checking a certificate) is so common.&lt;/p&gt;&#xA;&lt;p&gt;In order to reduce delay and power consumption, it pays to use at least the simplest of the below-O(N&lt;sup&gt;2&lt;/sup&gt;) multiplication algorithms: &lt;a href=&quot;https://en.wikipedia.org/wiki/Karatsuba_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Karatsuba multiplication&lt;/a&gt;, which is O(N&lt;sup&gt;≈1.6&lt;/sup&gt;). There is a threshold before that pays (especially on modern CPUs with fast multipliers), which can be down to about 10 limbs (&lt;a href=&quot;https://www.cymatics.cc/Karatsuba-Multiplication.html&quot; rel=&quot;noreferrer&quot;&gt;reference&lt;/a&gt;). For 64×64 limbs, Karatsuba would typically reduce computing time by a factor of nearly (4/3)&lt;sup&gt;2&lt;/sup&gt; ≈ 1.7, which is better than nothing. That's part of why implementations based on &lt;a href=&quot;https://gmplib.org/&quot; rel=&quot;noreferrer&quot;&gt;GMP&lt;/a&gt; are faster. For low-end devices with 16-bit limbs, or when doing 4096-bit RSA, that's a factor (4/3)&lt;sup&gt;3&lt;/sup&gt; ≈ 2.3, and quite worth using.&lt;/p&gt;&#xA;&lt;p&gt;On the server side, there are more computations (about 50 times more work) and that can sometime represent a sizable fraction of the total workload, but the incentive to use Karatsuba for the bulk of the work is actually lower: the numbers manipulated are half as wide, and sometime the limbs are bigger.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;There are other applications of &lt;a href=&quot;https://en.wikipedia.org/wiki/Karatsuba_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Karatsuba&lt;/a&gt; and its generalization &lt;a href=&quot;https://en.wikipedia.org/wiki/Toom%E2%80%93Cook_multiplication&quot; rel=&quot;noreferrer&quot;&gt;Toom-Cook&lt;/a&gt; in cryptography, not limited to RSA; e.g. batch verification of ECC signatures, see Daniel J. Bernstein's &lt;a href=&quot;https://binary.cr.yp.to/bbe-20090604.pdf&quot; rel=&quot;noreferrer&quot;&gt;Batch binary Edwards&lt;/a&gt;. In the specialized subfield of cryptanalysis, there even are uses of &lt;a href=&quot;https://en.wikipedia.org/wiki/Sch%C3%B6nhage%E2%80%93Strassen_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Schönhage-Strassen&lt;/a&gt;, e.g. &lt;a href=&quot;http://www.crypto-uni.lu/jscoron/publications/iso97962joc.pdf#page=10&quot; rel=&quot;noreferrer&quot;&gt;cryptanalysis of ISO 9796-2 signatures&lt;/a&gt;. It's in &lt;a href=&quot;https://gmplib.org/&quot; rel=&quot;noreferrer&quot;&gt;GMP&lt;/a&gt; for a reason.&lt;/p&gt;&#xA;&lt;p&gt;The recent &lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-02070778/document&quot; rel=&quot;noreferrer&quot;&gt;Harvey-Hoeven algorithm&lt;/a&gt; is a satisfying achievement, but is not going to be used in practical applications. I even doubt that it can ever be implemented: it seems to work for numbers in the order of 1729&lt;sup&gt;12&lt;/sup&gt; bits, which is about 10&lt;sup&gt;22&lt;/sup&gt; times the RAM in a &lt;a href=&quot;https://en.wikipedia.org/wiki/Fugaku_(supercomputer)&quot; rel=&quot;noreferrer&quot;&gt;current supercomputer&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="917" LastEditorUserId="917" LastEditDate="2020-06-29T02:32:37.283" LastActivityDate="2020-06-29T02:32:37.283" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1410" PostTypeId="1" CreationDate="2020-06-27T21:38:37.567" Score="12" ViewCount="156" Body="&lt;p&gt;I've been referring to Dr Mohri's paper [&lt;a href=&quot;https://link.springer.com/article/10.1007/s11837-013-0738-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1007/s11837-013-0738-5&lt;/a&gt;] for the cluster variation method (CVM). I wish to calculate the configurational entropy of a binary FCC system.&lt;/p&gt;&#xA;&lt;p&gt;Cluster probabilities are probabilities of certain clusters existing in the system. Let's consider nearest neighbour (NN) pairs as clusters. A binary FCC cell (let's say AB type) can have &lt;span class=&quot;math-container&quot;&gt;$\ce{AA}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{AB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{BA}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\ce{BB}$&lt;/span&gt; pairs. For this, &lt;span class=&quot;math-container&quot;&gt;$y_{\ce{A,A}}$&lt;/span&gt; would be the probability of &lt;span class=&quot;math-container&quot;&gt;$\ce{AA}$&lt;/span&gt; pairs existing. If the total number of pairs were &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; then the number of &lt;span class=&quot;math-container&quot;&gt;$\ce{AA}$&lt;/span&gt; pairs would be &lt;span class=&quot;math-container&quot;&gt;$N\cdot y_{\ce{A,A}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the CVM, we define &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-point correlation functions &lt;span class=&quot;math-container&quot;&gt;$\xi_n$&lt;/span&gt;, which are used to calculate cluster probabilities, as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\xi_n=\frac{\sum_{p_1}\sum_{p_2}...\sum_{p_n}\sigma(p_1)\sigma(p_2)...\sigma(p_n)}{N(n)}\label{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the case of NN pairs, we use a 2-point correlation function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}\xi_2=\frac{\sum_{p}\sum_{p'}\sigma(p)\sigma(p')}{N(2)}\label{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N(2)$&lt;/span&gt; is the total number of pairs in the crystal (cell), &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; are each of the lattice points, &lt;span class=&quot;math-container&quot;&gt;$p'$&lt;/span&gt; are the NN points of &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\sigma(p)$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\sigma(p')$&lt;/span&gt;) are spin variables which are taken to be &lt;span class=&quot;math-container&quot;&gt;$+1$&lt;/span&gt; if &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt; is at &lt;span class=&quot;math-container&quot;&gt;$p/p'$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt; if &lt;span class=&quot;math-container&quot;&gt;$\ce{B}$&lt;/span&gt; is at &lt;span class=&quot;math-container&quot;&gt;$p/p'$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The general probability formula is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$y_{{i_1}{i_2}...{i_n}}=\frac{1}{2^n}\bigg[1+\sum_{j=1}^nC_j(i_{k})\xi_j\bigg]\tag{3}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$C_j(i_k)$&lt;/span&gt; is all the unique j-member combinations of &lt;span class=&quot;math-container&quot;&gt;$i_k$&lt;/span&gt; values.&lt;/p&gt;&#xA;&lt;p&gt;I understand the correlation formula up to pairs. I want to use it for bigger clusters like NN triangles and NN tetrahedrons.&lt;/p&gt;&#xA;&lt;p&gt;Let's consider NN triangles now. In the &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt;-point correlation function formula, we'll have &lt;span class=&quot;math-container&quot;&gt;$p_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_1$&lt;/span&gt;'s NN &lt;span class=&quot;math-container&quot;&gt;$p_2$&lt;/span&gt;, and one of these:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$p_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_2$&lt;/span&gt;'s NN &lt;span class=&quot;math-container&quot;&gt;$p_3$&lt;/span&gt;, that is the 3&lt;sup&gt;rd&lt;/sup&gt; vertex of all possible NN triangular clusters containing &lt;span class=&quot;math-container&quot;&gt;$p_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_2$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$p_2$&lt;/span&gt;'s NN.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I assumed 1 to be correct since it makes sense for the idea of considering NN triangular clusters, but when I use it I get negative values for certain cluster probabilities.&lt;/p&gt;&#xA;&lt;p&gt;To be specific, I used it for NN tetrahedrons which have &lt;span class=&quot;math-container&quot;&gt;$2^4 = 16$&lt;/span&gt; possible clusters (&lt;span class=&quot;math-container&quot;&gt;$\ce{AAAA}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{BBBB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{AAAB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{AABB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{BBBA}$&lt;/span&gt;, and so on). I got a negative value for the cluster probability for &lt;span class=&quot;math-container&quot;&gt;$\ce{BBBB}$&lt;/span&gt;, i.e. &lt;span class=&quot;math-container&quot;&gt;$y_{\ce{BBBB}} &amp;lt; 0$&lt;/span&gt;. So my query is, &lt;strong&gt;how come I got a negative cluster probability?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It works perfectly well as long as I work with just NN pairs.&lt;/p&gt;&#xA;&lt;p&gt;Update: The following are values I got for an &lt;span class=&quot;math-container&quot;&gt;$AB_3$&lt;/span&gt; type FCC cell:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Point correlation function: -0.5&#xA;Pair correlation function: -0.0658682634730539&#xA;Tetrahedron correlation function: 0.034482758620689655&#xA;Triangle correlation function: 0.2328767123287671&#xA;xA = 0.25&#xA;xB = 0.75&#xA;yA,A = -0.016467065868263474&#xA;yA,B = 0.26646706586826346&#xA;yB,A = 0.26646706586826346&#xA;yB,B = 0.48353293413173654&#xA;wA,A,A,A = -0.07211067944413488&#xA;wA,A,A,B = -0.07654919259261354&#xA;wA,A,B,A = -0.07654919259261354&#xA;wA,A,B,B = 0.02760427421020029&#xA;wA,B,A,A = -0.08478272552674529&#xA;wA,B,A,B = 0.01937074127606855&#xA;wA,B,B,A = 0.01937074127606855&#xA;wA,B,B,B = 0.09843645255544649&#xA;wB,A,A,A = 0.014019669682835561&#xA;wB,A,A,B = 0.11817313648564941&#xA;wB,A,B,A = 0.11817313648564941&#xA;wB,A,B,B = 0.19723884776502737&#xA;wB,B,A,A = 0.12640666941978113&#xA;wB,B,A,B = 0.2054723806991591&#xA;wB,B,B,A = 0.2054723806991591&#xA;wB,B,B,B = 0.1602533596010624&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The cell in POSCAR (VASP) format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR&#xA;3.5639592128110129&#xA;  0.00000000 -0.50000000 -1.50000000&#xA;  2.00000000  1.00000000 -1.00000000&#xA;  2.00000000 -2.50000000  0.50000000&#xA;  A   B&#xA;  12  36&#xA;Direct&#xA;  1.00000000  1.00000000  1.00000000&#xA;  0.25000000  0.25000000  0.25000000&#xA;  0.29166667  0.29166667  0.45833333&#xA;  0.45833333  0.45833333  0.29166667&#xA;  0.08333333  0.58333333  0.41666667&#xA;  0.12500000  0.62500000  0.62500000&#xA;  0.62500000  0.62500000  0.12500000&#xA;  0.66666667  0.66666667  0.33333333&#xA;  0.70833333  0.70833333  0.54166667&#xA;  0.37500000  0.87500000  0.87500000&#xA;  0.45833333  0.95833333  0.29166667&#xA;  0.91666667  0.91666667  0.58333333&#xA;  0.04166667  0.04166667  0.20833333&#xA;  0.50000000  1.00000000  0.50000000&#xA;  0.08333333  0.08333333  0.41666667&#xA;  0.54166667  0.04166667  0.70833333&#xA;  0.12500000  0.12500000  0.62500000&#xA;  0.58333333  0.08333333  0.91666667&#xA;  0.16666667  0.16666667  0.83333333&#xA;  0.62500000  0.12500000  0.12500000&#xA;  0.20833333  0.20833333  0.04166667&#xA;  0.66666667  0.16666667  0.33333333&#xA;  0.70833333  0.20833333  0.54166667&#xA;  0.75000000  0.25000000  0.75000000&#xA;  0.33333333  0.33333333  0.66666667&#xA;  0.79166667  0.29166667  0.95833333&#xA;  0.37500000  0.37500000  0.87500000&#xA;  0.83333333  0.33333333  0.16666667&#xA;  0.41666667  0.41666667  0.08333333&#xA;  1.00000000  0.50000000  1.00000000&#xA;  0.87500000  0.37500000  0.37500000&#xA;  0.04166667  0.54166667  0.20833333&#xA;  0.91666667  0.41666667  0.58333333&#xA;  0.50000000  0.50000000  0.50000000&#xA;  0.95833333  0.45833333  0.79166667&#xA;  0.54166667  0.54166667  0.70833333&#xA;  0.58333333  0.58333333  0.91666667&#xA;  0.16666667  0.66666667  0.83333333&#xA;  0.20833333  0.70833333  0.04166667&#xA;  0.25000000  0.75000000  0.25000000&#xA;  0.29166667  0.79166667  0.45833333&#xA;  0.75000000  0.75000000  0.75000000&#xA;  0.33333333  0.83333333  0.66666667&#xA;  0.79166667  0.79166667  0.95833333&#xA;  0.83333333  0.83333333  0.16666667&#xA;  0.41666667  0.91666667  0.08333333&#xA;  0.87500000  0.87500000  0.37500000&#xA;  0.95833333  0.95833333  0.79166667&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="116" LastEditorUserId="7" LastEditDate="2020-07-05T00:21:40.280" LastActivityDate="2020-07-05T00:21:40.280" Title="Correlation Functions in the Cluster Variation Method" Tags="|vasp|entropy|correlation-functions|" AnswerCount="0" CommentCount="9" ClosedDate="2020-07-10T17:13:00.107" ContentLicense="CC BY-SA 4.0" />
  <row Id="1411" PostTypeId="1" CreationDate="2020-06-27T21:58:32.553" Score="12" ViewCount="326" Body="&lt;p&gt;I am trying to model 3D Poiseuille flow of an argon gas confined between two parallel platinum plates by using LAMMPS. I have one reference paper, as given in [1] below. I built my platinum structure correctly and I placed Ar atoms and run my simulation. At the end of simulation, I checked the density and it was totally wrong. I suspect that, I am not able to build sufficient number of atoms in my model. I try to use equations given below to obtain number of atoms but I couldn't decide the number of Ar atoms in my model, still. So, I need your help.&lt;/p&gt;&#xA;&lt;p&gt;In the paper, they obtain the diameter of atoms by using the Knudsen number. After that I divided this into 2 to get the radius, then I obtained the lattice parameter by &lt;span class=&quot;math-container&quot;&gt;$ 2 \sqrt2 r $&lt;/span&gt;. Then, I build argon as lattice fcc a. However, the final result and density is not correct. Therefore, I suspect that, the number of atoms in my system is wrong.&lt;/p&gt;&#xA;&lt;p&gt;So, my question is, how I can obtain lattice constant from the Kn number and obtain the correct density, for instance, for the Kn = 0.1 case in the reference paper [1] ?&lt;/p&gt;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://doi.org/10.1080/15567265.2016.1215364&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1080/15567265.2016.1215364&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="964" LastEditorUserId="5" LastEditDate="2020-07-01T20:06:27.203" LastActivityDate="2020-07-01T20:06:27.203" Title="Poiseuille flow by LAMMPS" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="8" ClosedDate="2020-07-11T19:17:38.427" ContentLicense="CC BY-SA 4.0" />
  <row Id="1412" PostTypeId="1" AcceptedAnswerId="1413" CreationDate="2020-06-29T00:19:02.147" Score="18" ViewCount="1933" Body="&lt;p&gt;The adoption of atom-typing allowed for the creation of incredibly widely used force-fields (FF) such as &lt;code&gt;GROMOS/AMBER/OPLS&lt;/code&gt; and many more. Because of the assumptions required in Molecular Mechanical (MM) models, in order to be accurate, at least part of the force-field must be fit to experimental data. This is very tedious, and there are many years, decades even, between updates to a FF.&lt;/p&gt;&#xA;&lt;p&gt;Recent FF development has utilized chemical perception rather than atom-typing and seems to have alot of potential. For instance, the &lt;a href=&quot;https://openforcefield.org&quot; rel=&quot;noreferrer&quot;&gt;openFF consortium&lt;/a&gt; seems to be making large strides in creating an open source, easy to use and tinker with, FF.&lt;/p&gt;&#xA;&lt;p&gt;Also, Parallel and GPU computing have come along way in the last decade. I would hope/assume that GPUs should make parameter optimization considerably faster than in previous decades.&lt;/p&gt;&#xA;&lt;p&gt;Are there FF groups/projects in development that have the aim of being open source and highly &amp;quot;tinkerable&amp;quot;, and are we in sight of being able to generate custom FFs somewhat on the fly, as we need them rather than relying on databases of atom-types fit nearly exclusively to solutes in water?&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2020-06-29T18:43:05.770" LastActivityDate="2020-06-29T18:49:11.740" Title="What is the cutting edge for open-source Force-Field generation?" Tags="|open-source|interatomic-potentials|optimization|molecular-mechanics|forcefields|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1413" PostTypeId="2" ParentId="1412" CreationDate="2020-06-29T01:08:16.833" Score="16" Body="&lt;h2&gt;ForceBalance&lt;/h2&gt;&#xA;&lt;p&gt;ForceBalance is one approach which aims at making it easier to create force fields from a combination of theoretical and experimental data. I believe it's within the OpenMM framework.&lt;/p&gt;&#xA;&lt;p&gt;The paper on the work can be found here&#xA;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jz500737m&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/jz500737m&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the GitHub page it says&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;The purpose of ForceBalance is to create force fields by applying a highly general and systematic process with explicitly specified input data and optimization methods, paving the way to higher accuracy and improved reproducibility.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;The code can be downloaded here&#xA;&lt;a href=&quot;https://github.com/leeping/forcebalance&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/leeping/forcebalance&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-06-29T01:36:26.113" LastActivityDate="2020-06-29T01:36:26.113" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1414" PostTypeId="2" ParentId="1355" CreationDate="2020-06-29T01:12:09.470" Score="16" Body="&lt;p&gt;Even the simplest better-than-schoolbook (O(n^2)) algorithms like Karatsuba are only useful in practice for large &lt;code&gt;n&lt;/code&gt;.  &lt;strong&gt;But what is &lt;code&gt;n&lt;/code&gt;?  It's not single bits, and it's not decimal digits.&lt;/strong&gt;  (Posting this tangent as requested in comments.)&lt;/p&gt;&#xA;&lt;p&gt;Software implementations of an extended-precision multiply algorithm work in integer chunks as wide as the hardware provides.  On a 64-bit CPU, that's usually 64x64 =&amp;gt; 128-bit integer multiplication, e.g. the &lt;a href=&quot;https://www.felixcloutier.com/x86/mul&quot; rel=&quot;noreferrer&quot;&gt;x86-64 &lt;code&gt;mul&lt;/code&gt; instruction&lt;/a&gt;.  (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1355/did-the-2019-discovery-of-on-logn-multiplication-have-a-practical-outcome/1409#1409&quot;&gt;@fgrieu's answer&lt;/a&gt; has more detail on this, including the term &amp;quot;limb&amp;quot; for such a chunk.)&lt;/p&gt;&#xA;&lt;p&gt;That fixed-width CPU instruction runs in fixed time (regardless of the &lt;em&gt;value&lt;/em&gt; on most CPUs; &lt;a href=&quot;https://stackoverflow.com/questions/4125033/floating-point-division-vs-floating-point-multiplication/45899202#45899202&quot;&gt;division is the only instruction that's slow enough to justify variable latency in a modern pipelined CPU&lt;/a&gt;, and in the most recent x86-64 CPUs even it's constant).  e.g. on modern Intel and AMD CPUs, &lt;code&gt;mul r64&lt;/code&gt; or &lt;code&gt;mulx&lt;/code&gt; have a throughput of 1 per cycle and a latency of 3 to 4 cycles (for the low and high halves of the output, respectively: &lt;a href=&quot;https://www.uops.info/html-instr/MUL_R64.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.uops.info/html-instr/MUL_R64.html&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Hardware doesn't &amp;quot;know&amp;quot; it's doing one big multiply, it's just doing each fixed-width part separately.  Hardware can easily be parallel (adding partial products) if you can throw enough transistors at the problem.  &lt;a href=&quot;https://stackoverflow.com/questions/26370287/how-modern-x86-processors-actually-compute-multiplications&quot;&gt;HW multipliers in CPUs&lt;/a&gt; use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Dadda_multiplier&quot; rel=&quot;noreferrer&quot;&gt;Dadda tree&lt;/a&gt; design.  This is simpler than doing 63 additions of shifted versions of the other 64-bit input (or &lt;code&gt;0&lt;/code&gt; where this input has a 0 bit) using normal adders: carry propagation can be deferred.  Hardware tricks like that are AFAIK unrelated to any of the sub-N^2 algorithmic tricks.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Such a multiply instruction, and add-with-carry, are the building blocks for schoolbook multiplication's O(n^2) time complexity.  e.g. 128-bit multiplication (producing a 128-bit result) takes 3 multiplies on x86-64: &lt;a href=&quot;https://godbolt.org/z/qBAbfQ&quot; rel=&quot;noreferrer&quot;&gt;https://godbolt.org/z/qBAbfQ&lt;/a&gt;.  To also produce the high half, all of those multiplies would have to be &amp;quot;full&amp;quot; 64x64=&amp;gt;128 instead of only 64x64 =&amp;gt; 64 for the low x high and high x low cross products, and we'd need to do the high x high product, for a total of 4 &lt;code&gt;mul&lt;/code&gt; instructions.&lt;/p&gt;&#xA;&lt;p&gt;e.g. &lt;a href=&quot;https://stackoverflow.com/questions/33217920/32-bit-extended-multiplication-via-stack/33218993#33218993&quot;&gt;this SO answer&lt;/a&gt; shows 32x32 =&amp;gt; 64-bit multiply using 16-bit x86 so each input is 2 limbs, and the output is 2+2 = 4 limbs, requiring 2*2 = 4 multiplies of 16x16 =&amp;gt; 32 bits each.  Exactly the same pattern would apply for 64x64 =&amp;gt; 128 on a 32-bit machine, or 128x128 =&amp;gt; 256 on a 64-bit machine.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Since that building block is opaque to software, and/or shuffling individual bits around would be much more expensive than it's worth, &lt;code&gt;n&lt;/code&gt; is only 64 for 4096-bit integer multiply.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;To allow better instruction-level parallelism (letting &lt;a href=&quot;https://en.wikipedia.org/wiki/Superscalar_processor&quot; rel=&quot;noreferrer&quot;&gt;superscalar CPUs&lt;/a&gt; do the same work in less time) and reducing overhead of &lt;code&gt;mov&lt;/code&gt; instructions, Intel introduced (in Broadwell) the ADX extension that allows two parallel dependency chains of add-with-carry.  &lt;a href=&quot;https://www.intel.com/content/dam/www/public/us/en/documents/white-papers/ia-large-integer-arithmetic-paper.pdf&quot; rel=&quot;noreferrer&quot;&gt;This whitepaper&lt;/a&gt; shows the advantages it gives for small problems (like 512-bit x 512-bit multiplication (8 x 8 limbs)).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;For floating-point, an FP multiplier involves an integer multiplier for the 53x53-bit =&amp;gt; 53-bit correctly rounded mantissa (the most significant 53 bits of the full integer product) plus hardware to add the exponents, and check for / handle overflow / underflow and NaN.  See &lt;a href=&quot;https://electronics.stackexchange.com/questions/452181/why-does-intels-haswell-chip-allow-floating-point-multiplication-to-be-twice-as&quot;&gt;Why does Intel's Haswell chip allow floating point multiplication to be twice as fast as addition?&lt;/a&gt; for some info about how FP ALUs are designed, and the barely-related question of why Intel made the design choices they did in Haswell and Skylake.&lt;/p&gt;&#xA;&lt;p&gt;To get extra FP precision, one technique is so-called &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Double-precision_floating-point_format&quot; rel=&quot;noreferrer&quot;&gt;double-double&lt;/a&gt;&amp;quot;: wide mantissa using two &lt;code&gt;double&lt;/code&gt;s, but only the exponent from one of them.  Using that only takes a handful of double-precision math operations, like &lt;a href=&quot;https://stackoverflow.com/questions/31647409/float128-and-double-double-arithmetic&quot;&gt;6 to 20&lt;/a&gt; depending on which operation and whether FMA (fused multiply-add without intermediate rounding) is available.  &lt;strong&gt;The relevant width is n=2 doubles, not n=36 decimal digits.&lt;/strong&gt; (And &lt;a href=&quot;https://en.wikipedia.org/wiki/Double-precision_floating-point_format&quot; rel=&quot;noreferrer&quot;&gt;IEEE FP is a binary format&lt;/a&gt;, not decimal, although there are decimal FP formats that exist, with some CPUs even having hardware support for them, such as PowerPC.)&lt;/p&gt;&#xA;&lt;p&gt;Note that a SIMD multiplier just replicates that for each SIMD element.  double-double can SIMD efficiently if you store separate vectors of lo / hi halves so you don't need to shuffle to line up the corresponding halves of a single number.  e.g. &lt;a href=&quot;https://stackoverflow.com/questions/30573443/optimize-for-fast-multiplication-but-slow-addition-fma-and-doubledouble&quot;&gt;this Q&amp;amp;A&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h3&gt;Other extended-precision number representations&lt;/h3&gt;&#xA;&lt;p&gt;You &lt;em&gt;could&lt;/em&gt; store numbers as an array of bytes, each byte holding a single decimal digit.  But that's pretty terrible.  Historically, it was not uncommon to use a simplistic format like that, especially for a score counter in a game that gets printed on screen in decimal format constantly.  Or &lt;a href=&quot;https://en.wikipedia.org/wiki/Binary-coded_decimal#Packed_BCD&quot; rel=&quot;noreferrer&quot;&gt;BCD&lt;/a&gt; (2 decimal digits per 8-bit byte, each in a separate 4-bit nibble).&lt;/p&gt;&#xA;&lt;p&gt;But this is pretty bad, especially for multiplying numbers stored in this format, because then &lt;code&gt;n&lt;/code&gt; becomes large and complexity scales with N^2 (for the simple schoolbook algorithm).&lt;/p&gt;&#xA;&lt;p&gt;@davidbak commented:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;w.r.t. &amp;quot;nobody uses decimal digits as an extended-precision format&amp;quot; - is that true? I know there used to be implementations of multi precision integer arithmetic that used the largest power of 10 that would fit in a word as the base - e.g., 10^9 for 32-bit machines. Made conversions to&amp;lt;-&amp;gt;from a human-readable base 10 notation much easier and cost only a &amp;quot;reasonable&amp;quot; overhead for some definition of reasonable that might depend on your use case. Is that not done anymore? (Although strictly speaking those aren't decimal digits, just power-of-ten digits...)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Indeed, larger powers of 10 could be sane when you need frequent conversion to/from a decimal string, or multiply/divide by powers of 10. But then a 36-digit number is 4 chunks of 9, not 36 chunks of 1.  e.g. one use-case was &lt;a href=&quot;https://codegolf.stackexchange.com/a/135618/30206&quot;&gt;printing the first 1000 decimal digits of &lt;code&gt;Fib(10^9)&lt;/code&gt; (x86-64 asm code-golf)&lt;/a&gt; where it's handy to have right shift by 1 limb be division by a power of 10, and for conversion to decimal to only need to consider the current limb, converting that to 9 decimal digits without having to do extended-precision division where the remainder depends on all higher bits.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;See also &lt;a href=&quot;https://codereview.stackexchange.com/a/237764&quot;&gt;this code-review answer&lt;/a&gt; about an implementation based on single decimal digits&lt;/strong&gt;.  I included some details about what CPython does, and some other links.  It's not rare for beginners to come up with that as an idea, but non-toy libraries use at least 10^9 as the base for &amp;quot;limbs&amp;quot;, unless we're talking about BCD.&lt;/p&gt;&#xA;&lt;p&gt;Or more commonly binary extended precision using all 32 bits per 32-bit integer, or sometimes only 2^30 to leave room for high-level language handling of carry in/out (like in CPython) without access to an asm carry flag.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Another advantage of leaving some spare bits per limb is to allow deferred carry normalization, making SIMD for addition efficiently possible. See @Mysticial's answer on &lt;a href=&quot;https://stackoverflow.com/q/8866973&quot;&gt;Can long integer routines benefit from SSE?&lt;/a&gt;.  Especially for extended-precision addition, leaving some slack in each limb is actually interesting if you design around that format with awareness of when to normalize as an extra step.  (@Mysticial is the author of y-cruncher and also works on Prime95; he implemented its use of FP-FMA to take advantage of the FP mantissa multipliers for bit-exact integer work.)&lt;/p&gt;&#xA;&lt;p&gt;That answer also points out that &amp;quot;really large bignum&amp;quot; multiplications can be done as an FFT.&lt;/p&gt;&#xA;&lt;p&gt;Normally (with standard techniques) it's very hard to take advantage of SIMD for extended-precision; within one operation, there's a serial dependency between each element: you don't know if there's carry-in to this element until you process the previous element (for addition).&lt;/p&gt;&#xA;&lt;p&gt;For multiplication, it's usually even worse: SIMD doesn't usually have very wide multipliers, and with the result being twice as wide as the inputs it's a problem where to put them.&lt;/p&gt;&#xA;&lt;p&gt;The amount of work done by one building block &lt;a href=&quot;https://stackoverflow.com/questions/28807341/simd-signed-with-unsigned-multiplication-for-64-bit-64-bit-to-128-bit/28811226#28811226&quot;&gt;should be measured as the &amp;quot;product bits&amp;quot; you compute per cycle&lt;/a&gt;, e.g. 64x64 =&amp;gt; 128-bit full multiply does 64x64 = 4096 units of work.  But a 4x 32x32=&amp;gt;64-bit SIMD multiply (like AVX2 &lt;code&gt;vpmuludq&lt;/code&gt;) does &lt;code&gt;32^2&lt;/code&gt; = 1024 units of work per element, with 4 elements, for a total of 4096 units of multiply work.  And it leaves more adding of partial products not done.  So even in theory, ignoring other factors, AVX2 &lt;code&gt;vpmuludq&lt;/code&gt; on a 256-bit vector is break-even with scalar.&lt;/p&gt;&#xA;&lt;p&gt;AVX512 has 64x64 =&amp;gt; 64-bit multiply (but still no way to get the upper-half of the full result so it's no more helpful for BigInteger than 32x32 =&amp;gt; 64, I think).  &lt;a href=&quot;https://en.wikipedia.org/wiki/AVX-512#IFMA&quot; rel=&quot;noreferrer&quot;&gt;AVX512IFMA&lt;/a&gt; more directly exposes what the FP mantissa multipliers can do, providing separate low and high half 52x52 =&amp;gt; 104-bit multiply.&lt;/p&gt;&#xA;&lt;p&gt;(Other SIMD integer multiply instructions like &lt;code&gt;vpmulld&lt;/code&gt; that do 32x32 =&amp;gt; 32-bit usually decode to two separate uops for the vector-ALU ports, so they can use the same per-element multipliers as FP mantissas.  But those multipliers are only 52x52 or 24x24-bit.  Making them wider would cost significantly more for these wide SIMD ALUs, and only help the fairly rarely used SIMD-integer multiply instructions.)&lt;/p&gt;&#xA;" OwnerUserId="907" LastEditorUserId="5" LastEditDate="2020-06-29T19:14:41.797" LastActivityDate="2020-06-29T19:14:41.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1415" PostTypeId="2" ParentId="157" CreationDate="2020-06-29T01:13:29.400" Score="12" Body="&lt;p&gt;Predicting a crystal structure without experimental input is often called &amp;quot;ex nihilo&amp;quot; (out of nothing) structure prediction. Most materials modelling programs have optimisation methods to take a user-supplied initial structure and optimise it (i.e. find a low energy, zero force/stress configuration). These methods are known as &amp;quot;local optimisation methods&amp;quot; because they find the low-energy, zero force/stress structure near the starting configuration, not necessarily the lowest energy structure that is possible. As an example, if your initial structure is a carbon diamond crystal then the software will find the optimal lattice constants of diamond and move the atoms to the high symmetry sites (if they weren't already there).&lt;/p&gt;&#xA;&lt;p&gt;In order to predict crystal structures, you need to be able to find the structures with the lowest possible energies. Methods to do this are known as &amp;quot;global optimisation methods&amp;quot; and there are many different flavours. A select few are:&lt;/p&gt;&#xA;&lt;h2&gt;Simulated annealing&lt;/h2&gt;&#xA;&lt;p&gt;This method is inspired by the physical processes of crystallisation as matter cools. If your modelling software has molecular dynamics capabilities, then you can do this method yourself. Essentially you heat your initial system up, let the atoms wander around in configurational space, then cool it down and see where they go. Repeat... repeat... repeat... It is not very efficient, so I don't recommend it for &amp;quot;real research&amp;quot; in general, but it's very easy to do.&lt;/p&gt;&#xA;&lt;h2&gt;Basin Hopping&lt;/h2&gt;&#xA;&lt;p&gt;A related, much more sophisticated and reliable method is &amp;quot;basin hopping&amp;quot; which can actually be quite efficient for some classes of problem. In essence, this method tries to identify the &amp;quot;basins of attraction&amp;quot; as it proceeds (a &amp;quot;basin&amp;quot; is the set of configurations which all optimise to the same structure) and to force the system out of the known &amp;quot;basins&amp;quot; and, therefore, into a new one.&lt;/p&gt;&#xA;&lt;p&gt;See, for example,&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Global structure search for molecules on surfaces: Efficient sampling with curvilinear coordinates&amp;quot;, K. Krautgasser et al, &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;145&lt;/strong&gt;(8), 084117 (2016); &lt;a href=&quot;https://doi.org/10.1063/1.4961259&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1063/1.4961259&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms&amp;quot;, D.J. Wales and J.P.K. Doye, &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;101&lt;/strong&gt;(28) 5111 (1997); &lt;a href=&quot;https://doi.org/10.1021/jp970984n&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/jp970984n&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There's even a basin hopping algorithm in scipy, though I've never used it.&lt;/p&gt;&#xA;&lt;h2&gt;Genetic algorithms (GA)&lt;/h2&gt;&#xA;&lt;p&gt;These methods are inspired by the development of populations of animals. They work by generating a large group of candidate structures (the &amp;quot;population&amp;quot;), evaluating how good they are (their &amp;quot;fitness&amp;quot;) and, based on that, choosing some of the structures to mix together to create new candidate structures (called &amp;quot;breeding&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;breeding&amp;quot; usually involves picking a pair of &amp;quot;parent&amp;quot; structures from the population, and creating one or more new &amp;quot;child&amp;quot; structures by (a) taking parts of each of the parent structures (called &amp;quot;crossover&amp;quot;); and (b) adding some random changes (&amp;quot;mutations&amp;quot;), such as perturbing the atomic positions. The new child structures are often filtered to remove some unlikely ones, and the remainder are evaluated for their fitness and added to the population. This forms the next &amp;quot;generation&amp;quot;, who can then have children of their own, which can have children of &lt;em&gt;their&lt;/em&gt; own etc. You also need to remove poor structures from the population (&amp;quot;death&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;In the materials modelling context, it is common practice to optimise each child structure with the usual local optimisation methods in order to make them as good as they can be.&lt;/p&gt;&#xA;&lt;p&gt;There are a huge number of different genetic algorithms because there are lots of choices, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How do you evaluate &amp;quot;fitness&amp;quot;?&lt;/li&gt;&#xA;&lt;li&gt;How do you use the &amp;quot;fitness&amp;quot; to choose &amp;quot;parent&amp;quot; structures?&lt;/li&gt;&#xA;&lt;li&gt;How do you generate the &amp;quot;children&amp;quot; from the &amp;quot;parents&amp;quot;?&lt;/li&gt;&#xA;&lt;li&gt;Which mutation changes do you allow?&lt;/li&gt;&#xA;&lt;li&gt;Do you let all the children enter the population?&lt;/li&gt;&#xA;&lt;li&gt;When do you remove structures from the population?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Genetic algorithms can be very efficient for materials prediction, however you should beware the huge number of choices! Even once you've answered all the questions above, you still have to decide how many structures should be in each generation, how many generations to run, what the actual mutation probabilities should be, which properties you wish to include in your fitness measure...&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Improved real-space genetic algorithm for crystal structure and polymorph prediction&amp;quot;,&#xA;N. L. Abraham and M. I. J. Probert, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;77&lt;/strong&gt;, 134117 (2008); &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.77.134117&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.77.134117&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Crystal structure prediction using ab initio evolutionary techniques: Principles and applications&amp;quot;, A. R. Oganov and C. W. Glass, &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;124&lt;/strong&gt; 244704 (2006); &lt;a href=&quot;https://doi.org/10.1063/1.2210932&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1063/1.2210932&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;XtalOpt: An open-source evolutionary algorithm for crystal structure prediction&amp;quot;,&#xA;D. C. Lonie and E. Zurek, &lt;em&gt;Comp. Phys. Comm.&lt;/em&gt; &lt;strong&gt;182&lt;/strong&gt; (2) 372-387 (2011); &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2010.07.048&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.cpc.2010.07.048&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And, if you'll forgive me advertising my own student's work:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Simultaneous Prediction of the Magnetic and Crystal Structure of Materials Using a Genetic Algorithm&amp;quot;, E. J. Higgins, P. J. Hasnip and M.I.J. Probert, &lt;em&gt;Crystals&lt;/em&gt; &lt;strong&gt;439&lt;/strong&gt; (2019); &lt;a href=&quot;https://doi.org/10.3390/cryst9090439&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.3390/cryst9090439&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There's an implementation of a genetic algorithm in the popular Atomistic Simulation Environment (ASE; &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/&lt;/a&gt;), as well as XTalOpt and USPEX.&lt;/p&gt;&#xA;&lt;h2&gt;Bio-inspired algorithms&lt;/h2&gt;&#xA;&lt;p&gt;There are a huge number of methods drawn from the behaviour of living creatures, many based on how creatures find resources. Particle swarm optimisation, ant colony optimisation, bird-flocking... For example:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Crystal Structure Prediction via Particle Swarm Optimization&amp;quot;, Y. Wang, J. Lv, L. Zhu, and Y. Ma, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;82&lt;/strong&gt; 094116 (2010); &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.82.094116&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.82.094116&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(The above work is implemented in the CALYPSO package.)&lt;/p&gt;&#xA;&lt;h2&gt;Ab Initio Random Structure Searching (AIRSS)&lt;/h2&gt;&#xA;&lt;p&gt;So far, all of the methods described have been general global optimisation methods which can be applied to pretty much any optimisation problem. In the context of materials modelling, this means they can be used with continuum models, coarse-grained molecular models, atomistic forcefields and quantum mechanical methods.&lt;/p&gt;&#xA;&lt;p&gt;In recent years a much simpler scheme has demonstrated great success across a range of materials problems. The Ab Initio Random Structure Searching (AIRSS) method is, at its heart, a Monte Carlo-style random sampling of configurational space, coupled with the usual local optimisation of each new structure. It exploits the observation that, when the electrons are treated quantum mechanically, the low energy material structures lie within broad basins, which are relatively easy to find. This is not generally true of optimisation problems, and in fact even within materials modelling it is not true of many forcefields, which often have jagged energy landscapes; it does appear to be true of most &amp;quot;real&amp;quot; materials though, and this is reflected in the results of quantum mechanical models.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Ab initio random structure searching&amp;quot;, C.J. Pickard and R.J. Needs,  &lt;em&gt;J. Phys.: Condens. Matter&lt;/em&gt; &lt;strong&gt;23&lt;/strong&gt; 053201 (2011) ; &lt;a href=&quot;https://doi.org/10.1088/0953-8984/23/5/053201&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1088/0953-8984/23/5/053201&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The AIRSS method is implemented in the AIRSS software: &lt;a href=&quot;https://www.mtg.msm.cam.ac.uk/Codes/AIRSS&quot; rel=&quot;noreferrer&quot;&gt;https://www.mtg.msm.cam.ac.uk/Codes/AIRSS&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2020-06-29T01:19:03.903" LastActivityDate="2020-06-29T01:19:03.903" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1416" PostTypeId="1" CreationDate="2020-06-29T02:45:29.657" Score="21" ViewCount="186" Body="&lt;p&gt;I'm trying to simulate a graphene flake with its edge C atoms saturated by H atoms, in a temperature ramp from 300 K to 1600 K, using LAMMPS and the AIREBO potential proposed by Stuart et al. in 2000.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The problem is when the temperature is close to 500 K the C-H bonds start breaking and at 1600 K all of the H atoms are unbonded.&lt;/strong&gt; It also occurs if I use a bilayer graphene flake even if it is two times bigger than the here shown.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What do you think about that?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;My input card is below. It looks very similar to the example included in the LAMMPS folder, so I don't know why is this happening.&lt;/p&gt;&#xA;&lt;p&gt;Thanks a lot in advance!&lt;/p&gt;&#xA;&lt;p&gt;Pic1: simulation at 300 K&#xA;Pic2: simulation at 1600 K (H atoms are randomly distributed in the box)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;################&#xA;# graphene n14_l1                              &#xA;################&#xA;&#xA;units           metal&#xA;boundary        p p p&#xA;atom_style      atomic&#xA;read_data       mainFlake_n14_l1.dat&#xA;#read_restart   name.restart&#xA;&#xA;mass        1 12.01&#xA;mass            2 1.008&#xA;&#xA;pair_style      airebo 3.0 1 1&#xA;pair_coeff      * * CH.airebo C H&#xA;&#xA;neighbor        0.3 bin&#xA;neigh_modify    delay 10&#xA;&#xA;#---------------------------------------- relax&#xA;timestep        0.0005  # 0.5 fs&#xA;thermo          20&#xA;dump            1 all custom 2 min.lammpstrj id element x y z&#xA;minimize        1.0e-10 1.0e-11 10000 100000&#xA;&#xA;reset_timestep  0&#xA;undump          1&#xA;&#xA;#---------------------------------------- MD&#xA;timestep        0.002   # 2 fs&#xA;velocity        all create 273.00 32345 rot yes mom yes dist gaussian&#xA;fix     1 all nvt temp 273.0 1600.0 0.01&#xA;thermo          1000&#xA;thermo_style    custom step temp pe ke etotal&#xA;dump            1 all custom 200 md.lammpstrj id element x y z&#xA;dump_modify     1 element C H&#xA;restart         20000 restart1 restart2&#xA;&#xA;#---------------------------------------- Run&#xA;run             2500000    # 5 ns&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DHsNk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DHsNk.png&quot; alt=&quot;pic1&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/mPSC4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mPSC4.png&quot; alt=&quot;pi2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="562" LastEditorUserId="5" LastEditDate="2020-06-30T00:25:13.627" LastActivityDate="2020-07-15T17:24:31.623" Title="Why can't I reproduce the behavior of an H-saturated graphene flake?" Tags="|molecular-dynamics|lammps|graphene|2d-lattice|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="1417" PostTypeId="1" AcceptedAnswerId="1420" CreationDate="2020-06-29T03:25:32.250" Score="16" ViewCount="809" Body="&lt;p&gt;Gaussian cubegen and surface generators in Gaussview seem to only allow to map the ESP on SCF densities. I used G16 for the ESP generation. I would like to plot it on the solvent accessible surface. Is there any (free) software that allows me to do that?&lt;/p&gt;&#xA;" OwnerUserId="705" LastEditorUserId="5" LastEditDate="2020-06-29T17:11:42.257" LastActivityDate="2020-06-29T17:11:42.257" Title="How to map the electrostatic potential from GAUSSIAN, on a solvent accessible surface?" Tags="|software|gaussian|visualization-software|electrostatic|implicit-solvent|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1418" PostTypeId="5" CreationDate="2020-06-29T07:01:28.587" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-06-29T07:01:28.587" LastActivityDate="2020-06-29T07:01:28.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1419" PostTypeId="4" CreationDate="2020-06-29T07:01:28.587" Score="0" Body="The properties of graphene and their modelling." OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-07-31T19:23:15.907" LastActivityDate="2020-07-31T19:23:15.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1420" PostTypeId="2" ParentId="1417" CreationDate="2020-06-29T11:55:57.647" Score="10" Body="&lt;p&gt;The &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;Jmol&lt;/a&gt; software is able to plot different &lt;a href=&quot;http://jmol.sourceforge.net/docs/surface/&quot; rel=&quot;noreferrer&quot;&gt;surfaces&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the example below, the system is a Mobius strip and the ESP was calculated using &lt;a href=&quot;http://openmopac.net/&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt; but as Jmol is full compatible with Gaussian outputs, I think there will be no problem.&lt;/p&gt;&#xA;&lt;p&gt;Mobius strip structure:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/Tpzta.jpg&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;Mobius solvent-accessible surface (SAS):&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/6BJS2.jpg&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;Mobius electrostatic potential mapped on solvent-accessible surface:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/XueDq.jpg&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;To obtain the images above, the procedure was:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;load the output file from MOPAC with the graphical information.&lt;/li&gt;&#xA;&lt;li&gt;open the script console.&lt;/li&gt;&#xA;&lt;li&gt;create the SAS with the command: &lt;code&gt;isosurface ignore(solvent) sasurface 1.2&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;map the electrostatic potential on SAS with the command:  &lt;code&gt;isosurface resolution 6 sasurface map mep&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-29T11:55:57.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1421" PostTypeId="2" ParentId="1412" CreationDate="2020-06-29T18:25:55.150" Score="11" Body="&lt;h2&gt;ForceBalance&lt;/h2&gt;&#xA;&lt;p&gt;Cody is right, ForceBalance is designed for the task of generating custom force fields.  Force fields have a lot of variability in their functional forms, representation of parameters (as text, XML files or objects in code), the possible values or ranges of parameters, the software that runs simulations using the force field, the experimental data that the force field is fitted to, and so on.  This means the workflow to produce a force field can vary depending on the needs of the project.&lt;/p&gt;&#xA;&lt;p&gt;ForceBalance lets you carry out the force field optimization in a systematic and reproducible way by accommodating as much of this variability as possible in a single calculation.  You can fit parameters to experimental properties (such as density of a liquid), &lt;em&gt;ab initio&lt;/em&gt; properties (such as QM calculations of energy / forces for a set of configurations), or any linear combination.  A number of properties are implemented, each of which can be computed using any of several software packages (Gromacs, AMBER, Tinker, OpenMM).  FB is also used to fit the OpenFF small molecule parameter set in a manuscript we're currently writing.&lt;/p&gt;&#xA;&lt;p&gt;Extension of ForceBalance to new types of data and simulation software can be done by writing new &amp;quot;target&amp;quot; or &amp;quot;engine&amp;quot; classes.  It is available via the 3-clause BSD license.  I'd be happy to answer more questions.&lt;/p&gt;&#xA;" OwnerUserId="975" LastEditorUserId="5" LastEditDate="2020-06-29T18:49:11.740" LastActivityDate="2020-06-29T18:49:11.740" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1422" PostTypeId="2" ParentId="928" CreationDate="2020-06-29T22:51:39.533" Score="4" Body="&lt;p&gt;A partial, preliminary answer to collect my thoughts (or maybe just a test of &lt;a href=&quot;https://meta.wikimedia.org/wiki/Cunningham%27s_Law&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cunningham's Law&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I believe I have determined the reason for the discrepancy. In terms of calculating a derivative with respect to a given mode, my numerical derivative procedure seems to be incorrect. While this approach should work fine for modes that are all orthogonal to each other (which is the case for the normal modes), the localization procedure should generally lead to nonorthogonal modes.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/8MrxU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8MrxU.png&quot; alt=&quot;A set of skew coordinates&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I take the directional derivative using the formula in my question, I won't just be getting the derivative along the desired local mode. Instead, I will get additional contributions from any of the other modes that overlap with it. For a simple example of this, consider the figure above. In a coordinate system where the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; axis is tilted by some amount &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; towards the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; axis. The directional derivative of a function &lt;span class=&quot;math-container&quot;&gt;$f(x,y,z)$&lt;/span&gt; along &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; would no longer just be &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial f}{\partial x}$&lt;/span&gt;, but would now have a component related to &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial f}{\partial z}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I suspect (but have not proven) that the other procedure of transforming the derivative just gives me the component corresponding to the individual mode I'm interested in.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-06-29T22:51:39.533" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1423" PostTypeId="2" ParentId="1134" CreationDate="2020-06-29T23:20:58.987" Score="10" Body="&lt;p&gt;I will list 5 issues with F12/R12 methods, and then try to explain them the best I can:&lt;/p&gt;&#xA;&lt;h2&gt;Need for an auxiliary basis set&lt;/h2&gt;&#xA;&lt;p&gt;Most (if not all) F12/R12 methods require more than just a standard single-particle Gaussian basis set. For one of the most common elements (carbon) in electron structure calculations, you can see some of these auxiliary basis sets on Basis Set Exchange, for example by typing &amp;quot;F12&amp;quot; into the search field:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mbIzX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mbIzX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that they only go up to QZ. This is a problem if you want to get close to the basis set limit: advocates for F12/R12 usually say that using these methods gains you 2-3 levels of Z (meaning that QZ-F12 might be as good as 6Z or 7Z without F12), but you will unlikely get results at the quality of 8Z using QZ-F12. A few days ago I posted on arXiv &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;this paper in which we went up to aug-cc-pCV8Z&lt;/a&gt; for the carbon atom, and &lt;em&gt;&lt;strong&gt;still&lt;/strong&gt;&lt;/em&gt; basis set incompleteness error was the largest source of error in our final ionization energy: specifically, extrapolations to the CBS limit using FCI level calculations at aug-cc-pCV7Z and aug-cc-pCV8Z gave extrapolated values that were &lt;em&gt;&lt;strong&gt;more than 12 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; away from the aug-cc-pCV8Z energy.&lt;/strong&gt;&lt;/em&gt; That is 12x bigger than our targeted accuracy of &lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt;1 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;, so ideally we would be doing calculations at 9Z or 10Z or even even higher. Since F12 methods are claimed to gain you only 2-3 levels of Z, this would mean we would need auxiliary basis sets for 6Z-F12 (at the very least) to beat our 8Z results. &lt;em&gt;&lt;strong&gt;I have still never seen an cc-pCV5Z-F12 basis set&lt;/strong&gt;&lt;/em&gt; although I do know that aug-cc-pV5Z-F12 have existed (albeit only since 2015). So to compete with my aug-cc-pCV8Z calculation, F12 methods are stuck with aug-cc-pCVQZ-F12 or aug-cc-pV5Z-F12, which is not as good enough. The auxiliary basis set also makes F12 method &lt;strong&gt;non-variational!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Loss of accuracy due to density fitting and other approximations&lt;/h2&gt;&#xA;&lt;p&gt;Let's say that an aug-cc-pCV5Z-12 basis set did exist, and did gain us 3Z, would it be able to compete with my aug-cc-pCV8Z calculation? This is where I would say that F12 might be good for gaining you 3Z in terms of giving 5Z quality results with a DZ basis set (where your goal is to get milli-hartree or kcal/mol precision) but &lt;em&gt;&lt;strong&gt;not for getting 8Z quality results with a 5Z or even 6Z basis set when your goal is micro-hartree or cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; precision.&lt;/strong&gt;&lt;/em&gt; There's so many approximations (such as density fitting) that go into F12 methods, that can be ignored at the milli-hartree or kcal/mol level but &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; at the micro-hartree or cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; level. Apart from density fitting, let me show this nice table &lt;a href=&quot;https://arxiv.org/abs/1807.06058&quot; rel=&quot;noreferrer&quot;&gt;from a 2018 paper&lt;/a&gt; which shows how many terms are ignored from the &amp;quot;full&amp;quot; F12 theory, in various variants of F12 which are implemented to make their computational cost more reasonable:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LkIn7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LkIn7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Empirical (or chosen in an &lt;em&gt;ad hoc&lt;/em&gt; way) parameter &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Many F12/R12 methods rely on choosing a value for &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; in the correlation factor:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{1}&#xA;f_{12} = -\frac{1}{\gamma}e^{-\gamma r_{12}}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This isn't such a big problem when aiming for kcal/mol precision (although some might say it's a bit inelegant), but if you really want to reach the basis set limit to reach &amp;quot;spectroscopic&amp;quot; accuracy, you may have to optimize this parameter, which then becomes very expensive.&lt;/p&gt;&#xA;&lt;h2&gt;Increased cost due to needing the density matrix&lt;/h2&gt;&#xA;&lt;p&gt;Some electronic structure methods that are implemented within the F12/R12 scheme may rely on a density matrix rather than just the wavefunction, &lt;a href=&quot;https://arxiv.org/abs/1605.07065&quot; rel=&quot;noreferrer&quot;&gt;for example in the case of FCIQMC-F12 where the cost of using the F12/R12 scheme is at least 2x the CPU cost and 2x the RAM cost&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Not all post-HF methods are implemented with F12/R12&lt;/h2&gt;&#xA;&lt;p&gt;Many of the most common post-HF methods have been implemented within some variant of an F12/R12/CT scheme. These post-HF methods include MP2, GF2, CCSD, CCSD(2), CCSD(3), CCSD(T), CCSDT, CCSDT(2), CCSDTQ, CASSCF, CASPT2, MRCI, MRCI+Q, DMRG and FCIQMC.&lt;/p&gt;&#xA;&lt;p&gt;But many post-HF methods have &lt;strong&gt;not&lt;/strong&gt; yet been implemented within an F12/R12 schemes. These include (to the best of my knowledge), CCSDT(Q) and any level of CC beyond CCSDTQ; CC(2), CC(3), CC(4), etc.; MR-ACPF, MR-AQCC, RASSCF, RASPT2, GASSCF, GASPT2, etc.; HCI, iFCI, MBE-FCI, etc. If you're aiming for reaching the CBS limit with high-accuracy, you probably also want to use a high-accuracy method to treat electron correlation, and the state-of-the-art post-HF methods are not implemented within the F12/R12 scheme (and when some of them are, such as FCIQMC, it is not very &amp;quot;black-box&amp;quot; as you may have to use several codes and &lt;em&gt;really&lt;/em&gt; know what you're doing: the paper I mentioned needed to use a tweaked version of GAMESS plus a tweaked version of MPQC or a tweaked version of a code written by Takeshi Yanai which is not packaged for public use, in addition to NECI). Recently a new CT (canonical transcorrelation) method was developed for FCIQMC, but has the issue that you pointed out, about needing 3-electron integrals (but not 4-electron integrals!).&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; F12 methods certainly have their place and are of great value to people aiming for kcal/mol (or less) accuracy. If aiming for high accuracy (for example cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;) you will suffer from various limitations such as: not having the required auxiliary basis set to reach your desired level of basis set convergence, losing accuracy due to approximations in F12/R12 implementations, not being able to use state-of-the-art post-HF methods to treat the electron correlation very accurately, and/or the added cost will not be worth it and you might be better off just using a much larger basis set with no attempt to introduce explicit correlation, such as the aug-cc-pCV8Z that I used in the above mentioned paper.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2020-06-29T23:20:58.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1425" PostTypeId="2" ParentId="13" CreationDate="2020-06-30T09:11:15.023" Score="5" Body="&lt;p&gt;1RDMs are just simple matrices, which can be stored in either dense or sparse form, possibly combined with triangular storage (the matrix is often symmetric). 1RDMs are passed around in a number of formats, like Gaussian formatted checkpoint and Molden, and can be visualized for density isosurfaces etc.&lt;/p&gt;&#xA;&lt;p&gt;2RDMs are a bit more problematic, since they can become very large; because of this it might be that not all programs even store them in full but rather form and process only selected blocks at a time. The 2RDMs also contain more symmetries due to the particle interchanges, e.g. &lt;span class=&quot;math-container&quot;&gt;$\Gamma(pq|rs)=-\Gamma(qp|rs)=-\Gamma(pq|sr)=\Gamma(qp|sr)$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\Gamma(pq|rs)=\Gamma(rs|pq)$&lt;/span&gt; which means that there may be several choices on how to do this.&lt;/p&gt;&#xA;&lt;p&gt;However, the assumption here appears to be that the system is so small that all the &lt;span class=&quot;math-container&quot;&gt;$O(N^4)$&lt;/span&gt; integrals can be stored. In this case, one might think about using the FCIDUMP format to store the density matrices, too. The original FCIDUMP format doesn't store the Fock matrix, but extended versions do; this means that you should be able to save the 1RDM using a Fock matrix convention and the 2RDM using the two-electron integral convention.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-06-30T09:11:15.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1426" PostTypeId="2" ParentId="422" CreationDate="2020-06-30T09:22:09.403" Score="6" Body="&lt;p&gt;There's two later review articles by Schollwöck that weren't in Nike's excellent list:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;2011:&lt;/strong&gt; &lt;a href=&quot;http://doi.org/10.1098/rsta.2010.0382&quot; rel=&quot;noreferrer&quot;&gt;Phil. Trans. R. Soc. A (2011) 369, 2643–2661&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2011:&lt;/strong&gt; &lt;a href=&quot;http://dx.doi.org/10.1016/j.aop.2010.09.012&quot; rel=&quot;noreferrer&quot;&gt;Annals of Physics 326 (2011) 96–192&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-06-30T16:36:18.193" LastActivityDate="2020-06-30T16:36:18.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1427" PostTypeId="2" ParentId="1224" CreationDate="2020-06-30T09:34:12.420" Score="13" Body="&lt;h2&gt;Quantum Mobile Virtual Machine&lt;/h2&gt;&#xA;&lt;p&gt;Disclaimer: Not exactly a Linux Distibution but a Virtual Machine (VM)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.materialscloud.org/work/quantum-mobile&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum Mobile&lt;/a&gt; is a virtual machine for computational materials science.The VM is based on Ubuntu 18.04.4 LTS with VirtualBox 6.1.4.&lt;/p&gt;&#xA;&lt;p&gt;It comes with simulation codes - &lt;strong&gt;BigDFT, cp2k, fleur, Quantum ESPRESSO, Siesta, Wannier90, yambo&lt;/strong&gt;, together with &lt;strong&gt;AiiDA and the AiiDA lab jupyter environment.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Tools included -&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Atomistic - &lt;strong&gt;xcrysden, jmol, cif2cell, ase, pymatgen, seekpath, spglib,&#xA;pycifrw&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Visualization - &lt;strong&gt;grace, gnuplot, matplotlib, bokeh, jupyter&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Simulation environment - &lt;strong&gt;slurm, OpenMPI, FFT/BLAS/LAPACK, gcc,&#xA;gfortran, singularity&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2021-05-20T00:07:06.737" LastActivityDate="2021-05-20T00:07:06.737" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1428" PostTypeId="1" CreationDate="2020-06-30T13:33:04.553" Score="22" ViewCount="674" Body="&lt;p&gt;This is my first time here and I think you can help me.&lt;/p&gt;&#xA;&lt;p&gt;I would like to try (just for fun) to create a new DFT functional starting from experimental data. Do you have any manual, procedure or something that can help me? I know that the recent functionals (like the ones from Truhlar's group) are parametrized to fit experimental data, then I wonder how I can do that by myself.&lt;/p&gt;&#xA;&lt;p&gt;The idea behind this question is that some years ago I ran some calculation with a molecule I synthesized and crystallized, obtaining also crystallographic information. The optimization of the geometry with a lot of different functionals fails to reproduce the experimental structure. Only with MP2 I was able to obtain the correct geometry. Now I wondered if it is possible to create a DFT functional starting from an experimental structure.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="5" LastEditDate="2020-06-30T16:24:59.520" LastActivityDate="2020-07-01T14:55:34.913" Title="Create a new DFT functional from experimental data" Tags="|density-functional-theory|reference-request|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1429" PostTypeId="2" ParentId="1224" CreationDate="2020-06-30T14:10:35.257" Score="7" Body="&lt;h2&gt;Clear Linux&lt;/h2&gt;&#xA;&lt;p&gt;I think that if you need performance &lt;a href=&quot;https://clearlinux.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Clear Linux&lt;/a&gt; is the best choice. It's a distribution created by Intel but give also the best performance also with PC with AMD CPU respect to other distributions. Look at phoronix.com for benchmark.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="5" LastEditDate="2020-09-07T20:58:16.287" LastActivityDate="2020-09-07T20:58:16.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1430" PostTypeId="2" ParentId="1428" CreationDate="2020-06-30T14:55:33.723" Score="12" Body="&lt;p&gt;That's an okay toy project, but you shouldn't expect too much from it. Dozens (or hundreds!) of functionals have been fit to experimental data over several decades with varying success. You didn't specify what property you would be looking at; however, one of the key problems in the fitting effort is that depending on the property, the experiments may be quite far from the calculation.&lt;/p&gt;&#xA;&lt;p&gt;Single-point energies are the easiest target, since they are comeasurable between wave function theory and density functional theory. But, this problem has already been solved, starting out with Truhlar's functionals and finishing with the tour de force by Mardirossian and Head-Gordon, in which billions of functional forms were fit to a huge dataset of high-level (i.e. coupled-cluster) data, and the most predictive functional forms were chosen; even their most sophisticated functionals  contain few parameters. (They also do a good job of testing the functionals with molecules that don't appear in their training set.) You should definitely have a look at their work on the wB97X-V &lt;a href=&quot;https://doi.org/10.1039/C3CP54374A&quot; rel=&quot;noreferrer&quot;&gt;Phys. Chem. Chem. Phys. 16, 9904 (2014)&lt;/a&gt;, B97M-V &lt;a href=&quot;https://doi.org/10.1063/1.4907719&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 142, 074111 (2015)&lt;/a&gt;, and wB97M-V &lt;a href=&quot;https://doi.org/10.1063/1.4952647&quot; rel=&quot;noreferrer&quot;&gt;&#xA;J. Chem. Phys. 144, 214110 (2016)&lt;/a&gt; functionals, as well as the double hybrid wB97M(2) functional &lt;a href=&quot;https://doi.org/10.1063/1.5025226&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 148, 241736 (2018)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, the fitting procedure itself is quite simple. What you do is set up a functional form and make an initial guess for the parameters. You converge the wave functions with this functional, and calculate the energy and its derivatives with respect to the parameters in your functional for all of your molecules (this will probably require some heavy modifications to the quantum chemistry code). Next, you update the parameters by requiring that e.g. the root-mean-squared error is minimized for your molecular test set; if your parameters are linear then you get a matrix equation, if you have non-linear parameters you may end up having to do direct optimization with line searches and so on. Then, you recompute the wave functions, the energy and its derivatives for all your molecules, and re-fit. Once the parameters have converged, you're done.&lt;/p&gt;&#xA;&lt;p&gt;The real problem is ensuring that what you're doing actually makes sense. You have to have a large training set of molecules, ensure that the functional is numerically stable i.e. doesn't exhibit pathological grid dependence (e.g. SCAN is terrible in this respect even though it's &amp;quot;from first principles&amp;quot;), and make sure that the accuracy is transferable. These are all things that have been screwed up in one way or another in many recent functionals, except the aforementioned ones.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-01T14:55:34.913" LastActivityDate="2020-07-01T14:55:34.913" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1431" PostTypeId="2" ParentId="1428" CreationDate="2020-06-30T15:01:42.460" Score="14" Body="&lt;p&gt;An starting point can be the following review paper:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1088/0965-0393/13/1/R01&quot; rel=&quot;noreferrer&quot;&gt;Designing meaningful density functional theory calculations in materials science—a primer. Ann E Mattsson &lt;em&gt;et al&lt;/em&gt;. 2005 Modelling Simul. Mater. Sci. Eng. 13 R1 (DOI: 10.1088/0965-0393/13/1/R01)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As the authors state:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Our primary goal is to provide practical guidance in the design of&#xA;meaningful DFT simulations, and we discuss many of the computational&#xA;issues that need to be confronted. Adapting a set of calculations to&#xA;simulate a given physical property involves careful construction of a&#xA;model system and detailed manipulation of many options available in a&#xA;code. The need to check and verify the adequacy of any calculation&#xA;with respect to computational variables is repeatedly demonstrated. A&#xA;secondary goal is to encourage publishing salient calculational&#xA;details. For very large calculations, reporting the specifics is&#xA;especially important.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Another important guide can be the article:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://dx.doi.org/10.1063/1.1904565&quot; rel=&quot;noreferrer&quot;&gt;Prescription for the design and selection of density functional&#xA;approximations: More constraint satisfaction with fewer fits. John P. Perdew et a. J. Chem. Phys. 123, 062201 (2005); DOI: 10.1063/1.1904565)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here the authors addressed some issues like:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Is density functional theory &lt;em&gt;ab initio&lt;/em&gt;?&lt;/li&gt;&#xA;&lt;li&gt;Why the uniform density limit is sacrosanct.&lt;/li&gt;&#xA;&lt;li&gt;Is exact exchange needed?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A good question they ask is: &amp;quot;&lt;em&gt;Is there any secure place for empiricism in Kohn–Sham density functional theory?&lt;/em&gt;&amp;quot;. Later on, they answer: &amp;quot;&lt;em&gt;...we hope that empiricism can be completely avoided by modeling the adiabatic connection, somewhat as in Ref. 76. (Note, however, that limited empiricism&#xA;can provide a useful tack-on long-range van der Waals correction...)&lt;/em&gt;&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-06-30T15:01:42.460" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1432" PostTypeId="1" CreationDate="2020-06-30T16:34:08.500" Score="13" ViewCount="987" Body="&lt;p&gt;I am doing a CCSD(T) geometry optimization on a series of molecules. One of the geometry optimizations took about 2 weeks even though an analogous molecule with the same number of basis functions took less then 2 days to converge to a minimum. After 30 iterations, the calculation aborted with the 'error' message about exceeding the maximum number of iterations. I checked energies at different geometry optimization steps and noticed that the optimization had taken the molecule further from the minimal energy value so far. Furthermore, the bondlengths are more reasonable for the optimization step corresponding to the minimal energy value so far: the molecule should be symmetric (and it is at the 4th optimization step) but it's becoming a bit too asymmetric as the optimization progresses. Also, the energy seems to only change by a miniscule amount in the last iterations. I used the optimized geometry obtained from a CCSD calculation as the initial guess.&#xA;My route section:&#xA;#p opt=z-matrix freq=noraman rccsd(t)/genecp maxdisk=15950MB&lt;/p&gt;&#xA;&lt;p&gt;A mixed aug-cc-pVTZ-PP/aug-cc-pVTZ basis set was used in both CCSD and CCSD(T) calculatons.&lt;/p&gt;&#xA;&lt;p&gt;Now, I'm not sure that simply increasing the number of iterations will help... Any advice would be greatly appreciated!&lt;/p&gt;&#xA;&lt;p&gt;Update: I tried setting MaxStep to 5. It appeared to help at first because I reached a point where 3 out of 4 convergence criteria were satisfied. Even the remaining criterion was very close to the threshold value. The first calculation (with N=30) only produced some points with 2 satisfied convergence criteria. But then the calculation with MaxStep=5 started deviating as well. So I used this point with 3 satisfied convergence criteria as the initial guess for the next calculation (setting Maxstep to 1). A similar thing happened here. Here are the respective output fragments:&lt;/p&gt;&#xA;&lt;p&gt;MaxStep=5&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;`Maximum Force 0.000117 0.000450 YES &#xA;RMS Force 0.000060 0.000300 YES &#xA;Maximum Displacement 0.001992 0.001800 NO  &#xA;RMS Displacement 0.001109 0.001200 YES`&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;MaxStep=1&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;`Maximum Force 0.000116 0.000450 YES  &#xA; RMS Force 0.000060 0.000300 YES &#xA; Maximum Displacement 0.001911 0.001800 NO  &#xA; RMS Displacement 0.001007 0.001200 YES`&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YE5A4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YE5A4.png&quot; alt=&quot;Energies at different optimization steps&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="723" LastEditorUserId="5" LastEditDate="2020-08-01T00:52:20.113" LastActivityDate="2020-08-01T07:17:01.177" Title="A CCSD(T) geometry optimization in Gaussian09 is deviating too far from the minimum. How do I deal with it?" Tags="|ab-initio-calculations|quantum-chemistry|computational-chemistry|gaussian|coupled-cluster|" AnswerCount="2" CommentCount="18" ContentLicense="CC BY-SA 4.0" />
  <row Id="1433" PostTypeId="1" AcceptedAnswerId="1435" CreationDate="2020-06-30T17:36:14.777" Score="14" ViewCount="412" Body="&lt;p&gt;I am not very familiar with scanning a PES for a bulk structure, and I'd be very appreciative for some suggestions.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="792" LastEditDate="2020-07-12T09:56:43.490" LastActivityDate="2020-07-12T09:56:43.490" Title="How can I scan the whole PES of a bulk structure?" Tags="|density-functional-theory|computational-chemistry|phonons|potential-energy-surface|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1434" PostTypeId="1" CreationDate="2020-06-30T19:15:34.243" Score="13" ViewCount="666" Body="&lt;p&gt;I am currently designing a toy model to calculate an interatomic potential (for an infinite repeating lattice) this toy model needs to scale and perform better than DFT simulations. But sadly I have little knowledge of DFT simulations.&lt;/p&gt;&#xA;&lt;p&gt;I did find this paper ( &lt;a href=&quot;https://www.nature.com/articles/nphys1370&quot; rel=&quot;noreferrer&quot;&gt;https://www.nature.com/articles/nphys1370&lt;/a&gt; ) but it only specifies that the calculation time scales with O(N^3) (where N is the total number of atoms taken into account, or only in the unit cell?) and sadly I can't find any real numbers or benchmarks for the calculation time.&lt;/p&gt;&#xA;&lt;p&gt;The reason why I care about the real calculation time is that for example an algorithm which scales like O(N^2) but takes 20 seconds per 'sub calculation' is going to perform worse than a O(N^3) algorithm which takes 1 second per 'sub calculation' as long as N&amp;lt;20.&lt;/p&gt;&#xA;&lt;p&gt;So my question: Does anybody know of any benchmarks of DFT simulations?&lt;/p&gt;&#xA;" OwnerUserId="985" LastEditorUserId="5" LastEditDate="2020-06-30T22:59:20.177" LastActivityDate="2020-07-15T12:06:45.007" Title="What is the speed/time required for DFT simulations?" Tags="|density-functional-theory|software|high-performance-computing|algorithms|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1435" PostTypeId="2" ParentId="1433" CreationDate="2020-06-30T20:46:18.040" Score="12" Body="&lt;p&gt;The potential energy surface (PES) is a 3N-dimensional function for a bulk system containing N atoms (in reality 3N-3 to account for the trivial translational degrees of freedom). For a bulk structure, N typically represents the number of atoms in a simualtion cell with periodic boundary conditions, which is of the order of &lt;span class=&quot;math-container&quot;&gt;$10^2$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$10^3$&lt;/span&gt;, so the function is of very high dimension. The number &lt;span class=&quot;math-container&quot;&gt;$10^2$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$10^3$&lt;/span&gt; comes from a typical DFT calculation; if you use cheaper methods (e.g. force fields) then that number can be larger, or if the method is more expensive (e.g. quantum chemistry) then the number is somewhat smaller. In any case, you are sampling a high dimensional function, which is an extremely hard problem.&lt;/p&gt;&#xA;&lt;p&gt;So what can be done to scan this potential energy surface? These are a few options:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Phonon calculations.&lt;/strong&gt; A (meta)stable bulk structure sits at a local minimum of the PES. A phonon calculation determines the Hessian around this minimum, that is, the curvature of the PES around the minimum. Phonon calculations are relatively straight-forward to perform (say at the DFT level), and typically provide very useful information about the low-energy part of the PES. This is useful for calculating thermodynamic properties of a crystal at relatively low temperatures (when atoms do not move very far away from the minimum). One can explore a little further away by including terms beyond the second derivative in the expansion about the minimum (referred to as anharmonic terms), but these still essentially give a local view of the PES around the minimum.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Transition states.&lt;/strong&gt; Considering two structures associated with two nearby minima in the PES, it is possible to locate the minimum energy path between the two. This path goes through a saddle point of the PES, which is called a transition state. A well-known technique to find this is the nudged elastic band method, which requires knowledge of the two minima and calculates the saddle point. Another method that can allow one to &amp;quot;jump&amp;quot; from one minimum to another nearby minimum is molecular dynamics. These methods still provide a local view of the PES, but they explore it in a wider region than a phonon calculation would.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Structure prediction.&lt;/strong&gt; If you want a more uniform sampling of the PES, then you are entering the realm of structure prediction. These methods try to explore as many minima as possible of the potential energy surface. The basic idea is to generate structures at random (corresponding to arbitrary points in the PES) and then relax them to the local minimum. Repeating this many times allows you to explore basins around different minima of the PES. There are different methods that allow you to do this, which differ by how they generate the &amp;quot;next&amp;quot; structure (e.g. stochastic, genetic, particle swarm algorithms). These methods provide a global view of the potential energy surface, but lack in detail, so, for example, would have to be complemented with phonon calculations to explore the important low-energy region of a material at low temperatures.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;David Wales has a book on some of this, you can find more details in his &lt;a href=&quot;https://www.ch.cam.ac.uk/group/wales/energy-landscapes-book-0&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-01T04:59:41.470" LastActivityDate="2020-07-01T04:59:41.470" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1436" PostTypeId="2" ParentId="1359" CreationDate="2020-06-30T21:26:04.983" Score="12" Body="&lt;p&gt;When I first read your question, I found it somewhat puzzling. I have to admit, I still do in part. Why? Well, even your link defines &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; as a sum of matrix elements &lt;span class=&quot;math-container&quot;&gt;$\langle m,m'|V_{ee}|m',m\rangle$&lt;/span&gt;. Mathematically, each of these matrix elements is an integral involving wave functions in the system. If we know these wave functions or know how to approximate them it is conceptually straight-forward to calculate the integrals, save for possible divergences. Leaving such issues aside, I'd say &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is eminently quantifiable, at least in principle. (And demonstrably also in practice for e.g. few-body systems and atoms.)&lt;/p&gt;&#xA;&lt;p&gt;Now, I suspect the above is a kind of pedantic answer that doesn't really get to the heart of the question you wanted to ask. In the question itself and your comments below it, you make a clear distinction between the Hubbard &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; and Hund's &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; by saying one is linked to on-site electron-electron interactions and calling the other a pure exchange effect. You then ask how &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; can be given a value similar to that of the Coulomb repulsion. This suggests that there might be a misconception about the nature of exchange effects at play. In fact, Hund's type exchange while magnetic in effect, is due to a combination of the Coulomb force and the Pauli exclusion principle.&lt;/p&gt;&#xA;&lt;h2&gt;A simple version&lt;/h2&gt;&#xA;&lt;p&gt;The simplest version of this physics shows up already in the treatment of two-electron atoms (notably Helium). This problem is discussed in textbooks like Sakurai's Modern Quantum Mechanics in more detail than I will go here. Thus I'll just jump to the result for the energy associated with the Coulomb repulsion between the two electrons (which is treated as a perturbation on top of a non-interacting ground state):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left\langle \frac{e^2}{r_{12}} \right\rangle = I \pm J, \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$r_{12}$&lt;/span&gt; is the distance between the two electrons. The upper sign goes with a spin singlet state, and the minus sign with a spin triplet state. &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; are called the direct and exchange integrals, given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;I = \int \mathrm{d}^3 \mathbf{x}_1 \int \mathrm{d}^3 \mathbf{x}_2 | \psi_{100} \left( \mathbf{x}_1 \right)|^2 | \psi_{nlm} \left( \mathbf{x}\right)|^2 \frac{e^2}{r_{12}},\tag{2}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;J = \int \mathrm{d}^3 \mathbf{x}_1 \int \mathrm{d}^3 \mathbf{x}_2  \psi_{100} \left( \mathbf{x}_1 \right)  \psi_{nlm} \left( \mathbf{x}_2\right) \frac{e^2}{r_{12}} \psi_{100}^\star \left( \mathbf{x}_2 \right)  \psi_{nlm}^\star \left( \mathbf{x}_1\right).\tag{3}&#xA;$$&lt;/span&gt;&#xA;I don't want to go into detail about the notation here, but the difference in structure is clear. In &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; we have a density-density interaction, but &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; involves a mixing or exchange of the two wave functions at the two coordinates. While the sign of &lt;span class=&quot;math-container&quot;&gt;$\pm J$&lt;/span&gt; is determined by the spin state and enforced by the antisymmetry of the wave function, the magnitude &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is set by the Coulomb repulsion, and is indeed quantifiable.&lt;/p&gt;&#xA;&lt;h2&gt;In materials&lt;/h2&gt;&#xA;&lt;p&gt;I will here loosely follow the notation of another book I like: Physics of Transition Metal Oxides by Maekawa et al. For concreteness we consider two &lt;span class=&quot;math-container&quot;&gt;$3d$&lt;/span&gt; elecrons, labeled &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;, with positions &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt; and wave functions &lt;span class=&quot;math-container&quot;&gt;$\Psi(r_1)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Psi(r_2)$&lt;/span&gt;. In the context of this stack we can think of them either as two localized molecular orbitals (as in &lt;a href=&quot;https://en.wikipedia.org/wiki/Linear_combination_of_atomic_orbitals&quot; rel=&quot;nofollow noreferrer&quot;&gt;LCAO&lt;/a&gt;) or as two &lt;a href=&quot;https://en.wikipedia.org/wiki/Wannier_function&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wannier functions&lt;/a&gt;. The Coulomb interaction between them is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \frac{1}{2} \int \int \Psi^\dagger (r_1) \Psi^\dagger (r_2) \frac{e^2}{|r_1-r_2|} \Psi(r_2) \Psi(r_1) \mathrm{d}\tau_1\tau_2,\tag{4}&#xA;$$&lt;/span&gt;&#xA;where we integrate over spatial variables and sum over spin degrees of freedom. (Both steps are hidden inside the &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; symbols.) We can now decompose the wave function&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Psi (r) = \sum_{n,m,\sigma} c_{nm\sigma} \psi_{nm} (r) \theta_\sigma,\tag{5}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; denotes site, &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; denotes orbital quantum number, and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; the spin quantum number. &lt;span class=&quot;math-container&quot;&gt;$\psi_{nm}$&lt;/span&gt; is the spatial wave function, and &lt;span class=&quot;math-container&quot;&gt;$\theta_\sigma$&lt;/span&gt; is the spin wave function. In second quantization, &lt;span class=&quot;math-container&quot;&gt;$c_{nm\sigma}$&lt;/span&gt; is the annihilation operator associated with an electron with these quantum numbers. Then, if we include the spatial integration inside the matrix elements, we can write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H   = \frac{1}{2} \sum_{n,m,\sigma} \langle n_1 m_1, n_2m_2| \frac{e^2}{|r_1-r_2|} | n_3m_3,n_4m_4\rangle c^\dagger_{n_1 m_1 \sigma_1} c^\dagger_{n_2 m_2 \sigma_2} c_{n_4 m_4 \sigma_2} c_{n_3 m_3 \sigma_1}.\tag{6}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This expression includes multiple processes. First, we have the one-site (&lt;span class=&quot;math-container&quot;&gt;$n_1=n_2=n_3=n_4=n$&lt;/span&gt;) one-orbital (&lt;span class=&quot;math-container&quot;&gt;$m_1=m_2=m_3=m_4$&lt;/span&gt;) case,,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H_U = \frac{1}{2}\sum_\sigma \langle n,n| \frac{e^2}{|r_1-r_2|} | n,n\rangle c^\dagger_{n\sigma}c^\dagger_{n,-\sigma} c_{n,-\sigma} c_{n\sigma} = Un_{n\uparrow}n_{n\downarrow},\tag{7}&#xA;$$&lt;/span&gt;&#xA;with &lt;span class=&quot;math-container&quot;&gt;$n_{n\sigma}=c_{n\sigma}^\dagger c_{n\sigma}$&lt;/span&gt;. This is of course nothing but our friend the Hubbard interaction, where the messy details of the matrix element is hidden behind the symbol &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Two electron on the same site (&lt;span class=&quot;math-container&quot;&gt;$n_1=n_2=n_3=n_4=n$&lt;/span&gt;), but in different orbitals produce the so-called Hund coupling (c.f. Hund's rules). We get&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;H_H =   \frac{1}{2} \langle m_1,m_2 | \frac{e^2}{|r_1-r_2|} |m_1,m_2\rangle \sum_{\sigma_1,\sigma_2} c_{m_1\sigma_1}^\dagger c_{m_1\sigma_1}c_{m_2\sigma_2}^\dagger c_{m_2\sigma_2} \tag{8}\\&#xA;    - \frac{1}{2} \langle m_1,m_2 | \frac{e^2}{|r_1-r_2|} |m_2,m_1\rangle  \sum_{\sigma_1,\sigma_2} c_{m_1\sigma_1}^\dagger c_{m_1\sigma_2}c_{m_2\sigma_2}^\dagger c_{m_2\sigma_1}\tag{9}\\&#xA;    \equiv K_{m_1m_2} n_{n_1}n_{n_2} - 2J_{m_1m_2} \left( \mathbf{S}_{m_1m_2}\cdot \mathbf{S}_{n_2} + \frac{1}{4} n_{m_1}m_{n_2}\right).\tag{10}&#xA;\end{align}&lt;/span&gt;&#xA;Here &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is a on-site inter-orbital Coulomb density-density interaction, and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; represents the Hund's coupling. You can see that this matches (up to coefficients) Eq. (11) in the &lt;a href=&quot;https://www.cond-mat.de/events/correl12/manuscripts/cococcioni.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;notes&lt;/a&gt; you linked in the question. Note that the magnitude of &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;, like that of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, is related to the strength of the Coulomb force between the two electrons.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, inter-site terms like direct exchange can be derived, and ultimately quantified.&lt;/p&gt;&#xA;&lt;h2&gt;First-principles calculation&lt;/h2&gt;&#xA;&lt;p&gt;Although the Hubbard &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; and Hund &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; are often treated as semi-empirical parameters in materials modeling, and sometimes assigned values using rules of thumb (that I don't know the origin of), there are some first-principles frameworks that can be employed to calculate them accurately. To get reliable values, screening effects must be taken into account. This can be done while downfolding to effective Hamiltonians using e.g. the constrained Random Phase Approximation (cRPA) and constrained GW approximation, which can use DFT band structures as inputs (though there are subtleties concerning double-counting of correlation effects). For details on cRPA see e.g. Chapter 7 in &lt;a href=&quot;https://www.cond-mat.de/events/correl11/manuscripts/correl11.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this set of lecture notes&lt;/a&gt;. For cGW, some developments are described in &lt;a href=&quot;https://arxiv.org/abs/1211.0597&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://arxiv.org/abs/1901.00763&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It's worth noting that such calculations often uncover significant non-local (i.e. intersite) Coulomb interactions, see e.g. &lt;a href=&quot;https://arxiv.org/abs/1904.01523&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; on &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-RuCl&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; from last year and references therein. Such non-local interactions are often overlooked, but might have important effects in strongly correlated systems.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="5" LastEditDate="2020-12-31T04:12:45.890" LastActivityDate="2020-12-31T04:12:45.890" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1437" PostTypeId="2" ParentId="1360" CreationDate="2020-07-01T03:13:51.863" Score="8" Body="&lt;p&gt;Recently chemical graph theory has been used to give more physical and chemical insight on whether destructive quantum interference exists or not. Hope that helps. Let me know if I can help further.&lt;/p&gt;&#xA;&lt;p&gt;Tsuji, Yuta, Ernesto Estrada, Ramis Movassagh, and Roald Hoffmann. &amp;quot;Quantum interference, graphs, walks, and polynomials.&amp;quot; Chemical reviews 118, no. 10 (2018): 4887-4911.&lt;/p&gt;&#xA;" OwnerUserId="604" LastEditorUserId="5" LastEditDate="2020-07-01T03:19:06.027" LastActivityDate="2020-07-01T03:19:06.027" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1438" PostTypeId="1" CreationDate="2020-07-01T03:57:25.613" Score="16" ViewCount="1252" Body="&lt;p&gt;I did this in VASP but I guess this would be the case for any program. I have a structure that has a cubic conventional cell (a = 9.86 A). I found the primitive cell (a=b=c=6.97, alpha=90, beta=60, gamma=120) and used that as the input structure.&lt;/p&gt;&#xA;&lt;p&gt;I relaxed the structure and that results in changes in the cell (a=7.23,b=6.97,c=7.2,alpha=90.99,beta=58.1,gamma=121).&lt;/p&gt;&#xA;&lt;p&gt;Isn't the cubic symmetry now broken because the lattice parameters and angles have all changed? How do I go from the relaxed primitive cell back to the conventional cubic cell??&lt;/p&gt;&#xA;&lt;p&gt;Edit:&#xA;Initial CIF file (conventional cell), as well as the input POSCAR (primitive cell) and output CONTCAR files are here: &lt;a href=&quot;https://github.com/DoubleKx/arg_example&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/DoubleKx/arg_example&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Edit2: I'm trying to replicate the examples from &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemmater.6b02648&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. I'm on Part 1. I've found the primitive cell, enumerated the structure, and run a relaxation (on just one of the enumerated structures).&lt;/p&gt;&#xA;" OwnerUserId="979" LastEditorUserId="979" LastEditDate="2020-07-01T21:17:58.877" LastActivityDate="2020-07-01T21:17:58.877" Title="How to convert from primitive to conventional after structure relaxation?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1439" PostTypeId="1" CreationDate="2020-07-01T07:52:28.770" Score="45" ViewCount="9013" Body="&lt;p&gt;I am evaluating the atomic charge of a system using inter-atomic potentials and comparing with using DFT. I know about the following types of partial charge: Mulliken, Bader, Qeq. I wonder what are the differences between the methods, such as pros and cons.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps we can get an answer explaining each of the following types of &lt;a href=&quot;https://en.wikipedia.org/wiki/Partial_charge&quot; rel=&quot;noreferrer&quot;&gt;partial charge&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;B̶a̶d̶e̶r̶ &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1444/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;M̶u̶l̶l̶i̶k̶e̶n̶, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1447/5&quot;&gt;[link to answer]&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1465/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;L̶ö̶w̶d̶i̶n̶, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1465/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;E̶S̶P̶-̶d̶e̶r̶i̶v̶e̶d̶ &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1450/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coulson,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;natural charges,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;C̶M̶5̶ &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1446/5&quot;&gt;[link to answer]&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;density fitted,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;H̶i̶r̶s̶h̶f̶e̶l̶d̶ &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1446/5&quot;&gt;[link to answer]&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Maslen,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Politzer,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;V̶o̶r̶o̶n̶o̶i̶, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1505/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;D̶D̶E̶C̶, [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2294/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;NBO-based,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;dipole-based,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;ATP/Born/Callen/Szigeti,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Chelp,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;C̶h̶e̶l̶p̶G̶ ̶(̶B̶r̶e̶n̶e̶m̶a̶n̶)̶ &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1450/5&quot;&gt;[link to answer]&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Merz-Singh-Kollman,&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;formal charges;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;any QM or theoretically derived charge model.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here is a good &lt;a href=&quot;http://bigdft.org/images/5/54/2011-10_AS_Charges.pdf&quot; rel=&quot;noreferrer&quot;&gt;starting point&lt;/a&gt; for anyone that wants to explain one of the above types of partial charge in the format of my (Nike Dattani's) answer.&lt;/p&gt;&#xA;" OwnerUserId="748" LastEditorUserId="5" LastEditDate="2020-09-16T23:40:25.070" LastActivityDate="2023-08-09T00:05:46.853" Title="What are the types of charge analysis?" Tags="|one-topic-per-answer|conceptual-dft|atoms-in-molecules|" AnswerCount="10" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1440" PostTypeId="2" ParentId="1438" CreationDate="2020-07-01T08:10:07.000" Score="8" Body="&lt;p&gt;From what I understand in your question you have you started with a conventional cell with bases &lt;span class=&quot;math-container&quot;&gt;$B_{conv}$&lt;/span&gt; and you found a transformation matrix &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; to the unit cell such that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{unit} = C B_{conv}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then you relaxed the unit cell and you received a &amp;quot;new&amp;quot; unit cell &lt;span class=&quot;math-container&quot;&gt;$\tilde{B}_{unit}$&lt;/span&gt;. The closest approximation to your old conventional cell should thus be.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\tilde{B}_{conv} = C^{-1} \tilde{B}_{unit}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Naturally, it will not be perfectly cubic again as the first unit cell was relaxed.&lt;/p&gt;&#xA;" OwnerUserId="250" LastActivityDate="2020-07-01T08:10:07.000" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1441" PostTypeId="2" ParentId="1439" CreationDate="2020-07-01T14:59:38.880" Score="12" Body="&lt;p&gt;Don't use Mulliken for charge analysis. It is basically a random number generator, since it lacks a basis set limit. By choosing a different basis set representation, you can basically freely move the electrons around; e.g. in a one-center expansion all the electrons are counted for the expansion center whereas all the other nuclei in the system become bare. The same problem also exists in the Löwdin method (which somehow many people think is better!) but in a much worse way.&lt;/p&gt;&#xA;&lt;p&gt;Bader charges are often exaggerated.&lt;/p&gt;&#xA;&lt;p&gt;I've never heard of Qeq charges.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-08T10:05:05.730" LastActivityDate="2020-07-08T10:05:05.730" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1442" PostTypeId="1" CreationDate="2020-07-01T15:36:53.650" Score="6" ViewCount="243" Body="&lt;p&gt;I have been assigned a project on the generation of a force-field of Al (aluminum) for a LAMMPS potential.&lt;/p&gt;&#xA;&lt;p&gt;I have no idea how to proceed and what to do next. Can anyone please let me know how should I proceed further?&lt;/p&gt;&#xA;" OwnerUserId="989" LastEditorUserId="5" LastEditDate="2020-07-01T16:56:42.627" LastActivityDate="2020-07-01T16:56:42.627" Title="How do I generate an aluminum force-field for a LAMMPS input file?" Tags="|molecular-modeling|molecular-dynamics|pseudopotentials|lammps|forcefields|" AnswerCount="0" CommentCount="4" ClosedDate="2020-07-11T19:18:12.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="1443" PostTypeId="2" ParentId="1439" CreationDate="2020-07-01T15:55:55.933" Score="18" Body="&lt;p&gt;To give a example of the &amp;quot;random number generator&amp;quot; behavior of &lt;a href=&quot;https://en.wikipedia.org/wiki/Mulliken_population_analysis&quot; rel=&quot;noreferrer&quot;&gt;Mulliken charge analysis&lt;/a&gt; pointed by @SusiLehtola, below I'm showing the results of some test runs I did before on the CO2 molecule using &lt;a href=&quot;http://www.psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt; version 1:1.1-5 (default version on Ubuntu 18.04 repository as of july 2020).&lt;/p&gt;&#xA;&lt;p&gt;For reproducibility purposes, first my input files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~/Documentos/stackexchange$ more *.in | cat&#xA;::::::::::::::&#xA;CO2_dipole_631plusGd.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  6-31+G(d)&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_631plusplusGdp.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  6-31++G(d_p)&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_augccpVDZ.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  aug-cc-pVDZ&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_augccpVTZ.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  aug-cc-pVTZ&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_augpcseg1.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  aug-pcseg-1&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_augpcseg2.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  aug-pcseg-2&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_pcseg1.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  pcseg-1&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;::::::::::::::&#xA;CO2_dipole_pcseg2.in&#xA;::::::::::::::&#xA;memory 4 Gb&#xA;&#xA;set basis  pcseg-2&#xA;molecule {&#xA;0 1&#xA;   C       -3.47367        0.73246        0.22361&#xA;   O       -2.43476        1.12414       -0.22175&#xA;   O       -4.51237        0.34053        0.66926&#xA;}&#xA;optimize('B3LYP-D')&#xA;E, wfn = energy('B3LYP-D', return_wfn=True)&#xA;oeprop(wfn, &amp;quot;MULLIKEN_CHARGES&amp;quot;, &amp;quot;DIPOLE&amp;quot;, title = &amp;quot;CO2 B3LYP-D&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now the results I got:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~/Documentos/stackexchange$ grep -A 4 'Mulliken Charges: (a.u.)' *.out&#xA;CO2_dipole_631plusGd.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_631plusGd.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_631plusGd.out-       1     C     2.62564  2.62564  0.00000  0.74871&#xA;CO2_dipole_631plusGd.out-       2     O     4.18718  4.18718  0.00000 -0.37436&#xA;CO2_dipole_631plusGd.out-       3     O     4.18718  4.18718  0.00000 -0.37436&#xA;--&#xA;CO2_dipole_631plusplusGdp.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_631plusplusGdp.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_631plusplusGdp.out-       1     C     2.62564  2.62564  0.00000  0.74871&#xA;CO2_dipole_631plusplusGdp.out-       2     O     4.18718  4.18718  0.00000 -0.37436&#xA;CO2_dipole_631plusplusGdp.out-       3     O     4.18718  4.18718  0.00000 -0.37436&#xA;--&#xA;CO2_dipole_augccpVDZ.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_augccpVDZ.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_augccpVDZ.out-       1     C     2.82315  2.82315  0.00000  0.35370&#xA;CO2_dipole_augccpVDZ.out-       2     O     4.08842  4.08842  0.00000 -0.17685&#xA;CO2_dipole_augccpVDZ.out-       3     O     4.08843  4.08843  0.00000 -0.17686&#xA;--&#xA;CO2_dipole_augccpVTZ.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_augccpVTZ.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_augccpVTZ.out-       1     C     2.80993  2.80993  0.00000  0.38014&#xA;CO2_dipole_augccpVTZ.out-       2     O     4.09503  4.09503  0.00000 -0.19007&#xA;CO2_dipole_augccpVTZ.out-       3     O     4.09504  4.09504  0.00000 -0.19007&#xA;--&#xA;CO2_dipole_augpcseg1.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_augpcseg1.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_augpcseg1.out-       1     C     2.35311  2.35311  0.00000  1.29377&#xA;CO2_dipole_augpcseg1.out-       2     O     4.32345  4.32345  0.00000 -0.64689&#xA;CO2_dipole_augpcseg1.out-       3     O     4.32344  4.32344  0.00000 -0.64688&#xA;--&#xA;CO2_dipole_augpcseg2.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_augpcseg2.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_augpcseg2.out-       1     C     2.51884  2.51884  0.00000  0.96233&#xA;CO2_dipole_augpcseg2.out-       2     O     4.24057  4.24057  0.00000 -0.48114&#xA;CO2_dipole_augpcseg2.out-       3     O     4.24059  4.24059  0.00000 -0.48119&#xA;--&#xA;CO2_dipole_pcseg1.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_pcseg1.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_pcseg1.out-       1     C     2.71634  2.71634  0.00000  0.56732&#xA;CO2_dipole_pcseg1.out-       2     O     4.14183  4.14183  0.00000 -0.28366&#xA;CO2_dipole_pcseg1.out-       3     O     4.14183  4.14183  0.00000 -0.28366&#xA;--&#xA;CO2_dipole_pcseg2.out:  Mulliken Charges: (a.u.)&#xA;CO2_dipole_pcseg2.out-   Center  Symbol    Alpha    Beta     Spin     Total&#xA;CO2_dipole_pcseg2.out-       1     C     2.70233  2.70233  0.00000  0.59534&#xA;CO2_dipole_pcseg2.out-       2     O     4.14883  4.14883  0.00000 -0.29767&#xA;CO2_dipole_pcseg2.out-       3     O     4.14883  4.14883  0.00000 -0.29767&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, the results on Mulliken charge analysis can change a lot, depending on the basis set you use to run the calculation. About Bader and Qeq charges, I haven't much to say, as I lack experience dealing with them.&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2020-07-01T15:55:55.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1444" PostTypeId="2" ParentId="1439" CreationDate="2020-07-01T16:40:14.570" Score="24" Body="&lt;h2&gt;Bader charge analysis&lt;/h2&gt;&#xA;&lt;p&gt;In Bader's theory of &lt;em&gt;Atoms in Molecules&lt;/em&gt;, we partition a molecule into &amp;quot;atoms&amp;quot; which are separated from each other by surfaces of minimum charge density:&lt;/p&gt;&#xA;&lt;p&gt;                                          &lt;img src=&quot;https://i.stack.imgur.com/mjQzH.png&quot; width=&quot;300&quot;&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can then calculate the partial charges of the &amp;quot;atoms&amp;quot; in the molecule, e.g. H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O might yield:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{cc}&#xA;\rm{Atom} &amp;amp; \rm{Charge}\\&#xA;\hline&#xA;\rm{O} &amp;amp; -1.150\\&#xA;\rm{H} &amp;amp; +0.425\\&#xA;\rm{H} &amp;amp; +0.425&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Meaning that each hydrogen has &amp;quot;given away&amp;quot; 0.575 of an electron.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There is an &lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;nofollow noreferrer&quot;&gt;up-to-date code&lt;/a&gt; last updated in 2020, and available in &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorials/bader/bader.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GPAW&lt;/a&gt;, &lt;a href=&quot;http://bigdft.org/Wiki/index.php?title=Bader_charge_analysis&quot; rel=&quot;nofollow noreferrer&quot;&gt;BigDFT&lt;/a&gt;, VASP and CASTEP. It is also implemented for VASP in &lt;a href=&quot;https://github.com/jkitchin/vasp/blob/master/vasp/bader.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this python script&lt;/a&gt; and also &lt;a href=&quot;http://www.demon-software.com/public_html/support/htmlug/ug-node105.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;available in deMon2k&lt;/a&gt;. Martin's comment says it's also available in Multiwfn. A 3rd option is the &lt;a href=&quot;https://github.com/materialsproject/pymatgen/blob/7c70c1ad5a1c489bfb5e4fbd53804630ac48d248/pymatgen/command_line/bader_caller.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;BaderAnalysis&lt;/code&gt; class&lt;/a&gt; in &lt;code&gt;pymatgen&lt;/code&gt; for use with VASP and Cube.&lt;/li&gt;&#xA;&lt;li&gt;It is based on the density rather than the wavefunction. &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1394/5&quot;&gt;Walter Kohn also believes the wavefunction is inappropriate for large molecules&lt;/a&gt; but has no problem with the density.&lt;/li&gt;&#xA;&lt;li&gt;Susi's comment says that Bader's method has a basis set limit; and Susi's and ksousa's answers explain that the Mulliken method doesn't have a well-defined basis set limit, so it won't converge to anything when you approach towards a complete basis set.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I will need help here. I only found out what &amp;quot;charge analysis&amp;quot; is after doing research to try to answer this question. I've never used (or learned) Mulliken, Bader, or any other type of charge analysis before.&lt;/li&gt;&#xA;&lt;li&gt;Susi mentioned that Bader charges can be counterintuitive, which based on my hour of research on the topic today, seems to be a fundament of Bader's AIM concept for interpreting chemical bonds in general.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/users/206/andrew-rosen&quot;&gt;Andrew Rosen&lt;/a&gt; pointed out that &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.10351&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; describes another con.  Indeed, my reading of the article's abstract found a claim that Bader charge analysis can suggest ionic character even for covalent bonds.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="3677" LastEditDate="2023-08-09T00:05:46.853" LastActivityDate="2023-08-09T00:05:46.853" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1445" PostTypeId="1" CreationDate="2020-07-01T17:06:13.483" Score="21" ViewCount="348" Body="&lt;p&gt;I'm currently trying to surface reaction of small molecules on metal oxides in VASP. Several papers I've read have approached surface energy calculations in a variety of ways. I first began looking at how surface energies are obtained without any adsorbates considered. This seemed like a logical starting point since I assumed the surface energy would be calculated via &lt;span class=&quot;math-container&quot;&gt;$E(\text{Surface+Adsorbate})-(E(\text{Surface})+E(\text{Adsorbate}))$&lt;/span&gt;, so I would need to find the clean surface energy to start with.&lt;/p&gt;&#xA;&lt;p&gt;The best approach to reach a converged seems to have received some debate. Fiorentini and Methfessel [1] finds that the widely used expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sigma=\lim_{N\to\infty}\frac{1}{2}(E_\text{slab}^N-NE_\text{bulk})\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;is poor at reaching a stable converged surface energy, where N represents the number of slab layers. Instead they find the expression (linear fit to slab energies):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_\text{slab}^N\approx2\sigma+NE_\text{bulk}\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;reaches a stable convergence. A later study [2] finds the first expression to be adequate at reaching surface energies only when large enough k-point set is used.&lt;/p&gt;&#xA;&lt;p&gt;When it comes to adsorption energies on surfaces I mostly find that researchers [3] [4] approach the calculations using a semi-infinite slab  where the top layers are allowed to relax and an arbitrary 1 or 2 layers are frozen below. However, I've yet to find a critical evaluation of such approach. Is it worth performing a series of convergence tests on the number of layers frozen, as well as the number of layers themselves? I can imagine this would become quite time consuming.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, I have seen others suggest that a better approach is using a symmetrical slab model. That is, putting the same adsorbate on  the &amp;quot;bottom&amp;quot; side of the slab in exactly the same geometry as the top. Again, I would like to hear people's thoughts on this choice of method, and whether this approach has more 'validity' than the semi-infinite approach. Any paper recommendations welcome to, I found the Fiorentini and Methfessel paper in a discussion on the VASP forum.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Fiorentini, V., &amp;amp; Methfessel, M. (1996). Extracting convergent surface energies from slab calculations. Journal of Physics Condensed Matter, 8(36), 6525–6529.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Da Silva, J. L. F., Stampfl, C., &amp;amp; Scheffler, M. (2006). Converged properties of clean metal surfaces by all-electron first-principles calculations. Surface Science, 600(3), 703–715.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Lischka, M., &amp;amp; Groß, A. (2003). Hydrogen on palladium: a model system for the interaction of atoms and molecules with metal surfaces. Recent Developments in Vacuum Science and Technology, 661(2), 111–132.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Mamun, O., Winther, K. T., Boes, J. R., &amp;amp; Bligaard, T. (2019). High-throughput calculations of catalytic properties of bimetallic alloy surfaces. Scientific Data, 6(1), 1–9.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="990" LastEditorUserId="7" LastEditDate="2020-07-01T19:00:51.917" LastActivityDate="2020-07-06T20:15:45.343" Title="Semi-infinite surfaces for adsorption: a valid approach?" Tags="|density-functional-theory|vasp|adsorption|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1446" PostTypeId="2" ParentId="1439" CreationDate="2020-07-01T20:11:39.967" Score="20" Body="&lt;h2&gt;Hirshfeld / CM5 (Charge Model 5)&lt;/h2&gt;&#xA;&lt;p&gt;My main interest is in explaining CM5 charges, but to do that it's necessary to briefly explain what Hirshfeld charges are.&lt;/p&gt;&#xA;&lt;p&gt;Hirshfeld charges are obtained as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$q_X=Z_X-\int\frac{\rho^0_X(\mathbf{r})}{\sum_Y\rho^0_Y(\mathbf{r})}\rho(r)d\mathbf{r}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$Z_X$&lt;/span&gt; is the atomic number of element &lt;span class=&quot;math-container&quot;&gt;$\ce{X}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the molecular density and &lt;span class=&quot;math-container&quot;&gt;$\rho_X^0$&lt;/span&gt; is density of &lt;span class=&quot;math-container&quot;&gt;$\ce{X}$&lt;/span&gt; as an isolated atom. Essentially, the density, and thus the charge, is partitioned in proportion to the atomic density. This approach has been found to be &lt;strong&gt;less basis set dependent&lt;/strong&gt; than similar population analysis methods (e.g. Mulliken, Lowdin).&lt;/p&gt;&#xA;&lt;p&gt;One &lt;strong&gt;drawback&lt;/strong&gt; is that Hirshfeld charges alone don't do a great job of reproducing experimental observables like the molecular dipole moment, suggesting they may not be physically reasonable. This is where CM5 (Charge Model 5) charges come into play [1]. These are obtained as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$q_k^\text{CM5}=q_k^{\text{Hirsh}}+\sum_{k'\neq k}T_{kk'}B_{kk'}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$B_{kk'}=\exp\big[-\alpha(r_{kk'}-R_{Z_k}-R_{Z_{k'}})\big]$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T_{k,k'}=\begin{cases}D_{Z_k,Z_{k'}} &amp;amp; Z_k,Z_{k'}=1,6,7,8 (\ce{H,C,N,O})\\&#xA;D_{Z_k}-D_{Z_{k'}} &amp;amp; \text{other elements}\end{cases}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The basis idea is that the Hirshfeld charge are corrected based on the bond order between two atoms &lt;span class=&quot;math-container&quot;&gt;$B_{kk'}$&lt;/span&gt;. The bond order itself is parameterized by &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and its effect on the charge of a given element is parameterized by &lt;span class=&quot;math-container&quot;&gt;$T_{kk'}$&lt;/span&gt;, more specifically the underlying &lt;span class=&quot;math-container&quot;&gt;$D_k$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$D_{k,k'}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k'$&lt;/span&gt; index all the atoms in the molecule, but &lt;span class=&quot;math-container&quot;&gt;$T_{kk'}$&lt;/span&gt; only depends on which two elements are involved). This approach gives physically &lt;strong&gt;reasonable&lt;/strong&gt; atomic charges that can be used to &lt;strong&gt;accurately&lt;/strong&gt; calculate molecular dipole moments. Since Hirshfeld charges are fairly &lt;strong&gt;simple to compute&lt;/strong&gt; for any SCF calculation, CM5 charges can &lt;strong&gt;easily&lt;/strong&gt; be added on top.&lt;/p&gt;&#xA;&lt;p&gt;The main &lt;strong&gt;drawback&lt;/strong&gt; is that CM5 was only parameterized for some elements (&lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{Ca}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{Br}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{I}$&lt;/span&gt;, along with some special parameters for common organic pairs like &lt;span class=&quot;math-container&quot;&gt;$\ce{O-H}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{C-H}$&lt;/span&gt;, etc.). However there are still values for all elements. &lt;span class=&quot;math-container&quot;&gt;$D_{Z_K}$&lt;/span&gt; is set equal to 0 for all transitions metals, Lanthanides, and Actinides and the elements in the same column of the periodic table are constrained to satisfy &lt;span class=&quot;math-container&quot;&gt;$D_{Z_k}=CD_{\bar{Z_k}}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is another parameter &lt;span class=&quot;math-container&quot;&gt;$\bar{Z_k}$&lt;/span&gt; refers to the next element up in the column.&lt;/p&gt;&#xA;&lt;p&gt;CM&lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; charges with &lt;span class=&quot;math-container&quot;&gt;$x&amp;lt;5$&lt;/span&gt; employ a similar approach, but were parameterized on small training sets to correct Lowdin charges. Due to the basis set dependence of Lowdin charges, they are only suitable for use with certain small basis sets, the largest being 6-31+G(d,p).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Aleksandr V. Marenich, Steven V. Jerome, Christopher J. Cramer, and Donald G. Truhlar&#xA;Journal of Chemical Theory and Computation 2012 8 (2), 527-541&#xA;DOI: 10.1021/ct200866d&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-09-16T22:26:49.467" LastActivityDate="2020-09-16T22:26:49.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1447" PostTypeId="2" ParentId="1439" CreationDate="2020-07-01T20:40:35.483" Score="18" Body="&lt;h1&gt;Mulliken population analysis&lt;/h1&gt;&#xA;&lt;p&gt;The Mulliken charge scheme is based on the Linear Combination of Atomic Orbitals (LCAO), so, it is based on the system wave function and was described in a series of papers by R. S. Mulliken&lt;sup&gt;1,2,3,4&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The idea is that the normalized Molecular Orbital (MO), &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt;, of a diatomic molecule is written as a linear combination of normalized Atomic Orbitals (AO), &lt;span class=&quot;math-container&quot;&gt;$\chi_j$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\chi_k$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_i = c_{ij} \chi_j + c_{ik} \chi_k$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Assuming that the MO is occupied by &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons, these &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons can be distributes as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$N {\phi_i}^2 = N {c_{ij}}^2 {\chi_j}^2 + N {c_{ik}}^2 {\chi_k}^2 + 2 N c_{ik} \chi_i \chi_j$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Integrating over all electronic coordinates and as the MO and AO are normalized::&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$N = N {c_{ij}}^2 + N {c_{ik}}^2 + 2 N c_{ij} c_{ik} S_{jk}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$1 = {c_{ij}}^2 + {c_{ik}}^2 + 2 c_{ij} c_{ik} S_{jk}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$S_{jk}$&lt;/span&gt; is the overlap integral of the two Atomic Orbitals.&lt;/p&gt;&#xA;&lt;p&gt;According to Mulliken interpretation, the subpopulations &lt;span class=&quot;math-container&quot;&gt;$N {c_{ij}}^2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N {c_{ik}}^2$&lt;/span&gt; are called the &lt;em&gt;net atomic populations&lt;/em&gt; on atoms &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$2 N c_{ij} c_{ik} S_{jk}$&lt;/span&gt; is called the &lt;em&gt;overlap population&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A convenient way to re-write the previous equation is in matrix form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${P_i} = \left( {\begin{array}{*{20}{c}}&#xA;{c_{ij}^2}&amp;amp;{2{c_{ij}}c{}_{ik}{S_{jk}}}\\&#xA;{2{c_{ij}}c{}_{ik}{S_{jk}}}&amp;amp;{c_{ik}^2}&#xA;\end{array}} \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To take into account the populations from all the electrons in all the molecular orbitals, the net population matrix can be defined as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\rm{Net Population}} = \sum\limits_{i = occupied} {{P_i}}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;As &lt;strong&gt;pros&lt;/strong&gt;, we have that these populations are easily calculated (almost any software can calculate them). As &lt;strong&gt;cons&lt;/strong&gt;, they are heavily dependent on system wave functions and then, on the chosen basis sets (not random!).&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;[1] Mulliken, R.S. Electronic Population Analysis on LCAO-MO. Molecular Wave Functions. I, J. Chem. Phys. (1955), 23, 1833-1840.&lt;/p&gt;&#xA;&lt;p&gt;[2] Mulliken, R.S. Electronic Population Analysis on LCAO-MO. Molecular Wave Functions. II. Overlap Populations, Bond Orders, and Covalent Bond Energies, J. Chem. Phys. (1955), 23, 1841-1846.&lt;/p&gt;&#xA;&lt;p&gt;[3] Mulliken, R.S. Electronic Population Analysis on LCAO-MO. Molecular Wave Functions. III. Effects of Hybridization on Overlap and Gross AO Populations, J. Chem. Phys. (1955), 23, 2338-2342.&lt;/p&gt;&#xA;&lt;p&gt;[4] Mulliken, R.S. Electronic Population Analysis on LCAO-MO. Molecular Wave Functions. IV. Bonding and Antibonding in LCAO and Valence-Bond Theories, J. Chem. Phys. (1955), 23, 2343-2346.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-07-02T10:55:44.400" LastActivityDate="2020-07-02T10:55:44.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1448" PostTypeId="2" ParentId="1445" CreationDate="2020-07-01T22:33:50.400" Score="13" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Is it worth performing a series of convergence tests on the number of layers frozen, as well as the number of layers themselves? I can imagine this would become quite time consuming.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, it is generally considered a valid approach, and if you are new to a given material, you should be running such convergence tests both with regards to the number of layers in the slab and the number of layers allowed to move. Of course, you have to keep some layers fixed otherwise it will not be representative of a bulk surface. At the same time, it can be too rigid if you only let the top layer move. For people that work in this field, they often have a good handle on how many layers to use based on prior work, so you will likely not see a convergence test in every paper. However, it is best practice. As a side-note, for high-throughput calculations (such as the &lt;em&gt;Sci. Data&lt;/em&gt; paper you mentioned), there is a more significant balance that needs to be had with regards to the accuracy-cost tradeoff since they are purposefully trying to study as many materials as possible.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Alternatively, I have seen others suggest that a better approach is using a symmetrical slab model. That is, putting the same adsorbate on the &amp;quot;bottom&amp;quot; side of the slab in exactly the same geometry as the top. Again, I would like to hear people's thoughts on this choice of method, and whether this approach has more 'validity' than the semi-infinite approach.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Generally, the reason for doing this is to avoid the presence of a fictitious dipole moment in your slab. It is a separate issue from the number of layers question you asked. My view is that this is a bit of an archaic route. In VASP and other codes, you can use a dipole correction to offset any dipole present in an asymmetrical slab model. Refer to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/IDIPOL&quot; rel=&quot;noreferrer&quot;&gt;IDIPOL&lt;/a&gt; flag for more details.&lt;/p&gt;&#xA;&lt;p&gt;In general, the answers to many of your questions are discussed in the &amp;quot;Modeling materials using density functional theory&amp;quot; ebook by Kitchin, found &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.html#orgheadline43&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-07-01T22:39:56.743" LastActivityDate="2020-07-01T22:39:56.743" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1449" PostTypeId="2" ParentId="121" CreationDate="2020-07-02T00:09:00.287" Score="8" Body="&lt;p&gt;There is certainly Lammps, which has a fix efield that allows you to apply electric field in your chosen cartesian direction. But I am not sure if it works for your purposes. You can play around with it to see.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://lammps.sandia.gov/doc/fix_efield.html&quot; rel=&quot;noreferrer&quot;&gt;https://lammps.sandia.gov/doc/fix_efield.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-07-02T00:09:00.287" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1450" PostTypeId="2" ParentId="1439" CreationDate="2020-07-02T02:59:03.730" Score="20" Body="&lt;h2&gt;Electrostatic potential (ESP) derived charges&lt;/h2&gt;&#xA;&lt;p&gt;Note that ESP&lt;sup&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/CHELPG&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;&lt;/sup&gt; derived charges include &lt;a href=&quot;https://en.wikipedia.org/wiki/CHELPG&quot; rel=&quot;noreferrer&quot;&gt;ChelpG&lt;/a&gt; (CHarges from ELectrostatic Potentials using a Grid-based method), the Merz–Kollman (MK) &lt;sup&gt;&lt;a href=&quot;http://archive.ambermd.org/200604/0020.html&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;&lt;/sup&gt;, and the RESP (restrained electrostatic potential) &lt;sup&gt;[3]&lt;/sup&gt; scheme. While there are differences between the approaches the general idea is similar between the different methods. The main difference between the approaches is how the &amp;quot;grids&amp;quot; are selected. The points are selected in a regularly spaced cubic grid for CHELPG while the MK and the Resp schemes use points located on nested Connolly surfaces.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Basis set completeness:&lt;/strong&gt; The charges calculated with the CHELPG method are more systematic and predictable than charge methods based on the wave function or the electron density topology &lt;sup&gt;[4]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;These types of charges are used in molecular mechanics. &lt;a href=&quot;http://archive.ambermd.org/200604/0020.html&quot; rel=&quot;noreferrer&quot;&gt;AMBER developers use RESP/MK, GLYCAM developers use RESP/CHELPG and CHARMM developers ESP/CHELPG and RESP/MK ChelpG, MK.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For floppy/flexible molecules ESP charges can be fit to multiple conformers to provide a better overall fit.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The charges of atoms can be constrained to certain values like unit charge. This is essential for making the building blocks of complex systems like proteins&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Amino acids are parameterized with &amp;quot;caps&amp;quot; e.g. ACE or NME caps which complete the valence, these caps are constrained to unit charge so when they are removed the remaining &amp;quot;lego&amp;quot; piece has unit charge and can be easily combined with other amino acids to create a protein.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Many different programs can calculate RESP and CHELPG.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ESP charges are not good for atoms which are located far from the points at which the electrostatic potential is calculated (see &lt;a href=&quot;https://en.wikipedia.org/wiki/CHELPG&quot; rel=&quot;noreferrer&quot;&gt;ChelpG&lt;/a&gt;). The RESP is apparently slightly better because it restrains certain charges with a hyperbolic restraint function. However when dealing with more complex systems the RESP charges are always calculated, when possible, with caps to limit the size and therefore to obtain more realistic charges &lt;sup&gt;[5]&lt;/sup&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The electrostatic potential is the amount of work necessary to move a charge from infinity to that point.&lt;/li&gt;&#xA;&lt;li&gt;Besler, B. H.; Merz, K. M.; Kollman, P. A. J Comput Chem 1990, 11, 431&lt;/li&gt;&#xA;&lt;li&gt;C. I. Bayly et. al. J. Phys. Chem. 97, 10269 (1993)&lt;/li&gt;&#xA;&lt;li&gt;Charge distribution in the water molecule -A comparison of methods, F. MARTIN, H. ZIPSE, Journal of Computational Chemistry, 2005, 10.1002/jcc.20157&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://ambermd.org/tutorials/advanced/tutorial1/section1.htm&quot; rel=&quot;noreferrer&quot;&gt;http://ambermd.org/tutorials/advanced/tutorial1/section1.htm&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-02T03:33:27.637" LastActivityDate="2020-07-02T03:33:27.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1451" PostTypeId="2" ParentId="1439" CreationDate="2020-07-02T11:58:56.950" Score="23" Body="&lt;p&gt;Just to add to the discussion:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Mulliken charges are flawed in many aspects, but we know how and why, and therefore we accept its use,&#xA;since it is simple and easily computed. But very dependent on the size of the basis set.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Mulliken charges do not reproduce the dipole (or higher) moment, but can be made to do so easily:&#xA;Thole, van Duijnen, &amp;quot;A general population analysis preserving the dipole moment”&#xA;Theoret. Chim. Acta 1983, 63, 209–221&#xA;&lt;a href=&quot;http://www.dx.doi.org/10.1007/BF00569246&quot; rel=&quot;noreferrer&quot;&gt;www.dx.doi.org/10.1007/BF00569246&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Based on a multipole expansion (used in ADF for the Coulomb potential) we have extended this to&#xA;quadrupoles etc.&#xA;M. Swart, P.Th. van Duijnen and J.G. Snijders&#xA;&amp;quot;A charge analysis derived &amp;gt; from an atomic multipole expansion&amp;quot;&#xA;J. Comput. Chem. 2001, 22, 79-88&#xA;&lt;a href=&quot;http://www.dx.doi.org/10.1002/1096-987X(20010115)22:1%3C79::AID-JCC8%3E3.0.CO;2-B&quot; rel=&quot;noreferrer&quot;&gt;http://www.dx.doi.org/10.1002/1096-987X(20010115)22:1%3C79::AID-JCC8%3E3.0.CO;2-B&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Note that the multipoles result directly from the charge density, no fitting needed to the electrostatic&#xA;potential at some grid outside the molecule (as done by other electrostatic potential fitted charge analyses).&#xA;For each atom, its multipoles are represented by redistributed fractional atomic charges (with a weight&#xA;function based on distance to keep these as close to the original atom as possible), the sum of these&#xA;fractional atomic charges then add up to e.g. MDC-m (when only monopoles are redistributed), MDC-d&#xA;(both monopoles and dipoles redistributed), MDC-q (monopoles, dipoles, quadrupoles redistributed).&lt;/p&gt;&#xA;&lt;p&gt;For the N:+:C60 quartet state &lt;a href=&quot;http://www.ccl.net/cgi-bin/ccl/message-new?2020%2006%2028%20006&quot; rel=&quot;noreferrer&quot;&gt;as mentioned by Tom&lt;/a&gt;, the MDC-m works best.&lt;/p&gt;&#xA;&lt;p&gt;MDC-m, charge N -0.017, spin-dens. charge N 2.874; charge C 0.0003, spin-dens. charge C 0.002&#xA;MDC-d, charge N 0.136, spin-dens. charge N 0.722; charge C -0.002, spin-dens. charge C 0.038&#xA;MDC-q, charge N 0.062, spin-dens. charge N 0.729; charge C ranging from +0.05 to -0.05, spin-dens. charge C 0.038&#xA;In this case, the only other places where to put fractional charges are at the cage, hence not a&#xA;representative sample for the method an sich.&lt;/p&gt;&#xA;&lt;p&gt;I must add here that the Mulliken analysis works excellently: charge N -0.062, spin-dens. charge N 2.970.&#xA;Hirshfeld (0.138) and Voronoi (0.259) charges for N are larger (no spin-density equivalent available within ADF).&lt;/p&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;Finally, see also the following papers:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;M. Cho, N. Sylvetsky, S. Eshafi, G. Santra, I. Efremenko,  J.M.L. Martin&#xA;The Atomic Partial Charges Arboretum: Trying to See the Forest for the Trees&#xA;ChemPhysChem 2020, 21, 688-696&#xA;&lt;a href=&quot;http://www.dx.doi.org/10.1002/cphc.202000040&quot; rel=&quot;noreferrer&quot;&gt;www.dx.doi.org/10.1002/cphc.202000040&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;G. Aullón, S Alvarez&#xA;Oxidation states, atomic charges and orbital populations in transition metal complexes.&#xA;Theor. Chem. Acc. 2009, 123, 67-73&#xA;&lt;a href=&quot;http://www.dx.doi.org/10.1007/s00214-009-0537-9&quot; rel=&quot;noreferrer&quot;&gt;www.dx.doi.org/10.1007/s00214-009-0537-9&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;G. Knizia&#xA;Intrinsic Atomic Orbitals: An Unbiased Bridge between Quantum Theory and Chemical Concepts&#xA;J. Chem. Theory Comp. 2013, 9, 4834-4843&#xA;&lt;a href=&quot;http://www.dx.doi.org/10.1021/ct400687b&quot; rel=&quot;noreferrer&quot;&gt;www.dx.doi.org/10.1021/ct400687b&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2020-07-02T11:58:56.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1452" PostTypeId="2" ParentId="1416" CreationDate="2020-07-02T12:43:43.607" Score="10" Body="&lt;p&gt;From the available information, I think it is caused by the small value of &lt;span class=&quot;math-container&quot;&gt;$T_{damp}$&lt;/span&gt;. This causes the &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; to fluctuate wildly, which can induce unwanted bond-breaking. Best practise is to keep &lt;span class=&quot;math-container&quot;&gt;$T_{damp}$&lt;/span&gt; value around &lt;span class=&quot;math-container&quot;&gt;$100 \times \text{timestep}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, I will suggest you use a much larger neighbour bin size (&lt;span class=&quot;math-container&quot;&gt;$\approx 3 Å $&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="605" LastEditorUserId="7" LastEditDate="2020-07-15T17:24:31.623" LastActivityDate="2020-07-15T17:24:31.623" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1453" PostTypeId="1" CreationDate="2020-07-02T13:24:16.710" Score="12" ViewCount="509" Body="&lt;p&gt;I used GAUSSIAN/GAUSSVIEW to calculate the GIAO Magnetic shielding tensor (ppm), but I forgot to calculate the Nuclear spin-spin coupling J (Hz). How can I use the .chk file or .log file to calculate only the spin-spin coupling constants?&lt;/p&gt;&#xA;&lt;p&gt;I do not want to re-do the full nmr calculation. This is what I used:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;# nmr=giao b3lyp/6-311g(d,p) pop=full geom=connectivity&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="999" LastEditorUserId="5" LastEditDate="2020-07-09T20:29:35.923" LastActivityDate="2020-07-15T18:14:20.037" Title="Calculate spin-spin coupling based on previous GIAO calculation with Gaussian" Tags="|computational-chemistry|gaussian|nuclear-magnetic-resonance|fine-and-hyperfine-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1454" PostTypeId="5" CreationDate="2020-07-02T16:01:36.103" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:01:36.103" LastActivityDate="2020-07-02T16:01:36.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1455" PostTypeId="4" CreationDate="2020-07-02T16:01:36.103" Score="0" Body="For questions about modeling the adsorption, the process of molecules attaching to a solid surface." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:01:36.103" LastActivityDate="2020-07-02T16:01:36.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1456" PostTypeId="5" CreationDate="2020-07-02T16:09:46.867" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:09:46.867" LastActivityDate="2020-07-02T16:09:46.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1457" PostTypeId="4" CreationDate="2020-07-02T16:09:46.867" Score="0" Body="For questions about polarizabilites. Most commonly, this refers to the electric dipole-electric dipole polarizability." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:09:46.867" LastActivityDate="2020-07-02T16:09:46.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1458" PostTypeId="5" CreationDate="2020-07-02T16:12:39.513" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:12:39.513" LastActivityDate="2020-07-02T16:12:39.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1459" PostTypeId="4" CreationDate="2020-07-02T16:12:39.513" Score="0" Body="For questions about the IQmol molecular editing GUI" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-02T16:12:39.513" LastActivityDate="2020-07-02T16:12:39.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1460" PostTypeId="2" ParentId="181" CreationDate="2020-07-02T16:34:22.120" Score="17" Body="&lt;p&gt;Before talking about the pros and cons of ML-potentials, there is a huge conceptual difference between empirical- and ML-potential that needs to be clarified.&lt;/p&gt;&#xA;&lt;p&gt;In empirical potentials, one uses data from experiments to find the parameters of a fixed functional form that would explain the experiment. This is an &lt;a href=&quot;https://en.wikipedia.org/wiki/Inverse_problem&quot; rel=&quot;noreferrer&quot;&gt;inverse problem&lt;/a&gt; which is mathematically ill-posed (in the sense of Hadamard).&lt;/p&gt;&#xA;&lt;p&gt;However, ML-potentials are not posed as an inverse problem. Here, in the framework of Potential Energy Surfaces (PES), one starts by selecting a set of distinct nuclear geometries, compute their energies using some quantum chemistry method. Then, the PES is obtained by solving a regression problem, where one seeks to minimise the &lt;a href=&quot;https://en.wikipedia.org/wiki/Empirical_risk_minimization&quot; rel=&quot;noreferrer&quot;&gt;empirical risk functional&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The point is, the two approaches are conceptually very different.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;where is the position of ML potentials? Are they accurate? Or fast? Or both?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Depends on the model you use to solve the regression problem. You can use Neural Networks, Kernel-methods, or even polynomial fitting. These methods differ from each other in terms of training complexity, prediction complexity and their ability to approximate highly nonlinear functions.  A wide variety of algorithms have been successfully used to obtain PESs.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is this easy/hard to learn?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It depends on the quality of your data and the algorithm you're using. But, in general, developing any ML-model is an iterative procedure (candidate model-train-test).&lt;/p&gt;&#xA;" OwnerUserId="423" LastEditorUserId="423" LastEditDate="2020-07-02T17:12:00.363" LastActivityDate="2020-07-02T17:12:00.363" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1461" PostTypeId="1" AcceptedAnswerId="1462" CreationDate="2020-07-02T18:08:01.317" Score="15" ViewCount="1051" Body="&lt;p&gt;I completed an &lt;em&gt;ab initio&lt;/em&gt; molecular dynamic (AIMD) simulation in VASP for a hypothetical material. The simulation was done for 5ps with 1fs steps and the temperature was set to 300K using Nosé–Hoover thermostat. Now I've extracted the total energy variation w.r.t time and could not decide if the material is potentially stable or not from the plot. &lt;a href=&quot;https://i.stack.imgur.com/mX0Fy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mX0Fy.png&quot; alt=&quot;AIMD plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Does this support that the material could be stable since the total energy converges around  &lt;span class=&quot;math-container&quot;&gt;$\ce{-800 eV/cell}$&lt;/span&gt; after 1ps? My concern is there is a huge variation in total energy during the 1st pico second, what does that mean? And what other tests should I do to investigate stability/instability of materials using AIMD simulations (e.g. variation of bond length over time)?&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="792" LastEditDate="2020-07-12T09:55:29.960" LastActivityDate="2020-07-12T09:55:29.960" Title="Ab initio molecular dynamics to check material stability at finite temperature" Tags="|density-functional-theory|molecular-dynamics|vasp|phonons|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1462" PostTypeId="2" ParentId="1461" CreationDate="2020-07-03T09:53:04.617" Score="13" Body="&lt;p&gt;This is a description of some methods available to study dynamical and chemical stability, not limited to MD:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Dynamical stability.&lt;/strong&gt; The question here is: given a compound in a particular structure, is this structure dynamically stable or is there a lower-energy structure that can be accessed without jumping over an energy barrier? From a potential energy surface (PES) point of view, the question is: is this structure at a local minimum of the PES, or is it at a saddle point? The most straight-forward way of answering this question is to perform a phonon calculation. If all phonon frequencies are real, then the system is dynamically stable (at a local minimum), but if there are some imaginary frequencies, then the system may be dynamically unstable (at a saddle point). So my immediate suggestion would be to do a phonon calculation (which is also much cheaper than an MD simulation). If all frequencies are real, then you are done, the structure is dynamically stable. If you encouter imaginary frequencies, then the structure may or may not be dynamically stable. The structure definitely sits at a saddle point of the PES, but entropic contributions may help stabilize it at finite temperature (you are looking at the free energy surface rather than at the PES). A well-known example of this latter case is that of perovskites, which undergo a series of temperature-induced structural phase transitions. In this case, phonons are of no use (the relevant terms are anharmonic), and MD may come in handy. My suggestion would then be to start with the lower energy structure that the imaginary phonons take you to, and then run and MD simulation to see if the structure &amp;quot;symmetrizes&amp;quot; from the local minimum to the saddle point.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Chemical stability.&lt;/strong&gt; The question here is: given a compound with a particular stoichiometry, will is decompose into other compounds? MD is not really a viable way to answer it in general; instead, you probably want to go down the route of structure prediction. What you would do is to generate multiple candidate structures at different stoichiometries, and then construct a Hull diagram to investigate if your structure will stay put or decompose. MD can simply not access the long time scales that are necessary to see something like a phase decomposition.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-03T09:53:04.617" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1464" PostTypeId="2" ParentId="121" CreationDate="2020-07-03T18:41:09.993" Score="5" Body="&lt;p&gt;Actually that depends on what you're trying to achieve with the simulation. Generally speaking the magnetic field is not much different from the electric field, therefore the effect can be incorporated with small changes to &lt;code&gt;fix efield&lt;/code&gt; in LAMMPS to account for different constants. In fact, this was what we did in a &lt;a href=&quot;https://doi.org/10.1016/j.jmmm.2014.04.037&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; some time ago. However, the effect of the external magnetic field on magnetized particles is just a torque, and hence it makes sense to apply the torque only to spherically asymmetrical particles.&lt;/p&gt;&#xA;" OwnerUserId="1005" LastActivityDate="2020-07-03T18:41:09.993" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1465" PostTypeId="2" ParentId="1439" CreationDate="2020-07-03T20:53:57.650" Score="18" Body="&lt;h2&gt;Mulliken and Löwdin population analysis&lt;/h2&gt;&#xA;&lt;p&gt;In the atomic orbital basis set (enumerated in Greek indices), one finds that the number of electrons &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is equal to the trace of the product &lt;span class=&quot;math-container&quot;&gt;$\mathbf{PS}$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;N = \sum_\mu \left(\mathbf{PS}\right)_{\mu\mu} = \mathrm{Tr} \ \mathbf{PS}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P}$&lt;/span&gt; is the density matrix, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}$&lt;/span&gt; is the AO overlap matrix, and the sum runs over all basis functions. One can then decide to partition the electron population by associating non-intersecting subsets of the basis set to atoms, typically by taking those centered on atom &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; as belonging to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;. We will denote this as &lt;span class=&quot;math-container&quot;&gt;$\mu \in A$&lt;/span&gt; and define the &lt;strong&gt;Mulliken charge&lt;/strong&gt; on &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;q_A^\text{Mulliken} = Z_A \ - \sum_{\mu \ \in \ A} \left(\mathbf{PS}\right)_{\mu\mu}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$Z_A$&lt;/span&gt; is the nuclear charge of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Non-uniqueness of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{PS}$&lt;/span&gt;:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The trace has the property of cylic permutability:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{Tr} \ \mathbf{ABC} = \mathrm{Tr} \ \mathbf{CAB} = \mathrm{Tr} \ \mathbf{BCA}&#xA;$$&lt;/span&gt;&#xA;which can be applied to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{PS}$&lt;/span&gt; as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{Tr} \ \mathbf{PS} = \mathrm{Tr} \ \mathbf{P}\mathbf{S}^{1-x}\mathbf{S}^{x} = \mathrm{Tr} \ \mathbf{S}^{x}\mathbf{P}\mathbf{S}^{1-x}&#xA;$$&lt;/span&gt;&#xA;which holds at least for &lt;span class=&quot;math-container&quot;&gt;$x \in \mathbb{Q}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One can then set &lt;span class=&quot;math-container&quot;&gt;$x = \frac{1}{2}$&lt;/span&gt; and obtain the &lt;strong&gt;Löwdin charge&lt;/strong&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;q_A^\text{Löwdin} = Z_A - \sum_{\mu \ \in \ A} \left(\mathbf{S}^\frac{1}{2}\mathbf{P}\mathbf{S}^{\frac{1}{2}}\right)_{\mu\mu}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Discussion/Cons:&lt;/strong&gt; As pointed out by others, theses types of analysis are particularly susceptible to the basis set. Intramolecular basis set superposition error (BSSE) is also an important factor. I would further note that any scheme for atomic charge is flawed in the sense that it does not represent an observable. Therefore, values should only be considered relative to prototypical systems.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Source:&#xA;A Szabo, NS Ostlund: &lt;em&gt;Modern Quantum Chemistry&lt;/em&gt;, Dover Publications, 1996.&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-07-11T16:36:51.973" LastActivityDate="2020-07-11T16:36:51.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1466" PostTypeId="1" CreationDate="2020-07-03T20:57:25.670" Score="4" ViewCount="70" Body="&lt;p&gt;How can someone properly decide on an appropriate level of theory MM, QM...&#xA;What are the checklists throughout the experiment (in-silico)?&#xA;How to decide a proper control case/group?&#xA;For example from personal experience, it happened to me to work without a control (ground truth). I have realized this makes it difficult for the results to stand.&#xA;There is a general workflow bellow:&lt;br /&gt;&#xA;Question --&amp;gt; Sample --&amp;gt; Method --&amp;gt; Results&lt;br /&gt;&#xA;So sample should include the test case(s) and a control. Other principles may be method reproducibility. I am just realizing how general this can be and can extend to any scientific method in general or depending on the type of question. But I am interested in an in-silico view.&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="125" LastEditDate="2020-07-04T09:37:51.800" LastActivityDate="2020-07-04T09:37:51.800" Title="How to properly design a modeling experiment?" Tags="|qmmm|materials-design|" AnswerCount="0" CommentCount="5" ClosedDate="2020-07-05T02:56:21.083" ContentLicense="CC BY-SA 4.0" />
  <row Id="1467" PostTypeId="2" ParentId="857" CreationDate="2020-07-04T14:20:07.173" Score="5" Body="&lt;h2&gt;GoodVibes&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/bobbypaton/GoodVibes&quot; rel=&quot;noreferrer&quot;&gt;GoodVibes&lt;/a&gt; is able to calculate what you want from Gaussian logfiles. From its documentation (using scaled vibrational frequencies):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python -m goodvibes examples/methylaniline.out -v 0.95&#xA;&#xA;   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)&#xA;   *********************************************************************************************************&#xA;o  methylaniline      -326.664901   0.135012   -326.521265   0.040238   0.040091   -326.561503   -326.561356&#xA;   *********************************************************************************************************&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="63" LastEditorUserId="5" LastEditDate="2020-07-04T14:32:31.520" LastActivityDate="2020-07-04T14:32:31.520" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1468" PostTypeId="2" ParentId="312" CreationDate="2020-07-05T12:35:43.037" Score="3" Body="&lt;p&gt;Magnetic-Field-Density-Functional-Theory (BDFT) is an alternative to CDFT in which the notion of universality of the DFT functional is relaxed (Grayce and Harris, 1994). It can be thought of as regarding the external magnetic field &lt;span class=&quot;math-container&quot;&gt;$\textbf{B}$&lt;/span&gt; or equivalently the vector potential &lt;span class=&quot;math-container&quot;&gt;$\textbf{A}$&lt;/span&gt; as fixed. In practice, it means approximations must be developed that change with &lt;span class=&quot;math-container&quot;&gt;$\textbf{B}$&lt;/span&gt; / &lt;span class=&quot;math-container&quot;&gt;$\textbf{A}$&lt;/span&gt; directly and are specific to a type of external field. If the dependence on &lt;span class=&quot;math-container&quot;&gt;$\textbf{B}$&lt;/span&gt; can be modelled, then BDFT may provide a simpler route to a DFT useful for systems in a magnetic field.&lt;/p&gt;&#xA;" OwnerUserId="159" LastActivityDate="2020-07-05T12:35:43.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1469" PostTypeId="2" ParentId="901" CreationDate="2020-07-05T17:06:43.583" Score="11" Body="&lt;h2&gt;Wiberg (1968)&lt;/h2&gt;&#xA;&lt;p&gt;Let's start with the &amp;quot;classic&amp;quot; bond order paper by Ken Wiberg (born in 1927 and still alive!).&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;Wiberg Bond Index (WBI)&lt;/strong&gt; between fragments A and B of AB is calculated as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{1}&#xA;W_{AB} \equiv \sum_{\mu \in A}\sum_{\nu \in B}D_{\mu \nu}^2~ ,&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is the following density matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{2}&#xA;D_{\mu \nu} \equiv \sum_{i\in \alpha }C_{\mu i}C_{\nu i} +  \sum_{i\in \beta }C_{\mu i}C_{\nu i}~,&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; are atomic orbitals for fragments A and B respectively, and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; denote spins, and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is the matrix of atomic orbital coefficients in the LCAO formalism.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is old and primitive. Easily you could take into account the overlap matrix  &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; and the spin density matrix &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; to get the Mayer Bond Index (MBI) or an analogous WBI.&lt;/li&gt;&#xA;&lt;li&gt;It relies on wavefunctions, which &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1394/5&quot;&gt;Walter Kohn has said is not legitimate for large systems&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;While this bond order can easily be decomposed into &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; bonding components for linear molecules, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0166128008005058&quot; rel=&quot;nofollow noreferrer&quot;&gt;some more work may be necessary for more general molecules&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Despite the MBI being objectively more sophisticated, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0166128008005058&quot; rel=&quot;nofollow noreferrer&quot;&gt;a detailed 2008 study&lt;/a&gt; of both MBI and WBI concluded with a recommendation to use WBI and cited two reasons:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It was quite &lt;strong&gt;stable with respect to basis set size&lt;/strong&gt; (see Fig. 1) and this concluding quote &amp;quot;For the description of bond orders the preference is given to WBI      calculated with NAO, because these indices are stable enough with respect to basis set variation.&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;Their WBI results were close to what we might expect: &amp;quot;The valences calculated using the WBI values taking into account both the covalent and ionic components of the chemical bonds are close to the formal atomic valences of main-group elements.&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;It's very simple, easy to calculate, and therefore likely available in most software.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-02T20:06:18.320" LastActivityDate="2020-08-02T20:06:18.320" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1470" PostTypeId="2" ParentId="154" CreationDate="2020-07-05T23:02:44.293" Score="9" Body="&lt;p&gt;The Tran-Blaha functional is not a generally useful functional, so I would not describe it as &amp;quot;trustworthy&amp;quot; at all. For example, it is not size-extensive so twice as much material does not have twice the energy, and hence you can't use it for any thermodynamics or phase stability or finite-displacement phonons etc. There isn't a proper potential either, so you can't use it self-consistently, and it's very fiddly to get pseudopotentials right since it couples the core and valence states via one of its parameters.&lt;/p&gt;&#xA;&lt;p&gt;The usual claim is that the Tran-Blaha functional is &amp;quot;good for band-gaps&amp;quot;. I think a single scalar quantity is a poor indicator of functional quality, and band-gaps are especially poor since it is not at all clear what the Kohn-Sham gap with the &amp;quot;true&amp;quot; functional would be. My experience is that this functional is usually very poor for band-structures compared to, say, PBE, although it does tend to open up the Kohn-Sham gap more.&lt;/p&gt;&#xA;&lt;p&gt;I think the SCAN functional has far more potential (pun intended) to be generally useful, once its various pathologies have been addressed. It may be used self-consistently, obeys many exact conditions and it is possible to construct pseudopotentials for it -- which, incidentally, is crucial to getting reasonable results with it in a pseudopotential program.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-07-05T23:02:44.293" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1471" PostTypeId="1" CreationDate="2020-07-06T10:15:39.663" Score="9" ViewCount="202" Body="&lt;p&gt;In the multi-configurational time-dependent Hartree (MCTDH) theory, one essential step that reduces the memory and time cost is to form a single particle function (SPF) basis ansatz as shown in equations in (1) and (2) in the linked review literature&lt;sup&gt;1&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Equation (1):&lt;/p&gt;&#xA;&lt;p&gt;(&lt;em&gt;f&lt;/em&gt;: degrees of freedom, &lt;span class=&quot;math-container&quot;&gt;$q_1, \ldots, q_f$&lt;/span&gt;: coordinates)&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Psi \left( {{q_1}, \ldots {q_f},t} \right) &amp;amp;= \sum\limits_{{j_1}}^{{n_1}} { \ldots \sum\limits_{{j_p}}^{{n_p}} {{A_{{j_1} \ldots {j_p}}}\left( t \right)\varphi _{{j_1}}^{\left( 1 \right)}\left( {{Q_1},t} \right) \ldots } } \varphi _{{j_p}}^{\left( p \right)}\left( {{Q_p},t} \right)\tag{1}\\&#xA; &amp;amp;= \sum\limits_J {{A_J}{\Phi _J}}\tag{2}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Equation (1) is a direct product expansion of &lt;em&gt;p&lt;/em&gt; sets of orthonormal time-dependent basisfunctions &lt;span class=&quot;math-container&quot;&gt;$\left\{ {\varphi {}^{\left( \kappa  \right)}} \right\}$&lt;/span&gt;, known as single-particle functions (SPFs). The coordinate for each set of &lt;span class=&quot;math-container&quot;&gt;${n_\kappa }$&lt;/span&gt; functions is a composite coordinate of one or more system coordinates (equation 2):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{c}&#xA;{Q_\kappa } = \left( {{q_a},{q_b}, \ldots } \right).\tag{2}&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, the reference fails to explain in detail how to construct time-dependent, orthonormal SPFs from a primitive basis set. How is this done?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;G.A. Worth, et al. Using the MCTDH wavepacket propagation method to describe multimode non-adiabatic dynamics. Int. Rev. Phys. Chem. 27, 569–606 (2008). DOI: &lt;a href=&quot;http://dx.doi.org/10.1080/01442350802137656&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1080/01442350802137656&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-12-28T03:46:00.253" LastActivityDate="2021-02-22T19:40:18.010" Title="How to construct the single particle function (SPF) basis in MCTDH?" Tags="|quantum-dynamics|mctdh|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1472" PostTypeId="1" AcceptedAnswerId="1474" CreationDate="2020-07-06T10:32:57.307" Score="6" ViewCount="176" Body="&lt;p&gt;In the multi-configurational time-dependent Hartree (MCTDH) method, the equation of motion is derived from the time-dependent Schrödinger equation by substituting the wavefunction ansatz expanded in a single particle function (SPF) basis. The wavepacket dynamics is solved by solving a series of decoupled equations of motion in the SPF basis as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;i\dot\phi^{(k)}=(1-\hat{P}^{(k)})(\boldsymbol \rho^{(k)})^{-1}\boldsymbol{H}^{(k)}\phi^{(k)}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the definition of the quantities, one could refer to the linked article:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/01442350802137656&quot; rel=&quot;noreferrer&quot;&gt;https://www.tandfonline.com/doi/full/10.1080/01442350802137656&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I wonder if someone knows how to derive this equation above from the time dependent Schrödinger equation?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-07-06T20:07:34.323" LastActivityDate="2021-02-22T16:30:12.183" Title="How is MCTDH derived?" Tags="|quantum-chemistry|mctdh|quantum-dynamics|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1473" PostTypeId="1" CreationDate="2020-07-06T17:20:34.087" Score="1" ViewCount="268" Body="&lt;p&gt;According to a web page I can no longer find, some brittle materials such as glass have a very high theoretical strength but they tend to have surface cracks which magnify tension at the tip greatly lowering the observed strength. I believe that when a substance has the ability to keep being pulled thinner, it is as ductile as possible and cannot undergo fatigue. I think a material is as malleable as possible when it can keep being squeezed thinner without breaking. If a material is as malleable as possible, that doesn't necessarily mean it is as ductile is possible. Pushing a material thinner in one direction is like pulling it thinner in two directions in a really high pressure environment and I guess really high pressure can make a material as ductile as possible that isn't normally. Therefore under normal conditions, being as ductile as possible is a stronger property than being as malleable as possible.&lt;/p&gt;&#xA;&lt;p&gt;I'm looking to see if buckminsterfullerene, the substance composed of C60 molecules in the shape of a soccer ball is as ductile as metarials can possibly be under normal conditions, that is, it can keep being pulled thinner and thinner like gold. It might not only be as ductile as possible but also have an insanely high yield strength. In addition to that, I believe almost everything would have more cohesion than adhesion to it. I read that soot has C60 molecules in it and I also collected soot and observed with my own eyes that soot was hydrophobic so I'm wondering if soot is made of buckminsterfullerene particles. Since it's hydrophobic, that means water's adhesion to it is less than half its cohesion. It only has to be a tiny bit less than half. Then extreme roughness of the collected soot will be even more hydrophobic.&lt;/p&gt;&#xA;&lt;p&gt;According to &lt;a href=&quot;https://www.azonano.com/article.aspx?ArticleID=5158&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.azonano.com/article.aspx?ArticleID=5158&lt;/a&gt;, buckminsterfullerene is very ductile. According to &lt;a href=&quot;https://faculty.csbsju.edu/frioux/c60/BondingC60.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://faculty.csbsju.edu/frioux/c60/BondingC60.pdf&lt;/a&gt;, each buckminsterfullerene molecule has 90 localized bonds between 2 carbon atoms and 60 electrons delocalized throughout the entire molecule. Probably 30 delocalized orbits each of which has 2 electrons. Also according to that pdf file, its molecules form a face centered cubic arrangement.&lt;/p&gt;&#xA;&lt;p&gt;Because of the hybridization scheme of each molecule, I expect that if you have just two of them held together by Vanderwalls forces, it would take a lot less force to get one sliding along the surface of the other than it would to pull them apart from each other. Since they form a face centered cubic arrangement and can slide along one another so easily, I'm wondering whether with sufficient tension, that material will just keep being pulled thinner and thinner and just round the tips of any cracks and therefore be totally immune to fatigue.&lt;/p&gt;&#xA;&lt;p&gt;However, it does not mean nothing can make it undergo brittle fracture. For example suppose you made it into the following shape. A sphere with ring hooks on its surface. Now add to the surface of it even smaller ring hooks all over its surface. Now add even smaller ring hooks all over the surface of this shape. Now if you start tugging on all of the hooks of any size, it will create tension in all 3 directions in the interior of the sphere and may lead to brittle fracture even if it can normally keep being pulled thinner and thinner.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I wonder what the ductility of C&lt;span class=&quot;math-container&quot;&gt;$_{60}$&lt;/span&gt; is? In particular, have there been any quantum mechanical calculations of this ductility? If none have been done before, how would one go about doing this quantum mechanical calculation?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, an answer to the second question cannot be used by me. I will not understand it but it doesn't hurt to ask it. Maybe a researcher will be able to read and understand the answer to that question and use it to help them invest in research on building materials. An answer on whether there was a lab report confirming by observation whether it can keep being pulled thinner and thinner will also do.&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="1014" LastEditDate="2021-01-26T02:40:37.983" LastActivityDate="2021-02-08T21:51:51.827" Title="How ductile is C60?" Tags="|ab-initio-calculations|nanoparticles|mechanical-properties|" AnswerCount="0" CommentCount="6" ClosedDate="2021-06-23T21:07:35.103" ContentLicense="CC BY-SA 4.0" />
  <row Id="1474" PostTypeId="2" ParentId="1472" CreationDate="2020-07-06T17:45:12.937" Score="13" Body="&lt;p&gt;I will outline the way it was derived in the original 1990 paper. We start with an ansatz for the time-dependent wavefunction:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{1}&#xA;\psi(x_1,\ldots,x_n;t) = \sum_{j_1=1}^{m_1}\cdots \sum_{j_n=1}^{m_n}a_{j_1\cdots j_n}\phi_{j_1}^{(1)}(x_1,t)\cdots \phi_{j_n}^{(n)}(x_n,t),&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with single-particle functions (SPFs) satisfying (the second constraint is to make MCTDH simpler):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{2}\label{ortho}&#xA;\langle \phi_i^{(k)} | \phi_j^{(k)}\rangle =\delta_{ij} ~,~ \langle \phi_i^{(k)} | \dot\phi_j^{(k)}\rangle =0.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now we will use the Dirac-Frenkel variational principle (DFVP) to optimize the parameters:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{3}\label{DiracFrenkel}&#xA;\langle \delta \psi |(H-\rm{i}\frac{\partial}{\partial t})|\psi\rangle =0.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Making use of all 4 equations so far, leads to this (you may need some practice with using DFVP):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{4}\label{}&#xA;\textrm{i}\dot a_{j_1\ldots j_n}=\langle \phi_{j_1}^{(1)}\cdots\phi_{j_n}^{(n)}|H|\psi\rangle .&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we define the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;J &amp;amp;\equiv (j_1,j_2,\ldots ,j_{k-1},j_{k+1},\ldots ,j_n)\tag{5}\\&#xA;\mathbf{A}^{(k)} &amp;amp;\equiv a_{j_1\ldots j_{k-1},j,j_{k+1}}^{(k)} \equiv A_{Jj}^{(k)} \tag{6}\\&#xA;\mathbf{B}^{(k)} &amp;amp;\equiv \left(\mathbf{A}^{(k)\dagger}\mathbf{A}^{(k)\dagger} \right)^{-1}\mathbf{A}^{(k)\dagger}\tag{7}\\&#xA;\hat{H}^{(k)}_{IJ} &amp;amp;\equiv \langle \phi_I^{(k)} |H|\phi_J^{(k)}\rangle \tag{8}\\&#xA;\hat{P}^{(k)}&amp;amp;\equiv \sum_{j=1}^{m_k}|\phi_j^{(k)}\rangle\langle \phi_k^{(k)}|\tag{9},&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;we can instead write:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{10}&#xA;\textrm{i}|\dot\phi_i^{(k)}\rangle = (1 - \hat{P}^{(k)})\sum_{IJj}B_{iI}^{(k)}\hat{H}_{IJ}^{(k)}A_{Jj}^{(k)}|\phi_j^{(k)}\rangle.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;These are the original working equations for MCTDH, and they are also almost exactly written the way you've written, except with &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; instead  of &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;: This is enough to get you started. &lt;strong&gt;A full derivation of the working MCTDH equation typically takes more than 60 lines, assuming you already have available some handy DFVP expressions.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="141" LastEditDate="2020-07-07T07:37:23.737" LastActivityDate="2020-07-07T07:37:23.737" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1475" PostTypeId="2" ParentId="1445" CreationDate="2020-07-06T20:15:45.343" Score="7" Body="&lt;p&gt;If you need an adsorption energy, then Andrew Rosen's answer gives good points. Symmetric adsorbate deposition will require about twice thicker slab, than single sided adsorption. So it is not really good idea today. Additionaly it is worth noting that you need to converge not only with slab width, but also with slab size along surface dimensions.&lt;/p&gt;&#xA;&lt;p&gt;You also mentioned about surface energy. It is completely different thing. You do not need to reach convergence of surface energy if you are interested in adsorption energy only. Error cancellation can work on you here.&lt;/p&gt;&#xA;" OwnerUserId="277" LastActivityDate="2020-07-06T20:15:45.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1476" PostTypeId="2" ParentId="502" CreationDate="2020-07-06T20:27:31.653" Score="6" Body="&lt;p&gt;If your molecules form not too many types of adsorption complexes on your surfaces, then you can built a lattice model with SuSMoST ( &lt;a href=&quot;http://SuSMoST.com/&quot; rel=&quot;noreferrer&quot;&gt;http://SuSMoST.com/&lt;/a&gt; ) and run a short  Monte Carlo simulation at high temperature.  High temperature Monte Carlo gives you essentially a random structure.&lt;/p&gt;&#xA;" OwnerUserId="277" LastEditorUserId="5" LastEditDate="2020-07-06T20:37:55.047" LastActivityDate="2020-07-06T20:37:55.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1477" PostTypeId="2" ParentId="901" CreationDate="2020-07-07T12:22:14.137" Score="8" Body="&lt;p&gt;It depends on what you want from it. If you're an organic chemist, you'd be mostly interested in the type of bond (single, double, triple, aromatic), and for that the bond order is most relevant (but tricky to compute). I sent a &lt;a href=&quot;https://rdcu.be/b7r7m&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper away earlier this year&lt;/a&gt; which deals with the choice of bond order analysis, and will post a link to it when it will be &lt;a href=&quot;https://rdcu.be/b7r7m&quot; rel=&quot;nofollow noreferrer&quot;&gt;online&lt;/a&gt;. But if done properly, you can see e.g. the change from aromatic bond in benzene to triple bond in acetylene if you dissociate benzene into its three components &lt;span class=&quot;math-container&quot;&gt;$\ce{H-C≡C-H}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you're however interested in the interaction of a metal with a nanostructure, then probably you're more interested in the energy. In 2007, I published this paper on the metal-ligand bonding in metallocenes (&lt;a href=&quot;http://www.dx.doi.org/10.1016/j.ica.2006.07.073&quot; rel=&quot;nofollow noreferrer&quot;&gt;Inorg. Chim. Acta 2007, 360, 179&lt;/a&gt;),using the energy decomposition analysis (EDA) as available in &lt;a href=&quot;https://www.scm.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;the ADF program&lt;/a&gt;, using fragments. I.e. you prepare two fragments: (i) metal, (ii) ligands, and compute the change in energy if you bring them together.&#xA;This will work as well for your system of metal/nanostructure, by preparing a fragment of the metal, and one for the nanostructure. In &lt;a href=&quot;http://www.dx.doi.org/10.1039/c2cp42045g&quot; rel=&quot;nofollow noreferrer&quot;&gt;a followup paper&lt;/a&gt; on the metallocenes we thus showed that V(0) binds very strongly to a super[6]cyclophane cage (&lt;em&gt;belonging to &amp;quot;Predicting new molecules by quantum chemical methods&amp;quot; special issue&lt;/em&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Of course you could also compute the intrinsic force constant for that particular bond, with all kind of if's and but's. But that would be opening up a whole new discussion.&lt;/p&gt;&#xA;&lt;p&gt;The paper I mentioned above can be read &lt;a href=&quot;https://rdcu.be/b7r7m&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="998" LastEditorUserId="998" LastEditDate="2020-09-20T17:18:22.917" LastActivityDate="2020-09-20T17:18:22.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1478" PostTypeId="1" AcceptedAnswerId="1506" CreationDate="2020-07-07T17:55:52.723" Score="22" ViewCount="4374" Body="&lt;p&gt;I am trying to find the&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Young's Modulus of an aluminum alloy&lt;/li&gt;&#xA;&lt;li&gt;The yield stress&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Below is the data for the stress-strain curve. I tried finding the region where the slope is constant and to my surprise, I found that only 4 data points, in the beginning, give me a straight line. After that, there is another straight line that gives me a different slope. I am confused as to which line to use for the calculation of Young's Modulus. If I use the second line I get an answer that does not conform with the reality of the alloy.&lt;/p&gt;&#xA;&lt;p&gt;So, I tried to find a package for the same : &lt;a href=&quot;https://pythonhosted.org/MatPy/Material%20Analytics.html&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a link for the package which seems very useful. I wanted to download it but could not find it on conda( I am using Jupyter). I was hoping if someone would provide me with the link too.&lt;/p&gt;&#xA;&lt;p&gt;PS: If there is no such package I would be grateful to receive help with the question without the package, too using Python.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Eng. Strain Eng. Stress&#xA;0.000000    4.174826667&#xA;0.00000444  4.188426667&#xA;0.0000103   4.164346667&#xA;-3.28E-06   4.202586667&#xA;4.294E-05   7.26848&#xA;0.0001964   16.04202667&#xA;0.0003372   22.67858667&#xA;0.00048938  27.47632&#xA;0.00065652  30.70698667&#xA;0.00083308  32.89658667&#xA;0.00101768  34.41408&#xA;0.0012028   35.57272&#xA;0.001385    36.52789333&#xA;0.0015676   37.36733333&#xA;0.00173426  38.04624&#xA;0.00193392  38.65781333&#xA;0.00210862  39.24997333&#xA;0.00228426  39.80757333&#xA;0.00245992  40.32866667&#xA;0.00263822  40.91192&#xA;0.00280184  41.40042667&#xA;0.00298324  41.87698667&#xA;0.00315386  42.37184&#xA;0.00333258  42.77624&#xA;0.00347468  43.24722667&#xA;0.00365992  43.64136&#xA;0.003817    44.06544&#xA;0.00399314  44.49149333&#xA;0.0041544   44.90893333&#xA;0.00432732  45.32496&#xA;0.0044855   45.73408&#xA;0.00464472  46.13429333&#xA;0.00482466  46.54008&#xA;0.00499114  46.85842667&#xA;0.00514588  47.30917333&#xA;0.00529986  47.64224&#xA;0.00546718  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103.3256267&#xA;0.19968054  103.3173067&#xA;0.1998769   103.3345067&#xA;0.20007006  103.3161867&#xA;0.20028094  103.3212&#xA;0.20049422  103.3245333&#xA;0.20068414  103.3006667&#xA;0.20090788  103.3594933&#xA;0.20112678  103.3889067&#xA;0.20132238  103.3805867&#xA;0.20152278  103.3234133&#xA;0.20173122  103.3778133&#xA;0.2019276   103.36504&#xA;0.20214328  103.38336&#xA;0.20234772  103.37392&#xA;0.20253928  103.35672&#xA;0.20273644  103.3722667&#xA;0.20296178  103.3711467&#xA;0.20315336  103.3450667&#xA;0.20335294  103.36672&#xA;0.20356862  103.42112&#xA;0.20376664  103.36392&#xA;0.20397668  103.3817067&#xA;0.20418272  103.4155467&#xA;0.20437828  103.40944&#xA;0.20458916  103.40168&#xA;0.20479842  103.4227733&#xA;0.20501652  103.4355467&#xA;0.2052137   103.3889067&#xA;0.20540202  103.42888&#xA;0.20562334  103.3772533&#xA;0.20581812  103.45664&#xA;0.2060314   103.4089067&#xA;0.20622054  103.46608&#xA;0.20642336  103.4238933&#xA;0.20664066  103.43608&#xA;0.20683944  103.44608&#xA;0.20707204  103.4527467&#xA;0.2072507   103.4627467&#xA;0.20746158  103.4805067&#xA;0.20765634  103.4699467&#xA;0.2078624   103.4766133&#xA;0.20806118  103.4627467&#xA;0.20827364  103.46552&#xA;0.2084821   103.4710667&#xA;0.20867204  103.4799467&#xA;0.20888772  103.4605333&#xA;0.2091187   103.4227733&#xA;0.20931108  103.48384&#xA;0.20950342  103.4633067&#xA;0.20971752  103.4677333&#xA;0.2099147   103.4699467&#xA;0.21013844  103.4694133&#xA;0.21032434  103.51048&#xA;0.2105481   103.4721867&#xA;0.2107332   103.49104&#xA;0.21096178  103.5321333&#xA;0.211167    103.51216&#xA;0.21137706  103.5043733&#xA;0.21157584  103.5082667&#xA;0.21177464  103.5249333&#xA;0.21199838  103.5226933&#xA;0.21218912  103.54936&#xA;0.21240724  103.53656&#xA;0.21261486  103.5077067&#xA;0.21282334  103.5332267&#xA;0.21304304  103.5587733&#xA;0.21325954  103.5526667&#xA;0.21345512  103.5870933&#xA;0.21365956  103.54488&#xA;0.21386558  103.51992&#xA;0.21408448  103.5593333&#xA;0.21429294  103.5509867&#xA;0.21449334  103.52824&#xA;0.2147026   103.5793067&#xA;0.21492152  103.5854133&#xA;0.21512996  103.57264&#xA;0.21534 103.5432267&#xA;0.21554282  103.5809867&#xA;0.21574404  103.5759733&#xA;0.21596858  103.54656&#xA;0.21617142  103.5848533&#xA;0.21636296  103.5632&#xA;0.21658588  103.5515467&#xA;0.21679434  103.5881867&#xA;0.21700602  103.54824&#xA;0.21721044  103.60816&#xA;0.21743018  103.61872&#xA;0.2176394   103.5721067&#xA;0.21785268  103.5682133&#xA;0.21805792  103.6065067&#xA;0.21825348  103.58208&#xA;0.2184732   103.60152&#xA;0.21867604  103.60152&#xA;0.21890378  103.61984&#xA;0.21910582  103.6059467&#xA;0.21929816  103.6104&#xA;0.2195074   103.61816&#xA;0.21971826  103.6131733&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also please tell me how reliable the new python package is.&lt;/p&gt;&#xA;" OwnerDisplayName="user1015" LastEditorUserId="5" LastEditDate="2020-08-04T22:14:21.080" LastActivityDate="2022-05-25T07:03:27.897" Title="How to find Young's Modulus using stress strain curve using Python?" Tags="|python|answer-with-calculation|stress-strain|" AnswerCount="3" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1479" PostTypeId="1" CreationDate="2020-07-07T19:01:08.217" Score="2" ViewCount="37" Body="&lt;p&gt;I'm comparing the cost of dialysis in each country. The x axis is health expenditure per capita. The y axis is cost of dialysis per patient. As you will see, this incredibly produces a near liner model. Except, for the U.S. Although some would expect the U.S. to be above the model line, the U.S. is well below the expected value.&lt;/p&gt;&#xA;&lt;p&gt;What is the best way to statistically demonstrate this for a medical journal publication? Can you say an actual value is statistically different than an expected value? &lt;a href=&quot;https://i.stack.imgur.com/r2P8T.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/r2P8T.jpg&quot; alt=&quot;graph&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1017" LastActivityDate="2020-07-07T19:01:08.217" Title="What is the best way to compare an actual value from an expected value on a linear model?" Tags="|mathematical-modeling|" AnswerCount="0" CommentCount="1" ClosedDate="2020-07-07T19:22:33.210" ContentLicense="CC BY-SA 4.0" />
  <row Id="1480" PostTypeId="1" CreationDate="2020-07-07T20:43:06.427" Score="29" ViewCount="3379" Body="&lt;p&gt;Is 2x2x2 enough, or is larger needed? I know that a convergence test must be carried out, but increasing supercell size enormously increases computational time, and I am using the Python program Phonopy.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="792" LastEditDate="2020-07-22T06:25:30.637" LastActivityDate="2020-11-02T22:09:21.800" Title="How big should a supercell be in phonon calculations?" Tags="|density-functional-theory|phonons|numerical-convergence|phonopy|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1481" PostTypeId="2" ParentId="1480" CreationDate="2020-07-08T06:17:06.637" Score="17" Body="&lt;p&gt;Ideally, a convergence test would be the best way to decide the required size of the supercell, but it can get expensive.&lt;/p&gt;&#xA;&lt;p&gt;When phonopy (or any similar calculation technique) finds displacements in the cell based on symmetry, the idea is to see how the displacement of certain ions affects the forces on every ion within the cell. We must then take care that the displaced ions don't affect themselves i.e. the effect of their displacement doesn't interact with itself. I think every type of atom would exert a different potential, which might also depend on the # of electrons taken to be valence electrons, so there can't be a definitive answer to this question (except convergence).&lt;/p&gt;&#xA;&lt;p&gt;Luckily, on the &lt;a href=&quot;https://sourceforge.net/projects/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sourceforge forum for phonopy&lt;/a&gt; they suggest using a supercell with at least 7 angstrom length in each direction.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-11-02T22:09:21.800" LastActivityDate="2020-11-02T22:09:21.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1482" PostTypeId="2" ParentId="1480" CreationDate="2020-07-08T07:56:38.867" Score="34" Body="&lt;p&gt;&lt;strong&gt;Quick Summary&lt;/strong&gt;: There's no way around performing a convergence test. However, it is possible to obtain convergence &lt;em&gt;much&lt;/em&gt; faster than the Phonopy approach by using nondiagonal supercells [&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.184301&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;The basic quantity you build when performing a phonon calculation is the matrix of force constants, given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha,i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})=\frac{\partial^2 E}{\partial u_{p\alpha i}\partial u_{p^{\prime}\alpha^{\prime}i^{\prime}}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the potential energy surface in which the nuclei move, &lt;span class=&quot;math-container&quot;&gt;$u_{p\alpha i}$&lt;/span&gt; is the displacement of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (of all atoms in the basis), in Cartesian direction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;), and located in the cell within the supercell at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt;. This matrix of force constants is, roughly speaking, measuring the following: if I move an atom at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt;, what force does an atom at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_{p^{\prime}}$&lt;/span&gt; feel? If the atoms are sufficiently far apart &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{R}_p-\mathbf{R}_{p^{\prime}}|\gg1$&lt;/span&gt;, then the atoms do not feel the force, and &lt;span class=&quot;math-container&quot;&gt;$D_{i\alpha,i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})\to0$&lt;/span&gt;.&#xA;So you need a supercell large enough to capture all relevant non-zero entries in the matrix of force constants. An equivalent picture emerges when we consider the relation between a supercell of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt;, which is equivalent to sampling the Brillouin zone (BZ) of the system with a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; grid of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt; (as the BZ of the supercell is correspondingly smaller compared to the BZ of the primitive cell). In this language, you need a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid sampling the BZ that is large enough.&lt;/p&gt;&#xA;&lt;p&gt;So how quickly does &lt;span class=&quot;math-container&quot;&gt;$D_{i\alpha,i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})$&lt;/span&gt; go to zero? There is no general answer to this question, it is system-dependent. Therefore, you &lt;em&gt;must&lt;/em&gt; perform a convergence test. One thing to note is that the size of your primitive cell will play a role: if you are looking at diamond, with a very small primitive cell containing only 2 atoms, then a &lt;span class=&quot;math-container&quot;&gt;$2\times 2\times 2$&lt;/span&gt; grid will definitely not be large enough. However, if you consider a system with a primitive cell containing many atoms, for example &lt;span class=&quot;math-container&quot;&gt;$\ce{In_2O_3}$&lt;/span&gt; with 40 atoms in the primitive cell, then a &lt;span class=&quot;math-container&quot;&gt;$2\times 2\times 2$&lt;/span&gt; grid may be enough. Another thing to consider is the shape of the primitive cell. If your primitive cell is very elongated along one direction, then the distances are larger already along that direction, so you would probably be better off with a non-uniform sampling grid.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Diagonal supercells.&lt;/strong&gt; So how are calculations performed in practice? When you need to sample a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt;, then a code like Phonopy builds a supercells of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt;. This is accomplished using what I call a &lt;em&gt;diagonal supercell&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{s_1} \\&#xA;\mathbf{a}_{s_2} \\&#xA;\mathbf{a}_{s_3} &#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;N_1 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; N_2 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; N_3&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{p_1} \\&#xA;\mathbf{a}_{p_2} \\&#xA;\mathbf{a}_{p_3} &#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{s_1},\mathbf{a}_{s_2},\mathbf{a}_{s_3})$&lt;/span&gt; are the supercell lattice parameters, and &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{p_1},\mathbf{a}_{p_2},\mathbf{a}_{p_3})$&lt;/span&gt; are the primitive cell lattice parameters. As you correctly say, this can very quickly become extremely expensive computationally. There are many published phonon calculations that are not properly converged because of this computational bottleneck. However, if you want to do a proper job, there is no way around performing a convergence test. However, things can be done better than this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Nondiagonal supercells.&lt;/strong&gt; It was recently pointed out that, in order to sample a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt;, it is possible to build &lt;em&gt;smaller&lt;/em&gt; supercells that are mathematicall exactly equivalent to the diagonal supercells. These are called &lt;em&gt;nondiagonal supercells&lt;/em&gt; because they exploit the fact that you can build an equally valid supercell not only by scaling the primitive cell lattice vectors, but also by making linear combinations of them. In this case, you obtain:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{s_1} \\&#xA;\mathbf{a}_{s_2} \\&#xA;\mathbf{a}_{s_3} &#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{p_1} \\&#xA;\mathbf{a}_{p_2} \\&#xA;\mathbf{a}_{p_3} &#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; entries are not necessarily zero for &lt;span class=&quot;math-container&quot;&gt;$i\neq j$&lt;/span&gt;. Exploiting this additional degree of freedom, then when you want to sample a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid of size &lt;span class=&quot;math-container&quot;&gt;$N_1\times N_2\times N_3$&lt;/span&gt;, the largest supercell you need is of size given by the &lt;em&gt;lowest common multiple&lt;/em&gt; of &lt;span class=&quot;math-container&quot;&gt;$N_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$N_2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$N_3$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This leads to a dramatic reduction of computational time: if you are interested in sampling a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid of size &lt;span class=&quot;math-container&quot;&gt;$N\times N\times N$&lt;/span&gt;, then with diagonal supercells (e.g. Phonopy), you need a supercell of size &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt;. With nondiagonal supercells, you need a supercell of size &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;. In the original paper there is an extreme example for calculating the phonons of diamond using a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid of size &lt;span class=&quot;math-container&quot;&gt;$48\times48\times48$&lt;/span&gt;. Using Phonopy this would be completely impossible, as it would require a supercell of size 110,592 (containing 221,184 atoms)! This calculation is in fact possible (and relatively easy), using nondiagonal supercells, which would only require a supercell of size 48 (containing 96 atoms).&lt;/p&gt;&#xA;&lt;p&gt;Disclaimer: I am an author of the nondiagonal supercell paper.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Lloyd-Williams, J., &amp;amp; Monserrat, B. (2015). Lattice dynamics and electron-phonon coupling calculations using nondiagonal supercells, Phys. Rev. B, 92, 184301 DOI: 10.1103/PhysRevB.92.184301.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-10-29T22:15:46.390" LastActivityDate="2020-10-29T22:15:46.390" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1483" PostTypeId="2" ParentId="1193" CreationDate="2020-07-08T08:08:03.857" Score="10" Body="&lt;p&gt;Often we are hung up on the idea of making sure we generate an SQS of a size (i.e. # of atoms) that matches the composition of our system. For instance, in the case of &lt;span class=&quot;math-container&quot;&gt;$A_3B$&lt;/span&gt; we would generally take multiples of 4 as the # of atoms. This isn't always enough, especially in your case. Since you want to make a cell that is ordered in certain layers and disordered in others, you are limiting yourself in terms of # of atoms required to generate the SQS.&lt;/p&gt;&#xA;&lt;p&gt;This '&lt;strong&gt;integer&lt;/strong&gt; # of atoms and corresponding composition' constraint also applies to sub-lattices in your cell. Sometimes the overall cell might comply with this constraint but certain symmetry equivalent sites may not. I don't know how exactly does one determine sublattices in a partially ordered cell but &lt;code&gt;corrdump&lt;/code&gt; seems to be the way out - &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/forum/viewtopic.php?f=15&amp;amp;t=410&amp;amp;p=1484&amp;amp;hilit=Impossible%20to%20match%20point%20correlations%20due%20to%20incompatible%20supercell%20size&amp;amp;sid=9dcb407ef9eb2dd9e1e019181ce566ff&quot; rel=&quot;noreferrer&quot;&gt;read here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In your case, 192 atoms turn out to be the minimum # of atoms that comply with this constraint.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-07-08T16:20:49.067" LastActivityDate="2020-07-08T16:20:49.067" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1484" PostTypeId="1" AcceptedAnswerId="1485" CreationDate="2020-07-08T10:37:08.437" Score="14" ViewCount="481" Body="&lt;p&gt;Is there any paper that proves/disproves that the occupied orbitals obtained using full Configuration Interaction (CI) are the same as the orbitals obtained using DFT (assuming we use the exact functional, which is not found yet)?&lt;/p&gt;&#xA;" OwnerUserId="882" LastEditorUserId="882" LastEditDate="2020-07-08T11:21:24.497" LastActivityDate="2020-07-09T16:09:59.920" Title="Orbitals in full CI and DFT with true functional" Tags="|density-functional-theory|full-configuration-interaction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1485" PostTypeId="2" ParentId="1484" CreationDate="2020-07-08T11:38:38.917" Score="15" Body="&lt;p&gt;FCI doesn't really have &amp;quot;occupied orbitals&amp;quot; in the mean-field sense, since all orbitals become fractionally occupied. What one usually does is look at natural orbitals, which one gets by diagonalizing the one-particle density matrix; then each spin-orbital has some occupation number &lt;span class=&quot;math-container&quot;&gt;$f_n \in [0,1]$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, DFT isn't really aiming to reproduce the orbitals but rather the electron density, i.e., the diagonal part of the one-particle density matrix. There has also been a lot of unclarity in this question: again, Kohn-Sham DFT uses a set of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; fully occupied spin-orbitals, whereas the exact solution i.e. FCI has &lt;span class=&quot;math-container&quot;&gt;$K\gg N$&lt;/span&gt; fractionally occupied orbitals, that should yield the same total density at every point in space.&lt;/p&gt;&#xA;&lt;p&gt;This question has been discussed recently by Mayer et al in a short letter, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.7b00562&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 13, 3961 (2017)&lt;/a&gt;. The authors point out that FCI and exact DFT can never be equivalent in a finite basis set; the equivalence only holds in an &lt;em&gt;&lt;strong&gt;infinite and complete&lt;/strong&gt;&lt;/em&gt; basis.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-07-09T16:09:59.920" LastActivityDate="2020-07-09T16:09:59.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1486" PostTypeId="1" AcceptedAnswerId="1501" CreationDate="2020-07-08T12:07:18.743" Score="19" ViewCount="1778" Body="&lt;p&gt;I often encounter terms such as (Helmholtz, Gibbs) &lt;strong&gt;free energy&lt;/strong&gt;,  &lt;strong&gt;potential energy&lt;/strong&gt; and &lt;strong&gt;total energy&lt;/strong&gt; when describing the energy of a physical system at atomic level. Sometimes I stumble upon &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/002236977490033X&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Coulomb energy&lt;/strong&gt;&lt;/a&gt;, which adds more to the confusion. My (vague) understanding is that potential energy of a cell should be equal to Coulomb energy of that cell.&lt;/p&gt;&#xA;&lt;p&gt;Could someone explain the differences/similarities between these terms, including what contributes to the &amp;quot;total energy&amp;quot; found in a DFT (VASP) calculation?&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-07-10T02:58:53.603" Title="Difference between potential energy, free energy and Coulomb energy in solid state physics" Tags="|density-functional-theory|vasp|condensed-matter|free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1487" PostTypeId="2" ParentId="1480" CreationDate="2020-07-08T16:44:08.510" Score="15" Body="&lt;p&gt;Considering this in terms of a 2x2x2 supercell matrix is the wrong way to think about this, as choice depends on the cell length and bonding type.  Given that rigorous convergence testing is near-impossible (see ProfM's answer), what saves the method is the rapid fall-off with distance of the force constant matrix &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt;. This &amp;quot;nearsigtedness&amp;quot; means that the effect of a displacement of one atom will decrease with distance with a rapid power-law (see &lt;a href=&quot;http://link.aps.org/doi/10.1103/PhysRevB.50.13035&quot; rel=&quot;noreferrer&quot;&gt;Gonze et al&lt;/a&gt;). They show the decay of force constants in Quartz to near-zero at a distance of ~&lt;span class=&quot;math-container&quot;&gt;$7.5 \overset{\circ}{\mathrm{A}}$&lt;/span&gt;. Consequently a cutoff radius of &lt;span class=&quot;math-container&quot;&gt;$7.5 \overset{\circ}{\mathrm{A}}$&lt;/span&gt;, or a diameter of &lt;span class=&quot;math-container&quot;&gt;$15 \overset{\circ}{\mathrm{A}}$&lt;/span&gt; will suffice.&lt;/p&gt;&#xA;&lt;p&gt;So in that case a supercell dimension of &lt;span class=&quot;math-container&quot;&gt;$15 \overset{\circ}{\mathrm{A}}$&lt;/span&gt; on a side or greater will be large enough to ensure that there is no aliasing error from overlap of the (supercell)-periodic images of the force constant matrix [*]. The 7A referred to in a previous answer is unlikely to be sufficient. This is strongly material/bonding-dependent. In polar materials and very rigid materials the fall-off is slower than in soft materials.  For example in graphite the in-plane force constants decay much more slowly than the interlayer ones.&lt;/p&gt;&#xA;&lt;p&gt;[*] Gonze &lt;em&gt;et al.&lt;/em&gt; also show that a model correction for the Coulomb dipole contribution can be used to reduce the acceptable cutoff, but this is not usually done for finite-displacement calculations as Born charges and dielectric permittivity tensors are required.]&lt;/p&gt;&#xA;" OwnerUserId="498" LastEditorUserId="5" LastEditDate="2020-07-16T04:04:12.257" LastActivityDate="2020-07-16T04:04:12.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1488" PostTypeId="2" ParentId="385" CreationDate="2020-07-08T16:55:23.783" Score="10" Body="&lt;p&gt;I have looked for a similar set of benchmarks and haven't found one, unfortunately. Hopefully the data referred to in the comments comes through!&lt;/p&gt;&#xA;&lt;p&gt;In the meantime, I have an MIT-licensed implementation of the Wolf-like alternative to Ewald that @PhilHasnip &lt;a href=&quot;https://arxiv.org/abs/1801.01070&quot; rel=&quot;noreferrer&quot;&gt;linked to&lt;/a&gt;. Here is &lt;a href=&quot;https://github.com/wcwitt/real-space-electrostatic-sum&quot; rel=&quot;noreferrer&quot;&gt;the repository&lt;/a&gt;. Forces and stresses are available. You could try benchmarking against that, and I'd be happy to participate in generating a database.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastActivityDate="2020-07-08T16:55:23.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1489" PostTypeId="2" ParentId="391" CreationDate="2020-07-09T06:23:10.157" Score="4" Body="&lt;p&gt;As many have mentioned in the comments, the problem may not just be &lt;em&gt;me&lt;/em&gt; and it may not just be the TB09 / TB-mBJ meta-GGA (MGGA).&lt;/p&gt;&#xA;&lt;p&gt;First, it seems that the main application and success of TB09 is in yielding band &lt;strong&gt;gaps&lt;/strong&gt; of semiconductors and insulators with an accuracy reported to be &lt;em&gt;close&lt;/em&gt; to that of HSE06 or even &lt;em&gt;GW&lt;/em&gt;. One weakness that has been pointed out is that it while it improves on band gaps (compared to LDA, GGA), it underestimates bandwidths. For further reading on this, go &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.075121&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.83.195134&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It seems like emphasis is made on using TB09 with caution and will be applicable to systems under very particular conditions. However, it seems that as far as the Meta-GGAs (MGGA) go, TB09 seems to be a &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.5118863&quot; rel=&quot;nofollow noreferrer&quot;&gt;very good option&lt;/a&gt; for modeling intrinsic semiconductors. For other systems, extensive parameter fitting may be required and at that point - value whether it is worth it for &lt;em&gt;you&lt;/em&gt; and for that &lt;em&gt;specific&lt;/em&gt; project. Two of many examples of the extension of TB09 are &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b01147&quot; rel=&quot;nofollow noreferrer&quot;&gt;surfaces&lt;/a&gt; and hybrid halide &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.035139&quot; rel=&quot;nofollow noreferrer&quot;&gt;perovskites&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://www.tddft.org/programs/libxc/functionals/libxc-5.0.0/&quot; rel=&quot;nofollow noreferrer&quot;&gt;LIBXC&lt;/a&gt;, the TB09 functional is listed in the &lt;em&gt;Meta-GGA Exchange&lt;/em&gt; section listed as &amp;quot;MGGA_X_TB09 (id=208): Tran &amp;amp; Blaha 09&amp;quot; and has been around for a while, in various LIBXC versions. As far as Quantum ESPRESSO, LIBXC itself should not be the root cause of any issues, especially for QE v.6.0 and newer.&lt;/p&gt;&#xA;&lt;p&gt;As some have mentioned in the comments, converging MGGA in general is not an easy task and multiple factors need to be analyzed, such as the pseudopotentials and the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.7b02882&quot; rel=&quot;nofollow noreferrer&quot;&gt;kinetic energy density&lt;/a&gt;... one of my most recent errors was related precisely to this. Quantum ESPRESSO is no exception.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I asked this question here on May 5th, 2020.&lt;/strong&gt; My 'war' with TB09-in-QE was around November 2019, and ultimately decided it would be easier and faster to get it done with Wien2K and that was done. However I didn't want to accept that defeat. Aside from TB09, I tried converging TPSS and I tried different sets of pseudopotentials, tried reading final GGA densities and wavefunctions as a starting point, among other things.&lt;/p&gt;&#xA;&lt;p&gt;On May 7th, 2020 , two days after the question was posted here, another QE user encountered a similar challenge. The same challenge, to be exact.&lt;/p&gt;&#xA;&lt;p&gt;I quote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Hello, &lt;strong&gt;I know this was discussed here before&lt;/strong&gt;, but I still haven’t&#xA;found a satisfactory solution. &lt;strong&gt;Can someone share a nontrivial working&#xA;example of an SCF calculation of a periodic solid with TB09?&lt;/strong&gt; If I&#xA;start “from scratch”, SCF diverges. Previously it was suggested to&#xA;start from a density calculated with a different functional, but when&#xA;I try to read in PBE density, it complains that it cannot read the&#xA;kinetic energy file (which obviously cannot be there). &lt;strong&gt;Same problem&#xA;with TPSS.&lt;/strong&gt; I was using pseudo-dojo NC pseudos for PBE - could this be&#xA;the source of the problem? Should TPSS or SCAN pseudos work better&#xA;(and where do I get them from)?&lt;/p&gt;&#xA;&lt;p&gt;Thanks, Michal Krompiec Merck KGaA&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;We might have well been trying to model the same system! Same pseudos, same errors, same alternative MGGA probed. MGGA convergence issues are well known in QE and unfortunately, the (quoting Paolo Gianozzi) &amp;quot;nasty numerical&#xA;behavior of meta-GGAs&amp;quot; give us headaches. Paolo Gianozzi is one of the masterminds behind Quantum ESPRESSO, and even he &lt;em&gt;had no more advice to give&lt;/em&gt; at one point during the thread.&lt;/p&gt;&#xA;&lt;p&gt;I don't want to re-post the thread here, but I will summarize three possible solutions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Modify the source code! Didn't work for Michael, but maybe your luck will be different.&lt;/li&gt;&#xA;&lt;li&gt;Get in code mode and &lt;em&gt;HACK&lt;/em&gt; the functional; i.e. gradually go from PBE to TB09 with some function.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;TB09 on top of SCAN on top of PBE. Literally, run a PBE scf, and use the data as starting point for SCAN. Once you get SCAN to converge, use that data for TB09. This was proposed by Reinaldo, who did this to study some semiconductors using QE v.6.5 and Michael found a happy ending, as it worked for them too.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Full thread is &lt;a href=&quot;https://www.mail-archive.com/users@lists.quantum-espresso.org/msg37843.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is TB-mBJ / TB09 problematic in Quantum ESPRESSO? YES, but so are other MGGAs.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Like everything, the TB09 seems to have its strengths and weaknesses, and at the end of the day one must evaluate whether it is in one's best interest to use TB09 in your project and if the answer is YES, then ask yourself if &lt;em&gt;why&lt;/em&gt; and &lt;em&gt;what for&lt;/em&gt;? In my honest opinion, this will determine whether it is worth-while to do extensive troubleshooting and coding. If I NEED to get SCAN working before I can get TB09, then maybe I no longer want TB09? Again, really depends on the project.&lt;/p&gt;&#xA;&lt;p&gt;As many have mentioned in the comment section and in another post on the site related to TB09, it isn't the holy-grail of functionals and at the end of the day it won't beat (or look as good) as a result (or a line in the results section of your paper) as HSE06, GW, or maybe even other MGGAs. However, TB09 has had major success in the semiconductor physics community and that makes it very valuable.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My two cents on TB09:&lt;/strong&gt; It's good. It's cool. I think it is genuinely interesting and amazing that a model exists that can yield (in many cases) bandgaps comparable to experimental values at low cost. It isn't perfect and that is why it, as well as any other functional, should be used with CAUTION. Moreover, I think it would be great to extend the potential to better fit complex systems like some authors have done. Gives it a nice classic theory feel to it. Also, I do think that learning to use multiple codes (e.g. Quantum ESPRESSO, VASP, Wien2K, Abinit, etc.) can actually save you time in the long run. While I was fighting with QE, I reproduced my GGA reuslts and had the TB09 results in Wien2K. Most of the papers I've read that employ TB09 are based on Wien2K. I gave it a try, and didn't really have any issues with it. Nobody would have cared one bit if I had managed to get the result in QE for a material that an undergrad was studying, even if I explained to them how &lt;em&gt;hard&lt;/em&gt; it was for me and how it's important to me to stay as open-source as possible ... and that's kind of my point. I may have lost the battle, but the war continues.&lt;/p&gt;&#xA;" OwnerUserId="175" LastActivityDate="2020-07-09T06:23:10.157" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1490" PostTypeId="2" ParentId="907" CreationDate="2020-07-09T06:57:49.897" Score="4" Body="&lt;p&gt;Whenever I hear &lt;em&gt;spintronics&lt;/em&gt;, &lt;em&gt;valleytronics&lt;/em&gt;, &lt;em&gt;twistronics&lt;/em&gt; or anything that really breaks down to the study of quantum transport, I always think of the people who taught me Quantum Mechanics and work in this field and a code called kwant.&lt;/p&gt;&#xA;&lt;p&gt;While I do not study these topics myself, I used to try to learn related topics and I took a couple workshops since I was considering focusing on this corner of condensed matter theory. Also, I do not know (as I have not seen) &lt;em&gt;automated&lt;/em&gt; processes applied to valleytroinics.&lt;/p&gt;&#xA;&lt;p&gt;Mostly, what I've seen is that people work with effective Hamiltonians, such as Tight-Binding models to study the electronic structure and valley engineering. This is usually accompanied by numerical simulations, which I have seen done using the &lt;a href=&quot;https://kwant-project.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;kwant&lt;/a&gt; code.&lt;/p&gt;&#xA;&lt;p&gt;Kwant is an open-source code written in python that makes quantum-transport simulations on tight-binding models &lt;em&gt;easy&lt;/em&gt;. To run the simulations, however, you &lt;em&gt;need&lt;/em&gt; to know the form of the Tight-Binding model Haniltonian. I have seen it combined with pybinding, (python tight-binding), and if one wants to get fancy, it is possible to start with DFT, construct a DFT-fitted Tight-Binding model (with the aid of Wannier90) and then use that TB Hamiltonian in Kwant.&lt;/p&gt;&#xA;&lt;p&gt;One article I had &amp;quot;at hand&amp;quot; that uses Kwant for Valleytronics is &lt;strong&gt;&amp;quot;Valley engineering by strain in Kekulé-distorted graphene&amp;quot;&lt;/strong&gt; &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.035411&quot; rel=&quot;nofollow noreferrer&quot;&gt;PHYSICAL REVIEW B 99, 035411 (2019)&lt;/a&gt;. I happen to know some of the authors of that paper and have even learned the basics of Kwant with them.&lt;/p&gt;&#xA;&lt;p&gt;However, a quick Google Scholar search of &amp;quot;Valleytronics Kwant&amp;quot; yields over 33 results. As you mentioned, this field is in its infancy and there is still much room for development.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps, or gets the ball rolling.&lt;/p&gt;&#xA;" OwnerUserId="175" LastActivityDate="2020-07-09T06:57:49.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1491" PostTypeId="1" AcceptedAnswerId="1493" CreationDate="2020-07-09T15:10:33.310" Score="12" ViewCount="1303" Body="&lt;p&gt;I am using the &lt;code&gt;pyscf&lt;/code&gt; code, where the Fock matrix can be obtained by:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf&#xA;mol = gto.Mole()&#xA;mol.atom = geometry&#xA;mol.basis = '3-21G'&#xA;mol.build&#xA;&#xA;mean_field = scf.RHF(mol)&#xA;mean_field.scf()&#xA;&#xA;Fao = mean_field.get_fock()&#xA;print(Fao)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where &lt;code&gt;geometry&lt;/code&gt; can be set for a system of interest, and the basis set &lt;code&gt;3-21G&lt;/code&gt; can easily be changed.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I have realised I do not fully understand what the rows and columns of the Fock matrix actually represent, and I have read that this is in the atomic basis and not the molecular basis?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;How does this relate to the molecular orbital coefficients obtained by: &lt;code&gt;mo_coeff = mean_field.mo_coeff&lt;/code&gt;, having already understood that a realtionship can be obtained by the Roothan-Hall equations &lt;code&gt;FC = SCe&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="794" LastEditDate="2020-07-09T17:35:47.020" LastActivityDate="2020-07-10T10:31:03.100" Title="What do the rows and columns of a Fock matrix represent?" Tags="|electronic-structure|ab-initio-calculations|self-consistent-field|hartree-fock|pyscf|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1492" PostTypeId="2" ParentId="1098" CreationDate="2020-07-09T15:32:54.910" Score="3" Body="&lt;p&gt;One place to start is just altering how you form your graphs or their corresponding matrix representation. The simplest representation is probably an unweighted graph, which corresponds to an adjacency matrix and just tells you what atoms neighbor each other. Depending on your interest, this description can be improved by using the bond order to weight the edges.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can include information related to distance, whether that is simply encoding the shortest number of bonds between two atoms. If you are willing to use a continuous model, the actual Euclidean distances can be used. More general versions of this idea have been developed in the context of machine learning to create simplified molecular descriptors. This &lt;a href=&quot;https://singroup.github.io/dscribe/tutorials/basics.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt; gives a basic summary of some commonly used continuous models, such as the Coulomb matrix, which includes both distance and charge information about the atoms/bonds of molecule. Again, these are continuous, but I would expect that it would be possible to include some notion of charge in a graph model as well. This is just to say perhaps you could still use a graph, but encode different information than you are currently.&lt;/p&gt;&#xA;&lt;p&gt;Machine learning and cheminformatics have also inspired the development of &lt;a href=&quot;http://infochim.u-strasbg.fr/FC/docs/Intro/FC_DB.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular fingerprints&lt;/a&gt;, which encode certain features of a molecule (e.g. number of rings, aromaticity, presence/absence of some substructure or functional group) rather than the exact arrangement of atoms. These are often expressed as simple bits strings, which makes comparisons very simple to perform. The choice of the features to include is an area of active study, but has generally been along the lines of manually choosing them using chemical intuition about the intended property to be studied or automatic generation of features through some type of learning process.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-09T15:32:54.910" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1493" PostTypeId="2" ParentId="1491" CreationDate="2020-07-09T17:34:05.280" Score="9" Body="&lt;p&gt;The short answer is: it is the matrix representation of the Fock operator in the given basis set, in this case, the atomic orbital (AO) basis. The Fock operator itself is a mean-field, independent particle approximation to the electronic Hamilton operator of the system (with other approximations beyond the scope of this Q&amp;amp;A).&lt;/p&gt;&#xA;&lt;p&gt;The rows/columns (the matrix must be Hermitian, therefore it does not matter) thus refer to one basis function each. The equation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{F}\mathbf{C} = \mathbf{S}\mathbf{C}\mathbf{\epsilon}&#xA;$$&lt;/span&gt;&#xA;is a special eigenvalue problem, which can be similarity-transformed to an orthogonalized basis set to read&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{F'}\mathbf{C'} = \mathbf{C'}\mathbf{\epsilon}&#xA;$$&lt;/span&gt;&#xA;which is a standard eigenvalue problem, solvable by diagonalization techniques. The &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt; are the canonical molecular orbital (MO) coefficients for the non-orthogonal AO basis set.&lt;/p&gt;&#xA;&lt;p&gt;Note that in the canonical MO basis set, the Fock matrix is diagonal by definition. Other choices for MO basis sets exist, such as localized MOs.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Source:&#xA;A Szabo, NS Ostlund: &lt;em&gt;Modern Quantum Chemistry&lt;/em&gt;, Dover Publications, 1996.&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="794" LastEditDate="2020-07-10T04:07:38.433" LastActivityDate="2020-07-10T04:07:38.433" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1494" PostTypeId="5" CreationDate="2020-07-09T17:39:11.917" Score="0" Body="&lt;p&gt;NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters.&lt;/p&gt;&#xA;&lt;p&gt;The NWChem software can handle:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Biomolecules, nanostructures, and solid-state&lt;/li&gt;&#xA;&lt;li&gt;From quantum to classical, and all combinations&lt;/li&gt;&#xA;&lt;li&gt;Ground and excited-states&lt;/li&gt;&#xA;&lt;li&gt;Gaussian basis functions or plane-waves&lt;/li&gt;&#xA;&lt;li&gt;Scaling from one to thousands of processors&lt;/li&gt;&#xA;&lt;li&gt;Properties and relativistic effects&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;NWChem is actively developed by a consortium of developers and maintained by the EMSL located at the Pacific Northwest National Laboratory (PNNL) in Washington State. Researchers interested in contributing to NWChem should review the Developers page. The code is distributed as open-source under the terms of the Educational Community License version 2.0 (ECL 2.0).&lt;/p&gt;&#xA;&lt;p&gt;The NWChem development strategy is focused on providing new and essential scientific capabilities to its users in the areas of kinetics and dynamics of chemical transformations, chemistry at interfaces and in the condensed phase, and enabling innovative and integrated research at EMSL. At the same time continued development is needed to enable NWChem to effectively utilize architectures of tens of petaflops and beyond.&lt;/p&gt;&#xA;&lt;p&gt;Description source: &lt;a href=&quot;https://nwchemgit.github.io&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://nwchemgit.github.io&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-09T17:39:11.917" LastActivityDate="2020-07-09T17:39:11.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1495" PostTypeId="4" CreationDate="2020-07-09T17:39:11.917" Score="0" Body="For questions about the NWChem computational chemistry program." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-09T17:39:11.917" LastActivityDate="2020-07-09T17:39:11.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1496" PostTypeId="5" CreationDate="2020-07-09T17:42:02.493" Score="0" Body="&lt;p&gt;PySCF is an open-source collection of electronic structure modules powered by Python. The package aims to provide a simple, lightweight, and efficient platform for quantum chemistry calculations and methodology development.&lt;/p&gt;&#xA;&lt;p&gt;Description source: &lt;a href=&quot;http://pyscf.org/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://pyscf.org/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-09T17:42:02.493" LastActivityDate="2020-07-09T17:42:02.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1497" PostTypeId="4" CreationDate="2020-07-09T17:42:02.493" Score="0" Body="For questions about or related to the PySCF electronic structure package for Python" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2023-02-21T15:42:19.353" LastActivityDate="2023-02-21T15:42:19.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1498" PostTypeId="5" CreationDate="2020-07-09T20:31:40.677" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-09T20:31:40.677" LastActivityDate="2020-07-09T20:31:40.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1499" PostTypeId="4" CreationDate="2020-07-09T20:31:40.677" Score="0" Body="For questions about (or related to) fine structure and/or hyperfine structure: the spectroscopic structures resulting from spin-spin, spin-rotation, spin-orbit, orbit-orbit, and other interactions between nuclear and/or electron spins and other types of angular momentum such as molecular rotation and orbital angular momentum." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-09T20:31:40.677" LastActivityDate="2020-07-09T20:31:40.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1500" PostTypeId="2" ParentId="1478" CreationDate="2020-07-10T00:55:00.950" Score="17" Body="&lt;p&gt;I designed the Python program a few years back but haven't looked at it in some time.&lt;/p&gt;&#xA;&lt;p&gt;The __init__.py line can be commented out for your usage. That &amp;quot;model&amp;quot; was for my team's use case, and it looks like I got rid of it.&lt;/p&gt;&#xA;&lt;p&gt;You may be better off importing the &amp;quot;material_analytics.py&amp;quot; directly, and using those functions right on your dataset. They are designed to work with data like yours, and each specifies the format it expects for stress/strain samples. Keep in mind these modules are designed for high strain rate samples, and as such this is just an approximation and no guarantees can be made about the results.&lt;/p&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;" OwnerUserId="1025" LastActivityDate="2020-07-10T00:55:00.950" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1501" PostTypeId="2" ParentId="1486" CreationDate="2020-07-10T02:58:53.603" Score="16" Body="&lt;p&gt;I can't answer in the context of DFT/VASP, where these terms might have specific uses, but I can offer some general comments.&lt;/p&gt;&#xA;&lt;p&gt;These terms are not necessarily mutually exclusive:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Total energy&lt;/strong&gt; probably refers to the combined kinetic and interaction energy &lt;span class=&quot;math-container&quot;&gt;$E=K+P...$&lt;/span&gt; resulting from summing/integrating over the whole Hamiltonian. In DFT this would be the combination of all functionals.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;[Helmholtz/Gibbs] Free Energy&lt;/strong&gt; refers to the thermodynamic energy available to do work (at constant &lt;em&gt;T&lt;/em&gt;). Basically, the total internal energy of the system subtracting out the energy that is 'trapped in entropy.'&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Potential energy&lt;/strong&gt; (in this context) most likely refers to the particle-particle interactions. This could include the energy from the pseudopotentials and the electron-electron (Coulomb) interactions.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Coulomb energy:&lt;/strong&gt; in the most general sense, you are correct: the only source of potential energy is the Coulomb force. However, it's possible that this term is referring to a &lt;em&gt;specific&lt;/em&gt; contribution such as &lt;em&gt;just&lt;/em&gt; the potential energy from the psuedopotentials. (Someone better-versed in DFT can provide a more intelligent answer here). In the specific context of the reference you cited, the Coulomb energy appears to be calculated from the Coulomb interactions of the nuclei (in the lattice) with the electronic charge uniformly smeared out between them.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-07-10T02:58:53.603" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1502" PostTypeId="2" ParentId="1491" CreationDate="2020-07-10T10:31:03.100" Score="7" Body="&lt;p&gt;Formally, the Fock matrix is the density matrix derivative of the Hartree-Fock or Kohn-Sham energy functional. The Fock matrix returned by PySCF is in the atomic-orbital basis, which is actually the same as the molecular basis. If the orbitals satisfy the self-consistent field equations, then in the &lt;strong&gt;molecular orbital&lt;/strong&gt; basis the Fock matrix is diagonal.&lt;/p&gt;&#xA;&lt;p&gt;See our open access overview on SCF calculations for more information: &lt;a href=&quot;https://www.mdpi.com/1420-3049/25/5/1218&quot; rel=&quot;noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-10T10:31:03.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1503" PostTypeId="2" ParentId="688" CreationDate="2020-07-10T14:44:00.033" Score="4" Body="&lt;p&gt;As far as I am aware, double hybrids were first proposed by Truhlar and coworkers in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp049253v&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A 2004, 108, 21, 4786–4791&lt;/a&gt;. If you look at the paper, in addition to MP2 they also proposed a double hybrid based on QCISD, i.e. the quadratic configuration interaction method which can be viewed as an approximate coupled-cluster method.&lt;/p&gt;&#xA;&lt;p&gt;There's no reason &lt;em&gt;a priori&lt;/em&gt; why more elaborate post-HF methods than MP2 couldn't be employed in a double hybrid DFT functional. However, the reason why this isn't usually done is probably due to cost and accuracy: going to higher-order methods introduces much steeper scaling with system size (already MP2 is quite expensive!), while the improvements in accuracy are probably quite low and still dominated by the DFT part: at some point it's just better to discard DFT altogether and just use the post-HF method!&lt;/p&gt;&#xA;&lt;p&gt;Note also that in addition to MP2, some double hybrids employ the random phase approximation, see e.g. &lt;a href=&quot;https://doi.org/10.1039/C5CP06600J&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Chem. Chem. Phys. 18, 20926 (2016)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-10T14:44:00.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1504" PostTypeId="2" ParentId="647" CreationDate="2020-07-10T14:54:45.333" Score="6" Body="&lt;p&gt;I think the rationale is pretty well explained in the paper by Heyd, Scuseria and Ernzerhof, i.e. &lt;a href=&quot;http://doi.org/10.1063/1.1564060&quot; rel=&quot;noreferrer&quot;&gt;Journal of Chemical Physics 118, 8207 (2003)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For insulators there is a large gap, and the density matrix and the exchange interactions decay exponentially when you go farther and farther from the cell at the origin. (This means that in this case, you can easily also apply further screening to the exchange.)&lt;/p&gt;&#xA;&lt;p&gt;For metals there is no gap, which leads to a divergence in Hartree-Fock. (This problem is just an issue of Hartree-Fock, as it neglects correlation which should become significant for metals!) However, if you switch to short-range only exchange, you kill the divergence, thus making the functional better behaved.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-10T14:54:45.333" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1505" PostTypeId="2" ParentId="1439" CreationDate="2020-07-10T18:10:01.310" Score="14" Body="&lt;h2&gt;Voronoi charges&lt;/h2&gt;&#xA;&lt;p&gt;Voronoi charges (here called VC) are based on the partition of the real space in a system into Voronoi polyhedra.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; A given point in space belongs to the polyhedron of some atom if the point is closer to that atom than to any other atom. This allows to partition the space and thus assign the point charge expectation value of a given point to the appropriate atom. After summing over all points/integrating and adding the nuclear charge, one obtains the VC.&lt;/p&gt;&#xA;&lt;p&gt;The algorithm requires a numerical integration and thus, use of a grid. While grids are common in DFT, it is not &lt;em&gt;a priori&lt;/em&gt; clear what their performance is for VC determination. &lt;strong&gt;The grids might not give good accuracy in the cell border regions.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;VC would seem to be sensitive to the geometry. Consider the case of the molecule &lt;span class=&quot;math-container&quot;&gt;$\ce{HF}$&lt;/span&gt;: As one (artificially) shortens the bond distance, hydrogen will leech electron density from fluorine, though most chemists would happily assign the same &lt;span class=&quot;math-container&quot;&gt;$\delta\pm$&lt;/span&gt; to the atoms at any (bonded) distance.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; There are several different names for this concept due to their (re)discovery by many different people. See the Wikipedia article on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Voronoi_diagram&quot; rel=&quot;noreferrer&quot;&gt;Voronoi diagram&lt;/a&gt; for some of them.&lt;/p&gt;&#xA;&lt;p&gt;Source: F Jensen: &lt;em&gt;Introduction to Computational Chemistry&lt;/em&gt;, 2nd ed., Wiley, 2007.&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-07-11T16:36:07.200" LastActivityDate="2020-07-11T16:36:07.200" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1506" PostTypeId="2" ParentId="1478" CreationDate="2020-07-10T18:49:15.287" Score="16" Body="&lt;p&gt;I was able to run the code on your data and got a Young's Modulus of &lt;span class=&quot;math-container&quot;&gt;$2.08236\times10^{-5}$&lt;/span&gt;. This clearly doesn't seem right for an aluminum system, though I don't know the units you are using.&lt;/p&gt;&#xA;&lt;p&gt;To get this, I had to make a few changes to both the code and your data.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;As suggested, by Enusi, I commented out &lt;code&gt;from model import stress_strain&lt;/code&gt; from the __init__.py file.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Line 159 of material_analytics.py (&lt;code&gt;return data[0,1] + young_modulus*(x-offset)&lt;/code&gt;) starts with a tab rather than spaces. This needs to be changed for the code to run.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are using Python3.x, one of the functions uses &lt;code&gt;xrange&lt;/code&gt;, which no longer exists after Python2.x. This needs to be replaced with &lt;code&gt;range&lt;/code&gt; in order to run.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I removed your first and fourth data points. The &lt;code&gt;youngs_modulus&lt;/code&gt; function uses a log at some point, so it will give warnings if you pass it numbers that are zero or negative.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I can only guess that something is wrong with your choice of data points. The curve below is an example stress-strain curve for steel and then your aluminum alloy curve. Your curve does not really have a linear section and looks more like the example curve after the yield strength.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8znsi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8znsi.png&quot; alt=&quot;Stress-strain curve&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/SK3uC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SK3uC.png&quot; alt=&quot;User stress-strain curve&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-11T03:46:01.040" LastActivityDate="2020-07-11T03:46:01.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1507" PostTypeId="2" ParentId="411" CreationDate="2020-07-11T02:55:26.497" Score="9" Body="&lt;h2&gt;LocVib (part of MoViPac)&lt;/h2&gt;&#xA;&lt;p&gt;I have never used VEDA before, but according to the paper, it decomposes the normal modes into vibrations of atomic groups, bond stretching, bending or something else.  Something similar is &lt;strong&gt;LocVib&lt;/strong&gt;, which localizes normal modes to localized vibrational modes by maximizing the &amp;quot;distances&amp;quot;  between vibrational modes and &amp;quot;atomic contribution&amp;quot; to a mode, like localization of molecular orbitals.&lt;/p&gt;&#xA;&lt;p&gt;LocVib is not same as VEDA, and the operation is somehow more complex.  The user need to select a subset of all normal modes on their own and the localization would be done by the software, and finally localized modes, typically related to several atoms will be printed out, with derived frequencies from the normal modes.&lt;/p&gt;&#xA;&lt;p&gt;The software is in Python 2 and the github page is &lt;a href=&quot;https://github.com/chjacob-tubs/LocVib&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/chjacob-tubs/LocVib&lt;/a&gt;.  It is also part of &lt;a href=&quot;https://reiher.ethz.ch/software/movipac.html&quot; rel=&quot;noreferrer&quot;&gt;MoViPac&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="5" LastEditDate="2020-07-11T03:23:39.943" LastActivityDate="2020-07-11T03:23:39.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1508" PostTypeId="2" ParentId="901" CreationDate="2020-07-11T21:31:20.930" Score="8" Body="&lt;h2&gt;Laplacian Bond Order&lt;/h2&gt;&#xA;&lt;p&gt;This method is an extension of the QTAIM (Quantum Theory of Atoms In Molecules) concept of using the Laplacian of the electron density &lt;span class=&quot;math-container&quot;&gt;$\nabla^2\rho$&lt;/span&gt; to characterize bonding. Standard QTAIM just uses the value of &lt;span class=&quot;math-container&quot;&gt;$\nabla^2\rho$&lt;/span&gt; at bond critical points (minimum electron density along the bond, max along orthogonal directions), but these values are unintuitive and often don't accurately describe the strength or character (covalent/noncovalent) of the bond.&lt;/p&gt;&#xA;&lt;p&gt;To make this idea more accurate and the values more in line with chemical intuition, the Laplacian Bond Order uses a weighted integral of the Laplacian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\text{LBO}_{AB}=-10\int_{\nabla^2\rho&amp;lt;0}w_A(r)w_B(r)\nabla^2\rho(r)dr$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The weight for any given atom is 1 close to it and decays smoothly to 0 as it approaches another atom. At any point in space, the weight of all atoms has to add up to 1. This weight function could be arbitrary (provided it meets these criteria), but LBO  uses the so called Becke weighting function.&lt;/p&gt;&#xA;&lt;p&gt;Integrating over the negative region of the Laplacian is done to specifically capture covalent bonding. The &lt;span class=&quot;math-container&quot;&gt;$-10$&lt;/span&gt; was chosen ad hoc to make the magnitude fit chemical intuition about covalent bonds.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Matches chemical intuition for a wide range of systems.&lt;/li&gt;&#xA;&lt;li&gt;Well correlated with bond dissociation energy (at least for organic molecules and diatomics) and bond frequency (at least for CO in metal complexes).&lt;/li&gt;&#xA;&lt;li&gt;Tracks well with structural changes (e.g. weaker bonds in strained rings, weakening during double bond rotation or diatomics dissociation).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Basis set dependent, should probably use at least aug-cc-pvdz.&lt;/li&gt;&#xA;&lt;li&gt;Can only capture covalent interactions (though this can be an advantage in some cases).&lt;/li&gt;&#xA;&lt;li&gt;Currently only implemented for two body interactions (though in principle this shouldn't be difficult to extend)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-11T21:31:20.930" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1509" PostTypeId="2" ParentId="659" CreationDate="2020-07-11T21:35:30.263" Score="12" Body="&lt;h2&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;Your question reminds me of a quote by Paul Dirac,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The underlying physical laws necessary for the mathematical theory of a large part of physics and the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble. It therefore becomes desirable that approximate practical methods of applying quantum mechanics should be developed, which can lead to an explanation of the main features of complex atomic systems without too much computation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(He published &lt;a href=&quot;http://rspa.royalsocietypublishing.org/content/royprsa/123/792/714.full.pdf&quot; rel=&quot;noreferrer&quot;&gt;this in 1929&lt;/a&gt;, but the overall sentiment remains relevant. See &lt;a href=&quot;https://chemistry.stackexchange.com/q/50681&quot;&gt;this Chemistry.SE question&lt;/a&gt; for a discussion about the degree to which it's true.)&lt;/p&gt;&#xA;&lt;p&gt;At least from a physicist's perspective, the point of models like the Heisenberg Hamiltonian is to have a simpler description that is &amp;quot;good enough&amp;quot;, and lets us focus on the relevant low-energy degrees of freedom. In doing so we can hopefully come to &lt;em&gt;understand&lt;/em&gt; a system, at least in some regime. A key point is that these models have a limited range of validity, but if this range includes experimentally relevant energy and temperature scales they can be very useful. Clearly, at high enough energies where charge excitations begin to appear, the idea of a pure magnetic insulator (a potentially confusing term that means insulators that have some form of magnetism) breaks down. Then again, we could say the same about first principles quantum chemistry — at high enough energy we can no longer neglect particle physics effects! It's a beautiful and non-trivial fact that simplified &amp;quot;effective&amp;quot; descriptions are valid at different scales (be they energy, length, particle number, etc.) and that we can forget about some details from the level below, while finding new emergent behavior as we climb the ladder of scale.&lt;/p&gt;&#xA;&lt;h2&gt;Is the Heisenberg Hamiltonian good enough?&lt;/h2&gt;&#xA;&lt;p&gt;Certainly the antiferromagnetic Heisenberg has some &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/525/671&quot;&gt;close realizations in materials&lt;/a&gt;. However, given your choice of sign for &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; and mention of the Bloch &lt;span class=&quot;math-container&quot;&gt;$T^{3/2}$&lt;/span&gt; law suggests you're more interested in ferromagnetic systems. I can't claim expertise in these, but maybe I can say something general. Many ferromagnets are itinerant systems, which is exemplified by &lt;a href=&quot;https://en.wikipedia.org/wiki/Stoner_criterion&quot; rel=&quot;noreferrer&quot;&gt;Stoner's model&lt;/a&gt; of majority and minority spin bands, which can be considered a mean-field approximation of a Hubbard Hamiltonian. This itinerant limit is completely different from the localized limit that leads to the Heisenberg spin model, which is applicable to magnetic insulators. Before the early 1950s this picture was not really clear, and there was a debate about which model would be more appropriate — especially when it came to &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; electrons in iron group metals. The Stoner model didn't reproduce the Curie-Weiss law as well as the Heisenberg model, but could explain fractional saturation moments. In addition, it wasn't clear at the time how to get a ferromagnetic &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; in case of the Heisenberg model.&lt;/p&gt;&#xA;&lt;p&gt;Nature being nature didn't seem to entirely favor either limit, so people like Van Vleck and others worked on &amp;quot;middle-of-the-road&amp;quot; theories to better describe such systems. Eventually this led to more involved theories, including a successful Self-Consistent Renormalization (SCR) theory introduced by Moriya and Kawabata. Such theories elucidated the differences between the two limits, and how to describe them. In &lt;a href=&quot;https://doi.org/10.2183/pjab.82.1&quot; rel=&quot;noreferrer&quot;&gt;Moriya's words&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Around 1960’s a widely accepted point of view, after the long controversy, was that the magnetic insulator compounds and rare earth magnets are described in terms of the localized electron model while the ferromagnetic d-electron metals should be described on the itinerant electron model with the approximation method beyond the mean field level, properly taking account of the effects of electron-electron correlations. One of the clearest motivations for this consensus was the successful experimental observations of the d-electron Fermi surfaces in ferromagnetic Fe and Ni and their good comparisons with the results of band theoretical calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The conclusion is that, in many cases, the Heisenberg Hamiltonian is far from good enough. But in the case of ferromagnetic insulators it can be good enough — especially if you allow for some anisotropy, either in the case of an XXZ anisotropy &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;, or a single-ion anisotropy &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;, as in&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H   =   J \sum_{\langle i,j\rangle} \left[ S_i^x S_j^x + S_i^y S_j^y + \Delta S_i^z S_j^z \right] + D \sum_i \left( S_i^z \right)^2,&#xA;$$&lt;/span&gt;&#xA;or other interactions, like the Dzyaloshinskii-Moriya interaction (DMI) in the case of oxides with heavier ions. I provide a list of such FM insulating materials below.&lt;/p&gt;&#xA;&lt;h2&gt;What is the performance of the Heisenberg Hamiltonian compared to a first principles Hamiltonian? What are the pros and cons?&lt;/h2&gt;&#xA;&lt;p&gt;Unfortunately I don't really have a satisfactory answer to this question. I don't know of a direct benchmark. But we can return to the dichotomy of the two limits discussed above. For itinerant systems, first-principles calculations should of course do better, but it's not a very fair comparison. In the limit of ferromagnetic insulators, the energy scales are typically on the order of 1-10 meV or &lt;em&gt;less&lt;/em&gt;. Practically speaking, that's beyond the accuracy of DFT-based methods and electronic stucture quantum Monte Carlo. On the other hand, spin models lose by walkover when it comes to the physics they neglect, and thus have nothing to say about some properties and experiments. &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728125/&quot; rel=&quot;noreferrer&quot;&gt;Quantum chemistry&lt;/a&gt; does have some highly accurate wave function approaches, but they tend to scale very badly with system size. E.g. the CCSD(T) method famously scales as &lt;span class=&quot;math-container&quot;&gt;$N^7$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the system size. This makes it pretty much a non-starter to use them to explore large-scale collective magnetic phenomena.&lt;/p&gt;&#xA;&lt;p&gt;Personally I hope to see more progress in this area. It would be very useful to have a reliable first-principles method to derive low energy spin Hamiltonians, that can then be explored in more detail. (Some experiments, like neutron scattering, are more naturally interpreted in terms of spin Hamiltonians.) It might also speed up discovery of materials hosting exotic phases.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h2&gt;Appendices&lt;/h2&gt;&#xA;&lt;h2&gt;Ferromagnetic insulators&lt;/h2&gt;&#xA;&lt;p&gt;While ferromagnetic insulators appear to be rare compared to antiferromagnetic ones, there are some examples, and they seem to have applications in spintronics and to induce ferromagnetic backgrounds in nonmagnetic materials. The most well-known is probably &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.7.160&quot; rel=&quot;noreferrer&quot;&gt;EuO, discovered in 1961&lt;/a&gt;, and similar Europium chalcogenides EuX (X=O, S, Se, Te). These are well-described by the Heisenberg Hamiltonian, as discussed in the review by &lt;a href=&quot;https://orproxy.lib.utk.edu:2054/science/article/pii/0370157386901390&quot; rel=&quot;noreferrer&quot;&gt;Mauger and Goodart, Physics Reports &lt;strong&gt;141&lt;/strong&gt;, 51-176 (2006)&lt;/a&gt;. In these materials the ferromagnetic coupling appears to be due to an indirect Eu-Eu exchange.&lt;/p&gt;&#xA;&lt;p&gt;I provide a partial list of ferromagnetic insulating compounds here, but note that some may have differnt (including more complicated) spin model Hamiltonians.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;EuO&lt;/li&gt;&#xA;&lt;li&gt;EuS&lt;/li&gt;&#xA;&lt;li&gt;EuSe&lt;/li&gt;&#xA;&lt;li&gt;EuTe&lt;/li&gt;&#xA;&lt;li&gt;YTiO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;SeCuO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;BiMnO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;La&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;NiMnO&lt;span class=&quot;math-container&quot;&gt;$_6$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;LaMnO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;CaMNO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (Spaldin)&lt;/li&gt;&#xA;&lt;li&gt;Sr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;CrOsO&lt;span class=&quot;math-container&quot;&gt;$_6$&lt;/span&gt; (&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.75.020404&quot; rel=&quot;noreferrer&quot;&gt;source&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;La&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;CoMnO&lt;span class=&quot;math-container&quot;&gt;$_6$&lt;/span&gt; (&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.035131&quot; rel=&quot;noreferrer&quot;&gt;source&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Yttrium iron garnet (YIG)&lt;/li&gt;&#xA;&lt;li&gt;CoFe2O4 (mentioned &lt;a href=&quot;https://u.osu.edu/kawakamigroup/science2015/epitaxial-growth-of-thin-film-heterostructures-for-spintronics-applications/ferromagnetic-insulators/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Lu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;V&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O&lt;span class=&quot;math-container&quot;&gt;$_7$&lt;/span&gt; (includes DMI, &lt;a href=&quot;https://science.sciencemag.org/content/329/5989/297&quot; rel=&quot;noreferrer&quot;&gt;source&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Cu(1-3)-bdc (with DMI, &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.115.106603&quot; rel=&quot;noreferrer&quot;&gt;source&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Above Spaldin refers to Nicola Spaldin's book &lt;a href=&quot;https://www.cambridge.org/core/books/magnetic-materials/4C8C2C5DF32C9E8D528E1E8D26381C1F&quot; rel=&quot;noreferrer&quot;&gt;Magnetic Materials: Fundamentals and Applications&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Other mechanisms&lt;/h2&gt;&#xA;&lt;p&gt;Despite what I've written above, the Heisenberg Hamiltonian is actually sometimes relevant also to metals (which we'd naturally think of as itinerant). The idea is that the conduction electrons provide a non-magnetic background, and that the presence of nuclear spins or magnetic ions interact with this conduction electron background as to produce a long-range Heisenberg interaction, which can be either ferro- or antiferromagnetic. This is known as the &lt;a href=&quot;https://en.wikipedia.org/wiki/RKKY_interaction&quot; rel=&quot;noreferrer&quot;&gt;RKKY interaction&lt;/a&gt;. Again, it's worth noting that in the RKKY limit there are conduction electrons present, but the derived effective Heisenberg Hamiltonian still describes part of the physics. Other mechanisms include Zener carrier-mediated exchange, and &lt;a href=&quot;https://en.wikipedia.org/wiki/Double-exchange_mechanism&quot; rel=&quot;noreferrer&quot;&gt;double exchange&lt;/a&gt;. See e.g. Spaldin for a discussion of these.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2020-07-12T14:26:53.050" LastActivityDate="2020-07-12T14:26:53.050" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1510" PostTypeId="2" ParentId="1364" CreationDate="2020-07-14T12:37:18.207" Score="3" Body="&lt;p&gt;You can get a tutorial for what you want in this way:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Open the VirtualNanoLab&lt;/li&gt;&#xA;&lt;li&gt;From the &lt;code&gt;Help&lt;/code&gt; menu, got to &lt;code&gt;VNL Tutorials...&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Click at the first option &lt;code&gt;Complete List&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Look for &lt;em&gt;Building an interface between Ag(100) and Au(111)&lt;/em&gt; (fifth tutorial)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;(or get it on-line &lt;a href=&quot;https://docs.quantumatk.com/tutorials/ag_au_interface/ag_au_interface.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Also, I did the following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;added a shift between the surface to create a gap&lt;/li&gt;&#xA;&lt;li&gt;repeat the cell in order to get a supercell (&lt;code&gt;Bulk Tools -&amp;gt; Repeat&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;change the lattice parameters (&lt;code&gt;Bulk Tools -&amp;gt; Lattice Parameters&lt;/code&gt;) to create the vacuum regions (note: you have to maintain the coordinates as Cartesian)&lt;/li&gt;&#xA;&lt;li&gt;Center the atoms in the new cell (&lt;code&gt;Coordinate Tools -&amp;gt; Center&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;I exported as CIF but you can exported to other formats too.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here is the final system:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/YY994.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YY994.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;CIF file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    data_global&#xA;_cell_length_a 25.9775&#xA;_cell_length_b 14.7098&#xA;_cell_length_c 34.8923&#xA;_cell_angle_alpha 90&#xA;_cell_angle_beta 90&#xA;_cell_angle_gamma 90&#xA;_symmetry_space_group_name_H-M 'P -1'&#xA;loop_&#xA;_symmetry_equiv_pos_as_xyz&#xA;  'x,y,z'&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;Ag 0.0277776 0.0277763 0.31587&#xA;Ag 0.361111 0.0277763 0.31587&#xA;Ag 0.694445 0.0277763 0.31587&#xA;Ag 0.138889 0.0277763 0.31587&#xA;Ag 0.472222 0.0277763 0.31587&#xA;Ag 0.805556 0.0277763 0.31587&#xA;Ag 0.25 0.0277763 0.31587&#xA;Ag 0.583333 0.0277763 0.31587&#xA;Ag 0.916667 0.0277763 0.31587&#xA;Ag 0.0277776 0.227777 0.31587&#xA;Ag 0.361111 0.227777 0.31587&#xA;Ag 0.694445 0.227777 0.31587&#xA;Ag 0.138889 0.227777 0.31587&#xA;Ag 0.472222 0.227777 0.31587&#xA;Ag 0.805556 0.227777 0.31587&#xA;Ag 0.25 0.227777 0.31587&#xA;Ag 0.583333 0.227777 0.31587&#xA;Ag 0.916667 0.227777 0.31587&#xA;Ag 0.0277776 0.427778 0.31587&#xA;Ag 0.361111 0.427778 0.31587&#xA;Ag 0.694445 0.427778 0.31587&#xA;Ag 0.138889 0.427778 0.31587&#xA;Ag 0.472222 0.427778 0.31587&#xA;Ag 0.805556 0.427778 0.31587&#xA;Ag 0.25 0.427778 0.31587&#xA;Ag 0.583333 0.427778 0.31587&#xA;Ag 0.916667 0.427778 0.31587&#xA;Ag 0.0277776 0.627778 0.31587&#xA;Ag 0.361111 0.627778 0.31587&#xA;Ag 0.694445 0.627778 0.31587&#xA;Ag 0.138889 0.627778 0.31587&#xA;Ag 0.472222 0.627778 0.31587&#xA;Ag 0.805556 0.627778 0.31587&#xA;Ag 0.25 0.627778 0.31587&#xA;Ag 0.583333 0.627778 0.31587&#xA;Ag 0.916667 0.627778 0.31587&#xA;Ag 0.0277776 0.827779 0.31587&#xA;Ag 0.361111 0.827779 0.31587&#xA;Ag 0.694445 0.827779 0.31587&#xA;Ag 0.138889 0.827779 0.31587&#xA;Ag 0.472222 0.827779 0.31587&#xA;Ag 0.805556 0.827779 0.31587&#xA;Ag 0.25 0.827779 0.31587&#xA;Ag 0.583333 0.827779 0.31587&#xA;Ag 0.916667 0.827779 0.31587&#xA;Ag 0.0833332 0.127777 0.374417&#xA;Ag 0.416667 0.127777 0.374417&#xA;Ag 0.75 0.127777 0.374417&#xA;Ag 0.194444 0.127777 0.374417&#xA;Ag 0.527778 0.127777 0.374417&#xA;Ag 0.861111 0.127777 0.374417&#xA;Ag 0.305555 0.127777 0.374417&#xA;Ag 0.638889 0.127777 0.374417&#xA;Ag 0.972222 0.127777 0.374417&#xA;Ag 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0.374417&#xA;Ag 0.194444 0.927779 0.374417&#xA;Ag 0.527778 0.927779 0.374417&#xA;Ag 0.861111 0.927779 0.374417&#xA;Ag 0.305555 0.927779 0.374417&#xA;Ag 0.638889 0.927779 0.374417&#xA;Ag 0.972222 0.927779 0.374417&#xA;Ag 0.0277776 0.0277763 0.432965&#xA;Ag 0.361111 0.0277763 0.432965&#xA;Ag 0.694445 0.0277763 0.432965&#xA;Ag 0.138889 0.0277763 0.432965&#xA;Ag 0.472222 0.0277763 0.432965&#xA;Ag 0.805556 0.0277763 0.432965&#xA;Ag 0.25 0.0277763 0.432965&#xA;Ag 0.583333 0.0277763 0.432965&#xA;Ag 0.916667 0.0277763 0.432965&#xA;Ag 0.0277776 0.227777 0.432965&#xA;Ag 0.361111 0.227777 0.432965&#xA;Ag 0.694445 0.227777 0.432965&#xA;Ag 0.138889 0.227777 0.432965&#xA;Ag 0.472222 0.227777 0.432965&#xA;Ag 0.805556 0.227777 0.432965&#xA;Ag 0.25 0.227777 0.432965&#xA;Ag 0.583333 0.227777 0.432965&#xA;Ag 0.916667 0.227777 0.432965&#xA;Ag 0.0277776 0.427778 0.432965&#xA;Ag 0.361111 0.427778 0.432965&#xA;Ag 0.694445 0.427778 0.432965&#xA;Ag 0.138889 0.427778 0.432965&#xA;Ag 0.472222 0.427778 0.432965&#xA;Ag 0.805556 0.427778 0.432965&#xA;Ag 0.25 0.427778 0.432965&#xA;Ag 0.583333 0.427778 0.432965&#xA;Ag 0.916667 0.427778 0.432965&#xA;Ag 0.0277776 0.627778 0.432965&#xA;Ag 0.361111 0.627778 0.432965&#xA;Ag 0.694445 0.627778 0.432965&#xA;Ag 0.138889 0.627778 0.432965&#xA;Ag 0.472222 0.627778 0.432965&#xA;Ag 0.805556 0.627778 0.432965&#xA;Ag 0.25 0.627778 0.432965&#xA;Ag 0.583333 0.627778 0.432965&#xA;Ag 0.916667 0.627778 0.432965&#xA;Ag 0.0277776 0.827779 0.432965&#xA;Ag 0.361111 0.827779 0.432965&#xA;Ag 0.694445 0.827779 0.432965&#xA;Ag 0.138889 0.827779 0.432965&#xA;Ag 0.472222 0.827779 0.432965&#xA;Ag 0.805556 0.827779 0.432965&#xA;Ag 0.25 0.827779 0.432965&#xA;Ag 0.583333 0.827779 0.432965&#xA;Ag 0.916667 0.827779 0.432965&#xA;Au 0.0277776 0.138888 0.549167&#xA;Au 0.361111 0.138888 0.549167&#xA;Au 0.694445 0.138888 0.549167&#xA;Au 0.138889 0.138888 0.549167&#xA;Au 0.472222 0.138888 0.549167&#xA;Au 0.805556 0.138888 0.549167&#xA;Au 0.25 0.138888 0.549167&#xA;Au 0.583333 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0.549167&#xA;Au 0.361111 0.805557 0.549167&#xA;Au 0.694445 0.805557 0.549167&#xA;Au 0.138889 0.805557 0.549167&#xA;Au 0.472222 0.805557 0.549167&#xA;Au 0.805556 0.805557 0.549167&#xA;Au 0.25 0.805557 0.549167&#xA;Au 0.583333 0.805557 0.549167&#xA;Au 0.916667 0.805557 0.549167&#xA;Au 0.0833332 0.972224 0.549167&#xA;Au 0.416667 0.972224 0.549167&#xA;Au 0.75 0.972224 0.549167&#xA;Au 0.194444 0.972224 0.549167&#xA;Au 0.527778 0.972224 0.549167&#xA;Au 0.861111 0.972224 0.549167&#xA;Au 0.305555 0.972224 0.549167&#xA;Au 0.638889 0.972224 0.549167&#xA;Au 0.972222 0.972224 0.549167&#xA;Au 0.0833332 0.083332 0.616649&#xA;Au 0.416667 0.083332 0.616649&#xA;Au 0.75 0.083332 0.616649&#xA;Au 0.194444 0.083332 0.616649&#xA;Au 0.527778 0.083332 0.616649&#xA;Au 0.861111 0.083332 0.616649&#xA;Au 0.305555 0.083332 0.616649&#xA;Au 0.638889 0.083332 0.616649&#xA;Au 0.972222 0.083332 0.616649&#xA;Au 0.0277776 0.249999 0.616649&#xA;Au 0.361111 0.249999 0.616649&#xA;Au 0.694445 0.249999 0.616649&#xA;Au 0.138889 0.249999 0.616649&#xA;Au 0.472222 0.249999 0.616649&#xA;Au 0.805556 0.249999 0.616649&#xA;Au 0.25 0.249999 0.616649&#xA;Au 0.583333 0.249999 0.616649&#xA;Au 0.916667 0.249999 0.616649&#xA;Au 0.0833332 0.416666 0.616649&#xA;Au 0.416667 0.416666 0.616649&#xA;Au 0.75 0.416666 0.616649&#xA;Au 0.194444 0.416666 0.616649&#xA;Au 0.527778 0.416666 0.616649&#xA;Au 0.861111 0.416666 0.616649&#xA;Au 0.305555 0.416666 0.616649&#xA;Au 0.638889 0.416666 0.616649&#xA;Au 0.972222 0.416666 0.616649&#xA;Au 0.0277776 0.583334 0.616649&#xA;Au 0.361111 0.583334 0.616649&#xA;Au 0.694445 0.583334 0.616649&#xA;Au 0.138889 0.583334 0.616649&#xA;Au 0.472222 0.583334 0.616649&#xA;Au 0.805556 0.583334 0.616649&#xA;Au 0.25 0.583334 0.616649&#xA;Au 0.583333 0.583334 0.616649&#xA;Au 0.916667 0.583334 0.616649&#xA;Au 0.0833332 0.750001 0.616649&#xA;Au 0.416667 0.750001 0.616649&#xA;Au 0.75 0.750001 0.616649&#xA;Au 0.194444 0.750001 0.616649&#xA;Au 0.527778 0.750001 0.616649&#xA;Au 0.861111 0.750001 0.616649&#xA;Au 0.305555 0.750001 0.616649&#xA;Au 0.638889 0.750001 0.616649&#xA;Au 0.972222 0.750001 0.616649&#xA;Au 0.0277776 0.916668 0.616649&#xA;Au 0.361111 0.916668 0.616649&#xA;Au 0.694445 0.916668 0.616649&#xA;Au 0.138889 0.916668 0.616649&#xA;Au 0.472222 0.916668 0.616649&#xA;Au 0.805556 0.916668 0.616649&#xA;Au 0.25 0.916668 0.616649&#xA;Au 0.583333 0.916668 0.616649&#xA;Au 0.916667 0.916668 0.616649&#xA;Au 0.0277776 0.0277763 0.68413&#xA;Au 0.361111 0.0277763 0.68413&#xA;Au 0.694445 0.0277763 0.68413&#xA;Au 0.138889 0.0277763 0.68413&#xA;Au 0.472222 0.0277763 0.68413&#xA;Au 0.805556 0.0277763 0.68413&#xA;Au 0.25 0.0277763 0.68413&#xA;Au 0.583333 0.0277763 0.68413&#xA;Au 0.916667 0.0277763 0.68413&#xA;Au 0.0833332 0.194443 0.68413&#xA;Au 0.416667 0.194443 0.68413&#xA;Au 0.75 0.194443 0.68413&#xA;Au 0.194444 0.194443 0.68413&#xA;Au 0.527778 0.194443 0.68413&#xA;Au 0.861111 0.194443 0.68413&#xA;Au 0.305555 0.194443 0.68413&#xA;Au 0.638889 0.194443 0.68413&#xA;Au 0.972222 0.194443 0.68413&#xA;Au 0.0277776 0.361111 0.68413&#xA;Au 0.361111 0.361111 0.68413&#xA;Au 0.694445 0.361111 0.68413&#xA;Au 0.138889 0.361111 0.68413&#xA;Au 0.472222 0.361111 0.68413&#xA;Au 0.805556 0.361111 0.68413&#xA;Au 0.25 0.361111 0.68413&#xA;Au 0.583333 0.361111 0.68413&#xA;Au 0.916667 0.361111 0.68413&#xA;Au 0.0833332 0.527778 0.68413&#xA;Au 0.416667 0.527778 0.68413&#xA;Au 0.75 0.527778 0.68413&#xA;Au 0.194444 0.527778 0.68413&#xA;Au 0.527778 0.527778 0.68413&#xA;Au 0.861111 0.527778 0.68413&#xA;Au 0.305555 0.527778 0.68413&#xA;Au 0.638889 0.527778 0.68413&#xA;Au 0.972222 0.527778 0.68413&#xA;Au 0.0277776 0.694445 0.68413&#xA;Au 0.361111 0.694445 0.68413&#xA;Au 0.694445 0.694445 0.68413&#xA;Au 0.138889 0.694445 0.68413&#xA;Au 0.472222 0.694445 0.68413&#xA;Au 0.805556 0.694445 0.68413&#xA;Au 0.25 0.694445 0.68413&#xA;Au 0.583333 0.694445 0.68413&#xA;Au 0.916667 0.694445 0.68413&#xA;Au 0.0833332 0.861112 0.68413&#xA;Au 0.416667 0.861112 0.68413&#xA;Au 0.75 0.861112 0.68413&#xA;Au 0.194444 0.861112 0.68413&#xA;Au 0.527778 0.861112 0.68413&#xA;Au 0.861111 0.861112 0.68413&#xA;Au 0.305555 0.861112 0.68413&#xA;Au 0.638889 0.861112 0.68413&#xA;Au 0.972222 0.861112 0.68413&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-14T12:37:18.207" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1512" PostTypeId="1" CreationDate="2020-07-14T18:34:29.840" Score="19" ViewCount="315" Body="&lt;p&gt;Does anybody know about an accurate quadrature rule over &lt;em&gt;three&lt;/em&gt; Euler angles &lt;span class=&quot;math-container&quot;&gt;$\theta, \phi, \chi$&lt;/span&gt;?&#xA;I am trying to calculate the average value of an arbitrary function &lt;span class=&quot;math-container&quot;&gt;$f(\theta, \phi, \chi)$&lt;/span&gt; for a given probability distribution &lt;span class=&quot;math-container&quot;&gt;$\rho(\theta, \phi, \chi)$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle f\rangle_{\rho} = \int_0^{2\pi} d\chi \int_0^{2\pi} d\phi\int_0^{\pi} \sin\theta d\theta f(\theta, \phi, \chi)\rho(\theta, \phi, \chi) \approx \sum_{l} w_l g(\theta_l, \phi_l, \chi_l)&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f(\theta, \phi, \chi)$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt;  sum-of-products of single angle-coordinate functions. &lt;span class=&quot;math-container&quot;&gt;$w_l$&lt;/span&gt; are quadrature weights and &lt;span class=&quot;math-container&quot;&gt;$(\theta_l, \phi_l, \chi_l)$&lt;/span&gt; represents a single grid point. &lt;span class=&quot;math-container&quot;&gt;$g(\theta, \phi, \chi) =  \sin\theta f(\theta, \phi, \chi)\rho(\theta, \phi, \chi)$&lt;/span&gt; and an appropriate quadrature weight-function is implicitly included in &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Such an integration is sometimes needed in orientation averaged calculations of material/molecule's properties.&lt;/p&gt;&#xA;&lt;p&gt;What we can assume about &lt;span class=&quot;math-container&quot;&gt;$\rho(\theta, \phi, \chi)$&lt;/span&gt; is that it is a linear combination of the products of the Wigner D-matrices: &lt;span class=&quot;math-container&quot;&gt;$\rho(\theta, \phi, \chi) = \sum_{K,K'} c_{KK'} D^{(J)}_{KM}(\theta, \phi, \chi)D^{(J')}_{K'M'}(\theta, \phi, \chi)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So to sum up. It seems there is a need for a simple quadrature scheme for integration over three Euler angles: &lt;span class=&quot;math-container&quot;&gt;$\theta, \phi, \chi$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Update:&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ways around the need for explicit three-Euler angle &lt;span class=&quot;math-container&quot;&gt;$\theta, \phi, \chi$&lt;/span&gt; quadrature:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Expanding &lt;span class=&quot;math-container&quot;&gt;$f(\theta, \phi, \chi)$&lt;/span&gt; in the Wigner matrices basis is one way of proceeding here. The appropriate integrals can be calculated analytically. But for some functions &lt;span class=&quot;math-container&quot;&gt;$f(\theta, \phi, \chi)$&lt;/span&gt; this method is very inefficient, as the Wigner expansion has many terms.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Another possibility, if we are dealing with a quantum system, is to solve the Schroedinger equation for wavefunctions in three separate system-fixed embeddings of the coordinate frame. Then one can choose the system-fixed z-axis to be the axis in the system that we want to quantify (average over). In such a case only &lt;span class=&quot;math-container&quot;&gt;$\theta, \phi$&lt;/span&gt; are needed.&#xA;&lt;em&gt;The down-side&lt;/em&gt; to this approach is that one needs to repeat calculations for three independent embeddings, which for some embeddings and some external potentials can be very unnatural. In the case of rotational dynamics problems the complete symmetric-top basis sets guarantee accuracy of the solutions regardless of the embedding chosen. Rotational wavefunction representations among different embeddings differ only by the coefficients. In good embeddings the rotational wavefunction can be reprsented compactly in the basis, but if the embedding is poor, often many basis functions are needed. In the case of problems which add coupling of rotational degrees of freedom to some other internal or external degrees of freedom, the choice of embedding is often critical for quick convergence of the variational procedure.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="99" LastEditorUserId="5" LastEditDate="2020-10-22T23:21:24.747" LastActivityDate="2020-11-11T09:49:45.983" Title="Quadrature over three Euler Angles for orientation averaging" Tags="|molecular-dynamics|mathematical-modeling|quantum-dynamics|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1513" PostTypeId="1" AcceptedAnswerId="2104" CreationDate="2020-07-14T19:21:40.753" Score="32" ViewCount="3817" Body="&lt;p&gt;Similar to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/5&quot;&gt;What are the types of charge analysis?&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/901/5&quot;&gt;What are the types of bond orders?&lt;/a&gt;, and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/392/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;, I would like to ask: What are the different variations/flavors of DFT (density functional theory)?&lt;/p&gt;&#xA;&lt;p&gt;I ask users to stick to one of the following, and explain it &lt;em&gt;compactly&lt;/em&gt; as I did &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;DFTB: Density functional tight binding&lt;/li&gt;&#xA;&lt;li&gt;DFPT: Density functional perturbation theory [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2167/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;SCC-DFTB: Self Consistent Charge DFTB&lt;/li&gt;&#xA;&lt;li&gt;TD-DFT: time-dependent DFT&lt;/li&gt;&#xA;&lt;li&gt;TD-DFRT: time-dependent density functional response theory [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1284/5&quot;&gt;link to answer there&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;BS-DFT: Broken-symmetry DFT&lt;/li&gt;&#xA;&lt;li&gt;MDFT: Molecular DFT&lt;/li&gt;&#xA;&lt;li&gt;MDFT-dev&lt;/li&gt;&#xA;&lt;li&gt;DFT-D(EFP)&lt;/li&gt;&#xA;&lt;li&gt;BDFT: Magnetic field DFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1468/5&quot;&gt;link to answer there&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;CDFT: Current DFT&lt;/li&gt;&#xA;&lt;li&gt;KS-DFT: Kohn-Sham DFT&lt;/li&gt;&#xA;&lt;li&gt;OF-DFT: orbital-free DFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1518/5&quot;&gt;link to answer here&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;TAO-DFT: Thermally-Assisted-Occupation DFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9108/5410&quot;&gt;link to answer there&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;DC-DFT: Density-corrected DFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1260/5&quot;&gt;link to answer there&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Constrained DFT&lt;/li&gt;&#xA;&lt;li&gt;Conceptual DFT&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.0c00208&quot; rel=&quot;nofollow noreferrer&quot;&gt;vMSDFT&lt;/a&gt; (variational multi-state DFT)&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;ab initio&lt;/em&gt; DFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1212/5&quot;&gt;link to answer there&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;MCPDFT (Multiconfigurational Pair Density Functional Theory)&lt;/li&gt;&#xA;&lt;li&gt;SCDFT (Superconducting DFT) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1828/5&quot;&gt;link to answer here&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;RT-TDDFT [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2104/5&quot;&gt;link to answer here&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;RT-TDDFPT&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.473129&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mesoscopic DFT&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;NEGF+DFT&lt;/li&gt;&#xA;&lt;li&gt;Reduced Density Matrix Functional Theory (RDMFT)&lt;/li&gt;&#xA;&lt;li&gt;Density Matrix Embedding Theory (DMET)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="579" LastEditDate="2022-05-28T03:28:28.000" LastActivityDate="2022-05-28T03:28:28.000" Title="What are the types of DFT?" Tags="|density-functional-theory|one-topic-per-answer|td-dft|terminology|density-functional-tight-binding|" AnswerCount="6" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1514" PostTypeId="2" ParentId="1513" CreationDate="2020-07-14T20:11:57.723" Score="20" Body="&lt;h3&gt;CDFT: Current DFT&lt;/h3&gt;&#xA;&lt;p&gt;Current DFT is defined via the generalized Hohenberg-Kohn theorem (HKT), which extends the traditional HKT to account for the effect of magnetic fields. The generalized HKT says that the scalar potential &lt;span class=&quot;math-container&quot;&gt;$\mathbf{V}$&lt;/span&gt;, the (nondegenerate) ground state wavefunction &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;, and the &lt;em&gt;vector potential&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{A}$&lt;/span&gt; are uniquely determined by the ground state density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and the &lt;em&gt;paramagnetic current density&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$j_p$&lt;/span&gt;. From [1], the physical and paramagnetic current densities are related by &lt;span class=&quot;math-container&quot;&gt;$$j=j_p+\frac{e}{mc}n\mathbf{A}$$&lt;/span&gt; Note, the total/physical current density is not used, as the factor involving the vector potential leads to gauge dependence and thus wouldn't &lt;em&gt;uniquely&lt;/em&gt; determine the ground state.&lt;/p&gt;&#xA;&lt;p&gt;Similar to standard DFT, this results in a variational principle, where the true &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j_p$&lt;/span&gt; minimize a functional for the ground state energy. This can in turn be shown to be equivalent to solving a set of one-electron equations, e.g. Kohn-Sham CDFT. One of main challenges in the development of this area is formulating new functionals that incorporate &lt;span class=&quot;math-container&quot;&gt;$j_p$&lt;/span&gt; into the exchange-correlation functional while maintaining gauge invariance.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;G. Vignale and Mark Rasolt &amp;quot;Current- and spin-density-functional theory for inhomogeneous electronic systems in strong magnetic fields&amp;quot; Phys. Rev. B 37, 10685 DOI: 10.1103/PhysRevB.37.10685&lt;/li&gt;&#xA;&lt;li&gt;James W. Furness, et al &amp;quot;Current Density Functional Theory Using Meta-Generalized Gradient Exchange-Correlation Functionals&amp;quot; J. Chem. Theory Comput. 2015, 11, 4169−4181 DOI: 10.1021/acs.jctc.5b00535&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-08-27T14:46:15.567" LastActivityDate="2020-08-27T14:46:15.567" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1515" PostTypeId="1" AcceptedAnswerId="1516" CreationDate="2020-07-15T01:03:25.913" Score="43" ViewCount="6565" Body="&lt;p&gt;For a matter modelling person, the most valuable resource is computing power. For many of us, computing power at hand limits the scale of problems we can solve. There are many national supercomputing facilities for academics. What are the resources available in each country?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-09-08T17:37:52.907" LastActivityDate="2020-12-28T07:39:49.870" Title="Supercomputers around the world" Tags="|high-performance-computing|one-topic-per-answer|" AnswerCount="14" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1516" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T02:50:21.390" Score="24" Body="&lt;h1&gt;Canada: Compute Canada&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Before Compute Canada (Antiquity)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Supercomputing in Canada began with several disparate  groups:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;1997&lt;/strong&gt;: MACI (Multimedia Advanced Comp. Infrastructure) is formed from  Alberta universities.&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;2001&lt;/strong&gt;: &lt;a href=&quot;https://www.westgrid.ca/about_westgrid/history&quot; rel=&quot;nofollow noreferrer&quot;&gt;WestGrid&lt;/a&gt; is formed by 7 Alberta and BC institutions (facilities launched in 2003).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;1998&lt;/strong&gt;: &lt;a href=&quot;https://en.wikipedia.org/wiki/High_Performance_Computing_Virtual_Laboratory&quot; rel=&quot;nofollow noreferrer&quot;&gt;HPCVL&lt;/a&gt; is formed by institutions in Toronto and eastern Ontario.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2000&lt;/strong&gt;: &lt;a href=&quot;https://web.archive.org/web/20001204153800/http://www.rqchp.qc.ca:80/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RQCHP&lt;/a&gt; is formed in Quebec. Little information is available about it (see the URL link).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2001&lt;/strong&gt;: &lt;a href=&quot;https://www.sharcnet.ca/my/about/history&quot; rel=&quot;nofollow noreferrer&quot;&gt;SHARCNET&lt;/a&gt; is formed by 7 Ontario universities, by 2019 it has 19 institutions.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2001&lt;/strong&gt;: &lt;a href=&quot;http://www.clumeq.ca/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CLUMEQ&lt;/a&gt; is formed with some institutions in Quebec (facilities launched in 2002).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2003&lt;/strong&gt;: &lt;a href=&quot;https://www.ace-net.ca/who-we-are/acenet/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACENET&lt;/a&gt; is formed with institutions in Atlantic (Far-Eastern) Canada.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2004&lt;/strong&gt;: &lt;a href=&quot;https://www.scinethpc.ca/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SciNet&lt;/a&gt; is formed with University of Toronto &amp;amp; some Ontario hospitals (facilities in 2009).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also in &lt;strong&gt;2003&lt;/strong&gt;: high-speed optical link was made between WestGrid &amp;amp; SHARCNET (West and East).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Amalgamation into Compute Canada (CC)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;2006&lt;/strong&gt;: WestGrid, HPCVL, SciNet, SHARCNET, CLUMEQ, RQCHP &amp;amp; ACEnet formed CC.&#xA;&lt;ul&gt;&#xA;&lt;li&gt;\$60 million from CFI's National Platforms Fund and \$2 million/year from NSERC.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2011:&lt;/strong&gt; Everything is split into just 4 regions: West, Ontario, Quebec, East:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;HPCVL, SciNet &amp;amp; SHARCNET form Compute Ontario (just a name, they're autonomous).&lt;/li&gt;&#xA;&lt;li&gt;CLUMEQ &amp;amp; RQCHP form Calcul Quebec.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;2012&lt;/strong&gt;:  CC is incorporated as a non-profit, and received $30 million more from CFI.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2016&lt;/strong&gt;: CC starts deploying supercomputers (HPC existed before but through the sub-groups).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Throughout this time SHARCNET, and the others continue expanding to include more universities, colleges, and research institutions. ComputeOntario adds HPC4Health. Sub-groups of CC grow.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;HPC facilities offered&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You would have to ask a separate question to go into detail about all the systems that are offered by virtue of the fact that CC is an amalgamation of several pre-existing consortia. The following is what was made available after the formation of CC:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://docs.computecanada.ca/wiki/Cedar&quot; rel=&quot;nofollow noreferrer&quot;&gt;2017: Cedar&lt;/a&gt; (Vancouver, BC)&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Enetered Top500 &lt;a href=&quot;https://www.top500.org/system/179113/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ranked #87&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;94,528 CPU cores, 2502 nodes.&lt;/li&gt;&#xA;&lt;li&gt;1532 GPUs.&lt;/li&gt;&#xA;&lt;li&gt;504T of RAM (for CPUs alone).&lt;/li&gt;&#xA;&lt;li&gt;2.2P of node-local SSD space.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/home&lt;/code&gt; 250TB total.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/scratch&lt;/code&gt; 3.7PB total (LUSTRE).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/project&lt;/code&gt; 10PB total.&lt;/li&gt;&#xA;&lt;li&gt;Double-precision: 936 TFLOPS for CPUs, 2.744 PFLOPS for GPUs, 3.6 PFLOPS total.&lt;/li&gt;&#xA;&lt;li&gt;CPU: Broadwell E5-2683/E7-4809/E5-2650, some SkyLake &amp;amp; CascadeLake added later.&lt;/li&gt;&#xA;&lt;li&gt;GPU: Originally Pascal P100 w/ 12G or 16G HBM2 RAM but 32G Volta V100 added later.&lt;/li&gt;&#xA;&lt;li&gt;Interconnect: OmniPath (v1) at 100Gbit/s bandwidth.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://docs.computecanada.ca/wiki/Graham&quot; rel=&quot;nofollow noreferrer&quot;&gt;2017: Graham&lt;/a&gt; (Waterloo, Ontario)&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Enetered Top500  &lt;a href=&quot;https://www.top500.org/system/179047/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ranked #96&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;41,548 CPU cores, 1185 nodes.&lt;/li&gt;&#xA;&lt;li&gt;520 GPUs&lt;/li&gt;&#xA;&lt;li&gt;128T of RAM (for CPUs alone).&lt;/li&gt;&#xA;&lt;li&gt;1.5P of node-local SSD space.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/home&lt;/code&gt; 64 TB total.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/scratch&lt;/code&gt; 3.6PB total (LUSTRE).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/project&lt;/code&gt; 16 PB total.&lt;/li&gt;&#xA;&lt;li&gt;Double-precision: Unknown.&lt;/li&gt;&#xA;&lt;li&gt;CPU: Broadwell {E5-2683, E7-4850} v4, some SkyLake &amp;amp; CascadeLake added later.&lt;/li&gt;&#xA;&lt;li&gt;GPU: Pascal P100 w/ 12G HBM2 RAM but 16G Volta V100 &amp;amp; Turing T4 added later.&lt;/li&gt;&#xA;&lt;li&gt;Interconnect: Mellanox FDR 56Gb/s (GPU &amp;amp; cloud), EDR 100Gb/s InfiniBand (rest).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-28T07:39:49.870" LastActivityDate="2020-12-28T07:39:49.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1517" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T07:47:37.037" Score="20" Body="&lt;h1&gt;USA: Facilities funded by NSF&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;XSEDE (Extreme Science and Engineering Discovery Environment)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;XSEDE (pronounced like &amp;quot;exceed&amp;quot;) provides access to both computational resources and trainings on HPC. These may be especially useful if your institution does not provide good support for scientific computing.&lt;/p&gt;&#xA;&lt;p&gt;From their &lt;a href=&quot;https://www.xsede.org/web/site/for-users/getting-started&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;XSEDE provides live and recorded training on a wide range of research computing topics.&lt;/li&gt;&#xA;&lt;li&gt;XSEDE programs offer our users in-depth collaborations and on-campus facilitators.&lt;/li&gt;&#xA;&lt;li&gt;Most US-based researchers are eligible for no-cost XSEDE allocations. Get started in two weeks or less!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-07-20T03:19:08.597" LastActivityDate="2020-07-20T03:19:08.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1518" PostTypeId="2" ParentId="1513" CreationDate="2020-07-15T11:34:42.243" Score="19" Body="&lt;h3&gt;OF-DFT: Orbital-free density functional theory&lt;/h3&gt;&#xA;&lt;p&gt;Hohenberg and Kohn established that the ground state energy, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, of interacting electrons in a potential, &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt;, is a functional of the electron density, &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;E[n] = F[n] + \int \mathrm{d}\mathbf{r} \, v(\mathbf{r}) n(\mathbf{r}) .&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;While this statement is formally true, we do yet not have a convenient way to compute the &amp;quot;universal functional&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$F[n]$&lt;/span&gt; exactly for most cases. To carry out OF-DFT, one chooses an explicit form for &lt;span class=&quot;math-container&quot;&gt;$F[n]$&lt;/span&gt;, likely an approximation, and varies the electron density to find the particular &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; that minimizes &lt;span class=&quot;math-container&quot;&gt;$E[n]$&lt;/span&gt;, yielding the ground state. Quantities like forces and stresses then follow from Hellmann–Feynman-type formulas.&lt;/p&gt;&#xA;&lt;p&gt;Both the advantages and challenges of OF-DFT stem from its simplicity; wave functions and density matrices are eschewed altogether. For cases when OF-DFT is suitably accurate, it is extremely attractive from a computational standpoint, in significant part because &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;, the sole working variable, grows only linearly with system size. However, for much of the periodic table, OF-DFT remains less accurate than other electronic structure methods.&lt;/p&gt;&#xA;&lt;p&gt;Modern implementations of OF-DFT often build on the insights of Kohn and Sham, who considered &lt;span class=&quot;math-container&quot;&gt;$F[n]$&lt;/span&gt; in the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;F[n] = T_s[n] + E_{Hxc}[n] ,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$T_s[n]$&lt;/span&gt; is the kinetic energy of an auxiliary system of noninteracting electrons (with the same electron density as the interacting system) and &lt;span class=&quot;math-container&quot;&gt;$E_{Hxc}[n]$&lt;/span&gt; subsumes electrostatic, exchange, and correlation contributions. The full Kohn-Sham scheme determines &lt;span class=&quot;math-container&quot;&gt;$T_s[n]$&lt;/span&gt; implicitly, but exactly, following the introduction of single-electron orbitals. The corresponding orbital-free approach, in contrast, approximates &lt;span class=&quot;math-container&quot;&gt;$T_s[n]$&lt;/span&gt; with an explicit density functional, while utilizing the same approximations for &lt;span class=&quot;math-container&quot;&gt;$E_{Hxc}[n]$&lt;/span&gt;. Simple approximations to &lt;span class=&quot;math-container&quot;&gt;$T_s[n]$&lt;/span&gt; include the Thomas-Fermi functional,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{3}&#xA;T_{TF}[n] = \frac{3}{10}(3\pi^2)^{2/3}\int \mathrm{d}\mathbf{r} \, n^{5/3}(\mathbf{r}) ,&#xA;$$&lt;/span&gt;&#xA;and the Weizsäcker functional,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;T_W[n]&#xA;&amp;amp; = -\frac{1}{2} \int \mathrm{d}\mathbf{r} \, n^{1/2}(\mathbf{r}) \nabla^2 n^{1/2}(\mathbf{r}) \tag{4}\\ &#xA;&amp;amp; = \int \mathrm{d}\mathbf{r} \, \left[ \frac{1}{8} \frac{|\nabla n(\mathbf{r})|^2}{n(\mathbf{r})} - \frac{1}{4} \nabla^2 n(\mathbf{r}) \right],\tag{5}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;both of which are exact for certain limiting cases and predate the Hohenberg-Kohn theorems by decades.&lt;/p&gt;&#xA;&lt;p&gt;For more (disclaimer: from my perspective), here is a recent review of successful OF-DFT applications in materials science:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;W.C. Witt, B.G. del Rio, J.M. Dieterich, and E.A. Carter, &lt;em&gt;Orbital-free density functional theory for materials research&lt;/em&gt;, Journal of Materials Research 33 (2018) (DOI: &lt;a href=&quot;http://dx.doi.org/10.1557/jmr.2017.462&quot; rel=&quot;noreferrer&quot;&gt;10.1557/jmr.2017.462&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="5" LastEditDate="2020-08-27T14:46:06.763" LastActivityDate="2020-08-27T14:46:06.763" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1519" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T11:48:09.887" Score="15" Body="&lt;h1&gt;Brazil: CENAPADs&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;CENAPAD stands for &lt;em&gt;&lt;strong&gt;Ce&lt;/strong&gt;ntro &lt;strong&gt;Na&lt;/strong&gt;cional de &lt;strong&gt;P&lt;/strong&gt;rocessamento de &lt;strong&gt;A&lt;/strong&gt;lto &lt;strong&gt;D&lt;/strong&gt;esempenho&lt;/em&gt; (National High Performance Processing Center). They form a supercomputing network instituted by the Ministry of Science, Technology and Innovation (MCTI) and coordinated by the National High Performance Processing System (&lt;a href=&quot;https://www.lncc.br/sinapad/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SINAPAD&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Some of them are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.cenapad.unicamp.br/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CENAPAD-SP&lt;/a&gt;: it is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Campinas&quot; rel=&quot;nofollow noreferrer&quot;&gt;Campinas&lt;/a&gt; city in &lt;a href=&quot;https://en.wikipedia.org/wiki/S%C3%A3o_Paulo_(state)&quot; rel=&quot;nofollow noreferrer&quot;&gt;São Paulo&lt;/a&gt; state,  linked to the Research Office of &lt;a href=&quot;https://www.unicamp.br/unicamp/&quot; rel=&quot;nofollow noreferrer&quot;&gt;UNICAMP&lt;/a&gt; (State University of Campinas, the third best Latin American university).&#xA;Hardware: The IBM Power 750 Express system is made up of 40 IBM P750 SMP computational nodes, using 3.55GHz Power7 processors. There are 32 colors (processing cores), 128GB of RAM and 908.8 GFlops of theoretical performance in each computational node, totaling 1280 colors, 5TB of RAM, theoretical processing capacity of approximately 37 TFLOPs and sustained capacity (linpack) of 27 TFLOPs. An IBM iDataPlex / GPU device with twelve nVIDIA Tesla M2050 GPU cards, installed on six X86 servers with Intel Xeon Processor X5570 (2.93GHz) processors, is also available.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.lcc.ufmg.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CENAPAD-MG&lt;/a&gt;: it is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Belo_Horizonte&quot; rel=&quot;nofollow noreferrer&quot;&gt;Belo Horizonte&lt;/a&gt; city in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Minas_Gerais&quot; rel=&quot;nofollow noreferrer&quot;&gt;Minas Gerais&lt;/a&gt; state, linked to the Scientific Computing Division of the Scientific Computing Laboratory (LCCUFMG) at &lt;a href=&quot;http://www.ufmg.br&quot; rel=&quot;nofollow noreferrer&quot;&gt;Federal University of Minas Gerais (UFMG)&lt;/a&gt;. Hardware: It is characterized by a cluster of 53 computational nodes physically distributed in 4 racks, each node with 2 quadcore processors and 16 Gigabytes of main memory, adding a total of 848 processing cores (colors) and approximately 1.7 Terabytes of memory distributed by the machine. The theoretical performance potential of the cluster translates into 9 Teraflops (nine trillion elementary operations per second). This equipment is served by an internal communication network of the type INFINIBAND that interconnects all nodes, and that is specially dedicated for parallel calculation, and by storage with a storage capacity of 45 TB for data and backup.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.cenapad-rj.lncc.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CENAPAD-RJ&lt;/a&gt;: it is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Petr%C3%B3polis&quot; rel=&quot;nofollow noreferrer&quot;&gt;Petrópolis&lt;/a&gt; (Imperial City) city in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rio_de_Janeiro_(state)&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rio de Janeiro&lt;/a&gt; state, linked to the &lt;a href=&quot;https://www.lncc.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;National Laboratory for Scientific Computing (LNCC)&lt;/a&gt;. Hardware: SunHPC: 72 nodes with 2 Intel(R) Xeon(R) CPU E5440 (8 cores) and 16GB RAM each. Altix-XE: 30 nodes with 2 Intel(R) Xeon(R) E5520 (8 cores) and 24GB RAM each; 6 nodes with 2 Xeon X6560 hexacore (12 cores), 98GB RAM and 2 NVIDIA TeslaS2050 (896 cores) each; 2 nodes Tyan FT72-B7015 with 2 Xeon X6560 hexacore (12 cores), 24GB RAM, 4 NVIDIA TeslaC2050 (1792 cores) each; 4 nodes SGI C1104G with 2 Intel Xeon 8-core E5-2660, 64GB RAM and 1 NVIDIA TeslaK20 each. Altix ICE8400: 25 nodes with 2 Xeon X6560 hexacore (12 cores) and 48GB RAM each.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://cenapad.ufc.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CENAPAD-UFC&lt;/a&gt;: it is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fortaleza&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fortaleza&lt;/a&gt; city in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Cear%C3%A1&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ceará&lt;/a&gt; state, linked to the Research Office of &lt;a href=&quot;http://www.ufc.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Federal University of Ceara (UFC)&lt;/a&gt;. Hardware: 48 nodes Bullx B500 with 2 Intel X5650 Hexa-Core 2,67 Ghz and 24GB RAM each (576 processing cores and 1,152 GB of RAM, reaching approximately 6.2 TFlops of processing) and 3 GPUs Bullx B515 with 2 NVIDIA K20m, 2 Intel E5-2470 Octa-Core 2,3GHz and 96GB RAM each (48 processing cores, 288GB of RAM and 15GB of GPU and can reach approximately 8Tflops of processing)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://cesup.ufrgs.br/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CESUP&lt;/a&gt;: it is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Porto_Alegre&quot; rel=&quot;nofollow noreferrer&quot;&gt;Porto Alegre&lt;/a&gt; city in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rio_Grande_do_Sul&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rio Grande do Sul&lt;/a&gt; state, linked to the &lt;a href=&quot;http://www.ufrgs.br/english/home&quot; rel=&quot;nofollow noreferrer&quot;&gt;Federal University of Rio Grande do Sul (UFRGS)&lt;/a&gt;. Hardware: 64 nodes with 2 AMD Opteron Twelve-Core (6176 SE and 6238) and 64 GB RAM, 6 nodes with 8 AMD Opteron 8356 Quad-core and 128 GB RAM, and 24 nodes with Intel Xeon Silver 4116 Twelve-Core and 96 GB RAM and 32 GPU.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Bellow is the distribution of SINAPAD related centers.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OcYql.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OcYql.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Just as a curiosity, the image below shows the CPU use by Brazilian states between 1995 and 2015.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uDk9C.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uDk9C.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-08-04T23:02:21.703" LastActivityDate="2020-08-04T23:02:21.703" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1520" PostTypeId="2" ParentId="1434" CreationDate="2020-07-15T12:06:45.007" Score="3" Body="&lt;p&gt;As the comments to your question suggest, there isn't a simple answer as there are many issues involved like system size, numerical tricks, hardware configuration, etc.&lt;/p&gt;&#xA;&lt;p&gt;There is an specific project that it is being developed at &lt;a href=&quot;https://www.nist.gov/&quot; rel=&quot;nofollow noreferrer&quot;&gt;National Institute of Standards and Technology (NIST)&lt;/a&gt; under the name of &lt;a href=&quot;https://www.nist.gov/programs-projects/dft-benchmarking&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT Benchmarking&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The major accomplishments of the project are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Investigation the convergence of important physical quantities like lattice constant and bulk modulus as afunction of k-points and smearing;&lt;/li&gt;&#xA;&lt;li&gt;Computation of lattice constant, elastic constants, and relative energies for single elements in various structures (fcc, bcc, hcp, sc, diam, ..) using various exchange-correlation functionals.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The project manager is Francesca Tavazza (francesca.tavazza @ nist.gov).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-15T12:06:45.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1521" PostTypeId="1" CreationDate="2020-07-15T13:50:56.610" Score="17" ViewCount="694" Body="&lt;p&gt;I would like to know what are the different types of pseudopotentials, the pro and cons, and what properties can/cannot be calculated with them?&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-21T00:00:26.270" LastActivityDate="2022-07-04T16:49:51.313" Title="What are the types of pseudopotentials?" Tags="|density-functional-theory|one-topic-per-answer|pseudopotentials|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1522" PostTypeId="2" ParentId="1453" CreationDate="2020-07-15T17:09:04.830" Score="5" Body="&lt;p&gt;You will have to run a new calculation to get the spin-spin constants. Gaussian computes the shielding tensor &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\sigma}$&lt;/span&gt; and spin-spin coupling constants &lt;span class=&quot;math-container&quot;&gt;$\mathbf{K}$&lt;/span&gt; using a linear response formalism. For these properties, which are both 2nd rank tensors/2nd derivatives of the energy, this means they are calculated by forming a perturbed density with respect to one parameter and contracting it with the other, unperturbed parameter.&lt;/p&gt;&#xA;&lt;p&gt;The shielding tensor component for an atom &lt;span class=&quot;math-container&quot;&gt;$\sigma_\ce{A}$&lt;/span&gt; is the second derivative of the energy with  respect to the dipole of &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{A}$&lt;/span&gt;, and the external magnetic field &lt;span class=&quot;math-container&quot;&gt;$\mathbf{B}^\text{ext}$&lt;/span&gt;. Gaussian by default forms the magnetic perturbed density to calculate this (and I haven't seen a way to change it). The spin-spin constant &lt;span class=&quot;math-container&quot;&gt;$K_\ce{AB}$&lt;/span&gt; is the second derivative of the energy with  respect to the dipole of &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{A}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\ce{B}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{B}$&lt;/span&gt;. Here is a &lt;a href=&quot;https://ja01.chem.buffalo.edu/downloads/review-structureandbonding.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Link explaining some of the theory&lt;/a&gt;. Since Gaussian didn't form the electric dipole perturbed density when calculating &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\sigma}$&lt;/span&gt;, the data from the previous calculation doesn't allow you to compute &lt;span class=&quot;math-container&quot;&gt;$\mathbf{K}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;You can at least avoid repeating the SCF&lt;/strong&gt; by including &lt;code&gt;guess=read&lt;/code&gt; and &lt;code&gt;%oldchk=old_chk_name.chk&lt;/code&gt; to get the result from the previous calculation, but there is no getting around repeating the CPHF portion of the calculation. In principle, Gaussian could be made to form the electric dipole perturbed density when calculating the shielding tensor and store the result in the chk, which should give you most of what you would need to later run a spin-spin calculation. However, &lt;strong&gt;I'm not aware of a way to store this with Gaussian's existing keywords/user interface.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-07-15T18:14:20.037" LastActivityDate="2020-07-15T18:14:20.037" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1523" PostTypeId="1" CreationDate="2020-07-15T19:33:53.033" Score="20" ViewCount="2053" Body="&lt;p&gt;I am new to the world of Molecular Dynamics, and am curious to know &lt;em&gt;exactly&lt;/em&gt; what is considered to be an &lt;em&gt;ab initio&lt;/em&gt; Molecular Dynamics (AIMD) method, and how do they work?&lt;/p&gt;&#xA;&lt;p&gt;The seminal work by Roberto Car and Michele Parrinello, titled &amp;quot;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.55.2471&quot; rel=&quot;noreferrer&quot;&gt;Unified Approach for Molecular Dynamics and Density-Functional Theory&lt;/a&gt;&amp;quot; was published 35 years ago!&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have recently come across the following &amp;quot;types&amp;quot; of MD methods while reading some research papers:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Born-Oppenheimer Molecular Dynamics&lt;/li&gt;&#xA;&lt;li&gt;Car-Parinello Molecular Dynamics &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1525/5&quot;&gt;[link to answer]&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;2nd generation CPMD&lt;/li&gt;&#xA;&lt;li&gt;Approximate Car-Parrinello-like Langevin Born-Oppenheimer Molecular Dynamics&lt;/li&gt;&#xA;&lt;li&gt;Many-body Molecular Dynamics&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.2008258?journalCode=jcp&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;ab initio&lt;/em&gt; Ehrenfest Dynamics&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/dev/documentation/ehrenfest/ehrenfest_theory.html&quot; rel=&quot;noreferrer&quot;&gt;TDDFT/MD&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If I am missing methods, which I am sure I am, please feel free to add them through an answer!&#xA;Also, it would be appreciated if &lt;em&gt;&lt;strong&gt;one&lt;/strong&gt;&lt;/em&gt; method is explained per answer, and is summarized in &lt;strong&gt;2-3 paragraphs&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-07-28T18:21:28.087" LastActivityDate="2020-08-03T20:41:18.680" Title="What are the types of ab initio Molecular Dynamics?" Tags="|molecular-dynamics|ab-initio-calculations|one-topic-per-answer|terminology|aimd|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1524" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T19:37:35.450" Score="17" Body="&lt;h1&gt;USA: Facilities funded by DOE&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;For USA, XSEDE was mentioned in [another answer](https://mattermodeling.stackexchange.com/a/1517/671). It is funded by the US National Science Foundation. There are also some facilities under Department of Energy (DOE) that might be more or less approachable depending on research profile and funding sources.&#xA;&lt;p&gt;&lt;strong&gt;NERSC (National Energy Research Scientific Computing Center)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nersc.gov&quot; rel=&quot;noreferrer&quot;&gt;NERSC&lt;/a&gt;, located at Lawrence Berkeley National Laboratory, is the primary computing facility for DOE. Currently its main HPC system is &lt;a href=&quot;https://docs.nersc.gov/systems/cori/&quot; rel=&quot;noreferrer&quot;&gt;Cori&lt;/a&gt;, a Cray XC40 at #16 on the Top500 list, but a new Cray system named &lt;a href=&quot;https://www.nersc.gov/systems/perlmutter/&quot; rel=&quot;noreferrer&quot;&gt;Perlmutter&lt;/a&gt; is supposed to be installed late 2020 through mid 2021. Both systems have (will have) both GPU-accelerated and pure CPU nodes. NERSC also provides a good amount of training opportunities for its users, some in cooperation with the leadership facilities mentioned below.&lt;/p&gt;&#xA;&lt;p&gt;From their &lt;a href=&quot;https://www.nersc.gov/about/nersc-mission/&quot; rel=&quot;noreferrer&quot;&gt;mission statement&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The mission of the National Energy Research Scientific Computing Center (NERSC) is to accelerate scientific discovery at the DOE Office of Science through high performance computing and data analysis.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;From their &lt;a href=&quot;https://www.nersc.gov/about/&quot; rel=&quot;noreferrer&quot;&gt;website:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;More than 7,000 scientists use NERSC to perform basic scientific research across a wide range of disciplines, including climate modeling, research into new materials, simulations of the early universe, analysis of data from high energy physics experiments, investigations of protein structure, and a host of other scientific endeavors.&lt;/p&gt;&#xA;&lt;p&gt;All research projects that are funded by the DOE Office of Science and require high performance computing support are eligible to apply to use NERSC resources. Projects that are not funded by the DOE Office of Science, but that conduct research that supports the Office of Science mission may also apply.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;DOE also has two so-called leadership computing facilities. The point of these is not to support typical, small-scale computational research. Instead, they deliberately target a limited number of large-scale projects in need of large allocations, projects that may not be possible elsewhere. From experience with OLCF there is often also a need to demonstrate that your code can take advantage of the hardware offered.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;OLCF (Oak Ridge Leadership Computing Facility)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.olcf.ornl.gov/&quot; rel=&quot;noreferrer&quot;&gt;Oak Ridge Leadership Computing Facility&lt;/a&gt; (formerly known as the National Leadership Computing Facility), located at Oak Ridge National Laboratory, is home to the Summit supercomputer that debuted as #1 on the Top500 list, but was &lt;a href=&quot;https://www.top500.org/lists/top500/2020/06/&quot; rel=&quot;noreferrer&quot;&gt;recently dethroned&lt;/a&gt; to #2. It's next supercomputer, &lt;a href=&quot;https://www.olcf.ornl.gov/frontier/&quot; rel=&quot;noreferrer&quot;&gt;Frontier&lt;/a&gt;, is supposed to reach exascale performance, and open to users in 2022.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;ALCF (Argonne Leadership Computing Facility)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.alcf.anl.gov/&quot; rel=&quot;noreferrer&quot;&gt;Argonne Leadership Computing Facility&lt;/a&gt; (at Argonne National Laboratory) has a similar role. Currently, its main supercomputer is &lt;a href=&quot;https://www.alcf.anl.gov/alcf-resources/theta&quot; rel=&quot;noreferrer&quot;&gt;Theta&lt;/a&gt; (#34 on the Top500 list). Their planned exascale supercomputer &lt;a href=&quot;https://alcf.anl.gov/aurora&quot; rel=&quot;noreferrer&quot;&gt;Aurora&lt;/a&gt; is coming in 2021.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="5" LastEditDate="2020-07-19T02:02:33.730" LastActivityDate="2020-07-19T02:02:33.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1525" PostTypeId="2" ParentId="1523" CreationDate="2020-07-15T20:14:55.557" Score="11" Body="&lt;h2&gt;CPMD: Car-Parrinello Molecular Dynamics&lt;/h2&gt;&#xA;&lt;p&gt;An approximation of BOMD (Born-Oppenheimer MD) where &lt;em&gt;fictitious dynamics&lt;/em&gt; is used on the electrons to keep them close to their ground state, so that we do not have to keep solving for their ground state at every single step. We start with Newton's 2nd law (as does classical MD), but instead of the force being calculated by a full-fledged &lt;em&gt;ab initio&lt;/em&gt; calculation at every step, the force itself has an EOM (equation of motion) which below is given by Eq. \eqref{eq:fictitious}. For one nucleus with position &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt; and several electrons with orbitals &lt;span class=&quot;math-container&quot;&gt;$\{\psi_i\}$&lt;/span&gt; we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{1}&#xA;\vec{F} &amp;amp;= m\vec{\ddot{r}} \\&#xA;- \nabla \, E\left[\{ \psi_i \} , \vec{r} \right] &amp;amp;= m\vec{\ddot{r}}\tag{2}\\&#xA;\mu \ddot{\psi}_i(\vec{r},t) &amp;amp;= - \frac{\delta E}{\delta \psi_i^*(\vec{r},t)} + \sum_j \Lambda_{ij} \psi_j(\vec{r},t),\tag{3}\label{eq:fictitious}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Lambda_{ij}$&lt;/span&gt; is a matrix of Lagrange multipliers to allow satisfaction of the constraint that the wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt; must be orthogonal; and &lt;span class=&quot;math-container&quot;&gt;$E[\{\psi_i\},\vec{r}]$&lt;/span&gt; is an energy functional (usually a Kohn–Sham energy one). For several nucleii, just make a new subscript for &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt; and change the functional to &lt;span class=&quot;math-container&quot;&gt;$E[\{\psi_i\},\{\vec{r_I}\}]$&lt;/span&gt;, then the equations are exactly the same.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implemented in:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.cpmd.org/wordpress/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CPMD&lt;/a&gt;: Literally named after the method! (open-source)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.cp2k.org/about&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K&lt;/a&gt;: Might also be named after the method! (open-source)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.nwchem-sw.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NWChem&lt;/a&gt; (open-source)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2020-07-27T17:51:38.187" LastActivityDate="2020-07-27T17:51:38.187" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1526" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T20:32:10.520" Score="14" Body="&lt;h1&gt;MÉXICO&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;Mexico has several supercomputing centers that provide service to the nation's academic researchers. These are the main ones (not in any particular order). &lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;&lt;strong&gt;Kan Balam (2007): Universidad Nacional Autónoma de México (UNAM)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;by Hewlett-Packard&lt;/li&gt;&#xA;&lt;li&gt;1,368 AMD Opteron 2.6 GHz processors&lt;/li&gt;&#xA;&lt;li&gt;3,016 GB of RAM y 160 TB for storage,&lt;/li&gt;&#xA;&lt;li&gt;Processing capability of 7 TFlops (teraflops)&lt;/li&gt;&#xA;&lt;li&gt;Runs on GNU/Linux&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Aitzaloa (2008): Universidad Autónoma Metropolitana (UAM)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2,160 Intel Xeon E5272 QuadCore&lt;/li&gt;&#xA;&lt;li&gt;100TB storage&lt;/li&gt;&#xA;&lt;li&gt;Processing capability of 18 TFlops&lt;/li&gt;&#xA;&lt;li&gt;#226 of Top500 in 2008&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Atócatl (2011): Universidad Nacional Auónoma de México (UNAM)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Used primarily by and for the National Institute of Astrophysics.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Abacus (2014): Centro de Investigación y Estudios Avanzados (CINVESTAV)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;8,904 cores, Intel Xeon E5&lt;/li&gt;&#xA;&lt;li&gt;100 GPU K40 , Nvidia,&lt;/li&gt;&#xA;&lt;li&gt;1.2 Petabytes for storage y 40TB of RAM&lt;/li&gt;&#xA;&lt;li&gt;Can reach 400 Teraflops.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Miztli (2013): Universidad Nacional Autónoma de México (UNAM)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;HP Cluster Platform 3000SL&lt;/li&gt;&#xA;&lt;li&gt;5,312 Intel Xeon E5-2670&lt;/li&gt;&#xA;&lt;li&gt;16 GPU NVIDIA m2090&lt;/li&gt;&#xA;&lt;li&gt;15,000 GB RAM&lt;/li&gt;&#xA;&lt;li&gt;750 TB for storage&lt;/li&gt;&#xA;&lt;li&gt;runs on Linux Redhat&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Yoltla (2014): Universidad Autónoma Metropolitana (UAM)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;4,920 CPUS,&lt;/li&gt;&#xA;&lt;li&gt;6,912 GB RAM,&lt;/li&gt;&#xA;&lt;li&gt;70TB storage&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Reaches 45 TFlops.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Xiuhcoatl (2012): Centro de Investigación y Estudios Avanzados (CINVESTAV)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;4,724 CPU y 374,144 GPU&lt;/li&gt;&#xA;&lt;li&gt;Up to 250 TFlops by itself,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Connected via Optical Fiber to Kan Balam and Aitzaloa, combined &amp;gt; 7000 CPUs, 300 TFlops&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The supercomputers mentioned until now are owned by universities or university research centers. Additionally, Mexico has a National Supercomputing Laboratory, which gives service to uses nationwide as well. It is hosted by the Benemérita Universidad Autónoma de Puebla, (BUAP) and is called &amp;quot;Laboratorio nacional de Supercómputo&amp;quot; (LNS). Their full infrastructure page is &lt;a href=&quot;http://lns.org.mx/?q=infraestructura%20&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; , and below a summary of Cuetlaxcoapan, the main one.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cuetlaxcoapan: LNS&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;6796 CPU cores&lt;/li&gt;&#xA;&lt;li&gt;2048 GB RAM&lt;/li&gt;&#xA;&lt;li&gt;1520 CUDA cores&lt;/li&gt;&#xA;&lt;li&gt;Nvidia k40&lt;/li&gt;&#xA;&lt;li&gt;Storage of 1.2 Petabytes (PB)&lt;/li&gt;&#xA;&lt;li&gt;Capability up to  153.408 Tflops.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-07-19T02:04:17.887" LastActivityDate="2020-07-19T02:04:17.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1528" PostTypeId="1" CreationDate="2020-07-15T21:24:09.687" Score="4" ViewCount="137" Body="&lt;p&gt;I have been unable to figure out what the Kohn anomaly is. What exactly is it, and why is it important?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-07-20T03:52:28.150" LastActivityDate="2020-07-20T03:52:28.150" Title="What is the Kohn anomaly?" Tags="|density-functional-theory|phonons|" AnswerCount="0" CommentCount="2" ClosedDate="2020-07-16T00:41:28.317" ContentLicense="CC BY-SA 4.0" />
  <row Id="1529" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T22:31:03.877" Score="13" Body="&lt;h1&gt;USA: Facilities funded by DOD&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Other answers have addressed National Science Foundation (NSF) resources via XSEDE &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1517/671&quot;&gt;here&lt;/a&gt; and Department of Energy (DOE) resources &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/671/anyon&quot;&gt;here&lt;/a&gt; within the United States. Another set of computing resources in the US are those via the Department of Defense (DoD).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;HPCMP (High Performance Computing Modernization Program)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The DoD High Performance Computing Modernization Program (HPCMP) handles the computing centers administered by the DoD. As might be expected, the DoD HPCMP resources are meant for research that aligns with DoD mission statements. For those interested, the Army Research Laboratory (ARL), Air Force Research Laboratory (AFRL), and Navy Research Laboratory (NRL) all put out broad agency announcements (BAAs) that describe the current areas of research. An example for the Army Research Office can be found &lt;a href=&quot;https://www.arl.army.mil/business/broad-agency-announcements/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Access to DoD HPCMP resources is generally restricted to those that already receive research funding from the DoD, so they are not as easy to get access to as NSF's XSEDE or DOE's NERSC. However, it is a major source of research computing in the US all the same. The DoD HPCMP has several machines that are meant for unclassified research that academics can get access to, provided they are supported by the DoD. These machines are outlined &lt;a href=&quot;https://centers.hpc.mil/systems/unclassified.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and include many of the top computing machines in the world. As an example, the US Air Force's &lt;a href=&quot;https://centers.hpc.mil/systems/unclassified.html#Mustang&quot; rel=&quot;noreferrer&quot;&gt;Mustang&lt;/a&gt; is currently #80 on the &lt;a href=&quot;https://www.top500.org/lists/top500/list/2020/06/?page=1&quot; rel=&quot;noreferrer&quot;&gt;TOP500 list&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2020-07-19T01:58:53.157" LastActivityDate="2020-07-19T01:58:53.157" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1531" PostTypeId="2" ParentId="1515" CreationDate="2020-07-15T23:26:35.253" Score="18" Body="&lt;h1&gt;United Kingdom (Great Britain)&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;http://www.archer.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;ARCHER (Advanced Research Computing High End Resource)&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;ARCHER is as of today the UK's national supercomputing service, run by the EPCC (Edinburgh Parallel Computing Centre). It has been operating since late 2013, and is based around a Cray XC30 supercomputer. &lt;strong&gt;Note, however, ARCHER is right at the end of its lifecycle.&lt;/strong&gt; It was due to shut down in February of this year, but things are slightly behind schedule. (In fact, ARCHER2 is currently being set up, and is due to be operational shortly; see below.)&lt;/p&gt;&#xA;&lt;p&gt;Here is a brief overview of its capabilities from the &lt;a href=&quot;https://www.archer2.ac.uk/about/hardware.html&quot; rel=&quot;noreferrer&quot;&gt;hardware &amp;amp; software informational page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ARCHER compute nodes contain two 2.7 GHz, 12-core E5-2697 v2 (Ivy Bridge) series processors. Each of the cores in these processors can support 2 hardware threads (Hyperthreads). Within the node, the two processors are connected by two QuickPath Interconnect (QPI) links.&lt;/p&gt;&#xA;&lt;p&gt;Standard compute nodes on ARCHER have 64 GB of memory shared between the two processors. There are a smaller number of high-memory nodes with 128 GB of memory shared between the two processors. The memory is arranged in a non-uniform access (NUMA) form: each 12-core processor is a single NUMA region with local memory of 32 GB (or 64 GB for high-memory nodes). Access to the local memory by cores within a NUMA region has a lower latency than accessing memory on the other NUMA region.&lt;/p&gt;&#xA;&lt;p&gt;There are 4544 standard memory nodes (12 groups, 109,056 cores) and 376 high memory nodes (1 group, 9,024 cores) on ARCHER giving a total of 4920 compute nodes (13 groups, 118,080 cores). (See the &amp;quot;Aries Interconnect&amp;quot; section below for the definition of a group.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There is a &lt;a href=&quot;http://www.archer.ac.uk/about-archer/&quot; rel=&quot;noreferrer&quot;&gt;general overview&lt;/a&gt; of the ARCHER service on the official website, and &lt;a href=&quot;https://www.epcc.ed.ac.uk/facilities/archer&quot; rel=&quot;noreferrer&quot;&gt;another&lt;/a&gt; on the EPCC website.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.archer.ac.uk/access/&quot; rel=&quot;noreferrer&quot;&gt;Academic access&lt;/a&gt; is straightforward if you have an EPSRC or NERC research grant, though other avenues may also allow access, in particular limited access for new users. Access is open to all domains within the remit of the EPSRC and NERC.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.epcc.ed.ac.uk/facilities/archer&quot; rel=&quot;noreferrer&quot;&gt;Commercial and industrial access&lt;/a&gt; is also available, though obviously paid. In particular, an &lt;a href=&quot;https://www.epcc.ed.ac.uk/facilities/demand-computing/archer&quot; rel=&quot;noreferrer&quot;&gt;on-demand&lt;/a&gt; (pay-per-core-hour) service is available.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://www.archer2.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;ARCHER2&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The successor to ARCHER is currently being installed at the EPCC. See the &lt;a href=&quot;https://www.archer2.ac.uk/news&quot; rel=&quot;noreferrer&quot;&gt;news section&lt;/a&gt; on the website.&lt;/p&gt;&#xA;&lt;p&gt;Again, here is a brief overview from the &lt;a href=&quot;https://www.archer2.ac.uk/about/hardware.html&quot; rel=&quot;noreferrer&quot;&gt;hardware &amp;amp; software informational page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ARCHER2 will be a Cray Shasta system with an estimated peak performance of 28 PFLOP/s. The machine will have 5,848 compute nodes, each with dual AMD EPYC Zen2 (Rome) 64 core CPUs at 2.2GHz, giving 748,544 cores in total and 1.57 PBytes of total system memory.&lt;/p&gt;&#xA;&lt;p&gt;ARCHER2 should be capable on average of over eleven times the science throughput of ARCHER, based on benchmarks which use five of the most heavily used codes on the current service. As with all new systems, the relative speedups over ARCHER vary by benchmark. The ARCHER2 science throughput codes used for the benchmarking evaluation are estimated to reach 8.7x for CP2K, 9.5x for OpenSBLI, 11.3x for CASTEP, 12.9x for GROMACS, and 18.0x for HadGEM3.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The criteria for &lt;a href=&quot;https://www.archer2.ac.uk/support-access/access.html&quot; rel=&quot;noreferrer&quot;&gt;academic Access&lt;/a&gt; are apparently very similar as for ARCHER. Right now there is an &lt;a href=&quot;https://epsrc.ukri.org/funding/calls/access-to-high-performance-computing/&quot; rel=&quot;noreferrer&quot;&gt;open call for EPSRC access&lt;/a&gt; with a deadline of 4 September 2020.&lt;/li&gt;&#xA;&lt;li&gt;I cannot at present find any information on the ARCHER2 website about commercial/industrial access. Perhaps that will come later, after launch.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;http://mmmhub.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;MMM Hub (Materials and Molecular Modelling Hub)&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This one couldn't more more suited to the concern of this SE, as is evident in the name!&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Hub hosts a high performance computing facility known as Thomas. Thomas is a 17,000 core machine based around Lenovo 24 core Intel x86-64 nodes. It is designed to support small to medium sized capacity computing focusing on materials and molecular modelling. 75% of Thomas is reserved for Tier-2 use by MMM Hub partners who are contributing towards the running costs of the facility. The other 25% of the machine is available free of charge to materials and molecular modelling researchers from anywhere in the UK.&lt;/p&gt;&#xA;&lt;p&gt;The Hub is operated through the partnership of eight of the UK’s leading universities (UCL, Imperial College London, Queen Mary University of London, Queen’s University Belfast, the University of Kent, King’s College London, the University of Southampton and the University of Oxford) and OCF Plc.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Per the page for the &lt;a href=&quot;http://mmmhub.ac.uk/thomas&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Thomas&lt;/em&gt; supercomputer&lt;/a&gt;, &amp;quot;75% of Thomas is reserved for Tier-2 use by MMM Hub partners who are contributing towards the running costs of the facility. The other 25% of the machine is available free of charge to materials and molecular modelling researchers from anywhere in the UK.&amp;quot; See that page for points of contacts at each institution.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;http://www.hpc-uk.ac.uk/facilities/&quot; rel=&quot;noreferrer&quot;&gt;Other HPC Services&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;See the above link for other (Tier 2) services. Note that some like DiRAC are domain-specific (targeted at particle physics and astronomy research), though paid access is available for users outside of these fields.&lt;/p&gt;&#xA;" OwnerUserId="43" LastEditorUserId="5" LastEditDate="2020-07-19T02:02:23.000" LastActivityDate="2020-07-19T02:02:23.000" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1532" PostTypeId="2" ParentId="1521" CreationDate="2020-07-16T02:09:41.283" Score="15" Body="&lt;h2&gt;Summary of the &amp;quot;milestone&amp;quot; pseudopotential (PP) papers&lt;/h2&gt;&#xA;&lt;p&gt;Since it wasn't available anywhere &amp;amp; took me a few hours, it's an answer rather than question-edit:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Local pseudo-potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;1935: &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1749559&quot; rel=&quot;noreferrer&quot;&gt;Zusatzpotential / Hellmann&lt;/a&gt; (Generally &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cphc.201100387&quot; rel=&quot;noreferrer&quot;&gt;credited&lt;/a&gt; as the first pseudopotential).&lt;/li&gt;&#xA;&lt;li&gt;1936: Fermi pseudopotential (for s-wave scattering of a free neutron by a nucleus).&lt;/li&gt;&#xA;&lt;li&gt;1958: &lt;a href=&quot;https://www.worldcat.org/title/pseudopotentials-in-the-theory-of-metals/oclc/542496&quot; rel=&quot;noreferrer&quot;&gt;Harrison&lt;/a&gt; (FPPM: First-Principle PP method, fitted to nearly free e- Fermi surface of &lt;span class=&quot;math-container&quot;&gt;$\ce{Al}$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;li&gt;1959: &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.116.287&quot; rel=&quot;noreferrer&quot;&gt;Phillips-Kleinman&lt;/a&gt; (core-val. orthogonalization terms replaced by &amp;quot;hard-core&amp;quot; potential).&lt;/li&gt;&#xA;&lt;li&gt;1968: &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1670479&quot; rel=&quot;noreferrer&quot;&gt;Weeks-Rice&lt;/a&gt; (extended the single valence e- work of Phillips to many valence e-).&lt;/li&gt;&#xA;&lt;li&gt;1973: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.8.1777&quot; rel=&quot;noreferrer&quot;&gt;Appelbaum-Hamann potential&lt;/a&gt; (smooth potential for &lt;span class=&quot;math-container&quot;&gt;$\ce{Si^{4+}}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; works for band gaps in &lt;span class=&quot;math-container&quot;&gt;$\ce{Si}$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Non-local pseudo-potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;1979: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;noreferrer&quot;&gt;HSC&lt;/a&gt; (norm-conserving PP: exact energies &amp;amp; nodeless &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_c$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;li&gt;1980: &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0022-3719/13/9/004&quot; rel=&quot;noreferrer&quot;&gt;Kerker PP&lt;/a&gt; (non-singluar PP: exact for &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_c$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\dot\psi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ddot\psi$&lt;/span&gt; matched with &lt;em&gt;ab initio&lt;/em&gt;).&lt;/li&gt;&#xA;&lt;li&gt;1982: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.48.1425&quot; rel=&quot;noreferrer&quot;&gt;Kleinman-Bylander&lt;/a&gt; (highly simple).&lt;/li&gt;&#xA;&lt;li&gt;1990: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.41.1227&quot; rel=&quot;noreferrer&quot;&gt;RRKJ Optimized PPs&lt;/a&gt; (improve plane-wave convergence).&lt;/li&gt;&#xA;&lt;li&gt;1990: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.41.7892&quot; rel=&quot;noreferrer&quot;&gt;Ultra-soft / Vanderbilt&lt;/a&gt; (norm-conservation not needed for &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;: allows far more flexibility).&lt;/li&gt;&#xA;&lt;li&gt;1990: &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0038109890906866&quot; rel=&quot;noreferrer&quot;&gt;Troullier-Martins&lt;/a&gt; (scheme for generating very soft norm-conserving PPs for PWs).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Generalizations of pseudo-potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;1994: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.50.17953&quot; rel=&quot;noreferrer&quot;&gt;Blöchl&lt;/a&gt; (generalization of PPs and LAPWs based on a linear transformation).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-22T15:44:41.913" LastActivityDate="2020-07-22T15:44:41.913" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1533" PostTypeId="2" ParentId="1515" CreationDate="2020-07-16T02:45:17.717" Score="13" Body="&lt;p&gt;Universities have supercomputers of smaller magnitude, but permit the same function.&#xA;A supercomputer is not a fancy state of the art set up. It's processing and computing power is determined by the number of independent processors equipped to it. A real supercomputer may even use obsolete and years old processors (whose acquisition value is insignificant) Using state of the art processors would make them ridiculously expensive than they already are. A state of the art xeon processor from Intel for example costs thousands, acquiring the chip set needed to build a supercomputer would cost over 2 billion dollars! for the chips alone. Obsolete chips from disposed computers cost virtually nothing. With the advent of mainframe computing; companies that specialized in supercomputer structures either went out of business or folded like Cray, Wang, etc.&lt;/p&gt;&#xA;&lt;p&gt;Common mainframes can be built. A simple mother board is equipped with several processors than the mother boards are inserted into a box (Shelves, which is connected to vertically on a rack. Then the mainframe chassis are linked. A supercomputer does what your computer at home does......with tens of thousands of processors; some dedicated to graphics/physics engines exclusively.&lt;/p&gt;&#xA;&lt;p&gt;With distributive computing and cloud set up, processing without the need of large mainframes is becoming more apparent. Google rents supercomputer time.&#xA;One company &amp;quot;Cycle Computing&amp;quot; has assemebled a makeshift super computer from linking old mainframes, the cost 1,300 bucks per hour&lt;/p&gt;&#xA;&lt;p&gt;The biggest detriment to supercomputing now is energy consumption. The proliferation of more and more computing power has led to an exponential rise in energy demand. Processors get hot, for every watt of energy dedicated to actual processing 3 watts are needed to mechanically move waste heat away from the system. As more and more systems are added; more and more heat energy must be passed. Air based heat exchangers in cold climates may help with this (Thor Data Center in Reykjavik, Iceland, this supercomputer runs air cooling units outside) In the mid 1990s a top 10 supercomputer required in the range of 100 kilowatt, in 2010 the top 10 supercomputers required between 1 and 2 megawatt. For larger scale supercomputing, vaster energy requirements and energy dedicated solely to heat dissipation.&lt;/p&gt;&#xA;" OwnerUserId="1044" LastEditorUserId="1044" LastEditDate="2020-07-30T00:02:18.827" LastActivityDate="2020-07-30T00:02:18.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1535" PostTypeId="1" CreationDate="2020-07-16T06:33:56.243" Score="17" ViewCount="1097" Body="&lt;p&gt;Since the beginning of the century, &lt;a href=&quot;http://susi.theochem.tuwien.ac.at/index.html&quot; rel=&quot;noreferrer&quot;&gt;Wien2K&lt;/a&gt; has proven to be a very powerful player in computational condensed matter and materials physics.&lt;/p&gt;&#xA;&lt;p&gt;Wien2K is an all-electron periodic DFT code based on the Augmented Planewave + Local Orbital [APW+lo] method, and also widely known as Full-Potential - Linearized Augmented Planewave [FP-LAPW+lo] method, or simply LAPW. It is known or said to be one of the &lt;em&gt;most accurate methods&lt;/em&gt; for modeling solids. Wien2K is very nice, but it is not free.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do you know of any open-source &amp;amp; community LAPW codes alternative to Wien2K?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;What has been your experience with them?&lt;/p&gt;&#xA;&lt;p&gt;I am particularly interested in codes that invite developers.&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-07-16T12:14:29.390" LastActivityDate="2021-11-11T13:48:33.830" Title="What are some open-source all-electron DFT alternatives to Wien2K?" Tags="|density-functional-theory|software|one-topic-per-answer|wien2k|solid-state-physics|" AnswerCount="5" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1536" PostTypeId="5" CreationDate="2020-07-16T17:16:19.277" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-16T17:16:19.277" LastActivityDate="2020-07-16T17:16:19.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1537" PostTypeId="4" CreationDate="2020-07-16T17:16:19.277" Score="0" Body="For questions about modeling with explicitly simulated solvent molecules. This is typically in the context of electronic structure theory, where solvation effects are included by simulating solvent molecules quantum mechanically (explicit) and/or by some sort of classical continuum (implicit)." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-16T17:16:19.277" LastActivityDate="2020-07-16T17:16:19.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1538" PostTypeId="1" AcceptedAnswerId="1783" CreationDate="2020-07-16T17:31:10.260" Score="11" ViewCount="1303" Body="&lt;p&gt;When doing VASP calculations for large cells, we get a warning:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;You have a (more or less) 'large supercell' and for larger cells it&#xA;might be more efficient to use real space projection operators. So try&#xA;&lt;code&gt;LREAL= Auto&lt;/code&gt;  in the INCAR file.&#xA;Mind:   For very  accurate calculation you might also keep the reciprocal projection scheme.  (i.e. &lt;code&gt;LREAL=.FALSE.&lt;/code&gt;)&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why is using real space projection operators efficient for large supercells, and why are they less accurate?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-28T03:05:29.897" LastActivityDate="2020-07-28T03:05:29.897" Title="Real space projection vs reciprocal space projection in DFT calculations" Tags="|density-functional-theory|vasp|condensed-matter|" AnswerCount="1" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1539" PostTypeId="1" CreationDate="2020-07-16T20:29:45.753" Score="12" ViewCount="412" Body="&lt;p&gt;Statistical Mechanics is the basis of molecular level calculations of properties and averages. Nowadays free energy calculations are fairly &amp;quot;turn-the-crank&amp;quot;, which is not necessarily a good thing. It is easy to perform a free energy calculation and get a number.&lt;/p&gt;&#xA;&lt;p&gt;In the molecular dynamics package GROMACS, for instance, alchemical free energy calculations are only valid if done in the NVT ensemble. This is because GROMACS samples potential energies, thus one can calculate (or press a button on pymbar or another piece of software)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \Delta A = -kT \ln \langle \exp(-\beta \Delta \mathcal{U}) \rangle&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\Delta A$&lt;/span&gt; is the difference in the Helmholtz free energy between two states, &lt;span class=&quot;math-container&quot;&gt;$\beta = \frac{1}{kT}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{U}$&lt;/span&gt; is the difference in sampled potential energy between two states, and &lt;span class=&quot;math-container&quot;&gt;$\langle \rangle$&lt;/span&gt; is an ensemble average.&lt;/p&gt;&#xA;&lt;p&gt;If you run an NPT simulation you must instead sample&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \Delta G = -kT \ln \frac{\langle V \exp(-\beta \Delta \mathcal{U}) \rangle}{\langle V \rangle} &#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;While it is tempting to say that the volumes cancel so you only need the ensemble average of the NVT Boltzmann factor, this is not at all correct. GROMACS is aware that it is not correctly sampling the NPT and has tucked away a note in the user manual to the effect that for water at 298.15 K the error is small i.e., less than a kilojoule.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;a kilojoule can make a large difference to an equilibrium constant&lt;/li&gt;&#xA;&lt;li&gt;Chemistry does not happen at only 298.15! if you increase the temperature or density of the solvent (not all of us do water) the error quickly gets out of hand - this is particularly true for ionic liquids.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;Question:&lt;/h2&gt;&#xA;&lt;p&gt;Is this assumption (possibly error in other codes) present in other codes? Are there any MD codes that properly sample the NPT ensemble for free energy?&lt;/p&gt;&#xA;&lt;h2&gt;Note:&lt;/h2&gt;&#xA;&lt;p&gt;While Godzilla has shown entirely correctly how one &lt;em&gt;should&lt;/em&gt; sample the free energy in the NPT, neither his equation, or mine, which is equivalent for &lt;span class=&quot;math-container&quot;&gt;$\Delta G$&lt;/span&gt;, are implemented in GROMACS, and possibly others. I am looking for if any MD programs do implement the proper free energy sampling. They all properly do NPT sampling (I assume), but sampling the free energy is a step above and beyond.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-07-18T19:56:57.363" LastActivityDate="2020-07-18T19:56:57.363" Title="Are there any MD packages that do proper free energy sampling in the NPT ensemble?" Tags="|molecular-dynamics|gibbs-free-energy|thermodynamics|statistical-thermodynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1540" PostTypeId="1" AcceptedAnswerId="1545" CreationDate="2020-07-16T21:24:44.557" Score="11" ViewCount="1395" Body="&lt;p&gt;I am interested in calculating the Fock matrix in the molecular orbital basis with PySCF, though I am not clear on the methodology behind this task.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;In my attempt, I use the following script (for the example H&lt;span class=&quot;math-container&quot;&gt;$_{2}$&lt;/span&gt; molecule):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf&#xA;geometry = '''&#xA;    H   0.000   0.000   0.000&#xA;    H   0.000   0.000   0.740&#xA;'''&#xA;mol = gto.Mole()&#xA;mol.atom = geometry&#xA;mol.basis = '3-21g'&#xA;mol.build()&#xA;​&#xA;mf = scf.RHF(mol)&#xA;mf.scf()&#xA;​&#xA;Fao = mf.get_fock()&#xA;Fmo = mf.mo_coeff.T @ Fao @ mf.mo_coeff&#xA;​&#xA;print('F_mo')&#xA;print(Fmo)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this method, I first calculate the molecular mean-field. I then do matrix multiplication with the molecular coefficient transpose matrix (&lt;code&gt;mf.mo_coeff.T&lt;/code&gt;), the Fock matrix in the atomic basis (&lt;code&gt;Fao&lt;/code&gt;) and the molecular orbital coefficients (&lt;code&gt;mf.mo_coeff&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The resulting off-diagonal matrix elements are essentially zero for the H&lt;span class=&quot;math-container&quot;&gt;$_{2}$&lt;/span&gt; molecule and other larger systems taken to 10 decimal places (CH&lt;span class=&quot;math-container&quot;&gt;$_{4}$&lt;/span&gt;, NH&lt;span class=&quot;math-container&quot;&gt;$_{3}$&lt;/span&gt;, H&lt;span class=&quot;math-container&quot;&gt;$_{2}$&lt;/span&gt;O). This has confused me: I have seen other Fock matrices in the molecular orbital basis with off-diagonal elements present.&lt;/p&gt;&#xA;&lt;p&gt;I am therefore looking for confirmation of my method, and if there is a better way of doing this task?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="786" LastEditDate="2020-07-16T21:31:11.130" LastActivityDate="2020-07-17T05:18:13.737" Title="How to calculate the Fock matrix in the molecular orbital basis PySCF?" Tags="|hartree-fock|pyscf|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1541" PostTypeId="1" AcceptedAnswerId="1553" CreationDate="2020-07-16T23:59:45.867" Score="14" ViewCount="356" Body="&lt;p&gt;We all learned about single vs double vs triple bonds in high school chemistry and biology. We learned that unsaturated fats have double bonds whereas saturated fats have only single bonds, which makes unsaturated fats liquid (vs. solid) and easier to break/process by the body.&lt;/p&gt;&#xA;&lt;p&gt;I was impressed when this Stack Exchange first went live though, to learn about the existence of about a &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/901/5&quot;&gt;dozen different definitions of bond order&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I wonder if/how these have led to useful insights such as the textbook example I gave in the first paragraph of this question?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I can imagine studying some large un-studied molecule in which the bond orders are not known. Once I have an approximation of the wavefunction, I can calculate one of the many types of bond orders mentioned in the aforementioned question (such as the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1469/5&quot;&gt;Wiberg bond index&lt;/a&gt; explained here, which only needs the orbital coefficients from the LCAO model of a wavefunction); or if I have calculated the electron density, I can use one of the many techniques of &amp;quot;conceptual DFT&amp;quot; from the QTAIM framework or extensions, such as in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1508/5&quot;&gt;this answer&lt;/a&gt;. But the existence of &lt;em&gt;so many&lt;/em&gt; of these bond-order definitions, suggests that the very simple-to-calculate Wiberg bond index is not accurate enough for some people's liking (hence the need to formulate more complicated bond-order definitions).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If we wish to know the length of a bond and we are using some advanced wavefunction-based or DFT software, I suppose that we would just do geometry optimization in our quantum chemistry software anyway, which would give us an even better description of the bond lengths than some &amp;quot;heuristic&amp;quot; method such as assigning a bond-order.&lt;/li&gt;&#xA;&lt;li&gt;If we wish to know the strength of a bond (remembering &lt;a href=&quot;https://chemistry.stackexchange.com/q/73437/27342&quot;&gt;Tyberius's famous question from 3 years ago&lt;/a&gt;) we could just calculate the force constant for a particular bond, as &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1477/5&quot;&gt;MSwart said in this answer&lt;/a&gt;. This may add a bit to the cost of the quantum chemistry calculation, compared to just using a simple formula like the Wiberg bond-order formula, but probably not more than all of the other painful effort that goes into doing a quantum chemistry calculation (e.g. preparing a ZMAT/XYZ file, doing geometry optimization, converging an SCF, converging with respect to basis set and correlation-treatment, accounting for relativity and Born-Oppenheimer breakdown, etc.), and it seems it would be much more accurate (clearly the Wiberg formula is too simple because so many more sophisticated bond-order methods have been devised afterwards).&lt;/li&gt;&#xA;&lt;li&gt;I appreciate that we might want to &lt;a href=&quot;https://en.wikipedia.org/wiki/Structural_formula&quot; rel=&quot;noreferrer&quot;&gt;draw the chemical structure&lt;/a&gt; with all its single and double bonds, but the desire to do this hinges on the bond-order actually being truly useful, which wouldn't seem to always be the case with, for example, the Wiberg bond-order which seems to have needed added levels of seemingly un-ending further sophistication in dozens of subsequent papers.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1477/5&quot;&gt;MSwarts's answer to the previous question ends with&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Of course you could also compute the intrinsic force constant for that&#xA;particular bond, with all kind of ifs and buts. But that would be&#xA;opening up a whole new discussion.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Perhaps we can now have that discussion.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-17T00:49:07.830" LastActivityDate="2022-01-28T23:06:34.127" Title="Bond Order: When and how is it used today?" Tags="|reference-request|quantum-chemistry|education|conceptual-dft|valence-bond-theory|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1542" PostTypeId="2" ParentId="1539" CreationDate="2020-07-17T00:50:41.280" Score="10" Body="&lt;p&gt;It is straightforward to show that in a typical &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt; setting the Zwanzig equation still only depends on the energy difference and not on the volume (here I define &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; to be the Hamiltonian of each system, respectively and &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; to represent all variables over phase space):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{Z_{B,NPT}}{Z_{A,NPT}} = \int  \int e^{-\beta \Delta H(x)} \frac{e^{-\beta H_A(x)}}{Z_{A,NPT}} e^{-\beta PV} dxdV = \left&amp;lt;e^{-\beta \Delta H}\right&amp;gt;_{A,NPT}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;so I am not sure where you get this equation from &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt; it seems wrong to me. Of course, you still get &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt; contribution in this way, since the exponential averages have to be performed in the isothermal-isobaric ensemble, and these will generally be different to averages obtained in &lt;span class=&quot;math-container&quot;&gt;$NVT$&lt;/span&gt; (although in many practical purposes, virtually the same, especially in dense systems that are not near any critical points).&lt;/p&gt;&#xA;&lt;p&gt;I am not sure which part of the GROMACS manual you are referring to, but I suspect you are talking about the Berendsen barostat. The Berendsen barostat is known to be not rigorous but very good for equilibration (again, for many systems it is practically the same as a rigorous barostat and usually not the limiting error). For a production run you should use the Parrinello-Rahman barostat, which is considered to be rigorous. However, it is deterministic, which can lead to some practical problems regarding non-physical oscillations. This is the &amp;quot;rigorous&amp;quot; barostat implemented in GROMACS and to my knowledge this way of calculating free energies in &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt; is completely valid from a theoretical standpoint.&lt;/p&gt;&#xA;&lt;p&gt;Another rigorous barostat which is also stochastic is the Monte Carlo barostat. Unfortunately, it is only implemented in AMBER and OpenMM and not in GROMACS. As far as I know, NAMD comes with a Nosé-Hoover Langevin piston barostat which is also rigorous. You can see that pretty much every MD engine comes with a Berendsen barostat and a single rigorous barostat and they all use different rigorous barostats.&lt;/p&gt;&#xA;&lt;p&gt;As a final remark, if you are planning to run simulations at high temperatures, I'd be &lt;em&gt;much&lt;/em&gt; more worried about the validity of your model, presumably a force field, at these extreme conditions. Also, while it is true that 1 kJ/mol can be considered significant in some cases, there are so many errors when calculating free energies, including force field accuracy, insufficient sampling, estimator convergence (e.g. Zwanzig), or even the fact that you restrict your system to be a tiny box, that I would be much less worried about the impact of the barostat, or indeed the choice of thermodynamic ensemble on my results in most conceivable applications.&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="710" LastEditDate="2020-07-17T06:55:02.540" LastActivityDate="2020-07-17T06:55:02.540" CommentCount="17" ContentLicense="CC BY-SA 4.0" />
  <row Id="1543" PostTypeId="2" ParentId="1515" CreationDate="2020-07-17T03:20:26.467" Score="16" Body="&lt;h1&gt;China: National supercomputers&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;China has 6 national supercomputer centers and several university/Chinese academy of science supercomputer centers. Here are the brief about China national national supercomputer centers.&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTING CENTER IN CHANGSHA&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Hunan University is responsible for operation management, National University of Defense Technology is responsible for technical support.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The peak computing performance of the whole system is 1372 trillion times, of which, the peak computing performance of the whole system CPU is 317.3 trillion times, and the peak computing performance of GPU is 1054.7 trillion times.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The system is configured with 2048 blade nodes to form a computing array. The node adopts a 2-way 6-core Intel Xeon Westmere EP high-performance processor with a main frequency of 2.93GHz and a memory of 48GB. Each node is equipped with an Nvidia M2050 GPU. The single computing node has a peak CPU performance of 140.64GFlops and a peak GPU performance of 515GFlops.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTER CENTER IN TIANJING&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The National Supercomputing Tianjin Center is the first national supercomputing center approved for establishment in May 2009. It is equipped with the “Tianhe No. 1” supercomputer and the “Tianhe No. 3” prototype that ranked No. 1 in the world’s top 500 supercomputers in November 2010.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTER CENTER IN JINAN&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The National Supercomputing Jinan Center was founded in 2011. The E-class computing prototype was built in 2018, and the tens of billions of supercomputing platforms are under construction in 2019-2022&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTER CENTER IN GUANGZHOU&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The national supercomputing Guangzhou center business host-&amp;quot;Tianhe No. 2&amp;quot; supercomputer system, undertaken by the National University of Defense Technology. The peak calculation speed of the first phase of the &amp;quot;Tianhe 2&amp;quot; system is 549 billion times per second, the continuous calculation speed is 339 billion times per second, and the energy efficiency ratio is 1.9 billion double-precision floating-point operations per watt-second.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTING CENTER IN SHENZHEN&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Dawning 6000 &amp;quot;Nebula&amp;quot; supercomputer purchased by the National Supercomputing Center in Shenzhen has the second highest computing speed in the world: The world's supercomputing organization has measured the Dawning 6000 supercomputer with an operating speed of 1271 trillion times per second, ranking second in the world with double precision floating point The processing performance exceeds 2400 trillion times per second, the total memory capacity of the system is 232TB, and the storage is 17.2PB.&lt;/li&gt;&#xA;&lt;li&gt;There are a total of 2560 computing nodes in the main blade area. Each computing node is configured with two Intel Xeon X5650 CPUs (6-core 2.66GHz), 24GB memory, one NVidia C2050 GPU, one QDR IB network card, and the system peak value is 1271 trillion times per second. The fat node partition has a total of 128 rack-mounted server nodes. Each node is configured with 4 AMD Opteron 6136 (8-core 2.4GHz), 128GB memory, and 1 QDR IB network card.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NATIONAL SUPERCOMPUTING CENTER IN WUXI&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Shenwei Taihuguang Supercomputer is composed of 40 computing cabinets and 8 network cabinets. 4 super nodes composed of 32 arithmetic plug-ins are distributed among them. Each plug-in consists of 4 computing node boards, and one computing node board contains 2 &amp;quot;Shenwei 26010&amp;quot; high-performance processors. One cabinet has 1024 processors, and the whole &amp;quot;Shenwei·Light of Taihu Lake&amp;quot; has a total of 40960 processors. Each single processor has 260 cores, the motherboard is designed for dual nodes, and the onboard memory solidified by each CPU is 32GB DDR3-2133.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1031" LastEditorUserId="5" LastEditDate="2020-07-19T02:04:30.340" LastActivityDate="2020-07-19T02:04:30.340" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1544" PostTypeId="1" CreationDate="2020-07-17T03:38:56.053" Score="5" ViewCount="56" Body="&lt;p&gt;I was reading about the field of &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Energy_economics&quot; rel=&quot;noreferrer&quot;&gt;energy economics&lt;/a&gt;&amp;quot; and found it fascinating that there is a list of &amp;quot;top 20&amp;quot; authors:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/uEqg5.png&quot; Width=&quot;600&quot;&gt;&#xA;&lt;p&gt;At first this seemed strange: What does it even &lt;em&gt;mean&lt;/em&gt; to be the #4 best energy economist?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However they seem to have a &lt;a href=&quot;https://ideas.repec.org/top/&quot; rel=&quot;noreferrer&quot;&gt;rigorous procedure&lt;/a&gt; for evaluating people's research based on several criteria, and they update the results between the 3rd and 5th days of each month.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;They also have &amp;quot;top author&amp;quot; lists specifically for women, young people, deceased, and by where they graduated:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/DpGzN.png&quot; Width=&quot;200&quot;&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;I'm fascinated by the level of detail with which I can search and sort:&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/VPdzQ.png&quot; Width=&quot;600&quot;&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do we have something like this for people that model matter?&lt;/strong&gt; &lt;br&gt;&#xA;&lt;strong&gt;How about for any field of computational/theoretical (bio)chemistry/physics?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://academia.stackexchange.com/a/121697/93303&quot;&gt;Four of the top researchers in our field have been mentioned on Academia Stack Exchange&lt;/a&gt; in a &amp;quot;fun&amp;quot; answer, but it was based on &lt;em&gt;ad hoc&lt;/em&gt; criteria involving h-index, age, and perhaps personal opinion: Surely we can do better.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-17T03:38:56.053" Title="Do we have authorship rankings in our field or related fields?" Tags="|reference-request|history|education|" AnswerCount="0" CommentCount="4" ClosedDate="2020-07-29T04:07:17.773" ContentLicense="CC BY-SA 4.0" />
  <row Id="1545" PostTypeId="2" ParentId="1540" CreationDate="2020-07-17T05:18:13.737" Score="7" Body="&lt;p&gt;For &lt;strong&gt;canonical&lt;/strong&gt; MOs, it is expected that the off-diagonal elements of the described product with the Fock matrix are zero (within reasonable accuracy) because they are the result of the diagonalization of the Fock matrix.&lt;/p&gt;&#xA;&lt;p&gt;However, canonical MOs are not the only possible choice. One can &amp;quot;rotate&amp;quot; the MOs to minimize certain metrics in order to obtain, for instance, &lt;strong&gt;localized&lt;/strong&gt; MOs (LMO). Such rotations will keep the total energy and the electron density intact, but will disallow the interpretation of the diagonal values of the Fock matrix (represented in the LMO basis) as orbital energies.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-07-17T05:18:13.737" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1546" PostTypeId="2" ParentId="909" CreationDate="2020-07-17T09:49:26.923" Score="30" Body="&lt;p&gt;Topological materials form a broad family including insulators, semimetals, and superconductors, of which perhaps the best known are topological insulators. For concreteness, I will focus on topological insulators as these are the ones specifically mentioned in the question.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Topological insulator.&lt;/strong&gt; A topological insulator is an insulator whose Hamiltonian cannot be adiabatically connected to the atomic limit. Adiabatic means that, when tuning some external parameter (e.g. pressure, temperature) to change the Hamiltonian, the process is slow enough that the material stays in its ground state throughout.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Qualitative picture.&lt;/strong&gt; Consider an insulator like diamond. Imagine you pull the carbon atoms apart, taking each individual atom to one edge of the Universe, so that you end up with isolated carbon atoms -- this is what we call the &lt;em&gt;atomic limit&lt;/em&gt;. In diamond, it is possible to do this process without closing the bulk band gap, so we say that bulk diamond is adiabatically connected with the atomic limit, and as such diamond is a normal insulator. Now repeat the same with another material, say &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi_2Se_3}$&lt;/span&gt;, which in its crystalline form is also a bulk insulator. In this case, when you pull the system apart to reach the atomic limit it is impossible to do it without closing the bulk band gap. As such, &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi_2Se_3}$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt; adiabatically connected to the atomic limit, and we call it a topological insulator.&lt;/p&gt;&#xA;&lt;p&gt;So what is the reason for this picture of topological insulators? Broadly speaking, the electron wave function &amp;quot;twists&amp;quot; as you cross the Brillouin zone in a topological material. The electron wave function in the atomic limit is never twisted, so the twist needs to be undone when getting to that limit and this is what the band closure accomplishes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Topological invariants.&lt;/strong&gt; More rigorously, these twists can be characterized by so-called topological invariants, and their mathematical form depends on the type of topological material you are looking at, but are mostly related to Berry phase-like quantities that measure the evolution of the electron wave function as you cross the Brillouin zone. As an example, for 3-dimensional topological insulators, the topological invariant is a set of 4 numbers that can take one of two values (&lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; classification) and can be calculated by following the evolution of Wannier charge centers across the Brillouin zone as described in this paper&lt;sup&gt;[1]&lt;/sup&gt;, or if the system has inversion symmetry by simply calculating the parity of the eigenstates at special points in the Brilloin zone as described in this paper&lt;sup&gt;[2]&lt;/sup&gt;. Another well-known example is for Chern insulators (which roughly speaking are 2D materials with topological and magnetic orders) in which the topological invariant is the Chern number (an integer, so &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}$&lt;/span&gt; classification) obtained by integrating the Berry curvature over the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;First principles calculations.&lt;/strong&gt; So how do you figure out what the topological order of a material is? The way to do it is to calculate the corresponding topological invariant. As these calculations involve Berry phase-like quantities, the usual route in first principles calculations is to use Wannier functions, and packages that implement these calculations and have interfaces to major DFT packages include &lt;a href=&quot;http://z2pack.ethz.ch/doc/3.1/index.html&quot; rel=&quot;noreferrer&quot;&gt;Z2Pack&lt;/a&gt; and &lt;a href=&quot;http://www.wanniertools.com&quot; rel=&quot;noreferrer&quot;&gt;WannierTools&lt;/a&gt;. There are also several databases (e.g. the &lt;a href=&quot;https://www.topologicalquantumchemistry.org/#/&quot; rel=&quot;noreferrer&quot;&gt;Topologial Materials Database&lt;/a&gt; or &lt;a href=&quot;http://materiae.iphy.ac.cn&quot; rel=&quot;noreferrer&quot;&gt;Materiae&lt;/a&gt;) that include the topological classification of &lt;em&gt;many&lt;/em&gt; materials based on semilocal DFT. These databases are excellent starting points to figure out the possible topological order of a material, although it is known that higher levels of theory (e.g. hybrid functionals, &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt;) may lead to different results, so I recommend further analysis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Band inversion.&lt;/strong&gt; Having said all this, where does &amp;quot;band inversion&amp;quot; enter? The usual strategy to &lt;em&gt;get&lt;/em&gt; a topological insulator, and already used in the seminal paper by Kane and Mele&lt;sup&gt;[3]&lt;/sup&gt;, is to induce the wave function twist using spin-orbit coupling. This is a very simple schematic for &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi_2Se_3}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/u87AG.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/u87AG.jpg&quot; alt=&quot;Simple two-state schematic of spin orbit coupling of Bi2Se3. Spin orbit coupling creates a gap between the conduction band (upper, red) and the valence band (lower red)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Without spin-orbit coupling (left), the &amp;quot;conduction band&amp;quot; shown in red is made of &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals, and the &amp;quot;valence band&amp;quot;, shown in blue, of &lt;span class=&quot;math-container&quot;&gt;$\ce{Se}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals. However, the bands overlap and the system has no band gap. When spin-orbit coupling is included (right), a gap opens at the crossing points, and now we have a proper conduction band that has contributions from the band that made the valence band originally (blue) and &lt;em&gt;vice versa&lt;/em&gt; (imagine you continue the valence band in blue with a dashed line, it would then &amp;quot;join up&amp;quot; with the part of the conduction band in blue). This is called a band inversion. In the case of &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi_2Se_3}$&lt;/span&gt; it is very clear to identify, but in other materials it may be harder. A band inversion like this may suggest that the material has topological order, but the only way to confirm it is by calculating the topological invariant.&lt;/p&gt;&#xA;&lt;p&gt;So finally let's consider the paper you cite. As far as I understand, in this paper they call &amp;quot;band inversion&amp;quot; a situation in which the bands overlap (left diagram). They argue that such a band overlap is not necessarily induced by spin-orbit coupling, but instead by other effects such as perhaps a structural distortion. I think this is a reasonable statement, and they provide evidence in a range of materials for this. But what is essential to understand is that this is not enough to have a topological insulator, it is still necessary to open the band gap to get to a situation like the one depicted in the right diagram, and for this you usually still need spin-orbit coupling (and this is indeed the case in the paper you cite).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Additional comments.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;There are some additional subtleties with the above definition of adiabatic connection. We typically require that the Hamiltonian also obeys some symmetry throughout the entire adiabatic evolution, and depending on the symmetry that is obeyed we end up with different types of topological material. For example, when we say &amp;quot;topologial insulator&amp;quot; we typically understand &amp;quot;time-reversal invariant topological insulator&amp;quot;, which means that time reversal symmetry is conserved throughout. Another example may be to impose a crystalline symmetry, and then we could find a topological crystalline insulator.&lt;/li&gt;&#xA;&lt;li&gt;Another very famous feature of topological insulators is the presence of surface states. From the qualitative description above it is very easy to understand where they come from: the surface of a topological insulator is really the boundary between a topologically ordered bulk and a &amp;quot;normal&amp;quot; vacuum or air outside. As such, the wave function twist needs to be undone at this boundary, so the &amp;quot;gap&amp;quot; closes and we get metallic states, which are observed as surface states in this setup. These states have some nice features because they are protected by the underlying topology, and the presence of surface states (similar to the presence of band inversion) is indicative of topological order. You still want to calculate the topological invariant though to confirm this.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;P.S.: the basic features of topological materials can be understood with simple 2-band models. I am preparing a series of videos on this, and will share the link when I have them ready.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Soluyanov, A. A.; Vanderbilt, D. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.83.235401&quot; rel=&quot;noreferrer&quot;&gt;Computing topological invariants without inversion symmetry.&lt;/a&gt; &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2011,&lt;/strong&gt; &lt;em&gt;83&lt;/em&gt; (23), No. 235401. DOI: 10.1103/PhysRevB.83.235401.&lt;/li&gt;&#xA;&lt;li&gt;Fu, L.; Kane, C. L. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.76.045302&quot; rel=&quot;noreferrer&quot;&gt;Topological insulators with inversion symmetry.&lt;/a&gt; &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2007,&lt;/strong&gt; &lt;em&gt;76&lt;/em&gt; (4), No. 045302. DOI: 10.1103/PhysRevB.76.045302.&lt;/li&gt;&#xA;&lt;li&gt;Kane, C. L.; Mele, E. J. &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.95.226801&quot; rel=&quot;noreferrer&quot;&gt;Quantum Spin Hall Effect in Graphene.&lt;/a&gt; &lt;em&gt;Phys. Rev. Lett.&lt;/em&gt; &lt;strong&gt;2005,&lt;/strong&gt; &lt;em&gt;95&lt;/em&gt; (22), No. 226801. DOI: 10.1103/PhysRevLett.95.226801.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastEditorUserId="7" LastEditDate="2022-03-22T14:42:18.410" LastActivityDate="2022-03-22T14:42:18.410" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1548" PostTypeId="1" CreationDate="2020-07-17T12:46:12.707" Score="9" ViewCount="334" Body="&lt;p&gt;Studying magnetic systems, two frequently used approximations are the Heisenberg and Ising models (a discussion about these approximations can be read &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/659/24&quot;&gt;here&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{Heisenberg}&#xA;\hat{H}_H=-\sum_{\langle i j\rangle}J\hat{S}_i\hat{S}_j&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{Ising}&#xA;\hat{H}_I=-\sum_{\langle ij\rangle}J\hat{S}_i^z\hat{S}_j^z&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a theoretical method/way to determine realistic values for the &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; parameter?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="671" LastEditDate="2021-03-23T20:22:45.740" LastActivityDate="2023-08-10T07:00:24.327" Title="Is it possible to calculate/estimate the value of the J parameter to be used in the Heisenberg/Ising Hamiltonians?" Tags="|magnetism|model-hamiltonians|ising-model|spin-models|heisenberg-model|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1549" PostTypeId="1" CreationDate="2020-07-17T16:02:29.133" Score="9" ViewCount="1259" Body="&lt;p&gt;&lt;a href=&quot;https://www.materialsdesign.com/medea-software&quot; rel=&quot;noreferrer&quot;&gt;MedeA®&lt;/a&gt; is a software package developed by &lt;a href=&quot;https://www.materialsdesign.com/&quot; rel=&quot;noreferrer&quot;&gt;Materials Design Inc&lt;/a&gt;  for atomistic simulation of materials. According to official &lt;a href=&quot;https://www.vasp.at/faqs/&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt; VASP can only be acquired legally by either purchasing a license directly OR by purchasing a license from Materials Design Inc. Medea-VASP is built on VASP but all operations are carried out not by providing files such as INCAR, KPOINTS, POSCAR, and POTCAR, but via GUI.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/9dX6n.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9dX6n.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the pros and cons of using Medea-VASP over VASP directly?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-07-17T16:09:15.643" LastActivityDate="2020-07-19T17:13:03.427" Title="VASP vs MedeA-VASP" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1550" PostTypeId="1" AcceptedAnswerId="1907" CreationDate="2020-07-17T16:12:10.370" Score="10" ViewCount="291" Body="&lt;p&gt;I am interested in predicting the infrared spectra of bulk phase molecules, it seems that AIMD (ab initio molecular dynamics) is the current best approach. I have found a tutorial on using &lt;a href=&quot;https://brehm-research.de/files/spec_tutorial_2018.pdf&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt; to do exactly this, and I have seen a recent &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcb.0c05857?casa_token=0W5Rk5PVAYwAAAAA:8DVpT1xZpGWNI6kFTPawFNyqVApNT4EeuypkP0ClF3VtD_GznauGILf8gm0_m5fJ3fjeYNfKTKJLV6_9Mw&quot; rel=&quot;noreferrer&quot;&gt;publication&lt;/a&gt; for computing condensed phase infrared spectra. I'm not entirely sure how different condensed phase and bulk phase spectra would be (I guess this could be a bonus question; What's the difference between bulk phase and condensed phase infrared spectra).&lt;/p&gt;&#xA;&lt;p&gt;The mentioned above CP2K method seems to be very time consuming, I was wondering if there are other methods for doing these calculations?&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-07-17T16:28:42.210" LastActivityDate="2020-08-03T21:20:23.723" Title="What are some methods for modeling bulk phase infrared spectra?" Tags="|molecular-dynamics|ab-initio-calculations|cp2k|aimd|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1551" PostTypeId="1" CreationDate="2020-07-17T16:20:00.527" Score="23" ViewCount="1708" Body="&lt;p&gt;I am trying to derive the Slater-Koster equations (Table. 1 of Ref. 1) for the two-centre approximation of hopping integrals between atomic orbitals. I understand that Slater-Koster approximates the two centre hopping integral as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;E_{n,m} = \int{\psi^*_n (\textbf{r}-\textbf{R})H\psi_m (\textbf{r}) dV},\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;assuming that potential, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is spherically symmetric.&lt;/p&gt;&#xA;&lt;p&gt;I tried substituting spherical harmonics, &lt;span class=&quot;math-container&quot;&gt;$Y_{lm}$&lt;/span&gt; as the atomic orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi (\textbf{r})$&lt;/span&gt; but I am struggling to get to the result. First, I am not sure how to write the spherical harmonics &lt;span class=&quot;math-container&quot;&gt;$Y_{lm}$&lt;/span&gt; not centred at the origin. Then, I can't see how the integral would separate into two parts representing pi and sigma bonds.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know how to derive one of the Slater-Koster equations? For example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;E_{p_z, d_{x^2-y^2}} = \frac{1}{2}\sqrt{3}n(l^2-m^2) V_{pd\sigma} -n(l^2-m^2) V_{pd\pi},\tag{2}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$l,m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; are directional cosines of connecting vector &lt;span class=&quot;math-container&quot;&gt;$\textbf{R}$&lt;/span&gt; (i.e. &lt;span class=&quot;math-container&quot;&gt;$l=\sin{\beta}\cos{\alpha}=\frac{R_x}{R}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;References&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Slater, JC &amp;amp; Koster, GF, &amp;quot;Simplified LCAO Method for the Periodic Potential Problem&amp;quot; Physical Review (1954); link: &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.94.1498&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/pr/abstract/10.1103/PhysRev.94.1498&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1064" LastEditorUserId="5" LastEditDate="2020-07-31T21:31:29.900" LastActivityDate="2021-04-18T06:07:33.773" Title="Derivation of Slater-Koster equations" Tags="|electronic-structure|quantum-mechanics|tight-binding|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1552" PostTypeId="2" ParentId="1515" CreationDate="2020-07-17T17:25:08.143" Score="13" Body="&lt;h1&gt;USA: Facilities for High Throughput Computing (HTC)&lt;/h1&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Several other answers mention USA centers at national labs and NSF XSEDE. There's another NSF-funded project for high &lt;em&gt;throughput&lt;/em&gt; computing (HTC)*, versus traditional high &lt;em&gt;performance&lt;/em&gt; computing (HPC):&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;OSG (Open Science Grid)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://opensciencegrid.org/&quot; rel=&quot;noreferrer&quot;&gt;OSG&lt;/a&gt; is a distributed, &lt;a href=&quot;https://map.opensciencegrid.org/&quot; rel=&quot;noreferrer&quot;&gt;international network&lt;/a&gt; of computing facilities aimed at providing high throughput computing. Rather than having a large central system, they utilize the unused cycles of computers in their network (some of which are traditional HPC systems, whereas others are closer to commodity resources).&lt;/p&gt;&#xA;&lt;p&gt;Because OSG focuses on HTC across a distributed network, they have particular &lt;a href=&quot;https://opensciencegrid.org/about/computation/&quot; rel=&quot;noreferrer&quot;&gt;criteria&lt;/a&gt; about what sorts of jobs they can support. For example, parallelized parameter sweeps or image processing on discrete datasets would benefit from HTC/OSG, whereas jobs that share a large dataset or are otherwise tightly coupled wouldn't benefit much.&lt;/p&gt;&#xA;&lt;p&gt;Nonetheless, a lot of analyses can be broken into small, independent jobs to run opportunistically on the network, so they have a lot of &lt;a href=&quot;https://gracc.opensciencegrid.org/&quot; rel=&quot;noreferrer&quot;&gt;usage&lt;/a&gt; in the science communities.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;*Briefly, HTC differs from HPC in that HTC is focused on sustained execution of many discrete &amp;quot;jobs&amp;quot; over longer periods time (months/years), compared to the shorter time scales (seconds/days) for HPC-centric systems. For HTC, metrics like FLOPS or peak performance are not very relevant; instead, the amount of operations over a weeks/months/years is of interest. &lt;a href=&quot;https://research.cs.wisc.edu/htcondor/htc.html&quot; rel=&quot;noreferrer&quot;&gt;HTCondor&lt;/a&gt; has more about HTC, and is used in the OSG.&lt;/p&gt;&#xA;" OwnerUserId="1049" LastEditorUserId="5" LastEditDate="2020-07-19T02:06:22.980" LastActivityDate="2020-07-19T02:06:22.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1553" PostTypeId="2" ParentId="1541" CreationDate="2020-07-17T18:35:59.203" Score="12" Body="&lt;h3&gt;Why Bond Order?&lt;/h3&gt;&#xA;&lt;p&gt;Bond order isn't terribly useful to a computationalist directly; however, it can be  invaluable for translating Quantum Mechanical results into a framework thats readily understood by experimentalists.&lt;/p&gt;&#xA;&lt;p&gt;Experimental chemists tend to make predictions about material properties, reaction feasibility, molecular structure, etc. based on a combination of empirical heuristics (e.g. this synthesis route worked for a similar looking molecule, this type of reaction works better with less bulky ligands involved) and simplified, qualitative MO theory (e.g. &lt;a href=&quot;https://en.wikipedia.org/wiki/Ligand_field_theory&quot; rel=&quot;noreferrer&quot;&gt;Ligand Field theory&lt;/a&gt;). These simplified MO models give insight into the strength of intramolecular interactions and how these should change when different substituents are involved. They also allow for discussion of the symmetry of a given interaction and whether it favors/disfavors some desired outcome like ligand dissociation. These insights have led to general principles (&lt;a href=&quot;https://en.wikipedia.org/wiki/Pi_backbonding&quot; rel=&quot;noreferrer&quot;&gt;Pi backbonding&lt;/a&gt;,&lt;a href=&quot;https://en.wikipedia.org/wiki/Charge-transfer_complex#Metal-to-ligand_charge_transfer&quot; rel=&quot;noreferrer&quot;&gt;Charge transfer complexes&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Green%E2%80%93Davies%E2%80%93Mingos_rules&quot; rel=&quot;noreferrer&quot;&gt;Green-Davies-Mingos&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/18-electron_rule&quot; rel=&quot;noreferrer&quot;&gt;18-electron rule&lt;/a&gt;) that help to rationalize chemical behavior and predict new types of molecules and reactions.&lt;/p&gt;&#xA;&lt;p&gt;These simplified MO models basically correspond to a qualitatively produced minimal basis SCF calculation, so while they can be useful in broad strokes, there are bound to be some inaccuracies when they are applied in specific cases. Naturally, we can correct some of these misconceptions with higher level quantum calculations, but this isn't useful to the experimentalist unless we can also translate the results into the framework/heuristic that they are trying to use. These various bond order methods are all attempts to translate to QM results to this more understandable form. By being able to tell the chemist that say, Pi backdonation isn't occurring in some compound, or that using a more donating ligand increases the bond order, they can adjust their heuristics with that new information and come up with a different synthetic pathway or molecular structure to meet their goal.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Further reading&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Adam J. Bridgeman, Germán Cavigliasso, Luke R. Ireland, and Joanne Rothery J. Chem. Soc., Dalton Trans., 2001, 2095–2108&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h3&gt;Why Not Force Constants?&lt;/h3&gt;&#xA;&lt;p&gt;There is nothing strictly wrong with using force constants for this and there are some methods that use force constants to get a bond order. I think these methods have their place, but I'll just briefly enumerate some of the negatives of this approach.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Cost: For larger molecules/higher levels of theory, the cost of an optimization/frequency can greatly exceed that of the SCF. If you aren't interested in the frequencies for any other reason, it probably isn't worth incurring this extra cost.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Detail: The vibrations don't give as clear a picture of what is occurring electronically (e.g. symmetry, covalent v.s. ionic interaction), so they don't fit as well into the way that chemists tend to think about bonding (there are of course cases, like infrared/Raman spectroscopy, where these vibrational details are more important).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ambiguity: One of the difficult things with vibrational modes is they typically aren't localized to a particular bond, but are instead spread throughout the molecule. This can make it difficult to say which force constant, or combination of forces constants, describe the bond you are interested in. There are procedures to localize vibrational modes, but this just adds another layer of complexity, since these localized modes are coupled.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastEditorUserId="1380" LastEditDate="2021-06-28T08:05:19.677" LastActivityDate="2021-06-28T08:05:19.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1554" PostTypeId="1" AcceptedAnswerId="1559" CreationDate="2020-07-17T21:04:34.867" Score="17" ViewCount="455" Body="&lt;p&gt;I am studying the transition metal dichalcogenides (TMDCs) and one of the applications that these materials have is their use in &lt;a href=&quot;https://en.wikipedia.org/wiki/Valleytronics#:%7E:text=Valleytronics%20is%20the%20technology%20of,coined%20in%20analogy%20to%20spintronics.&quot; rel=&quot;nofollow noreferrer&quot;&gt;valleytronics&lt;/a&gt;. Valleytronics is related to the magnetic moment, Berry curvature, the spatial inversion symmetries, and the time-reversal symmetry.&lt;/p&gt;&#xA;&lt;p&gt;According to the time-reversal symmetry, Berry's curvature and magnetic moment are odd functions (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{\Omega(-k)}=-\mathbf{\Omega(k)}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m(-k)}=-\mathbf{m(k)}$&lt;/span&gt;).&#xA;According to the symmetry of spatial inversion, the functions are even (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{\Omega(-k)}=\mathbf{\Omega(k)}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m(-k)}=\mathbf{m(k)}$&lt;/span&gt;). Therefore, for valleytronics to exist, there does not have to be inversion symmetry, which occurs with a single-layer TMDCs.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How can I demonstrate that the functions are odd according to the &lt;strong&gt;time reversal symmetry&lt;/strong&gt; and even according to the &lt;strong&gt;spatial inversion symmetry&lt;/strong&gt;?&lt;/li&gt;&#xA;&lt;li&gt;What is the &lt;strong&gt;physical interpretation&lt;/strong&gt; of Berry's curvature and Berry's phase?&lt;/li&gt;&#xA;&lt;li&gt;H̶o̶w̶ ̶t̶o̶ ̶d̶e̶d̶u̶c̶e̶ ̶B̶e̶r̶r̶y̶'̶s̶ ̶e̶q̶u̶a̶t̶i̶o̶n̶s̶?̶ (Maybe a question for a new thread, since ProfM already answered 2 of the above and I answered the other).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="1218" LastEditDate="2021-04-04T09:09:20.820" LastActivityDate="2021-04-04T09:09:20.820" Title="Berry's curvature and magnetic moment in TMDCs" Tags="|transition-metals|berry-phase|2d-lattice|dichalcogenides|valleytronics|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1555" PostTypeId="2" ParentId="1535" CreationDate="2020-07-17T21:56:00.713" Score="12" Body="&lt;h2&gt;Elk&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free, and can be redistributed or modified under the terms of GPU General Public Licesence.&lt;/li&gt;&#xA;&lt;li&gt;Well explained &lt;a href=&quot;http://elk.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;on this webpage&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Well documented &lt;a href=&quot;http://elk.sourceforge.net/elk.pdf&quot; rel=&quot;noreferrer&quot;&gt;in this PDF file&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Interacts with the following codes:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/rohkeaID/elk-w90-improved&quot; rel=&quot;noreferrer&quot;&gt;Wannier90&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Phonopy&lt;/li&gt;&#xA;&lt;li&gt;NOMAD&lt;/li&gt;&#xA;&lt;li&gt;Libxc&lt;/li&gt;&#xA;&lt;li&gt;ASE&lt;/li&gt;&#xA;&lt;li&gt;DGrid&lt;/li&gt;&#xA;&lt;li&gt;Elk optics Analyzer&lt;/li&gt;&#xA;&lt;li&gt;PyProcar&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;Advertised in a few places as being focused strongly on being simple and easy to develop.&lt;/li&gt;&#xA;&lt;li&gt;Written in FORTRAN 2003 and an advertised strength is that it's all written in one language.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Finally, you said that you were particularly interested in codes that invite developers, and this exactly the case with Elk &amp;quot;Groups and individuals are actively encouraged to develop and release their own specialised versions of the Elk code under the GPL&amp;quot;. The Wannier90 interface mentioned above, was developed by people in Sweden and Russia, who were not part of the original Elk team.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-17T21:56:00.713" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1556" PostTypeId="1" AcceptedAnswerId="1841" CreationDate="2020-07-17T21:56:08.557" Score="14" ViewCount="283" Body="&lt;p&gt;When we think about computers and computing today, almost invariably we think about &lt;a href=&quot;https://en.wikipedia.org/wiki/Computer#Digital_computers&quot; rel=&quot;noreferrer&quot;&gt;digital computers&lt;/a&gt;, the ever-present objects today. But reading this question in the Chemistry stackexchange, &lt;a href=&quot;https://chemistry.stackexchange.com/q/60502/89908&quot;&gt;How are the atomic orbitals for multi electron atoms obtained?&lt;/a&gt;, there's a &lt;a href=&quot;https://chemistry.stackexchange.com/a/60517/89908&quot;&gt;great answer&lt;/a&gt; that delves a bit into the history of &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_mechanics&quot; rel=&quot;noreferrer&quot;&gt;quantum theory&lt;/a&gt; and matter modeling, with this interesting picture, reminding us that it wasn't always like that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1UpNa.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1UpNa.jpg&quot; alt=&quot;Douglas Hartree (left) and Arthur Porter (right) with the meccano differential analyzer.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That photo shows matter modeling pioneers, &lt;a href=&quot;https://en.wikipedia.org/wiki/Douglas_Hartree&quot; rel=&quot;noreferrer&quot;&gt;Douglas Hartree&lt;/a&gt; and Arthur Porter, together with a computer they built themselves to solve differential equations and study quantum-mechanical systems, in the 1930s, generating tables like these:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sRcIy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sRcIy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That was no ordinary computer, at least not in the sense we use the word today, because it predates digital machines like &lt;a href=&quot;https://en.wikipedia.org/wiki/ENIAC&quot; rel=&quot;noreferrer&quot;&gt;ENIAC&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Colossus_computer&quot; rel=&quot;noreferrer&quot;&gt;Colossus&lt;/a&gt; by several years. It was an &lt;a href=&quot;https://en.wikipedia.org/wiki/Analog_computer&quot; rel=&quot;noreferrer&quot;&gt;analog computer&lt;/a&gt;, a &lt;a href=&quot;https://en.wikipedia.org/wiki/Differential_analyser&quot; rel=&quot;noreferrer&quot;&gt;differential analyser&lt;/a&gt; built from parts of a children toy invented in 1898, called &lt;a href=&quot;https://en.wikipedia.org/wiki/Meccano&quot; rel=&quot;noreferrer&quot;&gt;Meccano&lt;/a&gt;, kind of a 19th century &lt;a href=&quot;https://en.wikipedia.org/wiki/Lego&quot; rel=&quot;noreferrer&quot;&gt;Lego&lt;/a&gt;. So Hartree and Porter pulled the equivalent to someone today building a working supercomputer from scratch, out of lego blocks, and using it successfully to do groundbreaking research. It was surely an impressive feat at the time. They were real-life &lt;a href=&quot;https://en.wikipedia.org/wiki/MacGyver&quot; rel=&quot;noreferrer&quot;&gt;McGyvers&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Before the digital revolution, analog computers like the one used by Hartree were used to tackle all sorts of hard problems you couldn't calculate by hand, like &lt;a href=&quot;https://en.wikipedia.org/wiki/Norden_bombsight&quot; rel=&quot;noreferrer&quot;&gt;ammunition trajectories&lt;/a&gt; and even to &lt;a href=&quot;https://www.npr.org/sections/ed/2014/10/22/356937347/the-slide-rule-a-computing-device-that-put-a-man-on-the-moon&quot; rel=&quot;noreferrer&quot;&gt;put men in the moon&lt;/a&gt; and bring them back safely. But as time passed and digital programmable devices were developed, and then became small and cheaper, analog computers became a road not taken in science, mostly forgotten, a footnote in history.&lt;/p&gt;&#xA;&lt;p&gt;Yet, I could find a paper (1) from the 70s showing how to solve the particle in a finite potential well with them. Also, once I watched &lt;a href=&quot;https://youtu.be/JLT6omWrvIw&quot; rel=&quot;noreferrer&quot;&gt;a talk&lt;/a&gt; by late physicist &lt;a href=&quot;https://en.wikipedia.org/wiki/Freeman_Dyson&quot; rel=&quot;noreferrer&quot;&gt;Freeman Dyson&lt;/a&gt; where he says it was proven (2, 3) in 1981 that some numbers are analog-computable but not Turing-computable, and thus analog computers are more powerful than digital computers, at least in principle.&lt;/p&gt;&#xA;&lt;p&gt;That makes me wonder, the use of Analog Computers really died out in Matter Modelling, or there's still people researching their use today, to tackle problems in the field?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/ed050p289&quot; rel=&quot;noreferrer&quot;&gt;Marron, Michael T. “Analog Computer Solution of a Particle in a Finite Well. A Physical Chemistry Experiment”. Journal of Chemical Education, vol. 50, no 4, abril de 1973, p. 289. DOI.org (Crossref), doi:10.1021/ed050p289.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://core.ac.uk/reader/81930022&quot; rel=&quot;noreferrer&quot;&gt;Richards, Ian. The wave equation with computable initial data such that its unique solution is not computable. core.ac.uk, https://core.ac.uk/reader/81930022. Acessed jul 17, 2020.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.worldscientific.com/doi/abs/10.1142/9789814602877_0007&quot; rel=&quot;noreferrer&quot;&gt;Dyson, Freeman J. Birds and Frogs: Selected Papers of Freeman Dyson, 1990–2014. WORLD SCIENTIFIC, 2015. DOI.org (Crossref), doi:10.1142/9158.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-07-20T04:19:23.890" LastActivityDate="2020-10-27T00:27:58.657" Title="Analog computing in matter modeling today: Any applications?" Tags="|high-performance-computing|hartree-fock|history|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1557" PostTypeId="1" AcceptedAnswerId="1558" CreationDate="2020-07-18T03:20:23.433" Score="21" ViewCount="1697" Body="&lt;p&gt;This question is inspired from a &lt;a href=&quot;https://mathematica.stackexchange.com/q/18393&quot;&gt;post&lt;/a&gt; in another SE. Many users these days use density functional theory codes as 'black boxes' and hence its natural to expect that they would have made many mistakes when first learning.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the common pitfalls encountered by new users of density functional theory?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-18T16:06:36.707" LastActivityDate="2020-07-23T07:11:27.607" Title="What are the pitfalls for new users of DFT?" Tags="|density-functional-theory|one-topic-per-answer|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1558" PostTypeId="2" ParentId="1557" CreationDate="2020-07-18T07:25:59.563" Score="18" Body="&lt;p&gt;Well, the first pitfall would be &lt;strong&gt;assuming that density functional theory calculations are non-ambiguous&lt;/strong&gt;, when the reality is that density functional theory can be implemented in a number of different ways ;)&lt;/p&gt;&#xA;&lt;p&gt;There are a multitude of ways one can screw up by not setting up the calculation properly:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;insufficent accuracy of quadrature&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;insufficient numerical representation&lt;/strong&gt; (basis set in general, k-point sampling in periodic calculations)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;non-applicability of the model&lt;/strong&gt; e.g. problems with strong correlation, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It is hard to make anything idiotproof, since idiots tend to be surprisingly inventive :D&lt;/p&gt;&#xA;&lt;p&gt;The better question is how to run the calculations as well as possible... and here the rule of thumb is generally to &lt;strong&gt;check that the calculation is converged with respect to ALL numerical parameters&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="88" LastEditDate="2020-07-23T07:11:27.607" LastActivityDate="2020-07-23T07:11:27.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1559" PostTypeId="2" ParentId="1554" CreationDate="2020-07-18T09:06:55.843" Score="16" Body="&lt;p&gt;The Berry curvature is defined as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Omega_{\mu\nu}(\mathbf{k})=\partial_{\mu}A_{\nu}(\mathbf{k})-\partial_{\nu}A_{\mu}(\mathbf{k}),&#xA;\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$A_{\mu}(\mathbf{k})=\langle u_{\mathbf{k}}|i\partial_{\mu}u_{\mathbf{k}}\rangle$&lt;/span&gt; is the Berry connection, &lt;span class=&quot;math-container&quot;&gt;$|u_{\mathbf{k}}\rangle$&lt;/span&gt; is a Bloch state, and &lt;span class=&quot;math-container&quot;&gt;$\partial_\mu\equiv \frac{\partial}{\partial k_\mu}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mu,\nu=x,y,z$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Invesion symmetry.&lt;/strong&gt; Under inversion, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}\to-\mathbf{k}$&lt;/span&gt;, so that applying the inversion operation &lt;span class=&quot;math-container&quot;&gt;$\mathcal{I}$&lt;/span&gt; on a Bloch state gives &lt;span class=&quot;math-container&quot;&gt;$&#xA;\mathcal{I}|u_{\mathbf{k}}\rangle=|u_{-\mathbf{k}}\rangle$&lt;/span&gt;. If the system is invariant under inversion, then &lt;span class=&quot;math-container&quot;&gt;$|u_{\mathbf{k}}\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|u_{-\mathbf{k}}\rangle$&lt;/span&gt; must be the same state up to a global phase, so that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathcal{I}|u_{\mathbf{k}}\rangle=e^{i\varphi_{\mathbf{k}}}|u_{\mathbf{k}}\rangle\Longrightarrow |u_{-\mathbf{k}}\rangle=e^{i\varphi_{\mathbf{k}}}|u_{\mathbf{k}}\rangle.\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the Berry connection, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{I}A_{\mu}(\mathbf{k})=A_{\mu}(-\mathbf{k})$&lt;/span&gt;. If the system has inversion symmetry, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{eqnarray}&#xA;A_{\mu}(-\mathbf{k})&amp;amp;=&amp;amp;\langle u_{-\mathbf{k}}|i\partial_{\mu}u_{-\mathbf{k}}\rangle \tag{3}\\&#xA;&amp;amp;=&amp;amp; \langle u_{\mathbf{k}}|e^{-i\varphi_{\mathbf{k}}}i\partial_{\mu}\left(e^{i\varphi_{\mathbf{k}}}u_{\mathbf{k}}\right)\rangle \tag{4}\\ &#xA;&amp;amp;=&amp;amp; \langle u_{\mathbf{k}}|e^{-i\varphi_{\mathbf{k}}}ie^{i\varphi_{\mathbf{k}}}\partial_{\mu}u_{\mathbf{k}}\rangle + \langle u_{\mathbf{k}}|e^{-i\varphi_{\mathbf{k}}}i^2e^{i\varphi_{\mathbf{k}}}u_{\mathbf{k}}\rangle\partial_{\mu}\varphi_{\mathbf{k}}\tag{4} \\&#xA;&amp;amp;=&amp;amp; \langle u_{\mathbf{k}}|i\partial_{\mu}u_{\mathbf{k}}\rangle -\partial_{\mu}\varphi_{\mathbf{k}} \tag{5}\\&#xA;&amp;amp;=&amp;amp;A_{\mu}(\mathbf{k})-\partial_{\mu}\varphi_{\mathbf{k}},\tag{6}&#xA;\end{eqnarray}&#xA;$$&lt;/span&gt;&#xA;where in the second line I used the result for the Bloch state in a system with inversion symmetry, and in the third line the chain rule for differentiation. This result means that for a system that is invariant under inversion, then &lt;span class=&quot;math-container&quot;&gt;$A_{\mu}(\mathbf{k})$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A_{\mu}(-\mathbf{k})$&lt;/span&gt; differ at most by a gauge transformation.&lt;/p&gt;&#xA;&lt;p&gt;We are now ready to look at the Berry curvature. Under inversion, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{I}\Omega_{\mu\nu}(\mathbf{k})=\Omega_{\mu\nu}(-\mathbf{k}$&lt;/span&gt;). If the system has inversion symmetry, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{eqnarray}&#xA;\Omega_{\mu\nu}(-\mathbf{k})&amp;amp;=&amp;amp;\partial_{\mu}A_{\nu}(-\mathbf{k})-\partial_{\nu}A_{\mu}(-\mathbf{k}) \tag{7}\\&#xA;&amp;amp;=&amp;amp;\partial_{\mu}\left(A_{\nu}(\mathbf{k})-\partial_{\nu}\varphi_{\mathbf{k}}\right)-\partial_{\nu}\left(A_{\mu}(\mathbf{k})-\partial_{\mu}\varphi_{\mathbf{k}}\right) \tag{8}\\&#xA;&amp;amp;=&amp;amp;\partial_{\mu}A_{\nu}(\mathbf{k})-\partial_{\nu}A_{\mu}(\mathbf{k})-\partial_{\mu}\partial_{\nu}\varphi_{\mathbf{k}}+\partial_{\nu}\partial_{\mu}\varphi_{\mathbf{k}} \tag{9}\\&#xA;&amp;amp;=&amp;amp;\partial_{\mu}A_{\nu}(\mathbf{k})-\partial_{\nu}A_{\mu}(\mathbf{k}) \tag{10}\\&#xA;&amp;amp;=&amp;amp;\Omega_{\mu\nu}(\mathbf{k})\tag{11},&#xA;\end{eqnarray}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where in the second line I used the result for the Berry connection in a system with inversion symmetry. This proves that for a system with inversion symmetry, &lt;span class=&quot;math-container&quot;&gt;$\Omega_{\mu\nu}(\mathbf{k})=\Omega_{\mu\nu}(-\mathbf{k})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Time reversal symmetry.&lt;/strong&gt; You can use an analogous procedure (I encourage you to try) to prove that for a time reversal invariant system, &lt;span class=&quot;math-container&quot;&gt;$\Omega_{\mu\nu}(\mathbf{k})=-\Omega_{\mu\nu}(-\mathbf{k})$&lt;/span&gt;. All you need to know is how the time reversal operator acts on a Bloch state, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}|u_{\mathbf{k}}\rangle=|u_{\mathbf{-k}}^{\ast}\rangle$&lt;/span&gt;, and the rest of the proof proceeds in the same way.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Physical interpretation.&lt;/strong&gt; Berry phase-like quantities look at the evolution of Bloch states at neighbouring &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in the Brillouin zone. As an example, the Berry connection is looking at the overlap between a state &lt;span class=&quot;math-container&quot;&gt;$|u_{\mathbf{k}}\rangle$&lt;/span&gt; and a state infinitessimally away from it, &lt;span class=&quot;math-container&quot;&gt;$\partial_{\mu}|u_{\mathbf{k}}\rangle$&lt;/span&gt;. As such, they are useful for calculation properties that depend on the structure of the Block states across the Brillouin zone. A well-known example is the calculation of topological invariants of materials, which measure the &amp;quot;twists&amp;quot; that the electronic wave function has when crossing the Brillouin zone. I am not familiar with applications in valleytronics, so will leave that for someone more knowledgeable.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Futher reading.&lt;/strong&gt; An excellent book to learn about Berry phase-like quantities and applications (modern theory of polarization, topological materials, etc.) is David Vanderbilt's &lt;a href=&quot;https://www.cambridge.org/core/books/berry-phases-in-electronic-structure-theory/DDD71CA4FE9AF5F3A2FB300E602F394A&quot; rel=&quot;noreferrer&quot;&gt;book&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-19T18:20:30.190" LastActivityDate="2020-07-19T18:20:30.190" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="1560" PostTypeId="5" CreationDate="2020-07-18T09:09:37.483" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-07-18T09:09:37.483" LastActivityDate="2020-07-18T09:09:37.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1561" PostTypeId="4" CreationDate="2020-07-18T09:09:37.483" Score="0" Body="Questions relating to properties that depend on Berry phase-like quantities " OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-18T13:40:53.700" LastActivityDate="2020-07-18T13:40:53.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1562" PostTypeId="2" ParentId="1557" CreationDate="2020-07-18T10:49:43.723" Score="20" Body="&lt;h2&gt;Use of outdated methods&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1558/794&quot;&gt;Susi Lehtola&lt;/a&gt; has given a good answer, to which I would add: &lt;strong&gt;Do not use outdated methods&lt;/strong&gt;. The fact that B3LYP/6-31G* calculations&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; are fast and ubiquitous is exactly &lt;em&gt;zero&lt;/em&gt; justification to run them for publication-level work. Take care to evaluate more than one functional and search for benchmark studies of related systems/properties to be able to have more confidence in your calculation. In the realm of molecular calculations, one specifically needs to understand the influence of the amount of Fock exchange on the property under consideration. Finally, a &lt;strong&gt;modern&lt;/strong&gt; dispersion/van-der-Waals correction is typically a simple addon to your calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; a not-so-random example&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-07-19T00:45:45.967" LastActivityDate="2020-07-19T00:45:45.967" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1563" PostTypeId="1" CreationDate="2020-07-18T18:01:47.510" Score="12" ViewCount="1427" Body="&lt;p&gt;I am performing a molecular dynamics simulation and I have calculated the velocity autocorrelation function (VACF), &lt;span class=&quot;math-container&quot;&gt;$\psi (t)$&lt;/span&gt; and mean square displacement, &lt;span class=&quot;math-container&quot;&gt;$\langle (\Delta r)^2 \rangle$&lt;/span&gt;. In my simulation, I have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; particles interacting with the Lennard-Jones potential function, and I am stepping forward in time from &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, in steps of &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From &lt;a href=&quot;https://ocw.mit.edu/courses/nuclear-engineering/22-103-microscopic-theory-of-transport-fall-2003/lecture-notes/lec3.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, I see that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ D = v_0^2 \int_0^{\infty} \psi(t) \mathrm{d}t$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8cTE4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8cTE4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt; is the thermal velocity.&lt;/p&gt;&#xA;&lt;p&gt;My question is, how do I calculate &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; if I only know values of &lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi(t)$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$[0,T]$&lt;/span&gt; (rather than up to &lt;span class=&quot;math-container&quot;&gt;$t=\infty$&lt;/span&gt;)? &lt;strong&gt;Is there a better way to do this?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any advice would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1070" LastEditorUserId="5" LastEditDate="2020-07-18T20:13:19.640" LastActivityDate="2020-09-15T22:32:16.633" Title="Calculating diffusion coefficient from Mean Squared Displacement" Tags="|molecular-dynamics|numerical-convergence|statistical-thermodynamics|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1565" PostTypeId="2" ParentId="1557" CreationDate="2020-07-18T22:55:52.687" Score="13" Body="&lt;h2&gt;Asymmetry of the grid&lt;/h2&gt;&#xA;&lt;p&gt;If you have done calculations using wavefunction based methods (e.g. Hartree-Fock, Moller-Plesset Perturbation Theory, Coupled Cluster) you are probably already aware that the result depends on the choice of basis set. While DFT can seem very similar, it has an additional dependence that isn't as commonly discussed: the exchange-correlation integrals are evaluated on a grid.&lt;/p&gt;&#xA;&lt;p&gt;The use of a grid can lead to surprising effects that you don't see with wavefunction based methods. For example, many DFT grids aren't rotationally invariant, meaning they can give a different energy for the same molecule in a different orientation. This has proven problematic for studies looking to compare the energy of different conformers without accounting for differences in orientation &lt;a href=&quot;https://chemrxiv.org/articles/Popular_Integration_Grids_Can_Result_in_Large_Errors_in_DFT-Computed_Free_Energies/8864204/4&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;. These errors can even propagate through to property calculations, such as NMR, where the most accurate analysis protocols depend on a conformational averaging. &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/mrc.4940&quot; rel=&quot;noreferrer&quot;&gt;[2]&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-19T13:21:37.597" LastActivityDate="2020-07-19T13:21:37.597" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1566" PostTypeId="1" AcceptedAnswerId="1614" CreationDate="2020-07-18T23:56:55.727" Score="18" ViewCount="406" Body="&lt;p&gt;Similar to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1568/5&quot;&gt;What are the types of SCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;What are the types of Quantum Monte Carlo?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1521/5&quot;&gt;What are the types of pseudopotentials?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1513/5&quot;&gt;What are the types of DFT?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/5&quot;&gt;What are the types of charge analysis?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/901/5&quot;&gt;What are the types of bond orders?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Let's be the first resource that explains the following in &lt;strong&gt;up to 3 paragraphs&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;UCASSCF&lt;/li&gt;&#xA;&lt;li&gt;RASSCF [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1569/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;GASSCF&lt;/li&gt;&#xA;&lt;li&gt;LASSCF [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1614/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;FCIQMC-SCF&lt;/li&gt;&#xA;&lt;li&gt;MRCI&lt;/li&gt;&#xA;&lt;li&gt;MR-ACPF&lt;/li&gt;&#xA;&lt;li&gt;MR-AQCC&lt;/li&gt;&#xA;&lt;li&gt;DMRG-SCF&lt;/li&gt;&#xA;&lt;li&gt;SHCI-SCF&lt;/li&gt;&#xA;&lt;li&gt;SA-CASSCF&lt;/li&gt;&#xA;&lt;li&gt;DOLO-SCF [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1833/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;DW-CASSCF&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For FCIQMC-SCF, DMRG-SCF, and SHCI-SCF, instead of explaining what FCQIMC, DMRG and SHCI are, please instead say which programs implement these methods, and anything special that had to be done in order for these to work (for example SHCI-SCF can be done with variational SHCI or with SHCI-PT2, and the one with PT2 is not variational, so the authors had to do a little extra to make it work).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="52" LastEditDate="2020-09-21T16:43:48.570" LastActivityDate="2020-09-21T16:55:49.513" Title="What are the types of MCSCF?" Tags="|reference-request|one-topic-per-answer|self-consistent-field|casscf|multi-reference|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1567" PostTypeId="2" ParentId="1563" CreationDate="2020-07-18T23:58:30.047" Score="8" Body="&lt;p&gt;As with all MD simulations, you have to assume (often wrongly) convergence with finite time. This is fairly easy to do with autocorrelation functions though, because you know that once they become negative, you are already in the random fluctuation (i.e. uncorrelated noise) zone and this is the point where you can stop. This is slightly trickier in some cases still, especially for unthermostatted systems, where you can have deterministic correlated oscillatory behaviour around zero, so this metric is not very good and I am not sure there is a better alternative than just visually inspecting the plot to pick a suitable cutoff. This won't be a problem, since you will typically sample for a longer time than your decorrelation time, mostly because you need multiple datapoints for autocorrelation function convergence. Finally, in some really pathological cases (e.g. in 1D systems), you can get decay to a constant value which is substantially larger than 0. Thankfully, this behaviour isn't very common at all but it is still worth knowing that it is possible (and in these cases I don't even know how one calculates a diffusion coefficient or whether doing so makes any sense in the first place).&lt;/p&gt;&#xA;&lt;p&gt;The problem with autocorrelation functions is that this oscillation (even the random one) can still impact your results depending on where you decide to stop and that's why I would say that calculating diffusion coefficients with mean-square displacement is much more robust, because you usually get an almost perfect straight line, whose slope you can accurately obtain from linear regression and this is pretty robust to noise, number of datapoints or cutoff choice (!), certainly more so than integrating the autocorrelation function. In cases where you don't get a straight line (e.g. superdiffusion or subdiffusion), this actually tells you that there is something else going on and calculating diffusion coefficients might need additional assumptions for this system. In any case, you get more information using the RMSD method.&lt;/p&gt;&#xA;&lt;p&gt;So the bottom line is: if you have a choice between integrating and not integrating, (almost) always choose a method that doesn't rely on integration and if this is for coursework, don't be too worried if the VACF method gives you noisier results (although it's always a good idea to be completely sure you aren't doing anything wrong).&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="710" LastEditDate="2020-07-19T00:12:12.570" LastActivityDate="2020-07-19T00:12:12.570" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1568" PostTypeId="1" AcceptedAnswerId="1589" CreationDate="2020-07-19T00:19:39.370" Score="19" ViewCount="1421" Body="&lt;p&gt;&lt;strong&gt;Many of us know the most common types of SCF&lt;/strong&gt; &lt;br&gt;&#xA;(though &lt;a href=&quot;https://en.wikipedia.org/wiki/Wikipedia:Stack_Exchange_is_eating_our_lunch_&quot; rel=&quot;nofollow noreferrer&quot;&gt;we can do better than Wikipedia&lt;/a&gt; at explaining them):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;RHF (Restricted Hartree-Fock), RKS (Restricted Kohn-Sham) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1573/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;UHF (Unrestricted Hartree-Fock), UKS (Unrestricted Kohn-Sham) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1592/794&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;ROHF (Restricted Open-Shell Hartree-Fock), ROKS (Restricted open-shell KS)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;But there's also less commonly known (and more powerful!) single-reference SCF methods:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;GHF (Generalized Hartree-Fock), GKS (Generalized Kohn-Sham) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1571/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4705280&quot; rel=&quot;nofollow noreferrer&quot;&gt;PHF&lt;/a&gt; (Projected Hartree-Fock)&lt;/li&gt;&#xA;&lt;li&gt;DHF (Dirac-Hartree-Fock) or Dirac-Fock [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1589/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;KR-DHF (Kramers Restricted DHF)&lt;/li&gt;&#xA;&lt;li&gt;KU-DHF (Kramers Unrestricted DHF)&lt;/li&gt;&#xA;&lt;li&gt;SOSCF (Second-order Hartree-Fock)&lt;/li&gt;&#xA;&lt;li&gt;TD-SCF (Time-dependent SCF)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=LyvqjepHrnI&quot; rel=&quot;nofollow noreferrer&quot;&gt;Complex GHF&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.122.1012&quot; rel=&quot;nofollow noreferrer&quot;&gt;GHF&lt;/a&gt; (Generalized HF of Valatin in 1961).&lt;/li&gt;&#xA;&lt;li&gt;GVB (Generalized Valence Bond) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2272/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Let's be the resource where people can learn these methods succintly!&lt;/strong&gt; &lt;br&gt;&#xA;(3 or fewer paragraphs please).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;Multi-configurational SCF methods can instead go here.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Note that RHF &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.470488&quot; rel=&quot;nofollow noreferrer&quot;&gt;sometimes&lt;/a&gt; stands for Roothan-Hartree-Fock.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-14T16:54:19.747" LastActivityDate="2020-09-14T16:54:19.747" Title="What are the types of SCF?" Tags="|reference-request|ab-initio-calculations|one-topic-per-answer|self-consistent-field|hartree-fock|" AnswerCount="5" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1569" PostTypeId="2" ParentId="1566" CreationDate="2020-07-19T04:03:28.127" Score="7" Body="&lt;h2&gt;RASSCF: Restricted Active Space SCF&lt;/h2&gt;&#xA;&lt;p&gt;In a Complete Active Space (CAS) calculation, one chooses a set of occupied/virtual orbitals (the active space) from an initial Slater determinant and forms additional configurations from all the possible rearrangements (hence, complete active space) of the electrons among those orbitals. As the name suggests, a RAS calculation defines an active space of orbitals, but restricts the type of rearrangements that are made. This is typically done by subdividing the active space in to three parts: R1, R2, R3.&lt;/p&gt;&#xA;&lt;p&gt;R2 is similar to the complete active space and all possible rearrangements among these orbitals are used. R1 is a set of initially occupied orbitals which is restricted to have at most &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; holes, where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is some parameter set by the user. R3 is a set of initially virtual orbitals, restricted to have at most &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; occupancies in the generated configurations. In the limit where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; are the size of R1 and R3 respectively, the calculation becomes a CASSCF.&lt;/p&gt;&#xA;&lt;p&gt;RASSCF is useful for situations where one would like to use CASSCF (e.g. degenerate ground states from SCF, modeling bond breaking), but where the system size is too large for CASSCF to be feasible.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.molcas.org/documentation/manual/node107.html&quot; rel=&quot;noreferrer&quot;&gt;OpenMOLCAS&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.molpro.net/info/release/doc/quickstart/node19.html&quot; rel=&quot;noreferrer&quot;&gt;Molpro&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.univie.ac.at/columbus/docs_COL70/columbus_molcas_link.html&quot; rel=&quot;noreferrer&quot;&gt;Columbus&lt;/a&gt; (via MOLCAS)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-07-19T04:47:43.810" LastActivityDate="2020-07-19T04:47:43.810" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1570" PostTypeId="1" AcceptedAnswerId="1983" CreationDate="2020-07-19T04:24:52.270" Score="11" ViewCount="121" Body="&lt;p&gt;I have an old TORQUE cluster (out of support) with 4 nodes running on Cent OS 6 and I am having trouble using the latest versions of Matter Modelling software. I recently came across &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1427/88&quot;&gt;Quantum Mobile Virtual Machine&lt;/a&gt; and installed it on the head-node. Now I can run calculations in the head node using the virtual machine, which is convenient because it comes with lots of software pre-installed and I don't have to tamper with my OS.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can I use the virtual machine to run calculations on other nodes using any scheduler?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-19T04:50:55.730" LastActivityDate="2020-08-13T01:05:13.103" Title="Which schedulers are compatible with a virtual machine?" Tags="|high-performance-computing|job-scheduler|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1571" PostTypeId="2" ParentId="1568" CreationDate="2020-07-19T04:39:21.827" Score="11" Body="&lt;h2&gt;GHF: Generalized Hartree Fock&lt;/h2&gt;&#xA;&lt;p&gt;In Restricted Hartree-Fock (RHF), the molecular orbitals are constructed as pairs, with a single spacial function being used to describe both an &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spin electron. Unrestricted Hartree-Fock (UHF) lifts this requirement, forming a unique set of MOs for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spin. &lt;strong&gt;Generalized Hartree-Fock takes this one step further and allows each MO to be an arbitrary linear combination of &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spin.&lt;/strong&gt; This makes the MOs expressible as &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Spinor&quot; rel=&quot;nofollow noreferrer&quot;&gt;spinors&lt;/a&gt;. RHF and UHF solutions can be seen as just special cases/subspaces of GHF solutions, which shows that the global minimum determined by GHF must be &lt;strong&gt;less than or equal to the global minimum of RHF/UHF&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;GHF ensures that the system wavefunction will be a continuous function of nuclear position, which is useful in the context of &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/7&quot;&gt;ab initio molecular dynamics&lt;/a&gt; or modeling bond breaking. GHF also has a tendency to produce a unique global minimum, making wavefunction optimizations less complicated. One &lt;strong&gt;drawback&lt;/strong&gt; of GHF solutions is that the true wavefunction should be an eigenfunction of &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt;, but this is not generally true for GHF [1]. GHF also has applications in studying magnetic phenomena, as it allows you to represent spin configurations that are not possible with RHF or UHF (e.g. noncollinear spins) [2].&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://sunqm.github.io/pyscf/_modules/pyscf/scf/ghf.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF&lt;/a&gt; (also allows GKS: Generalized Kohn-Sham)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gaussian.com/overlay3/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian&lt;/a&gt; (at least as an internal option, IOp(3/116=7, 15, or 19) for real, complex, or spinor basis)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.q-chem.com/qchem-website/manual/qchem51_manual/sect-gen_scfman.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QChem&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.chronusquantum.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chronus Quantum&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Bibliography:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Sharon Hammes-Schiffer and Hans C. Andersen J. Chem. Phys., Vol. 99, No. 3, 1 August 1993&lt;/li&gt;&#xA;&lt;li&gt;Feizhi Ding, Joshua J. Goings, Michael J. Frisch, and Xiaosong Li J.Chem.Phys. 141, 214111 (2014)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="1170" LastEditDate="2020-09-14T16:53:58.423" LastActivityDate="2020-09-14T16:53:58.423" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1572" PostTypeId="1" AcceptedAnswerId="1574" CreationDate="2020-07-19T06:56:06.613" Score="21" ViewCount="585" Body="&lt;p&gt;In the spirit of a succint answer (3 paragraphs maximum) to create a useful resource, what are the types of excited state calculation available for solids? Please add to the list:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Quasiparticle excitations&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;DFT: density functional theory&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;SCF [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1574/5_&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Constrained DFT&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;GW&lt;/em&gt;: Many-body perturbation theory in the &lt;em&gt;GW&lt;/em&gt; approximation&lt;/li&gt;&#xA;&lt;li&gt;VMC: Variational Quantum Monte Carlo&lt;/li&gt;&#xA;&lt;li&gt;DMC: Diffusion Quantum Monte Carlo&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Two-particle excitations&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;TDDFT: Time-dependent density functional theory&lt;/li&gt;&#xA;&lt;li&gt;BSE: Bethe-Salpeter equation&lt;/li&gt;&#xA;&lt;li&gt;VMC: Variational Quantum Monte Carlo&lt;/li&gt;&#xA;&lt;li&gt;DMC: Diffusion Quantum Monte Carlo&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-07-19T17:04:43.933" LastActivityDate="2021-01-03T05:38:16.847" Title="What methods are available for excited state calculations in solids?" Tags="|density-functional-theory|one-topic-per-answer|td-dft|gw-bse|excited-states|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1573" PostTypeId="2" ParentId="1568" CreationDate="2020-07-19T13:57:59.693" Score="9" Body="&lt;h2&gt;RHF: Restricted Hartree-Fock / RKS: Restricted Kohn-Sham&lt;/h2&gt;&#xA;&lt;p&gt;Restricted Hartree-Fock (RHF) is a self-consistent field approach: a mean-field approximation to the electronic, non-relativistic Schrödinger equation. The electron-electon interaction is modeled as a field influencing all electrons in the system, which are otherwise independent particles. Their &amp;quot;movement&amp;quot; and &amp;quot;positions&amp;quot; are described by orbitals, which are one-electron wavefunctions (WF). They are collected in a determinant (called Slater determinant in the case of HF) forming the many-electron WF, from which expectation values like energy or electron density can be calculated.&lt;/p&gt;&#xA;&lt;p&gt;In RHF, &lt;strong&gt;a pair of two electrons of opposite spin is restricted to use the same spatial orbital&lt;/strong&gt;. (Formally, there are also spin components, which together with the spatial orbital form the spin orbital.) All electrons are part of one such pair. In essence, all orbitals are always doubly occupied - at any geometry etc.&lt;/p&gt;&#xA;&lt;p&gt;Restriced Kohn-Sham DFT uses the same basic approach, the technical difference boils down to a different potential describing to non-Coulombic part of the electron-electron interaction. Note that the determinant is now called the Kohn-Sham determinant and refers to a fictitious system used &amp;quot;only&amp;quot; to determine the kinetic energy component of the underlying equations. However, it can also be used to calculate expectation values.&lt;/p&gt;&#xA;&lt;p&gt;One of the advantages of RHF/RKS is that the resulting many-electron WF is an eigenfunction of the total spin operator. Another advantage is the comparatively low computational cost and ease of implementation. For many ground-state compounds (think classical main-group organic chemistry) and their properties, RHF/RKS can be appropriately used. The disadvantage is that RHF/RKS do not work well when bonds are stretched or the state is not a closed-shell singlet. Similarly, most transition states are badly described. Post-RHF treatments can repair these deficiencies, albeit at large computational expense, with other approaches often being more cost-effective.&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-07-19T17:33:42.907" LastActivityDate="2020-07-19T17:33:42.907" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1574" PostTypeId="2" ParentId="1572" CreationDate="2020-07-19T15:44:00.953" Score="13" Body="&lt;h2&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;SCF&lt;/h2&gt;&#xA;&lt;p&gt;This method generates excited states by changing the occupancy of a ground state determinant and then carrying out a new SCF with that initial guess, with some restriction throughout to prevent variational collapse back to the ground state [1]. The most common approach to stay out of the ground state is the Maximum Overlap Method (MOM), which fills orbitals based on overlap with the occupied orbitals of the previous step rather than following the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Aufbau_principle&quot; rel=&quot;noreferrer&quot;&gt;Aufbau principle&lt;/a&gt;. Another recently developed approach is the Squared Gradient Method (SGM), which is designed to converge to the closest minima  [2].&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;SCF is one of the conceptually simplest ways to generate an excited state and it makes it very easy to target an excited state of a particular symmetry. It has also been shown to be effective for modeling double excitations which is difficult or impossible for standard TDDFT calculations [2]. One drawback is that excited states are often best described with multiple configurations, which &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;SCF can't represent. Another issue, and the flip side of being able to target specific symmetry excited states, is that the method is not particularly blackbox and you have to have some sense of the character of the excited state you are looking for.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ziegler, T.; Rauk, A.; Baerends, E. J. Theoretica&#xA;chimica acta 1977, 43, 261−271&lt;/li&gt;&#xA;&lt;li&gt;Diptarka Hait and Martin Head-Gordon J. Chem. Theory Comput. 2020, 16, 3, 1699–1710&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-19T15:59:38.490" LastActivityDate="2020-07-19T15:59:38.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1576" PostTypeId="2" ParentId="1549" CreationDate="2020-07-19T17:13:03.427" Score="6" Body="&lt;p&gt;There are no benefits beyond perceived ease-of-use. The main advantage of GUIs is that they can help inexperienced users get started quicker. This can be through a combination of reasonably selected default parameters for a given job type, behind-the-scenes file management (e.g. no need to construct your own POTCARs), and goal-directed options rather than a list of possible input parameters (e.g. you primarily specify what you &lt;em&gt;want&lt;/em&gt; to do, not necessarily the parameters to get you there). For well-built GUIs in general, there can be additional advantages, such as more seamless handling of complex job types. Naturally, GUIs are useful for educational settings as well.&lt;/p&gt;&#xA;&lt;p&gt;There are other GUIs that can be used to run VASP calculations. Examples include the &lt;a href=&quot;https://www.scm.com/doc/GUI/VASP_via_AMS.html&quot; rel=&quot;noreferrer&quot;&gt;Amsterdam Modeling Suite&lt;/a&gt;, &lt;a href=&quot;https://docs.quantumatk.com/tutorials/vasp.html&quot; rel=&quot;noreferrer&quot;&gt;QuantumATK&lt;/a&gt;, and &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;noreferrer&quot;&gt;Materials Studio&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-07-19T17:13:03.427" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1578" PostTypeId="1" CreationDate="2020-07-19T19:14:03.597" Score="20" ViewCount="1292" Body="&lt;p&gt;Almost anyone that has taken a Solid State Physics course will know, that any 3D crystal must be in one of the 14 &lt;a href=&quot;https://en.wikipedia.org/wiki/Bravais_lattice&quot; rel=&quot;noreferrer&quot;&gt;Bravais lattices&lt;/a&gt; due to symmetry operations and space filling.&lt;/p&gt;&#xA;&lt;p&gt;In 2015, a paper was published in &lt;em&gt;Scientific Reports&lt;/em&gt;&lt;sup&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Bravais_lattice&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;&lt;/sup&gt; (from &lt;em&gt;Nature publishing group&lt;/em&gt;) that reports the findings of a crystal in a forbidden symmetry. The work attracted some &lt;a href=&quot;https://www.forbes.com/sites/trevornace/2016/06/27/forbidden-symmetry-found-in-4-5-billion-year-old-meteorite/#2f2f4b8c4988&quot; rel=&quot;noreferrer&quot;&gt;attention&lt;/a&gt; as the crystal was found in the Khatyrka meteorite. The composition of the crystal was &lt;span class=&quot;math-container&quot;&gt;$\ce{Al_{71}Ni_{24}Fe_5}$&lt;/span&gt;. The figure below shows the high-resolution transmission electron microscopy (HRTEM).&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/NEasP.jpg&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;A similar issue came up in the same year when a new 2D tile was &lt;a href=&quot;https://www.theguardian.com/science/alexs-adventures-in-numberland/2015/aug/10/attack-on-the-pentagon-results-in-discovery-of-new-mathematical-tile&quot; rel=&quot;noreferrer&quot;&gt;found&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Are the claims about the crystals' &amp;quot;forbidden&amp;quot; symmetries due to a mistaken empirical hypothesis, a faulty mathematical theorem, or something else?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Bravais_lattice&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; Bindi, L., Yao, N., Lin, C. et al. &lt;em&gt;Natural quasicrystal with decagonal symmetry&lt;/em&gt;. Sci Rep 5, 9111 (2015). (DOI: &lt;a href=&quot;https://doi.org/10.1038/srep09111&quot; rel=&quot;noreferrer&quot;&gt;10.1038/srep09111&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-19T23:00:57.203" LastActivityDate="2020-07-19T23:00:57.203" Title="Is the number of possible Bravais lattices a mathematical fact?" Tags="|crystal-structure|crystallography|symmetry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1579" PostTypeId="2" ParentId="1578" CreationDate="2020-07-19T21:42:35.657" Score="22" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Quasicrystal&quot; rel=&quot;noreferrer&quot;&gt;Quasicrystals&lt;/a&gt; were known well before 2015. The recent developments is in showing that such crystals exist naturally, rather than just in synthesized samples. The first (nowadays generally accepted) clear demonstration of an aperiodic crystal was &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.53.1951&quot; rel=&quot;noreferrer&quot;&gt;published in 1984&lt;/a&gt;. Examples of such crystals remain very rare compared to periodic crystals, however. So rare in fact, that the initial discovery was far from universally accepted or believed at first, rather it was ridiculed. For example, Linus Pauling was quoted as saying &amp;quot;There is no such thing as quasicrystals, only quasi-scientists.&amp;quot;. However, despite the controversy the first author of that 1984 paper, &lt;a href=&quot;https://en.wikipedia.org/wiki/Dan_Shechtman&quot; rel=&quot;noreferrer&quot;&gt;Dan Schechtman&lt;/a&gt;, was vindicated and later awarded the 2011 Nobel prize in Chemistry for this discovery. I would hope this matter is at least mentioned in Solid State courses these days, if only as a lesson in humility.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The claims about the crystals &amp;quot;forbidden&amp;quot; symmetries are human made due to a lack of knowledge, due to mathematical failure or due something else?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You could call it a lack of mathematical knowledge, or maybe imagination. Bravais' work on lattices was done in the 1840s, and remains true for translation-invariant lattices (specifically, lattices with translational invariance in all spatial dimensions of the crystal). Much later, in the 1960s mathematicians started being interested in aperiodic tilings, but they mostly remained a curiosity until the demonstration of quasicrystals. These break the basic assumption of Bravais lattices, namely that every lattice position can be written&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{R}=n_1 \mathbf{a}_1+n_2 \mathbf{a}_2+n_3 \mathbf{a}_3,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$n_i$&lt;/span&gt; are integers, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_i$&lt;/span&gt; are primitive lattice vectors. Such a lattice structure strongly restricts the possible tilings, and hence the possible patterns in reciprocal space. This restriction produces a set of &amp;quot;allowed&amp;quot; symmetries in reciprocal space through what's known as the crystallographic restriction theorem.&lt;/p&gt;&#xA;&lt;p&gt;Empirically, the same symmetries kept showing up in crystallographic experiments, all the way back to von Laue's seminal x-ray diffraction experiments. As a result, prior to Schechtman et al.'s work, the term crystal &lt;a href=&quot;https://www.nobelprize.org/uploads/2018/06/shechtman-lecture_slides.pdf&quot; rel=&quot;noreferrer&quot;&gt;was generally defined&lt;/a&gt; to require the atoms to be arranged periodically. Up to this point, the problem isn't really that the symmetries were called &amp;quot;forbidden&amp;quot;, rather it's how dogmatically the theorem was believed to describe nature, without exploring effects of breaking the underlying assumptions.&lt;/p&gt;&#xA;&lt;p&gt;In contrast to Bravais lattices, quasicrystals have some kind of aperiodic or quasiperiodic way of tiling the plane / filling space. Such objects are a lot less natural to study than their periodic counterparts, so without direct evidence of them and the requisite mathematical machinery to make sense of them, they were basically not considered at all, or deemed unstable or impossible. One exception to the rule was a 1981 prediction by Alan Lindsay Mackay that a type of quasicrystals known as Penrose tilings would display a five-fold symmetry in reciprocal space, which would be one of the previously &amp;quot;forbidden&amp;quot; symmetries. Note that as this is a symmetry of a scattering pattern, it relies on how sites are arranged/ordered. Random impurity effects would not introduce a new symmetry like this.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Finally, to directly address the question in the title&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is the number of possible Bravais lattices a mathematical fact?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, it is. But Bravais lattices are periodic by definition, which crystals need not be.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2020-07-19T21:58:02.760" LastActivityDate="2020-07-19T21:58:02.760" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1580" PostTypeId="2" ParentId="1557" CreationDate="2020-07-19T23:56:47.503" Score="13" Body="&lt;h2&gt;Using DFT when it's not appropriate&lt;/h2&gt;&#xA;&lt;p&gt;There's a famous quote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;When you give someone a hammer, everything to them looks like a nail&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Many beginners only know DFT and try to use it on everything, even when the system is small enough to use CCSD(T) or some other method that is more accurate and not too expensive for small enough systems.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, many people use DFT as a black box, without knowing in detail how it works, when it works, and when it's expected to fail.&lt;/p&gt;&#xA;&lt;p&gt;For the transition-metal-containing system in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/596/5&quot;&gt;this post&lt;/a&gt;, 8 different fairly decent hybrid functionals were used, and the energy gap of interest ranged from -14.6 to +9.6 kcal/mol (a 25 kcal/mol range for a number that was estimated to be at most 15 kcal/mol in magnitude), and only 3 out of 8 functionals even gave the correct sign for this energy gap. For reference, the term &amp;quot;chemical accuracy&amp;quot; means an accuracy of +/- 1 kcal/mol, so 8 different fairly decent hybrid functionals give energy gaps spanning a range of 25 kcal/mol, it's quite bad.&lt;/p&gt;&#xA;&lt;h3&gt;Lessons learned:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Use CCSD(T) or MRCI+Q if you can.&lt;/strong&gt; Sometimes CCSD(T) is also bad, but in those cases you'll often know because it won't likely converge.&lt;/li&gt;&#xA;&lt;li&gt;Don't just check one functional, because in the mentioned example, one functional gave an energy gap of -14.6 kcal/mol and another one gave +9.6 kcal/mol for the same system. Try many functionals and check to see if they are giving values in agreement.&lt;/li&gt;&#xA;&lt;li&gt;Check ahead of time to see if the system you're studying is multi-reference, strongly correlated, or just poorly suited for DFT. For example if you're studying anions, then the &amp;quot;density-driven error&amp;quot; in DFT is known to be particularly bad and you might want to use &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1260/5&quot;&gt;Density-Corrected DFT&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Check to see if the functional you are using has been optimized on a dataset containing molecules similar to the one you're studying: Don't use a functional that was optimized only for organic systems, on a transition-metal-containing inorganic complex.&lt;/li&gt;&#xA;&lt;li&gt;Perhaps do an &lt;em&gt;a priori&lt;/em&gt; search for functionals that are well suited for your system.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-20T00:14:06.883" LastActivityDate="2020-07-20T00:14:06.883" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1581" PostTypeId="1" CreationDate="2020-07-20T01:29:52.853" Score="22" ViewCount="414" Body="&lt;p&gt;This is inspired from an amazingly successful question on Operations Research Stack Exchange: &lt;a href=&quot;https://or.stackexchange.com/questions/928/great-unsolved-problems-in-o-r&quot;&gt;What are the great unsolved problems in operations research?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h3&gt;Wikipedia has some huge lists of:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_physics&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Unsolved problems in physics&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_chemistry&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Unsolved problems in chemistry&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\star$&lt;/span&gt; But neither of them even mention the fact that the universal functonal in DFT is unknown! &lt;span class=&quot;math-container&quot;&gt;$\star$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h3&gt;Some great problems (not in the above lists!) were discussed in these answers:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;One of the first questions ever asked on this site was: &amp;quot;&lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2/5&quot;&gt;What is the closest thing we have to &amp;quot;the&amp;quot; universal density functional?&lt;/a&gt;&lt;/strong&gt;&amp;quot; &lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/555/5&quot;&gt;We can't yet theoretically predict the ground state hyperfine splitting of the H atom as accurately as we can measure it&lt;/a&gt;.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/2019/2293&quot;&gt;What is the &amp;quot;engineering complexity&amp;quot; for building a universal quantum computer?&lt;/a&gt;&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/2054/2293&quot;&gt;Have anyons been confirmed to exist?&lt;/a&gt;&lt;/strong&gt; (this one's for you &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/671/anyon&quot;&gt;Anyon&lt;/a&gt;!)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr&gt;&#xA;&lt;h3&gt;Some great problems (not in either of the above lists, as far as I know!) are here:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Finding a multi-electron relativistic and quantum mechanical method&lt;/strong&gt;: &#xA;&lt;ul&gt;&#xA;&lt;li&gt;the &lt;strong&gt;Schrödinger equation&lt;/strong&gt; is &lt;em&gt;non-relativistic&lt;/em&gt;,&lt;/li&gt;&#xA;&lt;li&gt;the &lt;strong&gt;Klein-Gordon equation&lt;/strong&gt; is relativistic but only works for &lt;em&gt;spinless particles&lt;/em&gt;,&lt;/li&gt;&#xA;&lt;li&gt;the &lt;strong&gt;Dirac equation&lt;/strong&gt; is a &lt;em&gt;1-electron equation&lt;/em&gt; and only &lt;em&gt;approximates QM&lt;/em&gt; to 1st order in &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;the &lt;strong&gt;Dirac-Coulomb-Breit equation&lt;/strong&gt; involves interacting electrons but is not invariant with respect to Lorentz transformations (it is &lt;em&gt;no longer properly relativistic&lt;/em&gt;) and like the Dirac equation &lt;em&gt;it is not properly quantum mechanical either&lt;/em&gt; since it is derive from first-order perturbation theory in the fine structure constant &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;!&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\therefore$&lt;/span&gt; &lt;strong&gt;There is no multi-electron, relativistic, QM equation&lt;/strong&gt; like the above four for single e-.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1593/5&quot;&gt;High temperature superconductivity&lt;/a&gt;&lt;/strong&gt;: For low-temperatures we have BCS theory, but for high-temperature superconductors we cannot even predict &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; (the critical temperature).&lt;/li&gt;&#xA;&lt;li&gt;How to get &lt;strong&gt;multi-reference coupled cluster&lt;/strong&gt; working well like CCSD(T) for single-reference?&lt;/li&gt;&#xA;&lt;li&gt;Can we come up with a black-box multi-reference method like CCSD(T) for single-reference?&lt;/li&gt;&#xA;&lt;li&gt;Is there a robust way to &lt;strong&gt;automatically select active spaces&lt;/strong&gt;?&lt;/li&gt;&#xA;&lt;li&gt;How best to reach the &lt;strong&gt;CBS limit&lt;/strong&gt; for post-SCF methods? How to solve the cusp problem?&lt;/li&gt;&#xA;&lt;li&gt;How to go &lt;strong&gt;beyond Gaussian orbitals&lt;/strong&gt;, and remain efficient?&lt;/li&gt;&#xA;&lt;li&gt;Can a quantum computer demonstrate beating a classical computer in the modeling of matter?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Can you explain any of these, or perhaps discuss the most recent progress, in up to 3 paragraphs?&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are some other unsolved problems in the computational / theoretical study of matter, and can you explain them in up to 3 paragraphs?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-16T22:20:04.970" LastActivityDate="2021-03-16T22:20:04.970" Title="What are the great unsolved questions in Matter Modeling?" Tags="|reference-request|one-topic-per-answer|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1582" PostTypeId="1" AcceptedAnswerId="1708" CreationDate="2020-07-20T02:11:22.400" Score="14" ViewCount="483" Body="&lt;p&gt;We are working on the excitonic properties of cadmium-based Quantum Dots (QD) and QD heterostructures. We have MedeA-VASP and hence we managed to make QD structure. Are QD calculations different from doing bulk calculations using VASP?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How are DFT calculations on Quantum Dots (QDs) done using VASP?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Also, are Gaussian orbitals better compared to plane wave basis sets for QD calculations?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1079" LastEditorUserId="5" LastEditDate="2020-07-20T03:26:58.463" LastActivityDate="2020-07-26T15:03:34.137" Title="Quantum Dot properties using VASP" Tags="|density-functional-theory|vasp|quantum-dots|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1583" PostTypeId="1" CreationDate="2020-07-20T02:18:47.917" Score="2" ViewCount="180" Body="&lt;p&gt;Is there a good model for the fluid dynamics of human ejaculation of semen?&lt;/p&gt;&#xA;&lt;p&gt;I'm looking to do some sperm motility research in the near future and would like to tinker with a model from a good paper.&lt;/p&gt;&#xA;" OwnerUserId="1080" LastEditorUserId="5" LastEditDate="2020-07-20T02:58:28.350" LastActivityDate="2020-07-20T02:58:28.350" Title="Modeling the fluid dynamics of semen" Tags="|mathematical-modeling|" AnswerCount="0" CommentCount="4" ClosedDate="2020-07-20T05:47:23.207" ContentLicense="CC BY-SA 4.0" />
  <row Id="1584" PostTypeId="2" ParentId="1554" CreationDate="2020-07-20T02:33:46.213" Score="12" Body="&lt;p&gt;Resolution for the time reversal symmetry:&lt;/p&gt;&#xA;&lt;p&gt;I need to demonstrate: &lt;span class=&quot;math-container&quot;&gt;$\Omega(-\mathbf{k})=-\Omega(\mathbf{k})$&lt;/span&gt; (Berry's curvature is a odd function under time reversal symmetry)&lt;/p&gt;&#xA;&lt;p&gt;Berry's curvature:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Omega_{\mu\nu}(\mathbf{k})=\partial_{\mu}A_{\nu}(\mathbf{k})-\partial_{\nu}A_{\mu}(\mathbf{k})\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the system is time-reversally invariant:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$T|u_k\rangle=e^{i\varphi_{\mathbf{k}}}|u_{\mathbf{k}}\rangle\Rightarrow |u_{-\mathbf{k}}^{*}\rangle=e^{i\varphi_{\mathbf{k}}}|u_{\mathbf{k}}\rangle\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The time reversal symmetry operator applied to Berry's curvature&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;T\Omega_{\mu\nu}(\mathbf{k})&amp;amp;=\langle\partial_{\mu}Tu_{\mathbf{k}}|i\partial_{\nu}Tu_{\mathbf{k}}\rangle-\langle\partial_{\nu}Tu_{\mathbf{k}}|i\partial_{\mu}Tu_{\mathbf{k}}\rangle\tag{5} \\&#xA;&amp;amp;=i\int d\mathbf{r}\partial_{\mu}Tu^{\ast}_{\mathbf{k}}\partial_{\nu}Tu_{\mathbf{k}}-i\int d\mathbf{r}\partial_{\nu}Tu^{\ast}_{\mathbf{k}}\partial_{\mu}Tu_{\mathbf{k}} \\&#xA;&amp;amp;=i\int d\mathbf{r}\partial_{\mu}u_{-\mathbf{k}}\partial_{\nu}u^{\ast}_{-\mathbf{k}}-i\int d\mathbf{r}\partial_{\nu}u_{-\mathbf{k}}\partial_{\mu}u^{\ast}_{-\mathbf{k}}\\&#xA;&amp;amp;=\Omega_{\nu\mu}(-\mathbf{k})\\&#xA;&amp;amp;=-\Omega_{\mu\nu}(-\mathbf{k}),&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;where I have used the position representation. Also, the Berry curvature is fully gauge invariant, so time reversal symmetry implies &lt;span class=&quot;math-container&quot;&gt;$T\Omega_{\mu\nu}(\mathbf{k})=\Omega_{\mu\nu}(\mathbf{k})$&lt;/span&gt;. Putting together the two expressions for &lt;span class=&quot;math-container&quot;&gt;$T\Omega_{\mu\nu}(\mathbf{k})$&lt;/span&gt; gives:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Omega_{\mu\nu}(\mathbf{k})=-\Omega_{\mu\nu}(-\mathbf{k})\tag{7}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="1065" LastEditDate="2020-07-22T12:58:19.237" LastActivityDate="2020-07-22T12:58:19.237" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="1585" PostTypeId="2" ParentId="1515" CreationDate="2020-07-20T03:24:49.440" Score="10" Body="&lt;h2&gt;Taiwan: National Center for High-performance Computing (NCHC)&lt;/h2&gt;&#xA;&lt;p&gt;Users can apply for time on nationally-shared computing resources (e.g. TAIWANIA 1). Unfortunately only a limited amount of the support is available in English (mostly in traditional Chinese).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nchc.org.tw/&quot; rel=&quot;noreferrer&quot;&gt;https://www.nchc.org.tw/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-07-20T03:24:49.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1586" PostTypeId="1" AcceptedAnswerId="1591" CreationDate="2020-07-20T04:37:46.237" Score="21" ViewCount="1946" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/High-throughput_screening&quot; rel=&quot;noreferrer&quot;&gt;High-throughput&lt;/a&gt; density functional theory (DFT) calculations are used to screen for new materials and conduct fundamental research in materials science and materials innovation. It involves computations on tens of thousands of compounds, and such a scale demands unique calculation and data management methodologies&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the different tools available for conducting high throughput density functional theory calculations?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Jain, Anubhav, et al. &amp;quot;A high-throughput infrastructure for density functional theory calculations.&amp;quot; Computational Materials Science 50.8 (2011): 2295-2310.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-21T01:07:47.947" LastActivityDate="2020-08-17T21:02:20.517" Title="Tools for high-throughput DFT studies?" Tags="|density-functional-theory|one-topic-per-answer|materials-informatics|materials-design|high-throughput|" AnswerCount="5" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1587" PostTypeId="2" ParentId="1586" CreationDate="2020-07-20T05:09:57.667" Score="15" Body="&lt;p&gt;I think these are some of the most popular:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt;(+&lt;a href=&quot;https://materialsproject.github.io/fireworks/&quot; rel=&quot;noreferrer&quot;&gt;fireworks&lt;/a&gt;+&lt;a href=&quot;https://materialsproject.github.io/custodian/&quot; rel=&quot;noreferrer&quot;&gt;custodian&lt;/a&gt; --&amp;gt; &lt;a href=&quot;https://atomate.org/index.html&quot; rel=&quot;noreferrer&quot;&gt;atomate&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;these are all part of &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;materials project&lt;/a&gt;, there are some good &lt;a href=&quot;https://materialsproject.org/references&quot; rel=&quot;noreferrer&quot;&gt;references&lt;/a&gt; available&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://oqmd.org/&quot; rel=&quot;noreferrer&quot;&gt;OpenQD&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;this is a database like materials project but it's &lt;a href=&quot;http://oqmd.org/documentation/publications&quot; rel=&quot;noreferrer&quot;&gt;been used for high-throughput calculations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.aiida.net/&quot; rel=&quot;noreferrer&quot;&gt;AiiDA&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;seems relatively newer but the site has a ton of good documentation and tutorials&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="979" LastActivityDate="2020-07-20T05:09:57.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1588" PostTypeId="2" ParentId="1521" CreationDate="2020-07-20T08:08:18.073" Score="9" Body="&lt;p&gt;To add to Nike's list, one should also differentiate between the energy consistent pseudopotentials used in quantum chemistry and the shape consistent pseudopotentials that dominate in the solid state community. Energy consistent pseudopotentials are also shape consistent, while shape consistent pseudopotentials result in much larger errors in the energy than with the energy consistent potentials.&lt;/p&gt;&#xA;&lt;p&gt;This minireview by Peter Schwerdtfeger might also be useful: &lt;a href=&quot;https://doi.org/10.1002/cphc.201100387&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemPhysChem 12, 3143 (2011)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="118" LastEditDate="2022-07-04T16:49:51.313" LastActivityDate="2022-07-04T16:49:51.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1589" PostTypeId="2" ParentId="1568" CreationDate="2020-07-20T08:10:47.327" Score="10" Body="&lt;h2&gt;DHF: Dirac-Hartree-Fock (or &amp;quot;Dirack-Fock&amp;quot;)&lt;/h2&gt;&#xA;&lt;p&gt;the DHF (Dirac-Hartree-Fock) or Dirac-Fock is the SCF method based upon four-component spinors (simply four-spinors), because of the four-component Dirac-Coulomb(-Breit/Gaunt) Hamiltonian. The 4-spinors decribe both positive - electronic - solutions as well as  negative, or &amp;quot;positronic&amp;quot; solutions.  We are interested in electronic solutions, which are considered for correlated calculations.&lt;/p&gt;&#xA;&lt;p&gt;4-spinors can be either Kramers restricted (KR) or Kramers unrestricted (KU). Four-component calculations are demanding because of extra small-component (S) basis functions. Good approximations to the Dirac Hamiltonian are two-component (2c) methods. 2c SCF then becomes identical with GHF.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Program packages of my choice:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.diracprogram.org/doku.php&quot; rel=&quot;noreferrer&quot;&gt;DIRAC&lt;/a&gt; based upon 4c/2c KR spinors (has both DFT and &lt;em&gt;ab initio&lt;/em&gt; methods)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.respectprogram.org/&quot; rel=&quot;noreferrer&quot;&gt;ReSpect&lt;/a&gt; upon KU spinors (has effective HF/DFT implementations)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="114" LastEditorUserId="5" LastEditDate="2020-07-20T15:46:50.403" LastActivityDate="2020-07-20T15:46:50.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1590" PostTypeId="1" CreationDate="2020-07-20T15:06:40.890" Score="15" ViewCount="398" Body="&lt;p&gt;I am trying to write some code to automatically generate a judicious set of graphics from DFT/fn-DMC calculations so that users can sanity check their results quickly. My literature review has found that &lt;a href=&quot;https://dl.acm.org/doi/10.5555/616024.617765&quot; rel=&quot;noreferrer&quot;&gt;volume rendering&lt;/a&gt; of the wavefunctions is a good first choice, then isosurfaces of constant &lt;span class=&quot;math-container&quot;&gt;$|\psi|^2$&lt;/span&gt;, and Fermi surfaces where appropriate.&lt;/p&gt;&#xA;&lt;p&gt;However, many of these visualization routines are computationally cheap, relative to the simulations, so the more ways to understand the simulation data, the merrier.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;What are the awesome graphics you have seen in published literature that gave you unique insight into a quantum system?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;What graphics should be co-produced with each simulation to make life easier for matter modelling practitioners?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Just to get things started:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1606.07680&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a paper with nice graphics (see Figure 5); it looks to my untrained eye like they are creating &amp;quot;widened Fermi surfaces&amp;quot; similar to the result of ARPES measurements.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nqSpu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nqSpu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.condmat.physics.manchester.ac.uk/pdf/mesoscopic/publications/graphene/RMP_2009.pdf&quot; rel=&quot;noreferrer&quot;&gt;2D systems&lt;/a&gt; (e.g. Figure 3) allow some more interesting band structure visualizations; although I imagine this is possible in 3D if we slice through a lattice plane.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Zuld3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Zuld3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Plotting the unit cell is an obvious choice, since many of these programs require hand-typed input decks. This won't give any unique insight, but it would be a good sanity check.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://science.sciencemag.org/content/365/6459/1278/tab-pdf&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt; is chock-full of killer graphics; I especially enjoy the Berry curvature field in figure 4c.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/N9DYS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/N9DYS.png&quot; alt=&quot;Berry Curvavture&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1086" LastEditorUserId="1086" LastEditDate="2020-07-21T12:53:50.023" LastActivityDate="2020-07-21T12:53:50.023" Title="Great computer graphics for matter modelling" Tags="|density-functional-theory|software|ab-initio-calculations|visualization-software|diffusion-monte-carlo|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1591" PostTypeId="2" ParentId="1586" CreationDate="2020-07-20T16:35:05.073" Score="19" Body="&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/979/user979&quot;&gt;previously stated&lt;/a&gt;, arguably the most mature and widely used set of tools is currently a combination of &lt;a href=&quot;https://github.com/materialsproject/pymatgen&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt;, &lt;a href=&quot;https://github.com/materialsproject/fireworks&quot; rel=&quot;noreferrer&quot;&gt;FireWorks&lt;/a&gt;, &lt;a href=&quot;https://github.com/materialsproject/custodian&quot; rel=&quot;noreferrer&quot;&gt;Custodian&lt;/a&gt;, and &lt;a href=&quot;https://github.com/hackingmaterials/atomate&quot; rel=&quot;noreferrer&quot;&gt;Atomate&lt;/a&gt; (which is built upon the prior three Python packages). These tools were constructed as part of the &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; but have seen uses in other high-throughput DFT studies.&lt;/p&gt;&#xA;&lt;p&gt;Another general workflow package for automating high-throughput DFT calculations is &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0927025612000717&quot; rel=&quot;noreferrer&quot;&gt;AFLOW&lt;/a&gt;, which has been used in constructing the &lt;a href=&quot;http://aflowlib.org/&quot; rel=&quot;noreferrer&quot;&gt;AFLOWlib&lt;/a&gt; repository.&lt;/p&gt;&#xA;&lt;p&gt;A similar package is &lt;a href=&quot;https://github.com/wolverton-research-group/qmpy&quot; rel=&quot;noreferrer&quot;&gt;qmpy&lt;/a&gt;, which has been used in constructing the &lt;a href=&quot;http://oqmd.org/&quot; rel=&quot;noreferrer&quot;&gt;Open Quantum Materials Database&lt;/a&gt;. As you can see, with each new database of DFT-computed properties, there are often specific workflow packages associated with them (typically because everyone's preferences and use-cases are different).&lt;/p&gt;&#xA;&lt;p&gt;One of the benefits of the &lt;a href=&quot;http://www.aiida.net/&quot; rel=&quot;noreferrer&quot;&gt;AiiDA&lt;/a&gt; package mentioned in the prior answer here is that it retains the calculation history of the entire workflow. Seeing as most robust workflows are somewhat dynamic in their settings (e.g. if an error appears, settings are changed), this can be useful for ensuring full transparency and reproducibility. AiiDA is what powers the data on the &lt;a href=&quot;https://www.materialscloud.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There are also many field-specific packages that attempt to automate workflows specific to that field, oftentimes using one or more of the aforementioned packages. For instance, the &lt;a href=&quot;https://github.com/ulissigroup/GASpy&quot; rel=&quot;noreferrer&quot;&gt;Generalized Adsorption Simulation for Python (GASpy)&lt;/a&gt; code by the Ulissi group is well-suited for automating DFT calculations of inorganic surfaces, as outlined &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jcim.8b00386&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Rosen et al. have also developed a &lt;a href=&quot;https://github.com/arosen93/mof_screen&quot; rel=&quot;noreferrer&quot;&gt;workflow&lt;/a&gt; for automating DFT calculations of metal–organic frameworks, as described &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.25787&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Yet another is the &lt;a href=&quot;https://mast.readthedocs.io/en/dev/&quot; rel=&quot;noreferrer&quot;&gt;MAterials Simulation Toolkit (MAST)&lt;/a&gt;, which allows users to build up &amp;quot;recipes&amp;quot; for automated workflows in a similar manner as Atomate and was originally developed with a focus on simulating defects and diffusion in solids, as described &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0927025616304591&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Edit #1: A new package, named [AMP&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;], was &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465520302113&quot; rel=&quot;noreferrer&quot;&gt;just published&lt;/a&gt; for automating DFT calculations of crystals. It looks like it has several ease-of-use features, such as robust default settings for commonly computed properties, automatically testing if a hybrid functional should be used, and an algorithm to identify complex magnetic orderings in an automated fashion. The code is available to download &lt;a href=&quot;https://data.mendeley.com/datasets/5rdw9jv5vp/1&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Edit #2: I somehow forgot to mention that the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;, which some of the prior toolkits use, is an extremely useful and flexible resource that can be used to construct your own workflows with some Python scripting. It's not specifically meant for high-throughput but can be used that way.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-08-17T21:02:20.517" LastActivityDate="2020-08-17T21:02:20.517" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1592" PostTypeId="2" ParentId="1568" CreationDate="2020-07-20T18:19:27.743" Score="5" Body="&lt;h2&gt;UHF: Unrestricted Hartree-Fock / UKS: Unrestricted Kohn-Sham&lt;/h2&gt;&#xA;&lt;p&gt;In UHF, the restriction for electrons to pair-wise share a spatial orbital is lifted. The &lt;strong&gt;spatial orbitals of spin-up and spin-down electrons can differ entirely&lt;/strong&gt;, as is the case for the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; dissociation (which is described far better by UHF than RHF, though not quantitatively correct). Another application are simpler open-shell cases, such as the lithium atom.&lt;/p&gt;&#xA;&lt;p&gt;The computational cost is a bit larger than for RHF because essentially all quantities appear twice (except for integrals over atomic orbitals) and are linked only through the Coulomb interaction between electrons of opposite spin. For closed-shell singlets, UHF is a waste of computational time, because at geometries close enough to the minimum, the UHF solution will collapse onto the RHF solution.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;UHF has the distinct disadvantage that it generally does not yield pure spin states. Instead of a doublet, one would obtain a mixture of a doublet (usually dominant), a quartet, a sextet etc. This can be quantified as the &amp;quot;spin contamination&amp;quot;. This can also make post-UHF treatments harder to implement.&lt;/p&gt;&#xA;&lt;p&gt;Concerning UKS, we note that some functionals also consider the spin-density for energy determination with &amp;quot;local spin-density approximation&amp;quot; (LSDA) being the simplest form.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; SCF stability analysis can be applied to force a UHF solution not found by the convergence algorithm/initial guess combination: R Seeger, JA Pople, &lt;em&gt;J Chem Phys&lt;/em&gt; &lt;strong&gt;66&lt;/strong&gt;, 3045 (1977), doi: &lt;a href=&quot;https://doi.org/10.1063/1.434318&quot; rel=&quot;noreferrer&quot;&gt;10.1063/1.434318&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;A Szabo, NS Ostlund: &lt;em&gt;Modern Quantum Chemistry&lt;/em&gt;, Dover Publications, 1996.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-07-20T18:19:27.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1593" PostTypeId="2" ParentId="1581" CreationDate="2020-07-20T22:08:15.517" Score="10" Body="&lt;h2&gt;High-temperature superconductivity&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2Iu7g.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2Iu7g.jpg&quot; alt=&quot;High-Tc superconductor levitating above a magnet&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Superconductivity&quot; rel=&quot;noreferrer&quot;&gt;Superconductivity&lt;/a&gt; is a fascinating macroscopic quantum phenomenon in which, as some material is cooled below a critical temperature, its electrical resistance abruptly vanishes. A superconductor can also expel magnetic flux, which allows levitation effects as shown in the picture above. The conventional form of superconductivity was first discovered in Mercury in 1911 by Heike Kamerlingh Onnes, but it took until 1957 for the microscopic Bardeen-Cooper-Schrieffer (BCS) theory to explain its origin. In short, electrons form bound states called Cooper pairs, due to an effective &lt;em&gt;attractive&lt;/em&gt; interaction mediated by phonons. However, there is a less conventional, less understood cousin known as high-temperature superconductivity, or high-&lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; superconductivity.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/High-temperature_superconductivity&quot; rel=&quot;noreferrer&quot;&gt;It&lt;/a&gt; is mentioned both on Wikipedia's &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_physics&quot; rel=&quot;noreferrer&quot;&gt;unsolved problems in physics page&lt;/a&gt; and on the &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_chemistry&quot; rel=&quot;noreferrer&quot;&gt;unsolved problems in chemistry page&lt;/a&gt;, but it equally applies to the study of matter. Since the &lt;a href=&quot;https://link.springer.com/article/10.1007%2FBF01303701&quot; rel=&quot;noreferrer&quot;&gt;1986 discovery by Bednorz and Müller of superconductivity in a copper oxide&lt;/a&gt;, with a transition temperature of &lt;span class=&quot;math-container&quot;&gt;$35$&lt;/span&gt; K (high for superconductors!), there's been an immense amount of experimental, computational and theoretical activity in the field. The goals are manifold, including finding a room temperature superconductor, and to understand the mechanism. Often these systems are very complex, formed from multi-layered crystals, and involve some degree of doping and electron-electron interactions, making their modeling a complex task indeed.&lt;/p&gt;&#xA;&lt;p&gt;Promising computational avenues include accurate simulations of model Hamiltonians (e.g. Hubbard Hamiltonians) in an effort to find the mechanism, and the ongoing development of suitable &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.245155&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;ab initio&lt;/em&gt; methods&lt;/a&gt; to model these systems. At this point, I personally think that such approaches represent the most likely path to understanding these materials, barring some breakthrough. However, that doesn't mean progress has stopped elsewhere. For example, additional clues keep coming in from experiments establishing &lt;a href=&quot;https://www.nature.com/articles/s41563-019-0585-z&quot; rel=&quot;noreferrer&quot;&gt;new classes of superconducting materials&lt;/a&gt;, and surprising &lt;a href=&quot;https://www.nature.com/articles/s41586-019-1375-0&quot; rel=&quot;noreferrer&quot;&gt;transport properties&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="5" LastEditDate="2020-07-20T22:45:54.623" LastActivityDate="2020-07-20T22:45:54.623" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1594" PostTypeId="1" AcceptedAnswerId="1634" CreationDate="2020-07-21T00:04:37.750" Score="13" ViewCount="571" Body="&lt;p&gt;Similar to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1568/5&quot;&gt;What are the types of SCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;What are the types of MCSCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1521/5&quot;&gt;What are the types of pseudopotentials?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1513/5&quot;&gt;What are the types of DFT?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/5&quot;&gt;What are the types of charge analysis?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/901/5&quot;&gt;What are the types of bond orders?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I would like to ask this time, if people can summarize the types of &lt;strong&gt;QMC&lt;/strong&gt; in up to 3 paragraphs:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0005754&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;FCIQMC&lt;/strong&gt; (Full Configuration Interaction Quantum Monte Carlo)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;VMC&lt;/strong&gt; (Variational Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DMC&lt;/strong&gt; (Diffusion Monte Carlo) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1620/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;FN-DMC&lt;/strong&gt; (Fixed-Node Diffusion Monte Carlo) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1621/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;AFQMC&lt;/strong&gt; (Auxilliary Field Quantum Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;PIMC&lt;/strong&gt; (Path Integral Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DQMC&lt;/strong&gt; (Determinant Quantum Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;CT-QMC&lt;/strong&gt; (Continuous-Time Quantum Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://arxiv.org/abs/2007.07379&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sign-corrected QMC&lt;/a&gt;&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1410.1877&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Clock Monte Carlo&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DDQMC&lt;/strong&gt; or &lt;strong&gt;DDMC&lt;/strong&gt; (Diagramatic Determinantal Quantum Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.052129&quot; rel=&quot;nofollow noreferrer&quot;&gt;DDQMC&lt;/a&gt;&lt;/strong&gt; (Driven Dissipative QMC)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.100.043301&quot; rel=&quot;nofollow noreferrer&quot;&gt;PQMC&lt;/a&gt;&lt;/strong&gt; (Projective Quantum Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;SSE-MC&lt;/strong&gt; (Stochastic Series Expansion Monte Carlo) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1634/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4823061&quot; rel=&quot;nofollow noreferrer&quot;&gt;GFMC&lt;/a&gt;&lt;/strong&gt; (Green's Function Monte Carlo)&lt;/li&gt;&#xA;&lt;li&gt;Any others you may wish to add!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-11T15:43:56.417" LastActivityDate="2021-06-11T15:43:56.417" Title="What are the types of Quantum Monte Carlo?" Tags="|one-topic-per-answer|quantum-monte-carlo|monte-carlo|diffusion-monte-carlo|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1595" PostTypeId="2" ParentId="1586" CreationDate="2020-07-21T01:05:58.217" Score="11" Body="&lt;p&gt;&lt;a href=&quot;https://qmcpack.org/about&quot; rel=&quot;noreferrer&quot;&gt;QMCPACK&lt;/a&gt;:  is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. QMCPACK is closely related to &lt;a href=&quot;https://qmcpack.org/nexus&quot; rel=&quot;noreferrer&quot;&gt;Nexus&lt;/a&gt;, which is another High Throughput Computing package for Quantum Chemistry calculations.&lt;/p&gt;&#xA;&lt;p&gt;To add on to something &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/206/andrew-rosen&quot;&gt;Andrew Rosen&lt;/a&gt; said&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;There are also many field-specific packages that attempt to automate workflows specific to that field&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have been working on a Python packge for automating workflow for High Throughput Computing of Raman activities using GAMESS(US). Its called &lt;a href=&quot;https://github.com/Cavenfish/autogamess&quot; rel=&quot;noreferrer&quot;&gt;AutoGAMESS&lt;/a&gt;, funny enough Andrew was actually one of the reviewers on my &lt;a href=&quot;https://joss.theoj.org/papers/10.21105/joss.01612.pdf&quot; rel=&quot;noreferrer&quot;&gt;JOSS paper&lt;/a&gt; on it.&lt;/p&gt;&#xA;&lt;p&gt;There are also many other field specific packages that deserve some advertising here:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/ReactionMechanismGenerator/AutoTST&quot; rel=&quot;noreferrer&quot;&gt;AutoTST&lt;/a&gt;: A framework to perform automated transition state theory calculations related to reaction families common in combustion.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.chemalive.com/2019/01/11/high-throughput-quantum-chemistry/&quot; rel=&quot;noreferrer&quot;&gt;ChemAlive&lt;/a&gt;: High Throughput Quantum Chemistry for Drug Discovery.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/hachmannlab/chemhtps&quot; rel=&quot;noreferrer&quot;&gt;ChemHTPS &lt;/a&gt;: A program suite to for conducting high-throughput computational screenings and generating chemical-modeling data.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-07-21T01:06:50.030" LastActivityDate="2020-07-21T01:06:50.030" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1596" PostTypeId="1" CreationDate="2020-07-21T01:36:57.620" Score="10" ViewCount="964" Body="&lt;p&gt;I am trying to write a molecular dynamics simulation for a Lennard-Jones fluid in a box with periodic boundary conditions. The box has no net momentum. I am writing this in python.&lt;/p&gt;&#xA;&lt;p&gt;I have written a library of functions to set up my box of particles. Then I am implementing it in a separate script.&#xA;Here is &lt;em&gt;dynamics.py&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import itertools&#xA;import numpy as np&#xA;import random&#xA;import time&#xA;import math&#xA;&#xA;random.seed(time.time())&#xA;&#xA;#create a box of particles&#xA;#make object Box which will hold all the particles&#xA;class Box:&#xA;    def __init__(self, numberOfParticles, boxLength, dimension, sigma, epsilon, temperature, dt):&#xA;        self.numberOfParticles = numberOfParticles&#xA;        self.boxLength = boxLength&#xA;        self.dimension = dimension&#xA;        self.sigma = sigma&#xA;        self.epsilon = epsilon&#xA;        self.temperature = temperature&#xA;        self.dt = dt #time step&#xA;        ##### non given quantities&#xA;        self.nrho = numberOfParticles/(boxLength**(dimension)) #number density&#xA;        self.particlePositions = np.zeros((numberOfParticles, dimension)) #do a cubic lattice&#xA;        self.particleVelocities = self.boxLength*(np.random.rand(numberOfParticles, dimension)-0.5) #assign randomly&#xA;        self.particleForces = np.zeros((numberOfParticles, dimension))&#xA;    #&#xA;    #&#xA;    #now to evaluate energy of configuration&#xA;    #evaluating kinetic energy of the system&#xA;&#xA;    def latticePositions(self):&#xA;&#xA;        pointsInLattice = math.ceil(self.numberOfParticles**(1/3))&#xA;&#xA;        spots = np.linspace(0, self.boxLength, num=pointsInLattice, endpoint=False)&#xA;        count = 0&#xA;&#xA;        for p in itertools.product(spots, repeat=3):&#xA;            p = np.asarray(list(p))&#xA;            self.particlePositions[count, :] = p&#xA;            count += 1&#xA;            if count&amp;gt;self.numberOfParticles-1:&#xA;                break&#xA;        #&#xA;        return self&#xA;#&#xA;&#xA;    def evaluateKineticEnergy(self):&#xA;        #square every element, add up the elements of each row&#xA;        kineticEnergy = 0.5*np.sum(np.square(self.particleVelocities))&#xA;        return kineticEnergy&#xA;#&#xA;    #I will be selecting a particle, and summing up all the potential energy arising&#xA;    #due to interactions with every other particle&#xA;&#xA;    def evaluatePotentialEnergy(self):&#xA;        energy = 0&#xA;        for i in range(self.numberOfParticles):&#xA;            for j in range(i+1, self.numberOfParticles):&#xA;                displacement = self.particlePositions[i,:]-self.particlePositions[j,:]&#xA;                for k in range(self.dimension):&#xA;                    if abs(displacement[k])&amp;gt;self.boxLength/2:&#xA;                        displacement[k] -= self.boxLength*np.sign(displacement[k])&#xA;                r = np.linalg.norm(displacement,2) #finding euclidean distance between two particles&#xA;                energy += (4*self.epsilon*((self.sigma/r)**12-(self.sigma/r)**6)) #evaluating potential energy, multiply by 2?&#xA;        return energy&#xA;    #sum of potential and kinetic energy is equal to the total energy&#xA;&#xA;    def evaluateTotalEnergy(self):&#xA;        totalEnergy = self.evaluatePotentialEnergy()+self.evaluateKineticEnergy()&#xA;        return totalEnergy&#xA;    #end of energy calculations&#xA;    #&#xA;    #&#xA;    #find the force each particle is experiencing due to the other particles&#xA;    #force = - gradient of potential&#xA;    def evaluateForce(self):&#xA;        self.particleForces = np.zeros((self.numberOfParticles, self.dimension))&#xA;        def LJForce(displacement):&#xA;            r = np.linalg.norm(displacement, 2)&#xA;            force = 48/(r**2)*(1/(r**12)-0.5*1/(r**6))*displacement&#xA;            return force&#xA;        for i in range(self.numberOfParticles):&#xA;            for j in range(i+1, self.numberOfParticles):&#xA;                rij = self.particlePositions[i,:]-self.particlePositions[j,:]&#xA;                for k in range(self.dimension):&#xA;                    if abs(rij[k])&amp;gt;self.boxLength/2:&#xA;                        rij[k] -= self.boxLength*np.sign(rij[k])&#xA;                rji = -rij&#xA;                self.particleForces[i,:] += LJForce(rij)&#xA;                self.particleForces[j,:] += -self.particleForces[i,:]&#xA;        return self&#xA;    #end of force evaluations&#xA;    #make sure total momentum of box is zero&#xA;    def stationaryCenterOfMass(self):&#xA;        #ensure center of mass is stationary&#xA;        v_cm = np.mean(self.particleVelocities, axis=0)&#xA;        self.particleVelocities = self.particleVelocities - v_cm&#xA;        return self&#xA;#&#xA;#&#xA;#&#xA;def VelocityVerletTimeStepping(currentBox):&#xA;    previousParticleForces = currentBox.particleForces&#xA;    currentBox.particlePositions = (currentBox.particlePositions + currentBox.particleVelocities*currentBox.dt + 0.5*currentBox.particleForces*(currentBox.dt)**2)%(currentBox.boxLength)&#xA;    currentBox = currentBox.evaluateForce()&#xA;    currentBox.particleVelocities = currentBox.particleVelocities + 0.5*(previousParticleForces + currentBox.particleForces)*currentBox.dt&#xA;    return currentBox&#xA;#&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now I am calling these functions to perform time-evolution. I am evaluating energy and ACF and plotting them against time to see if I have done this right.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import dynamics&#xA;import matplotlib.pyplot as plt&#xA;from mpl_toolkits.mplot3d import Axes3D&#xA;import numpy as np&#xA;import math&#xA;&#xA;#parameters of simulation&#xA;numberOfParticles = 100&#xA;dimension = 3&#xA;sigma = 1&#xA;epsilon = 1&#xA;temperature = 1&#xA;#max_iterations = 100&#xA;boxLength = 10*sigma&#xA;dt = 0.001 #time step&#xA;kb = 1 #boltzmann&#xA;##&#xA;#&#xA;#&#xA;&#xA;nmax = 100 #number of time steps to take&#xA;&#xA;#set up the box&#xA;&#xA;currentBox = dynamics.Box(numberOfParticles, boxLength, dimension, sigma, epsilon, temperature, dt)&#xA;&#xA;#placing particles in a lattice&#xA;currentBox = currentBox.latticePositions()&#xA;&#xA;#ensuring box has no net momentum&#xA;currentBox = currentBox.stationaryCenterOfMass()&#xA;&#xA;#calculating forces on particles in the box&#xA;currentBox = currentBox.evaluateForce()&#xA;&#xA;&#xA;#making a list of particle positions and velocities for acf and what not&#xA;particlePositionsList = [currentBox.particlePositions]&#xA;particleVelocityList = [currentBox.particleVelocities]&#xA;&#xA;#making a list of energies at various time steps to plot later&#xA;energy = np.zeros(nmax+1,)&#xA;energy[0] = currentBox.evaluateTotalEnergy()&#xA;&#xA;timepoints = np.arange(nmax+1)*currentBox.dt&#xA;&#xA;#start time stepping routine&#xA;#time points = 0, 1, 2, ..., nmax&#xA;for i in range(nmax):&#xA;&#xA;    #do the time step, knowing that currentBox already knows the particle forces at the moment&#xA;    currentBox = dynamics.VelocityVerletTimeStepping(currentBox) #evaluates forces on particles, updates particle positions and velocities&#xA;    energy[i+1] = currentBox.evaluateTotalEnergy()&#xA;&#xA;    particlePositionsList.append(currentBox.particlePositions)&#xA;    particleVelocityList.append(currentBox.particleVelocities)&#xA;&#xA;#&#xA;#print(energy)&#xA;&#xA;ACF = np.zeros(nmax+1,)&#xA;&#xA;for i in range(nmax+1):&#xA;    for j in range(nmax+1-i):&#xA;        ACF[i] = ACF[i] + np.sum(particleVelocityList[j]*particleVelocityList[j+i])&#xA;        #ACF[j] = ACF[j] + np.sum(particleVelocityList[i]*particleVelocityList[j+i]) #this one works&#xA;    #&#xA;    ACF[i] = ACF[i]/(nmax+1-i)&#xA;#&#xA;&#xA;&#xA;plt.plot(timepoints, energy)&#xA;plt.title(&amp;quot;Energy over time&amp;quot;)&#xA;plt.xlabel(&amp;quot;time&amp;quot;)&#xA;plt.ylabel(&amp;quot;energy&amp;quot;)&#xA;plt.ylim(np.amin(energy)*0.999, np.amax(energy)*1.001)&#xA;plt.show()&#xA;&#xA;plt.plot(timepoints, ACF)&#xA;plt.title(&amp;quot;Normalized VACF plot&amp;quot;)&#xA;plt.xlabel(&amp;quot;time&amp;quot;)&#xA;plt.ylabel(&amp;quot;VACF&amp;quot;)&#xA;plt.show()&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here are the results:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nru8R.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nru8R.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Cfu3U.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cfu3U.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Energy looks good, but ACF looks really wrong. This is how it is supposed to look like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XjScV.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XjScV.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am unsure where I am going wrong here. I am a lone software engineer thrust into the world of physics and molecular modelling, so any advice you have would be appreciated!!&lt;/p&gt;&#xA;&lt;p&gt;Edit 1: After initializing velocity according to a Gaussian distribution,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;self.particleVelocities = self.boxLength*(np.random.normal(0, 1, (numberOfParticles, dimension))) #assign velocity as per normal distr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These are the figures I get:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/olrse.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/olrse.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IHBRc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IHBRc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1070" LastEditorUserId="1070" LastEditDate="2020-07-21T04:35:46.770" LastActivityDate="2020-07-21T04:35:46.770" Title="I wrote a Python code to do MD for a Lennard-Jones fluid but the VACF is wrong: What might be the problem?" Tags="|software|molecular-dynamics|molecular-modeling|python|statistical-thermodynamics|" AnswerCount="0" CommentCount="10" ClosedDate="2020-07-29T03:55:38.990" ContentLicense="CC BY-SA 4.0" />
  <row Id="1597" PostTypeId="1" CreationDate="2020-07-21T03:35:34.170" Score="12" ViewCount="548" Body="&lt;p&gt;I have a large disordered cubic structure that I would like to do AIMD on to look at cation diffusion. I found the primitive cell and then ordered it to create several configurations. I will then relax each one and select the lowest energy configuration for AIMD. But first I have to relax the structures.&lt;/p&gt;&#xA;&lt;p&gt;Ordering the cell will naturally decrease the symmetry of the structure to something like tetragonal or monoclinic. Typically for a calculation in VASP we switch symmetry on (&lt;code&gt;ISYM=2&lt;/code&gt;). In this case, VASP detects tetragonal symmetry and forces the lattice parameters to fit those symmetry constraints, which is incorrect because I know the structure is cubic.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So my first question is: Is this okay?&lt;/strong&gt; I presume it isn't.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If not: What's the best or correct way to deal with this?&lt;/strong&gt; Just setting &lt;code&gt;ISYM=0&lt;/code&gt; or -1?&#xA;Or is it better to constrain the cell shape with &lt;code&gt;ISIF=2&lt;/code&gt;? Or maybe both?&lt;/p&gt;&#xA;&lt;p&gt;I was under the impression that the structure needs to be fully relaxed before doing AIMD: So then setting &lt;code&gt;ISIF=2&lt;/code&gt; would not be correct?&lt;/p&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2020-07-28T00:50:00.030" LastActivityDate="2020-07-28T04:36:44.697" Title="Dealing with symmetry of ordered primitive cell during DFT structure relaxation" Tags="|density-functional-theory|software|molecular-dynamics|vasp|symmetry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1598" PostTypeId="1" AcceptedAnswerId="1602" CreationDate="2020-07-21T09:07:43.157" Score="17" ViewCount="4836" Body="&lt;p&gt;A lot of references say that the Dirac cone in graphene is protected by inversion and time-reversal symmetries. How can one understand this statement? How can one show explicitly that the gapless state will be destroyed if the Hamiltonian violates either one of them? I know that inversion symmetry corresponds to different onsite energies on sublattices A and B, which can be represented by &lt;span class=&quot;math-container&quot;&gt;$\pm m \sigma_{z}$&lt;/span&gt; in a low energy effective Hamiltonian. We can always show explicitly that if the diagonal terms are different, a gap will open in the Dirac cone. How about the time-reversal symmetry?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="1218" LastEditDate="2021-04-04T08:35:29.770" LastActivityDate="2021-04-04T08:35:29.770" Title="How to understand the time-reversal symmetry in graphene?" Tags="|condensed-matter|band-structure|tight-binding|symmetry|graphene|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1599" PostTypeId="2" ParentId="1590" CreationDate="2020-07-21T09:18:00.967" Score="9" Body="&lt;h1&gt;Magnetic Anisotropy&lt;/h1&gt;&#xA;&lt;p&gt;The best way to understand magnetic anisotropy is to visualize it. I think a visualization should be co-produced with every calculation of magnetic anisotropic energy.&lt;/p&gt;&#xA;&lt;p&gt;The following &lt;a href=&quot;https://hal-univ-rennes1.archives-ouvertes.fr/hal-01381124/document&quot; rel=&quot;noreferrer&quot;&gt;figure&lt;/a&gt; shows Magnetocrystalline anisotropy energy calculated for G-type antiferromagnetic LiNbO3-type InFeO3&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;. &lt;a href=&quot;https://i.stack.imgur.com/5ZKeG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5ZKeG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another &lt;a href=&quot;https://www.nature.com/articles/ncomms3511.pdf?origin=ppub&quot; rel=&quot;noreferrer&quot;&gt;figure&lt;/a&gt; shows MAE of CuO calculated for the GS AF1 magnetic structure&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/rw52K.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rw52K.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Fujita, Koji, et al. &amp;quot;LiNbO3-type InFeO3: room-temperature polar magnet without second-order Jahn–Teller active ions.&amp;quot; Chemistry of Materials 28.18 (2016): 6644-6655.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Rocquefelte, Xavier, et al. &amp;quot;Room-temperature spin-spiral multiferroicity in high-pressure cupric oxide.&amp;quot; Nature Communications 4.1 (2013): 1-7.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-07-21T09:18:00.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1600" PostTypeId="2" ParentId="337" CreationDate="2020-07-21T09:25:24.123" Score="9" Body="&lt;p&gt;Calphad techniques should also be of interest.  Calphad is based on thermodynamic models of the Gibbs energy starting from describing the pure elements in gas, liquid and different crystalline structures (also meta-stable ones) and more or less complex models describing solutions with model parameters fitted to experimental data and (for the last 20 years or so) DFT data.&lt;br /&gt;&#xA;Multi-component databases with such model parameters, normally fitted to binary and ternary systems over some temperature range, can be extrapolated to calculate the stable state with systems up to 5-10 elements with reasonable accuracy.&lt;br /&gt;&#xA;Calphad started some 50 years ago as a tool to calculate phase diagrams from thermodynamics with model parameters fitted to experimental data.  But the thermodynamic description can provide chemical potentials, heat capacities, enthalpies etc also in meta-stable phases and it has become an important tool to simulate phase transformations.&lt;br /&gt;&#xA;There are a few commercial and free software available but the main problem is to find a good database, development of the databases is a tedious and slow process and the good databases can be quite expensive.&lt;/p&gt;&#xA;" OwnerUserId="1092" LastEditorUserId="52" LastEditDate="2020-07-21T15:04:41.997" LastActivityDate="2020-07-21T15:04:41.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1601" PostTypeId="1" AcceptedAnswerId="1935" CreationDate="2020-07-21T11:43:06.460" Score="15" ViewCount="287" Body="&lt;p&gt;In contrast to the perfect periodic bulk materials, now computational approaches are moving towards modeling ‘real’ materials or solid solutions with dopants, dislocations, grain boundaries, and interfaces [1].  For example, the special quasirandom structures (SQS) approach is one way of modeling random alloys with statistical site occupations [2].&lt;/p&gt;&#xA;&lt;p&gt;So my question is, what are other &lt;em&gt;ab initio&lt;/em&gt;/theoretical approaches of modeling disorder in materials and what disorder are they good at modeling?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1] Yang, Y., Chen, C., Scott, M. et al. Deciphering chemical order/disorder and material properties at the single-atom level. &lt;em&gt;Nature&lt;/em&gt; 542, 75–79 (2017). &lt;a href=&quot;https://doi.org/10.1038/nature21042&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/nature21042&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] Alex Zunger, S.-H. Wei, L. G. Ferreira, and James E. Bernard Special quasirandom structures &lt;em&gt;Phys. Rev. Lett.&lt;/em&gt; 65, 353 – Published 16 July 1990&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="1218" LastEditDate="2021-04-05T11:41:20.367" LastActivityDate="2021-04-05T13:15:50.610" Title="What ab initio methods are better suited to modelling disorder in materials?" Tags="|density-functional-theory|reference-request|ab-initio-calculations|one-topic-per-answer|disorder|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1602" PostTypeId="2" ParentId="1598" CreationDate="2020-07-21T11:51:14.013" Score="21" Body="&lt;p&gt;&lt;strong&gt;Two-band model for graphene.&lt;/strong&gt; To simplify the discussion of Dirac points, it is sufficient to consider a nearest-neighbor tight-binding 2-band model for graphene. This is a spinless model because spin-orbit is negligible in graphene. The Bloch Hamiltonian is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}(\mathbf{k})=&#xA;\begin{pmatrix}&#xA;0 &amp;amp; h(\mathbf{k}) \\&#xA;h^{\dagger}(\mathbf{k}) &amp;amp; 0&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$h(\mathbf{k})=-t\sum_j e^{i\mathbf{k}\cdot\mathbf{u}_j}$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; the hopping parameter, and &lt;span class=&quot;math-container&quot;&gt;$j=1,2,3$&lt;/span&gt; running over the three &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_j$&lt;/span&gt; nearest neighbors. In the pseudospin representations, this becomes:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}(\mathbf{k})=-t\sum_j\left[\sigma_1\cos(\mathbf{k}\cdot\mathbf{u}_j)-\sigma_2\sin(\mathbf{k}\cdot\mathbf{u}_j)\right].&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The energy spectrum is &lt;span class=&quot;math-container&quot;&gt;$E_{\pm}(\mathbf{k})=\pm|h(\mathbf{k})|$&lt;/span&gt;, and to obtain Diract points we must find a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}_0$&lt;/span&gt; for which &lt;span class=&quot;math-container&quot;&gt;$h(\mathbf{k}_0)=0$&lt;/span&gt;. This can generally happen in graphene because we have two terms in the Hamiltonian (one proportional to &lt;span class=&quot;math-container&quot;&gt;$\sigma_1$&lt;/span&gt; and one proportional to &lt;span class=&quot;math-container&quot;&gt;$\sigma_2$&lt;/span&gt;) and two variables (&lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_y$&lt;/span&gt;) that we can tune to enforce the vanishing of &lt;span class=&quot;math-container&quot;&gt;$h(\mathbf{k})$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}=\mathbf{k}_0$&lt;/span&gt;. In graphene, the Dirac points occur at the K and &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt;K points in the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;General 2-level system in 2 dimensions.&lt;/strong&gt; The Hamiltonian of a general &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;-level system can always be written in the basis of the &lt;em&gt;three&lt;/em&gt; Pauli matrices. In two dimensions, this means that we have three terms (&lt;span class=&quot;math-container&quot;&gt;$\sigma_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\sigma_2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\sigma_3$&lt;/span&gt;) but only two parameters (&lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_y$&lt;/span&gt;) to tune, so that a general 2-dimensional system has no crossing points. The reason graphene has crossing points is because the &lt;span class=&quot;math-container&quot;&gt;$\sigma_3$&lt;/span&gt; term is not present in the Hamiltonian. Why is is not present? Because there are some symmetries in the system that force it to be zero. As you correctly identified, they are time reversal symmetry and inversion symmetry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Time reversal symmetry.&lt;/strong&gt; Time reversal symmetry means that the Bloch Hamiltonian must obey:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}(\mathbf{k})=\hat{H}^{\ast}(-\mathbf{k}).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You should convince yourself that the tight-binding Hamiltonian above obeys this. Imagine we add a term &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})\sigma_3$&lt;/span&gt; to the Hamiltonian, to get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}_1(\mathbf{k})=&#xA;\begin{pmatrix}&#xA;f_3(\mathbf{k}) &amp;amp; h(\mathbf{k}) \\&#xA;h^{\dagger}(\mathbf{k}) &amp;amp; -f_3(\mathbf{k})&#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this case,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}^{\ast}_1(-\mathbf{k})=&#xA;\begin{pmatrix}&#xA;f_3^{\ast}(-\mathbf{k}) &amp;amp; [h(-\mathbf{k})]^{\ast} \\&#xA;[h^{\dagger}(-\mathbf{k})]^{\ast} &amp;amp; -f_3^{\ast}(-\mathbf{k})&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;f_3^{\ast}(-\mathbf{k}) &amp;amp; h(\mathbf{k})\\&#xA;h^{\dagger}(\mathbf{k}) &amp;amp; -f_3^{\ast}(-\mathbf{k})&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where we have used the fact that for the original Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\hat{H}(\mathbf{k})=\hat{H}^{\ast}(-\mathbf{k})$&lt;/span&gt; in the last step. If the system has time reversal symmetry, then the expression for &lt;span class=&quot;math-container&quot;&gt;$\hat{H}^{\ast}_1(-\mathbf{k})$&lt;/span&gt; must equal &lt;span class=&quot;math-container&quot;&gt;$\hat{H}_1(\mathbf{k})$&lt;/span&gt;, which implies &lt;span class=&quot;math-container&quot;&gt;$f_3^{\ast}(-\mathbf{k})=f_3(\mathbf{k})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Inversion symmetry.&lt;/strong&gt; Inversion symmetry implies &lt;span class=&quot;math-container&quot;&gt;$\sigma_1\hat{H}(-\mathbf{k})\sigma_1=\hat{H}(\mathbf{k})$&lt;/span&gt;, and you should again check that the original Hamiltonian obeys this. You can then also add a term &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})\sigma_3$&lt;/span&gt; to the Hamiltonian, and proceeding in the same way I did for time reversal symmetry (I encourage you to try), you will find that this imposes the condition &lt;span class=&quot;math-container&quot;&gt;$f_3(-\mathbf{k})=-f_3(\mathbf{k})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Combined time reversal and inversion symmetries.&lt;/strong&gt; If we have the term &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})\sigma_3$&lt;/span&gt; in the Hamiltonian, and insist that &lt;em&gt;both&lt;/em&gt; symmetries are obeyed then we have the following simultaneous conditions on &lt;span class=&quot;math-container&quot;&gt;$f_3$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{cases}&#xA;f_3^{\ast}(-\mathbf{k})=f_3(\mathbf{k}),\\&#xA;f_3(-\mathbf{k})=-f_3(\mathbf{k}).&#xA;\end{cases}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Putting them together, they imply that &lt;span class=&quot;math-container&quot;&gt;$f_3^{\ast}(-\mathbf{k})=-f_3(-\mathbf{k})$&lt;/span&gt;, which means that &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})$&lt;/span&gt; is purely imaginary. But for a Hermitian operator, &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})$&lt;/span&gt; must be purely real. These two conditions can only be obeyed simultaneously if &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})=0$&lt;/span&gt;. Therefore, graphene has no term proportional to &lt;span class=&quot;math-container&quot;&gt;$\sigma_3$&lt;/span&gt; in the Hamiltonian because of a combination of time reversal and inversion symmetries. This in turn implies that graphene has Dirac points because of a combination of time reversal and inversion symmetries.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Opening a gap in graphene.&lt;/strong&gt; If you break either of these two symmetries, then you no longer have &lt;span class=&quot;math-container&quot;&gt;$f_3=0$&lt;/span&gt;, and a gap develops. As you correctly identified, a term that breaks inversion symmetry is &lt;span class=&quot;math-container&quot;&gt;$f_3(\mathbf{k})\sigma_3=m\sigma_3$&lt;/span&gt;, which effectively places inequivalent on-site potentials on the two atoms in the primitive cell. This is what happens for example in monolayer hexagonal BN, which indeed has a gap. A term that you can add to break time reversal symmetry is to add a complex next-nearest-neighbor hopping &lt;span class=&quot;math-container&quot;&gt;$t^{\prime}e^{i\varphi}$&lt;/span&gt;. This is the famous term that Haldane added to kick-start the field of topological materials, and you can read the original paper &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.61.2015&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. If you go through the maths, you will find that the Bloch Hamiltonian acquires the term&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;f_3(\mathbf{k})\sigma_3=-2t^{\prime}\sum_j\sin(\mathbf{k}\cdot\mathbf{v}_j)\sigma_3,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where I have chosen the complex phase to be &lt;span class=&quot;math-container&quot;&gt;$\varphi=\pi/2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_j$&lt;/span&gt; are the three next-nearest-neighbors.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Spin-orbit coupling.&lt;/strong&gt; The discussion is different if spin-orbit coupling is included. Although it is completely negligible in graphene (&lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;eV scale), it played a very important role historically. With spin-orbit coupling we have a 4-band model, and you can add a spin-orbit term that &lt;em&gt;conserves&lt;/em&gt; time reversal and inversion symmetries, but still opens a gap. This is precisely what Kane and Mele did in their 2005 &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.95.226801&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; that led to the discovery of topological insulators.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-21T11:51:14.013" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="1603" PostTypeId="1" AcceptedAnswerId="1604" CreationDate="2020-07-21T11:56:14.740" Score="10" ViewCount="385" Body="&lt;p&gt;A simple calculation with Molpro 2012 on H2 molecule in cc-pvtz basis produces a molden file with 28 molecular orbitals. Each MO is defined with 30 AO/MO coefficient, but the number of symmetric AOs is 32, and the number of contractions is 28.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;memory, 200, m&#xA;&#xA;basis = cc-pvtz;&#xA;symmetry nosym;&#xA;geomtyp = xyz;&#xA;geometry = {&#xA;2&#xA;&#xA;H       0.00000000     0.00000000    -0.46904000&#xA;H       0.00000000     0.00000000     0.46904000&#xA;}&#xA;&#xA;{rhf;&#xA; WF, 2, 1, 0;&#xA;}&#xA;&#xA;put, molden, h2.molden;&#xA;---&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Part of Molpro output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; NUMBER OF PRIMITIVE AOS:          34&#xA; NUMBER OF SYMMETRY AOS:           32&#xA; NUMBER OF CONTRACTIONS:           28   (  28A   )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why the number of AO/MO coefficients is not equal to the number of symmetric AOs or the number of contractions?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="344" LastEditorUserId="5" LastEditDate="2020-07-22T03:45:16.060" LastActivityDate="2020-07-22T03:45:16.060" Title="How to interpret molden AO/MO coefficients?" Tags="|software|basis-sets|molpro|molden|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1604" PostTypeId="2" ParentId="1603" CreationDate="2020-07-21T12:14:59.273" Score="10" Body="&lt;p&gt;Okay, so there are many layers to this question. cc-pVTZ for H is [5s2p1d/3s], which comes out to 3 + 2*3 + 5 = 3+6+5 = 14 basis functions per atom, which are composed of 16 primitives (the contracted s function).&lt;/p&gt;&#xA;&lt;p&gt;Now, while there are 1 and 3 cartesians for the s and p shells, for the d shell you have 6 cartesian functions but only 5 spherical functions. This is important, since Gaussian-basis integrals are evaluated in the cartesian basis, and then contracted to get the spherical-basis integral. (There are closed-form relations for this translation.)&lt;/p&gt;&#xA;&lt;p&gt;For H2, you then have&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2*14 = 28 contracted basis functions; this is the &amp;quot;number of contractions&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;2*15 = 30 contracted cartesian basis functions, which is thus probably the format which Molden is using.&lt;/li&gt;&#xA;&lt;li&gt;2*16 = 32 primitive Gaussian basis functions with spherical D functions, this appears to be the &amp;quot;symmetry AOs&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;2*18 = 34 primitive Gaussian cartesian basis functions; this is the &amp;quot;primitive AOs&amp;quot;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-21T12:14:59.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1605" PostTypeId="2" ParentId="1581" CreationDate="2020-07-21T12:25:50.780" Score="9" Body="&lt;p&gt;Relativistic correlation methods are another interesting topic: usually one employs the no-pair approximation, which doesn't correlate the negative energy states. However, there's really no reason why the negative energy states shouldn't experience correlation effects, as well...&lt;/p&gt;&#xA;&lt;p&gt;I think there's been pretty good effort recently for the automatic selection of active spaces with the DMRG method, see &lt;a href=&quot;https://doi.org/10.1002/jcc.25869&quot; rel=&quot;noreferrer&quot;&gt;J. Comput. Chem. 40, 2216 (2019)&lt;/a&gt;. Somewhat similar approaches have also been used in earlier works, e.g. &lt;a href=&quot;https://doi.org/10.1063/1.4885815&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 140, 241103 (2014)&lt;/a&gt; ran large-active-space calculations  to figure out a smaller active space in which the production-level calculations were run.&lt;/p&gt;&#xA;&lt;p&gt;As to the beyond Gaussian orbitals question, numerical atomic orbitals (NAOs) are pretty good for this when combined with density fitting approaches; e.g. here's a RI-CCSD(T) study with NAOs: &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01294&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 4721 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-21T12:25:50.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1606" PostTypeId="1" CreationDate="2020-07-21T14:29:11.017" Score="13" ViewCount="3966" Body="&lt;p&gt;When I open a CIF file of a crystal structure in a typical molecular editor like Avogadro, then I just see a few symmetry-unique atoms scattered around the unit cell. But I don't see the full molecule with all its bonds. What is the easiest way to extract one individual molecular image with all its bonds from a cif file?&lt;/p&gt;&#xA;&lt;p&gt;The two problems are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Some atoms are not shown at all if they are not symmetry-unique.&lt;/li&gt;&#xA;&lt;li&gt;Even if all the atoms are shown, then chemical bonds may go between the images in different unit cells, so that bonds are not properly displayed within the unit cell.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Let me show a screenshot below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GNG95.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GNG95.png&quot; alt=&quot;Avogadro screenshot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I would like to happen is that the part with the orange atoms is moved up one unit cell, so that the carbon atoms attach to the blue nitrogen atoms shown at the top. Similarly all the scattered hydrogens have to be moved to different unit cells so that they attach to the atoms properly. This is clearly not a trivial task but it is something that would be needed whenever a CIF file is opened.&lt;/p&gt;&#xA;" OwnerUserId="115" LastEditorUserId="5" LastEditDate="2020-07-22T03:41:58.847" LastActivityDate="2021-10-18T21:25:53.257" Title="How do I extract a molecular structure from a CIF file?" Tags="|software|molecular-modeling|crystal-structure|cif|" AnswerCount="7" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1607" PostTypeId="2" ParentId="1606" CreationDate="2020-07-21T14:50:50.683" Score="5" Body="&lt;p&gt;In the case of Avogadro, the process is really straightforward. Go to&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;File -&amp;gt; Save As&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the pop-up window, you can save the data as .xyz or .mol (among many others) types.&lt;/p&gt;&#xA;" OwnerUserId="605" LastActivityDate="2020-07-21T14:50:50.683" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1608" PostTypeId="1" AcceptedAnswerId="1843" CreationDate="2020-07-21T15:00:38.477" Score="10" ViewCount="147" Body="&lt;p&gt;Can you remember any example of a work of fiction, for example, movie, book, short story, anime, et cetera, where computational matter modeling was an important plot device? I'm looking for examples were it was portrayed realistically (i.e. &lt;a href=&quot;https://en.wikipedia.org/wiki/Hard_science_fiction&quot; rel=&quot;nofollow noreferrer&quot;&gt;hard science fiction&lt;/a&gt; examples would be best).&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-07-29T02:36:54.853" LastActivityDate="2020-07-29T04:40:05.007" Title="Examples of matter modeling in fiction" Tags="|reference-request|history|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1609" PostTypeId="2" ParentId="1606" CreationDate="2020-07-21T15:16:41.050" Score="8" Body="&lt;p&gt;If you're not tethered to Avogadro&lt;/p&gt;&#xA;&lt;p&gt;You can use Mercury to change the system size by going to calculate, packing, and adjusting the cell size.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-21T15:51:44.910" LastActivityDate="2020-07-21T15:51:44.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1610" PostTypeId="1" AcceptedAnswerId="2018" CreationDate="2020-07-21T15:27:38.757" Score="9" ViewCount="1137" Body="&lt;p&gt;This question is complementary to a previous &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/156/88&quot;&gt;question&lt;/a&gt;. I have experience with the plane-wave DFT codes VASP and Quantum ESPRESSO. I would like to try SIESTA for the main purpose of using TranSIESTA for transport studies. Can someone help me get started by providing me some tips and mentioning &lt;strong&gt;how is it different from plane-wave codes?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-08-18T14:11:48.650" LastActivityDate="2020-08-18T14:11:48.650" Title="How is SIESTA and TranSIESTA different from plane wave DFT codes?" Tags="|density-functional-theory|siesta|transport|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1611" PostTypeId="2" ParentId="1606" CreationDate="2020-07-21T15:32:06.640" Score="10" Body="&lt;p&gt;A command line package I use very often to convert between structure formats (and other things) is c2x. You can download the code from their &lt;a href=&quot;https://www.c2x.org.uk&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt;, and a quick &amp;quot;c2x --formats&amp;quot; suggests that it supports both cif files and xyz files.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-21T15:32:06.640" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1612" PostTypeId="2" ParentId="1606" CreationDate="2020-07-21T15:52:39.180" Score="9" Body="&lt;p&gt;I tried out a few programs. It seems like &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;Jmol&lt;/a&gt; and &lt;a href=&quot;http://www.cmbi.ru.nl/molden/molden.html&quot; rel=&quot;noreferrer&quot;&gt;Molden&lt;/a&gt; do resolve the CIF structure and directly show me one molecule with all its bonds without requiring any further input.&lt;/p&gt;&#xA;&lt;p&gt;Other programs like Avogadro or a command-line conversion with OpenBabel just produce the raw data of atoms scattered in the unit cell.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-07-21T15:52:39.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1613" PostTypeId="1" CreationDate="2020-07-21T17:08:13.887" Score="9" ViewCount="611" Body="&lt;p&gt;In a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1515/supercomputers-around-the-world&quot;&gt;previous question&lt;/a&gt; it has been shown the computation capabilities of the countries all over the world. However, if I didn't miss something, the use of such supercomputers is limited to researchers within the country. Is there any supercomputer that can be used for foreign researchers?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-07-21T17:17:22.683" LastActivityDate="2020-07-22T03:38:47.467" Title="Supercomputers around the world, which allow access for researchers outside the country" Tags="|high-performance-computing|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1614" PostTypeId="2" ParentId="1566" CreationDate="2020-07-21T18:18:37.440" Score="10" Body="&lt;h2&gt;LASSCF: Localized Active Space SCF&lt;/h2&gt;&#xA;&lt;p&gt;An approximation to or generalization of (depending on how you look at it) CASSCF. In CASSCF, the wave function consists of an antisymmetrized product of two factors defined in two non-overlapping sets of orbitals: a single determinant of occupied inactive orbitals, and a general correlated wave function describing the electrons occupying the active orbitals. In LASSCF, the wave function is a product of one single determinant and &lt;strong&gt;several&lt;/strong&gt; general correlated wave function terms, defined in the Fock spaces of multiple, distinct, non-overlapping sets of active orbitals; usually, each active subspace is &lt;em&gt;localized&lt;/em&gt; (hence the name) around a particular atom or cluster of atoms within a large molecule, and the difference active subspaces are presumed to interact with one another only weakly. The initialism &amp;quot;vLASSCF&amp;quot; corresponds to the &lt;em&gt;variational&lt;/em&gt; extension in which all orbitals are optimized without any (direct or indirect) constraint and the Hellmann-Feynman theorem applies, and corresponds to a realization for &lt;em&gt;ab initio&lt;/em&gt; chemical models of the cluster mean-field (cMF) method developed by Jiménez-Hoyos and Scuseria.&lt;/p&gt;&#xA;&lt;p&gt;The purpose of LASSCF is similar to that of RASSCF and GASSCF, in that one purports to reduce the cost of an untenably expensive CASSCF calculation by splitting a large active space, described by a factorially large CI vector, into weakly-interacting subspace parts. However, the approximation (compared to CAS with the same active orbitals) inherent to a LAS wave function is more severe than in either RAS or GAS, and the corresponding savings in computational cost are likewise greater in principle. RAS and GAS limit the configurations the CI vector of the active space is allowed to explore in terms of excitations from a reference determinant, while LAS requires that the notional CI vector describing all active subspaces collectively must factorize into a product of subspace parts. This means that the total cost of solving the CI problems in LASSCF is linear with respect to the size of the molecule, provided the size of a single active subspace is held fixed.&lt;/p&gt;&#xA;&lt;p&gt;The method is currently only implemented in &lt;a href=&quot;https://github.com/MatthewRHermes/mrh&quot; rel=&quot;nofollow noreferrer&quot;&gt;mrh&lt;/a&gt;, an extension to &lt;a href=&quot;http://pyscf.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1097" LastEditorUserId="5" LastEditDate="2020-07-22T03:39:39.717" LastActivityDate="2020-07-22T03:39:39.717" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1615" PostTypeId="1" CreationDate="2020-07-21T20:00:06.040" Score="10" ViewCount="392" Body="&lt;p&gt;I noticed that we can calculate the Poisson ratio of a &lt;strong&gt;crystalline metals&lt;/strong&gt; with LAMMPS. I wonder if we can use that example for a &lt;strong&gt;metallic glass&lt;/strong&gt;! If no, is there any other way, with another software?&lt;/p&gt;&#xA;" OwnerDisplayName="user1099" LastEditorDisplayName="user1099" LastEditDate="2020-07-28T13:49:12.047" LastActivityDate="2021-06-11T18:28:23.043" Title="How can I calculate the Poisson ratio of an amorphous material with LAMMPS?" Tags="|molecular-dynamics|lammps|amorphous-materials|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1616" PostTypeId="2" ParentId="1613" CreationDate="2020-07-21T20:24:45.067" Score="10" Body="&lt;h2&gt;PRACE (Partnership for Advanced Computing in Europe)&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://prace-ri.eu&quot; rel=&quot;nofollow noreferrer&quot;&gt;PRACE&lt;/a&gt; is a European organization managing 7 main HPC centers in France, Germany, Italy, Spain, and Switzerland, and with 26 member countries that provide some additional resources.&lt;/p&gt;&#xA;&lt;p&gt;Access is through the evaluation of research proposals via peer-review, and some calls specifically mention that they are &amp;quot;designed for projects requiring access to resources not currently available in the PI’s own country and whose projects do not require resources on the very largest (Tier-0) European Supercomputers or very large computational allocations&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-07-22T03:38:47.467" LastActivityDate="2020-07-22T03:38:47.467" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1617" PostTypeId="2" ParentId="838" CreationDate="2020-07-21T22:16:15.713" Score="5" Body="&lt;p&gt;Sorry for the delay. The most recent capabilities I am aware of using VASP version 6 (not open source unfortunately) includes calculation of single point energies, geometry optimizations (some caveats here exist in terms of how strongly variational principle is captured), and I think also phonon calculations. Interestingly, VASP6 has an O(N^3) scaling. This means depending upon the computational resources available, one can model several hundred atoms in the unit cell. I am sure VASP manual has more technical details on this.&lt;/p&gt;&#xA;&lt;p&gt;If one only wants to do single point energy calculations here, it would be important to benchmark or understand how much the RPA energies will depend unit cell parameters that was obtained from a particular DFT flavor.&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-07-21T22:16:15.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1618" PostTypeId="1" CreationDate="2020-07-21T23:04:41.617" Score="8" ViewCount="138" Body="&lt;p&gt;This question is related to other one here in the MatterModelingSE:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1548/24&quot;&gt;Is it possible to calculate/estimate the value of the J parameter to be used in the Heisenberg/Ising hamiltonians?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here &lt;em&gt;J&lt;/em&gt; is the exchange interaction parameters between two nearest-neighbor spins using in Heisenberg and Ising hamiltonians to study magnetic systems:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{Heisenberg}&#xA;\hat{H}_H=-\sum_{\langle i j\rangle}J\hat{S}_i\hat{S}_j&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{Ising}&#xA;\hat{H}_I=-\sum_{\langle ij\rangle}J\hat{S}_i^z\hat{S}_j^z&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there an experimental (and measurable) observable that can be related to the &lt;em&gt;J&lt;/em&gt; parameter?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="671" LastEditDate="2021-06-14T14:14:29.243" LastActivityDate="2021-06-14T14:14:29.243" Title="What measured quantity can be associated to the value of the J parameter in the Heisenberg/Ising hamiltonians?" Tags="|magnetism|model-hamiltonians|ising-model|spin-models|heisenberg-model|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1620" PostTypeId="2" ParentId="1594" CreationDate="2020-07-22T08:18:14.157" Score="11" Body="&lt;h2&gt;DMC (Diffusion Monte Carlo)&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Theory.&lt;/strong&gt; Consider the Schrödinger equation in imaginary time &lt;span class=&quot;math-container&quot;&gt;$\tau=it$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;-\hbar\frac{\partial\psi(x,\tau)}{\partial\tau}=\hat{H}\psi(x,\tau).&#xA;$$&lt;/span&gt;&#xA;For a time-independent Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt;, the &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;-dependence can be solved in a way analogous to the usual time dependence to obtain:&#xA;&lt;span class=&quot;math-container&quot;&gt;$&#xA;\psi(x,\tau)=\sum_nc_n(0)e^{-E_n\tau/\hbar}\psi_n(x), &#xA;$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\hat{H}\psi_n(x)=E_n\psi_n(x)$&lt;/span&gt;. The function &lt;span class=&quot;math-container&quot;&gt;$\psi(x,\tau)$&lt;/span&gt; at imaginary time &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is a sum over an exponentially decaying superposition of energy eigenstates with the exponential decay rate proportional to &lt;span class=&quot;math-container&quot;&gt;$E_n/\hbar$&lt;/span&gt;. This means that in the limit of large &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi(x,\tau\gg1)\simeq c_0(0)e^{-E_0\tau}\psi_0(x).&#xA;$$&lt;/span&gt;&#xA;In this limit, the ground state &lt;span class=&quot;math-container&quot;&gt;$n=0$&lt;/span&gt; is &amp;quot;projected out&amp;quot; of the initial state, because the corresponding exponential decay is the slowest one. Therefore, by evolving the system in imaginary time we can obtain the ground state of the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\psi_0(x)$&lt;/span&gt; as the long imaginary time limit.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Algorithms.&lt;/strong&gt; So why is the method called &amp;quot;diffusion&amp;quot; Monte Carlo? The kinetic energy term of the Hamiltonian together with the imaginary time dependence is mathematically a diffusion equation, which is simulated using stochastic methods to evolve a collection of &amp;quot;walkers&amp;quot; or samples of the wave function. The potential term is then treated as a &amp;quot;branching&amp;quot; term, in which walkers are created or annihilated. Will the algorithm converge to the ground state? If the initial wave function has some overlap with the ground state, then the ground state will be projected out. Otherwise, the lowest energy state with non-zero overlap with the initial wave function will be projected out.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference.&lt;/strong&gt; An excellent review paper of the method was published some time ago in &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.33&quot; rel=&quot;noreferrer&quot;&gt;Reviews of Modern Physics&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-22T08:18:14.157" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1621" PostTypeId="2" ParentId="1594" CreationDate="2020-07-22T08:29:43.137" Score="10" Body="&lt;h2&gt;FN-DMC (Fixed-node diffusion Monte Carlo)&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Theory.&lt;/strong&gt; See my answer about DMC. The only addition for FN-DMC is that the ground state of an arbitrary Hamiltonian will not be antisymmetrized, and therefore DMC will not converge to the fermionic ground state of interest in electronic systems. To force the system to project out the fermionic ground state, then the nodes of the wave function are fixed during the simulation to those of a fermionic wave function.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Algorithms.&lt;/strong&gt; How are these nodes obtained? A typical approach is to first solve the problem using a different method (typically DFT or Hartree-Fock, but &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4931667&quot; rel=&quot;noreferrer&quot;&gt;sometimes with post-SCF methods like CISD&lt;/a&gt;) and then fixing the nodal surface to that predicted by these methods. Although fixing the nodal surface introduces an approximation to the method, the overall methodology is still one of the most accurate to solve the electronic structure problem in periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References.&lt;/strong&gt; An excellent review paper of the method was published some time ago in &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.33&quot; rel=&quot;noreferrer&quot;&gt;Reviews of Modern Physics&lt;/a&gt;, with an emphasis on the fixed-node formulation and applications to solids. Codes implementing this method include &lt;a href=&quot;https://vallico.net/casinoqmc/&quot; rel=&quot;noreferrer&quot;&gt;CASINO&lt;/a&gt;, &lt;a href=&quot;https://qmcpack.org&quot; rel=&quot;noreferrer&quot;&gt;QMCPACK&lt;/a&gt;, and &lt;a href=&quot;http://qwalk.github.io/mainline/&quot; rel=&quot;noreferrer&quot;&gt;QWalk&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-07-22T16:01:41.443" LastActivityDate="2020-07-22T16:01:41.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1622" PostTypeId="1" CreationDate="2020-07-22T12:34:15.757" Score="7" ViewCount="67" Body="&lt;p&gt;If you do a bibliography search about the codes used in matter modeling, you will find a large &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;list&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I played with a few of them (both free and commercial) and one of my findings is that the properties they can calculate are different, even being important properties. I am aware that they used different basis set (numerical orbitals, Slater functions, Gaussian function, Plane waves), considered all the electrons or just valence electrons, used different types of pseudopotentials, etc.&lt;/p&gt;&#xA;&lt;p&gt;My doubt is about the different properties they can calculate.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is this difference only related to the developers choice or there are some properties that can only be calculated following a given set-up?&lt;/strong&gt;&#xA;(for a given set-up I mean, a given type of basis-set or an specific pseudopotential type, for example)&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="142" LastEditDate="2020-07-23T09:38:28.807" LastActivityDate="2020-07-23T09:38:28.807" Title="Are there properties that can only be calculated with a given set-up?" Tags="|density-functional-theory|software|basis-sets|pseudopotentials|conceptual-dft|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1623" PostTypeId="2" ParentId="1622" CreationDate="2020-07-22T13:24:39.970" Score="8" Body="&lt;p&gt;Only a partial answer: some setups are surely better suited than others for a given property. Some developers recognize this and thus do not bother implementing properties for which their setup will be bad, other developers simply lack the time.&lt;/p&gt;&#xA;&lt;p&gt;One example that I am familiar with are NMR/ESR properties. The ADF package (using Slater basis functions) can calculate some such properties, for which the performance is thought of as better than with Gaussian basis functions. In the latter case, one attempts to handle the problem of the missing cusp at the nucleus by decontracting the basis set (meaning that the number of primitives is equal to the number of AO), and possibly even adding more &amp;quot;core&amp;quot; functions.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-07-22T13:24:39.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1624" PostTypeId="1" CreationDate="2020-07-22T15:15:44.447" Score="13" ViewCount="443" Body="&lt;p&gt;I am working with graphene growth on metal substrates. But I need some sample files to know if I am doing it in the right way because running multiple simulations in LAMMPS takes a lot of time. Can anyone help me in that? It will be really helpful.&lt;/p&gt;&#xA;&lt;p&gt;Any sample file regarding graphene growth will do (Prefered method: Chemical Vapour Deposition). &lt;strong&gt;Is there any place where I might be able to find such a sample LAMMPS file?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for the help.&lt;/p&gt;&#xA;" OwnerUserId="961" LastEditorUserId="5" LastEditDate="2020-12-31T04:21:17.653" LastActivityDate="2020-12-31T04:21:17.653" Title="Sample LAMMPS file for graphene growth on a metal surface" Tags="|molecular-dynamics|lammps|surfaces|graphene|software-input-file-request|" AnswerCount="0" CommentCount="2" ClosedDate="2021-06-09T19:06:26.247" ContentLicense="CC BY-SA 4.0" />
  <row Id="1625" PostTypeId="2" ParentId="1606" CreationDate="2020-07-22T17:13:59.503" Score="11" Body="&lt;p&gt;This is due to an unfortunate code-change in some versions of Open Babel. AFAIK, versions 3.0 and later have a heuristic to detect if the CIF contains a molecule, or is a traditional solid-state crystal structure (e.g., NaCl, YBCO, etc.). These versions are used by the latest development versions of Avogadro (1.93 / 1.94 at the moment).&lt;/p&gt;&#xA;&lt;p&gt;Based on your screenshot, it looks like you're using Avogadro 1.x. There isn't a great way to back-fix this, since I'm not maintaining that code. (I'd much rather just get 2.0 finished and out the door.)&lt;/p&gt;&#xA;&lt;p&gt;There are two work-arounds:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Convert with Open Babel (e.g., CML, MDL, etc.) and read in that&lt;/li&gt;&#xA;&lt;li&gt;Use &amp;quot;fill unit cell&amp;quot; to get all atoms, and build a super-cell if needed.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The patch is &lt;a href=&quot;https://github.com/openbabel/openbabel/pull/1823&quot; rel=&quot;noreferrer&quot;&gt;here #1823&lt;/a&gt;, although it would probably be a pain to apply the patch, rebuild Avogadro 1.x with the older versions of Open Babel it uses, etc.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-07-22T17:13:59.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1626" PostTypeId="1" AcceptedAnswerId="1627" CreationDate="2020-07-22T19:43:29.183" Score="6" ViewCount="111" Body="&lt;p&gt;I read in David Vanderbilt's book named &amp;quot;Berry Phases in Electronic Structure Theory - Electric Polarization, Orbital Magnetization and Topological Insulators&amp;quot; the definition of Berry curvature: &amp;quot;Berry curvature &lt;span class=&quot;math-container&quot;&gt;$\Omega(\mathbf{\lambda})$&lt;/span&gt; is simply defined as the Berry phase per unit area in (&lt;span class=&quot;math-container&quot;&gt;$\lambda_x,\,\lambda_y$&lt;/span&gt;) space&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Berry Curvature is defined by:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\Omega_{n,\mu\nu}(\mathbf{k})=\partial_{\mu}A_{n\nu}(\mathbf{k})-\partial_{\nu}A_{n\mu}(\mathbf{k})\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$A_{n\mu}(\mathbf{k})=\langle u_{n\mathbf{k}}|i\partial_{\mu}u_{n\mathbf{k}}\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A_{n\nu}(\mathbf{k})=\langle u_{n\mathbf{k}}|i\partial_{\nu}u_{n\mathbf{k}}\rangle$&lt;/span&gt; are Berry connections.&lt;/p&gt;&#xA;&lt;p&gt;Berry's curvature has the following property: &lt;span class=&quot;math-container&quot;&gt;$\Omega_{n,\mu\nu}=-\Omega_{n,\nu\mu}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How is this property mathematically demonstrated?&lt;/p&gt;&#xA;" OwnerUserId="1065" LastActivityDate="2020-07-22T19:51:37.010" Title="Property related with Berry curvature: $\Omega_{n,\mu\nu}=-\Omega_{n,\nu\mu}$" Tags="|condensed-matter|quantum-mechanics|berry-phase|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1627" PostTypeId="2" ParentId="1626" CreationDate="2020-07-22T19:51:37.010" Score="7" Body="&lt;p&gt;You can just exchange the &lt;span class=&quot;math-container&quot;&gt;$\mu,\nu$&lt;/span&gt; indices to verify the antisymmetry:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Omega_{n,\mu\nu}(\mathbf{k})=\partial_{\mu}A_{n\nu}(\mathbf{k})-\partial_{\nu}A_{n\mu}(\mathbf{k})\\&#xA;\Rightarrow  \Omega_{n,\nu\mu}(\mathbf{k})=\partial_{\nu}A_{n\mu}(\mathbf{k})-\partial_{\mu}A_{n\nu}(\mathbf{k}) = - \left( \partial_{\mu}A_{n\nu}(\mathbf{k})-\partial_{\nu}A_{n\mu}(\mathbf{k}) \right) = -\Omega_{n,\mu\nu}(\mathbf{k}).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-22T19:51:37.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1628" PostTypeId="2" ParentId="1606" CreationDate="2020-07-22T21:58:23.493" Score="6" Body="&lt;p&gt;If one has access to CCDC's Mercury app, the unique molecules (Z') can be easily written as mol2 or xyz files by the Save As option.&lt;/p&gt;&#xA;&lt;p&gt;Of course, this requires completely written CIF file (with metadata). Often times, some codes lazily output all coordinates in the unit cell.&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-07-22T21:58:23.493" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1629" PostTypeId="1" CreationDate="2020-07-22T22:43:42.703" Score="16" ViewCount="1374" Body="&lt;p&gt;One particularly field of matter modeling is that of &lt;a href=&quot;https://en.wikipedia.org/wiki/Strongly_correlated_material&quot; rel=&quot;noreferrer&quot;&gt;strongly correlated materials&lt;/a&gt;, heavy-fermion compounds with partially filled &lt;em&gt;&lt;strong&gt;4f&lt;/strong&gt;&lt;/em&gt; or &lt;em&gt;&lt;strong&gt;5f&lt;/strong&gt;&lt;/em&gt; orbitals. In brief, these are materials whose complex electronic structures cannot be appropriately described in terms of non-interacting entities. Here, DFT breaks down in this sense.&lt;/p&gt;&#xA;&lt;p&gt;On the site, other questions have focused on methods like Density Functional Theory (DFT), Molecular Dynamics and recently Quantum Monte Carlo (QMC). For these methods, lists of &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;DFT&lt;/a&gt; or &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_software_for_Monte_Carlo_molecular_modeling&quot; rel=&quot;noreferrer&quot;&gt;QMC&lt;/a&gt; software wiki pages are available. However, there is none for DMFT.&lt;/p&gt;&#xA;&lt;p&gt;I know some DFT codes have DMFT implemented (e.g. &lt;a href=&quot;https://docs.abinit.org/topics/DMFT/&quot; rel=&quot;noreferrer&quot;&gt;abinit&lt;/a&gt;), but are those the main ones used?&lt;/p&gt;&#xA;&lt;p&gt;What are the most popular DMFT codes used to model strongly correlated materials?&lt;/p&gt;&#xA;&lt;p&gt;To get the ball rolling, I found &lt;strong&gt;DMFTwDFT&lt;/strong&gt; which can be downloaded &lt;a href=&quot;https://github.com/DMFTwDFT-project/DMFTwDFT&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and the corresponding arxiv paper is &lt;a href=&quot;https://arxiv.org/abs/2002.00068&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="792" LastEditDate="2020-07-25T09:33:49.027" LastActivityDate="2021-06-14T02:39:10.473" Title="What are some codes available for Dynamical Mean Field Theory (DMFT)?" Tags="|software|electronic-structure|one-topic-per-answer|condensed-matter|dynamical-mean-field-theory|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1630" PostTypeId="1" CreationDate="2020-07-23T00:32:17.143" Score="11" ViewCount="319" Body="&lt;p&gt;In similar spirit to recent questions on &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1594/what-are-the-types-of-quantum-monte-carlo&quot;&gt;Quantum Monte Carlo&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1523/what-are-the-types-of-ab-initio-molecular-dynamics&quot;&gt;&lt;em&gt;ab-initio&lt;/em&gt; Molecular Dynamics&lt;/a&gt;, types of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1568/what-are-the-types-of-scf&quot;&gt;SCF&lt;/a&gt;, and others, I would like to ask:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the types of Quantum Molecular Dynamics (QMD)?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;As I have recently learned, Quantum Molecular Dynamics is different to AIMD and MD through the fact that in QMD, the &lt;em&gt;nuclei&lt;/em&gt; are treated quantum mechanically.&lt;/p&gt;&#xA;&lt;p&gt;I would like to ask here, if we can summarize the types of QMD in a few paragraphs:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PIMD (Feynman Path Integral Molecular Dynamics)&lt;/li&gt;&#xA;&lt;li&gt;CMD (Centroid Molecular Dynamics)&lt;/li&gt;&#xA;&lt;li&gt;RPMD (Ring Polymer Molecular Dynamics) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3546/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;*Feel free to let me know of other methods or include them as an answer!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also, it would be great if we limit one QMD method per answer (and per person).&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-10-19T05:44:22.743" LastActivityDate="2020-10-20T04:04:24.453" Title="What are the types of Quantum Molecular Dynamics (QMD)?" Tags="|molecular-dynamics|one-topic-per-answer|quantum-mechanics|terminology|quantum-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1631" PostTypeId="1" CreationDate="2020-07-23T04:24:44.453" Score="10" ViewCount="909" Body="&lt;p&gt;I am actually working on SARS-CoV-2 proteins. Specifically I am trying to tribologically disengage the Spike Glycoprotein from the Membrane protein using LAMMPS. The method is to use amorphous carbon as an abrasive to rub (mechanically wear) the contact point of both the above mentioned proteins.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The detailed explanation of my code (because I might have erred anwhere)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;em&gt;How I generated the datafile&lt;/em&gt;&lt;/strong&gt; :&lt;br /&gt;&#xA;-I downloaded the PDB (Protein Database) of both the proteins &lt;a href=&quot;https://www.rcsb.org/structure/6VXX&quot; rel=&quot;noreferrer&quot;&gt;spike&lt;/a&gt; and &lt;a href=&quot;https://www.rcsb.org/structure/3I6G&quot; rel=&quot;noreferrer&quot;&gt;membrane&lt;/a&gt;. &lt;br /&gt;&#xA;-Used &lt;a href=&quot;https://atomsk.univ-lille.fr/&quot; rel=&quot;noreferrer&quot;&gt;atomsk&lt;/a&gt; to &lt;a href=&quot;https://atomsk.univ-lille.fr/tutorial_lammps.php&quot; rel=&quot;noreferrer&quot;&gt;convert the PDB files to lammps data files.&lt;/a&gt; Used the command &lt;code&gt;atomsk protein_name.pdb lammps&lt;/code&gt;.&lt;br /&gt;&#xA;-This resulted in 2 LAMMPS datafiles. &lt;strong&gt;But&lt;/strong&gt; for the Membrane protein, instead of one molecule of the protein,  4 molecules packed into a Parallelogram like simulation box was generated&lt;a href=&quot;https://i.stack.imgur.com/fjirR.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fjirR.jpg&quot; alt=&quot;LAMMPS datafile(visualized) after the Atomsk process&quot; /&gt;&lt;/a&gt; &lt;br /&gt;&#xA;&lt;em&gt;I don't know why that happened but I was pretty happy that it did because I had to do build a layer of the Membrane protein anyway.&lt;/em&gt;&lt;br /&gt;&#xA;This is an image of the same Membrane protein before putting through Atomsk.&lt;a href=&quot;https://i.stack.imgur.com/ytl11.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ytl11.jpg&quot; alt=&quot;Protein downloaded without manipulation through Atomsk&quot; /&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;-You can observe at the top right corner area of each image to see that &lt;strong&gt;Bonds&lt;/strong&gt; checkbox has disappeared from the OVITO visualization after the pdb file was run through Atomsk and LAMMPS datafile was generated. &lt;em&gt;Again I have no idea about why that happenned!&lt;/em&gt;&lt;br /&gt;&#xA;-Next, I &amp;quot;placed&amp;quot; the spike glycoprotein on the &lt;em&gt;parallelogram membrane layer&lt;/em&gt; using &lt;a href=&quot;http://m3g.iqm.unicamp.br/packmol/home.shtml&quot; rel=&quot;noreferrer&quot;&gt;PACKMOL&lt;/a&gt;. I am actually worried about the junction where the spike protein meets the membrane protein because of manual placement of the proteins. &lt;br /&gt;&#xA;The code for Placing the spike on the membrane is as follows :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tolerance 3.0&#xA;filetype pdb&#xA;output E_S.pdb&#xA;&#xA;structure M.pdb&#xA;  number 1&#xA;  inside box -44. 0. 0. 156. 50. 130.&#xA;  center&#xA;  fixed 0. 0. 0. 0. 0. 0.&#xA;end structure&#xA;&#xA;structure S.pdb&#xA;  number 1&#xA;  inside box -44. 50. 0. 100. 200. 150.&#xA;  center&#xA;  fixed 0. 116. 0. 4.71238898 0. 0.&#xA;end structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;-After all this steps the model looked something like this:&lt;a href=&quot;https://i.stack.imgur.com/1ZHtZ.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1ZHtZ.jpg&quot; alt=&quot;Spike Protein over the membrane layer&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;-When visualized in &lt;a href=&quot;https://pymol.org/2/&quot; rel=&quot;noreferrer&quot;&gt;Pymol&lt;/a&gt; the spike glycoprotein on the membrane is very clearly visible.&lt;a href=&quot;https://i.stack.imgur.com/thdBz.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/thdBz.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;2. LAMMPS CODE&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Tribological detachment of SARS-CoV-2 Spike Glycoprotein.&#xA;&#xA;# definition&#xA;units           real                                                        # types of units used&#xA;dimension       3                                                           # Defines a 3D simulation&#xA;processors      * * *                                                       # Command for optimum usage of processors&#xA;boundary        p p p                                                       # Defines periodic boundary conditions&#xA;atom_style      charge                                                      # Defines atom type to be charge&#xA;&#xA;# SARS Input&#xA;read_data       lipid.dat                                                   # Reads the datafile&#xA;mass            1 12.0107                                                   #Carbon&#xA;mass            2 14.0067                                                   #Nitrogen&#xA;mass            3 15.9940                                                   #Oxygen&#xA;mass            4 32.0650                                                   #Sulphur&#xA;&#xA;# Group the abrasive atoms&#xA;region          carbonatoms block -96 -79 23 34 -8 11                                        # Defines a 3D block region called &amp;quot;abrasive&amp;quot; that is made up of the unit cell in the x-, y-, and z-direction for the given dimensions&#xA;group           carbonatoms region carbonatoms                                          # Assigns the name carbonatoms to atom type 1.&#xA;&#xA;# Group the  SARS data file&#xA;region          sars block -100 100 -26 185 -65 65 units box                # Create a region for the datafile&#xA;group           sars region sars                                            # group the input file with the name &amp;quot;sars&amp;quot;&#xA;&#xA;# Interatomic potentials&#xA;pair_style      reax/c NULL                                                 # Pair potential style ReaxFF&#xA;pair_coeff      * * ffield.reax.FC C N O S                                  # Assign Respective atoms&#xA;&#xA;# Settings&#xA;compute         peratom all pe/atom                                         # Compute potential energy per atoms&#xA;neighbor        2.0 bin                                                     # NEVER KNEW WHAT THIS IS !!!!!!!!!&#xA;neigh_modify    delay 20 every 1 check yes page 500000 one 50000            # Helps with the lost atoms error!!!&#xA;&#xA;# Initialization&#xA;velocity        all create 350 123456                                       # Setting temperature to 350 K&#xA;variable        t_step equal &amp;quot;step&amp;quot;                                         # Assigning a variable for step&#xA;variable        t_temp equal &amp;quot;temp&amp;quot;                                         # Assigning a variable for temperature&#xA;thermo          100                                                         # Show [#] for every 100 steps&#xA;thermo_style    custom step press temp pe                                   # Show [temp and step &amp;amp; PE ]&#xA;&#xA;# Relaxation&#xA;#fix             rigid sars addforce 0.0 0.0 0.0                            # Make the sars group immobile by reducing force to 'zero' in all direction&#xA;#fix             relax carbonatoms npt temp 250 250 0.5 iso 0 0 0.5 drag 1  # The start and end temperatures of abrasive is 250K and start and end pressure of abrasive is 0 and the abrasive is damped.&#xA;fix             charge all qeq/reax 1 0.0 10.0 1.0e-6 reax/c                # Fix needed for reaxFF. DONNO WHAT THIS DOES !!!!!!&#xA;variable        t equal 1                                                   # Assigning timestep&#xA;timestep        ${t}                                                        # Equating timestep&#xA;dump            1 all custom 200 equil.*.dump id type x y z fx fy fz        # Dump 'atom id' 'atom type' 'x,y,z coordinates' 'force along x,y,z coordinates'&#xA;run             1                                                           # Run for 2000 time steps&#xA;&#xA;# always remove fixes that are no longer needed&#xA;#unfix rigid&#xA;#unfix relax&#xA;#unfix charge&#xA;&#xA;#Scratching&#xA;fix  2 carbonatoms move linear 5 0 0 units box                              # Apply force in x direction for wear @ 5 Angstroms/femtosecond&#xA;dump 3 all custom 100 sars-Scratch.*.dump id type x y z fx fy fz            # Dump 'atom id' 'atom type' 'x,y,z coordinates' 'force along x,y,z coordinates'&#xA;run 1000                                                                    # Run for 2000 time steps&#xA;&#xA;# End simulation&#xA;print &amp;quot;All done&amp;quot;                                                            # HOPE TO SEE THIS AT THE END OF SCREEN&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;-Since I usually have a lot of issues with LAMMPS (I'm still in the learning curve) in the code, I have mentioned what &lt;strong&gt;I think&lt;/strong&gt; that command does in my code right next to the command itself. Please correct me if I'm wrong.\&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;2.1 Regarding LAMMPS data file (Lipid.dat in the code)&lt;/em&gt;&lt;/strong&gt;&lt;br /&gt;&#xA;-When visualized it looks something like this. The individual atom pointed out is one of the many amorphous carbon atoms likely to be used as the abrasive for tribological disengagement. I have used just one atom just to see if the code works right.&lt;em&gt;The coordinates of the pointed out atom is written is inside the data file itself (Refer &lt;strong&gt;Atom number 51227&lt;/strong&gt; in line number 51236 of the data file(lipid.dat))&lt;/em&gt;&lt;br /&gt;&#xA;Also the &lt;strong&gt;Bonds&lt;/strong&gt; checkbox is missing for some reason when visualized&#xA;&lt;a href=&quot;https://i.stack.imgur.com/XfbD0.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XfbD0.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;2.2 Results I'm getting:)&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:94)&#xA;  using 1 OpenMP thread(s) per MPI task&#xA;# Tribological detachment of SARS-CoV-2 Spike Glycoprotein.&#xA;&#xA;# definition&#xA;units           real                                                        # types of units used&#xA;dimension       3                                                           # Defines a 3D simulation&#xA;processors      * * *                                                       # Command for optimum usage of processors&#xA;boundary        p p p                                                       # Defines periodic boundary conditions&#xA;atom_style      charge                                                      # Defines atom type to be charge&#xA;&#xA;# SARS Input&#xA;read_data       lipid.dat                                                   # Reads the datafile&#xA;  orthogonal box = (-99.923 -24.73 -64.058) to (99.923 184.496 64.058)&#xA;  1 by 1 by 1 MPI processor grid&#xA;  reading atoms ...&#xA;  51227 atoms&#xA;  read_data CPU = 0.091445 secs&#xA;mass            1 12.0107                                                   #Carbon&#xA;mass            2 14.0067                                                   #Nitrogen&#xA;mass            3 15.9940                                                   #Oxygen&#xA;mass            4 32.0650                                                   #Sulphur&#xA;&#xA;# create the abrasive atoms&#xA;#lattice         diamond 3.57                                                # Defines a diamond lattice with unit length 3.57A&#xA;region carbonatoms block -96 -79 23 34 -8 11                                        # Defines a 3D block region called &amp;quot;abrasive&amp;quot; that is made up of the unit cell in the x-, y-, and z-direction for the given dimensions&#xA;#create_box      1 box                                                      # Creates a simulation box for the abrasive region.&#xA;#create_atoms    1 box                                                       # Creates atoms within the simulation box.&#xA;#mass            1 12.0107                                                   # Assign the mass of carbon.&#xA;group           carbonatoms region carbonatoms                                          # Assigns the name carbonatoms to atom type 1.&#xA;3 atoms in group carbonatoms&#xA;&#xA;&#xA;&#xA;# Group the  SARS data file&#xA;region          sars block -100 100 -26 185 -65 65 units box                # Create a region for the datafile&#xA;group           sars region sars                                            # group the input file with the name &amp;quot;sars&amp;quot;&#xA;51227 atoms in group sars&#xA;&#xA;# Interatomic potentials&#xA;pair_style      reax/c NULL                                                 # Pair potential style ReaxFF&#xA;pair_coeff      * * ffield.reax.FC C N O S                                  # Assign Respective atoms&#xA;Reading potential file ffield.reax.FC with DATE: 2013-06-28&#xA;WARNING: Changed valency_val to valency_boc for X (../reaxc_ffield.cpp:315)&#xA;&#xA;# Settings&#xA;compute         peratom all pe/atom                                         # Compute potential energy per atoms&#xA;neighbor        2.0 bin                                                       # NEVER KNEW WHAT THIS IS !!!!!!!!!&#xA;#neigh_modify    delay 5                                                     #------------&amp;quot;&amp;quot;----------&amp;quot;&amp;quot;--------&#xA;neigh_modify delay 20 every 1 check yes page 500000 one 50000&#xA;&#xA;# Initialization&#xA;velocity        all create 350 123456                                       # Setting temperature to 350 K&#xA;variable        t_step equal &amp;quot;step&amp;quot;                                         # Assigning a variable for step&#xA;variable        t_temp equal &amp;quot;temp&amp;quot;                                         # Assigning a variable for temperature&#xA;thermo          100                                                         # Show [#] for every 100 steps&#xA;thermo_style    custom step press temp pe                                   # Show [temp and step &amp;amp; PE ]&#xA;&#xA;# Relaxation&#xA;#fix             rigid sars addforce 0.0 0.0 0.0                             # Make the sars group immobile by reducing force to 'zero' in all direction&#xA;#fix             relax carbonatoms npt temp 250 250 0.5 iso 0 0 0.5 drag 1   # The start and end temperatures of abrasive is 250K and start and end pressure of abrasive is 0 and the abrasive is damped.&#xA;fix             charge all qeq/reax 1 0.0 10.0 1.0e-6 reax/c                # Fix needed for reaxFF. DONNO WHAT THIS DOES !!!!!!&#xA;variable        t equal 1                                                   # Assigning timestep&#xA;timestep        ${t}                                                        # Equating timestep&#xA;timestep        1                                                        &#xA;dump            1 all custom 200 equil.*.dump id type x y z fx fy fz        # Dump 'atom id' 'atom type' 'x,y,z coordinates' 'force along x,y,z coordinates'&#xA;run             1                                                        # Run for 2000 time steps&#xA;Neighbor list info ...&#xA;  update every 1 steps, delay 20 steps, check yes&#xA;  max neighbors/atom: 50000, page size: 500000&#xA;  master list distance cutoff = 12&#xA;  ghost atom cutoff = 12&#xA;  binsize = 6, bins = 34 35 22&#xA;  2 neighbor lists, perpetual/occasional/extra = 2 0 0&#xA;  (1) pair reax/c, perpetual&#xA;      attributes: half, newton off, ghost&#xA;      pair build: half/bin/newtoff/ghost&#xA;      stencil: half/ghost/bin/3d/newtoff&#xA;      bin: standard&#xA;  (2) fix qeq/reax, perpetual, copy from (1)&#xA;      attributes: half, newton off, ghost&#xA;      pair build: copy&#xA;      stencil: none&#xA;      bin: none&#xA;Per MPI rank memory allocation (min/avg/max) = 1299 | 1299 | 1299 Mbytes&#xA;Step Press Temp PotEng &#xA;       0   -10766.276          350   -3905465.6 &#xA;       1    -10766.28          350   -3905465.6 &#xA;Loop time of 5.4404 on 1 procs for 1 steps with 51227 atoms&#xA;&#xA;Performance: 0.016 ns/day, 1511.221 hours/ns, 0.184 timesteps/s&#xA;99.4% CPU use with 1 MPI tasks x 1 OpenMP threads&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 3.7494     | 3.7494     | 3.7494     |   0.0 | 68.92&#xA;Neigh   | 0          | 0          | 0          |   0.0 |  0.00&#xA;Comm    | 0.0001034  | 0.0001034  | 0.0001034  |   0.0 |  0.00&#xA;Output  | 0.0027405  | 0.0027405  | 0.0027405  |   0.0 |  0.05&#xA;Modify  | 1.688      | 1.688      | 1.688      |   0.0 | 31.03&#xA;Other   |            | 0.0001042  |            |       |  0.00&#xA;&#xA;Nlocal:    51227 ave 51227 max 51227 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Nghost:    13650 ave 13650 max 13650 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Neighs:    6.23875e+06 ave 6.23875e+06 max 6.23875e+06 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 6238751&#xA;Ave neighs/atom = 121.786&#xA;Neighbor list builds = 0&#xA;Dangerous builds = 0&#xA;&#xA;# always remove fixes that are no longer needed&#xA;#unfix rigid&#xA;#unfix relax&#xA;#unfix charge&#xA;#Scratching&#xA;&#xA;fix  2 carbonatoms move linear -5 0 0 units box                              # Apply force in x direction for wear @ 5 Angstroms/femtosecond&#xA;dump 3 all custom 100 sars-Scratch.*.dump id type x y z fx fy fz            # Dump 'atom id' 'atom type' 'x,y,z coordinates' 'force along x,y,z coordinates'&#xA;run 1000                                                                   # Run for 2000 time steps&#xA;Per MPI rank memory allocation (min/avg/max) = 1300 | 1300 | 1300 Mbytes&#xA;Step Press Temp PotEng &#xA;       1   -10766.277          350   -3905465.6 &#xA;     100   -562.05515    8180.9385   -3905397.2 &#xA;     200   -562.05562    8180.9385   -3905397.2 &#xA;     300   -562.05498    8180.9385   -3905397.2 &#xA;     400   -562.05579    8180.9385   -3905397.2 &#xA;     500   -562.05559    8180.9385   -3905397.2 &#xA;     600    -562.0559    8180.9385   -3905397.2 &#xA;     700    -562.0552    8180.9385   -3905397.2 &#xA;     800   -562.05578    8180.9385   -3905397.2 &#xA;     900   -562.05555    8180.9385   -3905397.2 &#xA;    1000   -562.05588    8180.9385   -3905397.2 &#xA;    1001   -562.19269    8180.9385     -3905428 &#xA;Loop time of 7549.05 on 1 procs for 1000 steps with 51227 atoms&#xA;&#xA;Performance: 0.011 ns/day, 2096.958 hours/ns, 0.132 timesteps/s&#xA;63.8% CPU use with 1 MPI tasks x 1 OpenMP threads&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 4092.2     | 4092.2     | 4092.2     |   0.0 | 54.21&#xA;Neigh   | 10.099     | 10.099     | 10.099     |   0.0 |  0.13&#xA;Comm    | 0.1589     | 0.1589     | 0.1589     |   0.0 |  0.00&#xA;Output  | 2721.7     | 2721.7     | 2721.7     |   0.0 | 36.05&#xA;Modify  | 724.69     | 724.69     | 724.69     |   0.0 |  9.60&#xA;Other   |            | 0.1211     |            |       |  0.00&#xA;&#xA;Nlocal:    51227 ave 51227 max 51227 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Nghost:    13650 ave 13650 max 13650 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Neighs:    6.23872e+06 ave 6.23872e+06 max 6.23872e+06 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 6238720&#xA;Ave neighs/atom = 121.786&#xA;Neighbor list builds = 50&#xA;Dangerous builds = 50&#xA;&#xA;# End simulation&#xA;print &amp;quot;All done&amp;quot;                                                            # HOPE TO SEE THIS AT THE END OF SCREEN&#xA;All done&#xA;&#xA;Please see the log.cite file for references relevant to this simulation&#xA;&#xA;Total wall time: 2:06:06&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;-The above is the result after the simulation is done. &lt;br /&gt;&#xA;-&lt;strong&gt;The single atom(&lt;em&gt;abrasive&lt;/em&gt;) which is supposed to move in x direction according to code does not move at all. Instead some other 2-3 atoms start moving outside the simulation box.&lt;/strong&gt;&lt;br /&gt;&#xA;I don't understand what is happening with this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;3.Appendix&lt;/em&gt;&lt;/strong&gt;&lt;br /&gt;&#xA;You can find all the necessary file for this issue over &lt;a href=&quot;https://github.com/HPQC-LABS/QCBugs/tree/master/Issue019&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Long story short&lt;/em&gt;&lt;/strong&gt;&lt;br /&gt;&#xA;-I expected the single abrasive atom to to move along the x-direction and do something to the S protein and M protein junction. It didn't. So if anyone can help me out regarding the same it would be amazing!&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="5" LastEditDate="2020-07-23T16:31:04.003" LastActivityDate="2020-07-24T10:51:28.570" Title="LAMMPS code that I wrote not behaving as expected. Some issue with the group &amp; region commands" Tags="|molecular-dynamics|lammps|visualization-software|proteins|covid-19|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1632" PostTypeId="1" CreationDate="2020-07-23T04:41:42.237" Score="15" ViewCount="661" Body="&lt;p&gt;In matter modelling we use self consistent approaches for calculating different properties. Many DFT codes find the ground state of the system by determining total energy self consistently. Going through literature on VASP calculations, I see that &lt;span class=&quot;math-container&quot;&gt;$10^{-6}$&lt;/span&gt; eV is used as standard in many calculations. Also I see that in literature and sample programs the convergence criteria for phonon calculations are more stringent (&lt;span class=&quot;math-container&quot;&gt;$10^{-8}$&lt;/span&gt; eV) than that for ground state energy calculation.&#xA;Also for geometry optimisations the default energy convergence criteria is &lt;span class=&quot;math-container&quot;&gt;$10^{-4}$&lt;/span&gt; eV. We also use total energy convergence for estimating kinetic energy cutoff and k spacing. I see many people using 1 meV as an energy threshold for these calculations.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;What levels of convergence are considered standard (required) for each type of calculation and Why?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Do these thresholds change between codes?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-07-24T14:43:17.110" Title="Standard values for level of convergence" Tags="|density-functional-theory|vasp|self-consistent-field|numerical-convergence|convergence-test|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1633" PostTypeId="1" CreationDate="2020-07-23T08:35:52.920" Score="15" ViewCount="444" Body="&lt;p&gt;As someone that wants to learn about computational chemistry,  mainly for its use in energy storage materials (and therefore DFT as the most practical method of it), I am wondering what is essential to learn about DFT. The theory behind it seems quite vague if someone does not have the practical mathematical formulations. When a chemist comes to use computational chemistry in software, it is something completely different compared to when they learn about DFT.&lt;/p&gt;&#xA;&lt;p&gt;What I understand is that the most essential task is the improvement of exchange correlation functionals to give better and more accurate results, which must be then compared with experimental observations, but the course that I have followed never discussed any way to do it. The consideration of LDA and GGA are never clear for a computational chemist for what is better or worse to use and the development of them is a job for a quantum physicist for example.&lt;/p&gt;&#xA;&lt;p&gt;So I am wondering, what is really the essential role of a chemist in computational chemistry and what does he/she have to learn to be effective?&lt;/p&gt;&#xA;" OwnerUserId="1108" LastEditorUserId="5" LastEditDate="2020-07-23T16:19:01.833" LastActivityDate="2020-07-30T02:30:32.600" Title="What is the role of a chemist in computational chemistry?" Tags="|density-functional-theory|computational-chemistry|functional|history|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1634" PostTypeId="2" ParentId="1594" CreationDate="2020-07-23T08:59:22.823" Score="7" Body="&lt;h2&gt;Stochastic Series Expansion (SSE) Monte Carlo&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Theory&lt;/strong&gt;: SSE is a &lt;strong&gt;finite-temperature, discrete-time&lt;/strong&gt; technique that works well for &lt;strong&gt;quantum spin&lt;/strong&gt; problems (e.g. Heisenberg model) and other &lt;strong&gt;lattice Hamiltonians&lt;/strong&gt; in any number of dimensions. The method works by expanding the partition function in a Taylor series&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1} Z = \mathrm{Tr}[ \rho] = \mathrm{Tr}[e^{-\beta H}] = \mathrm{Tr} \sum \limits_{\alpha_0} \sum \limits_{n=0}^\infty \left\langle \alpha_0 \left| \frac{(-\beta H)^n}{n!} \right| \alpha_0 \right\rangle $$&lt;/span&gt;&#xA;and then inserting a complete set of states in some basis between each term in the Taylor expansion&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2} Z = \sum \limits_n \frac{(-\beta)^n}{n!} \sum \limits_{\alpha_0} \sum \limits_{\alpha_1} ... \sum \limits_{\alpha_{n-1}} \langle \alpha_0 | H | \alpha_1  \rangle \langle \alpha_1 | H | \alpha_2 \rangle ... \langle \alpha_{n-1} | H | \alpha_0 \rangle $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The resulting matrix elements &lt;span class=&quot;math-container&quot;&gt;$\langle \alpha_{i} | H | \alpha_{i+1} \rangle$&lt;/span&gt; are usually simple to evaluate.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Algorithm:&lt;/strong&gt; The goal of the algorithm is to sample the sum in the previous equation. This is sum in an extremely high-dimensional space, perfect for importance sampling Monte Carlo. In general, the program stores a MC configuration as a starting state &lt;span class=&quot;math-container&quot;&gt;$\alpha_0$&lt;/span&gt; and the list of local operators that act upon that state (the operator string). There are many different methods of updates, but they generally consist of two steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A &lt;em&gt;diagonal&lt;/em&gt; update that adds and removes diagonal matrix elements, sampling the &lt;em&gt;order&lt;/em&gt; (&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) of the Taylor expansion.&lt;/li&gt;&#xA;&lt;li&gt;An &lt;em&gt;off-diagonal&lt;/em&gt; update which leaves &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; fixed and samples the configurations &lt;span class=&quot;math-container&quot;&gt;$\{\alpha\}$&lt;/span&gt;. These are commonly called operator loop updates and there are many different algorithms for different situations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Use case:&lt;/strong&gt; SSE is efficient for lattice Hamiltonians at finite temperature (although &lt;span class=&quot;math-container&quot;&gt;$T=0$&lt;/span&gt; can be reached as a limit). To measure any quantity that is &lt;em&gt;diagonal&lt;/em&gt; in the working basis is each, since the measurements can be directly computed from the SSE configurations, e.g.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3} \langle S^z \rangle = \mathrm{Tr} \left[ S^z e^{-\beta H} \right] $$&lt;/span&gt;&#xA;If an observable is off-diagonal in the simulation basis, but appears in the Hamiltonian, it can sometimes be calculated using some clever formula, e.g.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4} \langle E \rangle = -\frac{\langle n \rangle }{\beta}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5} \langle C_v \rangle = -\frac{\langle n(n-1) \rangle }{\beta } $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Computing arbitrary off-diagonal observables often requires complicated secondary sampling procedures.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt; The main source for learning about SSE is this big review article by Sandvik: &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1101.3281&lt;/a&gt;. There is also an excellent recorded lecture by Roger Melko from the &lt;a href=&quot;https://boulderschool.yale.edu/2010/boulder-school-2010-lecture-notes&quot; rel=&quot;nofollow noreferrer&quot;&gt;2010 Boulder Summer School&lt;/a&gt; (the link to the videos is right below the title).&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-07-23T16:26:28.993" LastActivityDate="2020-07-23T16:26:28.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1635" PostTypeId="1" AcceptedAnswerId="1637" CreationDate="2020-07-23T09:04:30.160" Score="19" ViewCount="1346" Body="&lt;p&gt;I came across the concept of using phonons to establish a material's dynamical stability, based on whether or not imaginary frequencies are present in its phonon band structure.&lt;/p&gt;&#xA;&lt;p&gt;What I am struggling with is how to determine the phase transitions based on a phonon band structure with such imaginary frequencies? From what I have read, the recipe is to &lt;em&gt;follow the imaginary phonons&lt;/em&gt;. What does this mean? How does one follow such imaginary modes?&lt;/p&gt;&#xA;&lt;p&gt;An example illustrating this using perovskite transitions from the high symmetry &lt;span class=&quot;math-container&quot;&gt;$Pm\overline{3}m$&lt;/span&gt; space group to lower symmetries will be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1019" LastEditorUserId="792" LastEditDate="2020-07-23T18:11:41.777" LastActivityDate="2020-07-23T18:11:41.777" Title="How to deduce phase transitions from a phonon calculation?" Tags="|band-structure|phonons|symmetry|perovskites|lattice-dynamics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1636" PostTypeId="2" ParentId="1632" CreationDate="2020-07-23T09:33:21.583" Score="10" Body="&lt;p&gt;This is an excellent question! The reality is complicated even in LCAO calculations: every code has different defaults, which also depend on the run type.&lt;/p&gt;&#xA;&lt;p&gt;It seems that older LCAO codes simultaneously look at the convergence of the energy, and of the density matrix. Looking only at the change in energy is really bad behavior, since it doesn't tell you anything about being close to an extremal point of the energy functional: it might be that your optimizer is just doing a poor job and that you still have a significant gradient - especially since the error in the energy is second order in the error in the density, meaning that the energy converges much faster than the density itself. Now, if you also look at the change density matrix, then you have better information on the convergence of the calculation; however, again if your optimizer is misbehaving then it might be that the change in density (and thereby the energy) are small even though the orbitals don't correspond to an extremal point.&lt;/p&gt;&#xA;&lt;p&gt;The best way to determine convergence is to look at the orbital gradient: if it is small, then you are sure to be close to an extremal point. (It might still be just a saddle point instead of a local minimum!) Most modern LCAO codes I know rely on this measure of convergence via the DIIS error metric. If the Roothaan-Hall equations are fulfilled, &lt;span class=&quot;math-container&quot;&gt;${\bf FC} = {\bf SCE}$&lt;/span&gt;, then you can show that the density matrix &lt;span class=&quot;math-container&quot;&gt;${\bf P}={\bf C_{\rm occ} C_{\rm occ}^{\rm T}}$&lt;/span&gt; commutes with the Fock matrix:  &lt;span class=&quot;math-container&quot;&gt;${\bf e} = {\bf S P F} - {\bf F P S} = {\bf 0}$&lt;/span&gt;; if the equation does not hold, there is an orbital gradient which is measured by the numerical value of the commutator. (Remember: the Fock matrix is diagonal in the converged MO basis!)&lt;/p&gt;&#xA;&lt;p&gt;Often, the convergence threshold for the orbital gradient i.e. DIIS error is of the order of &lt;span class=&quot;math-container&quot;&gt;$10^{-5}$&lt;/span&gt; or smaller for single-point calculations, &lt;span class=&quot;math-container&quot;&gt;$10^{-7}$&lt;/span&gt; for force calculations, and &lt;span class=&quot;math-container&quot;&gt;$10^{-9}$&lt;/span&gt; for post-HF calculations. But, there's still many ways in which to measure the norm of the DIIS error: common choices are either the root-mean-square norm &lt;span class=&quot;math-container&quot;&gt;$e = \sqrt{\sum_{ij} e_{ij}^2}$&lt;/span&gt; or the maximum absolute error &lt;span class=&quot;math-container&quot;&gt;$e = \max_{ij} |e_{ij}|$&lt;/span&gt;. Many programs implement both metrics, and you need to check which one is used by default.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-24T14:43:17.110" LastActivityDate="2020-07-24T14:43:17.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1637" PostTypeId="2" ParentId="1635" CreationDate="2020-07-23T10:33:14.057" Score="21" Body="&lt;p&gt;&lt;strong&gt;Background theory.&lt;/strong&gt; In the harmonic approximation, the potential energy surface (PES) is expanded about an equilibrium point to second order, to obtain the Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}=\sum_{p,\alpha}-\frac{1}{2m_{\alpha}}\nabla_{p\alpha}^2+\frac{1}{2}\sum_{p,\alpha,i}\sum_{p^{\prime},\alpha^{\prime},i^{\prime}}D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})u_{pi\alpha}u_{p^{\prime}i^{\prime}\alpha^{\prime}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The basic quantity one builds when calculating phonons is the &lt;em&gt;matrix of force constants&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})=\frac{\partial^2E}{\partial u_{pi\alpha}u_{p^{\prime}i^{\prime}\alpha^{\prime}}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is the expansion coefficient of the second order term in the potential energy surface &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; labelling the Cartesian direction, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; the atom in the basis, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt; is the position of the cell &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; in the crystal, and &lt;span class=&quot;math-container&quot;&gt;$u_{pi\alpha}$&lt;/span&gt; is the amplitude of displacement of the corresponding atom. Using periodicity of the crystal, we can define the &lt;em&gt;dynamical matrix&lt;/em&gt; at each &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point of the Brillouin zone as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{q})=\frac{1}{N_p\sqrt{m_{\alpha}m_{\alpha^{\prime}}}}\sum_{\mathbf{R}_p,\mathbf{R}_{p^{\prime}}}D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})e^{i\mathbf{q}\cdot(\mathbf{R}_p-\mathbf{R}_{p^{\prime}})},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N_p$&lt;/span&gt; is the number of cells in the supercell over which periodic boundary conditions are applied, and &lt;span class=&quot;math-container&quot;&gt;$m_{\alpha}$&lt;/span&gt; is the mass of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. Diagonalizing the dynamical matrix gives eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\omega^2_{\mathbf{q}\nu}$&lt;/span&gt; and eigenvectors &lt;span class=&quot;math-container&quot;&gt;$v_{\mathbf{q}\nu;i\alpha}$&lt;/span&gt;. From these, it is possible to define a set of normal coordinates:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;u_{\mathbf{q}\nu}=\frac{1}{\sqrt{N_p}}\sum_{\mathbf{R}_p,i,\alpha}\sqrt{m_{\alpha}}u_{pi\alpha}e^{-i\mathbf{q}\cdot{\mathbf{R}_p}}v_{-\mathbf{q}\nu;i\alpha},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in terms of which the Hamiltonian becomes a sum over uncoupled simple harmonic oscillators:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}=\sum_{\mathbf{q},\nu}-\frac{1}{2}\frac{\partial^2}{\partial u_{\mathbf{q}\nu}^2}+\frac{1}{2}\omega^2_{\mathbf{q}\nu}u_{\mathbf{q}\nu}^2.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The bosonic quasiparticles labelled by quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt; are called phonons, and have energy &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; and momentum &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Dynamically stable structure.&lt;/strong&gt; A dynamically stable structure is one whose equilibrium position is at a local minimum of the PES. As such, the eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\omega^2_{\mathbf{q}\nu}$&lt;/span&gt; of the dynamical matrix (Hessian) are all positive numbers, and as a consequence the phonon frequencies &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; are all real.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Dynamically unstable structure.&lt;/strong&gt; A dynamically unstable structure is one whose equilibrium position is at a saddle point of the PES. As such, some of the eigenvalues of the dynamical matrix are negative, and the corresponding phonon frequencies imaginary.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Physical interpretation.&lt;/strong&gt; Phonons measure the &lt;em&gt;curvature&lt;/em&gt; of the PES around the equilibrium position of the material. As we have seen, an imaginary frequency corresponds to a negative curvature, so it corresponds to a direction in the PES along which the energy &lt;em&gt;decreases&lt;/em&gt;. This means that there is a lower energy configuration of the material, and we say that the structure is then &lt;em&gt;dynamically unstable&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&amp;quot;Follow the imaginary modes&amp;quot;.&lt;/strong&gt; How can we find such lower-energy structure? The eigenvectors of the dynamical matrix associated with the imaginary phonons tell us the direction along which the energy decreases, so we can &amp;quot;follow those modes&amp;quot; to find the lower energy structure. This can be done by simply constructing a sequence of structures on which you displace the atoms by an amplitude &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{q}\nu}$&lt;/span&gt; (see equation above) of the imaginary phonon &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt;, and calculating the total energy of each of the resulting structures. For a saddle point, the resulting curve will be something like a double well, and the minima of the double well correspond to your new lower-energy structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Finite temperature.&lt;/strong&gt; The discussion up to this point concerns the potential energy surface, so temperature is neglected. If you are interested in a calculation at finite temperature, then you need the &lt;em&gt;free energy&lt;/em&gt; surface. This is much harder to calculate and you need anharmonic terms in your Hamiltonian to describe it properly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Perovskites.&lt;/strong&gt; Perovskites typically have a cubic structure at high temperature, and then upon lowering the temperature undergo a number of phase transitions to lower-symmetry structures (tetragonal, orthorhombic, and so on). Imagine a perovskite that has only two phases, tetragonal at low temperature and cubic at high temperature (generalizing to more phases is trivial). Then if you calculate the phonons in the cubic structure (saddle point) you will find imaginary modes, and following them will take you to the tetragonal structure (minimum). If you calculate the phonons in the tetragonal structure, they will all have real frequencies. So why is the cubic phase stable at high temperatures? This is because, although the cubic phase corresponds to a saddle point of the potential energy surface, above some critical temperature it corresponds to a minimum of the free energy surface. As such, above that critical temperature the cubic phase becomes dynamically stable. As I mentioned above, to investigate this phase transition (e.g. to calculate the critical temperature), you need to include anharmonic terms (phonon-phonon interactions), which is much harder computationally.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-23T10:33:14.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1638" PostTypeId="2" ParentId="1635" CreationDate="2020-07-23T11:39:31.357" Score="13" Body="&lt;p&gt;The answer of @ProfM is already very complete, but I wanted to tackle your question from a more practical point of view.&lt;/p&gt;&#xA;&lt;p&gt;The presence of imaginary frequencies indicate that there are atomic positions which are more energetically favorable at the ground state. So, the concept of &amp;quot;following&amp;quot; a mode means condensing it onto the reference structure, until you find the equilibrium positions.&lt;/p&gt;&#xA;&lt;p&gt;To give an example, we can start with &lt;span class=&quot;math-container&quot;&gt;$\ce{BaTiO_3}$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$Pm\overline{3}m$&lt;/span&gt; symmetry. By looking at the phonon frequencies you will notice the instability (imaginary frequency) at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;, which for this case in particular corresponds to the so-called ferroelectric mode.&lt;/p&gt;&#xA;&lt;p&gt;Once you know the phonon of interest, you can read its eigendisplacements (&lt;span class=&quot;math-container&quot;&gt;$U_{FE}$&lt;/span&gt;), condense them onto the reference structure (&lt;span class=&quot;math-container&quot;&gt;$S_{ref}$&lt;/span&gt;) using different amplitudes &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{\alpha} = S_{ref} + \alpha U_{FE}$$&lt;/span&gt;&#xA;and then calculate the energy for each of the resulting structures (&lt;span class=&quot;math-container&quot;&gt;$S_{\alpha}$&lt;/span&gt;). You will notice that, as you increase the value &lt;span class=&quot;math-container&quot;&gt;$|\alpha|$&lt;/span&gt;, the total energy of the system decreases until it starts increasing again, creating a potential well. The structure with the minimum energy will be the one at equilibrium (according to the selected mode).&lt;/p&gt;&#xA;&lt;p&gt;Coming back to the &lt;span class=&quot;math-container&quot;&gt;$\ce{BaTiO_3}$&lt;/span&gt; example, the new structure &lt;span class=&quot;math-container&quot;&gt;$S_{\alpha, E_{min}}$&lt;/span&gt; should show a &lt;span class=&quot;math-container&quot;&gt;$P4mm$&lt;/span&gt; symmetry. However, you would need to relax the phase, as strain also needs to be included.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note&lt;/strong&gt;: &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; can be any real value but it is case-specific (depending on the anharmonicities of the system and on the definition of the eigendisplacements), so would have to try with different options to determine which one is better for your case.&lt;/p&gt;&#xA;" OwnerDisplayName="user249" LastEditorUserId="7" LastEditDate="2020-07-23T12:50:37.557" LastActivityDate="2020-07-23T12:50:37.557" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1639" PostTypeId="1" CreationDate="2020-07-23T15:30:13.767" Score="11" ViewCount="300" Body="&lt;p&gt;I want to calculate the density of states of GaAs conduction band (preferably each valley like Gamma, L and X). Is there any software available where I can easily generate DOS?&lt;/p&gt;&#xA;&lt;p&gt;Has the DOS of GaAs been studied previously?&lt;/p&gt;&#xA;" OwnerUserId="1111" LastEditorUserId="5" LastEditDate="2020-07-23T18:14:19.543" LastActivityDate="2020-07-25T02:12:41.867" Title="Is there any software that can generate the electronic DOS of GaAs?" Tags="|density-functional-theory|quantum-espresso|band-structure|from-phys-se|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1640" PostTypeId="2" ParentId="1633" CreationDate="2020-07-23T16:17:28.143" Score="10" Body="&lt;p&gt;In terms of the role of chemists for what you call the &amp;quot;most essential task&amp;quot;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What I understand is that the most essential task is the improvement&#xA;of exchange correlation functionals to give better and more accurate&#xA;results&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;... &lt;strong&gt;the development of them&#xA;is a job for a quantum physicist for example&lt;/strong&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am reminded of two questions we've had here so far:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/392/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2/5&quot;&gt;What is the closest thing we have to &amp;quot;the&amp;quot; universal density functional?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;For the first question&lt;/strong&gt;: several milestones have been explained in the answers so far:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/N3BDU.png&quot; Width=&quot;300&quot;&gt;&#xA;&lt;p&gt;&lt;strong&gt;100% of these paper's have authors in chemistry departments.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In all cases, the first/only author is a chemist, except for the last paper, where the senior-most author John Perdew has a dual affiliation with Physics and Chemistry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For the second question:&lt;/strong&gt; Three people have answered so far, regarding what the closest thing to a &amp;quot;perfect&amp;quot; exchange-correlation functional might be, and all three of them were chemists, as well as the authors in the papers cited in those answers.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Summary:&lt;/strong&gt; Milestones in functional development over the years have come both from physicists and chemists, with many of the key papers since 1993 seemingly coming from people in chemistry departments (or in some cases with dual affiliation in both chemistry and physics).&lt;/p&gt;&#xA;&lt;p&gt;I am also not trying to say that chemists are more important than physicists: Walter Kohn (inventor of DFT) got his undergrad degree in Mathematics and his PhD in Physics, before getting a Nobel Prize in Chemistry. My answers &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1329/5&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1321/5&quot;&gt;here&lt;/a&gt; also show that much of the early DFT development was done on the uniform electron gas, by particle physicists like Keith Brueckner and Jeffrey Goldstone (these two were also important players in the coupled cluster method, which is now developed and used much more by chemists).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-23T16:17:28.143" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1641" PostTypeId="2" ParentId="1639" CreationDate="2020-07-23T17:13:20.047" Score="8" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$\ce{GaAs}$&lt;/span&gt; is one of the must studied semiconductors. One of its main application was as the active site of semiconductor laser, becoming the first stable material used on this devices (by stable, I mean long time duration at room temperature) and it is used in any red (due to the gap) laser pointer.&lt;/p&gt;&#xA;&lt;p&gt;For electronic data, you can consult &lt;a href=&quot;http://www.ioffe.ru/SVA/NSM/Semicond/GaAs/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; page at the Russian &lt;a href=&quot;http://www.ioffe.ru/index_en.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ioffe institute&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Answering your questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Codes for calculate the density of states (DOS): SIESTA, Quantum Espresso, ABINIT, ORCA, CASTEP (all free), VASP, CRYSTAL ($$$). (almost any software capable to work with periodic systems)*.&lt;/li&gt;&#xA;&lt;li&gt;Has DOS of GaAs been studied previously: Yes. In the Ioffe page you will find information about the electronic properties.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;*Be aware that one of the pitfalls of DFT is the calculation of the gap for semiconductor materials. But, the shape of the bands and DOS are calculated right.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-25T02:12:41.867" LastActivityDate="2020-07-25T02:12:41.867" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1642" PostTypeId="1" AcceptedAnswerId="8352" CreationDate="2020-07-23T20:13:51.390" Score="15" ViewCount="294" Body="&lt;p&gt;Cross-posted on &lt;a href=&quot;https://physics.stackexchange.com/q/508605/134583&quot;&gt;Physics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;The famous Hohenberg-Kohn theorems say that there is a one-to-one mapping between the many-body Hamiltonian, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{H}$&lt;/span&gt;, of a solid and its ground-state electron density &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt;. As far as I understand, this also means that all the properties of the ground-state wavefunction are encoded in the electron density itself (though perhaps not in a simple way).&lt;/p&gt;&#xA;&lt;p&gt;Density functional theory aims to solve for this ground-state electron density &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt; through various simplifications and manipulations of &lt;span class=&quot;math-container&quot;&gt;$\mathcal{H}$&lt;/span&gt; to make the process computationally tractable.&lt;/p&gt;&#xA;&lt;p&gt;I am interested in the reverse process, where an experimentalist comes up to me with their measured &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt;. In principle, a sufficiently accurate measurement of the electron density can be done with X-ray scattering (or electron microscopy) to obtain &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt;. Typically, such measurements of &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt; are only used to get the positions of the atoms in a crystal, but the Hohenberg-Kohn theorems and DFT suggest you could do a lot more with &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So my question is: &lt;strong&gt;Given an experimentally determined &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt; to arbitrary accuracy, what can we say about a material's properties using &amp;quot;inverse&amp;quot; DFT?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As a followup, what experimental accuracy for &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt; is needed to accurately determine those material properties?&lt;/p&gt;&#xA;" OwnerUserId="1113" LastEditorUserId="5" LastEditDate="2021-12-27T05:00:57.597" LastActivityDate="2021-12-27T05:00:57.597" Title="Can we &quot;invert&quot; Density Functional Theory through sufficiently accurate experiment?" Tags="|density-functional-theory|condensed-matter|from-phys-se|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1643" PostTypeId="1" CreationDate="2020-07-23T23:26:46.417" Score="8" ViewCount="434" Body="&lt;p&gt;The &lt;code&gt;FCIDUMP&lt;/code&gt; format was &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/0010465589900337?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;created by Peter Knowles and Nick Handy &lt;em&gt;circa&lt;/em&gt; 1989&lt;/a&gt; and now allows many electronic structure software packages to interact with each other.&lt;/p&gt;&#xA;&lt;p&gt;For example imagine we want to calculate the 1- and 2-electron integrals with &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00532&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenMOLCAS&lt;/a&gt; (likely the fastest and most general open-source software for calculating integrals) then run a rather special electronic structure method like FCIQMC with those integrals (FCIQMC is best done with the &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0005754&quot; rel=&quot;nofollow noreferrer&quot;&gt;NECI software&lt;/a&gt; written mainly by the people that invented and developed FCIQMC). In this case the integrals will be calculated in OpenMOLCAS, printed to an &lt;code&gt;FCIDUMP&lt;/code&gt; file, then the software NECI will read the integrals from that file.&lt;/p&gt;&#xA;&lt;p&gt;The following programs are able to interact with &lt;code&gt;FCIDUMP&lt;/code&gt; files in some way:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;MOLPRO&lt;/strong&gt;  (can read and write)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;PySCF&lt;/strong&gt; (can read and write)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;(Open)MOLCAS&lt;/strong&gt; (can write)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;ARROW&lt;/strong&gt; (can read and modify)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DALTON&lt;/strong&gt; (can write)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DIRAC&lt;/strong&gt; (can write)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;GAMESS&lt;/strong&gt; (can write, with a plug-in)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;DICE&lt;/strong&gt; (can read and maybe modify)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;BLOCK&lt;/strong&gt; (can read and maybe modify)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;CheMPS2&lt;/strong&gt; (can read and maybe modify)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;xacc&lt;/strong&gt; (can read)&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;anymore you wish to add&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The following can interact with the standard &lt;code&gt;FCIDUMP&lt;/code&gt; format of 1989, but can also support generalizations of it:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;NECI&lt;/strong&gt; (can read, and modify standard &lt;code&gt;FCIDUMP&lt;/code&gt; files, and can write some 3-body integrals)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;BAGEL&lt;/strong&gt; (can write complex-valued integrals for 4-component relativistic calculations)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;HANDE&lt;/strong&gt; (can include more 1-electron integrals, including orbital energies, can list UHF/RHF)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Psi4&lt;/strong&gt; (supports the generalized format of HANDE)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For some of these programs, like MOLPRO, &lt;code&gt;FCIDUMP&lt;/code&gt; format is supported &lt;strong&gt;natively&lt;/strong&gt; and it's quite straightforward to figure out how to read/write &lt;code&gt;FCIDUMP&lt;/code&gt; files, by browsing the software's manual. However other programs need an extra plug-in, and/or have some caveats, and/or require slightly non-trivial work to grease the wheels to support &lt;code&gt;FCIDUMP&lt;/code&gt; formatted integrals, and/or the support is not explained in the manual. &lt;strong&gt;In these cases, how does one read or write integrals in &lt;code&gt;FCIDUMP&lt;/code&gt; format?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Please write only one answer per software package).&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-03T02:42:54.223" LastActivityDate="2021-06-23T22:27:46.303" Title="How do the various programs read or write integrals in FCIDUMP format?" Tags="|software|electronic-structure|one-topic-per-answer|integrals|fcidump|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1644" PostTypeId="1" CreationDate="2020-07-23T23:49:33.173" Score="9" ViewCount="421" Body="&lt;p&gt;Experimentally, anisotropy factor is calculated by dividing the CD (circular dichroism) spectra by the absorbance spectra and multiplying by a factor of 32980 (in order to get a dimensionless quantity).&lt;/p&gt;&#xA;&lt;p&gt;Theoretical calculations can be performed via TDDFT to obtain rotatory and oscillatory strengths, obtaining excitations for each case and adjusting, for each excitation, a curve, obtaining then the &amp;quot;theoretical absorbance/CD spectra&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;How can then we define a theoretical anisotropy factor: Does it make sense? Should another calculation be performed?&lt;/p&gt;&#xA;&lt;p&gt;Would you divide both adjusted curves or divide the corresponding excitations, adjusting a new set of curves to what you get?&lt;/p&gt;&#xA;&lt;p&gt;Any clues?&lt;/p&gt;&#xA;" OwnerUserId="1116" LastEditorUserId="5" LastEditDate="2020-07-27T16:21:24.753" LastActivityDate="2023-09-28T18:18:50.030" Title="Is there an anisotropy factor (g factor) for TDDFT absorption and circular dichroism calculations?" Tags="|density-functional-theory|quantum-chemistry|td-dft|from-phys-se|spectroscopy|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1645" PostTypeId="1" CreationDate="2020-07-24T00:11:07.757" Score="6" ViewCount="270" Body="&lt;p&gt;I recently started using &lt;a href=&quot;http://m3g.iqm.unicamp.br/packmol/home.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;PACKMOL&lt;/a&gt; to pack a few proteins together. I wrote this PACKMOL code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tolerance 3.0&#xA;filetype pdb&#xA;output E_S.pdb&#xA;&#xA;structure E.pdb&#xA;  number 1&#xA;  inside box -44. 0. 0. 156. 50. 130.&#xA;  center&#xA;  fixed 0. 0. 0. 0. 0. 0.&#xA;end structure&#xA;&#xA;structure 6vxx.pdb&#xA;  number 1&#xA;  inside box -44. 50. 0. 100. 200. 150.&#xA;  center&#xA;  fixed 0. 116. 0. 4.71238898 0. 0.&#xA;end structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This code is to fix/attach one protein (SARS-CoV-2 Spike glycoprotein) onto another (SARS-CoV-2 Membrane protein)&#xA;I ended up fixing different values so that the structure would look like its attached.&#xA;When the code ran and the structure was generated the &amp;quot;Bonds&amp;quot; checkbox when visualized in the software &lt;a href=&quot;https://www.ovito.org/docs/current/&quot; rel=&quot;nofollow noreferrer&quot;&gt;OVITO&lt;/a&gt; was found missing meaning &lt;strong&gt;there is no bonding that exists&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Why did this happen?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="707" LastEditorUserId="605" LastEditDate="2022-12-10T10:53:34.150" LastActivityDate="2022-12-10T10:53:34.150" Title="Why am I losing bonds when I use PACKMOL on two proteins?" Tags="|molecular-dynamics|software|docking|covid-19|packmol|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1646" PostTypeId="1" AcceptedAnswerId="1798" CreationDate="2020-07-24T00:32:47.257" Score="13" ViewCount="1600" Body="&lt;p&gt;I frequently see LAMMPS codes, and almost all of them have the  &lt;code&gt;neighbor 0.5 bin&lt;/code&gt; command. I completely studied the &lt;a href=&quot;https://lammps.sandia.gov/doc/neighbor.html&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS manual for the neighbour command&lt;/a&gt; and did not understand anything regarding this command.&#xA;Could anyone help with these questions below?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What is the basic purpose of this command?&lt;/li&gt;&#xA;&lt;li&gt;What is a Neighbor list and why is it important?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="707" LastEditorUserId="707" LastEditDate="2020-07-28T03:14:23.750" LastActivityDate="2020-07-28T08:01:46.440" Title="What does the Neighbor command do in LAMMPS?" Tags="|software|molecular-dynamics|molecular-modeling|lammps|molecular-interactions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1647" PostTypeId="1" CreationDate="2020-07-24T02:26:32.950" Score="5" ViewCount="220" Body="&lt;p&gt;Complementary to this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1643/5&quot;&gt;How do the various programs read or write integrals in FCIDUMP format?&lt;/a&gt; which attempts to list all electronic structure packages that support the &lt;code&gt;FCIDUMP&lt;/code&gt; format for 1- and 2-electron integrals, I wonder which programs &lt;em&gt;do not&lt;/em&gt; support &lt;code&gt;FCIDUMP&lt;/code&gt; files, how such programs store their integrals, and what ways (if any) exist to get around the lack of support for for  &lt;code&gt;FCIDUMP&lt;/code&gt; files?&lt;/p&gt;&#xA;&lt;p&gt;There's some programs that print integrals in binary format only (rather than in the ASCII format of &lt;code&gt;FCIDUMP&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;GAUSSIAN&lt;/li&gt;&#xA;&lt;li&gt;ORCA&lt;/li&gt;&#xA;&lt;li&gt;CFOUR&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;anything else you may add&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There's other programs that print in ASCII but not exactly the &lt;code&gt;FCIDUMP&lt;/code&gt; format, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MRCC&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;anything else you may add&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I will answer below about how one can &amp;quot;hack&amp;quot; MRCC to read &lt;code&gt;FCIDUMP&lt;/code&gt; formatted integrals, and I am &lt;em&gt;very&lt;/em&gt; curious to see how it can be done for other programs!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-03T02:42:40.500" LastActivityDate="2020-09-10T18:19:41.180" Title="For software that does not support FCIDUMP format, what format is used and how can we get the software to interact with FCIDUMP integrals?" Tags="|software|one-topic-per-answer|integrals|orca|fcidump|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1648" PostTypeId="2" ParentId="1647" CreationDate="2020-07-24T02:26:32.950" Score="4" Body="&lt;h2&gt;MRCC&lt;/h2&gt;&#xA;&lt;p&gt;MRCC stores 1- and 2-electron integrals in an ASCII file called &lt;code&gt;fort.55&lt;/code&gt; which is formatted very similarly to &lt;code&gt;FCIDUMP&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;fort.55&lt;/code&gt; file stores the integral values and integral indices in exactly the same way as in &lt;code&gt;FCIDUMP&lt;/code&gt;, but has a different header. One has to delete the header of the &lt;code&gt;FCIDUMP&lt;/code&gt; file and replace it with something like this (here my example is for the frozen-core carbon atom with an aug-cc-pVDZ basis set):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                    22                     4&#xA;                     1                     2                     3&#xA;                     5                     1                     2&#xA;                     3                     5                     1&#xA;                     4                     6                     7&#xA;                     1                     2                     3&#xA;                     5                     1                     1&#xA;                     4                     6                     7&#xA;                     1&#xA; 0&#xA;  0.43849259240468241305E+00   1   1   2   2&#xA;  0.43849259240468135834E+00   1   1   3   3&#xA;  0.48783372394503787817E+00   2   2   3   3&#xA;  0.51270165447111978874E-01   1   2   2   5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the &lt;code&gt;fort.55&lt;/code&gt; header shown above, the 22 is the number of spatial orbitals, the 4 is the number of correlated electrons, and the 22 following numbers are the irreps for the spatial orbitals (in this case the carbon atom is being treated with &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; and you can use my &lt;a href=&quot;https://github.com/HPQC-LABS/QC_CheatSheet/blob/master/symmetry&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum Chemistry Cheat Sheet&lt;/a&gt; to convert between the numbering conventions of some of the most popular quantum chemistry codes (for example my cheat sheet tells you that the &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt; irrep is 5 in MOLPRO but 6 in MRCC).&lt;/p&gt;&#xA;&lt;p&gt;Once you have converted your &lt;code&gt;FCIDUMP&lt;/code&gt; file into a &lt;code&gt;fort.55&lt;/code&gt; file, you now have to &amp;quot;trick&amp;quot; MRCC into reading it (because by default MRCC is not meant to be reading in other program's integrals except in the specific cases where an interface has been written to communicate with a program).&lt;/p&gt;&#xA;&lt;p&gt;This can be done by using the keyword &lt;code&gt;iface=cfour&lt;/code&gt;, which makes MRCC think that it's getting a &lt;code&gt;fort.55&lt;/code&gt; file printed from the CFOUR-MRCC interface, &lt;em&gt;&lt;strong&gt;when really it came from an &lt;code&gt;FCIDUMP&lt;/code&gt;!&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-24T02:26:32.950" CommentCount="0" CommunityOwnedDate="2023-05-26T22:49:31.710" ContentLicense="CC BY-SA 4.0" />
  <row Id="1649" PostTypeId="1" CreationDate="2020-07-24T06:28:38.180" Score="12" ViewCount="399" Body="&lt;p&gt;When applying for PhD programs or looking for research experiences, what is a good way to evaluate the quality of a school's matter modeling research portfolio? For broader disciplines (physics, chemistry, materials science) there are well-established rankings, but matter modeling doesn't fit neatly into any of these categories.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="7" LastEditDate="2020-07-29T16:18:10.573" LastActivityDate="2020-07-29T16:18:10.573" Title="How to find good universities for matter modeling?" Tags="|education|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1650" PostTypeId="2" ParentId="1618" CreationDate="2020-07-24T06:48:30.283" Score="6" Body="&lt;p&gt;Here I'll assume that the material is &lt;em&gt;already&lt;/em&gt; believed to be roughly described by a model of the Heisenberg or Ising form. In that case, you just want a quantity that is easy to measure in your experiment and easy to extract from numerics (or with a well-established theoretical value).&lt;/p&gt;&#xA;&lt;p&gt;In practice, the choice of which quantity to use will depend on convenience. If you are already set up to measure the temperature dependence of specific heat, you might do that. You might also measure &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt;, or the magnetic field required to achieve total saturation. The choice will also be influenced by the parameter regime (temperature, field, pressure) in which the comparison to the theoretical model is the most relevant.&lt;/p&gt;&#xA;&lt;p&gt;Here are a couple examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In this neutron scattering study, they determined &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; by comparing the magnon excitation dispersion (measured with neutron scattering) to the theoretical predictions. &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.124.197203&quot; rel=&quot;noreferrer&quot;&gt;Dally &lt;em&gt;et al.&lt;/em&gt; Phys. Rev. Lett. &lt;strong&gt;124,&lt;/strong&gt; 197203 (2020)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;In this field-polarized study, they used the magnetic susceptibility fit to the (previously documented) Bonner-Fisher result. &lt;a href=&quot;https://doi.org/10.1038/s41567-017-0010-y&quot; rel=&quot;noreferrer&quot;&gt;Blanc, Trinh &lt;em&gt;et al.&lt;/em&gt; Nat. Phys. &lt;strong&gt;14,&lt;/strong&gt; 273 (2018)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-07-24T06:48:30.283" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1651" PostTypeId="2" ParentId="1649" CreationDate="2020-07-24T09:07:05.200" Score="13" Body="&lt;p&gt;In my experience the materials modelling field is unfortunately a bit niche to have a good ranking system. Having just done this to start my PhD, here are my tips.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Supercomputing and IT Facilities&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Check out all the universities with good access to supercomputers, either operating their own on site or have a significant stake in a consortium. Not only will these resources be vital to your own PhD but good computing facilities tend to attract the best researchers. Equally, an institute with good modelling researchers will be able to get the grants to build computing facilities, so it can tell you if the place has a history of computational work. If you go and visit a school, always ask what the IT department are like and how quick/flexible they are. A bad IT department can make or break a project.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Major Contributions in Field&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Have a look for people who have developed significant theories in their field that have been adopted into many other works. In my case I'd look to the people behind MD forcefields such as Goddard group at Caltech or people like Nosé, Parinello and Rahman who have developed thermostat and barostat algorithms. However, if you aren't interested in the work don't just follow a big name. Often less well known researchers have more time to discuss work with you and are more flexible to what you want to do.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Check the Type of Modelling&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Following on from the point above, make sure that the modelling being done is what you're interested in. A lot of PhD adverts state &amp;quot;modelling&amp;quot; as a buzzword without specifying what simulation scale or focus. From my own experience I'm interested in organic polymers, but this often comes under &amp;quot;soft matter&amp;quot; which also includes lots of biological/drug modelling work. Many people want to start incorporating modelling into their work, but a lot don't have the background and experience to help a PhD student get started in the field.&lt;/p&gt;&#xA;&lt;p&gt;Best of luck finding a PhD!&lt;/p&gt;&#xA;" OwnerUserId="1104" LastEditorUserId="1104" LastEditDate="2020-07-24T10:17:09.133" LastActivityDate="2020-07-24T10:17:09.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1652" PostTypeId="2" ParentId="1631" CreationDate="2020-07-24T10:51:28.570" Score="5" Body="&lt;p&gt;Not a full answer, and it's too big for as a comment, but I can explain the line&lt;code&gt;fix charge all qeq/reax 1 0.0 10.0 1.0e-6 reax/c&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This function uses the charge equilibration method (QEq) from Rappe and Goddard (&lt;a href=&quot;https://doi.org/10.1021/j100161a070&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/j100161a070&lt;/a&gt;) to calculate the partial charges on each atom in the simulation. It's not moving anything in the simulation and in this case I don't think the partial charges are even feeding into anything so I reckon you can remove that line without impacting the model. If you're using a forcefield that needs partial charges then I normally use something like the following code to print the the partial charges:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;group       type1 type 1    # For atomtype 1&#xA;compute     charge1 type1 property/atom q&#xA;compute     q1 type1 reduce ave c_charge1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Followed later by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;thermo_style    custom step pe c_q1 ...    # Where ... is any other computes etc.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope that helps explain at least some of the code!&lt;/p&gt;&#xA;" OwnerUserId="1104" LastActivityDate="2020-07-24T10:51:28.570" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1653" PostTypeId="2" ParentId="1633" CreationDate="2020-07-24T13:25:53.573" Score="9" Body="&lt;p&gt;As a computational chemist, I find my role is to act as a translator. In a molecular dynamics simulation, I need to know enough physics and maths to translate chemical structures into a physical model, and make sure that the physics at play produces a model that makes sense chemically. Then if I'm doing multiscale modelling, say at finite element level, I need to know enough engineering to translate my chemical model into a larger structure like a beam or panel.&lt;/p&gt;&#xA;&lt;p&gt;Nike makes the good point that a lot of seemingly physics based papers are written by chemists. My view on this is that these people are best translators, those that understand enough physics that they can develop new tools to represent chemistry in new and innovative ways.&lt;/p&gt;&#xA;&lt;p&gt;If you think of materials science as the crossroads of engineering, chemistry and physics, computational materials science pushes that even further by adding computer science into the mix.&lt;/p&gt;&#xA;" OwnerUserId="1104" LastEditorUserId="5" LastEditDate="2020-07-24T15:01:46.470" LastActivityDate="2020-07-24T15:01:46.470" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1654" PostTypeId="2" ParentId="1633" CreationDate="2020-07-24T14:53:58.693" Score="8" Body="&lt;p&gt;The role of the chemist in computational chemistry is to ask the right questions. Then, the computational chemist can step in, and start computing. The computational chemist should know which models are good for the problem in question, and what kinds of pitfalls to watch out for.&lt;/p&gt;&#xA;&lt;p&gt;Then, at the very deep end you have the method developers as well as the code developers, who know the intrinsics of the chemical models and how they are implemented. To develop code, you don't have to understand &lt;em&gt;why&lt;/em&gt; a method works, but to develop better methods you &lt;em&gt;do&lt;/em&gt; have to know this. What often happens is that people start by writing code, and then as their career advances the younger people step in...&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-24T14:53:58.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1655" PostTypeId="2" ParentId="1645" CreationDate="2020-07-24T14:57:25.780" Score="5" Body="&lt;p&gt;Packmol is used to pack molecules into a given box at random positions and with random rotations.&lt;/p&gt;&#xA;&lt;p&gt;If you want the spike glycoprotein to be attached to the membrane, you should probably prepare a new structure containing the two molecules as a single unit which Packmol won't break.&lt;/p&gt;&#xA;&lt;p&gt;Now you have achieved your goal. Next, you can use packmol for what it's really used for i.e. adding further molecules for solvation.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-24T19:49:44.947" LastActivityDate="2020-07-24T19:49:44.947" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1656" PostTypeId="1" CreationDate="2020-07-24T15:30:10.073" Score="11" ViewCount="152" Body="&lt;p&gt;When creating a new bond in a LAMMPS simulation with the command fix/bond create it is likely new angles/dihedrals/impropers be need to be set. This can be done with the atype/dtype/itype arguments however, these arguments seem to only take one integer value. I have models where many types of angles or dihedrals could be created from the formation of one new bond. &lt;strong&gt;How do you set multiple of these types at once, and specify which new angle/dihedral belongs to which type?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1104" LastEditorUserId="5" LastEditDate="2021-01-30T18:31:15.133" LastActivityDate="2021-01-30T18:31:15.133" Title="Setting multiple new atype/dtype/itype with LAMMPS fix bond/create" Tags="|software|molecular-dynamics|lammps|software-assistance|openpathsampling|" AnswerCount="0" CommentCount="3" ClosedDate="2021-04-18T13:36:28.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="1657" PostTypeId="1" CreationDate="2020-07-24T16:27:58.290" Score="17" ViewCount="618" Body="&lt;p&gt;The &lt;a href=&quot;https://www.mgi.gov/&quot; rel=&quot;noreferrer&quot;&gt;Materials Genome Initiative&lt;/a&gt; held a 2017 workshop, that led to this published report: &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0173-4&quot; rel=&quot;noreferrer&quot;&gt;de Pablo et al., &lt;em&gt;&amp;quot;New frontiers for the materials initiative,&amp;quot;&lt;/em&gt; npj Computational Materials &lt;strong&gt;5&lt;/strong&gt;, 41 (2019)&lt;/a&gt;. In part, this report lists various successes of the initiative, due to complementary theoretical, computational, and experimental studies. Perhaps more interestingly, it also lists several challenges for future research. One particular challenge that gets listed in several contexts is related to computational modeling of synthesis:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Improving computational support for the synthesis of soft materials would be very valuable. Although significant steps have been made using machine learning to predict outcomes of simple organic reactions,&lt;a href=&quot;https://doi.org/10.1021%2Facscentsci.7b00064&quot; rel=&quot;noreferrer&quot;&gt;36&lt;/a&gt;,&lt;a href=&quot;https://doi.org/10.1002%2Fchem.201604556&quot; rel=&quot;noreferrer&quot;&gt;37&lt;/a&gt; extending this capability to include a larger range of chemical variety and macromolecular synthesis would democratize chemical synthesis and accelerate our validation of theories for new chemistries. Computational guidance in the iterative experimental synthesis process is also critical to future advances.&lt;a href=&quot;https://doi.org/10.1021%2Facsnano.8b04726&quot; rel=&quot;noreferrer&quot;&gt;38&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Recent advances, particularly in x-ray diffraction at high temperatures, pressures, and inert environments could allow a more quantitative understanding of the thermodynamics of crystal synthesis. This could improve computational models of nucleation and crystal formation, help optimize the synthesis of known materials, as well as drive the discovery of new non-equilibrium compounds that are only stable under narrow conditions. Computational models of synthesis would be helpful to encourage feedback between theory and synthesis and enable calculations of optimal synthetic conditions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Often synthesis is referred to as an &lt;strong&gt;art&lt;/strong&gt;, which exudes respect for those active in the field, but may also signify that theory is lagging significantly behind the practice. Of course, synthesis typically occurs through rapid non-equilibrium processes, and sometimes at very elevated temperatures or in unusual atmospheres. This makes modeling such reactions beyond the input/output scope of simple reaction equations rather challenging, and a very different proposal to the calculation of equilibrium properties of some material post-synthesis. However, smart people have made progress on difficult problems before, and it seems clear that such modeling could potentially bring new insight and advance the art itself - and perhaps the design of novel materials.&lt;/p&gt;&#xA;&lt;p&gt;Hence, I wonder:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;How well can we theoretically or computationally model the &lt;em&gt;dynamics&lt;/em&gt; of synthesis today, whether of molecules or crystals? What is considered state-of-the art, and what are its limitations?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Have there been any particularly striking successes or failures in this regard?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Do such computations incorporate quantum physics?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Personally, I am particularly interested in the case of transition metal systems (e.g. oxides). However, I'd suspect there's been considerable advances on the side of molecular and organic chemistry, where there might be a large interest in such methods from the medical industry. In support of this hunch, I was able to find a &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_computer-assisted_organic_synthesis_software&quot; rel=&quot;noreferrer&quot;&gt;List of computer-assisted organic synthesis software&lt;/a&gt; on Wikipedia, but no matching lists for the general or inorganic cases.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-08-27T10:59:04.400" Title="How well can we model chemical synthesis?" Tags="|computational-chemistry|materials-design|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1658" PostTypeId="2" ParentId="1657" CreationDate="2020-07-24T16:37:24.177" Score="10" Body="&lt;p&gt;The computations &lt;em&gt;do&lt;/em&gt; include quantum physics, since the very bare minimum of electronic structure calculations involve the quantum mechanics of electrons.&lt;/p&gt;&#xA;&lt;p&gt;There's been quite a lot of development in computational chemistry in synthesis. While computational chemistry was pivotal already in the late 1980s in developing ozone safe alternatives to cholorofluorocarbons, see &lt;a href=&quot;https://physicstoday.scitation.org/doi/10.1063/1.2911179&quot; rel=&quot;nofollow noreferrer&quot;&gt;Physics Today 61, 4, 58 (2008)&lt;/a&gt;; nowadays computations are often leading the design effort of new syntheses since calculations are much faster to carry out than lab experiments, see &lt;a href=&quot;https://www.nature.com/articles/ncomms10109/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nature Communications volume 7, 10109 (2016)&lt;/a&gt;, for example.&lt;/p&gt;&#xA;&lt;p&gt;Cody briefly explained transition state theory below. I could also point out a recently published paper on a success of transition state theory: the H2S+Cl system where dynamical effects were though to be important is actually fully described by transition state theory, it's just that you need a very good quantum chemical description to achieve the necessary accuracy in the computations: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c00354&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 2020, acs.jctc.0c00354&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-25T07:57:52.450" LastActivityDate="2020-07-25T07:57:52.450" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1659" PostTypeId="1" AcceptedAnswerId="1663" CreationDate="2020-07-24T16:39:43.303" Score="7" ViewCount="548" Body="&lt;p&gt;Below is the free energy profile obtained after a histogram analysis of an umbrella sampling simulation. Generally, one is interested in the free energy difference (highest energy minus lowest energy). Let's assume that we have a good assumption where the lowest and highest are on the reaction coordinate.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Should one run an umbrella simulation on the entire reaction coordinate?&lt;/li&gt;&#xA;&lt;li&gt;Isn't sampling the lowest and highest energy region enough to derive the free energy difference?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uPSCB.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uPSCB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Image source: &lt;a href=&quot;http://www.mdtutorials.com/gmx/umbrella/07_analysis.html&quot; rel=&quot;noreferrer&quot;&gt;http://www.mdtutorials.com/gmx/umbrella/07_analysis.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="125" LastEditDate="2020-07-24T16:50:35.250" LastActivityDate="2020-07-25T00:58:44.453" Title="Is it required to sample the full reaction coordinate in umbrella sampling?" Tags="|binding-energy|enhanced-sampling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1660" PostTypeId="2" ParentId="1657" CreationDate="2020-07-24T17:16:49.957" Score="12" Body="&lt;p&gt;Okay first some basics:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For most reactions we do not need to run molecular dynamics&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Molecules are like springs and obey the principles of minimum energy. Therefore, normally the dynamics of a molecule will be distributed around the &amp;quot;minimum energy path&amp;quot; going from reactants to products.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/amwdK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/amwdK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The maximum along this minimum energy path is the transition state, and has energy &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt;, which can be used to calculate the rate of the reaction with transition state theory&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k=Ae^{-E_A/RT}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you were to run dynamics simulations, first you would find that would not be easy to observe a reaction take place; the movement and vibrations of the individual particles occur on the &lt;span class=&quot;math-container&quot;&gt;$10^{-15}$&lt;/span&gt; s timescale, but the reaction events are much rarer, and far between (e.g. seconds or longer) -- this is a consequence of the principle of minimum energy. Secondly, you would find that&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the reacting particles must collide with each other&lt;/li&gt;&#xA;&lt;li&gt;the reacting particles must have enough energy to break the old bonds&lt;/li&gt;&#xA;&lt;li&gt;the particles must have the proper orientation&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In other words, they follow the minimum energy path! This theory is a workhorse in modern computational chemistry and is used by the Nature paper linked by Susi Lehtola.&lt;/p&gt;&#xA;&lt;p&gt;Okay, now that that is in order, one apparent area where reaction modeling breaks down is when there is a bifurcation event after the transition state, for example &lt;a href=&quot;http://www.compchemhighlights.org/2014/04/post-transition-state-dynamics-in.html&quot; rel=&quot;noreferrer&quot;&gt;see here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;These &lt;strong&gt;DO&lt;/strong&gt; require molecular dynamics because there is recrossing and also dynamical effects with a bifurcating potential energy surface.&lt;/p&gt;&#xA;&lt;p&gt;However, if you're not aware of this then, then the products that you predict will be wildly off from experiments.&lt;/p&gt;&#xA;&lt;p&gt;See for example, this excellent paper by Singleton &lt;em&gt;et al.&lt;/em&gt;&#xA;&amp;quot;Recrossing and Dynamic Matching Effects on Selectivity in a Diels-Alder Reaction&amp;quot;, Angew Chem Int, Ed, &lt;strong&gt;2009&lt;/strong&gt;, 48, 9156&#xA;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/epdf/10.1002/anie.200903293&quot; rel=&quot;noreferrer&quot;&gt;https://onlinelibrary.wiley.com/doi/epdf/10.1002/anie.200903293&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-24T17:57:22.943" LastActivityDate="2020-07-24T17:57:22.943" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1661" PostTypeId="1" AcceptedAnswerId="1662" CreationDate="2020-07-24T18:06:19.103" Score="11" ViewCount="122" Body="&lt;p&gt;The output of Gaussian rotatory and oscillatory strength intensities, plus a gaussian/lorentzian fit, translates to a &lt;em&gt;theoretical&lt;/em&gt; CD/UV-vis spectra.&lt;/p&gt;&#xA;&lt;p&gt;In order to try and compare with experimental results, a transformation or change of scale is necessary.&lt;/p&gt;&#xA;&lt;p&gt;You can find &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B9780080977744009177?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; (and in other papers as well, e.g. &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ja906884m&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ja102934q&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) that Autschbach mentions a 22.97 approximate factor to go from &lt;span class=&quot;math-container&quot;&gt;$\Delta\epsilon$&lt;/span&gt; to &lt;em&gt;mdeg&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Still, I do not quite get the conversion though, so could someone please guide me step by step?&lt;/p&gt;&#xA;&lt;p&gt;I mean, from:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$10^{-40} \textrm{esu}^2\textrm{cm}^2\leftrightarrow \frac{l}{\ce{mol}\cdot \ce{cm}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;how would you do the dimensional analysis that they did in the paper?&lt;/p&gt;&#xA;" OwnerUserId="1116" LastEditorUserId="5" LastEditDate="2020-07-24T18:11:09.167" LastActivityDate="2021-06-28T20:39:17.823" Title="Regarding oscillatory strength theoretical units to experimental ones" Tags="|density-functional-theory|quantum-chemistry|mathematical-modeling|td-dft|spectroscopy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1662" PostTypeId="2" ParentId="1661" CreationDate="2020-07-24T19:11:26.693" Score="8" Body="&lt;p&gt;The expression you are describing is equation (6) from your first link: &lt;span class=&quot;math-container&quot;&gt;$$R_j=\frac{3\hbar c\ln(10)1000}{16\pi^2N_A}\int_\text{band j}\frac{\Delta\epsilon}{\omega}d\omega\tag{1}$$&lt;/span&gt; which defines the rotatory strength &lt;span class=&quot;math-container&quot;&gt;$R_j$&lt;/span&gt; of a band &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; as the differential absorption coefficient integrated over that band, with the units changed via a prefactor containing the reduced Planck constant (&lt;span class=&quot;math-container&quot;&gt;$\hbar$&lt;/span&gt;), the speed of light (&lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;), and Avogadro's number (&lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt;). The expression is the same for oscillatory strength, except it integrates just over the absorption coefficient, not the differential.&lt;/p&gt;&#xA;&lt;p&gt;The prefactor has units of &lt;span class=&quot;math-container&quot;&gt;$\pu{g*cm^3*mol*s^-2}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\hbar$&lt;/span&gt; has units &lt;span class=&quot;math-container&quot;&gt;$\pu{g*cm^2*s^-1}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; has units &lt;span class=&quot;math-container&quot;&gt;$\pu{cm*s^-1}$&lt;/span&gt;, and Avogdaro's number is &lt;span class=&quot;math-container&quot;&gt;$\pu{mol^-1}$&lt;/span&gt;). Due to dividing and then integrating by &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;, the units of the integrated intensity are just those of &lt;span class=&quot;math-container&quot;&gt;$\Delta\epsilon$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\pu{L*mol^-1cm^-1}=\pu{cm^2*mol^-1}$&lt;/span&gt;). Combining these, we get units of &lt;span class=&quot;math-container&quot;&gt;$\pu{g*cm^5*s^-2}$&lt;/span&gt;, which doesn't look very close to the desired result until you realize that the ESU &lt;span class=&quot;math-container&quot;&gt;$\pu{statcoulomb}$&lt;/span&gt; is equivalent to &lt;span class=&quot;math-container&quot;&gt;$\pu{g^{1/2}*cm^{3/2}*s^{-1}}$&lt;/span&gt;. Subbing this into the prior expression, we obtain &lt;span class=&quot;math-container&quot;&gt;$\pu{statcoulomb^2*cm^2}$&lt;/span&gt;, which is what we were looking for.&lt;/p&gt;&#xA;&lt;p&gt;I'll leave it to you to work out how the numerical value for the prefactor comes out to around &lt;span class=&quot;math-container&quot;&gt;$22.97$&lt;/span&gt;. You just need to plug in the various constants with the appropriate units.&lt;/p&gt;&#xA;&lt;p&gt;If you are interested in a derivation of the expression for the rotatory strength, there is one given in Chapter 6 of Jeanne McHale's &lt;a href=&quot;https://www.routledge.com/Molecular-Spectroscopy-2nd-Edition/McHale/p/book/9781466586581&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Molecular Spectroscopy&lt;/em&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-28T20:39:17.823" LastActivityDate="2021-06-28T20:39:17.823" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1663" PostTypeId="2" ParentId="1659" CreationDate="2020-07-24T21:18:11.670" Score="7" Body="&lt;p&gt;The short answer is: &lt;strong&gt;yes you need to sample the whole reaction coordinate if you want accurate free energy values&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you are simply interested in qualitative behaviour, then you might (key word being might) get away with fewer windows (but they still need to be distributed fairly uniformly), but I would only recommend this for a dry/test run and never for a production run. Otherwise, you need to be absolutely sure you get good phase space overlap between &lt;strong&gt;all&lt;/strong&gt; distributions, or you will either get huge deviations from the correct free energy values or your analysis will crash. The reason for this is quite simple: the method that umbrella sampling uses for analysis, the weighted histogram analysis method (&lt;strong&gt;WHAM&lt;/strong&gt;), relies on data from all windows in order to calculate relative populations. If you have gaps in your phase space, this in turn creates gaps in the PMF (potential of mean force) and WHAM cannot calculate the relative heights, meaning that it will either converge to a strange result or not converge at all.&lt;/p&gt;&#xA;&lt;p&gt;As a final note, I would say that one of the biggest disadvantages of umbrella sampling (apart from the cost) is the fact that the efficiency is directly dependent on the shape of the PMF, bearing in mind that the WHAM estimator is exponentially sensitive to the phase space overlap. For example, if you have a very high kinetic barrier, you will need to concentrate more windows around this point in order to get some overlap. This means that while you don't &amp;quot;need to know the answer to get the answer&amp;quot;, you do &amp;quot;need to know the answer to be certain in your convergence&amp;quot;. In other words, you might have to add extra windows after your analysis to make sure your distributions overlap and that the extra windows don't change your results, because they shouldn't.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I just noticed that the artifact at around 0.8 nm can be readily explained by the lack of phase space overlap, so this gives you quite a good idea of what to expect when you have insufficient data. The authors of the tutorial also seem to acknowledge that and they also state that you need to make sure you always have adequate overlap.&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="5" LastEditDate="2020-07-25T00:58:44.453" LastActivityDate="2020-07-25T00:58:44.453" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1664" PostTypeId="1" CreationDate="2020-07-24T22:57:37.460" Score="7" ViewCount="1708" Body="&lt;p&gt;Whenever read-write files get to about 20Gb, I get this error. I know that, in G09, one rw file  is limited to 16Gb. So I have set the software to write several RWFs. But it still keeps producing this error...&#xA;My input line and rwf line look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%rwf=1,15000mb,2,15000mb,3,13000mb&#xA;&#xA;#p opt freq=noraman rccsd/genecp nosymm&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any suggestions? Thank you in advance!&lt;/p&gt;&#xA;" OwnerUserId="723" LastEditorUserId="5" LastEditDate="2020-07-26T18:55:25.757" LastActivityDate="2020-07-26T18:55:25.757" Title="I get this error in Gaussian09 even though I have enough memory. &quot;Error termination in NtrErr: NtrErr called from FIOCnC.&quot; Any suggestions?" Tags="|quantum-chemistry|computational-chemistry|gaussian|coupled-cluster|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1665" PostTypeId="1" CreationDate="2020-07-24T23:35:46.613" Score="14" ViewCount="204" Body="&lt;p&gt;In the &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.2148954?journalCode=jcp&quot; rel=&quot;nofollow noreferrer&quot;&gt;original paper by Grimme&lt;/a&gt; introducing double hybrid functionals (also summarized in just 3 paragraphs &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;here&lt;/a&gt;), it says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;[As] opposed to nonempirical versions of KS-PT2 [19],&#xA;the single excitations contribution is neglected, i.e., we implicitly assume for all Fock matrix elements &lt;span class=&quot;math-container&quot;&gt;$f_{ia}=0$&lt;/span&gt;.&amp;quot; &lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the reason for neglecting these single-excitations?&lt;/strong&gt; &lt;br&gt;&#xA;Please accept my apologies if this question is too trivial, since my knowledge of how double-hybrid (or single hybrid!) functionals work, began and ends with my browsing of the original paper to write the above-mentioned 3 paragraph summary, fewer than 2 months ago.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-27T03:24:54.993" LastActivityDate="2021-04-27T03:24:54.993" Title="Why are single excitations ignored in the MP2 component of double hybrid functional calculations?" Tags="|density-functional-theory|ab-initio-calculations|quantum-chemistry|functional|many-body-perturbation-theory|" AnswerCount="1" CommentCount="4" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1666" PostTypeId="1" CreationDate="2020-07-24T23:52:11.677" Score="17" ViewCount="1188" Body="&lt;p&gt;Many problems in Computational Physics need the use of random number generators. When studying magnetic materials using the Heisenberg/Ising Hamiltonians (related questions about them can be seen &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/659/24&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/859/24&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1618/24&quot;&gt;here&lt;/a&gt;), one of the most used tools is the Metropolis method&lt;sup&gt;1&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The Metropolis method can be summarized in the chart below (the image is linked directly from &lt;a href=&quot;https://sunnyamrat.com/physics/magnets.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;img src=&quot;https://sunnyamrat.com/physics/img/metropolis-algorithm.png&quot; height=&quot;550&quot;&gt;&#xA;&lt;p&gt;In order to accept the energy due to the exchange in a spin state, a random number is generated and then compared with the probability of the change. So, this number must be as random as possible and with very low periodicity.&lt;/p&gt;&#xA;&lt;p&gt;I just remember (back to the late 90's) that one of the used random number generators was the Kirkpatrick-Stoll&lt;sup&gt;2&lt;/sup&gt; (also called &lt;a href=&quot;https://www.taygeta.com/rwalks/node2.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;R250&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;My question: &lt;strong&gt;Are there any other modern random number generators better than R250?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;(By &amp;quot;good&amp;quot;, I mean: low correlation, long period and fast to code and run.)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Metropolis, N.; Rosenbluth, A.W.; Rosenbluth, M.N.; Teller, A.H.; Teller, E. &lt;em&gt;Equation of State Calculations by Fast Computing Machines&lt;/em&gt;. J. Chem. Phys. 21 1087–1092 (1953) (DOI: &lt;a href=&quot;https://doi.org/10.1063/1.1699114&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1063/1.1699114&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Kirkpatrick, S., and E. Stoll, &lt;em&gt;A Very Fast Shift-Register Sequence Random Number Generator&lt;/em&gt;, J. Comp. Phys. 40 517-526 (1981) (DOI: &lt;a href=&quot;https://doi.org/10.1016/0021-9991(81)90227-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1016/0021-9991(81)90227-8&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastEditorUserId="625" LastEditDate="2021-06-07T17:37:28.143" LastActivityDate="2021-06-07T17:37:28.143" Title="What are good random number generators for Monte Carlo calculations?" Tags="|ising-model|spin-models|heisenberg-model|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1667" PostTypeId="1" AcceptedAnswerId="1671" CreationDate="2020-07-25T05:13:28.347" Score="15" ViewCount="930" Body="&lt;p&gt;My textbook &amp;quot;Density Functional Theory of Atoms and  Molecules&amp;quot; by Parr and Yang says that any N-representable density is derivable from a single determinantal wavefunction.&#xA;A density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is N-representable if it satisfies&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\rho(\mathbf r) = \int d\sigma_1\int |\psi(\mathbf x_1, \mathbf x_2, ... \mathbf x_N)|^2 d^3\mathbf x_2 ... d^3\mathbf x_N&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\psi(\mathbf x_1, \mathbf x_2, ... \mathbf x_N)$&lt;/span&gt; is antisymmetric in exchanging any pair of its arguments, and &lt;span class=&quot;math-container&quot;&gt;$x \equiv (\mathbf r, \sigma)$&lt;/span&gt;. An antisymmetric wavefunction is in general a linear combination of Slater determinants. What I want to prove is that the above &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; can also be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;\rho(\mathbf r) = \sum_{\sigma=1}^2 \sum_{i=1}^{N_\sigma} |\phi_{i\sigma}(\mathbf r)|^2&#xA;$$&lt;/span&gt;&#xA;for some set of wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\{\phi_i\}$&lt;/span&gt;. But I don't know where to go beyond this point.&lt;/p&gt;&#xA;&lt;p&gt;Can someone help me to prove this statement?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT&lt;/strong&gt;:&#xA;The Kohn-Sham DFT apparently unconditionally assumes that there exists a non-interacting system having ground state density that is identical to the exact ground state density of the original interacting system. Therefore, stated in a different way, my question can also be understood to ask about the existence of this reference system, does it really always exist for an arbitrary real electronic system? If it doesn't always exist, can one also specify which conditions does the original interacting system have to have in order for its non-interacting &amp;quot;twin&amp;quot; system to exist.&lt;/p&gt;&#xA;" OwnerUserId="1121" LastEditorUserId="1121" LastEditDate="2020-07-25T19:35:03.530" LastActivityDate="2020-11-14T02:06:04.087" Title="Electron density arising from Slater determinant wave function" Tags="|density-functional-theory|from-phys-se|atoms-in-molecules|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1668" PostTypeId="1" CreationDate="2020-07-25T06:32:46.817" Score="11" ViewCount="281" Body="&lt;p&gt;With no background in biological science, I need help with docking 2 proteins together. This issue is with regards to SARS-CoV-2. The 2 proteins are &lt;a href=&quot;https://www.rcsb.org/structure/6VXX&quot; rel=&quot;noreferrer&quot;&gt;Spike glycoprotein&lt;/a&gt; and &lt;a href=&quot;https://www.rcsb.org/structure/3I6G&quot; rel=&quot;noreferrer&quot;&gt;membrane protein&lt;/a&gt;. What are the necessary rules / requirements to be followed before docking the 2 above proteins?&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="5" LastEditDate="2020-07-25T06:45:21.017" LastActivityDate="2020-07-25T17:19:36.060" Title="What are the factors to consider before docking 2 proteins?" Tags="|molecular-dynamics|molecular-modeling|docking|proteins|covid-19|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1669" PostTypeId="1" CreationDate="2020-07-25T06:45:58.917" Score="7" ViewCount="77" Body="&lt;p&gt;I need to dock 2 proteins involved in SARS-CoV-2. They are the &lt;a href=&quot;https://www.rcsb.org/structure/6VXX&quot; rel=&quot;noreferrer&quot;&gt;spike glycoprotein&lt;/a&gt; &amp;amp; &lt;a href=&quot;https://www.rcsb.org/structure/3I6G&quot; rel=&quot;noreferrer&quot;&gt;membrane protein&lt;/a&gt;. I need them to be docked as described in the image below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0Crww.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0Crww.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since there are many docking software programs available I would need the easiest to use and dock the proteins as shown above.&#xA;It would be amazing if the answer could be specific to the proteins which are above specified.&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="5" LastEditDate="2020-07-25T06:50:19.063" LastActivityDate="2020-07-25T18:12:03.187" Title="Which non-commercial software can be used to dock two proteins?" Tags="|software|molecular-modeling|docking|proteins|covid-19|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1670" PostTypeId="1" CreationDate="2020-07-25T06:57:56.767" Score="5" ViewCount="105" Body="&lt;p&gt;I would like to pursue a Masters degree in Materials Science and more focused towards solar materials to make it more efficient and reducing the &lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/energy-payback-time&quot; rel=&quot;nofollow noreferrer&quot;&gt;energy payback time&lt;/a&gt;.&lt;br /&gt;&#xA;I had taken this &lt;a href=&quot;https://www.coursera.org/learn/solar-cells&quot; rel=&quot;nofollow noreferrer&quot;&gt;course&lt;/a&gt; and was pretty sure that material science has a humongous role for a solar future.&lt;/p&gt;&#xA;&lt;p&gt;I just wanted to know how computational material science and in turn DFT, has played a role in developing better solar materials.&#xA;In specific Thin-film solar materials and CIGS solar cells!&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="7" LastEditDate="2020-07-29T16:18:22.667" LastActivityDate="2020-08-14T11:34:55.313" Title="Has DFT helped in development of better solar materials?" Tags="|density-functional-theory|education|materials-engineering|solar-cells|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1671" PostTypeId="2" ParentId="1667" CreationDate="2020-07-25T07:46:41.433" Score="9" Body="&lt;p&gt;The proof that (2) is the density arising from a Slater determinant wave function can be found in basically any quantum chemistry textbook.&lt;/p&gt;&#xA;&lt;p&gt;(2) does NOT hold for multiconfigurational wave functions, since the one-particle density matrix becomes non-diagonal. You &lt;em&gt;can&lt;/em&gt; make the density diagonal like (2) by switching to natural orbitals, but then you have fractional occupations for ALL orbitals, instead of just the occupied set of orbitals in one-determinant theories like Hartree-Fock and Kohn-Sham density fucntional theory.&lt;/p&gt;&#xA;&lt;p&gt;edit: the edited question seems to be asking if exact DFT orbitals reproduce the full CI density, which has already been discussed in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1484/orbitals-in-full-ci-and-dft-with-true-functional&quot;&gt;Orbitals in full CI and DFT with true functional&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-26T09:11:31.790" LastActivityDate="2020-07-26T09:11:31.790" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1672" PostTypeId="2" ParentId="1629" CreationDate="2020-07-25T09:50:17.133" Score="10" Body="&lt;h2&gt;eDMFT&lt;/h2&gt;&#xA;&lt;p&gt;Link to website: &lt;a href=&quot;http://hauleweb.rutgers.edu/tutorials/index.html&quot; rel=&quot;noreferrer&quot;&gt;eDMFT&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Developer: Kristjan Haule at Rutgers University&lt;/p&gt;&#xA;&lt;p&gt;Main features from their &lt;a href=&quot;http://hauleweb.rutgers.edu/tutorials/whatis/whatis.html#XHaule_prb10&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;DFT+DMFT derived from the stationary Luttinger-Ward functional.&lt;/li&gt;&#xA;&lt;li&gt;Local correlated orbitals: real space (rather the usual choice of Wannier space).&lt;/li&gt;&#xA;&lt;li&gt;Exact double counting for DFT+DMFT from this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.196403&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Impurity solvers: continuous time quantum Monte Carlo, non-crossing, and one-crossing approximations.&lt;/li&gt;&#xA;&lt;li&gt;Can calculate free energies and forces.&lt;/li&gt;&#xA;&lt;li&gt;The DFT part is obtained from an interface to &lt;a href=&quot;http://www.wien2k.at&quot; rel=&quot;noreferrer&quot;&gt;Wien2K&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-25T09:50:17.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1673" PostTypeId="1" CreationDate="2020-07-25T11:47:08.167" Score="11" ViewCount="236" Body="&lt;p&gt;&lt;strong&gt;Note: Users wishing to answer this question may write a comment or a message in the chat indicating their desire for the question to be re-opened.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;I have an NVT ensemble of water molecules (liquid) and I want to calculate the Free energy (helmholtz or gibbs) whichever is equivalent to the following relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \Delta F = -RTlnQ \tag{1}$$&lt;/span&gt;&#xA;I can't calculate the value of Q in a traditional way i.e.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ Q=\frac{[Products]}{[Reactants]}\tag{2} $$&lt;/span&gt;&#xA;Is there any other way to calculate frame-wise free energy? I have the following values at my disposal currently (can calculate more if given a way):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;N (starting number of molecules - NOT intermediate count of reactants and products)&lt;/li&gt;&#xA;&lt;li&gt;V (box dimensions)&lt;/li&gt;&#xA;&lt;li&gt;T (frame-wise temperature)&lt;/li&gt;&#xA;&lt;li&gt;Total Energy (frame wise)&lt;/li&gt;&#xA;&lt;li&gt;Potential Energy (frame wise)&lt;/li&gt;&#xA;&lt;li&gt;Pressure (framewise)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I have also looked at FEP (Free energy perturbation) but unsure if that is applicable to an existing trajectory and if yes, then how.&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2021-03-15T21:00:41.330" LastActivityDate="2021-03-15T21:00:41.330" Title="Calculate free energy for a canonical (NVT) ensemble" Tags="|molecular-dynamics|free-energy|" AnswerCount="0" CommentCount="15" FavoriteCount="0" ClosedDate="2020-07-29T20:57:17.947" ContentLicense="CC BY-SA 4.0" />
  <row Id="1674" PostTypeId="2" ParentId="1668" CreationDate="2020-07-25T12:18:53.653" Score="12" Body="&lt;p&gt;The main requirement is to have structures files with good resolution. According to RSCB PDB &lt;a href=&quot;http://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/resolution&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Resolution is a measure of the quality of the data that has been collected on the crystal containing the protein or nucleic acid.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The figure bellow is an example of how the resolution indicates the quality of the structure (linked from original source):&lt;/p&gt;&#xA;&lt;img src=&quot;https://cdn.rcsb.org/pdb101/learn/resources/guide-to-understanding-pdb-data/images/resolution-figure.jpg&quot; height=&quot;500&quot;&gt;&#xA;&lt;p&gt;In your case, the structure of the Spike glycoprotein (PDB code: 6VXX) has resolution of &lt;span class=&quot;math-container&quot;&gt;$2.80\,\overset{\circ}{\mathrm{A}}$&lt;/span&gt; and the membrane protein (PDB code: 3I6G) has &lt;span class=&quot;math-container&quot;&gt;$2.20\,\overset{\circ}{\mathrm{A}}$&lt;/span&gt;. So, both structures are at the quality limit (a desired resolution for docking studies&lt;sup&gt;1&lt;/sup&gt; is resolution below &lt;span class=&quot;math-container&quot;&gt;$2.00\,\overset{\circ}{\mathrm{A}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another properties you have to worry about are the atomic charges, the protonation state, how to treat the flexibility (what residues will be considered flexible during the docking)&lt;sup&gt;2&lt;/sup&gt;, and the presence of co-factors and ligands/substrates.&lt;/p&gt;&#xA;&lt;p&gt;As the docking software will give you a still-image (a snap-shot conformation), it is recommended to run a Molecular Dynamics simulation using the pose obtained from the docking as input file.&lt;/p&gt;&#xA;&lt;p&gt;The web server &lt;a href=&quot;https://bianca.science.uu.nl/haddock2.4/&quot; rel=&quot;noreferrer&quot;&gt;HADDOCK&lt;/a&gt; is specialized in protein-protein docking, and will take care of must of the properties mentioned above (except the resolution).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Torsten Schwede &amp;amp; Manuel C. Peitsch. &lt;a href=&quot;https://books.google.com.br/books/about/Computational_Structural_Biology_Methods.html?id=Ik3ICgAAQBAJ&amp;amp;redir_esc=y&quot; rel=&quot;noreferrer&quot;&gt;Computational Structural Biology: Methods and Applications&lt;/a&gt;. World Scientific Publishing Company. 2012. ISBN 9789812778772.&lt;/li&gt;&#xA;&lt;li&gt;Ideally, all the residues should be considered flexible, but this will increase the computational time.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-07-25T14:38:58.433" LastActivityDate="2020-07-25T14:38:58.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1675" PostTypeId="1" CreationDate="2020-07-25T14:43:38.987" Score="5" ViewCount="74" Body="&lt;p&gt;What is the fundamental difference(s) between Ehrenfest dynamics and Born-Oppenheimer MD? Also, in what situation(s) or case(s) one is preferred than the other one?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="5" LastEditDate="2020-07-25T16:30:55.680" LastActivityDate="2020-07-25T16:30:55.680" Title="What is the difference between Ehrenfest dynamics and Born-Oppenheimer Molecular Dynamics?" Tags="|molecular-dynamics|molecular-modeling|ab-initio-calculations|quantum-dynamics|" AnswerCount="0" CommentCount="3" ClosedDate="2020-08-06T21:21:51.173" ContentLicense="CC BY-SA 4.0" />
  <row Id="1676" PostTypeId="1" CreationDate="2020-07-25T16:50:20.453" Score="10" ViewCount="235" Body="&lt;p&gt;I am a novice in Ehrenfest dynamics and would like to know why Ehrenfest dynamics suffers from the &amp;quot;overcoherence problem&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="5" LastEditDate="2020-07-31T21:25:44.897" LastActivityDate="2020-08-01T19:48:14.900" Title="What is the &quot;overcoherence problem&quot; in Ehrenfest dynamics?" Tags="|molecular-dynamics|molecular-modeling|ab-initio-calculations|quantum-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1677" PostTypeId="2" ParentId="1668" CreationDate="2020-07-25T17:15:23.587" Score="6" Body="&lt;p&gt;Another factor to consider might be blind docking or targeted. In this latter, only a region indicated on protein is targeted. In blind docking, the ligand will bind wherever suited on the protein while in targeted only the region indicated will be accessible to the ligand. Blind docking is closer to the real biological setting but computationally expensive.&#xA;You might want to have a look &lt;a href=&quot;https://www.nature.com/articles/s41598-017-15571-7/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for blind docking.&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2020-07-25T17:19:36.060" LastActivityDate="2020-07-25T17:19:36.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1678" PostTypeId="1" CreationDate="2020-07-25T17:41:11.707" Score="14" ViewCount="192" Body="&#xA;&lt;p&gt;In this &lt;a href=&quot;https://doi.org/10.1016/j.jmmm.2017.01.004&quot; rel=&quot;nofollow noreferrer&quot;&gt;work&lt;/a&gt;, graphene-based systems that are described by mixed spin-3/2 and spin-5/2 are studied using the &lt;a href=&quot;/questions/tagged/ising-model&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;ising-model&amp;#39;&quot; rel=&quot;tag&quot;&gt;ising-model&lt;/a&gt;. A diagram of the structure is shown bellow:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VMBeV.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VMBeV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Hamiltonian used is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{1}&#xA;{\small&#xA;{H_I} =  - J\sum\limits_{\left\langle {i,j} \right\rangle } {{S_i}{\sigma _j}}  - {J_\sigma }\sum\limits_{\left\langle {i,j} \right\rangle } {{\sigma _i}{\sigma _j}}  - {J_S}\sum\limits_{\left\langle {i,j} \right\rangle } {{S_i}{S_j}}  - {K_v}\left( {\sum\limits_i {S_i^2}  + \sum\limits_j {\sigma _j^2} } \right).&#xA;}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\left\langle {i,j} \right\rangle$&lt;/span&gt; refers to the sum over the nearest neighbors pairs, &lt;span class=&quot;math-container&quot;&gt;$\left[ i,j \right]$&lt;/span&gt; means sum over the next-nearest neighbors pairs, &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$J_S$&lt;/span&gt; are the exchange interaction constants between sites &lt;span class=&quot;math-container&quot;&gt;$\sigma−S$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\sigma−\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S−S$&lt;/span&gt;, respectively (see diagram above), and &lt;span class=&quot;math-container&quot;&gt;$K_v$&lt;/span&gt; is the crystal field anisotropy constant. The spins moments can take values &lt;span class=&quot;math-container&quot;&gt;$\sigma = ±3/2,±1/2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S=±5/2,±3/2,±1/2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;How are &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_\sigma$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_S$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; chosen?&lt;/h3&gt;&#xA;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-11-30T20:42:07.657" LastActivityDate="2023-03-24T11:04:57.873" Title="How to choose the values of J and spin parameters in a heterogeneous spin system?" Tags="|model-hamiltonians|ising-model|spin-models|heisenberg-model|spin-exchange|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1679" PostTypeId="1" CreationDate="2020-07-25T17:53:45.073" Score="12" ViewCount="134" Body="&lt;p&gt;A fractal is, accordingly &lt;a href=&quot;https://www.lexico.com/en/&quot; rel=&quot;noreferrer&quot;&gt;Oxford English Dictionary&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A curve or geometric figure, each part of which has the same statistical character as the whole. Fractals are useful in modeling structures (such as eroded coastlines or snowflakes) in which similar patterns recur at progressively smaller scales, and in describing partly random or chaotic phenomena such as crystal growth, fluid turbulence, and galaxy formation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;One of the must famous fractals is the Mandelbrot set:&lt;/p&gt;&#xA;&lt;img src=&quot;https://upload.wikimedia.org/wikipedia/commons/thumb/a/a4/Mandelbrot_sequence_new.gif/200px-Mandelbrot_sequence_new.gif&quot; height=&quot;250&quot;&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;Are there real examples where fractals were used to solve problems in Matter Modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-25T18:05:49.367" LastActivityDate="2020-07-30T09:02:09.677" Title="What are real examples where fractals were used in Matter Modeling?" Tags="|reference-request|condensed-matter|fractals|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1680" PostTypeId="2" ParentId="1666" CreationDate="2020-07-25T18:02:56.350" Score="14" Body="&lt;p&gt;It's been years since I've done Monte Carlo calculations (though it was more recent than the 90's!), so hopefully the information given below is still reasonably up-to-date. I've also had reason to look into pseudo-random number generation in the last few years, for other algorithms.&lt;/p&gt;&#xA;&lt;h2&gt;My question: &lt;strong&gt;Are there any other modern random number generators better than R250?&lt;/strong&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Yes. In fact, it's been known for a while that R250 has some bad properties and should be avoided. See e.g. &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.168692&quot; rel=&quot;noreferrer&quot;&gt;Ziff, &amp;quot;&lt;em&gt;Four-tap shift-register-sequence random-number generators,&lt;/em&gt;&amp;quot; Computers in Physics &lt;strong&gt;12&lt;/strong&gt;, 385 (1998)&lt;/a&gt; (alternative &lt;a href=&quot;https://arxiv.org/abs/cond-mat/9710104&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;) and references therein. Among the issues with R250 (or in generalized notation R(103,250)) Ziff mentions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;More recently, Ferrenberg et al. &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.69.3382&quot; rel=&quot;noreferrer&quot;&gt;[9]&lt;/a&gt; found that R(103, 250) leads to results being more&#xA;than 100 standard deviations from the (known) true values, in simulations of the Ising model with the Wolff cluster-flipping Monte-Carlo algorithm.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The basic problem of two-tap generators R(&lt;span class=&quot;math-container&quot;&gt;$a, b$&lt;/span&gt;) is that they have a built-in three-point correlation between &lt;span class=&quot;math-container&quot;&gt;$x_n$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$x_{n−a}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$x_{n−b}$&lt;/span&gt;, simply given by the generator itself, such that if any two of the &lt;span class=&quot;math-container&quot;&gt;$_n$&lt;/span&gt; are known, the third follows directly from the recursion &lt;span class=&quot;math-container&quot;&gt;$x_n = x_{n−a} \otimes x_{n−b}$&lt;/span&gt;. While these correlations are spread over the size &lt;span class=&quot;math-container&quot;&gt;$p = \max(a, b, c, . . .)$&lt;/span&gt; of the generator itself,&#xA;they can evidently still lead to significant errors. These three-point correlations have been recently brought out clearly in a simulation by Schmid and Wilding&lt;/p&gt;&#xA;&lt;p&gt;Other problems with this generator are also known. Compagner and Hoogland have&#xA;shown how a pattern of all 1’s in the initialization string leads to complex (and beautiful) pattern of subsequent bits that persists for a surprisingly long time. Shchur et al. showed that, if an event occurs with a probability close to one (such as 31/32), it is not too unlikely for say 249 successive true outcomes to occur, which then leads to a very serious error at the 250-th step, when the R(103, 250) generator is used.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h2&gt;(by &amp;quot;good&amp;quot;, I mean: low correlation, long period and fast to code and run)&lt;/h2&gt;&#xA;&lt;p&gt;The most popular multipurpose RNG these days is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Mersenne_Twister&quot; rel=&quot;noreferrer&quot;&gt;Mersenne Twister&lt;/a&gt;, introduced in &lt;a href=&quot;https://doi.org/10.1145/272991.272995&quot; rel=&quot;noreferrer&quot;&gt;Matsumo, and Nishimura, &amp;quot;&lt;em&gt;Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator,&lt;/em&gt;&amp;quot; ACM Transactions on Modeling and Computer Simulation &lt;strong&gt;8&lt;/strong&gt;, 3-30 (1998)&lt;/a&gt; (alternative &lt;a href=&quot;http://www.math.sci.hiroshima-u.ac.jp/%7Em-mat/MT/ARTICLES/mt.pdf&quot; rel=&quot;noreferrer&quot;&gt;non-paywall link&lt;/a&gt;). It has a long period, is reasonably fast, and is widely implemented in libraries. This works fine for sequential code, but it's &lt;a href=&quot;https://scicomp.stackexchange.com/q/23547/26675&quot;&gt;easy to make mistakes when implementing it in a parallel environment&lt;/a&gt;, e.g. for GPU implementations. In such cases, make sure to use a suitable implementation. There's a good discussion of the requirements in &lt;a href=&quot;https://doi.org/10.1016/j.matcom.2016.05.005&quot; rel=&quot;noreferrer&quot;&gt;L'Ecuyer, Munger, Oreshkin, and Simard, &amp;quot;&lt;em&gt;Random numbers for parallel computers: Requirements and methods, with emphasis on GPUs,&lt;/em&gt;&amp;quot; Mathematics and Computers in Simulation &lt;strong&gt;135&lt;/strong&gt;, 3-17 (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another more recent option is the so-called &lt;a href=&quot;https://en.wikipedia.org/wiki/Well_equidistributed_long-period_linear&quot; rel=&quot;noreferrer&quot;&gt;WELL generator&lt;/a&gt; (Well Equidistributed Long-period Linear) introduced in &lt;a href=&quot;https://doi.org/10.1145/1132973.1132974&quot; rel=&quot;noreferrer&quot;&gt;Panneton, L'Ecuyer, and Matsumoto, &amp;quot;&lt;em&gt;Improved long-period generators based on linear recurrences modulo 2,&lt;/em&gt;&amp;quot; ACM Transactions on Mathematical Software &lt;strong&gt;32&lt;/strong&gt;, 1-16 (2006)&lt;/a&gt; (alternative &lt;a href=&quot;http://www.iro.umontreal.ca/%7Elecuyer/myftp/papers/wellrng.pdf&quot; rel=&quot;noreferrer&quot;&gt;non-paywall link&lt;/a&gt;). In the &lt;a href=&quot;http://home.apache.org/%7Eluc/commons-math-3.6-RC2-site/userguide/random.html&quot; rel=&quot;noreferrer&quot;&gt;Apache Commons Math&lt;/a&gt; user guide it is stated that,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The WELL generators are more modern then MersenneTwister (the paper describing than has been published in 2006 instead of 1998) and fix some of its (few) drawbacks. If initialization array contains many zero bits, MersenneTwister may take a very long time (several hundreds of thousands of iterations to reach a steady state with a balanced number of zero and one in its bits pool). So the WELL generators are better to escape zeroland as explained by the WELL generators creators.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For a general Monte Carlo simulation I would probably pick one of these two, since they've been tested and explored in practical applications for a while now. Pragmatically speaking, a reviewer probably won't challenge you on their use. Also (though I'm not sure how much to read into it), the Mersenne Twister has excitingly been found to compare well to a physical, quantum-based random number generator, see &lt;a href=&quot;https://doi.org/10.1002/jcc.25065&quot; rel=&quot;noreferrer&quot;&gt;Ghersi, Parakh, and Mezei, &amp;quot;&lt;em&gt;Comparison of a quantum random number generator with pseudorandom number generators for their use in molecular Monte Carlo simulations,&lt;/em&gt;&amp;quot; Journal of Computational Chemistry &lt;strong&gt;38&lt;/strong&gt;, 2713-2720 (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, probably neither is the best at any one of the qualities you're looking for. If you need really fast, something out of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Xorshift&quot; rel=&quot;noreferrer&quot;&gt;Xorshift&lt;/a&gt; or &lt;a href=&quot;https://en.wikipedia.org/wiki/Permuted_congruential_generator&quot; rel=&quot;noreferrer&quot;&gt;Permuted congruential generator (PCG)&lt;/a&gt; families are probably the way to go. (While PCG has good statistical properties, some drawbacks are discussed in this &lt;a href=&quot;https://stats.stackexchange.com/q/337927&quot;&gt;Stats.SE question&lt;/a&gt;.) But if I were to go that route, I would consider checking the results using also a more conventional PRNG. That is probably a good idea anyway to make sure results don't depend on the specific choice of PRNG.&lt;/p&gt;&#xA;&lt;p&gt;Final note: It should &lt;strong&gt;not&lt;/strong&gt; be assumed that the mentioned pseudorandom number generators are cryptographically safe.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-25T18:02:56.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1681" PostTypeId="2" ParentId="1669" CreationDate="2020-07-25T18:09:54.467" Score="8" Body="&lt;h2&gt;HADDOCK&lt;/h2&gt;&#xA;&lt;p&gt;HADDOCK is both a web service and a standalone code.&lt;/p&gt;&#xA;&lt;p&gt;From the web server:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;HADDOCK (High Ambiguity Driven protein-protein DOCKing) is an information-driven flexible docking approach for the modeling of biomolecular complexes. HADDOCK distinguishes itself from ab-initio docking methods in the fact that it encodes information from identified or predicted protein interfaces in ambiguous interaction restraints (AIRs) to drive the docking process. HADDOCK can deal with a large class of modelling problems including protein-protein, protein-nucleic acids and protein-ligand.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;All the concerns about docking two proteins mentioned &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1674/24&quot;&gt;here&lt;/a&gt; are taking care of by HADDOCK automatically (except the protein resolution).&lt;/p&gt;&#xA;&lt;p&gt;To register go: &lt;a href=&quot;https://bianca.science.uu.nl/haddock2.4/&quot; rel=&quot;noreferrer&quot;&gt;https://bianca.science.uu.nl/haddock2.4/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To submit your job: &lt;a href=&quot;https://bianca.science.uu.nl/haddock2.4/submit/1&quot; rel=&quot;noreferrer&quot;&gt;https://bianca.science.uu.nl/haddock2.4/submit/1&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To read some tutorials: &lt;a href=&quot;https://www.bonvinlab.org/education/&quot; rel=&quot;noreferrer&quot;&gt;https://www.bonvinlab.org/education/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Docking software are designed in such a way to allow docking of any protein/ligands. They are not specific for any protein family or type of ligands. As all of them make use of forcefields, the only concern here is about having the right forcefield parameters for all the atoms.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-07-25T18:12:03.187" LastActivityDate="2020-07-25T18:12:03.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1682" PostTypeId="2" ParentId="1666" CreationDate="2020-07-25T18:57:19.420" Score="20" Body="&lt;p&gt;Depending on how many random numbers you need in a short amount of time, it might be worth to consider using a cryptographic PRNG. In particular AES-CTR.&lt;/p&gt;&#xA;&lt;p&gt;Now of course you might say that &amp;quot;but AES-CTR is soo slow&amp;quot;. Actually it isn't. If you only re-key every GB or so of generated data you get a speed of&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;about 12 CPU cycles needed for 16 bytes of random data &lt;em&gt;per core&lt;/em&gt; on all Intel CPUs since Sandy Bridge, meaning you get &lt;span class=&quot;math-container&quot;&gt;$4/3\cdot f\cdot c$&lt;/span&gt; bytes for &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; being the CPU frequency and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; being the core count.&lt;sup&gt;1&lt;/sup&gt;&lt;/li&gt;&#xA;&lt;li&gt;about 6 CPU cycles needed for 16 bytes of random data &lt;em&gt;per core&lt;/em&gt; on all AMD Ryzen-based CPUs, meaning you get &lt;span class=&quot;math-container&quot;&gt;$8/3\cdot f\cdot c$&lt;/span&gt; bytes for &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; being the CPU frequency and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; being the core count.&lt;sup&gt;1&lt;/sup&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://eprint.iacr.org/2018/392&quot; rel=&quot;noreferrer&quot;&gt;about 12 CPU cycles needed for 64 bytes of random data &lt;em&gt;per core&lt;/em&gt; on all Intel CPU with AVX-512 and the new VAES extension&lt;/a&gt; (currently only Ice Lake), meaning you get &lt;span class=&quot;math-container&quot;&gt;$16/3\cdot f\cdot c$&lt;/span&gt; bytes for &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; being the AVX-512 frequency and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; being the core count.&#xA;Alternatively, Zen3 CPUs have 256-bit VAES as well and achieve the same efficiency.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ieeexplore.ieee.org/document/8252225&quot; rel=&quot;noreferrer&quot;&gt;about 30GB/s on a high-end Nvidia Maxwell and newer GPUs&lt;/a&gt;. &lt;a href=&quot;https://eprint.iacr.org/2021/646&quot; rel=&quot;noreferrer&quot;&gt;Newer research indicates even higher performance at almost 40GB/s on high-end Maxwell (970) and almost 110GB/s on high-end Turing (2070S).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Additionally the quality of the random bytes you get is top-notch with even a determined adversary having an expected chance of less than &lt;span class=&quot;math-container&quot;&gt;$2^{-32}$&lt;/span&gt; for telling &lt;span class=&quot;math-container&quot;&gt;$2^{36}$&lt;/span&gt; AES-produced bytes apart from truly random bytes for a secret key. Then to maintain that quality you simply re-key every second or so (of full-speed output) without losing too much of your security bound.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Footnote 1: These numbers are justified with the AESENC instruction throughput which is 1 for all supported Intel architectures and 0.5 for Ryzen according to this &lt;a href=&quot;https://www.agner.org/optimize/instruction_tables.pdf&quot; rel=&quot;noreferrer&quot;&gt;380-page (PDF) sheet&lt;/a&gt;. The latency is typically overcome by computing up to 8 different AES blocks in parallel. The throughput is the sum of the reciprocal throughputs of: 1 XOR (initial key addition), 9 AESENC instructions, 1 AESENCLAST instruction, 1 ADD (AES input generation), the 11 round keys are assumed to be stored in XMM registers for all the computations and only computed + loaded once per re-keying.&lt;/p&gt;&#xA;" OwnerUserId="1128" LastEditorUserId="1128" LastEditDate="2021-06-03T11:48:13.363" LastActivityDate="2021-06-03T11:48:13.363" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1683" PostTypeId="1" AcceptedAnswerId="1829" CreationDate="2020-07-25T20:02:37.203" Score="13" ViewCount="133" Body="&lt;p&gt;For example, are there any methods to allow for modeling of photo-oxidation or photo-reduction of a compound on a semiconductor surface?  It appears there has been a lot of work on the bulk properties and recombination rate / exciton stability, but surface studies of these systems seem to be very problematic.&lt;/p&gt;&#xA;&lt;p&gt;I suspect that this might just be outside of the region of computational studies I am familiar with so any insight into this type of study would be interesting to me.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-07-26T21:09:56.690" LastActivityDate="2020-07-28T19:01:28.590" Title="What progress has been made in modelling photocatalytic reactions on semiconductor surfaces?" Tags="|reference-request|band-structure|surfaces|excited-states|photochemistry|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1684" PostTypeId="1" AcceptedAnswerId="1817" CreationDate="2020-07-25T20:34:48.120" Score="19" ViewCount="716" Body="&lt;p&gt;The number of all two-electron integrals:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\langle \phi_1 \phi_2|\phi_3\phi_4 \rangle = \int d^3\mathbf r' \int d^3\mathbf r'' \, \phi_1(\mathbf r'') \, \phi_2(\mathbf r') \frac{1}{|\mathbf r' - \mathbf r''|} \, \phi_3(\mathbf r') \, \phi_4(\mathbf r''),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; number of basis functions (I am using real-valued ones) is &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Not all of them are unique, but the number of unique integrals is &lt;span class=&quot;math-container&quot;&gt;$N(N+1)(N^2 + N + 2)/8$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Yet this number is still huge for a reasonably accurate basis set. I have a feeling that this number can be significantly reduced if one makes use of the &lt;strong&gt;point-group symmetry&lt;/strong&gt; of the molecule to determine the vanishing integrals. If yes, &lt;strong&gt;how is this done given the knowledge of the point group?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1121" LastEditorUserId="5" LastEditDate="2020-07-31T04:30:30.817" LastActivityDate="2021-07-21T03:33:50.713" Title="How is group theory used to deduce which of these integrals are equal to 0?" Tags="|electronic-structure|mathematical-modeling|symmetry|integrals|space-groups|" AnswerCount="4" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="1685" PostTypeId="1" CreationDate="2020-07-26T02:43:53.797" Score="15" ViewCount="292" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;We recently learned about the many types of MCSCF&lt;/a&gt;, which treat &amp;quot;static&amp;quot; electron correlation. There are then many ways  to treat further &amp;quot;dynamic&amp;quot; electron correlation to try and bridge the gap between the MCSCF and FCI. But these methods can vary drastically:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Some require 4-body RDMs (e.g. NEVPT2), others only 3-RDMs (e.g. cummulant methods).&lt;/li&gt;&#xA;&lt;li&gt;Some are size-consistent (e.g. NEVPT2), some are not (Davidson's +Q).&lt;/li&gt;&#xA;&lt;li&gt;Some are available everywhere (Davidson's +Q), some are only in in-house codes (AC0/AC1).&lt;/li&gt;&#xA;&lt;li&gt;ENPT2 can be parallelized w/ 100s of cores, NEVPT2 can be split into 8 parallel calculations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;I seek descriptions of all post-MCSCF dynamic correlation methods, including the following:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;formula for how the energy and/or wavefunction is calculated,&lt;/li&gt;&#xA;&lt;li&gt;N-Body RDM requirements,&lt;/li&gt;&#xA;&lt;li&gt;size-consistency and size-extensivity (or lack thereof),&lt;/li&gt;&#xA;&lt;li&gt;ability to Parallelize (or lack thereof),&lt;/li&gt;&#xA;&lt;li&gt;whether or not spin purity is guaranteed,&lt;/li&gt;&#xA;&lt;li&gt;invariance under orbital rotations (or lack thereof),&lt;/li&gt;&#xA;&lt;li&gt;absence (or risk) of intruder states,&lt;/li&gt;&#xA;&lt;li&gt;which software packages implement them.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Some post-MCSCF dynamic correlation methods I know include:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;NEVPT (usually truncated at 2nd order: NEVPT2),&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PC-NEVPT (partially contracted NEVPT),&lt;/li&gt;&#xA;&lt;li&gt;SC-NEVPT (strongly contracted NEVPT),&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;Multi-reference Davidson correction (+Q),&lt;/li&gt;&#xA;&lt;li&gt;Multi-reference Pople correction,&lt;/li&gt;&#xA;&lt;li&gt;ENPT (Epstein-Nesbet Pertubration Theory, often used with SHCI),&lt;/li&gt;&#xA;&lt;li&gt;Multi-reference Møller–Plesset Perturbation Theory,&lt;/li&gt;&#xA;&lt;li&gt;CASPT / RASPT / GASPT (usually truncated at 2nd order: CASPT2 / RASPT2 / GASPT2),&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.120.013001&quot; rel=&quot;nofollow noreferrer&quot;&gt;AC0 and AC1&lt;/a&gt; (Adiabatic Connection extrapolation schemes),&lt;/li&gt;&#xA;&lt;li&gt;TCC (Tailored Coupled Cluster),&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10122/5&quot;&gt;Externally Corrected Coupled Cluster&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;MPCDFT (Multiconfigurational Pair Density Functional Theory) [&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1513/5&quot;&gt;potentially described here too&lt;/a&gt;].&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4895977&quot; rel=&quot;nofollow noreferrer&quot;&gt;MPSPT&lt;/a&gt; (matrix product state perturbation theory)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-19T05:46:44.737" LastActivityDate="2022-12-19T05:46:44.737" Title="What are the ways to add dynamic correlation to an MCSCF wavefunction?" Tags="|ab-initio-calculations|one-topic-per-answer|casscf|electron-correlation|multi-reference|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1686" PostTypeId="1" CreationDate="2020-07-26T02:50:20.463" Score="13" ViewCount="606" Body="&lt;p&gt;I find it surprisingly difficult to find researches/papers on systematic &amp;quot;many-body interaction&amp;quot; extensions of the Ising model. Can somebody tell me a good review/article etc on this matter that goes through possible extensions of the Ising model in a somewhat systematic way?&lt;/p&gt;&#xA;&lt;p&gt;The usual &lt;span class=&quot;math-container&quot;&gt;$s_is_j$&lt;/span&gt; interaction can be extended in a few different ways:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Maintaining the product form.&#xA;In this case, we can imagine interactions like &lt;span class=&quot;math-container&quot;&gt;$s_is_js_k$&lt;/span&gt; which&#xA;would now break the &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; symmetry, but would recover it when we have&#xA;even numbers of spins in the interaction. I know that the three-body&#xA;Ising model has a first-order transition in the fully-connected&#xA;mean-field theory, and also know that there's a glassy phase for the&#xA;sparsely-connected mean-field version of it. When we get to&#xA;four-body interactions in this form, e.g. &lt;span class=&quot;math-container&quot;&gt;$s_is_js_ks_l$&lt;/span&gt; with&#xA;&lt;span class=&quot;math-container&quot;&gt;$\langle i,j,k,l \rangle$&lt;/span&gt; in plaquettes, this really resembles the &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; gauge theory&#xA;but is slightly different since the model we get by simply extending the normal&#xA;Ising model would have spins on the sites of the lattice. Still, I&#xA;was able to find papers talking about the &amp;quot;plaquette Ising model&amp;quot;&#xA;which I think is exactly the same as what I have in mind here.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Anyway, it would be good to know if there's a systematically sorted reference of these extension models, instead of some bunch of facts like I wrote here.&lt;/p&gt;&#xA;&lt;p&gt;Also, another way of extending the model could be...&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Maintaining its trend to let spins point in the same direction. We can have energetic terms that favor &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; spins pointing in the same direction, so the normal Ising model is &lt;span class=&quot;math-container&quot;&gt;$k=2$&lt;/span&gt;. I think this would also be a natural extension, but as far as I know, I don't even know if this model has a name. My intuition says that when k is large enough the &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; symmetry breaking should become a first-order transition, but couldn't find any actual study about this. Does anybody know anything about such kind of models?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="379" LastEditorUserId="5" LastEditDate="2020-07-29T00:35:48.853" LastActivityDate="2020-07-29T00:35:48.853" Title="Ising models with many-body interactions" Tags="|model-hamiltonians|ising-model|spin-models|solid-state-physics|k-local-hamiltonians|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1687" PostTypeId="1" CreationDate="2020-07-26T02:54:46.110" Score="11" ViewCount="446" Body="&lt;p&gt;There's no doubt about it. Machine Learning (ML) is one of the hottest topics out there and it plays an important role in computational science.&lt;/p&gt;&#xA;&lt;p&gt;One application I have seen is to use ML and Density Functional Theory DFT for the rational design of functional materials, for applications such as solar cells. Two examples are &lt;a href=&quot;https://www.nature.com/articles/s41467-018-05761-w&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.043802&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have never worked with ML myself and am curious to know, aside from being used in combination with existing methods,&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How is it being used and what are some key examples of ML being used to develop new - or extend existing methodologies for modeling matter? What is the current state of the art in this sense?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="175" LastActivityDate="2020-07-26T06:52:39.583" Title="Can Machine Learning lead to the more accurate theories and methods for matter modeling?" Tags="|reference-request|quantum-mechanics|machine-learning|many-body-physics|" AnswerCount="2" CommentCount="1" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1688" PostTypeId="1" CreationDate="2020-07-26T03:04:00.810" Score="14" ViewCount="176" Body="&lt;p&gt;There are many different computational methods used in matter modelling. For example: solving multi-electron Schroedinger equation, DFT with different approximations, Quantum Monte Carlo, etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How does each method scale with system size (and if possible, can you give a brief reason why)?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-26T13:12:10.233" LastActivityDate="2020-11-13T17:13:13.397" Title="Order of scaling for different algorithms" Tags="|density-functional-theory|one-topic-per-answer|quantum-monte-carlo|algorithms|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1689" PostTypeId="2" ParentId="1687" CreationDate="2020-07-26T03:55:22.810" Score="9" Body="&lt;p&gt;It is certainly possible to develop ML models that yield more accurate results than would be possible without ML.&lt;/p&gt;&#xA;&lt;p&gt;One route to do this is through so-called &amp;quot;Δ-learning&amp;quot; where you use ML to learn a &lt;em&gt;correction&lt;/em&gt; to a less expensive, often less accurate level of theory. An example can be found &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.5b00099&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for thermochemical properties of organic molecules. Somewhat related to this general idea, &lt;a href=&quot;https://arxiv.org/pdf/2007.08026.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; is a paper discussing how ωB97X-D/def2-TZVP energies were able to be predicted from semi-empirical GFN1-xTB input features.&lt;/p&gt;&#xA;&lt;p&gt;Naturally, another route one can take is to use ML with data from experiments, which can yield more accurate results than theory alone. For instance, it is well-established that GGA functionals yield underpredicted band gaps, and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpclett.8b00124&quot; rel=&quot;noreferrer&quot;&gt;prior ML work&lt;/a&gt; has been carried out to predict band gaps at greater-than-DFT accuracy with this in mind. Many other studies are of this type, such as this &lt;a href=&quot;https://chemrxiv.org/articles/Can_Machine_Learning_Be_More_Accurate_Than_TD-DFT_Prediction_of_Emission_Wavelengths_and_Quantum_Yields_of_Organic_Fluorescent_Materials/12111060&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; on ML models that can be more accurate than TD-DFT for emission wavelengths.&lt;/p&gt;&#xA;&lt;p&gt;Given a large dataset of inexpensive but somewhat inaccurate data and a smaller dataset of more expensive (or difficult to obtain) but accurate data, one can also use &amp;quot;transfer learning&amp;quot; to develop a ML model that has an accuracy comparable to the high-fidelity reference data. As an example, &lt;a href=&quot;https://www.nature.com/articles/s41467-019-10827-4&quot; rel=&quot;noreferrer&quot;&gt;this work&lt;/a&gt; showed that a neural network potential could approach CCSD(T)/CBS accuracy on a dataset that is largely DFT-generated.&lt;/p&gt;&#xA;&lt;p&gt;It is also possible to use ML models to identify likely issues or errors with a given calculation, as nicely demonstrated in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b00057&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; by Kulik and coworkers. Presumably, this could be used to make your calculations more accurate by knowing what calculation failures need to be addressed.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-07-26T04:00:48.587" LastActivityDate="2020-07-26T04:00:48.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1690" PostTypeId="1" CreationDate="2020-07-26T06:02:19.460" Score="17" ViewCount="3358" Body="&lt;p&gt;It's been taught by my lecturer that infrared (IR) spectra are widely used for chemical bonding determination.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;is it possible to calculate bond lengths according to the IR spectra?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If it is yes, let me know how to determine it.&#xA;If it is no, let me know another interpretation method which is more reliable for it.&lt;/p&gt;&#xA;" OwnerUserId="187" LastEditorUserId="5" LastEditDate="2020-07-27T01:06:58.023" LastActivityDate="2020-12-07T14:37:59.163" Title="Bond length from infrared spectra?" Tags="|molecular-modeling|spectroscopy|valence-bond-theory|" AnswerCount="5" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1691" PostTypeId="2" ParentId="1688" CreationDate="2020-07-26T06:32:52.457" Score="9" Body="&lt;p&gt;From my experience with &lt;strong&gt;Stochastic Series Expansion&lt;/strong&gt; (SSE) QMC (a type of discrete-time QMC) the computational cost scales like &lt;span class=&quot;math-container&quot;&gt;$\beta L^d$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In practice, it's often important to account for the finite-size gap &lt;span class=&quot;math-container&quot;&gt;$\Delta \propto 1/L$&lt;/span&gt;, so to stay consistently &lt;em&gt;above&lt;/em&gt; or &lt;em&gt;below&lt;/em&gt; that finite-size gap, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; is typically set to scale as &lt;span class=&quot;math-container&quot;&gt;$\beta = cL$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; is some constant, so the full scaling to see a desired effect is usually &lt;span class=&quot;math-container&quot;&gt;$L^{d+1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I don't have experience with other forms of QMC, like continuous time QMC, but I believe they are similar.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-07-26T06:32:52.457" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1692" PostTypeId="2" ParentId="1687" CreationDate="2020-07-26T06:52:39.583" Score="7" Body="&lt;p&gt;Within Monte Carlo (MC) methods, there are a few areas of active research in this regard:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Training ML models to &lt;strong&gt;identify phase transitions:&lt;/strong&gt; In practice, it challenging to identify phase transitions in Monte Carlo methods. The simulations only measure observables that are manually programmed in, so you have to know where to look, or you may not even realize that phase transition is occurring. Some phase transitions have nonobvious order parameters (especially for topological phase transitions. E.g. &lt;a href=&quot;https://doi.org/10.1038/nphys4035&quot; rel=&quot;noreferrer&quot;&gt;Carrasquilla &amp;amp; Melko Nat. Phys. &lt;strong&gt;13&lt;/strong&gt;, 431 (2017)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Training ML models on Monte Carlo configurations from a conventional method and then &lt;strong&gt;using the trained models to generate more data:&lt;/strong&gt; The idea here is to train a model that can generalize from (for example) a small system and generate accurate sample configurations from a larger system or one at a more difficult-to-study point. E.g. &lt;a href=&quot;https://arxiv.org/abs/1610.03137&quot; rel=&quot;noreferrer&quot;&gt;Liu, Qi, Meng &amp;amp; Fu, Phys. Rev. B &lt;strong&gt;95&lt;/strong&gt;, 041101 (2017)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Using ML to &lt;strong&gt;identify new types of MC update schemes:&lt;/strong&gt; For special cases, there are often clever cluster update algorithms that can greatly improve MC sampling efficiency, but these are difficult to discover. This line of inquiry attempts to train ML models to invent new update types (or at least get inspiration that humans can then refine into an algorithm). E.g. &lt;a href=&quot;https://doi.org/10.1103/PhysRevE.99.06210&quot; rel=&quot;noreferrer&quot;&gt;Zhao, Kao, Wu &amp;amp; Kao, Phys. Rev. E &lt;strong&gt;99&lt;/strong&gt;, 062106 (2019)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-07-26T06:52:39.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1693" PostTypeId="1" CreationDate="2020-07-26T07:08:02.600" Score="14" ViewCount="761" Body="&lt;p&gt;There are enough tensor-network/&lt;a href=&quot;https://en.wikipedia.org/wiki/Density_matrix_renormalization_group&quot; rel=&quot;noreferrer&quot;&gt;DMRG&lt;/a&gt; packages that support python (ALPS, OpenMPS, pyUni10) that it would seem (to an outsider) that it's possible to do some substantial work with DMRG without messing with C or any other languages. Are these packages sufficiently fast and full-featured that students could do meaningful research work using just python?&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-07-26T23:34:36.690" LastActivityDate="2021-05-25T12:36:12.233" Title="Is python sufficient for serious tensor network or DMRG calculations?" Tags="|software|python|dmrg|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1694" PostTypeId="1" CreationDate="2020-07-26T07:12:19.003" Score="8" ViewCount="295" Body="&lt;p&gt;&lt;strong&gt;What are the top journals that focus on or cover matter modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For context: I am a physicist, which is a small field, so I find it difficult to navigate the much-larger space of materials science and chemistry that much of the matter modeling work tends to get done.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="175" LastEditDate="2020-07-26T09:06:36.520" LastActivityDate="2020-07-29T21:32:09.353" Title="What are the top journals that focus on or cover matter modeling?" Tags="|reference-request|publishing|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1695" PostTypeId="1" CreationDate="2020-07-26T07:20:30.113" Score="9" ViewCount="363" Body="&lt;p&gt;What packages exist that can help someone, especially a new masters/PhD student get started with QMC on spin or Hubbard systems?&lt;/p&gt;&#xA;&lt;p&gt;As an example, for writing a stochastic series expansion QMC program for the 2D Heisenberg antiferromagnet.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-06-18T18:11:47.963" LastActivityDate="2021-06-20T08:39:21.243" Title="What packages exist for building quantum Monte Carlo simulations of spin or Hubbard Hamiltonians?" Tags="|one-topic-per-answer|software-recommendations|model-hamiltonians|quantum-monte-carlo|spin-models|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1696" PostTypeId="1" CreationDate="2020-07-26T08:05:27.873" Score="12" ViewCount="135" Body="&lt;p&gt;There are many flavors of DFT that are alternative to, or go beyond the Kohn-Sham formulation (KS-DFT).&#xA;Some of these are based on approximations that sacrifice accuracy when compared to KS-DFT, but in exchange are computationally cheaper and allow the modeling of larger systems.&lt;/p&gt;&#xA;&lt;p&gt;Two popular methods of this kind, are &lt;a href=&quot;https://en.wikipedia.org/wiki/Orbital-free_density_functional_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;Orbital-Free DFT&lt;/a&gt; (link to an answer on OFDFT &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1513/what-are-the-types-of-dft&quot;&gt;here&lt;/a&gt;) and &lt;a href=&quot;https://royalsocietypublishing.org/doi/full/10.1098/rsta.2012.0483&quot; rel=&quot;nofollow noreferrer&quot;&gt;Density Functional Tight-Binding&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I have not yet seen a comparative study on the performance of these methods, but I wonder if anyone here is able to offer any insights about how they may compare?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2021-11-23T21:35:02.703" LastActivityDate="2021-11-23T21:35:02.703" Title="Orbital-free DFT and Density Functional Tight-Binding: Comparison" Tags="|density-functional-theory|reference-request|tight-binding|density-functional-tight-binding|" AnswerCount="0" CommentCount="8" ClosedDate="2021-12-26T00:06:39.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="1697" PostTypeId="1" AcceptedAnswerId="1705" CreationDate="2020-07-26T08:37:42.840" Score="23" ViewCount="4011" Body="&lt;p&gt;I am new to the world of Molecular Dynamics (zero practical experience), and I know that a starting point to really go into the back-bone of MD is Statistical Mechanics (took a semester course in undergrad, loved it, will be the focus of my PhD).&lt;/p&gt;&#xA;&lt;p&gt;My ultimate goal is to become a &lt;em&gt;developer&lt;/em&gt; of advanced or modern MD, such as Many-body Molecular and Quantum MD methods (e.g. Path Integral MD). Example systems I am interested in being able to model are quantum fluids and super-critical fluids.&lt;/p&gt;&#xA;&lt;p&gt;What are some &lt;em&gt;essential&lt;/em&gt; books I need to get and read in order to become an avid MD theoretician? Are there any &lt;em&gt;must read&lt;/em&gt; papers I need to dedicate my weekend mornings to?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-07-27T01:06:41.983" LastActivityDate="2021-07-01T05:45:02.437" Title="References for Molecular Dynamics?" Tags="|reference-request|molecular-dynamics|statistical-thermodynamics|quantum-dynamics|" AnswerCount="5" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1698" PostTypeId="1" CreationDate="2020-07-26T08:42:40.213" Score="12" ViewCount="251" Body="&lt;p&gt;I am facing problems in calculating the phonon band structure for bilayer 2D systems. While the band structure mostly shows positive frequencies for the 1 layer system, going to 2 layers makes some frequencies imaginary. Moreover, the choice of van der Waals interaction also comes into account for the bilayer system and for some van der Waals functionals, phonon calculations are not properly implemented.&lt;/p&gt;&#xA;&lt;p&gt;Can someone share thoughts on calculating the phonon band structure for bilayer or perhaps multilayered 2D systems and which approach should be adopted to tackle this problem?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="792" LastEditDate="2020-07-26T16:43:47.060" LastActivityDate="2020-07-28T08:28:38.320" Title="Phonon Calculations for Bilayer 2D systems" Tags="|density-functional-theory|vasp|band-structure|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1699" PostTypeId="1" CreationDate="2020-07-26T08:47:29.447" Score="13" ViewCount="581" Body="&lt;p&gt;Can someone explain how to verify the presence of Rashba effect from the band structure calculations?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2021-01-22T07:16:46.813" LastActivityDate="2021-04-05T11:20:54.847" Title="Rashba effect in 2D systems" Tags="|band-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1700" PostTypeId="1" CreationDate="2020-07-26T08:52:56.540" Score="10" ViewCount="1085" Body="&lt;p&gt;Can someone share appropriate tags and method to apply Electric Field in VASP?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="88" LastEditDate="2020-07-26T14:43:34.680" LastActivityDate="2020-07-26T15:18:40.623" Title="Electric Field Calculations in VASP" Tags="|density-functional-theory|vasp|electric-field|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1701" PostTypeId="1" CreationDate="2020-07-26T08:59:09.863" Score="11" ViewCount="536" Body="&lt;p&gt;Topological insulators and quantum materials are gaining increasing interest across the physical, chemical and materials communities.&lt;/p&gt;&#xA;&lt;p&gt;Today, one can go to the &lt;a href=&quot;https://www.topologicalquantumchemistry.com/#/&quot; rel=&quot;noreferrer&quot;&gt;Topological Materials Database&lt;/a&gt; and see whether a given bulk system is a Topological Insulators or Weyl Semimetal, but it remains unclear (at least to a moral like me) what steps could be taken to determine this from scratch.&lt;/p&gt;&#xA;&lt;p&gt;If a DFT practitioner wants to model a a material and determine whether it has topological properties from scratch, with zero prior experience in these materials (but experience in semiconductors, surfaces, adsorption), what would be the &lt;em&gt;key elements&lt;/em&gt; and steps required to carry out such a study?&lt;/p&gt;&#xA;&lt;p&gt;Note: Assume that the researcher has already modeled the electronic band structure of a selected material with and without spin-orbit coupling.&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-07-26T18:58:23.017" LastActivityDate="2021-01-01T03:40:43.077" Title="How to model Topological Insulators from first-principles?" Tags="|density-functional-theory|topological-insulators|methodology|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1702" PostTypeId="2" ParentId="1701" CreationDate="2020-07-26T09:05:08.267" Score="6" Body="&lt;p&gt;Finding topological invariant number(called Z&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; number) can give information about topological invariance. Different codes are available for such calculations such as Z2pack or wanniertools and others.&lt;/p&gt;&#xA;" OwnerUserId="879" LastActivityDate="2020-07-26T09:05:08.267" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1703" PostTypeId="1" CreationDate="2020-07-26T09:07:52.463" Score="15" ViewCount="1123" Body="&lt;p&gt;Can magnetism and topological insulating behavior coexist in a material? If yes, can someone refer to a recent work?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="792" LastEditDate="2020-08-11T07:09:05.210" LastActivityDate="2020-08-11T07:09:05.210" Title="Magnetism and Topology" Tags="|magnetism|topological-insulators|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1704" PostTypeId="1" CreationDate="2020-07-26T09:15:01.633" Score="13" ViewCount="1793" Body="&lt;p&gt;How to distinguish between a Weyl semimetal and a Dirac semimetal? Which calculations are required to check their existence? Which codes can be used?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="792" LastEditDate="2020-07-30T08:12:24.540" LastActivityDate="2020-07-30T08:12:24.540" Title="Weyl Semimetal and Dirac semimetal" Tags="|weyl-semimetal|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1705" PostTypeId="2" ParentId="1697" CreationDate="2020-07-26T09:22:50.107" Score="17" Body="&lt;p&gt;A good place to start is the classical Allen-Tildesley book, Computer Simulation of Liquids, which covers the basics of molecular dynamics that hasn't really changed in a long time. The book can be supplemented with literature, such as review articles for whatever it is you want to do.&lt;/p&gt;&#xA;&lt;p&gt;Software manuals are also often quite useful to find out how things are done nowadays. For instance, GROMACS has had very good documentation for a long time; &lt;a href=&quot;http://manual.gromacs.org/current/reference-manual/index.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; is a link to their current reference manual which covers a lot of topics and has references to the original literature.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-26T09:22:50.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1706" PostTypeId="2" ParentId="1703" CreationDate="2020-07-26T09:25:14.740" Score="11" Body="&lt;p&gt;Not a very thorough answer, but it should get the ball rolling.&lt;/p&gt;&#xA;&lt;p&gt;Spontaneous magnetization or extrinsically magnetic TIs have been achieved through defect engineering in non-magnetic Topological Insulators. This is typically done via doping of 3&lt;em&gt;d&lt;/em&gt; magentic atoms (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Mn}$&lt;/span&gt;). A recent review (2019) published in &lt;em&gt;Nature Reviews Physics&lt;/em&gt; on the concepts and experimental progress on Magnetic Topological Insulators can be found &lt;a href=&quot;https://www.nature.com/articles/s42254-018-0011-5&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also last year, &lt;span class=&quot;math-container&quot;&gt;$\ce{MnBi_2Te_4}$&lt;/span&gt; was predicted and discovered. It is a van der Waals layered material, with intralayer ferromagnetic coupling. However, the interlayer coupling is anti-ferromagntic. The &lt;em&gt;nature&lt;/em&gt; article can be found &lt;a href=&quot;https://www.nature.com/articles/s41586-019-1840-9&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. This is big, so &lt;a href=&quot;https://phys.org/news/2019-12-intrinsic-magnetic-topological-insulator.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; is a physics news article about the discovery.&lt;/p&gt;&#xA;&lt;p&gt;Question: Given that these materials are layered, has anyone studied if the monolayer transitions to Ferromagnetic? That would be an intersesting study!&lt;/p&gt;&#xA;&lt;p&gt;Also, a theoretical study focused on extending the (then predicted) properties of &lt;span class=&quot;math-container&quot;&gt;$\ce{MnBi_2Te_4}$&lt;/span&gt; to a general class of compounds &lt;span class=&quot;math-container&quot;&gt;$\ce{MB_2X_4}$&lt;/span&gt;. Their methodology was based on primarily on DFT, so it will definitely be an interesting read (in reference my question you answered!).&lt;/p&gt;&#xA;&lt;p&gt;I am sure that there are more studies out by now. I would check recent publications in Physical Review journals to start!&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="7" LastEditDate="2020-07-26T13:16:50.887" LastActivityDate="2020-07-26T13:16:50.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1707" PostTypeId="2" ParentId="1697" CreationDate="2020-07-26T09:40:27.943" Score="19" Body="&lt;p&gt;Another extremely popular resource is Frenkel and Smit's textbook &amp;quot;Understanding Molecular Simulation&amp;quot;. It covers all basics on molecular dynamics, Monte Carlo, some common enhanced sampling methods, free energies and it even derives the Ewald summation. This is basically a book that doesn't shy away from messy derivations and it gives you a lot of example code for many of the basic algorithms. Great for a first course in MD.&lt;/p&gt;&#xA;&lt;p&gt;A personal favourite which is more theoretical is Tuckerman's &amp;quot;Statistical Mechanics: Theory and Molecular Simulation&amp;quot;. While it is certainly not as practical as the first book, it is specifically oriented towards theory of molecular simulation and it includes many interesting topics, including path integral methods so this one is also very relevant.&lt;/p&gt;&#xA;&lt;p&gt;Finally, a very good book on the aspect of integrators is Leimkuhler and Reich's &amp;quot;Simulating Hamiltonian Dynamics&amp;quot; textbook. I'd say it's much more advanced than the other two books and is strictly theoretical, so while it might not be of immediate use to you, it is definitely a good read.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-07-26T09:40:27.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1708" PostTypeId="2" ParentId="1582" CreationDate="2020-07-26T09:51:20.037" Score="11" Body="&lt;p&gt;Calculation of QD using VASP is not that much different from bulk calculations; you just need to ensure that sufficient vacuum is applied in all 3 spatial dimensions. My experience is that 10-15 Angstrom is sufficient, but this needs to be tested for your system and property of interest.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;em&gt;trends&lt;/em&gt; in many optical and electronic properties (such as absorption energy) of QD are reliable using conventional DFT with semi-local functionals such as PBE. It is well known that the first exciton peak decreases in energy as the size of the QD increases, due to the loss of quantum confinment effect.&lt;/p&gt;&#xA;&lt;p&gt;Another important thing to note is that ligands also play a very important role at controlling the optical properties. They are different from &amp;quot;bare&amp;quot; QD. In general the surface needs to be fully passivated with ligands while ensuring overall stoichiometry.&lt;/p&gt;&#xA;" OwnerUserId="1060" LastEditorUserId="792" LastEditDate="2020-07-26T10:04:03.057" LastActivityDate="2020-07-26T10:04:03.057" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1709" PostTypeId="2" ParentId="1703" CreationDate="2020-07-26T10:00:37.467" Score="10" Body="&lt;p&gt;Magnetic order and topological order can exist simultaneously.&lt;/p&gt;&#xA;&lt;p&gt;In fact, what one may call the very first proposal of an instrinsic topological material was &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.61.2015&quot; rel=&quot;noreferrer&quot;&gt;Haldane's model&lt;/a&gt; from 1988, which is an example of this. In this tight binding model, based on a hexagonal 2-dimensional lattice (think graphene), we have a next-nearest-neighbour complex hopping term which represents a staggered magnetic flux. As such, this model breaks time reversal symmetry which leads to an opening of the band gap of graphene (see my answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1598/how-to-understand-the-time-reversal-symmetry-of-graphene/1602#1602&quot;&gt;here&lt;/a&gt;) and to a non-zero Chern number, which results in the quantum anomalous Hall effect. The resulting topologically ordered material is called a Chern insulator, and the quantum anomalous Hall effect was realized experimentally in 2013 by doping magnetic chromium into the topological insulator (Bi,Sb)&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;Te&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; as reported in this &lt;a href=&quot;https://science.sciencemag.org/content/340/6129/167&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;. As Etienne Palos nicely explains in their answer, there has been a lot of work since in trying to get materials that exhibit simultaneous magnetic and topological orders intrinsically.&lt;/p&gt;&#xA;&lt;p&gt;A final remark about terminology. When people refer to &amp;quot;topological insulators&amp;quot;, it is typically understood that one is talking about &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; time-reversal invariant topological insulators. As such, breaking time reversal symmetry with magnetic order cannot be included in this classification, but instead leads to other types of topological order.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-26T10:00:37.467" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1710" PostTypeId="2" ParentId="1686" CreationDate="2020-07-26T10:02:38.907" Score="5" Body="&lt;p&gt;As a (very) incomplete answer to this question, here is &lt;strong&gt;one&lt;/strong&gt; paper discussing the Ising FM with a plaquette term. Here specifically chosen because there was not a good cluster algorithm for it (so they could try out a new algorithm: self-learning MC).&lt;/p&gt;&#xA;&lt;p&gt;Junwei Liu, Yang Qi, Zi Yang Meng &amp;amp; Liang Fu, &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.95.041101&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. B &lt;strong&gt;95&lt;/strong&gt;, 041101 (2017)&lt;/a&gt;&lt;br /&gt;&#xA;Also &lt;a href=&quot;https://arxiv.org/abs/1610.03137&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1610.03137&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-07-27T03:26:34.270" LastActivityDate="2020-07-27T03:26:34.270" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1711" PostTypeId="2" ParentId="1582" CreationDate="2020-07-26T15:03:34.137" Score="6" Body="&lt;p&gt;It is worthwhile to add to liuyun's answer that even though these calculations are in theory straightforward there are some caveats you have to acknowledge.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Band gap tends to be underestimated by conventional DFT methods. This can be fixed to some degree by relaxing your nanoparticle using functionals such as PBE then using a hybrid functional such as HSE06 as a single point for band structure.  This is something that must be benchmarked though since it is possible a relaxation at the HSE06 level will change things.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Computational limits will quickly become a problem with common experimental systems. As a quick check, using ASE-GUI to make a 1.9 nm nanoparticle results in 249 atoms and a massive unit cell.  This is where it may be useful to look at trends on smaller systems and/or using a lower level of theory to pre-optimize your particles.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I am not an expert in this sort of calculation but you seem concerned with exciton properties.  I do believe you will not get the optical absorption energy due to the exciton binding energy shifting the optical band gap higher than the electronic band gap.  You may need time dependent calculations for that, but you can use some codes to analyze the band structure for the effective masses of the electron and hole.  This may be enough for you depending on what your goal is.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This is less of an issue and more of a comment, ligands will shift the optical properties but solvents will as well.  Using VASPsol to handle solvent interactions may be useful.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You could also consider switching to a different code / approach, I believe GPAW supports TD-DFT calculations in LCAO mode which is a highly parallelizable method.  This won't give the same level of accuracy (using default basis sets at least, I do not know about the limit of accuracy as you increase the basis set).  This may let you directly find the optical absorption spectra.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-26T15:03:34.137" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1712" PostTypeId="2" ParentId="1703" CreationDate="2020-07-26T15:04:43.343" Score="7" Body="&lt;h2&gt;Topological magnon band structures&lt;/h2&gt;&#xA;&lt;p&gt;Another way of combining topology and magnetism is to consider a magnetic insulator with non-trivial magnon band structure. This setting is somewhat different from the usual picture of topological electron band structure in that i) the band structure represents only quasiparticle excitations, ii) the quasiparticles are bosonic, iii) the quasiparticles are electrically neutral. Nevertheless, we can define and calculate topological invariants for such systems - especially on the level of linear spin wave theory. In this setting, nontrivial topology is typically due to spin-orbit coupling related interactions, e.g. of the Dzyaloshinskii-Moriya type, or to noncollinear magnetic orders. The most straight-forward systems are analogs of Chern insulators where the bands are gapped and separated from each other, with a non-trivial Chern number. This can be linked to an non-quantized &lt;a href=&quot;https://science.sciencemag.org/content/329/5989/297.abstract&quot; rel=&quot;noreferrer&quot;&gt;magnon thermal Hall effect&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, it's also possible to have magnon band structures that are analogs of other electronic topological phases. For example, a ferromagnetic model on the honeycomb lattice was proposed in &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.117.227201&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, and shown to be analogous to Haldane's model mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1709/671&quot;&gt;ProfM's answer&lt;/a&gt; in one limit. Over the last several years it has also become popular to consider other interesting band structures, including &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.047203&quot; rel=&quot;noreferrer&quot;&gt;exotic band touching points&lt;/a&gt;, and analogs of topological semimetals.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-26T15:04:43.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1713" PostTypeId="2" ParentId="1690" CreationDate="2020-07-26T15:13:06.190" Score="11" Body="&lt;p&gt;This is a task suited to single crystal XRD.  This does require you to be able to form a crystal of your substance which can be difficult at times but this allows for potentially high accuracy of bond lengths/angles to be determined.&lt;/p&gt;&#xA;&lt;p&gt;In the spirit of this community though, if you do know the bonding structure from something like NMR, you could model the molecule in a code such as NWChem or Gaussian and with an appropriate level of theory (accounting for solvation etc) get fairly accurate bond lengths.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-26T15:13:06.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1714" PostTypeId="2" ParentId="1700" CreationDate="2020-07-26T15:18:40.623" Score="8" Body="&lt;p&gt;I think VASP has limited electric field ability right now, but someone may come along later and correct me.  If you have a surface in the Z direction, you could enable an electric field as such.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EFIELD = X # Units eV/A&#xA;IDIPOL = 3 # Z direction&#xA;LDIPOL = .TRUE. # Enable dipole corrections&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-26T15:18:40.623" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1715" PostTypeId="1" AcceptedAnswerId="1731" CreationDate="2020-07-26T15:29:35.403" Score="8" ViewCount="223" Body="&lt;p&gt;&lt;a href=&quot;https://www.mrcc.hu/index.php/forum/search?query=dynamic&amp;amp;childforums=1&quot; rel=&quot;nofollow noreferrer&quot;&gt;I have asked this question on the MRCC forum&lt;/a&gt; but did not get an answer.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to understand how to use CFOUR with the MRCC program for computing dynamic polarizability.  To begin with, I am trying the simple system of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The input passed to the CFOUR program is given below. This program finishes with error which is given in the second block.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;hydrogen_molecule&#xA;H&#xA;H 1 R&#xA;&#xA;R=1.41&#xA;&#xA;*ACES2(CALC=CCSD,BASIS=AUG-PVQZ,CHARGE=0,PROP=DYNAMICAL&#xA;SCF_CONV=10&#xA;CC_PROGRAM=MRCC&#xA;INPUT_MRCC=ON&#xA;CC_CONV=10&#xA;LINEQ_CONV=10&#xA;DIFFTYPE=UNRELAXED&#xA;MEMORY=14&#xA;MEM_UNIT=GB)&#xA;&#xA;%frequency&#xA;1&#xA;0.0856&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Last few lines of the output file received.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;.&#xA;.&#xA;.&#xA;  list                   233               1069156                  1034&#xA;                  1034&#xA;  list                   233                729316                   854&#xA;                   854&#xA;  list                   233               1483524                  1218&#xA;                  1218&#xA;  list                   233               1069156                  1034&#xA;                  1034&#xA;  list                   233               1069156                  1034&#xA;                  1034&#xA;  list                   233                729316                   854&#xA;                   854&#xA;         2874203179375         2874203179376         2874203180595&#xA;         2874203180613         2874203180614         2874203180706&#xA;         2874203180798&#xA;         2874203179375&#xA; [   1]   -0.9440567&#xA;         2874203179375                     0                     0&#xA; [   1]   -0.9440567&#xA;  scf energy  -1.02177241463266       0.375302907801333&#xA;         2874203179375         2874203179375         2874203179375&#xA; [   1]   -0.9440567&#xA;  escf- ...  0.375302907801617&#xA;  escf- ...  -1.88811334095569       0.491038018521418&#xA;  itot is                      0&#xA; using old mrcc fort.57&#xA; fort.56&#xA;     2     1     0     0     1     3     0     1     0     1     1     1     0     0     0    11     0     0           0.08560     0 13351&#xA;ex.lev,nsing,ntrip, rest,CC/CI, dens,conver, symm, diag,  CS ,spatial,  HF ,ndoub,nacto,nactv, tol ,maxex, sacc, freq, dboc, mem&#xA;  @CHECKOUT-I, Total execution time :       5.9000 seconds.&#xA;                9.25 seconds walltime passed&#xA; --executable xint finished with status            0&#xA; --invoking executable dmrcc&#xA; --executable dmrcc finished with status          127&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The full output file is available &lt;a href=&quot;https://www.mrcc.hu/media/kunena/attachments/1612/H2_MRCC_new.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Could someone clarify what would be the correct way to get this done?&#xA;(I can run test calculations if I receive suggestions.)&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Updates:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Last few lines of &lt;code&gt;fort.55&lt;/code&gt; file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        17                    46                    75&#xA;        86                    18                    92&#xA;        63                    41                    30&#xA;        87                    76                    64&#xA;        19                    65&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Error in the dmrcc execution was found to be related to the compiler (&lt;code&gt;dmrcc: error while loading shared libraries: libmkl_intel_ilp64.so: cannot open shared object file&lt;/code&gt;). After fixing it by setting the correct compilers before execution, the output received is &lt;a href=&quot;https://pastebin.com/i9buhwHD&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;.&#xA;Last few lines are shown below.&lt;/p&gt;&#xA;&lt;p&gt;Final results:&#xA;Total CCSD energy [au]:              -1.080378012654&lt;/p&gt;&#xA;&lt;p&gt;Calculating reduced density-matrix for root 1...&lt;/p&gt;&#xA;&lt;p&gt;Total energy from RDM [au]:          -0.928161992158&lt;/p&gt;&#xA;&lt;p&gt;************************ 2020-07-27 09:52:07 *************************&#xA;Normal termination of mrcc.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;--executable dmrcc finished with status            0&#xA;--invoking executable xdens&#xA;CCSD density and intermediates are calculated.&#xA;Unrelaxed density is calculated&#xA;enter routine DINTERF to read densities generated from external sources&#xA;two-particle density matrices&#xA;D(I,J)&#xA;0                     1                     1&#xA;1                     1                     1&#xA;1                     1                     0&#xA;1                     1                     1&#xA;1                     1                     1&#xA;1                     1                    19&#xA;30                    41                    46&#xA;65                    76                    87&#xA;1                    19                    30&#xA;41                    46                    65&#xA;76                    87                     0&#xA;0                     0                     0&#xA;0                     0                     0&#xA;0                     1                     1&#xA;DOO for spin                      1 -7.187996652958334E-002&#xA;1                     1&#xA;@RDDIR-F, I/O Error (IOSTAT =  25) on Unit  51.&#xA;@CHECKOUT-I, Total execution time :       0.0000 seconds.&#xA;--executable xdens finished with status            1&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1037" LastEditorUserId="5" LastEditDate="2020-08-04T22:12:18.880" LastActivityDate="2023-04-16T14:29:23.163" Title="Interfacing MRCC with CFOUR for dynamic polarizability" Tags="|coupled-cluster|mrcc|polarizability|answer-with-calculation|" AnswerCount="1" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="1716" PostTypeId="2" ParentId="1094" CreationDate="2020-07-26T15:35:24.207" Score="5" Body="&lt;p&gt;I have some limited experience with implicit solvents and attempting to polarize the system.  I would suggest that if you cannot afford to model the real solvation environment, try using a shell of solvent which can be polarized correctly.  This is also quite tricky to get working correctly, but may improve the situation since you are no longer using point charges directly to get polarization of the molecule.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-26T15:35:24.207" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1717" PostTypeId="2" ParentId="1690" CreationDate="2020-07-26T15:37:29.140" Score="9" Body="&lt;p&gt;Addendum: While the method described below is commonly used by experimentalists, I was mistaken that IR spectrum could not be used to obtain bond lengths. Nike's answer does a great job explaining how the entire potential energy surface can be determined by fitting using some model calculations. The important thing to learn from all this is that what you can compute is more often than not limited mainly by how complicated a model you are willing to use.&lt;/p&gt;&#xA;&lt;p&gt;IR can not be used in general to predict bond lengths, but under the right circumstances it is at least related. For example, the CO stretch frequencies of metal carbonyl compounds are &lt;a href=&quot;http://www.ilpi.com/organomet/carbonyl.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;related&lt;/a&gt; to the strength of the bond. If you know the bond lengths of few such compounds, you can derive a very accurate linear correlation between the bond length and the frequency.&lt;/p&gt;&#xA;&lt;p&gt;So while you can't directly predict bond lengths from IR alone, you can likely develop a correlation between a particular IR frequency and bond length for a series of related compounds. Depending on what you have available, these bond lengths could be experimental or could be obtained from quantum mechanical calculations.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-26T22:08:04.350" LastActivityDate="2020-07-26T22:08:04.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1718" PostTypeId="2" ParentId="1690" CreationDate="2020-07-26T15:59:53.740" Score="11" Body="&lt;p&gt;I agree with all answers provided so far: you cannot quantitatively &lt;em&gt;deduce&lt;/em&gt; bond lengths from infrared spectra. However, see the answer by Nike Dattani about the inverse, predicting IR spectra from theory.&lt;/p&gt;&#xA;&lt;p&gt;IR (and Raman) spectra can be very useful tools to &lt;em&gt;understand&lt;/em&gt; properties associated with bond lengths. An example I really like comes from the high pressure solid hydrogen literature. Studying high pressure hydrogen is extremely challenging, and standard structure determination techniques such as x-ray diffraction do not work very well because (i) samples are placed in diamond anvil cells to achieve the high pressures, so are very small, (ii) hydrogen is the lightest of all elements, so it only scatters x-rays very weakly, and (iii) hydrogen has no core electrons, so x-rays don't probe the position of the protons but instead probe the position of the bond.&lt;/p&gt;&#xA;&lt;p&gt;IR and Raman measurements are possible, and in fact are the main probes used to study this system. Hydrogen at pressures of about 200 GPa is in the so-called phase III, which is made of H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecules of a unique bond length. These lead to a single vibron Raman and IR peak. At higher pressures above about 230 GPa (although somewhat dependent on temperature), hydrogen undergoes a phase transition to so-called phase IV. This transition was identified by the appearance of a &lt;em&gt;second&lt;/em&gt; vibron peak in the Raman spectrum at a different frequency to the original one as explained in this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.125501&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;. The fact that there are &lt;em&gt;two&lt;/em&gt; distinct peaks indicates that there are now two types of H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecules, of different bond lengths. These phases are now called &amp;quot;mixed&amp;quot; phases, and are believed to be a stepping stone to atomic hydrogen. So although one cannot obtain quantitative bond lengths from an IR spectrum, they can still provide extremely useful information.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-26T18:39:47.660" LastActivityDate="2020-07-26T18:39:47.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1719" PostTypeId="1" CreationDate="2020-07-26T17:08:31.417" Score="12" ViewCount="171" Body="&lt;p&gt;I have two main modeling research lines: one related to structural biology (including rational drug design, &lt;em&gt;de novo&lt;/em&gt; design, polymorphism, etc.) and the other one related to condensed matter (nanostructures, crystals, etc.).&lt;/p&gt;&#xA;&lt;p&gt;Any time I submit a manuscript in the biological area, either the editors or the reviewers ask for experimental validation, even when we use very well established simulation tools to make the predictions (here we work only with small molecules and proteins, not with living organism simulations). On the other hand, when submitting a manuscript in the condensed matter area, we never received that complaint.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why are condensed matter predictions considered on par with experiment, while structural biology modeling receives more skepticism?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-12-20T00:47:57.753" LastActivityDate="2021-12-21T19:34:47.407" Title="Why are condensed matter predictions considered on par with experiment, while structural biology modeling receives more skepticism?" Tags="|density-functional-theory|condensed-matter|nanostructures|publishing|structural-biology|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1720" PostTypeId="2" ParentId="1690" CreationDate="2020-07-26T17:37:52.173" Score="13" Body="&lt;h3&gt;A &lt;em&gt;partial&lt;/em&gt; list of bond lengths I have determined from IR spectra over my career:&lt;/h3&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{ccc}&#xA;\rm{Molecule} &amp;amp; \rm{Bond ~Length ~ (picometers)} &amp;amp; \rm{References}\\&#xA;\hline&#xA;\ce{Li_2}(1^1\Sigma_g^+) &amp;amp; 267.298 74(19)&amp;amp; \href{}\textrm{2009 JCP, 2013 PRA} \\&#xA;\ce{Li_2}(1^3\Sigma_u^+) &amp;amp; 417.000 6(32)&amp;amp; \href{}\textrm{2011 JMS, 2013 PRA (2)}\\&#xA;\ce{Li_2}(1^1\Sigma_u^+) &amp;amp; 310.792 88(36)&amp;amp; \href{}\textrm{2009 JCP, 2013 PRA}\\&#xA;\ce{Li_2}(1^3\Sigma_g^+) &amp;amp; 306.543 6(16)&amp;amp; \href{}\textrm{2011 JMS, 2013 PRA (2)}\\&#xA;\ce{Li_2}(1^3\Pi_u) &amp;amp; 258.9 848(23)&amp;amp; \href{}\textrm{2015 arXiv}\\&#xA;\ce{BeH}(1^2\Sigma^+) &amp;amp; 134.2396(3)&amp;amp; \href{}\textrm{2015 JMS}\\&#xA;\ce{BeD}(1^2\Sigma^+) &amp;amp; 134.1713(3)&amp;amp; \href{}\textrm{2015 JMS}\\&#xA;\ce{BeT}(1^2\Sigma^+) &amp;amp; 134.1485(3)&amp;amp; \href{}\textrm{2015 JMS}\\&#xA;\vdots &amp;amp; \vdots &amp;amp; \vdots \\&#xA;\hline&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;The same methodology was used for the following molecules since 2009:&lt;/h3&gt;&#xA;&#xA;&lt;p&gt;Several electronic states and isotopologues of: Cs&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, Sr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, ArXe, LiCa, LiNa, MgH, Br&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, Mg&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, HF, HCl, HBr, HI, Be&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, NaH, and many more (&lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential#Applications&quot; rel=&quot;nofollow noreferrer&quot;&gt;see here for references&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h3&gt;There are several ways to do this:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The way I've been doing it is to fit a potential energy surface such that when fed through the vibrational Schrödinger equation, the eigenvalue differences match the experimental IR spectra.&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.34.57&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Philip Morse&lt;/strong&gt; did this for 56 different molecules in &lt;strong&gt;1929&lt;/strong&gt;&lt;/a&gt; and got &lt;span class=&quot;math-container&quot;&gt;$r_0$&lt;/span&gt; values with &amp;quot;calc-obs&amp;quot; (calculation minus observation) values within  &lt;span class=&quot;math-container&quot;&gt;$\pm 0.1\require{mediawiki-texvc}\,\AA$&lt;/span&gt; every time.&lt;/li&gt;&#xA;&lt;li&gt;But the Morse potential has two problems: (1) it has only 3 parameters (&lt;span class=&quot;math-container&quot;&gt;$D_e$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$k_e$&lt;/span&gt;), so it's not very flexible, and (2) it decays &lt;em&gt;exponentially&lt;/em&gt; to dissociation, when in fact we know it should decay with an inverse power-law, like &lt;span class=&quot;math-container&quot;&gt;$C_6/r^6$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;For several decades, any attempt to solve these two problems would cause us to lose the crucial property that the Morse potential is exactly solvable.&lt;/strong&gt; So people abandoned &amp;quot;direct potential fits&amp;quot; from the 1930s until recently.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Morse/Long-range (MLR) potential&lt;/strong&gt;&lt;/a&gt; that I developed with Bob LeRoy in the mid-to-late 2000s, solves both shortcomings of the Morse potential: It is a Morse potential at the bottom, but if you work out the calculus of &lt;span class=&quot;math-container&quot;&gt;$r\rightarrow \infty$&lt;/span&gt; you will discover that the potential literally becomes &lt;span class=&quot;math-container&quot;&gt;$C_6 / r^6$&lt;/span&gt; or whatever you want (you can choose your own long-range function &lt;span class=&quot;math-container&quot;&gt;$u(r)$&lt;/span&gt;) toward dissociation (and we have more parameters and hence more flexibility to fit to lots of data). By this time we had computers so we did not care about &amp;quot;exact solvability&amp;quot; and we could do iterative non-linear least-squares-fitting of &lt;em&gt;&lt;strong&gt;numerically&lt;/strong&gt;&lt;/em&gt; obtained eigenvalues of the vibrational Schrödinger equation, to 17,477 spectroscopic lines (many of them from FTIR: Fourier Tranform &lt;strong&gt;IR&lt;/strong&gt; spectra). &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.84.052502&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jim Mitroy called our 2009 paper a &amp;quot;landmark in diatomic spectral analysis&amp;quot;&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;Prior to the revival of &amp;quot;direct potential fits&amp;quot;, you could use Bob LeRoy's software &lt;a href=&quot;http://scienide2.uwaterloo.ca/%7Erleroy/dparfit/&quot; rel=&quot;nofollow noreferrer&quot;&gt;dParFit&lt;/a&gt; (diatomic parameter fit) to  fit IR spectra to band constants or Dunham constants, which will give you &lt;span class=&quot;math-container&quot;&gt;$B_0$&lt;/span&gt; (the rotational constant for the first vibrational level), from which you can estimate &lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt; very accurately (but not &lt;em&gt;directly&lt;/em&gt; as in a direct-potential-fit). Alternatively one can build a potential without numerically solving the Schrödinger equation (as necessary in the &amp;quot;direct potential fits&amp;quot; described above) via the semi-classical &lt;a href=&quot;http://scienide2.uwaterloo.ca/%7Erleroy/RKR1-16/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RKR method&lt;/a&gt; which will result in extremely accurate (with about as many digits as shown in my above table) bond lengths as well.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Polyatomics:&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ideals.illinois.edu/handle/2142/100778&quot; rel=&quot;nofollow noreferrer&quot;&gt;I generalized the MLR potential to polyatomics&lt;/a&gt; and in principle it can be used to directly fit IR spectra of polyatomics to equilibrium bond lengths, angles, force constants and atomization energies, but writing the code to do this non-linear least-squares-fitting is something I don't feel like doing now that I've found new enjoyment in working on &lt;a href=&quot;https://arxiv.org/abs/1901.04405&quot; rel=&quot;nofollow noreferrer&quot;&gt;quadratization&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1411.6758&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantum computing&lt;/a&gt;, &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513002294&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantum dynamics&lt;/a&gt;,  &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00532&quot; rel=&quot;nofollow noreferrer&quot;&gt;electronic structure&lt;/a&gt;, &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/54987413#54987413&quot;&gt;bioinformatics&lt;/a&gt;, and other areas. If I could afford a student, we could get this working for polyatomics in a month.&lt;/p&gt;&#xA;&lt;h3&gt;Side note:&lt;/h3&gt;&#xA;&lt;p&gt;Fitting an entire potential energy surface when there's no IR (infrared / vibrational) data available, and there's only MW (microwave / rotational) data available, was considered a bit more special, but &lt;a href=&quot;https://arxiv.org/abs/1408.2276&quot; rel=&quot;nofollow noreferrer&quot;&gt;we did it for ZnO in 2014&lt;/a&gt;. We obtained &lt;span class=&quot;math-container&quot;&gt;$r_e = 1.704682(2)$&lt;/span&gt; and the energy difference between &lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$v_1$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$728.395\pm0.007$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; when the best available value was &lt;span class=&quot;math-container&quot;&gt;$726\pm 20$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; at the time (we were about 3 orders of magnitude more accurate!). To obtain a &lt;em&gt;vibrational&lt;/em&gt; energy difference so precisely, without any vibrational spectra, is another strength of fitting potentials to spectroscopic data.&lt;/p&gt;&#xA;&lt;h3&gt;References for the table:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3264688&quot; rel=&quot;nofollow noreferrer&quot;&gt;2009 JCP&lt;/a&gt;, &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.88.062510&quot; rel=&quot;nofollow noreferrer&quot;&gt;2013 PRA&lt;/a&gt;, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;2011 JMS&lt;/a&gt;, &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.87.052505&quot; rel=&quot;nofollow noreferrer&quot;&gt;2013 PRA (2)&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1508.07184&quot; rel=&quot;nofollow noreferrer&quot;&gt;2015 arXiv&lt;/a&gt;, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285214001945&quot; rel=&quot;nofollow noreferrer&quot;&gt;2015 JMS&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-07T14:37:59.163" LastActivityDate="2020-12-07T14:37:59.163" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1721" PostTypeId="1" CreationDate="2020-07-26T18:29:21.103" Score="21" ViewCount="1055" Body="&lt;p&gt;Studying the interaction of a boron-nitride nanostructure with lead, we calculated the wave function using Gaussian software (single point energy with basis-set mix 6-311G++/lanl2dz and hseh1pbe functional) and did a topological analysis using the &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt; software.&lt;/p&gt;&#xA;&lt;p&gt;The properties analyzed in the topological study were the critical points/basins in the electron density (via QTAIM), the Laplacian of the electron density and the electron localization function (ELF). Images with some of the results are below.&lt;/p&gt;&#xA;&lt;p&gt;From the QTAIM analysis we got the the lead make a bond with one nitrogen atom at the nanostructure surface. This is due to the interbasin path together with the bond critical point between both atoms.&lt;/p&gt;&#xA;&lt;p&gt;The electron localization function is shown in Fig. 2. According to its definition&lt;sup&gt;1&lt;/sup&gt;, ELF took values among 0 and 1. The upper limit ELF=1, correspond to perfect localization and ELF=1/2 correspond to electron-gas like probability.&lt;/p&gt;&#xA;&lt;p&gt;My doubts is: &lt;strong&gt;after looking to Fig. 2, if a bond is formed between lead and nitrogen atoms, we shouldn't expect more red regions between both atoms?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fig. 1. Electron density. Bold deep blue lines: interbasin paths. Brown: (3,-3) nuclear critical point (NCP). Blue: (3,-1) bond critical point (BCP).&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/xSCNT.png&quot; height=&quot;450&quot;&gt;&#xA;&lt;p&gt;Fig. 2. Electron localization function.&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/hlZVY.png&quot; height=&quot;450&quot;&gt;&#xA;&lt;p&gt;Definition of ELF:&#xA;&lt;span class=&quot;math-container&quot;&gt;$ELF = {\left( {1 + \chi _\sigma ^2} \right)^{ - 1}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\chi _\sigma } = {D_\sigma }/D_\sigma ^0$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${D_\sigma } = {\tau _\sigma } - \frac{1}{4}\frac{{{{\left( {\nabla {\rho _\sigma }} \right)}^2}}}{{{\rho _\sigma }}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$D_\sigma ^0 = \frac{3}{5}{\left( {6{\pi ^2}} \right)^{2/3}}\rho _\sigma ^{5/3}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\tau _\sigma } = \sum\limits_i^\sigma  {{{\left| {\nabla {\psi _i}} \right|}^2}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where: &lt;span class=&quot;math-container&quot;&gt;$\tau _\sigma$&lt;/span&gt; is the kinetic energy for spin &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the electron density.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A. D. Becke and K. E. Edgecombe. A simple measure of electron localization in atomic and molecular systems. J. Chem. Phys. 92, 5397 (1990) (DOI: &lt;a href=&quot;http://dx.doi.org/10.1063/1.458517&quot; rel=&quot;noreferrer&quot;&gt;10.1063/1.458517&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2021-12-07T01:44:44.037" LastActivityDate="2021-12-07T01:44:44.037" Title="Interpreting electron localization function (ELF) results" Tags="|electron-density|atoms-in-molecules|multiwfn|" AnswerCount="0" CommentCount="11" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1722" PostTypeId="2" ParentId="1664" CreationDate="2020-07-26T18:29:34.770" Score="2" Body="&lt;p&gt;It turns out, splitting the scratch files doesn't help. I have a 32-bit version of Gaussian, and it has a 16Gb limit for the combined size of the scratch files (I don't know how I could miss that). So splitting the read-write file can't help here. Looks like I'll have to find better computational resources.&lt;/p&gt;&#xA;" OwnerUserId="723" LastActivityDate="2020-07-26T18:29:34.770" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1723" PostTypeId="2" ParentId="1693" CreationDate="2020-07-26T19:46:49.767" Score="11" Body="&lt;p&gt;There probably are good Python bindings to various DMRG implementations, which allow one to run DMRG from Python. Since the implementations typically rely on lower-level C/C++/Fortran routines, the calculations run quite quickly. E.g. PySCF appears to have bindings to various DMRG programs, see &lt;a href=&quot;https://sunqm.github.io/pyscf/dmrgscf.html&quot; rel=&quot;noreferrer&quot;&gt;https://sunqm.github.io/pyscf/dmrgscf.html&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you're talking about developing a new Python-only DMRG code, I doubt you'll succeed: the overhead is just too great. Julia might be an interesting alternative, though.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-26T19:46:49.767" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1724" PostTypeId="2" ParentId="831" CreationDate="2020-07-26T20:05:55.483" Score="4" Body="&lt;p&gt;Did you check that the bulk structures are stable? If they are, then the Coulomb part should be working, and the problem might be in your model.&lt;/p&gt;&#xA;&lt;p&gt;This type of problem is actually relatively common. If you use potentials that have been fit for bulk materials i.e. perfect crystals, you're only studying a small range of the possible configuration space: the atoms are perfectly bound, and have the perfect bond angles. Going to nanostructures, however, the atoms on the surface have fewer bonds than the ones inside, and all bets are off as to how the force field will behave.&lt;/p&gt;&#xA;&lt;p&gt;You're using the Coulomb-Buckingham potential, which is a pure pair potential &lt;span class=&quot;math-container&quot;&gt;$V(r) = A \exp(-Br) - C r^{-6} + q_1 q_2/ 4 \pi \epsilon_0 r$&lt;/span&gt;. I'm not an expert on iron nanoparticles, but I would assume that this kind of a pair potential is not expected to be very accurate as it neglects the effects of distance (the bonds might become stronger at shorter internuclear distances) and geometry (bond angle affects the strength of the bond).&lt;/p&gt;&#xA;&lt;p&gt;A more sophisticated potential, like Tersoff, might yield more reliable results. I even found a Fe-O potential published last year: &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/ab0931/meta&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys.: Condens. Matter 31 215401 (2019)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-26T20:05:55.483" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1725" PostTypeId="1" CreationDate="2020-07-26T23:16:34.597" Score="11" ViewCount="422" Body="&lt;p&gt;I have recently been working with non-collinear antiferromagnetic systems. I understand that, in order to obtain spin density, one must obtain the electron density in one configuration of spin and subtract the electron density in the other configuration.&lt;/p&gt;&#xA;&lt;p&gt;I am unsure as to how to go about this in my non-collinear system. Is it as simple as obtaining the electron density with my original antiferromagnetic configuration and then inverting the spin and running another SCF calculation? Is it necessary to restrict the spin configuration in any way?&lt;/p&gt;&#xA;&lt;p&gt;If anyone has experience with this, please let me know!&lt;/p&gt;&#xA;" OwnerUserId="204" LastEditorUserId="175" LastEditDate="2020-07-27T06:50:10.043" LastActivityDate="2020-08-08T18:25:01.633" Title="Spin density in systems with non-collinear magnetism using VASP" Tags="|density-functional-theory|vasp|magnetism|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1726" PostTypeId="2" ParentId="1693" CreationDate="2020-07-26T23:33:34.587" Score="8" Body="&lt;p&gt;I've heard people talking about working on tensor networks for electronic structure  since the 2000s, but here in the 2020s I'm aware of no code that can help me solve the problems in which I'm interested. I think &amp;quot;serious&amp;quot; tensor network codes for electronic structure are still a &amp;quot;dream&amp;quot;, and I'm becoming more and more doubtful that any time in the next few years we'll see (more general) tensor networks become &amp;quot;mainstream&amp;quot; in (almost) the way DMRG did.&lt;/p&gt;&#xA;&lt;p&gt;I have heard of progress with PEPS and MERA but mainly for spin Hamiltonians. I see that the Wikipedia page for DMRG currently provides links to &lt;a href=&quot;http://itensor.org/&quot; rel=&quot;noreferrer&quot;&gt;iTensor&lt;/a&gt;, and &lt;a href=&quot;https://uni10.gitlab.io/uni10/&quot; rel=&quot;noreferrer&quot;&gt;Uni10&lt;/a&gt; for which Adam Iaizzi (one of our favorite people, here at Matter Modeling SE) is a co-author. I can't quite figure out based on the documentation, how general of a tensor network iTensor supports, but it seems that whatever tensor networks they implement, can only be applied to spin Hamiltonians &amp;quot;models&amp;quot; rather than the &amp;quot;electronic structure Hamiltonian&amp;quot; in which I am personally interested. Uni10 seems to be able to do PEPS and MERA in addition to DMRG and maybe more, but again I cannot figure out to which Hamiltonians it can be applied. Both iTensor and Uni10 are written in C++.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is python sufficient for serious tensor network/DMRG calculations?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In 2011 &lt;a href=&quot;https://scholar.google.com/citations?user=HLFqTggAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;Martin Plenio&lt;/a&gt; told me at a Royal Society meeting that he coded a basic DMRG program himself in MATLAB (which you can imagine, is very doable). This means that NumPy too, can suffice for some purposes, since MATLAB and NumPy both call BLAS to do the heavy lifting (matrix arithmetic).&lt;/p&gt;&#xA;&lt;p&gt;I wrote a very similar code called &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513002294&quot; rel=&quot;noreferrer&quot;&gt;FeynDyn&lt;/a&gt; (Feynman Dynamics) for calcualting Feynman integrals numerically using the &amp;quot;tensor propagation algorithm&amp;quot;, which involves extremely high-rank tensors, organized in such a way that all necessary calculations can be done using matrix arithmetic (so the whole program is written in MATLAB which is about as fast as you can get for matrix arithmetic on either CPUs or GPUs). This is as far as I know, the &lt;strong&gt;fastest tensor propagation code for Feynman integrals&lt;/strong&gt; based on all comparisons I've done to FORTRAN codes written by leading colleagues in the field: Not only does it get the calculations done faster than all FORTRAN codes I've compared it to, when I run both my code and their code on a CPU, but thanks to the GPU programmers working at MathWorks my code benefits from a major speed-up, while none of the FORTRAN or C++ codes do can run on GPUs (they could probably get their codes working on GPUs with OpenACC or some CUDA wrapper but only someone who knows their code well enough can do it, and based on what I understand, those codes were not &lt;em&gt;&lt;strong&gt;vectorized&lt;/strong&gt;&lt;/em&gt; like mine, so they'll probably have to write the code from scratch to compete with my GPU performance). I had never heard of NumPy when I started writing FeynDyn, but my understanding is that it could be similar in performance &lt;strong&gt;but might not get the same GPU acceleration&lt;/strong&gt; (at least not nearly as easily!).&lt;/p&gt;&#xA;&lt;h3&gt;&lt;strong&gt;Closing thoughts:&lt;/strong&gt;&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If the fastest tensor propagation code for Feynman integrals is written in MATLAB, and beats the FORTRAN codes written by other world leaders in the field, then NumPy may also do reasonably well &lt;strong&gt;on CPUs&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;li&gt;This is because the tensor propagation algorithm (not too different from what happens in a tensor network code, in terms of core low-level arithmetic used) can be &lt;em&gt;&lt;strong&gt;vectorized&lt;/strong&gt;&lt;/em&gt; so that it can pretty much be done using &lt;em&gt;only&lt;/em&gt; BLAS functions that were written by people whose job was to make BLAS as fast as possible.&lt;/li&gt;&#xA;&lt;li&gt;As far as I know, Python (and Octave!) have not caught up to MATLAB in terms of &lt;em&gt;&lt;strong&gt;GPU computing&lt;/strong&gt;&lt;/em&gt;. It can be frustrating to work with MATLAB due to licensing issues and the amount of time it takes to load (it doesn't sound like the most important thing, but it's still a problem for me even in 2020). Nevertheless, even my present MSc student who was born in the mid-90s prefers MATLAB for some of the things we're doing.&lt;/li&gt;&#xA;&lt;li&gt;I am one of the most anti-Python people you'll meet, and when I first saw this question I immediately thought of pointing to the fact that all &amp;quot;serious&amp;quot; electronic structure codes use FORTRAN or C++, at least for the numerically expensive parts, but halfway through writing this answer I remembered the similarity between my tensor propagation code and tensor networks, and have come to the conclusion that &lt;strong&gt;NumPy is sufficient, but MATLAB is better for the GPU support and Julia might be the best thing in the middle.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-26T23:33:34.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1727" PostTypeId="1" AcceptedAnswerId="1729" CreationDate="2020-07-27T02:02:16.150" Score="10" ViewCount="576" Body="&lt;p&gt;I am trying to understand the Berry phase through the evolution of a system that evolves adiabatically.&lt;/p&gt;&#xA;&lt;p&gt;Schrodinger's equation is:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H(\lambda)|n(\lambda)\rangle=E_n|n(\lambda)\rangle \tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; labels the eigenstates. If &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; doesn't change with time, the wave function is:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\psi(t)=e^{-iE_nt/\hbar}|n\rangle \tag{2}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is slowly changing in time and if we approximated it as constant in each interval &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt;, the phase evolution would be:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\prod e^{-iE_n\Delta t/\hbar}=e^{-i\sum E_n(t)\Delta t/\hbar} \tag{3}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the continuum limit the sum turns into an integral, and we expect the phase evolution to be of the form &lt;span class=&quot;math-container&quot;&gt;$|\psi(t)\rangle=e^{-i\gamma(t)}|n(t)\rangle$&lt;/span&gt; with&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\gamma(t)=\frac{1}{\hbar}\int_{0}^{t} E_n(t')dt' \tag{4}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Questions&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How did they get equation number (2)?&lt;/li&gt;&#xA;&lt;li&gt;Where did the exponential come from?&lt;/li&gt;&#xA;&lt;li&gt;Why is the phase in equation (4) called a dynamic phase?&lt;/li&gt;&#xA;&lt;li&gt;What physical meaning does &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; have?&lt;/li&gt;&#xA;&lt;li&gt;What does &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; symbolize?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;: David Vanderbit - &amp;quot;Berry Phases in Electronic Structure Theory -  Electric Polarization, Orbital Magnetization and Topological Insulators&amp;quot; (2018, Cambridge University Press)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-07-27T02:25:16.860" LastActivityDate="2020-07-27T04:33:06.887" Title="Dynamic phase in an adiabatic system" Tags="|quantum-mechanics|berry-phase|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1728" PostTypeId="1" AcceptedAnswerId="1814" CreationDate="2020-07-27T02:30:59.693" Score="11" ViewCount="440" Body="&lt;p&gt;The image below refers to a phenomenon that occurs in TMDCs (transition metal dichalcogenides) monolayers that allowed the development of valleytronics. Why are there separate bands of different colors in this image (some with red on top and blue on the bottom and others with blue on top and red on the bottom)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dpFCX.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dpFCX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Figure is taken from:&lt;/strong&gt; &lt;a href=&quot;https://www.nature.com/articles/nchem.1589&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nature chemistry, 5(4):263–275, 2013&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="1218" LastEditDate="2021-03-20T07:06:36.997" LastActivityDate="2021-03-20T07:08:46.933" Title="Separation of valence bands in transition metal dichalcogenides (TMDs)" Tags="|band-structure|from-phys-se|materials-engineering|valleytronics|dichalcogenides|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1729" PostTypeId="2" ParentId="1727" CreationDate="2020-07-27T02:43:37.593" Score="9" Body="&lt;p&gt;The exponential comes from solving a linear differential equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\frac{\textrm{d}|\psi(t)\rangle}{\textrm{d}t} &amp;amp;= -\frac{\textrm{i}}{\hbar}H|\psi(t)\rangle\tag{1}\\&#xA;|\psi(t)\rangle &amp;amp;=e^{-\frac{\rm{i}}{\hbar}Ht}|\psi(t=0)\rangle\tag{2}\label{eq:matrixDynamics}.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now if you diagonalize &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; then instead of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; you have a matrix with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; diagonal entries: &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt;. The matrix exponential of a diagonal matrix is just the matrix of scalar exponentials of the diagonals, so &lt;span class=&quot;math-container&quot;&gt;$e^{-\frac{\rm{i}}{\hbar}Ht}$&lt;/span&gt; becomes the diagonal matrix with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; diagonal entries of &lt;span class=&quot;math-container&quot;&gt;$e^{-\frac{\rm{i}}{\hbar}E_nt}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now we can write the matrix equation of Eq. \eqref{eq:matrixDynamics} as &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; scalar equations which are exactly like your Eq. 2, except, are you possibly missing a subscript &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; for your &lt;span class=&quot;math-container&quot;&gt;$\psi(t)$&lt;/span&gt;? If not, maybe the textbook has a typo (most textbooks have several of them). Unless &lt;span class=&quot;math-container&quot;&gt;$|n\rangle$&lt;/span&gt; is the initial wavefunction at &lt;span class=&quot;math-container&quot;&gt;$t=0$&lt;/span&gt;, in which case I guess the equation is fine the way it is.&lt;/p&gt;&#xA;&lt;p&gt;I have answered  your questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How did they get equation number (2)?&lt;/li&gt;&#xA;&lt;li&gt;Where did the exponential come from?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But your next question seems to be about a different equation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Why is the phase in equation (4) called a dynamic phase?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I would guess it's called dynamic phase because it's a phase (exponent of a complex number) and it's dynamic (changing with respect to time). Jun has offered another possible explanation in his answer: they couldn't just call it the &amp;quot;phase&amp;quot; because they want to distinguish it from the Berry phase which is a geometric phase, so they called it something else, and since it's changing with time, I think it makes sense that they called it the &amp;quot;dynamic&amp;quot; phase.&lt;/p&gt;&#xA;&lt;p&gt;As for your last two questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What physical meaning does λ have?&lt;/li&gt;&#xA;&lt;li&gt;What does λ symbolize?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It's just a parameter of the Hamiltonian. &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1554/berrys-curvature-and-magnetic-moment-transition-metal-dichalcogenides#comment2498_1559&quot;&gt;Remember&lt;/a&gt; that in your other question we established that &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; can be &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; which is a nuclear coordinate, but ProfM used the wave-vector &lt;span class=&quot;math-container&quot;&gt;$\textbf{k}$&lt;/span&gt; instead, because he wanted to speak in the context of a Brillouin zone.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-27T03:12:32.710" LastActivityDate="2020-07-27T03:12:32.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1730" PostTypeId="2" ParentId="1727" CreationDate="2020-07-27T02:49:07.790" Score="7" Body="&lt;p&gt;Here are some basic comments:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I don't think you should call Eq(1) as the Schrödinger equation. It's just defining the energy eigen states/values, or in other words, establishing the relation of those with the Hamiltonian.&lt;/li&gt;&#xA;&lt;li&gt;The Schrödinger equation is &lt;span class=&quot;math-container&quot;&gt;$i\hbar\frac{d}{d t} |n(\lambda)\rangle = \hat{H}(\lambda)|n(\lambda)\rangle$&lt;/span&gt;, telling you how the quantum state evolves in time.&lt;/li&gt;&#xA;&lt;li&gt;So you can write down the solution in the form of Eq(2), since it's just a first-order differential equation. This is standard, and Nike has answered nicely in great detail.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It's tricky to answer your second question &amp;quot;why is the dynamical phase factor called so?&amp;quot; because after all, it's just a matter of history. But my understanding is that because the phase in Eq(4) shows up as a natural consequence of time evolution (i.e. dynamics). There's also the Berry phase (geometric phase) that comes from the geometry of the parameter space, so people had to name the phase of Eq(4) to distinguish it with the Berry/geometric phase, and well, I guess there simply was no better wording people came up with.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; can basically be any parameter of the Hamiltonian. The strength of the interaction, strength of a magnetic field, the strength of some potential energy... etc.&#xA;I think the easiest way to imagine things is to just think of it as the size of the box you're containing the particle or whatever. Having a box around your particle is basically the same as having a huge potential energy that surrounds your particle so the particle doesn't go outside. Then, changing the size of the box can be expressed in terms of changing the parameters of your potential energy function. Does &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; seem more intuitive now? Of course, this &amp;quot;box&amp;quot; is just one example, and &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; can be virtually any parameter in the Hamiltonian as long as you have the technology to control/change it in some way.&lt;/p&gt;&#xA;" OwnerUserId="379" LastEditorUserId="379" LastEditDate="2020-07-27T04:33:06.887" LastActivityDate="2020-07-27T04:33:06.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1731" PostTypeId="2" ParentId="1715" CreationDate="2020-07-27T03:39:56.280" Score="5" Body="&lt;p&gt;I have got your calculation successfully completed:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  The final electronic energy is        -0.928161992153724 a.u.    This &#xA;  computation required                          318.38 seconds (walltime).&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My output (and input) files are &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/1715&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. They are the same as yours, except my ZMAT uses &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/GENBAS&quot; rel=&quot;noreferrer&quot;&gt;my basis set database&lt;/a&gt;, which I don't think will make a difference for you, since your output file did not complain about the basis set. If you want to try what I did, just run &lt;code&gt;xcfour&lt;/code&gt; with my ZMAT file, and make sure you have my GENBAS file (hyperlinked above) in the same folder. Nothing else was different in my ZMAT.&lt;/p&gt;&#xA;&lt;p&gt;I ran the job like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export PATH=&lt;span class=&quot;math-container&quot;&gt;$PATH:/pool/nike/MRCC&#xA;export PATH=/pool/dattani/MRCC:$&lt;/span&gt;PATH&#xA;export PATH=&lt;span class=&quot;math-container&quot;&gt;$PATH:/pool/nike/cfour_v2.00beta/bin&#xA;export PATH=$&lt;/span&gt;PATH:/pool/dattani/cfour_v2.00beta/bin&#xA;&#xA;xclean&#xA;xcfour &amp;gt; out.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These are the possible reasons why your job failed:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You may want to run &lt;code&gt;xclean&lt;/code&gt; before running CFOUR.&lt;/li&gt;&#xA;&lt;li&gt;I'm using CFOUR v2.00 Beta, and you're using CFOUR v1.2&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-27T03:39:56.280" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1732" PostTypeId="1" CreationDate="2020-07-27T03:40:00.810" Score="8" ViewCount="350" Body="&lt;p&gt;I've been meaning to learn how to use DMRG (density matrix renormalization group) for a long time. Which packages have an easy learning curve? I specifically mean it should be easy to actually learn how to write your &lt;strong&gt;own&lt;/strong&gt; calculations that do nontrivial things, &lt;strong&gt;not&lt;/strong&gt; just run an example code that they provide.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I want to do calculations on spin systems or lattice bosons/fermions. Heisenberg or Hubbard-like models.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-06-22T00:20:45.100" LastActivityDate="2021-06-22T00:20:45.100" Title="What are some DMRG packages with an easy learning curve?" Tags="|one-topic-per-answer|software-recommendations|high-performance-computing|dmrg|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1733" PostTypeId="1" CreationDate="2020-07-27T05:07:30.680" Score="16" ViewCount="256" Body="&lt;p&gt;In the &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.041101&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; that introduced &amp;quot;Self-learning MC&amp;quot; (an ML-inspired MC technique, as I understand) the authors consider a many-body Ising model as an example to show the efficiency of their algorithm. The model looks like this:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;H= -J \sum_{\langle i,j\rangle} S_i S_j - K \sum_{ijkl\in p}S_iS_jS_k S_l \tag{1} ,&#xA;\end{equation}&lt;/span&gt;&#xA;where the second term runs for all plaquettes &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; on the square lattice.&lt;/p&gt;&#xA;&lt;p&gt;In the paper, I found an explanation that says &lt;em&gt;&amp;quot;For &lt;span class=&quot;math-container&quot;&gt;$K=0$&lt;/span&gt;,&#xA;this model reduces to the standard Ising model which can&#xA;be simulated efficiently by the Wolff method. However, for&#xA;&lt;span class=&quot;math-container&quot;&gt;$K\neq0$&lt;/span&gt;, no simple and efficient global update method is known.&amp;quot;&lt;/em&gt;&#xA;The Wolff algorithm &lt;strong&gt;can&lt;/strong&gt; be applied to this model, and they indeed compare the &amp;quot;naive Wolff algorithm&amp;quot; with the new self-learning MC. It seems that while the Wolff algorithm does speed up MC compared to local updates, it still has a very similar asymptotic suffering in relaxation (Fig 3 in the paper).&lt;/p&gt;&#xA;&lt;p&gt;My question is this:&#xA;Is there an intuitive way to understand &lt;em&gt;&lt;strong&gt;why&lt;/strong&gt;&lt;/em&gt; this slowing down happens in the Wolff algorithm? To me, it seems like it might work just fine as in the 2-body Ising model, because it's not that different (at least in terms of implementation).&lt;/p&gt;&#xA;" OwnerUserId="379" LastEditorUserId="5" LastEditDate="2021-11-30T20:40:35.093" LastActivityDate="2021-11-30T20:40:35.093" Title="Why does the Wolff algorithm slow down in a 4-body Ising model?" Tags="|ising-model|monte-carlo|solid-state-physics|k-local-hamiltonians|" AnswerCount="0" CommentCount="1" ClosedDate="2023-11-08T00:16:54.770" ContentLicense="CC BY-SA 4.0" />
  <row Id="1734" PostTypeId="1" CreationDate="2020-07-27T06:13:30.457" Score="8" ViewCount="64" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Bethe_lattice&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bethe lattice&lt;/a&gt; is exactly solvable in the limit where each lattice site has an infinite number of nearest-neighbors. In this limit it yields a semi-circular density of states in the conduction band. In which specific materials is it a good model for the electronic structure?&lt;/p&gt;&#xA;" OwnerUserId="215" LastEditorUserId="671" LastEditDate="2021-03-23T17:54:57.400" LastActivityDate="2021-03-23T17:54:57.400" Title="For which materials is the Bethe lattice a good model to compute the density of states of the conduction band?" Tags="|electronic-structure|model-hamiltonians|electron-correlation|" AnswerCount="0" CommentCount="3" ClosedDate="2021-06-22T14:04:50.500" ContentLicense="CC BY-SA 4.0" />
  <row Id="1735" PostTypeId="1" CreationDate="2020-07-27T06:28:12.847" Score="10" ViewCount="342" Body="&lt;p&gt;Prior to the discovery of graphene, the Mermin-Wagner theorem was used to argue that purely two-dimensional materials would not be stable as two-dimensional order would show logarithmic divergences at long range and fluctuations would spontaneously melt the crystal. Yet, graphene exists and it has very good mechanical properties. Are the predictions of the Mermin-Wagner theorem inapplicable in this case or are there still observable effects of the theorem at large scale?&lt;/p&gt;&#xA;" OwnerUserId="215" LastEditorUserId="792" LastEditDate="2020-07-27T08:30:38.293" LastActivityDate="2020-07-28T03:09:05.887" Title="Does the Mermin-Wagner theorem influence the stability of graphene?" Tags="|crystal-structure|graphene|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1736" PostTypeId="2" ParentId="1701" CreationDate="2020-07-27T07:42:08.720" Score="11" Body="&lt;p&gt;There is a whole zoo of topological phases, and hopefully someone will provide a more complete answer, but here are some thoughts.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Symmetry and dimension.&lt;/strong&gt; The topological classification of a material with a gap (topological insulator or topological superconductor) depends on (i) symmetry and (ii) dimension. These relations are summarized by the so-called tenfold way shown in this table (from this &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1367-2630/12/6/065010/meta&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QaL2W.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QaL2W.gif&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;Symmetry&amp;quot; columns correspond to time reversal symmetry (T), particle-hole symmetyry (C), and chiral symmetry (S), with &amp;quot;0&amp;quot; meaning no symmetry, &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\pm1$&lt;/span&gt;&amp;quot; is the square of the antiunitary operator of the symmetry. The &amp;quot;Dimension&amp;quot; columns correspond to the spatial dimension (1, 2, and 3 are most relevant for real systems, but some higher-dimensional synthetic systems have also been &lt;a href=&quot;https://www.nature.com/articles/s42254-019-0045-3&quot; rel=&quot;noreferrer&quot;&gt;explored&lt;/a&gt;). A well-known example are &lt;em&gt;time-reversal invariant topological insulators&lt;/em&gt; (what are typically called topological insulators), which obey time reversal symmetry (and for electrons T&lt;span class=&quot;math-container&quot;&gt;$^2=-1$&lt;/span&gt;) and fall into class AII. You will see this means that there is no topological classification for 1D, and both 2D and 3D have a &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; classification, as is well-known for these materials. Another example are &lt;em&gt;Chern insulators&lt;/em&gt;, which fall into class A and admit a &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}$&lt;/span&gt; classification in even dimensions only.&lt;/p&gt;&#xA;&lt;p&gt;So how do you figure what are the topological properties of your material? First you need to figure out what the relevant symmetries are and what the dimension is, so that you know where it falls in the tenfold way. For example for a &amp;quot;topological insulator&amp;quot; in 3D, the relevant symmetry is time-reversal symmetry and the dimension is obviously 3. Then, you need to figure out how to calculate the corresponding topological invariant, in this case &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt;. As Shahid Sattar described in their answer, in this case it can be done using a number of standard packages like &lt;a href=&quot;http://z2pack.ethz.ch&quot; rel=&quot;noreferrer&quot;&gt;Z2Pack&lt;/a&gt; or &lt;a href=&quot;http://www.wanniertools.com&quot; rel=&quot;noreferrer&quot;&gt;WannierTools&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Topological quantum chemistry.&lt;/strong&gt; Beyond the three symmetries described above, crystalline symmetries further constrain topological order. Additionally, semimetallic systems also admit a topological classification. The database that you refer to in your question uses the formalism known as &lt;em&gt;topological quantum chemistry&lt;/em&gt; to classify these phases. In short, it uses the symmetry of the various high-symmetry &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; points in the Brillouin zone to determine the degeneracies of the bands at those points, and then uses the symmetries along the paths connecting these points to determine the allowed connectivities of the bands. Each possible connectivity corresponds to a possible topological phase. Then depending on where the Fermi level is, one gets an insulating or a semimetallic phase.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.topologicalquantumchemistry.com/#/&quot; rel=&quot;noreferrer&quot;&gt;Topological Quantum Chemistry Database&lt;/a&gt; covers almost any material you may ever encounter, so they essentially have done the job for you. However, all their calculations are based on semilocal DFT, and this can be problematic (see for example this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.041109&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;). Therefore, I would use the database as a good starting point, but then do your own calculations to figure out what is really going on (e.g. using hybrid functionals or the &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt; approximation to get better estimates fo the bands).&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-27T07:42:08.720" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1737" PostTypeId="1" AcceptedAnswerId="1738" CreationDate="2020-07-27T08:40:49.893" Score="10" ViewCount="1233" Body="&lt;p&gt;The documentation for PySCF can be found here: &lt;a href=&quot;https://sunqm.github.io/pyscf/&quot; rel=&quot;noreferrer&quot;&gt;https://sunqm.github.io/pyscf/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, it does not explicitly state in the documentation what unit of energy is used.&#xA;Is there a way to find this out?&lt;/p&gt;&#xA;" OwnerDisplayName="user1024" LastEditorUserId="7" LastEditDate="2021-07-09T17:10:33.343" LastActivityDate="2021-07-09T17:10:33.343" Title="What unit of energy does PySCF use?" Tags="|pyscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1738" PostTypeId="2" ParentId="1737" CreationDate="2020-07-27T08:48:31.033" Score="10" Body="&lt;p&gt;Same as any other electronic structure code: &lt;a href=&quot;https://en.wikipedia.org/wiki/Hartree_atomic_units&quot; rel=&quot;noreferrer&quot;&gt;atomic units&lt;/a&gt; are used. The unit of energy is Hartree, &lt;span class=&quot;math-container&quot;&gt;$E_h$&lt;/span&gt;, in which the ground state energy of hydrogen is exactly &lt;span class=&quot;math-container&quot;&gt;$-0.5$&lt;/span&gt;. One Hartree is roughly 27.211 386 245 988 eV, see &lt;a href=&quot;https://physics.nist.gov/cgi-bin/cuu/Value?hrev&quot; rel=&quot;noreferrer&quot;&gt;the NIST database&lt;/a&gt;. The atomic unit for length is the Bohr radius, &lt;span class=&quot;math-container&quot;&gt;$a_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Defining things in terms of atomic units has the huge advantage that the results of a calculation don't depend on the numerical values of various conversion factors, e.g. Å to bohr in the input geometry conversion, and hartree to eV in the energy printout...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-07-27T16:38:06.413" LastActivityDate="2020-07-27T16:38:06.413" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1739" PostTypeId="1" CreationDate="2020-07-27T08:58:20.213" Score="9" ViewCount="92" Body="&lt;p&gt;iDMRG or infinite-size density matrix renormalization group, is a common technique in condensed matter. It seems that usually people believe that it reliably captures infinite-size behavior.  I have found plenty of resources describing &lt;strong&gt;how&lt;/strong&gt; it works (mathematically), but I want a &lt;strong&gt;heuristic/intuitive explanation&lt;/strong&gt; for how a system composed of effectively two sites (each with a large tensor) can capture physics that is occurring at all different length scales.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-11-30T20:34:00.603" LastActivityDate="2021-11-30T20:34:00.603" Title="How does infinite DMRG work?" Tags="|condensed-matter|dmrg|" AnswerCount="0" CommentCount="0" ClosedDate="2022-01-13T01:52:46.257" ContentLicense="CC BY-SA 4.0" />
  <row Id="1740" PostTypeId="2" ParentId="1697" CreationDate="2020-07-27T09:01:27.360" Score="10" Body="&lt;p&gt;Another good book that starts from the very beginning and it's very hands-on is &amp;quot;The art of molecular dynamics&amp;quot; by D. C. Rapaport. It is particularly useful if you want to code up a MD code yourself. This is something I always recommend, even if you want to go on and use one of the big MD packages out there, since you will learn the essentials and troubleshoot many of the classic issues that one encounters in MD simulations (setting the time step, coupling a thermostat/barostat, understanding how neighbour lists work, &lt;em&gt;etc.&lt;/em&gt;).&lt;/p&gt;&#xA;" OwnerUserId="674" LastActivityDate="2020-07-27T09:01:27.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1741" PostTypeId="1" CreationDate="2020-07-27T10:03:10.860" Score="10" ViewCount="128" Body="&lt;p&gt;Does it make any sense to calculate edge states for topological semimetals while they don't have any global gap?&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="792" LastEditDate="2020-07-28T07:51:16.003" LastActivityDate="2020-07-28T07:51:16.003" Title="Edge states in Topological Semimetals" Tags="|ab-initio-calculations|vasp|topological-insulators|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1742" PostTypeId="1" CreationDate="2020-07-27T11:03:48.370" Score="7" ViewCount="143" Body="&lt;p&gt;I wanted to understand the change in the Hamiltonian function as an unbiased simulation goes from one stable basin to the other.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Does the Hamiltonian stay constant or does it change as the &lt;strong&gt;unbiased&lt;/strong&gt; simulation proceeds (in timestep)?&lt;/li&gt;&#xA;&lt;li&gt;What determines this change?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-07-27T20:42:40.197" LastActivityDate="2020-07-27T20:42:40.197" Title="Does the Hamiltonian of an unbiased simulation change when the simulation moves from a stable basin to another?" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1743" PostTypeId="1" CreationDate="2020-07-27T11:25:00.807" Score="6" ViewCount="144" Body="&lt;p&gt;Is there any connection between charge density wave and band inversion? Or is there any system in which band inversion follows the same mechanism as the CDW? I am just trying to find a connection between them and I will really appreciate it if someone can help me.&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2020-08-27T16:15:42.463" LastActivityDate="2020-08-27T17:18:33.333" Title="Charge density wave and band inversion" Tags="|ab-initio-calculations|band-structure|solid-state-physics|charge-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1744" PostTypeId="2" ParentId="1742" CreationDate="2020-07-27T11:32:55.267" Score="7" Body="&lt;p&gt;This depends on your thermodynamic ensemble. If you are sampling from an &lt;span class=&quot;math-container&quot;&gt;$NVE$&lt;/span&gt; ensemble, the energy function will stay roughly constant (but in practice there will be a positive energy drift which on average increases linearly with respect to time, due to discretisation errors).&lt;/p&gt;&#xA;&lt;p&gt;In other more common ensembles, such as &lt;span class=&quot;math-container&quot;&gt;$NVT$&lt;/span&gt;, you sample from the relevant Boltzmann-like distribution, e.g. &lt;span class=&quot;math-container&quot;&gt;$\frac{e^{-\beta H(r,p)}}{Z_{NVT}}$&lt;/span&gt;, so yes, the values of the Hamiltonian will change as the simulation progresses, in order to sample from the appropriate distribution. The exact way these energies change over time largely depends on your thermostat (and barostat, if you are running in &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt;). With stochastic thermostats and barostats, you get a discontinuous change in energy over time, while the extended Lagrangian thermostats and barostats basically run &lt;span class=&quot;math-container&quot;&gt;$NVE$&lt;/span&gt; in an extended ensemble, so your energies will change continuously over time in this case. The exact form of that change needs to be derived uniquely for every combination of a thermostat and barostat.&lt;/p&gt;&#xA;&lt;p&gt;Of course, there are other practical factors which will affect your energy over time as well, such as cutoffs, switching functions and long-range summations of the electrostatics, but the effects of these on the energy change over time are largely unpredictable (and often discontinuous), to the best of my knowledge.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-07-27T11:32:55.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1745" PostTypeId="1" CreationDate="2020-07-27T12:03:05.870" Score="10" ViewCount="820" Body="&lt;p&gt;From &lt;a href=&quot;https://en.wikipedia.org/wiki/Superconductivity&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia&lt;/a&gt;, superconductivity is&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the set of physical properties observed in certain materials where electrical resistance vanishes and magnetic flux fields are expelled from the material. Any material exhibiting these properties is a superconductor.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;One of the conventional explanations is the &lt;a href=&quot;https://en.wikipedia.org/wiki/BCS_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;BCS theory&lt;/a&gt; (Bardeen–Cooper–Schrieffer theory) that dictates that the superconductivity is due to the condensation of electron pairs called &lt;a href=&quot;https://en.wikipedia.org/wiki/Cooper_pair&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cooper pairs&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's suppose I have a given material: &lt;strong&gt;is there a theoretical method or modeling tool that I could use to test if the material will behave as a superconductor?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="792" LastEditDate="2020-07-28T18:48:11.870" LastActivityDate="2020-07-28T18:50:47.910" Title="Methods for studying superconductivity?" Tags="|density-functional-theory|superconductivity|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1746" PostTypeId="1" AcceptedAnswerId="6371" CreationDate="2020-07-27T12:46:40.853" Score="12" ViewCount="171" Body="&lt;p&gt;Consider the following derivation in David Vanderbilt's book &amp;quot;&lt;a href=&quot;https://www.cambridge.org/core/books/berry-phases-in-electronic-structure-theory/DDD71CA4FE9AF5F3A2FB300E602F394A&quot; rel=&quot;nofollow noreferrer&quot;&gt;Berry Phases in Electronic Structure Theory - Electric Polarization, Orbital Magnetization and Topological Insulators&lt;/a&gt;&amp;quot; (2018, Cambridge University Press (page 100).&lt;/p&gt;&#xA;&lt;p&gt;The wave function for the adiabatic approach is as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;|\psi(t)\rangle=e^{i\phi(\lambda(t))}e^{-i\gamma(t)}|n(t)\rangle \tag{1}\label{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$e^{i\phi(\lambda(t))}$&lt;/span&gt; is the geometric phase or Berry phase and &lt;span class=&quot;math-container&quot;&gt;$e^{-i\gamma(t)}$&lt;/span&gt; is dynamic phase.&lt;/p&gt;&#xA;&lt;p&gt;Berry phase has the following mathematical expression:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\phi(t)=\int_{\lambda(0)}^{\lambda(t)}A_n(\lambda)d\lambda \tag{2}\label{2}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A_n$&lt;/span&gt; is Berry connection.&lt;/p&gt;&#xA;&lt;p&gt;Dynamic phase has the following mathematical expression:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\gamma(t)=\frac{1}{\hbar}\int_{0}^{t}E_n(t')dt' \tag{3}\label{3}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Expanding equation number (1) with first order &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; terms:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;|\psi(t)\rangle=e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\big[|n(\lambda)\rangle+\dot{\lambda}|\delta n(t)\rangle\big] \tag{4}\label{4}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Equation (4) solves the time-dependent Schrödinger equation to order zero in &lt;span class=&quot;math-container&quot;&gt;$\dot{\lambda}$&lt;/span&gt;, but we now require that it should also do so at first order.&lt;/p&gt;&#xA;&lt;p&gt;For this purpose we can discard terms that scale like &lt;span class=&quot;math-container&quot;&gt;$\ddot{\lambda}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\lambda^2$&lt;/span&gt;. You get:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;(E_n-H_{\lambda})|\delta n\rangle=-i\hbar (\partial_{\lambda}+iA_n)|n\rangle. \tag{5}\label{5}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which can also be written like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;(E_n-H_{\lambda})|\delta n\rangle=-i\hbar \mathcal{Q}_{n}|\partial_{\lambda}n\rangle \tag{6}\label{6}&#xA;\end{equation}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Q}_n=1-|n\rangle\langle n|$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How did they get equation (5) and (6) from equation (4)?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="7" LastEditDate="2021-07-13T15:27:55.420" LastActivityDate="2021-07-13T15:32:35.110" Title="Adiabatic equation related to the Berry phase for lambda with first order terms" Tags="|mathematical-modeling|quantum-mechanics|berry-phase|derivations|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1747" PostTypeId="1" AcceptedAnswerId="1832" CreationDate="2020-07-27T13:12:49.720" Score="8" ViewCount="134" Body="&lt;p&gt;I have been studying about &lt;a href=&quot;https://en.wikipedia.org/wiki/Metamaterial&quot; rel=&quot;noreferrer&quot;&gt;metamaterials&lt;/a&gt; and their amazing abilities to interact with EM Waves.&lt;br /&gt;&#xA;I came across a concept called Metamaterial cloaking (something like Harry Potter's invisible cloak kinda material). I also know that most of them are based on artificial structures called &lt;a href=&quot;https://en.wikipedia.org/wiki/Split-ring_resonator&quot; rel=&quot;noreferrer&quot;&gt;Split Ring Resonators&lt;/a&gt;.&lt;br /&gt;&#xA;There have been some research works using &lt;a href=&quot;https://www.comsol.co.in/&quot; rel=&quot;noreferrer&quot;&gt;COMSOL&lt;/a&gt; for &lt;a href=&quot;https://www.comsol.com/paper/comsol-multiphysics-in-plasmonics-and-metamaterials-12481&quot; rel=&quot;noreferrer&quot;&gt;metamaterial modelling&lt;/a&gt; but I would like to know what are some better software programs that could be used to computationally study and research about metamaterials?&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="5" LastEditDate="2020-07-28T21:07:41.513" LastActivityDate="2020-07-28T23:11:39.977" Title="Which software programs can be used to study SRR (split ring resonator) based meta-material and its cloaking properties" Tags="|software|metamaterials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1748" PostTypeId="1" CreationDate="2020-07-27T13:15:58.170" Score="10" ViewCount="817" Body="&lt;p&gt;Electronic transport calculations play an important role in device simulation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What tools can do electronic transport calculation?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am familiar with &lt;a href=&quot;https://departments.icmab.es/leem/siesta/About/overview.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TranSIESTA&lt;/a&gt; (a module of &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SIESTA&lt;/a&gt; program) and &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk/resources/feature-list.html#negf&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumATK&lt;/a&gt;, (but please feel free to add those as answers to make a complete recommendation list).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="52" LastEditDate="2020-08-17T20:39:21.057" LastActivityDate="2020-10-06T03:21:14.527" Title="Tools for electronic transport calculations" Tags="|one-topic-per-answer|transport|software-recommendations|electronic-transport|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1749" PostTypeId="1" CreationDate="2020-07-27T13:29:05.747" Score="10" ViewCount="275" Body="&lt;p&gt;Both software I know that do electronic transport calculations (&lt;a href=&quot;https://departments.icmab.es/leem/siesta/About/overview.html&quot; rel=&quot;noreferrer&quot;&gt;TranSIESTA&lt;/a&gt; and &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk/resources/feature-list.html#negf&quot; rel=&quot;noreferrer&quot;&gt;QuantumATK&lt;/a&gt;) , use Non-equilibrium Green's function (NEGF) method.&lt;/p&gt;&#xA;&lt;p&gt;Are there other theoretical methods that can be used to calculate electronic transport properties?&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-17T07:08:54.977" Title="Theories for electronic transport calculations" Tags="|siesta|electronic-transport|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1750" PostTypeId="2" ParentId="1693" CreationDate="2020-07-27T14:04:09.040" Score="9" Body="&lt;p&gt;I would argue that you can use a package like &lt;a href=&quot;https://g1257.github.io/dmrgPlusPlus/index.html&quot; rel=&quot;noreferrer&quot;&gt;DMRG++&lt;/a&gt;, which is written in C++, without knowing much C/C++ or indeed any language. It has its own input format that takes some getting used to (unfortunately it isn't overly well documented), but the outputs are provided in text and hdf5 formats that you can then manipulate with your favorite scripting language - e.g. python. Yet all heavy lifting, so to speak, is done by the provided C++ code. Unless you need to modify or troubleshoot that code, perhaps to add a non-standard model, you can definitively avoid messing with C++. Also, the code is actively maintained so even in such cases it might be possible to avoid messing with C++ yourself.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-27T14:04:09.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1751" PostTypeId="2" ParentId="1748" CreationDate="2020-07-27T14:44:28.900" Score="7" Body="&lt;h3&gt;Nanodcal&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.nanoacademic.ca:8080/showArticle.jsp?id=17&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nanodcal&lt;/a&gt; is implemented with real space density functional theory (DFT) using the Keldysh nonequilibrium Green’s function formalism (NEGF). It can calculate nonlinear and non-equilibrium quantum transport properties of two-probe open device structures. The software uses linear combination of atomic orbitals (LCAO) to expand physical quantities and atomic cores are defined by norm conserving nonlocal pseudopotentials.&#xA;It is implemented using MATLAB and computationally intensive parts uses C. A free license allows nanodcal to run on multicore single CPU. For more efficient work, parallel license is required. You can download the free version &lt;a href=&quot;http://www.hzwtech.com/software-product/16.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.nanoacademic.ca:8080/showArticle.jsp?id=21&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Nanobuild:&lt;/strong&gt;&lt;/a&gt; is a graphics tool that can be used with Nanodcal for building multi-probe atomic structures&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-08-17T13:42:31.583" LastActivityDate="2020-08-17T13:42:31.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1752" PostTypeId="1" CreationDate="2020-07-27T15:26:33.540" Score="9" ViewCount="52" Body="&lt;p&gt;There are three (at least that I'm aware of) commonly used approaches to obtain linear response properties (e.g electric polarizability, optical rotation, NMR shielding tensors)&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Sum over states&lt;/strong&gt;: The properties can formally be written as a sum of matrix elements of the perturbations &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; over all excited states. In practice, compute enough excited states to converge the property. Tends to converge slowly with the number of states.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Response functions&lt;/strong&gt;: The properties can also be written in terms of response relations, which leads us instead to compute the perturbed density with respect to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;) and contract it with &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;) to compute the property.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Derivatives&lt;/strong&gt;: These properties are also derivatives of the energy with respect to these perturbations. One can derive analytic formulas or compute numerical derivatives. Analytical formulas are complex and don't (directly) apply to frequency dependent properties. Numerical derivatives require repeated calculations and tuning the step size.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For optical rotation, and I believe most other linear properties, the second approach above has won out as the best way to do the computation in general. But I'm curious if this holds for computing nonlinear properties (e.g. &lt;span class=&quot;math-container&quot;&gt;$n^{\text{th}}$&lt;/span&gt; hyperpolarizability, &lt;a href=&quot;https://en.wikipedia.org/wiki/Kerr_effect&quot; rel=&quot;noreferrer&quot;&gt;the Kerr Effect&lt;/a&gt;) as well or whether the cost/benefit analysis of these methods changes.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-27T16:47:57.830" Title="Approach for Higher Order Response Properties" Tags="|electronic-structure|spectroscopy|response-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1753" PostTypeId="2" ParentId="1745" CreationDate="2020-07-27T16:31:19.330" Score="11" Body="&lt;p&gt;It is possible to calculate the superconducting critical temperature &lt;span class=&quot;math-container&quot;&gt;$T_{\mathrm{c}}$&lt;/span&gt; of &lt;em&gt;phonon-mediated superconductors&lt;/em&gt; using first principles modelling methods. However, the calculations are not trivial.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Theory.&lt;/strong&gt; The basic quantity that goes into the calculation is the electron-phonon matrix element:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;g(\mathbf{k},n;\mathbf{k}',n';\mathbf{q},\nu)=\left\langle\mathbf{k}n\left|\frac{\partial V}{\partial u_{\mathbf{q}\nu}}\right|\mathbf{k}'n'\right\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This represents the scattering from an initial electron state &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{k}',n')$&lt;/span&gt; to a final electron state &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{k},n)$&lt;/span&gt; mediated by a phonon &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt;, where the electron-phonon interaction is the change in the potential &lt;span class=&quot;math-container&quot;&gt;$\delta V$&lt;/span&gt; due to the presence of a phonon of amplitude &lt;span class=&quot;math-container&quot;&gt;$\delta u_{\mathbf{q}\nu}$&lt;/span&gt;. Once you have this matrix element, everything follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;First, you realise that the electrons that contribute to&#xA;superconductivity are those around the Fermi energy&#xA;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{\mathrm{F}}$&lt;/span&gt;, so that you calculate the average of the&#xA;electron-phonon coupling matrix element for a phonon&#xA;&lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt; over the Fermi surface:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle\langle|g_{\mathbf{q}\nu}|^2\rangle\rangle=\frac{\frac{1}{N_{\mathbf{k}}}\sum_{\mathbf{k},n}\frac{1}{N_{\mathbf{k}'}}\sum_{\mathbf{k}',n'}\delta(\epsilon_{\mathbf{k}n}-\epsilon_{\mathrm{F}})\delta(\epsilon_{\mathbf{k}'n'}-\epsilon_{\mathrm{F}})|g(\mathbf{k},n;\mathbf{k}',n';\mathbf{q},\nu)|^2}{\left[\frac{1}{N_{\mathbf{k}}}\sum_{\mathbf{k},n}\delta(\epsilon_{\mathbf{k}n}-\epsilon_{\mathrm{F}})\right]^2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The sums run over a grid of &lt;span class=&quot;math-container&quot;&gt;$N_{\mathbf{k}}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points and&#xA;the delta functions select only those electrons whose energies are&#xA;near the Fermi energy. In this expression I have directly written&#xA;the sums over a discrete set of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points (rather than the&#xA;integrals that one gets from the analytical theory) to prepare for&#xA;the discussion of the numerics below.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;One then usually defines the so-called electron-phonon coupling&#xA;constant of phonon mode &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt; as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lambda_{\mathbf{q}\nu}=\frac{2N(\varepsilon_{\mathrm{F}})}{\omega_{\mathbf{q}\nu}}\langle\langle|g_{\mathbf{q}\nu}|^2\rangle\rangle,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N(\varepsilon_{\mathrm{F}})$&lt;/span&gt; is the density of states at the&#xA;Fermi level and &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; is the phonon frequency.&#xA;The total electron-phonon coupling constant is then obtained by&#xA;summing (integrating) over the phonon Brillouin zone:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lambda=\frac{1}{N_{\mathbf{q}}}\sum_{\mathbf{q},\nu}\lambda_{\mathbf{q}\nu}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You can then calculate the superconducting critical temperature,&#xA;with methods ranging from the semiempirical &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.167.331&quot; rel=&quot;noreferrer&quot;&gt;McMillan formula&lt;/a&gt; to&#xA;the Green's function based &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.024505&quot; rel=&quot;noreferrer&quot;&gt;Migdal-Eliashberg formalism&lt;/a&gt;. In any case,&#xA;the basic quantity is still the electron-phonon matrix element&#xA;above.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Practical calculations.&lt;/strong&gt; The basic matrix element &lt;span class=&quot;math-container&quot;&gt;$g(\mathbf{k},n;\mathbf{k}',n';\mathbf{q},\nu)$&lt;/span&gt; can be calculated relatively easily within density functional theory, either using finite differences or linear response, and codes that implement this include &lt;a href=&quot;https://www.quantum-espresso.org&quot; rel=&quot;noreferrer&quot;&gt;Quantum Espresso&lt;/a&gt; and &lt;a href=&quot;https://www.abinit.org&quot; rel=&quot;noreferrer&quot;&gt;Abinit&lt;/a&gt;. The major challenge of these calculations comes from the double sum over the electronic Brillouin zone (sums over &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}'$&lt;/span&gt;) and the sum over the phonon Brillouin zone (sum over &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;). These sums converge very slowly, so &lt;em&gt;many&lt;/em&gt; terms need to be included. It is often the case that the number of terms needed is impossibly large for a direct treatment, so what is typically done is to calculate the electron-phonon matrix elements on a coarse grid of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; points, and then some interpolation method is used to obtain these terms on finer grids. Perhaps the most-used approach to this is Wannier interpolation, as implemented in the &lt;a href=&quot;https://epw-code.org&quot; rel=&quot;noreferrer&quot;&gt;EPW code&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Other comments.&lt;/strong&gt; (i) The approach described above is possibly the most extensively used approach to calculate &lt;span class=&quot;math-container&quot;&gt;$T_{\mathrm{c}}$&lt;/span&gt; using first principles methods, and it leads to reasonable values for most phonon-mediated superconductors. There are alternative approaches to perform these calcualtions, such as so-called density functional theory for superconductors (SCDFT), but I don't know enough about it to write an answer. Hopefully someone more knowledgeable will. (ii) I don't think it is possible to study superconductors that are &lt;em&gt;not&lt;/em&gt; phonon-mediated using first principles methods, but I would be happy to learn more if someone knows better.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-27T16:31:19.330" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1754" PostTypeId="2" ParentId="1752" CreationDate="2020-07-27T16:47:57.830" Score="1" Body="&lt;p&gt;Options 2 and 3 appear to be the same: the response is almost always the response of the energy, since the wave function is determined by the energy principle.&lt;/p&gt;&#xA;&lt;p&gt;To clarify: in many methods (e.g. Hartree-Fock or CC) one computes the derivative of the energy functional with respect to the property (e.g. polarizability or NMR shielding constants); this turns out to lead to (generalized) response densities that you need to solve from the Schrödinger equation, and at the end you get your property by contracting the densities.&lt;/p&gt;&#xA;&lt;p&gt;There may also be several ways in which to choose your perturbation, e.g. for NMR shielding constants your variables are the external magnetic field and the nuclear shieldings. I forget the details, but the idea is this: you can first perturb with the shieldings, and then contract with the magnetic field response, but this obviously becomes horribly slow for many nuclei. Instead, you can first perturb with the magnetic field, solving the response equations for the 3 components of the field, after which you can get the shieldings just by contracting the fixed response to the external field with the relevant matrices for the individual nuclei; this approach scales to large numbers of atoms.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-27T16:47:57.830" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1755" PostTypeId="1" CreationDate="2020-07-27T16:52:12.990" Score="8" ViewCount="93" Body="&lt;p&gt;If we have a (classical) computer about the size of a room and if its computational power is only limited by &lt;a href=&quot;https://www.nature.com/articles/nature13570&quot; rel=&quot;noreferrer&quot;&gt;fundamental limits to computation&lt;/a&gt;, &lt;strong&gt;what is the largest system we can study using different approximations/methods in a reasonable amount of time&lt;/strong&gt;?&lt;/p&gt;&#xA;&lt;p&gt;The question is out of curiosity and hence we need some assumptions. Please be free to edit the question if the following asssumptions are not reasonable or if we need more assumptions.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Size of the room is 5m x 5m&lt;/li&gt;&#xA;&lt;li&gt;Reasonable time = 1 month&lt;/li&gt;&#xA;&lt;li&gt;Property to be calculated = ground state energy of the system&lt;/li&gt;&#xA;&lt;li&gt;Accuracy - milli-Hartree&lt;/li&gt;&#xA;&lt;li&gt;Type of the system - Alkenes of length &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-07-27T18:38:49.700" LastActivityDate="2020-07-27T18:38:49.700" Title="What's the largest system we can study based on &quot;fundamental limits to computation&quot;?" Tags="|high-performance-computing|" AnswerCount="0" CommentCount="2" ClosedDate="2020-12-31T04:59:46.823" ContentLicense="CC BY-SA 4.0" />
  <row Id="1756" PostTypeId="2" ParentId="1644" CreationDate="2020-07-27T17:03:08.647" Score="3" Body="&lt;p&gt;Someone else can probably answer this in more detail, but most software packages allow for simulated spectra to be calculated just as you have said (not just the excitations).  You can probably take the spectra and treat it the same as your experimental spectra.&lt;/p&gt;&#xA;&lt;p&gt;At the very least, I was able to find a recent paper that appears to have done exactly just that.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.scielo.br/scielo.php?script=sci_arttext&amp;amp;pid=S0103-50532020000300613&amp;amp;lng=en&amp;amp;nrm=iso&quot; rel=&quot;nofollow noreferrer&quot;&gt;TD-DFT Analysis of the Dissymmetry Factor in Camphor&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-27T17:03:08.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1757" PostTypeId="2" ParentId="1699" CreationDate="2020-07-27T17:12:36.930" Score="12" Body="&lt;p&gt;&lt;strong&gt;Theory.&lt;/strong&gt; The Rashba effect can be described with a 2-band model:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}=\frac{\hbar^2}{2m}(k_x^2+k_y^2)\mathbb{1}_2+\alpha_{\mathrm{R}}(\sigma_1 k_y-\sigma_2 k_x),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\alpha_{\mathrm{R}}$&lt;/span&gt; is the Rashba parameter and all other terms have their usual meanings. Diagonalizing this Hamiltonian gives the energy dispersion:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{\pm}=\frac{\hbar^2}{2m}(k_x^2+k_y^2)\pm\alpha_{\mathrm{R}}\sqrt{k_x^2+k_y^2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first term is the usual quadratic dispersion of electron bands, which is independent of the Rashba parameter, whereas the second term splits these bands to lead to the characteristic shape of Rashba bands:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5ygb3.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5ygb3.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As the Rashba Hamiltonian is isotropic in &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; can be any direction in that plane.&lt;/p&gt;&#xA;&lt;p&gt;When you diagonalize the Hamiltonian you also obtain the corresponding wave functions, which are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\psi_{\pm}(\mathbf{k})\rangle\propto\begin{pmatrix}&#xA;1 \\ \mp ie^{i\phi}&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;in circular coordinates where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}=k(\cos\phi,\sin\phi,0)$&lt;/span&gt;. You can then calculate the spin texture associated with these states by calculating the expectation value of the vector of Pauli matrices:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \psi_{\pm}(\mathbf{k})|\sigma|\psi_{\pm}(\mathbf{k})\rangle=&#xA;\begin{pmatrix}&#xA;\pm\sin\phi \\&#xA;\pm\cos\phi &#xA;\end{pmatrix}. \label{eq:spin}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;At an energy below the crossing point of the bands you get this spin texture:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WYoyu.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WYoyu.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the right diagram, the red and blue arrows represent the &amp;quot;spin&amp;quot; direction at that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point of the circular projections of the bands at constant energy &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;. And at an energy above the crossing point you get this spin texture:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wuCkM.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wuCkM.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Your question.&lt;/strong&gt; So how do you verify the presence of the Rashba effect from band structure calculations? Essentially, you will have the Rashba effect at a band edge if you can describe the band energies according to the equation for &lt;span class=&quot;math-container&quot;&gt;$E_{\pm}$&lt;/span&gt; above, and the spin texture according to corresponding equation above. No realistic material will &lt;em&gt;exactly&lt;/em&gt; match those expressions (for example because the Rashba Hamiltonian is isotropic in the &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt; plane), but if the bands are close enough, then the system is said to exhibit the Rasbha effect. I should add that the term &amp;quot;Rashba effect&amp;quot; is used very generously, so even when the band energies and spin textures deviate significantly from those of the Rashba Hamiltonian, people may describe them as Rashba bands.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-27T17:12:36.930" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1758" PostTypeId="2" ParentId="139" CreationDate="2020-07-27T17:30:18.027" Score="8" Body="&lt;p&gt;I felt that it's important to note that &lt;strong&gt;not all universality classes are determined solely by spacial dimension and symmetry&lt;/strong&gt;, even when the interactions are local.&lt;/p&gt;&#xA;&lt;p&gt;The easiest model that exemplifies this is probably the Ashkin-Teller model in 2D. It has a continuously varying (thus infinite variety of) critical exponents (universality classes) depending on the value of the parameter in the Hamiltonian. The symmetry does not change for different values of the parameter, so this is a counter example to the often made claim that universality classes are determined only by dimensionality and symmetry.&#xA;The critical exponent values written in the wikipedia chart with &amp;quot;Ashkin-Teller&amp;quot; only corresponds to ONE point of this continuum of criticalities.&lt;/p&gt;&#xA;&lt;p&gt;Of course, this kind of examples are rare, and &lt;em&gt;usually&lt;/em&gt; universality classes could indeed be predicted from the spacial dimension and the symmetry. But I think it's important to realize that the claim is not a rigorously proven theorem, but is more like a guideline.&#xA;There are even recent works on trying to find a non-Ising &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; symmetry breaking universality class (&lt;a href=&quot;https://arxiv.org/abs/1803.00578&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1803.00578&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Also, to add to the list, I think the cubic-anisotropic Heisenberg universality class is one that is easy to be mistaken with the normal isotropic Heisenberg universality class. The critical exponents are close anyway, and it's actually hard to numerically distinguish them, but RG calculations say that the anisotropy perturbation is relevant, meaning that it flows to a separate fixed point.&lt;/p&gt;&#xA;" OwnerUserId="379" LastActivityDate="2020-07-27T17:30:18.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1759" PostTypeId="2" ParentId="1735" CreationDate="2020-07-27T17:54:28.543" Score="6" Body="&lt;p&gt;This &lt;a href=&quot;https://physics.stackexchange.com/q/478518/134583&quot;&gt;Physics Stack Exchange thread&lt;/a&gt; answers this question very well.&lt;/p&gt;&#xA;&lt;p&gt;Apparently, the length scale of such &amp;quot;logarithmic divergence&amp;quot; is actually merely in the order of atomic distances even if the entire graphene sheet is as large as the solar system!&#xA;So practically, the results of the theorem is irrelevant to the real-world graphene, even though mathematically the theorem is perfectly applicable to graphene. (Note: Sometimes the MW theorem is misunderstood to be prohibiting ANY continuous symmetry breaking in 2D short-ranged systems, even though this is not true: &amp;quot;hexatic&amp;quot; order in 2D hard sphere systems is a good example for this).&lt;/p&gt;&#xA;&lt;p&gt;This is so cool because it essentially challenges our belief in the &amp;quot;thermodynamic limit&amp;quot; as a good approximation of macroscopic substances!&lt;/p&gt;&#xA;" OwnerUserId="379" LastEditorUserId="379" LastEditDate="2020-07-28T03:09:05.887" LastActivityDate="2020-07-28T03:09:05.887" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1760" PostTypeId="1" CreationDate="2020-07-27T18:05:15.210" Score="4" ViewCount="276" Body="&lt;p&gt;I am interested in studying material heat transport using Density Functional Theory. Searching, I found a work&lt;sup&gt;1&lt;/sup&gt; about using &lt;em&gt;ab initio&lt;/em&gt; equilibrium molecular dynamics (AIMD) as implemented in &lt;a href=&quot;http://quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;QuantumEspresso&lt;/a&gt; (QE) software.&lt;/p&gt;&#xA;&lt;p&gt;I already used/tested QE for other simpler calculations and I found it &lt;em&gt;very hungry&lt;/em&gt; about hardware resources (RAM memory and hard disk space).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there other codes capable to do DFT quantum simulation of atomic heat transport?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A. Marcolongo, P. Umari and S. Baroni. Microscopic theory and quantum simulation of atomic heat transport. Nature Phys 12, 80–84 (2016) (DOI: &lt;a href=&quot;http://dx.doi.org/10.1038/nphys3509&quot; rel=&quot;noreferrer&quot;&gt;10.1038/nphys3509&lt;/a&gt;) (preprint &lt;a href=&quot;https://arxiv.org/abs/1503.04188&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-09-11T03:17:54.750" Title="DFT code for quantum simulation of atomic heat transport" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1761" PostTypeId="1" CreationDate="2020-07-27T18:11:41.130" Score="11" ViewCount="159" Body="&lt;p&gt;I would like to model the diffusion of various small molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{MeOH}$&lt;/span&gt;, etc.) through polymeric barrier material (e.g. polyethylene, ethylene vinyl alcohol, polyethylene terephthalate, etc.) in order to predict their transmission rates. I am initially looking for rough estimates to differentiate between classes of barrier materials, but would like to eventually be able to determine how small modifications of the polymers can affect their barrier properties.&lt;/p&gt;&#xA;&lt;p&gt;Is this possible? If so, what codes and methods would be useful, and what should I read to get started?&lt;/p&gt;&#xA;" OwnerUserId="695" LastEditorUserId="695" LastEditDate="2020-07-28T14:10:38.917" LastActivityDate="2020-07-29T20:00:12.497" Title="Modelling Diffusion of Molecules Through a Physical Barrier" Tags="|molecular-dynamics|molecular-modeling|polymers|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1762" PostTypeId="2" ParentId="1523" CreationDate="2020-07-27T18:24:31.137" Score="8" Body="&lt;h1&gt;2nd Generation CPMD&lt;/h1&gt;&#xA;&lt;p&gt;Car-Parrinello MD avoids repeatedly solving the electronic problem by propagating the orbitals as if they were particles governed by Newton's equations. This is much more efficient than having to solve at each time step as is done in Born-Oppenheimer MD, though at the cost of decreasing the maximum timestep for the dynamics (too large a step will lose the ground state), slightly reduced accuracy (not exactly at the ground state for each time step) and introducing a spurious &amp;quot;mass parameter&amp;quot; to describe the electronic motion.&lt;/p&gt;&#xA;&lt;p&gt;To address these problems, Thomas Kuhne et al. developed the &amp;quot;Car-Parrinello like approach to BOMD&amp;quot;, also referred to as second-generation CPMD. The key differences of this approach are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Rather than propagating the orbitals (or rather the MO coefficients &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt;), 2nd-CPMD propagates the density &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P}$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$\mathbf{PS}$&lt;/span&gt; for nonorthogonal orbitals). The density seems to evolve more smoothly than the coefficients, making it easier to work with.&lt;/li&gt;&#xA;&lt;li&gt;A predictor-corrector method (in their paper, the Always Stable Predictor Corrector (ASPC) method, but in principle any such method) is used to propagate the density. This generates a prediction of the next coefficients &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}^p(t_n)$&lt;/span&gt; based on the previous &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; density matrices. A corrected set of coefficients &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}(t_n)$&lt;/span&gt; is then formed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{C}(t_n)=\omega \text{MIN}[\mathbf{C}^p(t_n)]+(1-\omega)\mathbf{C}^p(t_n)$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\omega=\frac{K}{2K-1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\text{MIN}$&lt;/span&gt; is a minimization and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is a parameter which determines the accuracy &lt;span class=&quot;math-container&quot;&gt;$O(\Delta t^{2K-2})$&lt;/span&gt;. This update procedure eliminates the need for the mass parameter.&lt;/li&gt;&#xA;&lt;li&gt;The nuclear dynamics become dissipative, possibly due to the nonsymplectic electron dynamics. This is corrected by performing a short validation run of dynamics to compute a damping coefficient &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; for the system.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are some finer details to make this scheme work (specific parameterization of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt;, how &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; is obtained) which are available in the original papers (both of which have arXiv preprint versions available).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;CP2K&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Thomas D. Kühne, Matthias Krack, Fawzi R. Mohamed, and Michele Parrinello Phys. Rev. Lett. 98, 066401 DOI: 10.1103/PhysRevLett.98.066401&lt;/li&gt;&#xA;&lt;li&gt;Kühne, T.D. (2014), Second generation Car–Parrinello molecular dynamics. WIREs Comput Mol Sci, 4: 391-406. DOI: 10.1002/wcms.1176&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-31T22:31:52.793" LastActivityDate="2020-07-31T22:31:52.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1763" PostTypeId="1" CreationDate="2020-07-27T19:03:05.877" Score="8" ViewCount="73" Body="&lt;p&gt;I am trying to understand the symmetry elements of space group number 194 (P&lt;span class=&quot;math-container&quot;&gt;$6_3$&lt;/span&gt;/mmc), which is hexagonal and has 24 symmetry operations.&lt;/p&gt;&#xA;&lt;p&gt;In the table of symmetry operations it says that it has three glide planes, which I marked in the figure (see blue rectangles). However, more than three glide planes are represented in the figure, since there are more dashed, dashed-dotted and dotted lines than those lines which are represented in the rectangles. Why do more glide planes appear than those three on the table of symmetry operations?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MlG4U.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MlG4U.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FEA1U.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FEA1U.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Images taken from International Tables of Crystallography)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-08-30T21:51:05.467" LastActivityDate="2020-08-30T21:51:05.467" Title="Symmetry of glide planes" Tags="|condensed-matter|symmetry|from-phys-se|crystallography|space-groups|" AnswerCount="0" CommentCount="2" ClosedDate="2020-12-31T04:59:16.577" ContentLicense="CC BY-SA 4.0" />
  <row Id="1764" PostTypeId="1" AcceptedAnswerId="1767" CreationDate="2020-07-27T19:08:31.780" Score="11" ViewCount="699" Body="&lt;p&gt;I'm trying to get the fractional coordinates for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mo}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2-2H}$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2-2H}$&lt;/span&gt;, where 2H is the phase. &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2-2H}$&lt;/span&gt; is a bilayer, in which each layer is separated from each other by Van der Waals forces. The &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2-2H}$&lt;/span&gt; belongs to the &lt;a href=&quot;https://i.stack.imgur.com/GBvWP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;space group 194&lt;/a&gt; (&lt;a href=&quot;https://i.stack.imgur.com/UuBOo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;table continued&lt;/a&gt;, from International Tables of Crystallography pages 600 and 601) and is hexagonal.&lt;/p&gt;&#xA;&lt;p&gt;As the unit cell contains two layers of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2}$&lt;/span&gt;, I believe that to find the fractional coordinates of each element, I need &lt;span class=&quot;math-container&quot;&gt;$\ce{Mo}$&lt;/span&gt;to be in a Wyckoff position with multiplicity 2 and &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt; to be in a Wyckoff position with multiplicity 4. The problem is that there are several positions with this type of multiplicity (2a, 2b, 2c and 2d for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mo}$&lt;/span&gt;; 4e and 4f for &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt;), but the crystal tends to acquire the most stable Wyckoff positions. How can I know which Wyckoff positions for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mo}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt; make the crystal stable?&lt;/p&gt;&#xA;&lt;p&gt;I a passage in [1] that says it is necessary to calculate the bond length for each of the combinations. Once the bond length is calculated, how do I know which combination for Mo and S is most stable?&lt;/p&gt;&#xA;&lt;h4&gt;References:&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Newnham, R. E. &lt;a href=&quot;https://doi.org/10.1007/978-3-642-50017-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structure-Property Relations.&lt;/a&gt; &lt;strong&gt;1975&lt;/strong&gt;. DOI: 10.1007/978-3-642-50017-6.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="7" LastEditDate="2022-02-17T20:09:49.930" LastActivityDate="2022-02-17T20:09:49.930" Title="Get fractional coordinates from special Wyckoff positions" Tags="|symmetry|from-chem-se|molecular-interactions|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1765" PostTypeId="1" CreationDate="2020-07-27T19:18:00.483" Score="7" ViewCount="722" Body="&lt;p&gt;I'm doing my calculations using G09W. My OS is Windows 7 (64-bit). This error occurs in the frequency calculation. What's even weirder is that it seems to happen right after everything is already calculated (all the energies and corrections). But the output file doesn't contain the fragment that should say that all 4 convergence criteria are satisfied and that a stationary point is located.&lt;/p&gt;&#xA;&lt;p&gt;It reads 'Error on Z-matrix line number      3:  angle Alpha is outside the valid range of 0 to 180. Conversion from Z-matrix to cartesian coordinates failed:'&lt;/p&gt;&#xA;&lt;p&gt;Apparently, Gaussian doesn't deal well with linear fragments and this molecule is linear. That is generally known. But how do I fix this? I can't really use the results obtained untill the error is dealt with, can I?&lt;/p&gt;&#xA;&lt;p&gt;My input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=4    &#xA;%mem=1400MB&#xA;%chk=D:\!HNGH\aug-cc-pwCVTZ\CCSDT XeH2 freq.chk    &#xA;#p freq=noraman rccsd(t)/genecp maxdisk=15900MB&#xA;Title Card Required&#xA;&#xA;0 1&#xA;Xe&#xA;H   1   R12&#xA;H   1   R13           2   A213&#xA;R12           =        1.92821600&#xA;R13           =        1.92934900&#xA;A213          =        180.00000000&#xA;Xe     0&#xA;S   11   1.00&#xA;   6456.4000000              0.0002500&#xA;    974.0610000              0.0016300&#xA;    214.4290000              0.0047330&#xA;     31.3308000             -0.0336990&#xA;     19.6130000              0.2439310&#xA;      8.8860900             -0.7646530&#xA;      2.3250800              0.9007940&#xA;      1.1842200              0.4415130&#xA;      0.4268540              0.0214160&#xA;      0.2016450             -0.0030880&#xA;      0.0921780              0.0008510&#xA;S   11   1.00&#xA;   6456.4000000             -0.0001300&#xA;    974.0610000             -0.0008850&#xA;    214.4290000             -0.0023580&#xA;     31.3308000              0.0072910&#xA;     19.6130000             -0.0926390&#xA;      8.8860900              0.3537950&#xA;      2.3250800             -0.6158300&#xA;      1.1842200             -0.4130600&#xA;      0.4268540              0.5793340&#xA;      0.2016450              0.6254620&#xA;      0.0921780              0.1423370&#xA;S   1   1.00&#xA;      2.444900D+00           1.000000D+00&#xA;S   1   1.00&#xA;      1.535200D+00           1.000000D+00&#xA;S   1   1.00&#xA;      0.4268540              1.0000000&#xA;S   1   1.00&#xA;      0.2016450              1.0000000&#xA;S   1   1.00&#xA;      0.1143000              1.0000000&#xA;S   1   1.00&#xA;      0.0476000              1.0000000&#xA;P   9   1.00&#xA;    191.1700000              0.0007650&#xA;     22.5178000              0.0369520&#xA;     10.0604000             -0.2806880&#xA;      5.5576200              0.1427170&#xA;      2.6962500              0.6356540&#xA;      1.3076400              0.3932570&#xA;      0.5306750              0.0410560&#xA;      0.2224610             -0.0022510&#xA;      0.0868810              0.0007740&#xA;P   9   1.00&#xA;    191.1700000             -0.0003290&#xA;     22.5178000             -0.0127810&#xA;     10.0604000              0.1082740&#xA;      5.5576200             -0.0720510&#xA;      2.6962500             -0.2845800&#xA;      1.3076400             -0.1852050&#xA;      0.5306750              0.3583360&#xA;      0.2224610              0.5883940&#xA;      0.0868810              0.2572450&#xA;P   1   1.00&#xA;      5.323800D+00           1.000000D+00&#xA;P   1   1.00&#xA;      1.625100D+00           1.000000D+00&#xA;P   1   1.00&#xA;      0.6953000              1.0000000&#xA;P   1   1.00&#xA;      0.1135000              1.0000000&#xA;P   1   1.00&#xA;      0.0420000              1.0000000&#xA;D   9   1.00&#xA;    142.9710000              0.0007360&#xA;     41.3057000              0.0053720&#xA;     10.9222000             -0.0288270&#xA;      6.8240800              0.1199100&#xA;      3.6669600              0.3324640&#xA;      1.9828900              0.3892090&#xA;      1.0539900              0.2483590&#xA;      0.5299030              0.0776110&#xA;      0.2192000              0.0073660&#xA;D   1   1.00&#xA;      2.520100D+00           1.000000D+00&#xA;D   1   1.00&#xA;      1.254800D+00           1.000000D+00&#xA;D   1   1.00&#xA;      0.5299030              1.0000000&#xA;D   1   1.00&#xA;      0.2192000              1.0000000&#xA;D   1   1.00&#xA;      0.0917000              1.0000000&#xA;F   1   1.00&#xA;      5.615800D+00           1.000000D+00&#xA;F   1   1.00&#xA;      1.614800D+00           1.000000D+00&#xA;F   1   1.00&#xA;      0.4779000              1.0000000&#xA;F   1   1.00&#xA;      0.2287000              1.0000000&#xA;G   1   1.00&#xA;      1.753000D+00           1.000000D+00&#xA;****&#xA;H 0&#xA;aug-cc-pVTZ&#xA;****&#xA;XE     0&#xA;XE-ECP     4     28&#xA;g potential&#xA;  1&#xA;2      1.0000000              0.0000000&#xA;s-g potential&#xA;  3&#xA;2     40.0051840             49.9979620&#xA;2     17.8122140            281.0133030&#xA;2      9.3041500             61.5382550&#xA;p-g potential&#xA;  4&#xA;2     15.7017720             67.4391420&#xA;2     15.2586080            134.8747110&#xA;2      9.2921840             14.6633000&#xA;2      8.5590030             29.3547300&#xA;d-g potential&#xA;  6&#xA;2     15.1856000             35.4369080&#xA;2     14.2845000             53.1957720&#xA;2      7.1218890              9.0462320&#xA;2      6.9919630             13.2236810&#xA;2      0.6239460              0.0848530&#xA;2      0.6472840              0.0441550&#xA;f-g potential&#xA;  4&#xA;2     20.8815570            -23.0892950&#xA;2     20.7834430            -30.0744750&#xA;2      5.2533890             -0.2882270&#xA;2      5.3611880             -0.3869240&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="723" LastEditorUserId="5" LastEditDate="2020-07-28T21:48:01.693" LastActivityDate="2020-07-29T19:58:14.367" Title="I get an error 'Conversion from Z-matrix to cartesian coordinates failed' in Gaussian09. Any suggestions?" Tags="|quantum-chemistry|computational-chemistry|gaussian|coupled-cluster|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="1766" PostTypeId="1" AcceptedAnswerId="1787" CreationDate="2020-07-27T19:32:05.807" Score="9" ViewCount="191" Body="&lt;p&gt;Experimentally, determining the absolute valence and conductance band positions can be difficult.  While DFT often underestimates band gaps, experimentally the band gap is a far more accessible measurement that could be used to find the band position of the valence or conductance band if one is known.&lt;/p&gt;&#xA;&lt;p&gt;The fundamental question here is, can either the absolute valence or conductance band of a semiconductor be determined accurately with respect to vacuum using DFT.  If so, what kind of error can be expected in these systems.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-28T02:53:59.923" Title="Absolute Valence and Conductance Band Position" Tags="|density-functional-theory|band-structure|experimental|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1767" PostTypeId="2" ParentId="1764" CreationDate="2020-07-27T19:58:16.820" Score="11" Body="&lt;p&gt;From that reference, what we got is the bond length from the atomic positions.&lt;/p&gt;&#xA;&lt;p&gt;One easy way is to look for a CIF file with the crystal information.&lt;/p&gt;&#xA;&lt;p&gt;From the CIF49801 bellow, we get the following info:&lt;/p&gt;&#xA;&lt;p&gt;(label type_symbol symmetry_multiplicity Wyckoff_symbol fract_x fract_y fract_z B_iso_or_equiv occupancy)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Mo1 Mo4+ 2 c 0.3333 0.6667 0.25     . 1.&#xA;    S1  S2-  4 f 0.3333 0.6667 0.621(3) . 1.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Whereas from the CIF84180, we get the following info:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Mo1 Mo4+ 2 d 0.6667 0.3333 0.25     . 1.&#xA;    S1  S2-  4 f 0.3333 0.6667 0.120(1) . 1.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The full CIFs were obtained from the ICSD - Inorganic Crystal Structure Database.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CIF49801:&#xA;&#xA;#(C) 2020 by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure.  All rights reserved.&#xA;data_49801-ICSD&#xA;_database_code_ICSD 49801&#xA;_audit_creation_date 1987-01-31&#xA;_audit_update_record 2015-02-01&#xA;_chemical_name_common 'Molybdenum disulfide'&#xA;_chemical_formula_structural 'Mo S2'&#xA;_chemical_formula_sum 'Mo1 S2'&#xA;_chemical_name_structure_type MoS2(4H)&#xA;_chemical_name_mineral ''Molybdenite 2H''&#xA;_exptl_crystal_density_diffrn 5.&#xA;_citation_title 'On the Structure of Molybdenum Diselenide and Disulfide'&#xA;loop_&#xA;_citation_id&#xA;_citation_journal_full&#xA;_citation_year&#xA;_citation_journal_volume&#xA;_citation_page_first&#xA;_citation_page_last&#xA;_citation_journal_id_ASTM&#xA;primary 'Zeitschrift fuer Anorganische und Allgemeine Chemie (1950) (DE)' 1986&#xA;540 15 17 ZAACAB&#xA;loop_&#xA;_citation_author_citation_id&#xA;_citation_author_name&#xA;primary 'Bronsema, K.D.'&#xA;primary 'de Boer, J.L.'&#xA;primary 'Jellinek, F.'&#xA;_cell_length_a 3.16021&#xA;_cell_length_b 3.16021&#xA;_cell_length_c 12.294(4)&#xA;_cell_angle_alpha 90.&#xA;_cell_angle_beta 90.&#xA;_cell_angle_gamma 120.&#xA;_cell_volume 106.33&#xA;_cell_formula_units_Z 2&#xA;_space_group_name_H-M_alt 'P 63/m m c'&#xA;_space_group_IT_number 194&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 'x, x-y, -z+1/2'&#xA;2 '-x+y, y, -z+1/2'&#xA;3 '-y, -x, -z+1/2'&#xA;4 '-x+y, -x, -z+1/2'&#xA;5 '-y, x-y, -z+1/2'&#xA;6 'x, y, -z+1/2'&#xA;7 '-x, -x+y, z+1/2'&#xA;8 'x-y, -y, z+1/2'&#xA;9 'y, x, z+1/2'&#xA;10 'x-y, x, z+1/2'&#xA;11 'y, -x+y, z+1/2'&#xA;12 '-x, -y, z+1/2'&#xA;13 '-x, -x+y, -z'&#xA;14 'x-y, -y, -z'&#xA;15 'y, x, -z'&#xA;16 'x-y, x, -z'&#xA;17 'y, -x+y, -z'&#xA;18 '-x, -y, -z'&#xA;19 'x, x-y, z'&#xA;20 '-x+y, y, z'&#xA;21 '-y, -x, z'&#xA;22 '-x+y, -x, z'&#xA;23 '-y, x-y, z'&#xA;24 'x, y, z'&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_oxidation_number&#xA;Mo4+ 4&#xA;S2- -2&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_B_iso_or_equiv&#xA;_atom_site_occupancy&#xA;Mo1 Mo4+ 2 c 0.3333 0.6667 0.25 . 1.&#xA;S1 S2- 4 f 0.3333 0.6667 0.621(3) . 1.&#xA;#End of TTdata_49801-ICSD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CIF84180:&#xA;&#xA;#(C) 2020 by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure.  All rights reserved.&#xA;data_84180-ICSD&#xA;_database_code_ICSD 84180&#xA;_audit_creation_date 1999-01-19&#xA;_audit_update_record 2013-02-01&#xA;_chemical_name_common 'Molybdenum(IV) sulfide - 2H'&#xA;_chemical_formula_structural 'Mo S2'&#xA;_chemical_formula_sum 'Mo1 S2'&#xA;_chemical_name_structure_type MoS2(4H)&#xA;_chemical_name_mineral ''Molybdenite 2H''&#xA;_exptl_crystal_density_diffrn 5.&#xA;_citation_title&#xA;&#xA;;&#xA;Characteristics of the crystal structure, electrophysical properties, and&#xA;model of the valence band spectrum of laminar compounds of molybdenum&#xA;disulfide type&#xA;;&#xA;loop_&#xA;_citation_id&#xA;_citation_journal_full&#xA;_citation_year&#xA;_citation_journal_volume&#xA;_citation_page_first&#xA;_citation_page_last&#xA;_citation_journal_id_ASTM&#xA;primary 'Izvestiya Akademii Nauk SSSR, Neorganicheskie Materialy' 1983 19 1060&#xA;1065 IVNMAW&#xA;loop_&#xA;_citation_author_citation_id&#xA;_citation_author_name&#xA;primary 'Kalikhman, V.L.'&#xA;_cell_length_a 3.16&#xA;_cell_length_b 3.16&#xA;_cell_length_c 12.29&#xA;_cell_angle_alpha 90.&#xA;_cell_angle_beta 90.&#xA;_cell_angle_gamma 120.&#xA;_cell_volume 106.28&#xA;_cell_formula_units_Z 2&#xA;_space_group_name_H-M_alt 'P 63/m m c'&#xA;_space_group_IT_number 194&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 'x, x-y, -z+1/2'&#xA;2 '-x+y, y, -z+1/2'&#xA;3 '-y, -x, -z+1/2'&#xA;4 '-x+y, -x, -z+1/2'&#xA;5 '-y, x-y, -z+1/2'&#xA;6 'x, y, -z+1/2'&#xA;7 '-x, -x+y, z+1/2'&#xA;8 'x-y, -y, z+1/2'&#xA;9 'y, x, z+1/2'&#xA;10 'x-y, x, z+1/2'&#xA;11 'y, -x+y, z+1/2'&#xA;12 '-x, -y, z+1/2'&#xA;13 '-x, -x+y, -z'&#xA;14 'x-y, -y, -z'&#xA;15 'y, x, -z'&#xA;16 'x-y, x, -z'&#xA;17 'y, -x+y, -z'&#xA;18 '-x, -y, -z'&#xA;19 'x, x-y, z'&#xA;20 '-x+y, y, z'&#xA;21 '-y, -x, z'&#xA;22 '-x+y, -x, z'&#xA;23 '-y, x-y, z'&#xA;24 'x, y, z'&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_oxidation_number&#xA;Mo4+ 4&#xA;S2- -2&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_B_iso_or_equiv&#xA;_atom_site_occupancy&#xA;Mo1 Mo4+ 2 d 0.6667 0.3333 0.25 . 1.&#xA;S1 S2- 4 f 0.3333 0.6667 0.120(1) . 1.&#xA;#End of TTdata_84180-ICSD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-27T19:58:16.820" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1768" PostTypeId="1" AcceptedAnswerId="1871" CreationDate="2020-07-27T20:01:58.883" Score="11" ViewCount="783" Body="&lt;p&gt;I am studying the transition metal dichalcogenides (TMDs) and I have seen webinars and articles that said that these materials exhibited the anomalous quantum Hall effect related to the curvature of Berry, which changes the speed of electrons:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\dot{r}=\frac{1}{\hbar}\frac{\partial \epsilon_n(\mathbf{k})}{\partial \mathbf{k}}-\dot{\mathbf{k}}\,\times \Omega_n(\mathbf{k}) &#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From what I've been reading, I understood that Hall's anomalous effect consists of a set of three phenomena:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;intrinsic deflection&lt;/li&gt;&#xA;&lt;li&gt;side-jump&lt;/li&gt;&#xA;&lt;li&gt;skew-scattering&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Berry's curvature is related to the first phenomenon (intrinsic deflection), but I didn't understand how electrons move and how that term appears. The other two effects I was reading but I didn't understand what they were. Everything I found seemed very complicated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Questions:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What does the quantum anomalous Hall phenomenon consist of?&lt;/li&gt;&#xA;&lt;li&gt;How does each phenomenon contribute and where does each of the three terms come from?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Shiomi, Yuki, &amp;quot;Anomalous and Topological Hall Effects in Itinerant Magnets&amp;quot;, Springer Theses (pages 499-501)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-08-07T17:52:26.893" LastActivityDate="2020-08-07T17:52:26.893" Title="Anomalous Quantum Hall Effect" Tags="|quantum-mechanics|berry-phase|dichalcogenides|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1769" PostTypeId="2" ParentId="1690" CreationDate="2020-07-27T21:22:44.740" Score="6" Body="&lt;p&gt;I am surprised no-one above mentions the &lt;a href=&quot;http://hyperphysics.phy-astr.gsu.edu/hbase/molecule/vibrot.html#c3&quot; rel=&quot;noreferrer&quot;&gt;classic textbook example of the IR spectrum of HCl gas&lt;/a&gt;, which shows rather beautiful rotational structure superimposed on the vibrational band. The spacing of the rotational peaks, of course gives direct access to the angular momentum and the bond length.&lt;/p&gt;&#xA;&lt;p&gt;I say &amp;quot;directly&amp;quot; and &amp;quot;of course&amp;quot; - but you have to know the mass of the respective atoms and trust the selection rules. Another charm of the method is that you can see apparent bond lengthening when the molecule is raised to a high rotational state - which is sufficient to prompt thought about the real significance of bond length.&lt;/p&gt;&#xA;" OwnerUserId="1143" LastEditorUserId="5" LastEditDate="2020-07-27T22:21:12.640" LastActivityDate="2020-07-27T22:21:12.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1770" PostTypeId="1" CreationDate="2020-07-27T21:28:43.060" Score="11" ViewCount="611" Body="&lt;p&gt;TMDs are transition metal dichalcogenides and have the chemical formula MX&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; where M is the transition metal and X is the chalcogen. An example of a TMD is MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I would like to demonstrate that the Hamiltonian of TMDs (transition metal dichalcogenides) is given by the following formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\hat{H}_0=at(\tau k_x\hat{\sigma}_x+k_y\hat{\sigma}_y)+\frac{\Delta}{2}\hat{\sigma}_z-\lambda\tau\frac{\hat{\sigma}_z-1}{2}\hat{s}_z \tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\tau=\pm1$&lt;/span&gt; is the valley index, &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is the lattice constant, &lt;span class=&quot;math-container&quot;&gt;$\hat{\sigma}$&lt;/span&gt; are Pauli matrices, &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is the hopping integral, and &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; is the energy gap.&lt;/p&gt;&#xA;&lt;p&gt;From what I've seen in articles and presentations, the first Hamiltonian term is similar to graphene, the second term is related to the breaking of symmetry that opens a band gap and the last term is the spin orbit coupling.&lt;/p&gt;&#xA;&lt;p&gt;The basis wave functions chosen for the conduction and valence bands at K are related by time-reversal symmetry, consisting of hybridized d-orbitals from the transition metal with magnetic quantum numbers of m=0 and m=2&lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;, respectively:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;|\phi_c\rangle=|d_{z^2}\rangle\tag{1}&#xA;\end{equation}&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;|\phi_{v}^{\tau}\rangle=\frac{1}{\sqrt{2}}(|d_{x^2-y^2}\rangle+i\tau|d_{xy}\rangle)&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Questions:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How do you get the Hamiltonian formula for transition metal dichalcogenides? How to derivate the expression above (equation (1))?&lt;/li&gt;&#xA;&lt;li&gt;What does the parameter &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; mean? I don't understand what they mean by &amp;quot;hopping integral&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;Why did you choose this basis wave functions?&lt;/li&gt;&#xA;&lt;li&gt;What is &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; in the mathematical formula?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;: Modtland, Brian, &amp;quot;Exploring Valleytronics in 2D Transition Metal Dichalcogenides&amp;quot; (MIT) (page 48 - equation (2.1)) (click here to see the &lt;a href=&quot;https://dspace.mit.edu/bitstream/handle/1721.1/115776/1036987679-MIT.pdf?sequence=1&amp;amp;isAllowed=y&quot; rel=&quot;nofollow noreferrer&quot;&gt;document&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="1218" LastEditDate="2020-11-29T09:28:43.290" LastActivityDate="2020-12-01T06:12:39.470" Title="How to derive the effective Hamiltonian of two-dimensional TMDCs monolayers?" Tags="|model-hamiltonians|quantum-mechanics|dichalcogenides|derivations|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1771" PostTypeId="1" AcceptedAnswerId="1816" CreationDate="2020-07-27T21:31:36.117" Score="8" ViewCount="1382" Body="&lt;p&gt;Transition metal dichalcogenides (TMDs) are composed of three atomic planes and often two atomic species: a metal and two chalcogens. The honeycomb, hexagonal lattice has three fold symmetry and can permit mirror plane symmetry and / or inversion symmetry. [16] In the macroscopic bulk crystal, or more precisely, for an even number of monolayers, the crystal structure has an inversion center. In the case of a monolayer (or any odd number of layers), the crystal may or may not have an inversion center.&#xA;Why does a bilayer have inversion symmetry and a trilayer or monolayer does not have inversion symmetry? How can I see this in the image?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/p8Mhi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/p8Mhi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-08-07T17:52:21.360" LastActivityDate="2020-08-07T17:52:21.360" Title="Inversion symmetry in 2D materials" Tags="|from-phys-se|symmetry|space-groups|2d-lattice|dichalcogenides|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1772" PostTypeId="1" CreationDate="2020-07-27T21:33:42.617" Score="10" ViewCount="165" Body="&lt;p&gt;I want to draw the energy (&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;) diagrams for a simple cubic cell of parameter &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, where each atom provides two electrons for the almost free electron levels for planes [100], [110] and [111].&lt;/p&gt;&#xA;&lt;p&gt;I calculate &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; for the first Brillouin zone:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{\text{ first Brillouin zone}}=\frac{\pi}{a}=\frac{3,14}{a}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I calculate &lt;span class=&quot;math-container&quot;&gt;$k_{\text{Fermi}}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$n=\frac{2}{a^3}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{F}=(3\pi^2n)^{1/3}=\big(3\pi^2\frac{2}{a^3}\big)=\frac{(6\pi^2)^{1/3}}{a}\approx \frac{3,90}{a}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I calculate &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; for the plane [100]:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{x}=\frac{\pi}{a}\hat{x}=\frac{3,14}{a}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{[100]}=\frac{\pi}{a}=\frac{3,14}{a} = k_{\text{ first Brillouin zone}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I calculate &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; for the plane [110]:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{k}=\frac{\pi}{a}\hat{x}+\frac{\pi}{a}\hat{y}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{[110]}=\frac{\sqrt{2}\pi}{a}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I calculate &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; for the plane [111]:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{k}=\frac{\pi}{a}\hat{x}+\frac{\pi}{a}\hat{y}+\frac{\pi}{a}\hat{z}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k_{[111]}=\frac{\sqrt{3}\pi}{a}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally I made the drawings of the energy bands for each plane:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dyAsL.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dyAsL.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I understand why in the first zone of Brillouin there is a discontinuity as in the case of plane [100], where the material is conductor, but I do not understand for the planes [110] and [111].&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;As for planes [110] and [111], &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is greater than &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; of the first Brillouin zone, should there also be in the drawing a discontinuity in the first Brillouin zone?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Why is it just a single semi-filled band?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Are they insulators or conductors in this case (planes [110] and [111])?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-12-31T04:41:43.743" LastActivityDate="2020-12-31T04:41:43.743" Title="How can I draw the energy bands for the first and second zones of Brillouin? Is it conductor or insulator?" Tags="|band-structure|from-phys-se|brillouin-zone|materials-engineering|physical-properties-of-materials|" AnswerCount="0" CommentCount="1" ClosedDate="2021-03-19T16:20:42.760" ContentLicense="CC BY-SA 4.0" />
  <row Id="1773" PostTypeId="1" AcceptedAnswerId="1775" CreationDate="2020-07-27T21:36:08.083" Score="3" ViewCount="691" Body="&lt;p&gt;I want to understand the electronic band structure diagram of the following image, corresponding to &lt;span class=&quot;math-container&quot;&gt;$\text{MoS}_2$&lt;/span&gt; (TMD):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tTwyY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tTwyY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I read about DFT (density functional theory).&lt;/p&gt;&#xA;&lt;p&gt;DFT is based on solving the Schrodinger equation for a set of atoms. Through the Born Oppenheimer approach, it is possible to decouple the nuclear and electronic wave functions.&#xA;We just then need to solve the Schrodinger equation for electrons. Using the two Hohenberg and Kohn theorems, we obtain the Kohn Scham equations:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\bigg[-\frac{\hbar}{2m}\nabla^2+V(r)+V_H(r)+V_{XC}(r)\bigg]\psi_i(r)=\epsilon_i(r)\psi_i$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Computationally the problem is solved as follows:&lt;/p&gt;&#xA;&lt;p&gt;-Define n[r] (random)&lt;/p&gt;&#xA;&lt;p&gt;-Solve Kohn Scham equation and find &lt;span class=&quot;math-container&quot;&gt;$\psi(r)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;-Calculate new n(r): &lt;span class=&quot;math-container&quot;&gt;$n(r)=2\sum\psi^{*}(r)\psi(r)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;-If n(r) calculated is equal to the original, the program will stop. If they're different, the program recalculate the Kohn Scham equation with n(r) calculated previously.&lt;/p&gt;&#xA;&lt;p&gt;According to Hohenberg and Kohn's theorem 1, each electronic density uniquely corresponds to an energy in the ground state, therefore, once the program ends, knowing the electronic density, we know the energy in the ground state.&lt;/p&gt;&#xA;&lt;p&gt;I don't understand how DFT relates to the various lines obtained from the graph and I don't understand what DFT is related to orbitals. How was the graph obtained based on the DFT?&lt;/p&gt;&#xA;" OwnerUserId="1065" LastActivityDate="2020-07-27T22:02:55.900" Title="Interpretation of electronic band structure diagram" Tags="|density-functional-theory|electronic-structure|band-structure|quantum-mechanics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1774" PostTypeId="1" AcceptedAnswerId="2174" CreationDate="2020-07-27T21:49:19.807" Score="17" ViewCount="292" Body="&lt;p&gt;This question is somewhat broad, but hopefully I can convey my point and elicit some worthwhile discussion.&lt;/p&gt;&#xA;&lt;p&gt;One of the fundamental difficulties of machine learning is trying to develop a model that will work beyond your training set. The issue is that it has proven very challenging to develop a machine learning model that can extrapolate (e.g. derive insight about unseen, &amp;quot;outer&amp;quot; regions of the input space, with &amp;quot;outer&amp;quot; meaning input parameters larger/smaller than any in the test set). So instead, one often tries to develop the training set such that they can interpolate (e.g. derive insight about unseen, &amp;quot;inner&amp;quot; regions where the input parameters are between ones from the training set). However, the topography of a given input space and how it relates to some output property are precisely the problems one is hoping to solve with machine learning!&lt;/p&gt;&#xA;&lt;p&gt;So my question is, what are some general techniques that Matter Modelers use to &amp;quot;smartly&amp;quot; sample input? What sort of intuition can we apply to ensure our training set has a wide boundary and that we are interpolating, rather than extrapolating, when applying our model to a test set? For some properties, this is fairly intuitive. For example [1], in developing a training set to model a potential energy surface, chose their training set by iteratively adding points that maximized the minimum distance from any existing point in the set. Here, the sample space is over physical distance, so there is an intuitive way to determine a boundary. But what sort of guidelines are available to make this selection more generalizable to other types of input without as clear a notion of distance?&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Dral, Pavlo O.;  Owens, Alec;  Yurchenko, Sergei N.;  Thiel, Walter J. Chem. Phys. 146, 244108 (2017); DOI:10.1063/1.4989536&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-08-30T21:51:58.767" LastActivityDate="2022-02-16T20:00:59.397" Title="General Techniques for Smart Sampling in Matter Machine Learning?" Tags="|reference-request|machine-learning|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1775" PostTypeId="2" ParentId="1773" CreationDate="2020-07-27T22:02:55.900" Score="4" Body="&lt;p&gt;Started as a comment, turned into an answer. Someone else can give more detail and precision in the explanation, but here I'll just give a rough sketch of the general idea.&lt;/p&gt;&#xA;&lt;p&gt;I think you may have conflated &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; with the system wavefunction. In the Kohn-Sham equations, &lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt; is an orbital and &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt; the energy of that orbital. Going from a molecular case to a periodic system, we can think of combining the orbitals of the monomers to create a crystal orbital, but this crystal orbital and its energy will depend on how we align the phase of the monomer orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The band structures in your post depict just that: each band corresponds to a monomer orbital and the band gives the energy of the crystal orbital (y-axis) with respect to the phase arrangement of the monomer orbitals (x-axis). The symbols on the x-axis are labels for particular points in k-space that define the phase with which the orbitals combine. For example, the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point is the origin in k-space and corresponds to each monomer orbital having the same phase in the crystal orbital. Another point might mark that the phase of the orbitals changes by &lt;span class=&quot;math-container&quot;&gt;$\pi/2$&lt;/span&gt; for each monomer unit.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-27T22:02:55.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1776" PostTypeId="1" AcceptedAnswerId="1803" CreationDate="2020-07-27T22:05:54.397" Score="3" ViewCount="80" Body="&lt;p&gt;I am trying to synthesize MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; crystals in a furnace with two temperature zones.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that the oven is not very wide, so the temperature of the hottest zone influences the temperature of the cold zone. This is visible in the Excel chart I obtained from the practice, in which I placed the temperature of the hot zone at 800ºC, the temperature of the cold zone at 375ºC and the thermocouple type K in a certain position.&lt;/p&gt;&#xA;&lt;p&gt;The minutes of the experiment are shown on the x-axis and the temperature is shown on the Y-axis. The blue line is the temperature data for the hot zone over time, the orange line is the temperature data for the cold zone over time and the gray line is the temperature data for the type K thermocouple at over time.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nyvld.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nyvld.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The objective is for the thermocouple to be stable close to 300ºC and 50ºC before reaching 800ºC (that is, in this case, at 750ºC), the thermocouple must measure a temperature of at least 290ºC.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that as the oven takes a long time to cool down, I can only draw a temperature profile per day, which makes the progress of my thesis very slow. I do not know the location of the thermocouples inside the oven, which indicate the temperature of the cold zone and the hot zone, so it is necessary to make several attempts to find the perfect position to reach a temperature close to 300ºC in the thermocouple.&lt;/p&gt;&#xA;&lt;p&gt;The influence of the hot zone in the cold zone is visualized by the existence of a &amp;quot;hump&amp;quot; in the graph of the temperature of the cold zone (orange line). In addition, the furnace has Argon gas necessary for the synthesis of the crystals.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Is there a way to simulate the oven computationally to know how it influences one temperature zone in the other?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;And is there any way to simulate the oven in the computer in order to be able to move a type K thermocouple inside it to try to find the perfect position where it reaches 300ºC and maintains that temperature?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What programs do you recommend to draw this graph and others like this superimposed for my thesis? I didn't want to present the charts in Excel.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="142" LastEditDate="2020-07-28T11:33:45.963" LastActivityDate="2020-07-28T13:12:52.107" Title="How to simulate a furnace computationally" Tags="|condensed-matter|high-performance-computing|graphical-processing-unit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1777" PostTypeId="1" CreationDate="2020-07-27T22:29:17.293" Score="5" ViewCount="70" Body="&lt;p&gt;Some of the work I do in the study of discrete dislocation dynamics (a branch of materials modeling) involves topological changes on a graph: changes in the connectivity of nodes, as well as deletion and addition of nodes. This means the graph structure is unknown and dynamically changing. As such, there is very little that can be known of the graph at any point without traversing it completely.&lt;/p&gt;&#xA;&lt;p&gt;I've been thinking that there must be a way to do some sort of &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(\log N)$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$N=$&lt;/span&gt; number of graphs) parallelisation via reduction &lt;em&gt;if&lt;/em&gt; we can communicate information between nodes. However, given that the structure of the graph is largely unknown and its storage in memory is not necessarily ordered, I'm thinking of not bothering.&lt;/p&gt;&#xA;&lt;p&gt;Every algorithm I've come across exploits some feature that greatly limits the graph's properties, but in this case the only feature is that all of them are closed. The only way of knowing which nodes belong to which graph is to follow the connectivity. There's also the issue of the scaling constant and communication latency depending on how the data is segmented for parallelisation. So minimising inter-thread/core communication is quite important.&lt;/p&gt;&#xA;&lt;p&gt;Admittedly, this could be somewhat naively achieved by traversing the connectivity and parallelising over closed graphs, thus running the serial algorithm for each closed graph, but the memory scaling of this naive algorithm is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(N)$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$N=$&lt;/span&gt; number of graphs), nevermind the number of nodes in each graph.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any ideas/suggestions? This would help a lot with some of our newer simulations with high dislocation densities.&lt;/p&gt;&#xA;" OwnerUserId="1142" LastEditorUserId="7" LastEditDate="2020-07-29T21:41:06.757" LastActivityDate="2020-07-29T21:41:06.757" Title="Parallel algorithms on unstructured closed graphs" Tags="|high-performance-computing|mathematical-modeling|algorithms|" AnswerCount="0" CommentCount="5" ClosedDate="2020-07-30T14:59:25.100" ContentLicense="CC BY-SA 4.0" />
  <row Id="1778" PostTypeId="1" CreationDate="2020-07-27T23:43:32.270" Score="9" ViewCount="707" Body="&lt;p&gt;2D materials (such as graphene) are mostly exfoliated from their 3D bulk counterpart. I am wondering how we can calculate work function for a 2D material? Normally electrostatic potential in the out-of-plane direction is required to obtain E&lt;span class=&quot;math-container&quot;&gt;$_{\rm{vac}}$&lt;/span&gt;, which is later used in the definition of work function (WF=E&lt;span class=&quot;math-container&quot;&gt;$_{\rm{vac}}$&lt;/span&gt;-E&lt;span class=&quot;math-container&quot;&gt;$_{\rm{Fermi}}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do we need electrostatic potential for both bulk and 2D system to compute work function or is it only the 2D material for which it should be computed?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2020-07-28T02:34:20.123" LastActivityDate="2020-07-28T02:39:43.603" Title="Work Function Problem" Tags="|density-functional-theory|electronic-structure|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1779" PostTypeId="1" CreationDate="2020-07-27T23:53:46.360" Score="9" ViewCount="338" Body="&lt;p&gt;The Raman spectrum of a material shows certain 'active' modes for which we get experimental signatures. Phonon calculations are mostly used to calculate vibrational modes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can we determine the nature of these modes from a phonon calculation (e.g., if the mode is an in-plane or out-of-plane or of some other type)?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2020-07-28T02:42:10.593" LastActivityDate="2020-07-28T07:01:11.377" Title="Phonon Calculations and Vibrational Modes" Tags="|density-functional-theory|phonons|vibrations|spectroscopy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1780" PostTypeId="1" CreationDate="2020-07-27T23:55:23.010" Score="11" ViewCount="604" Body="&lt;p&gt;I work with magnetic materials and I haven't found a way to automatically plot structures with their corresponding magnetic moments. For this specific project I am using VASP. I am trying to plot something like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oRFoum.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oRFoum.png&quot; alt=&quot;Magnetic moment plot example.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My POSCAR and OUTCAR files are uploaded to the Matter Modeling SE github page under the folder for question #1780: &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/1780&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="204" LastEditorUserId="5" LastEditDate="2020-07-30T02:01:03.037" LastActivityDate="2020-07-31T15:44:08.897" Title="How to automatically plot atomic structures with magnetic moments?" Tags="|crystal-structure|magnetism|visualization-software|spin|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1781" PostTypeId="1" CreationDate="2020-07-27T23:59:34.837" Score="11" ViewCount="190" Body="&lt;p&gt;The following questions have worked out very well  :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;What are the types of Quantum Monte Carlo?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1568/5&quot;&gt;What are the types of SCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;What are the types of MCSCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1521/5&quot;&gt;What are the types of pseudopotentials?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1513/5&quot;&gt;What are the types of DFT?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/5&quot;&gt;What are the types of charge analysis?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/901/5&quot;&gt;What are the types of bond orders?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the same format, I am interested in a 2-3 paragraph explanation of what separates each &amp;quot;flavor&amp;quot; of DMRG from the others, and in which software each DMRG flavor is implemented. I know of the following types of DMRG, but if people know others they are welcome to add them!&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1908.10588&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;t-DMRG&lt;/strong&gt;&lt;/a&gt; (time-adaptive DMRG, or time-dependent DMRG: &lt;a href=&quot;https://arxiv.org/abs/1907.12044&quot; rel=&quot;noreferrer&quot;&gt;TD-DMRG&lt;/a&gt;, or &lt;a href=&quot;https://arxiv.org/abs/1803.11342&quot; rel=&quot;noreferrer&quot;&gt;Dynamical DMRG&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.5031140&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;p-DMRG&lt;/strong&gt;&lt;/a&gt; (stochastic perturbative DMRG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0701243&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;TMRG&lt;/strong&gt;&lt;/a&gt; (transfer matrix RG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.97.195125&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;SDMRG&lt;/strong&gt;&lt;/a&gt; (symmetrized DMRG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/0704.1949&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;CTMRG&lt;/strong&gt;&lt;/a&gt; (corner transfer matrix RG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1739/5&quot;&gt;&lt;strong&gt;iDMRG&lt;/strong&gt;&lt;/a&gt; (infinite DMRG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1905.05956&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;ED/DMRG&lt;/strong&gt;&lt;/a&gt; (hybrid exact-diagonalization/DMRG)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1902.10006&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Thermal DMRG&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1908.10880&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Zero-site DMRG&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1702.07721&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;DMRG-X&lt;/strong&gt;&lt;/a&gt; (DMRG targeted for highly excited states)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.6b00696&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;DMRG-isPT&lt;/strong&gt;&lt;/a&gt; (DMRG with inner space perturbation theory)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;Acronyms that signify the combining of ordinary DMRG with another method, such as &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.8b00960&quot; rel=&quot;noreferrer&quot;&gt;DMRG-TCC&lt;/a&gt;,  &lt;a href=&quot;https://arxiv.org/abs/1405.5642&quot; rel=&quot;noreferrer&quot;&gt;DMRG-SCF&lt;/a&gt;, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00969&quot; rel=&quot;noreferrer&quot;&gt;SA-DMRG-SCF&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1605.05526&quot; rel=&quot;noreferrer&quot;&gt;DMRG-CASPT2&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4976644&quot; rel=&quot;noreferrer&quot;&gt;DMRG-CASSCF&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1808.06273&quot; rel=&quot;noreferrer&quot;&gt;DMRG-PDFT&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.4895977&quot; rel=&quot;noreferrer&quot;&gt;MPSPT&lt;/a&gt; and DMRG-QUAPI are unnecessary for this question (though if there's interest, a different question could cover those, as well as techniques like spin-adapted DMRG).&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-30T01:24:44.260" LastActivityDate="2020-07-30T01:24:44.260" Title="What are the types of DMRG?" Tags="|reference-request|one-topic-per-answer|terminology|dmrg|computational-frameworks|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1782" PostTypeId="1" AcceptedAnswerId="1794" CreationDate="2020-07-28T00:53:00.477" Score="6" ViewCount="71" Body="&lt;p&gt;I want to represent parallel transport as in the following figure, but next to this figure I would like to place a diagram with the two arrows (of the initial state and of the final state that are present at the top of the spherical surface) and the angle between them, to see better and put more emphasis on the analogy with the Berry phase.&lt;/p&gt;&#xA;&lt;p&gt;How can I draw the two arrows and the angle? Is there a program that allows me to do this and is free? What programs do you use to draw images from scratch and are free (and provide good images for example, to put in articles)?&lt;/p&gt;&#xA;&lt;p&gt;The image was taken from this &lt;a href=&quot;http://repositorio.ufes.br/bitstream/10/7457/1/tese_8437_Disserta%C3%A7%C3%A3o%20final%201%20C%C3%A1ssio.pdf&quot; rel=&quot;noreferrer&quot;&gt;thesis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uUuCrm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uUuCrm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2020-07-28T00:56:17.993" LastActivityDate="2020-07-28T05:43:46.740" Title="Create an image from scratch with the vectors that represent the Berry phase for parallel transport (classic system)" Tags="|software|visualization-software|materials-design|berry-phase|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1783" PostTypeId="2" ParentId="1538" CreationDate="2020-07-28T02:12:45.223" Score="5" Body="&lt;p&gt;When doing calculations in real space, there are aliasing errors that can occur.  This can result in slightly incorrect energies with respect to small shifts.  By working in real space, the calculation of projector operators will scale closer to the number of atoms rather than the number of plane waves since they can be evaluated within a sphere around the atom.  The real space method becomes more favorable as the number of atoms increases, which is why you get this warning for large cells.&lt;/p&gt;&#xA;&lt;p&gt;This aliasing error is different than the eggbox / wrap around errors that occur with lower &lt;code&gt;PREC&lt;/code&gt; values and can be compounded on top of it when considering very small energy differences.  For large cells that need to be evaluated within meV, you should relax with &lt;code&gt;LREAL=Auto&lt;/code&gt;, then &lt;code&gt;LREAL=False&lt;/code&gt; if you expect this error will make a difference.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-07-28T03:05:00.943" LastActivityDate="2020-07-28T03:05:00.943" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1784" PostTypeId="1" CreationDate="2020-07-28T02:15:20.000" Score="7" ViewCount="309" Body="&lt;p&gt;From Statistical Mechanics obtain an expression for the heat capacity of a solid is given by&lt;sup&gt;1&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\tag{1}&#xA;{C_V}\left( T \right) = k\int\limits_0^\infty  {\frac{{{{\left( {uv} \right)}^2}{e^{uv}}}}{{{{\left( {{e^{uv}} - 1} \right)}^2}}}g\left( v \right)dv}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$u=h/kT$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt;: Plank constant, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; Boltzmann constant, &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;: temperature) and &lt;span class=&quot;math-container&quot;&gt;$g(v)$&lt;/span&gt; is the phonon density of states distribution.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;Is it possible to calculate &lt;span class=&quot;math-container&quot;&gt;$g(v)$&lt;/span&gt; using Density Functional Theory?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;C. A. Tavares, &lt;em&gt;et al&lt;/em&gt;. &lt;em&gt;Solving ill-posed problems faster using fractional-order Hopfield neural network&lt;/em&gt;. J. Comp. Appl. Math. 381 112984 (2021) (DOI: &lt;a href=&quot;http://dx.doi.org/10.1016/j.cam.2020.112984&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cam.2020.112984&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-28T18:39:21.303" Title="Obtaining phonon density of states from Density Functional Theory" Tags="|density-functional-theory|phonons|phonon-density-of-state|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1785" PostTypeId="2" ParentId="1778" CreationDate="2020-07-28T02:29:11.060" Score="5" Body="&lt;p&gt;You are right in that the Work function (the term is more pertinent to metals in my opinion) or Ionization energy (a generic term) can be calculated as:&#xA;E&lt;sub&gt;vac&lt;/sub&gt; - E&lt;sub&gt;HOMO&lt;/sub&gt;. You can calculate the vacuum level in most DFT packages by doing a calculation for the average electrostatic potential in vacuum. This obviously makes sense only for a 2-D material (in bulk, the potential would just be asymptotic with out-of-plane distance).&lt;/p&gt;&#xA;&lt;p&gt;For a vacuum calculation, you don't need to consider the bulk material at all. You can easily reconcile this because the work-function in the simplest texts is defined as removing an electron from the surface. You can just calculate the electrostatic potential for a range of out-of-plane distances and make sure it saturates ( if the vacuum is thick enough, this should not be a problem). In my experience, I've seen many papers on materials where the potential starts saturating for a distance of 0.1 nm (which is the minimum recommended vacuum in DFT calculations typically).&lt;/p&gt;&#xA;&lt;p&gt;Edits: There is a slight distinction between E&lt;sub&gt;Fermi&lt;/sub&gt; and E&lt;sub&gt;HOMO&lt;/sub&gt;. For semiconductors, at 0 K, the Fermi level is ill-defined. Can lie anywhere in the gap. But in literature, people plot bandstructures with Valence band maximum aligned to zero.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="5" LastEditDate="2020-07-28T02:39:43.603" LastActivityDate="2020-07-28T02:39:43.603" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1786" PostTypeId="1" CreationDate="2020-07-28T02:48:59.033" Score="13" ViewCount="165" Body="&lt;p&gt;According to &lt;a href=&quot;https://en.wikipedia.org/wiki/Volunteer_computing&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Volunteer computing is a type of distributed computing in which people donate their computers' unused resources to a research-oriented project&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;An example of a volunteer computing project is &lt;a href=&quot;https://setiathome.berkeley.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SETI@home&lt;/a&gt; (for extraterrestrial intelligence search, -hibernating now-).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can people here please explain the such projects in Matter Modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Active:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://setiathome.berkeley.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Folding@home&lt;/a&gt; [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1835/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://boinc.bakerlab.org/rosetta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rosetta@home&lt;/a&gt; [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6484/653&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;li&gt;Cleanmobility.now&lt;/li&gt;&#xA;&lt;li&gt;RNA World&lt;/li&gt;&#xA;&lt;li&gt;CAS@home&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.scienceathome.org/about-us/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ScienceAtHome&lt;/a&gt; [&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1840/5&quot;&gt;link to answer&lt;/a&gt;]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Inactive:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Genome@home&lt;/li&gt;&#xA;&lt;li&gt;POEM@Home&lt;/li&gt;&#xA;&lt;li&gt;SIMAP&lt;/li&gt;&#xA;&lt;li&gt;DENIS@Home&lt;/li&gt;&#xA;&lt;li&gt;USPEX@Home&lt;/li&gt;&#xA;&lt;li&gt;eOn&lt;/li&gt;&#xA;&lt;li&gt;Leiden Classical&lt;/li&gt;&#xA;&lt;li&gt;QMC@Home&lt;/li&gt;&#xA;&lt;li&gt;Magnetism@home&lt;/li&gt;&#xA;&lt;li&gt;SLinCA&lt;/li&gt;&#xA;&lt;li&gt;DrugDiscovery@home&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="653" LastEditDate="2021-08-01T08:28:42.233" LastActivityDate="2021-08-01T08:28:42.233" Title="Citizen science projects in Matter Modeling" Tags="|one-topic-per-answer|high-performance-computing|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1787" PostTypeId="2" ParentId="1766" CreationDate="2020-07-28T02:53:59.923" Score="4" Body="&lt;p&gt;Absolute energy values (or more specifically, the Kohn-Sham eigenvalues) that you obtain from KS-DFT calculations are meaningless. You are right in that one could do a vacuum calculation in DFT and align the band-structure with respect to vacuum. The electronic band-gap that you obtain however, is still underestimated, as you mentioned (in KS-DFT). If your question is with regard to how much error is usually incurred in calculation of bandgaps, it depends on your system but it is definitely significant and there are many sources in literature that you could refer to.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, if your question is with regard to how much error is incurred in calculation of the HOMO or LUMO, the error is not as significant typically. Let's assume you want to calculate the ionization energy ( as E&lt;sub&gt;vacuum&lt;/sub&gt; - E&lt;sub&gt;HOMO&lt;/sub&gt; ). I can't seem to find a comprehensive study of the efficacy of Ionization energy calculations in KS-DFT but &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3491272?journalCode=jcp&quot; rel=&quot;nofollow noreferrer&quot;&gt;this is a good starting point&lt;/a&gt; on the nuances involved in such a calculation - delving into the validity of Koopman's theorem etc. From what I have personally encountered, errors in ionization energy of up to 0.5 eV are not uncommon. A GW quasiparticle calculation can give you a better, more reliable estimate in this case. But this is certainly on the lesser side of the scale if you compare electronic band-gaps.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-07-28T02:53:59.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1788" PostTypeId="2" ParentId="1203" CreationDate="2020-07-28T03:34:18.127" Score="6" Body="&lt;p&gt;For reasons that may be apparent from the plots you show in the question, complicated band structures are often referred to as spaghetti. It can be difficult to know what individual bands represent, and to form an intuition for them. However, if we calculate the projection of individual bands onto some orbital (often atomic s,p,d,f orbitals) and plot that, we may get a better understanding of the system. A projected density of states (PDOS) plot has essentially the same idea behind it, but for fatbands we show the projections as functions of both momentum and energy. I believe the projection onto orbitals with different angular momentum (&lt;span class=&quot;math-container&quot;&gt;$l=0,1,2,...$&lt;/span&gt;) was traditionally represented with the line width, which resulted in thick (or &amp;quot;fat&amp;quot;) bands and the &amp;quot;fatband&amp;quot; moniker. However, with the reduced importance of print journals, encoding this projection information with color instead of line width seems to have become common.&lt;/p&gt;&#xA;&lt;p&gt;For an illustration using bulk silver, and some discussion on how to calculate fatbands using the ELK and QuantumEspresso codes, see this post on &lt;a href=&quot;https://christoph-wolf.at/2018/07/24/from-fatbands-to-wannier-functions-of-silver/&quot; rel=&quot;noreferrer&quot;&gt;Christoph Wolf's blog&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-28T03:34:18.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1789" PostTypeId="1" AcceptedAnswerId="1795" CreationDate="2020-07-28T04:02:12.233" Score="7" ViewCount="432" Body="&lt;p&gt;I am aware that there exists a flowchart about how to determine the point group of a molecule with a given geometry, such as given in the diagram available in&#xA;&lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Book%3A_Symmetry_(Vallance)/03._Symmetry_Classification_of_Molecules%3A_Point_groups&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemLibre Texts&lt;/a&gt;. If we just look at the geometry visually or having it pictured in mind, it wouldn't be difficult to follow this flowchart. But I would like to automate this procedure inside my electronic-structure code.&lt;/p&gt;&#xA;&lt;p&gt;Is there a well-established computational method to determine, e.g. how many rotational axes of symmetry a molecule has? Is it possible to perform this identification generally, that is, in a way in which I don't need to write a function or routine dedicated for each symmetry type? References are much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1121" LastEditorUserId="52" LastEditDate="2020-07-28T19:39:50.083" LastActivityDate="2020-07-28T19:39:50.083" Title="Are there computational methods for the determination of the point group symmetry of a molecule of a given geometry?" Tags="|space-groups|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1790" PostTypeId="1" CreationDate="2020-07-28T04:03:27.237" Score="16" ViewCount="3569" Body="&lt;p&gt;I'm interested in doing molecular docking. What are some free programs for it and what are their pros and cons?&lt;/p&gt;&#xA;" OwnerUserId="1146" LastEditorUserId="5" LastEditDate="2020-07-28T04:06:01.760" LastActivityDate="2022-07-25T18:51:18.727" Title="What are some free programs to do docking?" Tags="|software|one-topic-per-answer|open-source|docking|" AnswerCount="8" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1791" PostTypeId="1" CreationDate="2020-07-28T04:09:13.953" Score="16" ViewCount="1804" Body="&lt;p&gt;Calculation of band structure and Density of States (DOS) is ubiquitous in matter modelling research publications.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are some properties that can be deduced from a band structure plot and density of states diagram? Also if possible explain how to deduce them?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-07-28T04:12:52.877" LastActivityDate="2021-03-20T07:17:48.943" Title="Properties that can be deduced from Band structure and DOS" Tags="|electronic-structure|band-structure|density-of-states|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1792" PostTypeId="2" ParentId="1597" CreationDate="2020-07-28T04:36:44.697" Score="5" Body="&lt;p&gt;Assuming that the structure starts from one symmetry and you distort it into another, VASP will want to find the symmetry it expects and use it.  One straightforward way to fix this problem while also increasing the chance of finding the actual minima is to break the symmetry yourself.&lt;/p&gt;&#xA;&lt;p&gt;One way to do this is to randomly displace atoms by a small amount.  This can be done using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; with the rattle command.  By randomly displacing the structure a few times you can also ensure that random minor numerical noise doesn't result in relaxing into one structure versus another.  If you are expecting large displacements, you might find that the structure relaxes to different configurations depending on how they are rattled.  This is a very manual and very primitive global relaxation method but works quite well when you start from a good guess.&lt;/p&gt;&#xA;&lt;p&gt;Here is a simple python script that would allow you to rattle atoms on the command line using ASE.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#! /usr/bin/env python&#xA;from ase import Atoms&#xA;from sys import argv&#xA;from ase.io import read, write&#xA;import random&#xA;&#xA;file = argv[1]&#xA;rattle_amount = float(argv[2])&#xA;atoms = read(file)&#xA;atoms.rattle(rattle_amount, seed=int(random.uniform(0,2000)))&#xA;write(file, atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This can be used as follows (with any file format ASE supports).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python rattle.py bulk_structure.POSCAR 0.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-07-28T04:36:44.697" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1793" PostTypeId="1" AcceptedAnswerId="1950" CreationDate="2020-07-28T04:57:08.600" Score="11" ViewCount="1096" Body="&lt;p&gt;What modern software supports the generation of LEED patterns?  It seems most LEED simulation packages are quite old and do not work on modern hardware.  Is there something that prevents common software like VASP from simulating LEED or is it just not implemented?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="35" LastEditDate="2020-08-16T12:12:11.840" LastActivityDate="2020-08-16T12:12:11.840" Title="Simulated low energy electron diffraction (LEED) patterns" Tags="|software|vasp|diffraction|electron-diffraction|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1794" PostTypeId="2" ParentId="1782" CreationDate="2020-07-28T05:32:36.153" Score="6" Body="&lt;p&gt;The figure you are showing can be made in Adobe Illustrator or Gimp&lt;/p&gt;&#xA;&lt;p&gt;I've recreated a crude rendition (very quickly) using adobe illustrator&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Z7LVU.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Z7LVU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The steps to get this far are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;create a sphere&lt;/li&gt;&#xA;&lt;li&gt;cut the sphere in half with pathfinder divider tool&lt;/li&gt;&#xA;&lt;li&gt;Revolve the half sphere with the 3d effect&lt;/li&gt;&#xA;&lt;li&gt;in the revolve menu select Wireframe surface&lt;/li&gt;&#xA;&lt;li&gt;in the revolve menu select map art (this is how I got the blue colors to add). I used the process rectangle &amp;quot;symbol&amp;quot;. I used two surfaces, the 1st and 4th. because those showed up how I wanted them too (I'm not sure if this is the best way).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The arrows can be added in and &amp;quot;revolved and beveled&amp;quot; to get them in the proper orientation.&lt;/p&gt;&#xA;&lt;p&gt;For more information you should probably seek help on the Adobe illustrator Stack Exchange.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-28T05:43:46.740" LastActivityDate="2020-07-28T05:43:46.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1795" PostTypeId="2" ParentId="1789" CreationDate="2020-07-28T06:25:18.593" Score="5" Body="&lt;p&gt;In order to get this question answered there are a variety of algorithms for determining symmetry.&lt;/p&gt;&#xA;&lt;p&gt;Here is what I've found&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://pubs.acs.org/doi/10.1021/ci990322q&quot; rel=&quot;noreferrer&quot;&gt;Simple Algorithms for Determining the Molecular Symmetry&lt;/a&gt; -- not open access&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.degruyter.com/view/journals/chem/3/4/article-p647.xml&quot; rel=&quot;noreferrer&quot;&gt;New computer program to calculate the symmetry of Molecules&lt;/a&gt; -- open access and with some matlab code snippets&lt;/p&gt;&#xA;&lt;p&gt;I've also found this link to a &lt;a href=&quot;https://www.researchgate.net/post/Is_there_any_software_that_can_help_to_identify_the_symmetry_of_different_molecules&quot; rel=&quot;noreferrer&quot;&gt;Researchgate page&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This lists software that can identify the symmetry for you including:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;chemcraft&lt;/li&gt;&#xA;&lt;li&gt;GaussView&lt;/li&gt;&#xA;&lt;li&gt;symmol&lt;/li&gt;&#xA;&lt;li&gt;3dmolsym&lt;/li&gt;&#xA;&lt;li&gt;Jmol&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Symmol was linked to &lt;a href=&quot;http://www.ccp14.ac.uk/ccp/web-mirrors/symmol/%7Epila/&quot; rel=&quot;noreferrer&quot;&gt;the source code&lt;/a&gt; so if you can read Fortran you could translate their algorithms to suit your own needs.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-07-28T06:25:18.593" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1796" PostTypeId="2" ParentId="1779" CreationDate="2020-07-28T06:54:46.713" Score="6" Body="&lt;p&gt;Let &lt;span class=&quot;math-container&quot;&gt;$u_{pi\alpha}$&lt;/span&gt; be the displacement of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; in the basis located in supercell with position &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt; and in Cartesian direction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. With this &amp;quot;Cartesian&amp;quot; description of the motion of the atoms, it then becomes very simple to understand whether an atom moves out of plane (zero amplitude &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; components), or in plane (zero amplitude &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; component), or in any other direction you may be interested in. So how do you figure out these &lt;span class=&quot;math-container&quot;&gt;$u_{pi\alpha}$&lt;/span&gt; displacements for a given phonon mode?&lt;/p&gt;&#xA;&lt;p&gt;A phonon mode is labelled by quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; is the momentum and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; the branch index. This phonon is characterized by a frequency &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; and eigenvector &lt;span class=&quot;math-container&quot;&gt;$v_{\mathbf{q}\nu;i{\alpha}}$&lt;/span&gt;, which are obtained by diagonalizing the dynamical matrix (I outlined these calculations in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;answer&lt;/a&gt;). Phonon modes provide an alternative basis in which you can characterize the motion of the atoms in the system by the so-called normal modes, of amplitude &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{q}\nu}$&lt;/span&gt;. These correspond to &amp;quot;collective&amp;quot; motions of atoms, which have the advantage that lead to a Hamiltonian that is a set of uncoupled simple harmonic oscillators (so very beneficial computationally), but the motion is not always easy to see.&lt;/p&gt;&#xA;&lt;p&gt;The general formula relating the normal modes coordinates and the Cartesian coordinates is (again, see my answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;here&lt;/a&gt; for further details):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;u_{pi\alpha}=\frac{1}{\sqrt{N_pm_{\alpha}}}\sum_{\mathbf{q},\nu}u_{\mathbf{q}\nu}e^{i\mathbf{q}\cdot\mathbf{R}_p}v_{\mathbf{q}\nu;i\alpha},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N_p$&lt;/span&gt; is the number of primitive cells in the periodic supercells and &lt;span class=&quot;math-container&quot;&gt;$m_{\alpha}$&lt;/span&gt; is the mass of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. Therefore, what you want to do once you have found the phonon frequencies and eigenvectors is to pick a particular phonon mode &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{q},\nu)$&lt;/span&gt; and calculate what the corresponding &lt;span class=&quot;math-container&quot;&gt;$u_{pi\alpha}$&lt;/span&gt; is. In the equation above, this means that all &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{q}\nu}$&lt;/span&gt; apart from the one corresponding to the mode you are interested in will be zero.&lt;/p&gt;&#xA;&lt;p&gt;Most codes that calculate phonons will have some way of directly outputting the Cartesian atomic displacements &lt;span class=&quot;math-container&quot;&gt;$u_{pi\alpha}$&lt;/span&gt; so that you can directly visualize them.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-07-28T07:01:11.377" LastActivityDate="2020-07-28T07:01:11.377" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1797" PostTypeId="2" ParentId="1741" CreationDate="2020-07-28T07:50:37.287" Score="4" Body="&lt;p&gt;Topological semimetals &lt;em&gt;do&lt;/em&gt; have interesting edge states. Here I give two examples:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Weyl semimetals. The edge states are called &amp;quot;Fermi arcs&amp;quot;, which are constant-energy states that connect the projections of the Weyl points onto the surface. The &lt;a href=&quot;https://en.wikipedia.org/wiki/Weyl_semimetal#/media/File:Weyl_Balents.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia article&lt;/a&gt; has a very nice depiction of Fermi arcs.&lt;/li&gt;&#xA;&lt;li&gt;Nodal line semimetals. The edge states are called &amp;quot;drumhead states&amp;quot;, and again are relatively flat states that are contained within the projection of the bulk nodal line onto the surface.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Standard packages to calculate topological properties typically have the appropriate functionality to calculate these surface states of semimetals. For example, here is the descprition from &lt;a href=&quot;http://www.wanniertools.com/features.html#sscalculation&quot; rel=&quot;nofollow noreferrer&quot;&gt;WannierTools&lt;/a&gt;, which uses a Green's function approach.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-28T07:50:37.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1798" PostTypeId="2" ParentId="1646" CreationDate="2020-07-28T08:01:46.440" Score="8" Body="&lt;p&gt;Neighbour lists are not just a feature of LAMMPS, but of just about any MD engine out there. When you are evaluating your energy function, it is extremely common to have some sort of cutoff for the short-range forces, so that you reduce the complexity of their evaluation from e.g. &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$O(N)$&lt;/span&gt;. However, simply checking whether two atoms are within a cutoff distance is also an &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; operation, so it's not something you want to do at each timestep. Here's where neighbour lists come to the rescue: you build a list containing each particle's neighbours within a cutoff &lt;span class=&quot;math-container&quot;&gt;$r_n$&lt;/span&gt;, which means that as long as you are sure the particles haven't moved a distance greater than &lt;span class=&quot;math-container&quot;&gt;$r_n-r_{cut}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$r_{cut}$&lt;/span&gt; is the force evaluation cutoff), you only need to check the force interactions in that neighbour list, which is a massive upgrade from having to check all interactions!&lt;/p&gt;&#xA;&lt;p&gt;And here's the catch: if your &lt;span class=&quot;math-container&quot;&gt;$r_n-r_{cut}$&lt;/span&gt; (also called a &amp;quot;skin&amp;quot; region, your first argument) is large, you will need to build the neighbour list less frequently, but you will need to check more force interactions within each neighbour list. This means that there will be an optimal value of the skin region for achieving maximum computational efficiency but it will unfortunately be system-specific and in some systems even coordinate-specific (e.g. if some parts of your system diffuse faster, they will require faster updates). This is difficult to know &lt;em&gt;a priori&lt;/em&gt;, so you either have to guess a good value beforehand, or even spend some time optimising it by hand for a typical system of yours, so that you use that hand-tuned value for all subsequent simulations.&lt;/p&gt;&#xA;&lt;p&gt;The second argument is, as far as I understand, related to the building of the neighbour list itself. Naively building a neighbour list from scratch is also an &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; operation (Verlet list), but you can do a similar trick and create something like a &amp;quot;neighbour list of neighbour lists&amp;quot;, i.e. you partition your box into regions, each roughly as big as one neighbour list region, and bin each particle (an &lt;span class=&quot;math-container&quot;&gt;$O(N)$&lt;/span&gt; operation) to each cell region. After a neighbour list update is triggered, you only need to consider particles from the cell regions immediately surrounding your current one in order to do this, so this is also an &lt;span class=&quot;math-container&quot;&gt;$O(N)$&lt;/span&gt; operation. This whole method is called a cell list and is usually the preferred way to update a neighbour list. This is what I think the second parameter (&amp;quot;style&amp;quot;) does &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt; I imagine &amp;quot;bin&amp;quot; value stands for a cell list update, while the &amp;quot;nsq&amp;quot; value stands for a naive &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; update.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-07-28T08:01:46.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1799" PostTypeId="2" ParentId="1698" CreationDate="2020-07-28T08:28:38.320" Score="8" Body="&lt;p&gt;The presence of imaginary frequencies in a phonon dispersion can have two sources:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Physical origin. If the imaginary frequency appears at a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point in the Brillouin zone that is included in the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid that you explicitly calculate (e.g. one of the points in the &lt;span class=&quot;math-container&quot;&gt;$N\times N\times N$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid if you use a supercell of size &lt;span class=&quot;math-container&quot;&gt;$N\times N\times N$&lt;/span&gt;), then this means that the imaginary frequency is &lt;em&gt;physical&lt;/em&gt;. This is telling you that your structure is not at a local minimum of the potential energy landscape, but instead at a saddle point, and there is a lower energy structure that you should be using instead. So what do you have to do to find this lower energy structure? You have to distort your original structure along the wave vector associated with the imaginary mode to find the real minimum. A previous &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;discussion&lt;/a&gt; went into some detail about how to do this.&lt;/li&gt;&#xA;&lt;li&gt;Underconvergence. If the imaginary frequency appears at a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point in the Brillouin zone that is &lt;em&gt;not&lt;/em&gt; included in the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid that you explicitly calculate, then this may be because of underconvergence. When you plot a phonon dispersion you perform a Fourier interpolation over the grid that you explicitly calculate to obtain phonon frequencies at other points in the Brillouin zone that you don't explicitly calculate. This interpolation may introduce spurious imaginary modes if your explicitly calculated &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid is not large enough. In this case, the solution is to perform more calculations at larger &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grids (larger supercells) until either the imaginary frequencies go away, or you can confirm that they are actually physical by explicitly including them in your direct calculation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;So why may you get imaginary frequencies in the bilayer when you didn't get them in the monolayer? For case 1 above, this may be caused by the way in which you constructed the bilayer. If you simply made a copy of the monolayer and placed it next to the original monolayer, then it may be that the interaction between the two layers means that your individual layers want to distort. In this case, the imaginary frequency is telling you which way to distort to get to the energy minimum. For case 2 above, it could be that a converged &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid for the monolayer is not converged for the bilayer, which may very well happen in the out-of-plane direction.&lt;/p&gt;&#xA;&lt;p&gt;Your other question was about using phonons with van der Waals interactions. But this question can be made more general: with what level of theory can phonons be calculated? The answer depends on the method you use to calculate phonons. For finite difference methods: if you can calculate forces, then you can also calculate phonons. As forces are typically available, then you can calculate phonons with most methods using finite differences. If you instead use density functional perturbation theory, here you are limited to the actual implementation that a given code has. For phonons, this is typically restricted to semilocal functionals.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-28T08:28:38.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1800" PostTypeId="1" CreationDate="2020-07-28T09:28:58.720" Score="9" ViewCount="169" Body="&lt;p&gt;How can we know that the non-trivial band topology in a system is driven by spin-orbit coupling (SOC) or by band inversion?&lt;/p&gt;&#xA;&lt;p&gt;Based on my understanding, SOC causes the band inversion and makes the system non-trivial, but I would like to make sure that my understanding is correct.&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2020-08-30T21:54:16.353" LastActivityDate="2020-08-30T21:54:16.353" Title="Is the non-trivial band topology in a system, caused by spin-orbit-coupling or band inversion?" Tags="|density-functional-theory|band-structure|solid-state-physics|topological-insulators|spin-orbit-coupling|" AnswerCount="0" CommentCount="5" ClosedDate="2021-03-19T16:21:25.693" ContentLicense="CC BY-SA 4.0" />
  <row Id="1801" PostTypeId="2" ParentId="1684" CreationDate="2020-07-28T09:29:37.620" Score="4" Body="&lt;p&gt;Boy, you're not starting off easy. Proper implementation of symmetry is quite a job, especially since most systems of interest nowadays have no symmetry.&lt;/p&gt;&#xA;&lt;p&gt;For a reference, you can look at e.g. Dovesi's work on the use of symmetry in CRYSTAL, which is a periodic Hartree-Fock code using Gaussian orbitals. Symmetry is much more important in the periodic case, since the periodic packing introduces many more symmetries than in molecules. However, at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point (&lt;span class=&quot;math-container&quot;&gt;${\bf k}={\bf 0}$&lt;/span&gt;) you're essentially reduced to molecular symmetry. (CRYSTAL can use symmetry with periodic boundaries in 0, 1, 2, or 3 dimensions for molecules, rods, planes, and crystalline systems.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.560290608&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem 29, 1755 (1986)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-28T09:29:37.620" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1803" PostTypeId="2" ParentId="1776" CreationDate="2020-07-28T11:32:06.037" Score="6" Body="&lt;p&gt;This sounds like a very standard problem for multiphysics applications. The oven is comprised of a heating element, insulation, and argon gas inside it. You will have both radiative and convective transfer of heat inside the oven, and you'll need to model both to find out how the temperature distribution develops. &lt;a href=&quot;https://www.comsol.fi/paper/multiphysics-approach-of-the-performance-of-a-domestic-oven-15478&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; is a demonstration of COMSOL for a conventional oven, which is the same problem in principle.&lt;/p&gt;&#xA;&lt;p&gt;However, simulations might not be the best answer, since you would need to know your oven very accurately in order to set up the simulations correctly. Easier options would probably be putting in more thermocouples or other instruments so that you can track the development of the temperature around the oven. A heat camera might also be an option.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-07-28T13:12:52.107" LastActivityDate="2020-07-28T13:12:52.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1804" PostTypeId="2" ParentId="1684" CreationDate="2020-07-28T11:32:52.700" Score="9" Body="&lt;p&gt;First, you have to transform all the basis functions into the irreducible representations (irreps) of the point group of the molecule. You can do this with standard projection formulas.&lt;/p&gt;&#xA;&lt;p&gt;Once, you know the irreps of the basis functions, you have to look at the product table of the point group to find out whether the product of those four basis functions contains the totally symmetric irrep. If it does, then the integral has to be computed. Otherwise you know it is vanishing.&lt;/p&gt;&#xA;&lt;p&gt;I think a good reference is Albert Cotton's &amp;quot;Chemical Applications of Group Theory&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-07-28T11:32:52.700" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1806" PostTypeId="2" ParentId="1790" CreationDate="2020-07-28T11:56:42.960" Score="11" Body="&lt;h2&gt;CDOCKER&lt;/h2&gt;&#xA;&lt;p&gt;CDOCKER is docking program developed by the &lt;a href=&quot;https://brooks.chem.lsa.umich.edu/&quot; rel=&quot;noreferrer&quot;&gt;Brooks Lab&lt;/a&gt; and it works with CHARMM. CHARMM does have a free version named &lt;a href=&quot;https://www.charmm.org/charmm/showcase/news/free-charmm/&quot; rel=&quot;noreferrer&quot;&gt;charmm&lt;/a&gt;. The difference is no DOMDEC or GPU high performance modules.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros&lt;/strong&gt;: Rigid and flexible receptors, highly customizable&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons&lt;/strong&gt;: Need to get free charmm, creating scripts can sometimes be laborious, no high performance GPU modules&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1002/jcc.10306&quot; rel=&quot;noreferrer&quot;&gt;Wu, G.; et al. J. Comput. Chem. 2003, 24, 1549-1562.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://dx.doi.org/10.1002%2Fjcc.24259&quot; rel=&quot;noreferrer&quot;&gt;Gagnon, J. K.; et al. J. Comput. Chem. 2016, 753-762.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="24" LastEditDate="2020-07-28T16:49:38.697" LastActivityDate="2020-07-28T16:49:38.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1807" PostTypeId="1" AcceptedAnswerId="1819" CreationDate="2020-07-28T12:50:24.307" Score="5" ViewCount="514" Body="&lt;p&gt;For relaxation of transition metal dichalcogenides (e.g.: WS2) using the VASP code, what is the best choice for vdW correction method (e.g.: DFT-D2, DFT-D3 or optB88-vdW) that can give you good results ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2020-08-07T17:51:21.000" LastActivityDate="2020-08-07T17:51:21.000" Title="Best vdW correction functional for transition metal dichalcogenides" Tags="|density-functional-theory|vasp|ab-initio-calculations|dispersion-correction|dichalcogenides|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1808" PostTypeId="1" AcceptedAnswerId="1873" CreationDate="2020-07-28T12:59:49.767" Score="9" ViewCount="1100" Body="&lt;p&gt;Taking a bulk WS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; (bilayer) structure and relaxing it with &lt;code&gt;ISIF=3&lt;/code&gt; and &lt;code&gt;IVDW=10&lt;/code&gt; (DFT-D2 method) using the VASP code. Then opening this structure with VESTA software. Are the shown &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; lattice constants the optimized ones? Or is there something else that must be done to extract them?&#xA;Here is the CONTCAR of the relaxed structure:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;W2S4-D2                                    &#xA;   1.00000000000000     &#xA;     3.1894907296110424   -0.0000000015017362    0.0000000000000000&#xA;    -1.5947448663004180    2.7621798956603310   -0.0000000000000000&#xA;    -0.0000000000000000   -0.0000000000000000   12.1495560778044602&#xA;   W    S &#xA;     2     4&#xA;Direct&#xA;  0.3333330000000032  0.6666669999999968  0.2500000000000000&#xA;  0.6666669999999968  0.3333330000000032  0.7500000000000000&#xA;  0.3333330000000032  0.6666669999999968  0.6212727769502864&#xA;  0.6666669999999968  0.3333330000000032  0.1212727769502864&#xA;  0.3333330000000032  0.6666669999999968  0.8787272230497136&#xA;  0.6666669999999968  0.3333330000000032  0.3787272230497136&#xA; &#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2020-07-31T12:32:25.893" LastActivityDate="2021-05-28T15:01:50.020" Title="How to extract lattice constants a and c from relaxed hexagonal structure using VASP?" Tags="|density-functional-theory|vasp|optimization|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1809" PostTypeId="1" AcceptedAnswerId="1812" CreationDate="2020-07-28T13:04:51.047" Score="7" ViewCount="1030" Body="&lt;p&gt;The method that I am following in creating a hexagonal lattice POSCAR file is by downloading it from &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;https://materialsproject.org/&lt;/a&gt; website. Now, I want to learn how to create it manually starting from given information in an article. Could someone of you give me a detailed method to do that?&#xA;Please be detailed and thank you in advance for devoting time to read and answer this question.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2020-07-28T13:16:56.347" Title="How to create a POSCAR for hexagonal structure for VASP calculations?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1810" PostTypeId="1" AcceptedAnswerId="1818" CreationDate="2020-07-28T13:06:50.717" Score="8" ViewCount="390" Body="&lt;p&gt;I have seen that in many articles of 2D materials calculations that VASP is the most used one among DFT codes. Could please explain to me why?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="52" LastEditDate="2020-07-29T02:22:54.607" LastActivityDate="2020-07-29T02:22:54.607" Title="Why is VASP so popular for 2D materials?" Tags="|density-functional-theory|vasp|2d-lattice|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1811" PostTypeId="2" ParentId="1051" CreationDate="2020-07-28T13:14:28.850" Score="1" Body="&lt;p&gt;First of all, thanks to everyone who contributed to answer and discuss this question, your responses helped me to found the solution. Which is the vdW correction was missing in my calculations. Since that WS2 is a layered material, vdW interlayer correction must be added. So, I have added IVDW=10 in INCAR file to include the DFT-D2 method and this gaves me good results.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2020-07-28T13:14:28.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1812" PostTypeId="2" ParentId="1809" CreationDate="2020-07-28T13:16:56.347" Score="4" Body="&lt;p&gt;You can use the software VESTA to create the structure as mentioned &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/409/88&quot;&gt;here&lt;/a&gt; and export the structure to POSCAR&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-07-28T13:16:56.347" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1813" PostTypeId="1" CreationDate="2020-07-28T13:18:26.920" Score="9" ViewCount="104" Body="&lt;p&gt;I am seeking some models or references on how to couple, or what to take into consideration, while coupling first-order phase transitions (for magnetic systems) and second-order phase transitions, in regards to order and disorder in these systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41567-018-0201-1?proof=true19#article-info&quot; rel=&quot;nofollow noreferrer&quot;&gt;This is an example of such a system&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="298" LastEditorUserId="5" LastEditDate="2020-07-28T20:29:06.577" LastActivityDate="2020-07-28T20:29:06.577" Title="Coupling between 1st and 2nd order phase transitions?" Tags="|reference-request|ising-model|monte-carlo|statistical-thermodynamics|phase-transitions|" AnswerCount="0" CommentCount="2" ClosedDate="2021-04-25T03:32:18.260" ContentLicense="CC BY-SA 4.0" />
  <row Id="1814" PostTypeId="2" ParentId="1728" CreationDate="2020-07-28T13:20:18.063" Score="6" Body="&lt;p&gt;I should start by saying that I am no expert in MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, so this answer is my guess from looking at the reference you provide, and would be happy if someone corrects me.&lt;/p&gt;&#xA;&lt;p&gt;The general things to keep in mind when looking at such band structures are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;If the system has time reversal symmetry, then if there is an electron with quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{k},\uparrow)$&lt;/span&gt;, then there is another electron with quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(-\mathbf{k},\downarrow)$&lt;/span&gt; with the same energy.&lt;/li&gt;&#xA;&lt;li&gt;If the system has inversion symmetry, then if there is an electron with quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{k},\uparrow)$&lt;/span&gt;, then there is another electron with quantum numbers &lt;span class=&quot;math-container&quot;&gt;$(-\mathbf{k},\uparrow)$&lt;/span&gt; with the same energy.&lt;/li&gt;&#xA;&lt;li&gt;If the system has &lt;em&gt;both&lt;/em&gt; time reversal and inversion symmetry, then both conditions above apply, which together mean that each electron state is doubly degenerate.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Therefore, to have splitting of energies between electrons of opposite spins, we need to break one of the two symmetries above. In MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, the symmetry that is broken is inversion symmetry. However, inversion symmetry breaking &lt;em&gt;per se&lt;/em&gt; is not enough to split the bands energetically, you also need a spin-dependent term in the Hamiltonian. This is provided by the spin-orbit interaction.&lt;/p&gt;&#xA;&lt;p&gt;Based on these general comments, this is my guess for what happens in the diagram you sent:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Green valleys.&lt;/strong&gt; The green valleys correspond to the conduction band. Although the system breaks inversion symmetry, the spin-orbit coupling in these bands is very weak, so to a good approximation there is no energy splitting of electrons of opposite spin, so the green valleys are doubly-degenerate.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Red and blue valleys.&lt;/strong&gt; These valleys correspond to the valence band. Spin-orbit coupling is strong for these bands, so together with inversion symmetry breaking they lead to a splitting of bands with opposite spin (the blue bands are spin &amp;quot;down&amp;quot; and the red bands spin &amp;quot;up&amp;quot;). However, time reversal symmetry is still present, so property 1 above still needs to be obeyed. To see what the implications of this are, let the two energies in valley K be &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$E_2&amp;gt;E_1$&lt;/span&gt;. This means that the up electron (red) has energy &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt;, and the down electron (blue) has energy &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; at K. Time reversal symmetry then says that there is another electron at &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt;K with energy &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt; but with opposite spin to the electron with energy &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt; in K (so down electron, blue). Similarly, the &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; down electron at K has a time reversal partner at &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt;K with the same energy but up spin. Hence, at &lt;span class=&quot;math-container&quot;&gt;$-$&lt;/span&gt;K the colors switch.&lt;/p&gt;&#xA;&lt;p&gt;This discussion assumes that the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;-component of spin is a good quantum number (so I can say &amp;quot;up&amp;quot; and &amp;quot;down&amp;quot;). This is not strictly true when spin-orbit coupling is present, because now we need to consider the total angular moment (sum of spin and orbital components). However, in many systems spin is very close to a good quantum number, so we allow for this language.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-28T13:20:18.063" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1815" PostTypeId="1" AcceptedAnswerId="1858" CreationDate="2020-07-28T13:29:48.993" Score="7" ViewCount="127" Body="&lt;p&gt;Is &lt;a href=&quot;https://vallico.net/casinoqmc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASINO&lt;/a&gt; code capable of performing orbital-space QMC calculations?&lt;/p&gt;&#xA;" OwnerUserId="207" LastEditorUserId="5" LastEditDate="2020-07-30T14:32:51.573" LastActivityDate="2020-07-30T14:32:51.573" Title="Support for orbital-space Quantum Monte Carlo in CASINO?" Tags="|electronic-structure|quantum-monte-carlo|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1816" PostTypeId="2" ParentId="1771" CreationDate="2020-07-28T14:17:35.413" Score="8" Body="&lt;p&gt;Let's give it another go: In the monolayer you would place the inversion centre on the green atom. But this would reverse the direction of the trigonal prism formed by the yellow atoms. Hence, there can't be an inversion centre.&lt;/p&gt;&#xA;&lt;p&gt;In the bilayer the inversion centre is between the layers. Then the direction of the trigonal prism is reversed but it is also translated into a different layer, which is arranged in the proper way. Placing an inversion centre between layers is only possible if you have an even number of layers.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-07-28T14:17:35.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1817" PostTypeId="2" ParentId="1684" CreationDate="2020-07-28T14:53:34.893" Score="14" Body="&lt;p&gt;The question is too broad to be answered directly so I will provide a somewhat general scheme.&lt;/p&gt;&#xA;&lt;p&gt;Basically in an integral like&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\int  d\mu A B C&#xA;$$&lt;/span&gt;&#xA;one would seek to expand each part in irreducible representations of a given group, say for instance&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;B=\frac{1}{\vert \mathbf{r}-\mathbf{r}^\prime\vert}&#xA;=\frac{1}{r} \sum_{\ell} \left(\frac{r'}{r}\right)^\ell \sqrt{\frac{4\pi}{2\ell+1}}Y^{\ell}_0(\theta,\varphi)&#xA;\end{align}&lt;/span&gt;&#xA;where here the group would be &lt;span class=&quot;math-container&quot;&gt;$SO(3)$&lt;/span&gt; and the irreducible representations are labelled by &lt;span class=&quot;math-container&quot;&gt;$\ell$&lt;/span&gt;.  Doing the same for &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;em&gt;v.g.&lt;/em&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;C&amp;amp;=\sum_{\ell m} c_{\ell m}Y^\ell_{m}(\theta,\varphi)\, ,\\&#xA;A&amp;amp;=\sum_{\ell m} a_{\ell m}Y^\ell_{m}(\theta,\varphi)\, .&#xA;\end{align}&lt;/span&gt;&#xA;The integral then becomes&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\frac{1}{r}\sum_{\ell_1m_1;\ell_2m_2;\ell}&#xA;a_{\ell_1m_1}c_{\ell_2m_2}\left(\frac{r'}{r}\right)^\ell &#xA;\sqrt{\frac{4\pi}{2\ell+1}}&#xA;\int Y^{\ell_1}_{m_1}(\theta,\varphi)Y^\ell_0(\theta,\varphi)&#xA;Y^{\ell_2}_{m_2}(\theta,\varphi) \tag{1}&#xA;\end{align}&lt;/span&gt;&#xA;and the last term is automatically &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; unless we have&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\ell_1\otimes\ell\otimes\ell_2&amp;amp;=\mathbf{0}+\ldots...\,  , \tag{2a}\\&#xA;m_1+m_2&amp;amp;=0 \tag{2b}&#xA;\end{align}&lt;/span&gt;&#xA;where (2a) comes from angular momentum coupling to the representation &lt;span class=&quot;math-container&quot;&gt;$\mathbf{0}$&lt;/span&gt; (i.e. total &lt;span class=&quot;math-container&quot;&gt;$L=0$&lt;/span&gt;) and (2b) is the condition on &lt;span class=&quot;math-container&quot;&gt;$SO(2)\sim U(1)$&lt;/span&gt; that the resulting magnetic quantum number is &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There is nothing &lt;em&gt;a priori&lt;/em&gt; to restrict the sum over &lt;span class=&quot;math-container&quot;&gt;$\ell_1,\ell_2,\ell$&lt;/span&gt; in (1) unless you have some prior knowledge of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The same general principle holds for point groups.  In the case of&#xA;point groups you would expand each &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; in terms of representation of the specific point group, and use the great orthogonality theorem of representations (also called &lt;a href=&quot;https://en.wikipedia.org/wiki/Schur_orthogonality_relations#Coordinates_statement&quot; rel=&quot;noreferrer&quot;&gt;Schur orthogonality relations&lt;/a&gt;).  Probably the integral would be broken in group elements multiplied by cosets, i.e .the integration would be written as &lt;span class=&quot;math-container&quot;&gt;$g\cdot h$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is in the group, and some sums over &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; would be &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; if the combination of representations contained in the decomposition of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; can be combined to the identity (or trivial) representation.  There would then remain integration over cosets.  This is &lt;em&gt;a bit&lt;/em&gt; of what happens in the example above: writing a rotation as &lt;span class=&quot;math-container&quot;&gt;$R_z(\varphi) R_y(\theta)$&lt;/span&gt; (there is no third angle here) the condition &lt;span class=&quot;math-container&quot;&gt;$m_1+m_2=0$&lt;/span&gt; gets rid of the &lt;span class=&quot;math-container&quot;&gt;$R_z(\varphi)$&lt;/span&gt; integration and the result is an integration over &lt;span class=&quot;math-container&quot;&gt;$R_y(\theta)$&lt;/span&gt; only.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Mildred_Dresselhaus&quot; rel=&quot;noreferrer&quot;&gt;Prof. Mildred Dresselhaus&lt;/a&gt; of MIT still has &lt;a href=&quot;http://web.mit.edu/course/6/6.734j/www/group-full02.pdf&quot; rel=&quot;noreferrer&quot;&gt;coursenotes available&lt;/a&gt;, and co-wrote an excellent textbook on the general topic.&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;So it seems your “real solid harmonics“ are basically the same as my spherical harmonics, up to some linear combinations.&lt;/p&gt;&#xA;&lt;ol start=&quot;0&quot;&gt;&#xA;&lt;li&gt;I do not understand your comment re: Hilbert space.  The Hilbert space here is the space of all 2-particle states (as you have written your states as products of two states).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;So a more or less general procedure would be as follows.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Find the linear combinations of your basis sets that transform by irreducible representations of your points group.   For instance, if you “only” need axial symmetry, then combinations of the type &lt;span class=&quot;math-container&quot;&gt;$Y^\ell_m\pm Y^\ell_{-m}$&lt;/span&gt; will produce cosine and sine pieces that are symmetric or antisymmetric w/r to reversal of the &lt;span class=&quot;math-container&quot;&gt;$\hat z$&lt;/span&gt; axis.  There are systematic ways of finding these, using projection operator techniques (someone already pointed that out).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This decomposition is usually not that bad if the group has few representations but then some irreps may occur more than once and it can be a computational headache unless one is careful.  In other words, the projection technique might provide you with multiple solutions which you have to specialize and properly normalize.   The projection gives you (usually) one state in the irrep and you may have to work a little more to construct the remaining states, although with point groups the matrix representations are well known so it’s not that bad.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Basically the step above means you are no longer working with functions &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\phi_3}\boldsymbol{\phi_4}$&lt;/span&gt; in your original basis set but some combinations of states. You also need to expand the Coulomb term in this way.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The last step is to use orthogonality of group functions to eliminate some terms.  The non-zero terms that survive are those for which the tensor product &lt;span class=&quot;math-container&quot;&gt;$\Gamma^*_k\otimes \Gamma_r\otimes \Gamma_i$&lt;/span&gt; contains the identity representation.  Here, &lt;span class=&quot;math-container&quot;&gt;$\Gamma^*_k$&lt;/span&gt; is one piece in the sum of the expansion of &lt;span class=&quot;math-container&quot;&gt;$\phi_1\phi_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Gamma_r$&lt;/span&gt; is one piece in the sum of the expansion of &lt;span class=&quot;math-container&quot;&gt;$1/\vert\mathbf{r}-\mathbf{r'}\vert$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\Gamma_i$&lt;/span&gt; is one piece in the expansion of &lt;span class=&quot;math-container&quot;&gt;$\phi_3\phi_4$&lt;/span&gt;.  This type of triple product may occur more than once for &lt;span class=&quot;math-container&quot;&gt;$(k,r,i)$&lt;/span&gt; if the irreps &lt;span class=&quot;math-container&quot;&gt;$\Gamma_k$&lt;/span&gt; &lt;em&gt;etc&lt;/em&gt; occur more than once in the decomposition of the old basis set in the basis set.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You get to decide if finding these combinations ends up saving time over simply evaluating the original integrals.&lt;/p&gt;&#xA;" OwnerUserId="1148" LastEditorUserId="5" LastEditDate="2020-08-03T05:07:37.323" LastActivityDate="2020-08-03T05:07:37.323" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="1818" PostTypeId="2" ParentId="1810" CreationDate="2020-07-28T16:29:41.130" Score="7" Body="&lt;p&gt;I am not aware of any reason (and don't see) why VASP is more popular than its contemporaries for 2D materials. VASP does have some features that other packages don't, but it also has its own drawbacks. You can refer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/561/quantum-espresso-vs-vasp/952#952&quot;&gt;this discussion&lt;/a&gt; where differences between the two most common packages (VASP and Quantum ESPRESSO) are outlined.&lt;/p&gt;&#xA;&lt;p&gt;In general, I have come across more papers that report calculations done on VASP, rather than say QE. This is not specific to 2D materials.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-07-28T16:29:41.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1819" PostTypeId="2" ParentId="1807" CreationDate="2020-07-28T16:35:15.630" Score="3" Body="&lt;p&gt;DFT-D2 is simple and reliable. I've used DFT-D2 for most of my worked on 2D materials but I do I have to caution you that I have not specifically work on TMGs. You can test out the results you obtain from both DFT-D2 and DFT-D3 and compare them. Another idea is to look at literature. There is a labyrinth of data on TMGs and you can look under the 'methods' section of the papers.&lt;/p&gt;&#xA;&lt;p&gt;This also depends on the kind of functional you use in KS-DFT. If you're using LDA, it's not practical to use vdw corrections because LDA already over-binds and using a vdw correction makes it only worse. If you're using PBE for example, it should be fine.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-07-28T16:35:15.630" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1820" PostTypeId="2" ParentId="1790" CreationDate="2020-07-28T16:54:08.203" Score="7" Body="&lt;h2&gt;AUTODOCK VINA&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://vina.scripps.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Autodock Vina&lt;/a&gt; (&lt;a href=&quot;https://dx.doi.org/10.1002%2Fjcc.21334&quot; rel=&quot;nofollow noreferrer&quot;&gt;associated paper&lt;/a&gt;) is quite old and hasn't been updated since 2011 but is still commonly used.&lt;/p&gt;&#xA;&lt;p&gt;Autodock Vina has flexible ligands by default, although selected (or all) dihedrals (a.k.a. torsions) can be made rigid by the user. The receptor is rigid by default, but flexible regions can be selected by the user.&lt;/p&gt;&#xA;&lt;p&gt;Vina is the program used under-the-hood by some free servers such as &lt;a href=&quot;http://cao.labshare.cn/cb-dock/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CB-Dock&lt;/a&gt; (&lt;a href=&quot;https://doi.org/10.1038/s41401-019-0228-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;associated paper&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="24" LastEditDate="2020-07-29T23:22:35.727" LastActivityDate="2020-07-29T23:22:35.727" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1821" PostTypeId="2" ParentId="1790" CreationDate="2020-07-28T17:11:29.737" Score="6" Body="&lt;h2&gt;FlexPepDock&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.rosettacommons.org/docs/latest/application_documentation/docking/flex-pep-dock&quot; rel=&quot;nofollow noreferrer&quot;&gt;FlexPepDock&lt;/a&gt; (&lt;a href=&quot;https://doi.org/10.1371/journal.pone.0018934&quot; rel=&quot;nofollow noreferrer&quot;&gt;associated paper&lt;/a&gt;) is part of the Rosetta toolkit and useful for peptide–protein docking.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros&lt;/strong&gt;: Peptides are fully flexible. Makes use of Rosetta's excellent protein modeling facilities.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons&lt;/strong&gt;: Requires a Rosetta installation (free). Doesn't yet support disulfide bridges or cyclization.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="118" LastEditDate="2022-07-25T18:51:18.727" LastActivityDate="2022-07-25T18:51:18.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1822" PostTypeId="2" ParentId="1790" CreationDate="2020-07-28T17:15:40.667" Score="7" Body="&lt;h2&gt;MEGADOCK&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.bi.cs.titech.ac.jp/megadock/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Megadock&lt;/a&gt; (&lt;a href=&quot;https://doi.org/10.1145/2506583.2506693&quot; rel=&quot;nofollow noreferrer&quot;&gt;associated paper&lt;/a&gt;) is a free GPU-enabled docking program for rigid protein–protein docking.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros&lt;/strong&gt;: Very fast. Can screen thousands of structures in a few hours.&#xA;&lt;strong&gt;Cons&lt;/strong&gt;: Both ligand and receptor are rigid. For proteins only.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="24" LastEditDate="2020-07-29T23:23:02.310" LastActivityDate="2020-07-29T23:23:02.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1823" PostTypeId="7" CreationDate="2020-07-28T17:45:00.063" Score="0" Body="&lt;p&gt;For any questions you might have about how sites in the Stack Exchange Network function, in terms of acceptable questions/answers, Code of Conduct, etc., check below.&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="7" LastEditDate="2022-03-14T18:31:08.983" LastActivityDate="2022-03-14T18:31:08.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1825" PostTypeId="1" CreationDate="2020-07-28T17:49:31.193" Score="7" ViewCount="215" Body="&lt;p&gt;This is something I don't understand comprehensively. Also aren't default external pressure values equal to zero for DFT codes?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-07-28T20:18:04.007" LastActivityDate="2020-07-29T23:14:47.307" Title="What's the logic of applying external pressure to a structure in a periodic DFT calculation for geometry optimization?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1826" PostTypeId="2" ParentId="1704" CreationDate="2020-07-28T17:55:30.760" Score="9" Body="&lt;p&gt;Here are a few thoughts:&lt;/p&gt;&#xA;&lt;h3&gt;Weyl semimetal&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;Weyl point.&lt;/strong&gt; A Weyl point is a point at which 2 bands cross. This places severe constraints on which type of material can host Weyl points, because in materials with both time-reversal and inversion symmetries, bands are already doubly-degenerate (spin up and down have the same energy at every &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point), so all band crossings will involve 4 (rather than 2) bands and will therefore &lt;em&gt;not&lt;/em&gt; be Weyl points. This means that a prerequisite to have a Weyl point is that the material breaks time reversal symmetry (e.g. ferromagnet), or inversion symmetry. The latter futher requires that there is a spin-dependent term in the Hamiltonian to actually split the spin degeneracy of the bands (as inversion symmetry breaking alone is not spin dependent), which can be accomplished with spin-orbit coupling.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Weyl semimetal.&lt;/strong&gt; A Weyl semimetal is simply a material that has a Weyl point at (or very near) the Fermi energy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Characterization.&lt;/strong&gt; A Weyl point is a source or sink (monopole) of Berry curvature, so you can characterize a Weyl point by constructing a surface in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-space that encloses the Weyl point, and then calculating the Chern number over that surface. It will be &lt;span class=&quot;math-container&quot;&gt;$+1$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt; for Weyl points, and the sign is called the chirality of the Weyl point.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Codes.&lt;/strong&gt; Most codes that allow you to calculate topological properties can be used to characterize Weyl points. For example, &lt;a href=&quot;http://z2pack.ethz.ch&quot; rel=&quot;noreferrer&quot;&gt;Z2Pack&lt;/a&gt; or &lt;a href=&quot;http://www.wanniertools.com&quot; rel=&quot;noreferrer&quot;&gt;WannierTools&lt;/a&gt;, both of which have interfaces with some of the major DFT codes.&lt;/p&gt;&#xA;&lt;h3&gt;Dirac semimetal&lt;/h3&gt;&#xA;&lt;p&gt;A Dirac semimetal is similar to a Weyl semimetal, but now the crossing involves four bands rather than two. This means that the symmetry breaking conditions are not as severe, and a well-known example of a material that hosts Dirac points is graphene. In fact, the very presence of Dirac points in graphene is protected by time-reversal and inversion symmetry (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1598/how-to-understand-the-time-reversal-symmetry-of-graphene/1602#1602&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-28T17:55:30.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1827" PostTypeId="2" ParentId="1784" CreationDate="2020-07-28T18:15:18.897" Score="6" Body="&lt;p&gt;&lt;strong&gt;Short answer.&lt;/strong&gt; Yes, it is possible to calculate the phonon density of states using density functional theory. You can calculate the phonon frequencies on an arbitrarily large &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid to construct the density of states, and most DFT codes will have the functionality to do this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Longer answer.&lt;/strong&gt; The density of states is given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;g(\omega)=\sum_{\nu}\int\frac{d\mathbf{q}}{(2\pi)^3}\delta(\omega-\omega_{\mathbf{q}\nu})\approx\frac{1}{N_{\mathbf{q}}}\sum_{\nu}\sum_{\mathbf{q}}\Delta(\omega-\omega_{\mathbf{q}\nu}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; is the phonon frequency at wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; and branch &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt;. The first equality is the analytical definition, and the second approximate equality is a practical expression in which the integral over the Brillouin zone is replaced by a sum over a discrete grid of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points, and the delta function is replaced by a function &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; of some width (e.g. a Gaussian).&lt;/p&gt;&#xA;&lt;p&gt;Therefore, all you need for a calculation of the density of states is to have the phonon frequencies &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; at many different &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points for the sum to provide a converged result. The practical question then becomes calculating the phonon frequencies using DFT. To do that, you need to diagonalize the dynamical matrix &lt;span class=&quot;math-container&quot;&gt;$D(\mathbf{q})$&lt;/span&gt; at that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point, whose eigenvalues are the squares of the frequencies. In turn, the dynamical matrix is the Fourier transform of the matrix of force constants, which roughly speaking measures the force that an atom feels when another atom moves. The entries in the matrix of force constants decay away as the distance between atoms increases, so in a simple real-space picture, if you have a large enough supercell, then the matrix of force constants is converged. Once you have a converged matrix of force constants, you can calculate the Fourier transform to build the dynamical matrix at any &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point you want. I went over some detail about how to do this in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This procedure is relatively well-established and it is relatively easy to obtain well-converged results. Major DFT codes support the calculation of phonons, and as a simple post-processing step they also support the calculation of phonon densities of states.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-07-28T18:39:21.303" LastActivityDate="2020-07-28T18:39:21.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1828" PostTypeId="2" ParentId="1745" CreationDate="2020-07-28T18:33:07.040" Score="3" Body="&lt;p&gt;As mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1753/671&quot;&gt;ProfM's answer&lt;/a&gt;, there is an extension to DFT known as SCDFT, that aims to account for the symmetry breaking that occurs in a superconductor. Lecture notes on SCDFT from Antonio Sanna can be found &lt;a href=&quot;https://www.cond-mat.de/events/correl17/manuscripts/sanna.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, like ProfM, I don't know enough about this approach to provide any real details. Instead, the reason I write this answer is to mention a very recent development that was published &lt;em&gt;yesterday&lt;/em&gt;:&#xA;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.057001&quot; rel=&quot;nofollow noreferrer&quot;&gt;A. Sanna, C. Pellegrini, and E. K. U. Gross, &amp;quot;&lt;em&gt;Combining Eliashberg Theory with Density Functional Theory for the Accurate Prediction of Superconducting Transition Temperatures and Gap Functions&lt;/em&gt;,&amp;quot; Physical Review Letters &lt;strong&gt;125&lt;/strong&gt;, 057001 (2020)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In short, it seems that Sanna and collaborators have managed to create a functional that approximates Eliashberg theory much better than the standard SCDFT functional, LM2005. Their method is computationally cheaper than solving the full Eliashberg equations, and appears to be rather accurate for the systems they've tested so far, which may open up a new door to predicting new materials with phonon-mediated superconductivity. Below is shown a figure comparing the Eliashberg result, the new SCDFT functional and LM2005 for a simple model as a function of the electron-phonon coupling &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;. Below that is their figure comparing theory and experiment. &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; is the critical temperature, and &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; is the gap.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4jDa3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4jDa3.png&quot; alt=&quot;Figure 2: Comparison of critical temperatures as a function of electron-phonon coupling&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/E9hbz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/E9hbz.png&quot; alt=&quot;Figure 3: Comparison between theoretical and experimental critical temperatures and gaps&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2020-07-28T18:50:47.910" LastActivityDate="2020-07-28T18:50:47.910" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1829" PostTypeId="2" ParentId="1683" CreationDate="2020-07-28T19:01:28.590" Score="2" Body="&lt;p&gt;While I'm not familiar with surfaces, I can provide the theory  for photoredox molecules. Presumably, this can be extended to surfaces with the correct level of theory, which perhaps others can elaborate on.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I'm quoting from reference 1 with some commentary in brackets&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The reduction potentials associated with the excited states cannot&#xA;be directly measured [but testing different compounds can give an&#xA;upper bound] and are typically calculated from known cyclic&#xA;voltammetry (CV) and spectroscopic data&lt;/p&gt;&#xA;&lt;p&gt;As an approximation, the excited-state potentials of a catalyst are related to its ground state potentials and its zero−zero excitation energy (E0,0). E0,0 can be estimated by the difference in energy between *PC and PC which can be approximated by the maximum emission of the catalyst [or simulation].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Oxidative Quenching&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{red}[PC^{+1}/PC^*] = E_{red}[PC^{+1}/PC] - E_{0,0}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{PC^{+1} +e^{-1} -&amp;gt; PC^{*}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reductive Quenching&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{red}[PC^*/PC^{-1}] = E_{red}[PC/PC^{-1}] + E_{0,0}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{PC^{*} +e^{-1} -&amp;gt; PC^{-1}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Shining Light on Photoredox Catalysis: Theory and Synthetic Applications&#xA;Joseph W. Tucker and Corey R. J. Stephenson&#xA;The Journal of Organic Chemistry 2012 77 (4), 1617-1622&#xA;DOI: 10.1021/jo202538x&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-07-28T19:01:28.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1830" PostTypeId="1" AcceptedAnswerId="1844" CreationDate="2020-07-28T19:23:40.243" Score="10" ViewCount="222" Body="&lt;p&gt;Apart from what is obvious (from a Google Search), what are the various resources available if I want to learn how to do something in VASP (for example, starting an HSE06 calculation)?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2020-07-28T21:42:15.490" LastActivityDate="2020-07-29T05:43:53.387" Title="What resources are available to learn how to do something in VASP?" Tags="|density-functional-theory|software|reference-request|vasp|one-topic-per-answer|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1831" PostTypeId="1" CreationDate="2020-07-28T22:16:03.620" Score="10" ViewCount="94" Body="&lt;p&gt;The Jahn-Teller effect arises from the symmetry breaking (distortion) of the local environment for the crystal field of 3d transitional metal ions.The distortion result in energy saving of electronic energy from the splitting of the degeneracy energy levels of octahedron / tetrahedral environment. Jahn-Teller effect is responsible for the hopping mechanism between Mn3+ and Mn4+ in some solid state structure.&lt;/p&gt;&#xA;&lt;p&gt;The question is that is there current computational methods available to model the Jahn-Teller effect in solid state structure? Is there any reference available?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-11-08T01:25:06.463" LastActivityDate="2020-11-08T01:25:06.463" Title="What are the methods of modeling Jahn-Teller effects in a solid-state material?" Tags="|reference-request|one-topic-per-answer|computational-chemistry|solid-state-physics|" AnswerCount="0" CommentCount="3" ClosedDate="2020-12-31T16:50:04.027" ContentLicense="CC BY-SA 4.0" />
  <row Id="1832" PostTypeId="2" ParentId="1747" CreationDate="2020-07-28T23:11:39.977" Score="4" Body="&lt;p&gt;I am not specialised in metamaterial modelling (even though my group does just that and I have designed a couple of SRRs myself), but I believe the most widely used software for designing antennas and metamaterials including SRRs is &lt;a href=&quot;https://www.3ds.com/products-services/simulia/products/cst-studio-suite/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CST Studio&lt;/a&gt;. It is equipped with many tools to design even complex nanostructures in a few clicks and run the full wave simulations.&lt;/p&gt;&#xA;&lt;p&gt;CST can be integrated with matlab and controlled from a matlab code which is very useful to automate those structure designing and simulations. CST is meant for Windows OS but has a Linux distribution too which I managed to install and work with on my Ubuntu OS.&lt;/p&gt;&#xA;&lt;p&gt;That being said, this is a commercial software, so you might have to look for a university/company license.&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2020-07-28T23:11:39.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1833" PostTypeId="2" ParentId="1566" CreationDate="2020-07-29T00:03:56.377" Score="2" Body="&lt;h2&gt;DOLO (Do Localized Orbital) CASSCF&lt;/h2&gt;&#xA;&lt;p&gt;CASSCF can capture static electron correlation (i.e. orbital degeneracies), and it is very important to select the active space which includes the degenerate orbitals. For example, in a bond breaking event the &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;* orbital will become degenerate and should be in the active space. However, anyone familiar with CASSCF will know how difficult it is to get the active space that you want. Particularly, if you are trying to solve for orbitals which are not the frontier orbitals. CASSCF can have many solutions, and sometimes you have to rotate really weird orbitals into the active space region and even that is not guaranteed to work and you might ask,... &lt;em&gt;&lt;strong&gt;why?&lt;/strong&gt;&lt;/em&gt; The reason is orbital rotations which are involved in the SCF part mix the orbitals. So even if you start with something that you like, you aren't guaranteed to keep that.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;So what can we do?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Use DOLO!&#xA;In DOLO convergence is imposed with the condition that the orbitals remain “as similar as possible” to the initial orbital, i.e. it avoid total diagonalization of Fock or Density matrices. Therefore, nice localized orbitals can be used and they remain nice localized orbitals.&lt;/p&gt;&#xA;&lt;p&gt;For some nice free pictures see &lt;a href=&quot;http://www.theochem.unito.it/lcc2004/tevangelisti.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;these slides&lt;/a&gt;. Also the original reference:&#xA;Direct generation of local orbitals for multireference treatment and subsequent uses for the calculation of the correlation energy, Daniel Maynau, Stefano Evangelisti, Nathalie Guihéry, Carmen J. Calzado and Jean-Paul Malrieu, J. Chem. Phys. 116, 10060 (2002). My favorite example, is the dissociation of a C-H bond in ethylene. Without DOLO these requires the full valence active space. But with DOLO the minimal (2,2) active space can be used.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Note, I haven't actually used DOLO. It can be found &lt;a href=&quot;https://github.com/LCPQ/Cost_package/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here, in the COST package from Toulouse&lt;/a&gt;.  &lt;strong&gt;But why isn't this more popular?!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-09-21T16:55:49.513" LastActivityDate="2020-09-21T16:55:49.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1834" PostTypeId="2" ParentId="428" CreationDate="2020-07-29T01:21:31.523" Score="4" Body="&lt;p&gt;The work function is surface-dependent, and sensitive to surface reconstructions and passivation, amongst other things. The Fermi level of the infinite bulk material would be a rather crude proxy for the workfunction.&lt;/p&gt;&#xA;&lt;p&gt;You also need to be aware that the Fermi level as computed in most periodic DFT codes is calculated with respect to an arbitrary pseudopotential-dependent reference energy, not a &amp;quot;zero vacuum level&amp;quot;, so you would need to correct for this. Essentially, the DFT eigenenergies (and hence the Fermi energy) are computed with respect to the mean electrostatic potential in the simulation cell, and this includes a contribution from the local part of the pseudopotential. Adding a molecule to the surface in a periodic simulation is actually adding an infinite, periodic array of molecules and this changes the mean electrostatic potential (in addition to any actual physical or chemical phenomena).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-07-29T01:21:31.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1835" PostTypeId="2" ParentId="1786" CreationDate="2020-07-29T02:08:24.453" Score="10" Body="&lt;h1&gt;Folding@home&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Research area&lt;/strong&gt;: Protein folding and protein structure prediction (mainly for studying diseases)&lt;br&gt;&#xA;&lt;strong&gt;Initiated by&lt;/strong&gt;: Vijay Pande (while at Stanford University)&lt;br&gt;&#xA;&lt;strong&gt;Present leader&lt;/strong&gt;: Greg Bowman (Washington University in St. Louis)&lt;br&gt;&#xA;&lt;strong&gt;Active&lt;/strong&gt;: October 2000 to Present &lt;br&gt;&#xA;&lt;strong&gt;Supported OS&lt;/strong&gt;: Windows, Mac, Linux&lt;br&gt;&#xA;&lt;strong&gt;Supported hardware types&lt;/strong&gt;: CPU, GPU, PlayStation 3 (in past), Sony Xperia smartphone (in past)&lt;br&gt;&#xA;&lt;strong&gt;Peak FLOPS&lt;/strong&gt;: 2.43 exa-FLOPS on 12 April 2020 (claimed to reach exascale) &lt;br&gt;&#xA;&lt;strong&gt;Resulted in&lt;/strong&gt;: 220+ publications &lt;br&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-29T02:17:17.313" LastActivityDate="2020-07-29T02:17:17.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1836" PostTypeId="5" CreationDate="2020-07-29T02:24:38.743" Score="0" Body="" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-29T02:24:38.743" LastActivityDate="2020-07-29T02:24:38.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1837" PostTypeId="4" CreationDate="2020-07-29T02:24:38.743" Score="0" Body="Questions that were first asked on Physics Stack Exchange." OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-05-02T20:25:41.557" LastActivityDate="2021-05-02T20:25:41.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1838" PostTypeId="5" CreationDate="2020-07-29T02:31:10.417" Score="0" Body="" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-29T02:31:10.417" LastActivityDate="2020-07-29T02:31:10.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1839" PostTypeId="4" CreationDate="2020-07-29T02:31:10.417" Score="0" Body="For questions related to the calculation of the interaction of spin electronic states or weak magnetic interaction between an electrons spin and orbital motion. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-29T02:31:10.417" LastActivityDate="2020-07-29T02:31:10.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1840" PostTypeId="2" ParentId="1786" CreationDate="2020-07-29T02:45:52.277" Score="8" Body="&lt;h1&gt;ScienceAtHome&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Research area&lt;/strong&gt;: Science-based games that generate real data for researchers. The original and most well known project is &lt;em&gt;Quantum Moves (2)&lt;/em&gt;, which is meant to provide new strategies for Quantum Optimal Control through user input in the game.&lt;br&gt;&#xA;&lt;strong&gt;Initiated/Led by&lt;/strong&gt;: Jacob F. Sherson, physics professor at Aarhus University.&lt;br&gt;&#xA;&lt;strong&gt;Active&lt;/strong&gt;: 2012-Present&lt;br&gt;&#xA;&lt;strong&gt;Operating Systems&lt;/strong&gt;: Windows, Mac&lt;br&gt;&#xA;&lt;strong&gt;Resulted in&lt;/strong&gt;: 35 publications as of 7/28/2020&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-07-29T02:49:03.520" LastActivityDate="2020-07-29T02:49:03.520" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1841" PostTypeId="2" ParentId="1556" CreationDate="2020-07-29T03:14:43.223" Score="9" Body="&lt;p&gt;I don't think analog computers are quite at the level they need to be yet, but there are people working to make them applicable to matter modeling applications.&lt;/p&gt;&#xA;&lt;p&gt;Dr. Rahul Sarpeshkar at MIT developed simple circuits to model a particular pair of &lt;a href=&quot;http://news.mit.edu/2011/analog-systems-biology-0928&quot; rel=&quot;noreferrer&quot;&gt;cellular protein production&lt;/a&gt; processes and mimic the differing pathways to the same result. They cite the continuous encoding/representation as being crucial for the simplicity of the implementation. They have also worked to address one of the biggest challenges of analog computing (the difficulty of hand crafting new circuits for each new type of problem) by developing an &lt;a href=&quot;http://news.mit.edu/2016/analog-computing-organs-organisms-0620&quot; rel=&quot;noreferrer&quot;&gt;analog compiler&lt;/a&gt; to simplify going from an algorithm to a finished circuit.&lt;/p&gt;&#xA;&lt;p&gt;Dr. Yannis Tsividis at Columbia University has worked on making &lt;a href=&quot;https://spectrum.ieee.org/computing/hardware/not-your-fathers-analog-computer&quot; rel=&quot;noreferrer&quot;&gt;analog chips&lt;/a&gt; that can aid digital computers in solving a problem. They found that they could obtain fast, reasonably accurate solutions to systems of differential equations. They mention the goal of passing these fast analog solutions as guesses to the digital computer, greatly decreasing the time and energy consumption needed to solve a problem. This is still a few steps away from actual matter modeling, but its easy to see how this could applied to, for example, find guesses for various electronic structure methods.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-10-27T00:27:58.657" LastActivityDate="2020-10-27T00:27:58.657" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1842" PostTypeId="2" ParentId="1432" CreationDate="2020-07-29T04:21:43.247" Score="4" Body="&lt;p&gt;Not a full answer to your particular problem, but a summary of the methods suggested for dealing with the headline issue of a diverging geometry optimization.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Step size: if you are drifting away from what you believe to be a minimum, decreasing the size of each optimization step can help you avoid jumping out of a small well around the minimum.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Guess: if you want to do a high level geometry optimization, always start from a structure obtained by a reliable lower level method. Getting the search into the approximate region of the minimum can save a lot of computational time even for less tricky optimizations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Validity (method): make sure the method you are using gives reasonable energy for the system you are studying. If converging a single point energy at the CCSD(T) level is challenging or is producing unreasonable results, the forces and thus the optimization are likely to be unreliable as well.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Validity (computation): even if your overall level of theory is fine, your results can still be skewed if you aren't converging the energy tightly enough. Properties require tighter convergence than what is needed to get an accurate energy. The noise in a loosely converged energy can cause an optimization to bounce around erratically.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-07-29T21:51:45.323" LastActivityDate="2020-07-29T21:51:45.323" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1843" PostTypeId="2" ParentId="1608" CreationDate="2020-07-29T04:40:05.007" Score="8" Body="&lt;p&gt;The Last Question by Isaac Asimov is a short story where a computer is tasked with solving the problem of entropy.&lt;/p&gt;&#xA;&lt;p&gt;It's a brilliant story and definitely worth listening to and reading&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://youtu.be/ojEq-tTjcc0&quot; rel=&quot;noreferrer&quot;&gt;https://youtu.be/ojEq-tTjcc0&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-07-29T04:40:05.007" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1844" PostTypeId="2" ParentId="1830" CreationDate="2020-07-29T05:43:53.387" Score="6" Body="&lt;p&gt;Vasp has a very comprehensive online Manual setup in the format of a &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;noreferrer&quot;&gt;Wiki&lt;/a&gt;. That should always be your starting point for getting started with any type of calculation. The Vaspwiki includes things like:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Step-by-step details of running most types of calculations.&lt;/li&gt;&#xA;&lt;li&gt;Descriptions of input parameters, with details about when they are necessary or important.&lt;/li&gt;&#xA;&lt;li&gt;Several worked examples with sample input files to use as a starting point.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As an example, for HSE06 calculations you can find these details:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Necessary input parameters to choose the HSE06 hybrid functional (includes how to choose other hybrid functionals too): &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Specific_hybrid_functionals&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;An example of a calculation using HSE06 for with NiO: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NiO_HSE06&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;An example of a band structure calculation using HSE06 for silicon: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-07-29T05:43:53.387" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1845" PostTypeId="1" AcceptedAnswerId="1874" CreationDate="2020-07-29T09:38:18.117" Score="9" ViewCount="157" Body="&lt;p&gt;Calculations in the ground electronic state are probably the simplest cases where defaults in terms of charge (typically zero) and spin (singlet) are chosen by the calculation software. However, when dealing with reaction intermediates we encounter charged species with differing spin multiplicity. This radical may even correspond close to the first or second electronic state of the parent molecule, or a fragment and may require specified entry of the electronic state (as in CASSCF, RASSCF, etc).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What would be some good (general) resources to learn about modelling reaction intermediates (such as radicals). What are some of the caveats in such calculations.&lt;/strong&gt; I am interested in methods such as DFT, MCSCF, MPn etc. for learning purposes.&lt;/p&gt;&#xA;" OwnerUserId="1037" LastEditorUserId="5" LastEditDate="2020-07-29T13:50:20.687" LastActivityDate="2020-07-31T14:31:20.180" Title="What are some good ways to model radicals and similar intermediates of reactions" Tags="|density-functional-theory|quantum-chemistry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1846" PostTypeId="2" ParentId="1791" CreationDate="2020-07-29T18:02:54.403" Score="10" Body="&lt;p&gt;Some of the properties we can get from the band structure are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Band_gap&quot; rel=&quot;noreferrer&quot;&gt;Band gap&lt;/a&gt;: energy between the bottom of the conduction band (CB) and the top of the valence band (VB). The gap will give you if the material is a metal (zero gap), a semiconductor (gap greater than zero and lower than &lt;span class=&quot;math-container&quot;&gt;$\sim 3eV$&lt;/span&gt; or insulating (gap &lt;span class=&quot;math-container&quot;&gt;$&amp;gt; 3eV$&lt;/span&gt;). To identify the conduction/valence band, you need to identify the Fermi energy and look for the bands around it.&lt;/li&gt;&#xA;&lt;li&gt;The type of gap: &lt;a href=&quot;https://en.wikipedia.org/wiki/Band_gap#Direct_and_indirect_band_gap&quot; rel=&quot;noreferrer&quot;&gt;direct or indirect gap&lt;/a&gt;. If the minimum of the CB is aligned with the maximum of the VB (they have the same value of &lt;span class=&quot;math-container&quot;&gt;$\mathbf k$&lt;/span&gt;) the system has a direct gap. If the are no alignment, the gap is indirect. This has direct implication in optical transitions.&lt;/li&gt;&#xA;&lt;li&gt;Electron and &lt;a href=&quot;https://en.wikipedia.org/wiki/Electron_hole&quot; rel=&quot;noreferrer&quot;&gt;hole&lt;/a&gt; &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;noreferrer&quot;&gt;effective masses&lt;/a&gt;. In semiconductor physics, the effective mass is a very useful concept. Assuming that the bottom of the CB (an the top of the VB) are parabolic, the effective mass can be obtained from fitting the expression &lt;span class=&quot;math-container&quot;&gt;$E(\mathbf k) = E_0 + \frac{\hbar^2\mathbf k^2}{2m^*}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Spin polarization. Normally, the calculations are done considering both spins. In case the system present spin polarization, there would be split of the bands: one set for spin up and one set for spin down.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-07-30T15:36:53.167" LastActivityDate="2020-07-30T15:36:53.167" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1847" PostTypeId="2" ParentId="1780" CreationDate="2020-07-29T18:19:19.453" Score="9" Body="&lt;p&gt;This took some digging, but I can supply at least a partial answer.&lt;/p&gt;&#xA;&lt;p&gt;Assuming you can copy the list of magnetic moments to a list, you could trick whatever software you are using for visualization into outputting it indirectly. A typical POSCAR can look like the following.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H&#xA;   1.00000000000000&#xA;    25 0 0&#xA;    0 25 0&#xA;    0 0 25&#xA;   H&#xA;   2&#xA;Selective dynamics&#xA;Cartesian&#xA;  10 10 10   F   F   F&#xA;  10 10 11   F   F   F&#xA;&#xA;  0  0  0&#xA;  0  0  0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The last 2 sets of vectors represent a velocity and &lt;em&gt;some?&lt;/em&gt; softwares will automatically view and let you plot velocities in the way that you want.  Simply copying your magnetic moments to these will allow you to visualize it in anything you want (VMD, ASE, etc).&lt;/p&gt;&#xA;&lt;p&gt;Added on 7/31/2020&#xA;Here is an implementation using ASE to visualize vectors.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from sys import argv&#xA;from ase.io import read&#xA;from ase.visualize import view&#xA;import numpy as np&#xA;&#xA;file_in = argv[1]&#xA;text = open(file_in).readlines()&#xA;&#xA;orbital = 4&#xA;if len(argv) &amp;gt; 3:&#xA;    orbital = argv[2]&#xA;&#xA;x, y, z = None, None, None&#xA;&#xA;def process_mag(index):&#xA;    return_array = []&#xA;    while &amp;quot;--------&amp;quot; not in text[index]:&#xA;        return_array.append(float(text[index].split()[orbital]))&#xA;        index += 1&#xA;    return return_array&#xA;&#xA;for index in range(len(text)):&#xA;    if &amp;quot; magnetization (x)&amp;quot; in text[index]:&#xA;        index += 4&#xA;        x = process_mag(index)&#xA;    if &amp;quot; magnetization (y)&amp;quot; in text[index]:&#xA;        index += 4&#xA;        y = process_mag(index)&#xA;    if &amp;quot; magnetization (z)&amp;quot; in text[index]:&#xA;        index += 4&#xA;        z = process_mag(index)&#xA;&#xA;directions = zip(x, y, z)&#xA;&#xA;for X, Y, Z in directions:&#xA;    print(&amp;quot;{} {} {}&amp;quot;. format(X, Y, Z))&#xA;&#xA;atoms = read(file_in)&#xA;atoms.set_velocities(np.array(directions)/10)&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This can be run with the OUTCAR as the first argument and optionally the magnetization orbital as the second (although it will default to total).  Then by clicking &amp;quot;show velocities&amp;quot; under &amp;quot;view&amp;quot; menu, the vectors will be shown. The script will also print the X Y Z data for you to plot in another software.&lt;/p&gt;&#xA;&lt;p&gt;It seems that most software packages ignore the POSCAR velocities, this is a somewhat annoying consequence of the file format being badly documented.  Maybe there is another approach that someone can give since this is a bad visualization for publications.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ajcw7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ajcw7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-07-31T15:44:08.897" LastActivityDate="2020-07-31T15:44:08.897" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1848" PostTypeId="2" ParentId="1761" CreationDate="2020-07-29T18:45:31.450" Score="4" Body="&lt;p&gt;The challenge of studying diffusion through physical barriers is that these processes can take on the order of microseconds or seconds. Therefore studying the molecular dynamics of a long trajectory, for example to calculate the Free Energy or potential of mean force (PMF) is practically impossible.&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless, a technique which is very promising for studying diffusion through membranes, and other porous materials is called &lt;strong&gt;Milestoning&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In Milestoning the reaction coordinate e.g. the Z-direction is split into discrete sections aka &amp;quot;milestones&amp;quot;, therefore smaller dynamics can be performed within the milestones in parallel and these can be stitched together to generate the complete free energy landscape&lt;/p&gt;&#xA;&lt;p&gt;For example, see this image which is taken from the second reference&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FFP3P.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FFP3P.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Faradjianl, Anton K.; Elber, Ron;&#xA;Computing time scales from reaction coordinates by milestoning&#xA;J. Chem. Phys. 120(23), 10880-10889 (2004) &lt;a href=&quot;https://doi.org/10.1063/1.1738640&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.1738640&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Mugnai, Mauro L.; Elber, Ron;&#xA;Extracting the diffusion tensor from molecular dynamics simulation with Milestoning&#xA;J. Chem. Phys. 142, 014105 (2015) &lt;a href=&quot;https://doi.org/10.1063/1.4904882&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.4904882&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="695" LastEditDate="2020-07-29T20:00:12.497" LastActivityDate="2020-07-29T20:00:12.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1849" PostTypeId="2" ParentId="1765" CreationDate="2020-07-29T19:58:14.367" Score="3" Body="&lt;p&gt;You should change your input to avoid defining a linear angle. This can be done by introducing a dummy atom. Here is an example with your input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 1&#xA;H&#xA;Xe   1   R12&#xA;X    2   1.0     1   A1&#xA;H    2   R13     3   A1    1    D1&#xA;&#xA;R12  =   1.92821600&#xA;R13  =   1.92934900&#xA;A1   =   90.0000000&#xA;D1   =   180.000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By defining the hydrogen as perpendicular to the dummy atom rather than 180 degrees with respect to each other, you can still work with a linear molecule, but not have to worry about the angles you have defined going out of range for Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;Also, you may want to use &lt;code&gt;R12&lt;/code&gt; for both &lt;span class=&quot;math-container&quot;&gt;$\ce{Xe-H}$&lt;/span&gt; bond lengths. This molecule should be symmetric and specifying them with the same variable will enforce that throughout the calculation.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-29T19:58:14.367" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1850" PostTypeId="2" ParentId="1694" CreationDate="2020-07-29T21:32:09.353" Score="4" Body="&lt;h1&gt;Journal of Chemical Theory and Computation (JCTC)&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2019 Impact Factor: 5.011&lt;/li&gt;&#xA;&lt;li&gt;2019 Total Citations: 33,459&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This a popular journal from the &lt;a href=&quot;https://pubs.acs.org/page/jctcce/about.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;American Chemical Society&lt;/a&gt; (ACS) that focuses exclusively on &lt;em&gt;new&lt;/em&gt; developments in electronic structure theory, molecular dynamics, and statistical mechanics; the journal doesn't accept papers &amp;quot;...that are straightforward applications of known methods&amp;quot;. So this covers advances in theory and methods, but not just papers that happened to apply DFT.&lt;/p&gt;&#xA;&lt;h1&gt;Journal of Chemical Information and Modeling (JCIM)&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2019 Impact Factor: 4.549&lt;/li&gt;&#xA;&lt;li&gt;2019 Total Citations: 19,075&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Another &lt;a href=&quot;https://pubs.acs.org/page/jcisd8/about.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACS journal&lt;/a&gt; which focuses on cheminformatics, applications of machine learning, computational interfaces, and chemical representations. You will find some electronic structure/MD papers here as well, but the emphasis of these papers will be different than those in JCTC.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-07-29T21:32:09.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1851" PostTypeId="2" ParentId="1825" CreationDate="2020-07-29T23:14:47.307" Score="3" Body="&lt;p&gt;One of the possible justification is to know how the material behave under high pressure. You can think in synthesize the material under different thermodynamic conditions or even thinking in some materials you can get from the inner core of the Earth or from meteorites.&lt;/p&gt;&#xA;&lt;p&gt;A beautiful example recently simulated and them obtained in laboratory is related to what was called by the authors &lt;em&gt;forbidden chemistry&lt;/em&gt;&lt;sup&gt;1&lt;/sup&gt;: they simulate the formation of sodium chloride (&lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt;) at high pressures and show how the 1:1 ionic stoichiometry was broken. They not only simulate it but also growth the crystals on the laboratory and characterized by X-Ray diffraction. The new ionic sodium chloride stoichiometry where &lt;span class=&quot;math-container&quot;&gt;$\ce{Na3Cl}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Na2Cl}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Na3Cl2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl3}$&lt;/span&gt;, or &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl7}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;More information about the method and other experimentally confirmed prediction can be seen in the USPEX &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Jordi Ibáñez Insa. &lt;em&gt;Reformulating Table Salt Under Pressure&lt;/em&gt;. Nature, 342, 1459-1460 (2013) (DOI: &lt;a href=&quot;http://dx.doi.org/10.1126/science.1247699&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1126/science.1247699&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-29T23:14:47.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1852" PostTypeId="2" ParentId="1790" CreationDate="2020-07-29T23:30:35.277" Score="6" Body="&lt;h2&gt;PLANTS&lt;/h2&gt;&#xA;&lt;p&gt;PLANTS uses a class of stochastic optimization algorithms called ant colony optimization (ACO).&lt;/p&gt;&#xA;&lt;p&gt;Feature &lt;a href=&quot;https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/pharmazie-und-biochemie/pharmazie/pharmazeutische-chemie/pd-dr-t-exner/research/plants/&quot; rel=&quot;noreferrer&quot;&gt;list&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ACO-based search engine&#xA;two scoring functions (PLANTS_CHEMPLP and PLANTS_PLP)&#xA;flexible protein side-chains&#xA;rigid-body docking of multiconformer libraries into rigid and flexible receptors&#xA;constraint system&#xA;docking with selected explicit, displaceable water molecules&#xA;fully automatic ligand setup (rotatable bond identification, atom typing ...)&#xA;virtual screening&#xA;rescoring capability&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note: the docking software &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-discovery/components/gold/&quot; rel=&quot;noreferrer&quot;&gt;GOLD&lt;/a&gt; uses and recommend the PLANTS score function.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-07-29T23:30:35.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1853" PostTypeId="2" ParentId="1781" CreationDate="2020-07-29T23:53:18.333" Score="5" Body="&lt;h2&gt;p-DMRG&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/1803.07150&quot; rel=&quot;noreferrer&quot;&gt;Perturbatively corrected DMRG&lt;/a&gt; by &lt;a href=&quot;https://scholar.google.com/citations?user=RjSgzhEAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Sheng Guo&lt;/strong&gt;&lt;/a&gt;, &lt;a href=&quot;https://scholar.google.com/citations?user=MYZZUJ0AAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Zhendong Li&lt;/strong&gt;&lt;/a&gt;, and &lt;a href=&quot;https://scholar.google.com/citations?user=TDzdHZgAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Garnet Chan&lt;/strong&gt;&lt;/a&gt; (in 2018).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Motivation:&lt;/strong&gt; DMRG scales poorly with respect to the number of basis functions. the above paper says that DMRG's cost is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}\left(M^3D^3\right)$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; basis functions and a bond dimension of &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;, and that &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; often has to scale as &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}\left(M\right)$&lt;/span&gt;, making the DMRG cost scale quite steeply with the number of basis functions: &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}\left(M^6\right)$&lt;/span&gt;.  &lt;em&gt;Basically:&lt;/em&gt; DMRG is very powerful for studying &lt;a href=&quot;https://arxiv.org/abs/1809.10307&quot; rel=&quot;noreferrer&quot;&gt;50 electrons with 50 basis functions&lt;/a&gt;, but would require too mcuh RAM even for studying &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;6 electrons in 500 basis functions&lt;/a&gt;. It is excellent for treating &lt;em&gt;static correlation&lt;/em&gt; of highly multi-reference systems, but poor for treating the remaining &lt;em&gt;dynamic correlation&lt;/em&gt;.&lt;/p&gt;&#xA;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Description:&lt;/strong&gt; Partition the Hamiltonian into &lt;span class=&quot;math-container&quot;&gt;$H_0+V$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; is solved  &amp;quot;exactly&amp;quot; with standard DMRG, and the resulting MPS &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt; is used to treat &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; perturbatively: but the partition is done such that &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; requires a &lt;em&gt;much&lt;/em&gt; smaller bond dimension &lt;span class=&quot;math-container&quot;&gt;$D_0$&lt;/span&gt; than you would need if you were to treat the whole Hamiltonian with standard DMRG; &lt;em&gt;and&lt;/em&gt; while treatment of &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; requires a large bond dimension &lt;span class=&quot;math-container&quot;&gt;$D_1$&lt;/span&gt;, the treatment is done via minimization of a Hylerraas functional and a sum of MPSs, which is far less expensive than a standard DMRG treatment, and this allows &lt;span class=&quot;math-container&quot;&gt;$D_1$&lt;/span&gt; to be roughly as big as the &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; in standard DMRG would be if one were to try to treat the entire Hamiltonian with similar accuracy in comparison with p-DMRG. &lt;a href=&quot;https://arxiv.org/abs/1803.07150&quot; rel=&quot;noreferrer&quot;&gt;Much thought went into how best to define &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; in the first paper&lt;/a&gt;, but a &lt;a href=&quot;https://arxiv.org/abs/1803.09943&quot; rel=&quot;noreferrer&quot;&gt;second paper posted on arXiv 8 days later&lt;/a&gt; settled on an Epstein-Nesbet partitioning, and also introduced an even more efficient way to treat the perturbative correction by using a stochastic method.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cost:&lt;/strong&gt; The more efficient stochastic algorithm (2nd paper) has two cost contributions: &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O} \left(M^3D_1^2D_0 \right)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O} \left(N_s N^2 K^3 D_0^2 \right)$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$N_s$&lt;/span&gt; samples in the stochastic sampling.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations:&lt;/strong&gt; The two aforementioned papers don't mention any software packages in which the method is implemented, and I see no mention of it in the documentation for PySCF (of which all three of the authors of the aforementioned papers, are very involved). Since the method was introduced 2 years ago, it may be in early stages and only implemented in an in-house code by the original authors, though I would not be surprised if it were to be implemented in PySCF shortly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Remarks:&lt;/strong&gt; The original authors emphasize that p-DMRG is different from DMRG-CASPT2 or DMRG-NEVPT2 where there is a CAS/non-CAS partition rather than an Epstein-Nesbet partition. p-DMRG targets &lt;em&gt;quantitative&lt;/em&gt; accuracy for systems with more basis functions than standard DMRG can handle, but far fewer basis functions than what one would have in a &lt;em&gt;qualitative&lt;/em&gt; treatment of dynamic correlation in DMRG-CASPT2. Also, there is a parameter &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; which can be tuned for example to avoid intruder states in &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt;: They found &lt;span class=&quot;math-container&quot;&gt;$\lambda=1$&lt;/span&gt; to be more prone to the intruder state problem, so they mainlused &lt;span class=&quot;math-container&quot;&gt;$\lambda=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\lambda=1/2$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2020-07-29T23:53:18.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1854" PostTypeId="2" ParentId="1633" CreationDate="2020-07-30T02:19:39.150" Score="5" Body="&lt;p&gt;The role of the chemist in computational chemistry is to provide the real physical evidence. Computational chemistry deals with models, and predictions. It can give you insight into the &lt;em&gt;mystical quantum&lt;/em&gt; nature of molecules but it's just that, a prediction.&lt;/p&gt;&#xA;&lt;p&gt;The experimental chemist can then use those models and predictions to guide their experiments, which can support or oppose the predictions and models. The new experimental data can then be used to improve the models, and the process repeats itself!&lt;/p&gt;&#xA;&lt;p&gt;This diagram describes well the typical workflow of a computational chemist and experimental chemist.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bqTcE.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bqTcE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Of course, any good computational chemist can do both. They can come up with a good chemical idea, find experimentally relevant details in the literature or get someone to collaborate with, make hypotheses, test those hypotheses, gain insight and repeat the process. This is why it is good to have a good all around training. Don't be a monkey who just pushes a button. Think for yourself!&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-07-30T02:30:32.600" LastActivityDate="2020-07-30T02:30:32.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1855" PostTypeId="2" ParentId="1679" CreationDate="2020-07-30T02:58:21.777" Score="9" Body="&lt;p&gt;The &lt;a href=&quot;https://www.cambridge.org/core/journals/mrs-bulletin/article/fractal-models-and-the-structure-of-materials/B66DE8259950FC78769FE900679CF0AA&quot; rel=&quot;noreferrer&quot;&gt;review&lt;/a&gt; that @Anyon cited focuses on the use of fractal geometry to classify and model the structure of disordered materials, e.g. structures synthesized by the sol-gel method.&lt;/p&gt;&#xA;&lt;p&gt;The computational work is nicely summarized in the following figure taken from the paper:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/prk62l.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/prk62l.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &amp;quot;Reaction-Limited&amp;quot;, &amp;quot;Ballistic&amp;quot; and &amp;quot;Diffusion-Limited&amp;quot; correspond to 3 different types of simulations, and each model specifies different growth kinetics. In these simulations, particles are moving in random walks and growth occurs when certain conditions are met.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Monomer-Cluster&amp;quot; simulations start with a seed at a particular site and the growth events happen when a monomer lands on a site neighboring the seed, increasing the seed size. On the other hand, in &amp;quot;Cluster-Cluster&amp;quot; simulations, the seeds are allowed to move around and interact with each other, resulting in extended structures.&lt;/p&gt;&#xA;&lt;p&gt;The D values on the bottom-left corner of each simulation correspond to the fractal dimension. In a 3D embedding space, this dimension relates the mass (&lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;) of an object to its size (&lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;)&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;M \sim R^{D}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In a 2D embedding space, the surface area (&lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;) and size of an object are related through the surface fractal dimension (&lt;span class=&quot;math-container&quot;&gt;$D_S$&lt;/span&gt;)&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;S \sim R^{D_S}. &#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Moreover, when scattering techniques are used on fractal objects, the intensity (&lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;) of the incidental beam is related to the wave vector (&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;), through:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;I \sim K^{-2D+D_S}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;These relationships, along with the simulations mentioned previously, allow to classify structures and identify the growth factors in kinetic growth systems.&lt;/p&gt;&#xA;" OwnerUserId="204" LastEditorUserId="204" LastEditDate="2020-07-30T04:11:05.290" LastActivityDate="2020-07-30T04:11:05.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1856" PostTypeId="2" ParentId="1642" CreationDate="2020-07-30T07:17:51.657" Score="5" Body="&lt;p&gt;This is not a direct answer to your question, but I hope to get the ball rolling.&lt;/p&gt;&#xA;&lt;p&gt;In the question, you ask about reverse-engineering an &lt;em&gt;experimentally&lt;/em&gt; obtained density to say something about density functional theory (DFT). While I am not aware of any examples of this, there are examples of reverse-engineering a &lt;em&gt;computationally&lt;/em&gt; obtained density to say something about density functional theory.&lt;/p&gt;&#xA;&lt;p&gt;As an example, consider this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.109.036402&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. They introduce &amp;quot;a self consistent algorithm for reverse engineering the exact potential from the known time-dependent charge and current densities&amp;quot;. What does this mean? They solve a simple problem in a numerically exact way to obtain the charge (and current) density, and then reverse-engineer them to obtain the exact Kohn-Sham potential. In this particular example, they are interested in time-dependent DFT, and their work shows some interesting features of the corresponding Kohn-Sham potential, such as a non-local dependence of the charge density in both space and time.&lt;/p&gt;&#xA;&lt;p&gt;Overall, while this is not a direct answer to your question about &amp;quot;experimentally determined densities&amp;quot;, I hope it helps see what can be accomplished by reverse-engineering DFT.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="695" LastEditDate="2020-07-30T15:14:05.613" LastActivityDate="2020-07-30T15:14:05.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1857" PostTypeId="2" ParentId="1749" CreationDate="2020-07-30T07:30:20.330" Score="6" Body="&lt;h1&gt;Boltzmann Transport&lt;/h1&gt;&#xA;&lt;p&gt;Transport of electrons in the presence of electric field and magnetic field can be described uisng &lt;a href=&quot;https://en.wikipedia.org/wiki/Boltzmann_equation&quot; rel=&quot;noreferrer&quot;&gt;Boltzmann transport equation&lt;/a&gt;. There are Classical and semi-classical formalisms and a detailed analysis can be found &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B9780128171035000116&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Codes like &lt;a href=&quot;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap2/&quot; rel=&quot;noreferrer&quot;&gt;BoltzTrap2&lt;/a&gt;, &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513003160&quot; rel=&quot;noreferrer&quot;&gt;BoltzWann&lt;/a&gt;, &lt;a href=&quot;https://nanohub.org/groups/needs/lantrap&quot; rel=&quot;noreferrer&quot;&gt;LanTrap&lt;/a&gt; etc. have implemented BTE and can be used to study thermoelectric and electronic transport in materials.&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-07-30T07:30:20.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1858" PostTypeId="2" ParentId="1815" CreationDate="2020-07-30T08:35:44.217" Score="5" Body="&lt;p&gt;CASINO is a continuum quantum Monte Carlo code, allowing you to perform variational and diffusion quantum Monte Carlo.&lt;/p&gt;&#xA;&lt;p&gt;Best wishes,&lt;/p&gt;&#xA;&lt;p&gt;Neil.&lt;/p&gt;&#xA;" OwnerUserId="1152" LastActivityDate="2020-07-30T08:35:44.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1859" PostTypeId="1" AcceptedAnswerId="1861" CreationDate="2020-07-30T09:02:01.880" Score="20" ViewCount="1233" Body="&lt;p&gt;I am currently trying to simulate a large box of QM/MM water molecules with SPC/Fw model and GGA DFT functional (a cube of 40 angstrom sides). To validate the QM and MM simulations separately, I am testing a pure MM box of same dimensions with SPC/Fw model, and I was trying to set the LJ and coulomb cutoff length. I am using CP2K software and pairwise-style cutoff. By the conventions I should set the cutoff to &amp;lt;1/2 of smallest box dimension (~19 angstroms). But I encountered these two papers about this issue for liquid water:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1063/1.2198208&quot; rel=&quot;noreferrer&quot;&gt;Liquid water simulation: A critical examination of cutoff length&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/ct0502256&quot; rel=&quot;noreferrer&quot;&gt;The Origin of Layer Structure Artifacts in Simulations of Liquid Water&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;both published in 2006, which suggests that larger cutoff lengths can lead to &amp;quot;layering&amp;quot; and other artifacts in pure water simulations. Elsewhere, I can find papers which suggest to keep the cutoff length to 9-12 angstroms (as discussed here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/776/rule-of-thumb-for-morse-potential-cutoff-in-molecular-dynamics&quot;&gt;Rule-of-thumb for Morse potential cutoff in molecular dynamics?&lt;/a&gt;). So my question is: Does it makes sense then to limit cutoffs till 12 angstroms? And are there any significant issues particularly for QM/MM simulations?&lt;/p&gt;&#xA;&lt;p&gt;For more details on the QM/MM setup: I am using an &lt;a href=&quot;https://www.cp2k.org/events:2016_summer_school:qmmm&quot; rel=&quot;noreferrer&quot;&gt;additive QM/MM system with electrostatic embedding&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="118" LastEditDate="2020-07-31T13:32:50.927" LastActivityDate="2020-07-31T13:32:50.927" Title="Does increasing Lennard-Jones cutoff means higher accuracy?" Tags="|molecular-dynamics|molecular-interactions|qmmm|molecular-mechanics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1860" PostTypeId="2" ParentId="1679" CreationDate="2020-07-30T09:02:09.677" Score="4" Body="&lt;p&gt;It has been recognized that fractal features are exploited in numerous natural materials. The properties conferred by fractal geometry (for instance, efficient utilization of material and filling of space) have in addition inspired some material modelers to incorporate the scale-invariant properties of fractals into their designs. An understanding of fractal principles can therefore be implemented by material modelers in two ways: &lt;em&gt;a priori&lt;/em&gt;, to design features into materials conferred by the fractal nature; or &lt;em&gt;a posteriori&lt;/em&gt;, to understand or describe the properties of materials.&lt;/p&gt;&#xA;&lt;p&gt;I post just two examples found quickly  with an online search for the keywords &amp;quot;fractal material properties simulation&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The first example [Ref. 1] rather stunningly exploits the scale-free geometric property of fractals to design a stretchable electrode through appropriate fractal slicing of the starting polymeric material.&lt;/p&gt;&#xA;&lt;p&gt;A second example [Ref. 2] uses fractal principles to describe the hierarchical structure of palm fibers, and uses a model derived from this description to relate material properties to structure at different scales.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;References&lt;/em&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Yigil Cho, Joong-Ho Shin, Avelino Costa, Tae Ann Kim, Valentin Kunin, Ju Li, Su Yeon Lee, Shu Yang, Heung Nam Han, In-Suk Choi, and David J. Srolovitz. Engineering the shape and structure of materials by fractal cut. PNAS December 9, 2014 111 (49) 17390-17395; first published November 24, 2014 &lt;a href=&quot;https://doi.org/10.1073/pnas.1417276111&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1073/pnas.1417276111&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Wang, Y., Zhang, T., Jing, L., Deng, P., Zhao, S., and Guan, D. (2020). &amp;quot;Exploring natural palm fiber’s mechanical performance using multi-scale fractal structure simulation,&amp;quot; BioRes. 15(3), 5787-5800.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="120" LastActivityDate="2020-07-30T09:02:09.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1861" PostTypeId="2" ParentId="1859" CreationDate="2020-07-30T10:28:22.513" Score="12" Body="&lt;p&gt;Very interesting question!&lt;/p&gt;&#xA;&lt;p&gt;The LJ potential is quite benign in that it has a &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; decay, which is pretty rapid. However, MD codes typically go a bit farther than a straightaway truncation at &lt;span class=&quot;math-container&quot;&gt;$r_{\rm max}$&lt;/span&gt;, but instead also apply an analytical correction for the region &lt;span class=&quot;math-container&quot;&gt;$[r_{\rm max},\infty)$&lt;/span&gt;. The analytical correction for the cut-off can be justified by long-range statistics: things look more and more uniform the farther you go from a point.&lt;/p&gt;&#xA;&lt;p&gt;However, the cutoff needs to be large enough so that things really become uniform at that stage, that is, the pair correlation function &lt;span class=&quot;math-container&quot;&gt;$g(r)=1$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$r \ge r_{\rm max}$&lt;/span&gt;; otherwise you end up affecting the behavior of the system.&lt;/p&gt;&#xA;&lt;p&gt;While in principle increasing the cutoff should make simulations more accurate, the findings of the two papers you linked would seem to insinuate that this is not true.&lt;/p&gt;&#xA;&lt;p&gt;However, one should not think that it is the cutoff that is to blame, but rather the water model. It looks like the water models have either been trained for systems that are too small, and/or the training model calculations have not been fully converged with respect to all computational parameters. What one is seeing is emergent behavior from an incorrect water model: when the calculations are performed numerically accurately, the system stops behaving in a physical manner. A smaller cutoff implies forcing an uniform structure at long range; if you instead use a larger cutoff, the systems starts to exhibit long-range structures.&lt;/p&gt;&#xA;&lt;p&gt;So, while my general advice is to converge the cutoffs so that the system's properties do not change anymore, if you have a case where it has been reported that too large values for the cutoff result in inaccurate behavior, then you need to limit the cutoffs to smaller values.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-30T10:28:22.513" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1862" PostTypeId="2" ParentId="1859" CreationDate="2020-07-30T10:34:22.390" Score="13" Body="&lt;p&gt;I am afraid I can't be of much help regarding the QM part of your simulation, but I can give some thoughts on the MM part. In short: &lt;strong&gt;you should use the cutoff that was used to validate your force field&lt;/strong&gt;. While a proper &lt;em&gt;ab initio&lt;/em&gt; method is expected to improve with a longer cutoff, this is not necessarily true for force fields. The reason for that is that force fields are inevitably overfitted to either QM data or existing experimental data, meaning that the further you stray from the validated conditions, the less certain you can be in your results. In the original SPC/Fw paper, the cutoff they use for validation is 9 Å, so this is the cutoff I would use for the MM part.&lt;/p&gt;&#xA;&lt;p&gt;Note that this may not be necessarily true with a complicating QM method on top, and I am not sure whether a standard practice for a &amp;quot;best cutoff&amp;quot; exists in this case. To me, this sounds like the type of question that warrants its own research project.&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="710" LastEditDate="2020-07-30T10:40:39.360" LastActivityDate="2020-07-30T10:40:39.360" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1863" PostTypeId="2" ParentId="1515" CreationDate="2020-07-30T10:55:13.690" Score="9" Body="&lt;h2&gt;Finland&lt;/h2&gt;&#xA;&lt;p&gt;Finland has a long history in supercomputing; &lt;a href=&quot;https://www.csc.fi/en/home&quot; rel=&quot;noreferrer&quot;&gt;CSC - the Finnish IT Center for Science&lt;/a&gt;, administered by the Finnish Ministry of Education and Culture, has provided computing services since 1971, starting with an Univac computer.&lt;/p&gt;&#xA;&lt;p&gt;The strategy in Finland has been to pool national resources from the start, and this has enabled Finnish researchers to have access to have access to up-to-date computer resources for many decades. The policy of CSC has been to update their supercomputers regularly, and they've been a semi-permanent attender on the &lt;a href=&quot;https://www.top500.org/&quot; rel=&quot;noreferrer&quot;&gt;top 500 list of supercomputers in the world&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Although many universities and departments in Finland also operate their own computer clusters, &lt;strong&gt;anyone&lt;/strong&gt; with an academic affiliation in Finland can get a CSC user account, and apply for their computational resources with a relatively easy procedure.&#xA;This has greatly aided computational work (especially in matter modeling!) for a long time.&lt;/p&gt;&#xA;&lt;p&gt;CSC is currently installing new supercomputers. In addition to the recently installed Puhti supercomputer (Atos BullSequana X400 supercomputer, 1.8 petaflops, 682 nodes with 2x20 core Xeon Gold 6230 i.e. 27280 cores in total, a mix of memory sizes on each node and a 4+ PB Lustre storage system),  the upcoming Mahti and Lumi supercomputers will lead to a huge increase in computing power.&lt;/p&gt;&#xA;&lt;p&gt;Mahti is a Atos BullSequana XH2000 supercomputer, with 1404 nodes with a peak performance of 7.5 petaflops. Each node has two 64 core AMD EPYC 7H12 (Rome) processors with a 2.6 GHz base frequency (3.3 GHz max boost), and 256 GB of memory. Mahti will  also have a 8.7 PB Lustre parallel storage system. Mahti should become generally available for Finnish users in August 2020.&lt;/p&gt;&#xA;&lt;p&gt;Lumi is a EuroHPC supercomputer, with a computing power of over 200 petaflops, and over 60 PB of storage, and will become available in early 2021. Although this is a European joint project, since the supercomputer is based in Finland, it will have a quota for Finnish users.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-07-30T10:55:13.690" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1864" PostTypeId="1" CreationDate="2020-07-30T13:17:27.790" Score="8" ViewCount="349" Body="&lt;p&gt;I was trying to calculate the hyperpolarizability &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; of a cluster of two water molecules in Gaussian16 using the route card:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;code&gt;#t cam-b3lyp/daug-cc-pvtz  Polar  nosymm scf=tight int=grid=superfine&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;code&gt;#t cam-b3lyp/daug-cc-pvtz  Polar=doubleNumer  nosymm scf=tight int=grid=superfine&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The files which can be used for testing are attached in these links [&lt;a href=&quot;https://pastebin.com/Cm27RCf6&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;], [&lt;a href=&quot;https://pastebin.com/HxxwQLZ3&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;p&gt;In case (1) I got a value of 83.44 au for the &lt;span class=&quot;math-container&quot;&gt;$\beta_{xxx}$&lt;/span&gt;. For (2) I got a value of 23.66 au for &lt;span class=&quot;math-container&quot;&gt;$\beta_{xxx}$&lt;/span&gt;. I also altered the distance between two water molecules by &lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt; 0.5 angstroms and I got an average &lt;span class=&quot;math-container&quot;&gt;$\beta_{xxx}$&lt;/span&gt; value of 23.44 au .&lt;/p&gt;&#xA;&lt;p&gt;I am not sure about the capabilities of other electronic structure codes (I know ORCA does not have an option to calculate hyperpolarizability; &lt;del&gt; Dalton &lt;/del&gt; Turbomole does, but I don't have access to it), but &lt;strong&gt;is this error reproducible in other codes or this is just a problem of G16?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;From Gaussian16 support, I got the following response:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We have reviewed this further and it is a numerical error which is caused by near linear dependencies in the basis set which the analytic second derivative for beta is not handling well.  You can see this if you use aug-cc-pvtz in place of&#xA;daug-cc-pvtz.&lt;/p&gt;&#xA;&lt;p&gt;It is also possible to get a better analytic value using Polar=(Cubic,Fourpoint) which is more numerically stable but also significantly more time consuming computationally.  With that method the results are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;#p cam-b3lyp/daug-cc-pvtz Polar=(Cubic,fourpoint) nosymm scf=conver=10 int=grid=superfine&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\beta_{xxx}$&lt;/span&gt;=23.473904&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;code&gt;#p cam-b3lyp/daug-cc-pvtz Polar=DoubleNumer nosymm scf=Conver=10 int=grid=superfine&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\beta_{xxx}$&lt;/span&gt;=23.5511654&lt;/p&gt;&#xA;&lt;p&gt;where you see the comparison with numerical is about 5 significant figures.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="1151" LastEditDate="2020-07-30T20:19:05.190" LastActivityDate="2020-08-02T04:13:50.630" Title="Is this G16 molecular hyperpolarizability error reproducible in other software?" Tags="|software|electronic-structure|quantum-chemistry|gaussian|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1865" PostTypeId="1" CreationDate="2020-07-30T13:33:59.833" Score="13" ViewCount="3151" Body="&lt;p&gt;Let's say I want to make k-point convergence test for graphite. And let's say it converges at 12x12x4.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do I first need to do a k-point convergence test for equal k-points on xyz directions then make another k-point convergence test with changing k-point only along z-direction?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am asking because I don't want to use 12x12x12 k-points if it already converges for 12x12x4.&lt;/p&gt;&#xA;" OwnerUserId="1154" LastEditorUserId="5" LastEditDate="2020-08-04T22:12:34.847" LastActivityDate="2021-09-27T21:18:27.093" Title="How to make a k-point convergence test for a bulk structure with a lower k-point in the z-direction?" Tags="|vasp|quantum-espresso|convergence-test|k-points|answer-with-calculation|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1867" PostTypeId="1" CreationDate="2020-07-30T16:40:17.003" Score="7" ViewCount="3346" Body="&lt;p&gt;Is it possible to to display the atom legend in VESTA and export the structure including the legend as a vector/raster image?&lt;/p&gt;&#xA;&lt;p&gt;I found &lt;a href=&quot;https://groups.google.com/forum/#!topic/vesta-discuss/xjVzlnFw6Zo&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; discussion from 2013 requesting this feature. Has it been added?&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="5" LastEditDate="2020-08-30T21:56:38.760" LastActivityDate="2020-08-30T23:01:44.967" Title="Atom legend in VESTA" Tags="|software|visualization-software|vesta|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1868" PostTypeId="2" ParentId="1865" CreationDate="2020-07-30T16:43:28.777" Score="12" Body="&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;If you have already obtained satisfactory convergence with a (relatively) sparse k-point grid, there is no motivation to go for a denser grid. So if you have already achieved convergence with 12x12x4, there's no need to go to 12x12x12.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are talking about graphene, which is 2-D, there is no need to sample points along the out-of-plane direction.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There are some more nuances, which you haven't mentioned in the question, but I will comment anyway. Even grids usually have better convergence than odd grids because you avoid sampling the high-symmetry points. So you should typically try to use even k-meshes for your BZ integrations. But there is an exception (for materials with hexagonal BZs) in the case of graphene, you should not use a gamma-centered (even) grid because you tend to generate points outside the brillouin zone.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-07-30T16:43:28.777" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="1869" PostTypeId="2" ParentId="1515" CreationDate="2020-07-30T18:54:57.340" Score="9" Body="&lt;h1&gt;Switzerland&lt;/h1&gt;&#xA;&lt;p&gt;In Switzerland, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Swiss_National_Supercomputing_Centre&quot; rel=&quot;noreferrer&quot;&gt;Swiss National Supercomputing Centre&lt;/a&gt; (CSCS) provides most computing power. Refer to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Swiss_National_Supercomputing_Centre&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt; article for a list of all the computing resources; it started with a 2-processor computer in 1992. Most notably though, since December 2012 it is the provider of &lt;a href=&quot;https://en.wikipedia.org/wiki/Piz_Daint_(supercomputer)&quot; rel=&quot;noreferrer&quot;&gt;Piz Daint&lt;/a&gt;, which in 2016 after an upgrade became the third most powerful supercomputer in the world with 25 petaflops. Piz Daint is a Cray XC50/XC40 system featuring Nvidia Tesla P100 GPUs. The title of &amp;quot;third most powerful supercomputer in the world&amp;quot; is not current anymore, unfortunately. CSCS at the time of writing does provide four other active clusters. The CSCS computers are used by universities and research facilities including Meteo/weather services and private stakeholders.&lt;/p&gt;&#xA;&lt;p&gt;Of course many universities and sub-departments have their own little clusters of computers  for their high performance and specialized applications. Empirically, when studying at ETH Zürich, I had access to a cluster for students of the D-CHAB (chemistry department) called Realbeaver, the ETH-computer-cluster &lt;a href=&quot;https://scicomp.ethz.ch/wiki/Euler&quot; rel=&quot;noreferrer&quot;&gt;Euler&lt;/a&gt;, that is currently in stage VII of expansions as well as Piz Daint which I mentioned above.&#xA;For the latter two, the computer resources are limited according to some shareholder agreements. For students, the resources generally depend on the course they are taking/the group they do their project in.&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="108" LastEditDate="2020-07-31T13:48:25.670" LastActivityDate="2020-07-31T13:48:25.670" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1870" PostTypeId="2" ParentId="63" CreationDate="2020-07-30T19:00:23.507" Score="5" Body="&lt;h1&gt;2009 (Tkatchenko−Scheffler) TS&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevLett.102.073005&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tkatchenko−Scheffler model&lt;/a&gt; for van der Waals interactions (vdW) defines the &lt;span class=&quot;math-container&quot;&gt;$C_6^{AB}$&lt;/span&gt; parameters in an &lt;em&gt;ab-initio&lt;/em&gt; fashion. In TS model the vdW energy &lt;span class=&quot;math-container&quot;&gt;$E_{vdw}$&lt;/span&gt; is defined as,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;E_{\text{vdW}} = -\frac{1}{2}\sum_{A,B}f_{\text{damp}}\left(R_{AB},R^{0}_{A},R^{0}_{B}\right)C_{6}^{AB}R^{-6}_{AB} \tag{1} \end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$R^0_{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R^0_{B}$&lt;/span&gt; are the vdW radii. The &lt;span class=&quot;math-container&quot;&gt;$C_6^{AB}$&lt;/span&gt; parameter can defined by the Casimir-Polder integral exactly:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C_6^{AB}=\frac{3}{\pi}\int_{0}^{\infty}\alpha_{{A}}(i\omega)\alpha_{{B}}(i\omega)d\omega \tag{2} \label{eq:eq2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\alpha_{A/B}(i\omega)$&lt;/span&gt; is the frequency-dependent polarizability of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; evaluated at imaginary frequencies. The &lt;span class=&quot;math-container&quot;&gt;$\alpha_{A/B}(i\omega)$&lt;/span&gt; can be replaced by an approximate &lt;span class=&quot;math-container&quot;&gt;$\alpha^1_{A/B}(i\omega)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\alpha^1_{A}(i\omega)=\alpha^{0}_{A}/[1-(\omega/\eta_{A})^2]$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\alpha^{0}_{A}$&lt;/span&gt; is the static polarizability of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\eta_{A}$&lt;/span&gt; is an &lt;em&gt;effective frequency&lt;/em&gt;. Simplifying \eqref{eq:eq2}, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C_6^{AB}=\frac{3}{2}[\eta_{A}\eta_{B}/(\eta_{A}+\eta_{B})]\alpha_{A}^0\alpha_{B}^0\tag{3}\label{eq:eq3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which after further simplification results in:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C_6^{AB}=\frac{2C_6^{AA}C_6^{BB}}{[\frac{\alpha_{B}^0}{\alpha_{A}^0}C_6^{AA}+\frac{\alpha_{A}^0}{\alpha_{B}^0}C_6^{BB}]}\tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$C_6^{AA}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_{A}^0$&lt;/span&gt; can be determined from &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1779576&quot; rel=&quot;nofollow noreferrer&quot;&gt;highly accurate benchmark calculations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note: Here &lt;span class=&quot;math-container&quot;&gt;$C_6^{ij}\equiv C_6^{AB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$i\equiv A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j\equiv B$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="7" LastEditDate="2020-07-30T20:55:27.993" LastActivityDate="2020-07-30T20:55:27.993" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1871" PostTypeId="2" ParentId="1768" CreationDate="2020-07-31T04:25:20.943" Score="10" Body="&lt;h2&gt;What is the quantum anomalous Hall effect?&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XM88b.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XM88b.png&quot; alt=&quot;Six Hall effects&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Figure from &lt;a href=&quot;https://doi.org/10.1146/annurev-conmatphys-031115-011417&quot; rel=&quot;noreferrer&quot;&gt;C-X. Liu, S-C. Zhang, and X-L. Qi. &amp;quot;&lt;em&gt;The Quantum Anomalous Hall&#xA;Effect: Theory and Experiment,&lt;/em&gt;&amp;quot; Annual Review of Condensed Matter Physics &lt;strong&gt;7&lt;/strong&gt;, 301-321 (2016)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/1508.07106&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;In short, the quantum anomalous Hall effect (QAHE) is the quantized version of the regular anomalous Hall effect (AHE). That is, a quantized Hall effect that does not require an external magnetic field. Historically, Edwin Hall first discovered the (now regular) &lt;a href=&quot;https://en.wikipedia.org/wiki/Hall_effect&quot; rel=&quot;noreferrer&quot;&gt;Hall effect&lt;/a&gt; in 1879, in a metallic sheet perpendicular to a magnetic field carrying a current. The magnetic field deflects electrons preferentially to one side through the Lorentz force, leading to a voltage &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; developing across the sample but perpendicular to both magnetic field and the applied current.&lt;/p&gt;&#xA;&lt;p&gt;As von Klitzing discovered in 1980, a similar effect occurs in two-dimensional electron systems at low temperatures and strong fields, except with a quantized response. This is of course the &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_Hall_effect&quot; rel=&quot;noreferrer&quot;&gt;integer quantum Hall effect&lt;/a&gt;. Specifically, the conductance satisfies &lt;span class=&quot;math-container&quot;&gt;$\sigma=\frac{I}{V_H} = \nu \frac{e^2}{h}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; is the Hall voltage, &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; is an integer, and &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; is Planck's constant. (At even lower temperatures the particularly exotic fractional quantum Hall effect occurs, where &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; can take fractional values. That is beyond the scope of this post.) Heuristically, we can imagine the case where the applied field is so strong that electrons in the center of the sample are stuck in cyclotron orbits, as in panel (d) of the figure above. However, near the edge of the sample we get so-called skipping orbits, which results in that the states near the upper edge only move in one direction, and states near the lower edge move in the opposite direction. These edge states are called chiral. For more details see e.g. &lt;a href=&quot;https://topocondmat.org/w3_pump_QHE/QHEedgestates.html&quot; rel=&quot;noreferrer&quot;&gt;these notes&lt;/a&gt;. The integer &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; turns out to be the (first) Chern number, also known as the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.49.405&quot; rel=&quot;noreferrer&quot;&gt;TKNN invariant&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In 1881 Hall published his finding that the Hall voltage is significantly higher in ferromagnetic materials than in nonmagnetic ones. This was dubbed the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hall_effect#Anomalous_Hall_effect&quot; rel=&quot;noreferrer&quot;&gt;anomalous Hall effect&lt;/a&gt; (AHE). Whereas the regular Hall effect could be explained using relatively simple physics, it did take a long time to develop a full understanding of the AHE. By the 1930s, it had been empirically demonstrated that the Hall resistivity in ferromagnetic metals satisfies&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho_{xy}= R_0 H_z + R_s M_z,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$H_z$&lt;/span&gt; is the applied magnetic field, and &lt;span class=&quot;math-container&quot;&gt;$M_z$&lt;/span&gt; is the spontaneous magnetization. The first term represents the regular Hall effect (which tends to saturate in metals), and the second contains the AHE. While the parameter &lt;span class=&quot;math-container&quot;&gt;$R_0$&lt;/span&gt; depends mainly on carrier density, &lt;span class=&quot;math-container&quot;&gt;$R_s$&lt;/span&gt; is material specific. Note that AHE remains at zero field, assuming time-reversal symmetry is spontaneously broken, as it tends to be in ferromagnetic materials.&lt;/p&gt;&#xA;&lt;p&gt;Given the discovery of the IQH it was natural to ask whether we can also have a quantized anomalous Hall effect (QAHE), that is can we have a quantized Hall conductance induced by a mechanism other than a magnetic field? Perhaps even in zero field? The first proposal of such a system was due to &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.61.2015&quot; rel=&quot;noreferrer&quot;&gt;Haldane in 1988&lt;/a&gt;, previously discussed on the site &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1703/671&quot;&gt;here&lt;/a&gt;. This type of system is protected again by the Chern number, and known as a Chern insulator.&lt;/p&gt;&#xA;&lt;p&gt;To complete the picture, note that spin-orbit coupling acts similar to a magnetic field, but with opposite sign for opposite sign spins. Using this approach, it is possible to construct what looks like two copies of the AHE in a way that doesn't break time-reversal symmetry, resulting in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin_Hall_effect&quot; rel=&quot;noreferrer&quot;&gt;spin Hall effect&lt;/a&gt;, or two copies of the QAHE resulting in the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.95.146802&quot; rel=&quot;noreferrer&quot;&gt;quantum spin Hall effect&lt;/a&gt;, also known as 2D topological insulators. The latter are protected by a &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; topological invariant.&lt;/p&gt;&#xA;&lt;h2&gt;What is the source of the anomalous Hall effect?&lt;/h2&gt;&#xA;&lt;p&gt;As mentioned above, the AHE resisted theoretical description for a long time. In part because it doesn't have one single physical origin, but has contributions from magnetism, spin-orbit coupling and disorder effects. In part it's because we didn't have all the appropriate theoretical concepts until the 80s and 90s, and it took still longer until we had the computational materials modeling in place to help sort out which mechanism(s) would dominate in a given material. There's an excellent and comprehensive review by &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.82.1539&quot; rel=&quot;noreferrer&quot;&gt;Nagaosa, Sinova, Onoda, MacDonald, and Ong, &amp;quot;&lt;em&gt;Anomalous Hall effect&lt;/em&gt;,&amp;quot; Reviews of Modern Physics &lt;strong&gt;82&lt;/strong&gt;, 1539-1592 (2010)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/0904.4154&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;) that covers the history and mechanisms in detail. It also has this figure, which lays out the mechanisms clearly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QbWjb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QbWjb.png&quot; alt=&quot;Anomalous Hall mechanisms&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The intrinsic mechanism is due to the Berry phase of the electron bands in the system, and results in a modification of the electron group velocity (so-called &amp;quot;anomalous velocity&amp;quot;) that is perpendicular to an applied electric field. Since you say you're not sure how the term appears, I will refer you to another excellent review article: &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.82.1959&quot; rel=&quot;noreferrer&quot;&gt;Di Xiao, Ming-Che Chang, and Qian Niu, &amp;quot;&lt;em&gt;Berry phase effects on electronic properties&lt;/em&gt;,&amp;quot; Reviews of Modern Physics &lt;strong&gt;82&lt;/strong&gt;, 1959-2007 (2010)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/0907.2021&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;), specifically the derivations leading up to Eq. (3.6). However, the point here is that the intrinsic contributions come from Berry curvatures, which comes from the band structure itself. When summed over occupied bands in a ferromagnetic metal, the net current from this mechanism typically remains finite.&lt;/p&gt;&#xA;&lt;p&gt;There are also two extrinsic mechanisms in the presence of disorder, known as side-jump and skew scattering. Skew scattering is due to asymmetric disorder scattering when spin-orbit coupling is present. It is well-described by standard Boltzmann theory, and tends to dominate in highly conductive ferromagnets. The side-jump story is a complicated one. It can be related to a transverse displacement of an incoming electron hitting an impurity,  but ultimately its role is less clear and often less interesting. To quote Nagaosa et al.,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A practical approach, which is followed at present for materials in which &lt;span class=&quot;math-container&quot;&gt;$\sigma^{AH}$&lt;/span&gt; seems to be independent of &lt;span class=&quot;math-container&quot;&gt;$\sigma_{xx}$&lt;/span&gt; is to first calculate the intrinsic contribution to the AHE. If this explains the observation (and it appears that it&#xA;usually does), then it is deemed that the intrinsic mechanism dominates. If not, we can take some comfort from understanding on the basis of simple model results that there can be other contributions to &lt;span class=&quot;math-container&quot;&gt;$\sigma^{AH}$&lt;/span&gt; which are also independent of &lt;span class=&quot;math-container&quot;&gt;$\sigma_{xx}$&lt;/span&gt; and can for the most part be identified with the side-jump mechanism.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Rule of thumb:&lt;/strong&gt; Often the intrinsic mechanism dominates in systems with strong spin-orbit coupling, so it does seem likely to be the most important mechanism in TMDs (transition metal dichalcogenides). However, there may be some material and sample dependence.&lt;/p&gt;&#xA;&lt;h2&gt;What is the source of the quantum anomalous Hall effect?&lt;/h2&gt;&#xA;&lt;p&gt;This question has a much simpler answer: it's the intrinsic mechanism. To have a quantized response, we need something integer-valued to arise from one of these three mechanisms. The way to get that is to integrate the Berry curvature over a full band, and getting a nonzero Chern number. When can we integrate over a full band? Well, we want to avoid the typical situation in a metal, where there is an open Fermi sea, which would mean integrating over only some fraction of the states in a band (the occupied states). Instead, we generally want an insulating system. (This of course has the side effect of reducing the number of mobile carriers, thus decreasing the role of the extrinsic disorder mechanisms.)&lt;/p&gt;&#xA;&lt;p&gt;There were proposals that the QAHE state can occur in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.161414&quot; rel=&quot;noreferrer&quot;&gt;graphene with strong Rashba spin-orbit coupling and exchange effects&lt;/a&gt; (also &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.83.155447&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;). One way to achieve the exchange effects is to place the graphene sheet close to a ferromagnetic material, as has been explored experimentally &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5001318&quot; rel=&quot;noreferrer&quot;&gt;e.g. here&lt;/a&gt;. However, so far I don't think these efforts have succeeded in obtaining a quantized response. Generally it is difficult to achieve strong enough spin-orbit coupling in graphene. (Some readers may be familiar with the attempts of doping graphene to achieve a quantum spin Hall insulator.)&lt;/p&gt;&#xA;&lt;p&gt;Given the similarity between TMDs and graphene, I imagine these references can be good conceptual starting points also for TMDs. With the huge interest in Moiré structures, which allow tunable interaction strengths, there likely is a lot more literature on multilayer systems too. For example, &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.121.026402&quot; rel=&quot;noreferrer&quot;&gt;here's one paper&lt;/a&gt; proposing a quantum anomalous Hall effect regime in twisted bilayer TMDs. I'm however not up to date on the experimental situation in these materials.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-31T04:25:20.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1872" PostTypeId="2" ParentId="1865" CreationDate="2020-07-31T06:56:31.700" Score="9" Body="&lt;p&gt;I agree with the answer provided by Xivi76. I just wanted to add that some codes have a very nice functionality that facilitates convergence: rather than explicitly writing out a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid &lt;span class=&quot;math-container&quot;&gt;$n_1\times n_2\times n_3$&lt;/span&gt;, in which in principle you have to converge three values; you can instead specify a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point &lt;em&gt;spacing&lt;/em&gt; or &lt;em&gt;density&lt;/em&gt;, in which case you only have to vary one value. This is useful in the following situations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The cell lattice parameters are of different length, like in your graphite example. In this case, specifying the spacing directly generates fewer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points along Brillouin zone directions that are shorter (corresponding to longer real space lattice parameters).&lt;/li&gt;&#xA;&lt;li&gt;You are interested in performing a series of supercell calculations (e.g. to study phonons). In this case, specifying the spacing directly allows you to construct consistent &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grids for the various supercell sizes and shapes. This consistency is not perfect of course, because it may not be possible to exactly divide the dimensions of a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid precisely into a smaller Brillouin zone arising from a given supercell, but it does the best possible job.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As examples, Castep uses the keyword &lt;a href=&quot;http://www.tcm.phy.cam.ac.uk/castep/Parameters/node145.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;KPOINT_MP_SPACING&lt;/a&gt;, while Vasp uses the keyword &lt;a href=&quot;https://www.vasp.at/wiki/index.php/KSPACING&quot; rel=&quot;nofollow noreferrer&quot;&gt;KSPACING&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-08-02T07:03:14.767" LastActivityDate="2020-08-02T07:03:14.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1873" PostTypeId="2" ParentId="1808" CreationDate="2020-07-31T11:31:46.167" Score="7" Body="&lt;p&gt;The CONTCAR file contains the final position and velocities from a VASP run. You can find out more information from this &lt;a href=&quot;https://www.vasp.at/wiki/index.php/CONTCAR&quot; rel=&quot;noreferrer&quot;&gt;vasp wiki page&lt;/a&gt; or from VASP manual. Please note, the 3rd 4th and 5th lines are the information about lattice constants a,b and c respectively. If you open this in VESTA the values shown for a, b and c are the magnitude of the corresponding lattice vectors. If you are getting  &lt;span class=&quot;math-container&quot;&gt;$\alpha=90^{\circ}, \beta=90^{\circ}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma=120^{\circ}$&lt;/span&gt;, then you are with a relaxed hexagonal lattice.&lt;br/&gt;&#xA;From the CONTCAR it seems to me that the relaxed cell parameters are not of the hexagonal unit cell, as I can see a very small fraction on the y component of the a vector. For a perfectly hexagonal unit cell it must be zero.&lt;br/&gt;&#xA;You can try another run of &lt;code&gt;ISIF=3&lt;/code&gt; with a higher MP K-points grids(Assuming you are using optimised &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-centered K-points). This may take you to the perfectly relaxed unit cell for a hexagonal lattice.&lt;/p&gt;&#xA;" OwnerUserId="765" LastEditorUserId="5" LastEditDate="2020-07-31T12:25:18.220" LastActivityDate="2020-07-31T12:25:18.220" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1874" PostTypeId="2" ParentId="1845" CreationDate="2020-07-31T14:14:54.867" Score="5" Body="&lt;p&gt;Theoretical studies of open-shell excited species is a wide open field of active and cutting-edge research. I would suggest you to look for papers in theoretical photochemistry, reviews such as this &lt;a href=&quot;https://doi.org/10.1021/acs.chemrev.8b00244&quot; rel=&quot;nofollow noreferrer&quot;&gt;one&lt;/a&gt;, &lt;a href=&quot;https://www.springer.com/gp/book/9783319899718&quot; rel=&quot;nofollow noreferrer&quot;&gt;books&lt;/a&gt;, or even &lt;a href=&quot;http://pollux.chem.umn.edu/8021/Lectures/OpenShell_8.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;research workshops&lt;/a&gt;! In general, the density functionals should be used after serious testing for open-shell excited species.&lt;/p&gt;&#xA;&lt;p&gt;In general, I would recommend three main books for understanding and getting a general overview of density and wavefunction-based methods&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.wiley.com/en-us/Essentials+of+Computational+Chemistry%3A+Theories+and+Models%2C+2nd+Edition-p-9780470091821&quot; rel=&quot;nofollow noreferrer&quot;&gt;Essentials of Computational Chemistry: Theories and Models&lt;/a&gt;: General overview about various applications and areas in computational chemistry.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.wiley.com/en-us/Introduction+to+Computational+Chemistry%2C+3rd+Edition-p-9781118825990&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introduction to Computational Chemistry&lt;/a&gt;: More details about implementation and  formulations of computational methods.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9781119019572&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Electronic-Structure Theory&lt;/a&gt;: State-of-the-art textbook for wavefunction methods.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Note: I am in no way, shape, or form affiliated with Wiley&amp;amp;Co.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2020-07-31T14:31:20.180" LastActivityDate="2020-07-31T14:31:20.180" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1875" PostTypeId="1" AcceptedAnswerId="1876" CreationDate="2020-07-31T14:16:02.213" Score="10" ViewCount="245" Body="&lt;p&gt;I wanted to understand the Free Energy Perturbation in an NVT ensemble.&#xA;Wikipedia explains it as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ &#xA;\tag{1}&#xA;\Delta F = F_1 - F_0 = -\kappa T \ln \left&amp;lt;\exp\left( \frac{-(E_1-E_0)}{\kappa T}\right) \right&amp;gt;. &#xA;$$&lt;/span&gt;&#xA;Can I compute the above for micro-states separated by 50 timesteps? How do I deal with the average in that case: what is the strategy to actually compute it?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-07-31T20:27:31.533" LastActivityDate="2021-01-08T19:39:26.403" Title="Can I compute the free energy difference in (temporally) nearby micro-states using the Zwanzig equation for Free Energy Perturbation?" Tags="|molecular-dynamics|free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1876" PostTypeId="2" ParentId="1875" CreationDate="2020-07-31T15:32:42.227" Score="11" Body="&lt;p&gt;As I have previously discussed with you, &lt;strong&gt;there is no such thing as frame-wise free energies&lt;/strong&gt;, so the premise of your question is flawed. With this in mind, I think it  would actually be useful to tell something about what FEP &lt;em&gt;can&lt;/em&gt; do.&lt;/p&gt;&#xA;&lt;p&gt;FEP is used to calculate the free energy difference between two macrostates with corresponding Hamiltonians &lt;span class=&quot;math-container&quot;&gt;$H_0(x)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H_1(x)$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; denotes all phase space variables (you can also perturb the number of particles, the box volume and even work in other ensembles, but I am not going to deal with these cases here to keep it simple). Note that when we talk about different Hamiltonians, we mean &lt;strong&gt;different functional forms, not different values&lt;/strong&gt;. This means that for the same phase space point &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, the difference in these Hamiltonians &lt;span class=&quot;math-container&quot;&gt;$\Delta H(x)$&lt;/span&gt; is in general not zero. Then, the Zwanzig equation tells you that you can calculate the free energies between the two macrostates using the identity:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$e^{-\beta \Delta F} = \left&amp;lt;e^{-\beta \Delta H(x)}\right&amp;gt;_0\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The expectation value can also be written as an integral, just to make it more clear:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left&amp;lt;e^{-\beta \Delta H(x)}\right&amp;gt;_0 \equiv \int_{V} e^{-\beta \Delta H(x)} p_0(x) dx\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$p_0(x)$&lt;/span&gt; is the normalised Boltzmann distribution for ensemble 0:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$p_0(x) \equiv \frac{e^{-\beta H_0(x)}}{Z_0}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This basically means that you can in principle calculate the free energy between the two macrostates simply by sampling only one of them (which is what you do by running MD). After you obtain the  structures from ensemble 0, then you can evaluate &lt;span class=&quot;math-container&quot;&gt;$e^{-\beta \Delta H(x)}$&lt;/span&gt; for each one of them, and the average of these will eventually converge to &lt;span class=&quot;math-container&quot;&gt;$e^{-\beta \Delta F}$&lt;/span&gt;. Note that at the end of that, you are still calculating an ensemble average between the macrostates, and the microstates you get are simply a tool to get more datapoints for your free energy estimator.&lt;/p&gt;&#xA;&lt;p&gt;I guess this is the point where I have to note that the theory of this is sound and simple enough to understand but the primary problem with the Zwanzig equation is that you can have very quick decrease in sampling efficiency once your Hamiltonians become even slightly different. In these cases, it is advisable to introduce additional intermediate Hamiltonians, so that the variance in the exponential terms is manageable for each simulation.&lt;/p&gt;&#xA;&lt;p&gt;I am not going to go into more detail about the practicalities, though, because I suspect that you don't actually need FEP for your application, judging by your previous questions. Since FEP is only relevant if you are trying to calculate free energy difference between two Hamiltonians, I will reiterate that if you want to calculate the effective free energy between different regions of phase space with the same Hamiltonian, then you need methods that calculate potentials of mean force (PMFs), such as umbrella sampling, metadynamics, etc, that need you to define a reaction coordinate.&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="5" LastEditDate="2021-01-08T19:39:26.403" LastActivityDate="2021-01-08T19:39:26.403" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1877" PostTypeId="5" CreationDate="2020-07-31T19:11:36.290" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:11:36.290" LastActivityDate="2020-07-31T19:11:36.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1878" PostTypeId="4" CreationDate="2020-07-31T19:11:36.290" Score="0" Body="For questions about algorithms and numerical methods." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:11:36.290" LastActivityDate="2020-07-31T19:11:36.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1879" PostTypeId="5" CreationDate="2020-07-31T19:14:20.763" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:14:20.763" LastActivityDate="2020-07-31T19:14:20.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1880" PostTypeId="4" CreationDate="2020-07-31T19:14:20.763" Score="0" Body="Questions about quantum dynamics methods (MCTDH, t-DMRG, Feynman integral dynamics, etc.), or in some cases about quantum dynamics itself. Quantum dynamics is usually the dynamics of wavefunctions, density matrices, reduced density matrices, Wigner functions, or properties/expectation-values." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:14:20.763" LastActivityDate="2020-07-31T19:14:20.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1881" PostTypeId="5" CreationDate="2020-07-31T19:22:45.840" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:22:45.840" LastActivityDate="2020-07-31T19:22:45.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1882" PostTypeId="4" CreationDate="2020-07-31T19:22:45.840" Score="0" Body="Questions about solid state physics." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-07-31T19:22:45.840" LastActivityDate="2020-07-31T19:22:45.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1883" PostTypeId="2" ParentId="1551" CreationDate="2020-07-31T23:03:21.503" Score="13" Body="&lt;p&gt;Spherical harmonics are not themselves full atomic orbitals. Consider the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hydrogen_atom#Wavefunction&quot; rel=&quot;noreferrer&quot;&gt;Hydrogen wave function&lt;/a&gt;, which separates into a radial part and an angular part. The latter is a spherical harmonic, but the former is some other function (in the case of Hydrogen it's a Laguerre polynomial). In general, we can approximate the angular part for other atoms with the same spherical harmonics, but we usually don't  know the radial part analytically. Hence, if you want to directly evaluate Eq. (1) by integration you also need to find the radial part somewhere. The strength of Slater's and Koster's work, however, is that we can avoid this problem entirely, by hiding all radial dependence in the Slater-Koster parameters (in your example they are &lt;span class=&quot;math-container&quot;&gt;$V_{pd\sigma}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_{pd\pi}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;For simplicity, I'll focus on the case of an &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; overlap. This simplifies the geometry, and will let me borrow pictures and notation from &lt;a href=&quot;http://www.menet.umn.edu/%7Edtraian/tony-thesis.pdf&quot; rel=&quot;noreferrer&quot;&gt;this thesis&lt;/a&gt;. Let's say we have an &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; orbital at site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; with wave function &lt;span class=&quot;math-container&quot;&gt;$\psi_{is}$&lt;/span&gt;, and a &lt;span class=&quot;math-container&quot;&gt;$p_\alpha$&lt;/span&gt; orbital at site &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; with wave function &lt;span class=&quot;math-container&quot;&gt;$\psi_{jp_\alpha}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\alpha \in \{x,y,z\}$&lt;/span&gt;. In Dirac's bra-ket notation, the overlap between them can be written&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{s,p_\alpha}=\langle \psi_{is}|H_{2c}|\psi_{jp_\alpha}\rangle = \langle S|H_{2c}|P_\alpha\rangle, \tag{3}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$H_{2c}$&lt;/span&gt; is the two-center Hamiltonian, and we've introduced short-hand notation for the the two wave functions. Of course, behind the bra-ket notation you have exactly the kind of overlap integral shown in Eq. (1).&lt;/p&gt;&#xA;&lt;p&gt;Next step is to work out the geometry. Let &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt; be the vector connecting sites &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, and let &lt;span class=&quot;math-container&quot;&gt;$\vec{d}$&lt;/span&gt; be a unit vector along the same direction. We decompose the &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; orbital at site &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; into components parallel to (&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;) and perpendicular to (&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;) the vector &lt;span class=&quot;math-container&quot;&gt;$\vec{d}$&lt;/span&gt;, as shown in this figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nJ93C.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nJ93C.png&quot; alt=&quot;S-p atomic orbital overlap decomposition&quot; /&gt;&lt;/a&gt;&#xA;Figure from Anthony Carlson's 2006 MSc thesis at University of Minnesota.&lt;/p&gt;&#xA;&lt;p&gt;In this notation, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; (and also &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;) is used to denote the component of angular momentum about the axis &lt;span class=&quot;math-container&quot;&gt;$\vec{d}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; means zero, &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; means &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;, etc. To proceed, we also define &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; as pointing along the &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; orbital, and &lt;span class=&quot;math-container&quot;&gt;$\vec{n}$&lt;/span&gt; as a vector perpendicular to &lt;span class=&quot;math-container&quot;&gt;$\vec{d}$&lt;/span&gt; in the plane spanned by &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{d}$&lt;/span&gt;. Then, the &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; orbital (at site &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;) can be decomposed&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|P_\alpha\rangle = \vec{a}\cdot\vec{d}|P_\sigma\rangle + \vec{a}\cdot\vec{n}|P_\pi\rangle. \tag{4}&#xA;$$&lt;/span&gt;&#xA;Then, the overlap is simply&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle S|H_{2c}|P_\alpha\rangle = \left( \vec{a}\cdot \vec{d} \right) \langle S | H_{2c} |P_\sigma\rangle + \left( \vec{a}\cdot\vec{n} \right) \langle S | H_{2c} | P_\pi\rangle, \tag{5}&#xA;$$&lt;/span&gt;&#xA;where the second term is zero by symmetry. Further, we can easily express this in terms of directional cosines since we can without loss of generality choose &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; to be parallel to one of the coordinate axes. With&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;d_x=\frac{\vec{r}\cdot\hat{x}}{|\vec{r}|},\quad d_y=\frac{\vec{r}\cdot\hat{y}}{|\vec{r}|},\quad d_z=\frac{\vec{r}\cdot\hat{z}}{|\vec{r}|}, \tag{6}&#xA;$$&lt;/span&gt;&#xA;we get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle S|H_{2c}|P_\alpha\rangle = d_\alpha \langle S|H_{2c}|P_\alpha\rangle = d_\alpha V_{sp\sigma}, \tag{7}&#xA;$$&lt;/span&gt;&#xA;where all radial overlap is hidden in the parameter &lt;span class=&quot;math-container&quot;&gt;$V_{sp\sigma}$&lt;/span&gt;. In tight-binding models it's common to denote this overlap integral &lt;span class=&quot;math-container&quot;&gt;$t_{sp\sigma}$&lt;/span&gt; if it occurs in a hopping term.&lt;/p&gt;&#xA;&lt;p&gt;The same approach works for other orbital combinations. You just need to set up the geometry and coordinate systems properly, and know where the atomic orbitals point. (Admittedly this can become quite complicated in some systems, e.g. transition metal oxides.) Then the Slater-Koster parameters can be treated as tuning parameters - either tuned to explore possible phenomena in some system, or fit to reproduce some experiment or calculated band structure.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2020-07-31T23:27:12.233" LastActivityDate="2020-07-31T23:27:12.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1884" PostTypeId="2" ParentId="185" CreationDate="2020-07-31T23:52:30.607" Score="5" Body="&lt;p&gt;The continued fraction expansion is the most common way to calculate real-frequency dynamical Green's functions using &lt;a href=&quot;https://en.wikipedia.org/wiki/Lanczos_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Lanczos exact diagonalization&lt;/a&gt;. The method was introduced in this setting in &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.59.2999&quot; rel=&quot;noreferrer&quot;&gt;Gagliano, E. R., and Balseiro, C. A., &amp;quot;&lt;em&gt;Dynamical Properties of Quantum Many-Body Systems at Zero Temperature&lt;/em&gt;,&amp;quot; Physical Review Letters &lt;strong&gt;59&lt;/strong&gt;, 2999 (1987)&lt;/a&gt;, but a more common reference these days is &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.66.763&quot; rel=&quot;noreferrer&quot;&gt;Dagotto, E., &amp;quot;&lt;em&gt;Correlated electrons in high-temperature superconductors&lt;/em&gt;,&amp;quot; Reviews of Modern Physics &lt;strong&gt;66&lt;/strong&gt;, 763 (1994)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The same expansion was also used in the first attempts to calculate dynamical correlation functions using the density-matrix renormalization group, see &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.52.R9827&quot; rel=&quot;noreferrer&quot;&gt;K. A. Hallberg, &amp;quot;&lt;em&gt;Density-matrix algorithm for the calculation of dynamical properties of low-dimensional systems&lt;/em&gt;,&amp;quot; Physical Review B &lt;strong&gt;52&lt;/strong&gt;, R9827(R) (1995)&lt;/a&gt;. However, it was discovered that the method has some issues, especially with higher frequencie, see &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.60.335&quot; rel=&quot;noreferrer&quot;&gt;Kühner, T. D., and White, S. R., White&amp;quot;&lt;em&gt;Dynamical correlation functions using the density matrix renormalization group&lt;/em&gt;,&amp;quot; Physical Review B &lt;strong&gt;60&lt;/strong&gt;, 335 (1999)&lt;/a&gt;. Today, it's mostly been displaced by other methods in the DMRG setting.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-07-31T23:52:30.607" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1885" PostTypeId="2" ParentId="1432" CreationDate="2020-08-01T07:17:01.177" Score="5" Body="&lt;p&gt;I'm always using CFOUR for CCSD(T) calculations, so bear with me. With CFOUR you can actually specify the irrep occupations, and works very well for the optimizations. But, there is one big snag. You need to master Z-matrices.&lt;/p&gt;&#xA;&lt;p&gt;Now back to your question. If you know it should be symmetric, why not simply impose symmetry?&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2020-08-01T07:17:01.177" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1886" PostTypeId="2" ParentId="1864" CreationDate="2020-08-01T07:26:27.050" Score="4" Body="&lt;p&gt;Since the basis set seems to play a big role, from my paper (1999):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;A lot of effort has been put into constructing basis sets specially&#xA;designed for accurate calculations of the polarizability [18–22].&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;[18] H.-J. Werner, W. Meyer, Mol. Phys. 31 (1976) 855–872. &lt;br&gt;[19] A.J. Sadlej, Theor. Chim. Acta 81 (1991) 329.&lt;br&gt;&#xA;[20] A.J. Sadlej, Theor. Chim. Acta 81 (1991) 45.&lt;br&gt;&#xA;[21] A.J. Sadlej, M. Urban, J. Mol. Struct. (THEOCHEM) 80 (1991) 234.&lt;br&gt;&#xA;[22] A.J. Sadlej, Theor. Chim. Acta 79 (1991) 123.&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Have you tried the Sadlej basis sets? Or the Frank Jensen ones?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.dx.doi.org/10.1080/00268976.2013.793832&quot; rel=&quot;nofollow noreferrer&quot;&gt;We used&lt;/a&gt; Jensen's pcS-n for NMR properties, and I know that for polarizability it is not the nuclear region but the extended region that needs to be described well, but I was just wondering how good they are. At least in our study they converged much better with basis-set cardinal number than Dunning's ones.&lt;/p&gt;&#xA;" OwnerUserId="998" LastEditorUserId="5" LastEditDate="2020-08-01T15:27:30.460" LastActivityDate="2020-08-01T15:27:30.460" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1887" PostTypeId="1" AcceptedAnswerId="1893" CreationDate="2020-08-01T15:14:28.393" Score="10" ViewCount="619" Body="&lt;p&gt;Usually it is suggested to do a phonon calculation. What are the other ways?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="984" LastEditDate="2020-08-01T19:18:56.067" LastActivityDate="2020-08-03T09:05:17.650" Title="What are the methods that can be used to ensure that an optimized geometry is a local minimum?" Tags="|density-functional-theory|phonons|vibrations|geometry|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1888" PostTypeId="1" CreationDate="2020-08-01T16:10:58.887" Score="10" ViewCount="1714" Body="&lt;p&gt;I have generated MOs of a molecular system and I need to recreate its electronic density via &lt;span class=&quot;math-container&quot;&gt;$\rho(r)=\sum_{A_i}|\psi_i(\mathbf{r})|^2$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is a set of occupied MOs. I am trying to do this via extracting each MO individually in Gaussian16 Cubegen utility:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cubegen 16 MO=&lt;span class=&quot;math-container&quot;&gt;${i} input.fchk MO$&lt;/span&gt;{i}.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am looking for post-processing codes which can manipulate gaussian cube data, i.e., square and summation, preferably in a batch-processing fashion. For the codes I know, Gaussian's Cubman can add only two cubes files at a time; &lt;a href=&quot;https://github.com/funkymunkycool/Cube-Toolz&quot; rel=&quot;noreferrer&quot;&gt;another&lt;/a&gt; code has issues with Gaussian's MO cube file format. I tried to understand PySCF implementation, but I am not able to fully grasp it. If someone has a simpler, standalone implementation for such a code, please let me know in the answers below.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2020-08-02T16:23:17.643" LastActivityDate="2021-09-11T21:47:15.353" Title="Codes for post-processing Gaussian cube files?" Tags="|electronic-structure|one-topic-per-answer|gaussian|open-source|pyscf|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1889" PostTypeId="1" AcceptedAnswerId="1900" CreationDate="2020-08-01T17:28:12.437" Score="12" ViewCount="118" Body="&lt;p&gt;What are the current theories of computational chemistry for studying homochirality (for example the phenomenon discussed &lt;a href=&quot;https://www.quantamagazine.org/chiral-key-found-to-origin-of-life-20141126/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;https://www.nature.com/articles/nchem.1264&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and in many other places)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://fias.uni-frankfurt.de/%7Eberger/group/Electroweak/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electroweak chemistry&lt;/a&gt; has been developed to answer such questions on a more physical level, but do we have significant results or understanding of chirality from this theory?&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2020-08-02T16:33:51.623" LastActivityDate="2020-08-03T07:15:56.013" Title="Theoretical origins of stereochemistry" Tags="|reference-request|relativistic|biomaterials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1890" PostTypeId="2" ParentId="1888" CreationDate="2020-08-01T17:39:52.173" Score="8" Body="&lt;h2&gt;Multiwfn&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiwfn&lt;/a&gt; is a great tool for cube file analysis and wfn file analysis that can probably do almost everything you want to do.  It is capable of doing math between cube files, outputting that file and then continuing to do more math.  I believe it also allows for custom formulas to be input into the source code in some straightforward way (I have never needed to) then use it for convenience.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-08-02T16:18:18.157" LastActivityDate="2020-08-02T16:18:18.157" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="1891" PostTypeId="2" ParentId="1676" CreationDate="2020-08-01T19:48:14.900" Score="4" Body="&lt;p&gt;Generally speaking, Ehrenfest dynamics tries to model nonadiabatic processes. These are processes where an electronic wavepacket propagates on several potential energy surfaces. The different surfaces have different forces associated to them. This means that the parts of the wavepacket on the different surfaces move in different directions. Ultimately, this leads to decoherence - the parts on the different surfaces do not know about each other anymore.&lt;/p&gt;&#xA;&lt;p&gt;Ehrenfest dynamics produces only one trajectory that runs on all the potential surfaces in lockstep. This produces an artifical superposition of excited states, which has no possibility for decoherence.&lt;/p&gt;&#xA;&lt;p&gt;You can start with the discussion around Figure 3 in &lt;a href=&quot;https://dx.doi.org/10.1021/acs.jctc.9b00525&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 2019, 15, 5031&lt;/a&gt; and work your way up from there.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-08-01T19:48:14.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1892" PostTypeId="2" ParentId="1888" CreationDate="2020-08-01T20:02:28.463" Score="6" Body="&lt;h2&gt;TheoDORE&lt;/h2&gt;&#xA;&lt;p&gt;Dealing with cube files is fairly easy as long as they all have the same grid definition. A cube file is basically just a long vector of numbers and you can add and multiply them as you wish. You can for example check &lt;a href=&quot;https://sourceforge.net/p/theodore-qc/code/ci/master/tree/theodore/lib_util.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;lib_util.py&lt;/a&gt; of the TheoDORE package. This might do what you want in a simple scriptable form. Maybe the &lt;code&gt;lin_comb&lt;/code&gt; routine does what you want. Or you can write an analagous routine for adding squared values.&lt;/p&gt;&#xA;" OwnerUserId="115" LastEditorUserId="5" LastEditDate="2020-08-02T16:18:38.207" LastActivityDate="2020-08-02T16:18:38.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1893" PostTypeId="2" ParentId="1887" CreationDate="2020-08-02T07:44:00.717" Score="10" Body="&lt;p&gt;This depends on what you are studying. For molecular systems without periodicity, the simplest approach is to carry out a vibrational frequency analysis and confirm that there are no imaginary modes. It is considered standard to carry out a vibrational frequency analysis for all investigated structures, provided the number of investigated systems is not prohibitively large.&lt;/p&gt;&#xA;&lt;p&gt;For extended solids, which it sounds like you're modeling, it is much less common to confirm the result of a structure relaxation is indeed a minimum, although it can't hurt and is always a good idea if feasible. A phonon calculation can indeed be used to confirm your location in the potential energy surface.&lt;/p&gt;&#xA;&lt;p&gt;There are other options though for extended solids. If you are modeling the adsorption of a molecule onto a surface, you can likely assume that the surface atoms are near or at their minimum energy positions (if you have pre-relaxed the adsorbate-free structure). In this case, you could perform a vibrational frequency analysis of just the adsorbate atoms (or, even better, the adsorbate atoms and a few nearby surface atoms) to confirm there are no imaginary modes. &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/vibrations/modes.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; has an excellent vibrational analysis function that works with many of the most popular DFT packages, which I recommend if you're using a code like VASP. Beyond this, you can always try slightly modifying the atomic positions of the converged structure in several different ways, re-optimizing each structure to see if the same low-energy configuration is found. Of course, this does not guarantee you have arrived at a local minimum, but it can provide further support.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-08-02T07:44:00.717" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1894" PostTypeId="2" ParentId="1865" CreationDate="2020-08-02T10:30:40.013" Score="7" Body="&lt;ul&gt;&#xA;&lt;li&gt;As far as my knowledge this a relationship between k-points and lattice constants values. I'll give you an example of a layered hexagonal material &lt;strong&gt;WS2&lt;/strong&gt;:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Lattice constants :&lt;/strong&gt; &lt;code&gt;a=3.17 b=3.17 c=12.41&lt;/code&gt; ; so &lt;code&gt;c/a = 12.41/3.17=3.91&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;K-points :&lt;/strong&gt; If I chose &lt;code&gt;kx=12&lt;/code&gt;, &lt;code&gt;ky&lt;/code&gt; will be equal to &lt;code&gt;12&lt;/code&gt; but &lt;code&gt;kz&lt;/code&gt; should be equal to an integer close to the &lt;code&gt;kx&lt;/code&gt; divided by &lt;strong&gt;&lt;code&gt;c/a&lt;/code&gt;&lt;/strong&gt;. I mean &lt;code&gt;kz=12/3.91=3.06&lt;/code&gt;. So the consistent k-points will be &lt;code&gt;12x12x3&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's say that I chose &lt;code&gt;kx=9&lt;/code&gt;, &lt;code&gt;ky=9&lt;/code&gt; and &lt;code&gt;kz&lt;/code&gt; will be =9/(c/a)=9/4=&lt;code&gt;2.25&lt;/code&gt;. So we'll have &lt;code&gt;9x9x2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Remember it is linked with your c/a ration and k-points should be integers.&lt;/li&gt;&#xA;&lt;li&gt;You have to conduct first K-points convergence tests for multiple&#xA;values (e.g.: 9x9x2, 10x10x3,11x11x3 ,12x12x3 ...etc) and check where the energy is minimum.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note : for cubic systems the k-points are equal, because lattice constants are equal.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2020-08-02T10:30:40.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1896" PostTypeId="1" AcceptedAnswerId="3884" CreationDate="2020-08-02T11:41:58.300" Score="21" ViewCount="4221" Body="&lt;p&gt;Let's say I want to relax a structure using VASP. K-points and ENCUT convergence tests must be conducted &lt;strong&gt;&lt;code&gt;before or after relaxation&lt;/code&gt;&lt;/strong&gt;? and which tags should be included inside the &lt;code&gt;INCAR&lt;/code&gt; file during convergence tests?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="88" LastEditDate="2020-08-02T12:03:08.857" LastActivityDate="2020-12-06T05:11:48.953" Title="k-points and ENCUT convergence tests before or after relaxation?" Tags="|density-functional-theory|vasp|quantum-espresso|convergence-test|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1897" PostTypeId="2" ParentId="1896" CreationDate="2020-08-02T15:47:38.703" Score="25" Body="&lt;p&gt;This is a good question. In general, it often may not matter too much, but as with all aspects of numerical convergence, the only way for you to know for sure is to investigate. The concise answer is that in most cases, you can probably feel quite comfortable using the starting geometry for your convergence tests if: 1) the structure is reasonable (e.g. it's from experiments, taken from a database, converged at a different level of theory) and 2) the lattice constants do not change substantially after structure relaxation. Regardless, for any properties of interest, it is never a bad idea to check every now and then that the settings you are using are numerically converged.&lt;/p&gt;&#xA;&lt;p&gt;This is a matter of opinion, but here is what I would suggest if you're particularly unsure. Carry out an (initial) structure relaxation with what are likely to be some reasonably accurate settings. The general rule-of-thumb for volume relaxation is to use (at least) 1.3 times the largest &lt;code&gt;ENMAX&lt;/code&gt; value in your pseudopotential (&lt;code&gt;POTCAR&lt;/code&gt;) files to prevent Pulay stresses. I often just use 520 eV for the plane-wave kinetic energy cutoff (&lt;code&gt;ENCUT&lt;/code&gt;) since that's the maximum it could possibly be using the standard VASP 5.4 pseudopotentials. As for the number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points, that's going to be a bit trickier, but you can follow the lead of the &lt;a href=&quot;http://oqmd.org/documentation/vasp&quot; rel=&quot;noreferrer&quot;&gt;OQMD&lt;/a&gt; or the &lt;a href=&quot;https://materialsproject.org/docs/calculations&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; and use ~1000 &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points per number of atoms in the cell, distributed in a way that places more &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points along dimensions with smaller lattice constants. This would likely give you a quite reliable geometry to start with.&lt;/p&gt;&#xA;&lt;p&gt;With this cleaner geometry, you can carry out your convergence tests and decide what you will use for the remainder of the project when studying this system. Of course, any new settings you decide upon must be used to re-relax your structure such that it is again at a local minimum in the potential energy surface for the production-quality settings you have chosen. Since the initial geometry and final geometry here are likely to be quite similar, you can feel comfortable not running yet another convergence test, although there is never harm in checking.&lt;/p&gt;&#xA;&lt;p&gt;As for input flags, the following are the most important:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Plane-wave kinetic energy cutoff (&lt;code&gt;ENCUT&lt;/code&gt;): Higher values are better but are more computationally expensive. I would start with the default obtained using &lt;code&gt;prec='Accurate'&lt;/code&gt; and/or 1.3 times the maximum &lt;code&gt;ENMAX&lt;/code&gt; value in your &lt;code&gt;POTCAR&lt;/code&gt; files. Increase &lt;code&gt;ENCUT&lt;/code&gt; by increments of ~50 eV or so until you feel comfortable with the results.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points (&lt;code&gt;KPOINTS&lt;/code&gt;): Again, higher numbers are better here. In general, you want to use more &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points along smaller lattice constants. There are &lt;a href=&quot;https://pymatgen.org/pymatgen.io.vasp.inputs.html#pymatgen.io.vasp.inputs.Kpoints.automatic_density&quot; rel=&quot;noreferrer&quot;&gt;several utilities&lt;/a&gt; in Pymatgen and elsewhere, such as the &lt;a href=&quot;http://muellergroup.jhu.edu/K-Points.html&quot; rel=&quot;noreferrer&quot;&gt;JHU &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid server&lt;/a&gt;, that can be very helpful with arranging the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points. The ideal number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points changes significantly with cell volume, so this is one to keep an eye on if your structure changes drastically after relaxation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The numerical tolerance for converging the electronic energy (&lt;code&gt;EDIFF&lt;/code&gt;): A smaller number is better here. For ensuring accurate geometries, this value does not have to be too small. A default of &lt;code&gt;10E-4&lt;/code&gt; is often okay. However, if the potential energy surface is flat, this may lead to issues converging the structure to the local minimum because of numerically inaccurate forces, in which case you would need to decrease the value further. For other properties, you may need a lower value of &lt;code&gt;EDIFF&lt;/code&gt; as well, which I recommend decreasing in intervals of one order of magnitude until you are satisfied. Typically, I use &lt;code&gt;1E-6&lt;/code&gt; for most of my work.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The numerical tolerance for the forces during structure relaxation (&lt;code&gt;EDIFFG&lt;/code&gt;): This tells VASP when to stop the structure relaxation, and values closer to zero will bring you closer to the desired point in the potential energy surface. Generally, I would recommend going no higher than 0.05 eV/Å (&lt;code&gt;EDIFF=-0.05&lt;/code&gt;) and often recommend 0.03 eV/Å as a good starting point. Try decreasing this value in intervals of ~0.01 eV/Å until you are satisfied. You can also use a tolerance based solely on energy differences between iterations, but I generally recommend against this in practice.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The following flags are less crucial but still important to consider:&lt;/p&gt;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;The size of the integration grid (&lt;code&gt;NGX&lt;/code&gt;, &lt;code&gt;NGY&lt;/code&gt;, &lt;code&gt;NGZ&lt;/code&gt;): Larger values are better here. Generally speaking, I have never found this to be an issue if you use &lt;code&gt;prec='Accurate'&lt;/code&gt;, which automatically sets the values for the integration grid to quite reasonable defaults. This will effect the energy as well as several derived properties, perhaps most notably are partial atomic charges, such as those via the &lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;noreferrer&quot;&gt;Bader&lt;/a&gt; method. Some meta-GGA functionals have been shown to be quite sensitive to the integration grid, but I have found &lt;code&gt;prec='Accurate'&lt;/code&gt; to still yield appropriate results in this case.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The smearing width (&lt;code&gt;SIGMA&lt;/code&gt;). Depending on the smearing scheme used (&lt;code&gt;ISMEAR&lt;/code&gt;), lower values often yield better numerical precision, but potentially at the expense of a more difficult convergence of the self-consistent field. You will want to confirm the the energy before and after extrapolation to the 0 K limit (from the fictitious temperature that is dependent on &lt;code&gt;SIGMA&lt;/code&gt;) is reasonably close to one another. The closer these energies are, the less you have to worry about an inaccurate interpolation. If there are concerns, I often suggest using Gaussian smearing (&lt;code&gt;ISMEAR=0&lt;/code&gt;) with &lt;code&gt;SIGMA&lt;/code&gt; set to &lt;code&gt;0.01&lt;/code&gt;, which you can tweak by half-orders of magnitude or so depending on what you observe.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The number of bands (&lt;code&gt;NBANDS&lt;/code&gt;). Higher numbers are better, and this will most notably influence band structures. Often, the default values are a reasonable start.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The number of grid-points when evaluating the density of states (DOS) (&lt;code&gt;NEDOS&lt;/code&gt;). Higher numbers are better, and generally the default of 301 is not ideal. Increasing this to 2000 or so may yield better results. This will only influence the DOS, so you can neglect this setting if you are not interested in visualizing the DOS for your work.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;An important note in all of this is that whether you are numerically converged or not will depend strongly on the property of interest. A geometry is going to be much less sensitive to numerical convergence than a electronic property like a band gap. Also, if you are interested in producing numerically precise energies, then it is worth remembering that all energies are only meaningful when they are relative. For instance, if you are modeling a reaction energy, there will be both a product and a reactant. In these cases, due to fortuitous error-cancellation, energy &lt;em&gt;differences&lt;/em&gt; will converge significantly faster than absolute energies, and you may wish to perform your convergence tests on the difference to reduce the overall computational cost of your project.&lt;/p&gt;&#xA;&lt;p&gt;You may also find my answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/170/what-are-good-ways-to-reduce-computing-time-when-working-with-large-systems-in-v/172#172&quot;&gt;&amp;quot;What are good ways to reduce computing time when working with large systems in VASP?&amp;quot;&lt;/a&gt; to be helpful.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-08-02T18:08:46.353" LastActivityDate="2020-08-02T18:08:46.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1898" PostTypeId="2" ParentId="1896" CreationDate="2020-08-02T18:39:53.993" Score="11" Body="&lt;p&gt;Andrew's answer covers a lot of other considerations but not some useful additional ones in the case of relaxing unit cell parameters in solids. If the unit cell is being optimized in addition to atomic positions, the cell stress converges more slowly with respect to energy cutoff and k-points compared to forces and total energy. A good way to check this is to converge the calculated total stress to within 0.03 kbar with your initial structure (if it's reasonably close to the relaxed one, like an experimental structure). Then when you do your relaxation (making the total stress zero or a desired set value), an additional scf calculation is performed, resetting the G-vectors to those for the new unit cell (QE does this automatically, I'm not sure about VASP). If the stress from that calculation is not also zero, you are possibly not converged with respect to cutoff.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-08-02T18:39:53.993" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1899" PostTypeId="2" ParentId="1684" CreationDate="2020-08-03T04:11:50.677" Score="5" Body="&lt;p&gt;To start with, while it's not as necessary, you can apply symmetry arguments to one-electron integrals. Consider &lt;span class=&quot;math-container&quot;&gt;$\langle\mu|O_1|\nu\rangle$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$O_1$&lt;/span&gt; is some one-electron operator. If the molecule has some point group symmetry, we can form basis functions/operators that are irreducible representations of the group. Once we have the functions expressed in terms of irreps (as described in a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1789/are-there-computational-methods-for-the-determination-of-the-point-group-symmetr?r=SearchResults&quot;&gt;question&lt;/a&gt; here), we can easily determine which integrals must vanish just from the group multiplication table: &lt;span class=&quot;math-container&quot;&gt;$$\Gamma_{\text{TSR}}\notin\Gamma_\mu \otimes\Gamma_{O_1} \otimes\Gamma_\nu\to\langle\mu|O_1|\nu\rangle=0$$&lt;/span&gt; Here, &lt;span class=&quot;math-container&quot;&gt;$\Gamma_x$&lt;/span&gt; is the irrep of &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and TSR is the totally symmetric representation. So if the symmetric representation is not in the product of the irreps, the integral must vanish.&lt;/p&gt;&#xA;&lt;p&gt;To give a concrete example, consider a water molecule, which has &lt;span class=&quot;math-container&quot;&gt;$C_{2v}$&lt;/span&gt; symmetry (&lt;a href=&quot;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=402&amp;amp;option=4&quot; rel=&quot;nofollow noreferrer&quot;&gt;character table&lt;/a&gt;) We can look at the very simple example of overlap integrals (&lt;span class=&quot;math-container&quot;&gt;$O_1=1$&lt;/span&gt;). In this case, the integrals will only be nonzero when the irrep of &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; are the same, as this ensures the TSR is in their product. In the best case in terms of reducing the cost, you will have an equal number of basis functions of each irrep. For water, this would reduce the number of overlap integrals needed from &lt;span class=&quot;math-container&quot;&gt;$(N^2+N)/2$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$(\frac{N^2}{4}+N)/2$&lt;/span&gt; where the &lt;span class=&quot;math-container&quot;&gt;$4$&lt;/span&gt; comes from the number of irreps.&lt;/p&gt;&#xA;&lt;p&gt;Two electron integrals are in principle the same, but involve 4 functions rather than 2. Also, we are almost always interested in the Coulomb operator, which is totally symmetric, so we only need to consider the irreps of the 4 functions. We can reduce this to looking at the symmetry of pairs of functions/charge distributions to make the evaluation basically the same as the case of the overlap integrals, though obviously with many more integrals. Combined with integral screening (e.g Cauchy-Schwarz) you can see a fairly substantial reduction in size. While Hartree-Fock is formally &lt;span class=&quot;math-container&quot;&gt;$O(N^4)$&lt;/span&gt; due to forming the 2e integrals, in practice with codes that's use integral screening and symmetry this can be reduced to less than &lt;span class=&quot;math-container&quot;&gt;$O(N^3)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Others have mentioned the limits of applying symmetry and that many molecules in for example biology have no symmetry. However, there are areas like inorganic chemistry, where many molecules of interest are symmetric or nearly so. This can used to accelerate, as an example, geometry optimizations by using the idealized, symmetric geometry, which can be obtained at reduced cost, as a guess to obtain the true, nearly symmetric structure.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-21T03:33:50.713" LastActivityDate="2021-07-21T03:33:50.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1900" PostTypeId="2" ParentId="1889" CreationDate="2020-08-03T07:15:56.013" Score="9" Body="&lt;p&gt;Relating to the question about electroweak chemistry: the parity violation effect of the weak force on chiral asymmetry has been considered for quite a while now. A good accessible introduction to the problem can be found here: &lt;a href=&quot;http://www.ir.ethz.ch/preprints/MQ354%20Quack%20Kanazawa%20Workshop.pdf&quot; rel=&quot;noreferrer&quot;&gt;Molecular Parity Violation and Chirality: The Asymmetry of Life and the Symmetry Violations in Physics, by Martin Quack.&lt;/a&gt; Another rather early papers on electroweak chemistry can be found here: &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/1439-7641(20000804)1:1%3C57::AID-CPHC57%3E3.0.CO;2-J&quot; rel=&quot;noreferrer&quot;&gt;Electroweak Quantum Chemistry of Alanine: Parity Violation in Gas and Condensed Phases&lt;/a&gt; - more literature can be pulled out from the citations metric to the above papers.&lt;/p&gt;&#xA;&lt;p&gt;Several candidate molecules have been proposed, such as CHBrClF, HSSH and derivatives of the latter, in which this asymmetry could be measured spectroscopically. So far however, such an observation is still elusive, due to weakness of this naturally occurring interaction, which may be causing only very small shift between the sets of rotational-vibrational energy levels of the left-handed and right-handed forms of a chiral species.&lt;/p&gt;&#xA;&lt;p&gt;Some recent attempts to measure parity violation in chiral molecules have been reported here: &lt;a href=&quot;https://pubs.rsc.org/--/content/articlelanding/2017/cp/c7cp01139c/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;High-resolution FTIR spectroscopy of trisulfane HSSSH: a candidate for detecting parity violation in chiral molecules&lt;/a&gt;. A rather intriguing recent result reporting plausible 'electroweak interference' in asymmetric synthesis can be found here: &lt;a href=&quot;https://www.nature.com/articles/s41557-019-0321-y&quot; rel=&quot;noreferrer&quot;&gt;Energy threshold for chiral symmetry breaking in molecular self-replication&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Next, relating more to the first question: apart from natural possible sources of chiral asymmetry, some people proposed ways to synthetically induce and study this chiral asymmetry with appropriately tailored electromagnetic fields. Excellent frontier studies in this field are conducted in the O. Smirnova's group, see, for instance: &lt;a href=&quot;https://www.nature.com/articles/s41566-019-0531-2&quot; rel=&quot;noreferrer&quot;&gt;Synthetic chiral light for efficient control of chiral light–matter interaction&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Not to mention one, there are a bunch of approaches to achieve enantio-selective chiral response or dynamical discrimination (parity breaking) in chiral species. These approaches are largely based on the fact that a mixed product of some molecular properties, such as the electric dipole moment: &lt;span class=&quot;math-container&quot;&gt;$\vec{\mu}_a(R) \cdot \vec{\mu}_b(R) \times \vec{\mu}_c(R) = - \vec{\mu}_a(S) \cdot \vec{\mu}_b(S) \times \vec{\mu}_c(S)$&lt;/span&gt; changes sign between enantiomers (R/S) (this mixed product is &lt;em&gt;time-even&lt;/em&gt; and &lt;em&gt;parity-odd&lt;/em&gt;). M. Schnell's group is perhaps leading the way in enantio-sensitive spectroscopy, which utilizes the sign-change property of the mixed-dipole moment product: &lt;a href=&quot;https://www.nature.com/articles/nature12150&quot; rel=&quot;noreferrer&quot;&gt;Enantiomer-specific detection of chiral molecules via microwave spectroscopy&lt;/a&gt;. Suitable molecules must therefore have three significant components of the electric dipole moment and the interacting radiation must be resonant with three rotational transitions. This is however not enough to induce any dissymetry in populations of left- and right- enantiomers, only enantio-specific signal can be measured.&lt;/p&gt;&#xA;&lt;p&gt;For chiral discrimination to be possible a chiral molecule must interact with another chiral field. One proposal for such a discriminatory interaction is given here: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.123.243202&quot; rel=&quot;noreferrer&quot;&gt;Field-Induced Diastereomers for Chiral Separation&lt;/a&gt;, which is based on a more general quantity which is parity-odd and time-even: mixed product of the electronic polarisability and the electric dipole moment: &lt;span class=&quot;math-container&quot;&gt;$\alpha_{xz}\mu_y$&lt;/span&gt;, which in the presence of a chiral field is responsible for discrimination in rotational-vibrational populations in a wider class of chiral molecules. Only off-resonant lasers and a dc electric field are needed in this case to induce asymmetry in the populations of left- and right- enantiomers. Some natural environments can possibly create instances of similar conditions.&lt;/p&gt;&#xA;&lt;p&gt;I'm sure there are many other approaches, which I ignorantly omitted, and which more specifically target the problem of homochirality of life. &lt;em&gt;Please feel encouraged to update and edit with more references&lt;/em&gt;. So far, to the best of my knowledge a commonly considered mechanism for homochirality involve the weak interaction (parity violation). An interesting research path leads along the interactions of parity-odd molecular properties (mixed products of electronic polarisability and the electric dipole moment, or even nuclear quadrupole moment) with chiral electromagnetic fields.&lt;/p&gt;&#xA;" OwnerUserId="99" LastActivityDate="2020-08-03T07:15:56.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1901" PostTypeId="2" ParentId="1888" CreationDate="2020-08-03T08:44:20.137" Score="6" Body="&lt;p&gt;Why the need to reprocess .cube files, when you can&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;generate a cube straight away for the electron density with &lt;code&gt;cubegen&lt;/code&gt; (see &lt;code&gt;Density=Type&lt;/code&gt; in &lt;a href=&quot;https://gaussian.com/cubegen/&quot; rel=&quot;noreferrer&quot;&gt;the cubegen documentation&lt;/a&gt; or&lt;/li&gt;&#xA;&lt;li&gt;skip the cube files altogether and use the formatted checkpoint file for visualization, allowing an adaptable level of resolution and avoiding a huge amount of unnecessary storage?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are a bunch of programs that can read Gaussian formatted checkpoint files, e.g. Avogadro and IQmol, and visualize loads of properties.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-03T08:44:20.137" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1902" PostTypeId="2" ParentId="1887" CreationDate="2020-08-03T09:05:17.650" Score="5" Body="&lt;p&gt;In order to check if a geometry is a local minimum, it is a necessary and sufficient condition that the Hessian is positive (semi)definite, i.e. that the lowest eigenvalue of the nuclear Hessian is non-negative.&lt;/p&gt;&#xA;&lt;p&gt;Namely, expanding the energy &lt;span class=&quot;math-container&quot;&gt;$E({\bf R})$&lt;/span&gt; around the reference point &lt;span class=&quot;math-container&quot;&gt;${\bf R}_0$&lt;/span&gt; you have the Taylor expansion&#xA;&lt;span class=&quot;math-container&quot;&gt;$E({\bf R}) = E({\bf R}_0) - {\bf g} \cdot  ({\bf R}-{\bf R}_0)  + \frac 1 2 ({\bf R}-{\bf R}_0)^{\rm T} \cdot {\bf H} \cdot ({\bf R}-{\bf R}_0) + \mathcal{O}(|({\bf R}-{\bf R}_0)|^3)$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf g} = -[\nabla E({\bf R})]_{{\bf R}={\bf R}_0}$&lt;/span&gt; is the gradient and &lt;span class=&quot;math-container&quot;&gt;$H_{ij} = -\partial^2 E / \partial R_i \partial R_j $&lt;/span&gt; is the nuclear Hessian, which has the size &lt;span class=&quot;math-container&quot;&gt;$3N_{\rm atoms} \times 3N_{\rm atoms}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;At an extremum &lt;span class=&quot;math-container&quot;&gt;${\bf g}={\bf 0}$&lt;/span&gt;; this is what the optimizer finds for you. However, in some cases you can find that the Hessian has negative eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\lambda_i$&lt;/span&gt; with corresponding eigenvectors &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\rho}_i$&lt;/span&gt;. Now, if you set &lt;span class=&quot;math-container&quot;&gt;${\bf R}={\bf R}_0+\epsilon \boldsymbol{\rho}_i$&lt;/span&gt;, you will find that &lt;span class=&quot;math-container&quot;&gt;$E(\epsilon)=E({\bf R})=E({\bf R}_0) + \frac 1 2 \epsilon^2 \lambda_i +  \mathcal{O}(|\epsilon|^3)$&lt;/span&gt;. Since &lt;span class=&quot;math-container&quot;&gt;$\lambda_i&amp;lt;0$&lt;/span&gt;, this means you can find a lower energy by moving the atoms slightly along &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\rho}_i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A frequency calculation means computing &lt;strong&gt;all&lt;/strong&gt; eigenvalues of the Hessian, which becomes costly in large systems. (I'm not sure what is done in phonon calculations.) However, since you only need the lowest eigenvalue of the Hessian to check if you are at a local minimum, iterative diagonalizers such as the Davidson method can be used to focus only on the lowest roots of the nuclear Hessian.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, there are also some methods that need only gradient information to estimate the lowest eigenvalue of the nuclear Hessian; a &amp;quot;dimer method&amp;quot; has been suggested e.g. by Henkelman and Jónsson in &lt;a href=&quot;https://doi.org/10.1063/1.480097&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 111, 7010 (1999)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-03T09:05:17.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1903" PostTypeId="1" AcceptedAnswerId="1909" CreationDate="2020-08-03T12:48:26.823" Score="9" ViewCount="807" Body="&lt;p&gt;In the recent publication:&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1021/acsomega.9b03839&quot; rel=&quot;nofollow noreferrer&quot;&gt;Density Functional Theory Calculation on the Structural, Electronic, and Optical Properties of Fluorene-Based Azo Compounds&lt;/a&gt;&amp;quot;,&lt;/p&gt;&#xA;&lt;p&gt;the author claimed to have used Gaussian16 on an Intel core i3-6006U CPU@2.00 GHz, 1.99 GHz. In my understanding of such basis sets, it is difficult to do this.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to do TD-DFT calculations with 6-31+G(d,p) on a laptop?&lt;/p&gt;&#xA;" OwnerUserId="397" LastEditorUserId="142" LastEditDate="2020-08-05T10:36:42.813" LastActivityDate="2020-08-05T10:36:42.813" Title="Is it possible to do TD-DFT/6-31G+(d,p) calculations on a laptop?" Tags="|high-performance-computing|gaussian|td-dft|molpro|answer-with-calculation|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1904" PostTypeId="2" ParentId="1550" CreationDate="2020-08-03T19:40:41.147" Score="3" Body="&lt;p&gt;I'm not an expert in MD/AIMD software so I can really only discuss methods rather than an actual workflow/software that can carry it out.&lt;/p&gt;&#xA;&lt;p&gt;One approach that has been explored for accelerating AIMD and electronic structure methods in general is to combine calculations on fragments to approximate an electronic structure. &lt;a href=&quot;https://www.asc.ohio-state.edu/herbert.44/projects/AIMD.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;John Herbert's Group&lt;/a&gt; is doing work in this avenue, though I think it's too early for an established workflow to exist.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, if you are willing to sacrifice some accuracy for speed, you can do classical molecular dynamics. If you have a good force field for your system, you can just compute the overall dipole classically from the charges and distances, getting the IR spectrum from the Fourier transformed time correlation.&lt;/p&gt;&#xA;&lt;p&gt;A third route would be to use classical MD to get snapshots and then obtain the IR from an extrapolation/Boltzmann weighting of electronic structure calculations on these snapshots. I know of this being done for UV/Vis and I have found at least &lt;a href=&quot;https://europepmc.org/articles/pmc5544906/bin/nihms884238-supplement-supplementary_information.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;one paper&lt;/a&gt; that takes this sort of approach.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-08-03T19:40:41.147" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1905" PostTypeId="2" ParentId="1523" CreationDate="2020-08-03T20:27:22.300" Score="6" Body="&lt;p&gt;&lt;strong&gt;&lt;em&gt;ab initio&lt;/em&gt; Ehrenfest Dynamics&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;From &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.2008258&quot; rel=&quot;noreferrer&quot;&gt;Li &lt;em&gt;et.al.&lt;/em&gt;,2005, JCP&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&amp;quot;The Born Oppenheimer (BO) and extended Lagrangian (EL) trajectories are founded on the assumption that &lt;strong&gt;a single electronic potential surface governs the dynamics&lt;/strong&gt;. .. A major limitation of adiabatic trajectories is that they are not applicable to reactions involving nonadiabatic electronic processes, i.e., multiple potential-energy surfaces.&amp;quot;&lt;/em&gt; (Ex: Conical Intersections)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Dakif.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Dakif.png&quot; alt=&quot;Potential Energy Surfaces of multiple electronic states&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To account for electronic adiabaticity, we solve the full time-dependent Schrödinger equation for both nuclear and electronic degrees of freedom. In Ehrenfest methodology, the adiabatic potential energy surface&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ &#xA;E_{eff} = \langle\Phi|\hat{H_{el}}|\Phi\rangle = \sum_i |a_i|^2 E_i^2$$&lt;/span&gt;&#xA;Thus, the atoms evolve on an effective potential representing an average over the adiabatic states weighted by their state populations &lt;span class=&quot;math-container&quot;&gt;$|a_i|^2$&lt;/span&gt;. The method is also therefore referred to as mean-field approach. As a comparison, for BOMD/Ehrenfest dynamics:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;BOMD&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}_{el} (\mathbf{r}; \mathbf{R}) \Phi_k(\mathbf{r}; \mathbf{R}) = E^{el}_k(\mathbf{R})\Phi_k(\mathbf{r}; \mathbf{R})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$M_I\ddot{\mathbf{R}}_I =-\nabla_IE^{el}_k(\mathbf{R})=-\mathop{\nabla_I}_{\text{min }\Phi_k}\langle\Phi_k|\hat{H}_{el}|\Phi_k\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The electronic wavefunction &lt;span class=&quot;math-container&quot;&gt;$\Phi_k(\mathbf{r}; \mathbf{R})$&lt;/span&gt; is static (only implicit time-dependence) and the nuclear degrees of freedom are handled classically. The nuclear degrees of freedom are decoupled from electronic degrees of freedom, while for each MD step the electronic wavefunction has to be optimized for the ground state.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ehrenfest dynamics&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$i\hbar\frac{\partial \Phi(\mathbf{r};\mathbf{R},t)}{\partial t}=&#xA;\hat{H}_{el} (\mathbf{r}; \mathbf{R}) \Phi(\mathbf{r};\mathbf{R},t) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$M_I\ddot{\mathbf{R}}_I =-\nabla_I\langle\hat{H}_{el}(\mathbf{r};\mathbf{R})\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here we have an explicit time dependence of the electronic wavefunction. Electronic and nuclear time evolutions are propagated with a three-time-step integrator. The electronic wavefunction is evolved via TD-SCF approach.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="7" LastEditDate="2020-08-03T20:41:18.680" LastActivityDate="2020-08-03T20:41:18.680" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1906" PostTypeId="1" CreationDate="2020-08-03T20:58:38.490" Score="9" ViewCount="266" Body="&lt;p&gt;What free quantum chemistry packages that have constrained DFT (CDFT) implemented? A google search does not reveal anything, perhaps there may exist a better resource to find the packages.&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="142" LastEditDate="2020-08-05T10:37:14.680" LastActivityDate="2020-08-05T10:37:14.680" Title="Freely available constrained DFT implementations" Tags="|density-functional-theory|software|open-source|software-recommendations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1907" PostTypeId="2" ParentId="1550" CreationDate="2020-08-03T21:09:39.327" Score="4" Body="&lt;p&gt;&lt;strong&gt;Vibrational maps and density of states&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In water AIMD community, to avoid excessively heavy calculations of molecular moments, researchers use velocity autocorrelation function (which converge much faster),  obtaining vibrational densities of state and use &lt;a href=&quot;http://pubs.acs.org/doi/10.1021/acs.chemrev.9b00813&quot; rel=&quot;nofollow noreferrer&quot;&gt;vibrational maps&lt;/a&gt; to scale the VDOS spectra appropriately. Many researchers also simply calculate &lt;a href=&quot;https://d-nb.info/1123074526/34&quot; rel=&quot;nofollow noreferrer&quot;&gt;vibrational/phonon DOS spectra&lt;/a&gt; as the partitioning of the total dipole moment into molecular dipole moments is not straightforward. VDOS spectra can also be used to &lt;a href=&quot;https://par.nsf.gov/servlets/purl/10080354&quot; rel=&quot;nofollow noreferrer&quot;&gt;compare and disentangle vibrational contributions&lt;/a&gt; from various molecular species in bulk phase.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="1151" LastEditDate="2020-08-03T21:20:23.723" LastActivityDate="2020-08-03T21:20:23.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1908" PostTypeId="2" ParentId="1906" CreationDate="2020-08-03T21:13:54.253" Score="8" Body="&lt;p&gt;&lt;strong&gt;CP2K&lt;/strong&gt; (condensed phase+gas-phase)&lt;/p&gt;&#xA;&lt;p&gt;This tutorial demonstrates how to perform constrained DFT (CDFT) simulations with &lt;a href=&quot;https://www.cp2k.org/howto:cdft&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;In CP2K multiple cónstraints for multiple cDFT states can be utilized.&lt;/li&gt;&#xA;&lt;li&gt;For the cDFT weight function, CP2K can utilize Becke or Hirshfeld partitioning.&lt;/li&gt;&#xA;&lt;li&gt;CP2K can perform fully QM or QM/MM MD simulations with cDFT for bulk systems in gaussian plane wave formalism.&lt;/li&gt;&#xA;&lt;li&gt;Extensive support and documentation available at &lt;a href=&quot;https://groups.google.com/g/cp2k&quot; rel=&quot;noreferrer&quot;&gt;cp2k's google groups&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Example publications: &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2020/cp/c9cp05133c&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.5038959&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202007813&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="1151" LastEditDate="2020-08-03T23:31:06.057" LastActivityDate="2020-08-03T23:31:06.057" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1909" PostTypeId="2" ParentId="1903" CreationDate="2020-08-03T21:25:52.170" Score="11" Body="&lt;h3&gt;Basis set name versus number of total orbitals&lt;/h3&gt;&#xA;&lt;p&gt;I would like to first address a part of the question that appears to be a misconception about the use of a 6-31+G(d,p) basis set, since you wrote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In my understanding of such basis sets, it is difficult to do this.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;6-31+G(d,p) is not a &amp;quot;big&amp;quot; or &amp;quot;small&amp;quot; basis set, unless we're dealing with a big or small number of atoms (and aiming for a big or small amount of accuracy in our solution to the electronic Schrödinger equation). 6-31+G(d,p) is a fairly &lt;em&gt;&lt;strong&gt;small&lt;/strong&gt;&lt;/em&gt; basis set if we are dealing with a small molecule and only aiming to do TD-DFT. As currently written, the question only indicates that the paper was studying &amp;quot;azo&amp;quot; compounds, so the question alone does not tell us if the basis set is manageable or not manageable on a laptop computer. The question mentioned a journal publication, and we have to look into that paper to see what specific &amp;quot;azo&amp;quot; molecules are being discussed, before we can assess anything.&lt;/p&gt;&#xA;&lt;h3&gt;The calculation mentioned in the paper is possible on a laptop&lt;/h3&gt;&#xA;&lt;p&gt;The largest XYZ file in the articles &lt;a href=&quot;https://pubs.acs.org/doi/suppl/10.1021/acsomega.9b03839/suppl_file/ao9b03839_si_001.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Supplementary PDF&lt;/a&gt; is for a molecule with 46 atoms: &lt;strong&gt;bis(9H-fluoren-2-yl)diazene&lt;/strong&gt; (which they call AzoFL). &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/1903/molpro.out&quot; rel=&quot;nofollow noreferrer&quot;&gt;I just ran for you&lt;/a&gt; a CCSD(T)/6-31+G(d,p) calculation in MOLPRO, which seems to show that 6-31+G(d,p) seems manageable for a 46-atom molecule. I am aware the authors of the paper mentioned in the question, used Gaussian16, but I do not have access to Gaussian, so I used MOLPRO, which I do not think will affect whether or not the calculation is feasible on a laptop.&lt;/p&gt;&#xA;&lt;p&gt;Since CSCD(T) is much more expensive than B3-LYP/TD-DFT (which is what is used in the paper), I conclude that B3-LYP/TD-DFT is feasible with the same or even smaller resources. The CCSD(T) calculation is still running, but the fact that it is running, is enough to know that it is possible (if the calculation is not possible due to lack of disk space or RAM, MOLPRO would have told us earlier in the output file).&lt;/p&gt;&#xA;&lt;p&gt;What I have finished though is HF and MP2, and neither of them (nor the integrals) took more than 1000 seconds:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; PROGRAMS   *        TOTAL      RMP2       RHF       INT&#xA; CPU TIMES  *      1872.67    488.34    832.73    551.49&#xA; REAL TIME  *      3816.76 SEC&#xA; DISK USED  *        84.74 GB&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The disk space needed was only 85GB, which most laptops do have available. Unfortunately MOLPRO did not print the &amp;quot;peak RAM usage&amp;quot;, and as user &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1903/is-it-possible-to-do-td-dft-calculations-with-large-basis-set-on-a-notebook#comment3284_1903&quot;&gt;Anyon has pointed out&lt;/a&gt;, the CPU you mention in your question has a maximum capacity of 32GB of RAM, so this is the main limitation. I can re-run the calculation to only use 32GB of RAM and see what happens, but when the total disk usage is 85GB, it essentially means that a machine with 32GB of RAM will be enough, even if it means some of the disk has to act as SWAP space. I would not recommend doing this very often though, because if you're reading and writing 85GB too often, the lifetime of your disk might be affected.&lt;/p&gt;&#xA;&lt;h3&gt;Concluding remarks&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is possible to do a 46-atom TD-DFT-B3LYP/6-31+G(d,p) calculation on a laptop with an Intel Core i3-6006U CPU, but it requires 85GB of disk space, and I wouldn't recommend doing such calculations often if you care about the lifetime of your disk.&lt;/li&gt;&#xA;&lt;li&gt;The name of the basis set, for example: 6-31+G(d,p), is not what matters in determining whether or not TD-DFT-B3LYP is possible, as much as the number of atoms, and more importantly the total number of orbitals.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-04T12:52:20.623" LastActivityDate="2020-08-04T12:52:20.623" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1910" PostTypeId="1" CreationDate="2020-08-04T10:18:53.080" Score="7" ViewCount="142" Body="&lt;p&gt;I need to perform some MD calculations and then trajectories of some small molecules analyzed.&lt;/p&gt;&#xA;&lt;p&gt;What I have is&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;protein&lt;/li&gt;&#xA;&lt;li&gt;cofactor (FAD)&lt;/li&gt;&#xA;&lt;li&gt;small molecule (either single O2 molecule or single Chlorine atom)&lt;/li&gt;&#xA;&lt;li&gt;crystallographic waters&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The software I can access is Gromacs (with yum install)&lt;/p&gt;&#xA;&lt;p&gt;I have tried and tried to get this to run (for 6 months perhaps), to no avail. The input files located on the web do not work on the version of Gromacs provided by the yum install command.&lt;/p&gt;&#xA;&lt;p&gt;Is there a kind soul somewhere that would have suitable input files that would do all the steps described below and who'd be willing to pass them on to me?&lt;/p&gt;&#xA;&lt;p&gt;What needs to be done is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;add waters to the crystallographic waters in order to fill a box of suitable size&lt;/li&gt;&#xA;&lt;li&gt;generate parameter and topology files for each component separately&lt;/li&gt;&#xA;&lt;li&gt;merge these into global parameter and topology files for the system&lt;/li&gt;&#xA;&lt;li&gt;run initial Energy Minimization&lt;/li&gt;&#xA;&lt;li&gt;run M.D. simulations&lt;/li&gt;&#xA;&lt;li&gt;analyze the trajectories of the small molecules.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1176" LastEditorUserId="5" LastEditDate="2020-08-30T21:57:09.713" LastActivityDate="2020-09-26T22:47:25.490" Title="How to do molecular dynamics calculations and analyse trajectories of small molecules?" Tags="|molecular-dynamics|gromacs|biomaterials|" AnswerCount="0" CommentCount="6" ClosedDate="2020-09-28T14:07:31.213" ContentLicense="CC BY-SA 4.0" />
  <row Id="1911" PostTypeId="1" AcceptedAnswerId="1914" CreationDate="2020-08-04T15:15:36.953" Score="12" ViewCount="931" Body="&lt;p&gt;Can someone that works with CASTEP and VASP explain to me how a workflow might change between the two programs?  I am very familiar with VASP but have not used CASTEP before.&lt;/p&gt;&#xA;&lt;p&gt;As an example, assuming we have an atomic model that is well defined (from a tool such as ASE) we can make a POSCAR file.  Likewise, the calculation parameters are largely set in the INCAR file.  How does CASTEP work in comparison?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="88" LastEditDate="2020-08-05T21:28:58.687" LastActivityDate="2022-07-12T15:57:27.650" Title="Moving from VASP to CASTEP for bulk crystal and surface calculations" Tags="|software|vasp|periodic-system|atomic-simulation-environment|castep|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1912" PostTypeId="5" CreationDate="2020-08-04T18:14:21.837" Score="0" Body="" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-08-04T18:14:21.837" LastActivityDate="2020-08-04T18:14:21.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1913" PostTypeId="4" CreationDate="2020-08-04T18:14:21.837" Score="0" Body="For questions related to 2-dimensional materials which are periodic, i.e. crystalline. " OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-08-04T18:14:21.837" LastActivityDate="2020-08-04T18:14:21.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1914" PostTypeId="2" ParentId="1911" CreationDate="2020-08-04T20:52:20.147" Score="11" Body="&lt;p&gt;The workflow transferring from VASP to CASTEP is quite similar. Within VASP, there are four main files that you need for a calculation:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;POSCAR – gives the positions of the atoms within the unit cell and its lattice vectors.&lt;/li&gt;&#xA;&lt;li&gt;KPOINTS – sets the k-point mesh to be used.&lt;/li&gt;&#xA;&lt;li&gt;POTCAR – determines the type of pseudopotential to be used.&lt;/li&gt;&#xA;&lt;li&gt;INCAR – controls most of the main calculation parameters.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;On the other hand, within CASTEP, there are two files, the seed.cell and the seed.param files, where seed is an arbitrary name you give to the system. The seed.cell essentially contains all of the POSCAR and KPOINT parameters at once. In CASTEP, the pseudopotential is automatically generated by the programme, so you do not need to procure a POTCAR file of any sort. The specific pseudopotential which you would like to use (i.e. NCP or USP) can be set within seed.cell file as well. The seed.param file is essentially the equivalent to the INCAR file in VASP and it controls the same types of calculation parameters (e.g. cutoff, XC functional, etc.).&lt;/p&gt;&#xA;&lt;p&gt;ASE supports CASTEP input and output formats, so atomic models can be written out into a seed.cell file the same way a POSCAR is written out with &lt;code&gt;ase.io.write&lt;/code&gt; using the keyword &lt;code&gt;format=castep-cell&lt;/code&gt;. Additionally, if you are already using the VASP calculator (&lt;code&gt;ase.calculators.vasp&lt;/code&gt;) within ASE to prepare your input parameters/files, there is also one for CASTEP (&lt;code&gt;ase.calculators.castep&lt;/code&gt;) as well.&lt;/p&gt;&#xA;" OwnerUserId="1008" LastEditorUserId="1008" LastEditDate="2020-08-06T22:15:38.917" LastActivityDate="2020-08-06T22:15:38.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1915" PostTypeId="2" ParentId="1865" CreationDate="2020-08-04T20:57:30.717" Score="6" Body="&lt;p&gt;I will try to give the most practical answer, the reality of &amp;quot;&lt;em&gt;is this converged&lt;/em&gt;&amp;quot; is that you cannot know without checking by going past it.  You say that you would like to save time doing these calculations, but the worst loss of time is sometimes the loss of your own human time as you get confusing results later.&lt;/p&gt;&#xA;&lt;p&gt;I am unsure how you came to the number of 4 (cell vector * kpts?), but lets see using GPAW if that makes sense.  I am using what are likely unconverged settings with an unrelaxed structure.  Even then, lets see if we see a convergence on a (12, 12, X) kpoint set.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EsMUD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EsMUD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, there is something strange going on around 6 or 7 kpts in the z direction but otherwise looks converged at 4.  Tightening my settings might remove that strange bump. If I saw this and could not correct it, I would probably choose to run initial optimizations at (12, 12, 4) and final optimizations at (12, 12, 8).&lt;/p&gt;&#xA;&lt;p&gt;I &lt;strong&gt;strongly&lt;/strong&gt; recommend you do the same and check what you see.  If you are unsure what convergence looks like you could provide us with a similar graph.  If you have a property of the system you are investigating, use that as well as total energy.&lt;/p&gt;&#xA;&lt;p&gt;GPAW version 20.1.0 and ASE version 3.19.2 were used to generate this data.  Here is the script I used.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import bulk&#xA;from ase.visualize import view&#xA;from gpaw import GPAW, PW&#xA;import matplotlib.pyplot as plt&#xA;from matplotlib.colors import LogNorm&#xA;import numpy as np&#xA;&#xA;a = 1.42&#xA;c = 6.70&#xA;&#xA;kpt_min = 1&#xA;kpt_max = 16&#xA;&#xA;atoms = bulk(&amp;quot;C&amp;quot;, crystalstructure=&amp;quot;hcp&amp;quot;, a=a, c=c)&#xA;&#xA;x = np.arange(kpt_min, kpt_max)&#xA;e = np.zeros((kpt_max-kpt_min))&#xA;&#xA;for index, kpt in enumerate(x):&#xA;    calc = GPAW(mode=PW(350), kpts=(12, 12, kpt), occupations={'name': 'fermi-dirac', 'width': 0.05})&#xA;    atoms.calc = calc&#xA;&#xA;    e[index] = atoms.get_potential_energy()&#xA;&#xA;plt.plot(x, e, linestyle=&amp;quot;-&amp;quot;, marker=&amp;quot;o&amp;quot;)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-04T20:57:30.717" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1916" PostTypeId="5" CreationDate="2020-08-04T22:17:19.750" Score="0" Body="&lt;p&gt;Other calculations such as &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1662/5&quot;&gt;this one&lt;/a&gt; could be included, but at present this tag is only used when an answer includes the result of running a calculation on a computer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-04T22:17:19.750" LastActivityDate="2020-08-04T22:17:19.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1917" PostTypeId="4" CreationDate="2020-08-04T22:17:19.750" Score="0" Body="Questions in which at least one answer contains the result of running a calculation on a computer, or perhaps writing some code." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-04T22:17:19.750" LastActivityDate="2020-08-04T22:17:19.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1918" PostTypeId="1" CreationDate="2020-08-04T23:51:46.493" Score="14" ViewCount="671" Body="&lt;p&gt;Let's say you optimize an experimental geometry of a structure with very large basis sets, strict optimization settings with different XC functionals and after calculating phonons of this structure and you get imaginary frequencies. Does this mean that this structure not stable at all? If so, how they are studied experimentally at all?&lt;/p&gt;&#xA;" OwnerUserId="984" LastActivityDate="2020-08-07T14:38:04.363" Title="What does it mean if a strictly optimized experimental geometry presents imaginary frequencies?" Tags="|density-functional-theory|phonons|vibrations|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1919" PostTypeId="2" ParentId="1918" CreationDate="2020-08-05T00:26:14.833" Score="6" Body="&lt;p&gt;You mention phonons, so I assume you are doing periodic structures which I am not entirely familiar with since I study mostly single molecules. Although, when I get imaginary frequencies from optimized geometries of single molecules this typically implies that the isomer in question is not a stable minimum on the potential energy surface (PES). This does not rule out the geometry from being a stable minimum on other multiplicity PES, for example you may have certain isomers give imaginary frequencies on the singlet level but not at the triplet level.&lt;/p&gt;&#xA;&lt;p&gt;For the case of periodic structures, I can only speculate that if the geometry matches the experimental geometry perfectly then perhaps another parameter does not match the experimental sample.&lt;/p&gt;&#xA;" OwnerUserId="65" LastActivityDate="2020-08-05T00:26:14.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1920" PostTypeId="2" ParentId="1918" CreationDate="2020-08-05T06:02:09.980" Score="14" Body="&lt;p&gt;Assuming that all calculation parameters associated with the electronic structure are properly converged, then obtaining imaginary frequencies can mean one of two things.&lt;/p&gt;&#xA;&lt;h3&gt;Physical imaginary frequencies&lt;/h3&gt;&#xA;&lt;p&gt;This situation corresponds to obtaining imaginary frequencies on &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points that are included in the &lt;span class=&quot;math-container&quot;&gt;$n_1\times n_2\times n_3$&lt;/span&gt; grid that you explicitly calculate. In this case, the imaginary frequencies are physical and indicate that the structure is not dynamically stable and is not at a minimum of the potential energy landscape, but instead at a saddle point. Distorting the structure along the wave vector associated with the imaginary frequency will allow you to find a lower-energy structure (a recent &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;answer&lt;/a&gt; provides details about how to do this).&lt;/p&gt;&#xA;&lt;p&gt;So how is it possible that you have imaginary modes but the structure is observed experimentally? There could be multiple reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;It could be that the structure is at a saddle point of the potential energy surface but at a minimum of the free energy surface at some temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;. In this case, the experimental structure is possibly measured at high temperature and if temperature were lowered experimentally a structural phase transition associated with the imaginary mode would occur. From a computational point of view, you could explore the free energy surface to determine if the imaginary modes disappear at finite temperature by performing anharmonic phonon calculations. A well-known example of this phenomenon are perovskites like BaTiO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, which are cubic at high temperatures experimentally, but if you calculate the phonons you will find imaginary frequencies. This is because at low temperatures this structure transitions from cubic to tetragonal (and at even lower temperatures to other structures).&lt;/li&gt;&#xA;&lt;li&gt;The above scenario could play out even at &lt;span class=&quot;math-container&quot;&gt;$T=0$&lt;/span&gt; K. In this case, rather than anharmonic thermal fluctuations stabilizing the structure, it is quantum fluctuations that do it.&lt;/li&gt;&#xA;&lt;li&gt;You mention in your question that you have checked different XC functionals. How thorough were you at this? There are examples in which all of LDA, PBE, and other semilocal functionals give imaginary frequencies, but hybrid functionals for example don't. In this case, it would be an issue with the electronic structure method used.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h3&gt;Underconverged imaginary frequencies&lt;/h3&gt;&#xA;&lt;p&gt;This situation corresponds to obtaining imaginary frequencies on &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points that are not included in the &lt;span class=&quot;math-container&quot;&gt;$n_1\times n_2\times n_3$&lt;/span&gt; grid that you explicitly calculate. In this case, the imaginary frequencies are probably a result of underconvergence in the phonon part of the calculation and arise from Fourier interpolation performed over the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid that you explicitly calculate to construct frequencies at other &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points.&lt;/p&gt;&#xA;&lt;p&gt;So how can you address this scenario? The only option is to converge the phonon calculations by performing calculations on finer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grids (larger supercells if you are using the finite displacement method).&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-08-07T14:38:04.363" LastActivityDate="2020-08-07T14:38:04.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1921" PostTypeId="1" CreationDate="2020-08-05T06:12:52.273" Score="24" ViewCount="487" Body="&#xA;&lt;p&gt;It would be appreciated if you could explain one of the tools below (or another tool not listed), in the format used here (for example):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4501/5&quot;&gt;What software will allow me to combine two images?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1222/5&quot;&gt;What software is available to do molecular dynamics on Windows?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/414/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;One software description per answer please.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PyCDT&lt;/li&gt;&#xA;&lt;li&gt;PyDEF&lt;/li&gt;&#xA;&lt;li&gt;pylada&lt;/li&gt;&#xA;&lt;li&gt;pymatgen (the parts for point defect calculations)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;" OwnerUserId="1031" LastEditorUserId="5" LastEditDate="2021-11-30T20:29:33.753" LastActivityDate="2021-11-30T20:29:33.753" Title="What are the tools available for point defects calculations?" Tags="|one-topic-per-answer|software-recommendations|python|defects|pymatgen|" AnswerCount="0" CommentCount="7" ClosedDate="2021-12-26T00:06:09.610" ContentLicense="CC BY-SA 4.0" />
  <row Id="1922" PostTypeId="1" CreationDate="2020-08-05T07:09:05.053" Score="9" ViewCount="584" Body="&lt;p&gt;I am doing a phonon calculation for a phase using a 2x2x1 supercell (after geometry optimization of the structure). I am getting an error when computing the DOS and band structure after computing the force sets. The crystal structure of the initial and the final structures are the same.&#xA;Here is the error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;*phonopy -p -s band.conf&#xA;        _&#xA;  _ __ | |__   ___  _ __   ___   _ __  _   _&#xA; | '_ \| '_ \ / _ \| '_ \ / _ \ | '_ \| | | |&#xA; | |_) | | | | (_) | | | | (_) || |_) | |_| |&#xA; | .__/|_| |_|\___/|_| |_|\___(_) .__/ \__, |&#xA; |_|                            |_|    |___/&#xA;                                  1.12.6-r32&#xA;Python version 2.7.12&#xA;Spglib version 1.10.3&#xA;Band structure mode&#xA;Settings:&#xA;  Supercell: [2 2 1]&#xA;Spacegroup: P6_3/mcm (193)&#xA;Computing force constants...&#xA;Encounter some problem in compute_permutation.&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/usr/local/bin/phonopy&amp;quot;, line 659, in &amp;lt;module&amp;gt;&#xA;    computation_algorithm=settings.get_fc_computation_algorithm())&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/api_phonopy.py&amp;quot;, line 372, in produce_force_constants&#xA;    computation_algorithm=computation_algorithm)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/api_phonopy.py&amp;quot;, line 1299, in _run_force_constants_from_forces&#xA;    computation_algorithm=computation_algorithm)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 87, in get_fc2&#xA;    computation_algorithm=computation_algorithm)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 704, in _get_force_constants_disps&#xA;    computation_algorithm=computation_algorithm)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 261, in solve_force_constants&#xA;    symprec)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 579, in _solve_force_constants_svd&#xA;    symprec)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 275, in get_positions_sent_by_rot_inv&#xA;    symprec)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 853, in _compute_permutation_for_rotation&#xA;    symprec)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 889, in _compute_permutation_c&#xA;    permutation_error()&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/phonopy/harmonic/force_constants.py&amp;quot;, line 877, in permutation_error&#xA;    raise ValueError(&amp;quot;Input forces are not enough to calculate force constants, &amp;quot;&#xA;ValueError: Input forces are not enough to calculate force constants, or something wrong (e.g. crystal structure does not match).*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What should I do?&lt;/p&gt;&#xA;" OwnerUserId="1178" LastEditorUserId="792" LastEditDate="2020-08-05T11:43:31.267" LastActivityDate="2020-12-01T17:42:28.270" Title="&quot;Input forces are not enough to calculate force constants&quot; Phonopy error?" Tags="|density-functional-theory|phonons|phonopy|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="1923" PostTypeId="1" CreationDate="2020-08-05T13:29:42.217" Score="4" ViewCount="107" Body="&lt;p&gt;Is there a threshold? Could I say that my final geometries are the same with 'energy difference = 0.05 meV/atom' ?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-08-30T21:57:39.993" LastActivityDate="2020-08-31T06:38:20.720" Title="How much energy difference could be used to distinguish optimized results from different initial geometries for the same structure?" Tags="|density-functional-theory|optimization|structure|geometry|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1924" PostTypeId="1" CreationDate="2020-08-05T15:35:59.580" Score="13" ViewCount="1997" Body="&lt;p&gt;I am writing a simple Lennard-Jones fluid simulation in LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;So far, I have outputted the temperature, volume, density, total energy, enthalpy, pressure, and all of it seems to be believable every 500 steps. This leads me to believe that my simulation is doing the right physics.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;thermo_style    custom step temp vol density etotal pe ke enthalpy press&#xA;thermo_modify   format float %14.6f #format in log file&#xA;thermo 500 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I wanted to evaluate the autocorrelation function for my simulation. Looking up the LAMMPS documentation I see the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;compute velacf all vacf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From my understanding, the deal with a vacf is that I need the entire simulation to be complete before I start computing it, since&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi(t_d) = \frac{1}{N_{part}}\sum_{i=1}^{N_{part}} \sum_{j=0}^{f-d} \mathbf{v}_i(t_j)\cdot\mathbf{v}_i(t_j+t_d)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$N_{part}$&lt;/span&gt; is the number of particles, and &lt;span class=&quot;math-container&quot;&gt;$t_f$&lt;/span&gt; is the final time, and &lt;span class=&quot;math-container&quot;&gt;$t_i+t_j = t_{i+j}$&lt;/span&gt; (equal time steps taken throughout simulation).&lt;/p&gt;&#xA;&lt;p&gt;How do I make LAMMPS get me an output of VACF at each time, so I can use it for analysis and visualization?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-05-27T20:14:23.763" Title="Using the VACF command in LAMMPS to get the velocity autocorrelation function" Tags="|molecular-dynamics|lammps|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1925" PostTypeId="2" ParentId="1924" CreationDate="2020-08-05T16:07:58.037" Score="8" Body="&lt;p&gt;You don't need to wait for the completed simulation to evaluate VACF. VACF is usually calculated by subdividing the entire trajectory into &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; fragments, where &lt;span class=&quot;math-container&quot;&gt;$N=T/\tau$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the total(current) length of the simulation and &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the autocorrelation length which depends on the molecular features of the system under study. You can also choose an appropriate &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; by comparing the convergence of the VACF via changing &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The simplified relation is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\text{VACF}=\frac{1}{N}\cdot\frac{\tau}{T}\sum_{i=1}^{N_{atom}}\sum_{n=1}^{T/\tau}\sum_{t=0}^{t=\tau}\langle \textbf{v}(t_0)\cdot \textbf{v}(t_0+t)\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the autocorrelation length and &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; denotes the total length of the trajectory.&lt;/p&gt;&#xA;&lt;p&gt;That being said, there are a few utilities you can use to extract VACF for your simulation. &lt;a href=&quot;https://docs.mdanalysis.org/2.0.0-dev0/index.html&quot; rel=&quot;noreferrer&quot;&gt;MDAnaylsis&lt;/a&gt; is a swiss-army knife for molecular dynamics and can be easily used for extracting and analysing many features for MD, including VACF.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2020-08-05T16:07:58.037" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1926" PostTypeId="1" CreationDate="2020-08-05T19:52:22.650" Score="10" ViewCount="2121" Body="&lt;pre&gt;&lt;code&gt;suppl = Chem.SDMolSupplier('1.sdf')&#xA;for mol in suppl:&#xA;  if mol is None: continue&#xA;  # print(mol.GetNumAtoms())&#xA;&#xA;fps = [Chem.RDKFingerprint(x) for x in supply]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am facing many errors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ERROR: Problems encountered parsing Mol data, M  END missing around line 16739&#xA;...&#xA;ERROR: Explicit valence for atom # 0 O, 3, is greater than permitted&#xA;...&#xA;ERROR: Could not sanitize molecule ending on line 78558&#xA;...&#xA;ERROR: Post-condition Violation&#xA;RDKit ERROR: Element 'Alkyl' not found&#xA;RDKit ERROR: Violation occurred on line 91 in file /home/conda/feedstock_root/build_artifacts/rdkit_1593788763912/work/Code/GraphMol/PeriodicTable.h&#xA;RDKit ERROR: Failed Expression: anum &amp;gt; -1&#xA;&#xA;...&#xA;WARNING: not removing hydrogen atom without neighbors&#xA;&#xA;&#xA;RDKit WARNING: atom 0 has specified valence (4) smaller than the drawn valence 6.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I correct these?&lt;/p&gt;&#xA;" OwnerUserId="397" LastEditorUserId="5" LastEditDate="2020-08-07T18:09:56.873" LastActivityDate="2020-08-07T18:09:56.873" Title="RDkit: While converting a *.sdf file to fingerprint, I'm facing several errors" Tags="|python|chemoinformatics|rdkit|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1927" PostTypeId="1" CreationDate="2020-08-05T20:07:26.360" Score="8" ViewCount="262" Body="&lt;p&gt;They look like the same thing, but their definitions are confusing. Additionally, while it's possible to use 'tolerance'&amp;lt; 0.05 in AIMS easily, in ASE, some structures never optimize if you choose fmax &amp;lt; 0.05. If they are the same thing, one should use the same value for both codes for comparison of the results, right?&lt;/p&gt;&#xA;&lt;p&gt;I put their explanations from their documentations. These definitions confuse me. In one it says per atom, and in other one, it says all individual atoms&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;relax_geometry (control.in)&#xA;Usage: &lt;strong&gt;relax_geometry type tolerance&lt;/strong&gt; Purpose: Specifies if a structure optimization (geometry relaxation) is requested, and which. type specifies the type of requested structure optimization. Default: none. tolerance: Specifies the maximum residual force component per atom (in eV/Å) below which the geometry relaxation is considered converged.&lt;/em&gt; - &lt;strong&gt;FHI-aims Manual&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The convergence criterion is that the force on all individual atoms should be less than fmax:&lt;/em&gt; - &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/optimize.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-09-26T20:27:02.013" LastActivityDate="2020-09-26T20:27:02.013" Title="ASE's fmax and FHI-AIMS's relax_geometry bfgs &quot;tolerance&quot;. Are they same?" Tags="|density-functional-theory|geometry-optimization|numerical-convergence|atomic-simulation-environment|fhi-aims|" AnswerCount="0" CommentCount="9" ClosedDate="2020-12-31T16:51:46.130" ContentLicense="CC BY-SA 4.0" />
  <row Id="1928" PostTypeId="2" ParentId="467" CreationDate="2020-08-05T21:59:52.030" Score="16" Body="&lt;h2&gt;MERCURY&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/mercury/&quot; rel=&quot;noreferrer&quot;&gt;Mercury&lt;/a&gt; is a specialized software to treat/manipulate crystal structures. It is part of the &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/csd/&quot; rel=&quot;noreferrer&quot;&gt;Cambridge Structural Database (CSD)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From Mercury's site, it allows you to:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Generate packing diagrams, define and visualize Miller planes, and take slices through a crystal in any direction.&lt;/li&gt;&#xA;&lt;li&gt;Build and explore networks of intermolecular contacts to gain an understanding of the strengths and weaknesses of structures and identify the key interactions that drive crystal packing.&lt;/li&gt;&#xA;&lt;li&gt;Display space-group symmetry elements&lt;/li&gt;&#xA;&lt;li&gt;Calculate and display voids (free space in crystal structures) based either on contact surface or solvent accessible surface&lt;/li&gt;&#xA;&lt;li&gt;Perform molecule-based gas phase calculations via an interface to MOPAC&lt;/li&gt;&#xA;&lt;li&gt;Calculate intermolecular potentials and display e.g. the strongest user-defined interactions in the crystal structure&lt;/li&gt;&#xA;&lt;li&gt;View Bravais, Friedel, Donnay and Harker (BFDH) theoretical crystal morphologies.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The free version can be downloaded in this &lt;a href=&quot;https://www.ccdc.cam.ac.uk/support-and-resources/Downloads/&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt; (available for Windows, Linux and Mac) and the instructions to activate it are &lt;a href=&quot;https://www.ccdc.cam.ac.uk/support-and-resources/support/case/?caseid=e007c31c-6bd5-ea11-9687-005056957156&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Two examples of images produced with it (from it's site):&lt;/p&gt;&#xA;&lt;p&gt;Fig. 1. Refcode &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/search?pid=csd:ASETEZ&quot; rel=&quot;noreferrer&quot;&gt;ASETEZ&lt;/a&gt; - Iron-molybdenum inorganic ring (shown with orange and blue polyhedra, respectively)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://web.archive.org/web/20201101032959/https://www.ccdc.cam.ac.uk/solutions/csd-system/components/mercury/ASETEZ_large.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://web.archive.org/web/20201101032959/https://www.ccdc.cam.ac.uk/solutions/csd-system/components/mercury/ASETEZ_large.png&quot; height=&quot;300&quot;&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fig. 1. Refcode &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/search?pid=csd:CUIMDZ01&quot; rel=&quot;noreferrer&quot;&gt;CUIMDZ01&lt;/a&gt;, a polymorph of a copper imidazolate framework (often called a 'ZIF' that shows the copper polyhedra and channel structure of the void space&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JBro4.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JBro4.jpg&quot; height=&quot;300&quot;&gt;&lt;/a&gt;&lt;br /&gt;&#xA;&lt;sub&gt;(source: &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-system/components/mercury/CUIMDZ01.png&quot; rel=&quot;noreferrer&quot;&gt;cam.ac.uk&lt;/a&gt;)&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="118" LastEditDate="2020-12-26T06:47:05.033" LastActivityDate="2020-12-26T06:47:05.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1929" PostTypeId="1" CreationDate="2020-08-06T00:32:16.743" Score="9" ViewCount="611" Body="&lt;p&gt;I generated an FCIDUMP file, which is copied below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;FCI NORB=2, NELEC=2,MS2=0,UHF=.FALSE.,ORBSYM=1,5,ISYM=1, &amp;amp;END&#xA;&#xA; 6.74493103326006093745E-01 1 1 1 1&#xA; 6.63472044860555665302E-01 1 1 2 2    &#xA; 6.63472044860555665302E-01 2 2 1 1    &#xA; 6.97397949820408036281E-01 2 2 2 2    &#xA; 1.81287535812332034624E-01 2 1 2 1    &#xA;-1.25247730398215462166E+00 1 1 0 0&#xA;-4.75934461144127241017E-01 2 2 0 0&#xA; 7.43077168397780152276E-01 0 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not really sure what the indices mean. In particular, I would like to link it to the following definition of the one and two electron integrals (see attached pictures for their definitions and results which are taken from &lt;a href=&quot;https://arxiv.org/abs/1001.3855&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). It is not obvious to me how to match the indices. The result I am trying to obtain is in the second attached figure. I was able to guess most of results, except the ones with value 0.663472.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cTNk4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cTNk4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have checked following references:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/0010465589900337&quot; rel=&quot;nofollow noreferrer&quot;&gt;This one&lt;/a&gt;, which is not really helpful yet.&lt;/li&gt;&#xA;&lt;li&gt;I also found &lt;a href=&quot;https://theochem.github.io/horton/2.0.2/user_hamiltonian_io.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt; describing the FCIDUMP file explicitly, it is close to the integrals I want, but not quite exactly.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Any help is really appreciated. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1183" LastEditorUserId="5" LastEditDate="2020-08-17T18:25:19.983" LastActivityDate="2020-08-17T18:25:19.983" Title="What do the indices mean in an FCIDUMP file?" Tags="|integrals|psi4|fcidump|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1930" PostTypeId="2" ParentId="1926" CreationDate="2020-08-06T02:25:20.680" Score="10" Body="&lt;p&gt;Without seeing the SDF itself it's hard to be specific, but here's what the error messages are telling you, in general:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the first one normally indicates a badly formed record in the SDF. If you look at around that line in the file you will, hopefully, see a misformed record.&lt;/li&gt;&#xA;&lt;li&gt;The next one, &amp;quot;Explicit valence&amp;quot; indicates that the molecule has an atom (in this case an &amp;quot;O&amp;quot;) that has the equivalent of three bonds to it. That's not chemically reasonable, so the software complains&lt;/li&gt;&#xA;&lt;li&gt;The error about &amp;quot;Alkyl&amp;quot; is self explanatory: there's a molecule in the SDF which has an atom with symbol &amp;quot;Alkyl&amp;quot;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The rest are warnings.&lt;/p&gt;&#xA;&lt;p&gt;An aside: the best way to get RDKit help is by subscribing to the rdkit-discuss mailing list and posting there. I can't monitor every possible stackexchange and this is a forum which is difficult for occasional users.&lt;/p&gt;&#xA;" OwnerUserId="1184" LastActivityDate="2020-08-06T02:25:20.680" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1931" PostTypeId="2" ParentId="1929" CreationDate="2020-08-06T03:17:34.847" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I was able to guess most of results, except the ones with value&#xA;0.663472.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am able to confirm that your integrals are correct even for the 0.663472 case, because by calculating them myself in MOLPRO (a completely different program from what you used), I get the same indices of 2 2 1 1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;FCI NORB=  2,NELEC=  2,MS2= 0, ORBSYM=1,5,ISYM=0,&#xA;  0.6744931033260081E+00   1   1   1   1  &#xA;  0.6634720448605567E+00   2   2   1   1   &amp;lt;---------------&#xA;  0.6973979494693358E+00   2   2   2   2  &#xA;  0.1812875358123322E+00   2   1   2   1  &#xA; -0.1252477303982147E+01   1   1   0   0  &#xA; -0.4759344611440753E+00   2   2   0   0  &#xA;  0.7137758743754461E+00   0   0   0   0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hence the reason why the indices are different in the paper you're looking at, would be due to symmetry considerations.&lt;/p&gt;&#xA;&lt;p&gt;Now that I've confirmed that your indices are indeed correct, I would like you to work out how the known symmetry relations for integrals lead from our indices to those shown in the paper (if I do that part for you, then it would be like solving a &amp;quot;homework question&amp;quot;). The most important way I could help you was to give you the confidence that your indices are indeed correct.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-06T03:24:36.510" LastActivityDate="2020-08-06T03:24:36.510" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="1932" PostTypeId="2" ParentId="1922" CreationDate="2020-08-06T09:51:54.443" Score="7" Body="&lt;p&gt;I have never used Phonopy, so we will have to wait for an actual user for a full answer.&lt;/p&gt;&#xA;&lt;p&gt;However, I can make some general statements about phonon calculations that could plausibly explain your error. The starting point of any phonon calculation is the construction of the matrix of force constants:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{\alpha i;\alpha'i'}(\mathbf{R}_p,\mathbf{R}_{p'})=\frac{\partial^2E}{\partial u_{p\alpha i}\partial u_{p'\alpha'i'}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the potential energy surface, &lt;span class=&quot;math-container&quot;&gt;$u_{p\alpha i}$&lt;/span&gt; is the displacement of an atom in a cell located at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt; in the supercell, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is the atom of the basis you are moving, and &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is the Cartesian direction in which you are moving the atom. Essentially, the matrix of force constants captures the lowest-order non-zero non-constant term in the Taylor expansion of the energy of the atoms about their equilibrium position, so it allows you to study their harmonic vibrations.&lt;/p&gt;&#xA;&lt;p&gt;For a supercell containing &lt;span class=&quot;math-container&quot;&gt;$N_{p}$&lt;/span&gt; primitive cells (in your case &lt;span class=&quot;math-container&quot;&gt;$N_p=2\times2\times1=4$&lt;/span&gt;) and a system with &lt;span class=&quot;math-container&quot;&gt;$N_{\mathrm{at}}$&lt;/span&gt; atoms per primitive cell, there are at total of &lt;span class=&quot;math-container&quot;&gt;$3N_{p}N_{\mathrm{at}}-3$&lt;/span&gt; degrees of freedom, where the &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt; comes from the &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt; possible Cartesian directions, and the &lt;span class=&quot;math-container&quot;&gt;$-3$&lt;/span&gt; comes from the trivial translational modes.&lt;/p&gt;&#xA;&lt;p&gt;The discussion above suggests that you would naively need a total of &lt;span class=&quot;math-container&quot;&gt;$3N_{p}N_{\mathrm{at}}-3$&lt;/span&gt; calculations to determine all force constants. In reality, you can use symmetry to reduce the number of force constants you need to calculate explicitly. Most phonon codes do this, and my guess would be that Phonopy should also do this. Most probably, Phonopy suggests that you calculate a subset of the force constants based on symmetry, and then uses these as input to build the full matrix of force constants. The error that there are not enough force constants suggests that the symmetry finder failed, so it requested fewer force constants than it needed in reality.&lt;/p&gt;&#xA;&lt;p&gt;As I said, this is not a direct answer because I have never used Phonopy. But while we are waiting for a direct answer, my suggestion would be to check whether symmetry is treated correctly in your calculation.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-06T09:51:54.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1933" PostTypeId="1" AcceptedAnswerId="2382" CreationDate="2020-08-06T10:15:40.207" Score="8" ViewCount="156" Body="&lt;p&gt;Gaussian-n theory has been used for a long time to assess the accuracy of density functionals, and for some reason still appears to be used in the literature even though much more accurate alternatives like the Weizmann ab initio datasets, e.g. &lt;a href=&quot;https://doi.org/10.1016/j.cplett.2011.05.007&quot; rel=&quot;noreferrer&quot;&gt;W4-11&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1002/jcc.24854&quot; rel=&quot;noreferrer&quot;&gt;W4-17&lt;/a&gt;, are available.&lt;/p&gt;&#xA;&lt;p&gt;The Gaussian-n test sets include at least&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;G2-1 test set &lt;a href=&quot;https://doi.org/10.1063/1.460205&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 94, 7221 (1991)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;G2 neutral test set a.k.a. G2/97, adding more molecules (G2-2 test set) to the G2-1 test set &lt;a href=&quot;https://doi.org/10.1063/1.473182&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 106, 1063 (1997)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;G3/99 test set &lt;a href=&quot;https://doi.org/10.1063/1.481336&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 112, 7374 (2000)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;G3/05 test set &lt;a href=&quot;https://doi.org/10.1063/1.2039080&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 123, 124107 (2005)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;but none of these works contains the actual molecular geometries or the inputs that are available as supplementary information in the Weizmann sets.&lt;/p&gt;&#xA;&lt;p&gt;I have found geometries for G2/97 in &lt;a href=&quot;https://doi.org/10.1063/1.4704796&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 136, 164102 (2012)&lt;/a&gt; that suggests new, more accurate reference energies for the database; but the geometries are in a PDF file which will be painstaking to parse, and the other databases are still missing.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know where to find the databases in machine readable format? If I missed some Gn test sets, please let me know as well.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-28T10:55:21.753" Title="Gaussian-n test sets in machine readable format?" Tags="|reference-request|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1934" PostTypeId="1" AcceptedAnswerId="2125" CreationDate="2020-08-06T18:16:45.813" Score="9" ViewCount="136" Body="&lt;p&gt;I have seen an article&lt;sup&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp501289s&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;&lt;/sup&gt; that describes a HF approach to working with exotic muonic atoms.  I am curious about how far DFT has been extended for modeling muonic chemistry.  Are there psuedopotentials avilable in any code for muonic substitutions into an element for example or is this something DFT fails to capture correctly?&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-29T06:58:49.920" Title="Muonic Modeling" Tags="|density-functional-theory|hartree-fock|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1935" PostTypeId="2" ParentId="1601" CreationDate="2020-08-06T18:28:47.710" Score="9" Body="&lt;p&gt;Better late than never for a partial answer.&lt;/p&gt;&#xA;&lt;p&gt;I have worked with modeling the disorder of coverage on surfaces of materials.  Recently we published a &lt;a href=&quot;https://www.nature.com/articles/s41524-020-0345-2&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; where we give a very general approach to modeling adsorbate-adsorbate interactions which we have seen is a problem in current literature.  By using non-ideal buildups of coverage (where each adsorbate is not equally spaced), we have been able to identify better models of NO coverage on Pt&lt;sub&gt;3&lt;/sub&gt;Sn.  You can see below that at accessible high coverages, the structure is heavily disordered and would be incredibly difficult to find.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/k9Cup.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k9Cup.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A large problem with modeling disorder is getting any useful information out of it.  This problem needs to be solved before very disordered models will give better results than ideal models.  In contrast to the comment by Camps, I don't feel making a good disordered model is difficult, the hard part is understanding what part of the disorder is actually relevant to the result.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-08-07T09:43:14.213" LastActivityDate="2020-08-07T09:43:14.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1936" PostTypeId="2" ParentId="1926" CreationDate="2020-08-06T19:08:22.450" Score="7" Body="&lt;p&gt;As noted by Dr. Landrum, the errors that you are seeing are due to problems in the generation of the original SDF (i.e., improper molecule ending, the atom connectivity, and the use of &amp;quot;Alkyl&amp;quot; as an atom). Generally, RDKit just lets you know that it cannot generate the molecule because of an error in the SDF, and then, instead of producing an RDKit mol object, it produces an instance of &lt;code&gt;None&lt;/code&gt;, which is why the example code in the RDKit docs have the &lt;code&gt;if mol is None: continue&lt;/code&gt; line of code that you included in your example. If you are happy to skip these molecules when you are generating the RDKit fingerprints, you may do so by first removing any molecules that could not be generated and then calculating the fingerprints, as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# import relevant rdkit objects&#xA;from rdkit.Chem import RDKFingerprint, SDMolSupplier&#xA;&#xA;# create instance of sdf reader&#xA;suppl = SDMolSupplier('1.sdf')&#xA;&#xA;# read all molecules besides ones with errors into a list&#xA;mols = [mol for mol in suppl if mol is not None]&#xA;&#xA;# calculate fingerprints&#xA;fps = [RDKFingerprint(mol) for mol in mols]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that to actually remove the molecules that are throwing errors, you should not read them directly from &lt;code&gt;SDMolSupplier&lt;/code&gt;. As the code is written in your example, it simply will cycle through all of the molecules, see if they are &lt;code&gt;None&lt;/code&gt; (i.e., threw an error while being generated), and then move on - it doesn't actually &lt;i&gt;remove&lt;/i&gt; the molecules that are &lt;code&gt;None&lt;/code&gt;, as the sample code I suggested does. Otherwise, you will run into issues when generating the fingerprints, since &lt;code&gt;RDKFingerprint&lt;/code&gt; needs an RDKit mol object to calculate from and will, therefore, throw an error if you try &lt;code&gt;RDKFingerprint(None)&lt;/code&gt; (which is what will happen if you forget to remove the &lt;code&gt;None&lt;/code&gt; objects between reading the SDF and calculating the fingerprints.&lt;/p&gt;&#xA;&lt;p&gt;If you cannot skip the problematic molecules in the SDF, you should return to the original file and try to repair the errors inside before calculating fingerprints using RDKit. Here is a useful resource that really breaks down what each mol in an SDF contains: &lt;a href=&quot;https://chem.libretexts.org/Courses/University_of_Arkansas_Little_Rock/ChemInformatics_(2017)%3A_Chem_4399%2F%2F5399/2.2%3A_Chemical_Representations_on_Computer%3A_Part_II/2.2.2%3A_Anatomy_of_a_MOL_file&quot; rel=&quot;noreferrer&quot;&gt;https://chem.libretexts.org/Courses/University_of_Arkansas_Little_Rock/ChemInformatics_(2017)%3A_Chem_4399%2F%2F5399/2.2%3A_Chemical_Representations_on_Computer%3A_Part_II/2.2.2%3A_Anatomy_of_a_MOL_file&lt;/a&gt;. It has been helpful to me in combing through to correct similar errors.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1187" LastActivityDate="2020-08-06T19:08:22.450" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1937" PostTypeId="5" CreationDate="2020-08-06T19:43:53.120" Score="0" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;The Atomic Simulation Environment (ASE) is a set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations. The code is freely available under the GNU LGPL license.&lt;/p&gt;&#xA;&lt;p&gt;ASE provides interfaces to different codes through Calculators which are used together with the central Atoms object and the many available algorithms in ASE.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Description from: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-08-06T19:43:53.120" LastActivityDate="2020-08-06T19:43:53.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1938" PostTypeId="4" CreationDate="2020-08-06T19:43:53.120" Score="0" Body="For questions about the Atomic Simulation Environment (ASE) tools and Python modules" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-08-06T19:43:53.120" LastActivityDate="2020-08-06T19:43:53.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1939" PostTypeId="5" CreationDate="2020-08-06T19:47:33.760" Score="0" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;CASTEP is a full-featured materials modelling code based on a first-principles quantum mechanical description of electrons and nuclei. It uses the robust methods of a plane-wave basis set and pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;The current version of CASTEP is version 18.1 - see Getting CASTEP for information on how to obtain this version.&lt;/p&gt;&#xA;&lt;p&gt;The code is developed by the Castep Developers Group (CDG) who are all UK based academics.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Description from: &lt;a href=&quot;http://www.castep.org/CASTEP/CASTEP&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.castep.org/CASTEP/CASTEP&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-08-06T19:47:33.760" LastActivityDate="2020-08-06T19:47:33.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1940" PostTypeId="4" CreationDate="2020-08-06T19:47:33.760" Score="0" Body="For questions about the electronic structure/molecular dynamics program CASTEP" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-08-06T19:47:33.760" LastActivityDate="2020-08-06T19:47:33.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1941" PostTypeId="2" ParentId="1929" CreationDate="2020-08-06T20:53:06.313" Score="4" Body="&lt;p&gt;I would like to post a partial answer that I have for now.&lt;/p&gt;&#xA;&lt;p&gt;For the indices ijkl in the FCIDUMP file, it corresponds to the integral (see &lt;a href=&quot;https://theochem.github.io/horton/2.0.2/user_hamiltonian_io.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://theochem.github.io/horton/2.0.2/user_hamiltonian_io.html&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\int dx_1dx_2\chi_i^*(x_1)\chi_k^*(x_2)\chi_j(x_1)\chi_l(x_2)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;while the indices in the paper, it is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;\int dx_1dx_2\chi_i^*(x_1)\chi_j^*(x_2)\chi_k(x_2)\chi_l(x_1)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have ignored some other factors which are not relevant here.&#xA;We see that there are two differences, one is the order of the indices, and the other is the &lt;span class=&quot;math-container&quot;&gt;$x_{1,2}$&lt;/span&gt; arguments. Thus we have the following mapping&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ijkl in FCIDUMP file = iklj in the paper, for the spatial orb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Further, with the second equation above, we have the following symmetry property&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{3}&#xA;ijkl = jilk = lkji&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the second equality is due to reality requirement of the integral. With these, we are ready to understand the integrals in FCIDUMP file one by one. First, we need to subtract all the indices by 1, so that it matches with those in the paper. So we have&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 6.74493103326006093745E-01 0 0 0 0 &#xA; 6.63472044860555665302E-01 0 0 1 1     &#xA; 6.63472044860555665302E-01 1 1 0 0  &#xA; 6.97397949820408036281E-01 1 1 1 1     &#xA; 1.81287535812332034624E-01 1 0 1 0     &#xA;-1.25247730398215462166E+00 0 0 -1 -1&#xA;-4.75934461144127241017E-01 1 1 -1 -1&#xA; 7.43077168397780152276E-01 -1 -1 -1 -1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Next, the very last row is the nuclear repulsion energy, which is not of our interest here. The 2nd and 3rd to last rows are the 1-body integral, which are pretty easy to understand. So let's focus on the 2-body integral.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$0000$&lt;/span&gt;. After using the mapping in the 3rd Equation, it is the same for the labeling of the spatial orb in the paper. The first two (from the right) means 2 0-th spatial orbs are occupied, and this can only be the case if both spin-up and down are occupied. Using the labeling of the spin-orbital, it would be 10 (or 01). Similarly for the next two indices. Thus we have 0110 in the spin-orbital basis (why it is not 1010, I am not sure, and maybe this is due to convention). By the symmetry in Eq. 4, we have also 1001.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$1111$&lt;/span&gt;. The argument is essentially the same as above, except that now we are dealing with 1st spatial orb, with the spin-up and down labeled as 23. Thus we have 3223 and 2332 for the spin-orb in the paper.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$0011$&lt;/span&gt;. Now with the mapping in Eq. 3, it is in fact 0110 for the spatial orb in the paper. The first two indices 10 means the 0th and 1st spatial orbs are occupied, and they could be either spin up and down. Thus we have &lt;span class=&quot;math-container&quot;&gt;$2\times2=4$&lt;/span&gt; options: 20, 30, 21, 31 for the first two indices of the spin-orbs. Thus put it together, we have 0220, 0330, 1221, 1331 for the spin orbs. Again, I am not sure why we don't have 2020, maybe due to convention.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$1100$&lt;/span&gt;. This is essentially the same as above, where we realize that it is 1001 for the spatial orb in the paper. With the same logic, we have 2002, 3003, 2112, and 3113. These can essentially be obtained with the symmetry property in Eq. 4.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$1010$&lt;/span&gt;. Ok, I am stuck here for now... Will update this after I figure it out.&lt;/p&gt;&#xA;" OwnerUserId="1183" LastEditorUserId="1183" LastEditDate="2020-08-07T01:46:39.070" LastActivityDate="2020-08-07T01:46:39.070" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="1942" PostTypeId="1" CreationDate="2020-08-07T03:49:45.870" Score="9" ViewCount="105" Body="&lt;p&gt;I'm looking for a way to run the Weighted Histogram Analsys Method, but I don't have a time series to feed to the code as one would usually do, but rather I have histograms coming from the de-biasing of a metadynamics simulation. Does anyone know of any code that can do that?&lt;/p&gt;&#xA;" OwnerUserId="677" LastEditorUserId="5" LastEditDate="2021-10-30T20:04:30.270" LastActivityDate="2021-10-30T20:04:30.270" Title="Is there any code that runs WHAM starting from histograms rather than time series?" Tags="|software|molecular-dynamics|software-recommendations|metadynamics|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-30T23:45:00.337" ContentLicense="CC BY-SA 4.0" />
  <row Id="1943" PostTypeId="2" ParentId="1515" CreationDate="2020-08-07T12:09:35.163" Score="11" Body="&lt;h1&gt;India : National Supercomputing Mission&lt;/h1&gt;&#xA;&lt;h3&gt;Supercomputing and the C-DAC Missions:&lt;/h3&gt;&#xA;&lt;p&gt;Supercomputing in India started in the 1980's. After difficulties in obtaining supercomputers from abroad for weather forecasting and academic work (due to the potential for dual-use), it was decided to build ingenious supercomputing facilities.&lt;/p&gt;&#xA;&lt;p&gt;Supercomputers were made by &lt;a href=&quot;https://www.cdac.in/index.aspx?id=about&quot; rel=&quot;noreferrer&quot;&gt;C-DAC&lt;/a&gt; (Center for Development of Advanced Computing, est. 1987) Pune, in several 'Missions', leading to the production of the PARAM (PARAllel Machine, also 'supreme' in &lt;em&gt;Sanskrit&lt;/em&gt;) series.&lt;/p&gt;&#xA;&lt;p&gt;Examples include PARAM 8000 (1990- several models including exports to Germany UK and Russia), PARAM-9000 (1994), PARAM Padma (2002), PARAM ISHAN (2016, IIT Guwahati campus) and PARAM Brahma (2020, IISER Pune campus). These supercomputers are interfaced with via the PARAMNet. (&lt;a href=&quot;https://en.wikipedia.org/wiki/Indian_Institutes_of_Technology&quot; rel=&quot;noreferrer&quot;&gt;IIT's&lt;/a&gt; (Indian Institute of Technology) and &lt;a href=&quot;https://en.wikipedia.org/wiki/Indian_Institutes_of_Science_Education_and_Research&quot; rel=&quot;noreferrer&quot;&gt;IISER's&lt;/a&gt; (Indian Institute of Scientific Education and Research) are families of premier Indian research and technical institutes).&lt;/p&gt;&#xA;&lt;h3&gt;12th plan:&lt;/h3&gt;&#xA;&lt;p&gt;There also exists a project under the 12th five-year plan handled by the Indian Institute of Science (IISc) Banglore.&lt;/p&gt;&#xA;&lt;h3&gt;National Supercomputing Mission (NSM):&lt;/h3&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://nsmindia.in/about&quot; rel=&quot;noreferrer&quot;&gt;National Supercomputing Mission&lt;/a&gt; jointly implemented by Department of Science and Technology (DST) Ministry of Electronics and Information Technology (MeitY), IISc and C-DAC is creating 70 supercomputers in various academic and research institutes linked by a high-speed network.&lt;/p&gt;&#xA;&lt;p&gt;3 supercomputers were built during 2015-19 and 17 are being built in 2020.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h1&gt;List of supercomputing facilities:&lt;/h1&gt;&#xA;&lt;p&gt;As per C-DAC's &lt;a href=&quot;https://www.cdac.in/index.aspx?id=hpc_nsf_national_supercomputing_facilities&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;C-DAC has commissioned and operates three national supercomputing facilities for HPC users community.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;These are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;National PARAM Supercomputing Facility at C-DAC, Pune (runs Param Yuva II)&lt;/li&gt;&#xA;&lt;li&gt;C-DAC's Terascale Supercomputing Facility at C-DAC, Bengaluru&lt;/li&gt;&#xA;&lt;li&gt;Bioinformatics Resources and Applications Facility (BRAF) at C-DAC, Pune&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;C-DAC also provides high-performance computing facilities in the form of &lt;a href=&quot;https://www.cdac.in/index.aspx?id=hpc_ss_param_shavak&quot; rel=&quot;noreferrer&quot;&gt;PARAM SHAVAK&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Other than the facilities directly hosted by C-DAC, most premier academic institutions have supercomputing facilities. Examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Param Brahma (IISER Pune, since late-2019/ early 2020)&lt;/li&gt;&#xA;&lt;li&gt;Param Shivay (IIT BHU, since 2019)&lt;/li&gt;&#xA;&lt;li&gt;Param Ishan (IIT Guwahati, since 2016)&lt;/li&gt;&#xA;&lt;li&gt;HPC (IIT Delhi)&lt;/li&gt;&#xA;&lt;li&gt;HP Apollo 6000 (IIT Delhi)&lt;/li&gt;&#xA;&lt;li&gt;Virgo (IIT Madras)&lt;/li&gt;&#xA;&lt;li&gt;SahasraT (IISc Banglore)&lt;/li&gt;&#xA;&lt;li&gt;Colour Boson (Tata Institute of Fundamental Research)&lt;/li&gt;&#xA;&lt;li&gt;PARAM Kanchenjunga (NIT Sikkim, since 2016)&lt;/li&gt;&#xA;&lt;li&gt;Pratyush (Indian Institute of Tropical Meteorology, this may not be generally available  for materials work, but it is India's most powerful supercomputer ranking #67 in the TOP-500 list for 2020)&lt;/li&gt;&#xA;&lt;li&gt;Aaditya (Indian Institute of Tropical Meteorology)&lt;/li&gt;&#xA;&lt;li&gt;Mihir (National Centre for Medium Range Weather Forecasting)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Top of the line supercomputers are also available with other organizations. Examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;SAGA-220 (Supercomputer for Aerospace with GPU Architecture-220 teraflops) by ISRO&lt;/li&gt;&#xA;&lt;li&gt;Eka by  Computational Research Laboratories, Tata Sons&lt;/li&gt;&#xA;&lt;li&gt;Virgo Supernova by Wipro Infotech&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The above list is not complete. Many other institutions also operate supercomputing facilities (For instance, IIT Roorkee has a PARAM 10000).&#xA;And those that don't often have lower powered server clusters offering computing power to researchers (IIT Indore operates an IBMx Intel HPC cluster).&lt;/p&gt;&#xA;" OwnerUserId="1188" LastEditorUserId="1188" LastEditDate="2020-08-07T12:21:00.057" LastActivityDate="2020-08-07T12:21:00.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1944" PostTypeId="2" ParentId="532" CreationDate="2020-08-07T13:11:02.450" Score="11" Body="&lt;p&gt;The question was about &amp;quot;orbital basis sets&amp;quot; but explicitly mentions Gaussians; I guess the topic here is &lt;strong&gt;atomic orbital&lt;/strong&gt; basis sets. In this case, the &lt;strong&gt;molecular orbitals&lt;/strong&gt; are expanded as a &lt;strong&gt;linear combination of atomic orbitals&lt;/strong&gt; (LCAO) as&#xA;&lt;span class=&quot;math-container&quot;&gt;$ \psi_i({\bf r}) = \sum_{\alpha} C_{\alpha i} \chi_\alpha({\bf r})$&lt;/span&gt;; minimizing the Hartree-Fock / density functional energy with respect to the expansion coefficients &lt;span class=&quot;math-container&quot;&gt;$C_{\alpha i}$&lt;/span&gt; typically leads to Roothaan-Hall type equations &lt;span class=&quot;math-container&quot;&gt;${\bf FC}={\bf SCE}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf F}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; are the Fock and overlap matrices and &lt;span class=&quot;math-container&quot;&gt;${\bf E}$&lt;/span&gt; is a diagonal matrix of the energy eigenvalues.&lt;/p&gt;&#xA;&lt;p&gt;Atomic-orbital basis sets have the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$ \chi_{\alpha}^{nlm}({\bf r})=R_{nl}(r)Y_l^m(\hat{\bf r})$&lt;/span&gt; (non-relativistic case), and since few atomic orbitals already give qualitatively good results, you don't need a huge number of them, and you can diagonalize the Fock matrix exactly.&#xA;You can also use atomic-orbital basis sets in the context of solid state calculations, in which case you actually use a periodic, symmetry adapted version&#xA;&lt;span class=&quot;math-container&quot;&gt;$\chi_{\alpha}^{nlm}({\bf r};{\bf k})=\sum_{\bf g} e^{i{\bf k}\cdot{\bf g}} \chi_{\alpha}^{nlm}({\bf r}-{\bf R}_\alpha-{\bf g})$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;${\bf R}_\mu$&lt;/span&gt; are the coordinates of the center of the basis function, &lt;span class=&quot;math-container&quot;&gt;${\bf g}$&lt;/span&gt; sums over the lattice vectors, and &lt;span class=&quot;math-container&quot;&gt;${\bf k}$&lt;/span&gt; is the crystal momentum; but crystalline case is largely analogous to the molecular one.&lt;/p&gt;&#xA;&lt;p&gt;The basis functions used in the expansion &lt;span class=&quot;math-container&quot;&gt;$ \psi_i({\bf r}) = \sum_{\alpha} C_{\alpha i} \chi_\alpha({\bf r})$&lt;/span&gt; &lt;em&gt;don't have to be&lt;/em&gt; atomic orbitals - using e.g. finite element basis functions or plane waves is perfectly fine as well - but then your basis set can become very large (10k, 100k, even 1M basis functions!), which makes solving the eigenvalue problem in the Roothaan-Hall equation prohibitively costly; this is why finite element and plane wave calculations typically use other ways to find the self-consistent solution.&lt;/p&gt;&#xA;&lt;p&gt;Three kinds of radial functions are commonly used: Gaussian-type orbitals (GTOs) &lt;span class=&quot;math-container&quot;&gt;$R_{nl} = r^l \exp(-\zeta r^2)$&lt;/span&gt;, Slater-type orbitals (STOs) &lt;span class=&quot;math-container&quot;&gt;$R_{nl} = r^n \exp(-\zeta r)$&lt;/span&gt;, and numerical atomic orbitals (NAOs) &lt;span class=&quot;math-container&quot;&gt;$R_{nl} = u_{nl}(r)/r$&lt;/span&gt;. If you have few basis functions, then NAO &lt;span class=&quot;math-container&quot;&gt;$\gg$&lt;/span&gt; STO &lt;span class=&quot;math-container&quot;&gt;$&amp;gt;$&lt;/span&gt; GTO, since&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;NAOs are &lt;em&gt;numerically exact solutions&lt;/em&gt; for the gas-phase atom, i.e. a minimal basis is exact for a non-interacting atom [depending on the level of theory]&lt;/li&gt;&#xA;&lt;li&gt;STOs have the correct asymptotic form far away and at the nucleus [in principle], but don't do such a good job at describing the accurate form of the orbitals of the many-electron atom&lt;/li&gt;&#xA;&lt;li&gt;GTOs have a qualitatively correct form, but have the wrong asymptotics both at the nucleus and far away. However...&lt;/li&gt;&#xA;&lt;li&gt;contracted GTO basis functions (cGTOs) &lt;span class=&quot;math-container&quot;&gt;$R_{nl} = r^l \sum_n d_n \exp(-\zeta_n r^2)$&lt;/span&gt; do a &lt;strong&gt;much&lt;/strong&gt; better job at describing the form of the real atomic orbitals; contracted GTOs can be thought of as &amp;quot;primitive&amp;quot; versions of NAOs, and almost all GTO basis sets actually contain cGTOs.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, if you use a large radial expansion, I don't think that the form of the individual basis functions matters that much, as large expansions accrue enough variational freedom to describe whatever electronic structure you throw at the problem. Traditionally one avoids large expansions due to pathological problems with overcompleteness; however, I have recently shown that a simple numerical trick can be used to overcome this issue in &lt;a href=&quot;http://doi.org/10.1063/1.5139948&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 151, 241102 (2019)&lt;/a&gt; and &lt;a href=&quot;http://doi.org/10.1103/PhysRevA.101.032504&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. A 101, 032504 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;GTOs have been the overwhelming favorite in calculations, since despite their drawbacks, they carry the huge benefit of analytic integrals evaluation: the integrals are both fast to calculate, and numerically exact. STOs and NAOs, on the other hand, require numerical quadrature. While quadrature can be made adaptively better, in many computations you also need to evaluate nuclear forces and Hessians, and especially the second derivatives for the Hessian can be tricky to compute accurately enough. The situation is, however, changing: while STOs have not become mainstream, there's been a lot of work with NAOs which have shown great accuracy and become usable even for coupled-cluster calculations, see the FHI-aims program.&lt;/p&gt;&#xA;&lt;p&gt;For more details and discussion on solving the SCF equations, see e.g. our recent &lt;strong&gt;open access&lt;/strong&gt; overview paper in &lt;a href=&quot;http://doi.org/10.3390/molecules25051218&quot; rel=&quot;noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can also find a lengthier discussion on Gaussian-type orbitals, Slater-type orbitals and numerical atomic orbitals as well as other numerical approaches for electronic structure in my other recent &lt;strong&gt;open access&lt;/strong&gt; review paper, &lt;a href=&quot;http://doi.org/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25968 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-08-13T10:53:21.137" LastActivityDate="2020-08-13T10:53:21.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1945" PostTypeId="1" AcceptedAnswerId="1951" CreationDate="2020-08-07T17:42:41.540" Score="8" ViewCount="146" Body="&lt;p&gt;This is a trend that's observed in most materials that I've observed. When you go from bulk to monolayer, the bandgap of the material &lt;strong&gt;increases&lt;/strong&gt;: this is true for commonly studied materials like transition metal-dichalcogenides (MoS&lt;sub&gt;2&lt;/sub&gt;, WSe&lt;sub&gt;2&lt;/sub&gt;,MoSe&lt;sub&gt;2&lt;/sub&gt;,WS&lt;sub&gt;2&lt;/sub&gt;), as can be seen in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssa.201700218#:%7E:text=For%20monolayer%20MoS2%2C%20MoSe2%2C%20WS2,eV%20(WSe2)%20are%20predicted&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What is the physical origin behind this?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-08-07T18:07:42.120" LastActivityDate="2020-08-08T18:04:02.770" Title="Physical origin for higher bandgaps when going from bulk to few-layers" Tags="|band-structure|2d-lattice|transition-metals|dichalcogenides|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1946" PostTypeId="2" ParentId="3" CreationDate="2020-08-07T21:17:29.613" Score="5" Body="&lt;p&gt;Like many others, the correlation consistent sets start from an MCHF (i.e. small CASSCF) ground state calculation.&lt;/p&gt;&#xA;&lt;p&gt;For Li and Be the MCHF ground state has S orbitals only, but there's also a low lying P state where you promote one s electron to the p shell. The P configuration is so low that you typically include a p shell for Li and Be basis sets.&lt;/p&gt;&#xA;&lt;p&gt;Now, when you go down in the periodic table to Ca, you're next to the transition metals, and you might expect a state with electrons in the D orbitals to appear.&lt;/p&gt;&#xA;&lt;p&gt;If I remember correctly what Kirk told me half a decade ago when I was visiting him at WSU, the issue was that while in Ca the state with occupations on the 3d shell is easily optimized, but the one in K is a Rydberg-like state, which you don't want to use in a general-use molecular basis set.&lt;/p&gt;&#xA;&lt;p&gt;The problem with the D orbitals was the reason why he hadn't produced a basis set for K back then, but I guess they have figured a way around the problem :)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-07T21:17:29.613" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1947" PostTypeId="1" CreationDate="2020-08-07T23:00:08.087" Score="9" ViewCount="178" Body="&lt;p&gt;Do you know of a good software or web server tool that helps doing docking of proteins with rather large glycans? An example I'm interested in is tens of dimers of sugars (or similar), docked to proteins. I know sugars are somewhat hard to study because of their flexibility, but I was wondering if there was something out there for this case?&lt;/p&gt;&#xA;" OwnerUserId="484" LastEditorUserId="5" LastEditDate="2020-09-06T02:54:58.297" LastActivityDate="2020-12-04T18:19:16.757" Title="Docking proteins with glycans" Tags="|software|software-recommendations|proteins|docking|biomaterials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1948" PostTypeId="1" CreationDate="2020-08-08T07:15:42.613" Score="10" ViewCount="1241" Body="&lt;p&gt;Good afternoon all,&lt;/p&gt;&#xA;&lt;p&gt;My post is inquiring about the mathematical derivation behind the Monoclinic crystal structure (c axis unique).&#xA;The Brillouin zone (BZ) I really would like to derive is shown below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/hEEtK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hEEtK.png&quot; alt=&quot;From C.J. Bradley, A.P. Cracknell - Mathematical Theory of Symmetry in Solids_ Representation Theory for Point Groups and Space Groups-Oxford University Press (1972)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The plan for at least in the 2D system a and b is the following:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Get reciprocal lattice vectors a and b from you lattice vectors.&lt;/li&gt;&#xA;&lt;li&gt;Draw vectors a, b, -a, -b, a+b, and -a-b in paper.&lt;/li&gt;&#xA;&lt;li&gt;Bisect them. (It should be the equation of a straight line passing mid-distance from the vector, and forming a 90 degree angle with the vector, which is what a bisector is.)&lt;/li&gt;&#xA;&lt;li&gt;Determine the points where two consecutive bisectors join, by writing down the equations of their straight lines and making them equal.&lt;/li&gt;&#xA;&lt;li&gt;The points where bisectors cross are your high symmetry points. And this process, repeated for all pairs of vectors in point 2, give you the first Brillouin zone.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I got the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ewari.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ewari.png&quot; alt=&quot;My calculation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When i started calculating the bisector equations it got really messy and I hope to get someone to help continue the work or find a suitable reference to know how we got the BZ.&lt;/p&gt;&#xA;" OwnerUserId="604" LastEditorUserId="5" LastEditDate="2020-08-08T15:38:14.503" LastActivityDate="2020-08-08T15:38:14.503" Title="How to derive the k-path for monoclinic lattice structure?" Tags="|electronic-structure|ab-initio-calculations|band-structure|2d-lattice|k-points|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1949" PostTypeId="2" ParentId="1948" CreationDate="2020-08-08T08:47:56.763" Score="5" Body="&lt;p&gt;Not a direct answer to your question, but I hope you will still find this relevant. A very useful online tool to construct Brillouin zones and conventional &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-paths for structures of any symmetry is SeeK-path.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Inputs.&lt;/strong&gt; It accepts input structures in the formats from major DFT codes (Quantum Espresso, Castep, Vasp), as well as other formats like cif, xyz, or pbd. Additionally, you can simply specify a space group without providing a structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Outputs.&lt;/strong&gt; The online tool then generates the Brillouin zone, labelled with the corresponding high symmetry points. Additionally, it generates a proposed &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point path connecting high symmetry points.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Link.&lt;/strong&gt; You can access the website &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference.&lt;/strong&gt; All is explained in this &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0927025616305110?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; (or arXiv &lt;a href=&quot;https://arxiv.org/abs/1602.06402&quot; rel=&quot;noreferrer&quot;&gt;version&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-08-08T09:01:43.983" LastActivityDate="2020-08-08T09:01:43.983" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1950" PostTypeId="2" ParentId="1793" CreationDate="2020-08-08T16:34:37.170" Score="5" Body="&lt;p&gt;Partial answer, somewhat link-only...&lt;/p&gt;&#xA;&lt;p&gt;The website of Prof. Michel A. Van Hove, Emeritus Chair Professor in Physics and Ex-Director, Institute of Computational and Theoretical Studies, Hong Kong Baptist University is &lt;a href=&quot;http://www.icts.hkbu.edu.hk/vanhove/#Download_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.icts.hkbu.edu.hk/vanhove/#Download_software&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There you can see links to many LEED simulation packages. See also &lt;a href=&quot;http://www.icts.hkbu.edu.hk/vanhove/#Pubs&quot; rel=&quot;nofollow noreferrer&quot;&gt;publications&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Professor Van Hove is author of many things, including these books:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://books.google.com/books?id=qC_vCAAAQBAJ&amp;amp;printsec=frontcover&amp;amp;dq=van+hove+leed&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=2ahUKEwjKn6uohIzrAhULkJQKHSxnDlAQ6AEwAHoECAUQAg#v=onepage&amp;amp;q=van%20hove%20leed&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;Surface Crystallography by LEED: Theory, Computation and Structural Results&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://books.google.com/books?id=bWLyCAAAQBAJ&amp;amp;printsec=frontcover&amp;amp;dq=van+hove+leed&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=2ahUKEwjKn6uohIzrAhULkJQKHSxnDlAQ6AEwAXoECAQQAg#v=onepage&amp;amp;q=van%20hove%20leed&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;Low-Energy Electron Diffraction: Experiment, Theory and Surface Structure Determination&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What modern software supports the generation of LEED patterns?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I would like to know the answer to this as well!&lt;/p&gt;&#xA;&lt;p&gt;If you only need the positions of possible LEED spots but no intensity information, then on that page you can find&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Graphical LEED pattern simulator: &lt;a href=&quot;http://www.fhi-berlin.mpg.de/KHsoftware/LEEDpat/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;LEEDpat&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;which is old but I believe still runs on modern Windows OS. It is a little hard to run if you are not familiar with the five 2D Bravais lattices and 17 wallpaper groups (cf. &lt;a href=&quot;https://math.stackexchange.com/q/3566248/284619&quot;&gt;Number of possible rotational domains of one 2D lattice on top of another?&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;I've asked &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/527/201&quot;&gt;Overview of how self-consistent dynamical low-energy electron diffraction simulations are performed&lt;/a&gt; It received the usual answer which is something like &lt;em&gt;find someone who does it and collaborate with them&lt;/em&gt;, but I feel it's time to make a modern package and incorporate the older programs compilable codes into some modern environment like Python.&lt;/p&gt;&#xA;&lt;p&gt;The current answer says &amp;quot;I'm talking several 100k lines of code&amp;quot; but I'm sure much of that can be replace with modern numerical libraries now.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2020-08-08T16:43:54.227" LastActivityDate="2020-08-08T16:43:54.227" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1951" PostTypeId="2" ParentId="1945" CreationDate="2020-08-08T17:22:12.427" Score="9" Body="&lt;p&gt;Quantum confinement can occur when the exciton (electron-hole quasiparticle) radius is larger than the size of the semiconductor.  Due to this confinement, the energy levels which can be occupied by the exciton are quantized into discrete energy levels.  This will spread the band gap due to missing states that would exist in the bulk material.&lt;/p&gt;&#xA;&lt;p&gt;This confinement can also only occur in a single direction.  In these materials, the perpendicular direction to the plane is shorter than what is typical of the limit of confinement.  In general, you can start to suspect confinement will play a role if any direction in your semiconductor is less than 5-10 nm.&lt;/p&gt;&#xA;&lt;p&gt;Here is a source for additional reading.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://cdn.intechopen.com/pdfs/70534.pdf&quot; rel=&quot;noreferrer&quot;&gt;Quantum Confinement Effect of 2D Nanomaterials&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="671" LastEditDate="2020-08-08T18:04:02.770" LastActivityDate="2020-08-08T18:04:02.770" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1952" PostTypeId="2" ParentId="1725" CreationDate="2020-08-08T17:36:02.590" Score="5" Body="&lt;p&gt;Extracting the spin density should supposedly be as simple as reading the CHGCAR and extracting the X Y Z density separately (It is all output).  You can then treat this the same way as spin up / down.&lt;/p&gt;&#xA;&lt;p&gt;As a bonus, if you can link a reasonably sized non collinear CHGCAR somewhere I may be able to make you something to split it for you.&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=14290&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vasp Forums&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-08-08T18:25:01.633" LastActivityDate="2020-08-08T18:25:01.633" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1953" PostTypeId="1" CreationDate="2020-08-08T19:02:39.473" Score="10" ViewCount="234" Body="&lt;p&gt;Assume that the numbers of k-points in each direction are sufficient.&lt;/p&gt;&#xA;&lt;p&gt;Example - Lengths of lattice vectors: &lt;span class=&quot;math-container&quot;&gt;$2\: 2\: 4$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Required k-mesh: &lt;span class=&quot;math-container&quot;&gt;$9\times 9\times 5$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Would a &lt;span class=&quot;math-container&quot;&gt;$9\times 9\times 9$&lt;/span&gt; k-mesh work? Will it affect the calculation in any way&lt;/strong&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Intuitively, I would think it wouldn't affect the calculation because &lt;span class=&quot;math-container&quot;&gt;$9$&lt;/span&gt; in the 3rd lattice vector direction is still higher than the required &lt;span class=&quot;math-container&quot;&gt;$5$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="88" LastEditDate="2020-08-09T12:59:59.210" LastActivityDate="2020-08-09T12:59:59.210" Title="Is it okay to take a cubic Monkhorst-Pack k-mesh for a non-cubic supercell in a DFT calculation?" Tags="|density-functional-theory|vasp|k-points|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1954" PostTypeId="2" ParentId="1953" CreationDate="2020-08-08T19:21:26.340" Score="9" Body="&lt;p&gt;It will obviously affect the calculation time, which would be the only reason I would discourage you based on my knowledge.  It should not harm anything to continue with a higher symmetry k-mesh, but I believe there are problems with a lower symmetry k-mesh.&lt;/p&gt;&#xA;&lt;p&gt;Lattice of (2, 2, 4) can use a k-mesh of (9, 9, 5)&lt;/p&gt;&#xA;&lt;p&gt;Lattice of (4, 4, 4) should probably not use a mesh of (9, 9, 5)&lt;/p&gt;&#xA;&lt;p&gt;I am by no means an expert in this topic though.  I am just aware of warnings I have seen while running different codes.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-08T19:21:26.340" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1955" PostTypeId="2" ParentId="532" CreationDate="2020-08-08T22:09:10.613" Score="8" Body="&lt;p&gt;&lt;strong&gt;London Orbitals or Gauge-Including Atomic Orbitals (GIAOs)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;These are used for computing magnetic properties of molecules.&lt;/p&gt;&#xA;&lt;p&gt;In practical electronic structure calculations where a finite basis set is used, magnetic properties are not origin invariant.&lt;/p&gt;&#xA;&lt;p&gt;In practice that means that if you computed, say, magnetizabilities or a circular dichroism spectra of a molecule centered at (0,0,0), and then re-did the calculation at, say 100 Angstroms away, (100,0,0), then you would get &lt;em&gt;wildly&lt;/em&gt; different answers for the magnetic properties even if you have the same molecular geometry, wave function, energy, etc.&lt;/p&gt;&#xA;&lt;p&gt;This is obviously not OK.&lt;/p&gt;&#xA;&lt;p&gt;One solution is to make the orbitals themselves magnetic-field dependent by pre-multiplying the field-free atomic orbitals (commonly Gaussian, but not &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/j100002a024&quot; rel=&quot;nofollow noreferrer&quot;&gt;necessarily&lt;/a&gt;) with a magnetic-field dependent phase factor, or plane wave. For all practical purposes, this eliminates the origin dependence.&lt;/p&gt;&#xA;&lt;p&gt;Mathematically, a London orbital or GIAO, &lt;span class=&quot;math-container&quot;&gt;$\chi^{\textrm{GIAO}}(\mathbf{r} - \mathbf{R})$&lt;/span&gt;, centered at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; looks like a plane-wave/atomic-orbital hybrid:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\chi^{\textrm{GIAO}}(\mathbf{r} - \mathbf{R}) = \mathrm{exp}\left(\frac{i}{2}\left(\mathbf{R} \times \mathbf{B} \right) \cdot \left(\mathbf{r} - \mathbf{R}\right)\right)\chi^{\textrm{AO}}(\mathbf{r} - \mathbf{R})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where the field-free atomic orbital &lt;span class=&quot;math-container&quot;&gt;$\chi^{\textrm{AO}}(\mathbf{r} - \mathbf{R})$&lt;/span&gt; is multiplied by the magnetic field &lt;span class=&quot;math-container&quot;&gt;$\mathbf{B}$&lt;/span&gt; dependent phase factor. (And &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; is the electronic coordinate vector.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Lots of software, like Gaussian or DALTON, utilize GIAOs when computing molecular magnetic properties such as magnetizabilities, chiroptical properties, etc. Because these properties are defined in the limit as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{B}\to \mathbf{0}$&lt;/span&gt;, you don't have to use a special London orbital basis set, as it's already taken into account by the theoretical method.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, finite magnetic field calculations are much less common, but here are some programs:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://folk.uio.no/eriktel/london/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;London&lt;/a&gt; (available by request only?)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://urania.chem.washington.edu/chronusq/chronusq_public&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChronusQuantum&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;A few papers:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;F. London, &amp;quot;Théorie quantique des courants interatomiques dans les combinaisons aromatiques.&amp;quot; J. Phys. Radium 8, 397 (1937).&lt;/li&gt;&#xA;&lt;li&gt;Helgaker, Trygve, and Poul Jorgensen. &amp;quot;An electronic Hamiltonian for origin independent calculations of magnetic properties.&amp;quot; The Journal of chemical physics 95.4 (1991): 2595-2601.&lt;/li&gt;&#xA;&lt;li&gt;Ruud, Kenneth, et al. &amp;quot;Hartree–Fock limit magnetizabilities from London orbitals.&amp;quot; The Journal of chemical physics 99.5 (1993): 3847-3859.&lt;/li&gt;&#xA;&lt;li&gt;Tellgren, Erik I., Alessandro Soncini, and Trygve Helgaker. &amp;quot;Nonperturbative ab initio calculations in strong magnetic fields using London orbitals.&amp;quot; The Journal of chemical physics 129.15 (2008): 154114.&lt;/li&gt;&#xA;&lt;li&gt;Stopkowicz, Stella, et al. &amp;quot;Coupled-cluster theory for atoms and molecules in strong magnetic fields.&amp;quot; The Journal of chemical physics 143.7 (2015): 074110.&lt;/li&gt;&#xA;&lt;li&gt;Sun, Shichao, et al. &amp;quot;Simulating Magnetic Circular Dichroism Spectra with Real-Time Time-Dependent Density Functional Theory in Gauge Including Atomic Orbitals.&amp;quot; Journal of Chemical Theory and Computation 15.12 (2019): 6824-6831.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1166" LastEditorUserId="1166" LastEditDate="2020-08-12T19:00:25.843" LastActivityDate="2020-08-12T19:00:25.843" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1956" PostTypeId="1" CreationDate="2020-08-09T08:07:40.750" Score="21" ViewCount="5524" Body="&lt;p&gt;I am trying to do spin-orbit coupled calculations for various topological insulators. I have found papers using Quantum Espresso with ONCV pseudopotentials and papers using VASP with PAW pseudopotentials. I know that PAW is also available in Quantum Espresso. But which would be better: ONCV or PAW?&lt;/p&gt;&#xA;&lt;p&gt;Also, as a general question, why would one prefer one pseudopotential over the other?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2020-08-11T23:57:42.317" LastActivityDate="2020-10-12T18:14:23.323" Title="What is the difference between Ultrasoft, ONCV and PAW Pseudopotentials? Which is better for a spin-orbit coupled calculation?" Tags="|vasp|quantum-espresso|pseudopotentials|topological-insulators|spin-orbit-coupling|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1957" PostTypeId="1" AcceptedAnswerId="1958" CreationDate="2020-08-09T11:32:07.107" Score="9" ViewCount="306" Body="&lt;p&gt;One of the challenges of modelling completely new material using DFT is the selection of initial geometry. Usually, an experimental structure (cif) which appears to be similar to the new material in question is selected intuitively (correct me if I'm wrong) and several such selections are made to comparatively analyse the optimised free-energies if necessary. I found a similar &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1126/how-much-does-the-initial-geometry-affect-the-final-geometry-in-optimization-cal&quot;&gt;question&lt;/a&gt; that concludes optimised geometry depends heavily on the initial geometry.&lt;/p&gt;&#xA;&lt;p&gt;Let us assume the full relaxation of ionic positions, cell volume and cell shape is carried out starting from some geometry.&lt;/p&gt;&#xA;&lt;p&gt;My question is, is there a possibility to change the initial crystal system during relaxation? Can it change from orthorhombic to cubic, tetragonal etc., for example, in the process of finding a local minimum in the potential energy surface?&lt;/p&gt;&#xA;&lt;p&gt;If it does not change even after the relaxation, does that mean the selected initial geometry is a good starting point?&lt;/p&gt;&#xA;" OwnerUserId="857" LastEditorUserId="857" LastEditDate="2020-08-10T11:17:07.530" LastActivityDate="2020-08-10T11:17:07.530" Title="Is there a possibility to change the initial crystal system during full geometric relaxation?" Tags="|density-functional-theory|geometry-optimization|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1958" PostTypeId="2" ParentId="1957" CreationDate="2020-08-09T16:52:22.440" Score="8" Body="&lt;p&gt;In general this depends on the potential energy surface.  If symmetry is turned off and the cell is allowed to change shape and size, then no promises are made either way on what will be found.  Shallow local minima may be skipped over due to the optimization process, which will likely send you to a higher symmetry if that is the most stable structure.&lt;/p&gt;&#xA;&lt;p&gt;This is easy to imagine, take an FCC cell (of something that actually prefers FCC like Pt) and displace one atom 0.2A or so.  You can also extend one cell vector by a similar amount.  Run with your given settings and watch as the cell comes back to the original FCC cell with its symmetry.  This is a bit of a contrived example, but it shows that you can go from one symmetry to another via relaxation.&lt;/p&gt;&#xA;&lt;p&gt;Going from high symmetry to low symmetry typically causes problems if symmetry is turned on.  This often manifests itself as an error in the software though.  A good example of high symmetry to lower symmetry is an adsorbate moving from a top site to a bridge site on a Pt(111) surface.  This can occur if the top site is a local maximum rather than a local minimum.  You can see below that this would lower the symmetry of the cell.  This is a quite common problem to see.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0s6Qp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0s6Qp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-09T16:52:22.440" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1959" PostTypeId="1" CreationDate="2020-08-09T18:20:38.940" Score="15" ViewCount="200" Body="&lt;p&gt;What are the best packages that can generate candidate structures for quantum chemical optimization (DFT or CCSD) to find the global minimum? I am working on the gas-phase small inorganic clusters (number of atoms less than 30).&lt;/p&gt;&#xA;" OwnerUserId="477" LastActivityDate="2020-08-12T16:58:45.433" Title="Candidate structures for global minimum determination" Tags="|one-topic-per-answer|quantum-chemistry|potential-energy-surface|geometry-optimization|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1960" PostTypeId="2" ParentId="1959" CreationDate="2020-08-10T04:39:39.963" Score="8" Body="&lt;h2&gt;Confab OpenBabel&lt;/h2&gt;&#xA;&lt;p&gt;source documentation: &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/3DStructureGen/multipleconformers.html&quot; rel=&quot;noreferrer&quot;&gt;https://open-babel.readthedocs.io/en/latest/3DStructureGen/multipleconformers.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Example:&#xA;&lt;code&gt;obabel &amp;lt;inputfile&amp;gt; -O &amp;lt;outputfile&amp;gt; --confab [confab options]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Some of the options include ecutoff and rcutoff (which help eliminate duplicates)&lt;/p&gt;&#xA;&lt;p&gt;OpenBabel can be easily downloaded through Anaconda, the python package manager.&lt;/p&gt;&#xA;&lt;p&gt;However, the energy cutoff criterion may be unreliable for inorganic molecules (you'll have to see) because the molecular mechanics parameters may be unreliable for those elements.&lt;/p&gt;&#xA;&lt;p&gt;The best bet is to try to generate as many unique conformers as possible and optimize all of them to find which is the lowest energy.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2020-08-10T04:39:39.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1961" PostTypeId="2" ParentId="1957" CreationDate="2020-08-10T09:55:24.070" Score="4" Body="&lt;p&gt;A geometry relaxation is a calculation that locates a local minimum of the potential energy surface. Symmetry &lt;em&gt;can&lt;/em&gt; change during a geometry relaxation, but the interplay between symmetry and minima of the potential energy surface is interesting. If you enforce the symmetry of the starting structure during your geometry relaxation, then you encounter two situations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;From low to high symmetry.&lt;/strong&gt; Imposing a symmetry to your structure means that a set of symmetry operations are definitely obeyed by that structure. However, this does not forbid &lt;em&gt;additional&lt;/em&gt; symmetry operations to also be obeyed by that structure, and therefore it is possible to go from low to high symmetry. The higher symmetry is only enforced numerically, so it is advisable to impose the higher symmetry after the geometry relaxation to include the newly found symmetry operations exactly. Tristan Maxson provided a nice example of this in their&#xA;answer. As another example, take diamond in the cubic fcc structure,&#xA;reduce the symmetry to tetragonal to create your initial structure,&#xA;and then when you relax the structure it will fall back to the cubic&#xA;structure increasing its symmetry.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;From high to low symmetry.&lt;/strong&gt; If you are enforcing a certain symmetry in your structure, but the real structure you are looking for has a lower symmetry, then it is impossible to find it during your geometry relaxation. This is because imposing a symmetry on your structure effectively reduces the dimensionality of the potential energy surface by removing all &amp;quot;directions&amp;quot; that are not consistent with the symmetry you are imposing. This means that when you relax imposing symmetry you will fall to a local minimum of this symmetry-constrained lower-dimensional energy surface, rather than to a local minimum of the real energy surface. If the real ground state of the system has a lower symmetry, then this means that the minimum in the symmetry-constrained lower-dimensional energy surface is in reality a saddle point in the full energy surface, but you have no way of finding this out with your symmetry-constrained geometry relaxation. However, a good way to test for this once you have found your structure with a symmetry constraint is to perform a subsequent phonon calculation. A phonon calculation gives you the Hessian about the stationary point in the potential energy surface, and if you are at a saddle point of the full energy surface this will come out as a negative eigenvalue of the Hessian, corresponding to an imaginary phonon frequency. The associated eigenvector tells you in which direction to distort the structure to find the lower energy lower symmetry structure.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If you do not enforce the symmetry of the starting structure, then in principle you can change from low to high symmetry or from high to low symmetry during the relaxation.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-10T09:55:24.070" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1962" PostTypeId="1" AcceptedAnswerId="2154" CreationDate="2020-08-10T12:45:47.773" Score="7" ViewCount="328" Body="&lt;p&gt;I know that iDMRG (infinite-density matrix renormalization group) calculations are usually treated as capturing all the thermodynamic-limit behavior of a system, and I have also heard that there are add-on techniques for calculating quantities like correlation lengths. I know this all can't be perfect or no one would do finite-size DMRG calculations.&lt;/p&gt;&#xA;&lt;p&gt;Here is my question: what are the limitations of iDMRG, &lt;strong&gt;and&lt;/strong&gt; how does it go wrong?&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-08-31T17:32:39.787" Title="iDMRG: are there subtle ways that finite-size effects creep in?" Tags="|dmrg|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1963" PostTypeId="1" CreationDate="2020-08-10T19:17:54.987" Score="5" ViewCount="220" Body="&lt;p&gt;Szabo/Ostlund list the CI matrix elements between singlet symmetry-adapted configurations (SAC) in Table 4.1 of their book:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle ^1\Psi^r_ a \lvert \mathcal{H} - E_ 0 \rvert ^1\Psi^r_ a \rangle,&#xA;\langle \Psi_ 0 \lvert \mathcal{H} \rvert ^1\Psi^{rr}_ {aa} \rangle,&#xA;\langle \Psi_ 0 \lvert \mathcal{H} \rvert ^1\Psi^{rs}_ {aa} \rangle,&#xA;\langle \Psi_ 0 \lvert \mathcal{H} \rvert ^1\Psi^{rr}_ {ab} \rangle,&#xA;\langle \Psi_ 0 \lvert \mathcal{H} \rvert ^A\Psi^{rs}_ {ab} \rangle,&#xA;\langle \Psi_ 0 \lvert \mathcal{H} \rvert ^B\Psi^{rs}_ {ab} \rangle, &#xA;\langle ^1\Psi^{rr}_ {aa} \lvert \mathcal{H} - E_ 0 \rvert ^1\Psi^{rr}_ {aa} \rangle,&#xA;\langle ^1\Psi^{rs}_ {aa} \lvert \mathcal{H} - E_ 0 \rvert ^1\Psi^{rs}_ {aa} \rangle,&#xA;\langle ^1\Psi^{rr}_ {ab} \lvert \mathcal{H} - E_ 0 \rvert ^1\Psi^{rr}_ {ab} \rangle,&#xA;\langle ^A\Psi^{rs}_ {ab} \lvert \mathcal{H} - E_ 0 \rvert ^A\Psi^{rs}_ {ab} \rangle,&#xA;\langle ^B\Psi^{rs}_ {ab} \lvert \mathcal{H} - E_ 0 \rvert ^B\Psi^{rs}_ {ab} \rangle,&#xA;\langle ^A\Psi^{rs}_ {ab} \lvert \mathcal{H} \rvert ^B\Psi^{rs}_ {ab} \rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The expressions are given in terms of restricted, canonical MOs. While I have been able to arrive at the same results for all listed elements I tried so far, I am apparently unable to correctly derive elements that are not listed. I do not believe that they are all &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am testing my toy SCF/MP2/CIS/CID implementation against ORCA and am able to reproduce RHF, UHF, RMP2, and RCIS/TDHF results for different systems with good precision. However, CID in general eludes me thus far. &lt;span class=&quot;math-container&quot;&gt;$\ce{H_2}$&lt;/span&gt; in a minimal basis set (single-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt;) works correctly, as does &lt;span class=&quot;math-container&quot;&gt;$\ce{He}$&lt;/span&gt; in double-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt;. However, my results for &lt;span class=&quot;math-container&quot;&gt;$\ce{He}$&lt;/span&gt; in triple-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; are rather far off.&lt;/p&gt;&#xA;&lt;p&gt;I am looking for the correctly derived off-diagonal elements of the CISD matrix. Lacking this, concrete pointers on which other, freely available QC suite will print the matrix are also welcome. Unfortunately, I am reduced to the status of a hobbyist without access to literature.&lt;/p&gt;&#xA;&lt;p&gt;Edit: In the comments, it was asked how I was confident in the integrals. The AO integral code is ancient and has been verified for RHF and UHF against ORCA and Turbomole. While performing the CID calculation, the RHF and RMP2 energies are being calculated at the same time, and match the ORCA results. I just performed a calculation for &lt;span class=&quot;math-container&quot;&gt;$\ce{BeH2}$&lt;/span&gt; with matching results - given the number of AO/MO involved, I feel confident in my AO-MO-transformation.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;A Szabo, NS Ostlund &lt;em&gt;Modern Quantum Chemistry&lt;/em&gt;, Dover Publications, first edition, 1996.&lt;/p&gt;&#xA;" OwnerUserId="794" LastEditorUserId="5" LastEditDate="2020-08-20T19:56:47.477" LastActivityDate="2020-08-21T14:28:43.873" Title="What are the other matrix elements in singlet symmetry-adapted CISD?" Tags="|ab-initio-calculations|quantum-chemistry|electron-correlation|configuration-interaction|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1964" PostTypeId="2" ParentId="1911" CreationDate="2020-08-10T22:05:45.473" Score="12" Body="&lt;p&gt;As the answer above mentioned, the biggest difference is perhaps CASTEP takes two input files with suffix &amp;quot;cell&amp;quot; and &amp;quot;param&amp;quot;, other things are very similar. After all, both programs do plane-wave pseudopotential calculations.&lt;/p&gt;&#xA;&lt;p&gt;Below are a few other subtle differences (or tips?) - I am a CASTEP user recently started using VASP!&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In CASTEP the calculation job is selected by a single &lt;code&gt;task&lt;/code&gt; keyword in the param file, rather than multiple tags as in VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Bandstructure/DOS calculation in VASP typically take two steps, but in CASTEP the program itself can do a self-consistent calculation followed by a non self-consistent calculation in one go - you just need to supply two sets of kpoints paths/meshes.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Variable cell geometry optimisations in CASTEP default to &amp;quot;constant cut-off&amp;quot; so typically there is no need to redo a single point calculation for the optimised geometry. But still, mind the Pulay stress!&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Parallelisation in CASTEP is fully automatic and there is no need to set NCORE KPAR explicitly like in VASP. It tends to maximise kpoints parallelisation which is most efficient, but sometimes this can lead to high memory usage.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;CASTEP has a &lt;code&gt;--dryrun&lt;/code&gt; option - you can make use it to check memory requirements and a number of kpoints to decide the number of MPI processes.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The cell file also takes a few keyword options such as &lt;code&gt;SYMMETRY_GENERATE&lt;/code&gt; and &lt;code&gt;SNAP_TO_SYMMEYRY&lt;/code&gt;. The former turns on the symmetry and the latter snap the atoms to their high symmetry positions in case the input coordinates do not have high floating-point precision. You almost always want those two in the &lt;code&gt;cell&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;ASE can be very useful for generating CASTEP inputs. I have also made another simpler package for just writing simple input files in python called &lt;a href=&quot;https://pypi.org/project/castepinput/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;castepinput&lt;/code&gt;&lt;/a&gt;. It is used by a more complex package for interfacing CASTEP with a workflow/data management engine called &lt;a href=&quot;https://aiida.net&quot; rel=&quot;nofollow noreferrer&quot;&gt;AiiDA&lt;/a&gt; (&lt;a href=&quot;https://aiida-castep.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;aiida-castep&lt;/a&gt;). It also has interfaces to VASP and Quantum-Espresso.&lt;/p&gt;&#xA;" OwnerUserId="1020" LastEditorUserId="671" LastEditDate="2022-07-12T15:57:27.650" LastActivityDate="2022-07-12T15:57:27.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1965" PostTypeId="2" ParentId="190" CreationDate="2020-08-11T08:49:07.033" Score="10" Body="&lt;h1&gt;Quantum Monte Carlo&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;What are the types of Quantum Monte Carlo?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Methods&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;SSE QMC: Stochastic Series Expansion QMC&lt;/li&gt;&#xA;&lt;li&gt;SAC: Stochastic Analytic Continuation (an add-on technique for real-time dynamics)&lt;/li&gt;&#xA;&lt;li&gt;VMC: &lt;a href=&quot;https://en.wikipedia.org/wiki/Variational_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Variational Monte Carlo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;DMC: &lt;a href=&quot;https://en.wikipedia.org/wiki/Diffusion_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Diffusion Monte Carlo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;t-VMC: &lt;a href=&quot;https://en.wikipedia.org/wiki/Time-dependent_variational_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Time-dependent variational Monte Carlo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;CT-QMC: &lt;a href=&quot;https://en.wikipedia.org/wiki/Continuous-time_quantum_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Continuous time QMC&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;DDQMC (or DDMC): [Diagrammatic determinantal QMC]&lt;/li&gt;&#xA;&lt;li&gt;PIMC: &lt;a href=&quot;https://en.wikipedia.org/wiki/Path_integral_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Path integral Monte Carlo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Packages&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ALF: &lt;a href=&quot;https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/&quot; rel=&quot;noreferrer&quot;&gt;Algorithms Lattice Fermions&lt;/a&gt; (Auxiliary-field QMC package)&lt;/li&gt;&#xA;&lt;li&gt;ALPS: &lt;a href=&quot;http://alps.comp-phys.org/mediawiki/index.php/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;Algorithms and Libraries for Physics Simulations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://vallico.net/casinoqmc/what-is-casino/&quot; rel=&quot;noreferrer&quot;&gt;CASINO&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Feel free to comment with more suggestions and I can add them to the answer.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-08-11T14:31:17.593" LastActivityDate="2020-08-11T14:31:17.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1966" PostTypeId="2" ParentId="190" CreationDate="2020-08-11T16:30:15.413" Score="6" Body="&lt;h2&gt;General&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;DFT: Density Functional Theory (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/density-functional-theory&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;TDDFT: Time-dependent density functional theory (&lt;a href=&quot;https://en.wikipedia.org/wiki/Time-dependent_density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;LDA: Local Density Approximation (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/local-density-approximation&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;GGA: Generalized Gradient Approximation (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/generalized-gradient-approximation&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;HF: Hartree-Fock (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/hartree-fock-method&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;post HF: Post Hartree-Fock (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/post-hartree-fock-methods&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;RHF: Restricted Hartree-Fock (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/restricted-open-shell-hartree-fock&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;UHF: Unrestricted Hartree-Fock (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/unrestricted-hartree-fock-calculation&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;FMO: Fragment Molecular Orbital (&lt;a href=&quot;https://staff.aist.go.jp/d.g.fedorov/fmo/main.html&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;MP: Møller-Plesset Perturbation Theory (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/mller-plesset-perturbation-theory&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$k \cdot p$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$k \cdot p$&lt;/span&gt; perturbation theory (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/kp-perturbation-theory&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;MO: Molecular Orbital (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/molecular-orbital&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;HOMO: Highest Occupied Molecular Orbital (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/highest-occupied-molecular-orbital&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;LUMO: Lowest Unoccupied Molecular Orbital (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/lowest-unoccupied-molecular-orbital&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;VB: Valence Band (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/valence-band&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;CB: Conduction Band (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/conduction-band&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;DOS: Density of State (&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/density-of-state&quot; rel=&quot;noreferrer&quot;&gt;...&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;PDOS: Partial Density of State&lt;/li&gt;&#xA;&lt;li&gt;LDOS: Local Density of State&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-08-11T16:41:01.170" LastActivityDate="2020-08-11T16:41:01.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1967" PostTypeId="1" AcceptedAnswerId="4010" CreationDate="2020-08-11T18:48:30.843" Score="12" ViewCount="412" Body="&lt;p&gt;I want to create a nanoparticle of CuO and predict it's structure. I've done unit cell relaxation with Quantum ESPRESSO. One tool to predict nanocluster structure is Calypso which is PSO-based. I'm using Quantum ESPRESSO with it. If anyone does &lt;a href=&quot;http://www.calypso.cn/documentation/&quot; rel=&quot;noreferrer&quot;&gt;Calypso structure prediction&lt;/a&gt;, what are some ways for predicting nanocluster structure?&#xA;I want to use this nanostructure to calculate TDDFT and some other optical properties.&lt;/p&gt;&#xA;&lt;p&gt;If there is any other way to predict a nanoparticle's structure (without Calypso) please let me know.&lt;/p&gt;&#xA;" OwnerUserId="1200" LastEditorUserId="5" LastEditDate="2020-09-26T20:46:26.427" LastActivityDate="2020-12-31T08:12:52.940" Title="How do I predict the structure of a nanoparticle with Calypso and Quantum ESPRESSO?" Tags="|quantum-espresso|software-recommendations|geometry-optimization|structure|nanoparticles|" AnswerCount="1" CommentCount="8" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1968" PostTypeId="1" CreationDate="2020-08-11T22:01:09.597" Score="7" ViewCount="226" Body="&lt;p&gt;I am trying to program a collective variable in PLUMED which is basically the number of bonds in the shortest Hydrogen bond wire in a system of water molecules. I plan to use the &lt;a href=&quot;https://www.plumed.org/doc-v2.5/user-doc/html/_h_b_o_n_d__m_a_t_r_i_x.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;HBond_Matrix&lt;/a&gt; from plumed to accomplish this.&lt;/p&gt;&#xA;&lt;p&gt;As per documentation, I can use the following to...&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...analyze the number of hydrogen bonds each of the oxygen atoms in a box of water participates in. Each water molecule can participate in a hydrogen bond in one of two ways. It can either donate one of its hydrogen atom to the neighboring oxygen or it can accept a bond between the hydrogen of a neighboring water molecule and its own oxygen. The input below allows you to output information on the number of hydrogen bonds each of the water molecules donates and accepts. This information is output in two xyz files which each contain five columns of data. The first four of these columns are a label for the atom and the x, y and z position of the oxygen. The last column is then the number of accepted/donated hydrogen bonds.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;mat: HBOND_MATRIX ATOMS=1-192:3 HYDROGENS=2-192:3,3-192:3 SWITCH={RATIONAL R_0=3.20} HSWITCH={RATIONAL R_0=2.30} ASWITCH={RATIONAL R_0=0.167pi} SUM&#xA;rsums: ROWSUMS MATRIX=mat MEAN&#xA;csums: COLUMNSUMS MATRIX=mat MEAN&#xA;DUMPMULTICOLVAR DATA=rsums FILE=donors.xyz&#xA;DUMPMULTICOLVAR DATA=csums FILE=acceptors.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since I can't loop over the matrix and determine the number of bonds in each H-Bond wire, is there another amalgamation of basic functions that might do the trick?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-09-26T20:49:05.237" LastActivityDate="2020-09-26T20:49:05.237" Title="Collective variable to determine the number of bonds in the shortest Hydrogen bond wire" Tags="|software|molecular-dynamics|plumed|collective-variable|hydrogen-bonds|" AnswerCount="0" CommentCount="6" ClosedDate="2020-11-29T02:55:20.103" ContentLicense="CC BY-SA 4.0" />
  <row Id="1969" PostTypeId="5" CreationDate="2020-08-11T22:03:06.733" Score="0" Body="&lt;p&gt;PLUMED is a plugin that works with a large number of molecular dynamics codes. It can be used to analyze features of the dynamics on-the-fly or to perform a wide variety of free energy methods. PLUMED can also work as a Command Line Tools to perform analysis on trajectories saved in most of the existing formats.&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="1102" LastEditDate="2020-08-12T08:24:53.943" LastActivityDate="2020-08-12T08:24:53.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1970" PostTypeId="4" CreationDate="2020-08-11T22:03:06.733" Score="0" Body="Questions relating to the use of the PLUMED software." OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-08-11T23:52:12.223" LastActivityDate="2020-08-11T23:52:12.223" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1971" PostTypeId="5" CreationDate="2020-08-11T22:11:36.560" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-08-11T22:11:36.560" LastActivityDate="2020-08-11T22:11:36.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1972" PostTypeId="4" CreationDate="2020-08-11T22:11:36.560" Score="0" Body="A collective variable is a function of the particle positions or other collective variables. It is usually used to bias a simulation along a particular dimension." OwnerUserId="1102" LastEditorUserId="1102" LastEditDate="2020-08-11T23:52:24.767" LastActivityDate="2020-08-11T23:52:24.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1973" PostTypeId="2" ParentId="1197" CreationDate="2020-08-12T03:06:58.070" Score="7" Body="&lt;p&gt;Not really sure about benchmarks for solid state TS geometries. A couple of scattered piece of references are:&lt;/p&gt;&#xA;&lt;p&gt;(i) This paper by Ceder's group has several related TS barriers: aip.scitation.org/doi/pdf/10.1063/1.4960790&lt;/p&gt;&#xA;&lt;p&gt;(ii) Then there is Henkelman's paper for bulk unit cell TS calculations: aip.scitation.org/doi/abs/10.1063/1.3684549. Maybe you are already aware, but in surface catalysis you can find a ton of references for adatom (transition metals or organics) diffusional barriers on various transition metal surfaces - LMK if interested.&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-08-12T03:06:58.070" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1974" PostTypeId="2" ParentId="1959" CreationDate="2020-08-12T05:34:35.787" Score="7" Body="&lt;h1&gt;xtb&lt;/h1&gt;&#xA;&lt;p&gt;The Grimme group's freely available &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;nofollow noreferrer&quot;&gt;xtb tight binding program&lt;/a&gt; based on the &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/gfnff.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GFN force field&lt;/a&gt; can be used to rank candidate structures in energy with the &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/crest.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CREST&lt;/a&gt; tool.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-08-12T16:58:45.433" LastActivityDate="2020-08-12T16:58:45.433" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1975" PostTypeId="2" ParentId="1959" CreationDate="2020-08-12T07:04:17.867" Score="6" Body="&lt;h2&gt;CCDC&lt;/h2&gt;&#xA;&lt;p&gt;The Cambridge Crystallographic Data Centre organizes a regular organic crystal structure prediction blind test as detailed in their &lt;a href=&quot;https://www.ccdc.cam.ac.uk/Community/initiatives/CSPBlindTests/&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;. These started in 1999 and the latest (the sixth one) was held in 2015. Participants, which include leading research groups in structure prediction, are asked to predict the structure of a range of molecules, the latest test including compounds like a small rigid molecule, drug candidates with multiple polymorphs, and salt hydrates. Although the title of the blind test specifies &amp;quot;organic&amp;quot; crystals, the methods used should be applicable to what you are trying to do.&lt;/p&gt;&#xA;&lt;p&gt;Each blind test has an associated paper, and you can find the latest &lt;a href=&quot;http://scripts.iucr.org/cgi-bin/paper?S2052520616007447&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2020-08-12T16:58:24.200" LastActivityDate="2020-08-12T16:58:24.200" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1976" PostTypeId="1" AcceptedAnswerId="2012" CreationDate="2020-08-12T08:33:01.077" Score="11" ViewCount="1970" Body="&lt;p&gt;I have had a look at the example of Silicon provided &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&#xA;in the &lt;code&gt;WIKIVASP&lt;/code&gt; website, and I noticed that the &lt;code&gt;KPOINTS&lt;/code&gt; file used for HSE06 bandstructure contains two parts as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Automatically generated mesh&#xA;      26&#xA;Reciprocal lattice&#xA;    0.00000000000000    0.00000000000000    0.00000000000000             1&#xA;    0.16666666666667    0.00000000000000    0.00000000000000             8&#xA;    0.33333333333333    0.00000000000000    0.00000000000000             8&#xA;    0.50000000000000    0.00000000000000    0.00000000000000             4&#xA;    0.16666666666667    0.16666666666667    0.00000000000000             6&#xA;    0.33333333333333    0.16666666666667    0.00000000000000            24&#xA;    0.50000000000000    0.16666666666667    0.00000000000000            24&#xA;   -0.33333333333333    0.16666666666667    0.00000000000000            24&#xA;   -0.16666666666667    0.16666666666667    0.00000000000000            12&#xA;    0.33333333333333    0.33333333333333    0.00000000000000             6&#xA;    0.50000000000000    0.33333333333333    0.00000000000000            24&#xA;   -0.33333333333333    0.33333333333333    0.00000000000000            12&#xA;    0.50000000000000    0.50000000000000    0.00000000000000             3&#xA;    0.50000000000000    0.33333333333333    0.16666666666667            24&#xA;   -0.33333333333333    0.33333333333333    0.16666666666667            24&#xA;   -0.33333333333333    0.50000000000000    0.16666666666667            12&#xA;0.00000000 0.00000000 0.00000000 0.000&#xA;0.00000000 0.05555556 0.05555556 0.000&#xA;0.00000000 0.11111111 0.11111111 0.000&#xA;0.00000000 0.16666667 0.16666667 0.000&#xA;0.00000000 0.22222222 0.22222222 0.000&#xA;0.00000000 0.27777778 0.27777778 0.000&#xA;0.00000000 0.33333333 0.33333333 0.000&#xA;0.00000000 0.38888889 0.38888889 0.000&#xA;0.00000000 0.44444444 0.44444444 0.000&#xA;0.00000000 0.50000000 0.50000000 0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;My question is: could you explain to me what is the meaning of the second part of this file that contains zeros at the end? And how can one generate a file like this for calculating the HSE06 bandstructure for any material?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="792" LastEditDate="2020-08-17T07:59:33.307" LastActivityDate="2021-08-24T10:07:32.490" Title="How to generate KPOINTS file for HSE06 band-structure calculations?" Tags="|density-functional-theory|vasp|k-points|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1977" PostTypeId="2" ParentId="1976" CreationDate="2020-08-12T09:30:54.967" Score="12" Body="&lt;p&gt;The usual strategy to perform a band structure calculation in DFT has two steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Perform a self-consistent calculation using a uniform &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid to determine the self-consistent potential.&lt;/li&gt;&#xA;&lt;li&gt;Perform a non-self-consistent calculation using the potential determined in step 1 for some &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point path along the Brillouin zone.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In VASP, the above strategy works in a somewhat convoluted way if you are using a hybrid functional: you have to do both steps at once. The two blocks in the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points file that you show perform these two steps.&lt;/p&gt;&#xA;&lt;p&gt;The first block corresponds to the uniform &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid to perform the self-consistent calculation. The last column of integers in the file gives the multiplicity of the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points: you are only doing calculations in the irreducible Brillouin zone, and the multiplicity tells you how many other points in the full Brillouin zone are related to that one, so that when you calculate Brillouin zone averages (for example to determine the self-consistent potential) you need to weight each &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point by that number.&lt;/p&gt;&#xA;&lt;p&gt;The second block corresponds to the non-uniform &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point path along which you want to calculate the band structure. The bands are also calculated for these points, so you get the corresponding eigenvalues in the output and you can plot the  band structure from those. But because their weight (fourth column) is zero, they don't contribute to averages over the Brillouin zone, so they don't contribute to the self-consistent potential. You want to enforce this because in the calculation of BZ averages you want a uniform grid, not the highly non-uniform sampling that a path provides.&lt;/p&gt;&#xA;&lt;p&gt;With this strategy, at the end of the self-consistent calculation you have essentially reproduced the two steps above in one go: the first block of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points is used for determining the self-consistent potential, and the second block does not contribute to the self-consistent potential but you still get the bands so that you can calculate the band structure.&lt;/p&gt;&#xA;&lt;p&gt;How can you generate such a file? I am not sure if there is an automatic way of generating it. However, an easy option is to first do a band structure calculation using a non-hybrid functional, say PBE. You first do the self-consistent calculation, where you give the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid you want (say &lt;span class=&quot;math-container&quot;&gt;$n_1\times n_2\times n_3$&lt;/span&gt;) in the KPOINTS file, and then the OUTCAR file has a list of the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in the irreducible BZ with the corresponding weights, that you can copy-paste as the first block. Similarly, you can then do a PBE band structure calculation specifying the high symmetry points in the BZ, and the VASP OUTCAR file will contain the specific points along the path. You can then copy-paste these as the second block, and remember to add the &amp;quot;0&amp;quot; weights as a fourth column.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-12T09:30:54.967" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1978" PostTypeId="2" ParentId="1601" CreationDate="2020-08-12T10:14:46.897" Score="8" Body="&lt;p&gt;A very neat recent development for the modelling of disorder is the so-called &lt;em&gt;localization landscape theory&lt;/em&gt;, first introduced &lt;a href=&quot;https://www.pnas.org/content/109/37/14761&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Consider a general Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\hat{H}=-\frac{\hbar^2}{2m}\nabla^2+V$&lt;/span&gt;. The landscape function &lt;span class=&quot;math-container&quot;&gt;$u$&lt;/span&gt; is defined as the solution to this equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}u=1.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This innocent-looking landscape function has been shown to encode a great deal of information for studying the complex energy landscapes associated with disorder. For example, it can be shown that (i) the eigenstates &lt;span class=&quot;math-container&quot;&gt;$\psi(\mathbf{r})$&lt;/span&gt; and eigenenergies &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; of the Hamiltonian obey &lt;span class=&quot;math-container&quot;&gt;$|\psi(\mathbf{r})|\leq Eu(\mathbf{r})$&lt;/span&gt;, so that the localization landscape function &lt;span class=&quot;math-container&quot;&gt;$u$&lt;/span&gt; delimits localization regions in space, or that (ii) the function &lt;span class=&quot;math-container&quot;&gt;$W(\mathbf{r})=1/u(\mathbf{r})$&lt;/span&gt; acts as a confining potential that controls quantities like the exponential decay of Anderson localized states.&lt;/p&gt;&#xA;&lt;p&gt;The localization landscape theory has recently been adopted in materials simulations of disorder. This series of three papers provides a very comprehensive introduction to the theory, and a demonstration of what is possible:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Basic theory and modelling: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.144204&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Urbach tails of disordered InGaN alloy quantum well layers: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.144205&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Carrier transport and recombination in light emitting diodes: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.144206&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-12T10:14:46.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1979" PostTypeId="1" AcceptedAnswerId="1981" CreationDate="2020-08-12T17:09:53.077" Score="14" ViewCount="813" Body="&lt;p&gt;For example, GPAW supports both plane-wave and atomic-orbital basis methods.  I know that atomic-orbital basis methods can have difficulty with electrons occupying vacancies for example, but what types of systems are good or bad for atomic-orbital-based methods.&lt;/p&gt;&#xA;&lt;p&gt;To be clear I would like to know what types of systems have which pros and cons of both methods.  I am particularly curious about metal vs semiconductor and surface vs bulk vs nanoparticle etc.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="1218" LastEditDate="2021-02-20T09:00:19.967" LastActivityDate="2021-02-22T10:04:59.010" Title="When are atomic-orbital-basis (rather than plane-wave) methods appropriate in periodic DFT?" Tags="|basis-sets|pseudopotentials|gpaw|plane-waves|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1980" PostTypeId="2" ParentId="1956" CreationDate="2020-08-12T17:22:45.683" Score="5" Body="&lt;p&gt;Spin-orbit coupling is an effect that is dependent on the relativistic effect. So you should use fully relativistic PP(pseudopotentials) whatever you use. Another thing is that PP often varies from your material structure. So, the efficiency of PP is highly dependent on what your simulation output parameter is. There are a lot of things related to the performance of the simulation. So, my suggestion is you can benchmark on a small scale. You can see this paper below I wrote for benchmarking. Though it's on Quantum espresso but I think the process is similar.&#xA;&lt;a href=&quot;http://dx.doi.org/10.13140/RG.2.2.25087.23207&quot; rel=&quot;noreferrer&quot;&gt;http://dx.doi.org/10.13140/RG.2.2.25087.23207&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1200" LastActivityDate="2020-08-12T17:22:45.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1981" PostTypeId="2" ParentId="1979" CreationDate="2020-08-12T23:07:42.973" Score="12" Body="&lt;p&gt;The clearest example in my mind is if you want to understand the orbital-based contributions to some phenomena (e.g. bonding, a reaction energy), particularly if the periodic material being modeled is more like a molecular solid where the chemical picture of orbitals is more intuitive than bands. There are several schemes out there that try to go from PAW to localized basis set-like results though, including the &lt;a href=&quot;https://github.com/jrschmidt2/periodic-NBO&quot; rel=&quot;noreferrer&quot;&gt;periodic extension to natural bonding orbitals (NBOs)&lt;/a&gt;, &lt;a href=&quot;http://ion.chem.usu.edu/%7Eboldyrev/ssadndp.php&quot; rel=&quot;noreferrer&quot;&gt;Solid State Adaptive Natural Density Partitioning (SSAdNDP)&lt;/a&gt;, and the &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.26353&quot; rel=&quot;noreferrer&quot;&gt;LOBSTER&lt;/a&gt; code.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-08-13T00:44:38.457" LastActivityDate="2020-08-13T00:44:38.457" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1982" PostTypeId="2" ParentId="1976" CreationDate="2020-08-12T23:35:01.523" Score="7" Body="&lt;p&gt;To add to ProfM's answer, you can generate lists of k-points along high-symmetry paths in the Brillouin zone using XCrySDen. Open your structure (you can format it as a XYZ file) and go to the &lt;em&gt;Tools&lt;/em&gt; menu, and open &lt;em&gt;k-path selection&lt;/em&gt;. Now you will be shown your Brillouin zone, and you can click the points you want to include in your path. After you're satisfied with that, you'll be able to specify how many points you want along each segment of the path, and save the file. You can use that output file to create the second block you refer to in your question.&lt;/p&gt;&#xA;&lt;p&gt;There may also be other programs that can do this!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WAl6H.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WAl6H.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-08-12T23:35:01.523" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1983" PostTypeId="2" ParentId="1570" CreationDate="2020-08-13T00:57:46.313" Score="10" Body="&lt;p&gt;Always happy to hear of new use cases for Quantum Mobile!&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Disclaimer: I've maintained Quantum Mobile over the past 2-3 years&lt;/em&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I use the virtual machine to run calculations on other nodes using any scheduler?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As others have mentioned in the comments, if you want to run any simulation code on the compute nodes, it will need to be installed there as well (either inside a VM or on the bare metal).&#xA;If you install Quantum Mobile on the compute nodes as well, and you are able to ssh into the VMs on the compute nodes from the one on the head node, you may be able to configure a cluster using the SLURM scheduler that is bundled with Quantum Mobile.&lt;/p&gt;&#xA;&lt;p&gt;I need to mention, though, that this is the first time I come across the use case of using Quantum Mobile to run both the head and compute nodes of a cluster. The &lt;a href=&quot;https://github.com/marvel-nccr/quantum-mobile&quot; rel=&quot;noreferrer&quot;&gt;Quantum Mobile Desktop Edition&lt;/a&gt; aims mainly at a course/tutorial context, where it provides a standardized environment with the graphical desktop that users are familiar with.&lt;/p&gt;&#xA;&lt;p&gt;For production calculations, you may prefer to install the codes directly on your machine in order to avoid any overhead from virtualization.&#xA;We recently added the &lt;a href=&quot;https://github.com/marvel-nccr/quantum-mobile-cloud-edition/releases&quot; rel=&quot;noreferrer&quot;&gt;Quantum Mobile Cloud Edition&lt;/a&gt; that is intended for launching directly on cloud services like AWS or GCP  with no additional setup.&#xA;We should eventually also release a standalone ISO (I will ping the current maintainers); you could then flash the ISO to your nodes directly, without the need of virtualization.&lt;/p&gt;&#xA;&lt;p&gt;I would further like to mention that besides the pre-built images, you can also use the &lt;a href=&quot;https://github.com/marvel-nccr/quantum-mobile-cloud-edition&quot; rel=&quot;noreferrer&quot;&gt;ansible playbook&lt;/a&gt; to provision any bare-metal or virtual server under your control (assuming the server runs Ubuntu 16.04 or 18.04).&#xA;This is what we do in order to build the images, and it allows you to customize the setup, e.g. removing codes you don't need or adding new ones.&lt;/p&gt;&#xA;&lt;p&gt;For further, in-depth discussions concerning Quantum Mobile, please consider posting to the &lt;a href=&quot;http://www.aiida.net/mailing-list/&quot; rel=&quot;noreferrer&quot;&gt;AiiDA mailing list&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2020-08-13T01:05:13.103" LastActivityDate="2020-08-13T01:05:13.103" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="1984" PostTypeId="2" ParentId="953" CreationDate="2020-08-13T07:15:13.813" Score="6" Body="&lt;p&gt;I think there are none. If you look at e.g. the work by Dunning, the problem is that the functions appear in a semi-random order: e.g. the second D function may be energetically more important than the first F function, so you go from 1D -&amp;gt; 2D -&amp;gt; 2D1F -&amp;gt; etc, but it can also be less important, and then you would go 1D -&amp;gt; 1D1F -&amp;gt; 2D1F, etc. This is something I've seen first hand when trying to form property-optimized basis sets automatically; you can get pretty weird-looking results from such a procedure. (By 1D -&amp;gt; 2D -&amp;gt; 2D1F, I mean having one d-orbital, then two d-orbitals, then two d-orbitals and one f-orbital, in the basis set sequence).&lt;/p&gt;&#xA;&lt;p&gt;The solution of picking the functions in groups like 1D, 2D1F, 3D2F1G, etc is elegant in that you get a more or less consistent basis in any case, since you collect all contributions of the same order. Petersson's nZaP basis sets that are designed for constant error in the energy per electron across the periodic table also use a similar composition, since they're likewise designed for post-HF calculations. In contrast, Jensen's sets have a different composure since the polarization effects behave differently to the correlation effects; for the pc sets the composition is more like 1D -&amp;gt; 2D1F -&amp;gt; 4D2F1G etc.&lt;/p&gt;&#xA;&lt;p&gt;As to the part that deals with the exponents: Dunning-style sets are designed to be additive, so the exponents are optimized in steps - with the exception of the cc-pwCVXZ sets for transition metals where the exponents would overlap too much and so the exponents are relaxed. In contrast, Petersson's nZaP sets and the polarization-consistent Jensen basis sets use optimized primitives, although uses Hartree-Fock contracted orbitals and adds fresh primitives to describe the polarization and correlation effects, so it's not fully optimized at post-HF level of theory.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-08-13T16:32:22.823" LastActivityDate="2020-08-13T16:32:22.823" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1985" PostTypeId="1" AcceptedAnswerId="2207" CreationDate="2020-08-13T18:38:21.440" Score="16" ViewCount="572" Body="&lt;p&gt;I would be very grateful for some newbie-level advice from a thermodynamics guru.&lt;/p&gt;&#xA;&lt;p&gt;I ran NPT simulations on a particular system (in CP2K software) to get fluid densities for use in fluid dynamics applications.  Before the lockdown, a colleague mentioned that it might be interesting to use the results for describing mixing in the system thermodynamically (the system is made up of two endmember compositions).  I finally thought about it, but &lt;strong&gt;can't figure out if my NPT internal energy data are meaningful&lt;/strong&gt; and don't want to bother my colleague, who has been sick.  I would love advice.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I would like to know if I can simply sum my NPT ensemble-derived kinetic and potential energies to calculate internal energy&lt;/strong&gt;.  The reason I ask is that I came across a comment online where someone seemed to think the thermostat would interfere with the kinetic energy values.&lt;/p&gt;&#xA;&lt;p&gt;I can't decide if this is true.  I know that energy is not conserved for NPT simulations--that energy is either added or subtracted to maintain a constant temperature.  However, it seems like that should be fine because I want the system to be at a particular temperature.  I could run another set of simulations in a different ensemble.  But that would mean a lot of extra time and computational resources, so I want to be really certain before diving in to doing more simulations.&lt;/p&gt;&#xA;&lt;p&gt;With regard to energy not being conserved for NPT simulations, I'm wondering if it matters that my goal is to provide people with data on the thermodynamics of mixing in the system.  In other words, for the data to be useful, I need to be compare internal energies from distinct simulations run at the same pressure and temperature, but different endmember fractions (compositions)--one internal energy value by itself probably won't be useful.  I'm not sure if I'm being clear here...  The bottom line is that I can't figure out if it would be like comparing apples and oranges to compare internal energy values from different NPT simulations (and therefore cannot use my existing results to describe the thermodynamics of this system).&lt;/p&gt;&#xA;&lt;p&gt;I have searched online for information on this, but probably don't know enough to be familiar with useful search terms.  If anyone has any hints on how to think this through, I'd be very appreciative.  Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1035" LastEditorUserId="5" LastEditDate="2020-08-30T22:02:47.553" LastActivityDate="2020-09-04T16:34:03.477" Title="Is there any reason not to sum the kinetic and potential energy from an NPT simulation to get internal energy?" Tags="|molecular-dynamics|molecular-modeling|statistical-thermodynamics|thermodynamics|cp2k|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="1986" PostTypeId="2" ParentId="1956" CreationDate="2020-08-13T22:26:54.973" Score="16" Body="&lt;p&gt;&lt;strong&gt;Pseudopotentials (PPs)&lt;/strong&gt; describe the effective interaction between the valence electrons and a nuclei screened by frozen core electrons. This approximation makes DFT calculations less computationally expensive as only valence electrons are treated explicitly and the resulting valence wavefunctions no longer oscillate rapidly near the cores to ensure orthogonality with core electron wavefunctions, thus, converging with fewer plane waves.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pseudo-wavefunctions&lt;/strong&gt; which arise from PPs are constructed to agree with the true all-electron wavefunction (where all electrons are treated explicitly) beyond a cutoff &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt;. The two most common types of PPs are the norm-conserving PPs (NCPPs) and ultrasoft PPs (USPPs). NCPPs impose the restriction that the total integrated ED within &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt; has to match the all-electron electron density, whilst USPPs relax this condition, requiring fewer planewaves to describe their pseudo-wavefunctions. The ONCV pseudopotential you mention is an example of a NCPP, although it is a more ‘modern’ variant using a similar construction method to USPPs, so that it requires fewer planewaves compared to traditional NCPPs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Projector augmented waves (PAWs)&lt;/strong&gt; are a method of restoring the pseudo- to the all-electron wavefunctions and uses pseudopotentials which are linked closely to USPPs. It expands the all-electron wavefunction within &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt; of an atomic site &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; into a basis set of atomic wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\Phi_{u}^{\mathbf{R}}$&lt;/span&gt;, called partial waves. The pseudo-wavefunctions are also expanded into a basis set of pseudo-partial waves &lt;span class=&quot;math-container&quot;&gt;$\tilde{\Phi}_{u}^{\mathbf{R}}$&lt;/span&gt; which correspond to pseudised versions of the all-electron partial waves. The coefficients for the expansion of both the all-electron and pseudo-wavefunctions are the same,  &lt;span class=&quot;math-container&quot;&gt;$\langle {\tilde{p}_{u}^{\mathbf{R}}} | {\tilde{\phi}_{i}} \rangle$&lt;/span&gt;, and they are found using projector functions &lt;span class=&quot;math-container&quot;&gt;$\tilde{p}_{u}^{\mathbf{R}}$&lt;/span&gt; which are orthonormal to the pseudo-partial waves. In essence, the PAW method maps the pseudo-wavefunction to the all-electron wavefunction through a linear transformation &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; which evaluates the difference between the all-electron and pseudo-wavefunctions:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;| {\phi_{i}} \rangle=  \mathcal{T} | {\tilde{\phi}_{i}} \rangle =  | {\tilde{\phi}_{i}} \rangle + \sum_{\mathbf{R}} \sum_{u} \left ( | {\Phi}_{u} \rangle -   | {\tilde{\Phi}}_{u} \rangle \right ) \langle {\tilde{p}_{u}^{\mathbf{R}}} | {\tilde{\phi}_{i}} \rangle&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is no systematic manner for deciding which pseudopotential is ‘better’ as a pseudopotential that works well for obtaining one property may not work well for another property. In general, you would expect the PAW pseudopotential to be more accurate compared to the ultrasoft pseudopotential since the projector augmented waves should restore the pseudo-wavefunction up to the all-electron wavefunction behaviour, but this does not always guarantee that it would be more accurate than USPPs or NCPPs. I am not familiar with spin-orbit calculations for topological insulators but the only way to truly determine which pseudopotential is ‘best’ for determining a specific materials property is to benchmark the different pseudopotentials against the same property obtained from an all-electron DFT method on an example system as all of these pseudopotentials are trying approximate it.&lt;/p&gt;&#xA;" OwnerUserId="1008" LastEditorUserId="5" LastEditDate="2020-10-12T18:14:23.323" LastActivityDate="2020-10-12T18:14:23.323" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="1987" PostTypeId="1" AcceptedAnswerId="2010" CreationDate="2020-08-14T09:07:17.550" Score="10" ViewCount="1563" Body="&lt;p&gt;I want to perform &lt;code&gt;HSE06 band-structure&lt;/code&gt; calculation of a &lt;code&gt;WS2 monolayer&lt;/code&gt;which has the following POSCAR with &lt;code&gt;17Ang&lt;/code&gt; vacuum:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; W2S4                                   &#xA;   1.00000000000000     &#xA;     3.1912863255000001    0.0000000000000000    0.0000000000000000&#xA;    -1.5956425563000001    2.7637348281000000    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   20.1269199999999984&#xA;   W    S &#xA;     1     2&#xA;Direct&#xA;  0.6666670084824631  0.3333329922369330  0.5000000000000000&#xA;  0.3333330949386806  0.6666670699615054  0.4218851941843354&#xA;  0.3333330949386806  0.6666670699615054  0.5781148058156645&#xA; &#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;How I can make a good VASP input files for HSE06 bandstructure calculation?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-03-31T13:29:41.400" Title="How to make a good HSE06 bandstructure for TMDC monolayer material (e.g.: WS2) in terms of VASP calculation INPUTS?" Tags="|density-functional-theory|vasp|band-structure|hse06|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1988" PostTypeId="1" AcceptedAnswerId="2219" CreationDate="2020-08-14T09:12:03.247" Score="25" ViewCount="7515" Body="&lt;p&gt;I am currently using &lt;a href=&quot;http://www.p4vasp.at/#/&quot; rel=&quot;noreferrer&quot;&gt;p4vasp&lt;/a&gt; for drawing DOS and band-structure plots, but it is not much handy in modifying the OUTPUTS. Could you please suggest any other good software or tools for that?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="88" LastEditDate="2020-08-14T15:06:23.030" LastActivityDate="2023-09-25T07:32:24.357" Title="What are some good band-structure/DOS plotting tools/styles?" Tags="|vasp|band-structure|quantum-espresso|dos|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1989" PostTypeId="2" ParentId="1987" CreationDate="2020-08-14T09:38:34.247" Score="7" Body="&lt;p&gt;First you need a proper self-consistent calculation. Then you will need the previous wavefunction for HSE self-consistent calculations, and set the related parameter with ALGO = All/Damped. Then calculate the band structure with ALGO = Normal. Have a look at the manual and there are plenty of example in VASPWiki I believe.&lt;/p&gt;&#xA;" OwnerUserId="1022" LastActivityDate="2020-08-14T09:38:34.247" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1990" PostTypeId="2" ParentId="1670" CreationDate="2020-08-14T11:26:36.207" Score="6" Body="&lt;p&gt;To make a start in answering this question, &lt;a href=&quot;https://doi.org/10.1038/natrevmats.2015.4&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; is a review on &amp;quot;Computational predictions of energy materials using DFT&amp;quot; by Jain et al. (2016).&lt;/p&gt;&#xA;&lt;p&gt;The bar for inclusion was:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;examples where theoretical prediction has led to the experimental discovery of a new material or exposed an important technological facet of a known material.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Table 1 contains a couple of examples from the photovoltaics field (although not the specific subfields mentioned in the question):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2007 PCDTBT, Candidate copolymer donor material with high power conversion efficiency for bulk-heterojunction organic photovoltaic solar cells&lt;/li&gt;&#xA;&lt;li&gt;2014 Organic dyes, New class of organic dyes for dye‐sensitized solar cells&lt;/li&gt;&#xA;&lt;li&gt;2013–2015, Ba2BiTaO6, p-Type transparent conducting oxide that utilizes alignment between Bi 6s and O 2p states&lt;/li&gt;&#xA;&lt;li&gt;2014, TaIrGe, Unconventional p-type half-Heusler transparent conducting oxide composed of all heavy metal atoms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;By now, publishing an update of this table would probably be worthwhile.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2020-08-14T11:34:55.313" LastActivityDate="2020-08-14T11:34:55.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1991" PostTypeId="2" ParentId="1586" CreationDate="2020-08-14T12:04:51.680" Score="6" Body="&lt;p&gt;The community-edited &lt;a href=&quot;https://github.com/tilde-lab/awesome-materials-informatics&quot; rel=&quot;nofollow noreferrer&quot;&gt;awesome materials informatics list&lt;/a&gt; has a section on &amp;quot;software frameworks&amp;quot;, which includes many of the tools mentioned in the answers here &amp;amp; more.&lt;/p&gt;&#xA;&lt;p&gt;Contributions welcome!&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2020-08-15T12:35:48.263" LastActivityDate="2020-08-15T12:35:48.263" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="1992" PostTypeId="2" ParentId="24" CreationDate="2020-08-14T13:57:41.330" Score="7" Body="&lt;p&gt;To add to the previous answer: the new lead-free halide double perovskite &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs_2InAgCl_6}$&lt;/span&gt; was discovered by first-principles and then synthesized:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;G. Volonakis et al. &lt;em&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{Cs_2InAgCl_6}$&lt;/span&gt;: A New Lead-Free Halide Double Perovskite with Direct Band Gap&lt;/em&gt;, J. Phys. Chem. Lett. &lt;strong&gt;8&lt;/strong&gt;, 772 (2017) &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpclett.6b02682&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jpclett.6b02682&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'm sure there are other such examples. In addition ab-initio calculations made many predictions on specific materials properties of existing perovskites before they were measured (more common than discovering new ones).&lt;/p&gt;&#xA;" OwnerUserId="1209" LastEditorUserId="5" LastEditDate="2020-08-14T14:49:56.767" LastActivityDate="2020-08-14T14:49:56.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1993" PostTypeId="2" ParentId="1988" CreationDate="2020-08-14T14:40:20.353" Score="24" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/383/88&quot;&gt;Here&lt;/a&gt; is an excellent answer by &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/206/andrew-rosen&quot;&gt;Andrew&lt;/a&gt; on pre/post processing tools available for VASP. I will introduce another tool I have used for plotting bandstructure and DOS.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://romerogroup.github.io/pyprocar/index.html&quot; rel=&quot;noreferrer&quot;&gt;PyProcar&lt;/a&gt; is an open-source Python library providing a set of functions that manage data from the PROCAR file obtained with VASP calculations. It supports &lt;strong&gt;VASP, Elk, Quantum ESPRESSO and ABINIT&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PyProcar is capable of performing&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;plotting plain and spin/atom/orbital projected band structures and Fermi surfaces- both in 2D and 3D&lt;/li&gt;&#xA;&lt;li&gt;Fermi velocity plots&lt;/li&gt;&#xA;&lt;li&gt;unfolding bands of a super cell&lt;/li&gt;&#xA;&lt;li&gt;comparing band structures from multiple DFT calculations&lt;/li&gt;&#xA;&lt;li&gt;plotting partial density of states&lt;/li&gt;&#xA;&lt;li&gt;generating a k-path for a given crystal structure.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here is a Bandstructure with DOS plot made using PyPROCAR&#xA;&lt;a href=&quot;https://i.stack.imgur.com/B1ax3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B1ax3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-08-14T14:48:04.823" LastActivityDate="2020-08-14T14:48:04.823" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="1994" PostTypeId="1" CreationDate="2020-08-14T21:31:19.953" Score="14" ViewCount="384" Body="&lt;p&gt;I see that for some structures that have imaginary frequencies, they mention CDW, but I could not find any reasonable explanation about the relation between them.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Does CDW cause instability in the structures?&lt;/li&gt;&#xA;&lt;li&gt;If so, how?&lt;/li&gt;&#xA;&lt;li&gt;Is it something related to the Kohn-Sham formalism at zero Kelvin? I mean isn't it existing in room temperature?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="5" LastEditDate="2020-08-14T21:49:32.073" LastActivityDate="2020-08-27T19:24:33.263" Title="What is a &quot;Charge Density Wave&quot; and how is it related to the imaginary frequencies on phonon dispersion bandstructures?" Tags="|density-functional-theory|phonons|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1995" PostTypeId="2" ParentId="551" CreationDate="2020-08-14T23:09:37.730" Score="4" Body="&lt;p&gt;Just throwing a couple of ideas out there:&lt;/p&gt;&#xA;&lt;p&gt;(i) Perform a free energy perturbation or potential of mean force calculation as available in typical classical MD setups. For known salt systems in water, this is well studied and should result in decent results (e.g., &lt;a href=&quot;http://doi.org/10.1021/jp8001614&quot; rel=&quot;nofollow noreferrer&quot;&gt;Joung and Chaetham's paper&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;(ii) Do a classical MD in explicit solvent for the solute of interest &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; carve out the solute core for QM &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; run geometry optimization and frequency calculations. Of course, do this over multiple snapshots from MD to capture averaged solvent effects&lt;/p&gt;&#xA;" OwnerUserId="664" LastEditorUserId="63" LastEditDate="2020-08-16T15:17:01.097" LastActivityDate="2020-08-16T15:17:01.097" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1997" PostTypeId="1" AcceptedAnswerId="2008" CreationDate="2020-08-15T11:25:45.390" Score="13" ViewCount="3369" Body="&lt;p&gt;I tried to create a band structure with the mBJ-LDA method using VASP. I found information that the &lt;code&gt;KPOINTS&lt;/code&gt; file should be created according to the &amp;quot;0-weight (Fake) SC procedure&amp;quot; (as for HSE).&lt;/p&gt;&#xA;&lt;p&gt;I have a problem because when I approach the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points corresponding to the second block, I get a structure in which only the points from the second block are contained, not the path between them. How can I increase the accuracy of the mapping of the band structure?&#xA;Thank you for your help, it's very important to me.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fQ6mX.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fQ6mX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1216" LastEditorUserId="1218" LastEditDate="2021-03-31T13:24:05.690" LastActivityDate="2022-04-09T04:51:47.190" Title="mBJ-LDA band structure calculation using VASP" Tags="|density-functional-theory|vasp|band-structure|k-points|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="1998" PostTypeId="2" ParentId="1586" CreationDate="2020-08-15T11:57:18.960" Score="3" Body="&lt;h1&gt;QCArchive&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://qcarchive.molssi.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MolSSI QCArchive project&lt;/a&gt; is designed for running, storing and accessing hundreds of millions of quantum chemistry calculations for individuals and groups of researchers at any scale. The project has been discussed in a recent article, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1491&quot; rel=&quot;nofollow noreferrer&quot;&gt;WIREs e1491 (2020)&lt;/a&gt;, which also has a &lt;a href=&quot;https://chemrxiv.org/articles/preprint/The_MolSSI_QCArchive_Project_An_Open-Source_Platform_to_Compute_Organize_and_Share_Quantum_Chemistry_Data/11908356/1&quot; rel=&quot;nofollow noreferrer&quot;&gt;chemRxiv preprint&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-15T11:57:18.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="1999" PostTypeId="2" ParentId="1997" CreationDate="2020-08-15T12:12:28.930" Score="9" Body="&lt;p&gt;If you give the explicit points in the KPOINTS file in VASP for a band structure calculation, for example as required for hybrid functionals, the bands will only be calculated at the explicit &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points you list. For example, if you have a cubic cell and want the path between &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt; and X at &lt;span class=&quot;math-container&quot;&gt;$(0.5,0,0)$&lt;/span&gt;, then simply writing:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;0.0 \,\, 0.0 \,\, 0.0 \\&#xA;0.5 \,\, 0.0 \,\, 0.0&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in your KPOINTS file will calculate the bands at these two points, but not at the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in between. To get more &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points between these two points, you need to &lt;em&gt;explicitly&lt;/em&gt; include them in your list. For example, to include five points when going from &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; to X in the cubic cell you should write:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;0.0 \,\, 0.0 \,\, 0.0 \\&#xA;0.1 \,\, 0.0 \,\, 0.0 \\&#xA;0.2 \,\, 0.0 \,\, 0.0 \\&#xA;0.3 \,\, 0.0 \,\, 0.0 \\&#xA;0.4 \,\, 0.0 \,\, 0.0 \\&#xA;0.5 \,\, 0.0 \,\, 0.0&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This will calculate the bands at each of these points. For finer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point sampling, you simply need to increase the number of divisions between the path end-points.&lt;/p&gt;&#xA;&lt;p&gt;If you are not using a hybrid functional, then you can use the &amp;quot;Line-mode&amp;quot; in the KPOINTS file where you only need to specify the end points of the path and VASP automatically calculates the bands at the extra points between the end points.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-15T12:12:28.930" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2000" PostTypeId="1" CreationDate="2020-08-15T13:50:55.757" Score="7" ViewCount="1496" Body="&lt;p&gt;Which one is better in case of a phonon calculation and does DFPT also have small negative frequencies near Gamma due to the numerical noise? What are their advantages and disadvantages?&lt;/p&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="792" LastEditDate="2020-08-15T18:40:47.563" LastActivityDate="2020-08-15T18:40:47.563" Title="DFPT vs Finite Difference Method" Tags="|density-functional-theory|phonons|vibrations|" AnswerCount="1" CommentCount="1" ClosedDate="2020-08-15T21:09:08.817" ContentLicense="CC BY-SA 4.0" />
  <row Id="2001" PostTypeId="1" AcceptedAnswerId="2003" CreationDate="2020-08-15T15:52:49.957" Score="11" ViewCount="190" Body="&lt;p&gt;I want to calculate wulff construction for CuO of space group C2/c. Can any one help me with its crystallographic plane/Miller indices and their corresponding relaxed surface energy? If you can provide any related paper that will be very helpful..&lt;/p&gt;&#xA;&lt;p&gt;Note that, I know the Miller indices of CuO, but doesn't know their corresponding surface energy.&lt;/p&gt;&#xA;" OwnerUserId="1200" LastEditorUserId="5" LastEditDate="2020-08-15T18:45:21.823" LastActivityDate="2020-08-15T18:45:21.823" Title="CuO (monoclinic) crystallographic plane and their relaxed surface energy" Tags="|reference-request|crystal-structure|crystallography|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2002" PostTypeId="2" ParentId="2000" CreationDate="2020-08-15T16:43:14.483" Score="3" Body="&lt;p&gt;From my understanding, the main difference is that DFPT is theoretically more sound where the electric field perturbations enter the hamiltonian and thus is calculated self consistently in the electronic and geometric optimization. This allows for several physical properties to be extracted (dielectric tensor, polarizabilities, Born charges, etc.) besides the phonon frequencies.&lt;/p&gt;&#xA;&lt;p&gt;Computational limitations arise in DFPT to be restricted to small unit cells, while finite differences allow handling much larger unit cells.&lt;/p&gt;&#xA;&lt;p&gt;If you are a VASP user, you may recognize the tags, IBRION=5/6 for FD and LEPSILON=True for DFPT, which may tell you some more technical differences.&lt;/p&gt;&#xA;" OwnerUserId="664" LastActivityDate="2020-08-15T16:43:14.483" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2003" PostTypeId="2" ParentId="2001" CreationDate="2020-08-15T18:14:51.667" Score="6" Body="&lt;p&gt;I recommend that you calculate directly.  You can use a package like ASE to generate terminations of a given surface using the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#ase.build.surface&quot; rel=&quot;noreferrer&quot;&gt;build&lt;/a&gt; module.  For the treatment of surface energies I would refer you to this &lt;a href=&quot;https://arxiv.org/pdf/cond-mat/9610046.pdf&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.  If you find that an automated approach to surface terminations would be useful you may also want to look at &lt;a href=&quot;https://catkit.readthedocs.io/en/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;CatKit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Once you have surface energies, wulff constructions can be done using &lt;a href=&quot;https://gitlab.com/materials-modeling/wulffpack&quot; rel=&quot;noreferrer&quot;&gt;WulffPack&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As for a source for CuO surface energies, I did not find a good source in my quick search but you can probably find a couple sources for different facets.  I don't recommend you go this route though as you will have to piece together different results from different papers.  Though, to some degree this is good.  This means it will be a useful result in of itself.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-15T18:14:51.667" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="2004" PostTypeId="1" CreationDate="2020-08-15T19:39:18.047" Score="7" ViewCount="793" Body="&lt;p&gt;I have executed the SCF calculation and obtained the results. After which I used kmesh.pl to extract k-points. I was able to run wannier calculations but there was an error&#xA;Checking info from wannier.nnkp file&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Real lattice is ok&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Reciprocal lattice is ok&#xA;Something wrong!&#xA;&lt;code&gt;numk= 512 iknum= 35&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;  Error in routine pw2wannier90 (512):&#xA;  Wrong number of k-points&#xA;  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;stopping ...       &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can somebody kindly provide insights on how to obtain k-points for HSE calculations. Any help in this regard would be highly appreciated. How to make use of opengrid to extract kpoints to be used in wannier calculations. Pseudopotentials which I employ are ultrasoft ones!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1219" LastEditorUserId="5" LastEditDate="2020-11-29T01:25:51.560" LastActivityDate="2020-11-29T01:25:51.560" Title="Calculating band structure with HSE using Open_grid (Quantum ESPRESSO)" Tags="|quantum-espresso|band-structure|k-points|software-assistance|" AnswerCount="0" CommentCount="6" ClosedDate="2020-11-29T02:55:26.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="2005" PostTypeId="1" CreationDate="2020-08-15T21:14:55.960" Score="18" ViewCount="990" Body="&lt;p&gt;I see that in many papers where optimization results presented, they do not mention phonons and their force convergence criterion is 0.01 eV/A. Can you publish a result like that? And is not this tolerance too high? Could the reason for using this tolerance be because of the non-measurable effect of lower tolerances on the resulting geometry? I also saw that in the papers where phonons were presented, lower tolerances were being used. Is it a convention in the community?&lt;/p&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="35" LastEditDate="2020-08-16T11:59:42.597" LastActivityDate="2020-08-16T11:59:42.597" Title="Logic of published geometry optimization results without checking phonons" Tags="|density-functional-theory|phonons|vibrations|geometry|geometry-optimization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2006" PostTypeId="2" ParentId="2005" CreationDate="2020-08-16T00:23:47.783" Score="14" Body="&lt;p&gt;Phonon calculations tend to be very expensive to run.  That being said, for gas phase molecules it is very common and expected that frequency calculations are run to ensure the molecule is not on a saddle point.&lt;/p&gt;&#xA;&lt;p&gt;In general, you can publish anything if it makes it past peer review.  Phonon calculations are something you would do if you fear you are on the saddle point but in my experience it is much harder to optimize to a saddle point in bulk.  For this reason, I expect others feel the same and it is just not commonly performed.  If you have the computational time and power though, I don't think anyone will ever ask &amp;quot;Why would you bother?&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;It should be noted though that anytime entropy/zero point energy is mentioned that they likely have actually done a frequency calculation even if they are not referring to it explicitly.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-16T00:23:47.783" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2007" PostTypeId="1" CreationDate="2020-08-16T05:02:34.740" Score="8" ViewCount="545" Body="&lt;p&gt;I am modelling water using a TIP3P flexible system. I am using the pair, bond and angle parameters given on the &lt;a href=&quot;https://lammps.sandia.gov/doc/Howto_tip3p.html#howto-tip3p&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS webpage&lt;/a&gt;. I am trying to run an &lt;span class=&quot;math-container&quot;&gt;$NPT$&lt;/span&gt; simulation at &lt;span class=&quot;math-container&quot;&gt;$298\,K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$1 \,\mathrm{atm}$&lt;/span&gt; - so I will be using real units in my LAMMPS simulation.&lt;/p&gt;&#xA;&lt;p&gt;I have created a 30-by-30-by-30 angstrom box and I am placing my water molecules in a lattice in this box. I am imposing periodic boundary conditions on all sides of the box. I am using LJ and Coulomb interactions to model my system, but I am not sure what to use as a cut-off distance for the TIP3P simulation.&lt;/p&gt;&#xA;&lt;p&gt;I expect to see a density of 0.982 g/cc, but I am not seeing that. Also, I expect pressure to be 1 atm, but my pressure in my dump output is huge - and is also negative sometimes.&lt;/p&gt;&#xA;&lt;p&gt;What am I doing wrong? Any advice would be appreciated to debug my code.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;variable        data_name      index    sys.data &#xA;variable        settings_name  index    sys.settings&#xA;variable        nsteps         index    10000     &#xA;variable        avg_freq       index    500 &#xA;variable        coords_freq    index    2000 &#xA;variable        thermo_freq    index    500&#xA;variable        dump4avg       index    50 &#xA;variable        Tinit      index    300 &#xA;variable        T0         index    298 &#xA;variable        Tf         index    298 &#xA;variable        vseed1      index  8453 &#xA;variable        vseed2      index  8892 &#xA;&#xA;&#xA;#===========================================================&#xA;# GENERAL PROCEDURES&#xA;#===========================================================&#xA;units       real&#xA;dimension   3   &#xA;newton      on  &#xA;boundary    p p p   &#xA;atom_style  full    &#xA;#===========================================================&#xA;# FORCE FIELD DEFINITION&#xA;#===========================================================&#xA;pair_style     lj/cut/coul/cut 5 5 &#xA;bond_style     harmonic&#xA;angle_style    harmonic&#xA;dihedral_style none &#xA;kspace_style   none &#xA;improper_style none &#xA;pair_modify     mix geometric shift yes &#xA;&#xA;#===========================================================&#xA;# SETUP SIMULATIONS&#xA;#===========================================================&#xA;# READ IN COEFFICIENTS/COORDINATES/TOPOLOGY&#xA;read_data &lt;span class=&quot;math-container&quot;&gt;${data_name} #read sys.data&#xA;#include $&lt;/span&gt;{settings_name} #read sys.settings&#xA;&#xA;# SET RUN PARAMETERS&#xA;timestep    0.01        #real-units, in femtoseconds&#xA;run_style   verlet      # Velocity-Verlet integrator&#xA;&#xA;# SET OUTPUTS&#xA;thermo_style    custom step temp vol density etotal pe ke enthalpy press #lammps predefined keywords&#xA;thermo_modify   format float %14.6f #format in log file&#xA;thermo &lt;span class=&quot;math-container&quot;&gt;${thermo_freq} #store all of the above information every $&lt;/span&gt;{thermo_freq} time step. ${x} refers to the variable x&#xA;&#xA;# DECLARE RELEVANT OUTPUT VARIABLES&#xA;variable        my_step equal   step #these are LAMMPS predefined words for timestep, temperature, density, potential energy, and so on&#xA;variable        my_temp equal   temp&#xA;variable        my_rho  equal   density&#xA;variable        my_pe   equal   pe&#xA;variable        my_ke   equal   ke&#xA;variable        my_etot   equal  etotal&#xA;variable        my_ent  equal   enthalpy&#xA;variable        my_P    equal   press&#xA;variable        my_vol  equal   vol&#xA;&#xA;fix averages all ave/time &lt;span class=&quot;math-container&quot;&gt;${dump4avg} $&lt;/span&gt;(v_avg_freq/v_dump4avg) ${avg_freq} v_my_temp v_my_etot v_my_pe v_my_ke v_my_ent v_my_P file thermo.avg&#xA;&#xA;#write a file called thermo.avg, compute averages of&#xA;# CREATE COORDINATE DUMPS&#xA;&#xA;dump crds all custom ${coords_freq} coords.lammpstrj id type x y z vx vy vz&#xA;dump_modify crds sort id&#xA;&#xA;bond_coeff * 450 0.9572 #not sure why I have to do this here&#xA;angle_coeff * 55 104.52&#xA;&#xA;#===========================================================&#xA;# RUN DYNAMICS&#xA;#===========================================================&#xA;velocity all create &lt;span class=&quot;math-container&quot;&gt;${Tinit} $&lt;/span&gt;{vseed1} mom yes rot yes #zero out momentum and any rotation&#xA;fix dynamics all npt temp &lt;span class=&quot;math-container&quot;&gt;${T0} $&lt;/span&gt;{Tf} 298 iso 1.0 1.0 100.0&#xA;run             &lt;span class=&quot;math-container&quot;&gt;${nsteps}&#xA;write_data      $&lt;/span&gt;{data_name}.end pair ii&#xA;unfix dynamics&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-03-03T05:26:51.063" LastActivityDate="2021-03-03T05:26:51.063" Title="Modelling water using the TIP3P flexible system" Tags="|molecular-dynamics|lammps|software-assistance|" AnswerCount="1" CommentCount="10" ClosedDate="2020-09-18T18:25:13.453" ContentLicense="CC BY-SA 4.0" />
  <row Id="2008" PostTypeId="2" ParentId="1997" CreationDate="2020-08-16T06:09:12.247" Score="13" Body="&lt;p&gt;Here I will take &lt;a href=&quot;https://www.materialsproject.org/materials/mp-2646/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mg3Sb2 from Materials Project&lt;/a&gt; as an example to demonstrate the bandstructure calculation flow with the MBJ method.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(I) structure relaxation&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(II) PBE band calculation based on the relaxed structure&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(a) self-consistent (SCF) calculation [10_scf_cal].&lt;/li&gt;&#xA;&lt;li&gt;(b) band calculation based on converged charge density at (II-a) [11_band_cal].&lt;/li&gt;&#xA;&lt;li&gt;(c) read and plot EIGENVALUE.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vXXDa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vXXDa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(III) MBJ band calculation based on step (II).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(a) PBE SCF calculation with zero weight k-points.&lt;/p&gt;&#xA;&lt;h3&gt;HOW TO WRITE KPOINTS&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt; (1) Copy the IBZKPT at step (II-a) into KPOINTS&#xA; (2) Find all k-points from OUTCAR at step (II-b) and add to the KPOINTS with zero weight.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;INCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt; ISTART=0&#xA; ICHARG=2&#xA; ENCUT=400&#xA; EDIFF=1E-6&#xA; NELM=300&#xA; ISMEAR=-5&#xA; IALGO=38&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(b) MBJ SCF calculation with zero weight k-points.&lt;/p&gt;&#xA;&lt;h3&gt;INCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt; ### Read PBE wavefunction&#xA; ISTART=1&#xA; ICHARG=0&#xA; ENCUT=400&#xA; EDIFF=1E-6&#xA; NELM=300&#xA; ISMEAR=-5&#xA;&#xA; ###MBJ:&#xA; METAGGA=MBJ&#xA; LASPH=.TRUE.&#xA; LMAXMIX=4&#xA; GGA=CA&#xA; #CMBJ=XXX     &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(c) read and plot the EIGENVALE with zero weight k-point.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/sOTcQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sOTcQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PS: all related input files can be accessed through this link: &lt;a href=&quot;https://github.com/Kohn-X/MBJ_cal&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Kohn-X/MBJ_cal&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-18T04:45:20.763" LastActivityDate="2021-02-18T04:45:20.763" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2009" PostTypeId="2" ParentId="2005" CreationDate="2020-08-16T06:42:12.400" Score="14" Body="&lt;p&gt;In general it is &lt;em&gt;not&lt;/em&gt; justified to published the geometry of a system without performing a phonon calculation. This is where you may end up in the potential energy surface depending on which type of calculation you perform:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Geometry optimization.&lt;/strong&gt; With a geometry optimization, you may end up at a local minimum or at a saddle point of the potential energy surface. You can end up at a saddle point if you perform a geometry optimization enforcing the initial symmetry of the system (a very common strategy), because enforcing symmetry reduces the dimensionality of the potential energy surface which may lead to the removal of important directions that lower the energy further. With only a geometry optimization there is no way of distinguishing between a saddle point or a minimum, and this is why you need phonons.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Phonons.&lt;/strong&gt; With phonons, you are calculating the Hessian about a stationary point of the potential energy surface, to which you got via a geometry optimization. If all eigenvalues of the Hessian are positive (corresponding to real and positive phonon frequencies, which are the square root of the eigenvalues), you then know that you are at a local minimum. If an eigenvalue of the Hessian is negative (imaginary phonon frequency), then you are at a saddle point. You should then distort the structure along the phonon eigenvector associated with the negative eigenvalue and you will find a lower-energy structure by performing a new geometry optimization. Combining geometry optimizations and phonons in this way can ensure that you end up at a local minimum.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Structure prediction.&lt;/strong&gt; With phonons you can ensure that you are at a local minimum of the potential energy surface. However, there&#xA;is no way to ensure that you are at the &lt;em&gt;global minimum&lt;/em&gt;. In fact,&#xA;there is no general solution to the problem of locating the global&#xA;minimum of the energy surface. However, structure prediction methods have&#xA;shown to be rather good at finding them, so depending on how much&#xA;is known about your material, it may be a good idea to perform a&#xA;structure search.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Having said all this, when may it be justified to perform a geometry optimization &lt;em&gt;without&lt;/em&gt; a phonon calculation? I would say that: (i) if the material is well-characterized experimentally, and (ii) the properties you are interested in are not directly related to phonons (e.g. optical properties); then I think most people would consider it OK to assume that the experimental structure is a reasonable guess, and only perform a geometry optimization before moving on to performing the additional calculations you are really interested in that are not connected to phonons.&lt;/p&gt;&#xA;&lt;p&gt;For your questions about numerical tolerances, the guideline should always be that the quantity that you are interested in is converged to the required level. Phonons &lt;em&gt;do&lt;/em&gt; typically require relatively stringent numerical tolerances, in particular a lower energy tolerance for the SCF cycle convergence because forces are not variational.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-16T06:42:12.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2010" PostTypeId="2" ParentId="1987" CreationDate="2020-08-16T07:48:28.990" Score="12" Body="&lt;p&gt;I. self-consistent at PBE level. [1scf]&lt;/p&gt;&#xA;&lt;p&gt;II. band calculation based on previous converged charge density. [2band]&lt;/p&gt;&#xA;&lt;p&gt;III. HSE self-consistent calculation based on PBE self-consistent wavefunction. [3HSE_scf]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;===HSE06 related tags in scf cal.&#xA;&#xA; LHFCALC = .TRUE.               !select the HSE06 hybrid functional&#xA;&#xA; HFSCREEN = 0.2&#xA;&#xA; ALGO = Damped&#xA;&#xA; TIME = 0.4&#xA;&#xA;====&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;IV. HSE band calculation based on previous HSE self-consistent wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;(a) mv &lt;code&gt;IBZKPT&lt;/code&gt; &lt;code&gt;KPOINTS&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;(b) add k-points in reciprocal space from &lt;code&gt;OUTCAR&lt;/code&gt; in band calculations to &lt;code&gt;KPOINTS&lt;/code&gt; with zero weights.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;===HSE06 related tags in band cal.&#xA;&#xA; LHFCALC = .TRUE.               !select the HSE06 hybrid functional&#xA;&#xA; HFSCREEN = 0.2&#xA;&#xA; ALGO = Normal&#xA;&#xA; TIME = 0.4&#xA;&#xA;====&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;V. Plot band with &lt;code&gt;EIGENVAL&lt;/code&gt; by excluding k-points with nonzero weight.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-31T13:29:41.400" LastActivityDate="2021-03-31T13:29:41.400" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2011" PostTypeId="1" AcceptedAnswerId="2013" CreationDate="2020-08-16T11:22:56.620" Score="11" ViewCount="258" Body="&lt;p&gt;There is a whole lot of literature behind &lt;em&gt;ab initio&lt;/em&gt; modelling of alloys with statistical site occupancies. These include VCA, SQS, CPA, supercell approach, etc. This question does not aim to compare these approaches, but it rather assumes a case where the supercell approach is used to model a new alloy using the DFT framework.&lt;/p&gt;&#xA;&lt;p&gt;Consider some alloy &lt;span class=&quot;math-container&quot;&gt;$\ce{A_{0.33}B_{0.67}C3}$&lt;/span&gt;. A supercell of size 1x1x3 (it's small, but for the sake of understanding) is generated  and the geometry optimisation is performed.&lt;/p&gt;&#xA;&lt;p&gt;Now, I have two questions.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;During the supercell generation, the space group symmetry of the original alloy can be (is probably) lowered, because the supercell may not support the same amount of symmetry operations. Therefore, how plausible is it to report the symmetry of the optimised supercell as the final relaxed symmetry of the original alloy? Are there any strategies to go back to the original unit cell from a relaxed supercell?&lt;/li&gt;&#xA;&lt;li&gt;What is the convention when reporting the optimised lattice parameters? Do you report the parameters as they are for the supercell ~(a, b, 3c), or do you take the average ~(a, b, c&lt;sub&gt;avg&lt;/sub&gt;)?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="857" LastEditorUserId="5" LastEditDate="2020-08-16T16:58:56.560" LastActivityDate="2020-08-16T21:40:16.527" Title="How would you report the lattice parameters of an alloy, modelled using a supercell" Tags="|density-functional-theory|terminology|alloys|geometry-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2012" PostTypeId="2" ParentId="1976" CreationDate="2020-08-16T13:32:47.697" Score="8" Body="&lt;p&gt;In order to generate the k-path for &lt;em&gt;&lt;strong&gt;any material&lt;/strong&gt;&lt;/em&gt;, the first thing to know is the crystal system (&lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_system&quot; rel=&quot;noreferrer&quot;&gt;a&lt;/a&gt;,&lt;a href=&quot;https://en.wikipedia.org/wiki/Bravais_lattice&quot; rel=&quot;noreferrer&quot;&gt;b&lt;/a&gt;) of it. This information can be obtained experimentally via X-ray diffraction analysis, form the crystallographic information file (CIF) or from material databases.&lt;/p&gt;&#xA;&lt;p&gt;Knowing the crystal system, then you have to look for the corresponding Brillouin zone. The Brillouin zone page from &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;noreferrer&quot;&gt;wikipedia&lt;/a&gt; is a good starting point (if you know French, you can read the &lt;a href=&quot;http://gallica.bnf.fr/ark:/12148/bpt6k31445&quot; rel=&quot;noreferrer&quot;&gt;original work&lt;/a&gt; from Léon Brillouin). The wiki page is based on the work of Stefano Curtarolo&lt;sup&gt;1&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now that you know the Brillouin zone, you need to select the high symmetry points to start building the k-path. In the reference 1, the authors already suggest a path for each system.&lt;/p&gt;&#xA;&lt;p&gt;Finally, you have to define the number of points between the high symmetry points in your k-path (the greater this number are, better the band structure graphics definition is).&lt;/p&gt;&#xA;&lt;h3&gt;A practical example: Silicon.&lt;/h3&gt;&#xA;&lt;p&gt;The crystal system of &lt;a href=&quot;https://en.wikipedia.org/wiki/Silicon&quot; rel=&quot;noreferrer&quot;&gt;silicon&lt;/a&gt; is face-centered cubic (FCC):&lt;/p&gt;&#xA;&lt;img src=&quot;https://upload.wikimedia.org/wikipedia/commons/d/d7/Cubic%2C_face-centered.png&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;From reference 1, the Brillouin zone is:&lt;/p&gt;&#xA;&lt;img src=&quot;https://ars.els-cdn.com/content/image/1-s2.0-S0927025610002697-gr2.jpg&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;The positions of the high symmetry points Γ, X, W, K, L, U are shown in the figure. In this case, the authors recommend the path Γ–X–W–K–Γ–L–U–W–L–K|U–X. In order to get a continuity in the band structure graph, it is necessary to choose the path were the symmetry points are in direct sequence.&lt;/p&gt;&#xA;&lt;p&gt;From table 3 in reference 1, we have the coordinates of each symmetry point:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{*{20}{c}}&#xA;{}&amp;amp;{x{b_1}}&amp;amp;{x{b_2}}&amp;amp;{x{b_3}}\\&#xA;\Gamma &amp;amp;0&amp;amp;0&amp;amp;0\\&#xA;K&amp;amp;{3/8}&amp;amp;{3/8}&amp;amp;{3/4}\\&#xA;L&amp;amp;{1/2}&amp;amp;{1/2}&amp;amp;{1/2}\\&#xA;U&amp;amp;{5/8}&amp;amp;{1/4}&amp;amp;{5/8}\\&#xA;W&amp;amp;{1/2}&amp;amp;{1/4}&amp;amp;{3/4}\\&#xA;X&amp;amp;{1/2}&amp;amp;0&amp;amp;{1/2}&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Lets create the k-path between the Γ and L points. The coordinate for Γ is &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt; and for L is &lt;span class=&quot;math-container&quot;&gt;$(0.5,0.5,0.5)$&lt;/span&gt;, using 6 points in between:&lt;/p&gt;&#xA;&lt;p&gt;(this calculation can be done with a manual calculator or using a spreadsheet program)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{*{20}{c}}&#xA;0&amp;amp;0&amp;amp;0&amp;amp;{(\Gamma )}\\&#xA;{0.1}&amp;amp;{0.1}&amp;amp;{0.1}&amp;amp;{}\\&#xA;{0.2}&amp;amp;{0.2}&amp;amp;{0.2}&amp;amp;{}\\&#xA;{0.3}&amp;amp;{0.3}&amp;amp;{0.3}&amp;amp;{}\\&#xA;{0.4}&amp;amp;{0.4}&amp;amp;{0.4}&amp;amp;{}\\&#xA;{0.5}&amp;amp;{0.5}&amp;amp;{0.5}&amp;amp;{(L)}&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Following these steps, you are in full control of the k-path selecting the high symmetry points to be used and the quality of the path (the number of points between the high symmetry points).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;W. Setyawan, S. Curtarolo, &lt;em&gt;High-throughput electronic band structure calculations: Challenges and tools&lt;/em&gt;. Computational Materials Science. 49 299–312 (2010) (DOI: &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2010.05.010&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.commatsci.2010.05.010&lt;/a&gt;). arXiv:&lt;a href=&quot;https://ui.adsabs.harvard.edu/link_gateway/2010arXiv1004.2974S/arxiv:1004.2974&quot; rel=&quot;noreferrer&quot;&gt;1004.2974&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-16T13:32:47.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2013" PostTypeId="2" ParentId="2011" CreationDate="2020-08-16T15:22:53.093" Score="9" Body="&lt;p&gt;By making a supercell and modifying it in some way, you are creating an entirely new structure which you hope can give you some insight by being compared to the original structure. Any of the conclusions you draw from your calculations will come from the modified supercell, rather than a version where you have converted it back into the primitive cell. Some software packages, like pymatgen, are able to describe structures with partial occupancies, but I do not think it is possible to systematically convert a relaxed supercell to a primitive cell without losing information.&lt;/p&gt;&#xA;&lt;p&gt;For this reason, it is most logical to report the geometry, symmetry and other properties of the supercell. This is what I have observed to be the convention in the literature. Reporting the raw data based on the supercell is also important to make your work as transparent and reproducible as possible.&lt;/p&gt;&#xA;&lt;p&gt;Depending on what you are trying to show, it may be possible to report properties normalized per atom. For example, instead of reporting the lattice parameters of your 1x1x3 supercell in the primitive cell by &amp;quot;averaging&amp;quot; the c lattice parameter, it might be equally effective for your application to compare the volume of the primitive and supercells per atom.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="1179" LastEditDate="2020-08-16T21:40:16.527" LastActivityDate="2020-08-16T21:40:16.527" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2014" PostTypeId="1" AcceptedAnswerId="2027" CreationDate="2020-08-16T17:34:28.800" Score="9" ViewCount="337" Body="&lt;p&gt;Spin-polarised calculations come at a computational cost and I tend to take &lt;code&gt;ISPIN = 2&lt;/code&gt; only after I'm done with a proper initial relaxation of the structure, so the k-mesh, &lt;code&gt;ENCUT&lt;/code&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; are already converged before magnetism is accounted for. Is this approach alright?&lt;/p&gt;&#xA;&lt;p&gt;Does spin-coupling affect the k-mesh (or &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;) convergence?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="88" LastEditDate="2020-08-17T02:00:10.760" LastActivityDate="2020-08-18T14:23:46.200" Title="k-points convergence for spin polarised vs non-polarised DFT calculations" Tags="|density-functional-theory|vasp|k-points|numerical-convergence|convergence-test|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2015" PostTypeId="1" AcceptedAnswerId="2068" CreationDate="2020-08-16T18:19:39.370" Score="12" ViewCount="280" Body="&lt;p&gt;An equilibrium structure would be at a local minimum but that doesn't happen with all relaxation calculations. Relaxed structures tend to have some resultant forces on ions. What amount of these forces can be accepted? Is 0.05 eV/&lt;span class=&quot;math-container&quot;&gt;$\unicode{xC5}$&lt;/span&gt; acceptable?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-08-17T20:48:03.200" LastActivityDate="2020-08-27T15:54:18.230" Title="Permissible amount of forces on ions in a relaxed structure" Tags="|density-functional-theory|ab-initio-calculations|geometry-optimization|potential-energy-surface|" AnswerCount="2" CommentCount="8" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2016" PostTypeId="1" AcceptedAnswerId="2025" CreationDate="2020-08-16T18:39:28.457" Score="11" ViewCount="782" Body="&lt;p&gt;Smearing (smearing width &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, to be precise) has always been confusing. I understand what it &lt;strong&gt;is&lt;/strong&gt; but can't pin it down when it comes to DFT calculations. Should it be converged like k-points and energy cut-off? If yes, then when - before we converge k-points and energy cut-off or after?&lt;/p&gt;&#xA;&lt;p&gt;Also, which properties does it affect in the calculation, and how?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="88" LastEditDate="2020-08-17T02:00:51.683" LastActivityDate="2020-08-19T12:38:49.467" Title="Which properties of a material calculated using density functional theory are affected by smearing?" Tags="|density-functional-theory|vasp|ab-initio-calculations|k-points|convergence-test|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2017" PostTypeId="2" ParentId="2016" CreationDate="2020-08-17T06:12:37.173" Score="5" Body="&lt;p&gt;You can make a convergence test to obtain reasonable results. Usually, for k-sampling and energy cutoff, you can take some values from experiences (of course, you can also make convergence tests).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(a) &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/ENCUT&quot; rel=&quot;nofollow noreferrer&quot;&gt;ENCUT&lt;/a&gt;=largest ENMAX on the POTCAR file &lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt; 1.5&lt;/li&gt;&#xA;&lt;li&gt;(b) &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Number_of_k_points_and_method_for_smearing&quot; rel=&quot;nofollow noreferrer&quot;&gt;KPOINTS&lt;/a&gt;: you can using &lt;a href=&quot;http://vaspkit.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASPKIT&lt;/a&gt; to generate KPOINTS when you prepare a POSCAR.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;=====================================================&lt;/p&gt;&#xA;&lt;p&gt;updated answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why we need the smearing method?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The original idea of the smearing method can refer &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.40.3616&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, this method is devoted to dealing with the numerical integration in the Brillouin zone for metals.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;One useful definition of a metal is that in metal the Brillouin zone can be divided into regions that are occupied and unoccupied by electrons. The surface in k space that separates these two regions is called the &lt;strong&gt;Fermi surface.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;From the point of view of calculating integrals in k space, this is a significant complication because the functions that are integrated change discontinuously from nonzero values to zero at the Fermi surface. &lt;strong&gt;If no special efforts are made in calculating these integrals, very large numbers of k points are needed to get well-converged results.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;After that, the smearing method has been developed to dealing with semiconductors and insulators.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to choose a suitable smearing method for your system?  (I assume you are using the VASP package and provide a &lt;strong&gt;recipe&lt;/strong&gt; to perform the calculation.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If you don't have enough information (metal/semiconductor/insulator), you can always use the Gaussian smearing method. The setting [ISMEAR=0, SIGMA=0.05] in VASP will give you a reasonable result.&lt;/li&gt;&#xA;&lt;li&gt;When you know the system is metal, you can use the MP smearing method to relax your system. [ISMEAR=1, SIGMA=0.2] (Keep the entropy term less than 1 meV per atom. )&lt;/li&gt;&#xA;&lt;li&gt;For semiconductors or insulators, use the tetrahedron method [ISMEAR=-5], if the cell is too large (or if you use only a single or two k-points) use ISMEAR=0 in combination with a small SIGMA=0.03-0.05.&lt;/li&gt;&#xA;&lt;li&gt;For the calculations of the density of states and very accurate total energy calculations (no relaxation in metals) use the tetrahedron method [ISMEAR=-5].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Should it be converged like k-points and energy cut-off?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For simple system, you can take the previous recipe to obtain resonable results.&lt;/li&gt;&#xA;&lt;li&gt;For some complex systems, you should take ISMEAR=0 and testing the value of SIGMA.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If yes, then when - before we converge k-points and energy cut-off or after?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can take a higher energy cut-off and a fine k-mesh to test the convergence of SIGMA. (&lt;span class=&quot;math-container&quot;&gt;$\dfrac{3}{2} \times $&lt;/span&gt; the maximum cut-off in POTCAR and using VASPKIT to generate KPOINTS with high accuracy.)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Also, which properties does it affect in the calculation, and how?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As Andrew Rosen said, it will affect the integral of total energy and thereby all properties derived from it. Because the pickup of SIMGA decides the convergence of numeric integral.&lt;/p&gt;&#xA;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-08-19T12:38:49.467" LastActivityDate="2020-08-19T12:38:49.467" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2018" PostTypeId="2" ParentId="1610" CreationDate="2020-08-17T07:05:00.583" Score="6" Body="&lt;p&gt;Siesta relies on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Linear_combination_of_atomic_orbitals&quot; rel=&quot;nofollow noreferrer&quot;&gt;LCAO&lt;/a&gt; method which is different from the plane wave (PW) formalism encountered in the VASP and QE codes.&lt;/p&gt;&#xA;&lt;p&gt;A noteworthy difference between the two types of methods is the &lt;em&gt;convergence of precision&lt;/em&gt;. In PW there is basically a single value (the plane-wave cutoff) that you simply increase to improve precision.&#xA;In LCAO the basis set is more important since there are length cutoff's of the orbital ranges. One can always improve precision by increasing the orbital ranges but there are still many more parameters to fine-tune. It is vital to really look into the details of improving precision for individual LCAO codes.&lt;/p&gt;&#xA;&lt;p&gt;TranSiesta is an extension for Siesta that implements the non-equilibrium Green function theory. The Green function theory relies on &lt;em&gt;self-energies&lt;/em&gt; which are basically the equivalent of a semi-infinite (but not limited to) bulk parts. This is drastically different from PW codes and other codes with full periodicity. The semi-infinite replaces a part of the Hamiltonian with the exact bulk equivalent such that one is really simulating a semi-infinite bulk electrode connected to a device. For instance if we label a Gold ABC stacking with A, and a molecule with M, and create a simulation cell comprising A-M-A.&lt;br /&gt;&#xA;In PW this would equate to simulating:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ...[A-M-A]A-M-A[A-M-A]...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;with each &lt;code&gt;[ ]&lt;/code&gt; repeated infinitely.&lt;/p&gt;&#xA;&lt;p&gt;In NEGF theory one would replace &lt;code&gt;A&lt;/code&gt; with the equivalent bulk part thus simulating something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ...[A][A]A-M-A[A][A]...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where each &lt;code&gt;[ ]&lt;/code&gt; is repeated infinitely.&lt;/p&gt;&#xA;&lt;p&gt;You'll notice the drastic change in the full system.&#xA;This puts certain constraints when performing the simulation since it is required that the &lt;em&gt;simulation cell&lt;/em&gt;'s &lt;code&gt;A&lt;/code&gt; parts are converged towards the bulk properties (i.e. same potential). Otherwise one would create an artificial interface between the simulation cell and the &lt;em&gt;exact&lt;/em&gt; bulk properties of &lt;code&gt;A&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As for transport in either method there are implementation details that make the LCAO method much easier to implement.&#xA;The fact that the basis set is local means that one can efficiently calculate the surface self-energies&lt;a href=&quot;https://doi.org/10.1088/0305-4608/15/4/009&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt;; these are the basis of &amp;quot;bulk&amp;quot; transport. The reason is that one can &lt;em&gt;easily&lt;/em&gt; partition the system into &amp;quot;electrode&amp;quot; and &amp;quot;device&amp;quot; regions. And thus efficiently attach bulk surface self-energies, see above.&lt;/p&gt;&#xA;&lt;p&gt;In PW codes this partitioning is not as simple due to the non-local basis set, see this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/393/88&quot;&gt; question&lt;/a&gt;&#xA;While in fact one &lt;em&gt;can&lt;/em&gt; implement transport calculations in PW &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.74.245404&quot; rel=&quot;nofollow noreferrer&quot;&gt;[2]&lt;/a&gt;  it seems it is more difficult and not as standardized in codes.&lt;/p&gt;&#xA;&lt;p&gt;However, before endeavouring into transport calculations it is highly recommended to really understand the basis of Siesta (LCAO) and fine-tune the calculations, then secondly understanding the requirements of the interface potential.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;M P Lopez Sancho et al 1985 J. Phys. F: Met. Phys. 15 851&lt;/li&gt;&#xA;&lt;li&gt;Garcia-Lekue, Aran, and Lin-Wang Wang. &amp;quot;Elastic quantum transport calculations for molecular nanodevices using plane waves.&amp;quot; Physical Review B 74.24 (2006): 245404.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastEditorUserId="88" LastEditDate="2020-08-18T07:49:12.660" LastActivityDate="2020-08-18T07:49:12.660" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2019" PostTypeId="2" ParentId="1749" CreationDate="2020-08-17T07:08:54.977" Score="3" Body="&lt;p&gt;I believe the plane-wave codes can utilise a form of the wave-function matching technique to calculate device modes coupled to scattering states in the bulk parts, see e.g. &lt;a href=&quot;http://dx.doi.org/10.1103/PhysRevB.74.245404&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dx.doi.org/10.1103/PhysRevB.74.245404&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2020-08-17T07:08:54.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2020" PostTypeId="2" ParentId="1748" CreationDate="2020-08-17T08:50:22.430" Score="6" Body="&lt;h3&gt;OpenMX&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.openmx-square.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenMX&lt;/a&gt; is another LCAO code (similar to SIESTA) which is implemented in C. It also implements the NEGF formalism similar to TranSiesta.&lt;/p&gt;&#xA;&lt;p&gt;It is &lt;em&gt;open source&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2020-08-19T10:00:58.513" LastActivityDate="2020-08-19T10:00:58.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2021" PostTypeId="2" ParentId="2014" CreationDate="2020-08-17T08:57:21.067" Score="2" Body="&lt;p&gt;1 Spin polarization needs to be open (&lt;code&gt;ISPIN=2&lt;/code&gt;) at structure relaxation.&lt;/p&gt;&#xA;&lt;p&gt;2 K-mesh can be generated with &lt;a href=&quot;http://vaspkit.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASPKIT&lt;/a&gt; according to your calculation accuracy.&lt;/p&gt;&#xA;&lt;p&gt;3 Spin-polarization/spin-orbit coupling has no influence on K-mesh/smearing convergence. You can test these tags with scalar calculation.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-08-17T13:40:45.513" LastActivityDate="2020-08-17T13:40:45.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2022" PostTypeId="1" AcceptedAnswerId="2023" CreationDate="2020-08-17T11:10:11.927" Score="15" ViewCount="3592" Body="&lt;p&gt;What is the best way to optimize monolayer geometry in VASP?&#xA;Should the same method be used for an n-layer (n=2,3,4,5)?&lt;/p&gt;&#xA;" OwnerUserId="1216" LastEditorUserId="5" LastEditDate="2020-08-17T13:39:07.293" LastActivityDate="2021-04-05T08:32:32.090" Title="Geometry optimization for n-layers in VASP" Tags="|vasp|geometry-optimization|geometry|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2023" PostTypeId="2" ParentId="2022" CreationDate="2020-08-17T11:54:40.663" Score="13" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What is the best way to optimize monolayer geometry in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For the geometric optimization of the monolayer in VASP, you should use the following key tags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ISIF=4             % firstly using 4 then 2    &#xA; IBRION=2     &#xA; NSW=300                 &#xA; EDIFFG=-0.005 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can search the explanation for each tag in &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/ISIF&quot; rel=&quot;noreferrer&quot;&gt;VASPWIKI&lt;/a&gt;. For completeness, I give an INCAR template for geometric optimization in VASP.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System=Monolayer&#xA;ISTART=0       !startjob: 0-new 1-cont 2-samecut&#xA;ICHARG=2       !charge: 1-file 2-atom 10-const&#xA;ENCUT=500      !energy cutoff in eV&#xA;EDIFF=1E-6     !stopping-criterion for electronic upd.&#xA;NELM=300       !nr. of electronic steps&#xA;ISMEAR=0       !part. occupancies: -5 Blochl -4-tet -1-fermi 0-gaus 0 MP&#xA;SIGMA=0.05     !broadening in eV -4-tet -1-fermi 0-gaus&#xA;IALGO=38       !algorithm: use only 8 (CG) or 48 (RMM-DIIS), default CG algorithm (IALGO=38)&#xA;&#xA;Dynamic:&#xA;ISIF=4         !2:relax ions only; 3:also relax volume and cell shape; 4:relax ions+cellshape, volume=fixed&#xA;IBRION=2       !ionic relaxation: 0-MD 1-quasi-New 2-CG&#xA;NSW=300        !number of steps for ionic upd&#xA;EDIFFG=-0.005  !stopping-criterion for ionic upd&#xA;&#xA;Output:&#xA;LCHARG=.FALSE. !don't create CHGCAR&#xA;LWAVE=.FALSE.  !don't create WAVECAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I assume that you can generate  POTCAR and KPOINTS file (see another answer) for your calculation. Note the lattice constant in POSCAR of your monolayer should take the experimental lattice constant if exists. Or you can take the other answer's strategy. After all these input files are prepared, you can perform your calculation.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Should the same method be used for an n-layer (n=2,3,4,5)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Almost you can use the previous tags. However, you should add one more tag to consider van der Waals interaction between layers, which is important to the simulation of n-layers 2D materials. There are three main strategies to consider van der Waals interaction.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Strategy A:&#xA;IVDW = 11&#xA;&#xA;#Strategy B:&#xA;LUSE_VDW = .TRUE.&#xA;GGA = MK&#xA;PARAM1 = 0.1234&#xA;PARAM2 = 1.0000&#xA;LUSE_VDW = .TRUE.&#xA;AGGAC = 0.0000&#xA;&#xA;#Strategy C:&#xA;LUSE_VDW = .TRUE.&#xA;GGA = BO&#xA;PARAM1 = 0.1833333333&#xA;PARAM2 = 0.2200000000&#xA;LUSE_VDW = .TRUE.&#xA;AGGAC = 0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For more strong interlayer interaction, you should use the &lt;a href=&quot;https://sites.google.com/site/haoweipeng/softwares&quot; rel=&quot;noreferrer&quot;&gt;scan+rvv10 method (VASP 5.4.4 or more recent version):&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;METAGGA = SCAN&#xA;LASPH = T&#xA;ADDGRID = T&#xA;LUSE_VDW = T&#xA;BPARAM = 15.7&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In addition, if you POSCAR contains lots of atoms with n-layer structure, larger than 10, you should add:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; LREAL=auto.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-04-03T14:25:04.780" LastActivityDate="2021-04-03T14:25:04.780" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2024" PostTypeId="2" ParentId="1760" CreationDate="2020-08-17T14:02:22.447" Score="5" Body="&lt;h3&gt;QuantumATK&lt;/h3&gt;&#xA;&lt;p&gt;One can use DFT plus NEGF to simulating these properties. For example, you can use&#xA;&lt;a href=&quot;https://docs.quantumatk.com/tutorials/atk_transport_calculations/atk_transport_calculations.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumATK&lt;/a&gt; to realize your simulation.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-08-18T10:39:21.317" LastActivityDate="2020-08-18T10:39:21.317" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2025" PostTypeId="2" ParentId="2016" CreationDate="2020-08-17T17:07:05.847" Score="10" Body="&lt;p&gt;In brief, it will influence the electronic energy and thereby all properties derived from that. Too small a smearing width and you might have trouble converging the self-consistent field. Too large and the extrapolation back to 0 K from the fictitious finite temperature will be less accurate. Depending on the smearing method (e.g. Gaussian smearing), you can treat it as a property you can decrease until the energy extrapolation is minimal. This is not necessarily the case for all smearing methods though. The order in which you carry out convergence tests is somewhat a matter of opinion, and you should always validate your assumptions. However, I would probably do it after determining a plane-wave kinetic energy cutoff and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid. I should also mention that the smearing width may influence the band edges and thereby the computed band gap depending on its value, so this is another property to take into consideration.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-08-17T20:08:44.597" LastActivityDate="2020-08-17T20:08:44.597" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2026" PostTypeId="2" ParentId="1760" CreationDate="2020-08-18T07:44:31.610" Score="4" Body="&lt;h3&gt;PHtrans (TBtrans)&lt;/h3&gt;&#xA;&lt;p&gt;In the latest &lt;a href=&quot;https://gitlab.com/siesta-project/siesta&quot; rel=&quot;nofollow noreferrer&quot;&gt;TBtrans&lt;/a&gt; release (4.1 and beyond) one can also do phonon-transport based on NEGF methods.&lt;/p&gt;&#xA;&lt;p&gt;Essentially the NEGF equations for phonons are largely the same (with some minor differences) and will allow one to perform transport calculations of phonons using dynamical matrices as calculated from other codes.&lt;/p&gt;&#xA;&lt;p&gt;Currently the supporting Python script &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt; can read the dynamical matrix from GULP and write to PHtrans conforming input options to do phonon-transport. We are working on extracting the DFT related dynamical matrices, but still work to do.&lt;/p&gt;&#xA;&lt;p&gt;Disclaimer: I am the author of both sisl and PHtrans&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="5" LastEditDate="2020-08-18T08:39:43.303" LastActivityDate="2020-08-18T08:39:43.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2027" PostTypeId="2" ParentId="2014" CreationDate="2020-08-18T14:23:46.200" Score="3" Body="&lt;p&gt;If you compare calculations with and without spin polarization and your system is magnetic, the orbitals that are occupied will change. Strictly speaking, this means that everything would need to be rechecked for convergence.&lt;/p&gt;&#xA;&lt;p&gt;In practice, the convergence threshold for the energy cutoff and k-points will probably be close and there’s no way to know without testing whether the spin polarized version would require more k-points or less k-points than the calculations which are not spin polarized.&lt;/p&gt;&#xA;&lt;p&gt;I would suggest that you do your convergence testing with the calculation settings you are using for your production calculations.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2020-08-18T14:23:46.200" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2028" PostTypeId="1" AcceptedAnswerId="2031" CreationDate="2020-08-18T14:50:13.980" Score="8" ViewCount="383" Body="&lt;p&gt;I have seen the terms semi-canonicalized and canonicalized used in relation to the Fock matrix, density matrices, and orbitals; however, I am unsure what these terms actually describe.&lt;/p&gt;&#xA;&lt;p&gt;For instance:&lt;/p&gt;&#xA;&lt;p&gt;In the communication: &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3503173&quot; rel=&quot;nofollow noreferrer&quot;&gt;ROHF theory made simple&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;At convergence of the iterative procedure, the orbitals resulting from&#xA;our optimization procedure are the same as the semicanonical orbitals&#xA;previously proposed in the literature.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Or in the paper: &lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.063301&quot; rel=&quot;nofollow noreferrer&quot;&gt;Canonical density matrix perturbation theory&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The canonical density matrix perturbation theory can be used to&#xA;calculate temperature-dependent response properties.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;How do the semi-canonicalized and canonicalized terms relate to the Fock matrix, density matrices, and orbitals? Is it possible to switch between them?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2020-08-18T22:50:45.467" LastActivityDate="2020-08-18T22:50:45.467" Title="Semi-canonicalisation vs canonicalisation of the Fock matrix and orbitals" Tags="|computational-chemistry|hartree-fock|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2029" PostTypeId="2" ParentId="2022" CreationDate="2020-08-18T15:23:47.267" Score="12" Body="&lt;p&gt;I highly recommend reading: &lt;a href=&quot;http://web.mit.edu/ceder/publications/2013_Wenhao_Sun_Surface_Slabs.pdf&quot; rel=&quot;noreferrer&quot;&gt;Efficient creation and convergence of surface slabs&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The following answer will assume a reasonable level of VASP knowledge (where keywords can be looked up at the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manua&quot; rel=&quot;noreferrer&quot;&gt;VASP wiki&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The best way to optimize a monolayer or surface in VASP follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;First, optimize your bulk structure. This will give you a reasonable estimation.&lt;/li&gt;&#xA;&lt;li&gt;From the optimized bulk structure, form your monolayer or surface. There are many codes that can do this for you. I recommend &lt;code&gt;pymatgen&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Introduce a vacuum layer of about 15 A, to limit interactions between periodic images.&lt;/li&gt;&#xA;&lt;li&gt;You will now want to run the same &lt;code&gt;INCAR&lt;/code&gt; file you used to optimize your bulk structure with the difference: &lt;code&gt;ISIF = 2&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;You should also change your &lt;code&gt;KPOINT&lt;/code&gt; file to &lt;code&gt;k k 1&lt;/code&gt;; where k is equal to the number of points used to optimize your bulk structure and 1 is set in the direction of the vacuum.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The ionic relaxation of your &lt;code&gt;INCAR&lt;/code&gt; file should take the form:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;IBRION = 2&#xA;NSW = 200&#xA;EDIFFG = -1E-02&#xA;ISIF = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Your &lt;code&gt;KPOINT&lt;/code&gt; file should look like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Automatic mesh&#xA;0&#xA;Gamma&#xA;  k   k   1&#xA;  0.  0.  0.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note: This is a gamma centred mesh, which is often advantageous.&#xA;If you are doing any kind of surface calculations, I also recommend the use of the revised for solids PBE (PBEsol) functional. This has been proven to give better results than PBE and other GGA functionals.&lt;/p&gt;&#xA;&lt;p&gt;If you wish to deal with magnetism, then this is a lot harder with a few pitfalls. To understand these pitfalls, I would recommend asking this as a separate question. However, the paper &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcc.8b07823&quot; rel=&quot;noreferrer&quot;&gt;'Noncollinear Relativistic DFT + U Calculations of Actinide Dioxide Surfaces'&lt;/a&gt; offers a detailed explanation.&lt;/p&gt;&#xA;" OwnerUserId="786" LastActivityDate="2020-08-18T15:23:47.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2030" PostTypeId="2" ParentId="562" CreationDate="2020-08-18T19:31:18.693" Score="4" Body="&lt;p&gt;For special quasirandom structures, the main advantage is that treating the atoms explictly allows the cell shape and ionic positions to be relaxed, capturing local atomic distortions which play a relatively large role in the electronic structure, energy and other properties. In principle, the VCA and other mean field approaches to disorder capture the same physical information as the unrelaxed SQS, and the ability to relax the SQS enables the calculated properties to be more physically realistic than the mean field approaches.&lt;/p&gt;&#xA;&lt;p&gt;The additional degrees of freedom in the supercell are also related to a potential disadvantage of using SQS to predict the properties of disordered materials. SQS can often be &lt;a href=&quot;https://doi.org/10.1038/ncomms8559&quot; rel=&quot;noreferrer&quot;&gt;mechanically unstable&lt;/a&gt; and the true energy that would be observed experimentally is often between the unrelaxed (higher energy) and relaxed (lower energy) states. When relaxing SQS, care must be taken to be sure that the symmetry of the ordered structure is preserved, otherwise the results will not be meaningful. An example can be seen in &lt;a href=&quot;https://doi.org/10.1016/j.actamat.2020.01.056&quot; rel=&quot;noreferrer&quot;&gt;Figure 3 of Skripnyak &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt;, which shows that for bcc Ti-V, unrelaxed SQS predicts the same mixing energies as the Coherent Potential Approximation (CPA), another mean field method, while the relaxed SQS predicts much lower mixing energies and the experimentally measured mixing energies are in between the unrelaxed and relaxed states.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2020-08-18T19:31:18.693" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2031" PostTypeId="2" ParentId="2028" CreationDate="2020-08-18T20:26:44.173" Score="8" Body="&lt;p&gt;For simplicity, I will stick to the restricted Hartree-Fock level of theory since the question of canonical and semi-canonical orbitals already exists there.&lt;/p&gt;&#xA;&lt;p&gt;Let's remember the SCF equations: &lt;span class=&quot;math-container&quot;&gt;${\bf F C} = {\bf SCE}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;${\bf F}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; are the Fock and overlap matrices, with &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; the orbital coefficients and &lt;span class=&quot;math-container&quot;&gt;${\bf E}$&lt;/span&gt; the corresponding orbital energies.&lt;/p&gt;&#xA;&lt;p&gt;Left-projecting the SCF equation by &lt;span class=&quot;math-container&quot;&gt;${\bf C}^{\rm T}$&lt;/span&gt; gives &lt;span class=&quot;math-container&quot;&gt;${\bf C}^{\rm T} {\bf F C} = {\bf E}$&lt;/span&gt;, since &lt;span class=&quot;math-container&quot;&gt;${\bf C}^{\rm T}{\bf SC}={\bf 1}$&lt;/span&gt; is the basis set version of the orbital orthonormality condition &lt;span class=&quot;math-container&quot;&gt;$\langle i | j \rangle = \delta_{ij}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We can identify &lt;span class=&quot;math-container&quot;&gt;${\bf C}^{\rm T} {\bf F C}$&lt;/span&gt; as the Fock matrix in the molecular orbital basis, &lt;span class=&quot;math-container&quot;&gt;${\bf F}^{\rm MO} = {\bf C}^{\rm T} {\bf F C}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;By definition, &lt;strong&gt;canonical orbitals diagonalize the Fock matrix&lt;/strong&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{F}^{\text{MO}}=\left(\begin{array}{ccc}&#xA;\epsilon_{1} &amp;amp; \cdots &amp;amp; 0\\&#xA;\vdots &amp;amp; \ddots &amp;amp; \vdots\\&#xA;0 &amp;amp; \cdots &amp;amp; \epsilon_{n}&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and typically, the first &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; orbitals are occupied.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Semicanonical orbitals only diagonalize the occupied-occupied and the virtual-virtual blocks&lt;/strong&gt;, while the occupied-virtual and virtual-occupied blocks may be nonzero:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{F}^{\text{MO}}=\left(\begin{array}{cc}&#xA;\boldsymbol{\epsilon}_{o} &amp;amp; \boldsymbol{\Delta}_{ov}\\&#xA;\boldsymbol{\Delta}_{vo} &amp;amp; \boldsymbol{\epsilon}_{v}&#xA;\end{array}\right)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Once you have defined the orbitals via the Fock matrices, you can build density matrices.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;It is in general not possible to switch&lt;/strong&gt; between the canonical and the semicanonical forms, since the transformation to canonize semicanonical orbitals may change the orbitals in a way that is not allowed by the theory.&lt;/p&gt;&#xA;&lt;p&gt;For instance, semicanonical orbitals are used in several self-consistent field convergence algorithms in order to precondition the descent direction. Semicanonization does not affect the energy of the wave function at the SCF level of theory, meaning you can diagonalize the Fock matrix in the occupied and virtual blocks; then, you have a pretty good estimate for the diagonal Hessian as &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{a}-\epsilon_{i}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\epsilon_a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt; denote virtual and occupied orbital diagonal values.&lt;/p&gt;&#xA;&lt;p&gt;The semicanonical and canonical orbitals are only the same in SCF when the orbitals satisfy the SCF equations, i.e. the occupied-virtual gradients vanish, &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\Delta}_{ov}={\bf 0}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PS. the second paper you linked talks about &amp;quot;canonical (NVT) free-energy ensembles&amp;quot; which is a thermodynamical concept which should not be confused with the present context of orbitals.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-08-18T20:34:45.100" LastActivityDate="2020-08-18T20:34:45.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2032" PostTypeId="1" AcceptedAnswerId="2033" CreationDate="2020-08-19T00:53:48.370" Score="11" ViewCount="480" Body="&lt;p&gt;First of all, thank you for your help!&#xA;You are so helpful every time.&lt;/p&gt;&#xA;&lt;p&gt;I would like to calculate the influence of the structural defects on the electronic structure in the HfS2 monolayer. With VESTA software, I created a supercell in which I created a defect.&#xA;What is important for this type of calculation?&#xA;How large a supercell guarantees that I have no interactions between individual defects?&#xA;What traps can I fall into?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7Nmrm.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7Nmrm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1216" LastActivityDate="2021-02-17T10:52:25.840" Title="How to start with structural defects in monolayer?" Tags="|density-functional-theory|vasp|band-structure|condensed-matter|defects|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2033" PostTypeId="2" ParentId="2032" CreationDate="2020-08-19T06:48:34.200" Score="11" Body="&lt;p&gt;First of all, I assume that you are taking VASP to perform your calculation.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, I assume that your structural defect is taking a Hf atom from your structure. (You can deal with substitutional doping with similar logic.)&lt;/p&gt;&#xA;&lt;p&gt;Thirdly, for the HfS2 monolayer, there are two phases, namely T-phase and H-phase. The T-phase monolayer was fabricated in the experiment, however, the phonon spectrum indicates that the H-phase monolayer is thermally unstable. So I assume that you are considering the defects problem in the T-phase HfS2 monolayer.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is important for this type of calculation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;When the T-phase is doping, you should take the spin-orbit coupling into account due to the broken inversion symmetry and the existence of heavy atom Hf.&lt;/li&gt;&#xA;&lt;li&gt;To simulate HfS2 monolayer, a large vacuum (20 angstroms) should be included along the z-direction.&lt;/li&gt;&#xA;&lt;li&gt;You should relax your doped structure to find the lowest-energy configuration.&lt;/li&gt;&#xA;&lt;li&gt;Defects may induce magnetism in your system, you should make a spin-polarized calculation to verify that.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How large a supercell guarantees that I have no interactions between individual defects?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;A &lt;span class=&quot;math-container&quot;&gt;$4\times 4\times1$&lt;/span&gt; supercell is enough. You can ref &lt;a href=&quot;https://ui.adsabs.harvard.edu/abs/2018PhRvB..97t5138A/abstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, in which the author investigated the monolayer T-phase PtSe2 with substitutional doping.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What traps can I fall into?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Without building supercell.&lt;/li&gt;&#xA;&lt;li&gt;Without consideration of spin-orbit coupling.&lt;/li&gt;&#xA;&lt;li&gt;Without adding enough vacuum along the z-direction.&lt;/li&gt;&#xA;&lt;li&gt;The lattice constant is important, you should take experimental lattice constant to build your model not taking bulk lattice constant.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-17T10:52:25.840" LastActivityDate="2021-02-17T10:52:25.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2034" PostTypeId="2" ParentId="1748" CreationDate="2020-08-19T10:00:41.733" Score="6" Body="&lt;h3&gt;TranSIESTA (SIESTA)&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;TranSIESTA&lt;/a&gt; is an LCAO code (similar to OpenMX) which is implemented in fortran. The NEGF methods here allows N&amp;gt;=1 -terminal calculations as well as real space self-energies (for single device/defect calculations).&lt;/p&gt;&#xA;&lt;p&gt;It is &lt;em&gt;open source&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="88" LastEditDate="2020-10-06T03:21:14.527" LastActivityDate="2020-10-06T03:21:14.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2035" PostTypeId="2" ParentId="1748" CreationDate="2020-08-19T11:35:22.780" Score="5" Body="&lt;p&gt;I provide more information about the tools for quantum transport.&lt;/p&gt;&#xA;&lt;h2&gt;KITE&lt;/h2&gt;&#xA;&lt;p&gt;KITE is an open-source Python/C++ software suite for real-space tight-binding (TB) simulations of electronic structure and bulk quantum transport properties of disordered systems scalable to multi-billions of atomic orbitals.&lt;/p&gt;&#xA;&lt;h2&gt;Kwant&lt;/h2&gt;&#xA;&lt;p&gt;Kwant is a free (open source), powerful, and easy to use Python package for numerical calculations on tight-binding models with a strong focus on quantum transport.&lt;/p&gt;&#xA;&lt;h2&gt;Questaal&lt;/h2&gt;&#xA;&lt;p&gt;Questaal is a suite of electronic structure programs. The LMTO-CPA-NEGF module of Questaal can perform the simulation of quantum transport with disorder.&lt;/p&gt;&#xA;&lt;h2&gt;EMTO:&lt;/h2&gt;&#xA;&lt;p&gt;EMTO-CPA is an all-electron density functional theory code based on the Exact Muffin-Tin Orbitals formalism, which can deal with quantum transport problem with the consideration of disorder.&lt;/p&gt;&#xA;&lt;h2&gt;QUANTUM ESPRESSO (QE)&lt;/h2&gt;&#xA;&lt;p&gt;QE is open-source software, which can also do &lt;strong&gt;Quantum transport&lt;/strong&gt; calculation.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-08-19T15:25:03.857" LastActivityDate="2020-08-19T15:25:03.857" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2036" PostTypeId="1" AcceptedAnswerId="2037" CreationDate="2020-08-19T12:23:01.430" Score="12" ViewCount="1185" Body="&lt;p&gt;Suppose I have a system with a property that is highly dependent on the density of k-points, namely the dielectric function. Using a small supercell, say with 4 atoms, I've reached the maximum allowed sampling of Quantum ESPRESSO (34x34x34), and I am not confident that I've achieved the convergence. To go further I should change the source code and recompile the program, however, this is not the case by the moment. If a make a supercell with twice the volume of the former, using the same k-sampling (the maximum one, for instance) ensures a denser mesh. Is this procedure a good workaround to increase the sampling, since I still have a manageable structure and the runtime is acceptable?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="389" LastEditDate="2020-08-19T14:46:19.173" LastActivityDate="2020-08-19T16:03:35.430" Title="Increasing supercell size to increase K-points sampling" Tags="|quantum-espresso|k-points|convergence-test|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2037" PostTypeId="2" ParentId="2036" CreationDate="2020-08-19T16:03:35.430" Score="12" Body="&lt;p&gt;&lt;strong&gt;Short answer:&lt;/strong&gt; Yes, doubling the volume of the simulation cell you will be able to effectively sample a finer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid to calculate the dielectric function. However, the calculation will be more expensive than simply increasing the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points directly in the primitive cell calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Longer answer:&lt;/strong&gt; In reciprocal space, the volume of the Brillouin zone is divided by two when you double the real space supercell volume. This means that, if you keep the same density of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points you had for your original cell, then the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in the new BZ will only be half of the number you had in the original BZ. However, the states in the original BZ corresponding to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points that are now left outside the BZ of the supercell will be folded into the new BZ, such that the total number of states per &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point will be twice as many as you originally had, so that overall you have the exact same level of sampling. What you are proposing to do is to increase the density of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points by sampling the same number of points in the new smaller BZ compared to the original larger BZ. In this way, you are effectively increasing your &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point sampling.&lt;/p&gt;&#xA;&lt;p&gt;This strategy should work OK for quantities that depend on a BZ integration, such as the calculation of the total energy or of the dielectric function. However, for quantities for which you are interested in the location of states in the original BZ (for example to locate the band gap extrema of an insulator), then band folding will complicate the analysis significantly.&lt;/p&gt;&#xA;&lt;p&gt;A final point: although this strategy will work, I would highly recommend that you do modify Quantum Espresso to increase the hard-coded limit on the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points so that you can do the calculation with a primitive cell. With this strategy the computational cost should be smaller.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-19T16:03:35.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2038" PostTypeId="1" CreationDate="2020-08-19T19:00:08.220" Score="7" ViewCount="101" Body="&lt;p&gt;Let's consider a fictitious &lt;code&gt;AB&lt;/code&gt; type binary alloy. &lt;code&gt;AB&lt;/code&gt; is known to exist in a &lt;code&gt;B2&lt;/code&gt; type ordered structure. We want to compare the DoS (density of states) between this structure for &lt;code&gt;AB&lt;/code&gt; and a completely disordered structure. On disordering, &lt;code&gt;AB&lt;/code&gt; would become a &lt;code&gt;BCC&lt;/code&gt; type random solid solution.&lt;/p&gt;&#xA;&lt;p&gt;Now, what are the inputs for a DFT code that we must consider carefully? Should the k-mesh spacing, plane wave energy cut-off, and smearing width (&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;) be the same for both to be able to compare them or should we converge these for each of them individually?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-08-19T20:11:30.797" LastActivityDate="2020-08-20T08:05:07.060" Title="Input constraints while comparing different DFT calculated properties for the same material but different atomic arrangement" Tags="|density-functional-theory|vasp|k-points|convergence-test|numerical-convergence|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2039" PostTypeId="1" AcceptedAnswerId="2040" CreationDate="2020-08-20T03:36:19.073" Score="11" ViewCount="1973" Body="&lt;p&gt;I have a system that has 1 k-point, 54 atoms, &lt;code&gt;NBANDS=152&lt;/code&gt;, and &lt;code&gt;NGZ=80&lt;/code&gt;. I'm running an AIMD simulation on VASP version 5.4.4&lt;/p&gt;&#xA;&lt;p&gt;The supercomputer has 32 cores/node. It's a LINUX cluster linked by Infiniband, modern multicore machine. I was wondering what would be the best way to select parameters and request resources to get an efficient and fast calculation. Here are some scenarios I've considered. I'm curious what would be the &amp;quot;best&amp;quot; method (in terms of efficiency and speed).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Based on what I read &lt;a href=&quot;https://www.nsc.liu.se/%7Epla/blog/2015/01/12/vasp-how-many-cores/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I should request something like 19 bands (152/8). Maybe set NBANDS=160 to request an even 20 cores.&lt;/li&gt;&#xA;&lt;li&gt;Would I then set NCORE=20 in my INCAR file and request 20 cores on 1 node?&lt;/li&gt;&#xA;&lt;li&gt;Or would it be better to set NCORE = 10. And then request something like 2 nodes and 10 cores per node? or would that create too much communication overhead and slow down the simulation?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;If I decide to use # of cores = # of atoms = 54&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Would I set NCORE=32, and then request 54 cores over 2 nodes (32 on 1 node + 22 on the second)? Or 9 cores/node and 6 nodes?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Can't I just request the whole node? 1 node, 32 cores&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;so then set NCORE=32 and I just request the whole node. However the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NCORE&quot; rel=&quot;noreferrer&quot;&gt;VASP manual&lt;/a&gt; suggests against this because that would make NPAR=1&lt;/li&gt;&#xA;&lt;li&gt;this confuses me a bit because I would assume 32 cores on one node would be more efficient than having cores across several nodes communicating with each other&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2020-08-20T03:40:45.553" LastActivityDate="2020-08-21T03:50:20.327" Title="Parallelization in VASP" Tags="|vasp|high-performance-computing|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2040" PostTypeId="2" ParentId="2039" CreationDate="2020-08-20T04:04:47.820" Score="13" Body="&lt;p&gt;As someone that has done a lot of benchmarking for VASP,  I would suggest you try the experimental approach.  I do believe VASP will add additional bands for you if need be for parallelization, so I would not worry about that personally.  The layout of the node physically (32 cores on 1 processor vs 16 cores on 2 processors vs special AMD processor layouts on a single CPU) can differ significantly from cluster to cluster you cannot know what is optimal without trying.&lt;/p&gt;&#xA;&lt;p&gt;Since you are running MD simulations it seems, I think it is well worth it to benchmark each system before you run a long simulation.  Minor changes don't require you to rebenchmark but if you go from 50 to 150 to 300 atoms, the ideal may change.  Run a series of quick calculations with the entire range of NCORE that seems reasonable.  Use the best result.  I tend to check every factor of the largest node.&lt;/p&gt;&#xA;&lt;p&gt;For 32 cores, I would check NCORE=(1, 2, 4, 8, 16, 32).  I would time it against 10 or so geometric steps.  This may seem like a waste of time, but it may end up saving large amounts of time in the future.&lt;/p&gt;&#xA;&lt;p&gt;I would almost always suggest requesting entire nodes unless you have a good reason to not do so.  You may eventually see a KPAR option as well while looking around, I have heard mixed opinions.  I have personally never got a better result with kpoint parallelization than without it.  It may make a memory difference though.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-20T04:04:47.820" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2041" PostTypeId="2" ParentId="2038" CreationDate="2020-08-20T07:52:13.933" Score="6" Body="&lt;p&gt;The best strategy when performing convergence tests is to directly converge the quantity you are interested in. This &amp;quot;quantity&amp;quot; can be a straight-forward physical property, like the band gap of a material, or a &lt;em&gt;composite&lt;/em&gt; (for lack of a better word) property. In your case, you are interested in comparing the electronic density of states (DOS) between two compounds, so my suggestion would be to build a relevant composite property.&lt;/p&gt;&#xA;&lt;p&gt;Here is a naïve proposal for your case. Let &lt;span class=&quot;math-container&quot;&gt;$g_A(E)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g_B(E)$&lt;/span&gt; be the densities of states of the two compounds you are comparing, and let &lt;span class=&quot;math-container&quot;&gt;$(E_1,E_2)$&lt;/span&gt; be the energy range over which you want to compare the densities of states. Then I can define a quantity &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; that measures the difference between the two densities of states, for example as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta=\frac{1}{E_2-E_1}\int_{E_1}^{E_2} \sqrt{\left[g_A(E)-g_B(E)\right]^2} dE.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My suggestion would be to converge &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; with respect to the relevant parameters. If you individually converge &lt;span class=&quot;math-container&quot;&gt;$g_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g_B$&lt;/span&gt;, then their difference should also be converged, but converging &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; instead may provide important computational gains because there may be some &amp;quot;cancellation of errors&amp;quot; in the convergence of the &lt;em&gt;difference&lt;/em&gt; between &lt;span class=&quot;math-container&quot;&gt;$g_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g_B$&lt;/span&gt;, which is what you are really interested in.&lt;/p&gt;&#xA;&lt;p&gt;As to the parameters you should converge, I agree that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points (both for the self-consistent and non-self-consistent parts of the calculation), energy cut-off, and smearing width are important. Depending on what you want to achieve with the comparison, it may also be important to play around with the limits &lt;span class=&quot;math-container&quot;&gt;$(E_1,E_2)$&lt;/span&gt; in an expression like the one for &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; above.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-20T07:52:13.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2042" PostTypeId="2" ParentId="2038" CreationDate="2020-08-20T08:05:07.060" Score="4" Body="&lt;p&gt;To compare calculations, it’s best to have all the calculation parameters possible the same, including the k-mesh spacing, plane wave energy cut-off, and the Brillouin zone integration method (with the same smearing width, if applicable). The settings must also be sufficiently converged for each case.&lt;/p&gt;&#xA;&lt;p&gt;In your example, if the B2 case a tighter k-point spacing while the disordered case required a higher energy cutoff to be converged, then the calculations to be compared should use both the tighter k-point spacing and the higher energy cutoff.&lt;/p&gt;&#xA;&lt;p&gt;It’s also key to highlight that the calculations should have the same k-point &lt;em&gt;spacing&lt;/em&gt;, i.e. no matter the crystal size, the density of points in the volume is the same. This pattern should be applied to any setting related to an extrinsic property, such as the k-point sampling, since cell volume is an extrinsic property.&lt;/p&gt;&#xA;&lt;p&gt;Some settings like smearing width are complicated, because there’s not necessarily a &lt;em&gt;converged&lt;/em&gt; value in terms of correctness. Too small or too large can cause issues, as discussed in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2025/1179&quot;&gt;this answer&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2020-08-20T08:05:07.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2043" PostTypeId="1" CreationDate="2020-08-20T08:42:19.270" Score="12" ViewCount="1075" Body="&lt;p&gt;In molecular dynamics simulations of proteins, the radius of gyration is often used to assess the compactness of a protein.&#xA;When comparing two protein radius of gyration, what difference can be considered significant 1 Angstrom, 5 Angstroms, 10 angstroms? Significant meaning: yes it is definitely more compact or no it is definitely not more compact. I have been searching through but can't find any reference related to that.&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2020-09-26T20:51:09.810" LastActivityDate="2020-11-10T03:13:45.700" Title="How much of a difference in a protein's radius of gyration can be considered significant?" Tags="|molecular-dynamics|proteins|biomaterials|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2044" PostTypeId="1" CreationDate="2020-08-20T09:45:33.023" Score="11" ViewCount="839" Body="&lt;p&gt;I read a paper from Science (DOI &lt;a href=&quot;https://doi.org/10.1126/science.aah5975&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1126/science.aah5975&lt;/a&gt;), “Density functional theory is straying from the path toward the exact functional”. They were trying to make a point that accurate energy prediction does not always imply accurate electron density. In this study, they used the CCSD as a reference method for electron density predictions.&lt;/p&gt;&#xA;&lt;p&gt;But CCSD’s total energy prediction is much less accurate than DFT’s (DOI &lt;a href=&quot;https://doi.org/10.3390/molecules25153485&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.3390/molecules25153485&lt;/a&gt;), so how can we be sure that CCSD’s electron density would be so accurate that it can be safely used as a reference?&lt;/p&gt;&#xA;&lt;p&gt;Is there another way to address the accuracy of the calculated electron density?&lt;/p&gt;&#xA;" OwnerUserId="888" LastActivityDate="2020-08-20T10:27:39.767" Title="Which method gives the most accurate electron density, and how can it be verified experimentally?" Tags="|density-functional-theory|quantum-mechanics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2045" PostTypeId="2" ParentId="2044" CreationDate="2020-08-20T10:27:39.767" Score="15" Body="&lt;p&gt;The coupled-cluster hierarchy is a systematic approach to the exact many-body solution to the electronic Schrödinger equation, which yields size extensive energies and often converges extremely rapidly with respect to the maximum rank of excitations included in the model.&lt;/p&gt;&#xA;&lt;p&gt;CCSD(T) is widely known as the &amp;quot;golden standard of quantum chemistry&amp;quot;, since it has been shown to yield excellent agreement for e.g. atomization energies of small molecules, see Fig 2 in &lt;a href=&quot;https://doi.org/10.1063/1.481544&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 112, 9229 (2000)&lt;/a&gt; for a powerful demonstration. I would like to note here that the reference energies the Chachiyo paper is using &lt;strong&gt;come from nothing but CCSD(T) calculations&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, whenever you have a molecule that is not dominated by weak i.e. dynamical correlation effects, you need to also include higher-order excitations; see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.5036795&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 149, 034102 (2018)&lt;/a&gt; for a recent benchmark study.&lt;/p&gt;&#xA;&lt;p&gt;The accuracy of the CCSD energy and density can be verified by going up the ladder of CC theory, to CCSD(T), CCSDT, CCSDT(Q), CCSDTQ, CCSDTQ(5), CCSDTQ5, etc. However, every rung of the ladder means a significant increase in the computational cost. If your molecule is well-behaved, then the density should converge rather rapidly when you go up the ladder. It's pretty easy to find counterexamples, too, see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.4996044&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 147, 154105 (2017)&lt;/a&gt;; however, by the point where you have included all possible excitations, i.e. full coupled-cluster theory, then you have reached exactness i.e. full agreement with the full configuration interaction model.&lt;/p&gt;&#xA;&lt;p&gt;One should note here that the density can be expected to converge less rapidly than the energy: if the wave function is variational, the error in the energy is second-order in the wave function, while the error in the density is only first-order in the wave function! Still, by the point when you get to full coupled-cluster, your density is exact.&lt;/p&gt;&#xA;&lt;p&gt;It's also important to note that whenever one is discussing the post-HF level of theory like coupled-cluster, the one-electron basis set is hugely important. For instance, while coupled-cluster calculations yield worse energies than density functional approximation in small basis sets, &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.5b00081&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 11, 2036 (2015)&lt;/a&gt;, the disagreements between coupled-cluster theory and experiment goes away when you are careful about what you are doing, see e.g. &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.6b00970&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 13, 1044 (2017)&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.6b00971&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 13, 1057 (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As a final point, agreement with experiment is not always simple: experiments often have several sources of error, which may not be obvious.  In fact, there are several examples of cases where &lt;strong&gt;calculations have shown errors in the experiments&lt;/strong&gt;, see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.2911179&quot; rel=&quot;noreferrer&quot;&gt;Physics Today 61, 4, 58 (2008)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-20T10:27:39.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2046" PostTypeId="1" AcceptedAnswerId="2047" CreationDate="2020-08-20T12:31:54.690" Score="9" ViewCount="380" Body="&lt;p&gt;I have been performing CISD calculations with PySCF and I have a query surrounding the occupation of the orbitals. Here, the occupancies are calculated from the eigenvalues of the 1-electron restricted density matrix.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Taking the hydrogen fluoride molecule as an example, this is how the calculation is set up:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from numpy import linalg as LA&#xA;from pyscf import gto, scf, lib, ci&#xA;lib.num_threads(1)&#xA;&#xA;geometry = '''&#xA;      H       0.0     0.0     0.0&#xA;      F       0.0     0.0     1.1&#xA;'''&#xA;molecule = gto.Mole()&#xA;molecule.atom = geometry&#xA;molecule.basis = '3-21g'&#xA;molecule.build()&#xA;&#xA;occupied_space = [occ for occ in range(int(molecule.nelectron * .5))]&#xA;print(occupied_space)&#xA;&#xA;mf = scf.RHF(molecule)&#xA;mf.scf()&#xA;&#xA;my_ci = ci.CISD(mf=mf,&#xA;                frozen=None,&#xA;                mo_coeff=None,&#xA;                mo_occ=None)&#xA;my_ci.kernel()&#xA;rdm1 = my_ci.make_rdm1()&#xA;&#xA;evals = LA.eigvalsh(rdm1)[::-1]&#xA;print(evals)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When the CISD argument &lt;code&gt;frozen = None&lt;/code&gt; is set, the following eigenvalues are obtained:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[1.99994686e+00 1.99455156e+00 1.99008540e+00 1.99008540e+00&#xA; 1.96069255e+00 3.79033668e-02 9.52687575e-03 9.52687575e-03&#xA; 5.33169546e-03 1.84641520e-03 5.03007156e-04]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This shows clear non-integer occupation of all the occupied/core orbitals.&lt;/p&gt;&#xA;&lt;p&gt;If one sets &lt;code&gt;frozen = [0, 1, 2, 3]&lt;/code&gt;; the eigenvalues/occupancies are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[2.00000000e+00 2.00000000e+00 2.00000000e+00 2.00000000e+00&#xA; 1.99475055e+00 4.28307558e-03 7.83866124e-04 1.23523177e-04&#xA; 4.09351267e-05 1.78677364e-05 1.79726837e-07]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This shows that the HOMO is allowed to relax, smearing occupation into the virtual orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The really confusing part is when &lt;code&gt;frozen = [1, 2, 3, 4]&lt;/code&gt;; which yields the following eigenvalues:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[2.00000000e+00 2.00000000e+00 2.00000000e+00 2.00000000e+00&#xA; 1.99998097e+00 7.30194999e-06 4.82147944e-06 3.45239124e-06&#xA; 3.45239124e-06 9.06692496e-12 1.69884163e-12]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, the HOMO (orbital 4, which should be frozen) has non-integer occupation, and the first unfrozen occupied orbital (orbital 0) retains complete integer occupation.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My question has two components. What is causing the occupation smearing in this CISD calculation (as this is not a DFT calculation), and why is the HOMO relaxing when &lt;code&gt;frozen = [1, 2, 3, 4]&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="786" LastActivityDate="2020-08-20T12:55:20.543" Title="PySCF: eigenvalues, non-integer occupation, CISD calculations, and frozen lists" Tags="|configuration-interaction|pyscf|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2047" PostTypeId="2" ParentId="2046" CreationDate="2020-08-20T12:55:20.543" Score="6" Body="&lt;p&gt;One should not confuse the &amp;quot;smearing&amp;quot; used to facilitate self-consistent field convergence, especially for density functional calculations in periodic systems, and the role of fractional natural orbital occupation numbers that arise naturally from the many-particle nature of the exact wave function.&lt;/p&gt;&#xA;&lt;p&gt;Natural orbitals are typically ordered in decreasing magnitude. In fact, I would bet a beer on PySCF reordering the natural orbitals so that the 2nd through 5th frozen orbital are reordered to the bottom. The occupation numbers are clearly different between the calculations, and you see that there's a significant difference in the strength of the correlation between the HOMO and the deepest core orbital: when you only correlate the HOMO, the occupation number for the lowest unoccupied natural orbital (LUNO) is &lt;span class=&quot;math-container&quot;&gt;$4.28\times10^{-3}$&lt;/span&gt;, whereas when you only correlate the F 1s orbital the LUNO is &lt;span class=&quot;math-container&quot;&gt;$7.30\times10^{-6}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-20T12:55:20.543" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2048" PostTypeId="1" CreationDate="2020-08-20T13:46:12.127" Score="11" ViewCount="312" Body="&lt;p&gt;Below is just the end of the output file, and the top of the input file. This is for the molecule FDICTF. The calculation did not run out of time. I ran a batch of 15 molecules, all with same calculation parameters, but it only worked on about half of them. FDICTF is just an example, I have a few more molecules with the same type of output files. What could be the reason for it working on some and not others? It is missing all of the spectra data that should be at the end of the file. (I am new to using DFT, sorry if this doesn't make complete sense. I just can't figure out what went wrong since it worked for some but not others.)&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;B( 53-C , 54-C ) :   1.5172 B( 53-C , 68-O ) :   0.1105 B( 53-C ,110-H ) :   0.9562 &#xA;B( 54-C , 55-C ) :   1.1493 B( 54-C , 67-C ) :   0.9971 B( 54-C , 68-O ) :  -0.1453 &#xA;B( 55-C , 56-C ) :   1.4318 B( 55-C , 61-C ) :   1.0453 B( 56-C , 57-C ) :   1.0448 &#xA;B( 56-C , 59-C ) :   1.0416 B( 57-C , 58-N ) :   3.0058 B( 59-C , 60-N ) :   2.9698 &#xA;B( 61-C , 62-C ) :   1.3770 B( 61-C , 66-C ) :   1.3228 B( 62-C , 63-C ) :   1.4188 &#xA;B( 62-C ,111-H ) :   0.9452 B( 63-C , 64-C ) :   1.3873 B( 63-C ,112-H ) :   0.9669 &#xA;B( 64-C , 65-C ) :   1.3779 B( 64-C ,113-H ) :   0.9722 B( 65-C , 66-C ) :   1.3850 &#xA;B( 65-C ,114-H ) :   0.9805 B( 66-C , 67-C ) :   0.9656 B( 66-C , 68-O ) :  -0.1478 &#xA;B( 67-C , 68-O ) :   2.1912 &#xA;&#xA;-------&#xA;TIMINGS&#xA;-------&#xA;&#xA;Total SCF time: 0 days 4 hours 36 min 24 sec &#xA;&#xA;Total time                  ....   16584.016 sec&#xA;Sum of individual times     ....   16561.618 sec  ( 99.9%)&#xA;&#xA;Fock matrix formation       ....   16251.256 sec  ( 98.0%)&#xA;  Split-RI-J                ....    1508.011 sec  (  9.3% of F)&#xA;  Chain of spheres X        ....   14201.435 sec  ( 87.4% of F)&#xA;  COS-X 1 center corr.      ....       0.000 sec  (  0.0% of F)&#xA;  XC integration            ....     535.544 sec  (  3.3% of F)&#xA;    Basis function eval.    ....     129.950 sec  ( 24.3% of XC)&#xA;    Density eval.           ....     199.951 sec  ( 37.3% of XC)&#xA;    XC-Functional eval.     ....       8.636 sec  (  1.6% of XC)&#xA;    XC-Potential eval.      ....     185.009 sec  ( 34.5% of XC)&#xA;Diagonalization             ....      28.788 sec  (  0.2%)&#xA;Density matrix formation    ....      10.079 sec  (  0.1%)&#xA;Population analysis         ....       2.300 sec  (  0.0%)&#xA;Initial guess               ....      60.384 sec  (  0.4%)&#xA;Orbital Transformation      ....       0.000 sec  (  0.0%)&#xA;Orbital Orthonormalization  ....       0.000 sec  (  0.0%)&#xA;DIIS solution               ....       8.437 sec  (  0.1%)&#xA;SOSCF solution              ....      28.080 sec  (  0.2%)&#xA;Grid generation             ....     172.294 sec  (  1.0%)&#xA;------------------------------------------------------------------------------&#xA;                        ORCA TD-DFT/TDA CALCULATION&#xA;------------------------------------------------------------------------------&#xA;&#xA;Input orbitals are from        ... FDICTF.gbw&#xA;CI-vector output               ... FDICTF.cis&#xA;Tamm-Dancoff approximation     ... operative&#xA;CIS-Integral strategy          ... AO-integrals&#xA;Integral handling              ... AO integral Direct&#xA;Max. core memory used          ... 1000 MB&#xA;Reference state                ... RHF&#xA;Generation of triplets         ... off&#xA;Follow IRoot                   ... off&#xA;Number of operators            ... 1&#xA;Orbital ranges used for CIS calculation:&#xA; Operator 0:  Orbitals  77...243  to 244...2426&#xA;XAS localization array:&#xA; Operator 0:  Orbitals  -1... -1&#xA;-------------------&#xA;XC-INTEGRATION GRID&#xA;-------------------&#xA;&#xA;General Integration Accuracy     IntAcc      ...  3.670&#xA;Radial Grid Type                 RadialGrid  ... Gauss-Chebyshev&#xA;Angular Grid (max. acc.)         AngularGrid ... Lebedev-50&#xA;Angular grid pruning method      GridPruning ... 3 (G Style)&#xA;Weight generation scheme         WeightScheme... Becke&#xA;Basis function cutoff            BFCut       ...    1.0000e-11&#xA;Integration weight cutoff        WCut        ...    1.0000e-14&#xA;Grids for H and He will be reduced by one unit&#xA;&#xA;# of grid points (after initial pruning)     ...  69146 (   0.1 sec)&#xA;# of grid points (after weights+screening)   ...  60425 (   3.5 sec)&#xA;nearest neighbour list constructed           ...    0.0 sec&#xA;Grid point re-assignment to atoms done       ...    0.0 sec&#xA;Grid point division into batches done        ...    0.0 sec&#xA;Reduced shell lists constructed in    2.7 sec&#xA;&#xA;Total number of grid points                  ...    60425&#xA;Total number of batches                      ...      997&#xA;Average number of points per batch           ...       60&#xA;Average number of grid points per atom       ...      525&#xA;Average number of shells per batch           ...   219.07 (23.13%)&#xA;Average number of basis functions per batch  ...   534.24 (22.01%)&#xA;Average number of large shells per batch     ...   129.47 (59.10%)&#xA;Average number of large basis fcns per batch ...   323.68 (60.59%)&#xA;Maximum spatial batch extension              ...  23.82, 23.85, 27.74 au&#xA;Average spatial batch extension              ...   4.01,  3.99,  4.20 au&#xA;&#xA;---------------------&#xA;COSX-INTEGRATION GRID&#xA;---------------------&#xA;&#xA;General Integration Accuracy     IntAcc      ...  2.670&#xA;Radial Grid Type                 RadialGrid  ... Gauss-Chebyshev&#xA;Angular Grid (max. acc.)         AngularGrid ... Lebedev-50&#xA;Angular grid pruning method      GridPruning ... 3 (G Style)&#xA;Weight generation scheme         WeightScheme... Becke&#xA;Basis function cutoff            BFCut       ...    1.0000e-11&#xA;Integration weight cutoff        WCut        ...    1.0000e-14&#xA;Grids for H and He will be reduced by one unit&#xA;&#xA;# of grid points (after initial pruning)     ...  39130 (   0.0 sec)&#xA;# of grid points (after weights+screening)   ...  34531 (   2.0 sec)&#xA;nearest neighbour list constructed           ...    0.0 sec&#xA;Grid point re-assignment to atoms done       ...    0.0 sec&#xA;Grid point division into batches done        ...    0.0 sec&#xA;Reduced shell lists constructed in    1.7 sec&#xA;&#xA;Total number of grid points                  ...    34531&#xA;Total number of batches                      ...      602&#xA;Average number of points per batch           ...       57&#xA;Average number of grid points per atom       ...      300&#xA;Average number of shells per batch           ...   227.19 (23.99%)&#xA;Average number of basis functions per batch  ...   555.00 (22.87%)&#xA;Average number of large shells per batch     ...   135.98 (59.85%)&#xA;Average number of large basis fcns per batch ...   340.55 (61.36%)&#xA;Maximum spatial batch extension              ...  19.59, 17.35, 18.43 au&#xA;Average spatial batch extension              ...   4.64,  4.62,  4.85 au&#xA;&#xA;&#xA;---------------&#xA;TD-DFT XC SETUP&#xA;---------------&#xA;&#xA;DFT calculation                         ... on&#xA;Name of the grid file                   ... FDICTF.grid_cis.tmp&#xA;Exchange functional (TD-DFT)            ... B88&#xA;   X-Alpha parameter    XAlpha (TD-DFT) ...  0.666667&#xA;   Becke's b parameter  XBeta (TD-DFT)  ...  0.004200&#xA;Correlation functional (TD-DFT)         ... LYP&#xA; LDA part of GGA corr.  LDAOpt (TD-DFT) ... VWN-5&#xA;Hybrid DFT                              ... on&#xA;   Exchange mixing (TD-DFT)             ...  0.200&#xA;   GGA exch. scaling (TD-DFT)           ...  0.720&#xA;   GGA corr. scaling (TD-DFT)           ...  0.810&#xA;&#xA;Building densities             ... done&#xA;Calculating rho(r) on the grid ... done&#xA;Building xc-kernel on the grid ... done&#xA;                    *** TD-DFT CALCULATION INITIALIZED ***&#xA;&#xA;&#xA;------------------------&#xA;DAVIDSON-DIAGONALIZATION&#xA;------------------------&#xA;&#xA;Dimension of the eigenvalue problem            ... 364561&#xA;Number of roots to be determined               ...     50&#xA;Maximum size of the expansion space            ...    250&#xA;Maximum number of iterations                   ...    100&#xA;Convergence tolerance for the residual         ...    2.500e-07&#xA;Convergence tolerance for the energies         ...    2.500e-07&#xA;Orthogonality tolerance                        ...    1.000e-14&#xA;Level Shift                                    ...    0.000e+00&#xA;Constructing the preconditioner                ... o.k.&#xA;Building the initial guess                     ... o.k.&#xA;Number of trial vectors determined             ...    250&#xA;&#xA;&#xA;                       ****Iteration    0****&#xA;&#xA;   Memory handling for direct AO based CIS:&#xA;   Memory per vector needed      ...   233 MB&#xA;   Memory needed                 ... 35056 MB&#xA;   Memory available              ...  1000 MB&#xA;   Number of vectors per batch   ...     4&#xA;   Number of batches             ...    38&#xA;   Time for densities:     7.164&#xA;   Time for RI-J (Direct):   243.313&#xA;   Time for K (COSX):  1566.586&#xA;   Time for XC-Integration:    32.703&#xA;   Time for Sigma-Completion:   252.782&#xA;   Time for densities:     7.118&#xA;   Time for RI-J (Direct):   240.438&#xA;   Time for K (COSX):  1580.230&#xA;   Time for XC-Integration:    32.681&#xA;   Time for Sigma-Completion:   253.632&#xA;   Time for densities:     7.136&#xA;   Time for RI-J (Direct):   244.329&#xA;   Time for K (COSX):  1603.495&#xA;   Time for XC-Integration:    33.324&#xA;   Time for Sigma-Completion:   253.471&#xA;   Time for densities:     7.130&#xA;   Time for RI-J (Direct):   244.473&#xA;   Time for K (COSX):  1601.764&#xA;   Time for XC-Integration:    33.165&#xA;   Time for Sigma-Completion:   253.394&#xA;   Time for densities:     7.127&#xA;   Time for RI-J (Direct):   243.253&#xA;   Time for K (COSX):  1597.751&#xA;   Time for XC-Integration:    33.072&#xA;   Time for Sigma-Completion:   253.515&#xA;   Time for densities:     7.156&#xA;   Time for RI-J (Direct):   243.971&#xA;   Time for K (COSX):  1590.556&#xA;   Time for XC-Integration:    32.612&#xA;   Time for Sigma-Completion:   253.133&#xA;   Time for densities:     7.137&#xA;   Time for RI-J (Direct):   242.502&#xA;   Time for K (COSX):  1588.696&#xA;   Time for XC-Integration:    32.741&#xA;   Time for Sigma-Completion:   253.630&#xA;   Time for densities:     7.144&#xA;   Time for RI-J (Direct):   242.696&#xA;   Time for K (COSX):  1595.863&#xA;   Time for XC-Integration:    32.328&#xA;   Time for Sigma-Completion:   253.632&#xA;   Time for densities:     7.153&#xA;   Time for RI-J (Direct):   247.977&#xA;   Time for K (COSX):  1608.125&#xA;   Time for XC-Integration:    33.885&#xA;   Time for Sigma-Completion:   253.473&#xA;   Time for densities:     7.150&#xA;   Time for RI-J (Direct):   241.209&#xA;   Time for K (COSX):  1592.880&#xA;   Time for XC-Integration:    32.274&#xA;   Time for Sigma-Completion:   253.328&#xA;   Time for densities:     7.113&#xA;   Time for RI-J (Direct):   239.899&#xA;   Time for K (COSX):  1571.082&#xA;   Time for XC-Integration:    32.255&#xA;   Time for Sigma-Completion:   252.393&#xA;   Time for densities:     7.103&#xA;   Time for RI-J (Direct):   243.055&#xA;   Time for K (COSX):  1583.049&#xA;   Time for XC-Integration:    32.733&#xA;   Time for Sigma-Completion:   252.484&#xA;   Time for densities:     7.126&#xA;   Time for RI-J (Direct):   240.579&#xA;   Time for K (COSX):  1562.547&#xA;   Time for XC-Integration:    31.900&#xA;   Time for Sigma-Completion:   252.464&#xA;   Time for densities:     7.130&#xA;   Time for RI-J (Direct):   241.194&#xA;   Time for K (COSX):  1567.233&#xA;   Time for XC-Integration:    32.327&#xA;   Time for Sigma-Completion:   252.550&#xA;   Time for densities:     7.153&#xA;   Time for RI-J (Direct):   247.862&#xA;   Time for K (COSX):  1585.512&#xA;   Time for XC-Integration:    32.939&#xA;   Time for Sigma-Completion:   252.636&#xA;   Time for densities:     7.156&#xA;   Time for RI-J (Direct):   249.366&#xA;   Time for K (COSX):  1591.706&#xA;   Time for XC-Integration:    33.488&#xA;   Time for Sigma-Completion:   252.471&#xA;   Time for densities:     7.151&#xA;   Time for RI-J (Direct):   246.413&#xA;   Time for K (COSX):  1541.171&#xA;   Time for XC-Integration:    31.136&#xA;   Time for Sigma-Completion:   243.965&#xA;   Time for densities:     6.951&#xA;   Time for RI-J (Direct):   244.105&#xA;   Time for K (COSX):  1510.471&#xA;   Time for XC-Integration:    30.040&#xA;   Time for Sigma-Completion:   237.790&#xA;   Time for densities:     6.758&#xA;   Time for RI-J (Direct):   237.220&#xA;   Time for K (COSX):  1492.961&#xA;   Time for XC-Integration:    29.271&#xA;   Time for Sigma-Completion:   234.147&#xA;   Time for densities:     6.759&#xA;   Time for RI-J (Direct):   235.394&#xA;   Time for K (COSX):  1442.287&#xA;   Time for XC-Integration:    26.322&#xA;   Time for Sigma-Completion:   209.837&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   215.071&#xA;   Time for K (COSX):  1423.819&#xA;   Time for XC-Integration:    25.976&#xA;   Time for Sigma-Completion:   208.485&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   216.329&#xA;   Time for K (COSX):  1429.640&#xA;   Time for XC-Integration:    26.486&#xA;   Time for Sigma-Completion:   209.741&#xA;   Time for densities:     6.257&#xA;   Time for RI-J (Direct):   214.654&#xA;   Time for K (COSX):  1417.850&#xA;   Time for XC-Integration:    26.041&#xA;   Time for Sigma-Completion:   206.205&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   216.218&#xA;   Time for K (COSX):  1426.613&#xA;   Time for XC-Integration:    26.309&#xA;   Time for Sigma-Completion:   207.979&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   214.048&#xA;   Time for K (COSX):  1418.713&#xA;   Time for XC-Integration:    25.576&#xA;   Time for Sigma-Completion:   208.764&#xA;   Time for densities:     6.255&#xA;   Time for RI-J (Direct):   218.270&#xA;   Time for K (COSX):  1432.516&#xA;   Time for XC-Integration:    26.314&#xA;   Time for Sigma-Completion:   208.865&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   214.991&#xA;   Time for K (COSX):  1423.939&#xA;   Time for XC-Integration:    25.795&#xA;   Time for Sigma-Completion:   208.027&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   219.051&#xA;   Time for K (COSX):  1442.555&#xA;   Time for XC-Integration:    26.705&#xA;   Time for Sigma-Completion:   207.003&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   215.912&#xA;   Time for K (COSX):  1428.339&#xA;   Time for XC-Integration:    26.148&#xA;   Time for Sigma-Completion:   208.215&#xA;   Time for densities:     6.256&#xA;   Time for RI-J (Direct):   212.064&#xA;   Time for K (COSX):  1409.923&#xA;   Time for XC-Integration:    25.054&#xA;   Time for Sigma-Completion:   209.891&#xA;   Time for densities:     6.256&#xA;   Time for RI-J (Direct):   215.856&#xA;   Time for K (COSX):  1429.373&#xA;   Time for XC-Integration:    25.817&#xA;   Time for Sigma-Completion:   208.836&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   214.364&#xA;   Time for K (COSX):  1418.400&#xA;   Time for XC-Integration:    25.667&#xA;   Time for Sigma-Completion:   209.146&#xA;   Time for densities:     6.256&#xA;   Time for RI-J (Direct):   214.240&#xA;   Time for K (COSX):  1417.835&#xA;   Time for XC-Integration:    25.770&#xA;   Time for Sigma-Completion:   208.430&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   218.812&#xA;   Time for K (COSX):  1441.877&#xA;   Time for XC-Integration:    26.897&#xA;   Time for Sigma-Completion:   207.258&#xA;   Time for densities:     6.255&#xA;   Time for RI-J (Direct):   214.819&#xA;   Time for K (COSX):  1417.861&#xA;   Time for XC-Integration:    25.929&#xA;   Time for Sigma-Completion:   207.159&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   218.539&#xA;   Time for K (COSX):  1437.060&#xA;   Time for XC-Integration:    26.949&#xA;   Time for Sigma-Completion:   209.076&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   215.894&#xA;   Time for K (COSX):  1429.750&#xA;   Time for XC-Integration:    25.883&#xA;   Time for Sigma-Completion:   207.482&#xA;   Time for densities:     3.127&#xA;   Time for RI-J (Direct):   121.137&#xA;   Time for K (COSX):  1381.663&#xA;   Time for XC-Integration:    11.355&#xA;   Time for Sigma-Completion:   105.765&#xA;   Size of expansion space: 150&#xA;   Lowest Energy          :     0.073703322994&#xA;   Maximum Energy change  :     0.167460922287 (vector 49)&#xA;   Maximum residual norm  :     0.005593157183&#xA;&#xA;                       ****Iteration    1****&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   227.006&#xA;   Time for K (COSX):  1416.896&#xA;   Time for XC-Integration:    29.482&#xA;   Time for Sigma-Completion:   208.594&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   227.416&#xA;   Time for K (COSX):  1420.207&#xA;   Time for XC-Integration:    29.226&#xA;   Time for Sigma-Completion:   208.928&#xA;   Time for densities:     6.253&#xA;   Time for RI-J (Direct):   225.802&#xA;   Time for K (COSX):  1419.376&#xA;   Time for XC-Integration:    28.889&#xA;   Time for Sigma-Completion:   208.621&#xA;   Time for densities:     6.254&#xA;   Time for RI-J (Direct):   225.947&#xA;   Time for K (COSX):  1421.603&#xA;   Time for XC-Integration:    28.884&#xA;   Time for Sigma-Completion:   209.100&#xA;   Time for densities:     6.252&#xA;   Time for RI-J (Direct):   226.558&#xA;   Time for K (COSX):  1423.414&#xA;   Time for XC-Integration:    29.108&#xA;   Time for Sigma-Completion:   208.065&#xA;   Time for densities:     6.252&#xA;   Time for RI-J (Direct):   226.618&#xA;   Time for K (COSX):  1427.386&#xA;   Time for XC-Integration:    29.157&#xA;   Time for Sigma-Completion:   208.610&#xA;   Time for densities:     6.257&#xA;   Time for RI-J (Direct):   226.253&#xA;   Time for K (COSX):  1442.565&#xA;   Time for XC-Integration:    30.288&#xA;   Time for Sigma-Completion:   225.916&#xA;   Time for densities:     6.338&#xA;   Time for RI-J (Direct):   235.355&#xA;   Time for K (COSX):  1448.204&#xA;   Time for XC-Integration:    30.594&#xA;   Time for Sigma-Completion:   225.645&#xA;   Time for densities:     6.472&#xA;   Time for RI-J (Direct):   234.948&#xA;   Time for K (COSX):  1443.967&#xA;   Time for XC-Integration:    29.199&#xA;   Time for Sigma-Completion:   224.636&#xA;   Time for densities:     6.312&#xA;   Time for RI-J (Direct):   231.692&#xA;   Time for K (COSX):  1439.590&#xA;   Time for XC-Integration:    30.292&#xA;   Time for Sigma-Completion:   226.137&#xA;   Time for densities:     6.366&#xA;   Time for RI-J (Direct):   230.344&#xA;   Time for K (COSX):  1522.631&#xA;   Time for XC-Integration:    35.575&#xA;   Time for Sigma-Completion:   243.854&#xA;   Time for densities:     6.992&#xA;   Time for RI-J (Direct):   255.152&#xA;   Time for K (COSX):  1506.713&#xA;   Time for XC-Integration:    30.891&#xA;   Time for Sigma-Completion:   229.144&#xA;   Time for densities:     3.142&#xA;   Time for RI-J (Direct):   131.001&#xA;   Time for K (COSX):  1419.567&#xA;   Time for XC-Integration:    14.346&#xA;   Time for Sigma-Completion:   111.968&#xA;   Size of expansion space: 200&#xA;   Lowest Energy          :     0.069860979344&#xA;   Maximum Energy change  :     0.007865057214 (vector 5)&#xA;   Maximum residual norm  :     0.000561992491&#xA;&#xA;                       ****Iteration    2****&#xA;   Time for densities:     6.366&#xA;   Time for RI-J (Direct):   235.202&#xA;   Time for K (COSX):  1438.655&#xA;   Time for XC-Integration:    31.056&#xA;   Time for Sigma-Completion:   225.029&#xA;   Time for densities:     6.306&#xA;   Time for RI-J (Direct):   233.933&#xA;   Time for K (COSX):  1439.209&#xA;   Time for XC-Integration:    30.386&#xA;   Time for Sigma-Completion:   224.084&#xA;   Time for densities:     6.319&#xA;   Time for RI-J (Direct):   232.765&#xA;   Time for K (COSX):  1435.074&#xA;   Time for XC-Integration:    30.556&#xA;   Time for Sigma-Completion:   223.672&#xA;   Time for densities:     6.328&#xA;   Time for RI-J (Direct):   233.617&#xA;   Time for K (COSX):  1442.053&#xA;   Time for XC-Integration:    30.530&#xA;   Time for Sigma-Completion:   224.874&#xA;   Time for densities:     6.418&#xA;   Time for RI-J (Direct):   234.067&#xA;   Time for K (COSX):  1440.038&#xA;   Time for XC-Integration:    30.471&#xA;   Time for Sigma-Completion:   223.441&#xA;   Time for densities:     6.283&#xA;   Time for RI-J (Direct):   232.125&#xA;   Time for K (COSX):  1446.043&#xA;   Time for XC-Integration:    30.453&#xA;   Time for Sigma-Completion:   225.328&#xA;   Time for densities:     6.349&#xA;   Time for RI-J (Direct):   232.636&#xA;   Time for K (COSX):  1633.468&#xA;   Time for XC-Integration:    37.699&#xA;   Time for Sigma-Completion:   257.350&#xA;   Time for densities:     7.270&#xA;   Time for RI-J (Direct):   267.315&#xA;   Time for K (COSX):  1662.962&#xA;   Time for XC-Integration:    38.251&#xA;   Time for Sigma-Completion:   257.217&#xA;   Time for densities:     7.271&#xA;   Time for RI-J (Direct):   270.001&#xA;   Time for K (COSX):  1676.381&#xA;   Time for XC-Integration:    38.865&#xA;   Time for Sigma-Completion:   257.181&#xA;   Time for densities:     7.273&#xA;   Time for RI-J (Direct):   267.543&#xA;   Time for K (COSX):  1670.651&#xA;   Time for XC-Integration:    38.729&#xA;   Time for Sigma-Completion:   256.997&#xA;   Time for densities:     7.268&#xA;   Time for RI-J (Direct):   267.345&#xA;   Time for K (COSX):  1668.001&#xA;   Time for XC-Integration:    38.439&#xA;   Time for Sigma-Completion:   257.138&#xA;   Time for densities:     7.284&#xA;   Time for RI-J (Direct):   268.747&#xA;   Time for K (COSX):  1665.276&#xA;   Time for XC-Integration:    38.820&#xA;   Time for Sigma-Completion:   257.013&#xA;   Time for densities:     3.650&#xA;   Time for RI-J (Direct):   154.902&#xA;   Time for K (COSX):  1663.197&#xA;   Time for XC-Integration:    19.689&#xA;   Time for Sigma-Completion:   129.440&#xA;   Size of expansion space: 250&#xA;   Lowest Energy          :     0.069710698184&#xA;   Maximum Energy change  :     0.000987274861 (vector 46)&#xA;   Maximum residual norm  :     0.000083311195&#xA;   Rebuilding the expansion space&#xA;&#xA;                       ****Iteration    3****&#xA;   Time for densities:     7.334&#xA;   Time for RI-J (Direct):   252.363&#xA;   Time for K (COSX):  1639.154&#xA;   Time for XC-Integration:    34.901&#xA;   Time for Sigma-Completion:   259.069&#xA;   Time for densities:     7.262&#xA;   Time for RI-J (Direct):   252.911&#xA;   Time for K (COSX):  1640.507&#xA;   Time for XC-Integration:    35.402&#xA;   Time for Sigma-Completion:   259.365&#xA;   Time for densities:     7.303&#xA;   Time for RI-J (Direct):   251.134&#xA;&#xA;&lt;/pre&gt;&#xA;&lt;pre&gt;&#xA;&#xA;# ORCA input file&#xA;# ../FDICTF.out&#xA;! B3LYP def2-TZVP def2/J RIJCOSX Grid4 TightSCF&#xA;%maxcore 1000&#xA;%tddft&#xA;  maxdim 5&#xA;  nroots 50&#xA;  end&#xA;* xyz 0 1&#xA;   C        0.07759        -1.52869         0.93688&#xA;   O        0.48555        -1.65927         2.06911&#xA;   C        0.37228        -0.43876        -0.01512&#xA;   C        1.12046         0.70580         0.17670&#xA;&#xA;&lt;/pre&gt;&#xA;" OwnerUserId="1233" LastEditorUserId="5" LastEditDate="2020-11-08T01:45:22.750" LastActivityDate="2020-11-08T01:45:22.750" Title="I ran TDDFT on some small molecules. For some files, the ORCA output files cut short and contain no absorption data. What could be the reason?" Tags="|density-functional-theory|td-dft|orca|software-assistance|" AnswerCount="0" CommentCount="5" ClosedDate="2020-11-13T16:12:11.783" ContentLicense="CC BY-SA 4.0" />
  <row Id="2049" PostTypeId="1" CreationDate="2020-08-20T14:22:34.350" Score="9" ViewCount="468" Body="&lt;p&gt;I have got aggregate of 4 non-protein compounds I would submit for molecular dynamics simulation. The problem is I can't find software capable to do that. Amber, GROMACS, LAMMPS, all of them require structure to be built up from the aminoacids so the topology can be read. I've seen GROMACS has x2top that should be able to generate topology from non-protein structure. However, for my system it fails. What can I do?&lt;/p&gt;&#xA;&lt;p&gt;What I need is to achieve most probable relative positions of each of four compounds belonging to the one aggregate compound.&lt;/p&gt;&#xA;&lt;p&gt;Here are .xyz coordinates of the aggregate:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;248&#xA;    Energy:    -128.8882289&#xA;N          2.94981        4.07926       -5.95549&#xA;C          1.55689        4.07222       -5.57866&#xA;H          0.95978        3.62638       -6.43298&#xA;C          0.93686        5.43505       -5.21651&#xA;C          0.87184        6.32909       -6.38603&#xA;C          1.67148        7.45272       -6.69880&#xA;N          1.24256        8.02487       -7.89049&#xA;C          0.19644        7.27018       -8.30869&#xA;N         -0.06225        6.22632       -7.42362&#xA;C          1.30522        3.12008       -4.38134&#xA;O          0.47546        2.19923       -4.49799&#xA;N          2.01969        3.35894       -3.21757&#xA;C          1.92802        2.65116       -2.01591&#xA;C          0.88945        1.74242       -1.73904&#xA;C          0.84547        1.06621       -0.51116&#xA;F         -0.18927        0.21946       -0.29679&#xA;C          1.82258        1.27431        0.49798&#xA;N          1.80287        0.69700        1.80611&#xA;N          1.39566       -0.45359        1.96381&#xA;C          1.34687       -1.02655        3.27192&#xA;C          1.52415       -2.43840        3.37979&#xA;F          1.81094       -3.17945        2.28364&#xA;C          1.42458       -3.09620        4.60909&#xA;C          1.13511       -2.37755        5.79381&#xA;N          1.02421       -3.08555        6.99322&#xA;C          1.04112       -2.55703        8.27589&#xA;O          1.18165       -1.33803        8.49824&#xA;C          0.83998       -3.56312        9.44452&#xA;H         -0.17494       -4.03912        9.27838&#xA;N          0.78281       -2.92516       10.73973&#xA;C          1.93934       -4.64304        9.37883&#xA;C          1.54272       -5.80248        8.55823&#xA;C          2.10713       -6.27545        7.34959&#xA;N          1.46038       -7.43692        6.94522&#xA;C          0.51317       -7.68025        7.88448&#xA;N          0.53075       -6.71251        8.88577&#xA;C          0.94035       -0.98628        5.70659&#xA;C          1.05359       -0.32782        4.47349&#xA;F          0.84082        1.00858        4.45349&#xA;C          2.86069        2.20697        0.20128&#xA;F          3.83578        2.45682        1.10659&#xA;C          2.91419        2.87552       -1.02517&#xA;H          3.47097        4.75474       -5.43025&#xA;H          3.04735        4.27405       -6.93267&#xA;H          1.54324        5.94078       -4.41699&#xA;H         -0.09332        5.25659       -4.80267&#xA;H          2.51022        7.85384       -6.12959&#xA;H         -0.39199        7.42945       -9.22115&#xA;H         -0.78097        5.54995       -7.49636&#xA;H          2.71437        4.07873       -3.24086&#xA;H          0.09023        1.54368       -2.47318&#xA;H          1.57350       -4.18887        4.63032&#xA;H          1.02086       -4.08511        6.91187&#xA;H          0.11162       -2.18010       10.73068&#xA;H          1.67727       -2.55447       10.99878&#xA;H          2.18617       -4.99839       10.41904&#xA;H          2.88063       -4.20359        8.95158&#xA;H          2.93228       -5.84292        6.78254&#xA;H         -0.19451       -8.51933        7.88727&#xA;H         -0.06349       -6.66413        9.67581&#xA;H          0.69461       -0.38655        6.59911&#xA;H          3.74390        3.58154       -1.20015&#xA;H        -15.18170       -5.74686       -4.99155&#xA;F         -7.02571       -5.08907       -3.98787&#xA;H          0.65534      -11.21141       -2.50902&#xA;H         -9.52391       -4.63234       -4.36237&#xA;N        -14.25254       -5.57136       -4.66445&#xA;H        -13.91637       -4.71222       -5.05351&#xA;C          1.18679      -11.63930       -1.65826&#xA;H          2.08113       -9.05540       -1.64176&#xA;C         -9.32902       -5.35310       -3.54994&#xA;C         -8.00147       -5.67502       -3.25496&#xA;H        -11.78293       -4.83581       -3.83134&#xA;N          1.11328      -12.99119       -1.34556&#xA;C          2.03505      -10.97543       -0.74023&#xA;C          2.44727       -9.55973       -0.70751&#xA;N        -11.70170       -5.56231       -3.14774&#xA;H          3.57245       -9.50454       -0.72587&#xA;C        -10.39538       -5.93575       -2.82231&#xA;C        -14.21157       -5.56054       -3.22256&#xA;C         -7.67004       -6.60441       -2.22389&#xA;C          1.90085      -13.16305       -0.25528&#xA;N         -6.28334       -6.81223       -1.93951&#xA;H        -15.66861       -1.98691       -4.18721&#xA;H        -15.00747       -6.26815       -2.83416&#xA;C        -16.24979       -2.62698       -3.52327&#xA;C        -12.87527       -6.14638       -2.69589&#xA;N          2.48240      -11.96293        0.14523&#xA;N        -17.62237       -2.47886       -3.36451&#xA;C         -4.49640       -8.10162       -1.25030&#xA;N         -5.88501       -7.91808       -1.55368&#xA;C         -3.87925       -9.32440       -1.64388&#xA;H          3.17318       -7.23677        0.36085&#xA;F         -4.56957      -10.23766       -2.36676&#xA;C         -3.70257       -7.19528       -0.49914&#xA;C         -2.55065       -9.60942       -1.31470&#xA;O          0.35611       -6.94553        0.32760&#xA;C         -2.37455       -7.48350       -0.15432&#xA;C         -1.77678       -8.68949       -0.56764&#xA;F         -4.23242       -6.02796       -0.06245&#xA;C          0.53834       -8.17137        0.18934&#xA;C        -10.08912       -6.84769       -1.79487&#xA;H          2.07812      -14.10928        0.27181&#xA;C        -15.78188       -3.69142       -2.71834&#xA;C          1.90838       -8.82060        0.53509&#xA;N         -0.46010       -9.03051       -0.24672&#xA;C         -8.75617       -7.18141       -1.51305&#xA;C        -17.99820       -3.43334       -2.47759&#xA;H         -2.12268      -10.56741       -1.65501&#xA;C        -14.40721       -4.19212       -2.54285&#xA;H         -1.81598       -6.74527        0.44577&#xA;H         -0.19493       -9.97937       -0.43360&#xA;N          2.86803       -7.88077        1.06569&#xA;H        -13.69657       -3.43595       -2.97421&#xA;H          3.09956      -11.82715        0.90716&#xA;N        -16.90981       -4.19498       -2.05957&#xA;H        -19.01808       -3.61296       -2.11480&#xA;O        -12.90229       -7.09102       -1.88528&#xA;H        -10.88203       -7.32042       -1.19068&#xA;H        -16.92146       -4.93886       -1.40693&#xA;F         -8.52681       -8.05466       -0.50489&#xA;H          1.69989       -9.56622        1.36285&#xA;H          2.46898       -7.36611        1.82784&#xA;H        -14.16857       -4.30034       -1.44929&#xA;H         18.09012        9.42357       -1.81836&#xA;F         16.48163        1.39387       -2.87539&#xA;H          7.96220       -4.06105       -3.51819&#xA;H         17.60268        3.68354       -2.56623&#xA;N         17.92323        8.43985       -1.73935&#xA;H         18.68774        7.93896       -2.14905&#xA;C          7.37441       -4.57902       -2.75953&#xA;H          9.42815       -6.32849       -3.18884&#xA;C         16.75252        3.51753       -1.88275&#xA;C         16.06761        2.30160       -1.96011&#xA;H         17.92140        5.71877       -1.46626&#xA;N          6.15726       -4.08817       -2.30354&#xA;C          7.67815       -5.80012       -2.11118&#xA;C          8.83234       -6.69634       -2.31074&#xA;N         17.09147        5.70197       -0.90756&#xA;H          8.45585       -7.72472       -2.57522&#xA;C         16.36409        4.50931       -0.94985&#xA;C         17.71875        8.06851       -0.35999&#xA;C         14.95253        2.01848       -1.11633&#xA;C          5.71401       -4.98725       -1.39019&#xA;N         14.35655        0.72269       -1.21801&#xA;H         21.61587        8.58107       -0.75362&#xA;H         17.19055        8.92234        0.16625&#xA;C         21.09462        9.17140        0.00018&#xA;C         16.74102        6.87002       -0.24821&#xA;N          6.60605       -6.04649       -1.24540&#xA;N         21.60136       10.37175        0.48346&#xA;C         12.54069       -0.70153       -1.10751&#xA;N         13.14748        0.58850       -1.03360&#xA;C         11.16073       -0.75363       -1.47075&#xA;H         10.79779       -8.38500       -1.72194&#xA;F         10.49608        0.37743       -1.80507&#xA;C         13.15822       -1.93853       -0.78035&#xA;C         10.45825       -1.96102       -1.50679&#xA;O         12.02403       -5.92934       -1.08952&#xA;C         12.45238       -3.15052       -0.80187&#xA;C         11.09434       -3.18059       -1.17037&#xA;F         14.45681       -1.97792       -0.40174&#xA;C         10.80784       -5.65638       -1.12525&#xA;C         15.27807        4.24224       -0.09560&#xA;H          4.78194       -4.91884       -0.81412&#xA;C         19.85964        8.88077        0.62505&#xA;C          9.73569       -6.78130       -1.06352&#xA;N         10.33617       -4.35316       -1.19072&#xA;C         14.58375        3.02684       -0.18691&#xA;C         20.69763       10.81665        1.39124&#xA;H          9.39657       -1.93873       -1.80486&#xA;C         18.98066        7.71141        0.44765&#xA;H         12.98913       -4.07196       -0.51983&#xA;H          9.35005       -4.23241       -1.32787&#xA;N         10.30574       -8.09865       -0.89693&#xA;H         19.56647        6.90777       -0.07566&#xA;H          6.50934       -6.82415       -0.64051&#xA;N         19.62080        9.94087        1.50745&#xA;H         20.77041       11.74227        1.97621&#xA;O         15.70174        6.99012        0.42661&#xA;H         14.94922        4.97548        0.66030&#xA;H         18.84443       10.03273        2.11405&#xA;F         13.55602        2.82368        0.67020&#xA;H          9.12052       -6.57875       -0.13351&#xA;H         10.94041       -8.10690       -0.12051&#xA;H         18.66052        7.30605        1.44630&#xA;H        -13.76816       14.18822        0.15446&#xA;F         -7.80049        8.53951       -1.12529&#xA;H         -7.63542       -1.62444       -0.88481&#xA;H         -9.18708       10.67465       -0.82679&#xA;N        -13.17375       13.38157        0.17397&#xA;H        -12.40898       13.52486       -0.45771&#xA;C         -7.26280       -2.38041       -0.19256&#xA;H         -4.92758       -1.46248       -1.31115&#xA;C         -9.45404        9.87889       -0.11042&#xA;C         -8.75922        8.66874       -0.17804&#xA;H        -10.77948       11.98996        0.22485&#xA;N         -8.11638       -3.21139        0.52310&#xA;C         -5.91608       -2.69441        0.10809&#xA;C         -4.67369       -2.10453       -0.42557&#xA;N        -11.12066       11.31524        0.88069&#xA;H         -4.00416       -2.93001       -0.79885&#xA;C        -10.47282       10.07761        0.85340&#xA;C        -12.71357       13.14074        1.52107&#xA;C         -9.04883        7.58895        0.71076&#xA;C         -7.31478       -4.02595        1.25291&#xA;N         -8.22918        6.42421        0.60687&#xA;H        -10.97501       16.64039        0.56276&#xA;H        -13.61494       13.20121        2.20653&#xA;C        -11.72035       16.60868        1.35758&#xA;C        -12.18298       11.69437        1.68630&#xA;N         -5.96893       -3.74749        1.02909&#xA;N        -12.42268       17.73783        1.76153&#xA;C         -7.84670        4.15808        0.85037&#xA;N         -8.66644        5.32269        0.93868&#xA;C         -8.51924        2.89889        0.78641&#xA;H         -2.17063       -1.22446       -0.39021&#xA;F         -9.87124        2.84337        0.74802&#xA;C         -6.42644        4.11547        0.87959&#xA;C         -7.81553        1.69236        0.74875&#xA;O         -3.58659        1.12673        0.30641&#xA;C         -5.71718        2.90526        0.84970&#xA;C         -6.40005        1.67698        0.77865&#xA;F         -5.70416        5.25640        0.96629&#xA;C         -4.39806        0.21018        0.54285&#xA;C        -10.77381        9.02711        1.73940&#xA;H         -7.64584       -4.80706        1.94962&#xA;C        -12.12509       15.48849        2.12004&#xA;C         -3.92767       -1.26917        0.63595&#xA;N         -5.74810        0.44199        0.76341&#xA;C        -10.07810        7.81061        1.66405&#xA;C        -13.24784       17.32506        2.75528&#xA;H         -8.39188        0.75356        0.69354&#xA;C        -11.63630       14.09952        2.06136&#xA;H         -4.61552        2.94570        0.88616&#xA;H         -6.33787       -0.36423        0.85277&#xA;N         -2.49355       -1.41802        0.53990&#xA;H        -10.72396       14.07694        1.40613&#xA;H         -5.19146       -4.22413        1.41527&#xA;N        -13.09845       15.96346        3.00678&#xA;H        -13.95622       17.95292        3.31041&#xA;O        -12.70838       10.94446        2.52936&#xA;H        -11.55643        9.13140        2.50996&#xA;H        -13.58224       15.42900        3.68464&#xA;F        -10.40171        6.84946        2.56012&#xA;H         -4.21459       -1.62930        1.67173&#xA;H         -2.03679       -0.78457        1.17047&#xA;H        -11.33159       13.74988        3.08562&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1234" LastEditorUserId="5" LastEditDate="2020-08-21T03:04:36.790" LastActivityDate="2020-08-21T10:52:00.060" Title="How to build a simulation model for a molecular dynamics simulation" Tags="|software|molecular-dynamics|lammps|from-chem-se|software-recommendations|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2050" PostTypeId="2" ParentId="2049" CreationDate="2020-08-21T01:28:43.707" Score="5" Body="&lt;p&gt;The question is how to build a simulation model rather than the choice of software. You can build a box and then put your four molecules into the box.&#xA;I have used the supported coordinates to build a structure file [xxx.vasp] (You can use VESTA software to open it and view it). The key point is how to set the position of these molecules. If the position is set down, you can use VASP or any other software to perform molecular dynamics. XXX.vasp can be read by VASP software.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;struct&#xA;1.0&#xA;   80.0000000000         0.0000000000         0.0000000000&#xA;    0.0000000000        80.0000000000         0.0000000000&#xA;    0.0000000000         0.0000000000        80.0000000000&#xA;C    H    F    N    O&#xA;96   88   16   40    8&#xA;Cartesian&#xA;77.964949608        69.024572372        79.259772301&#xA;77.552728653        70.440268517        79.292488098&#xA;10.395380259        74.064249992        77.177691460&#xA;14.211570024        74.439458847        76.777439117&#xA; 7.670040131        73.395590782        77.776107788&#xA;78.099150658        66.836948395        79.744720459&#xA;16.249790192        77.373018265        76.476731300&#xA;12.875269651        73.853621483        77.304110527&#xA; 4.496399760        71.898379326        78.749699593&#xA; 3.879249990        70.675601959        78.356118202&#xA; 3.702569902        72.804718018        79.500861168&#xA; 2.550649941        70.390582085        78.685297966&#xA; 2.374550104        72.516498566        79.845681190&#xA; 1.776780039        71.310510635        79.432358742&#xA;79.461660385        71.828632355         0.189340003&#xA;10.089119673        73.152308464        78.205127716&#xA;15.781880617        76.308579445        77.281661034&#xA;78.091621399        71.179399490         0.535090044&#xA; 8.756170273        72.818589211        78.486948013&#xA;17.998199463        76.566658020        77.522411346&#xA;14.407210350        75.807881355        77.457151413&#xA;72.625589371        75.420980453        77.240471840&#xA;63.247480392         3.517529964        78.117251396&#xA;63.932390213         2.301599979        78.039889336&#xA;72.321848869        74.199881554        77.888817787&#xA;71.167659760        73.303661346        77.689261436&#xA;63.635911942         4.509309828        79.050149918&#xA;62.281250954         8.068510294        79.640011787&#xA;65.047469139         2.018480003        78.883671761&#xA;74.285988808        75.012750626        78.609809875&#xA;58.905382156         9.171400070         0.000180000&#xA;63.258981705         6.870020032        79.751791954&#xA;67.459306717        79.298467636        78.892488480&#xA;68.839268684        79.246368408        78.529248238&#xA;66.841778755        78.061470985        79.219651222&#xA;69.541749954        78.038978577        78.493208885&#xA;67.547616959        76.849479675        79.198131561&#xA;68.905658722        76.819410324        78.829631805&#xA;69.192161560        74.343619347        78.874750137&#xA;64.721927643         4.242239892        79.904398918&#xA;10.472819805        10.077610016         0.853400007&#xA;60.140361786         8.880769610         0.625049993&#xA;70.264310837        73.218698502        78.936481476&#xA;65.416250229         3.026840091        79.813089371&#xA;59.302368164        10.816650391         1.391240060&#xA;61.019339561         7.711409926         0.447649993&#xA; 7.262800336        77.619590759        79.807438850&#xA; 9.454039335         9.878889918        79.889578819&#xA; 8.759220243         8.668740392        79.821958542&#xA; 5.916079879        77.305588722         0.108089997&#xA; 4.673689902        77.895469666        79.574432373&#xA;12.713569403        13.140740395         1.521070004&#xA; 9.048830271         7.588950396         0.710759982&#xA; 7.314780354        75.974049568         1.252910048&#xA;11.720349789        16.608680487         1.357579976&#xA;12.182979584        11.694370508         1.686300039&#xA; 7.846699953         4.158080220         0.850370005&#xA; 8.519240618         2.898890078         0.786409974&#xA; 6.426439881         4.115470052         0.879589990&#xA; 7.815529704         1.692360044         0.748749971&#xA; 5.717179775         2.905260026         0.849699974&#xA; 6.400049925         1.676979959         0.778649971&#xA; 4.398059845         0.210180003         0.542850010&#xA;10.773810148         9.027110338         1.739400029&#xA;12.125089169        15.488489866         2.120039910&#xA; 3.927670121        78.730831146         0.635950044&#xA;10.078099966         7.810609937         1.664049923&#xA;13.247840405        17.325060368         2.755280137&#xA;11.636300087        14.099519253         2.061359882&#xA; 9.329019785        74.646902084        76.450061798&#xA; 8.001469374        74.324979782        76.745038033&#xA;77.085809708         2.875519991        78.974828720&#xA;78.813209534        68.360700607        78.341741562&#xA;77.139310837         2.206970006         0.201280005&#xA;79.059648514        79.013719559         5.706590414&#xA;78.946409225        79.672179222         4.473490119&#xA;79.160017967        76.436882019         9.444519877&#xA;78.443107605         4.072219729        74.421339035&#xA;79.486827850        72.319750786         7.884479761&#xA;79.063138962         5.435050130        74.783492088&#xA;79.128160477         6.329089999        73.613967896&#xA;78.328518867         7.452720404        73.301200867&#xA;79.803562164         7.270179987        71.691308022&#xA;78.694782257         3.120079935        75.618658066&#xA;78.071980476         2.651160061        77.984089851&#xA;79.110550880         1.742419899        78.260960579&#xA;79.154529572         1.066210046        79.488840103&#xA;78.177418709         1.274310052         0.497980006&#xA;78.653130531        78.973450661         3.271920085&#xA;78.475852013        77.561597824         3.379790187&#xA;78.575420380        76.903800964         4.609089792&#xA;78.864889145        77.622451782         5.793809891&#xA;78.958878517        77.442970276         8.275890350&#xA;78.060660362        75.356960297         9.378830194&#xA;78.457279205        74.197521210         8.558230400&#xA;77.892870903        73.724551201         7.349590063&#xA; 0.174940005        75.960879326         9.278380275&#xA;79.344658852        68.788590431        77.490978241&#xA; 9.523909688        75.367660522        75.637631416&#xA;13.916370869        75.287780762        74.946489334&#xA;77.918868065        70.944600105        78.358240128&#xA;11.782929897        75.164189339        76.168661118&#xA;76.427550316        70.495457649        79.274129868&#xA;15.668609142        78.013091087        75.812788010&#xA;15.007469654        73.731851578        77.165842056&#xA;76.826820374        72.763228416         0.360850021&#xA;10.882029533        72.679581642        78.809318542&#xA;16.921459436        75.061140060        78.593068123&#xA;78.300108910        70.433778763         1.362849921&#xA;77.531018257        72.633891106         1.827839911&#xA;14.168570042        75.699658394        78.550710678&#xA;61.909880638         9.423569441        78.181638718&#xA;72.037801743        75.938949585        76.481809616&#xA;77.921881676        65.890722275         0.271809995&#xA; 2.122679949        69.432592392        78.344988823&#xA; 1.815979928        73.254728317         0.445769988&#xA; 0.194930006        70.020627975        79.566397667&#xA;13.696570396        76.564049721        77.025790215&#xA;76.900439262        68.172850609         0.907159969&#xA;19.018080235        76.387038231        77.885198593&#xA;62.397317886         3.683540225        77.433772087&#xA;61.312260628         7.938960195        77.850952148&#xA;62.078599930         5.718770027        78.533740044&#xA;70.571851730        73.671512604        76.811161041&#xA;71.544151306        72.275280952        77.424778938&#xA;58.384132385         8.581069708        79.246377945&#xA;62.809448242         8.922340274         0.166250002&#xA;69.202213287        71.614999771        78.278059959&#xA;60.433530807         6.907770038        79.924340248&#xA;73.490657806        73.175849915        79.359488487&#xA;59.229588509        11.742269993         1.976210028&#xA;65.050783157         4.975480139         0.660300031&#xA;61.155567169        10.032730103         2.114049941&#xA;70.879478455        73.421249390        79.866490364&#xA;69.059591293        71.893100739        79.879488945&#xA;76.529030800         4.754740298        74.569749832&#xA;76.952648163         4.274050295        73.067331314&#xA;78.456759453         5.940780044        75.583009720&#xA; 0.093319993         5.256589651        75.197329521&#xA;77.489781380         7.853839993        73.870410919&#xA; 0.391990021         7.429450154        70.778851509&#xA; 0.780970007         5.549950004        72.503638268&#xA;77.285628319         4.078730047        76.759138107&#xA;79.909768105         1.543679982        77.526822090&#xA;78.426499367        75.811128616         4.630320072&#xA;78.979139328        75.914888382         6.911870241&#xA;79.888381958        77.819900513        10.730680227&#xA;78.322730064        77.445530891        10.998780727&#xA;77.813830376        75.001611710        10.419039726&#xA;77.119369507        75.796408653         8.951579928&#xA;77.067718506        74.157080650         6.782540083&#xA; 0.194509998        71.480669975         7.887269855&#xA; 0.063490001        73.335871696         9.675809741&#xA;79.305391312        79.613451958         6.599110365&#xA;76.256098747         3.581539989        78.799848557&#xA;15.181699991        74.253139496        75.008449554&#xA;61.339478493         7.306050062         1.446300000&#xA;13.768160343        14.188220501         0.154459998&#xA; 7.635419965        78.375558853        79.115190506&#xA; 9.187080264        10.674650669        79.173212051&#xA;11.556429863         9.131399989         2.509959936&#xA;13.582240343        15.428999662         3.684639931&#xA; 4.214590192        78.370699883         1.671729982&#xA; 2.036789954        79.215431213         1.170469970&#xA;11.331589222        13.749879599         3.085619807&#xA;79.040222168         3.626379967        73.567018509&#xA;12.408980131        13.524860144        79.542288780&#xA; 4.927579761        78.537521362        78.688850403&#xA;10.779479742        11.989959478         0.224849992&#xA; 4.004159868        77.069988251        79.201149940&#xA;10.975010395        16.640390158         0.562760010&#xA;13.614939451        13.201210499         2.206530124&#xA; 2.170629948        78.775539398        79.609789848&#xA; 7.645840049        75.192937851         1.949619949&#xA; 8.391879797         0.753559992         0.693539977&#xA; 4.615519941         2.945699990         0.886159986&#xA; 5.191460252        75.775871277         1.415269971&#xA; 6.337870359        79.635767937         0.852769986&#xA;10.723960400        14.076939821         1.406129897&#xA;13.956220150        17.952921391         3.310410082&#xA;75.218057632        75.081157684        79.185881615&#xA;70.603427887        78.061270714        78.195137978&#xA;67.010869980        75.928039551        79.480171204&#xA;70.649948120        75.767588615        78.672127724&#xA;14.252539873        74.428639412        75.335550308&#xA;11.701700687        74.437689781        76.852259636&#xA; 6.283339858        73.187770844        78.060488701&#xA;77.517600060        68.037071228         0.145229995&#xA;17.622369528        77.521138191        76.635489464&#xA; 5.885009766        72.081918716        78.446321487&#xA;78.886718750        67.008810043        78.654441833&#xA;65.643448830         0.722690001        78.781991005&#xA;73.393950462        73.953509331        78.754601479&#xA;58.398637772        10.371749401         0.483460017&#xA;66.852521896         0.588500015        78.966398239&#xA;69.694261551        71.901350021        79.103069305&#xA;78.757438660         8.024870157        72.109508514&#xA;77.050189972         4.079259932        74.044508934&#xA;73.842740059        75.911831856        77.696461678&#xA;62.908530235         5.701969862        79.092440605&#xA;69.663829803        75.646839142        78.809280396&#xA; 0.062250001         6.226319671        72.576379776&#xA;77.980308533         3.358939886        76.782431602&#xA;60.379199982         9.940870404         1.507450044&#xA;13.173749447        13.381569386         0.173969995&#xA; 8.116379976        76.788611412         0.523100011&#xA;11.120660305        11.315239668         0.880689994&#xA; 8.229180574         6.424210072         0.606869981&#xA; 5.968929529        76.252508163         1.029090062&#xA;12.422679663        17.737829685         1.761530042&#xA; 8.666440248         5.322690010         0.938680023&#xA; 5.748099685         0.441989973         0.763409957&#xA; 2.493550032        78.581981659         0.539899990&#xA;13.098449707        15.963460207         3.006779850&#xA;78.197131157         0.697000027         1.806109995&#xA;78.604340553        79.546408653         1.963810027&#xA;78.975791931        76.914448738         6.993219852&#xA; 0.460099988        70.969491005        79.753279686&#xA;77.131967545        72.119231224         1.065690070&#xA;16.909809113        75.805020332        77.940430641&#xA;62.076768875         8.439849615        78.260650635&#xA;79.217190742        77.074842453        10.739729404&#xA;78.539619446        72.563080788         6.945220232&#xA;79.469251633        73.287491798         8.885769844&#xA; 7.025710344        74.910931587        76.012129784&#xA; 4.569570124        69.762339592        77.633237839&#xA; 8.526809812        71.945338249        79.495110512&#xA;63.518371582         1.393869966        77.124609947&#xA; 9.871239662         2.843369842         0.748019964&#xA;10.401709080         6.849460006         2.560120225&#xA; 5.704160333         5.256400108         0.966290012&#xA;78.189058304        76.820549965         2.283639908&#xA; 0.189270005         0.219459999        79.703211784&#xA;79.159178734         1.008579955         4.453489780&#xA;76.164221764         2.456820011         1.106590033&#xA;66.443977356         2.823680043         0.670199990&#xA; 7.800489664         8.539509773        78.874711990&#xA;69.503917694         0.377429985        78.194928169&#xA;65.543189049        78.022079468        79.598259926&#xA; 4.232420027        73.972039223        79.937548637&#xA;64.298257828         6.990119815         0.426610000&#xA; 3.586589992         1.126729995         0.306410007&#xA;79.524540901         2.199229896        75.502009392&#xA;12.708380222        10.944459438         2.529360056&#xA;67.975969315        74.070658684        78.910479546&#xA;12.902290821        72.908978462        78.114719391&#xA;78.818349838        78.661971092         8.498240709&#xA;79.643888474        73.054471016         0.327600017&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-08-21T01:28:43.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2051" PostTypeId="2" ParentId="2039" CreationDate="2020-08-21T03:50:20.327" Score="7" Body="&lt;p&gt;I thought I would post the results of the benchmarking as per Tristan's suggestion. Maybe it will be useful for someone in the future. I only did 10 steps in the MD (1 fs step size, 10 fs total).&lt;/p&gt;&#xA;&lt;p&gt;Percent differences are all relative to the NCORE=1 run with 32 cores and 1 node. There's a 33% speedup by going to the 2 nodes with 64 cores (NCORE=32).&lt;/p&gt;&#xA;&lt;p&gt;Obviously this may differ depending on your cluster. This is the Graham cluster on Sharcnet in Canada by the way - so hopefully it's useful to fellow Canadians out there :)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Oubth.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Oubth.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="979" LastActivityDate="2020-08-21T03:50:20.327" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2052" PostTypeId="2" ParentId="1963" CreationDate="2020-08-21T08:36:09.990" Score="2" Body="&lt;p&gt;An easier route to using symmetry-adapted CI with hand-derived matrix elements is to implement CI with determinant strings. That is, you construct bitstrings of which orbitals are occupied in the determinant, and you don't care about adapting your basis for &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2$&lt;/span&gt;. This is the way most codes work, since the resulting algorithm is easy to make very fast, whereas spin-adaptation may require you to limit your expansion length.&lt;/p&gt;&#xA;&lt;p&gt;The string based CI works in the space of spin-orbitals. For instance, the Hartree-Fock state would be &lt;span class=&quot;math-container&quot;&gt;$|{\rm HF}\rangle = (1, 1, \dots, 1, 1, 0, 0, \dots, 0, 0)^{\rm T}$&lt;/span&gt;, and the first excited determinant would be &lt;span class=&quot;math-container&quot;&gt;$(1, 1, \dots, 1, 0, 1, 0, \dots, 0, 0)^{\rm T}$&lt;/span&gt;. What you need to do is just build all the determinants that have the wanted &lt;span class=&quot;math-container&quot;&gt;$\hat{S}_z$&lt;/span&gt;, i.e. the correct number of &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; electrons.&lt;/p&gt;&#xA;&lt;p&gt;Now, building the CI Hamiltonian is very straightforward: once you have the bitstrings &lt;span class=&quot;math-container&quot;&gt;$|i\rangle$&lt;/span&gt;, you can obtain the matrix elements &lt;span class=&quot;math-container&quot;&gt;$\langle i | H | j \rangle$&lt;/span&gt; with e.g. the &lt;a href=&quot;https://en.wikipedia.org/wiki/Slater%E2%80%93Condon_rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slater-Condon rules&lt;/a&gt;. The matrix element is zero unless &lt;span class=&quot;math-container&quot;&gt;$|i\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|j\rangle$&lt;/span&gt; differ by at most a double excitation; you can find out the difference in the states' occupations with a bit-wise XOR operation. Counting the bits in the result of the XOR gives 0 if the determinants match, 2 if they differ by a single excitation, 4 in the case of a double excitation, and you don't care about the rest since the matrix element is zero.&lt;/p&gt;&#xA;&lt;p&gt;You can build the sparse Hamiltonian in memory, if you don't go to huge active spaces just by looping over the pairs of bit strings, and use library implementations of sparse matrix diagonalizers.&lt;/p&gt;&#xA;&lt;p&gt;The best thing about using this method, in addition to being relatively straightforward to implement, is that you can do arbitrary level CI with it: CID, CISD, CISDT, CISDTQ, ..., all the way to FCI and CASSCF.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-08-21T14:28:43.873" LastActivityDate="2020-08-21T14:28:43.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2053" PostTypeId="2" ParentId="2049" CreationDate="2020-08-21T10:52:00.060" Score="2" Body="&lt;p&gt;There are two issues here:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How to build A model for simulations?&lt;/li&gt;&#xA;&lt;li&gt;How to create the input files from the model from step 1 to my molecular dynamic software?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For the first step I would try to use any specific software for design/build/draw structures to manually create the system. Also, it is possible to use software like &lt;a href=&quot;http://m3g.iqm.unicamp.br/packmol/home.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;Packmol&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the second step, and as each molecular dynamic have its own input structure, you need the &amp;quot;conversion&amp;quot; tool that come with it to use as input the structure from step 1. I rather prefer to use a recommended graphical user interface for the molecular dynamics software. For example, the software DESMOND came with the MAESTRO graphical interface where you setup the inputs and also analyses the outputs.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-21T10:52:00.060" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2054" PostTypeId="1" CreationDate="2020-08-21T17:51:35.290" Score="9" ViewCount="354" Body="&lt;p&gt;In molecular mechanics, the energy is often written as a sum of bonds, angles and torsion energies, and an electrostatic term, e.g.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V = \sum_{bonds} K_r (r-r_{eq})^2 +\sum_{angles}K_{\theta}(\theta -\theta_0)^2 +\sum_{dihedrals}V_n/2 [1+cos(n\phi -\gamma)] + \sum_{i&amp;lt;j}[\frac{A_{ij}}{R_{ij}^{12}} + \frac{B_{ij}}{R_{ij}^{6}} + \frac{q_1 q_2}{\epsilon R_{ij}}]$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;While this is pretty easy to evaluate, the nuclear energy derivatives (gradient) are more complex because they need to be written in the Cartesian coordinate system.&lt;/p&gt;&#xA;&lt;p&gt;This reference:&lt;/p&gt;&#xA;&lt;p&gt;First and second derivative matrix elements for the stretching, bending, and torsional energy, Kenneth J. Miller, Robert J. Hinde, and Janet Anderson, Journal of Computational Chemistry, vol 10, 63-76, 1989, &lt;a href=&quot;https://www.onlinelibrary.wiley.com/doi/abs/10.1002/jcc.540100107&quot; rel=&quot;noreferrer&quot;&gt;https://www.onlinelibrary.wiley.com/doi/abs/10.1002/jcc.540100107&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Outlines the mathematics for calculating the nuclear energy derivatives for the bonds, angles and torsions but it's rather complicated.&lt;/p&gt;&#xA;&lt;p&gt;For example, I don't understand Table V.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there any open-source codes which implement this at a high-level?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'd like to use this code to supplement the text and for educational purposes so the easier the code the better&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-08-21T20:03:26.813" LastActivityDate="2020-08-22T17:05:43.650" Title="How to calculate the nuclear energy derivatives in molecular mechanics?" Tags="|reference-request|open-source|software-recommendations|molecular-mechanics|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2055" PostTypeId="1" CreationDate="2020-08-21T19:25:41.283" Score="9" ViewCount="447" Body="&lt;p&gt;I am new to crystal plasticity simulations and have been studying the concepts from &amp;quot;Introduction to Crystal Plasticity&amp;quot; in Mechanics of Microstructured Materials book. Additionally, I have been going through the publicly available UMAT for crystal plasticity (Huang 1991). I have also come across a paper titled &amp;quot;Comparison of the implicit and explicit finite element methods using crystal plasticity (2007),&amp;quot; where the authors have implemented the model in Abaqus/Explicit environment.&lt;/p&gt;&#xA;&lt;p&gt;Though I now understand the theoretical basis of the crystal plasticity formulation, I have been unable to implement the model as a VUMAT subroutine, as carried out in the paper. &lt;a href=&quot;https://imechanica.org/comment/30452&quot; rel=&quot;nofollow noreferrer&quot;&gt;I received the VUMAT file here&lt;/a&gt;, but when I tried to run it I got the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;The executable package.exe aborted with system error code 1073740940&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1240" LastEditorUserId="5" LastEditDate="2020-12-31T05:23:22.810" LastActivityDate="2020-12-31T05:23:22.810" Title="&quot;The executable package.exe aborted with system error code 1073740940&quot; in ABAQUS with the following VUMAT for crystal plasticity" Tags="|crystal-structure|finite-element-analysis|software-input-file-request|crystal-plasticity|abaqus|" AnswerCount="0" CommentCount="1" ClosedDate="2021-06-22T13:58:28.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="2056" PostTypeId="2" ParentId="2054" CreationDate="2020-08-21T19:52:11.897" Score="6" Body="&lt;p&gt;Typically, force evaluation happens in Cartesian coordinates regardless of the approach (QM or MM). In QM codes the forces may then be projected into internal coordinates, which in turn is usually dependent on the geometry, see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.478397&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 110, 4986 (1999)&lt;/a&gt;; even though this carries some cost, it is more than offset by the savings in fewer QM calculations. Also solids can be optimized in internal coordinates, see &lt;a href=&quot;https://doi.org/10.1016/S0009-2614(01)00030-6&quot; rel=&quot;noreferrer&quot;&gt;Chem. Phys. Lett. 335, 321 (2001)&lt;/a&gt;.  (AFAIK molecular dynamics codes don't use internal coordinates for geometry optimization, but I may be mistaken.)&lt;/p&gt;&#xA;&lt;p&gt;The equations for the gradients and hessians for your force field are a bit complicated, but straightforward, since you're still in the Cartesian space. Table V is just a helper table of multiple-angle formulas for cosine:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\begin{aligned}\cos \phi_{ijkl} &amp;amp;= \cos \phi_{ijkl} \\ \cos 2\phi_{ijkl} &amp;amp;= -1 + 2 \cos^2 \phi_{ijkl} \\ \cos 3\phi_{ijkl} &amp;amp;= -3\cos \phi_{ijkl} + 4 \cos^3 \phi_{ijkl} \\ \cos 4\phi_{ijkl} &amp;amp;= 1 -8\cos^2 \phi_{ijkl} + 8 \cos^4 \phi_{ijkl} \end{aligned}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and so on for &lt;span class=&quot;math-container&quot;&gt;$\cos 5\phi_{ijkl}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\cos 6\phi_{ijkl}$&lt;/span&gt;. They say in the main text (in the section on torsional motion) that using these trigonometric identities avoids undefined values at &lt;span class=&quot;math-container&quot;&gt;$\phi_{ijkl}=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi_{ijkl}=\pi/2$&lt;/span&gt; for the derivatives that get divided by  &lt;span class=&quot;math-container&quot;&gt;$\sin \phi_{ijkl}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, if you're hoping for high-level implementations - meaning simple and very intelligible code - my guess is that you're out of luck: since the evaluation of forces is a key bottleneck in MD codes, it is probably heavily optimized in all codes.&lt;/p&gt;&#xA;&lt;p&gt;Your potential is quite simple, consisting of the harmonic bond and angle stretching, dihedral, and Lennard-Jones term, so it is probably available in almost any molecular dynamics code. (I think you are actually missing the Coulomb term that is typically included to model electrostatic interactions between non-bonded regions.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.gromacs.org/&quot; rel=&quot;noreferrer&quot;&gt;GROMACS&lt;/a&gt; is one of the better-known open source molecular MD codes out there, and it is fast. It used to be written in plain C; I think it may have gotten some C++ later on. I haven't really looked at the source code in a decade...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-08-21T20:05:46.110" LastActivityDate="2020-08-21T20:05:46.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2057" PostTypeId="1" AcceptedAnswerId="2060" CreationDate="2020-08-21T21:53:43.540" Score="8" ViewCount="350" Body="&lt;p&gt;I was looking for a dataset of alanine dipeptide trajectories. I was wondering whether there is such dataset available or it is unlikely to find one and I should start running molecular dynamics simulations myself. If so, what software would be easier to work with for a beginner.&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="5" LastEditDate="2020-08-21T23:08:58.350" LastActivityDate="2020-09-01T21:43:16.643" Title="Alanine dipeptide trajectories dataset" Tags="|molecular-dynamics|reference-request|molecular-modeling|databases|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2058" PostTypeId="2" ParentId="2054" CreationDate="2020-08-21T22:12:09.847" Score="7" Body="&lt;p&gt;You iterate through the bond, angle, torsion, etc. contributions and sum the gradients on each atom.&lt;/p&gt;&#xA;&lt;p&gt;When we were implementing these for Open Babel, we found a very nice dissertation which gave some insight into MMFF94 gradients:&lt;/p&gt;&#xA;&lt;p&gt;Dr. Andreas Moll &lt;a href=&quot;https://doi.org/10.22028/D291-25896&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;BALLView : a molecular viewer and modeling tool&lt;/em&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Bonds - harmonic potential leads to, e.g.:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S_{i j} \frac{\hat{\mathbf{d}_{\mathrm{jj}}}}{\left|\mathbf{d}_{\mathrm{ij}}\right|}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Angle Bend, e.g.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;B_{i j k} \frac{\hat{\mathbf{d}}_{\mathrm{ij}} \times \hat{\mathbf{d}}_{\mathrm{ki}} \times \hat{\mathbf{d}}_{\mathrm{ij}}}{\left|\mathbf{d}_{\mathrm{ij}}\right|}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Torsion, e.g.;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;T_{i j k l} \frac{-\hat{\mathbf{d}}_{\mathrm{ij}} \times \hat{\mathrm{d}}_{\mathrm{jk}}}{\sin (\phi)^{2}\left|\mathbf{d}_{\mathrm{ij}}\right|}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The code in Open Babel can be found starting here:&#xA;&lt;a href=&quot;https://github.com/openbabel/openbabel/blob/4709b0752109db593f1bee6298ef3bfa718d260d/src/forcefield.cpp#L3608&quot; rel=&quot;nofollow noreferrer&quot;&gt;forcefield.cpp&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It's basically a bunch of cross-products and normalizations to get the force on each atom from a particular interaction.&lt;/p&gt;&#xA;&lt;p&gt;OpenMM looks like they have their implementations &lt;a href=&quot;https://github.com/openmm/openmm/tree/master/platforms/common/src/kernels&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; - fairly similar in approach.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2020-08-22T17:05:43.650" LastActivityDate="2020-08-22T17:05:43.650" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2059" PostTypeId="1" CreationDate="2020-08-22T06:36:12.360" Score="12" ViewCount="599" Body="&lt;p&gt;What software currently can be accessibly used to calculate collision cross section using the geometries obtained from DFT? In my case, Q-Chem is used for geometry optimization.&lt;/p&gt;&#xA;&lt;p&gt;The goal is to compute cross-section which can be compared with CCS (collisional cross-section) obtained from Ion Mobility Mass Spectrometry experiments where gases like N&lt;sub&gt;2&lt;/sub&gt;, Ar or He could be used. I found relevant papers in &lt;i&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.organomet.8b00128&quot; rel=&quot;nofollow noreferrer&quot;&gt;Organometallics&lt;/a&gt;&lt;/I&gt; and &lt;I&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.organomet.8b00128&quot; rel=&quot;nofollow noreferrer&quot;&gt;PCCP&lt;/a&gt;&lt;/I&gt; as examples of calculations of CCS.&lt;/p&gt;&#xA;&lt;p&gt;I'm aware of iMos, but I haven't tested it yet. Is there any other software which is capable of performing this calculation?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2020-09-28T22:12:33.017" LastActivityDate="2020-09-30T00:04:07.500" Title="Is there a software that can calculate collision cross-sections involving molecules with several atoms?" Tags="|software|software-recommendations|q-chem|apple-operating-system|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="2060" PostTypeId="2" ParentId="2057" CreationDate="2020-08-22T17:12:59.900" Score="5" Body="&lt;p&gt;There are many sets, depending on force field or method (e.g., semiempirical, quantum, etc.) explicit or implicit solvent, etc., but if you're starting out, alanine dipeptide is one of the Amber tutorials, which include comparison production runs and analysis linked from the page:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://ambermd.org/tutorials/basic/tutorial0/&quot; rel=&quot;noreferrer&quot;&gt;http://ambermd.org/tutorials/basic/tutorial0/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-08-22T17:12:59.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2061" PostTypeId="1" AcceptedAnswerId="2062" CreationDate="2020-08-22T18:20:06.423" Score="11" ViewCount="1015" Body="&lt;p&gt;This is from the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LORBIT&quot; rel=&quot;noreferrer&quot;&gt;entry for &lt;code&gt;LORBIT&lt;/code&gt;&lt;/a&gt; in the &lt;code&gt;VASP Wiki&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;em&gt;For &lt;code&gt;LORBIT &amp;gt;= 11&lt;/code&gt; and &lt;code&gt;ISYM = 2&lt;/code&gt; the partial charge densities are not correctly symmetrized and can result in different charges for&#xA;symmetrically equivalent partial charge densities.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For example, in the calculations of &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni_3Al}$&lt;/span&gt; with spin-orbit coupling (&lt;code&gt;ISPIN = 2&lt;/code&gt;), I got different charges and magnetic moments for each of the three &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt; atoms when I used symmetry (&lt;code&gt;ISYM = 1&lt;/code&gt;) whereas with symmetry off (&lt;code&gt;ISYM = 0&lt;/code&gt;) the partial charges and magnetic moments on each &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt; atom were equal. In both cases though, the total charge and magnetic moment remained the same.&lt;/p&gt;&#xA;&lt;p&gt;That brings me to the electronic Density of States (DoS), specifically partial DoS. I read on the VASP forum that &lt;code&gt;ISYM = 0&lt;/code&gt; is required for a proper projection of the DoS on each atom. That exact &lt;a href=&quot;https://cms.mpi.univie.ac.at/vasp-forum/viewtopic.php?f=3&amp;amp;t=306&quot; rel=&quot;noreferrer&quot;&gt;page&lt;/a&gt; is inaccessible at the moment, but you can get a sense of the idea from the discussion on &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?t=15403#:%7E:text=The%20difference%20is%2C%20when%20ISYM,is%20symmetric%20with%20ISYM%3D0.&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt; as well.&lt;/p&gt;&#xA;&lt;p&gt;A general workflow to calculate electronic DoS using VASP:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Converge and relax the system as usual.&lt;/li&gt;&#xA;&lt;li&gt;Increase the # of k-points, and turn &lt;code&gt;ICHARG = 11&lt;/code&gt; so that the charge density from step 1 (written in the &lt;code&gt;CHGCAR&lt;/code&gt; file) is used. Also, no relaxation in this step with &lt;code&gt;IBRION = -1&lt;/code&gt; and &lt;code&gt;NSW = 0&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;The doubt&lt;/strong&gt;: Should I take &lt;code&gt;ISYM = 0&lt;/code&gt; in step 2 or during the last relaxation in step 1? The latter gets too expensive. I also have a doubt if there is an intermediate step involved (let's call it step 1.5):&lt;/p&gt;&#xA;&lt;p&gt;1.5. After proper convergence and relaxation of the system, increase the # of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points, and do one final relaxation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;span class=&quot;math-container&quot;&gt;$2^{nd}$&lt;/span&gt; doubt&lt;/strong&gt;: If step 1.5 is required then do we turn &lt;code&gt;ISYM = 0&lt;/code&gt; for this one or not? An &lt;code&gt;ISIF = 3&lt;/code&gt; type of complete relaxation with a higher # of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points and &lt;code&gt;ISYM = 0&lt;/code&gt; is extremely expensive.&lt;/p&gt;&#xA;&lt;p&gt;Any guidance/discussion is welcome.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="52" LastEditDate="2020-08-23T01:48:46.567" LastActivityDate="2020-08-23T01:48:46.567" Title="Effect of ISYM tag on Partial Density of States (VASP version &lt; 6)" Tags="|density-functional-theory|vasp|symmetry|charge-density|density-of-states|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2062" PostTypeId="2" ParentId="2061" CreationDate="2020-08-22T19:12:46.780" Score="7" Body="&lt;p&gt;Based on the &lt;a href=&quot;https://www.researchgate.net/post/What_is_the_difference_between_LDOS_and_PDOS_and_how_to_visualize_these_using_VASP2/54feaa63ef97136e028b46b6/citation/download&quot; rel=&quot;noreferrer&quot;&gt;comments I shared above&lt;/a&gt;, it seems that the quality of the charge density is fine. It is just the projection onto atoms that may not be done correctly. If this is indeed the case, then you don't need to re-relax the structure  (Step #1). You &lt;em&gt;should&lt;/em&gt; be able to read in the charge density and set &lt;code&gt;ISYM=0&lt;/code&gt; (symmetry disabled) and be okay. &lt;em&gt;Disclaimer&lt;/em&gt;: Only one way to find out -- give it a try! If it's expensive, drop the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points just for a simple test.&lt;/p&gt;&#xA;&lt;p&gt;As for your proposed Step #1.5, that's a separate question altogether. The answer to that question is whether increasing the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points will notably alter the geometry. If increasing the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points keeps essentially the same geometry, then you can likely increase it to get a more accurate density of states without worrying that the structure is not a local minimum in the potential energy surface. This will entirely depend on the difference in &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points and the system of interest.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-08-22T22:00:39.520" LastActivityDate="2020-08-22T22:00:39.520" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2063" PostTypeId="2" ParentId="2061" CreationDate="2020-08-22T21:35:13.423" Score="8" Body="&lt;p&gt;The typical calculation flow for the density of states is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Geometric relaxation to obtain the lowest-energy structure (CONTCAR) [1relax] (For your system, you should do the spin-polarized calculation by setting ISPIN=2).&lt;/li&gt;&#xA;&lt;li&gt;Using the relaxed structure to perform the electronic self-consistent calculation to obtain converged charge density [2scf].&lt;/li&gt;&#xA;&lt;li&gt;Using the converged charge density to calculate the density of states [3dos].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;At the final step, you can increase the k sampling to obtain a smooth curve.&lt;/p&gt;&#xA;&lt;p&gt;For the geometric relaxation and self-consistent calculation, you can use the default value of ISYM.&lt;/p&gt;&#xA;&lt;p&gt;As for the effect of ISYM on the partial density of states, you can test different ISYM with LORBIT=1 by plotting the DODCAR. Usually, you can just use the default value of ISYM, which will give you reasonable results.&lt;/p&gt;&#xA;&lt;p&gt;For your initial observation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In the spin-polarized coupled (ISPIN=2) calculations with Ni3Al, I got different charges and magnetic moments on each of the three Ni atoms when I kept symmetrization option ISYM on i.e. ISYM = 1. On turning it off (ISYM = 0), partial charges and magnetic moments on each  atom became equal. In both cases though, total charge and magnetic moment remained the same.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Only the total charge and magnetic moment are meaningful. The comparison for the charges and magnetic moments on each Ni atom for different ISYM is meaningless. You can compare the charges and magnetic moments for different atoms with the same ISYM value.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-08-22T21:35:13.423" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2064" PostTypeId="1" AcceptedAnswerId="2066" CreationDate="2020-08-23T14:51:32.063" Score="12" ViewCount="1782" Body="&lt;p&gt;I want to calculate the surface energy of CuO and for that, I've asked &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2001/cuo-monoclinic-crystallographic-plane-and-their-relaxed-surface-energy?noredirect=1#comment3579_2001&quot;&gt;CuO (monoclinic) crystallographic plane and their relaxed surface energy&lt;/a&gt;. But for the lack of knowledge of the surface termination process, I didn't understand the answer clearly. Can anyone please explain to me about surface termination and how to do that for a monoclinic structure and how to calculate the surface energy of that surface termination. Basically I want to know the science behind it. Can anyone help me with some resources to understand it?&lt;/p&gt;&#xA;" OwnerUserId="1200" LastEditorUserId="697" LastEditDate="2020-08-23T20:26:23.743" LastActivityDate="2020-08-24T00:51:20.147" Title="What is Surface termination and how to make surface termination of a crystal structure?" Tags="|density-functional-theory|reference-request|crystal-structure|surfaces|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2065" PostTypeId="1" CreationDate="2020-08-23T20:24:31.793" Score="7" ViewCount="246" Body="&lt;p&gt;I want to know the protonation state of some pdb ligands. For example, on the &lt;a href=&quot;http://www.rcsb.org/3d-view/2B4R?preset=ligandInteraction&amp;amp;sele=AES&quot; rel=&quot;noreferrer&quot;&gt;ligand&lt;/a&gt;, I want to know if the nitrogen is in its tertiary or quaternary form. I have been looking on the structure page and on the validation report without success.&#xA;I am thinking about deriving the protonation state from the ph information of the structure environment, in this case 7.2. But I am not sure if this make sense.&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2020-09-23T20:01:35.150" Title="Protonation state of pdb ligand" Tags="|proteins|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2066" PostTypeId="2" ParentId="2064" CreationDate="2020-08-23T20:46:33.927" Score="10" Body="&lt;p&gt;Determining a surface energy requires a few steps.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculate a bulk structure&lt;/li&gt;&#xA;&lt;li&gt;Cut a surface termination manually or using a tool&lt;/li&gt;&#xA;&lt;li&gt;Calculate the surface structure&lt;/li&gt;&#xA;&lt;li&gt;Calculate the surface energy&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I will try to provide some references to tools and methodology rather than attempting to describe this entire process since it is out of the scope of an SE question.&lt;/p&gt;&#xA;&lt;p&gt;To do these calculations you will want to use some DFT software such as &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/index.html&quot; rel=&quot;noreferrer&quot;&gt;GPAW&lt;/a&gt;, &lt;a href=&quot;https://www.vasp.at/&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt;, &lt;a href=&quot;http://www.castep.org/&quot; rel=&quot;noreferrer&quot;&gt;CASTEP&lt;/a&gt;, &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt;, or &lt;a href=&quot;https://molmod.ugent.be/deltacodesdft&quot; rel=&quot;noreferrer&quot;&gt;others&lt;/a&gt;.  I have just named the ones I have personally looked into but for these types of calculations any periodic code should work.  Most of these codes will interface with &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;, a python package which will generate bulk / surface structures for you.&lt;/p&gt;&#xA;&lt;p&gt;Here are some specific references to surface energy and DFT as a whole.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9780470447710&quot; rel=&quot;noreferrer&quot;&gt;Density Functional Theory: A Practical Introduction&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/8/36/005/meta&quot; rel=&quot;noreferrer&quot;&gt;Extracting convergent surface energies from slab calculations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.pdf&quot; rel=&quot;noreferrer&quot;&gt;Modeling materials using density functional theory&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It may be more straightforward to collaborate with someone that already does this work that has shared interests, unless you wish to do computational work yourself.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-23T20:46:33.927" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2067" PostTypeId="2" ParentId="2064" CreationDate="2020-08-24T00:51:20.147" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What is surface termination?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The following figure should give you a clear understanding of the surface termination. Note that the vacuum should be large enough to avoid the interaction between slabs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BHYva.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BHYva.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to make the surface termination of a crystal structure?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There are lots of methods to realize this. For example, you can use ASE that Tristan Maxson recommended. Materials Studio (MS) and VESTA can also do that. To understand the details, I recommend VESTA for your system. For VESTA, you can find many tutorials on YOUTUBE, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=ywR5pWqbllE&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=ywR5pWqbllE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=iGC_FizUVAs&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=iGC_FizUVAs&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-08-24T00:51:20.147" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2068" PostTypeId="2" ParentId="2015" CreationDate="2020-08-24T01:40:55.017" Score="6" Body="&lt;p&gt;This completely depends on what you're looking to model and the type of material you're modeling. A standard rule-of-thumb is generally no greater than 0.05 eV/Å for the maximum net force on any atom, but even this can often be too large, particularly (but not exclusively) in the case of highly flexible materials or molecular crystals. Personally, I like 0.03 eV/Å, but that's again based on experience for a very specific class of materials I study (MOFs). For other materials, that very well may not be sufficient. It will also depend heavily on the property of interest, with energies being less sensitive than vibrational modes as one example. There is unfortunately no proper answer to this question. You simply have to test it and see.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-08-24T01:40:55.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2069" PostTypeId="1" CreationDate="2020-08-24T04:10:30.150" Score="9" ViewCount="182" Body="&lt;p&gt;I have a fair idea of generating and modeling crystalline materials but what non commercial software programs can be used to model amorphous carbon of a specific dimension, say a &lt;span class=&quot;math-container&quot;&gt;$6\times6\times6$&lt;/span&gt; Å cube filled with amorphous carbon?&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="142" LastEditDate="2020-08-25T16:12:54.640" LastActivityDate="2020-08-27T15:41:30.410" Title="Which non-commercial softwares can be used to model amorphous carbon?" Tags="|software|molecular-modeling|open-source|software-recommendations|amorphous-materials|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2070" PostTypeId="1" CreationDate="2020-08-24T04:20:37.447" Score="10" ViewCount="1399" Body="&lt;p&gt;Typically one does velocity scaling to &amp;quot;heat&amp;quot; their sample with MD.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;How do we do this in VASP? Is it by setting the &lt;code&gt;SMASS=-1&lt;/code&gt; and &lt;code&gt;MDALGO=0&lt;/code&gt; tags?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Why can't we &amp;quot;heat&amp;quot; using a Nose-Hoover thermostat? &lt;code&gt;SMASS=0&lt;/code&gt;, &lt;code&gt;MDALGO=2&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;*when I tried both methods for &amp;quot;heating&amp;quot; (100 to 600 K) I found the total E increases in method 1 and decreases in method 2. Why is this the case? I'd expect energy to rise since I started in my ground state configuration. I'm using an NVT ensemble by the way (&lt;code&gt;ISIF=2&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Edit: I think my post was too long before so I simplified it&lt;/p&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2020-08-26T21:01:41.127" LastActivityDate="2020-09-02T20:37:07.650" Title="AIMD and velocity scaling in VASP" Tags="|molecular-dynamics|vasp|ab-initio-calculations|aimd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2071" PostTypeId="2" ParentId="1790" CreationDate="2020-08-24T04:25:30.420" Score="4" Body="&lt;p&gt;&lt;strong&gt;PATCHDOCK&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://bioinfo3d.cs.tau.ac.il/PatchDock/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Patchdock&lt;/a&gt; is a Molecular Docking Algorithm Based on Shape Complementarity Principles.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Web Based&lt;/li&gt;&#xA;&lt;li&gt;Over 100 possible docked structures with the first one being the best structure.&lt;/li&gt;&#xA;&lt;li&gt;Free&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Takes over 2.5 to 3 hours for the results to be sent to you via mail&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="707" LastActivityDate="2020-08-24T04:25:30.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2072" PostTypeId="2" ParentId="1790" CreationDate="2020-08-24T08:11:02.373" Score="3" Body="&lt;h2&gt;Open Drug Discovery Toolkit&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://oddt.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Open Drug Discovery Toolkit&lt;/a&gt; provides nice features of rescoring with different scoring function your docked poses. This is important due to the limitations of scoring functions.&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="52" LastEditDate="2020-08-24T21:08:00.727" LastActivityDate="2020-08-24T21:08:00.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2073" PostTypeId="1" AcceptedAnswerId="2075" CreationDate="2020-08-24T08:35:22.257" Score="5" ViewCount="1135" Body="&lt;p&gt;I need to calculate the RMSD between a co-crystallized ligand and my ligands and a non-co-crystallized ligand with GLIDE but I don't know how. Could someone explain to me how to do it? Many thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="5" LastEditDate="2020-08-24T17:41:24.110" LastActivityDate="2020-08-27T09:49:07.867" Title="How to calculate RMSD with GLIDE?" Tags="|docking|geometry|schrodinger-software|software-assistance|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2074" PostTypeId="1" CreationDate="2020-08-24T15:08:40.957" Score="4" ViewCount="90" Body="&lt;p&gt;What one can do to eliminate basis set superposition error (BSSE) if there is no chance to use larger basis sets or counterpoise correction.&lt;/p&gt;&#xA;" OwnerUserId="1213" LastActivityDate="2020-08-24T15:08:40.957" Title="What are the some other ways to handle BSSE rather than counterpoise correction and using larger basis sets?" Tags="|density-functional-theory|basis-sets|basis-set-superposition-error|" AnswerCount="0" CommentCount="9" ClosedDate="2020-08-24T16:09:56.363" ContentLicense="CC BY-SA 4.0" />
  <row Id="2075" PostTypeId="2" ParentId="2073" CreationDate="2020-08-24T19:10:25.687" Score="3" Body="&lt;p&gt;The software GLIDE is not used for RMSD calculation. GLIDE is dedicated to do small ligand/protein docking (rigid/rigid and flexible/rigid).&lt;/p&gt;&#xA;&lt;p&gt;You can calculate the RMSD by hand, using MAESTRO, CHIMERA and VMD interfaces (all free for academics) among many other software (also free).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-24T19:10:25.687" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2076" PostTypeId="2" ParentId="2065" CreationDate="2020-08-24T19:20:32.093" Score="1" Body="&lt;p&gt;In general, you have to decide the system pH for which you want to do the simulations, then, use a tool to protonate your system accordingly.&lt;/p&gt;&#xA;&lt;p&gt;The choosing of the pH will depends on the type of system, applicability, physiology, etc. For example, you could simulate a protein in physiological conditions (pH 7.2) but also simulate the behavior of the same protein in a sensor that works at different pH. In this case, you have to protonate two times.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-24T19:20:32.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2077" PostTypeId="1" CreationDate="2020-08-25T00:18:14.147" Score="12" ViewCount="991" Body="&lt;p&gt;I am running a NVT TIP3P simulation of water with 125 molecules of water in a 16-by-16-16 angstrom box with periodic boundary conditions on LAMMPS, with a time-step of 1 fs for 10 ps.&lt;/p&gt;&#xA;&lt;p&gt;Once the simulation runs, I extract the positions of these particles at each time-step into a .lammpstrj file, then process the data in python to evaluate the dipole moment of my ensemble.&lt;/p&gt;&#xA;&lt;p&gt;To evaluate dielectric constant &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, I will make use of the following relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \epsilon = 1+\frac{4\pi}{3k_bT} \left( \langle |M|^2\rangle-\langle |M| \rangle ^2 \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From classical electrodynamics, we know that &lt;span class=&quot;math-container&quot;&gt;$$\mathbf{M} = \sum_{i=1}^N q_i \mathbf{r}_i$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, can I still apply this formula to evaluate dipole moment when I have periodic boundary conditions?&lt;/strong&gt; Because of periodic boundary conditions, one portion of a molecule might be on one side of the box, while the other portion is on the other side of the box, and this I think leads to artificially large fluctuations, because the molecules are flickering on the edge of the box.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Given the position and charge of each atom in your simulation with periodic boundary conditions, what is the most effective algorithm to evaluate the dielectric constant?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2020-08-25T00:24:24.050" LastActivityDate="2023-09-25T15:22:54.607" Title="Algorithm for calculating dielectric constant of water TIP3P" Tags="|molecular-dynamics|statistical-thermodynamics|dielectric-constants|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2078" PostTypeId="1" CreationDate="2020-08-25T00:40:06.650" Score="12" ViewCount="328" Body="&lt;p&gt;Does there exist a program that can compare a series of (ideally&lt;code&gt;.xyz&lt;/code&gt;) files to each other to identify duplicate structures, and then identify the structures in some way?&lt;/p&gt;&#xA;&lt;p&gt;I know that &lt;code&gt;obabel&lt;/code&gt; has the &lt;code&gt;-oconfabreport&lt;/code&gt; function. However it only identifies if a duplicate exists (I have used &lt;code&gt;-xr&lt;/code&gt; for RMSD), but not the pair of structures themselves. Using this wouldn’t be bad, but across a large range of conformers it is difficult.&lt;/p&gt;&#xA;&lt;p&gt;I am looking to compare conformers of the same molecule, so no changes in number of atoms or charge.&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="142" LastEditDate="2020-09-05T12:33:47.263" LastActivityDate="2020-09-16T15:59:55.863" Title="How to classify structures and identify duplicates from a set of .xyz files?" Tags="|software-recommendations|" AnswerCount="2" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="2079" PostTypeId="2" ParentId="2077" CreationDate="2020-08-25T04:35:49.467" Score="4" Body="&lt;p&gt;Molecules will not be on both sides of the box at once because this is explicitly prevented by most good MD packages. You can calculate distances which take into consideration the PBC. For example, here is a code to calculate all the pairwise distances with periodic boundary conditions (x_size = [16,16,16])&lt;/p&gt;&#xA;&lt;p&gt;This is modified from &lt;a href=&quot;https://en.wikipedia.org/wiki/Periodic_boundary_conditions&quot; rel=&quot;nofollow noreferrer&quot;&gt;periodic boundary conditions on Wikipedia&lt;/a&gt;. I've essentially added a list to store all the pairwise distances, and calculated the distance as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$r = \sum_i \sqrt{(x_i-x_0)^2 + (y_i-y_0)^2 + (z_i-z_0)^2 } $&lt;/span&gt; with the &lt;code&gt;np.linalg.norm&lt;/code&gt; function.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;r=[]&#xA;for i in range(0, N):&#xA;     for j in range(0, N):&#xA;        dx1 = x[j] - x[i]&#xA;        dx = np.mod(dx1, x_size * 0.5)&#xA;        r.append(np.linalg.norm(dx))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;np.mod&lt;/code&gt; is choosing the distance which is the smallest distance. It is the remainder of dividing the distance by &lt;code&gt;x_size/2&lt;/code&gt;. So if the closest molecule is one image away, it is further than &lt;code&gt;x_size/2&lt;/code&gt;, from the center of the box. Therefore, dividing by &lt;code&gt;x_size/2&lt;/code&gt; removes this extra amount.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2020-08-25T16:43:20.373" LastActivityDate="2020-08-25T16:43:20.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2080" PostTypeId="1" CreationDate="2020-08-25T14:57:48.613" Score="13" ViewCount="12915" Body="&lt;p&gt;I have a problem with geometry optimization in Gaussian software with M062X method. The structure was smoothly optimized using M062X/Gen. Nevertheless, I need very accurate results so afterwards the job was submitted once more, but this time with &lt;code&gt;Opt=VeryTight&lt;/code&gt; and &lt;code&gt;Int=UltraFine&lt;/code&gt; keywords. Nevertheless, I got the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Optimization stopped.&#xA;    -- Number of steps exceeded,  NStep= 126&#xA;    -- Flag reset to prevent archiving.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;...  and at the end:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error termination request processed by link 9999.&#xA;Error termination via Lnk1e in /usr/local/gaussian/2016-C.01/g16/l9999.exe at Tue Aug 25 16:05:14 2020.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What can I do? The input is following and, as I told, geometry is taken directly from the previous step which was performed using the same method and basis but without &lt;code&gt;Opt=VeryTight&lt;/code&gt; and &lt;code&gt;Int=UltraFine&lt;/code&gt; keywords.&lt;/p&gt;&#xA;&lt;p&gt;I'm stuck, don't know what to do. Any idea?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=vacCFI_7_8.chk&#xA;#p M062X/Gen&#xA;opt=(Cartesian,maxcycles=200,verytight,restart) freq&#xA;int=ultrafine&#xA;geom=check guess=read&#xA;scf=xqc&#xA;&#xA;vacCFI_7_8&#xA;&#xA;0 1&#xA;&#xA;H     0&#xA;S   3   1.00&#xA;     34.0613410              0.60251978D-02&#xA;      5.1235746              0.45021094D-01&#xA;      1.1646626              0.20189726&#xA;S   1   1.00&#xA;      0.32723041             1.0000000&#xA;S   1   1.00&#xA;      0.10307241             1.0000000&#xA;P   1   1.00&#xA;      0.8000000              1.0000000&#xA;P   1   1.00&#xA;      0.95774129632D-01      1.0000000&#xA;****&#xA;C     0&#xA;S   6   1.00&#xA;  13575.3496820              0.22245814352D-03&#xA;   2035.2333680              0.17232738252D-02&#xA;    463.22562359             0.89255715314D-02&#xA;    131.20019598             0.35727984502D-01&#xA;     42.853015891            0.11076259931&#xA;     15.584185766            0.24295627626&#xA;S   2   1.00&#xA;      6.2067138508           0.41440263448&#xA;      2.5764896527           0.23744968655&#xA;S   1   1.00&#xA;      0.57696339419          1.0000000&#xA;S   1   1.00&#xA;      0.22972831358          1.0000000&#xA;S   1   1.00&#xA;      0.95164440028D-01      1.0000000&#xA;S   1   1.00&#xA;      0.48475401370D-01      1.0000000&#xA;P   4   1.00&#xA;     34.697232244            0.53333657805D-02&#xA;      7.9582622826           0.35864109092D-01&#xA;      2.3780826883           0.14215873329&#xA;      0.81433208183          0.34270471845&#xA;P   1   1.00&#xA;      0.28887547253           .46445822433&#xA;P   1   1.00&#xA;      0.10056823671           .24955789874&#xA;D   1   1.00&#xA;      1.09700000             1.0000000&#xA;D   1   1.00&#xA;      0.31800000             1.0000000&#xA;D   1   1.00&#xA;      0.90985336424D-01      1.0000000&#xA;F   1   1.00&#xA;      0.76100000             1.0000000&#xA;****&#xA;O     0&#xA;S   6   1.00&#xA;  27032.3826310              0.21726302465D-03&#xA;   4052.3871392              0.16838662199D-02&#xA;    922.32722710             0.87395616265D-02&#xA;    261.24070989             0.35239968808D-01&#xA;     85.354641351            0.11153519115&#xA;     31.035035245            0.25588953961&#xA;S   2   1.00&#xA;     12.260860728            0.39768730901&#xA;      4.9987076005           0.24627849430&#xA;S   1   1.00&#xA;      1.1703108158           1.0000000&#xA;S   1   1.00&#xA;      0.46474740994          1.0000000&#xA;S   1   1.00&#xA;      0.18504536357          1.0000000&#xA;S   1   1.00&#xA;      0.70288026270D-01      1.0000000&#xA;P   4   1.00&#xA;     63.274954801            0.60685103418D-02&#xA;     14.627049379            0.41912575824D-01&#xA;      4.4501223456           0.16153841088&#xA;      1.5275799647           0.35706951311&#xA;P   1   1.00&#xA;      0.52935117943           .44794207502&#xA;P   1   1.00&#xA;      0.17478421270           .24446069663&#xA;P   1   1.00&#xA;      0.51112745706D-01      1.0000000&#xA;D   1   1.00&#xA;      2.31400000             1.0000000&#xA;D   1   1.00&#xA;      0.64500000             1.0000000&#xA;D   1   1.00&#xA;      0.14696477366          1.0000000&#xA;F   1   1.00&#xA;      1.42800000             1.0000000&#xA;****&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is .xyz geometry:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O         -4.44721        1.17772       -0.00003&#xA;C         -3.68389        0.06486       -0.00000&#xA;O         -4.16201       -1.03886        0.00003&#xA;C         -2.24755        0.39366       -0.00001&#xA;C         -1.34975       -0.59256        0.00001&#xA;C          0.10468       -0.46469        0.00000&#xA;C          0.87630       -1.62398       -0.00001&#xA;C          2.26287       -1.55445       -0.00001&#xA;C          2.88570       -0.32236       -0.00001&#xA;O          4.23767       -0.13929       -0.00001&#xA;C          2.12513        0.85396        0.00001&#xA;O          2.73759        2.06167        0.00002&#xA;C          0.74994        0.77741        0.00001&#xA;H         -5.36979        0.88538       -0.00002&#xA;H         -1.98671        1.44280       -0.00003&#xA;H         -1.74093       -1.60620        0.00003&#xA;H          0.38777       -2.58968       -0.00001&#xA;H          2.86062       -2.45869       -0.00002&#xA;H          4.69415       -0.98608       -0.00002&#xA;H          3.69353        1.92694        0.00001&#xA;H          0.19248        1.70441        0.00002&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user1247" LastEditorDisplayName="user1247" LastEditDate="2020-08-25T20:07:27.367" LastActivityDate="2020-08-31T19:43:37.610" Title="How to fix Error Link9999 in Gaussian" Tags="|density-functional-theory|quantum-chemistry|computational-chemistry|gaussian|" AnswerCount="1" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="2081" PostTypeId="2" ParentId="2069" CreationDate="2020-08-25T15:55:05.350" Score="8" Body="&lt;p&gt;I am no expert in this area, but just to get the ball rolling...&lt;/p&gt;&#xA;&lt;p&gt;The main issue simulating disordered phases is that one typically needs large simulation cells to capture the relevant length scales associated with the disorder of interest. Large simulation boxes typically mean some compromise in terms of the computational method you can use. For example, using traditional DFT methods is limited to about 1,000 atoms.&lt;/p&gt;&#xA;&lt;p&gt;In this context, in recent years there has been a lot of work on developing machine learning potentials (a very generic term) parametrized with DFT calculations, that give accuracies similar to those of DFT but at much smaller computational expense, enabling simulations like the ones you are interested in. To highlight an example, I will pick the Gaussian Approximation Potential (GAP) scheme, for which you can find the code &lt;a href=&quot;https://libatoms.github.io/GAP/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I chose GAP for my answer because I recently read a paper using it that was directly looking at what you are interested in, amorphous carbon. You can find the paper &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.094203&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-25T15:55:05.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2082" PostTypeId="1" CreationDate="2020-08-26T03:41:26.227" Score="8" ViewCount="321" Body="&lt;p&gt;I'm trying to write a program to calculate the neighbor lists of crystal systems. I found a few  codes that are able to calculate it for orthogonal systems. How can I do it for non-orthogonal cells ?&lt;/p&gt;&#xA;&lt;p&gt;The first link mentions a transformation from non-orthogonal to orthogonal representation. If I do this transformation how can I get back to the original lattice with the corresponding distances ?&lt;/p&gt;&#xA;&lt;p&gt;Some examples that I found interesting are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.acclab.helsinki.fi/%7Eknordlun/moldyn/moldyn_course_everything.pdf&quot; rel=&quot;noreferrer&quot;&gt;Some theory and parts of codes&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://cacs.usc.edu/education/cs596/src/md/md.c&quot; rel=&quot;noreferrer&quot;&gt;An example of a simplistic neighbor list &lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://cacs.usc.edu/education/cs596/src/lmd/lmd.c&quot; rel=&quot;noreferrer&quot;&gt;A more elaborated version using linked list&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1249" LastActivityDate="2020-08-26T12:19:01.133" Title="How to calculate the orthogonal representation of a HCP cell?" Tags="|molecular-dynamics|crystal-structure|solid-state-physics|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2083" PostTypeId="1" AcceptedAnswerId="2096" CreationDate="2020-08-26T06:59:50.483" Score="11" ViewCount="545" Body="&lt;p&gt;This question is in relation to &lt;a href=&quot;https://chemistry.stackexchange.com/questions/139171/anomalous-boiling-point-of-iso-alkanes&quot;&gt;Anomalous boiling point of &amp;quot;iso-&amp;quot; alkanes&lt;/a&gt; on Chemistry SE.&lt;/p&gt;&#xA;&lt;p&gt;I want to compute the boiling point of the different isomers of an n-carbon alkane to check what factors are affecting the boiling point since the empirically determined density trend and boiling point trend are not the same.&lt;/p&gt;&#xA;" OwnerUserId="1174" LastEditorUserId="181" LastEditDate="2020-08-29T19:15:16.937" LastActivityDate="2020-09-01T06:57:46.020" Title="How does one compute the boiling point of a liquid made of a particular molecule?" Tags="|molecular-dynamics|lammps|monte-carlo|intermolecular-forces|thermodynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2084" PostTypeId="2" ParentId="2082" CreationDate="2020-08-26T12:13:16.173" Score="7" Body="&lt;p&gt;I understand that you are trying to implement &lt;a href=&quot;https://en.wikipedia.org/wiki/Cell_lists&quot; rel=&quot;noreferrer&quot;&gt;cell lists&lt;/a&gt;. For orthogonal unit cell (or even better - cubic) the cells that subdivide the unit cell are nicely aligned with the unit cell. Wikipedia has this illustration:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/File:CellLists_Ghosts.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qKFMym.png&quot; alt=&quot;cubic cell lists&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a non-orthogonal unit cell the calculations are more complex, but you can still use a rectangular box divided into cells. Here is an illustration from the &lt;a href=&quot;http://manual.gromacs.org/documentation/2016/manual-2016.pdf&quot; rel=&quot;noreferrer&quot;&gt;Gromacs manual&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ichFk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ichFk.png&quot; alt=&quot;non-orthogonal cell lists&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you could subdivide the unit cell into cells that have the same angles as the unit cell. It would make some calculations simpler, but the cells would need to be larger to assure that the search radius doesn't go beyond neighboring cells. So it'd probably be slower overall.&lt;/p&gt;&#xA;&lt;p&gt;I'm aware that some math or pseudo-code would be more helpful, but skipped it for the same reason it is skipped in books – these things are tedious and are better left as an exercise for the reader. :-)&lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="792" LastEditDate="2020-08-26T12:19:01.133" LastActivityDate="2020-08-26T12:19:01.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2085" PostTypeId="1" CreationDate="2020-08-26T16:22:12.410" Score="8" ViewCount="109" Body="&lt;p&gt;In spectroscopy it is common to describe excited-states as ionic or covalent.&lt;/p&gt;&#xA;&lt;p&gt;I understand the  concept on a toy model e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; with a minimal basis set&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Phi_0 &amp;amp;= [\chi_A(1) + \chi_B(1)][\chi_A(2) + \chi_B(2)]\tag{1} \\&#xA; &amp;amp;= \underbrace{\chi_A(1)\chi_A(2) + \chi_B(1)\chi_B(2)}_{\mathrm{Ionic \ Part}} + \underbrace{\chi_A(1)\chi_B(2) + \chi_B(1)\chi_A(2)}_{\mathrm{Covalent \ Part}}\tag{2}&#xA;\end{align}&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; are the AOs, &lt;span class=&quot;math-container&quot;&gt;$A,B$&lt;/span&gt; are the atom labels, and &lt;span class=&quot;math-container&quot;&gt;$1,2$&lt;/span&gt; are the electron labels.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However, how can I determine ionic/covalent for more complex molecules using computations?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, I am doing complete-active space self-consistent field calculations and I have the CI coefficients &lt;span class=&quot;math-container&quot;&gt;$c_i$&lt;/span&gt; for the different determinants e.g. here are the &lt;span class=&quot;math-container&quot;&gt;$c_i$&lt;/span&gt; coefficients for the first excited-state&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0.70266226570264  X54 A55 B56&#xA;    0.70266226570264  X54 B55 A56&#xA;    0.07890494054450  A54 B55 X56&#xA;    0.07890494054450  B54 A55 X56&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; refers to an &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; electron, B a &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; electron, and X doubly occupied orbital.&lt;/p&gt;&#xA;&lt;p&gt;I've determined using symmetry that the first excited-state is of &lt;span class=&quot;math-container&quot;&gt;$B_u$&lt;/span&gt; symmetry (orbital 55=&lt;span class=&quot;math-container&quot;&gt;$b_g$&lt;/span&gt;, orbital 56=&lt;span class=&quot;math-container&quot;&gt;$a_u$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$b_g\times a_u=B_u$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-10-19T20:45:07.417" LastActivityDate="2021-10-19T20:45:07.417" Title="How to classify ionic and covalent excited-states?" Tags="|symmetry|spectroscopy|configuration-interaction|casscf|photochemistry|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-07T03:04:08.193" ContentLicense="CC BY-SA 4.0" />
  <row Id="2086" PostTypeId="2" ParentId="2069" CreationDate="2020-08-26T18:59:56.287" Score="7" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$6\times6\times6$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$Å^3$&lt;/span&gt; is a very small size for an amorphous material, which supposedly has no long range order. But the minimal size that yields a usefull amorphous sample depends on the material and the property you want to study.&lt;/p&gt;&#xA;&lt;p&gt;The difficulty usually lies in the generation of the amorphous sample(s) that you want to investigate. Here, the traditional approach is melt-and-quench (MQ), where you randomize the positions of the atoms with molecular dynamics (MD) well above the melting temperature of the material. Then the melt is cooled rapidly, cooling rates often are in the range of 1 to 50 K/ps. &lt;a href=&quot;https://docs.quantumatk.com/tutorials/amorphous_structures/amorphous_structures.html&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a tutorial that walks you through the steps, for a commercial software though, but this is the only tutorial that I know of. You should be able to replicate the steps with any MD (force-field, semi-empirical, DFT) package that you like.&lt;/p&gt;&#xA;&lt;p&gt;The MD can be performed with DFT for small samples and for short MD times, several dozen of ps at the most. Otherwise, the MQ can be performed with classical MD given the availability of a suitable parametrization or with a semi-empirical method such as DFTB. Afterwards, the sample can be further annealed or optimized, and investigated at any level of theory you desire.&lt;/p&gt;&#xA;&lt;p&gt;As long as the software can handle a few dozen to a 100s of atoms you can use it to study amorphous materials.&lt;/p&gt;&#xA;" OwnerUserId="295" LastActivityDate="2020-08-26T18:59:56.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2087" PostTypeId="1" AcceptedAnswerId="2088" CreationDate="2020-08-26T19:45:56.950" Score="9" ViewCount="566" Body="&lt;p&gt;I was looking at the data on this &lt;a href=&quot;https://www.topologicalquantumchemistry.org/#/detail/15852&quot; rel=&quot;noreferrer&quot;&gt;page&lt;/a&gt; for a NiWO4 calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DSHG3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DSHG3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I can see unoccupied bands near the fermi level that appear to be below the band gap.  What does this actually mean physically or is it an artifact of DFT?  I suspect this may be related to it being a topological insulator.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-27T10:39:58.520" Title="Can the fermi level of a semiconductor be below the valence band?" Tags="|density-functional-theory|band-structure|topological-insulators|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2088" PostTypeId="2" ParentId="2087" CreationDate="2020-08-26T20:10:09.170" Score="9" Body="&lt;p&gt;There are two different questions in your post:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The band structure that you are reproducing is not that of a semiconductor. There are bands crossing the Fermi level, so the material is metallic. Looking at the link that you include in the post, there is a plot of the density of states (DOS) right next to the plot you reproduce here of the band structure, and in the DOS it is also clear that the Fermi level is within a group of bands, so the material is a metal.&lt;/li&gt;&#xA;&lt;li&gt;Whether the material &lt;em&gt;really&lt;/em&gt; is a metal or this is an artifact of DFT is a different question. Semilocal DFT does underestimate band gaps, so if we were to assume that the calculations to generate this band structure are semilocal DFT, it could be that repeating them with a hybrid functional or with many-body perturbation theory techniques a gap opened and the system became a semiconductor. Then again, perhaps the system would stay metallic.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;These points are not related to the material being a topological insulator: a topological insulator must have an insulating bulk, and the material you are looking at is a metal.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-08-27T10:39:58.520" LastActivityDate="2020-08-27T10:39:58.520" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2089" PostTypeId="1" CreationDate="2020-08-26T21:03:36.057" Score="9" ViewCount="385" Body="&lt;p&gt;I am running a molecular dynamics simulation of water in TIP3P, and I am storing the positions of my particles in a 2D array called &lt;code&gt;relevant_positions&lt;/code&gt;. The number of particles in my simulation is &lt;code&gt;numPart&lt;/code&gt;. I am running a simulation from &lt;code&gt;t=0&lt;/code&gt; to &lt;code&gt;t=n_time_points-1&lt;/code&gt;. In effect, I have snapshots of positions of particles at &lt;code&gt;n_time_points&lt;/code&gt; time points.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to evaluate the MSD of my simulation, and this is the code I am using:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for d in range(1, n_time_points):&#xA;    for i in range(0, n_time_points-d):&#xA;        msd[d] += np.sum(np.square(\&#xA;        relevant_positions[numPart*(d+i):numPart*(d+i+1),:] -\&#xA;        relevant_positions[numPart*i:numPart*(i+1),:]))&#xA;    msd[d] = msd[d]/(n_time_points-d) &#xA;&#xA;msd = msd/numPart&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result I am getting with this is:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Ldr0y.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ldr0y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I expect this to be a straight line, but it clearly is not. What am I doing incorrectly here?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2020-08-27T19:28:24.470" Title="Evaluating the MSD of my simulation" Tags="|molecular-dynamics|python|algorithms|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2090" PostTypeId="5" CreationDate="2020-08-26T21:25:33.190" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-26T21:25:33.190" LastActivityDate="2020-08-26T21:25:33.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2091" PostTypeId="4" CreationDate="2020-08-26T21:25:33.190" Score="0" Body="Questions of the form &quot;Is there a software that can do...?&quot; and similar." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-26T21:25:33.190" LastActivityDate="2020-08-26T21:25:33.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2092" PostTypeId="2" ParentId="2089" CreationDate="2020-08-26T21:27:06.690" Score="5" Body="&lt;p&gt;I have no prior experience with molecular dynamics really, but to get you started I have found a resource with a &lt;a href=&quot;http://home.ustc.edu.cn/%7Elipai/scripts/python_scripts/python_msd.html&quot; rel=&quot;noreferrer&quot;&gt;pretty detailed method&lt;/a&gt; of calculating the MSD (Mean square displacement).&lt;/p&gt;&#xA;&lt;p&gt;Looking at your plot, I suspect that periodic boundary conditions are somehow causing you a problem.  It looks like it converges to a value that happens when everything scatters as far as it can on average from its starting position.  When an atom wraps around the cell, its position will jump from a large number (such as 10.5 angstroms) to a small number (0.1 angstroms).  This will be seen as displacement by your code, I believe.&lt;/p&gt;&#xA;&lt;p&gt;If you want a really bad solution to fix your code though, you could throw away any displacements greater than a specific value corresponding to something like half the unit cell (an impossible distance to move in your MD simulation).  This would remove the problematic data points.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms.get_all_distances&quot; rel=&quot;noreferrer&quot;&gt;Using ASE for distance calculations&lt;/a&gt; between atoms for each timestep would allow you to account for periodic boundary conditions as it supports taking distances with regards to it.  This would be a much better solution.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-26T21:27:06.690" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2093" PostTypeId="1" AcceptedAnswerId="2113" CreationDate="2020-08-26T21:32:23.607" Score="20" ViewCount="2716" Body="&lt;p&gt;Most of the artificial muscles are based on either pneumatic power or nylon fibers being heated so they contract. These methods consume more energy than what can be utilized.&lt;/p&gt;&#xA;&lt;p&gt;Likewise, in early days when the light bulbs that produced photons by heating the filament (which also requires considerable energy), they were replaced by energy efficient light-emitting diodes.&lt;/p&gt;&#xA;&lt;p&gt;Are there any promising materials that can do the same for artificial muscles by converting electric energy directly to actuation instead of into heat and actuation being the side product of the heat itself?&lt;/p&gt;&#xA;" OwnerUserId="1251" LastEditorUserId="5" LastEditDate="2020-08-27T22:26:08.390" LastActivityDate="2020-08-28T17:55:58.793" Title="Artificial muscles and their efficiency" Tags="|materials-engineering|" AnswerCount="5" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2094" PostTypeId="2" ParentId="2093" CreationDate="2020-08-26T21:44:57.053" Score="15" Body="&lt;p&gt;This question is more about engineering than materials modeling, but I will try to supply a partial answer and let others decide if it isn't.  You may get a better answer at Physics.SE.&lt;/p&gt;&#xA;&lt;p&gt;My first thought would be that hydraulic power is a straightforward improvement over pneumatic since there is less energy wasted due to the compression of air.  But if we want to move to a more materials based way of thinking you can also look at piezoelectric actuators.&lt;/p&gt;&#xA;&lt;p&gt;A piezoelectric actuator is a linear (typically) motor that works by applying a voltage to a material that can contract or expand in response to the voltage.  This is something that I imagine could actually be modeled to some degree using computational methods such as DFT.  These types of motors are currently used for some applications already, but not in the same manner as muscle fiber.  They are used for really fine control of small movements (in the nm range).&lt;/p&gt;&#xA;&lt;p&gt;Since these materials actually work in a similar manner to a muscle, I think these are the &amp;quot;LED&amp;quot;s of a muscle fiber.  A quick google search gives a variety of efficiencies for electric to mechanical work but it seems that it is somewhere around &lt;a href=&quot;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7728053&quot; rel=&quot;noreferrer&quot;&gt;25%&lt;/a&gt;.  Surely this is higher than needing to constantly heat a nylon fiber for example, but I am not sure.  This also may have a lot of room for improvement, but I am not an expert in the topic.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-08-26T21:46:11.697" LastActivityDate="2020-08-26T21:46:11.697" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2095" PostTypeId="2" ParentId="2093" CreationDate="2020-08-27T00:18:39.740" Score="10" Body="&lt;h3&gt;Photochemical &amp;quot;Muscles&amp;quot;&lt;/h3&gt;&#xA;&lt;p&gt;All motors require energy, and you mentioned that heat maybe problematic because of heat loss. So you might be interested in photochemistry. These reactions can be made to be highly photon (i.e. energy) efficient and directional.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Feringa Motors&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A promising technology for artificial muscles are those based off the light-driven  molecular motors such as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Synthetic_molecular_motor&quot; rel=&quot;nofollow noreferrer&quot;&gt;Feringa rotary motors&lt;/a&gt;. For example, the Feringa motor can be utilized to produce &amp;quot;Macroscopic contraction of a gel induced by the integrated motion of light-driven molecular motors&amp;quot; &lt;sup&gt;[1]&lt;/sup&gt;. This is almost exactly how a muscle fiber works. Essentially, there are three components: a) the motor which turns unidirectionally with light and heat, b) two polymer strands which are connected to the opposite ends of the motor, and c) the modulator which binds together the end of the polymer. Therefore, when the motor spins it causes the polymer strands to wrap around each other and to contract. Furthermore, when you want to uncontract/uncoil the strands you open the modulator with a different wavelength of light.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Optomechanical devices&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another great example are &lt;strong&gt;&amp;quot;optomechanical devices&amp;quot;&lt;/strong&gt; which can produce macroscopic motion. My favorite is the &amp;quot;Photoinduced peeling of crystals&amp;quot;&lt;sup&gt;[2]&lt;/sup&gt;. See this&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://vimeo.com/319451571&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qYpKM.png&quot; alt=&quot;Video thumbnail&quot; /&gt;&lt;strong&gt;Photoinduced peeling a molecular crystal&lt;/strong&gt; on Chemistry World&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another  author to look at for optomechanics is the Professor Garcia-Garibay, he has been interested in crystalline artificial muscles. For example, in reference &lt;sup&gt;[3]&lt;/sup&gt; is a picture similar to this so it deserves a citation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rFRBI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rFRBI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Rotaxane Shuttles&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, rotaxane is a mechanically interlocked molecular architecture that can be used to produce macroscopic motion similar to a muscle. These typically operate by changing the protonation states. But this action can be performed by either chemical or photochemical inputs (e.g. a photoacid!)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://commons.wikimedia.org/w/index.php?title=File%3ARot.ogv&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qUtqf.png&quot; alt=&quot;Video thumbnail&quot; /&gt;&lt;strong&gt;The operation of a molecular shuttle&lt;/strong&gt; on Wikipedia&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ke, C. A Light-Powered Clockwork. Nat. Nanotechnol. 2017, 12 (6), 504–506. &lt;a href=&quot;https://doi.org/10.1038/nnano.2017.44&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/nnano.2017.44&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Tong, F.; Al-Haidar, M.; Zhu, L.; Al-Kaysi, R. O.; Bardeen, C. J. Photoinduced Peeling of Molecular Crystals. Chem. Commun. 2019, 55 (26), 3709–3712. &lt;a href=&quot;https://doi.org/10.1039/c8cc10051a&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1039/c8cc10051a&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Vogelsberg, C. S.; Garcia-Garibay, M. A. Crystalline Molecular Machines: Function, Phase Order, Dimensionality, and Composition. Chem. Soc. Rev. 2012, 41 (5), 1892–1910. &lt;a href=&quot;https://doi.org/10.1039/c1cs15197e&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1039/c1cs15197e&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-08-27T22:27:34.603" LastActivityDate="2020-08-27T22:27:34.603" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2096" PostTypeId="2" ParentId="2083" CreationDate="2020-08-27T04:46:19.273" Score="14" Body="&lt;p&gt;I would like to start off by saying this is first and foremost a thermodynamic problem.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, and as a result of thermodynamics, refer to &lt;a href=&quot;https://en.wikipedia.org/wiki/Phase_rule&quot; rel=&quot;noreferrer&quot;&gt;Gibbs Phase Rule&lt;/a&gt; which says&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;F = C - P + 2&#xA;\end{equation}&lt;/span&gt;&#xA;Where F = degrees of freedom, C = number of components, and P = number of phases. You seem to be after a pure liquid so &lt;span class=&quot;math-container&quot;&gt;$C=1$&lt;/span&gt;, and, you are after boiling, so there is a liquid and vapor, so, &lt;span class=&quot;math-container&quot;&gt;$P=2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hence, &lt;span class=&quot;math-container&quot;&gt;$F = 1-2 +2 = 1$&lt;/span&gt;. &lt;em&gt;You have 1 degree of freedom you must set before you can do anything&lt;/em&gt;. You need to set temperature, or pressure, or some other intensive variable because it turns out a pure liquid of anything can boil at many different conditions - infinitely many. Water only boils at 100 Celsius if the pressure is fixed at 1 bar. If you change the pressure, the water will boil at a different temperature.&lt;/p&gt;&#xA;&lt;h2&gt;Solving for the boiling point&lt;/h2&gt;&#xA;&lt;p&gt;The thermodynamics is the main thing. At the boiling point the chemical potential, pressure and temperature of the molecule will be the same in both phases. So, you need to calculate the chemical potential and either pressure or temperature depending on what you decided to set as your degree of freedom. You can use anything for this. You can use&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.britannica.com/science/thermodynamics/Equations-of-state&quot; rel=&quot;noreferrer&quot;&gt;macroscopic thermodynamic equations of state&lt;/a&gt; to calculate P,V or T and chemical potential.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.sklogwiki.org/SklogWiki/index.php/Gibbs_ensemble_Monte_Carlo&quot; rel=&quot;noreferrer&quot;&gt;Gibbs Ensemble Monte Carlo&lt;/a&gt; which simultaneously simulates a vapor and liquid simulations and does many fast and inaccurate chemical potential trial calculations via particle swaps between boxes, and also measures P to ensure all equilibrium criteria are met.&lt;/li&gt;&#xA;&lt;li&gt;You can use Molecular dynamics with Free energy calculations to manually calculate the free energy of the particles and from this directly calculate the chemical potentials in the vapor and liquid for the molecule of interest, it is trivial to calculate the P, T , V or whatever else you need in MD. While Gibbs ensemble does thousands of quick, somewhat sloppy chemical potential calculations, this will do very expensive and accurate, single calculations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are vapor-liquid coexistence methods for essentially tracing the boiling point as a function of a variable and these typically use free energy methods such as thermodynamic integration and free energy perturbation (because these all directly lead to chemical potentials which is the overarching requirement).&lt;/p&gt;&#xA;&lt;p&gt;David Kofke is a great researcher whose work you should look into if you are wanting to use molecular based force-field models, for instance &lt;a href=&quot;https://www.researchgate.net/publication/228565899_A_comparison_of_molecular-based_models_to_determine_vapor-liquid_phase_coexistence_in_hydrogen_fluoride&quot; rel=&quot;noreferrer&quot;&gt;A comparison of molecular-based models to determine vapor-liquid phase coexistence in hydrogen fluoride&lt;/a&gt;. There are many others who do molecular based modelling, but you can use any scale of modelling so long as the thermodynamic requirements are met - and again, this comes down to chemical potentials being equal in each phase, as well as typically T and pressure. You need to specify 1 and only 1 intensive variable (T, P, density etc).&lt;/p&gt;&#xA;&lt;h2&gt;Final Note:&lt;/h2&gt;&#xA;&lt;p&gt;Some people like to use fugacity rather than chemical potential. I do not know why. Fugacity is theoretically fine to use, but such a mess to think about.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2020-09-01T06:57:46.020" LastActivityDate="2020-09-01T06:57:46.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2097" PostTypeId="2" ParentId="2093" CreationDate="2020-08-27T05:48:29.957" Score="6" Body="&lt;h3&gt;Pneumatic &amp;quot;muscles&amp;quot;&lt;/h3&gt;&#xA;&lt;p&gt;Basically, these involve an inflatable tube (essentially a long balloon) surrounded by a tube of fiber mesh that is anchored to the surfaces that force will be exerted upon. When the inflatable tube is filled with air using a pneumatic pump, it expands until it reaches the mesh. This puts the mesh under a tensile force around the radius of the tube, contracting its length and exerting a force upon its mounting points.&lt;/p&gt;&#xA;&lt;p&gt;These &amp;quot;muscles&amp;quot; aren't particularly powerful, and have a very limited range of motion, but they do work, and don't involve converting electricity into heat as the mechanism of the motion. The Hacksmith, for instance, used them to build an arm exoskeleton that was capable of lifting a few hundred pounds a few inches.&lt;/p&gt;&#xA;" OwnerUserId="1253" LastEditorUserId="5" LastEditDate="2020-08-27T22:27:05.920" LastActivityDate="2020-08-27T22:27:05.920" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2098" PostTypeId="1" AcceptedAnswerId="2121" CreationDate="2020-08-27T09:41:15.707" Score="5" ViewCount="137" Body="&lt;p&gt;I would like to know if anyone knows of a material where the conductivity drops when the current increases? Usually, it's the opposite.&lt;/p&gt;&#xA;" OwnerUserId="1254" LastEditorUserId="5" LastEditDate="2020-08-27T14:55:39.250" LastActivityDate="2020-08-28T15:24:46.837" Title="Is there a material where the conductivity drops when the current increases?" Tags="|physical-properties-of-materials|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2100" PostTypeId="2" ParentId="2093" CreationDate="2020-08-27T10:24:52.237" Score="9" Body="&lt;p&gt;A research group lead by &lt;a href=&quot;https://profiles.utdallas.edu/ray.baughman&quot; rel=&quot;nofollow noreferrer&quot;&gt;Prof. Ray Baughman&lt;/a&gt;, from the University of Texas at Dallas, uses a yarn of carbon nanotubes. From the abstract of one of its works&lt;sup&gt;1&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We show that an electrolyte-filled twist-spun carbon nanotube yarn,&#xA;much thinner than a human hair, functions as a torsional artificial&#xA;muscle in a simple three-electrode electrochemical system, providing a&#xA;reversible 15,000° rotation and 590 revolutions per minute. A&#xA;hydrostatic actuation mechanism, as seen in muscular hydrostats in&#xA;nature, explains the simultaneous occurrence of lengthwise&#xA;contractiona nd torsional rotation during the yarn volume increase&#xA;caused by electrochemical double-layercharge injection. The use of a&#xA;torsional yarn muscle as a mixer for a fluidic chip is demonstrated.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;A similar idea is used by the &lt;a href=&quot;http://ipri.uow.edu.au/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Intelligent Polymer Research Institute&lt;/a&gt; in Australia (&lt;a href=&quot;https://asknature.org/idea/carbon-nanotube-artificial-muscle/&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The image below is from a mini-review authored by Prof. Baughman&lt;sup&gt;2&lt;/sup&gt;, showing SEM images of (a) a CNT sheet being drawn from a CNT forest (which is on the left in this image), (b) Fermat-type twist insertion during spinning a yarn from a CNT forest, (c) a single-ply, twisted, non-coiled CNT yarn, and (d) a single-ply, coiled yarn&lt;/p&gt;&#xA;&lt;img src=&quot;https://media.springernature.com/full/springer-static/image/art%3A10.1186%2Fs40580-014-0036-0/MediaObjects/40580_2014_36_Fig1_HTML.gif&quot; width=&quot;600&quot;&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Javad Foroughi, &lt;em&gt;et al.&lt;/em&gt; &lt;em&gt;Torsional Carbon NanotubeArtificial Muscles&lt;/em&gt;, Science, 334, 494, 2011 (DOI: &lt;a href=&quot;http://dx.doi.org/10.1126/science.1211220&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1126/science.1211220&lt;/a&gt;, &lt;a href=&quot;https://www.researchgate.net/publication/51716206_Torsional_Carbon_Nanotube_Artificial_Muscles&quot; rel=&quot;nofollow noreferrer&quot;&gt;ResearchGate&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Jae Ah Lee, Ray H Baughman &amp;amp; Seon Jeong Kim, &lt;em&gt;High performance electrochemical and electrothermal artificial muscles from twist-spun carbon nanotube yarn&lt;/em&gt;. Nano Convergence, 2, 8, 2015 (DOI: &lt;a href=&quot;https://dx.doi.org/10.1186/s40580-014-0036-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1186/s40580-014-0036-0&lt;/a&gt; Open Acess!)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2020-08-28T17:55:58.793" LastActivityDate="2020-08-28T17:55:58.793" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2101" PostTypeId="2" ParentId="1657" CreationDate="2020-08-27T10:59:04.400" Score="1" Body="&lt;p&gt;There is an initiative from IBM called &lt;a href=&quot;https://rxn.res.ibm.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RoboRXN&lt;/a&gt;. It is a free web service for predicting chemical reactions.&lt;/p&gt;&#xA;&lt;p&gt;From the IBM Research Blog recent &lt;a href=&quot;https://www.ibm.com/blogs/research/2020/08/roborxn-automating-chemical-synthesis/&quot; rel=&quot;nofollow noreferrer&quot;&gt;post&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The magic behind the RXN for Chemistry is a state-of-the-art neural&#xA;machine learning translation method that can predict the most likely&#xA;outcome of a chemical reaction using neural machine translation&#xA;architectures. Similar to translating Italian to English, our method&#xA;translates the language of chemistry converting reactants and reagents&#xA;to products, using the SMILE representation to describe chemical&#xA;entities.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Some features of RoboRXN are:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;We provide a state-of-the-art trained artificial intelligence (AI)    model that can be used in your daily research activities irrespective&#xA;of the purpose&lt;/li&gt;&#xA;&lt;li&gt;Use the prediction mode to open a project and invite collaborators to collectively plan complex synthesis.&lt;/li&gt;&#xA;&lt;li&gt;Use the challenge mode to test your Organic Chemistry knowledge and prepare for class exams&lt;/li&gt;&#xA;&lt;li&gt;Design your retrosynthesis either using the automatic or the interactive mode. In the interactive mode, IBM RXN for Chemistry –just&#xA;like an assistant – recommends disconnections and you choose.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-08-27T10:59:04.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2102" PostTypeId="1" AcceptedAnswerId="2151" CreationDate="2020-08-27T12:48:32.073" Score="9" ViewCount="225" Body="&lt;p&gt;Is it possible to incorporate the empty d-orbitals of a p-block element (suppose  it is chlorine) into a VASP calculation?&#xA;If yes, what is the standard procedure to incorporate these orbitals.&lt;/p&gt;&#xA;" OwnerUserId="765" LastEditorUserId="142" LastEditDate="2020-09-01T09:02:31.120" LastActivityDate="2020-09-01T09:02:31.120" Title="Incorporation of empty d-electrons of a p-block element in calculations in VASP?" Tags="|vasp|electronic-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2103" PostTypeId="2" ParentId="2102" CreationDate="2020-08-27T12:53:33.303" Score="10" Body="&lt;p&gt;The empty orbitals are always included in plane wave calculations. The plane waves don't conform to atomic symmetry, and can be seen to contain contributions of arbitrary angular momentum.&lt;/p&gt;&#xA;&lt;p&gt;If you were to use an atomic basis set, then you would need to put in D basis functions explicitly; however, this is pretty much always done in practice at least in the quantum chemistry community, since you need D fuctions to describe polarization of the P orbitals. Typically, a polarized double-zeta basis will have D functions for Cl, a triple-zeta basis will also have F functions, and a quadruple-zeta basis will have G functions.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-27T12:53:33.303" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2104" PostTypeId="2" ParentId="1513" CreationDate="2020-08-27T14:15:14.993" Score="9" Body="&lt;h3&gt;Real-time TDDFT (RT-TDDFT)&lt;/h3&gt;&#xA;&lt;p&gt;This is the straightforward non-perturbative solution of the TDDFT equations by means of direct propagation in time. Pioneered by &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.46.12990&quot; rel=&quot;noreferrer&quot;&gt;Theilhaber&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.54.4484&quot; rel=&quot;noreferrer&quot;&gt;Yabana &amp;amp; Bertsch&lt;/a&gt; it has since found its way into several molecular or solid-state codes.&lt;/p&gt;&#xA;&lt;p&gt;The TDDFT equations in the Kohn–Sham (KS) framework are&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;i \frac{\partial}{\partial t} \phi_i (t) = H^\mathrm{KS}(t)\phi_i (t),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; are the occupied KS orbitals and &lt;span class=&quot;math-container&quot;&gt;$H^\mathrm{KS}(t)$&lt;/span&gt; is the time-dependent KS Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;In RT-TDDFT, the orbitals &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; are evolved in time in a stepwise fashion. The propagation from time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; to time &lt;span class=&quot;math-container&quot;&gt;$t+\Delta t$&lt;/span&gt; is performed by means of evolution operator &lt;span class=&quot;math-container&quot;&gt;$U(t+\Delta t, t)$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_i (t+\Delta t) = U(t+\Delta t, t)\phi_i (t),&#xA;$$&lt;/span&gt;&#xA;where the evolution operator is constructed from the KS Hamiltonian. Because of the time dependence of the Hamiltonian, both explicit via a typically present time-dependent external field, and implicit via the time-dependent KS orbitals used to construct it, the TDKS equation is non-linear. Therefore, the time evolution is aided by some iterative or predictor-corrector scheme to ensure stable evolution. Examples of solvers include the Magnus, Crank–Nicholson or Runge–Kutta propagator.&lt;/p&gt;&#xA;" OwnerUserId="544" LastEditorUserId="5" LastEditDate="2020-08-27T14:45:54.030" LastActivityDate="2020-08-27T14:45:54.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2105" PostTypeId="2" ParentId="2098" CreationDate="2020-08-27T15:33:54.293" Score="9" Body="&lt;p&gt;This occurs in superconductors. In the simplest version (called type-I BCS superconductors) there is a resistanceless state at low temperature, magnetic field, and current density. When the current density is raised over a critical value, a transition into a state with finite resistance occurs. This was discovered by Kamerlingh Onnes in the 1910s in mercury. In other types of superconductors, the details may be more complex, but the central point of a resistanceless state disappearing at high current density remains.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-08-27T15:33:54.293" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2106" PostTypeId="2" ParentId="2069" CreationDate="2020-08-27T15:41:30.410" Score="7" Body="&lt;p&gt;What the other folks have said is valid. But just to answer your question specifically, if you want to do DFT, there are many free packages that can do this type of thing. If you are wanting to do AIMD, CP2k is very fast and can handle a lot of atoms (but it is really hard to compile!). I mainly work on lattice dynamics calculations and use ABINIT for this. ABINIT also can do a lot of different things with AIMD too, but I have never used it for this. I think CP2k will be faster for AIMD due to the algorithms they use, but I can't give any details without doing some googling. Some other free software that I have used and that work well are Quantum Espresso and GPAW.&lt;/p&gt;&#xA;&lt;p&gt;If you only want to do classical molecular dynamics (i.e. many more atoms in a cell) you can try LAMMPS (very good) and Gromacs (haven't used it). I can't say whether or not the empirical potentials will be suited to your problem (this is an important physics question you will have to consider) but there are many options to choose from for carbon. Check the potentials that come with LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, it is possible to do hybrid quantum/classical simulations. I think these are hard to do correctly, but I have been told by some colleagues that they are a very powerful tool. You can calculate certain properties in the 'quantum' region while coupling this part to a classical simulation to try to recover some of the more long-range affects.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2020-08-27T15:41:30.410" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2107" PostTypeId="2" ParentId="2015" CreationDate="2020-08-27T15:46:33.667" Score="5" Body="&lt;p&gt;As others have mentioned, there is no 'rule of thumb', but I do phonon calculations (PHONOPY and DFPT) and did some checking a long time ago to converge the phonon energies. I found ~ 0.001 eV/A to be more than low enough for all cases that I checked. Note that, while relaxation to high precision is expensive, once it gets close to the minimum, the positions usually converge more quickly. Note that in some instances, the energy cutoff (for plane wave codes that I use) might have to be sufficiently high to remove noise in the forces if you want such a low value.&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="116" LastEditDate="2020-08-27T15:54:18.230" LastActivityDate="2020-08-27T15:54:18.230" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2108" PostTypeId="2" ParentId="1056" CreationDate="2020-08-27T16:18:47.943" Score="11" Body="&lt;h3&gt;Computational Physics by Thijssen&lt;/h3&gt;&#xA;&lt;p&gt;The book starts at the simple Hartree problem, builds up to the Hartree-Fock problem, and eventually walk's the reader through constructing a pseudopotential planewave DFT program for silicon (gamma point only, but the generalization to other K points is straighforward). It covers the theory, provides coding exercises, and sample programs are on the author's website. I have found this book indispensable for actually understanding what I am doing when I set parameters in a calculation, interpreting outputs, etc.&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="5" LastEditDate="2020-08-27T20:08:53.817" LastActivityDate="2020-08-27T20:08:53.817" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2109" PostTypeId="2" ParentId="1743" CreationDate="2020-08-27T17:18:33.333" Score="6" Body="&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1038/s41467-020-16290-w&quot; rel=&quot;noreferrer&quot;&gt;N. Mitsuishi et al. &lt;em&gt;&amp;quot;Switching of band inversion and topological surface states by charge density wave,&amp;quot;&lt;/em&gt; Nature Communications &lt;strong&gt;11&lt;/strong&gt;, 2466 (2020)&lt;/a&gt; may be of interest to you. I don't think there is any a priori connection between charge density waves and band inversion. Essentially, a charge density wave is a periodic modulation of charge density and lattice (typically due to electron-phonon coupling). This can modify the band structure in various interesting ways, which need not include a band inversion. However, in the linked paper they demonstrate that, in the transition metal dichalcogenide VTe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, they can drive a charge density wave that results in a topological band inversion.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Topologically nontrivial materials host protected edge states associated with the bulk band inversion through the bulk-edge correspondence. Manipulating such edge states is highly desired for developing new functions and devices practically using their dissipation-less nature and spin-momentum locking. Here we introduce a transition-metal dichalcogenide VTe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, that hosts a charge density wave (CDW) coupled with the band inversion involving V3&lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; and Te5&lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; orbitals. Spin- and angle-resolved photoemission spectroscopy with first-principles calculations reveal the huge anisotropic modification of the bulk electronic structure by the CDW formation, accompanying the selective disappearance of Dirac-type spin-polarized topological surface states that exist in the normal state. Thorough three dimensional investigation of bulk states indicates that the corresponding band inversion at the Brillouin zone boundary dissolves upon the CDW formation, by transforming into anomalous flat bands. Our finding provides a new insight to the topological manipulation of matters by utilizing CDWs’ flexible characters to external stimuli.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-08-27T17:18:33.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2110" PostTypeId="2" ParentId="1994" CreationDate="2020-08-27T19:19:27.983" Score="7" Body="&lt;p&gt;Charge density waves (CDW's) exist in a few circumstances that I know of.&lt;/p&gt;&#xA;&lt;p&gt;The simplest example I can think of is the CDW due to nesting of the Fermi surface. This can be discussed in the context of the 'Peierls instability.' Kittel's Introduction to Solid State Physics provides a decent description of the phonon renormalization in this case (pp 422). Essentially, in a 1D metal, a gap opens in the electronic bands when the symmetry is lowered by a lattice distortion with Q =  twice the Fermi wave vector (the so called 'nesting vector'). The levels near the band gap shift down so that the total electronic energy is lowered slightly. However, the lattice distortion introduces some 'strain' energy in the total electronic/lattice system. So if one minimizes the total energy with respect to the lattice distortion, one finds a stable configuration with a slightly distorted lattice.&lt;/p&gt;&#xA;&lt;p&gt;From the point of view of the electrons, there is now a state at the BZ edge with group velocity = 0 and wave vector +- the Fermi wave vector. This is a standing wave which appears as a periodic modulation of the charge density. From the point of view of the phonons, the periodically modulated charge density perturbs the lattice towards distortions at nesting vector. If you work out a lattice dynamical problem, you will find that forces that aren't restorative (i.e. an instability) lead to imaginary frequencies.&lt;/p&gt;&#xA;&lt;p&gt;This is not a phenomena unique to Kohn-Sham formalism and is not restricted to 0 temperature, but there is a 'Peierls transition temperature' where thermal occupation of electrons to higher energy states overcomes the simple energy lowering described above and the distortion disappears.&lt;/p&gt;&#xA;&lt;p&gt;There is a related phenomena called a 'Kohn anomaly' where (in the Lindhard approximation) the dielectric function has a divergence at the nesting vector. Essentially the ion-ion interaction is screened by the electrons, but for electrons with k = +- the Fermi wave vector, the Lindhard expression for the dielectric function blows up and the phonon energy is renormalized to 0. See Ashcroft and Mermin, chapter 26 for a better discussion.&lt;/p&gt;&#xA;&lt;p&gt;There is another popular example of materials hosting CDW's: the cuprates. In these materials, the existence of CDW's is a contentious issue. Static CDW's have been observed in a few isolated instances (narrow doping and temperature range), but it is argued that dynamic CDW fluctuations exist more broadly in the cuprates. These CDW's are speculated to exist due to many body correlations and aren't well understood. Another issue is that observing dynamic CDW's is difficult. However, one viewpoint (taken by my research group) is to look for phonon anomalies at nesting wave vector in these materials and, by analogy to Kohn/Peierls anomalies, argue that dynamic CDW waves are present. If you are interested in this, see &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.101.184508&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.101.184508&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="1258" LastEditDate="2020-08-27T19:24:33.263" LastActivityDate="2020-08-27T19:24:33.263" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2111" PostTypeId="2" ParentId="2089" CreationDate="2020-08-27T19:28:24.470" Score="4" Body="&lt;p&gt;Alright, so it turns out @TristanMaxson was right - it was the periodic boundary conditions that were messing with my computation. The solution to it was to find the unwrapped coordinates of my system.&lt;/p&gt;&#xA;&lt;p&gt;This is how I unwrapped my coordinates:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;unwrapped_positions = relevant_positions.copy()&#xA;for ts in range(0,n_time_points-1):&#xA;    periodic_displacement = \&#xA;    relevant_positions[numPart*(ts+1):numPart*(ts+2),:]-\&#xA;    relevant_positions[numPart*(ts):numPart*(ts+1),:]&#xA;&#xA;    boundary_crossing = (np.abs(periodic_displacement) &amp;gt; (L/2))*1&#xA;    boundary_crossing_sign = np.sign(periodic_displacement)&#xA;&#xA;    absolute_displacement = periodic_displacement\&#xA;    - boundary_crossing*boundary_crossing_sign*L&#xA;&#xA;    unwrapped_positions[numPart*(ts+1):numPart*(ts+2),:] = \&#xA;    unwrapped_positions[numPart*(ts):numPart*(ts+1),:] + \&#xA;    absolute_displacement&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;followed by:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;msd = np.zeros(np.shape(t))&#xA;msd[0] = 0&#xA;&#xA;for d in range(1, n_time_points):&#xA;    for i in range(0, n_time_points-d):&#xA;        msd[d] += np.sum(np.square(\&#xA;        unwrapped_positions[numPart*(d+i):numPart*(d+i+1),:] -\&#xA;        unwrapped_positions[numPart*i:numPart*(i+1),:]))&#xA;    msd[d] = msd[d]/(n_time_points-d)&#xA;&#xA;msd = msd/numPart&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, there was an inherent flaw in my code - I wasn't averaging my MSD right, apart from the fact that I had problems with wrapped coordinates.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2020-08-27T19:28:24.470" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2112" PostTypeId="1" AcceptedAnswerId="2115" CreationDate="2020-08-28T02:08:49.397" Score="23" ViewCount="5149" Body="&lt;p&gt;Considering how GPUs in matter modeling was first recognized in gaming devices like PlayStation, it is also interesting to consider whether ARM64 chips, which are the type of chips in modern smart phones, will play a similarly revolutionary role in matter modeling.&lt;/p&gt;&#xA;&lt;p&gt;Now it is no secret that ARM64 is something that should be considered seriously. For example, &lt;a href=&quot;https://www.neowin.net/news/apple-announces-that-its-macs-will-start-using-its-own-custom-arm-processors&quot; rel=&quot;noreferrer&quot;&gt;Apple's recent announcement&lt;/a&gt; that all MACs will come with the ARM64 processor, and the Microsoft Surface X Pro, which runs on ARM64 with a full Windows 10 build. Furthermore, &lt;a href=&quot;https://wccftech.com/microsoft-backports-wsl2-to-windows-10-1909-and-1903/#:%7E:text=Microsoft%20said%20that%20if%20you%20are%20using%20an,distributions%20interact%20with%20Windows%20and%20bringing%20several%20improvements.&quot; rel=&quot;noreferrer&quot;&gt;Windows Subsystem for Linux2 (WSL2)&lt;/a&gt; is also compatible with ARM64.&lt;/p&gt;&#xA;&lt;p&gt;The benefits of ARM64 are the &amp;quot;small form factors&amp;quot; which allow it to be more power efficient, smaller, thinner and lighter. Furthermore, they have instant on capability, and long standby times. These are particularly promising from a consumer standpoint but could also be beneficial for high-performance computing as well.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However, the serious drawbacks of ARM64 is the software compatibility.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notably I found &lt;a href=&quot;https://www.olcf.ornl.gov/wp-content/uploads/2019/11/ARM_NVIDIA_APP_EVALUATION-1.pdf&quot; rel=&quot;noreferrer&quot;&gt;this link&lt;/a&gt; which lists ARM + NVIDIA HPC Software that are currently compatible:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;CoMet&lt;/li&gt;&#xA;&lt;li&gt;LAMMPS&lt;/li&gt;&#xA;&lt;li&gt;NAMD&lt;/li&gt;&#xA;&lt;li&gt;VMD&lt;/li&gt;&#xA;&lt;li&gt;DCA++&lt;/li&gt;&#xA;&lt;li&gt;Gromacs&lt;/li&gt;&#xA;&lt;li&gt;LSMS&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;What other popular matter modeling software are compatible with ARM64 or what software are notoriously not currently compatible?&lt;/strong&gt; (e.g. Adobe creative cloud is apparently not yet completely supported by ARM64)&lt;/p&gt;&#xA;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2020-08-28T18:27:34.640" LastActivityDate="2020-11-21T13:28:19.247" Title="Is ARM64 the next big thing?" Tags="|high-performance-computing|software-recommendations|soft-question|" AnswerCount="6" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2113" PostTypeId="2" ParentId="2093" CreationDate="2020-08-28T03:05:39.143" Score="6" Body="&lt;p&gt;Hasel actuators can contact and expand fast and use veggtable oil and plastic. Here is a video on how the work &lt;a href=&quot;https://youtu.be/Yi8tUJowAuo&quot; rel=&quot;noreferrer&quot;&gt;https://youtu.be/Yi8tUJowAuo&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1261" LastActivityDate="2020-08-28T03:05:39.143" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2114" PostTypeId="2" ParentId="2112" CreationDate="2020-08-28T07:37:04.727" Score="13" Body="&#xA;&lt;p&gt;Any code that does not have core parts written in machine level code (assembly) is going to be portable to arm64 straight away; you just have to recompile the program. This is the whole point of having programming languages in the first place: you need to be able to run your program on different architectures without rewriting the program from scratch, like in the early days of computing.&lt;/p&gt;&#xA;&lt;p&gt;The main issue in portability is that there are some pitfalls in languages like C and Fortran that you have to be aware of, namely, intrinsic types / default types may have different defaults on different platforms. However, any adequate programmer can write code that cross-compiles. It's not so long ago that there was the switch from x86 to x86_64, where you already had to face similar issues with portability.&lt;/p&gt;&#xA;&lt;p&gt;And if you go to the supercomputing world, you'll see that there's been quite a bit of heterogeneity for a long time: in addition to x86 and x86_64, you've also had other kinds of processor architectures like SPARC and Power. Since most codes are designed to run (also) on supercomputers, portability has been a key issue for a very long time.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-08-28T20:35:49.170" LastActivityDate="2020-08-28T20:35:49.170" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2115" PostTypeId="2" ParentId="2112" CreationDate="2020-08-28T07:48:09.633" Score="27" Body="&lt;p&gt;&lt;strong&gt;It depends on what chips datacenters are using.&lt;/strong&gt; If large data centers switch over to ARM-based processors, scientific computing will follow. Since most of our software is open source (or not far from that), converting to ARM compatibility will not be too much of an issue once the demand is there.&lt;/p&gt;&#xA;&lt;p&gt;Scientific computing is currently dominated by enterprise-grade Intel-compatible x86_64 processors. The reason for this is not because those are necessarily the best possible processors for scientific computing, but because they are available. Semiconductor manufacturing has massive economies of scale, and scientific computing is a relatively tiny market, so we end up buying whatever high performance chips are used by commercial data centers. &lt;strong&gt;So the real question is this: are commercial data centers going to switch over to ARM chips? Or are they going to stick to x86?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As far as that question goes, I have no idea. For now, I suspect that x86 maintains a performance edge in power-hungry data center processors, but that could change.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update from Nov 2020:&lt;/strong&gt; The initial reviews of the performance of Apple's new ARM-based Macs are very promising, even when they are translating binaries compiled for x86. I think this makes it much more likely that other firms were make big investments in desktop and possibly server-class ARM-based processors.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-11-21T13:28:19.247" LastActivityDate="2020-11-21T13:28:19.247" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2116" PostTypeId="1" CreationDate="2020-08-28T08:14:50.793" Score="9" ViewCount="98" Body="&lt;p&gt;I see in many sources the exfoliation energy defined with the unit &lt;span class=&quot;math-container&quot;&gt;$meV/A^2$&lt;/span&gt; I frankly don't understand how it's calculated and I couldn't find any mathematical formula for that. its unit confuses me. I was wondering if anyone could explain the concept mathematically. And how can I convert it into the interlayer binding energy (&lt;span class=&quot;math-container&quot;&gt;$meV/Atom$&lt;/span&gt;)&lt;/p&gt;&#xA;" OwnerDisplayName="user1263" LastActivityDate="2020-08-29T02:18:47.510" Title="What is exfoliation energy per unit area?" Tags="|density-functional-theory|binding-energy|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2117" PostTypeId="2" ParentId="70" CreationDate="2020-08-28T08:36:25.297" Score="6" Body="&lt;p&gt;Another reason can be the choice of Hamiltonian, for example relativistic vs. non-relativistic (especially spin-orbit including). In relativistic theories, the orbitals are complex as opposed to real orbitals in non-relativistic codes, so it has to be programmed accordingly. Moreover, relativistic orbitals possess a multi-component spinor structure, meaning that some objects suddenly become vectors or matrices and do not commute any more. This means that many core routines, especially when aiming for an optimized efficient code, will end up different in relativistic and non-relativistic codes.&lt;/p&gt;&#xA;" OwnerUserId="544" LastActivityDate="2020-08-28T08:36:25.297" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2118" PostTypeId="1" CreationDate="2020-08-28T10:02:02.073" Score="8" ViewCount="935" Body="&lt;p&gt;Can someone share appropriate tags and methods to perform virtual crystal approximation calculations in VASP?&lt;/p&gt;&#xA;" OwnerUserId="1136" LastActivityDate="2020-08-28T10:38:52.487" Title="How to perform virtual crystal approximation calculations in VASP?" Tags="|density-functional-theory|vasp|condensed-matter|computational-chemistry|solid-state-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2119" PostTypeId="2" ParentId="2118" CreationDate="2020-08-28T10:38:52.487" Score="6" Body="&lt;p&gt;In general the best resource for details about VASP tags and their use is the VASP wiki page. For the virtual crystal approximation the relevant tag appears to be &amp;quot;VCA&amp;quot; and the corresponding wiki page is &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/VCA&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have never used the virtual crystal approximation, so cannot speak about its merits. However, I would highlight the text at the bottom of the VASP wiki page, which suggests that calculations may not be very reliable:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Caveats: Unfortunately results of this kind of VCA calculations are&#xA;often not very reliable. The problems are even apparent in the&#xA;original publications by [2]. The key point is that the used PAW&#xA;potentials need to be constructed in such a way that the pseudo atomic&#xA;waves are very similar for the potentials that are &amp;quot;mixed&amp;quot; (in the&#xA;example above this would be the Ge and Sn potentials). This can be&#xA;achieved by carefully optimizing the radial cutoffs. Furthermore, the&#xA;local potentials of the two POTCAR files need to be very similar. This&#xA;means that results for many standard potentials are not accurate. For&#xA;instance, Vegard's law is often not even approximately observed&#xA;(instead the volume is way too large at 50 % mixing). The problem is&#xA;particularly severe, if semi-core states are treated as valence&#xA;states. For instance, for the Ge and Sn alloy the d electrons had to&#xA;be treated as core electrons to obtain reasonable results. Any&#xA;attempts to tread the d electrons as valence states lead to crossly&#xA;incorrect results.&lt;/p&gt;&#xA;&lt;p&gt;[2] L. Bellaiche and D. Vanderbilt, Phys. Rev. B 61, 7877 (2000).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-28T10:38:52.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2120" PostTypeId="2" ParentId="2112" CreationDate="2020-08-28T11:18:29.863" Score="17" Body="&lt;p&gt;I'd expect that x86_64 will remain the architecture of choice for computing throughput for quite a while, and that there might even be a way to deliberately re-enable the Spectre/Meltdown vulnerabilities because they give a nice speed boost and are irrelevant if you don't share the CPU with anyone else.&lt;/p&gt;&#xA;&lt;p&gt;ARM shines in the datacenter because a lot of the work there is simple text processing with many conditional branches between long runs of waiting for I/O, and ARM is a lot more power-efficient there as they have a short pipeline and very little logic that remains active while the CPU is idle.&lt;/p&gt;&#xA;&lt;p&gt;If you have a workload with fewer branches, Intel gets an edge, if you have almost no branches and the problem is massively parallel, GPUs win.&lt;/p&gt;&#xA;&lt;p&gt;For any long-running computation, you probably want to run it for a few seconds on different architectures and compare speed and power requirements before you make a decision which one is optimal.&lt;/p&gt;&#xA;" OwnerUserId="1266" LastActivityDate="2020-08-28T11:18:29.863" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2121" PostTypeId="2" ParentId="2098" CreationDate="2020-08-28T12:45:48.633" Score="7" Body="&lt;p&gt;This also occurs in &lt;a href=&quot;https://en.wikipedia.org/wiki/Incandescent_light_bulb&quot; rel=&quot;nofollow noreferrer&quot;&gt;traditional (filament) light bulbs&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The filament resides in an evacuated glass envelope, backfilled with a percentage of inert gas, to prevent oxidization and immediate failure.  The filament is constructed of a fine tungsten (likely alloy) wire, wrapped into a microscopically-tight spiral, then this wrapped again into a slightly larger spiral.  The double-wrapping greatly increases the effective length, and thus the total electrical resistance.  The length is specifically chosen to be compatible with various standard supply voltages (120v, 240v etc.)  The diameter of the filament is also responsible for the &amp;quot;power&amp;quot; of the lamp, with larger diameters making more light (and using more energy.)&lt;/p&gt;&#xA;&lt;p&gt;The moment a light switch is thrown, the bulb appears as a low resistance (high conductance) as the filament is cold.  This causes a large current to flow for a very short amount of time, which quickly heats the filament to red-hot.  As the temperature increases, the filament becomes more resistive (less conductive) and the temperature-increase-rate slows.  Eventually (perhaps 0.1s) later, this rate drops to zero, and the bulb is glowing white-hot in an equilibrium state.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Addition&lt;/em&gt;: I think most (if not all) pure metals exhibit this behavior (decreasing conductance / increasing resistance with increasing temperature.)  Such is termed a &amp;quot;PTC&amp;quot; or &lt;a href=&quot;https://en.wikipedia.org/wiki/Temperature_coefficient&quot; rel=&quot;nofollow noreferrer&quot;&gt;positive temperature coefficient&lt;/a&gt; of resistance.  As the atoms heat up, they are forced to expand, increasing the inter-atom distance, which makes them less electrically conductive.  Tungsten is used for lamps due to it's extremely high melting point, which allows a wider range of operation, up to the white-hot point which few other materials can survive.&lt;/p&gt;&#xA;&lt;p&gt;Semi-conductor materials (such as atomically doped silicon used in practically all computer systems today) tend to have NTC or negative temperature coefficients, meaning they become &lt;em&gt;more&lt;/em&gt; conductive at higher temperatures. Thus &amp;quot;heat sinking&amp;quot; (keeping them cool) is needed for dense integrated circuits today.&lt;/p&gt;&#xA;" OwnerUserId="1268" LastEditorUserId="1268" LastEditDate="2020-08-28T15:24:46.837" LastActivityDate="2020-08-28T15:24:46.837" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2122" PostTypeId="1" CreationDate="2020-08-29T01:25:41.820" Score="8" ViewCount="934" Body="&lt;p&gt;I have a very general question but still quite important since I didn't find convincing tools to get the structural analysis done for LAMMPS dump file (trajectories). I am looking for post processing tools to understand:&lt;/p&gt;&#xA;&lt;p&gt;(i) Number (and lengths?) of hydrogen bonds between sets of molecules/atom-indices as a function of time. &lt;em&gt;&lt;strong&gt;Also&lt;/strong&gt;&lt;/em&gt;, does the tool take into account periodicity for hydrogen bond formers across the the unit cell?&lt;/p&gt;&#xA;&lt;p&gt;(ii) Find distances between sets of molecules/atom-indices as a function of time including effect of periodicity.&lt;/p&gt;&#xA;&lt;p&gt;(iii) Thoughts on other (except RDF, which is calculated pretty reliably from several softwares like VMD etc) interesting structural features that could be analyzed from the trajectories are welcome too.&lt;/p&gt;&#xA;&lt;p&gt;Please include helpful resources/links on tutorials of those softwares if you can.&lt;/p&gt;&#xA;" OwnerUserId="664" LastEditorUserId="5" LastEditDate="2020-08-29T02:16:53.183" LastActivityDate="2020-08-30T13:41:38.667" Title="Tools for structural analysis on LAMMPS trajectories" Tags="|molecular-dynamics|reference-request|lammps|software-recommendations|structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2123" PostTypeId="1" AcceptedAnswerId="2195" CreationDate="2020-08-29T02:09:30.317" Score="8" ViewCount="373" Body="&lt;p&gt;I understand that some codes allow for or have external tools to perform band unfolding in super cell calculations.  Normally these codes give band structures that are somewhat grainy and not nearly as clean as we normally see in a non-supercell band structure.&lt;/p&gt;&#xA;&lt;p&gt;What benefits exist to band unfolding over leaving the original band structure when reporting supercell band structures?  Presumably you could directly compare the supercell with the dopant (or other change) to the unmodified supercell.  Is there an analogous method to density of states in supercell calculations?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-08-29T02:18:36.103" LastActivityDate="2020-09-03T09:52:59.233" Title="Supercell band structure unfolding advantages" Tags="|reference-request|band-structure|density-of-states|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2124" PostTypeId="2" ParentId="2116" CreationDate="2020-08-29T02:18:47.510" Score="3" Body="&lt;p&gt;Unfortunately, these appear to be the same quantity (a somewhat disappointing answer).  They only differ in units, you can convert between the atomwise and area based units by simply calculating the area per atom in the cell. This is commonly seen for surface energies as well.  You can see it reported either way in literature.&lt;/p&gt;&#xA;&lt;p&gt;Interestingly, we never really see this sort of unit used in adsorbate calculations where it tends always be reported atomwise but when analyzing a coverage I imagine you could also treat it the same way.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-29T02:18:47.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2125" PostTypeId="2" ParentId="1934" CreationDate="2020-08-29T06:58:49.920" Score="5" Body="&lt;p&gt;Available implementations of DFT are capable of studying positive muons (&lt;span class=&quot;math-container&quot;&gt;$\mu^{+}$&lt;/span&gt;) because from an electronic point of view they are the same as protons (H&lt;span class=&quot;math-container&quot;&gt;$^{+}$&lt;/span&gt;). This effectively means that all calculations involving protons can be straight-forwardly re-interpreted as calculations involving muons (with the caveats detailed below). In this context, two situations are commonly studied: (i) a positive muon, which is equivalent to adding a positively charged proton (charged defect), (ii) muonium, a situation in which the positive muon binds to an electron (neutral defect). Although in principle it is straight-forward to simulate positive muons in DFT, here are a few things to consider:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Defect calculations.&lt;/strong&gt; Muons in matter are essentially defects, so simulations must take into account all subtleties that arise in defect calculations. For example, when using codes with periodic boundary conditions, one should consider the spurious defect-defect interaction (which is particularly severe for charged defects) by converging the simulation with respect to supercell size and/or applying appropriate correction schemes. This is entirely equivalent to what one would do to study protons. The canonical reference for studying defects in materials is &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.86.253&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Muon site.&lt;/strong&gt; As with any defect calculation, an important question is what the structure of the defect is. In the case of muons, which are typically implanted in a material, the question is: where is the muon? The answer is not trivial and may require a full structure prediction exercise comparing the relative energies of multiple potential muon sites. This is entirely equivalent to what one would do to study protons. A recent paper studying muon sites can be found &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.121108&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Quantum zero-point motion.&lt;/strong&gt; Up to this point, the discussion has been entirely equivalent between &lt;span class=&quot;math-container&quot;&gt;$\mu^{+}$&lt;/span&gt; and H&lt;span class=&quot;math-container&quot;&gt;$^+$&lt;/span&gt;. This is because these two particles are entirely equivalent from an electronic point of view. Where they differ is in their mass, and this is reflected in the vibrational contribution to the energy, which is mostly dominated by quantum fluctuations (zero-point motion) for light particles such as muons or protons. This means that to simulate muons one must carefully consider the vibrational contribution. A reasonable starting point would be to treat vibrations at the harmonic level of theory, but the light mass of the muon will almost always require the inclusion of anharmonic terms too. Another early interesting idea for simulating the vibrational properties of muons is a &amp;quot;double&amp;quot; Born-Oppenheimer approximation, in which the degrees of freedom of the system are separated into three (rather than the usual two) groups: electrons (small mass), muons (intermediate mass), and the rest of atoms in the system (large mass), as described &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.60.13534&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Once you have characterized the energetics of the muon as described above, many DFT codes also allow you to calculate the hyperfine tensor, describing the interaction between the electron spins and the muon spin. This is relevant for example in muon spin relaxation experiments, where muons are used to study the local magnetic structure of materials.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-08-29T06:58:49.920" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2126" PostTypeId="2" ParentId="2112" CreationDate="2020-08-29T17:35:17.750" Score="5" Body="&lt;p&gt;ARM64 may not have to be the next big thing to cause a positive change.  Competition between two standards could result in extensions of either standard to improve them.  We already see vendor specific extensions making a big difference with intel vs amd for example.&lt;/p&gt;&#xA;&lt;p&gt;From what I have seen, as long as the software support is good (as others have pointed out, a lot of codes could just be recompiled against ARM), ARM will either be strong enough to become the dominant architecture or it will at least positively impact x86_64 indirectly via extensions.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-29T17:35:17.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2127" PostTypeId="2" ParentId="398" CreationDate="2020-08-29T17:48:24.033" Score="3" Body="&lt;p&gt;To add some further information to Raz's answer, it is also possible to talk about the nanoparticle case.  With computing power getting stronger and codes becoming more efficient it is becoming more and more possible to explore almost physical systems.  Nanoparticles for example can be modeled directly based on either experimental observations (TEM, XRD, XPS results) or based on surface energies and wulff constructions.&lt;/p&gt;&#xA;&lt;p&gt;For these calculations one might go about the following process to create the nanoparticle model.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculate surface energies of all relevant surface terminations, possibly even modeling changes due to coverage effects&lt;/li&gt;&#xA;&lt;li&gt;Perform a wulff construction to get a good initial guess at the structure&lt;/li&gt;&#xA;&lt;li&gt;Explore deviations in the wulff construction, edges and corners are not modeled directly and their effect becomes stronger and stronger as the particle gets smaller.  DFT will tend to not explore massive particles, so this might be a big factor.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It may also be possible to use some type of mixed model for large nanoparticles where part of the nanoparticle is calculated at the DFT theory level and at some distance the DFT is replaced by a force field.  This allows for the modeling of corner sites for example which would not be reasonable to model using a pure DFT model.&lt;/p&gt;&#xA;&lt;p&gt;It is also worthwhile to remember that while solvation is typically needed for calculations in aqueous environments (with a large impact on the surface), implicit models can perform well in non-hydrogen bonding solvation environments.  Optionally, you can just restrict yourself to collaborating with people who only work in a perfect vacuum.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-29T17:48:24.033" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2128" PostTypeId="1" CreationDate="2020-08-29T19:24:23.853" Score="13" ViewCount="1622" Body="&lt;p&gt;I have never found any tags or documentation regarding external magnetic field in VASP but in different well known &lt;a href=&quot;https://advances.sciencemag.org/content/5/6/eaaw5685&quot; rel=&quot;noreferrer&quot;&gt;published articles&lt;/a&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;, the implementation of the external magnetic field by VASP has been discussed.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone please explain &lt;strong&gt;how is it possible to simulate the external magnetic field in VASP&lt;/strong&gt;?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Li, Jiaheng, et al. &amp;quot;Intrinsic magnetic topological insulators in van der Waals layered MnBi2Te4-family materials.&amp;quot; Science Advances 5.6 (2019): eaaw5685.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2020-08-30T20:55:11.607" LastActivityDate="2020-08-31T12:33:42.347" Title="External magnetic field in VASP?" Tags="|density-functional-theory|vasp|high-performance-computing|condensed-matter|magnetic-field|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2129" PostTypeId="2" ParentId="2128" CreationDate="2020-08-29T23:29:07.870" Score="7" Body="&lt;p&gt;&lt;strong&gt;VASP can't deal with the external magnetic field&lt;/strong&gt;, but VASP can deal with the spin-polarized and noncolinear magnetism. You should read carefully the cited paper. As far as I have known, MnBi2Te4 is AFM semiconductor. You can do the spin-polarized calculation and noncolinear calculation for it with VASP.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-08-29T23:29:07.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2130" PostTypeId="2" ParentId="2128" CreationDate="2020-08-30T03:03:33.290" Score="4" Body="&lt;p&gt;To address the paper, I don't believe they actually do any calculations in magnetic fields, they simply state what they expect would occur due to other calculations previously done by others.  Since VASP is a pretty closed off code, I would be surprised if anyone has implemented magnetic fields into VASP directly.&lt;/p&gt;&#xA;&lt;p&gt;My understanding is that DFT tends breakdown in these sorts of calculations so you need a highly specialized code (BDFT?) in order to do these calculations.  This would likely require the ability to make psuedopotentials which are appropriate to the theory changes.  I am very uninformed on this part of the field though.&lt;/p&gt;&#xA;&lt;p&gt;Staying on topic though, for those two reasons I suspect they speculate on these calculations rather than actually performing them.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-08-30T03:03:33.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2131" PostTypeId="1" AcceptedAnswerId="2150" CreationDate="2020-08-30T06:27:38.523" Score="12" ViewCount="2126" Body="&lt;p&gt;I've just run across a nomenclature for coincidence lattices at grain boundaries which uses a capital greek letter sigma followed by an integer. For example A.D. Rollett's 2016 &lt;a href=&quot;http://pajarito.materials.cmu.edu/lectures/L14-CSL_Theory_GBE-17Mar16.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Grain Boundary Engineering &amp;amp; Coincident Site Lattice (CSL) Theory&lt;/a&gt; (also &lt;a href=&quot;https://web.archive.org/web/20221008014025/http://pajarito.materials.cmu.edu/lectures/L14-CSL_Theory_GBE-17Mar16.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;archived&lt;/a&gt;) includes references to &lt;span class=&quot;math-container&quot;&gt;$\Sigma 3$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Sigma 5$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Sigma 7$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Sigma 13$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Question(s):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is it possible to explain what this means and how to know which sigma applies a given grain boundary?&lt;/li&gt;&#xA;&lt;li&gt;Does this apply to 1D grain boundaries between 2D grains as well? (e.g. adjacent islands of graphene side-by-side on a supporting surface)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2022-10-08T01:39:20.563" LastActivityDate="2022-10-08T01:43:01.823" Title="What does capital sigma followed by an integer (Σn) mean in the context of grain boundaries?" Tags="|crystallography|terminology|graphene|grain-boundaries|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2132" PostTypeId="2" ParentId="2128" CreationDate="2020-08-30T07:57:08.110" Score="5" Body="&lt;p&gt;I think that the &lt;em&gt;standard&lt;/em&gt; VASP distribution cannot deal with external magnetic fields, but there are a number of papers in which VASP has been modified to enable calculations with an external magnetic field.&lt;/p&gt;&#xA;&lt;p&gt;This &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.106.107202&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; by Bousquet, Spaldin, and Delaney explains how to incorporate a Zeeman field in the Hohenberg-Kohn energy functional (Eqs. 1 and 2 in the paper), implements it in VASP, and uses it to perform calculations under an applied external magnetic field.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="792" LastEditDate="2020-08-31T12:33:42.347" LastActivityDate="2020-08-31T12:33:42.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2133" PostTypeId="2" ParentId="2122" CreationDate="2020-08-30T12:11:41.487" Score="9" Body="&lt;p&gt;There are three main Python tools that I am aware of that can do what you want and much more (and in all fairness, since you have access to all coordinates, you can code up literally whatever you want with any of these). Disclaimer: I haven't worked extensively with all of these, so make sure you try all of them, since I am not listing them in any particular order:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;MDAnalysis (&lt;a href=&quot;https://www.mdanalysis.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.mdanalysis.org/&lt;/a&gt;): good for massive trajectories, has a lot of analysis tools, but has a bit of a steep learning curve. As far as I know, it can handle PBC's just fine, as well as calculate hydrogen bonds. Not sure about hydrogen bonds across PB, but I assume it does that? I guess you'll have to try and see — software changes all the time anyway.&lt;/li&gt;&#xA;&lt;li&gt;MDTraj (&lt;a href=&quot;http://mdtraj.org/&quot; rel=&quot;noreferrer&quot;&gt;http://mdtraj.org/&lt;/a&gt;): good for small trajectories, NumPy integration and quick-and-dirty analyses. Also has quite a few analysis tools, including what you need and I think it's more straightforward to use than MDAnalysis.&lt;/li&gt;&#xA;&lt;li&gt;Pytraj (&lt;a href=&quot;https://amber-md.github.io/pytraj/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;https://amber-md.github.io/pytraj/latest/index.html&lt;/a&gt;): I haven't used this one, but apparently it can use either of the previous two for trajectory I/O, so it's more flexible in this regard. Also, it seems to support many different types of analyses (including H-bond analysis, not sure about how it handles PBC) + MPI parallelisation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A nice summary about how these three differ, which could be somewhat outdated (but is the only thing I could find), can be found here: &lt;a href=&quot;https://github.com/Amber-MD/pytraj/issues/445&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/Amber-MD/pytraj/issues/445&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2020-08-30T12:11:41.487" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2134" PostTypeId="2" ParentId="2122" CreationDate="2020-08-30T13:41:38.667" Score="7" Body="&lt;p&gt;You can use OVITO as well which allows you to post-process your dump file&#xA;&lt;a href=&quot;https://www.ovito.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.ovito.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1286" LastActivityDate="2020-08-30T13:41:38.667" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2135" PostTypeId="1" CreationDate="2020-08-30T17:08:58.967" Score="8" ViewCount="578" Body="&lt;p&gt;For electronic density of states (DoS) calculations with &lt;code&gt;VASP&lt;/code&gt;, it is recommended that &lt;code&gt;VASP&lt;/code&gt;'s internal symmetry routine is turned off by setting &lt;code&gt;ISYM = 0&lt;/code&gt;. This way, all k-points in the Brillouin zone are sampled. Should the same be done with q-points while calculating phonon DoS?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="792" LastEditDate="2020-09-01T15:22:08.953" LastActivityDate="2020-09-01T15:22:08.953" Title="Should all q-points in the first Brillouin zone be sampled in phonon density of states calculations?" Tags="|vasp|phonons|phonopy|phonon-density-of-state|q-points|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2136" PostTypeId="5" CreationDate="2020-08-30T21:58:58.850" Score="0" Body="&lt;p&gt;More information can be found on the software's website &lt;a href=&quot;https://aimsclub.fhi-berlin.mpg.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-30T21:58:58.850" LastActivityDate="2020-08-30T21:58:58.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2137" PostTypeId="4" CreationDate="2020-08-30T21:58:58.850" Score="0" Body="Questions about the FHI-aims software package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-30T21:58:58.850" LastActivityDate="2020-08-30T21:58:58.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2138" PostTypeId="5" CreationDate="2020-08-30T22:00:10.057" Score="0" Body="&lt;p&gt;More information can be found on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Metadynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia page&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-30T22:00:10.057" LastActivityDate="2020-08-30T22:00:10.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2139" PostTypeId="4" CreationDate="2020-08-30T22:00:10.057" Score="0" Body="Questions about Metadynamics, a method first suggested by by Alessandro Laio and Michele Parrinello in 2002." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-30T22:00:10.057" LastActivityDate="2020-08-30T22:00:10.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2140" PostTypeId="2" ParentId="1867" CreationDate="2020-08-30T23:01:44.967" Score="3" Body="&lt;p&gt;No, this is not possible in VESTA at this time.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-08-30T23:01:44.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2142" PostTypeId="2" ParentId="1923" CreationDate="2020-08-31T06:38:20.720" Score="2" Body="&lt;p&gt;The question makes no sense, since a solid state system might have different phases, or a molecule might have different conformers. They may all be proper local minima of the energy functional, and with very small overall total energy differences.&lt;/p&gt;&#xA;&lt;p&gt;For instance, &lt;a href=&quot;https://doi.org/10.1021/jp312644t&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A 117, 2269 (2013)&lt;/a&gt; is a benchmark study for the 52 different conformers of the melatonin molecule (C13H16N2O2). The molecule has thus 33 atoms, and an energy difference threshold of 0.05 meV/atom would yield 1.65 meV in total, which would mean 0.038 kcal/mol. In this case it thus turns out that &lt;strong&gt;provided if you work hard to find the minima&lt;/strong&gt; you can differentiate between the conformers by an energy criterion. However, if you go to a larger system, the simple energy criterion might not work.&lt;/p&gt;&#xA;&lt;p&gt;In the worst case you might have two conformers that are &lt;em&gt;structurally different&lt;/em&gt;, but have the same energy; e.g. &lt;a href=&quot;https://en.wikipedia.org/wiki/Jahn%E2%80%93Teller_effect&quot; rel=&quot;nofollow noreferrer&quot;&gt;the Jahn-Teller effect&lt;/a&gt; can result in a double well potential.&lt;/p&gt;&#xA;&lt;p&gt;The best way to distinguish whether you have indeed converged to the same structure also requires checking the minimal geometry itself, by both visual and computational means. You might establish the similarity of the structure by fingerprints, for example; e.g. show that &lt;span class=&quot;math-container&quot;&gt;$ R = \sum_{i}^{N_{\rm atoms}} ({\bf x}_i - {\bf x}_i')^2$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;${\bf x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf x}'$&lt;/span&gt; are your two structures, is small. (Note that permutations of the nuclei is allowed so you should minimize &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; with respect to swaps of identical atoms.)&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-31T06:38:20.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2143" PostTypeId="1" AcceptedAnswerId="2147" CreationDate="2020-08-31T08:39:10.527" Score="7" ViewCount="495" Body="&lt;p&gt;&lt;strong&gt;Hello there,&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm trying to calculate condensed Fukui functions for atoms of ascorbate (anion!). For some reason, when calculating nucleophilicity, the functions are negative. The equation I use is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;f_A^- = P_A(N) - P_A(N-1)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;First of all, please confirm whether I am correct - since anion is being examined, &lt;code&gt;N&lt;/code&gt; is the anion charges and &lt;code&gt;N-1&lt;/code&gt; is the radical (&lt;code&gt;0 2&lt;/code&gt;) charges?&lt;/p&gt;&#xA;&lt;p&gt;Here are charges I obtained from Hirshfeld population analysis for N, N-1 and calculated condensed Fukui function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IZBSX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IZBSX.png&quot; alt=&quot;Charges and fukui&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="user1247" LastEditorDisplayName="user1247" LastEditDate="2020-08-31T16:30:03.690" LastActivityDate="2020-08-31T16:30:03.690" Title="Why I get negative value of condensed Fukui functions?" Tags="|electronic-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2144" PostTypeId="2" ParentId="2112" CreationDate="2020-08-31T08:43:13.723" Score="8" Body="&lt;p&gt;The main difference between ARM64 and x86_64 architectures is their core design. The x86_64 uses NUMA when more cores are involved, whereas ARM64 has a more versatile design, and can have unified memory access. The ARM64 design is less complex than the x86_64, and for highly parallel computing, a simpler design may help the performance.&lt;/p&gt;&#xA;&lt;p&gt;I see at least two reasons why ARM64 may be the &amp;quot;next big thing&amp;quot; for server processing.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Unified Memory Model&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In practice, when working with highly parallel processing, you are likely to share data between threads/cores. A first set of threads (typically a modeling orchestrator) may e.g. prepare the various modeling parameters. Then another set of threads (typically the modelling engine) will process the actual data. Then another set of threads will join all previous computation into the output content.&lt;/p&gt;&#xA;&lt;p&gt;Memory buffers are therefore likely to flow from one core to the other, and ARM64 simple memory design may have a very good impact. No need to deal with NUMA memory copies.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Higher Number of Cores&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks to its more simple design, ARM64 is likely to add more cores to the silicon, with less die consumption and lower power. I have used Intel Knight Landing (Xeon Phi) high-end CPUs, and their massively parallel process was with somewhat slow Atom cores, with a non uniform memory layout: you have on-chip fast memory, which needs to be addressed especially. I bought and read the &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0128091940&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference book about this CPU&lt;/a&gt; and it needs to adapt the software. Custom software with AVX512 opcodes are needed to leverage the Intel HW platform, whereas with ARM64 the cores are running regular code.&lt;/p&gt;&#xA;&lt;p&gt;The ARM64 design will probably make it easier to add more cores to the chip, without needing deed software change.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Don't Take My Word For It&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A good read about the future of ARM64 is what AWS is offering as cloud solution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.anandtech.com/show/15578/cloud-clash-amazon-graviton2-arm-against-intel-and-amd&quot; rel=&quot;noreferrer&quot;&gt;https://www.anandtech.com/show/15578/cloud-clash-amazon-graviton2-arm-against-intel-and-amd&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In short: ARM64 may really be the next big thing for software using CPU...&lt;/p&gt;&#xA;" OwnerUserId="1296" LastActivityDate="2020-08-31T08:43:13.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2145" PostTypeId="2" ParentId="2112" CreationDate="2020-08-31T08:44:43.977" Score="4" Body="&lt;p&gt;When I read your question I remembered a gitlab pages that list all the softwares ported to the arm architecture and their development progress.&#xA;You can find it here: &lt;a href=&quot;https://gitlab.com/arm-hpc/packages/-/wikis/categories/allPackages&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/arm-hpc/packages/-/wikis/categories/allPackages&lt;/a&gt;&#xA;Hope this can help.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2020-08-31T08:44:43.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2146" PostTypeId="1" AcceptedAnswerId="2149" CreationDate="2020-08-31T12:32:53.753" Score="9" ViewCount="469" Body="&lt;h3&gt;Roothaan Hall Equations:&lt;/h3&gt;&#xA;&lt;p&gt;The Hartree-Fock equations are a set of modified Schrodinger equations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$f_{i}\psi_{m}=\epsilon_{m}\psi_{m}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The Fock operator (&lt;span class=&quot;math-container&quot;&gt;$f_{i}$&lt;/span&gt;) is given by (restricted case):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$f_{i}=&#xA;\hat{h}_{i}+\sum_{j=1}^{n/2}[2\hat{J}_{j}(i)-\hat{K}_{j}(i)]$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;and the molecular orbitals are expressed as a linear combination of (&lt;span class=&quot;math-container&quot;&gt;$N_{b}$&lt;/span&gt;) atomic orbitals (&lt;span class=&quot;math-container&quot;&gt;$\chi_{o}$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{m}&#xA;=\sum_{o=1}^{N_{b}}c_{om}\chi_{o}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;By substituting &lt;span class=&quot;math-container&quot;&gt;$\psi_{m}$&lt;/span&gt;, one obtains:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$f_{i}\sum_{o=1}^{N_{b}}c_{om}\chi_{o}=&#xA;\epsilon_{m}\sum_{o=1}^{N_{b}}c_{om}\chi_{o}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If one now multiplies from the left by &lt;span class=&quot;math-container&quot;&gt;$\chi_{o'}$&lt;/span&gt;, and integrates over the coordinates of particle i:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sum_{o=1}^{N_{b}}c_{om}\int\chi_{o'}f_{i}\chi_{o}dr_{1}=&#xA;\epsilon_{m}\sum_{o=1}^{N_{b}}c_{om}\int\chi_{o'}\chi_{o}dr_{1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sum_{o=1}^{N_{b}}F_{o'o}c_{om}=&#xA;\epsilon_{m}\sum_{o=1}^{N_{b}}S_{o'o}c_{om}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$F_{o'o}=\int\chi_{o'}f_{i}\chi_{o}dr_{1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$S_{o'o}=\int\chi_{o'}\chi_{o}dr_{1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The expression has the form of a relation between matrix elements of the product matrices FC and SC. If one introduces the diagonal matrix &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; along the diagonal, the expression can be written as the matrix equality:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$FC = SC\epsilon$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;An Example:&lt;/h3&gt;&#xA;&lt;p&gt;To set up the Roothann equations for the HF molecule using the &lt;span class=&quot;math-container&quot;&gt;$N_{b} = 2$&lt;/span&gt; basis set H1s (&lt;span class=&quot;math-container&quot;&gt;$\chi_{a}$&lt;/span&gt;) and F2p&lt;span class=&quot;math-container&quot;&gt;$_{z}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\chi_{a}$&lt;/span&gt;) one can write the two molecular orbitals (m = a, b) as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{a}=c_{Aa}\chi_{A} + c_{Ba}\chi_{B}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{b}=c_{Ab}\chi_{A} + c_{Bb}\chi_{B}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The following matrices are obtained:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$F = \begin{bmatrix}F_{A}(A)&amp;amp;F_{A}(B)\\ F_{B}(A)&amp;amp;F_{B}(B)\end{bmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$S = \begin{bmatrix} 1 &amp;amp; S \\ S &amp;amp; 1 \end{bmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$C = \begin{bmatrix} c_{Aa} &amp;amp; c_{Ab} \\ c_{Ba} &amp;amp; c_{Bb} \end{bmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then the Roothan equations (&lt;span class=&quot;math-container&quot;&gt;$FC=SC\epsilon$&lt;/span&gt;) are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\begin{bmatrix}F_{AA}&amp;amp;F_{AB}\\ F_{BA}&amp;amp;F_{BB}\end{bmatrix} \begin{bmatrix} c_{Aa} &amp;amp; c_{Ab} \\ c_{Ba} &amp;amp; c_{Bb} \end{bmatrix} = \begin{bmatrix} 1 &amp;amp; S \\ S &amp;amp; 1 \end{bmatrix} \begin{bmatrix} c_{Aa} &amp;amp; c_{Ab} \\ c_{Ba} &amp;amp; c_{Bb} \end{bmatrix} \begin{bmatrix} \epsilon_{a} &amp;amp; 0 \\ 0 &amp;amp; \epsilon_{b} \end{bmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Question:&lt;/h3&gt;&#xA;&lt;p&gt;In many textbooks and lectures, the Roothan equations are often described after an introduction to the Slater determinant.&lt;/p&gt;&#xA;&lt;p&gt;If the total wavefunction from the HF example can be written in the form of a Slater determinant:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Psi = \frac{1}{\sqrt{N!}}\begin{bmatrix} \psi_{a}(i)&amp;amp;\psi_{b}(i)\\ \psi_{a}(j)&amp;amp;\psi_{b}(j)\end{bmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How is the normalization constant used in the Slater determinant built into these equations?&lt;/p&gt;&#xA;&lt;p&gt;Note: The derivation has come from Atkins' Physical Chemistry 9th Edition&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="794" LastEditDate="2020-09-01T04:07:23.043" LastActivityDate="2020-09-01T04:07:23.043" Title="Normalization constant and Roothaan Equations" Tags="|quantum-chemistry|self-consistent-field|hartree-fock|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2147" PostTypeId="2" ParentId="2143" CreationDate="2020-08-31T12:40:55.557" Score="4" Body="&lt;p&gt;First, about the signs. There's nothing odd with having summed partial charges of -1 and 0 for a single anion and a neutral molecule, respectively, since the sum is just the charge state of your system. Even in the neutral system some individual partial charges will be negative, and others positive; this is determined by the relative electronegativities of the atoms.&lt;/p&gt;&#xA;&lt;p&gt;Since you want to look at the population of electrons, not elementary charge, you might want to flip the sign of your Fukui function; &lt;span class=&quot;math-container&quot;&gt;$f_+({\bf r}) = \rho_{N+1}({\bf r})-\rho_N({\bf r})$&lt;/span&gt; is defined in terms of electron densities &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, not charge densities &lt;span class=&quot;math-container&quot;&gt;$-\rho$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now, about the method. Hirshfeld analysis is well-known to yield unreliable partial charges. Instead of the original scheme, which is dependent on a set of reference atom densities, improved alternatives such as the iterative Hirshfeld method, &lt;a href=&quot;https://doi.org/10.1063/1.2715563&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 126, 144111 (2007)&lt;/a&gt;, and its later developments like the minimal-basis iterative Stockholder method, &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.6b00456&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 12, 3894 (2016)&lt;/a&gt;, might yield better results.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-31T12:40:55.557" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2148" PostTypeId="2" ParentId="2146" CreationDate="2020-08-31T12:51:03.563" Score="3" Body="&lt;p&gt;The normalization constant for the Slater determinant is not incorporated into these equations. The HF equations give you the molecular orbitals while the Slater determinant is just a way of putting those orbitals together to make the full electronic wavefunction. You can find the orbitals without worrying about the wavefunction normalization.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-08-31T12:51:03.563" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2149" PostTypeId="2" ParentId="2146" CreationDate="2020-08-31T13:26:03.070" Score="8" Body="&lt;p&gt;The normalization constant &lt;strong&gt;is&lt;/strong&gt; built into the Roothaan-Hall equation. Namely, when you derive the Hartree-Fock energy expression from the wave function, you integrate out all the orbitals that don't &amp;quot;touch&amp;quot; the Hamiltonian, and the permutations of the orbitals &amp;quot;kill off&amp;quot; the normalization constant.&lt;/p&gt;&#xA;&lt;p&gt;Now, when you have the energy expression, you can substitute the expansion of the orbitals in the basis set, and vary the energy with respect to the expansion coefficients; you get the Roothaan-Hall equations as a result.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-08-31T13:26:03.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2150" PostTypeId="2" ParentId="2131" CreationDate="2020-08-31T14:41:08.417" Score="11" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; values represent the volume of the Coincident Site Lattice (CSL) of the grain boundary in terms of the volume of the unit cell of the crystal. In general, grain boundaries with higher symmetry have lower &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; values.&lt;/p&gt;&#xA;&lt;p&gt;Note that CSL boundaries are &lt;em&gt;special&lt;/em&gt; grain boundaries. So, they do not represent all grain boundaries comprehensively. But, for CSL boundaries, one way to calculate the &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; value by first constructing the CSL, measuring its volume, and dividing the result by the volume of the unit cell of crystal.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, it can be difficult to understand CSLs without visuals, but the explanation in the link in the question (to &lt;a href=&quot;http://pajarito.materials.cmu.edu/lectures/L14-CSL_Theory_GBE-17Mar16.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Prof. Rollett's notes&lt;/a&gt;, also &lt;a href=&quot;https://web.archive.org/web/20221008014025/http://pajarito.materials.cmu.edu/lectures/L14-CSL_Theory_GBE-17Mar16.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;archived&lt;/a&gt;) is a good place to start. The notes on crystal defects by Prof. Dr. Föll also has a helpful &lt;a href=&quot;https://www.tf.uni-kiel.de/matwis/amat/def_en/kap_7/backbone/r7_1_2.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;section on CSL&lt;/a&gt;. Apart from these resources, most texts on grain boundaries will have discussions on CSL boundaries and &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; values.&lt;/p&gt;&#xA;" OwnerUserId="22" LastEditorUserId="201" LastEditDate="2022-10-08T01:43:01.823" LastActivityDate="2022-10-08T01:43:01.823" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2151" PostTypeId="2" ParentId="2102" CreationDate="2020-08-31T14:49:21.310" Score="3" Body="&lt;p&gt;If I understand the question, you want to add Hubbard U correction to d orbitals on chlorine atoms? I think you can get bands with d-orbital character by including enough empty bands, but I don't think there is any point. The Hubbard U correction term only adds an energy penalty between occupied orbitals and the d-orbitals will not be occupied (unless you add lots of electrons). An analogous argument is true with e.g. the Hartree potential; the unoccupied states don't contribute to the density and don't alter the potential.&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2020-08-31T14:49:21.310" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2152" PostTypeId="5" CreationDate="2020-08-31T15:59:22.910" Score="0" Body="&lt;p&gt;More information is available at the &lt;a href=&quot;https://en.wikipedia.org/wiki/Abaqus&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia page for ABAQUS&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-31T15:59:22.910" LastActivityDate="2020-08-31T15:59:22.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2153" PostTypeId="4" CreationDate="2020-08-31T15:59:22.910" Score="0" Body="Questions about the finite element analysis software ABAQUS." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-08-31T15:59:22.910" LastActivityDate="2020-08-31T15:59:22.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2154" PostTypeId="2" ParentId="1962" CreationDate="2020-08-31T17:32:39.787" Score="4" Body="&lt;p&gt;The iDMRG algorithm is tailored for translationally invariant 1D systems with area law ground states (gapped states). If that's what you're interested in, iDMRG is hard to beat for accuracy, &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.205127&quot; rel=&quot;nofollow noreferrer&quot;&gt;assuming it does converge to the ground state&lt;/a&gt;. (In some cases, analytical solutions by e.g. the Bethe ansatz are possible. They may offer an improvement, but it can be very hard to calculate interesting properties from such solutions.) In practice, iDMRG can also be used to approximate other types of states. For example, iDMRG is often applied also to 2D systems, which are treated as quasi-1D ones by wrapping the lattice on a cylinder of infinite length but finite circumference. Of course, this procedure introduces finite-size effects.&lt;/p&gt;&#xA;&lt;p&gt;There's also a more subtle way finite-size effects can enter. It is sometimes said that iDMRG trades finite-size scaling for finite-entanglement scaling. This is controlled by the (finite) so-called bond dimension parameter &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; of the matrix product state (MPS). It essentially encodes how large ground state entanglement can be captured numerically. Too low &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; can give inaccurate results. For area law states in 1D systems you can, at least in principle, always find a &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; large enough. However, for critical systems the entanglement entropy &lt;span class=&quot;math-container&quot;&gt;$S\propto \ln L$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is the system length,  more care is needed, see &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.255701&quot; rel=&quot;nofollow noreferrer&quot;&gt;F. Pollmann, S. Mukerjee, A.M. Turner and J.E. Moore, Phys. Rev. Lett. &lt;strong&gt;102&lt;/strong&gt;, 255701 (2009)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/0812.2903&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv link&lt;/a&gt;). In quasi-1D systems the entanglement cut involves more sites (higher &amp;quot;area&amp;quot;), and so one needs to choose large enough &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; for the given circumference, which practically has to be balanced against the computational cost of increasing either parameter. Similarly, excited states are typically not area law states. Another area of interest is in studies of thermalization of quantum systems, or other time evolution problems. In such cases, the entanglement entropy tends to grow with time, and &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; puts a limit on how long one can evolve for. (Of course, all of these aspects also apply to finite MPS studies.)&lt;/p&gt;&#xA;&lt;p&gt;The main technical limitation of iDMRG relative to finite-size DMRG is that it uses a translationally invariant ansatz. That assumption certainly doesn't always hold. Recently, disordered systems have attracted a lot of attention due to e.g. many-body localization. Further, I want to note that people only really realized how capable iDMRG is around 2008 and thereafter, through works such as I. P. McCulloch's (&lt;a href=&quot;https://arxiv.org/abs/0804.2509&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:0804.2509&lt;/a&gt;), so inertia and availability of existing well-developed general codes probably still favors finite-size DMRG calculations a bit. I'm not sure how iDMRG compares to finite-size DMRG in terms of ease-of-use or performance, which may be more significant considerations than numerical accuracy.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-08-31T17:32:39.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2155" PostTypeId="1" CreationDate="2020-08-31T18:31:00.233" Score="6" ViewCount="1016" Body="&lt;p&gt;The answer can be a complete description of all the things we must be attentive to while converging q-points.&lt;/p&gt;&#xA;&lt;p&gt;A peculiar thing that I feel contradicted about: Generally, we don't take an equal # of k-points in an electronic DFT calculation when the cell has different lengths in different directions. &lt;code&gt;VASP&lt;/code&gt; even prints a warning - &amp;quot;Reciprocal lattice and k-lattice belong to different class of lattices&amp;quot;, whereas &lt;code&gt;phonopy&lt;/code&gt; doesn't give any error/warning if I take an equal # of q-points for such cells.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="792" LastEditDate="2020-09-01T15:22:41.917" LastActivityDate="2020-09-01T15:46:06.050" Title="Best practice(s) for q-points convergence in phonon density of states calculations" Tags="|vasp|phonons|convergence-test|phonopy|q-points|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2156" PostTypeId="5" CreationDate="2020-08-31T18:41:04.583" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-08-31T18:41:04.583" LastActivityDate="2020-08-31T18:41:04.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2157" PostTypeId="4" CreationDate="2020-08-31T18:41:04.583" Score="0" Body="For questions about the calculation of phonon density of states (DoS) or the theories involved in them." OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-08-31T19:04:49.047" LastActivityDate="2020-08-31T19:04:49.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2158" PostTypeId="5" CreationDate="2020-08-31T18:42:57.530" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-08-31T18:42:57.530" LastActivityDate="2020-08-31T18:42:57.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2159" PostTypeId="4" CreationDate="2020-08-31T18:42:57.530" Score="0" Body="For questions regarding $\mathbf{q}$-points in the Brillouin zone of phonon calculations." OwnerUserId="116" LastEditorUserId="792" LastEditDate="2020-09-01T18:34:32.800" LastActivityDate="2020-09-01T18:34:32.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2160" PostTypeId="2" ParentId="2080" CreationDate="2020-08-31T19:43:37.610" Score="10" Body="&lt;p&gt;&lt;strong&gt;TL;DR:&lt;/strong&gt; There really isn't a straightforward way to fix this error, or a way to guarantee success. This usually involves a very detailed hands-on troubleshooting session, because everything is dependent on everything and even tiny screws could lead to a significant change and often the underlying issues are worse than toggling a switch (or adding a keyword).&lt;/p&gt;&#xA;&lt;h2&gt;What does the error &lt;em&gt;Error termination request processed by link 9999.&lt;/em&gt; actually mean?&lt;/h2&gt;&#xA;&lt;p&gt;Gaussian often isn't very straight forward with its errors. There are multiple explanation sites of common errors on the internet because of this. The description of it is actually given many lines above. If you look up &lt;a href=&quot;https://gaussian.com/capabilities/?tabid=3&quot; rel=&quot;noreferrer&quot;&gt;link 9999 on the gaussian online manual&lt;/a&gt;, then you'll find:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;L9999: Finalizes calculation and output&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So that's the &lt;em&gt;something-went-wrong-catch-all&lt;/em&gt; of Gaussian. That usually means Gaussian's internal procedures set a flag to prevent it from terminating normally.&lt;/p&gt;&#xA;&lt;p&gt;In your specific case (and I experienced none other) it simply means the optimiser didn't find a stationary point within the allocated resources.&lt;/p&gt;&#xA;&lt;p&gt;Anyone can reproduce this error quickly with the following minimal example:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;%chk=error.chk&#xA;#P PM6 opt(maxcycle=3) &#xA;&#xA;L9999 error producing input&#xA;&#xA;0,1&#xA;O 0. 0. 0.&#xA;H 1. 0. 0.&#xA;H 0. 1. 0.&#xA;&#xA;! Blank line at the end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Obviously, the above example forces the error for demonstration purposes only. BTW, the &lt;code&gt;!&lt;/code&gt; is the comment character; these lines will be ignored. (The last line is there because SE decides to remove crucial blank lines automagically. So the example is copy-pastable with the comment.)&lt;/p&gt;&#xA;&lt;p&gt;Now, Gaussian isn't the best at communicating. You'll find (as you did) the following:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;[...]&#xA; Optimization stopped.&#xA;    -- Number of steps exceeded,  NStep=   3&#xA;    -- Flag reset to prevent archiving.&#xA;                           ----------------------------&#xA;                           ! Non-Optimized Parameters !&#xA;                           ! (Angstroms and Degrees)  !&#xA; --------------------------                            --------------------------&#xA;[...]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There it tells you that at &lt;code&gt;NStep= 3&lt;/code&gt; the number of steps is exceeded (more to that end later), and that'll reset some flag to prevent something. That's actually the internal procedure to cause the final message.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Steps and Cycles.&lt;/strong&gt;&#xA;Apparently Gaussian isn't very consistent in its terminology. Steps may be called cycles. So the keyword option &lt;code&gt;maxcycle=&lt;/code&gt; sets the maximum &lt;code&gt;NStep&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, the L9999 error isn't as much an error as it is a message to you: Basically the program is trying to tell you that it failed to reach what you have asked of it. &lt;em&gt;The underlying issue&lt;/em&gt; is somewhere in the set-up of your calculation.&lt;/p&gt;&#xA;&lt;h2&gt;Fixing the &lt;em&gt;'error'&lt;/em&gt;&lt;/h2&gt;&#xA;&lt;p&gt;You need to perform a deep-dive into the nitty-gritty details of your calculation.&lt;/p&gt;&#xA;&lt;p&gt;In the most common case, your starting guess simply was too far away from the stationary point. You can plot the convergence with each cycle to see what is going on. Most molecular viewers have that built in.&lt;br /&gt;&#xA;In the best case, you are a few cycles away from convergence. You can then simply restart the calculation. I recommend setting up a new calculation to prevent accidental overwriting. For the example above, this would be (in the same directory, requires &amp;gt; G09 D.01):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;%oldchk=error.chk&#xA;%chk=error-cont.chk&#xA;#P PM6 opt(maxcycle=300, restart) &#xA;&#xA;L9999 error restart&#xA;&#xA;0,1&#xA;O 0. 0. 0.&#xA;H 1. 0. 0.&#xA;H 0. 1. 0.&#xA;&#xA;! Blank line at the end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So increasing the &lt;code&gt;maxcycle&lt;/code&gt; value might already fix the 'error'. Note that the default is &lt;code&gt;128&lt;/code&gt;, so you need to set something higher than that if you &lt;code&gt;restart&lt;/code&gt;. Another common way is to simply extract the last coordinates and start a new calculation.&lt;br /&gt;&#xA;In most cases on &lt;code&gt;tight&lt;/code&gt; optimisation criteria and a reasonably well-behaved molecule, the default cycles will suffice. You can always save time by running pre-optimisations first. I recommend starting with semi-empirics, then increase to a pure functional with a split valence basis set. The new Gaussian versions in conjunction with a queueing system can handle chaining those calculations easily (use &lt;a href=&quot;https://gaussian.com/link0/&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;%oldchk&lt;/code&gt;&lt;/a&gt;), so you don't waste time.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Everything beyond that is magic.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Often, when you get to know your molecules, you will also know whether the default number of cycles will suffice and you can adjust your default route section.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Your example is a bit more than the default as you are trying to converge to &lt;code&gt;verytight&lt;/code&gt;. The first question you need to ask yourself is why you are doing this and whether this is really necessary. In my personal and very subjective experience, it takes about thrice the time (and cycles) to converge from &lt;code&gt;tight&lt;/code&gt; to &lt;code&gt;verytight&lt;/code&gt; as it takes from &lt;code&gt;loose&lt;/code&gt; to &lt;code&gt;tight&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In order to get to convergence in fewer cycles, tighten the integration grid. The default is &lt;code&gt;int(ultrafine)&lt;/code&gt; so you do not need to specify this. If you are running on a smaller grid, then your calculations are not reliable (&lt;a href=&quot;https://blogs.sciencemag.org/pipeline/archives/2019/07/17/get-ready-to-recalculate&quot; rel=&quot;noreferrer&quot;&gt;Get Ready to Recalculate by Derek Lowe&lt;/a&gt;). If you are doing benchmark tests, and you want them to be benchmarks for the method not the grid, then use &lt;a href=&quot;https://gaussian.com/integral/?tabid=1&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;int(superfine)&lt;/code&gt;&lt;/a&gt;. It might also be a good idea to force tighter SCF convergence with &lt;a href=&quot;https://gaussian.com/scf/?tabid=1&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;scf(conver=9)&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The estimation or calculation of the step and step direction is directly influenced by the quality of the wave function/ density matrix. If that's too coarse, you likely circle around the minimum.&lt;/p&gt;&#xA;&lt;p&gt;You can adjust the step size to force it to go slower, &lt;code&gt;opt(maxstep=10)&lt;/code&gt;, the default is &lt;code&gt;30&lt;/code&gt;. Whenever you do that, you should increase the cycles appropriately. An okay rule of thumb is by halving the step size to double the cycles. This is usually a good idea when trying to converge transition states.&lt;/p&gt;&#xA;&lt;p&gt;Sometimes, the estimation of the Hessian is not good enough. You might want to start your calculation with something better than a guess, then  use &lt;code&gt;opt(calcFC)&lt;/code&gt;. Alternatively, you can run a frequency calculation of your guess structure and analyse that before doing anything else. This might help identifying lower lying issues in the molecular structure. If you do, &lt;code&gt;opt(RCFC)&lt;/code&gt; will be your friend.&lt;br /&gt;&#xA;If you really, really want it, and you know exactly what you are doing (or you don't care anymore), then calculating force constants at every step is the &lt;em&gt;brute-force&lt;/em&gt; method, i.e. &lt;code&gt;opt(calcall)&lt;/code&gt;. I do not recommend this, it is very, very wasteful. There are intermediate options to do these things, so study the manual for more.&lt;/p&gt;&#xA;&lt;p&gt;I always recommend using redundant coordinates. Often enough the default is good enough. In rare cases they won't. The evil ones are near 0 or 180° angles, sometimes rings, cages, strongly delocalised parts of the molecule, long bonds, dispersive interactions, etc., the list is long. You can build your own redundant coordinates and that might help in those cases.&lt;br /&gt;&#xA;If you are not yet doing it, you should &lt;strong&gt;switch to generalised internal coordinates&lt;/strong&gt; (requires G16): &lt;code&gt;geom=GIC&lt;/code&gt;. If you need examples, browse on Chemistry.SE.&lt;/p&gt;&#xA;&lt;p&gt;If you really, really want to add more brute to your force, you can try optimising in cartesian coordinates. Note that you will not take advantage of many features of the Berny algorithm, you'll introduce more constraints, and you will need more cycles. (For a well-behaved molecule I'd add about 25% to be safe, but that is again as subjective as it gets.)&lt;/p&gt;&#xA;&lt;p&gt;If you are still convinced that what you are looking for exists, you can try a different algorithm. I have never used it, but I heard about people using it.&lt;/p&gt;&#xA;&lt;h2&gt;The final failure&lt;/h2&gt;&#xA;&lt;p&gt;&lt;em&gt;In most cases,&lt;/em&gt; if you get the L9999 error and it cannot easily be fixed (and I would include increasing the grid here), there is a deep-lying issue. You should check whether other methods produce sensible results. If your optimisations with very tight criteria succeed at BP86, PBE, TPSS, B3LYP, PBE0, TPSSh, etc., but not on M06-2X, then the problem might be that the Minnesota functional doesn't describe your system well enough. (I've only picked that because of the example. B3LYP is much more likely to fail producing sensible results. Statistically speaking.)&lt;br /&gt;&#xA;The usual way to go about that is to look for benchmarks studies in that field. Many things have been done already and you don't have to reinvent the wheel. (If only I could remember some of the quality review articles. I'm sure [or at least hopeful] someone will comment them below.)&lt;/p&gt;&#xA;&lt;h2&gt;The post-final &lt;em&gt;Hoorah!&lt;/em&gt;&lt;/h2&gt;&#xA;&lt;p&gt;There are alternative programs to Gaussian. It might not be a terrible idea to cross-validate.&lt;/p&gt;&#xA;" OwnerUserId="49" LastActivityDate="2020-08-31T19:43:37.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2161" PostTypeId="1" AcceptedAnswerId="2162" CreationDate="2020-08-31T23:42:20.843" Score="7" ViewCount="3073" Body="&lt;p&gt;It seems &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; was phased out in Ubuntu 20.04 (Focal Fossa) and derivatives like Mint 20 (Ulyana). Now the version available in the repositories is &lt;a href=&quot;https://www.openchemistry.org/projects/avogadro2/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro 2&lt;/a&gt;. If you had Avogadro installed in 18.04, and did a upgrade, it is replaced with Avogadro 2.&lt;/p&gt;&#xA;&lt;p&gt;I faced a minor issue while trying to adapt my workflow to the new version. While drawing some molecules, I found the new location of the geometry optimization tool, under Extensions &amp;gt; Open Babel &amp;gt; Optimize geometry. The problem was, the relevant entry, together with others in the same location, were grayed out, and unselectable, as the image below shows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XBo5f.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XBo5f.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It was a headscratcher, and I spent some time figuring out what was the problem, and opened this question afterwards to document the solution, to help other people that may face the same issue.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-09-09T23:11:11.137" LastActivityDate="2020-09-09T23:11:11.137" Title="Why the Open Babel submenu is faded out in Avogadro 2 and I can't optimize geometry in Mint 20?" Tags="|software|molecular-modeling|visualization-software|avogadro|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2162" PostTypeId="2" ParentId="2161" CreationDate="2020-08-31T23:42:20.843" Score="10" Body="&lt;h3&gt;Solution: Install Open Babel&lt;/h3&gt;&#xA;&lt;p&gt;The underlying cause is that Open Babel was not installed by default as a dependency of Avogadro 2. I think this is odd, as basic features like geometry optimization depend on it. Anyway, just installing Open Babel separately fixed the problem. To install it, open the terminal and input the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo apt install openbabel&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When the installation is finished, and you restart Avogadro 2, now you can select Optimize geometry, and the other functions that rely on Open Babel:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FYS8I.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FYS8I.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-09-01T16:53:36.280" LastActivityDate="2020-09-01T16:53:36.280" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2163" PostTypeId="1" AcceptedAnswerId="2232" CreationDate="2020-09-01T02:03:13.027" Score="12" ViewCount="2865" Body="&lt;p&gt;It seems &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro&lt;/a&gt; was phased out in Ubuntu 20.04 (Focal Fossa) and derivatives like Mint 20 (Ulyana). Now the version available in the repositories is &lt;a href=&quot;https://www.openchemistry.org/projects/avogadro2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro 2&lt;/a&gt;. If you had Avogadro installed in 18.04, and did a upgrade, it is replaced with Avogadro 2.&lt;/p&gt;&#xA;&lt;p&gt;The original Avogadro had a very useful feature, where we could generate input files for several Quantum Chemistry packages. Now the problem is, Avogadro 2 doesn't seem to have the input generators as part of the base install, working out-of-the-box. It seems this functionality was moved to a set of plugins. I tried to get them working, by two different routes, but had no sucess so far. I'm describing what I tried to do, if somebody knows how to sort this problem.&lt;/p&gt;&#xA;&lt;h3&gt;First try: Built-in plugin downloader.&lt;/h3&gt;&#xA;&lt;p&gt;Opening Extensions &amp;gt; Plugin Downloader, we are presented the following screen:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/n8o8D.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/n8o8D.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;By the description, avogenerators is what I'm looking for. When I select it, and click on Download Selected, it tells me the download was sucessful:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NrMbD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NrMbD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But when I go back to the work area, the menus are unchanged, even after reset. So I think this route failed.&lt;/p&gt;&#xA;&lt;h3&gt;Second try: Download with GIT&lt;/h3&gt;&#xA;&lt;p&gt;I seeked some guidance on this issue in the &lt;a href=&quot;https://github.com/OpenChemistry/avogenerators#readme&quot; rel=&quot;nofollow noreferrer&quot;&gt;plugin page on github&lt;/a&gt;, but found only this remark:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Installing&lt;/p&gt;&#xA;&lt;p&gt;These scripts need to be installed in a location where the Avogadro 2&#xA;application can find them. They use the JSON API described in the&#xA;Avogadro 2 API documentation, but the best way to learn is to look at&#xA;the existing scripts and adapt them to your needs.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Anyway, I proceeded to install GIT:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~/src$ sudo apt install git-all&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And try to clone the plugin repository:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~/src$ git clone https://github.com/OpenChemistry/avogenerators.git&#xA;Cloning into 'avogenerators'...&#xA;remote: Enumerating objects: 211, done.&#xA;remote: Total 211 (delta 0), reused 0 (delta 0), pack-reused 211&#xA;Receiving objects: 100% (211/211), 70.05 KiB | 481.00 KiB/s, done.&#xA;Resolving deltas: 100% (130/130), done.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From this point it was not clear what to do. I tried to navigate from the Open button into the cloned project folder, and it recognizes the plugin.json file as something that can be opened:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/V4Xls.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/V4Xls.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But when you try to load the plugin, it just throws a error:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2Zg0E.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2Zg0E.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Third try (Update September 10, 2020): Git download in proper location.&lt;/h3&gt;&#xA;&lt;p&gt;Following the advice in answer comments, I tried to repeat the Git download of the plugins, but this time under ~/.local/share/OpenChemistry/Avogadro/inputGenerators, creating missing subfolders to complete the path, when needed:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~&lt;span class=&quot;math-container&quot;&gt;$ cd ~/.local/share/OpenChemistry/Avogadro/&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro$&lt;/span&gt; ls&#xA;other&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro&lt;span class=&quot;math-container&quot;&gt;$ mkdir inputGenerators&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro$&lt;/span&gt; cd inputGenerators/&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro/inputGenerators&lt;span class=&quot;math-container&quot;&gt;$ git clone https://github.com/OpenChemistry/avogenerators.git&#xA;Cloning into 'avogenerators'...&#xA;remote: Enumerating objects: 211, done.&#xA;remote: Total 211 (delta 0), reused 0 (delta 0), pack-reused 211&#xA;Receiving objects: 100% (211/211), 70.05 KiB | 268.00 KiB/s, done.&#xA;Resolving deltas: 100% (130/130), done.&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro/inputGenerators$&lt;/span&gt; ls&#xA;avogenerators&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro/inputGenerators&lt;span class=&quot;math-container&quot;&gt;$ cd avogenerators/&#xA;user@machine:~/.local/share/OpenChemistry/Avogadro/inputGenerators/avogenerators$&lt;/span&gt; ls&#xA;dalton.py         inputgeneratortest.py  nwchem.py    pyscf.py&#xA;gamessuk.py       LICENSE                orca.py      qchem.py&#xA;gaussian.py       molpro.py              plugin.json  README.md&#xA;generators.cmake  mopac.py               psi4.py      terachem.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Still didn't suceed.&lt;/p&gt;&#xA;&lt;h3&gt;Closing remarks&lt;/h3&gt;&#xA;&lt;p&gt;If I didn't just fumbled somewhere, and other people are able to reproduce the problem, I think this is a breaking issue, as the input generators should be critical to many people besides me. It would be nice if the original Avogadro were available in the repositories as a fallback in situations like this. All the tests in this posts were done in a machine running Mint 20 (Ulyana).&lt;/p&gt;&#xA;&lt;h1&gt;Edit&lt;/h1&gt;&#xA;&lt;p&gt;Given Geoff's answer telling the problem is probably related to the locations the plugins are expected to be, I did a search for the Avogadro related locations in my machine, as I think it may be useful.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~$ sudo find / -iwholename 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‘/run/user/1000/gvfs’: Permissão negada&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-09-11T00:34:26.133" LastActivityDate="2023-11-21T16:56:20.653" Title="How to make the input generator plugin work in Avogadro 2 on GNU/Linux?" Tags="|software|molecular-modeling|visualization-software|avogadro|" AnswerCount="5" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2164" PostTypeId="2" ParentId="2161" CreationDate="2020-09-01T02:37:32.907" Score="6" Body="&lt;p&gt;Geoff Hutchison might be able to provide a more up to date and authoritative answer, but I can at least point to some explanation of why OpenBabel isn't included by default with Avogadro 2: &lt;a href=&quot;https://blog.kitware.com/avogadro-2-and-open-chemistry/&quot; rel=&quot;noreferrer&quot;&gt;https://blog.kitware.com/avogadro-2-and-open-chemistry/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The important points of the article are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The developers wanted to separate the Avogadro application from the various libraries/plugins that it used to have a more modular code.&lt;/li&gt;&#xA;&lt;li&gt;To switch the license of the code from GPLv2+ to BSD, they had to change how they interfaced with OpenBabel. This improved some Avogadro features and made it easier to upgrade Avogadro and Open Babel independently of each other.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-09-01T02:37:32.907" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2166" PostTypeId="1" AcceptedAnswerId="2176" CreationDate="2020-09-01T12:06:57.493" Score="7" ViewCount="1123" Body="&lt;p&gt;Good morning!&lt;/p&gt;&#xA;&lt;p&gt;I would like to test the biaxial tensile strain and compressive strain in a hexagonal material from the TMDC group (for example HfS2).&#xA;How to get it into VASP?&#xA;What are the best ways to optimize geometry?&#xA;Can I fall into some traps?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;HfS2&#xA;1.0&#xA; 3.6389749050         0.0000000000         0.0000000000&#xA;-1.8194881106         3.1514448821         0.0000000000&#xA; 0.0000000000         0.0000000000        22.8899211884&#xA; Hf    S&#xA;  1    2&#xA; Direct&#xA; 0.000000000         0.000000000         0.500000000&#xA; 0.666666985         0.333332986         0.563098013&#xA; 0.333332986         0.666666985         0.436901987&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could you help me with this as example?&lt;/p&gt;&#xA;" OwnerUserId="1216" LastEditorUserId="1216" LastEditDate="2020-09-02T17:49:19.177" LastActivityDate="2022-11-10T08:44:38.307" Title="How to start with biaxial tensile strain and compressive strain in TMDCs using VASP?" Tags="|vasp|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2167" PostTypeId="2" ParentId="1513" CreationDate="2020-09-01T12:24:40.367" Score="10" Body="&lt;h3&gt;Density functional perturbation theory (DFPT)&lt;/h3&gt;&#xA;&lt;p&gt;This method refers to the calculation of the linear response of the system under some external perturbation.&lt;/p&gt;&#xA;&lt;p&gt;Consider some set of parameters &lt;span class=&quot;math-container&quot;&gt;$\{\lambda_i\}$&lt;/span&gt;. The first and second derivatives of the total energy with respect to these parameters in DFT read:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial E}{\partial\lambda_i}=\int\frac{\partial V(\mathbf{r})}{\partial\lambda_i}n(\mathbf{r})d\mathbf{r},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial^2 E}{\partial\lambda_i\lambda_j}=\int\frac{\partial^2V(\mathbf{r})}{\partial\lambda_i\lambda_j}n(\mathbf{r})d\mathbf{r}+\int\frac{\partial n(\mathbf{r})}{\partial\lambda_i}\frac{V(\mathbf{r})}{\partial\lambda_j}d\mathbf{r}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The trickier part of the calculation is the derivative of the density &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;, which can be written in terms of the first order change of the Kohn-Sham orbitals in the presence of the perturbation, which in turn can be determined using standarnd first order pertubation theory.&lt;/p&gt;&#xA;&lt;p&gt;This general formalism can be applied to study a variety of physical properties depending on the choice of parameters &lt;span class=&quot;math-container&quot;&gt;$\{\lambda_i\}$&lt;/span&gt;. For example, if the parameters are chosen to be atomic coordinates &lt;span class=&quot;math-container&quot;&gt;$\lambda_i=\mathbf{R}_i$&lt;/span&gt;, then the second derivative above corresponds to the matrix of force constants that can be used to calculate phonons. Another commonly used perturbation is that caused by an external electric field.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Baroni, Gironcoli, Dal Corso, Giannozzi, &lt;em&gt;Phonons and related crystal properties from density-functional perturbation theory&lt;/em&gt;, Rev. Mod. Phys. &lt;strong&gt;73&lt;/strong&gt;, 515 (2001)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-01T12:24:40.367" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2168" PostTypeId="2" ParentId="2135" CreationDate="2020-09-01T15:01:41.813" Score="4" Body="&lt;p&gt;&lt;strong&gt;Background.&lt;/strong&gt; The phonon density of states &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;g(\omega)=\sum_{\nu}\int\frac{d\mathbf{q}}{(2\pi)^3}\delta(\omega-\omega_{\mathbf{q}\nu})\approx\frac{1}{N_{\mathbf{q}}}\sum_{\nu}\sum_{\mathbf{q}}\Delta(\omega-\omega_{\mathbf{q}\nu}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; is the energy and &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; the energy of a phonon of wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; and branch &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt;. In the first equality the integral is over the full Brillouin zone. The second approximate equality gives a practical expression for the density of states used in numerical calculations, where the integral over the Brillouin zone is replaced by a sum over a discrete set of &lt;span class=&quot;math-container&quot;&gt;$N_{\mathbf{q}}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points, and these points should cover the Brillouin zone uniformly. The &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; function is a narrow function that peaks at &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; (e.g. a Gaussian) and replaces the Dirac &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; function in the numerical calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Brillouin zone sampling.&lt;/strong&gt; The integral or sum cover the entire Brillouin zone, so you need &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points across the entire zone. However, you only need to calculate explicitly the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points in the irreducible Brillouin zone (whose size depends on the symmetry of the system), because all other points can be constructed by applying the symmetry operations without the need to perform additional calculations. Having said this, the Fourier interpolation that is used to construct the dynamical matrix at arbitrary &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points after the coarse &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid has been fully converged is very cheap in computational terms. Therefore, it would not be a problem to brute-force sample the entire Brillouin zone at the Fourier interpolation step.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;VASP.&lt;/strong&gt; I use my own code to calculate phonons starting from the forces calculated from VASP (my code works in a similar fashion to Phonopy but exploits nondiagonal supercell to dramatically reduce the computational cost). Symmetry can be fully expoited in the VASP calculations for the forces, and on top of that only the phonons at the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points in the irreducible Brillouin zone need to be calculated. I am writing this about my code to show that &lt;em&gt;in principle&lt;/em&gt; one can use full symmetry when using VASP as an engine for the force calculations in phonon studies. However, I cannot say what other phonon codes like Phonopy do &lt;em&gt;in practice&lt;/em&gt; and whether in that case you can also use full symmetry.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-01T15:01:41.813" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2169" PostTypeId="2" ParentId="2155" CreationDate="2020-09-01T15:46:06.050" Score="5" Body="&lt;p&gt;In a calculation of the phonon density of states, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points feature in two ways:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Explicitly calculated &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points.&lt;/strong&gt; These are the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points for which you explicitly calculate the dynamical matrix, and are typically referred to as forming the &amp;quot;coarse &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid&amp;quot;. If you are using finite differences to calculate phonons, then these will correspond to the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points commensurate with the supercells that you are using in the calculations. If you are using DFPT to calculate phonons, then these will correspond to the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points for which you explicitly calculate the response. You should converge the density of states with respect to the coarse &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Interpolated &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points.&lt;/strong&gt; A coarse &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid that is converged (in the sense that the corresponding matrix of force constants decays to zero) is typically not enough to obtain a smooth phonon density of states. Instead, what you typically do is to perform a new phonon calculation on a much denser grid, typically called the &amp;quot;fine &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid&amp;quot;. For this second calculation, the dynamical matrices on the fine grid are not explicitly calculated but instead are constructed by Fourier interpolation over those of the coarse grid. You should converge the density of states with respect to the fine &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In practice, the computational bottleneck is in converging the coarse grid because you are explicitly doing the calculations in that case. My advice would be to pick a fixed size for the fine grid that is relatively large (larger than typical converged coarse grid sizes). Then perform a series of calculations for that fixed fine grid by increasing the size of the coarse grid until the DOS profile converges. This allows you to converge the coarse grid. Then fix the coarse grid to the converged value and now increase the size of the fine grid until the DOS profile converges again. The final combination of coarse and fine grids should be a good set of converged parameters.&lt;/p&gt;&#xA;&lt;p&gt;As to how many &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points to pick along each crystallographic direction, there is no fundamental reason why you should not be able to use the same number in all directions. However, convergence is typically faster along a direction that is longer, so a general rule of thumb for practical calculations is to use a grid of uniform density.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-01T15:46:06.050" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2170" PostTypeId="1" AcceptedAnswerId="2171" CreationDate="2020-09-01T16:26:07.670" Score="7" ViewCount="805" Body="&lt;p&gt;I have a number of trajectories of alanine dipeptide molecule and I'm interested in computing dihedral angles of each configuration.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\quad\quad\quad\quad$&lt;/span&gt;&lt;a href=&quot;https://i.stack.imgur.com/efI1N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/efI1N.png&quot; alt=&quot;Attempt to depict phi and psi peptide angles&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Have I selected the right atoms for computing each angle in the above image? Is possible to compute both angles, &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;, given only the coordinates of the heavy atoms (without the hydrogen in the green circle)?&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="1241" LastEditDate="2020-09-01T17:14:25.180" LastActivityDate="2020-09-01T17:35:50.313" Title="Dihedral angles of alanine dipeptide" Tags="|molecular-dynamics|proteins|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2171" PostTypeId="2" ParentId="2170" CreationDate="2020-09-01T16:53:10.410" Score="7" Body="&lt;p&gt;&lt;a href=&quot;https://proteopedia.org/wiki/index.php/Ramachandran_Plots&quot; rel=&quot;noreferrer&quot;&gt;Proteopedia&lt;/a&gt; suggests that the &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; angles of a Ramachandran plot only involve carbon and nitrogen atoms in their definition and specifically the carbons and nitrogens in the backbone of the protein or &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-peptide. These definitions are also used in an &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3061398/&quot; rel=&quot;noreferrer&quot;&gt;article from BioMol Concepts&lt;/a&gt;, describing new ways of presenting Ramachandran plots, which suggests these definitions are standard.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; should be the dihedral from a carbonyl carbon &lt;span class=&quot;math-container&quot;&gt;$\ce{C}_{i-1}$&lt;/span&gt;, to the following nitrogen &lt;span class=&quot;math-container&quot;&gt;$\ce{N}_i$&lt;/span&gt;, to the alpha carbon &lt;span class=&quot;math-container&quot;&gt;$\ce{C(\alpha)}_{i}$&lt;/span&gt;, to the next carbonyl carbon &lt;span class=&quot;math-container&quot;&gt;$\ce{C}_{i}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; should be the dihedral from nitrogen (the same from the definition of &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;) &lt;span class=&quot;math-container&quot;&gt;$\ce{N}_{i}$&lt;/span&gt;, to the alpha carbon &lt;span class=&quot;math-container&quot;&gt;$\ce{C(\alpha)}_{i}$&lt;/span&gt;, to the carbonyl carbon &lt;span class=&quot;math-container&quot;&gt;$\ce{C}_{i}$&lt;/span&gt;, to the next nitrogen &lt;span class=&quot;math-container&quot;&gt;$\ce{N}_{i+1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So to answer your questions, your drawing depicts two different dihedral angles and the actual &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; angles only involve heavy, backbone atoms. In your image, &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; is given by the (2,4,5,7) angle while &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; is the (4,5,7,9) angle.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-09-01T17:35:50.313" LastActivityDate="2020-09-01T17:35:50.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2172" PostTypeId="1" CreationDate="2020-09-01T19:54:43.007" Score="26" ViewCount="334" Body="&lt;p&gt;Machine learning is an increasingly common tool for developing force fields for molecular dynamics simulations. It's not totally clear what should be considered a machine-learning potential, but let's just say a machine learning potential is one which has many, many parameters which do not have any obvious physical interpretation. Any kind of neural network, Gaussian process, or permutationally invariant polynomial model, I would consider as an ML potential for this question.&lt;/p&gt;&#xA;&lt;p&gt;I have had quite a few conversations in which people say things along the lines of &amp;quot;machine learning potentials are slower than molecular mechanics potentials.&amp;quot; I've observed this to be true for certain ML potentials I've used, but I haven't seen any real benchmarking of this.&lt;/p&gt;&#xA;&lt;p&gt;Are there references which provide good comparisons of the speed of ML potentials to comparable classical force fields? I have seen a few papers comparing the accuracy of, for instance, classical versus ML water models, but not a corresponding comparison of the speeds of these models.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/2008.04198&quot; rel=&quot;noreferrer&quot;&gt;Here is a recent paper&lt;/a&gt; which augments a classical force field with an ML force field to kind of get the best of both worlds (speed and accuracy) to a certain extent. I still don't see a real time comparison though.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-03-23T15:27:15.603" LastActivityDate="2021-03-28T17:49:51.713" Title="Benchmark Timings of Machine Learning Potentials vs Molecular Mechanics Force Fields" Tags="|molecular-dynamics|reference-request|machine-learning|forcefields|benchmark-timings|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2173" PostTypeId="2" ParentId="2057" CreationDate="2020-09-01T21:43:16.643" Score="3" Body="&lt;p&gt;This &lt;a href=&quot;https://markovmodel.github.io/mdshare/ALA2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; contains three independent simulations from the following papers:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;F. Nüske, et al: Markov State Models from short non-Equilibrium Simulations - Analysis and Correction of Estimation Bias, J. Chem. Phys. 146 (2017), 094104.&lt;/li&gt;&#xA;&lt;li&gt;C. Wehmeyer and F. Noé: Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics, J. Chem. Phys. 148 (2018), 241703.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1241" LastActivityDate="2020-09-01T21:43:16.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2174" PostTypeId="2" ParentId="1774" CreationDate="2020-09-01T22:00:46.090" Score="13" Body="&lt;p&gt;This is not an exhaustive answer. This is an evolving research area in terms of applying ML to dataset generation. I am most familiar with the use case for constructing atomistic potential energy surfaces.&lt;/p&gt;&#xA;&lt;p&gt;The most common techniques I have seen all fall under the category of active learning. The goal of active learning in this context is essentially to determine whether or not a newly proposed structure for a dataset is redundant. Of course, no structure will be truly redundant, so the algorithm is essentially building a continuum that discriminates the similarity between structures in terms of how much new information they bring to the dataset. If a structure brings a lot of new information, then the uncertainty in the current models prediction should be large.&lt;/p&gt;&#xA;&lt;p&gt;There are many ways one can train the agent in an active learning model. I am not an expert on any of them, so I'll just give some references and a description of my understanding.&lt;/p&gt;&#xA;&lt;p&gt;In Ref. [1], a Gaussian process regression model is used to determine which configurations should be sampled for a many-body potential energy surface (PES). That is, one would have a separate fit for the 1-body, 2-body, etc. pieces of the PES, and these are combined via the many-body expansion. The way this model works is by having the active-learning model try to estimate the uncertainty in the prediction of the model which has been fitted to some initial dataset. So, a good candidate structure to add to the dataset is one which has a large uncertainty in the prediction (likely because it falls in the extrapolation category, rather than the interpolation category).&lt;/p&gt;&#xA;&lt;p&gt;In Ref. [2], the criteria for including a new data point in the training set is determined using a model called query-by-committee. What I have gathered is that one keeps around many different models which are generated from different subsets of the total available dataset. That detail could be wrong, but in any case, there is some way in which you keep around multiple similar models. One then proposes a new candidate structure, and each model labels that structure (predicts the energy/forces in the context of a PES). Then, the new structure is added to the dataset based on a parameter which related to the standard deviation of the predicted labels. Again, higher standard deviation means you want to add that structure more.&lt;/p&gt;&#xA;&lt;p&gt;Ref. [3] is sort of an on-the-fly application of any active learning method, really, in which the new structures are determined via a molecular dynamics simulation (based on an &lt;em&gt;ab initio&lt;/em&gt; method in this case). So, one uses the active learning method to determine if the new structure is similar to old structures, and if so, then you use a trained model to propagate the dynamics, and otherwise you do the full &lt;em&gt;ab initio&lt;/em&gt; evaluation, and add the new labeled data to the training set. I guess part of the simulation is pausing to re-train the model on-the-fly, but I imagine it would be more efficient to do this in batches or something. So, this is basically a way that one can start out doing AIMD and end up doing classical MD with an &lt;em&gt;ab initio&lt;/em&gt; trained PES. That will be quite cool if this works out in the long-term. I can imagine some interesting things you can do if you have a split CPU/GPU architecture for doing the training and force evaluation in parallel without having to fully stop either at any point (then like rewinding the dynamics at certain points).&lt;/p&gt;&#xA;&lt;p&gt;Ref. [4] is another example of a similar procedure where the researchers refine a neural-network potential on-the-fly using a committee-based approach. In this case, they definitely do random sub-sampling of an initial &lt;em&gt;ab initio&lt;/em&gt; simulation of water, and then train many neural network potentials, all of the same form, and then determine the uncertainty in a prediction based on the standard of all the predictions from the members of the committee, which are the various NN potentials.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Zhai, Y.; Caruso, A.; Gao, S.; Paesani, F. Active learning of many-body configuration space: Application to the Cs+–water MB-nrg potential energy function as a case study. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;152&lt;/em&gt; (14), 14410&lt;/li&gt;&#xA;&lt;li&gt;Smith, J. S.; Nebgen, B.; Lubbers, N.; Isayev, O.; Roitberg, A. E. &lt;a href=&quot;https://doi.org/10.1063/1.5023802&quot; rel=&quot;nofollow noreferrer&quot;&gt;Less is more: Sampling chemical space with active learning&lt;/a&gt;. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;148&lt;/em&gt; (24), 241733. DOI: 10.1063/1.5023802.&lt;/li&gt;&#xA;&lt;li&gt;Jinnouchi, R.; Miwa, K.; Karsai, F.; Kresse, G.; Asahi, R. &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.0c01061&quot; rel=&quot;nofollow noreferrer&quot;&gt;On-the-Fly Active Learning of Interatomic Potentials for Large-Scale Atomistic Simulations&lt;/a&gt;. &lt;em&gt;J. Phys. Chem. Lett.&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;11&lt;/em&gt; (17), 6946–6955. DOI: 10.1021/acs.jpclett.0c01061.&lt;/li&gt;&#xA;&lt;li&gt;Schran, C., Brezina, K., &amp;amp; Marsalek, O. (2020). &lt;a href=&quot;https://arxiv.org/ct?url=https%3A%2F%2Fdx.doi.org%2F10.1063%2F5.0016004&amp;amp;v=349532b3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Committee neural network potentials control generalization errors and enable active learning. arXiv preprint&lt;/a&gt; arXiv:2006.01541.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2022-02-16T20:00:59.397" LastActivityDate="2022-02-16T20:00:59.397" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2175" PostTypeId="1" CreationDate="2020-08-31T20:58:30.523" Score="8" ViewCount="84" Body="&lt;p&gt;When running a molecular dynamics simulation on a singular water molecule in vacuum to analyze its normal modes of vibration from the NVE (microcanonical) ensemble, the bending mode frequency is almost never present in comparison with the two stretching modes in the power spectrum.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why do these normal modes not equilibrate the same way?&lt;/strong&gt; Clearly the all three vibrational modes are not equilibrated equally.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit: Realized solution to missing bending mode.&lt;/strong&gt;&#xA;In NVE simulations for singular water molecule we rely on initialization of velocities using Maxwell-Boltzmann at a given temperature that is around 2 times the desired temperature. If this initialization of motion was motion strictly a combination of stretching modes, there is no reason for energy to transfer to the bending mode no matter how long you run. It's like saying, if you have three springs connecting two objects between two walls, and you give the initial condition of one of the two normal modes (say in-phase oscillation), in principle you will never see the other normal mode (out-of-phase oscillation) no matter how long you wait...&lt;/p&gt;&#xA;" OwnerUserId="1006" OwnerDisplayName="Houndbobsaw" LastEditorUserId="1006" LastEditDate="2020-09-02T05:55:24.873" LastActivityDate="2020-09-02T05:55:24.873" Title="Equilibration of normal modes in water molecule" Tags="|molecular-dynamics|computational-chemistry|vibrations|" AnswerCount="0" CommentCount="10" ClosedDate="2020-10-19T14:48:30.863" ContentLicense="CC BY-SA 4.0" />
  <row Id="2176" PostTypeId="2" ParentId="2166" CreationDate="2020-09-02T01:53:41.557" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How to get it into VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;The key point is to generate different POSCAR files.&lt;/strong&gt; Once you prepare input files, you can perform the calculation with VASP. I will assume you are considering &lt;a href=&quot;https://materialsweb.org/twodmaterials/result/mw-290&quot; rel=&quot;noreferrer&quot;&gt;monolayer T-phase HfS2&lt;/a&gt; and show how to generate compressive and tensile structures.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Initial structure:[HfS2.vasp]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;HfS2&#xA;1.0&#xA; 3.6389749050         0.0000000000         0.0000000000&#xA;-1.8194881106         3.1514448821         0.0000000000&#xA; 0.0000000000         0.0000000000        22.8899211884&#xA; Hf    S&#xA;  1    2&#xA; Direct&#xA; 0.000000000         0.000000000         0.500000000&#xA; 0.666666985         0.333332986         0.563098013&#xA; 0.333332986         0.666666985         0.436901987&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Then you can apply the biaxial strain for this structure by changing the length of &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{b}$&lt;/span&gt; at the same time. In detail, you can do this with the following python script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;def bistrain(path1,path2,strain):&#xA;&#xA;  with open(path1,'r') as f1:&#xA;    lines = f1.readlines()&#xA;&#xA;  lattice = np.zeros((3,3))&#xA;  for i in range(3):lattice[i,:]=list(map(float,lines[2+i].strip().split()))&#xA;&#xA;  lattice[0:2,0:2]=lattice[0:2,0:2]*strain&#xA;&#xA;  with open(path2+'strain_'+str(strain)+'.vasp','w') as f2:&#xA;    f2.write(lines[0])&#xA;    f2.write(lines[1])&#xA;&#xA;  for j in range(3):f2.write(&amp;quot;%20.16f  %20.16f  %20.16f&amp;quot; %(lattice[j,0],lattice[j,1],lattice[j,2])+'\n')&#xA;&#xA;&#xA;  for k in range(5,len(lines)):f2.write(lines[k])&#xA;&#xA;  #==================================================================&#xA;  path1='./HfS2.vasp'&#xA;  path2='./'&#xA;  #strain=0.99   ## compressive strain&#xA;  strain=1.01    ## tensile strain &#xA;  bistrain(path1,path2,strain)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What are the best ways to optimize geometry?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When the POSCAR is prepared, you can relax the structure &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2022/geometry-optimization-for-n-layers-in-vasp/2023#2023&quot;&gt;referring to this answer.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I fall into some traps?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For the initial structure, you should use fractional coordinates rather than Cartesian coordinates.&lt;/p&gt;&#xA;&lt;p&gt;May it hopes.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-02T01:53:41.557" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2177" PostTypeId="1" CreationDate="2020-09-02T08:52:21.567" Score="5" ViewCount="1175" Body="&lt;p&gt;It is mentioned &lt;a href=&quot;https://www.tcm.phy.cam.ac.uk/castep/documentation/WebHelp/content/modules/castep/thcastepbackground.htm&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It is possible to correct for the DFT band gap error by introducing an empirical scissors correction, which is effectively a rigid shift of the conduction band with respect to the valence band. This approach produces satisfactory results for such properties as optical spectra, provided the experimental band gap is accurate. The scissors operator scheme is very difficult to use in predictive studies and in the context of band gap engineering, when there is little or no experimental information about the electronic structure&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I implement scissor correction in VASP to study optical properties&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2020-09-02T10:02:31.777" Title="How to implement scissor-correction in VASP to study optical properties?" Tags="|density-functional-theory|vasp|band-structure|optical-properties|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2178" PostTypeId="2" ParentId="2177" CreationDate="2020-09-02T10:02:31.777" Score="3" Body="&lt;p&gt;For VASP, the model BSE method implements scissor operator correction to calculate the optical properties in the BSE framework. &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Improving_the_dielectric_function&quot; rel=&quot;nofollow noreferrer&quot;&gt;In particular, you can follow this tutorial.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, this method is able to deal with bulk materials. For two dimensional materials, you can use &lt;a href=&quot;http://www.yambo-code.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;YAMBO&lt;/a&gt; and &lt;a href=&quot;https://berkeleygw.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BerkeleyGW&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-02T10:02:31.777" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2179" PostTypeId="2" ParentId="2123" CreationDate="2020-09-02T11:57:20.290" Score="5" Body="&lt;p&gt;There are many applications/advantages for supercell band unfolding. Take the band unfolding program KPROJ as an example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl502107v&quot; rel=&quot;noreferrer&quot;&gt;Nano Lett. 14, 5189 (2014)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A k-projection technique (&lt;strong&gt;supercell band unfolding&lt;/strong&gt;) that includes the &lt;span class=&quot;math-container&quot;&gt;$k_\perp$&lt;/span&gt;-dependence of the surface bands is used to separate the contributions arising from the silicene and the substrate, allowing a consistent comparison between the calculations and the angle-resolved photoemission experiments.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.96.245111&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B 96, 245111&lt;/a&gt; and &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5100240&quot; rel=&quot;noreferrer&quot;&gt;Appl. Phys. Lett. 114, 223102 (2019)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Studying the effects of doping and interfacing.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/ncomms5311&quot; rel=&quot;noreferrer&quot;&gt;Nat. Commun. 5, 4311 (2014).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Understanding STS experiments.&lt;/p&gt;&#xA;&lt;p&gt;The most important point is that you can figure out &lt;strong&gt;which states are coming from which atoms&lt;/strong&gt; with band unfolding technique.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-02T11:57:20.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2180" PostTypeId="1" AcceptedAnswerId="2466" CreationDate="2020-09-02T12:20:20.933" Score="9" ViewCount="91" Body="&lt;p&gt;I was trying to look at the alanine dipeptide trajectories from &lt;a href=&quot;https://markovmodel.github.io/mdshare/ALA2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt; and track the trajectories in a Ramachandran plot. Below is a plot based on dihedral angles at each timestep for all trajectories (three simulations).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\qquad\qquad\qquad$&lt;/span&gt;&lt;a href=&quot;https://i.stack.imgur.com/C2Oj7m.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/C2Oj7m.png&quot; alt=&quot;Ramachandran plot of MD trajectory&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I was wondering what is the criteria (based on dihedral angles) to classify each configuration based on it's conformation and how many classes of conformations do we have in total? Something like the following picture:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\qquad$&lt;/span&gt;&lt;a href=&quot;https://i.stack.imgur.com/kuYUKl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kuYUKl.png&quot; alt=&quot;Diagram depicting phi and psi and an example Ramachandran plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="5" LastEditDate="2020-09-26T21:03:01.043" LastActivityDate="2020-10-09T14:13:14.627" Title="Finding conformations of peptide based on dihedral angles" Tags="|molecular-dynamics|software-recommendations|proteins|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2181" PostTypeId="1" AcceptedAnswerId="2184" CreationDate="2020-09-02T12:55:49.193" Score="7" ViewCount="838" Body="&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt;&#xA;In Hartree-Fock theory, the two-electron integral is given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$[ij|kl]$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$\int dx_{1}dx_{2}(\chi_{i}(x_{1})\chi_{j}(x_{1})\frac{1}{r_{12}}\chi_{k}^{*}(x_2)\chi_{l}(x_{2})$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am interested in writing out the 2e-integral for the Helium atom (for a given basis set) in PySCF. I want to do this with, and without density-fitting (DF)/resolution-of-identity (RI).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Attempt:&lt;/strong&gt; In my attempt to produce the 2e-integral from PySCF (without DF/RI), I have used the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto&#xA;mol = gto.M(atom='He 0 0 0', basis='6-31g')&#xA;eri = mol.intor('int2e', aosym='s8')&#xA;print(eri)&#xA;&#xA;&amp;gt;&amp;gt; [1.54393568 0.78544719 0.42702546 0.80395186 0.47618957 0.61593794]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; I was expecting a much larger data set.&#xA;I also imagined that there should be an SCF loop; however, this is not indicated by the PySCF documentation. &lt;strong&gt;Why am I getting unexpected results?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for any help.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Note: This question is related to the following earlier questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1154/one-center-two-electron-integrals-between-1s-sto&quot;&gt;One-center two-electron integrals between 1s STO&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/692/what-programs-can-do-electron-integrals-and-scf-calculations-with-more-than-one&quot;&gt;What programs can do electron integrals and SCF calculations with more than one CPU?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/62/exchange-correlation-two-electron-integrals&quot;&gt;Exchange-Correlation Two-Electron Integrals&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2021-02-05T18:44:27.467" LastActivityDate="2021-07-11T13:12:27.797" Title="Why is my quantum chemistry software not printing as many 2e- integrals as I expect?" Tags="|hartree-fock|integrals|pyscf|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2182" PostTypeId="1" CreationDate="2020-09-02T16:02:01.950" Score="7" ViewCount="130" Body="&lt;p&gt;I have a series of alanine dipeptide trajectories and would like to get the conformation type (&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, etc.) from the atom coordinates or dihedral angles. Does any package (like RDKit for instance) answer this?&lt;/p&gt;&#xA;" OwnerUserId="1241" LastActivityDate="2021-02-08T15:19:53.320" Title="Software recommendations for peptide conformation" Tags="|molecular-dynamics|software-recommendations|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2183" PostTypeId="1" CreationDate="2020-09-02T16:03:43.200" Score="7" ViewCount="157" Body="&lt;p&gt;I am studying Pd(II) metal-organic systems and have used GFN2-xTB (with implicit solvation) for high-throughput optimisation of candidate structures. I use the relative energies (from xtb) of different structural isomers as a screening metric based on empirical results. For the sake of validation, I aim to recreate those relative isomer energy calculations using DFT (optimisation, also with implicit solvation), which has previously been shown to agree with the xtb relative energies, for the top candidates.&lt;/p&gt;&#xA;&lt;p&gt;I am aware that GFN2-xTB is parameterised with a focus on geometries, frequencies and NCIs - not energies, so validation (by DFT) of its use in my workflow is important.&lt;/p&gt;&#xA;&lt;p&gt;I have a single case so far (although there may be more) where the relative isomer energies from DFT (PBE0/def2-svp/D3BJ) and xTB are opposing and in this case, I expect the difference to be due to a specific chemical functionality.&lt;/p&gt;&#xA;&lt;p&gt;My question here is about the approaches one might use to understand this type of result. I do not have a lot of expertise in exploring the specific components of DFT/semiempirical calculations. So far, I have tried to understand this effect with a small model system of the different isomers that isolates the effect of the troublesome functionality. However, I am curious about the best way to analyse the results. I.e. is comparing the energy difference of all of the components (electronic energy, Gsolv, dispersion correction) appropriate?&lt;/p&gt;&#xA;&lt;p&gt;If anyone could point me in the direction of a good resource on this type of issue, that would be appreciated. I am currently in the process of going back to some basic DFT reading.&lt;/p&gt;&#xA;" OwnerUserId="582" LastActivityDate="2020-09-05T15:30:38.723" Title="Approaches to understanding different relative energies between semiempirical and DFT methods" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2184" PostTypeId="2" ParentId="2181" CreationDate="2020-09-02T16:04:09.780" Score="5" Body="&lt;p&gt;I figured it might be worthwhile to address some the misconceptions in the question, as they are probably fairly common.&lt;/p&gt;&#xA;&lt;h3&gt;No SCF prior&lt;/h3&gt;&#xA;&lt;p&gt;The AO two-electron integrals (and actually all the AO integrals used in the SCF procedure) can be generated before doing any cycles. This is because they are just among atomic orbitals, which we know from the beginning of the calculation. In practice, you will probably see two-electron integrals recomputed during the SCF cycle, but this is just to avoid storing ~&lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt; such values, which becomes exorbitant for even fairly small calculations.&lt;/p&gt;&#xA;&lt;p&gt;To compute MO integrals, you would need to have completed all the SCF cycles, but as long as you aren't doing any Post-SCF methods, you don't actually need to explicitly transform the AO integrals to MO in order to compute the energy.&lt;/p&gt;&#xA;&lt;h3&gt;Fewer integrals than expected&lt;/h3&gt;&#xA;&lt;p&gt;This just comes down to symmetry. For &lt;span class=&quot;math-container&quot;&gt;$\ce{He}$&lt;/span&gt; with the 6-31G basis set, you have two atomic orbitals, which should lead to &lt;span class=&quot;math-container&quot;&gt;$2^4=16$&lt;/span&gt; two-electron integrals. However, because the integrals have permutational symmetry (see this &lt;a href=&quot;https://chemistry.stackexchange.com/questions/71527/how-does-one-compute-the-number-of-unique-2-electron-integrals-for-a-given-basis&quot;&gt;question on Chem SE&lt;/a&gt;), there are actually only 6 unique integrals, which you have written in your question.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;mol.intor('int2e', aosym='s8')&lt;/code&gt; command explicitly asks it to use this permutational symmetry. If you wanted it to simply produce all &lt;span class=&quot;math-container&quot;&gt;$n^4$&lt;/span&gt; integrals, you could instead use &lt;code&gt;mol.intor('int2e', aosym='s1')&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-11T13:12:27.797" LastActivityDate="2021-07-11T13:12:27.797" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2185" PostTypeId="2" ParentId="2182" CreationDate="2020-09-02T16:21:48.107" Score="6" Body="&lt;p&gt;[1] is a nice article that compares a couple of methods of protein structure assignment based on how well they agree with each other and how well they agree with expert assignments made in the Protein Data Bank. In the paper, they develop a new program called KAKSI, for which they make include an install link at the end of the paper.&lt;/p&gt;&#xA;&lt;p&gt;It's important to note that assigning secondary structure is somewhat subjective, so different programs will have different criteria for what constitutes an &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; helix or &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; sheet, both in terms of what features are considered (carbon-carbon distances, &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;/&lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;, hydrogen bond patterns) and what values correspond to a particular secondary structure element.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Taly,  J.-F.;  Martin,  J.;  Letellier,  G.;  de  Brevern,  A.  G.;  Gibrat,  J.-F.;  Marin,  A.  &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1249586/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Protein secondary structure assignment revisited:  a detailed analysis of different assignment methods&lt;/a&gt;. BMC Struct. Biol.2005,5, 17.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-09-02T17:49:48.687" LastActivityDate="2020-09-02T17:49:48.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2186" PostTypeId="1" CreationDate="2020-09-02T18:03:03.467" Score="14" ViewCount="1729" Body="&lt;p&gt;Can I use one code for geometry optimization and another code for a single point calculation on that optimized geometry? Can one publish results like that?&lt;/p&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="7" LastEditDate="2021-07-29T19:13:49.100" LastActivityDate="2021-07-29T19:13:49.100" Title="Can I use two different codes?" Tags="|density-functional-theory|software|geometry-optimization|" AnswerCount="5" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2187" PostTypeId="2" ParentId="2186" CreationDate="2020-09-02T18:17:29.687" Score="8" Body="&lt;p&gt;This has been done previously. In my experience the geometry is found with one code, and solvent corrections are performed with another. I have personally done this[1], and have had the results published. I performed a geometry optimization using QChem, and then solvent corrections using ORCA.&lt;/p&gt;&#xA;&lt;p&gt;Reference:&lt;/p&gt;&#xA;&lt;p&gt;[1] T. J. Doyon, J. C. Perkins, S. A. Baker Dockrey, E. O. Romero, K. C. Skinner,  P. M. Zimmerman, A. R. H. Narayan “Chemoenzymatic o-quinone methide formation” J. Am. Chem. Soc. 2019, 141, 20269–20277.&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-09-02T18:17:29.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2188" PostTypeId="2" ParentId="2186" CreationDate="2020-09-02T19:47:42.167" Score="9" Body="&lt;p&gt;Depending on what properties you care about.. maybe. I don't suggest this in general. I work on phonon calculations where forces must relaxed to a pretty strict tolerance. It has been my experience that the relaxed structure (using e.g. VASP) is not usually identical to what another code finds (e.g. ABINIT). Of course, the two structures are close and further relaxation with the 2nd code (in my case ABINIT) converges in only a couple steps. For something like total energy or electronic density of states, it probably doesn't really matter.&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2020-09-02T19:47:42.167" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2189" PostTypeId="2" ParentId="2186" CreationDate="2020-09-02T20:25:19.733" Score="-2" Body="&lt;p&gt;Sure. But you have to be aware that the referees can question about that.&lt;/p&gt;&#xA;&lt;p&gt;If there is no physical reason to mix codes, why mixing?&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-09-02T20:25:19.733" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2190" PostTypeId="2" ParentId="2070" CreationDate="2020-09-02T20:37:07.650" Score="2" Body="&lt;p&gt;I think I figured out parts of my question. But would really benefit from a VASP/AIMD expert weighing in.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;This appears to be the correct way of doing velocity scaling in VASP. And you can scale the velocity every &lt;code&gt;NBLOCK&lt;/code&gt; steps (but I'm not sure if/when it's more appropriate to scale every 1 step, 10 steps, etc.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Technically you can I think. I set the parameters listed in my question. And also &lt;code&gt;TEBEG = 100&lt;/code&gt; and &lt;code&gt;TEEND = 600&lt;/code&gt;. The temperatures and energies rose. I just don't know if this is correct to &amp;quot;heat&amp;quot; this way since I normally see people just do a constant temperature with a Nose-Hoover thermostat and NVT ensemble&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;*the total E actually decreased in method 2 because the potential energy of the bath decreased. So technically I should just look at E0+EK (the potential + kinetic energy), which does increase as the &amp;quot;temperature increases&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="979" LastActivityDate="2020-09-02T20:37:07.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2191" PostTypeId="1" AcceptedAnswerId="2193" CreationDate="2020-09-02T22:08:45.697" Score="25" ViewCount="1364" Body="&lt;p&gt;When carrying out a molecular dynamics simulation, one has to choose an ensemble. Depending on the problem, one usually works in the microcanonical (NVE), canonical (NVT), or grand canonical ensemble (NPT).&lt;/p&gt;&#xA;&lt;p&gt;In the NVE ensemble, maintaining reversibility of the simulation is very easy, as the total energy is conserved, so simply starting at the endpoint of the simulation with reversed momenta should reproduce the initial trajectory but in reverse.&lt;/p&gt;&#xA;&lt;p&gt;In the NVT and NPT ensembles, one has to maintain a constant temperature and/or pressure. Taking NVT as an example, there are many different ways to keep a constant temperature using different thermostats. Thermostats are all methods of keeping temperature constant by exchanging heat with a hypothetical heat bath. There is a range of complexities of thermostats and there's no need to discuss the subtleties of these here. The important point is only that some commonly-used thermostats, such as Nose-Hoover chains, are deterministic and hence result in reversible dynamics. On the other hand, there are Langevin thermostats which are very effective and efficient but are stochastic. So, short of playing a pseudo random generator backwards, the dynamics are not reversible. (I've never seen that reversing a random number generator thing done, but I think it's at least possible in principle?)&lt;/p&gt;&#xA;&lt;p&gt;I've seen it mentioned many times in the literature that Langevin thermostats result in dynamics which are not reversible. Because I've seen this mentioned so many times, I've always believed it to be important, but I have no idea why one would care about being able to use the end of a simulation as new initial conditions and then propagating the simulation in reverse.&lt;/p&gt;&#xA;&lt;p&gt;So, why does the reversibility of a molecular dynamics simulation matter? In what situations does using a deterministic thermostat/barostat provide a distinct advantage over a stochastic one?&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-01-30T03:09:35.200" Title="Why do people care about reversibility in molecular dynamics simulations?" Tags="|molecular-dynamics|computational-chemistry|statistical-thermodynamics|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2192" PostTypeId="2" ParentId="2166" CreationDate="2020-09-02T23:07:58.340" Score="8" Body="&lt;p&gt;Just to add to jack's answer.  This is easily implemented in &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Here is the same example which creates biaxial strain POSCARs from -5% to 5% strain in 1% increments.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from os import makedirs&#xA;import numpy as np&#xA;&#xA;for strain in np.arange(0.95, 1.05, 0.01):&#xA;    atoms = read(&amp;quot;POSCAR&amp;quot;)&#xA;    atoms.cell[0:2, 0:2] *= strain&#xA;    atoms.positions[:, 0:2] *= strain&#xA;    makedirs(&amp;quot;biaxial_{}&amp;quot;.format(strain))&#xA;    atoms.write(&amp;quot;biaxial_{}/POSCAR&amp;quot;.format(strain))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-02T23:07:58.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2193" PostTypeId="2" ParentId="2191" CreationDate="2020-09-03T01:14:31.943" Score="22" Body="&lt;p&gt;This is an excellent question! Reversibility in MD is useful because:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Time-reversibility in a  numerical integrator leads to a doubling of the accuracy order (&lt;a href=&quot;http://dx.doi.org/10.1017/S0962492917000101&quot; rel=&quot;noreferrer&quot;&gt;see Propositions 5.2 and Theorem 6.2 here&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Reversible maps &lt;a href=&quot;https://projecteuclid.org/euclid.aoap/1027961031&quot; rel=&quot;noreferrer&quot;&gt;can be readily Metropolized&lt;/a&gt;, for example in a hybrid Monte-Carlo scheme. This gives an easy way to enhance the sampling efficiency and eliminate the finite time-step error for sampling.&lt;/li&gt;&#xA;&lt;li&gt;Reversibility is aesthetically pleasing, since the exact equations of motion (both classical and quantum) are reversible.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am sure there are other reasons I have missed. These are the ones that come to mind.&lt;/p&gt;&#xA;" OwnerUserId="349" LastActivityDate="2020-09-03T01:14:31.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2194" PostTypeId="2" ParentId="2186" CreationDate="2020-09-03T03:00:49.697" Score="13" Body="&lt;p&gt;&lt;strong&gt;Absolutely.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I do this all the time, and often use several codes, since each code has its own strengths and weaknesses.&lt;/p&gt;&#xA;&lt;p&gt;I used 7 different codes in &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; where all I was doing was the ionization energy of one carbon atom (this means calculating the energy of a neutral carbon atom, and the energy of a singly ionized carbon cation and then reporting the difference between these two energies).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MOLPRO was used to optimize the basis sets (because not many codes can optimize basis set exponents).&lt;/li&gt;&#xA;&lt;li&gt;GAUSSIAN was used to optimize the k-type functions in the basis sets (GAUSSIAN cannot automatically optimize exponents, so we had to do the optimization manually, but GAUSSIAN can treat k-type functions whereas MOLPRO cannot).&lt;/li&gt;&#xA;&lt;li&gt;MOLCAS was used to calculate the integrals, because even though GAUSSIAN can use k-type and l-type functions, it cannot print the integrals in FCIDUMP format but MOLCAS can; and the integrals needed to be in FCIDUMP format because it's the format that NECI reads.&lt;/li&gt;&#xA;&lt;li&gt;NECI was used to do the FCIQMC calculations (the other programs either can't do FCIQMC or can't do it with as much control as we needed).&lt;/li&gt;&#xA;&lt;li&gt;CFOUR was used to calculate the DBOC and X2C corrections because MOLPRO, GAUSSIAN, MOLCAS and NECI couldn't do these at the time (and still probably cannot do DBOC).&lt;/li&gt;&#xA;&lt;li&gt;MRCC was used to calculate coupled cluster calculations for the X2C and DBOC corrections beyond CCSD(T), since the other programs cannot go beyond CCSD(T).&lt;/li&gt;&#xA;&lt;li&gt;Psi3 (a precursor to Psi4) was used to optimize some of the functions of the basis sets (but this part was done before we started this project, and it was the subject of previous papers, so we did not need to use Psi3 or Psi4 directly in this paper).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It is a &lt;em&gt;&lt;strong&gt;very&lt;/strong&gt;&lt;/em&gt; common thing to calculate integrals in one program, and post-SCF calculations in another program. That is the purpose of the &lt;a href=&quot;/questions/tagged/fcidump&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;fcidump&amp;#39;&quot; rel=&quot;tag&quot;&gt;fcidump&lt;/a&gt; file: To calculate integrals in one program, print them in FCIDUMP format, which is the universal format that almost all programs can read.&lt;/p&gt;&#xA;&lt;p&gt;Why is it that MOLPRO, PySCF, (Open)MOLCAS, ARROW, DALTON, DIRAC, GAMESS, DICE, BLOCK, CheMPS2, xacc, NECI, BAGEL, HANDE, Psi4 and probably others, can all read FCIDUMP format? It's because &lt;strong&gt;people want to be able to calculate integrals in one program and post-SCF calculations in a different program.&lt;/strong&gt; This is also the reason why MRCC has interfaces with CFOUR, MOLPRO, Psi4, DIRAC, ORCA, COLUMBUS, AMBER: people want to be able to calculate integrals in one program and do high-order coupled cluster in a different program. There's several other examples.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;As for geometry optimization:&lt;/strong&gt; We actually do single-point energy calculations at geometries obtained by different programs &lt;em&gt;all the time&lt;/em&gt; when we take a geometry from the literature and do a single-point energy calculation on it. We often even take the geometry from an X-ray crystallography experiment, then do a single-point energy calculation on it. Some programs can do certain types of single-point energy calculations (maybe they have a special DFT functional implemented, for example) but cannot do geometry optimization because the optimization algorithm is simply not implemented.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;But be careful:&lt;/strong&gt; Frozen-core CCSD(T) is MOLPRO, doesn't mean the same thing as frozen-core CCSD(T) in CFOUR, for example. What a method means in one software, is not necessarily what it means in another software. In addition to making sure you are clear in your paper about which basis set, SCF, post-SCF, and other methods are used, it is a good idea to also say which program was used (for both the geometry optimization, and for the single-point energy calculation).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-09-03T03:00:49.697" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2195" PostTypeId="2" ParentId="2123" CreationDate="2020-09-03T09:52:59.233" Score="6" Body="&lt;p&gt;Some reasons why you may want to do band unfolding have been explained by Jack. What I would like to add here concerns your second question about doing band structure calculations in the supercell: you don't want to do that.&lt;/p&gt;&#xA;&lt;p&gt;Supercells are typically needed when studying non-periodic systems using calculations with periodic boundary conditions. These could include the study of point defects (non-periodic in all 3 dimensions), line defects (non-periodic in 2 directions), surfaces or interfaces (non-periodic in 1 direction), etc. In all these cases, you build a supercell that is long along the non-periodic direction (or directions) so that you attempt to approach the non-periodic limit. In reality, what you have is still a periodic system in that direction, but the period is large enough that it is indistinguishable from a truly non-periodic system (of course this is the ideal, in practice you may not be able to use a large-enough supercell to reach this desired limit).&lt;/p&gt;&#xA;&lt;p&gt;So what does this all mean for a band dispersion? A band dispersion is a relation between the energy and momentum of an electron, &lt;span class=&quot;math-container&quot;&gt;$E(\mathbf{k})$&lt;/span&gt;, where the momentum &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; takes some allowed value in the first Brillouin zone. We need to distinguish two scenarios:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Real non-periodic system.&lt;/strong&gt; In a real non-periodic system, the size of the Brillouin zone along the non-periodic direction(s) is zero, that is, there is no Brillouin zone along that direction. This means it makes no sense to talk about a band dispersion along the non-periodic direction. The correct way to think about this is in terms of densities of states, which &lt;em&gt;are&lt;/em&gt; well-defined even for a non-periodic system.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Simulating a non-periodic system with a supercell.&lt;/strong&gt; In this case, you will have a very long supercell along the non-periodic direction, which means that you will have a very short Brillouin zone along that direction, but crucially it will not be zero. So in principle you &lt;em&gt;could&lt;/em&gt; plot/calculate a dispersion along this short Brillouin zone direction as you suggest. However, this dispersion has no physical meaning. You will get band folding, so a large number of overlaping bands. The larger the supercell, the more bands you will get, until they form a sort of continuum. This is actually the band folding slowly building up the density of states of the truly non-periodic system, which is what is really meaningful in a non-periodic system. Therefore, my advice would be to focus on the physically meaningful density of states when attempting to simulate non-periodic systems.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-03T09:52:59.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2196" PostTypeId="1" AcceptedAnswerId="2214" CreationDate="2020-09-03T14:51:37.790" Score="9" ViewCount="249" Body="&lt;p&gt;I made a binary special quasi-random structure (SQS) using &lt;code&gt;mcsqs&lt;/code&gt; (distributed as part of the &lt;code&gt;alloy theoretic automated toolkit (ATAT)&lt;/code&gt;). The structure was generated using their own example FCC input file - &lt;code&gt;rndstr.in&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1 1 1 90 90 90&#xA;0   0.5 0.5&#xA;0.5 0   0.5&#xA;0.5 0.5 0&#xA;0 0 0 A,B&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The space group for FCC is 225, but the SQS generated are random. One had a space group of 8, another 12, yet another 160.&lt;/p&gt;&#xA;&lt;p&gt;As far as I understand, SQS maintain symmetry. They are random, so perhaps an &lt;span class=&quot;math-container&quot;&gt;$L1_2$&lt;/span&gt; ordered structure with space group 221 would not be an SQS, but 225 FCC is what any FCC SQS should be. Why then is &lt;code&gt;mcsqs&lt;/code&gt; giving such haphazard results?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-01-02T20:16:06.900" LastActivityDate="2021-01-02T20:16:06.900" Title="Why does mcsqs change the space group of generated SQS?" Tags="|symmetry|space-groups|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2197" PostTypeId="2" ParentId="1271" CreationDate="2020-09-03T17:07:46.277" Score="3" Body="&lt;h3&gt;FINDSYM&lt;/h3&gt;&#xA;&lt;p&gt;Another useful tool to determine crystal symmetry is &lt;a href=&quot;https://stokes.byu.edu/iso/findsym.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;FINDSYM&lt;/a&gt;. It works with the .cif format exclusively, so you may have to convert your structural files to .cif before using it.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-09-03T18:27:20.430" LastActivityDate="2020-09-03T18:27:20.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2198" PostTypeId="1" AcceptedAnswerId="2199" CreationDate="2020-09-03T20:19:19.863" Score="10" ViewCount="440" Body="&lt;p&gt;As the title says, the Morse potential (&lt;a href=&quot;https://en.wikipedia.org/wiki/Morse_potential&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Morse_potential&lt;/a&gt;) is an exactly solvable model in quantum mechanics, just like the quantum harmonic oscillator. Extensions of it are used in modeling molecular vibrational states to great success as far as I know.&lt;/p&gt;&#xA;&lt;p&gt;However, in solid state physics we seem to stop at using phonons (collections of harmonic oscillators) to describe the vibrations of solids. Why not use the Morse potential to model the interactions between atoms in a solid instead of as harmonic springs, if it's just as exactly solvable?&lt;/p&gt;&#xA;" OwnerUserId="1303" LastActivityDate="2020-09-04T18:30:37.977" Title="Morse potential for phonons in solids instead of the harmonic potential approximation?" Tags="|phonons|vibrations|solid-state-physics|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2199" PostTypeId="2" ParentId="2198" CreationDate="2020-09-03T21:34:52.487" Score="10" Body="&lt;h3&gt;Some people do:&lt;/h3&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3556940&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; there is a system coupled to a bath of Morse oscillators rather than a bath of harmonic oscillators, but it is not exactly solvable, they used a numerical approach called &lt;a href=&quot;/questions/tagged/mctdh&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;mctdh&amp;#39;&quot; rel=&quot;tag&quot;&gt;mctdh&lt;/a&gt;. When it is said that the Morse potential is &amp;quot;exactly solvable&amp;quot;, what it means is that you can solve the vibrational Schroedinger equation for a Morse potential analytically (the end result is a formula for the vibrational energies and wavefunctions of the system). What about if there is a spin coupled to 500 Morse oscillators, do we have an exact solution for the overall energies and wavefunctions of this very complicated system? We do not even have an exact solution in the case where the oscillators are harmonic oscillators; this would be called the &amp;quot;spin-boson problem&amp;quot; and it's not exactly solvable except in specific cases. Finally, even if there &lt;em&gt;&lt;strong&gt;was&lt;/strong&gt;&lt;/em&gt; only one Morse oscillator, the solutions that you see in that Wikipedia page you linked, are not very simple or easy to use: For example the exact solutions for the quantum harmonic oscillator do not involve generalized Laguerre polynomials but for the Morse oscillator they do.&lt;/p&gt;&#xA;&lt;h3&gt;Most people don't:&lt;/h3&gt;&#xA;&lt;p&gt;In solid state physics, many people model a system coupled to phonons using models like the spin-boson model or generalizations of it. For example in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.081305&quot; rel=&quot;noreferrer&quot;&gt;this paper of mine&lt;/a&gt; we study how a qubit would undergo decoherence if a quantum computer were to be made with GaAs quantum dots. The qubit can be defined as follows: 0 = absence of an exciton, 1 = presence of an exciton, so it's a 2-level system, but it's coupled to all of the vibrations of the semiconductor lattice in which it lies. 2-level systems can be considered as &amp;quot;spin-1/2 particles&amp;quot;, so what we have is a spin interacting with a bunch of vibrations. These vibrations are approximated to be harmonic oscillators, so we simply have the aforementioned &amp;quot;spin-boson problem&amp;quot; which has been studied for several decades (and still cannot be solved exactly most of the time). Now there's several reasons why we chose this simple spin-boson model with harmonic oscillators rather than using a Morse potential:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Neither case (harmonic oscillators or Morse oscillators) is exactly solvable when you have not only the oscillators (nuclear vibrations) but also the spin (or electronic/excitonic degrees of freedom), but at least for the harmonic case we have simple analytic expressions for things such as the Feynman-Vernon influence functional which describes the influence of the vibrations on the spin; for Morse oscillators we do not have such a simple influence functional. So the calculations are much easier in the harmonic case compared to the Morse oscillator case.&lt;/li&gt;&#xA;&lt;li&gt;A Morse oscillator &lt;em&gt;&lt;strong&gt;is&lt;/strong&gt;&lt;/em&gt; actually harmonic at the very bottom, and only starts to deviate from a harmonic oscillator for much larger internuclear distances as the system starts to &lt;em&gt;&lt;strong&gt;dissociate.&lt;/strong&gt;&lt;/em&gt; If we were to model a qubit in a GaAs semiconductor at such a high temperature that the semiconductor is in the midst of breaking apart (the Ga and As atom are dissociating from one another), we may wish to use an anharmonic potential, but this is rarely (or never!) the case. &lt;strong&gt;Consider this:&lt;/strong&gt; Which vibrational levels of these oscillators actually have a significant population in your system? Surely not the ones at the top of &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1005/5&quot;&gt;this Morse potential&lt;/a&gt; (see v=8 and 9 and observe that their outer turning points are at internuclear distances of around r=12 and 14 which is about triple the internuclear distance at equilibrium; do you picture your solid-state lattice having its internuclear distances so far away from equilibrium in the normal scenario in your interest?).&lt;/li&gt;&#xA;&lt;li&gt;For this particular system, a spectral distribution function (which tells you how strongly each oscillator couples to the &amp;quot;spin&amp;quot;) was determined from fitting the dynamics of the spin-boson model, and the empirically obtained parameters of the spectral function matched almost exactly the values of those parameters obtained from first-principles calculations, and the chances of this being pure luck are so extremely low that we believe that the simple spin-boson model with harmonic oscillators is an excellent approximation.&lt;/li&gt;&#xA;&lt;li&gt;If we were not in a case where we know the spin-boson model with harmonic oscillators is an excellent approximation (as described in the last bullet point), we can stop and think about all the other multitude of approximations we are making (maybe the ignoring of spin-orbit coupling, maybe the ignoring of the difference between relativistic mass and non-relativistic mass, maybe the use of the Born-Oppenheimer separation between the electronic/excitonic and nuclear/phononic/bosonic degrees of freedom, or maybe we don't have the exact parameters for the exact solid in question so we are just assuming we can use the parameters from a similar solid that has been studied in more detail, etc.), and then realize that there's just so many approximations going on that &lt;a href=&quot;https://www.brainyquote.com/quotes/john_von_neumann_137953&quot; rel=&quot;noreferrer&quot;&gt;Jon von Neumann's quote&lt;/a&gt; applies: &lt;strong&gt;&amp;quot;Why be precise when we don't know what we're talking about?&amp;quot;&lt;/strong&gt; Will you use quadruple precision (33-36 digits) for solving a differential equation telling you what weather it will be tomorrow, when the coefficients in the differential equation have enormous error bars? Then don't use an anharmonic bath if you don't have a fairly precise description of all other relevant information (relativistic effects, spin-orbit coupling, etc.).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; The bottom line is that you would be making your life harder (more difficult equations that can only be solved less efficiently or with less accuracy with the same resources), and most of the time you would not be gaining a better understanding of the relevant physics.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-04T02:00:03.683" LastActivityDate="2020-09-04T02:00:03.683" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2200" PostTypeId="2" ParentId="2078" CreationDate="2020-09-04T00:09:41.267" Score="7" Body="&lt;p&gt;There are two ways I have approached this type of problem in the past. Which method is preferable depends on the types of structures you are trying to filter through.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Using the Kabsch Algorithm:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Roughly the way this method works is as follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Rotate all molecules into a common frame determined by the current structure&lt;/li&gt;&#xA;&lt;li&gt;Take the difference of cartesian coordinates between all pairs of molecules&lt;/li&gt;&#xA;&lt;li&gt;Throw out any structure which has differences smaller than some threshold&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The hard part of this approach is how to rotate all the molecules into a common frame. The simplest way to do this that I am aware of is using the Kabsch algorithm. The kabsch algorithm calculates the optimal rotation matrix to a point which minimizes the RMSD between two points. The rotation matrix is typically calculated via the singular-value decomposition. There is some interesting math behind why the SVD is the appropriate way to do this, but I think it's probably unnecessary here.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/charnley/rmsd/blob/master/rmsd/calculate_rmsd.py&quot; rel=&quot;noreferrer&quot;&gt;Here is a python implementation&lt;/a&gt; on github which is designed to rotate molecules into the same frame using the kabsch algorithm. I have used this code before and it works as expected.&lt;/p&gt;&#xA;&lt;p&gt;So, the way you do this in total is to read all of your structures into a list of numpy arrays, loop through this list and rotate every molecule after the current on onto the axes of the current molecule. Then, take the difference between this molecule and all subsequent molecules. If the resulting matrix is appropriately close to all zeros (probably by maximum vector length, but whatever metric is probably fine), then you can remove all those molecules which meet your convergence criteria.&lt;/p&gt;&#xA;&lt;p&gt;Keep doing this process until you reach the end of the list. As a side note, you should pre-process the molecules by shifting everything by its centroid.&lt;/p&gt;&#xA;&lt;p&gt;If you had to do this with like millions of structures which are very large, then the algorithm would be pretty expensive as you have to do a bunch of matrix factorizations and the algorithms is worst-case &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; for the comparison step.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Graph-Based Approach&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another way to filter out duplicate molecules is by representing each molecule as a graph. Forming the graph is fairly simple as long as you have a good measure of when two atoms are connected. So, for instance, the edges of the graph are likely to be represented by covalent bonds. One can also represent the edges by hydrogen bonds if you're working with a van der Waal's cluster of some kind.&lt;/p&gt;&#xA;&lt;p&gt;The way this method works is as follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Build a graph representing each molecule based on some connectivity criteria&lt;/li&gt;&#xA;&lt;li&gt;Perform an isomorphism check among all pairs of graphs, keeping only one of each unique graph&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In theory, the hardest part of this is doing the isomorphism check, but there are great software packages which can do this for you, such as &lt;a href=&quot;https://networkx.github.io/&quot; rel=&quot;noreferrer&quot;&gt;networkx&lt;/a&gt; for a Python option.&lt;/p&gt;&#xA;&lt;p&gt;If you use networkx, probably the easiest way to build the graphs is to determine the connectivity of all atoms in each molecule, and build an &lt;a href=&quot;https://en.wikipedia.org/wiki/Adjacency_matrix&quot; rel=&quot;noreferrer&quot;&gt;adjacency matrix&lt;/a&gt;. networkx can then make a graph object from this adjacency matrix. Then you do just as in the previous method and loop through the pairs of molecules removing any which turn out to be isomorphic to the current reference graph.&lt;/p&gt;&#xA;&lt;p&gt;Now, this method seems pretty easy, but a graph representation of a molecule is not unique. For instance, all graphs representing the boat, chair, and planar conformations of cyclohexane result in identical graphs. In order to make the conformations distinguishable, you have to attach weights to either the edges or the nodes of the graph. Probably the easiest thing to do would be to attach a list of angles of each triplet of atoms. You would also need to label the handedness of each chiral center, as I don't think angles would be enough there.&lt;/p&gt;&#xA;&lt;p&gt;The advantage of the graph approach is that it avoids problems with numerical precision, and it can be fairly fast I think. The drawback is having to make these weights for the nodes if you have to keep around minima which only differ by rotation of atoms in space.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this is helpful!&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2020-09-04T00:09:41.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2201" PostTypeId="2" ParentId="2186" CreationDate="2020-09-04T02:02:26.670" Score="5" Body="&lt;p&gt;Yes, absolutely.&lt;/p&gt;&#xA;&lt;p&gt;The reason is that different codes are &lt;strong&gt;required&lt;/strong&gt; to generate exactly the same results if they refers to the same methods.&lt;/p&gt;&#xA;&lt;p&gt;E.g., if you use Gaussian, Orca, Molpro, NWChem, Psi4, PySCF...(I cannot list the full list) to perform HF/cc-pVTZ to study H&lt;sub&gt;2&lt;/sub&gt;, they should generate exactly the same results, including the energy and wave functions.&lt;/p&gt;&#xA;&lt;p&gt;Different packages can of course output in different formats.  Besides, Different packages can have different default values for some parameters (E.g., the threshold of optimization, the geminal beta of explicit correlated methods, size of integral grids, the initial orbital for SCF iteration, etc.)  It is the users' responsibility to check the default value, because apparently it is impossible for the pioneer package to tell you how will the after-coming software treats the default values.&lt;/p&gt;&#xA;&lt;p&gt;So, if you perform the exactly same computation use two different packages, here &lt;strong&gt;same&lt;/strong&gt; means the same explicitly given parameters and implicit parameters, while get different results, we should consider&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;At least one of them has a bug; or&lt;/li&gt;&#xA;&lt;li&gt;They should be referred as different methods, e.g., the PM7 methods in Gaussian and in MOPAC. This should be mentioned in the manual, or should be considered as a bug.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In summary, it is the methods matter, not the software.  Since it is a common way to perform the geometry optimization using a cheaper method, and to do the single-point computation using a more accurate method, of course it is acceptable to use different software, considering some methods are only available in less-used packages.&lt;/p&gt;&#xA;" OwnerUserId="339" LastActivityDate="2020-09-04T02:02:26.670" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2202" PostTypeId="2" ParentId="2198" CreationDate="2020-09-04T02:15:46.617" Score="6" Body="&lt;p&gt;Even in treating molecular vibrations, the Morse potential is not always the best, because:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There's cases where the potential is more &amp;quot;harmonic&amp;quot; than &amp;quot;Morse-like&amp;quot;, for example in the asymmetric stretching of water.  It is the same case in solid state physics: considering the most crude approximation that we fix all the atoms in a solid while looking into the motion of one atom in bulk.&lt;/li&gt;&#xA;&lt;li&gt;The Morse potential is more expensive to evaluate since it has two more  parameters than the harmonic potential when considering just two atoms, and it is even harder when we consider the polyatomic case.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="339" LastEditorUserId="5" LastEditDate="2020-09-04T18:30:37.977" LastActivityDate="2020-09-04T18:30:37.977" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2203" PostTypeId="1" CreationDate="2020-09-04T02:33:27.467" Score="10" ViewCount="168" Body="&lt;p&gt;In computational chemistry when using transition state theory we often use standard states for all involved structures. However, sometimes people argue that it should be corrected for concentration (and/or pressure) since that can influence the free energy.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume we got a reaction A + B &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; C. A is 5 molar, B is 2 molar. What concentration should be used for each structure A, B, C and the transition state TS?&lt;/p&gt;&#xA;&lt;p&gt;If I use starting concentrations the concentration of C would be 0, which is problematic, but if I use final concentrations B would be 0. And in any case in my understanding of transition state theory the concentration of the transition state is considered to be 0.&lt;/p&gt;&#xA;&lt;p&gt;And what is best to do in cases with several intermediates, different equilibrium and things like that?&lt;/p&gt;&#xA;&lt;p&gt;So how does one actually correct for concentration?&lt;/p&gt;&#xA;" OwnerUserId="705" LastEditorUserId="5" LastEditDate="2020-09-26T21:06:03.680" LastActivityDate="2020-10-30T14:54:18.440" Title="Correcting thermodynamic data for concentration, what concentration is best to use?" Tags="|computational-chemistry|thermodynamics|transition-state|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2204" PostTypeId="1" CreationDate="2020-09-04T14:05:08.480" Score="8" ViewCount="334" Body="&lt;p&gt;I would like to use &amp;quot;&lt;a href=&quot;https://lammps.sandia.gov/doc/fix_deposit.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;fix deposit&lt;/a&gt;&amp;quot; with ReaxFF to add atoms to a simulation in which I deposit molecules on a surface.&lt;/p&gt;&#xA;&lt;p&gt;I have built working scripts for my system with other force fields. However, there is an issue with the ReaxFF implementation in LAMMPS where depositing new molecules into a system will cause an error &lt;a href=&quot;https://lammps.sandia.gov/threads/msg66005.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;(too many ghost atoms&lt;/a&gt;). As per the link, the error most likely arises because the USER-REAXC package pre-allocates memory for atoms based on the initial number of atoms in the simulation box.&lt;/p&gt;&#xA;&lt;p&gt;I do know the maximum number of atoms needed before the simulation starts. I am looking for a workaround for this issue, which would allow me to pre-allocate memory for this number of atoms, which I can later add to the simulation box.&lt;/p&gt;&#xA;" OwnerUserId="1203" LastEditorUserId="5" LastEditDate="2021-10-30T20:03:00.317" LastActivityDate="2021-10-30T20:03:00.317" Title="Fix deposit and USER-REAXC: pre-allocating memory for atoms when using LAMMPS with ReaxFF" Tags="|molecular-dynamics|high-performance-computing|lammps|software-assistance|forcefields|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-26T00:05:54.740" ContentLicense="CC BY-SA 4.0" />
  <row Id="2206" PostTypeId="2" ParentId="2191" CreationDate="2020-09-04T16:23:01.313" Score="13" Body="&lt;p&gt;I would argue the main reason this is important is philosophical, linked to the history of science and determinism (&lt;a href=&quot;https://en.wikipedia.org/wiki/Laplace%27s_demon&quot; rel=&quot;noreferrer&quot;&gt;as proposed by Laplace&lt;/a&gt;). Newtonian mechanics is mathematically reversable while any observation in a &amp;quot;real world&amp;quot; system is one of irreversibility and increasing entropy, which is why we end up with &lt;a href=&quot;https://en.wikipedia.org/wiki/Loschmidt%27s_paradox&quot; rel=&quot;noreferrer&quot;&gt;Loschmidt paradox&lt;/a&gt;. From a theoretical point of view, keeping a link to a Hamiltonian in the NVT ensemble (as in the Nosé-Hoover thermostat) preserves a number of nice mathematical properties, including &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.37.252&quot; rel=&quot;noreferrer&quot;&gt;time-reversible equations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In practice, the finite precision of a molecular simulation means than even an NVT run isn't reversible. &lt;a href=&quot;https://doi.org/10.1017/CBO9780511816581&quot; rel=&quot;noreferrer&quot;&gt;Small errors grow&lt;/a&gt; until the final state has lost the precision required to get back to the initial state when we reverse the time integrator. The fact this point is often ignored show how infrequently this is a concern in most MD studies. In getting thermodynamics properties from MD, we deliberately average the system for long enough that all dynamic information is lost (all of phase space covered satisfying the ergodic hypothesis) so the reversibility is irrelevant. Even for non-equilibrium thermodynamics we work with an ensemble of phase spaces trajectories where the individual trajectories are unimportant.&lt;/p&gt;&#xA;&lt;p&gt;A &lt;a href=&quot;https://doi.org/10.1007/BF01048022&quot; rel=&quot;noreferrer&quot;&gt;little known work by Verlet&lt;/a&gt; using integers appears to provide exact reversibility using MD. Some interesting &lt;a href=&quot;https://arxiv.org/pdf/1801.09899.pdf&quot; rel=&quot;noreferrer&quot;&gt;recent&lt;/a&gt; work by Bill Hoover explores some applications of exactly reversable integrators.&lt;/p&gt;&#xA;" OwnerUserId="1305" LastEditorUserId="1305" LastEditDate="2020-09-06T14:25:00.550" LastActivityDate="2020-09-06T14:25:00.550" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2207" PostTypeId="2" ParentId="1985" CreationDate="2020-09-04T16:34:03.477" Score="7" Body="&lt;p&gt;Energy in an NPT simulation is not conserved, but (once equilibrated), it will fluctuate around an average value, and that average value has meaning. That is the ensemble average for your NPT and is a valuable and useful property.&lt;/p&gt;&#xA;&lt;p&gt;You are also correct that the internal energy is the summation of potential and kinetic contributions. To be thorough, pp. 60 of Computer Simulations Of Liquids by Allen &amp;amp; Tildesley (2nd edition) note&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    E = \langle H\rangle = \langle \mathcal{K} \rangle + \langle \mathcal{V} \rangle&#xA;\end{equation}&lt;/span&gt;&#xA;where E is internal energy, H is Hamiltonian, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{K}$&lt;/span&gt; is kinetic energy and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{V}$&lt;/span&gt; is potential energy (calculated using a force-field in this case). I recommend &lt;a href=&quot;https://global.oup.com/academic/product/computer-simulation-of-liquids-9780198803201?cc=ca&amp;amp;lang=en&amp;amp;&quot; rel=&quot;noreferrer&quot;&gt;Allen &amp;amp; Tildesley&lt;/a&gt; as well as &lt;a href=&quot;https://www.amazon.ca/Understanding-Molecular-Simulation-Algorithms-Applications/dp/0122673514&quot; rel=&quot;noreferrer&quot;&gt;Frenkel &amp;amp; Smit &lt;/a&gt;if you want more information on gathering ensemble averaged properties from atomistic simulations. They are the two tomes of the field.&lt;/p&gt;&#xA;&lt;p&gt;It is fair to compare the internal energies of two different composition simulations. It is however critical that both simulations are properly equilibrated and sampled so that &lt;span class=&quot;math-container&quot;&gt;$\langle \mathcal{K} \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\langle \mathcal{V} \rangle$&lt;/span&gt; are reliable estimates.&lt;/p&gt;&#xA;&lt;p&gt;I recommend equilibrating for several nanoseconds at the least, and sampling for several nanoseconds at the least.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2020-09-04T16:34:03.477" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2208" PostTypeId="2" ParentId="2183" CreationDate="2020-09-04T21:15:00.747" Score="5" Body="&lt;p&gt;When modeling metal-organic systems, it is not uncommon for DFT to be wrong by far more than 5 kJ/mol. They are notoriously tricky to model. On the DFT side of things, I can say you're using a pretty small basis set of def2-SVP. That's going to be one factor limiting the quality of your DFT results. Also, Pd is pretty heavy, and relativistic corrections might be important. None of this is to mention the inherent limitations of PBE0.&lt;/p&gt;&#xA;&lt;p&gt;On the semi-empirical side, GFN2-xTB is not meant for reliable energies of systems, and I'd expect it to do particularly poorly for transition metal complexes. It is going to be very difficult to &lt;em&gt;understand&lt;/em&gt; why the two give very different results, seeing how highly empirical GFN2-xTB is by design. Without a thorough benchmarking comparing the energies of many different systems at the PBE0-D3(BJ)/def2-SVP level of theory and GFN2-xTB level of theory, it's going to be hard to make any claims. It should also be mentioned that there are a few differences here regardless. For instance, GFN2-xTB uses the D4 dispersion correction scheme, whereas you are using D3(BJ) at the DFT level. Furthermore, you are using an implicit solvation model with GFN2-xTB but not with DFT.&lt;/p&gt;&#xA;&lt;p&gt;Since GFN2-xTB is supposed to be alright for vibrational frequencies, you can compare the vibrational contribution to the enthalpy or Gibbs free energy between PBE0-D3(BJ)/def2-SVP and GFN2-xTB to start. That will give you an idea if it's related to poor geometries and/or frequencies. Beyond that, you can compare the electronic energies. The only way to identify any systematic effect here is to compare the energies for many different systems to see if you can identify trends, and there simply may not be any. Overall, I personally would be &lt;em&gt;very&lt;/em&gt; hesitant to compare the relative energies of any inorganic or metal-organic systems using any empirical method, including GFN2-xTB.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-09-05T15:30:38.723" LastActivityDate="2020-09-05T15:30:38.723" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2209" PostTypeId="2" ParentId="1078" CreationDate="2020-09-05T01:51:50.320" Score="6" Body="&lt;p&gt;TeraChem is commercial, but the demo mode will handle calculations taking up to ten minutes and that is free. Ten minutes for a single point energy and gradient gets you pretty far with TeraChem (unlike other CPU codes).&lt;/p&gt;&#xA;" OwnerUserId="1307" LastActivityDate="2020-09-05T01:51:50.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2210" PostTypeId="1" AcceptedAnswerId="2211" CreationDate="2020-09-05T12:14:08.733" Score="11" ViewCount="3768" Body="&lt;p&gt;This question is coming from &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5129311?journalCode=apl&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, which investigated the spontaneous spin and valley polarizations of monolayer LaBr2.&lt;/p&gt;&#xA;&lt;p&gt;The geometric information of monolayer LaBr2 is displayed as following (Br: black, La: orange):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iPs3N.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iPs3N.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then the author argues that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As shown in (a), each La atom is trigonal prismatic coordinated to six Br atoms. Under such a condition, the d orbitals of La split into three groups: &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$e_1$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$d_{xz}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_{yz}$&lt;/span&gt;), and &lt;span class=&quot;math-container&quot;&gt;$e_2$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$d_{xy}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_{x^2-y^2}$&lt;/span&gt;), see (d):&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oLYXC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oLYXC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How may I understand this partition of five d-orbitals under such a trigonal prismatic geometry?&lt;/li&gt;&#xA;&lt;li&gt;Is that related to crystal splitting?&lt;/li&gt;&#xA;&lt;li&gt;How to explain this?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2021-11-10T18:13:48.727" LastActivityDate="2021-11-10T18:13:48.727" Title="How to understand the crystal field splitting of d-orbitals in a trigonal prismatic geometry?" Tags="|solid-state-physics|crystal-field|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2211" PostTypeId="2" ParentId="2210" CreationDate="2020-09-05T23:11:30.803" Score="10" Body="&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Is that related to crystal splitting?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes. In case there are any doubts, the caption to the figure does make it clear that it's related to &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;noreferrer&quot;&gt;crystal field splitting&lt;/a&gt;, &amp;quot;(d) The splitting of d orbitals&#xA;under the trigonal prismatic crystal field&amp;quot;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How may I understand this partition of five d-orbitals under such a trigonal prismatic geometry?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you haven't already done so, I would recommend first working through the more symmetric case of an octahedral environment (cubic crystal field). My go-to reference for this would be the book &lt;em&gt;&amp;quot;Physics of Transition Metal Oxides&amp;quot;&lt;/em&gt; edited by Maekawa et al., Springer (2010), but it's also treated in many other books. If you have worked through that case, it should be clear that reducing the symmetry from that of a free atom to an octahedral environment introduces an energy splitting between the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals, and that further reducing the symmetry may introduce further splitting. The details of how this manifests in the trigonal prismatic environment was worked out in &lt;a href=&quot;https://orproxy.lib.utk.edu:2113/10.1016/0022-4596(71)90007-7&quot; rel=&quot;noreferrer&quot;&gt;R. Huisman, R. de Jonge, C. Haas, and F. Jellinek, &lt;em&gt;&amp;quot;Trigonal-prismatic coordination in solid compounds of transition metals,&amp;quot;&lt;/em&gt; Journal of Solid State Chemistry &lt;strong&gt;3&lt;/strong&gt;, 56-66 (1971)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, I'm not aware of a more pedagogical reference that covers the details for the trigonal-prismatic case. (If anyone does, please post an answer.) Hence the separate recommendation to cover the cubic crystal field first. However, if you end up going this route, do note that there is a change of coordinate system. Maekawa et al. have the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; axis point, towards a ligand, but Huisman et al. does not, as shown in their Fig. 1. This does change the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-orbital labels and the geometry, but not the overall logic.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UrYM1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UrYM1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;With that out of the way, let's jump straight to Huisman et al.'s results in their figure 3 (shown below). The lower states are related to &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;-orbitals, and can be ignored for our current purposes. The upper levels are related to the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-orbitals. On the left you have the free ion case, where there is perfect degeneracy. On the right is the octahedral case, where the orbitals split into a lower three-fold degenerate &lt;span class=&quot;math-container&quot;&gt;$t_{2g}^*$&lt;/span&gt; manifold (involving &lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_{xy}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d_{x^2-y^2}$&lt;/span&gt;) and an upper two-fold &lt;span class=&quot;math-container&quot;&gt;$e_g^*$&lt;/span&gt; manifold (with &lt;span class=&quot;math-container&quot;&gt;$d_{xz}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_{yz}$&lt;/span&gt;). (I think the asterisk is just used to distinguish these manifolds/subspaces from the &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;-orbital ones.) To see that this makes sense, you can think about crystal field splitting as an electrostatics problem. The orbital has to pay an energy penalty if it points towards another ion with other electrons present. Hence the orbitals that point &amp;quot;between&amp;quot; nearby ligands have the lowest energy.&lt;/p&gt;&#xA;&lt;p&gt;Then, in the tetragonal prismatic case, &lt;span class=&quot;math-container&quot;&gt;$t_{2g}*$&lt;/span&gt; splits into a single-degenerate &lt;span class=&quot;math-container&quot;&gt;$a_1'^*$&lt;/span&gt; level (&lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt;), and a double-degenerate &lt;span class=&quot;math-container&quot;&gt;$e'^*$&lt;/span&gt; manifold (&lt;span class=&quot;math-container&quot;&gt;$d_{xy}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_{x^2-y^2}$&lt;/span&gt;). (&lt;span class=&quot;math-container&quot;&gt;$e''^*$&lt;/span&gt; has the same orbitals as &lt;span class=&quot;math-container&quot;&gt;$e_g^*$&lt;/span&gt;.) Again we can use electrostatics for a quick sanity check. By tuning &lt;span class=&quot;math-container&quot;&gt;$\theta_0$&lt;/span&gt; we do change the symmetry between &lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${d_{xy},\,d_{x^2-y^2}}$&lt;/span&gt; but not between &lt;span class=&quot;math-container&quot;&gt;$d_{xz}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d_{yz}$&lt;/span&gt;. Hence, the latter can change in energy, but not split up. However, I don't have a similar hand-waving argument to determine whether &lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt; is the lowest in energy or not. I think this depends on the lattice details.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hpbvn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hpbvn.png&quot; alt=&quot;Crystal field splitting in ideal trigonal prism and ideal octahedron&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-09-05T23:11:30.803" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2212" PostTypeId="1" AcceptedAnswerId="2213" CreationDate="2020-09-06T18:34:26.793" Score="8" ViewCount="271" Body="&lt;p&gt;I must confess some ignorance... I just became aware of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Scientific_Vector_Language&quot; rel=&quot;noreferrer&quot;&gt;Scientific Vector Language&lt;/a&gt; (SVL) which has been around since 1994 and was created solely for computational chemistry.&lt;/p&gt;&#xA;&lt;p&gt;It has a large database of &lt;a href=&quot;https://svl.chemcomp.com/&quot; rel=&quot;noreferrer&quot;&gt;modules/API/functions/scripts&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The group behind this language is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_Computing_Group&quot; rel=&quot;noreferrer&quot;&gt;Chemical Computing Group&lt;/a&gt;. While they have competitors for their software which is the Molecular Operating Environment, which runs on SVL, I don't know if their competitors have gone so far as to develop their own programming language.&lt;/p&gt;&#xA;&lt;p&gt;Are there other programming languages that have been developed specifically for computational chemistry that I am not aware of?&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2020-09-07T20:57:07.877" LastActivityDate="2020-09-07T20:57:07.877" Title="Are there other custom chemistry programming languages besides SVL?" Tags="|one-topic-per-answer|computational-chemistry|matter-modeling-specific-technology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2213" PostTypeId="2" ParentId="2212" CreationDate="2020-09-07T07:31:31.387" Score="7" Body="&lt;h3&gt;SIAL (ACES III)&lt;/h3&gt;&#xA;&lt;p&gt;Implementing high-level quantum chemistry methods efficiently in parallel becomes extremely complicated due to the large number of tensors that need to be distributed.&lt;/p&gt;&#xA;&lt;p&gt;In the ACES III program this problem has been solved by writing the methods in a domain specific programming language called super instruction assembly language or SIAL (pronounced &amp;quot;sail&amp;quot; for easy communication) that is then executed by a parallel virtual machine.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.qtp.ufl.edu/aces/mp2grad_uhf_sv1_sial.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Example code for computing the MPBT(2) gradient based on UHF orbitals&lt;/a&gt;&#xA;&lt;a href=&quot;http://www.qtp.ufl.edu/aces/downloads/SIALProgrammerGuide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Programmers' guide&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2020-09-07T19:31:06.230" LastActivityDate="2020-09-07T19:31:06.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2214" PostTypeId="2" ParentId="2196" CreationDate="2020-09-07T10:35:20.383" Score="4" Body="&lt;p&gt;These are some general comments about modelling disorder which I think address your question, but note I cannot provide specifics about the codes you are using.&lt;/p&gt;&#xA;&lt;p&gt;Imagine a simple configuration with only two sites for the discussion:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q3mLp.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q3mLp.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Both atoms are of the same type (blue) so that this configuration has a mirror plane down the middle of the two atoms (dashed black line). This is a symmetry of the pure crystal (think your FCC symmetry). Now imagine that we can alloy this system with another type of atom (red) in a 50-50 composition, such  that the average alloy composition looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jnprR.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jnprR.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this case, the mirror plane down the middle is still a symmetry of the alloy. This is because we are building this abstract concept of a partial occupancy of a site (half blue half red), and this is precisely what we mean when we say that an alloy has a certain symmetry.&lt;/p&gt;&#xA;&lt;p&gt;However, the real material is not as shown in the schematic above because you cannot have partial occupancies of a given site, you either have one atom or the other. These are two examples of &lt;em&gt;real&lt;/em&gt; configurations of the system:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QvlRr.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QvlRr.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You will notice that none of these obey the mirror symmetry down the middle. This is equivalent to your particular realizations of disordered supercells: none of those will obey the nominal FCC symmetry of the crystal.&lt;/p&gt;&#xA;&lt;p&gt;So again, what do we mean by an alloy having a particular symmetry? If you consider all possible realization of disorder (none of which will in general obey a particular symmetry), this forms your ensemble of disorder realizations. If you now calculate the average over all these realizations, then you will get the &amp;quot;partial occupancy&amp;quot; picture (half blue half red sites above), which &lt;em&gt;does&lt;/em&gt; obey the symmetry of interest.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-07T10:35:20.383" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2215" PostTypeId="1" AcceptedAnswerId="2216" CreationDate="2020-09-07T15:01:06.513" Score="10" ViewCount="225" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fYeib.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fYeib.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Q1: As shown in the previous figure, what's the physical meaning of absorbance (y-axis) in the absorption spectrum calculated with the GW-BSE method?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Q2: Here the absorbance for the absorption onset &lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$X_2$&lt;/span&gt; is so low, is it meaningful to talk about it?  Or what's the physical difference between &lt;span class=&quot;math-container&quot;&gt;$X_1/X_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$X_3$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PS: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.101.245401&quot; rel=&quot;nofollow noreferrer&quot;&gt;this figure is cut from this paper.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-05T23:36:18.117" LastActivityDate="2021-02-05T23:36:18.117" Title="What's the meaning of absorbance in the absorption spectrum calculated by the GW-BSE method?" Tags="|gw-bse|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2216" PostTypeId="2" ParentId="2215" CreationDate="2020-09-07T19:23:50.260" Score="8" Body="&lt;p&gt;The term &lt;em&gt;absorbance&lt;/em&gt; does not have anything directly related to the &lt;a href=&quot;https://en.wikipedia.org/wiki/GW_approximation&quot; rel=&quot;noreferrer&quot;&gt;GW approximation&lt;/a&gt; or the &lt;a href=&quot;https://en.wikipedia.org/wiki/Bethe%E2%80%93Salpeter_equation&quot; rel=&quot;noreferrer&quot;&gt;Bethe-Salpeter equation&lt;/a&gt; (BSE). The &amp;quot;absorbance&amp;quot; is a property of a material, while GW and BSE are just methods of calculating things. It's similar to saying that the conductivity of a material has to do with how much a material allows the flow of electrons, but nothing directly related to &amp;quot;DFT&amp;quot; which is just a method that can be used to estimate conductivity.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So what is absorbance?&lt;/strong&gt; I searched &amp;quot;absorbance&amp;quot; in the paper and it appeared only a few times, and the second instance was their definition of it:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;we plot the optical absorbance by &lt;span class=&quot;math-container&quot;&gt;$A(\omega) = \frac{\omega d}{c}\epsilon_2(\omega)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\epsilon_2(\omega)$&lt;/span&gt; is the calculated imaginary part of the dielectric function and &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; represents the distance between adjacent &lt;span class=&quot;math-container&quot;&gt;$\ce{CrCl_3}$&lt;/span&gt; layers along the periodic direction of our calculation.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Much more can be said about &lt;a href=&quot;https://en.wikipedia.org/wiki/Absorbance&quot; rel=&quot;noreferrer&quot;&gt;absorbance&lt;/a&gt; in general, but in the specific paper figure in the question, it is exactly defined by the formula in the above quote. The definition with words rather than formulas is given &lt;a href=&quot;https://en.wikipedia.org/wiki/Absorption_(electromagnetic_radiation)&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The absorbance of an object quantifies how much of the incident light&#xA;is absorbed by it&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The last link I gave says that one of the &amp;quot;measures&amp;quot; of absorbance is the &amp;quot;complex dielectric constant&amp;quot; which leads to &lt;a href=&quot;https://en.wikipedia.org/wiki/Relative_permittivity&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt; that defines it as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Permittivity&quot; rel=&quot;noreferrer&quot;&gt;permitivity&lt;/a&gt; of the material divided by the permitivity of a vacuum. In the paper's formula for absorbance, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_2(\omega)$&lt;/span&gt; is simply the imaginary part of this &amp;quot;complex-valued dielectric constant&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Finally you asked whether or not the two small peaks are meaningful, which I feel can be asked as a separate question. I don't think anyone working on that specific paper or its immediate community knows about Matter Modeling Stack Exchange yet (since we're still so new and small), but at least I can say that those small peaks were significant enough for them to show them in an inset figure.&lt;/p&gt;&#xA;&lt;p&gt;They also go on for multiple pages talking about &lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$X_2$&lt;/span&gt;, especially in this part which highlights their importance:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Importantly, we observe two characteristic excitonic peaks in the&#xA;optical spectrum at the low energy regime, which are marked as &lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$X_2$&lt;/span&gt; at 1.48 and 2.25 eV in Fig. 3(a), respectively. It is worth&#xA;mentioning that more excitonic states are around &lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$X_2$&lt;/span&gt; while most&#xA;of them are optically dark. In the inset of Fig. 3(a), we also mark&#xA;the lowest energy dark exciton, &lt;span class=&quot;math-container&quot;&gt;$X_0$&lt;/span&gt;, whose energy is about 20 meV below&#xA;&lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt; but its dipole oscillator strength is about four orders of&#xA;magnitude smaller than that of &lt;span class=&quot;math-container&quot;&gt;$X_1$&lt;/span&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-07T19:29:50.473" LastActivityDate="2020-09-07T19:29:50.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2217" PostTypeId="5" CreationDate="2020-09-07T19:25:19.307" Score="0" Body="&lt;p&gt;More information about GW &lt;a href=&quot;https://en.wikipedia.org/wiki/GW_approximation&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and more about BSE &lt;a href=&quot;https://en.wikipedia.org/wiki/Bethe%E2%80%93Salpeter_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-07T19:25:19.307" LastActivityDate="2020-09-07T19:25:19.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2218" PostTypeId="4" CreationDate="2020-09-07T19:25:19.307" Score="0" Body="Questions about the GW approximation or the Bethe-Salpeter Equation (BSE)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-07T19:25:19.307" LastActivityDate="2020-09-07T19:25:19.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2219" PostTypeId="2" ParentId="1988" CreationDate="2020-09-07T21:01:08.627" Score="18" Body="&lt;p&gt;Another option is &lt;a href=&quot;https://smtg-bham.github.io/sumo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sumo&lt;/a&gt;, which is a Python toolkit for plotting and analysis of ab initio solid-state calculation data. It supports VASP, CASTEP and Questaal. Plotting is mostly done through a command-line interface. It can also generate the band paths in the first place. There is also support for plotting phonon bands generate with phononpy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lcL68.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lcL68.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1020" LastEditorUserId="6055" LastEditDate="2023-09-25T07:32:24.357" LastActivityDate="2023-09-25T07:32:24.357" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2220" PostTypeId="1" AcceptedAnswerId="2345" CreationDate="2020-09-07T22:40:39.757" Score="8" ViewCount="100" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/387/what-are-some-approaches-to-modeling-charged-point-defects-in-materials&quot;&gt;A previous question&lt;/a&gt; addressed how to deal with charge defects in bulk materials.  What can be done to treat a 2D surface with respect to charge?&lt;/p&gt;&#xA;&lt;p&gt;For example, how can an absorption energy of OH&lt;sup&gt;-&lt;/sup&gt; on Pt(111) be calculated and what should be considered in this system to get meaningful values.  Likewise, what about a charged defect of the surface itself in a monolayer material such as graphene.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-21T23:21:31.190" Title="Working with charged surfaces" Tags="|surfaces|electrostatic|charge-transfer|methodology|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2221" PostTypeId="1" AcceptedAnswerId="2228" CreationDate="2020-09-08T04:21:37.927" Score="11" ViewCount="218" Body="&lt;p&gt;Are there any known codes or scripts to generate an adaptive k-mesh for DFT calculations? For example, I'd like to make the k-mesh near the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point (e.g., half the zone) more denser (&lt;span class=&quot;math-container&quot;&gt;$20\times20\times20$&lt;/span&gt;) than other region (&lt;span class=&quot;math-container&quot;&gt;$8\times8\times8$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2020-09-08T21:42:27.360" LastActivityDate="2020-09-09T13:11:49.447" Title="adaptive k-mesh" Tags="|density-functional-theory|software-recommendations|k-points|numerical-convergence|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2222" PostTypeId="1" AcceptedAnswerId="2223" CreationDate="2020-09-08T05:40:42.760" Score="10" ViewCount="193" Body="&lt;p&gt;I'd like to investigate the structural relaxations of the excited state for periodic systems. It seems BSE is a practical method that has already been implemented in many codes for static calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I'm wondering if there's any code with extensions to force evaluations?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2020-09-08T17:56:00.977" LastActivityDate="2020-09-08T17:56:00.977" Title="Is there a software that has implemented forces of BSE calculations for solids?" Tags="|density-functional-theory|software-recommendations|td-dft|gw-bse|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2223" PostTypeId="2" ParentId="2222" CreationDate="2020-09-08T13:59:18.410" Score="8" Body="&lt;p&gt;I am not aware of any public codes that have a force implementation for excited state calculations using the Bethe-Salpeter equation (happy to be corrected on this front). However, the methodology to do this was published some time ago by Ismail-Beige and Louie in this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.90.076401&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;, where they also have an in-house implementation that they use to validate the methodology by studying:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;photoexcited carbon dioxide and ammonia molecules, and the calculations accurately describe the excitation energies and photoinduced structural deformations&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-08T13:59:18.410" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2225" PostTypeId="1" AcceptedAnswerId="7017" CreationDate="2020-09-08T21:19:00.810" Score="17" ViewCount="371" Body="&lt;p&gt;&lt;strong&gt;Is there a way to empirically determine an appropriate thermostat damping factor given a timestep size and a numerical integration method?&lt;/strong&gt; For example, I would like one for the surface and the molecule, and I will describe more below.&lt;/p&gt;&#xA;&lt;p&gt;I am computing a set of simulations in LAMMPS, using ReaxFF, tracking the path of a single (~4 atom) gas molecule as it interacts with a (~600 atom) surface.&lt;/p&gt;&#xA;&lt;p&gt;Two thermostats are imposed on the system, one for the surface, one for the molecule.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix surfaceFix  surface  temp/csvr &lt;span class=&quot;math-container&quot;&gt;${surfTemp} $&lt;/span&gt;{surfTemp} &lt;span class=&quot;math-container&quot;&gt;${surfaceDampingFactor}&#xA;fix moleculeFix molecule temp/csvr $&lt;/span&gt;{molTemp}  &lt;span class=&quot;math-container&quot;&gt;${molTemp}  $&lt;/span&gt;{moleculeDampingFactor}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I know intuitively that the surface temperature should be more tightly regulated than the temperature of the molecule, since the molecule trajectory is a dependent variable in the experiment. Yet I don't have a way of determining the value of each damping factor.&lt;/p&gt;&#xA;&lt;p&gt;For instance with the molecule, errors are introduced in the limit of both small and large damping factors:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In the case of weak thermostatting, the force calculations can diverge and we introduce an error due to the precision limits of numerical integration.&lt;/li&gt;&#xA;&lt;li&gt;In the case of strong thermostatting, we introduce an error in the energy transferred between the molecule and the surface.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Both of these errors could cause the effect of &amp;quot;hopping&amp;quot;: where the molecule is provided with a non-physical velocity that causes it to jump into or out of locations that would otherwise be impossible.&lt;/p&gt;&#xA;&lt;p&gt;There must be a connection between the timestep size + integration method, and the damping factor needed to correct for the deviation in forces that these produce. Naturally the damping required would also depend on the mechanics of the thermostat, and its effect on different degrees of freedom, but an answer addressing any thermostat is of interest.&lt;/p&gt;&#xA;" OwnerUserId="1203" LastEditorUserId="5" LastEditDate="2021-10-30T20:06:48.803" LastActivityDate="2021-11-08T01:31:08.107" Title="Empirically determining thermostat damping factor" Tags="|software|molecular-dynamics|lammps|intermolecular-forces|molecular-mechanics|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2226" PostTypeId="1" AcceptedAnswerId="4814" CreationDate="2020-09-08T21:35:36.383" Score="14" ViewCount="293" Body="&lt;p&gt;I'd like to investigate the structural relaxations of the excited state for periodic systems. BSE and TDDFT are two promising methods for this purpose. While there is a discussion on forces with BSE here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2222/is-there-a-software-that-has-implemented-forces-of-bse-calculations-for-solids&quot;&gt;Is there a software that has implemented forces of BSE calculations for solids?&lt;/a&gt;, &lt;strong&gt;I'm wondering if there is a software for forces with TDDFT.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2021-04-11T22:28:40.903" LastActivityDate="2021-04-26T11:41:25.880" Title="Is there a software that has implemented forces of TDDFT calculations for solids?" Tags="|one-topic-per-answer|software-recommendations|td-dft|geometry-optimization|structure|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="2227" PostTypeId="1" AcceptedAnswerId="2235" CreationDate="2020-09-08T22:10:50.797" Score="8" ViewCount="191" Body="&lt;p&gt;In general, the orbital magnetic dipole moment operator is defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$- {e\over2} \mathbf{r \times v} \tag{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{v=p}/m$&lt;/span&gt; is true only for simple Hamiltonian like &lt;span class=&quot;math-container&quot;&gt;$-1/2\ \nabla^2+V$&lt;/span&gt;, but not for normal DFT implementations with semi-local or nonlocal pseudopotentials. For the PAW method (projector augmented wave), e.g., implemented in vasp, if I would evaluate the matrix elements of the orbital magnetic dipole moment operator within the PAW spheres, i.e., &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_i|\mathbf{r \times v}|\phi_j\rangle$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; is the all-electron partial wave, then can I use the linear momentum representation?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2020-10-12T18:27:28.767" LastActivityDate="2020-10-12T18:27:28.767" Title="Evaluate the orbital magnetic dipole moment within the PAW sphere" Tags="|density-functional-theory|vasp|pseudopotentials|projector-augmented-wave|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2228" PostTypeId="2" ParentId="2221" CreationDate="2020-09-09T09:39:57.237" Score="6" Body="&lt;p&gt;In &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt; one can create a Monkhorst-Pack grid with zooming capabilities.&lt;/p&gt;&#xA;&lt;p&gt;Here is a small Python snippet which creates the k-points for the zoomed in region.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import sisl&#xA;&#xA;# time-reversal-symmetry&#xA;trs = True&#xA;&#xA;# first argument is the lattice vectors (in case you want them in 1/Ang)&#xA;# in this case it is just a square box of side-lengths 1 Ang&#xA;MP_3x3 = sisl.MonkhorstPack(1, [3, 3, 1], trs=trs)&#xA;assert np.allclose(MP_3x3.weight.sum(), 1.)&#xA;&#xA;MP_3x3_zoom = sisl.MonkhorstPack(1, [3, 3, 1], size=[1/3, 1/3, 1], trs=trs)&#xA;# density is only 1 / 9&#xA;assert np.allclose(MP_3x3_zoom.weight.sum(), 1. / 3 ** 2)&#xA;&#xA;MP = MP_3x3.copy()&#xA;MP.replace([0] * 3, MP_3x3_zoom)&#xA;assert np.allclose(MP.weight.sum(), 1.)&#xA;&#xA;# List k-points&#xA;print(MP_3x3.k[:, :2])&#xA;print(MP_3x3_zoom.k[:, :2])&#xA;print(MP.k[:, :2])&#xA;&#xA;import matplotlib.pyplot as plt&#xA;def kplot(MP):&#xA;    plt.scatter(MP.k[:, 0], MP.k[:, 1], MP.weight * 500, alpha=0.5)&#xA;#kplot(MP_3x3)&#xA;#kplot(MP_3x3_zoom)&#xA;kplot(MP)&#xA;&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For &lt;code&gt;trs=False&lt;/code&gt; you find a grid looking like this (sizes of k-points correspond to the weights associated with a BZ integration):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/30cko.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/30cko.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The script in sisl also checks whether weights are preserved and whether the sizes of the BZ correspond to each other.&lt;/p&gt;&#xA;&lt;p&gt;For your case you could do:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# Replace a single point (Gamma) with higher density&#xA;MP = sisl.MonkhorstPack(1, [8] * 3, trs=trs)&#xA;MP_20 = sisl.MonkhorstPack(1, [20] * 3, size=[1/8] * 3,trs=trs)&#xA;MP.replace([0] * 3, MP_20)&#xA;&#xA;# Replace 3x3x3 k-points around Gamma by&#xA;MP = sisl.MonkhorstPack(1, [8] * 3, trs=trs)&#xA;MP_20 = sisl.MonkhorstPack(1, [20] * 3, size=[3/8] * 3,trs=trs)&#xA;MP.replace([0] * 3, MP_20)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you try to do something that is invalid, you'll get error messages ;)&#xA;E.g. if the weight/volume of the replaced k-point(s) does not match the weights of the inserted k-points.&#xA;Note, with the above machinery you can nest as many zoom regions as necessary.&lt;/p&gt;&#xA;&lt;p&gt;Disclaimer: I am the author of the package.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2020-09-09T13:11:49.447" LastActivityDate="2020-09-09T13:11:49.447" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2229" PostTypeId="1" CreationDate="2020-09-09T12:42:38.127" Score="9" ViewCount="536" Body="&lt;p&gt;I am using VASP5.4.4 to calculate the mechanical properties of the cubic phase SnTe. The structure can be found in the &lt;a href=&quot;https://materialsproject.org/materials/mp-16364/&quot; rel=&quot;noreferrer&quot;&gt;materials project website.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In detail, I use the following INCAR to calculate the elastic constants of the primitive cell (2 atoms) and the conventional cell (8 atoms) of SnTe.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System:&#xA;ISTART=0                       !startjob: 0-new 1-cont 2-samecut&#xA;ICHARG=2                       !charge: 1-file 2-atom 10-const&#xA;ENCUT=400                      !energy cutoff in eV&#xA;EDIFF=1E-5                     !stopping-criterion for electronic upd.&#xA;#NELM=300                      !nr. of electronic steps&#xA;ISMEAR=0                       !part. occupancies: -5 Blochl -4-tet -1-fermi 0-gaus 0 MP&#xA;SIGMA=0.05                     !broadening in eV -4-tet -1-fermi 0-gaus&#xA;&#xA;Dynamic:&#xA;PREC=Accurate&#xA;ISIF=3 &#xA;IBRION=6&#xA;NFREE=4&#xA;POTIM=0.015&#xA;SYMPREC=1E-8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The results for the two cells is shown below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Primitive cell (&lt;span class=&quot;math-container&quot;&gt;$\alpha=\beta=\gamma=60^\circ$&lt;/span&gt;;&lt;span class=&quot;math-container&quot;&gt;$a=b=c$&lt;/span&gt;;2 atoms):&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;TOTAL ELASTIC MODULI (kBar)&#xA;Direction    XX          YY          ZZ          XY          YZ          ZX&#xA;--------------------------------------------------------------------------------&#xA;XX         754.4756    162.3949    290.3213     -0.0000   -180.9152     -0.0000&#xA;YY         162.3949    754.4756    290.3213     -0.0000    180.9152     -0.0000&#xA;ZZ         290.3213    290.3213    626.5492     -0.0000      0.0000     -0.0000&#xA;XY          -0.0000     -0.0000     -0.0000    296.0404     -0.0000   -180.9152&#xA;YZ        -180.9152    180.9152      0.0000     -0.0000    423.9667     -0.0000&#xA;ZX          -0.0000     -0.0000     -0.0000   -180.9152     -0.0000    423.9667&#xA;--------------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Conventional cell (&lt;span class=&quot;math-container&quot;&gt;$\alpha=\beta=\gamma=90^\circ$&lt;/span&gt;;&lt;span class=&quot;math-container&quot;&gt;$a=b=c$&lt;/span&gt;;8 atoms):&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt; Direction    XX          YY          ZZ          XY          YZ          ZX&#xA; --------------------------------------------------------------------------------&#xA; XX        1140.9524     43.2055     43.2055      0.0000      0.0000     -0.0000&#xA; YY          43.2055   1140.9524     43.2055      0.0000      0.0000      0.0000&#xA; ZZ          43.2055     43.2055   1140.9524      0.0000      0.0000     -0.0000&#xA; XY           0.0000      0.0000      0.0000    164.8906      0.0000      0.0000&#xA; YZ           0.0000      0.0000      0.0000     -0.0000    164.8906     -0.0000&#xA; ZX          -0.0000      0.0000     -0.0000      0.0000     -0.0000    164.8906&#xA; --------------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Why the results of the primitive cell are different from the conventional cell? They are both cubic phase SnTe.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;For the cubic phase system, there are only four independent elastic constants&lt;/strong&gt;. It seems that the results of the conventional cell are correct. However, the results of the primitive cell are like the trigonal system because there are six independent elastic constants. What am I missing here?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-09-26T21:12:06.250" LastActivityDate="2020-11-28T12:58:41.390" Title="Problem related to the calculation of elastic constant with VASP5.4.4" Tags="|density-functional-theory|vasp|elastic-constants|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2230" PostTypeId="1" CreationDate="2020-09-09T16:27:27.690" Score="7" ViewCount="89" Body="&lt;p&gt;What are the available methods for the calculation of reference interaction energies of layered materials and in which codes they are implemented? For example, I know RPA-ACFDT in the DFT concept. But it's very computationally expensive and not suitable for complex structures. What are some other methods which are practically available? It does not have to be in the DFT concept, but it has to be used as reference data since experimental interaction energies for layered materials are not available.&lt;/p&gt;&#xA;&lt;p&gt;Since I'm asking for both the method and the implemented, a format such as in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1853/5&quot;&gt;this answer&lt;/a&gt; can be suitable.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-09-09T18:05:22.757" LastActivityDate="2020-09-17T14:33:08.660" Title="What are the methods for calculating interaction energies of layered materials, and where are they implemented?" Tags="|density-functional-theory|one-topic-per-answer|electron-correlation|random-phase-approximation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2231" PostTypeId="1" AcceptedAnswerId="2313" CreationDate="2020-09-09T18:49:22.303" Score="9" ViewCount="140" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;This question comes as a follow-up to &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2214/116;&quot;&gt;https://mattermodeling.stackexchange.com/a/2214/116;&lt;/a&gt; nonetheless, it is relevant on its own as well.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To designate a particular crystal structure to a random solid solution (rss, in this question) means assigning an ensemble of all possible random states of this solution with that specific crystal structure. For instance, an FCC rss has complete FCC symmetry only in its idealized theoretical random state. In contrast, in reality, any one of the randomly possible configurations of this solution will have a symmetry that is lesser than FCC.&lt;/p&gt;&#xA;&lt;p&gt;For an rss, every atom has a different local chemical environment that means they each would have a different electronic density of states. Given that, does a partial density of states (PDoS) matter?&lt;/p&gt;&#xA;&lt;p&gt;Let's say for an 8 atom structure of an AB type rss, PDoS for each of the 8 atoms will be different and make sense. Does a collective PDoS for the 4 A atoms or the 4 B atoms make sense, though?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-09-16T17:08:27.407" LastActivityDate="2020-09-18T17:17:16.563" Title="Partial density of states in random solid solutions" Tags="|crystal-structure|symmetry|density-of-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2232" PostTypeId="2" ParentId="2163" CreationDate="2020-09-09T19:27:17.370" Score="9" Body="&lt;p&gt;&lt;strong&gt;tldr; they need to be in certain directories to be found.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't know why the input generators were not part of the install package. Certainly on Mac, and AFAIK on Windows, they are and should be. On the other hand, Linux package maintainers often have rules about how they're supposed to handle such things and perhaps it's a separate package.&lt;/p&gt;&#xA;&lt;p&gt;In Avogadro 2, we've made input generators and a bunch of other things into Python scripts. Basically, the script will pass some JSON to Avogadro to create a form (e.g., DFT functionals, basis sets, job types, etc.) and Avogadro passes JSON with the user options to the script.&lt;/p&gt;&#xA;&lt;p&gt;This means in principle, users can easily add new generators, tweak the options, etc. with minimal coding. It also means updates can happen whenever, not just when we issue a release.&lt;/p&gt;&#xA;&lt;p&gt;We're working on a plugin directory and better plugin installation (e.g., download or use git to grab plugins). &lt;em&gt;I mean, doesn't every editor have plugins now?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;The downloader has some known bugs, but it's been a busy start to the semester, unfortunately.&lt;/p&gt;&#xA;&lt;p&gt;Avogadro will look in a few places for input generator scripts:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;${INSTALL_LIBRARY_DIR}/avogadro2/scripts/inputGenerators/&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;QStandardPaths::standardLocations(QStandardPaths::AppLocalDataLocation) + type&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Generally on Linux, that might be:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;/usr/local/lib/avogadro2/scripts/inputGenerators/&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;~/.local/share/OpenChemistry/Avogadro/inputGenerators/&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/usr/local/share/OpenChemistry/Avogadro/inputGenerators/&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;/usr/share/OpenChemistry/Avogadro/inputGenerators/&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It's fairly easy to tweak the code to look at different directories, so please let me know in the comments.&lt;/p&gt;&#xA;&lt;p&gt;On my Mac, I created a symlink from &lt;code&gt;~/Library/Application Support/OpenChemistry/Avogadro/inputGenerators&lt;/code&gt; to the git repository.&lt;/p&gt;&#xA;&lt;p&gt;There's a definite need for a &amp;quot;please install this download for me&amp;quot; - and if anyone has a few hours, I'd happy help get that done. We can definitely use some help - lots of tasks are fairly quick.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2020-09-10T01:46:29.123" LastActivityDate="2020-09-10T01:46:29.123" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2233" PostTypeId="1" AcceptedAnswerId="2236" CreationDate="2020-09-09T23:33:39.870" Score="11" ViewCount="1045" Body="&lt;p&gt;Is there a formula for analytical gradients (for geometry optimization) for the DLPNO-CCSD method? I ask because I know that it is not implemented in ORCA. Maybe PNO-CCSD is implemented in MRCC or MOLPRO.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-09-10T11:35:23.023" LastActivityDate="2020-09-10T18:04:56.050" Title="Analytic gradient for DLPNO-CCSD" Tags="|coupled-cluster|geometry-optimization|orca|molpro|mrcc|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2234" PostTypeId="2" ParentId="179" CreationDate="2020-09-10T02:41:06.687" Score="8" Body="&lt;p&gt;This is possible via &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; as well.  There are modules which can handle space groups via &lt;a href=&quot;https://spglib.github.io/spglib/&quot; rel=&quot;noreferrer&quot;&gt;spglib&lt;/a&gt;.  I will focus on an application that hasn't been discussed yet.&lt;/p&gt;&#xA;&lt;p&gt;ASE has an advantage that you can &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html?highlight=strain%20filter#the-fixsymmetry-class&quot; rel=&quot;noreferrer&quot;&gt;enforce symmetry&lt;/a&gt; during an optimization of cell size / positions.  Here is an example that can be run with &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/index.html&quot; rel=&quot;noreferrer&quot;&gt;GPAW&lt;/a&gt; which will load a geometry (&lt;code&gt;POSCAR&lt;/code&gt;) and optimize the cell size and shape while keeping the original symmetry.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from ase.optimize.bfgs import BFGS&#xA;from ase.constraints import UnitCellFilter&#xA;from ase.spacegroup.symmetrize import FixSymmetry&#xA;from gpaw import GPAW, PW&#xA;&#xA;atoms = read(&amp;quot;POSCAR&amp;quot;)&#xA;atoms.set_constraint(FixSymmetry(atoms))&#xA;&#xA;si.calc = GPAW(xc='PBE',&#xA;               mode=PW(400, dedecut='estimate'),&#xA;               kpts=(4, 4, 4),&#xA;               txt='stress.txt')&#xA;&#xA;uf = UnitCellFilter(si)&#xA;relax = BFGS(uf)&#xA;relax.run(fmax=0.05)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The full trajectory will be contained in &lt;code&gt;stress.txt&lt;/code&gt;.  &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html#supported-calculators&quot; rel=&quot;noreferrer&quot;&gt;Other calculators that ASE supports&lt;/a&gt; can be used by simply changing the GPAW based lines to another calculator.  It will need to implement a stress tensor though, so this restricts use somewhat.  For example, GPAW does not support stress tensor calculations in FD or LCAO modes currently.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-10T02:41:06.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2235" PostTypeId="2" ParentId="2227" CreationDate="2020-09-10T09:07:02.730" Score="4" Body="&lt;ol&gt;&#xA;&lt;li&gt;Velocity is not really used in quantum mechanics, since it is the momentum that is the canonical variable. Leave velocity to classical physics.&lt;/li&gt;&#xA;&lt;li&gt;The momentum operator &lt;span class=&quot;math-container&quot;&gt;${\bf p}$&lt;/span&gt; makes sense for whatever Hamiltonian. It will just only share eigenstates with the Hamiltonian in cases where &lt;span class=&quot;math-container&quot;&gt;$\hat{H}=\hat{H}({\bf p})$&lt;/span&gt;, e.g. the free particle &lt;span class=&quot;math-container&quot;&gt;$\hat{H}={\bf p}^2/2m$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;The concept of the angular momentum operator &lt;span class=&quot;math-container&quot;&gt;$\hat{\bf L}$&lt;/span&gt; originates from the central field problem, where the potential is purely radial: &lt;span class=&quot;math-container&quot;&gt;$V({\bf r})=V(r)$&lt;/span&gt;. In this case you can show that in classical physics &lt;span class=&quot;math-container&quot;&gt;${\bf L}={\bf r} \times {\bf p}$&lt;/span&gt; is a constant of motion. However, it turns out that also in quantum mechanics &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{\bf L}$&lt;/span&gt; are compatible operators, i.e. &lt;span class=&quot;math-container&quot;&gt;$[\hat{H},\hat{\bf L}^2]=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$[\hat{H},\hat{\bf L}_z]=0$&lt;/span&gt;, meaning that the eigenstates of the system are eigenstates of both the Hamiltonian and the angular momentum operator.&lt;/li&gt;&#xA;&lt;li&gt;You can evaluate matrix elements of &lt;span class=&quot;math-container&quot;&gt;${\bf L}={\bf r} \times {\bf p}$&lt;/span&gt; within the quantum mechanical sense. There are two obvious ways to do this. If you are in coordinate space then &lt;span class=&quot;math-container&quot;&gt;${\bf r}={\bf r}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf p}=-i\hbar \nabla_{\bf r}$&lt;/span&gt;. However, you can also evaluate in momentum space: &lt;span class=&quot;math-container&quot;&gt;${\bf p}={\bf p}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf r}=i\hbar \nabla_{\bf p}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-10T09:07:02.730" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2236" PostTypeId="2" ParentId="2233" CreationDate="2020-09-10T09:28:50.500" Score="13" Body="&lt;p&gt;Note that the DLPNO method is only implemented in ORCA. There are indeed analogous and similarly efficient and accurate methods, the PNO-LCCSD method in Molpro [doi.org/10.1021/acs.jctc.7b00799] and the LNO-CCSD method in MRCC [doi.org/10.1021/acs.jctc.9b00511].&lt;/p&gt;&#xA;&lt;p&gt;To my knowledge exact analytical gradients are not implemented for either of them. There is an impressive implementation for analytical DLPNO-MP2 gradient in ORCA [https://doi.org/10.1063/1.5086544] and a first derivative for DLPNO-CCSD with respect to electric field components [http://dx.doi.org/10.1063/1.4962369].&lt;/p&gt;&#xA;&lt;p&gt;So far it is not completely clear what kind of applications would benefit from the significantly higher cost of local CCSD or CCSD(T) gradients compared to, e.g., DFT, we will see.&lt;/p&gt;&#xA;" OwnerUserId="317" LastEditorUserId="317" LastEditDate="2020-09-10T18:04:56.050" LastActivityDate="2020-09-10T18:04:56.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2237" PostTypeId="2" ParentId="2233" CreationDate="2020-09-10T11:25:28.580" Score="8" Body="&lt;p&gt;As far as I know, analytic gradients for DLPNO-CCSD are not available in ORCA. Analytic first derivatives are available for both closed-shell and high-spin open-shell cases, which could be used for computing other first-order properties.&lt;/p&gt;&#xA;&lt;p&gt;As the first exercise to implement analytic gradients within the DLPNO setup, the DLPNO-MP2 method was considered and the additional steps to implement gradients, especially those related to orbital response contributions, were carefully analysed.&lt;/p&gt;&#xA;&lt;p&gt;It is indeed not clear whether or not it is worthwhile to use DLPNO-CC for geometry optimization, while there are cheaper and more efficient DFT methods for this purpose.&lt;/p&gt;&#xA;" OwnerUserId="1329" LastActivityDate="2020-09-10T11:25:28.580" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2238" PostTypeId="1" CreationDate="2020-09-10T15:02:43.497" Score="14" ViewCount="6261" Body="&lt;p&gt;Sorry if this question is too simple for this community but I still couldn't find an answer to it.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Do gamma-centred and gamma only grid mean the same thing?&lt;/li&gt;&#xA;&lt;li&gt;If not, what's the difference?&lt;/li&gt;&#xA;&lt;li&gt;How do they differ from Monkhorst-Pack grid?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="5" LastEditDate="2020-09-10T16:09:02.813" LastActivityDate="2020-09-11T10:49:34.867" Title="Monkhorst-Pack, Gamma-centred and gamma only" Tags="|density-functional-theory|k-points|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2239" PostTypeId="2" ParentId="1647" CreationDate="2020-09-10T18:19:41.180" Score="3" Body="&lt;p&gt;GAMESS(US) has this facility implemented, but this feature may not be available in the public release.&lt;/p&gt;&#xA;" OwnerUserId="1329" LastActivityDate="2020-09-10T18:19:41.180" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2240" PostTypeId="1" CreationDate="2020-09-11T00:55:42.233" Score="6" ViewCount="342" Body="&lt;p&gt;The velocity operator is defined as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}=i[H,\mathbf{r}]$&lt;/span&gt; for the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; satisfying &lt;span class=&quot;math-container&quot;&gt;$H\psi=\epsilon \psi$&lt;/span&gt;. This can be obtained from the Ehrenfest theorem. I'm wondering if &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}=i[H,\mathbf{r}]$&lt;/span&gt; still holds for &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; satisfying the generalized Schrodinger equation &lt;span class=&quot;math-container&quot;&gt;$H\psi=\epsilon S\psi$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the overlap operator?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2020-09-11T02:47:59.430" LastActivityDate="2020-09-11T04:14:49.087" Title="Velocity operator for a Hamiltonian that satisfies the generalized Schrodinger equation" Tags="|quantum-mechanics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2241" PostTypeId="2" ParentId="1760" CreationDate="2020-09-11T02:00:29.863" Score="2" Body="&lt;h3&gt;κALDo&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/nanotheorygroup/kaldo&quot; rel=&quot;nofollow noreferrer&quot;&gt;κALDo&lt;/a&gt; is a python-based versatile and scalable opensource software to compute phonon transport in crystalline and amorphous solids. κALDo uses the real space Quasi-Harmonic Green-Kubo (QHGK) approach and three different solvers of the linearized Boltzmann Transport Equation (BTE): direct inversion, self-consistent, and relaxation time approximation and runs on GPUs and CPUs using Tensorflow. Using the Atomic Simulation Environment, κALDo can calculate the inter atomic force constants using several ab initio and molecular dynamics codes, thus enabling the use of first-principles DFT, empirical forcefields and semi-empirical tight- binding.&lt;/p&gt;&#xA;&lt;p&gt;You can download the code &lt;a href=&quot;https://github.com/nanotheorygroup/kaldo&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. Documentation is available &lt;a href=&quot;https://nanotheorygroup.github.io/kaldo/index.html#&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;Original paper is available at &lt;a href=&quot;https://arxiv.org/pdf/2009.01967.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;arxiv&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Tutorials to experiment with kaLDO can be run using Google Colab&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://colab.research.google.com/github/nanotheorygroup/kaldo/blob/master/docs/docsource/crystal_presentation.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;Thermal transport calculation for the silicon crystal using the&#xA;BTE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://colab.research.google.com/github/nanotheorygroup/kaldo/blob/master/docs/docsource/amorphous_presentation.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;Thermal transport calculation for the silicon amorphous&#xA;using the QHGK method&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/0eAD2.png&quot; width=&quot;300&quot;&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-09-11T03:17:54.750" LastActivityDate="2020-09-11T03:17:54.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2242" PostTypeId="2" ParentId="2240" CreationDate="2020-09-11T04:14:49.087" Score="6" Body="&lt;p&gt;Consider a time-independent operator &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;, its expectation value, and the time derivative of the expectation value (by applying the product rule for derivatives):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{1}&#xA;\langle \mathbf{r}\rangle &amp;amp;\equiv \int \psi^* \mathbf{r}\psi \,\,\, dr\\&#xA;\frac{\rm{d}}{\textrm{d}t}\langle \mathbf{r}\rangle &amp;amp;= \int \left(\frac{\rm{d}}{\textrm{d}t}\psi^*\right) \mathbf{r}\psi \,dr + \int  \psi^* \mathbf{r}\left(\frac{\rm{d}}{\textrm{d}t}\psi\right)\,dr\tag{2}. &#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now let's plug in the Schrödinger equation (with &lt;span class=&quot;math-container&quot;&gt;$\hbar=1$&lt;/span&gt; since that's what you had) and its conjugate: &lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{3}&#xA;\frac{\rm{d}}{\textrm{d}t}\psi &amp;amp;= -\textrm{i}H\psi \\&#xA;\frac{\rm{d}}{\textrm{d}t}\psi^* &amp;amp;= \textrm{i}H\psi^*. \tag{4}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The result is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\frac{\rm{d}}{\textrm{d}t}\langle \mathbf{r}\rangle &amp;amp;= \int \left(\textrm{i}H\psi^* \right) \mathbf{r}\psi \,dr + \int  \psi^* \mathbf{r}\left(-\textrm{i}H\psi \right)\,dr\tag{5}  \\&#xA;\langle \mathbf{v}\rangle &amp;amp;\equiv\textrm{i} \left[H ,\langle \mathbf{r}\rangle   \right].\tag{6}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I never explicitly mentioned anyhting about eigenvalues and never used &lt;span class=&quot;math-container&quot;&gt;$H\psi = \epsilon\psi$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$H\psi = \epsilon S \psi$&lt;/span&gt;: I just used:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the definition of an expectation value &lt;span class=&quot;math-container&quot;&gt;$\langle \cdot \rangle$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;the product rule for derivatives,&lt;/li&gt;&#xA;&lt;li&gt;the Schrödinger equation (see the derivation of the Schrödinger equation in Section 2.2 of &lt;a href=&quot;https://ocw.mit.edu/courses/physics/8-05-quantum-physics-ii-fall-2013/lecture-notes/MIT8_05F13_Chap_06.pdf&quot; rel=&quot;noreferrer&quot;&gt;this PDF&lt;/a&gt; to see why this is the equation of motion for &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; if we want its norm to be preserved as Born's rule relates wavefunction norms to probabilities: i.e. unitary evolution), so we have used:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Born's rule,&lt;/li&gt;&#xA;&lt;li&gt;the law that probabilities must sum up to 1,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;the definitions:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle \mathbf{v}\rangle \equiv \frac{\rm{d}}{\textrm{d}t}\langle \mathbf{r}\rangle$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$[A,B] \equiv AB-BA$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\textrm{i}^2=-1.$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;On page 20 of the same &lt;a href=&quot;https://ocw.mit.edu/courses/physics/8-05-quantum-physics-ii-fall-2013/lecture-notes/MIT8_05F13_Chap_06.pdf&quot; rel=&quot;noreferrer&quot;&gt;aforementioned PDF&lt;/a&gt; you can see how the Heisenberg equation of motion is derived, if you want to do something similar without expectation values.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-09-11T04:14:49.087" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2243" PostTypeId="2" ParentId="2238" CreationDate="2020-09-11T09:44:23.770" Score="12" Body="&lt;p&gt;&lt;strong&gt;Gamma Only:&lt;/strong&gt;&#xA;A k-point mesh (grid) only includes (samples) the gamma point of the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Gamma Centred:&lt;/strong&gt;&#xA;A k-point mesh (grid) that is centred around the gamma point of the Brillouin zone, and includes other points (often equally spaced, though not always). A gamma centred k-point grid often reduces computation cost, and contains important information with regard to band-gaps. However, a gamma centred k-point grid can fail to describe metallic ground-states. In general, a gamma k-point grid is often more advantages (although check your system).&lt;/p&gt;&#xA;&lt;p&gt;For instance, in relation to surface calculations (from &lt;a href=&quot;http://web.mit.edu/ceder/publications/2013_Wenhao_Sun_Surface_Slabs.pdf&quot; rel=&quot;noreferrer&quot;&gt;Efficient creation and convergence of surface slabs&lt;/a&gt;):&#xA;One must also be mindful that the k-point sampling accurately&#xA;reflects the reciprocal Bravais lattice of the surface Brillouin zone&#xA;— for example, the (111) surfaces of FCC and BCC crystals are hexagonal and require a gamma-centered odd k-point grid.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Monkhorst-Pack:&lt;/strong&gt;&#xA;A special type of k-point mesh (grid). The sampling k-points are distributed homogeneously in the Brillouin zone, with rows or columns of k-points running parallel to the reciprocal lattice vectors that span the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;From the original paper &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.13.5188&quot; rel=&quot;noreferrer&quot;&gt;Special points for Brillouin-zone integrations&lt;/a&gt;:&#xA;A method is given for generating sets of special points in the Brillouin zone which provides an efficient means of integrating periodic functions of the wave vector. The integration can be over the entire Brillouin zone or over specified portions thereof.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Note: The question relates to k-point grids, often encountered in planewave density functional theory.&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="786" LastEditDate="2020-09-11T10:49:34.867" LastActivityDate="2020-09-11T10:49:34.867" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2244" PostTypeId="1" AcceptedAnswerId="2245" CreationDate="2020-09-11T10:28:38.760" Score="5" ViewCount="456" Body="&lt;p&gt;I've noted a curious thing with PySCF when updating the molecular orbital coefficients of the mean-field object.&#xA;If one prints out the Fock matrix in the atomic basis (&lt;code&gt;F_ao&lt;/code&gt;) from the &lt;code&gt;mean_field&lt;/code&gt;, the values can differ once the &lt;code&gt;mo_coeff&lt;/code&gt; has been updated.&lt;/p&gt;&#xA;&lt;p&gt;The following is an extreme example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf&#xA;import numpy as np&#xA;&#xA;molecule = gto.Mole()&#xA;geometry = &amp;quot;&amp;quot;&amp;quot;&#xA;  O   0.000000   0.000000   0.000000&#xA;  H   0.758602   0.000000   0.504284&#xA;  H   0.758602   0.000000  -0.504284&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;molecule.atom = geometry&#xA;molecule.basis = &amp;quot;3-21g&amp;quot;&#xA;molecule.build()&#xA;&#xA;mean_field = scf.RHF(molecule)&#xA;mean_field.scf()&#xA;&#xA;F_ao1 = mean_field.get_fock()&#xA;mean_field.mo_coeff = np.loadtxt('0.txt')&#xA;F_ao2 = mean_field.get_fock()&#xA;&#xA;for row in range(len(F_ao1[0])):&#xA;    for col in range (len(F_ao1[0])):&#xA;        m = print(&amp;quot;{:10.6f}&amp;quot;.format(F_ao1[row][col]), end = &amp;quot; &amp;quot;)&#xA;    print(m)&#xA;print()&#xA;&#xA;for row in range(len(F_ao2[0])):&#xA;    for col in range (len(F_ao2[0])):&#xA;        m = print(&amp;quot;{:10.6f}&amp;quot;.format(F_ao2[row][col]), end = &amp;quot; &amp;quot;)&#xA;    print(m)&#xA;print()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;0.txt&lt;/code&gt; is a file containing a 13x13 matrix with all elements 0.&lt;/p&gt;&#xA;&lt;p&gt;I had assumed that the Fock matrix in the atomic basis would not be recalculated and was a stored object?&#xA;Is there an explanation for this behaviour?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;For reference, the output is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;---F_ao1---&#xA;-20.312687  -5.701111  -4.466295   0.000000   0.000000   0.036176  -0.000000   0.000000   0.007744  -0.589952  -1.509333  -0.589952  -1.509333 None&#xA; -5.701111  -1.628973  -2.433482   0.000000   0.000000   0.057360   0.000000   0.000000   0.041249  -0.715556  -1.164825  -0.715556  -1.164825 None&#xA; -4.466295  -2.433482  -2.132193   0.000000   0.000000   0.087107   0.000000   0.000000   0.196043  -0.702254  -1.079343  -0.702254  -1.079343 None&#xA;  0.000000   0.000000   0.000000   0.329725   0.000000  -0.000000  -0.772527   0.000000  -0.000000   0.477856   0.266686  -0.477856  -0.266686 None&#xA;  0.000000   0.000000   0.000000   0.000000   0.199071   0.000000  -0.000000  -0.799305   0.000000   0.000000   0.000000  -0.000000  -0.000000 None&#xA;  0.036176   0.057360   0.087107  -0.000000   0.000000   0.270456  -0.000000   0.000000  -0.791339   0.385320   0.258909   0.385320   0.258909 None&#xA; -0.000000   0.000000   0.000000  -0.772527  -0.000000  -0.000000  -0.228986  -0.000000  -0.000000   0.350672   0.173939  -0.350672  -0.173939 None&#xA;  0.000000   0.000000   0.000000   0.000000  -0.799305   0.000000  -0.000000  -0.018129   0.000000   0.000000   0.000000  -0.000000  -0.000000 None&#xA;  0.007744   0.041249   0.196043  -0.000000   0.000000  -0.791339  -0.000000   0.000000  -0.151176   0.286736   0.251041   0.286736   0.251041 None&#xA; -0.589952  -0.715556  -0.702254   0.477856   0.000000   0.385320   0.350672   0.000000   0.286736  -0.114823  -0.639373  -0.132769  -0.341354 None&#xA; -1.509333  -1.164825  -1.079343   0.266686   0.000000   0.258909   0.173939   0.000000   0.251041  -0.639373  -0.609333  -0.341354  -0.539374 None&#xA; -0.589952  -0.715556  -0.702254  -0.477856  -0.000000   0.385320  -0.350672  -0.000000   0.286736  -0.132769  -0.341354  -0.114823  -0.639373 None&#xA; -1.509333  -1.164825  -1.079343  -0.266686  -0.000000   0.258909  -0.173939  -0.000000   0.251041  -0.341354  -0.539374  -0.639373  -0.609333 None&#xA;&#xA;---F_ao2---&#xA;-32.880976  -7.706070  -6.427702   0.000000   0.000000   0.024455   0.000000   0.000000   0.003460  -0.829238  -2.157992  -0.829238  -2.157992 None&#xA; -7.706070 -10.178522  -8.072464   0.000000   0.000000   0.160239   0.000000   0.000000   0.096904  -1.784625  -3.309188  -1.784625  -3.309188 None&#xA; -6.427702  -8.072464  -8.320350   0.000000   0.000000   0.152962   0.000000   0.000000   0.252444  -2.656440  -4.381549  -2.656440  -4.381549 None&#xA;  0.000000   0.000000   0.000000  -8.774770   0.000000  -0.000000  -4.261563   0.000000   0.000000   1.468854   0.828412  -1.468854  -0.828412 None&#xA;  0.000000   0.000000   0.000000   0.000000  -8.692929   0.000000   0.000000  -4.186167   0.000000   0.000000   0.000000   0.000000   0.000000 None&#xA;  0.024455   0.160239   0.152962  -0.000000   0.000000  -8.742686   0.000000   0.000000  -4.232005   1.162911   0.707275   1.162911   0.707275 None&#xA;  0.000000   0.000000   0.000000  -4.261563   0.000000   0.000000  -5.400436   0.000000   0.000000   2.523505   1.731794  -2.523505  -1.731794 None&#xA;  0.000000   0.000000   0.000000   0.000000  -4.186167   0.000000   0.000000  -5.159485   0.000000   0.000000   0.000000   0.000000   0.000000 None&#xA;  0.003460   0.096904   0.252444   0.000000   0.000000  -4.232005   0.000000   0.000000  -5.305976   1.995294   1.491102   1.995294   1.491102 None&#xA; -0.829238  -1.784625  -2.656440   1.468854   0.000000   1.162911   2.523505   0.000000   1.995294  -4.947012  -3.548389  -0.288794  -1.280573 None&#xA; -2.157992  -3.309188  -4.381549   0.828412   0.000000   0.707275   1.731794   0.000000   1.491102  -3.548389  -4.642069  -1.280573  -2.706780 None&#xA; -0.829238  -1.784625  -2.656440  -1.468854   0.000000   1.162911  -2.523505   0.000000   1.995294  -0.288794  -1.280573  -4.947012  -3.548389 None&#xA; -2.157992  -3.309188  -4.381549  -0.828412   0.000000   0.707275  -1.731794   0.000000   1.491102  -1.280573  -2.706780  -3.548389  -4.642069 None&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="786" LastActivityDate="2020-09-11T10:59:05.327" Title="PySCF: atomic basis Fock matrix changes after mo_coeff update" Tags="|pyscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2245" PostTypeId="2" ParentId="2244" CreationDate="2020-09-11T10:59:05.327" Score="9" Body="&lt;p&gt;The Fock matrix is defined as &lt;span class=&quot;math-container&quot;&gt;$F_{\mu \nu} = \partial E / \partial P_{\mu \nu}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf P}$&lt;/span&gt; is the density matrix and &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the total energy functional (here: restricted Hartree-Fock i.e. RHF). The RHF density matrix is given by &lt;span class=&quot;math-container&quot;&gt;${\bf P} = 2 {\bf C}_{\rm occ} {\bf C}^{\rm T}_{\rm occ}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf C}_{\rm occ}$&lt;/span&gt; are the occupied orbital coefficients.&lt;/p&gt;&#xA;&lt;p&gt;Since the energy is non-linear in the density (Hartree-Fock is quadratic in the density matrix), the Fock matrix depends on the density matrix: &lt;span class=&quot;math-container&quot;&gt;${\bf F}={\bf F}({\bf P})$&lt;/span&gt;. If you change the density matrix, the Fock matrix will also change.&lt;/p&gt;&#xA;&lt;p&gt;By examining the properties of the density matrix, you can see that the density matrix does not change if you only mix occupied orbitals with occupied orbitals, and/or virtual orbitals with virtual orbitals. However, if you rotate occupied orbitals into virtual orbitals (and vice versa), the density matrix changes, and thereby also the Fock matrix and the total energy change.&lt;/p&gt;&#xA;&lt;p&gt;For a more thorough discussion see e.g. our recent open-access overview in &lt;a href=&quot;https://www.mdpi.com/1420-3049/25/5/1218&quot; rel=&quot;noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-11T10:59:05.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2246" PostTypeId="1" CreationDate="2020-09-11T17:47:46.560" Score="10" ViewCount="617" Body="&lt;p&gt;I have a structure composed of many MX4 tetrahedral units. When doing MD on this structure I find that just one M atom moves into a trigonal planar coordination (MX3). I was wondering how to set constraints such that the M atom is always bonded to 4 X atoms in a tetrahedral coordination environment.&lt;/p&gt;&#xA;&lt;p&gt;I came across the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ICONST&quot; rel=&quot;nofollow noreferrer&quot;&gt;ICONST option&lt;/a&gt;, but I'm not sure how to use it to implement the constraint for all the M atoms in my structure.&lt;/p&gt;&#xA;&lt;p&gt;POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Li6 P1 S5 Cl1&#xA;1.0&#xA;-4.929500 0.000000 -4.929500&#xA;4.929500 -4.929500 0.000000&#xA;-4.929500 -4.929500 0.000000&#xA;Li P S Cl&#xA;6 1 5 1&#xA;direct&#xA;0.370400 0.018000 0.018000 Li+&#xA;0.629600 0.611600 0.018000 Li+&#xA;0.964000 0.352400 0.018000 Li+&#xA;0.629600 0.611600 0.352400 Li+&#xA;0.036000 0.018000 0.611600 Li+&#xA;0.370400 0.018000 0.611600 Li+&#xA;1.000000 0.500000 0.500000 P5+&#xA;0.500000 0.250000 0.250000 S2-&#xA;0.761060 0.141590 0.619470 S2-&#xA;0.761060 0.619470 0.619470 S2-&#xA;0.238940 0.619470 0.619470 S2-&#xA;0.238940 0.619470 0.141590 S2-&#xA;0.000000 0.000000 1.000000 Cl-&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2021-09-21T22:21:02.847" LastActivityDate="2021-09-21T22:21:02.847" Title="Constraining coordination or bond lengths for certain atoms in VASP" Tags="|vasp|molecular-dynamics|geometry|" AnswerCount="0" CommentCount="11" ClosedDate="2022-01-02T20:27:02.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="2247" PostTypeId="1" AcceptedAnswerId="2302" CreationDate="2020-09-11T19:01:17.667" Score="12" ViewCount="1868" Body="&lt;p&gt;I have a rather general question of what software packages exist to do Quantum Theory Atom in Molecule (QTAIM) analysis of periodic and non-periodic systems.  Working with Gaussian I have previously used &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt;.  What other codes exist and what advantages/disadvantages do they have?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-09-16T02:05:59.547" LastActivityDate="2020-12-16T05:38:37.377" Title="What software can be used to do QTAIM analysis?" Tags="|one-topic-per-answer|software-recommendations|atoms-in-molecules|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2248" PostTypeId="1" AcceptedAnswerId="2279" CreationDate="2020-09-12T07:46:24.670" Score="11" ViewCount="222" Body="&lt;p&gt;I am beginner of material modelling that's why my question may be basic and I have no direction. If we want to see whether two crystal layer(semiconductor) can be put together, can the DFT calculation let us to find the answer?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2020-09-12T22:26:58.340" LastActivityDate="2020-09-16T02:27:15.403" Title="How to determine whether we can put two semiconductor thin film together?" Tags="|density-functional-theory|heterostructures|solid-solid-interface|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2249" PostTypeId="2" ParentId="2248" CreationDate="2020-09-12T10:38:40.747" Score="9" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In the experiment, you can always put two semiconducting crystal layers together.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For DFT simulation, you can also stack two semiconducting crystal layers together, but you must consider the lattice match. For example, monolayer MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and monolayer WS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; can be stacked directly because these two monolayers have almost the same lattice constant. But if you want to stack graphene and MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, you must build supercells (with almost the same lattice constants) of both monolayers and then stack together.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;These ideas to build a reasonable 2D heterostructure model for DFT simulation can be applied to the bulk materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-12T11:01:35.597" LastActivityDate="2020-09-12T11:01:35.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2250" PostTypeId="5" CreationDate="2020-09-12T23:46:09.987" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:46:09.987" LastActivityDate="2020-09-12T23:46:09.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2251" PostTypeId="4" CreationDate="2020-09-12T23:46:09.987" Score="0" Body="Questions about metallic complexes." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:46:09.987" LastActivityDate="2020-09-12T23:46:09.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2252" PostTypeId="5" CreationDate="2020-09-12T23:47:04.043" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:04.043" LastActivityDate="2020-09-12T23:47:04.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2253" PostTypeId="4" CreationDate="2020-09-12T23:47:04.043" Score="0" Body="Questions about energy dispersion." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:04.043" LastActivityDate="2020-09-12T23:47:04.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2254" PostTypeId="5" CreationDate="2020-09-12T23:47:16.940" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:16.940" LastActivityDate="2020-09-12T23:47:16.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2255" PostTypeId="4" CreationDate="2020-09-12T23:47:16.940" Score="0" Body="Questions about effective mass." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:16.940" LastActivityDate="2020-09-12T23:47:16.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2256" PostTypeId="5" CreationDate="2020-09-12T23:47:31.063" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:31.063" LastActivityDate="2020-09-12T23:47:31.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2257" PostTypeId="4" CreationDate="2020-09-12T23:47:31.063" Score="0" Body="Questions about solubility." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:31.063" LastActivityDate="2020-09-12T23:47:31.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2258" PostTypeId="5" CreationDate="2020-09-12T23:47:46.727" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:46.727" LastActivityDate="2020-09-12T23:47:46.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2259" PostTypeId="4" CreationDate="2020-09-12T23:47:46.727" Score="0" Body="Questions about the virtual crystal approximation." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:47:46.727" LastActivityDate="2020-09-12T23:47:46.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2260" PostTypeId="5" CreationDate="2020-09-12T23:48:03.397" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:03.397" LastActivityDate="2020-09-12T23:48:03.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2261" PostTypeId="4" CreationDate="2020-09-12T23:48:03.397" Score="0" Body="Questions about spin crossover complexes." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:03.397" LastActivityDate="2020-09-12T23:48:03.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2262" PostTypeId="5" CreationDate="2020-09-12T23:48:44.800" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:44.800" LastActivityDate="2020-09-12T23:48:44.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2263" PostTypeId="4" CreationDate="2020-09-12T23:48:44.800" Score="0" Body="Questions about vibronic interactions (interactions involving both vibrational and electronic degrees of freedom)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:44.800" LastActivityDate="2020-09-12T23:48:44.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2264" PostTypeId="5" CreationDate="2020-09-12T23:48:58.590" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:58.590" LastActivityDate="2020-09-12T23:48:58.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2265" PostTypeId="4" CreationDate="2020-09-12T23:48:58.590" Score="0" Body="Questions about zero point energy." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-12T23:48:58.590" LastActivityDate="2020-09-12T23:48:58.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2266" PostTypeId="1" CreationDate="2020-09-13T01:00:42.930" Score="10" ViewCount="358" Body="&lt;p&gt;Even some DFT methods or beyond DFT methods such as MP2 calculations are computationally very expensive today even with clusters. If you compare QMC (quantum monte carlo) calculations with them, are the QMC calculations way too much expensive? Is it worth to invest time in QMC?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="984" LastEditDate="2020-09-13T06:04:14.407" LastActivityDate="2020-09-13T07:13:18.980" Title="Are QMC calculations practical for periodic structure calculations?" Tags="|density-functional-theory|high-performance-computing|quantum-monte-carlo|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2267" PostTypeId="2" ParentId="2266" CreationDate="2020-09-13T07:13:18.980" Score="8" Body="&lt;p&gt;Quantum Monte Carlo (QMC) calculations in various forms, for example variational QMC or diffusion QMC have been used to study periodic systems for decades. In most cases, they provide results that are more accurate than DFT, so it is often taken as a reference for solid state calculations. Indeed, the pioneering QMC calculations of the electron gas by Ceperley and Alder (see &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.45.566&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) form the basis of common approximations to exchange correlation functionals, so in a sense enable DFT.&lt;/p&gt;&#xA;&lt;p&gt;So is it worth investing time in QMC? The method is still computationally more expensive than DFT, so the answer depends. If the system/property you are interested in is well-described by DFT (e.g. weak correlations) then there is no point in doing QMC calculations. However, if you need higher accuracy, there is a definite case for using QMC methods. Another point to consider for the longer term is that many QMC methods are trivially parallelizable, so they are capable of making full use of modern computer architectures, which means that they will probably become increasingly pervasive.&lt;/p&gt;&#xA;&lt;p&gt;The go-to review article of the use of QMC methods to study solids by Matthew Foulkes and co-workers can be found &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.33&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is a list of codes that implement QMC calculations for solids that are widely used (feel free to add more):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;CASINO: &lt;a href=&quot;https://vallico.net/casinoqmc/&quot; rel=&quot;noreferrer&quot;&gt;https://vallico.net/casinoqmc/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;QMCPACK: &lt;a href=&quot;https://qmcpack.org&quot; rel=&quot;noreferrer&quot;&gt;https://qmcpack.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;QWalk: &lt;a href=&quot;http://qwalk.github.io/mainline/&quot; rel=&quot;noreferrer&quot;&gt;http://qwalk.github.io/mainline/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-13T07:13:18.980" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2268" PostTypeId="2" ParentId="1513" CreationDate="2020-09-13T13:56:44.803" Score="10" Body="&lt;h3&gt;KS-DFT: Kohn-Sham DFT&lt;/h3&gt;&#xA;&lt;p&gt;The KS-DFT is proposed to deal with the problems of &lt;strong&gt;orbital-free DFT (OFDFT)&lt;/strong&gt;, which has been explained by @wcw. OFDFT attempts to compute the energy of interacting electrons, as the functional of the density. While this brute force approach is in principle correct, in practice it is not very accurate. This is due to &lt;strong&gt;the lack of accurate approximations for the kinetic energy functional&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then Kohn and Sham proposed an alternative approach in order to overcome this problem.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.140.A1133&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. 140, A1133 (1965)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the Kohn-Sham approach, a fictitious non-interacting system is constructed, in such a way, that its density is the same as that of the interacting electrons. The core ideas can be summarized in the following figure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/E1Eo6.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/E1Eo6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;By introducing a fictitious KS non-interacting electron system, the problem OFDFT encountered is well solved.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.southampton.ac.uk/assets/centresresearch/documents/compchem/DFT_L6.pdf&quot; rel=&quot;noreferrer&quot;&gt;You can find more details on this lecture note written by C.-K.Skylaris.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="792" LastEditDate="2020-09-13T14:04:21.260" LastActivityDate="2020-09-13T14:04:21.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2269" PostTypeId="1" CreationDate="2020-09-13T19:39:26.207" Score="7" ViewCount="195" Body="&lt;p&gt;I had some experience with the ACFDT-RPA, but despite its promising features it's not practical most of the time, and for that reason, I'm looking for a new method for reference calculations.&lt;/p&gt;&#xA;&lt;p&gt;QMC is the first alternative for me. Since I'm not familiar with QMC, what are its advantages/disadvantages over ACFDT-RPA? For example, &lt;strong&gt;is it computationally more expensive?&lt;/strong&gt; &lt;strong&gt;Is restarting the calculation possible?&lt;/strong&gt; (it's not possible with the ACFDT-RPA since it's implemented as a post-processing method due to its cost).&lt;/p&gt;&#xA;&lt;p&gt;Principally, both methods give the exact ground state energy.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2021-04-11T22:32:08.157" LastActivityDate="2021-04-11T22:35:54.993" Title="What are the advantages/disadvantages of QMC over ACFDT-RPA?" Tags="|density-functional-theory|quantum-monte-carlo|random-phase-approximation|high-precision|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2270" PostTypeId="5" CreationDate="2020-09-13T21:35:13.517" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-13T21:35:13.517" LastActivityDate="2020-09-13T21:35:13.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2271" PostTypeId="4" CreationDate="2020-09-13T21:35:13.517" Score="0" Body="Questions asking for help debugging one's own code, or debugging an issue when using someone else's code. Slightly different from the [software-assistance] tag which is for people asking for help with the usage of some software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-27T21:45:07.830" LastActivityDate="2020-09-27T21:45:07.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2272" PostTypeId="2" ParentId="1568" CreationDate="2020-09-14T10:36:00.097" Score="3" Body="&lt;h2&gt;GVB: Generalized Valence Bond&lt;/h2&gt;&#xA;&lt;p&gt;Unlike the Hartree−Fock (HF) wave function, Generalized Valence Bond GVB accounts for nondynamical correlation in valence orbitals. Compared with the complete-active-space self-consistent field (CASSCF) wave function, obtaining the GVB wave function is in principle less computationally demanding since the number of configurations is smaller. Unfortunately, GVB becomes problematic for molecules larger than a few atoms since the number of linearly independent spin functions (which grows factorially) becomes prohibitively high, and there is no unique way of truncating that number.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Ref: J. Chem. Theory Comput. 2019, 15, 8, 4430–4439 'Generalized Valence Bond Perfect-Pairing Made Versatile Through Electron-Pairs Embedding'&lt;/p&gt;&#xA;" OwnerUserId="786" LastActivityDate="2020-09-14T10:36:00.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2273" PostTypeId="2" ParentId="2007" CreationDate="2020-09-14T19:38:50.883" Score="2" Body="&lt;p&gt;The author seems to have abandoned this question but I will summarize what the comments are saying.&lt;/p&gt;&#xA;&lt;p&gt;It seems this issue was likely related to the cutoff applied to the TIP3P model.  This resulted in pressure and density values that were incorrect.  Since the author was doing an NPT simulation and reported an incorrect pressure was seen (the average pressure is fixed), it is also likely that they were taking instantaneous values rather than the average value which may also contribute to the error seen.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-14T19:38:50.883" CommentCount="0" CommunityOwnedDate="2020-09-14T19:38:50.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="2274" PostTypeId="2" ParentId="1790" CreationDate="2020-09-14T21:02:32.410" Score="6" Body="&lt;h2&gt;&lt;strong&gt;1. Ab-initio protein--protein docking:&lt;/strong&gt;&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://vakser.compbio.ku.edu/main/resources_gramm1.03.php&quot; rel=&quot;noreferrer&quot;&gt;GRAMM&lt;/a&gt; (=Global Range Molecular Modeling)&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Performs rigid-body docking based on the shape complementarity and Miyazawa-Jernigan contact potentials;&lt;/li&gt;&#xA;&lt;li&gt;Exhaustively samples the search space (i.e., identifies the Global Energy Minimum solution, in the given formulation);&lt;/li&gt;&#xA;&lt;li&gt;Very fast (employs Fast Fourier Transform) and is suitable for high-throughput docking;&lt;/li&gt;&#xA;&lt;li&gt;Allows clustering of docking poses as a postprocessing;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;limitations&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;currently no account for flexibility of molecules;&lt;/li&gt;&#xA;&lt;li&gt;most likely will fail in application to antibodies;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.rosettacommons.org/docs/latest/application_documentation/docking/docking-protocol&quot; rel=&quot;noreferrer&quot;&gt;RosettaDock&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;is effectively a set of protocols/pipelines that cover a wide range of docking problems. There is no single universally applicable protocol to all cases.&lt;/li&gt;&#xA;&lt;li&gt;Efficient application requires analysis of the target and choosing the most suitable pipeline.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.attract.ph.tum.de/services/ATTRACT/documentation.html&quot; rel=&quot;noreferrer&quot;&gt;ATTRACT/iATTRACT&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;An inherently flexible docking protocol that employs Normal Modes Analysis at both the global docking stage (ATTRACT) and the refinement stage (iATTRACT).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;quite good benchmarking results for protein--protein complexes (in terms of the  &lt;a href=&quot;https://www.capri-docking.org/&quot; rel=&quot;noreferrer&quot;&gt;CAPRI&lt;/a&gt; criteria)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The package is written in a mixture of C, Python, bash and FORTRAN and is difficult to navigate/modify;&lt;/li&gt;&#xA;&lt;li&gt;virtually impossible to prepare input to the pipeline. For this purpose the developers created a &lt;a href=&quot;http://www.attract.ph.tum.de/services/ATTRACT/attract.html&quot; rel=&quot;noreferrer&quot;&gt;web-server&lt;/a&gt; specifically for the preparation of input and configuration files that must be downloaded and run on a locally compiled code.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;&lt;strong&gt;2. Template-based protein--protein docking:&lt;/strong&gt;&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://zhanglab.ccmb.med.umich.edu/MM-align/&quot; rel=&quot;noreferrer&quot;&gt;MM-align&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is a class of cases when one has an experimentally-solved structure of a protein--protein complex with monomers very similar in structure to those that must be docked: i.e.&lt;/p&gt;&#xA;&lt;p&gt;A-B  is an experimentally-solved structure of a dimer complex (monomers A and B)&lt;/p&gt;&#xA;&lt;p&gt;one has monomers A' and B' (the target complex A'-B') such, that TM-score(A,A') &amp;gt; 0.5 and TM-score(B, B') &amp;gt; 0.5. Then, A' might be structurally aligned onto A and B' might be structurally aligned onto B. Thus, one gets the structure of complex A'-B'.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;robust and easy.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;templates (i.e., A-B) must be known.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Discussion of these issues and the latest benchmarking results can be found here:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25875&quot; rel=&quot;noreferrer&quot;&gt;How to choose templates for modeling of protein complexes: Insights from benchmarking template‐based docking&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25889?af=R&quot; rel=&quot;noreferrer&quot;&gt;Application of docking methodologies to modeled proteins&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1338" LastActivityDate="2020-09-14T21:02:32.410" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2275" PostTypeId="1" AcceptedAnswerId="2276" CreationDate="2020-09-15T02:55:24.970" Score="11" ViewCount="820" Body="&lt;p&gt;I found there are very few tutorials regarding how to use the CPA method in VASP. Are there any nice materials available?&lt;/p&gt;&#xA;&lt;p&gt;Also what are the pros and cons of CPA and VCA? If CPA is more reliable then VCA, why do people still use VCA?&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1339" LastEditorUserId="5" LastEditDate="2020-09-15T05:02:14.123" LastActivityDate="2020-09-15T05:02:14.123" Title="How to use coherent-potential approximation (CPA) method in VASP?" Tags="|vasp|reference-request|virtual-crystal-approximation|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2276" PostTypeId="2" ParentId="2275" CreationDate="2020-09-15T03:34:20.440" Score="9" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;VASP utilizes a plane-wave basis to solve the Kohn-Sham equation. However, the CPA method is formulated in the framework of Green's function. Therefore, you cannot do the CPA simulation in VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For the DFT simulation with the consideration of disorder effect, if you want to use the CPA method, you can use &lt;a href=&quot;https://www.questaal.org/&quot; rel=&quot;noreferrer&quot;&gt;the Questaal package&lt;/a&gt;, which provides a Kohn-Sham equation solver in the framework of Green's function.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;As for the pros and cons of CPA and VCA, you can read &lt;a href=&quot;https://www.tcm.phy.cam.ac.uk/castep/documentation/WebHelp/content/modules/castep/thcastepdisorder.htm&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-15T03:34:20.440" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2277" PostTypeId="2" ParentId="432" CreationDate="2020-09-15T15:00:41.997" Score="3" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Schematic electron occupation of allowed energy bands for an insulator, metal, semimetal, and semiconductor:&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/s8vqG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s8vqG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the vertical extent of the boxes indicates the allowed energy regions and the green areas indicate the regions filled with electrons.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In a &lt;strong&gt;semimetal&lt;/strong&gt; one band is almost filled and another band is nearly empty at absolute zero.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The electron occupancy of the &lt;strong&gt;semimetal&lt;/strong&gt; is slightly different from the filling of &lt;strong&gt;metal&lt;/strong&gt; in which the allowed band is partially filled.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There are many examples of semimetal in our real world, like two-dimensional material graphene.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eECaW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eECaW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How small/unique the overlap should be so that we can classify a material as a semi-metal?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I guess the touched two bands should share an energy window between &lt;span class=&quot;math-container&quot;&gt;$[0,0.005]$&lt;/span&gt; eV. And you can identify that by first-principles energy band calculation.&lt;/p&gt;&#xA;&lt;p&gt;PS: A pure &lt;strong&gt;semiconductor&lt;/strong&gt; becomes an insulator at absolute zero. The left of the two semiconductors shown is at finite temperature, with carriers excited thermally. The other semiconductor is electron-deficient because of impurities.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-16T01:22:07.263" LastActivityDate="2020-09-16T01:22:07.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2278" PostTypeId="1" AcceptedAnswerId="2341" CreationDate="2020-09-15T15:56:37.363" Score="13" ViewCount="3742" Body="&lt;p&gt;Jupyter notebooks have always been a great way for me to create high-quality graphs, and write code.&lt;/p&gt;&#xA;&lt;p&gt;The features also continue to improve with packages such as &lt;a href=&quot;https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906&quot; rel=&quot;noreferrer&quot;&gt;Jupyter Lab&lt;/a&gt;, and now &lt;a href=&quot;https://medium.com/swlh/the-new-jupyter-book-4028f054893f&quot; rel=&quot;noreferrer&quot;&gt;Jupyter Books&lt;/a&gt;, which continue to improve the environment and capabilities of the Jupyter ecosystem.&lt;/p&gt;&#xA;&lt;p&gt;However, I've never had any luck visualizing 3d structures such as xyz files in Jupyter Notebook.&lt;/p&gt;&#xA;&lt;p&gt;What packages can be used to visualize 3d structures in Jupyter (IPython)?&lt;/p&gt;&#xA;&lt;p&gt;Please list any pros/cons, and a link to further documentation/installation instructions. A simple example of some code would also be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2024-02-19T08:16:35.117" Title="Molecular visualization software in Jupyter (IPython) Notebooks" Tags="|one-topic-per-answer|visualization-software|python|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2279" PostTypeId="2" ParentId="2248" CreationDate="2020-09-15T16:12:43.107" Score="6" Body="&lt;p&gt;Speaking as someone who does both computational modeling and experiment, there is not a trivial answer! I'm not sure if you are referring to 2D materials (which Jack addressed in his answer) but I am not experienced with that, so I will try to answer in the context of general thin films.&lt;/p&gt;&#xA;&lt;p&gt;In experiment, you can of course deposit films on any substrate you wish, but what you really get at the end of it isn't always straightforward. Let's assume that you can grow the films epitaxially with good lattice matching, and that you have a good understanding of the steps needed to ensure a single, known surface termination on the substrate. There's still no guarantee that you will get a clean interface, since different materials can still chemically react with each other. For example, growth of non-silicon oxides (MOx) on silicon can result in a Si/SiO2/MOx structure rather than Si/MOx. A nice paper on why SrTiO3 is not a good gate dielectric material is &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.83.165318&quot; rel=&quot;noreferrer&quot;&gt;Kolpak and Ismail-Beigi, Phys. Rev. B &lt;strong&gt;83&lt;/strong&gt;, 165318&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;On the computational side, predicting what the interface will be is also not easy. There is a large space of possible terminations and arrangements to explore. The paper I referenced shows a small exploration of the possibilities with SrTiO3 and Si. There is no way of knowing for sure what your real-life termination will be without experiment. Usually you have some known idea of termination and structure (from high resolution cross-sectional transmission electron microscopy, for example) which you can then model to get some insights from electronic structure. It's challenging to make predictions purely from modeling in these cases.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-09-15T16:12:43.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2280" PostTypeId="1" CreationDate="2020-09-15T17:26:06.073" Score="14" ViewCount="2952" Body="&lt;p&gt;I would like to do start doing some basic calculations using DFT. I am interested in solid state physics of strongly correlated materials in 3D (for example high temperature superconductors) or 2D (for example, graphene, or transition metal dichalcogenide monolayers). I prefer free software (ideally, open source, but at least free of charge) which is easy to use. I am interested in DFT as a tool to calculate properties of materials, and I am not interested in learning the details of DFT (at least not now) and also I am not interested in software developing.&lt;/p&gt;&#xA;&lt;p&gt;I have a background in solid state physics, but I am a complete beginner of DFT. I was thinking about ABINIT, JDFTx, or Quantum Espresso, or any other free/easy to use package. Any suggestion?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/570383/any-suggestion-for-a-dft-software-package-for-a-beginner?noredirect=1#comment1305108_570383&quot;&gt;Cross post from physics stack exchange&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1331" LastEditorUserId="5" LastEditDate="2020-09-16T17:55:58.230" LastActivityDate="2020-09-21T10:46:40.973" Title="DFT software package for a beginner?" Tags="|density-functional-theory|software-recommendations|open-source|from-phys-se|" AnswerCount="5" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2281" PostTypeId="2" ParentId="2278" CreationDate="2020-09-15T18:05:58.687" Score="11" Body="&lt;h3&gt;NGLVIEW&lt;/h3&gt;&#xA;&lt;p&gt;I discovered it very recently when I was using &lt;a href=&quot;https://www.mdanalysis.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDAnalysis&lt;/a&gt; to play with molecular dynamic trajectories. Therefore, I am not able to write about pros/cons.&lt;/p&gt;&#xA;&lt;p&gt;Site: &lt;a href=&quot;https://github.com/nglviewer/nglview&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/nglviewer/nglview&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;An IPython/Jupyter widget to interactively view molecular structures and trajectories. Utilizes the embeddable NGL Viewer for rendering. Support for showing data from the file-system, RCSB PDB, simpletraj and from objects of analysis libraries mdtraj, pytraj, mdanalysis, ParmEd, rdkit, ase, HTMD, biopython, cctbx, pyrosetta, schrodinger's Structure&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-09-21T18:49:22.387" LastActivityDate="2020-09-21T18:49:22.387" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2282" PostTypeId="2" ParentId="2280" CreationDate="2020-09-15T18:50:05.700" Score="8" Body="&lt;h3&gt;SIESTA&lt;/h3&gt;&#xA;&lt;p&gt;I strongly recommend SIESTA. From the &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;SIESTA is both a method and its computer program implementation, to perform efficient electronic structure calculations and ab initio molecular dynamics simulations of molecules and solids. SIESTA's efficiency stems from the use of a basis set of strictly-localized atomic orbitals. A very important feature of the code is that its accuracy and cost can be tuned in a wide range, from quick exploratory calculations to highly accurate simulations matching the quality of other approaches, such as plane-wave methods.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As it uses numerical orbitals, the demand for memory is lower than the codes you mention. Some of the properties it can calculate:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Total and partial energies.&lt;/li&gt;&#xA;&lt;li&gt;Atomic forces.&lt;/li&gt;&#xA;&lt;li&gt;Stress tensor.&lt;/li&gt;&#xA;&lt;li&gt;Electric dipole moment.&lt;/li&gt;&#xA;&lt;li&gt;Atomic, orbital and bond populations (Mulliken).&lt;/li&gt;&#xA;&lt;li&gt;Electron density.&lt;/li&gt;&#xA;&lt;li&gt;Geometry relaxation, fixed or variable cell.&lt;/li&gt;&#xA;&lt;li&gt;Constant-temperature molecular dynamics (Nose thermostat).&lt;/li&gt;&#xA;&lt;li&gt;Variable cell dynamics (Parrinello-Rahman).&lt;/li&gt;&#xA;&lt;li&gt;Spin polarized calculations (collinear or not).&lt;/li&gt;&#xA;&lt;li&gt;k-sampling of the Brillouin zone.&lt;/li&gt;&#xA;&lt;li&gt;Local and orbital-projected density of states.&lt;/li&gt;&#xA;&lt;li&gt;COOP and COHP curves for chemical bonding analysis.&lt;/li&gt;&#xA;&lt;li&gt;Dielectric polarization.&lt;/li&gt;&#xA;&lt;li&gt;Vibrations (phonons).&lt;/li&gt;&#xA;&lt;li&gt;Band structure.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The code can be downloaded from &lt;a href=&quot;http://gitlab.com/siesta-project/siesta&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The page has links to the &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Manuals/manuals.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt;, &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt; and &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/list.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;mailing list&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One big feature it has is the TranSIESTA module that permits doing transport calculation using several electrodes.&lt;/p&gt;&#xA;&lt;p&gt;As an example, here is an input file. It is free format and designed to use keywords for the task you want to complete:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        # ---------------------------------------------------------------------------&#xA;        # Name and Label&#xA;        # ---------------------------------------------------------------------------&#xA;        &#xA;        SystemName          BN-Cd-p0&#xA;        SystemLabel         BN-Cd-p0&#xA;        &#xA;        # ---------------------------------------------------------------------------&#xA;        # Lattice&#xA;        # ---------------------------------------------------------------------------&#xA;        &#xA;        LatticeConstant             12.787740 Ang&#xA;        &#xA;        %block LatticeVectors&#xA;             1.394587      0.000000      0.000000&#xA;             0.000000      1.394587      0.000000&#xA;             0.000000      0.000000      1.000000&#xA;        %endblock LatticeVectors&#xA;        &#xA;        # ---------------------------------------------------------------------------&#xA;        # Species and Atoms&#xA;        # ---------------------------------------------------------------------------&#xA;        &#xA;        NumberOfSpecies        3&#xA;        NumberOfAtoms        121&#xA;        &#xA;        %block ChemicalSpeciesLabel&#xA;          1   5  B&#xA;          2   7  N&#xA;          3  48  Cd&#xA;        %endblock ChemicalSpeciesLabel&#xA;        &#xA;        # ---------------------------------------------------------------------------&#xA;        # Atomic Coordinates&#xA;        # ---------------------------------------------------------------------------&#xA;        AtomicCoordinatesFormat Ang&#xA;        &#xA;        %block AtomicCoordinatesAndAtomicSpecies&#xA;           12.92631935    8.92625145    2.84349444   1       1  B&#xA;           12.92618164    8.92582742    7.10464184   1       2  B&#xA;           12.93639581    8.92650310   11.36723889   1       3  B&#xA;        .&#xA;        .&#xA;        .&#xA;           12.20659949    6.53582303    9.93994222   2     117  N&#xA;           12.73788419    7.68704422    0.71272677   1     118  B&#xA;           12.72084758    7.68856837    4.97486209   1     119  B&#xA;           12.73073524    7.68655704    9.23576392   1     120  B&#xA;            8.91680374    2.17946810    5.76712116   3     121  Cd&#xA;        %endblock AtomicCoordinatesAndAtomicSpecies&#xA;        &#xA;        PAO.BasisSize     DZP&#xA;        MD.TypeOfRun      CG&#xA;        MD.NumCGsteps     0&#xA;        MinSCFIterations  3&#xA;        MaxSCFIterations  1000&#xA;        SpinPolarized     .true.&#xA;        MeshCutoff        500 Ry&#xA;        DM.MixingWeight   0.25&#xA;        DM.NumberPulay    1&#xA;        DM.Tolerance      0.001&#xA;        XC.functional     GGA&#xA;        XC.authors        PBE&#xA;        SolutionMethod diagon&#xA;        &#xA;        #############################&#xA;        XML.Write .true.&#xA;        &#xA;---------------------------------------------------------------------------&#xA;        # ---------------------------------------------------------------------------&#xA;        &#xA;        &#xA;        XML.Write .true.&#xA;        #############################&#xA;        WriteEigenvalues       .true.&#xA;        WriteKbands            .true.&#xA;        WriteBands             .true.&#xA;        WriteWaveFunctions     .true.&#xA;        SaveRho                       .true.&#xA;        SaveElectrostaticPotential    .true.&#xA;        UseSaveData            .true.                &#xA;        &#xA;        %block kgrid_Monkhorst_Pack&#xA;           1   0   0    0.0&#xA;           0   1   0    0.0&#xA;           0   0   20   0.0&#xA;         %endblock kgrid_Monkhorst_Pack&#xA;        &#xA;         %block BandLines&#xA;          1  0.00 0.00 0.00   \Gamma  #Starting from gamma point&#xA;          200  0.00 0.00 1.00  Z       #200 points from gamma to Z.&#xA;          %endblock BandLines&#xA;        &#xA;        %block LocalDensityOfStates&#xA;            -20.00 0.00 eV&#xA;        %endblock LocalDensityOfStates&#xA;        &#xA;        %block ProjectedDensityOfStates&#xA;            -7.0 1.0 0.05 1000 eV&#xA;        %endblock ProjectedDensityOfStates&#xA;        &#xA;        #################################&#xA;        # Charge calculation            #&#xA;        #################################&#xA;        WriteMullikenPop       1&#xA;        WriteDenchar           .true.&#xA;        WriteHirshfeldPop      .true.&#xA;        WriteVoronoiPop        .true.&#xA;        SaveTotalCharge        .true.&#xA;        SaveBaderCharge        .true.&#xA;        #################################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-09-20T16:16:00.803" LastActivityDate="2020-09-20T16:16:00.803" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2283" PostTypeId="1" AcceptedAnswerId="2401" CreationDate="2020-09-15T20:28:17.747" Score="23" ViewCount="2476" Body="&lt;p&gt;There are many things that can be done with the output of a molecular dynamics simulation, but one of the more powerful things is the ability to compute the vibrational density of states (or the infrared spectrum and raman spectrum). It is well known that the vibrational density of states can be related to the fourier transform of the velocity autocorrelation function (VACF). My question is, how exactly do I compute this autocorrelation function?&lt;/p&gt;&#xA;&lt;p&gt;To be more concrete, suppose I have a large file of xyz-formatted velocities, as I would get from a molecular dynamics simulation (MD). Each velocity frame is separated in time by &lt;span class=&quot;math-container&quot;&gt;$k\Delta t$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is the stride at which you save the velocities and &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; is the actual simulation time step.&lt;/p&gt;&#xA;&lt;p&gt;The VACF is defined as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C(t)=A\langle\vec{v}(0)\cdot\vec{v}(t)\rangle&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is some normalization constant and &lt;span class=&quot;math-container&quot;&gt;$\vec{v}(t)$&lt;/span&gt; is the velocity of the system at time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. The reason I am asking this question is not because there aren't resources explaining how to calculate this quantity, and why it is useful, but because there are way too many of them and they often contradict each other.&lt;/p&gt;&#xA;&lt;p&gt;First of all, there is a fairly trivial way to calculate this which is to actually do the dot-product between all the velocity vectors for all values of time and just average them. This scales as &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; and is almost never used because there is an elegant way to calculate correlation functions using fourier transforms which is much more efficient, so the answer should describe that approach, though I don't think it's necessary to describe what a fourier transform actually is in answering this question.&lt;/p&gt;&#xA;&lt;p&gt;Here are some questions I would like answered in detail, which aren't totally clear to me because of conflicting information I have seen.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What value should be chosen for the normalization constant &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;?&lt;/li&gt;&#xA;&lt;li&gt;Is the final VACF meant to be the sum of the VACFs of the velocity components for each atom, or the mean of the VACFs? (I'm pretty sure it's the sum, but I've seen the mean written in a few places.)&lt;/li&gt;&#xA;&lt;li&gt;This is the question that is least clear to me. Where does the gap between frames, &lt;span class=&quot;math-container&quot;&gt;$k\Delta t$&lt;/span&gt;, enter the picture when calculating the VACF?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;There is a very good outline of how to do this mathematically in this &lt;a href=&quot;https://physics.stackexchange.com/questions/282734/phonon-density-of-states-from-velocity-autocorrelation-function&quot;&gt;Physics SE question&lt;/a&gt;. What I am hoping for is something more like an algorithm or an answer written in pseudo-code.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-07-09T11:55:42.967" Title="How exactly does one compute the vibrational density of states from the output of a molecular dynamics simulation?" Tags="|molecular-dynamics|spectroscopy|correlation-functions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2284" PostTypeId="2" ParentId="1563" CreationDate="2020-09-15T22:32:16.633" Score="3" Body="&lt;p&gt;&lt;strong&gt;Translation diffusion coefficient&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$D_{t}$&lt;/span&gt; may be calculated by linear fitting of the MSD of center of mass of a molecule:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$MSD(\tau)=&amp;lt;(\textbf{r}(t+\tau)-\textbf{r}(t))^{2}&amp;gt;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D_{t}=\frac{MSD(\tau)}{6\tau}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the lag time between the two positions. One should also be aware of the artifacts from the periodic boundary conditions (is they are imposed).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Rotational diffusion coefficient&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$D_{r}$&lt;/span&gt; may be estimated through fitting of the correlation functions and estimation of the rotational correlation time &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tau=S_{R}^{2}\tau_{R_{s}}+(1-S_{R}^{2})\tau_{R_{f}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$\tau_{R_{s}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\tau_{R_{f}}$&lt;/span&gt; being the slow and fast correlation times respectively; &lt;span class=&quot;math-container&quot;&gt;$S_{R}^{2}$&lt;/span&gt; is a parameter in fitting of the correlation function. The &lt;span class=&quot;math-container&quot;&gt;$D_{r}$&lt;/span&gt; acquires following form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D_{r}=\frac{1}{6\tau}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Examples of these calculations can be found here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.jpcb.7b08785&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/jp0761564&quot; rel=&quot;nofollow noreferrer&quot;&gt;Evaluating Rotational Diffusion from Protein MD Simulations&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1338" LastActivityDate="2020-09-15T22:32:16.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2285" PostTypeId="1" AcceptedAnswerId="2297" CreationDate="2020-09-14T19:01:15.647" Score="9" ViewCount="62" Body="&lt;p&gt;I'd like to be able to recover the maximum value that any of the basis functions can take, as well as their maximum derivative. How can I do this?&lt;/p&gt;&#xA;&lt;p&gt;For context, I need it because I want to calculate the values of the variable listed in Eq. 66 from the paper by Babbush et al. [&lt;a href=&quot;https://doi.org/10.1088/1367-2630/18/3/033032&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Babbush, R.; Berry, D. W.; Kivlichan, I. D.; Wei, A. Y.; Love, P. J.; Aspuru-Guzik, A. Exponentially More Precise Quantum Simulation of Fermions in Second Quantization. &lt;em&gt;New J. Phys.&lt;/em&gt; &lt;strong&gt;2016&lt;/strong&gt;, 18 (3), 033032. DOI: &lt;a href=&quot;https://doi.org/10.1088/1367-2630/18/3/033032&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1088/1367-2630/18/3/033032&lt;/a&gt;. (Open Access)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1345" OwnerDisplayName="Pablo" LastEditorUserId="142" LastEditDate="2020-09-17T10:02:25.027" LastActivityDate="2020-09-17T10:16:24.987" Title="How can I determine the maximum value of a spin orbital and its derivative in any direction?" Tags="|quantum-chemistry|computational-chemistry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2286" PostTypeId="2" ParentId="2247" CreationDate="2020-09-16T02:03:53.283" Score="8" Body="&lt;h3&gt;Multiwfn&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt; is a QTAIM package which supports most quantum chemistry codes, seemingly focusing on non-periodic systems.  For example, from a formatted Gaussian checkpoint file it is capable of calculating cube files of properties such as the electrostatic potential or electron localization function.  These properties can then be used for many advanced uses of which I have only personally explored a few in a recent article I worked on.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Critical point analysis of electron density: Identify bonds and lone pairs which exist in a molecule&lt;/li&gt;&#xA;&lt;li&gt;Charge analysis of electron density: Identify partial oxidation states arising from polarized bonds or from charge transfer in complexes&lt;/li&gt;&#xA;&lt;li&gt;Noncovalent interaction analysis (NCI): Identify where weak interaction/bonding is occurring as well as where steric effects are taking place within the molecule&lt;/li&gt;&#xA;&lt;li&gt;Interaction Region Indicator (IRI) / Density Overlap Regions Indicator (DORI) analysis: Similar to NCI analysis but strong chemical bonding can also be visually seen.&lt;/li&gt;&#xA;&lt;li&gt;Electrostatic potential analysis: Identify local maxima and minima on an isosurface of electrostatic potential.  This allows for accurate quantification of the isosurface, compared to just visual identification.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Multiwfn was used to produce the following figure &lt;a href=&quot;https://doi.org/10.1002/anie.202004384&quot; rel=&quot;noreferrer&quot;&gt;in this article&lt;/a&gt; showing an anion-anion bond.  &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;noreferrer&quot;&gt;VMD&lt;/a&gt; was used to visualize the calculated NCI analysis from Multiwfn.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uTIV5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uTIV5.png&quot; alt=&quot;Interaction of I- interaction with I4Q-&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-12-16T05:38:37.377" LastActivityDate="2020-12-16T05:38:37.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2287" PostTypeId="2" ParentId="2248" CreationDate="2020-09-16T02:27:15.403" Score="5" Body="&lt;p&gt;Since we focusing on matter modeling I would try to provide a method a general method of actually creating these models.  As others have mentioned, you will need to deal with the problem of mismatching lattices.  This can be deal with by either directly stretching the lattice of one material to match the other and simply stacking them or we can make a model which allows for the material to be closer to its original lattice constant.&lt;/p&gt;&#xA;&lt;p&gt;One way to do this for surfaces that share the same cell shape is to find cell transformations which preserve the cell shape but result in repetitions of the cell.  This can easily be done by generating 2x2 or 3x3 cell repetitions for example, but we can also find other valid cell transformations that will work.  For example, in a FCC surface we can find cells which repeat the cell the following number of times within the same shape.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1, 3, 4, 7, 9, 12, 13, 16, 19, 21, 25, 27, 28, 31, 36, 37, 39, 43, 48, 49&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These cannot be identified visually very easily, but these cells are generally referred to as root cells in literature with various symbols.  Finding them has been automated in &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#ase.build.root_surface&quot; rel=&quot;noreferrer&quot;&gt;ASE within the build module&lt;/a&gt; and it has been generalized to all surface shapes.  This cell can then be minimally strained by stretching or compressing it to match two surfaces together.&lt;/p&gt;&#xA;&lt;p&gt;The final result is that you can match an oxide such as TiO&lt;sub&gt;2&lt;/sub&gt; to WO&lt;sub&gt;3&lt;/sub&gt; for example if both surfaces share the same cell shape.  One surface will need to be slightly strained (typically the overlayer) but this can be minimized.  It may be that some strain is favorable as well, and this can be modeled in the same way.  This avoids a strain that is only applied in one direction which may be unphysical.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-16T02:27:15.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2288" PostTypeId="1" AcceptedAnswerId="2290" CreationDate="2020-09-16T09:22:50.560" Score="9" ViewCount="1389" Body="&lt;p&gt;I have two different crystal structure and I want to create a heterostructure but the problem is that the shape of their unit cell is different. I know how to combine them if their unit cell are same. Is there anyone who can tell me how to do that? I am a complete beginner in this field. Thank you very much!&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2020-09-16T18:00:30.577" LastActivityDate="2021-04-23T06:00:56.187" Title="Creating a heterostructure in VESTA" Tags="|crystal-structure|materials-design|vesta|heterostructures|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2289" PostTypeId="2" ParentId="2288" CreationDate="2020-09-16T10:36:08.560" Score="1" Body="&lt;p&gt;Make a supercell of both the unit cells, so that they fit on top of each other.&lt;/p&gt;&#xA;" OwnerUserId="1341" LastActivityDate="2020-09-16T10:36:08.560" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2290" PostTypeId="2" ParentId="2288" CreationDate="2020-09-16T11:11:05.983" Score="8" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Since the constituent monolayers have generally differing lattice constants, special care is needed in the construction of the atomic models in such a way that the strain is minimized.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Let us denote the primitive cell basis vectors of a hexagonal 2D material &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; as {&lt;span class=&quot;math-container&quot;&gt;$a_i$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$b_i$&lt;/span&gt;}. The supercell basis vector may be constructed as &lt;span class=&quot;math-container&quot;&gt;$n_ia_i$&lt;/span&gt;+&lt;span class=&quot;math-container&quot;&gt;$m_ib_i$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$n_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt; are integers. The second basis vector is always oriented at&#xA;a &lt;span class=&quot;math-container&quot;&gt;$120^\circ$&lt;/span&gt; angle (Keep &lt;span class=&quot;math-container&quot;&gt;$\alpha=\beta=90^\circ$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma=120^\circ$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;We then search for a set of integers such that the&#xA;magnitude of the supercell basis vectors in materials &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; approximately match:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\boxed{|n_ia_i + m_ib_i| \approx |n_j a_j + m_j b_j |}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In practice, we choose the smallest supercell for which the strain is less than &lt;span class=&quot;math-container&quot;&gt;$2\%$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Example: MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;/MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; heterostructure.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GxDkp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GxDkp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Ref: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.88.085318&quot; rel=&quot;noreferrer&quot;&gt;Phys.Rev.B 88, 085318&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In particular, if you want to stack a monolayer with cubic lattice (&lt;span class=&quot;math-container&quot;&gt;$a_i,b_i, \alpha=\beta=\gamma=90^\circ$&lt;/span&gt;) on a hexagonal lattice (&lt;span class=&quot;math-container&quot;&gt;$a_i,b_i, \alpha=\beta=90^\circ, \gamma=120^\circ$&lt;/span&gt;), you can first transform the hexagonal lattice (&lt;span class=&quot;math-container&quot;&gt;$a_j,b_j$&lt;/span&gt;) into a rectangular lattice (&lt;span class=&quot;math-container&quot;&gt;$a_k,b_k, \alpha=\beta=\gamma=90^\circ$&lt;/span&gt;) with rotation matrix &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; in VESTA:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{bmatrix} 1 &amp;amp; 1 &amp;amp; 0 \\ 0 &amp;amp; 2 &amp;amp; 0 \\ 0 &amp;amp; 0 &amp;amp; 1 \end{bmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and then use the following equations to find matched lattice constants:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\boxed{|n_i a_i| \approx |n_k a_k| \quad |m_i b_i| \approx |m_k b_k| }$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-16T12:55:50.727" LastActivityDate="2020-09-16T12:55:50.727" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2291" PostTypeId="2" ParentId="2078" CreationDate="2020-09-16T15:59:55.863" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I am looking to compare conformers of the same molecule, so no changes in number of atoms or charge.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://zhanglab.ccmb.med.umich.edu/TM-align/&quot; rel=&quot;noreferrer&quot;&gt;TM-align&lt;/a&gt;  to perform rigid-body structural alignment and to identify the &lt;span class=&quot;math-container&quot;&gt;$RMSD$&lt;/span&gt; between two structures.&lt;/p&gt;&#xA;&lt;p&gt;If I understand your problem correctly, you have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; conformers of the same molecule.&#xA;And you need to identify structural similarity between them.&lt;/p&gt;&#xA;&lt;p&gt;So, choose one of the conformers as a reference (an arbitrary one) and align all the other &lt;span class=&quot;math-container&quot;&gt;$(N-1)$&lt;/span&gt; onto this reference using TM-align. TM-align will output the &lt;span class=&quot;math-container&quot;&gt;$RMSD$&lt;/span&gt; values for each such alignment and also the corresponding spatial transform (and the &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.20264&quot; rel=&quot;noreferrer&quot;&gt;TM-score&lt;/a&gt; as well).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Case 1:&lt;/strong&gt; your conformers have different conformations (e.g., different values of dihedrals of the backbones), then the &lt;span class=&quot;math-container&quot;&gt;$RMSD$&lt;/span&gt; produced by TM-align will reflect this difference.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Case 2:&lt;/strong&gt; In case your conformers have the same conformations (i.e., same backbone dihedrals) and differ only in their spatial positions. Then you may record the spatial transforms produced by TM-align. After that, you may pipeline these spatial transforms to another software --&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://team.inria.fr/nano-d/software/rigidrmsd/&quot; rel=&quot;noreferrer&quot;&gt;RigidRMSD&lt;/a&gt;  performs calculation of the &lt;span class=&quot;math-container&quot;&gt;$RMSD$&lt;/span&gt; between two structures without performing spatial transforms! (this is achieved by formulating the problem in terms of the inertia tensor -- see more details in the corresponding publication: &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.23569&quot; rel=&quot;noreferrer&quot;&gt;Rapid determination of RMSDs corresponding to macromolecular rigid body motions&lt;/a&gt; )&lt;/p&gt;&#xA;&lt;p&gt;Thus, you get the &lt;span class=&quot;math-container&quot;&gt;$RMSD$&lt;/span&gt; values that correspond to spatial transforms.&lt;/p&gt;&#xA;" OwnerUserId="1338" LastActivityDate="2020-09-16T15:59:55.863" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2292" PostTypeId="2" ParentId="901" CreationDate="2020-09-16T16:04:49.090" Score="8" Body="&lt;h2&gt;How to test bond order methods for chemical consistency&lt;/h2&gt;&#xA;&lt;p&gt;Some of the bond order methods that claim to work do not give consistent results across different SZ values of a spin multiplet or different levels of theory (i.e., basis sets and exchange-correlation functionals). Consequently, there have been several published methods claimed to compute bond orders that do not work. Tests of this kind were performed in the article referenced below for the oxygen molecule in different spin states (singlet, triplet, and quintet) at different bond lengths and for different exchange-correlation approaches (e.g., DFT, CCSD, SAC-CI) and basis sets. For a fixed bond length and spin multiplet (e.g., triplet spin state at 200 pm bond length), the SZ=S and SZ=0 molecules are almost energy degenerate (except for a tiny spin-orbit coupling energy), have nearly identical electron density distributions, and therefore should have similar computed bond orders. However, many of the existing bond order methods fail this simple test for chemical consistency, because they give huge differences (1.5-2 bonds difference in some cases) between nearly chemical equivalent states.&lt;/p&gt;&#xA;&lt;p&gt;see this article (open access):  T. A. Manz, “Introducing DDEC6 atomic population analysis: part 3. Comprehensive method to compute bond orders,” RSC Advances, 7 (2017) 45552-45581 (open access) &lt;a href=&quot;https://doi.org/10.1039/c7ra07400j&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1039/c7ra07400j&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Additionally, one should require the bond order to work well for both molecular and periodic materials, including materials with localized bonding electrons (e.g., insulators or small molecules) as well as ones with highly delocalized bonding electrons (e.g., metallic conductors). A new bond order definition satisfying those properties was introduced in the article cited above.&lt;/p&gt;&#xA;&lt;p&gt;As another test of bond order definitions, one could start with the smallest molecules (i.e., diatomic molecules) and ask for which bond order definitions have worked well enough to compute bond orders for a large number of diatomic bond orders. Only one quantum-mechanically computed bond order definition has ever been applied in a published systematic study of bond orders for a large number of diatomic molecules. See the article below:&lt;/p&gt;&#xA;&lt;p&gt;T. Chen and T. A. Manz, “Bond orders of the diatomic molecules,” RSC Advances, 9 (2019) 17072-17092 (open access) &lt;a href=&quot;https://doi.org/10.1039/c9ra00974d&quot; rel=&quot;noreferrer&quot;&gt;DOI:10.1039/c9ra00974d&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1342" LastActivityDate="2020-09-16T16:04:49.090" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2293" PostTypeId="2" ParentId="2280" CreationDate="2020-09-16T16:44:00.897" Score="12" Body="&lt;h3&gt;QuantumVITAS&lt;/h3&gt;&#xA;&lt;p&gt;As I understand, OP's requirements are&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Do basic calculations using DFT&lt;/li&gt;&#xA;&lt;li&gt;Prefer open source software which is easy to use&lt;/li&gt;&#xA;&lt;li&gt;Interested in DFT only as a tool to calculate properties of materials&lt;/li&gt;&#xA;&lt;li&gt;Not interested in learning details of DFT/software developing&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Since the OP is already aware of Quantum ESPRESSO and is interested only in calculating basic properties of materials using an opensource easy to use software I will introduce a new GUI for Quantum ESPRESSO named &lt;a href=&quot;https://www.quantumvitas.org/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;QuantumVITAS&lt;/strong&gt;&lt;/a&gt; (Quantum Visualization Interacting Toolkit for Ab-initio Simulations). It comes bundled with Quantum Espresso engine and pseudopotential libraries and works out of the box in Windows, Linux and Mac OS.&lt;/p&gt;&#xA;&lt;p&gt;It is capable of doing&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Magnetism and spin orbital coupling (SOC)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;DFT+U&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Hybrid functionals&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Van der Waals corrections&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Structural optimization/relaxation (OPT)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Density of states (DOS)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Band structure (including spin polarized and SOC)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Molecular dynamics (Born–Oppenheimer MD)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Time-dependent density-functional theory (TDDFT)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Phonon (gamma point, DOS, dispersion, raman, dielectric constant)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;NEB (Nudged Elastic Band) for transition energy barrier calculation&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Projection to atomic orbitals (to each atom or to each element, also in the spin polarized case and SOC)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5N0CC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5N0CC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;WARNING : The tool should not be used as a black box and be aware about &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1557/88&quot;&gt;pitfalls&lt;/a&gt; awaiting you!.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="5" LastEditDate="2020-09-20T16:16:26.197" LastActivityDate="2020-09-20T16:16:26.197" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2294" PostTypeId="2" ParentId="1439" CreationDate="2020-09-16T19:28:44.370" Score="10" Body="&lt;h2&gt;Density-Derived Electrostatic and Chemical approaches&lt;/h2&gt;&#xA;&lt;p&gt;Net atomic charges have two primary applications (dual use):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;to quantify charge transfer between atoms in materials; this identifies cations and anions and&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;to provide an electrostatic model in classical force fields using atomistic simulations (e.g., classical molecular dynamics or Monte Carlo simulations).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The older charge partitioning methods were not optimized for this dual use. For example, charges fit specifically to the electrostatic potential (CHELP, CHELPG, Merz-Kollman, etc.) often did not give any kind of reasonable chemical description for buried atoms.&lt;/p&gt;&#xA;&lt;p&gt;The density-derived electrostatic and chemical (DDEC&lt;sup&gt;[1]&lt;/sup&gt;) methods are optimized to assign net atomic charges that give a good approximation both to the electrostatic potential surrounding the material as well as to the chemical charge states of atoms in materials. In other words, they are optimized for dual use.&lt;/p&gt;&#xA;&lt;p&gt;A key design consideration in the DDEC family of methods is to create methods that work across an extremely broad range of material types including molecules, ions, nano-structured materials, metals, insulators, dense and porous solids, organometallics, and polymers for all chemical elements of atomic number 1 to 108.&lt;/p&gt;&#xA;&lt;p&gt;Another key design consideration is that iterative processes to compute DDEC net atomic charges, atomic spin moments, and other atom-in-material properties should be rapid, robust, and converge to unique solutions. Several generations of improvements of the DDEC methods have been published. Unfortunately, there were some problems with the earliest DDEC approaches (e.g., DDEC1, DDEC2, and DDEC3) that caused non-unique convergence ('runaway charges') in some materials. The latest generation (DDEC6&lt;sup&gt;[2-5]&lt;/sup&gt;) fixes these convergence problems.&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;density-derived&amp;quot; refers to atom-in-material properties (e.g., net atomic charges, atomic spin moments, bond orders, atomic multipoles, etc.) that are computed as functionals of the electron and spin density distributions. One can also imagine additional properties that are computed from the first-order density matrix or molecular orbitals that are not functionals of the electron and spin density distributions. These &amp;quot;orbital-derived&amp;quot; properties include spdfg populations of atoms in materials, projected density of states plots, bond order components assigned to individual orbitals, etc. Together, these &amp;quot;density-derived&amp;quot; and &amp;quot;orbital-derived&amp;quot; properties form the Standard Atoms in Materials Method (SAMM). In other words, recent generation DDEC (e.g., DDEC6) method is the &amp;quot;density-derived&amp;quot; part of the SAMM.&lt;/p&gt;&#xA;&lt;p&gt;A key design consideration of the SAMM approach is that all of the various component methods should work together to provide a chemically consistent description of atoms in materials. This means the net atomic charges, atomic spin moments, atomic multipoles, bond orders, bond order components, spdfg populations, polarizabilities, dispersion coefficients, and projected density of states plots should be chemically compatible with each other. For example, when summing the individual populations of the spdfg subshell populations for spin-up and spin-down electrons in a magnetic material, these yield the prior-computed net atomic charges and atomic spin moments and have chemical consistency with the computed bond orders. Moreover, the &amp;quot;orbital-derived&amp;quot; properties from the SAMM method are designed to be chemically consistent with &amp;quot;density-derived&amp;quot; properties. For example, integrating the projected density of states (PDOS) curves for a particular atom in a material regenerates the prior-computed net atomic charges, atomic spin moments, and bond orders.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Manz, T. A.; Sholl, D. S. &lt;a href=&quot;https://doi.org/10.1021/ct100125x&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemically Meaningful Atomic Charges That Reproduce the Electrostatic Potential in Periodic and Nonperiodic Materials.&lt;/a&gt; &lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; &lt;strong&gt;2010,&lt;/strong&gt; &lt;em&gt;6&lt;/em&gt; (8), 2455–2468. DOI: 10.1021/ct100125x.&lt;/li&gt;&#xA;&lt;li&gt;Manz, T. A.; Limas, N. G. &lt;a href=&quot;https://doi.org/10.1039/c6ra04656h&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introducing DDEC6 atomic population analysis: part 1. Charge partitioning theory and methodology.&lt;/a&gt; &lt;em&gt;RSC Adv.&lt;/em&gt; &lt;strong&gt;2016,&lt;/strong&gt; &lt;em&gt;6&lt;/em&gt; (53), 47771–47801. DOI: 10.1039/c6ra04656h.&lt;/li&gt;&#xA;&lt;li&gt;Limas, N. G.; Manz, T. A. &lt;a href=&quot;https://doi.org/10.1039/c6ra05507a&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introducing DDEC6 atomic population analysis: part 2. Computed results for a wide range of periodic and nonperiodic materials.&lt;/a&gt; &lt;em&gt;RSC Adv.&lt;/em&gt; &lt;strong&gt;2016,&lt;/strong&gt; &lt;em&gt;6&lt;/em&gt; (51), 45727–45747. DOI: 10.1039/c6ra05507a.&lt;/li&gt;&#xA;&lt;li&gt;Manz, T. A. &lt;a href=&quot;https://doi.org/10.1039/c7ra07400j&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introducing DDEC6 atomic population analysis: part 3. Comprehensive method to compute bond orders.&lt;/a&gt; &lt;em&gt;RSC Adv.&lt;/em&gt; &lt;strong&gt;2017,&lt;/strong&gt; &lt;em&gt;7&lt;/em&gt; (72), 45552–45581. DOI: 10.1039/c7ra07400j.&lt;/li&gt;&#xA;&lt;li&gt;Limas, N. G.; Manz, T. A. &lt;a href=&quot;https://doi.org/10.1039/c7ra11829e&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introducing DDEC6 atomic population analysis: part 4. Efficient parallel computation of net atomic charges, atomic spin moments, bond orders, and more.&lt;/a&gt; &lt;em&gt;RSC Adv.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;8&lt;/em&gt; (5), 2678–2707. DOI: 10.1039/c7ra11829e.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1342" LastEditorUserId="7" LastEditDate="2022-03-22T14:25:00.363" LastActivityDate="2022-03-22T14:25:00.363" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2295" PostTypeId="2" ParentId="2230" CreationDate="2020-09-17T01:27:41.110" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What are the available methods for the calculation of reference interaction energies of layered materials?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I assume that the meaning of the &amp;quot;reference interaction energy&amp;quot; is the interlayer binding energy between layers. Then you can use &lt;strong&gt;SCAN+rVV10 method&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Reference paper: &lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041005&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. X 6, 041005&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Description: The resultant SCAN+rVV10 is the only vdW density functional to date that yields excellent interlayer binding energies and spacings, as well as intralayer&#xA;lattice constants in 28 layered materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Where are they implemented?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;VASP5.4.4 and more recently released versions.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In detail, you can follow &lt;a href=&quot;https://sites.google.com/site/haoweipeng/softwares&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt; to investigate your system.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="697" LastEditDate="2020-09-17T14:33:08.660" LastActivityDate="2020-09-17T14:33:08.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2296" PostTypeId="1" CreationDate="2020-09-17T07:07:56.210" Score="11" ViewCount="179" Body="&lt;p&gt;Let's say I optimized geometry with PBE+D3, does it matter if I make single point bandstructure calculation with just PBE or PBE+D3 since D3 is a additive method.&lt;/p&gt;&#xA;" OwnerUserId="984" LastActivityDate="2020-09-17T19:50:10.237" Title="Band structure with additive dispersion methods" Tags="|density-functional-theory|dispersion-correction|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2297" PostTypeId="2" ParentId="2285" CreationDate="2020-09-17T10:16:24.987" Score="3" Body="&lt;p&gt;The two-electron integrals &lt;span class=&quot;math-container&quot;&gt;$(\alpha \beta | \gamma \delta )$&lt;/span&gt; are typically evaluated in terms of the atomic orbital (AO) basis functions, since in a Gaussian basis set these can be done analytically. Figuring out the maximal value of the AO and its derivatives is trivial, since you know the analytic form of the function, which is highly monotonic.&lt;/p&gt;&#xA;&lt;p&gt;However, for calculations including electron correlation i.e. quantum computing applications and post-Hartree-Fock methods you actually need the integrals in the molecular orbital (MO) basis, which are obtained from the AO integrals with the transform&#xA;&lt;span class=&quot;math-container&quot;&gt;$(ij|kl)=\sum_{\alpha\beta\gamma\delta} C_{\alpha i} C_{\beta j} C_{\gamma k} C_{\delta l} (\alpha \beta | \gamma \delta )$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; are the MO coefficients. (In practice, the transform is carried out as four consecutive one-index transforms that can be expressed as matrix-matrix products, since this scales as &lt;span class=&quot;math-container&quot;&gt;$N^5$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$N^8$&lt;/span&gt;.)&lt;/p&gt;&#xA;&lt;p&gt;Now, the question is: how to determine the maximal value of a MO &lt;span class=&quot;math-container&quot;&gt;$\phi_i({\bf r}) = \sum_\alpha C_{\alpha i} \chi_{\alpha} ({\bf r})$&lt;/span&gt; and its derivative, where &lt;span class=&quot;math-container&quot;&gt;$\chi_\alpha$&lt;/span&gt; is the AO. This is a &lt;a href=&quot;https://en.wikipedia.org/wiki/Global_optimization&quot; rel=&quot;nofollow noreferrer&quot;&gt;global optimization problem&lt;/a&gt;, for which there is no simple solution. You essentially need to sample over all of &lt;span class=&quot;math-container&quot;&gt;${\bf r}$&lt;/span&gt; to find where the minima lie, and you still don't have a guarantee of finding the real minimum.&lt;/p&gt;&#xA;&lt;p&gt;There are clever schemes, though, to directly estimate the value of the AO two-electron integral; this allows avoiding explicit computation of AO small integrals.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-17T10:16:24.987" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2298" PostTypeId="2" ParentId="2296" CreationDate="2020-09-17T12:51:23.287" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;It doesn't matter. The self-consistent calculation will use the Hamiltonian constructed from the relaxed structure, in which the D3 has been applied and should not be considered again.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Take bilayer MoSe2 as an example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CoOFV.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CoOFV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This structure is optimized with PBE+D3 using the VASP package. With this relaxed structure, I have calculated the band structure with and without the consideration of D3 in the INCAR file. One can not see any difference between the two band structures.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XPOxk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XPOxk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-17T19:50:10.237" LastActivityDate="2020-09-17T19:50:10.237" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2299" PostTypeId="2" ParentId="2296" CreationDate="2020-09-17T14:30:59.320" Score="5" Body="&lt;p&gt;A PBE vs PBE+D3 calculation will have the same band structure if the same geometry is used.  If the geometry is optimized, however, they can differ but the D3 correction does not directly influence the band structure just the geometry.&lt;/p&gt;&#xA;&lt;p&gt;You can validate this method by considering that these corrections can often be done by an external step such as combining VASP with D3 using ASE rather than VASP's internal tools.  To VASP, nothing about these calculations is different, the correction happens afterward.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-17T14:30:59.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2300" PostTypeId="1" CreationDate="2020-09-17T16:02:18.783" Score="10" ViewCount="593" Body="&lt;p&gt;I did an AIMD run in VASP using 64 cores (32 cores/node) and 250 GB of memory (125 GB/node) for 5 ps (1 fs time step). The calculation took 12.6 hours to complete. CPU efficiency was 99.7% and memory efficiency was 42%.&lt;/p&gt;&#xA;&lt;p&gt;So I estimated for a 50 ps run with the exact same parameters I would need approximately 126 hours. So I requested 6 days to be safe. Interestingly after 6 days the run timed out and completed only ~22 ps when I checked the output files. CPU efficiency was 98.9% and memory efficiency was 158%!&lt;/p&gt;&#xA;&lt;p&gt;I don't understand why the memory is getting overloaded and then I guess &amp;quot;slowing&amp;quot; down the calculation once it gets to about 20 ps? Perhaps I'm missing something. Maybe I need more memory and cores? Or can I get around this by simply splitting the 50 ps into individual 10 ps runs?&lt;/p&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2020-09-17T16:53:54.293" LastActivityDate="2020-10-07T10:52:56.930" Title="Choosing RAM, CPU time, # of cores, and other parameters for an MD run" Tags="|molecular-dynamics|vasp|high-performance-computing|aimd|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2301" PostTypeId="1" CreationDate="2020-09-17T16:15:23.743" Score="7" ViewCount="101" Body="&lt;p&gt;I carried out a simple single-point PBE calculation on two different graphene monolayers (only &lt;code&gt;c&lt;/code&gt; is different) using VASP with 12x12x1 k-grid.&lt;/p&gt;&#xA;&lt;p&gt;Geometry 1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;graphene&#xA;1.0&#xA;1.22800000 -2.12695839  0.00000000&#xA;1.22800000  2.12695839  0.00000000&#xA;0.00000000  0.00000000  25&#xA;2&#xA;direct&#xA;   0.00000000  0.00000000  0.25000000&#xA;   0.33333333  0.66666667  0.25000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Geometry 2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;graphene&#xA;1.0&#xA;1.22800000 -2.12695839  0.00000000&#xA;1.22800000  2.12695839  0.00000000&#xA;0.00000000  0.00000000  100&#xA;2&#xA;direct&#xA;   0.00000000  0.00000000  0.25000000&#xA;   0.33333333  0.66666667  0.25000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get two different energy results and a different number of maximum number of plane waves from the output. Why? Since they don't have periodicity on the z-direction how this effects?&lt;/p&gt;&#xA;&lt;p&gt;Is there a protocol to follow for 2D materials calculations in VASP? I don't know what I am doing wrong.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-09-17T16:51:40.253" LastActivityDate="2020-09-18T09:13:20.737" Title="Different energies for two different geometries where only the monolayer c lattice constant is different?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="2302" PostTypeId="2" ParentId="2247" CreationDate="2020-09-17T17:23:39.393" Score="11" Body="&lt;h3&gt;Critic2&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/aoterodelaroza/critic2&quot; rel=&quot;noreferrer&quot;&gt;critic2&lt;/a&gt; is a very nice QTAIM code that supports interfaces to many codes, including also periodic systems: &amp;quot;WIEN2k, elk, PI, Quantum ESPRESSO, abinit, VASP, DFTB+, Gaussian, psi4, siesta, and to any other program capable of writing the scalar field of interest to a grid&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;From personal experience, critic2 is very straight forward to compile and the developer is responsive to any issues, so definitely recommended!&lt;/p&gt;&#xA;&lt;p&gt;Purely to calculate Bader charge basins, the &lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;noreferrer&quot;&gt;Henkelman Bader tool&lt;/a&gt; is also very fast and reliable for specifically gridded data (VASP CHGCAR or Gaussian CUBE).&lt;/p&gt;&#xA;&lt;p&gt;There is also a newer tool called &lt;a href=&quot;https://github.com/LLNL/TopoMS&quot; rel=&quot;noreferrer&quot;&gt;TopoMS&lt;/a&gt; that promises improved robustness and has some compelling case-studies in its paper.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;QTAIM&amp;quot; itself is a broad topic, for example I'm not aware which tools currently available might be able to access information about, for example, bond bundles or other features.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="5" LastEditDate="2020-12-16T05:38:23.083" LastActivityDate="2020-12-16T05:38:23.083" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2303" PostTypeId="2" ParentId="2" CreationDate="2020-09-17T17:32:44.793" Score="12" Body="&lt;p&gt;Since this is a very active research topic the answer here might change regularly. Just within the last few months we've seen updates to the SCAN functional in the form of &lt;a href=&quot;https://arxiv.org/abs/2008.03374&quot; rel=&quot;noreferrer&quot;&gt;r2SCAN&lt;/a&gt; and the de-orbitalized &lt;a href=&quot;https://arxiv.org/abs/2008.12420&quot; rel=&quot;noreferrer&quot;&gt;r2SCAN-L&lt;/a&gt;. These are both functionals that attempt to satisfy all known physical constraints that can be &lt;em&gt;in-principle&lt;/em&gt; satisfied by a semi-local functional, although it should be noted that r2SCAN relaxes one of these constraints (the fourth-order gradient expansion) for the benefit of numerical accuracy. To achieve a &amp;quot;universal&amp;quot; functional, these exact constraints have to be satisfied, and SCAN is the closest we have at least in terms of a semi-local functional.&lt;/p&gt;&#xA;&lt;p&gt;However, there are limits to how good a semi-local functional can be even in principle, and ultimately non-local information is required for a true &amp;quot;universal functional.&amp;quot; This is what has made the hybrid functionals so popular. In the solid-state community, HSE06 has become a de facto standard, but its universality is limited by including a fixed amount of Hartree-Fock exchange, when the true value of mixing is expected to vary according to the material's dielectric properties. There have been some &amp;quot;dielectric-dependent&amp;quot; functionals developed, as well as schemes to use HSE but to optimize the amount of mixing, and this is also an active research topic.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="5" LastEditDate="2020-09-17T17:54:47.963" LastActivityDate="2020-09-17T17:54:47.963" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2305" PostTypeId="2" ParentId="2280" CreationDate="2020-09-17T23:46:17.553" Score="3" Body="&lt;h3&gt;Questaal&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Website: &lt;a href=&quot;https://www.questaal.org/about/questaal/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.questaal.org/about/questaal/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Description: &lt;strong&gt;Questaal&lt;/strong&gt; is the most advanced open-source DFT package to study strong correlation physics in 3D materials. In detail, &lt;strong&gt;Questaal&lt;/strong&gt; implements a QSGW+DMFT module to that.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When localized electronic orbitals (&lt;span class=&quot;math-container&quot;&gt;$d-$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$f-$&lt;/span&gt; type) participate in the states near the Fermi level, the effect of electronic correlation can not be included as a small perturbation (RPA) and more accurate methods have to be invoked. The &lt;strong&gt;Questaal&lt;/strong&gt; code has been interfaced with the Continuous-Time Quantum Monte Carlo solver developed by K. Haule and coworkers. This couples the QSGW description of the lattice with state-of-the-art Dynamical Mean Field Theory approaches. This code requires that Haule’s CTQMC be installed. The interface to that code is [lmfdmft].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Download page:&lt;a href=&quot;https://www.questaal.org/get/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.questaal.org/get/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Published papers with Questaal: &lt;a href=&quot;https://www.questaal.org/news/categories/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.questaal.org/news/categories/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-09-20T16:15:51.557" LastActivityDate="2020-09-20T16:15:51.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2306" PostTypeId="1" AcceptedAnswerId="2307" CreationDate="2020-09-18T02:59:15.083" Score="9" ViewCount="506" Body="&lt;p&gt;In the paper &lt;a href=&quot;https://doi.org/10.1238/Physica.Topical.083a00083&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;High Precision Theory of Atomic Helium&amp;quot;&lt;/a&gt;, Drake lists the then best-known ground state energy of the Schrödinger equation for helium to 22 digits as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\lambda_0 \approx -2.90372437703411959382$$&lt;/span&gt;&#xA;in atomic units.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1103/PhysRevA.66.024501&quot; rel=&quot;noreferrer&quot;&gt;Korobov&lt;/a&gt; gives the ground state to 24 digits as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\lambda_0 \approx -2.903724377034119598311159.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In 2007, we get ~45 digits with &lt;a href=&quot;https://doi.org/10.1063/1.2801981&quot; rel=&quot;noreferrer&quot;&gt;Nakashima and Nakasuji's&lt;/a&gt; calculation of:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\lambda_0 = −2.90372437703411959831115924519440444669690537.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am looking for the highest precision calculation of the helium ground state, but with Nakashima and Nakasuji's paper, the trail goes cold. The closest citing article is again from &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.98.012510&quot; rel=&quot;noreferrer&quot;&gt;Korobov&lt;/a&gt;, which suggests perhaps not all of Nakasuji's digits are correct.&lt;/p&gt;&#xA;&lt;p&gt;What is the most accurate computation of the helium ground state?&lt;/p&gt;&#xA;&lt;p&gt;I am also interested in the first excited state.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1103/PhysRevA.98.012510&quot; rel=&quot;noreferrer&quot;&gt;Korobov&lt;/a&gt; lists the first excited state at &lt;span class=&quot;math-container&quot;&gt;$\lambda_1 \approx -2.145974046054417415805028975461921$&lt;/span&gt;, but is this the best calculation?&lt;/p&gt;&#xA;" OwnerUserId="1086" LastEditorUserId="5" LastEditDate="2020-09-18T15:58:23.610" LastActivityDate="2020-09-18T15:58:23.610" Title="High precision helium energy" Tags="|high-performance-computing|computational-chemistry|quantum-chemistry|atomic-physics|high-precision|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2307" PostTypeId="2" ParentId="2306" CreationDate="2020-09-18T04:15:55.653" Score="12" Body="&lt;p&gt;The 2006 variational calculation by Schwartz is lower (more accurate) than Nakashima &amp;amp; Nakatsuji's 2007 energy:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2006 Schwartz:              -2.903724377034119598311159245194404446696925309838&#xA;2007 Nakashima &amp;amp; Nakatsuji: -2.90372437703411959831115924519440444669690537&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The lowest variational upper bounds ground state energies for the first 6 elements, based on the non-relativistic Schrödinger equation are given in Table 1 of &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;my paper about the carbon atom&lt;/a&gt;, as well as the relevant citations.&lt;/p&gt;&#xA;&lt;p&gt;For the first excited state you have referred to a paper by Korobov that was published in 2018, and has been cited 10 times according to Google Scholar, but none of those papers were about excited states of He, which is enough for me to conclude that no better calculation has been done since 2018 (there is only a very, very, small number of people that are interested in anything smaller than a pico-Hartree, so if anyone were do better than what was state-of-the-art in 2018 they would have cited the Korobov paper).&lt;/p&gt;&#xA;&lt;p&gt;Keep in mind that QED corrections to the Schrödinger equation have errors as big as 0.00001 in the units that you and I are using to present these numbers, so the differences between the numbers for the ground state energies that you have given by Drake (1999), Korobov (2002), Nakashima &amp;amp; Nakatsuji (2007) and the value I've given by Schwartz (2006), is of no practical relevance.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-09-18T04:15:55.653" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2308" PostTypeId="2" ParentId="2227" CreationDate="2020-09-18T05:55:37.477" Score="0" Body="&lt;p&gt;I think we can safely use &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v=p}/m$&lt;/span&gt; to evaluate the orbital magnetic dipole moment &lt;span class=&quot;math-container&quot;&gt;$-e/2m(\mathbf{r\times p})$&lt;/span&gt; within the PAW sphere, since within the PAW sphere the all-electron wave functions are subjected to the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H=\mathbf{p}^2/2m + V$&lt;/span&gt;[Phys. Rev. B 50, 17953 (1994)].&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2020-09-18T05:55:37.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2309" PostTypeId="2" ParentId="2301" CreationDate="2020-09-18T09:06:09.737" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I guess what your calculation is not done correctly.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have run the self-consistent calculation with VASP. For the first structure, I obtain the energy is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\boxed{-18.438584 (\text{eV})}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the second structure, I obtain the energy is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\boxed{-18.438713 (\text{eV})}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The energy difference between the two structures is negligible. So the first vacuum space in the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;-direction is good to obtain the converged results.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is there a protocol to follow for 2D materials calculations in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This website: &lt;a href=&quot;http://www.2dmatpedia.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.2dmatpedia.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-18T09:13:20.737" LastActivityDate="2020-09-18T09:13:20.737" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2310" PostTypeId="2" ParentId="392" CreationDate="2020-09-18T14:07:58.033" Score="7" Body="&lt;h1&gt;2001 (Taylor &lt;em&gt;et al.&lt;/em&gt;): DFT+NEGF&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Combining density functional theory (NEGF) with nonequilibrium Green's function method (NEGF),  a self-consistent first-principles technique for modeling quantum transport properties of atomic and molecular scale nanoelectronic devices under external bias potentials is reported.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Implementation packages: &lt;a href=&quot;https://docs.quantumatk.com/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumATK&lt;/a&gt;, &lt;a href=&quot;http://www.nanoacademic.ca:8080/nchannel.jsp?id=2&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nanodcal&lt;/a&gt; and &lt;a href=&quot;https://www.questaal.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Questaal&lt;/a&gt; ...&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Reference: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.63.245407&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys.Rev.B 63, 245407&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This paper has been chosen as one of &lt;a href=&quot;https://journals.aps.org/prb/50th&quot; rel=&quot;nofollow noreferrer&quot;&gt;Physical Review B 50th Anniversary Milestones:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The following is the comments:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Over the last few decades, there has been an explosion in the realm of nanotechnology, nanodevices, and nanomaterials, where anything ‘nano’ has become part of the condensed matter and materials physics lexicon. As has often been restated, this is due to the great potential for technological applications. However, this potential produced the need for a better understanding of the fundamental physics at the atomic scale not just for molecular modeling, but for device and application purposes as well. In the early 2000s, the use of density functional theory (DFT) and ab initio modeling continued to revolutionize the way we understand materials. Two outstanding PRB papers reported on the incursion of DFT into the arena of quantum electron transport properties by means of nonequilibrium Green’s functions. They helped pave the way for the advancement of device modeling at the atomistic level.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-02T13:39:51.743" LastActivityDate="2021-01-02T13:39:51.743" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2311" PostTypeId="2" ParentId="392" CreationDate="2020-09-18T15:01:40.447" Score="3" Body="&lt;h1&gt;Solving the band-gap problem at DFT level (2008)&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;To obtain the correct band-gap in semiconductor physics and materials science is very important for device applications, such as charge transport and optical absorption. It is well known that DFT with PBE exchange-correlation functional will underestimate the band-gap of semiconducting materials. Currently, some methods based on DFT have been proposed, such as hybrid functional and GW approximation. Unfortunately, these schemes are computationally prohibitive for large systems, especially when the spin-orbit coupling becomes important. How to solve the band-gap problem at the DFT level cost is the core problem of this field.  This following cited paper tries to explain the failure of conventional exchange-correlation functional from the viewpoint of the fractional charge, which can be considered as one of the most important developments in recent years.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ref: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.100.146401&quot; rel=&quot;nofollow noreferrer&quot;&gt;Localization and Delocalization Errors in Density Functional Theory and Implications for Band-Gap Prediction.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-20T13:24:43.057" LastActivityDate="2021-01-20T13:24:43.057" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2313" PostTypeId="2" ParentId="2231" CreationDate="2020-09-18T17:17:16.563" Score="2" Body="&lt;p&gt;An 8 atom structure can have a PDoS of each atom assigned to orbitals, but your question is more about does the collective PDoS of those 4 atoms which are different combinations to form anything interesting.&lt;/p&gt;&#xA;&lt;p&gt;A PDoS is useful for assigning which states come from what orbitals or atoms, so I would say that this probably depends on your particular system.  Try to plot it and see what you get, the full DoS can be seen as the collective PDoS of all atoms, so it makes sense to split these by elements, orbitals, spin, etc.  Your system will determine if anything useful can be determined.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-18T17:17:16.563" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2314" PostTypeId="1" CreationDate="2020-09-19T00:50:35.837" Score="9" ViewCount="198" Body="&lt;p&gt;I'm looking for a text for computational biology which is similar in structure to a book called &lt;em&gt;Computational Materials Science&lt;/em&gt; by June Gunn Lee.&lt;/p&gt;&#xA;&lt;p&gt;In his book, Lee discusses the theory of MD simulations and also uses examples with code from LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering if there are any MD related texts for biological applications and using NAMD or GROMACS.&lt;/p&gt;&#xA;" OwnerUserId="1353" LastEditorUserId="5" LastEditDate="2020-09-20T18:49:12.353" LastActivityDate="2020-09-20T18:49:12.353" Title="Computational biology textbook similar to &quot;Computational Materials Science&quot; by June Gunn Lee" Tags="|molecular-dynamics|reference-request|molecular-modeling|gromacs|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2315" PostTypeId="2" ParentId="2314" CreationDate="2020-09-19T03:53:32.687" Score="6" Body="&lt;p&gt;This &lt;a href=&quot;https://books.google.co.in/books/about/Computational_Biophysics.html?id=PSxVAQAAQBAJ&amp;amp;source=kp_book_description&amp;amp;redir_esc=y&quot; rel=&quot;noreferrer&quot;&gt;book&lt;/a&gt; by Klaus Schulten is detailed and explains concepts with examples from NAMD and visulaization from VMD.&lt;/p&gt;&#xA;" OwnerUserId="707" LastActivityDate="2020-09-19T03:53:32.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2316" PostTypeId="1" AcceptedAnswerId="2326" CreationDate="2020-09-19T12:43:06.237" Score="8" ViewCount="105" Body="&lt;p&gt;I've read papers in DFT studies on band gap tuning in semiconductors and the usually studied methods are either through doping or application of external strain. But it is always just one or the other. I've never come across any paper where they investigated how simultaneously varying both the amount of doping and strain affects the electronic structure of materials. Why is this so? Is there some physics-based reason for this or is it just because simultaneously varying both the amount of doping and strain might be computationally expensive?&lt;/p&gt;&#xA;" OwnerUserId="347" LastActivityDate="2020-09-21T11:36:34.897" Title="Combined effects of strain and doping on the electronic structure of semiconductors" Tags="|density-functional-theory|from-phys-se|solid-state-physics|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2317" PostTypeId="1" CreationDate="2020-09-19T20:29:18.673" Score="12" ViewCount="280" Body="&lt;p&gt;When we present our Density Functional Theory simulation results e.g. lattice parameters, stacking fault energies, band gaps, etc. to  people who are experimentalists then the very first question which they ask is about the validity of those numbers. Since the calculations are done at ~0 kelvin, they start doubting those numbers.&lt;br /&gt;&#xA;I know that in the absolute terms these numbers may not have that much meaning unless they are compared with some reference.&lt;br /&gt;&#xA;I want to know the take of Matter Modeling community on this.&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="5" LastEditDate="2020-09-19T21:12:25.053" LastActivityDate="2020-10-08T20:03:19.027" Title="How to explain Density Functional Theory results to an experimentalist?" Tags="|density-functional-theory|quantum-chemistry|quantum-mechanics|materials-design|materials-engineering|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2318" PostTypeId="1" AcceptedAnswerId="2322" CreationDate="2020-09-20T03:06:31.610" Score="9" ViewCount="323" Body="&lt;p&gt;Currently, I have to put two different materials together to form a heterostructure. I've already transformed the unit cell of material A from trigonal to cubic. Now the unit cell has a rectangular shape in a,b plane, and the other one has a square dimension. I've try my best to find the size such that to minimize the mismatch of the unit cell. For example, now one unit cell has a &lt;span class=&quot;math-container&quot;&gt;$13.614 \times 13.614$&lt;/span&gt; angstrom unit and the other one has a &lt;span class=&quot;math-container&quot;&gt;$13.326 \times 15.388$&lt;/span&gt; dimension. Can I take an average on the lattice constant in b dimension and stretch the first lattice a little bit and compress another a little bit so that I can create a heterostructure? Is it acceptable? How large will it affect the result of the DFT calculation?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="1218" LastEditDate="2020-09-20T03:22:46.843" LastActivityDate="2020-09-20T06:44:56.110" Title="acceptable range of stretching of a lattice unit cell when we do the heterostructure" Tags="|density-functional-theory|vasp|vesta|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2319" PostTypeId="2" ParentId="2280" CreationDate="2020-09-20T03:13:56.303" Score="1" Body="&lt;h3&gt;Quantum ESPRESSO&lt;/h3&gt;&#xA;&lt;p&gt;I think you should choose a code which has a lot of citations, implying that the results obtained from that code are reliable and reasonable and it can deal with various physical problems. Among DFT codes, Quantum ESPRESSO has more than 12k citations, and it could be good choice.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2020-09-20T16:17:23.197" LastActivityDate="2020-09-20T16:17:23.197" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2320" PostTypeId="1" CreationDate="2020-09-20T03:35:23.123" Score="12" ViewCount="176" Body="&lt;p&gt;I am looking for chemical potential from literature.&lt;span class=&quot;math-container&quot;&gt;$^{1,2}$&lt;/span&gt;&#xA;I compared the method and data they provided. They use the Fitted Elemental Reference Energy method via GGA+U on VASP employing PAW. The U values in these papers are a little different. As far as I understand from the papers, the chemical potential is equal to total energy of an isolated atom in a box (for example, 10x10x10). Am I right? Then I think it should be similar. However, I found that the data are somehow inconsistent. For example:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Element&lt;/th&gt;&#xA;&lt;th&gt;Paper 2 (Table 1)&lt;/th&gt;&#xA;&lt;th&gt;Paper 1 (Table V: Appendix)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Fe&lt;/td&gt;&#xA;&lt;td&gt;2.200&lt;/td&gt;&#xA;&lt;td&gt;-6.15&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Mn&lt;/td&gt;&#xA;&lt;td&gt;1.987&lt;/td&gt;&#xA;&lt;td&gt;-7.00&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Co&lt;/td&gt;&#xA;&lt;td&gt;1.987&lt;/td&gt;&#xA;&lt;td&gt;-4.75&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can anyone please explain this?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Stevanović, V., Lany, S., Zhang, X., and Zunger, A. Correcting density functional theory for accurate predictions of compound enthalpies of formation: Fitted elemental-phase reference energies&#xA;Phys. Rev. B 85, 115104 &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.85.115104&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.85.115104&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Kirklin, S., Saal, J., Meredig, B. et al. The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies. npj Comput Mater 1, 15010 (2015). &lt;a href=&quot;https://doi.org/10.1038/npjcompumats.2015.10&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/npjcompumats.2015.10&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2021-10-30T20:10:06.693" LastActivityDate="2021-10-30T20:10:06.693" Title="Inconsistent data of chemical potential from different papers" Tags="|density-functional-theory|vasp|projector-augmented-wave|reproducing-data-from-papers|" AnswerCount="0" CommentCount="11" ClosedDate="2023-02-07T03:07:05.827" ContentLicense="CC BY-SA 4.0" />
  <row Id="2321" PostTypeId="2" ParentId="2318" CreationDate="2020-09-20T03:40:47.430" Score="8" Body="&lt;p&gt;There are lots of papers about the strain engineering of two-dimensional materials. For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl2035749&quot; rel=&quot;noreferrer&quot;&gt;Strain-Engineering of Band Gaps in Piezoelectric Boron Nitride Nanoribbons&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp501734s&quot; rel=&quot;noreferrer&quot;&gt;Tuning Electronic and Magnetic Properties of Early Transition-Metal Dichalcogenides via Tensile Strain&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The tensile strain even up to &lt;span class=&quot;math-container&quot;&gt;$10\%$&lt;/span&gt; is considered.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I take an average on the lattice constant in b dimension and stretch the first lattice a little bit and compress another a little bit so that I can create a heterostructure? Is it acceptable?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The answer is OK. You can take that as your initial structure and relax to find the optimized lattice constant.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How large will it affect the result of the DFT calculation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There are many things affected by strain, such as the band-gap, carrier mobility, and band alignment. Of course, how large the influence depends on the range of applied strain.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-20T03:59:43.303" LastActivityDate="2020-09-20T03:59:43.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2322" PostTypeId="2" ParentId="2318" CreationDate="2020-09-20T06:44:56.110" Score="10" Body="&lt;p&gt;I would like to add to Jack's answer that beyond the raw numbers of what an acceptable amount of strain may be, it can also be important to consider the physical situation of interest when matching two different compounds in a heterostructure. This is particularly relevant for your point about &amp;quot;taking the average&amp;quot; of the lattice parameters of the two compounds that you are matching. Situations that may occur in which you don't want to take the average include:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Epitaxial strain. When you are looking into experiments that grow a thin film on a substrate, in the experiment the lattice parameter of the substrate is not affected because the material is almost in its bulk configuration while it is mostly the thin film that completely adapts to the substrate lattice parameter. When simulating such a situation, you typically want to only change the lattice parameter of the thin film part of the heterostructure, not take the average of the two.&lt;/li&gt;&#xA;&lt;li&gt;Bulk modulus. Even when the experimental situation you are trying to model is one in which there is no clear substrate-film distinction, different materials respond differently to compression/extension, as characterized by the bulk modulus. Rather than averaging the lattice parameters, a better approach may be to take the respective bulk moduli into account, to decide which material may be amenable to a larger compression/extension.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-20T06:44:56.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2323" PostTypeId="1" CreationDate="2020-09-20T09:15:16.457" Score="10" ViewCount="158" Body="&lt;p&gt;What's the best way for parallelization in VASP for periodic systems? In the documentation, it mostly explains it for the local computer and molecule calculation. Apparently, these explanations don't help for periodic system calculations using supercomputer systems.&lt;/p&gt;&#xA;&lt;p&gt;Let's say I want to do an MP2/GW/RPA calculation and I have access to 1000 cores (10 nodes each 100 cores). What would be the best way for me to make a good parallelization and have a fast result?&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2020-11-29T02:28:48.967" LastActivityDate="2020-11-29T02:28:48.967" Title="I have access to 1000 cores across 10 nodes, what would be the best way to prallelize an MP2, GW, or RPA calculation for a periodic system in VASP?" Tags="|density-functional-theory|vasp|computational-chemistry|high-performance-computing|" AnswerCount="0" CommentCount="9" ClosedDate="2020-12-17T04:24:47.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="2324" PostTypeId="2" ParentId="392" CreationDate="2020-09-20T09:59:27.757" Score="6" Body="&lt;h1&gt;2014 (Gagliardi): MPCDFT&lt;/h1&gt;&#xA;&lt;p&gt;Multiconfiguration Pair-Density Functional Theory (MC-PDFT) is a theoretical framework that combines multiconfigurational wave functions with a generalization of density functional theory.&#xA;As the reference wavefunction is multiconfigurational rather than being a single Slater determinant, it has the advantage that it can describe strongly correlated systems, bond dissociations, and electronic excitations. This requires a new type of density functionals (functionals of the total&#xA;density, its gradient, and the on-top pair density) that can be obtained by translating conventional density functionals of the spin densities. As the on-top pair density is an element of the two-particle density matrix, this goes beyond the Hohenberg−Kohn theorem that refers only to the one-particle density.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;G. Li Manni, R. K. Carlson, S. Luo, D. Ma, J. Olsen, D. G. Truhlar, L. Gagliardi, &lt;a href=&quot;https://dx.doi.org/10.1021/ct500483t&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiconfiguration pair-density functional theory.&lt;/a&gt; J. Chem. Theory Comput. 10, 3669–3680 (2014).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;L. Gagliardi, D. G. Truhlar, G. L. Manni, R. K. Carlson, C. E. Hoyer, J. L. Bao, &lt;a href=&quot;https://dx.doi.org/10.1021/acs.accounts.6b00471&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiconfiguration pair-density functional theory: A new way to treat strongly correlated systems.&lt;/a&gt; Acc. Chem. Res. 50, 66–73 (2017).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastEditorUserId="5" LastEditDate="2020-12-03T19:27:58.000" LastActivityDate="2020-12-03T19:27:58.000" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2325" PostTypeId="1" AcceptedAnswerId="2331" CreationDate="2020-09-20T10:00:39.720" Score="14" ViewCount="3462" Body="&lt;p&gt;Should the presence of a d block element in the unit cell mandate the need for performing spin-polarized calculations? I wanted to find out the DOS, PDOS, and the band structure. I'm new to DFT and I'm using the Quantum ESPRESSO package (where spin polarized calculations correspond to &lt;code&gt;nspin = 2&lt;/code&gt;. It would be nice if someone could guide me through doing it.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-09-20T18:44:52.410" LastActivityDate="2020-09-21T02:40:17.297" Title="When should spin polarized calculations be done?" Tags="|density-functional-theory|vasp|quantum-espresso|magnetism|spin|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2326" PostTypeId="2" ParentId="2316" CreationDate="2020-09-20T11:19:41.233" Score="2" Body="&lt;p&gt;I suspect the reason is due to the model.  Often doping is performed in the dilute doping region where you do not relax the cell to optimize the strain induced by the adsorbate.  This is because it is assumed the doping is done in a way that the bulk structure imposes its lattice constant on the dopant.  The dopant actually does induce strain so they are not independent of each other.&lt;/p&gt;&#xA;&lt;p&gt;The problem becomes experimentally creating a doped and strained material.  Growing a thin film that is doped (one way to induce strain) will probably result in segregation of the dopant.  For this reason its probably just not well explored.  If an experimentally tunable system is identified where both knobs can be turned independently,  doping and strain,  this would be well suited to dft studies.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-20T11:19:41.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2327" PostTypeId="1" CreationDate="2020-09-20T11:21:08.687" Score="12" ViewCount="1086" Body="&lt;p&gt;The meta-GGA &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevLett.115.036402&quot; rel=&quot;noreferrer&quot;&gt;SCAN functional&lt;/a&gt; has been there for a while. Despite the lack of SCAN (ultrasoft/PAW) pseudopotentials, various works used it in plane-wave pseudopotential calculations with pseudopotentials generated using PBE (in particular, using VASP, such as &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.4.065405&quot; rel=&quot;noreferrer&quot;&gt;this work&lt;/a&gt; and &lt;a href=&quot;https://www.nature.com/articles/s41524-018-0117-4&quot; rel=&quot;noreferrer&quot;&gt;this work&lt;/a&gt;), and reported improvements compared to GGA.&lt;/p&gt;&#xA;&lt;p&gt;I am wondering how much impact does the use of inconsistent pseudopotentials have, and whether the results are still reliable?&lt;/p&gt;&#xA;&lt;p&gt;PS: I am aware that &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.5094646&quot; rel=&quot;noreferrer&quot;&gt;rSCAN&lt;/a&gt; has enabled the pseudopotential generations, and there is a recent paper proposed the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpclett.0c02405&quot; rel=&quot;noreferrer&quot;&gt;r2SCAN&lt;/a&gt; function aiming to improve the accuracy of rSCAN. So hopefully SCAN pseudopotentials will arrive soon.&lt;/p&gt;&#xA;" OwnerUserId="1020" LastEditorUserId="5" LastEditDate="2020-09-20T16:24:12.440" LastActivityDate="2020-09-21T10:08:49.800" Title="Are meta-GGA functionals SCAN (and its variants) ok to use in planewave DFT with the PBE pseudopotentials?" Tags="|density-functional-theory|pseudopotentials|functional|plane-waves|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2328" PostTypeId="2" ParentId="2325" CreationDate="2020-09-20T11:26:18.717" Score="10" Body="&lt;p&gt;Unfortunately,  without performing spin polarized calculations you cannot know if it will matter.  Further,  you must perform different magnetic configurations (AFM,  FM,  PM) to know which is stable.&lt;/p&gt;&#xA;&lt;p&gt;If you can experimentally show if its magnetic or not this will help. Certain elements tend to be magnetic as well.  If you have Ni,  Co,  or Fe then you almost definitely need spin polarization.&lt;/p&gt;&#xA;&lt;p&gt;In short, you cannot know without checking. You can save time by starting from non-spin polarized calculations though.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-20T11:26:18.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2329" PostTypeId="2" ParentId="2327" CreationDate="2020-09-20T11:30:43.930" Score="4" Body="&lt;p&gt;New functionals often use PBE as a base.  This is due to the benefit that everyone is using the same slightly incorrect psuedopotential,  meaning it is reproducible.  In VASP the psuedopotentials cannot be generated by the user but codes like CASTEP and GPAW can generate them on the fly as needed.&lt;/p&gt;&#xA;&lt;p&gt;Using PBE as a base for SCAN is not ideal, but its consistent and easy.  I don't think anyone would consider it incorrect to do since this is common practice. Your concern is valid though&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-09-20T11:30:43.930" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2330" PostTypeId="1" CreationDate="2020-09-20T12:14:04.783" Score="6" ViewCount="108" Body="&lt;p&gt;In modelling using molecular mechanics can one state that &amp;quot;all structural variations are energy driven?&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The statement is related to protein-ligand binding in modelling.&#xA;Sometimes one can assess system by looking at structural stability on one hand but also on energy values.&#xA;If all structure variations are energy driven, I think it makes more sense to focus more on energy than structure.&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2020-12-28T03:55:51.650" LastActivityDate="2020-12-28T03:55:51.650" Title="Is this statement correct: &quot;All structural variations are energy driven&quot;?" Tags="|structure|molecular-mechanics|potential-energy-surface|" AnswerCount="0" CommentCount="4" ClosedDate="2020-10-07T12:38:06.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="2331" PostTypeId="2" ParentId="2325" CreationDate="2020-09-20T12:32:20.773" Score="9" Body="&lt;p&gt;I agree with Tristan that the fool proof method is to do a spin-polarized self consistent calculation and look at the final magnetic moment. If the final magnetic moment is non-zero you should include spin polarization in your calculations.&lt;/p&gt;&#xA;&lt;p&gt;However, from a practical point of view you can have a look at the &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1/88&quot;&gt;existing databases&lt;/a&gt;. In particular if you are working on bulk materials, you can look at the &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;materials project&lt;/a&gt; database. For example according to the database &lt;a href=&quot;https://materialsproject.org/materials/mp-5986/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{BaTiO_3}$&lt;/span&gt; is non magentic&lt;/a&gt; and &lt;a href=&quot;https://materialsproject.org/materials/mp-19035/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{BaFeO_3}$&lt;/span&gt; is magnetic&lt;/a&gt;. This will give you an idea prior to doing calculations and might be useful if you are screening for materials.&lt;/p&gt;&#xA;&lt;p&gt;PS: As suggested by Andrew, you should not rely on DFT databases too much with regards to magnetic behavior. They almost all use a high-spin magnetic initialization, which is entirely arbitrary. It is possible that the magnetic ground state is something entirely different (potentially even a state with no magnetic moments at all).&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2020-09-21T02:40:17.297" LastActivityDate="2020-09-21T02:40:17.297" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2332" PostTypeId="2" ParentId="548" CreationDate="2020-09-20T12:50:40.917" Score="7" Body="&lt;p&gt;This is a very nice question touching ongoing research. I cannot really provide a nice answer to it but I would like to share a few thoughts I had when thinking about this question.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;1. I think mentioning the Hohenberg-Kohn theorem in the question puts Becke's statement slightly into the wrong context. In this context one should first realize that there is an object even simpler than the ground-state electron density containing all details of the investigated system: The many-body Hamiltonian&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H} = \hat{T} + \hat{V}_\text{ee} + \hat{V}_\text{ext}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;consisting of the kinetic energy operator &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt;, the Coulomb interactions &lt;span class=&quot;math-container&quot;&gt;$\hat{V}_\text{ee}$&lt;/span&gt;, and the external potential &lt;span class=&quot;math-container&quot;&gt;$\hat{V}_\text{ext}$&lt;/span&gt;. You can actually write it down in every detail on a sheet of paper.&lt;/p&gt;&#xA;&lt;p&gt;Hohenberg and Kohn show for Hamiltonians of this form with the known expressions for &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{V}_\text{ee}$&lt;/span&gt; that there is a one-to-one mapping between the ground-state density and the external potential. At least up to a constant potential shift.&lt;/p&gt;&#xA;&lt;p&gt;Essentially this means that the positions and charges of the atomic nuclei are encoded in the ground-state density. But more complex external potentials are also possible. The form of the external potential does not have to be known beforehand. For the rest of the Hamiltonian this is not the case. It is assumed that it has the form sketched above: There is no one-to-one mapping between the density and the form of &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{V}_\text{ee}$&lt;/span&gt; which actually contain all the interactions you asked about.&lt;/p&gt;&#xA;&lt;p&gt;There even is an obvious counterexample for such a one-to one mapping: Kohn and Sham construct an auxiliary system of noninteracting electrons featuring the same ground-state density.&lt;/p&gt;&#xA;&lt;p&gt;So on this level the ground-state density only in connection with knowledge of the form of &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{V}_\text{ee}$&lt;/span&gt; contains all the interesting interaction details. But as mentioned this is also encoded in the Hamiltonian.&lt;/p&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ol&gt;&#xA;2. I think Becke's statement has to be seen in the context of energy functionals to extract the ground-state energy of an interacting many-electron system from the respective density.&#xA;&lt;p&gt;Such energy functionals are typically based on the Kohn-Sham system which is constructed such that the most significant contributions to the energy of the interacting many-electron system are easily accessible. This includes the Hartree energy, the energy due to the external potential, and the kinetic energies of the single-electron Kohn-Sham orbitals. Everything beyond these energy contributions is integrated into the exchange-correlation energy for which no exact expression is known.&lt;/p&gt;&#xA;&lt;p&gt;Fortunately this energy contribution often is not the dominating part and even simple approximations cover it with a good enough accuracy, e.g., the local density approximation that assumes the exchange-correlation energy of a homogeneous electron gas. For the homogeneous electron gas an expression for the exchange energy in terms of the density is known and the correlation energy can numerically be calculated by simulations.&lt;/p&gt;&#xA;&lt;p&gt;As indicated in my first sentence of this answer improving the accuracy of approximations to the exchange-correlation functional is ongoing research. One knows several properties the exact exchange-correlation functional has to fulfill. I think getting an intuitive physical picture on how the interactions are encoded in the ground-state density is strongly connected to knowing and understanding these properties. Unfortunately I cannot give you insights on this.&lt;/p&gt;&#xA;&lt;p&gt;Systematic improvements to the exchange-correlation functional often go beyond only using the charge density in a direct way. Since most of the exchange-correlation energy is due to exchange you see many approaches to express the exchange part exactly in terms of Kohn-Sham orbitals. This can then be used to construct a hybrid functional or to combine it with the random phase approximation to the correlation energy.&lt;/p&gt;&#xA;&lt;p&gt;Of course, one actually does not want to use the Kohn Sham orbitals for this because the resulting expressions are connected to significant computational demands. But the fact that it is done in this way indicates how difficult it is to directly extract the exchange-correlation energy from the density. It might also indicate that a practically usable physical picture directly connecting the density to the respecive interactions is not really available. But of course, it might also indicate that the encoding of this quantity in the rather featureless electron density is just too subtile to be usable.&lt;/p&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2020-09-20T12:50:40.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2333" PostTypeId="2" ParentId="2280" CreationDate="2020-09-20T15:06:30.320" Score="7" Body="&lt;h3&gt;CASTEP&lt;/h3&gt;&#xA;&lt;p&gt;I would recommend &lt;a href=&quot;http://www.castep.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASTEP&lt;/a&gt;. It is not open source but does have a cost-free academic license option.&#xA;It is very easy to use and beginner-friendly, with sensible &amp;quot;default&amp;quot; parameters and has a built-in help system. The on-the-fly pseudopotential generation system makes calculations very easy to set up and avoids some common pitfalls. MPI parallelisation is also automatic and efficient.&lt;/p&gt;&#xA;&lt;p&gt;You can not use it for commercially though, as it is sold as part of the Materials Studio.&lt;/p&gt;&#xA;" OwnerUserId="1020" LastEditorUserId="1020" LastEditDate="2020-09-21T10:46:40.973" LastActivityDate="2020-09-21T10:46:40.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2334" PostTypeId="1" CreationDate="2020-09-20T22:41:18.443" Score="7" ViewCount="706" Body="&lt;p&gt;I look at the STO-3G basis set for Carbon atom (downloaded from the &lt;a href=&quot;https://www.basissetexchange.org/basis/sto-3g/format/json/?version=1&amp;amp;elements=6&quot; rel=&quot;nofollow noreferrer&quot;&gt;basissetexchange.org&lt;/a&gt;) and I see one set of exponents and two sets of coefficients for the p-orbitals.&lt;/p&gt;&#xA;&lt;p&gt;How do these exponents and coefficients match with the expressions for Gaussian primitives:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$g_{\{x,y,z\}}(\alpha_{\{x,y,z\}},|\textbf{r}|)=(\frac{128\cdot \alpha_{\{x,y,z\}}^{5}}{\pi^{3}})^{1/4}\cdot \{x,y,z\}\cdot\exp(-\alpha_{\{x,y,z\}}\cdot r^{2})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I took a look at the original &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1672392&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, but still miss it.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1338" LastEditorUserId="5" LastEditDate="2020-09-21T05:25:16.900" LastActivityDate="2020-09-21T05:25:16.900" Title="p-orbitals in STO-3G basis set" Tags="|basis-sets|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2335" PostTypeId="2" ParentId="2334" CreationDate="2020-09-21T02:49:24.333" Score="6" Body="&lt;p&gt;It will help slightly to look at the basis description as it is entered into Gaussian.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C     0&#xA;S   3   1.00&#xA;      0.7161683735D+02       0.1543289673D+00&#xA;      0.1304509632D+02       0.5353281423D+00&#xA;      0.3530512160D+01       0.4446345422D+00&#xA;SP   3   1.00&#xA;      0.2941249355D+01      -0.9996722919D-01       0.1559162750D+00&#xA;      0.6834830964D+00       0.3995128261D+00       0.6076837186D+00&#xA;      0.2222899159D+00       0.7001154689D+00       0.3919573931D+00&#xA;****&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can, what is specified is not two sets of coefficients for p orbitals, but rather an 'sp' orbital. This is actually just an s and a p orbital that share the same exponents, but use different coefficients for the constituent gaussian functions. When the STO-nG basis sets were originally designed, it was considered too computationally intensive to independently optimize a set of exponents for the valence s and p orbitals. To avoid this cost, they optimized a single set of exponents that would be used for both, but still determined separate coefficients for each.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-09-21T02:49:24.333" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2336" PostTypeId="2" ParentId="2334" CreationDate="2020-09-21T05:24:30.787" Score="6" Body="&lt;p&gt;Just like the answer of Tyberius, I suggest looking at the basis set data in the format of a popular software, instead of the general JSON format which is what is in the link you gave us. While the GAUSSIAN format is more compact, I think it's even more clear in the CFOUR format, which is the same way the data is presented if you choose MOLCAS, AcesII, DALTON, DIRAC, deMon2K, TURBOMOLE, MOLPRO, and some other places:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C:STO-3G&#xA;STO-3G Minimal Basis (3 functions/AO)&#xA;&#xA;    2&#xA;    0    1&#xA;    2    1&#xA;    6    3&#xA;&#xA;0.2941249355D+01 0.6834830964D+00 0.2222899159D+00 0.7161683735D+02 0.1304509632D+02 0.3530512160D+01 &#xA;&#xA;-0.9996722919D-01 0.0&#xA; 0.3995128261D+00 0.0&#xA; 0.7001154689D+00 0.0&#xA; 0.0              0.1543289673D+00 &#xA; 0.0              0.5353281423D+00 &#xA; 0.0              0.4446345422D+00 &#xA;&#xA;0.2941249355D+01 0.6834830964D+00 0.2222899159D+00 &#xA;&#xA; 0.1559162750D+00 &#xA; 0.6076837186D+00 &#xA; 0.3919573931D+00 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let me now explain what everything means:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    2       # Number of types of functions (here we have S and P)&#xA;    0    1  # Types of functions (0 = S-type, 1 = P-type)&#xA;    2    1  # Number of contractions (2 S-type, 1 P-type)&#xA;    6    3  # Number of primitives   (6 S-type, 3 P-type)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then we have the 6 S-type primitives followed by 12 S-type contraction coefficients, but notice that 6 of the contraction coefficients are 0, so that we are left with only 3 contraction coefficients for 1s and 3 contraction coefficients for 2s. &lt;strong&gt;This is why it's called STO-&lt;em&gt;3&lt;/em&gt;G: There's 3 primitives for each orbital.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So the 1s orbitals are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\phi_{1s} &amp;amp;= c_{11} g_s(\alpha_1) + c_{21} g_s(\alpha_2) + c_{31} g_s(\alpha_3) + \color{gray}{c_{41} g_s(\alpha_4)+c_{51} g_s(\alpha_5)+c_{61} g_s(\alpha_6) }\\&#xA;\phi_{2s} &amp;amp;= \color{gray}{c_{12} g_s(\alpha_1) + c_{22} g_s(\alpha_2) + c_{32} g_s(\alpha_3)} + c_{42} g_s(\alpha_4)+c_{52} g_s(\alpha_5)+c_{62} g_s(\alpha_6), &#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\alpha_1,\alpha_2,\alpha_3,\alpha_4,\alpha_5,\alpha_6$&lt;/span&gt; are given in this line:&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;0.2941249355D+01 0.6834830964D+00 0.2222899159D+00 0.7161683735D+02 0.1304509632D+02 0.3530512160D+01 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then the &lt;span class=&quot;math-container&quot;&gt;$c_{ij}$&lt;/span&gt; matrix of coefficients is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-0.9996722919D-01 0.0&#xA; 0.3995128261D+00 0.0&#xA; 0.7001154689D+00 0.0&#xA; 0.0              0.1543289673D+00 &#xA; 0.0              0.5353281423D+00 &#xA; 0.0              0.4446345422D+00 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Because of the &lt;code&gt;0.0&lt;/code&gt; entries, we actually only have 3 terms for 1s and 3 terms for 2s, which is why it's called STO-&lt;em&gt;3&lt;/em&gt;G.&lt;/p&gt;&#xA;&lt;p&gt;So now your question was about the P-type orbitals. The 3 exponents (&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; in your question) are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0.2941249355D+01 0.6834830964D+00 0.2222899159D+00 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the 3 contraction coefficients are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 0.1559162750D+00 &#xA; 0.6076837186D+00 &#xA; 0.3919573931D+00 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$\phi_{2p}$&lt;/span&gt; is a sum of three terms.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-09-21T05:24:30.787" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2337" PostTypeId="2" ParentId="2327" CreationDate="2020-09-21T10:08:49.800" Score="10" Body="&lt;p&gt;It is well known that using pseudopotentials generated with a functional which is inconsistent with the functional used in the plane-wave calculation can lead to serious problems, see &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.57.2134&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for example.&lt;/p&gt;&#xA;&lt;p&gt;It was also shown that for a potential-only meta-GGA (TB), the choice of pseudopotential makes a &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.235103&quot; rel=&quot;noreferrer&quot;&gt;huge difference&lt;/a&gt; in the band gap, and in particular using PBE pseudopotentials lead to severely underestimated band gaps compared to the all-electron calculations with the TB potential.&lt;/p&gt;&#xA;&lt;p&gt;Another &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4984939&quot; rel=&quot;noreferrer&quot;&gt;study&lt;/a&gt; showed that PBE pseudopotentials do lead to inaccuracies when combined with SCAN in the plane-wave calculation, although it is somewhat less severe overall - but keep in mind that this study was not too comprehensive.&lt;/p&gt;&#xA;&lt;p&gt;I would say that as a minimum you must state that this is what you did and indicate that this is an &lt;em&gt;uncontrolled&lt;/em&gt; approximation and could be a cause of a range of errors. You may be able to get an idea about the error due to the inconsistency, for your particular system, by comparing to all-electron results, even as a spot-check or for a proxy system.&lt;/p&gt;&#xA;&lt;p&gt;The fact that a lot of studies are conducted with inconsistent pseudopotentials does not mean that such usage is ideal or even correct.&lt;/p&gt;&#xA;" OwnerUserId="1358" LastActivityDate="2020-09-21T10:08:49.800" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2338" PostTypeId="2" ParentId="2316" CreationDate="2020-09-21T11:29:35.220" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I've never come across any paper where they investigated how simultaneously varying both the amount of doping and strain affects the electronic structure of materials. Why is this so?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Doping and strain are viewed as effective methods to engineer the properties of materials. It is true that doping and strain can be applied at the same time. However, from the viewpoint of simulation, we don't want to do that. &lt;strong&gt;Because we hardly deduce that the final results are engineered by what method.&lt;/strong&gt; For example, if the strain will open the gap, but the doping will close the gap. Then the final result manifests the gap doesn't change. Can we say that strain and the doping don't affect the band-gap of materials? Or can we say that strain will close the gap and the doping will open the gap?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is there some physics-based reason for this or is it just because simultaneously varying both the amount of doping and strain might be computationally expensive?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The computation amount depends on many elements: such as the number of the atom, the sampling of k mesh and the energy cutoff, and so on.&lt;/li&gt;&#xA;&lt;li&gt;If you just want to study strain, then you can choose the primitive cell. The computational amount will keep a minimum.&lt;/li&gt;&#xA;&lt;li&gt;If you want to study doping, then the cell is decided by the concentration with the supercell method.&lt;/li&gt;&#xA;&lt;li&gt;If you want to study doping and strain simultaneously, the cell is also decided by the concentration with the supercell method. Therefore it doesn't change the computational amount compared with the doping simulation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-09-21T11:36:34.897" LastActivityDate="2020-09-21T11:36:34.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2339" PostTypeId="1" AcceptedAnswerId="2340" CreationDate="2020-09-21T14:30:18.577" Score="14" ViewCount="243" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When we perform matter simulation with first-principles calculation, building a reasonable model always be the very first and important step. However, people utilize different tools to build their model on top of their background. I know some tools such as &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt; and &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Studio&lt;/a&gt; from my computational condensed matter physics background.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The purpose that I post this question is to look for the complete list of model building tools from your backgrounds. I hope you can share your tools to build a model and list its common functions. And I hope this question and the expected answer will be beneficial for the whole matter modeling community.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The answer presented &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1513/what-are-the-types-of-dft&quot;&gt;as this format&lt;/a&gt; is appreciable.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-04-05T13:14:47.870" LastActivityDate="2021-04-05T13:14:47.870" Title="How to build matter modeling models with appropriate tools?" Tags="|density-functional-theory|vesta|materials-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2340" PostTypeId="2" ParentId="2339" CreationDate="2020-09-21T15:19:32.630" Score="16" Body="&lt;h3&gt;Atomic Simulation Environment (Surfaces)&lt;/h3&gt;&#xA;&lt;p&gt;I am going to narrowly cover &lt;strong&gt;surface&lt;/strong&gt; models in this answer since &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; is more than capable of handling a wide range of models from nanoparticles, surfaces, 2D layered materials, bulk 3D materials, etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#the-following-functions-are-provided&quot; rel=&quot;noreferrer&quot;&gt;Metal Surfaces&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Pt(111) models for example can be easily created within the ase.build module as follows.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111&#xA;slab = fcc111('Pt', size=(2,2,3), vacuum=10.0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;FCP, BCC, and HCP surfaces with preassigned sites can be generated for a couple of low index facets.  An example model of a Cu surface with atoms placed in these sites is found on the documentation page.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Wd4jI.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Wd4jI.png&quot; alt=&quot;FCC(111) Cu surface with marked atoms&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#create-specific-non-common-surfaces&quot; rel=&quot;noreferrer&quot;&gt;Oxide / General Surfaces&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;When there is no predefined function available for the surface you want, there is a generic function that produces a cell.  It can be called as follows given that you can provide a bulk structure.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import surface&#xA;s1 = surface('Pt', (2, 1, 1), 9)&#xA;s1.center(vacuum=10, axis=2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This function unfortunately will not define absorption sites for you and there is no guarantee that there will be an inversion symmetry between the top and bottom of the surface.  This makes it significantly more finicky to work with, but if you can find a good consistent set of parameters you can define your own helper function to generate &amp;quot;nice&amp;quot; surfaces.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#create-root-cuts-of-surfaces&quot; rel=&quot;noreferrer&quot;&gt;Root Surfaces (Supercell calculations)&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In literature, you may see supercell surfaces being referred to as a 4x4 cell for example meaning that the primitive surface cell was repeated 4 times in the x and y.  This is fairly restrictive in terms of computational power, moving from a 3x3 to a 4x4 results in almost double the number of atoms.&lt;/p&gt;&#xA;&lt;p&gt;To smooth this gap, so-called root cells can be formed.  These get their name from the fact that fcc-like surfaces with a 30-60-90 cell have potential cell transformations where the x/y vector is not multiplied by an integer value such as 3 or 4, but it is multiplied by a root such as root(12) and the entire cell is rotated.  This has the nice property for fcc-like cells that a root(12) cell will have 12 repetitions of the primitive surface cell (like a 3x4) but will maximize the distance for any atom interacting with its periodic image.&lt;/p&gt;&#xA;&lt;p&gt;Not many codes support this in a general manner, but ASE's implementation can also handle cells which are not fcc-like.  In practice, you create a 1x1 surface to use as a primitive surface cell and call the root_surface function with a valid root.  If you do not know the valid roots there is a root_surface_analysis function to help you.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111, root_surface&#xA;atoms = fcc111('Ag', (1, 1, 3))&#xA;atoms = root_surface(atoms, 27)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GEkXr.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GEkXr.png&quot; alt=&quot;root(27) silver cell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-09-21T16:06:18.900" LastActivityDate="2020-09-21T16:06:18.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2341" PostTypeId="2" ParentId="2278" CreationDate="2020-09-21T18:06:48.330" Score="6" Body="&lt;h3&gt;3Dmol.js&lt;/h3&gt;&#xA;&lt;p&gt;I highly recommend &lt;a href=&quot;https://3dmol.csb.pitt.edu&quot; rel=&quot;nofollow noreferrer&quot;&gt;3Dmol.js&lt;/a&gt; through the py3dmol extension.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;3Dmol.js is an object-oriented, WebGL based JavaScript library for online molecular visualization - No Java required!&#xA;With 3Dmol.js, you can add beautifully rendered molecular visualizations to your web applications. Features include:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;support for pdb, sdf, mol2, xyz, and cube formats&lt;/li&gt;&#xA;&lt;li&gt;parallelized molecular surface computation&lt;/li&gt;&#xA;&lt;li&gt;sphere, stick, line, cross, cartoon, and surface styles&lt;/li&gt;&#xA;&lt;li&gt;atom property based selection and styling&lt;/li&gt;&#xA;&lt;li&gt;labels&lt;/li&gt;&#xA;&lt;li&gt;clickable interactivity with molecular data&lt;/li&gt;&#xA;&lt;li&gt;geometric shapes including spheres and arrows&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;3Dmol.js supports XYZ, CIF, PDB, MMTF, .. a huge variety of &lt;a href=&quot;http://3dmol.csb.pitt.edu/doc/types.html#FileFormats&quot; rel=&quot;nofollow noreferrer&quot;&gt;file formats&lt;/a&gt;, including volumetric data such as Gaussian Cube files, VASP, etc.&lt;/p&gt;&#xA;&lt;p&gt;Some examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://nbviewer.jupyter.org/github/3dmol/3Dmol.js/blob/master/py3Dmol/examples.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;official examples&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://rdkit.blogspot.com/2016/07/using-ipywidgets-and-py3dmol-to-browse.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;combining RDKit and py3dmol for conformations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://iwatobipen.wordpress.com/2020/03/07/rendering-molecular-orbital-on-jupyter-notebook-psikit-py3dmol-rdkit-memo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;rendering molecular orbitals&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://birdlet.github.io/2019/10/02/py3dmol_example/&quot; rel=&quot;nofollow noreferrer&quot;&gt;birdlet blog&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastEditorUserId="5" LastEditDate="2020-09-21T18:49:15.887" LastActivityDate="2020-09-21T18:49:15.887" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2342" PostTypeId="1" AcceptedAnswerId="2343" CreationDate="2020-09-21T18:30:11.987" Score="12" ViewCount="2151" Body="&lt;p&gt;I am a beginner and newly started running DFT calculations to find out the electronic band structure of certain materials in Quantum ESPRESSO. But we have to select the pseudopotential for running the SCF loop. There are lots of pseudopotential files(.UPF format) available on the internet for the same material. Which is quite confusing for me to select which one I Should use. How they are different from one another? Does it depend on the type of calculation we are going to perform or which property of materials we are looking for? Can I generate a pseudopotential file by myself? If yes, how.&lt;/p&gt;&#xA;&lt;p&gt;Please, Clarify my doubts! It will be helpful to me in my learning process.&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1218" LastEditDate="2020-09-21T19:25:25.460" LastActivityDate="2020-09-22T19:30:35.300" Title="How to choose pseudopotential for DFT calculations in Quantum ESPRESSO?" Tags="|density-functional-theory|computational-chemistry|condensed-matter|quantum-espresso|self-consistent-field|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2343" PostTypeId="2" ParentId="2342" CreationDate="2020-09-21T19:24:16.477" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How to choose pseudopotential for DFT calculations in Quantum ESPRESSO?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can find almost all the pseudopotentials (PP) from the following website for all elements in the periodical table.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.pseudo-dojo.org/&quot; rel=&quot;noreferrer&quot;&gt;PP for Quantum Espresso&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Currently, there are four parameters that you can choose.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;type: NC(Scalar and FR version)/PAW&lt;/li&gt;&#xA;&lt;li&gt;XC: LDA/PBE/PBEsol&lt;/li&gt;&#xA;&lt;li&gt;accuracy: standard/stringent&lt;/li&gt;&#xA;&lt;li&gt;format: upf/html/psp8/psml/djrepo&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How they differ from one another? Does it depend on the type of calculation we are going to perform or which property of materials we are looking for?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, it depends on the materials that you are modeling. There are many things that need to be considered in the generated PP and hence differ. For example, the spin-orbit coupling (SOC) should be included or not. If you consider SOC, you should use the FR version. Which method is utilized to generate this PP? It is differed by PAW and NC.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I generate a pseudopotential file by myself?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, you can. BUT as a beginner, I strongly recommend you use the existed PP database.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-21T19:24:16.477" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2344" PostTypeId="1" CreationDate="2020-09-21T19:38:06.457" Score="10" ViewCount="448" Body="&lt;p&gt;Is anyone familiar with Tkatchenko's new &lt;a href=&quot;https://arxiv.org/abs/1910.03073&quot; rel=&quot;nofollow noreferrer&quot;&gt;MBD-NL method&lt;/a&gt;? How does it differ from DFT-TS? I couldn't understand everything from the paper.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="5" LastEditDate="2021-02-28T20:01:44.463" LastActivityDate="2021-04-29T10:21:42.183" Title="How does MBD (MBD-NL) differ from DFT-TS?" Tags="|density-functional-theory|dispersion-correction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2345" PostTypeId="2" ParentId="2220" CreationDate="2020-09-21T23:21:31.190" Score="4" Body="&lt;p&gt;A straightforward way to model the interaction of charged species with a surface is to use a cluster model instead of simulating the surface as a slab with periodic boundary conditions (1).&lt;/p&gt;&#xA;&lt;p&gt;Cluster models are not perfect, they can be affected by border effects that require large clusters, to be representative of the bulk system, by coverage effects, as a single molecule interacts with the surface, and charge effects, as in a cluster there is a small number of atoms, compared to the bulk, to delocalize the charge.&lt;/p&gt;&#xA;&lt;p&gt;But they have the advantage of being amenable to the most powerful and accurate first-principles methods (2), trivially model charged species, and are well suited to studying the details of local chemical bonding. To incorporate bulk effects in cluster models, embedding potential methods have been proposed and successfully applied to the O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; reaction on Al(111) (3), H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; dissociation on the Au nanoparticle (4), adsorption (2), and band gaps (5). I have used a Pt&lt;span class=&quot;math-container&quot;&gt;$_{15}$&lt;/span&gt; cluster to investigate the adsorption of L-cysteine (that can be charged depending on the pH) on Pt(111) (The geometries for the clusters are given in the &lt;a href=&quot;http://www.rsc.org/suppdata/c6/ra/c6ra26576f/c6ra26576f1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electronic Supplementary Material&lt;/a&gt;) (6).&lt;/p&gt;&#xA;&lt;p&gt;You can start with the geometry of the slab and cut a cluster that is large enough to describe your system but small enough to be run a calculation in a reasonable time. Usually, the atoms on the border of the cluster and in lower layers have their positions fixed to avoid large distortions. The charge of the system will be equal to the charge of the adsorbent, assuming that your surface is neutral. Any molecular electronic structure code can be used for that. I recommend using &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/portal&quot; rel=&quot;nofollow noreferrer&quot;&gt;Orca&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;L. A. Curtiss, M. S. Gordon (eds.), Computational Materials Chemistry: Methods and Applications, Springer (2005).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A. Kubas, D. Berger, H. Oberhofer, D. Maganas, K. Reuter, F. Neese, &lt;a href=&quot;https://dx.doi.org/10.1021/acs.jpclett.6b01845&quot; rel=&quot;nofollow noreferrer&quot;&gt;Surface Adsorption Energetics Studied with “gold Standard” Wave-Function-Based Ab Initio Methods: Small-Molecule Binding to TiO2(110)&lt;/a&gt;. J. Phys. Chem. Lett. 7, 4207–4212 (2016).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;F. Libisch, C. Huang, P. Liao, M. Pavone, E. A. Carter, &lt;a href=&quot;https://dx.doi.org/10.1103/PhysRevLett.109.198303&quot; rel=&quot;nofollow noreferrer&quot;&gt;Origin of the energy barrier to chemical reactions of O 2 on Al(111): Evidence for charge transfer, not spin selection.&lt;/a&gt; Phys. Rev. Lett. 109, 1–5 (2012).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;F. Libisch, J. Cheng, E. A. Carter, &lt;a href=&quot;https://dx.doi.org/10.1524/zpch.2013.0406&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electron-transfer-induced dissociation of H2 on gold nanoparticles: Excited-state potential energy surfaces via embedded correlated wavefunction theory.&lt;/a&gt; Z. Phys. Chem. 227, 1455–1466 (2013).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A. Dittmer, R. Izsák, F. Neese, D. Maganas, &lt;a href=&quot;https://dx.doi.org/10.1021/acs.inorgchem.9b00994&quot; rel=&quot;nofollow noreferrer&quot;&gt;Accurate Band Gap Predictions of Semiconductors in the Framework of the Similarity Transformed Equation of Motion Coupled Cluster Theory.&lt;/a&gt; Inorg. Chem. 58, 9303–9315 (2019).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A. H. B. Dourado, A. P. de Lima Batista, A. G. S. Oliveira-Filho, P. T. A. Sumodjo, S. I. Cordoba de Torresi, &lt;a href=&quot;https://dx.doi.org/10.1039/C6RA26576F&quot; rel=&quot;nofollow noreferrer&quot;&gt;l -Cysteine electrooxidation in alkaline and acidic media: a combined spectroelectrochemical and computational study.&lt;/a&gt; RSC Adv. 7, 7492–7501 (2017).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2020-09-21T23:21:31.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2346" PostTypeId="1" CreationDate="2020-09-22T03:15:19.473" Score="12" ViewCount="404" Body="&lt;p&gt;Recently, for entrance exams, I have been dealing with a lot of weird compounds. One of them is &lt;span class=&quot;math-container&quot;&gt;$\ce{K3[Mn(CN)6]}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The objective was to predict the magnetic moment of the above complex.&#xA;&lt;br /&gt;&#xA;I predict that the number of &lt;em&gt;unpaired electrons&lt;/em&gt; in the metal is &lt;strong&gt;2&lt;/strong&gt; which straight away implies that the magnetic moment must be &lt;strong&gt;2.8&lt;/strong&gt; but since it is a mere speculation considering the strong-ligand &lt;span class=&quot;math-container&quot;&gt;$\ce{CN^-}$&lt;/span&gt; I would like to confirm it by modelling the compound. The data for the given complex is not available/accessible for me.&lt;/p&gt;&#xA;&lt;p&gt;An &lt;a href=&quot;https://www.researchgate.net/post/How_does_one_calculate_magnetic_moment_using_Gaussian09&quot; rel=&quot;noreferrer&quot;&gt;article&lt;/a&gt; available online says to calculate the average of Gross Orbital Population (in Gaussian09). Trying it out gave an output of 1.&lt;/p&gt;&#xA;&lt;p&gt;Hence, I would like to know how do I find the magnetic moment computationally (maybe using Gaussian, Gamess, Terachem, OCRA, etc.).&lt;/p&gt;&#xA;&lt;p&gt;As a sidenote, since NMR uses magnetic field, can it be useful for computing magnetic moment?&lt;/p&gt;&#xA;" OwnerUserId="1362" LastEditorUserId="5" LastEditDate="2020-09-22T04:20:13.040" LastActivityDate="2022-02-16T15:57:35.550" Title="Predicting magnetic moment of a metal complex computationally" Tags="|computational-chemistry|magnetism|transition-metals|magnetic-field|metal-complexes|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2347" PostTypeId="1" AcceptedAnswerId="2351" CreationDate="2020-09-22T11:27:46.667" Score="13" ViewCount="8831" Body="&lt;p&gt;I am doing DFT calculations with pw.x executable in Quantum Espresso. For this we have to choose right K-points grid in order to perform error-less calculation. But I have no idea about how can I choose optimal values of K-points? How to converge it?&#xA;Do I have to perform same calculation with different values of K-points (by randomly guessing it).&lt;br /&gt;&#xA;What will be the effect on band structure if I take very high values of K-points or low value of K-points?&lt;/p&gt;&#xA;&lt;p&gt;Please, clarify my doubts.&#xA;Thanking you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2020-09-26T20:40:29.033" Title="How to know optimal K-points grid values for good DFT calculation?" Tags="|density-functional-theory|band-structure|quantum-espresso|open-source|k-points|" AnswerCount="5" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2348" PostTypeId="2" ParentId="2347" CreationDate="2020-09-22T13:08:30.973" Score="9" Body="&lt;p&gt;You can upload your structure [many formats are supported] into the following website to generate the input file for your Quantum Espresso calculation.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud Website&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are three choices for the k sampling in terms of the distance between two k points.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Very fine [0.15 1/A]&lt;/li&gt;&#xA;&lt;li&gt;Fine [0.2 1/A]&lt;/li&gt;&#xA;&lt;li&gt;Normal [0.3 1/A]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Very often, you can just take the fine option to obtain reliable results.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-22T13:08:30.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2349" PostTypeId="2" ParentId="2347" CreationDate="2020-09-22T15:26:33.027" Score="12" Body="&lt;p&gt;Like many other parameters in QE one of the best methods is to simply test yourself and weight your options.&lt;/p&gt;&#xA;&lt;p&gt;You may start with 1x1x1 and go to 3x3x3 for example and check the following.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Do you get convergence?&lt;/li&gt;&#xA;&lt;li&gt;What is final energy?&lt;/li&gt;&#xA;&lt;li&gt;What is dE in the final step?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;(plot the above parameters to see the diminishing returns)&lt;/p&gt;&#xA;&lt;p&gt;Then determine computation time expense vs. accuracy gained.&lt;/p&gt;&#xA;" OwnerUserId="1366" LastActivityDate="2020-09-22T15:26:33.027" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2350" PostTypeId="1" AcceptedAnswerId="2361" CreationDate="2020-09-22T17:37:05.057" Score="13" ViewCount="3206" Body="&lt;p&gt;I am currently new to DFT calculations in Quantum ESPRESSO. Though, I have read some research papers for determining spin polarization and Half-metallicity in certain Heusler alloys. These research papers shows some theoretical calculations about Density of States at fermi level and showing band structures in first brillouin zone. But if I want to predict by myself such new materials, how can I do that? For eg:Mn2CoAl.&lt;br /&gt;&#xA;I have basic knowledge of DFT calculation, SCF loops, Pseudopotentials and running simple calculations in Quantum ESPRESSO.&lt;br /&gt;&#xA;What are the steps do I have to follow for spin polarization and Half metallicity prediction in new materials?&lt;/p&gt;&#xA;&lt;p&gt;Please, clarify my doubts!&lt;br /&gt;&#xA;Thanking you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-09-23T02:22:27.193" LastActivityDate="2020-09-24T17:33:16.197" Title="How to do spin polarization calculations using Quantum ESPRESSO?" Tags="|density-functional-theory|computational-chemistry|quantum-espresso|open-source|magnetism|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2351" PostTypeId="2" ParentId="2347" CreationDate="2020-09-22T19:20:33.350" Score="13" Body="&lt;p&gt;As already specified in the previous answers, the choice of K-Grid mesh should be taken upon verifying the convergence of the desired quantity. We usually start with the convergence of the total energy, but for other properties like optical spectra, for example, the converged grid with respect to the energy should not be enough, and a denser grid is usually required.&lt;/p&gt;&#xA;&lt;p&gt;With respect to the question&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What will be the effect on band structure if I take very high values of K-points or low value of K-points?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To the band structure calculation, the path in the Brillouin zone should be explicitly given. A denser grid leads to a more resolved band structure, however, the computational cost increases significantly with respect to a coarser grid. For a coarse grid, details of the band structure could not be properly resolved, however, the calculation time will be reduced.&lt;/p&gt;&#xA;&lt;p&gt;The size of the primitive cell should also be taken into account. For large (super)cells fewer k-points are required since the Brillouin zone is decreased with increasing the cell.&lt;/p&gt;&#xA;&lt;p&gt;Last but not least, for the Monkhost-Pack grid Quantum ESPRESSO allows for shifting the grid by setting&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Kx Ky Kz 0 0 0 (non-shifted)&#xA;Kx Ky Kz 1 1 1 (shifted)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Depending on the symmetries of the structure, the shift moves the k-point mesh semilattice. The number of inequivalent points then decreases, resulting in a reduction in the total number of k-points. More information can be found in the &lt;a href=&quot;https://blog.virtuallab.co.kr/en/2019/05/24/4-how-to-set-the-k-point-more-properly-shift/&quot; rel=&quot;noreferrer&quot;&gt;Material Square blog&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lPTqP.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lPTqP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-09-22T19:20:33.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2352" PostTypeId="2" ParentId="2342" CreationDate="2020-09-22T19:30:35.300" Score="6" Body="&lt;p&gt;The &lt;a href=&quot;https://www.materialscloud.org/discover/sssp/table/efficiency&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud&lt;/a&gt; Initiative has provided a very useful tool, the &lt;strong&gt;Standard solid-state pseudopotentials (SSSP)&lt;/strong&gt;, as&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A standard solid-state pseudopotentials (SSSP) library optimized for precision and efficiency.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The two libraries (SSSP Precision and SSSP Efficiency) cover for each element either the best in class (among many libraries, or generated by us), or occasionally allow for a compromise (either expensive and accurate, or less expensive and a bit less accurate).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The convergence pattern of each element includes for each of the considered family (represented by a color):&#xA;the total number of electrons in the valence, Z;&#xA;delta value (the error in the equation of state compared with all-electron WIEN2k results, developed by Cottenier group), at full converged cutoff;&#xA;the largest phonon frequency, ωmax, at the zone boundary (as a number), at full cutoff; and then as a function of wave function cutoff:&#xA;the discrepancy of all phonon frequencies, δω̄, at the zone boundary, with respect to the converged value;&#xA;the convergence of the pressure, δVpress, with respect to the converged value;&#xA;the convergence of the cohesive energy, δEcoh, with respect to the converged value;&#xA;the convergence of the band's structure, η10, and max η10 with respect to the converged value.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pDQwD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pDQwD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They also provided the calculated band structures, as a reference against several pseudo-potential libraries. It is a very good starting point when starting the choice of pseudo-potential.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-09-22T19:30:35.300" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2353" PostTypeId="1" CreationDate="2020-09-23T03:49:22.970" Score="6" ViewCount="53" Body="&lt;p&gt;Given an ensemble of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; diatomic molecules, we know that the rotational partition function is given by &lt;span class=&quot;math-container&quot;&gt;$$Z_r = z_r^N$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$$z_r = \sum_{l} (2l+1)e^{-Kl(l+1)}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$K = \beta \hbar ^2 /2I$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I want to apply this to calculate the &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; for an ensemble of &lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt; (hydrogen) molecules in the low &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; limit and the high &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; limit for a certain quantum mechanical simulation. Before I run the simulation, I want to have an idea of how the results should look like.&lt;/p&gt;&#xA;&lt;p&gt;For a general canonical ensemble, &lt;span class=&quot;math-container&quot;&gt;$C_v = \left( \partial E / \partial T \right)_V$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$E = -(\partial Z / \partial \beta$&lt;/span&gt;). &lt;em&gt;How would I evaluate the &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; for a system of one mole of para-&lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; (singlet state) and one mole of ortho-&lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; (triplet state) in the high temperature limit and low temperature limit? How would I find the partition function for an HD molecule?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;After doing some research, I see that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$Z_{para}= \sum_{l \,\text{even}} (2l+1)e^{-\beta \hbar ^2 l(l+1)/2I}$$&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$Z_{ortho}= \sum_{l \,\text{even}} (2l+1)e^{-\beta \hbar ^2 l(l+1)/2I}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know that because of the different multiplicities of these two states at equilibrium, the rotational partition function at low &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; looks like&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$z_r = \frac{1}{4} \sum_{l \,\text{even}} (2l+1)e^{-\beta \hbar ^2 l(l+1)/2I} + \frac{3}{4} \sum_{l \, \text{odd}} (2l+1)e^{-\beta \hbar ^2 l(l+1)/2I} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;After seeing &lt;a href=&quot;http://www.cmp.caltech.edu/%7Emcc/Ph127/a/Lecture_19.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this document&lt;/a&gt;, I can see how &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; looks like for ortho, para-&lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt;, and their equilibrium. How do you find the partition function - and then &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$HD$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2020-09-23T16:32:41.953" LastActivityDate="2020-09-23T16:32:41.953" Title="Evaluating $C_v$ for one mole $H_2$ molecules in a quantum simulation" Tags="|quantum-mechanics|statistical-thermodynamics|" AnswerCount="0" CommentCount="4" ClosedDate="2020-10-14T03:50:16.550" ContentLicense="CC BY-SA 4.0" />
  <row Id="2355" PostTypeId="2" ParentId="2346" CreationDate="2020-09-23T07:37:51.563" Score="7" Body="&lt;p&gt;The main question here is whether the question makes sense for &lt;span class=&quot;math-container&quot;&gt;${\rm K}_3[{\rm Mn(CN)}_6]$&lt;/span&gt; as a molecular complex.&lt;/p&gt;&#xA;&lt;p&gt;Looks like the material has a solid state structure &lt;a href=&quot;https://materials.springer.com/isp/crystallographic/docs/sd_1100190&quot; rel=&quot;noreferrer&quot;&gt;https://materials.springer.com/isp/crystallographic/docs/sd_1100190&lt;/a&gt; which you could with solid state methods. As a complex it's not obvious where the potassiums would go, so you would probably start out by getting rid of the potassiums in the +1 charge state to get &lt;span class=&quot;math-container&quot;&gt;$[{\rm Mn(CN)}_6]^{3-}$&lt;/span&gt;.&#xA;If you further assumed the &lt;span class=&quot;math-container&quot;&gt;${\rm CN}$&lt;/span&gt; to be &lt;span class=&quot;math-container&quot;&gt;${\rm CN}^-$&lt;/span&gt;, you would get a +3 oxidation state for &lt;span class=&quot;math-container&quot;&gt;${\rm Mn}$&lt;/span&gt;, and two unpaired electrons, see e.g. &lt;a href=&quot;https://www.quora.com/What-is-the-hybridisation-of-Mn-CN-6-3;&quot; rel=&quot;noreferrer&quot;&gt;https://www.quora.com/What-is-the-hybridisation-of-Mn-CN-6-3;&lt;/a&gt; but your question was about a computational value.&lt;/p&gt;&#xA;&lt;p&gt;You could get the magnetic moment on the metal by running some calculations on the &lt;span class=&quot;math-container&quot;&gt;$[{\rm Mn(CN)}_6]^{3-}$&lt;/span&gt; complex. However, this is not nearly as it sounds like: transition metal complexes are often challenging due to near-degeneracies, which means that  the numbers you get from your calculations may be complete garbage (I'm not sure whether this is the case for this complex): density functional approximations may be unreliable, whereas wave function methods may require a very fine balance between static and dynamic correlation to make the computed ground state match the experimental one. Setting up the necessary model and making sure that the computed number is converged with respect to all parameters is a huge hassle.&lt;/p&gt;&#xA;&lt;p&gt;This is an interesting question, but I fear it may be quite a lot of work to get a reliable answer from theory!&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-23T07:37:51.563" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2356" PostTypeId="1" CreationDate="2020-09-23T08:13:20.137" Score="7" ViewCount="193" Body="&lt;h3&gt;Background&lt;/h3&gt;&#xA;&lt;p&gt;Let &lt;code&gt;qA&lt;/code&gt; and &lt;code&gt;qB&lt;/code&gt; represent unit, orientation quaternions of grain A and grain B of a grain boundary in the lab reference frame, respectively. Let &lt;code&gt;qm&lt;/code&gt; be the misorientation quaternion of &lt;code&gt;qA&lt;/code&gt; and &lt;code&gt;qB&lt;/code&gt;. Quaternion inversion (&lt;code&gt;qinv&lt;/code&gt;) and quaternion multiplication (&lt;code&gt;qmult&lt;/code&gt;) are discussed in &lt;a href=&quot;https://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quaternions and spatial rotations&lt;/a&gt;. Let &lt;code&gt;mA&lt;/code&gt; be the boundary plane normal pointing from grain A to grain B in the sample reference frame. Let &lt;code&gt;nA&lt;/code&gt; be the boundary plane normal pointing outwards from grain A towards grain B in the grain A crystal reference frame. All boundary planes are represented in 3D Cartesian coordinates.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-matlab prettyprint-override&quot;&gt;&lt;code&gt;qinv(qA) = [qA(1) -qA(2:4)]&#xA;qinv(qB) = [qB(1) -qB(2:4)]&#xA;&#xA;qmult(qA,qB) ~= qmult(qB,qA) %non-commutative&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;My Understanding&lt;/h3&gt;&#xA;&lt;p&gt;I think the misorientation quaternion is obtained by one of the following two conversions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;qm = qmult(qinv(qA),qB);&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;qm = qmult(qB,qinv(qA));&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I think the boundary plane normal is represented by:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-matlab prettyprint-override&quot;&gt;&lt;code&gt;nA = qmult(qA,qmult([0 mA],qinv(qA)));&#xA;nA = nA(2:4); %drop 1st element which is 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;While the two misorientation quaternions share the same misorientation angle, they each represent rotations around different axes, and thus (as far as I understand), a different grain boundary.&lt;/p&gt;&#xA;&lt;h3&gt;Question&lt;/h3&gt;&#xA;&lt;p&gt;What is the appropriate conversion of (&lt;code&gt;qA&lt;/code&gt;, &lt;code&gt;qB&lt;/code&gt;, &lt;code&gt;mA&lt;/code&gt;) triplets to (&lt;code&gt;qm&lt;/code&gt;, &lt;code&gt;nA&lt;/code&gt;) pairs?&lt;/p&gt;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&lt;p&gt;DOI: &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0965-0393/23/8/083501&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1088/0965-0393/23/8/083501&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1371" LastEditorUserId="5" LastEditDate="2021-06-22T00:41:38.343" LastActivityDate="2021-12-28T23:27:48.250" Title="How to convert lab frame quaternions and plane normal to misorientation quaternion and crystal plane normal for grain boundaries?" Tags="|crystal-structure|crystallography|grain-boundaries|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2358" PostTypeId="1" CreationDate="2020-09-23T21:28:42.533" Score="12" ViewCount="6820" Body="&lt;p&gt;I'm new to Quantum ESPRESSO and I have read that there are several scenarios when &lt;strong&gt;relax&lt;/strong&gt; calculations are preferred over &lt;strong&gt;vc-relax&lt;/strong&gt; calculations, for example in maintaining vacuum while modelling surface. Is there any other scenario wherein I'd probably use &lt;strong&gt;vc-relax&lt;/strong&gt; over &lt;strong&gt;relax&lt;/strong&gt;. Or can I get away with just a relax calculation? Since &lt;strong&gt;vc-relax&lt;/strong&gt; calculations are computationally more expensive.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="7" LastEditDate="2021-01-02T20:30:57.010" LastActivityDate="2021-01-02T20:30:57.010" Title="When should &quot;vc-relax&quot; be performed over &quot;relax&quot; calculations in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|geometry-optimization|cell-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2360" PostTypeId="2" ParentId="2358" CreationDate="2020-09-24T01:00:45.343" Score="15" Body="&lt;p&gt;'vc-relax' and 'relax' are two quite different functionalities of the PW module. 'vc' stands for 'variable cell', so the cell shape (angles and length) as well as the atomic coordinates are optimized. Both the forces and stress tensor are calculated in 'vc-relax'. 'relax' only does the atomic coordinates optimization, i.e., only the forces are calculated. which tag to choose depends on your system and properties that you are looking for. For example, for phonon calculations, you mush use 'vc-relax' to fully relax the force and stress to get rid of any imaginary frequency issue.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2020-09-24T01:00:45.343" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2361" PostTypeId="2" ParentId="2350" CreationDate="2020-09-24T17:21:26.523" Score="9" Body="&lt;p&gt;First, I would recommend reading through the pw.scf input file description, provided &lt;a href=&quot;http://www.quantum-espresso.org/Doc/INPUT_PW.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The relevant parameters are in the &amp;amp;SYSTEM namelist of the input file. To do a basic, linear spin-polarized calculation, you would need to set at least two additional parameters. If I have two types of atom, say, Fe and O, then if Fe is listed first under atomic types (it is type '1'), then the additional parameters you need to set are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nspin = 2&#xA;starting_magnetization(1) = 0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you want to change the magnetic ordering, such as the various antiferromagnetic possibilities, or in general study different magnetizations on different atoms of the same type, you need to define different atomic types for the same element, such as Fe1, Fe2, etc. So you could have&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nspin = 2&#xA;starting_magnetization(1) = 0.5&#xA;starting_magnetization(2) = -0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where atomic type 1 is &amp;quot;Fe1&amp;quot;, and type 2 is &amp;quot;Fe2&amp;quot;. Keep in mind this isn't a constraint, it's just a starting point that hopefully leads you to a certain local minimum.&lt;/p&gt;&#xA;&lt;p&gt;There are many parameters relevant for magnetic systems. It's worth going through the documentation carefully to understand what is available (non-collinear magnetism, spin-orbit coupling, starting charge, occupation matrices with DFT+&lt;em&gt;U&lt;/em&gt;, etc.)&lt;/p&gt;&#xA;&lt;p&gt;I can't comment on half-metallicity prediction since I'm not familiar with the topic, but hopefully this can get you going in the right direction with starting your calculations.&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-09-24T17:33:16.197" LastActivityDate="2020-09-24T17:33:16.197" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2362" PostTypeId="2" ParentId="2347" CreationDate="2020-09-24T18:26:23.807" Score="8" Body="&lt;p&gt;To build on the other good answers here, there are also numerous ways to generate k-point grids.&lt;/p&gt;&#xA;&lt;p&gt;The most common method (described here) is Monkhorst-Pack, which is the method you'll see in typical DFT tutorials.&lt;/p&gt;&#xA;&lt;p&gt;However, there are now better methods, called &amp;quot;generalized k-point grids&amp;quot;, for these techniques see:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.93.155109&quot; rel=&quot;noreferrer&quot;&gt;Wisesa, Pandu, Kyle A. McGill, and Tim Mueller. &amp;quot;Efficient generation of generalized Monkhorst-Pack grids through the use of informatics.&amp;quot; Physical Review B 93.15 (2016): 155109.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0927025618304105&quot; rel=&quot;noreferrer&quot;&gt;Morgan, Wiley S., et al. &amp;quot;Efficiency of generalized regular k-point grids.&amp;quot; Computational Materials Science 153 (2018): 424-430.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0927025619306391&quot; rel=&quot;noreferrer&quot;&gt;Morgan, Wiley S., et al. &amp;quot;Generalized regular k-point grid generation on the fly.&amp;quot; Computational Materials Science 173 (2020): 109340.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and articles cited therein.&lt;/p&gt;&#xA;&lt;p&gt;Practically, to generate grids using this technique, you can use the Mueller research groups's &lt;a href=&quot;http://muellergroup.jhu.edu/K-Points.html&quot; rel=&quot;noreferrer&quot;&gt;k-point server or kplib&lt;/a&gt; (an interface for which exists in &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt;, or you can use &lt;a href=&quot;https://github.com/msg-byu/autoGR&quot; rel=&quot;noreferrer&quot;&gt;autoGR&lt;/a&gt; from Gus Hart's group.&lt;/p&gt;&#xA;&lt;p&gt;Typically, these techniques &lt;em&gt;are&lt;/em&gt; better than Monkhorst-Pack, but if you're only doing one or two calculations the advice to run with a fine Monkhorst-Pack grid might just be easier, especially if you're starting out (e.g. using the Materials Cloud Quantum Espresso link posted by Jack, or using the VASP input sets in &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; to give recommended grid densities). Convergence tests are always recommended, and in general Gamma-centered grids are preferred (the economy of shifting the grid is not worth the loss of the Gamma point, in my opinion, better to just run with a slightly higher grid density).&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2020-09-24T18:26:23.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2363" PostTypeId="1" AcceptedAnswerId="2367" CreationDate="2020-09-11T16:28:19.843" Score="13" ViewCount="429" Body="&lt;p&gt;In many of the free/open-source QM programs like GAMESS, ORCA, NWChem, the calculation of analytic hessians is not possible when a meta-GGA density functional is used, like M06-2X. My first question is — why is this? Why do meta-GGA functionals not have analytic hessians?&lt;/p&gt;&#xA;&lt;p&gt;However, when I used Gaussian 16, I have found that it can calculate analytic hessians for M06-2X as well. My first guess was that Gaussian was automatically shifting to numerical calculation, but after reading the output file, it seems that Gaussian is performing CPHF on M06-2X (or some variation of CPHF, I am new to all of this). This should not be possible. So how does Gaussian do it?&lt;/p&gt;&#xA;&lt;p&gt;Does it have something to with the coding of the programs or the theory of the m-GGA method itself?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; At the time I wrote the question, Orca 4.2.1 did not have analytic hessians for m-GGA functionals. However, the most recent update, Orca 5.0, made m-GGA analytic hessians available.&lt;/p&gt;&#xA;" OwnerUserId="1380" OwnerDisplayName="Shoubhik R Maiti" LastEditorUserId="1380" LastEditDate="2021-08-01T14:46:03.927" LastActivityDate="2021-08-03T13:32:22.547" Title="Analytic Hessians for meta-GGA functionals" Tags="|quantum-chemistry|computational-chemistry|density-functional-theory|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2364" PostTypeId="2" ParentId="2363" CreationDate="2020-09-12T08:10:51.520" Score="10" Body="&lt;p&gt;Meta-GGA density functionals are dependent on the kinetic energy density&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tau_\sigma (\mathbf{r}) = \sum_i^\text{occ} \frac{1}{2} \lvert \nabla \phi_{\sigma,i} (\mathbf{r}) \rvert^2&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\phi_{\sigma,i} (\mathbf{r})$&lt;/span&gt; are Kohn-Sham orbitals.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; Certain spatial derivatives of this quantity will be necessary for the calculation of the Hessian and I have been told that achieving the necessary accuracy in the grid-based calculation is non-trivial.&lt;/p&gt;&#xA;&lt;p&gt;Personally, I believe that this is down to most people assuming that little value is gained by mGGA frequencies over GGA frequencies. Of course, one should ideally use the Hessian to verify that one has reached a local minimum in one's geometry optimization, but beyond this, the usefulness may be limited. Therefore, development resources are directed elsewhere.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; Piotr de Silva, Clémence Corminboeuf, &amp;quot;Communication: A new class of non-empirical explicit density functionals on the third rung of Jacob’s ladder,&amp;quot; &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2015&lt;/strong&gt;, &lt;em&gt;143&lt;/em&gt;, 111105 (&lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.4931628&quot; rel=&quot;noreferrer&quot;&gt;PDF&lt;/a&gt;), &lt;a href=&quot;http://dx.doi.org/10.1063/1.4931628&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1063/1.4931628&lt;/a&gt;. Note that some authors use a different prefactor.&lt;/p&gt;&#xA;" OwnerUserId="794" OwnerDisplayName="TAR86" LastActivityDate="2020-09-13T16:25:02.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2365" PostTypeId="2" ParentId="2278" CreationDate="2020-09-24T20:25:54.663" Score="5" Body="&lt;p&gt;I second nglview for any kind of molecular visualization, it's fast and works well with large simulations.&lt;/p&gt;&#xA;&lt;p&gt;For atomistic visualization of crystal structures (e.g. small-cell inorganic crystals), &lt;a href=&quot;https://docs.crystaltoolkit.org/jupyter.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Crystal Toolkit&lt;/a&gt; has a nice Jupyter integration that is closely integrated into &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;pymatgen&lt;/a&gt;. This option is intended for people doing materials science and who want direct, literal visualizations of the Python objects they're working with, e.g. unit cells, specific defined bonds, charge density isosurfaces, color-coding by site properties, etc.&lt;/p&gt;&#xA;&lt;p&gt;(As a disclaimer, I develop Crystal Toolkit, a work-in-progress with more docs coming soon, but I'm happy to answer questions.)&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="1333" LastEditDate="2020-09-26T17:21:59.533" LastActivityDate="2020-09-26T17:21:59.533" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2366" PostTypeId="2" ParentId="305" CreationDate="2020-09-25T00:31:52.330" Score="11" Body="&lt;p&gt;Time-evolution of conceptual DFT quantities has been considered starting, I think, with Chattaraj ~2000. (I imagine there is some earlier work by Ghosh and/or Harbola, but I do not know a reference.) Example references: IJQC v91 633 (2003); J. Phys. Chem. A (Feature article) v21, 4513 (2019); Chapter 13 in &amp;quot;Theoretical Aspects of Chemical Reactivity&amp;quot; (ed. by Toro-Labbe, Elsevier, 2007). The issue is discussed (with more references) in the recent round-table perspective article Theoretical Chemistry Accounts v139, 36 (2020).&lt;/p&gt;&#xA;&lt;p&gt;I do not really see much issue at a superficial level, though for the purpose of describing chemical reactions the more typical approach is that, instead of considering time-dependence, instead one looks at how reactivity indicators change along a reaction path (which, in the limit of zero temperature, represents a sort of &amp;quot;leading line&amp;quot; about which reactive trajectories cluster). This is primarily represented in the work of Chattaraj and especially Toro-Labbe (1990s-present). Looking at chemical reactivity indicators along a minimum-energy-path (functionally but not quite mathematically equivalently, the IRC) tends to give a clearer picture of the driving forces of a reaction because one can never be certain that a given reactive trajectory (time-dependent path) is representative, and it is likely that there is some &amp;quot;sloshing&amp;quot; around the reactant/product wells that may obfuscate the interpretation. The Toro-Labbe group, especially, has made excellent use of this strategy. Of course, there are always the necessary caveat that correlation and causality are inequivalent.&lt;/p&gt;&#xA;&lt;p&gt;For photochemistry (e.g., the work of Christophe Morell) or truly dynamic (e.g. scattering) processes, it seems more interesting to me to look at the time-dependent quantities. At a superficial level, one can derive an &lt;em&gt;analogue&lt;/em&gt; of the reactivity indicators using the same strategy, namely differentiation of the energy (of the ground or any other stationary state) with respect to the number of electrons and/or the (possibly time-dependent) external potential. This was done by Chattaraj and Poddar (1990s), Ayers &amp;amp; Parr (~2000), and Davidson, Johnson, and Yang (in a different context, ~2010). For a nondegenerate stationary state, the chemical potential and all other reativity indicators are cleanly defined as responses (and the same treatment that Cardenas, Cedillo, Bultinck, and Ayers developed for quasi-degenerate states could be extended), only requiring a suitable (Gorling, Nagy, Levy, Ayers) definition of the time-independent excited-state DFT functional. (The Theophilou, Gross, Oliviera, Kohn, Fromager, etc. ensemble excited-state-functional could be used too.) At a formal level, though, the same types of &amp;quot;working formulas&amp;quot; one would ordinarily use would still hold.&lt;/p&gt;&#xA;&lt;p&gt;To make treatments of time-dependent reactivity indicators more rigorous one would need to leave the usual energy-based formulations behind, and move to the action (cf. the work of van Leeuwen); matters may be much more complicated (but if one wishes to be rigorous about differentiation in DFT, matters are always complicated anyway). My intuition is that, but for some mathematical niceties/footnotes, the &amp;quot;working formulas&amp;quot; of conceptual DFT would remain essentially unchanged.&lt;/p&gt;&#xA;" OwnerUserId="1376" LastActivityDate="2020-09-25T00:31:52.330" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2367" PostTypeId="2" ParentId="2363" CreationDate="2020-09-25T10:00:58.073" Score="9" Body="&lt;p&gt;To clarify the statements at the beginning of the question, at variance to NWChem which truly is &lt;a href=&quot;https://en.wikipedia.org/wiki/Free_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;free software&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;although the source code for GAMESS is available if you sign the license agreement, it is not open-source or free software, while&lt;/li&gt;&#xA;&lt;li&gt;ORCA is neither open source nor free software (it is available at no cost for academic users)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As to the claim about the lack of analytic Hessians for meta-GGAs in free software, this is true: in addition to NWChem, analytic Hessians for meta-GGAs are also missing in PySCF and Psi4.&lt;/p&gt;&#xA;&lt;p&gt;There's no &lt;em&gt;a priori&lt;/em&gt; reason for this: there's nothing that prevents analytic Hessians in Gaussian-basis codes, since it is perfectly possible to compute gradients and Hessians from the variational energy functional expressed in the atomic-orbital basis, see e.g. Pople et al in &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/000926149285009Y&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Phys. Lett. 199, 557 (1992)&lt;/a&gt;. The key point here is that since the orbitals are expanded in terms of analytical functions, we can compute whatever derivatives we want!&lt;/p&gt;&#xA;&lt;p&gt;If you do the calculation, it turns out that gradients can be computed just from the knowledge of the self-consistent field wave function just like in Hartree-Fock, whereas to compute Hessians you also need to solve for the perturbation in the wave function with the coupled-perturbed approach (this is what you see in Gaussian).&lt;/p&gt;&#xA;&lt;p&gt;Now, the reason why meta-GGA Hessians are not available in most codes is that the implementation gets quite hairy. If you have an LDA, the inputs are the spin densities, &lt;span class=&quot;math-container&quot;&gt;$n_\uparrow$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n_\downarrow$&lt;/span&gt;. For GGAs, you add the reduced gradients &lt;span class=&quot;math-container&quot;&gt;$\gamma_{\sigma \sigma'} = \nabla n_\sigma \cdot \nabla n_{\sigma'}$&lt;/span&gt;; that is, &lt;span class=&quot;math-container&quot;&gt;$\gamma_{\uparrow \uparrow}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma_{\uparrow \downarrow} = \gamma_{\downarrow \uparrow}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma_{\downarrow \downarrow}$&lt;/span&gt;, and for meta-GGAs also &lt;span class=&quot;math-container&quot;&gt;$\tau_\uparrow$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\tau_\downarrow$&lt;/span&gt;. This means that you have 2 input variables for LDAs, 5 for GGAs and 7 for meta-GGAs, meaning you have 2, 5, and 7 first derivatives for LDAs, GGAs, and meta-GGAs, respectively, which will be contracted with something that looks like the electron density to get the nuclear gradient.&lt;/p&gt;&#xA;&lt;p&gt;For the Hessian, you get more terms. For meta-GGAs you can pick the first index in 7 ways, and the second index in 6 ways; eliminating the permutation of the two gives 21 second derivatives of the exchange-correlation function. (Compare this to GGAs that only have 10 terms, or LDAs that only have 1 term!)   But, this is not the whole story: the above pertains only to the change in the exchange-correlation energy; you also get the coupling term of the density response (i.e. first derivative of electron density with respect to perturbation) with the gradient of the exchange-correlation energy; this is not symmetric so it would appear to add 7*7=49 more terms, bringing the total up to 70 terms.&lt;/p&gt;&#xA;&lt;p&gt;The implementation of analytical Hessians is painstaking work, and since there's no new science in it, it just hasn't been a priority in free software programs. Analytical Hessians are available in commercial codes like Gaussian and Q-Chem, because they are needed for many routine applications in industry.&lt;/p&gt;&#xA;&lt;p&gt;Things might change in the future, though: although laborious, the implementation of the analytic Hessians is straightforward. It's just a question of someone dedicating a few weeks of their time to write down the equations, implement them, and check that they are correct by finite differences...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-08-03T13:32:22.547" LastActivityDate="2021-08-03T13:32:22.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2368" PostTypeId="1" AcceptedAnswerId="2383" CreationDate="2020-09-25T14:36:42.537" Score="11" ViewCount="1083" Body="&lt;p&gt;What's the crystal orbital Hamiltonian population (COHP) or the crystal orbital overlap population (COOP)? What's the relation between the bandstructure or density of states (DOS) and COHP/COOP? Why we can read the information about bonding or antibonding information from COHP and COOP?&lt;/p&gt;&#xA;&lt;p&gt;A clear physical picture will be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-28T14:34:36.267" Title="What's the crystal orbital Hamiltonian population?" Tags="|density-functional-theory|vasp|band-structure|density-of-states|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2369" PostTypeId="1" CreationDate="2020-09-25T20:58:04.777" Score="6" ViewCount="315" Body="&lt;p&gt;I'm new to the Quantum ESPRESSO package. There are articles outlining the procedure of indirectly simulating the P-E loop of piezo-electric materials via Berry phase calculations.One procedure is indicated below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Perform a set of finite field calculations and plot the stress vs applied electric field, then the slope at zero field gives you the piezoelectric coefficients. For a more elegant solution, you can check the following paper: S. de Gironcoli et al. PRL 62, 2853 (1989)&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;But I couldn't find any explicit step-wise procedure for simulating the P-E loop.&lt;/strong&gt; So any help regarding the topic will be good.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2021-10-30T20:12:14.293" LastActivityDate="2021-10-30T20:12:14.293" Title="Is there any way to simulate the Polarization vs Electric Field loop of BaTiO3 using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|berry-phase|electric-field|polarizability|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-26T00:03:18.940" ContentLicense="CC BY-SA 4.0" />
  <row Id="2370" PostTypeId="1" AcceptedAnswerId="2372" CreationDate="2020-09-26T14:50:51.170" Score="13" ViewCount="850" Body="&lt;p&gt;I have performed the DFT calculation for Silicon in Quantum ESPRESO. I have tried to calculate the electronic band structure, the shape of wiggles of bands are mostly matching but the energy values are not matching with the referenced literatures. I have attached the figure of the calculated band structure by me.&lt;a href=&quot;https://i.stack.imgur.com/GznYc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GznYc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It's valance bands are going above the '0' value, which is not correct.&lt;br /&gt;&#xA;Please, suggest me how I can resolve this energy value issue. It will be helpful in my learning process.&lt;br /&gt;&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-09-26T15:46:54.870" LastActivityDate="2020-09-27T23:23:54.930" Title="Si energy band values are not matching with literature values" Tags="|density-functional-theory|band-structure|quantum-espresso|crystal-structure|brillouin-zone|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2371" PostTypeId="1" CreationDate="2020-09-26T15:04:52.347" Score="7" ViewCount="774" Body="&lt;p&gt;I'm new to molecular dynamics and DFT. The aim was to study the Raman spectra of a molecule in a medium. As we know the Raman spectra of a molecule change due to the induced polarization in the presence of different solvent molecules. Since the GROMACS package can analyse molecules present in different solvents we can create boxes containing the molecule and different solvents. But since I'm new to the software I'm not sure if Raman Spectra generation is possible. Or is there some other software package I could use to fulfil the needs mentioned above.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-10-19T14:44:22.730" LastActivityDate="2020-10-19T14:44:22.730" Title="Is it possible to simulate the Raman spectra via Molecular Dynamics (MD) using the GROMACS package?" Tags="|molecular-dynamics|spectroscopy|gromacs|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2372" PostTypeId="2" ParentId="2370" CreationDate="2020-09-26T15:55:23.617" Score="14" Body="&lt;p&gt;The y-axis corresponds to the direct eigenvalues from your DFT calculation. You need to set the valence band maximum to '0' manually. The DFT output of your calculation will give the highest occupied state energy (or the Fermi energy, if you use occupations smearing). So whatever that energy is, subtract that from the energies in your band plot.&lt;/p&gt;&#xA;&lt;p&gt;A note on the Fermi energy value outputted in DFT codes: it's only really useful in the case of metals, or when likewise there are occupied states at the Fermi level, such as in heterostructures, slabs etc. In insulators and semiconductors, its position within the band gap depends on the smearing and some other computational factors, and isn't physically meaningful.&lt;/p&gt;&#xA;&lt;p&gt;When you do align to the Fermi energy (by defining &lt;span class=&quot;math-container&quot;&gt;$E_F=0$&lt;/span&gt;) in these cases, you should use the value calculated from the scf calculation. Prof. Stefano de Gironcoli answered this question in the Quantum Espresso mailing list (pw_forum):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the ONLY Fermi energy that is meaningful is the one corresponding to a&#xA;scf calculation... which is calculated  consistently with the&#xA;corresponding  charge density.&#xA;All nscf or band calculations are performed  on grids which might  give&#xA;non-regular sampling of the BZ...  you should not use the corresponding&#xA;fermi energy .&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-09-27T23:23:54.930" LastActivityDate="2020-09-27T23:23:54.930" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2373" PostTypeId="2" ParentId="2347" CreationDate="2020-09-26T20:40:29.033" Score="6" Body="&lt;p&gt;This question has been well-answered. But I would like to add in a few points too.&lt;/p&gt;&#xA;&lt;p&gt;In addition to observing the energy, you can also observe the convergence of outputs which are really sensitive to the K_point grid like the crystal pressure which is given by &lt;strong&gt;&amp;quot;P = &amp;quot;&lt;/strong&gt;  above your stress values in your SCF output file. The convergence of such hypersensitive outputs will automatically imply the convergence of other outputs too for various K_point grid values. Moreover, if the bravis-lattice is cubic it's good to choose even values over odd values, for the K_point grid, due to the effect of the Irreducible Brillouin Zone(IBZ) that would essentially give you a higher accuracy but with the same execution time as given below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6GApx.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6GApx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There would be tricks like this for your specific crystal lattice too.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-09-26T20:40:29.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2374" PostTypeId="5" CreationDate="2020-09-26T20:59:06.977" Score="0" Body="&lt;p&gt;There is also this: &lt;a href=&quot;https://apple.stackexchange.com/&quot;&gt;https://apple.stackexchange.com/&lt;/a&gt;, for questions that are more to do with the OS and less to do with scientific computing.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-26T20:59:06.977" LastActivityDate="2020-09-26T20:59:06.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2375" PostTypeId="4" CreationDate="2020-09-26T20:59:06.977" Score="0" Body="Questions related to macOS / iOS." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-26T20:59:06.977" LastActivityDate="2020-09-26T20:59:06.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2376" PostTypeId="5" CreationDate="2020-09-26T21:14:45.873" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-26T21:14:45.873" LastActivityDate="2020-09-26T21:14:45.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2377" PostTypeId="4" CreationDate="2020-09-26T21:14:45.873" Score="0" Body="Questions about high-precision or high-accuracy calculations (even though these two things don't meant he same thing, they are related enough to fit in one tag for now)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-26T21:14:45.873" LastActivityDate="2020-09-26T21:14:45.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2378" PostTypeId="1" CreationDate="2020-09-27T09:35:45.427" Score="11" ViewCount="1193" Body="&lt;p&gt;I am a beginner and have performed the DFT calculation in Quantum ESPRESSO for calculation of the direct and indirect bandgap of Silicon. I found the indirect bandgap to be 0.6551 eV. Now, I have several doubts:&lt;br /&gt;&#xA;1)Is this calculated indirect bandgap at room temp. or at 0K?&lt;br /&gt;&#xA;2)If it is at room temperature the indirect bandgap should be around 1.1 eV as from the literature. So is there any energy correction factor that has to be performed to calculate the actual band gap values?&lt;br /&gt;&#xA;Please, clarify my doubts.&lt;br /&gt;&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-09-27T13:31:24.920" LastActivityDate="2020-09-27T14:51:30.583" Title="Is there an energy gap correction factor that needs to be used in DFT calculations?" Tags="|density-functional-theory|electronic-structure|band-structure|quantum-espresso|brillouin-zone|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2379" PostTypeId="2" ParentId="2378" CreationDate="2020-09-27T10:52:44.393" Score="11" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Is this calculated indirect bandgap at room temp. or at 0K?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;QE is based on the density functional theory (DFT). DFT is a ground-state (0K) theory and hence the calculated bandstructure is 0K.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If it is at room temperature the indirect bandgap should be around 1.1 eV as from the literature. So is there any energy correction factor that has to be performed to calculate the actual band gap values?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;First of all, the DFT with PBE functional will underestimate the bandgap of semiconducting materials, you can correct this by HSE06 calculation or GW calculation. Both HSE06 and GW can give you the bandgap values comparable to the experiment. The temperature effect can not be considered in the framework of DFT.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-09-27T10:52:44.393" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2380" PostTypeId="1" CreationDate="2020-09-27T13:10:26.820" Score="11" ViewCount="126" Body="&lt;p&gt;I'm afraid this question might be too basic or too naive or both, but here goes!&lt;/p&gt;&#xA;&lt;p&gt;For optical diffraction by periodic nano-structures (gratings, semiconductor manufacturing metrology) the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rigorous_coupled-wave_analysis&quot; rel=&quot;noreferrer&quot;&gt;rigorous coupled wave equation&lt;/a&gt; or RCWA (&lt;a href=&quot;http://emlab.utep.edu/pdfs/Poster_RCWA.pdf&quot; rel=&quot;noreferrer&quot;&gt;also&lt;/a&gt;) was sort-of a gold standard until &lt;a href=&quot;https://en.wikipedia.org/wiki/Finite-difference_time-domain_method&quot; rel=&quot;noreferrer&quot;&gt;Finite Difference Time Domain&lt;/a&gt; or FDTD methods were computationally achievable.&lt;/p&gt;&#xA;&lt;p&gt;Analogous to the optical diffraction situation, the dynamical diffraction of electrons and X-rays has been traditionally calculated with static solutions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; Have FDTD methods had inroads into simulation of scattering of electrons and X-rays by crystals for the purposes of comparing to measured patterns and/or spectra?&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;One reason&lt;/em&gt; that I'm asking is that LEED calculations are somewhat of a black box in that much of the code is from the 1980's and '90's and reimplementing them in a modern computational environment in a friendly way (e.g. Python wrapper, calls to standard libraries instead of all those DIY methods) will be hard. While computationally intense, FDTD methods might be somewhat easier to implement using modern techniques; but I'd like to see if this has been tried, and if so with what degree of success.&lt;/p&gt;&#xA;&lt;p&gt;For more on traditional low energy electron diffraction (LEED) simulation see:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/527/201&quot;&gt;Overview of how self-consistent dynamical low-energy electron diffraction simulations are performed&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1793/201&quot;&gt;Simulated low energy electron diffraction (LEED) patterns&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Wikipedia: &lt;a href=&quot;https://en.wikipedia.org/wiki/Dynamical_theory_of_diffraction&quot; rel=&quot;noreferrer&quot;&gt;Dynamical theory of diffraction&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2021-06-11T17:18:23.773" LastActivityDate="2021-06-11T17:18:23.773" Title="Have FDTD methods made inroads into dynamical simulation of electron and/or X-ray scattering by crystals?" Tags="|crystal-structure|crystallography|electron-diffraction|x-ray-diffraction|finite-difference-time-domain|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2381" PostTypeId="2" ParentId="2378" CreationDate="2020-09-27T14:51:30.583" Score="12" Body="&lt;p&gt;I would like to add a few clarifications to Jack's answer:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Standard DFT calculations with fixed ionic positions are actually not even 0 K. A better way to describe them is that they are &lt;em&gt;static lattice&lt;/em&gt; calculations. The difference between static lattice and 0 K is the contribution from quantum zero-point fluctuations. This contribution is generally small, particularly for heavy ions, but can also be sizeable. In the case of silicon, it changes the band gap by about 50 meV.&lt;/li&gt;&#xA;&lt;li&gt;It is actually possible to include the role of temperature in the band gap of a semiconductor using DFT. There are two main contributions to this temperature dependence: thermal expansion and electron-phonon coupling. Both can be calculated using DFT (or beyond-DFT methods), and in the case of silicon you can find details in this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.93.100301&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; [disclaimer: I am the author].&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-09-27T14:51:30.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2382" PostTypeId="2" ParentId="1933" CreationDate="2020-09-28T10:55:21.753" Score="1" Body="&lt;p&gt;As @anyon suggested, I contacted Larry directly. He also directed me to using the archive.org versions of the databases. As soon as I have the time, I'll try to add the databases into an up-to-date database collection to facilitate their use.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-28T10:55:21.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2383" PostTypeId="2" ParentId="2368" CreationDate="2020-09-28T14:34:36.267" Score="6" Body="&lt;p&gt;There is a great description given of COOP in Roald Hoffman's &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0471187100&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Solids and Surfaces: A Chemist's View of Bonding in Extended Structures&lt;/a&gt;. It is sometimes referred to as the Overlap Population Weighted Density of States (OPWDOS) which makes the meaning a bit clearer: its the density of states, weighted by the overlap for a given bond (&lt;span class=&quot;math-container&quot;&gt;$c_ic_jS_{ij}$&lt;/span&gt;). This results in a signed DOS, as the overlap population can be positive or negative. This quantity is similar (though not exactly equivalent) to the molecular concept of bond order, where a positive COOP denotes a favorable/bonding interaction and a negative COOP indicates an unfavorable/antibonding interaction. We can see an example of this below from Hoffman's book, giving an example for a simple hydrogen chain.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yIFGY.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yIFGY.png&quot; alt=&quot;COOP plot of H atom chain&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;COHP, as mentioned in Kevin J.M.'s &lt;a href=&quot;http://schmeling.ac.rwth-aachen.de/cohp/index.php?menuID=2textID=2&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt; is a variation on the same concept, where the weighting is now done based on off-diagonal Hamiltonian elements as opposed to off-diagonal overlap elements. There are apparently advantages to describing binding this way, but I haven't gotten to look at the &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/j100135a014&quot; rel=&quot;noreferrer&quot;&gt;original COHP paper&lt;/a&gt; to see why it is better than COOP. One difference to look out for is the COHP plots are generally actually -COHP to make them more comparable with COOP plots. This is because a negative Hamiltonian element would correspond to a favorable interaction.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-09-28T14:34:36.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2384" PostTypeId="1" AcceptedAnswerId="7223" CreationDate="2020-09-28T19:51:30.237" Score="11" ViewCount="234" Body="&lt;p&gt;I am trying to determine the optical properties of bulk Aluminium and related alloys using Quantum ESPRESSO. I am using both the epsilon.x and the simple.x modules to get wavelength-dependent dielectric functions. However, when comparing to experimental data, the results are not in good agreement, even trying to adjust the inter and intra-smearing parameters. I simulated and compared the results for Gold and Silver alloys with no major problems (results agreed very well with the experimental ones), but with the Aluminium, I faced lots of difficulties. In the &lt;a href=&quot;https://doi.org/10.1038/s41524-019-0266-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;literature&lt;/a&gt; I found&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;From a convergence study on the dielectric function, we decided to&#xA;employ an interpolation k-grid of 64x64x64 and η = γ = 0,1 eV in&#xA;SIMPLE for each elemental metal considered, with the exception of&#xA;elemental aluminum for which, because of very slow convergence of&#xA;ε_inter with respect to k-point sampling...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Are there any other options beyond increasing the k-sampling and the number of unoccupied bands, to achieve better results?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2021-10-19T20:47:02.617" LastActivityDate="2021-12-09T02:44:26.880" Title="Are there any other options beyond increasing the k-sampling and the number of unoccupied bands, to achieve better results?" Tags="|quantum-espresso|transition-metals|numerical-convergence|optical-properties|metals|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2385" PostTypeId="2" ParentId="2059" CreationDate="2020-09-29T05:56:51.853" Score="7" Body="&lt;h2&gt;iMos&lt;/h2&gt;&#xA;&lt;p&gt;iMos is Ion Mobility Software based on MATLAB parallelized code that can model Collisional Cross-Section. Tool is available for macOS, Linux and Windows and developed by Carlos Larriba-Andaluz. Installer, code comments and tutorials can be found &lt;a href=&quot;http://www.imospedia.com/imos/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="184" LastEditDate="2020-09-30T00:04:07.500" LastActivityDate="2020-09-30T00:04:07.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2386" PostTypeId="1" CreationDate="2020-09-29T09:40:19.293" Score="8" ViewCount="87" Body="&lt;p&gt;Using DFT calculations, how one can predict the new half metallic materials with higher degree of spin polarization. I want to know the steps which have to be followed in prediction of new materials. I have read some research papers on half metallics, but I don't know the exact procedure to start with.I have done some basic DFT calculations on Si, diamond, Fe and Al.&lt;br /&gt;&#xA;Please, someone suggest me where and how to start predicting HMF materials.&lt;br /&gt;&#xA;Thanking you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-10-18T18:41:14.523" LastActivityDate="2020-10-25T14:57:39.760" Title="How to predict new Half Metallic materials with higher degree of spin polarization?" Tags="|density-functional-theory|quantum-espresso|condensed-matter|magnetism|vesta|" AnswerCount="1" CommentCount="4" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2387" PostTypeId="1" CreationDate="2020-09-29T15:46:10.533" Score="13" ViewCount="96" Body="&lt;p&gt;The title is basically my question. Viscoelastic materials are characterized by a constitutive equation between stress and strain involving a convolution integral. This integral is weighted with a relaxation kernel (or memory kernel).&lt;/p&gt;&#xA;&lt;p&gt;Usually, the memory kernel is convex and decreasing (actually, it is often an exponential), but I was wondering if there exist materials for which the memory kernel is nonconvex.&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much to anyone willing to respond!&lt;/p&gt;&#xA;" OwnerUserId="1386" LastEditorUserId="5" LastEditDate="2021-06-22T00:46:57.803" LastActivityDate="2021-06-22T00:46:57.803" Title="A viscoelastic material with nonconvex memory kernel?" Tags="|mathematical-modeling|stress-strain|physical-properties-of-materials|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2389" PostTypeId="1" CreationDate="2020-09-29T20:14:03.200" Score="8" ViewCount="1444" Body="&lt;p&gt;The question is quite simple — how to interpret NBO results of second order perturbation theory analysis? As I have read several papers the most important interactions are &lt;span class=&quot;math-container&quot;&gt;$\pi\rightarrow\pi^{*}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$LP\rightarrow\sigma^{*}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$LP\rightarrow\pi^{*}$&lt;/span&gt;. However, how to check whether they corresponds to resonance or hyperconjugation effect?&lt;/p&gt;&#xA;&lt;p&gt;In the paper of Milenković et al. (10.20450/mjcce.2019.1333), for structure below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/vhx6G.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vhx6G.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A following data of NBO-analysis was gathered:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ieoCv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ieoCv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The authors claim that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The most important interaction (n-π*) energy, related to resonance in the molecule, is electron donation from the LP2(O) atom orbitals to the antibonding acceptor π*(C–C) of the phenyl ring (LP2(O5) → π*(C5–C6) (159.2 kJ mol–1)). This large interaction energy indicates hyperconjugation between the electron-donating oxygen atom and the phenyl ring.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Later similarly:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Besides LP2(O) → π*(C–C) and LP2(O) → σ*(C–C) interactions, strong intra- molecular hyperconjugative interactions are formed by orbital overlap between π(C–C) → π*(C–C) bond orbitals, resulting in intramolecular charge transfer (ICT), which causes stabilization of the system.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The problem for me is how to distinguish hyperconjugation from resonance? I was sure that, quoting wiki –&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... hyperconjugation is the interaction of the electrons in a sigma (σ) orbital (e.g. C–H or C–C) with an adjacent unpopulated non-bonding p or antibonding σ* or π* orbitals to give a pair of extended molecular orbitals.&#xA;Thus, why would LP2(O) → π*(C–C) be hyperconjugation if it is rather resonance?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;I have also found somewhere about &lt;code&gt;Intramolecular Charge Transfer&lt;/code&gt;. Could someone briefly explain how it can be understood and found in this analysis?&lt;/p&gt;&#xA;&lt;p&gt;Kind regards&lt;/p&gt;&#xA;" OwnerDisplayName="user1247" LastEditorUserId="5" LastEditDate="2020-10-18T19:15:59.533" LastActivityDate="2020-10-18T19:15:59.533" Title="How to interpret second order perturbation theory analysis from NBO calculations?" Tags="|density-functional-theory|quantum-chemistry|gaussian|" AnswerCount="0" CommentCount="3" ClosedDate="2021-01-23T13:13:00.920" ContentLicense="CC BY-SA 4.0" />
  <row Id="2390" PostTypeId="1" AcceptedAnswerId="2391" CreationDate="2020-09-30T11:45:22.150" Score="7" ViewCount="562" Body="&lt;p&gt;I am trying to run a SHCI calculation in PYSCF with DICE;&#xA;however, I want to freeze the first two core orbitals and the highest 3 virtual orbitals in a calculation.&lt;/p&gt;&#xA;&lt;p&gt;In other parts of PySCF this can normally be accomplished with the &lt;code&gt;frozen&lt;/code&gt; argument. Here, I am not sure how the frozen argument is implemented.&lt;/p&gt;&#xA;&lt;p&gt;The following is example code taken from: &lt;a href=&quot;https://sanshar.github.io/Dice/usingincasscf.html?highlight=shciscf&quot; rel=&quot;noreferrer&quot;&gt;https://sanshar.github.io/Dice/usingincasscf.html?highlight=shciscf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf&#xA;from pyscf.future.shciscf import shci&#xA;&#xA;# Initialize C2 molecule&#xA;b =  1.243&#xA;mol = gto.Mole()&#xA;mol.build(&#xA;verbose = 5,&#xA;output = None,&#xA;atom = [&#xA;    ['C',(  0.000000,  0.000000, -b/2)],&#xA;    ['C',(  0.000000,  0.000000,  b/2)], ],&#xA;basis = {'C': 'ccpvdz', },&#xA;symmetry = True,&#xA;symmetry_subgroup = 'D2h',&#xA;spin = 0&#xA;)&#xA;&#xA;# Create HF molecule&#xA;mf = scf.RHF( mol )&#xA;mf.conv_tol = 1e-9&#xA;mf.scf()&#xA;&#xA;# Number of orbital and electrons&#xA;norb = 26&#xA;nelec = 8&#xA;&#xA;# Create SHCI molecule for just variational opt.&#xA;# Active spaces chosen to reflect valence active space.&#xA;mch = shci.SHCISCF( mf, norb, nelec )&#xA;mch.fcisolver.mpiprefix = 'mpirun -np 2'&#xA;mch.fcisolver.stochastic = True&#xA;mch.fcisolver.nPTiter = 0&#xA;mch.fcisolver.sweep_iter = [ 0, 3 ]&#xA;mch.fcisolver.DoRDM = True&#xA;mch.fcisolver.sweep_epsilon = [ 5e-3, 1e-3 ]&#xA;e_shci = mch.mc1step()[0]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="786" LastActivityDate="2020-09-30T12:14:44.663" Title="PySCF: Implementing SHCI frozen argument" Tags="|pyscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2391" PostTypeId="2" ParentId="2390" CreationDate="2020-09-30T12:14:44.663" Score="9" Body="&lt;p&gt;Freezing can have two meanings: either freezing the occupation (doubly occupied core orbitals and inactive virtual orbitals), or freezing the spatial orbital in orbital optimization (here: in SHCI-SCF).&lt;/p&gt;&#xA;&lt;p&gt;In the former case, figuring out the number of frozen core orbitals and inactive virtual orbitals is easy: since you are specifying the number of electrons and number of orbitals, you don't need to specify the number of frozen core or frozen virtual orbitals. The number of active occupied orbitals can be determined by counting the electrons, whereas the number of active virtual orbitals is simply the number of active orbitals minus the number of active occupied orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The latter case is also quite simple: you just zero out the update for the frozen orbitals, so that they aren't changed.&lt;/p&gt;&#xA;&lt;p&gt;In PySCF, the &lt;code&gt;frozen&lt;/code&gt; argument appears to refer to the latter case, see e.g. &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/a75bfbbc940f9d0a7ec047468a675221a05111a8/pyscf/mcscf/mc1step.py#L882&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/pyscf/pyscf/blob/a75bfbbc940f9d0a7ec047468a675221a05111a8/pyscf/mcscf/mc1step.py#L882&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This option does not appear to be implemented in the SHCI code &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/pyscf/shciscf/shci.py&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/pyscf/pyscf/blob/master/pyscf/shciscf/shci.py&lt;/a&gt;. It should, however, be quite simple to hack the SHCI code to add support for a &lt;code&gt;frozen&lt;/code&gt; argument by e.g. copy-pasting the freezing code from other methods. You can fork PySCF, make the relevant changes and file a pull request so that the feature becomes available to everyone.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-09-30T12:14:44.663" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2392" PostTypeId="1" AcceptedAnswerId="2402" CreationDate="2020-09-30T14:46:44.410" Score="10" ViewCount="107" Body="&lt;p&gt;Do we have water models so far which are flexible? How good can they model specific properties of water and are they currently used with force fields and in actual simulations?&lt;/p&gt;&#xA;" OwnerUserId="1388" LastEditorUserId="5" LastEditDate="2020-09-30T19:56:12.343" LastActivityDate="2020-10-02T02:15:15.930" Title="What is the state-of-the-art in current flexible water models?" Tags="|molecular-dynamics|forcefields|water|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2393" PostTypeId="1" AcceptedAnswerId="2397" CreationDate="2020-09-30T16:28:41.730" Score="12" ViewCount="698" Body="&lt;p&gt;A follow up question for &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1791/88&quot;&gt;this question&lt;/a&gt;. What are the different properties that can be deduced from a phonon dispersion curve and Phonon DOS? Also if possible explain how to deduce them?&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="792" LastEditDate="2020-10-01T08:47:06.227" LastActivityDate="2020-10-01T08:49:21.490" Title="Phonon dispersion and phonon DOS" Tags="|phonons|phonon-dispersion|phonon-density-of-state|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2394" PostTypeId="5" CreationDate="2020-09-30T19:56:35.167" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-30T19:56:35.167" LastActivityDate="2020-09-30T19:56:35.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2395" PostTypeId="4" CreationDate="2020-09-30T19:56:35.167" Score="0" Body="For modeling of H2O or H2O clusters." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-09-30T19:56:35.167" LastActivityDate="2020-09-30T19:56:35.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2396" PostTypeId="2" ParentId="1791" CreationDate="2020-10-01T01:47:36.293" Score="8" Body="&lt;p&gt;I would like to add some information to Camps's answer. &lt;strong&gt;In essence, the band structure should consider the information about each quantum state obtained by solving the Kohn-Sham equation for the periodic solids.&lt;/strong&gt; The quantum state for solids can be formally expressed as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$|atom, k, orbital,spin\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The band-gap can be considered as global information extracted from the whole band structure while the effective mass can be considered as the deduced information from the local part of the whole band structure.&lt;/p&gt;&#xA;&lt;p&gt;As the state indicated, you can obtain more information from the projected band structure. [If you use VASP, all related information is printed in the PROCAR file.] Therefore, you can know that each state in the band structure is contributed by atom, orbital, and spin. I will give you some examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Project to the atom (PtSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;/MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://i.stack.imgur.com/U2UUd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/U2UUd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Projected to the orbital (PtSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;/MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x7dap.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x7dap.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Projected to the spin (MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://i.stack.imgur.com/QmB4B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QmB4B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Ref:&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5125303?journalCode=apl&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tunable giant Rashba-type spin splitting in PtSe2/MoSe2 heterostructure&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As for the density of states, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; information in each quantum state is integrated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$|atom,orbital,spin\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What information can be obtained is like the band structure.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-20T07:17:48.943" LastActivityDate="2021-03-20T07:17:48.943" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2397" PostTypeId="2" ParentId="2393" CreationDate="2020-10-01T08:49:21.490" Score="12" Body="&lt;p&gt;The phonon dispersion relates the phonon frequencies &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt; for each branch &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; with the phonon wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;, typically along a path in the Brillouin zone joining high-symmetry points. The phonon density of states compresses this information by integrating over &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; and summing over &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;g(\omega)=\sum_{\nu}\int\frac{d\mathbf{q}}{(2\pi)^3}\delta(\omega-\omega_{\mathbf{q}\nu}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and some information is thus lost in the density of states. Quantities that can be extracted from a phonon dispersion include (happy for others to add more to the list):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Speed of sound. The linear slope of the three acoustic branches as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}\to0$&lt;/span&gt; provide the speed of sound propagation in the material.&lt;/li&gt;&#xA;&lt;li&gt;Raman mode frequencies. The Raman mode frequencies are given by some of the optical mode frequencies as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}\to0$&lt;/span&gt;. However, to determine which modes are Raman active you need to complement the dispersion relation with a symmetry analysis of the optical modes, and to determine the intensity of the Raman signal you need to complement the dispersion with a calculation of the Raman activity tensor.&lt;/li&gt;&#xA;&lt;li&gt;Infrared mode frequencies. Similar to Raman frequencies, but with different symmetry rules and intensities.&lt;/li&gt;&#xA;&lt;li&gt;LO-TO splitting. Longitudinal optical modes set up oscillating dipoles that lead to long-range electric fields that split the degeneracy between transverse and optical modes as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}\to0$&lt;/span&gt;. The magnitude of LO-TO splitting depends on the dielectric permitivity and the Born effective charges, so you can assess how polar the material is through the LO-TO splitting.&lt;/li&gt;&#xA;&lt;li&gt;Helmholtz free energy. The phonon contribution to the free energy can be deduced from the phonon dispersion by occupying each phonon mode according to the Bose-Einstein distribution at the corresponding temperature. As this quantity only depends on the phonon energy, this is something that you can also directly extract from the phonon density of states.&lt;/li&gt;&#xA;&lt;li&gt;Dynamical stability. The abscence of imaginary phonon frequencies indicates that the system is dynamically stable (at a local minimum of the potential energy surface). Conversly, if there are imaginary phonon frequencies the system is dynamically unstable. Complementing this information with the atomic displacements of the imaginary modes provides information about the direction in which the structure needs to be distorted to lower its energy.&lt;/li&gt;&#xA;&lt;li&gt;Topological phonons. Although less well-known than their electronic counterparts, phonon dispersions also support a topological classification. For example, you may encounter topologically protected Weyl phonons or nodal line phonons. The dispersion itself will provide the degeneracy points/lines, but for a full classification you need to complement it with a symmetry/topology analysis.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Phonon dispersions also serve as starting points to study phonon-related properties. For example, the inclusion of anharmonic terms (phonon-phonon interactions) can help explore thermal transport or temperature-driven structural phase transitions. The coupling of phonons with electrons (electron-phonon interactions) can help explore electronic transport, superconductivity, carrier relaxation in semiconductors, etc.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-01T08:49:21.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2398" PostTypeId="1" CreationDate="2020-10-01T10:42:50.380" Score="9" ViewCount="1278" Body="&lt;p&gt;I have been using the HPCE on our campus for MD simulations using GROMACS.&#xA;However, when I use the following script, after the job starts to run on the cluster, gets stuck at Step 0 in the log file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#PBS -e errorfile.err&#xA;#PBS -o logfile.log&#xA;#PBS -l walltime=24:00:00&#xA;#PBS -l select=4:ncpus=6&#xA;cd $PBS_O_WORKDIR&#xA;module load intel2020 gromacs2020.1&#xA;gmx mdrun -s npt.tpr -deffnm npt -v     &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The same would run smoothly if I submit the job with high number of processors like 40 or 80. However, there is generally a long queue for such high usage. What could be the reason for the job to not proceed beyond step 0 even after hours for lower number of processors?&lt;/p&gt;&#xA;&lt;p&gt;Example output files when I had terminated the system after 12min. The &lt;code&gt;.err&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    GROMACS:      gmx mdrun, version 2020.1&#xA;    Executable:   /lfs/sware/gromacs2020.1/bin/gmx&#xA;    Data prefix:  /lfs/sware/gromacs2020.1&#xA;    Working dir:  /lfs/usrhome/phd/ch18d408/poly/long/350/1/try&#xA;    Command line:&#xA;      gmx mdrun -s npt.tpr -deffnm npt -v&#xA;    &#xA;    Reading file npt.tpr, VERSION 2020.1 (single precision)&#xA;    Changing nstlist from 10 to 100, rlist from 1 to 1&#xA;    &#xA;    Using 6 MPI threads&#xA;    &#xA;    Non-default thread affinity set, disabling internal thread affinity&#xA;    &#xA;    Using 6 OpenMP threads per tMPI thread&#xA;    &#xA;    starting mdrun 'polymer'&#xA;    500000 steps,   1000.0 ps.&#xA;    &#xA;    step 0&#xA;    &#xA;    Received the TERM signal, stopping within 100 steps&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the &lt;code&gt;.log&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    GROMACS:      gmx mdrun, version 2020.1&#xA;Executable:   /lfs/sware/gromacs2020.1/bin/gmx&#xA;Data prefix:  /lfs/sware/gromacs2020.1&#xA;Working dir:  /lfs/usrhome/phd/ch18d408/poly/long/350/1/try&#xA;Process ID:   15343&#xA;Command line:&#xA;  gmx mdrun -s npt.tpr -deffnm npt -v&#xA;&#xA;GROMACS version:    2020.1&#xA;Verified release checksum is 5cde61b9d46b24153ba84f499c996612640b965eff9a218f8f5e561f94ff4e43&#xA;Precision:          single&#xA;Memory model:       64 bit&#xA;MPI library:        thread_mpi&#xA;OpenMP support:     enabled (GMX_OPENMP_MAX_THREADS = 64)&#xA;GPU support:        CUDA&#xA;SIMD instructions:  AVX_512&#xA;FFT library:        Intel MKL&#xA;RDTSCP usage:       enabled&#xA;TNG support:        enabled&#xA;Hwloc support:      disabled&#xA;Tracing support:    disabled&#xA;C compiler:         /lfs/sware/intel2019/compilers_and_libraries_2019.0.117/linux/mpi/intel64/bin/mpiicc Intel 19.0.0.20180804&#xA;C compiler flags:   -xCORE-AVX512 -qopt-zmm-usage=high -mkl=sequential -std=gnu99 -ip -funroll-all-loops -alias-const -ansi-alias -no-prec-div -fimf-domain-exclusion=14 -qoverride-limits&#xA;C++ compiler:       /lfs/sware/intel2019/compilers_and_libraries_2019.0.117/linux/mpi/intel64/bin/mpiicpc Intel 19.0.0.20180804&#xA;C++ compiler flags: -xCORE-AVX512 -qopt-zmm-usage=high -mkl=sequential -ip -funroll-all-loops -alias-const -ansi-alias -no-prec-div -fimf-domain-exclusion=14 -qoverride-limits -qopenmp&#xA;CUDA compiler:      /lfs/sware/cuda-10.1/bin/nvcc nvcc: NVIDIA (R) Cuda compiler driver;Copyright (c) 2005-2019 NVIDIA Corporation;Built on Sun_Jul_28_19:07:16_PDT_2019;Cuda compilation tools, release 10.1, V10.1.243&#xA;CUDA compiler flags:-std=c++14;-gencode;arch=compute_30,code=sm_30;-gencode;arch=compute_35,code=sm_35;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_35,code=compute_35;-gencode;arch=compute_50,code=compute_50;-gencode;arch=compute_52,code=compute_52;-gencode;arch=compute_60,code=compute_60;-gencode;arch=compute_61,code=compute_61;-gencode;arch=compute_70,code=compute_70;-gencode;arch=compute_75,code=compute_75;-use_fast_math;;-xCORE-AVX512 -qopt-zmm-usage=high -mkl=sequential -ip -funroll-all-loops -alias-const -ansi-alias -no-prec-div -fimf-domain-exclusion=14 -qoverride-limits -qopenmp&#xA;CUDA driver:        0.0&#xA;CUDA runtime:       N/A&#xA;&#xA;&#xA;Running on 1 node with total 40 cores, 40 logical cores (GPU detection deactivated)&#xA;Hardware detected:&#xA;  CPU info:&#xA;    Vendor: Intel&#xA;    Brand:  Intel(R) Xeon(R) Gold 6248 CPU @ 2.50GHz&#xA;    Family: 6   Model: 85   Stepping: 7&#xA;    Features: aes apic avx avx2 avx512f avx512cd avx512bw avx512vl clfsh cmov cx8 cx16 f16c fma hle htt intel lahf mmx msr nonstop_tsc pcid pclmuldq pdcm pdpe1gb popcnt pse rdrnd rdtscp rtm sse2 sse3 sse4.1 sse4.2 ssse3 tdt x2apic&#xA;    Number of AVX-512 FMA units: 2&#xA;  Hardware topology: Only logical processor count&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;M. J. Abraham, T. Murtola, R. Schulz, S. Páll, J. C. Smith, B. Hess, E.&#xA;Lindahl&#xA;GROMACS: High performance molecular simulations through multi-level&#xA;parallelism from laptops to supercomputers&#xA;SoftwareX 1 (2015) pp. 19-25&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;S. Páll, M. J. Abraham, C. Kutzner, B. Hess, E. Lindahl&#xA;Tackling Exascale Software Challenges in Molecular Dynamics Simulations with&#xA;GROMACS&#xA;In S. Markidis &amp;amp; E. Laure (Eds.), Solving Software Challenges for Exascale 8759 (2015) pp. 3-27&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R.&#xA;Shirts, J. C. Smith, P. M. Kasson, D. van der Spoel, B. Hess, and E. Lindahl&#xA;GROMACS 4.5: a high-throughput and highly parallel open source molecular&#xA;simulation toolkit&#xA;Bioinformatics 29 (2013) pp. 845-54&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;B. Hess and C. Kutzner and D. van der Spoel and E. Lindahl&#xA;GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable&#xA;molecular simulation&#xA;J. Chem. Theory Comput. 4 (2008) pp. 435-447&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;D. van der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark and H. J. C.&#xA;Berendsen&#xA;GROMACS: Fast, Flexible and Free&#xA;J. Comp. Chem. 26 (2005) pp. 1701-1719&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;E. Lindahl and B. Hess and D. van der Spoel&#xA;GROMACS 3.0: A package for molecular simulation and trajectory analysis&#xA;J. Mol. Mod. 7 (2001) pp. 306-317&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;H. J. C. Berendsen, D. van der Spoel and R. van Drunen&#xA;GROMACS: A message-passing parallel molecular dynamics implementation&#xA;Comp. Phys. Comm. 91 (1995) pp. 43-56&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;++++ PLEASE CITE THE DOI FOR THIS VERSION OF GROMACS ++++&#xA;https://doi.org/10.5281/zenodo.3685919&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;&#xA;The number of OpenMP threads was set by environment variable OMP_NUM_THREADS to 6&#xA;&#xA;Input Parameters:&#xA;   integrator                     = md&#xA;   tinit                          = 0&#xA;   dt                             = 0.002&#xA;   nsteps                         = 500000&#xA;   init-step                      = 0&#xA;   simulation-part                = 1&#xA;   comm-mode                      = Linear&#xA;   nstcomm                        = 100&#xA;   bd-fric                        = 0&#xA;   ld-seed                        = -464515634&#xA;   emtol                          = 10&#xA;   emstep                         = 0.01&#xA;   niter                          = 20&#xA;   fcstep                         = 0&#xA;   nstcgsteep                     = 1000&#xA;   nbfgscorr                      = 10&#xA;   rtpi                           = 0.05&#xA;   nstxout                        = 0&#xA;   nstvout                        = 0&#xA;   nstfout                        = 0&#xA;   nstlog                         = 500&#xA;   nstcalcenergy                  = 100&#xA;   nstenergy                      = 500&#xA;   nstxout-compressed             = 500&#xA;   compressed-x-precision         = 1000&#xA;   cutoff-scheme                  = Verlet&#xA;   nstlist                        = 10&#xA;   pbc                            = xyz&#xA;   periodic-molecules             = false&#xA;   verlet-buffer-tolerance        = 0.005&#xA;   rlist                          = 1&#xA;   coulombtype                    = PME&#xA;   coulomb-modifier               = Potential-shift&#xA;   rcoulomb-switch                = 0&#xA;   rcoulomb                       = 1&#xA;   epsilon-r                      = 1&#xA;   epsilon-rf                     = inf&#xA;   vdw-type                       = Cut-off&#xA;   vdw-modifier                   = Potential-shift&#xA;   rvdw-switch                    = 0&#xA;   rvdw                           = 1&#xA;   DispCorr                       = EnerPres&#xA;   table-extension                = 1&#xA;   fourierspacing                 = 0.16&#xA;   fourier-nx                     = 128&#xA;   fourier-ny                     = 128&#xA;   fourier-nz                     = 128&#xA;   pme-order                      = 4&#xA;   ewald-rtol                     = 1e-05&#xA;   ewald-rtol-lj                  = 0.001&#xA;   lj-pme-comb-rule               = Geometric&#xA;   ewald-geometry                 = 0&#xA;   epsilon-surface                = 0&#xA;   tcoupl                         = V-rescale&#xA;   nsttcouple                     = 10&#xA;   nh-chain-length                = 0&#xA;   print-nose-hoover-chain-variables = false&#xA;   pcoupl                         = Berendsen&#xA;   pcoupltype                     = Isotropic&#xA;   nstpcouple                     = 10&#xA;   tau-p                          = 2&#xA;   compressibility (3x3):&#xA;      compressibility[    0]={ 4.50000e-05,  0.00000e+00,  0.00000e+00}&#xA;      compressibility[    1]={ 0.00000e+00,  4.50000e-05,  0.00000e+00}&#xA;      compressibility[    2]={ 0.00000e+00,  0.00000e+00,  4.50000e-05}&#xA;   ref-p (3x3):&#xA;      ref-p[    0]={ 3.50000e+02,  0.00000e+00,  0.00000e+00}&#xA;      ref-p[    1]={ 0.00000e+00,  3.50000e+02,  0.00000e+00}&#xA;      ref-p[    2]={ 0.00000e+00,  0.00000e+00,  3.50000e+02}&#xA;   refcoord-scaling               = COM&#xA;   posres-com (3):&#xA;      posres-com[0]=-4.31721e-03&#xA;      posres-com[1]= 2.26425e-01&#xA;      posres-com[2]= 9.22131e-01&#xA;   posres-comB (3):&#xA;      posres-comB[0]=-4.31721e-03&#xA;      posres-comB[1]= 2.26425e-01&#xA;      posres-comB[2]= 9.22131e-01&#xA;   QMMM                           = false&#xA;   QMconstraints                  = 0&#xA;   QMMMscheme                     = 0&#xA;   MMChargeScaleFactor            = 1&#xA;qm-opts:&#xA;   ngQM                           = 0&#xA;   constraint-algorithm           = Lincs&#xA;   continuation                   = false&#xA;   Shake-SOR                      = false&#xA;   shake-tol                      = 0.0001&#xA;   lincs-order                    = 4&#xA;   lincs-iter                     = 1&#xA;   lincs-warnangle                = 30&#xA;   nwall                          = 0&#xA;   wall-type                      = 9-3&#xA;   wall-r-linpot                  = -1&#xA;   wall-atomtype[0]               = -1&#xA;   wall-atomtype[1]               = -1&#xA;   wall-density[0]                = 0&#xA;   wall-density[1]                = 0&#xA;   wall-ewald-zfac                = 3&#xA;   pull                           = false&#xA;   awh                            = false&#xA;   rotation                       = false&#xA;   interactiveMD                  = false&#xA;   disre                          = No&#xA;   disre-weighting                = Conservative&#xA;   disre-mixed                    = false&#xA;   dr-fc                          = 1000&#xA;   dr-tau                         = 0&#xA;   nstdisreout                    = 100&#xA;   orire-fc                       = 0&#xA;   orire-tau                      = 0&#xA;   nstorireout                    = 100&#xA;   free-energy                    = no&#xA;   cos-acceleration               = 0&#xA;   deform (3x3):&#xA;      deform[    0]={ 0.00000e+00,  0.00000e+00,  0.00000e+00}&#xA;      deform[    1]={ 0.00000e+00,  0.00000e+00,  0.00000e+00}&#xA;      deform[    2]={ 0.00000e+00,  0.00000e+00,  0.00000e+00}&#xA;   simulated-tempering            = false&#xA;   swapcoords                     = no&#xA;   userint1                       = 0&#xA;   userint2                       = 0&#xA;   userint3                       = 0&#xA;   userint4                       = 0&#xA;   userreal1                      = 0&#xA;   userreal2                      = 0&#xA;   userreal3                      = 0&#xA;   userreal4                      = 0&#xA;   applied-forces:&#xA;     electric-field:&#xA;       x:&#xA;         E0                       = 0&#xA;         omega                    = 0&#xA;         t0                       = 0&#xA;         sigma                    = 0&#xA;       y:&#xA;         E0                       = 0&#xA;         omega                    = 0&#xA;         t0                       = 0&#xA;         sigma                    = 0&#xA;       z:&#xA;         E0                       = 0&#xA;         omega                    = 0&#xA;         t0                       = 0&#xA;         sigma                    = 0&#xA;     density-guided-simulation:&#xA;       active                     = false&#xA;       group                      = protein&#xA;       similarity-measure         = inner-product&#xA;       atom-spreading-weight      = unity&#xA;       force-constant             = 1e+09&#xA;       gaussian-transform-spreading-width = 0.2&#xA;       gaussian-transform-spreading-range-in-multiples-of-width = 4&#xA;       reference-density-filename = reference.mrc&#xA;       nst                        = 1&#xA;       normalize-densities        = true&#xA;       adaptive-force-scaling     = false&#xA;       adaptive-force-scaling-time-constant = 4&#xA;grpopts:&#xA;   nrdf:       31229&#xA;   ref-t:         298&#xA;   tau-t:         0.5&#xA;annealing:          No&#xA;annealing-npoints:           0&#xA;   acc:            0           0           0&#xA;   nfreeze:           N           N           N&#xA;   energygrp-flags[  0]: 0&#xA;&#xA;Changing nstlist from 10 to 100, rlist from 1 to 1&#xA;&#xA;&#xA;Initializing Domain Decomposition on 6 ranks&#xA;Dynamic load balancing: locked&#xA;Minimum cell size due to atom displacement: 0.703 nm&#xA;Initial maximum distances in bonded interactions:&#xA;    two-body bonded interactions: 0.403 nm, LJ-14, atoms 30848 30853&#xA;  multi-body bonded interactions: 0.403 nm, Ryckaert-Bell., atoms 30853 30848&#xA;Minimum cell size due to bonded interactions: 0.443 nm&#xA;Maximum distance for 5 constraints, at 120 deg. angles, all-trans: 0.764 nm&#xA;Estimated maximum distance required for P-LINCS: 0.764 nm&#xA;This distance will limit the DD cell size, you can override this with -rcon&#xA;Scaling the initial minimum size with 1/0.8 (option -dds) = 1.25&#xA;Using 0 separate PME ranks, as there are too few total&#xA; ranks for efficient splitting&#xA;Optimizing the DD grid for 6 cells with a minimum initial size of 0.956 nm&#xA;The maximum allowed number of cells is: X 20 Y 20 Z 20&#xA;Domain decomposition grid 6 x 1 x 1, separate PME ranks 0&#xA;PME domain decomposition: 6 x 1 x 1&#xA;Domain decomposition rank 0, coordinates 0 0 0&#xA;&#xA;The initial number of communication pulses is: X 1&#xA;The initial domain decomposition cell size is: X 3.33 nm&#xA;&#xA;The maximum allowed distance for atoms involved in interactions is:&#xA;                 non-bonded interactions           1.000 nm&#xA;(the following are initial values, they could change due to box deformation)&#xA;            two-body bonded interactions  (-rdd)   1.000 nm&#xA;          multi-body bonded interactions  (-rdd)   1.000 nm&#xA;              virtual site constructions  (-rcon)  3.333 nm&#xA;  atoms separated by up to 5 constraints  (-rcon)  3.333 nm&#xA;&#xA;When dynamic load balancing gets turned on, these settings will change to:&#xA;The maximum number of communication pulses is: X 1&#xA;The minimum size for domain decomposition cells is 1.000 nm&#xA;The requested allowed shrink of DD cells (option -dds) is: 0.80&#xA;The allowed shrink of domain decomposition cells is: X 0.30&#xA;The maximum allowed distance for atoms involved in interactions is:&#xA;                 non-bonded interactions           1.000 nm&#xA;            two-body bonded interactions  (-rdd)   1.000 nm&#xA;          multi-body bonded interactions  (-rdd)   1.000 nm&#xA;              virtual site constructions  (-rcon)  1.000 nm&#xA;  atoms separated by up to 5 constraints  (-rcon)  1.000 nm&#xA;&#xA;Using 6 MPI threads&#xA;&#xA;Non-default thread affinity set, disabling internal thread affinity&#xA;&#xA;Using 6 OpenMP threads per tMPI thread&#xA;&#xA;System total charge: -0.000&#xA;Will do PME sum in reciprocal space for electrostatic interactions.&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee and L. G. Pedersen &#xA;A smooth particle mesh Ewald method&#xA;J. Chem. Phys. 103 (1995) pp. 8577-8592&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;Using a Gaussian width (1/beta) of 0.320163 nm for Ewald&#xA;Potential shift: LJ r^-12: -1.000e+00 r^-6: -1.000e+00, Ewald -1.000e-05&#xA;Initialized non-bonded Coulomb Ewald tables, spacing: 9.33e-04 size: 1073&#xA;&#xA;Generated table with 1000 data points for 1-4 COUL.&#xA;Tabscale = 500 points/nm&#xA;Generated table with 1000 data points for 1-4 LJ6.&#xA;Tabscale = 500 points/nm&#xA;Generated table with 1000 data points for 1-4 LJ12.&#xA;Tabscale = 500 points/nm&#xA;&#xA;Using SIMD 4x8 nonbonded short-range kernels&#xA;&#xA;Using a 4x8 pair-list setup:&#xA;  updated every 100 steps, buffer 0.000 nm, rlist 1.000 nm&#xA;At tolerance 0.005 kJ/mol/ps per atom, equivalent classical 1x1 list would be:&#xA;  updated every 100 steps, buffer 0.000 nm, rlist 1.000 nm&#xA;&#xA;Using Lorentz-Berthelot Lennard-Jones combination rule&#xA;&#xA;Long Range LJ corr.: &amp;lt;C6&amp;gt; 5.0152e-04&#xA;&#xA;Removing pbc first time&#xA;&#xA;Initializing Parallel LINear Constraint Solver&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;B. Hess&#xA;P-LINCS: A Parallel Linear Constraint Solver for molecular simulation&#xA;J. Chem. Theory Comput. 4 (2008) pp. 116-122&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;The number of constraints is 6385&#xA;There are constraints between atoms in different decomposition domains,&#xA;will communicate selected coordinates each lincs iteration&#xA;&#xA;Linking all bonded interactions to atoms&#xA;There are 18465 inter update-group virtual sites,&#xA;will an extra communication step for selected coordinates and forces&#xA;&#xA;Intra-simulation communication will occur every 10 steps.&#xA;&#xA;++++ PLEASE READ AND CITE THE FOLLOWING REFERENCE ++++&#xA;G. Bussi, D. Donadio and M. Parrinello&#xA;Canonical sampling through velocity rescaling&#xA;J. Chem. Phys. 126 (2007) pp. 014101&#xA;-------- -------- --- Thank You --- -------- --------&#xA;&#xA;There are: 12539 Atoms&#xA;There are: 18465 VSites&#xA;Atom distribution over 6 domains: av 5167 stddev 199 min 4989 max 5507&#xA;&#xA;Constraining the starting coordinates (step 0)&#xA;&#xA;Constraining the coordinates at t0-dt (step 0)&#xA;Center of mass motion removal mode is Linear&#xA;We have the following groups for center of mass motion removal:&#xA;  0:  rest&#xA;RMS relative constraint deviation after constraining: 2.31e-05&#xA;Initial temperature: 300.037 K&#xA;&#xA;Started mdrun on rank 0 Fri Oct  2 15:05:27 2020&#xA;&#xA;           Step           Time&#xA;              0        0.00000&#xA;&#xA;   Energies (kJ/mol)&#xA;          Angle Ryckaert-Bell.  Improper Dih.          LJ-14     Coulomb-14&#xA;    4.45652e+02   -4.13382e+02    2.39002e+00    5.76587e+02    3.22453e+02&#xA;        LJ (SR)  Disper. corr.   Coulomb (SR)   Coul. recip. Position Rest.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can also download the &lt;code&gt;.err&lt;/code&gt; and &lt;code&gt;.log&lt;/code&gt; files &lt;a href=&quot;https://www.dropbox.com/sh/q8qhimo0adag0ry/AABGezTsqwCnNkEcbm6L3W18a?dl=0&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The job would just get killed after the time allocated if I do not terminate.&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2020-10-18T19:23:31.000" LastActivityDate="2020-11-13T15:04:51.257" Title="Why does my calculation using GROMACS get stuck at step 0?" Tags="|molecular-dynamics|high-performance-computing|gromacs|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2399" PostTypeId="1" CreationDate="2020-10-01T13:47:58.583" Score="10" ViewCount="911" Body="&lt;p&gt;I'm a beginner when it comes to DFT and Quantum Espresso.&lt;/p&gt;&#xA;&lt;p&gt;Consider I have a lattice which has associated magnetic properties. So for geometric optimization should I take into account the magnetic character while doing VC-relax in Quantum ESPRESSO. Or can I get reasonable good predictions for DOS and band-structure calculations if I do the VC-relax without taking the magnetic effects into consideration?&lt;/p&gt;&#xA;&lt;p&gt;Apart for that if I am to do VC-relax with the magnetic effects taken into account (nspin = 2) what pseudo-potential should I use?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in Advance.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="7" LastEditDate="2021-01-02T20:33:27.827" LastActivityDate="2021-01-02T20:33:27.827" Title="Should I do vc-relax with nspin=2 in Quantum Espresso for magnetic samples?" Tags="|quantum-espresso|geometry-optimization|density-of-states|nspin|cell-optimization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2400" PostTypeId="1" CreationDate="2020-10-01T18:19:12.910" Score="8" ViewCount="97" Body="&lt;p&gt;I have a &lt;code&gt;.xyz&lt;/code&gt; file for a trajectory and I want to perform block analysis on it, and to find the decorrelation time and to perform analysis on that as well.&lt;/p&gt;&#xA;&lt;p&gt;What software can I use to perform block analysis?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2021-04-21T05:07:40.327" LastActivityDate="2021-04-21T05:07:40.327" Title="What software can perform block analysis on time sequence data?" Tags="|software|software-recommendations|mathematical-modeling|uncertainty-analysis|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2401" PostTypeId="2" ParentId="2283" CreationDate="2020-10-02T00:48:14.503" Score="11" Body="&lt;p&gt;Ok, I figured out the answer, so I will go ahead and answer my own question.&lt;/p&gt;&#xA;&lt;p&gt;First, I will provide an overview in bullet points:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[Optional] Generate the velocities at evenly spaced frames from the geometries by the equation &lt;span class=&quot;math-container&quot;&gt;$\frac{x(t)-x(t-\Delta T)}{n\Delta t}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$x(t)$&lt;/span&gt; is the geometry at time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the lag between frames form the simulation that are saved and &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; is the simulation time step.&lt;/li&gt;&#xA;&lt;li&gt;Read in the velocities generated in the previous step or which were saved from the simulation. Note that it is slightly better to use the ones from the simulation since they will tend to be slightly more accurate due to the fact that after the simulation one does not usually have access to all of the data which one does during the simulation&lt;/li&gt;&#xA;&lt;li&gt;Compute the average &lt;span class=&quot;math-container&quot;&gt;$\langle v(t)v(t+T)\rangle$&lt;/span&gt; (more on this in a minute)&lt;/li&gt;&#xA;&lt;li&gt;Renormalize the above time correlation by its value at &lt;span class=&quot;math-container&quot;&gt;$t=0$&lt;/span&gt;, so that the max value is &lt;span class=&quot;math-container&quot;&gt;$1.0$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Perform a fourier transform of the renormalized velocity autocorrelation function (VACF)&lt;/li&gt;&#xA;&lt;li&gt;Get the discrete frequencies used to build up the fourier transform for plotting purposes&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Detailed Answer:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;First, you need to get your hands on a bunch of velocities which are evenly spaced in time. Typically this time will not be the simulation time, but you will need to know what the time actually is.&lt;/p&gt;&#xA;&lt;p&gt;Now, the original source of my confusion was due to the fact that nearly any paper you read which says they computed the VACF will use the following equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathrm{VACF}=\langle v(0)v(t)\rangle$$&lt;/span&gt;&#xA;This is an incredibly terse notation, normally &lt;span class=&quot;math-container&quot;&gt;$\langle\rangle$&lt;/span&gt; would imply an ensemble average which means you average some quantity for one or many atoms over time. The fact a time average and the true ensemble average are equal is due to the ergodic principle, which I won't describe here.&lt;/p&gt;&#xA;&lt;p&gt;What you are computing in the VACF is really not an ensemble average though. You are averaging over &lt;em&gt;all atoms&lt;/em&gt; and &lt;em&gt;all time lags&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, I will rewrite this equation as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle v(t)v(t+T)\rangle=\sum_{i=1}^{T}\sum_{j=1}^{N}v_j(t_i)\cdot v_j(t_i+n\Delta t)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once again, &lt;span class=&quot;math-container&quot;&gt;$n\Delta t$&lt;/span&gt; is the time-spacing between frames. &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the total length of signal you have (i.e. number of points in the time-series). Notice that since each time windows will be getting shorter as &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; increases, one usually performs the first sum up to &lt;span class=&quot;math-container&quot;&gt;$M/2$&lt;/span&gt; as long as this is long enough that the correlation function has sufficiently decohered within that window. This ensures that one has the same statistical accuracy in each time window by keeping the length of each window the same. One can further increase the accuracy by taking a very long time series as one might get from MD and chopping it into independent segments and averaging the result of the above signal over those independent segments.&lt;/p&gt;&#xA;&lt;p&gt;Finally, one usually renormalizes &lt;span class=&quot;math-container&quot;&gt;$\langle v(t)v(t+T)\rangle$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\langle v(0)v(0)\rangle$&lt;/span&gt;. That is, the first point in the TCF will equal &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; and all other points should be bounded between &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;. This is proper to do since this is a correlation function, and correlations are usually normalized to lie between &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Computational Details:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The pertinent equation I have written up above is quite easy to calculate numerically. It is just two nested for loops. However, this can be extremely slow to calculate as it scales quadratically, and one often has very long time-series and many atoms when doing MD. It turns out, for reasons I won't explain here, that the calculation of either autocorrelation functions or cross-correlation functions can be written in terms of a fourier transform and inverse fourier transform. In that case, rather than directly computing the product as above, one computes a fourier transform of the time series, takes the product of that series with itself, and inverse fourier transforms.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Getting the VDOS:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Going from a correlation function to something more physically meaningful is usually rather simple, as there are many physical observables which are directly related to some kind of TCF. So, to get the VDOS, which is what I happened to be asking about, one simple performs a fourier transform of the VACF. There is a last point which is that the fourier transform builds up a frequency-space representation of a time-domain signal from periodic basis functions (usually it's a complex basis formed of sines and cosines). So, to actually plot the VDOS, which is what you usually want, you need to get the frequencies of these basis functions and the corresponding intensities.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Practical Details:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If all you want are simple auto-correlations and cross-correlations, there is a small python package called &lt;a href=&quot;https://github.com/pdebuyl-lab/tidynamics&quot; rel=&quot;noreferrer&quot;&gt;tidynamics&lt;/a&gt; which can do this. It's also quite easy to implement these correlations calculations using either &lt;a href=&quot;https://pypi.org/project/pyFFTW/&quot; rel=&quot;noreferrer&quot;&gt;pyfftw&lt;/a&gt; or the &lt;a href=&quot;https://numpy.org/doc/stable/reference/routines.fft.html&quot; rel=&quot;noreferrer&quot;&gt;numpy fft module&lt;/a&gt;. Note that to get the frequencies for the VDOS, you need the function &lt;a href=&quot;https://numpy.org/doc/stable/reference/generated/numpy.fft.fftfreq.html#numpy.fft.fftfreq&quot; rel=&quot;noreferrer&quot;&gt;np.fft.fftfreq&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="7" LastEditDate="2020-10-02T04:28:35.957" LastActivityDate="2020-10-02T04:28:35.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2402" PostTypeId="2" ParentId="2392" CreationDate="2020-10-02T02:15:15.930" Score="9" Body="&lt;p&gt;Allow me to begin with a disclaimer: what you have asked is a very contentious question among people who work on water models. I think much more contentious than it should be. Not necessarily because there's an obvious answer, but because there are many people who work on water models who really believe in their own model. The problem is that water is involved in almost everything and no model has been used in all those scenarios.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TLDR:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;People use the MB-Pol potential, developed by the Paesani group, as if it gives you the correct answer for both static and dynamical quantities for water. Indeed, the potential comes very close to doing that for many observable properties and for reference calculations carried out at the coupled-cluster level of theory[1]. The reason I phrased that first sentence as I did is because I have very little doubt that in ten years, there will be some new model which is somehow shown to be slightly more accurate than MB-Pol which becomes the new standard. This is simply the way of things in the water-modelling world.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Some Background:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is almost certain that more models have been developed for water than for any other substance. This is because water itself has many unique properties which need to be understood and because the effect of water as a solvent is often necessary when trying to study some other material.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Rigid Models:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Because one is sometimes only interested in the dielectric properties of water and how they affect some other molecule, there are many rigid, fixed-charge models of water which rely on the Lennard-Jones potential (or something similar) to describe intermolecular interactions. The TIP and SPC families of potentials fall in this class.[2] These are often used in biomolecular simulations. These are definitely not the most accurate water models made, so I will not discuss them further here.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Flexible Models:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I do not know the historical reasons for first creating rigid water models rather than flexible ones, but I suspect it is because introducing flexible bonds and angles causes the potential to be much more expensive to calculate during molecular dynamics (MD) since one essentially introduced many more degrees of freedom into the system. Also, having flexible bonds which vibrate at the high-frequency of an OH stretch greatly decreases the time step one can use in an MD simulation. (There are ways around this using multiple time-stepping algorithms). The most accurate models we have are most definitely flexible models, as these can describe the infrared spectrum of water, more accurately describe hydrogen-bonding, nuclear quantum effects, etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;A Subtlety in Fitting Potentials:&lt;/strong&gt;&#xA;A detail which I think is important to mention is to make a distinction between water models which actually try to model the potential energy surface (PES) of water, and those which are trying to approximate some kind of mean free energy surface via a potential energy function. The TIP4P and SPC models fall into the latter category, as they are parameterized against experimental data. Since the actual potential energy values are not experimentally accessible in any meaningful way, virtually any model which uses experimental data in its parameterization is likely not modelling the PES, but actually has many complex effects &amp;quot;baked in&amp;quot;. All the potentials I discuss from here on will be models of the actual PES of water. This means that, in principle, the dynamics of these potentials should be calculated using path integral simulations to capture nuclear quantum effects. Some papers make this mistake of comparing classical simulations of one of these models to experiment without addressing how quantum nuclei would change the answer.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Classical Potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In my eyes, there are two categories of water models which are both flexible and are true models of the PES. These are what I will call classical models and machine-learning (ML) models. The classical potentials are called as such because they are trying to model the quantum interactions of electron densities via some parameterizable classical model. these typically have only a handful of parameters. What I mean by classical is that the model is most often based on the mutlipole expansion in some way.&lt;/p&gt;&#xA;&lt;p&gt;The best example I am aware of for this category are the Thole-type water models. The most popular of these are TTM2.1-F [3] and TTM3-F [4]. The former of these has more accurate energetics and the latter of these has more accurate dynamics. I know it seems like that shouldn't be possible, but I promise it's true. I think there is an argument to be made (and which is somewhat ongoing in the literature) that TTM2.1-F is about as accurate energetically as any other existing water model, but it has too stiff of bonds, and thus does not reproduce the red-shifts of hydrogen bonded OH stretches properly. These models also both reproduce the opening of the HOH angle going from gas to liquid to ice. No classical model before TTM2-F had done this because the dipole should increase going from gas to liquid to ice, and this is not possible unless the charges on each atom are allowed to vary as a function of the bond length and angle.&lt;/p&gt;&#xA;&lt;p&gt;Another popular family of classical potentials used for water is the AMOEBA model [5]. This has been updated many times and, as far as I know, is quite popular in biomolecular simulations, as I think it is fast and can be mixed with other substances. I will describe in a minute a massive shortcoming of many potentials which is that they can only really describe water interacting with itself.&lt;/p&gt;&#xA;&lt;p&gt;Another excellent feature of classical water models is that even though they attempt to be quantitatively accurate representations of the PES of water, they are still very fast to evaluate. On the other hand, some of the ML potentials I will discuss are much slower than these classical models (but much faster than DFT, for instance).&lt;/p&gt;&#xA;&lt;p&gt;I am sure there are other classical water models worth mentioning, and I will likely update this answer as they get brought up.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Machine Learning Potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Machine Learning (ML) models of water are the type of model being developed most actively. These models almost all try to do some kind of direct fit of the PES of water and hence tend to have literally tens of thousands of parameters. They tend to be slower to evaluate than classical potentials, but also generally more accurate (though it depends on the actual model).&lt;/p&gt;&#xA;&lt;p&gt;As far as I'm aware the first of what I'm calling ML water models is the HBB2 potential from Joel Bowman's group [6]. This model includes a spectroscopically accurate 1-body potential[7], an explicit fit of the 2-body interactions and the 3-body interactions among water molecules. The fit is done via permutationally-invariant polynomials, which at the time was not really considered an ML method, but many would now consider it to be one.&lt;/p&gt;&#xA;&lt;p&gt;The model which built on HBB2 by generating more and more accurate training data is known as MB-Pol and is developed by Francesco Paesani's group[1]. This model includes the same 1-body potential[7] as HBB2, an explicit 2-body potential fit to 40,000 CCSD(T)/CBS water dimer geometries, an explicit 3-body potential fit to 12,000 CCSD(T)/aug-cc-pVTZ water trimer geometries, and a classical treatment of the 4-body and higher-order terms via the multipole expansion. This model has been shown to accurately reproduce many experimentally determined properties of water in all phases[1].&lt;/p&gt;&#xA;&lt;p&gt;There is also a new crop of potentials being produced which are fitted via neural networks (NNs). While these are useful potentials in that they are the only ones discussed which can dissociate (whether or no they do this accurately is not something I've seen addressed in a convincing way). I won't go into much more detail as these are not the most accurate models specifically for water because NNs require massive amounts of data to give reliable results, so any &lt;em&gt;ab initio&lt;/em&gt; NN potentials tend to be trained on DFT calculations. DFT functionals are often parameterized against experiments and/or CCSD(T) calculations, and DFT tends to not do well over the entire phase diagram of water, so I have no problem saying these potentials are not the most accurate ones thus far. They are useful if you need a dissociable model though.&lt;/p&gt;&#xA;&lt;p&gt;I found quite an interesting paper recently which tries to survey the history of modelling water computationally which is called: &amp;quot;Modelling Water: A Lifetime Enigma&amp;quot;.[8] As someone who studies water, I believe this is a very fitting title.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Heterogeneous Simulations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There are two important features which I haven't addressed in detail. One is that water can dissociate. For most simulations of gas and condensed phases of water, dissociation doesn't really matter. It happens so rarely as to be completely negligible. However, there are some problems where the entire effect is predicated on water dissociating. These would include proton transport, water splitting, acid-base reactions, etc. So, the lack of highly-accurate dissociable water potentials is a problem. One recent model is known as Rex-Pon[9]. I am not sure how accurate it is.&lt;/p&gt;&#xA;&lt;p&gt;The second problem is the general utility of these models. The question specifically asked&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;are they currently used with force fields in actual simulations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The answer to this is that it depends. By force fields, I assume you mean the simple molecular mechanics models which usually depend only on a couple of parameters and are common in biomolecular simulations. The problem here is that these potentials are not necessarily compatible with the water models described here. Most potentials need to live in their own world in order to give reliable results. Virtually all of the classical and ML potentials I described can only describe water-water interactions. I am pretty sure AMOEBA is a general potential (i.e. it can describe arbitrary atoms) as is Rex-Pon. The only problem is that general potentials tend to be less accurate, so one has to be very careful to know the limitations of your model and decide if it's useful for the problem at hand.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Another way to answer this question is to say that the whole question of modelling water is an absolute mess. In modelling water, everything is possible, but nothing is certain.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1]: Reddy, S. K., Straight, S. C., Bajaj, P., Huy Pham, C., Riera, M., Moberg, D. R., ... &amp;amp; Paesani, F. (2016). On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice. The Journal of chemical physics, 145(19), 194504.&lt;/p&gt;&#xA;&lt;p&gt;[2]: Paschek, D. (2004). Temperature dependence of the hydrophobic hydration and interaction of simple solutes: An examination of five popular water models. The Journal of chemical physics, 120(14), 6674-6690.&lt;/p&gt;&#xA;&lt;p&gt;[3]: Fanourgakis, G. S., &amp;amp; Xantheas, S. S. (2006). The flexible, polarizable, Thole-type interaction potential for water (TTM2-F) revisited. The Journal of Physical Chemistry A, 110(11), 4100-4106.&lt;/p&gt;&#xA;&lt;p&gt;[4]: Fanourgakis, G. S., &amp;amp; Xantheas, S. S. (2008). Development of transferable interaction potentials for water. V. Extension of the flexible, polarizable, Thole-type model potential (TTM3-F, v. 3.0) to describe the vibrational spectra of water clusters and liquid water. The Journal of chemical physics, 128(7), 074506.&lt;/p&gt;&#xA;&lt;p&gt;[5]: Ren, P., &amp;amp; Ponder, J. W. (2004). Temperature and pressure dependence of the AMOEBA water model. The Journal of Physical Chemistry B, 108(35), 13427-13437.&lt;/p&gt;&#xA;&lt;p&gt;[6]: Shank, A., Wang, Y., Kaledin, A., Braams, B. J., &amp;amp; Bowman, J. M. (2009). Accurate ab initio and “hybrid” potential energy surfaces, intramolecular vibrational energies, and classical ir spectrum of the water dimer. The Journal of chemical physics, 130(14), 144314.&lt;/p&gt;&#xA;&lt;p&gt;[7]: Partridge, H., &amp;amp; Schwenke, D. W. (1997). The determination of an accurate isotope dependent potential energy surface for water from extensive ab initio calculations and experimental data. The Journal of Chemical Physics, 106(11), 4618-4639.&lt;/p&gt;&#xA;&lt;p&gt;[8]: Ouyang, J. F., &amp;amp; Bettens, R. (2015). Modelling water: A lifetime enigma. CHIMIA International Journal for Chemistry, 69(3), 104-111.&lt;/p&gt;&#xA;&lt;p&gt;[9]: Naserifar, S., &amp;amp; Goddard, W. A. (2019). Liquid water is a dynamic polydisperse branched polymer. Proceedings of the National Academy of Sciences, 116(6), 1998-2003.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2020-10-02T02:15:15.930" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2403" PostTypeId="1" CreationDate="2020-10-02T17:41:42.457" Score="5" ViewCount="297" Body="&lt;p&gt;The 4-index 2-electron integral can be obtained for the He atom with the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from pyscf import gto, scf, ao2mo&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = &amp;quot;&amp;quot;&amp;quot;&#xA;    He    0.    0.    0.&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;mol.basis = &amp;quot;cc-pvdz&amp;quot;&#xA;mol.build()&#xA;&#xA;# Run Hartree-Fock.&#xA;mf = scf.RHF(mol)&#xA;mf.kernel()&#xA;&#xA;# Find electron-repulsion integrals (eri).&#xA;eri = ao2mo.kernel(mol, mf.mo_coeff)&#xA;eri = np.asarray(ao2mo.restore(1, eri, mol.nao))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am interested in obtaining the 2-index (A) and 3-index (CIAB) matrices, which can be used to form the 4-index 2-electron (eri) integral.&#xA;I have looked at the list of possible means by which this is accomplished in &lt;a href=&quot;https://sunqm.github.io/pyscf/modules/gto.html?highlight=int1e_ipnuc_sph&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF code&lt;/a&gt;; however, I am unsure of the correct answer.&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2020-10-03T01:52:04.293" LastActivityDate="2023-05-15T07:25:00.017" Title="PySCF: 2-index and 3-index matrix" Tags="|integrals|pyscf|software-assistance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2404" PostTypeId="2" ParentId="2403" CreationDate="2020-10-03T08:47:43.007" Score="4" Body="&lt;p&gt;In the density fitting / resolution-of-the-identity (RI) formalism, a two-electron integral &lt;span class=&quot;math-container&quot;&gt;$(ij|kl)$&lt;/span&gt; in the atomic-orbital basis is approximated as &lt;span class=&quot;math-container&quot;&gt;$(ij|kl) \approx \sum_{PQ} (ij|P) (P|Q)^{-1} (Q|kl)$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; are auxiliary functions, and &lt;span class=&quot;math-container&quot;&gt;$(P|Q)^{-1}$&lt;/span&gt; is the inverse Coulomb overlap matrix.&lt;/p&gt;&#xA;&lt;p&gt;The RI expression can be written in a form that resembles the Cholesky expression &lt;span class=&quot;math-container&quot;&gt;$(ij|kl) = \sum_P L_{ij}^P L_{kl}^P$&lt;/span&gt; by introducing the &amp;quot;B matrix&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$B_{ij}^Q = \sum_P (ij|P) (P|Q)^{-1/2}$&lt;/span&gt;. With the B-matrix, you get the integral as &lt;span class=&quot;math-container&quot;&gt;$(ij|kl) \approx \sum_Q B_{ij}^Q B_{kl}^Q$&lt;/span&gt;. Using this form is convenient since you can use the same implementations for both Cholesky and RI.&lt;/p&gt;&#xA;&lt;p&gt;The density fitting code in PySCF is documentated:&#xA;&lt;a href=&quot;https://pyscf.org/user/df.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pyscf.org/user/df.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;pyscf.df.incore.cholesky_eri&lt;/code&gt; function returns &lt;code&gt;2D array of (naux,nao*(nao+1)/2) in C-contiguous&lt;/code&gt;. This is the &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; matrix.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-05-15T07:25:00.017" LastActivityDate="2023-05-15T07:25:00.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2405" PostTypeId="1" CreationDate="2020-10-03T14:00:18.093" Score="16" ViewCount="981" Body="&lt;p&gt;I have been trying to simulate the properties of Bi&lt;sub&gt;2&lt;/sub&gt;Se&lt;sub&gt;3&lt;/sub&gt;. But the lattice parameters given in Materials Project (which I believe is obtained computationally) is inconsistent with that of experimental data, i.e. a = 4.18976606 (Materials Project) , a=0.413(hq graphene). Even the band gap, which I believe is supposed to be 0.3 eV for bulk structure is different in Materials Project(0.54 eV).&lt;/p&gt;&#xA;&lt;p&gt;So, When do I use the lattice parameter obtained computationally? Also, what is the reason for this difference? What to do if there is no available experimental data?&lt;/p&gt;&#xA;&lt;p&gt;Thank You,&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="1195" LastEditDate="2020-10-03T14:16:02.850" LastActivityDate="2023-12-04T22:59:00.060" Title="When do I use the lattice parameters obtained computationally vs experimentally?" Tags="|density-functional-theory|periodic-system|2d-lattice|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2406" PostTypeId="2" ParentId="2405" CreationDate="2020-10-03T14:40:33.583" Score="10" Body="&lt;p&gt;I will give a quick answer from my experience, but typically you want to use the computed lattice parameter.  The reason for this is that otherwise you induce strain in your computed cell, but in general this is a red flag anyways.  You really want your computed lattice parameter to match if possible which might involve using a different functional or even things such as DFT+U corrections.&lt;/p&gt;&#xA;&lt;p&gt;I am actually not sure of any circumstance where you would want to use the experimental lattice constant over the calculated one.  Maybe someone can list a reason.  Also keep in mind the experimental lattice constant is taken at some experimental conditions, which are not represented in the calculation (frozen geometry, 0K, etc).&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-03T14:40:33.583" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2407" PostTypeId="1" CreationDate="2020-10-03T17:30:24.777" Score="9" ViewCount="170" Body="&lt;p&gt;I am trying to optimize the crystal structure based on Delta SCF. But I am not so familiar with ABINIT at all. As the ABINIT website do not provide further information. It would be super nice if someone could share the input files of ABINIT for Delta SCF. Thanks in advance!&lt;/p&gt;&#xA;&lt;p&gt;Best regards,&#xA;Bo&lt;/p&gt;&#xA;" OwnerUserId="1022" LastEditorUserId="5" LastEditDate="2021-01-22T21:14:15.760" LastActivityDate="2021-01-22T21:14:15.760" Title="How to do a Delta SCF calculation using ABINIT?" Tags="|density-functional-theory|self-consistent-field|software-input-file-request|abinit|" AnswerCount="0" CommentCount="4" ClosedDate="2021-07-29T19:18:18.290" ContentLicense="CC BY-SA 4.0" />
  <row Id="2408" PostTypeId="5" CreationDate="2020-10-03T17:42:48.740" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-04T03:19:37.180" LastActivityDate="2020-10-04T03:19:37.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2409" PostTypeId="4" CreationDate="2020-10-03T17:42:48.740" Score="0" Body="Depricated since it's a typo." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-04T03:19:37.180" LastActivityDate="2020-10-04T03:19:37.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2410" PostTypeId="1" AcceptedAnswerId="3755" CreationDate="2020-10-04T02:08:49.217" Score="8" ViewCount="149" Body="&lt;p&gt;I am considering the relaxation for the following zigzag graphene nanoribbon.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DvJrv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DvJrv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the boundary of the zigzag graphene(C: brown) nanoribbon has been passivated with one H atom. I have performed the spin-polarized and spin-unpolarized calculations with VASP. Surprisingly, I found that the spin-polarized calculation gives me lower total energy. Moreover, the total magnetic momentum can be traced back to the C atom passivated with H atom.&lt;/p&gt;&#xA;&lt;p&gt;Should the zigzag graphene nanoribbon present a spin-polarized ground state? Although the boundary has been passivated. By the way, I have also passivated the boundary with 2 H atoms and then there is net total residual magnetic momentum. Should I use 2 H atoms to passivate the boundary of the zigzag graphene nanoribbon?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-16T11:38:32.537" Title="Why are there some residual magnetic moment on the zigzag graphene nanoribbon passivated with H atom?" Tags="|density-functional-theory|vasp|nspin|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2411" PostTypeId="2" ParentId="2405" CreationDate="2020-10-04T02:56:07.823" Score="8" Body="&lt;p&gt;I have to disagree with the answer of @Tristan.&lt;/p&gt;&#xA;&lt;p&gt;The x-ray diffraction, both powder and single crystal, has enough precision and quality (equipment and software) to give very good and real experimental values.&lt;/p&gt;&#xA;&lt;p&gt;It is well known that very few DFT approximations (methods, functional, pseudopotential, basis set, etc.) give good lattice values. And when we said &lt;em&gt;good&lt;/em&gt;, we mean in agreement with experimental ones (by the way, one of the path to test your simulation results is comparing with experimental ones).&lt;/p&gt;&#xA;&lt;p&gt;So, my advice is always use data from experimental measurements. In this case, from deposited CIF files.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-10-04T02:56:07.823" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="2412" PostTypeId="5" CreationDate="2020-10-04T03:20:19.997" Score="0" Body="&lt;p&gt;Official website of ABINIT: &lt;a href=&quot;https://www.abinit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.abinit.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-04T03:20:19.997" LastActivityDate="2020-10-04T03:20:19.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2413" PostTypeId="4" CreationDate="2020-10-04T03:20:19.997" Score="0" Body="For questions about the software package ABINIT" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-04T03:20:19.997" LastActivityDate="2020-10-04T03:20:19.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2414" PostTypeId="1" CreationDate="2020-10-04T05:37:55.243" Score="9" ViewCount="5316" Body="&lt;p&gt;I want to understand, what is the intuition behind using the occupations='smearing' or 'tetrahedra' in Quantum ESPRESSO input file? I mean how we can interpret what is going to happen inside of crystal structure if I choose this option? How it will affect the band structure and how electrons are going to be filled in orbitals? I want to understand the connection between this input option and its effect on crystal structure.&lt;br /&gt;&#xA;Please, clarify my doubt.&lt;br /&gt;&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2020-10-22T17:53:35.620" Title="What is the physical meaning of occupations='smearing' in Quantum ESPRESSO?" Tags="|density-functional-theory|electronic-structure|quantum-espresso|computational-chemistry|solid-state-physics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2415" PostTypeId="1" AcceptedAnswerId="2416" CreationDate="2020-10-04T10:21:20.207" Score="13" ViewCount="747" Body="&lt;p&gt;I'm trying to learn GAMESS and performing a simple PES scan of oxygen molecule. After the completion of the calculations I get a .log file with lots of sections like that:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ---- SURFACE MAPPING GEOMETRY ----&#xA; COORD 1= 1.500 COORD 2= 0.000&#xA; HAS ENERGY VALUE    -149.438497&#xA; O      0.00000   0.00000   1.25000&#xA; O      0.00000   0.00000   0.25000&#xA; ----------------------------------&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, is it possible to get PES scan result as one table with all of coordinates?&lt;/p&gt;&#xA;&lt;p&gt;Here is my input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=N31 NGAUSS=6 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=UHF RUNTYP=SURFACE MAXIT=50 MULT=3 COORD=ZMT NZVAR=0 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM MWORDS=937 MEMDDI=937 PARALL=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SURF IVEC1(1)=1,2 IGRP1(1)=1 ORIG1=1 DISP1=0.5 NDISP1=10 $&lt;/span&gt;END&#xA;&#xA; $DATA &#xA;O2&#xA;C1&#xA;O  &#xA;O   1   R12&#xA;&#xA;R12 = 0.5&#xA; &lt;span class=&quot;math-container&quot;&gt;$END&#xA; $&lt;/span&gt;ZMAT IZMAT(1)=1,2,1,  $END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1432" OwnerDisplayName="roma ichenko" LastEditorUserId="5" LastEditDate="2021-03-22T16:52:10.987" LastActivityDate="2021-03-22T16:52:10.987" Title="How to get potential energy surface from GAMESS?" Tags="|computational-chemistry|high-performance-computing|gamess|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2416" PostTypeId="2" ParentId="2415" CreationDate="2020-10-04T17:52:20.360" Score="13" Body="&lt;p&gt;I know it is easy to get the PES tabulated very neatly in MOLPRO with a command like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{table,r,scf,ccsd,ccsd_t &#xA;head, R,HF-SCF,CCSD,CCSD(T) &#xA;sort,1,2,3} &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which for a diatomic molecule like yours, gives the following output:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;  R      HF-SCF        CCSD       CCSD(T)&#xA; 1.5 -108.3566620 -108.6007993 -108.6060512&#xA; 1.6 -108.6053845 -108.8602358 -108.8662569&#xA; 1.7 -108.7675654 -109.0332410 -109.0401624&#xA; 1.8 -108.8668845 -109.1435633 -109.1515330&#xA; 1.9 -108.9206732 -109.2086077 -109.2177903&#xA; 2.0 -108.9417215 -109.2412265 -109.2518027&#xA; 2.1 -108.9395089 -109.2509444 -109.2631091&#xA; 2.2 -108.9210615 -109.2448104 -109.2587715 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Someone that uses GAMESS more than me might give an analogous solution for GAMESS.&lt;/p&gt;&#xA;&lt;p&gt;However you might want a very quick solution so that you can get back to working on your project, so below is a solution you can use immediately.&lt;/p&gt;&#xA;&lt;p&gt;The command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep &amp;quot;COORD 1=&amp;quot; gamess.log &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;would give the following type of following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COORD 1= 1.5 COORD 2= 0.000&#xA;COORD 1= 1.6 COORD 2= 0.000&#xA;COORD 1= 1.7 COORD 2= 0.000&#xA;COORD 1= 1.8 COORD 2= 0.000&#xA;COORD 1= 1.9 COORD 2= 0.000&#xA;COORD 1= 2.0 COORD 2= 0.000&#xA;COORD 1= 2.1 COORD 2= 0.000&#xA;COORD 1= 2.2 COORD 2= 0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep &amp;quot;HAS ENERGY VALUE&amp;quot; gamess.log &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;would give the following type of output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;HAS ENERGY VALUE   -108.3566620 &#xA;HAS ENERGY VALUE   -108.6053845 &#xA;HAS ENERGY VALUE   -108.7675654 &#xA;HAS ENERGY VALUE   -108.8668845 &#xA;HAS ENERGY VALUE   -108.9206732 &#xA;HAS ENERGY VALUE   -108.9417215 &#xA;HAS ENERGY VALUE   -108.9395089 &#xA;HAS ENERGY VALUE   -108.9210615 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You then have the R and V(R) values printed in a more convenient way, and you can then chop the rest off easily in VIM, or if you're unfamiliar with VIM you can import this data into Excel or Google Sheets or MATLAB and have the software automatically separate the columns, from which point you can copy and paste the results into a table.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;grep&lt;/code&gt; command can be improved, and combined with clever use of &lt;code&gt;awk&lt;/code&gt; to make the table directly from the command line, but it would be more complicated and my above answer is probably the simplest and most immediate solution without figuring out how to get GAMESS to make the table the way MOLPRO does (if GAMESS can even do it).&lt;/p&gt;&#xA;&lt;p&gt;If anyone wishes to test the above &lt;code&gt;grep&lt;/code&gt; commands or to test their own improvements of them, the above &lt;code&gt;grep&lt;/code&gt; results were done on &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/2415/gamess.log&quot; rel=&quot;noreferrer&quot;&gt;this file&lt;/a&gt; which is now in the &amp;quot;Modeling Matters&amp;quot; GitHub repository.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-04T18:34:52.497" LastActivityDate="2020-10-04T18:34:52.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2417" PostTypeId="1" AcceptedAnswerId="2480" CreationDate="2020-10-04T18:49:37.373" Score="11" ViewCount="485" Body="&lt;p&gt;(I use &lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt; to visualize supercells with the &lt;code&gt;VASP&lt;/code&gt; &lt;code&gt;POSCAR&lt;/code&gt; format.)&lt;/p&gt;&#xA;&lt;p&gt;Consider the following cell which has haunted me:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR&#xA;3.5668661195641991&#xA;  1.00000000 -1.00000000 -1.00000000&#xA;  1.00000000  1.00000000 -1.00000000&#xA;  1.50000000  0.00000000  2.50000000&#xA;   A  B&#xA;   8  24&#xA;Direct&#xA;  1.00000000  1.00000000  1.00000000&#xA;  0.06250000  0.06250000  0.25000000&#xA;  0.65625000  0.15625000  0.12500000&#xA;  0.71875000  0.21875000  0.37500000&#xA;  0.81250000  0.81250000  0.25000000&#xA;  0.15625000  0.65625000  0.12500000&#xA;  0.21875000  0.71875000  0.37500000&#xA;  0.93750000  0.93750000  0.75000000&#xA;  0.12500000  0.12500000  0.50000000&#xA;  0.53125000  0.03125000  0.62500000&#xA;  0.18750000  0.18750000  0.75000000&#xA;  0.59375000  0.09375000  0.87500000&#xA;  0.25000000  0.25000000  1.00000000&#xA;  0.31250000  0.31250000  0.25000000&#xA;  0.37500000  0.37500000  0.50000000&#xA;  0.03125000  0.53125000  0.62500000&#xA;  0.78125000  0.28125000  0.62500000&#xA;  0.43750000  0.43750000  0.75000000&#xA;  0.09375000  0.59375000  0.87500000&#xA;  0.84375000  0.34375000  0.87500000&#xA;  0.90625000  0.40625000  0.12500000&#xA;  0.56250000  0.56250000  0.25000000&#xA;  0.96875000  0.46875000  0.37500000&#xA;  0.62500000  0.62500000  0.50000000&#xA;  0.28125000  0.78125000  0.62500000&#xA;  0.68750000  0.68750000  0.75000000&#xA;  0.34375000  0.84375000  0.87500000&#xA;  0.75000000  0.75000000  1.00000000&#xA;  0.40625000  0.90625000  0.12500000&#xA;  0.50000000  0.50000000  1.00000000&#xA;  0.46875000  0.96875000  0.37500000&#xA;  0.87500000  0.87500000  0.50000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wish to rotate (or transform) this cell so that its non-orthogonal lattice vectors become orthogonal. I'm not sure anymore if this can be done.&lt;/p&gt;&#xA;&lt;p&gt;Required lattice vectors (though, not a 100 % confident if this is what I need):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a` = 1.0 -1.0  0.0&#xA;b` = 1.0  1.0 -2.5&#xA;c` = 2.5  2.5  2.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Original intent: This is a random FCC solid solution (SQS). I want to change the cell so that it looks like a usual FCC supercell.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-10-11T11:35:39.660" LastActivityDate="2020-10-12T20:38:31.283" Title="Lattice representation: change of unit cell" Tags="|visualization-software|vesta|special-quasirandom-structures|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2418" PostTypeId="1" CreationDate="2020-10-05T20:59:59.257" Score="9" ViewCount="108" Body="&lt;p&gt;I have to generate a topology file for a molecule like Sodium Triphosphate, and I do not find forcefields available in the literature. So as a starting point would like to use engines like LigParGen for OPLS. I will have to submit one molecule without the sodium ions.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;As it accepts molecules only upto a charge of -2 and I have a charge of -5, can I consider adding hydrogens to terminal charged oxygens, generate the file, delete the hydrogens and all data related to them under all directives, and add the extra charge back onto the oxygens?&lt;/li&gt;&#xA;&lt;li&gt;Why or why not is this procedure correct?&lt;/li&gt;&#xA;&lt;li&gt;Is there a better way to approach this problem in case of polymers with a lot of charge?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2020-10-05T21:31:46.613" LastActivityDate="2020-10-07T12:08:57.990" Title="Generating topology for charged molecules" Tags="|molecular-dynamics|gromacs|forcefields|polymers|charged-molecules|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2419" PostTypeId="1" CreationDate="2020-10-06T06:42:52.037" Score="8" ViewCount="702" Body="&lt;p&gt;I am a beginner using VASP to do material modeling. I have made a heterostructure model written in the form of a POSCAR file. But the supercell is too big (it contains 60 atoms) so that the computational speed is slow (unreasonably slow) even I put it into the cluster. How can I make an effective INCAR setting to do the calculation in structure relaxation and self-consistent calculation process?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="1218" LastEditDate="2020-10-26T13:27:06.860" LastActivityDate="2020-10-26T13:47:57.990" Title="How to create an effective INCAR setting in VASP for a heterostructure calculation？" Tags="|density-functional-theory|vasp|heterostructures|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2420" PostTypeId="1" AcceptedAnswerId="2421" CreationDate="2020-10-06T15:34:41.813" Score="12" ViewCount="972" Body="&lt;p&gt;How do you calculate the change in dipole moment from the ground to first excited state using ORCA? I have done DFT to get the dipole moment at the ground state and TDDFT of this neutral molecule. How would I get the dipole moment of the first excited state though? I have tried using the keywords to test it out from the ORCA input library example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! Engrad Keepdens&#xA;%maxcore 1000&#xA;%tddft&#xA;  nroots 5 #number of states to be computed&#xA;  Iroot 2 #electing the excited state&#xA;  end &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However in my output file I got two dipole moments. Is one of these the dipole moment of the second excited state?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                            ***************************************&#xA;                            *     ORCA property calculations      *&#xA;                            ***************************************&#xA;&#xA;                                    ---------------------&#xA;                                    Active property flags&#xA;                                    ---------------------&#xA;   (+) Dipole Moment&#xA;&#xA;&#xA;------------------------------------------------------------------------------&#xA;                       ORCA ELECTRIC PROPERTIES CALCULATION&#xA;------------------------------------------------------------------------------&#xA;&#xA;Dipole Moment Calculation                       ... on&#xA;Quadrupole Moment Calculation                   ... off&#xA;Polarizability Calculation                      ... off&#xA;GBWName                                         ... AQx.gbw&#xA;Electron density file                           ... AQx.scfp&#xA;The origin for moment calculation is the CENTER OF MASS  = (19.676450, -8.066302 -0.130676)&#xA;&#xA;-------------&#xA;DIPOLE MOMENT&#xA;-------------&#xA;                                X             Y             Z&#xA;Electronic contribution:     59.75528      40.37126      28.07622&#xA;Nuclear contribution   :    -60.31050     -43.16268     -30.49310&#xA;                        -----------------------------------------&#xA;Total Dipole Moment    :     -0.55522      -2.79142      -2.41688&#xA;                        -----------------------------------------&#xA;Magnitude (a.u.)       :      3.73385&#xA;Magnitude (Debye)      :      9.49069&#xA;&#xA;&#xA;&#xA;--------------------&#xA;Rotational spectrum &#xA;--------------------&#xA; &#xA;Rotational constants in cm-1:     0.001089     0.000336     0.000262 &#xA;Rotational constants in MHz :    32.661377    10.062791     7.849287 &#xA;&#xA; Dipole components along the rotational axes: &#xA;x,y,z [a.u.] :     2.336172    -2.544708    -1.417172 &#xA;x,y,z [Debye]:     5.938077    -6.468135    -3.602164 &#xA;&#xA; &#xA;&#xA;                        *** CIS RELAXED DENSITY ***&#xA;&#xA;------------------------------------------------------------------------------&#xA;                       ORCA ELECTRIC PROPERTIES CALCULATION&#xA;------------------------------------------------------------------------------&#xA;&#xA;Dipole Moment Calculation                       ... on&#xA;Quadrupole Moment Calculation                   ... off&#xA;Polarizability Calculation                      ... off&#xA;GBWName                                         ... AQx.gbw&#xA;Electron density file                           ... AQx.cisp&#xA;The origin for moment calculation is the CENTER OF MASS  = (19.676450, -8.066302 -0.130676)&#xA;&#xA;-------------&#xA;DIPOLE MOMENT&#xA;-------------&#xA;                                X             Y             Z&#xA;Electronic contribution:     59.47513      39.61229      27.69494&#xA;Nuclear contribution   :    -60.31050     -43.16268     -30.49310&#xA;                        -----------------------------------------&#xA;Total Dipole Moment    :     -0.83537      -3.55038      -2.79817&#xA;                        -----------------------------------------&#xA;Magnitude (a.u.)       :      4.59704&#xA;Magnitude (Debye)      :     11.68475&#xA;&#xA;&#xA;&#xA;--------------------&#xA;Rotational spectrum &#xA;--------------------&#xA; &#xA;Rotational constants in cm-1:     0.001089     0.000336     0.000262 &#xA;Rotational constants in MHz :    32.661377    10.062791     7.849287 &#xA;&#xA; Dipole components along the rotational axes: &#xA;x,y,z [a.u.] :     2.884110    -3.245341    -1.510784 &#xA;x,y,z [Debye]:     7.330824    -8.249002    -3.840108 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1233" LastEditorUserId="5" LastEditDate="2021-04-08T04:04:05.030" LastActivityDate="2021-04-08T04:04:05.030" Title="How do you calculate the change in dipole moment from ground to first excited state using ORCA?" Tags="|density-functional-theory|td-dft|orca|dipole|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2421" PostTypeId="2" ParentId="2420" CreationDate="2020-10-06T16:07:37.913" Score="8" Body="&lt;p&gt;This second dipole moment is almost surely the excited state.  You can see the nuclear contributions are identical and the rotational constants are also the same.  This means they are both calculations of the same geometry.  You can also see the magnitude of the dipole moment increases in the second calculation.  This is very common in excited states.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/excited-state-calculations/tddft&quot; rel=&quot;noreferrer&quot;&gt;ORCA documentation&lt;/a&gt; also seems to state that &lt;code&gt;*** CIS RELAXED DENSITY ***&lt;/code&gt; indicates this is the TD-DFT dipole moment.  I suspect both the excited and ground state are output.  If you change the &lt;code&gt;Iroot&lt;/code&gt; option you may get different excited state dipole moments, I am not sure if the &lt;code&gt;Iroot&lt;/code&gt; 2 corresponds to the first or second excited state. You should check this.&lt;/p&gt;&#xA;&lt;p&gt;Disclaimer: I have never used ORCA.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-06T16:07:37.913" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2422" PostTypeId="5" CreationDate="2020-10-06T18:04:02.493" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-06T18:04:02.493" LastActivityDate="2020-10-06T18:04:02.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2423" PostTypeId="4" CreationDate="2020-10-06T18:04:02.493" Score="0" Body="Questions about dipole moments." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-06T18:04:02.493" LastActivityDate="2020-10-06T18:04:02.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2424" PostTypeId="1" AcceptedAnswerId="2426" CreationDate="2020-10-06T20:10:33.913" Score="16" ViewCount="2273" Body="&lt;p&gt;I am learning DFT and the Hohenberg Kohn Theorem of Existence. It says that there is a one-to-one correspondence between the external potential and the density.&lt;/p&gt;&#xA;&lt;p&gt;However the proofs that I have seen only show that potential gives a unique density. How do we know that a density gives a unique potential? This would require that the Schrodinger equation has a unique solution. Is this true and is there a proof for this? Does the Schrödinger equation yield a unique wavefunction and density?&lt;/p&gt;&#xA;&lt;p&gt;I asked this at &lt;a href=&quot;https://physics.stackexchange.com/q/542754/260076&quot;&gt;Physics SE&lt;/a&gt; and got no answers.&lt;/p&gt;&#xA;" OwnerUserId="1398" LastEditorUserId="5" LastEditDate="2020-10-07T02:17:07.430" LastActivityDate="2020-10-08T16:51:19.513" Title="Does the Schrödinger equation have unique solutions?" Tags="|density-functional-theory|quantum-chemistry|quantum-mechanics|from-phys-se|wavefunctions|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2425" PostTypeId="1" CreationDate="2020-10-06T20:33:43.013" Score="6" ViewCount="157" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/t3Fmh.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/t3Fmh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Total DoS for two different q-point grids, &lt;span class=&quot;math-container&quot;&gt;$100\times100\times100$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$101\times101\times101$&lt;/span&gt;, are graphed above. The DoS for &lt;span class=&quot;math-container&quot;&gt;$63\times63\times63$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$65\times65\times65$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$71\times71\times71$&lt;/span&gt;, &lt;em&gt;&lt;span class=&quot;math-container&quot;&gt;$72\times72\times72$&lt;/span&gt;&lt;/em&gt;, &lt;span class=&quot;math-container&quot;&gt;$81\times81\times81$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$85\times85\times85$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$101\times101\times101$&lt;/span&gt; are same (barely differences of &lt;span class=&quot;math-container&quot;&gt;$0.0000000001$&lt;/span&gt;). Even  numbered grids have a similar DoS too but different from odd ones (&lt;span class=&quot;math-container&quot;&gt;$100$&lt;/span&gt; vs. &lt;span class=&quot;math-container&quot;&gt;$101$&lt;/span&gt; above). &lt;span class=&quot;math-container&quot;&gt;$72\times72\times72$&lt;/span&gt; is the only odd (english) one that matches odd (math) grids.&lt;/p&gt;&#xA;&lt;p&gt;Any reason for all of this? Which one should I use?&lt;/p&gt;&#xA;&lt;p&gt;Find some data below (click to zoom in!):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JxJZ5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JxJZ5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/iG36P.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iG36P.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/pqZTL.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pqZTL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/TFVwP.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TFVwP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-10-06T21:08:33.990" LastActivityDate="2020-10-06T21:08:33.990" Title="Odd/even q-point mesh in harmonic phonon density of states (DoS) calculations" Tags="|phonons|convergence-test|phonon-density-of-state|q-points|" AnswerCount="0" CommentCount="7" ClosedDate="2021-01-23T13:12:27.793" ContentLicense="CC BY-SA 4.0" />
  <row Id="2426" PostTypeId="2" ParentId="2424" CreationDate="2020-10-06T21:19:14.757" Score="15" Body="&lt;p&gt;The solutions to the Schrödinger equation are not unique in general, and uniqueness depends on several things such as the &lt;em&gt;form of the potential&lt;/em&gt; and &lt;em&gt;boundary conditions&lt;/em&gt;. Many papers have discussed uniqueness of solutions to the Schrödinger equation for specific classes of potentials and boundary conditions, but in general it is possible to come up with cases where the &lt;a href=&quot;https://math.stackexchange.com/q/3115671/202425&quot;&gt;solution is not unique&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In fact for most potentials and boundary conditions, the Schrödinger equation has several solutions (a ground state solution, and several excited state solutions).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is at least the ground state solution unique?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For many &amp;quot;physically realistic&amp;quot; potentials and boundary conditions that we normally use (for example, Morse potentials and generalizations of it) we do have a unique ground state &lt;em&gt;energy&lt;/em&gt;, but keep in mind that multiple wavefunction solutions can have the same ground state energy: These are called &lt;em&gt;&lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Degenerate_energy_levels&quot; rel=&quot;nofollow noreferrer&quot;&gt;degenerate solutions&lt;/a&gt;&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What about DFT and the Hohenberg-Kohn Theorem of Existence?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The theorem states that &amp;quot;the external potential (and hence the total energy), is a unique functional of the electron density.&amp;quot; This means that for a given density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, there is a unique energy functional &lt;span class=&quot;math-container&quot;&gt;$E[\rho(r)]$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's say there's a degenerate energy level that has two degenerate solutions to the Schrödinger equation, with densities &lt;span class=&quot;math-container&quot;&gt;$\rho_1(r)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho_2(r)$&lt;/span&gt;. There is a unique energy functional of &lt;span class=&quot;math-container&quot;&gt;$\rho_1(r)$&lt;/span&gt;, which is  &lt;span class=&quot;math-container&quot;&gt;$E_1[\rho_1(r)]$&lt;/span&gt;, and a unique functional of  &lt;span class=&quot;math-container&quot;&gt;$\rho_2(r)$&lt;/span&gt;, which is &lt;span class=&quot;math-container&quot;&gt;$E_2[\rho_2(r)]$&lt;/span&gt;. When these two functionals are applied, the resulting energy is the same either way (because the energy is degenerate), but that doesn't mean the functionals are the same or the densities are the same.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;An energy can correspond to two different solutions of the Schrödinger equation, each with their own &lt;strong&gt;unique&lt;/strong&gt; functional that gives that energy.&lt;/em&gt; Since these two solutions of the Schrödinger equation are not the same, the solutions are &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; unique.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T16:51:19.513" LastActivityDate="2020-10-08T16:51:19.513" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2427" PostTypeId="2" ParentId="2399" CreationDate="2020-10-06T22:46:30.983" Score="4" Body="&lt;p&gt;If the system is magnetic you need to use &lt;code&gt;nspin=2&lt;/code&gt;. You can use any pseudopotential, unless you want to see SOC, in which case you need to use a fully relativistic pseudopotential.&lt;/p&gt;&#xA;" OwnerUserId="1399" LastEditorUserId="5" LastEditDate="2020-10-06T22:47:25.160" LastActivityDate="2020-10-06T22:47:25.160" CommentCount="0" CommunityOwnedDate="2023-05-27T00:21:53.577" ContentLicense="CC BY-SA 4.0" />
  <row Id="2428" PostTypeId="2" ParentId="2400" CreationDate="2020-10-06T23:27:59.300" Score="5" Body="&lt;h2&gt;pyblock&lt;/h2&gt;&#xA;&lt;p&gt;This simple Python code does a &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.457480&quot; rel=&quot;noreferrer&quot;&gt;Flyvbjerg-Petersen blocking analysis&lt;/a&gt; on column(s) of data. It is also used in some larger softwae packages, such as  &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;noreferrer&quot;&gt;NECI&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can run the code with the following command if you have just one column of data:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python blocking.py -f180000 -d5 -o/ file.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where in this case &lt;code&gt;180000&lt;/code&gt; is the line in &lt;code&gt;file.out&lt;/code&gt; at which you want to begin the blocking analysis, and &lt;code&gt;-d5&lt;/code&gt; tells the program that you want to apply the blocking analysis to column 5 of the data in &lt;code&gt;file.out&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to do the blocking analysis on a ratio, then the command would be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python blocking.py -f180000 -d1 -d5 -o/ file.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where here we are doing column 1 divided by column 5.&lt;/p&gt;&#xA;&lt;p&gt;I have several examples on my GitHub page, for example in &lt;a href=&quot;https://github.com/HPQC-LABS/FeMoco/tree/master/Reiher1/FCIQMC-PT2/102.4m/uniformData&quot; rel=&quot;noreferrer&quot;&gt;this folder&lt;/a&gt;, you can see that I applied the above commands to the file &lt;code&gt;RDMEstimates.uniform&lt;/code&gt; and the result of the blocking analysis was printed to the file &lt;code&gt;blockingResult.txt&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;See also:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;pyblock Documentation: &lt;a href=&quot;https://pyblock.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;https://pyblock.readthedocs.io/en/latest/&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;pyblock GitHub page: &lt;a href=&quot;https://github.com/jsspencer/pyblock&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/jsspencer/pyblock&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-10-06T23:27:59.300" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2429" PostTypeId="2" ParentId="2399" CreationDate="2020-10-06T23:43:18.803" Score="7" Body="&lt;p&gt;It is a bit difficult to answer this question, due to the information provided. If you are a beginner, using vc-relax will have its pros and cons.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;With regards to using nspin=2:&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Recall that when you use nspin=2, you are saying that you will define the initial magnetization for the involved species.  So, just keep in mind that spin-polarized calculations will be more expensive than non-polarized...and if you perform fully-relativistic calculations then those will be more expensive than spin-polarized.&lt;/p&gt;&#xA;&lt;p&gt;If magnetic properties are really important in your work and if there may be some non-collinear magnetism, spin-polarized would be a good start and then even compare with spin-orbit coupling as well. Be cautious about &lt;em&gt;which&lt;/em&gt; atoms to consider for this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;With regards to vc-relax&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Variable cell relaxation should be used with caution, and making sure that all parameters are properly optimized and after convergence tests have been performed.&#xA;This depends on the symmetry of your system and how well you are treating the system to begin with.&lt;/p&gt;&#xA;&lt;p&gt;With vc-relax, you control the degrees of freedom that your crystal will have. You can, for example, say that you only want the diagonal elements to change (a1, b2, c3) but preserve symmetry (cell-shape), or  you can fix the volume and give the cell-shape freedom (if not careful, this will lead you AWAY from the global minimum!), you can also go &amp;quot;all out&amp;quot; by letting both the shape and volume change.&lt;/p&gt;&#xA;&lt;p&gt;If careful, you can save as lot of time. If not careful, you'll find yourself spending more time trying to get it right and might end up &amp;quot;manually&amp;quot; optimizing a cell (analyze the system's energy as a function of Volume and then fit an equation of state).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Final remarks and things to think about as a beginner!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Is there experimental data available for the material you are modeling?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;If there is available crystallographic data for that material, I would recommend keeping it simple at first. Start with the experimental structure, run a vc-relax that fixes symmetry but will vary volume. Do this without spin-polarization. If it is a bulk structure, adding a vdW correction won't do you any harm (e.g. Grimme-D3).&#xA;Run this calculation and compare your computed unit cell with the experimental data. If all is well... you should be within 3%. If you think there may be some improvement, then include nspin=2... but I don't think it will be all that significant.&lt;/p&gt;&#xA;&lt;p&gt;In my experience, for many materials optimizing with PBE-D3-SOC (SOC = Spin Orbit Coupling gives almost identical geometries to PBE-D3).&lt;/p&gt;&#xA;&lt;p&gt;I would recommend trying to save time during optimization and save that time for the modeling of properties, with SP and SOC.&lt;/p&gt;&#xA;" OwnerUserId="175" LastActivityDate="2020-10-06T23:43:18.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2430" PostTypeId="2" ParentId="2300" CreationDate="2020-10-07T07:28:55.070" Score="2" Body="&lt;p&gt;For MD I recommend The Gamma Cantered KPOINTS with Grid mesh 1  1  1.&lt;/p&gt;&#xA;" OwnerUserId="1162" LastActivityDate="2020-10-07T07:28:55.070" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2431" PostTypeId="2" ParentId="2300" CreationDate="2020-10-07T10:52:56.930" Score="3" Body="&lt;p&gt;This won't directly answer your question, but a note of caution about focusing &lt;strong&gt;too much&lt;/strong&gt; on optimization.&lt;/p&gt;&#xA;&lt;p&gt;It's definitely worth doing some experimentation to find an efficient combination of memory, # of cpus, etc when you're getting ready to run big simulations. This is especially true for challenging problems where you will be at the limit of your computational resources. &lt;strong&gt;But,&lt;/strong&gt; let not the perfect be the enemy of the good for a few reasons:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It's basically impossible to do controlled benchmark experiments. Your code will be running on a cluster with other jobs, interacting with them in nontrivial ways that you can't anticipate.&lt;/li&gt;&#xA;&lt;li&gt;Small changes in the exact type of CPU or network traffic can affect performance in unexpected nonlinear ways.&lt;/li&gt;&#xA;&lt;li&gt;Changes in the parameters of your simulation, or even different runs of the same simulation, can have different performance.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;CPU time is cheap, your time is valuable.&lt;/strong&gt; Once you've established a protocol that is not monstrously inefficient, it's probably good enough to proceed. You can always monitor performance to make sure nothing is going wrong.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-10-07T10:52:56.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2432" PostTypeId="2" ParentId="2418" CreationDate="2020-10-07T12:08:57.990" Score="1" Body="&lt;p&gt;There are two options here and the choice depends on what you intend to do with your results.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are going to perform QM calculations after MD, then you can just alter the charges as you outlined in your question. This is because QM will correct any issues you might come across. However, you need to make sure the molecule will behave in the manner in which you would expect. You cannot just cram some parameters in a molecule to make the code accept them.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are only doing MD, you might be able to borrow the parameters or follow the procedure outlined in this &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/ct5004143&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. They use a system very similar to yours.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Even if you are performing QM calculations afterwards, you could just use procedure 2 in general.&lt;/p&gt;&#xA;" OwnerUserId="510" LastActivityDate="2020-10-07T12:08:57.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2433" PostTypeId="1" CreationDate="2020-10-07T14:51:37.827" Score="14" ViewCount="596" Body="&lt;p&gt;Following up on &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/467/which-are-the-freely-available-crystal-structure-visualization-softwares&quot;&gt;this question about freely available crystal structure visualization codes&lt;/a&gt;, I wish to know what &lt;strong&gt;procedures&lt;/strong&gt; people follow from start to finish in preparing images of their materials for publication. A procedure can comprise of tools (codes and otherwise), colour schemes, angles, axes (or some other way to describe directions), lighting, or any other details, how much ever minute they may be.&lt;/p&gt;&#xA;&lt;p&gt;Let's keep answers restricted to one visualization software (e.g., &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt;) and accompanying details unless there's someone who uses two or more visualization software in tandem.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-12T22:56:46.723" LastActivityDate="2020-12-12T22:56:46.723" Title="Suggestions for a good crystal structure visualization workflow" Tags="|one-topic-per-answer|crystal-structure|visualization-software|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2434" PostTypeId="1" CreationDate="2020-10-07T15:19:33.867" Score="8" ViewCount="1281" Body="&lt;p&gt;As mysterious as k-points are, why is there a cut-off for an odd and even k-mesh preference?&lt;/p&gt;&#xA;&lt;p&gt;On the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;noreferrer&quot;&gt;VASP wiki&lt;/a&gt; page titled, &amp;quot;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Number_of_k_points_and_method_for_smearing&quot; rel=&quot;noreferrer&quot;&gt;Number of k points and method for smearing&lt;/a&gt;&amp;quot;, they say results when using odd k-meshes shouldn't be compared to those when using even k-meshes (section: Comparing different k-point meshes). In the section &amp;quot;Some other considerations&amp;quot;, they go on to say that even meshes are better up to 8 k-points in a direction while odd meshes are better beyond 8. What is the physics behind it or is it a code-level preference?&lt;/p&gt;&#xA;&lt;p&gt;As an aside: I recently asked a question about &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2425/odd-even-q-point-mesh-in-harmonic-phonon-density-of-states-dos-calculations?noredirect=1#comment4553_2425&quot;&gt;odd/even q-points for phonon DoS calculations&lt;/a&gt; where I received a comment suggesting that the problem could be similar to that of k-points in electronic calculations.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-10-07T15:26:32.287" LastActivityDate="2020-10-13T23:46:19.120" Title="k-points: Odd vs. Even" Tags="|density-functional-theory|vasp|k-points|brillouin-zone|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2435" PostTypeId="1" AcceptedAnswerId="2481" CreationDate="2020-10-07T16:29:21.620" Score="9" ViewCount="917" Body="&lt;p&gt;I am studying atomic slabs which are periodic in 2 dimensions. Normally in the third dimension, I add a vacuum layer and use dipole correction to mimic proper boundary conditions. Recently I have discovered a property 'assume_isolated' with a parameter '2D' in Quantum Espresso implemented in the way described in &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.96.075448&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. B, 96(7), 75448 (2017)&lt;/a&gt; In the paper the authors apply this formalism to the graphene which is atomically thin. Is this formalism applicable for slabs with a thickness of about 3 nm? When I applied it I saw strange oscillations in the potential for the vacuum layer where I expected to see flat lines. It seems like as there are some atoms in the vacuum layer appeared (image charges?).&lt;/p&gt;&#xA;&lt;p&gt;Below are two examples with a silicon slab.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;With a vacuum layer and dipole correction:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/xugfp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xugfp.png&quot; alt=&quot;Vacuum layer and dipole correction&quot; /&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;With &lt;code&gt;assume_isolated&lt;/code&gt; with the parameter &lt;code&gt;2D&lt;/code&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/f0019.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/f0019.png&quot; alt=&quot;With assume_isolated + 2D&quot; /&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1402" LastEditorUserId="5" LastEditDate="2020-10-10T21:53:19.530" LastActivityDate="2020-10-12T02:00:18.940" Title="Quantum ESPRESSO: parameter &quot;assume_isolated&quot;: is it applicable to slabs?" Tags="|quantum-espresso|2d-lattice|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2436" PostTypeId="2" ParentId="2415" CreationDate="2020-10-07T19:35:56.803" Score="9" Body="&lt;p&gt;It's not the simplest alternative, but sometimes to learn a bit of &lt;a href=&quot;https://en.wikipedia.org/wiki/Regular_expression&quot; rel=&quot;noreferrer&quot;&gt;regular expressions&lt;/a&gt; and one scripting language can help a lot in tasks like this. It's a really worth time investment, if you have a little time to spare.&lt;/p&gt;&#xA;&lt;p&gt;For example, I ran your input in my machine, saving the results to PES_scan_oxygen.log, and in &lt;a href=&quot;https://www.python.org/&quot; rel=&quot;noreferrer&quot;&gt;Python 3&lt;/a&gt; wrote a script to read this log and extract the coordinates and energies to a CSV file, that can be opened with a spreadsheet. The lines preceded by # are comments, to help explain what is done at each step of the script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Imports regular expression (regex) library&#xA;import re&#xA;&#xA;def pes2csv(gamess_output):&#xA;    '''&#xA;    Function takes the PES scan output as its input, and returns .CSV file&#xA;    with matching values of radius and energy.&#xA;    '''&#xA;    # Creates regex pattern for line with energy value&#xA;    energy_pattern = re.compile(r&amp;quot;HAS ENERGY VALUE\s+(\S+)&amp;quot;)&#xA;    # Creates regex pattern for line with radius value&#xA;    coordinate_pattern = re.compile(r&amp;quot;COORD 1= (\S+) &amp;quot;)&#xA;&#xA;    # Opens file with the raw data&#xA;    with open(gamess_output, &amp;quot;r&amp;quot;) as f:&#xA;        # Splits the file in lines, makes a list with them&#xA;        line_list = f.readlines()&#xA;&#xA;    # Initiate list where we'll save our R and Energy values with headers&#xA;    pair_list = [&amp;quot;R;Energy\n&amp;quot;]&#xA;&#xA;    # For every line i in the file&#xA;    for i in range(len(line_list)):&#xA;        # If line i is the start of surface mapping geometry section&#xA;        if line_list[i] == &amp;quot; ---- SURFACE MAPPING GEOMETRY ----\n&amp;quot;:&#xA;            # Searches the pattern for radius in the next line&#xA;            R_match = coordinate_pattern.search(line_list[i+1])&#xA;            # Searches the pattern for energy in the second next line&#xA;            Energy_match = energy_pattern.search(line_list[i+2])&#xA;            # Assembles one line for our final CSV using &amp;quot;;&amp;quot; as delimiter, puts it on pair_list&#xA;            pair_list.append(R_match.group(1) + &amp;quot;;&amp;quot; + Energy_match.group(1) + &amp;quot;\n&amp;quot;)&#xA;&#xA;    # Creates a CSV file named PES.csv, in the same folder the script is saved&#xA;    with open(&amp;quot;PES.csv&amp;quot;, &amp;quot;w&amp;quot;) as g:&#xA;        # Save the contents of pair_list to the CSV file we just created&#xA;        g.writelines(pair_list)&#xA;    print(&amp;quot;Data saved to CSV file. Look your folder&amp;quot;)&#xA;    &#xA;# Now we can call the function on our gamess output file, to extract the data&#xA;pes2csv(&amp;quot;PES_scan_oxygen.log&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you have Python 3 installed in your machine, save this script to a .py file in the same folder where the gamess output file is located, and runs it, now there's a PES.csv file in the folder, with just the data you want, as seen in the spreadsheet:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1LFFi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1LFFi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The decimal separator looks wrong, but it's just because I have the language of Libreoffice set to Portuguese, where dots are used as the thousands delimiter and comma to separate the decimal part of a number (the reverse of what is done in English).&lt;/p&gt;&#xA;&lt;p&gt;For this particular example, to write down the script was probably overkill, as the final table has only 11 lines, and Nike's suggestion of using grep + manual import would be faster. But the problem with approaches involving manual steps is that they don't scale well. In large data sets it becomes tedious and time-consuming. In large spreadsheets you can spend a lot of time just scrolling up and down. So the time investment learning to automate it pays when you have large files or lots of files, what eventually happens with everybody.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-10-08T12:21:47.203" LastActivityDate="2020-10-08T12:21:47.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2437" PostTypeId="1" AcceptedAnswerId="8491" CreationDate="2020-10-07T23:56:28.390" Score="14" ViewCount="307" Body="&lt;p&gt;I thought that carbon with its even number of protons and neutrons has no magnetic spin or moment and yet I learn that neutrons are scattered quite effectively by carbon atoms.&lt;/p&gt;&#xA;&lt;p&gt;I understood that neutrons interacted with matter through the strong force and through their magnetic moment so why should they be scattered by carbon?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance!&lt;/p&gt;&#xA;&lt;p&gt;Edit: I think am getting confused between scattering due to path difference and scattering due to the magnetic moment.  I think scattering can be considered as having an incoherent and coherent aspect.  A nucleus with no magnetic moment such as carbon 12 generates no incoherent scattering but it a neutron 'wave' could be scattered by the spatial structure of matter, the coherent aspect (like Youngs slits).  Is that it?&lt;/p&gt;&#xA;" OwnerUserId="1404" LastEditorUserId="5" LastEditDate="2020-10-16T18:14:56.660" LastActivityDate="2022-01-06T05:33:13.767" Title="Why do neutrons scatter from carbon when its nucleus has no magnetic moment?" Tags="|diffraction|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2438" PostTypeId="5" CreationDate="2020-10-08T05:07:09.363" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:07:09.363" LastActivityDate="2020-10-08T05:07:09.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2439" PostTypeId="4" CreationDate="2020-10-08T05:07:09.363" Score="0" Body="Questions about non-adiabatic dynamics or anything non-adiabatic." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:07:09.363" LastActivityDate="2020-10-08T05:07:09.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2440" PostTypeId="5" CreationDate="2020-10-08T05:09:08.757" Score="0" Body="&lt;p&gt;More information can be found here: &lt;a href=&quot;https://en.wikipedia.org/wiki/YAMBO_code&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/YAMBO_code&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:09:08.757" LastActivityDate="2020-10-08T05:09:08.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2441" PostTypeId="4" CreationDate="2020-10-08T05:09:08.757" Score="0" Body="Questions about the many-body theory code YAMBO" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:09:08.757" LastActivityDate="2020-10-08T05:09:08.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2442" PostTypeId="5" CreationDate="2020-10-08T05:11:31.177" Score="0" Body="&lt;p&gt;More information can be found in these places:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Transition_metal_dichalcogenide_monolayers&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Transition_metal_dichalcogenide_monolayers&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Chalcogenide#Dichalcogenides&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Chalcogenide#Dichalcogenides&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:11:31.177" LastActivityDate="2020-10-08T05:11:31.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2443" PostTypeId="4" CreationDate="2020-10-08T05:11:31.177" Score="0" Body="Questions about dichalcogenides." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:11:31.177" LastActivityDate="2020-10-08T05:11:31.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2444" PostTypeId="5" CreationDate="2020-10-08T05:12:48.827" Score="0" Body="&lt;p&gt;More information can be found here: &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Brillouin_zone&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:12:48.827" LastActivityDate="2020-10-08T05:12:48.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2445" PostTypeId="4" CreationDate="2020-10-08T05:12:48.827" Score="0" Body="Questions about Brillouin zones." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:12:48.827" LastActivityDate="2020-10-08T05:12:48.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2446" PostTypeId="5" CreationDate="2020-10-08T05:13:55.857" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:13:55.857" LastActivityDate="2020-10-08T05:13:55.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2447" PostTypeId="4" CreationDate="2020-10-08T05:13:55.857" Score="0" Body="Questions about ab-initio molecular dynamics (AIMD)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:13:55.857" LastActivityDate="2020-10-08T05:13:55.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2448" PostTypeId="5" CreationDate="2020-10-08T05:14:55.137" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:14:55.137" LastActivityDate="2020-10-08T05:14:55.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2449" PostTypeId="4" CreationDate="2020-10-08T05:14:55.137" Score="0" Body="Questions about experimental science related in any way to matter and of interest to some matter modelers." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:14:55.137" LastActivityDate="2020-10-08T05:14:55.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2450" PostTypeId="5" CreationDate="2020-10-08T05:15:55.573" Score="0" Body="&lt;p&gt;More information can be found here: &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:15:55.573" LastActivityDate="2020-10-08T05:15:55.573" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2451" PostTypeId="4" CreationDate="2020-10-08T05:15:55.573" Score="0" Body="Questions about the ATAT software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T05:15:55.573" LastActivityDate="2020-10-08T05:15:55.573" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2452" PostTypeId="1" CreationDate="2020-10-08T11:39:24.370" Score="16" ViewCount="3158" Body="&lt;p&gt;A newcomer to density functional theory calculations is exposed to jargon which sounds rather non-technical at first. For instance, 'charge density' is something that is actually a term in the formalism, whereas terms like 'first principles' seem adjectival. Please help me understand what they mean and their relevance as to why are they associated with the theory almost everywhere.&lt;/p&gt;&#xA;" OwnerUserId="1406" LastEditorUserId="5" LastEditDate="2020-10-09T20:51:36.030" LastActivityDate="2020-10-09T20:51:36.030" Title="What are &quot;first principles&quot; calculations?" Tags="|density-functional-theory|terminology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2453" PostTypeId="1" CreationDate="2020-10-08T12:14:28.950" Score="9" ViewCount="627" Body="&lt;p&gt;I am new at VASP, and apparently, cutoff convergence is not something like kpoint convergence. Is using &lt;code&gt;ENCUT=1.5xENMAX&lt;/code&gt; can be justified? For RPA, GW and MP2 calculations, I cannot use larger values.&lt;/p&gt;&#xA;" OwnerUserId="984" LastActivityDate="2020-10-20T16:35:31.470" Title="Suggested cutoff for high level VASP calculations" Tags="|density-functional-theory|vasp|plane-waves|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2454" PostTypeId="2" ParentId="2452" CreationDate="2020-10-08T13:04:32.033" Score="15" Body="&lt;p&gt;First Principles mean starting directly at the level of established science and not making assumptions such as any empirical models or parameter fitting. &lt;br /&gt;&#xA;With respect to DFT, EMF (Electromagnetic force) is a very strong force governing nucleus and electrons (referring to a single atom).&lt;br /&gt;&#xA;With that, atoms, molecules, macro molecules and materials are built up. Whatever happens in materials (be it physical deformation or its fundamental properties) comes from this basic interaction. &lt;br /&gt;&#xA;The law that governs these small particles and their interaction is &lt;strong&gt;Quantum Mechanics&lt;/strong&gt;. The calculation methods (DFT) based on QM &lt;strong&gt;do not&lt;/strong&gt; use fitting parameters from experiments or assume anything. They are solely dependent on basic laws of physics (&lt;em&gt;not Newton's laws&lt;/em&gt;).&lt;br /&gt;&#xA;Thus they are named as &lt;em&gt;&lt;strong&gt;First Principle (ab initio) Methods&lt;/strong&gt;&lt;/em&gt;.&lt;br /&gt;&#xA;&lt;strong&gt;Just to give an idea:&lt;/strong&gt; The only information these calculation methods need is the &lt;strong&gt;Atomic Number&lt;/strong&gt; of the atoms involved.&lt;/p&gt;&#xA;" OwnerUserId="707" LastEditorUserId="707" LastEditDate="2020-10-09T09:48:19.877" LastActivityDate="2020-10-09T09:48:19.877" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2455" PostTypeId="1" CreationDate="2020-10-08T13:44:44.370" Score="16" ViewCount="128" Body="&lt;p&gt;I would like to use an AI-derived force field as they seemed to have lesser computational cost.&#xA;Which simulation package (Gromacs, Amber, NAMD...) currently implement some of them?&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2020-10-08T13:59:34.273" LastActivityDate="2020-10-13T17:44:41.850" Title="Which modelling package currently implements an AI derived force field?" Tags="|software-recommendations|forcefields|machine-learning|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2456" PostTypeId="2" ParentId="1283" CreationDate="2020-10-08T14:10:04.983" Score="2" Body="&lt;p&gt;I managed to get the converged U&lt;span class=&quot;math-container&quot;&gt;$_{0.01}$&lt;/span&gt;Cu&lt;span class=&quot;math-container&quot;&gt;$_{0.99}$&lt;/span&gt; potential by converging a pure Uranium potential in a Cu lattice. Then by increasing the concentration of Cu and using the old converged potential as a starting potential you can increase the concentration of Cu in steps until finally reaching a converged U&lt;span class=&quot;math-container&quot;&gt;$_{0.01}$&lt;/span&gt;Cu&lt;span class=&quot;math-container&quot;&gt;$_{0.99}$&lt;/span&gt; potential. This is a good method to try in any binary alloy system if you have a point that doesn't seem to converge.&lt;/p&gt;&#xA;" OwnerUserId="863" LastActivityDate="2020-10-08T14:10:04.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2457" PostTypeId="5" CreationDate="2020-10-08T16:26:26.903" Score="0" Body="&lt;p&gt;See here for a review paper: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/cr990029p&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/cr990029p&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T16:26:26.903" LastActivityDate="2020-10-08T16:26:26.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2458" PostTypeId="4" CreationDate="2020-10-08T16:26:26.903" Score="0" Body="Questions about conceptual DFT." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T16:26:26.903" LastActivityDate="2020-10-08T16:26:26.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2459" PostTypeId="5" CreationDate="2020-10-08T16:27:36.333" Score="0" Body="&lt;p&gt;More information here: &lt;a href=&quot;https://en.wikipedia.org/wiki/Atoms_in_molecules&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Atoms_in_molecules&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T16:27:36.333" LastActivityDate="2020-10-08T16:27:36.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2460" PostTypeId="4" CreationDate="2020-10-08T16:27:36.333" Score="0" Body="Questions about QTAIM (Quantum Theory of Atoms in Molecules)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-08T16:27:36.333" LastActivityDate="2020-10-08T16:27:36.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2461" PostTypeId="2" ParentId="2437" CreationDate="2020-10-08T16:54:16.260" Score="5" Body="&lt;p&gt;There are a few possibilities (the relevant importance of each probably varies depending on the type of scattering and the material).&lt;/p&gt;&#xA;&lt;p&gt;Even for pure C12, neutrons can scatter off unpaired electrons, since many allotropes have unpaired valence electrons. Neutrons can also scatter off the nucleus itself by nuclear forces. Graphite is used in some nuclear reactors as a neutron moderator precisely because it scatters neutrons, slowing them down so they have a better chance of causing causing fission when they hit a Uranium nucleus. See Wikipedia for &lt;a href=&quot;https://en.wikipedia.org/wiki/Neutron_cross_section#Type_of_reaction_dependence&quot; rel=&quot;nofollow noreferrer&quot;&gt;Neutron cross section.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-10-08T17:01:30.130" LastActivityDate="2020-10-08T17:01:30.130" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="2462" PostTypeId="2" ParentId="2317" CreationDate="2020-10-08T20:03:19.027" Score="2" Body="&lt;p&gt;I had the same doubt regarding the validity of my calculations. In some cases, it was astonishing how certain well-known quantities like the bandgap of Silicon could be easily underestimated by DFT. But as seen in most research papers on DFT calculations, there is a difference in experimental and predicted values. This depends on various factors including the type of pseudopotentials, consideration of spin-orbit coupling etc.. But there are ways to work around such innate differences and observe what works for you. You could use different pseudopotentials, and if that's not showing evident change, you can use codes that implement LAPW methods rather than plane-waves. The idea is not to make your calculations as close to the experimental values as possible, it's just to know if the physical properties predicted are in fact due to the inherent physics of the material. There may be cases where the presence of impurities, measurement error..etc can affect your data. That noise is unremovable. So its better to see if your predicted values are in the range allowed for the parameter in consideration.&lt;/p&gt;&#xA;&lt;p&gt;I hope it's a viable thought.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-08T20:03:19.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2463" PostTypeId="2" ParentId="2405" CreationDate="2020-10-08T20:34:23.077" Score="17" Body="&lt;p&gt;To respond directly regarding the Materials Project data, I'm a staff member there so maybe I can shed some light.&lt;/p&gt;&#xA;&lt;p&gt;Materials Project computed data is currently generated using a technique known as Density Functional Theory (DFT) with the PBE exchange-correlation functional. This results in some well-understood, &lt;em&gt;systematic&lt;/em&gt; differences from experiment. Typically, this means that our computed lattice parameters will over-estimate experimental lattice parameters by 2-3% on average. Note that layered materials (any material where van der Waals bonding might be significant) will have larger errors in their inter-layer distance. Finally, note that these lattice parameters are nominally at 0 K, and do not take thermal expansion into account.&lt;/p&gt;&#xA;&lt;p&gt;Note that lattice parameters on Materials Project are often given as their primitive cell, if you want the conventional lattice parameters make sure to download the CIF file in the &amp;quot;conventional&amp;quot; setting.&lt;/p&gt;&#xA;&lt;p&gt;Band gaps will be systematically &lt;em&gt;under-estimated&lt;/em&gt; by a large degree when using PBE (see &lt;a href=&quot;http://docs.materialsproject.org/methodology/electronic-structure/&quot; rel=&quot;noreferrer&quot;&gt;our documentation&lt;/a&gt;). Spin-orbit coupling is also not included. The electronic band structures on Materials Project are most useful for seeing the shapes of the bands and the character of the gap (e.g. indirect, direct, between what symmetry points, etc.), the absolute magnitude of the band gaps are only useful for &lt;em&gt;trends&lt;/em&gt; between different materials.&lt;/p&gt;&#xA;&lt;p&gt;Better computational techniques can give results with smaller systematic errors, and we're constantly evaluating using some of these better techniques with the Materials Project. The trade-off here is that Materials Project tries to calculate properties for 100,000s of materials, and so using these better techniques is not always practically possible due to their computational cost.&lt;/p&gt;&#xA;&lt;p&gt;With this context, to answer the question of &amp;quot;which should I use?&amp;quot;, the question depends on what you want to use it for. If you want to know the &amp;quot;true&amp;quot; value, always defer to high-quality X-ray diffraction (bearing in mind the experimental value might be affected by grown-in strain, impurities, the temperature the measurement is taken at and other factors). However, if you want to do additional calculations with PBE, it's often easier to start from the previously-computed geometry. The computed geometry is also useful for examining differences between materials (e.g. varying composition) and also for materials where high-quality experimental data has not been acquired.&lt;/p&gt;&#xA;&lt;p&gt;Likewise, for band gap, I would always defer to the experimental value, but of course there are also experimental issues too; experimentally, the &lt;em&gt;optical&lt;/em&gt; gap is usually what is measured (e.g. via photoluminescence), there might be defect levels, finite temperature effects, excitonic effects, unintentional doping, Moss-Burstein shifts, etc., you might be only measuring the direct gap, whereas computationally you're predicting the fundamental gap (strictly speaking, the &amp;quot;Kohn Sham gap&amp;quot; using traditional DFT, which is another very important but subtle point). So there's no easy answer for which is better. The computational picture might give you a better picture for how a hypothetical pristine material might behave, but is typically most useful for trends and comparisons between similar materials.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps! Happy to answer further questions.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="1333" LastEditDate="2020-10-09T01:28:30.257" LastActivityDate="2020-10-09T01:28:30.257" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2464" PostTypeId="1" CreationDate="2020-10-09T11:03:56.300" Score="8" ViewCount="150" Body="&lt;p&gt;&lt;strong&gt;Disclaimer: Assume the person asking is a novice in DFT and condensed matter physics in general.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the localized density approximation (LDA), the exchange correlation potential is considered a function of a constant charge density, whereas in GGA, it is a function of the gradient of charge density as well:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;V_{(xc)}^{LDA} = f(\rho_{(r)})&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;V_{(xc)}^{GGA} = f(\rho_{(r)},\nabla\rho_{(r)})&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What role does the constant charge density play in GGA? Also, in literature, methods describe DFT calculations done with GGA as &lt;em&gt;parameterized by so-and-so&lt;/em&gt;. What does that mean?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-10-09T11:09:49.090" LastActivityDate="2020-10-16T16:05:17.740" Title="Parameterization in the generalised gradient approximation (GGA)" Tags="|density-functional-theory|exchange-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2465" PostTypeId="1" AcceptedAnswerId="2468" CreationDate="2020-10-09T14:07:21.257" Score="15" ViewCount="843" Body="&lt;p&gt;It is often claimed (e.g. &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12/what-correlation-effects-are-included-in-dft/21#21?newreg=c5aca9e620cc4eb49d1048cf7465493a&quot;&gt;here&lt;/a&gt;), that Density Functional Theory is in principle exact. This seems to be a very strong statement to me.&#xA;Are all current limitations only of a technical nature rather than a fundamental?&lt;/p&gt;&#xA;&lt;p&gt;There are a few reasons why I'm a bit skeptical:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Lots  of work in condensed-matter physics is being done by people without DFT; e.g. related to topology, polarons, superconductivity...&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;All information is in the electron density&amp;quot;. This means the single-particle reduced density matrix. As this is clearly a huge reduction from the exponentially large Hilbert space of the many-body system, I could argue that it makes DFT a semiclassical method?&lt;/li&gt;&#xA;&lt;li&gt;More recent numerical methods for quantum systems, such as tensor networks (MPS/DMRG/...) seem much more advanced (even if applied to simple setups), and even then they are only &lt;em&gt;perturbatively&lt;/em&gt; exact, in bond dimension.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Am I missing something?&lt;/p&gt;&#xA;" OwnerUserId="1409" LastEditorUserId="5" LastEditDate="2020-10-10T20:33:05.407" LastActivityDate="2020-10-10T20:33:05.407" Title="How exact is DFT, really?" Tags="|density-functional-theory|quantum-mechanics|quantum-dynamics|" AnswerCount="1" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="2466" PostTypeId="2" ParentId="2180" CreationDate="2020-10-09T14:13:14.627" Score="6" Body="&lt;p&gt;I don't think that any classification of dihedral angles exists.&lt;/p&gt;&#xA;&lt;p&gt;α and β that you see in the picture refer to alpha helices and beta sheets – structural elements of proteins (&lt;a href=&quot;https://en.wikipedia.org/wiki/Protein_secondary_structure&quot; rel=&quot;noreferrer&quot;&gt;secondary structure&lt;/a&gt;).&#xA;What is neither a helix nor β-strand is called a loop or coil.&#xA;Sometimes more detailed categories are used – for example, 3&lt;sub&gt;10&lt;/sub&gt; and π helices can be used as separate categories.&lt;/p&gt;&#xA;&lt;p&gt;So it's not that dipeptides are classified into multiple categories.&#xA;It's that secondary structural elements of proteins have certain dihedral angles.&lt;/p&gt;&#xA;&lt;p&gt;As an illustration, below is a figure from the &lt;a href=&quot;https://doi.org/10.1016/s0022-2836(63)80023-6&quot; rel=&quot;noreferrer&quot;&gt;Ramachandran's paper from 1963&lt;/a&gt;. The author marks there, for example, where the ideal left-handed α-helix is. But the same φ/ψ angles can also happen in a loop.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fhQLT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fhQLT.png&quot; alt=&quot;Ramachandran plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2020-10-09T14:13:14.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2467" PostTypeId="1" CreationDate="2020-10-09T23:02:56.257" Score="9" ViewCount="444" Body="&lt;p&gt;I want to get the equations that model free energy for a given phase in a given alloy system (see attached image). I do &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; just want to get values of free energy for specific compositions. Is it possible to extract the equations themselves from a Thermo-Calc database? Ideally, I'd like to be able to do this in TC_Python, but if it's only possible in Console Mode I could work with that.&lt;/p&gt;&#xA;&lt;p&gt;Example Output I found (but don't know the code used to generate it):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        PARAMETER G(HCP_A3,CO:VA;0)  298.15  +GHSERCO;,,N !&#xA;        PARAMETER G(HCP_A3,NI:VA;0)  298.15  +GHCPNI;,,N !&#xA;        FUNCTION GHSERCO    298.15  +310.241+133.36601*T&#xA;        -25.0861*T*LN(T)-.002654739*T**2-1.7348E-07*T**3&#xA;        +72527*T**(-1)  1768.0  Y  -17197.666+253.28374*T&#xA;        -40.5*T*LN(T)+9.3488E+30*T**(-9);,,   N !&#xA;        FUNCTION GHSERNI    298.15  -5179.159+117.854*T&#xA;        -22.096*T*LN(T)-.0048407*T**2;&#xA;        1728.0  Y  -27840.655+279.135*T-43.1*T*LN(T)&#xA;        +1.12754E+31*T**(-9);,,  N   !&#xA;        PARAMETER L(HCP_A3,CO,NI:VA;0)  298.15  -1620-.385*T;,,N !&#xA;        PARAMETER TC(HCP_A3,CO:VA;0)  298.15  +1396;,,N !&#xA;        PARAMETER BMAGN(HCP_A3,CO:VA;0)  298.15  1.35;,,N !&#xA;        PARAMETER TC(HCP_A3,NI:VA;0)  298.15  633;,,N !&#xA;        PARAMETER BMAGN(HCP_A3,NI:VA;0)  298.15  .52;,,N !&#xA;        PARAMETER TC(HCP_A3,CO,NI:VA;0)  298.15  411;,,N !&#xA;        PARAMETER TC(HCP_A3,CO,NI:VA;1)  298.15  -99;,,N!&#xA;        PARAMETER BMAGN(HCP_A3,CO,NI:VA;0)  298.15  1.046;,,N !&#xA;        PARAMETER BMAGN(HCP_A3,CO,NI:VA;1)  298.15  .165;,,N !&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="5" LastEditDate="2020-10-10T03:45:43.463" LastActivityDate="2020-10-24T14:43:31.640" Title="For a Thermo-Calc database, is it possible to view the equation/parameters of the Gibbs free energy models?" Tags="|thermodynamics|gibbs-free-energy|calphad|thermo-calc|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2468" PostTypeId="2" ParentId="2465" CreationDate="2020-10-09T23:40:28.000" Score="12" Body="&lt;p&gt;I'll try to give a short but reasonably rigorous way of thinking about the exactness of density functional theory (DFT).&lt;/p&gt;&#xA;&lt;p&gt;Consider &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons under the influence of a fixed external potential &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt; for which the ground state electron density is &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;. The external potential might be a sum of individual potentials from atomic nuclei, but it could also be something else.&lt;/p&gt;&#xA;&lt;p&gt;This information, somewhat surprisingly, is sufficient for determining the &lt;em&gt;exact&lt;/em&gt; quantum mechanical ground state energy of the interacting electron system (at least in principle). One conceptual approach involves the formula&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_v[n] = \underset{\Psi \to n}{\mathrm{min}} \left\langle \Psi \right| \hat{T}+\hat{V}_{ee} \left| \Psi \right\rangle&#xA;    + \int \mathrm{d}\mathbf{r} \, v(\mathbf{r}) n(\mathbf{r}).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The notation is a little abstract, so let's go term by term.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The left hand side, &lt;span class=&quot;math-container&quot;&gt;$E_v[n]$&lt;/span&gt;, just represents the energy of the electrons as a functional of the density &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;, assuming a fixed &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The second part, &lt;span class=&quot;math-container&quot;&gt;$\underset{\Psi \to n}{\mathrm{min}} \left\langle \Psi \right| \hat{T}+\hat{V}_{ee} \left| \Psi \right\rangle$&lt;/span&gt;, is the most unfamiliar to newcomers. It says: (a) consider all admissible &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron wave functions &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; that collapse to the prescribed electron density &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;; (b) from these, choose the particular &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; that minimizes &lt;span class=&quot;math-container&quot;&gt;$\left\langle \Psi \right| \hat{T}+\hat{V}_{ee} \left| \Psi \right\rangle$&lt;/span&gt;, which is the sum of the kinetic (&lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;) and electron-electron interaction (&lt;span class=&quot;math-container&quot;&gt;$V_{ee}$&lt;/span&gt;) energies; and (c) return this minimal &lt;span class=&quot;math-container&quot;&gt;$T+V_{ee}$&lt;/span&gt; as the result.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The third part, &lt;span class=&quot;math-container&quot;&gt;$\int \mathrm{d}\mathbf{r} \, v(\mathbf{r}) n(\mathbf{r})$&lt;/span&gt;, is the interaction between the electrons and the external potential.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;DFT involves a bit more than just this formula (which is due to Levy and Lieb building on work of Hohenberg and Kohn). But the formula underpins DFT's exactness.&lt;/p&gt;&#xA;&lt;p&gt;The practical difficulties for DFT stem from the fact that &lt;span class=&quot;math-container&quot;&gt;$\underset{\Psi \to n}{\mathrm{min}} \left\langle \Psi \right| \hat{T}+\hat{V}_{ee} \left| \Psi \right\rangle$&lt;/span&gt; is conceptually elegant, but nearly impossible to implement in most cases (having &lt;a href=&quot;https://www.nature.com/articles/nphys1370&quot; rel=&quot;noreferrer&quot;&gt;NP-like complexity&lt;/a&gt;). The panoply of density functional approximations provide alternatives to implementing this term directly. They are often sufficiently accurate for answering questions in physics, chemistry, and materials science, but not always.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2020-10-10T11:53:04.280" LastActivityDate="2020-10-10T11:53:04.280" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="2469" PostTypeId="1" AcceptedAnswerId="3558" CreationDate="2020-10-10T04:53:15.370" Score="18" ViewCount="2740" Body="&lt;p&gt;The central goal of the first-principles simulation with DFT is to solve the Kohn-Sham equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$[-\dfrac{1}{2}\nabla^2+v_{\textit{eff}}(\vec{r})]\phi_n(\vec{r})=E_n\psi_n(\vec{r}) \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the atomic unit has been adopted. But the EQ.(1) can only be utilized to predict the properties of materials without magnetic properties and strong spin-orbit coupling (SOC). When the spin degree is considered, the simulation can be classified into three types according to the properties of materials:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Spin-unpolarized [for non-magnetic materials with weak SOC];&lt;/li&gt;&#xA;&lt;li&gt;Spin-polarized [for magnetic materials with weak SOC];&lt;/li&gt;&#xA;&lt;li&gt;Noncolinear [for non-magnetic/magnetic materials with strong SOC];&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But what's the essential difference between them? How can I understand them from the viewpoint of solving the Kohn-Sham equation in the framework of density functional theory?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-27T00:06:54.683" LastActivityDate="2021-02-27T00:06:54.683" Title="What's the difference between spin-unpolarized, spin-polarized and non-colinear calculation?" Tags="|density-functional-theory|kohn-sham|spin-orbit-coupling|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2470" PostTypeId="1" CreationDate="2020-10-10T10:36:17.523" Score="13" ViewCount="639" Body="&lt;p&gt;How much energy difference could be considered as tight convergence? Is total energy difference lower than 1 meV/atom good enough for kpoint convergence for total energy calculation?&lt;/p&gt;&#xA;" OwnerUserId="1412" LastEditorUserId="5" LastEditDate="2020-10-10T11:47:15.553" LastActivityDate="2020-10-10T11:47:15.553" Title="Is total energy difference lower than 1 meV/atom good enough for k-point convergence?" Tags="|density-functional-theory|k-points|convergence-test|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2471" PostTypeId="2" ParentId="2470" CreationDate="2020-10-10T11:22:19.770" Score="10" Body="&lt;p&gt;When using a method like density functional theory we have to consider the accuracy of (i) the numerical solution of the problem and (ii) the physical model we use.&lt;/p&gt;&#xA;&lt;p&gt;The convergence you are refering to is numerical (i.e. how many &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points to include in the numerical approximation of replacing an integral over the Brillouin zone with a discrete sum). In this case, convergence is not something that you can decide on in absolute terms: it depends on what you are interested in. For example, if you are interested in resolving an energy of 100 meV/atom, then converging to below 1 meV/atom is definitely good enough. However, if you want to resolve an energy of 2 meV/atom, then converging below 1 meV/atom may not be sufficient.&lt;/p&gt;&#xA;&lt;p&gt;Having said this, it is also important to keep in mind the accuracy of the physical model used. In the example of density functional theory, you can converge the numerics of your system to below 1 meV/atom, but you may have uncertainties that can be several orders of magnitude larger due to the physical approximations (e.g. choice of exchange-correlation functional).&lt;/p&gt;&#xA;&lt;p&gt;What can we conclude from this? I would say that in most situations, converging energy differences to below 1 meV/atom is good enough. DFT is typically not accurate on the 1 meV/atom energy scale, so the physical model places a strong constraint on what you can achieve. Having said this, you should always consider your convergence on a case-by-case basis to decide what you need to confidently answer the scientific question you have.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-10T11:22:19.770" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="2472" PostTypeId="1" AcceptedAnswerId="2475" CreationDate="2020-10-10T12:46:44.487" Score="9" ViewCount="598" Body="&lt;p&gt;I'm new to micromagnetics and the finite difference method. The &lt;a href=&quot;https://mumax.github.io/&quot; rel=&quot;noreferrer&quot;&gt;mumax3 software&lt;/a&gt; lets you create a variety of geometric shapes. I would like to create a core-shell particle to study magneto-electric effects. Is there a way to visualize the geometry created in mumax3. More specifically I would like a software similar to VMD etc.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="88" LastEditDate="2020-10-10T13:12:58.603" LastActivityDate="2020-11-12T21:54:04.230" Title="How to visualize MuMax3 shapes?" Tags="|magnetism|visualization-software|mumax3|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2473" PostTypeId="1" CreationDate="2020-10-10T17:03:20.030" Score="19" ViewCount="546" Body="&lt;p&gt;I'm looking to get your opinions on the most promising density functionals to use for thermochemistry and kinetics of transition metal complexes. However, as eloquently laid out by Tom Manz on this &lt;a href=&quot;http://www.ccl.net/cgi-bin/ccl/message-new?2019+03+15+001&quot; rel=&quot;noreferrer&quot;&gt;CCL post&lt;/a&gt;, I am not &lt;em&gt;solely&lt;/em&gt; interested in the best functional according to a given benchmark set. As a practical user, there are several other important considerations I'd like to emphasize given my needs:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;There must be support for geometry optimizations and analytical vibrational frequencies for this functional in either ORCA or Gaussian, the former because it is free and publicly available and the latter as a last resort because many computing facilities have a license. For ORCA, this requirement sadly rules out ωB97X-V and ωB97M-V (no support for gradients with nonlocal correlation) and all meta-(hybrid)-GGAs (no support for analytical frequencies). Naturally, this requirement also implies that the functional must be present in ORCA (including via &lt;a href=&quot;https://tddft.org/programs/libxc/&quot; rel=&quot;noreferrer&quot;&gt;libxc&lt;/a&gt;) or Gaussian as well. For Gaussian, meta-(hybrid)-GGAs have support for analytical frequencies, but there is a much more limited selection of functionals (e.g. ωB97X-V and ωB97M-V are not present).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Converging the self-consistent field (SCF) should be as minimal a nightmare as possible. Older meta-(hybrid)-GGAs, such as M06, can be particularly problematic here. This is largely resolved with newer Minnesota functionals that include smoothness constraints, such as revM06 and MN15, but these functionals violate Condition #1 and #4, respectively.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ideally, I'd like it to also be reasonable at capturing spin states of transition metal complexes. This is perhaps asking for a lot, but I put it down anyway. M06-2X, for instance, is shown to be good at predicting kinetics for organometallic reactions, but the very high fraction of HF exchange (i.e. 54%) is concerning for other properties.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If given the option, I'd prefer a functional that does not have an exorbitant number of fitted parameters. I will always have some degree of hesitation with MN15, for instance.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;On one hand, a Minnesota functional would seem to be ideal based solely on the title of this post alone. However, the fact that all of them are meta-(hybrid) functionals rules out their practical use with ORCA, and the newer revised versions of the M06 family are not present in Gaussian. On the other hand, I like what I've seen with the range-separated hybrids ωB97X-V and ωB97M-V, but both can't readily be used in ORCA or Gaussian as mentioned above.&lt;/p&gt;&#xA;&lt;p&gt;I feel like this mostly leaves me with ωB97X-D as the clearest choice to consider. However, I guess this would be sacrificing the greater accuracy of ωB97X-V for the availability of ωB97X-D. In terms of modifications to ωB97X-D, to my surprise ωB97X with D3(BJ) corrections does worse than the standard -D (i.e. D2) correction for barrier heights according to &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.9b01546&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. Will need to investigate this more.&lt;/p&gt;&#xA;&lt;p&gt;Any suggestions are welcome.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2020-12-03T21:52:21.370" LastActivityDate="2021-04-19T02:11:31.683" Title="Promising functionals for transition metal chemistry" Tags="|density-functional-theory|reference-request|functional|transition-metals|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="2474" PostTypeId="2" ParentId="2417" CreationDate="2020-10-10T18:40:29.960" Score="6" Body="&lt;p&gt;I used the structure manipulation scripts provided by &lt;a href=&quot;https://www.mtg.msm.cam.ac.uk/Codes/AIRSS&quot; rel=&quot;nofollow noreferrer&quot;&gt;AIRSS&lt;/a&gt; to generate the conventional cell associated with your primitive cell. I think AIRSS uses &lt;a href=&quot;https://spglib.github.io/spglib/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Spglib&lt;/a&gt; under the hood for this task, so you could probably use Spglib directly if you wanted.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Original cell&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AhY25.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AhY25.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;New cell&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vrwR2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vrwR2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;POSCAR file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR&#xA;1.0000000000000000     &#xA;10.0886200000   0.0000000000   0.0000000000&#xA;0.0000000000   7.1337300000   0.0000000000&#xA;-2.5221540330   0.0000000000  10.0886187273&#xA;A         B         &#xA;16        48&#xA;Direct&#xA;0.0000000000   0.0000000000   0.0000000000&#xA;0.4375000000   0.5000000000   0.7500000000&#xA;0.0937500000   0.2500000000   0.8750000000&#xA;0.0312500000   0.2500000000   0.6250000000&#xA;0.6875000000   0.5000000000   0.7500000000&#xA;0.0937500000   0.7500000000   0.8750000000&#xA;0.0312500000   0.7500000000   0.6250000000&#xA;0.5625000000   0.5000000000   0.2500000000&#xA;0.5000000000   0.5000000000   0.0000000000&#xA;0.9375000000   0.0000000000   0.7500000000&#xA;0.5937500000   0.7500000000   0.8750000000&#xA;0.5312500000   0.7500000000   0.6250000000&#xA;0.1875000000   0.0000000000   0.7500000000&#xA;0.5937500000   0.2500000000   0.8750000000&#xA;0.5312500000   0.2500000000   0.6250000000&#xA;0.0625000000   0.0000000000   0.2500000000&#xA;0.3750000000   0.5000000000   0.5000000000&#xA;0.2187500000   0.2500000000   0.3750000000&#xA;0.3125000000   0.5000000000   0.2500000000&#xA;0.1562500000   0.2500000000   0.1250000000&#xA;0.2500000000   0.5000000000   0.0000000000&#xA;0.1875000000   0.5000000000   0.7500000000&#xA;0.1250000000   0.5000000000   0.5000000000&#xA;0.2187500000   0.7500000000   0.3750000000&#xA;0.9687500000   0.2500000000   0.3750000000&#xA;0.0625000000   0.5000000000   0.2500000000&#xA;0.1562500000   0.7500000000   0.1250000000&#xA;0.9062500000   0.2500000000   0.1250000000&#xA;0.8437500000   0.2500000000   0.8750000000&#xA;0.9375000000   0.5000000000   0.7500000000&#xA;0.7812500000   0.2500000000   0.6250000000&#xA;0.8750000000   0.5000000000   0.5000000000&#xA;0.9687500000   0.7500000000   0.3750000000&#xA;0.8125000000   0.5000000000   0.2500000000&#xA;0.9062500000   0.7500000000   0.1250000000&#xA;0.7500000000   0.5000000000   0.0000000000&#xA;0.8437500000   0.7500000000   0.8750000000&#xA;-0.0000000000   0.5000000000   0.0000000000&#xA;0.7812500000   0.7500000000   0.6250000000&#xA;0.6250000000   0.5000000000   0.5000000000&#xA;0.8750000000   0.0000000000   0.5000000000&#xA;0.7187500000   0.7500000000   0.3750000000&#xA;0.8125000000   0.0000000000   0.2500000000&#xA;0.6562500000   0.7500000000   0.1250000000&#xA;0.7500000000   0.0000000000   0.0000000000&#xA;0.6875000000   0.0000000000   0.7500000000&#xA;0.6250000000   0.0000000000   0.5000000000&#xA;0.7187500000   0.2500000000   0.3750000000&#xA;0.4687500000   0.7500000000   0.3750000000&#xA;0.5625000000   0.0000000000   0.2500000000&#xA;0.6562500000   0.2500000000   0.1250000000&#xA;0.4062500000   0.7500000000   0.1250000000&#xA;0.3437500000   0.7500000000   0.8750000000&#xA;0.4375000000   0.0000000000   0.7500000000&#xA;0.2812500000   0.7500000000   0.6250000000&#xA;0.3750000000   0.0000000000   0.5000000000&#xA;0.4687500000   0.2500000000   0.3750000000&#xA;0.3125000000   0.0000000000   0.2500000000&#xA;0.4062500000   0.2500000000   0.1250000000&#xA;0.2500000000   0.0000000000   0.0000000000&#xA;0.3437500000   0.2500000000   0.8750000000&#xA;0.5000000000   0.0000000000   0.0000000000&#xA;0.2812500000   0.2500000000   0.6250000000&#xA;0.1250000000   0.0000000000   0.5000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I realize this isn't exactly what you wanted (e.g., the new cell vectors aren't actually orthogonal), but I am leaving it here because of the comments requesting for me to undelete the answer.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2020-10-12T20:38:31.283" LastActivityDate="2020-10-12T20:38:31.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2475" PostTypeId="2" ParentId="2472" CreationDate="2020-10-10T19:41:32.197" Score="6" Body="&lt;p&gt;I have found a site with a web-app interface called &lt;a href=&quot;http://dynamag.ugent.be/mumax-view/&quot; rel=&quot;noreferrer&quot;&gt;MuMax-view&lt;/a&gt;. But inorder to view the geometries, the initial shape should be created, set as the geometry and saved. Running that file results in a geom*.ovf file which could be opened in the web-app.&lt;/p&gt;&#xA;&lt;p&gt;Hope this is useful.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-10T19:41:32.197" CommentCount="1" CommunityOwnedDate="2020-10-23T17:34:05.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="2476" PostTypeId="1" CreationDate="2020-10-10T22:35:54.953" Score="6" ViewCount="153" Body="&lt;p&gt;In their &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0364591613000540?casa_token=4ZuPaJBAydkAAAAA:y8sN6Z0NkZ9m12eZQCgbjAa6APIYyPsMgUVuetIVeWvr8EB_RbfBpAIR9lNDdlR5wb0BfvYCHZqR&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, Van de Walle et al. describe how their code &lt;code&gt;mcsqs&lt;/code&gt; treats cluster correlations in the algorithm to generate special quasirandom structures (SQS). In the third section, titled 'Algorithm', they describe how cluster correlations in a perfectly random state are determined. Somehow I can't seem to understand the equation. Can someone help me understand it?&lt;/p&gt;&#xA;&lt;p&gt;If a responder wishes to use illustrations, a perfect test case would be the correlation for nearest neighbour (NN) pairs.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-02T13:01:57.290" LastActivityDate="2020-12-04T10:19:53.943" Title="Cluster correlations for a perfectly random state in the Alloy Theoretic Automated Toolkit" Tags="|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2477" PostTypeId="2" ParentId="2163" CreationDate="2020-10-11T15:10:44.770" Score="4" Body="&lt;h1&gt;Workaround: Install the Windows port of old Avogadro under Linux, using Wine (tested under Mint 20).&lt;/h1&gt;&#xA;&lt;p&gt;Not a proper fix, but should get you going while this issue is sorted out by the developers and packagers. It's possible to install the standalone .exe version of the old Avogadro for Windows under Linux, using &lt;a href=&quot;https://en.wikipedia.org/wiki/Wine_(software)&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wine&lt;/a&gt;. Wine is a compatibility layer, used by many people to run games under Linux, even if there is no Linux port for a given game. I tested it with Avogadro, and it worked.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Install PlayOnLinux (graphical frontend for Wine).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In your terminal, input the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo apt install playonlinux&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The package manager should download about 140MB of the software and all prerequisites, so it may take a while.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Download the Avogadro win32 executable at &lt;a href=&quot;https://sourceforge.net/projects/avogadro/files/avogadro/1.2.0/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://sourceforge.net/projects/avogadro/files/avogadro/1.2.0/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Launch PlayOnLinux, click &amp;quot;install a program&amp;quot;:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FlWt7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FlWt7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;Click &amp;quot;Install a non-listed program&amp;quot;:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UbxdK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UbxdK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;Read the prompts and click next until you reach the manual installation prompt:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9ZbOA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9ZbOA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Z4Hii.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Z4Hii.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gO2Qn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gO2Qn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;6&quot;&gt;&#xA;&lt;li&gt;Select &amp;quot;Install a program in a new virtual drive&amp;quot;. Click next:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xR4QU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xR4QU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;7&quot;&gt;&#xA;&lt;li&gt;Input a name for the virtual drive where the software will be installed. I used just &amp;quot;avogadro&amp;quot;, but you can use another name if you want:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VSa4D.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VSa4D.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;8&quot;&gt;&#xA;&lt;li&gt;The next screen you can just leave as it is (checkboxes unmarked). Click next:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/44DVQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/44DVQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;9&quot;&gt;&#xA;&lt;li&gt;Select &amp;quot;32 bits windows installation&amp;quot; (as the .exe version of Avogadro is compiled for a 32 bits environment). Click next:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4rftR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4rftR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;10&quot;&gt;&#xA;&lt;li&gt;Wait a bit while PlayOnLinux creates your virtual driver, click next, and then browse for the .exe file you downloaded in step 2. Open it. Next:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jDQUQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jDQUQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CFWNh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CFWNh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4tyMw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4tyMw.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3F7kE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3F7kE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;11&quot;&gt;&#xA;&lt;li&gt;Now PlayOnLinux will run the Avogadro Setup Wizard. The steps here are the same you would do in a normal windows install. Just go through the wizard steps and accept the license agreement. The defaults in each prompt should be OK.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/06uTx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/06uTx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;12&quot;&gt;&#xA;&lt;li&gt;When you reach the end of the installer wizard, and click finish, PlayOnLinux will ask you to choose a file to make a shortcut. Select Avogadro.exe, and click next:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WpW0x.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WpW0x.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;13&quot;&gt;&#xA;&lt;li&gt;Now you can quit PlayOnLinux, and reboot your computer. After the reboot, you'll see the shortcut for old Avogadro under Wine in your desktop:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MFR7y.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MFR7y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;14&quot;&gt;&#xA;&lt;li&gt;Now you should be able to run the old Avogadro just by clicking the shortcut. It will render the graphics a bit slower, as it's running through the compatibility layer, but you will be able to keep using the input generators, and other functionality, while it gets ported to the Avogadro 2 from the repository:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GFkK9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GFkK9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2020-10-11T15:10:44.770" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="2478" PostTypeId="1" AcceptedAnswerId="2479" CreationDate="2020-10-11T19:36:08.470" Score="8" ViewCount="532" Body="&lt;p&gt;I have encountered an error using cif2cell while covering a CIF file from COD to quantum ESPRESSO format. The error is as follows.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;command typed:&#xA;&lt;strong&gt;$cif2cell crystal.cif -p quantum-espresso -o crystal.in&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;***Warning: Space group operation check failed for Hall symbol -P 1 (H-M symbol P-1).&#xA;***Warning: Site occupancies not found, assuming all occupancies = 1. Traceback (most recent call last): File “/usr/local/bin/cif2cell”,&#xA;line 1574, in  docstring = StandardDocstring() File&#xA;“/usr/local/bin/cif2cell”, line 1021, in StandardDocstring tmpstring2&#xA;+= “. Reference number : “+ref.databasecode&#xA;TypeError: must be str, not NoneType&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This seems to be a bug in the Quantum Mobile platform too.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2021-10-18T18:46:11.767" Title="How to resolve the cif2cell TypeError?" Tags="|density-functional-theory|quantum-espresso|cif|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="2479" PostTypeId="2" ParentId="2478" CreationDate="2020-10-11T19:36:08.470" Score="5" Body="&lt;p&gt;There is a way around it you can include a NULL database code [using the &lt;strong&gt;_cod_database_code&lt;/strong&gt; keyword ]under the &lt;strong&gt;data_global&lt;/strong&gt; keyword in CIF and it will work.&lt;/p&gt;&#xA;&lt;p&gt;example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;data_global&#xA;_cod_database_code               None&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This worked for me. Since the &lt;strong&gt;cod_databse_code&lt;/strong&gt; is just for printing the first few comments in the input file created by cif2cell it will resolve the issue without affecting the crystal information which we intend to provide.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2020-10-12T19:06:30.563" LastActivityDate="2020-10-12T19:06:30.563" CommentCount="0" CommunityOwnedDate="2020-10-23T17:33:37.873" ContentLicense="CC BY-SA 4.0" />
  <row Id="2480" PostTypeId="2" ParentId="2417" CreationDate="2020-10-11T20:43:52.530" Score="6" Body="&lt;p&gt;I will start by re-stating your question to make sure I understand what you mean. You have a cell with lattice vectors written in Cartesian coordinates as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\mathbf{a}=\hat{\mathbf{x}}-\hat{\mathbf{y}}-\hat{\mathbf{z}} \\&#xA;\mathbf{b}=\hat{\mathbf{x}}+\hat{\mathbf{y}}-\hat{\mathbf{z}} \\&#xA;\mathbf{c}=1.5\hat{\mathbf{x}}+2.5\hat{\mathbf{z}}&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;You then seek a transformation of this cell to obtain a new cell with the following lattice vectors:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\mathbf{a}^{\prime}=\hat{\mathbf{x}}-\hat{\mathbf{y}} \\&#xA;\mathbf{b}^{\prime}=\hat{\mathbf{x}}+\hat{\mathbf{y}}-2.5\hat{\mathbf{z}} \\&#xA;\mathbf{c}^{\prime}=2.5\hat{\mathbf{x}}+2.5\hat{\mathbf{y}}+2\hat{\mathbf{z}}&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;A superlattice is related to an original lattice by a transformation matrix &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; whose matrix elements &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; are &lt;em&gt;integers&lt;/em&gt;. The relation is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\mathbf{a}^{\prime} \\&#xA;\mathbf{b}^{\prime} \\&#xA;\mathbf{c}^{\prime}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a} \\&#xA;\mathbf{b} \\&#xA;\mathbf{c}&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;So your question is: can we find a matrix &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; of integer elements that obeys this equation? I think the answer is &lt;em&gt;no&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is most easily seen with the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{c}^{\prime}$&lt;/span&gt; lattice vector:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\mathbf{c}^{\prime}&amp;amp;=&amp;amp;S_{31}\mathbf{a}+S_{32}\mathbf{b}+S_{33}\mathbf{c} \\&#xA;&amp;amp;=&amp;amp;S_{31}(\hat{\mathbf{x}}-\hat{\mathbf{y}}-\hat{\mathbf{z}})+S_{32}(\hat{\mathbf{x}}+\hat{\mathbf{y}}-\hat{\mathbf{z}})+S_{33}(1.5\hat{\mathbf{x}}+2.5\hat{\mathbf{z}}) \\&#xA;&amp;amp;=&amp;amp;(S_{31}+S_{32}+1.5S_{33})\hat{\mathbf{x}}+(-S_{31}+S_{32})\hat{\mathbf{y}}+(-S_{31}-S_{32}+2.5S_{33})\hat{\mathbf{z}}.&#xA;\end{eqnarray}&lt;/span&gt;&#xA;You want this to equal:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{c}^{\prime}=2.5\hat{\mathbf{x}}+2.5\hat{\mathbf{y}}+2\hat{\mathbf{z}}.&#xA;$$&lt;/span&gt;&#xA;If you compare the &lt;span class=&quot;math-container&quot;&gt;$\hat{\mathbf{y}}$&lt;/span&gt; components, your condition becomes:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;-S_{31}+S_{32}=2.5.&#xA;$$&lt;/span&gt;&#xA;This equation has no solution for integer &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt;, so you cannot build the second set of cell parameters from the first.&lt;/p&gt;&#xA;&lt;p&gt;[Disclaimer: plenty of signs and numbers, so may have a mistake in the calculation. However, you should still be able to use this strategy to figure out the correct answer if different.]&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-11T20:43:52.530" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="2481" PostTypeId="2" ParentId="2435" CreationDate="2020-10-11T21:58:01.790" Score="3" Body="&lt;p&gt;Technically I'm not answering your question of whether this method is applicable to slabs of ~3 nm thickness, but wanted to give you an answer that could be helpful anyway. I would not generally use '2D' for slabs, although I have not tested it before. The parameter of interest here is &lt;code&gt;assume_isolated = 'esm'&lt;/code&gt;. In my own experience, with ESM vs. a standard dipole correction the energies and potentials come out identical, assuming you converged your vacuum thickness and other calculation parameters.&lt;/p&gt;&#xA;&lt;p&gt;As a side note, switching between a dipole correction or ESM can be a strategy to try when a slab is giving you SCF convergence problems.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Also, I think you should be able to use '2D' for slabs. There may be something odd going on here.&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-10-12T02:00:18.940" LastActivityDate="2020-10-12T02:00:18.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2482" PostTypeId="1" AcceptedAnswerId="3732" CreationDate="2020-10-12T02:27:05.603" Score="12" ViewCount="1678" Body="&lt;p&gt;The charge density is an important physical quantity obtained from first-principles calculations based on density functional theory (DFT). Much useful information about the investigated materials can be extracted from it, such as chemical bonding, charge transfer, and orbital hybridization. Here I post this question to ask:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What can we learn by inspecting charge densities calculated with DFT?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Here is an example answer to this question &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.201504572&quot; rel=&quot;nofollow noreferrer&quot;&gt;following this paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pLf34.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pLf34.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The author compares the differential charge density accumulation between bilayer PtS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and concludes the bilayer PtS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; will host a more strong interlayer coupling due to the significant charge accumulation.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1021" LastEditDate="2020-10-13T19:12:49.843" LastActivityDate="2020-11-12T00:57:16.110" Title="What can we learn by inspecting charge densities calculated with DFT?" Tags="|density-functional-theory|charge-density|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="2483" PostTypeId="1" CreationDate="2020-10-12T15:09:12.753" Score="5" ViewCount="1341" Body="&lt;p&gt;&lt;strong&gt;Disclaimer: Assume the questioner is a novice in DFT&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is PAW an improvement over the pseudopotential method? In terms of Perdew, Burke, and Ernzerhof (PBE) parameterization, what is the difference between PAW-PBE and GGA-PBE?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-10-12T18:26:21.617" LastActivityDate="2020-10-13T00:05:29.797" Title="The projector augmented wave (PAW) method, pseudopotentials (PP), and exchange correlation functionals" Tags="|density-functional-theory|pseudopotentials|gpaw|exchange-correlation|projector-augmented-wave|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2484" PostTypeId="1" CreationDate="2020-10-12T17:33:04.690" Score="7" ViewCount="52" Body="&lt;p&gt;Can we design metal organic frameworks, layered double hydroxide using LAMMPS? How?&lt;/p&gt;&#xA;&lt;p&gt;I want to synthesize a metal organic framework or such materials, and I want to ask if I put two to three chemicals in the simulation and allow it to incubate under certain temperature/pressure/catalyst, will the reaction proceed?&lt;/p&gt;&#xA;&lt;p&gt;Will I be able to see if the reaction is happening or not? Will I be able to see the synthesis of metal organic framework in &lt;em&gt;in silico&lt;/em&gt; mode?&lt;/p&gt;&#xA;" OwnerUserId="1417" LastEditorUserId="5" LastEditDate="2020-11-29T01:17:37.073" LastActivityDate="2020-11-29T01:17:37.073" Title="Reaction simulation at specific temperature, pH and pressure" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="1" ClosedDate="2020-12-03T22:10:32.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="2485" PostTypeId="5" CreationDate="2020-10-12T18:26:33.267" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-12T18:26:33.267" LastActivityDate="2020-10-12T18:26:33.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2486" PostTypeId="4" CreationDate="2020-10-12T18:26:33.267" Score="0" Body="Questions about PAW." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-12T18:26:33.267" LastActivityDate="2020-10-12T18:26:33.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2487" PostTypeId="1" CreationDate="2020-10-12T20:31:40.230" Score="10" ViewCount="589" Body="&lt;p&gt;Let's say I want to work with the slabs, and I want to add 20 Angstrom vacuum space. Do I need just to set lattice parameter &lt;code&gt;c=20&lt;/code&gt; and k-point 1 in this direction?&lt;/p&gt;&#xA;" OwnerUserId="1412" LastEditorUserId="5" LastEditDate="2020-10-12T21:19:40.220" LastActivityDate="2020-10-12T21:19:40.220" Title="How to set vacuum space for slabs?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="2488" PostTypeId="2" ParentId="2487" CreationDate="2020-10-12T20:39:49.703" Score="7" Body="&lt;p&gt;If you are using fractional coordinates in your input file, setting &lt;code&gt;c=20&lt;/code&gt;, will &amp;quot;zoom&amp;quot; all your cell.&lt;/p&gt;&#xA;&lt;p&gt;Increasing cell parameters in order to add vacuum will work only if using Cartesian coordinates.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-10-12T21:19:17.267" LastActivityDate="2020-10-12T21:19:17.267" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="2489" PostTypeId="1" CreationDate="2020-10-12T20:58:49.420" Score="14" ViewCount="198" Body="&lt;p&gt;Consider the following &lt;code&gt;bestcorr.out&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2   0.866025    -0.000000   0.000000    -0.000000&#xA;2   0.866025    0.000000    -0.000000   0.000000&#xA;2   0.866025    -0.000000   0.000000    -0.000000&#xA;2   1.000000    -0.000000   0.000000    -0.000000&#xA;2   1.000000    -0.000000   -0.000000   -0.000000&#xA;2   1.000000    -0.000000   0.000000    -0.000000&#xA;2   1.414214    -0.000000   0.000000    -0.000000&#xA;2   1.414214    -0.000000   -0.000000   -0.000000&#xA;2   1.414214    0.006944    0.000000    0.006944&#xA;Objective_function= -1.630678&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This was for a BCC ternary SQS. Let's consider the 1st nearest neighbour (NN) pairs. There are three of them; how do we differentiate among them?&lt;/p&gt;&#xA;&lt;p&gt;Here is the part of &lt;code&gt;clusters.out&lt;/code&gt; that concerns these pairs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4&#xA;0.86603&#xA;2&#xA;1.50000 0.50000 0.50000 1 0&#xA;1.00000 -0.00000 1.00000 1 0&#xA;&#xA;8&#xA;0.86603&#xA;2&#xA;1.50000 0.50000 0.50000 1 1&#xA;1.00000 -0.00000 1.00000 1 0&#xA;&#xA;4&#xA;0.86603&#xA;2&#xA;1.50000 0.50000 0.50000 1 1&#xA;1.00000 -0.00000 1.00000 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It might be helpful to see the &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node47.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;mcsqs manual page&lt;/a&gt; and &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node35.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;corrdump manual page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Why are there 3 different kinds of pairs with the same distance? At first, I thought in a ternary alloy it could mean AB, BC, and CA pairs. A, B, and C being constituent atoms. Now that I think of it, that doesn't make sense else it would apply to triangles and higher clusters as well but it doesn't.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-12-25T20:56:08.037" LastActivityDate="2021-12-25T20:56:08.037" Title="How to differentiate similar clusters in the mcsqs output in ATAT?" Tags="|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T03:23:13.667" ContentLicense="CC BY-SA 4.0" />
  <row Id="2490" PostTypeId="2" ParentId="2483" CreationDate="2020-10-13T00:05:29.797" Score="3" Body="&lt;p&gt;PAW is proposed to deal with the interaction between electrons and ions. However, PBE or GGA (PBE just one kind of GGA) is just the exchange-correlation functional. You can think PAW and PBE are related to the two different terms in the Kohn-Sham equation. So your question is totally meaningless because you are comparing two completely different concepts.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-10-13T00:05:29.797" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3490" PostTypeId="2" ParentId="1979" CreationDate="2020-10-13T02:40:14.603" Score="5" Body="&lt;p&gt;The question is related essentially to solve the Kohn-Sham equation with an atomic-like basis set. In fact, different implementations of DFT are distinguished mainly by their basis set and how they orthogonalize themselves to the core levels. In particular, the choice of basis set forms the core of any electronic structure method.&lt;/p&gt;&#xA;&lt;p&gt;Dedepending on the choice of basis set and how to orthogonalize, four methods are proposed as shown in the following figure (Nuclei are shown as dots):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jCfYv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jCfYv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The all-electron methods APW and KKR on the right substitute (augment)&#xA;the envelope function (green) with numerical solutions of partial waves inside&#xA;augmentation spheres (blue and red). Parts inside augmentation spheres are&#xA;called ‘‘partial waves’’.&lt;/li&gt;&#xA;&lt;li&gt;The two figures on the left use a pseudopotential&#xA;allowing their envelope functions to be smooth, with no augmentation needed.&#xA;A pseudopotential’s radius corresponds to a characteristic augmentation radius.&lt;/li&gt;&#xA;&lt;li&gt;The top two figures use plane waves for envelope functions; the bottom two&#xA;use atom-centered local basis sets.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The example implementation for these methods:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PP-PW: VASP&lt;/li&gt;&#xA;&lt;li&gt;APW: Wien2K&lt;/li&gt;&#xA;&lt;li&gt;PP-LO: Gaussian&lt;/li&gt;&#xA;&lt;li&gt;KKR: &lt;a href=&quot;https://www.questaal.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Questaal&lt;/a&gt; (This is what you are looking for!)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For a more detailed comparison between these methods, you can take a look at &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465519303868?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;the implementation paper of Questaal.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When are atomic-orbital-basis (rather than plane-wave) methods appropriate in periodic DFT?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you want to combine NEGF with DFT to calculate the transport properties of the device, you should use atomic-orbital-basis, as Questaal adopted.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-22T10:04:59.010" LastActivityDate="2021-02-22T10:04:59.010" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3491" PostTypeId="1" AcceptedAnswerId="4059" CreationDate="2020-10-13T15:37:32.493" Score="12" ViewCount="643" Body="&lt;p&gt;I am trying to repeat the result of &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202003425&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; for Zn absorbed on the armchair graphene slab.&lt;/p&gt;&#xA;&lt;p&gt;The relaxed top and side structures are the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TmpLa.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TmpLa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OyRpi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OyRpi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The relaxed structure is almost the same as the cited paper. Then the energy calculation based on this relaxed structure is listed below:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;E(slab+Zn)=-759.31696 (eV)&lt;/li&gt;&#xA;&lt;li&gt;E(slab)=-759.30724 (eV)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The energy of Zn is obtained from its bulk calculation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;E(Zn)=-1.1078938 (eV)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Then the binding energy is estimated as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;=E(slab+Zn)-E(slab)-E(Zn)=1.0981738 (eV)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, the result of the cited paper is -0.2 eV:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/B6KQR.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B6KQR.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What am I missing?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For completeness, I will give my input cards for relaxation and static calculations as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; System=2D&#xA; ISTART=0        !startjob: 0-new 1-cont 2-samecut&#xA; ICHARG=2        !charge: 1-file 2-atom 10-const&#xA; ENCUT=500       !energy cutoff in eV&#xA; EDIFF=1E-6      !stopping-criterion for electronic upd.&#xA; NELM=300        !nr. of electronic steps&#xA; ISMEAR=0        !part. occupancies&#xA; SIGMA=0.05      !broadening in eV -4-tet -1-fermi 0-gaus&#xA; IALGO=38&#xA; LREAL=Auto&#xA; IVDW=11&#xA;&#xA; #------------------&#xA; #ISPIN=2        !spin polarized calculation (2-yes 1-no)&#xA; #MAGMOM=128*0   !initial mag moment / atom&#xA; #LSORBIT=.TRUE. !if .TRUE. switches on spin-orbit coupling&#xA; #SAXIS= 0 0 1   !quantisation axis for spin&#xA; #ISYM=0         !symmetry: 0-nonsym 1-usesym&#xA;&#xA; Dynamic:&#xA; ISIF=2          &#xA; IBRION=2&#xA; NSW=300&#xA; EDIFFG=-0.005&#xA;&#xA; Parallelization:&#xA; NPAR=8&#xA; #KPAR=4&#xA;&#xA; Output:&#xA; LCHARG=.FALSE.&#xA; LWAVE=.FALSE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;=========================================&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; System=2D&#xA; ISTART=0        !startjob: 0-new 1-cont 2-samecut&#xA; ICHARG=2        !charge: 1-file 2-atom 10-const&#xA; ENCUT=500       !energy cutoff in eV&#xA; EDIFF=1E-6      !stopping-criterion for electronic upd.&#xA; NELM=300        !nr. of electronic steps&#xA; ISMEAR=0        !part. occupancies&#xA; SIGMA=0.05      !broadening in eV -4-tet -1-fermi 0-gaus&#xA; IALGO=38&#xA; LREAL=Auto&#xA; IVDW=11&#xA;&#xA; #------------------&#xA; #ISPIN=2        !spin polarized calculation (2-yes 1-no)&#xA; #MAGMOM=128*0   !initial mag moment / atom&#xA; #LSORBIT=.TRUE. !if .TRUE. switches on spin-orbit coupling&#xA; #SAXIS= 0 0 1   !quantisation axis for spin&#xA; #ISYM=0         !symmetry: 0-nonsym 1-usesym&#xA;&#xA; Dynamic:&#xA; #ISIF=2          &#xA; #IBRION=2&#xA; #NSW=300&#xA; #EDIFFG=-0.005&#xA;&#xA; #Parallelization:&#xA; NPAR=8&#xA; #KPAR=4&#xA;&#xA; Output:&#xA; #LCHARG=.FALSE.&#xA; #LWAVE=.FALSE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For convenience, the computational details for the cited paper are put below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gVLDl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gVLDl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-10-13T21:10:11.257" LastActivityDate="2021-03-18T23:31:52.733" Title="Binding energy calculation for Zn atom on armchair graphene slab?" Tags="|vasp|molecular-modeling|binding-energy|graphene|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3492" PostTypeId="1" AcceptedAnswerId="3498" CreationDate="2020-10-13T17:36:36.273" Score="16" ViewCount="1803" Body="&lt;p&gt;I'm having an issue installing the open-source version of Pymol using Anaconda on Windows. I have Python 3.8.3 installed and when I try to add the package with Conda using &lt;code&gt;conda install -c tpeulen pymol-open-source&lt;/code&gt;, I get the error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;UnsatisfiableError: The following specifications were found&#xA;to be incompatible with the existing python installation in your environment:&#xA;&#xA;Specifications:&#xA;&#xA;  - pymol-open-source -&amp;gt; python[version='&amp;gt;=3.7,&amp;lt;3.8.0a0']&#xA;&#xA;Your python: python=3.8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Okay so it can't do Python 3.8? Not a problem, I'll just make a Python 3.7 virtual environment &lt;code&gt;conda create -n &amp;quot;py37&amp;quot; python=3.7.9&lt;/code&gt;. Except, for some reason this still returns an error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;UnsatisfiableError: The following specifications were found&#xA;to be incompatible with the existing python installation in your environment:&#xA;&#xA;Specifications:&#xA;&#xA;  - pymol-open-source -&amp;gt; python[version='&amp;gt;=2.7,&amp;lt;2.8.0a0|&amp;gt;=3.6,&amp;lt;3.7.0a0|&amp;gt;=3.8,&amp;lt;3.9.0a0|&amp;gt;=3.5,&amp;lt;3.6.0a0']&#xA;&#xA;Your python: python=3.7&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This claims that Python3.8 should work and the only version that doesn't work is 3.7! So, as a last attempt I tried switching to Python 3.6.12 and, sure enough, I got another error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;UnsatisfiableError: The following specifications were found&#xA;to be incompatible with the existing python installation in your environment:&#xA;&#xA;Specifications:&#xA;&#xA;  - pymol-open-source -&amp;gt; python[version='&amp;gt;=3.7,&amp;lt;3.8.0a0']&#xA;&#xA;Your python: python=3.6&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This says only 3.7 will work, but that is clearly not the case. Am I using Conda wrong here or is there some issue with this package? How can I get the open-source PyMol installed properly?&lt;/p&gt;&#xA;&lt;p&gt;Note: There is Incentive PyMol released by Schrodinger, which I could successfully install through Conda, but this is only a trial version. I would like to use the free version if possible.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:06:17.043" LastActivityDate="2021-11-10T18:06:17.043" Title="Open Source PyMol Conda Package: UnsatisfiableError" Tags="|python|software-assistance|open-source|pymol|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3493" PostTypeId="1" CreationDate="2020-10-13T17:37:12.327" Score="10" ViewCount="188" Body="&lt;p&gt;I am trying to understand how to quantify the electronic interaction/conduction/overlap between two metal cores at varying distances. As someone who works primarily with classical MD, and has less experience in first-principles simulations, I wanted to know if those more experienced could give some recommendations on the most appropriate simulation/software to do this, and the type of output that would be used to quantify this.&lt;/p&gt;&#xA;" OwnerUserId="599" LastActivityDate="2020-10-14T13:03:55.683" Title="Quantifying electronic overlap?" Tags="|density-functional-theory|electronic-structure|electron-correlation|electronic-transport|atomic-physics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3494" PostTypeId="2" ParentId="2455" CreationDate="2020-10-13T17:44:41.850" Score="6" Body="&lt;p&gt;I don't know the implementation details, and if can be counted as &amp;quot;AI derived force field&amp;quot;, but, If you're interested in metal complexes, there's a free software, Python-based tool called molSimplify, that uses machine learning to optimize geometry of metal complexes. From &lt;a href=&quot;http://hjkgrp.mit.edu/molSimplify-tutorials&quot; rel=&quot;noreferrer&quot;&gt;their site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Geometry optimization with density functional theory (DFT), a general&#xA;procedure to obtain the ground state structures of a complex, is&#xA;computationally demanding in terms of time and can also easily fail.&#xA;Two main failure modes are 1) the expected geometry cannot maintain&#xA;stable during the DFT simulation (e.g., ligand dissociation) and 2)&#xA;the electronic structure of the optimized geometry is bad, which&#xA;indicates the system of study is out of the domain of applicability of&#xA;DFT. Either case can only be identified after a simulation completes,&#xA;leading to a massive waste of the computational resources (and your&#xA;time!).&lt;/p&gt;&#xA;&lt;p&gt;To address this challenge, we built machine learning models to&#xA;classify the simulation outcomes and readily achieved a good&#xA;performance on the out-of-sample test data.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For more details, see their paper &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b00057&quot; rel=&quot;noreferrer&quot;&gt;Duan, Chenru, et al. “Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models”. Journal of Chemical Theory and Computation, vol. 15, no 4, abril de 2019, p. 2331–45. ACS Publications, doi:10.1021/acs.jctc.9b00057.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2020-10-13T17:44:41.850" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3495" PostTypeId="2" ParentId="35" CreationDate="2020-10-13T21:10:56.217" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;General Info&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As far as I understand you're taking a Fourier Transform of an image. In your case, that image corresponds to that of a microstructure alloy. So basically in 2D-Fourier transforms we are trying to model the intensity levels of the image and represent it in terms of a frequency plot. This is analogous to the 1D Fourier transform.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is there a relationship between the angle of these bands in the&#xA;Fourier image and the orientation of the grain boundaries in the real&#xA;space image?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This can only be answered if there was an image provided. But still one could say that there is a relationship between the bands and the orientation of the grain boundaries. In the image of simple patters given below you can see the relation between the Spatial and Fourier domains. For an image of an alloy microstructure we cannot explicitly see the realtionship due to the immense detail in the spatial domain.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NeLo6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NeLo6.png&quot; alt=&quot;2D Fourier Transform&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Another observation is that if high frequencies are removed, and the&#xA;inverse Fourier transform is taken, a significant amount of noise is&#xA;removed, and I am mostly left with the grain boundaries of the&#xA;microstructure. Is there any other kind of useful information that can&#xA;be extracted from the Fourier image?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This disappearence of noise takes place because the noise being a sharply varying intensity value is modelled by high frequencies in the Frequency domain. Removing those will in face reveal the boundaries which are represented by smoothly varing intensity values.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps. :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-13T21:10:56.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3496" PostTypeId="2" ParentId="2434" CreationDate="2020-10-13T21:26:21.207" Score="7" Body="&lt;p&gt;The reason why even number k-point grids are prefered in the case of some symmetries like FCC lattices is mainly due to the concept of the Irreducible Brillouin Zone (IBZ).&lt;/p&gt;&#xA;&lt;p&gt;Here is an example for FCC:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GHHan.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GHHan.png&quot; alt=&quot;IBZ for FCC&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the number of points in the k-point grid in the IBZ is the same for even as well as odd k-points (M value). Here the points in the IBZ determine the execution speed of the code (given by tm/t1). But since the even number k-point grid have more accuracy due to larger number of k points, we prefer them over the odd values. It's like having more accuracy for the same execution speed.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-10-13T23:46:19.120" LastActivityDate="2020-10-13T23:46:19.120" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3497" PostTypeId="2" ParentId="3492" CreationDate="2020-10-13T21:35:23.563" Score="9" Body="&lt;p&gt;If you're using Linux its better if you install such packages using the apt-get method.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;apt-get install pymol&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I've encountered a similar error while installing MatPlotLib through conda.&lt;/p&gt;&#xA;&lt;p&gt;For more info you can follow this link:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pymolwiki.org/index.php/Linux_Install&quot; rel=&quot;noreferrer&quot;&gt;https://pymolwiki.org/index.php/Linux_Install&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-13T21:35:23.563" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3498" PostTypeId="2" ParentId="3492" CreationDate="2020-10-13T22:19:47.573" Score="9" Body="&lt;p&gt;I was able to find a workaround to get open source PyMol installed on Windows. Christoph Gohlke at the University of California has a large library of &lt;a href=&quot;https://www.lfd.uci.edu/%7Egohlke/pythonlibs/#pymol&quot; rel=&quot;nofollow noreferrer&quot;&gt;precompiled Python wheel files&lt;/a&gt; of various scientific packages, including PyMol. I was able to find a Windows version for Python 3.8 &lt;code&gt;pymol‑2.5.0a0‑cp38‑cp38‑win_amd64.whl&lt;/code&gt; and after downloading this file, I was able to install PyMol using pip &lt;code&gt;python -m pip install pymol‑2.5.0a0‑cp38‑cp38‑win_amd64.whl&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As mentioned on the &lt;a href=&quot;https://pymolwiki.org/index.php/Windows_Install&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyMol wiki&lt;/a&gt;, I also had to pip install the &lt;code&gt;pyqt5&lt;/code&gt; package to get the graphical window working. I'm still puzzled why Conda didn't work, but at least it's possible to access this program on Windows.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-07T18:06:41.350" LastActivityDate="2021-07-07T18:06:41.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3499" PostTypeId="1" CreationDate="2020-10-14T06:48:08.107" Score="11" ViewCount="158" Body="&lt;p&gt;I am trying to create a KNIME workflow that would accept a list of compounds and carry out &lt;strong&gt;bioisosteric replacements&lt;/strong&gt; (we will use the following &lt;em&gt;example&lt;/em&gt; here: &lt;em&gt;carboxylic acid to tetrazole&lt;/em&gt;) automatically.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NOTE: I am using the following workflow as inspiration : &lt;a href=&quot;https://www.myexperiment.org/workflows/2683.html&quot; rel=&quot;noreferrer&quot;&gt;RDKit-bioisosteres (myexperiment.org)&lt;/a&gt;. This uses a text file as SMARTS input. &lt;strong&gt;I cannot seem to replicate the SMARTS format used here.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For this, I plan to use the &lt;a href=&quot;https://nodepit.com/node/org.rdkit.knime.nodes.onecomponentreaction2.RDKitOneComponentReactionNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;Rdkit One Component Reaction&lt;/a&gt; node which uses a set of compounds to carry out the reaction on as input and a SMARTS string that defines the reaction.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My issue is the generation of a working SMARTS string describing the reaction.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would like to input two SDF files (or another format, not particularly attached to SDF): one with the group to replace (&lt;em&gt;carboxylic acid&lt;/em&gt;) and one with the list of possible bioisosteric replacements (&lt;em&gt;tetrazole&lt;/em&gt;). I would then combine these two in KNIME and generate a SMARTS string for the reaction to then be used in the &lt;em&gt;Rdkit One Component Reaction&lt;/em&gt; node.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NOTE: The input SDF files have the structures written with an&#xA;attachment point (*COOH for the carboxylic acid for example) which&#xA;defines where the group to replace is attached. I suspect this is the&#xA;cause of many of the issues I am experiencing.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So far, I can easily generate the reactions in RXN format using the &lt;a href=&quot;https://nodepit.com/node/com.epam.indigo.knime.rbuilder.IndigoReactionBuilderNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;Reaction Builder node&lt;/a&gt; from the Indigo node package. However, converting this reaction into a SMARTS string that is accepted by the &lt;a href=&quot;https://nodepit.com/node/org.rdkit.knime.nodes.onecomponentreaction2.RDKitOneComponentReactionNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;Rdkit One Component Reaction&lt;/a&gt; node has proven tricky.&lt;/p&gt;&#xA;&lt;p&gt;What I have tried so far:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Converting RXN to SMARTS (&lt;a href=&quot;https://nodepit.com/node/org.knime.chem.base.node.converter.parser.MolParserNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;Molecule Type Cast&lt;/a&gt; node) : gives the following error code : &lt;code&gt;scanner: BufferScanner::read() error&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Converting the Source and Target molecules into SMARTS (&lt;em&gt;Molecule Type Cast&lt;/em&gt; node) : gives the following error code : &lt;code&gt;SMILES loader: unrecognised lowercase symbol: y&lt;/code&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;showing this as a string in KNIME shows that the conversion is not carried out and the string is of SDF format : &lt;code&gt;*filename*.sdf 0 0 0 0  0 0    0 V3000M V30 BEGIN&lt;/code&gt; etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Converting the Source and Target molecules into RDkit first (&lt;a href=&quot;https://nodepit.com/node/org.rdkit.knime.nodes.molecule2rdkit.Molecule2RDKitConverterNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;RDkit from Molecule&lt;/a&gt; node) then from RDkit into SMARTS (&lt;a href=&quot;https://nodepit.com/node/org.rdkit.knime.nodes.rdkit2molecule.RDKit2MoleculeConverterNodeFactory&quot; rel=&quot;noreferrer&quot;&gt;RDkit to Molecule&lt;/a&gt; node, SMARTS option). This outputs the following SMARTS strings:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Carboxylic acid : &lt;code&gt;[#6](-[#8])=[#8]&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Tetrazole : &lt;code&gt;[#6]1:[#7H]:[#7]:[#7]:[#7]:1&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This is as close as I've managed to get. I can then join these two smarts strings with &lt;code&gt;&amp;gt;&amp;gt;&lt;/code&gt; in between (output: &lt;code&gt;[#6](-[#8])=[#8]&amp;gt;&amp;gt;[#6]1:[#7H]:[#7]:[#7]:[#7]:1&lt;/code&gt;) to create a SMARTS reaction string but this is not accepted as an input for the Rdkit One Component Reaction node.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Error message in KNIME console :&#xA;ERROR RDKit One Component Reaction 0:40       Creation of Reaction from SMARTS value failed: null&#xA;WARN  RDKit One Component Reaction 0:40       Invalid Reaction SMARTS: missing&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Note that the SMARTS strings that this last option (3.) generates are very different than the ones used in the &lt;a href=&quot;https://www.myexperiment.org/workflows/2683.html&quot; rel=&quot;noreferrer&quot;&gt;myexperiments.org example&lt;/a&gt; (&lt;code&gt;[*:1][C:2]([OH])=O&amp;gt;&amp;gt;[*:1][C:2]1=NNN=N1&lt;/code&gt;). I also seem to have lost the attachment point information through these conversions which are likely to cause issues in the rest of the workflow.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Therefore I am looking for a way to generate the SMARTS strings used in the myexperiments.org example on my own sets of substituents.&lt;/strong&gt; Obviously doing this by hand is not an option. I would also like this workflow to use only the open-source nodes available in KNIME and not proprietary nodes (Schrodinger etc.).&lt;/p&gt;&#xA;&lt;p&gt;Hopefully, someone can help me out with this. If you need my current workflow I am happy to upload that with the source files if required.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for your help,&lt;/p&gt;&#xA;&lt;p&gt;Stay safe and healthy!&lt;/p&gt;&#xA;&lt;p&gt;-Antoine&lt;/p&gt;&#xA;" OwnerUserId="1420" LastActivityDate="2020-10-18T13:22:14.630" Title="Bioisosteric replacement using SMARTS (KNIME and RDKit)" Tags="|computational-chemistry|rdkit|" AnswerCount="0" CommentCount="4" ClosedDate="2020-12-03T21:59:26.110" ContentLicense="CC BY-SA 4.0" />
  <row Id="3501" PostTypeId="2" ParentId="2469" CreationDate="2020-10-14T09:20:09.273" Score="7" Body="&lt;p&gt;As far I understand, to search for spin-polarized solutions, the DFT code will have to solve two coupled Kohn-Sham equations, one for each of the two spin species. There is both direct and indirect coupling between the two Kohn-Sham equations .&lt;/p&gt;&#xA;&lt;p&gt;The direct coupling comes about by the dependence of the effective potential in the Kohn-Sham equation corresponding to spin-up/down electrons on the number densities (or charge densities) of both spin-up and spin-down electrons (most evidently, the Hartree part of the effective potential depends on the total number density, which is the sum of the number densities of spin-up and spin-down electrons).&lt;/p&gt;&#xA;&lt;p&gt;The indirect coupling comes about by the requirement that the total numbers of spin-up and spin-down electrons must add up to a given integer N, the total number of electrons in the system.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-14T09:20:09.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3502" PostTypeId="2" ParentId="3493" CreationDate="2020-10-14T09:30:21.527" Score="4" Body="&lt;p&gt;By the &amp;quot;metal cores&amp;quot;, If you're referring to the overlapping of wave functions of electrons of metal ions separated by a distance, then you can in principle use quantum ESPRESSO to get some insights. You can define a CIF file with the ions separated at varying distances from each other and visualize the electronic density.&lt;/p&gt;&#xA;&lt;p&gt;Apart from quantum ESPRESSO, you can also use CP2K to create STM images in conduction mode. I'm not quite sure about the latter but it's worth a try.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-14T09:30:21.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3503" PostTypeId="1" AcceptedAnswerId="3512" CreationDate="2020-10-14T12:58:32.920" Score="10" ViewCount="342" Body="&lt;p&gt;There are various questions on this SE that discuss DFT in terms of band gaps - &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/265/are-there-any-cases-where-lda-gga-overestimates-band-gaps-if-so-what-is-the-rea&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1202/is-the-electronic-band-gap-the-only-thing-that-is-affected-when-switching-from&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2378/is-there-an-energy-gap-correction-factor-that-needs-to-be-used-in-dft-calculatio&quot;&gt;here&lt;/a&gt;, and elsewhere - but they touch upon different aspects.&lt;/p&gt;&#xA;&lt;p&gt;P.S.: I'm asking this from the mind-frame of someone who doesn't know much more than how to put tags together in some DFT code's input file and get a shining, all-hail-lords-Kohn-and-Sham energy per atom value as the output.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-12T23:00:16.827" LastActivityDate="2020-12-12T23:00:16.827" Title="What are the pitfalls of calculating band gaps via density functional theory?" Tags="|density-functional-theory|" AnswerCount="2" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="3504" PostTypeId="2" ParentId="3493" CreationDate="2020-10-14T13:03:55.683" Score="5" Body="&lt;p&gt;I recommend the use of &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt; package. This software is free with Windows/Linux versions. It uses the wave function calculated from other software.&lt;/p&gt;&#xA;&lt;p&gt;From the site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Briefly speaking, Multiwfn can perform wavefunction analyses based on outputted file of almost all well-known quantum chemistry programs, such as Gaussian, ORCA, GAMESS-US, Molpro, NWChem, Dalton, xtb, PSI4, Molcas, Q-Chem, MRCC, deMon2k, Firefly, CFour, Turbomole...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This imply you have to set-up your calculations using one of those software above and then, use Multiwfn to run the analysis you want.&lt;/p&gt;&#xA;&lt;p&gt;Some of the analysis it is able to do:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Topology analysis for any real space function, such as electron density (AIM analysis), Laplacian, ELF, LOL, electrostatic potential&#xA;and so on. Critical points (CPs) can be located, topology paths and&#xA;interbasin surfaces can be generated, and then they can be directly&#xA;visualized in a 3D GUI window or be plotted in plane map. Value of&#xA;various real space functions can be calculated at critical points or&#xA;along topology paths. CP properties can be decomposed as orbital&#xA;contributions.&lt;/li&gt;&#xA;&lt;li&gt;Population analysis. Hirshfeld, Hirshfeld-I, VDD, Mulliken, Löwdin, Modified Mulliken (including three methods: SCPA, Stout &amp;amp; Politzer,&#xA;Bickelhaupt), Becke, ADCH (Atomic dipole moment corrected Hirshfeld),&#xA;CM5, CHELPG, Merz-Kollmann, RESP (Restrained ElectroStatic Potential),&#xA;RESP2, AIM (Atoms-In-Molecules), EEM (Electronegativity Equalization&#xA;Method) and PEOE (Gasteiger) are supported. Electrostatic interaction&#xA;energy of two given fragments can be calculated based on atomic&#xA;charges.&lt;/li&gt;&#xA;&lt;li&gt;Orbital composition analysis. Mulliken, Stout &amp;amp; Politzer, SCPA, Hirshfeld, Hirshfeld-I, Becke, natural atomic orbital (NAO) and AIM&#xA;methods are supported to obtain orbital composition. Orbital&#xA;delocalization index (ODI) can be outputted to quantify extent of&#xA;spatial delocalization of orbitals.&lt;/li&gt;&#xA;&lt;li&gt;Plotting total, partial, overlap population density-of-states (TDOS, PDOS, OPDOS) and MO-PDOS. Up to 10 fragments can be very flexibly and&#xA;conveniently defined. Local DOS (LDOS) can also be plotted for a point&#xA;as curve map or for a line as color-filled map. Furthermore, plotting&#xA;photoelectron spectrum (PES) based on (generalized) Koopmans' theorem&#xA;is fully supported.&lt;/li&gt;&#xA;&lt;li&gt;Analyzing real space functions in fuzzy atomic spaces (defined by Becke, Hirshfeld or Hirshfeld-I partitions). These quantities can be&#xA;computed: Integral of real space functions in atomic spaces or in&#xA;overlap region between atomic spaces, dipole and multipole moments of&#xA;atom/fragment/molecule, atomic overlap matrix (AOM), localization and&#xA;delocalization indices (LI, DI), condensed linear response kernel,&#xA;multi-center DI, as well as four aromaticity indices, namely FLU,&#xA;FLU-pi, PDI and information-theoretic index.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;... and many more.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-10-14T13:03:55.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3505" PostTypeId="1" CreationDate="2020-10-14T13:43:11.983" Score="14" ViewCount="1640" Body="&lt;p&gt;Fermi energy is affected by the temperature and whether the material is an insulator/semiconductor/metal, but how is the Fermi energy determined in DFT calculations and how reliable are the obtained values?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2022-04-08T12:18:40.833" LastActivityDate="2022-04-08T12:18:40.833" Title="Determining Fermi energy in density functional theory" Tags="|density-functional-theory|fermi-energy|" AnswerCount="3" CommentCount="3" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3507" PostTypeId="2" ParentId="3505" CreationDate="2020-10-15T05:12:15.540" Score="8" Body="&lt;p&gt;Usually, it is assumed that the Fermi energy is the energy of the highest occupied electronic state. It is well defined for metals with partially filled bands. For semiconductors and dielectrics, however, there may be a discrepancy between different software packages, since the Fermi energy can correspond to the center of the bandgap at &lt;span class=&quot;math-container&quot;&gt;$\pu{0 K}$&lt;/span&gt; in the case of an undoped semiconductor or it can be at the top of the valence band. The former convention pins the Fermi energy to the energy of a state which has the occupation probability of &lt;span class=&quot;math-container&quot;&gt;$0.5$&lt;/span&gt; even at &lt;span class=&quot;math-container&quot;&gt;$T&amp;gt;\pu{0 K}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1402" LastEditorUserId="7" LastEditDate="2022-01-17T15:23:08.977" LastActivityDate="2022-01-17T15:23:08.977" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3508" PostTypeId="2" ParentId="3503" CreationDate="2020-10-15T05:26:36.657" Score="2" Body="&lt;p&gt;DFT is not applicable for computing the bandgap. If it gives it close to the experimental results, it is more or less accidentally. Usually, DFT is used as a basis set generator for subsequent computations based on GW theory or TDDFT.&lt;/p&gt;&#xA;&lt;p&gt;DFT is by definition the ground-state theory - all Kohn-Sham theorems constituting the basis of DFT have been derived regarding the ground state properties. Also, there is no proof (at least I have not seen any) that Kohn-Sham orbitals can be somehow related to the excited states. The bandgap is a property related to the excited states though.&lt;/p&gt;&#xA;" OwnerUserId="1402" LastEditorUserId="1402" LastEditDate="2020-10-17T02:09:57.323" LastActivityDate="2020-10-17T02:09:57.323" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="3509" PostTypeId="2" ParentId="2163" CreationDate="2020-10-15T06:00:31.880" Score="4" Body="&lt;p&gt;I found in the Avogadro forum the solution to this problem. Compile the source code by following the simple instructions reported here:&#xA;&lt;a href=&quot;https://discuss.avogadro.cc/t/possible-issue-with-debian-ubuntu-packages-for-avogadro2-and-input-generators/3306&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://discuss.avogadro.cc/t/possible-issue-with-debian-ubuntu-packages-for-avogadro2-and-input-generators/3306&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I tried and it worked for me.&#xA;It seems to be a bug with the packaging process.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="5" LastEditDate="2020-10-15T09:32:14.890" LastActivityDate="2020-10-15T09:32:14.890" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3510" PostTypeId="1" AcceptedAnswerId="3526" CreationDate="2020-10-12T19:27:17.437" Score="15" ViewCount="532" Body="&lt;p&gt;I am new to computational chemistry, I have used mainly GAMESS and Orca. In GAMESS, there are orbital localisation schemes like Pipek-Mezey, Ruedenberg-Edminston, etc. which generate orbitals that resemble the traditional 2-centre-2-electron bonds that chemists use.&lt;/p&gt;&#xA;&lt;p&gt;There is also the NBO program which can interface with GAMESS. It produces 'natural bonding orbitals' which are also said to resemble the traditional bonding types in organic chemistry. (I have not used the NBO program myself.)&lt;/p&gt;&#xA;&lt;p&gt;What is the difference between localised orbitals and NBOs? Are they the same thing, or different implementations of the same thing, or are they completely different?&lt;/p&gt;&#xA;" OwnerUserId="1380" OwnerDisplayName="Shoubhik R Maiti" LastEditorUserId="49" LastEditDate="2020-10-15T14:59:55.373" LastActivityDate="2020-10-16T18:03:23.690" Title="What is the difference between orbital localisation and NBO?" Tags="|computational-chemistry|quantum-chemistry|gamess|orbitals|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3511" PostTypeId="2" ParentId="3510" CreationDate="2020-10-13T11:06:14.093" Score="11" Body="&lt;p&gt;Note: This was a response I've originally written on Chemistry Stack Exchange, so it was intended to be very brief.&lt;/p&gt;&#xA;&lt;p&gt;Natural Bond Orbital Theory is basically (among plenty of other uses) providing an orbital localisation scheme to achieve similarity to Lewis structures. In some of my answers you have probably read the term 'Lewis-like' structures for these occasions.&lt;/p&gt;&#xA;&lt;p&gt;The NBO Theory has been around for quite some time and it is an evolving theory with many possible applications (see also &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1323/49&quot;&gt;Plotting of natural bond orbitals&lt;/a&gt;. It can be a very distinguished and helpful tool for interpretation of chemical bonds, structures, and reaction. At its core, however, it is also an orbital localisation scheme, just like the ones you have mentioned (ref. also &lt;a href=&quot;https://en.wikipedia.org/wiki/Localized_molecular_orbitals&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia: Localised MO&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Natural_bond_orbital&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia: NBO&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Since there are no &lt;em&gt;true&lt;/em&gt; localised orbitals, there won't be one 'correct' answer, hence there are different approaches. See for some similarities &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/49&quot;&gt;What are the types of charge analysis?&lt;/a&gt;&#xA;This question on Chemistry Stack Exchange is also related: &lt;a href=&quot;https://chemistry.stackexchange.com/q/285/4945&quot;&gt;What is natural bond orbital theory used for?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR:&lt;/strong&gt; For most intents and purposes, NBO can be considered an orbital localisation scheme, which shares some of the goals with others, but the theory can be applied to analyse bonding further.&lt;/p&gt;&#xA;" OwnerUserId="49" OwnerDisplayName="Martin - マーチン" LastEditorUserId="49" LastEditDate="2020-10-15T11:21:21.357" LastActivityDate="2020-10-15T11:21:21.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3512" PostTypeId="2" ParentId="3503" CreationDate="2020-10-15T20:59:17.587" Score="9" Body="&lt;p&gt;The important thing to keep in mind is that the Kohn-Sham (KS) band gap is &lt;em&gt;not&lt;/em&gt; the fundamental/quasiparticle gap. Even theoretically. This is not an 'underestimation' of the band gap. They are not the same gap.&lt;/p&gt;&#xA;&lt;p&gt;The fundamental quasiparticle (QP) gap is calculated as the difference between valence band maxima and conduction band minima, but &lt;em&gt;for different hamiltonians&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A part of the exchange-correlation potential called the response potential has changed in a discontinuous manner as you've added the new electron to see where your conduction band minima is. That added electron has changed the hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;I think this little bit is really a dominant pitfall (I'm sure there are many others). It helps to keep in mind that &lt;strong&gt;the KS gap is not the QP gap&lt;/strong&gt;. Even with the 'exact' KS functional, you wouldn't get the bandgap that compares favourably with experimental QP gaps.&lt;/p&gt;&#xA;&lt;p&gt;Almost the entirety of the above rant has been taken from:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2017/cp/c7cp02123b#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2017/cp/c7cp02123b#!divAbstract&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/cp/c3cp52547c#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2013/cp/c3cp52547c#!divAbstract&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As above, I'm sure there are many other pitfalls, but this is the one I like to keep in mind the most.&lt;/p&gt;&#xA;" OwnerUserId="512" LastActivityDate="2020-10-15T20:59:17.587" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3513" PostTypeId="2" ParentId="2469" CreationDate="2020-10-15T23:33:20.577" Score="10" Body="&lt;p&gt;Basically, this is the split between restricted, unrestricted, and generalized Hartree-Fock (or Kohn-Sham) theory.&lt;/p&gt;&#xA;&lt;p&gt;In the restricted theory, both the spin-up and spin-down electrons occupy the same spatial orbital: &lt;span class=&quot;math-container&quot;&gt;$\psi_{2n}({\bf r}) = \phi_n ({\bf r}) |\uparrow \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\psi_{2n+1}({\bf r}) = \phi_n ({\bf r}) |\downarrow \rangle$&lt;/span&gt;. This is the Ansatz you use to solve the Kohn-Sham equations. (In the restricted open-shell theory, the number of spin-up and spin-down electrons may not match.)&lt;/p&gt;&#xA;&lt;p&gt;In the unrestricted theory, the spin-up and spin-down electrons can have different spatial parts, for which the Ansatz reads: &lt;span class=&quot;math-container&quot;&gt;$\psi_{2n}({\bf r}) = \phi^\uparrow_n ({\bf r}) |\uparrow \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\psi_{2n+1}({\bf r}) = \phi^\downarrow _n ({\bf r}) |\downarrow \rangle$&lt;/span&gt;. If you have a well-behaved system near the equilibrium, the unrestricted solution typically collapses to the restricted solution.&lt;/p&gt;&#xA;&lt;p&gt;Most non-relativistic quantum chemistry is based on these two approaches. However, the generalized theory, in which the orbitals aren't eigenfunctions of &lt;span class=&quot;math-container&quot;&gt;$\hat{S}_z$&lt;/span&gt; anymore, as you also allow mixing of spin-up and spin-down character, has also been found to be useful in e.g. bond breaking &lt;a href=&quot;https://doi.org/10.1021/ct200345a&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 7, 2667 (2011)&lt;/a&gt;, but you really need it if you have an operator in your Hamiltonian that couples the spins.&lt;/p&gt;&#xA;&lt;p&gt;Formally, the Ansatz of the generalized approach looks something like &lt;span class=&quot;math-container&quot;&gt;$\psi_{n}({\bf r}) = c_\uparrow \phi^\uparrow _n ({\bf r}) |\uparrow \rangle  + c_\downarrow \phi^\downarrow _n ({\bf r}) |\downarrow \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-10-15T23:33:20.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3514" PostTypeId="2" ParentId="2464" CreationDate="2020-10-15T23:56:50.893" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What role does the constant charge density play in GGA?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Most GGAs give out LDAs at the limit of zero gradient. This is, however, not always true.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Also, in literature, methods describe DFT calculations done with GGA as parameterized by so-and-so. What does that mean?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;GGAs is a form of functional, like LDA: it does not say anything about which functional form is used. You can fit i.e. parametrize the functional in an infinite number of ways. This is an issue already at the LDA level: even though the exchange functional can be derived easily, the correlation part is only known at certain points derived from e.g. quantum Monte Carlo simulations. Some sort of interpolation is necessary to get a functional that can be evaluated at arbitrary densities, e.g. LibXC has almost 40 different LDA correlation functionals for three dimensional systems. If you go to the GGA level, the exchange functionals also have different forms.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="7" LastEditDate="2020-10-16T16:05:17.740" LastActivityDate="2020-10-16T16:05:17.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3515" PostTypeId="1" AcceptedAnswerId="3517" CreationDate="2020-10-16T01:54:23.707" Score="10" ViewCount="814" Body="&lt;p&gt;A quick google search of the Minnesota Functionals will lead you to the wikipedia page on them where it will state the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;M11-L: Local functional (0% HF exchange) with dual-range DFT exchange. Intended to be fast, to be good for transition metals, inorganic, organometallics and non-covalent interactions, and to improve much over M06-L.&#xA;M11: Range-separated hybrid functional with 42.8% HF exchange in the short-range and 100% in the long-range. Intended for main group thermochemistry, kinetics and non-covalent interactions, with an intended performance comparable to that of M06-2X, and for TD-DFT applications, with an intended performance comparable to M06-HF.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;along with more descriptions of the rest of the functionals. Within each description it gives and an intended use for the functional. I was wondering if there exists a master-list with similar descriptions for all the currently existing functionals.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know of any such list?&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-10-16T17:13:42.083" LastActivityDate="2020-10-16T17:13:42.083" Title="Is there a list of all functionals?" Tags="|density-functional-theory|functional|databases|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3516" PostTypeId="2" ParentId="3515" CreationDate="2020-10-16T02:13:15.673" Score="8" Body="&lt;p&gt;I don't think so. The Minnesota functional wiki page is a bit weird, since general density functional approximations don't have a page, and much more popular functionals like various LDAs, GGAs (e.g. BP86, PBE) and meta-GGAs (e.g. TPSS) haven't been described.&lt;/p&gt;&#xA;&lt;p&gt;Most functionals are intended for ground-state energy calculations, while some are fit for properties (e.g. NMR shifts). However, the choice of the functional shouldn't follow just the original intent of the authors, but the actual performance of the functional for whatever it is you are doing. The exact functional should reproduce all properties exactly, but approximate functionals differ in their accuracy depending on what is studied.&lt;/p&gt;&#xA;&lt;p&gt;There are several independent assessments of density functionals, and it is always good to check a few widely used functionals yourself against higher-level reference data to see which ones work for your purpose.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-10-16T02:13:15.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3517" PostTypeId="2" ParentId="3515" CreationDate="2020-10-16T03:43:23.223" Score="9" Body="&lt;p&gt;While it doesn't include intended uses directly and isn't necessarily exhaustive, check out the list of exchange-correlation functionals implemented by Libxc. There are a lot! They also include the literature references for each functional.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.tddft.org/programs/libxc/functionals/&quot; rel=&quot;noreferrer&quot;&gt;https://www.tddft.org/programs/libxc/functionals/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-16T03:43:23.223" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3518" PostTypeId="1" CreationDate="2020-10-16T11:50:36.280" Score="8" ViewCount="716" Body="&lt;p&gt;Can we calculate electron affinity of a semiconductor (e.g., for Si) using density functional theory calculations in VASP? Which calculations are needed to compute electron affinity and band offsets?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="686" LastEditDate="2020-10-16T22:59:14.520" LastActivityDate="2020-10-16T22:59:14.520" Title="Electron Affinity of Semiconductors via DFT" Tags="|density-functional-theory|vasp|surfaces|heterostructures|solid-solid-interface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3519" PostTypeId="1" AcceptedAnswerId="4197" CreationDate="2020-10-16T12:52:39.690" Score="7" ViewCount="226" Body="&lt;p&gt;I'm trying to perform a QSPR research and for it I need to generate a library of compounds.&#xA;Now I'm using a plugin for MarvinSkectch for enumerating Markush structures but it doesn't work properly (maybe I misuse it). So I'm looking for a free/trial software that allows to generate compound library based on general structure.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2020-11-29T01:35:15.570" LastActivityDate="2021-01-23T10:00:53.370" Title="Software to generate compound library" Tags="|software-recommendations|qsar|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3521" PostTypeId="5" CreationDate="2020-10-16T13:17:15.093" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-10-16T13:17:15.093" LastActivityDate="2020-10-16T13:17:15.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3522" PostTypeId="4" CreationDate="2020-10-16T13:17:15.093" Score="0" Body="Questions related to the GAMESS(US) or GAMESS(UK) software." OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2020-10-16T15:04:34.233" LastActivityDate="2020-10-16T15:04:34.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3523" PostTypeId="1" CreationDate="2020-10-16T15:25:43.503" Score="10" ViewCount="93" Body="&lt;p&gt;I'm trying to calculate the adsorption energies of various adsorbates on Fe2O3 surfaces (although, with there being many possible surfaces for Fe2O3 it is quite complex, but that's for another time...). I was wondering should I converge my adsorption energies versus the number of unit cells or add layers of atoms such that I am adding fractions of unit cells to the bottom of my slab? If its the case of unit cells, the Fe2O3 unit cell as a slab is already reasonably large, but doubling or even tripling it leads to it becoming unusably expensive for the resources I have available. Alternatively, adding atoms is less expensive but here we are breaking the stoichiometry of the unit cell.&lt;/p&gt;&#xA;&lt;p&gt;What would you advise?&lt;/p&gt;&#xA;&lt;p&gt;Here is my unit cell with&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A/B lengths = 5.035&lt;/li&gt;&#xA;&lt;li&gt;C length = 13.750.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uk0MF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uk0MF.png&quot; alt=&quot;Image of unit cell of Fe2O3&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="990" LastEditorUserId="5" LastEditDate="2020-12-03T22:06:28.703" LastActivityDate="2020-12-03T22:06:28.703" Title="Converge number of layers of atoms or number of unit cells for adsorption calculations?" Tags="|density-functional-theory|vasp|transition-metals|adsorption|" AnswerCount="0" CommentCount="10" ClosedDate="2021-01-23T13:14:12.167" ContentLicense="CC BY-SA 4.0" />
  <row Id="3524" PostTypeId="1" CreationDate="2020-10-16T17:07:12.677" Score="9" ViewCount="578" Body="&lt;p&gt;I have two polymer molecules with benzene rings as a part of them. I would like to understand how the interactions between them influences the solvability of the polymer in a non-aqeous solvent. I understand that it's termed under pi-stacking. Is it just about the distances between the two rings? If so, should I just calculate the distance between the centres of the two rings at different time instants?&lt;/p&gt;&#xA;&lt;p&gt;Can someone explain how to qualitatively and quantitatively understand pi-pi stacking using GROMACS or any other tools?&lt;/p&gt;&#xA;" OwnerUserId="148" LastActivityDate="2020-10-16T17:30:37.813" Title="Is there a way to understand pi-pi interactions through GROMACS?" Tags="|molecular-dynamics|gromacs|polymers|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3525" PostTypeId="2" ParentId="3524" CreationDate="2020-10-16T17:30:37.813" Score="6" Body="&lt;p&gt;I fear that GROMACS may not be able to capture the interaction you are talking about (If someone is an expert in GROMACS please correct me).  This sort of pi-stacking interaction will likely result in either a charge transfer (if asymmetric) or some sort of pi-pi bonding interaction that a forcefield is unlikely to capture.&lt;/p&gt;&#xA;&lt;p&gt;If you took a snapshot of the MD and looked at a DFT level you may see some favorable interactions occurring, this might be a good use of QM/MM calculations.  In a DFT calculation, you can quantify the charge transfer and orbital overlaps.&lt;/p&gt;&#xA;&lt;p&gt;You should see if your forcefield is validated to reproduce pi-pi interactions as a first step.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-16T17:30:37.813" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3526" PostTypeId="2" ParentId="3510" CreationDate="2020-10-16T18:03:23.690" Score="9" Body="&lt;p&gt;In short, natural atomic orbitals are the orbitals you get from diagonalizing the one-particle reduced density matrix. One can then localize this set of orbitals via some maximization criteria. Natural bond orbitals are the orbitals you get when maximizing the occupancy of orbitals such that electrons occupy the space between two atoms or on a single atom. These are then interpreted as bonds and lone pairs. The definition of these criteria somewhat hard to explain as you have to define the natural hybrid orbitals first and go from there.&lt;/p&gt;&#xA;&lt;p&gt;All localization schemes which don't begin with natural atomic orbitals define some arbitrary measure which should intuitively localize the orbitals and then maximize or minimize this measure. For instance, one might begin with the atomic orbitals and maximize electron repulsion, minimize orbital overlap on different atoms, or maximize partial charge on each atom, etc.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Orbital localization schemes and NBO orbitals both tend to result in orbitals that are localized and sort of look like the atomic orbitals chemists are familiar with. They are somewhat different from a theoretical point of view however.&lt;/p&gt;&#xA;&lt;p&gt;All orbital localization schemes (let's just call this a definition in case it's not strictly true) are unitary transformations of the canonical Hartree-Fock (HF) orbitals or some other choice of orbitals (e.g. post-HF). This means that the energy is unchanged under this transformation.&lt;/p&gt;&#xA;&lt;p&gt;For instance, the Edmiston-Reudenberg localization scheme iteratively maximizes the electron self-repulsion. Intuitively, this will make the orbitals compact since these integrals will be over all electrons and all orbitals. My understanding is that this method results in very good orbital localization, but it is not popular as it requires the calculation of many integrals which one would not ordinarily need to calculate.&lt;/p&gt;&#xA;&lt;p&gt;The Pipek-Mezey localization scheme takes the same idea but maximizes the partial charges in each orbital. These charges are trivial to calculate at virtually no extra expense as they are just related to the population of each orbital. The downside is that these charges are known to be arbitrary and highly basis set dependent. Nonetheless, the results work out quite well, so this is the method I have seen used the most.&lt;/p&gt;&#xA;&lt;p&gt;Natural Orbitals (NO) result in localized orbitals by diagonalizing the one-particle reduced density matrix (1-RDM), which can be formed from canonical HF orbitals (or other orbitals). For explanation of what that means see &lt;a href=&quot;https://chemistry.stackexchange.com/questions/80351/are-the-canonical-orbitals-of-hartree-fock-also-the-natural-orbitals&quot;&gt;this Chem.se question&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;NBOs are a further transformation of these NOs which variationally maximize the Lewis-like character of the orbitals. Basically, it maximally localizes the orbitals either between pairs of atoms or on a single atom. This sort of defines the dominant Lewis structure for the system.&lt;/p&gt;&#xA;&lt;p&gt;As an aside, I think it's somewhat dangerous to take any set of orbitals too seriously. The wavefunction and orbitals are not observable, so any inference you make on the basis of the wavefunction itself is coming from something which is not observable. Maybe the orbitals lead you to make a prediction about some observable quantity, but this always feels a bit &lt;em&gt;ad hoc&lt;/em&gt; to me.&lt;/p&gt;&#xA;&lt;p&gt;I also have it in my mind that there are certain types of orbitals derived from natural atomic orbitals which are not unitarily related to the atomic orbital basis used to form the 1-RDM. I can't find anything that says this though. I feel like I've heard of schemes where certain off-diagonal elements of the 1-RDM are thrown out if they are quite small. This would make the transformation non-unitary, but I don't know where that idea came from, so I could be mis-remembering something.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My understanding is that NBOs have been used to provide some physical interpretation of the electronic wavefunction in simple to understand terms. I don't know how common this is today. I don't seem to see many theoretical papers which do this, but I would think it might be more common in physical organic chemistry, and I don't commonly read papers in that field.&lt;/p&gt;&#xA;&lt;p&gt;Localization schemes are more commonly used, in my experience, to speed up certain types of post-HF calculations. This works because electron correlation between a particular pair of electrons falls off very quickly when the one-electron wavefunctions have a very small overlap. Thus, many schemes have been devised to get MP2 or CCSD energies at a cheaper cost than the full method by working in a localized basis. DLPNO-CCSD(T) is probably the most well-known method of this type. Generally, one can perform more effective integral screening when working in a localized basis as well.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2020-10-16T18:03:23.690" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3527" PostTypeId="2" ParentId="3518" CreationDate="2020-10-16T19:48:30.207" Score="5" Body="&lt;p&gt;This may be a bit of a rough answer, so apologies in advance...&lt;/p&gt;&#xA;&lt;p&gt;Since the eigenvalues obtained using non-energy-consistent pseudopotentials (i.e. the situation in VASP as far as I know) do not themselves have physical meaning, we typically use a slab system with an explicit vacuum, in order to make reference to vacuum. A more common situation is calculating work function of metal slabs, where you subtract the Fermi energy from the vacuum level to get the work function. In the case of electron affinity, I suppose you would subtract the conduction band minimum from the vacuum level. Here's how you would do this:&lt;/p&gt;&#xA;&lt;p&gt;Construct a slab with the desired crystal orientation. You will need to converge both the thickness of the slab (so the center is &amp;quot;bulk-like&amp;quot;), and the thickness of the vacuum region. You could probably follow the instructions &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Ni_111_surface_high_precision&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for VASP, but use your desired material and subtract the conduction band minimum energy rather than the code's output Fermi energy.&lt;/p&gt;&#xA;&lt;p&gt;Since you mentioned band offsets, I'm guessing you want to calculate them using the electron affinities. I just want to make sure you're aware that this method (Anderson's rule) does not work in many situations. If you're going to be calculating electron affinities with slabs anyways, you might as well explicitly calculate band offsets with a layered supercell. You can do this by determining the offset of the potentials on each side of the interface, and then using reference bulk calculations to determine the offsets. You can see &lt;a href=&quot;https://doi.org/10.1039/C6CP04997D&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; and the references therein. Another way to do this could be explicitly from layer-resolved projected density of states. &lt;a href=&quot;https://www.onlinelibrary.wiley.com/doi/10.1002/aelm.201900808&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt; does something like that. I also typically have used this method. I know the first method has some theory behind it, I'm not sure of how the second method compares in that regard.&lt;/p&gt;&#xA;&lt;p&gt;Also keep in mind that band offsets will also be affected by the challenges of calculating band gaps in DFT... It would be worth reading up on this. Good luck!&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-16T19:48:30.207" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3528" PostTypeId="1" CreationDate="2020-10-16T22:01:37.207" Score="9" ViewCount="2935" Body="&lt;p&gt;The requirement I have is to calculate the bulk modulus from the energy values at certain volumes obtained via DFT calculations. Can you provide the instructions to use the ev.x tool in the Quantum ESPRESSO code?&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="336" LastEditDate="2021-05-13T09:05:21.217" LastActivityDate="2021-05-13T09:05:21.217" Title="How to use the ev.x tool in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|elasticity|curve-fitting|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3530" PostTypeId="1" AcceptedAnswerId="3536" CreationDate="2020-10-16T22:23:35.450" Score="8" ViewCount="787" Body="&lt;p&gt;I am trying to model a system that has both anions and cations interacting with each other. (In this case it is calcium ion interacting with two small carboxylic acid molecules). Now, looking through literature, I have found many people dealing with such systems using augmented basis sets on all atoms.&lt;/p&gt;&#xA;&lt;p&gt;However, most introductory molecular modelling books say that augmented basis functions should only be used with anions, and atoms that are participating in long-range interactions. It is also frequently mentioned that using diffuse functions on cations can cause basis set overcompleteness problem.&lt;/p&gt;&#xA;&lt;p&gt;So what is the best choice and why? All augmented, or mixed, or no diffuse functions?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2020-10-30T19:36:17.323" LastActivityDate="2020-10-30T19:36:17.323" Title="Which basis set should be used for a system that contains both anions and cations?" Tags="|computational-chemistry|basis-sets|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3531" PostTypeId="1" CreationDate="2020-10-17T10:36:26.543" Score="6" ViewCount="669" Body="&lt;p&gt;When trying to manually optimise the geometry of the crystal, I've faced an issue wherein the code stopped the convergence process after just 100 steps (which was the default maximum). Is there a way to increase this?&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-18T05:06:26.097" Title="How can I increase the default maximum limit on step size for convergence in quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|geometry-optimization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3532" PostTypeId="2" ParentId="3531" CreationDate="2020-10-17T10:36:26.543" Score="6" Body="&lt;p&gt;If we need more than 100 iterations (the default maximum) to achieve convergence in the SCF calculation. To increase that number (let’s say, to 500), we need to add the following to the quantum-espresso input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;ELECTRONS&#xA;electron_maxstep = 500&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-17T10:36:26.543" CommentCount="0" CommunityOwnedDate="2020-10-23T17:33:09.620" ContentLicense="CC BY-SA 4.0" />
  <row Id="3533" PostTypeId="1" AcceptedAnswerId="3534" CreationDate="2020-10-17T10:54:47.870" Score="8" ViewCount="543" Body="&lt;p&gt;I needed the Energy and Volume values for predicting the bulk modulus of a crystal via the Birch Murmaghan equation. Can I get a bash script for doing the same.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-10-17T14:38:57.913" LastActivityDate="2020-10-17T14:38:57.913" Title="How to extract the Pressure, Energy and unit-cell volume from quantum ESPRESSO output file using bash script?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3534" PostTypeId="2" ParentId="3533" CreationDate="2020-10-17T10:54:47.870" Score="9" Body="&lt;p&gt;You can use the following script to do the extraction rather than manually looking through the entire document:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/sh&#xA;&#xA;grep &amp;quot;A=&amp;quot; Input_file_name.in&#xA;grep &amp;quot;unit-cell volume&amp;quot; Output_File_Name.out&#xA;grep &amp;quot;!&amp;quot; Output_File_Name.out&#xA;grep -A 5 &amp;quot;Computing stress&amp;quot; Output_File_Name.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Copy and paste the above code snippet into a file named &amp;quot;File_Name.sh&amp;quot; use the following command to make it executable.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;chmod +x File_Name.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Run the script as follows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./File_Name.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-17T10:54:47.870" CommentCount="0" CommunityOwnedDate="2020-10-23T17:32:17.537" ContentLicense="CC BY-SA 4.0" />
  <row Id="3535" PostTypeId="1" AcceptedAnswerId="3537" CreationDate="2020-10-17T20:16:00.760" Score="8" ViewCount="219" Body="&lt;p&gt;Let's say a &lt;em&gt;supercell&lt;/em&gt; has 100 atoms, and we want to see how charge is transferred from/to an atom to/from its nearest neighbours. I am more interested in knowing how to do this with density functional theory (DFT).&lt;/p&gt;&#xA;&lt;p&gt;Are charge-per-atom values, that any DFT code outputs, sufficient for the task?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-10-18T18:01:03.270" LastActivityDate="2020-11-03T23:55:46.777" Title="How can I do a charge transfer study in bulk crystalline materials?" Tags="|density-functional-theory|charge-transfer|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3536" PostTypeId="2" ParentId="3530" CreationDate="2020-10-17T21:26:12.880" Score="12" Body="&lt;p&gt;The safe choice is to use diffuse functions on all atoms. It is quite rare to run into pathological overcompleteness with standard augmented basis sets, unless you're looking at very high-energy geometries. Overcompleteness may become an issue if you're using multiply augmented basis sets, such as d-aug-cc-pVXZ or t-aug-cc-pVXZ, but as I've recently shown in &lt;a href=&quot;https://doi.org/10.1063/1.5139948&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 151, 241102 (2019)&lt;/a&gt;, even pathological linear dependencies can be straightforwardly removed with a simple modification to the basis set orthonormalization algorithms, which already implemented in several quantum chemistry codes.&lt;/p&gt;&#xA;&lt;p&gt;The guideline that &amp;quot;augmented basis functions should only be used with anions&amp;quot; is a bit wrong, since - like you said - diffuse basis functions also improve the description of long-range effects, which may be important even for DFT energies.&lt;/p&gt;&#xA;&lt;p&gt;Augmenting all atoms is simple, but the downside is that the calculations become more costly since the diffuse functions are less affected by integrals screening. My suggestion would be to first establish the complete basis set limit by looking at basis sets of increasing size with full augmentation, and then see if you can get away with omitting the diffuse functions in a part of your system if you need to do larger / longer calculations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-10-17T21:26:12.880" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3537" PostTypeId="2" ParentId="3535" CreationDate="2020-10-17T21:26:33.287" Score="7" Body="&lt;p&gt;The &lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;noreferrer&quot;&gt;Bader Charge Analysis&lt;/a&gt; can do just this.  If you can get your charge density into a CHGCAR format, you can use this program with any code.  It will divide the charge density into volumes by looking at the zero flux surfaces between atoms.  This is just one example of a atom in molecule analysis though, but one that is particularly robust for planewave based codes.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-17T21:26:33.287" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3538" PostTypeId="2" ParentId="3531" CreationDate="2020-10-18T04:11:06.437" Score="5" Body="&lt;p&gt;Anoop's answer is correct. Since you mentioned you are optimizing geometry, I thought I would add a related option that may be useful. Sometimes it is worth trying:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;scf_must_converge = .false.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;also within the &lt;code&gt;&amp;amp;ELECTRONS&lt;/code&gt; card, but only if you are having trouble with a single step in the geometry convergence. Sometimes when optimizing a structure, an intermediate step results in slow or no scf convergence, and allowing the code to just move past it often restores convergence in the following steps. Make sure this is the case by carefully checking the results if you use this option.&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="5" LastEditDate="2020-10-18T05:06:26.097" LastActivityDate="2020-10-18T05:06:26.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3539" PostTypeId="1" AcceptedAnswerId="3560" CreationDate="2020-10-18T11:28:03.430" Score="10" ViewCount="83" Body="&lt;p&gt;I would like to calculate some DFT+U values for a few elements (Fe, Co, Ni, Cu, Zn?) and am attempting to take the approach from the &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.73.195107&quot; rel=&quot;noreferrer&quot;&gt;Ceder 2006&lt;/a&gt; paper.  Where does the Ceder paper take its experimental values from?  It seems to be from NIST and a &amp;quot;Materials Thermochemistry&amp;quot; book, but I am having trouble finding or accessing these.&lt;/p&gt;&#xA;&lt;p&gt;Is there a list compiled for the redox reactions in the Ceder paper?  I could of course, just read the plot, but I would prefer a primary source for this data.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="671" LastEditDate="2020-10-18T16:17:44.493" LastActivityDate="2020-10-19T21:47:20.013" Title="DFT+U Values from Reference Formation Energies" Tags="|transition-metals|dft-u|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3540" PostTypeId="1" AcceptedAnswerId="3556" CreationDate="2020-10-18T15:27:49.153" Score="7" ViewCount="651" Body="&lt;p&gt;I often see DFT+U corrections for transition metals with delocalization problems, but a comment about applying a U correction to nitrogen or oxygen's p orbitals also shows up when digging around in the literature.  It seems this is not done often, which makes understanding why and when it is done more difficult to search.&lt;/p&gt;&#xA;&lt;p&gt;When is this appropriate to consider?&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-19T16:09:33.253" Title="Apply DFT+U to Oxygen/Nitrogen p Orbitals" Tags="|density-functional-theory|reference-request|dft-u|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3541" PostTypeId="5" CreationDate="2020-10-18T18:34:12.080" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-18T18:34:12.080" LastActivityDate="2020-10-18T18:34:12.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3542" PostTypeId="4" CreationDate="2020-10-18T18:34:12.080" Score="0" Body="When there's a calculation or data in a paper that the user is trying to reproduce." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-18T18:34:12.080" LastActivityDate="2020-10-18T18:34:12.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3543" PostTypeId="1" CreationDate="2020-10-18T19:40:06.320" Score="10" ViewCount="383" Body="&lt;p&gt;I have been using the &lt;a href=&quot;https://vampire.york.ac.uk/tutorials/bilayer-system-generation/&quot; rel=&quot;noreferrer&quot;&gt;Vampire atomistic simulation software&lt;/a&gt; for a while and it has a useful simulation for predicting the curie temperature. But in order to do that I need the exchange matrix of Co-CoO system which should include the constant which represents the interaction between spins in the Co part, spins in the CoO part and a constant representing the interaction of spins in the Co-CoO interface. So I have been able to obtain the values for the Co and CoO part by couldn't find any resources to calculate the term representing the interaction at the interface. Should I use the average of the two values I've obtained. How should I approach this problem?&lt;/p&gt;&#xA;&lt;p&gt;An excerpt from the VAMPIRE manual regarding this is given below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;material:exchange-matrix[index] = float [default 0.0 J/link] Defines&#xA;the pair-wise exchange energy between atoms of type index and&#xA;neighbour-index. The pairwise exchange energy is independent of the&#xA;coordination number, and so the total exchange integral will depend on&#xA;the number of nearest neighbours for the crystal lattice. The exchange&#xA;energy must be defined between all material pairs in the simulation,&#xA;with positive values representing ferromagnetic coupling, and negative&#xA;values representing antiferromagnetic coupling. For a ferromagnet with&#xA;a nearest neighbour exchange, the pairwise exchange energy can be&#xA;found from the Curie temperature by the mean-field expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$J_{ij} = \frac{(3k_{b}T_{c})}{\epsilon z}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$J_{ij}$&lt;/span&gt; is the exchange energy, &lt;span class=&quot;math-container&quot;&gt;$k_{b}$&lt;/span&gt; is the Boltzmann&#xA;constant, &lt;span class=&quot;math-container&quot;&gt;$T_{c}$&lt;/span&gt; is the Curie temperature, z is the coordination&#xA;number (number of nearest neighbours) and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is a correction&#xA;factor to account for spin-wave fluctuations in different crystal&#xA;lattices. If a custom unit cell file is used the exchange values&#xA;defined here are ignored.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have included the manual here in this link. &lt;a href=&quot;https://vampire.york.ac.uk/resources/vampire-manual.pdf&quot; rel=&quot;noreferrer&quot;&gt;VAMPIRE Manual&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-10-18T21:53:42.467" LastActivityDate="2020-12-04T12:21:53.890" Title="How to calculate the exchange matrix of a bilayer magentic system?" Tags="|magnetism|spin-exchange|atomistic-simulation|curie-temperature|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3544" PostTypeId="2" ParentId="2433" CreationDate="2020-10-18T21:40:13.563" Score="7" Body="&lt;h3&gt;VESTA&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YAJ82.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YAJ82.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'll list the features I played with in making the above cell, I'll update the answer whenever I find other features:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The properties window allows most of the aesthetic editing options.&lt;/li&gt;&#xA;&lt;li&gt;Atoms have better sizes relative to each other when represented with van der Waals radii.&lt;/li&gt;&#xA;&lt;li&gt;Width of bonds matters on the overall appearance of the cell.&lt;/li&gt;&#xA;&lt;li&gt;Each colour (atom/bond) works best within a certain range of shininess. Try to play with this feature.&lt;/li&gt;&#xA;&lt;li&gt;In my personal opinion, a lighter unit cell border helps bring the atoms at centre stage. Playing around with its width, colour, and shininess is worth the time.&lt;/li&gt;&#xA;&lt;li&gt;Under the view tab is the overall appearance option. This window helps play with lighting. The interface is interesting and worth trying. In the picture above, faint ambient lighting and less diffused lighting on atoms was used. This window also allows you to choose the background colour, cell projection, and depth.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-10-18T22:23:55.517" LastActivityDate="2020-10-18T22:23:55.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3545" PostTypeId="1" AcceptedAnswerId="3986" CreationDate="2020-10-19T03:25:48.693" Score="11" ViewCount="143" Body="&lt;p&gt;I have never used any AI driven calculation package before and to be honest don't fully understand the ins and outs of it. To be more specific I'm looking for something that can find local minima for molecules along with an absolute minima. I would like to get some quick exposure to some available packages (maybe some pros/cons) so that I can get a better idea of what exactly would be the ideal package for me.&lt;/p&gt;&#xA;&lt;p&gt;Please let me know what is available for this, and what exactly I should be looking out for (ie: ''Make sure you find AI driven not Monte Carlo based'').&lt;/p&gt;&#xA;&lt;p&gt;I would like to avoid calculating the whole PES, and would like to arrive at the minima more directly.&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-12-28T04:02:49.643" LastActivityDate="2020-12-31T03:22:14.857" Title="What are some available software packages for automated finding of local and absolute minima on PES?" Tags="|software-recommendations|machine-learning|potential-energy-surface|" AnswerCount="2" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="3546" PostTypeId="2" ParentId="1630" CreationDate="2020-10-19T05:12:06.143" Score="6" Body="&lt;h2&gt;RPMD (Ring Polymer Molecular Dynamics)&lt;/h2&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Introduction (correlation functions and Kubo transforms):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a time-dependent quantum operator &lt;span class=&quot;math-container&quot;&gt;$\hat{A}(t)$&lt;/span&gt; the &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Book%3A_Time_Dependent_Quantum_Mechanics_and_Spectroscopy_(Tokmakoff)/10%3A_Time-Correlation_Functions/10.03%3A_Quantum_Time-Correlation_Functions&quot; rel=&quot;nofollow noreferrer&quot;&gt;auto-correlation function&lt;/a&gt; of the operator at time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; versus at time 0 can be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;c_{AA}(t) \equiv \frac{\textrm{tr}\left( e^{-\beta H}\hat{A}(0)\hat{A}(t) \right)}{\textrm{tr}\left({e^{-\beta H}}\right)} \tag{1}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Applying the Kubo transformation to this, gives the Kubo-transformed auto-correlation function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tilde{c}_{AA}(t) \equiv \frac{\int_0^\beta \textrm{tr}\left( e^{-(\beta - \lambda) H}\hat{A}(0) e^{-\lambda H }\hat{A}(t) \right)\textrm{d}\lambda}{\beta\, \textrm{tr}\left({e^{-\beta H}}\right)} \tag{2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Remember from high school the chemical reaction rate &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. It can be written in terms of the above two expressions! Reaction rates depend on temperature so we'll write &lt;span class=&quot;math-container&quot;&gt;$k(T)$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;k(t) &amp;amp;=\frac{1}{Q_r(T)}\int_0^\infty c_{ff}(t)\textrm{d}t  \tag{3}\\&#xA;     &amp;amp;=\frac{1}{Q_r(T)}\int_0^\infty \tilde{c}_{ff}(t)\textrm{d}t. \tag{4}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Review of PIMD (Path Integral MD):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms, and we treat each of them as an &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-bead ring of artificial atoms (beads) we can make the approximation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;{\small&#xA;\textrm{tr}\left(e^{-\beta H}\right) \approx  \frac{1}{\left( 2\pi \hbar \right)^{3Nn}}\int \!\!\!\! \int  \cdots \int e^{-\frac{\beta}{n} H_n\left(\mathbf{p}_1,\ldots,\mathbf{p}_{Nn},\mathbf{q}_1,\ldots,\mathbf{q}_{Nn}\right)} \textrm{d}^3\mathbf{p}_1\ldots \textrm{d}^3\mathbf{p}_n \textrm{d}^3\mathbf{q}_1\ldots \textrm{d}^3\mathbf{q}_n\tag{5},&#xA;}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$H_n$&lt;/span&gt; is the Hamiltonian of the &lt;span class=&quot;math-container&quot;&gt;$N \times n$&lt;/span&gt; beads representing &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms and the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; beads connected by harmonic spring potentials representing each of the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms.&lt;/p&gt;&#xA;&lt;p&gt;This approximation becomes &lt;em&gt;exact&lt;/em&gt; when &lt;span class=&quot;math-container&quot;&gt;$n\rightarrow \infty$&lt;/span&gt;, which would mean we have an infinite-dimensional integral (known as a Feynman integral or &amp;quot;path integral&amp;quot;, in this case actually a double-Feynman-integral or Feynman double-integral since there's two entirely different &amp;quot;path&amp;quot; sets over which a Feynman integral is being done).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The &amp;quot;RPMD&amp;quot; approximation:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It might sound bizarre, because really PIMD is MD on &amp;quot;ring polymers&amp;quot; (ring polymer just being another name for the set of beads representing each atom), so PIMD could be called RPMD. However when people use the term &amp;quot;RPMD&amp;quot; they are referring to this approximation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}{\tiny&#xA;\!\!\!\!\!\!\!\!\tilde{c}_{AA}(t) \approx \frac{\int \!\!\! \int  \cdots \int e^{-\frac{\beta}{n} H_n\left(\mathbf{p}_1(t),\ldots,\mathbf{p}_{Nn}(t),\mathbf{q}_1(t),\ldots,\mathbf{q}_{Nn}(t)\right)}\hat{A}_n\left( \mathbf{q}_1(0),\ldots,\mathbf{q}_{Nn}(0)\right)  \hat{A}_n \left( \mathbf{q}_1(t),\ldots,\mathbf{q}_{Nn}(t) \right) \textrm{d}^3\mathbf{p}_1(0)\ldots \textrm{d}^3\mathbf{p}_n(0) \textrm{d}^3\mathbf{q}_1(0)\ldots \textrm{d}^3\mathbf{q}_n(0)}{\int \!\!\! \int  \cdots \int e^{-\frac{\beta}{n} H_n\left(\mathbf{p}_1,\ldots,\mathbf{p}_{Nn},\mathbf{q}_1,\ldots,\mathbf{q}_{Nn}\right)} \textrm{d}^3\mathbf{p}_1\ldots \textrm{d}^3\mathbf{p}_n \textrm{d}^3\mathbf{q}_1\ldots \textrm{d}^3\mathbf{q}_n }} \tag{6},&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\hat{A}_n\left( \mathbf{q}_1(t),\ldots,\mathbf{q}_{Nn}(t)\right)$&lt;/span&gt; involves for each of the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms, an average over all &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; of its beads at time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;{\small&#xA;\hat{A}_n\left( \mathbf{q}_1(t),\ldots,\mathbf{q}_{Nn}(t)\right) \equiv \frac{1}{n}\sum_{j=1}^n \hat{A}\left( &#xA;\mathbf{q}_{j}(t),\mathbf{q}_{n+j}(t),\mathbf{q}_{2n+j}(t),\ldots ,\mathbf{q}_{(N-1)n+j}(t) \right).\tag{7}&#xA;}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Unlike PIMD which calculates a static property exactly in the limit of &lt;span class=&quot;math-container&quot;&gt;$n\rightarrow \infty$&lt;/span&gt;, RPMD &lt;em&gt;approximates&lt;/em&gt; a function of time (the auto-correlation function) even in the limit as &lt;span class=&quot;math-container&quot;&gt;$n\rightarrow \infty$&lt;/span&gt;. However the approximation is exact (in the limit where &lt;span class=&quot;math-container&quot;&gt;$n\rightarrow \infty$&lt;/span&gt;) in some limits:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;infinitely high temperature,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$t \approx 0$&lt;/span&gt;, (short-time limit),&lt;/li&gt;&#xA;&lt;li&gt;harmonic limit (where the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms interact via harmonic potentials) if &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is linear,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat{A}=1$&lt;/span&gt; (the identity operator). &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is relatively cheap to calculate (compared to exact real-time quantum dynamics). It costs only a bit more than doing classical MD several (&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) times,&lt;/li&gt;&#xA;&lt;li&gt;it allows one to incorporate the effects of tunneling and zero-point-energy effects in an MD calculation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;coherence&amp;quot; between paths in the Feynman integral is not taken into account,&lt;/li&gt;&#xA;&lt;li&gt;the formulation above does not give attention to how non-adiabatic effects  would be treated. Several proposals have bee made for how to treat non-adiabatic effects, but no single proposal has stood out as a &amp;quot;gold standard&amp;quot; as far as I know.&lt;/li&gt;&#xA;&lt;li&gt;it's at least &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; times more expensive than doing classical MD, so it's applicability is limited to cases where quantum mechanical effects of nuclei are important enough for it to be worth the extra cost.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-20T04:04:24.453" LastActivityDate="2020-10-20T04:04:24.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3547" PostTypeId="2" ParentId="3540" CreationDate="2020-10-19T06:43:59.607" Score="3" Body="&lt;p&gt;I would like to take a poke at this even though my answer might not be completely satisfactory.&lt;/p&gt;&#xA;&lt;p&gt;The '+U' correction to DFT methods is typically useful for systems with highly localized orbitals - For example, the 3d orbitals of transition metals. But what's also interesting is that typically one also associates a Hubbard U value to the Oxygen/Nitrogen 3p orbitals in a calculation, if they are present in the material. This is what you have mentioned in the question. The idea is simple - you want to include a value of Hubbard 'U' so that these highly localized states are pushed away from the fermi level, otherwise they might hybridize incorrectly. From what I've seen, from systems like NiO, TiO etc which are very well researched, a value of 'U' is also applied for Oxygen. In these systems, the most localized orbitals are 3d of the Transition metal and 3p of the Oxygen. &lt;strong&gt;I might imagine that it is always better to use a value of 'U' for O/N&lt;/strong&gt; - the papers that assume a value of zero have probably concluded that inclusion of a non-zero value does not quantitatively affect the results.&lt;/p&gt;&#xA;&lt;p&gt;I would love to hear more if anyone else has insights on this.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-10-19T06:43:59.607" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3548" PostTypeId="2" ParentId="2453" CreationDate="2020-10-19T07:31:17.957" Score="5" Body="&lt;p&gt;Typically, the largest you would need for convergence, is &lt;code&gt;ENCUT = 1.3 * ENMAX&lt;/code&gt;. This is the same as specifying as the &lt;code&gt;PREC = ACCURATE&lt;/code&gt;. Going beyond these typically only changes the energy of the system of very few meV.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-10-19T07:31:17.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3549" PostTypeId="1" CreationDate="2020-10-19T10:40:48.007" Score="12" ViewCount="779" Body="&lt;p&gt;Let's say I have two codes. One is plane wave, and the other is using atomic orbitals as basis sets. How can I compare these two codes with the same functional? And let's say I want to optimise the same structure with these two codes (PBE). Principally they should give the same result, right?&lt;/p&gt;&#xA;" OwnerDisplayName="user1263" LastEditorUserId="142" LastEditDate="2020-10-20T01:33:24.770" LastActivityDate="2020-10-20T01:54:52.740" Title="Comparing calculations in plane wave and atomic orbital bases for the same functional" Tags="|density-functional-theory|geometry-optimization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3550" PostTypeId="1" CreationDate="2020-10-19T10:43:33.973" Score="12" ViewCount="1217" Body="&lt;p&gt;I have a perfect supercell structure Ni fcc. And I would like to dope another element O or N with a ratio of O:Ni=8:100 to the supercell of 3x3x3 and find the most stable ordering structure. The number of possible configurations is extremely large. I would like to ask if you know any code to generate all possible cases and remove of similar cases?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2020-10-19T13:08:59.997" LastActivityDate="2022-09-26T13:20:47.210" Title="Create doped structures to POSCAR files for vasp" Tags="|density-functional-theory|vasp|software-recommendations|" AnswerCount="5" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3551" PostTypeId="2" ParentId="3550" CreationDate="2020-10-19T13:09:43.200" Score="10" Body="&lt;p&gt;What you intend to do is crystal structure prediction (CSP). Just yesterday, I got to know about a crystal structure prediction blind-test that the &lt;a href=&quot;https://www.ccdc.cam.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;Cambridge Crystallographic Data Centre&lt;/a&gt; organises through &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1975/116&quot;&gt;this answer&lt;/a&gt; by one of my favourite people here on this stack exchange.&lt;/p&gt;&#xA;&lt;p&gt;Personally, I have some experience using &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;noreferrer&quot;&gt;USPEX&lt;/a&gt;. CSP is simply a global optimization problem in terms of the potential energy surface of the material. USPEX uses fingerprinting to make the search faster by eliminating similar structures. Many other interesting features in the code help make the search more robust and efficient.&lt;/p&gt;&#xA;&lt;p&gt;About your question, did you mean a ratio of N,O:Ni = &lt;span class=&quot;math-container&quot;&gt;$8:100$&lt;/span&gt;? And why is there a necessity for a 3x3x3 supercell?&lt;/p&gt;&#xA;" OwnerUserId="116" LastActivityDate="2020-10-19T13:09:43.200" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3552" PostTypeId="2" ParentId="2371" CreationDate="2020-10-19T13:20:49.683" Score="2" Body="&lt;p&gt;You can calculate the Raman spectra by using VASP and Phonopy assisted python package. Check all the details here: &lt;a href=&quot;https://github.com/raman-sc/VASP&quot; rel=&quot;nofollow noreferrer&quot;&gt;vasp-raman&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="879" LastActivityDate="2020-10-19T13:20:49.683" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3553" PostTypeId="2" ParentId="3549" CreationDate="2020-10-19T13:57:41.713" Score="7" Body="&lt;p&gt;Not necessarily. The LAPW method is often considered as the golden standard when it comes to correctness of DFT calculations. This happens because the atom-like orbitals within the muffin tin sphere closely resemble the physical condition hence you can have a greater accuracy when it comes to DFT predictions.&lt;/p&gt;&#xA;&lt;p&gt;But if you're refering to the case of using codes with atomic orbitals like GAUSSIAN over plane wave dft codes like Quantum ESPRESSO then the output accuracy depends on your system. It's better to use atomic basis set for aperiodic systems like molecules and a plane wave basis set for periodic basis sets like crystals.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="88" LastEditDate="2020-10-19T15:12:57.640" LastActivityDate="2020-10-19T15:12:57.640" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3554" PostTypeId="1" CreationDate="2020-10-19T14:03:34.120" Score="12" ViewCount="236" Body="&lt;p&gt;Crystal structure prediction codes like &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt;, use DFT calculated values of energy (&lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K) to study the phase space (or potential energy surface or internal energy surface, I'm confused which is it). All of this is at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K.&lt;/p&gt;&#xA;&lt;p&gt;Lattice dynamics is the direction to take in studying finite temperature properties of materials, but these studies are costly, very costly. The evolutionary algorithm that USPEX employs is quite costly too. At the current state of commercial computing infrastructure, combining the two sounds like a recipe for trouble.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What ways can we think of, machine learning or otherwise, to make finite temperature crystal structure prediction possible today?&lt;/strong&gt; (More interested in the &amp;quot;otherwise&amp;quot;.)&lt;/p&gt;&#xA;&lt;p&gt;Older post: HEAs or multiple atom alloys (MAAs) have become quite popular recently. The trend in modeling these materials is to represent them as random solid solutions. I use special quasirandom structures to model them. I wonder if this is appropriate. At each temperature, which configuration is the most stable is almost impossible to predict.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-06-16T18:18:41.147" LastActivityDate="2021-06-16T18:18:41.147" Title="Finite temperature crystal structure prediction" Tags="|crystal-structure|alloys|uspex|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3555" PostTypeId="2" ParentId="3550" CreationDate="2020-10-19T14:46:30.733" Score="12" Body="&lt;p&gt;I will give a secondary answer that does not involve USPEX. Realistically, picking about 8 atoms out of 108 requires you to test 352,025,629,371 combinations.  This is obviously too much to handle.  You can try one of two approaches.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Randomly sample the entire space, probably not that difficult to do but no promises you get a good result.  ASE can help you do this fairly easily and this can be run in a highly parallel manner.  With so many combinations to pick from, you will be unlikely to generate two of the same combination (although with translations and rotations etc you will probably generate some).  If we assume no symmetry is possible, picking 10,000 random cells you will only have a 0.014201% chance of generating two of the same cells.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Go from 1:107 ratio to 2:106 to 3:105, etc.  You can actually brute force this type of solution relatively quickly with modern hardware and reasonable calculation parameters, just by only keeping the top 5% of structures to add an additional dopant.  This type of solution is heavily helped by symmetry finding.  Here are two methods of this.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Niggli reduce each cell, compare if they align the same by element and position (assuming unrelaxed cell)&lt;/li&gt;&#xA;&lt;li&gt;Look at the coordination shell of the dopants.  See if all dopants see a similar coordination shell.  For example, if the oxygen is surrounded by Ni on all sides.  I have actually developed a &lt;a href=&quot;https://gitlab.com/jgreeley-group/graph-theory-surfaces&quot; rel=&quot;noreferrer&quot;&gt;code which can do this&lt;/a&gt; for multiple coordination shells.  The documentation is not so good at the moment but this will be fixed eventually hopefully.  Currently its designed to handle surfaces, not bulk, but this can be changed easily.  For now you may want to look at &lt;a href=&quot;https://www.nature.com/articles/s41524-020-0345-2&quot; rel=&quot;noreferrer&quot;&gt;our paper&lt;/a&gt; to understand exactly whats going on.&lt;/li&gt;&#xA;&lt;li&gt;Look into full python packages capable of doing this, pymatgen and ase both have some functionality for this.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You have too large of a search space for this to be exhaustive though no matter what you do.  Consider using a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/defects/defects.html&quot; rel=&quot;noreferrer&quot;&gt;different approach for making supercells&lt;/a&gt; that allows you to have less atoms but still keep them separated in space.  You may be able to do a 4:50 cell for example instead.&lt;/p&gt;&#xA;&lt;p&gt;I also won't explore it in this answer, but there are lots of genetic algorithms for this sort of thing as well, but I have never used them.  &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/ga/ga_fcc_alloys.html&quot; rel=&quot;noreferrer&quot;&gt;I will link an example from ASE.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-19T14:46:30.733" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3556" PostTypeId="2" ParentId="3540" CreationDate="2020-10-19T16:09:33.253" Score="5" Body="&lt;p&gt;I've done some work with applying &lt;em&gt;U&lt;/em&gt; to oxygen &lt;em&gt;p&lt;/em&gt; states. I've seen some vague arguments against it, which usually amount to &amp;quot;they're not as localized as &lt;em&gt;d&lt;/em&gt; states&amp;quot;, which of course can be true (&lt;em&gt;d&lt;/em&gt; states can also be quite itinerant, like &lt;span class=&quot;math-container&quot;&gt;$\sigma^*$&lt;/span&gt; states in some metallic nickelates). The real question though, is how &amp;quot;localized&amp;quot; does a state need to be before a &lt;em&gt;U&lt;/em&gt; correction offers some improvement in the description of the material. No one seems to have an answer for that.&lt;/p&gt;&#xA;&lt;p&gt;So instead of making hand-wavy intuition arguments, I'd rather let the proof be in the pudding. There is no reason &lt;em&gt;a priori&lt;/em&gt; to assume that you can never apply &lt;em&gt;U&lt;/em&gt; to oxygen &lt;em&gt;p&lt;/em&gt; states in some circumstances. It might not be done often in the literature because so much of the literature is using empirical (or not even empirical, &amp;quot;second-hand&amp;quot; empirical from other papers that could have been using completely different parameters!) &lt;em&gt;U&lt;/em&gt; values that make it more complicated to apply &lt;em&gt;U&lt;/em&gt; to more states. Self-consistent &lt;em&gt;U&lt;/em&gt; is very helpful here.&lt;/p&gt;&#xA;&lt;p&gt;In my last paper (&lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.101.165117&quot; rel=&quot;noreferrer&quot;&gt;shameless plug&lt;/a&gt;) I devoted a small section (section IV.C.7) to discussing this. In that work I used the ACBN0 method to calculate values of &lt;em&gt;U&lt;/em&gt; for &lt;em&gt;d&lt;/em&gt; and &lt;em&gt;p&lt;/em&gt; states on perovskite oxides. I also applied a &amp;quot;naive&amp;quot; &lt;em&gt;U&lt;/em&gt; from literature, only to the &lt;em&gt;d&lt;/em&gt; states. The character of the bonding can be very different between the two. Typically, applying &lt;em&gt;U&lt;/em&gt; to both &lt;em&gt;d&lt;/em&gt; and &lt;em&gt;p&lt;/em&gt; gave electronic structures that are in better agreement with HSE hybrid functional calculations, as well as almost universally better agreement with experimental lattice geometry. In ZnO, it's often discussed in the literature that you actually &lt;em&gt;need&lt;/em&gt; to apply &lt;em&gt;U&lt;/em&gt; to oxygen in order to increase the (KS) band gap to experimental values while keeping the magnitudes of &lt;em&gt;U&lt;/em&gt; values physically realistic. In addition, when interpreting experimental XPS, XES and XAS spectra in the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.55.418&quot; rel=&quot;noreferrer&quot;&gt;Zaanen-Sawatzky-Allen&lt;/a&gt; framework, there are significant Coulombic &lt;em&gt;U&lt;/em&gt; interactions between &lt;em&gt;p&lt;/em&gt; orbitals in many oxides. Often the magnitudes are &lt;em&gt;larger&lt;/em&gt; than the &lt;em&gt;d&lt;/em&gt; states because the orbitals are more populated. So there is at least some experimental support for this being a reasonable correction.&lt;/p&gt;&#xA;&lt;p&gt;That being said, you can also get better results beyond applying &lt;em&gt;U&lt;/em&gt; to only &lt;em&gt;d&lt;/em&gt; states in other ways, such as using DFT+&lt;em&gt;U&lt;/em&gt;+&lt;em&gt;V&lt;/em&gt;. But that method also doesn't preclude applying corrections to &lt;em&gt;p&lt;/em&gt; states either (in fact &lt;em&gt;V&lt;/em&gt; in many oxides will be a &lt;em&gt;d&lt;/em&gt;-&lt;em&gt;p&lt;/em&gt; interaction).&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-19T16:09:33.253" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3557" PostTypeId="1" AcceptedAnswerId="3559" CreationDate="2020-10-19T19:21:43.313" Score="8" ViewCount="400" Body="&lt;p&gt;I am currently trying to determine how DFT+U values can be determined self consistently.  I see that the bare and converged linear response matrix contain the difference in occupancies from the ground state.  I am wondering if my understanding of the approach is correct.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculate ground state and record the final occupancies&lt;/li&gt;&#xA;&lt;li&gt;Calculate perturbed state (bare) by applying U to the ground state charge density then taking the first set of occupancies from the first SCF step as the bare response matrix (bare - ground)&lt;/li&gt;&#xA;&lt;li&gt;Converge the bare state and take the final set of occupancies as the converged response matrix (converged - ground)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Then you end up with two matrices, the bare response matrix and the converged response matrix.  The U value is then taken as follows.&lt;/p&gt;&#xA;&lt;p&gt;U = (Converged&lt;sup&gt;-1&lt;/sup&gt;) - (Bare&lt;sup&gt;-1&lt;/sup&gt;)&lt;/p&gt;&#xA;&lt;p&gt;My question is maybe naive, but how does this final step of subtracting two matrices give a U value.&lt;/p&gt;&#xA;&lt;p&gt;I am using &lt;a href=&quot;http://hjkgrp.mit.edu/content/hubbard-u-multiple-sites&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; as a resource to understand what is going on in this method.&lt;/p&gt;&#xA;&lt;p&gt;If it at all matters, I would like to use CASTEP or GPAW as my calculator.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-19T21:22:19.477" Title="Determine DFT+U values by linear response" Tags="|density-functional-theory|dft-u|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3558" PostTypeId="2" ParentId="2469" CreationDate="2020-10-19T20:01:15.183" Score="18" Body="&lt;p&gt;Noncollinear magnetism means that the orientation of the magnetization varies in space. Examples for such structures are magnetic domain walls, spin spirals, or magnetic skyrmions. To describe these systems one has to consider the Kohn-Sham wave functions as spinors&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Psi_\nu(\mathbf{r}) = \begin{pmatrix} \psi_\nu^{\uparrow}(\mathbf{r}) \\ \psi_\nu^{\downarrow}(\mathbf{r})\end{pmatrix},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; is the index of the wave function, and &lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt; indicate up and down spins. From these objects one constructs the density matrix&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\rho_{\sigma,\sigma'}(\mathbf{r}) = \sum_\nu^\text{occ} \left(\psi_\nu^{\sigma}(\mathbf{r})\right)^\ast \psi_\nu^{\sigma'}(\mathbf{r}) = \frac{1}{2} \begin{pmatrix} n(\mathbf{r}) + m_\text{z}(\mathbf{r}) &amp;amp; m_\text{x}(\mathbf{r}) - im_\text{y}(\mathbf{r}) \\ m_\text{x}(\mathbf{r}) + im_\text{y}(\mathbf{r}) &amp;amp; n(\mathbf{r}) - m_\text{z}(\mathbf{r})\end{pmatrix},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; is the charge density and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}(\mathbf{r}) = \begin{pmatrix} m_\text{x}(\mathbf{r}) \\ m_\text{y}(\mathbf{r}) \\ m_\text{z}(\mathbf{r}) \end{pmatrix}$&lt;/span&gt; is the magnetization density.&lt;/p&gt;&#xA;&lt;p&gt;Magnetism is due to the exchange interaction, so when constructing a potential from this density the exact expression depends on the choice of the exchange-correlation functional. In general one obtains an exchange &lt;span class=&quot;math-container&quot;&gt;$\mathbf{B}$&lt;/span&gt; field and an effective potential matrix of the form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ V_{\sigma,\sigma'}(\mathbf{r}) = \begin{pmatrix} V(\mathbf{r}) + \mu_\text{B} B_\text{z}(\mathbf{r}) &amp;amp; \mu_\text{B}(B_\text{x}(\mathbf{r}) - i B_\text{y}(\mathbf{r})) \\ \mu_\text{B}(B_\text{x}(\mathbf{r}) + i B_\text{y}(\mathbf{r}))  &amp;amp; V(\mathbf{r}) - \mu_\text{B} B_\text{z}(\mathbf{r}) \end{pmatrix},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})$&lt;/span&gt; is the effective potential averaged over the spins. For the case of the local density approximation &lt;span class=&quot;math-container&quot;&gt;$\mathbf{B}(\mathbf{r})$&lt;/span&gt; points in the same direction as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;On the basis of this potential matrix one can then solve the Kohn-Sham equations for such noncollinear systems&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left\lbrace -\frac{1}{2}\nabla^2 \mathbf{I}_2 + V_{\sigma,\sigma'}(\mathbf{r})  \right\rbrace \Psi_\nu(\mathbf{r}) = \epsilon_\nu \Psi_\nu(\mathbf{r}).$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this expression &lt;span class=&quot;math-container&quot;&gt;$\mathbf{I}_2$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$2 \times 2$&lt;/span&gt; identity matrix.&lt;/p&gt;&#xA;&lt;p&gt;Note that the kinetic energy operator is spin-diagonal in this equation. In a relativistic description where one uses the Kohn-Sham-Dirac equation this is not the case due to the then included spin-orbit coupling. Spin-orbit coupling will also yield spin-offdiagonal matrix elements. This implies that spin-orbit coupling can cause noncollinear magnetism, but such structures can also have other causes, for example magnetic frustration.&lt;/p&gt;&#xA;&lt;p&gt;In the spin-polarized case in which a magnetic system only features collinear magnetism, i.e., the magnetization is oriented along the same axis everywhere in space, one can always find a &lt;span class=&quot;math-container&quot;&gt;$\text{z}$&lt;/span&gt; axis in the description above that coincides with this spin-quantization axis. If we consider such a setup the offdiagonal terms in the matrices vanish and the Kohn-Sham equations can be solved for the two spins separately.&lt;/p&gt;&#xA;&lt;p&gt;In the non-spinpolarized case the expressions for the two spins are identical: The Kohn-Sham states feature a spin-degeneracy and therefore it is enough to solve the Kohn-Sham equations for one of the spins and occupy each state with up to two electrons.&lt;/p&gt;&#xA;&lt;p&gt;Finally, please also note that spin-orbit coupling is not only relevant for systems featuring noncollinear magnetism. For example, in systems with collinear magnetism it causes magnetocrystalline anisotropy. Effects due to spin-orbit coupling in nonmagnetic systems include the Rashba effect and the Dresselhaus effect.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2020-10-19T20:01:15.183" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3559" PostTypeId="2" ParentId="3557" CreationDate="2020-10-19T21:22:19.477" Score="5" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; in this case is actually a matrix, since on Prof. Kulik's page that you linked, she is explaining multi-site &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; calculations. The perturbation of a single site may also affect the response at a different site (e.g. from your link, perturbing Mn can affect O).&lt;/p&gt;&#xA;&lt;p&gt;When doing the perturbations, you record the changes in all the occupations at different sites. Then when you do the matrix inversion these initial off-diagonal elements will have an affect on the resulting inverted matrix's diagonal elements. The diagonal elements &lt;span class=&quot;math-container&quot;&gt;$U_{ii}$&lt;/span&gt; are of course the values of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; for site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. This type of calculation takes into account the effect of neighboring atoms on a given atom's response to the perturbation, as opposed to the single-site &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; (which you could calculate separately for each site) that does not.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-19T21:22:19.477" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3560" PostTypeId="2" ParentId="3539" CreationDate="2020-10-19T21:47:20.013" Score="7" Body="&lt;p&gt;I can't help with the textbook, but the NIST-JANAF Thermochemical Tables are available here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://janaf.nist.gov/&quot; rel=&quot;noreferrer&quot;&gt;https://janaf.nist.gov/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-19T21:47:20.013" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3561" PostTypeId="2" ParentId="1122" CreationDate="2020-10-19T22:29:45.047" Score="8" Body="&lt;p&gt;You can check this &lt;a href=&quot;https://medium.com/@anoopreceivesmail/run-quantum-espresso-on-google-colab-9d1f7166865f&quot; rel=&quot;noreferrer&quot;&gt;article&lt;/a&gt; I've written on doing the same, but without using the ASE python library. Just create the input file as you would normally do along with the pseudo-potential files and keep them in a folder in your Google Colab content folder. The work-flow is much faster if you would like to use ASE but this method works without it as well.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I'll also include the link to the &lt;a href=&quot;https://colab.research.google.com/gist/AnoopANair/acba80f1ac2d5a39ae0d85d9dff2762b/quantum_espresso_colab.ipynb&quot; rel=&quot;noreferrer&quot;&gt;google colab notebook&lt;/a&gt; in just&#xA;in case.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Hope it helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="88" LastEditDate="2020-12-17T04:20:40.990" LastActivityDate="2020-12-17T04:20:40.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3562" PostTypeId="2" ParentId="3549" CreationDate="2020-10-20T01:54:52.740" Score="3" Body="&lt;p&gt;Like other atomic basis sets, numerical atomic orbitals are excellent for getting qualitative results with few basis functions, so you can expect e.g. good geometries for cheap. However, since they're ideally exact for isolated atoms, numerical atomic orbitals are also much less susceptible to basis set superposition error than Gaussian or Slater type orbitals. They also allow for all-electron a.k.a. full-potential calculations to be performed routinely.&lt;/p&gt;&#xA;&lt;p&gt;While a minimal basis of atomic orbitals is accurate for a single atom, you need polarization functions (e.g. D and F functions on oxygen) to be able to describe the breaking of the atomic symmetry in a molecule or crystal. Often, a triple-zeta basis (contains two polarization shells) yields results that are sufficiently converged.&lt;/p&gt;&#xA;&lt;p&gt;Plane wave calculations, on the other hand, have been dominating solid-state calculations for a long time. Although results can be obtained easily with plane-wave codes, it is important to go up high enough in the kinetic energy cutoff &lt;span class=&quot;math-container&quot;&gt;$E_{\rm cut}$&lt;/span&gt; so that the calculations are converged. (Several plane wave calculations in the literature are limited to STO-3G-like i.e. minimal-basis accuracy due to insufficient cutoffs!) You are also limited to using pseudopotentials or PAWs, since all-electron calculations are pretty much infeasible even for a single atom due to the uniform spatial resolution of plane waves.&lt;/p&gt;&#xA;&lt;p&gt;Comparing different computational approaches for the same calculation is quite tricky: a proper comparison requires cranking the approaches to the limit! In an atomic-orbital calculation, you need to include a complete set of S functions, P functions, D functions, etc, until your observable has converged; in a plane wave calculation you need to increase &lt;span class=&quot;math-container&quot;&gt;$E_{\rm cut}$&lt;/span&gt; until convergence has been achieved.&lt;/p&gt;&#xA;&lt;p&gt;The laboriousness of these comparisons is a reason why a paper showing that different computational approaches yield the same answer for the PBE functional got published in Science just a few years ago, see &lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;nofollow noreferrer&quot;&gt;Science 351, 6280 (2016)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It all depends on what you're interested in. There's probably no way to get the absolute energies to match between the codes, since even if both codes use pseudopotentials, they might be different. Geometries should be easier. Excitation spectra? Hard to say.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-10-20T01:54:52.740" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3563" PostTypeId="2" ParentId="483" CreationDate="2020-10-20T16:06:27.523" Score="4" Body="&lt;p&gt;I have faced a similar issue and it seems that something happens while calling calculate(). I think it may be because when you use the same single equilibrium calculation for determining the Gibbs energy it does without suspending the other phase and this might be creating the problems, but I am not sure. I would suggest trying two different single equilibrium calculations (one for FCC and another for BCC) each with only one phase entered while all others suspended and then calculate the T-zero temperature separately from the resulting Gibbs energy values by finding the temperature at which their difference is zero, like you have done in the first code.&lt;/p&gt;&#xA;&lt;p&gt;Another simpler way, in case you want to keep the original code with a single equilibrium calculation over a range of compositions, is to use enable_step_separate_phases() with calculate(), this usually works.&lt;/p&gt;&#xA;" OwnerUserId="301" LastActivityDate="2020-10-20T16:06:27.523" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3564" PostTypeId="2" ParentId="2453" CreationDate="2020-10-20T16:35:31.470" Score="3" Body="&lt;p&gt;I would go farther and ask, why is cutoff convergence unlike kpoint convergence?  You can very easily do a convergence study based on energy cutoffs.  Infact, this is often how &lt;code&gt;ENMAX&lt;/code&gt; is determined in a code.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example from the &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/setups/Ni.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GPAW documentation&lt;/a&gt; of the convergence of the Ni PAW potential.  As you can see, the error drops as the energy cutoff increases, you should determine what an acceptable error for your work.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YvYfA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YvYfA.png&quot; alt=&quot;https://wiki.fysik.dtu.dk/gpaw/setups/Ni.html&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can also look at the convergence of things such as band structures relative to &lt;code&gt;ENCUT&lt;/code&gt;.  In general though, as long as the &lt;code&gt;ENCUT&lt;/code&gt; is consistent, things should at least be comparable.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-20T16:35:31.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3565" PostTypeId="1" AcceptedAnswerId="3566" CreationDate="2020-10-21T00:06:33.970" Score="11" ViewCount="369" Body="&lt;p&gt;I have asked a similar &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2424/88&quot;&gt;question&lt;/a&gt; but after thinking about it I have a more specific question.&lt;/p&gt;&#xA;&lt;p&gt;According to &lt;a href=&quot;https://books.google.co.in/books/about/Time_Dependent_Density_Functional_Theory.html?id=hCNNsC4sEtkC&amp;amp;redir_esc=y&quot; rel=&quot;noreferrer&quot;&gt;Ullrich, Carsten A.. Time-Dependent Density-Functional Theory : Concepts and Applications&lt;/a&gt;, the Hohenberg–Kohn theorem states&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In a finite, interacting N-electron system with a given&#xA;particle–particle interaction there exists a one-to-one correspondence&#xA;between the external potential &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; and the ground-state density&#xA;&lt;span class=&quot;math-container&quot;&gt;$n_0(r)$&lt;/span&gt;. In other words, the external potential is a unique functional&#xA;of the ground-state density, &lt;span class=&quot;math-container&quot;&gt;$V[n_0](r)$&lt;/span&gt;, up to an arbitrary additive&#xA;constant.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The way I understand it, assuming V differs by more than a constant and psi differs by more than a phase, the logic is: one potential (V) yields one hamiltonian (H) which yields a wave function (Ψ) which yields a density (n). V -&amp;gt; Ψ -&amp;gt; n.&lt;/p&gt;&#xA;&lt;p&gt;V -&amp;gt; Ψ (ignoring constant)&#xA;This is proven in HK theorem via proof by contradiction&lt;/p&gt;&#xA;&lt;p&gt;Ψ -&amp;gt; n (ignoring phase factor)&#xA;This is proven in HK theorem via proof by contradiction.&lt;/p&gt;&#xA;&lt;p&gt;Then they conclude that:&#xA;We have thus shown that &lt;span class=&quot;math-container&quot;&gt;$Ψ_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Ψ′_0$&lt;/span&gt; give different densities &lt;span class=&quot;math-container&quot;&gt;$n_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n′_0$&lt;/span&gt;; but in the first step we showed that &lt;span class=&quot;math-container&quot;&gt;$Ψ_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Ψ′_0$&lt;/span&gt; also come from different potentials &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V′$&lt;/span&gt;. Therefore, a unique one-to-one correspondence exists between potentials and ground-state densities, which can be formally expressed by writing &lt;span class=&quot;math-container&quot;&gt;$V[n_0](r)$&lt;/span&gt;, and thus &lt;span class=&quot;math-container&quot;&gt;$V[n_0]$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This confuses me because they have only proven &amp;quot;one direction.&amp;quot; They have proven that two V's cannot give the same Ψ but they haven't proven that one V cannot yield more than one Ψ. Likewise they have proven that two Ψ's cannot give the same n but haven't proven that one Ψ cannot yield more than one n. Perhaps I'm missing something obvious but any insight would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1398" LastEditorUserId="88" LastEditDate="2020-10-21T06:27:33.153" LastActivityDate="2020-10-21T06:27:33.153" Title="Does One-to-One Correspondence of Hohenberg Kohn Theorem Mean Bijective or Injective and How to Prove it?" Tags="|density-functional-theory|quantum-chemistry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3566" PostTypeId="2" ParentId="3565" CreationDate="2020-10-21T03:12:17.587" Score="8" Body="&lt;p&gt;I'm not familiar with the Carsten Ullrich text you mention. However, one possibility is that he followed Hohenberg and Kohn's example of &lt;a href=&quot;https://journals.aps.org/pr/pdf/10.1103/PhysRev.136.B864&quot; rel=&quot;noreferrer&quot;&gt;assuming a non-degenerate ground state&lt;/a&gt;. If the ground state &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; is non-degenerate, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; can by definition only produce one &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You're correct that the proofs have to be modified when there is a degenerate ground state manifold. There's a nice discussion in &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.76.012508&quot; rel=&quot;noreferrer&quot;&gt;K. Capelle, C. A. Ullrich, G. Vignale, &lt;em&gt;Degenerate ground states and nonunique potentials: breakdown and restoration of density functionals&lt;/em&gt;, Physical Review A &lt;strong&gt;76&lt;/strong&gt;, p. 012508 (2007)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0610322&quot; rel=&quot;noreferrer&quot;&gt;arXiv link&lt;/a&gt;) that may answer some of your questions.&lt;/p&gt;&#xA;&lt;p&gt;I agree with Kevin's comment that the density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is fixed by the inner product &lt;span class=&quot;math-container&quot;&gt;$|\psi|^2$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-10-21T03:12:17.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3567" PostTypeId="1" AcceptedAnswerId="3577" CreationDate="2020-10-21T10:36:30.243" Score="10" ViewCount="256" Body="&lt;p&gt;A density of states (DoS) curve seems like an example of a curve for which curve fitting doesn't seem to make sense, or does it? How could we interpolate on such a curve, given that we got the curve from a discrete dataset?&lt;/p&gt;&#xA;&lt;p&gt;I thought of using an integrated DoS curve instead, since it has a nature suitable for fitting. Any suggestions are welcome.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="792" LastEditDate="2020-10-22T14:43:24.383" LastActivityDate="2020-10-22T14:43:24.383" Title="Validity of interpolation for density of states?" Tags="|k-points|density-of-states|curve-fitting|" AnswerCount="2" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3568" PostTypeId="1" CreationDate="2020-10-21T10:49:43.253" Score="6" ViewCount="860" Body="&lt;p&gt;&lt;code&gt;VASP&lt;/code&gt; has a tag &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NEDOS&quot; rel=&quot;noreferrer&quot;&gt;NEDOS&lt;/a&gt;, which helps specify the # of points on which the DoS is evaluated. Other than that, we have &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EMIN&quot; rel=&quot;noreferrer&quot;&gt;EMIN&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EMAX&quot; rel=&quot;noreferrer&quot;&gt;EMAX&lt;/a&gt;, which help decide the range of energy in which DoS is evaluated at NEDOS evenly spaced grid-points. This procedure misses the exact fermi energy point, at least in all of my calculations. Is there a way to make the code explicitly calculate DoS at the Fermi energy? I wish to avoid interpolation due to certain concerns as relayed &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3567/validity-of-interpolation-for-density-of-states&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="116" LastActivityDate="2020-10-21T12:17:26.933" Title="Find the value of density of states at the Fermi energy using VASP" Tags="|vasp|density-of-states|fermi-energy|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3569" PostTypeId="2" ParentId="3568" CreationDate="2020-10-21T11:51:27.513" Score="8" Body="&lt;p&gt;Let me suggest a simple answer, although I am not convinced you will get anything sufficently different for the fermi level than just using a converged grid.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Consider a range of energies such as 10 eV.&lt;/li&gt;&#xA;&lt;li&gt;Set &lt;code&gt;EMIN=Fermi-5&lt;/code&gt; and &lt;code&gt;EMAX=Fermi+5&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Set &lt;code&gt;NEDOS=Anything Odd&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As a rule, you should always hit the middle point doing this and the middle point is the Fermi level since you defined it that way.  This should work in essentially any DFT calculator.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-10-21T12:17:26.933" LastActivityDate="2020-10-21T12:17:26.933" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3570" PostTypeId="2" ParentId="3550" CreationDate="2020-10-21T12:20:02.267" Score="11" Body="&lt;h3&gt;ATAT (Alloy Theoretic Automated Toolkit)&lt;/h3&gt;&#xA;&lt;p&gt;ATAT is a software is specialized in solving such issues.&lt;/p&gt;&#xA;&lt;p&gt;It has a module to generate Special Quasirandom Structures (SQS), used to simulate  disordered solid solutions  as your case.&lt;/p&gt;&#xA;&lt;p&gt;The ATAT site is &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;The user guide is &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/manual.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;Tutorials are &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/tutorial/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://arxiv.org/abs/1907.10151&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-11-17T03:47:19.207" LastActivityDate="2020-11-17T03:47:19.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3571" PostTypeId="1" CreationDate="2020-10-21T13:57:37.657" Score="10" ViewCount="595" Body="&lt;p&gt;My knowledge in these areas of physics is lacking, so please expect naivety ahead (perhaps, dumb down your answer accordingly).&lt;/p&gt;&#xA;&lt;p&gt;From what I read online, spin orbit coupling is how the angular momentum of an electron w.r.t. the nucleus interacts with its spin. The word 'relativistic' came up every time. My quantum-dot sized brain already heats up at the mention of 'quantum mechanics'. What is spin orbit coupling (soc) and what does soc strength mean?&lt;/p&gt;&#xA;&lt;p&gt;I was told:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \textrm{soc}\:\textrm{strength} = \textrm{DoS}_{(\textrm{spin-up})_{E_F}} -\: \textrm{DoS}_{(\textrm{spin-down})_{E_F}}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; = Fermi energy.&lt;/p&gt;&#xA;&lt;p&gt;Questions on this SE (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/308/how-to-incorporate-the-effect-of-spin-orbit-coupling-in-electronic-structure-cal&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1144/spin-orbit-interaction-with-dft&quot;&gt;here&lt;/a&gt;) suggest soc calculations are an entirely different class of calculations that build upon a spin polarised calculation.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-10-24T20:50:15.497" LastActivityDate="2020-10-25T11:12:44.500" Title="Spin orbit coupling from spin polarized density of states?" Tags="|density-functional-theory|density-of-states|spin-orbit-coupling|spin-polarization|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3572" PostTypeId="2" ParentId="1354" CreationDate="2020-10-21T14:27:54.203" Score="5" Body="&lt;p&gt;Yes, we are working on the performance benchmark of many quantum chemistry program packages. If you're interested in, you can visit our Github repository: &lt;a href=&quot;https://github.com/r2compchem/benchmark-qm&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/r2compchem/benchmark-qm&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1448" LastActivityDate="2020-10-21T14:27:54.203" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3573" PostTypeId="2" ParentId="1354" CreationDate="2020-10-21T17:58:30.843" Score="5" Body="&lt;p&gt;I don't mean this answer to criticize your question in any way because it's actually a great question. My opinion, however, is that this is sort of the wrong question.&lt;/p&gt;&#xA;&lt;p&gt;I think a much easier and more relevant test is not how fast some calculation is on, say, a single core, but how well the implementation scales across many nodes, each with many cores. This is because many people doing quantum chemistry have access to very large computing clusters (either through their university, national lab, company, the cloud, etc.). Despite this, many electronic structure packages do not scale well beyond even a few nodes. Sometimes this is because the method does not scale well, in which case the code cannot be blamed, and sometimes it is because the code was not written to scale well. Usually, this is because the code was originally written in like 1970.&lt;/p&gt;&#xA;&lt;p&gt;I hesitate to be too specific because I have not used every electronic structure package to do large calculations. I have, however, done some very large calculations with NWChem and have found that the MP2 and CCSD(T) implementations scale linearly with the number of cores for a very long time. The triples part of CCSD(T) is actually known to scale linearly to the entire size of the Cori supercomputer at Nersc as implemented in NWChem.&lt;/p&gt;&#xA;&lt;p&gt;My personal experience is that Gaussian does not scale particularly well with the number of nodes. I think most people use Gaussian for DFT though, which I have never done, so take this statement with a big grain of salt.&lt;/p&gt;&#xA;&lt;p&gt;I have also used Molpro and out-of-the-box, it seems to be a very fast code. So, if you are only interested in single-core speed, I would guess that Molpro will fare very well. Their MCSCF implementation is famously good in my experience as well.&lt;/p&gt;&#xA;&lt;p&gt;Also, Psi4 is an excellent, modern electronic structure package which seems to have been made with parallelism in mind, so I would think it will scale better than many packages.&lt;/p&gt;&#xA;&lt;p&gt;This is why generally, for gas-phase ground state electronic structure I think Psi4 and NWChem are the way to go. They seem to be well-written and are free.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Generally, though, getting fair comparisons of the speed of two programs which implement the same method is very difficult. If you want to benchmark DFT, you need to use the same grid for each calculation, you need to run them on the exact same core of the same CPU. You need to make sure nothing is happening in the background of the computer you're running on that could interfere. You should run each calculation many times.&lt;/p&gt;&#xA;&lt;p&gt;Something like HF is even harder to benchmark fairly because HF is an iterative method. So, the initial guess you use, as well as things that accelerate iterations such as DIIS, make a big difference in how long the calculation takes. Also, when comparing, you need to make sure the integral thresholds are identical since most electronic structure programs will throw out certain integrals which are guaranteed to be smaller than some value. Also, for a large calculation, you need to be careful to make sure that the integrals are stored in an identical manner since sometimes the integrals are stored in RAM and other times they are stored partially on disk and still other times they just aren't stored and get re-calculated.&lt;/p&gt;&#xA;&lt;p&gt;For all of these reasons, performing a good-faith comparison of the speed of these packages is nearly impossible. Also, I would argue that the scaling matters much more than the zero-order speed.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2020-10-21T17:58:30.843" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3574" PostTypeId="2" ParentId="3571" CreationDate="2020-10-21T21:55:58.747" Score="7" Body="&lt;p&gt;I'll try to be as basic as I can in regard to explaining the stuff youve posted.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;From what I read online, spin-orbit coupling is how the angular&#xA;momentum of an electron w.r.t. the nucleus interacts with its spin.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, and there are two types interactions Russell Saunders coupling(LS coupling) and the j-j coupling. The electron has an orbital angular momentum(let's call it L) as it revolves around the nuclei and a spin angular momentum (Let's call it S) (This is where the relativistic stuff comes in !!. The spin is not a natural consequence of the Schrodinger equation, it's a consequence of the relativistic Dirac equation)&lt;/p&gt;&#xA;&lt;p&gt;LS coupling: This happens when the L and S of an individual electron interact strongly with the L and S of another electron respectively (i.e, L1 of electron 1 interacts with L2 of electron 2 and S1 &amp;amp; S2 does the same thing. But here L1 and S1 wont interact strongly). Then the total L and the total S interacts to give you the J value (which is the total angular momentum).&lt;/p&gt;&#xA;&lt;p&gt;J-J coupling: Here the L1 and S1 of electron 1 interact to give you j1 and then the j1, j2, j3.. etc of electrons 1 ,2 ,3 respectively interact together to give you the total J value. In such cases, the total L and the total S are not explicitly mentioned.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The word 'relativistic' came up every time.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Thats because the spin is a relativistic concept as its obtained from the Dirac equation.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is spin orbit coupling (soc) and what does soc strength mean?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You could think of SOC as the interaction of the particles spin with its motion in the presence of a potential. And about SOC strength a rough estimate would be the atomic number of the element.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \textrm{soc}\:\textrm{strength} \; \alpha \; Z^{4} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;That's why SOC is mostly seen in heavy elements.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \textrm{soc}\:\textrm{strength} = \textrm{DoS}_{(\textrm{spin-up})_{E_F}} -\: \textrm{DoS}_{(\textrm{spin-down})_{E_F}}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'm not entirely sure about this, so I'm not going to comment on this.&lt;/p&gt;&#xA;&lt;p&gt;Another method :&lt;/p&gt;&#xA;&lt;p&gt;You can study SOC if you could simulate the Electron paramagnetic resonance(EPR) spectra.&#xA;If the EPR spectra can be simulated. Then we can extract important Hamiltonian parameters such as D and E which are the zero-field splitting terms.&#xA;D and E quantify the extent of zero-field splitting.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \zeta = \; \textrm{spin orbit coupling constant} $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ D = \frac{\zeta}{6[g_{zz} - \frac{1}{2(g_{xx} + g_{yy})}]} $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E = \frac{\zeta}{12(g_{xx}-g_{yy})} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus, EPR spectra can be used to extract the spin-orbit coupling parameter &lt;strong&gt;provided that your material is EPR active&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="116" LastEditDate="2020-10-22T21:50:40.950" LastActivityDate="2020-10-22T21:50:40.950" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3575" PostTypeId="2" ParentId="3567" CreationDate="2020-10-22T07:31:16.777" Score="5" Body="&lt;p&gt;The density of states (DOS) is the number of different states at a particular energy level that electrons are permitted to occupy, i.e. the number of electron states per unit volume per unit energy.&lt;/p&gt;&#xA;&lt;p&gt;It is usually summarized by the equation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ DOS = (\frac{dN}{dE})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since the first derivative of N with respect to E exists, you can, in fact, interpolate the integrated DOS via a smoothly varying function. But the choice should be based on the function should be such that it's derivative at certain energies should give the DOS value at that energy.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-22T07:31:16.777" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3576" PostTypeId="1" AcceptedAnswerId="3815" CreationDate="2020-10-22T08:11:56.643" Score="8" ViewCount="137" Body="&lt;p&gt;I am using USPEX code. I would like to create structures with vacancies. I defined in the file &amp;quot;INPUT.txt&amp;quot; vacancy as Vc, but it stopped and said:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  'Element Vc does not exist. Please go back to check it again.'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you know how to define vacancy in USPEX? I did not find any description in USPEX manual.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2020-11-26T18:33:42.287" LastActivityDate="2020-11-26T18:33:42.287" Title="Vacancy with USPEX" Tags="|software-assistance|uspex|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3577" PostTypeId="2" ParentId="3567" CreationDate="2020-10-22T08:50:51.143" Score="11" Body="&lt;p&gt;Calculating densities of states is a tricky problem, as you correctly recognized. The density of states is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;g(E)=\sum_{n}\int\frac{d\mathbf{k}}{(2\pi)^3}\delta(E-E_{n\mathbf{k}}),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{n\mathbf{k}}$&lt;/span&gt; are the electronic energies and the integral is over the Brillouin zone. There are various strategies that one can follow, including:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Broadening.&lt;/strong&gt; The delta function is replaced by a smooth function (typically a Gaussian). This method smears out the sharper features, so you may need many &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points for convergence.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Adaptive broadening.&lt;/strong&gt; This is a broadening scheme in which the broadening is different at each &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point, and related to the gradient of the energy at that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point. This enables the description of sharp features with smaller number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points. A description of adaptive broadening can be found in this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.75.195121&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Interpolation.&lt;/strong&gt; The energy is calculated at a discrete grid covering the Brillouin zone (typically made of tetraheda) and the values in-between the grid points are interpolated, typically using linear or quadratic schemes. This method fails near band crossings because the different points are always joined by their respective &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; index. A description of the tetrahedron method can be found in this &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssb.2220540211&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Extrapolation.&lt;/strong&gt; The energy is extrapolated from the calculated &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point to allow for band crossings. This is a related &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.29.4331&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Overall, a very nice overview for calculating densities of states can be found in the paper introducing &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465514000460#br000075&quot; rel=&quot;noreferrer&quot;&gt;OPTADOS&lt;/a&gt;, a software package that implements the above options.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-22T08:50:51.143" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3578" PostTypeId="1" AcceptedAnswerId="3580" CreationDate="2020-10-22T11:29:42.647" Score="6" ViewCount="157" Body="&lt;p&gt;I'm looking for a simulation of different water models (TIP3P, SPC/E, TIP4P, water models with flexible bounds) where the differences in simulation speeds on a common architecture are really seen. Everyone says TIP4P is computationally more costly than TIP3P which makes sense as TIP4P has more degrees of freedom but I want to quantify it. Ideally I'd like to have a comparison between a water model with flexible bounds and one with rigid bounds but I'd happily take other sources as well.&lt;/p&gt;&#xA;" OwnerUserId="1388" LastActivityDate="2020-10-22T13:49:47.623" Title="Do we have specific benchmarks for the speed of a simulation of an empty water box with different water models?" Tags="|molecular-dynamics|molecular-interactions|water|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3579" PostTypeId="2" ParentId="1354" CreationDate="2020-10-22T12:48:29.147" Score="4" Body="&lt;p&gt;Since I leave academia (where I used the popular gaussian package) but I want to continue to do some research in my free time, I spend the last months trying to chose the best software for quantum chemistry calculations. I think the first thing one need to know is how much the software is updated with new methods, new DFT functionals.... After a first selection based on this, one need to know what is the system that will be used for running the calculation (i.e. laptop, desktop pc, workstation, cluster) to evaluate also the parallelization of the software (see for example the scaling of nwchem in a cluster with thousands of nodes). I will do my work on a desktop pc, so it's obvious that I need a well written code to run the calculation faster. However, like others said, you can compare different packages only if you use the same parameters (grid size, convergence threshold....).  In my research I also discover that most packages use external libraries (BLAS, LAPACK) for the hardest part of calculations such as matrix multiplications, integral evaluations... So I think the choice of the software may be done mostly on the basis of the frequency of the update. In the end, I think that most of the performance for a calculation with the same parameters could be attributed to : the optimization in the compilation phase (optimization flags); the choice of good libraries (ATLAS vs OPENBLAS vs MKL...; look for some benchmark and you will see how much they perform  very very different); the system you are using (linux version, linux scheduler, used file system, optimized kernel)... I' m still studying about this topic and these are my actual findings.  What I would like to do in the near future is&#xA;try to optimize all these parameters to see how much one can gain in term of time.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="982" LastEditDate="2020-10-22T22:11:46.903" LastActivityDate="2020-10-22T22:11:46.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3580" PostTypeId="2" ParentId="3578" CreationDate="2020-10-22T13:49:47.623" Score="5" Body="&lt;p&gt;You may be able to find some bounds on performance such as O(n&lt;sup&gt;3&lt;/sup&gt;) based on the number of water molecules etc, but honestly benchmarks not performed on your own hardware are always somewhat hard to use or accept.  Things such as memory speed can also influence things quite significantly so benchmarks are hard to look at for quantifiable differences.&lt;/p&gt;&#xA;&lt;p&gt;That being said, trends may apply, but you already know this since you know TIP4P is more computationally expensive than TIP3P.  If you want to quantify it, you really need to run your own benchmark.  Simply create a relevant water system and run it with all relevant methods for a couple of iterations and compare.&lt;/p&gt;&#xA;&lt;p&gt;If you do benchmark it for your system though, please add an answer sharing your benchmark and system.  Sometimes trends can shift based on software version or major hardware differences.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-22T13:49:47.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3581" PostTypeId="2" ParentId="3576" CreationDate="2020-10-22T13:53:41.707" Score="1" Body="&lt;p&gt;I never have used USPEX, but here is a bad solution to the problem even if it doesn't support vacancies.  Use a dummy element such as Na that is not in your system.  Post-process the structure afterwards to remove it, using something like ASE.  This is definitely not ideal, but you might find that it works to generate reasonable structures.&lt;/p&gt;&#xA;&lt;p&gt;USPEX might use the size information of the atom to fit them (I am unsure), so if it does be sure to pick an element with a similar size or charge etc to the atom where the vacancy would have formed.  This ensures it comes up with reasonable starting guesses.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-22T13:53:41.707" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3582" PostTypeId="2" ParentId="2414" CreationDate="2020-10-22T17:53:35.620" Score="6" Body="&lt;p&gt;Smearing is a mathematical trick implemented in codes like quantum ESPRESSO so as to aid in convergence. It has no physical meaning. You could think of it as follows:&lt;/p&gt;&#xA;&lt;p&gt;The orbitals are populated by electrons if the smearing is zero then the electrons are forced to acquired a set of finite energies without any tolerance factor to account for the error in the predicted energies. But with smearing turned on, you are essentially filling in fractions of an electron in some spread of energies within the vicinity of your original energy level. This helps in bringing in that error tolerence which is needed for convergence.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-22T17:53:35.620" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3583" PostTypeId="1" AcceptedAnswerId="3671" CreationDate="2020-10-22T18:19:54.920" Score="8" ViewCount="161" Body="&lt;p&gt;Can kinetic isotope effects be handled in density functional theory level calculations?  My intuition says that in the context of molecular dynamics simulations that they can be, but can transition state calculations reveal anything about kinetic isotope effects?&lt;/p&gt;&#xA;&lt;p&gt;For example the relationship between the activation energy and rate is commonly used as follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$k = Ae^{-E_{a}/RT}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Isotope effects must be folded into either the prefactor &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; or into the entropy change of &lt;span class=&quot;math-container&quot;&gt;$E_{a}$&lt;/span&gt;.  However it is unclear to me right now how this would actually be done, even when considering just trends in the reactivity.  I suspect that entropy is not the only thing affecting things, but it is unclear where the correction to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; would come from.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-10-31T04:56:20.863" LastActivityDate="2020-11-01T21:28:20.287" Title="Isotopes in Reaction Kinetics by Transition State Theory" Tags="|density-functional-theory|transition-state|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3585" PostTypeId="1" CreationDate="2020-10-22T21:00:00.223" Score="7" ViewCount="117" Body="&lt;p&gt;I have been following the FDTD tutorials for GPAW, and have been able to determine how to print the electric field strength (magnitude), but not the components of the electric field. How would I do this?&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&#xA;Jason Gray&lt;/p&gt;&#xA;&lt;p&gt;The tutorials I am following are: &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/electrodynamics/qsfdtd.html#advanced-example-near-field-enhancement&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; for the classical case and &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/electrodynamics/hybridscheme.html&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; for the hybrid quantum/classical scheme.&lt;/p&gt;&#xA;" OwnerUserId="1451" LastEditorUserId="5" LastEditDate="2020-10-23T01:08:55.053" LastActivityDate="2020-10-24T17:28:41.300" Title="How do I find the electric field components from an FDTD simulation using GPAW?" Tags="|gpaw|finite-difference-time-domain|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3586" PostTypeId="1" CreationDate="2020-10-22T21:43:50.147" Score="7" ViewCount="198" Body="&lt;p&gt;I have a few questions about default units. I am trying to find the default units for the density matrix and the core hamiltonian. I am assuming they are in e/(bohr)&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt; and Hartrees respectively. I am also trying to determine which units are being used in my input file for the Electric field intensity as they change based on the periodicity of the system. Is it in W/cm&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt; or in a.u? I have used the &lt;code&gt;PERIODIC NONE&lt;/code&gt; keyword for the cell so I am thinking it is in a.u.&lt;/p&gt;&#xA;&lt;p&gt;My input file is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;GLOBAL&#xA;  PROJECT BENZENE-UNPERTURBED&#xA;  RUN_TYPE ENERGY_FORCE&#xA;  PRINT_LEVEL low&#xA;&amp;amp;END GLOBAL&#xA;&amp;amp;FORCE_EVAL&#xA;  METHOD QS&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;KIND H&#xA;      BASIS_SET DZVP-GTH-PADE&#xA;      POTENTIAL GTH-PBE-q1&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND C&#xA;      BASIS_SET DZVP-GTH-PADE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND N&#xA;      BASIS_SET DZVP-GTH-PADE&#xA;      POTENTIAL GTH-PBE-q5&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;CELL&#xA;      ABC 30.0 30.0 30.0&#xA;      PERIODIC NONE&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;TOPOLOGY                                                                                      &#xA;      COORD_FILE_NAME benzene.xyz                                                                &#xA;      COORD_FILE_FORMAT xyz                                                                      &#xA;      &amp;amp;CENTER_COORDINATES                                                                        &#xA;      &amp;amp;END CENTER_COORDINATES                                                                    &#xA;    &amp;amp;END TOPOLOGY  &#xA;  &amp;amp;END SUBSYS&#xA;  &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME ./BASIS_SET&#xA;    POTENTIAL_FILE_NAME ./POTENTIALS&#xA;    &amp;amp;QS&#xA;      EPS_DEFAULT 1.0E-10&#xA;    &amp;amp;END QS&#xA;    &amp;amp;POISSON                                &#xA;      PERIODIC NONE    &#xA;      POISSON_SOLVER wavelet&#xA;      &amp;amp;WAVELET&#xA;        SCF_TYPE 100&#xA;      &amp;amp;END WAVELET                                                                          &#xA;    &amp;amp;END POISSON&#xA;    &amp;amp;MGRID&#xA;      CUTOFF 800&#xA;      NGRIDS 6     &#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;SCF&#xA;      SCF_GUESS RESTART&#xA;      EPS_SCF 1.0E-10&#xA;      MAX_SCF 100&#xA;      &amp;amp;DIAGONALIZATION T&#xA;        ALGORITHM STANDARD&#xA;      &amp;amp;END DIAGONALIZATION&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;    &amp;amp;REAL_TIME_PROPAGATION&#xA;      INITIAL_WFN SCF_WFN&#xA;      EPS_ITER 1E-9&#xA;      MAX_ITER 10&#xA;      MAT_EXP TAYLOR&#xA;      DELTA_PULSE_DIRECTION 0 0 1&#xA;    #  DENSITY_PROPAGATION .TRUE.&#xA;    &amp;amp;END REAL_TIME_PROPAGATION&#xA;    &amp;amp;EFIELD&#xA;      INTENSITY 1E10&#xA;      POLARISATION 1.0000000000000000 0.0000000000000000 0.0000000000000000&#xA;      WAVELENGTH [nm] 1E6&#xA;      &amp;amp;CONSTANT_ENV&#xA;           START_STEP 0&#xA;           END_STEP 1&#xA;      &amp;amp;END CONSTANT_ENV&#xA;    &amp;amp;END EFIELD&#xA;    &amp;amp;PRINT&#xA;      &amp;amp;AO_MATRICES&#xA;         ADD_LAST NUMERIC&#xA;         DENSITY .TRUE.&#xA;         CORE_HAMILTONIAN&#xA;         NDIGITS 30&#xA;      &amp;amp;END AO_MATRICES&#xA;    &amp;amp;END PRINT&#xA;  &amp;amp;END DFT&#xA;&amp;amp;END FORCE_EVAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you,&#xA;Jason Gray&lt;/p&gt;&#xA;" OwnerUserId="1451" LastEditorUserId="5" LastEditDate="2020-10-22T21:52:41.980" LastActivityDate="2020-10-28T17:05:55.040" Title="What are the default units for the core hamiltonian and the density AO matrices in CP2K?" Tags="|cp2k|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3587" PostTypeId="5" CreationDate="2020-10-23T03:28:00.460" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-23T03:28:00.460" LastActivityDate="2020-10-23T03:28:00.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3588" PostTypeId="4" CreationDate="2020-10-23T03:28:00.460" Score="0" Body="Questions about finding the molecular or material geometry that has the lowest energy." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-10-23T03:28:00.460" LastActivityDate="2020-10-23T03:28:00.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3589" PostTypeId="1" AcceptedAnswerId="3593" CreationDate="2020-10-23T08:50:46.103" Score="17" ViewCount="6741" Body="&lt;p&gt;Which software package(s) can be used to visualize the trajectory of VASP MD simulation?&lt;/p&gt;&#xA;&lt;p&gt;VMD claims that there is a plugin to read the VASP output, while in the last version for Linux, I did not find it (it is there in Windows version of VMD), so I cannot check my results with my eyes directly, unless I download it from server or change the format to the format VMD accepted.&lt;/p&gt;&#xA;&lt;p&gt;VESTA can read the format, but can only visualize the trajectory frame by frame, while I prefer to watch the movie.&lt;/p&gt;&#xA;&lt;p&gt;Some related, but not duplicate, questions are&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2433/methods-for-visualization-of-crystal-structures&quot;&gt;Methods for visualization of crystal structures&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1590/great-computer-graphics-for-matter-modelling&quot;&gt;Great computer graphics for matter modelling&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But my point here is to know the easiest way to check the MD simulation trajectory like watching the movie on Linux servers.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="5" LastEditDate="2020-10-23T18:47:58.263" LastActivityDate="2023-10-19T09:52:52.450" Title="How can I visualize the trajectory of a VASP simulation?" Tags="|vasp|one-topic-per-answer|visualization-software|" AnswerCount="5" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3590" PostTypeId="2" ParentId="3589" CreationDate="2020-10-23T15:28:45.617" Score="14" Body="&lt;h3&gt;ASE&lt;/h3&gt;&#xA;&lt;p&gt;You can use ASE environment to visualize, it has different options as well. e.g., you can use this command: &lt;code&gt;ase gui vasprun.xml&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2020-10-23T22:06:33.460" LastActivityDate="2020-10-23T22:06:33.460" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3591" PostTypeId="2" ParentId="3589" CreationDate="2020-10-23T17:20:23.300" Score="7" Body="&lt;h3&gt;JMol&lt;/h3&gt;&#xA;&lt;p&gt;To give you another option you can try &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jmol&lt;/a&gt; which runs on Java and should be fairly straight forward to compile on a Linux machine. Although to be honest I personally do not use it, just figured I would add to the list here.&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="5" LastEditDate="2020-10-23T18:47:51.540" LastActivityDate="2020-10-23T18:47:51.540" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3592" PostTypeId="1" AcceptedAnswerId="3623" CreationDate="2020-10-23T20:59:19.670" Score="11" ViewCount="1907" Body="&lt;p&gt;I have run the DFT calculation and plotted DOS of Fe(BCC) in Quantum ESPRESSO. I have attached the plot:&#xA;(click on image to see clearly)&#xA;&lt;a href=&quot;https://i.stack.imgur.com/zS9CG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zS9CG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But It's a wrong plot as it is not matched with the referenced DOS plots of Fe(BCC). Fermi energy is around 18 eV from the calculation. Now, I am stuck about how to get the right plot. I have already converged lattice constant and magnetic moment with plane wave numbers. I have also attached the PWSCF input files to perform the calculation.Now I have following questions:&lt;/p&gt;&#xA;&lt;p&gt;1)How can I plot DOS of Fe(BCC) rightly(shape of the curve is completely wrong)?&lt;br /&gt;&#xA;2)Is there any changes which I have to do in my input files?&lt;br /&gt;&#xA;3)Since it is a ferromagnetic system, DOS at Fermi level should be relatively low for spin down electrons, which is not appearing in the graph. Why is so?&lt;/p&gt;&#xA;&lt;p&gt;Input file for SCF calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                   title = 'Magnetization of Fe' ,&#xA;             calculation = 'scf' ,&#xA;                  outdir = '.' ,&#xA;              pseudo_dir = '.' ,&#xA;                  prefix = 'Fe' ,&#xA;           etot_conv_thr = 1.0D-6 ,&#xA;           forc_conv_thr = 1.0D-6 ,&#xA;                 tprnfor = .true. ,&#xA;                 tstress = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                   ibrav = 3,&#xA;                       A = 2.84197 ,&#xA;                     nat = 1,&#xA;                    ntyp = 1,&#xA;                    nbnd = 30,&#xA;                 ecutwfc = 100 , &#xA;                 ecutrho = 1000 ,&#xA;             occupations = 'smearing' ,&#xA;                 degauss = 0.05 ,&#xA;                smearing = 'gaussian' ,&#xA;                   nspin = 2 ,&#xA; starting_magnetization(1) = 0.1,      &#xA; /&#xA;&amp;amp;ELECTRONS&#xA;                conv_thr = 1.0D-6 ,&#xA; /&#xA;&amp;amp;IONS&#xA; /&#xA;&amp;amp;CELL&#xA; /      &#xA;ATOMIC_SPECIES&#xA;Fe   55.84500  Fe.pbe-spn-kjpaw_psl.0.2.1.UPF &#xA;ATOMIC_POSITIONS alat &#xA;  Fe      0.000000000    0.000000000    0.000000000 &#xA;K_POINTS automatic &#xA;  10 10 10   1 1 1 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input file for nscf calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                   title = 'Magnetization of Fe' ,&#xA;             calculation = 'nscf' ,&#xA;                  outdir = '.' ,&#xA;              pseudo_dir = '.' ,&#xA;                  prefix = 'Fe' ,&#xA;           etot_conv_thr = 1.0D-6 ,&#xA;           forc_conv_thr = 1.0D-6 ,&#xA;                 tprnfor = .true. ,&#xA;                 tstress = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                   ibrav = 3,&#xA;                       A = 2.84197 ,&#xA;                     nat = 1,&#xA;                    ntyp = 1,&#xA;                    nbnd = 30,&#xA;                 ecutwfc = 100 , &#xA;                 ecutrho = 1000 ,&#xA;             occupations = 'smearing' ,&#xA;                 degauss = 0.05 ,&#xA;                smearing = 'gaussian' ,&#xA;                   nspin = 2 ,&#xA;   starting_magnetization(1) = 0.1,      &#xA; /&#xA;&amp;amp;ELECTRONS&#xA;                conv_thr = 1.0D-6 ,&#xA; /&#xA;&amp;amp;IONS&#xA; /&#xA;&amp;amp;CELL&#xA; /      &#xA;ATOMIC_SPECIES&#xA;   Fe   55.84500  Fe.pbe-spn-kjpaw_psl.0.2.1.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Fe      0.000000000    0.000000000    0.000000000 &#xA;K_POINTS automatic &#xA;  20 20 20   1 1 1 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1361" LastEditDate="2020-10-25T06:27:01.940" LastActivityDate="2020-10-25T19:03:10.767" Title="Plotting density of states of Fe(BCC) using Quantum ESPRESSO" Tags="|density-functional-theory|electronic-structure|quantum-espresso|band-structure|dos|" AnswerCount="2" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="3593" PostTypeId="2" ParentId="3589" CreationDate="2020-10-23T22:02:09.427" Score="9" Body="&lt;h3&gt;VMD&lt;/h3&gt;&#xA;&lt;p&gt;I had to dig up the VMD script that I used for this. VMD doesn't detect the file type automatically, so you have to tell it to use &lt;code&gt;VASP_XDATCAR5&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the VMD Tk Console, you can load the XDATCAR file from VASP with the following command:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mol new XDATCAR type VASP_XDATCAR5&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or, if GUIs are your thing, you can open File -&amp;gt; New Molecule..., select the XDATCAR file, and select &lt;code&gt;VASP_XDATCAR5&lt;/code&gt; under &amp;quot;Determine file type&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xwjFK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xwjFK.png&quot; alt=&quot;Opening a VASP XDATCAR file in VMD.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="5" LastEditDate="2020-10-23T22:05:34.213" LastActivityDate="2020-10-23T22:05:34.213" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3594" PostTypeId="2" ParentId="3571" CreationDate="2020-10-24T01:17:33.633" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What is spin-orbit coupling (soc) and what does soc strength mean?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The spin-orbital coupling (SOC) is a relativistic effect. Mathematically, it can be represented as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\vec{L} \cdot \vec{S}$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\vec{L}$&lt;/span&gt; is orbital angular momentum and &lt;span class=&quot;math-container&quot;&gt;$\vec{S}$&lt;/span&gt; is spin angular momentum. How to identify the strength of SOC?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Taking the Hamiltonian without the consideration of SOC as &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, you can always obtain the energy dispersion as &lt;span class=&quot;math-container&quot;&gt;$E_1(\vec{k})$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Taking the &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and SOC term &lt;span class=&quot;math-container&quot;&gt;$\vec{L}\cdot \vec{S}$&lt;/span&gt; at the same time, you will obtain a new energy dispersion &lt;span class=&quot;math-container&quot;&gt;$E_2(\vec{k})$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Compare the &lt;span class=&quot;math-container&quot;&gt;$E_1(\vec{k})$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_2({\vec{k}})$&lt;/span&gt; and find the difference. Usually, you will find the band splitting due to SOC. If the splitting is large, you can think SOC is strong.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-10-25T11:12:44.500" LastActivityDate="2020-10-25T11:12:44.500" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3595" PostTypeId="2" ParentId="3592" CreationDate="2020-10-24T02:09:34.937" Score="7" Body="&lt;p&gt;I have noticed the error, I believe.  The example you link in the comments has two Fe atoms whereas your model only has one.  These expected results seem fairly consistent with an antiferromagnetic/ferrimagnetic system I believe, which will not be possible to model in a single atom representation.&lt;/p&gt;&#xA;&lt;p&gt;Please try to make a 2 atom unit cell and see if this fixes your problems.  This is a very surface level guess, but we can refine this answer if this turns out not to be the problem.  Also with such a small cell, maybe you can avoid the NSCF run altogether and just run a SCF calculation at 20x20x20 with your optimized geometry.&lt;/p&gt;&#xA;&lt;p&gt;Here is an &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/exercises/iron/iron.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;exercise from the GPAW documentation&lt;/a&gt; as some additional reading.&lt;/p&gt;&#xA;&lt;p&gt;Suggestion 2:&lt;/p&gt;&#xA;&lt;p&gt;Looking at the example you linked, I see they are using an ultrasoft potential and you are using a PAW potential.  Reading on the mailing list I see this can maybe have trouble with AFM structures, but as you note this should converge to an FM structure.  Can you check in the final output what the magnetization actually is?  Also try an ultrasoft potential.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2020-10-24T17:39:58.710" LastActivityDate="2020-10-24T17:39:58.710" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3596" PostTypeId="1" CreationDate="2020-10-24T04:21:37.830" Score="5" ViewCount="915" Body="&lt;p&gt;I have to do a electronic band structure calculation on a heterostructure using DFT calculation. First I do the calculation on each phase separately. I use a primitive unit cell to do the calculation and the band structure was assumed to be the band from the bulk. Since I have to change the unit cell when I do the calculation on my heterostructure, I try to use another unit cell with different shape to do the calculation again on each phase separately. I found that the band structure differ from the previous one which was done with primitive cell. I know that the band structure must be different, because the reciprocal space spanned by reciprocal vector become different and the Brillouin zone become different too. But the band gap of the system was changed. How can I understand it ?&#xA;I did the calculation on SnTe with a primitive cell and a large cell.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/8DDdD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8DDdD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;And the band structure was shown in below, for the left one it was done in primitive cell and calculate along the High symmetry point. Another one was done in a larger unit cell.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/1DJYl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1DJYl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="621" LastEditDate="2020-10-27T11:38:34.160" LastActivityDate="2020-10-27T11:38:34.160" Title="Calculating the band structure with different unit cell" Tags="|density-functional-theory|ab-initio-calculations|band-structure|brillouin-zone|heterostructures|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3597" PostTypeId="1" CreationDate="2020-10-24T13:07:12.510" Score="5" ViewCount="870" Body="&lt;p&gt;So, I know that to calculate surface band structure of a material, you have to take its 2D system eg. &lt;em&gt;single or few-layered&lt;/em&gt;. But, how to find the surface band structure in the case of heterostructures. This paper does it &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.90.035418&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Proximity-induced topological state in graphene&#xA;&amp;quot;&lt;/a&gt; but uses &lt;strong&gt;VASP&lt;/strong&gt; instead. Is it possible to do the same using &lt;strong&gt;Quantum espresso&lt;/strong&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2020-10-24T14:37:38.360" LastActivityDate="2020-10-25T00:37:51.713" Title="How to separate the band structure of different materials in heterostructures using Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|2d-lattice|graphene|heterostructures|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3598" PostTypeId="2" ParentId="2467" CreationDate="2020-10-24T14:36:55.177" Score="6" Body="&lt;p&gt;I am not sure about TC-Python but in console mode, you can access the Gibbs energy equations directly using the &lt;strong&gt;Gibbs Energy System (GES)&lt;/strong&gt; module. In case you need the details about a particular phase then you have to first define the system as usual and then after retrieving the data go to the GES module and use the &lt;strong&gt;List_phase_data&lt;/strong&gt; command. You will have to specify the phase and then you will get the thermochemical data for that phase. It includes the sublattice information and the Gibbs energy equations along with the temperature ranges where they are applicable. However, this command will give you everything in a condensed form. Some of the repeating equations will be replaced by symbols. You can get information about those symbols by using &lt;strong&gt;List_symbols&lt;/strong&gt; command along with the symbol name (for example list_symbols GHSERCO). There are several other applications, like modifying the phase description as per your requirement (for example turning off the effect of magnetic ordering for a phase). You can refer to the documentation for further details regarding the Gibbs energy system module.&lt;/p&gt;&#xA;&lt;p&gt;I tried PURE database and was able to get the same output as you have attached to your question.&lt;/p&gt;&#xA;" OwnerUserId="301" LastEditorUserId="301" LastEditDate="2020-10-24T14:43:31.640" LastActivityDate="2020-10-24T14:43:31.640" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3599" PostTypeId="2" ParentId="3589" CreationDate="2020-10-24T16:33:07.853" Score="6" Body="&lt;h3&gt;OVITO&lt;/h3&gt;&#xA;&lt;p&gt;Another option is the Open VIsualistion TOol (&lt;a href=&quot;https://www.ovito.org/&quot; rel=&quot;noreferrer&quot;&gt;OVITO&lt;/a&gt;) which has a user friendly interface, usable on multiple platform, and has some post processing and analysis tools readily available (plus a python interface to implement your own). According to the documentation it supports the following file formats : POSCAR / XDATCAR / CHGCAR&lt;/p&gt;&#xA;" OwnerUserId="1454" LastEditorUserId="5" LastEditDate="2020-10-24T19:53:58.043" LastActivityDate="2020-10-24T19:53:58.043" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3600" PostTypeId="2" ParentId="3585" CreationDate="2020-10-24T17:28:41.300" Score="2" Body="&lt;p&gt;You can get the induced field components from an induced field object. If you call your induced field object ind, then you can get the Fourier transform of the field components by accessing ind.Fef_wvg. Adding the initial kick strength to this and taking the magnitude you can get the total electric field. Comparing the total electric field magnitude to the field enhancement (ind.Ffe_wg) times the initial field magnitude you should get the same value.&lt;/p&gt;&#xA;" OwnerUserId="1451" LastActivityDate="2020-10-24T17:28:41.300" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3601" PostTypeId="1" AcceptedAnswerId="3625" CreationDate="2020-10-24T19:38:01.733" Score="5" ViewCount="38" Body="&lt;p&gt;Its normally that case that most material modeling techniques rely on energy minimizations, which result in the equilibrium solutions for most chemical of physical processes. While this is great for the general case, most things in life rely on disequilibrium to drive reactions/processes. One big field that uses disequilibrium chemistry for modeling reactions is Exoplanet Atmospheric Modeling, &lt;a href=&quot;https://ceps.spacescience.org/disequilibrium-chemistry.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; you can see a general idea of how its used in said field.&lt;/p&gt;&#xA;&lt;p&gt;What are some ways to model these disequilibrium processes with current software packages? As a bonus follow-up if you personal use disequilibrium processes in your research; how and why is it used?&lt;/p&gt;&#xA;" OwnerUserId="65" LastActivityDate="2020-10-25T22:29:36.110" Title="What are some ways to model disequilibrium processes with current software?" Tags="|software|one-topic-per-answer|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3602" PostTypeId="1" CreationDate="2020-10-24T23:01:47.243" Score="3" ViewCount="41" Body="&lt;p&gt;Cuprate superconductors have a pseudogap phase that is not well-understood. What attempts have been made to understand the pseudogap phase?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2021-06-11T17:21:39.890" LastActivityDate="2021-06-11T17:21:39.890" Title="How are pseudogap phases typically modelled?" Tags="|ab-initio-calculations|superconductivity|" AnswerCount="0" CommentCount="1" ClosedDate="2021-12-10T22:16:10.310" ContentLicense="CC BY-SA 4.0" />
  <row Id="3603" PostTypeId="1" CreationDate="2020-10-24T23:26:09.620" Score="7" ViewCount="52" Body="&lt;p&gt;Nematic phases in superconducting materials are studied in both angular-resolved photoelectron spectroscopy (ARPES) and second harmonic generation (SHG) experiments. What techniques, if any, are used to model these phases?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2021-06-11T17:22:34.150" LastActivityDate="2021-06-11T17:22:34.150" Title="How are nematic phases modelled?" Tags="|spectroscopy|superconductivity|" AnswerCount="0" CommentCount="2" ClosedDate="2021-12-15T15:03:38.267" ContentLicense="CC BY-SA 4.0" />
  <row Id="3604" PostTypeId="2" ParentId="686" CreationDate="2020-10-24T23:59:44.290" Score="5" Body="&lt;p&gt;While I am not sure how famous this was, there was a paper in Nature Nanotechnology that proposed a design for a charge-driven molecular water pump. Later, though, another article argued that the water flow the first paper reported was actually the result of a numerical artefact.&lt;/p&gt;&#xA;&lt;p&gt;This is the original paper:&lt;/p&gt;&#xA;&lt;p&gt;Gong, X., Li, J., Lu, H. et al. A charge-driven molecular water pump. Nature Nanotech 2, 709–712 (2007). &lt;a href=&quot;https://doi.org/10.1038/nnano.2007.320&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/nnano.2007.320&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The article that challenges the results of the original paper:&lt;/p&gt;&#xA;&lt;p&gt;Wong-ekkabut, J., Miettinen, M., Dias, C. et al. Static charges cannot drive a continuous flow of water molecules through a carbon nanotube. Nature Nanotech 5, 555–557 (2010). &lt;a href=&quot;https://doi.org/10.1038/nnano.2010.152&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/nnano.2010.152&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="46" LastActivityDate="2020-10-24T23:59:44.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3605" PostTypeId="2" ParentId="3597" CreationDate="2020-10-25T00:37:51.713" Score="6" Body="&lt;p&gt;I believe what you are referring to is a &amp;quot;projected&amp;quot; or &amp;quot;fat&amp;quot; band structure diagram. By assigning colors (or line thickness) to a basis on which you project the Kohn-Sham states (pseudoatomic orbitals, Wannier functions, etc.) you can plot the band structure in a way that shows the composition of all the states in the bands in terms of this basis. There are a few ways to do this in Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;This capability has been included for the last few versions in Quantum ESPRESSO itself. Look in the folder&#xA;&lt;code&gt;q-e/PP/examples/projected_bands_example/&lt;/code&gt;&#xA;for an example that shows how to do this. The projected states you're interested in will be those that correspond to the atoms on your surface. The &lt;code&gt;projwfc.x&lt;/code&gt; output labels these states according to the atom order you specify in your &lt;code&gt;ATOMIC_POSITIONS&lt;/code&gt; part of your input file.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Other codes that interface with QE can generate projected band structures. One example is &lt;a href=&quot;http://schmeling.ac.rwth-aachen.de/cohp/index.php?menuID=6&quot; rel=&quot;noreferrer&quot;&gt;LOBSTER&lt;/a&gt;. See section 3 of the user's guide. &lt;a href=&quot;http://www.wannier.org/features/&quot; rel=&quot;noreferrer&quot;&gt;Wannier90&lt;/a&gt; can also create projected band diagrams in terms of the maximally-localized Wannier functions it generates.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-25T00:37:51.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3606" PostTypeId="1" CreationDate="2020-10-25T01:32:35.650" Score="5" ViewCount="257" Body="&lt;p&gt;I have troubles with obtaining spectra for selected molecules in different DFT functionals.&lt;/p&gt;&#xA;&lt;p&gt;I calculate IR spectra for my target molecules (gold complexes with C/H/N/O/S/Au composition) to find how different levels of theory fit experimental data. In most cases everything looks fine, but for some unknown reason for two of them I have issues. In both cases the problem is the same: after geometry optimization is finished and I move to frequency job the Hessian appeared to have only -nan values:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Hessian of the SCF Energy&#xA;            1           2           3           4           5           6&#xA;    1        -nan        -nan        -nan        -nan        -nan        -nan&#xA;    2        -nan        -nan        -nan        -nan        -nan        -nan&#xA;    3        -nan        -nan        -nan        -nan        -nan        -nan&#xA;    4        -nan        -nan        -nan        -nan        -nan        -nan&#xA;    5        -nan        -nan        -nan        -nan        -nan        -nan&#xA;    6        -nan        -nan        -nan        -nan        -nan        -nan&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And I get an error message after that:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    # Finishing finite difference calculation for IDERIV #&#xA; ######################################################&#xA; ######################################################&#xA;&#xA;  ***ERROR*** Hessian Appears to have all zero or negative eigenvalues&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For one molecule it is with B3LYP, for the other one with BPBE. Same molecules in other functionals work smoothly.&lt;/p&gt;&#xA;&lt;p&gt;I had the same problem a few times for other complexes, but it was always resolved when I distorted the initial structure and re-performed optimization+frequency calculation. Calculation of frequencies alone with a given structure does not solve the issue either.&lt;/p&gt;&#xA;&lt;p&gt;What might be the reason and possible solution for that?&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="5" LastEditDate="2021-07-07T18:33:14.237" LastActivityDate="2021-07-07T18:33:14.237" Title="Q-Chem gives &quot;Hessian Appears to have all zero or negative eigenvalues&quot; error when calculating Frequencies" Tags="|software-assistance|vibrations|q-chem|" AnswerCount="0" CommentCount="8" ClosedDate="2021-01-23T13:10:53.180" ContentLicense="CC BY-SA 4.0" />
  <row Id="3607" PostTypeId="2" ParentId="3586" CreationDate="2020-10-25T01:57:39.357" Score="2" Body="&lt;p&gt;I have yet to find an explicit place where this is stated in the documentation, but the default unit for energy, and thus the core Hamiltonian, seems to be a.u., that is, hartree. Similarly, the default length unit seems to be angstroms, so the density matrix elements are likely in angstroms&lt;span class=&quot;math-container&quot;&gt;$^{-3}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From the &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/EFIELD.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K Documentation&lt;/a&gt; the E-Field is given in units of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{W}\cdot\mathrm{cm}^{-2}$&lt;/span&gt; when the &lt;code&gt;Intensity&lt;/code&gt; keyword is specified and you are performing Real-time propagation.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="142" LastEditDate="2020-10-28T17:05:55.040" LastActivityDate="2020-10-28T17:05:55.040" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3608" PostTypeId="1" AcceptedAnswerId="3621" CreationDate="2020-10-25T02:01:51.390" Score="11" ViewCount="3458" Body="&lt;p&gt;I was reading &lt;a href=&quot;https://www.nature.com/articles/sdata201422&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; on the QM9 synthetic molecular database and  their computed properties. It is stated that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;All properties were calculated at the B3LYP/6-31G(2df,p) level of&#xA;quantum chemistry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I was wondering what this 'level of theory' exactly means.&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="5" LastEditDate="2020-10-26T01:36:00.460" LastActivityDate="2020-10-26T01:36:00.460" Title="What does &quot;level of theory&quot; mean?" Tags="|quantum-chemistry|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3609" PostTypeId="2" ParentId="3608" CreationDate="2020-10-25T02:51:01.890" Score="10" Body="&lt;p&gt;&lt;code&gt;B3LYP&lt;/code&gt; refers to the functional being used.  It is a hybrid functional and it is very commonly used, but is often not sufficient and better functionals are available nowadays. It is constructed by a specific combination of HF, GGA, and LDA functionals.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;6-31G(2df,p)&lt;/code&gt; is a Pople basis set, specifically a valence double-zeta polarized basis set. It has been modified to add 2 diffuse functions for d orbitals and 1 diffuse function for p orbitals on heavy atoms.  It also has an extra diffuse functions for p orbitals on hydrogens.  This basis set is okay for a lot of work, but there are alternatives nowadays as well that I believe function better.&lt;/p&gt;&#xA;&lt;p&gt;Overall, this is a pretty standard level of theory for molecular computations, but I would not call it a very modern level of theory.  That being said, this paper is from 2014 so I am unsure how these would fit in at that time.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-25T02:51:01.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3610" PostTypeId="1" AcceptedAnswerId="3616" CreationDate="2020-10-25T03:19:00.787" Score="16" ViewCount="6044" Body="&lt;p&gt;Both Classical Monte Carlo (MC) and Classical Molecular Dynamics (MD) simulations are used to perform simulations of ensembles of molecules. These MC calculations are calculating thermodynamic properties via an ensemble average, while the MD simulations are doing so via a time average. For ergodic systems, these two approaches should give the same answer.&lt;/p&gt;&#xA;&lt;p&gt;Are there scenarios (with ergodic systems) where one method has a particular advantage over the other?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2021-03-30T04:42:30.057" LastActivityDate="2021-03-30T04:42:30.057" Title="Classical Monte Carlo vs. Molecular Dynamics" Tags="|molecular-dynamics|monte-carlo|ergodicity|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3611" PostTypeId="1" CreationDate="2020-10-25T03:26:37.360" Score="12" ViewCount="285" Body="&lt;p&gt;Given the large difference between simulation timescales and the timescales on which we normally interact with ensembles of molecules, the time average of a molecular dynamics simulation does not always match what we would expect to observe experimentally. Effectively, there is an ergodicity problem as the molecular dynamics simulation is not exploring the entirety of the relevant phase space.&lt;/p&gt;&#xA;&lt;p&gt;What techniques exist to improve the handling of non-ergodic systems for molecular dynamics simulations?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2020-11-20T22:45:12.490" LastActivityDate="2021-07-23T17:32:24.253" Title="Methods to handle non-ergodic systems with Molecular Dynamics" Tags="|molecular-dynamics|ergodicity|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3612" PostTypeId="1" CreationDate="2020-10-25T03:35:48.807" Score="12" ViewCount="109" Body="&lt;p&gt;Conventional superconductors are often modelled using Bardeen-Cooper-Schrieffer (BCS) theory with an s-wave order parameter, but not all superconductors describable with BCS theory have an s-wave order parameter.&lt;/p&gt;&#xA;&lt;p&gt;Are there any particular requirements needed to model p- or d-wave BCS superconductors in &lt;em&gt;ab initio&lt;/em&gt; calculations, which are not included when modelling s-wave superconductors?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2021-08-15T17:36:42.087" LastActivityDate="2021-08-15T17:36:42.087" Title="First principles calculations beyond s-wave BCS superconductors" Tags="|ab-initio-calculations|condensed-matter|superconductivity|bcs-theory|" AnswerCount="0" CommentCount="2" ClosedDate="2021-12-15T15:04:14.293" ContentLicense="CC BY-SA 4.0" />
  <row Id="3613" PostTypeId="1" AcceptedAnswerId="3620" CreationDate="2020-10-25T03:45:19.577" Score="7" ViewCount="75" Body="&lt;p&gt;Some materials have various competing and/or synergistic orders, such as charge density waves and superconducting pairing.&lt;/p&gt;&#xA;&lt;p&gt;Are there signatures of such an interplay between orders that can be seen in the results of ab initio calculations?&lt;/p&gt;&#xA;" OwnerUserId="46" LastActivityDate="2020-10-25T17:02:38.767" Title="Signatures of Competing Orders in Ab Initio Calculations" Tags="|ab-initio-calculations|superconductivity|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3614" PostTypeId="1" AcceptedAnswerId="3622" CreationDate="2020-10-25T04:11:21.697" Score="6" ViewCount="68" Body="&lt;p&gt;Rotating molecules have an associated magnetic moment that can couple with both nuclear and electronic spin magnetic moments, thereby impacting the hyperfine energies of rotating molecules.&lt;/p&gt;&#xA;&lt;p&gt;Can one compute such rotational magnetic moments from &lt;em&gt;ab initio&lt;/em&gt; calculations?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2020-10-25T18:06:44.483" LastActivityDate="2020-10-25T18:40:58.490" Title="Rotational magnetic moment and ab-initio calculations" Tags="|ab-initio-calculations|fine-and-hyperfine-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3615" PostTypeId="1" CreationDate="2020-10-25T04:25:48.417" Score="8" ViewCount="102" Body="&lt;p&gt;Are there any &lt;em&gt;ab initio&lt;/em&gt; packages that take advantage of Floquet's theorem (which one can think of as a generalization of Bloch's theorem from space to time) in order to study the impact of an oscillating electric field on the electronic energies of the system?&lt;/p&gt;&#xA;&lt;p&gt;Or, would one study such systems with a different ab initio approach?&lt;/p&gt;&#xA;" OwnerUserId="46" LastEditorUserId="5" LastEditDate="2021-01-22T21:01:55.300" LastActivityDate="2021-01-23T23:21:45.403" Title="Floquet's Theorem and ab-initio Calculations" Tags="|ab-initio-calculations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3616" PostTypeId="2" ParentId="3610" CreationDate="2020-10-25T07:36:19.803" Score="14" Body="&lt;p&gt;One important difference between Monte Carlo (MC) and Molecular Dynamics (MD) sampling is that to generate the correct distribution, samples in MC need not follow a physically allowed process, all that is required is that the generation process is ergodic. This can be exploited to accelerate MC schemes. The typical example of this is the Ising model, where the physical steps are individual spin flips, but instead we can replace these individual spin flips by flips of &lt;em&gt;clusters&lt;/em&gt; of spins, which could for example help accelerate equilibration to a paramagnetic phase from a starting ferromagnetic configuration.&lt;/p&gt;&#xA;&lt;p&gt;The advantages provided by the scheme described above imply that all information about the actual physical process is lost in MC sampling. This is where MD is more advantageous: in MD you are actually following a physical path, so you can gain information not only about equilibrium configurations, but also about how you physically get there.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-25T07:36:19.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3617" PostTypeId="2" ParentId="3608" CreationDate="2020-10-25T09:12:04.387" Score="11" Body="&lt;p&gt;The DFT computational level is decided by the choosing of exchange-correlation functional, such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Local-density_approximation&quot; rel=&quot;noreferrer&quot;&gt;LDA&lt;/a&gt; and GGA. The following figure called Jacob's ladder lists five levels/generations of DFT exchange-correlation functionals, in which you can find B3LYP. In general, a higher exchange-correlation-functional level will give you more reliable results but with a more computational cost.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Osju1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Osju1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;PS: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp0734474&quot; rel=&quot;noreferrer&quot;&gt;This figure is coming from this paper (Figure. 2).&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-10-25T12:02:44.133" LastActivityDate="2020-10-25T12:02:44.133" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3619" PostTypeId="2" ParentId="2386" CreationDate="2020-10-25T14:57:39.760" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;In essential, the semiconducting behaviors in one spin direction and the metal properties in the other spin direction indicates that the material belongs to the family of half-metal materials.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For example, the &lt;a href=&quot;https://www.mdpi.com/2073-4352/10/6/509&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;FeSnS&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; compound&lt;/a&gt; is predicted as half-metal by investigating its spin-polarized band structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZoEOK.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZoEOK.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to predict new Half Metallic materials with a higher degree of spin polarization?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The prediction of half-metal materials can be studied easily with spin-polarized DFT calculations. The only important thing is that you need to compare the band structure for different spin channels.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-10-25T14:57:39.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3620" PostTypeId="2" ParentId="3613" CreationDate="2020-10-25T17:02:38.767" Score="9" Body="&lt;p&gt;In the specific case of charge density wave and superconductivity, both are phenomena that can be calculated using density functional theory:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Charge density wave. It usually manifests as an imaginary phonon in the reference structure that drives the charge density wave formation.&lt;/li&gt;&#xA;&lt;li&gt;Superconductivity. Phonon-mediated superconductivity can be calculated almost routinely in the context of density functional theory, the basic quantity being the electron-phonon matrix element.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A nice example of this interplay occurs in TiSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, and density functional theory is capable of describing both phenomena as explained in this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.106.196406&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I do not really have a good general answer, but I would say that the usual approach in a first principles context (e.g. DFT) would be to separately evaluate the energy of the system in the competing phases and then compare the results.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-10-25T17:02:38.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3621" PostTypeId="2" ParentId="3608" CreationDate="2020-10-25T17:54:20.963" Score="12" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3609/5&quot;&gt;Tristan's answer&lt;/a&gt; explains what B3LYP and 6-31G(2df,p) are. I agree with everything Tristan said, I will just write an answer that is a bit more generic: not specific to B3LYP and 6-31G(2df,p).&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Level of theory&amp;quot; in quantum chemistry, is a phrase indicating &amp;quot;how accurate&amp;quot; a calculation is. It is usually denoted in the form X/Y where X refers to how accurately the energy (or property) is calculated within the specific basis set being used, and Y refers to the basis set used (&lt;em&gt;i.e.&lt;/em&gt; how the wavefunction is modeled). Here are some examples:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{lcc c}&#xA; &amp;amp; \textrm{Accuracy within basis set used} &amp;amp; &amp;amp;\textrm{Basis set used}\\&#xA;\hline&#xA;\textrm{B3LYP/6-31G(2df,p)} &amp;amp;\textrm{B3LYP} &amp;amp;&amp;amp; \textrm{6-31G(2df,p)}\\&#xA;\textrm{CCSD(T)/cc-pVDZ} &amp;amp; \textrm{CCSD(T)} &amp;amp; &amp;amp;\textrm{cc-pVDZ}\\&#xA;\textrm{FCI/STO-3G} &amp;amp; \textrm{FCI} &amp;amp; &amp;amp;\textrm{STO-3G} \\&#xA;\textrm{MP2/def2-SVP } &amp;amp; \textrm{MP2} &amp;amp;&amp;amp; \textrm{def2-SVP}\\&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Warning:&lt;/strong&gt; In this terminology, even if the &amp;quot;level of theory&amp;quot; is exact (&lt;em&gt;i.e.&lt;/em&gt; &lt;strong&gt;FCI/CBS&lt;/strong&gt; or &amp;quot;Full Configuration Interaction&amp;quot; in a &amp;quot;Complete Basis Set&amp;quot;), the energy or property being calculated is still not necessarily exact, because it does not make clear the level of treatment of relativistic, beyond-Born-Oppenheimer, hyperfine, electro-weak, and other effects. Within this notion of &amp;quot;level of theory&amp;quot;, all that &amp;quot;exact&amp;quot; really means, is that the Schrödinger equation is being solved to full numerical convergence &lt;em&gt;for the specific Hamiltonian being used&lt;/em&gt; (which could be non-relativistic, ignoring nuclear-electron correlation, or approximate in any of a number of different ways).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-10-25T17:54:20.963" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3622" PostTypeId="2" ParentId="3614" CreationDate="2020-10-25T18:40:58.490" Score="4" Body="&lt;p&gt;The &lt;em&gt;ab initio&lt;/em&gt; calculation of hyperfine properties of molecules has been done, for example by Jeremy Hutson's group in &lt;a href=&quot;https://arxiv.org/abs/0807.1907&quot; rel=&quot;nofollow noreferrer&quot;&gt;this work&lt;/a&gt;, &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.96.042506&quot; rel=&quot;nofollow noreferrer&quot;&gt;this work&lt;/a&gt;, and &lt;a href=&quot;https://arxiv.org/abs/0810.4709&quot; rel=&quot;nofollow noreferrer&quot;&gt;this work&lt;/a&gt;. Table I in the last of those papers, and Tables I, II, III, and IV of the first of those papers, all show that high accuracy &lt;em&gt;ab initio&lt;/em&gt; methods are not even necessary, as B3LYP/QZ4P &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3621/5&quot;&gt;level of theory&lt;/a&gt; reproduces experimental hyperfine properties almost exactly.&lt;/p&gt;&#xA;&lt;p&gt;All calculations in those three papers use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Amsterdam_Density_Functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;ADF&lt;/a&gt; software the calculate all hyperfine properties, except for the rotational &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; factor which is calculated using the &lt;a href=&quot;https://en.wikipedia.org/wiki/Dalton_(program)&quot; rel=&quot;nofollow noreferrer&quot;&gt;DALTON&lt;/a&gt; software. The manuals for these programs, will say more about what precisely they are doing when you calculate these hyperfine properties.&lt;/p&gt;&#xA;&lt;p&gt;One way that you can obtain the molecular magnetic moment of a molecule is by using this definition of the magnetic moment:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\mathbf{m} \equiv -\hat{\mathbf{x}}\frac{\partial E}{\partial B_x} -\hat{\mathbf{y}}\frac{\partial E}{\partial B_y} -\hat{\mathbf{z}}\frac{\partial E}{\partial B_z}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So as long as you have a sub-routine that can calculate the energy of a molecule in the presence of a magnetic field (&lt;em&gt;i.e.&lt;/em&gt; a typical &lt;em&gt;ab initio&lt;/em&gt; calculation with the Hamiltonian containing the extra term &lt;span class=&quot;math-container&quot;&gt;$\hat{H}_B$&lt;/span&gt;), you can get the magnetic moment.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-10-25T18:40:58.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3623" PostTypeId="2" ParentId="3592" CreationDate="2020-10-25T18:52:05.620" Score="7" Body="&lt;p&gt;After some testing, I've found that the discrepancy isn't from pseudopotentials, number of atoms in the unit cell, or any other of your calculation parameters. I tested a few things like k-point mesh, energy cutoff, and swapping pseudopotentials. I also found you could sometimes converge to a non-magnetic ground state with certain combinations unless you set the starting magnetization to a higher value than the 0.1 you use in your calculation (0.4 worked). I also reduced the number of bands in your calculation input file. Is there any reason you need so many in a system with 16 electrons? 1.3 * (1/2 # of electrons) usually works fine. At most I've ever set is # bands = # electrons.&lt;/p&gt;&#xA;&lt;p&gt;First, pseudopotentials. Your reference calculation uses a LOW accuracy ultrasoft pseudopotential, from PSLibrary 1.0.0. The target energy cutoff is around 45 Ry. Your calculation uses PAW, also from PSLibrary (but the older, more recommended version from the SSSP library), and is the higher-accuracy version with larger cutoff (typically over 75-80 Ry). This shouldn't really explain the large discrepancy in DOS in itself, unless something was seriously wrong with the pseudopotential.&lt;/p&gt;&#xA;&lt;p&gt;Next, the unit cell. You used the primitive BCC cell, while the reference uses the conventional cell. QE uses symmetry to reduce the computational workload, and these two approaches should be completely equivalent for a ferromagnetic system where you only need one type of atom.&lt;/p&gt;&#xA;&lt;p&gt;I did some quick test calculations on my laptop. The issue comes from the nscf calculation in the reference. There is likely something unconverged in the reference calculation you used. From my replication test, the nscf Fermi energy difference vs. the scf calculation, as well as the cell pressure of the final vc-relax verification scf step being larger than the minimum converged value in the final bfgs step, both indicate that the calculations are possibly not converged with respect to k-points and/or energy cutoff.&lt;/p&gt;&#xA;&lt;p&gt;You can see in this plot, the weird DOS comes up after the reference's nscf calculation. Your scf+nscf calculation is in agreement with the reference's scf calculation. I'm not sure why the plot on that website seems to look more like the scf result rather than the nscf, but I ran the input files directly from how they were provided on that blog post.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SHdUV.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SHdUV.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The lesson: don't trust a calculation just because it's been posted online in a tutorial. I think it's just for instruction, not rigorously tested for convergence and possible issues stemming from that.&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2020-10-25T19:03:10.767" LastActivityDate="2020-10-25T19:03:10.767" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3624" PostTypeId="1" CreationDate="2020-10-25T20:04:03.540" Score="7" ViewCount="115" Body="&lt;p&gt;In Torquato's book &amp;quot;&lt;a href=&quot;https://link.springer.com/book/10.1007/978-1-4757-6355-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Random Heterogeneous Materials&lt;/a&gt;&amp;quot;, he has written:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{p}{\rho kT} = 1+2^{d-1}\eta g_2 (D^{+})\tag{1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$g_2(D^+)$&lt;/span&gt; is the contact value from the right-side of the radial distribution function, and &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; is a dimensionless reduced density, where &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; is the dimension, &lt;span class=&quot;math-container&quot;&gt;$\eta = \rho v(D)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$v(D)$&lt;/span&gt; is the volume of a cylinder with radius &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;After a couple lines, he states that for hard spheres, via the Ornstein-Zernike equation, we can rewrite the above equation in terms of the direct correlation function &lt;span class=&quot;math-container&quot;&gt;$c(r)$&lt;/span&gt; as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{p}{\rho kT} = 1+2^{d-1}\eta [c(D^+)-c(D^-)]\tag{2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How does he reach this conclusion?&lt;/p&gt;&#xA;&lt;p&gt;Ornstein-Zernike states:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$h(r_{12}) = c(r_{12}) + \rho \int d\mathbf{r}_3 c(r_{13})h(r_{32})\tag{3}$$&lt;/span&gt;&#xA;which after a Fourier transform becomes, where &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; is the position of the particle &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$r_{ij}$&lt;/span&gt; is the displacement vector &lt;span class=&quot;math-container&quot;&gt;$r_i-r_j$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\hat{C} (\mathbf{k}) = \frac{\hat{H}(\mathbf{k})}{1+\rho \hat{H}(\mathbf{k})}\tag{4}$$&lt;/span&gt;&#xA;where, &lt;span class=&quot;math-container&quot;&gt;$\hat{C} = \mathcal{F}[c], \hat{H} = \mathcal{F} [h]$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\mathcal{F}$&lt;/span&gt; is the Fourier transform.&#xA;However, I don't see how to simplify this to the second equation he has. I would appreciate any advice you have.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-09-21T22:40:24.870" LastActivityDate="2021-09-21T22:40:24.870" Title="Deriving relations for a hard sphere phase diagram" Tags="|mathematical-modeling|statistical-thermodynamics|derivations|radial-distribution-function|correlation-functions|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-28T14:53:40.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="3625" PostTypeId="2" ParentId="3601" CreationDate="2020-10-25T22:29:36.110" Score="2" Body="&lt;p&gt;To study system on disequilibrium, just apply the wanted conditions and run the calculations under such conditions. For example, &lt;a href=&quot;https://uspex-team.org/en/oganov/about&quot; rel=&quot;nofollow noreferrer&quot;&gt;Prof. Oganov&lt;/a&gt; (developer of &lt;a href=&quot;https://uspex-team.org/en/uspex/overview&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt; software) has very interesting studies about NaCl at high pressures, methane on Neptune (&lt;a href=&quot;https://uspex-team.org/static/file/CH4-JCP-2010.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;pdf&lt;/a&gt;) and other materials under extreme conditions, all in disequilibrium conditions.&lt;/p&gt;&#xA;&lt;p&gt;Particularly, one of my research lines is rational drug design. One of the methodology I use is to study the interactions of small molecules with proteins. In this case, I study, for example, the electronic properties in equilibrium (isolated molecule) and after interacting with the protein (out of equilibrium).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-10-25T22:29:36.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3626" PostTypeId="2" ParentId="3596" CreationDate="2020-10-25T22:47:19.467" Score="3" Body="&lt;p&gt;The electronic band structure is a concept for periodic system. Heterostructures are not periodic system (in the direction of heterostructure grow). What is done is an approximation where the bulk's band of each bulk system is combined using the band off-sets.&lt;/p&gt;&#xA;&lt;p&gt;Some reference about how to calculate band off-sets are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Theoretical calculations of heterojunction discontinuities in the Si/Ge systems. Chris G. Van de Walle et al., PHYSICAL REVIEW B 34, 5621 (1986)&lt;/li&gt;&#xA;&lt;li&gt;First-principles calculation of the band offset at BaO/BaTiO3 and SrO/SrTiO3 interfaces. J. Junquera et al., PHYSICAL REVIEW B 67, 155327 (2003)&lt;/li&gt;&#xA;&lt;li&gt;Band alignment at metal/ferroelectric interfaces: Insights and artifacts from first principles. M. Stengel, et al., PHYSICAL REVIEW B 83, 235112 (2011)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This is widely used studying semiconductor lasers, for example.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-10-25T22:47:19.467" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3627" PostTypeId="1" AcceptedAnswerId="3647" CreationDate="2020-10-26T06:19:17.740" Score="8" ViewCount="189" Body="&lt;p&gt;I am reading a &lt;a href=&quot;https://books.google.ca/books?hl=en&amp;amp;lr=&amp;amp;id=eUgWDAAAQBAJ&amp;amp;oi=fnd&amp;amp;pg=PR7&amp;amp;dq=relativistic+many-body+theory+Ingvar&amp;amp;ots=ZVHfhrCegD&amp;amp;sig=-lvlCZKiHicm9zdNBmn7OYOYNq4&amp;amp;redir_esc=y#v=onepage&amp;amp;q=relativistic%20many-body%20theory%20Ingvar&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;textbook&lt;/a&gt; on many-electron theory, which gives a Bloch equation in its generalized form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;[\Omega,H_0]P=Q(V\Omega-\Omega V_{eff})P,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; denotes the projection from exact state to a model state:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;P\mid \psi^{(\alpha)}\rangle=\mid \psi_0^{(\alpha)}\rangle,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; denotes a mapping from the model state to the exact state:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;\Omega\mid \psi_0^{(\alpha)}\rangle=\mid \psi^{(\alpha)}\rangle,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$Q=1-P$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The textbook I use has an ambiguous derivation of the Bloch equation with many steps skipped. I would appreciation if someone could explain to me how it is derived.&lt;/p&gt;&#xA;&lt;p&gt;It's eq. 55 on pg 21 of the textbook.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2020-10-26T22:04:27.977" LastActivityDate="2020-11-03T03:41:15.467" Title="How is the Bloch equation derived?" Tags="|electronic-structure|derivations|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3628" PostTypeId="1" AcceptedAnswerId="6568" CreationDate="2020-10-26T06:53:19.297" Score="11" ViewCount="143" Body="&lt;p&gt;When doing molecular dynamics simulations, there are countless sources of error (i.e. approximations and numerics).&lt;/p&gt;&#xA;&lt;p&gt;Molecular dynamics can be used to determine intrinsic thermal properties such as Melting Point/Freezing Point/Boiling Point. What tools do give me a quantified error on these properties, and what is the underlying thechnique to quantify all these different error terms?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2021-08-14T17:52:16.050" LastActivityDate="2021-08-15T06:37:34.827" Title="How can I quantify the uncertainty of thermal molecule properties in molecular dynamics simulations?" Tags="|molecular-dynamics|physical-properties-of-materials|thermal|uncertainty-analysis|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3629" PostTypeId="1" CreationDate="2020-10-26T07:00:42.843" Score="8" ViewCount="83" Body="&lt;p&gt;There are a number of molecules which no human should ever have to taste for safety reasons. Still, it could be interesting to know how it interacts with the taste buds. Applications could also include knowing how much to dilute or mix in aroma to medication in the pharmaceutical industry.&lt;/p&gt;&#xA;&lt;p&gt;What methods are there to determine the taste of a compound without putting a human in danger?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2021-01-22T20:56:45.103" LastActivityDate="2021-04-26T15:34:30.470" Title="What methods are there to computationally determine the taste of a molecule?" Tags="|reference-request|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3630" PostTypeId="1" AcceptedAnswerId="6584" CreationDate="2020-10-26T08:23:18.470" Score="12" ViewCount="178" Body="&lt;p&gt;I can imagine one aspect of flammability (the ability of a substance to ignite on fire) to include calculating the kinetics and thermodynamics of the reaction of the system with oxygen. This is not generalizable though, since in some systems (e.g. alkali metals) there is no need for oxygen in its pure form for the system to catch on fire.&#xA;What is the &amp;quot;general&amp;quot; way to determine flammability?&lt;/p&gt;&#xA;" OwnerUserId="108" LastEditorUserId="5" LastEditDate="2021-08-18T13:05:02.960" LastActivityDate="2021-08-18T14:41:46.100" Title="How can one computationally determine the flammability of a molecular system?" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|physical-properties-of-materials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3631" PostTypeId="1" CreationDate="2020-10-26T11:09:35.627" Score="7" ViewCount="1014" Body="&lt;p&gt;I am looking for any software, or scientific works, or search phrase in the field of simulating graphic modeling of squeezing objects. I would like to simulate packing very oddly shaped soft elastic objects in a larger rectangular 2-D container. I am not interested in finding optimal packing solution. I am interested in modeling the squeezing of the shapes which depends on material properties and applied force. The objects are made of rubber or clay substances. Object shapes may be distorted depending on the properties of the substance and applied force.&lt;/p&gt;&#xA;" OwnerUserId="1464" LastEditorUserId="88" LastEditDate="2020-10-26T16:23:34.527" LastActivityDate="2020-10-26T16:23:34.527" Title="Computer simulation of squeezing flexible objects with force" Tags="|software|one-topic-per-answer|software-recommendations|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3632" PostTypeId="2" ParentId="3631" CreationDate="2020-10-26T12:33:31.053" Score="6" Body="&lt;h3&gt;COMSOL Multiphysics&lt;/h3&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.comsol.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;COMSOL Multiphysics&lt;/a&gt; software has a &lt;a href=&quot;https://www.comsol.com/products/specifications/structural-mechanics/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structural Mechanic&lt;/a&gt; module that can help you.&lt;/p&gt;&#xA;&lt;p&gt;It has a good interface to design your system (with CAD tools) and add the possibility to add the type of physics you need to solve. One of the main feature is that you can connect one type of physics, for example, mechanical study, with thermal study.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.comsol.com/products/specifications/all/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; you can find all the specifications.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-10-26T16:07:43.483" LastActivityDate="2020-10-26T16:07:43.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3633" PostTypeId="2" ParentId="2419" CreationDate="2020-10-26T13:47:57.990" Score="2" Body="&lt;p&gt;Two things are important for the computational speed for VASP users. The first thing is ENCUT, which is controlled by the INCAR file. For a quick calculation, you can pick up this value just by referring to the ENMAX values of your POTCAR file. The other thing is the k sampling, which is decided by KPOINTS file. For your system with 60 atoms, I guess your &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; are very large and hence you can use lesser points for your simulations. For convenience, you can utilize the &lt;a href=&quot;http://vaspkit.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASPKIT&lt;/a&gt; tool to automatically generate KPOINTS file with low/medium KP-resolved values for a quick calculation.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-10-26T13:47:57.990" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3634" PostTypeId="2" ParentId="3631" CreationDate="2020-10-26T14:13:37.920" Score="5" Body="&lt;h3&gt;Rhinocerous-3d&lt;/h3&gt;&#xA;&lt;p&gt;I agree with the COMSOL Multiphysics answer.&lt;/p&gt;&#xA;&lt;p&gt;In addition to that,&#xA;you can use &lt;a href=&quot;https://www.rhino3d.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rhinocerous-3d&lt;/a&gt; if simulating the scenario is the idea behind your question. But if you are just looking forward to visualize the effects, you can use &lt;a href=&quot;https://www.blender.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Blender&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Both of them have a lot of tutorials online.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-10-26T16:08:43.250" LastActivityDate="2020-10-26T16:08:43.250" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3635" PostTypeId="2" ParentId="3596" CreationDate="2020-10-26T15:17:06.560" Score="1" Body="&lt;p&gt;I think Camps gives a mostly correct answer for this.  I will say though, it may be possible in some cases to generate a band structure in the direction of the heterostructure by making a periodic bulk heterojunction.  By layering two materials with minimal (or large if intended) strain in a bulk system with bulk crystal structure, you may get some interesting effects.&lt;/p&gt;&#xA;&lt;p&gt;You may also see some effects in a 2D surface band structure, but I am unsure what you should expect there.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-10-26T15:17:06.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3636" PostTypeId="1" CreationDate="2020-10-26T17:39:11.063" Score="11" ViewCount="677" Body="&lt;p&gt;I have seen that in certain cases Hubbard-U correction is relevant yet I have seen a number of papers that have not used it. So, I want to know if there is any theoretical basis for finding this potential or is it just by using empirical data. Also, what are the situations in which I have to use Hubbard-U potential.&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2020-10-26T18:07:07.883" LastActivityDate="2020-11-12T01:30:51.393" Title="How to calculate the potential in Hubbard-U correction and when to apply it?" Tags="|density-functional-theory|model-hamiltonians|hubbard-model|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3637" PostTypeId="1" CreationDate="2020-10-26T17:43:25.893" Score="10" ViewCount="1149" Body="&lt;p&gt;In many cases especially when it comes catalysis (which is what I work in) the effect of solvent comes into effect. I have seen papers that takes into account water as solvent by adding a number of water molecules as a layer in over the 2D system. Is there any better but not so obvious method to do this in Quantum ESPRESSO. Also, is it possible to consider acidic or basic medium?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="671" LastEditDate="2020-11-06T19:23:28.740" LastActivityDate="2020-12-04T01:32:14.400" Title="How to apply solvent model in Quantum ESPRESSO?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3638" PostTypeId="1" CreationDate="2020-10-26T17:47:31.013" Score="10" ViewCount="1545" Body="&lt;p&gt;I have seen papers that take change in Gibbs Energy by just adding a 'eU' term where U is the potential applied. Is there any better way to do this in Quantum Espresso? And is the former way accurate enough?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2020-10-26T19:51:43.070" Title="How to model electric field in Quantum ESPRESSO?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3639" PostTypeId="1" CreationDate="2020-10-26T17:51:23.940" Score="6" ViewCount="225" Body="&lt;p&gt;Papers with DFT calculations that use VASP work with PAW pseudopotentials which are also available in PS Library. I assume they are different since VASP is commercial. Given that, how different are they in terms of accuracy?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="116" LastEditDate="2020-10-26T19:03:40.993" LastActivityDate="2020-10-28T15:45:23.007" Title="How better is PAW available in VASP when compared to that present in PS Library?" Tags="|software|vasp|pseudopotentials|gpaw|projector-augmented-wave|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3640" PostTypeId="1" CreationDate="2020-10-26T17:59:24.310" Score="6" ViewCount="62" Body="&lt;p&gt;An example would be that when we dope Nitrogen in graphene its conductivity decreases. This can be explained through other means. But can this be explained through the change in its band structure?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2020-11-29T01:49:06.247" LastActivityDate="2021-01-05T23:28:49.520" Title="How to understand effect of increase in band gap generated away from Fermi energy on conductivity?" Tags="|band-structure|physical-properties-of-materials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3642" PostTypeId="1" AcceptedAnswerId="3649" CreationDate="2020-10-26T18:12:34.650" Score="18" ViewCount="9375" Body="&lt;p&gt;I have been using 'nscf' for DOS calculation since it is faster and therefore possible to use a higher kpoints. But why is it faster? why not use it in the place of 'scf'?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2020-10-26T19:44:45.157" LastActivityDate="2022-02-13T21:52:27.033" Title="What is nscf calculation in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3643" PostTypeId="1" CreationDate="2020-10-26T18:22:55.213" Score="3" ViewCount="111" Body="&lt;p&gt;This might be very broad question. Since ML application in Matter Modelling is emerging field it would good to understand how it is applied and why it is useful.&lt;/p&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2020-10-26T21:41:30.333" Title="How to proceed with learning application of Machine Learning in material modelling?" Tags="|density-functional-theory|machine-learning|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3644" PostTypeId="2" ParentId="3642" CreationDate="2020-10-26T19:43:27.983" Score="20" Body="&lt;p&gt;NSCF stands for non-self-consistent field calculation and, as explicit by its name, the calculation is not performed in a self-consistent fashion as the SCF (self-consistent field) one. The latter performs the solution trying to minimize the density charge functional until a predetermined limit in the energy difference between two consecutive steps. The convergence against the k-points mesh should also be achieved. Therefore the SCF calculation should be performed first to ensures the minimum Khom-Sham energy state that should resemble the system's ground state.&lt;/p&gt;&#xA;&lt;p&gt;Calculations such as the Band structure, Density of States, and optical properties, in general, require a denser grid at the reciprocal space.  Thus the NSCF calculation should be performed after the SCF one, sampling the system to a denser mesh in the reciprocal space, allowing for the aforementioned calculations.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-10-26T19:43:27.983" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3645" PostTypeId="2" ParentId="3638" CreationDate="2020-10-26T19:51:43.070" Score="4" Body="&lt;p&gt;From the Quantum ESPRESSO &lt;a href=&quot;https://www.quantum-espresso.org/Doc/pw_user_guide/node10.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;website:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There are two different implementations of macroscopic electric fields in pw.x: via an external sawtooth potential (input variable tefield=.true.) and via the modern theory of polarizability (lelfield=.true.). The former is useful for surfaces, especially in conjunction with dipolar corrections (dipfield=.true.): see examples/dipole_example for an example of application. Electric fields via the modern theory of polarization are documented in example 10. The exact meaning of the related variables, for both cases, is explained in the general input documentation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I don't know if it is what are you looking for, but the tag &lt;em&gt;tefield&lt;/em&gt; should help you.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-10-26T19:51:43.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3646" PostTypeId="2" ParentId="3643" CreationDate="2020-10-26T21:41:30.333" Score="6" Body="&lt;p&gt;The term &amp;quot;Machine learning&amp;quot; is quite general. Let's look at the three main domains of it :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Supervised-Learning: In this method, you would need to train a neural network or a statistical learning algorithm on a labelled training set. Some examples of its application in DFT involve :&lt;/p&gt;&#xA;&lt;p&gt;i) &lt;a href=&quot;https://www.nature.com/articles/s41467-020-17265-7&quot; rel=&quot;noreferrer&quot;&gt;The development of accurate exchange and correlation functionals .&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;ii) &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adts.201800128&quot; rel=&quot;noreferrer&quot;&gt;Improving the speed and accuracy of DFT calculations&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;iii) &lt;a href=&quot;https://link.springer.com/article/10.1007/s10822-006-9042-6&quot; rel=&quot;noreferrer&quot;&gt;Prediction of reaction kinematics&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Unsupervised-Learning: This category mainly involves clustering, dimensionality reduction..etc. And you would be training using unlabeled data. Such methods are used for finding out hidden relations that may pre-exist in your data or may be brought about via a basis transformation. The set of techniques falling under this catogory are used mainly for the analysis of the data obtained via DFT. Some examples include :&lt;/p&gt;&#xA;&lt;p&gt;i) &lt;a href=&quot;https://pubs.rsc.org/lv/content/articlelanding/2012/an/c2an35378d/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;Raman-Spectra analysis&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;ii) &lt;a href=&quot;https://www.nature.com/articles/s41598-017-18931-5&quot; rel=&quot;noreferrer&quot;&gt;Accuracy improvement and finding the most probable functional&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Reinforcement Learning: In this method, you would find that the learning process depends on a scalar reward. You can imagine it being similar to the Monte-Carlo method with an associated reward. It does share a lot of statistical concepts with MC like markov states. This method is existant in literature but I'm not entirely familiar with its application to DFT.&lt;/p&gt;&#xA;&lt;p&gt;i) &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/ab94f2/meta&quot; rel=&quot;noreferrer&quot;&gt;reference&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You can also check this &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2515-7639/ab084b/meta&quot; rel=&quot;noreferrer&quot;&gt;review paper&lt;/a&gt; out too.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-26T21:41:30.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3647" PostTypeId="2" ParentId="3627" CreationDate="2020-10-27T02:54:21.397" Score="6" Body="&lt;p&gt;They start with the time-independent Schrödinger equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;H|\psi^\alpha\rangle  = E^\alpha |\psi^\alpha\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then they define &lt;span class=&quot;math-container&quot;&gt;$|\psi_0^\alpha\rangle$&lt;/span&gt; to be what they call a &amp;quot;model state&amp;quot;, which is an approximation to the true state &lt;span class=&quot;math-container&quot;&gt;$|\psi^\alpha\rangle$&lt;/span&gt; but more easily accessible, and is related to the true state by a Møller operator  &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt;, and to the true energy &lt;span class=&quot;math-container&quot;&gt;$E^\alpha$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$H_{\textrm{eff}}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;|\psi^\alpha\rangle \equiv \Omega |\psi_0^\alpha\rangle ~~~, ~~~ H_{\textrm{eff}}|\psi_0^\alpha\rangle\equiv E^\alpha |\psi_0^\alpha\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can multiply the second part of Eq 2 by &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; on both sides of the equation, then re-write it using the first part of Eq 2:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{2}&#xA;\tag{3}&#xA;\Omega H_{\textrm{eff}}|\psi_0^\alpha\rangle &amp;amp;= E^\alpha |\psi^\alpha\rangle.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Likewise we can simply substitute the first part of Eq 2 into Eq 1 and get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{3}&#xA;\tag{4}&#xA; H \Omega |\psi_0^\alpha\rangle &amp;amp;= E^\alpha |\psi^\alpha\rangle.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since the right-side of Eqs 3 and 4 are the same, we can equate the left sides too:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{3}&#xA;\tag{5}&#xA;\Omega H_{\textrm{eff}}|\psi_0^\alpha\rangle  &amp;amp;=  H \Omega |\psi_0^\alpha\rangle.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then they say that since Eq 5 applies for all model states (&lt;em&gt;i.e.&lt;/em&gt; all values of &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;) we can replace &lt;span class=&quot;math-container&quot;&gt;$|\psi_0^\alpha\rangle$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{3}&#xA;\tag{6}&#xA;\Omega H_{\textrm{eff}}P  &amp;amp;=  H \Omega P.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;By partitioning &lt;span class=&quot;math-container&quot;&gt;$H=H_0 + V$&lt;/span&gt; we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{3}&#xA;\tag{6}&#xA;\Omega H_{\textrm{eff}}P  &amp;amp;=  H_0 \Omega P + V \Omega P.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What happens next is not explained in the text, but they get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{3}&#xA;\tag{7}&#xA;H_{\textrm{eff}}  &amp;amp;=  PH_0  P + PV \Omega P.&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To get the last term, I would left-multiply all terms by &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, but something else must have happened for the two other terms to be the way they are. Anyway, they make the second term in Eq. 7 to be defined as &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; and remove the &lt;span class=&quot;math-container&quot;&gt;$H_{\textrm{eff}}$&lt;/span&gt; to get the equation at the beginning of your question. They cite [113,117,124] but with your Google Books link, I can't see pages 61 to 405 and it seems the bibliography is at the end (in those missing pages). Do you happen to know what [113,117,124] are?&lt;/p&gt;&#xA;&lt;p&gt;Anyway, they finally say that in the case where all model states have the same energy &lt;span class=&quot;math-container&quot;&gt;$E_0$&lt;/span&gt;, we get the original Bloch equation that they say was derived in the late 1950s by the French nuclear physicist &lt;em&gt;&lt;strong&gt;Claude Bloch&lt;/strong&gt;&lt;/em&gt;, (&lt;em&gt;not&lt;/em&gt; the much more famous Bloch equation first presented in 1948 by the Swiss-American physicist &lt;em&gt;&lt;strong&gt;Felix Bloch&lt;/strong&gt;&lt;/em&gt; and his PhD student Roald Wangsness):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{8}&#xA;\left(E_0 - H_0  \right)\Omega P = V \Omega P  - \Omega W.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; After a lot more searching I have found that the author of that book explained this same derivation in a lot more detail in &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0022-3700/7/18/010&quot; rel=&quot;nofollow noreferrer&quot;&gt;this 1974 paper&lt;/a&gt;. Pay attention to what he says about &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; not being &amp;quot;true&amp;quot; inverses of each other, and what happens when you combine them. It is also quite amazing that the notation is almost the same in the &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0029558258901160?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;original 1958 paper of Claude Bloch&lt;/a&gt;. The paper is in French, but it's not too hard to follow the equations (he shows quite a lot of steps!).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-03T03:41:15.467" LastActivityDate="2020-11-03T03:41:15.467" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3648" PostTypeId="1" CreationDate="2020-10-27T12:10:49.957" Score="6" ViewCount="633" Body="&lt;p&gt;I would like to build a supercell with vesta.&lt;/p&gt;&#xA;&lt;p&gt;As a starting point I have a unit cell with polarization, I used it as my first structure in Vesta.&lt;/p&gt;&#xA;&lt;p&gt;File -&amp;gt; New Structure -&amp;gt; Import&lt;/p&gt;&#xA;&lt;p&gt;The supercell should consist of two unit cells of the same type. The second unit cell should be shifted and rotated 90°. Thus i will get two domains with different polarization. I tried this with&lt;/p&gt;&#xA;&lt;p&gt;Phase -&amp;gt; Import&lt;/p&gt;&#xA;&lt;p&gt;I set the first element of the global coordinate system to the length of the unit cell to shift the second structure, I deleted all duplicated atoms. But how can I rotate the second structure and how can I merge these two to one supercell?&lt;/p&gt;&#xA;&lt;p&gt;Has somebody experiences with VESTA?&lt;/p&gt;&#xA;&lt;p&gt;Thanks a lot for any help.&lt;/p&gt;&#xA;" OwnerUserId="1469" LastEditorUserId="1469" LastEditDate="2020-10-28T08:06:15.507" LastActivityDate="2020-10-29T12:15:41.627" Title="Build VESTA supercell with two domains" Tags="|vesta|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3649" PostTypeId="2" ParentId="3642" CreationDate="2020-10-27T14:21:33.853" Score="16" Body="&lt;p&gt;The central goal of KS-DFT is solving Kohn-Sham equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H\psi_i(\vec{r})=\left( -\dfrac{\nabla^2}{2}+V_{ks}[\vec{r};\psi_i(\vec{r})] \right)\psi_i(\vec{r})=E_i\psi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the atomic unit has been adopted. Note that the Kohn-Sham equation is a nonlinear differential equation and hence we need to solve it self-consistently. The workflow can be summarized as the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/47YFq.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/47YFq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Once the self-consistent calculation is done then the converged charge density is obtained.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;With this converged charge density at the previous self-consistent run, you can always construct the KS Hamiltonian once again and diagonalize it to obtain eigenvalues along the assigned K path in reciprocal space or calculate the density of states on a denser uniform k mesh. Note that you just read the converged charge density to construct the Hamiltonian without any update for the charge density, that's the meaning of &lt;strong&gt;NSCF&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-10-28T12:34:00.683" LastActivityDate="2020-10-28T12:34:00.683" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3650" PostTypeId="1" AcceptedAnswerId="3651" CreationDate="2020-10-27T14:55:59.677" Score="11" ViewCount="731" Body="&lt;p&gt;If the GGA xc energy is defined as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[n] = \int n(\mathbf{r}) \varepsilon_{xc}[n(\mathbf{r}), \nabla n(\mathbf{r})]\ d\mathbf{r},&#xA;$$&lt;/span&gt;&#xA;the potential can be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{xc}[n] = \varepsilon_{xc} + n\frac{\partial \varepsilon_{xc}}{\partial n} - \nabla\cdot\left[n\frac{\partial \varepsilon_{xc}}{\partial \nabla n}\right].&#xA;$$&lt;/span&gt;&#xA;The third term (if I understand it correctly) requires the evaluation of a divergence term &lt;span class=&quot;math-container&quot;&gt;$\left(\nabla\cdot\right)$&lt;/span&gt; which (I think) needs the spatial information of the points in the grid.&lt;/p&gt;&#xA;&lt;p&gt;However, from LibXC &lt;a href=&quot;https://www.tddft.org/programs/libxc/manual/#gga&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt;, to calculate the GGA potential the user only needs to supply the density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and the density gradients &lt;span class=&quot;math-container&quot;&gt;$\nabla n$&lt;/span&gt;, without any further information on grid points.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;how to calculate the divergence term above if only &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\nabla n$&lt;/span&gt; are given?&lt;/strong&gt;&#xA;Or do I miss something?&lt;/p&gt;&#xA;" OwnerUserId="882" LastEditorUserId="85" LastEditDate="2022-02-23T10:30:30.697" LastActivityDate="2022-02-23T10:30:30.697" Title="How does libxc calculate the potential of GGA functionals?" Tags="|density-functional-theory|exchange-correlation|libxc|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3651" PostTypeId="2" ParentId="3650" CreationDate="2020-10-27T21:46:04.157" Score="12" Body="&lt;p&gt;Libxc does not compute the full potential. Instead, it provides necessary ingredients for &lt;em&gt;the code that calls Libxc&lt;/em&gt; to compute the potential. This strategy allows the library to work with a variety of codes employing different grid types.&lt;/p&gt;&#xA;&lt;p&gt;For example, a code for single atoms might compute the divergence term on a radial grid with finite differences. A plane wave code could compute the divergence term with Fourier Transforms. There are many possibilities, but the design of Libxc allows it to work in all of these circumstances. The only downside is that the client code has to do a bit of the work itself.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;For practical purposes—assuming the simplest case without spin polarization—it helps to recognize that Libxc recasts GGAs into the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[n] = \int n \, \epsilon(n, \sigma) \, d\mathbf{r},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\sigma=|\nabla n|^2$&lt;/span&gt;. The associated potential (valid for most boundary conditions) is then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;v_{xc} = \epsilon + n \frac{\partial \epsilon}{\partial n} - 2 \nabla \cdot \left(n \frac{\partial \epsilon}{\partial \sigma} \nabla n\right) .&#xA;$$&lt;/span&gt;&#xA;To compute the real space potential using Libxc:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;your code provides &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; at points in space;&lt;/li&gt;&#xA;&lt;li&gt;Libxc returns &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and the derivatives &lt;span class=&quot;math-container&quot;&gt;$\partial \epsilon / \partial n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\partial \epsilon / \partial \sigma$&lt;/span&gt;;&lt;/li&gt;&#xA;&lt;li&gt;your code assembles the potential, computing the divergence term in some suitable manner.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;There are a few other strategies worth knowing about too. For example, another form for the real space potential is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;v_{xc} = \epsilon + n \frac{\partial \epsilon}{\partial n} - 2 \left(\frac{\partial \epsilon}{\partial \sigma} + n \frac{\partial^2 \epsilon}{\partial n \partial \sigma}\right) \sigma - 2 n \frac{\partial^2 \epsilon}{\partial \sigma^2} \nabla n \cdot \nabla \sigma - 2n \frac{\partial \epsilon}{\partial \sigma} \nabla^2 n,&#xA;$$&lt;/span&gt;&#xA;which is obtained by expanding the divergence analytically. I have on rare occasions found this form useful (in a plane wave code for systems with vacuum), getting &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and its first and second derivatives from Libxc.&lt;/p&gt;&#xA;&lt;p&gt;Finally, as Susi Lehtola (who would know) points out, it's worth asking if you actually need the potential in real space. You might only need &lt;em&gt;integrals involving the real space potential&lt;/em&gt;, in which case you can avoid the divergence term with integration by parts.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2020-10-29T22:18:36.930" LastActivityDate="2020-10-29T22:18:36.930" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3652" PostTypeId="2" ParentId="3648" CreationDate="2020-10-28T08:06:31.480" Score="5" Body="&lt;p&gt;I want to rotate the second structure &lt;span class=&quot;math-container&quot;&gt;$\theta=90^{\circ}$&lt;/span&gt; about the x-axis. The rotation matrix is given as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$R_x(90^{\circ})=\begin{pmatrix}1&amp;amp;0&amp;amp;0\\0&amp;amp;0&amp;amp;-1\\0&amp;amp;1&amp;amp;0\end{pmatrix}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Start a new Vesta window:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;New Structure&lt;/code&gt;-&amp;gt; &lt;code&gt;Structure parameters&lt;/code&gt; -&amp;gt; &lt;code&gt;Import&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Import your first structure/origin unit cell. Maybe one have first to shift the cell, so that the main atom is placed in the origin (edit &lt;code&gt;Unit cell&lt;/code&gt;-&amp;gt; &lt;code&gt;Transform&lt;/code&gt; -&amp;gt;&lt;code&gt;Origin shift p&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Next add the second structure:&#xA;&lt;code&gt;Phase&lt;/code&gt; -&amp;gt; &lt;code&gt;Import&lt;/code&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;One have to shift the second structure, chose the second Phase, edit the &lt;code&gt;Global coordinate system&lt;/code&gt; for example x = length of unit cell.&lt;/li&gt;&#xA;&lt;li&gt;Go to &lt;code&gt;Unit cell&lt;/code&gt;, check if the second phase is chosen, go to &lt;code&gt;Transform&lt;/code&gt;, insert the rotation matrix (for example &lt;span class=&quot;math-container&quot;&gt;$R_x(90)$&lt;/span&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Structure parameters&lt;/code&gt; -&amp;gt; &lt;code&gt;Remove duplicate atoms&lt;/code&gt;. Since the periodic boundaries atoms were counted twice one can also lower the boundaries from &lt;span class=&quot;math-container&quot;&gt;$1 \to 0.99$&lt;/span&gt; or the more easy way just delete later the redundant atoms (on the intersecting plane) in your xyz-output file.&lt;/li&gt;&#xA;&lt;li&gt;Delete the bonds (&lt;code&gt;Ctrl - B&lt;/code&gt;-&amp;gt; klick on the bonds and &lt;code&gt;Delete&lt;/code&gt;) so that we just have the atom positions as the input for the supercell.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Now we have two unit cells with different polarization. We can save it and use is for further calculations as the basic for the supercell.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Qz7K2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Qz7K2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1469" LastEditorUserId="1469" LastEditDate="2020-10-29T12:15:41.627" LastActivityDate="2020-10-29T12:15:41.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3653" PostTypeId="1" CreationDate="2020-10-28T13:26:03.357" Score="10" ViewCount="247" Body="&lt;p&gt;The formation of the covalent bond is usually understood from the electron sharing, like explained &lt;a href=&quot;https://www.expii.com/t/covalent-bonding-biology-definition-role-10346&quot; rel=&quot;noreferrer&quot;&gt;by the following figure&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/a52P9.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a52P9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, this simple physical picture seemingly hinders many things. In quantum mechanics or chemistry, the electron is represented fully by the wavefunction.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Therefore, how can I understand the formation of the covalent bond from electron/wavefunction interaction?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have gained some initial ideas when two wavefunctions are touched, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Deformation;&lt;/li&gt;&#xA;&lt;li&gt;Electrostatic attraction;&lt;/li&gt;&#xA;&lt;li&gt;Exchange;&lt;/li&gt;&#xA;&lt;li&gt;Polarization;&lt;/li&gt;&#xA;&lt;li&gt;Charge transfer.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These processes/concepts play an important role when two wavefunctions interacted. (I'm sorry I can't find concrete references for these concepts or processes.) In these processes, the attraction interaction (bonding) will compete with the repulsion interaction (antibonding) to find the ground state.&lt;/p&gt;&#xA;&lt;p&gt;I post this question to look a full understanding of the formation of the covalent bond from electron wavefunction interaction.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-10-29T16:33:50.327" Title="How to understand the formation of covalent bond from the viewpoint of wavefunction interaction?" Tags="|quantum-chemistry|quantum-mechanics|valence-bond-theory|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3654" PostTypeId="2" ParentId="3639" CreationDate="2020-10-28T15:45:23.007" Score="3" Body="&lt;p&gt;This isn't a perfect comparison of what you asked, but I think it can help. I'll refer to PAW datasets as &amp;quot;pseudopotentials&amp;quot; here since that is how they are used in practice.&lt;/p&gt;&#xA;&lt;p&gt;According to this relatively recent &lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, when compared to all-electron calculations, the Standard Solid State Pseudopotential library (which has many PSLibrary pseudopotentials in it, though it is a mix of PAW, ultrasoft and norm-conserving ONCV from a few sources) is comparable in accuracy (delta gauge 0.5) to VASP PAW (delta gauge 0.6). When comparing only PSLibrary 1.0.0 PAW (which, if you read the documentation, was &amp;quot;updated&amp;quot; simply to improve the consistency of the pseudopotential generation approach, not necessarily make individual pseudopotentials more accurate), the delta gauge was slightly higher at 0.9. If you wanted to make an &amp;quot;optimal&amp;quot; set of PAW datasets from PSLibrary, using a mix of version 1.0.0 and older pseudopotentials (choosing the best from &lt;a href=&quot;https://materialscloud.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialscloud.org/&lt;/a&gt;) they would probably be comparable in accuracy vs. VASP, at least when using the delta gauge metric.&lt;/p&gt;&#xA;&lt;p&gt;There are also other things to consider, such as the specific subset of PAW (high or low accuracy), and the accuracy you get vs. the &amp;quot;hardness&amp;quot;, i.e. how low of an energy cutoff you can get away with. I don't think there's a thorough analysis of this, but while both commercial and non-commercial software have their pros and cons, I don't think you will necessarily have more accurate results from a commercial code.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-10-28T15:45:23.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3655" PostTypeId="2" ParentId="1774" CreationDate="2020-10-29T10:49:25.207" Score="5" Body="&lt;p&gt;There are several tricks to improve the prediction that your neural network or regressor/classifier makes :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;To select the appropriate features from the input space. Say if youre input space has around 100 features and you want to determine 10 features that affects youre output the most. This can be done by&lt;/p&gt;&#xA;&lt;p&gt;i) &lt;a href=&quot;https://en.wikipedia.org/wiki/Dimensionality_reduction&quot; rel=&quot;noreferrer&quot;&gt;dimensionality reduction&lt;/a&gt; via feature extraction: In this, you would be taking combinations of existing features so that it best represents your data.&lt;/p&gt;&#xA;&lt;p&gt;eg: &lt;a href=&quot;https://towardsdatascience.com/a-one-stop-shop-for-principal-component-analysis-5582fb7e0a9c&quot; rel=&quot;noreferrer&quot;&gt;Principle Component Analysis&lt;/a&gt;, &lt;a href=&quot;https://towardsdatascience.com/linear-discriminant-analysis-in-python-76b8b17817c2&quot; rel=&quot;noreferrer&quot;&gt;Linear Discriminant Analysis&lt;/a&gt; .. etc&lt;/p&gt;&#xA;&lt;p&gt;ii) dimensionality reduction via feature elimination: This is more simple in terms of implementation and the features do retain their physical interpretability. Here you would drop the least important features so as to keep the most important ones :&lt;/p&gt;&#xA;&lt;p&gt;eg: &lt;a href=&quot;https://www.statisticshowto.com/lasso-regression/&quot; rel=&quot;noreferrer&quot;&gt;Lasso Regression&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;To apply regularization: This involves constraining your weights to a specific range provided you know what that range is. This can also be done automatically by using a constraint parameter and tuning it via trial and error on your validation set.&lt;/p&gt;&#xA;&lt;p&gt;eg: &lt;a href=&quot;https://www.statisticshowto.com/ridge-regression/&quot; rel=&quot;noreferrer&quot;&gt;Ridge regression,&lt;/a&gt; &lt;a href=&quot;https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html&quot; rel=&quot;noreferrer&quot;&gt;Ridge classifier&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;To apply drop-out: Choosing to switch on/off certain nodes with a fixed probability will help in reducing overfitting.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;eg: &lt;a href=&quot;https://machinelearningmastery.com/dropout-for-regularizing-deep-neural-networks/&quot; rel=&quot;noreferrer&quot;&gt;dropout-regularization&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;And as an overall idea, the lack of generalization of you're neural network is mainly due to poor &lt;a href=&quot;https://towardsdatascience.com/hyperparameters-optimization-526348bb8e2d&quot; rel=&quot;noreferrer&quot;&gt;hyperparameter optimization&lt;/a&gt;. That's why for training and tuning the network, you would use the &lt;a href=&quot;https://towardsdatascience.com/train-validation-and-test-sets-72cb40cba9e7&quot; rel=&quot;noreferrer&quot;&gt;training&lt;/a&gt; and &lt;a href=&quot;https://towardsdatascience.com/train-validation-and-test-sets-72cb40cba9e7&quot; rel=&quot;noreferrer&quot;&gt;validation set&lt;/a&gt; respectively. After which the network is tested on the &lt;a href=&quot;https://towardsdatascience.com/train-validation-and-test-sets-72cb40cba9e7&quot; rel=&quot;noreferrer&quot;&gt;testing set.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope this gives an insight :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-10-29T10:49:25.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3656" PostTypeId="2" ParentId="3653" CreationDate="2020-10-29T16:33:50.327" Score="7" Body="&lt;p&gt;There is more than one way to answer this question well. I'll give one answer here.&lt;/p&gt;&#xA;&lt;p&gt;Let's treat the two atoms (that will form a covalent bond) as two localized election states (orbitals). The detailed shape isn't important. The Hamiltonian of this system could be written:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H =  V (n_{\uparrow,1} n_{\downarrow,1}+ n_{\uparrow,2} n_{\downarrow,2}) - t \sum \limits_{s=\pm1/2} (c^\dagger_{s,2} c_{s,1} + c^\dagger_{s,1} c_{s,2}) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$n_{s,i}$&lt;/span&gt; is the total number of electrons on site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; (0,1, or 2) and the &lt;span class=&quot;math-container&quot;&gt;$c^\dagger_{s,1} c_{s,2}$&lt;/span&gt; terms 'hop' an electron with spin &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; from site 1 to 2 (and vice versa).&lt;/p&gt;&#xA;&lt;p&gt;Basically here you have &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; representing an electron-electron repulsion (they don't want to be on the same site) and &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; representing a &lt;strong&gt;tunneling&lt;/strong&gt; between the two sites. This tunneling is roughly proportional to the &lt;em&gt;wavefunction overlap&lt;/em&gt; between the site 1 and 2:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ t \approx \int d^3r \psi_1 \psi_2 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Now&lt;/em&gt;, when the two atoms are far away, that overlap will be small and &lt;span class=&quot;math-container&quot;&gt;$t\to 0$&lt;/span&gt;. In this limit we just have two isolated atoms. If we put two electrons in the system, the ground state would have one on each site with any combination of spins.&lt;/p&gt;&#xA;&lt;p&gt;As you bring the two atoms closer together, the tunneling becomes finite and it breaks the degeneracy, lowering the energy of a pair of opposite aligned spins because they can tunnel back and forth and pick up a &lt;span class=&quot;math-container&quot;&gt;$-t^2/V$&lt;/span&gt; decrease in energy (from second order degenerate perturbation theory.&lt;/p&gt;&#xA;&lt;p&gt;This example is essentially the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hubbard_model&quot; rel=&quot;noreferrer&quot;&gt;Hubbard model.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-10-29T16:33:50.327" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3657" PostTypeId="1" AcceptedAnswerId="3659" CreationDate="2020-10-29T21:50:48.433" Score="20" ViewCount="4165" Body="&lt;p&gt;Negative frequencies &amp;quot;in general&amp;quot; mean the direction of displacement is reverse to that in positive frequencies.&lt;/p&gt;&#xA;&lt;p&gt;Does it mean two frequencies with opposite signs but the same magnitude give the same energy in the context of the energy-angular frequency relation?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \omega = \frac{\epsilon}{\bar{h}}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What does this mean for two phonons with frequencies with the same magnitude but opposite signs?&lt;/p&gt;&#xA;&lt;p&gt;(This question came to mind because the code &lt;code&gt;phonopy&lt;/code&gt; outputs DoS for negative frequencies as well.)&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-12-28T03:11:35.600" LastActivityDate="2021-04-04T05:06:32.777" Title="What do negative phonon frequencies signify?" Tags="|phonons|vibrations|phonopy|phonon-density-of-state|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3658" PostTypeId="1" CreationDate="2020-10-29T21:59:28.500" Score="14" ViewCount="248" Body="&lt;p&gt;The orbital magnetization in periodic solids has been nicely described by the so-called modern theory of magnetization [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0505518&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;,&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0512142&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;,&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0502340&quot; rel=&quot;nofollow noreferrer&quot;&gt;3&lt;/a&gt;,&lt;a href=&quot;https://arxiv.org/abs/0704.3824&quot; rel=&quot;nofollow noreferrer&quot;&gt;4&lt;/a&gt;].&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\mathcal{M}_{orb}  = -\frac{1}{2} \Im \sum_{n,\mathbf{k}} f_{n\mathbf{k}} w_{\mathbf{k}} \langle \partial_\mathbf{k} u_{n\mathbf{k}} | \times (\mathcal{H}_{\mathbf{k}}+\epsilon_{\mathbf{k}}-2\mu)|\partial_\mathbf{k} u_{n\mathbf{k}} \rangle. &#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f_{n\mathbf{k}}$&lt;/span&gt; is the Fermi occupation of band &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$w_{\mathbf{k}}$&lt;/span&gt; is the k-point weight. &lt;span class=&quot;math-container&quot;&gt;$u_{n\mathbf{k}}$&lt;/span&gt; is the cell periodic part of the Bloch function &lt;span class=&quot;math-container&quot;&gt;$\psi_{n\mathbf{k}}=e^{i\mathbf{k \cdot r}}u_{n\mathbf{k}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{H}_{\mathbf{k}}u_{n\mathbf{k}}=\epsilon_{\mathbf{k}}u_{n\mathbf{k}}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the chemical potential. &lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt; is cross product. &lt;br /&gt;&#xA;&lt;strong&gt;I'm wondering if we could calculate &lt;span class=&quot;math-container&quot;&gt;$\mathcal{M}_{orb}$&lt;/span&gt; in the following way (in atomic units):&lt;/strong&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\mathcal{M}_{orb} &amp;amp;= - \frac{1}{2} \sum_{n,\mathbf{k}} f_{n\mathbf{k}} w_{\mathbf{k}} \langle \psi_{n\mathbf{k}} | \mathbf{r} \times \mathbf{v} | \psi_{n\mathbf{k}} \rangle \tag{2}\\&#xA;&amp;amp;= - \frac{1}{2} \sum_{n,\mathbf{k}} f_{n\mathbf{k}} w_{\mathbf{k}} \langle u_{n\mathbf{k}} | \mathbf{r} \times \mathbf{v_k} | u_{n\mathbf{k}} \rangle \tag{3}\\&#xA;&amp;amp;= - \frac{1}{2} \sum_{n,\mathbf{k}} f_{n\mathbf{k}} w_{\mathbf{k}} \sum_m \langle u_{n\mathbf{k}} | \mathbf{r} |u_{m\mathbf{k}}\rangle \times \langle u_{m\mathbf{k}} |\mathbf{v_k} | u_{n\mathbf{k}} \rangle \tag{4}\\&#xA;&amp;amp;={\small - \frac{1}{2} \sum_{n,\mathbf{k}} f_{n\mathbf{k}} w_{\mathbf{k}} \left( \mathcal{A}_{nn}(\mathbf{k}) \times \partial_\mathbf{k} \epsilon_\mathbf{k} + \frac{i}{\hbar}\sum_{m} \mathcal{A}_{nm}(\mathbf{k}) \times \mathcal{A}_{mn}(\mathbf{k})(\epsilon_{m\mathbf{k}}-\epsilon_{n\mathbf{k}})  \right)}&#xA;\tag{5}&#xA;\end{align}&lt;/span&gt;&#xA;where I have used in Eq. (4) the completeness relation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sum_m |u_{mk}\rangle \langle u_{mk}|=1\tag{6},$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; running over all the states (which should be subjected to a convergence study for real calculations) and in Eq. (5) the relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$i\hbar \langle u_{m\mathbf{k}} |\mathbf{v_k} | u_{n\mathbf{k}} \rangle =\mathcal{A}_{mn}(\mathbf{k}) (\epsilon_{n\mathbf{k}}-\epsilon_{m\mathbf{k}})\tag{7}.$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\mathcal{A}_{mn}(\mathbf{k})=i \langle u_{m\mathbf{k}} |\nabla_\mathbf{k} | u_{n\mathbf{k}} \rangle$&lt;/span&gt;. So the calculation of the orbital magnetization is reduced to evaluate the matrix elements of the Berry connection and band gradient.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2022-01-13T00:33:02.527" LastActivityDate="2022-01-13T00:33:02.527" Title="Orbital magnetization in periodic solids" Tags="|density-functional-theory|magnetism|periodic-system|berry-phase|derivations|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3659" PostTypeId="2" ParentId="3657" CreationDate="2020-10-29T22:35:22.957" Score="25" Body="&lt;p&gt;Phonons are a measure of the curvature of the potential energy surface about a stationary point. In particular, the matrix of force constants is calculated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha,i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})=\frac{\partial^2 E}{\partial u_{p\alpha i}\partial u_{p^{\prime}\alpha^{\prime}i^{\prime}}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the potential energy surface in which the nuclei move, &lt;span class=&quot;math-container&quot;&gt;$u_{p\alpha i}$&lt;/span&gt; is the displacement of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (of all atoms in the basis), in Cartesian direction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;), and located in the cell within the supercell at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt;. This quantity is the second-order derivative of the energy in all possible directions, so it measures the curvature about the reference point. To obtain phonons, one transforms the matrix of force constants into the dynamical matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{q})=\frac{1}{N_p\sqrt{m_{\alpha}m_{\alpha^{\prime}}}}\sum_{\mathbf{R}_p,\mathbf{R}_{p^{\prime}}}D_{i\alpha;i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})e^{i\mathbf{q}\cdot(\mathbf{R}_p-\mathbf{R}_{p^{\prime}})},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N_p$&lt;/span&gt; is the number of cells in the supercell over which periodic boundary conditions are applied, and &lt;span class=&quot;math-container&quot;&gt;$m_{\alpha}$&lt;/span&gt; is the mass of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. Using standard mathematical language, these two matrices are essentially Hessians.&#xA;Diagonalizing the dynamical matrix gives eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\omega^2_{\mathbf{q}\nu}$&lt;/span&gt; and eigenvectors &lt;span class=&quot;math-container&quot;&gt;$v_{\mathbf{q}\nu;i\alpha}$&lt;/span&gt;. The key quantity for our discussion are the eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\omega^2_{\mathbf{q}\nu}$&lt;/span&gt; which can be:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Positive. Positive eigenvalues indicate a positive curvature of the potential energy surface, so the energy increases quadratically if you displace the atoms in the directions given by the associated eigenvector, and the eigenvalue magnitude tells you how &amp;quot;fast&amp;quot; the energy increases.&lt;/li&gt;&#xA;&lt;li&gt;Negative. Negative eigenvalues indicate a negative curvature of the potential energy surface, so the energy decreases quadratically if you displace the atoms in the directions given by the associated eigenvector, and the eigenvalue magnitude tells you how &amp;quot;fast&amp;quot; the energy decreases.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If you are performing calculations for a structure at a (local) minimum of the potential energy surface, then all eigenvalues will be positive (positive-definite Hessian). If you are performing calculations for a structure at a saddle point of the potential energy surface, then most eigenvalues will be positive, but those associated with the directions which lower the energy will be negative.&lt;/p&gt;&#xA;&lt;p&gt;Now we come to the key point: phonon frequencies are given by the &lt;em&gt;square root&lt;/em&gt; of the eigenvalues of the dynamical matrix. As these eigenvalues are either positive or negative, then phonon frequencies are either positive real numbers or purely &lt;em&gt;imaginary&lt;/em&gt; numbers. &lt;strong&gt;Phonon frequencies cannot be negative: they are either positive or imaginary.&lt;/strong&gt; Many codes output imaginary frequencies as &amp;quot;negative&amp;quot; numbers, but this is a convention that in principle assumes that the user knows that &amp;quot;negative&amp;quot; frequencies are really imaginary, but which I think has traditionally led to big confusions, particularly for new people in the field.&lt;/p&gt;&#xA;&lt;p&gt;Having clarified this, I will rephrase your question: what does it mean when two eigenvalues of the dynamical matrix, &lt;span class=&quot;math-container&quot;&gt;$\omega^2_{\mathbf{q}\nu}$&lt;/span&gt;, have the same magnitude but opposite sign?&#xA;In terms of phonon frequencies, the equivalent question would be: what does it mean that two phonon frequencies, &lt;span class=&quot;math-container&quot;&gt;$\omega_{\mathbf{q}\nu}$&lt;/span&gt;, have the same magnitude when one is real and one imaginary? In both cases, what that means is that the magnitude of the curvature of the potential energy surface is the same, but in one case the energy increases and in the other the energy decreases.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="1218" LastEditDate="2021-04-04T05:06:32.777" LastActivityDate="2021-04-04T05:06:32.777" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3660" PostTypeId="1" CreationDate="2020-10-30T00:58:18.290" Score="8" ViewCount="292" Body="&lt;p&gt;I have figured out a way to input a custom electric field in a .cube format, but I am not sure I am doing it in the proper way. Currently my file contains information for the magnitude of the electric field at every point, but I would expect that instead of one file, three should be read in with each file corresponding to the electric field components. Can someone please help me figure out which is the proper implementation?&lt;/p&gt;&#xA;&lt;p&gt;I have attached my input file and a portion of the E-field cube file.&lt;/p&gt;&#xA;&lt;p&gt;Input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;FORCE_EVAL&#xA;  METHOD QUICKSTEP&#xA;  &amp;amp;DFT&#xA;    &amp;amp;QS&#xA;        EPS_DEFAULT 1.0E-14&#xA;    &amp;amp;END QS&#xA;    &amp;amp;REAL_TIME_PROPAGATION&#xA;       MAX_ITER 10 &#xA;       MAT_EXP TAYLOR&#xA;       EPS_ITER 1.0E-12&#xA;       INITIAL_WFN SCF_WFN&#xA;       DELTA_PULSE_DIRECTION 0 0 1&#xA;    &amp;amp;END REAL_TIME_PROPAGATION&#xA;    &amp;amp;EFIELD&#xA;       INTENSITY 1.0E10&#xA;       POLARISATION 1 0 0&#xA;       WAVELENGTH [nm] 1000000&#xA;       ENVELOP CUSTOM&#xA;       &amp;amp;CUSTOM_ENV&#xA;         EFIELD_FILE_NAME Efield_10ang.cube&#xA;       &amp;amp;END CUSTOM_ENV&#xA;    &amp;amp;END EFIELD&#xA;    BASIS_SET_FILE_NAME ./BASIS_SET&#xA;    POTENTIAL_FILE_NAME ./POTENTIALS&#xA;    &amp;amp;MGRID&#xA;      CUTOFF 600&#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;SCF&#xA;      MAX_SCF 100&#xA;      EPS_SCF 1.0E-12&#xA;      SCF_GUESS RESTART &#xA;      &amp;amp;OT &#xA;        MINIMIZER DIIS&#xA;      &amp;amp;END OT&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;    &amp;amp;PRINT&#xA;      &amp;amp;EFIELD_CUBE&#xA;         ADD_LAST NUMERIC&#xA;      &amp;amp;END EFIELD_CUBE&#xA;      &amp;amp;AO_MATRICES&#xA;         ADD_LAST NUMERIC&#xA;         DENSITY .TRUE.&#xA;         CORE_HAMILTONIAN&#xA;         NDIGITS 30&#xA;      &amp;amp;END AO_MATRICES&#xA;    &amp;amp;END PRINT&#xA;    &amp;amp;POISSON&#xA;       POISSON_SOLVER  WAVELET&#xA;       PERIODIC NONE &#xA;       &amp;amp;WAVELET&#xA;         SCF_TYPE  100&#xA;       &amp;amp;END WAVELET&#xA;    &amp;amp;END POISSON&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;CELL&#xA;      ABC 30.0 30.0 30.0&#xA;      PERIODIC NONE&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;TOPOLOGY&#xA;      COORD_FILE_FORMAT XYZ&#xA;      COORD_FILE_NAME pyridine.xyz&#xA;      &amp;amp;CENTER_COORDINATES&#xA;      &amp;amp;END CENTER_COORDINATES&#xA;    &amp;amp;END TOPOLOGY&#xA;    &amp;amp;KIND H&#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q1&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND C &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND N &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q5&#xA;    &amp;amp;END KIND&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&amp;amp;GLOBAL&#xA;  PROJECT Pyridine&#xA;  RUN_TYPE ENERGY&#xA;  PRINT_LEVEL HIGH&#xA;&amp;amp;END GLOBAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Efield_10ang.cube file portion:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;11 0.000000 0.000000 0.000000&#xA;57   0.9945927169914764   0   0&#xA;57   0   0.9945927238394396   0&#xA;57   0   0   0.9945927238394396&#xA;6    0.000000   25.988706   30.628889   28.345892&#xA;6    0.000000   28.624866   30.628881   28.345892&#xA;6    0.000000   29.942925   28.345880   28.345892&#xA;6    0.000000   28.624855   26.062893   28.345892&#xA;6    0.000000   25.988694   26.062904   28.345892&#xA;7    0.000000   24.670634   28.345902   28.345892&#xA;1    0.000000   24.949649   32.428610   28.345892&#xA;1    0.000000   29.663935   32.428706   28.345892&#xA;1    0.000000   32.021150   28.345823   28.345892&#xA;1    0.000000   29.663911   24.263171   28.345892&#xA;1    0.000000   24.949627   24.263078   28.345892&#xA;64156942035.733894 74314885275.23355 78858558500.71252 72617231997.33998 60722897205.954254 55684113714.90756 &#xA;68577175936.8303 86457942116.51447 92015955011.45152 91486690262.97147 81350353880.25954 65006905355.54635 &#xA;48525242734.31002 43608183596.30585 38285826534.91427 36406667509.88023 35753459578.79435 33541376678.246166 &#xA;27425449449.5296 22684261780.8113 18102830197.073315 14300560407.661577 19645443175.050713 34368584401.54891 &#xA;45626581661.24721 43140917883.42243 38184290251.83974 42416516365.51176 46683485885.74924 42416516365.51176 etc.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1451" LastEditorUserId="5" LastEditDate="2020-11-29T02:25:27.043" LastActivityDate="2021-01-06T00:01:16.103" Title="Reading in E-field with CP2K" Tags="|density-functional-theory|cp2k|software-assistance|electric-field|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3661" PostTypeId="1" CreationDate="2020-10-30T05:19:48.743" Score="8" ViewCount="937" Body="&lt;p&gt;I am trying to run spin polarized DFT calculation on system Ti2FeSn.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nsMurm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nsMurm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am doing vc-relax calculation to relax the unit cell but having problem to converge total energy. Total magnetization is also sometimes increases and sometimes decreases on&#xA;each iteration step and final total magnetization is also getting converged to '0'. This system is supposed to be half metallic system with magnetic moment of 2 Bohr mag/cell (as per the reference &lt;a href=&quot;https://doi.org/10.1016/j.intermet.2013.01.005&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1016/j.intermet.2013.01.005&lt;/a&gt;). I am trying to run DFT calculation to see if I can converge to the same results.&lt;br /&gt;&#xA;I have also attached the pwscf input file which I am using for the calculation in Quantum Espresso:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                   title = 'Ti2FeSn' ,&#xA;             calculation = 'vc-relax' ,&#xA;                  outdir = '.' ,&#xA;              pseudo_dir = '.' ,&#xA;                  prefix = 'Ti2FeSn' ,&#xA;           etot_conv_thr = 1.0D-6 ,&#xA;           forc_conv_thr = 1.0D-6 ,&#xA;                 tstress = .true. ,&#xA;                 tprnfor = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                   ibrav = 2,&#xA;               celldm(1) = 10,&#xA;                     nat = 4,&#xA;                    ntyp = 3,&#xA;                 ecutwfc = 40 ,&#xA;                 ecutrho = 400 ,&#xA;             occupations = 'smearing' ,&#xA;                smearing = 'marzari-vanderbilt' ,&#xA;                 degauss = 0.01,&#xA;                   nspin = 2 ,&#xA; starting_magnetization(1) = 0.2,&#xA; starting_magnetization(2) = 0.4,&#xA; starting_magnetization(3) = 0.2,&#xA;          &#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Ti   55.84500  ti_pbe_v1.4.uspp.F.UPF &#xA;   Fe  118.71000  Fe.pbe-spn-kjpaw_psl.0.2.1.UPF &#xA;   Sn   47.86700  Sn_pbe_v1.uspp.F.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Ti      0.000000000    0.000000000    0.000000000    &#xA;   Ti      0.250000000    0.250000000    0.250000&#xA;   Fe      0.500000000    0.500000000    0.500000000    &#xA;   Sn     -0.250000000   -0.250000000   -0.250000000    &#xA;K_POINTS automatic &#xA;  6 6 6   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any suggestion on how can I resolve this issue and get same results as in the reference will be helpful.&lt;br /&gt;&#xA;Thanking you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-11-08T04:54:21.593" LastActivityDate="2020-11-08T04:54:21.593" Title="Spin polarized DFT calculation in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|band-structure|dos|nspin|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="3662" PostTypeId="1" CreationDate="2020-10-30T12:36:05.673" Score="13" ViewCount="670" Body="&lt;p&gt;I want to build amorphous &lt;span class=&quot;math-container&quot;&gt;$\ce{Al_2O_3}$&lt;/span&gt; with the AIMD (ab initio molecular dynamics) method implemented in VASP.&#xA;I'm thinking of this process in three steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Build initial supercell&lt;/li&gt;&#xA;&lt;li&gt;Melt&lt;/li&gt;&#xA;&lt;li&gt;Quench&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I have questions about all these steps, but here I will just address the first.&lt;/p&gt;&#xA;&lt;h2&gt;Supercell size&lt;/h2&gt;&#xA;&lt;p&gt;The conventional cell of &lt;span class=&quot;math-container&quot;&gt;$\ce{Al_2O_3}$&lt;/span&gt; (taken from &lt;a href=&quot;https://materialsproject.org/materials/mp-755483/#&quot; rel=&quot;nofollow noreferrer&quot;&gt;the materials project website&lt;/a&gt;) contains 15 atoms, as shown in the following figure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KuJYYm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KuJYYm.png&quot; alt=&quot;Al2O3 conventional cell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To do AIMD calculations, we must have enough atoms in the simulated cell. This means that I need to build a supercell. For the current system, is a &lt;span class=&quot;math-container&quot;&gt;$3 \times 3 \times 1$&lt;/span&gt; (135 atoms) supercell OK? To obtain a reasonable amorphous structure, &lt;strong&gt;how big should the melt supercell be?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-01-13T00:39:38.517" LastActivityDate="2022-01-13T00:39:38.517" Title="How to build amorphous Al2O3 using the AIMD method implemented in VASP?" Tags="|vasp|molecular-dynamics|amorphous-materials|aimd|" AnswerCount="0" CommentCount="9" ClosedDate="2023-11-08T00:21:25.667" ContentLicense="CC BY-SA 4.0" />
  <row Id="3663" PostTypeId="2" ParentId="2203" CreationDate="2020-10-30T14:54:18.440" Score="2" Body="&lt;p&gt;TLDR: The rate constant calculated by transition state theory depends on the standard-state (gas-phase: ideal gas at a partial pressure of 1 atm or any state concentration (1 cm&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt; molecule&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; or 1 mol L&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;), liquid-phase solutes as in an ideal solution of 1 mol L&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;) and all species (reactants and transition state) should be in that specific reference state. The introduction of concentration effects can be made with microkinetic models.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Now let me try to convince you of that. The rate law for a bimolecular elementary reaction &lt;span class=&quot;math-container&quot;&gt;$\mathrm{A} + \mathrm{B} \to \mathrm{C} + \mathrm{D}$&lt;/span&gt; is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{d[\mathrm{C}]}{dt} = k [\mathrm{A}] [\mathrm{B}] $$&lt;/span&gt;&#xA;and according to transition state theory the rate constant, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, at temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; can be calculated as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ k(T)  = \frac{k_\mathrm{B}T}{h}\frac{Q^\ddagger(T)}{Q^\mathrm{A}(T)Q^\mathrm{B}(T)} \exp[-V^\ddagger_\mathrm{MEP}/k_\mathrm{B}T]$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$k_\mathrm{B}$&lt;/span&gt; is the Boltzmann constant, &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; is the Planck constant, &lt;span class=&quot;math-container&quot;&gt;$Q^\ddagger(T)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Q^\mathrm{A}(T)$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$Q^\mathrm{B}(T)$&lt;/span&gt; are the partition functions of the transition state, reactant A and reactant B, respectively, and &lt;span class=&quot;math-container&quot;&gt;$V^\ddagger_\mathrm{MEP}$&lt;/span&gt; is the classical barrier along the minimum energy path. &lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Each partition function is a product of the translational partition function per unit volume, &lt;span class=&quot;math-container&quot;&gt;$\Phi_\mathrm{tr}(T)$&lt;/span&gt;, and the internal partition function.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ Q(T) = \Phi_\mathrm{tr}(T) Q_\mathrm{int}(T)$$&lt;/span&gt;&#xA;with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \Phi_\mathrm{tr}(T) = \left( \frac{2\pi m k_\mathrm{B}T}{h^2} \right)^{3/2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that the ratio between the translational partition functions per unit volume of transition state and reactants can be written as the partition function for the relative motion of the collision:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{\Phi_\mathrm{tr}^\ddagger(T)}{\Phi_\mathrm{tr}^\mathrm{A}(T)\Phi_\mathrm{tr}^\mathrm{B}(T)} = \left( \frac{h^2}{2\pi\mu k_\mathrm{B}T}\right)^{3/2}$$&lt;/span&gt;&#xA;with &lt;span class=&quot;math-container&quot;&gt;$\mu = \frac{m_\mathrm{A}m_\mathrm{B}}{m_\mathrm{A} + m_\mathrm{B}}$&lt;/span&gt;. This only makes sense if the partition functions are calculated at the same reference state, implicitly here the volume.&lt;/p&gt;&#xA;&lt;p&gt;So, when using the Eyring equation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ k(T) = \frac{k_\mathrm{B}T}{hc^\circ} \exp[-\Delta^\ddagger G^\circ/RT]$$&lt;/span&gt; the Gibbs free energies for the transition state and reactants must be calculated at the standard-state indicated in &lt;span class=&quot;math-container&quot;&gt;$c^\circ$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To include concentration effects of has to integrate the rate laws for all reactions of interest. There are several options of codes that do that given a set of chemical equations, rate constants and initial conditions (and other techinical stuff to solve the equations): Acuchem&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt;, Copasi&lt;span class=&quot;math-container&quot;&gt;$^4$&lt;/span&gt;, Pilgrim&lt;span class=&quot;math-container&quot;&gt;$^5$&lt;/span&gt;, and probably others.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;M. Besora, F. Maseras, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1372&quot; rel=&quot;nofollow noreferrer&quot;&gt;Microkinetic modeling in homogeneous catalysis&lt;/a&gt;. Wiley Interdiscip. Rev. Comput. Mol. Sci. 8, 1–13 (2018).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A. Fernández-Ramos, J. A. Miller, S. J. Klippenstein, D. G. Truhlar, &lt;a href=&quot;http://pubs.acs.org/doi/abs/10.1021/cr050205w&quot; rel=&quot;nofollow noreferrer&quot;&gt;Modeling the Kinetics of Bimolecular Reactions&lt;/a&gt;. Chem. Rev. 106, 4518–4584 (2006).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;W. Braun, J. T. Herron, D. K. Kahaner, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/epdf/10.1002/kin.550200107&quot; rel=&quot;nofollow noreferrer&quot;&gt;Acuchem: A computer program for modeling complex chemical reaction systems&lt;/a&gt;. Int. J. Chem. Kinet. 20, 51–62 (1988).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;S. Hoops, S. Sahle, R. Gauges, C. Lee, J. Pahle, N. Simus, M. Singhal, L. Xu, P. Mendes, U. Kummer, &lt;a href=&quot;https://academic.oup.com/bioinformatics/article/22/24/3067/208398&quot; rel=&quot;nofollow noreferrer&quot;&gt;COPASI--a COmplex PAthway SImulator&lt;/a&gt;. Bioinformatics. 22, 3067–74 (2006).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;D. Ferro-Costas, D. G. Truhlar, A. Fernández-Ramos, &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465520302149&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pilgrim: A thermal rate constant calculator and a chemical kinetics simulator&lt;/a&gt;. Comput. Phys. Commun. 256, 107457 (2020).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2020-10-30T14:54:18.440" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3664" PostTypeId="1" AcceptedAnswerId="6215" CreationDate="2020-10-31T04:24:11.460" Score="13" ViewCount="160" Body="&lt;p&gt;I know that in non-periodic codes such as Gaussian the fluorescence spectra of molecule can be calculated in the following manner.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Relax geometry&lt;/li&gt;&#xA;&lt;li&gt;TD-DFT to find excited state&lt;/li&gt;&#xA;&lt;li&gt;Relax excited state geometry&lt;/li&gt;&#xA;&lt;li&gt;TD-DFT again to find new excited state level&lt;/li&gt;&#xA;&lt;li&gt;Vertical emission is step 4 excited state to step 4 ground state&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Is this possible to do for bulk / nanoparticle materials in some analogous manner for photoemission spectra?  If so, what do we learn in the process?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-06-22T00:53:52.200" LastActivityDate="2021-06-22T08:52:25.573" Title="Photoemission Spectra of Solids" Tags="|density-functional-theory|spectroscopy|excited-states|photoluminescence|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3665" PostTypeId="1" AcceptedAnswerId="3667" CreationDate="2020-10-31T04:45:09.253" Score="12" ViewCount="920" Body="&lt;p&gt;I am looking for a software that is capable of converting some generic atomic format such as .xyz or POSCAR into a .stl format.  Ideally it would support automatic generation of bonds so that the model would be connected rather than just being floating balls for atoms.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-11-20T01:46:19.190" Title="3D Visualization of Molecule / Surface by 3D Model (.stl)" Tags="|software-recommendations|visualization-software|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3666" PostTypeId="1" AcceptedAnswerId="3683" CreationDate="2020-10-31T11:14:26.150" Score="10" ViewCount="593" Body="&lt;p&gt;Is there any script that can remove fake k-points from a &lt;code&gt;vasprun.xml&lt;/code&gt; file for HSE06 band structure calculation? Because removing it manually is a time-consuming task.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-03-31T13:17:37.367" LastActivityDate="2021-03-31T13:17:37.367" Title="How to remove the fake k-points from vasprun.xml file in the calculation of HSE06 band structure?" Tags="|density-functional-theory|vasp|band-structure|hse06|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3667" PostTypeId="2" ParentId="3665" CreationDate="2020-10-31T15:23:16.023" Score="12" Body="&lt;h2&gt;OpenBabel&lt;/h2&gt;&#xA;&lt;p&gt;This masterpiece of software can convert between a huge amount of different file formats.&lt;/p&gt;&#xA;&lt;p&gt;The mains site can be accessed &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In my Linux box running OpenBabel 3.0.0, the commands for reading and writing return the following:&lt;/p&gt;&#xA;&lt;p&gt;Exporting/writing formats (&lt;code&gt;obabel -L formats write&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;p&gt;(&lt;strong&gt;stl -- STL 3D-printing&lt;/strong&gt; format is in the list)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;acesin -- ACES input format&#xA;adf -- ADF cartesian input format&#xA;alc -- Alchemy format&#xA;ascii -- ASCII format&#xA;bgf -- MSI BGF format&#xA;box -- Dock 3.5 Box format&#xA;bs -- Ball and Stick format&#xA;c3d1 -- Chem3D Cartesian 1 format&#xA;c3d2 -- Chem3D Cartesian 2 format&#xA;cac -- CAChe MolStruct format&#xA;caccrt -- Cacao Cartesian format&#xA;cache -- CAChe MolStruct format&#xA;cacint -- Cacao Internal format&#xA;can -- Canonical SMILES format&#xA;cdjson -- ChemDoodle JSON&#xA;cdxml -- ChemDraw CDXML format&#xA;cht -- Chemtool format&#xA;cif -- Crystallographic Information File&#xA;ck -- ChemKin format&#xA;cml -- Chemical Markup Language&#xA;cmlr -- CML Reaction format&#xA;cof -- Culgi object file format&#xA;com -- Gaussian Input&#xA;confabreport -- Confab report format&#xA;CONFIG -- DL-POLY CONFIG&#xA;CONTCAR -- VASP format&#xA;CONTFF -- MDFF format&#xA;copy -- Copy raw text&#xA;crk2d -- Chemical Resource Kit diagram(2D)&#xA;crk3d -- Chemical Resource Kit 3D format&#xA;csr -- Accelrys/MSI Quanta CSR format&#xA;cssr -- CSD CSSR format&#xA;ct -- ChemDraw Connection Table format&#xA;cub -- Gaussian cube format&#xA;cube -- Gaussian cube format&#xA;dalmol -- DALTON input format&#xA;dmol -- DMol3 coordinates format&#xA;dx -- OpenDX cube format for APBS&#xA;ent -- Protein Data Bank format&#xA;exyz -- Extended XYZ cartesian coordinates format&#xA;fa -- FASTA format&#xA;fasta -- FASTA format&#xA;feat -- Feature format&#xA;fh -- Fenske-Hall Z-Matrix format&#xA;fhiaims -- FHIaims XYZ format&#xA;fix -- SMILES FIX format&#xA;fps -- FPS text fingerprint format (Dalke)&#xA;fpt -- Fingerprint format&#xA;fract -- Free Form Fractional format&#xA;fs -- Fastsearch format&#xA;fsa -- FASTA format&#xA;gamin -- GAMESS Input&#xA;gau -- Gaussian Input&#xA;gjc -- Gaussian Input&#xA;gjf -- Gaussian Input&#xA;gpr -- Ghemical format&#xA;gr96 -- GROMOS96 format&#xA;gro -- GRO format&#xA;gukin -- GAMESS-UK Input&#xA;gukout -- GAMESS-UK Output&#xA;gzmat -- Gaussian Z-Matrix Input&#xA;hin -- HyperChem HIN format&#xA;inchi -- InChI format&#xA;inchikey -- InChIKey&#xA;inp -- GAMESS Input&#xA;jin -- Jaguar input format&#xA;k -- Compare molecules using InChI&#xA;lmpdat -- The LAMMPS data format&#xA;lpmd -- LPMD format&#xA;mae -- Maestro format&#xA;maegz -- Maestro format&#xA;mcdl -- MCDL format&#xA;mcif -- Macromolecular Crystallographic Info&#xA;MDFF -- MDFF format&#xA;mdl -- MDL MOL format&#xA;ml2 -- Sybyl Mol2 format&#xA;mmcif -- Macromolecular Crystallographic Info&#xA;mmd -- MacroModel format&#xA;mmod -- MacroModel format&#xA;mna -- Multilevel Neighborhoods of Atoms (MNA)&#xA;mol -- MDL MOL format&#xA;mol2 -- Sybyl Mol2 format&#xA;mold -- Molden format&#xA;molden -- Molden format&#xA;molf -- Molden format&#xA;molreport -- Open Babel molecule report&#xA;mop -- MOPAC Cartesian format&#xA;mopcrt -- MOPAC Cartesian format&#xA;mopin -- MOPAC Internal&#xA;mp -- Molpro input format&#xA;mpc -- MOPAC Cartesian format&#xA;mpd -- MolPrint2D format&#xA;mpqcin -- MPQC simplified input format&#xA;mrv -- Chemical Markup Language&#xA;msms -- M.F. Sanner's MSMS input format&#xA;nul -- Outputs nothing&#xA;nw -- NWChem input format&#xA;orcainp -- ORCA input format&#xA;outmol -- DMol3 coordinates format&#xA;paint -- Painter format&#xA;pcjson -- PubChem JSON&#xA;pcm -- PCModel Format&#xA;pdb -- Protein Data Bank format&#xA;pdbqt -- AutoDock PDBQT format&#xA;png -- PNG 2D depiction&#xA;pointcloud -- Point cloud on VDW surface&#xA;POSCAR -- VASP format&#xA;POSFF -- MDFF format&#xA;pov -- POV-Ray input format&#xA;pqr -- PQR format&#xA;pqs -- Parallel Quantum Solutions format&#xA;qcin -- Q-Chem input format&#xA;report -- Open Babel report format&#xA;rinchi -- RInChI&#xA;rsmi -- Reaction SMILES format&#xA;rxn -- MDL RXN format&#xA;sd -- MDL MOL format&#xA;sdf -- MDL MOL format&#xA;smi -- SMILES format&#xA;smiles -- SMILES format&#xA;stl -- STL 3D-printing format&#xA;svg -- SVG 2D depiction&#xA;sy2 -- Sybyl Mol2 format&#xA;tdd -- Thermo format&#xA;text -- Read and write raw text&#xA;therm -- Thermo format&#xA;tmol -- TurboMole Coordinate format&#xA;txt -- Title format&#xA;txyz -- Tinker XYZ format&#xA;unixyz -- UniChem XYZ format&#xA;VASP -- VASP format&#xA;vmol -- ViewMol format&#xA;xed -- XED format&#xA;xyz -- XYZ cartesian coordinates format&#xA;yob -- YASARA.org YOB format&#xA;zin -- ZINDO input format&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Importing/reading formats (&lt;code&gt;obabel -L formats reads&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;abinit -- ABINIT Output Format&#xA;acesout -- ACES output format&#xA;acr -- ACR format&#xA;adfband -- ADF Band output format&#xA;adfdftb -- ADF DFTB output format&#xA;adfout -- ADF output format&#xA;alc -- Alchemy format&#xA;aoforce -- Turbomole AOFORCE output format&#xA;arc -- Accelrys/MSI Biosym/Insight II CAR format&#xA;axsf -- XCrySDen Structure Format&#xA;bgf -- MSI BGF format&#xA;box -- Dock 3.5 Box format&#xA;bs -- Ball and Stick format&#xA;c09out -- Crystal 09 output format&#xA;c3d1 -- Chem3D Cartesian 1 format&#xA;c3d2 -- Chem3D Cartesian 2 format&#xA;caccrt -- Cacao Cartesian format&#xA;can -- Canonical SMILES format&#xA;car -- Accelrys/MSI Biosym/Insight II CAR format&#xA;castep -- CASTEP format&#xA;ccc -- CCC format&#xA;cdjson -- ChemDoodle JSON&#xA;cdx -- ChemDraw binary format&#xA;cdxml -- ChemDraw CDXML format&#xA;cif -- Crystallographic Information File&#xA;ck -- ChemKin format&#xA;cml -- Chemical Markup Language&#xA;cmlr -- CML Reaction format&#xA;cof -- Culgi object file format&#xA;CONFIG -- DL-POLY CONFIG&#xA;CONTCAR -- VASP format&#xA;CONTFF -- MDFF format&#xA;crk2d -- Chemical Resource Kit diagram(2D)&#xA;crk3d -- Chemical Resource Kit 3D format&#xA;ct -- ChemDraw Connection Table format&#xA;cub -- Gaussian cube format&#xA;cube -- Gaussian cube format&#xA;dallog -- DALTON output format&#xA;dalmol -- DALTON input format&#xA;dat -- Generic Output file format&#xA;dmol -- DMol3 coordinates format&#xA;dx -- OpenDX cube format for APBS&#xA;ent -- Protein Data Bank format&#xA;exyz -- Extended XYZ cartesian coordinates format&#xA;fa -- FASTA format&#xA;fasta -- FASTA format&#xA;fch -- Gaussian formatted checkpoint file format&#xA;fchk -- Gaussian formatted checkpoint file format&#xA;fck -- Gaussian formatted checkpoint file format&#xA;feat -- Feature format&#xA;fhiaims -- FHIaims XYZ format&#xA;fract -- Free Form Fractional format&#xA;fs -- Fastsearch format&#xA;fsa -- FASTA format&#xA;g03 -- Gaussian Output&#xA;g09 -- Gaussian Output&#xA;g16 -- Gaussian Output&#xA;g92 -- Gaussian Output&#xA;g94 -- Gaussian Output&#xA;g98 -- Gaussian Output&#xA;gal -- Gaussian Output&#xA;gam -- GAMESS Output&#xA;gamess -- GAMESS Output&#xA;gamin -- GAMESS Input&#xA;gamout -- GAMESS Output&#xA;got -- GULP format&#xA;gpr -- Ghemical format&#xA;gro -- GRO format&#xA;gukin -- GAMESS-UK Input&#xA;gukout -- GAMESS-UK Output&#xA;gzmat -- Gaussian Z-Matrix Input&#xA;hin -- HyperChem HIN format&#xA;HISTORY -- DL-POLY HISTORY&#xA;inchi -- InChI format&#xA;inp -- GAMESS Input&#xA;ins -- ShelX format&#xA;jin -- Jaguar input format&#xA;jout -- Jaguar output format&#xA;log -- Generic Output file format&#xA;lpmd -- LPMD format&#xA;mae -- Maestro format&#xA;maegz -- Maestro format&#xA;mcdl -- MCDL format&#xA;mcif -- Macromolecular Crystallographic Info&#xA;MDFF -- MDFF format&#xA;mdl -- MDL MOL format&#xA;ml2 -- Sybyl Mol2 format&#xA;mmcif -- Macromolecular Crystallographic Info&#xA;mmd -- MacroModel format&#xA;mmod -- MacroModel format&#xA;mol -- MDL MOL format&#xA;mol2 -- Sybyl Mol2 format&#xA;mold -- Molden format&#xA;molden -- Molden format&#xA;molf -- Molden format&#xA;moo -- MOPAC Output format&#xA;mop -- MOPAC Cartesian format&#xA;mopcrt -- MOPAC Cartesian format&#xA;mopin -- MOPAC Internal&#xA;mopout -- MOPAC Output format&#xA;mpc -- MOPAC Cartesian format&#xA;mpo -- Molpro output format&#xA;mpqc -- MPQC output format&#xA;mrv -- Chemical Markup Language&#xA;msi -- Accelrys/MSI Cerius II MSI format&#xA;nwo -- NWChem output format&#xA;orca -- ORCA output format&#xA;out -- Generic Output file format&#xA;outmol -- DMol3 coordinates format&#xA;output -- Generic Output file format&#xA;pc -- PubChem format&#xA;pcjson -- PubChem JSON&#xA;pcm -- PCModel Format&#xA;pdb -- Protein Data Bank format&#xA;pdbqt -- AutoDock PDBQT format&#xA;png -- PNG 2D depiction&#xA;pos -- POS cartesian coordinates format&#xA;POSCAR -- VASP format&#xA;POSFF -- MDFF format&#xA;pqr -- PQR format&#xA;pqs -- Parallel Quantum Solutions format&#xA;prep -- Amber Prep format&#xA;pwscf -- PWscf format&#xA;qcout -- Q-Chem output format&#xA;res -- ShelX format&#xA;rsmi -- Reaction SMILES format&#xA;rxn -- MDL RXN format&#xA;sd -- MDL MOL format&#xA;sdf -- MDL MOL format&#xA;siesta -- SIESTA format&#xA;smi -- SMILES format&#xA;smiles -- SMILES format&#xA;smy -- SMILES format using Smiley parser&#xA;sy2 -- Sybyl Mol2 format&#xA;t41 -- ADF TAPE41 format&#xA;tdd -- Thermo format&#xA;text -- Read and write raw text&#xA;therm -- Thermo format&#xA;tmol -- TurboMole Coordinate format&#xA;txt -- Title format&#xA;txyz -- Tinker XYZ format&#xA;unixyz -- UniChem XYZ format&#xA;VASP -- VASP format&#xA;vmol -- ViewMol format&#xA;xml -- General XML format&#xA;xsf -- XCrySDen Structure Format&#xA;xtc -- XTC format&#xA;xyz -- XYZ cartesian coordinates format&#xA;yob -- YASARA.org YOB format&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-10-31T15:23:16.023" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3668" PostTypeId="1" CreationDate="2020-10-31T20:53:46.690" Score="18" ViewCount="750" Body="&lt;p&gt;The harmonic approximation gives a non-zero kinetic energy at 0 K for which Heisenberg's uncertainty principle is used as an explanation. A particle at 0 K couldn't be stationary because that would violate its wave-like nature.&lt;/p&gt;&#xA;&lt;p&gt;Then there is the talk of zero-point potential energy. By the virtue of its existence, a particle with a finite mass would hold some energy within itself irrespective of being or not being in motion.&lt;/p&gt;&#xA;&lt;p&gt;The first is easy to understand. The second, though, it would make sense only if the particle was in some field that exerts potential on it. Are there implications here that come from theories that a casually thermodynamics-educated person wouldn't comprehend?&lt;/p&gt;&#xA;&lt;p&gt;Also, am I right to assume that the term zero-point energy, when used in atomistic modeling literature, is used solely to mean the first kind described above?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-11-01T11:37:44.263" LastActivityDate="2020-11-03T15:58:31.307" Title="On the nature of zero-point energy (ZPE)" Tags="|temperature|zero-point-energy|harmonic-approximation|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3669" PostTypeId="2" ParentId="3665" CreationDate="2020-10-31T22:37:11.067" Score="6" Body="&lt;p&gt;If you have access to CrystalMaker, you can output .stl (and other 3D formats) with bonds retained. You can then pop it into Blender or PowerPoint or any other program to view the 3D structure. Mercury also has some 3D file output formats. For some examples, you can see my post &lt;a href=&quot;https://twitter.com/Andrew_S_Rosen/status/1283546841531985921&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. &lt;a href=&quot;https://www.samson-connect.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SAMSON&lt;/a&gt; now has an option to output 3D .obj files.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-11-20T01:46:19.190" LastActivityDate="2020-11-20T01:46:19.190" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3670" PostTypeId="2" ParentId="3668" CreationDate="2020-11-01T15:14:35.977" Score="15" Body="&lt;p&gt;In the Born-Oppenheimer approximation nuclei are assumed to behave as classical point-like particles. However, in reality the wave-particle duality also applies to them, and so the Schrödinger equation should also be solved for the nuclei &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; in the potentials &lt;span class=&quot;math-container&quot;&gt;$V^I({\bf R})$&lt;/span&gt; generated by the electrons.&lt;/p&gt;&#xA;&lt;p&gt;The harmonic approximation implies not using the full potential to solve the nuclear Schrödinger equation, but rather using a second-order Taylor approximation&#xA;&lt;span class=&quot;math-container&quot;&gt;$V^I({\bf R}) \approx V^I({\bf R}_0) + \nabla V^I({\bf R})_{{\bf R}={\bf R}_0} \cdot ({\bf R}-{\bf R}_0) + \frac 1 2 ({\bf R}-{\bf R}_0) \cdot \nabla\nabla V^I({\bf R})_{{\bf R}={\bf R}_0} \cdot ({\bf R}-{\bf R}_0) + \mathcal{O}(|({\bf R}-{\bf R}_0)|^3)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;around the minimum-energy geometry at &lt;span class=&quot;math-container&quot;&gt;${\bf R}={\bf R}_0$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\nabla V^I({\bf R})_{{\bf R}={\bf R}_0}={\bf 0}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The zero-point energy is simply the energy of the nuclear wave function's ground state. The ground state is stationary, since it is an eigenfunction of the Hamiltonian. However, as a quantum mechanical wave function, it naturally has both kinetic and potential energy.&lt;/p&gt;&#xA;&lt;p&gt;The concept of &amp;quot;motion&amp;quot; does not make sense within the generally accepted Copenhagen interpretation of quantum mechanics.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-11-01T15:14:35.977" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3671" PostTypeId="2" ParentId="3583" CreationDate="2020-11-01T21:28:20.287" Score="7" Body="&lt;p&gt;The canonical transition state theory expression for the thermal rate constant, with tunneling correction, is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ k(T) = \kappa(T) \frac{k_\mathrm{B}T}{hc^\circ}\exp [-\Delta^\ddagger G/RT]$$&lt;/span&gt;&#xA;which is just the Eyring equation with a tunneling correction &lt;span class=&quot;math-container&quot;&gt;$\kappa(T)$&lt;/span&gt;.&#xA;The Gibbs free energy of activation, &lt;span class=&quot;math-container&quot;&gt;$\Delta^\dagger G$&lt;/span&gt;, is calculated using the partition functions (translational, vibrational, and rotational) of the transition state and reactants. These depend on the masses of the atoms, so this is how the kinetic isotope effects are included.&lt;/p&gt;&#xA;&lt;p&gt;There is also tunneling. If we use the simple semiclassical Wigner correction&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \kappa^\mathrm{W}(T) = 1 + \frac{1}{24}|\hbar\omega^\ddagger/k_\mathrm{B}T|^2$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\omega^\ddagger$&lt;/span&gt; is the imaginary frequency of the transition state, we can see that an isotopic substitution would change the frequency and, consequently, the rate constant.&lt;/p&gt;&#xA;&lt;p&gt;As your question also mentions Density Functional Theory, I would like to point out that in the Born–Oppenheimer approximation the potential energy surface is independent of the nuclear masses, so all isotopic effects are handled as shown above if one uses transition state theory. Even if the DFT description of the PES is very wrong, I think, that overall trends for kinetic isotope effects would be OK.&lt;/p&gt;&#xA;&lt;p&gt;For some examples of transition state theory calculations of kinetic isotope effects, I recommend the following papers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;E. F. V. de Carvalho, G. D. Vicentini, T. V. Alves, O. Roberto-Neto, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.26092&quot; rel=&quot;noreferrer&quot;&gt;Variational transition state theory rate constants and H/D kinetic isotope effects for CH3 + CH3OCOH reactions.&lt;/a&gt; J. Comput. Chem. 41, 231–239 (2020).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;L. Simón-Carballido, T. V. Alves, A. Dybala-Defratyka, A. Fernández-Ramos, &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcb.5b09671&quot; rel=&quot;noreferrer&quot;&gt;Kinetic Isotope Effects in Multipath VTST: Application to a Hydrogen Abstraction Reaction.&lt;/a&gt; J. Phys. Chem. B. 120, 1911–1918 (2016).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2020-11-01T21:28:20.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3672" PostTypeId="1" AcceptedAnswerId="3705" CreationDate="2020-11-02T00:04:48.590" Score="11" ViewCount="249" Body="&lt;p&gt;The first software I used to run calculations was Gaussian09. When submitting a input, I used to see a pattern of resource usage where the allocated CPU quickly maxed out, remaining high most of the time, with not much disk activity.&lt;/p&gt;&#xA;&lt;p&gt;Later, when I started to use Gamess (US), I was a bit confused, because it didn't follow this resource usage pattern. Instead, I saw allocated CPU utilization bellow maximum for most of the time, with occasional spikes, and heavy disk usage for most of the time.&lt;/p&gt;&#xA;&lt;p&gt;To illustrate it, I ran a single point energy (SPE) calculation on a C20 molecule (the reference system benchmarked on the page @r2compchem pointed in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3572/243&quot;&gt;a answer&lt;/a&gt; to another question of mine), with the following input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! C20 | Single Point | B3LYP/6-31G(d)&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=N31 NGAUSS=6 NDFUNC=1 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=ENERGY ICHARG=0 MULT=1 DFTTYP=B3LYP $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM MWORDS=250 $&lt;/span&gt;END&#xA;&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;Title&#xA;C1&#xA;C     6.0  -2.56361   2.53552  -1.18910&#xA;C     6.0  -2.58167   1.21111  -0.56424&#xA;C     6.0  -2.71457   2.35598  -2.63472&#xA;C     6.0  -2.74378   0.21303  -1.62368&#xA;C     6.0  -2.82592   0.92060  -2.90331&#xA;C     6.0   0.45050   1.49084  -3.31626&#xA;C     6.0   0.61261   2.48891  -2.25682&#xA;C     6.0   0.43244   0.16642  -2.69140&#xA;C     6.0   0.69474   1.78135  -0.97719&#xA;C     6.0   0.58339   0.34597  -1.24577&#xA;C     6.0  -0.45654   2.18038  -0.16469&#xA;C     6.0  -1.25022   3.13457  -0.94217&#xA;C     6.0  -1.27943   0.99162   0.06888&#xA;C     6.0  -0.58944   3.32525  -2.23517&#xA;C     6.0  -0.63671  -0.14211  -0.59927&#xA;C     6.0  -1.49446   2.84406  -3.28123&#xA;C     6.0  -0.85174   1.71033  -3.94938&#xA;C     6.0  -1.67463   0.52156  -3.71581&#xA;C     6.0  -1.54173  -0.62330  -1.64533&#xA;C     6.0  -0.88096  -0.43262  -2.93833&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Logging resource usage, I got the following execution profile:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/frK13.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/frK13.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Some time after identifying this execution pattern for the first time, I learned there is a keyword you can use to control whether Gamess (US) precomputes and stores integrals on disk or if it just keeps recalculating them on the fly. The default value, .FALSE., precomputes and stores integrals on disk. If for the same system I set it to .TRUE. by hand, adding the line \$SCF DIRSCF=.TRUE. \$END to the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! C20 | Single Point | B3LYP/6-31G(d)&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=N31 NGAUSS=6 NDFUNC=1 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=ENERGY ICHARG=0 MULT=1 DFTTYP=B3LYP $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM MWORDS=250 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA;&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;Title&#xA;C1&#xA;C     6.0  -2.56361   2.53552  -1.18910&#xA;C     6.0  -2.58167   1.21111  -0.56424&#xA;C     6.0  -2.71457   2.35598  -2.63472&#xA;C     6.0  -2.74378   0.21303  -1.62368&#xA;C     6.0  -2.82592   0.92060  -2.90331&#xA;C     6.0   0.45050   1.49084  -3.31626&#xA;C     6.0   0.61261   2.48891  -2.25682&#xA;C     6.0   0.43244   0.16642  -2.69140&#xA;C     6.0   0.69474   1.78135  -0.97719&#xA;C     6.0   0.58339   0.34597  -1.24577&#xA;C     6.0  -0.45654   2.18038  -0.16469&#xA;C     6.0  -1.25022   3.13457  -0.94217&#xA;C     6.0  -1.27943   0.99162   0.06888&#xA;C     6.0  -0.58944   3.32525  -2.23517&#xA;C     6.0  -0.63671  -0.14211  -0.59927&#xA;C     6.0  -1.49446   2.84406  -3.28123&#xA;C     6.0  -0.85174   1.71033  -3.94938&#xA;C     6.0  -1.67463   0.52156  -3.71581&#xA;C     6.0  -1.54173  -0.62330  -1.64533&#xA;C     6.0  -0.88096  -0.43262  -2.93833&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now I get the following execution profile:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LQlXV.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LQlXV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That is just what I was used to before.&lt;/p&gt;&#xA;&lt;p&gt;Since when I first learned this, I always set DIRSCF to .TRUE., for the following reasons:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In my experience, the calculations run faster when the integrals are not precomputed and stored on disk. Notice in my example, the DIRSCF=.FALSE. version took about 5000s to finish, while the DIRSCF=.TRUE. took a little under 1000s;&lt;/li&gt;&#xA;&lt;li&gt;In my experience, the system keeps more responsive under heavy CPU load than with heavy disk read/write load;&lt;/li&gt;&#xA;&lt;li&gt;As a rule of thumb, I assume a device with moving parts is more subject to early failure on heavy loads. HDs have moving parts, while CPUs have not. So I think is wiser to load the CPU instead of disk, when I have a choice.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Said that, what puzzles me to this day is that, if Gamess (US) creators set the default value of DIRSCF to .FALSE., they probably had good reason to do so, and I just don't know why. Initially I assumed it was just some sort of space-speed trade-off, but then I noticed the stored version usually runs slower, and was left wondering.&lt;/p&gt;&#xA;&lt;p&gt;So, If someone more experienced here could explain what are the trade-offs involved in setting DIRSCF to either .TRUE. or the default .FALSE., and what are the situations where is appropriate to use each setting, I would be grateful.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-11-02T01:12:49.200" LastActivityDate="2020-11-06T04:47:05.213" Title="What are the trade-offs setting DIRSCF to either .TRUE. or .FALSE. (the default) in GAMESS (US)?" Tags="|software|computational-chemistry|quantum-chemistry|high-performance-computing|gamess|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3674" PostTypeId="1" CreationDate="2020-11-02T11:03:33.490" Score="16" ViewCount="1723" Body="&lt;p&gt;I hope you are doing well. I am new to VASP, and my project is &amp;quot;Optical properties of 2D materials on VASP&amp;quot; but I have no idea how to run a simple calculation with VASP. I will be very thankful if someone guides me.&#xA;Thank you so much.&lt;/p&gt;&#xA;" OwnerUserId="1384" LastEditorUserId="5" LastEditDate="2021-08-05T13:18:02.190" LastActivityDate="2022-06-24T04:37:55.500" Title="How to start with the optical properties of 2D materials with the VASP code?" Tags="|vasp|optical-properties|software-input-file-request|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3675" PostTypeId="2" ParentId="3674" CreationDate="2020-11-02T12:16:41.820" Score="12" Body="&lt;p&gt;The VASP manual is always the first resource to check, you can find it &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. As a beginner, following &amp;quot;Getting Started&amp;quot; should help you greatly, from how to install the code, some details of the background theory, and how to run simple calculations.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-11-02T12:16:41.820" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3676" PostTypeId="2" ParentId="365" CreationDate="2020-11-02T14:40:35.193" Score="12" Body="&lt;h1&gt;Common Lisp&lt;/h1&gt;&#xA;&lt;p&gt;Recently I watched a couple impressive talks by Christian Schafmeister, where he discusses how they actually built a full fledged &lt;a href=&quot;https://en.wikipedia.org/wiki/Common_Lisp&quot; rel=&quot;noreferrer&quot;&gt;Common Lisp&lt;/a&gt; implementation on top of LLVM, named &lt;a href=&quot;https://github.com/clasp-developers/clasp.git&quot; rel=&quot;noreferrer&quot;&gt;Clasp&lt;/a&gt;, targeted at molecular design:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=0rSMt1pAlbE&quot; rel=&quot;noreferrer&quot;&gt;Clasp: Common Lisp using LLVM and C++ for Designing Molecules&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=mbdXeRBbgDM&quot; rel=&quot;noreferrer&quot;&gt;2018 LLVM Developers’ Meeting: C. Schafmeister “Lessons Learned Implementing Common Lisp with LLVM”&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Common Lisp is a dynamic language almost as old as Fortran. Among the reasons to choose it, Schafmeister cites a stable standard, proper macros and unmatched energy efficiency when compared to other dynamic languages, as shown in this table[2]:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/e7Bf8.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e7Bf8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://dl.acm.org/doi/abs/10.5555/3323215.3323223&quot; rel=&quot;noreferrer&quot;&gt;Schafmeister, Christian A., and Alex Wood. “Clasp Common Lisp Implementation and Optimization.” Proceedings of the 11th European Lisp Symposium on European Lisp Symposium, European Lisp Scientific Activities Association, 2018, pp. 59–64.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://greenlab.di.uminho.pt/wp-content/uploads/2017/10/sleFinal.pdf&quot; rel=&quot;noreferrer&quot;&gt;Pereira, Rui, et al. “Energy Efficiency across Programming Languages: How Do Energy, Time, and Memory Relate?” Proceedings of the 10th ACM SIGPLAN International Conference on Software Language Engineering, Association for Computing Machinery, 2017, pp. 256–267. ACM Digital Library, doi:10.1145/3136014.3136031.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://dl.acm.org/doi/abs/10.5555/3005729.3005738&quot; rel=&quot;noreferrer&quot;&gt;Schafmeister, Christian E. “CANDO: A Compiled Programming Language for Computer-Aided Nanomaterial Design and Optimization Based on Clasp Common Lisp.” Proceedings of the 9th European Lisp Symposium on European Lisp Symposium, ELS2016, 2015, p. 9.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-11-02T16:00:46.553" LastActivityDate="2020-11-02T16:00:46.553" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3677" PostTypeId="2" ParentId="365" CreationDate="2020-11-02T18:54:47.633" Score="12" Body="&lt;h1&gt;Bash Scripting&lt;/h1&gt;&#xA;&lt;p&gt;I have used bash scripts to automate materials modelling workflows. You can use online resources to learn more about &lt;a href=&quot;https://www.tutorialspoint.com/unix/index.htm&quot; rel=&quot;noreferrer&quot;&gt;bash commands&lt;/a&gt; and &lt;a href=&quot;https://www.tutorialspoint.com/unix/shell_scripting.htm&quot; rel=&quot;noreferrer&quot;&gt;bash scripting&lt;/a&gt;. The idea is simple. If you have a repetitive and time-consuming task just write the terminal commands (usually run directly in the command line interface) on to a &amp;quot;file_name.sh&amp;quot; file and run it.&lt;/p&gt;&#xA;&lt;p&gt;An example of a bash script to extract pressure, energy values from a quantum ESPRESSO output file can be found &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3533/how-to-extract-the-pressure-energy-and-unit-cell-volume-from-quantum-espresso-o/3534#3534&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-11-02T18:54:47.633" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3678" PostTypeId="1" AcceptedAnswerId="3686" CreationDate="2020-11-02T21:05:20.080" Score="20" ViewCount="1014" Body="&lt;p&gt;I first saw the term &amp;quot;chemputer&amp;quot; when reading about the work of Neil Ostlund (who you may know as one of the authors of the famous book &amp;quot;Modern Quantum Chemistry&amp;quot;). Based on the description &lt;a href=&quot;http://www.hyper.com/AboutUs/CompanyHistory/tabid/385/Default.aspx&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, my understanding is that a chemputer is a computer specifically designed to do computational chemistry calculations (and for clarity, I will say that I wouldn't consider any quantum computer a chemputer since none of them have enough qubits to do any useful chemistry calculation).&lt;/p&gt;&#xA;&lt;p&gt;Last week the term &amp;quot;chemputer&amp;quot; arose again, along with the word ChemPU (analogous to CPU, GPU, and GPU) in the context of a paper published in Science a week ago, and discussed &lt;a href=&quot;https://www.cnbc.com/2020/10/24/how-a-digital-breakthrough-could-revolutionize-drug-industry.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. This time the &amp;quot;chemputer&amp;quot; is described as a &amp;quot;robotic chemist that can produce chemicals from XDL programs&amp;quot;. The group that published the Science paper has been using the word chemputer in this context &lt;a href=&quot;https://phys.org/news/2018-11-chemputer-app-controlled-revolution-drug-production.html&quot; rel=&quot;noreferrer&quot;&gt;since some years ago&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There is also the phrase &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_computer&quot; rel=&quot;noreferrer&quot;&gt;chemical computer&lt;/a&gt;&amp;quot; whcih is described in the preceding link as a computer where computations are performed by naturally occurring chemical reactions.&lt;/p&gt;&#xA;&lt;p&gt;I am curious to know if the word has been used in any way other than the above three ways. One may also pick one of the above three meanings of chemputer, and describe it in more detail in the &lt;a href=&quot;/questions/tagged/one-topic-per-answer&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;one-topic-per-answer&amp;#39;&quot; rel=&quot;tag&quot;&gt;one-topic-per-answer&lt;/a&gt; format. I am also curious to know if there's examples other than Neil Ostlund's one, of computers specifically made to do computational chemistry calculations (the first type of chemputer), but that seems different enough from my first question that it may better be asked separately.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-07-30T20:23:21.130" LastActivityDate="2021-07-30T20:23:21.130" Title="What is a chemputer?" Tags="|software|one-topic-per-answer|high-performance-computing|terminology|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3679" PostTypeId="2" ParentId="3674" CreationDate="2020-11-03T00:42:17.767" Score="13" Body="&lt;p&gt;Due to the enhanced coulomb interaction and the quantum confinement effect in the two-dimensional limit, the optical properties should be investigated with the GW+BSE method.&lt;/p&gt;&#xA;&lt;p&gt;The practical calculation flow is the following if you are considering using VASP&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Perform a ground state DFT or hybrid calculation.&lt;/li&gt;&#xA;&lt;li&gt;Based on previous converged charge density and wavefunction, increasing the number of unoccupied  orbitals to generate new charge density and wavefunction. (&lt;code&gt;# of atoms*[100-200]&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Preform a GW calculation (keeping orbitals fixed) and calculate the quasiparticle energies and screened   Coulomb kernel. (Keep the &lt;code&gt;Wxxx.tmp&lt;/code&gt; and &lt;code&gt;WFULLxxx.tmp&lt;/code&gt; files).&lt;/li&gt;&#xA;&lt;li&gt;Perform BSE calculation   (the dielectric function will be written in &lt;code&gt;vasprun.xml&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5010881&quot; rel=&quot;nofollow noreferrer&quot;&gt;Related research paper&lt;/a&gt; on the optical properties of two-dimensional materials using GW+BSE implemented in VASP.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.045209&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP's GW+BSE implementation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Dielectric_properties_of_Si_using_BSE&quot; rel=&quot;nofollow noreferrer&quot;&gt;BSE calculation of silicon&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="697" LastEditDate="2020-11-29T00:02:28.970" LastActivityDate="2020-11-29T00:02:28.970" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3680" PostTypeId="2" ParentId="365" CreationDate="2020-11-03T00:49:17.497" Score="11" Body="&lt;h1&gt;MATLAB&lt;/h1&gt;&#xA;&lt;p&gt;I have upvoted a lot of the other answers here, and I didn't write this answer at first because most matter modeling software doesn't use it, mainly for reasons I mention below.&lt;/p&gt;&#xA;&lt;p&gt;However, there's a lot of answers here now: not just the &lt;em&gt;best&lt;/em&gt; or &lt;em&gt;most popular&lt;/em&gt; languages for matter modeling, and MATLAB does have its place. You will quickly notice that I love MATLAB and will appear biased, so I will start first with the disadvantages:&lt;/p&gt;&#xA;&lt;h2&gt;Disadvantages:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It costs a lot of money (not a big problem if you're at a university or company that offers free or very cheap licenses, but license renewal can still be a headache and supercomputers with thousands of cores often won't have a license). The free &amp;quot;clone&amp;quot; of MATLAB called Octave, is still not perfect: there's slight differences between MATLAB and Octave, there's some issues with the GUI, running things on GPUs is not as straightforward as in MATLAB, not all toolboxes are available, the debugger and profiler are not the same, etc.&lt;/li&gt;&#xA;&lt;li&gt;It's a heavy-weight program that (by default) takes a long time to load (compared to python which opens right when you run the command: &lt;code&gt;python&lt;/code&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Things such as loops within loops or function calls within function calls can significantly &lt;strong&gt;slow down the code&lt;/strong&gt;, so you won't always get the speeds that you'll get with FORTRAN, C or C++.&lt;/li&gt;&#xA;&lt;li&gt;While theoretically you can do anything you want in MATLAB (including object oriented programming), &amp;quot;full-fledged&amp;quot; programming languages like Python might allow more flexibility (for example for arrays within arrays, without using cell arrays).&lt;/li&gt;&#xA;&lt;li&gt;The symbolic computing toolbox is not as user-friendly as a full-fledged symbolic programming software like Mathematica or Maple (which unfortunately isn't very popular anymore though).&lt;/li&gt;&#xA;&lt;li&gt;There's no native support for arbitrary-precision arithmetic (unless possibly with the symbolic computing toolbox).&lt;/li&gt;&#xA;&lt;li&gt;In my limited experience of using the machine learning toolbox for reinforcement learning, I found it to be very inefficient compared to TensorFlow.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;Advantages:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MATLAB is extremely quick and convenient for coding and debugging. It is like Python, where you don't have to compile every time you want to test your code, but significantly simpler and easier to code than Python, for example I provided &lt;a href=&quot;https://quantumcomputing.stackexchange.com/questions/4306/density-matrix-of-a-hamiltonian-function&quot;&gt;this code to answer a question on Quantum Computing Stack Exchange&lt;/a&gt; and in MATLAB it was very simple and painless to write:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr&gt;&#xA;&lt;pre&gt;&lt;code&gt;function H = Hamiltonian(alpha,h) &#xA;x=[0  1;  1 0 ];&#xA;y=[0 -1i; 1i 0];&#xA;z=[1  0;  0 -1];&#xA;I=eye(2);&#xA;H = alpha*kron(kron(x,x),I)+...&#xA;    alpha*kron(kron(y,y),I)+...&#xA;    alpha*kron(kron(I,x),x)+...&#xA;    alpha*kron(kron(I,y),y)+...&#xA;    h*kron(kron(I,z),I);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But the python version is longer and much more painful to write, as there's so many more unnecessary parentheses and extra symbols that need to be included:&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;def Hamiltonian(alpha,h):&#xA;x = np.array([[0,1],[1,0]])&#xA;y = np.array([[0,-1j],[1j,0]])&#xA;z = np.array([[1,0],[0,-1]])&#xA;I = np.array([[1,0],[0,1]])&#xA;H =  (alpha*np.kron(np.kron(Sx,Sx),I))&#xA;H =+ (alpha*np.kron(np.kron(Sy,Sy),I))&#xA;H =+ (alpha*np.kron(np.kron(I,Sx),Sx)) &#xA;H =+ (alpha*np.kron(np.kron(I,Sy),Sy))&#xA;H =+ (h*np.kron(np.kron(I,Sz),I))&#xA;return H&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://raw.githubusercontent.com/ndattani/matlabVSpython/master/2.bmp&quot; rel=&quot;noreferrer&quot;&gt;output for that example&lt;/a&gt; is also much clearer and prettier in MATLAB than for Python. Here's another example that came up in the &lt;a href=&quot;https://raw.githubusercontent.com/ndattani/matlabVSpython/master/1.bmp&quot; rel=&quot;noreferrer&quot;&gt;past&lt;/a&gt;: Get 10 random integers from 6-19.&lt;/p&gt;&#xA;&lt;p&gt;In MATLAB:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;randperm(14,10)+5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In Python:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;np.random.choice(range(6,19), 10, replace=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have not yet found an example which was the other way around, where Python could do something more neatly or easily than MATLAB. If you do know any examples, I'd love to see you add it to &lt;a href=&quot;https://github.com/ndattani/matlabVSpython/blob/master/comparisons.txt&quot; rel=&quot;noreferrer&quot;&gt;this &amp;quot;MATLAB vs Python&amp;quot; Git repo&lt;/a&gt; I made some time ago. Maybe what Python calls &amp;quot;broadcasting&amp;quot; is simpler than MATLAB's version which is &lt;code&gt;bsxfun&lt;/code&gt; (binary singleton expansion function), but since version 2016b this is no longer true.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If you spend a little more time vectorizing things properly and turning your code into a form that only uses built-in functions (these are MATLAB functions, such as matrix multiplication, that are optimized as much as possible and then compiled into machine code, so running them will be as fast in MATLAB as in FORTRAN or C), your code can be as fast or faster than FORTRAN or C. My code &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513002294&quot; rel=&quot;noreferrer&quot;&gt;FeynDyn&lt;/a&gt; (Feynman Dynamics) for quantum dynamics using the Feynman integral is in MATLAB and is faster than all the FORTRAN codes that do the same thing. There's also the possibility to compile the code into C or FORTRAN or CUDA, and also to generate C or CUDA code. MATLAB can call C or CUDA or FORTRAN sub-routines, and MATLAB functions can also be compiled to be run by C or CUDA or FORTRAN codes.&lt;/li&gt;&#xA;&lt;li&gt;Running your code on GPUs can require as little as two extra lines: one to get the data copied from the CPU to the GPU, and one to gather it back. Most important number crunching functions in MATLAB are implemented efficiently in CUDA and compiled to machine code already by the MATLAB engineers.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Large user community.&lt;/strong&gt; MATLAB has been around since the 70s and almost every engineer or scientific programmer in the world has used it as some point. MATLAB has its own Q/A site called &amp;quot;MATLAB Answers&amp;quot; whereas for Python all I know is that it's a &amp;quot;tag&amp;quot; in StackOverflow. Most things that you want to do in MATLAB have already been done by someone else, and can be found online easily. &lt;em&gt;Just about anything you've thought of doing in computing, has been done in MATLAB already&lt;/em&gt; (for example I wanted to let people use one of my codes but didn't want them to see the code yet because it was messy, and someone many years ago wanted to do this too, so there's a feature to make &lt;code&gt;p-code&lt;/code&gt; which is an unreadable file, like a binary file in compiled languages, that runs the code as normal).&lt;/li&gt;&#xA;&lt;li&gt;There's a plethora of toolboxes with tens of thousands of functions already implemented (Bioinformatics toolbox, Image processing toolbox, Parallel Computing Toolbox, and dozens and dozens more).&lt;/li&gt;&#xA;&lt;li&gt;It comes with a debugger and profiler that are better than anything I've seen for other languages (like &lt;code&gt;gdb&lt;/code&gt; for FORTRAN) except maybe something like the Java debugger in Dr. Java or Eclipse (I don't know if their profiler is comparably good though).&lt;/li&gt;&#xA;&lt;li&gt;Just as FORTRAN was &lt;em&gt;&lt;strong&gt;designed&lt;/strong&gt;&lt;/em&gt; for numerical computing, and therefore has several advantages over things like C and C++ which were designed to be &amp;quot;for everyone&amp;quot; including writing operating systems, GUIs, games, etc., &lt;strong&gt;MATLAB was built for no other reason than to do high-performance numerical computing&lt;/strong&gt;. Python has the same spirit of being easy to code and not having to compile the code every time you want to test it, but Python was built &amp;quot;for everyone&amp;quot; including those who want to make web apps, GUIs, games, etc. Python therefore isn't naturally catered around scientific computing, and requires you to import packages in order to do those things, and those packages like Numpy still make it unnatural to do simple things like defining a matrix (see the examples above).&lt;/li&gt;&#xA;&lt;li&gt;Now in its 6th decade, MATLAB has had many new functions and features and toolboxes added, but the core functionality is mostly the same. MATLAB code from decades ago will often still run, whereas Python 2 and Python 3 can be wildly different.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;Some MATLAB programs in matter modeling:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://spindynamics.org/group/?page_id=12&quot; rel=&quot;noreferrer&quot;&gt;Spinach&lt;/a&gt; for  spin dynamics that supports NMR, EPR, MRI, DNP, MAS, Optimal Control, PHIP, singlet state NMR, and other forms of Magnetic Resonance spectroscopy, and was developed by Ilya Kuprov and his group.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465513002294&quot; rel=&quot;noreferrer&quot;&gt;FeynDyn&lt;/a&gt; (Feynman Dynamics) for quantum dynamics using the Feynman integral on CPUs or GPUs, written by myself.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-03T17:31:13.390" LastActivityDate="2020-11-03T17:31:13.390" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3681" PostTypeId="1" CreationDate="2020-11-03T13:30:46.750" Score="12" ViewCount="136" Body="&lt;p&gt;I am trying to understand space groups in crystallography. In International tables for crystallography, for a nonsymmorphic space group, they list some symmetry operations. 8 of them are listed under the (0,0,0)+ set and 8 in the (1/2, 1/2, 1/2)+ set. What does this mean? Are there 16 operations in total? How do the sets differ?&lt;/p&gt;&#xA;&lt;p&gt;Edit:&#xA;I find similar notation for symmorphic space groups as well. There are some space groups with only one set and some with two or more, and I don't understand what determines the number of sets.&lt;/p&gt;&#xA;" OwnerUserId="1490" LastEditorUserId="5" LastEditDate="2020-12-29T13:27:13.167" LastActivityDate="2020-12-29T13:27:13.167" Title="What does it mean to assign group operations to distinct sets for space groups?" Tags="|crystal-structure|symmetry|from-phys-se|terminology|space-groups|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3682" PostTypeId="1" AcceptedAnswerId="3702" CreationDate="2020-11-03T14:22:32.513" Score="8" ViewCount="317" Body="&lt;p&gt;In CASTEP, can you start with a converged density for a lower level of theory for a starting guess for HSE06?  If you can, what functional is suggested or is it something that will cause more headache than it is worth?&lt;/p&gt;&#xA;&lt;p&gt;If you know for another code, feel free to leave your experience as well.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-11-12T17:40:46.297" Title="HSE06 Starting Guess" Tags="|functional|charge-density|hse06|castep|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3683" PostTypeId="2" ParentId="3666" CreationDate="2020-11-03T14:32:27.273" Score="5" Body="&lt;p&gt;Here I write a python script to read the EIGENVAL of VASP to exclude the fake points used in the HSE06 band calculation, taking silicon as an example.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/Kohn-X/vasp_HSE06_band_read_and_plot&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/Kohn-X/vasp_HSE06_band_read_and_plot&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The final plot is the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VJm64.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VJm64.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-03T14:32:27.273" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3684" PostTypeId="2" ParentId="3668" CreationDate="2020-11-03T15:58:31.307" Score="3" Body="&lt;p&gt;The Born-Oppenheimer (BO) approximation works well at high temperatures (far from 0 K), but the quantum nature of the nuclei (i.e. the zero-point energy) &lt;strong&gt;is&lt;/strong&gt; an important consideration at low temperatures.&lt;/p&gt;&#xA;&lt;p&gt;A great example of this is the difference between the &lt;strong&gt;Einstein&lt;/strong&gt; and Debye models of a solid.&lt;/p&gt;&#xA;&lt;p&gt;In the &lt;a href=&quot;https://en.wikipedia.org/wiki/Einstein_solid&quot; rel=&quot;nofollow noreferrer&quot;&gt;Einstein model,&lt;/a&gt; the nuclei are treated as identical independent 3D quantum harmonic oscillators (masses fixed to springs attached to an imaginary rigid lattice. If you use this model to predict the heat capacity of a solid, you will find it goes exponentially to zero as &lt;span class=&quot;math-container&quot;&gt;$T\to0$&lt;/span&gt;. This did not match experiments.&lt;/p&gt;&#xA;&lt;p&gt;In the &lt;a href=&quot;https://en.wikipedia.org/wiki/Debye_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;Debye model,&lt;/a&gt;, the nuclei are attached by springs to &lt;strong&gt;each other&lt;/strong&gt; and undergo collective oscillations. The collective excitation of this &lt;em&gt;interacting&lt;/em&gt; system are &lt;strong&gt;phonons&lt;/strong&gt; and the predicted heat capacity decays to zero at &lt;span class=&quot;math-container&quot;&gt;$C_v \propto T^3$&lt;/span&gt;, which matches experiments.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yyHek.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yyHek.jpg&quot; alt=&quot;Heat capacity predicted by the Einstein and Debye models&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-11-03T15:58:31.307" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3685" PostTypeId="1" CreationDate="2020-11-03T17:31:10.930" Score="14" ViewCount="2490" Body="&lt;p&gt;I'm fairly new to DFT. I would like to plot the DOS and band structure of Cobalt Oxide (CoO). But since CoO is anti ferro magnetic, how would I approach the problem? would I create an input file wherein I should assign starting magentization to spins as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O61AY.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O61AY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;by using names like Co1 and Co2 in the Atomic species name card. Or would the act of putting nspin = 2, along with a starting magnetisation for all cobalt atoms suffice?&#xA;Maybe someone who is experience could shed some light on how to properly model an anti-ferro magentic system.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1491" LastActivityDate="2022-12-22T18:35:17.203" Title="How to model an anti-ferromagnetic crystal in quantum ESPRESSO properly?" Tags="|density-functional-theory|band-structure|density-of-states|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3686" PostTypeId="2" ParentId="3678" CreationDate="2020-11-03T19:15:49.933" Score="9" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I am curious to know if the word has been used in any way other than the above three ways.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://winter.staff.shef.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;Mark. J. Winter&lt;/a&gt; at University of Sheffield has used the word differently — not as a term meaning something specific, but as a name for the so-called &lt;a href=&quot;https://winter.group.shef.ac.uk/chemputer/&quot; rel=&quot;noreferrer&quot;&gt;Sheffield ChemPuter&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Welcome to the University of Sheffield's ChemPuter, a set of simple interactive calculators for chemistry on the World-Wide Web.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This usage of the word clearly doesn't define &amp;quot;&lt;em&gt;&lt;strong&gt;a&lt;/strong&gt; chemputer&lt;/em&gt;&amp;quot;, at least not in the sense expected in the question. Nevertheless, a Google Scholar search reveals that the set of codes has been cited or used a nontrivial number of times, so it seemed worthwhile to document it in an answer here.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zRoWH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zRoWH.png&quot; alt=&quot;Screenshot from the Sheffield ChemPuter page&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-11-03T19:15:49.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3687" PostTypeId="1" AcceptedAnswerId="3738" CreationDate="2020-11-03T19:48:46.500" Score="9" ViewCount="350" Body="&lt;p&gt;I am trying to understand the interaction between the nucleophile and the substrate for some SN2 reactions (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{I- +CH3Cl-&amp;gt;CH3I + Cl-}$&lt;/span&gt;) at the transition states. Now, it seems that EDA would be able to analyse this interaction.&lt;/p&gt;&#xA;&lt;p&gt;But the problem is that the program I am using (GAMESS) requires the charge and multiplicity of each of the fragments to be defined. I have done EDA before with neutral systems. In this case, I am not sure how to define the charges at the transition state, because from what I know, at transition state, the negative charge is delocalised, mainly between the nucleophile and the leaving group (so each of them can be assumed to have, roughly +1/2 charge). I have no idea how to set the multiplicity either, but I guess leaving all to 1 could work. The way the program calculates EDA is by calculating each fragment separately, and then the supermolecule, so there is no way to avoid setting charges and multiplicities.&lt;/p&gt;&#xA;&lt;p&gt;I have also found multiple papers online which have used EDA on transition states (e.g. &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/jacs.9b02893&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;), so it is definitely doable.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone help me with this?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2020-11-03T20:16:04.440" LastActivityDate="2020-11-12T17:07:19.097" Title="Energy decomposition analysis (EDA) at transition state" Tags="|quantum-chemistry|transition-state|gamess|eda|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3688" PostTypeId="5" CreationDate="2020-11-03T19:49:28.327" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2020-11-03T19:49:28.327" LastActivityDate="2020-11-03T19:49:28.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3689" PostTypeId="4" CreationDate="2020-11-03T19:49:28.327" Score="0" Body="For questions on energy decomposition analysis (EDA)" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2020-11-04T15:08:06.303" LastActivityDate="2020-11-04T15:08:06.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3690" PostTypeId="1" CreationDate="2020-11-03T21:41:53.050" Score="13" ViewCount="188" Body="&lt;p&gt;Phonon density of states (DoS), &lt;span class=&quot;math-container&quot;&gt;$g_{(\omega_i)}$&lt;/span&gt;, help understand the distribution of states across frequencies of vibration. &lt;span class=&quot;math-container&quot;&gt;$\int g_{(\omega_i)}d\omega_i =$&lt;/span&gt; the number of states between &lt;span class=&quot;math-container&quot;&gt;$\omega_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d\omega_i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;DoS values aren't integers, at least none in my calculations were. Wouldn't the possible number of states in any range of frequency be an integer, or is this some quantum/wave effect?&lt;/p&gt;&#xA;&lt;p&gt;If we think about a crystal with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms. Each atom has its own set of frequencies, so the equations above work for each atom. Codes like &lt;code&gt;Phonopy&lt;/code&gt; output DoS as if it represented the frequencies of vibration of the whole crystal system of all &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms. The following equations are from Dr. Brent Fultz's review of the &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0079642509000577?casa_token=jLeJgkepgDUAAAAA:4pVSUNNyAKrJci1phBe1m7BTSAFmwWefLclag8q9Vzx86zpjvICrSnCaGr36Bg176-h-M0sA#!&quot; rel=&quot;nofollow noreferrer&quot;&gt;vibrational thermodynamics of materials&lt;/a&gt;. &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; is the canonical &lt;em&gt;harmonic&lt;/em&gt; partition function.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;Z_i = \frac{e^{-\beta \epsilon_i/2}}{1 - e^{-\beta \epsilon_i}}\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;Z_N = \prod_{i}^{3N}\frac{e^{-\beta \epsilon_i/2}}{1 - e^{-\beta \epsilon_i}}\tag{2}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first equation is about each of the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; oscillators and the second about the whole system.&lt;/p&gt;&#xA;&lt;p&gt;I'm confused with regards to the way lattice dynamics codes like &lt;code&gt;Phonopy&lt;/code&gt; output DoS data. Can someone help me organize my thoughts here and put the right pieces in place?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-11-08T00:08:33.007" LastActivityDate="2020-11-08T00:08:33.007" Title="Phonon density of states in statistical thermodynamics" Tags="|statistical-thermodynamics|phonopy|phonon-density-of-state|lattice-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3691" PostTypeId="2" ParentId="3535" CreationDate="2020-11-03T23:35:41.117" Score="6" Body="&lt;p&gt;There are couple of options:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Bader analysis&lt;/li&gt;&#xA;&lt;li&gt;Charge density difference (plot in vesta is easy). Take CHGCAR(A+B) and subtract CHGCAR(A) and CHGCAR(B). It can be easily done in vesta &amp;gt;edit&amp;gt; volumetric data&lt;/li&gt;&#xA;&lt;li&gt;Mulken population analysis (use chgmol programme)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2020-11-03T23:55:46.777" LastActivityDate="2020-11-03T23:55:46.777" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3693" PostTypeId="1" AcceptedAnswerId="3695" CreationDate="2020-11-04T00:55:54.747" Score="19" ViewCount="1370" Body="&lt;p&gt;I often find that when talking to experimentalists outside of the field of nanomaterials, it is nearly impossible to explain Miller indices concisely.  As this often comes up during talks from other students or even faculty, how would you suggest it be explained assuming they have only a generic chemistry background?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-11-05T04:29:40.930" LastActivityDate="2020-12-30T08:09:17.803" Title="How to explain Miller indices to someone outside nanomaterials?" Tags="|crystal-structure|surfaces|crystallography|terminology|geometry|" AnswerCount="4" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3694" PostTypeId="2" ParentId="3693" CreationDate="2020-11-04T04:07:33.430" Score="13" Body="&lt;p&gt;Assuming a generic chemistry background I wouldn't assume that knowledge of crystal structure would be too in depth at an undergraduate level. It is definitely encountered, but depending on the type of chemistry you want to go into, you probably never deal with solid state chemistry. I would first explain briefly how crystals are described by periodic lattices, with basis vectors that describe translations of atoms to build the structure. Then I would say that Miller indices are related to planes that intersect the basis vectors. Since you want to talk about planes that you can visually picture inside of the unit cell (for convenience), you talk about intersections at fractional distances along the basis vectors. The indices are the reciprocals of the fractions, once again for convenience. Then go on to say that if the plane never intersects a basis vector, you say it has an infinite intersection distance, and the reciprocal is 0. Diffraction peak locations of light is unique for crystals of the same structure, because diffraction occurs at the miller planes.&lt;/p&gt;&#xA;" OwnerUserId="1451" LastActivityDate="2020-11-04T04:07:33.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3695" PostTypeId="2" ParentId="3693" CreationDate="2020-11-04T08:37:25.233" Score="19" Body="&lt;p&gt;You can see it with &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;noreferrer&quot;&gt;VESTA software.&lt;/a&gt; For example, we can see the different lattice planes of NaCl crystal.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[001] plane of NaCl:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9rdrb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9rdrb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[101] plane of NaCl:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sotmU.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sotmU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[111] plane of NaCl:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7q4FI.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7q4FI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-12-30T01:08:52.127" LastActivityDate="2020-12-30T01:08:52.127" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3696" PostTypeId="1" CreationDate="2020-11-04T11:54:09.063" Score="24" ViewCount="1427" Body="&lt;p&gt;A little bit of coding can a long way in matter modeling. Coding is not used only to write big programs but can be used for scripting, data processing, automation, and more. But sometimes many resources (books, papers, etc.) are generic and superficial.&lt;/p&gt;&#xA;&lt;p&gt;Are any good resources to learn to code in the context of matter modeling? What do you recommend?&lt;/p&gt;&#xA;" OwnerUserId="878" LastActivityDate="2021-01-05T00:03:03.870" Title="What are good resources to learn to code for matter modeling?" Tags="|reference-request|education|" AnswerCount="6" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3697" PostTypeId="2" ParentId="3696" CreationDate="2020-11-04T12:51:34.863" Score="12" Body="&lt;p&gt;This question is quite generic but I always plug the &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/&quot; rel=&quot;noreferrer&quot;&gt;online DFT book&lt;/a&gt; by Kitchin. Its a good resource showing how python can run VASP which is probably a good starting point.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="-1" LastEditDate="2020-11-04T21:59:58.327" LastActivityDate="2020-11-04T21:59:58.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3698" PostTypeId="2" ParentId="3696" CreationDate="2020-11-04T14:22:51.883" Score="13" Body="&lt;p&gt;Code can be used to automate, derive insights and to calculate more observations with the given set of data.&lt;/p&gt;&#xA;&lt;p&gt;Automation: This can be done via &lt;a href=&quot;https://www.tutorialspoint.com/unix/shell_scripting.htm&quot; rel=&quot;noreferrer&quot;&gt;bash scripts&lt;/a&gt; or through the &lt;a href=&quot;https://www.tutorialsteacher.com/python/os-module&quot; rel=&quot;noreferrer&quot;&gt;os module&lt;/a&gt; in python. This is an example &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3533/how-to-extract-the-pressure-energy-and-unit-cell-volume-from-quantum-espresso-o/3534#3534&quot;&gt;bash script&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Deriving insights and data manipulation: This can be done using small python scripts and some modules that may come in handy are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tutorialspoint.com/numpy/index.htm&quot; rel=&quot;noreferrer&quot;&gt;numpy&lt;/a&gt; [for array manupulation]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tutorialspoint.com/python_pandas/index.htm&quot; rel=&quot;noreferrer&quot;&gt;pandas&lt;/a&gt; [for dataset manipulation]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tutorialspoint.com/scipy/index.htm&quot; rel=&quot;noreferrer&quot;&gt;scipy&lt;/a&gt; [in case you want to fit curves and do interpolations]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tutorialspoint.com/scikit_learn/index.htm&quot; rel=&quot;noreferrer&quot;&gt;sklearn&lt;/a&gt; [a machine learning library that would help you get statistical inferences from an ensemble]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-11-04T14:22:51.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3699" PostTypeId="2" ParentId="3696" CreationDate="2020-11-04T17:11:48.917" Score="12" Body="&lt;h3&gt;For quantum Monte Carlo or exact/Lanczos diagonalization&lt;/h3&gt;&#xA;&lt;p&gt;I recommend &lt;em&gt;Computational Studies of Quantum Spin Systems&lt;/em&gt; by Anders Sandvik &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1101.3281&lt;/a&gt;, or &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3518900&quot; rel=&quot;noreferrer&quot;&gt;AIP Conf. Pro. &lt;strong&gt;1297&lt;/strong&gt;, 135 (2010)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This review is designed to teach you how to write quantum Monte Carlo simulations of &lt;strong&gt;spin systems&lt;/strong&gt; like the Heisenberg model. There are also example codes from the workshop on &lt;a href=&quot;http://physics.bu.edu/%7Esandvik/vietri/index.html&quot; rel=&quot;noreferrer&quot;&gt;Sandvik's website&lt;/a&gt; (note of caution: there may be a bug where the random number generator doesn't work for the SSE code, so you may have to substitute your own RNG).&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="97" LastEditDate="2020-11-04T17:24:11.030" LastActivityDate="2020-11-04T17:24:11.030" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3700" PostTypeId="2" ParentId="3690" CreationDate="2020-11-04T17:22:58.910" Score="5" Body="&lt;p&gt;There are two possible things tripping you up here:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Phonons are &lt;strong&gt;collective&lt;/strong&gt; oscillations: they involve the motion of all the atoms together. Therefore it only makes sense to talk about the phonons of the whole system, not any individual atom.&lt;/li&gt;&#xA;&lt;li&gt;The density of states only makes sense as you take &lt;span class=&quot;math-container&quot;&gt;$N\to \infty$&lt;/span&gt;. For finite &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, there is a finite/discrete number of phonon modes, and so the density of states would be a series of delta functions. As you take &lt;span class=&quot;math-container&quot;&gt;$N\to \infty$&lt;/span&gt;, the spacing between the modes goes to zero and you're left with a continuum and thus a continuous DOS.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-11-04T17:22:58.910" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3701" PostTypeId="2" ParentId="3693" CreationDate="2020-11-05T06:59:24.720" Score="5" Body="&lt;p&gt;I would propably explain that there are different planes within a crystal, show some of them in an animation or pyhsical prop and depending on the depth of the presentation just omit the numbering and details.&lt;/p&gt;&#xA;" OwnerUserId="1496" LastEditorUserId="792" LastEditDate="2020-11-06T07:35:14.480" LastActivityDate="2020-11-06T07:35:14.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3702" PostTypeId="2" ParentId="3682" CreationDate="2020-11-05T12:26:53.907" Score="8" Body="&lt;p&gt;Yes, you can do this. First, do a normal PBE calculation (HSE is built on-top of PBE) which generates an &lt;code&gt;&amp;lt;seed&amp;gt;.check&lt;/code&gt; and &lt;code&gt;&amp;lt;seed&amp;gt;.castep_bin&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;Then add this line&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;reuse : &amp;lt;name of the check/castep_bin file&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to the &lt;code&gt;param&lt;/code&gt; file of your HSE06 calculation. This will let CASTEP read in and reuse the previous charge density and wavefunction for the new calculation.&lt;/p&gt;&#xA;&lt;p&gt;Starting from an existing charge density and wavefunction will usually reduce the number of SCF cycles needed to reach convergence.&lt;/p&gt;&#xA;&lt;p&gt;As a side note, you can also do a HSE06 bandstructure on top of a PBE charge density in one single calculation with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;task : spectral&#xA;spectral_task : bandstructure&#xA;xc_functional : pbe&#xA;spectral_xc_functional : hse06&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will make the program first solve the eletronic structure with PBE and use the obtained charge density for the subsequent HSE06 bandstructure calculation.&lt;/p&gt;&#xA;" OwnerUserId="1020" LastEditorUserId="403" LastEditDate="2020-11-12T17:40:46.297" LastActivityDate="2020-11-12T17:40:46.297" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3703" PostTypeId="2" ParentId="3661" CreationDate="2020-11-05T14:44:05.453" Score="5" Body="&lt;ul&gt;&#xA;&lt;li&gt;The calculated structure is the following:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1DI9p.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1DI9p.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The self-consistent input file for QE calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation = 'scf'&#xA;etot_conv_thr =   4.0000000000d-05&#xA;forc_conv_thr =   1.0000000000d-04&#xA;outdir = './out/'&#xA;prefix = 'aiida'&#xA;pseudo_dir = './pseudo/'&#xA;tprnfor = .true.&#xA;tstress = .true.&#xA;verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;degauss =   1.4699723600d-02&#xA;ecutrho =   1.0800000000d+03&#xA;ecutwfc =   9.0000000000d+01&#xA;ibrav = 0&#xA;nat = 4&#xA;nspin = 2&#xA;ntyp = 3&#xA;occupations = 'smearing'&#xA;smearing = 'cold'&#xA;starting_magnetization(1) =   3.1250000000d-01&#xA;starting_magnetization(2) =   1.0000000000d-01&#xA;starting_magnetization(3) =   4.1666666667d-01&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;conv_thr =   8.0000000000d-10&#xA;electron_maxstep = 80&#xA;mixing_beta =   4.0000000000d-01&#xA;/&#xA;ATOMIC_SPECIES&#xA;Fe     55.847 Fe.pbe-spn-kjpaw_psl.0.2.1.UPF&#xA;Sn     118.71 Sn_pbe_v1.uspp.F.UPF&#xA;Ti     47.88 ti_pbe_v1.4.uspp.F.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;Ti           0.0000000000       0.0000000000       0.0000000000&#xA;Ti           0.7500000000       0.7500000000       0.7500000000&#xA;Fe           0.5000000000       0.5000000000       0.5000000000&#xA;Sn           0.2500000000       0.2500000000       0.2500000000&#xA;K_POINTS automatic&#xA;11 11 11 0 0 0&#xA;CELL_PARAMETERS angstrom&#xA;3.7418479919       0.0000000000       0.0000000000&#xA;1.8709239960       3.2405354181       0.0000000000&#xA;1.8709239960       1.0801784727       3.0552060918&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Output magnetization:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;total magnetization       =     3.64 Bohr mag/cell&#xA;total magnetization       =     1.70 Bohr mag/cell&#xA;total magnetization       =     2.00 Bohr mag/cell&#xA;total magnetization       =     1.94 Bohr mag/cell&#xA;total magnetization       =     1.96 Bohr mag/cell&#xA;total magnetization       =     1.55 Bohr mag/cell&#xA;total magnetization       =     1.24 Bohr mag/cell&#xA;total magnetization       =     1.07 Bohr mag/cell&#xA;total magnetization       =     1.07 Bohr mag/cell&#xA;total magnetization       =     1.04 Bohr mag/cell&#xA;total magnetization       =     1.04 Bohr mag/cell&#xA;total magnetization       =     1.05 Bohr mag/cell&#xA;total magnetization       =     1.04 Bohr mag/cell&#xA;total magnetization       =     1.04 Bohr mag/cell&#xA;total magnetization       =     1.03 Bohr mag/cell&#xA;total magnetization       =     1.03 Bohr mag/cell&#xA;total magnetization       =     1.02 Bohr mag/cell&#xA;total magnetization       =     1.02 Bohr mag/cell&#xA;total magnetization       =     1.02 Bohr mag/cell&#xA;total magnetization       =     1.01 Bohr mag/cell&#xA;total magnetization       =     1.01 Bohr mag/cell&#xA;total magnetization       =     1.01 Bohr mag/cell&#xA;total magnetization       =     1.01 Bohr mag/cell&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A useful website to generate the input file for QE calculation: &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;noreferrer&quot;&gt;https://www.materialscloud.org/work/tools/qeinputgenerator&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-05T14:44:05.453" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3704" PostTypeId="1" AcceptedAnswerId="9124" CreationDate="2020-11-05T22:57:56.373" Score="15" ViewCount="247" Body="&lt;p&gt;The first order variation of the wave function &lt;span class=&quot;math-container&quot;&gt;$\Delta \psi_n$&lt;/span&gt; is obtained by standard perturbation theory (Eq. 25 of ref &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.515&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;(H_{SCF}-\epsilon_n)|\Delta \psi_n \rangle = -(\Delta V_{SCF} - \Delta \epsilon)|\psi_n\rangle \tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, in practical implementations, the following equation (Eq. 30 of the same ref) is adopted and an iterative algorithm like conjugate-gradient approach is employed to find the solution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;(H_{SCF}-\epsilon_n-\alpha P_v)|\Delta \psi_n \rangle = -P_c\Delta V_{SCF}|\psi_n\rangle \tag{2}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the projection operator with &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; for valence/occupied and conduction/empty states, respectively. The &lt;span class=&quot;math-container&quot;&gt;$\alpha P_v$&lt;/span&gt; term is added to eliminate the singularity of the linear operator &lt;span class=&quot;math-container&quot;&gt;$H_{SCF}-\epsilon_n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;As Eq. (2) is one typical way to evaluate the occupied states variation with the aid of projection operators, how can we calculate the derivative of conduction states?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2022-01-28T01:02:28.333" LastActivityDate="2022-05-21T03:56:33.247" Title="First order variation of the wave function of conduction states" Tags="|mathematical-modeling|quantum-mechanics|dfpt|derivations|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3705" PostTypeId="2" ParentId="3672" CreationDate="2020-11-06T04:47:05.213" Score="5" Body="&lt;p&gt;I would say the reason that they default to storing the integrals is because there is no obvious choice to make one way or the other as it depends a lot on what resources are available and how large of a calculation you are doing. I have encountered this same situation while using Molpro before. In fact, every electronic structure package I'm aware of has an option to either compute the integrals directly or cache them on disk. Many packages also have semi-direct methods for caching some integrals and directly computing others. To be more specific, I'll quote a relevant section from the &lt;a href=&quot;https://www.molpro.net/info/release/doc/manual/node137.html&quot; rel=&quot;noreferrer&quot;&gt;Molpro manual&lt;/a&gt; which I think answers your questions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Most methods implemented in MOLPRO can be performed integral-direct, i.e., the methods are integral driven with the two-electron integrals in the AO basis being recomputed whenever needed, avoiding the bottleneck of storing these quantities on disk. Exceptions are currently full CI (FCI), perturbative triple excitations (T), UMP2, RMP2, CPP, MRCI-F12, and RS2-F12. For small molecules, this requires significantly more CPU time, but reduces the disk space requirements when using large basis sets. However, due to efficient prescreening techniques, the scaling of the computational cost with molecular size is lower in integral-direct mode than in conventional mode, and therefore integral-direct calculations for extended molecules may even be less expensive than conventional ones. The break-even point depends strongly on the size of the molecule, the hardware, and the basis set. Depending on the available disk space, calculations with more than 150–200 basis functions in one symmetry should normally be done in integral-direct mode.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2020-11-06T04:47:05.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3706" PostTypeId="2" ParentId="3696" CreationDate="2020-11-06T12:42:19.797" Score="17" Body="&lt;h2&gt;&lt;a href=&quot;https://missing.csail.mit.edu/&quot; rel=&quot;noreferrer&quot;&gt;The missing semester&lt;/a&gt;: An MIT Course&lt;/h2&gt;&#xA;&lt;p&gt;For a beginner in the field, most often the difficulty would be in working with unix-like environments, which is the only way to access many of the matter modeling software and probably the most convenient way to analyse the outputs of the calculations. And this is often learned the hard way by searching the internet on how to work with different tools for different purposes, which often takes a long time to get going with and is most often frustrating for people less familiar with the working of these systems. This course introduces one to the basic components of a unix-like environment, working with shell, scripting, editing files, data analysis and many more which would help build a base understanding of these systems from which one can easily learn the specific tools required for one's work. It's named aptly as &amp;quot;the missing semester&amp;quot; as it is often not covered while teaching computational techniques and is left to the learner to figure out on their own.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2020-11-06T12:42:19.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3707" PostTypeId="1" CreationDate="2020-11-07T10:06:13.360" Score="10" ViewCount="190" Body="&lt;p&gt;I know that this is quite general. But we have all written code for processing output files from various dft codes. The functionality of which, may range from analysing time traces to finding transitions from the band structure. It could be nice if they could be shared here as snippets themselves or as github repo links. This would be helpful for people who would need them and at the sametime provide a different way of looking at things in terms of writing code for post-processing.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-11-07T10:13:48.693" LastActivityDate="2021-09-06T12:33:20.187" Title="Can you list some useful code snippets for processing quantum ESPRESSO output files?" Tags="|software|one-topic-per-answer|quantum-espresso|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3708" PostTypeId="2" ParentId="3707" CreationDate="2020-11-08T04:28:55.007" Score="5" Body="&lt;p&gt;&lt;strong&gt;BURAI 1.3:A GUI of Quantum ESPRESSO&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Web link:&lt;a href=&quot;https://nisihara.wixsite.com/burai&quot; rel=&quot;noreferrer&quot;&gt;https://nisihara.wixsite.com/burai&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Tutorial link: &lt;a href=&quot;https://nisihara.wixsite.com/burai/usage&quot; rel=&quot;noreferrer&quot;&gt;https://nisihara.wixsite.com/burai/usage&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How to create QE's Input File.&lt;/li&gt;&#xA;&lt;li&gt;How to calculate.&lt;/li&gt;&#xA;&lt;li&gt;How to create a model&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Youtube tutorial: &lt;a href=&quot;https://www.youtube.com/watch?v=Zvj79g3UiaU&amp;amp;list=PLUhYFZgYOn8fS5zeNNWF66YU1nZuGltjz&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=Zvj79g3UiaU&amp;amp;list=PLUhYFZgYOn8fS5zeNNWF66YU1nZuGltjz&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;By the way, QE has support utilities like pp.x for data analysis.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-08T04:28:55.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3709" PostTypeId="1" AcceptedAnswerId="3741" CreationDate="2020-11-08T13:05:52.627" Score="9" ViewCount="2031" Body="&lt;p&gt;The following figure is the electron localization function (ELF) for monolayer LaBr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dPUeF.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dPUeF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The ELF is calculated to reflect the bonding character in SL LaBr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. As shown in the figure, ELF shows two localization areas: one is located around La (brown color) and the other around Br (grey color) atoms. Almost no electron is localized between La and Br atoms, suggesting the typical ionic bonding, with La atoms donating electrons to Br atoms.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However, this bond character can be understood from the charge density plot. So what's the difference between charge density and the electron localization function (ELF)? What else can we read from the ELF plot?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-12T19:52:02.340" Title="What's the difference between charge density and the electron localization function (ELF)?" Tags="|charge-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3710" PostTypeId="1" CreationDate="2020-11-08T13:15:49.643" Score="13" ViewCount="376" Body="&lt;p&gt;I have used a few codes for studying magnetic materials (specifically core-shell nanoparticles with an AFM shell and an FM core). These are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://vampire.york.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;Vampire&lt;/a&gt;:  For the calculation of curie temperature via Magnetisation-Temperature curve simulations;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mumax.github.io/&quot; rel=&quot;noreferrer&quot;&gt;Mumax3&lt;/a&gt;: For Micromagnetics simulations; and&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://zenodo.org/record/1136068#.X6fuzRZX600&quot; rel=&quot;noreferrer&quot;&gt;Vegas&lt;/a&gt;: This is an old package using the heisenberg model. [I havent been able to use this due to compilation issues].&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Are there any other software packages?&#xA;I have also heard of &lt;a href=&quot;https://math.nist.gov/oommf/&quot; rel=&quot;noreferrer&quot;&gt;OOMMF&lt;/a&gt;, &lt;a href=&quot;https://ubermag.github.io/&quot; rel=&quot;noreferrer&quot;&gt;Ubermag&lt;/a&gt; and others but I'm not familiar with them. So it would be nice if anyone could shed some light on the main use cases (what kind simulations could be easily done using such software).&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-11-09T17:30:10.743" LastActivityDate="2021-06-20T08:43:23.327" Title="Are there any codes to study magnetic materials?" Tags="|one-topic-per-answer|software-recommendations|magnetism|heisenberg-model|atomistic-simulation|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3711" PostTypeId="1" AcceptedAnswerId="3714" CreationDate="2020-11-08T15:07:53.400" Score="16" ViewCount="1147" Body="&lt;p&gt;I am a beginner user of the Pymatgen package. In order to process the data from VASP DFT calculation software, I use Pymatgen to visualize the output band structure. When I do spin polarised band calculation, I cannot separate the band structure of spin up and spin down into 2 different subplots or graphs. Can anyone tell me how can I deal with this? Because it looks messy when the package automatically plot it into the same graph.&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="85" LastEditDate="2021-05-23T04:49:20.990" LastActivityDate="2021-05-23T04:49:20.990" Title="How to separate the data plot for spin up and spin down band structure into 2 different graphs, in Pymatgen?" Tags="|vasp|band-structure|visualization-software|pymatgen|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3712" PostTypeId="1" CreationDate="2020-11-08T22:12:05.770" Score="11" ViewCount="818" Body="&lt;p&gt;What is the best python package to construct Smooth Overlap of Atomic Positions (SOAP) descriptors given SMILES representation of a molecule? Is this even possible without providing 3D geometry? An example would be appreciated (The example in the &lt;a href=&quot;https://reader.elsevier.com/reader/sd/pii/S0010465519303042?token=D2C663B36B76915A9056778DE71717CBE731E776618DCF7507E301C5A03002A88F5896EFAC7D5D1A4B36EC1AF65CE93F&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; from &lt;code&gt;dscribe&lt;/code&gt; package is too trivial and cannot be extended to other molecules)&lt;/p&gt;&#xA;&lt;p&gt;P.S. I'm trying to generate these descriptors for QM9 dataset molecules. Is there any databases that already has computed it?&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="52" LastEditDate="2020-11-09T08:54:24.703" LastActivityDate="2020-11-12T19:36:18.067" Title="Generating SOAP descriptors in python" Tags="|software|python|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3713" PostTypeId="1" CreationDate="2020-11-08T23:25:17.357" Score="10" ViewCount="186" Body="&lt;p&gt;I have tried to simulate the hysteresis loop for the exchange spring structure using &lt;em&gt;&lt;strong&gt;Mumax3&lt;/strong&gt;&lt;/em&gt;. I have already simulated the hysteresis loop for the conventional bilayer soft-hard structure. Please find the code (given in the link below) I used for the simulation and the hysteresis loop obtained from the simulation, which clearly shows two different coercivities from soft and hard layers, respectively. Hope, this code is correct. Please let me know if you found anything wrong in the code.&lt;/p&gt;&#xA;&lt;p&gt;However, our experimental system is quite different from the conventional soft-hard structure. This system will also be a bilayer system like the conventional system. Additionally, we need to introduce the geometry as the following image (image-1.png) attached in the enclosure, where both the shaded black and the unshaded blank regions are magnetic. However, the magnetic properties of the two regions are different, i.e., the shaded black region is hard-magnetic, and the blank white region is soft-magnetic with OOP and IP anisotropy, respectively.&lt;/p&gt;&#xA;&lt;p&gt;Now, what I faced the problem is that, while I set the hard magnetic properties in the figure, the rest of the image is still blank! Instead, I want to assign the blank portion as soft magnetic properties. As the unshaded portion is blank, I am not getting the required result! I am stuck at defining such nonconventional complex geometry.&lt;/p&gt;&#xA;&lt;p&gt;Link for the codes and the image: &lt;a href=&quot;https://drive.google.com/drive/folders/1-ZVRwPAsAl_pI506m29PVqepNwdntZmw?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/drive/folders/1-ZVRwPAsAl_pI506m29PVqepNwdntZmw?usp=sharing&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could you please let me know where I should modify the code for the nonconventional system?&lt;/p&gt;&#xA;" OwnerUserId="1505" LastEditorUserId="1505" LastEditDate="2020-11-09T09:55:48.273" LastActivityDate="2020-11-09T12:45:36.353" Title="How to define a nonconventional geometry to obtain exchange spring hysteresis loop structure using MuMax3?" Tags="|geometry-optimization|mumax3|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3714" PostTypeId="2" ParentId="3711" CreationDate="2020-11-09T00:35:26.787" Score="13" Body="&lt;p&gt;Here I provide an example with my own python scripts to realize your purpose rather than using Pymatgen (You can save data firstly with Pymatgen and plot with python). I assume that you can perform correctly the band and dos calculations with the VASP code. The example I pick up is the monolayer FM NiBr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; and the final result is the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pZH1C.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pZH1C.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Example GitHub link: &lt;a href=&quot;https://github.com/Kohn-X/VASP_two_spins&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Kohn-X/VASP_two_spins&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-11-25T08:37:08.830" LastActivityDate="2020-11-25T08:37:08.830" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3715" PostTypeId="2" ParentId="3678" CreationDate="2020-11-09T10:25:01.637" Score="9" Body="&lt;p&gt;The term chemputer also refers to a universal chemical synthesis robot - this is because the robot uses a high level abstraction of chemical synthesis. From this approach we developed a programming language for chemistry that can be run on the chemputer robot. Since in principle ANY chemical can be made in our robot, and the langauge is universal, we coined the term chemputer. The system is being developed and expanded so that all chemistry can be expressed in the chemical programming language. This has defined a new standard for chemical synthesis see chemputer.org&lt;/p&gt;&#xA;" OwnerUserId="1507" LastActivityDate="2020-11-09T10:25:01.637" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3716" PostTypeId="2" ParentId="3685" CreationDate="2020-11-09T10:57:25.770" Score="11" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The key point is the setting of starting_magnetization. &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm269&quot; rel=&quot;nofollow noreferrer&quot;&gt;You can find an explanation on the pw.x input description page.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Here I give you an example to set this tag. The structure picked here is the monolayer CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;. To achieve an AFM configuration, a square lattice with four Cr atoms is built as follows:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2Ulitm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2Ulitm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Antiferromagnetic configuration setting: Cr1 (&lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt;) / Cr2 (&lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt;) / Cr3=Cr1 (&lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt;) / Cr4=Cr2 (&lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;All I atoms are non-magnetic.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;QE scf input card:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;    calculation='scf'&#xA;    prefix='CrI3'&#xA;    outdir='./tmp/'&#xA;    pseudo_dir='./pseudo/'&#xA;    etot_conv_thr=1.0d-05&#xA; /&#xA; &amp;amp;SYSTEM&#xA;    ibrav=0&#xA;    nat=16&#xA;    ntyp=3&#xA;    ecutwfc=60&#xA;    ecutrho=720&#xA;    occupations='smearing'&#xA;    smearing='mp'&#xA;    degauss=0.02&#xA;    nspin=2&#xA;    starting_magnetization(1)= 3  !note that ntype=3&#xA;    starting_magnetization(2)=-3&#xA;    starting_magnetization(3)= 0&#xA;  /&#xA;  &amp;amp;ELECTRONS&#xA;    conv_thr=1.0d-8&#xA;    mixing_beta=0.7&#xA;    electron_maxstep=200&#xA;  /&#xA;  ATOMIC_SPECIES&#xA;    Cr1  51.996 cr_pbe_v1.5.uspp.F.UPF&#xA;    Cr2  51.996 cr_pbe_v1.5.uspp.F.UPF&#xA;    I    126.9045 I.pbe-n-kjpaw_psl.0.2.UPF&#xA;  ATOMIC_POSITIONS crystal&#xA;    Cr1  0.0000000000  0.0000000000   0.3304567040&#xA;    Cr2  0.0000000000  0.3333333430   0.3297766150&#xA;    Cr1  0.5000000000  0.5000000000   0.3304567040&#xA;    Cr2  0.5000000000  0.8333333730   0.3297766150&#xA;    I    0.1495049890  0.1672649980   0.4083212910&#xA;    I    0.6495050190  0.6672649980   0.4083212910&#xA;    I    0.1743501420  0.4911199810   0.4083212910&#xA;    I    0.6743501420  0.9911199810   0.4083212910&#xA;    I    0.6761449580  0.3416150210   0.4083212910&#xA;    I    0.1761449580  0.8416150210   0.4083212910&#xA;    I    0.8504950400  0.1660683450   0.2519120570&#xA;    I    0.3504950400  0.6660683160   0.2519120570&#xA;    I    0.3256500360  0.3422133330   0.2519120570&#xA;    I    0.8256500360  0.8422133330   0.2519120570&#xA;    I    0.8238549830  0.4917183820   0.2519120570&#xA;    I    0.3238549830  0.9917184110   0.2519120570&#xA;  CELL_PARAMETERS angstrom&#xA;    6.8670001030       0.0000000000       0.0000000000&#xA;    0.0000000000      11.8939924240       0.0000000000&#xA;    0.0000000000       0.0000000000      20.0000000000&#xA;  K_POINTS automatic&#xA;    4 2 2 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Total magnetization in each electronic step:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VoAZEm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VoAZEm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Once you know how to do the self-consistent calculation, all left calculations are easily performed.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-12-22T18:35:17.203" LastActivityDate="2022-12-22T18:35:17.203" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3717" PostTypeId="2" ParentId="3713" CreationDate="2020-11-09T12:45:36.353" Score="8" Body="&lt;p&gt;I'll try to give you an answer and a way to proceed&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;However, our experimental system is quite different from the&#xA;conventional soft-hard structure. This system will also be a bilayer&#xA;system like the conventional system.&#xA;Additionally, we need to introduce the geometry as the following image&#xA;(image-1.png) attached in the enclosure, where both the shaded black&#xA;and the unshaded blank regions are magnetic. However, the magnetic&#xA;properties of the two regions are different, i.e., the shaded black&#xA;region is hard-magnetic, and the blank white region is soft-magnetic&#xA;with OOP and IP anisotropy, respectively.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;From this If I understand correctly , you have a bilayer system and in the top layer there is a pattern as shown in this image. In the non-conventional code you have mentioned it like that.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(&amp;quot;The grid sizes for the simulation along X, Y, Z directions, respectively:&amp;quot;)  &#xA;Nx := 64 &#xA;Ny := 64 &#xA;Nz := 64 &#xA;setgridsize(Nx, Ny, Nz)&#xA;&#xA;print(&amp;quot;The cell sizes for the simulation along X, Y, Z directions, respectively:&amp;quot;) &#xA;cx := 5e-9 &#xA;cy := 5e-9 &#xA;cz := 5e-9 &#xA;setcellsize(cx, cy, cz) &#xA;softth:=Nz-32 &#xA;hardth:=Nz-softth&#xA;&#xA;print(&amp;quot;Define different regions:&amp;quot;) &#xA;fig1:= imageShape(&amp;quot;image-1.png&amp;quot;) &#xA;defregion(1, (layers(softth, Nz))) &amp;lt;============== &#xA;defregion(2, fig1) &amp;lt;============================== These lines  &#xA;setgeom( fig1 ) &amp;lt;=================================&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But since you need the Fig 1 structure to be embedded in the cuboid&lt;/p&gt;&#xA;&lt;p&gt;you need to set the geometry to a cuboid and then define a region inside the cuboid.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(&amp;quot;The grid sizes for the simulation along X, Y, Z directions, respectively:&amp;quot;)&#xA;Nx := 64&#xA;Ny := 64&#xA;Nz := 64&#xA;setgridsize(Nx, Ny, Nz)&#xA;&#xA;print(&amp;quot;The cell sizes for the simulation along X, Y, Z directions, respectively:&amp;quot;)&#xA;cx := 5e-9&#xA;cy := 5e-9&#xA;cz := 5e-9&#xA;setcellsize(cx, cy, cz)&#xA;softth:=Nz-32&#xA;hardth:=Nz-softth&#xA;&#xA;print(&amp;quot;Define different regions:&amp;quot;)&#xA;&#xA;// This is done to define an cuboidal geometry&#xA;setgeom( cuboid(Nx*cx, Ny*cy, Nz*cz) )&#xA;// to extract the geometry from the image&#xA;fig1:= imageShape(&amp;quot;image-1.png&amp;quot;)&#xA;//lower soft magnetic layer&#xA;defregion(1, (layers(softth, Nz)))&#xA;=================== set properties of region 1 here=================&#xA;//upper hard magnetic layer&#xA;defregion(2, (layers(0, 32)))&#xA;=================== set properties of region 2 here=================&#xA;&#xA;defregion(3, fig1)&#xA;=================== set properties of the embedded geometry here=================&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This should work logically.. because you are acquiring regions, setting the parameters and then going for the regions within the previous regions.&lt;/p&gt;&#xA;&lt;p&gt;And if you need the pattern to be embedded in a soft magnetic single layer just delete region 2 and specify layer1 from 0 to 64.&lt;/p&gt;&#xA;&lt;p&gt;You can visualize the geometry by following &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2472/how-to-visualize-mumax3-shapes/2475#2475&quot;&gt;this&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-11-09T12:45:36.353" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3718" PostTypeId="2" ParentId="2043" CreationDate="2020-11-09T14:43:47.067" Score="6" Body="&lt;p&gt;It depends on your actual scenario. If we assume that you have two Molecular Dynamics (MD) replicas for the same protein (and their respective trajectories), then when you perform a Radius of Gyration (&lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt;) computation from a MD trajectory you commonly end up with a time series for the values for it, &lt;span class=&quot;math-container&quot;&gt;$R_g(t)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From &lt;span class=&quot;math-container&quot;&gt;$R_g(t)$&lt;/span&gt; you can already plot the time series of the values (always good to visualize beforehand) and, once the simulation has converged for each replica, compute a histogram/distribution, so you should end up with something like the following for each MD trajectory (so, two of them in total).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AY7n5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AY7n5.png&quot; alt=&quot;Example distribution for radius of gyration&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then you can use a statistical two-sample test like the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kolmogorov-Smirnov test&lt;/a&gt; to compare both distributions and actually assess if there is a significant statistical difference between both of them.&lt;/p&gt;&#xA;&lt;p&gt;Now, on the other hand, if what you have is just two individual values for &lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt; then I suspect you can just directly use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Approximation_error&quot; rel=&quot;nofollow noreferrer&quot;&gt;relative error&lt;/a&gt; between them (surely one of the samples can be considered a reference) to have an idea how one deviates from another. Maybe something like &lt;span class=&quot;math-container&quot;&gt;$&amp;gt;5$&lt;/span&gt; percent is significant, this is subjective.&lt;/p&gt;&#xA;" OwnerUserId="484" LastEditorUserId="484" LastEditDate="2020-11-10T03:13:45.700" LastActivityDate="2020-11-10T03:13:45.700" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3719" PostTypeId="2" ParentId="467" CreationDate="2020-11-10T02:23:45.320" Score="14" Body="&lt;h1&gt;XCrySDen&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Official website:&lt;a href=&quot;http://www.xcrysden.org/XCrySDen.html&quot; rel=&quot;noreferrer&quot;&gt;http://www.xcrysden.org/XCrySDen.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;XCrySDen is a crystalline and molecular structure visualization program aiming at the display of isosurfaces and contours, which can be superimposed on crystalline structures and interactively rotated and manipulated. It runs on GNU/Linux. It also possesses some tools for analysis of properties in reciprocal space such as the interactive selection of k-paths in the Brillouin zone for the band-structure plots and visualization of Fermi surfaces.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It can visualise chemical structures for the following ab initio simulation software:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Quantum ESPRESSO&lt;/li&gt;&#xA;&lt;li&gt;WIEN2k&lt;/li&gt;&#xA;&lt;li&gt;CRYSTAL&lt;/li&gt;&#xA;&lt;li&gt;GAUSSIAN&lt;/li&gt;&#xA;&lt;li&gt;Orca&lt;/li&gt;&#xA;&lt;li&gt;FHI98MD&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-20T13:26:18.357" LastActivityDate="2021-01-20T13:26:18.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3720" PostTypeId="1" CreationDate="2020-11-10T06:24:53.010" Score="11" ViewCount="1179" Body="&lt;p&gt;I was able to calculate band energies in quantum espresso. How to convert them to values that are in terms of difference from vacuum energy?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2023-06-21T10:41:13.720" Title="How to calculate the energy of conduction band and valence band with respect to vacuum in quantum espresso?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3721" PostTypeId="2" ParentId="3720" CreationDate="2020-11-10T08:30:41.160" Score="12" Body="&lt;p&gt;First of all, you need to find where the vacuum energy level is. To that purpose, you first need to calculate the planar average of the electrostatic potential &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2014/cp/c4cp01975j#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;like the following figure&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bXRuW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bXRuW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;from which you can find the vacuum energy level. How to obtain this figure with Quantum Espresso?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Self-consistent calculation with pw.x.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PP.html#idm22&quot; rel=&quot;nofollow noreferrer&quot;&gt;Postprocessing with pw.x.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;INPUTPP&#xA;   outdir='./tmp'&#xA;   plot_num=11&#xA;   filplot='pp11.dat'&#xA; /&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Take the planar average of the electrostatic potential with &lt;a href=&quot;https://github.com/QEF/q-e/blob/master/PP/src/average.f90&quot; rel=&quot;nofollow noreferrer&quot;&gt;average.x.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2023-06-21T10:41:13.720" LastActivityDate="2023-06-21T10:41:13.720" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3722" PostTypeId="1" AcceptedAnswerId="3725" CreationDate="2020-11-10T13:44:50.873" Score="14" ViewCount="2836" Body="&lt;p&gt;Sorry if this question is too simple for the community but I really could not find an explanation. A detailed answer would be appreciated.&lt;/p&gt;&#xA;" OwnerDisplayName="user1263" LastEditorUserId="5" LastEditDate="2020-11-10T19:10:08.053" LastActivityDate="2020-11-11T06:30:17.273" Title="High-Performance Computing: What does &quot;Mio CPUh&quot; mean?" Tags="|high-performance-computing|terminology|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3723" PostTypeId="2" ParentId="3722" CreationDate="2020-11-10T14:42:18.570" Score="16" Body="&lt;p&gt;&amp;quot;Mio&amp;quot; refers to &amp;quot;Million&amp;quot; and &amp;quot;CPUh&amp;quot; is the abbreviation of &lt;a href=&quot;http://www.gridrepublic.org/joomla/components/com_mambowiki/index.php/GFlops,_G-hours,_and_CPU_hours&quot; rel=&quot;noreferrer&quot;&gt;CPU hours&lt;/a&gt;, also refered to as &lt;a href=&quot;http://www.gridrepublic.org/joomla/components/com_mambowiki/index.php/GFlops,_G-hours,_and_CPU_hours&quot; rel=&quot;noreferrer&quot;&gt;Core hours&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is a good read if you need to know more about &lt;a href=&quot;https://epcced.github.io/hpc-intro/aio.html&quot; rel=&quot;noreferrer&quot;&gt;HPC&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is an interesting &lt;a href=&quot;https://www.reddit.com/r/explainlikeimfive/comments/3kwipw/eli5_cpu_render_time_vs_real_life_time/&quot; rel=&quot;noreferrer&quot;&gt;reddit post&lt;/a&gt; on the same topic.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2020-11-10T19:10:48.233" LastActivityDate="2020-11-10T19:10:48.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3724" PostTypeId="2" ParentId="467" CreationDate="2020-11-10T19:31:03.423" Score="18" Body="&lt;h1&gt;Avogadro&lt;/h1&gt;&#xA;&lt;p&gt;Avogadro is generally considered to be a “molecular editor,” designed to construct and view molecules and materials in 3D. It's a cross-platform software. Even when its mainly used for constructing molecules, it's also useful for creating and visualizing unit cells and slabs.&lt;/p&gt;&#xA;&lt;p&gt;These are some tutorials for constructing:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://avogadro.cc/docs/building-materials/building-a-polymer-unit-cell/&quot; rel=&quot;noreferrer&quot;&gt;Unit-cells in Avogadro&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://avogadro.cc/docs/building-materials/building-a-crystal-slab/&quot; rel=&quot;noreferrer&quot;&gt;Slabs in Avogadro&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It can also &lt;a href=&quot;https://avogadro.cc/docs/extensions/abinit-generator/&quot; rel=&quot;noreferrer&quot;&gt;generate input files&lt;/a&gt; for different DFT codes&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="30" LastEditDate="2020-12-26T20:11:42.080" LastActivityDate="2020-12-26T20:11:42.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3725" PostTypeId="2" ParentId="3722" CreationDate="2020-11-11T06:30:17.273" Score="6" Body="&lt;p&gt;HPCs work by allowing you to run jobs on many computers with many CPUs in parallel. CPUh refers to how many CPUs are being used for how long (the h in CPUh stands for hours).&lt;/p&gt;&#xA;&lt;p&gt;For instance, you may have a job that needs 64 CPUs and will run for a whole day. That would be 1536 CPU hours. The largest jobs I see on our (relatively small) HPC are 128 CPUs for about four weeks straight. That's about 86,000 CPU hours. Most of our jobs are much smaller, sometimes fractions of a CPUh.&lt;/p&gt;&#xA;&lt;p&gt;Jobs that need in the millions (Mio) CPU hours are truly massive, and would likely be running on the largest supercomputers around. You might find those jobs in weather forecasting, particle physics, government-sponsored encryption breaking, and similar applications.&lt;/p&gt;&#xA;" OwnerUserId="1515" LastActivityDate="2020-11-11T06:30:17.273" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3726" PostTypeId="2" ParentId="1512" CreationDate="2020-11-11T09:49:45.983" Score="1" Body="&lt;p&gt;I don't know of any exact methods, but &lt;a href=&quot;https://github.com/nschloe/quadpy&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;quadpy&lt;/code&gt;&lt;/a&gt; is a really good place to start, and possibly ask the related question there.&lt;/p&gt;&#xA;&lt;p&gt;Not really an answer, but more of a &lt;em&gt;hint&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2020-11-11T09:49:45.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3727" PostTypeId="2" ParentId="3710" CreationDate="2020-11-11T13:56:03.603" Score="5" Body="&lt;p&gt;If you already know the electron spatial wavefunctions, then it should be possible to calculate the spin exchange coefficients between electrons on neighboring atoms (by directly integrating them) and generate a spin-interaction-only Hamiltonian. Then you can plug it all into a QMC that is designed just to handle spin (such as Stochastic Series Expansion).&lt;/p&gt;&#xA;&lt;p&gt;The drawbacks of this approach are that &lt;strong&gt;(1)&lt;/strong&gt; you have to know the electron spatial wavefunctions in advance and &lt;strong&gt;(2)&lt;/strong&gt; your exchange coefficients might produce a &lt;em&gt;QMC sign problem&lt;/em&gt;, which means QMC would not work.&lt;/p&gt;&#xA;&lt;p&gt;I'm &lt;strong&gt;100%&lt;/strong&gt; open to feedback to help refine this answer.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-11-11T13:56:03.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3728" PostTypeId="1" AcceptedAnswerId="3731" CreationDate="2020-11-10T19:14:22.570" Score="14" ViewCount="415" Body="&lt;p&gt;I am revisiting some exercises in Thijssen's &lt;em&gt;Computational Physics&lt;/em&gt; book, particularly chapter 4 on the Hartree-Fock method. I am interested in the method of nonlinear optimisation for its own purposes, but if there is a better way to approach the problem in this context, I'd be interested in that as well. I know this is discussed in &lt;em&gt;Numerical Recipes&lt;/em&gt; (Thijssen cites it), but either I do not understand or am looking at the wrong section of the book.&lt;/p&gt;&#xA;&lt;p&gt;The problem, in brief, is to calculate the ground state wave function of the helium atom. He does this by expanding the wave function in 4 gaussian basis functions,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi({\bf r}) =\sum_{p=1}^4 C_p e^{-\alpha_p r^2},&#xA;$$&lt;/span&gt;&#xA;but he provides all &lt;span class=&quot;math-container&quot;&gt;$\alpha_p$&lt;/span&gt;s so that we have a &lt;em&gt;linear&lt;/em&gt; variational problem, which I've already successfully solved (in Fortran).&lt;/p&gt;&#xA;&lt;p&gt;However, I am wondering how he obtains these &lt;span class=&quot;math-container&quot;&gt;$\alpha_p$&lt;/span&gt;s and how I would approach such problems more generally. It seems to me that the problem gets much more messy, as we have 2 variables per basis function and of course the vector &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; is not a sufficient representation. The &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; tensor that he defines,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Q_{prqs} = \int d^3r_1d^3r_2\chi_p(r_1)\chi_r(r_2)\frac 1{|r_1-r_2|}\chi_q(r_1)\chi(r_2) &#xA;= \frac{2\pi^{5/2}}{(\alpha_p+\alpha_q)(\alpha_r+\alpha_s)\sqrt{\alpha_p+\alpha_q+\alpha_r+\alpha_s}}&#xA;$$&lt;/span&gt;&#xA;where the &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt;s are gaussians, also becomes much more complicated since it contains non-constant &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;s now. More generally, it seems like the problem is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\min_{{\bf C}, {\bf \alpha}} 2{\bf C}^Th{\bf C}+\sum_{pqrs}Q_{prqs}C_pC_qC_rC_s&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; is the independent-particle Hamiltonian, all subject to a highly nonlinear constraint &lt;span class=&quot;math-container&quot;&gt;$H{\bf C}=E'S{\bf C}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; contains these messy &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;s. There doesn't seem to be any easy way to solve this, so I was wondering where to go from here (do we simplify further, use a dual problem, or is there some kind of really powerful convex solver that I am unaware of?).&lt;/p&gt;&#xA;" OwnerUserId="1522" OwnerDisplayName="tmph" LastEditorUserId="142" LastEditDate="2020-11-21T15:18:29.410" LastActivityDate="2020-11-21T15:18:29.410" Title="Optimization of Gaussian basis sets within the Hartree-Fock Method" Tags="|basis-sets|hartree-fock|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3729" PostTypeId="5" CreationDate="2020-11-11T20:18:31.310" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-11-11T20:18:31.310" LastActivityDate="2020-11-11T20:18:31.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3730" PostTypeId="4" CreationDate="2020-11-11T20:18:31.310" Score="0" Body="For questions related to valleytronics, which uses a combination of electron spin and valleys in a materials band structure to store information" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-11-11T20:18:31.310" LastActivityDate="2020-11-11T20:18:31.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3731" PostTypeId="2" ParentId="3728" CreationDate="2020-11-12T00:27:25.540" Score="12" Body="&lt;p&gt;There are a lot of different methods, but a good starting point to understand how this might be done is the method of steepest descent. First we take the generalised eigenvalue expression you cite and rearrange to express the energy expectation value as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E=\frac{\phi^\dagger \mathrm{H}\phi}{\phi^\dagger \mathrm{S}\phi},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where I've generalised to allow complex wavefunctions for completeness, so the Hermitian conjugate (denoted by &lt;span class=&quot;math-container&quot;&gt;$\dagger$&lt;/span&gt;) has replaced the transpose in your expression.&lt;/p&gt;&#xA;&lt;p&gt;The variational principle tells us that the ground-state energy we seek is the minimum possible value of this expectation value. If we start with some trial &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and compute the energy expectation value, we may also ask how this expectation value would change if we made a small change to &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;. Differentiating the expectation value with respect to &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; using the quotient rule (where the matrix-derivative here may be interpreted as being element-wise) we obtain:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{cl}&#xA;\frac{\delta E}{\delta \phi^\dagger} &amp;amp;= \frac{\left(\phi^\dagger \mathrm{S}\phi\right)\mathrm{H}\phi - \left(\phi^\dagger \mathrm{H}\phi\right)\mathrm{S}\phi}{\left(\phi^\dagger \mathrm{S}\phi\right)^2}\\&#xA;&amp;amp;= \frac{\mathrm{H}\phi - E\mathrm{S}\phi}{\phi^\dagger \mathrm{S}\phi}.&#xA;\end{array}&#xA;$$&lt;/span&gt;&#xA;If we assume that &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; is S-orthonormalised, such that &lt;span class=&quot;math-container&quot;&gt;$\phi^\dagger \mathrm{S}\phi=I$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; is the identity) then we can write this more compactly as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{cl}&#xA;\frac{\delta E}{\delta \phi^\dagger} &amp;amp;= \mathrm{H}\phi - E\mathrm{S}\phi.&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This expression tells us the direction in which to change &lt;span class=&quot;math-container&quot;&gt;$\phi^\dagger$&lt;/span&gt; in order to &lt;em&gt;increase&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; most rapidly; since we wish to &lt;em&gt;decrease&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, we should change &lt;span class=&quot;math-container&quot;&gt;$\phi^\dagger$&lt;/span&gt; in the opposite direction.&lt;/p&gt;&#xA;&lt;p&gt;Now at this point I should note that we don't actually want to change &lt;span class=&quot;math-container&quot;&gt;$\phi^\dagger$&lt;/span&gt;, we want to change &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and there's a complication here which arises from the fact that this is a generalised eigenvalue problem. The gradient I've derived is covariant (it transforms like &lt;span class=&quot;math-container&quot;&gt;$S\phi$&lt;/span&gt; under a change of basis), and we need a contravariant quantity (transforms like &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; under a change of basis) if we're going to use it to update &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;. There are several avenues for getting this, but probably the simplest and most computationally efficient is to pre-multiply by &lt;span class=&quot;math-container&quot;&gt;$S^{-1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We may now define a direction,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = -S^{-1}\frac{\delta E}{\delta \phi^\dagger} = -S^{-1}\mathrm{H}\phi - E\phi,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in your example above, there are two ways in which we may change &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;: we can change &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;; and we can change &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. Our search direction &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; contains changes to &lt;em&gt;both&lt;/em&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{rl}&#xA;D = \left(\begin{array}{c}&#xA;D_C\\&#xA;D_\alpha&#xA;\end{array}\right)&#xA;&amp;amp;= -\left(\begin{array}{c}&#xA;\frac{\delta E}{\delta C^\dagger}\\&#xA;\frac{\delta E}{\delta \alpha}&#xA;\end{array}\right)\\&#xA;&amp;amp;= -\frac{\delta E}{\delta \phi^\dagger}\left(\begin{array}{c}&#xA;\frac{\delta \phi^\dagger}{\delta C^\dagger}\\&#xA;\frac{\delta \phi^\dagger}{\delta \alpha}\\&#xA;\end{array}\right)\\&#xA;&amp;amp;= -(H-ES)\phi\left(\begin{array}{c}&#xA;\frac{\delta \phi^\dagger}{\delta C^\dagger}\\&#xA;\frac{\delta \phi^\dagger}{\delta \alpha}&#xA;\end{array}\right)&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We may now search along the direction &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; for an improved estimate of the ground state &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;. The simplest approach is to use a line-search method, whereby we define&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi^\prime (\lambda) = \phi + \lambda D$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;by which we mean&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(\begin{array}{c}&#xA;C^\prime(\lambda)\\&#xA;\alpha^\prime(\lambda)&#xA;\end{array}\right)&#xA;= \left(\begin{array}{c}&#xA;C\\&#xA;\alpha&#xA;\end{array}\right)&#xA;+\lambda \left(\begin{array}{c}&#xA;D_C\\&#xA;D_\alpha&#xA;\end{array}\right)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now we find the minimum expectation value of the energy with respect to &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; (a 1D minimisation problem, so fairly straightforward). Note that the choice of function of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; above means that &lt;span class=&quot;math-container&quot;&gt;$\phi^\prime$&lt;/span&gt; is not orthonormalised in general, even if &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; are, which necessitates re-orthonormalisation later on. More sophisticated methods are available which do not have this side-effect.&lt;/p&gt;&#xA;&lt;p&gt;Once we have the value of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; which minimises the energy expectation value, &lt;span class=&quot;math-container&quot;&gt;$\lambda_{opt}$&lt;/span&gt;, we have an improved estimate of the ground state &lt;span class=&quot;math-container&quot;&gt;$\phi^{new}=\phi(\lambda_{opt})$&lt;/span&gt;. We may now compute the energy derivative about &lt;span class=&quot;math-container&quot;&gt;$\phi^{new}$&lt;/span&gt;, and hence a new search direction, and the procedure repeats.&lt;/p&gt;&#xA;&lt;p&gt;There is a complication in that the sensitivity to changes in &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; will be very different, leading to ill-conditioning; this can be resolved by &amp;quot;preconditioning&amp;quot; the search direction (see later on).&lt;/p&gt;&#xA;&lt;p&gt;This iterative update procedure is usually terminated when the change in solution falls below some tolerance criterion -- the change usually being measured by the change in the energy expectation value or the magnitude of the gradient.&lt;/p&gt;&#xA;&lt;p&gt;This method is relatively crude and only performs well when the expectation values associated with the underlying basis states are similar; if this is not satisfied, then the problem becomes ill-conditioned and can take many iterations to converge (it may even diverge).&lt;/p&gt;&#xA;&lt;p&gt;The conditioning is dependent on the curvature of the energy expectation with respect to &lt;span class=&quot;math-container&quot;&gt;$\phi^\dagger$&lt;/span&gt;, and if we knew what that was we could compute an improved search direction (what you do is pre-multiply the gradient by the inverse of the curvature tensor). Unfortunately in electronic structure calculations we don't usually know what the curvature is analytically, and it's very expensive to compute. However, two practical improvements are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Preconditioning -- premultiply the gradient by an &lt;em&gt;approximation&lt;/em&gt; to the inverse curvature; in the case of electronic structure calculations this would often be based on parts of the Hamiltonian which dominate in particular regimes, for example the work of Teter, Payne and Allan (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.40.12255&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.40.12255&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Quasi-Newton method -- essentially, use gradient information from previous iterations to estimate the curvature and produce an improved search direction; examples include the popular conjugate gradients and (L-)BFGS methods.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These two approaches may be combined, and preconditioned quasi-Newton methods can be extremely efficient. Quasi-Newton methods are fairly standard across optimisation problems and you'll see the same methods cropping up time and time again; in contrast, finding a good preconditioning approach will require careful thought about the behaviour of your particular problem, so different approaches are employed in different domains.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2020-11-13T02:02:21.887" LastActivityDate="2020-11-13T02:02:21.887" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3732" PostTypeId="2" ParentId="2482" CreationDate="2020-11-12T00:57:16.110" Score="6" Body="&lt;p&gt;When you see charge densities plotted in the literature, they are usually plotting particular isosurfaces (contours) and are trying to show &amp;quot;where the electrons are&amp;quot;. Charge density differences can be useful in trying to understand the changes in a system, for example charge transfer as a molecule approaches a surface (although this often isn't very accurate with common XC functionals). Plotting spin-densities can be very useful to see where the regions of magnetism are, and what nature of magnetism is present (e.g. ferromagnetic or antiferromagnetic).&lt;/p&gt;&#xA;&lt;p&gt;People often try to use the electron density as a proxy quantity for other properties. For example, if you think there should be a covalent bond between layers, then you would expect to find significant electron density in the inter-layer region. If indeed there is a high electron density in this region, then you might argue that this is evidence of a strong bond. In my opinion this is not a very strong argument, because it assumes local interaction with the density, whereas layers could be interacting strongly via non-local interactions (Coulomb interactions such as in ionic materials, for example, or van der Waals interactions) in which case there is no need for a high electron density in the inter-layer region. In fact it is trivial to compute the inter-layer force constant and essentially &amp;quot;measure&amp;quot; the strength of the interaction, so I would always prefer that.&lt;/p&gt;&#xA;&lt;p&gt;Note that, in principle, the ground state density tells you &lt;em&gt;everything&lt;/em&gt; about the ground state of the system -- this is essentially the 1st Hohenberg-Kohn theorem. However, in practice this is not as useful as it may appear at first, since we don't actually know &lt;em&gt;how&lt;/em&gt; most of the properties depend on the density, just that they do!&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-12T00:57:16.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3733" PostTypeId="2" ParentId="3636" CreationDate="2020-11-12T01:30:51.393" Score="9" Body="&lt;p&gt;I assume you mean including a Hubbard U potential within a Kohn-Sham density functional theory (DFT) calculation. The main reason why you might wish to do this is because you are studying a material for which you expect a significant self-interaction error.&lt;/p&gt;&#xA;&lt;p&gt;The self-interaction error arises because the Hartree term in the DFT energy functional is the Coulomb interaction of the whole density with itself,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_H = \frac{1}{2}\iiint{ \frac{\rho(\bf r)\rho(\bf r^\prime)}{4\pi\epsilon_0\left\vert {\bf r}-{\bf r^\prime}\right\vert} d^3{\bf r}d^3{\bf r^\prime}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This density has contributions from every particle, which means that there is a contribution to the energy associated with a particle interacting with itself - this is unphysical!&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;true&amp;quot; exchange-correlation functional would remove this spurious &lt;em&gt;self-interaction&lt;/em&gt; and everything would be fine, but the approximate functionals can only remove the self-interaction approximately. If you look at the form of &lt;span class=&quot;math-container&quot;&gt;$E_H$&lt;/span&gt; you can see that the self-interaction will be strongest when a particle's density is large, and since the total particle density must integrate to 1 this typically means the particle is strongly localised.&lt;/p&gt;&#xA;&lt;p&gt;The usual cases where a Hubbard U should be considered are when modelling systems with d- or f-states, especially if they are partially filled. These states should usually be strongly localised, moderately low energy states (shallow core states), but because of the self-interaction their energy is raised spuriously and partially delocalised (because this reduces the self-interaction energy). It is not unusual for the energy of partially filled d- or f-states to be raised enough for them to approach the Fermi level, &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;, and hybridise with bonding states. There are other cases where these effects are significant (e.g. the N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; triple-bond); the rule of thumb is that you need to worry about it whenever there are localised regions of high density arising from small particle numbers.&lt;/p&gt;&#xA;&lt;p&gt;On a lighter note, I wrote a limerick to help people remember the key aspects:&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;I once had some d-states I knew&lt;br /&gt;&#xA;should be found at low E, not near &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;&lt;br /&gt;&#xA;this spurious reaction&lt;br /&gt;&#xA;to self-interaction&lt;br /&gt;&#xA;was cured with a small Hubbard U&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;For actually &lt;em&gt;computing&lt;/em&gt; an appropriate Hubbard U, I refer you to the discussion here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/109/671&quot;&gt;What is the appropriate way of determining a value for the Hubbard-like potential U for LDA+U / GGA+U calculations?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;NB using a Hubbard U is computationally efficient, but it is not the only way to solve this. One alternative method is to use a screened exchange functional, which explicitly removes self-interaction at short ranges (where the worst effects arise).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-12T01:30:51.393" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3734" PostTypeId="2" ParentId="119" CreationDate="2020-11-12T02:41:53.883" Score="10" Body="&lt;p&gt;In orbital-free DFT, the key quantity is the particle density (not the density matrix, the actual density). The particle density is a scalar 3D field; when we increase the particle number in our simulation, the values of the particle density change, subject to the constraint that for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; particles in a volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; of space,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\iiint_V \rho({\bf r})d^3{\bf r} = N.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Although the &lt;em&gt;values&lt;/em&gt; change if &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; changes, the density remains a 3D scalar field and takes up the same amount of computer storage. The size of the density does not depend on the number of particles and so scales as O(1) in particle count -- better than linear scaling!&lt;/p&gt;&#xA;&lt;p&gt;If we increase the simulation volume instead, then the density now extends over a greater volume and clearly the 3D field must be extended over the additional space. The size of the density scales linearly with the simulation volume, since the volume directly controls how much space we have to represent with our density.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully you can now see why the &lt;em&gt;size&lt;/em&gt; of the density object scales linearly with system size. The size of a data object gives a lower bound for the computational time, assuming that every element of the object has to be checked at least once. However, there is no guarantee that the computational time &lt;em&gt;does&lt;/em&gt; scale linearly with system size. It is easy to construct functionals whose computational cost scales far worse than the size of the data object, for example multiple nested integrals over all spatial dimensions. I think the argument for linear-scaling computational time is based on using a semi-local energy functional; even including a Hartree term makes the calculation worse than linear-scaling, strictly speaking, although most people wouldn't complain about the extra factor of &lt;span class=&quot;math-container&quot;&gt;$\log(N)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note that whether orbital-free methods scale linearly or not is unrelated to whether the material being simulated is an insulator or a metal. This is in contrast to most &amp;quot;linear-scaling DFT&amp;quot; approaches, which rely on the density &lt;em&gt;matrix&lt;/em&gt; decaying exponentially in real-space in order to truncate it safely, which is only valid for systems with a band-gap. Orbital-free methods do not use the density-matrix, so are not subject to the same constraints; in fact the most successful applications of orbital-free DFT are mostly to high-temperature metals (e.g. liquid sodium); even Thomas-Fermi(-Dirac) can perform reasonably in these situations, yet they are amongst the worst cases for density-matrix-based linear-scaling DFT.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2020-11-13T02:05:04.210" LastActivityDate="2020-11-13T02:05:04.210" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3736" PostTypeId="1" CreationDate="2020-11-12T15:33:20.180" Score="10" ViewCount="189" Body="&lt;p&gt;How can I simulate the work function given by Ultraviolet Photoelectron Spectrum (UPS) of a molecule or a molecular crystal?&lt;/p&gt;&#xA;&lt;p&gt;I thought it is an easy job: Just do a geometry optimization and get the energy of the neutral molecule and then using the same geometry to get the energy of the cation, the difference in energy can be the UPS given ionization energy.  However&#xA;I read a &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.200390065&quot; rel=&quot;nofollow noreferrer&quot;&gt;review&lt;/a&gt;, where what UPS can measure is discussed.&lt;/p&gt;&#xA;&lt;p&gt;It is said that what UPS gives is like &lt;span class=&quot;math-container&quot;&gt;$$\phi_{\rm m}=E_{\rm vac}(s)-E_{\rm F},$$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$$E_{\rm vac}(\infty)-E_{\rm VB},$$&lt;/span&gt;&#xA;which can be computed using the procedure I described. The symbols are&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{\rm vac}(s)$&lt;/span&gt;: vacuum level of a finite-size sample&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{\rm vac}(\infty)$&lt;/span&gt;: vacuum level at infinity&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{\rm F}$&lt;/span&gt;: Fermi level&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{\rm VB}$&lt;/span&gt;: top of valence band, or in molecular system, energy of neutral species, or, if we stuck to molecular orbital theory, HOMO.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I am confused in the following points&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Why the Fermi level instead of HOMO are measured since in some case no electrons occupies Fermi level?&lt;/li&gt;&#xA;&lt;li&gt;How can I compute the &lt;span class=&quot;math-container&quot;&gt;$E_{\rm vac}(s)$&lt;/span&gt; using quantum chemistry software packages?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="339" LastEditorUserId="339" LastEditDate="2020-11-14T06:59:39.790" LastActivityDate="2020-11-14T06:59:39.790" Title="How can I simulate the work function given by Ultraviolet Photoelectron Spectrum (UPS)?" Tags="|electronic-structure|spectroscopy|fermi-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3737" PostTypeId="1" AcceptedAnswerId="3746" CreationDate="2020-11-12T15:35:57.450" Score="11" ViewCount="105" Body="&lt;p&gt;I want to study the effect of nitrogen interstitials on oxygen diffusion in metals and vice-versa. Would you suggest MSD calculations in LAMMPS to be a viable method for this? There aren't many interatomic potentials for different metals with N and O, so I am unsure where to start as well.&lt;/p&gt;&#xA;&lt;p&gt;Any pointers would be a huge help, thanks.&lt;/p&gt;&#xA;" OwnerUserId="1527" LastActivityDate="2020-11-13T09:08:37.893" Title="Modelling nitrogen interstitial barrier to oxygen diffusion in metals" Tags="|lammps|metals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3738" PostTypeId="2" ParentId="3687" CreationDate="2020-11-12T17:01:16.450" Score="3" Body="&lt;p&gt;Very interesting question. I have no experience doing EDA, but as I'll probably  need to do it in the future, I used your question as a starting point to learn more about it. I did some research, but unfortunately could not find clear guidance on how to set the charges. In the Gamess (US) user group, a user called Marcela Tormena posted a small but detailed &lt;a href=&quot;https://groups.google.com/g/gamess/c/tot3apbncwE/m/bWwocAZBBwAJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt; on how to do EDA on a transition state. But her example system involved only neutral species, so there was no advice on charge assignment.&lt;/p&gt;&#xA;&lt;p&gt;I also found a article[1] suggesting a split in 3 fragments, with both attacking and leaving groups charged -1, and the central part charged +1, adding to a net charge of -1:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Thirdly, the particular choice of molecular fragments for the EDA needs&#xA;attention, because the absolute values of each of the energy terms will&#xA;depend intimately on this.Here we consider that the correspondence&#xA;between the energies and properties of the TS as well as the reactant&#xA;and product states of the SN2 reaction Y(-) + RX --&amp;gt; X(-)- + RY&#xA;can best be characterised from the fully separated fragments X(-) +&#xA;R(+) + Y(-).[21] Our choice of fragments differs from that used by&#xA;Bickelhaupt and co-workers, who decomposed the energy of interaction of&#xA;X- and RY. In addition to comparing all energies to common origin, our&#xA;approach has the ad-vantage of eliminating the use of activation&#xA;strain analysisas introduced by Bickelhaupt.[32]Moreover, we think&#xA;that it is more realistic to consider the nascent and the breaking bonds&#xA;simultaneously because they are closely associated with each other.&#xA;This holds in particular for the transition structure in which the two&#xA;bonds are equally important.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Note in his systems, both nucleophile and leaving group are the same, while in yours these are different species, so I don't know if the same consideration applies.&lt;/p&gt;&#xA;&lt;p&gt;While not a definitive answer, I hope this is helpful.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Fernández, Israel, et al. “The Interplay between Steric and Electronic Effects in SN2 Reactions.” Chemistry – A European Journal, vol. 15, no. 9, 2009, pp. 2166–75. Wiley Online Library, doi:&lt;a href=&quot;https://doi.org/10.1002/chem.200801833&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1002/chem.200801833&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2020-11-12T17:07:19.097" LastActivityDate="2020-11-12T17:07:19.097" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3739" PostTypeId="2" ParentId="163" CreationDate="2020-11-12T17:20:51.657" Score="17" Body="&lt;p&gt;Pure plane-wave basis sets have the following advantages when used in periodic DFT (or HF) simulations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Orthogonal&lt;/li&gt;&#xA;&lt;li&gt;Computationally simple (operators with derivatives are particularly straightforward)&lt;/li&gt;&#xA;&lt;li&gt;Low-scaling methods allow easy transformations between real- and reciprocal-space&lt;/li&gt;&#xA;&lt;li&gt;Basis set size does not scale with electron count&lt;/li&gt;&#xA;&lt;li&gt;Independent of atomic positions&lt;/li&gt;&#xA;&lt;li&gt;Their accuracy is controlled with a single parameter, and it is systematically improvable&lt;/li&gt;&#xA;&lt;li&gt;Model all space with equal accuracy&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However there are some disadvantages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Basis set size scales with simulation volume - vacuum is not &amp;quot;free&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;Basis sets are usually large &amp;quot;per atom&amp;quot; - it is not usually practical to construct the full Hamiltonian explicitly (or any other operator) and you must solve the eigenequations iteratively&lt;/li&gt;&#xA;&lt;li&gt;Model all space with equal accuracy - no scope for focusing effort on &amp;quot;interesting&amp;quot; regions&lt;/li&gt;&#xA;&lt;li&gt;Extend throughout space (no simple real-space truncation possible in integrals - e.g. the Fock operator is computationally expensive)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In contrast, (periodic) local basis sets generally have the following advantages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Basis set size does not scale with simulation volume&lt;/li&gt;&#xA;&lt;li&gt;Basis set is typically &lt;em&gt;compact&lt;/em&gt;, with few basis states &amp;quot;per atom&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;Model space with variable accuracy - basis can be tuned to improve representation in regions of interest, and reduce accuracy in uninteresting regions&lt;/li&gt;&#xA;&lt;li&gt;Basis functions are local, and real-space truncations are straightforward in multi-basis set integrals&lt;/li&gt;&#xA;&lt;li&gt;Some basis choices (e.g. Gaussians) allow analytic integration of some energy terms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and the following disadvantages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Non-orthogonal&lt;/li&gt;&#xA;&lt;li&gt;Computationally complicated (often)&lt;/li&gt;&#xA;&lt;li&gt;They depend on the atomic positions (leading to Pulay forces)&lt;/li&gt;&#xA;&lt;li&gt;Basis set size scales with electron count&lt;/li&gt;&#xA;&lt;li&gt;Model space with variable accuracy - need to decide a priori where to spend the computational effort, i.e. which regions are &amp;quot;interesting&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;No single parameter to control their accuracy; not always systematically improvable&lt;/li&gt;&#xA;&lt;li&gt;Some basis set choices are not easy to transform between real- and reciprocal-space&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Roughly speaking, plane-wave methods are efficient when computing and applying the terms of the Hamiltonian, but lead to a much larger dimensionality in the eigenvalue problem and must compute a subset of states; local basis sets often take more time constructing the eigenvalue problem, but it is quite compact and can be solved directly (e.g. with LAPACK) to generate the full eigenspectrum.&lt;/p&gt;&#xA;&lt;p&gt;There is no reason in principle why you cannot use a hybrid approach (e.g. like CP2K) whereby you transform to a different basis set to perform certain parts of the calculation. You can gain some of the advantages of both, but unfortunately you may suffer from some of the disadvantages of both as well -- for example, when switching from plane-waves to Gaussians the Fock operator becomes much more compact and computationally tractable, but you need to ensure that there are Gaussians in all the &amp;quot;interesting&amp;quot; regions of space. The computational cost of the transformation can also be problematic.&lt;/p&gt;&#xA;&lt;p&gt;Two final comments:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;Muffin tin&amp;quot; programs use mixed basis sets, using localised basis functions to represent the regions of space near nuclei, and plane-waves in the interstitial regions. This is efficient in both regions, but matching the descriptions at the boundaries can be tricky&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Wannier transformations allow a &amp;quot;lossless&amp;quot; transformation of the occupied Kohn-Sham states from a plane-wave representation to a local representation. However, the transformation scales cubically and is not well-conditioned, usually relying on a &amp;quot;guess&amp;quot; transformation which would be generated from a local basis set (typically LCAO)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2020-11-13T01:44:04.323" LastActivityDate="2020-11-13T01:44:04.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3740" PostTypeId="2" ParentId="3712" CreationDate="2020-11-12T19:36:18.067" Score="9" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I'm trying to generate these descriptors for QM9 dataset molecules.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://figshare.com/collections/Quantum_chemistry_structures_and_properties_of_134_kilo_molecules/978904&quot; rel=&quot;noreferrer&quot;&gt;XYZ files&lt;/a&gt; are available for the QM9 dataset. It would be more sensible to run SOAP on these geometries. As mentioned, the SOAP descriptor only makes sense when you have the co-ordinates of the atoms in your molecule, and there's no strict unambiguous mapping from SMILES to atomic co-ordinates, and methods that do exist do not give you a relaxed (equilibrium) geometry in any case.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is the best python package to construct Smooth Overlap of Atomic Positions (SOAP) descriptors given SMILES representation of a molecule?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you do want to work from a SMILES string, &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;Open Babel&lt;/a&gt; can do this with its &lt;code&gt;gen3D&lt;/code&gt; option and there is an Open Babel Python package available. Once you have your co-ordinates, &lt;a href=&quot;https://singroup.github.io/dscribe/latest/&quot; rel=&quot;noreferrer&quot;&gt;dscribe&lt;/a&gt; would be a great library to use to calculate the SOAP descriptors, although other libraries are available.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2020-11-12T19:36:18.067" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3741" PostTypeId="2" ParentId="3709" CreationDate="2020-11-12T19:52:02.340" Score="7" Body="&lt;p&gt;In simple terms, the charge density gives you the probability of finding an electron at a given point, while the electron localization function (ELF) gives you the probability of finding &lt;em&gt;another&lt;/em&gt; electron at that same point, therefore it is very sensitive to open shell / shared electron interactions.&lt;/p&gt;&#xA;&lt;p&gt;The ELF equals 0.5 for a metallic-like electron density, and goes to 1 for highly-localized electrons (lone pairs, covalent bonds).&lt;/p&gt;&#xA;&lt;p&gt;More formally, the ELF is related to the kinetic energy density, and can be thought of as the excess kinetic energy density as a result of Pauli exclusion.&lt;/p&gt;&#xA;&lt;p&gt;There are many methods to try to obtain a chemically intuitive picture of bonding from the outputs of a Density Functional Theory (DFT) calculation, such as the ELF, but also QTAIM/Bader methods. These methods are only indicators, there is no single unambiguous way to back out a chemically intuitive picture of bonding from a DFT calculation. Each has its own trade-offs and their own advocates.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1380732307800069&quot; rel=&quot;noreferrer&quot;&gt;This chapter&lt;/a&gt; is a nice reference for further reading, and &lt;a href=&quot;http://www2.cpfs.mpg.de/ELF/index.php?content=01quant/02dens.txt&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt; also has a nice summary.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2020-11-12T19:52:02.340" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3742" PostTypeId="2" ParentId="3710" CreationDate="2020-11-12T21:40:27.490" Score="5" Body="&lt;p&gt;In addition to those listed, &lt;a href=&quot;https://spinw.org&quot; rel=&quot;noreferrer&quot;&gt;Spin-W&lt;/a&gt; is another option:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;SpinW is a MATLAB library that can plot and numerically simulate magnetic structures and excitations of given spin Hamiltonian using classical Monte Carlo simulation and linear spin wave theory.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;SpinW also has a Python library available, although this is not yet a first-class citizen (you can't &lt;code&gt;pip&lt;/code&gt; install it).&lt;/p&gt;&#xA;&lt;p&gt;There's also the &lt;a href=&quot;http://alps.comp-phys.org/mediawiki/index.php/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;ALPS&lt;/a&gt; library and related projects like &lt;a href=&quot;http://alpscore.org&quot; rel=&quot;noreferrer&quot;&gt;ALPSCore&lt;/a&gt;, although these may be more useful if you're writing your own simulation code.&lt;/p&gt;&#xA;&lt;p&gt;All these codes give similar capabilities, namely that if you have a model Hamiltonian (e.g. a simple Heisenberg model) you can perform simulations of large system sizes (such as nanoparticles) at finite temperature and derive relevant thermodynamic information, usually via Monte Carlo. Calculation accuracy will be limited by the accuracy of the underlying Hamiltonian. To calculate the Hamiltonian parameters (e.g., for the Heisenberg model, your &lt;span class=&quot;math-container&quot;&gt;$J_{ij}$&lt;/span&gt; terms) will usually require a first-principles method such as DFT.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2020-11-12T21:40:27.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3743" PostTypeId="2" ParentId="2472" CreationDate="2020-11-12T21:54:04.230" Score="3" Body="&lt;p&gt;The web-app interface (Mumax-View) mentioned in the previous answer is fine. However, you could try to use &amp;quot;Muview&amp;quot; locally on your computer. You could find the software &lt;a href=&quot;https://github.com/grahamrow/Muview2/releases&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. This is a very useful software to visualize the spin configuration of the geometry.&lt;/p&gt;&#xA;" OwnerUserId="1505" LastActivityDate="2020-11-12T21:54:04.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3744" PostTypeId="1" CreationDate="2020-11-12T22:38:53.607" Score="10" ViewCount="254" Body="&lt;p&gt;Lattice dynamics codes like &lt;code&gt;Phonopy&lt;/code&gt; output density of states, &lt;span class=&quot;math-container&quot;&gt;$g_{(\omega)}$&lt;/span&gt;, as a function of frequency. Since &lt;span class=&quot;math-container&quot;&gt;$\int g_{(\omega)}d\omega$&lt;/span&gt; is the number of states between &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d\omega$&lt;/span&gt;, can the same be extended to &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\epsilon = 2\pi\omega$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;To put it briefly: Are &lt;span class=&quot;math-container&quot;&gt;$g_{(\omega_i)}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g_{(\epsilon_i)}$&lt;/span&gt; the same for &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i = 2\pi\omega_i$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Intuitively, a phonon vibrating at &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; will have an energy of &lt;span class=&quot;math-container&quot;&gt;$\epsilon = 2\pi\omega$&lt;/span&gt;, so the number of states between &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d\omega$&lt;/span&gt; should be the same as that between &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d\epsilon$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\epsilon = 2\pi\omega$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d\epsilon = 2\pi d\omega$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One way I see this intuition being wrong is &lt;span class=&quot;math-container&quot;&gt;$d\epsilon \ne 2\pi d\omega$&lt;/span&gt; but &lt;span class=&quot;math-container&quot;&gt;$\epsilon = 2\pi\omega$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;All of this sprang up into my head while I was trying to calculate harmonic and quasi-harmonic properties from the &lt;code&gt;Phonopy&lt;/code&gt; output.&lt;/p&gt;&#xA;&lt;p&gt;I'm confused (which might be apparent from the overuse of the equation &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\epsilon = 2\pi\omega$&lt;/span&gt;&amp;quot; in the post). Will be glad to get some insight. Also, please feel free to rewrite the post in a way that those redundant equations can be removed.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I understand &lt;span class=&quot;math-container&quot;&gt;$d\epsilon \ne 2\pi d\omega$&lt;/span&gt; sounds silly. To make it sound less silly, &lt;a href=&quot;https://gofile.io/d/mY8qtd&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; are phonopy output files for Ni&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;Al. Can you try and find the zero-point energy? It doesn't match with what the code outputs. Here is what I tried:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import math&#xA;&#xA;def main():&#xA;&#xA;    kB = 1.380649 * (10**-23) #Boltzmann Cconstant (J/K)&#xA;&#xA;    hbar = 1.054571817 * (10**-34) #Planck's constant (hbar in J.s)&#xA;&#xA;    NA = 6.02214 * (10**23) #Avogadro's number (per mole)&#xA;&#xA;    num_atoms = 4 #Number of atoms in the primitive cell that Phonopy finds, equal to natoms in thermal_properties.yaml&#xA;&#xA;    with open('freq.dat') as f: #freq.dat = cat mesh.yaml | grep frequency&#xA;&#xA;        lines = f.readlines() #Store each line in the list lines&#xA;&#xA;        A = np.empty(len(lines), dtype = float) #Create an empty array A to store the contents of the file&#xA;&#xA;        for i in range(len(lines)):&#xA;            A[i] = float(lines[i].split()[1])&#xA;&#xA;    for i in range(len(A)):&#xA;        A[i] = A[i] * 2 * math.pi * (10**12) #Convert frequency (THz) to angular frequency (radians/s)&#xA;        A[i] = (A[i] * hbar) / 1000 #Convert angular frequency (radians/s) to energy (KJ)&#xA;&#xA;    #Calculate the Zero Point Energy (ZPE) (KJ/mol)&#xA;    ZPE = 0&#xA;&#xA;    for i in range(len(A)):&#xA;        ZPE = ZPE + (A[i] / 2) #(A[i] / 2) = hbar x omega / 2&#xA;    ZPE = (ZPE * NA) / (num_atoms)&#xA;    print(&amp;quot;ZPE = {0}&amp;quot;.format(ZPE))&#xA;&#xA;if __name__ == '__main__':&#xA;    main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-01-22T20:50:27.517" LastActivityDate="2021-01-22T20:50:27.517" Title="Phonon density of states as a function of frequency vs energy" Tags="|phonons|phonopy|lattice-dynamics|phonon-density-of-state|quasi-harmonic-approximation|" AnswerCount="0" CommentCount="3" ClosedDate="2021-09-05T23:10:53.357" ContentLicense="CC BY-SA 4.0" />
  <row Id="3745" PostTypeId="2" ParentId="3728" CreationDate="2020-11-13T00:41:32.700" Score="8" Body="&lt;p&gt;Short answer: don't do it.&lt;/p&gt;&#xA;&lt;p&gt;While optimizing the exponents in a basis set for your system is possible in principle, the optimization is very expensive. You may also end up ruining the accuracy of your properties, since the basis set may become biased.&lt;/p&gt;&#xA;&lt;p&gt;Basis sets of various quality are routinely available in the literature. Instead of reoptimizing the primitive basis, it is much cheaper to just use a bigger basis set i.e. more exponents from the start.&lt;/p&gt;&#xA;&lt;p&gt;How are the basis sets in the literature formed? Often, the construction of basis sets starts from atomic calculations. At a later stage, the sets are tested in molecular calculations, and higher-angular-momentum basis functions are added to describe polarization effects.&lt;/p&gt;&#xA;&lt;p&gt;Phil's answer above explains how to do multidimensional optimization in general. However, since solving the self-consistent field problem with respect to the orbital coefficients &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; is often quite tricky, and since you might also be interested in running calculations at post-Hartree-Fock levels of theory, usually the exponent optimization is just taken out of the electronic structure calculation. Namely, for each set of exponents &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\alpha}$&lt;/span&gt; you can solve for the electronic wave function &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; and the resulting energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;. You can determine the gradient &lt;span class=&quot;math-container&quot;&gt;$\nabla_{\boldsymbol{\alpha}}E$&lt;/span&gt; either analytically from the energy expression, or by finite differences. The multidimensional optimization for &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\alpha}$&lt;/span&gt; is often realized with the L-BFGS method.&lt;/p&gt;&#xA;&lt;p&gt;Full optimization is, however, often not required. Once you have enough exponents, the ones in the middle start to follow a linear sequence in &lt;span class=&quot;math-container&quot;&gt;$\log \alpha$&lt;/span&gt;. Even-tempering is often a very good starting point for basis sets; probably the majority of basis sets that have been published use even-tempering.&lt;/p&gt;&#xA;&lt;p&gt;In the even tempering scheme, you define your sets in terms of just two parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta&amp;gt;1$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\alpha_i = \alpha_0 \beta^i$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$i\in[0,N-1]$&lt;/span&gt;. In the limit of a complete basis, &lt;span class=&quot;math-container&quot;&gt;$N\to\infty$&lt;/span&gt;, one has &lt;span class=&quot;math-container&quot;&gt;$\alpha_0 \to -\infty$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta\to1$&lt;/span&gt;. Now instead of optimizing &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; exponents, it suffices to optimize just the two parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to be more accurate, you can throw in &lt;span class=&quot;math-container&quot;&gt;$k\in[1,N]$&lt;/span&gt; more parameters. The exponent optimization is well-behaved if you express them in a basis of Legendre polynomials, see &lt;a href=&quot;https://doi.org/10.1063/1.1516801&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 118, 1101 (2003)&lt;/a&gt;. Note, however, that the possibility of landing on a local minimum instead of the global one increases as a function of the number of parameters!&lt;/p&gt;&#xA;&lt;p&gt;PS. I have recently suggested an even simpler scheme to forming accurate basis sets from a simple physical principle, requiring no electronic structure calculations at all, see &lt;a href=&quot;https://doi.org/10.1063/1.5144964&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 152, 134108 (2020)&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/2001.04224&quot; rel=&quot;noreferrer&quot;&gt;arXiv:2001.04224&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-11-13T00:41:32.700" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3746" PostTypeId="2" ParentId="3737" CreationDate="2020-11-13T09:08:37.893" Score="9" Body="&lt;p&gt;I assume that you want to model how the oxygen atom migrates or diffuses in the interstitial region of Ni-based metal. With the LAMMPS package, you are trying to solve this problem with classical molecular dynamics. How to interatomic potentials is important but kind of tricky. However, you can use the Nudged Elastic Band (NEB) method to find the migration path from the angle of the fist-principles.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The nudged elastic band (NEB) is a method for finding saddle points and minimum energy paths between known reactants and products. The method works by optimizing a number of intermediate images along the reaction path. Each image finds the lowest energy possible while maintaining equal spacing to neighboring images. This constrained optimization is done by adding spring forces along with the band between images and by projecting out the component of the force due to the potential perpendicular to the band.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In detail, you can use this method in the VASP package with &lt;a href=&quot;https://theory.cm.utexas.edu/vtsttools/neb.html&quot; rel=&quot;noreferrer&quot;&gt;the VTST function.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-13T09:08:37.893" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3747" PostTypeId="2" ParentId="3736" CreationDate="2020-11-13T13:30:41.347" Score="9" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You can use &lt;a href=&quot;https://galore.readthedocs.io/en/latest/readme.html&quot; rel=&quot;noreferrer&quot;&gt;Galore package&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Galore is a package which applies Gaussian and Lorentzian broadening to data from ab initio calculations, such as VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The two main intended applications are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Gaussian and Lorentzian broadening of electronic density-of-states, with orbital weighting to simulate UPS/XPS/HAXPES measurements.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Application of Lorentzian instrumental broadening to simulated Raman spectra from DFPT calculations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://galore.readthedocs.io/en/latest/tutorials.html&quot; rel=&quot;noreferrer&quot;&gt;On the tutorial page&lt;/a&gt;, you will find a UPS example with SnO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-13T13:30:41.347" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3748" PostTypeId="2" ParentId="2398" CreationDate="2020-11-13T15:04:51.257" Score="4" Body="&lt;p&gt;Turns out that it works with a simple addition of -ntomp and -np flags in the last line. Though I still do not know the answer to why it wouldn't run if not for them, when it can work for the higher number of processors like 40 or 80.&lt;/p&gt;&#xA;&lt;p&gt;The edited  script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#PBS -e errorfile.err&#xA;#PBS -o logfile.log&#xA;#PBS -l walltime=24:00:00&#xA;#PBS -l select=4:ncpus=6&#xA;cd $PBS_O_WORKDIR&#xA;module load intel2020 gromacs2020.1&#xA;gmx mdrun -ntomp 6 -ntmpi 4 -s npt.tpr -deffnm npt -v &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="148" LastActivityDate="2020-11-13T15:04:51.257" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3749" PostTypeId="2" ParentId="1688" CreationDate="2020-11-13T17:13:13.397" Score="7" Body="&lt;p&gt;Conventional implementations of Kohn-Sham DFT scale cubically with system size. This is principally because at some point they:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;orthonormalise a set of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; trial states, each expressed in a basis comprising &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; basis states; this has a computational cost &lt;span class=&quot;math-container&quot;&gt;$O(MN^2)+O(N^3)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;diagonalise a dense Hamiltonian matrix in the subspace of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; trial states, which has computational cost &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The number of basis states in the basis, &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;, also scales with simulation size. Precisely &lt;em&gt;how&lt;/em&gt; it scales with simulation size depends on the nature of the basis set; for example, in plane-wave bases the number of states is proportional to the simulation volume, whereas in local basis sets it is proportional to the number of electrons.&lt;/p&gt;&#xA;&lt;p&gt;The problem can be recast in terms of the density matrix, rather than the trial states directly, and for systems with a band-gap the off-diagonal terms in the real-space density-matrix &lt;span class=&quot;math-container&quot;&gt;$D({\bf r},{\bf r^\prime})$&lt;/span&gt; decay exponentially with distance &lt;span class=&quot;math-container&quot;&gt;$\vert{\bf r}-{\bf r^\prime}\vert$&lt;/span&gt;. This allows the density matrix to be truncated safely beyond some chosen cut-off distance which, in turn, allows &lt;em&gt;linear&lt;/em&gt; scaling methods to be used.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-13T17:13:13.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3750" PostTypeId="2" ParentId="1667" CreationDate="2020-11-14T02:06:04.087" Score="8" Body="&lt;p&gt;On the specific subject of the &amp;quot;EDIT&amp;quot;, this was exactly the concern addressed by Mel Levy in the 1970s, e.g.&lt;/p&gt;&#xA;&lt;p&gt;M. Levy, &amp;quot;Universal variational functionals of electron densities, first-order density matrices, and natural spin-orbitals and solution of the v-representability problem&amp;quot;, &lt;em&gt;PNAS&lt;/em&gt; &lt;strong&gt;76 (12)&lt;/strong&gt; 6062-6065 (1979); &lt;a href=&quot;https://doi.org/10.1073/pnas.76.12.6062&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1073/pnas.76.12.6062&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The original Hohenberg-Kohn proof relied on several conditions, some of which were explicit (non-degenerate ground state) and some were implicit (N-representability, v-representability). Mel Levy's proof of the theorem is much more general and robust, but it is also rather longer and involved, which may be why people often still present the original, restricted proof.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-14T02:06:04.087" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3752" PostTypeId="1" AcceptedAnswerId="3784" CreationDate="2020-11-14T14:13:32.250" Score="12" ViewCount="316" Body="&lt;p&gt;This question is inspired by &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3636/how-to-calculate-the-potential-in-hubbard-u-correction-and-when-to-apply-it/3733?noredirect=1#comment6185_3733&quot;&gt;this post.&lt;/a&gt; In the Kohn-Sham framework of density functional theory, the total energy is expressed as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E=E_{kin}^{non}+E_{ext}+E_{H}+E_{xc}$$&lt;/span&gt;&#xA;in which&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The first term is the kinetic energy of the non-interacting system:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E^{non}_{kin}=-\dfrac{1}{2}\sum_i^{n}\phi_i^*(\vec{r})\nabla^2\phi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The second term is the external energy:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_{ext}=\int\phi^*(\vec{r})U_{ext}(\vec{r})\phi(\vec{r}) d\vec{r}=\int U_{ext}(\vec{r})\rho(\vec{r})d\vec{r}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The third term is the Hartree energy:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_H=\dfrac{1}{2}\int \int \dfrac{\rho(\vec{r})\rho(\vec{r}')}{|\vec{r}-\vec{r}'|}d\vec{r}d\vec{r}'$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The last term is the exchange-correlation term needs to be approximated, such as LDA, which includes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Exchange energy;&lt;/li&gt;&#xA;&lt;li&gt;Correlation energy;&lt;/li&gt;&#xA;&lt;li&gt;The kinetic energy difference between the interacting system and the non-interacting system;&lt;/li&gt;&#xA;&lt;li&gt;The self-interaction error in the Hartree energy.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3636/how-to-calculate-the-potential-in-hubbard-u-correction-and-when-to-apply-it/3733?noredirect=1#comment6185_3733&quot;&gt;In this post,&lt;/a&gt; Phil Hasnip has claimed that including a Hubbard U potential within a Kohn-Sham density functional theory (DFT) calculation is to study a material for which you expect a significant self-interaction error.&lt;/p&gt;&#xA;&lt;p&gt;So is there any other interesting physics contained in the exchange-correlation functional in the framework of KS-DFT?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-11-15T01:06:23.273" LastActivityDate="2020-11-21T15:27:30.607" Title="What's the physics contained in the exchange-correlation functional in the framework of KS-DFT?" Tags="|density-functional-theory|ab-initio-calculations|kohn-sham|exchange-correlation|self-interaction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3753" PostTypeId="1" CreationDate="2020-11-15T18:05:06.587" Score="14" ViewCount="492" Body="&lt;p&gt;I notice that most codes can only perform finite difference calculations when including van der Waals interaction. Are there any codes that can apply density functional perturbation theory (DFPT) in combining with van der Waals interaction? Thank you in advance!&lt;/p&gt;&#xA;&lt;p&gt;Best regards,&#xA;Bo&lt;/p&gt;&#xA;" OwnerUserId="1022" LastActivityDate="2020-11-16T02:06:16.287" Title="Which codes can perform density functional perturbation theory (DFPT) calculations for a van der Waals (vdW) material?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3754" PostTypeId="2" ParentId="3753" CreationDate="2020-11-15T22:05:40.010" Score="7" Body="&lt;p&gt;&lt;strong&gt;Unfortunately, these vdW correction schemes are currently not available for calculations based on density functional perturbation theory. Therefore, the following suggestion is meaningless.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You can combine VASP with phonopy to realize your purpose.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;VASP: &lt;a href=&quot;https://www.vasp.at/&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Phonopy: &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;noreferrer&quot;&gt;https://phonopy.github.io/phonopy/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://phonopy.github.io/phonopy/vasp-dfpt.html#vasp-dfpt-interface&quot; rel=&quot;noreferrer&quot;&gt;Here is an example&lt;/a&gt; of VASP+DFPT, all that you need do are put the van der Waals interaction &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/IVDW&quot; rel=&quot;noreferrer&quot;&gt;(IVDW)&lt;/a&gt; in the INCAR of VASP calculation (step 4).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-11-16T02:06:16.287" LastActivityDate="2020-11-16T02:06:16.287" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3755" PostTypeId="2" ParentId="2410" CreationDate="2020-11-16T11:38:32.537" Score="5" Body="&lt;p&gt;This is consistent with some work we did on graphene nanoribbons a few years ago. We used LDA for this work, though from memory PBE gave similar results. This was using CASTEP, so different pseudopotentials to you and a different implementation of the plane-wave DFT method, so it can be considered independent verification.&lt;/p&gt;&#xA;&lt;p&gt;Like you, we found that the bare zigzag edge was spin polarised fairly strongly (this is well studied now); passivating with one hydrogen per edge carbon reduced the spin polarisation enormously, but did not completely suppress it; and passivating with two hydrogens per edge carbon led to a non-spin-polarised ground state. The most stable edge structure was the two-hydrogen passivation. We published our findings here:&lt;/p&gt;&#xA;&lt;p&gt;“Theoretical study of core-loss electron energy-loss spectroscopy at graphene nanoribbon edges”, Nobuyuki Fujita, Philip Hasnip, Matt Probert and Jun Yuan, J. Phys. Condens. Matter 27, 305301 (2015). &lt;a href=&quot;https://doi.org/10.1088/0953-8984/27/30/305301&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1088/0953-8984/27/30/305301&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-16T11:38:32.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3756" PostTypeId="2" ParentId="3550" CreationDate="2020-11-17T03:18:04.187" Score="4" Body="&lt;h3&gt;SOD (Site-Occupation Disorder code)&lt;/h3&gt;&#xA;&lt;p&gt;I found that &lt;a href=&quot;https://github.com/gcmt-group/sod&quot; rel=&quot;nofollow noreferrer&quot;&gt;SOD code&lt;/a&gt; can help to do it well.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2020-11-17T03:48:00.097" LastActivityDate="2020-11-17T03:48:00.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3757" PostTypeId="1" AcceptedAnswerId="3807" CreationDate="2020-11-17T20:46:46.700" Score="10" ViewCount="85" Body="&lt;p&gt;Preparing good figures is an important part of reporting molecular modeling results. There are many programs that can be used to visualize and generate images from all sorts of programs and approaches. However, each of them uses different colors for the elements and use arbitrary sphere sizes in ball-and-stick representations.&lt;/p&gt;&#xA;&lt;p&gt;I know that a lot of these choices are a matter of taste, but are there any more or less accepted conventions for the color of each element in figures? Or for the choice of sphere radius in a ball-and-stick representation ( there are many possible choices: van der Waals radii, ionic radii, covalent radii)?&lt;/p&gt;&#xA;&lt;p&gt;It would be great if there is some more or less universal representation that looks good and  prevents me from editing figures too much.&lt;/p&gt;&#xA;" OwnerUserId="878" LastActivityDate="2020-11-24T20:45:19.463" Title="Are there any conventions or guidelines to prepare images of molecular/crystal structures?" Tags="|visualization-software|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3758" PostTypeId="1" AcceptedAnswerId="3954" CreationDate="2020-11-18T02:28:03.023" Score="12" ViewCount="610" Body="&lt;p&gt;I have been having trouble with the VIBRATIONAL_ANALYSIS routine. Namely, the routine keeps timing out. I am trying to find the vibrational modes of Pyridine in a non periodic system, as well as &lt;span class=&quot;math-container&quot;&gt;$\ce{Mo2C}$&lt;/span&gt; in a periodic system. I'm running on 16 nodes in parallel, but it still takes a long time. I have tried making the box smaller for pyridine, but that changes the vibrational modes significantly. I have included the full input files at the end.&lt;/p&gt;&#xA;&lt;p&gt;For Pyridine parameters I have (so far):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EPS_DEFAULT 1E-10&#xA;CUTOFF 800&#xA;NGRIDS 6&#xA;REL_CUTOFF 40&#xA;MAX_SCF 100&#xA;EPS_SCF 1.0E-07&#xA;POISSON_SOLVER  WAVELET&#xA;PERIODIC NONE &#xA;ABC 30.0 30.0 30.0&#xA;TYPE MINIMIZATION&#xA;MAX_DR    1.0E-03&#xA;MAX_FORCE 1.0E-03&#xA;RMS_DR    1.0E-03&#xA;RMS_FORCE 1.0E-03&#xA;DX 1E-3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For Mo2C parameters I have (so far):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EPS_DEFAULT 1E-10&#xA;CUTOFF 800&#xA;NGRIDS 5&#xA;REL_CUTOFF 70&#xA;MAX_SCF 200&#xA;EPS_SCF 1.0E-07&#xA;ABC 4.75411  5.24148  6.07649&#xA;ALPHA_BETA_GAMMA 90 90 90&#xA;SYMMETRY ORTHORHOMBIC&#xA;PERIODIC XYZ&#xA;(GEO_OPT SECTION)&#xA;TYPE MINIMIZATION&#xA;MAX_DR    1.0E-03&#xA;MAX_FORCE 1.0E-03&#xA;RMS_DR    1.0E-03&#xA;RMS_FORCE 1.0E-03&#xA;DX 1E-3&#xA;(CELL_OPT SECTION)&#xA;TYPE GEO_OPT&#xA;MAX_DR    1.0E-03&#xA;MAX_FORCE 1.0E-03&#xA;RMS_DR    1.0E-03&#xA;RMS_FORCE 1.0E-03&#xA;DX 1E-3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input file for Pyridine:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;FORCE_EVAL&#xA;  METHOD QUICKSTEP&#xA;  &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME ./BASIS_SET&#xA;    POTENTIAL_FILE_NAME ./POTENTIALS&#xA;    &amp;amp;QS&#xA;       EPS_DEFAULT 1E-10&#xA;    &amp;amp;END QS&#xA;    &amp;amp;MGRID&#xA;      CUTOFF 800&#xA;      NGRIDS 6&#xA;      REL_CUTOFF 40&#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;SCF&#xA;      MAX_SCF 100&#xA;      EPS_SCF 1.0E-07&#xA;      SCF_GUESS RESTART&#xA;      &amp;amp;OT&#xA;         MINIMIZER DIIS&#xA;      &amp;amp;END OT&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;    &amp;amp;POISSON&#xA;       POISSON_SOLVER  WAVELET&#xA;       PERIODIC NONE &#xA;       &amp;amp;WAVELET&#xA;         SCF_TYPE  100&#xA;       &amp;amp;END WAVELET&#xA;    &amp;amp;END POISSON&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;CELL&#xA;      ABC 30.0 30.0 30.0&#xA;      PERIODIC NONE&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;TOPOLOGY&#xA;      COORD_FILE_FORMAT XYZ&#xA;      COORD_FILE_NAME pyridine.xyz&#xA;      &amp;amp;CENTER_COORDINATES&#xA;      &amp;amp;END CENTER_COORDINATES&#xA;    &amp;amp;END TOPOLOGY&#xA;    &amp;amp;KIND H&#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q1&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND C &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND N &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q5&#xA;    &amp;amp;END KIND&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&amp;amp;GLOBAL&#xA;  PROJECT Pyridine&#xA;  RUN_TYPE VIBRATIONAL_ANALYSIS&#xA;  PRINT_LEVEL LOW&#xA;  EXTENDED_FFT_LENGTHS&#xA;&amp;amp;END GLOBAL&#xA;&#xA;&amp;amp;MOTION&#xA;  &amp;amp;GEO_OPT&#xA;! to calculate vibrational spectrum tight convergence is required because frequencies are very sensitive to force constant&#xA;    TYPE MINIMIZATION&#xA;    MAX_DR    1.0E-03&#xA;    MAX_FORCE 1.0E-03&#xA;    RMS_DR    1.0E-03&#xA;    RMS_FORCE 1.0E-03&#xA;    MAX_ITER 200&#xA;    OPTIMIZER CG&#xA;  &amp;amp;END&#xA;&amp;amp;END&#xA;! setup parameters to perform a Normal Modes analysis&#xA;&amp;amp;VIBRATIONAL_ANALYSIS&#xA;!   &amp;amp;MODE_SELECTIVE&#xA;!      LOWEST_FREQUENCY 0.0&#xA;!      FREQUENCY   630&#xA;!      ATOMS 6 1&#xA;!      INITIAL_GUESS RESTART&#xA;!      RESTART_FILE_NAME Pyridine-VIBRATIONS-1.mol &#xA;!      EPS_NORM  1.0E-4&#xA;!      EPS_MAX_VAL 1.0E-5&#xA;!   &amp;amp;END&#xA;!Specify the number of processors to be used per replica environment (for parallel runs)&#xA;NPROC_REP 4&#xA;!Specify the increment to be used to construct the HESSIAN with finite difference method&#xA;   DX 1E-3&#xA;   &amp;amp;PRINT&#xA;     &amp;amp;PROGRAM_RUN_INFO ON&#xA;     &amp;amp;END&#xA;   &amp;amp;END&#xA;&amp;amp;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input file for Mo2C:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;FORCE_EVAL&#xA;  METHOD QUICKSTEP&#xA;  &amp;amp;DFT&#xA;    &amp;amp;QS&#xA;      EPS_DEFAULT 1.0E-10&#xA;    &amp;amp;END QS&#xA;    &amp;amp;POISSON&#xA;      PERIODIC XYZ&#xA;    &amp;amp;END POISSON&#xA;    BASIS_SET_FILE_NAME ./BASIS_SET&#xA;    POTENTIAL_FILE_NAME ./POTENTIALS&#xA;    &amp;amp;MGRID&#xA;      CUTOFF 800&#xA;      NGRIDS 5&#xA;      REL_CUTOFF 70&#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;SCF&#xA;      MAX_SCF 200&#xA;      EPS_SCF 1.0E-07&#xA;      SCF_GUESS RESTART&#xA;      &amp;amp;MIXING T&#xA;        ALPHA 0.5&#xA;        METHOD PULAY_MIXING&#xA;        NPULAY 5&#xA;      &amp;amp;END MIXING&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;CELL&#xA;      ABC 4.75411  5.24148  6.07649&#xA;      ALPHA_BETA_GAMMA 90 90 90&#xA;      SYMMETRY ORTHORHOMBIC&#xA;      PERIODIC XYZ&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;TOPOLOGY&#xA;      COORD_FILE_FORMAT XYZ&#xA;      COORD_FILE_NAME mo2c.xyz&#xA;    &amp;amp;END TOPOLOGY&#xA;    &amp;amp;KIND Mo&#xA;      BASIS_SET TZVP-MOLOPT-SR-GTH&#xA;      POTENTIAL GTH-PBE-q14 &#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND C &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&amp;amp;GLOBAL&#xA;  PROJECT MoC2&#xA;  RUN_TYPE GEO_OPT&#xA;  PRINT_LEVEL LOW&#xA;  EXTENDED_FFT_LENGTHS&#xA;&amp;amp;END GLOBAL&#xA;&#xA;&amp;amp;MOTION&#xA;  &amp;amp;GEO_OPT&#xA;! to calculate vibrational spectrum tight convergence is required because frequencies are very sensitive to force constant&#xA;    TYPE MINIMIZATION&#xA;    MAX_DR    1.0E-03&#xA;    MAX_FORCE 1.0E-03&#xA;    RMS_DR    1.0E-03&#xA;    RMS_FORCE 1.0E-03&#xA;    MAX_ITER 200&#xA;    OPTIMIZER CG&#xA;  &amp;amp;END&#xA;  &amp;amp;CELL_OPT&#xA;! to calculate vibrational spectrum tight convergence is required because frequencies are very sensitive to force constant&#xA;    MAX_DR    1.0E-03&#xA;    MAX_FORCE 1.0E-03&#xA;    RMS_DR    1.0E-03&#xA;    RMS_FORCE 1.0E-03&#xA;    MAX_ITER 200&#xA;    OPTIMIZER CG&#xA;    TYPE GEO_OPT&#xA;  &amp;amp;END&#xA;&amp;amp;END&#xA;! setup parameters to perform a Normal Modes analysis&#xA;&#xA;!&amp;amp;VIBRATIONAL_ANALYSIS&#xA;!Specify the number of processors to be used per replica environment (for parallel runs)&#xA;!NPROC_REP 4&#xA;!Specify the increment to be used to construct the HESSIAN with finite difference method&#xA;!DX 1E-08&#xA;!   &amp;amp;PRINT&#xA;!     &amp;amp;PROGRAM_RUN_INFO ON&#xA;!     &amp;amp;END&#xA;!   &amp;amp;END&#xA;!&amp;amp;END&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1451" LastEditorUserId="7" LastEditDate="2020-12-04T15:12:59.780" LastActivityDate="2020-12-18T04:17:33.557" Title="Geometric optimization taking a long time. Are my convergence criteria too tight in CP2K?" Tags="|density-functional-theory|high-performance-computing|geometry-optimization|vibrations|cp2k|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3759" PostTypeId="1" CreationDate="2020-11-18T04:44:32.033" Score="2" ViewCount="131" Body="&lt;p&gt;I wonder whether or not it would be useful to design and construct a double-sided &lt;a href=&quot;https://en.wikipedia.org/wiki/Whiteboard&quot; rel=&quot;nofollow noreferrer&quot;&gt;Whiteboard&lt;/a&gt; (i.e. the front and back sides can both be used)?&lt;/p&gt;&#xA;&lt;p&gt;The cost of the Whiteboard product would increase, but would it be worth it for the increased functionality?&lt;/p&gt;&#xA;" OwnerUserId="1537" LastEditorUserId="5" LastEditDate="2020-11-18T05:09:20.380" LastActivityDate="2020-11-21T05:10:15.397" Title="Would the increase in cost, of a double-sided whiteboard, make it worth it to engineer such a device?" Tags="|materials-engineering|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3760" PostTypeId="1" AcceptedAnswerId="3761" CreationDate="2020-11-19T05:51:20.333" Score="9" ViewCount="709" Body="&lt;p&gt;I want to study the properties of metal-organic framework (MOF) materials with DFT implemented in VASP. What's the pitfall for this kind of simulation? Which points should I take special care of?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I will clarify my question with more details as Andrew Rosen suggested.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If I want to relax the geometry of the MOF materials, which algorithm do I take (ISIF=?) in VASP?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If I want to perform a self-consistent calculation with VASP, what do I need to take care of?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If I want to study the absorption of MOF on atoms, what do I need to take care of?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PS: The original question is split into three questions. They are closely related to the DFT simulation of MOF materials. For convenience, I will link them below:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3763/how-to-obtain-mof-structures-to-perform-dft-simulation-with-vasp&quot;&gt;How to obtain MOF structures to perform DFT simulation with VASP?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3765/whatre-the-difference-between-mof-materials-isolated-cluster-and-periodical-s&quot;&gt;What&amp;#39;re the difference between MOF materials, isolated cluster, and periodical solid?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-11-20T00:57:27.677" LastActivityDate="2020-11-21T15:21:22.800" Title="What are the pitfalls for the simulation of MOF materials with VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3761" PostTypeId="2" ParentId="3760" CreationDate="2020-11-19T05:57:13.143" Score="10" Body="&lt;p&gt;I recommend reading &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.chemrev.0c00148&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Electronic Structure Modeling of Metal–Organic Frameworks&amp;quot;&lt;/a&gt; by Mancuso and coworkers for an overview of some subtle considerations when carrying out electronic structure calculations of MOFs.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If I want to relax the geometry of the MOF materials, which algorithm&#xA;do I take (ISIF=?) in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There is no single best answer for this. In &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.25787&quot; rel=&quot;nofollow noreferrer&quot;&gt;prior work&lt;/a&gt;, I had tested a variety of optimization algorithms for a diverse set of MOF structures. Empirically, I found that using the conjugate gradient (CG) algorithm (&lt;code&gt;ibrion=2&lt;/code&gt;) is generally both robust and fairly efficient in most cases. When the forces get small (i.e. you get close to the local minimum in the potential energy surface), the CG algorithm can often fail though with MOFs. In these cases, I have empirically found that switching to FIRE (&lt;code&gt;iopt=7&lt;/code&gt;, &lt;code&gt;ibrion=3&lt;/code&gt; with &lt;a href=&quot;http://theory.cm.utexas.edu/vtsttools/optimizers.html#fire-parameters-iopt-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;VTST&lt;/a&gt;) is generally the best choice. I have used CG &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; FIRE to optimize &lt;a href=&quot;https://chemrxiv.org/articles/preprint/Machine_Learning_the_Quantum-Chemical_Properties_of_Metal_Organic_Frameworks_for_Accelerated_Materials_Discovery_with_a_New_Electronic_Structure_Database/13147616&quot; rel=&quot;nofollow noreferrer&quot;&gt;tens of thousands of MOF structures&lt;/a&gt; with great success. The only exception is if the forces are &lt;em&gt;extremely&lt;/em&gt; high in the initial geometry optimization steps. In these cases, I have empirically found that using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE's BFGSLineSearch algorithm&lt;/a&gt; for a few steps does a nice job at smoothly resolving the high forces without causing the structure to &amp;quot;explode&amp;quot; or anything like that.&lt;/p&gt;&#xA;&lt;p&gt;As a side-note, you mentioned the &lt;code&gt;isif&lt;/code&gt; flag in your question. That does not choose the type of geometry optimization algorithm but rather which degrees of freedom to relax. In general, you should ensure that your material is the minimum energy structure with respect to the atomic positions and cell shape/volume. In other words, use &lt;code&gt;isif=3&lt;/code&gt;. Typically, when modeling adsorbates with MOFs, the guest-free MOF structure will be optimized with &lt;code&gt;isif=3&lt;/code&gt; and then the lattice constants fixed thereafter (i.e. &lt;code&gt;isif=2&lt;/code&gt; is used). This inherently assumes that the lattice constants of the MOF do not change when adsorbates are introduced, which is typically (although not always) true.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If I want to perform a self-consistent calculation with VASP, what do&#xA;I need to take care of?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In general, nothing special has to be done for MOFs. If you're using VASP as you mention, ensure that your property of interest is converged with respect to the plane-wave kinetic energy cutoff and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid.  Make sure you enable spin-polarization if there is any possibility of unpaired electrons in your system. Beyond this, you may find my &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/170/what-are-good-ways-to-reduce-computing-time-when-working-with-large-systems-in-v/172#172&quot;&gt;prior answer&lt;/a&gt; to the question &amp;quot;What are good ways to reduce computing time when working with large systems in VASP?&amp;quot; to be helpful.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If I want to study the absorption of MOF on atoms, what do I need to&#xA;take care of?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You will need to ensure that you consider various adsorption modes for a given adsorbate. If you don't do this, you may end up modeling a configuration that is not the minimum energy configuration. If the adsorbate induces a change in oxidation state of the MOF, keep in mind that your typical GGA functionals like PBE will probably be fairly insufficient. You can check out &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/5.0010166&quot; rel=&quot;nofollow noreferrer&quot;&gt;this article&lt;/a&gt; for some suggestions about modeling the adsorption of species that oxidize metal centers of MOFs. Also, in DFT, people often only include one adsorbate per unit cell, but in reality you should remember that it is very possible multiple adsorbates would be present and there could be adsorbate–adsorbate interactions or coverage-dependent effects.&lt;/p&gt;&#xA;&lt;p&gt;To systematically add adsorbates to MOFs, you may be interested in the &lt;a href=&quot;https://github.com/arosen93/mof-adsorbate-initializer&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOF Adsorbate Initializer&lt;/a&gt; for small molecule adsorbates or the &lt;a href=&quot;https://github.com/haoyuanchen/mof-big-adsorbate-initializer&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOF Big Adsorbate Initializer&lt;/a&gt; for larger ones.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="142" LastEditDate="2020-11-21T15:21:22.800" LastActivityDate="2020-11-21T15:21:22.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3762" PostTypeId="1" CreationDate="2020-11-19T16:36:11.170" Score="6" ViewCount="286" Body="&lt;p&gt;I've been trying to run a Thermo-Calc one axis equilibrium calculation on some quaternary alloys in the TCHEA4 database. Most of the calculations work fine, but for some alloys it gets stuck in a loop (forever) where it is trying to find the start of a phase change. I can sometimes get it to run for these problematic alloys by setting the global test interval to 1 or by increasing the number of grid points for global minimization, but I don't want to have to fudge things like that. What is the reason the calculations are hanging and how can it be fixed reliably?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;:&#xA;        Phase Region from    651.989   &#xA;        11:35:58,357 INFO   BCC_B2#1 SIGMA#1 SIGMA#2&#xA;        11:35:58,478 INFO   Global test at  5.80000E+02&#xA;        11:35:59,482 INFO    Backtracking to find phase change for SIGMA#3&#xA;        11:35:59,617 INFO   Global check of adding phase at  6.51989E+02&#xA;        11:36:01,482 INFO   Calculated     4 equilibria&#xA;        11:36:01,483 INFO   Phase Region from    651.989&#xA;        11:36:01,484 INFO   BCC_B2#1 SIGMA#1 SIGMA#2 SIGMA#3&#xA;        11:36:01,557 INFO   Global check of removing phase at  6.51989E+02&#xA;        11:36:03,571 INFO   Calculated     3 equilibria&#xA;        11:36:03,572 INFO   Phase Region from    651.989&#xA;        11:36:03,572 INFO   BCC_B2#1 SIGMA#1 SIGMA#2&#xA;        11:36:03,710 INFO   Global test at  5.80000E+02&#xA;        11:36:05,276 INFO    Backtracking to find phase change for SIGMA#3&#xA;        11:36:05,477 INFO   Global check of adding phase at  6.51989E+02&#xA;        11:36:07,188 INFO   Calculated     4 equilibria&#xA;        11:36:07,189 INFO   Phase Region from    651.989&#xA;        11:36:07,189 INFO   BCC_B2#1 SIGMA#1 SIGMA#2 SIGMA#3&#xA;        11:36:07,275 INFO   Global check of removing phase at  6.51989E+02&#xA;        11:36:07,675 INFO   Calculated     3 equilibria&#xA;        11:36:07,675 INFO   Phase Region from    651.989&#xA;        11:36:07,676 INFO   BCC_B2#1 SIGMA#1 SIGMA#2&#xA;        11:36:07,800 INFO   Global test at  5.80000E+02&#xA;        11:36:09,098 INFO    Backtracking to find phase change for SIGMA#3&#xA;        11:36:09,318 INFO   Global check of adding phase at  6.51989E+02&#xA;        11:36:11,029 INFO   Calculated     4 equilibria&#xA;        11:36:11,030 INFO   Phase Region from    651.989&#xA;        11:36:11,031 INFO   BCC_B2#1 SIGMA#1 SIGMA#2 SIGMA#3&#xA;        11:36:11,096 INFO   Global check of removing phase at  6.51989E+02&#xA;        11:36:13,019 INFO   Calculated     3 equilibria&#xA;        11:36:13,020 INFO   Phase Region from    651.989&#xA;        11:36:13,021 INFO   BCC_B2#1 SIGMA#1 SIGMA#2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This just continues without end.&lt;/p&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="5" LastEditDate="2021-01-22T20:49:53.400" LastActivityDate="2021-01-22T20:49:53.400" Title="Why does Thermo-Calc one axis equilibrium calculation get stuck in never ending loop?" Tags="|thermodynamics|software-assistance|gibbs-free-energy|calphad|thermo-calc|" AnswerCount="0" CommentCount="5" ClosedDate="2021-03-14T23:53:18.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="3763" PostTypeId="1" AcceptedAnswerId="3764" CreationDate="2020-11-20T00:48:39.953" Score="10" ViewCount="1009" Body="&lt;p&gt;For bulk and two-dimensional materials, we can download the structures from many databases, such as &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; and &lt;a href=&quot;https://cmr.fysik.dtu.dk/&quot; rel=&quot;noreferrer&quot;&gt;CMR&lt;/a&gt;. Are there also similar databases for MOF (metal-organic framework) materials or structures? How can I build a reasonable structure, namely a &lt;code&gt;POSCAR&lt;/code&gt; in VASP?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="206" LastEditDate="2020-11-20T00:59:17.907" LastActivityDate="2023-04-28T17:43:49.513" Title="Where to obtain MOF structures suitable for carrying out DFT simulations?" Tags="|density-functional-theory|structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3764" PostTypeId="2" ParentId="3763" CreationDate="2020-11-20T00:50:57.410" Score="13" Body="&lt;p&gt;In the examples below, you can generate a &lt;code&gt;POSCAR&lt;/code&gt; by using a variety of tools, such as the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt;, to convert between &lt;code&gt;CIF&lt;/code&gt; and &lt;code&gt;POSCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Experimental MOF Structures&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;CoRE MOF Database:&lt;/strong&gt; The Computation-Ready, Experimental (CoRE) MOF database (&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jced.9b00835&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, &lt;a href=&quot;https://zenodo.org/record/3677685&quot; rel=&quot;nofollow noreferrer&quot;&gt;database link&lt;/a&gt;). This database contains experimental crystal structures of MOFs obtained from the Cambridge Structural Database and the supporting informations of various papers. There are two versions: the FSR (free solvent removed) and ASR (all solvent removed) subsets. The former has all free (i.e. unbound) solvent removed from the pores, whereas the later removes all unbound and bound solvent. This database contains roughly 14,000 3D MOFs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;CSD MOF Subset:&lt;/strong&gt;&#xA;The Cambridge Structural Database (CSD) MOF subset (&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.7b00441&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, &lt;a href=&quot;https://sites.google.com/view/csdmofsubset/home&quot; rel=&quot;nofollow noreferrer&quot;&gt;database link&lt;/a&gt;). This database contains experimental crystal structures of MOFs (and coordination polymers) from the Cambridge Structural Database. It contains many more structures than the CoRE MOF database but uses a less strict definition on what a MOF is. You can use the list of reference codes and pull up structures &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/?&quot; rel=&quot;nofollow noreferrer&quot;&gt;manually from the CSD&lt;/a&gt; or use the CCDC ConQuest software as described &lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2020/ce/d0ce00299b&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; to query the database in a systematic fashion. This database contains nearly 100,000 MOF-like structures and grows with every release of the CSD. There is also a free subset called the &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2590238521001132&quot; rel=&quot;nofollow noreferrer&quot;&gt;CSD MOF Collection&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;HEALED MOF Database&lt;/strong&gt;: Dataset of MOFs with attention to only including atomically precise building blocks, described &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acsami.2c13100&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pyrene MOF Dataset&lt;/strong&gt;: Dataset of experimentally characterized Pyrene-based MOFs (&lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2021/cs/d0cs00424c&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, &lt;a href=&quot;https://archive.materialscloud.org/record/2020.156&quot; rel=&quot;nofollow noreferrer&quot;&gt;dataset&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;mBUD SBU Database&lt;/strong&gt;: Dataset of MOF building blocks obtained using the mBUD code, described &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jcim.1c00547&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;PORMAKE SBU Database&lt;/strong&gt;: Dataset of MOF building blocks obtained for use with the PORMAKE code, described &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acsami.1c02471&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;DFT-optimized MOF Structures&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;QMOF Database:&lt;/strong&gt; If you are looking for DFT-optimized structures, check out the Quantum MOF (QMOF) database (&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2590238521000709&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper 1&lt;/a&gt;, &lt;a href=&quot;https://www.nature.com/articles/s41524-022-00796-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper 2&lt;/a&gt;, &lt;a href=&quot;https://github.com/arosen93/QMOF&quot; rel=&quot;nofollow noreferrer&quot;&gt;database link&lt;/a&gt;), which I have constructed. It contains over 20,000 DFT-optimized structures, and there is a user interface on the &lt;a href=&quot;http://materialsproject.org/mofs&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;DFT-Optimized CoRE MOF Subset:&lt;/strong&gt; There is also a DFT-optimized subset of 1340 MOFs found in the CoRE MOF database (&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemmater.6b04226&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, &lt;a href=&quot;https://zenodo.org/record/3986569#.XzfKcpMzY8N&quot; rel=&quot;nofollow noreferrer&quot;&gt;database link&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h3&gt;Hypothetical MOF Structures&lt;/h3&gt;&#xA;&lt;p&gt;If the MOF you want has yet to be made, you may be interested in constructing hypothetical MOF CIFs from known building blocks. Several tools and databases are outlined below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;ToBaCCo&lt;/strong&gt;: There is the Topologically Based Crystal Constructor, known as ToBaCCo (&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.cgd.7b00848&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper 1&lt;/a&gt;, &lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2019/ce/c8ce01637b&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper 2&lt;/a&gt;, &lt;a href=&quot;https://github.com/tobacco-mofs/tobacco_3.0&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub&lt;/a&gt;). Unlimited number of MOFs can be made using this code, in principle. A set of ToBaCCo MOFs can be found on &lt;a href=&quot;https://mof.tech.northwestern.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOFDB&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;hMOFs:&lt;/strong&gt; There is a dataset of ~130,000 hypothetical MOFs (hMOFs) described &lt;a href=&quot;https://www.nature.com/articles/nchem.1192&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;MOF+:&lt;/strong&gt; There is the hypothetical MOF construction code called &lt;a href=&quot;https://www.mofplus.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOF+&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;B&amp;amp;W:&lt;/strong&gt; Boyd and Woo have a MOF construction code outlined &lt;a href=&quot;https://pubs.rsc.org/--/content/articlehtml/2016/ce/c6ce00407e&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Nanoporousmaterials.org:&lt;/strong&gt; The website &lt;a href=&quot;http://nanoporousmaterials.org/databases&quot; rel=&quot;nofollow noreferrer&quot;&gt;nanoporousmaterials.org&lt;/a&gt; has several databases of nanoporous materials, including hypothetical MOF-5 analogues. Hypothetical MOF-74 analogues from the same group can be found &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/SC/c6sc01477a&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;ARC-MOF Database&lt;/strong&gt;: Dataset of both experimental and hypothetical MOFs with ab initio REPEAT charges described &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.chemmater.2c02485&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Ultrastable MOF Database&lt;/strong&gt;: Dataset of hypothetical MOFs tailored for high stability, described &lt;a href=&quot;https://www.cell.com/matter/pdf/S2590-2385(23)00111-X.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EC-MOF Database&lt;/strong&gt;: Dataset of hypothetical MOFs based on conductivity, described &lt;a href=&quot;https://arxiv.org/abs/2210.17428&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Genomic MOF Database&lt;/strong&gt;: Dataset of hypothetical MOFs found &lt;a href=&quot;https://figshare.com/s/ec378d7315581e48f1e4&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; based on prior work on COF construction described &lt;a href=&quot;https://www.nature.com/articles/s41467-018-07720-x&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Meta-Repositories&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;MOFX-DB:&lt;/strong&gt; The &lt;a href=&quot;https://mof.tech.northwestern.edu&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOFX-DB&lt;/a&gt; contains MOF structures (with selected properties) from the CoRE MOF, ToBaCCo, and hMOF databases, described &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jced.2c00583&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2023-04-28T17:43:49.513" LastActivityDate="2023-04-28T17:43:49.513" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3765" PostTypeId="1" AcceptedAnswerId="3766" CreationDate="2020-11-20T00:54:23.447" Score="8" ViewCount="293" Body="&lt;p&gt;Should I take MOF (metal-organic framework) as a periodic structure or an isolated cluster? What's the difference between them? If it's periodic, can I do an analysis of the electronic structure, such as band structure and density of states? If it's an isolated cluster, do I need to put a large vacuum along with the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; directions? In essence, is there any difference between isolated clusters and periodic solid when modeling MOF structures?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-11-20T02:42:17.947" LastActivityDate="2020-11-20T02:42:17.947" Title="What differences are there when modeling metal-organic-frameworks as isolated clusters or periodic solids?" Tags="|density-functional-theory|electronic-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3766" PostTypeId="2" ParentId="3765" CreationDate="2020-11-20T01:15:02.390" Score="7" Body="&lt;p&gt;There is no article better suited for your question than &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.chemrev.0c00148&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Electronic Structure Modeling of Metal–Organic Frameworks&amp;quot;&lt;/a&gt; by Mancuso and coworkers. There is also some nice discussion about periodic structures versus cluster models in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acscentsci.7b00500&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Computational Design of Functionalized Metal–Organic Framework Nodes for Catalysis&amp;quot;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Whether you choose to model a MOF as a periodic structure or isolated cluster is a matter of preference and depends on the property you wish to model. The only way to get reasonable band structures and density of states is to use a periodic structure of a MOF (i.e. the full crystalline unit cell). If you are using a plane-wave density functional theory (DFT) code like VASP, as alluded to in your other questions, I also generally do not recommend using a cluster model. In principle, you can use a cluster model in a periodic DFT code like VASP with artificial vacuum space surrounding the cluster to avoid self-interactions, but there is rarely a justifiable reason to do this. DFT codes that use Gaussian basis sets and meant for molecular systems are far better suited for using cluster models.&lt;/p&gt;&#xA;&lt;p&gt;This begs the question – why would you ever use a cluster model? Well, if you are studying a phenomenon that is relatively local (e.g. a catalytic reaction happening at a specific active site), it is unlikely that the framework atoms far away from the active site will influence the reactivity. In this case, it might make sense to carve a representative cluster of your MOF, ensuring that all dangling bonds are capped and the charge of your system is balanced. Using a cluster model also lets you model an inherently smaller system, which means you can afford to use more computationally expensive (yet hopefully more accurate) methods like (meta-)hybrid functionals or wavefunction theory. These would typically be impractical to do with a periodic structure.&lt;/p&gt;&#xA;&lt;p&gt;Of course, using a cluster model has its disadvantages. By truncating the system, you may ignore subtle but important structural or electronic effects from the atoms you have essentially removed from consideration. For this reason, it is a good idea to do some benchmarking to ensure the properties of interested computed from the cluster model are largely representative of the original periodic system. Sometimes, in a given project it can be beneficial to use both approaches depending on what you wish to answer. There are also other approaches, such as QM/MM, that allow you to model a periodic structure at a computational cost approaching that of a typical cluster model.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-11-20T02:37:34.100" LastActivityDate="2020-11-20T02:37:34.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3768" PostTypeId="1" CreationDate="2020-11-20T09:47:44.550" Score="6" ViewCount="145" Body="&lt;p&gt;I want to know how to make 2D Quantum dots in Vesta?&lt;/p&gt;&#xA;" OwnerUserId="1384" LastEditorUserId="5" LastEditDate="2020-11-20T12:53:05.153" LastActivityDate="2020-11-20T14:31:45.880" Title="How To make 2D Quantum dots in VESTA" Tags="|density-functional-theory|vesta|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3769" PostTypeId="1" CreationDate="2020-11-20T11:32:13.997" Score="12" ViewCount="241" Body="&lt;p&gt;The theory of elasticity is essential in engineering. The most basic law is that any piece becomes smaller if one compresses it. My question is:&lt;/p&gt;&#xA;&lt;p&gt;How can a piece of material expand (some minutes, hours, or days) after being compressed?&lt;/p&gt;&#xA;&lt;p&gt;It is against our intuition. A related topic is the development of (meta)material with negative Poisson's ratio, which is also counterintuitive.&lt;/p&gt;&#xA;&lt;p&gt;I suppose such material is possible, for example, a linear spring (as harmonic oscillator) with a very long period (you press it today, it expands tomorrow). I am wondering whether there is subfield developing such unusual material.&lt;/p&gt;&#xA;" OwnerUserId="1551" LastActivityDate="2020-11-20T15:28:34.813" Title="What material will expand after being compressed?" Tags="|materials-design|metamaterials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3770" PostTypeId="1" CreationDate="2020-11-20T14:04:34.650" Score="6" ViewCount="67" Body="&lt;p&gt;I have been working with an anti-ferromagnetic material Cobalt Oxide. And in the image given below the blue spheres are Co ions. The blue spheres form a tetrahedron shape.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Zpmka.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Zpmka.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And I've assigned the spin configuration as per this image I've taken from an online thesis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3hQNw.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3hQNw.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So according to the image, the 3 Co atoms in a plane will be assigned on spin(say up) and the remaining one Co atom is assigned a down spin. I have given the code below (input file):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL &#xA; calculation = &amp;quot;scf&amp;quot;&#xA; prefix = &amp;quot;CoO&amp;quot;&#xA; outdir = &amp;quot;./outdir&amp;quot;&#xA; pseudo_dir = &amp;quot;.&amp;quot;&#xA; tprnfor = .true.&#xA; tstress = .true.&#xA; verbosity = &amp;quot;low&amp;quot;&#xA;&#xA;/&#xA;&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =    4.59861&#xA;  nat = 8&#xA;  ntyp = 3&#xA;  ecutwfc = 60&#xA;  ecutrho = 445&#xA;  nspin = 2&#xA;  starting_magnetization(1)=  1&#xA;  starting_magnetization(2)= -1&#xA;  occupations = &amp;quot;smearing&amp;quot;&#xA;  smearing = &amp;quot;mv&amp;quot;&#xA;  degauss = 0.005d0&#xA;  &#xA;/&#xA;&amp;amp;electrons &#xA;    conv_thr = 1d-8&#xA;    mixing_beta = 0.7d0&#xA;/&#xA;&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA;  0.000000000000000   1.000000000000000   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   1.000000000000000 &#xA;ATOMIC_SPECIES&#xA;  Co   58.93300  Co.pbe-spn-kjpaw_psl.0.3.1.UPF&#xA;  Co1   58.93300  Co.pbe-spn-kjpaw_psl.0.3.1.UPF&#xA;   O1   15.99900   O.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA; Co    0.250000000000000   0.750000000000000   0.750000000000000 &#xA; Co1   0.250000000000000   0.250000000000000   0.250000000000000 &#xA; Co    0.750000000000000   0.750000000000000   0.250000000000000 &#xA; Co    0.750000000000000   0.250000000000000   0.750000000000000 &#xA; O1    0.500000000000000   0.500000000000000   0.500000000000000 &#xA; O1   0.500000000000000   0.000000000000000   0.000000000000000 &#xA; O1    0.000000000000000   0.500000000000000   0.000000000000000 &#xA; O1    0.000000000000000   0.000000000000000   0.500000000000000 &#xA;&#xA;K_POINTS {automatic}&#xA; 17 17 17 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But the magnetization is non-zero. which is wrong.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; total magnetization       =     6.01 Bohr mag/cell&#xA; absolute magnetization    =    10.32 Bohr mag/cell&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It would be nice if someone could shed some light on this .Thanks in advance :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-11-21T00:25:36.977" Title="How can I assign spins to an non-planar Anti-Ferro Magnetic system (CoO in this case)?" Tags="|density-functional-theory|magnetism|anti-ferromagnetic|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3772" PostTypeId="2" ParentId="3769" CreationDate="2020-11-20T15:28:34.813" Score="7" Body="&lt;p&gt;I think you need to know the potential energy surface (PES) of the system. Assuming the system is in equilibrium before applying the deformation, any modification will take it to a non-equilibrium state. Depending on in which points of the PES the system is/go and the amount of strain/stress accumulated during the compression, the tendency is to free the extra energy and came back to equilibrium.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-11-20T15:28:34.813" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3774" PostTypeId="1" AcceptedAnswerId="3775" CreationDate="2020-11-20T20:28:43.653" Score="7" ViewCount="179" Body="&lt;p&gt;I am calculating MSDs for the first time and have been struggling to find newbie-level resources on understanding them.  If anyone could please suggest any resources or provide guidance on how to interpret MSD results, I would be grateful.&lt;/p&gt;&#xA;&lt;p&gt;I have been running NPT simulations to collect data for use in fluid dynamics simulations.  However, I now realize that I have used low temperatures compared to people who have looked at similar systems.  So I want to evaluate MSDs to make sure the simulations are ergodic.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I don't have much experience with statistics and a basic point I don't understand is &lt;strong&gt;whether it is the slope of the MSD or the R value that matters&lt;/strong&gt;.  Or both.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;An example of an MSD I have calculated is below.  I get this output (I can't control the time interval used, the software chooses it):&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;Linear regression interval 41.52 - 83.03 ps.&#xA;MSD(t) = -10806.283111 + 1575.888517 * t&#xA;R = 0.977891&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When I calculate a slope on the interval &lt;strong&gt;1 ps to where the curve goes vertical&lt;/strong&gt;, I get &lt;strong&gt;~0.8&lt;/strong&gt;, which I know is not great.  I don't know what an acceptable value would be but am guessing &amp;gt;0.9.  &lt;strong&gt;I do get 0.95&lt;/strong&gt; if I calculate the slope not from 1 ps, but from &lt;strong&gt;10 ps&lt;/strong&gt;.  But on a log-log plot, that's a small interval.  Is it unacceptably small?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SprL6.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SprL6.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1035" LastEditorUserId="5" LastEditDate="2020-11-21T07:08:10.643" LastActivityDate="2020-11-21T07:08:10.643" Title="For ergodicity, what is the significance of the R value and slope?" Tags="|molecular-dynamics|molecular-modeling|statistical-thermodynamics|thermodynamics|ergodicity|" AnswerCount="1" CommentCount="5" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3775" PostTypeId="2" ParentId="3774" CreationDate="2020-11-20T22:41:56.007" Score="8" Body="&lt;h3&gt;Short introduction to ergodicity&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Ergodicity&lt;/strong&gt; is when the time-average equals the ensemble-average.&lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;A process is &lt;strong&gt;ergodic&lt;/strong&gt; if the time-average &amp;quot;converges in the square mean&amp;quot; to the ensemble average.&lt;/li&gt;&#xA;&lt;li&gt;A sequence &lt;span class=&quot;math-container&quot;&gt;$X_t$&lt;/span&gt; &lt;strong&gt;converges in the square mean&lt;/strong&gt; to &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; if:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\lim_{t\rightarrow \infty}\langle \left|X_t - X\right|^2 \rangle = 0,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\langle x \rangle$&lt;/span&gt; means the mean (average) of &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. So if the &lt;strong&gt;mean&lt;/strong&gt; of the &lt;strong&gt;square&lt;/strong&gt; of the absolute difference between the time-average and ensemble-average (i.e. the &lt;strong&gt;MSD&lt;/strong&gt; between them) approaches zero, then the process can be said to be ergodic.&lt;/p&gt;&#xA;&lt;h3&gt;Short introduction to generalized diffusion&lt;/h3&gt;&#xA;&lt;p&gt;If we plot MSD&lt;span class=&quot;math-container&quot;&gt;$(t)$&lt;/span&gt; with MSD on the vertical axis and &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; on the horizontal axis, and fit the data to a power law form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;\textrm{MSD}(t) = Dt^\alpha,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is the &lt;strong&gt;diffusion constant,&lt;/strong&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is the &lt;strong&gt;generalized diffusion exponent&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;normal diffusion&lt;/strong&gt; is characterized by &lt;span class=&quot;math-container&quot;&gt;$\alpha=1$&lt;/span&gt;, meaning MSD&lt;span class=&quot;math-container&quot;&gt;$(t)$&lt;/span&gt; is linear.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;sub-diffusion&lt;/strong&gt; is characterized by &lt;span class=&quot;math-container&quot;&gt;$0&amp;lt;\alpha&amp;lt;1$&lt;/span&gt;, meaning MSD&lt;span class=&quot;math-container&quot;&gt;$(t)$&lt;/span&gt; is sub-linear.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;super-diffusion&lt;/strong&gt; is characterized by &lt;span class=&quot;math-container&quot;&gt;$\alpha&amp;gt;1$&lt;/span&gt;, meaning MSD&lt;span class=&quot;math-container&quot;&gt;$(t)$&lt;/span&gt; is super-linear.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Short introduction to statistical regression&lt;/h3&gt;&#xA;&lt;p&gt;The &lt;strong&gt;coefficient of determination&lt;/strong&gt; is given by &lt;span class=&quot;math-container&quot;&gt;$R^2$&lt;/span&gt; and is a measure of the &amp;quot;goodness of fit&amp;quot;. Specifically, when you fit a line or curve through data, how well does that line or curve predict the data? If &lt;span class=&quot;math-container&quot;&gt;$R^2 = 1$&lt;/span&gt; then the data is perfectly predicted by your fitted line or curve.&lt;/p&gt;&#xA;&lt;h3&gt;Application to your case&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I don't understand is whether it is the slope of the MSD or the R&#xA;value that matters. Or both.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You could plot your MSD&lt;span class=&quot;math-container&quot;&gt;$(t)$&lt;/span&gt; and fit the data to Eq. 2, which will give you an &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, which will tell you what type of diffusion you have. But since you chose to do a log-log plot, Eq. 2 has to be modified accordingly:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{3}&#xA;\log\textrm{MSD}(t) &amp;amp;= \frac{\alpha \log D}{\log 10} \log(t), \\&#xA;y &amp;amp;= m x, ~~~ m \equiv\alpha\left(\frac{ \log D}{\log 10}\right). \tag{4}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Slope:&lt;/strong&gt; Eq. 4 tells us that a very large slope may be indicative of super-diffusion, and a very small slope may be indicative of sub-diffusion.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;-value:&lt;/strong&gt; Your &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; value implies an &lt;span class=&quot;math-container&quot;&gt;$R^2$&lt;/span&gt; of 0.956, which means that in the area where you did the fit (41.52 - 83.03 ps) the data is fairly linear (could be more linear but could be a lot worse).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-11-20T22:41:56.007" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3776" PostTypeId="5" CreationDate="2020-11-20T22:46:10.767" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-20T22:46:10.767" LastActivityDate="2020-11-20T22:46:10.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3777" PostTypeId="4" CreationDate="2020-11-20T22:46:10.767" Score="0" Body="Questions about ergodicity, non-ergodicity, ergodic or non-ergodic systems, fractional Brownian motion, anomalous diffusion, etc." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-20T22:46:10.767" LastActivityDate="2020-11-20T22:46:10.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3778" PostTypeId="2" ParentId="3770" CreationDate="2020-11-21T00:25:36.977" Score="4" Body="&lt;p&gt;The problem is that you haven't got a unit cell which can support that magnetic structure. Your cell is a perfectly good representation of the &lt;em&gt;atomic&lt;/em&gt; periodicity, but it is not compatible with the desired &lt;em&gt;magnetic&lt;/em&gt; periodicity -- remember that the magnetic structure of a material does not need to have the same periodicity as the atomic structure (or, indeed, &lt;em&gt;any&lt;/em&gt; periodicity!).&lt;/p&gt;&#xA;&lt;p&gt;A periodic simulation program needs to work with a simulation cell which, when repeated periodically throughout all space, generates the electronic structure you want, which means it must obey respect both the atomic &lt;em&gt;and&lt;/em&gt; magnetic symmetries. Since the relevant planes for the magnetic structure you want are (111) planes, I suggest you re-orient your cell along the (111)-direction. With this new cell, the magnetic structure you seek is simply alternating up and down spins in the out-of-plane direction.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2020-11-21T00:25:36.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3779" PostTypeId="2" ParentId="3759" CreationDate="2020-11-21T05:10:15.397" Score="2" Body="&lt;p&gt;The product/material that you are considering to engineer, has already been engineered and been &lt;em&gt;successful&lt;/em&gt; in the market. Three such examples are &lt;a href=&quot;https://i.stack.imgur.com/e5fOR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;these ones&lt;/a&gt; which I found in a Google Images search, where you can &lt;a href=&quot;https://www.google.com/search?q=double+sided+whiteboards&amp;amp;source=lnms&amp;amp;tbm=isch&amp;amp;sa=X&amp;amp;ved=2ahUKEwjyuvCz6ZLtAhVUGFkFHY62A9cQ_AUoAnoECA4QBA&amp;amp;biw=1598&amp;amp;bih=827&quot; rel=&quot;nofollow noreferrer&quot;&gt;see many more&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From a materials engineering perspective, no new material needs to be designed, since the device can be constructed using materials that have already been engineered, and just making &lt;span class=&quot;math-container&quot;&gt;$2\times$&lt;/span&gt; as much of it. The maximum cost &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt; of making the double-sided device, in terms of the cost &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; of making a single-sided device, would be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\max (C_2) = 2C_1 + \epsilon,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is the overhead cost of having to glue together the two slabs of material. In reality though, the manufacturing cost might be much less than twice the cost of making one such device, because instead of making two separate devices and attaching them together, the whole two-sided device can be made simultaneously and possibly save some overhead costs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There is minimal engineering work to be done, and the materials-design portion of the project luckily doesn't require the design of any &lt;em&gt;new&lt;/em&gt; type of material, since the most important material for such devices was already designed and can be re-used here (dry erase boards are typically made of the organic compound &lt;a href=&quot;https://en.wikipedia.org/wiki/Melamine&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;melamine&lt;/strong&gt;&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;The total cost of the melamine for the product will be proportional to the number of square cm of material desired, which will be at most double (in the worst case) the cost for one-sided devices, and in some cases the cost will be exactly the same as before because we would just avoid covering the the back-side of the melamine board. These costs are worth it, to the extent that the product is already on the market and people purchase it.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-11-21T05:10:15.397" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3780" PostTypeId="1" CreationDate="2020-11-21T06:14:45.143" Score="7" ViewCount="3221" Body="&lt;p&gt;I am trying to run spin polarised DFT calculation in Quantum ESPRESSO on system Co2MnSi. I kept starting magnetization for all these three species as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;starting_magnetization(Co) = 0.3,&#xA;starting_magnetization(Mn) = 0.5,&#xA;starting_magnetization(Si) = 0.2,&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have used the fact that Cobalt has 3 valance electrons in up, hence positive 0.3. Similarly for Mn and Si.Convergence is not achieved even after 100 iterations using these values as starting magnetization.&lt;/p&gt;&#xA;&lt;p&gt;1)Is this the wrong assumption I am using for initialising starting_magnetization? If yes, What should be right fact for choosing initialization value?&lt;/p&gt;&#xA;&lt;p&gt;2)Can I also use 'tetrahedra' smearing for magnetic systems?&lt;/p&gt;&#xA;&lt;p&gt;Please clarify my doubts!&lt;br /&gt;&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1361" LastEditDate="2020-11-21T08:34:06.877" LastActivityDate="2020-11-21T13:55:40.563" Title="How to choose starting magnetization while doing spin polarised calculation in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|spin-models|spin-polarization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3781" PostTypeId="1" CreationDate="2020-11-21T07:39:26.823" Score="12" ViewCount="277" Body="&lt;p&gt;What are some of the biggest open-questions / challenges in Condensed Phase theory and computation? What efforts are being done to answer them?&lt;/p&gt;&#xA;&lt;p&gt;I realize Condensed Phase chemistry is a huge field, but there &lt;em&gt;must&lt;/em&gt; be those questions that &amp;quot;everyone knows&amp;quot; are still open (e.g. Room-Temperature Superconductivity in Condensed Matter Physics, functional Spintronic devices).&lt;/p&gt;&#xA;&lt;p&gt;I am thinking there are some challenges in really predicting reactions in complex environments... any references a beginner should look at?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-11-21T16:50:43.267" LastActivityDate="2020-11-21T16:50:43.267" Title="What are some of the biggest theoretical and computational challenges in Condensed Phase Chemistry?" Tags="|reference-request|computational-chemistry|qmmm|quantum-dynamics|transition-state|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3782" PostTypeId="2" ParentId="3781" CreationDate="2020-11-21T13:32:33.343" Score="10" Body="&lt;h2&gt;The Monte Carlo Sign Problem&lt;/h2&gt;&#xA;&lt;p&gt;For classical systems, Monte Carlo works extremely well. Quantum Monte Carlo is very powerful, but there are many interesting systems that suffer from the &lt;a href=&quot;https://en.wikipedia.org/wiki/Numerical_sign_problem&quot; rel=&quot;noreferrer&quot;&gt;sign problem&lt;/a&gt;, which makes Monte Carlo exponentially hard.&lt;/p&gt;&#xA;&lt;p&gt;Rather than discuss this in detail here, see the discussion on the sign problem on the &lt;a href=&quot;https://physics.stackexchange.com/q/243027&quot;&gt;physics SE.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-11-21T13:32:33.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3783" PostTypeId="2" ParentId="3780" CreationDate="2020-11-21T13:55:40.563" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Is this the wrong assumption I am using for initializing starting_magnetization? If yes, What should be the right fact for choosing the initialization value?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The initial magnetization is not so important. I will tell you how to generate the input file with a convenient method in which the initial magnetization will be considered automatically. I will assume that you are calculating the MnCo2Si in the ferromagnetic phase. The structure is shown below and can be download from &lt;a href=&quot;https://materialsproject.org/materials/mp-4492/#&quot; rel=&quot;noreferrer&quot;&gt;the materials project database&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/emX2g.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/emX2g.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once you obtain the structure, you can generate an input file for self-consistent calculation with this &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;noreferrer&quot;&gt;online website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TlWKp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TlWKp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The input file is as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/43yW9.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/43yW9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In particular, the downloaded PWscf.zip file will contain the corresponding pseudopotential files.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I also use 'tetrahedra' smearing for magnetic systems?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The system is metal, you should use the smearing method properly.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-21T13:55:40.563" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3784" PostTypeId="2" ParentId="3752" CreationDate="2020-11-21T15:27:30.607" Score="5" Body="&lt;p&gt;You have already detailed what the physics contained in the exchange-correlation functional is.&lt;/p&gt;&#xA;&lt;p&gt;Self-interaction error is not physical; it is an artifact in density functional approximations that arises from imperfect cancellation of the Coulomb and exchange interactions. Although several schemes have been suggested to remove self-interaction error, the one by Perdew and Zunger being the most well-known, these schemes tend to be problematic in that they are&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;hideously expensive computationally&lt;/li&gt;&#xA;&lt;li&gt;hard to minimize properly (e.g. the Perdew-Zunger functional requires &lt;em&gt;complex&lt;/em&gt; orbitals even for a gas-phase atom without external fields)&lt;/li&gt;&#xA;&lt;li&gt;may break molecular symmetries&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Another failure of density functional approximations is in modeling systems with strong correlations, such as many transition metal complexes and multiple bond breaking.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-11-21T15:27:30.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3785" PostTypeId="1" AcceptedAnswerId="4800" CreationDate="2020-11-21T18:51:38.430" Score="11" ViewCount="418" Body="&lt;p&gt;I know that it is possible to get order constitution data for phases when using Thermo-Calc's GUI (e.g. to get &amp;quot;BCC_B2 DISORD&amp;quot; instead of just &amp;quot;BCC_B2&amp;quot;) for a single equilibrium calculation, but I can't find a way to do it in TC-Python. I can get ordering data from TC_Python when using the PropertyDiagram module, but again, I am interested in getting it from single equilibrium calculations. I think it might be possible to do by using the &amp;quot;Sublattice()&amp;quot; method on the individual phases, but I haven't been able to get it to work. If someone could provide some example code how to do this or at least outline the approach that would be great!&lt;/p&gt;&#xA;&lt;p&gt;Here's a basic example of how I would get phase data with TC_python. This does NOT tell me the order constitution which is the problem.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from tc_python import *&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;This example shows how to create a single equilibrium calculation                &#xA;from a ternary system and configure it to calculate the solidus &#xA;and liquidus temperature using fixed phase conditions for the &#xA;liquid phase. &#xA; &#xA;There can be multiple solutions to a fixed phase condition and it is &#xA;good practice to perform a regular equilibrium calculation close to &#xA;where the phase transition is. This example starts with an equilibrium &#xA;calculation at 1700K in order to get good start values.           &#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;&#xA;def list_stable_phases(calc_result):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    List the stable phases and their amount on screen.&#xA;&#xA;    Args:&#xA;        calc_result: Calculation result from an equilibrium calculation&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    stable_phases = calc_result.get_stable_phases()&#xA;    for phase in stable_phases:&#xA;        print(&amp;quot;Amount of &amp;quot; + phase + &amp;quot; = {0:.3f}&amp;quot;.format(calc_result.get_value_of('NP(' + phase + ')')))&#xA;&#xA;&#xA;with TCPython() as session:&#xA;    # create equilibrium calculation object and set conditions&#xA;    eq_calculation = (&#xA;        session.&#xA;            set_cache_folder(os.path.basename(__file__) + &amp;quot;_cache&amp;quot;).&#xA;            select_database_and_elements(&amp;quot;FEDEMO&amp;quot;, [&amp;quot;Fe&amp;quot;, &amp;quot;Cr&amp;quot;, &amp;quot;C&amp;quot;]).&#xA;            get_system().&#xA;            with_single_equilibrium_calculation().&#xA;            set_condition(ThermodynamicQuantity.temperature(), 1700.0).&#xA;            set_condition(ThermodynamicQuantity.mass_fraction_of_a_component(&amp;quot;Cr&amp;quot;), 0.1).&#xA;            set_condition(ThermodynamicQuantity.mass_fraction_of_a_component(&amp;quot;C&amp;quot;), 0.01)&#xA;&#xA;    )&#xA;&#xA;    # calculate equilibrium and list stable phases&#xA;    calc_result = eq_calculation.calculate()&#xA;    list_stable_phases(calc_result)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="1410" LastEditDate="2021-04-21T23:07:21.570" LastActivityDate="2021-04-23T17:53:33.563" Title="How to get order constitution data for single equilibrium calculation in Thermo-Calc's TC Python module?" Tags="|python|thermodynamics|gibbs-free-energy|calphad|thermo-calc|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3786" PostTypeId="1" CreationDate="2020-11-21T18:55:34.203" Score="12" ViewCount="1341" Body="&lt;p&gt;Even though it is a powerful tool, Quantum ESPRESSO's hardware requirements are very high. For instance, to evaluate optical properties, even for structures with tens of atoms, Quantum ESPRESSO can require more than 100GB of RAM. What about VASP?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2020-11-23T20:26:08.050" LastActivityDate="2020-11-24T00:29:12.333" Title="How many GB of RAM would be needed for VASP to evaluate optical properties of a material?" Tags="|vasp|quantum-espresso|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3787" PostTypeId="1" AcceptedAnswerId="3788" CreationDate="2020-11-22T14:27:10.593" Score="17" ViewCount="747" Body="&lt;p&gt;This question is coming from an answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2363/analytic-hessians-for-meta-gga-functionals&quot;&gt;to one of my previous questions&lt;/a&gt;. During optimizations, QM programs usually compute the gradient(first derivative) analytically, and take a guess of the hessian (second derivatives). If the hessian is needed a coupled-perturbed hartree fock (CPHF) or coupled-perturbed Kohn-Sham (CPKS) is usually required which is very computationally expensive. From what I have been told, the gradient does not need CPHF, it can be calculated directly from the SCF.&lt;/p&gt;&#xA;&lt;p&gt;My question is why the second derivative is so much more expensive than the first derivative? For a compound I was working on, the first derivatives took about 2 minutes, while the second derivatives took almost 15 minutes to run. That's more than 7 times! What I don't understand is that if the SCF solution can be differentiated once w.r.t the coordinates, then why can't it be differentiated twice?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="7" LastEditDate="2021-07-12T01:39:13.137" LastActivityDate="2021-09-29T15:30:07.560" Title="Why is CPHF/CPKS necessary for calculating second derivatives?" Tags="|geometry-optimization|kohn-sham|hartree-fock|response-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3788" PostTypeId="2" ParentId="3787" CreationDate="2020-11-22T18:25:36.623" Score="14" Body="&lt;p&gt;It comes down to the fact that HF and KS both are variational methods. This &lt;a href=&quot;https://www.lct.jussieu.fr/pagesperso/toulouse/enseignement/molecular_properties.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;short article&lt;/a&gt; by Julien Toulouse gives a great description of ways to compute static/dynamic response properties. I'll just summarize the relevant portion.&lt;/p&gt;&#xA;&lt;p&gt;We can compute derivatives of the energy with respect to any variable &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{dE}{dx}=\frac{\partial E}{\partial x}+\sum_i \frac{\partial E}{\partial p_i}|_{\mathbf{p}=\mathbf{p}^0}  \frac{\partial p_i^0}{\partial x}$$&lt;/span&gt;&#xA;Here we are writing the derivative in two terms. The first is due to the explicit dependence of the energy on the variable &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. The latter term is due to &lt;em&gt;implicit&lt;/em&gt; dependence, with the energy depending on particular wavefunction parameters &lt;span class=&quot;math-container&quot;&gt;$\mathbf{p}$&lt;/span&gt;, which in turn may depend on &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. For SCF methods, these parameters are just the MO coefficients &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For a general method, this would require some type of response calculation to solve, as we typically don't have an explicit form for &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial p_i^0}{\partial x}$&lt;/span&gt;. However, since the energy for HF/KS is  variational &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial E}{\partial p_i}|_{\mathbf{p}=\mathbf{p}^0}=0$&lt;/span&gt;, which zeros out this term.&lt;/p&gt;&#xA;&lt;p&gt;So to compute the forces with HF/KS, we only need to consider the explicit dependence of the energy on the nuclear positions. However, once we want to compute the Hessian, we can no longer ignore this implicit term. If we write the Hessian as a derivative of the force in the same form as above, the force is not variationally optimal and so this terms doesn't cancel. Thus we need to determine the dependence of the MO coefficients on the nuclear positions, which is typically done using CPHF/CPKS.&lt;/p&gt;&#xA;&lt;p&gt;You can get a rough order of magnitude estimate of a 2nd order property from just the explicit term. For example, when computing the polarizability (2nd derivative of the energy with respect to an applied electric field) Gaussian will print out an approximate polarizability, which it calculates by just contracting the dipole with itself rather than the perturbed electric density. While this can sometimes be close to the final result, I'm not aware of any formal bound on the size of the implicit contribution, so in general it would be a major approximation to neglect the perturbation of the density.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-09-29T15:30:07.560" LastActivityDate="2021-09-29T15:30:07.560" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3789" PostTypeId="5" CreationDate="2020-11-22T18:28:59.940" Score="0" Body="&lt;p&gt;&lt;strong&gt;Examples:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3759/5&quot;&gt;Would the increase in cost, of a double-sided whiteboard, make it worth it to engineer such a device?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2093/5&quot;&gt;Artificial muscles and their efficiency&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-22T18:28:59.940" LastActivityDate="2020-11-22T18:28:59.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3790" PostTypeId="4" CreationDate="2020-11-22T18:28:59.940" Score="0" Body="Questions related to the design of materials (cost-effectiveness, functionality, fabrication procedures, etc.)" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-22T18:28:59.940" LastActivityDate="2020-11-22T18:28:59.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3791" PostTypeId="1" CreationDate="2020-11-22T22:32:40.350" Score="15" ViewCount="1199" Body="&lt;p&gt;I understand that a harmonic picture of the potential in a material isn't enough to study lattice dynamics thoroughly. The quasi-harmonic approximation is a good workaround and helps incorporate thermal expansion effects in the lattice.&lt;/p&gt;&#xA;&lt;p&gt;I've read and heard at times that a so-and-so material is anharmonic. The implication being that neither of harmonic or quasi-harmonic approximations suffices and a non-harmonic expansion of the potential is required.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can we decide which material needs what, or specifically that a particular material &lt;em&gt;is&lt;/em&gt; anharmonic?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A pseudo-related question but one that I thought would do better as a separate thread: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3792/is-there-an-upper-limit-of-temperature-after-which-the-quasi-harmonic-approximat&quot;&gt;Is there an upper limit of temperature after which the quasi-harmonic approximation (QHA) fails?&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-11-27T20:24:24.067" LastActivityDate="2020-11-27T20:24:24.067" Title="What does it mean to say a material is 'anharmonic'?" Tags="|phonons|lattice-dynamics|quasi-harmonic-approximation|harmonic-approximation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3792" PostTypeId="1" CreationDate="2020-11-22T22:40:53.567" Score="9" ViewCount="265" Body="&lt;p&gt;I can't seem to articulate what made me ask this question but it sprang up when I asked: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3791/what-does-it-mean-to-say-a-material-is-anharmonic&quot;&gt;What does it mean to say a material is &amp;#39;anharmonic&amp;#39;?&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I've heard before that the electronic entropy becomes a force to reckon at extreme (near melting) temperatures since electrons acquire tremendous energy at such temperatures. Does the failure of the QHA have something to do with this? I don't as such understand the physical meaning (rather the implication) of 'coupling' but is electron-phonon coupling the demise of QHA? Also, does phonon-phonon coupling have any role to play here?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-06-11T17:27:38.287" LastActivityDate="2021-06-12T06:58:59.317" Title="Is there an upper limit of temperature after which the quasi-harmonic approximation (QHA) fails?" Tags="|phonons|lattice-dynamics|temperature|quasi-harmonic-approximation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3793" PostTypeId="2" ParentId="3791" CreationDate="2020-11-23T08:17:24.583" Score="15" Body="&lt;p&gt;This is a difficult question without a straight-forward answer. In general you have to perform a test to decide whether the harmonic approximation is sufficient or whether you need to include higher order anharmonic terms in the potential expansion. Due to the computational cost of including anharmonic terms, very often systems are assumed to be harmonic without further checks, which can be problematic.&lt;/p&gt;&#xA;&lt;p&gt;Having said this, here are a few thoughts one can also use as a starting point. At equilibrium, a material sits at a local minimum of the potential energy surface. The harmonic approximation is then based on the assumption that the atomic nuclei/ions do not move very far away from this minimum, and that a second order expansion of the energy around the minimum is sufficient to describe atomic vibrations. Therefore, the harmonic approximation will break down when the atoms move significantly far away from equilibrium. A few examples include:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;High temperature. At sufficiently high temperature, solids melt, and all materials will behave in an anharmonic manner sufficiently close to melting. But what temperature is that? It is strongly material dependent. A starting estimate could be to use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Melting_point#Predicting_the_melting_point_of_substances_(Lindemann%27s_criterion)&quot; rel=&quot;noreferrer&quot;&gt;Lindemann criterion&lt;/a&gt; which, roughly speaking, states that the melting temperature of a material corresponds to the atomic vibrational amplitudes approaching 15-30% of the interatomic distance. Therefore, if your atoms are vibrating anywhere near these amplitudes, it is likely anharmonic terms are important.&lt;/li&gt;&#xA;&lt;li&gt;Light elements. The vibrational amplitudes of an element are larger the smaller the mass. This means that anharmonic terms tend to be larger for the lighter elements, and indeed in some like hydrogen (lightest of all elements) they can dominate even at zero temperature (quantum fluctuations are anharmonic).&lt;/li&gt;&#xA;&lt;li&gt;Structural phase transitions. Even if your system is well below the melting point or not made of light elements, structural phase transitions can be dominated by anharmonic vibrational terms. The most well-known example of this are perhaps the perovskite family, which typically exhibits a series of temperature-induced structural phase transitions from high symmetry high temperature cubic to lower temperature lower symmetry tetragonal, orthorhombic, etc. The higher symmetry structures correspond to saddle points of the potential energy surface (rather than minima), and the structures are stabilized to those points through anharmonic vibrations. A purely harmonic description would lead to the presence of imaginary modes that would drive you towards the lowest energy structure, and fail to describe the stability of the higher symmetry higher temperature structures.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-11-23T08:17:24.583" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3794" PostTypeId="1" AcceptedAnswerId="3799" CreationDate="2020-11-23T12:10:45.353" Score="9" ViewCount="1256" Body="&lt;p&gt;Recently, I learnt that basis sets can be contracted as segmented (like def2 or 6-31G) or general (like cc-PVTZ, or ANO). The general contraction allows all the primitives to appear in all shells, whereas segmented does not do that. Most books on quantum chemistry also mention that QM programs usually cannot handle general contraction very well, and instead they duplicate the primitives for each shell, and computes the same integrals multiple times.&lt;/p&gt;&#xA;&lt;p&gt;However, there is not much written about which QM programs can actually handle general contractions well, and which programs can't. The books mention a method called screening which prevents the same integral being calculated twice.&lt;/p&gt;&#xA;&lt;p&gt;The manuals of the common softwares (Gaussian, GAMESS, orca etc.) don't mention clearly if they have any such method. (To add to the problem, main parts of the manuals are often old, and has not been updated as the program got updated). For example, GAMESS manual mentions an 'integral screening' but that seems to refer to ignoring 2e-integrals that contribute very little to the energy. Gaussian manual &lt;a href=&quot;https://gaussian.com/integral/&quot; rel=&quot;nofollow noreferrer&quot;&gt;mentions&lt;/a&gt; that general contraction basis sets can be transformed to remove primitives that have &lt;span class=&quot;math-container&quot;&gt;$\mathrm{&amp;lt;10^{-4}}$&lt;/span&gt; coefficients, but I am not sure if this is the same as screening. Orca mentions that segmented basis sets are faster, but doen't mention if it has anything to deal with general basis sets.&lt;/p&gt;&#xA;&lt;p&gt;So, my questions are - 1) Which programs at present can properly use generally contracted basis sets (without duplicating primitives)? 2) If this can be done simply by checking if an integral has been calculated before, then why is it difficult to implement?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2020-11-24T17:31:18.813" LastActivityDate="2020-11-24T17:31:18.813" Title="Which software is good with generally contracted basis sets?" Tags="|basis-sets|gaussian|integrals|gamess|benchmark-timings|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3795" PostTypeId="2" ParentId="3794" CreationDate="2020-11-23T14:32:55.817" Score="8" Body="&lt;p&gt;&lt;strong&gt;Integral Screening&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is possible to place upper bounds on integrals based on the Cauchy-Schwartz inequality:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left( a a | b b \right) \ge \left( a c | b d \right)&#xA;$$&lt;/span&gt;&#xA;If the first integral is computed and deemed insignificant, the latter is as well. One can further combine this with the appropriate density matrix element and decide that the resulting contribution to the Fock/Kohn-Sham matrix is insignificant and can be discarded. Obviously, this applies to the case of a &amp;quot;direct&amp;quot; SCF, in which most or all integrals are recalculated on every iteration.&lt;/p&gt;&#xA;&lt;p&gt;I have not yet heard of other uses for the word screening in relation to integrals. It is not entirely unreasonable to discard a primitive from a contracted basis function if its coefficient is too small, but I think this is a decision to be taken by the user, that is, by using custom input of the basis set.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why recalculate integrals&lt;/strong&gt; (&lt;em&gt;If this can be done simply by checking if an integral has been calculated before, then why is it difficult to implement?&lt;/em&gt;)&lt;/p&gt;&#xA;&lt;p&gt;There are too many integrals to keep them in main memory. Some programs may write some to disk, but there is a non-zero writing/reading time cost associated with that. Some programs try to be smart and put the most expensive integrals on disk.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Which programs at present can properly use generally contracted basis sets (without duplicating primitives)?&lt;/em&gt;&#xA;This is hard to judge. Some programs may provide the references to the integral algorithm used (In case of Gaussian, I found: M. Head-Gordon and J. A. Pople, J. Chem. Phys., 89 (1988) 5777), where it may take an expert to decided whether the algorithm is geared towards general or segmented.&lt;/p&gt;&#xA;&lt;p&gt;The reason why some algorithms work well with one but not the other is that in case of general contraction, one must keep different intermediates in memory to be efficient. If the basis set is not constructed accordingly, one ends up not benefitting from keeping the intermediates for which other savings/more efficient ways were discarded. I found the PRISM algorithm paper illuminating, together with the papers that cite it, it may be a decent entry point into the subject: P. M. W. Gill, J. A. Pople, Int. J. of Quantum Chem., Vol. 40, (1991) 753.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-11-23T14:32:55.817" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3796" PostTypeId="2" ParentId="3611" CreationDate="2020-11-23T16:10:36.490" Score="8" Body="&lt;h2 id=&quot;metadynamics-1i9d&quot;&gt;Metadynamics&lt;/h2&gt;&#xA;&lt;p&gt;One way to make your dynamics explore more of phase space is to force it out of regions it has already explored. Metadynamics does this by intermittently adding bias potentials (typically Gaussians) to the system Hamiltonian. These bias potentials are functions of user defined collective variables, which should be chosen such that states of interest can be clearly distinguished from each other. The figure below gives a good example of how metadynamics proceeds; a common analogy is that you are exploring a potential energy surface that is slowly being filled with sand/water around the current state. In the long time limit, the bias potentials should sum up to the free energy, but with the opposite sign.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/flE97.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/flE97.png&quot; alt=&quot;Example of Metadynamics&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The main difficultly of this method is determining what collective variables need to be considered in order to fully describe your system. Its an area of active of research to develop fairly general collective variables (or at least guidelines for their selection) for a variety of systems. As an example of what these collective variables can look like, consider &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.119.015701&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;, a paper by Michele Parrinello, who originally proposed the concept of metadynamics. In this paper, they define an enthalpic and an entropic collective variables to model crystal formation of aluminum and sodium.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pablo M. Piaggi, Omar Valsson, and Michele Parrinello PRL &lt;strong&gt;119&lt;/strong&gt;, 015701 (2017)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-21T03:37:03.657" LastActivityDate="2021-07-21T03:37:03.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3797" PostTypeId="2" ParentId="3791" CreationDate="2020-11-23T17:27:34.280" Score="4" Body="&lt;p&gt;A &amp;quot;pure harmonic system&amp;quot; does not allow opportunity for evolution. It is the equivalent of a fixed point. In initial consideration, its stability seems appealing, as it appears to be a goal (or “the goal”) of an imperfect system. However, it only embodies that moniker once, and change is the only real constant. Pure harmonics are fragile, brittle, and only stable conditionally. &lt;em&gt;What's really appealing is resonance.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="1570" LastEditorUserId="5" LastEditDate="2020-11-23T19:03:57.710" LastActivityDate="2020-11-23T19:03:57.710" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3798" PostTypeId="1" CreationDate="2020-11-23T18:14:11.373" Score="5" ViewCount="523" Body="&lt;p&gt;Recently I am trying to calculate the BSE and IQP transition dipole based on VASP lecture on &lt;a href=&quot;https://www.vasp.at/wiki/images/2/29/VASP_lecture_BSE.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;BSE&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Plotting_the_BSE_fatband_structure_of_Si&quot; rel=&quot;nofollow noreferrer&quot;&gt;BSE fatband&lt;/a&gt;. However, I have a few questions regarding the BSE and IQP oscillator strength. From the slides, it says that the BSE oscillator strength is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;| ( f_{ck} - f_{vk} ) F_{cvk} A_{cvk} |^2&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the IQP oscillator strength is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2} F_{cvk} = \dfrac{\langle \psi_c | p_i | \psi_v \rangle}{E_{ck} - E_{vk}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is about the parameters in the two formula and how they connect to each other:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;In the BSE formula, is &lt;span class=&quot;math-container&quot;&gt;$( f_{ck} - f_{vk} )$&lt;/span&gt; set to be 1? Or it depends on smearing?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Does &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; in the formula for &lt;span class=&quot;math-container&quot;&gt;$F_{cvk}$&lt;/span&gt; mean Cartesian coordinate? If so, do I need to add &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; contributions to get a total &lt;span class=&quot;math-container&quot;&gt;$F_{cvk}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Are &lt;span class=&quot;math-container&quot;&gt;$ \langle  \psi_c | p_i | \psi_v \rangle$&lt;/span&gt; and &lt;code&gt;CDER_BETWEEN_STATES(NB1,NB2,NK,ISP,1:3)&lt;/code&gt; the same parameter? If so, what is the unit of &lt;span class=&quot;math-container&quot;&gt;$ \langle \psi_c | p_i | \psi_v \rangle$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Since the &lt;code&gt;WAVEDER&lt;/code&gt; contains spin up and spin down, do we need to add them up to get a total &lt;span class=&quot;math-container&quot;&gt;$F_{cvk}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$A_{cvk}$&lt;/span&gt;, I notice that in &lt;code&gt;BSEFATBAND&lt;/code&gt;, column 6 is the absolute value of coupling coefficient (radius of circles), and column 9/10 is the real/imaginary part of the coupling coefficient. I notice that we need to multiple &lt;span class=&quot;math-container&quot;&gt;$Nk^3$&lt;/span&gt; to column 9/10 to make the absolute value equal to column 6. I do not know which &lt;span class=&quot;math-container&quot;&gt;$A_{cvk}$&lt;/span&gt; should I use to get the BSE oscillator strength.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;As we can get &lt;span class=&quot;math-container&quot;&gt;$F_{cvk}$&lt;/span&gt; from &lt;code&gt;WAVEDER&lt;/code&gt;, &lt;span class=&quot;math-container&quot;&gt;$A_{cvk}$&lt;/span&gt; from &lt;code&gt;BSEFATBAND&lt;/code&gt;, can we use these parameters to get the BSE oscillator strength output in &lt;code&gt;vasprun.xml&lt;/code&gt;? I have tried to do this but I could not establish a correspondence between the BSE oscillator strength formula and the &lt;code&gt;vasprun.xml&lt;/code&gt; output.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Any insights for any questions would be super helpful to my research. Thank you for your kind help!&lt;/p&gt;&#xA;&lt;p&gt;Best regards,&lt;/p&gt;&#xA;&lt;p&gt;Bo&lt;/p&gt;&#xA;" OwnerUserId="1022" LastEditorUserId="1218" LastEditDate="2021-03-11T22:47:46.533" LastActivityDate="2022-04-15T23:40:57.810" Title="BSE and IQP oscillator strength from VASP" Tags="|vasp|gw-bse|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3799" PostTypeId="2" ParentId="3794" CreationDate="2020-11-23T22:44:25.910" Score="8" Body="&lt;h1&gt;General vs segmented contraction&lt;/h1&gt;&#xA;&lt;p&gt;Unless one is using a fully decontracted a.k.a &amp;quot;primitive&amp;quot; basis set, one uses contracted Gaussian-type orbitals (cGTOs), which are given as a linear combination of the primitive Gaussian-type orbitals (pGTOs):&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\chi_i^\text{cGTO}({\bf r}) = \sum_{\alpha} d_{\alpha i} \chi_\alpha^\text{pGTO}({\bf r}) $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can write the cGTOs in terms of the pGTOs as a matrix equation: &lt;span class=&quot;math-container&quot;&gt;${\bf X}^\text{cGTO} = {\bf X}^\text{pGTO} {\bf D}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume our primitive exponents are given as a vector &lt;span class=&quot;math-container&quot;&gt;$(\alpha_1, \alpha_2, \dots, \alpha_N)^{\rm T}$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\alpha_1 &amp;gt; \alpha_2 &amp;gt; \dots &amp;gt; \alpha_N$&lt;/span&gt;. In a generally contracted basis set, &lt;span class=&quot;math-container&quot;&gt;${\bf D}$&lt;/span&gt; typically looks like&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{D}=\left(\begin{array}{cccccc}&#xA;x &amp;amp; \cdots &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;\vdots &amp;amp; \ddots &amp;amp; \vdots &amp;amp; \vdots &amp;amp; \vdots &amp;amp; \vdots\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 1 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 1&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; marks a non-zero entry. You have &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; primitives (rows in D), which are contracted to &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atomic orbitals (columns filled with the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;s), and then you have freed up the few most diffuse functions as primitive functions to be able to describe changes in the valence region.&lt;/p&gt;&#xA;&lt;p&gt;Often the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atomic orbitals are orthonormal to each other (&lt;span class=&quot;math-container&quot;&gt;${\bf D}^{\rm T} {\bf SD}={\bf 1}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; is the overlap), but this is not always the case; IIRC the correlation consistent sets for the transition metals have significant overlap between the contracted functions, since the first functions come from atomic Hartree-Fock calculations, while the last come from configuration interaction calculations and are not orthogonal to the Hartree-Fock orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The thing about generally contracted basis sets is that there is some flexibility in the way you can pick the functions. All that matters in the end is the &lt;em&gt;span&lt;/em&gt; of the basis, so you are free to make transformations to your basis as long as the span stays the same. This means you're free to substract columns from each other: for example, if &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; form a linearly independent basis, &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$x-y$&lt;/span&gt; also span the same basis.&lt;/p&gt;&#xA;&lt;p&gt;Now, note that I have two free primitives in the basis, which means these functions can be fully represented by the basis. I can just drop these functions from the general contraction, since I can eliminate the coefficients by substracting the free primitives with the correct weight from the contracted functions. (This is called a Davidson rotation and is what &amp;quot;optimize general contractions&amp;quot; mean on the Basis Set Exchange; see &lt;a href=&quot;https://doi.org/10.1016/0009-2614(96)00917-7&quot; rel=&quot;noreferrer&quot;&gt;Chem. Phys. Lett. 1996, 260, 514−518&lt;/a&gt;.)&#xA;I now get&#xA;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{D}=\left(\begin{array}{cccccc}&#xA;x &amp;amp; \cdots &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;\vdots &amp;amp; \ddots &amp;amp; \vdots &amp;amp; \vdots &amp;amp; \vdots &amp;amp; \vdots\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 1 &amp;amp; 0\\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 1&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But, it does not stop here: I can eliminate entries in the fully contracted block, too, by adding and substracting vectors. Let's say the contracted block looks like this:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{D}=\left(\begin{array}{cccc}&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I can take the first column from the left and substract it from the other ones to make the coefficient of the tightest exponent vanish. Next, I take the second column and make the coefficient of the second-tightest function go away.. and keep going until I've made it to the right-most column.&lt;/p&gt;&#xA;&lt;p&gt;I can also do the same thing in reverse: I take the last column and make the most diffuse coefficient vanish in the other columns, and repeat until I am back on the right. Then I get&#xA;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{D}=\left(\begin{array}{cccc}&#xA;x &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;x &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;0 &amp;amp; x &amp;amp; x &amp;amp; x\\&#xA;0 &amp;amp; 0 &amp;amp; x &amp;amp; x\\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; x&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Suddenly, you see that the contraction matrix has developed quite a few zeros. If the contraction length is not very long, &lt;span class=&quot;math-container&quot;&gt;$N\approx K$&lt;/span&gt;, the columns are mostly zeros (the extreme case is &lt;span class=&quot;math-container&quot;&gt;$N=K$&lt;/span&gt; where you can choose &lt;span class=&quot;math-container&quot;&gt;${\bf D}={\bf 1}$&lt;/span&gt; i.e. to just use uncontracted primitives).&lt;/p&gt;&#xA;&lt;p&gt;Moreover, one can get even more sparsity by discarding small elements &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; in the columns, and (possibly) reoptimizing the contraction coefficients and exponents for a pre-specified sparsity pattern, e.g.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{D}=\left(\begin{array}{cccc}&#xA;x &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\&#xA;x &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;0 &amp;amp; x &amp;amp; 0 &amp;amp; 0\\&#xA;0 &amp;amp; x &amp;amp; x &amp;amp; 0\\&#xA;0 &amp;amp; 0 &amp;amp; x &amp;amp; x\\&#xA;0 &amp;amp; 0 &amp;amp; x &amp;amp; x\\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; x&#xA;\end{array}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Frank Jensen has written a very nice article on this a few years ago, see &lt;a href=&quot;https://doi.org/10.1021/ct401026a&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 2014, 10, 3, 1074–1085&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h1&gt;Integral evaluation&lt;/h1&gt;&#xA;&lt;p&gt;What does this have to do with integral evaluation? The two-electron integrals &lt;span class=&quot;math-container&quot;&gt;$(pq|rs)$&lt;/span&gt; can be evaluated analytically for Gaussian basis functions. However, the analytical integrals are known only for the &lt;strong&gt;primitives&lt;/strong&gt;, which means that to get the integrals for the contracted functions one has to calculate&#xA;&lt;span class=&quot;math-container&quot;&gt;$(pq|rs) = \sum_{\alpha \beta \gamma \delta} d_{\alpha p} d_{\beta q} d_{\gamma r} d_{\delta s} (\alpha \beta|\gamma \delta)$&lt;/span&gt;, instead, where &lt;span class=&quot;math-container&quot;&gt;$\alpha \beta \gamma \delta$&lt;/span&gt; stand for the primitive functions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If&lt;/strong&gt; you have a segmented basis set, where there are a lot of zeros in the contraction matrix, it is more efficient to evaluate the integrals one shell quartet at a time; that is, you recompute all the primitive integrals for each &lt;span class=&quot;math-container&quot;&gt;$(pq|rs)$&lt;/span&gt; you're aiming for, because most primitives only contribute to a single contracted basis function. This means that you have simpler code, but also has the additional benefit that you can easily perform the contractions &lt;em&gt;within&lt;/em&gt; the two-electron integral evaluation algorithm, which makes some steps cheaper in the computation, depending on the used integrals evaluation algorithm. Indeed, most codes assume this approach; e.g. this is how Gaussian, Psi4, Q-Chem, and Orca operate.&lt;/p&gt;&#xA;&lt;p&gt;However, if you have a generally contracted basis set (especially when &lt;span class=&quot;math-container&quot;&gt;$K \gg N$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N \gg 1$&lt;/span&gt;), the programs that rely internally on segmented basis sets run into troble, as instead of computing the &lt;span class=&quot;math-container&quot;&gt;$K^4$&lt;/span&gt; primitive shell quartets, you basically need to compute the &lt;span class=&quot;math-container&quot;&gt;$K^4$&lt;/span&gt; quartets &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt; times. Screening for combinations of primitives that have small contributions helps a bit, but this is still extremely slow.&lt;/p&gt;&#xA;&lt;p&gt;As far as I understand, the generally contracted programs compute &lt;strong&gt;all&lt;/strong&gt; primitive shell quartets &lt;strong&gt;once&lt;/strong&gt;, and then form the &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt; contractions with the &lt;span class=&quot;math-container&quot;&gt;${\bf D}$&lt;/span&gt;'s per the equation above to get the target integrals &lt;span class=&quot;math-container&quot;&gt;$(pq|rs)$&lt;/span&gt;. (Disclaimer: I have never written a general contraction code.)&lt;/p&gt;&#xA;&lt;p&gt;Programs that handle generally contracted basis sets well are far fewer, but they do exist. For instance, &lt;a href=&quot;https://gitlab.com/Molcas/OpenMolcas&quot; rel=&quot;noreferrer&quot;&gt;OpenMolcas&lt;/a&gt; handles general contractions. &lt;a href=&quot;https://github.com/pyscf/pyscf&quot; rel=&quot;noreferrer&quot;&gt;PySCF&lt;/a&gt; is also very efficient with generally contracted basis set. Both programs are open source and freely available. &lt;a href=&quot;https://github.com/nwchemgit/nwchem&quot; rel=&quot;noreferrer&quot;&gt;NWChem&lt;/a&gt; is also open source and freely available, and claims to support general contractions (see the opening paragraph of &lt;a href=&quot;https://nwchemgit.github.io/Basis.html&quot; rel=&quot;noreferrer&quot;&gt;their documentation on basis sets&lt;/a&gt;), but it's so slow that I'm not sure whether this is really the case; see below.&lt;/p&gt;&#xA;&lt;p&gt;On the commercial side, IIRC Molpro has excellent support for general contractions, and is faster than OpenMolcas.&lt;/p&gt;&#xA;&lt;h1&gt;Benchmarks&lt;/h1&gt;&#xA;&lt;p&gt;To see whether your program supports general contractions is quite simple: just try running e.g. a transition metal system with a correlation consistent basis set. For instance, in cc-pVDZ the first-row transition metals have a [20s16p8d2f|6s5p3d1f] contraction pattern, so &lt;span class=&quot;math-container&quot;&gt;$K=20$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N=6$&lt;/span&gt; for s orbitals, &lt;span class=&quot;math-container&quot;&gt;$K=16$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N=5$&lt;/span&gt; for p orbitals, and &lt;span class=&quot;math-container&quot;&gt;$K=8$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N=3$&lt;/span&gt; for d orbitals, which make them quite heavy.&lt;/p&gt;&#xA;&lt;p&gt;Although I'm usually against mindless benchmarks, here one makes sense. I'll take the Zn atom and Zn2 dimer (R=2.3 Å) as examples, since they're nice closed-shell systems.&lt;/p&gt;&#xA;&lt;p&gt;I performed all benchmarks on my laptop with 4 cores, using Fedora 32 packages: &lt;code&gt;psi4-1.3.2-2.fc32.x86_64&lt;/code&gt;, &lt;code&gt;python3-pyscf-1.7.5-1.fc32.x86_64&lt;/code&gt; employing the optimized integrals library &lt;code&gt;qcint-4.0.5-1.fc32.x86_64&lt;/code&gt;, &lt;code&gt;nwchem-openmpi-7.0.2-1.fc32.x86_64&lt;/code&gt;, and &lt;code&gt;OpenMolcas-20.10-1.fc32.x86_64&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Psi4&lt;/h2&gt;&#xA;&lt;p&gt;As I said above, Psi4 is an example of a program that assumes segmented basis sets.&lt;/p&gt;&#xA;&lt;p&gt;Setting &lt;code&gt;scf_type = pk&lt;/code&gt; to enforce exact integrals instead of the default use of density fitting (which would make the calculation a LOT faster), the HF calculation on the zinc atom  took about 19 seconds wall time. Final energy -1777.84665520791896&lt;/p&gt;&#xA;&lt;p&gt;Running the dimer took considerably longer: 216 seconds of wall time. Final energy -3555.64477390092725&lt;/p&gt;&#xA;&lt;h2&gt;PySCF&lt;/h2&gt;&#xA;&lt;p&gt;The PySCF calculation on the Zn atom runs in about 0.7 seconds of wall time. Final energy -1777.846655207936010&lt;/p&gt;&#xA;&lt;p&gt;The Zn2 dimer took about 1.4 seconds wall time. Final energy -3555.644773900906785&lt;/p&gt;&#xA;&lt;h2&gt;OpenMolcas&lt;/h2&gt;&#xA;&lt;p&gt;Running the Zn atom took about 2 seconds. Final energy -1777.846655208&lt;/p&gt;&#xA;&lt;p&gt;The Zn2 dimer took about 5 seconds. Final energy -3555.644773901&lt;/p&gt;&#xA;&lt;h2&gt;NWChem&lt;/h2&gt;&#xA;&lt;p&gt;After running for 5 minutes on four cores for the Zn atom, without seeing even one iteration of SCF, I cancelled the execution...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-11-23T22:49:54.347" LastActivityDate="2020-11-23T22:49:54.347" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3800" PostTypeId="2" ParentId="3786" CreationDate="2020-11-24T00:29:12.333" Score="7" Body="&lt;p&gt;This question is kind of general. I will outline some points related.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Firstly, it depends on the theoretical levels that you use to calculate the optical properties. In general, there are three levels:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Independent level;&lt;/li&gt;&#xA;&lt;li&gt;RPA (random phase approximation) level;&lt;/li&gt;&#xA;&lt;li&gt;GW&amp;amp;BSE level;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The first one is memory friendly in terms of the empty bands contained. However, the last two are very memory-consuming even for a small system.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Secondly, it depends on how large your system and whether includes the spin-orbit coupling or not.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Thirdly, you must test the parameters to obtain converged results. All these parameters are closely related to memory consumption. In VASP, the key parameters are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;KMESH&lt;/li&gt;&#xA;&lt;li&gt;ENCUT&lt;/li&gt;&#xA;&lt;li&gt;BANDS &amp;amp; ENCUTGW&lt;/li&gt;&#xA;&lt;li&gt;NBANDSV&lt;/li&gt;&#xA;&lt;li&gt;NBANDSO&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For your example with tens of atoms, to obtain converged results I believe 100G memory is not enough in VASP. In summary, you can test it and get some feeling.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-24T00:29:12.333" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3801" PostTypeId="2" ParentId="3794" CreationDate="2020-11-24T04:05:55.193" Score="6" Body="&lt;h2&gt;MOLPRO&lt;/h2&gt;&#xA;&lt;p&gt;Continuing Susi's excellent benchmarking for &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn_2}$&lt;/span&gt;, MOLPRO 2012 gives for &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RHF-SCF energy:    -1777.84665521&#xA;CPU time for INT:      0.42 SEC&#xA;CPU time for RHF:      0.01 SEC&#xA;Disk used for INT:    12.87 MB&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However the RHF energy was converged already at iteration 1, so there wasn't much work to do:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ITERATION    DDIFF          GRAD             ENERGY        2-EL.EN.            DIPOLE MOMENTS         DIIS   ORB.&#xA;1      0.000D+00      0.000D+00     -1777.84665521   1412.514729    0.00000    0.00000    0.00000    0    start&#xA;2      0.000D+00      0.328D-06     -1777.84665521   1412.514530    0.00000    0.00000    0.00000    0    orth&#xA;&#xA; Final occupancy:   6   2   2   1   2   1   1   0&#xA;&#xA; !RHF STATE 1.1 Energy              -1777.846655206719&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn_2}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RHF-SCF energy:    -3555.64477389&#xA;CPU time for INT:      1.85 SEC&#xA;CPU time for RHF:      0.03 SEC&#xA;Disk used for INT:    28.64 MB&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This time the program actually did something for the RHF iterations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ITERATION    DDIFF          GRAD             ENERGY        2-EL.EN.            DIPOLE MOMENTS         DIIS   ORB.&#xA;    1      0.000D+00      0.000D+00     -3555.64052105   3233.546012    0.00000    0.00000    0.00000    0    start&#xA;    2      0.000D+00      0.302D-02     -3555.64412736   3238.277667    0.00000    0.00000    0.00000    1    diag&#xA;    3      0.131D-01      0.237D-02     -3555.64463460   3236.375359    0.00000    0.00000    0.00000    2    diag&#xA;    4      0.373D-02      0.709D-03     -3555.64472506   3236.809227    0.00000    0.00000    0.00000    3    diag&#xA;    5      0.210D-02      0.294D-03     -3555.64476998   3236.644635    0.00000    0.00000    0.00000    4    diag&#xA;    6      0.215D-02      0.737D-04     -3555.64477361   3236.670571    0.00000    0.00000    0.00000    5    diag&#xA;    7      0.548D-03      0.192D-04     -3555.64477389   3236.660433    0.00000    0.00000    0.00000    6    diag&#xA;    8      0.178D-03      0.250D-05     -3555.64477389   3236.659036    0.00000    0.00000    0.00000    7    diag&#xA;    9      0.189D-04      0.443D-06     -3555.64477389   3236.659009    0.00000    0.00000    0.00000    8    diag&#xA;   10      0.373D-05      0.512D-07     -3555.64477389   3236.659037    0.00000    0.00000    0.00000    0    orth&#xA;&#xA; Final occupancy:   8   3   3   1   8   3   3   1&#xA;&#xA; !RHF STATE 1.1 Energy              -3555.644773894570&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;This was all with &lt;em&gt;only 1 core&lt;/em&gt;&lt;/strong&gt; but to compare it to Susi's benchmarks, we would need to be using the same hardware. I have put my output files in the &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/3794&quot; rel=&quot;noreferrer&quot;&gt;folder for this question&lt;/a&gt; on GitHub, in case anyone wants to try on their hardware (but when the runtimes are so short, comparisons are probably not so valuable: perhaps we need to do this on a bigger basis set so that the programs actually have to take a substantial amount of time calculating things). Also if anyone wants to put their files in the Git repo, I can run them on the same hardware I used to do the above calculations, and can share the results here.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-11-24T04:05:55.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3802" PostTypeId="2" ParentId="3798" CreationDate="2020-11-24T08:48:49.093" Score="3" Body="&lt;p&gt;Your question is not so focus. I assume that you want to read the BSE oscillator strength from the VASP output.&lt;/p&gt;&#xA;&lt;p&gt;I strongly advise you that take a look at this link:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Plotting_the_BSE_fatband_structure_of_Si&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Plotting_the_BSE_fatband_structure_of_Si&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;After the (model)BSE calculation we first look into the [vasprun.xml] file to have a look at the BSE eigenvalues and the oscillator strengths (exact numbers can of course differ depending on the method you use and the density of your k-point grid).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oVCZL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oVCZL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which the first column is the BSE eigenvalue, the second line the BSE oscillator.&lt;/p&gt;&#xA;&lt;p&gt;You can obtain similar results with IQP calculation at DFT or RPA levels with [LOPITCS=TRUE] in the INCAR file.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-11-24T08:48:49.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3803" PostTypeId="2" ParentId="43" CreationDate="2020-11-24T14:43:13.197" Score="6" Body="&lt;p&gt;As a retired professor in Computational Thermodynamics I am happy that young students try to use the Calphad methods to understand materials.  However, to model a phase using Calphad there are some background needed.  A Calphad database is built from a set of data for the pure elements in different phases describing how the Gibbs energy of the element vary with T from 300 K up to some higher T.  Such data are obtained from experimental data for the stable state or estimated for metastable phases for the elements.  It also include the heat capacity of the element.&#xA;For solution phases one can introduce excess parameters which depend on the fraction of the elements and is normally constant or linearly T dependent.  One does not use higher T terms (such as Tln(T)) unless one has experimental heat capacity for the solution.&#xA;There are several models to select from which can describe LRO or SRO transitions in the phase which require more model parameters.  Some of these can be determined by DFT calculations unless there are experimental data.&#xA;In short, try to find some reference paper or book to read about Calphad, it is not just and an equation or a black box.&lt;/p&gt;&#xA;" OwnerUserId="1092" LastActivityDate="2020-11-24T14:43:13.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3804" PostTypeId="1" CreationDate="2020-11-24T15:36:24.340" Score="15" ViewCount="277" Body="&lt;p&gt;I typically run DFT calculations with 1000 to 5000 atoms using CP2K.  This works fine but I'm interested in BigDFT also.  Is there anyone here that has  experience using BigDFT and is able to compare it with CP2K for scaling and calculation speed?&lt;/p&gt;&#xA;" OwnerUserId="1577" LastEditorUserId="7" LastEditDate="2021-07-29T19:14:04.473" LastActivityDate="2021-07-29T19:14:04.473" Title="CP2K vs BigDFT comparison" Tags="|cp2k|benchmark-timings|bigdft|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-13T02:01:21.817" ContentLicense="CC BY-SA 4.0" />
  <row Id="3805" PostTypeId="5" CreationDate="2020-11-24T17:20:35.977" Score="0" Body="&lt;p&gt;Website: &lt;a href=&quot;http://bigdft.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://bigdft.org&lt;/a&gt; &lt;br&gt;&#xA;Wiki entry: &lt;a href=&quot;https://en.wikipedia.org/wiki/BigDFT&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/BigDFT&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-24T17:20:35.977" LastActivityDate="2020-11-24T17:20:35.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3806" PostTypeId="4" CreationDate="2020-11-24T17:20:35.977" Score="0" Body="Questions about the software BigDFT." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-24T17:20:35.977" LastActivityDate="2020-11-24T17:20:35.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3807" PostTypeId="2" ParentId="3757" CreationDate="2020-11-24T20:45:19.463" Score="5" Body="&lt;p&gt;In terms of the colours, the main elements in organic chemistry are usually represented via the following colours:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;H - white&lt;/li&gt;&#xA;&lt;li&gt;C - black&lt;/li&gt;&#xA;&lt;li&gt;N - blue&lt;/li&gt;&#xA;&lt;li&gt;O - red&lt;/li&gt;&#xA;&lt;li&gt;S - yellow&lt;/li&gt;&#xA;&lt;li&gt;Cl - green&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In terms of sphere radius, it makes sense to use a value that is specific to the atom, for example the van-der-Waals radius (e.g. 25% of the van-der-Walls radius). If you use that, then the H-atoms appear smaller than the other atoms.&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2020-11-24T20:45:19.463" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3808" PostTypeId="1" AcceptedAnswerId="3810" CreationDate="2020-11-24T21:12:28.953" Score="11" ViewCount="203" Body="&lt;p&gt;Assuming I have an experimental powder XRD spectra and I have a number of computational structures without any knowledge of which is correct, how can I simulate the powder XRD spectra?  Once I have determined which structure is most likely, can I use the powder XRD to further refine the lattice constants of the structure?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2020-11-24T21:25:54.963" LastActivityDate="2020-11-25T11:26:42.570" Title="Pattern X-Ray Diffraction Fitting" Tags="|periodic-system|x-ray-diffraction|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3809" PostTypeId="2" ParentId="1103" CreationDate="2020-11-25T07:52:18.977" Score="7" Body="&lt;p&gt;Let me add 2 notes&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;MKL has a &lt;em&gt;secret&lt;/em&gt; env-var to force the use of AVX2 extensions etc. For details, see &lt;a href=&quot;https://www.pugetsystems.com/labs/hpc/How-To-Use-MKL-with-AMD-Ryzen-and-Threadripper-CPU-s-Effectively-for-Python-Numpy-And-Other-Applications-1637/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The magic is setting the environment variable:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;MKL_DEBUG_CPU_TYPE=5&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;note however that Intel can at any release remove this flag, so one is not guaranteed this will work in later releases.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Another great library is &lt;a href=&quot;https://github.com/flame/blis&quot; rel=&quot;nofollow noreferrer&quot;&gt;blis&lt;/a&gt; it basically works like OpenBLAS but with a different mind-set, so to speak. Really great package as well!&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2020-12-02T08:31:38.533" LastActivityDate="2020-12-02T08:31:38.533" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3810" PostTypeId="2" ParentId="3808" CreationDate="2020-11-25T11:26:42.570" Score="8" Body="&lt;p&gt;You have two different question in the same post.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;how can I simulate the powder XRD spectra?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To just simulate the XRD spectra you can use this answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/146/24&quot;&gt;https://mattermodeling.stackexchange.com/a/146/24&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;can I use the powder XRD to further refine the lattice constants of the structure?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The short answer: yes.&lt;/p&gt;&#xA;&lt;p&gt;The long answer:&#xA;For the fitting process, or refinement, you don't need a set of starting structures. One of the successful method to obtain the crystal parameters from a powder diffraction pattern is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rietveld_refinement&quot; rel=&quot;noreferrer&quot;&gt;Rietveld method&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In this method, you only need one starting structure. Then, the software generate a theoretical pattern (as in your first question) and then the method uses a least squares approach to refine/fit the theoretical pattern to the experimental one. Here several parameters are changed. This process is repeated several times until attain convergence. In case the figure of merit (see below) be bad, you can then use another structure from your set as starting one.&lt;/p&gt;&#xA;&lt;p&gt;The parameters that are fitted are several and can be used further to describe your structure:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Background parameters: usually 1 to 12 parameters.&lt;/li&gt;&#xA;&lt;li&gt;Sample displacement: sample transparency, and zero shift corrections. (move peak position)&lt;/li&gt;&#xA;&lt;li&gt;Multiple peak shape parameters.&lt;/li&gt;&#xA;&lt;li&gt;FWHM parameters: i.e. Caglioti parameters (see section 3.1.2)&lt;/li&gt;&#xA;&lt;li&gt;Asymmetry parameters (FCJ parameters)&lt;/li&gt;&#xA;&lt;li&gt;Unit cell dimensions&lt;/li&gt;&#xA;&lt;li&gt;one to six parameters (a, b, c, α, β, γ), depending on the crystal family/system, for each present phase.&lt;/li&gt;&#xA;&lt;li&gt;Preferred orientation, and sometimes absorption, porosity, and extinction coefficients, which can be independent for each phase.&lt;/li&gt;&#xA;&lt;li&gt;Scale factors (for each phase)&lt;/li&gt;&#xA;&lt;li&gt;Positional parameters of all independent atoms in the crystal model (generally 0 to 3 per atom).&lt;/li&gt;&#xA;&lt;li&gt;Population parameters&lt;/li&gt;&#xA;&lt;li&gt;Occupation of site positions by atoms.&lt;/li&gt;&#xA;&lt;li&gt;Atomic displacement parameters&lt;/li&gt;&#xA;&lt;li&gt;Isotropic and anisotropic (temperature) parameters.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The parameters that measure the quality of the fit (figures of merit) indicating the quality of the fit are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Profile Residual (reliability factor)&lt;/li&gt;&#xA;&lt;li&gt;Weighted profile residual&lt;/li&gt;&#xA;&lt;li&gt;Bragg residual&lt;/li&gt;&#xA;&lt;li&gt;Expected profile residua&lt;/li&gt;&#xA;&lt;li&gt;Goodness of fit&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Finally, &lt;a href=&quot;https://youtu.be/bYjJY2CSJjs&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; you can view a tutorial about Rietveld refinement using the &lt;a href=&quot;https://www.ill.eu/sites/fullprof/&quot; rel=&quot;noreferrer&quot;&gt;Fullprof Suite&lt;/a&gt; (one of the best software for this task).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-11-25T11:26:42.570" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3812" PostTypeId="1" CreationDate="2020-11-26T01:44:35.757" Score="7" ViewCount="114" Body="&lt;p&gt;I have two brakets (the angular momentum matrix elements) that are&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \langle \partial_\mathbf{k} \psi_{n \mathbf{k}} |  \times \mathbf{p} | \psi_{m \mathbf{k}} \rangle \tag{1} $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \langle \psi_{n \mathbf{k}} |  \mathbf{p} \times  | \partial_\mathbf{k}  \psi_{m \mathbf{k}} \rangle \tag{2} $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\psi_{n \mathbf{k}}$&lt;/span&gt; is Bloch wave function with band index &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\mathbf{p}$&lt;/span&gt; is the momentum operator and &lt;span class=&quot;math-container&quot;&gt;$\partial_\mathbf{k} = {\partial}/{\partial_\mathbf{k}}$&lt;/span&gt;. Using the Hermitian conjugate relation &lt;span class=&quot;math-container&quot;&gt;$\partial^{\dagger}=-\partial$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\partial_{\mathbf{k}} \times \mathbf{p} = \mathbf{0}$&lt;/span&gt;, I obtained&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\textrm{Eq.}~(1)&amp;amp;=-\langle \psi_{n \mathbf{k}} | \partial_\mathbf{k} \left [ \times \mathbf{p} | \psi_{m \mathbf{k}} \rangle \right ] \tag{3} \\&#xA;&amp;amp;=-\left [ \langle \psi_{n \mathbf{k}} | (\partial_\mathbf{k}  \times \mathbf{p} )| \psi_{m \mathbf{k}} \rangle -\langle \psi_{n \mathbf{k}} |  \mathbf{p} \times  | \partial_\mathbf{k}  \psi_{m \mathbf{k}} \rangle \right ] \tag{4} = \textrm{Eq.}~(2)&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;Or I can simply use &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r} \times \mathbf{p} = - \mathbf{p} \times \mathbf{r}$&lt;/span&gt; to prove (1)=(2).  However, in my implementations, with &lt;span class=&quot;math-container&quot;&gt;$\partial_{\mathbf{k}} \psi_{n \mathbf{k}}$&lt;/span&gt; replaced by the covariant derivative &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Q} \partial_{\mathbf{k}} \psi_{n \mathbf{k}}$&lt;/span&gt;  where &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Q}$&lt;/span&gt; is the projection operator on the empty states$, I found (1) and (2) are not always equal but at some k points and band pairs. &lt;strong&gt;Am I missing something?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2021-11-18T06:05:28.520" LastActivityDate="2021-11-18T06:05:28.520" Title="Equations related to the first-order derivative of the wavefunction" Tags="|density-functional-theory|dfpt|" AnswerCount="0" CommentCount="10" ClosedDate="2021-11-29T19:21:02.120" ContentLicense="CC BY-SA 4.0" />
  <row Id="3813" PostTypeId="1" CreationDate="2020-11-26T02:37:16.823" Score="11" ViewCount="177" Body="&lt;p&gt;I have to calculate the elastic constants of a Cubic system using a Density functional theory-based software. A cubic system will be mechanically stable if it satisfies the Born-stability condition (eq. 6 from &lt;a href=&quot;https://arxiv.org/abs/1410.0065&quot; rel=&quot;nofollow noreferrer&quot;&gt;ref&lt;/a&gt;),&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C_{11}−C_{12}&amp;gt;0 ;C_{11}+2C_{12}&amp;gt;0 ;C_{44}&amp;gt;0.\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But in my case, the system failed to satisfy the first condition (&lt;span class=&quot;math-container&quot;&gt;$C_{11}-C_{44}$&lt;/span&gt; should be &amp;gt; 0 but I am getting a negative value).&lt;/p&gt;&#xA;&lt;p&gt;How I can make this system stable, like applying stress, strain or something else? My aim is to predict if this material is useful in photovoltaic cells (up to ~2eV) and in thermometric devices (up to 800 Kelvin).&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-02-28T19:39:40.257" LastActivityDate="2021-05-31T03:59:29.720" Title="How can we make a mechanically unstable cubic system, stable" Tags="|mechanical-properties|thermal|elastic-constants|optical-properties|elasticity|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3814" PostTypeId="2" ParentId="2229" CreationDate="2020-11-26T14:59:51.003" Score="4" Body="&lt;p&gt;Conventional cell is the unit cell where the symmetry is properly defined whereas, primitive cell may not always indicate the actual symmetry. For example, FCC is a proper conventional unit cell but its primitive cell looks like a rhombohedron. Again, the lattice parameters of both cells are different (From materials project- conventional = 6.417 angstrom, primitive = 4.537 angstrom). A quick google search would show the lattice parameter of SnTe to be in the range of 6.302–6.327 angstrom. Distance between the atoms can directly affect the elastic property. Hence, the difference in the elastic constant values. It would be better to consider the conventional unit cell for calculation (as it has both symmetry and lattice parameter closer to the experimental value).&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2020-11-26T14:59:51.003" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3815" PostTypeId="2" ParentId="3576" CreationDate="2020-11-26T15:20:15.760" Score="3" Body="&lt;p&gt;(Source: this &lt;a href=&quot;https://groups.google.com/g/uspex/c/DeHCkHyrVWA/m/f-PLlUoqBgAJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;question about point defects&lt;/a&gt; on the USPEX google group.)&lt;/p&gt;&#xA;&lt;p&gt;This seems like a restricted crystal structure prediction problem since knowing the crystal structure of the system beforehand becomes a requirement. You must specify a space group (or other symmetry groups like the point, layer, etc groups) via the &lt;code&gt;symmetries&lt;/code&gt; tag in the &lt;code&gt;INPUT.txt&lt;/code&gt; file. Given that, there arise two scenarios:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;When you know exactly how many vacancies there are.&lt;/li&gt;&#xA;&lt;li&gt;When there can be a variable number of vacancies.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Let's say your material is &lt;span class=&quot;math-container&quot;&gt;$A_2B_3O_{10}$&lt;/span&gt; and you wish to study &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; vacancies.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Scenario 1: Fixed composition USPEX calculation.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;calculationType = 300&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Mention less number of &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; atoms in &lt;code&gt;numSpecies&lt;/code&gt; in accordance with the number of vacancies the material has. For instance, when there are two &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; vacancies:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%atomType&#xA;A B O&#xA;%EndAtomType&#xA;&#xA;%numSpecies&#xA;2 3 8&#xA;%EndNumSpecies&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Scenario 2: Variable composition USPEX calculation.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;calculationType = 301&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let's assume there could be up to three &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; vacancies:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%atomType&#xA;A B O&#xA;%EndAtomType&#xA;&#xA;%numSpecies&#xA;2 3 7&#xA;0 0 1&#xA;%EndNumSpecies&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;All predicted structures would be a combination of &lt;span class=&quot;math-container&quot;&gt;$x\cdot(A_2B_3O_7)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y\cdot O$&lt;/span&gt; i.e. &lt;span class=&quot;math-container&quot;&gt;$A_{2x}B_{3x}O_{7(x+y)}$&lt;/span&gt;. This way you'll get the best structure among all with &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; vacancies ranging from one to three.&lt;/p&gt;&#xA;" OwnerUserId="116" LastActivityDate="2020-11-26T15:20:15.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3816" PostTypeId="1" CreationDate="2020-11-27T05:07:22.227" Score="13" ViewCount="1085" Body="&lt;p&gt;If I am using Quantum ESPRESSO for bandstructure calculations, how can I know the number of CPUs necessary for such a calculation? I deal mostly with ternary transition metal oxides which have at least 10 atoms per unit cell. An example would be TiVO4. In the supercluster where I run these calculations, there are 40 CPUs per node. The CPU time available for a calculation is one week.&lt;/p&gt;&#xA;" OwnerUserId="1582" LastEditorUserId="1582" LastEditDate="2020-12-12T15:06:16.427" LastActivityDate="2020-12-14T20:47:14.103" Title="Deciding the number of CPUs for a DFT calculation for band structure in Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|high-performance-computing|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3817" PostTypeId="2" ParentId="2229" CreationDate="2020-11-28T12:58:41.390" Score="4" Body="&lt;p&gt;Based on symmetry of the simulation cell, vasp algorithm distort the unit cell.&#xA;Distortion change the energetics and stress of unit cell which in turn gives us stress strain relationship,further algorithm uses this relation for calculating elastic constants. As your simulation box symmetry is different, you are getting different distortion which is resulting in two different results. Its always good to use conventional cell for calculating elastic constants.&#xA;Let me discuss on more thing that, we often encounter discrepency in results while using IBRION=6 , I suggest you to stick with more conventional way of using strain-energy relation for calculating elastic constants.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2020-11-28T12:58:41.390" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3818" PostTypeId="1" AcceptedAnswerId="4425" CreationDate="2020-11-28T15:07:15.747" Score="9" ViewCount="141" Body="&lt;p&gt;I have known some kinds of stability of materials, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Mechanical stability;&lt;/li&gt;&#xA;&lt;li&gt;Dynamical stability;&lt;/li&gt;&#xA;&lt;li&gt;Thermal stability&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In particular, they can be studied with first-principles computational methods:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Mechanical &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Elastic constants &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Born criteria.&lt;/li&gt;&#xA;&lt;li&gt;Dynamical &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Phonon spectrum &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Is there negative frequency?&lt;/li&gt;&#xA;&lt;li&gt;Thermal &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Ab-initio molecular dynamics &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Structure distortion.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Then are there other kinds of stability of materials? How to demonstrate that with computation approaches?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-28T21:44:14.487" Title="Are there other kinds of stability of materials? How to demonstrate that with computation approaches?" Tags="|density-functional-theory|molecular-dynamics|phonon-dispersion|thermal|mechanical-properties|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3819" PostTypeId="1" AcceptedAnswerId="3820" CreationDate="2020-11-28T17:51:08.783" Score="5" ViewCount="99" Body="&lt;p&gt;What sources would you recommend (or if you could instead explain it to me that would be great). I have never studied crystallography but must do a module on it and in some of the questions we were given to practice the following is asked:&lt;/p&gt;&#xA;&lt;p&gt;Give the area of a &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{3} \times \sqrt{3})$&lt;/span&gt;R&lt;span class=&quot;math-container&quot;&gt;$30^°$&lt;/span&gt; surface unit mesh on the surface of an (0001) hcp crystal with lattice parameters a = 4.2 Å and c = 5.5 Å?&lt;/p&gt;&#xA;" OwnerUserId="1590" LastEditorUserId="697" LastEditDate="2020-11-28T18:27:00.027" LastActivityDate="2020-11-28T19:40:51.503" Title="How can I find the area of an overlayer structure?" Tags="|crystallography|adsorption|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3820" PostTypeId="2" ParentId="3819" CreationDate="2020-11-28T18:23:06.137" Score="6" Body="&lt;p&gt;The 0001 facet area will be only dependent on the &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; lattice constant.  To solve for the area of that surface, you will just need to find the area of a rhombus with a &lt;span class=&quot;math-container&quot;&gt;$60^{\circ}$&lt;/span&gt; angle.&lt;/p&gt;&#xA;&lt;p&gt;To read the intended cell, start from the unit cell of the 0001 surface.  Then multiply the surface vectors by the two values given, &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt;.  Then you rotate the surface vectors around the z axis by the value given, &lt;span class=&quot;math-container&quot;&gt;$30^{\circ}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A = S^2\sin(A^{\circ})$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A = (\sqrt{3}*4.2)^2\sin(60^{\circ})$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A = 45.83$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="7" LastEditDate="2020-11-28T19:40:51.503" LastActivityDate="2020-11-28T19:40:51.503" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3821" PostTypeId="1" CreationDate="2020-11-28T20:48:36.753" Score="5" ViewCount="604" Body="&lt;p&gt;I have been using cif2cell for converting CIF files into quantum ESPRESSO input files. But cif2cell always keeps the ibrav value to be zero and indicates the CELL_PARAMETERS. As per the quantum ESPRESSO website, the following is provided.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;with ibrav=0 lattice vectors must be given with a sufficiently large&#xA;number of digits and with the correct symmetry, or else symmetry&#xA;detection may fail and strange problems may arise in symmetrization. The &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#ibrav&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Plus there is this excerpt in their GitLab repo :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There is no sure way to distinguish between true symmetry breaking and&#xA;sloppy data. If it works for you (it should if you provide enough&#xA;significant digits for crystal axis and atomic positions), no problem,&#xA;but nobody who uses ibrav=0 is allowed to complain any longer about&#xA;symmetry. The &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/issues/131&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So does it mean that when considering systems with a larger &lt;strong&gt;ntyp&lt;/strong&gt; value {number of unique elements}, that I should resort to finding out the symmetry using an explicit ibrav value, rather than using ibrav = 0 and specifying the cell parameters.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-12-04T18:20:51.017" Title="Is there a difference in performance when the symmetry is specified via ibrav in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|symmetry|geometry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3822" PostTypeId="5" CreationDate="2020-11-29T01:36:35.450" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node47.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node47.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T01:36:35.450" LastActivityDate="2020-11-29T01:36:35.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3823" PostTypeId="4" CreationDate="2020-11-29T01:36:35.450" Score="0" Body="Questions about the MCSQC software for Monte Carlo calculations related to Special Quasirandom Structures." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T01:36:35.450" LastActivityDate="2020-11-29T01:36:35.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3824" PostTypeId="5" CreationDate="2020-11-29T01:37:39.133" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node35.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node35.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T01:37:39.133" LastActivityDate="2020-11-29T01:37:39.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3825" PostTypeId="4" CreationDate="2020-11-29T01:37:39.133" Score="0" Body="Questions about the software CORRDUMP." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T01:37:39.133" LastActivityDate="2020-11-29T01:37:39.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3826" PostTypeId="5" CreationDate="2020-11-29T02:25:44.473" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T02:25:44.473" LastActivityDate="2020-11-29T02:25:44.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3827" PostTypeId="4" CreationDate="2020-11-29T02:25:44.473" Score="0" Body="Questions asking for assistance with the use or compilation of a software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-11-29T02:25:44.473" LastActivityDate="2020-11-29T02:25:44.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3828" PostTypeId="2" ParentId="1770" CreationDate="2020-11-29T09:26:40.350" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How do you get the Hamiltonian formula for transition metal dichalcogenides? How to derivate the expression above (equation (1))?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You can use the &lt;span class=&quot;math-container&quot;&gt;$ k \cdot p$&lt;/span&gt; method to derive this effective Hamiltonian. Please take a look at &lt;a href=&quot;https://www.burkard.uni-konstanz.de/typo3temp/secure_downloads/104600/0/aab81b52e7181657d21db641d3721c171e1f3e9a/Kormanyos_2053-1583_2_2_022001.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; for the details.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$k \cdot p$&lt;/span&gt; theory for two-dimensional transition metal dichalcogenide semiconductors.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What does the parameter  mean? I don't understand what they mean by &amp;quot;hopping integral&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You can just view it as a parameter of this tight-binding Hamiltonian (just a convention), which needs to be fitted by first-principles calculations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why did you choose this basis wave functions?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It is decided by the group of the wave vector at the band edges (&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;) is &lt;span class=&quot;math-container&quot;&gt;$C_{3h}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is &lt;span class=&quot;math-container&quot;&gt;$$&lt;/span&gt; in the mathematical formula?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$2\lambda$&lt;/span&gt; is the spin splitting at the valence band top&#xA;caused by the spin-orbit coupling, which can be decided with first-principles calculations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Useful references:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.196802&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.196802&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.88.085433&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.88.085433&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-11-29T09:32:33.427" LastActivityDate="2020-11-29T09:32:33.427" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3829" PostTypeId="2" ParentId="1728" CreationDate="2020-11-29T09:57:57.747" Score="2" Body="&lt;p&gt;ProfM's argument is absolutely right. Here I support a more detailed explanation based on first-principles calculations.&lt;/p&gt;&#xA;&lt;p&gt;The spin-resolved band structure of monolayer MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; with the consideration of spin-orbit coupling is shown below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/pukGl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pukGl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You can first find the two split valence bands around &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-K$&lt;/span&gt; valleys. In particular, spin-&lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; is a good quantum number at these valleys.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The conduction band edges around &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-K$&lt;/span&gt; are almost degenerated.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The first Brillouin zone of monolayer MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; is hexagonal, there are three &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-K$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;With the above information, I believe you can understand the image you posted.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-20T07:08:46.933" LastActivityDate="2021-03-20T07:08:46.933" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3830" PostTypeId="1" CreationDate="2020-11-29T14:04:30.677" Score="8" ViewCount="94" Body="&lt;p&gt;I have drawn three surface meshes from a hexagonal material for the &lt;span class=&quot;math-container&quot;&gt;$(0001)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(1\bar{1}00)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(1\bar{1}01)$&lt;/span&gt;.&#xA;The first one would be the top horizontal surface of the hexagonal structure, the second a vertical rectangular surface from one of the walls, and the third one would be a rectangle at an angle to intersect the c-axis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;But does this mean then that this last one is oblique because it is inclined to intersect the c-axis? How do I identify an oblique surface mesh?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The definition I have been given for an oblique surface mesh is that &amp;quot;&lt;em&gt;it doesn't have a 90 degree angle between the basis vectors.&lt;/em&gt;&amp;quot; but what are the basis vectors? Are there the &lt;span class=&quot;math-container&quot;&gt;$a_1, a_2,a_3, c$&lt;/span&gt; vectors? If so, aren't these always the same independent on the surface of the crystal?&lt;/p&gt;&#xA;&lt;p&gt;I believe that these meshes are rectangular but I am not entirely sure and would like to know if there are any sources I can check to learn the subject better.&lt;/p&gt;&#xA;" OwnerUserId="1590" LastEditorUserId="7" LastEditDate="2022-01-13T16:18:25.157" LastActivityDate="2022-01-13T16:18:25.157" Title="How do I identify an oblique surface mesh?" Tags="|crystallography|surfaces|space-groups|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3832" PostTypeId="1" AcceptedAnswerId="3833" CreationDate="2020-11-29T18:36:48.917" Score="12" ViewCount="881" Body="&lt;p&gt;Are there any important considerations to make for density of state calculations for supercells?  With band structures typically band unfolding schemes make things easier to understand but is there anything analogous for density of states?&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-11-02T11:43:40.573" Title="Density of States of Supercells" Tags="|band-structure|density-of-states|castep|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3833" PostTypeId="2" ParentId="3832" CreationDate="2020-11-29T19:36:53.460" Score="14" Body="&lt;p&gt;The density of states reads:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;g(E)=\sum_{n}\int\frac{d\mathbf{k}}{(2\pi)^3}\delta(E-E_{n\mathbf{k}}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E_{n\mathbf{k}}$&lt;/span&gt; are the electronic energies and the integral is over the Brillouin zone (BZ).&lt;/p&gt;&#xA;&lt;p&gt;If you calculate &lt;span class=&quot;math-container&quot;&gt;$g(E)$&lt;/span&gt; in the primitive cell, then you will integrate over the primitive cell BZ. If you calculate &lt;span class=&quot;math-container&quot;&gt;$g(E)$&lt;/span&gt; in a supercell, then you will integrate over the supercell BZ, which is a fraction of the primitive cell BZ. This means you will have fewer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points. However, this will be exactly compensated by the additional bands &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; that you will get due to band folding. Therefore, the density of states is the same in a primitive cell or a supercell.&lt;/p&gt;&#xA;&lt;p&gt;The situation is different to what happens for a band structure because in a band structure you want to resolve the energies in terms of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; &lt;em&gt;for the primitive cell&lt;/em&gt;. This is why you need to undo band folding in a supercell calculation to turn the states from the supercell BZ to the primitive cell BZ. For densities of states, you integrate over &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; and sum over &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, so band folding does not affect the result in any way.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-11-29T19:36:53.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3834" PostTypeId="1" AcceptedAnswerId="4424" CreationDate="2020-11-29T21:08:02.650" Score="10" ViewCount="436" Body="&lt;p&gt;I'm trying to reconstruct the surface &lt;span class=&quot;math-container&quot;&gt;$(1\bar{1}01)$&lt;/span&gt; in an hexagonal material and the reconstruction is described by the matrix &lt;span class=&quot;math-container&quot;&gt;$\begin{pmatrix} \hspace{3mm}3 \hspace{2mm}1 \\-1 \hspace{2mm}2 \end{pmatrix}$&lt;/span&gt; .&lt;/p&gt;&#xA;&lt;p&gt;The surface looks a lot like the picture on the right &lt;a href=&quot;https://i.stack.imgur.com/hq8nn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hq8nn.png&quot; alt=&quot;1101 surface example&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;But how do I proceed on reconstructing the surface? How do I apply this matrix to 4 Miller-indices?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've looked for the concept of reconstruction in the books &amp;quot;Introduction to Crystallography&amp;quot; by Dr. Hoffmann, &amp;quot;Crystallography An Introduction&amp;quot; by Dr. Borchardt-Ott but none of these books seem to demonstrate how this is done.&lt;/p&gt;&#xA;" OwnerUserId="1590" LastEditorUserId="1590" LastEditDate="2020-11-30T09:13:16.287" LastActivityDate="2021-02-28T10:32:43.503" Title="How do I reconstruct the surface with known Miller indices?" Tags="|crystallography|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3835" PostTypeId="1" AcceptedAnswerId="3836" CreationDate="2020-11-30T02:58:02.987" Score="11" ViewCount="340" Body="&lt;p&gt;I'm trying to make a pipeline geometry optimization -&amp;gt; calculation of polarizability/hyperpolarizability. And NWChem seems pretty good for it, the only thing I can't understand its how to calculate hyperpolarizability.&lt;/p&gt;&#xA;&lt;p&gt;Currently I'm using this input, but it gives me only polarizability (alpha as 3x3 matrix) and I need hyperpolarizability (beta as 3x3x3 tensor).&lt;/p&gt;&#xA;&lt;p&gt;Full input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;MeCN&amp;quot;&#xA;charge 0&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;   C       -6.60969        1.24918       -0.00000&#xA;   C       -6.19457       -0.15256       -0.00000&#xA;   H       -7.63700        1.35035       -0.36238&#xA;   H       -5.96068        1.84678       -0.64699&#xA;   H       -6.56251        1.66855        1.00937&#xA;   N       -5.86512       -1.26505        0.00000&#xA;end&#xA;&#xA;basis&#xA;  * library 6-31G*&#xA;end&#xA;&#xA;dft&#xA;  xc b3lyp&#xA;  mult 1&#xA;end&#xA;&#xA;property&#xA; response  2 7.73178E-2   # response order and frequency in Hartree energy units  &#xA; end&#xA;&#xA;task dft energy&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="70" LastEditDate="2020-11-30T18:34:32.183" LastActivityDate="2020-12-06T00:26:56.497" Title="Calculating hyperpolarizability in NWChem" Tags="|density-functional-theory|physical-properties-of-materials|optical-properties|nwchem|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3836" PostTypeId="2" ParentId="3835" CreationDate="2020-11-30T16:50:09.660" Score="8" Body="&lt;h1&gt;Major Issue&lt;/h1&gt;&#xA;&lt;p&gt;The major issue here is that NWChem doesn't support second-order response in the DFT code: &amp;quot;Response calculations are currently supported only for order 1 (linear response), single frequency, electric field and mixed electric-magnetic field perturbations.&amp;quot; [&lt;a href=&quot;https://nwchemgit.github.io/Properties.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;]&lt;/p&gt;&#xA;&lt;p&gt;The NWChem coupled-cluster response property capability supports hyperpolarizabilities (I wrote it) and I guess that you got the impression the DFT code supported this too from the paper:&lt;/p&gt;&#xA;&lt;p&gt;J. R. Hammond and K. Kowalski, &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;em&gt;130&lt;/em&gt;, 194108 (2008). &amp;quot;Parallel computation of coupled-cluster hyperpolarizabilities.&amp;quot; [&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3134744&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;]&lt;/p&gt;&#xA;&lt;p&gt;However, that paper used Dalton for DFT hyperpolarizabilities (see the end of Section II).  The Dalton response property code was amazing and the primary motivation for using NWChem is to compute coupled-cluster response properties in parallel and/or with ROHF/UHF references (because NWChem TCE uses the spin-orbital formalism).&lt;/p&gt;&#xA;&lt;p&gt;If it helps at all, below are the results for methylcyanide from that paper:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/tadFI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tadFI.png&quot; alt=&quot;CH3CN hyperpolarizabilities with DFT and CC methods&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eI6Fi.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eI6Fi.png&quot; alt=&quot;CH3CN hyperpolarizabilities with CC and many basis sets&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Minor Issue&lt;/h1&gt;&#xA;&lt;p&gt;There is a relatively simple issue in the input file above.  You need to specify the &lt;code&gt;property&lt;/code&gt; task rather than the &lt;code&gt;energy&lt;/code&gt; task for the input parser to look at the &lt;code&gt;property .. end&lt;/code&gt; block.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;MeCN&amp;quot;&#xA;charge 0&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;   C       -6.60969        1.24918       -0.00000&#xA;   C       -6.19457       -0.15256       -0.00000&#xA;   H       -7.63700        1.35035       -0.36238&#xA;   H       -5.96068        1.84678       -0.64699&#xA;   H       -6.56251        1.66855        1.00937&#xA;   N       -5.86512       -1.26505        0.00000&#xA;end&#xA;&#xA;basis&#xA;  * library 6-31G*&#xA;end&#xA;&#xA;dft&#xA;  xc b3lyp&#xA;  mult 1&#xA;end&#xA;&#xA;property&#xA; response  2 7.73178E-2   # response order and frequency in Hartree energy units  &#xA;end&#xA;&#xA;task dft property&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;CCSD Results&lt;/h1&gt;&#xA;&lt;p&gt;It isn't going to be practical for larger molecules, but I was able to obtain the CCSD result using NWChem just now:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo&#xA;  &#xA;start CH3CN_ccsd_aug-cc-pvdz_hyperpolar&#xA;&#xA;permanent_dir .&#xA;scratch_dir .&#xA;&#xA;memory stack 1600 mb heap 200 mb global 1400 mb noverify&#xA;&#xA;geometry units bohr&#xA;  symmetry cs&#xA;  N      2.5028407872      0.0000000000      0.0000000000&#xA;  C      0.3138164240      0.0000000000      0.0000000000&#xA;  C     -2.4431799386      0.0000000000      0.0000000000&#xA;  H     -3.1404599851      0.9650062580     -1.6714398685&#xA;  H     -3.1404599851      0.9650062580      1.6714398685&#xA;  H     -3.1404599851     -1.9300125160      0.0000000000&#xA;end&#xA;&#xA;basis spherical&#xA;  * library aug-cc-pvdz&#xA;end&#xA;&#xA;#set lindep:tol 1d-9&#xA;set int:acc_std 1d-14&#xA;&#xA;scf&#xA;  singlet&#xA;  rhf&#xA;  direct&#xA;end&#xA;&#xA;tce&#xA;  scf&#xA;  freeze atomic&#xA;  ccsd&#xA;  maxiter 100&#xA;  thresh 1.0e-7&#xA;  io ga&#xA;  2eorb&#xA;  2emet 13&#xA;  tilesize 18&#xA;  attilesize 30&#xA;end&#xA;&#xA;set tce:lineresp T&#xA;set tce:leftresp T&#xA;set tce:respaxis T T T&#xA;set tce:afreq 0.0&#xA;set tce:bfreq 0.0&#xA;&#xA;task tce energy&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CCSD Quadratic Response&#xA; Static Hyperpolarizability&#xA; -----------------------------------------------&#xA; beta(X,X,X) =      -34.504019056 / au&#xA; beta(X,Y,Y) =        3.997809593 / au&#xA; beta(X,Z,Z) =        3.997810512 / au&#xA; beta(Y,X,Y) =        3.997809593 / au&#xA; beta(Y,Y,X) =        3.997809593 / au&#xA; beta(Y,Y,Y) =        4.544908021 / au&#xA; beta(Y,Z,Z) =       -4.544912885 / au&#xA; beta(Z,X,Z) =        3.997810512 / au&#xA; beta(Z,Y,Z) =       -4.544912885 / au&#xA; beta(Z,Z,X) =        3.997810512 / au&#xA; beta(Z,Z,Y) =       -4.544912885 / au&#xA; -----------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This result was obtained using my Mac laptop with one core in approximately 10 minutes using a binary compiled with GCC 10 and the NWChem internal BLAS, which is the slowest but most reliable build.  Larger basis sets will increase the computational requirements quickly.&lt;/p&gt;&#xA;" OwnerUserId="70" LastEditorUserId="70" LastEditDate="2020-12-06T00:26:56.497" LastActivityDate="2020-12-06T00:26:56.497" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3837" PostTypeId="1" CreationDate="2020-11-30T22:13:36.137" Score="9" ViewCount="82" Body="&lt;p&gt;Suppose I have a functioning molecular dynamics package for classical MD. I want to extend this code to run path integral MD. I know that a surprisingly small number of new features need to be implemented, but the literature I am aware of is quite formal, where I'd be interested to look at a more algorithmic description of what steps need to be added to the usual integration of Newton's equations in classical MD.&lt;/p&gt;&#xA;&lt;p&gt;Any references, books or articles, you've seen which fit the description, I'd love to look at. Alternatively, a simple reference implementation would be nice. It's quite easy to find reference implementations of path integral monte carlo, but not as much PIMD.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-01-29T22:39:47.507" Title="Algorithmic description of implementing path integral molecular dynamics?" Tags="|molecular-dynamics|reference-request|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3838" PostTypeId="2" ParentId="1770" CreationDate="2020-11-30T23:27:51.227" Score="4" Body="&lt;ul&gt;&#xA;&lt;li&gt;As @Jack suggested, try the &lt;span class=&quot;math-container&quot;&gt;$\vec{k} \cdot \vec{p}$&lt;/span&gt; method.&lt;/li&gt;&#xA;&lt;li&gt;The hopping integral &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt; is &amp;quot;borrowed&amp;quot; from the Hubbard model. It is the kinetic term in the Hamiltonian that explains electrons being able to &amp;quot;hop&amp;quot; from one atomic site to another. In real space, it is an integral of the orbital overlap between the two neighboring atomic sites located at &lt;span class=&quot;math-container&quot;&gt;$\vec{x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{x}'$&lt;/span&gt;, respectively. &lt;span class=&quot;math-container&quot;&gt;$t_{ij} = \int \phi_i (\vec{x}) \phi_j (\vec{x}') \mathrm{d}^3 \vec{x}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1596" LastEditorUserId="1596" LastEditDate="2020-12-01T06:12:39.470" LastActivityDate="2020-12-01T06:12:39.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3839" PostTypeId="2" ParentId="1535" CreationDate="2020-12-01T00:02:42.883" Score="9" Body="&lt;h3&gt;Elk / EXCITING&lt;/h3&gt;&#xA;&lt;p&gt;Like @Nike Dattani suggested, Elk is an open-source well-documented FP-LAPW DFT package. Also, LAPW stands for Linearly-Augmented Plane Wave. &lt;a href=&quot;https://link.springer.com/book/10.1007/978-0-387-29684-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;Singh's book&lt;/a&gt; is an excellent introduction for this topic.&#xA;(Disclaimer: I'm currently developing an extension to Elk / EXCITING to compute response functions and estimate Hubbard model parameters using the constrained RPA method, here in our research group at U. of Tennessee. Coincidentally the &amp;quot;working&amp;quot; name of the package is Exciting-Plus, but it's still being optimized so not ready for public use yet.)&lt;/p&gt;&#xA;" OwnerUserId="1596" LastEditorUserId="5" LastEditDate="2020-12-02T21:32:30.860" LastActivityDate="2020-12-02T21:32:30.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3840" PostTypeId="2" ParentId="1535" CreationDate="2020-12-01T01:05:42.367" Score="6" Body="&lt;h2&gt;Questaal&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Questaal is a suite of electronic structure programs. The codes can be used to model arbitrary materials, but they are mostly designed to answer condensed-matter theory questions about solid-state (periodic) structures. The majority of the codes use an all-electron implementation of density-functional theory. This includes several forms (Hamiltonian and Green’s function) that serve different purposes. There is an all-electron implementation of GW theory, used most particularly in a quasiparticle self-consistent form (QSGW). Tight-binding based on user-supplied empirical Hamiltonians is also supported. Recent development work includes Dynamic Mean Field Theory (DMFT-QSGW), the Bethe Salpeter Equation (BSE), and direct (Green Function) solution of the Dirac equation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Website: &lt;a href=&quot;https://www.questaal.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.questaal.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-12-03T10:11:25.030" LastActivityDate="2020-12-03T10:11:25.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3841" PostTypeId="1" AcceptedAnswerId="3847" CreationDate="2020-12-01T01:55:39.277" Score="7" ViewCount="86" Body="&lt;p&gt;In order to model an interstitial trapped in a metal lattice, and the associated incorporation energy, which should be used - &amp;quot;relax&amp;quot; or &amp;quot;vc-relax&amp;quot;? I want to understand the lattice expansion from the interstitial, and that tells me vc-relax, while i realize that an interstitial introduction would involve some lattice strain which would suggest relax.&lt;/p&gt;&#xA;&lt;p&gt;I was using the energy difference &lt;span class=&quot;math-container&quot;&gt;$E_{\rm intAinM} = E(M+A)-(E(M)+E(A))$&lt;/span&gt; to calculate interstitial incorporation energy from both, and they are not the same as one would imagine.&lt;/p&gt;&#xA;&lt;p&gt;I would love you hear some suggestions or insights into this.&lt;/p&gt;&#xA;" OwnerUserId="1527" LastEditorUserId="1355" LastEditDate="2020-12-01T11:15:47.357" LastActivityDate="2020-12-01T23:38:10.950" Title="Relax vs VC-Relax for interstitial incorporation energy" Tags="|density-functional-theory|quantum-espresso|geometry-optimization|defects|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3842" PostTypeId="1" AcceptedAnswerId="3846" CreationDate="2020-12-01T13:18:05.227" Score="11" ViewCount="780" Body="&lt;p&gt;This question is related to this paper: &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpclett.7b01042&quot; rel=&quot;noreferrer&quot;&gt;J. Phys. Chem. Lett. 2017, 8, 13, 2999–3007&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tNXIu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tNXIu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above figure shows symmetry analysis for the band structure. The author writes:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The band symmetry and parity analyses were carried out with the QUANTUM ESPRESSO package based on GBRV PBE scalar relativistic potentials and Pseudodojo fully relativistic potentials.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;How do this with QE? In particular, how to find the irreducible representations for bands and the point group for high symmetry &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; points?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-12-01T13:30:32.677" LastActivityDate="2021-03-30T13:14:49.200" Title="How to analyze the band symmetry with Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|k-points|symmetry|space-groups|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3843" PostTypeId="2" ParentId="1922" CreationDate="2020-12-01T17:24:54.790" Score="4" Body="&lt;p&gt;This error (input forces are not enough to calculate force constants) may arise when you are trying to plot the band structure or the density of state plots for some systems. Sometimes setting a higher symmetry tolerance for a structure may cause this type of error. A lower symmetry setting can solve the issue. The following command can be used in phonopy before plotting the DOS or BS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; phonopy --tolerance=1e-4 -p mesh.conf  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; phonopy --tolerance=1e-4 -p band.conf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastEditorUserId="5" LastEditDate="2020-12-01T17:42:28.270" LastActivityDate="2020-12-01T17:42:28.270" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3844" PostTypeId="2" ParentId="1103" CreationDate="2020-12-01T17:35:41.643" Score="6" Body="&lt;p&gt;AMD's answer to Intel's MKL is called &lt;a href=&quot;https://developer.amd.com/amd-aocl/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;AMD Optimizing CPU Libraries (AOCL)&lt;/strong&gt;&lt;/a&gt;, which is coincidentally based on BLIS. In addition, it also includes FLAME (for LAPACK functionality), FFTW, and others.&lt;/p&gt;&#xA;" OwnerUserId="1596" LastActivityDate="2020-12-01T17:35:41.643" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3846" PostTypeId="2" ParentId="3842" CreationDate="2020-12-01T22:53:32.080" Score="6" Body="&lt;p&gt;This is standard output of &lt;code&gt;bands.x&lt;/code&gt; which is a post-processing code to plot band structures used in QE under the PP folder.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2020-12-02T01:10:16.603" LastActivityDate="2020-12-02T01:10:16.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3847" PostTypeId="2" ParentId="3841" CreationDate="2020-12-01T23:38:10.950" Score="6" Body="&lt;p&gt;You should use a large enough supercell such that the effect of vc-relax and relax are negligible. This means that the strain due to the impurity is local.&lt;/p&gt;&#xA;&lt;p&gt;The following paper provides a comprehensive review on defect calculation in DFT.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.86.253&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.86.253&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1060" LastActivityDate="2020-12-01T23:38:10.950" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3848" PostTypeId="1" CreationDate="2020-12-02T01:48:43.277" Score="14" ViewCount="3188" Body="&lt;p&gt;I know an electron can have two spin states, &amp;quot;spin up&amp;quot; and &amp;quot;spin down&amp;quot;, but recently I was asked how many spin states do &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu^+}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu^{2+}}$&lt;/span&gt; have, and why? Does anyone know the answer? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1601" LastEditorUserId="5" LastEditDate="2020-12-02T19:39:25.847" LastActivityDate="2020-12-03T21:32:56.600" Title="How many spin states do Cu+ and Cu2+ have and why?" Tags="|transition-metals|from-chem-se|spin-orbit-coupling|spin|metal-complexes|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3849" PostTypeId="1" AcceptedAnswerId="3851" CreationDate="2020-12-02T02:26:45.410" Score="54" ViewCount="9262" Body="&lt;p&gt;There was some recent media reporting about a purported Google breakthrough on applying &lt;a href=&quot;https://en.wikipedia.org/wiki/Machine_learning&quot; rel=&quot;noreferrer&quot;&gt;machine learning&lt;/a&gt; techniques to tackle the &lt;a href=&quot;https://en.wikipedia.org/wiki/Protein_folding&quot; rel=&quot;noreferrer&quot;&gt;protein folding&lt;/a&gt; problem, as told for example in this news article, &lt;a href=&quot;https://arstechnica.com/science/2020/11/deepmind-ai-handles-protein-folding-which-humbled-previous-software/&quot; rel=&quot;noreferrer&quot;&gt;DeepMind AI handles protein folding, which humbled previous software&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately there is not much details, as no peer-reviewed paper was published yet. But supposing the paper is eventually published, and the claims confirmed as legitimate and not just hot air, what are the implications? I understand that a reliable way to predict the folding patterns of proteins &lt;em&gt;in silico&lt;/em&gt; could be a huge step over the experimental means like &lt;a href=&quot;https://en.wikipedia.org/wiki/X-ray_crystallography&quot; rel=&quot;noreferrer&quot;&gt;x-ray crystallography&lt;/a&gt;, that sometimes requires even crystals &lt;a href=&quot;https://www.nature.com/articles/npjmgrav201510&quot; rel=&quot;noreferrer&quot;&gt;grown in space&lt;/a&gt; at great cost. Besides the large quantitative but incremental cost and time savings, are there any non-obvious qualitative differences in the kind of research enabled if such a breaktrough is confirmed?&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="5" LastEditDate="2020-12-07T00:57:52.640" LastActivityDate="2021-03-02T07:19:34.743" Title="DeepMind just announced a breakthrough in protein folding, what are the consequences?" Tags="|molecular-modeling|proteins|machine-learning|structural-biology|protein-folding|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3850" PostTypeId="1" CreationDate="2020-12-02T04:30:26.730" Score="7" ViewCount="171" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4xm0G.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4xm0G.png&quot; alt=&quot;With solute&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/xZdrs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xZdrs.png&quot; alt=&quot;Pure solvent&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have a system with a dense liquid solvent and a polymer solute. I have inserted all the molecules randomly using &lt;code&gt;gmx insert-molecules&lt;/code&gt; and then did the energy minimization and equilibration steps to get to the required density.  However as the solvent is so dense, there's no space for the movement of the polymer molecules over the course of the production simulation run. I have waited for upto 10ns but there barely seems to be a change. Is there a way to build such systems to observe change in properties with and without the solute in shorter periods of time? Should I consider smaller densities of solvent or higher concentrations of solute? If so, what is the criteria to match the properties like viscosity from the simulation with that of experimental properties that are performed at high densities and low concentrations of solute?&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2021-06-11T17:31:09.943" LastActivityDate="2021-06-11T17:31:09.943" Title="How to effectively simulate high density systems in GROMACS?" Tags="|molecular-dynamics|gromacs|polymers|" AnswerCount="0" CommentCount="10" ClosedDate="2021-12-26T00:07:09.413" ContentLicense="CC BY-SA 4.0" />
  <row Id="3851" PostTypeId="2" ParentId="3849" CreationDate="2020-12-02T04:49:17.673" Score="57" Body="&lt;p&gt;Imagine if given an amino acid sequence, you could quickly calculate what the shape of the corresponding protein would be.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;You would be able to predict what effect a &lt;em&gt;mutation&lt;/em&gt; would have on the shape of the protein.&lt;/strong&gt; Switching just one glutamic acid with valine completely changes the shape of hemoglobin to the extent that people with this mutation are said to have a disease called &amp;quot;sickle cell anemia&amp;quot;. Likewise, &lt;em&gt;&lt;strong&gt;there might be a substitution that we haven't even discovered yet&lt;/strong&gt;&lt;/em&gt;  that would &lt;em&gt;increase&lt;/em&gt; our capacity to inhale oxygen, leading to super-human strength just as the glutamic acid to valine substitution causes can have severe implications (sick cell anemia).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;You could do inverse design.&lt;/strong&gt; For example if you want a protein that looks and can behave like a stapler, you could search for the amino acid sequence that gives you the protein shaped the way you want, a bit like DNA origami but &lt;em&gt;without the need for staples:&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KgoPS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KgoPS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;So what did DeepMind announce 2 days ago?&lt;/h3&gt;&#xA;&lt;p&gt;First of all, the link you provided is to an article &lt;em&gt;about&lt;/em&gt; what they did. &lt;a href=&quot;https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology&quot; rel=&quot;noreferrer&quot;&gt;This is the original blog post that DeepMind published 2 days ago&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What they announced was that they did very well in the CASP 14 competition. This is a competition for protein folding predictions that has been going on every two years since 1993 and this is the 14th competition that has taken place. In this competition, researchers try to predict the structure of various proteins, and the predictions are evaluated based on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Global_distance_test&quot; rel=&quot;noreferrer&quot;&gt;Global Distance Test&lt;/a&gt;. In 2018 DeepMind won the CASP 13 competition with a median score of almost 60 GDT, whereas the winning teams in CASP 7 (2006) to CASP 12 (2016) never got far above 40 GDT.&lt;/p&gt;&#xA;&lt;p&gt;In the 2020 competition, DeepMind shattered this record again, by getting a median score of 92.4 GDT, which means that atom positions were predicted correctly within 1.6 Angstroms.&lt;/p&gt;&#xA;&lt;h3&gt;Was it peer reviewed?&lt;/h3&gt;&#xA;&lt;p&gt;This was a competition, for which impartial judges evaluate contestants &lt;em&gt;quantitatively&lt;/em&gt; based on a single number, the GDP. This is even better than peer review. Peer review for journals, does not involve the referees actually testing the authors' software to see if it reproduces some standard benchmark: it is just a process where scientists guess whether or not they believe that the authors' calculation really did do what they said they did. This competition was a bit like a race, where Usain Bolt was determined by Olympic judges to break the record for the 100m sprint, and non-judges can also believe it because they for the most part saw it happen on TV, just like you can check the results of the 2020 protein folding competition &lt;a href=&quot;https://predictioncenter.org/decoysets2019/results.cgi&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Then why are people saying that they haven't submitted the paper yet?&lt;/h3&gt;&#xA;&lt;p&gt;They won a major competition, so now the authors can get credit for it in the way that is most relevant for their careers as researchers: by publishing in Nature or Science and getting citations on Google Scholar for it. They will likely just report the results of the competition, which we already know. They might reveal some details about any algorithmic developments they made between 2018 and 2020, but they are also a private company and might not reveal everything the way a research institute not owned by a for-profit company sometimes would by institutional policy be required.&lt;/p&gt;&#xA;&lt;h3&gt;So was a &amp;quot;50-year-old problem solved&amp;quot;, as they claim?&lt;/h3&gt;&#xA;&lt;p&gt;Not really. The particular benchmark set for CASP 14 was solved to an accuracy that had never been achieved by any research group for any previous CASP benchmark set. &lt;strong&gt;However, next time the CASP benchmark set can just be made more difficult and they will be back to not being able to predict the protein structures.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is however a significant achievement that the protein structures in this benchmark set (which was supposed to be hard by 2020 standards) were reproduced with atom positions correct to about 1.6 Angstroms. It means that scientists can now be &lt;em&gt;that&lt;/em&gt; sure about their protein folding predictions for proteins of similar complexity to the ones in the CASP 14 competition set.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update!&lt;/strong&gt; After this question, someone else asked a question which pointed out that AlphaFold might struggle for some important types of proteins such hemoglobin, here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3887/5&quot;&gt;Does DeepMind&amp;#39;s new protein folding software (AlphaFold) also work well for metalloproteins (proteins with metal cofactors)?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-19T17:40:43.727" LastActivityDate="2020-12-19T17:40:43.727" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="3852" PostTypeId="1" AcceptedAnswerId="3855" CreationDate="2020-12-02T05:53:19.890" Score="12" ViewCount="892" Body="&lt;p&gt;I am trying to simulate a 3D hard-spheres in a box system in Python. The idea behind this is that I have to create a system in a 1x1x1 box with periodic boundary conditions and with &lt;span class=&quot;math-container&quot;&gt;$N = 500$&lt;/span&gt; particles of diameter &lt;span class=&quot;math-container&quot;&gt;$d\approx0.09$&lt;/span&gt; (approximately) since packing fraction &lt;span class=&quot;math-container&quot;&gt;$\phi = 0.2$&lt;/span&gt;, which cannot overlap.&lt;/p&gt;&#xA;&lt;p&gt;My algorithm:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Initiate a random box by picking a particle &lt;span class=&quot;math-container&quot;&gt;$(x, y, z)$&lt;/span&gt; from a uniform distribution.&lt;/li&gt;&#xA;&lt;li&gt;Place another particle in the box, by picking &lt;span class=&quot;math-container&quot;&gt;$(x, y, z)$&lt;/span&gt; from a uniform distribution. Make sure it is not overlapping with the first one.&lt;/li&gt;&#xA;&lt;li&gt;Place a third one, make sure it does not overlap with the first &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Repeat this process for all particles up to &lt;span class=&quot;math-container&quot;&gt;$N = 500$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I just have to make sure that I am imposing my periodic boundary conditions correctly.&lt;/p&gt;&#xA;&lt;p&gt;What I have to do next is evaluate the radial distribution function. Which simply means that I have to pick a particle, evaluate its distance from every other particle, and based on the distance, I place the other particle in a bin corresponding to its distance.&#xA;My bins are essentially intervals like &lt;span class=&quot;math-container&quot;&gt;$[0,0.05), [0.05,0.1), [0.1, 0.15), ... [0.95, 1]$&lt;/span&gt;, so a particle at a distance &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; from my reference particle will go in to the bin which has &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; in its interval. If &lt;span class=&quot;math-container&quot;&gt;$r = 0.82$&lt;/span&gt;, it will go to bin corresponding to &lt;span class=&quot;math-container&quot;&gt;$[0.8, 0.85)$&lt;/span&gt;. The thickness of my shell in this example is &lt;span class=&quot;math-container&quot;&gt;$\Delta r = 0.05$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$n_i(r)$&lt;/span&gt; is the number of particles in the shell at a distance &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; from particle &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, I define &lt;span class=&quot;math-container&quot;&gt;$$n(r) =  \sum _{i=1} ^N n_i(r)\tag{1}$$&lt;/span&gt;&#xA;Then I define&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}g(r) = \frac{\frac{n(r)}{N}}{4\pi r^2 \Delta r \rho }$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\rho=N/V$&lt;/span&gt; is the number density. In my code, I am only considering the closest image of my particles.&lt;/p&gt;&#xA;&lt;p&gt;However, when I plot &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; against &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, I get the following plot&#xA;&lt;a href=&quot;https://i.stack.imgur.com/xxo1h.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xxo1h.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I kind of believe that it goes to zero because I have periodic boundary conditions, and I am only considering the closest image of my molecules. I don't think this is correct though for multiple reasons: the graph should be plateauing around 1, and it should not be going to zero.&#xA;Looking at the plots &lt;a href=&quot;https://demonstrations.wolfram.com/RadialDistributionFunctionForHardSpheres/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, I definitely believe I am going wrong somewhere.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is my normalization incomplete for my radial distribution function?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do periodic boundary conditions lead to &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; going to zero for hard spheres?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-08-08T23:18:26.297" LastActivityDate="2021-08-08T23:18:26.297" Title="Normalization condition in evaluating the radial distribution function for a hard-spheres system" Tags="|molecular-modeling|python|radial-distribution-function|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3853" PostTypeId="2" ParentId="2476" CreationDate="2020-12-02T12:43:12.147" Score="3" Body="&lt;p&gt;&lt;strong&gt;Caution: Self answer ahead!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's understand it with an example of a binary &lt;span class=&quot;math-container&quot;&gt;$AB$&lt;/span&gt; compound.&lt;/p&gt;&#xA;&lt;p&gt;A correlation function for a particular type of cluster (pair, triangle, tetrahedron, etc.), &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, is defined as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\rho_\alpha\: =\: &amp;lt;cluster function&amp;gt;_\alpha,\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; represents the type of cluster and &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;...&amp;gt;$&lt;/span&gt; represents an average over all clusters equivalent to &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; by symmetry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;cluster function = \prod_i{\gamma_{\alpha_i,M_i}}_{(\sigma_i)} \tag{2}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The cluster function is a product of a quantity which in the sense of binary alloys is called a spin variable (inspired by the Ising model), whereas, in general, for multicomponent systems seems to have no name. The paper cited in the question denotes it as &lt;span class=&quot;math-container&quot;&gt;$\gamma_{\alpha_i,M_i}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; represents a lattice point, &lt;span class=&quot;math-container&quot;&gt;$\alpha_i$&lt;/span&gt; takes two values, 0 for when &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is not in a certain cluster and 1 when it is, and &lt;span class=&quot;math-container&quot;&gt;$M_i$&lt;/span&gt; is simply the number of type of atoms, 2 for binary, 3 for ternary, and so on. &lt;em&gt;Note: &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_i$&lt;/span&gt; aren't the same.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Convention: &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; equals 1 for any site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; that isn't part of the particular cluster &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\alpha_i\: =\: 0$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; in equation 2 is an occupation variable which holds the information about which atom occupies lattice site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. It takes values from &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$M_i - 1$&lt;/span&gt;. For example, in a ternary alloy, &lt;span class=&quot;math-container&quot;&gt;$\sigma_i\: =\: 0, 1,$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\sigma_i\: =\:&#xA;\begin{cases}&#xA;-1, &amp;amp; \text{atom A on i}\\&#xA;    +1, &amp;amp; \text{atom B on i}&#xA;\end{cases}&#xA;\tag{3}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's calculate the pair correlation for &lt;span class=&quot;math-container&quot;&gt;$AB$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha\: =\: 2$&lt;/span&gt; (pair)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$M_i\: =\: 2$&lt;/span&gt; (binary)&lt;/p&gt;&#xA;&lt;p&gt;In a perfectly random phase, each lattice point &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is equally likely to be occupied by &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; since it is an equiatomic alloy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha_i$&lt;/span&gt; will be &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; for all lattice points that aren't in the particular pair we are calculating the cluster function for and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; for those that are part of the pair. So the four possible values of &lt;span class=&quot;math-container&quot;&gt;${\gamma_{\alpha_i,M_i}}_{(\sigma_i)}$&lt;/span&gt; for a binary are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\gamma_{0,2}}_{(0)}\: =\: 1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\gamma_{0,2}}_{(1)}\: =\: 1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\gamma_{1,2}}_{(0)}\: =\: -1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\gamma_{1,2}}_{(1)}\: =\: +1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In a random phase of &lt;span class=&quot;math-container&quot;&gt;$AB$&lt;/span&gt;, every lattice site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; on average has a &lt;span class=&quot;math-container&quot;&gt;$0.5$&lt;/span&gt; occupation of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$0.5$&lt;/span&gt; of &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;. To calculate the correlation function, &lt;span class=&quot;math-container&quot;&gt;$\rho_\alpha$&lt;/span&gt;, we need to take an average of cluster functions for all equivalent clusters &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. Every pair (even higher clusters) in a perfectly random phase is equivalent, so all cluster functions are the same and equal to the average, hence equal to the correlation function.&lt;/p&gt;&#xA;&lt;p&gt;The value of &lt;span class=&quot;math-container&quot;&gt;${\gamma_{1,2}}_{(\sigma_i = 0,1)}\: =\: 0.5\cdot (-1) + 0.5\cdot (+1) = 0$&lt;/span&gt; for each site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So the cluster function for a pair which contains two lattice points &lt;span class=&quot;math-container&quot;&gt;$=\: 0\cdot 0\: = 0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, the correlation function, &lt;span class=&quot;math-container&quot;&gt;$\rho_2$&lt;/span&gt;, is equal to &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-04T10:19:53.943" LastActivityDate="2020-12-04T10:19:53.943" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3854" PostTypeId="1" AcceptedAnswerId="3866" CreationDate="2020-12-02T12:44:48.307" Score="11" ViewCount="1647" Body="&lt;p&gt;The following passage about the merits of density-functional perturbation theory (DFPT) is extracted from this seminal paper: &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.515&quot; rel=&quot;noreferrer&quot;&gt;Phonons and related crystal properties from density-functional perturbation theory&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;One of the greatest advantages of DFPT—as compared to other nonperturbative methods for calculating the vibrational properties of crystalline solids (such as the frozen-phonon or molecular-dynamics spectral analysis methods)—is that within DFPT the responses to perturbations of different wavelengths are decoupled. This feature allows one to calculate phonon frequencies at arbitrary wave vectors &lt;span class=&quot;math-container&quot;&gt;$\vec{q}$&lt;/span&gt; &lt;strong&gt;avoiding the use of supercells&lt;/strong&gt; and with a workload that is essentially independent of the phonon wavelength.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;noreferrer&quot;&gt;Phonopy&lt;/a&gt; is an open-source package for phonon calculations at harmonic and quasi-harmonic levels. In particular, Phonopy is interfaced with VASP. The following link is the tutorial about how to calculate the phonon band structure of NaCl with VASP+DFPT.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://phonopy.github.io/phonopy/vasp-dfpt.html#vasp-dfpt-interface&quot; rel=&quot;noreferrer&quot;&gt;https://phonopy.github.io/phonopy/vasp-dfpt.html#vasp-dfpt-interface&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/T834z.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/T834z.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;However, the second step of this tutorial to use VASP is the construction of a supercell. Why?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-12-03T19:31:18.333" LastActivityDate="2020-12-04T01:12:15.230" Title="Why do we need to build a supercell to use the DFPT in Phonopy interfaced with VASP?" Tags="|density-functional-theory|software|vasp|phonopy|dfpt|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3855" PostTypeId="2" ParentId="3852" CreationDate="2020-12-02T15:42:02.430" Score="10" Body="&lt;p&gt;As you suggesting, your computed &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; goes to zero at large &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; because of your handling of the periodic boundary conditions. You should include every particle at a distance of &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; whether it's in the main cell or not, and not only the closest particle.&lt;/p&gt;&#xA;&lt;p&gt;If it's not clear for you, the following picture may help you. Imagine you're computing &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; for the red particle of the bottom-left corner, then getting only the closest particle would mean that you only take &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt; into account, while &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r_3$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_4$&lt;/span&gt; are also smaller than &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; and should be considered when computing &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yj3Tt.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yj3Tt.png&quot; alt=&quot;pbc_and_rdf&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2020-12-02T15:42:02.430" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3856" PostTypeId="1" AcceptedAnswerId="3869" CreationDate="2020-12-02T15:47:21.867" Score="14" ViewCount="1962" Body="&lt;p&gt;I would like to ask how to use PHONOPY to define which band is LO, TO or LA, TA, or ZO or ZA.&#xA;I attach a picture from &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/28/10/103005&quot; rel=&quot;noreferrer&quot;&gt;https://iopscience.iop.org/article/10.1088/0953-8984/28/10/103005&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/sZHo2.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sZHo2.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2024-03-20T19:58:56.273" Title="How to determine LA/TA, ZA/ZO and LO/TO by PHONOPY" Tags="|phonons|phonopy|phonon-dispersion|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3857" PostTypeId="2" ParentId="3848" CreationDate="2020-12-02T19:21:06.740" Score="12" Body="&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}^+$&lt;/span&gt;&lt;/h3&gt;&#xA;&lt;p&gt;This ion has 28 electrons. If all of them are up (i.e. aligned with the +z axis), then since each electron has a spin of magnitude 1/2, we would have a total spin of +14. If all of them are down we would have a total spin of -14. We could also have 1 up and 27 down, meaning &lt;span class=&quot;math-container&quot;&gt;$+\frac{1}{2} - \frac{27}{2} = -\frac{26}{2} = -13$&lt;/span&gt;. The number of total possibilities is &lt;span class=&quot;math-container&quot;&gt;$28 + 1 = 29$&lt;/span&gt;. &lt;strong&gt;This is the number of possibilities for the spin projection quantum number.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;However what they might not say in your textbook is that quantum states can exist also in superpositions such as: &lt;span class=&quot;math-container&quot;&gt;$a|\frac{1}{2}\rangle + b|-\frac{1}{2}\rangle$&lt;/span&gt;, as long as &lt;span class=&quot;math-container&quot;&gt;$|a|^2 + |b|^2=1$&lt;/span&gt;. You can have an infinite number of superpositions parameterized by &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; if we set &lt;span class=&quot;math-container&quot;&gt;$a=\cos\theta,b=\sin\theta$&lt;/span&gt;. You can have even more types of superpositions (parameterized by another angle &lt;span class=&quot;math-container&quot;&gt;$\varphi$&lt;/span&gt;) by adding a factor of &lt;span class=&quot;math-container&quot;&gt;$e^{\rm{i\varphi}}$&lt;/span&gt; to either &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;. Superpositions don't tend to last long though, due to decoherence, so it's not common to say that &amp;quot;there's an infinite number of possibilities for the spin state&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, even when we have 1 electron up and 27 down, there's 27 different choices you can make for the up electron, so there's actually &lt;span class=&quot;math-container&quot;&gt;$2^{28}$&lt;/span&gt; possible spin configurations, though many of them would not last long because of &lt;em&gt;orbital&lt;/em&gt; angular momentum considerations (i.e. filling up the &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt; orbital first, before the &lt;span class=&quot;math-container&quot;&gt;$2p$&lt;/span&gt; orbitals), and many of them will be equivalent in energy due to symmetry.&lt;/p&gt;&#xA;&lt;p&gt;If you are wondering which states have been observed experimentally, you can see at the &lt;a href=&quot;https://physics.nist.gov/cgi-bin/ASD/energy1.pl?de=0&amp;amp;spectrum=Cu+II&amp;amp;submit=Retrieve+Data&amp;amp;units=0&amp;amp;format=0&amp;amp;output=0&amp;amp;page_size=15&amp;amp;multiplet_ordered=0&amp;amp;conf_out=on&amp;amp;term_out=on&amp;amp;level_out=on&amp;amp;biblio=on&amp;amp;temp=&quot; rel=&quot;noreferrer&quot;&gt;NIST website that there's quite a lot of them&lt;/a&gt; but the first state with a spin of +2 is more than 5x higher in energy than the first state with spin +1, which is about 22000 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; in energy above the state with spin 0 (i.e. 14 electrons up and 14 electrons down), so without a laser or a very high temperature, you are most likely to find this ion in the spin 0 state:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pJHMj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pJHMj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}^{2+}$&lt;/span&gt;&lt;/h3&gt;&#xA;&lt;p&gt;Now we have 27 electrons, and 28 possibilities for the spin projection quantum number. We can also have an infinite number of superpositions, but we usually don't talk about those. &lt;a href=&quot;https://physics.nist.gov/cgi-bin/ASD/energy1.pl?de=0&amp;amp;spectrum=Cu+III&amp;amp;submit=Retrieve+Data&amp;amp;units=0&amp;amp;format=0&amp;amp;output=0&amp;amp;page_size=15&amp;amp;multiplet_ordered=0&amp;amp;conf_out=on&amp;amp;term_out=on&amp;amp;level_out=on&amp;amp;biblio=on&amp;amp;temp=&quot; rel=&quot;noreferrer&quot;&gt;NIST tells us that many different states have been observed, but every single one of them seems to have a spin projection quantum number with magnitude of 1 or 3&lt;/a&gt;, but unlike for &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}^+$&lt;/span&gt; where there was multiple studies all the way up to the year 2017, for &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}^{2+}$&lt;/span&gt; they all come from the same 1990 reference. Here's the first few:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yoE3z.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yoE3z.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;But be careful:&lt;/h3&gt;&#xA;&lt;p&gt;Spin isn't always a &lt;a href=&quot;https://en.wikipedia.org/wiki/Good_quantum_number&quot; rel=&quot;noreferrer&quot;&gt;good quantum number&lt;/a&gt;. For example in the hydrogen atom, &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; does not commute with the Dirac Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, but &lt;span class=&quot;math-container&quot;&gt;$J = L + S$&lt;/span&gt; is a &amp;quot;good quantum number&amp;quot; because &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; commutes with &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What the above paragraph is saying, is that due to spin-orbit coupling, you can't always get away with considering spin on its own since &amp;quot;spin angular momentum&amp;quot; and &amp;quot;orbital angular momentum&amp;quot; are married. You would instead talk about &amp;quot;total angular momentum&amp;quot; states, or &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;-states, for which as a general guideline you can think of a triplet as having 3, and a doublet having 2, (see the above screenshots which show three different levels for each triplet and 2 different levels for each doublet, but unfortunately only 4 levels for the pentuplet).&lt;/p&gt;&#xA;&lt;p&gt;In reality it's not just the electron-spin and electron-orbital angular momenta that couple to each other, and there's also nuclear-spin and nuclear-rotation, and even &lt;a href=&quot;https://en.wikipedia.org/wiki/Halo_nucleus&quot; rel=&quot;noreferrer&quot;&gt;nuclear-orbital&lt;/a&gt; angular momentum, and surely even more than that, which can also be considered, which means that even &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is probably not a &amp;quot;good quantum number&amp;quot; in a grand unified theory of everything, &lt;strong&gt;but in maybe 90% of scientific applications it's okay to just consider spin, and in maybe 99.9999999% applications it is okay to use &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;&lt;/strong&gt; (that means that maybe only 1 in every 1 billion scientific studies would require one to go beyond using only &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;, in fact maybe it's less because I don't know of any studies at all that go beyond just using &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; though they may exist in studies that are specifically trying to look at when the &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; quantum number breaks down).&lt;/p&gt;&#xA;&lt;p&gt;Note that &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is always a better quantum number than &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;, so there's cases where &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; can be used and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; would not be a good idea to use, but there's never a case where spin is a good quantum number and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is not (though using &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; without &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; may be better for simplicity and presentation in cases where &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is not absolutely necessary for the point being conveyed, e.g. for low-accuracy spectroscopy of an atom with low enough mass that relativistic corrections are not necessary, and spectroscopy at such low-resolution that fine and hyperfine structure are not visible).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-02T19:32:17.177" LastActivityDate="2020-12-02T19:32:17.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3858" PostTypeId="5" CreationDate="2020-12-02T19:43:17.210" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-02T19:43:17.210" LastActivityDate="2020-12-02T19:43:17.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3859" PostTypeId="4" CreationDate="2020-12-02T19:43:17.210" Score="0" Body="For questions about &quot;spin angular momentum&quot;, spin states, and anything else having to do with spin." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-02T19:43:17.210" LastActivityDate="2020-12-02T19:43:17.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3860" PostTypeId="2" ParentId="3848" CreationDate="2020-12-02T20:28:47.997" Score="11" Body="&lt;p&gt;Often when one is asked for the number of spin states, we are interested in determining the spin state of metal complexes containing these ions, rather than the lone ion itself.  If you are interested in just the lone ion itself, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3857/5&quot;&gt;Nike Dattani's answer&lt;/a&gt; goes into depth about that. My answer will focus on the determination of spin states of ions within metal complexes.&lt;/p&gt;&#xA;&lt;p&gt;Chemists tend to look at this through the lens of &lt;a href=&quot;https://en.wikipedia.org/wiki/Ligand_field_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ligand Field Theory&lt;/a&gt;, which is basically a minimal basis Linear-Combination of Atomic Orbitals (LCAO) scheme to qualitatively describe bonding in a molecule. A full summary of this approach is more than I could fit (or reliably convey here), but I can give a very stripped down summary.&lt;/p&gt;&#xA;&lt;p&gt;For metal complexes, the spin state is affected by:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The symmetry of the molecule&lt;/li&gt;&#xA;&lt;li&gt;The number of valence electrons on the metal ion&lt;/li&gt;&#xA;&lt;li&gt;The type of ligands attached to the metal center&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The symmetry of the molecule leads to a particular arrangement of Molecular Orbitals (MOs), which affects how stable a given spin state would be. For example, many metals complexes are octahedral, which leads to a frontier orbital arrangement like the picture below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/anIww.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/anIww.png&quot; alt=&quot;octahedral crystal field splitting&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The number of d-electrons affects how many of these orbitals are filled. For example, &lt;span class=&quot;math-container&quot;&gt;$[\ce{Cu(H2O)_6}]^{2+}$&lt;/span&gt; would fill 4 of these orbitals and half fill the last since &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu^{2+}}$&lt;/span&gt; has 9 valence electrons. This would leave us with one unpaired electron, resulting in a spin multiplicity of 2.&lt;/p&gt;&#xA;&lt;p&gt;The attached ligands can also play a role in determining the spin state. Considering the octahedral splitting again, the ligands affect how large the gap is between the upper and lower set of orbitals. The splitting effect competes with the energy penalty due to Coulomb repulsion of putting electrons in the same orbital. Consider the example of a metal with 5 valence electrons, say &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe^{3+}}$&lt;/span&gt;. Depending on the ligand, the complex can either be low-spin or high-spin.&lt;/p&gt;&#xA;&lt;p&gt;In a low spin complex (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{[Fe(NO2)6]^{3-}}$&lt;/span&gt;), the splitting is large, so it is more energetically favorable to pair electrons than to &amp;quot;promote&amp;quot; them to the upper orbitals.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Hs16K.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Hs16K.png&quot; alt=&quot;Low spin splitting&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a high spin complex like &lt;span class=&quot;math-container&quot;&gt;$\ce{[FeBr6]^{3-}}$&lt;/span&gt;, the splitting is small and so it is more energetically favorable to &amp;quot;promote&amp;quot; electrons to the upper orbitals than to pair them.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/9O2Ii.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9O2Ii.png&quot; alt=&quot;High spin splitting&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Getting back to your example, &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu+}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu^{2+}}$&lt;/span&gt; tend to form singlet and doublet spin state complexes, respectively. The reason for this lack of variety is that, even with different ligands altering the splitting, there are still 10/9 electrons that need to fill into these 5 orbitals and there just aren't different ways to arrange them without occupying higher energy orbitals.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2020-12-03T21:32:56.600" LastActivityDate="2020-12-03T21:32:56.600" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3861" PostTypeId="2" ParentId="1535" CreationDate="2020-12-02T21:08:58.533" Score="4" Body="&lt;h3&gt;CP2K&lt;/h3&gt;&#xA;&lt;p&gt;This program can do all-electron calculations using the GAPW method.&lt;/p&gt;&#xA;" OwnerUserId="1577" LastEditorUserId="5" LastEditDate="2020-12-02T21:31:15.553" LastActivityDate="2020-12-02T21:31:15.553" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3862" PostTypeId="1" CreationDate="2020-12-03T02:18:09.400" Score="14" ViewCount="190" Body="&lt;p&gt;Before taking the deep dive (see linked questions below) into calculating the diffraction of 20 to 200 eV electrons from crystal surfaces, I'd like to generate a simple &amp;quot;muffin-tin potential&amp;quot; (see below) from some simple analytical approximation that roughly matches what might be calculated as the electrostatic potential that an incident electron would feel passing through a mid-sized atom (hydrogen &amp;lt;&amp;lt; atom &amp;lt;&amp;lt; uranium) arranged in a crystal.&lt;/p&gt;&#xA;&lt;p&gt;I can start to learn how to calculate phase shifts and angular distributions with this.&lt;/p&gt;&#xA;&lt;p&gt;Wikipedia's &lt;a href=&quot;https://en.wikipedia.org/wiki/Muffin-tin_approximation&quot; rel=&quot;noreferrer&quot;&gt;Muffin-tin approximation&lt;/a&gt; talks about this but doesn't offer any equations out-of-hand.&lt;/p&gt;&#xA;&lt;p&gt;The zeroth order approximation would be a nuclear positive point charge and a uniform sphere of negative charge and I can certainly start with that; with vague uniformity argument based on the exclusion principle. A flat &amp;quot;inner potential&amp;quot; of 5 to 15 eV is often assumed between atoms in this context. At small distances it would have to be flattened since near the nucleus it goes to infinity.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; But is there a somewhat better approximation than that available?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5YA2D.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5YA2Dm.png&quot; alt=&quot;uniform electron sphere with point nucleus&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Cross-section through a &amp;quot;one-muffin tin&amp;quot; made from a uniform &lt;span class=&quot;math-container&quot;&gt;$r = 1$&lt;/span&gt; electron sphere and a point nucleus, arbitrarily flattened at the bottom. These would be arranged in space at each atom's location and a constant potential would fill the space between them.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Long term goal for background only:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/527/201&quot;&gt;Overview of how self-consistent dynamical low-energy electron diffraction simulations are performed&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2380/201&quot;&gt;Have Finite Difference Time Domain methods made inroads into dynamical simulation of electron and/or X-ray scattering by crystals?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1793/201&quot;&gt;Simulated low energy electron diffraction (LEED) patterns&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2020-12-03T04:13:41.773" LastActivityDate="2020-12-04T22:17:43.467" Title="Analytical expression for an atomic lattice &quot;muffin-tin&quot; potential for purposes of illustration and simple scattering calculations" Tags="|pseudopotentials|diffraction|electron-diffraction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3863" PostTypeId="2" ParentId="1572" CreationDate="2020-12-03T08:57:12.147" Score="10" Body="&lt;h1&gt;GW+BSE:&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Excited states in the framework of many-body Green's function comprise charged excitations, where the number of electrons in the system changes from &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$N-1$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$N + 1$&lt;/span&gt;, and natural excitations, where the number of electrons remains constant.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In the &lt;span class=&quot;math-container&quot;&gt;$|N\rangle \rightarrow |N-1\rangle$&lt;/span&gt; case, an electron in the valence band (occupied orbital) is kicked out of the system by photon irradiation. In the &lt;span class=&quot;math-container&quot;&gt;$|N\rangle \rightarrow |N+1\rangle$&lt;/span&gt; case, an electron from infinity falls into the conduction band (unoccupied orbital), emitting a photon simultaneously. These two processes are related to photoemission spectroscopy and inverse photon spectroscopy, through which we can study the electronic structure, ionization potential, and electron affinity of materials and molecules.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IasUh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IasUh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In the &lt;span class=&quot;math-container&quot;&gt;$|N\rangle \rightarrow |N\rangle$&lt;/span&gt; case, an electron in the valence band is boosted into the conduction band after absorbing a photon, leaving a hole in the valence band. The excited electron and the hole left in the valence band are coupled together by Coulomb interaction, forming an exciton. The energy and oscillator strength of the exciton can be measured through optical absorption spectroscopy.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x52PO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x52PO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Single-particle Green's function describes the electron addition or removal process in the system. If &lt;span class=&quot;math-container&quot;&gt;$|N,0\rangle$&lt;/span&gt; stands for the ground state of the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron system, then the single-particle Green's function is defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$G(1,2) \equiv G(\vec{r}_1t_1,\vec{r}_2t_2)=-i\langle N,0|T[\hat{\psi}(\vec{r}_1t_1)\hat{\psi}^\dagger(\vec{r}_2t_2)]|N,0\rangle$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\hat{\psi}^{\dagger}(\vec{r}t)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{\psi}(\vec{r}t)$&lt;/span&gt; are the fermion creation and annihilation operators in the Heisenberg picture, respectively, &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the Wick's time-ordering operator which has the effect of ordering the operators with largest time on the left. In the Lehmann representation, the solution for single-particle Green's function can be simplfied as the following quasiparticle Kohn-Sham-like equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\left[ -\dfrac{1}{2}\nabla^2+V_H(\vec{r})+V_{ext}+\Sigma[E_i^{QP}] \right]\psi_i^{QP}(\vec{r})=E_i^{QP}\psi_i^{QP} \tag{1}$$&lt;/span&gt;&#xA;in which the self-energy &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; play the same role as the exchang-correlation functional in Kohn-Sham equation. However, solutions of Eq.(1) are quasiparticle energies and quasiparticle wavefunctions which are physically more meaningful than the solutions of Kohn-Sham equation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The motion of two-particle Green's function obeys the Bethe-Salpeter equation (BSE):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$L(1,2;1',2')=G(1,2')G(2',1')+\int G(1,3)G(3',1')K(3,4';3',4)L(4,2;4',2')d(3,3',4',4)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is the two-particle correlation function defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$L(1,2;1',2')=-G_2(1,2;1',2')+G(1,1')G(2,2')$$&lt;/span&gt;&#xA;and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is the two-particle (electron-hole) interaction kernel. The BSE can be turned into an eigenvalue problem:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(E_c-E_v)A_{vc}^S+\sum_{v'c'}K_{vc,v'c'}^{AA}(\Omega_S)A_{v'c'}^S=\Omega_SA_{vc}^S$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$A_{vc}^S$&lt;/span&gt; the exciton wavefunction and &lt;span class=&quot;math-container&quot;&gt;$\Omega_S$&lt;/span&gt; is the exciton egienvalue. By solving BSE eigenequation, the optical spectrum with electron-hole interaction can be obtained.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ref: &lt;a href=&quot;https://www.researchgate.net/publication/301940861_GW_method_and_Bethe-Salpeter_equation_for_calculating_electronic_excitations_GW_method_and_Bethe-Salpeter_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;GW method and Bethe-Salpeter equation for calculating electronic excitations: GW method and Bethe-Salpeter equation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-03T05:38:16.847" LastActivityDate="2021-01-03T05:38:16.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3864" PostTypeId="1" AcceptedAnswerId="4807" CreationDate="2020-12-03T10:53:50.347" Score="12" ViewCount="259" Body="&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41467-018-05759-4&quot; rel=&quot;noreferrer&quot;&gt;In this paper&lt;/a&gt;, it is mentioned that a non-centrosymmetric system with time-reversal symmetry doesn't have a linear response. It is actually a consequence of the Onsager reciprocal theorem.&lt;/p&gt;&#xA;&lt;p&gt;But I didn't understand the theorem properly. Can anyone give an intuitive picture of why the linear response is absent in a non-centrosymmetric system with time-reversal symmetry?&lt;/p&gt;&#xA;" OwnerUserId="1594" LastEditorUserId="5" LastEditDate="2021-02-28T05:11:53.937" LastActivityDate="2021-04-26T02:57:13.770" Title="Why linear response is absent in a non-centrosymmetric system with time reversal symmetry?" Tags="|mathematical-modeling|symmetry|optical-properties|weyl-semimetal|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3865" PostTypeId="1" AcceptedAnswerId="8857" CreationDate="2020-12-03T16:02:58.950" Score="14" ViewCount="397" Body="&lt;p&gt;&lt;strong&gt;How do I know if the reconstruction in the picture is a 2x2 reconstruction or not?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;             &#xA;                     &lt;a href=&quot;https://i.stack.imgur.com/v1q21.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/v1q21.png&quot; alt=&quot;crystallography&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe that this corresponds to a 2x2 reconstruction because there's an even horizontal and vertical distance between the half-order and the full-order points in the corners of the pattern but I don't really understand how this is any different from a 4x4 or so.&lt;/p&gt;&#xA;&lt;p&gt;On the &lt;a href=&quot;https://en.wikipedia.org/wiki/Low-energy_electron_diffraction&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia page&lt;/a&gt; on LEED the following image is shown, representing the superposition of two different patterns, the 2x1, and the 1x2 patterns. These look identical to me apart from the direction of the drawn rectangle which thus far I have presumed to be a choice of the individual.&lt;/p&gt;&#xA;&lt;p&gt;             &#xA;                        &lt;a href=&quot;https://i.stack.imgur.com/EAHgQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EAHgQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can these projections also indicate if such a surface is faceted? If so, how can this be deduced?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1590" LastEditorUserId="5" LastEditDate="2021-09-05T22:39:50.240" LastActivityDate="2023-03-10T19:02:41.977" Title="How do I know if the reconstruction in the picture is a 2x2 reconstruction?" Tags="|surfaces|crystallography|electron-diffraction|nanostructures|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3866" PostTypeId="2" ParentId="3854" CreationDate="2020-12-03T18:24:19.587" Score="10" Body="&lt;p&gt;Disclaimer: I have never used Phonopy.&lt;/p&gt;&#xA;&lt;p&gt;The advantage of using DFPT is that in principle it can be used to calculate a perturbation of finite wave vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; using the primitive cell. This should be contrasted with finite differences, which can only be used to calculate perturbations at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. If you want to access a non-&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; wave vector using finite differences, then you need to map that wave vector to the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point by constructing a commensurate supercell.&lt;/p&gt;&#xA;&lt;p&gt;I think the problem with the DFPT implementation of VASP is that it can only calculate phonons at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;. This means that the DFPT implementation of VASP is then no different to a finite differences implementation, in the sense that you also need to build supercells to map the wave vector you are interested in into the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. In turn, this means that there is no advantage to doing the calculations with DFPT, you may as well use finite differences in this case.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="1218" LastEditDate="2020-12-04T01:12:15.230" LastActivityDate="2020-12-04T01:12:15.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3867" PostTypeId="2" ParentId="392" CreationDate="2020-12-03T18:44:19.800" Score="9" Body="&lt;h1&gt;1997 (Marzari &amp;amp; Vanderbilt): MLWF&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;These methods enable a more qualitative view of the electron density by projecting the Bloch wavefunctions into localized Wannier functions [1], which is especially useful when it comes to transition metal systems, but not limited to these.&lt;/li&gt;&#xA;&lt;li&gt;This description enables DFT practitioners to &amp;quot;talk&amp;quot; to the modelling community, since now we can approximate the physics and chemistry of the system in terms of orbitals.&lt;/li&gt;&#xA;&lt;li&gt;Two major milestones are the description of the maximally localized Wannier functions (MLWF) method by Marzari and Vanderbilt [2] and its community open-source implementation as &lt;code&gt;Wannier90&lt;/code&gt; [3].&lt;/li&gt;&#xA;&lt;li&gt;There are still ongoing work to perfect the method (such as alternative projection criteria), and to apply it to study other (more &lt;em&gt;exotic&lt;/em&gt;) material systems. For instance, recently it has been used to describe the effective physics of the spin liquid candidate &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{RuCl_3}$&lt;/span&gt; [4].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1] G.H. Wannier, &lt;em&gt;Phys. Rev.&lt;/em&gt; &lt;strong&gt;52&lt;/strong&gt;, 191 (1937), doi:&lt;a href=&quot;https://doi.org/10.1103/PhysRev.52.191&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRev.52.191&lt;/a&gt;&lt;br&gt;&#xA;[2] N. Marzari &amp;amp; D. Vanderbilt, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;56&lt;/strong&gt;, 12847 (1997), doi:&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.56.12847&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRevB.56.12847&lt;/a&gt;; N. Marzari &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;Rev. Mod. Phys.&lt;/em&gt; &lt;strong&gt;84&lt;/strong&gt;, 1419 (2002), doi:&lt;a href=&quot;https://doi.org/10.1103/RevModPhys.84.1419&quot; rel=&quot;noreferrer&quot;&gt;10.1103/RevModPhys.84.1419&lt;/a&gt;&lt;br&gt;&#xA;[3] A.A. Mostofi &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;Comput. Phys. Commun.&lt;/em&gt; &lt;strong&gt;178&lt;/strong&gt;, 685 (2008), doi:&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2007.11.016&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2007.11.016&lt;/a&gt;; A.A. Mostofi &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;Comput. Phys. Commun.&lt;/em&gt; &lt;strong&gt;185&lt;/strong&gt;, 2309 (2014), doi:&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2014.05.003&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2014.05.003&lt;/a&gt;; G. Pizzi &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;J. Phys. Cond. Mat.&lt;/em&gt; &lt;strong&gt;32&lt;/strong&gt;(16), 165902 (2020), doi:&lt;a href=&quot;https://doi.org/10.1088/1361-648X/ab51ff&quot; rel=&quot;noreferrer&quot;&gt;10.1088/1361-648X/ab51ff&lt;/a&gt;&lt;br&gt;&#xA;[4] C. Eichstaedt &lt;em&gt;et al.&lt;/em&gt;, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;100&lt;/strong&gt;, 075110 (2019), doi:&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.100.075110&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRevB.100.075110&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1596" LastEditorUserId="5" LastEditDate="2020-12-03T19:23:20.760" LastActivityDate="2020-12-03T19:23:20.760" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3868" PostTypeId="2" ParentId="3862" CreationDate="2020-12-03T19:43:52.773" Score="7" Body="&lt;p&gt;The Augmented Plane Wave (APW) method, and by extension Linearly-Augmented Plane Wave method are both generalizations of the Muffin Tin Approximation.&lt;/p&gt;&#xA;&lt;p&gt;In both the APW and LAPW methods, the potential &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; is defined as a piecewise function [1] with a single parameter: the muffin-tin radius &lt;span class=&quot;math-container&quot;&gt;$r_\mathrm{MT}$&lt;/span&gt;.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V(r) = %&#xA;\begin{cases}&#xA;\sum_{lm} V_{lm} (r) Y_{lm} (\hat{r}) &amp;amp; r &amp;lt; r_\mathrm{MT} &amp;amp; (\mathrm{core}) \\&#xA;V_K e^{i K r} &amp;amp; r &amp;gt; r_\mathrm{MT} &amp;amp; (\mathrm{interstitial})&#xA;\end{cases}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The values of the potential &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt;, the wavefunction &lt;span class=&quot;math-container&quot;&gt;$\phi(r)$&lt;/span&gt;, and the electronic density &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; are matched at &lt;span class=&quot;math-container&quot;&gt;$r = r_\mathrm{MT}$&lt;/span&gt; to ensure that the derivative exists for each of them.&lt;/p&gt;&#xA;&lt;p&gt;The following illustration is from Singh &amp;amp; Nordstrom (2006) [2],&#xA;&lt;a href=&quot;https://i.stack.imgur.com/9rzPg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9rzPg.png&quot; alt=&quot;LAPW basis functions&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;On solving the non-relativistic Schrödinger equation, the same book remarks the following in ch. 5, p. 63.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;These differential equations [the radial Schrödinger equation] may be solved on the radial mesh using standard, e.g. predictor-corrector methods.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;On matching the two piecewise parts (ch. 4, p. 44):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Noting that from Schrödinger's equation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ (E_2 - E_1) ~ r ~ u_1 (r) ~ u_2 (r) = u_2 (r) ~ \frac{ \mathrm{d}^2 ~ r ~ u_1(r) }{\mathrm{d}r^2} - u_1 (r) ~ \frac{ \mathrm{d}^2 ~ r ~ u_2(r) }{\mathrm{d}r^2} $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$u_1 (r)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$u_2 (r)$&lt;/span&gt; are radial solutions at different energies &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt;. The overlap is constructed using this relation and integrating by parts; the surface terms vanish if either &lt;span class=&quot;math-container&quot;&gt;$u_1 (r)$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$u_2 (r)$&lt;/span&gt; vanish on the sphere boundary, while the other terms cancel.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Anyway, I personally don't think solving the radial Schrödinger equation is too computationally expensive, given the current state of computers. But if you want to avoid it at all costs, there is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kronig%E2%80%93Penney_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kronig-Penney model&lt;/a&gt;, which is a lot simpler at the expense of accuracy.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;[1] &amp;quot;The Full Potential APW methods&amp;quot;, &lt;a href=&quot;http://susi.theochem.tuwien.ac.at/lapw/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://susi.theochem.tuwien.ac.at/lapw/index.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] Singh &amp;amp; Nordstrom (2006), &lt;em&gt;Planewaves, Pseudopotentials, and the LAPW Method, 2nd Edition&lt;/em&gt;, Springer. &lt;a href=&quot;https://link.springer.com/book/10.1007/978-0-387-29684-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;SpringerLink&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1596" LastEditorUserId="1596" LastEditDate="2020-12-04T22:17:43.467" LastActivityDate="2020-12-04T22:17:43.467" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3869" PostTypeId="2" ParentId="3856" CreationDate="2020-12-03T21:40:15.400" Score="12" Body="&lt;p&gt;There are two major techniques used to model phonon interactions - The frozen phonon method and density functional perturbation theory (DFPT). Phonopy is used to carry out calculations in the frozen phonon scheme. ProfM does a fantastic job delineating the differences between the two methods &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/89/are-there-differences-in-accuracy-and-reliability-between-the-frozen-phonon-meth&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The first step in such a finite displacement scheme is to generate supercells with small 'q' shifts in different directions. Next, the forces between atoms in the 'displaced' crystals are calculated to construct a force constant matrix. Diagonalizing this matrix leads us to the normal modes at any particular wavevector 'q'. First, we need to generate supercells using phonopy - This is the simplest step and there are different ways to do this, whether you work with QE (Quantum ESPRESSO) or VASP. (Check phonopy documentation here: &lt;a href=&quot;https://phonopy.github.io/phonopy/vasp.html&quot; rel=&quot;noreferrer&quot;&gt;https://phonopy.github.io/phonopy/vasp.html&lt;/a&gt;). Once phonopy generates the supercells, your first task (the 'pre-processing' step in phonopy) is complete.&lt;/p&gt;&#xA;&lt;p&gt;Typically, the scheme to calculate the vibrational modes would be to perform a charge density calculation for all these supercells. Once this is done, the outputs of these files can be used to construct the force constant matrix (this is the 'calculation of forces' section in phonopy).&lt;/p&gt;&#xA;&lt;p&gt;The information regarding eigenvectors of the modes can be found by generating the mesh.yaml file, which is part of the post-processing process listed on the phonopy webpage. Again, this can be generated with a simple one-line command. I was able to scrap one of the mesh.yaml files for a system (which has 6 atoms in the cell) that I worked on a long time back and here's a snippet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;frequency:     2.5939095837&#xA;eigenvector:&#xA;- # atom 1&#xA;  - [  0.14423900354589,  0.00000000000000 ]&#xA;  - [ -0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;- # atom 2&#xA;  - [ -0.14423900354589,  0.00000000000000 ]&#xA;  - [ -0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;- # atom 3&#xA;  - [ -0.32762271902471,  0.00000000000000 ]&#xA;  - [ -0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;- # atom 4&#xA;  - [  0.32762271902471,  0.00000000000000 ]&#xA;  - [ -0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;- # atom 5&#xA;  - [ -0.60980198739832,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;- # atom 6&#xA;  - [  0.60980198739832,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;  - [  0.00000000000000,  0.00000000000000 ]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first line lists the frequency of the mode in TerraHertz. What follows next is the eigenvector of the modes - The real and imaginary components are listed along all three cartesian directions. From this snippet, one can infer that all atoms move along 'x'. Additionally, the imaginary parts of all eigenvectors are zero - This has nothing to do with my particular system, but due to the fact that first-order Raman spectroscopy can only be used to probe near the Gamma point (because momentum of incident photon is much less compared to size of the Brillouin zone).&lt;/p&gt;&#xA;&lt;p&gt;Now that I have inferred that all atoms in this vibrational mode move along 'x', I would have to take a look at the supercell and observe the direction of the 'q' shift. If the 'q' shift is also along 'x', then this mode would be a longitudinal mode and if the 'q' shift was along 'y', this mode would be transverse. Whether the modes are optical or acoustic, can usually be logically inferred because the three lowest frequency modes are acoustic.&lt;/p&gt;&#xA;&lt;p&gt;I have not performed a phonon calculation for graphene. But, the modes reported in the paper referenced in the question, can be inferred in the way that I've described above - whether it be TA, LA, LO, TO. ZO and ZA are not much different - they just indicate bending out-of-plane (along 'z') and this can also be checked by looking at the 'z' components of the eigenvectors of modes in question.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="5" LastEditDate="2020-12-03T21:49:55.720" LastActivityDate="2020-12-03T21:49:55.720" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3870" PostTypeId="2" ParentId="3816" CreationDate="2020-12-04T00:52:11.453" Score="8" Body="&lt;p&gt;I am not an expert on Quantum ESPRESSO -QE- (just played with it some time ago), but as with any code, the choose of the number of CPUs to run the code is intrinsically related to how each task is coded and which of the parallel interface is used. It is not because you have access to thousand of CPUs that your job will run faster.&lt;/p&gt;&#xA;&lt;p&gt;Specifically for QE, &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node17.html&quot; rel=&quot;noreferrer&quot;&gt;chapter 3&lt;/a&gt; of the QE &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node1.html&quot; rel=&quot;noreferrer&quot;&gt;User's Guide&lt;/a&gt; is dedicated to parallelism. From this chapter, we have the several levels of parallelization implemented in QE:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;world: is the group of all processors (MPI_COMM_WORLD).&#xA;images: Processors can then be divided into different &amp;quot;images&amp;quot;, each corresponding to a different self-consistent or linear-response&#xA;calculation, loosely coupled to others.&lt;/li&gt;&#xA;&lt;li&gt;pools: each image can be subpartitioned into &amp;quot;pools&amp;quot;, each taking care of a group of k-points.&lt;/li&gt;&#xA;&lt;li&gt;bands: each pool is subpartitioned into &amp;quot;band groups&amp;quot;, each taking care of a group of Kohn-Sham orbitals (also called bands, or&#xA;wavefunctions). Especially useful for calculations with hybrid&#xA;functionals.&lt;/li&gt;&#xA;&lt;li&gt;PW: orbitals in the PW basis set, as well as charges and density in either reciprocal or real space, are distributed across processors.&#xA;This is usually referred to as &amp;quot;PW parallelization&amp;quot;. All&#xA;linear-algebra operations on array of PW / real-space grids are&#xA;automatically and effectively parallelized. 3D FFT is used to&#xA;transform electronic wave functions from reciprocal to real space and&#xA;vice versa. The 3D FFT is parallelized by distributing planes of the&#xA;3D grid in real space to processors (in reciprocal space, it is&#xA;columns of G-vectors that are distributed to processors).&lt;/li&gt;&#xA;&lt;li&gt;tasks: In order to allow good parallelization of the 3D FFT when the number of processors exceeds the number of FFT planes, FFTs on&#xA;Kohn-Sham states are redistributed to ``task'' groups so that each&#xA;group can process several wavefunctions at the same time.&#xA;Alternatively, when this is not possible, a further subdivision of FFT&#xA;planes is performed.&lt;/li&gt;&#xA;&lt;li&gt;linear-algebra group: A further level of parallelization, independent on PW or k-point parallelization, is the parallelization&#xA;of subspace diagonalization / iterative orthonormalization. Both&#xA;operations required the diagonalization of arrays whose dimension is&#xA;the number of Kohn-Sham states (or a small multiple of it). All such&#xA;arrays are distributed block-like across the ``linear-algebra group'',&#xA;a subgroup of the pool of processors, organized in a square 2D grid.&#xA;As a consequence the number of processors in the linear-algebra group&#xA;is given by n2, where n is an integer; n2 must be smaller than the&#xA;number of processors in the PW group. The diagonalization is then&#xA;performed in parallel using standard linear algebra operations. (This&#xA;diagonalization is used by, but should not be confused with, the&#xA;iterative Davidson algorithm). The preferred option is to use ELPA and&#xA;ScaLAPACK; alternative built-in algorithms are anyway available.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Here, you also will find the needed command line switches in order to setup a parallel calculation (&lt;code&gt;-nimage&lt;/code&gt;, &lt;code&gt;-npools&lt;/code&gt;, &lt;code&gt;-nband&lt;/code&gt;, &lt;code&gt;-ntg&lt;/code&gt;, &lt;code&gt;-ndiag&lt;/code&gt; and &lt;code&gt;-northo&lt;/code&gt;).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-12-04T00:52:11.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3871" PostTypeId="2" ParentId="3637" CreationDate="2020-12-04T01:32:14.400" Score="6" Body="&lt;p&gt;When working with solvents, you have two options to simulate it: implicit solvation (sometimes called continuum solvation) or explicit solvation.&lt;/p&gt;&#xA;&lt;p&gt;In the first case, a potential of mean forces is used to approximate the averaged behavior of many highly dynamic solvent molecules. One of the main used model is the &lt;a href=&quot;https://en.wikipedia.org/wiki/COSMO_solvation_model&quot; rel=&quot;noreferrer&quot;&gt;COSMO solvation model&lt;/a&gt; where the solvent is treated as a continuum with a permittivity &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the second case, the molecules representing the solvent are added explicitly to your model (as in the example you used of adding water molecules over a 2D system).&lt;/p&gt;&#xA;&lt;p&gt;In general, the calculations run faster using implicit solvation.&lt;/p&gt;&#xA;&lt;p&gt;Back to your question, Quantum ESPRESSO, &lt;em&gt;per se&lt;/em&gt;, does not work with solvents. But, there is an external module named &lt;a href=&quot;http://www.quantum-environ.org/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;ENVIRON&lt;/strong&gt;&lt;/a&gt;. From it's site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Environ&lt;/strong&gt; is a computational library aimed at introducing environment effects into atomistic first-principles simulations, in particular for applications in surface science and materials design.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Some of the features of &lt;strong&gt;Environ&lt;/strong&gt; are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Electrostatic effects of solvation. nviron allows to model the main electrostatic effects of a liquid solution on a solute, being it an isolated molecule or an incommensurate, linear or planar, system.&lt;/li&gt;&#xA;&lt;li&gt;Cavitation and pressure effects. By exploiting the definitions of quantum-volume (Cococcioni 2005) and quantum-surface (Scherlis 2006) of a system in terms of isosurfaces of its electronic density, two complex embedding effects are included in Environ.&lt;/li&gt;&#xA;&lt;li&gt;Electrostatic effects due to periodic-boundary conditions. A few of the most common approaches to remove artifacts due to periodic boundary conditions in aperiodic or partially periodic systems have been implemented in the Environ library.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The latest &lt;strong&gt;Environ&lt;/strong&gt; release, version 1.1, is compatible with QE, version 6.4.x and 6.3.x and you can download it from &lt;a href=&quot;http://www.quantum-environ.org/download.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-12-04T01:32:14.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3872" PostTypeId="1" AcceptedAnswerId="3922" CreationDate="2020-12-04T11:42:29.973" Score="11" ViewCount="1167" Body="&lt;p&gt;I'm quite new to spin-polarized DFT and have been trying to study &lt;span class=&quot;math-container&quot;&gt;$BaVSe_{3}$&lt;/span&gt; which is ferromagnetic (with a &lt;strong&gt;Final Magnetic Moment of 0.052 Bohr Mag&lt;/strong&gt;) as per the Materials Project repository [picture 1]. The Vanadium carries the moment as per &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwiT2PL9nrTtAhU4zTgGHR7wADoQFjAAegQIBBAC&amp;amp;url=https%3A%2F%2Fbib.irb.hr%2Fdatoteka%2F375274.Akrap_2008_PRB_78_p235111.pdf&amp;amp;usg=AOvVaw0NERY4HjQCpRnPCd4cTip5&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. But when a spin-polarized SCF was executed [as per the input file 1], the &lt;strong&gt;total magnetization was obtained as 1.95 Bohr Mag/cell&lt;/strong&gt;. The two values are quite different so am I doing something wrong here?  Or are these values different things?&lt;/p&gt;&#xA;&lt;p&gt;I'm using the primitive cell CIF file obtained from the Materials Project repo [Cif file] and have converted it directly into the Quantum ESPRESSO input file using &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwiCw7CWoLTtAhUW9XMBHULwCm4QFjABegQIAxAC&amp;amp;url=https%3A%2F%2Fpypi.org%2Fproject%2Fcif2cell%2F&amp;amp;usg=AOvVaw0LroaZz4aACzO91h-3J45N&quot; rel=&quot;noreferrer&quot;&gt;cif2cell&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Picture 1&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oRcMQ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oRcMQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;input file 1&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './outdir'&#xA;  verbosity = 'low'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =    7.02663&#xA;  nat = 10&#xA;  ntyp = 3&#xA;  ecutwfc = 55&#xA;  ecutrho = 650&#xA;  nspin = 2&#xA;  starting_magnetization(1) = 1&#xA;  starting_magnetization(2) = 0&#xA;  starting_magnetization(3) = 0&#xA;&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss = 0.005d0      &#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1e-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  0.866025403784439  -0.500000000000000   0.000000000000000 &#xA;  0.000000000000000   1.000000000000000   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   0.857028191323579 &#xA;ATOMIC_SPECIES&#xA;  V    50.94150  V.pbe-spnl-kjpaw_psl.1.0.0.UPF&#xA;  Ba   137.32700 Ba.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;  Se   78.96000  Se.pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA;  Ba   0.333333333333333   0.666666666666667   0.250000000000000 &#xA;  Ba   0.666666666666667   0.333333333333333   0.750000000000000 &#xA;  Se   0.833430000000000   0.666666666666667   0.250000000000000 &#xA;  Se   0.833236666666667   0.166570000000000   0.250000000000000 &#xA;  Se   0.166570000000000   0.833236666666667   0.750000000000000 &#xA;  Se   0.333333333333333   0.166763333333333   0.250000000000000 &#xA;  Se   0.166763333333333   0.333333333333333   0.750000000000000 &#xA;  Se   0.666666666666667   0.833430000000000   0.750000000000000 &#xA;  V   0.000000000000000   0.000000000000000   0.000000000000000 &#xA;  V   0.000000000000000   0.000000000000000   0.500000000000000 &#xA;K_POINTS {automatic}&#xA;  17 17 17 0 0 0&#xA;      &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Picture 2&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kUG0I.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kUG0I.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;CIF file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# CIF file created by FINDSYM, version 7.1&#xA;&#xA;data_findsym-output&#xA;_audit_creation_method FINDSYM&#xA;_cod_database_code               None&#xA;_cell_length_a    7.0266300000&#xA;_cell_length_b    7.0266300000&#xA;_cell_length_c    6.0220200000&#xA;_cell_angle_alpha 90.0000000000&#xA;_cell_angle_beta  90.0000000000&#xA;_cell_angle_gamma 120.0000000000&#xA;_cell_volume      257.4939303923&#xA;&#xA;_symmetry_space_group_name_H-M &amp;quot;P 63/m 2/m 2/c&amp;quot;&#xA;_symmetry_Int_Tables_number 194&#xA;_space_group.reference_setting '194:-P 6c 2c'&#xA;_space_group.transform_Pp_abc a,b,c;0,0,0&#xA;&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 x,y,z&#xA;2 x-y,x,z+1/2&#xA;3 -y,x-y,z&#xA;4 -x,-y,z+1/2&#xA;5 -x+y,-x,z&#xA;6 y,-x+y,z+1/2&#xA;7 x-y,-y,-z&#xA;8 x,x-y,-z+1/2&#xA;9 y,x,-z&#xA;10 -x+y,y,-z+1/2&#xA;11 -x,-x+y,-z&#xA;12 -y,-x,-z+1/2&#xA;13 -x,-y,-z&#xA;14 -x+y,-x,-z+1/2&#xA;15 y,-x+y,-z&#xA;16 x,y,-z+1/2&#xA;17 x-y,x,-z&#xA;18 -y,x-y,-z+1/2&#xA;19 -x+y,y,z&#xA;20 -x,-x+y,z+1/2&#xA;21 -y,-x,z&#xA;22 x-y,-y,z+1/2&#xA;23 x,x-y,z&#xA;24 y,x,z+1/2&#xA;&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_label&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_occupancy&#xA;_atom_site_fract_symmform&#xA;Ba1 Ba   2 c 0.33333 0.66667 0.25000 1.00000 0,0,0    &#xA;V1  V    2 a 0.00000 0.00000 0.00000 1.00000 0,0,0    &#xA;Se1 Se   6 h 0.83343 0.66686 0.25000 1.00000 Dx,2Dx,0 &#xA;&#xA;# end of cif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2020-12-04T11:50:09.873" LastActivityDate="2021-01-20T20:24:58.330" Title="Is the &quot;Final Magnetic moment&quot; in the materials project repository same as the &quot;total magnetization&quot; value in Quantum ESPRESSO output files?" Tags="|density-functional-theory|quantum-espresso|magnetism|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3873" PostTypeId="2" ParentId="3543" CreationDate="2020-12-04T12:21:53.890" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;But in order to do that I need the exchange matrix of Co-CoO system&#xA;which should include the constant which represents the interaction&#xA;between spins in the Co part, spins in the CoO part and a constant&#xA;representing the interaction of spins in the Co-CoO interface.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The Co-CoO (FM- AFM) interfacial exchange energy can be taken to be equal to the exchange coefficient of the Bulk Ferromagnetic layer. This is based on what is being specified on &lt;a href=&quot;https://vampire.york.ac.uk/tutorials/bilayer-system-generation/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VAMPIRE's tutorial on bilayered systems&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Information from VAMPIRE&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The exchange between the two materials (the interfacial exchange) is&#xA;defined as a ferromagnetic interaction with the same strength as the&#xA;bulk. Note that the interaction strength from material 1 to 2 must be&#xA;the same as from material 2 to 1.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is for a bilayered system. But for a core-shell system, the following input file and material file can be used.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;create:crystal-structure = fcc &#xA;create:sphere &#xA;dimensions:unit-cell-size = 3.524 !A &#xA;dimensions:system-size-x = 11.0 !nm &#xA;dimensions:system-size-y = 11.0 !nm &#xA;dimensions:system-size-z = 11.0 !nm &#xA;dimensions:particle-size = 11.0.0 !nm &#xA;material:file = Co.mat &#xA;sim:temperature = 300.0 &#xA;sim:minimum-temperature=0 &#xA;sim:maximum-temperature=2000 &#xA;sim:temperature-increment=10 &#xA;sim:time-steps-increment=1 &#xA;sim:equilibration-time-steps:1000 &#xA;sim:loop-time-steps=1000 &#xA;sim:program = curie-temperature &#xA;sim:integrator =monte-carlo &#xA;output:real-time &#xA;output:temperature &#xA;output:magnetisation &#xA;output:magnetisation-length &#xA;output:mean-magnetisation-length &#xA;screen:temperature &#xA;screen:mean-magnetisation-length &#xA;config:atoms &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Material file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;materials:num-materials=2 &#xA;# The shell&#xA;material[1]:material-name = &amp;quot;AFM&amp;quot; &#xA;material[1]:material-element = &amp;quot;Co&amp;quot;   &#xA;material[1]:exchange-matrix[1] = -4.27e-22    &#xA;material[1]:exchange-matrix[2] = 5.75e-21 &#xA;material[1]:atomic-spin-moment = 2.55 !muB    &#xA;material[1]:damping-constant = 1.0    &#xA;material[1]:uniaxial-anisotropy-constant = 6.96e-24 &#xA;# The core  &#xA;material[2]:material-name = &amp;quot;FM&amp;quot;  &#xA;material[2]:material-element = &amp;quot;O&amp;quot; &#xA;material[2]:exchange-matrix[1] = 5.75e-21 &#xA;material[2]:exchange-matrix[2] = 5.75e-21 &#xA;material[2]:atomic-spin-moment = 1.59 !muB    &#xA;material[2]:damping-constant = 1.0    &#xA;material[2]:uniaxial-anisotropy-constant = 2.98e-24   &#xA;material[1]:core-shell-size = 1.0 &#xA;material[2]:core-shell-size = 0.90909  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For more files, you can look at this &lt;a href=&quot;https://github.com/AnoopANair/CoO-Co-Coreshell-results-and-code&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github repo&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-12-04T12:21:53.890" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3874" PostTypeId="1" AcceptedAnswerId="3879" CreationDate="2020-12-04T17:34:42.353" Score="25" ViewCount="2308" Body="&lt;p&gt;My background is mostly in (applied) math with healthy doses of physics and computer science. Are there any good introductions to protein folding and its challenges for someone with that kind of quantitative background but very little knowledge of biology, chemistry, etcetera?&lt;/p&gt;&#xA;" OwnerUserId="1638" LastEditorUserId="5" LastEditDate="2020-12-07T00:57:39.313" LastActivityDate="2021-12-15T15:22:12.993" Title="Introduction to protein folding for mathematicians" Tags="|reference-request|mathematical-modeling|proteins|structural-biology|protein-folding|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3875" PostTypeId="2" ParentId="3874" CreationDate="2020-12-04T18:08:35.060" Score="12" Body="&lt;p&gt;Someone more familiar with the problem might have a better suggestion, but I recently came across &lt;a href=&quot;https://people.math.sc.edu/dix/&quot; rel=&quot;noreferrer&quot;&gt;Daniel B. Dix'&lt;/a&gt; notes on &lt;a href=&quot;https://people.math.sc.edu/dix/fold.pdf&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Mathematical Models of Protein Folding&lt;/em&gt;&lt;/a&gt;. This is not my field, so I won't guarantee correctness. However, to a layman at least, these notes seem well suited for someone with your background. The abstract reads&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We present an elementary introduction to the protein folding problem directed&#xA;toward applied mathematicians. We do not assume any prior knowledge of statistical mechanics or of protein chemistry. Our goal is to show that as well as being an extremely important&#xA;physical, chemical, and biological problem, protein folding can also be precisely formulated as&#xA;a set of mathematics problems. We state several problems related to protein folding and give&#xA;precise definitions of the quantities involved. We also attempt to give physical derivations&#xA;justifying our model.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-12-04T18:08:35.060" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3876" PostTypeId="2" ParentId="1947" CreationDate="2020-12-04T18:19:16.757" Score="4" Body="&lt;p&gt;The main issue here is not about the type of ligands (glycans) even when it is known that there are force fields that are specific for each type of system. The main issue is about how flexible and big is the ligand you are using to dock.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.schrodinger.com/glide&quot; rel=&quot;nofollow noreferrer&quot;&gt;GLIDE&lt;/a&gt; software, for example, has been increasing the number of atoms and rotatable bonds it is able to handle. Since 2015-1 release, it can handle ligands with up to 500 atoms and 100 rotatable bonds (versus 300 and 50 in previous releases).&lt;/p&gt;&#xA;&lt;p&gt;In case of &lt;a href=&quot;http://vina.scripps.edu/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;AutodockVina&lt;/a&gt; software, the default values are 2048 atoms and 32 torsions, but these values can be changed in the variables MAX_ATOMS and MAX_TORS in the constants.h.&lt;/p&gt;&#xA;&lt;p&gt;There are some webservers for docking, but I am not aware of their limitations. Some of them are &lt;a href=&quot;http://www.swissdock.ch/pages/soap_access&quot; rel=&quot;nofollow noreferrer&quot;&gt;SwissDock&lt;/a&gt;, &lt;a href=&quot;https://durrantlab.pitt.edu/webina/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Webmina&lt;/a&gt;, &lt;a href=&quot;http://blaster.docking.org/start.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;DockBlaster&lt;/a&gt;, and &lt;a href=&quot;https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::MTiAutoDock&quot; rel=&quot;nofollow noreferrer&quot;&gt;MTiAutoDock&lt;/a&gt; 1.0, among others.&lt;/p&gt;&#xA;&lt;p&gt;If this software aren't able to treat your system, you can use a different method to study the interactions between the proteins and glycans, ex. semiempirical software &lt;a href=&quot;http://openmopac.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOPAC&lt;/a&gt; using &lt;a href=&quot;http://openmopac.net/manual/mozyme.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOZYME&lt;/a&gt; keyword, Fragment Molecular Orbital inside GAMESS-US or go directly to molecular dynamics.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-12-04T18:19:16.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3877" PostTypeId="2" ParentId="3821" CreationDate="2020-12-04T18:20:51.017" Score="6" Body="&lt;p&gt;There is no guaranteed increase in performance if you specify a non-zero value for ibrav. There is an additional layer to this - Whether the atomic positions are specified in cartesian or crystal coordinates (sometimes some symmetries can be missed out on QE). On both points, you would need to run a test calculation and see how many symmetries QE detects. This is mentioned in the output file after some data about the system and the K points. If all the symmetries you expect to be detected are found to be QE, it will greatly reduce the computational cost of the calculation.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2020-12-04T18:20:51.017" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3878" PostTypeId="1" CreationDate="2020-12-04T23:31:41.903" Score="8" ViewCount="617" Body="&lt;p&gt;The structure was created using Stillinger Weber with LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;The command I used was the following:&#xA;&lt;code&gt;mpiexec -np $PBS_NP --machinefile $PBS_NODEFILE /opt/spack/opt/spack/linux-centos7-x86_64/intel-18.0.2/cp2k-develop-fw3esv3ywfndzwchh6qphm4nfp253aco/bin/cp2k.popt -o cp2kMD.out silicon64.inp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can the Hamiltonian be nonconvex?&lt;/p&gt;&#xA;&lt;p&gt;Here is the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@SET SYSTEM silicon8&#xA;@SET LIBDIR ~/cp2k&#xA;&#xA;&#xA;&amp;amp;GLOBAL&#xA;  PROJECT ${SYSTEM}&#xA;  RUN_TYPE ENERGY&#xA;  PRINT_LEVEL MEDIUM&#xA;&amp;amp;END GLOBAL&#xA;&amp;amp;FORCE_EVAL&#xA;  METHOD Quickstep&#xA;  STRESS_TENSOR ANALYTICAL&#xA;  &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME ~/abtstSi/cp2kmd/PBE/BASIS_SET&#xA;    POTENTIAL_FILE_NAME ~/abtstSi/cp2kmd/PBE/GTH_POTENTIALS&#xA;    &amp;amp;POISSON&#xA;      PERIODIC XYZ&#xA;    &amp;amp;END POISSON&#xA;    &amp;amp;SCF&#xA;      SCF_GUESS ATOMIC&#xA;      EPS_SCF 1.0E-8&#xA;      MAX_SCF 500&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;KIND Si&#xA;      ELEMENT   Si&#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;CELL&#xA;      ABC 7.68 10.86116 15.36&#xA;      ALPHA_BETA_GAMMA  90.0 90.0 90.0&#xA;      PERIODIC XYZ&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;COORD&#xA;Si 7.05927 6.64266 5.37576&#xA;Si 1.76237 9.252659999999999 5.21654&#xA;Si 1.22129 10.0626 10.6935&#xA;Si 2.6313200000000005 1.9667599999999998 12.6966&#xA;Si 6.8577 8.98551 4.63333&#xA;Si 1.83598 3.60553 7.161880000000001&#xA;Si 7.35508 0.528038 5.59927&#xA;Si 3.9881700000000007 9.96088 0.6837730000000001&#xA;Si 1.8054 0.803562 4.11245&#xA;Si 7.63652 2.6251399999999996 0.546681&#xA;Si 1.08848 0.709195 1.7654&#xA;Si 0.7939940000000001 7.6549499999999995 11.3353&#xA;Si 0.123084 0.9485609999999999 9.42303&#xA;Si 6.44041 2.60145 4.83899&#xA;Si 1.42496 4.16918 15.2986&#xA;Si 4.4713 7.25779 12.83&#xA;Si 2.46468 7.359639999999999 14.24&#xA;Si 6.9968 1.29906 14.058600000000002&#xA;Si 6.08778 10.2214 15.0148&#xA;Si 3.5213200000000002 4.75244 9.93462&#xA;Si 1.8154100000000002 3.8253399999999997 11.5148&#xA;Si 5.65175 4.03603 6.687490000000001&#xA;Si 7.52268 7.27055 0.699091&#xA;Si 4.51691 2.88637 2.9541&#xA;Si 3.3048 7.84857 4.20158&#xA;Si 7.156880000000001 9.50139 1.82017&#xA;Si 7.43061 3.1365499999999997 10.5857&#xA;Si 1.0672 5.350579999999999 13.299500000000002&#xA;Si 5.28622 9.39642 12.561000000000002&#xA;Si 1.1846200000000002 0.18134899999999998 12.9538&#xA;Si 3.1005 5.90203 7.56032&#xA;Si 6.701040000000001 10.0717 7.5551&#xA;Si 5.76607 5.066889999999999 11.0669&#xA;Si 4.519260000000001 6.08691 5.54111&#xA;Si 3.41978 7.47243 1.41607&#xA;Si 4.1169 0.37773099999999993 11.3865&#xA;Si 5.632110000000001 2.36772 12.2505&#xA;Si 4.60556 7.57004 8.80234&#xA;Si 3.19236 4.68417 3.79859&#xA;Si 3.38263 1.45833 1.21872&#xA;Si 1.4199 1.16354 7.33426&#xA;Si 3.31172 2.83036 14.804700000000002&#xA;Si 6.33074 3.99995 2.03448&#xA;Si 4.865850000000001 9.68236 3.13388&#xA;Si 7.478370000000001 4.1583 8.27792&#xA;Si 4.263060000000001 0.7377769999999999 4.33558&#xA;Si 0.7445280000000001 6.71793 7.63183&#xA;Si 1.7130400000000001 5.84304 1.83262&#xA;Si 4.86432 8.66803 6.547920000000001&#xA;Si 3.16261 6.99151 10.881300000000001&#xA;Si 7.483300000000001 8.274009999999999 13.7653&#xA;Si 6.364810000000001 9.18195 10.1728&#xA;Si 0.0874567 4.91559 3.78355&#xA;Si 6.81633 6.657199999999999 9.667010000000001&#xA;Si 1.46051 3.19541 4.84721&#xA;Si 1.2459 9.04408 7.58636&#xA;Si 6.28422 5.63362 13.235&#xA;Si 5.39731 3.9856199999999995 14.5655&#xA;Si 5.41372 6.109999999999999 0.813683&#xA;Si 4.09035 2.86163 8.28733&#xA;Si 1.7804 9.85183 15.001300000000002&#xA;Si 3.10574 9.46592 9.22525&#xA;Si 4.91753 0.752929 9.04135&#xA;Si 3.5791200000000005 0.0752674 6.74137&#xA;    &amp;amp;END COORD&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The following is the CP2K output&lt;/p&gt;&#xA;&lt;p&gt;I can't include all the output but the following is the SCF part:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   497 P_Mix/Diag. 0.40E+00    1.4   576.42755204        63.8866362031  4.07E+00&#xA;   498 P_Mix/Diag. 0.40E+00    1.4   628.09173001        53.9808222782 -9.91E+00&#xA;   499 P_Mix/Diag. 0.40E+00    1.4   976.73936963        69.7309890316  1.58E+01&#xA;   500 P_Mix/Diag. 0.40E+00    1.4  1278.54363778        52.4883144534 -1.72E+01&#xA;&#xA;  Leaving inner SCF loop after reaching   500 steps.&#xA;&#xA;&#xA;  Electronic density on regular grids:       -255.9999999043        0.0000000957&#xA;  Core density on regular grids:              255.9999999562       -0.0000000438&#xA;  Total charge density on r-space grids:        0.0000000520&#xA;  Total charge density g-space grids:           0.0000000520&#xA;&#xA;  Overlap energy of the core charge distribution:               0.00000000021129&#xA;  Self energy of the core charge distribution:               -656.51151540102558&#xA;  Core Hamiltonian energy:                                    290.84105129210911&#xA;  Hartree energy:                                             501.21656005088914&#xA;  Exchange-correlation energy:                                -83.05778148873662&#xA;&#xA;  Total energy:                                                52.48831445344740&#xA;&#xA; *** WARNING in qs_scf.F:542 :: SCF run NOT converged ***&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1653" LastEditorUserId="85" LastEditDate="2020-12-08T12:15:35.393" LastActivityDate="2020-12-08T22:15:31.677" Title="Failure of CP2K density functional software to converge for a 64 Si atom amorphous structure" Tags="|density-functional-theory|numerical-convergence|cp2k|amorphous-materials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3879" PostTypeId="2" ParentId="3874" CreationDate="2020-12-05T03:23:23.203" Score="18" Body="&lt;p&gt;Great question! Protein folding has been in open question for decades. Just recently, there's been a lot of discussion regarding DeepMind's &lt;a href=&quot;https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology&quot; rel=&quot;nofollow noreferrer&quot;&gt;AlphaFold project&lt;/a&gt;, which was &lt;em&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3849/5&quot;&gt;discussed at length on our very own site here&lt;/a&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My answer will be complementary to the one above, but the references I will provide will be closer to the &lt;em&gt;physics&lt;/em&gt; side of the problem.&lt;/p&gt;&#xA;&lt;p&gt;First thing's first, what you should be studying is &lt;em&gt;Statistical Mechanics&lt;/em&gt; both in and out of equilibrium. How deep you want to dive into Statistical Mechanics will depend on your research interests or requirements.&lt;/p&gt;&#xA;&lt;p&gt;As an introduction, a text that would be suitable for you should also be suitable for a biochemist wanting to come to the quantitative side. A &amp;quot;meet halfway&amp;quot; book.&lt;/p&gt;&#xA;&lt;p&gt;This is it:&#xA;&lt;em&gt;&amp;quot;&lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0815344309&quot; rel=&quot;nofollow noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience&lt;/a&gt;&amp;quot;&lt;/em&gt;&#xA;by Ken A. Dill and Sarina Bromberg&lt;/p&gt;&#xA;&lt;p&gt;If you've had &lt;em&gt;healthy doses of physics&lt;/em&gt;, this book is a great introduction to basic statistical physics, thermodynamics and biophysics. I definitely recommend it. The problems are not difficult and facilitate the development of the needed physical intuition.&lt;/p&gt;&#xA;&lt;p&gt;The author, Ken Dill is well-known for his contributions in this field. One of his most cited papers is: &amp;quot;&lt;a href=&quot;https://doi.org/10.1021/ma00200a030&quot; rel=&quot;nofollow noreferrer&quot;&gt;A lattice statistical mechanics model of the conformational and sequence spaces of proteins&lt;/a&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;An alternative text on this subject is Lectures on &lt;a href=&quot;https://www.worldscientific.com/worldscibooks/10.1142/5741&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;&amp;quot;Statistical Physics and Protein Folding&amp;quot;&lt;/em&gt;&lt;/a&gt;, by Kerson Huang, late professor emeritus at MIT.&lt;/p&gt;&#xA;&lt;p&gt;Depending on how much Statistical Mechanics you want to learn, I would also recommend David Chandler's &amp;quot;Introduction to Modern Statistical Mechanics&amp;quot; as a supporting text. Other classics are great too.&lt;/p&gt;&#xA;&lt;p&gt;A great amount of literature is around, some focusing even on &lt;a href=&quot;https://www.pnas.org/content/116/19/9360&quot; rel=&quot;nofollow noreferrer&quot;&gt;topolgy in protein folding&lt;/a&gt;, others more focused on the computational-bio aspect, but I think these are the &lt;em&gt;basics&lt;/em&gt; from the physics side.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully a good start!&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="175" LastEditDate="2020-12-14T08:44:47.457" LastActivityDate="2020-12-14T08:44:47.457" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3880" PostTypeId="1" AcceptedAnswerId="3885" CreationDate="2020-12-05T10:42:20.177" Score="10" ViewCount="349" Body="&lt;p&gt;My field of research is computational materials science/mechanics. My work is on the &amp;quot;numerical modeling of shot peening process&amp;quot;. This is a typical &lt;a href=&quot;https://doi.org/10.1016/j.surfcoat.2019.125247&quot; rel=&quot;nofollow noreferrer&quot;&gt;publication&lt;/a&gt; in my field. My work is not very numerically intensive and is application based. I implemented a damage model in Finite element analysis.&lt;/p&gt;&#xA;&lt;p&gt;Now, whenever I submit my work to computationally intensive journal like &lt;a href=&quot;https://www.journals.elsevier.com/computational-materials-science&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Materials Science&lt;/a&gt;, it gets desk rejected citing &amp;quot;beyond the scope of the journal&amp;quot; as the reason for rejection.&lt;/p&gt;&#xA;&lt;p&gt;However, when I submit to applied journals like &lt;a href=&quot;https://www.journals.elsevier.com/surface-and-coatings-technology&quot; rel=&quot;nofollow noreferrer&quot;&gt;Surface and Coatings Technology&lt;/a&gt; and &lt;a href=&quot;https://www.springer.com/journal/11666&quot; rel=&quot;nofollow noreferrer&quot;&gt;Journal of Thermal Spray Technology&lt;/a&gt;, it gets accepted without much review. I just get few minor questions and it gets accepted.&lt;/p&gt;&#xA;&lt;p&gt;Typical review comments involve:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;generic questions about the modeling technique used (mesh size, boundary conditions, constitutive equations used), which are more of clarifications rather than any deep questions.&lt;/li&gt;&#xA;&lt;li&gt;Comment about adding a figure or a simple explanation for a statement in the paper.&lt;/li&gt;&#xA;&lt;li&gt;Question about the future work and implications on real life application.&lt;/li&gt;&#xA;&lt;li&gt;Rest are about typos in the manuscript.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Is the low level of review questions a reflection on the quality of the journal? Am I submitting my papers to wrong journals?&lt;/p&gt;&#xA;&lt;p&gt;Papers similar to my work are published in the journals mentioned.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note: my question got &lt;a href=&quot;https://academia.stackexchange.com/questions/159671/my-publications-are-always-accepted-without-much-review-in-the-journal-is-that&quot;&gt;deleted at Academia.SE&lt;/a&gt; so that is why I hoped it could be welcomed here.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1655" LastEditorUserId="5" LastEditDate="2020-12-06T17:04:08.550" LastActivityDate="2020-12-09T15:11:02.443" Title="Why are my publications getting accepted without much review from some journals, but getting rejected by the journal Computational Materials Science?" Tags="|physical-properties-of-materials|finite-element-analysis|publishing|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3881" PostTypeId="1" AcceptedAnswerId="4081" CreationDate="2020-12-05T14:12:04.640" Score="12" ViewCount="192" Body="&lt;p&gt;&lt;a href=&quot;https://cmr.fysik.dtu.dk/c2db/c2db.html#c2db&quot; rel=&quot;noreferrer&quot;&gt;Computational 2D Materials Database (C2DB)&lt;/a&gt;, &lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/dashboard/ptable&quot; rel=&quot;noreferrer&quot;&gt;2D structures and layered materials&lt;/a&gt;, and &lt;a href=&quot;http://www.2dmatpedia.org/query?collection=2dmaterials&amp;amp;search_string=top-down&quot; rel=&quot;noreferrer&quot;&gt;2D Materials Encyclopedia&lt;/a&gt; are three major databases for two-dimensional materials based on DFT calculation.&lt;/p&gt;&#xA;&lt;p&gt;However, I note that some structures predicted by these two databases are not stable mechanically by the phonon spectrum.&lt;/p&gt;&#xA;&lt;p&gt;For example, the &lt;a href=&quot;https://cmrdb.fysik.dtu.dk/c2db/row/HfS2-2c5e65012601&quot; rel=&quot;noreferrer&quot;&gt;H-phase HfS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/a&gt; is predicted to be stable by C2DB, but the phonon spectrum shows an obvious negative frequency:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O35G9.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O35G9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Similar predictions are conducted by 2D Materials Encyclopedia. For example, the monolayer &lt;a href=&quot;http://www.2dmatpedia.org/2dmaterials/doc/2dm-2497&quot; rel=&quot;noreferrer&quot;&gt;BiI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; with P6m2 symmetry&lt;/a&gt; is predicted while the phonon spectrum display also imaginary frequencies:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AI6IJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AI6IJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;PS: All the shown phonon spectrum are calculated with the VASP+DFPT method and a &lt;span class=&quot;math-container&quot;&gt;$4 \times 4 \times 1$&lt;/span&gt; supercell is adopted.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, how reliable the predicted structures in the 2D materials database? And what's the most believable database for 2D materials?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-12-06T01:55:27.123" LastActivityDate="2021-01-07T16:51:53.197" Title="Reliability about the predicted two-dimensional crystal structures based on DFT high-throughput calculation?" Tags="|density-functional-theory|phonopy|databases|dfpt|high-throughput|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3882" PostTypeId="1" AcceptedAnswerId="4423" CreationDate="2020-12-05T18:08:34.020" Score="9" ViewCount="595" Body="&lt;p&gt;I'm running a series of calculation for nonlinear chromophores. The general pipeline is geometry optimization (B3LYP/def2-TZVP) -&amp;gt; Frequencies -&amp;gt; Hyperpolarizability calculation (M06-2X (or CAM-B3LYP or MP2)/aug-cc-TZVP).&lt;/p&gt;&#xA;&lt;p&gt;At the moment I plan to run Orca for optimization and frequencies because it is faster and GAMESS-US for  hyperpolarizability, but I want to switch to the software that can do both tasks.&lt;/p&gt;&#xA;&lt;p&gt;I can run anything that is free (at least for academia) and can be parallelized. Please help me find a suitable software, I could only think of NWChem/LSDalton (but that's also two separate codes).&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-02-28T05:19:53.887" LastActivityDate="2021-02-28T06:25:16.483" Title="A good software for DFT optimization and nonlinear optical properties" Tags="|density-functional-theory|one-topic-per-answer|software-recommendations|gaussian|optical-properties|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3883" PostTypeId="1" CreationDate="2020-12-05T21:27:22.117" Score="7" ViewCount="195" Body="&lt;p&gt;Gibbs free energy, &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;, for a crystalline solid material could be described as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;G\: =\: H_{T=0}\: +\: H_{T&amp;gt;0}\: +\: \text{ZPE}\: -\: T\cdot S,&#xA;\end{equation}&lt;/span&gt;&#xA;Where &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is enthalpy, ZPE is the zero-point energy and S is entropy (all kinds).&lt;/p&gt;&#xA;&lt;p&gt;Solids (condensed matter might be a better term) are highly incompressible, so their internal energy computed with either empirical potentials or otherwise can be considered equal to their enthalpy. That takes care of the &lt;span class=&quot;math-container&quot;&gt;$H_{T=0}$&lt;/span&gt; term. What about the rest? Can each of them be included in a Thermocalc phase transition study?&lt;/p&gt;&#xA;&lt;p&gt;I haven't explored Thermocalc enough (blame it on VASP!). As far as I know, we make Gibbs free energy equations for a material at various temperature ranges and dump those in a .tdb (database) file. If these other terms are accounted for, please help me understand how, code and theory-wise.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-12-07T02:36:18.733" LastActivityDate="2020-12-07T10:42:22.917" Title="What information about a crystalline solid material goes into calculating phase diagrams in Thermo-Calc, and how?" Tags="|gibbs-free-energy|calphad|thermo-calc|phase-transitions|phase-diagram|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3884" PostTypeId="2" ParentId="1896" CreationDate="2020-12-06T03:16:06.943" Score="7" Body="&lt;p&gt;I do generally follow the follwoing:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Keep basic tags EDIFF, EDIFF to 1E-07 and 1E-06 (or -0.005) generally. i do use defaults if i want to do a faster run just for checking.  and i dont know how can we preempt or know the potential surface is flat or not, as mentioned by Rosen. As in his answer said&amp;quot;...However, if the potential energy surface is flat, this may lead to issues converging the structure to the local minimum because of numerically inaccurate forces.....&amp;quot;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;for KPOINTS i use 30 to 40 times the reciprocal lattice parameter. (Eg.  if a=3, b=4, c=6, then KPOINTS be 40/a, 40/b, 40/c). Not known the origin of such thumb rule !!! :). If its slab, surface or 2D material, then the Z-direction KPOINT will be 1.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;i avoid using any other tags, except ISMEAR, ISYM and run static calculations for ENCUT and KPOINTS convergence.&#xA;Still i face convergence issues.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;but I did not face such issues so far in QE (just a basic learner now)&#xA;Regards&lt;/p&gt;&#xA;" OwnerUserId="1657" LastEditorUserId="5" LastEditDate="2020-12-06T05:11:48.953" LastActivityDate="2020-12-06T05:11:48.953" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3885" PostTypeId="2" ParentId="3880" CreationDate="2020-12-06T06:20:05.763" Score="16" Body="&lt;p&gt;In summary, your papers on the numerical simulations of shot peening processes were rejected by &lt;a href=&quot;https://www.journals.elsevier.com/computational-materials-science&quot; rel=&quot;noreferrer&quot;&gt;Computational Materials Science&lt;/a&gt; but easily got through the review process at &lt;a href=&quot;https://www.journals.elsevier.com/surface-and-coatings-technology&quot; rel=&quot;noreferrer&quot;&gt;Surface and Coatings Technology&lt;/a&gt; and &lt;a href=&quot;https://www.springer.com/journal/11666&quot; rel=&quot;noreferrer&quot;&gt;Journal of Thermal Spray Technology&lt;/a&gt;, and you are wondering:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is the low level of review questions a reflection on the quality of&#xA;the journal? Am I submitting my papers to wrong journals?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;First of all, one of those journals where your papers are getting accepted with ease has a significantly higher impact factor than the journal where your papers are getting rejected (3.8 vs 2.9, which is quite a big difference for journals with this range of impact factors). So it is unlikely that this is a reflection of the quality of the journals, and is more likely a reflection of your choice of journal where you submitted the paper.&lt;/p&gt;&#xA;&lt;p&gt;The two journals that you say are accepting your papers with ease, have very specific titles, and seem to be much more appropriate for your specific area. The journal where your papers are getting rejected (Comptuational Materials Science) has a much more generic name, and therefore might look at first sight like they equally welcome all types of &amp;quot;computational materials science&amp;quot; papers such as your own ones, but upon closer look at the other papers typically published in that journal, they have a much stronger focus on &lt;em&gt;ab initio&lt;/em&gt; quantum-mechanical modeling of materials or molecular dynamics simulations (computational chemistry, quantum chemistry, condensed-matter physics, solid-state physics, etc.) much more than &lt;em&gt;&lt;strong&gt;computational macroscopic materials science&lt;/strong&gt;&lt;/em&gt; which seems to be more of what you are doing (the &amp;quot;typical paper&amp;quot; in your field, which you showed us, is about physical properties of steel in the &amp;quot;macroscopic engineering&amp;quot; setting of aviation engineering). Computational Materials Science is a journal that seems much more aimed at &lt;em&gt;&lt;strong&gt;microscopic modeling of materials&lt;/strong&gt;&lt;/em&gt; even though the title might make it look like it welcomes papers from all areas of computational materials science.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;It usually does no harm to look at some of the papers in the most recent issue of a journal, and even write to the editor an informal inquiry about the suitability of the journal for your paper, before formally submitting the paper, since this can save you the loss of time (and energy and enthusiasm!) associated with having a paper rejected.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-06T15:01:19.970" LastActivityDate="2020-12-06T15:01:19.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3886" PostTypeId="2" ParentId="3874" CreationDate="2020-12-06T20:16:56.887" Score="10" Body="&lt;h3&gt;Preamble&lt;/h3&gt;&#xA;&lt;p&gt;Since I don't know your &lt;em&gt;specific&lt;/em&gt; background, this is a generic answer for any &lt;em&gt;applied mathematician&lt;/em&gt; wishing to enter the field of protein folding. Not everything will apply specifically to you, and please don't feel offended if there's something I assume you don't already know or do!&lt;/p&gt;&#xA;&lt;p&gt;First of all, as a fellow mathematician (I was trained in university as a mathematician and made the switch over to computational chemistry/biochemistry later in life), congratulations on making the first step towards working on (more) real-world problems. One of the first things you might notice will be that work in this field can be much &amp;quot;higher impact&amp;quot;, so your papers may get cited and mentioned in the media much more often than you're accustomed, but also the field can be far more competitive and developing familiarity with how things work here can take some time. While papers in chemistry and biology get more citations (on average) than in applied math, you might still find it equally difficult to find funding because there's more people working in the field. Contrary to many math fields, conference papers are worth almost nothing compared to journal articles, and even arXiv papers can be totally ignored by many departments (when there's so many papers in the field, some people just don't want to spend the time reading things that are not published in refereed journals unless they know the author(s) or the paper was recommended to someone who they trust). While talks in math are often done &amp;quot;at the chalkboard&amp;quot;, talks in computational chemistry are almost always done with a slide-show presentation. &lt;strong&gt;Finally, get used to having to read a larger &lt;em&gt;volume&lt;/em&gt; of papers and learning the skills required to be able to capture the important details &lt;em&gt;efficiently&lt;/em&gt;, as opposed to in applied math where you might be encouraged to read a smaller number of papers but much more slowly.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even more importantly, stop thinking about &amp;quot;existence and uniqueness&amp;quot; for solutions to the relevant differential equations in computational biology, and suppress all temptations to be &amp;quot;overly&amp;quot; rigorous about everything. &lt;em&gt;&lt;strong&gt;Do not&lt;/strong&gt;&lt;/em&gt; tell the reader that your conclusion is only valid on a &amp;quot;simply connected bounded open subset whose boundary is a simple piece-wise &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt; closed curve&amp;quot; and avoid using too much jargon or mathematical symbols (just write &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is between 0 and 1&amp;quot; rather than &lt;span class=&quot;math-container&quot;&gt;$a\in[0,1]$&lt;/span&gt;, the readers are smart enough to know from the context whether or not &amp;quot;between&amp;quot; should be extrapolated to imply &amp;quot;between an including&amp;quot;, and do not say &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\forall x \in \mathbb{R}$&lt;/span&gt;&amp;quot; because any smart reader will assume that &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; is a real number (or a complex number or Hermitian operator for much of quantum-mechanical modeling). &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/55851882#55851882&quot;&gt;Stop worrying about which Banach space you're using&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I already said &amp;quot;Finally...&amp;quot; and &amp;quot;Even more importantly...&amp;quot; so I'm running out of ways to start sentences now, but there's still more advice to give: &lt;strong&gt;Be patient and respectful to others working in the field&lt;/strong&gt; (remember the opening to my answer: I'm not making any assumptions about &lt;em&gt;you&lt;/em&gt;, just giving advice for applied mathematicians in general). There's just so much literature out there (compared to applied math at least), so not everyone will know everything, and everyone will certainly have a different academic history. &lt;em&gt;Many&lt;/em&gt; people will not know as much math as you, but many will in fact surprisingly know even more than you.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h3&gt;Answer&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;This is what I'd recommend for an applied mathematician that has taken a healthy dose of physics and computer science,  but hasn't yet had their booster shots   biology and chemistry &lt;em&gt;to review and renew&lt;/em&gt; their knowledge in these fields:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Actually spend some time to learn the very basics of biochemistry, rather than trying to use mathematics to model something for which high school (and some primary school students) these days know more than you. For protein folding, this simply means to learn the answer to:&lt;/li&gt;&#xA;&lt;li&gt;Which elements are found in proteins (most of biology has H,C,O,N, but proteins differ from nucleic acids in that proteins have S and nucleic acids have P)?&lt;/li&gt;&#xA;&lt;li&gt;What is a &amp;quot;functional group&amp;quot;, in particular: amino group and carboxyl group?&lt;/li&gt;&#xA;&lt;li&gt;What is an amino acid, peptide bond, dipeptide, polypepdide, polypeptide chain, and finally: &lt;strong&gt;protein&lt;/strong&gt;?&lt;/li&gt;&#xA;&lt;li&gt;What is electronegativity and electropositivity? What is a hydrogen bond? How does a hydrogen bond work. What are Van der Waals forces? Why do hydrophobic and hydrophilic mean? What are steric interactions?&lt;/li&gt;&#xA;&lt;li&gt;What is primary/secondary/tertiary/quaternary structure in the context of proteins? What is a structural motif? What is an alpha helix, beta sheet, and disulfide bridge?&lt;/li&gt;&#xA;&lt;li&gt;What is a Ramachandran plot?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The above could be covered in a 1-week crash course. Email me at nike@hpqc.org if you think there would be enough interest for me to organize one.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Now for some of the techniques and theory:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_dynamics&quot; rel=&quot;noreferrer&quot;&gt;Molecular dynamics&lt;/a&gt; is just Newton's 2nd law applied to a large number of particles, and is implemented in a lot of open source software.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Statistical_mechanics&quot; rel=&quot;noreferrer&quot;&gt;Statistical mechanics&lt;/a&gt; is what &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3879/5&quot;&gt;Etienne's answer&lt;/a&gt; discusses, but you don't have to learn everything or read that whole textbook. Just review Gibbs free energy, Boltzman distributions, and things such as &lt;span class=&quot;math-container&quot;&gt;$e^{-\beta H}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Contrary to what some people might tell you, quantum mechanics can almost entirely be avoided for protein folding simulations, but do review the concept of a classical potential energy surface, and a classical Hamiltonian. Many people forcefully interject quantum mechanics into computational chemistry that can avoid quantum mechanics, largely because their area of expertise is in the quantum realm and they want to try to raise the impact of their work. It's true that quantum mechanics is absolutely essential for understanding most of molecular structure and how the potential energy surfaces used are actually calculated, using what is colloquially known as &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_chemistry&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;quantum chemistry&amp;quot; or &amp;quot;electronic structure theory&amp;quot;&lt;/a&gt;, however a beginner applied mathematician trying to take their first steps in protein folding, might wish to just use potential energy surfaces that comes from X-ray experiments or from other people's &lt;em&gt;ab initio&lt;/em&gt; calculations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The above could also be covered in a 1-week crash course. Email me at nike@hpqc.org if you think there would be enough interest for me to organize one.&lt;/p&gt;&#xA;&lt;p&gt;Now you might want to read some seminal papers on the topic of protein folding, to get an idea of &lt;em&gt;what has already been done&lt;/em&gt;. There's too many papers, but some papers by certain authors have such titles and citation counts that you might not want to miss them, for example (others can feel free to add more lines if I have missed anyone):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scholar.google.com/citations?user=hd1j2w0AAAAJ&amp;amp;hl=en&amp;amp;oi=ao&quot; rel=&quot;noreferrer&quot;&gt;Peter Wolnyes&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scholar.google.com/citations?hl=en&amp;amp;user=k7vghtEAAAAJ&amp;amp;view_op=list_works&quot; rel=&quot;noreferrer&quot;&gt;Klaus Schulten&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-12-06T20:16:56.887" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3887" PostTypeId="1" AcceptedAnswerId="3888" CreationDate="2020-12-07T00:12:33.340" Score="18" ViewCount="949" Body="&lt;p&gt;(1) Commonly, the metal is at the active site which needs the most prediction precision.&lt;/p&gt;&#xA;&lt;p&gt;(2) Typically, there is only one (or a few) metals in a protein, which contains far more other atoms. So, the structural data that could be used to train AlphaFold could contain far less information about the metal elements.&lt;/p&gt;&#xA;&lt;p&gt;(3) The more complex electron shell of metal atoms also makes the data less useful, since its bonding pattern is more flexible than carbon, etc.&lt;/p&gt;&#xA;&lt;p&gt;(4) Most proteins don't have metals at all.&lt;/p&gt;&#xA;&lt;p&gt;Given that maybe there is not enough structural data about protein local structure around metal atoms, then AlphaFold cannot predict local structure around metals well. Is that right?&lt;/p&gt;&#xA;&lt;p&gt;Note: Most the structure far away from the metal could be not affected very much by the metal, the local structure around the metal is the concern.&lt;/p&gt;&#xA;" OwnerUserId="1663" LastEditorUserId="5" LastEditDate="2020-12-07T21:22:29.870" LastActivityDate="2020-12-07T21:22:29.870" Title="Does DeepMind's new protein folding software (AlphaFold) also work well for metalloproteins (proteins with metal cofactors)?" Tags="|transition-metals|proteins|machine-learning|metal-complexes|protein-folding|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3888" PostTypeId="2" ParentId="3887" CreationDate="2020-12-07T00:54:06.370" Score="17" Body="&lt;p&gt;It's a great question! Some of my answer will be taken from my &lt;a href=&quot;https://ai.stackexchange.com/a/25031/19524&quot;&gt;answer to your question on the AI stack exchange&lt;/a&gt;, but &lt;a href=&quot;https://meta.stackexchange.com/a/4712/391772&quot;&gt;cross-site questions are allowed&lt;/a&gt; and your question here is slightly different so my answer is slightly different.  I'll address your points in reverse chronological order:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(4) Most proteins don't have metals at all.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://authors.library.caltech.edu/25052/1/BioinCh.pdf&quot; rel=&quot;noreferrer&quot;&gt;It was estimated in 1999&lt;/a&gt; that about 50% of all proteins are metalloproteins, and &lt;a href=&quot;https://www.nature.com/articles/nrmicro2057&quot; rel=&quot;noreferrer&quot;&gt;in 2009&lt;/a&gt; that at least 25% of all proteins are. So quite a lot of proteins are in fact metalloproteins. Maybe not &amp;quot;most&amp;quot; of them, but certainly enough to use as training data for the purposes of what AlphaFold has done so far.&lt;/p&gt;&#xA;&lt;p&gt;Also it's not exactly the protein itself that has the metal in metalloproteins, since naturally occurring amino acids that we know so far, do not have metals. Instead, the metal is contained in a co-factor, which is separate from the protein but plays an important role nonetheless.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(3) The more complex electron shell of metal atoms also makes the data less useful, since its bonding pattern is more flexible than carbon, etc.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It is true that metals are typically harder to model than C,H,O,N,S, if doing &lt;em&gt;ab initio&lt;/em&gt; calculations on the metals or &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/tagged/metal-complexes&quot;&gt;metal-containing complexes&lt;/a&gt;. However the purpose of machine learning in protein folding studies, is to skip &lt;em&gt;ab initio&lt;/em&gt;, statistical-dynamical and/or molecular-dynamical calculations of the relevant structures and simply use training data to predict the protein structures. Therefore, while solving the many-electron Schroedinger equation typically has a cost that scales exponentially with respect to the number of electrons, it is not true when using a neural network (for example) to &amp;quot;learn&amp;quot; patterns in the solutions to the Schroedinger equation and regurgitate them with cost that scale only linearly.&lt;/p&gt;&#xA;&lt;p&gt;That being said, there needs to be enough training data available (as you correctly pointed out) to learn what happens near the metal co-factors: The answer to this is that there's indeed enough metalloproteins to sufficiently populate a training set, but they won't always contain enough of the specific metals involved in every metalloprotein. For example lots of data will be available for proteins containing Fe since Fe is in hemoglobin (for example) which is essential to the functioning of red blood cells to absorb oxygen; but the protein &lt;a href=&quot;https://en.wikipedia.org/wiki/Vanabins&quot; rel=&quot;noreferrer&quot;&gt;vanabins&lt;/a&gt; contains vanadium which is much more rare and therefore training data involving it will be much less available. You're also correct that metal elements can form more bonds than typical elements found in organic compounds.&lt;/p&gt;&#xA;&lt;p&gt;So it depends on the metal in the relevant co-factor. Fe-based co-factors will have quite a lot of training data available, as will Mg-based ones, Zn-based ones, and a lot of other ones which contain the &amp;quot;more common&amp;quot; metals. For proteins like vanabins which contains vanadium, you are quite correct that training data will be limited, but also keep in mind that vanabins is a very rare protein found in &lt;a href=&quot;https://en.wikipedia.org/wiki/Ascidiacea&quot; rel=&quot;noreferrer&quot;&gt;sea squirts&lt;/a&gt; and we already know more about its structure (through X-ray crystallography, which means we don't need machine learning for it) than we even know about what it even does. The chances of other vanadium-containing co-factors in metalloproteins being very significant is too low to justify working on protein folding algorithms specifically for them.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(2) Typically, there is only one (or a few) metals in a protein, which contains far more other atoms. So, the structural data that could be used to train AlphaFold could contain far less information about the metal elements.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That's true, but molecular dynamics simulations can be done on billions of other systems that contain metal elements (and X-ray crystallography structures, or other experimental structures), to generate training sets that could help with this. &lt;strong&gt;Training the neural network to learn about the effects of metals on molecular structure, can be done on plenty of other systems that contain proteins, not just metalloproteins.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Remember though that AlphaFold is for the most part a &amp;quot;proprietary&amp;quot; software written by DeepMind which is owned by a for-profit company, and while there's some information available about AlphaFold, we don't know everything about what went into AlphaFold. I would guess that they didn't actually train their machine learning systems to understand how metals work in the settings of non-proteins. I would guess that this level of sophistication wasn't needed for the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3851/5&quot;&gt;CASP13 and CASP14 competitions in which they participated&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(1) Commonly, the metal is at the active site which needs the most prediction precision.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;While it's true that &amp;quot;commonly the metal is at the active site&amp;quot; as in hemoglobin's binding site for oxygen, it's not true that the active site is the part that needs the most prediction for protein &lt;em&gt;&lt;strong&gt;folding&lt;/strong&gt;&lt;/em&gt; precision: the example again is hemoglobin, where a single substitution of glutamic acid with valine (far from the active site) completely changes the shape of the protein to the extent that people with this mutation are said to have a disease called &amp;quot;sickle cell anemia&amp;quot;. Nevertheless, that is testament to the fact that minor changes in anything (including the presence of a metal-containing co-factor), can cause huge changes to the overall structure, which is probably why such complicated quaternary structures are not likely to be present in CASP competitions just yet (but let's allow someone working more closely in that domain, to answer in better detail about this part).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-07T01:05:42.583" LastActivityDate="2020-12-07T01:05:42.583" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3889" PostTypeId="1" AcceptedAnswerId="3890" CreationDate="2020-12-07T01:17:16.030" Score="12" ViewCount="494" Body="&lt;p&gt;In most textbooks the precise Schrödinger euqation of a molecule is given (and the &amp;quot;beautiful thing&amp;quot; stops here), then born oppenheimer approximation is made, then layers of other approximations are made, the reason behind is to make the modal tractable with contemporary computuing power.&lt;/p&gt;&#xA;&lt;p&gt;But are there examples where none of the major approximations are made at all and a &amp;quot;precise numerical solution&amp;quot; (finite element like? - I'm not sure if QM problems can be solved like this) is made? After a lot of search I never found such examples, I am not even sure they exists.&lt;/p&gt;&#xA;&lt;p&gt;The reason for this curiosity is:&lt;/p&gt;&#xA;&lt;p&gt;(1) It is very amazing if a solution without the major approximations is made and the result is indeed closer to experiment result than the predictios with approximations.&lt;/p&gt;&#xA;&lt;p&gt;(2) Although the cost is very high and &amp;quot;doesn't worth it&amp;quot;, but at least it can be done for one or a few times (in science history), not never. Although QM is verified in almost every experiments, but a direct prediction of molecule properties without any major approximations is more convincing since you witness the rightness of QM in this situation, not just &amp;quot;know it will work but can't try&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;(3) At least it can be done on the most simple molecule, e.g. di-hydrogen molecule (not sure whether this is a trivial case, if so, then more complexer one is considered instead), won't the most powerful computer today give a precise prediction on these simple molecules?&lt;/p&gt;&#xA;&lt;p&gt;Note:&lt;/p&gt;&#xA;&lt;p&gt;A harder version is the relativisic prediction which is based on Dirac's equation. This one make sense on molecule since a lot of precision is lost without relativisic effects. But maybe only heavier elements can show the difference so this is not easy to setup for the computing power today, so it is not a major concern here. An even harder version is based on quantum electrodynamics which is even more amazing but also even more intractable even for the most simlest molecule I guess.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Updated&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;To make the question more clear:&lt;/p&gt;&#xA;&lt;p&gt;(1) The title is changed, the old one may be misleading&lt;/p&gt;&#xA;&lt;p&gt;(2) The focus of OP is the prediction method, not the result, although if a prediction method as described is used, the result should be very precise.&lt;/p&gt;&#xA;&lt;p&gt;(3) The focus of OP is a general prediction of molecule which at least contains two atoms with a few electrons. To be general, it should give the &amp;quot;precise numerical prediction&amp;quot; of both the (multi particle) eigen functions (as listed in the &amp;quot;pure and beautiful&amp;quot; Schrödinger euqation mentioned in OP) and eigen values, not only some parameters (e.g. only eigen value) that can be measured in experiments. Here &amp;quot;precise numerical prediction&amp;quot; means a nemerical method that can get any degree of precision given enough computing effort (OP is not sure whether such method exist which is also a concern of OP).&lt;/p&gt;&#xA;&lt;p&gt;(4) High precision is indeed not very important in OP. For example, some QED or RQM may give some prediction about &amp;quot;some parameters&amp;quot; mentioned in (3) with very high precision, but that is not a &amp;quot;general prediction&amp;quot; as described in (3). OP already mentioned to make such &amp;quot;general prediction&amp;quot; QED and RQM could be out of reach with today's computing power. A &amp;quot;general prediction&amp;quot; based on the multi particle Schrödinger euqation, without all the approximation methods, is very enough.&lt;/p&gt;&#xA;" OwnerUserId="1663" LastEditorUserId="1663" LastEditDate="2020-12-08T10:25:54.367" LastActivityDate="2020-12-08T10:25:54.367" Title="Are there examples of ab initio predictions on small molecules without the &quot;major approximations&quot;?" Tags="|high-performance-computing|quantum-chemistry|numerical-convergence|monte-carlo|high-precision|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3890" PostTypeId="2" ParentId="3889" CreationDate="2020-12-07T02:00:16.267" Score="12" Body="&lt;p&gt;I wrote an &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/555/5&quot;&gt;answer to a similar question&lt;/a&gt; in the past, but focused in that question only on the state-of-the-art ultra-high precision calculations on atoms and the three most common isotopologues of &lt;span class=&quot;math-container&quot;&gt;$\ce{H_2}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I will &lt;em&gt;first&lt;/em&gt; repeat those here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Atomization energy of the H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;35999.582834(11) cm^-1 (present most accurate experiment)&#xA;35999.582820(26) cm^-1 (present most accurate calculation)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://arxiv.org/pdf/1902.09471.pdf&quot; rel=&quot;noreferrer&quot;&gt;here for more info&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Fundamental vibration of the H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4161.16632(18) cm^-1 (present most accurate experiment)&#xA;4161.16612(90) cm^-1 (present most accurate calculation)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://arxiv.org/pdf/1304.6390.pdf&quot; rel=&quot;noreferrer&quot;&gt;here for HD and D&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now I suppose you want to know about molecules with more electrons or more nucleons? Well you came to the right place.&lt;/p&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{HeH^+}$&lt;/span&gt;: 2 electrons, 3-5 nucleons, 2 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4759077&quot; rel=&quot;noreferrer&quot;&gt;A landmark paper&lt;/a&gt; on ultra-high precision &lt;em&gt;ab initio&lt;/em&gt; potentials for &lt;span class=&quot;math-container&quot;&gt;$\ce{HeH^+}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{HeD^+}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{HeT^+}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-00569877&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;ab initio&lt;/em&gt; calculations&lt;/a&gt; on  the first 66 electronic states of &lt;span class=&quot;math-container&quot;&gt;$\ce{HeH^+}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{LiH^+}$&lt;/span&gt;: 3 electrons, 4 nucleons, 2 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4869517&quot; rel=&quot;noreferrer&quot;&gt;Ultra-high precision potentials&lt;/a&gt; using explicitly correlated Gaussians (ECGs).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{Li_2}$&lt;/span&gt;: 6 electrons, 6-8 nucleons, 2 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/2006.16415&quot; rel=&quot;noreferrer&quot;&gt;July 2020 pre-print of a paper&lt;/a&gt; on the &lt;span class=&quot;math-container&quot;&gt;$1^3\Sigma_u^+$&lt;/span&gt; state using Slater-type orbitals.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/Li2/a/r%3D4.1700_Angstroms/summary.pdf&quot; rel=&quot;noreferrer&quot;&gt;AI ENERGIES Database results&lt;/a&gt; results for the same state but even more accurate than the July 2020 paper: aug-cc-pCV7Z calculations at FCI level, accurate to within 0.01 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{BeH}$&lt;/span&gt;: 5 electrons, 9-12 nucleons, 2 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1408.3301&quot; rel=&quot;noreferrer&quot;&gt;Potentials and vibrational levels are compared to experiment&lt;/a&gt; for BeH, BeD, and BeT.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{BH}$&lt;/span&gt;: 6 electrons, 11 nucleons, 2 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3195061&quot; rel=&quot;noreferrer&quot;&gt;Non-Born Oppenheimer calculations that represent the largest number of electrons treated&lt;/a&gt; without the Born-Oppenheimer approximation. Here's a quote from the paper:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The results shown in this work represent a year of continuous&#xA;calculations with the use of 6 processors/24 cores quadcore Intel&#xA;Xeon 2.67 GHz or quadcore AMD Opteron 2.2 GHz&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H_2O}$&lt;/span&gt;: 10 electrons (8 correlated), 3 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/H2O/summary.txt&quot; rel=&quot;noreferrer&quot;&gt;AI ENERGIES Database entry showing FCI-level results&lt;/a&gt; up to a cc-pV9Z basis set.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{O_3}$&lt;/span&gt;: 24 electrons (18 correlated), 3 nuclei&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4990673&quot; rel=&quot;noreferrer&quot;&gt;Hundreds of thousands of CPU hours were used&lt;/a&gt; to do FCIQMC, DMRG, FN-DMC, and uncontracted MRCI+Q, AQCC, and ACPF on &lt;span class=&quot;math-container&quot;&gt;$\ce{O}_3$&lt;/span&gt; with only 6 electrons frozen.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{He_{60}}$&lt;/span&gt;: 120 electrons, 60 nuclei (Helium Buckyball / Fullerene)&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You asked about &amp;quot;finite element methods&amp;quot; but most of the above calculations, even for H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; use basis set methods instead, However an extremely small number of people do solve the many-electron Schroedinger equation &amp;quot;on a grid&amp;quot;, one of them being &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/142/susi-lehtola&quot;&gt;our very own Susi Lehtola&lt;/a&gt; who has &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;written an entire review on such numerical calculations on atoms and diatomic molecules&lt;/a&gt;, and another one of them being Hiroshi Nakatsuji who famously once calculated the ground state electronic energy of the He atom to about 40 digits of precision. Even he uses basis set methods for larger systems though, for example &lt;a href=&quot;https://pdfs.semanticscholar.org/444e/84380d6fca966c04db107646a1431e7aca0c.pdf&quot; rel=&quot;noreferrer&quot;&gt;in in this paper where he calculated energies for &lt;span class=&quot;math-container&quot;&gt;$\ce{He_{60}}$&lt;/span&gt;&lt;/a&gt;. You just can't do the explicitly correlated integrals efficiently for a 60-atom system, but if someone does decide to spend their entire year's CPU allocation on it, then I'm sure Nakatsuji would try to obtain the electronic Schroedinger equation using his famous explicitly correlated methods.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-07T02:19:47.277" LastActivityDate="2020-12-07T02:19:47.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3891" PostTypeId="1" AcceptedAnswerId="3908" CreationDate="2020-12-07T03:20:13.057" Score="11" ViewCount="1547" Body="&lt;p&gt;As a part of my coursework I have to calculate root mean square of fluctuation (RMSF) of a protein trajectory over the last 5 nanoseconds of simulation. I have used the inbuilt &lt;code&gt;measure rmsf&lt;/code&gt; function of VMD. However, I want to write a script by myself to get a better understanding of both VMD and Tcl. This is the script I have written:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set outfile [open ~/rmsf.dat w]&#xA;# trajectory is at top&#xA;set frame_num [molinfo top get numframes] &#xA;# calculating minimum frame of 5ns window&#xA;set min_frame [expr {$frame_num - ($frame_num / 5) - 1}] &#xA;set full [atomselect 0 &amp;quot;protein&amp;quot;] # selecting reference pdb &#xA;set prot [atomselect top &amp;quot;protein&amp;quot;]&#xA;# create empty list to store rmsf values&#xA;set rmsf {}&#xA;foreach i [$full get index] {&#xA;    lappend rmsf 0&#xA;}&#xA;#iterate over frames&#xA;for {set j $min_frame} {$j &amp;lt; $frame_num} {incr j} {&#xA;    $prot frame $j&#xA;    $prot update&#xA;    # iterate over each atom&#xA;    foreach i [$full get index] {&#xA;        lset rmsf $i [expr {[lindex $rmsf $i]} + {[vecdist [lindex [$full get {x y z}] $i] [lindex [$prot get {x y z}] $i]]}]&#xA;    }&#xA;}&#xA;# putting output&#xA;foreach i [$full get index] {&#xA;    puts $outfile [expr {sqrt([lindex $rmsf $i]/250)}]&#xA;}&#xA;$prot delete&#xA;$full delete&#xA;close $outfile&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My calculated &lt;code&gt;rmsf&lt;/code&gt; values differ from the default calculated values. I guess this can be because I have used a different reference compared to default, or I calculated it wrong.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which frame does VMD use as a reference in &lt;code&gt;measure rmsf&lt;/code&gt; the first frame in selection or the first frame of the entire trajectory?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1605" LastEditorUserId="52" LastEditDate="2020-12-09T18:30:51.203" LastActivityDate="2020-12-09T18:30:51.203" Title="Calculating RMSF in VMD" Tags="|software|visualization-software|proteins|software-assistance|vmd|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3892" PostTypeId="1" AcceptedAnswerId="3929" CreationDate="2020-12-07T09:31:47.607" Score="21" ViewCount="2539" Body="&lt;p&gt;Using DFT calculations we can know the electronic and magnetic property of the system at 0 K. I am wondering if there is any computational method to know the curie temperature of magnetic materials? Can I know the Curie temperature using Quantum Espresso?&lt;/p&gt;&#xA;&lt;p&gt;Any suggestion will be helpful.&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2020-12-08T00:13:26.643" LastActivityDate="2021-05-06T15:12:38.293" Title="Is it possible to calculate the Curie temperature for magnetic systems?" Tags="|density-functional-theory|quantum-espresso|magnetism|curie-temperature|anti-ferromagnetic|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3894" PostTypeId="2" ParentId="3883" CreationDate="2020-12-07T10:42:22.917" Score="5" Body="&lt;p&gt;Enthalpy and entropy are the temperature dependent terms in free energy from which enthalpy is a dominant term mainly at lower temperature and entropy is dominant at higher temperature (because randomness is more at higher temperature). This temperature effect can be considered by utilizing the heat capacity at constant pressure (Cp). Phonopy code is there to evaluate Cp as a function of temperature (Quasi harmonic approximation).&lt;/p&gt;&#xA;&lt;p&gt;Change in enthalpy and entropy terms are obtained by integrating Cp and Cp/T from 0 K to the desired temperature, respectively.&lt;/p&gt;&#xA;&lt;p&gt;Other terms like magnetic ordering (if the system is magnetic), pressure effect (mostly in geology) can also be included. Another most important term is the excess free energy,  which is due to the interaction between the different kinds of atoms. This is basically used while considering solid solutions.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2020-12-07T10:42:22.917" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3895" PostTypeId="2" ParentId="3892" CreationDate="2020-12-07T11:28:58.823" Score="13" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I am wondering if there is any computational method to know the curie&#xA;temperature of magnetic materials?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, there is!. Simulations to determine Curie Temperature are usually done via Monte-Carlo methods, with the assumptions taken from the Heisenberg model. I haven't done any Curie Temperature Simulations using DFT but it is possible as this answer on &lt;a href=&quot;https://www.researchgate.net/post/Curie-Temperature-Calculation-by-DFT-MD-calculations-vasp&quot; rel=&quot;noreferrer&quot;&gt;ResearchGate&lt;/a&gt; suggests.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can I know the Curie temperature using Quantum Espresso?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Rather than using Quantum ESPRESSO or any such DFT based codes, you're better off using Atomistic Spin model based codes like &lt;a href=&quot;https://vampire.york.ac.uk/&quot; rel=&quot;noreferrer&quot;&gt;VAMPIRE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is even a &lt;a href=&quot;https://vampire.york.ac.uk/tutorials/simulation/curie-temperature/&quot; rel=&quot;noreferrer&quot;&gt;tutorial on Curie Temperature simulations&lt;/a&gt; as given in their website&lt;/p&gt;&#xA;&lt;p&gt;VAMPIRE does, in fact, have issues when considering unit cells of different symmetry in one simulation if you're creating something similar to a bi-layer or a core-shell geometry.&lt;/p&gt;&#xA;&lt;p&gt;You could check out a Curie Temperature calculation I've done for a core-shell system &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3543/how-to-calculate-the-exchange-matrix-of-a-bilayer-magentic-system&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2020-12-07T11:28:58.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3896" PostTypeId="1" CreationDate="2020-12-07T12:25:07.457" Score="10" ViewCount="549" Body="&lt;p&gt;I want to incorporate the temperature effect on elastic constant (EC) of a system using VASP.&lt;br /&gt;&#xA;From literature, there are two ways which can be used to get the temperature effect on EC i) ab initio molecular dynamics ii) standard DFT with quasi harmonic approximation (as far as I know). Based on the second approach, standard DFT calculation with IBRION = 5 or 6 with ISIF = 3 tags can generate EC at 0 Kelvin for a particular volume. Again, volume vs. temperature data is one of the outputs of the phonon codes (QHA). But somehow I am not able to correlate this two quantities.&lt;/p&gt;&#xA;&lt;p&gt;Can somebody please explain a detailed way for getting the temperature effect by considering both theories and code (VASP)?&lt;/p&gt;&#xA;" OwnerUserId="1178" LastEditorUserId="1178" LastEditDate="2020-12-07T17:07:04.567" LastActivityDate="2022-05-24T04:50:32.743" Title="Temperature effect on elastic constant using VASP" Tags="|density-functional-theory|phonopy|temperature|elastic-constants|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3897" PostTypeId="1" CreationDate="2020-12-07T17:00:58.837" Score="12" ViewCount="153" Body="&lt;p&gt;Are there any standalone open source software codes available for periodic polarizable QM/MM embedding MD simulations? In my knowledge, CP2K only has the option for electrostatic embedding and other software such as GROMACS or CHARMM require coupling with Gaussian or ORCA electronic structure codes. Non-periodic implementations are also welcome but I am looking for periodic implementations.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2021-12-15T07:09:02.240" LastActivityDate="2021-12-15T07:09:02.240" Title="Periodic polarizable QM/MM embedding" Tags="|molecular-dynamics|software-recommendations|one-topic-per-answer|cp2k|qmmm|" AnswerCount="0" CommentCount="10" ClosedDate="2022-01-14T01:26:20.197" ContentLicense="CC BY-SA 4.0" />
  <row Id="3898" PostTypeId="2" ParentId="3892" CreationDate="2020-12-07T23:17:18.913" Score="10" Body="&lt;p&gt;(I'll answer with crystalline solids in mind.)&lt;/p&gt;&#xA;&lt;p&gt;You could study the material's magnetic and non-magnetic phases and construct their Gibbs free energy (G) vs temperature (T) profiles.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;G\: =\: H_{T=0}\: +\: H_{T&amp;gt;0}\: +\: \text{zero point energy}\: -\: T\cdot S, \tag{1}&#xA;\end{equation}&lt;/span&gt;&#xA;Where H is enthalpy, and S is entropy (any kind).&lt;/p&gt;&#xA;&lt;p&gt;Based on your system, you may have to alter equation &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; and add/remove terms.&lt;/p&gt;&#xA;&lt;p&gt;The following are certain ways to calculate each of the terms in equation &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$H_{T=0}$&lt;/span&gt;: Density functional theory based geometry optimization calculations are my best guess. Luckily, you wanted this option as well.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$H_{T&amp;gt;0}$&lt;/span&gt; and zero point energy: Lattice dynamics studies (vibrational frequency calculations, for molecules) should be sufficient. Codes like &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phonopy&lt;/a&gt;, &lt;a href=&quot;http://wolf.ifj.edu.pl/phonon/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PHONON&lt;/a&gt;, and &lt;a href=&quot;http://tutorials.crystalsolutions.eu/tutorial.html?td=dispersion&amp;amp;tf=dispersion-ht&quot; rel=&quot;nofollow noreferrer&quot;&gt;CRYSTAL&lt;/a&gt;, all work with DFT codes as force calculators. There is more to lattice dynamics than meets the eye: &lt;a href=&quot;https://en.wikipedia.org/wiki/Quasi-harmonic_approximation&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quasiharmonic approximation&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Anharmonicity#:%7E:text=An%20oscillator%20that%20is%20not,techniques%20have%20to%20be%20used.&quot; rel=&quot;nofollow noreferrer&quot;&gt;anharmonicity&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, S: this is tricky. You need to figure out which kinds of entropy matter for your system in the temperature range of interest. Accordingly, you need to then calculate each of those entropies.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;span class=&quot;math-container&quot;&gt;$2^{nd}$&lt;/span&gt; method&lt;/strong&gt;: I'm not too familiar with the CALPHAD (Calculation of phase diagram) method. As far as I understand, you create Gibbs free energy models from experimental or DFT data (or their hybrid) and compute G at various T. I just happened to ask this very question two days ago here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3883/what-information-about-a-crystalline-solid-material-goes-into-calculating-phase&quot;&gt;What information about a crystalline solid material goes into calculating phase diagrams in Thermo-Calc, and how?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For fluids, the &lt;span class=&quot;math-container&quot;&gt;$P\cdot V$&lt;/span&gt; term may also have to be added on a case by case basis.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-11T11:32:00.467" LastActivityDate="2020-12-11T11:32:00.467" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3899" PostTypeId="1" AcceptedAnswerId="3923" CreationDate="2020-12-08T03:52:25.310" Score="16" ViewCount="2398" Body="&lt;p&gt;I am trying to pack hard-spheres in a unit cubical box, such that these spheres cannot overlap on each other. This is being done in Python.&#xA;I am given some packing fraction &lt;code&gt;f&lt;/code&gt;, and the number of spheres in the system is &lt;code&gt;N&lt;/code&gt;.&#xA;So, I say that the diameter of each sphere will be&#xA;&lt;code&gt;d = (p*6/(math.pi*N)**)1/3)&lt;/code&gt;.&#xA;My box has periodic boundary conditions - which means that there is a recurring image of my box in all direction. If there is a particle who is at the edge of the box and has a portion of it going beyond the wall, it will stick out at the other side.&lt;/p&gt;&#xA;&lt;p&gt;This is my code, with me generating a configuration array called &lt;code&gt;box&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import pandas as pd&#xA;import math&#xA;import matplotlib.pyplot as plt&#xA;from mpl_toolkits.mplot3d import Axes3D&#xA;&#xA;np.random.seed(1)&#xA;#initialize the system&#xA;L = 1 #length of box&#xA;N = 500 #number of particles in a box&#xA;phi = np.asarray([0.2,0.45]) #packing fractions&#xA;#calculating the particle diameters so that we get the right density and packing fractions&#xA;d = (phi[1]*6/(N*math.pi))**(1/3)&#xA;#d=0.12 (approx)&#xA;rho = N/(L**3) #number density&#xA;&#xA;#intitalize box&#xA;box = np.random.uniform(0,1,(N, 3))&#xA;&#xA;#simulation 1&#xA;diameter = d #tolerance&#xA;#check if box is valid&#xA;&#xA;#this is a collection of loops to check if the particles we have placed are&#xA;#not overlapping&#xA;#we place i = 0 particle, no problem&#xA;#then we place the other particles, and we check with all the previously placed particles if&#xA;#the placement is okay or not&#xA;&#xA;for i in range(1,N):&#xA;    mybool=True&#xA;    print(&amp;quot;particles in box: &amp;quot; + str(i))&#xA;    while (mybool): #the deal with this while loop is that if we place a bad particle, we need to change its position, and restart the process of checking&#xA;        for j in range(0,i):&#xA;            displacement=box[j,:]-box[i,:]&#xA;            for k in range(3):&#xA;                if abs(displacement[k])&amp;gt;L/2:&#xA;                    displacement[k] -= L*np.sign(displacement[k])&#xA;            distance = np.linalg.norm(displacement,2) #check distance between ith particle and the trailing j particles&#xA;            if distance&amp;lt;diameter:&#xA;                box[i,:] = np.random.uniform(0,1,(1,3)) #change the position of the ith particle randomly, restart the process&#xA;                break&#xA;            if j==i-1 and distance&amp;gt;diameter:&#xA;                mybool = False&#xA;                break&#xA;#print(np.linalg.norm(box[0,:]-box[119,:]))&#xA;#test script to check if the above generated a sound configuration worked or not&#xA;for i in range(1,N):&#xA;    for j in range(0,i):&#xA;        displacement=box[j,:]-box[i,:]&#xA;        for k in range(3):&#xA;            if abs(displacement[k])&amp;gt;L/2:&#xA;                displacement[k] -= L*np.sign(displacement[k])&#xA;        distance = np.linalg.norm(displacement,2) #check distance between ith particle and the trailing j particles&#xA;        if distance&amp;lt;diameter:&#xA;            print(&amp;quot;this is bad&amp;quot;)&#xA;##########&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My attempt:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Create a numpy N-by-3 array &lt;code&gt;box&lt;/code&gt; which holds the position vector of each particle &lt;code&gt;[x,y,z]&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;The first particle is fine as it is.&lt;/li&gt;&#xA;&lt;li&gt;The next particle in the array is checked with all the previous particles. If the distance between them is more than &lt;code&gt;d&lt;/code&gt;, move on to the next particle. If they overlap, &lt;em&gt;randomly&lt;/em&gt; change the position vector of the particle in question. If the new position does not overlap with the previous atoms, accept it.&lt;/li&gt;&#xA;&lt;li&gt;Repeat steps 2-3 for the next particle.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am trying to populate my box with these hard spheres, in the following manner:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in range(1,N):&#xA;    mybool=True&#xA;    print(&amp;quot;particles in box: &amp;quot; + str(i))&#xA;    while (mybool): #the deal with this while loop is that if we place a bad particle, we need to change its position, and restart the process of checking&#xA;        for j in range(0,i):&#xA;            displacement=box[j,:]-box[i,:]&#xA;            for k in range(3):&#xA;                if abs(displacement[k])&amp;gt;L/2:&#xA;                    displacement[k] -= L*np.sign(displacement[k])&#xA;            distance = np.linalg.norm(displacement,2) #check distance between ith particle and the trailing j particles&#xA;            if distance&amp;lt;diameter:&#xA;                box[i,:] = np.random.uniform(0,1,(1,3)) #change the position of the ith particle randomly, restart the process&#xA;                break&#xA;            if j==i-1 and distance&amp;gt;diameter:&#xA;                mybool = False&#xA;                break&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The problem with this code is that if &lt;code&gt;p=0.45&lt;/code&gt;, it is taking a really, really long time to converge. Is there a better method to solve this problem, more efficiently?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2020-12-08T15:32:39.657" LastActivityDate="2022-10-12T03:51:11.810" Title="Is there a more efficient hard sphere packing algorithm?" Tags="|python|monte-carlo|" AnswerCount="3" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="3900" PostTypeId="1" CreationDate="2020-12-08T09:07:45.380" Score="7" ViewCount="799" Body="&lt;p&gt;Can anybody share methods to apply an external Electric field in ORCA? thanks!&lt;/p&gt;&#xA;" OwnerUserId="1669" LastEditorUserId="5" LastEditDate="2020-12-08T09:18:55.357" LastActivityDate="2020-12-08T22:28:29.233" Title="Adding external electric field in ORCA with specific strength" Tags="|orca|electric-field|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3901" PostTypeId="2" ParentId="3880" CreationDate="2020-12-08T13:13:19.703" Score="3" Body="&lt;p&gt;I think you may be not clear on how to find a suitable journal for your paper. I suggest that you can copy the title and abstract, then paste them to the websites of Elsevier or Web of Science. These websites will recommend which journal you should submit to.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://journalfinder.elsevier.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Elsevier&lt;/a&gt; and &lt;a href=&quot;https://mjl.clarivate.com/home?mm=&quot; rel=&quot;nofollow noreferrer&quot;&gt;Web of Science&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2020-12-09T15:11:02.443" LastActivityDate="2020-12-09T15:11:02.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3902" PostTypeId="1" CreationDate="2020-12-08T18:37:15.883" Score="14" ViewCount="513" Body="&lt;p&gt;During an ab-inito MD simulation one can generate the electron density cube file which basically provides the electronic density data in a standard volumetric format as shown &lt;a href=&quot;http://paulbourke.net/dataformats/cube/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. The file consists of a header which includes the atom information and the size as well as orientation of the volumetric data. This is followed by the volumetric data, one scalar per data element in 3D.&lt;/p&gt;&#xA;&lt;p&gt;In case of a MD xyz trajectory, the file consists of xyz coordinates as snapshots with respect to time, which one can visualize using any common software like VMD or MOLDEN. One can save multiple fragments of the trajectory, concatenating or pruning them for relevant atoms. So my question &lt;strong&gt;is there a way to visualize a series of electronic density cubes same way as an MD xyz trajectory?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am looking for open-source software solutions with which this might be possible to do so, for ex: &lt;a href=&quot;http://jmol.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;Jmol&lt;/a&gt;. I understand that one might need to preset isosurfaces and visualization settings and might need to have low resolution cube files for this task, but does anyone here have any experience in dealing with this issue or have any ideas about it?&lt;/p&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2020-12-08T20:18:28.747" Title="Visualizing MD generated electron density cubes as trajectories" Tags="|molecular-dynamics|software-recommendations|visualization-software|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3903" PostTypeId="2" ParentId="3902" CreationDate="2020-12-08T19:39:11.020" Score="15" Body="&lt;p&gt;Jmol is completely capable to do what you want. It reads &lt;code&gt;cube&lt;/code&gt; file format and works with scripts. Take a look at this &lt;a href=&quot;http://wiki.jmol.org/index.php/Creating_Movies&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt; related to making movies.&lt;/p&gt;&#xA;&lt;p&gt;The idea is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Your filenames must consist of a combination of text and a sequence of ordered numbers (e.g. myfiles_0001.cube, myfiles_0002.cube, etc.),&lt;/li&gt;&#xA;&lt;li&gt;Make a loop, and inside it:&lt;/li&gt;&#xA;&lt;li&gt;Load each file,&lt;/li&gt;&#xA;&lt;li&gt;Plot the property you want,&lt;/li&gt;&#xA;&lt;li&gt;Export as an image (JPG, PNG),&lt;/li&gt;&#xA;&lt;li&gt;Combine the images in order to create the film.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In each step you are in control of:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the quality of the property been plotted,&lt;/li&gt;&#xA;&lt;li&gt;the quality of the exported image,&lt;/li&gt;&#xA;&lt;li&gt;the quality of the movie created.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here is an example I used with MOPAC. In this case, the files have a root name (&lt;code&gt;test_&lt;/code&gt;) together with the number representing each step of my simulation (going from 1 to 999). In my case, the file with the property information is in MGF format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;clear&#xA;&#xA;name_root=&amp;quot;test_&amp;quot;&#xA;for i in {1..999}&#xA;do&#xA;   echo &lt;span class=&quot;math-container&quot;&gt;$i&#xA;   fname_in=&quot;$&lt;/span&gt;name_root&lt;span class=&quot;math-container&quot;&gt;$i.mgf&quot;&#xA;   fname_out=&quot;$&lt;/span&gt;name_root&lt;span class=&quot;math-container&quot;&gt;$i.jpg&quot;&#xA;   jmol $&lt;/span&gt;fname_in --nosplash --silent --nodisplay --script MEP_export -q85 --write JPG:$fname_out&#xA;done&#xA;&#xA;convert -limit memory 0 -limit map 0 *.jpg movie.gif&#xA;convert -limit memory 0 -limit map 0 *.jpg movie.mpg&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The code &lt;code&gt;--script MEP_export&lt;/code&gt; calls the MEP export options used by Jmol to generate the electrostatic potential:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;color background white&#xA;axes&#xA;rotate y 45&#xA;isosurface resolution 6 solvent map mep translucent; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is another (more compact) script with the same idea (this script is for Jmol)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fname = &amp;quot;test_1.mgf&amp;quot;;&#xA;nFrames = 100;&#xA;thisFrame = 0;&#xA;width = 640;&#xA;height = 480;&#xA;&#xA;&#xA;background white;&#xA;&#xA;message loop;&#xA;load @fname;&#xA;isosurface resolution 6 solvent map mep translucent;&#xA;refresh;&#xA;write image @width @height @fileName;&#xA;thisFrame = thisFrame + 1;&#xA;fname = name.replace(&amp;quot;1&amp;quot;,&amp;quot;&amp;quot; + (thisFrame)[-4][0]);&#xA;&#xA;&#xA;if (thisFrame &amp;lt; nFrames);goto loop;endif; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A final GIF:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/3xzZ3.gif&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-12-08T20:18:28.747" LastActivityDate="2020-12-08T20:18:28.747" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3904" PostTypeId="2" ParentId="3878" CreationDate="2020-12-08T22:15:31.677" Score="3" Body="&lt;p&gt;After modifying your file, I was able to get a converged energy of -250.37 hartrees, using CP2K v7.0 `(git:d15a9c53f), however I think this can be run on any CP2K version beyond v2.5.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    14 OT DIIS     0.15E+00    0.4     0.00000001      -250.3728024712 -3.24E-11&#xA;    15 OT DIIS     0.15E+00    0.4     0.00000001      -250.3728024712 -2.69E-11&#xA;    16 OT DIIS     0.15E+00    0.4     9.7858E-09      -250.3728024712 -3.97E-11&#xA;&#xA;  *** SCF run converged in    16 steps ***&#xA;  Electronic density on regular grids:       -255.9999999988        0.0000000012&#xA;  Core density on regular grids:              255.9999999562       -0.0000000438&#xA;  Total charge density on r-space grids:       -0.0000000426&#xA;  Total charge density g-space grids:          -0.0000000426&#xA;&#xA;  Overlap energy of the core charge distribution:               0.00000000021129&#xA;  Self energy of the core charge distribution:               -656.51151540102558&#xA;  Core Hamiltonian energy:                                    135.62949829361440&#xA;  Hartree energy:                                             345.88853381770627&#xA;  Exchange-correlation energy:                                -75.37931918172779&#xA;&#xA;  Total energy:                                              -250.37280247122129&#xA;&#xA;  outer SCF iter =   13 RMS gradient =   0.98E-08 energy =       -250.3728024712&#xA;  outer SCF loop converged in  13 iterations or  256 steps&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The modifications are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME ./GTH_BASIS_SETS&#xA;    POTENTIAL_FILE_NAME ./GTH_POTENTIALS&#xA;    &amp;amp;POISSON&#xA;      PERIODIC XYZ&#xA;    &amp;amp;END POISSON&#xA;    &amp;amp;SCF&#xA;      MAX_SCF  20&#xA;      EPS_SCF     1E-08&#xA;      SCF_GUESS  RESTART&#xA;      &amp;amp;OT  T&#xA;        MINIMIZER  DIIS&#xA;        PRECONDITIONER  FULL_KINETIC&#xA;      &amp;amp;END OT&#xA;      &amp;amp;OUTER_SCF  T&#xA;        EPS_SCF     1E-08&#xA;        MAX_SCF  20&#xA;      &amp;amp;END OUTER_SCF&#xA;      &amp;amp;PRINT&#xA;        &amp;amp;RESTART  SILENT&#xA;          BACKUP_COPIES  1&#xA;        &amp;amp;END RESTART&#xA;      &amp;amp;END PRINT&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;KIND Si&#xA;      ELEMENT   Si&#xA;      BASIS_SET DZVP-GTH-q4&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;One of my assumption here is that you are trying to use DZVP-GTH Basis for Si atom (works for generic GGA functionals such as PBE). The significant change here is the utilization of the Orbital Transform (OT) optimizer. I would recommend a quick overview of &lt;a href=&quot;https://www.cp2k.org/_media/events:2016_summer_school:20160824_scf.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;literature&lt;/a&gt; on OT methods for CP2K, as these are really crucial for a faster SCF convergence with CP2K.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2020-12-08T22:15:31.677" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3905" PostTypeId="2" ParentId="3900" CreationDate="2020-12-08T22:28:29.233" Score="7" Body="&lt;p&gt;From the &lt;a href=&quot;https://orcaforum.kofo.mpg.de&quot; rel=&quot;noreferrer&quot;&gt;ORCA forum&lt;/a&gt; &lt;a href=&quot;https://orcaforum.kofo.mpg.de/viewtopic.php?f=8&amp;amp;t=4461&amp;amp;p=18293&amp;amp;hilit=how%20to%20add%20electric%20field#p18293&quot; rel=&quot;noreferrer&quot;&gt;thread&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Actually there is an undocumented feature for this purpose:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;%scf&#xA;   efield X-field-strength-in-a.u. , Y-field-strength-in-a.u. , Z-field-strength-in-a.u.&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I have used it to compare dipole moments obtained via numeric and analytic differentiation and it worked fine. But do be careful as undocumented features do not officially exist (although in this case it might have just been overlooked in the manual)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I searched the &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/?cat=1&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt;, but didn't find any mention about how to add it.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-12-08T22:28:29.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3906" PostTypeId="1" AcceptedAnswerId="3909" CreationDate="2020-12-09T06:01:51.287" Score="10" ViewCount="198" Body="&lt;p&gt;Is the topological phase in a Weyl semimetal is intrinsic or symmetry protected? How can we realize that?&lt;/p&gt;&#xA;&lt;p&gt;If symmetry protected, which symmetry protects the topological phase of non-centrosymmetric Weyl semimetals and magnetic Weyl semimetals?&lt;/p&gt;&#xA;" OwnerUserId="1594" LastActivityDate="2020-12-09T20:08:35.377" Title="Topological order in Weyl Semimetal" Tags="|symmetry|topological-insulators|weyl-semimetal|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3907" PostTypeId="1" CreationDate="2020-12-09T14:00:51.897" Score="6" ViewCount="92" Body="&lt;p&gt;I want to draw Pd(75)Au(5)Si(20) metallic glass nanocomposite. How to draw exact this metallic glass nanocomposite.&lt;/p&gt;&#xA;" OwnerUserId="1422" LastEditorUserId="5" LastEditDate="2020-12-10T01:08:50.010" LastActivityDate="2020-12-11T18:43:43.860" Title="Generating glass nanocomposite structure in VESTA" Tags="|vesta|metals|nanostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3908" PostTypeId="2" ParentId="3891" CreationDate="2020-12-09T15:37:06.777" Score="6" Body="&lt;p&gt;The problem in the sript I had written was that my system was not able to handle that many variables at one go. So I made the calculations piecewise i.e. 40 atoms at a time and the results closely match the values one gets from the inbuilt function. In any case, calculating RMSF for just the C alpha atoms gives more information about the structural changes in the protein than measuring it for all atoms. I wrote the following script to do the same:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set outfile [open savefile.dat w]&#xA;set ref [atomselect 0 &amp;quot;protein&amp;quot;]&#xA;set sel [atomselect top &amp;quot;protein&amp;quot;]&#xA;for { set f 0 } { $f &amp;lt; [molinfo top get numframes] } { incr f } {&#xA;$sel frame $f&#xA;$sel move [measure fit $sel $ref]&#xA;}&#xA;$sel delete&#xA;$ref delete&#xA;set sel [atomselect top &amp;quot;name CA&amp;quot;]&#xA;set val [measure rmsf $sel]&#xA;for {set i 0} {$i &amp;lt; [llength $val]} { incr i} {&#xA;    puts $outfile [lindex $val $i]&#xA;}&#xA;$sel delete&#xA;close $outfile&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also figured out the inbuilt &lt;code&gt;measure rmsf&lt;/code&gt; function uses the average of the whole trajectory (that is why I aligned the trajectories in the script) as a reference rather than a specific frame. One can actually modify this by going into /src/Measure.C file in the source code if required.&lt;/p&gt;&#xA;" OwnerUserId="1605" LastEditorUserId="5" LastEditDate="2020-12-09T15:59:05.930" LastActivityDate="2020-12-09T15:59:05.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3909" PostTypeId="2" ParentId="3906" CreationDate="2020-12-09T20:08:35.377" Score="11" Body="&lt;p&gt;A Weyl point is a crossing of two bands. A two-band crossing can be described using the general Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}(\mathbf{k})=d_0(\mathbf{k})+d_1(\mathbf{k})\sigma_1+d_2(\mathbf{k})\sigma_2+d_3(\mathbf{k})\sigma_3&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; are the Pauli matrices. The eigenvalues are given by &lt;span class=&quot;math-container&quot;&gt;$E_{\pm}=d_0\pm\sqrt{d_1^2+d_2^2+d_3^2}$&lt;/span&gt;, so that a band crossing occurs when &lt;span class=&quot;math-container&quot;&gt;$d_1^2+d_2^2+d_3^2=0$&lt;/span&gt;. This equation involves three parameters, and in a three dimensional system, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}=(k_1,k_2,k_3)$&lt;/span&gt; has three components, so you can generically tune the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; vector to make the two bands degenerate without the need of any symmetry.&lt;/p&gt;&#xA;&lt;p&gt;Having established this, if you consider a system with both time reversal and inversion symmetry, then every band is doubly degenerate (spin up and spin down electrons have the same energy at every &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point). This means that potential band crossings would involve four (rather than two) bands, and be Dirac rather than Weyl points. So a pre-requisite before you can have a Weyl point is that you need to break the spin degeneracy caused by time reversal and inversion symmetries. This can be accomplished by breaking one of these two symmetries.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2020-12-09T20:08:35.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3910" PostTypeId="1" CreationDate="2020-12-10T07:18:07.343" Score="8" ViewCount="57" Body="&lt;p&gt;I work with SERS, where the Raman signal gets enhanced by the electric field of the nanoparticles. Now I like to simulate this kind of spectrum with Gaussian. I found a paper[1], where it looks very nice how they simulate it. They don't get a bond between the molecule and the silver nanoparticle. If I try it on my own, then the nanoparticles are thrown away by Gaussian. Has anyone of you an idea of how they simulate it? My idea is the following workflow: Frist, they optimize the attached molecule alone; after this, they made a scan with one variable. The variable is the distance between the part of the molecule where the nanoparticle should attach and the nanoparticle itself. And after this, they put the nanoparticle in the distance with the lowest energy and make a single point calculation with options to get the orbitals and the ESP mapping. It makes sense, or is it not an ordinary workflow for gaussian? I learned Gaussian myself so I'm not sure at all.&lt;/p&gt;&#xA;&lt;p&gt;[1] Gao, Y.; Xu, M.-L.; Xiong, J. J. Environ. Sci. Heal. Part B 2019, 54, 665-675&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="243" LastEditDate="2020-12-10T22:47:46.480" LastActivityDate="2020-12-11T17:54:04.630" Title="Simulation of electronic potential from nanoparticles interacting with molecules" Tags="|density-functional-theory|computational-chemistry|gaussian|electrostatic|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3911" PostTypeId="1" AcceptedAnswerId="6123" CreationDate="2020-12-10T10:58:27.860" Score="10" ViewCount="496" Body="&lt;p&gt;The Chemcraft website says that it is possible to create a potential energy surface. Nevertheless, it doesn't work for my Gaussian scan job.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=propylcyclohexan_scan_30.chk&#xA;#p GFINPUT POP(FULL) PM6 Opt=modredundant&#xA;&#xA; propylcyclohexan_scan_30&#xA;&#xA;0 1&#xA;C         -2.32729        0.36923       -0.26826&#xA;C         -1.86086        1.79592        0.04793&#xA;C         -1.42371       -0.68619        0.35867&#xA;H         -2.35296        0.22494       -1.35567&#xA;H         -3.35311        0.22391        0.09146&#xA;C         -0.38557        2.05033       -0.34666&#xA;H         -1.99132        1.97106        1.12477&#xA;H         -2.51564        2.50378       -0.47169&#xA;C          0.03534       -0.45199       -0.00958&#xA;H         -1.73512       -1.68573        0.02974&#xA;H         -1.53451       -0.66689        1.44998&#xA;C          0.49676        0.97326        0.33008&#xA;H          0.17109       -0.63513       -1.08350&#xA;H          0.66387       -1.18248        0.51357&#xA;H          0.48096        1.10355        1.41947&#xA;H          1.53881        1.06369        0.01138&#xA;C          0.03241        3.54672       -0.05839&#xA;H         -0.30194        1.90196       -1.43267&#xA;C          1.54273        3.82216       -0.15556&#xA;H         -0.26571        3.76488        0.97694&#xA;H         -0.55219        4.21744       -0.69950&#xA;C          2.23970        5.10589       -0.65389&#xA;H          2.00099        3.01727       -0.72714&#xA;H          1.90136        3.75452        0.88334&#xA;H          2.45381        5.07336       -1.75369&#xA;H          3.23327        4.96387       -0.25958&#xA;H          2.02974        6.11114       -0.31960&#xA;&#xA;D 6 17 19 22 S 11 30.0&#xA;D 12 6 17 19 S 11 30.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is possible to open the output file from this job and see the scan steps, but the &amp;quot;view scan graph&amp;quot; button does not work. Does Chemcraft need information that I forgot to calculate?&lt;/p&gt;&#xA;" OwnerUserId="1682" LastEditorUserId="5" LastEditDate="2021-02-28T05:14:35.767" LastActivityDate="2021-07-22T15:55:16.010" Title="How to create a Potential Energy Surface in Chemcraft?" Tags="|software|visualization-software|software-assistance|potential-energy-surface|chemcraft|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="3912" PostTypeId="1" CreationDate="2020-12-10T11:40:43.603" Score="9" ViewCount="218" Body="&lt;p&gt;I want to get familiar with the conformer calculation. I found a paper where they did the conformer calculations already for the molecule I work with. The paper can found &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/nj/c6nj02743a#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the experimental section, they write that they cut conformers after a second optimization after the scan for conformers by a few values. The take from the twenty structures they get only those with energies up to 0.59 kcal/mol. This should be a limit of conformational stability at 300 K. But they don't cite a reference for this fact. Is this something everybody knows through their academic education? - or have they just forget to cite the reference? If this is the case, does somebody have a reference for this?&lt;/p&gt;&#xA;&lt;p&gt;I taught Gaussian myself, and I read in the Gaussian manual that a stable conformed is a minimum of the potential energy surface (PES). In the paper &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/nj/c6nj02743a#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, they show structures that look not like the PES minimum. Is it possible in reason of these cut-off values that the stable conformer is not automatically the minimum?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/nj/c6nj02743a#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt; Moreira et al., Computational electronic structure of the bee killer insecticide imidacloprid, New Journal of Chemistry, 2016, 40, 10353-10362&lt;/p&gt;&#xA;&lt;p&gt;Add: I have not found a reference for the cut-off value for the stability of the conformers. Does someone have a similar problem? Or work on something which is similar?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="1680" LastEditDate="2020-12-13T16:52:00.603" LastActivityDate="2020-12-15T04:27:20.640" Title="Energy cut-off value for conformer calculations" Tags="|density-functional-theory|computational-chemistry|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3913" PostTypeId="1" CreationDate="2020-12-10T11:42:27.507" Score="16" ViewCount="578" Body="&lt;p&gt;What's the most efficient way to compare the two DFT codes in terms of computation time, basis sets (for example, one plane wave vs one atomic orbitals), functional performance, etc.?&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2020-12-10T20:36:38.543" LastActivityDate="2020-12-16T05:18:54.523" Title="What's the best way to compare two DFT codes?" Tags="|density-functional-theory|software|high-performance-computing|basis-sets|benchmark-timings|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3914" PostTypeId="2" ParentId="3913" CreationDate="2020-12-10T12:10:51.713" Score="9" Body="&lt;p&gt;There are many options to answer your question.&lt;/p&gt;&#xA;&lt;p&gt;Just to compare the computation time, the first condition is to run the simulations with the same hardware i.e. in the same system (two different set-ups even with the same type of hardware can perform differently). Also, both codes have to be compiled with the same compiler and with the same compiling optimization options. Finally, the physical system used should be the same.&lt;/p&gt;&#xA;&lt;p&gt;For the other comparisons, you will need a third set of data. I strongly recommend to look for a system where the theoretical predictions are in accordance with experimental ones and then use the experimental data as a reference.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-12-10T20:37:56.537" LastActivityDate="2020-12-10T20:37:56.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3915" PostTypeId="1" CreationDate="2020-12-10T13:32:59.097" Score="19" ViewCount="534" Body="&lt;p&gt;This may be a sensitive question that may cause theoretical scientists to feel injured.&lt;/p&gt;&#xA;&lt;p&gt;Today my paper was rejected after assigning it to the editor. Here is what the editor said about the reason:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;With your manuscript, in absence of experimental data supporting the&#xA;theoretical predictions, I am sadly unable to conclude that the work&#xA;represents a clear conceptual and methodological advance that would&#xA;likely generate interest among our readership. The paper is better&#xA;suited for a broad-topic journal focused on hypothesis-driven&#xA;research, without any evaluation of immediate impact.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;My question is whether the theoretical data are just something that must follow the experimental data. Are predicted data meaningless without experimental data?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2020-12-10T18:15:59.397" LastActivityDate="2020-12-10T18:45:56.153" Title="Theoretical paper was rejected by the editor due to no experimental data: Is this common?" Tags="|experimental|publishing|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3916" PostTypeId="2" ParentId="3915" CreationDate="2020-12-10T18:39:43.330" Score="15" Body="&lt;p&gt;This all depends very much on the journal. It is not necessarily something that should make you &amp;quot;feel injured&amp;quot;, since there's many journals that allow for the publication of theoretical calculations that are completely devoid of experimental support.&lt;/p&gt;&#xA;&lt;p&gt;This specific wording that the editor used:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The paper is better suited for a broad-topic journal focused on&#xA;hypothesis-driven research, without any evaluation of immediate impact&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;makes it appear that the journal to which you submitted, prefers to publish papers that will have &amp;quot;immediate impact&amp;quot; rather than papers that generate a hypothesis to be tested later by experimentalists. Furthermore the beginning of the editor's message:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;With your manuscript, in absence of experimental data supporting the&#xA;theoretical predictions...&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;indicates to me that this journal prefers to publish work that is experimentally supported.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Examples of journals in our field that are like this include JACS and Angewandte Chemie&lt;/strong&gt;&lt;/em&gt;, the former being notorious for not publishing work in theoretical chemistry without experimental support. However &amp;quot;International Journal of Quantum Chemistry&amp;quot; and &lt;a href=&quot;https://www.sciencedirect.com/journal/journal-of-molecular-structure-theochem&quot; rel=&quot;noreferrer&quot;&gt;THEOCHEM&lt;/a&gt; do publish a lot of papers that are purely theoretical (however you have not told us which journal you're discussing, so it's hard to tell whether or not you're a molecular matter modeler or a materials matter modeler: based on your other questions it looks like you work more in the solid-state side of things, meaning that you'd be looking more at physics journals than chemistry journals, so &amp;quot;Physica Status Solidi B&amp;quot; might be a journal for you to consider).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My question is whether the theoretical data are just something that&#xA;must follow the experimental data. Are predicted data meaningless&#xA;without experimental data?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It absolutely does not have to follow experimental data, and it is absolutely &lt;em&gt;not&lt;/em&gt; &amp;quot;meaningless&amp;quot; without experimental data, &lt;em&gt;however&lt;/em&gt; a trap that a lot of middle-scale academics fall into is that they think that because they solved a challenging problem that involved a lot of work, it should be publishable in a good journal. Unfortunately there's millions of challenging problems that we can get students to solve, which will be of very little interest to other people, so if a journal wants to maintain its reputation as one of the &amp;quot;most cited&amp;quot; or &amp;quot;most viewed&amp;quot; journals in the field, it often has to choose only the most &amp;quot;impactful&amp;quot; or &amp;quot;widely interesting&amp;quot; papers to publish. Now especially in our field of matter modeling, a lot of theoretical results are in fact meaningless from an experimental standpoint (&lt;em&gt;not&lt;/em&gt; meaningless altogether, because by telling the reader what a certain method predicted under the conditions of the calculations, it still says something meaningful about the &lt;em&gt;method&lt;/em&gt;) because you can get numbers with DFT (for example) that are just completely wrong. Many journals will not be interested in publishing such results, which is why journals catering &lt;em&gt;specifically&lt;/em&gt; to theoretical work (e.g. International Journal of Quantum Chemistry or THEOCHEM) were created to let theoreticians have a place to put their results.&lt;/p&gt;&#xA;&lt;p&gt;Finally I'll say that many editors get a &lt;em&gt;&lt;strong&gt;large volume&lt;/strong&gt;&lt;/em&gt; of papers each day, and it's not uncommon for them to give generic rejection letters that are made to look polite and personal but really are copied and pasted. If you see your question's edit history, you might notice that you made a lot of grammatical errors just in writing this question alone, and if your paper looked anything like that, the editor might (based on the writing quality alone) not have wanted to waste the time of the referees, since it's not always easy to find senior academics that are willing to volunteer their time towards reviewing a (poorly written) paper for free. So if you see lots of theoretical papers in that journal, without experimental support, consider that your paper just didn't meet the journal's quality standards.&lt;/p&gt;&#xA;&lt;p&gt;I will also end with what are I wrote at the end of &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3885/5&quot;&gt;this answer&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It usually does no harm to look at some of the papers in the most&#xA;recent issue of a journal, and even write to the editor an informal&#xA;inquiry about the suitability of the journal for your paper, before&#xA;formally submitting the paper, since this can save you the loss of&#xA;time (and energy and enthusiasm!) associated with having a paper&#xA;rejected.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;By doing this you can see in advance whether or not the journal accepts papers without experimental support.&lt;/p&gt;&#xA;&lt;p&gt;I would recommend next time also to tell us &lt;em&gt;&lt;strong&gt;which journal&lt;/strong&gt;&lt;/em&gt; you're discussing, and if you don't mind even showing us the paper we can help you a lot more than you might have originally thought.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-10T18:45:56.153" LastActivityDate="2020-12-10T18:45:56.153" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3917" PostTypeId="5" CreationDate="2020-12-10T18:55:37.213" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.chemcraftprog.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.chemcraftprog.com/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-10T18:55:37.213" LastActivityDate="2020-12-10T18:55:37.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3918" PostTypeId="4" CreationDate="2020-12-10T18:55:37.213" Score="0" Body="Questions about the software ChemCraft." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-10T18:55:37.213" LastActivityDate="2020-12-10T18:55:37.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3919" PostTypeId="1" CreationDate="2020-12-10T23:09:40.990" Score="29" ViewCount="4434" Body="&lt;p&gt;Very recently, China &lt;a href=&quot;https://www.livescience.com/china-quantum-supremacy.html&quot; rel=&quot;noreferrer&quot;&gt;claims&lt;/a&gt; achieving 'Quantum Supremacy' with the world's fastest Quantum Computer. Their computer was designed as a circuit of lasers, beam splitters and mirrors (see &lt;a href=&quot;https://science.sciencemag.org/content/early/2020/12/02/science.abe8770&quot; rel=&quot;noreferrer&quot;&gt;figure bellow&lt;/a&gt;) and to solve a very specific problem called Gaussian boson sampling.&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/UB0SU.jpgg&quot; width=&quot;400&quot; height=&quot;400&quot;&gt;&#xA;&lt;p&gt;The quantum computer from Google, for example, consists of microscopic circuits of superconducting metal that entangle 53 qubits in a complex superposition state. In the case of IBM, their quantum chips are formed by &lt;a href=&quot;https://www.ibm.com/quantum-computing/developers/&quot; rel=&quot;noreferrer&quot;&gt;microwave resonators in combination with Josephson superconducting junctions&lt;/a&gt;. In case of the IBM, there is already, an open source SDK called &lt;a href=&quot;https://www.ibm.com/quantum-computing/developers/&quot; rel=&quot;noreferrer&quot;&gt;Qiskit&lt;/a&gt; that expresses quantum computing concepts intuitively and concisely in Python. In both cases, it is possible to program the computers to solve different tasks.&lt;/p&gt;&#xA;&lt;p&gt;My questions is: &lt;strong&gt;how honest is the Chinese claim of quantum supremacy?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-12-12T06:54:58.693" LastActivityDate="2023-11-14T19:38:29.170" Title="How does the recent Chinese quantum supremacy claim compare with Google's?" Tags="|high-performance-computing|quantum-computing|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3920" PostTypeId="2" ParentId="3919" CreationDate="2020-12-10T23:23:14.830" Score="34" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;how honest is the Chinese claim of quantum supremacy?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's equally (or at least as) honest in comparison to Google's claim.&lt;/p&gt;&#xA;&lt;p&gt;In a comment to &lt;a href=&quot;https://quantumcomputing.stackexchange.com/questions/11895/why-google-has-used-sqrtx-and-sqrty-instead-of-x-and-y-in-supremac/11955#comment15587_11955&quot;&gt;this answer at Quantum Computing Stack Exchange&lt;/a&gt;, Craig Gidney (who works at Google and was a co-author on Google's Quantum Supremacy paper), confirmed that the classical computer would have been &lt;code&gt;2^(20*7/4) = 34359738368&lt;/code&gt; times faster if Google's hardware used CZ gates instead of their gates. This would mean that the 10,000 years that they said it would take classical computers to do the calculation that Google did, would become 9 seconds.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore IBM pointed out that the estimations Google made about the time it would take the classical computer, assumed that the classical computer could only use RAM and no disk at all, and if you allow the classical computer to use disk (which in this case, since they used Oak Ridge National Lab's Summit supercomputer, has petabytes available rather than just terabytes) then even though I/O is slower on disk than RAM you will save so much time by not re-calculating things, that you will get several orders of magnitude further speed-up for the classical computer.&lt;/p&gt;&#xA;&lt;p&gt;I'm not aware of anything like this for the Chinese experiment, but to be clear: &lt;a href=&quot;https://en.wikipedia.org/wiki/Boson_sampling&quot; rel=&quot;nofollow noreferrer&quot;&gt;boson sampling&lt;/a&gt; is not enough to do &amp;quot;universal&amp;quot; computation, however universal computation is &lt;em&gt;not&lt;/em&gt; a requirement for quantum supremacy. The probability distribution from which boson-samplers sample, is &lt;a href=&quot;https://en.wikipedia.org/wiki/%E2%99%AFP&quot; rel=&quot;nofollow noreferrer&quot;&gt;#P&lt;/a&gt;-difficult to calculate on a classical computer, which means that no polynomially scaling classical algorithm is known to be able to simulate such a distribution. &lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/2244/2293&quot;&gt;Discussions have taken place&lt;/a&gt; on the Quantum Computing Stack Exchange about whether or not boson sampling can be used to &amp;quot;calculate&amp;quot; the permanent of a complex-valued matrix (this is known to be a #P problem for classical computers), for example.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, Figure 1 of &lt;a href=&quot;https://arxiv.org/abs/1805.01450&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; shows that it wasn't hard for the authors to simulate 144 qubits on a classical computer. That paper was published 1 year earlier than Google's quantum &amp;quot;supremacy&amp;quot; claim! This was discussed in more detail &lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/30167/2293&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In any case, &amp;quot;quantum supremacy&amp;quot; is a buzzword and until people are actually using quantum devices to solve useful problems, classical computers are superior because people actually find them valuable enough to purchase.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-11-14T19:38:29.170" LastActivityDate="2023-11-14T19:38:29.170" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="3921" PostTypeId="2" ParentId="3913" CreationDate="2020-12-10T23:53:30.247" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What's the best way to compare two DFT codes?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I assume here the DFT means Kohn-Sham density functional theory (KS-DFT). The central task of KS-DFT is to solve the following Kohn-Sham equation (atomic unit is adopted):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left[-\dfrac{1}{2}\nabla^2+V_{ks}[\psi_i(\vec{r})]\right]\psi_i(\vec{r})=E_i\psi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is a nonlinear differential equation to be solved self-consistently. There are many elements that are related to solving the Kohn-Sham equation. For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt;: How to choose a basis to expand the wavefunction? plane-wave or local orbital?&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{ks}$&lt;/span&gt;: How to treat effective potential? All electron or pseudopotential?&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$-\dfrac{1}{2}\nabla^2$&lt;/span&gt;: Is it necessary to consider spin-orbit coupling?&lt;/li&gt;&#xA;&lt;li&gt;How to choose the exchange-correlation functional?&lt;/li&gt;&#xA;&lt;li&gt;....&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Usually, different KS-DFT code will have their independent choice about these elements. Therefore, you can hardly find a general method to compare two KS-DFT codes. Although this task is untouchable, you can generate almost reasonable physical results based on different Kohn-Sham DFT codes, as discussed by this paper: &lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;nofollow noreferrer&quot;&gt;Reproducibility in density functional theory calculations of solids&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Although there is no absolute reference against which to compare two DFT codes due to each approach has its own intricacies and approximations, to quantify differences between two DFT codes, the &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; gauge is formulated by &lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/10408436.2013.772503&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lejaeghere et al.&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2020-12-16T05:18:54.523" LastActivityDate="2020-12-16T05:18:54.523" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3922" PostTypeId="2" ParentId="3872" CreationDate="2020-12-11T01:39:57.733" Score="8" Body="&lt;p&gt;With the Materials Project and magnetism, it's often useful to download the structure directly and examine the magnetic moments on that structure, for example using the &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;pymatgen&lt;/a&gt; Python code and the &lt;code&gt;MPRester&lt;/code&gt; class, like so:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen import MPRester&#xA;with MPRester() as mpr:  # you may need to supply your API key in the parentheses here, see materialsproject.org/dashboard&#xA;    struct = mpr.get_structure_by_material_id('mp-27363')&#xA;print(struct)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For this mp-id, this gives:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Full Formula (Ba2 V2 Se6)&#xA;Reduced Formula: BaVSe3&#xA;abc   :   7.035690   7.035690   5.902194&#xA;angles:  90.000000  90.000000 119.366265&#xA;Sites (10)&#xA;  #  SP           a         b         c    magmom&#xA;---  ----  --------  --------  --------  --------&#xA;  0  Ba    0.663884  0.336116  0.754951     0.001&#xA;  1  Ba    0.336116  0.663884  0.254951     0&#xA;  2  V     0.974167  0.025833  0.013237     1.029&#xA;  3  V     0.025833  0.974167  0.513237     1.041&#xA;  4  Se    0.329967  0.163445  0.243081    -0.061&#xA;  5  Se    0.836555  0.670033  0.243081    -0.063&#xA;  6  Se    0.829283  0.170717  0.274618    -0.082&#xA;  7  Se    0.163445  0.329967  0.743081    -0.06&#xA;  8  Se    0.670033  0.836555  0.743081    -0.062&#xA;  9  Se    0.170717  0.829283  0.774618    -0.083&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is in units of Bohr magneton, so the moment on the V is &lt;code&gt;1.029 µB&lt;/code&gt;, and the total moment &lt;em&gt;per unit cell&lt;/em&gt; is 1.66 µB (&lt;code&gt;sum(struct.site_properties['magmom'])&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why the discrepancy?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Two reasons,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;in a DFT calculation, the magnetic moment you obtain is very sensitive to both your initial ordering (ferromagnetic, antiferromagnetic, etc.) and also your use of Hubbard U. It is very common that different authors use different U values. The Materials Project uses a U of &lt;a href=&quot;https://docs.materialsproject.org/methodology/gga-plus-u/&quot; rel=&quot;nofollow noreferrer&quot;&gt;3.25 eV&lt;/a&gt; on vanadium. This can also be affected by pseudo potentials, which will necessarily be different between simulation code like Quantum Espresso and VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;the discrepancy on Materials Project could be the result of our slow-but-steady progress towards more explicitly calculating magnetic order of materials (e.g. see &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0199-7.pdf?origin=ppub&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;). While the values reported by MP from an individual calculation always remain the same, the values reported on the &amp;quot;material details page&amp;quot; can change from release to release as new calculations come in, and bug in this case is also possible (we strive for quality but it's a large database and bugs do happen, we encourage people to check our database release logs where we disclose issues as we discover them).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;We (meaning, people working on the Materials Project) try to be responsive on &lt;a href=&quot;https://matsci.org/materials-project&quot; rel=&quot;nofollow noreferrer&quot;&gt;matsci.org/materials-project&lt;/a&gt; if you want to ask a question directly, or you can contact us over email.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;In conclusion,&lt;/strong&gt; your value of 1.95 µB per cell actually seems fairly reasonable!&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="1333" LastEditDate="2021-01-20T20:24:58.330" LastActivityDate="2021-01-20T20:24:58.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3923" PostTypeId="2" ParentId="3899" CreationDate="2020-12-11T03:30:21.863" Score="10" Body="&lt;p&gt;If you want faster solution, you can use simplification. If there are more than some critical amount of spheres (about 100), then grid solution is likely almost as good as true solution. Make a triangle grid, and only check the grid size, adding or removing rows and columns. Add another grid on top, until you have enough spheres to satisfy your requirements. Most closely packed spheres pattern looks like this:&#xA;&lt;img src=&quot;https://hexnet.org/files/images/hexnet/content_close-packing.png&quot; alt=&quot;close packing of spheres&quot; /&gt;&#xA;And there is no need to calculate spheres in between the edges, because their perfect arrangement is known. You will have gaps on the borders of a box, even with 'poking from another side', because spheres size likely wont arrange to a perfect grid on the edge. This solution takes about the same time for any size of the box and number of spheres, because you are only checking the boundary.&lt;/p&gt;&#xA;&lt;p&gt;If you want more precise solution, you need physical simulation. Put all your spheres randomly in a box, with overlapping. Then start the simulation with gravity and pushing overlapping spheres away. Calculate each step all the forced that act on a sphere, sum it, apply the sum as a force acting against sphere's inertia.&#xA;You will need nearest neighbor search, that will be your true enemy, simulation itself is simple.&#xA;&lt;a href=&quot;https://en.m.wikipedia.org/wiki/Nearest_neighbor_search&quot; rel=&quot;noreferrer&quot;&gt;https://en.m.wikipedia.org/wiki/Nearest_neighbor_search&lt;/a&gt;&#xA;There are a few dozen solutions, but since you will need dynamic, lots of them wont work fast enough, mostly because tree rebuilding is often expensive. I would suggest graph based, local, without global index.&lt;/p&gt;&#xA;&lt;p&gt;What you can plug in your code right now to get an answer:&#xA;&lt;a href=&quot;https://pynndescent.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;https://pynndescent.readthedocs.io/en/latest/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Further reading:&#xA;&lt;a href=&quot;https://www.cs.princeton.edu/cass/papers/www11.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://www.cs.princeton.edu/cass/papers/www11.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;p.s. This is probably the most universal and complex algorithm there is. From selecting next film to watch, to determening if fingerprint matches.&lt;/p&gt;&#xA;" OwnerUserId="1690" LastEditorUserId="7" LastEditDate="2021-11-13T14:03:14.110" LastActivityDate="2021-11-13T14:03:14.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3924" PostTypeId="2" ParentId="3896" CreationDate="2020-12-11T03:34:57.367" Score="5" Body="&lt;p&gt;It is always better to write your own code to get elastic constants. For example , In case of cubic system, we need three types of distorsion to unit cell. Now elastic constant is simply slope of second order fit of energies at different value of distorsion (see different publications) normalized with Volume minima (volume corresponds to  minimum energy) .&#xA;To calculate elastic constants at higher temperature, we need two things&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Free energy of crystal at different temperature( use phonopy)&lt;/li&gt;&#xA;&lt;li&gt;Volume minima at higher temp( we can get from v-t)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Second order fit of free energy (at higher temp) normalized with volume minima of that temp will give elastic constants at higher temperature.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2020-12-11T03:34:57.367" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3925" PostTypeId="1" CreationDate="2020-12-11T07:25:58.467" Score="10" ViewCount="89" Body="&lt;p&gt;When you load a metal and the deformation results in permanent plastic deformation, the input work should be converted into heat and thus dissipate. But for about 100 years people have struggled to fully grasp how much work is converted to heat and how much stored in the microstructure. This ratio between input work and output heat is commonly known as the &amp;quot;Taylor-Quinney Coefficient&amp;quot;. A lot of the trouble comes from the fact that experiments don't really agree one with the other on this measured coefficient. So in &lt;a href=&quot;https://authors.elsevier.com/a/1cDcd4r9SUJ4kH&quot; rel=&quot;noreferrer&quot;&gt;our paper&lt;/a&gt; we have decided to use MD as the &amp;quot;perfect experiment&amp;quot; and employ the same analysis methods as done by the experimentalists.&lt;/p&gt;&#xA;&lt;p&gt;As a side note, I think it can be beneficial for us modelers and theoreticians to &amp;quot;cross over&amp;quot; and see what tools and methods are used in experiments and maybe get some insight and inspiration from them.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Does anyone have thoughts about what we did in &lt;a href=&quot;https://authors.elsevier.com/a/1cDcd4r9SUJ4kH&quot; rel=&quot;noreferrer&quot;&gt;our paper&lt;/a&gt;?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="1691" LastEditorUserId="5" LastEditDate="2020-12-12T03:03:56.387" LastActivityDate="2021-04-25T01:13:28.373" Title="Using Molecular Dynamics as an experimentalist to study how much plastic work is converted to heat, does anyone have any comments on our paper?" Tags="|molecular-dynamics|lammps|crystal-plasticity|" AnswerCount="0" CommentCount="3" ClosedDate="2021-04-25T01:13:32.350" ContentLicense="CC BY-SA 4.0" />
  <row Id="3926" PostTypeId="1" CreationDate="2020-12-10T04:46:09.020" Score="11" ViewCount="243" Body="&lt;p&gt;I need to &amp;quot;build&amp;quot; an organometallic molecule in Blender/Python then represent it resting on a crystal surface.&lt;/p&gt;&#xA;&lt;p&gt;I'm looking at a &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/compound/Chloroaluminum-phthalocyanine#section=3D-Conformer&quot; rel=&quot;nofollow noreferrer&quot;&gt;PubChem summary for Chloroaluminum phthalocyanine&lt;/a&gt; and I can download some JSON files and generate a crude plot for it.&lt;/p&gt;&#xA;&lt;p&gt;According to the description this is a calculated shape and size and for my purposes that &lt;em&gt;sounds like&lt;/em&gt; it should be close enough for me for now, as much as +/-5 % is acceptable at the moment. I just want to see roughly how large this molecule is.&lt;/p&gt;&#xA;&lt;p&gt;I am assuming that the coordinates are in Angstroms, but I can not find anything that says that explicitly here.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that the 2D JSON shows it to be about 11 Angstroms from one end to the other, but the 3D JSON shows a molecule that will be more like 16 Angstroms when stretched out.&lt;/p&gt;&#xA;&lt;p&gt;That substantial difference suggests I can't yet assume those coordinates are what I think they are, so I'd like to ask:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; How can I interpret the 2D and 3D coordinates of atom locations from a PubChem summary of an organometallic molecule? Which of these JSON files should I use? The molecule's &amp;quot;arms&amp;quot; are shown bent in the 3D representation, am I free to &amp;quot;flatten&amp;quot; them to show the molecule laying flat?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;note:&lt;/strong&gt; This is for illustration/animation purposes, not for deriving information about interaction.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bqw7t.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bqw7t.png&quot; alt=&quot;Structure2D_CID_123667.json&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;above:&lt;/strong&gt; &lt;code&gt;Structure2D_CID_123667.json&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;below:&lt;/strong&gt; &lt;code&gt;Conformer3D_CID_5282330.json&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/s9bTK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s9bTK.png&quot; alt=&quot;Conformer3D_CID_5282330.json&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A three-dimensional representation of the compound. The 3D structure is not experimentally determined, but computed by PubChem. More detailed information on this conformer model is described in the PubChem3D thematic series published in the Journal of Cheminformatics.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PPsIw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PPsIwm.png&quot; alt=&quot;screenshot&quot; /&gt;&lt;/a&gt; click for larger&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;from mpl_toolkits.mplot3d import Axes3D &#xA;import json&#xA;&#xA;# https://pubchem.ncbi.nlm.nih.gov/compound/Chloroaluminum-phthalocyanine&#xA;&#xA;fnames = ('Conformer3D_CID_5282330.json',&#xA;          'Structure2D_CID_123667.json')&#xA;&#xA;molecule = dict()&#xA;&#xA;for fname in fnames:&#xA;    if '3D' in fname:&#xA;        dim = '3D'&#xA;    else:&#xA;        dim = '2D'&#xA;        &#xA;    with open(fname, 'r') as infile:&#xA;        info = json.load(infile)&#xA;&#xA;    data       = info['PC_Compounds'][0]&#xA;    atoms      = data['atoms']  &#xA;    atom_id    = atoms['aid']  &#xA;    element_id = atoms['element']  &#xA;    coords     = data['coords'][0]['conformers'][0]&#xA;    if dim == '3D':&#xA;        x, y, z = [coords[axis] for axis in 'xyz']&#xA;    else:&#xA;        x, y    = [coords[axis] for axis in 'xy']&#xA;        z       = len(x) * [0]&#xA;    things = zip(atom_id, element_id, x, y, z)&#xA;&#xA;    mol = dict()&#xA;    molecule[dim] = mol&#xA;    for thing in things:&#xA;        try:&#xA;            mol[thing[1]].append(thing)&#xA;        except:&#xA;            mol[thing[1]] = [thing]&#xA;    &#xA;with open('molecule', 'w') as outfile:&#xA;    json.dump(molecule, outfile)&#xA;&#xA;if True:&#xA;    # plot 2D&#xA;    fig = plt.figure()&#xA;    ax  = fig.add_subplot(1, 1, 1, projection='3d')&#xA;    for elem, data in molecule['2D'].items():&#xA;        atom_id, element_id, x, y, z = zip(*data)&#xA;        ax.plot(x, y, z, 'o', markersize=16)&#xA;        print('elem: ', elem, len(x))&#xA;    plt.show()&#xA;&#xA;    # plot 3D&#xA;    fig = plt.figure()&#xA;    ax  = fig.add_subplot(1, 1, 1, projection='3d')&#xA;    for elem, data in molecule['3D'].items():&#xA;        atom_id, element_id, x, y, z = zip(*data)&#xA;        ax.plot(x, y, z, 'o', markersize=16)&#xA;        print('elem: ', elem, len(x))&#xA;    plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="201" OwnerDisplayName="uhoh" LastEditorUserId="5" LastEditDate="2021-02-28T05:16:59.473" LastActivityDate="2021-11-01T12:10:29.390" Title="Interpret 2D and 3D data from a PubChem summary of organometallic molecule? Can I &quot;flatten&quot; it when showing on a surface?" Tags="|molecular-modeling|python|databases|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3927" PostTypeId="2" ParentId="3910" CreationDate="2020-12-11T17:54:04.630" Score="2" Body="&lt;p&gt;I already did the same type of calculation but for different system (functionalized carbon nanotube interacting with heavy metals).&lt;/p&gt;&#xA;&lt;p&gt;About your workflow, the only step I will do different is that instead a single point optimization I'll run a full geometry optimization. This is due that you can not be sure that the point you selected from the scan correspond, exactly, to the minimum potential energy (even with a dense scan).&lt;/p&gt;&#xA;&lt;p&gt;Related to the nanoparticle being thrown away, I will play with different methods (semiempirical, DFT, Hartree-Fock), with different functionals and with different basis sets (I am not too sure if B3LYP is a good choice for silver).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2020-12-11T17:54:04.630" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3928" PostTypeId="2" ParentId="3907" CreationDate="2020-12-11T18:11:30.537" Score="2" Body="&lt;p&gt;In order to visualize structures in VESTA, you need a file with the crystal or molecular structure. This files are very difficult to created by hand. The near structure I found in the ICSD database was for &lt;span class=&quot;math-container&quot;&gt;$\ce{Pd_{0.74}Au_{0.08}Si_{0.18}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The CIF file is bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#(C) 2020 by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure.  All rights reserved.&#xA;data_108005-ICSD&#xA;_database_code_ICSD 108005&#xA;_audit_creation_date 2006-10-01&#xA;_chemical_name_common 'Gold palladium silicon (0.08/0.74/0.18)'&#xA;_chemical_formula_structural 'Au0.08 Pd0.74 Si0.18'&#xA;_chemical_formula_sum 'Au0.08 Pd0.74 Si0.18'&#xA;_chemical_name_structure_type fcc(ccp)#Cu&#xA;_exptl_crystal_density_diffrn 10.73&#xA;_citation_title&#xA;'SAXS study on crystallization of an amorphous Pd76 Au6 Si18 alloy'&#xA;loop_&#xA;_citation_id&#xA;_citation_journal_full&#xA;_citation_year&#xA;_citation_journal_volume&#xA;_citation_page_first&#xA;_citation_page_last&#xA;_citation_journal_id_ASTM&#xA;primary 'Journal of Materials Science' 1984 19 1476 1485 JMTSAS&#xA;loop_&#xA;_citation_author_citation_id&#xA;_citation_author_name&#xA;primary 'Suzuki, R.O.'&#xA;primary 'Osamura, K.'&#xA;_cell_length_a 3.95&#xA;_cell_length_b 3.95&#xA;_cell_length_c 3.95&#xA;_cell_angle_alpha 90.&#xA;_cell_angle_beta 90.&#xA;_cell_angle_gamma 90.&#xA;_cell_volume 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z'&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_oxidation_number&#xA;Au0+ 0&#xA;Pd0+ 0&#xA;Si0+ 0&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_B_iso_or_equiv&#xA;_atom_site_occupancy&#xA;Au1 Au0+ 4 a 0 0 0 . .08&#xA;Pd1 Pd0+ 4 a 0 0 0 . .74&#xA;Si1 Si0+ 4 a 0 0 0 . .18&#xA;#End of TTdata_108005-ICSD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2020-12-11T18:43:43.860" LastActivityDate="2020-12-11T18:43:43.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3929" PostTypeId="2" ParentId="3892" CreationDate="2020-12-11T19:47:24.000" Score="16" Body="&lt;p&gt;This is an important question, and I will do my best to answer it in a way that adds to the nice suggestions made in earlier answers.&lt;/p&gt;&#xA;&lt;p&gt;In short, the answer is yes, but only with the help of some other models and approaches. In this response, I will focus on the conventional (computational) approach to this question, using lattice models and Monte Carlo Methods.&lt;/p&gt;&#xA;&lt;p&gt;This approach, generally speaking, involves running a series of spin-polarized DFT calculations for different magnetic configurations. The next step is to map the results of these calculations (total energies and/or electronic structure) to a lattice model. There a two main ways to do this, which I touch on below. The transition temperature (Curie temperature for ferromagnets) can then be identified by running Monte Carlo (MC) simulations on this lattice model, and observing at what temperature your order parameter (in this case total magnetization) goes to zero (paramagnetic transition), or heat capacity &amp;quot;spikes,&amp;quot; etc... The VAMPIRE documentation for this is included here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://vampire.york.ac.uk/tutorials/curie-temperature-simulation/&quot; rel=&quot;noreferrer&quot;&gt;https://vampire.york.ac.uk/tutorials/curie-temperature-simulation/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In theory, you could perform MC runs with DFT energy evaluations. However, practically speaking the lattice model provides a cheap alternative to exploring the magnetic configuration space of your system.&lt;/p&gt;&#xA;&lt;p&gt;I encourage you explore the magnetic exchange workflow recently implemented in &lt;em&gt;atomate&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://atomate.org/atomate.vasp.workflows.base.html#module-atomate.vasp.workflows.base.exchange&quot; rel=&quot;noreferrer&quot;&gt;https://atomate.org/atomate.vasp.workflows.base.html#module-atomate.vasp.workflows.base.exchange&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;which calculates the parameters of a lattice model from DFT energies (using &lt;em&gt;pymatgen&lt;/em&gt; functions linked below), and estimates the transition temperature using the MC method implemented in the VAMPIRE code suite (suggested in a previous answer).&lt;/p&gt;&#xA;&lt;p&gt;The workflow calls the Heisenberg model mapper implemented in &lt;em&gt;pymatgen&lt;/em&gt;:&#xA;&lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.magnetism.heisenberg.html&quot; rel=&quot;noreferrer&quot;&gt;https://pymatgen.org/pymatgen.analysis.magnetism.heisenberg.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Some more details&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the lattice picture, the energy of arrangements of different spins can be calculated in a relatively straightforward way using the effective Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{H} = - \sum_{\langle i,j \rangle} J_{ij} \delta_{ij} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the sum is over all pairwise interactions between sites (the pair of sites &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; is indicated by &lt;span class=&quot;math-container&quot;&gt;$\langle i,j \rangle$&lt;/span&gt;). In the &lt;a href=&quot;https://en.wikipedia.org/wiki/Ising_model&quot; rel=&quot;noreferrer&quot;&gt;Ising&lt;/a&gt; picture, &lt;span class=&quot;math-container&quot;&gt;$\delta_{ij} = \sigma_i \sigma_j$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$\sigma_k = \pm 1$&lt;/span&gt; indicates the up/down spin state at site &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;). In the &lt;a href=&quot;https://en.wikipedia.org/wiki/Classical_Heisenberg_model&quot; rel=&quot;noreferrer&quot;&gt;classical Heisenberg&lt;/a&gt; picture, &lt;span class=&quot;math-container&quot;&gt;$\delta_{ij} = \vec{s}_i \cdot \vec{s}_j$&lt;/span&gt; (the dot product between spins represented as vectors in 3D space).&lt;/p&gt;&#xA;&lt;p&gt;One way to calculate &lt;span class=&quot;math-container&quot;&gt;$J_{ij}$&lt;/span&gt; values from DFT using the &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0304885386903367&quot; rel=&quot;noreferrer&quot;&gt;KKR-Green's function method&lt;/a&gt;, another is by solving a matrix vector system (implemented in the &lt;em&gt;atomate&lt;/em&gt; workflow). For a physical intuition behind these exchange interaction values, I suggest referring to a book in solid state physics/chemistry, such as the well known text by Ashcroft and Mermin.&lt;/p&gt;&#xA;&lt;p&gt;Famous examples of these lattice models include Ising and Heisenberg (both &amp;quot;classical&amp;quot; and &amp;quot;quantum&amp;quot; formulations). However, there are many more, such as the Potts and XY models. Theorists have studied these models extensively for years. Despite the simplicity of these models compared to density functional theory approaches, these lattice models are able to capture the physics relevant to the order-to-disorder (ordered to paramagnetic) phase transition in magnets.&lt;/p&gt;&#xA;&lt;p&gt;Common assumptions underlying these models include the approximation that each atom has an effective &amp;quot;spin&amp;quot; or magnetic moment on each atom. This assumption is reasonable for many systems with &amp;quot;localized&amp;quot; moments - more on some of the major limitations of this simplification &lt;a href=&quot;https://en.wikipedia.org/wiki/Exchange_interaction#Limitations_of_the_Heisenberg_Hamiltonian_and_the_localized_electron_model_in_solids&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Alternatively, there are other approaches that include &amp;quot;higher order&amp;quot; expansions to the free energy of your system using &amp;quot;cluster expansion&amp;quot; or &amp;quot;cluster multipole expansion,&amp;quot; however, I will not focus on those approaches here.&lt;/p&gt;&#xA;&lt;p&gt;I am currently working on extending this mapping to include the effect of atomic displacements in the model, in addition to magnetic interactions. These spin-lattice (magnon-phonon) coupling effects have been shown to also shift the phase transition temperature. I've run out of allowed references, however, if your curious, search for &amp;quot;compressible Heisenberg/Ising,&amp;quot; &amp;quot;spin-lattice coupling Hamiltonian,&amp;quot; or &amp;quot;Bean-Rodbell&amp;quot; model.&lt;/p&gt;&#xA;&lt;p&gt;A helpful lesson that I've learned is that it's important to be aware of the assumptions of different lattice models, and understanding the relevant physics that we want to capture. As the famous saying goes:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;All models are wrong but some are useful.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="1694" LastEditorUserId="1694" LastEditDate="2020-12-11T19:56:57.170" LastActivityDate="2020-12-11T19:56:57.170" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3930" PostTypeId="1" AcceptedAnswerId="3931" CreationDate="2020-12-13T04:28:28.903" Score="18" ViewCount="1819" Body="&lt;p&gt;Consider a zero-field Ising model with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; spins and periodic boundary conditions, with the Hamiltonian given by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H = -K \sum _{(ij)} s_i s_j\tag{1}$$&lt;/span&gt;&#xA;in 1D and 2D, where &lt;span class=&quot;math-container&quot;&gt;$K = \frac{J}{k_BT}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is the coupling constant energy. If I run a Monte Carlo simulation with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; particles with Metropolis sampling, &lt;strong&gt;how do I spot the critical &lt;span class=&quot;math-container&quot;&gt;$K_c$&lt;/span&gt; value?&lt;/strong&gt; Onsager's solution in 2D predicted a critical point at &lt;span class=&quot;math-container&quot;&gt;$K_c = 0.4406868$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, when I run a simulation with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; particles and I track the Hamiltonian per particle &lt;span class=&quot;math-container&quot;&gt;$(H/N)$&lt;/span&gt; and the magnetization per particle &lt;span class=&quot;math-container&quot;&gt;$\left(\sum _i s_i /N\right)$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; values going from &lt;span class=&quot;math-container&quot;&gt;$0.1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$0.7$&lt;/span&gt; in increments of &lt;span class=&quot;math-container&quot;&gt;$0.1$&lt;/span&gt;, how do I spot the region of the critical coupling constant?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There has to be a signature of the critical point that is stronger when &lt;span class=&quot;math-container&quot;&gt;$K=0.4$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K=0.5$&lt;/span&gt; that should lead me to think that the critical value of &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is between these two numbers, right?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2020-12-14T20:22:50.527" LastActivityDate="2020-12-17T05:33:59.153" Title="Ising model: How can I spot the critical point?" Tags="|magnetism|model-hamiltonians|ising-model|spin-models|phase-transitions|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3931" PostTypeId="2" ParentId="3930" CreationDate="2020-12-14T00:43:08.340" Score="17" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, when I run a simulation with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; particles and I track the Hamiltonian per particle &lt;span class=&quot;math-container&quot;&gt;$(H/N)$&lt;/span&gt; and the magnetization per particle &lt;span class=&quot;math-container&quot;&gt;$\left(\sum _i s_i /N\right)$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; values going from &lt;span class=&quot;math-container&quot;&gt;$0.1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$0.7$&lt;/span&gt; in increments of &lt;span class=&quot;math-container&quot;&gt;$0.1$&lt;/span&gt;, how do I spot the region of the critical coupling constant?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There has to be a signature of the critical point that is stronger when &lt;span class=&quot;math-container&quot;&gt;$K=0.4$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K=0.5$&lt;/span&gt; that should lead me to think that the critical value of &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is between these two numbers, right?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The thermal phase transition in the 2D Ising model is of continuous nature, meaning among other things that the magnetization per particle,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{M}{N} = \left| \frac{\sum_i s_i}{N} \right| \propto \left( T_\mathrm{c} - T \right)^\beta,\quad T&amp;lt;T_\mathrm{c},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\beta=1/8$&lt;/span&gt; in 2D, and &lt;span class=&quot;math-container&quot;&gt;$M/N=0$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$T&amp;gt;T_\mathrm{c}$&lt;/span&gt;. In other words, it decays continuously as the critical temperature is approached from below (which corresponds to reducing &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;). You can set a threshold (e.g. machine precision) and look for the phase transition this way (e.g. using a binary search), but it is an imprecise method. A much sharper signature is found in the specific heat, &lt;span class=&quot;math-container&quot;&gt;$C_V=\partial E/\partial T$&lt;/span&gt;, which (in 2D) diverges logarithmically as &lt;span class=&quot;math-container&quot;&gt;$T\rightarrow T_\mathrm{c}$&lt;/span&gt;. Generally, it is useful to look also at such derivatives (higher order derivatives of the free energy) when studying transitions. In the presence of a field, the magnetic susceptibility is useful, for example.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Also, what is the criticality condition for 1 dimension?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Actually, the 1D Ising chain in zero field does not have a finite-temperature phase transition. Instead it's disordered at all finite temperatures. However, there exists a critical point at &lt;span class=&quot;math-container&quot;&gt;$T=0$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2020-12-14T00:43:08.340" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3932" PostTypeId="2" ParentId="3849" CreationDate="2020-12-14T06:58:52.623" Score="7" Body="&lt;p&gt;Probably one of the important applications is Computer Aided Drug Discovery (CADD). If the protein structure could be accurately predicted, one could design protein-ligand docking on the binding pockets and run molecule dynamics simulations.&lt;/p&gt;&#xA;&lt;p&gt;In the lead identification process of a CADD, the starting point is normally be the experimental data for the crystal structure of a protein and structural based virtual screening is conducted based on the protein structure to search for hits (or potential lead compounds) for the receptor (the protein). In this process, the resolution of the experimental data could directly affect the quality of structural based virtual screen. In the case when the high resolution protein structure is not available, if one could predict the protein structure computationally, it would improve the result of structural based virtual screening.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="141" LastEditDate="2021-03-02T07:19:34.743" LastActivityDate="2021-03-02T07:19:34.743" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3933" PostTypeId="2" ParentId="3930" CreationDate="2020-12-14T15:11:10.543" Score="14" Body="&lt;p&gt;As &lt;strong&gt;Anyon&lt;/strong&gt; correctly pointed out, there is no phase transition at finite temperature in 1D.&lt;/p&gt;&#xA;&lt;p&gt;In 2D there are a number of different ways to identify the phase transition (I'm assuming you're using Monte Carlo). You &lt;strong&gt;could&lt;/strong&gt; directly look at the magnetization, but a more reliable signature is the &lt;strong&gt;magnetic susceptibility,&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$\chi_m (K)$&lt;/span&gt;, which is &lt;strong&gt;strongly peaked&lt;/strong&gt; around &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; (the same is true for the specific heat). This is a much stronger signal.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; can be described by a partial derivative w.r.t. the field, but a more useful way to measure it is in terms of the &lt;em&gt;fluctuations&lt;/em&gt; in the magnetization:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi = \frac{d \langle m \rangle}{dh} \Big|_{h\to 0} = \frac{N}{kT} \left( \langle m^2 \rangle - \langle | m |\rangle^2 \right) \tag{1}$$&lt;/span&gt;&#xA;Using this definition avoids the need for numerical derivatives (there is a similar trick for the specific heat). This method is described on p. 34 of &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;noreferrer&quot;&gt;this excellent review article by Sandvik.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;But,&lt;/strong&gt; any simulation is at &lt;strong&gt;finite size&lt;/strong&gt;. To make an even &lt;em&gt;more precise&lt;/em&gt; measurement, you could take advantage of &lt;strong&gt;finite-size scaling&lt;/strong&gt;, which allows you use the finite-size effects to determine the &lt;span class=&quot;math-container&quot;&gt;$L\to\infty$&lt;/span&gt; transition point. Using the critical exponents (which are known), you can collapse &lt;span class=&quot;math-container&quot;&gt;$\chi(T,L)$&lt;/span&gt; curves onto a single rescaled&#xA;&lt;span class=&quot;math-container&quot;&gt;$$L^{-\kappa/\nu} \chi(T,L) = t L^{1/\nu} \tag{2}$$&lt;/span&gt;&#xA;(using the reduced temperature &lt;span class=&quot;math-container&quot;&gt;$t \equiv \frac{T-T_c}{T_c}$&lt;/span&gt;). For a full description of this approach, see &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;noreferrer&quot;&gt;Sandvik arXiv:1101.3281, p. 35.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Yuapn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Yuapn.png&quot; alt=&quot;Finite size scaling collapse of the Ising model, from Sandvik arXiv&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2020-12-14T20:11:25.587" LastActivityDate="2020-12-14T20:11:25.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3934" PostTypeId="1" AcceptedAnswerId="3946" CreationDate="2020-12-14T18:54:02.923" Score="11" ViewCount="1013" Body="&lt;p&gt;In the Hartree method, it is known that the wavefunction of the system does not obey the antisymmetry principle of fermions - that is when you swap two particles, they don't up a negative sign. Therefore, electrons are filled by making sure that Pauli's exclusion principle is obeyed in every step. A Slater determinant is considered to be an improvement because it does satisfy the many-body antisymmetry nature of fermions, and often takes the form (for say, a 2 particle system):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{aligned}\Psi (\mathbf {x} _{1},\mathbf {x} _{2})&amp;amp;={\frac {1}{\sqrt {2}}}\{\chi _{1}(\mathbf {x} _{1})\chi _{2}(\mathbf {x} _{2})-\chi _{1}(\mathbf {x} _{2})\chi _{2}(\mathbf {x} _{1})\}\\&amp;amp;={\frac {1}{\sqrt {2}}}{\begin{vmatrix}\chi _{1}(\mathbf {x} _{1})&amp;amp;\chi _{2}(\mathbf {x} _{1})\\\chi _{1}(\mathbf {x} _{2})&amp;amp;\chi _{2}(\mathbf {x} _{2})\end{vmatrix}}\end{aligned}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, are Slater determinants found in practice in Kohn-Sham Density Functional theory?&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2020-12-16T21:25:52.277" LastActivityDate="2020-12-16T21:25:52.277" Title="Does Kohn-Sham DFT use Slater determinants?" Tags="|density-functional-theory|hartree-fock|kohn-sham|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3935" PostTypeId="2" ParentId="3934" CreationDate="2020-12-14T19:16:02.830" Score="7" Body="&lt;p&gt;From the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kohn%E2%80%93Sham_equations&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia article on Kohn-Sham equations&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;As the particles in the Kohn–Sham system are non-interacting&#xA;fermions, the Kohn–Sham wavefunction is a single &lt;em&gt;&lt;strong&gt;Slater determinant&lt;/strong&gt;&lt;/em&gt;&#xA;constructed from a set of orbitals.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So the answer to your question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Are slater determinants found in practice in Kohn-Sham Density&#xA;Functional theory?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is yes.&lt;br&gt;&#xA;Other users that have a deeper knowledge of DFT than me might tell you more!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-14T19:51:10.067" LastActivityDate="2020-12-14T19:51:10.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3936" PostTypeId="1" CreationDate="2020-12-14T20:06:29.817" Score="8" ViewCount="139" Body="&lt;p&gt;Apart from using &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1444/5&quot;&gt;Bader charge analysis&lt;/a&gt; or energy of formation estimation, I wonder if there is a way to compute the bond energy of constituent bonds in a crystal using density functional theory.&lt;/p&gt;&#xA;&lt;p&gt;Let's say I have a disordered &lt;span class=&quot;math-container&quot;&gt;$AB$&lt;/span&gt; crystal. There could be multiple possible arrangements of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; given the disorder, thereby resulting in many possible supercells. Is it possible to find the bond strength for each bond in one such supercell?&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-06-22T01:06:49.560" LastActivityDate="2021-06-22T01:06:49.560" Title="Can we calculate bond enthalpies for each bond in a supercell of a disordered AB crystal using DFT?" Tags="|density-functional-theory|crystal-structure|crystallography|solid-state-physics|disorder|" AnswerCount="0" CommentCount="6" ClosedDate="2021-11-19T01:37:42.303" ContentLicense="CC BY-SA 4.0" />
  <row Id="3937" PostTypeId="2" ParentId="3816" CreationDate="2020-12-14T20:15:06.227" Score="2" Body="&lt;p&gt;As mentioned in the previous answer and comments, choosing the correct number of processors depends on several factors. Quantum ESPRESSO has several levels of parallelization, that can be used accordingly to the system being simulated.&lt;/p&gt;&#xA;&lt;p&gt;Matching the k-points sampling with the number of pools, for example, tends to decrease the calculation times. The convergence thresholds can also play an important role in the calculation times, and the number of processors can speed up the simulation or even get it worst.&lt;/p&gt;&#xA;&lt;p&gt;Since band structure and Dos calculation rely on pw.x package, from the pw.x user &lt;a href=&quot;https://www.quantum-espresso.org/Doc/pw_user_guide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;guide&lt;/a&gt; we have:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;pw.x can run in principle on any number of processors. The effectiveness of parallelization is ultimately judged by the ”scaling”, i.e. how the time needed to perform a job scales with the number of processors, and depends upon:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the size and type of the system under study;&lt;/li&gt;&#xA;&lt;li&gt;the judicious choice of the various levels of parallelization (detailed in Sec.4.4);&lt;/li&gt;&#xA;&lt;li&gt;the availability of fast interprocess communications (or lack of it).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Ideally one would like to have linear scaling,  i.e. T ∼  T0/Np for Np processors,  where T0 is the estimated time for serial execution.  In addition,  one would like to have linear scaling of the RAM per processor: ON ∼ O0/Np, so that large-memory systems fit into the RAM of each processor. Parallelization on k-points:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;guarantees (almost) linear scaling if the number of k-points is a multiple of the number of pools;&lt;/li&gt;&#xA;&lt;li&gt;requires little communications (suitable for ethernet communications);&lt;/li&gt;&#xA;&lt;li&gt;reduces the required memory per processor by distributing wavefunctions (but not other quantities like the charge density), unless you setdiskio=’high’.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Parallelization on PWs:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;yields  good  to  very  good  scaling,  especially  if  the  number  of  processors  in  a  pool  is  a divisor of N3 and Nr3(the dimensions along the z-axis of the FFT grids,nr3 and nr3s, which coincide for NCPPs);&lt;/li&gt;&#xA;&lt;li&gt;requires heavy communications (suitable for Gigabit ethernet up to 4, 8 CPUs at most,specialized communication hardware needed for 8 or more processors);&lt;/li&gt;&#xA;&lt;li&gt;yields almost linear reduction of memory per processor with the number of processors in the pool.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A note on scaling:  optimal serial performances are achieved when the data are as much as possible kept into the cache.  As a side effect, PW parallelization may yield superlinear (better than linear) scaling, thanks to the increase in serial speed coming from the reduction of datasize (making it easier for the machine to keep data in the cache).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;VERY IMPORTANT: For each system there is an optimal range of number of processors on which to run the job.  A too large number of processors will yield performance degradation.  If the size of pools is especially delicate: Np should not exceed N3 and Nr3, and should ideally be no larger than 1/2÷1/4 N3 and/or Nr3.  In order to increase scalability, it is often convenient to further subdivide a pool of processors into ”task groups”.  When the number of processors exceeds the number of FFT planes,  data can be redistributed to ”task groups” so that each group can process several wavefunctions at the same time. The optimal number of processors for ”linear-algebra” parallelization, taking care of multiplication  and  diagonalization  of M×M matrices,  should  be  determined  by  observing  the performances of cdiagh/rdiagh(pw.x) orortho(cp.x) for different numbers of processors inthe linear-algebra group (must be a square integer).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Those are general guidelines for the choice of the parallelization levels. Therefore some effort has to be applied to optimize the number of processors against the structure to be evaluated. With the time performing the simulation some feeling is acquired, easing the process.&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="389" LastEditDate="2020-12-14T20:47:14.103" LastActivityDate="2020-12-14T20:47:14.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3938" PostTypeId="2" ParentId="90" CreationDate="2020-12-14T20:45:34.680" Score="3" Body="&lt;p&gt;There are two different perspectives here. The first one is the creation of the SQS structure itself accomplished through the ATAT package, for example. The second one is the calculation of the slab properties.&lt;/p&gt;&#xA;&lt;p&gt;The SQS procedure returns the smaller structure that resembles the periodic structure properties. For alloys, for instance, the inputs are the concentrations, the preferred lattice symmetry, if any, and the length of the neighbors' interactions. We can also specify the desired quantity of atoms within the unit cell (not always preserved by the code). The resulting structure can be passed to the DFT (periodic) simulation.&lt;/p&gt;&#xA;&lt;p&gt;To perform the slab simulation, we need to add the vacuum in the desired direction. We can also repeat the structure making a supercell and perform a cleave to the desired plane.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2020-12-14T20:45:34.680" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3939" PostTypeId="2" ParentId="3912" CreationDate="2020-12-14T21:53:59.867" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;In the experimental section, they write that they cut conformers after a second optimization after the scan for conformers by a few values. The take from the twenty structures they get only those with energies up to 0.59 kcal/mol. This should be a limit of conformational stability at 300 K. But they don't cite a reference for this fact. Is this something everybody knows through their academic education?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is a hand-waving argument. If you calculate what is &lt;span class=&quot;math-container&quot;&gt;$k_B T$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$T=$&lt;/span&gt;300 K in units of cal/mol, you'll find the value &lt;span class=&quot;math-container&quot;&gt;$k_B T \approx$&lt;/span&gt; 595.762 cal, which rounds to 0.60 kcal/mol.&lt;/p&gt;&#xA;&lt;p&gt;But, there are some problems with this argument. First, the intrinsic error in DFT (especially M06-2X/6-311++G** as used in the paper!) is likely much larger. I think usually one would choose a much higher threshold, something like 3-5 kcal/mol, to screen out conformers from DFT for running more accurate calculations on them. M06-2X also has no dispersion; I would dispersion corrections might be significant for conformer energies.&lt;/p&gt;&#xA;&lt;p&gt;Of course, it is not the electronic energy but the free energy which is relevant, so the entropy term also plays an effect.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I taught Gaussian myself, and I read in the Gaussian manual that a stable conformed is a minimum of the potential energy surface (PES). In the paper 1, they show structures that look not like the PES minimum. Is it possible in reason of these cut-off values that the stable conformer is not automatically the minimum?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If I understand correctly, you've done a geometry optimization for imidacloprid. Geometry optimizations (like many other optimizations) typically converge onto the closest local minimum. However, the issue with conformers is that their number increases rapidly with the size of the molecule, and several of them may be thermodynamically accessible. For instance, melatonin has 52 unique conformers, see the study by Fogueri, Kozuch, Karton and Martin in &lt;a href=&quot;https://doi.org/10.1021/jp312644t&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A 117, 2269 ( 2013)&lt;/a&gt;. Locating all the conformers is a global optimization problem, which is difficult, since size of the solution space grows rapidly with the size of the system. To find the conformers, you need to scan over all the dihedral angles, in principle.&lt;/p&gt;&#xA;&lt;p&gt;Let's say you want to do find the global minimum conformer. If you scan the angles in steps of &lt;span class=&quot;math-container&quot;&gt;$30^\circ$&lt;/span&gt; as in the paper (I'm not sure if this is small enough for all systems), to go from &lt;span class=&quot;math-container&quot;&gt;$0^\circ$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$360^\circ$&lt;/span&gt; you need 12 steps, but since &lt;span class=&quot;math-container&quot;&gt;$0^\circ=360^\circ$&lt;/span&gt;, there are only &lt;span class=&quot;math-container&quot;&gt;$N=11$&lt;/span&gt; unique angles. This means that your procedure would be&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;scanning over all dihedral angles: &lt;span class=&quot;math-container&quot;&gt;$N=11$&lt;/span&gt; calculations&lt;/li&gt;&#xA;&lt;li&gt;scan over all pairs of dihedral angles: &lt;span class=&quot;math-container&quot;&gt;$N^2 = 121$&lt;/span&gt; calculations&lt;/li&gt;&#xA;&lt;li&gt;scan over all triplets of dihedral angles : &lt;span class=&quot;math-container&quot;&gt;$N^3 = 1331$&lt;/span&gt; calculations&lt;/li&gt;&#xA;&lt;li&gt;scan over all quartets of dihedral angles : &lt;span class=&quot;math-container&quot;&gt;$N^4 = 14641$&lt;/span&gt; calculations&lt;/li&gt;&#xA;&lt;li&gt;scan over all quintets of dihedral angles : &lt;span class=&quot;math-container&quot;&gt;$N^5 = 161051$&lt;/span&gt; calculations&lt;/li&gt;&#xA;&lt;li&gt;etc&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If you're lucky, you can safely truncate the procedure at a small number of simultaneous dihedral changes. Otherwise you may not find the global minimum. Still, my colleagues in the chemical industry tell me that doing conformational analysis is really important for chemistry.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2020-12-15T04:27:20.640" LastActivityDate="2020-12-15T04:27:20.640" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3940" PostTypeId="2" ParentId="90" CreationDate="2020-12-14T22:52:20.437" Score="1" Body="&lt;p&gt;As Anibal points in his answer, generating the SQS and using it for a surface calculation are two separate things, and shouldn't affect each other. You would still take all precautions as usual while performing the DFT calculation.&lt;/p&gt;&#xA;&lt;p&gt;That being said, there could be scenarios where you may want to restrict/prefer certain atom types amassing at edges or corners of the surface. A friend who studied cutting tools, and materials like diamond or silica used thereof, was very peculiar about atomically uniform edges. As always, it's all system dependent. Let your intuition roll!&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2020-12-15T07:53:25.957" LastActivityDate="2020-12-15T07:53:25.957" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3941" PostTypeId="2" ParentId="3930" CreationDate="2020-12-15T01:22:14.793" Score="8" Body="&lt;p&gt;I think Anyon's and taciteloquence's answers are perfect. I just want to add an emphasis on the following fact that frequently leads to confusion for beginners.&lt;/p&gt;&#xA;&lt;p&gt;The formal definition of the magnetization&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;m = \frac{\sum_i s_i}{N}&#xA;\end{equation}&lt;/span&gt;&#xA;has a symmetry that &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Prob}[m=+m_0]=\mathrm{Prob}[m=-m_0]$&lt;/span&gt;, since the energy of a particular configuration and a totally flipped version will have exactly the same energy. Therefore, &lt;span class=&quot;math-container&quot;&gt;$\langle m\rangle =0$&lt;/span&gt; for &lt;em&gt;&lt;strong&gt;all&lt;/strong&gt;&lt;/em&gt; temperature for a finite system. Only in an infinite system (thermodynamic limit) can this symmetry be broken, which is called spontaneous symmetry breaking.&lt;/p&gt;&#xA;&lt;p&gt;In principle, if you manage to correctly calculate the expectation value &lt;span class=&quot;math-container&quot;&gt;$\langle m\rangle$&lt;/span&gt;, it will always be 0, but when you are running for only a short time with a large system, the Monte Carlo simulation can be trapped in one side of the two macro states (corresponding to &lt;span class=&quot;math-container&quot;&gt;$\langle m\rangle =\pm m_0$&lt;/span&gt;). In order to correctly spot when this starts to happen (i.e. where the transition is), one way is to calculate the expectation value of the absolute magnetization &lt;span class=&quot;math-container&quot;&gt;$\langle |m|\rangle$&lt;/span&gt; as Anyon suggests. As you go to larger system sizes, &lt;span class=&quot;math-container&quot;&gt;$\langle |m|\rangle\rightarrow0$&lt;/span&gt; in the disordered phase, and &lt;span class=&quot;math-container&quot;&gt;$\langle |m|\rangle\rightarrow +m_0$&lt;/span&gt; in the ordered phase. Another way is to calculate the squared value &lt;span class=&quot;math-container&quot;&gt;$\langle m^2\rangle$&lt;/span&gt; also suggested by taciteloquence. This also tends to either &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$m_0^2$&lt;/span&gt; depending on which phase you're in. &lt;span class=&quot;math-container&quot;&gt;$\langle m^2\rangle$&lt;/span&gt; can be more common since it corresponds to the magnetic susceptibility when multiplied by the system volume, thus behaving more nicely.&lt;/p&gt;&#xA;&lt;p&gt;There are also other ways of determining the critical point such as spotting the &amp;quot;crossing point&amp;quot; for the Binder cumulant &lt;span class=&quot;math-container&quot;&gt;$\langle m^4\rangle/\langle m^2\rangle ^2$&lt;/span&gt;, or the correlation ratio &lt;span class=&quot;math-container&quot;&gt;$\xi/L$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, looking at the histogram of the order parameter &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; is always a choice. You measure the probability of the magnetization &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; being a particular value &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;, and do that for all &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;, getting a histogram &lt;span class=&quot;math-container&quot;&gt;$P(m)$&lt;/span&gt; telling you the distribution of possible &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; for a particular temperature. If this distribution is a Gaussian (when the system is large enough) centered at &lt;span class=&quot;math-container&quot;&gt;$m=0$&lt;/span&gt;, then you're in the disordered phase. If it is a combination of two Gaussian distributions centered at &lt;span class=&quot;math-container&quot;&gt;$m=\pm m_0$&lt;/span&gt;, you're in the ordered phase. At the critical point, you have a very broad (non-Gaussian) distribution at the center, barely becoming two separate peaks. All of the common methods I mentioned above are essentially different ways of detecting this &amp;quot;splitting&amp;quot; process of the Gaussian histogram.&lt;/p&gt;&#xA;" OwnerUserId="379" LastEditorUserId="379" LastEditDate="2020-12-17T05:33:59.153" LastActivityDate="2020-12-17T05:33:59.153" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3942" PostTypeId="1" AcceptedAnswerId="4022" CreationDate="2020-12-15T14:53:33.417" Score="27" ViewCount="2548" Body="&lt;p&gt;I'm running a DFT optimization (B3LYP/def2-TZVP) and frequencies in ORCA for a molecule. And I get one or two very small (1-6 cm^-1) imaginary frequencies which corresponds to a slight bend of the molecule.&lt;/p&gt;&#xA;&lt;p&gt;I assume that the frequencies arise from numerical integration errors as they decrease when I run the same calculation with better grid and tighter SCF.&lt;/p&gt;&#xA;&lt;p&gt;So is it appropriate to just leave it as is if I plan to run electronic properties calculation on this geometry with more high-level functional and basis (polarizability, hyperpolarizability, and maybe TD-DFT)?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2020-12-28T03:09:03.727" LastActivityDate="2022-02-16T22:07:13.637" Title="Is it right to neglect very small imaginary frequencies?" Tags="|geometry-optimization|vibrations|spectroscopy|orca|high-precision|" AnswerCount="2" CommentCount="18" ContentLicense="CC BY-SA 4.0" />
  <row Id="3943" PostTypeId="1" CreationDate="2020-12-16T03:51:44.513" Score="7" ViewCount="207" Body="&lt;p&gt;I used VASP as my DFT software to do a calculation on an anti-perovskite crystal. I try to reproduce the band structure from literature which was calculated based on HSE + SOC calculation. &lt;a href=&quot;https://www.researchgate.net/publication/264084992_Topological_Crystalline_Insulators_and_Dirac_Octets_in_Anti-perovskites&quot; rel=&quot;nofollow noreferrer&quot;&gt;Their result was shown below&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/xzX0hm.png&quot; alt=&quot;&quot; /&gt;]&lt;a href=&quot;https://i.stack.imgur.com/H313bm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I try to redo the calculation and plot the band along the same high symmetry line, here is what I got ( My K-point mesh is a bit low, so it may not be so smooth) :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/H313bm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/H313bm.png&quot; alt=&quot;Recalculated band structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It seems that the two graphs are qualitatively the same. But the gap at Gamma point was open up.&#xA;I have no idea what kind of mistake I've made.&#xA;And here is my INCAR setting in my calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; #Calculation Parameter&#xA;&#xA; ISMEAR = 0 ; SIGMA = 0.05&#xA; PREC = Normal&#xA; ENCUT = 350&#xA; ISPIN = 2&#xA; LWAVE = .TRUE.&#xA; LCHARG = .TRUE.&#xA; LSORBIT = .TRUE.&#xA; MAGMOM = 15*0&#xA; SAXIS = 0 0 1&#xA; GGA_COMPAT = .FALSE.&#xA;&#xA;#Electronic Relaxation&#xA;&#xA; EDIFF = 1E-05&#xA; ALGO = Normal&#xA; NELM = 500&#xA;&#xA;#Ionic Relaxation&#xA;&#xA; IBRION = -1&#xA; NSW = 0&#xA;&#xA;#HSE06&#xA;&#xA; LHFCALC = .TRUE.&#xA; HFSCREEN = 0.2&#xA; ALGO = Damped&#xA; TIME = 0.4&#xA; #AEXX = 0.25&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-10-30T20:13:33.083" LastActivityDate="2021-10-30T20:13:33.083" Title="The gap was open when I was doing an HSE + SOC DFT calculation" Tags="|density-functional-theory|vasp|band-structure|hse06|" AnswerCount="0" CommentCount="9" ClosedDate="2021-12-13T19:12:35.170" ContentLicense="CC BY-SA 4.0" />
  <row Id="3944" PostTypeId="1" AcceptedAnswerId="6928" CreationDate="2020-12-16T03:53:16.983" Score="17" ViewCount="673" Body="&lt;p&gt;I'm looking to solve quantum system in 1D and 2D consisting of a large number of sites.&lt;/p&gt;&#xA;&lt;p&gt;What are the pros and cons of each package, and which package is more suitable for what type of calculations?&lt;/p&gt;&#xA;&lt;p&gt;Many beginners will be benefit from the answers, and any help in this direction will be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Answers in the format of these examples would be appreciated:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/414/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1053/5&quot;&gt;How to &amp;quot;get my feet wet&amp;quot; in Density Functional Theory by simulating a water molecule using Python&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1215/5&quot;&gt;What software is available to do molecular dynamics on Windows?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1535/5&quot;&gt;What are some open-source all-electron DFT alternatives to Wien2K?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2433/5&quot;&gt;Suggestions for a good crystal structure visualization workflow&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1888/5&quot;&gt;Codes for post-processing Gaussian cube files?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2247/5&quot;&gt;What software can be used to do QTAIM analysis?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1748/5&quot;&gt;Tools for electronic transport calculations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1715" LastEditorUserId="1715" LastEditDate="2021-10-22T13:24:54.547" LastActivityDate="2021-10-23T04:18:58.670" Title="Software for solving quantum systems in 1D and 2D" Tags="|one-topic-per-answer|software-recommendations|condensed-matter|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3945" PostTypeId="1" AcceptedAnswerId="3952" CreationDate="2020-12-16T07:40:41.720" Score="14" ViewCount="310" Body="&lt;p&gt;CP2K implements the Gaussian and Augmented Planewaves (GAPW) approach for all-electron calculations. My understanding is that the GAPW method involves using atom-centered Gaussian type orbitals to represent rapidly varying electron density around nuclei, and planewaves for the electron density in the slowly varying interstitial regions.&lt;/p&gt;&#xA;&lt;p&gt;My question is: does use of the GAPW method mostly eliminate basis set superposition error effects, for example bond length contraction during optimization? I would think so, since the core regions probably will not overlap in most systems, but I may be misunderstanding how GAPW works.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="5" LastEditDate="2020-12-16T23:52:23.273" LastActivityDate="2020-12-17T22:35:58.743" Title="Is basis set superposition error reduced when using the GAPW method?" Tags="|basis-sets|cp2k|plane-waves|projector-augmented-wave|basis-set-superposition-error|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3946" PostTypeId="2" ParentId="3934" CreationDate="2020-12-16T15:59:27.833" Score="8" Body="&lt;p&gt;As Nike has already mentioned, Slater determinants occur in KS-DFT in much the same way that they do in Hartree-Fock as a way to combine a set of one-electron orbitals into an antisymmetric many-electron wavefunction. However in DFT, as the name suggests, we are typically more interested in the density. The Hohenberg-Kohn theorems show that DFT can, in principle, produce the exact ground state density and the density is used to compute various molecular properties.&lt;/p&gt;&#xA;&lt;p&gt;So why might we care about the wavefunction in DFT? In the limit of a complete basis set, it has been proven that the DFT density constructed from a single Slater determinant can reproduce exactly the density of a multideterminant method like Configuration Interaction. It is noteworthy that systems which seem to require a multideterminant description can in some sense be represented exactly with just a single Slater determinant.&lt;/p&gt;&#xA;&lt;p&gt;A recent paper [1] by Frank Jensen explored how this manifests in practice by trying to fit the density of finite basis full CI calculations using a DFT density constructed from orthogonal orbitals. While the end goal is reproducing the density, the interesting thing about it is that it shows that even for a sufficiently large finite basis, a single Slater determinant should suffice as the &amp;quot;square root of the density&amp;quot;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Philip Jakobsen and Frank Jensen &lt;em&gt;Representing Exact Electron Densities by a Single Slater Determinant in Finite Basis Sets&lt;/em&gt; J. Chem. Theory Comput. 2020, XXXX, XXX, XXX-XXX DOI: 10.1021/acs.jctc.0c01029&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2020-12-16T20:38:50.040" LastActivityDate="2020-12-16T20:38:50.040" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3947" PostTypeId="2" ParentId="3944" CreationDate="2020-12-16T16:15:47.340" Score="10" Body="&lt;p&gt;Note: This answer was written when the question was specifically about exact diagonalization codes. In an ED context, &amp;quot;a large number of spin sites&amp;quot; would maybe mean somewhere in the 24-40 range (maybe slightly more if really pushing the envelope, fewer for &lt;span class=&quot;math-container&quot;&gt;$t-J$&lt;/span&gt; and Hubbard models) since the Hilbert space grows exponentially. If one is looking to solve problems with larger numbers of sites than that, it's better to look to other computational methods like DMRG or QMC.&lt;/p&gt;&#xA;&lt;h2&gt;QuSpin&lt;/h2&gt;&#xA;&lt;p&gt;QuSpin is an open-source Python code that can do exact diagonalization of spin, fermion, and boson systems. It has a wide support for use of symmetries, constrained Hilbert spaces, various models, and time evolution. The combination of fairly simple Python syntax and a large number of tutorials make it a great choice for beginners, for small-scale experimentation, and time-evolution problems in many-body systems. However, the &lt;a href=&quot;https://weinbe58.github.io/QuSpin/parallelization.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;parallelization options&lt;/a&gt; are limited. As far as I know, as of v. 0.3.6 QuSpin only supports on-node parallelization through OpenMP and MKL. Thus QuSpin is typically not the best choice if you want to reach the largest systems. In addition, QuSpin seems to currently lack built-in support for dynamical correlation functions, which is of interest to modeling inelastic experiments.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Project on GitHub: &lt;a href=&quot;https://weinbe58.github.io/QuSpin/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://weinbe58.github.io/QuSpin/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Introducing paper: &lt;a href=&quot;https://scipost.org/SciPostPhys.2.1.003&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phillip Weinberg, and Marin Bukov, &lt;em&gt;QuSpin: a Python package for dynamics and exact diagonalisation of quantum many body systems part I: spin chains&lt;/em&gt;, SciPost Phys. &lt;strong&gt;2&lt;/strong&gt;, 003 (2017)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Follow-up paper: &lt;a href=&quot;https://scipost.org/SciPostPhys.7.2.020&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phillip Weinberg, and Marin Bukov, &lt;em&gt;QuSpin: a Python package for dynamics and exact diagonalisation of quantum many body systems. Part II: bosons, fermions and higher spins&lt;/em&gt;, SciPost Phys. &lt;strong&gt;7&lt;/strong&gt;, 020 (2019)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2021-10-08T01:34:03.290" LastActivityDate="2021-10-08T01:34:03.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3948" PostTypeId="2" ParentId="3934" CreationDate="2020-12-16T19:58:01.557" Score="8" Body="&lt;p&gt;A couple of comments perhaps to clarify some points.&lt;/p&gt;&#xA;&lt;p&gt;The first Hohenberg-Kohn theorem states that the one-electron density determines uniquely the energy, for a non-degenerate ground state. The second H-K theorem states that this density can be obtained by employing the variational principle, i.e. the density is obtained by minimizing the energy as a functional of a trial density. If the exact functional was known, this would give the exact density. BUT, the density MUST come from a proper antisymmetric wave function, you CANNOT use any freely varying density as your trial. This is known as the representability condition.&lt;/p&gt;&#xA;&lt;p&gt;In the Kohn-Sham version of DFT, this is ensured by parameterizing the density as a sum of orbital contributions, and fulfilling the antisymmetry requirement by placing them in a Slater Determinant with the usual orthonormality conditions for the orbitals.&lt;/p&gt;&#xA;&lt;p&gt;It can be shown that any valid density can be written in the form of a set of orbitals in a single Slater Determinant. This is a mathematical proof, and assumes a complete set of functions, i.e. a complete basis set. This is never fulfilled in practice, and in the above mentioned paper, we investigated how large the basis set should be in order to reduce the error to something like 'chemical accuracy'. The answer is a QZP quality basis set, but also shows that the DFT basis set should be the same as that used for generating the reference exact density. Exact here means exact within the basis set, i.e. full-CI.&lt;/p&gt;&#xA;&lt;p&gt;The mathematical proof thus shows that it should not be necessary to have more than one Slater Determinant in KS-DFT, as any density that can be expressed as arising from a wave function written as a sum of Slater Determinants can be exactly reproduced by a set of KS-orbitals, as long as the basis set is sufficiently large.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2020-12-16T19:58:01.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3949" PostTypeId="1" CreationDate="2020-12-17T03:36:12.563" Score="16" ViewCount="916" Body="&lt;p&gt;I am interested in learning how to do DFT+U calculations and was wondering if anyone has any good recommendations for books or articles.&lt;/p&gt;&#xA;" OwnerUserId="1736" LastEditorUserId="5" LastEditDate="2020-12-17T04:15:23.130" LastActivityDate="2020-12-17T08:29:24.953" Title="Are there any good books to learn how to use DFT+U?" Tags="|density-functional-theory|reference-request|dft-u|dynamical-mean-field-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3950" PostTypeId="2" ParentId="3949" CreationDate="2020-12-17T05:02:35.533" Score="15" Body="&lt;p&gt;I recommend &lt;em&gt;this&lt;/em&gt; as a go-to source now. We have discussed DFT+&lt;em&gt;U&lt;/em&gt; quite  a bit on this very site: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/109/what-is-the-appropriate-way-of-determining-a-value-for-the-hubbard-like-potentia&quot;&gt;GO&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Most modern books that cover DFT now cover DFT+&lt;em&gt;U&lt;/em&gt; as well, as I believe to be the case in &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/1441939547&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;David Singh's book&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Really though, you &lt;em&gt;absolutely need&lt;/em&gt; to check out &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/109/what-is-the-appropriate-way-of-determining-a-value-for-the-hubbard-like-potentia&quot;&gt;Kevin J.M.'s answer&lt;/a&gt;, it is extremely helpful, organized and gives the most relevant resrouces (Cococcioni, Marzari and other giants' works).&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this gets the ball rolling!&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2020-12-17T08:29:24.953" LastActivityDate="2020-12-17T08:29:24.953" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3951" PostTypeId="1" CreationDate="2020-12-17T13:17:46.107" Score="9" ViewCount="245" Body="&lt;p&gt;Consider the following scenario. A material has the E-k band scheme as shown in the figure (extended scheme of zones). Could anyone give me a suggestion regarding the following :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Electrical character of the material with the temperature.&lt;/li&gt;&#xA;&lt;li&gt;Sign of the Hall coefficient.&lt;/li&gt;&#xA;&lt;li&gt;Sign of the effective mass.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Gr9bP.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Gr9bP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the first case (Fermi level is the dotted line that appears for &lt;span class=&quot;math-container&quot;&gt;$E_{1}$&lt;/span&gt;), I have reasoned as follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;As the conduction band is half-full for the Fermi level, we are dealing with a conductive material.&lt;/li&gt;&#xA;&lt;li&gt;The effective mass is a tensor that describes the influence of internal forces on an electron that is subjected to an external force (usually an electric field). The effective mass is inversely proportional to the curvature of the electronic band, so the effective mass is negative.&lt;/li&gt;&#xA;&lt;li&gt;As the effective mass is negative, the Hall's coefficient is positive.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Would it be so?&lt;/p&gt;&#xA;" OwnerUserId="1744" LastEditorUserId="1744" LastEditDate="2020-12-17T16:15:08.733" LastActivityDate="2020-12-18T10:31:29.163" Title="Band theory: effective mass and Hall's coefficient" Tags="|band-structure|effective-mass|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3952" PostTypeId="2" ParentId="3945" CreationDate="2020-12-17T22:35:58.743" Score="9" Body="&lt;p&gt;Short answer: no.&lt;/p&gt;&#xA;&lt;p&gt;The idea of the GAPW method described in &lt;a href=&quot;https://link.springer.com/article/10.1007/s002140050523&quot; rel=&quot;noreferrer&quot;&gt;Theor. Chem. Acc. 103, 124 (1999)&lt;/a&gt; is simply to speed up the evaluation of the Coulomb and exchange-correlation contributions. Quoting from the conclusions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Starting from the GPW approach we substituted the PW auxiliary basis for the electron density by an&#xA;APW auxiliary basis which besides plane waves relies on&#xA;Gaussians. Therefore, the electron density, the XC&#xA;potential, and the Coulomb potential can be separated&#xA;into a smooth nonlocal contribution expanded in PW&#xA;and local contributions that can be described in&#xA;Gaussians and which can thus be treated analytically.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Füsti-Molnar and coworkers have pursued similar approaches also for molecules, see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.1467901&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 116, 7795 (2002)&lt;/a&gt;, &lt;a href=&quot;https://doi.org/10.1063/1.1849168&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 122, 074108 (2005)&lt;/a&gt;,  &lt;a href=&quot;https://doi.org/10.1063/1.1510121&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 117, 7827 (2002)&lt;/a&gt;, andn &lt;a href=&quot;https://doi.org/10.1063/1.1622922&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 119, 11080 (2003)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would also like to point out here that if one is pursuing periodic calculations with Gaussian basis sets, the basis functions are not really Gaussian anymore since one is actually using Bloch functions &lt;span class=&quot;math-container&quot;&gt;$\chi_\mu ({\bf k};{\bf r}) = \sum_{\bf g} \chi_\mu ({\bf r}-{\bf g}) \exp(i {\bf k} \cdot {\bf r})$&lt;/span&gt;, see e.g. the book by Pisani, Dovesi, and Roetti,  &lt;a href=&quot;https://link.springer.com/book/10.1007/978-3-642-93385-1&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1007/978-3-642-93385-1&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2020-12-17T22:35:58.743" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3953" PostTypeId="1" AcceptedAnswerId="3958" CreationDate="2020-12-17T22:55:11.930" Score="10" ViewCount="1738" Body="&lt;p&gt;Recently, I came across electron correlation methods that use local pair natural orbitals (LPNOs) or domain-based local pair natural orbitals (DLPNO), such as DLPNO-MP2, DLPNO-CCSD etc. The dynamic electron correlation is constrained to local areas and it reduces the computational cost. I tried to look at some papers such as &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S2210271X20302346&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; one, but I can't figure out what the PNOs actually are (or what they mean physically).&lt;/p&gt;&#xA;&lt;p&gt;So, what are these PNOs? How are they different to the usual orbital localization schemes such as Ruedenberg, Pipek-Mezey? And most importantly, why are they used for correlation calculation? It would help if the answer is explained in simple words, I am not much of a theoretician!&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2020-12-19T17:04:05.220" LastActivityDate="2020-12-19T17:04:05.220" Title="What are Pair Natural Orbitals?" Tags="|computational-chemistry|orca|coupled-cluster|electron-correlation|mrcc|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3954" PostTypeId="2" ParentId="3758" CreationDate="2020-12-18T04:15:49.890" Score="4" Body="&lt;p&gt;After a bit of hit and trial, I am able to run the pyridine sample, using CP2K v7.0 &lt;code&gt;(git:d15a9c53f)&lt;/code&gt;, however I think this can be run on any CP2K version beyond v2.5. The modified file is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  &amp;amp;FORCE_EVAL&#xA;  METHOD QUICKSTEP&#xA;  &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME ./BASIS_SET&#xA;    POTENTIAL_FILE_NAME ./GTH_POTENTIALS&#xA;    &amp;amp;QS&#xA;       EPS_DEFAULT 1E-10&#xA;    &amp;amp;END QS&#xA;    &amp;amp;MGRID&#xA;      CUTOFF 400&#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;SCF&#xA;      MAX_SCF  20&#xA;      EPS_SCF     1E-08&#xA;      SCF_GUESS  RESTART&#xA;      &amp;amp;OT  T&#xA;        MINIMIZER  DIIS&#xA;        PRECONDITIONER  FULL_KINETIC&#xA;      &amp;amp;END OT&#xA;      &amp;amp;OUTER_SCF  T&#xA;        EPS_SCF     1E-08&#xA;        MAX_SCF  20&#xA;      &amp;amp;END OUTER_SCF&#xA;      &amp;amp;PRINT&#xA;        &amp;amp;RESTART  SILENT&#xA;          BACKUP_COPIES  1&#xA;        &amp;amp;END RESTART&#xA;      &amp;amp;END PRINT&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;    &amp;amp;POISSON&#xA;       POISSON_SOLVER  WAVELET&#xA;       PERIODIC NONE &#xA;       &amp;amp;WAVELET&#xA;         SCF_TYPE  100&#xA;       &amp;amp;END WAVELET&#xA;    &amp;amp;END POISSON&#xA;  &amp;amp;END DFT&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;CELL&#xA;      ABC 30.0 30.0 30.0&#xA;      PERIODIC NONE&#xA;    &amp;amp;END CELL&#xA;    &amp;amp;TOPOLOGY&#xA;      COORD_FILE_FORMAT XYZ&#xA;      COORD_FILE_NAME pyridine.xyz&#xA;      &amp;amp;CENTER_COORDINATES&#xA;      &amp;amp;END CENTER_COORDINATES&#xA;    &amp;amp;END TOPOLOGY&#xA;    &amp;amp;KIND H&#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q1&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND C &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q4&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;KIND N &#xA;      BASIS_SET DZVP-GTH-PBE&#xA;      POTENTIAL GTH-PBE-q5&#xA;    &amp;amp;END KIND&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&amp;amp;GLOBAL&#xA;  PROJECT Pyridine&#xA;  RUN_TYPE VIBRATIONAL_ANALYSIS&#xA;  PRINT_LEVEL LOW&#xA;  EXTENDED_FFT_LENGTHS&#xA;&amp;amp;END GLOBAL&#xA;&#xA;&amp;amp;MOTION&#xA;  &amp;amp;GEO_OPT&#xA;! to calculate vibrational spectrum tight convergence is required because frequencies are very sensitive to force constant&#xA;    TYPE MINIMIZATION&#xA;    MAX_DR    1.0E-03&#xA;    MAX_FORCE 1.0E-03&#xA;    RMS_DR    1.0E-03&#xA;    RMS_FORCE 1.0E-03&#xA;    MAX_ITER 200&#xA;    OPTIMIZER CG&#xA;  &amp;amp;END&#xA;&amp;amp;END&#xA;! setup parameters to perform a Normal Modes analysis&#xA;&amp;amp;VIBRATIONAL_ANALYSIS&#xA;!   &amp;amp;MODE_SELECTIVE&#xA;!      LOWEST_FREQUENCY 0.0&#xA;!      FREQUENCY   630&#xA;!      ATOMS 6 1&#xA;!      INITIAL_GUESS RESTART&#xA;!      RESTART_FILE_NAME Pyridine-VIBRATIONS-1.mol &#xA;!      EPS_NORM  1.0E-4&#xA;!      EPS_MAX_VAL 1.0E-5&#xA;!   &amp;amp;END&#xA;!Specify the number of processors to be used per replica environment (for parallel runs)&#xA;NPROC_REP 4&#xA;!Specify the increment to be used to construct the HESSIAN with finite difference method&#xA;   DX 1E-3&#xA;   &amp;amp;PRINT&#xA;     &amp;amp;PROGRAM_RUN_INFO ON&#xA;     &amp;amp;END&#xA;   &amp;amp;END&#xA;&amp;amp;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I varied the cubic box length as 10, 20 and 30 angstroms and there was relatively insignificant effect on frequency calculations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;10 Ang^3                     20 Ang^3                 30 Ang^3&#xA;&#xA;     [FREQ] cm-1            [FREQ] cm-1             [FREQ] cm-1&#xA;      306.559373             307.614457               308.189936&#xA;      368.761441             381.380678               370.081145&#xA;      578.498921             591.875865               578.958510&#xA;      630.679041             632.222381               631.759367&#xA;      652.909718             653.938140               653.110369&#xA;      717.683491             723.258235               718.390117&#xA;      841.291874             841.755853               841.537638&#xA;      883.457892             883.747121               883.733166&#xA;      937.440211             937.725276               937.794444&#xA;      972.598159             972.540268               972.856600&#xA;      975.384418             985.095914               976.166601&#xA;     1042.925264            1045.181855              1043.247363&#xA;     1061.317180            1061.943046              1061.498007&#xA;     1066.390016            1066.772710              1066.463394&#xA;     1125.211196            1125.337595              1125.254047&#xA;     1176.780112            1176.789866              1176.722581&#xA;     1296.556279            1297.011609              1296.543748&#xA;     1368.961734            1371.370062              1368.715023&#xA;     1448.749298            1449.730137              1448.520992&#xA;     1455.387545            1455.803598              1455.480999&#xA;     1644.206969            1644.871006              1644.242656&#xA;     1645.693998            1646.204083              1645.595586&#xA;     3165.883661            3165.929198              3165.913233&#xA;     3171.541016            3171.575638              3171.569378&#xA;     3182.447441            3182.502989              3182.464905&#xA;     3190.435506            3190.499027              3190.471759&#xA;     3201.299231            3201.335631              3201.328153&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The significant changes here are Orbital Transform (OT) optimizer and 400 Ry plane cutoff to reduce the computational load.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2020-12-18T04:17:33.557" LastActivityDate="2020-12-18T04:17:33.557" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3955" PostTypeId="2" ParentId="3951" CreationDate="2020-12-18T10:31:29.163" Score="3" Body="&lt;p&gt;As you say, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;nofollow noreferrer&quot;&gt;effective mass&lt;/a&gt; is inversely proportional to the curvature.  However, it seems to me that &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; corresponds to an &lt;a href=&quot;https://en.wikipedia.org/wiki/Inflection_point&quot; rel=&quot;nofollow noreferrer&quot;&gt;inflection point&lt;/a&gt; in the band diagram. It means that the curvature and the effective mass change their signs around this point, with an divergent effective mass.&lt;/p&gt;&#xA;&lt;p&gt;It's quite debatable as it relies on graph reading, but I guess that the point wasn't chosen randomly if this picture comes from some teaching material with the goal of making you think about the concepts at hand.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2020-12-18T10:31:29.163" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3956" PostTypeId="1" CreationDate="2020-12-19T03:02:16.507" Score="13" ViewCount="160" Body="&lt;p&gt;The following is what a Penrose tiling looks like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/suLlWm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/suLlWm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know the verticies of a dodecahedron can be grouped into 5 groups each of which are the verticies of a tetrahedron. So I thought of the idea that maybe a covalent network of carbon atoms each of which makes 4 unstrained bonds and has the form of something like a Penrose tiling but is dodecahedral is mathematically possible.&lt;/p&gt;&#xA;&lt;p&gt;My question is&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Has there been a discussion of whether that is mathematically possible according to the Dalton model or something like that, which can easily be found?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That was my question. The rest is just facts I want to share.&lt;/p&gt;&#xA;&lt;p&gt;Diamond has 4 weak cleavage planes. Lonsdalite has 1. In either case, the cleavage plane is where there is only single bonds going through it perpendicular to it. If that form of diamond existed, it would probably have no such plane and therefore would probably have a higher fracture toughness when you apply tension in the direction perpendicular to the weakest cleavage plane or something like that. I think English is a bit flexible and they don't make the definition of fracture toughness that precise.&lt;/p&gt;&#xA;&lt;p&gt;I read on the internet about other covalent networks of carbon atoms that do have strained bonds, which included on that resembled a tessellation of the truncated octahedron. I already know about those discussions and am not interested in an answer that talks about that or any form other than the very specific form I was asking about here.&lt;/p&gt;&#xA;&lt;p&gt;Also, according to the Wikipedia article Quasicrystal, quasicrystal lacks periodic symmetry. It also says there are some quasicrystals in nature. I'm not sure they really are truly aperiodic.&lt;/p&gt;&#xA;&lt;p&gt;This:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pDerPm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pDerPm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;shows that you can take part of the Penrose tiling and turn it into a &lt;a href=&quot;https://en.wikipedia.org/wiki/Primitive_cell&quot; rel=&quot;nofollow noreferrer&quot;&gt;primitive cell&lt;/a&gt;. Maybe nature also takes part of what a true dodecahedral quasicrystal would look like and makes it into a primitive cell, but has the primitive cell large enough to include 5 subparts that have the relative orientation to one another like the 5 tetrahedra whose verticies form the verticies of a dodecahedron. The Wikipedia article Silicon nitride has an image with a description saying it is the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; phase of &lt;span class=&quot;math-container&quot;&gt;$Si_3N_4$&lt;/span&gt;. It also looks disordered. If you take that unit cell and turn it into a torus, maybe it can be split into 1 or multiple primitive cells each of which could be part of a quasicrystal and has 5 small parts that have the relative orientations of 5 tetrahedra that make a dodecahedron.&lt;/p&gt;&#xA;&lt;p&gt;Sources:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Penrose_Tiling_(Rhombi).svg&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://commons.wikimedia.org/wiki/File:Penrose_Tiling_(Rhombi).svg&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://commons.wikimedia.org/wiki/File:RegularRhombs.svg&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://commons.wikimedia.org/wiki/File:RegularRhombs.svg&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="5" LastEditDate="2020-12-24T23:06:38.940" LastActivityDate="2020-12-27T01:36:30.243" Title="Has a form of diamond with certain properties ever been theorized?" Tags="|mathematical-modeling|physical-properties-of-materials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3957" PostTypeId="2" ParentId="3953" CreationDate="2020-12-19T06:14:25.223" Score="8" Body="&lt;p&gt;I'll answer each of your three questions separately, but the one you say is &amp;quot;most important&amp;quot; will go first &lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;And most importantly, why are they used for correlation calculation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They can significantly reduce the cost of a calculation on a big system, especially when there is a large number of &amp;quot;virtual&amp;quot; orbitals (unoccupied orbitals) in the basis set. Effectively they allow the size of the virtual space to be reduced. You mentioned MP2 and CCSD, which scale rapidly with the number &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; of orbitals: &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(N^5)$&lt;/span&gt; for MP2 and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(N^6)$&lt;/span&gt; for CCSD, so when &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is large (for example 4000 orbitals for a 40 atom system) it can become absolutely crucial to effectively reduce &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; from a cost perspective. Without PNO based methods, it can be extremely difficult to do MP2 or CCSD on such a large number of atoms, even with a TZ basis set, but with LNO (similar to PNO) &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00511&quot; rel=&quot;noreferrer&quot;&gt;it was possible to do CCSD(T) on a molecule with 1023 atoms in a QZ basis set (44712 orbitals)&lt;/a&gt;. For a small number of atoms (for example 10), in not too large a basis set (for example QZ) then PNO based methods are probably not worth the trouble and slight loss of accuracy which occurs in implementations of PNO-MP2 and PNO-CCSD.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What are these PNOs?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The term was first proposed &lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.1727841&quot; rel=&quot;noreferrer&quot;&gt;in 1966 by Edmiston and Krauss&lt;/a&gt; as &amp;quot;pseudonatural orbitals&amp;quot; because, as &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1679283&quot; rel=&quot;noreferrer&quot;&gt;Mayer described it&lt;/a&gt; in some context they can be considered an approximation to natural orbitals (&amp;quot;natural orbitals&amp;quot; are eigenvectors of the 1-electron density matrix), even though they can be very different from natural orbitals. Later people started to refer to them as &amp;quot;pair natural orbitals&amp;quot; instead of &amp;quot;pseudonatural orbitals&amp;quot; but even people that call them pair natural orbitals mean the same thing as Edmiston and Krauss did. &lt;strong&gt;Pair natural orbitals are eigenvectors of the &amp;quot;pair density matrix&amp;quot;&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Since you said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It would help if the answer is explained in simple words, I am not&#xA;much of a theoretician!&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I might be getting a bit too zealous by getting into more detail, but perhaps others will appreciate it. PNOs are eigenvectors of the density matrix for the &amp;quot;independent pair wavefunctions&amp;quot; (I'll use the notation in the aforementioned paper by Mayer):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\Psi_0 + \sum_i \tilde{C}_P^{ai} \Phi_P^{ai} + \sum_{ij}\tilde{C}_P^{ij} \Phi_P^{ij},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Phi_P^{mn}$&lt;/span&gt; is a Slater determinant (configuration) obtained by coupling two electrons with orbitals &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; with a double hole state &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; (which is defined in the bottom-left corner of the 2nd page of Mayer's paper), and the coefficients &lt;span class=&quot;math-container&quot;&gt;$\tilde{C}$&lt;/span&gt; variationally minimize the energy of &lt;span class=&quot;math-container&quot;&gt;$\Psi_P$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In perhaps Frank Neese's earliest work on the subject &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3086717&quot; rel=&quot;noreferrer&quot;&gt;(circa 2009)&lt;/a&gt; he and co-authors say:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;each electron pair is treated by the most rapidly converging&#xA;expansion of external orbitals, that, by definition, is provided by&#xA;the natural orbitals that are specific for this pair [76]&amp;quot;,&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;where [76] is this &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.97.1474&quot; rel=&quot;noreferrer&quot;&gt;1955 paper by Lowdin&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How are they different to the usual orbital localization schemes such as Ruedenberg, Pipek-Mezey?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the aforementioned paper by Neese &lt;em&gt;et al.&lt;/em&gt; they say this right in the abstract:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The internal space is spanned by localized internal orbitals. The&#xA;external space is greatly compressed through the method of pair&#xA;natural orbitals PNOs&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;By &amp;quot;internal space&amp;quot; they mean occupied orbitals, and by &amp;quot;external space&amp;quot; they mean unoccupied orbitals. Basically: they localize the occupied orbitals by schemes such as the one by Pipek-Mezey, and they use PNO for the unoccupied orbitals.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-19T06:27:22.330" LastActivityDate="2020-12-19T06:27:22.330" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3958" PostTypeId="2" ParentId="3953" CreationDate="2020-12-19T15:12:41.577" Score="8" Body="&lt;p&gt;I think Nike has answered to all questions adequately enough. I am sharing my understanding as one of the developers of the PNO-based local coupled-cluster (CC) methods, codes for computing response properties in particular.&lt;/p&gt;&#xA;&lt;p&gt;In coupled-cluster theory, the correlated wavefunction is described in terms of &amp;quot;cluster amplitudes&amp;quot; (which are the wavefunction parameters). In the standard formulation of CC theory, these cluster amplitudes are defined in the basis of standard canonical Hartree-Fock (HF) orbitals. For large molecules, the number of cluster amplitudes defined in terms of HF orbitals may range up to a few billions (a crude estimate!). This makes the CC calculation formidable even on the most powerful and spacious computer on the planet. The only way to accomplish such calculations is to reduce the number of cluster amplitudes, in this way achieving a &lt;em&gt;compact description&lt;/em&gt; of the correlated wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Localized orbitals are used in quantum chemistry for various purposes. One of them is to get a compact description of the many-electron wavefunction. While the canonical HF orbitals spread over a large molecule as the whole, localized orbitals have much smaller spatial extents. Two types of orbital bases are needed to define the cluster amplitudes in CC theory: occupied orbitals and &amp;quot;virtual&amp;quot; or unoccupied orbitals. &lt;strong&gt;Pipek-Mezey or Foster-Boys schemes are used for obtaining only the localized occupied orbitals. The quest for a compact local description of the virtual orbitals is still open.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Several options have been put forth for defining a compact virtual orbital basis. I will not go into the details of all those. However, it is very important to mention that the pioneering idea in this field (local MP2 in particular) came from Prof. Peter Pulay, who proposed the use of the &amp;quot;Projected Atomic Orbitals&amp;quot;(PAOs). I will skip a description of them in this context.&lt;/p&gt;&#xA;&lt;p&gt;The use of the &amp;quot;Pair-natural orbitals&amp;quot; (PNOs) is another option to compress the virtual space. The PNOs were introduced in the context of Coupled Electron-Pair Approximations (CEPA) by Wilfried Meyer in 1970's (both PNO-CEPA and PNO-CI) and was resurrected recently by Prof. Frank Neese and co-workers (including myself) in the context of CC theory, or more specifically, the &lt;strong&gt;domain-based pair-natural orbital CC&lt;/strong&gt;  (DLPNO-CC) approach. Several applications involving very large molecular systems (even a whole crambin protein!) has demonstrated that the &lt;em&gt;PNOs provide the most compact description of the virtual orbital space&lt;/em&gt;, and the DLPNO-CC [both DLPNO-CCSD and DLPNO-CCSD(T)] method can truly achieve a linear scaling of the memory cost and the computational cost (in terms of wall times) with respect to system size.&lt;/p&gt;&#xA;&lt;p&gt;The way PNOs are derived in the DLPNO-CC approach is rather involved. Here is a simple recipe to obtain the PNOs (this is absolutely not how it works for DLPNO-CC and the description below should only be taken as a conceptually simplified guideline):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;For a large molecule, get the optimized HF-SCF MOs.&lt;/li&gt;&#xA;&lt;li&gt;Localize the occupied orbitals using Pipek-Mezey or the Foster-Boys scheme.&lt;/li&gt;&#xA;&lt;li&gt;Obtain MP2 guess for the cluster amplitudes using localized occupied orbitals and the canonical HF virtual orbitals.&lt;/li&gt;&#xA;&lt;li&gt;Define &amp;quot;&lt;strong&gt;pair density&lt;/strong&gt;&amp;quot; for each pair of localized occupied orbitals (&lt;em&gt;i,j&lt;/em&gt;). These pair densities are defined solely in terms of virtual orbitals. (I will skip the formula, as quite frankly, I do not know how to write equations on this platform).&lt;/li&gt;&#xA;&lt;li&gt;Diagonalize the pair density matrix. This gives the &amp;quot;pair-natural orbital&amp;quot; occupation numbers and the PNO coefficient vectors.&#xA;(Note: &lt;strong&gt;The term &amp;quot;natural orbitals&amp;quot; in general is used for designating a set of orbitals that diagonalizes the one-particle density matrix, e.g., MCSCF natural orbitals. The name &amp;quot;pair-natural orbitals&amp;quot; also derives from the same concept. The PNOs diagonalize the pair density matrix for every pair of localized occupied orbitals.&lt;/strong&gt;)&lt;/li&gt;&#xA;&lt;li&gt;The final step is to expand the PNOs in terms of certain basis functions. The DLPNO-CC approach expands them in terms of the PAOs mentioned above.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;How do the PNOs achieve a compact description of the virtual space? Once the pair density matrices are diagonalized, the PNO occupation numbers are compared to a user-defined threshold, TcutPNO, in the context of DLPNO-CC. All PNOs with occupation numbers less than TCutPNO are discarded. For each pair of localized occupied orbitals (&lt;em&gt;i,j&lt;/em&gt;), one thus obtains a much fewer number of PNOs to describe the virtual space than the billions of canonical virtual HF MOs. The cluster amplitudes are defined for each pair (&lt;em&gt;i,j&lt;/em&gt;) only in terms of the corresponding PNOs. This gives a highly compressed description of the correlated wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;I hope the descriptions above give some conceptual background and also addresses the questions. I did skip a lot of minute details, however.&lt;/p&gt;&#xA;" OwnerUserId="1329" LastActivityDate="2020-12-19T15:12:41.577" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3959" PostTypeId="1" CreationDate="2020-12-20T09:40:39.970" Score="13" ViewCount="175" Body="&lt;p&gt;I am looking for new QM/MM methodologies which have recently developed and implemented into MD packages. Any applications or molecular systems studies with these methods can be used as an example as well.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="7" LastEditDate="2020-12-22T15:49:12.480" LastActivityDate="2021-04-26T18:57:39.663" Title="Recent developments in QM/MM for Molecular Dynamics" Tags="|software|molecular-dynamics|reference-request|one-topic-per-answer|qmmm|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3960" PostTypeId="1" AcceptedAnswerId="3964" CreationDate="2020-12-21T00:13:06.030" Score="8" ViewCount="117" Body="&lt;p&gt;I am looking for a phosphorescence material that emits light (400nm - 600nm). The trick is I need the material not to heat up when absorbing or discharging the light, so basically, I hope it maintains room temperature. Furthermore, I am hoping it can maintain emitting light for a period of (20 min - 3 hours).&lt;/p&gt;&#xA;&lt;p&gt;Is there any commercial material as such or anything similar?&lt;/p&gt;&#xA;" OwnerUserId="1764" LastEditorUserId="5" LastEditDate="2020-12-26T06:04:34.027" LastActivityDate="2020-12-26T06:04:34.027" Title="What phosphorescence material emits light for a 1 hour period?" Tags="|spectroscopy|materials-design|experimental|photochemistry|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3961" PostTypeId="1" AcceptedAnswerId="3970" CreationDate="2020-12-21T09:07:07.480" Score="11" ViewCount="1990" Body="&lt;p&gt;I have the output of a simulation done using Periodic boundary conditions (PBC), however, the atom positions have been resolved, i.e. there are atoms outside the PBC-box now. Is there a software/formula that I can use to restore these positions back inside the box?&lt;/p&gt;&#xA;&lt;p&gt;I have an &lt;code&gt;.xyz&lt;/code&gt; file that contains the positions of the atoms.&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-12-29T19:31:09.433" LastActivityDate="2020-12-29T19:31:09.433" Title="Recalculate atom positions to account for periodic boundary conditions" Tags="|software|periodic-boundary-conditions|vmd|minimum-image-convention|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="3962" PostTypeId="1" CreationDate="2020-12-21T09:54:08.613" Score="8" ViewCount="93" Body="&lt;p&gt;I would like to know about possible applications of DIC in mechanical testing and the field of materials&#xA;science, when I search there is the general topics of DIC usages, but I would like to know applications in mechanical testing in material science.&lt;/p&gt;&#xA;" OwnerUserId="1765" LastEditorUserId="5" LastEditDate="2020-12-21T18:30:59.590" LastActivityDate="2020-12-22T15:20:48.797" Title="What are the possible applications of DIC (digital image correlation) in mechanical testing and the field of materials science?" Tags="|reference-request|materials-design|materials-engineering|physical-properties-of-materials|mechanical-properties|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3963" PostTypeId="1" CreationDate="2020-12-22T12:35:12.420" Score="7" ViewCount="201" Body="&lt;p&gt;I'm calculating the total energy at the ACFDT-RPA level using VASP in terms of &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ACFDT/RPA_calculations&quot; rel=&quot;noreferrer&quot;&gt;this tutorial&lt;/a&gt;. For the first three steps it uses:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISMEAR = 0 ; SIGMA = 0.05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but for the final step does not use these parameters. I think there it takes default parameters. Does it make difference?&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="1218" LastEditDate="2020-12-23T08:24:24.777" LastActivityDate="2020-12-24T05:32:55.670" Title="ISMEAR and SIGMA" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3964" PostTypeId="2" ParentId="3960" CreationDate="2020-12-22T13:43:24.343" Score="7" Body="&lt;p&gt;Strontium aluminate can be doped with europium to give a material with properties like you are expecting.  This can be optimized to give maximum fluorescent yield as well, but keep in mind this will likely shift the wavelength.&lt;/p&gt;&#xA;&lt;p&gt;The material must heat and cool in this process since absorption of light will not be 100% efficient and neither will the loss of light (some light may be emitted towards the material rather than outwards.).  Most heat production should occur during the &amp;quot;charging&amp;quot; phase of the cycle though since the heat produced will be due to the transition from high energy levels to lower but still excited energy levels by vibrational loss of energy.&lt;/p&gt;&#xA;&lt;p&gt;I am unsure what your application is, but &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/jp022062c&quot; rel=&quot;noreferrer&quot;&gt;here is a paper&lt;/a&gt; on the synthesis of these materials.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-12-22T13:43:24.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3965" PostTypeId="2" ParentId="3962" CreationDate="2020-12-22T15:20:48.797" Score="5" Body="&lt;p&gt;Digital Image Correlation is used a few different ways in mechanical testing. On larger samples, it can be used as a digital extensometer to measure the overall strain in the sample. For ductile samples, it can also show a map of strain fields and how those fields grow fastest around the point of failure. This is especially useful for a heterogeneous sample, e.g. in samples with compositional gradients. The experimental strain fields can be used in combination with finite element modeling to give an idea of the stress state, which often determines failure and can be used to calibrate failure models [1]. Using two simultaneous camera angles can also give you an idea of the 3D strain field of the sample.&lt;/p&gt;&#xA;&lt;p&gt;The second way DIC is commonly used is to expose grain-scale deformation mechanisms on smaller samples. The surface grain deformation can be mapped using optical microscopy, but this method becomes very powerful when done inside an SEM with nanoparticles providing the speckle pattern [2]. At such scales, the mechanisms of twinning and slip can be directly compared to mesoscale models such as crystal plasticity finite element methods.&lt;/p&gt;&#xA;&lt;p&gt;[1] I'd suggest groups like Allison Beese's at Penn State for this; see &lt;a href=&quot;https://doi.org/10.1016/j.actamat.2020.08.066&quot; rel=&quot;noreferrer&quot;&gt;doi:0.1016/j.actamat.2020.08.066&lt;/a&gt; for macroscopic experiments with computational comparison or &lt;a href=&quot;https://arxiv.org/abs/2001.11611&quot; rel=&quot;noreferrer&quot;&gt;arxiv:2001.11611&lt;/a&gt; for the functionally graded materials fabricated by additive manufacturing (no mechanical testing published for these yet -- FGMs still often crack during the build and need refined compositional pathways to avoid this).&lt;br /&gt;&#xA;[2] Sam Daly at UC Santa Barbara is well-established in these techniques; see &lt;a href=&quot;https://doi.org/10.1007/s11340-016-0217-3&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1007/s11340-016-0217-3&lt;/a&gt; for the SEM-DIC technique or &lt;a href=&quot;https://doi.org/10.1016/j.ijplas.2020.102917&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1016/j.ijplas.2020.102917&lt;/a&gt; for a recent comparison with crystal plasticity models.&lt;/p&gt;&#xA;" OwnerUserId="1180" LastActivityDate="2020-12-22T15:20:48.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3966" PostTypeId="1" AcceptedAnswerId="3998" CreationDate="2020-12-23T02:54:33.430" Score="8" ViewCount="190" Body="&lt;p&gt;Although the ferroelectric polarization is usually calculated with primitive cell using the Berry phase method, supercells are sometimes needed for particular applications, e.g., defects, doping, etc. As polarization is defined as the dipole moment divided by the volume, using larger supercell would not change the polarization in principle. However, due to the multi-value nature of the polarization according to the modern theory of polarization, the polarization of crystals is only defined modulo the polarization quanta&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{P} = \mathbf{P}_0 + \sum_{i=a,b,c} n_i \frac{e\mathbf{R}_i}{\Omega}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$n_i$&lt;/span&gt; is an integer, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_i$&lt;/span&gt; is the lattice vector, and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; the volume. As can be seen, supercell would change the polarization quanta &lt;span class=&quot;math-container&quot;&gt;${e\mathbf{R}_i}/{\Omega}$&lt;/span&gt;, thus change the calculated polarization &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P}_0$&lt;/span&gt;. So I'm wondering if there is any recipe or remedy on   the polarization calculations with supercells.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2020-12-29T18:28:27.750" Title="How to get correct ferroelectric polarization from a supercell calculation?" Tags="|density-functional-theory|ferroelectric|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3967" PostTypeId="1" CreationDate="2020-12-23T11:23:35.007" Score="11" ViewCount="667" Body="&lt;p&gt;For reason that I did not understand Avogadro has been phased out of Ubuntu 20.x and the available package &lt;code&gt;Avogadro2&lt;/code&gt; is instead another branch of the package, which unfortunately does not cover all the features.&#xA;As it appears impossible to install that older but more powerful version of Avogadro on last Ubuntu, does anyone know if it is still possible to delete selected atoms? I am really surprised such a basic feature has been &amp;quot;lost&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Basically, you can click and select atoms (although they do not appear selected for any displaying style but &amp;quot;ball and stick&amp;quot;), but then if you press CANCEL the whole model is deleted (all atoms). I was using this feature a lot to manipulate structures via GUI and now I just can't proceed unless I use my older Ubuntu distribution.&lt;/p&gt;&#xA;" OwnerUserId="1773" LastEditorUserId="1355" LastEditDate="2020-12-23T11:35:27.650" LastActivityDate="2021-01-12T08:09:03.340" Title="How to delete a selection with Avogadro2 (Ubuntu 20.x)?" Tags="|molecular-modeling|avogadro|graphical-user-interface|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="3968" PostTypeId="1" AcceptedAnswerId="3971" CreationDate="2020-12-23T13:51:54.867" Score="13" ViewCount="1121" Body="&lt;p&gt;I am performing a spin polarized DFT calculations in Quantum Espresso on a Co2MnSi ferromagnetic crystal. For this I have performed these steps:&lt;br /&gt;&#xA;&lt;strong&gt;1)&lt;/strong&gt; Performed &lt;code&gt;vc-relax&lt;/code&gt; calculation to find its lattice constant. Here is some lines from output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS (alat= 10.00000000)&#xA;-0.531670336   0.000000000   0.531670336&#xA; 0.000000000   0.531670336   0.531670336&#xA;-0.531670336   0.531670336  -0.000000000&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA;Co       0.000000000   0.000000000  -0.000000000&#xA;Mn       0.265835168   0.265835168   0.265835168&#xA;Co       0.531670336   0.531670336   0.531670336&#xA;Si      -0.265835168  -0.265835168  -0.265835168&#xA;End final coordinates&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Lattice constant found is as, &lt;code&gt;a = (10/0.5)*0.531670336 = 10.63340672&lt;/code&gt; Bohr and the final 'total magnetization' found at the end of the calculation is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  total magnetization       =     5.00 Bohr mag/cell&#xA;  absolute magnetization    =     5.39 Bohr mag/cell/cell&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;2)&lt;/strong&gt; Now I have plugged the value of lattice constant, (&lt;code&gt;celldm(1)=10.63340672&lt;/code&gt;) in &lt;code&gt;scf&lt;/code&gt; input file and performed the 'scf' calculation. But in the output file of &lt;code&gt;scf&lt;/code&gt;, final &lt;code&gt;total magnetization&lt;/code&gt;  is different than the &lt;code&gt;vc-relax&lt;/code&gt; output.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;total magnetization       =     4.56 Bohr mag/cell&#xA;absolute magnetization    =     5.01 Bohr mag/cell&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;My Question:&lt;/strong&gt;&lt;br /&gt;&#xA;Correct 'total magnetization' for this system is exact 5.00 (which I have got in the &lt;code&gt;vc-relax&lt;/code&gt; calculation) but why I'm getting different &lt;code&gt;total magnetization&lt;/code&gt; from the &lt;code&gt;scf&lt;/code&gt; calculation?&#xA;Shouldn't it be same cause this will affect the DOS calculation also? Also the total energy from two different calculation is different. Why is so? Am I performing the steps wrongly?&lt;/p&gt;&#xA;&lt;p&gt;Please clarify it.&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;&lt;p&gt;You can find the input and output files &lt;a href=&quot;https://github.com/UJ5/DFT-Calculations&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="7" LastEditDate="2021-01-02T20:33:07.400" LastActivityDate="2021-01-02T20:33:07.400" Title="Getting different total magnetic moment in 'scf' and 'vc-relax' calculations in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|magnetism|self-consistent-field|cell-optimization|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3969" PostTypeId="2" ParentId="3967" CreationDate="2020-12-23T15:25:33.400" Score="6" Body="&lt;p&gt;In the meantime I have found a couple of solutions and I am listing them here for other users, as frankly not many packages allow to easily (via mouse) select atoms and delete them.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;you can use &lt;code&gt;chimera&lt;/code&gt; as it offers the same feature via CTRL+mouse:&#xA;&lt;a href=&quot;https://www.cgl.ucsf.edu/chimera/data/downloads/1.15/linux_x86_64.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.cgl.ucsf.edu/chimera/data/downloads/1.15/linux_x86_64.html&lt;/a&gt; and then menu Actions -&amp;gt; Atoms/Bonds -&amp;gt; delete.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;if you still want to use &lt;code&gt;avogadro2&lt;/code&gt; on Linux you can actually delete atoms one-by-one by using right-click in &amp;quot;Draw&amp;quot; mode:&#xA;&lt;a href=&quot;https://discuss.avogadro.cc/t/delete-some-atoms-in-a-supercell/341/2&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://discuss.avogadro.cc/t/delete-some-atoms-in-a-supercell/341/2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1773" LastEditorUserId="1773" LastEditDate="2021-01-12T08:09:03.340" LastActivityDate="2021-01-12T08:09:03.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3970" PostTypeId="2" ParentId="3961" CreationDate="2020-12-23T19:07:11.790" Score="8" Body="&lt;p&gt;To visualize the trajectory you can use VMD and use its pbctools&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;vmd trajectory.xyz&#xA;&amp;gt; pbc set {a b c alpha betta gamma} -all&#xA;&amp;gt; pbc wrap&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;a&lt;/code&gt;, &lt;code&gt;b&lt;/code&gt;, and &lt;code&gt;c&lt;/code&gt; are the lattice vectors and &lt;code&gt;alpha&lt;/code&gt;, &lt;code&gt;beta&lt;/code&gt;, and &lt;code&gt;gamma&lt;/code&gt; the angles. The angles can be omitted if the box is orthorhombic. For more information see here: &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/plugins/pbctools&quot; rel=&quot;noreferrer&quot;&gt;https://www.ks.uiuc.edu/Research/vmd/plugins/pbctools&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To process the trajectory I'd recommend using one of the available python packages. Here is a code snippet using the Atomic Simulation Environment (ASE):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;xyz=io.read('trajectory.xyz',index=&amp;quot;:&amp;quot;)&#xA;for frame in xyz:&#xA;  frame.set_cell([a,b,c],[alpha,beta,gamma])&#xA;  frame.set_pbc([True,True,True])&#xA;  frame.wrap()&#xA;io.xyz.write_xyz('trajectory_wrapped.xyz',xyz)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Because the xyz-file contains no information about the cell you have to supply it separately. You can also use ASE to further process the coordinates if you wish. The documentation is here: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="5" LastEditDate="2020-12-23T20:18:28.970" LastActivityDate="2020-12-23T20:18:28.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3971" PostTypeId="2" ParentId="3968" CreationDate="2020-12-24T04:02:34.090" Score="9" Body="&lt;p&gt;Looking at your input and output files, I think the most likely explanation is a different local minimum in the energy, as mentioned by Andrew in the comments.&lt;/p&gt;&#xA;&lt;p&gt;If you look at the final scf step in the vc-relax output, it uses the starting magnetization from the last bfgs step, not the initial values you used at the start of the vc-relax.&lt;/p&gt;&#xA;&lt;p&gt;I would try two things:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Run a standalone scf calculation with the starting magnetizations used in the final scf step of the vc-relax calculation.&lt;/li&gt;&#xA;&lt;li&gt;Do another vc-relax starting from your relaxed cell parameters. You can see in your separate scf calculation that the cell stress has increased a lot. You may converge to a different geometry and ground state than your first vc-relax. You can either compare the energies from the two calculations and choose the lower, or choose one based on the magnetizations on the atoms (if applicable), i.e. whether one is closer to the spin arrangement you expect or desire to study.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2020-12-24T04:02:34.090" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3972" PostTypeId="2" ParentId="3963" CreationDate="2020-12-24T05:32:55.670" Score="5" Body="&lt;p&gt;Strictly speaking, you should be consistent and use the same smearing approach and smearing width for all calculations on a given structure. It has the potential to influence the (extrapolated, 0 K) energy, although the differences are likely to be minor. They probably just forgot to include the flags in the input file for that final calculation, but I'd recommend keeping them for consistency.&lt;/p&gt;&#xA;&lt;p&gt;The defaults are &lt;code&gt;ISMEAR=1&lt;/code&gt; and &lt;code&gt;SIGMA=0.2&lt;/code&gt;, which is quite different. If the energy is at all sensitive to &lt;code&gt;SIGMA&lt;/code&gt;, then you &lt;em&gt;may&lt;/em&gt; notice a slight difference in energies depending on which flags are used.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-12-24T05:32:55.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3973" PostTypeId="2" ParentId="3968" CreationDate="2020-12-24T05:39:24.383" Score="9" Body="&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt;: This no longer seems to be the issue, as the atomic positions are apparently essentially unchanged, per @KevinJ.M.'s comment. I will nonetheless keep the answer here because it is still important to consider going forward.&lt;/p&gt;&#xA;&lt;p&gt;It looks like you are getting a different magnetization because the structures are not identical. Your first structure is fully relaxed, including atomic positions and cell volume. You then took the optimized lattice constants, but not the optimized atomic positions, for the SCF calculation. This means the SCF calculation is &lt;em&gt;not&lt;/em&gt; the local minimum energy structure you found with the geometry optimization. You should not necessarily expect the magnetic moments to be the same. In this case, I imagine your structure in the SCF calculation has a fairly high degree of stress on it, and the fact that it's not quite a local minimum in the potential energy surface is why you are getting a close (but not identical, and non-integer) net magnetic moment. Regardless, this also explains why your energies are different – the structure isn't the same!&lt;/p&gt;&#xA;&lt;p&gt;If you aren't happy about the relaxed atomic positions, then you need to ask yourself why. You can't just neglect to update them because they don't look nice. Perhaps you want to enforce a given symmetry. Perhaps there is something missing from the structure that stabilizes the geometry. Perhaps the geometry you think you should have is not actually real at all! These are more problem-specific questions, not a DFT question at this point.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2020-12-24T06:52:40.717" LastActivityDate="2020-12-24T06:52:40.717" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3974" PostTypeId="1" AcceptedAnswerId="3983" CreationDate="2020-12-24T06:02:26.797" Score="11" ViewCount="376" Body="&lt;p&gt;I am interested in calculating some redox potentials of organic compounds (H,C,N,O,F,Cl,Br) in organic solvents such as MeCN.  I do not need absolute agreement with experiments since this is just a first pass to identify some potential candidates for experiments, so I am looking for the best simple approach to this problem.  An accuracy of +/- 0.5V would be sufficient for example, if this is doable.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2020-12-27T22:25:26.150" Title="Calculate Redox Potential" Tags="|reference-request|gaussian|solvation|redox|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3975" PostTypeId="1" CreationDate="2020-12-24T12:34:17.783" Score="9" ViewCount="531" Body="&lt;p&gt;I would like to construct a model analytical potential function for collision between CH3Cl and Ar. This would be the sum of CH3Cl intramolecular + CH3Cl---Ar intermolecular potential. First I would like to generate the ab Initio data points to be fitted using double many-body expansion or similar functions. I know how to set up PES scans (bond, angle, dihedral etc) using gaussian, Orca and Psi4 but I don't know how I would approach this problem. I would greatly appreciate if anyone would give a detailed procedure on how I can go about solving this and similar problems. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="416" LastEditorUserId="5" LastEditDate="2020-12-24T15:14:38.283" LastActivityDate="2020-12-26T19:58:38.120" Title="What is the procedure for constructing an ab initio potential energy surface for CH3Cl + Ar?" Tags="|ab-initio-calculations|computational-chemistry|forcefields|potential-energy-surface|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3976" PostTypeId="1" CreationDate="2020-12-24T12:38:12.963" Score="12" ViewCount="1789" Body="&lt;p&gt;I have been using &lt;code&gt;gromacs&lt;/code&gt; since years but I am always confused when I want to perform the following task: compute the RDF (radial distribution function) between the COMs (center of masses) of two selections or groups.&lt;/p&gt;&#xA;&lt;p&gt;I am assuming I can define selections within the command line via &lt;code&gt;-sel&lt;/code&gt; and &lt;code&gt;-ref-&lt;/code&gt; options, however I am always confused if to include &lt;code&gt;com&lt;/code&gt; there or in the &lt;code&gt;-selrpos&lt;/code&gt; option.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example:&lt;/strong&gt;&#xA;I have several residues and I want to compute the RDF between the COMs of the selection made by atoms C1 C2 C3 (in all residues). Possible syntax:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1&lt;span class=&quot;math-container&quot;&gt;$ gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &quot;com of name C1 C2 C3&quot; -sel &quot;com of name C1 C2 C3&quot; -selrpos res_com &#xA;2$&lt;/span&gt; gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &amp;quot;com of name C1 C2 C3&amp;quot; -sel &amp;quot;com of name C1 C2 C3&amp;quot;&#xA;3&lt;span class=&quot;math-container&quot;&gt;$ gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &quot;name C1 C2 C3&quot; -sel &quot;name C1 C2 C3&quot; -selrpos res_com &#xA;4$&lt;/span&gt; gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &amp;quot;name C1 C2 C3&amp;quot; -sel &amp;quot;name C1 C2 C3&amp;quot; -selrpos res_com -seltype res_com&#xA;5$ gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &amp;quot;name C1 C2 C3&amp;quot; -sel &amp;quot;name C1 C2 C3&amp;quot; -selrpos whole_res_com -seltype whole_res_com&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;1$&lt;/code&gt; and &lt;code&gt;2$&lt;/code&gt; return zero everywhere, while &lt;code&gt;3$&lt;/code&gt; peaks at atomic positions (not COMs). It seems only last commands (&lt;code&gt;4$&lt;/code&gt; or &lt;code&gt;5$&lt;/code&gt;) are doing somehow what I am looking for but I am not sure what is the difference (and there is difference). So, further confusion is due to the option listed for &lt;code&gt;selrpos&lt;/code&gt;: what would be the difference between res_com, whole_res_com, part_res_com and dyn_res_com?&#xA;Also, the option &lt;code&gt;seltype&lt;/code&gt; is only documented in last versions of &lt;code&gt;gmx rdf&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Besides, I am assuming I could pre-define &amp;quot;C1 C2 C3&amp;quot; as a group via &lt;code&gt;gmx make_ndx&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any clarification is welcome :)&lt;/p&gt;&#xA;" OwnerUserId="1773" LastEditorUserId="5" LastEditDate="2021-03-15T23:01:58.273" LastActivityDate="2021-03-15T23:01:58.273" Title="Compute RDF between COMs of two selections (or groups) using GROMACS" Tags="|molecular-dynamics|gromacs|radial-distribution-function|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3977" PostTypeId="2" ParentId="3975" CreationDate="2020-12-24T18:08:32.627" Score="11" Body="&lt;p&gt;We attempted to solve a similar problem when studying the (also highly symmetrical) &lt;span class=&quot;math-container&quot;&gt;$\ce{CH4}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{CF4}$&lt;/span&gt; homo- and hetero-dimers. I found it easiest to use internal coordinates and fixed molecular geometries to generate the hypersurface, but we also had large computational resources at our disposal and we might have benefitted from using even more, especially to generate more points at larger intermolecular distance.&lt;a href=&quot;http://dx.doi.org/10.1063/1.4919079&quot; rel=&quot;noreferrer&quot;&gt;Chattoraj, Risthaus, Rubner, Heuer, Grimme, &lt;em&gt;J. Chem. Phys.&lt;/em&gt;, &lt;strong&gt;142&lt;/strong&gt;, 164508 (2015)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In your particular case, you should be able to use&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ar}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt; distance&lt;/li&gt;&#xA;&lt;li&gt;the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ar}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{Cl}$&lt;/span&gt; (0 to 180°)&lt;/li&gt;&#xA;&lt;li&gt;a &lt;span class=&quot;math-container&quot;&gt;$\ce{Ar}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{Cl}$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; angle, wherein you use the &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; closest to the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ar}$&lt;/span&gt; (-60 to 60°)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The tricky part remains: picking the right values with which to cover the intervals, which is a bit of trial and error. Some researchers have used &amp;quot;self-healing&amp;quot; approaches, which mean that the configurations with the worst differences between reference and your model are used to refine the model.&lt;/p&gt;&#xA;&lt;p&gt;If you plan to not use a fixed molecular geometry, my approach is of course not valid.&lt;/p&gt;&#xA;" OwnerUserId="794" LastActivityDate="2020-12-24T18:08:32.627" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3978" PostTypeId="2" ParentId="3967" CreationDate="2020-12-24T20:23:26.070" Score="7" Body="&lt;p&gt;Yes, I saw your post on the forum - not sure why that commit didn't make it in, but I have a pull-request now.&lt;/p&gt;&#xA;&lt;p&gt;The long and short is that while the main &amp;quot;guts&amp;quot; of Avogadro 2 are finished, there's a lot of small pieces that need to be done (case in point). Help is always welcome - there are plenty of tasks that can be done in a few hours for anyone interested.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-12-24T20:23:26.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3979" PostTypeId="2" ParentId="3975" CreationDate="2020-12-24T23:01:33.727" Score="8" Body="&lt;p&gt;For 1D analytic potentials, I highly recommend to use &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3264688&quot; rel=&quot;noreferrer&quot;&gt;my potential energy form&lt;/a&gt; or a slight simplification of it, which I can help you with. This is known as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential&quot; rel=&quot;noreferrer&quot;&gt;Morse/Long-Range (MLR) potential&lt;/a&gt; and is now the &amp;quot;industry standard&amp;quot; in high-accuracy spectroscopy and some other areas.&lt;/p&gt;&#xA;&lt;p&gt;For analytic &lt;em&gt;&lt;strong&gt;multi-dimensional&lt;/strong&gt;&lt;/em&gt; potential energy surfaces, there's a few options.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Richard Dawes&lt;/strong&gt; and co-workers have done a lot of work in the area:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119518068.ch5&quot; rel=&quot;noreferrer&quot;&gt;The construction of &lt;em&gt;ab initio&lt;/em&gt;-based potential energy surfaces&lt;/a&gt; (book chapter)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://core.ac.uk/download/pdf/161954606.pdf&quot; rel=&quot;noreferrer&quot;&gt;AUTOSURF: A code for automated construction of potential energy surfaces&lt;/a&gt; (software)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Hui Li&lt;/strong&gt; has generalized the MLR potential (mentioned at the beginning of this answer, for 1D potentials) to multi-dimensional &lt;em&gt;&lt;strong&gt;intermolecular&lt;/strong&gt;&lt;/em&gt; potentials for Van der Waals complexes and reactions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tandfonline.com/doi/abs/10.1080/00268976.2018.1429687&quot; rel=&quot;noreferrer&quot;&gt;Overview&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.rsc.org/--/content/articlelanding/2008/cp/b800718g/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;3D potential for &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2 - He}$&lt;/span&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3041494&quot; rel=&quot;noreferrer&quot;&gt;5D potential for &lt;span class=&quot;math-container&quot;&gt;$\ce{H+3 + CO→H2 + HCO+}$&lt;/span&gt;  and &lt;span class=&quot;math-container&quot;&gt;$\ce{H+3 + CO→H2 + HOC+}$&lt;/span&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.4996086&quot; rel=&quot;noreferrer&quot;&gt;6D potential for &lt;span class=&quot;math-container&quot;&gt;$\ce{OCS - H2}$&lt;/span&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also I have generalized the MLR potential to multi-dimensional &lt;em&gt;&lt;strong&gt;intramolecular&lt;/strong&gt;&lt;/em&gt; potentials &lt;a href=&quot;https://ui.adsabs.harvard.edu/abs/2018isms.confEWB04D/abstract&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, and have some notes on it &lt;a href=&quot;https://github.com/ndattani/polyMLR&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. You may also like to look at the publications lists of Joel Bowman, Hua Guo, Per Jensen, David Schwenke, Antonio Varandas (a co-author of the book &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0471905402&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Potential Energy Functions&lt;/a&gt;, and many others (there's just so many ways to do it!).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-12-24T23:01:33.727" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3980" PostTypeId="2" ParentId="3975" CreationDate="2020-12-25T04:50:51.747" Score="8" Body="&lt;p&gt;On the fitting, I would recommend Dr. Nike Dattani's answer.  You can also try some other methods such as those using neural networks.&lt;/p&gt;&#xA;&lt;p&gt;I read your discussion and find that may be you have also some issues with the scanning using ab initio methods.&lt;/p&gt;&#xA;&lt;p&gt;The intermolecular interaction is often read&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta V_{\rm int}=\Delta V_{\rm int}(R, \theta, \phi),$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; define the position of Ar as if the COM of CH&lt;sub&gt;3&lt;/sub&gt;Cl locates at the origin of the polar coordinate system.&#xA;To scan this, the most common way to do the job is to write the Z-matrix,&#xA;which defines the relative position of the atoms by given the distance between two, angle between three, and dihedral between four atoms.&#xA;In our group, this job is often done by hand, because there are no to much atoms here.&#xA;If you need, you can check the manual of your preferred software, like in Molpro, it is &lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=molecular_geometry#z-matrix_input&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you can define the geometry of one geometry, you can scan the global PES by changing the parameters in the Z-matrix.&lt;/p&gt;&#xA;&lt;p&gt;I believe the trick here is to use &lt;code&gt;dummy centre&lt;/code&gt; to represent the COM.  It means the centre is just an indicator for a reference position instead of a real atom.  In the link to the Molpro manual, it is the &lt;code&gt;Q&lt;/code&gt; or &lt;code&gt;X&lt;/code&gt; atom.&lt;/p&gt;&#xA;&lt;p&gt;Also notice that if you are scanning the intermolecular PES, you need to minimize the Basis set suerposition error (BSSE) by using &lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=molecular_geometry#dummy_centres&quot; rel=&quot;nofollow noreferrer&quot;&gt;counterpoise correction&lt;/a&gt;,&#xA;where you need calculate the energy using the same basis (remember to include the basis for the dummy molecule) three times for every geometry and get the interaction potential as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta V_{\rm int}=E({\rm CH_3Cl+Ar})-E({\rm CH_3Cl})-E({\rm Ar}),$$&lt;/span&gt;&#xA;where the &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;'s are the energy get from the ab initio package you use.&lt;/p&gt;&#xA;&lt;p&gt;Note that you will find the terminology are greatly different among packages.&#xA;In my limited experience, &lt;a href=&quot;http://slater.chemie.uni-mainz.de/cfour/index.php?n=Main.MolecularGeometryInput&quot; rel=&quot;nofollow noreferrer&quot;&gt;CFOUR&lt;/a&gt; will call the first dummy centre (the &lt;code&gt;Q&lt;/code&gt; or &lt;code&gt;X&lt;/code&gt; ones) as 'dummy atom' while call the latter one 'ghost atoms'.  The difference between the two lies in whether the basis functions of the atom are kept in the ab initio computation.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="5" LastEditDate="2020-12-26T19:58:38.120" LastActivityDate="2020-12-26T19:58:38.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3982" PostTypeId="2" ParentId="3956" CreationDate="2020-12-27T01:36:30.243" Score="8" Body="&lt;p&gt;There are two related structures.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Dodecahedrane&quot; rel=&quot;noreferrer&quot;&gt;Dodecahedrane&lt;/a&gt; is known - &lt;span class=&quot;math-container&quot;&gt;$\ce{C20H20}$&lt;/span&gt; in which the carbon atoms form the lattice you described, with hydrogen atoms on the outside.&lt;/p&gt;&#xA;&lt;p&gt;Beyond that, &lt;span class=&quot;math-container&quot;&gt;$\ce{C20}$&lt;/span&gt;, a &lt;a href=&quot;https://en.wikipedia.org/wiki/Fullerene&quot; rel=&quot;noreferrer&quot;&gt;fullerene&lt;/a&gt; is known, and you can find a great variety of &lt;a href=&quot;https://web.archive.org/web/20150109011908/http://www.nanotube.msu.edu/fullerene/fullerene-isomers.html&quot; rel=&quot;noreferrer&quot;&gt;similar structures&lt;/a&gt;, from &lt;span class=&quot;math-container&quot;&gt;$\ce{C20}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\ce{C720}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As for your discussion of quasi-crystals, I think it's well established that there are indeed, aperiodic structures. The &lt;a href=&quot;https://www.nobelprize.org/prizes/chemistry/2011/press-release/&quot; rel=&quot;noreferrer&quot;&gt;Nobel Prize in Chemistry in 2011&lt;/a&gt; was awarded to Dan Shechtman for their discovery (and battle to ensure recognition).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-12-27T01:36:30.243" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="3983" PostTypeId="2" ParentId="3974" CreationDate="2020-12-27T01:57:04.720" Score="9" Body="&lt;p&gt;There are several protocols. Since you mention that you're mostly looking for trends, I'll give the faster method, e.g. by Jason Gilmore:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Expanding and Testing a Computational Method for Predicting the Ground State Reduction Potentials of Organic Molecules on the Basis of Empirical Correlation to Experiment&amp;quot;&#xA;&lt;a href=&quot;https://doi.org/10.1021/jo300853k&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Org. Chem.&lt;/em&gt; &lt;strong&gt;2012&lt;/strong&gt;, 77, 15, 6423–6430&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Optimize the geometry of the neutral and charged species in gas phase (e.g., a faster optimization)&lt;/li&gt;&#xA;&lt;li&gt;Optimize the geometry of the neutral and charged species in solution (e.g., using a polarizable continuum model for your solvent) with a good density functional and basis set.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The 2012 paper from Gilmore mentions optimizing in the gas phase and taking single point energies in solution.&lt;/p&gt;&#xA;&lt;p&gt;I'd recommend at least:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Using a &amp;quot;better&amp;quot; basis set (e.g, from the def2 or pc- series basis sets)&lt;/li&gt;&#xA;&lt;li&gt;Using dispersion correction (this likely won't make much difference but will give you better energies)&lt;/li&gt;&#xA;&lt;li&gt;Using, e.g. &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D3 or some newer functional (although B3LYP/6-31G* still works remarkably well)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Anyway, the main point is this:&#xA;Take the difference in total energy between the optimized neutral molecule (&lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt;) and the radical cation or radical anion (&lt;span class=&quot;math-container&quot;&gt;$D_0$&lt;/span&gt;) &lt;strong&gt;in the solution calculation&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is the ionization potential for that species in solution.&lt;/p&gt;&#xA;&lt;p&gt;It's not a full redox potential - for that you'll want &lt;a href=&quot;https://doi.org/10.1039/C4CP01572J&quot; rel=&quot;noreferrer&quot;&gt;a full thermodynamic cycle&lt;/a&gt; but it yields great trends that correlate very well for many organic redox potentials in acetonitrile.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="142" LastEditDate="2020-12-27T22:25:26.150" LastActivityDate="2020-12-27T22:25:26.150" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3984" PostTypeId="1" AcceptedAnswerId="3985" CreationDate="2020-12-27T17:44:33.343" Score="10" ViewCount="238" Body="&lt;p&gt;I'm trying to obtain an electron density from orbital information written in the Molden format by the formula,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho(\mathbf{r}) = \sum_{i}^{occ} |\phi_{i}(\mathbf{r})|^{2}. \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there any post-processing program to handle this job?&lt;/p&gt;&#xA;&lt;p&gt;I believe that I can make a script on my own, because the Molden file seems to provide coefficients of GTO, but want to check if there are already working examples.&lt;/p&gt;&#xA;&lt;p&gt;It would be desirable that the final density function data is in the format compatible with usual visualization software (such as Molden, VMD, etc.), but I think that it can be visualized if it is represented in a 3D grid.&lt;/p&gt;&#xA;" OwnerUserId="1789" LastEditorUserId="5" LastEditDate="2020-12-27T21:55:46.430" LastActivityDate="2020-12-27T21:55:46.430" Title="Calculating/Visualizing electronic density from orbital information written in the Molden format" Tags="|density-functional-theory|software|computational-chemistry|software-recommendations|from-chem-se|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3985" PostTypeId="2" ParentId="3984" CreationDate="2020-12-27T20:26:12.387" Score="9" Body="&lt;p&gt;I highly recommend &lt;a href=&quot;http://cclib.github.io/methods.html#density-matrix-calculation&quot; rel=&quot;noreferrer&quot;&gt;cclib&lt;/a&gt; which can read Molden and calculate the Density.&lt;/p&gt;&#xA;&lt;p&gt;While I haven't used them as much, I'm pretty certain you can do this with:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://orbkit.github.io/gridbased/highlevel.html&quot; rel=&quot;noreferrer&quot;&gt;Orbkit&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://theochem.github.io/horton/2.1.1/user_estruct_hf_dft.html#reading-a-guess-from-a-file&quot; rel=&quot;noreferrer&quot;&gt;Horton&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are undoubtedly other tools - Molden is a pretty standard format for quantum chemical interchange.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-12-27T20:26:12.387" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3986" PostTypeId="2" ParentId="3545" CreationDate="2020-12-28T07:13:31.887" Score="9" Body="&lt;p&gt;The &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; has two nice implementations of global optimization algorithms. The first is a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html#module-ase.optimize.basin&quot; rel=&quot;noreferrer&quot;&gt;basin hopping algorithm&lt;/a&gt; from a &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp970984n&quot; rel=&quot;noreferrer&quot;&gt;1997 paper&lt;/a&gt; by Wales and Doye in &lt;em&gt;J. Phys. Chem. A&lt;/em&gt;. The second is a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html#minima-hopping&quot; rel=&quot;noreferrer&quot;&gt;minima hopping algorithm&lt;/a&gt; from a &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1724816&quot; rel=&quot;noreferrer&quot;&gt;2004 paper&lt;/a&gt; by Goedecker in &lt;em&gt;J. Chem. Phys&lt;/em&gt;. There are several nice example use-cases &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/tutorials.html#global-optimization&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you're looking at relatively simple organic molecules, I agree with a prior comment that &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/crest.html&quot; rel=&quot;noreferrer&quot;&gt;CREST&lt;/a&gt; is a nice code for sampling lots of conformations to find low-energy structures, which uses the semi-empirical &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;xTB&lt;/a&gt; code as a driver.&lt;/p&gt;&#xA;&lt;p&gt;I should clarify though that finding a global minimum is easier said than done, and the success of any method will depend a lot on the various degrees of freedom for your system.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2020-12-28T07:13:31.887" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3987" PostTypeId="1" CreationDate="2020-12-28T07:43:08.300" Score="11" ViewCount="2119" Body="&lt;p&gt;I am using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; to write an &lt;code&gt;xyz&lt;/code&gt; file. Each frame in the file has a different PBC (periodic boundary condition). Currently, a frame starts like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;192&#xA;Lattice=&amp;quot;23.46511 0.0 0.0 0.0 23.46511 0.0 0.0 0.0 23.46511&amp;quot; Properties=species:S:1:pos:R:3:force:R:3 TotEnergy=-1103.24236 cutoff=-1.0 nneightol=1.2 pbc=&amp;quot;T T T&amp;quot;&#xA;O       11.72590000      14.59020000       1.86929000      -0.04213780       0.03788820       0.00314949&#xA;H       12.69400000      16.13880000       1.25499000      -0.03709700      -0.03453660       0.01566490&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The lattice coordinates are what I want to use as the PBC box. However, when I try to visualize this file in VMD, it throws the following error and doesn't show the box:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;vmd &amp;gt; pbc box&#xA;ERROR) Suspicious pbc side length (a=0.000000 b=0.000000 c=0.000000). Have you forgotten to set the pbc parameters?&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What should be done to include &lt;code&gt;a&lt;/code&gt;,&lt;code&gt;b&lt;/code&gt;,&lt;code&gt;c&lt;/code&gt; in the &lt;code&gt;xyz&lt;/code&gt; file so that it is compatible with &lt;code&gt;pbc box&lt;/code&gt; in VMD?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2020-12-28T08:48:25.490" LastActivityDate="2020-12-29T18:39:48.793" Title="How to include individual PBC box dimensions in xyz file format compatible with VMD" Tags="|software-assistance|atomic-simulation-environment|periodic-boundary-conditions|vmd|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3988" PostTypeId="1" AcceptedAnswerId="3989" CreationDate="2020-12-28T11:05:38.800" Score="17" ViewCount="822" Body="&lt;p&gt;The solution of the many-electron Schrodinger equation is the key to understand the properties of matter. However, it is notorious due to the exponential wall (&lt;a href=&quot;https://www.nobelprize.org/uploads/2018/06/kohn-lecture.pdf&quot; rel=&quot;noreferrer&quot;&gt;for example, see section II (C) of Walter Kohn's Nobel lecture&lt;/a&gt;) of the wavefunction. In fact, it is the Kohn-Sham &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;density functional reformulation&lt;/a&gt; of quantum mechanics that lays the foundation for the current matter modeling.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41557-020-0544-y&quot; rel=&quot;noreferrer&quot;&gt;A recent study published in nature chemistry&lt;/a&gt; claim that the deep-neural-network method numerically solves the electronic Schrödinger equation for molecules with up to 30 electrons with Quantum Monte Carlo methods.&lt;/p&gt;&#xA;&lt;p&gt;Can deep-neural-network offer similar insights or solutions about the solution of many-electron Schrödinger in the framework of density functional theory (DFT)?  Such as the finding of universal energy functional defined by Kohn-Sham's theorem? After all, many data/results based on DFT have been published.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2020-12-28T21:09:18.987" LastActivityDate="2020-12-29T03:18:18.700" Title="Deep Neural Networks: Are they able to provide insights for the many-electron problem or DFT?" Tags="|density-functional-theory|quantum-monte-carlo|kohn-sham|machine-learning|many-body-physics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3989" PostTypeId="2" ParentId="3988" CreationDate="2020-12-28T20:48:52.327" Score="12" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;However, it is notorious due to the exponential wall&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That is completely true, though there's indeed some methods such as &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;noreferrer&quot;&gt;FCIQMC&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5063376&quot; rel=&quot;noreferrer&quot;&gt;SHCI, and DMRG&lt;/a&gt; that try to mitigate this:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/64/5&quot;&gt;How to overcome the exponential wall encountered in full configurational interaction methods?&lt;/a&gt;. The cost of FCIQMC still scales exponentially with respect to the number of electrons when all other variables are treated as control variables, while DMRG scales polynomially in the number of electrons but exponentially in something else (called the &amp;quot;bond dimension&amp;quot;). So while there is probably always an exponential wall, the wall is not always the same wall, and it can take a lot longer to hit one wall than the other in many cases and &lt;em&gt;vice versa&lt;/em&gt; in other cases.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;for example, see section II (C) of Walter Kohn's Nobel lecture&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There has been some discussion about what Kohn said here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1394/5&quot;&gt;Was Walter Kohn wrong about this?&lt;/a&gt; (this is not 100% related to what you're saying, but it's related).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In fact, it is the Kohn-Sham density functional reformulation of quantum mechanics that lays the foundation for the current matter modeling.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That is true for some of the &amp;quot;current matter modeling&amp;quot; going on. There is also some matter modeling such as &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;my entirely &lt;em&gt;ab initio&lt;/em&gt; prediction of the carbon atom's ionization energy to within 1 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;&lt;/a&gt;, and everything in here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/554/5&quot;&gt;How accurate are the most accurate calculations?&lt;/a&gt;, and everything in here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3889/5&quot;&gt;Are there examples of ab initio predictions on small molecules without the &amp;quot;major approximations&amp;quot;?&lt;/a&gt;, and this: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2306/5&quot;&gt;High precision helium energy&lt;/a&gt;, and quite a lot more in the realm of matter modeling, for which people will run as far away from you if you ever mention DFT.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;A recent study published in nature chemistry claim that the deep-neural-network method numerically solves the electronic Schrödinger equation for molecules with up to 30 electrons with Quantum Monte Carlo methods.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Such studies are interesting, but we did 54 electrons both &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5063376&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can deep-neural-network offer similar insights&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Probably the number one criticism I've heard from machine learning experts is that while deep neural networks can give extremely impressive results, they usually do not give &lt;em&gt;&lt;strong&gt;insight&lt;/strong&gt;&lt;/em&gt; the way a physical theory does. For example, Yuri Boykov, a prominent expert in computer vision, told me that in person last year.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;or solutions about the solution of many-electron Schrödinger in the framework of density functional theory (DFT)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They can surely reproduce the same &amp;quot;solutions&amp;quot; within some margin of error, though this is typically for systems &lt;em&gt;&lt;strong&gt;similar to those on which the neural network was originally trained,&lt;/strong&gt;&lt;/em&gt; likely even more so than density functionals working best on systems for which the functionals were optimized, because even on completely different systems, at least the functionals typically have a lot of known physics built into them, see for example this: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1322/5&quot;&gt;Mathematical expression of SCAN (Strongly Constrained and Appropriately Normed) constraints in DFT&lt;/a&gt;, whereas &lt;strong&gt;neural networks are not born knowing anything about physics, chemistry or any theory of matter,&lt;/strong&gt;  though they do learn impressively quickly.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Such as the finding of universal energy functional defined by Kohn-Sham's theorem?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Let's keep our pants on for a little bit longer .&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2020-12-29T03:18:18.700" LastActivityDate="2020-12-29T03:18:18.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3990" PostTypeId="2" ParentId="3987" CreationDate="2020-12-28T21:27:36.110" Score="11" Body="&lt;p&gt;That is a modification of the standard &lt;a href=&quot;https://en.wikipedia.org/wiki/XYZ_file_format&quot; rel=&quot;noreferrer&quot;&gt;XYZ file format&lt;/a&gt; and is called &lt;a href=&quot;https://web.archive.org/web/20190811094343/https://libatoms.github.io/QUIP/io.html#extendedxyz&quot; rel=&quot;noreferrer&quot;&gt;extended XYZ format&lt;/a&gt;, and not all programs are compatible with it.&lt;/p&gt;&#xA;&lt;p&gt;From the &lt;a href=&quot;http://www.ks.uiuc.edu/Research/vmd/plugins/molfile/&quot; rel=&quot;noreferrer&quot;&gt;VMD Molfile Plugin Documentation&lt;/a&gt; page, it looks that VMD is only compatible with standard XYZ format.&lt;/p&gt;&#xA;&lt;p&gt;Also, take a look at &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3970/24&quot;&gt;this&lt;/a&gt; answer (to another question) about adding PBC info in VMD after loading standard XYZ file.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2020-12-28T21:49:15.573" LastActivityDate="2020-12-28T21:49:15.573" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3991" PostTypeId="1" AcceptedAnswerId="4023" CreationDate="2020-12-28T21:47:37.680" Score="11" ViewCount="133" Body="&lt;p&gt;The segmented contracted basis sets are usually handled well by the QM programs than generally contracted basis sets, as the primitives are not repeated. The correlation consistent basis sets (cc-PVnZ) are all generally contracted, and optimized for electron correlation calculations such as CCSD.&lt;/p&gt;&#xA;&lt;p&gt;Would it be possible to make segmented contracted basis sets that performed well for CCSD and other correlation methods? I have been told by my lecturer that in correlated calculations, the HF calculation is the fast step, so there is no real benefit to using segmented contraction. However, I am still curious as to whether it is possible, and if not then why?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-03T21:59:53.230" LastActivityDate="2021-04-05T19:57:31.883" Title="Is it possible to make segmented contracted basis sets for correlated calculations?" Tags="|basis-sets|coupled-cluster|electron-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3992" PostTypeId="1" CreationDate="2020-12-29T07:57:12.843" Score="14" ViewCount="1010" Body="&lt;p&gt;I would like to prove that a 2D material (Say ZnO) is ferroelectric. Since Ferroelectric materials are a subset of piezoelectric materials. How should I proceed to prove that the polarization is indicative of ferroelectric nature?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0IYs8.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0IYs8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;One way would be to show that the spontaneous polarization is reversed by reversing the applied electric field.&lt;/p&gt;&#xA;&lt;p&gt;But this seems not to be the case, as the &lt;a href=&quot;https://www.researchgate.net/post/How-does-confirm-ferroelectricity-from-Density-Functional-Theory&quot; rel=&quot;noreferrer&quot;&gt;Q&amp;amp;A which I've found on ResearchGate&lt;/a&gt; states :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;How does confirm ferroelectricity from Density Functional Theory ? Question&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Ferroelectric materials give spontaneous electric polarization? Is&#xA;there any limit of polarization value for ferroelectric materials?&#xA;How does differ (1) dielectric polarization (2) paraelectric&#xA;polarization and (3) ferroelectric polarization on the basis of DFT&#xA;calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Answer&lt;/strong&gt;&#xA;This is not a simple question! I will deal with the easier parts&#xA;first.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Your definition of ferroelectricity is incomplete. Yes, there should be a spontaneous polarization, but it must be reversible under&#xA;a sufficiently large electric field.&lt;/li&gt;&#xA;&lt;li&gt;The difference between ferroelectric polarization and dielectric or paraelectric polarisation is that in the latter two cases you need to&#xA;apply an electric field to observe the polarisation. The main&#xA;differences between paraelectric and dielectric polarization are&#xA;context - a paraelectric is the state just above the Curie temperature&#xA;of a ferroelectric material and as such will normally exhibit a&#xA;temperature dependence of permittivity that obeys the Curie Weiss law,&#xA;which is evidence of a soft phonon mode. Given the temperature&#xA;constraints of DFT, this is a difficult issue to address. Back to your&#xA;first question; with DFT you can determine whether your material has a&#xA;dipole moment by summing the Born effective charges in the unit cell.&#xA;However you need to be careful about whether you are looking a single&#xA;unit cell or a large supercell to determine whether the dipole moment&#xA;is coherent across all unit cells - that will then confirm whether you&#xA;have a spontaneous polarization and not an antipolar or randomly polar&#xA;material. BUT proving that the spontaneous polarisation is reversible&#xA;is the problem. Essentially the definition of a ferroelectric is a&#xA;phenomenological one - it relies on the observation of a field&#xA;reversible polarisation, which does cause some issues. In experiments,&#xA;you may have a material that from its crystal structure looks as&#xA;though it may have a spontaneous polarization, but for which the&#xA;coercive field is beyond the breakdown field of the material. You&#xA;cannot prove this is ferroelectric. However, your problem is slightly&#xA;different and comes down to how well equipped is your implementation&#xA;of DFT to calculate structures under applied electric fields, i.e. so&#xA;that you can prove reversibility of the dipole moment under a&#xA;sufficiently high field.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Apart from this is there anything I should keep in mind while working with 2D materials?&lt;/p&gt;&#xA;&lt;p&gt;It would be nice to hear some thoughts on the same!&lt;/p&gt;&#xA;&lt;p&gt;Thanks in Advance!&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2021-04-03T15:01:18.053" Title="How can I prove that a material is ferroelectric using DFT?" Tags="|density-functional-theory|2d-lattice|berry-phase|ferroelectric|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="3993" PostTypeId="2" ParentId="518" CreationDate="2020-12-29T10:38:10.137" Score="10" Body="&lt;p&gt;As pointed out by several people already, some information can be found elsewhere, as in &lt;a href=&quot;https://chemistry.stackexchange.com/questions/33764/is-density-functional-theory-an-ab-initio-method/33766#33766&quot;&gt;here&lt;/a&gt;. And also the differentiation between DFT (&lt;strong&gt;exact&lt;/strong&gt;) and density functional approximations (DFAs), as pointed out regularly by Mel Levy, can be found there.&lt;br&gt;&lt;br&gt;&#xA;However, I think there is one aspect missing, and here I would like to quote my late PhD supervisor Jaap Snijders. The most important aspect to know if a method is &lt;em&gt;ab initio&lt;/em&gt; or not, is related to the integrals. If the integrals can be computed &lt;em&gt;from the beginning&lt;/em&gt;, the method is &lt;em&gt;ab initio&lt;/em&gt;; if not, then not. In DFT, DFAs and wavefunction methods, the integrals can be computed, and hence, these methods are &lt;em&gt;ab initio&lt;/em&gt;. In semi-empirical methods (AM1, PM3, DFTB, xtb), some of the integrals are either estimated or approximated (from e.g. DFA results in case of DFTB/xtb), and therefore, these methods are &lt;strong&gt;not &lt;em&gt;ab initio&lt;/em&gt;&lt;/strong&gt;. Likewise for e.g. the Empirical Valence Bond method, which like the name already indicates, is empirical.&lt;br&gt;&lt;br&gt;&#xA;Whether or not a method gives the &lt;strong&gt;exact energy&lt;/strong&gt; is a different aspect. In that case only Full CI with infinite basis set and DFT give the exact energy, all other methods are approximations. By choosing a basis set of a certain size, one is approximating; by using &amp;quot;only&amp;quot; CCSD(T), one is approximating; by using a density functional like PBE, B3LYP or r2SCAN, one is approximating; etc.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2020-12-29T10:38:10.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="3994" PostTypeId="1" CreationDate="2020-12-29T11:51:47.480" Score="10" ViewCount="265" Body="&lt;p&gt;It seems to me that the definition of &amp;quot;nematic phase&amp;quot; is quite chamaleonic.&lt;/p&gt;&#xA;&lt;p&gt;Quoting from its first definition [Nature 393, 550 (1998)] for a 2-dimensional square lattice &amp;quot;The nematic phase breaks the four-fold rotation symmetry of the lattice, but leaves both translation and reflection symmetries unbroken&amp;quot;. This is clearly not possible; if you don't eliminate even reflection symmetries, you cannot break the 4-fold rotation symmetry (mirror planes act as generators of the 4-fold rotation symmetry). Then it is not clear if the therm 'lattice' refers to a true mathematical 'lattice' or to the crystal structure (that is a convolution of the lattice with the basis).&lt;/p&gt;&#xA;&lt;p&gt;Quoting from [Phys. Rev B77, 224509 (2008)] in iron superconductors &amp;quot;... a closely associated structural transition, which we wish to identify as the transition to an “electron nematic phase”&amp;quot;. But the structural transition is from the tetragonal to the orthorhombic system and actually breaks both mirror and translation symmetries. It seems to me that this statement is in contradiction with the above definition.&lt;/p&gt;&#xA;&lt;p&gt;In another paper it is stated &amp;quot;...the distortion is driven by electronic nematicity rather than a lattice (phonon) instability&amp;quot; [Nature Physics 11, 959–963(2015)].&lt;/p&gt;&#xA;&lt;p&gt;So, is it a nematic transition a structural transition simply not driven by lattice (structural) degrees of freedom?&lt;/p&gt;&#xA;" OwnerUserId="1807" LastEditorUserId="5" LastEditDate="2020-12-29T12:22:25.360" LastActivityDate="2020-12-29T12:44:09.647" Title="Nematicity in superconductors" Tags="|symmetry|crystallography|superconductivity|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="3995" PostTypeId="2" ParentId="3681" CreationDate="2020-12-29T12:14:20.943" Score="7" Body="&lt;p&gt;When your lattice is primitive you have only the (0,0,0)+ set; when your lattice has some kind of centering (body- or face-centering) other sets are present, such as (1/2, 1/2, 1/2)+ or (1/2, 1/2, 0)+&lt;/p&gt;&#xA;&lt;p&gt;It's not clear to me what you write. In the first page of the Internationl Tables you find all the symmetry operations that are listed with Roman numerals (1),(2),.... under the heading &amp;quot;Symmetry operations&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Then in the following page under the heading &amp;quot;Positions&amp;quot; you find the differnt Wyckoff sites. The first one represents the general position.&lt;/p&gt;&#xA;&lt;p&gt;Consider the Space Group n°40 - Imm2.&#xA;It has 8 symmetry operations, 4 for the (0,0,0)+ set and 4 for the (1/2,1/2,1/2)+&#xA;As you have 8 symmetry operations, you will have 8 different coordinates for the general position (8e). The Table gives you only the 4 coordinates referring to the (0,0,0)+ set; so the position x,y,z is given by the operation (1) (identity) and for this reason you read (1)x,y,z. the operation (2) is the 2-fold rotation along z, and the corresponding coordinates are -x,-y,z (in other words how the point in x,y,z is moved in a new position after applying the 2-fold rotation). and so on...&lt;/p&gt;&#xA;&lt;p&gt;The 4 remaining coordinates are obtained by simply adding (1/2,1/2,1/2) to each of the 4 above ones.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastEditorUserId="5" LastEditDate="2020-12-29T12:18:52.063" LastActivityDate="2020-12-29T12:18:52.063" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3996" PostTypeId="2" ParentId="3994" CreationDate="2020-12-29T12:44:09.647" Score="9" Body="&lt;h2&gt;Yes, nematic order is an alignment of rotational degrees of freedom without spatial structure.&lt;/h2&gt;&#xA;&lt;p&gt;One good example of a nematic phase occurs in a &lt;a href=&quot;https://en.wikipedia.org/wiki/Liquid_crystal#Nematic_phase&quot; rel=&quot;noreferrer&quot;&gt;liquid crystal composed of elongated molecules.&lt;/a&gt; The molecules can align their long axes (breaking the rotational symmetry) without forming any lattice or long-range correlations in their spatial positions. If you were to just look at the center-of-mass positions of the molecules, there would be no correlations.&lt;/p&gt;&#xA;&lt;p&gt;This term is often poorly defined and is used in many different ways, which can make it really difficult to know exactly what it means in a given situation.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2020-12-29T12:44:09.647" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="3997" PostTypeId="2" ParentId="3987" CreationDate="2020-12-29T13:50:35.773" Score="6" Body="&lt;p&gt;Camps is correct, VMD cannot directly parse the comment line of an xyz file because the extended ASE format is not recognized. You can, however, use a tcl-script to load the file and parse the comment line yourself. I am no tcl expert but here is an example that works for me:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-tcl prettyprint-override&quot;&gt;&lt;code&gt;set filename [lindex $argv 0]&#xA;    &#xA;# load the coordinates into vmd&#xA;mol new $filename waitfor all&#xA;    &#xA;# open the file to parse the lattice vectors&#xA;set file [open $filename]&#xA;    &#xA;set i 0&#xA;    &#xA;while {[gets &lt;span class=&quot;math-container&quot;&gt;$file line] &amp;gt;= 0} {&#xA;  # get the lines containing Lattice=&quot;&#xA;  if {[regexp {Lattice=\&quot;[ 0-9\.\-eE]*} $line lattice]} {  &#xA;    # extract the numbers from the line into v_arr&#xA;    set vectors [regexp -all -inline {\S+} [lindex [split $line \&quot;] 1]]&#xA;    set j 0     &#xA;    foreach v $vectors {&#xA;      set v_arr($j) $v&#xA;      incr j&#xA;    }&#xA;    # set the pbc for the i-th frame&#xA;    # uncomment the second line if the cell is not orthorhombic&#xA;    pbc set &quot;{$v_arr(0) $v_arr(4) $v_arr(8)}&quot; -first $i -last $i&#xA;    #pbc set &quot;{{$v_arr(0) $v_arr(1) $v_arr(2)} {$v_arr(3) $v_arr(4) $v_arr(5)} {$v_arr(6) $v_arr(7) $v_arr(8)}}&quot; -namd -first $i -last $&lt;/span&gt;i&#xA;    incr i&#xA;  }&#xA;}&#xA;    &#xA;close $file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Save the code into a file &amp;quot;pbc.tcl&amp;quot;. You can then invoke the script by running&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;vmd -e pbc.tcl -args trajectory.xyz&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;This will automatically load the coordinates and parse the lattice vectors from trajectory.xyz. The -e flag signals vmd to execute the code within pbc.tcl and passes the -args to the script.&lt;/p&gt;&#xA;" OwnerUserId="295" LastEditorUserId="7" LastEditDate="2020-12-29T18:39:48.793" LastActivityDate="2020-12-29T18:39:48.793" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="3998" PostTypeId="2" ParentId="3966" CreationDate="2020-12-29T18:25:51.793" Score="5" Body="&lt;p&gt;I'm not sure if I understand your question completely, especially this part:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As can be seen, supercell would change the polarization quanta &lt;span class=&quot;math-container&quot;&gt;$e\textbf{R}i/\Omega$&lt;/span&gt;, thus change the calculated polarization &lt;span class=&quot;math-container&quot;&gt;$\textbf{P}_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'm guessing &lt;span class=&quot;math-container&quot;&gt;$\textbf{P}_0$&lt;/span&gt; here stands for the polarization modulo &lt;span class=&quot;math-container&quot;&gt;$e\textbf{R}i/\Omega$&lt;/span&gt;. If that's the case, then I don't think using a supercell instead of a primitive cell will change the value of &lt;span class=&quot;math-container&quot;&gt;$\textbf{P}_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The macroscopic polarization in the framework of the &amp;quot;modern theory of polarization&amp;quot; is calculated by &lt;strong&gt;taking the difference&lt;/strong&gt; of values calculated with centrosymmetric structure and ferroelectric structure, assuming they are on the same &amp;quot;branch&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Using a supercell can indeed change the polarization quantum, but these changes take place in both centrosymmetric and ferroelectric structures and because the polarization of these two structures needs to be on the same &amp;quot;branch&amp;quot;, they have the same changes. In the end, the effect of using a supercell is canceled out.&lt;/p&gt;&#xA;&lt;p&gt;I hope this is helpful =)&lt;/p&gt;&#xA;" OwnerUserId="1804" LastEditorUserId="1804" LastEditDate="2020-12-29T18:28:27.750" LastActivityDate="2020-12-29T18:28:27.750" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="3999" PostTypeId="2" ParentId="3961" CreationDate="2020-12-29T19:20:54.857" Score="5" Body="&lt;p&gt;You can use &lt;a href=&quot;https://atomsk.univ-lille.fr&quot; rel=&quot;nofollow noreferrer&quot;&gt;ATOMSK&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The command:&lt;br /&gt;&#xA;&lt;code&gt;atomsk initial.xyz -wrap final.xyz&lt;/code&gt;&lt;br /&gt;&#xA;will wrap all the atom coordinates back into your simulation box.&lt;br /&gt;&#xA;&lt;code&gt;initial.xyz&lt;/code&gt; is your input file and &lt;code&gt;final.xyz&lt;/code&gt; is the output after wrapping all atoms back into the simulation box.&lt;/p&gt;&#xA;&lt;p&gt;You can get the output in many different formats. ATOMSK is quite powerful and simple to use. Please have a look at its &lt;a href=&quot;https://atomsk.univ-lille.fr/doc.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="5" LastEditDate="2020-12-29T19:29:34.677" LastActivityDate="2020-12-29T19:29:34.677" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4000" PostTypeId="1" CreationDate="2020-12-29T20:50:13.367" Score="13" ViewCount="649" Body="&lt;p&gt;The Kohn-Sham equation as described in &amp;quot;Density Functional Theory: A Practical Introduction&amp;quot; by Dr David Sholl is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\left[-\frac{\hbar^2}{2m}\nabla^2+V({\bf r})+V_H({\bf r})+V_{XC}({\bf r})\right]\psi_i({\bf r})=\varepsilon_i\psi_i({\bf r}).$$&lt;/span&gt; The first term on the left-hand side represents the kinetic energy of the electrons. The second term represents electron-ion interaction and the third represents electron-electron interaction. The last term is the exchange-correlation potential.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;With the Born-Oppenheimer approximation we neglect the kinetic energy of ions. What about the ion-ion interaction potential?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In lattice dynamics studies, we account specifically for the ion-ion interaction but with minute oscillations of the ions. I believe DFT would still account for the interaction among stationary ions in the static lattice viewpoint.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2020-12-29T23:43:23.073" LastActivityDate="2020-12-30T19:39:52.857" Title="Ion-ion interaction potential in Kohn-Sham DFT" Tags="|density-functional-theory|kohn-sham|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4001" PostTypeId="2" ParentId="4000" CreationDate="2020-12-29T23:58:17.997" Score="11" Body="&lt;p&gt;If the ion-ion interaction contributes a constant term to the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, then our new Hamiltonian is &lt;span class=&quot;math-container&quot;&gt;$H+C$&lt;/span&gt;. &lt;em&gt;&lt;strong&gt;The eigenvalue of a constant is just itself&lt;/strong&gt;&lt;/em&gt;, so we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;(H + C )\psi = (\epsilon + C)\psi&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So if your DFT code calculates only &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; (the energy if you neglect the ion-ion interaction), it is easy to obtain the energy &lt;em&gt;&lt;strong&gt;with&lt;/strong&gt;&lt;/em&gt; the ion-ion interaction by simply adding the constant &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;, which is something that does not need a complicated DFT code. The DFT code can easily add the energy coming from the ion-ion interaction &lt;em&gt;at the end of the calculation&lt;/em&gt; in the same way that things like the nuclear-nuclear repulsion energy might be added in a molecular quantum chemistry software.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2020-12-29T23:58:17.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4002" PostTypeId="2" ParentId="4000" CreationDate="2020-12-30T01:06:43.123" Score="10" Body="&lt;p&gt;Add more information to @Nike Dattani's answer:&lt;/p&gt;&#xA;&lt;p&gt;The matter can be viewed as a set of ions and electrons. The Kohn-Sham equation listed in your post aims to solve the electronic part. As for the ionic part, which is usually treated classically in the framework of Newton's mechanics. The ion-ion potential or force can be calculated with the empirical method (classical molecular dynamics) or the first-principles method (ab-initio molecular dynamics).&lt;/p&gt;&#xA;&lt;p&gt;Within the first-principles method, the total energy of the system is calculated with density functional theory then the force is calculated by energy derivative.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2020-12-30T01:06:43.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4003" PostTypeId="1" AcceptedAnswerId="6230" CreationDate="2020-12-30T03:15:47.563" Score="11" ViewCount="770" Body="&lt;p&gt;I am noticing a possible convergence problem in a magnetic &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; system I am studying.  In the &lt;code&gt;OSZICAR&lt;/code&gt; file I often see the rms(c) value go to about &lt;code&gt;0.2e+3&lt;/code&gt; and stabilize.  Can anyone suggest what may be wrong in my calculation that can cause this?&lt;/p&gt;&#xA;&lt;p&gt;I suspect the mixing parameters are the issue and I have tried the defaults as well as the pseudolinear mixing suggested by VASP of &lt;code&gt;AMIX=0.3&lt;/code&gt;, &lt;code&gt;BMIX=0.001&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Here is the start of the &lt;code&gt;OSZICAR&lt;/code&gt; output.  I am working on tungsten oxides using the materials project default parameters in terms of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, pseudopotentials, and general energy cutoffs.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1     0.996952880030E+03    0.99695E+03   -0.39229E+04  3360   0.140E+03&#xA;DAV:   2     0.420320154504E+02   -0.95492E+03   -0.89279E+03  3588   0.430E+02&#xA;DAV:   3    -0.925122529562E+02   -0.13454E+03   -0.13109E+03  3832   0.172E+02&#xA;DAV:   4    -0.981421469589E+02   -0.56299E+01   -0.55757E+01  3984   0.375E+01&#xA;DAV:   5    -0.983539220900E+02   -0.21178E+00   -0.21087E+00  5016   0.665E+00&#xA;DAV:   6    -0.983570555376E+02   -0.31334E-02   -0.31033E-02  4224   0.800E-01&#xA;DAV:   7    -0.983571847233E+02   -0.12919E-03   -0.12837E-03  4920   0.162E-01&#xA;DAV:   8    -0.983571860469E+02   -0.13235E-05   -0.13192E-05  2656   0.166E-02    0.662E+01&#xA;DAV:   9    -0.804838944016E+02    0.17873E+02   -0.44298E+01  4544   0.495E+01    0.381E+01&#xA;DAV:  10    -0.811208958861E+02   -0.63700E+00   -0.38276E+01  4936   0.568E+01    0.188E+03&#xA;DAV:  11    -0.814674048119E+02   -0.34651E+00   -0.42624E+00  3756   0.964E+00    0.188E+03&#xA;DAV:  12    -0.803474022983E+02    0.11200E+01   -0.27246E-01  4264   0.268E+00    0.184E+03&#xA;DAV:  13    -0.803447815420E+02    0.26208E-02   -0.15007E-02  3696   0.671E-01    0.184E+03&#xA;DAV:  14    -0.827481331115E+02   -0.24034E+01   -0.11705E+00  5324   0.101E+01    0.188E+03&#xA;DAV:  15    -0.830941535514E+02   -0.34602E+00   -0.19499E-01  4256   0.245E+00    0.188E+03&#xA;DAV:  16    -0.827076829935E+02    0.38647E+00   -0.19109E-01  4028   0.362E+00    0.188E+03&#xA;DAV:  17    -0.839071530160E+02   -0.11995E+01   -0.18920E+00  4072   0.775E+00    0.188E+03&#xA;DAV:  18    -0.852362012098E+02   -0.13290E+01   -0.19289E+00  4272   0.700E+00    0.188E+03&#xA;DAV:  19    -0.850163602711E+02    0.21984E+00   -0.43203E-01  3960   0.207E+00    0.188E+03&#xA;DAV:  20    -0.853790409329E+02   -0.36268E+00   -0.21727E+01  4452   0.694E+00&#xA;   1 F= -.85379041E+02 E0= -.85379041E+02  d E =-.853790E+02  mag=    -0.3688&#xA;quench:  g(F)=  0.000E+00 g(S)=  0.000E+00 dE (1.order)= 0.000E+00&#xA; bond charge predicted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-06-22T01:25:04.313" LastActivityDate="2021-06-23T18:31:05.967" Title="Charge density convergence within VASP using spin polarized DFT+U" Tags="|vasp|numerical-convergence|charge-density|dft-u|anti-ferromagnetic|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4004" PostTypeId="2" ParentId="3693" CreationDate="2020-12-30T08:09:17.803" Score="4" Body="&lt;p&gt;Take care in the figure posted by Jack that the [hkl] notation actually represents the vector plane, that is the direction perpendicular to the plane. The plane are indexed as (hkl).&lt;/p&gt;&#xA;&lt;p&gt;for example, the first figure should be read as (001) plane of NaCl, whereas [001] represents the direction along the c-axis.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2020-12-30T08:09:17.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4005" PostTypeId="2" ParentId="4000" CreationDate="2020-12-30T16:02:26.787" Score="8" Body="&lt;p&gt;I would like to emphasise a few aspects that seem to be a little bit between the lines in the other answers.&lt;/p&gt;&#xA;&lt;p&gt;Density functional theory is based on the fact that observables of an interacting-electron system can in principle be obtained from its ground-state electron density. The Kohn-Sham system is a means of obtaining this density (and a few other objects that make certain calculations more reasonable). Obviously the interaction between the nuclei does not directly affect the ground-state electron density and therefore it is not required to include this interaction directly in the Kohn-Sham system&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless this interaction is very important when calculating the total energy of a system. For a system with a unit cell &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; containing atoms with core charges &lt;span class=&quot;math-container&quot;&gt;$Z_\alpha$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\tau}_\alpha$&lt;/span&gt; and featuring a spin-dependent ground-state electron density &lt;span class=&quot;math-container&quot;&gt;$\rho^\sigma$&lt;/span&gt; and Kohn-Sham eigenvalues &lt;span class=&quot;math-container&quot;&gt;$E_{\nu,\sigma}$&lt;/span&gt; the total energy functional is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E_\text{total}[\rho^\uparrow,\rho^\downarrow] &amp;amp;= \underbrace{\left[\sum\limits_\sigma \left(\sum\limits_{\nu=1}^{N_\text{occ}^\sigma} E_{\nu,\sigma}\right) - \int\limits_{\Omega} \rho^\sigma(\mathbf{r}) V_{\text{eff},\sigma}(\mathbf{r}) d^3 r \right]}_{E_\text{kin}}\nonumber \\ &amp;amp;\phantom{=} + \underbrace{\frac{1}{2}\int\limits_{\Omega}\int\limits_{\Omega}\frac{\rho(\mathbf{r})\rho(\mathbf{r}')}{\vert\mathbf{r}-\mathbf{r}'\vert} d^3rd^3r' + \int\limits_{\mathbb{R}^3\backslash \Omega}\int\limits_{\Omega}\frac{\rho(\mathbf{r})\rho(\mathbf{r}')}{\vert\mathbf{r}-\mathbf{r}'\vert} d^3rd^3r'}_{E_\text{H}} \\ &amp;amp;\phantom{=} + \underbrace{\int\limits_{\Omega} V_\text{ext}(\mathbf{r}) \rho(\mathbf{r})d^3r \nonumber}_{E_\text{ext}} + E_\text{xc}[\rho^\uparrow,\rho^\downarrow] \\ &amp;amp;\phantom{=}  + \underbrace{\frac{1}{2}\sum\limits_{\alpha \in \Omega}^{N_\text{atom}} \sum\limits_{\substack{\beta \in \Omega \\ \alpha\neq \beta}}^{N_\text{atom}} \frac{Z_\alpha Z_\beta}{\vert\mathbf{\tau}_\alpha - \mathbf{\tau}_\beta\vert} + \sum\limits_{\alpha \not\in \Omega} \sum\limits_{\beta \in \Omega}^{N_\text{atom}} \frac{Z_\alpha Z_\beta}{\vert\mathbf{\tau}_\alpha - \mathbf{\tau}_\beta\vert}}_{E_\text{II}}.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this expression &lt;span class=&quot;math-container&quot;&gt;$E_\text{kin}$&lt;/span&gt; denotes the kinetic energy of the occupied Kohn-Sham orbitals, &lt;span class=&quot;math-container&quot;&gt;$E_\text{H}$&lt;/span&gt; the Hartree energy, &lt;span class=&quot;math-container&quot;&gt;$E_\text{ext}$&lt;/span&gt; the energy due to the interaction between the electrons and the external potential, &lt;span class=&quot;math-container&quot;&gt;$E_\text{XC}$&lt;/span&gt; the exchange-correlation energy, and &lt;span class=&quot;math-container&quot;&gt;$E_\text{II}$&lt;/span&gt; the energy due to the Coulomb interaction between the ionized atomic nuclei.&lt;/p&gt;&#xA;&lt;p&gt;By having a look at this expression two properties directly become obvious:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_\text{II}$&lt;/span&gt; gives an energy contribution that depends on the coordinates of the atomic nuclei relative to each other. This term therefore is important when calculating forces &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F}_\alpha = -\frac{\delta E_\text{total}}{\delta \mathbf{\tau}_\alpha}$&lt;/span&gt; and also when only relating different structures to each other that have slightly different atom distances, e.g., when calculating a lattice constant.&lt;/li&gt;&#xA;&lt;li&gt;For periodic systems like crystals &lt;span class=&quot;math-container&quot;&gt;$E_\text{H}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_\text{ext}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$E_\text{II}$&lt;/span&gt; each are divergent. This is because of the long range of the Coulomb interaction together with the inclusion of contributions from the whole space outside the unit cell. These energy contributions only become finite when combined. For such systems neglecting &lt;span class=&quot;math-container&quot;&gt;$E_\text{II}$&lt;/span&gt; therefore would result in a divergent total energy for the unit cell. Also care has to be taken to evaluate these contributions such that intermediate results don't diverge. A similar divergence arises if the periodically repeated unit cell is not charge neutral. Such a situation would lead to an infinite charge in the whole crystal implying an infinite electrostatic energy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Taking into account the ion-ion interaction within a DFT procedure therefore is essential, not optional. But you will not see it explicitly in the Kohn-Sham equations.&lt;/p&gt;&#xA;&lt;p&gt;[1] Of course, the issue of divergent contributions for infinite setups also has to be taken care of in the Kohn-Sham system.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2020-12-30T19:39:52.857" LastActivityDate="2020-12-30T19:39:52.857" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4006" PostTypeId="1" AcceptedAnswerId="4008" CreationDate="2020-12-30T19:19:25.320" Score="9" ViewCount="569" Body="&lt;p&gt;In &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.28.3160&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; old paper on Monte Carlo simulations of Lennard-Jones solid, specific heat behaviour (both &lt;span class=&quot;math-container&quot;&gt;$c_p$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c_v$&lt;/span&gt;) have been reported. As you can see from the picture below, both &lt;span class=&quot;math-container&quot;&gt;$c_p$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c_v$&lt;/span&gt; goes to &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$0K$&lt;/span&gt;. &lt;em&gt;[The units in the plot are dimensionless reduced units defined based on the Lennard-Jones potential parameters]&lt;/em&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/2Yf99.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2Yf99.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, the heat capacity goes to zero, if the temperature approaches &lt;span class=&quot;math-container&quot;&gt;$0K$&lt;/span&gt;. Why this is not reflected here? Could this be due to the lack of quantum effects in the simulation?&lt;/p&gt;&#xA;" OwnerUserId="605" LastEditorUserId="5" LastEditDate="2020-12-30T23:44:20.943" LastActivityDate="2020-12-30T23:44:20.943" Title="Why is specific heat not zero at absolute zero?" Tags="|statistical-thermodynamics|thermodynamics|monte-carlo|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4007" PostTypeId="2" ParentId="1697" CreationDate="2020-12-30T21:20:52.603" Score="4" Body="&lt;p&gt;Also worth mentioning Bill Hoover's excellent textbooks, &lt;a href=&quot;http://williamhoover.info/MD.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Dynamics&lt;/a&gt; which provide an introduction and a slightly different perspective on molecular dynamics, along with &lt;a href=&quot;http://williamhoover.info/book.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Statistical Mechanics&lt;/a&gt;. They are freely downloadable from &lt;a href=&quot;http://www.williamhoover.info/&quot; rel=&quot;nofollow noreferrer&quot;&gt;his website&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I also second Tuckerman's &amp;quot;Statistical Mechanics: Theory and Molecular Simulation&amp;quot; as one of the most accessible introdutions to the topic and Rapaport &amp;quot;The art of molecular dynamics&amp;quot; for anyone who wants to write an MD code themself.&lt;/p&gt;&#xA;&lt;p&gt;For non-equilibrium molecular dynamics, classics are the comprehensive but fairly steep Evans and Morriss &amp;quot;Statistical mechanics of nonequilibrium liquids&amp;quot; and the more accessible Todd and Daivis &amp;quot;Nonequilibrium Molecular Dynamics Theory, Algorithms and Applications&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="1305" LastEditorUserId="7" LastEditDate="2020-12-30T21:56:25.970" LastActivityDate="2020-12-30T21:56:25.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4008" PostTypeId="2" ParentId="4006" CreationDate="2020-12-30T21:52:34.060" Score="9" Body="&lt;p&gt;You are correct that this is due to not including quantum effects. Ref 1 in your figure is the paper cited below. In this paper, they explicitly mention that &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; calculated using the cell-cluster method is in good agreement only for sufficiently high reduced-temperatures. From section IV of this paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...the calculation is in acceptable agreement with experiment, except for low reduced temperatures, where quantum- mechanical effects become significant.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As further illustration, this paper has a similar plot of the cell-cluster results, but instead of comparing against Monte Carlo, they compare with experimental results for xenon.&lt;/p&gt;&#xA;&lt;p&gt;              &lt;a href=&quot;https://i.stack.imgur.com/mza5b.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mza5b.png&quot; alt=&quot;Heat capacities: cell-cluster vs experiment&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, the experimental results approach zero as they should. The cell-cluster results do at least satisfy &lt;a href=&quot;https://en.wikipedia.org/wiki/Mayer%27s_relation&quot; rel=&quot;noreferrer&quot;&gt;Mayer's Relation&lt;/a&gt;, which says &lt;span class=&quot;math-container&quot;&gt;$C_P-C_V=0$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$T=\pu{0K}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;K. Westera and E. R. Cowley Phys. Rev. B 11, 4008 (1975) DOI: 10.1103/PhysRevB.11.4008&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2020-12-30T21:52:34.060" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4009" PostTypeId="2" ParentId="3545" CreationDate="2020-12-31T03:22:14.857" Score="4" Body="&lt;h2&gt;Bayesian Optimization&lt;/h2&gt;&#xA;&lt;p&gt;There are some nice options for exploring potential energy surfaces using &lt;a href=&quot;https://en.wikipedia.org/wiki/Bayesian_optimization&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bayesian optimization&lt;/a&gt;. This has the advantage of using &lt;a href=&quot;https://en.wikipedia.org/wiki/Gaussian_process&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian Process regression&lt;/a&gt; to build a surrogate to the potential energy surface&lt;/p&gt;&#xA;&lt;p&gt;Bayesian optimization works extremely well for &amp;quot;expensive&amp;quot; functions (e.g., minutes to hours per point) in which the overhead of performing the GPR is offset by efficiently exploring the potential energy surface - perfect for first principles calculations.&lt;/p&gt;&#xA;&lt;p&gt;My group has some efficient methods for finding the global minima, but not exploring the entire PES.&lt;/p&gt;&#xA;&lt;p&gt;You might want to check out BOSS by the &lt;a href=&quot;http://cest.aalto.fi/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Aalto group&lt;/a&gt;:&#xA;&lt;a href=&quot;https://cest-group.gitlab.io/boss/tutorials.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://cest-group.gitlab.io/boss/tutorials.html&lt;/a&gt;&#xA;e.g.&#xA;&lt;a href=&quot;https://arxiv.org/abs/2006.15006&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Efficient Cysteine Conformer Search with Bayesian Optimization&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;They find a &amp;gt;10x speedup over a genetic algorithm.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2020-12-31T03:22:14.857" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4010" PostTypeId="2" ParentId="1967" CreationDate="2020-12-31T08:02:09.420" Score="5" Body="&lt;p&gt;&lt;strong&gt;1) Using CALYPSO with Quantum ESPRESSO&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I want to create a nanoparticle of CuO and predict it's structure.&#xA;I've done unit cell relaxation with Quantum ESPRESSO. One tool to&#xA;predict nanocluster structure is Calypso which is PSO-based. I'm using&#xA;Quantum ESPRESSO with it. If anyone does Calypso structure prediction,&#xA;what are some ways for predicting nanocluster structure?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I've never used CALYPSO but you could follow this &lt;a href=&quot;https://www.bragitoff.com/2019/03/nanocluster-global-optimization-using-calypso-and-quantum-espresso/&quot; rel=&quot;noreferrer&quot;&gt;tutorial&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;2) DFT on nanoclusters [The general stuff]:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can refer to this &lt;a href=&quot;https://www.youtube.com/watch?v=Z8TEpaW7RNc&quot; rel=&quot;noreferrer&quot;&gt;video&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;3) TDDFT on nanoclusters [TurboTDDFT + Quantum ESPRESSO]:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I want to use this nanostructure to calculate TDDFT and some other&#xA;optical properties.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Although I'm not an avid used of this software I've heard that this can be done via the &lt;strong&gt;TurboTDDFT software&lt;/strong&gt; along with Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465511001512&quot; rel=&quot;noreferrer&quot;&gt;TurboTDDFT software:&lt;/a&gt;&lt;/strong&gt; It is an implementation of the Liouville–Lanczos approach to linearized time-dependent density-functional theory, designed to simulate the optical spectra of molecular systems made of up to several hundred atoms.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Acquistion of the code as per comments in the paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Additional comments: !!!!! The distribution file for this program is&#xA;over 254 Mbytes and therefore is not delivered directly when download&#xA;or E-mail is requested. Instead a html file giving details of how the&#xA;program can be obtained is sent.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2020-12-31T08:12:52.940" LastActivityDate="2020-12-31T08:12:52.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4011" PostTypeId="1" CreationDate="2020-12-31T08:27:01.893" Score="11" ViewCount="1220" Body="&lt;p&gt;I have calculated Frequency dependent optical permittivity of Au using (VASP) my INCAR tag includes &lt;code&gt;LOPTICS=.TURE.&lt;/code&gt;, my &lt;code&gt;OUTCAR&lt;/code&gt; has expected frequency dependent &lt;code&gt;IMAGINARY DIELECTRIC FUNCTION&lt;/code&gt; and so to speak the data in xx yy zz xy yz zx format.&#xA;Unfortunately when it comes to plotting I have seen a very strange behavior i.e. the Au plots are for interband , rather than intraband or total. I used p4V , &lt;code&gt;vaspkit&lt;/code&gt; , bash files to separate out the Imaginary and real files but results have been shown are same and not responding according to literature. I shall be highly thankful to highlight the problem in my calculation.&#xA;Kramer-Kronig transformation is not enough using &lt;code&gt;LOPTICS&lt;/code&gt;? on the other hand GW0+BSE and &lt;code&gt;ALGO CHI&lt;/code&gt; takes a lot of memory and system can't finish the calculation.&lt;a href=&quot;https://i.stack.imgur.com/nHZph.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nHZph.png&quot; alt=&quot;Added picture is desired plotting but my calculation only shows the interband optical losses&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1326" LastEditorUserId="5" LastEditDate="2020-12-31T08:50:08.930" LastActivityDate="2021-01-06T15:06:02.397" Title="DFT optical calculation and plotting for real and imaginary permittivity in VASP?" Tags="|density-functional-theory|vasp|optical-properties|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4014" PostTypeId="1" CreationDate="2021-01-01T03:36:32.550" Score="10" ViewCount="1026" Body="&lt;p&gt;The following figure is the bulk structure of NiSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; downloaded from the &lt;a href=&quot;https://materialsproject.org/materials/mp-20901/&quot; rel=&quot;nofollow noreferrer&quot;&gt;materials project database.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yQmgJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yQmgJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now I want to study the properties of its [111] plane. In detail, I cut the slab with &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;atomic simulation environment (ASE)&lt;/a&gt; as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;from ase.build import surface&#xA;&#xA;####=============================================&#xA;&#xA;structA=read('NiSe2.vasp', format='vasp')&#xA;structB=surface(structA, (1,1,1), 3, vacuum=10)&#xA;write('111.vasp', structB, format='vasp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The cutted slab is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mCgRa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mCgRa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In particular, I find the Se5 atom is strange. In addition, the cutted slab is different from &lt;a href=&quot;https://pubs.rsc.org/en/Content/ArticleLanding/RA/2014/C3RA47564F#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8PCb6.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8PCb6.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here different terminations are considered. Therefore, how can I use ASE cut these (111) slabs with different terminations?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="6055" LastEditDate="2023-03-14T08:15:21.440" LastActivityDate="2023-03-14T08:15:21.440" Title="How to build the [111] slab model of NiSe2 with different terminations with ASE tool?" Tags="|python|crystallography|surfaces|atomic-simulation-environment|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4015" PostTypeId="2" ParentId="1701" CreationDate="2021-01-01T03:40:43.077" Score="6" Body="&lt;p&gt;As a first step, you can use the &lt;a href=&quot;http://www.wanniertools.com/&quot; rel=&quot;noreferrer&quot;&gt;WannierTools.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There are five typical examples in there.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Bi2Se3 (3D strong TI)&lt;/li&gt;&#xA;&lt;li&gt;MoS2 (2D QSHE)&lt;/li&gt;&#xA;&lt;li&gt;WTe2 (Type II Weyl semimetal)&lt;/li&gt;&#xA;&lt;li&gt;IrF4 (Nodal Chain metals)&lt;/li&gt;&#xA;&lt;li&gt;FeSi (Weyl point in Phonon system)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-01T03:40:43.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4016" PostTypeId="2" ParentId="4014" CreationDate="2021-01-01T04:51:56.523" Score="9" Body="&lt;p&gt;There is currently no tool built into ASE to do this sort of detective work on surface terminations.  I highly suggest that you take the approach of trying to eliminate dangling bonds first (for example, Se atoms with only 1 neighbor).  This will give you a more reasonable termination, but may not give you the desired Ni-Se ratio.  With a complex unit cell like this, you may not find a solution that is automated unfortunately.&lt;/p&gt;&#xA;&lt;p&gt;What you can do though if studying a common class of materials is to use ASE as a first pass, clean up the terminations in ase-gui, then save that template.  Then start from this template rather than the bulk material if you study similar materials.  You may find this easier if you color the atoms by coordination number.&lt;/p&gt;&#xA;&lt;p&gt;You may find &lt;a href=&quot;https://pymatgen.org/index.html&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; or &lt;a href=&quot;https://catkit.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;catkit&lt;/a&gt; more capable than ASE at generating surfaces, I have heard they tend to do a slightly better job but this is a complex issue.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-01T04:51:56.523" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4017" PostTypeId="1" CreationDate="2021-01-01T05:19:02.527" Score="14" ViewCount="937" Body="&lt;p&gt;I am reviewing some information in the Materials Project and notice that they do not use DFT+U to model copper oxides.  Since the methodology for fitting U is largely based on the 2006 Ceder paper, I am curious why this was omitted.&lt;/p&gt;&#xA;&lt;p&gt;Is DFT+U just not needed for copper oxides?  This is very surprising to me as most other 3d transition metals benefit from U corrections.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-01-02T17:30:34.773" LastActivityDate="2021-01-02T17:30:34.773" Title="Hubbard U correction for Copper" Tags="|reference-request|transition-metals|dft-u|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4018" PostTypeId="1" AcceptedAnswerId="4025" CreationDate="2021-01-01T13:51:38.427" Score="9" ViewCount="444" Body="&lt;p&gt;I have used both &lt;code&gt;SUMO&lt;/code&gt; and &lt;code&gt;P4VASP&lt;/code&gt; to generate a DOS plot. I have found that there's a shift (displacement) between the two DOS generated by the two computer programs. I am wondering which software has already subtracted the Fermi energy, or did both do that?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-01-01T14:09:19.447" LastActivityDate="2021-01-02T15:50:46.373" Title="Does the DOS plotted by p4vasp already have Fermi energy subtracted?" Tags="|density-functional-theory|vasp|density-of-states|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4021" PostTypeId="2" ParentId="4017" CreationDate="2021-01-01T17:50:03.237" Score="7" Body="&lt;p&gt;I can't speak as to how the Materials Project selects what information to display, but it's clear that the Hubbard &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; (or rather the correlations/interactions it attempts to capture) generally is important for copper oxides. This is very clear in the cuprate high-&lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; superconductors, which are often modeled as doped antiferromagnetic insulators. The &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; also helps in the case of simple copper oxides CuO, and Cu&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;O&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, but standard DFT + U is no panaceum and has problems with Cu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O, as discussed recently in &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.99.035154&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B 99, 035154 (2019)&lt;/a&gt; (alternate link at &lt;a href=&quot;http://orca-mwe.cf.ac.uk/119200/&quot; rel=&quot;noreferrer&quot;&gt;Cardiff repository&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-01-01T17:50:03.237" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4022" PostTypeId="2" ParentId="3942" CreationDate="2021-01-01T19:35:16.197" Score="27" Body="&lt;h2&gt;tldr: This is something of an eternal debate.&lt;/h2&gt;&#xA;&lt;p&gt;IMHO very small imaginary frequencies can be okay, but it depends on your system and needs.&lt;/p&gt;&#xA;&lt;p&gt;As you might see from the various comments above, there are often different opinions on whether very small imaginary frequencies matter. The truth is, that it depends a bit on the size of the molecule and what you plan to do.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;strong&gt;principle&lt;/strong&gt;, if you've reached a true local / global minima of the potential energy surface, there should &lt;em&gt;&lt;strong&gt;never&lt;/strong&gt;&lt;/em&gt; be imaginary frequencies, because if the second derivative is negative, you're not at a minimum with respect to that normal mode.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;strong&gt;practice&lt;/strong&gt;, for medium to large molecules it can be very hard to completely minimize and find a true minimum. Most geometry optimization methods include various routines to only stop when the forces are very small, the change in energy is very small, etc. But these don't guarantee a true minimum, which is why you should calculate frequencies and check (which you mention in the question).&lt;/p&gt;&#xA;&lt;p&gt;Remember that the potential energy surface has &lt;span class=&quot;math-container&quot;&gt;$3N-6$&lt;/span&gt; dimensions for non-linear molecules. For 10 atoms, that's already 24 degrees of freedom. In many molecules, these may be correlated (e.g., think about twisting a dihedral angle in a protein - you might smash into another atom). Many times the potential energy surface can be close to flat, so finding the exact minima is time-consuming.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You should check for numerical noise, try to push for better optimization tolerances, integration grids, convergence, etc.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;(It seems like you've done a lot of this based on your comments.)&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;It depends on your properties / needs. If you need rigorous thermochemistry, then there may be some energy error  between your current geometry and a true minima. In that case, do what you can to remove the minima.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In your case, in my experience, the property calculations you plan are relatively insensitive to the small energy / geometry difference. Consider if the atomic positions move &lt;span class=&quot;math-container&quot;&gt;$0.001Å$&lt;/span&gt; will the polarizability change much? Probably not. Similar story with TDDFT, which usually has a &lt;span class=&quot;math-container&quot;&gt;$\sim 0.1$&lt;/span&gt;—&lt;span class=&quot;math-container&quot;&gt;$0.2$&lt;/span&gt; eV error bar.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="142" LastEditDate="2022-02-15T20:21:32.970" LastActivityDate="2022-02-15T20:21:32.970" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4023" PostTypeId="2" ParentId="3991" CreationDate="2021-01-01T21:07:08.633" Score="7" Body="&lt;p&gt;Yes, it is perfectly possible. As I've discussed &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3799/142&quot;&gt;here&lt;/a&gt;, it is possible to convert generally contracted basis sets into (somewhat) segmented sets without any formal loss of accuracy; next, one would discard functions with tiny coefficients and  reoptimize the segmented exponents and contraction coefficients to end up with a segmented basis set.&lt;/p&gt;&#xA;&lt;p&gt;However, as you (or your lecturer) said, segmented basis sets are much less beneficial for correlated calculations than SCF theory, since whereas SCF is usually dominated by the cost of forming the Fock matrix (i.e. calculating the two-electron integrals), in correlated calculations the cost of forming the integrals is often small compared to the post-HF calculation itself. For instance, the traditional AO &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; MO integral transform has a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(N^5)$&lt;/span&gt; computational cost, while CCSD has an iterative  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(N^6)$&lt;/span&gt; computational cost.&lt;/p&gt;&#xA;&lt;p&gt;Also note that the Karlsruhe def2 sets employ segmented contractions, and the sets with two sets of polarization functions (def2-TZVPP and def2-QZVPP) are aimed for post-HF calculations, so you should be able to find out the speed difference yourself by comparing calculations in the def2 sets to corresponding ones with the cc sets.&lt;/p&gt;&#xA;&lt;p&gt;Addendum: I should also mention the Sapporo basis sets, which are likewise segmented and optimized for post-Hartree-Fock calculations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-04-05T19:57:31.883" LastActivityDate="2021-04-05T19:57:31.883" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4024" PostTypeId="2" ParentId="4017" CreationDate="2021-01-01T22:26:42.347" Score="10" Body="&lt;p&gt;Just to add to Anyon's answer:&lt;/p&gt;&#xA;&lt;p&gt;Since there may be practical considerations for using DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; in a database like the Materials Project (i.e. a value you're confident will give you generally correct properties in high-throughput calculations, is there a literature reference or other justification for the value, etc.) I would in general not assume that they didn't perform DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; because it doesn't help.&lt;/p&gt;&#xA;&lt;p&gt;There can be situations where somewhat counter-intuitively, DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; and even hybrid functionals can give worse results for some properties of correlated materials than a normal GGA calculation. For example, see the strongly correlated metal LaNiO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; (&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.86.235117&quot; rel=&quot;noreferrer&quot;&gt;HSE&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.101.165117&quot; rel=&quot;noreferrer&quot;&gt;DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;&lt;/a&gt;). Keep in mind that DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;(or hybrids for that matter) do not improve the treatment of correlation, they reduce self-interaction error. It also depends on &lt;em&gt;how&lt;/em&gt; the correction is applied and how the value of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; was determined.&lt;/p&gt;&#xA;&lt;p&gt;LaCuO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; is also a &lt;a href=&quot;https://journals.aps.org/prb/pdf/10.1103/PhysRevB.47.15269&quot; rel=&quot;noreferrer&quot;&gt;metallic oxide&lt;/a&gt;. I did some calculations on this material and found ACBN0's method of calculating &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; on both Cu and O provided better structural agreement with experiment than PBE. I didn't check other magnetic configurations to see if the experimentally observed order is the lowest energy though.&lt;/p&gt;&#xA;&lt;p&gt;Of course, how you define 'worse' is based on what properties you want to look at. This is different for say, lattice parameters and geometry, vs. asking if you can predict the most stable magnetic configuration or not, vs. K-S gap, vs. defect formation energies, and so on... For these types of databases I suppose you want a balanced approach, another factor to consider when deciding to include a &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; correction there or not.&lt;/p&gt;&#xA;&lt;p&gt;So for a shorter answer: you have to look deeper for some in-depth studies of a material to really know. If those don't exist, you can try to find the answer with your own calculations!&lt;/p&gt;&#xA;" OwnerUserId="686" LastActivityDate="2021-01-01T22:26:42.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4025" PostTypeId="2" ParentId="4018" CreationDate="2021-01-02T15:50:46.373" Score="7" Body="&lt;p&gt;From the SUMO &lt;a href=&quot;https://smtg-ucl.github.io/sumo/sumo-dosplot.html&quot; rel=&quot;noreferrer&quot;&gt;DOS documentation page&lt;/a&gt; we have that the option &lt;code&gt;--no-shift&lt;/code&gt; controls when to shift the Fermi energy or not:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--no-shift&#xA;&#xA;    don’t shift the VBM/Fermi level to 0 eV&#xA;&#xA;    Default: True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the case of P4VASP, from its page related to &lt;a href=&quot;http://www.p4vasp.at/#/doc/dosbands&quot; rel=&quot;noreferrer&quot;&gt;plotting DOS&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In all DOS/bandstructure graphs is the energy relative to the Fermi energy - i.e. the Fermi energy on the graph is zero.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-02T15:50:46.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4026" PostTypeId="1" AcceptedAnswerId="4427" CreationDate="2021-01-02T18:36:40.820" Score="7" ViewCount="272" Body="&lt;p&gt;What smearing would be ideal for a bcc W with interstitial O atom. I am running 3x3x3 unit cells with one N interstitial.&#xA;I am having convergence issues in &lt;code&gt;relax&lt;/code&gt; and &lt;code&gt;vc-relax&lt;/code&gt;, but not in &lt;code&gt;scf&lt;/code&gt;. Could this be due to smearing? I have tried mv and cold. For an additional interstitial atom, should we change or consider charge differences? There aren't many examples of interstitial atom studies other than papers which don't mentioned anything in particular about these.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;control&#xA;    calculation = 'vc-relax',&#xA;    etot_conv_thr =   1e-05&#xA;    forc_conv_thr =   1e-04&#xA;    tprnfor = .true.&#xA;    tstress = .true.&#xA;    verbosity = 'high'&#xA;    pseudo_dir = '.',&#xA;    !prefix='w',&#xA; /&#xA; &amp;amp;system&#xA;    ibrav = 1,&#xA;    celldm(1) = 18.000,&#xA;    nat = 55,&#xA;    ntyp= 2,&#xA;    ecutwfc = 50.0, ecutrho = 500.0,&#xA;    occupations='smearing', smearing='mv', degauss=0.01,&#xA;    !nbnd = 8,&#xA;    !nspin=2,&#xA;    starting_magnetization(1)= 0.6&#xA; /&#xA; &amp;amp;electrons&#xA;    mixing_beta = 0.7&#xA;    conv_thr=1e-6&#xA; /&#xA; &amp;amp;ions&#xA;    ion_dynamics='bfgs'&#xA; /&#xA; &amp;amp;cell&#xA;    cell_dynamics='bfgs'&#xA;    cell_dofree='volume'&#xA; /&#xA;ATOMIC_SPECIES&#xA; W 183.84 W.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA; O 15.999 O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;W      0.000000   0.000000   0.000000&#xA;W      0.166667   0.166667   0.166667&#xA;W      0.000000   0.000000   0.333333&#xA;W      0.166667   0.166667   0.500000&#xA;W      0.000000   0.000000   0.666667&#xA;W      0.166667   0.166667   0.833333&#xA;W      0.000000   0.333333   0.000000&#xA;W      0.166667   0.500000   0.166667&#xA;W      0.000000   0.333333   0.333333&#xA;W      0.166667   0.500000   0.500000&#xA;W      0.000000   0.333333   0.666667&#xA;W      0.166667   0.500000   0.833333&#xA;W      0.000000   0.666667   0.000000&#xA;W      0.166667   0.833333   0.166667&#xA;W      0.000000   0.666667   0.333333&#xA;W      0.166667   0.833333   0.500000&#xA;W      0.000000   0.666667   0.666667&#xA;W      0.166667   0.833333   0.833333&#xA;W      0.333333   0.000000   0.000000&#xA;W      0.500000   0.166667   0.166667&#xA;W      0.333333   0.000000   0.333333&#xA;W      0.500000   0.166667   0.500000&#xA;W      0.333333   0.000000   0.666667&#xA;W      0.500000   0.166667   0.833333&#xA;W      0.333333   0.333333   0.000000&#xA;W      0.500000   0.500000   0.166667&#xA;W      0.333333   0.333333   0.333333&#xA;W      0.500000   0.500000   0.500000&#xA;W      0.333333   0.333333   0.666667&#xA;W      0.500000   0.500000   0.833333&#xA;W      0.333333   0.666667   0.000000&#xA;W      0.500000   0.833333   0.166667&#xA;W      0.333333   0.666667   0.333333&#xA;W      0.500000   0.833333   0.500000&#xA;W      0.333333   0.666667   0.666667&#xA;W      0.500000   0.833333   0.833333&#xA;W      0.666667   0.000000   0.000000&#xA;W      0.833333   0.166667   0.166667&#xA;W      0.666667   0.000000   0.333333&#xA;W      0.833333   0.166667   0.500000&#xA;W      0.666667   0.000000   0.666667&#xA;W      0.833333   0.166667   0.833333&#xA;W      0.666667   0.333333   0.000000&#xA;O      0.416666   0.500000   0.500000&#xA;W      0.833333   0.500000   0.166667&#xA;W      0.666667   0.333333   0.333333&#xA;W      0.833333   0.500000   0.500000&#xA;W      0.666667   0.333333   0.666667&#xA;W      0.833333   0.500000   0.833333&#xA;W      0.666667   0.666667   0.000000&#xA;W      0.833333   0.833333   0.166667&#xA;W      0.666667   0.666667   0.333333&#xA;W      0.833333   0.833333   0.500000&#xA;W      0.666667   0.666667   0.666667&#xA;W      0.833333   0.833333   0.833333&#xA;! this is a comment that the code will ignore&#xA;K_POINTS automatic&#xA;4 4 4 1 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1527" LastEditorUserId="7" LastEditDate="2021-01-02T20:32:47.247" LastActivityDate="2021-03-01T20:10:40.550" Title="Smearing and charge balance for tungsten with interstitial oxygen in Quantum ESPRESSO" Tags="|quantum-espresso|numerical-convergence|cell-optimization|" AnswerCount="1" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="4027" PostTypeId="5" CreationDate="2021-01-02T20:34:38.343" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-01-02T20:34:38.343" LastActivityDate="2021-01-02T20:34:38.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4028" PostTypeId="4" CreationDate="2021-01-02T20:34:38.343" Score="0" Body="For questions regarding optimizations of unit cell dimensions." OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-01-02T20:36:26.010" LastActivityDate="2021-01-02T20:36:26.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4029" PostTypeId="2" ParentId="3696" CreationDate="2021-01-03T05:43:27.227" Score="7" Body="&lt;h2&gt;For Molecular Mechanics&lt;/h2&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.amazon.ca/Computer-Simulation-Liquids-Michael-Allen/dp/0198803206/ref=sr_1_1?dchild=1&amp;amp;keywords=allen%20and%20tildesley&amp;amp;qid=1609652344&amp;amp;s=books&amp;amp;sr=1-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;Allen &amp;amp; Tildesley&lt;/a&gt;. One of two molecular mechanics bibles. They have a github accounts with a ton of python and fortran &lt;a href=&quot;https://github.com/Allen-Tildesley/examples&quot; rel=&quot;nofollow noreferrer&quot;&gt;codes&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.amazon.ca/Understanding-Molecular-Simulation-Algorithms-Applications/dp/0122673514&quot; rel=&quot;nofollow noreferrer&quot;&gt;Frenkel &amp;amp; Smit&lt;/a&gt;, and they have fortran 90 code that you can find. A solid reference book.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;D. C. Rapaport &lt;a href=&quot;https://www.amazon.ca/Art-Molecular-Dynamics-Simulation/dp/0521825687&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Art of Molecular Simulation&lt;/a&gt;. Plenty of codes, written in C.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Andrew Leach &lt;a href=&quot;https://www.amazon.ca/Molecular-Modelling-Principles-Applications-2nd/dp/0582382106&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Modelling: Principles and Applications&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The first two cover molecular dynamics and Monte Carlo quite well. These are mandatory reference books. The third covers molecular dynamics quite well.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-01-05T00:03:03.870" LastActivityDate="2021-01-05T00:03:03.870" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4030" PostTypeId="1" AcceptedAnswerId="4386" CreationDate="2021-01-03T07:30:25.887" Score="13" ViewCount="497" Body="&lt;p&gt;My question is both specific and general.  While looking through the materials project database I found &lt;a href=&quot;https://materialsproject.org/materials/mp-19092/&quot; rel=&quot;noreferrer&quot;&gt;this entry&lt;/a&gt;.  The band structure reported and density of states are dramatically different it seems and I am unsure what to make of this.&lt;/p&gt;&#xA;&lt;p&gt;Does materials project determine band gap via band structure or density of states and how is such a large disagreement in energy alignment possible (or is it not in general).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jnHl4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jnHl4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-02-19T20:10:03.173" LastActivityDate="2021-02-21T13:55:25.573" Title="Band structure and density of states disagreement (mp-19092)" Tags="|vasp|band-structure|density-of-states|databases|materials-project|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4031" PostTypeId="2" ParentId="3696" CreationDate="2021-01-04T01:09:47.037" Score="5" Body="&lt;h1&gt;First-principles (ab initio) materials simulation:&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Here is an online course: &lt;a href=&quot;http://compmatphys.epotentia.com/&quot; rel=&quot;noreferrer&quot;&gt;http://compmatphys.epotentia.com/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Description:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It is possible to predict properties of materials “from scratch” or “ab initio”: by applying the laws of quantum physics to the atoms that make up the material. The methods for doing this have been developed by solid state physicists, and are now sufficiently mature to tackle materials engineering problems. These so-called “ab initio methods” are becoming a mandatory item in the toolbox of modern materials scientists. This course teaches you in a practical and hands-on way how to become a responsible user of these tools.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I strongly advise you to take the previous course as the starting point. After you complete that, you can find more tutorials and workshops from the website of Quantum Espresso.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.quantum-espresso.org/resources/tutorials&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/resources/tutorials&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-04T01:09:47.037" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4032" PostTypeId="1" AcceptedAnswerId="4036" CreationDate="2021-01-04T03:51:59.483" Score="10" ViewCount="564" Body="&lt;p&gt;What are the consequences for the bandgap if the conduction band edge and valence band edge are contributed by different spins?  Are there any driving forces that prevent an excitation from spin up to spin down for example?  Will this be significantly affected by spin-orbit coupling?&lt;/p&gt;&#xA;&lt;p&gt;I suspect this gets much more complicated considering the noncolinear spin case, but I only wish to consider the colinear case currently.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="1218" LastEditDate="2021-01-05T14:29:33.153" LastActivityDate="2021-01-05T14:29:33.153" Title="Spin considerations for the bandgap and optical excitations" Tags="|band-structure|density-of-states|spin|spintronics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4033" PostTypeId="1" AcceptedAnswerId="4126" CreationDate="2021-01-04T06:50:36.430" Score="12" ViewCount="477" Body="&lt;p&gt;Weyl semimetals are topological quantum materials whose low energy excitations emerges as massles Weyl Fermions. They have a band touching point near the Fermi level called Weyl node.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aeLH1.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aeLH1.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What is actually the energy dispersion relation of Weyl Fermions? More specifically, do we have to consider the band as a linear dispersion relation or as a conduction and valence band which takes the shape of two cones?&lt;/p&gt;&#xA;&lt;p&gt;I came up with this doubt because if we consider the band dispersion relation as linear, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_k=C\times (k-k_0)$$&lt;/span&gt;(For convenience consider 1D. but I know that Weyl semimetals are three dimensional)&lt;/p&gt;&#xA;&lt;p&gt;then the effective mass is given by &lt;span class=&quot;math-container&quot;&gt;$$m*=\frac{\hbar^2}{\frac{\partial^2E_k}{\partial k^2}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;that gives&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$m*=\frac{\hbar^2}{0}=\infty$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which contradicts the fact that Weyl Fermions are massless.&lt;/p&gt;&#xA;&lt;p&gt;But If we consider it as the latter one then the derivative is not defined at the Weyl node?&#xA;Where am I wrong in my calculations and concepts?&lt;/p&gt;&#xA;" OwnerUserId="1594" LastEditorUserId="7" LastEditDate="2021-07-03T17:29:40.703" LastActivityDate="2021-07-03T17:29:40.703" Title="Band structure of Weyl semimetal?" Tags="|band-structure|weyl-semimetal|effective-mass|energy-dispersion|topological-matter|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4034" PostTypeId="1" AcceptedAnswerId="4038" CreationDate="2021-01-04T14:50:47.490" Score="15" ViewCount="753" Body="&lt;p&gt;HF or DFT methods are variational so I can confidently say that any basis set that gives the lowest energy is the best for that system. However, I have learnt that post-HF methods such as MP2, MP3, MP4 and so on, or CCSD, CCSD(T) etc. are not variational, so the lowest energy does not necessarily means that its the best.&lt;/p&gt;&#xA;&lt;p&gt;So how can I compare the accuracy and efficiency of different basis sets such as def2, cc for correlated methods?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-01-05T05:17:56.763" LastActivityDate="2021-01-06T00:02:07.790" Title="How should I compare different basis sets for post-Hartree-Fock methods?" Tags="|basis-sets|coupled-cluster|electron-correlation|high-precision|many-body-perturbation-theory|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4035" PostTypeId="1" CreationDate="2021-01-04T15:37:44.757" Score="17" ViewCount="15086" Body="&lt;p&gt;I might decide to pursue material science.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Aptitude and background&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am from the UK, and for A-levels, I am studying Maths, Further Maths, Physics and Chemistry, and I am predicted decent grades in all of them.&lt;/p&gt;&#xA;&lt;p&gt;For my Morrisby Assessment taken a year ago: Numerical reasoning 70%, Abstract reasoning 80%, Verbal reasoning, 95% - This was slightly lower for numerical then I expected, but it does make sense since I have to try pretty hard in maths.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Physics&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Family likes the idea of me studying physics,&lt;/li&gt;&#xA;&lt;li&gt;Like quantum, thermal, chemical and nuclear physics,&lt;/li&gt;&#xA;&lt;li&gt;Opens the most doors out of compared to the other two, in that I can transfer into engineering/machine learning,&lt;/li&gt;&#xA;&lt;li&gt;Well-respected known undergrad for non-physics jobs.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;a bit more difficult for me (sometimes chem is a harder though)&lt;/li&gt;&#xA;&lt;li&gt;Dislike electricity, EM, fields, waves which are integral topics&lt;/li&gt;&#xA;&lt;li&gt;On the surface, there seems to be less direct jobs related to physics compared to chemistry, in/out of academia (please prove me wrong though, iIam only 18, hence why I am here asking!)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;em&gt;Chemistry:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Pros:&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Easier for me aptitude wise&lt;/li&gt;&#xA;&lt;li&gt;Like all parts of chemistry, apart from some niche topics&lt;/li&gt;&#xA;&lt;li&gt;(could be more transferrable to material science and nanotechnology? - therefore opening the 3rd option up as well&lt;/li&gt;&#xA;&lt;li&gt;Right now quantum chemistry and orbital approximations are my favorite subject&lt;/li&gt;&#xA;&lt;li&gt;Well-respected and known undergrad for non-chemistry jobs&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Less transferrable than physics&lt;/li&gt;&#xA;&lt;li&gt;Don't want to be stuck in an industrial/pharma job, where I am glorified lab rat following a list of instructions&lt;/li&gt;&#xA;&lt;li&gt;Lower job satisfaction on the internet compared to the other two&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;em&gt;Material science:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Pros&lt;/strong&gt;:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Very large interest for it since it combines chemistry and physics components I enjoy&lt;/li&gt;&#xA;&lt;li&gt;Possibly better paid, due to the large amounts of engineering involved&lt;/li&gt;&#xA;&lt;li&gt;Able to go into nuclear materials research, and medicinal too, therefore opening more opportunities than chemistry.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Cons:&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Less-respected well-known undergrad, and could always do it at postgrad level&lt;/li&gt;&#xA;&lt;li&gt;Studying metals and ceramics seems boring, I prefer nanostructures!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Having considered the above information, which degree out of the 3 may be better suited for me?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;After the considerations made in the answers below&lt;/strong&gt;, I think I shall lean towards a chemical physics degree, which has advanced material science modules :). It also allows me the option of switching to pure chemistry in 3rd year if I want to.&lt;/p&gt;&#xA;&lt;p&gt;I will do further research as well, around more universities.&lt;/p&gt;&#xA;&lt;p&gt;Thank you so much for the time and effort of your responses.&lt;/p&gt;&#xA;" OwnerUserId="1862" LastEditorUserId="5" LastEditDate="2023-09-16T17:39:57.470" LastActivityDate="2023-09-16T17:39:57.470" Title="Is it better for me to study chemistry or physics?" Tags="|quantum-chemistry|solid-state-physics|education|" AnswerCount="12" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="4036" PostTypeId="2" ParentId="4032" CreationDate="2021-01-04T20:42:47.287" Score="6" Body="&lt;p&gt;I don't think we need to talk about &lt;em&gt;driving forces&lt;/em&gt; (this sounds esoteric) instead calculating the &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Supplemental_Modules_(Physical_and_Theoretical_Chemistry)/Spectroscopy/Electronic_Spectroscopy/Spin-orbit_Coupling&quot; rel=&quot;noreferrer&quot;&gt;selection rule&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$P_T = \int \psi_1^* \mu \psi_2 d\tau$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt; are the wavefunctions of the two states involved in the transition and &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; the transition operator.&lt;/p&gt;&#xA;&lt;p&gt;This integral represents the transition probability (&lt;span class=&quot;math-container&quot;&gt;$P_T$&lt;/span&gt;). When the result is zero, the transition is called forbidden.&lt;/p&gt;&#xA;&lt;p&gt;As the spin is directional, the corresponding spin wavefunctions are odd. This directly implies that a transition where the spin &amp;quot;directions&amp;quot; are different, will result in &lt;span class=&quot;math-container&quot;&gt;$P_T = 0$&lt;/span&gt; and then, are considered as forbidden transition.&lt;/p&gt;&#xA;&lt;p&gt;Relaxation of &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Supplemental_Modules_(Physical_and_Theoretical_Chemistry)/Spectroscopy/Electronic_Spectroscopy/Selection_Rules_for_Electronic_Spectra_of_Transition_Metal_Complexes&quot; rel=&quot;noreferrer&quot;&gt;this rule&lt;/a&gt; (i.e. &lt;span class=&quot;math-container&quot;&gt;$P_T \neq 0$&lt;/span&gt;) can occur with the presence of &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Supplemental_Modules_(Physical_and_Theoretical_Chemistry)/Spectroscopy/Electronic_Spectroscopy/Spin-orbit_Coupling&quot; rel=&quot;noreferrer&quot;&gt;spin-orbit coupling&lt;/a&gt;, vibronic coupling and/or &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-acceptor/donnor mixing with d-orbitals.&lt;/p&gt;&#xA;&lt;p&gt;Answering your questions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What are the consequences for a bandgap if the conduction band and valence band are on different spins?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you have an odd number of electrons or anything else that break the system symmetry, you will/can have separated bands for the &lt;em&gt;spin-up&lt;/em&gt; and &lt;em&gt;spin-down&lt;/em&gt; configurations. This implies having two different bandgaps. You can explore this feature using your material as the core of spin-filter in &lt;a href=&quot;https://en.wikipedia.org/wiki/Spintronics&quot; rel=&quot;noreferrer&quot;&gt;spintronics&lt;/a&gt;, for example.&lt;/p&gt;&#xA;&lt;p&gt;The image bellow correspond to a boron-nitride nanotube interacting with a Ni atom.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/BmJSe.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BmJSe.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Are there any driving forces that prevent an excitation from spin up to spin down for example?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Nothing here about &lt;em&gt;driving forces&lt;/em&gt;, just selection rules.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Will this be significantly affected by spin-orbit coupling?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-04T20:42:47.287" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4037" PostTypeId="2" ParentId="4035" CreationDate="2021-01-04T20:54:30.677" Score="12" Body="&lt;p&gt;As a Bachelor in Physics that do research in Material Science and in Drug Development, I have to recommend you to go for the Physics degree. Also, you have to be aware about the type/specialization of the Physics course. For example, my undergrad Physics course was focused in Solid State, so, we had Quantum Mechanics, Solid State Physics and Crystallographic, all of them will help you in getting a better understanding of Material Science. On the other hand, I had a colleague, also Bachelor in Physics, that is Astrophysics. He never took any of the courses that I mentioned before in his undergrad.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-04T20:54:30.677" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4038" PostTypeId="2" ParentId="4034" CreationDate="2021-01-04T23:27:24.353" Score="11" Body="&lt;p&gt;First of all, MP2 (for example) is actually guaranteed to converge from above to the basis set limit even though MP2 in one specific basis set can give an energy lower than the FCI energy in that same basis set. So it's variational character in the basis set sense that matters here.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, variational character is not the most pertinent thing to consider when comparing basis sets, since basis sets are not designed to give the lowest total energy. I asked a related question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/953/5&quot;&gt;Which basis set families were optimized to give the lowest possible variational energy for a given number of orbitals?&lt;/a&gt;, and still no one seems to know of any basis set families that were optimized to get the lowest variational energy.&lt;/p&gt;&#xA;&lt;p&gt;When basis sets are designed, other properties are considered more important than lowest variational energy. For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What is the quality of the energy differences?&lt;/li&gt;&#xA;&lt;li&gt;How well does the basis set family extrapolate smoothly to the complete basis set limit?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you want to compare the def2 sequence to the cc-pVXZ (Dunning) sequence, then you have to first choose the property in which you are interested: Are you calculating ionization energies? Electron affinities? Atomization energies? Bond lengths? Dipole polarizabilities? Then you can see how well the def2 and Dunning basis sets &lt;strong&gt;reproduce known-to-be-accurate benchmark data for the specific property you're trying to calculate&lt;/strong&gt;, for similar molecules, and use this as a guideline for the molecule you're studying. &lt;strong&gt;Lowest total energy&lt;/strong&gt; is almost never the property at the centre of a scientific project, but all the other properties often are, so it's not always wisest to judge the quality of a basis set (for what you're trying to accomplish) based only on the lowest total energy rather than on the quality of the above things?&lt;/p&gt;&#xA;&lt;p&gt;There's much more to the trade than just this, and it's not easy to summarize in one answer, because which basis sets I would use will depend on so many other factors. For example in &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; I went all the way up to 8Z (aug-cc-pCV8Z), so I would never have even considered using the def2 series, which does not go beyond 4Z as far as I know. But in &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5063376&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; we knew it would be hopeless to get anywhere. near the complete basis set limit at the spectroscopic standard, and it was a large molecule so speed was very important and we used a def2 basis set.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Bottom line: for almost every scientifically meaningful study, lowest energy does not mean better basis set, so don't compare basis sets based only on variational characteristics.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-05T04:58:26.263" LastActivityDate="2021-01-05T04:58:26.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4039" PostTypeId="2" ParentId="4035" CreationDate="2021-01-04T23:36:27.650" Score="10" Body="&lt;p&gt;An Engineer's perspective:&lt;/p&gt;&#xA;&lt;p&gt;I started with a Bachelor's in Mechanical Engineering, and then moved to a Master's in Materials Science and Engineering. Worked for 4 years in the industry, and now came back to do a PhD in Materials Engineering.&lt;/p&gt;&#xA;&lt;p&gt;If I could go back, I would definitely do the same thing, but maybe invest more time in Physics along the way. Basic chemistry goes a long way here, as the relevance is mostly for inorganic chemistry rather than the large field of organic chemistry.&lt;/p&gt;&#xA;&lt;p&gt;While from physics, you don't avoid or &amp;quot;waste&amp;quot; much when you come to materials science. Of course, this is from an Metal engineering perspective. I have colleagues who come from a Physics background before getting into Materials Engineering, but they don't necessarily find any advantage, since current doctoral studies are more towards engineering in materials than towards the science side. This of course is one man's (engineer's) perspective.&lt;/p&gt;&#xA;&lt;p&gt;I realize this answer maybe neither here, nor there, depending on your exact interests, but I hope it helps in some way.&lt;/p&gt;&#xA;" OwnerUserId="1527" LastActivityDate="2021-01-04T23:36:27.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4040" PostTypeId="2" ParentId="4035" CreationDate="2021-01-04T23:52:05.953" Score="13" Body="&lt;p&gt;As someone who did his undergrad in Canada, PhD in UK, and acquired post-PhD research experience in Japan, Singapore, USA, Germany, and again in Canada: I can say that the dilemma you're facing is a major disadvantage of the undergrad UK system. The UK system has many advantages too! But the flexibility is better in other countries such as Canada and US.&lt;/p&gt;&#xA;&lt;p&gt;Based on everything you've said, if you were to apply to the university where I did my undergrad (University of Waterloo), there's the &lt;a href=&quot;https://uwaterloo.ca/waterloo-chemical-physics/undergraduate-students&quot; rel=&quot;noreferrer&quot;&gt;Chemical Physics degree&lt;/a&gt; that they offer. Or you can do what I did which is the &lt;a href=&quot;https://uwaterloo.ca/future-students/programs/honours-science&quot; rel=&quot;noreferrer&quot;&gt;Honours Science&lt;/a&gt; program, which allows you to take &lt;em&gt;&lt;strong&gt;whatever courses you want&lt;/strong&gt;&lt;/em&gt; as long as half of them are science courses. I took physics, mathematics, biology, geology, philosophy, anthropology, literature, music, computer science, engineering, and many other courses, and eventually I was even allowed to enter a &lt;em&gt;customized&lt;/em&gt; &amp;quot;double major + double minor&amp;quot; program: BSc in Science, BMath in Applied Mathematics, Minor in Physics, Minor in Biology, plus I did all the elective courses that I mentioned, and all within 4 years.&lt;/p&gt;&#xA;&lt;p&gt;In the USA it's similar, especially if you're in a liberal arts program, however it will cost you a &lt;em&gt;&lt;strong&gt;lot&lt;/strong&gt;&lt;/em&gt; more money. In UK there's still &lt;em&gt;excellent&lt;/em&gt; options such as the Natural Sciences program at Cambridge University, but spaces are limited. My recommendation is for you to find universities that will allow you to be flexible, as in the Canadian, US American, or Cambridge programs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Otherwise it is too hard to tell you whether you should choose chemistry or physics.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you choose to stay in the UK, and select a university that doesn't have a program like Cambridge's natural sciences program, then the final things I'll say are the following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In a physics program you'll be surrounded by people that (on average) like mathematics and programming more, and this may lead you to more interest or even opportunities in finance, machine learning, data science, etc.&lt;/li&gt;&#xA;&lt;li&gt;In a chemistry program you'll be surrounded by people that (on average) are more interested in pharmaceuticals, bio-medicine, environmental science, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Pfizer (a pharmaceutical company) made the first widely approved COVID-19 vaccine with no help from physicists, so don't underestimate how fruitful it might be to be in a program where you learn at least a bit of biochemistry and &amp;quot;life science&amp;quot;. At the same time, many of the high-paying jobs in quantitative science go to physicists (more often than chemists).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-05T04:50:43.247" LastActivityDate="2021-01-05T04:50:43.247" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4042" PostTypeId="2" ParentId="4035" CreationDate="2021-01-05T03:00:27.713" Score="20" Body="&lt;p&gt;I just joined this community to answer you after I've randomly seen your post, because I think there are a couple of important variables you may want to consider: &lt;strong&gt;your feelings and your intuition&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can rationally consider many variables, but you are very young and there may be topics that you like now that you will consider boring in the future, and the other way around. In my case, I started Physics because I loved Astrophysics. Then I realized that it was boring and I became interested in Particles' Physics, then in Computer Science, and then I ended up doing a PhD in Biology. Now I am a scientist working in complex biological systems, whatever that means: what I learned is that in a scientific job it is very important your motivation and passion, and that your choice will not be an all-or-nothing.&lt;/p&gt;&#xA;&lt;p&gt;In this respect, Physics is a great degree because you will acquire 1) strong quantitative skills; and 2) an important training to solve difficult problems, which you can then use to solve ANY problem. These skills are increasingly important because knowledge is becoming more and more multidisciplinary and quantitative, and Physics will bring you a very flexible background to jump from one area to another. I know physicists working in almost any area, from finances to psychology, and including the design of vaccines (I highlight this because someone said above that physicists were not involved in this kind of research but this is not true, physicists are very important contributors in drug-design computational methods, just think in the physics behind a model describing an energy interaction term between a protein active site and a ligand). I also think that quantitative skills are  difficult to acquire autonomously (I basically learned biology reading books, and I don't think I could have learned maths at the same page reading books) so I would try to learn these skills in university.&lt;/p&gt;&#xA;&lt;p&gt;As a final (very personal) opinion, there are some variables I would not take much into account, like how happy is your family with your choice or metrics about your capabilities (obviously as long as you are minimally comfortable with your choice). I am saying this because I can imagine that your family will be happy if you are happy, and because the fact that you are asking here shows that your motivation and initiative are stronger than any difference in the numerical reasoning % with respect to the best in this room.&lt;/p&gt;&#xA;&lt;p&gt;Good luck with your choice!&lt;/p&gt;&#xA;" OwnerUserId="1865" LastActivityDate="2021-01-05T03:00:27.713" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4043" PostTypeId="2" ParentId="4032" CreationDate="2021-01-05T03:25:34.787" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What are the consequences for a bandgap if the conduction band and valence band are on different spins?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The energy band of materials when the spin is involved (magnetic/nonmagnetic) are usually classified &lt;a href=&quot;https://academic.oup.com/nsr/article/3/3/365/2236578&quot; rel=&quot;nofollow noreferrer&quot;&gt;as follows:&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YjW8F.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YjW8F.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(a): ferromagnetic metals&lt;/li&gt;&#xA;&lt;li&gt;(b): half metals&lt;/li&gt;&#xA;&lt;li&gt;(c): topological insulator&lt;/li&gt;&#xA;&lt;li&gt;(d): half semiconductor&lt;/li&gt;&#xA;&lt;li&gt;(e): spin gapless semiconductor&lt;/li&gt;&#xA;&lt;li&gt;(f): bipolar magnetic semiconductor&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here I assume you are talking semiconductors, namely (d) and (f) in the previous screenshot. Essentially, the bandgap is decided by the position of the Fermi level. Interestingly, you will meet some materials in which the spin-up channel is metallic whereas the spin-down channel is a semiconductor. This is an important consequence of spin-involved band structure.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Are there any driving forces that prevent an excitation from spin up to spin down for example?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This question is explained by @Camps. The transitions from the valence band to the conduction band are related to the properties of bandstructure and wavefunctions, such as minimal direct gap, the overlap of the electron and the hole wavefunction, and symmetry of wavefunction. The information from the spin will also be reflected in the wavefunction.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Will this be significantly affected by spin-orbit coupling?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As for the bandgap, the spin-orbit coupling (SOC) will host a significant influence (more than 0.5eV) in some materials with heavy atoms, such as &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/ta/c6ta06806e#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;BiI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;&lt;/a&gt; and &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2014/%E2%80%8Bcp/c4cp01975j#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;BiTeI&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hyLLq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hyLLq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In addition, the SOC will influence the optical excitation in some nonmagnetic materials with heavy atoms. For example in TMDC monolayers, the spin-&lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; component is a good quantum number due to the interplay of lattice inversion symmetry and strong SOC, which will lead to &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.196802&quot; rel=&quot;nofollow noreferrer&quot;&gt;the selective photoexcitation of carriers with various combinations of the valley and spin indices&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9bMbm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9bMbm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-05T03:25:34.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4044" PostTypeId="2" ParentId="4034" CreationDate="2021-01-05T04:49:41.387" Score="10" Body="&lt;p&gt;In general, when computing any property with different models (e.g. level of theory, basis set, etc), if you don't have some kind of theoretical bound (like the variational principle) to determine what is a better result, you need a reference value to compare against.&lt;/p&gt;&#xA;&lt;p&gt;One choice for this reference is experimental results. At the end of the day, the goal of computations is to predict real properties, so it makes sense to use the experimentally measured values as a reference. When available, these are arguably the best reference you can have. One potential drawback is the somewhat rare possibility that there are significant errors in the experimental results. Another possible issue would stem from being &amp;quot;right for the wrong reasons&amp;quot;. For example, an experimental measured optical rotation might be the result of several conformers of a molecule; if you performed an OR calculation for a single conformer, you may incidentally reproduce the experimental value while doing a poor job of actually simulating the chosen conformer.&lt;/p&gt;&#xA;&lt;p&gt;Experimental data can often be sparse for systems from theoretical research. After all, if there were a plethora of experimental data in these areas, there wouldn't be as much of a need for simulation. Another common option for benchmarking is to use values from a sufficiently accurate model as you reference. &amp;quot;Sufficiently accurate&amp;quot; is going to be very dependent on the systems/properties you are looking at: a lot of small/medium sized chemical studies consider CCSD(T) with a large basis the &amp;quot;gold-standard&amp;quot; while materials research would probably neccesitate a smaller basis and/or DFT methods. The drawback of using another simulation as a reference is we don't necessarily know that a model with a higher level of theory is more accurate. However, post-HF methods are, at least in principle, systematically improvable, so can develop at least an approximate sense of how converged a property is with respect to the full CI/complete basis set limit.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-01-05T04:49:41.387" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4045" PostTypeId="5" CreationDate="2021-01-05T06:05:26.693" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-05T06:05:26.693" LastActivityDate="2021-01-05T06:05:26.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4046" PostTypeId="4" CreationDate="2021-01-05T06:05:26.693" Score="0" Body="Questions about education, course selection, career advice, etc." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-05T06:05:26.693" LastActivityDate="2021-01-05T06:05:26.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4047" PostTypeId="1" CreationDate="2021-01-05T07:07:47.020" Score="7" ViewCount="175" Body="&lt;p&gt;I originally made the title the question I had that is a more suitable question but then it ended up too long. I had the idea that if you replace some of the atoms in a covalent network with the atom of the element 1 atomic number higher, it will create antibonding electrons which random walk and some of them might random walk to the surface atoms filling their outer shells and making the surface nonstick and low friction if the network didn't already have low friction. I think this has so many applications. I believe that when a surface is etched smooth by a liquid whose contact angle with it is more than 0° so that the liquid won't cling to the material then evaporate redepositing what it etched away and then it goes against another surface that was also etched smooth, sometimes the force of kinetic friction per area is much higher than normal because of energy getting absorbed in the vibrations of the surface atoms sliding along one another. I also read on one web page that diamond has high friction with itself in an ultra high vacuum because its the atoms of the two surfaces form bonds with one another; and on another web page that diamond is not used as a space lubricant because it can wear out because of its high friction. I thinking it gave a coefficient of kinetic friction of diamond on itself in an ultra high vacuum as 1. I believe that when it is smooth and the normal force per area in contact is low, kinetic friction per area except for really low speeds is much higher and varies linearly with the sliding speed and is independent of the normal force, unlike what I learned in physics that it is independent of the sliding peed and varies linearly with the normal force. So maybe one problem with diamond is its friction with itself is so high in the area of contact that is comparable to its shear modulus and so it undergoes the stick-slip phenomenon and then parts in the tiny area of contact crash at really high speeds comparable to the speed of sound in the substance which I read was about 12 km/s, causing cracks to start or propagate and wear it out. I believe that by replacing some of the atoms in a covalent network with those of the element one atomic number higher and etching it smooth, it could be made nonstick and have a force of kinetic friction per actual area in contact at the atomic level that might not be very low at all but will still be far less than the shear modulus of the material. Maybe treated diamond could be etched into a Santoku chef's knife with a blade that is 2 atoms thick. My question is&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Has there ever been a discussion of the idea of replacing some atoms in a covalent network with that of the element one atomic number higher to make the surface nonstick or low friction? Can somebody who is an expert at looking hard for discussions on the desired topic tell me whether or not they are able to find a discussion of this idea and tell me the effort they made to find one if they can't find one?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Then if researchers read the answer to this question, they might be able to use it to help them invest in new research more efficiently.&lt;/p&gt;&#xA;&lt;p&gt;Update: I couldn't give a perfect answer to my question so I wrote a so so answer to my question to contribute some information that might aid researchers in developing revolutionary hard slick nonstick nondegradable materials. As described in that answer which I will write again here, I do not intend that answer to be a substitute for the type of answer I'm really looking for.&lt;/p&gt;&#xA;&lt;p&gt;Also, I saw that the question got closed. I feel like I already made it as clear as I am able to in the question box. Apparently, people found it confusing anyway and it got closed. This is the best I can make the question. There is nothing more I can do. I know I didn't add the second question in the question box from the very start but I believe I did it before the question got more votes to get it closed and maybe even after only one close vote.&lt;/p&gt;&#xA;&lt;p&gt;Update: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4350/has-there-been-research-on-improving-the-strength-of-graphene-based-materials/4366#4366&quot;&gt;This answer&lt;/a&gt; says one problem with graphene sheets is it has edges which are reactive. Maybe this idea could also be improvised to graphene sheets as well. Most of the nitrogen atoms in them will create antibonding electrons but a few of them will cause the atoms at the edges of a graphene sheet to have a full outer shell.&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="1014" LastEditDate="2021-02-21T20:25:40.657" LastActivityDate="2021-02-21T20:25:40.657" Title="Can replacing some of the atoms in a covalent network with that of the element one atomic number higher make it nonstick?" Tags="|mathematical-modeling|physical-properties-of-materials|" AnswerCount="1" CommentCount="3" ClosedDate="2021-01-11T21:29:26.617" ContentLicense="CC BY-SA 4.0" />
  <row Id="4048" PostTypeId="2" ParentId="4047" CreationDate="2021-01-05T07:07:47.020" Score="2" Body="&lt;p&gt;I don't know of any discussions of the idea of replacing atoms in a covalent network with the atom one atomic higher having the effect of the random walking elections themselves filling the outer shells of the surface atoms. However, I know that the web page &lt;a href=&quot;https://www.adadiamonds.com/knowledge-base/canary-yellow-lab-grown-diamonds&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.adadiamonds.com/knowledge-base/canary-yellow-lab-grown-diamonds&lt;/a&gt; talks about yellow lab grown diamond made by adding nitrogen into the diamond. It said nothing about the nitrogen doing what I described to the diamond. I do not have the expert skills or resources to go hunting for such discussions. I wrote this answer for no other reason than I had information about the canary yellow lab grown diamonds. And this is not the best answer there could be and should not be a substitute for another answer by somebody who has those expert skills and resources.&lt;/p&gt;&#xA;&lt;p&gt;At least, this answer tells about a company that is producing that type of diamond. Maybe researchers will then invest in research on whether that type of diamond would actually have the outer shells of its surface atoms filled by the antibonding elections already knowing that if they determine the answer to be yes, they will thereafter work with the company that produces that type of diamond to actually get it produced more efficiently. However another issue to address is that the movement of those electrons to the surface might create an entire surface full of electric diploes and cause it to attract polar substances such as water or other objects made of that kind of diamond.&lt;/p&gt;&#xA;&lt;p&gt;My question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3956/has-a-form-of-diamond-with-certain-properties-ever-been-theorized&quot;&gt;Has a form of diamond with certain properties ever been theorized?&lt;/a&gt; proposed a possible other form of diamond. The image&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Bh7kr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Bh7kr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;is what a Penrose tiling looks like. A quasicrystal is something like a Penrose tiling. The verticies of a dodecahedron can be split into 5 groups of 4 each of which are the verticies of a tetrahedron. The image&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/us1ni.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/us1ni.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;takes part of the Penrose tiling and turns it into a primitive cell. I believe some of the substances that were thought to be dodecahedral quasicrystals really have a primitive cell that contains 5 parts that have the same relative orientations as the 5 tetrahedra that make a dodecahedron. I think a primitive cell of the α phase of Silicon Nitride might actually be like that. Maybe there is a form of diamond like that too. If that type of diamond could exist, that would be even better. It would have no cleavage planes as weak as the 4 cleavage planes in diamond or the one cleavage plane in lonsdalite.&lt;/p&gt;&#xA;&lt;p&gt;Sources&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Penrose_Tiling_(Rhombi).svg&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://commons.wikimedia.org/wiki/File:Penrose_Tiling_(Rhombi).svg&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://commons.wikimedia.org/wiki/File:RegularRhombs.svg&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://commons.wikimedia.org/wiki/File:RegularRhombs.svg&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="1014" LastEditDate="2021-01-08T05:58:14.567" LastActivityDate="2021-01-08T05:58:14.567" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4049" PostTypeId="1" CreationDate="2021-01-05T07:33:55.457" Score="8" ViewCount="62" Body="&lt;p&gt;I'm studying a mechanism of fluorine substitution in my molecule (the project isn't that much about actual research as learning computational chemistry). There are two &lt;span class=&quot;math-container&quot;&gt;$\ce{C6F5}$&lt;/span&gt; rings and I want to know which one will be substituted first (I have more or less consistent experimental data for N-nicleophiles).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Two sides of each ring aren't equivalent, should I study nucleophile's approach each ring from each side (4 calculations in total)?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I assume a classical mechanism via a Meisenheimer complex, but when I try to optimize its structure it just expels the nucleophile (returns to reagents).&lt;/p&gt;&#xA;&lt;p&gt;So I run relaxed PES scan, bringing closer the nucleophile (&lt;span class=&quot;math-container&quot;&gt;$\ce{Me2NH}$&lt;/span&gt;) to &lt;span class=&quot;math-container&quot;&gt;$\ce{C6F5}$&lt;/span&gt; ring, optimize the maximum as TS and compute its vibration. I get only one imaginary vibration (as intended) but it corresponds to &lt;span class=&quot;math-container&quot;&gt;$\ce{C-F}$&lt;/span&gt; bond breaking, not &lt;span class=&quot;math-container&quot;&gt;$\ce{C-N}$&lt;/span&gt; bond forming (which I'm not certain about).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Can I make a conclusion from it, that reaction proceeds without an intermediate (I've found such examples in the literature) and has late TS (although the reagents have the energy higher than the products, which should produce early TS)?&lt;/li&gt;&#xA;&lt;li&gt;Is Hammond's postulate even applicable for an arbitrary non-model reaction?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-02-28T04:56:49.607" LastActivityDate="2021-02-28T04:56:49.607" Title="Reaction mechanism elucidation methodology" Tags="|density-functional-theory|reaction-mechanism|" AnswerCount="0" CommentCount="8" ClosedDate="2021-09-05T23:12:27.633" ContentLicense="CC BY-SA 4.0" />
  <row Id="4050" PostTypeId="1" AcceptedAnswerId="4068" CreationDate="2021-01-05T08:26:22.073" Score="5" ViewCount="188" Body="&lt;p&gt;When working with &lt;code&gt;gmx make_ndx&lt;/code&gt; I found very annoying the fact that atomic indexes are automatically ranked in the outputted index &lt;code&gt;.ndx&lt;/code&gt; file.&#xA;No matter how the selection is provided, the list of indexes in a group is always ranked.&lt;/p&gt;&#xA;&lt;p&gt;This is particularly problematic when building indexes for things such dihedral angles, where the ranking is obviously critical.&lt;/p&gt;&#xA;&lt;p&gt;Is anyone aware of a way to avoid this automatic and un-necessary ranking in the indexes?&lt;/p&gt;&#xA;" OwnerUserId="1773" LastEditorUserId="5" LastEditDate="2021-01-05T08:33:15.277" LastActivityDate="2021-01-06T12:20:00.917" Title="How to overcome gromacs make_ndx automatic ranking of atomic indexes?" Tags="|gromacs|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4051" PostTypeId="1" AcceptedAnswerId="4104" CreationDate="2021-01-05T08:40:18.037" Score="9" ViewCount="802" Body="&lt;p&gt;I am trying to understand the fundamental physics of a kind of problem. I will introduce a specific example and then list some of the broader qualms I hold. I have observed many band structures, be it spin-polarized or spin-degenerate. Let's take the case of CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, a well-studied 2D van der Waals semiconducting magnet. The monolayer band structure is what one would expect - it has spin-polarized carriers at the band edges, i.e. the majority and minority carriers occupy different energy eigenstates.&#xA;Moving onto the bilayer, however, the band structure is spin-degenerate. Many papers like this one &lt;a href=&quot;https://www.researchgate.net/publication/331840340_Magnetically_Switchable_Light-Matter_Interaction_in_the_Two-Dimensional_Magnet_CrI3&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt; report PT-symmetry (Parity-Time) as the cause for the degeneracy: basically, the Hamiltonian commutes with the product of P&lt;span class=&quot;math-container&quot;&gt;$\cdot$&lt;/span&gt;T. My main questions, which is not just specific to  CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, are as follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Is there a rigorous way when one looks at new material, to say if PT-symmetry would lead to a spin degeneracy? Because from what I've read, and I could totally be wrong, but it looks like people do band structure calculations and then attributes such a degeneracy to PT-symmetry.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I do not hold a good theoretical physics footing, so I don't know much about PT symmetry with regard to specific systems, but I do know about the universal CPT symmetry that is preserved. Is one just a subset of the other?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally, I am having a hard time trying to understand how the system can break inversion symmetry and time-reversal symmetry but the product of these two symmetry operators is still a 'good' quantum number i.e. one that commutes with the Hamiltonian.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;Monolayer CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; with spin-polarized bandstructure:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZGqBu.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZGqBu.png&quot; alt=&quot;Monolayer CrI3 with spin-polarized bandstructure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Bilayer CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, where spin carriers are degenerate:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7NFHt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7NFHt.png&quot; alt=&quot;Bilayer CrI3, where spin carriers are degenerate&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;PS: I am well aware that the answer might involve a thorough level of detail, so I'm very open to awarding bounty points for detailed answers.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="1218" LastEditDate="2021-01-10T06:02:18.043" LastActivityDate="2022-04-09T13:14:34.957" Title="PT-symmetry leading to spin-degenerate band structures" Tags="|band-structure|electronic-structure|magnetism|symmetry|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4052" PostTypeId="1" CreationDate="2021-01-05T08:55:48.073" Score="6" ViewCount="200" Body="&lt;p&gt;I get the message mentioned in the title after a distance scan with a Gaussian calculation. I have bound a gold atom to a carbon in the pyridine ring and now pull this further and further out with a relaxing scan. I used ONIOM to define two layers for pyridine and gold to calculate a set for heavy atoms. Of course, the pyridine charge changes when the gold is no longer bound to the pyridine. Is there a way to suppress this error with an option? The only thing that occurred to me would be to optimize the individual structures separately after and before the separation to preserve the orbitals. I'm only concerned with the energy available at this point, is it also influenced by the error message?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastActivityDate="2021-01-07T11:27:19.777" Title="Unresolvable inconsistency between charge and multiplicity and orbital occupancies. Error while Distance Scan" Tags="|density-functional-theory|binding-energy|orbitals|" AnswerCount="0" CommentCount="3" ClosedDate="2021-02-28T20:39:56.790" ContentLicense="CC BY-SA 4.0" />
  <row Id="4053" PostTypeId="2" ParentId="4035" CreationDate="2021-01-05T10:22:14.613" Score="9" Body="&lt;p&gt;I'm not working in material sciences but as a (particle) physicist I came into touch with solid physicists a lot. To elaborate: In particle physics, one of the main components is usually the scintillator crystal which is a very high advanced material. The material for it for an upcoming particle accelerator was entirely researched by our neighbour working group, means, the theoretical department was involved as well as the according experimental department. I know that the latter consists of roughly 2/3 physicists and 1/2 material scientists. The theoretical department is mainly composed of physicists with a few mathematicians alongside.&#xA;However, in addition that a new chair of the theoretical department is only involved in finding new materials for the circuits resp. processors for supercomputers and from my impression, according to the welcome lecture, this topic is far away from &amp;quot;material science/chemistry&amp;quot;. It is very, very mathematical.&lt;/p&gt;&#xA;&lt;p&gt;Despite from that, I know some physicists who are working for Infineon who specialized in solid / semiconductor physics. On the other hand, the girlfriend of my colleague owns an engineering degree in micro mechanis and worked for Infineon ~since the beginning of her study but they didn't keep her afterwards, though she did her bachelor and master thesis there in addition to further researches along her study. They clearly prefer physicists on an official level.&lt;/p&gt;&#xA;&lt;p&gt;Official, because, as she obviously really wants to stay in this field (and there are no similar companies where she is living), she got her steps into the company again via an engineer personnel service provider (and Infineon is now paying much more for her work as when they would have given her a regular contract in the beginning..).&lt;/p&gt;&#xA;&lt;p&gt;What I want to add here: It depends on what you want to do on a daily basis, respectively, which tools and in which worlds do you think. I know mathematicians working in optic fields, physicists working as AI engineers, my girlfriend is a biologist and is working as a quality manager and software tester for electromechanical devices for the chemical industry. My boss is a mathematician and supervises a lot of engineers together with a few scientists.&#xA;To conclude: From my feeling, you should choose material science while, from my pov, a combination of a bachelor in physics and a master in material science/engineering would be the best fit.&lt;/p&gt;&#xA;" OwnerUserId="1869" LastEditorUserId="1869" LastEditDate="2021-01-05T12:05:17.507" LastActivityDate="2021-01-05T12:05:17.507" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4054" PostTypeId="1" AcceptedAnswerId="6247" CreationDate="2021-01-05T10:46:34.903" Score="7" ViewCount="426" Body="&lt;p&gt;I have a system of 5 layers of an element + 1 layer of another one, I want the relaxed position of the last layer, and once I have it, proceed to calculate the pdos. I am performing simulations in the order:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Relax&lt;/li&gt;&#xA;&lt;li&gt;SCF with the new position&lt;/li&gt;&#xA;&lt;li&gt;NSCF (with 4x the number of k-points)&lt;/li&gt;&#xA;&lt;li&gt;PDOS&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The SCF output has magnetic moments and charge per site, the PDOS gives a &lt;code&gt;*.pdos.dat.lowdin&lt;/code&gt; file with the same information.&lt;/p&gt;&#xA;&lt;p&gt;My problem is that the charges and magnetic moments are different on the SCF and PDOS outputs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which ones should I trust? Why would they be different?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;SCF output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Magnetic moment per site:&#xA;atom:    1    charge:   10.8246    magn:    0.0110    constr:    0.0000&#xA;atom:    2    charge:   10.8934    magn:    0.0059    constr:    0.0000&#xA;atom:    3    charge:   10.9088    magn:   -0.0009    constr:    0.0000&#xA;atom:    4    charge:   10.9105    magn:    0.0414    constr:    0.0000&#xA;atom:    5    charge:   10.9245    magn:   -0.2424    constr:    0.0000&#xA;atom:    6    charge:   13.5294    magn:    3.5015    constr:    0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;*.pdos.dat.lowdin&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Atom #   1: total charge =  12.9768, s =  2.3048, p =  6.7101, d =  3.9619,&#xA;             spin up      =   6.4972, s =  1.1526,                          &#xA;             spin up      =   6.4972, p =  3.3561,                          &#xA;             spin up      =   6.4972, d =  1.9885,                          &#xA;             spin down    =   6.4796, s =  1.1522,                          &#xA;             spin down    =   6.4796, p =  3.3540,                          &#xA;             spin down    =   6.4796, d =  1.9734,                          &#xA;             polarization =   0.0177, s =  0.0004, p =  0.0021, d =  0.0151,&#xA; Atom #   2: total charge =  13.0022, s =  2.2288, p =  6.8375, d =  3.9359,&#xA;             spin up      =   6.5058, s =  1.1145,                          &#xA;             spin up      =   6.5058, p =  3.4196,                          &#xA;             spin up      =   6.5058, d =  1.9717,                          &#xA;             spin down    =   6.4964, s =  1.1143,                          &#xA;             spin down    =   6.4964, p =  3.4180,                          &#xA;             spin down    =   6.4964, d =  1.9642,                          &#xA;             polarization =   0.0094, s =  0.0003, p =  0.0016, d =  0.0075,&#xA; Atom #   3: total charge =  13.0153, s =  2.2252, p =  6.8123, d =  3.9778,&#xA;             spin up      =   6.5078, s =  1.1122,                          &#xA;             spin up      =   6.5078, p =  3.4082,                          &#xA;             spin up      =   6.5078, d =  1.9874,                          &#xA;             spin down    =   6.5075, s =  1.1131,                          &#xA;             spin down    =   6.5075, p =  3.4041,                          &#xA;             spin down    =   6.5075, d =  1.9904,                          &#xA;             polarization =   0.0003, s = -0.0009, p =  0.0042, d = -0.0030,&#xA; Atom #   4: total charge =  13.0454, s =  2.2269, p =  6.8300, d =  3.9885,&#xA;             spin up      =   6.5563, s =  1.1150,                          &#xA;             spin up      =   6.5563, p =  3.4206,                          &#xA;             spin up      =   6.5563, d =  2.0208,                          &#xA;             spin down    =   6.4891, s =  1.1119,                          &#xA;             spin down    =   6.4891, p =  3.4094,                          &#xA;             spin down    =   6.4891, d =  1.9678,                          &#xA;             polarization =   0.0673, s =  0.0031, p =  0.0112, d =  0.0530,&#xA; Atom #   5: total charge =  13.5800, s =  2.3248, p =  7.1741, d =  4.0811,&#xA;             spin up      =   6.5896, s =  1.1552,                          &#xA;             spin up      =   6.5896, p =  3.5647,                          &#xA;             spin up      =   6.5896, d =  1.8696,                          &#xA;             spin down    =   6.9904, s =  1.1696,                          &#xA;             spin down    =   6.9904, p =  3.6094,                          &#xA;             spin down    =   6.9904, d =  2.2115,                          &#xA;             polarization =  -0.4008, s = -0.0144, p = -0.0446, d = -0.3418,&#xA; Atom #   6: total charge =  14.2291, s =  2.6028, p =  5.9944, d =  5.6320,&#xA;             spin up      =   8.9997, s =  1.3448,                          &#xA;             spin up      =   8.9997, p =  2.9975,                          &#xA;             spin up      =   8.9997, d =  4.6574,                          &#xA;             spin down    =   5.2294, s =  1.2580,                          &#xA;             spin down    =   5.2294, p =  2.9969,                          &#xA;             spin down    =   5.2294, d =  0.9746,                          &#xA;             polarization =   3.7702, s =  0.0868, p =  0.0006, d =  3.6828,&#xA; Spilling Parameter:   0.0019                                               &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1870" LastEditorUserId="5" LastEditDate="2021-02-28T05:01:28.643" LastActivityDate="2021-06-26T09:11:44.580" Title="Incosistent charges and magnetic moments between SCF and PDOS calculations in Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4055" PostTypeId="2" ParentId="4035" CreationDate="2021-01-05T15:34:42.903" Score="11" Body="&lt;p&gt;I'm a fellow Brit who did Chemistry as a first Degree, before moving into a hybrid chemistry/statistics PhD and now works as a software engineer. My suggestion is not to get too caught up in the exact subject that you are studying and consider the areas you are enjoying the most and find the course that fits your interests, regardless of course title.&lt;/p&gt;&#xA;&lt;p&gt;A good way to help you understand what a department will focus on in the later years of your degree is to look at their research interests, as these vary wildly between departments at each institution. With your interests, you may find a physics department with a strong applied research focus is going to be more interesting overall, but you may also feel a chemistry department with a strong materials focus/strong physical research focus is right.&lt;/p&gt;&#xA;&lt;p&gt;I would also recommend, that if you can, you choose to take the integrated Masters' version of the degree program that the university offers. The integrated masters programs are typically 4 Years and gives an MChem for Chemists and a MPhys for physics. These programs will give you a chance in your final year to get involved with real research and may give you the impetus to carry on with research into a PhD (exactly what happened with me!). Generally speaking you will follow the same program for the first two years as those taking a BSc and then only diversify in year 3. Most programs in the UK are also pretty flexible about allowing you to transfer from the Masters program to the BSc if you want to.&lt;/p&gt;&#xA;&lt;p&gt;Although the academic content of your course is important, the phyiscal place is also really important and I could not recommend any more highly trying to get to the Universities that you are interested in for an open day and looking around the campus and the town/city they are located in. I know that is challenging in 2021 in the UK with the current Covid-19 situtation, but the feel of the place you will be spending a lot of time is incredibly important. I know from personal experience that although a course can be amazing on paper, it may not feel that way when you actually get to the city and tour the campus and facilities. If you are keen on a particular course, get in touch with the departments admissions tutor and ask questions. Admissions' tutors jobs are to answer questions and it shows alot of initiative to get in touch and ask questions. Admissions tutors do not forget those that show some willingness to do their own research and ask questions which might come in handy with getting offers later down the line.&lt;/p&gt;&#xA;" OwnerUserId="1872" LastActivityDate="2021-01-05T15:34:42.903" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4056" PostTypeId="2" ParentId="4035" CreationDate="2021-01-05T17:17:14.553" Score="9" Body="&lt;p&gt;I studied physics and three of my family members studied chemistry.&lt;/p&gt;&#xA;&lt;p&gt;Don't worry too much about the choice.   Any of those subjects will provide you with interesting study and enough career opportunities.&lt;/p&gt;&#xA;&lt;p&gt;Any scientific subject gets more interesting the harder you look at it (even Biology).&lt;/p&gt;&#xA;&lt;p&gt;You don't need lots of career opportunities, you only need a few.&lt;/p&gt;&#xA;&lt;p&gt;Many people study physics and then gradually move into more chemistry-based work, and vice-versa.&lt;/p&gt;&#xA;&lt;p&gt;Although getting a good chemistry degree is just as difficult academically as a physics one, psychologically physics is harder because you spend more of your time grappling with aspects that &lt;em&gt;nobody&lt;/em&gt; understands.   You also have to deal with aspects that not very many people understand, and where their understanding is entirely mathematical: Feynmann for example said that he couldn't explain his ideas to non-mathematicians, because he didn't understand them in non-mathematical ways.&lt;/p&gt;&#xA;&lt;p&gt;You might want to take into account that undergraduate chemistry labs require students to wear lab-coats and gloves and eye-protection, and to deal with dangerous chemicals and fume cupboards   If you are clumsy or nervous, you might not like that.&lt;/p&gt;&#xA;&lt;p&gt;If you study physics, you will be spending a lot of time with physicists.   If you are happy in a majority-male, geek-friendly environment, that might be perfect for you.&lt;/p&gt;&#xA;&lt;p&gt;Each of those subjects needs more people with communication skills, so your verbal reasoning will be valuable, and valued by employers.&lt;/p&gt;&#xA;" OwnerUserId="1874" LastActivityDate="2021-01-05T17:17:14.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4057" PostTypeId="1" CreationDate="2021-01-05T18:51:10.773" Score="3" ViewCount="292" Body="&lt;p&gt;I know that I learned in Chemistry class that a bond is defined to be ionic if the electronegativity difference between the atoms is more then 1.7, half the electronegativity difference between the most electronegative element fluorine and the least electronegative element francium. I think I heard that there's no clear definable distinction between a covalent bond and an ionic bond. I'm not sure it's the case that we can't define one. I believe we could define it by whether there is a localized electron pair at each bond. I know aluminum and oxygen have an electronegativity difference of more than 1.7. However, one web page said Corundum was a covalent network. Then I checked for myself and saw that corundum indeed probably does satisfy my definition of a covalent network. I know that sulfur can hybridize to make 6 covalent bonds with fluorine. Theoretically, could have a substance that's like corundum with the sulfur atoms instead of aluminum atoms and carbon atoms instead of oxygen atoms. Here we would say the sulfur hybridized to form 6 covalent bonds and the carbon is forming the usual 4. I know coordinate covalent bonds are possible also. If that substance could exist as a covalent network with a localized electron pair at each bond, why couldn't it also be a covalent network with a localized electron pair at each bond when you have aluminum and oxygen instead? It's still the exact same total number of protons per unit cell.&lt;/p&gt;&#xA;&lt;p&gt;My question is&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Has it already been researched whether corundum has a localized electron pair at each bond between an aluminum atom and an oxygen atom?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I know it's not completely clear but my questions was written the best way I can possible write it with my abilities and my lack of expertise in quantum mechanics. I can't figure out given how quantum mechanics works what my question would be, and I don't want to use my time on studying quantum mechanics. Maybe even if I did know how quantum mechanics worked, I would still be unable to figure an algorithm for determining what type of answer would satisfy me. When somebody is working on a complicated project that uses a lot of thinking, they can't figure out an algorithmic plan on how they will react to every situation. Rather, they trust themself to use their discretion later on what ever situation arises. A good answer would come from an expert who can function as if they are a future self of me and is good at hunting down existing research that they would use their discretion that they can write an answer about that has a good chance of satisfying me. As long as they write it in a way I can see as a good answer and see why it can be considered one, I think it will satisfy me.&lt;/p&gt;&#xA;&lt;p&gt;As described in my question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4047/can-replacing-some-of-the-atoms-in-a-covalent-network-with-that-of-the-element-o&quot;&gt;Can replacing some of the atoms in a covalent network with that of the element one atomic number higher make it nonstick?&lt;/a&gt;, maybe researchers will use an answer to that question to invest in new research. Then if they're going to invest in that research, then an answer to this question that corundum indeed does have a localized electron pair at each bond might further help them incorporate this idea into that idea and add corundum to the list of potential substances that can be treated that way to gain those revolutionary properties. Corundum will have the additional property that it can't combust. Maybe they will make hard highly nonstick nondegradable frying pans out of treated corundum.&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="1014" LastEditDate="2021-01-13T22:06:23.283" LastActivityDate="2021-01-13T22:06:23.283" Title="Can corundum be considered a covalent network?" Tags="|mathematical-modeling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4058" PostTypeId="2" ParentId="4035" CreationDate="2021-01-05T20:52:14.363" Score="5" Body="&lt;p&gt;I was in the same position as you 3 years ago! I liked chemistry the most and physics the second, but my dad is a physicist so he wanted me to study physics. I ended up choosing chemistry because math was never my strong point.&lt;/p&gt;&#xA;&lt;p&gt;My family eventually accepted me studying chemistry. I think what really matters is whether you can see yourself studying only the subject all year round. If you choose a subject that you don't have an interest in (regardless of whether or not you are smart enough for it), then you will quickly get bored at uni. Of course, as others said, your interest can change throughout your course. And you can also change courses if you wish. One of my friends studied environmental science for two years, and then switched to chemistry.&lt;/p&gt;&#xA;&lt;p&gt;For example, after 3 years of undergrad, I now don't want to work in the lab, wheras in the beginning lab was the most fun part. I think that realisation came after the second time I stabbed myself with a syringe last year. Now, I am planning to do a master's in computational chemistry (sort of a crossover between computer science and chemistry).&lt;/p&gt;&#xA;&lt;p&gt;Finally, some universities in UK offer a 'chemical physics' course which is a blend of physical chemistry and physics, with a little bit of organic and inorganic chemistry mixed in. You might want to look into those. Although, many universities are shutting down those courses (like my uni did), as there are so few people applying for them.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-01-05T20:52:14.363" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4059" PostTypeId="2" ParentId="3491" CreationDate="2021-01-05T22:42:04.270" Score="7" Body="&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3491/binding-energy-calculation-for-zn-atom-on-armchair-graphene-slab#comment5678_3491&quot;&gt;mentioned by @Camps in the comments&lt;/a&gt;, the Zn reference used in the paper is almost certainly that of an isolated Zn atom in the gas phase.&#xA;If I understand correctly from briefly scanning the paper, the source of Zn in the device (as viewed from the graphene-coated separator) will be Zn2+ ions dissolved in the electrolyte - not quite the same thing as Zn in the gas phase, but certainly not Zn bulk.&lt;/p&gt;&#xA;&lt;p&gt;In order to get an accurate result, take the cell you used for the slab+Zn calculation, delete the slab and recompute the total energy.&lt;/p&gt;&#xA;&lt;p&gt;I agree that the description &amp;quot;metallic Zn configuration&amp;quot; in conjunction with individual Zn atoms is somewhat confusing; it may have been intended to indicate the (neutral) charge state or a specific magnetic configuration - I'm sure the authors would be happy to clarify!&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-03-18T23:31:52.733" LastActivityDate="2021-03-18T23:31:52.733" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4060" PostTypeId="2" ParentId="3640" CreationDate="2021-01-05T23:28:49.520" Score="3" Body="&lt;p&gt;You are right to assume that the part of the band structure relevant for electronic conductivity is the one of electrons (and holes) with energies close to the Fermi energy.&lt;/p&gt;&#xA;&lt;p&gt;However, electronic conductivity is not determined by the electronic band structure alone.&#xA;If you take the simple Drude model for the conductivity&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \sigma = \frac{ne^2\tau}{m^*}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;you can think of the band structure providing the &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;nofollow noreferrer&quot;&gt;effective mass&lt;/a&gt; &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;, but not the relaxation time &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; in between scattering events.&#xA;This scattering time can be strongly affected by doping or other imperfections in the crystal.&lt;/p&gt;&#xA;&lt;p&gt;P.S. Strong Nitrogen doping of graphene (of the order of a few %) will also affect the band structure near the Fermi energy - see e.g. section 3.2 in &lt;a href=&quot;https://arxiv.org/pdf/1209.5228.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this randomly chosen preprint&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-01-05T23:28:49.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4061" PostTypeId="2" ParentId="3660" CreationDate="2021-01-06T00:01:16.103" Score="4" Body="&lt;p&gt;From looking at the very long wavelength you specified, I assume your intent is to apply a static field to the calculation?&#xA;I read &lt;a href=&quot;https://groups.google.com/g/cp2k/c/68FNiP-1L0k/m/QSxPrWkxAwAJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; that &lt;code&gt;EFIELD&lt;/code&gt; is intended for applying laser pulses and that you should use &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/EXTERNAL_POTENTIAL.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;EXTERNAL_POTENTIAL&lt;/a&gt; instead, with the &lt;code&gt;READ_FROM_CUBE&lt;/code&gt; option.&lt;/p&gt;&#xA;&lt;p&gt;Not sure whether printing the imposed potential is possible, but you could print the &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/PRINT/V_HARTREE_CUBE.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;hartree potential&lt;/a&gt; and make sure to use the same grid for your input.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-01-06T00:01:16.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4062" PostTypeId="2" ParentId="4034" CreationDate="2021-01-06T00:02:07.790" Score="5" Body="&lt;p&gt;Well, Nike already answered the point about the variationality: even though methods like MP2, CCSD, and CCSD(T) are non-variational in that they may over- or underestimate the  energy of the ground state (or excited states) of the Schrödinger equation, the energy reproduced by any given method typically &lt;strong&gt;does&lt;/strong&gt; behave variationally with respect to the basis set. You can understand this in another way: while CCSD(T) doesn't even have a wave function, you &lt;em&gt;can&lt;/em&gt; write a Lagrangian for it, which the solution minimizes. The one-electron basis set just affects the accuracy with which you're minimizing this functional.&lt;/p&gt;&#xA;&lt;p&gt;Note that this is not restricted to ab initio calculations. DFT is a celebrated class of methods, but the absolute energies reproduced by density functional approximations (DFAs) don't mean anything. DFT is most certainly non-variational with respect to the true solution to the Schrödinger equation; still, there are many atomic-orbital basis sets that are optimized for the minimization of DFT energies.&lt;/p&gt;&#xA;&lt;p&gt;I would still like to point out that absolute energies are for sure important for doing accurate benchmarks: the whole point of extrapolation schemes is that the error with respect to the basis set is monotonic, and the total energies approach the exact value from above.&lt;/p&gt;&#xA;&lt;p&gt;If you're studying a new property / a new level of theory, you should always check the convergence with respect to the basis set. If the changes from XZ to (X+1)Z are small, this typically means that you have reached convergence to the basis set limit; your absolute energy should then also be close to the correct value. This does not always happen though: even though you can reach sub-microhartree level accuracy in the total energy for self-consistent field calculations for light atoms in Gaussian basis sets, for heavy atoms the absolute energy is only accurate to millihartree &lt;a href=&quot;https://doi.org/10.1063/1.5144964&quot; rel=&quot;noreferrer&quot;&gt;[J. Chem. Phys. 152, 134108 (2020)]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PS. An interesting exception can be found in relativistic methods. The Dirac equation permits two classes of solutions: the electronic solutions with positive energies, and the positronic solutions with negative energies (a.k.a. Fermi sea). In a given AO basis set with K basis functions, you will have K positive-energy solutions, and K negative-energy solutions. The energy is not determined as a minimization of the energy functional with respect to orbital rotations as in non-relativistic theory, but rather as a mini-max procedure where you minimize with respect to electronic rotations and maximize with respect to positronic rotations. Because of this, the variational principle no longer applies. You can see this effect e.g. in calculations with the Douglas-Kroll-Hess (DKH) and exact two-component (X2C) approaches.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-01-06T00:02:07.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4063" PostTypeId="1" CreationDate="2021-01-06T00:22:33.833" Score="5" ViewCount="221" Body="&lt;p&gt;I just calculated the stiffness tensor for a given material (a monoclinic molecular crystal)&#xA;using molecular simulation. When trying to compare my results to published experimental results&#xA;I found that the crystal structure I used for simulation, though essentially the same as the one&#xA;used as reference system in experiment, has different base vectors/reference frame&#xA;(P21/n vs P21/a) - therefore I can compare invariants and averages but not the individual&#xA;components c_ij of the stiffness (as matrix in Voigt notation).&lt;/p&gt;&#xA;&lt;p&gt;So my question is: given the, altogether six, lattice vectors of the two crystal structures,&#xA;how can I use this information to generate a rotation matrix to transform&#xA;the Voigt matrix from experiment (based on a crystal in the P21/a space group) so that&#xA;I can compare it to my calculated numbers from simulation (based on a crystal with P21/n&#xA;symmetry)?&lt;/p&gt;&#xA;&lt;p&gt;What comes closest to an answer I found here:&#xA;&lt;a href=&quot;http://solidmechanics.org/text/Chapter3_2/Chapter3_2.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://solidmechanics.org/text/Chapter3_2/Chapter3_2.htm&lt;/a&gt;&#xA;but I am not sure what the two bases (e and m, in section 3.2.11 Basis change formulas&#xA;for anisotropic elastic constants) are - are these the normalized lattice vectors of the&#xA;two structures in Cartesian coordinates? if not what else?&lt;/p&gt;&#xA;&lt;p&gt;thanks!&lt;/p&gt;&#xA;&lt;p&gt;michael&lt;/p&gt;&#xA;" OwnerUserId="1878" LastEditorUserId="5" LastEditDate="2021-01-06T00:45:40.130" LastActivityDate="2021-01-06T15:32:18.453" Title="elastic constants transformation/basis change P21/a -&gt; P21/n" Tags="|solid-state-physics|mechanical-properties|elastic-constants|atomistic-simulation|elasticity|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4064" PostTypeId="1" AcceptedAnswerId="4085" CreationDate="2021-01-06T03:37:32.327" Score="7" ViewCount="613" Body="&lt;p&gt;The details are descripted &lt;a href=&quot;https://groups.google.com/g/cp2k/c/qVqrkdvaI0U&quot; rel=&quot;nofollow noreferrer&quot;&gt;elsewhere&lt;/a&gt;, but got no answer for days, so I post it here for help.&lt;/p&gt;&#xA;&lt;p&gt;As title said, I noticed a relatively big change in conserved quantity and don't know why.&lt;/p&gt;&#xA;&lt;p&gt;I've upload files on &lt;a href=&quot;https://github.com/jtyang-chem/Modeling_Matters/tree/master/4064/&quot; rel=&quot;nofollow noreferrer&quot;&gt;github&lt;/a&gt;, including in/out file and *.ener, two warnings in the /ext_res, I'll try other options when I have time&lt;/p&gt;&#xA;&lt;p&gt;Part of my input here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# &amp;amp;EXT_RESTART&#xA;#     RESTART_FILE_NAME job-1.RESTART&#xA;# &amp;amp;END EXT_RESTART&#xA;&amp;amp;GLOBAL&#xA;    EXTENDED_FFT_LENGTHS  T&#xA;    PRINT_LEVEL  MEDIUM&#xA;    PROJECT_NAME job&#xA;    RUN_TYPE MD&#xA;&amp;amp;END GLOBAL&#xA;&amp;amp;MOTION&#xA;    &amp;amp;MD&#xA;        ENSEMBLE  NVT&#xA;        STEPS 110000 # 220 ps&#xA;        TIMESTEP     1.9999999999999998E+00 # 2fs&#xA;        TEMPERATURE     1.0500000000000000E+03&#xA;        &amp;amp;THERMOSTAT&#xA;            &amp;amp;CSVR&#xA;                TIMECON     9.9999999999999986E+01&#xA;            &amp;amp;END CSVR&#xA;        &amp;amp;END THERMOSTAT&#xA;        &amp;amp;PRINT&#xA;            &amp;amp;ENERGY  SILENT&#xA;                &amp;amp;EACH&#xA;                    MD  1&#xA;                &amp;amp;END EACH&#xA;            &amp;amp;END ENERGY&#xA;            &amp;amp;PROGRAM_RUN_INFO  SILENT&#xA;                &amp;amp;EACH&#xA;                    MD  1&#xA;                &amp;amp;END EACH&#xA;            &amp;amp;END PROGRAM_RUN_INFO&#xA;        &amp;amp;END PRINT&#xA;    &amp;amp;END MD&#xA;    &amp;amp;PRINT&#xA;        &amp;amp;TRAJECTORY  SILENT&#xA;            FILENAME =trj1.xyz&#xA;            &amp;amp;EACH&#xA;                MD  1&#xA;            &amp;amp;END EACH&#xA;        &amp;amp;END TRAJECTORY&#xA;        &amp;amp;VELOCITIES  OFF&#xA;        &amp;amp;END VELOCITIES&#xA;        &amp;amp;FORCES  OFF&#xA;        &amp;amp;END FORCES&#xA;        &amp;amp;RESTART  ON&#xA;            BACKUP_COPIES  1&#xA;            &amp;amp;EACH&#xA;                MD  100&#xA;            &amp;amp;END EACH&#xA;        &amp;amp;END RESTART&#xA;        &amp;amp;RESTART_HISTORY  OFF&#xA;        &amp;amp;END RESTART_HISTORY&#xA;    &amp;amp;END PRINT&#xA;&amp;amp;END MOTION&#xA;&amp;amp;FORCE_EVAL&#xA;    METHOD  QS&#xA;    STRESS_TENSOR  ANALYTICAL&#xA;    &amp;amp;DFT&#xA;        BASIS_SET_FILE_NAME BASIS_MOLOPT&#xA;        POTENTIAL_FILE_NAME POTENTIAL&#xA;        WFN_RESTART_FILE_NAME diis-RESTART.wfn&#xA;        &amp;amp;SCF&#xA;            MAX_SCF  30&#xA;            EPS_SCF     9.9999999999999995E-07&#xA;            SCF_GUESS  RESTART&#xA;            &amp;amp;OT  T&#xA;                MINIMIZER  DIIS&#xA;                PRECONDITIONER  FULL_SINGLE_INVERSE&#xA;            &amp;amp;END OT&#xA;            &amp;amp;OUTER_SCF  T&#xA;                EPS_SCF     9.9999999999999995E-07&#xA;                MAX_SCF  5&#xA;            &amp;amp;END OUTER_SCF&#xA;            &amp;amp;PRINT&#xA;                &amp;amp;RESTART  ON&#xA;                    BACKUP_COPIES  1&#xA;                    &amp;amp;EACH&#xA;                        MD  100&#xA;                    &amp;amp;END EACH&#xA;                &amp;amp;END RESTART&#xA;            &amp;amp;END PRINT&#xA;        &amp;amp;END SCF&#xA;        &amp;amp;QS&#xA;            EPS_DEFAULT     1.0000000000000000E-10&#xA;            METHOD  GAPW&#xA;        &amp;amp;END QS&#xA;        &amp;amp;MGRID&#xA;            NGRIDS  5&#xA;            CUTOFF     4.2000000000000000E+02&#xA;            REL_CUTOFF     6.0000000000000000E+01&#xA;        &amp;amp;END MGRID&#xA;        &amp;amp;XC&#xA;            DENSITY_CUTOFF     1.0000000000000000E-10&#xA;            GRADIENT_CUTOFF     1.0000000000000000E-10&#xA;            TAU_CUTOFF     1.0000000000000000E-10&#xA;            &amp;amp;XC_FUNCTIONAL  NO_SHORTCUT&#xA;                &amp;amp;PBE  T&#xA;                &amp;amp;END PBE&#xA;            &amp;amp;END XC_FUNCTIONAL&#xA;            &amp;amp;VDW_POTENTIAL&#xA;                POTENTIAL_TYPE  PAIR_POTENTIAL&#xA;                &amp;amp;PAIR_POTENTIAL&#xA;                    R_CUTOFF     1.6000000000000000E+01&#xA;                    TYPE  DFTD3(BJ)&#xA;                    PARAMETER_FILE_NAME dftd3.dat&#xA;                    D3BJ_SCALING     1.0000000000000000E+00    4.1449999999999998E-01    1.2177000000000000E+00    4.8593000000000002E+00&#xA;                &amp;amp;END PAIR_POTENTIAL&#xA;            &amp;amp;END VDW_POTENTIAL&#xA;        &amp;amp;END XC&#xA;        &amp;amp;POISSON&#xA;            PERIODIC  XYZ&#xA;        &amp;amp;END POISSON&#xA;        &amp;amp;PRINT&#xA;            &amp;amp;E_DENSITY_CUBE  OFF&#xA;            &amp;amp;END E_DENSITY_CUBE&#xA;        &amp;amp;END PRINT&#xA;    &amp;amp;END DFT&#xA;    &amp;amp;SUBSYS&#xA;       ...&#xA;    &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="938" LastEditorUserId="938" LastEditDate="2021-01-07T08:41:32.933" LastActivityDate="2021-01-07T17:35:35.743" Title="cp2k conserved quantity changed when restart NVT MD?" Tags="|molecular-dynamics|cp2k|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4065" PostTypeId="2" ParentId="4035" CreationDate="2021-01-06T04:46:46.687" Score="6" Body="&lt;p&gt;Being great at what you like doing will open far more doors for you. You will find that there is a lot more variety of jobs than you think, and you will find interesting opportunities by being at the top of your field. It sounds like you will really excel at chemistry, and being in a field you are excited about is a lot better (Personal satisfaction and for interviews) than being in a field that you think has better opportunities.&lt;/p&gt;&#xA;&lt;p&gt;You have a lot of great pros and cons, but you will have to work in that field everyday. You should follow you passion and the job opportunities will follow.&lt;/p&gt;&#xA;" OwnerUserId="1880" LastActivityDate="2021-01-06T04:46:46.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4066" PostTypeId="1" AcceptedAnswerId="4070" CreationDate="2021-01-06T07:40:07.467" Score="8" ViewCount="276" Body="&lt;p&gt;I am running a quantum mechanical simulation on Psi4 for a certain number of monomers to generate data for a database. Some of these monomers are short, while some are long.&lt;/p&gt;&#xA;&lt;p&gt;At the moment, I am generating .pdb files for these monomers using their SMILES string, and using OpenBabel's genetic algorithm to generate possible optimal conformers to use for my simulation.&lt;/p&gt;&#xA;&lt;p&gt;Now obviously, if I could, I would generate as many conformers as possible for my monomers and throw them in Psi4 to generate all-encompassing data for them. However, since these computations are expensive, I can't do that and I have to budget my computational resources.&lt;/p&gt;&#xA;&lt;p&gt;My idea is that the smaller monomers would require a smaller number of conformers to accurately depict their properties (50-100), while the larger monomers, having more degrees of freedom , would need more conformers to depict their properties.&lt;/p&gt;&#xA;&lt;p&gt;I want to figure out a way to ballpark how many conformers do I need to evaluate for each monomer. How would you go about finding an estimate?&lt;/p&gt;&#xA;&lt;p&gt;For example, say you had something small, like isoprene, and something larger, like benzyl methacrylate. How many conformers would you make for each of them? Is there a combinatorial argument you can make regarding torsional strains (or something) that you can use to get an estimate?&lt;/p&gt;&#xA;&lt;p&gt;Any advice you have would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-01-06T15:15:16.097" Title="How do I figure out how many monomer configurations I need for my simulation?" Tags="|computational-chemistry|quantum-mechanics|psi4|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4067" PostTypeId="2" ParentId="4066" CreationDate="2021-01-06T12:10:28.063" Score="5" Body="&lt;p&gt;At a rough guess you can assume that the number of conformers you need to generate (N_conf) is directly proportional to the number of rotatable bonds (N_rot) in a given compound. I seem to recall that this number (of rotatable bonds) is something you can easily calculate, e.g., with openbabel.&#xA;So the number of conformers you request for a given compound would be&lt;/p&gt;&#xA;&lt;p&gt;N_conf = c * N_rot&lt;/p&gt;&#xA;&lt;p&gt;What you use for the constant c depends on your application, i.e., how dense a sampling of configurational space you want/need to perform, but for most applications I'd guess a value of n somewhere between 10 and 20 should be enough.&lt;/p&gt;&#xA;&lt;p&gt;Also, I seem to recall that, with default options, the algorithms used by openbabel automatically restrict the total number of generated conformers to something reasonable. If, for example you ask it to generate 1000 conformers for a small/rigid compound like benzene it will only give you a much smaller number than that.&lt;/p&gt;&#xA;&lt;p&gt;hope that helps!&lt;/p&gt;&#xA;" OwnerUserId="1878" LastActivityDate="2021-01-06T12:10:28.063" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4068" PostTypeId="2" ParentId="4050" CreationDate="2021-01-06T12:20:00.917" Score="3" Body="&lt;p&gt;I assume you by &amp;quot;ranking&amp;quot; you mean &amp;quot;sorting numerically&amp;quot; ...&#xA;I don't think there is a general solution for this in gmx - unless you are ready to do some script writing yourself ...&lt;/p&gt;&#xA;&lt;p&gt;As a workaround ... in an older gmx version there used to be a tool called mk_angndx&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://manual.gromacs.org/documentation/5.1/onlinehelp/gmx-mk_angndx.html?highlight=mk_angndx&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://manual.gromacs.org/documentation/5.1/onlinehelp/gmx-mk_angndx.html?highlight=mk_angndx&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't think this is available in more recent versions, so in the worst case you'd need to install the old version locally, use this binary to generate your index file and then use the generated index file with a newer gmx.&lt;/p&gt;&#xA;" OwnerUserId="1878" LastActivityDate="2021-01-06T12:20:00.917" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4069" PostTypeId="2" ParentId="4011" CreationDate="2021-01-06T15:06:02.397" Score="1" Body="&lt;p&gt;I took a look at the files posted on the Research gate platform.&lt;/p&gt;&#xA;&lt;p&gt;I'm not used to the VASP, but the results you reported are a bit strange. I've got the same kind of outputs using the &lt;a href=&quot;http://dx.doi.org/10.1016/j.cpc.2015.05.021&quot; rel=&quot;nofollow noreferrer&quot;&gt;EELS package&lt;/a&gt; from the Quantum ESPRESSO library, which uses the Quantum Liouville equation for the charge-density susceptibility.&lt;/p&gt;&#xA;&lt;p&gt;The reason may be the approximation VASP uses and the parameters used to perform the calculation. Reading the &amp;quot;OUTCAR&amp;quot;, it seems that VASP is using independent particle approximation, but I didn't find any information on the transferred momentum. To reproduce the experimental results, the transferred momentum should be set to zero (or almost zero, due to numerical limitations).&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2021-01-06T15:06:02.397" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4070" PostTypeId="2" ParentId="4066" CreationDate="2021-01-06T15:15:16.097" Score="12" Body="&lt;h2&gt;tldr; it depends on flexibility / number of rotatable bonds&lt;/h2&gt;&#xA;&lt;p&gt;A while ago, I answered a &lt;a href=&quot;https://chemistry.stackexchange.com/a/57286/5017&quot;&gt;related question&lt;/a&gt; - in general, molecules with fewer &amp;quot;rotatable bonds&amp;quot; need fewer conformers geometries generated to sample properly.&lt;/p&gt;&#xA;&lt;p&gt;Based on that, I would normally have said &amp;quot;50 is more than enough for up to 3-4 rotatable bonds&amp;quot; and beyond that, I'd guess somewhere around 250-500 depending on molecule size. (It's hard to do an exhaustive search for 20 rotatable bonds.. in principal, the rough rule-of-thumb has been &lt;span class=&quot;math-container&quot;&gt;$3^n$&lt;/span&gt; or ~3.5 billion possible conformers.)&lt;/p&gt;&#xA;&lt;p&gt;More recently, we published a &lt;a href=&quot;https://doi.org/10.26434/chemrxiv.12671027.v1&quot; rel=&quot;noreferrer&quot;&gt;preprint&lt;/a&gt; after studying over 120,000 small molecules and ~12 million conformers.&lt;/p&gt;&#xA;&lt;p&gt;While the number of &lt;em&gt;&lt;strong&gt;possible&lt;/strong&gt;&lt;/em&gt; conformers goes up exponentially with the number of rotatable bonds, we find (using the approximate density functional GFN2 method) that the number of low-energy conformers goes up much more slowly -- roughly quadratically with the number of rotatable bonds. So you'd probably be okay with ~500-1000 conformers for 20 rotatable bonds. (&lt;em&gt;Much better!&lt;/em&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BYRaj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BYRaj.png&quot; alt=&quot;number of low-energy conformers&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My suggestion - and what we're doing in the group now, is to generate a 3D geometry of your molecule. (Open Babel works fine. RDKit works fine. Avogadro works fine. No bias here.)&lt;/p&gt;&#xA;&lt;p&gt;Then you should likely do a conformer search using some type of quantum method. Our &lt;a href=&quot;https://doi.org/10.1002/qua.26381&quot; rel=&quot;noreferrer&quot;&gt;recent paper&lt;/a&gt; shows that GFN2 (or ANI-2x) have fairly good correlations with quantum methods.&lt;/p&gt;&#xA;&lt;p&gt;The Grimme group has made &lt;a href=&quot;https://github.com/grimme-lab/crest/releases&quot; rel=&quot;noreferrer&quot;&gt;CREST&lt;/a&gt; and &lt;a href=&quot;https://github.com/grimme-lab/xtb/releases&quot; rel=&quot;noreferrer&quot;&gt;XTB&lt;/a&gt; open source and they're quite easy to use. We're working on more efficient methods, but with CREST, you'll get a file with all conformer geometries within 6 kcal/mol of the minimum.&lt;/p&gt;&#xA;&lt;p&gt;You can then use those conformers for further calculations.&lt;/p&gt;&#xA;&lt;p&gt;As other people have mentioned, it may depend on how much your properties vary with conformer geometry. But this approach ensures a fairly robust, arguably exhaustive search with GFN2 (better than a force field).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-01-06T15:15:16.097" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4071" PostTypeId="2" ParentId="4063" CreationDate="2021-01-06T15:32:18.453" Score="4" Body="&lt;p&gt;In order to define the matrix transforming the P21/n structure into P21/a it is imperative to know the unique axis of both space groups.&lt;/p&gt;&#xA;&lt;p&gt;For example the contracted P21/n symbol can be used for the full P21/n11 symbol (unique monoclinic axis along a), for the full P121/n1 (unique axis along b) and for the full P1121/n (unique axis along c).&lt;/p&gt;&#xA;&lt;p&gt;The same apply for P21/a (i.e. it could stand for P21/n11,...).&lt;/p&gt;&#xA;&lt;p&gt;So you have to understand the exact settings of space groups, then you can find the transformation matrix relating them. For example, if you have the initial and final settings P121/n1 -&amp;gt; P121/a1 (same unique b axis in bth space groups), the corresponding transformation matrix is:&#xA;[-1 0 1]&#xA;[ 0 1 0]&#xA;[-1 0 0]&#xA;that is -a-c,b,a&lt;/p&gt;&#xA;&lt;p&gt;If you have P121/n1 -&amp;gt; P1121/a, than the transformation matrix is -a-c,c,b&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2021-01-06T15:32:18.453" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="4072" PostTypeId="1" AcceptedAnswerId="4083" CreationDate="2021-01-06T17:13:58.313" Score="10" ViewCount="1727" Body="&lt;p&gt;I have a bunch of monomers in the form of SMILES string and I want to generate conformers from them.&lt;/p&gt;&#xA;&lt;p&gt;At the moment, I am using  RDKit to convert these SMILES strings to .sdf files, then using OpenBabel to generate conformers using OpenBabel's default genetic algorithm.&lt;/p&gt;&#xA;&lt;p&gt;The problem with this method is that I am having to write these sdf files to disk using RDKit. Once that is done, I then separately run a OpenBabel command on my terminal to produce the low-energy conformers I want.&lt;/p&gt;&#xA;&lt;p&gt;My question is, is there a way to write a python script that accepts SMILES strings, creates an sdf-like object, and then calls the genetic algorithm to go to work on the file and generate conformer file for me to use? I don't want to have the preliminary step of converting the SMILES string to sdf in my workflow.&lt;/p&gt;&#xA;&lt;p&gt;The method I have right now works fine on my personal computer, but when I am accessing a remote cluster with memory constraints, I can't afford to use disk space by storing .sdf/.pdb/.mol files.&lt;/p&gt;&#xA;&lt;p&gt;Any advice you have would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;For reference, I am using &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/3DStructureGen/multipleconformers.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; to create my conformers. Is there a python command in openbabel or pybel that I can use to generate conformers from that SMILES string?&lt;/p&gt;&#xA;&lt;p&gt;The bash script I am using is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#! /bin/bash&#xA;&#xA;obabel -:&amp;quot;CC(=C)C(=O)OCCN(C)C&amp;quot; -O test_.pdb --gen3D -d&#xA;obabel test_.pdb -O test_op.pdb --conformer --nconf 30 --score rmsd --writeconformers&#xA;rm test_.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2021-01-07T05:28:25.000" LastActivityDate="2021-01-07T20:11:43.447" Title="Using OpenBabel or RDKIT Python API to generate conformers from a SMILES string" Tags="|computational-chemistry|python|rdkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4073" PostTypeId="1" AcceptedAnswerId="4078" CreationDate="2021-01-07T04:57:11.030" Score="6" ViewCount="126" Body="&lt;p&gt;To quote from a good textbook, which I don't remember:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Twins which are produced by mechanical deformation are called mechanical twins. Mechanical twins are produced in bcc or hcp metals under conditions of rapid rate of loading (shock loading) or decreased temperature.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I well understand this has to do with slip systems and dislocation veloctiy. But somehow I cannot connect them. What is the connection?&lt;/p&gt;&#xA;" OwnerUserId="1893" LastEditorUserId="5" LastEditDate="2021-01-07T05:05:56.797" LastActivityDate="2021-01-07T15:21:24.753" Title="Why does twinning take place in high rate of shock loading and low temperature?" Tags="|crystallography|physical-properties-of-materials|mechanical-properties|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4074" PostTypeId="1" AcceptedAnswerId="4082" CreationDate="2021-01-07T09:14:04.253" Score="12" ViewCount="310" Body="&lt;p&gt;I am generating conformers from SMILES string using OpenBabel.&#xA;The shell script looks something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel -:&amp;quot;C=C(C)C(=O)OCCN(C)C&amp;quot; -O test_.pdb --gen3D -d&#xA;obabel test_.pdb -O conf_op.xyz --conformer --nconf 30 --score rmsd --writeconformers&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am wondering how I can get more significant digits in my conformer search. Right now, the output has 6 significant digits. I would like to send this up to 12 if possible.&lt;/p&gt;&#xA;&lt;p&gt;This is how it looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;26&#xA;test_.pdb&#xA;C          3.58931       -1.28578        2.90344&#xA;C          4.15221       -0.82944        1.59187&#xA;C          4.95274       -1.60633        0.84210&#xA;C          3.75510        0.55018        1.18604&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there a way to increase accuracy? Any advice would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-01-07T16:56:08.350" Title="How to get more significant digits from OpenBabel?" Tags="|computational-chemistry|open-source|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4075" PostTypeId="1" CreationDate="2021-01-07T14:12:58.627" Score="21" ViewCount="265" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Time-dependent_density_functional_theory#:%7E:text=Time%2Ddependent%20density%2Dfunctional%20theory,as%20electric%20or%20magnetic%20fields.&quot; rel=&quot;noreferrer&quot;&gt;time-dependent density functional theory (TDDFT)&lt;/a&gt; and the many-body perturbation method (GW@BSE) are considered as the two most popular and successful methods to describe the excited-stated properties of materials. In fact, both methods have been reviewed in &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.74.601&quot; rel=&quot;noreferrer&quot;&gt;this classical paper published in the Review of Morden Physics&lt;/a&gt;. From that almost twenty years have passed. What are the recent developments of TDDFT? What's the most popular and successful package that implements TDDFT? And what're the main challenges to realize the simulation of real materials with TDDFT?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disclaimer:&lt;/strong&gt; According to the one-topic-per-answer, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4088/what-are-the-recent-developments-of-gwbse-to-simulate-the-excitated-properteis&quot;&gt;a twin question&lt;/a&gt; related to the GW@BSE method is asked in another post. But any comparisons between both methods in recent developments are welcome.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-09-05T22:45:25.640" LastActivityDate="2023-11-07T05:30:39.423" Title="What are the recent developments of TDDFT to simulate the excited properties of materials?" Tags="|density-functional-theory|one-topic-per-answer|td-dft|excited-states|gw-bse|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4076" PostTypeId="1" AcceptedAnswerId="6975" CreationDate="2021-01-07T14:15:12.607" Score="6" ViewCount="175" Body="&lt;p&gt;I'm using &lt;a href=&quot;https://aoterodelaroza.github.io/critic2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Critic2 software&lt;/a&gt; to perform post-processing of the charge density of metallic alloys. With the charge density obtained from the Self-Consistent-Field calculation (for that I'm using Quantum ESPRESSO), Critic uses both the Yu and Trinkle and Bader methods to perform the charge analysis.&lt;/p&gt;&#xA;&lt;p&gt;The results are the attractors (namely the atoms) within the structure, the atomic volumes, the all-electron density integrated into its basis (POP), the Laplacian of the all-electron basis (LAP), and the pseudo-density (since we use pseudo-potentials) ($2).&lt;/p&gt;&#xA;&lt;p&gt;Bellow an example of its output using the Yu and Trinkle method:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cYSFD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cYSFD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is: how to analyze such results? Or in a more general fashion, how to analyze charge results? All we got are numbers, what are their meanings?&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="5" LastEditDate="2021-09-05T22:46:18.967" LastActivityDate="2021-10-29T19:20:07.657" Title="Interpreting Critic2 charge analysis in metallic systems" Tags="|density-functional-theory|software|charge-density|population-analysis|critic2|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4077" PostTypeId="1" AcceptedAnswerId="4080" CreationDate="2021-01-07T14:32:03.127" Score="10" ViewCount="288" Body="&lt;p&gt;I worked with gaussian to simulate vibrational IR and Raman spectra. For that purpose, I scaled the vibrational frequencies from my gaussian calculation with the scaling factors from this website:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://cccbdb.nist.gov/vsfx.asp&quot; rel=&quot;noreferrer&quot;&gt;https://cccbdb.nist.gov/vsfx.asp&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am writing my bachelor thesis now and wonder where the website found the scaling factors. On the bottom of the page is a reference to a paper.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Some of the above values were taken from&lt;br /&gt;&#xA;A.P. Scott, L. Radom, Harmonic Vibrational Frequencies: An Evaluation of Hartree-Fock, Moller-Plesset, Quadratic Configuration Interaction, Density Functional Theory and Semiempirical Scale Factors, J. Phys. Chem. 100, 16502, 1996&lt;br /&gt;&#xA;In this table many scale factors were assumed to be the same for different basis sets and similar methods.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I read the paper and did not find the scale factors I used in my work.&#xA;For my thesis, I need papers to cite, so I want to ask, how did they assume the scale factors, or where did they find the other scale factors?&lt;/p&gt;&#xA;" OwnerUserId="1682" LastEditorUserId="7" LastEditDate="2021-07-30T20:16:18.857" LastActivityDate="2021-07-30T20:16:18.857" Title="Where did the &quot;Computational Chemistry Comparison and Benchmark DataBase&quot; find its scaling factors for vibrational specra?" Tags="|reference-request|spectroscopy|vibrations|databases|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4078" PostTypeId="2" ParentId="4073" CreationDate="2021-01-07T15:21:24.753" Score="6" Body="&lt;p&gt;It is important to distinguish the origin of twinning, because it produces different features (and different kinds of what is commonly referred to as &amp;quot;twinning&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;For example twinning can develop during the crystal growth as a special feature of the crystal morphology (contact or penetration twins). On the other hand, a single crystal undergoing a structural transition on cooling can develop what is called a 'domain structure' determined by the change of point-group symmetry; that is, in low temperature phase the original single crystal is actually composed of different domains (it is no longer a single crystal, whichever its external shape) oriented according to the crystallographic relationships holding for the point-group desymmetrization.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2021-01-07T15:21:24.753" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4079" PostTypeId="2" ParentId="4035" CreationDate="2021-01-07T15:23:46.520" Score="6" Body="&lt;p&gt;I think Natural Sciences could be a good fit for you. I studied almost the same A Levels you did and couldn't decide whether I preferred Physics or Chemistry. Studying Natural Sciences allowed me to take courses in both, and to choose the areas I liked most and leave out the ones I didn't&lt;/p&gt;&#xA;&lt;p&gt;It's worth bearing in mind that these subjects change in content when you study them at university - the maths content of Physics increases a LOT - you'll find yourself using a lot of matrices. Equally, I found Chemistry had more maths content than at A level, but that may vary from course to course.&lt;/p&gt;&#xA;&lt;p&gt;It's also worth knowing that most Natural Sciences courses let you transfer in the first year to study either Physics or Chemistry if you decide you definitely prefer one at university level.&lt;/p&gt;&#xA;&lt;p&gt;I'd recommend having a look at the Natural Sciences course at Bath to start, as it's highly customisable and lets you choose which elements of Chemistry to keep. There's also some good Chemical Physics courses out there too which have a similar structure!&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps, and good luck!&lt;/p&gt;&#xA;" OwnerUserId="1896" LastEditorUserId="5" LastEditDate="2021-01-07T15:29:01.527" LastActivityDate="2021-01-07T15:29:01.527" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4080" PostTypeId="2" ParentId="4077" CreationDate="2021-01-07T16:46:57.087" Score="9" Body="&lt;p&gt;I have a different page on the NIST website (&lt;a href=&quot;https://cccbdb.nist.gov/vibscale.asp&quot; rel=&quot;noreferrer&quot;&gt;https://cccbdb.nist.gov/vibscale.asp&lt;/a&gt;) that gives uncertainties in the scaling factors. I believe many of these were actually established by NIST themselves from the database itself.&lt;/p&gt;&#xA;&lt;p&gt;But many of them are in the &lt;a href=&quot;https://doi.org/10.1021/jp960976r&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; you cite, in Table 1:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vFFeA.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vFFeA.jpg&quot; alt=&quot;table of vibrational scaling factors&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you probably know, one problem is that most quantum chemical methods calculate &lt;em&gt;harmonic&lt;/em&gt; vibrational frequencies - and many vibrations have at least some &lt;em&gt;anharmonic&lt;/em&gt; character.&lt;/p&gt;&#xA;&lt;p&gt;There are &lt;em&gt;many&lt;/em&gt; more recent vibrational scaling papers. Basically, authors will compile high-quality experimental vibrational spectra, then compare individual experimental frequencies against computed frequencies from the various methods via linear least-squares regression for one scaling factor.&lt;/p&gt;&#xA;&lt;p&gt;A somewhat more recent compilation by Leo Radom can be found in &lt;a href=&quot;https://doi.org/10.1021/jp073974n&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;An Evaluation of Harmonic Vibrational Frequency Scale Factors&amp;quot; &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2007&lt;/strong&gt;, 111, 45, 11683–11700&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There are a bunch of other methods for &amp;quot;correcting&amp;quot; computed vibrational frequencies. There's a &lt;a href=&quot;https://doi.org/10.1007/978-3-030-01355-4_2&quot; rel=&quot;noreferrer&quot;&gt;review&lt;/a&gt; in &lt;em&gt;Molecular Spectroscopy—Experiment and Theory&lt;/em&gt; and undoubtedly by other authors as well.&lt;/p&gt;&#xA;&lt;p&gt;For example Grimme argues on scaling atomic masses instead of one-parameter scaling factors in a &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c00877&quot; rel=&quot;noreferrer&quot;&gt;recent paper&lt;/a&gt;. I still expect the single scale factor to remain popular for simplicity, though.&lt;/p&gt;&#xA;&lt;p&gt;At some point, perhaps anharmonic vibrational calculations will be more tractable, though the NIST group indicated in 2013 that &lt;a href=&quot;https://doi.org/10.1021/ct300293a&quot; rel=&quot;noreferrer&quot;&gt;anharmonic calculations may not be more accurate than scaled harmonic&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2021-01-07T21:00:21.370" LastActivityDate="2021-01-07T21:00:21.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4081" PostTypeId="2" ParentId="3881" CreationDate="2021-01-07T16:51:53.197" Score="14" Body="&lt;p&gt;&lt;em&gt;[Disclaimer - I am one of the co-authors of the &lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/&quot; rel=&quot;noreferrer&quot;&gt;2D database on Materials Cloud&lt;/a&gt; (What you call &amp;quot;2D structures and layered materials&amp;quot;, publishing the data of this work: &lt;a href=&quot;https://doi.org/10.1038/s41565-017-0035-5&quot; rel=&quot;noreferrer&quot;&gt;N. Mounet et al., Nature Nanotech. 13, 246–252 (2018)&lt;/a&gt; so I will mostly refer to it below]&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;In general, these studies &amp;quot;extract&amp;quot; a layer from a bulk 3D material, and then often perform a crystal-structure relaxation on the resulting 2D layer to find a local minimum. Some studies also perform additional tests to understand if the material is really exfoliable (e.g. in &lt;em&gt;Mounet et al.&lt;/em&gt; we compute also the binding energy of the bulk layered material).&lt;/p&gt;&#xA;&lt;p&gt;The relaxation of the structure, however, is not enough to guarantee that the system is stable. Here are just some of the possible reasons why you could end up only in a &lt;em&gt;local&lt;/em&gt; energy minimum:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the relaxation in many codes tries to keep the crystal symmetry, so you might remain in a high-symmetry configuration (e.g. at the top of a double well);&lt;/li&gt;&#xA;&lt;li&gt;in general, all these structual minimisation algorithms find only local minima close to the starting point (technically, it depends on which &amp;quot;basin of attraction&amp;quot; the starting point is);&lt;/li&gt;&#xA;&lt;li&gt;You might need a larger supercell to find a stable structure.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In &lt;em&gt;Mounet et al.&lt;/em&gt;, for a subset of the materials we found (easily exfoliable with small number of atoms in the unit cell, i.e. all those available on &lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud&lt;/a&gt;) we performed an additional step (first column of page 250 of the paper), where&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;First, we compute phonon frequencies at the Γ point in the Brillouin zone and, if we find imaginary-frequency modes (this can happen if atoms are constrained by symmetries to be in a saddle point), we displace them along the modes' eigenvectors first (see Methods), and then fully relax the structure. The procedure is iterated until all phonon energies at the Γ point become real and positive.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Therefore, for the systems from the Materials Cloud database, you should always find all phonons positive at Γ; there might still be phonons that are imaginary out of Γ, hinting at the need of a larger supercell, and/or at charge-density waves.&lt;/p&gt;&#xA;&lt;p&gt;For completeness, the method used to perform the algorithm above uses the algorithm of &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.87.184104&quot; rel=&quot;noreferrer&quot;&gt;A. Togo, I. Tanaka, Phys. Rev. B 87, 184104 (2013)&lt;/a&gt; and it's described in mode detail in the Methods section of the paper (and, of course, in Togo's paper in full detail).&lt;/p&gt;&#xA;&lt;p&gt;Finally, one final important note: when computing phonons of 2D materials in codes using periodic boundary conditions, it is crucial to use an appropriate correction to correct the effect of periodic images. But most importantly, the physics is quite different in 2D from 3D, for what concerns long-range effects on the phonon dispersion (just to mention one thing, there is no LO-TO splitting in 2D but a discontinuity in the derivative of the phonon branches).&#xA;The physics is described here: &lt;a href=&quot;https://doi.org/10.1021/acs.nanolett.7b01090&quot; rel=&quot;noreferrer&quot;&gt;T. Sohier &lt;em&gt;et al.&lt;/em&gt;, Nano Lett. 17, 3758–3763 (2017)&lt;/a&gt; and the method is implemented in Quantum ESPRESSO (and maybe also in some other codes).&lt;/p&gt;&#xA;&lt;p&gt;In &lt;em&gt;Mounet et al.&lt;/em&gt; we compute phonons taking these effects into account - you can check this, for instance, in the &lt;a href=&quot;https://www.materialscloud.org/discover/2dstructures/details/BN&quot; rel=&quot;noreferrer&quot;&gt;phonon dispersion of BN&lt;/a&gt;&#xA;where indeed there is no LO-TO splitting for the phonons (see e.g. the phonons at Γ around 40 THz).&lt;/p&gt;&#xA;" OwnerUserId="1897" LastActivityDate="2021-01-07T16:51:53.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4082" PostTypeId="2" ParentId="4074" CreationDate="2021-01-07T16:56:08.350" Score="10" Body="&lt;p&gt;The &lt;a href=&quot;https://www.wwpdb.org/documentation/file-format&quot; rel=&quot;noreferrer&quot;&gt;PDB file format&lt;/a&gt; has a strict specification on the number of columns, etc. (Consider that some proteins have &lt;em&gt;very&lt;/em&gt; large sizes, so distances can be many Ångstroms.)&lt;/p&gt;&#xA;&lt;p&gt;Thus, the number of decimal places are generally given by the file format.&lt;/p&gt;&#xA;&lt;p&gt;Some people have asked why Open Babel doesn't give more decimal places, e.g., in the XYZ format, which is, in principal, more flexible:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C          1.38320       -0.22154        0.00551&#xA;C          0.50683       -1.30676       -0.00807&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Consider that the accuracy above is 0.00001Å, far beyond any experimental technique. I picked that as a reasonable balance - adding more decimal places quickly adds up for file sizes across many larger molecules.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;In principal&lt;/em&gt;, there may be some small round-off errors if you're converting to XYZ from some calculation.&lt;/p&gt;&#xA;&lt;p&gt;If someone can provide clear justification that the round-off error produces significant error in a subsequent calculation, I'd consider that a bug worth fixing.&lt;/p&gt;&#xA;&lt;p&gt;You seem to be generating initial geometries with a force field. I'd guess that errors in bond lengths, angles, etc. from the force field (vs. quantum chemistry) are on the order of 0.01Å or larger, so even 5 decimal places seems overkill.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-01-07T16:56:08.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4083" PostTypeId="2" ParentId="4072" CreationDate="2021-01-07T17:05:20.197" Score="7" Body="&lt;p&gt;My colleague David Koes has a script for this purpose using RDKit &lt;a href=&quot;https://github.com/dkoes/rdkit-scripts/blob/master/rdconf.py&quot; rel=&quot;noreferrer&quot;&gt;rdconf.py&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A related Open Babel / Pybel script would be &lt;a href=&quot;https://gist.github.com/ghutchis/0766478cc9bc1c00f623ce560954b8c1&quot; rel=&quot;noreferrer&quot;&gt;globalopt.py&lt;/a&gt;, the main portion of which is reproduced below:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;pybel._builder.Build(mol.OBMol)&#xA;mol.addh()&#xA;&#xA;ff = pybel._forcefields[&amp;quot;mmff94&amp;quot;]&#xA;success = ff.Setup(mol.OBMol)&#xA;if not success:&#xA;    ff = pybel._forcefields[&amp;quot;uff&amp;quot;]&#xA;    success = ff.Setup(mol.OBMol)&#xA;    if not success:&#xA;        sys.exit(&amp;quot;Cannot set up forcefield&amp;quot;)&#xA;&#xA;ff.ConjugateGradients(100, 1.0e-3) # optimize geometry&#xA;ff.WeightedRotorSearch(100, 25) # generate conformers&#xA;&#xA;ff.GetCoordinates(mol.OBMol)&#xA;mol.write(&amp;quot;sdf&amp;quot;, &amp;quot;test.sdf&amp;quot;, overwrite=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This isn't quite what you describe because it only saves the lowest energy conformer. I have to go finish some other work, but should give you the basic idea. Both RDKit and Open Babel can do what you describe.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="7" LastEditDate="2021-01-07T20:11:43.447" LastActivityDate="2021-01-07T20:11:43.447" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4084" PostTypeId="2" ParentId="1" CreationDate="2021-01-07T17:25:31.120" Score="8" Body="&lt;p&gt;As an additional comment, the &lt;a href=&quot;https://www.optimade.org&quot; rel=&quot;noreferrer&quot;&gt;OPTIMADE consortium&lt;/a&gt; is developing a standard REST API to query many different databases with the same API.&#xA;Version 1.0 of the specs is out (on GitHub, and &lt;a href=&quot;https://doi.org/10.5281/zenodo.4195050&quot; rel=&quot;noreferrer&quot;&gt;a version with DOI for 1.0 on Zenodo&lt;/a&gt;).&#xA;Many of the DBs mentioned earlier are now working to expose their data via OPTIMADE.&lt;/p&gt;&#xA;&lt;p&gt;Beside performing the queries with any browser or command-line tool (&lt;code&gt;wget&lt;/code&gt;, &lt;code&gt;curl&lt;/code&gt;, ...), there are two &amp;quot;web&amp;quot; clients I am aware of:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://optimade.science/&quot; rel=&quot;noreferrer&quot;&gt;https://optimade.science/&lt;/a&gt; that allows to run the same query on multiple databases&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.materialscloud.org/work/tools/optimadeclient&quot; rel=&quot;noreferrer&quot;&gt;https://www.materialscloud.org/work/tools/optimadeclient&lt;/a&gt; that allows to perform queries using a convenient GUI (on one database at a time)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;em&gt;[Disclaimer: I am actively involved with the OPTIMADE consortium]&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="1897" LastActivityDate="2021-01-07T17:25:31.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4085" PostTypeId="2" ParentId="4064" CreationDate="2021-01-07T17:35:35.743" Score="4" Body="&lt;p&gt;In the input file you define&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;THERMOSTAT&#xA;    &amp;amp;CSVR&#xA;        TIMECON     9.9999999999999986E+01&#xA;    &amp;amp;END CSVR&#xA;&amp;amp;END THERMOSTAT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I guess you intended to use the CSVR (canonical sampling through velocity rescaling) thermostat. But because you did not set &lt;code&gt;TYPE CSVR&lt;/code&gt; CP2K uses the default Nose Hoover thermostat instead.&lt;/p&gt;&#xA;&lt;p&gt;However, CP2K does not save all thermostat sections to the restart file, only those that are active in the simulation AND are present in the input file. Because &lt;code&gt;&amp;amp;NOSE&lt;/code&gt; is not present in the input CP2K did not save the &lt;code&gt;&amp;amp;NOSE&lt;/code&gt; section to the restart file. Consequently, the information to properly restart the thermostat is lost. Therefore, the Nose Hoover thermostat is reinitialized when the MD is continued and the &amp;quot;conserved quantity&amp;quot; is not conserved.&lt;/p&gt;&#xA;&lt;p&gt;If you change the input file to&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;THERMOSTAT&#xA;    TYPE CSVR&#xA;    &amp;amp;CSVR&#xA;        TIMECON     9.9999999999999986E+01&#xA;    &amp;amp;END CSVR&#xA;&amp;amp;END THERMOSTAT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the &amp;quot;conserved quantity&amp;quot; should indeed be conserved in subsequent restarts.&lt;/p&gt;&#xA;" OwnerUserId="295" LastActivityDate="2021-01-07T17:35:35.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4086" PostTypeId="2" ParentId="4057" CreationDate="2021-01-07T21:04:36.290" Score="1" Body="&lt;p&gt;Maybe I didn't understand exactly your question, but it seems to me that you'd better take a look at Pauling's rules. Even though they are not always strictly respected, they works in most cases. The stability of a compound involves several factors and one of the most important is the radius ratio.&lt;/p&gt;&#xA;&lt;p&gt;About the distinction between ionic and covalent bond; again Pauling provided a formula for calculating the ionic and covalent percentage in the bond for binary compounds. Actually a pure covalent bonding can be found (for example in pure elements such as Ga), conversely a pure ionic compound has not yet been found (i.e. a very few percentage of covalent bonding is always present). I don'know the origin of the electronegativity difference &amp;gt; 1.7 value, but this number is meaningles by itself; I guess it refers to some specific binary stoichiometry. In fact you have to consider not only the electronegativity difference, but also how it is shared and this depends on the coordination number and ionic radius ratio. This factors affects the tendency of an atom in a molecule to attract electrons.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2021-01-07T21:04:36.290" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="4087" PostTypeId="2" ParentId="4035" CreationDate="2021-01-07T23:02:34.010" Score="6" Body="&lt;p&gt;I think one thing missing from other commenters here is the fact that your university and PhD concentration diminishes in importance and relevance as you get older. This begins almost immediately out of your PhD. Nowadays, a successful researcher will work inside a highly interdisciplinary team and pick up skills in additional areas. You'll start out confused and overwhelmed but gradually learn from reading and asking questions. The academic differences between you and your colleagues will begin to blur and it may be that some small, half-forgotten, and unexpected part of your formal training really sets you apart. For example, I am a computational chemist and I work with chemical engineers and materials scientists, one of which also does computational chemistry while the others are experts in spectroscopic and spectrometric characterization (rechargeable batteries). They often use mass spectrometry (MS) or X-ray photoelectron spectroscopy (XPS) to characterize materials formed as a result of parasitic reactions during the cycling of a battery. As a student, I became familiar with interpreting MS but never really learned XPS. Fast forward a few years working with this team and though I've literally never even seen an actual XPS instrument in person, I've become quite adept at interpreting the result to supplement and guide my computational experiments. My familiarity with organic chemistry sets me apart even though I focused on physical chemistry as a PhD student. The same is true for predictions of small-angle neutron scattering (SANS) from molecular dynamics simulations. I've never seen the instrument and learned next to nothing about it until my post-doctoral position. I picked up books off Amazon on topics in solid state chemistry and physics I was unfamiliar with.&lt;/p&gt;&#xA;&lt;p&gt;Study what gets you to where you want to be via the path of least resistance, it is a necessary part of modern science to develop a strong interdisciplinary knowledgebase. Note, 'resistance' here doesn't just mean the difficulty of the classes (haha), but whether you're motivated to learn about it, relevance (also emerging fields like machine learning), maybe a professor's recommendation, the opportunity to join a lab with experimentalists and theorists alike, whether there's a market for the skill post-graduation, etc.&lt;/p&gt;&#xA;&lt;p&gt;I can't say what is right for you to pursue, but if I were your age and wanted only to improve on my formal training and add a unique skill to my current team, I would do whatever is necessary to get me into courses on machine learning. This is much more difficult to develop an understanding of and keep up with out of school with all your other research and life duties competing for your time. This may mean a dual major in mathematics or computer science or maybe a minor concentration. I'd still pursue a chemistry degree. I'm pretty sure one of our previous post-docs in computational chemistry had a PhD in computer science and developed new methods to speed up density functional theory calculations. If nothing else, I hope my experience helps you feel more at ease choosing a degree knowing your career path isn't set in stone, there's considerable flexibility.&lt;/p&gt;&#xA;" OwnerUserId="1901" LastActivityDate="2021-01-07T23:02:34.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4088" PostTypeId="1" CreationDate="2021-01-08T02:49:28.650" Score="14" ViewCount="297" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4075/what-are-the-recent-developments-of-tddft-to-simulate-the-excitated-properteis-o&quot;&gt;A twin question&lt;/a&gt; related to the TDDFT method is asked in another post. But any comparisons between both methods in recent developments are welcome.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Time-dependent_density_functional_theory#:%7E:text=Time%2Ddependent%20density%2Dfunctional%20theory,as%20electric%20or%20magnetic%20fields.&quot; rel=&quot;nofollow noreferrer&quot;&gt;time-dependent density functional theory (TDDFT)&lt;/a&gt; and the many-body perturbation theory (GW@BSE) methods are considered as the two most popular and successful methods to describe the excited-stated properties of materials. In fact, both methods have been reviewed in &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.74.601&quot; rel=&quot;nofollow noreferrer&quot;&gt;this classical paper published in Review of Morden Physics&lt;/a&gt;. From that almost twenty years have passed. What are the recent developments of the GW@BSE method? And what are the current challenges to simulate real materials with the GW@BSE method? As far as I know, the &lt;a href=&quot;https://berkeleygw.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BerkeleyGW GROUP&lt;/a&gt; and &lt;a href=&quot;http://www.yambo-code.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Yambo GROUP&lt;/a&gt; have successfully implemented the framework of the GW@BSE method based on plane-wave DFT calculations. Are there any packages to realize this method, especially without dependence on plane-wave DFT?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-09-05T22:47:44.187" LastActivityDate="2023-03-10T19:06:55.507" Title="What are the recent developments of GW@BSE to simulate the excited properties of materials?" Tags="|density-functional-theory|one-topic-per-answer|td-dft|gw-bse|excited-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4089" PostTypeId="2" ParentId="4035" CreationDate="2021-01-08T11:33:37.387" Score="4" Body="&lt;p&gt;I would take a total different approach to solving this.&lt;/p&gt;&#xA;&lt;p&gt;Rather than focusing on the topics and their relative difficulty etc. Try to envision a hard problem that you want to solve and work on for a long time and from that point of view you find the skills needed to solve that challenge. Eg., be problem focused rather than solution focused. It's a similar approach to what is used when building a startup, you don't take a technology and try to find uses for it because its dam hard to find a business model etc. that fits nicely. But rather focus intensely on a hard problem and from there you try different solutions and you reverse engineer the problem until you iteratively find an optimal solution.&lt;/p&gt;&#xA;" OwnerUserId="1906" LastActivityDate="2021-01-08T11:33:37.387" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4090" PostTypeId="1" CreationDate="2021-01-08T14:44:21.367" Score="14" ViewCount="698" Body="&lt;p&gt;Say, I have two crystal structures of a particular organic molecule, the crystal structures are basically identical, apart from a rotation and redefinition of the lattice vectors/angles, a simple result of different choices during the structure refinement process after the xray or neutron experiment for structure determination.&#xA;As a practical example consider triclinic (P-1) malonic acid for which two structures have been published:&lt;/p&gt;&#xA;&lt;p&gt;one (MALNAC02) with: a,b,c, alpha,beta,gamma=5.156,5.341,8.407,71.48,76.12,85.09&lt;/p&gt;&#xA;&lt;p&gt;the other (MALNAC) with a,b,c, alpha,beta,gamma=5.33,5.14,11.25,102.7,135.17,85.17&lt;/p&gt;&#xA;&lt;p&gt;If I wanted to convert one structure to the other so that they perfectly overlap (apart from&#xA;a trivial translation step), by rotating it successively through one or more of the cartesian (x,y,z) axis through appropriate angles, how would I find these angles?&lt;/p&gt;&#xA;&lt;p&gt;I understand there are different ways to do this, other than the successive rotation around the cartesian axes (use a rotation matrix or Eulerian angles) but here I need to know these angles (around the cartesian axes), also I know there is not only one unique version of these angles  - but I am fine with having just one of them.&lt;/p&gt;&#xA;" OwnerUserId="1878" LastEditorUserId="5" LastEditDate="2021-01-08T14:50:29.400" LastActivityDate="2021-01-14T20:00:33.753" Title="Rotation of crystal structure to match another structure of the same compound/polymorph" Tags="|crystal-structure|symmetry|crystallography|geometry|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4091" PostTypeId="1" CreationDate="2021-01-08T18:13:54.530" Score="7" ViewCount="3237" Body="&lt;p&gt;The energy of a quantum harmonic oscillator is given as,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;E_{qho} = \left(n + \frac{1}{2}\right)\hbar\omega,\;\;\;\;\;\; n = 0,1,2,3,... \tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I understand the implications of the Heisenberg's uncertainty principle not permitting atoms to be at a standstill even at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K. This uncertainty is the reason for some energy possessed by atoms at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K - the &lt;em&gt;zero-point energy&lt;/em&gt; (ZPE). Most texts introduce ZPE by noting how with &lt;span class=&quot;math-container&quot;&gt;$n = 0$&lt;/span&gt; there is still a remnant energy equal to &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}\hbar\omega$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; only a number? If so, how has &lt;span class=&quot;math-container&quot;&gt;$n = 0$&lt;/span&gt; anything to do with temperature?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2021-01-09T11:57:36.923" LastActivityDate="2021-01-09T21:22:34.133" Title="Quantum harmonic oscillator, zero-point energy, and the quantum number n" Tags="|phonons|vibrations|zero-point-energy|" AnswerCount="5" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4092" PostTypeId="2" ParentId="4091" CreationDate="2021-01-08T18:51:16.520" Score="6" Body="&lt;p&gt;The quantum number n simply represents the different energy levels given by the harmonic oscillator.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{n=0}$&lt;/span&gt; does not correspond to a given temperature, but its relative occupation to other energy levels does correspond to a given temperature.  As a system rises in temperature, the higher energy levels can be occupied at greater numbers.  Likewise, at 0 K there is a requirement that only the lowest energy level is occupied.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-08T18:51:16.520" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4093" PostTypeId="2" ParentId="4091" CreationDate="2021-01-08T19:00:20.693" Score="10" Body="&lt;p&gt;The zero-point energy is of no importance here, since you can always choose your reference energy freely you can energy-shift your hamiltonian by &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}\hbar\omega$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \frac{p^2}{2m}+\frac{1}{2}m\omega^2x^2-\frac{1}{2}\hbar\omega,&#xA;$$&lt;/span&gt;&#xA;and the physics of the system will stay the same (the wave function will be the same). Since this wavefunction is not a delta-function located at zero (as it is in classical mechanics) but instead more spread out, you can interpret this as, for example, your atoms still vibrating when in this eigenstate of the hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;Regarding your question: Yes, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is just a number which is meant to label the energy eigenstates from lowest to highest. Temperature only plays in indirectly. To define a temperature, you have to define a thermal ensemble (you need more than one particle to do it properly) with an associated density matrix &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;. A common choice for this is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho = \frac{1}{z}\sum_{i=1}^{\infty}|i\rangle e^{-E_{i}/kT} \langle i|, z = \sum_{i=1}^{\infty}e^{-E_i/kT}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$|i\rangle$&lt;/span&gt; denote the energy eigenstates and &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt; the corresponding energy eigenvalues (in this case for the harmonic oscillator). &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is temperature, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; just a constant. You can interpret (similarly to a wavefunction expansion coefficient) that the factor &lt;span class=&quot;math-container&quot;&gt;$e^{-E_{i}/kT}/z$&lt;/span&gt; is a probability of being in the state &lt;span class=&quot;math-container&quot;&gt;$|i\rangle$&lt;/span&gt;. You can see that when &lt;span class=&quot;math-container&quot;&gt;$T\rightarrow 0$&lt;/span&gt;, only the coefficient with the lowest energy eigenvalue will remain (any coefficient with higher &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt;-value will vanish faster). From this can be deducted that for a general system (not just your harmonic oscillator example) the system will be in the lowest-energy state when &lt;span class=&quot;math-container&quot;&gt;$T\rightarrow 0$&lt;/span&gt; (as long as you have a thermal ensemble).&lt;/p&gt;&#xA;" OwnerUserId="1701" LastActivityDate="2021-01-08T19:00:20.693" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4094" PostTypeId="2" ParentId="4091" CreationDate="2021-01-08T19:56:56.347" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; only a number?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is indeed a number. Is it only a number? Well it's a &lt;em&gt;quantum number&lt;/em&gt; which means it labels the &lt;span class=&quot;math-container&quot;&gt;$n^{\textrm{th}}$&lt;/span&gt; excited energy level of the system (i.e. the &lt;span class=&quot;math-container&quot;&gt;$(n+1)^{\textrm{th}}$&lt;/span&gt; smallest eigenvalue of the system's Hamiltonian, with &lt;span class=&quot;math-container&quot;&gt;$n=0$&lt;/span&gt; corresponding to the &lt;em&gt;smallest&lt;/em&gt; eigenvalue, &lt;span class=&quot;math-container&quot;&gt;$n=1$&lt;/span&gt; corresponding to the &lt;em&gt;second&lt;/em&gt; smallest eigenvalue, &lt;em&gt;etc.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If so then how does &lt;span class=&quot;math-container&quot;&gt;$n = 0$&lt;/span&gt; have anything to do with temperature?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The density matrix of a system with the harmonic oscillator potential is often given in terms of the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\rho = \frac{e^{-\beta H}}{\textrm{tr}\left(e^{-\beta H}\right)},~~~~~~~~\beta\equiv \frac{1}{k_BT}.&#xA;\tag{1}&#xA;\label{eq:boltzmann}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The diagonals of the density matrix from top-left to bottom-right then tell you the probability of finding the system in &lt;span class=&quot;math-container&quot;&gt;$n=0,1,2,\ldots$&lt;/span&gt;, meaning that if the top-left element of the density matrix is &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, the system's probability of being found at the energy level corresponding to &lt;span class=&quot;math-container&quot;&gt;$n=0$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;. When &lt;span class=&quot;math-container&quot;&gt;$T=0$&lt;/span&gt; we have that the probability of the system being in any excited state (&lt;span class=&quot;math-container&quot;&gt;$n&amp;gt;0$&lt;/span&gt;) is extremely supressed by the decaying exponential, and you can count on finding the system at the &lt;span class=&quot;math-container&quot;&gt;$n=0$&lt;/span&gt; level. When &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is larger, the excited states will more likely get populated. As &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; approaches &lt;span class=&quot;math-container&quot;&gt;$+\infty$&lt;/span&gt;, the exponential becomes close to 1 and we approach a scenario where the probabilities become equal for each state &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Eq. 1 in this answer is also:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Eq. 1 in this answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1004/converting-adsorption-binding-energy-to-absolute-temperature/1005#1005&quot;&gt;Converting adsorption binding energy to absolute temperature&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Eq. 3 in this answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1875/can-i-compute-the-free-energy-difference-in-temporally-nearby-micro-states-usi/1876#1876&quot;&gt;Can I compute the free energy difference in (temporally) nearby micro-states using the Zwanzig equation for Free Energy Perturbation?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Eq. 2 in this answer:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4091/quantum-harmonic-oscillator-zero-point-energy-and-the-quantum-number-n/4093#4093&quot;&gt;Quantum harmonic oscillator, zero-point energy, and the quantum number n&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-01-08T20:40:03.820" LastActivityDate="2021-01-08T20:40:03.820" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4095" PostTypeId="2" ParentId="4090" CreationDate="2021-01-08T21:22:41.233" Score="8" Body="&lt;p&gt;If you know which atoms correspond to each other in the two structures,&#xA;you can use a &lt;em&gt;structural superposition&lt;/em&gt; method.&#xA;Least-squares superposition methods find the rotation matrix and translation that minimizes the RMSD between given points.&lt;/p&gt;&#xA;&lt;p&gt;There are a few well-established methods.&#xA;Recently, I had to use one and I picked &lt;a href=&quot;https://theobald.brandeis.edu/qcp/&quot; rel=&quot;noreferrer&quot;&gt;QCP&lt;/a&gt;&#xA;(because it comes with BSD-licensed C code),&#xA;but for a small set of points like in your problem any method should work.&lt;/p&gt;&#xA;" OwnerUserId="126" LastEditorUserId="126" LastEditDate="2021-01-08T23:41:29.017" LastActivityDate="2021-01-08T23:41:29.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4096" PostTypeId="1" AcceptedAnswerId="4097" CreationDate="2021-01-08T22:54:56.777" Score="9" ViewCount="917" Body="&lt;p&gt;I'm a beginner in DFT calculation. I have performed a DFT calculation on CuCoSnSe using PBE-GGA on Quantum Esspresso. When I plot the band structure and the total DOS, the band structure shows a behavior of the semiconductor with a direct bandgap, but the total DOS does not show the same behavior.&lt;/p&gt;&#xA;&lt;p&gt;Can someone give me an explanation of what happened or suggest some modifications to get reasonable results?&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/dJhiO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/ILfCY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="1218" LastEditDate="2021-01-09T02:03:31.950" LastActivityDate="2021-01-11T00:49:46.773" Title="inconsistent behavior between band structure and density of states" Tags="|density-functional-theory|vasp|quantum-espresso|wien2k|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4097" PostTypeId="2" ParentId="4096" CreationDate="2021-01-09T01:59:57.747" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;When I plot the band structure and the total DOS, the band structure shows a behavior of the semiconductor with a direct bandgap, but the total DOS does not show the same behavior.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The red arrow in your band structure is the direct gap at &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; point, rather than the gap defined as the difference between conduction band minimum (CBM) and valence band maximum (VBM). (The VBM is located between &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt;.) The direct bandgap is related to the position of your &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt;-pint, but your DOS can only reflect the information about the global bandgap, in which the information of &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt;-points is integrated. You can read this post to learn &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1791/properties-that-can-be-deduced-from-band-structure-and-dos/2396#2396&quot;&gt;what you can obtain from band structure and DOS&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The previous point is good to analyze the band structure and DOS of semiconductors. However, here your DOS and band structure manifest metallic features. There are two things that you should check:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The DOS displays ferromagnetic properties, which means you should plot the band structure with two spin-channels.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Whether the Fermi level in your DOS plot is consistent with your band structure plot or not?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-11T00:49:46.773" LastActivityDate="2021-01-11T00:49:46.773" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4098" PostTypeId="2" ParentId="4091" CreationDate="2021-01-09T02:23:41.630" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Is &lt;span class=&quot;math-container&quot;&gt;$$&lt;/span&gt; only a number?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In short, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the energy quantum number of the quantum harmonic oscillator.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If so then how does &lt;span class=&quot;math-container&quot;&gt;$$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; have anything to do with temperature?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In particular, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; means that the harmonic oscillator will stay at its ground state. &lt;strong&gt;Usually, the ground state of a quantum system is assumed to be lived at zero temperature.&lt;/strong&gt; Therefore, you can find a connection between &lt;span class=&quot;math-container&quot;&gt;$n=0$&lt;/span&gt; and zero-point.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Here is a post to talk about the relationship between zero temperature and ground state.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/294593/whats-the-relation-between-zero-temperature-and-ground-state-of-interacting-man&quot;&gt;https://physics.stackexchange.com/questions/294593/whats-the-relation-between-zero-temperature-and-ground-state-of-interacting-man&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Here is a post to talk about what's the size to talk about thermal equilibrium (This is important to define temperature):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/311357/whats-the-size-to-talk-about-thermal-equilibrium&quot;&gt;https://physics.stackexchange.com/questions/311357/whats-the-size-to-talk-about-thermal-equilibrium&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-09T02:23:41.630" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4099" PostTypeId="2" ParentId="4096" CreationDate="2021-01-09T05:31:12.440" Score="6" Body="&lt;p&gt;I personally suspect that you may have converged to two different magnetic states.  You should verify the final magnetic moments on each ion and confirm they are the same.  Did you restart the entire calculation or did you do a non-self consistent run of both?&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-09T05:31:12.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4100" PostTypeId="2" ParentId="4090" CreationDate="2021-01-09T08:33:20.160" Score="3" Body="&lt;p&gt;It seems to me that there is a discrepancy about the c-axis in the 2 unit cells, producing a significant difference in the unit cell volume (213.1 and 210.8, respectively).&lt;/p&gt;&#xA;&lt;p&gt;If you apply the transformation matrix [-b,-a,c] to the first unit cell 5.156 5.341 8.407 71.48 76.12 85.09 and compare with the second one you obtain:&lt;/p&gt;&#xA;&lt;p&gt;5.341 5.156 8.407 103.88 108.52 85.09 Transformed Unit Cell&#xA;5.33  5.14  11.25 102.7  135.17 85.17 Second Unit Cell&lt;/p&gt;&#xA;&lt;p&gt;You can see that a and b axes, as well as gamma (the angle between a and b) are in good agreement in both cases (within experimental differences), whereas the parameters where the c-axis plays a role diverge (c-axis and alfa and beta angles). I would suggest to draw both structures using the corresponding structural data (if available) as well as to compare the occupation of the special positions (if any) for the different atoms.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2021-01-09T08:33:20.160" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4101" PostTypeId="1" AcceptedAnswerId="4102" CreationDate="2021-01-09T10:41:35.100" Score="14" ViewCount="307" Body="&lt;p&gt;Currently I am trying to apply to a graduate program overseas. They require me to include a research proposal in my application. My topic of interest is computational materials science.&lt;/p&gt;&#xA;&lt;p&gt;So, one application of ab initio methods for modelling matter is density functional theory. In it, a central component is a formulation of the many-body Schrodinger equation known as the Kohm-Sham equation. The equation is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left( \frac{-\hbar^2\nabla^2}{2m} + \mathcal{V}_N(\textbf{r}) + \mathcal{V}_H(\textbf{r}) + \mathcal{V}_{xc}[\rho(\textbf{r})] \right) \phi_i(\textbf{r}) = \textit{E}_i \phi_i (\textbf{r})&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To solve this equation, one can apply the self consistency principle and iteratively solve the equation until convergence:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pick initial &lt;span class=&quot;math-container&quot;&gt;$\rho(\textbf{r})$&lt;/span&gt; and decide the exchange-correlation functional&lt;/li&gt;&#xA;&lt;li&gt;Calculate potentials&lt;/li&gt;&#xA;&lt;li&gt;Solve the eigenvalue problem&lt;/li&gt;&#xA;&lt;li&gt;Get new &lt;span class=&quot;math-container&quot;&gt;$\rho(\textbf{r})$&lt;/span&gt; and check for convergence&lt;/li&gt;&#xA;&lt;li&gt;Go to step 2 if necessary&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The eigenproblem step can get computationally expensive for large systems. The proposed research would speed up this step for certain systems by applying parallelization and relevant numerical techniques like spectral approximation, polynomial filtering, and spectral slicing. We also propose looking into modifying known iterative algorithms for solving the eigenvalue problem.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I feel like I'm throwing a dart while blindfolded with writing this research proposal for a graduate school application and would like some input.&lt;/p&gt;&#xA;" OwnerUserId="1907" LastEditorUserId="1907" LastEditDate="2021-06-04T23:55:32.143" LastActivityDate="2021-06-04T23:55:32.143" Title="DFT Knowledge Check for Posed Problem" Tags="|density-functional-theory|ab-initio-calculations|high-performance-computing|numerical-convergence|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4102" PostTypeId="2" ParentId="4101" CreationDate="2021-01-09T15:38:08.407" Score="12" Body="&lt;p&gt;I agree with Camps that your best bet is to look at a potential advisor and see what they study.  Your given example might be a bit of a stretch for some computational materials science advisors, due to its very fundamental nature of solving the problem rather than applying the problem.  This could be exactly what one advisor works on though so you should look around the department.&lt;/p&gt;&#xA;&lt;p&gt;You should look to see who does applied versus methods work for example, you would want to work with a methods orientated person for that project.  Machine learning is also a vague methods based project topic as well.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-09T15:38:08.407" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4103" PostTypeId="2" ParentId="4091" CreationDate="2021-01-09T21:22:34.133" Score="5" Body="&lt;p&gt;As has been stated in several other answers already, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is only a number, and the population of the states with different &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; depends on the temperature.&lt;/p&gt;&#xA;&lt;p&gt;However, an important point has not yet been mentioned. The quantum harmonic oscillator is often invoked for nuclear motion. It arises from the second-order Taylor expansion of the Born-Oppenheimer nuclear potential energy surface&#xA;&lt;span class=&quot;math-container&quot;&gt;$V({\bf R}) = V({\bf R}_0) + \nabla V|_{{\bf R}={\bf R}_0} \cdot({\bf R}-{\bf R}_0)+\frac 1 2 ({\bf R}-{\bf R}_0)\cdot \nabla\nabla V|_{{\bf R}={\bf R}_0}\cdot ({\bf R}-{\bf R}_0) + \mathcal{O}(|{{\bf R}-{\bf R}_0}|^3)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the first-order term vanishes since &lt;span class=&quot;math-container&quot;&gt;$\nabla V|_{{\bf R}={\bf R}_0} ={\bf 0}$&lt;/span&gt; at the minimum.&lt;/p&gt;&#xA;&lt;p&gt;Since the spatial extent of the states increases with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, the importance of anharmonic effects also grows with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, or with increasing temperature.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-01-09T21:22:34.133" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4104" PostTypeId="2" ParentId="4051" CreationDate="2021-01-10T02:38:49.907" Score="4" Body="&lt;p&gt;Basically, your question is related to the relationship between symmetries and energy bands. In the following, I will give a summary you can refer to and give a &lt;a href=&quot;https://courses.cit.cornell.edu/ece407/Lectures/handout_symmetries.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;course link&lt;/a&gt; to prove them.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Time-reverasl symmetry (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;) implies:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{n,-\chi}(-\vec{k})=E_{n,\chi}(\vec{k}) \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Inversion or parity symmetry (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;) implies:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{n,\chi}(-\vec{k})=E_{n,\chi}(\vec{k}) \tag{2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Then in crystals that have inversion and time-reversal symmetry implies:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{n,-\chi}(\vec{k})=E_{n,\chi}(\vec{k}) \tag{3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the energy quantum number, &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; the crystal momentum, and &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; the spin quantum number. This expression &lt;span class=&quot;math-container&quot;&gt;$(3)$&lt;/span&gt; should answer your question &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-symmetry leading to spin-degenerate band structures&amp;quot;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You may want to know how to derive these conclusions, please take a look at &lt;a href=&quot;https://courses.cit.cornell.edu/ece407/Lectures/handout_symmetries.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;these slides&lt;/a&gt;. (All these conclusions are borrowed from that, in which all the derivations are very pedagogical if you have basic training in solid-state physics.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The paper you cited discussed the change of energy band when considering different symmetry breaking:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(a): &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\checkmark$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\checkmark$&lt;/span&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(b): &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\checkmark$&lt;/span&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(c): &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and the material realization for case (c) with bilayer CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;. And the symmetry analysis of bilayer CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; is also stated in the main manuscript (section: Symmetry of 2D magnetic insulator CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The atomic crystal of CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; exhibits inversion symmetry (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;) with two inversion centers, one inside the monolayer and the other in between neighboring monolayers. The AFM order reduces the crystal symmetry by removing the interlayer inversion center. Therefore, an AFM bilayer breaks the inversion symmetry, although an FM bilayer does not. Another important feature is that the AFM ordered phase preserves &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt; symmetry while it breaks &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; independently; hence, no polarization exists in the ordered phase.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Now I believe you are comfortable about what the author is talking about with (1), (2), and (3).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Disclaimer: The previous answer can not be accepted. Because it doesn't solve the main point: &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; are broken but the combined &lt;span class=&quot;math-container&quot;&gt;$\mathcal{PT}$&lt;/span&gt; is conserved.&lt;/h3&gt;&#xA;&lt;p&gt;I have sent an email to the corresponding author of CrI3 and state the problem with him. I will list the main points below although I can't prove them.&lt;/p&gt;&#xA;&lt;p&gt;#Second email:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;TRS induces Kramers degeneracy, at k that respects TRS (like the Gamma point). This is because T is an anti-unitary operator. In other words, the Kramers theorem applies for any anti-unitary operator.&lt;/li&gt;&#xA;&lt;li&gt;The combined symmetry PT is also anti-unitary, because P is unitary and T is anti-U. Therefore, PT leads to Kramers degeneracy, at k that respect PT. As you know, any k-points respect PT.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;#First email:&lt;/p&gt;&#xA;&lt;p&gt;I assume that you understand the Kramers degeneracy induced by T.&#xA;Because PT is antisymmetric, PT leads to the same Kramers degeneracy at generic k point. Therefore, everywhere is doubly degenerate in the band structure.&lt;/p&gt;&#xA;&lt;p&gt;This is irrelevant to whether P/T is the symmetry of the system.&lt;/p&gt;&#xA;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;&lt;p&gt;=====================================================================&lt;/p&gt;&#xA;&lt;p&gt;A more detailed point-to-point answer after a long time:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is there a rigorous way to look at new material, to say if PT-symmetry would lead to a spin degeneracy? Because from what I've read, and I could totally be wrong, it looks like people do band structure calculations and then attributes such a degeneracy to PT-symmetry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Both the time-reversal operator &lt;span class=&quot;math-container&quot;&gt;$(\mathcal{T})$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{PT}$&lt;/span&gt; operator are anti-unitary operators for spin-half particles and admit the Kramers' degeneracy theorem for the spin (One can find an exact proof for this degeneracy theorem &lt;a href=&quot;https://press.princeton.edu/books/hardcover/9780691151755/topological-insulators-and-topological-superconductors&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this book&lt;/a&gt;: chapter IV)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I do not hold a good theoretical physics footing, so I don't know much about PT symmetry with regard to specific systems, but I do know about the universal CPT symmetry that is preserved. Is one just a subset of the other?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{CPT}$&lt;/span&gt; is a symmetry operator and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{PT}$&lt;/span&gt; is also a symmetry operator, therefore &lt;span class=&quot;math-container&quot;&gt;$\mathcal{PT}$&lt;/span&gt; can not be considered as a subset of &lt;span class=&quot;math-container&quot;&gt;$\mathcal{CPT}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Finally, I am having a hard time trying to understand how the system can break inversion symmetry and time-reversal symmetry but the product of these two symmetry operators is still a 'good' quantum number i.e. one that commutes with the Hamiltonian.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This question can be explained by the following screencast:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vo1m6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vo1m6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2022-04-09T13:14:34.957" LastActivityDate="2022-04-09T13:14:34.957" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4105" PostTypeId="1" AcceptedAnswerId="4118" CreationDate="2021-01-10T08:07:28.263" Score="6" ViewCount="75" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/W6oQL.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/W6oQL.jpg&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&#xA;Why are there solid lines drawn connecting the solid circles after twinning has taken place? Ideally, that explains a real plane, isn't it? But why are we going to get a plane out of nothing if we mechanically twin or a twinning is followed after heat treatment(annealing twins)?&lt;/p&gt;&#xA;" OwnerUserId="1893" LastEditorUserId="1355" LastEditDate="2021-01-10T08:52:05.270" LastActivityDate="2021-01-12T08:33:31.473" Title="Where is this extra plane coming from?" Tags="|condensed-matter|physical-properties-of-materials|materials-engineering|mechanical-properties|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4106" PostTypeId="1" CreationDate="2021-01-10T12:26:13.040" Score="10" ViewCount="1034" Body="&lt;p&gt;I am doing dehydrogenation of a molecule (say &lt;span class=&quot;math-container&quot;&gt;$\ce{C12H12}$&lt;/span&gt;) and I want to do  charge analysis for dehydrogenated  system (&lt;span class=&quot;math-container&quot;&gt;$\ce{C6H6}$&lt;/span&gt;). How I can proceed? I can use Quantum ESPRESSO and Gaussian codes.&#xA;Also, I would be grateful, if you can advice me the physical significance of the charge analysis of a molecule.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-01-11T16:38:13.080" LastActivityDate="2021-01-11T16:38:13.080" Title="How to perform charge analysis for a molecule" Tags="|quantum-espresso|gaussian|charge-transfer|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4107" PostTypeId="1" CreationDate="2021-01-10T18:01:52.293" Score="7" ViewCount="103" Body="&lt;p&gt;I'm trying to run a gas phase cluster calculation in CP2K. I want to create an outside force to constrain water molecules that are in the simulation within a radius of a central ion. I want to create a spherical cell of a given radius , fix the ion in the center and then run QMMD with the waters free to do their motion.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know how to create a spherical cell for the simulation with no periodic boundary conditions or a better way to impose this clustering constraint ?&lt;/p&gt;&#xA;" OwnerUserId="1912" LastActivityDate="2021-01-10T18:01:52.293" Title="CP2K Spherical Cell" Tags="|cp2k|periodic-boundary-conditions|" AnswerCount="0" CommentCount="2" ClosedDate="2021-02-28T20:40:18.960" ContentLicense="CC BY-SA 4.0" />
  <row Id="4108" PostTypeId="2" ParentId="4106" CreationDate="2021-01-10T18:27:32.507" Score="10" Body="&lt;p&gt;This is a very general answer, but let me point you in the right direction at least. If you are looking at a molecular system such as C&lt;sub&gt;6&lt;/sub&gt;H&lt;sub&gt;6&lt;/sub&gt;, you will likely want to use a non-periodic code such as Gaussian. &lt;a href=&quot;https://gaussian.com/population/&quot; rel=&quot;nofollow noreferrer&quot;&gt;This page&lt;/a&gt; describes many different methods of charge analysis and you can use this information to calculate charge transfer complexes and local charges on individual atoms.&lt;/p&gt;&#xA;&lt;p&gt;You should read the literature of your specific field for what method of charge analysis is best, but that will require more information.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="695" LastEditDate="2021-01-11T16:37:06.700" LastActivityDate="2021-01-11T16:37:06.700" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4110" PostTypeId="1" CreationDate="2021-01-11T06:37:00.067" Score="7" ViewCount="66" Body="&lt;p&gt;I was trying to study quantum dots of ZnO. But I'm pretty new to creating and passivating 0-dimensional particles. Is it always necessary to passivate the free surface of the quantum dot? Regarding the studies conducted, I would like to know how ligands affect the electronic properties of the quantum dot. But for that I need a reference hence would prefer the non-passivated state. If such a state can't be achieved how would one approach the problem of creating a reference for comparison.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in Advance :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2021-09-05T22:48:12.640" LastActivityDate="2021-09-05T22:48:12.640" Title="Is it necessary to terminate the surface ions in a quantum dot?" Tags="|density-functional-theory|reference-request|quantum-espresso|surfaces|quantum-dots|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-26T14:43:51.357" ContentLicense="CC BY-SA 4.0" />
  <row Id="4111" PostTypeId="1" AcceptedAnswerId="6867" CreationDate="2021-01-11T08:19:40.147" Score="9" ViewCount="288" Body="&lt;p&gt;I am using the &lt;a href=&quot;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BolzTraP code&lt;/a&gt; [I'm completely new to this code]  to calculate the thermo-electric coefficients as per this &lt;a href=&quot;https://www.youtube.com/watch?v=X8O3tXwTp9Y&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;. And the output file obtained from BoltzTraP is given below.  The column labels and what they stand for are given below :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Ef[Ry]&lt;/strong&gt; : Fermi Energy level&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;T [K]&lt;/strong&gt; : Temperature&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;N&lt;/strong&gt;: Number of Carriers&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;DOS(Ef)&lt;/strong&gt; : Density of States&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;S&lt;/strong&gt;: Seebeck Coefficient&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;s/t&lt;/strong&gt; : conductivity/ electron relaxation time&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;R_H&lt;/strong&gt;: Hall Coefficient&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;kappa0&lt;/strong&gt;: Thermal Conductivity&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;c&lt;/strong&gt;: Electronic Specific Heat&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;chi&lt;/strong&gt;: Pauli Magnetic Susceptibility&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  Ef[Ry]     T [K]            N         DOS(Ef)           S             s/t               R_H        kappa0         c                 chi&#xA; 0.39136    1.0000     14.59160339  0.27749010E+04  0.00000000E+00  0.15404697E+22 -0.16852985E-11 -0.00000000E+00  0.00000000E+00  0.41426895E-07&#xA; 0.39136    2.0000     14.59160339  0.13874505E+04 -0.12814074E-20  0.77023484E+21 -0.33705969E-11  0.10277212E+01  0.65901673E-14  0.20713447E-07&#xA; 0.39136    3.0000     14.59160339  0.92496701E+03 -0.44231269E-15  0.51348989E+21 -0.50558954E-11  0.23649732E+06  0.15165172E-08  0.13808965E-07&#xA; 0.39136    4.0000     14.59160339  0.69372528E+03 -0.23870272E-12  0.38511743E+21 -0.67411938E-11  0.95722814E+08  0.61381369E-06  0.10356724E-07&#xA; 0.39136    5.0000     14.59160340  0.55498083E+03 -0.98897905E-11  0.30809428E+21 -0.84264870E-11  0.31727480E+10  0.20344954E-04  0.82853882E-08&#xA; 0.39136    6.0000     14.59160341  0.46249068E+03 -0.11450615E-09  0.25674891E+21 -0.10111701E-10  0.30612680E+11  0.19630110E-03  0.69045896E-08&#xA; 0.39136    7.0000     14.59160348  0.39645474E+03 -0.64293135E-09  0.22008938E+21 -0.11796403E-10  0.14734045E+12  0.94481076E-03  0.59187295E-08&#xA; 0.39136    8.0000     14.59160376  0.34700703E+03 -0.23031393E-08  0.19263855E+21 -0.13479177E-10  0.46195667E+12  0.29623023E-02  0.51805175E-08&#xA; 0.39136    9.0000     14.59160447  0.30870652E+03 -0.61253650E-08  0.17137573E+21 -0.15156879E-10  0.10928617E+13  0.70082134E-02  0.46087238E-08&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here you can see that the coefficients from column 4 to 10 vary with temperature, for a given Ef or N.&lt;/p&gt;&#xA;&lt;p&gt;I've got the &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;ved=2ahUKEwjR_8uSrZPuAhUhyjgGHUuECHMQFjAAegQIAhAC&amp;amp;url=https%3A%2F%2Fwww.researchgate.net%2Fprofile%2FHilal_Balout%2Fpublication%2F325455856_BoltzTraP_Tools_UserGuide%2Fdata%2F5b0f22bb4585157f8724711d%2FUserGuide.pdf&amp;amp;usg=AOvVaw1GV3nf9Q7feHr1ZINvPGto&quot; rel=&quot;nofollow noreferrer&quot;&gt;BoltzTraP user guide&lt;/a&gt; but it doesn't mention as to which energy I should study the variation at. Should it be analysed at the Fermi Level which is obtained during the SCF calculation? or at the experimentally determined carrier concentration?&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2021-09-05T22:49:12.820" LastActivityDate="2021-10-10T00:50:44.590" Title="Which energy should I consider while trying to analyse the variation in transport coefficients with temperature?" Tags="|density-functional-theory|transport|boltztrap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4112" PostTypeId="2" ParentId="4106" CreationDate="2021-01-11T11:51:09.157" Score="8" Body="&lt;p&gt;Complementing the answer by @Tristan, in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1439/24&quot;&gt;question&lt;/a&gt; you will find the several methods used to determine the atomic charges.&lt;/p&gt;&#xA;&lt;p&gt;Also, you can use Gaussian to calculate/export the wavefunction and them use &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn&lt;/a&gt; package to estimate the system charges using several approaches:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Population analysis. Hirshfeld, Hirshfeld-I, VDD, Mulliken, Löwdin,&#xA;Modified Mulliken (including three methods: SCPA, Stout &amp;amp; Politzer,&#xA;Bickelhaupt), Becke, ADCH (Atomic dipole moment corrected Hirshfeld),&#xA;CM5, CHELPG, Merz-Kollmann, RESP (Restrained ElectroStatic&#xA;Potential), RESP2, AIM (Atoms-In-Molecules), EEM (Electronegativity&#xA;Equalization Method) and PEOE (Gasteiger) are supported.&#xA;Electrostatic interaction energy of two given fragments can be&#xA;calculated based on atomic charges.&lt;/li&gt;&#xA;&lt;li&gt;Orbital composition analysis. Mulliken, Stout &amp;amp; Politzer, SCPA, Hirshfeld, Hirshfeld-I, Becke, natural atomic orbital (NAO) and AIM methods are supported to obtain orbital composition. Orbital delocalization index (ODI) can be outputted to quantify extent of spatial delocalization of orbitals.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-11T11:51:09.157" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4113" PostTypeId="1" AcceptedAnswerId="4116" CreationDate="2021-01-11T13:50:34.467" Score="7" ViewCount="97" Body="&lt;p&gt;I'm trying to figure out for myself the necessity of high-accuracy compound methods for energy like W1 or Gn families. I'm learning computational chemistry by myself and sometimes lack systematical approach. As far as I understand they are used for high-end kinetics calculations of small molecules.&lt;/p&gt;&#xA;&lt;p&gt;So, is there a sense to use the more or less &amp;quot;regular&amp;quot; (not focusing on quantitatively modeling complex mechanisms) mechanistic calculations  on large organic molecules (~100 atoms) or something like MP2 with large basis set or high-level DFT functional will be more appropriate?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-01-11T23:22:25.663" LastActivityDate="2021-01-11T23:29:40.893" Title="High accuracy energy methods, are they worth it?" Tags="|thermodynamics|high-precision|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4114" PostTypeId="1" AcceptedAnswerId="4125" CreationDate="2021-01-11T15:55:01.113" Score="15" ViewCount="1092" Body="&lt;p&gt;Currently I'm using some software package to do the data analysis from the DFT calculation so that I can study the surface state of some topological insulator. I found that the method they use is called surface green function method. After obtaining the tight binding matrix of the system, in principle we can use it to do the surface state calculation to produce the ARPES result. I want to know the algorithm of this, but I can only find limited resource on internet. Is there any recommended source on this topic ?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-01-11T23:31:34.217" LastActivityDate="2021-01-13T20:38:01.267" Title="About the surface Greens function method for calculating the surface state" Tags="|density-functional-theory|reference-request|band-structure|topological-insulators|greens-functions|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4115" PostTypeId="1" CreationDate="2021-01-11T21:13:34.443" Score="8" ViewCount="343" Body="&lt;p&gt;I have a substrate that has a Br-C bond. In CHARRM the line below is included in the &lt;code&gt;.str&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;LONEPAIR COLI LP1    BR     C9     DIST 1.8900 SCAL 0.0&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have also included coordinates for the lone pair in the &lt;code&gt;.pdb&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ATOM     67  LP1 LIG     1       0.871  -0.147  -3.939  1.00  0.00      SUB&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I was able to solvate, minimize, and run dynamics on  the system. However, the lone pair does not move with the substrate, and the coordinates are not updated afterwards. This results in the lone pair being 4.5+ Å away from the bromine.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is if this is normal, or is there something additional I need to include?&lt;/strong&gt; Please let me know if any additional details would be useful. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="510" LastEditorUserId="5" LastEditDate="2021-09-05T22:51:31.537" LastActivityDate="2021-09-05T22:51:31.537" Title="Lone pairs in CHARMM for molecular dynamics" Tags="|molecular-dynamics|charmm|" AnswerCount="0" CommentCount="6" ClosedDate="2021-09-05T23:11:04.480" ContentLicense="CC BY-SA 4.0" />
  <row Id="4116" PostTypeId="2" ParentId="4113" CreationDate="2021-01-11T23:29:40.893" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;High accuracy energy methods, are they worth it?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They are absolutely worth it for many types of studies, but not worth it for other types of studies. It depends on precisely what the aim of your project is.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As far as I understand they are used for high-end kinetics calculations of small molecules.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They are also used for &lt;em&gt;&lt;strong&gt;spectroscopy&lt;/strong&gt;&lt;/em&gt;, &lt;em&gt;&lt;strong&gt;benchmarking&lt;/strong&gt;&lt;/em&gt; and for &lt;em&gt;&lt;strong&gt;fundamental science.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.87.052505&quot; rel=&quot;noreferrer&quot;&gt;this paper of mine&lt;/a&gt; the molecule was able to be &lt;em&gt;&lt;strong&gt;made&lt;/strong&gt;&lt;/em&gt; thanks to high-precision predictions. The molecule was made by photoassociation (using a photon to associate two atoms into a molecule), for which the frequency of the photons have to be exactly equal to the energy difference between the bound molecular state and the unbound atomic states, and it wouldn't have been possible without ultra-high-precision &lt;strong&gt;predictions&lt;/strong&gt; of this energy difference.&lt;/p&gt;&#xA;&lt;p&gt;Our &lt;a href=&quot;/questions/tagged/high-precision&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;high-precision&amp;#39;&quot; rel=&quot;tag&quot;&gt;high-precision&lt;/a&gt; tag here is starting to accumulate quite the collection of interesting questions, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/554/5&quot;&gt;How accurate are the most accurate calculations?&lt;/a&gt; (here the high accuracy &lt;em&gt;ab initio&lt;/em&gt; calculations are sometimes &lt;em&gt;more&lt;/em&gt; accurate than the best experiments, and you can see &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/554/how-accurate-are-the-most-accurate-calculations#comment4240_555&quot;&gt;this comment chain&lt;/a&gt; if you have questions about precision vs accuracy here).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2306/5&quot;&gt;High precision helium energy&lt;/a&gt; (here the high accuracy calculations are helpful as a benchmark, and in testing/developing novel numerical methods).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3889/5&quot;&gt;Are there examples of ab initio predictions on small molecules without the &amp;quot;major approximations&amp;quot;?&lt;/a&gt; (here we can learn some fundamental science about how the Born-Oppenheimer approximation breaks down for very light nuclei and when the precision is very high).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;on large organic molecules (~100 atoms) or something like MP2 with large basis set or high-level DFT functional will be more appropriate?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Depending on what you want to do, you might even want high-precision energies for your 100-atom system, but it won't be possible to go much further than MP2 for such a large system. &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00511&quot; rel=&quot;noreferrer&quot;&gt;It has been possible to do CCSD(T) on 1000 atoms&lt;/a&gt;, but it was a very expensive calculation and was only done in a TZ basis set, which means that the composite methods that you mentioned such as the W family and the Gn family, will be limited in how much they can offer; and the accuracy you gain from going from MP2 to CCSD(T) may not be so valuable when there's still so much basis set error anyways.&lt;/p&gt;&#xA;&lt;p&gt;If you are working on a 100-atom organic system, I would suggest MP2 or a DFT functional that is decent for that type of system, and to use a TZ basis set. Alternatively you can go up to CCSD or CCSD(T) if accuracy is more important to you, and you're willing to wait a few days on a supercomputer for each energy calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;It depends very much on what the aim of your project is.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-01-11T23:29:40.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4117" PostTypeId="2" ParentId="4114" CreationDate="2021-01-12T07:01:43.000" Score="6" Body="&lt;p&gt;You can see the open-source package WannierTools:&#xA;&lt;a href=&quot;https://github.com/quanshengwu/wannier_tools&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/quanshengwu/wannier_tools&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A brief description:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We present an open-source software package WannierTools, a software for the investigation of novel topological materials. This code works in the tight-binding framework, which can be generated by another software package Wannier90. It can help to classify the topological phase of a given material by calculating the Wilson loop and can get the surface state spectrum which is detected by angle-resolved photoemission (ARPES) and in scanning tunneling microscopy (STM) experiments. It also identifies positions of Weyl/Dirac points and nodal line structures, calculates the Berry phase around a closed momentum loop and Berry curvature in a part of the Brillouin zone(BZ). Besides, WannierTools also can calculate ordinary magnetoresistance for non-magnetic metal and semimetal using Boltzmann transport theory, calculate Landau level spectrum with given magnetic field direction and strength and get unfolded energy spectrum from a supercell calculation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-12T07:01:43.000" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4118" PostTypeId="2" ParentId="4105" CreationDate="2021-01-12T08:33:31.473" Score="5" Body="&lt;p&gt;solid circles represent the positions of atoms in the twinned region; these black circles represents the only atoms that are present there, whereas dashed circles are their original positions that after twinning are no more occupied on account of displacement.&lt;/p&gt;&#xA;&lt;p&gt;These black atoms are displaced from their original positions on account of twinning and hence form novel planes that are not found in the untwinned regions.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2021-01-12T08:33:31.473" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4120" PostTypeId="1" CreationDate="2021-01-12T14:40:44.063" Score="7" ViewCount="87" Body="&lt;p&gt;I would like to calculate the thermal transport coefficients like Thermal Conductivity, Seebeck coefficient etc for thermoelectric 0 D systems (quantum dots, &lt;a href=&quot;https://en.wikipedia.org/wiki/Nanoclusters&quot; rel=&quot;nofollow noreferrer&quot;&gt;nanoclusters&lt;/a&gt; ..etc).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For bulk materials, there is a package called &lt;a href=&quot;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BoltzTraP&lt;/a&gt; that uses&#xA;the output of Quantum ESPRESSO to calculate these coefficients.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Is there any such package (preferably open-source) that calculates such properties for 0 D systems?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2021-01-13T10:15:12.693" LastActivityDate="2021-01-21T13:52:28.947" Title="How to calculate Transport coeffiecients for 0 D systems?" Tags="|software|reference-request|nanoparticles|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4121" PostTypeId="2" ParentId="2077" CreationDate="2021-01-12T14:46:07.087" Score="4" Body="&lt;p&gt;Aren't you missing the volume in the denominator? And the order of the norm and average is probably off in the second term.&#xA;The original equation should be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon = 1 + &#xA;\frac{\langle |\mathbf{M}|^2\rangle -  |\langle\mathbf{M}\rangle|^2}&#xA;{3\epsilon_0 V k_B T}&#xA;$$&lt;/span&gt;&#xA;and in units where coulombs constant is one,&#xA;&lt;span class=&quot;math-container&quot;&gt;$k = 1 = (4\pi\epsilon_0)^{-1}$&lt;/span&gt;, you get &lt;span class=&quot;math-container&quot;&gt;$1/\epsilon_0 = 4\pi$&lt;/span&gt; as in your equation. (Also I'm not sure why the term &lt;span class=&quot;math-container&quot;&gt;$|\langle\mathbf{M}\rangle|^2$&lt;/span&gt; is there at all. The whole expression seem to be the trace of a dielectric tensor assuming rotational symmetry, and under rotational symmetry &lt;span class=&quot;math-container&quot;&gt;$\langle\mathbf{M}\rangle=0$&lt;/span&gt;. Maybe I'm misstaken or some else can comment on that. Including it could be a better approximation for finite times.)&lt;/p&gt;&#xA;&lt;p&gt;If the molecules are broken due to wrapping the coordinates, that could be a problem! You should check that, and &amp;quot;heal&amp;quot; them it if is the case. Alternatively you can probably turn off the coordinate wrapping in Lammps.&lt;/p&gt;&#xA;&lt;p&gt;Since the molecules are neutral, the total dipole moment is the sum of the molecular dipole moments and therefor independent of wrapping (as long a you don't break the molecules) and can be calculated with your second formula where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; runs over all atoms. Since the dipole of an uncharged system is independent of the origin &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt; can just be the position vector. So if &lt;code&gt;R&lt;/code&gt; is your Nx3 numpy-array of positions and &lt;code&gt;q&lt;/code&gt; the numpy-array of charges, you get your system dipole vector &lt;code&gt;M&lt;/code&gt; like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;M = 0&#xA;for i in range(len(R)):&#xA;  M += q[i] * R[i]  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or why not&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;M = q @ R&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which should come out in units of &lt;code&gt;eÅ&lt;/code&gt; assuming charges in units of electrons and distances in units of Ångstrom.&lt;/p&gt;&#xA;" OwnerUserId="1913" LastEditorUserId="1913" LastEditDate="2023-09-25T15:22:54.607" LastActivityDate="2023-09-25T15:22:54.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4123" PostTypeId="1" CreationDate="2021-01-13T08:55:10.703" Score="8" ViewCount="2675" Body="&lt;p&gt;Specifically, I am interested in the time-reversal symmetry &lt;span class=&quot;math-container&quot;&gt;$(\mathcal{T})$&lt;/span&gt; in quantum mechanics. The &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; is considered as an anti-unitary operator, namely:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{T}\psi(\vec{r},t)=\psi^*(\vec{r},-t)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;One of the most important properties related to &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kramers_theorem&quot; rel=&quot;noreferrer&quot;&gt;Kramers' degeneracy&lt;/a&gt;. I have known the external magnetic will break this symmetry. However, are there any conditions that will break explicitly the &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry? Such as the intrinsic magnetic ordering (AFM/FM) and spin-orbit coupling &lt;span class=&quot;math-container&quot;&gt;$et.all$&lt;/span&gt;? Any good tutorials and suggestions are welcome.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-15T03:28:05.250" Title="What will break the time-reversal symmetry?" Tags="|symmetry|quantum-mechanics|solid-state-physics|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4124" PostTypeId="1" AcceptedAnswerId="4128" CreationDate="2021-01-13T10:24:43.427" Score="6" ViewCount="137" Body="&lt;p&gt;I'm using Exciting Code to calculate some electronic band structures.  Starting with the &lt;a href=&quot;http://exciting-code.org/carbon-electronic-bandstructure-from-gw&quot; rel=&quot;nofollow noreferrer&quot;&gt;example of Si&lt;/a&gt; I get sensible output and can plot BAND.OUT and BAND-QP.OUT using PLOT-gwbands.py or directly in any plotting software (using BANDLINES.OUT to label the critical points).&lt;/p&gt;&#xA;&lt;p&gt;Looking in BAND.OUT, the x coordinate is rather puzzling.  I know it comes from the distance along the path W-L-Γ-X-W-K as specified in input.xml, but I can't get to the numbers in BANDLINES.OUT (the positions of the specified high-symmetry points) from first principles.&lt;/p&gt;&#xA;&lt;p&gt;From input.xml we have:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;lt;point coord=&amp;quot; 0.750   0.500   0.250&amp;quot; label=&amp;quot;W&amp;quot;/&amp;gt;&#xA;&amp;lt;point coord=&amp;quot; 0.500   0.500   0.500&amp;quot; label=&amp;quot;L&amp;quot;/&amp;gt;&#xA;&amp;lt;point coord=&amp;quot; 0.000   0.000   0.000&amp;quot; label=&amp;quot;GAMMA&amp;quot;/&amp;gt;&#xA;&amp;lt;point coord=&amp;quot; 0.500   0.500   0.000&amp;quot; label=&amp;quot;X&amp;quot;/&amp;gt;&#xA;&amp;lt;point coord=&amp;quot; 0.750   0.500   0.250&amp;quot; label=&amp;quot;W&amp;quot;/&amp;gt;&#xA;&amp;lt;point coord=&amp;quot; 0.750   0.375   0.375&amp;quot; label=&amp;quot;K&amp;quot;/&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I calculate the length of each segment by &lt;span class=&quot;math-container&quot;&gt;$\sqrt((h2-h1)^2+(k2-k1)^2+(l2-l1)^2)$&lt;/span&gt; and compare to BANDLINES.OUT:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Segment&lt;/th&gt;&#xA;&lt;th&gt;distance (BANDLINES.OUT)&lt;/th&gt;&#xA;&lt;th&gt;distance (between  coordinates)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;W-L&lt;/td&gt;&#xA;&lt;td&gt;0.4330295261&lt;/td&gt;&#xA;&lt;td&gt;0.353553390593274&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;L-Γ&lt;/td&gt;&#xA;&lt;td&gt;0.9633802174&lt;/td&gt;&#xA;&lt;td&gt;1.21957879437771&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Γ-X&lt;/td&gt;&#xA;&lt;td&gt;1.575776446&lt;/td&gt;&#xA;&lt;td&gt;1.92668557556426&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;X-W&lt;/td&gt;&#xA;&lt;td&gt;1.881974561&lt;/td&gt;&#xA;&lt;td&gt;2.28023896615753&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;W-K&lt;/td&gt;&#xA;&lt;td&gt;2.098489324&lt;/td&gt;&#xA;&lt;td&gt;2.45701566145417&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;I get a non-constant difference - the first row differs by a factor of about 0.82, the other rows by 1.17--1.27 (not close enough for rounding error)&lt;/p&gt;&#xA;&lt;p&gt;I've tried looking at the source (and am still trying) but as an experimentalist who has never done any Fortran, progress is very slow, so hopefully someone just knows.&lt;/p&gt;&#xA;" OwnerUserId="1921" LastEditorUserId="5" LastEditDate="2021-01-13T16:06:03.447" LastActivityDate="2021-01-14T11:12:16.957" Title="Band structure output from Exciting - what are the X units?" Tags="|software|band-structure|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4125" PostTypeId="2" ParentId="4114" CreationDate="2021-01-13T18:59:06.933" Score="11" Body="&lt;p&gt;The surface Green's function method is described in detail &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0305-4608/15/4/009/pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, but here is a summary.&lt;/p&gt;&#xA;&lt;h3&gt;Principal Layers:  Block Tridiagonal Form&lt;/h3&gt;&#xA;&lt;p&gt;We consider a semi-infinite system (a surface with an infinite bulk below it) and we split it into so-called &lt;em&gt;principal layers&lt;/em&gt;. A principal layer is a collection of atomic layers such that each principal layer &lt;em&gt;only interacts with nearest neighboring principal layers&lt;/em&gt;. The point of this being, the Hamiltonian takes the block tridiagonal form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{1}H = \begin{pmatrix}&#xA;H_{00} &amp;amp; V &amp;amp;  &amp;amp;  &amp;amp;   &amp;amp; &amp;amp; \\&#xA;V^\dagger &amp;amp; H_{11} &amp;amp; V &amp;amp;  &amp;amp;  &amp;amp; &amp;amp; \\&#xA; &amp;amp; V^\dagger &amp;amp; H_{22} &amp;amp; V &amp;amp; &amp;amp; \\&#xA;&amp;amp; &amp;amp; V^\dagger &amp;amp; \ddots &#xA;\end{pmatrix} $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; describes the interaction between principal layers, &lt;span class=&quot;math-container&quot;&gt;$H_{00}$&lt;/span&gt; describes interactions within the surface principal layer, and &lt;span class=&quot;math-container&quot;&gt;$H_{11}=H_{22}=H_{33}=\dots$&lt;/span&gt; describes interactions within bulk principal layers. For simplicity I have assumed all bulk principal layers are identical and all &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;'s are the same (valid for a perfect crystal).&lt;/p&gt;&#xA;&lt;h3&gt;Surface Green's Function + Recursion Relations&lt;/h3&gt;&#xA;&lt;p&gt;With this block form of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; in mind, we now turn to the Green's function / resolvent defined by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ G(\omega) = (\omega - H)^{-1} $$&lt;/span&gt;&#xA;And in particular, we look at the top-left element &lt;span class=&quot;math-container&quot;&gt;$G_{00}(\omega) = (\omega - H)^{-1}_{00}$&lt;/span&gt;. This defines the &lt;em&gt;surface Green's function&lt;/em&gt; and it contains the spectral information about the surface. To calculate it, we will take advantage of the block tridiagonal form of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; to derive recursion relations. By definition of &lt;span class=&quot;math-container&quot;&gt;$G(\omega)$&lt;/span&gt;, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align*} &#xA;(\omega - H) G(\omega) &amp;amp;= 1 \tag{2}\\&#xA;\sum_k(\omega \delta_{ik} - H_{ik}) G_{kj}&amp;amp;= \delta_{ij} \tag{3}\\&#xA;\end{align*}&lt;/span&gt;&#xA;This is the central equation we will use. From it, we can use the form of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; to extract the following two equations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\left( \omega - H_{00}   \right)G_{00} &amp;amp;= 1 + V G_{10} \tag{4}\\&#xA;\left( \omega - H_{nn} \right)G_{n0} &amp;amp;= V^\dagger G_{n-1,0} +  V G_{n+1,0}\tag{5}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;The Algorithm&lt;/h3&gt;&#xA;&lt;p&gt;We can now use the above two equations to derive an iterative scheme for arriving at &lt;span class=&quot;math-container&quot;&gt;$G_{00}$&lt;/span&gt;. Use the second equation for &lt;span class=&quot;math-container&quot;&gt;$G_{10}$&lt;/span&gt; and plug it into the first. Also use the second equation on itself for &lt;span class=&quot;math-container&quot;&gt;$G_{n-1,0}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$G_{n+1,0}$&lt;/span&gt; on the right. Group terms so that we can write the &lt;em&gt;renormalized&lt;/em&gt; equations&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\left( \omega - \varepsilon^S_1   \right)G_{00} &amp;amp;= 1 + \alpha_1 G_{20} \tag{6}\\&#xA;\left( \omega - \varepsilon_1 \right)G_{n0} &amp;amp;= \beta_1 G_{n-2,0} +  \alpha_1G_{n+2,0}\tag{7}&#xA;\end{align}&lt;/span&gt;&#xA;where we have grouped factors into the new blocks &lt;span class=&quot;math-container&quot;&gt;$\alpha_1, \beta_1, \varepsilon_1, $&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon^S_1$&lt;/span&gt;. Now repeat. Use the new second equation to plug in to the first new equation along with its own RHS. Continuing this way, after &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; iterations, we have&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\left( \omega - \varepsilon^S_m   \right)G_{00} &amp;amp;= 1 + \alpha_m G_{2^m0} \tag{8}\\&#xA;\left( \omega - \varepsilon_m \right)G_{n0} &amp;amp;= \beta_m G_{n-2^m,0} +  \alpha_mG_{n+2^m,0}\tag{9}&#xA;\end{align}&lt;/span&gt;&#xA;where at each iteration we obtain new &lt;em&gt;renormalized&lt;/em&gt; parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha,\beta,\varepsilon$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon^S$&lt;/span&gt;. Eventually, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; becomes very small so that the first equation becomes&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \left( \omega - \varepsilon^S_m   \right)G_{00} \approx 1  \tag{10}$$&lt;/span&gt;&#xA;and so we obtain the surface Green's function as &lt;span class=&quot;math-container&quot;&gt;$G_{00}(\omega) = (\omega - \varepsilon^S_m)^{-1}$&lt;/span&gt;&#xA;Then the spectral function gives us the surface state spectrum as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \rho_{00}(\omega) = -\frac{1}{\pi}\text{tr}\Im G_{00}(\omega + i0^+) \tag{11}.$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1687" LastEditorUserId="5" LastEditDate="2021-01-13T20:38:01.267" LastActivityDate="2021-01-13T20:38:01.267" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4126" PostTypeId="2" ParentId="4033" CreationDate="2021-01-13T22:58:37.157" Score="5" Body="&lt;p&gt;A Weyl point does indeed have linear dispersion. The effective mass tensor you are using &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{m^*_{ij}}\propto\frac{\partial^2\varepsilon(k)}{\partial k_i \partial k_j}$&lt;/span&gt; is not really well-defined here. After all, we only define the effective mass that way to match the common non-relativistic equation &lt;span class=&quot;math-container&quot;&gt;$\varepsilon = \frac{\hbar^2 k^2}{2m^*}$&lt;/span&gt;. A Weyl point is in no sense described by such an equation since its low-energy effective Hamiltonian is relativistic. Specifically, the effective Hamiltonian is a generalization of the Weyl Hamiltonian from high energy physics. This generalized form is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{1}H(k) = (a_\mu\cdot k)\sigma^\mu  $$&lt;/span&gt;&#xA;(more on this in the next section). The ordinary Weyl equation from high energy physics is given by the special case &lt;span class=&quot;math-container&quot;&gt;$H_{weyl}=k\cdot \sigma$&lt;/span&gt;. This describes massless chiral fermions as described in many other places.&lt;/p&gt;&#xA;&lt;h3&gt;General Weyl Point Dispersion&lt;/h3&gt;&#xA;&lt;p&gt;Now I will sketch the derivation of the general Weyl point dispersion (both Type-I and Type-II). In general, a Weyl point is an isolated linear crossing of two bands. In the vicinity of that crossing, we can focus on just those two bands which are described by a two-band Hamiltonian which is generally of the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}H(k) = h_\mu(k)\sigma^\mu =  h_0(k) \sigma^0 + h_x(k) \sigma^x + h_y(k)\sigma^y + h_z(k)\sigma^z$$&lt;/span&gt;&#xA;Taking the degenerate point to be at &lt;span class=&quot;math-container&quot;&gt;$k=0$&lt;/span&gt; and at &lt;span class=&quot;math-container&quot;&gt;$\varepsilon=0$&lt;/span&gt;, we can expand the functions &lt;span class=&quot;math-container&quot;&gt;$h_\mu$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$h_\mu(k) = \nabla_k h_\mu\big|_0 \cdot k + \dots$&lt;/span&gt;&#xA;so that the effective Hamiltonian at the Weyl point is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ H(k) =  (a_\mu\cdot k)\sigma^\mu $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$a_\mu = \nabla_k h_\mu\big|_0$&lt;/span&gt; are model-dependent vector parameters. This can be diagonalized to arrive at the general Weyl point dispersion relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{3}\varepsilon_\pm(k) = a_0\cdot k \pm \sqrt{(a_x\cdot k)^2 + (a_y\cdot k)^2 + (a_z\cdot k)^2}$$&lt;/span&gt;&#xA;Depending on &lt;span class=&quot;math-container&quot;&gt;$a_0$&lt;/span&gt;, this can be either a Type-I or Type-II Weyl point.&lt;/p&gt;&#xA;&lt;h3&gt;Multi-Weyl points&lt;/h3&gt;&#xA;&lt;p&gt;As a final note, I just want to mention that there are also so-called &lt;em&gt;multi-Weyl&lt;/em&gt; points which have non-linear dispersion and have higher chiralities. More about them &lt;a href=&quot;https://arxiv.org/abs/1111.7309&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1687" LastActivityDate="2021-01-13T22:58:37.157" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4127" PostTypeId="1" AcceptedAnswerId="4132" CreationDate="2021-01-14T05:33:08.617" Score="9" ViewCount="542" Body="&lt;p&gt;I am running a simple energy calculation on a conformer of 3-Sulfopropyl methacrylate, which is given my &lt;code&gt;C=C(C)C(=O)OCCCS(=O)(=O)[O-]&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is my workflow:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Generate conformers using genetic algorithm in OpenBabel&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel -:&amp;quot;C=C(C)C(=O)OCCCS(=O)(=O)[O-]&amp;quot; -O SPMA.pdb --gen3D -d&#xA;obabel SPMA.pdb -O SPMA_op.xyz --conformer --nconf 300 --score rmsd --writeconformers&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Extract coordinates of conformer, and put them in psi4 input file given by:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;memory 8 GB&#xA;molecule MA0 {&#xA;0 1&#xA;  C          3.89733        0.15289       -1.35762&#xA;  C          4.59280        1.05052       -0.63907&#xA;  C          5.20105        2.27534       -1.24308&#xA;  C          4.74095        0.79591        0.82319&#xA;  O          5.01564        1.66100        1.64197&#xA;  O          4.54800       -0.52000        1.09100&#xA;  C          5.28200       -1.03600        2.21300&#xA;  C          6.78400       -0.89700        2.00000&#xA;  C          7.24307       -1.67225        0.77007&#xA;  S          6.44265       -1.12891       -0.72122&#xA;  O          6.80895        0.28345       -0.80582&#xA;  O          7.02056       -1.98627       -1.75252&#xA;  O          5.02989       -1.37699       -0.43672&#xA;  H          3.77090        0.29082       -2.37251&#xA;  H          3.48966       -0.67439       -0.89456&#xA;  H          4.99668        2.29431       -2.29321&#xA;  H          6.25936        2.26265       -1.08586&#xA;  H          4.78246        3.14570       -0.78247&#xA;  H          5.04197       -2.07085        2.34094&#xA;  H          5.00988       -0.47515        3.08265&#xA;  H          7.29461       -1.27505        2.86096&#xA;  H          7.00956        0.13820        1.85038&#xA;  H          7.02443       -2.70921        0.91770&#xA;  H          8.29303       -1.50198        0.65390&#xA;  H          7.75698        0.36077       -0.99601&#xA;  H          7.95459       -1.75656       -1.87793&#xA;}&#xA;&#xA;set {&#xA;  scf_type          = df&#xA;  freeze_core       = true&#xA; &#xA;}&#xA;E, wfn = energy('HF-3c', return_wfn=True)&#xA;&#xA;oeprop(wfn, 'DIPOLE', 'QUADRUPOLE', 'MULTIPOLE(4)', 'MO_EXTENTS', 'MULLIKEN_CHARGES', 'LOWDIN_CHARGES', 'WIBERG_LOWDIN_INDICES', 'MAYER_INDICES', 'NO_OCCUPATIONS', title='Methacrylic acid (MA0)')&#xA;&#xA;print_variables()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Now I run psi4 on this file:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;code&gt;psi4 -n 2 -i SPMA_conf.in -o SPMA.out&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I run this, however, I get a wall of error messages.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Printing out the relevant lines from the Psithon --&amp;gt; Python processed input file:&#xA;      H          7.00956        0.13820        1.85038&#xA;      H          7.02443       -2.70921        0.91770&#xA;      H          8.29303       -1.50198        0.65390&#xA;      H          7.75698        0.36077       -0.99601&#xA;      H          7.95459       -1.75656       -1.87793&#xA;--&amp;gt; &amp;quot;&amp;quot;&amp;quot;,&amp;quot;MA0&amp;quot;)&#xA;    core.IO.set_default_namespace(&amp;quot;MA0&amp;quot;)&#xA;    core.set_global_option(&amp;quot;SCF_TYPE&amp;quot;, &amp;quot;df&amp;quot;)&#xA;    core.set_global_option(&amp;quot;FREEZE_CORE&amp;quot;, &amp;quot;true&amp;quot;)&#xA;    E, wfn = energy('HF-3c', return_wfn=True)&#xA;    oeprop(wfn, 'DIPOLE', 'QUADRUPOLE', 'MULTIPOLE(4)', 'MO_EXTENTS', 'MULLIKEN_CHARGES', 'LOWDIN_CHARGES', 'WIBERG_LOWDIN_INDICES', 'MAYER_INDICES', 'NO_OCCUPATIONS', title='Methacrylic acid (MA0)')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This seems to be the relevant portion of the error message...&lt;/p&gt;&#xA;&lt;p&gt;I have run the very same process on other conformers of other non-charged molecules, but I have not run into this problem. Is it because 3-Sulfopropyl methacrylate is charged?&lt;/p&gt;&#xA;&lt;p&gt;A similar problem arises when I run another charged molecule, like &lt;code&gt;C=C(C)C(=O)OCC[N+](C)(C)C&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can I fix this problem? Any advice you have would be appreciated!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2021-01-14T06:41:23.777" LastActivityDate="2021-01-14T20:06:19.763" Title="Error running psi4 on charged molecules" Tags="|computational-chemistry|quantum-chemistry|psi4|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4128" PostTypeId="2" ParentId="4124" CreationDate="2021-01-14T11:12:16.957" Score="3" Body="&lt;p&gt;The units are only part of the question, as it turns out. First though, I'll work out the unit conversion.&lt;/p&gt;&#xA;&lt;p&gt;By knowing the coordinates of the L point in reciprocal space are (0.5, 0.5, 0.5) we know its distance from Γ to be &lt;span class=&quot;math-container&quot;&gt;$\sqrt(0.5^2+0.5^2+0.5^2)$&lt;/span&gt; multiplied by a conversion factor.  This conversion factor must take into account the lattice constant &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, to account for the difference between diamond and silicon, and given that &lt;a href=&quot;http://exciting-code.org/atomic-units&quot; rel=&quot;nofollow noreferrer&quot;&gt;Exciting uses  atomic units&lt;/a&gt; with lengths in Bohr radii (&lt;span class=&quot;math-container&quot;&gt;$a_0 = 0.529~Å$&lt;/span&gt;) that factor should appear too. There's also a factor of &lt;span class=&quot;math-container&quot;&gt;$2 \pi$&lt;/span&gt;, which is omitted from some notations.&lt;/p&gt;&#xA;&lt;p&gt;The x scale is the distance along a series of straight lines between the points specified.  The difference between L and Γ is 0.53 x units, which means a scale factor of &lt;span class=&quot;math-container&quot;&gt;${\frac{2\pi}{(a / a_0)}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The further complication&lt;/em&gt; is that while &lt;code&gt;input.xml&lt;/code&gt;  uses a Wigner-Seitz primitive basis in which X is at (0.5,0.5,0), the output uses a conventional basis with X at  (0,1,0).  For interpreting the data, this means that you can't copy the coordinates of the critical points from &lt;code&gt;input.xml&lt;/code&gt;.  You need to change the basis.  A comparison, for the cubic structure I'm interested in, is &lt;a href=&quot;https://www.cryst.ehu.es/cgi-bin/cryst/programs/nph-kv-list?gnum=225&amp;amp;what=data&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.  That's enough to use the output, using the distances between points expressed in the conventional basis (&lt;code&gt;BANDLINES.OUT&lt;/code&gt; contains the cumulative distance along the 3d polyline). Note that I chose L for the calculation above, as it has the same coordinates in both bases.&lt;/p&gt;&#xA;&lt;p&gt;I've never written Fortran, or even tried to read it until now. Without trying to add debug output to the source, I think I know what happens: &lt;code&gt;initlattice.f90&lt;/code&gt; seems to call a vector-matrix multiplication (&lt;code&gt;r3mv.f90&lt;/code&gt;) on the atom coordinates and the (inverse of the) &lt;code&gt;basevect&lt;/code&gt; input.  That this process happens isn't obvious from the doucmentation; though &lt;a href=&quot;http://exciting-code.org/boron-how-to-start-an-exciting-calculation&quot; rel=&quot;nofollow noreferrer&quot;&gt;How to Start an exciting Calculation &lt;/a&gt; tells us about the input basis used. It says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The element crystal is used for defining the Bravais lattice of the studied system. It contains three lattice vectors (each specified by an element basevect) in units of the attribute scale that is given in Bohr. The element species describes the chemical composition of the studied system. Atomic coordinates are specified by the element atom. The primitive unit cell of diamond contains two carbon atoms, and their positions are given in the basis of the lattice vectors (lattice coordinates).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1921" LastActivityDate="2021-01-14T11:12:16.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4130" PostTypeId="1" AcceptedAnswerId="4137" CreationDate="2021-01-14T16:08:13.887" Score="5" ViewCount="4346" Body="&lt;p&gt;Somewhere I came across this phrase:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;expected diffraction angle for first order reflection.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;With respect to XRD do I take this as a rule of thumb that the diffraction will always be a first order one? I will quote some relatable lines:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The Bragg equation can be used for determining the lattice parameters of cubic crystals. Let us first consider the value that n should be assigned. A second order reflection from (100) planes should satisfy the following Bragg equation. &lt;span class=&quot;math-container&quot;&gt;$2\lambda=2d_{110}\sinθ$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\lambda=d_{100}\sin \theta$&lt;/span&gt;. Similarly a first order reflection from (200) planes should satisfy the following condition &lt;span class=&quot;math-container&quot;&gt;$\lambda=2d_{200}\sin \theta $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What do I consider the value of n as when this is given to me?&lt;/p&gt;&#xA;" OwnerUserId="1893" LastEditorUserId="5" LastEditDate="2021-01-15T11:14:48.127" LastActivityDate="2021-01-15T11:14:48.127" Title="Order of diffraction pattern confusion in XRD experiment" Tags="|crystal-structure|crystallography|structure|experimental|x-ray-diffraction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4131" PostTypeId="2" ParentId="4090" CreationDate="2021-01-14T20:00:33.753" Score="6" Body="&lt;p&gt;If you're familiar with Python, this can be done using &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; fairly easily.&lt;/p&gt;&#xA;&lt;p&gt;To illustrate, let's first define our problem:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymatgen.core.lattice import Lattice&#xA;from pymatgen.core.structure import Structure&#xA;&#xA;malnac_lattice = Lattice.from_parameters(5.33, 5.14, 11.25, 102.7, 135.17, 85.17)&#xA;malnac02_lattice = Lattice.from_parameters(5.156, 5.341, 8.407, 71.48, 76.12, 85.09)&#xA;&#xA;# here, because we're only interested in the lattices, &#xA;# we can define a &amp;quot;dummy structure&amp;quot; with a single H atom at the origin&#xA;&#xA;malnac_struct = Structure(malnac_lattice, [&amp;quot;H&amp;quot;], [[0.0, 0.0, 0.0]])&#xA;malnac02_struct = Structure(malnac02_lattice, [&amp;quot;H&amp;quot;], [[0.0, 0.0, 0.0]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now we have the structures defined, we can use &lt;code&gt;StructureMatcher&lt;/code&gt; to compare them and find the transformation to change one into the other.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymatgen.analysis.structure_matcher import StructureMatcher&#xA;&#xA;# StructureMatcher can accept different tolerances for judging equivalence&#xA;matcher = StructureMatcher(primitive_cell=False)&#xA;&#xA;# first, we can verify these lattices are equivalent&#xA;matcher.fit(malnac_struct, malnac02_struct)  # returns True&#xA;&#xA;# and we can get the transformation matrix from one to the other&#xA;# this returns the supercell matrix (e.g. change of basis), &#xA;# as well as any relevant translation, and mapping of atoms from one&#xA;# crystal to the other&#xA;matcher.get_transformation(malnac_struct, malnac02_struct)&#xA;# returns (array([[ 0, -1,  0], [-1,  0,  0], [ 0,  1,  1]]), array([0., 0., 0.]), [0])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives your answer:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{pmatrix}&#xA;0 &amp;amp; -1 &amp;amp; 0 \\ &#xA;-1 &amp;amp; 0 &amp;amp; 0 \\ &#xA;0 &amp;amp; 1 &amp;amp; 1&#xA;\end{pmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This matrix defines the transformation from the one set of lattice vectors (a, b, c) into the other, and the angles can be obtained from here.&lt;/p&gt;&#xA;&lt;p&gt;More information can be found in the pymatgen docs, or you can ask the developers (myself included) at &lt;a href=&quot;https://matsci.org/pymatgen&quot; rel=&quot;noreferrer&quot;&gt;matsci.org/pymatgen&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2021-01-14T20:00:33.753" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4132" PostTypeId="2" ParentId="4127" CreationDate="2021-01-14T20:06:19.763" Score="5" Body="&lt;p&gt;As you already figured out, the error is that the charge and multiplicity are inconsistent with the molecule; this is what Psi4 tells you:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;qcelemental.exceptions.ValidationError: Inconsistent or unspecified chg/mult: sys chg: None, frag chg: [0.0], sys mult: None, frag mult: [1]&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The problem is that the system has 111 electrons, which is an odd number, so you can't construct a spin-singlet wave function. Valid multiplicities for the neutral molecule are 2 (doublet), 4 (quartet), 6 (sextet), etc. The anion and cation both have an even number of electrons, so they can be in a singlet, triplet, quintet, etc.&lt;/p&gt;&#xA;&lt;p&gt;Note also that &lt;code&gt;freeze_core&lt;/code&gt; does nothing for self-consistent field calculations in Psi4.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-01-14T20:06:19.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4133" PostTypeId="2" ParentId="4123" CreationDate="2021-01-15T00:37:46.063" Score="8" Body="&lt;p&gt;I will first take a generic  view-point and then quote some examples in condensed matter &amp;amp; materials modeling. Time-reversal symmetry is one of two discrete symmetries usually discussed in the context of condensed-matter, the other being Parity(Inversion). The simplest way in which this concept is presented is a transformation :&#xA;&lt;span class=&quot;math-container&quot;&gt;$ t \rightarrow -t $&lt;/span&gt; . Think of it as a motion reversal - If you go back in time, does the system look the same?&lt;/p&gt;&#xA;&lt;p&gt;Take a video clip for example. And let us say you start to rewind the video. Your observation will basically be the same, but in reverse. Such a system is Time-reversal invariant, meaning it has T.R. symmetry. Now try to think of cases (not just systems) where such a reversal breaks a fundamental law of nature - The simplest example being, the 2&lt;span class=&quot;math-container&quot;&gt;$^{nd}$&lt;/span&gt; law of thermodynamics which effectively states that the total entropy in a system can only increase or stay constant. You will immediately conclude that winding back the clock (so to speak) breaks a fundamental law since you cannot remove entropy that has already been created.&lt;/p&gt;&#xA;&lt;p&gt;In condensed matter, a variety of systems break T.R. symmetry - Ferromagnets, Anti-ferromagnets, Chiral spin liquids, some Superconductors etc. The simplest case is the ferromagnet - There are two ways to reconcile this:&lt;/p&gt;&#xA;&lt;p&gt;a) If you relate the origin of magnetism to circulating current loops: Reversing the motion results in a current that flows in the opposite sense, giving you a magnetic field with the opposite sign. This clearly breaks T.R. symmetry.&lt;/p&gt;&#xA;&lt;p&gt;b) A more generic viewpoint: Spontaneous magnetization. Take a virgin sample of Iron. When you apply a magnetic field, it becomes magnetized. Can you remove the magnetic ordering ('demagnetize') the sample just by removal of the magnetic field?&lt;/p&gt;&#xA;&lt;p&gt;In the context of materials modeling, T.R. symmetry can often lead to degeneracies that improve the computational speed greatly. The simplest example is Kramer's rule, which can be proved trivially from by taking a conjugate of the time-dependent Schrodinger equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ E _n (\vec k) =  E _n (-\vec k) $&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the band index and &lt;span class=&quot;math-container&quot;&gt;$\vec k $&lt;/span&gt; runs over the brillouin zone&lt;/p&gt;&#xA;&lt;p&gt;As far as spin-orbit coupling is concerned, it does not break time-reversal symmetry by itself. Think of SO-coupling as &lt;span class=&quot;math-container&quot;&gt;$(coeffiecent)* L.S $&lt;/span&gt;. Since both L (angular momentum) and S (spin operator) change sign, their product retains the sign.&lt;/p&gt;&#xA;&lt;p&gt;I have not delved much into the math in my answer, but I would recommend &lt;a href=&quot;https://www.google.com/books/edition/Modern_Quantum_Mechanics/010yDwAAQBAJ?hl=en&amp;amp;gbpv=1&amp;amp;dq=sakurai+quantum+mechanics&amp;amp;printsec=frontcover&quot; rel=&quot;noreferrer&quot;&gt;Sakurai's Quantum Mechanics&lt;/a&gt;, a classic. For an insight into systems with non-trivial T.R. breaking,here's an excellent &lt;a href=&quot;https://physics.stackexchange.com/questions/29469/spontaneous-time-reversal-symmetry-breaking/30188?&quot;&gt;answer&lt;/a&gt; on physics stack exchange.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="683" LastEditDate="2021-01-15T00:53:03.403" LastActivityDate="2021-01-15T00:53:03.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4134" PostTypeId="1" AcceptedAnswerId="4136" CreationDate="2021-01-15T03:03:09.880" Score="7" ViewCount="271" Body="&lt;p&gt;Past semester we revisited the &lt;a href=&quot;https://en.wikipedia.org/wiki/H%C3%BCckel_method&quot; rel=&quot;noreferrer&quot;&gt;Hückel molecular orbital theory&lt;/a&gt; at class. One day I was trying to solve some problems with &lt;a href=&quot;https://www.sympy.org/en/index.html&quot; rel=&quot;noreferrer&quot;&gt;SymPy&lt;/a&gt;, a Python module that is a computer algebra system (&lt;a href=&quot;https://en.wikipedia.org/wiki/Computer_algebra_system&quot; rel=&quot;noreferrer&quot;&gt;CAS&lt;/a&gt;), and noticed something curious while getting symbolic solutions for the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fulvene&quot; rel=&quot;noreferrer&quot;&gt;pentafulvene&lt;/a&gt; molecule, as shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Python 3.8.5 (default, Sep  4 2020, 07:30:14) &#xA;Type &amp;quot;copyright&amp;quot;, &amp;quot;credits&amp;quot; or &amp;quot;license&amp;quot; for more information.&#xA;&#xA;IPython 7.19.0 -- An enhanced Interactive Python.&#xA;&#xA;from sympy import Symbol, Matrix, roots&#xA;&#xA;x = Symbol('x')&#xA;&#xA;M_pentafulvene = Matrix([[x, 1, 0, 0, 0, 0], [1, x, 1, 0, 0, 1], [0, 1, x, 1, 0, 0], [0, 0, 1, x, 1, 0], [0, 0, 0, 1, x, 1], [0, 1, 0, 0, 1, x]])&#xA;&#xA;M_pentafulvene&#xA;Out[4]: &#xA;Matrix([&#xA;[x, 1, 0, 0, 0, 0],&#xA;[1, x, 1, 0, 0, 1],&#xA;[0, 1, x, 1, 0, 0],&#xA;[0, 0, 1, x, 1, 0],&#xA;[0, 0, 0, 1, x, 1],&#xA;[0, 1, 0, 0, 1, x]])&#xA;&#xA;polynomial = M_pentafulvene.det()&#xA;&#xA;polynomial&#xA;Out[6]: &#xA;x**6 - 6*x**4 + 8*x**2 + 2*x - 1&#xA;&#xA;roots(polynomial)&#xA;Out[7]: &#xA;{-1: 1,&#xA; 1/2 - sqrt(5)/2: 1,&#xA; 1/2 + sqrt(5)/2: 1,&#xA; -(27/2 + 3*sqrt(687)*I/2)**(1/3)/3 - 4/(27/2 + 3*sqrt(687)*I/2)**(1/3): 1,&#xA; -(-1/2 + sqrt(3)*I/2)*(27/2 + 3*sqrt(687)*I/2)**(1/3)/3 - 4/((-1/2 + sqrt(3)*I/2)*(27/2 + 3*sqrt(687)*I/2)**(1/3)): 1,&#xA; -4/((-1/2 - sqrt(3)*I/2)*(27/2 + 3*sqrt(687)*I/2)**(1/3)) - (-1/2 - sqrt(3)*I/2)*(27/2 + 3*sqrt(687)*I/2)**(1/3)/3: 1}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, the expressions for three out of five solutions have &lt;span class=&quot;math-container&quot;&gt;$I = \sqrt -1$&lt;/span&gt;, the imaginary unit, as part of them. Seeing that, initially I was puzzled, as imaginary solutions would make no sense, and thought I made a mistake somewhere, but soon I perceived the imaginary part pratically vanishes when we evaluate the expressions:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;I = (-1)**0.5&#xA;&#xA;sqrt = lambda x: x**0.5&#xA;&#xA;for solution in roots(polynomial):&#xA;    print(eval(str(solution)))&#xA;    &#xA;-1&#xA;-0.6180339887498949&#xA;1.618033988749895&#xA;(-2.114907541476756+1.6653345369377348e-16j)&#xA;(1.8608058531117035+3.3306690738754696e-16j)&#xA;(0.2541016883650525-4.440892098500626e-16j)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There is a tiny imaginary remnant, on the order of &lt;span class=&quot;math-container&quot;&gt;$10^{-16}$&lt;/span&gt;. I don't know the implementation details of complex numbers in Python, but I suspect this tiny remnant is due some sort of rounding error.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, as is not that hard to came with polynomials containing integer coeficients that yield imaginary solutions, the trivial example being &lt;span class=&quot;math-container&quot;&gt;$x^2 + 1 = 0$&lt;/span&gt;. That made me wonder if one could &amp;quot;break&amp;quot; Hückel method by finding a example of a plausible compound whose associated secular determinant results in complex roots with a non negligible imaginary part. I actually tried to brute-force an answer, by writing a script to try solve every determinant for &amp;quot;valid&amp;quot; matrices up to a 7 carbon scaffold. By valid I mean, matrices that are symmetric around the main diagonal, whose lines and columns sum to a number greater than zero and equal or smaller than 3 (to avoid carbons with too many neighbors or none), and that represented fully connected structures:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import copy&#xA;import time&#xA;from sympy import Matrix, eye, symbols, nroots&#xA;&#xA;def load_symbol(L):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Takes all-numeric square matrix and replaces every entry in the main diagonal&#xA;    with variable x (SymPy symbol), returning a symbolic matrix.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    x = symbols('x')&#xA;    for i in range(len(L)):&#xA;        L[i][i] = x&#xA;    return L&#xA;&#xA;def valid_columns_rows(L):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Takes square matrix (list of n integer lists of size n), and verify if it &#xA;    could represent a valid Hückel secular determinant, by checking, if the sum &#xA;    of each row is &amp;gt; 0 and &amp;lt;= 3, then doing the same check to each column, as &#xA;    each sp2 carbon should be bonded to at least another carbon, and at most to &#xA;    other 3 coplanar carbons. Returns True if both checks are True, otherwise &#xA;    returns false.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    row_sums = [sum(row) for row in L]&#xA;    if min(row_sums) &amp;gt; 0 and max(row_sums) &amp;lt;= 3:&#xA;        column_sums = []&#xA;        for i in range(len(L)):&#xA;            ith_column = [row[i] for row in L]&#xA;            column_sums.append(sum(ith_column))&#xA;        return min(column_sums) &amp;gt; 0 and max(column_sums) &amp;lt;= 3&#xA;    else:&#xA;        return False&#xA;&#xA;def connected(L):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Checks if matrix represents fully connected structure, instead of a set&#xA;    of disjoined smaller fragments. Returns True if connected, otherwise&#xA;    returns False. As the Huckël secular determinant matrix has a similar form &#xA;    to the adjacency matrix of a graph, I used the power sum of adjacency &#xA;    matrix method given in Tan T Z, Gao S X, Yang W G. Determining the &#xA;    connectedness of an undirected graph. Journal of University of Chinese &#xA;    Academy of Sciences, 2018, 35(5): 582-588, available at &#xA;    http://html.rhhz.net/ZGKXYDXXB/20180502.htm&#xA;    It consists in calculating: &#xA;    S = I + M + M^2 + ... + M^(n-1),&#xA;    where M is the adjacency matrix and I the identity matrix of same size. &#xA;    If the first row of S has all elements &amp;gt; 0, then the system is connected.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    n = len(L)&#xA;    M = Matrix(L)&#xA;    S = eye(n)&#xA;    for i in range(n-1):&#xA;        S += M**(i+1)&#xA;    return min(S.row(0)) &amp;gt; 0&#xA;    &#xA;def diagonal_slice_generator(n):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Generates list of possible diagonal slices of size n, for a huckel secular &#xA;    determinant matrix. As after substituting (alpha - E)/beta = x, all elements&#xA;    off the principal diagonal become either 0 or 1, it just generates every&#xA;    binary number from 0 to 2**n - 1, pads with zeroes, converts to string&#xA;    then to integer lists.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    string_list = [list(str(bin(i))[2:].zfill(n)) for i in range(2**n)]&#xA;    integer_nested_list = [[int(char) for char in string] for string in string_list]&#xA;    return integer_nested_list&#xA;    &#xA;def secular2roots(M):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Given a symbolic matrix, tries to solve the Hückel secular determinant,&#xA;    numerically. If successful, returns solutions as list. If it fails to &#xA;    converge, returns empty list, and prints a warning.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    symbolic_matrix = Matrix(M)&#xA;    polynomial = symbolic_matrix.det()&#xA;    try:&#xA;        D = nroots(polynomial, maxsteps=500)&#xA;        return D&#xA;    except:&#xA;        print('Roots not found for polynomial', polynomial, 'from matrix:', M)&#xA;        return []&#xA;     &#xA;def symmetric_matrix_generator(n, L):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Takes integer n and list L, that must be composed of n sublists containing&#xA;    only 0 as element. Then grows recursively this list into a square matrix of&#xA;    size n, by adding pairs of identical diagonal slices above and below the&#xA;    main diagonal. The main diagonal is composed of the zeroes in the original&#xA;    list. It's a generator, yielding every possible n x n matrix symmetric &#xA;    around the main diagonal, until the search space is exhausted. The matrix&#xA;    must be symmetric because if carbon i is bound to carbon j, then carbon j&#xA;    must be bound to carbon i too, as chemical bonds are bidirectional.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    diagonals = diagonal_slice_generator(n-1)&#xA;    backup = copy.deepcopy(L)&#xA;    for cut in diagonals:&#xA;        for j in range(len(cut)):&#xA;            L[j+(len(L) - len(cut))].insert(0, cut[j])&#xA;            L[j].append(cut[j])&#xA;        if n &amp;gt; 2:&#xA;            yield from symmetric_matrix_generator(n-1, L)&#xA;        else:&#xA;            yield L&#xA;        L = copy.deepcopy(backup)&#xA;&#xA;def valid_matrix_generator(n):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Takes n as argument, then calls the previous symmetric_matrix_generator &#xA;    to get candidate square matrices of size n x n. Reject the ones unlikely&#xA;    to represent valid Hückel secular determinants, due to either not being&#xA;    fully connected, or to carbon atoms with none or more than 3 neighbors, &#xA;    yielding the rest.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    L = [[0] for i in range(n)]&#xA;    for e in symmetric_matrix_generator(n, L):&#xA;        if valid_columns_rows(e):&#xA;            if connected(e):&#xA;                yield e&#xA;&#xA;n = 7                   #Upper bound on size of matrix (lower bound is 2)&#xA;maximum = 0             #Stores largest imaginary part found&#xA;counter = 0             #Counts number of valid matrices processed&#xA;start = time.time()&#xA;&#xA;for i in range(2, n+1):&#xA;    for M in valid_matrix_generator(i):&#xA;        s = load_symbol(M)&#xA;        numeric_roots = secular2roots(s)&#xA;        if numeric_roots == []:&#xA;            pass&#xA;        else:&#xA;            if len(numeric_roots) &amp;lt; i:&#xA;                print('Missing roots in', s, 'found only', numeric_roots)&#xA;            candidate = abs(max([complex(n).imag for n in numeric_roots]))&#xA;            if candidate &amp;gt; maximum:&#xA;                maximum = candidate&#xA;                print('So far, largest imaginary part found in', numeric_roots, 'from', s)&#xA;        counter += 1&#xA;        if counter % 10000 == 0:&#xA;            print('So far', counter, 'valid matrices processed in', round(time.time() - start), 'sec.')&#xA;    print('Search space exhausted for n=', i, 'at', round(time.time() - start, 2), 'sec.')&#xA;print('Total of', counter, 'matrices processed in', round(time.time() - start), 2, 'sec.')&#xA;print('Maximum absolute imaginary part found in any solution set:\n', maximum)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Running this, I got the following output after nearly five hours:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Search space exhausted for n= 2 at 0.0 sec.&#xA;Search space exhausted for n= 3 at 0.02 sec.&#xA;Roots not found for polynomial x**4 - 6*x**2 + 8*x - 3 from matrix: [[x, 1, 1, 1], [1, x, 1, 1], [1, 1, x, 1], [1, 1, 1, x]]&#xA;Search space exhausted for n= 4 at 0.56 sec.&#xA;Search space exhausted for n= 5 at 10.17 sec.&#xA;So far, largest imaginary part found in [-3.00000000000000, -3.04533612508806e-16, 2.54155613029339e-16, 3.00000000000000, -2.78240672724667e-16*I, 3.33228889079154e-16*I] from [[x, 0, 0, 1, 1, 1], [0, x, 0, 1, 1, 1], [0, 0, x, 1, 1, 1], [1, 1, 1, x, 0, 0], [1, 1, 1, 0, x, 0], [1, 1, 1, 0, 0, x]]&#xA;Search space exhausted for n= 6 at 405.84 sec.&#xA;So far, largest imaginary part found in [-2.76155718183189, -1.36332823793268, -1.00000000000000, 1.00000000000000, 2.12488541976457, 0.999999999999903 + 1.674006560727e-13*I, 1.0000000000001 - 1.69100888096705e-13*I] from [[x, 0, 0, 1, 0, 1, 1], [0, x, 0, 0, 1, 1, 0], [0, 0, x, 0, 1, 0, 1], [1, 0, 0, x, 0, 1, 1], [0, 1, 1, 0, x, 0, 0], [1, 1, 0, 1, 0, x, 0], [1, 0, 1, 1, 0, 0, x]]&#xA;So far 10000 valid matrices processed in 512 sec.&#xA;So far 20000 valid matrices processed in 1344 sec.&#xA;So far 30000 valid matrices processed in 2142 sec.&#xA;So far 40000 valid matrices processed in 3014 sec.&#xA;So far 50000 valid matrices processed in 3820 sec.&#xA;So far 60000 valid matrices processed in 4678 sec.&#xA;So far 70000 valid matrices processed in 5646 sec.&#xA;So far 80000 valid matrices processed in 6648 sec.&#xA;So far 90000 valid matrices processed in 7686 sec.&#xA;So far 100000 valid matrices processed in 8770 sec.&#xA;So far 110000 valid matrices processed in 9928 sec.&#xA;So far 120000 valid matrices processed in 11113 sec.&#xA;So far 130000 valid matrices processed in 12374 sec.&#xA;So far 140000 valid matrices processed in 13698 sec.&#xA;So far 150000 valid matrices processed in 14996 sec.&#xA;Search space exhausted for n= 7 at 16231.49 sec.&#xA;Total of 158985 matrices processed in 16231 2 sec.&#xA;Maximum absolute imaginary part found in any solution set:&#xA; 1.674006560727002e-13&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After processing more than 150k matrices (the number of actual compounds is smaller due to some of the them corresponding to different labelling on the carbons), the numeric root finder of SymPy failed to find a solution in a single case. I tried to draw it, and I don't believe it represents a valid compound to apply Hückel method, as it probably can't be planar. The closest thing would be a 3D carbon tetrahedron where each face looks like a cyclopropene:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bKSE7.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bKSE7.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It seems my valid_matrix_generator() doesn't generate only valid examples. I think the problem is the lack of criteria to filter out compounds that can exist only in 3D. It's curious that the numeric solver failed to converge for this fourth degree equation, even if it could find solutions for all the others up to seventh degree. The symbolic solver show that it actually has solutions 1 and -3, corresponding to &lt;span class=&quot;math-container&quot;&gt;$(x-1)^3(x+3) = 0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, it failed in finding a single example with solutions containing a non negligible imaginary part. The largest found was of the order of &lt;span class=&quot;math-container&quot;&gt;$10^{-13}$&lt;/span&gt;. While the value is about 1000x larger than what I found in the pentafulvene example, that's still very small. I think it's another compound that would not actually be planar, and the equivalent 3D structure would correspond to something like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dWfTk.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dWfTk.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the end, as expected, it looks like it's not possible to get imaginary solutions for a Hückel secular determinant, but I'm not sure. If someone could explain me what mathematically precludes a solution being complex, I would be grateful.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="7" LastEditDate="2021-07-30T20:17:07.023" LastActivityDate="2021-07-30T20:17:07.023" Title="Is it possible to get complex numbers as solutions for a secular determinant in simple Hückel method (SHM)?" Tags="|quantum-chemistry|mathematical-modeling|numerical-convergence|semi-empirical-method|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4135" PostTypeId="2" ParentId="4123" CreationDate="2021-01-15T03:28:05.250" Score="8" Body="&lt;p&gt;Another way to &lt;em&gt;explicitly&lt;/em&gt; break time-reversal symmetry is by applying circularly polarized light. Under time reversal, left circularly polarized light transforms to right circularly polarized light, and vice versa. One way to see this is to note that circularly polarized light is an eigenstate of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin_angular_momentum_of_light&quot; rel=&quot;noreferrer&quot;&gt;spin angular momentum operator&lt;/a&gt;, which is odd under time reversal. Hence, if such light is applied to an otherwise time-reversal symmetric system, the Hamiltonian will no longer have &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry, and Kramers' theorem no longer applies.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-01-15T03:28:05.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4136" PostTypeId="2" ParentId="4134" CreationDate="2021-01-15T05:11:42.640" Score="9" Body="&lt;p&gt;In the Huckel method, you are just generating a very simplified version of the molecular Hamiltonian and determining it's eigenvalues. The molecular Hamiltonian will always be a Hermitian matrix (for the Huckel method, we can be more specific and say it's a real symmetric matrix by construction). Hermitian matrices are guaranteed to have all real eigenvalues (a &lt;a href=&quot;https://math.stackexchange.com/q/462982/418145&quot;&gt;simple proof&lt;/a&gt; is available on Math SE and tends to be covered in early quantum mechanics courses), so you won't be able to find a molecule where the Huckel method would produce imaginary/complex energies.&lt;/p&gt;&#xA;&lt;p&gt;As for the small imaginary values you are seeing, these are a mainly a consequence of the finite precision offered by floating point numbers. ~&lt;span class=&quot;math-container&quot;&gt;$10^{-16}$&lt;/span&gt; is roughly the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Machine_epsilon&quot; rel=&quot;noreferrer&quot;&gt;machine epsilon&lt;/a&gt; for double precision arithmetic, so it's not surprising to see some of your results have this small an imaginary part. As for the max value you saw of ~&lt;span class=&quot;math-container&quot;&gt;$10^{-13}$&lt;/span&gt;, the slightly larger imprecision can be attributed to the various solver routines you use having their own inherent imprecision when working with floating point numbers, leaving you with numerical noise in the imaginary part.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-01-15T21:38:13.213" LastActivityDate="2021-01-15T21:38:13.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4137" PostTypeId="2" ParentId="4130" CreationDate="2021-01-15T06:06:22.067" Score="4" Body="&lt;p&gt;In Bragg's law, &lt;span class=&quot;math-container&quot;&gt;$n\lambda=2d\sin(\theta)$&lt;/span&gt;. Here, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the order of the reflection, and corresponds to the path length difference between X-rays diffracted from two different layers of atoms, in terms of the number of wavelengths. So if the path lengths differ by exactly one wavelength, it is a first order reflection.&lt;/p&gt;&#xA;&lt;p&gt;By convention, we treat all reflections as first order, and introduce a different &amp;quot;effective&amp;quot; lattice spacing. This avoids having to deal with reflection order explicitly. As an example from the comments on the original question, if you consider a second order reflection from (100) planes, the equation is &lt;span class=&quot;math-container&quot;&gt;$2\lambda=2d_{100}\sin(\theta)$&lt;/span&gt; and a first order reflection from (200) planes is satisfied by &lt;span class=&quot;math-container&quot;&gt;$\lambda=2d_{200}\sin(\theta)$&lt;/span&gt;. But we know that &lt;span class=&quot;math-container&quot;&gt;$2d_{200}=d_{100}$&lt;/span&gt;, so these two conditions both correspond to the same diffraction angle in the material. Again, we just consider all reflections as first order by convention.&lt;/p&gt;&#xA;" OwnerUserId="686" LastEditorUserId="686" LastEditDate="2021-01-15T06:13:57.993" LastActivityDate="2021-01-15T06:13:57.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4138" PostTypeId="1" AcceptedAnswerId="4142" CreationDate="2021-01-15T10:28:02.497" Score="11" ViewCount="781" Body="&lt;p&gt;I tried to relax a &lt;strong&gt;4x4x1 supercell of ferromagnetic monolayer&lt;/strong&gt; material using the default settings (&lt;code&gt;ALGO = Normal&lt;/code&gt;) but it didn't converge. So, I switched to &lt;code&gt;ALGO = Fast&lt;/code&gt; and the results are converging normally now. Is this setting safe? Will this affect the accuracy of the results?&#xA;The used INCAR file is below :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ENCUT = 600 eV&#xA;PREC = Accurate&#xA;LREAL = Auto&#xA;EDIFFG = -0.001&#xA;EDIFF = 1E-8 &#xA;LCHARG = .FALSE.&#xA;LWAVE = .FALSE.&#xA;ISMEAR = 0&#xA;ADDGRID = .TRUE.&#xA;SIGMA = 0.03&#xA;NSW = 299&#xA;IBRION = 2&#xA;ISIF = 3&#xA;ISPIN = 2&#xA;MAGMOM = 16*2.0 32*0.0&#xA;ALGO = Fast # This was Normal before editing&#xA;#Mixer&#xA;AMIX     = 0.2&#xA;BMIX     = 0.00001&#xA;AMIX_MAG = 0.8&#xA;BMIX_MAG = 0.00001&#xA;&#xA;LASPH      = .TRUE.&#xA;&#xA;NCORE = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="272" LastEditorUserId="697" LastEditDate="2021-01-15T19:17:48.050" LastActivityDate="2021-01-15T19:17:48.050" Title="Are different eigensolvers consistent within VASP (Algo=Normal vs Fast)" Tags="|density-functional-theory|vasp|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4139" PostTypeId="2" ParentId="3976" CreationDate="2021-01-15T17:26:16.743" Score="5" Body="&lt;p&gt;The correct syntax is then the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$gmx rdf -f ftraj.xtc -s ftraj.tpr -ref &amp;quot;name C1 C2 C3&amp;quot; -sel &amp;quot;name C1 C2 C3&amp;quot; -selrpos part_res_com -seltype part_res_com&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My thoughts were partially clarified after consulting the useful command &lt;code&gt;gmx help selections positions&lt;/code&gt; where it is described that &lt;code&gt;POSTYPE can be atom, res_com, res_cog, mol_com or mol_cog, with an optional prefix whole_ part_ or dyn_&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;whole_&lt;/code&gt; calculates the centers for the whole residue/molecule, even if only part of it is selected&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;part_&lt;/code&gt; prefix calculates the centers for the selected atoms, but uses always the same atoms for the same residue/molecule&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;dyn_&lt;/code&gt; calculates the centers strictly only for the selected atoms.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, I still want to test the default behaviour (which should be &lt;code&gt;part_&lt;/code&gt; when selections are provided, and &lt;code&gt;whole_&lt;/code&gt; otherwise).&lt;/p&gt;&#xA;" OwnerUserId="1773" LastActivityDate="2021-01-15T17:26:16.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4140" PostTypeId="1" CreationDate="2021-01-15T18:04:17.427" Score="7" ViewCount="422" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7NaBh.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7NaBh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;c(O) = 0.40 wt% C&lt;/p&gt;&#xA;&lt;p&gt;c(&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;) = 0.022 wt% C&lt;/p&gt;&#xA;&lt;p&gt;c(FeC3) = 6.70 wt% C3&lt;/p&gt;&#xA;&lt;p&gt;For the Fe-C alloy with 99.6 wt% Fe-0.40 wt% C, determine (at the temperature immediately below the eutectoid) determine the amount of cementite formed (in g) per 100 g of steel&lt;/p&gt;&#xA;&lt;p&gt;Solution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{Fe_3C}{Fe_3C+\alpha} =\frac{C_0 - C_{\alpha}}{C_{Fe_3C}-C_{\alpha}}.100 = \frac{0.4-0.022}{6.7-0.022}.100 = 5.7g$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$Fe_3C = 5.7g$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha = 94.3g$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;but i though that since its 100g steel we got that alpha=(0.022 * 100) and Fe3C=(6.7 * 100)g . why is this wrong?&lt;/p&gt;&#xA;" OwnerDisplayName="user1934" LastEditorUserId="1355" LastEditDate="2021-01-16T06:18:42.763" LastActivityDate="2021-01-16T06:18:42.763" Title="How can I determine the amount of cementite formed (in g) per 100 g of steel?" Tags="|phase-diagram|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4141" PostTypeId="2" ParentId="4140" CreationDate="2021-01-15T18:31:11.753" Score="5" Body="&lt;p&gt;I think you are considering the carbon % in alpha-solid solution and Fe3C as the overall percentages of alpha-solid solution and Fe3C in the alloy. For example - 6.7% is the carbon amount in Fe3C, it is not the overall % of Fe3C in the alloy.So you can't just multiply 6.7 with 100 and indicate it as the amount of Fe3C in the alloy.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2021-01-15T18:31:11.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4142" PostTypeId="2" ParentId="4138" CreationDate="2021-01-15T18:41:00.747" Score="13" Body="&lt;p&gt;Changing ALGO should make no difference in an ideal world.  However, when you invoke spin polarization, you may find a different magnetic state from both algorithms.  The best practice would be to ensure that you converge to the right solution.&lt;/p&gt;&#xA;&lt;p&gt;That being said, the NORMAL algo is normally more robust than Fast.  This in general might be a bad sign for your system.  You can also try the ALL algo and see what that gives.&lt;/p&gt;&#xA;&lt;p&gt;I see you have also added an incar, here is some general advice that might influence convergence.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ADDGRID is a spooky keyword, I would say never use it but sometimes it helps.  I suggest leaving it off, convergence issues tend not to be fixed by it in general in these magnetic systems&lt;/li&gt;&#xA;&lt;li&gt;You are using a small sigma value, I would suggest using 0.2 and reduce it to your desired value after convergence.  It will not influence geometry much but will make convergence much easier.&lt;/li&gt;&#xA;&lt;li&gt;Leave the mixing settings at their defaults most of the time.  You can try this approach as a first attempt, but if it doesn't fix the problem do not keep it.&lt;/li&gt;&#xA;&lt;li&gt;Consider running a spin paired calculation first as a single point calculation, save the WAVECAR/CHGCAR, then add magnetization.  This often helps as well.&lt;/li&gt;&#xA;&lt;li&gt;EDIFF = 1e-8 is insanely accurate, use something more like 1e-4 or 1e-5 for geometry optimization.  If you find that you cannot converge the geometry you can raise it or switch to a VTST geometry optimizer which uses forces which are less sensitive to this.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2021-01-15T19:12:37.360" LastActivityDate="2021-01-15T19:12:37.360" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4143" PostTypeId="1" AcceptedAnswerId="4176" CreationDate="2021-01-15T22:02:54.003" Score="17" ViewCount="875" Body="&lt;p&gt;I recently came across something called the basis set projection in Q-chem's &lt;a href=&quot;https://manual.q-chem.com/5.2/Ch4.S4.SS5.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt;. What it seems to do is to take the converged SCF in a smaller basis set, and then &amp;quot;projects&amp;quot; that onto a larger basis set (by either constructing the Fock matrix from the previous density matrix, or by expanding the previous MOs onto the larger basis set). This is then used as a guess for the SCF with the larger basis set. The manual page of Q-chem does not have any reference on this, and I can't find any paper by a google search.&lt;/p&gt;&#xA;&lt;p&gt;However, this method seems to be well-established, because even old versions of GAMESS-US have an option of &lt;code&gt;GUESS=RDMINI&lt;/code&gt; in the &lt;code&gt;$GUESS&lt;/code&gt; section, which seems to be doing the same thing—reading the converged orbitals with a MINI basis set and then project that for a better guess.&lt;/p&gt;&#xA;&lt;p&gt;What is the mathematical procedure of this projection, and why/how does it work? (And if possible, please mention the references, I would like to read more on this!)&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-01-24T23:04:18.733" LastActivityDate="2021-01-24T23:04:18.733" Title="How is &quot;basis set projection&quot; done?" Tags="|basis-sets|self-consistent-field|q-chem|gamess|mrcc|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4144" PostTypeId="1" CreationDate="2021-01-16T04:00:35.917" Score="3" ViewCount="69" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Si(liq)=Si_\text{(1 wt% Fe)}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can you describe what is going on here?All that they ask for is change in Gibbs free energy for the process.I am completely unable to figure why this particular model is so important for a specific question.It would be great if someone could interpret both the analytical and the mathematical analogy to this.There is also a difference between Raoultian and Henrian State which is to be applied here. I do not understand which one I am supposed to use when.Why is &lt;span class=&quot;math-container&quot;&gt;$\text{1 wt% Fe}$&lt;/span&gt; so important?&lt;/p&gt;&#xA;" OwnerUserId="1893" LastActivityDate="2021-01-16T04:00:35.917" Title="Doubt in Raoultian and Henrian Standard State" Tags="|condensed-matter|thermodynamics|statistical-thermodynamics|materials-engineering|" AnswerCount="0" CommentCount="2" ClosedDate="2021-06-23T22:03:52.067" ContentLicense="CC BY-SA 4.0" />
  <row Id="4145" PostTypeId="1" CreationDate="2021-01-16T19:37:28.127" Score="5" ViewCount="135" Body="&lt;p&gt;Is there any relation between enthalpy, ionization potential, internal energy and HOMO/LUMO?&lt;/p&gt;&#xA;&lt;p&gt;I am dehydrogenating a molecule and I need to study the enthalpy of dehydrogenation. If I get any relation between above properties, then I can conclude something for my results.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-08-14T17:43:11.267" LastActivityDate="2021-08-14T17:43:11.267" Title="What is the relation between enthalpy, ionization potential, internal energy and HOMO/LUMO?" Tags="|density-functional-theory|computational-chemistry|hydrogen-bonds|" AnswerCount="0" CommentCount="11" ClosedDate="2021-12-26T00:06:54.020" ContentLicense="CC BY-SA 4.0" />
  <row Id="4146" PostTypeId="1" CreationDate="2021-01-17T06:51:33.780" Score="9" ViewCount="438" Body="&lt;p&gt;I wanted to observe the Projected Density of States of InP system passivated with Hydride ions. For that, the following input file was created.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA; calculation='scf',&#xA; outdir='./outdir',&#xA; prefix='InPH',&#xA; pseudo_dir='.',&#xA; verbosity='low',&#xA; tprnfor=.true.,&#xA; tstress=.true.,&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =   28.95873&#xA;  nat = 38&#xA;  ntyp = 3&#xA; ecutwfc=50,&#xA; ecutrho=400,&#xA; input_dft='pbe',&#xA; occupations='smearing',&#xA; starting_charge(1) = +3.0&#xA; starting_charge(2) = -3.0&#xA; starting_charge(3) = -1.0&#xA; smearing='mv',&#xA; degauss=0.005d0,&#xA;                       &#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA; conv_thr=1d-07,&#xA; mixing_beta=0.7d0,&#xA;/&#xA;&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA;  0.000000000000000   1.000000000000000   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   1.000000000000000 &#xA;ATOMIC_SPECIES&#xA;  In  114.81800   In.pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;   P   30.97300   P.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;   H    1.00750   H.pbe-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA;In   0.301777000000000   0.515510000000000   0.403224000000000 &#xA;In   0.489752000000000   0.303558000000000   0.415264000000000 &#xA;In   0.503499000000000   0.505059000000000   0.408072000000000 &#xA;In   0.501909000000000   0.513929000000000   0.598334000000000 &#xA;In   0.296909000000000   0.419582000000000   0.514790000000000 &#xA;In   0.492873000000000   0.398390000000000   0.315705000000000 &#xA;In   0.497050000000000   0.408959000000000   0.504514000000000 &#xA;In   0.510066000000000   0.608991000000000   0.499706000000000 &#xA;In   0.390717000000000   0.315763000000000   0.518452000000000 &#xA;In   0.401476000000000   0.501161000000000   0.310056000000000 &#xA;In   0.402099000000000   0.515299000000000   0.498794000000000 &#xA;In   0.602463000000000   0.505451000000000   0.505306000000000 &#xA;In   0.393310000000000   0.407603000000000   0.415739000000000 &#xA;In   0.399042000000000   0.422615000000000   0.605304000000000 &#xA;In   0.406187000000000   0.607978000000000   0.395822000000000 &#xA;In   0.594811000000000   0.396109000000000   0.407363000000000 &#xA; P   0.448966000000000   0.459054000000000   0.454312000000000 &#xA; P   0.440175000000000   0.354263000000000   0.367464000000000 &#xA; P   0.445543000000000   0.367260000000000   0.559101000000000 &#xA; P   0.455293000000000   0.551606000000000   0.354347000000000 &#xA; P   0.454803000000000   0.563518000000000   0.546515000000000 &#xA; P   0.348592000000000   0.457212000000000   0.361770000000000 &#xA; P   0.351886000000000   0.472249000000000   0.553642000000000 &#xA; P   0.546899000000000   0.448683000000000   0.359923000000000 &#xA; P   0.548477000000000   0.458559000000000   0.552198000000000 &#xA; P   0.341560000000000   0.363924000000000   0.467769000000000 &#xA; P   0.354314000000000   0.565300000000000   0.448689000000000 &#xA; P   0.543486000000000   0.352663000000000   0.460158000000000 &#xA; P   0.556644000000000   0.554867000000000   0.452761000000000 &#xA; H   0.642987000000000   0.469927000000000   0.474034000000000 &#xA; H   0.481225000000000   0.651348000000000   0.464263000000000 &#xA; H   0.255512000000000   0.450777000000000   0.480210000000000 &#xA; H   0.526102000000000   0.358078000000000   0.281589000000000 &#xA; H   0.522877000000000   0.266367000000000   0.377674000000000 &#xA; H   0.360938000000000   0.390592000000000   0.642932000000000 &#xA; H   0.271709000000000   0.550732000000000   0.361406000000000 &#xA; H   0.371546000000000   0.639032000000000   0.354239000000000 &#xA; H   0.367327000000000   0.536759000000000   0.271849000000000 &#xA;&#xA;K_POINTS {automatic}&#xA; 1 1 1  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here the quantum dot has 13 P&lt;span class=&quot;math-container&quot;&gt;$^{-3}$&lt;/span&gt; ions, 16 In&lt;span class=&quot;math-container&quot;&gt;$^{+3}$&lt;/span&gt; ions and 9 H&lt;span class=&quot;math-container&quot;&gt;$^{-}$&lt;/span&gt;. Hence the starting charge.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xVsBY.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xVsBY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I know if the systems are not interacting with each other? The diameter of the system is 8 angstrom and the unit cell&#xA;is cubic with a cell parameter of 28 angstroms&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;NOTE: The convergence of observables w.r.t variation in Cell parameters (as Tristan suggested) is one method. But if there are other more quantifiable methods like calculating the electron density in between two particles in adjacent cells, it would be nice to know :)&lt;/p&gt;&#xA;&lt;p&gt;Thanks in Advance!!&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2021-01-17T10:47:39.813" LastActivityDate="2021-01-17T10:47:39.813" Title="How can I know if 3D aperiodic systems are not interacting with each other using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|quantum-dots|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4147" PostTypeId="2" ParentId="4146" CreationDate="2021-01-17T07:22:44.580" Score="9" Body="&lt;p&gt;Since QE is a planewave based code and we are talking about cells, its important to realize its periodic so its always interacting with itself to some degree.  The only way to check if its sufficiently not interacting is to increase the cell size and see if your property changes.  If it does, repeat again until its converged just like kpoints or energy cutoffs.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-17T07:22:44.580" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4148" PostTypeId="1" AcceptedAnswerId="4178" CreationDate="2021-01-17T18:34:27.080" Score="14" ViewCount="145" Body="&lt;p&gt;Effective Hamiltonians modeling many-layered materials are often tuned using some sort of bias voltage. For instance, in a &lt;span class=&quot;math-container&quot;&gt;$4\times 4$&lt;/span&gt; Hamiltonian matrix to describe biased bilayer graphene using some basis, one often sees &lt;span class=&quot;math-container&quot;&gt;$diag(-U,-U,+U,+U)$&lt;/span&gt; added. By doing this, the (1,1) matrix element has &lt;span class=&quot;math-container&quot;&gt;$-U$&lt;/span&gt; added to it, the (3,3) matrix element has &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;, and so on. Tuning &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; can cause interesting phenomena, such as bandgap closing, etc. The physical justification for using &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; requires the presence of more than one layer: &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; can act as a bias voltage, for example, that modifies the coupling between the two layers and the four energy bands.&lt;/p&gt;&#xA;&lt;p&gt;Now, my question is: What is the physical justification/consequence of using such a parameter in a monolayer model? I was reading Ref. [1], which gives a &amp;quot;Three-band tight-binding model for monolayers of group-VIB transition metal dichalcogenides&amp;quot;.&#xA;Can I use a similar parameter &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; - such as &lt;span class=&quot;math-container&quot;&gt;$diag(-U,+U,+U)$&lt;/span&gt; or some other variant - in this case as well? Numerically, doing this will modify the band structure, but what does this correspond to physically? We don't have multiple layers in this case, and so the idea of the bias voltages tuning interlayer properties is not applicable here. So, I am trying to understand what exactly altering the diagonal means physically (what changes in the model besides the diagonal? is this a known experimental procedure?).&lt;/p&gt;&#xA;&lt;p&gt;I am relatively new to this field and I still do not understand the orbital bases used in Ref. [1] too well. However, based on Eqs. 5,8 and 9, it seems as if there is a constant material-dependent parameter added to the diagonal already &lt;span class=&quot;math-container&quot;&gt;$diag(\epsilon_1,\epsilon_2,\epsilon_2)$&lt;/span&gt;. But I am not sure what these &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt; correspond to physically, or mean. It feels as if these parameters can move the high-symmetry points around because I think they might be some sort of hopping, but this is just a guess.&lt;/p&gt;&#xA;&lt;p&gt;Any intuition will be appreciated!&lt;/p&gt;&#xA;&lt;p&gt;EDIT: After months, the comment+answer makes sense to me now.&lt;/p&gt;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://arxiv.org/abs/1305.6089&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/1305.6089&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-09-27T17:09:48.890" LastActivityDate="2021-09-27T17:09:48.890" Title="What are the physical consequences of adding a constant to the diagonal of the effective Hamiltonian of monolayer materials?" Tags="|density-functional-theory|condensed-matter|basis-sets|model-hamiltonians|physical-properties-of-materials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4149" PostTypeId="1" CreationDate="2021-01-18T16:03:47.977" Score="10" ViewCount="1286" Body="&lt;p&gt;I have just implemented VASP code with Gamma K-point, POSCAR of 128-atom supercell and INCAR like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   ISTART = 2&#xA;   ISPIN  = 2&#xA;   ICHARG = 1&#xA;   MAGMOM = 2*3 27*4 3 2*4 64*0 29*0&#xA;   ISMEAR = 0&#xA;   SIGMA  = 0.05&#xA;   NELMIN = 3&#xA;   NELM   = 60&#xA;   EDIFF  = 1E-05&#xA;   ISIF   = 2&#xA;   NSW    = 60&#xA;   IBRION = 3&#xA;   POTIM  = 0.1&#xA;   EDIFFG =-E-02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The problem is when the electronic relaxation reaches EDIFF, the electronic step does not stop. I just wonder if there is any other convergence requirement needed to be reached so that the electronic relaxation step stops.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7Syqc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7Syqc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/7LHb2.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7LHb2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2021-01-19T01:46:42.940" LastActivityDate="2021-01-19T03:45:32.563" Title="Why does the VASP electronic step not stop after getting converged?" Tags="|vasp|numerical-convergence|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4150" PostTypeId="2" ParentId="4149" CreationDate="2021-01-18T16:38:04.010" Score="6" Body="&lt;p&gt;It is not converged, it needs to hit &lt;code&gt;|-1E-5|&lt;/code&gt; on the &lt;strong&gt;fourth&lt;/strong&gt; and &lt;strong&gt;fifth&lt;/strong&gt; column.  It gets close on the fifth column, but never quite makes it there.  The lowest I see is about &lt;code&gt;|-1.7E-5|&lt;/code&gt;.  It seems to be struggling, if this isn't an optimized structure then you could lower &lt;code&gt;EDIFF&lt;/code&gt; to &lt;code&gt;1E-4&lt;/code&gt; or even &lt;code&gt;5E-4&lt;/code&gt; for some initial steps...Or simply do not worry about it and continue on regardless, over time you will converge faster with each geometric step.&lt;/p&gt;&#xA;&lt;p&gt;However, if this is a single point job then you might need to change to &lt;code&gt;ALGO=ALL&lt;/code&gt; for more stable convergence or change mixing settings.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2021-01-19T03:45:32.563" LastActivityDate="2021-01-19T03:45:32.563" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4151" PostTypeId="2" ParentId="4143" CreationDate="2021-01-18T23:14:33.007" Score="9" Body="&lt;p&gt;What you're describing is very common, and is not limited to GAMESS and Q-Chem.&lt;/p&gt;&#xA;&lt;p&gt;First, here's how to do it in MOLPRO, MRCC, GAMESS, Q-Chem (in fact the only electronic structure software that I regularly use which doesn't allow this type of projection into a bigger basis set, is CFOUR):&lt;/p&gt;&#xA;&lt;h3&gt;1) MOLPRO:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;basis=cc-pVDZ&#xA;hf           &#xA;basis=cc-pVQZ&#xA;hf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The HF calculation with the QZ basis set will be done wtih an initial guess taken from the DZ basis set. The manual might not say what is exactly happening, but it's likely to be very similar to what is done in MRCC and Q-Chem, which is to use the &lt;strong&gt;density&lt;/strong&gt; obtained from the previous SCF calculation (see below).&lt;/p&gt;&#xA;&lt;h3&gt;2) MRCC:&lt;/h3&gt;&#xA;&lt;p&gt;Do your calculation with the smaller basis set, such as cc-pVDZ, then &lt;strong&gt;save the &lt;code&gt;SCFDENSITIES&lt;/code&gt; and &lt;code&gt;VARS&lt;/code&gt;&lt;/strong&gt; files and make sure they're in the folder when you're running the calculation with the bigger basis set, such as cc-pVQZ, and used the keyword &lt;code&gt;scfiguess=restart&lt;/code&gt; which means &amp;quot;SCF initial guess&amp;quot; is restarted from the &lt;code&gt;SCFDENSITIES&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;Also it seems in the &lt;a href=&quot;https://www.mrcc.hu/MRCC/manual/pdf/manual.pdf&quot; rel=&quot;noreferrer&quot;&gt;2020 manual&lt;/a&gt; that there is now a new way to do it:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;To restart an SCF calculation with the cc-pVQZ basis set from the&#xA;densities obtained with the cc-pVDZ basis give: &lt;br&gt;&#xA;&lt;code&gt;basis=cc-pVQZ&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;basis_sm=cc-pVDZ&lt;/code&gt;&lt;br&gt;&#xA;&lt;code&gt;scfiguess=small&lt;/code&gt;&amp;quot;&lt;br&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;3) GAMESS(US):&lt;/h3&gt;&#xA;&lt;p&gt;You already mentioned to add: &lt;code&gt;GUESS=RDMINI&lt;/code&gt; to the &lt;code&gt;GUESS=RDMINI&lt;/code&gt;&lt;/p&gt;&#xA;&lt;h3&gt;4) Q-Chem:&lt;/h3&gt;&#xA;&lt;p&gt;As with the first method I suggested with MRCC, do the calculation in the smaller basis set, then run a new calculation with the bigger basis set and the keyword &lt;code&gt;SCF_GUESS = READ&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another way is to use (as mentioned in the link you provided) the keyword &lt;code&gt;BASIS2&lt;/code&gt; to give the name of the &lt;em&gt;&lt;strong&gt;smaller&lt;/strong&gt;&lt;/em&gt; basis set that you want to use, then you have the option of either using &lt;code&gt;BASISPROJTYPE=FOPPROJECTION&lt;/code&gt; (if you want to expand the MOs from the BASIS2 calculation into the larger basis) &lt;code&gt;BASISPROJTYPE=OVPROJECTION&lt;/code&gt; (if you want to construct the Fock matrix in the larger basis set using the density matrix of the initial, smaller basis set, which is what the MRCC manual says that MRCC does, then diagonalize the density matrix in the larger basis to obtain the natural orbitals as an initial guess for the SCF calculation in the larger basis).&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here's some references related to your question, that you may find helpful and/or interesting:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;This 1973 paper by William Fink: &amp;quot;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.560070602&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Projection between basis sets: A means of defining the electronic structure of functional subunits&amp;quot;&lt;/a&gt; explains a way to do basis set projection involving an &lt;strong&gt;orthogonal basis set&lt;/strong&gt;, then gives an example where a representation is obtained for a methyl group, from the result of an SCF calculation on methane.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This more recent 2014 paper by Soriano and Palacios: &lt;a href=&quot;https://arxiv.org/abs/1404.2043&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Theory of projections with non-orthogonal basis sets: Partitioning techniques and effective Hamiltonians&amp;quot;&lt;/a&gt; may shed some light for you for non-orthogonal bases.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;While this is a purely linear algebra perspective with no chemistry context, and is for projections onto &lt;em&gt;subspaces&lt;/em&gt;, you may still learn a lot from this Khan Academy lesson &lt;a href=&quot;https://www.khanacademy.org/math/linear-algebra/alternate-bases/orthonormal-basis/v/lin-alg-projections-onto-subspaces-with-orthonormal-bases&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Projections onto subspaces with orthonormal bases&amp;quot;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-19T03:40:44.330" LastActivityDate="2021-01-19T03:40:44.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4152" PostTypeId="1" AcceptedAnswerId="4153" CreationDate="2021-01-19T01:48:58.460" Score="9" ViewCount="951" Body="&lt;p&gt;I'm trying to study a Yb-Ge-Sb compound and would like to include spin-orbit coupling (SOC). In Quantum ESPRESSO, this is done by including the following tags in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; name list.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lspinorb = .true.&#xA;noncolin = .true.&#xA;starting_magnetization = 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;But in the case of the pseudo-potentials included, should I use fully relativistic pseudo-potentials for all the three elements?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;NOTE:  As per the materials project repository, the compound is non-magnetic.&lt;/p&gt;&#xA;" OwnerUserId="1491" LastEditorUserId="5" LastEditDate="2021-01-19T05:32:33.207" LastActivityDate="2021-01-22T20:07:42.197" Title="For which elements should I include spin orbit coupling in Quantum ESPRESSO?" Tags="|quantum-espresso|pseudopotentials|spin-orbit-coupling|relativistic|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4153" PostTypeId="2" ParentId="4152" CreationDate="2021-01-19T01:56:31.450" Score="9" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;But in the case of the pseudo-potentials included, should I use fully relativistic pseudopotentials for all three elements?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, you should use the fully relativistic pseudopotentials if you are considering spin-orbit coupling calculations.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When you should consider spin-orbit coupling?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If the investigated materials contain heavy atoms then you should consider spin-orbit coupling. This is irrelevant to its magnetic properties.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-19T01:56:31.450" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4154" PostTypeId="1" CreationDate="2021-01-19T04:02:07.620" Score="12" ViewCount="738" Body="&lt;p&gt;I am a grad student looking to simulate several XAS/XES and potentially RIXS spectra for some strongly correlated metal-oxides. The materials in question will likely require solving the Bethe-Salpeter equation in order to fully describe the many body effects.&lt;/p&gt;&#xA;&lt;p&gt;I was thinking to use OCEAN() to do this but the installation on the computing cluster I have been using is having a few problems with regards to running scripts that I just don't seem to be able to get over, such as not running DFT calculations in ABINIT in parallel, despite the flag being given for &lt;code&gt;mpirun -n N&lt;/code&gt; parallelism.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, a friend of mine has used Quantum ESPRESSO and we are both somewhat familiar with it. Can someone give me advice as to whether QE's &lt;code&gt;XSPECTRA.x&lt;/code&gt; or Ocean would be better for getting into XAS/XES calculations? I am willing to learn either one, but I would appreciate using the one with the easiest learning curve.&lt;/p&gt;&#xA;" OwnerUserId="1941" LastEditorUserId="5" LastEditDate="2022-01-13T01:00:08.283" LastActivityDate="2023-11-11T12:47:31.930" Title="Recommended code to do XAS/XES/RIXS calculations with?" Tags="|quantum-espresso|software-recommendations|spectroscopy|gw-bse|abinit|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4155" PostTypeId="2" ParentId="4152" CreationDate="2021-01-19T05:40:17.473" Score="10" Body="&lt;p&gt;Spin-orbit coupling is related to &lt;em&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Relativistic_quantum_chemistry&quot; rel=&quot;noreferrer&quot;&gt;relativity&lt;/a&gt;&lt;/em&gt; which is increasingly important for heavier elements.&lt;/p&gt;&#xA;&lt;p&gt;If you're aiming for ultra-high precision, as in this post on our site: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/554/5&quot;&gt;How accurate are the most accurate calculations?&lt;/a&gt;, you will need to include every possible effect, including spin-orbit coupling, for all elements including hydrogen.&lt;/p&gt;&#xA;&lt;p&gt;For most applications, one rule-of-thumb (which is still quite &lt;em&gt;ad hoc&lt;/em&gt;) is that relativity becomes important for elements around Krypton (element #36) and onward. This would mean that Yb and Sb would &lt;em&gt;&lt;strong&gt;most certainly&lt;/strong&gt;&lt;/em&gt; need to be treated relativistically, and it would also be wise to treat Ge (element #32) relativistically if this is within your means.&lt;/p&gt;&#xA;&lt;p&gt;What do I recommend? &lt;br&gt;&#xA;Include spin-orbit coupling for all three of those elements because Yb and Sb are considered to be &lt;em&gt;highly&lt;/em&gt; reltivistic, and you might as well include SO coupling for Ge too since it's also fairly heavy and you're already treating the other two elements with SO coupling.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-01-19T05:40:17.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4157" PostTypeId="1" CreationDate="2021-01-19T11:47:28.890" Score="5" ViewCount="157" Body="&lt;p&gt;I'm a beginner in DFT and Im using quantum espreso.&lt;/p&gt;&#xA;&lt;p&gt;I've seen the difference of &lt;strong&gt;hydrostatic pressure&lt;/strong&gt; being used as a criteria for converging my &lt;strong&gt;k-point grid&lt;/strong&gt; and &lt;strong&gt;plane-wave cut-off&lt;/strong&gt; values.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know the accepted threshold of &lt;strong&gt;Hydrostatic pressure&lt;/strong&gt; (in kbar  [as in quantum espresso]) difference used as a convergence criteria.&lt;/p&gt;&#xA;" OwnerUserId="1491" LastActivityDate="2021-01-19T11:47:28.890" Title="At what threshold would I assure convergence?" Tags="|density-functional-theory|quantum-espresso|convergence-test|" AnswerCount="0" CommentCount="3" ClosedDate="2021-06-23T21:49:46.007" ContentLicense="CC BY-SA 4.0" />
  <row Id="4158" PostTypeId="1" CreationDate="2021-01-19T12:01:59.353" Score="7" ViewCount="343" Body="&lt;p&gt;I was searching for a local-orbital ab-initio tight binding implementation of molecular dynamics and Ive found a code called &lt;a href=&quot;https://sites.google.com/site/fireballofficialsite/&quot; rel=&quot;nofollow noreferrer&quot;&gt;fireball&lt;/a&gt;. Ive tried to compile it but the code seems to be buggy and there is no manual.&lt;/p&gt;&#xA;&lt;p&gt;Is there any code similar to the one mentioned above?&lt;/p&gt;&#xA;" OwnerUserId="1491" LastEditorUserId="142" LastEditDate="2021-01-20T17:57:06.500" LastActivityDate="2021-01-29T11:47:22.640" Title="Is there any code for local-orbital ab initio tight binding molecular dynamics other than fireball?" Tags="|density-functional-theory|software|reference-request|software-recommendations|" AnswerCount="0" CommentCount="6" ClosedDate="2021-06-23T21:44:09.777" ContentLicense="CC BY-SA 4.0" />
  <row Id="4159" PostTypeId="1" AcceptedAnswerId="4179" CreationDate="2021-01-19T14:05:37.253" Score="5" ViewCount="194" Body="&lt;p&gt;In condensed matter physics, a &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_spin_liquid#:%7E:text=In%20condensed%20matter%20physics%2C%20a,absence%20of%20ordinary%20magnetic%20order.&quot; rel=&quot;noreferrer&quot;&gt;quantum spin liquid&lt;/a&gt; is a phase of matter that can be formed by interacting quantum spins in certain magnetic materials.&lt;/p&gt;&#xA;&lt;p&gt;The novel concept has been realized in many quantum materials, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;1T-TaS2 with triangular lattice.&lt;/li&gt;&#xA;&lt;li&gt;Rb2Cu3SnF12 with Kagome.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My question is can we find materials with spin liquid properties just based on DFT calculations?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-20T19:09:38.940" Title="How to predict spin liquid materials with DFT?" Tags="|density-functional-theory|materials-design|spin|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4160" PostTypeId="1" AcceptedAnswerId="4175" CreationDate="2021-01-19T15:16:59.263" Score="4" ViewCount="146" Body="&lt;p&gt;I'm investigating reaction mechanism and I want to calculate energies of my reagents, products and TS on a higher level of theory than I use for the geometries and frequencies.&lt;/p&gt;&#xA;&lt;p&gt;I'm thinking about MP2, but I've read that is has significant basis set dependence and it's advised to investigate convergence to CBS limit. Can I use double-hybrid DFT as a substituent, as far as I understand they aren't so basis set dependent?&lt;/p&gt;&#xA;&lt;p&gt;Is basis set dependence a thing to consider for regular mechanistic calculations that aren't pretending to be quantitative?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-01-20T17:56:16.603" Title="Using double-hybrid functional instead of MP2 to avoid basis set dependence" Tags="|density-functional-theory|reaction-mechanism|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="4162" PostTypeId="1" CreationDate="2021-01-19T15:55:27.560" Score="6" ViewCount="620" Body="&lt;p&gt;I have seen specific ways of constructing input files for&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3685/how-to-model-an-anti-ferromagnetic-crystal-in-quantum-espresso-properly&quot;&gt;Anti-ferromagnetic materials&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3872/is-the-final-magnetic-moment-in-the-materials-project-repository-same-as-the&quot;&gt;Ferromagnetic materials&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I represent a paramagnetic material in plane wave DFT codes like Quantum ESPRESSO. Do we assign opposite moments with different magnitudes? Or we do we assume the material to be Non-magnetic?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="1944" LastEditDate="2021-01-19T16:35:26.027" LastActivityDate="2021-01-19T19:58:52.917" Title="How can I properly represent paramagnetic materials in DFT calculations?" Tags="|reference-request|quantum-espresso|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4163" PostTypeId="1" AcceptedAnswerId="4166" CreationDate="2021-01-19T19:27:38.207" Score="11" ViewCount="1433" Body="&lt;p&gt;How to generate or create the correct &lt;code&gt;KPOINTS&lt;/code&gt; ( K-PATH) file for a 4x4x1 supercell bandstructure calculation ? Is there a software compatible with vasp can do that ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-01-20T18:55:23.120" Title="How to create a KPOINTS file (k-path) for 4x4x1 supercell bandstructure calculation?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4164" PostTypeId="2" ParentId="4162" CreationDate="2021-01-19T19:58:52.917" Score="5" Body="&lt;p&gt;Paramagnetic materials have fluctuating magnetic moments that cannot be described using density functional theory. They can be properly described using, for example, dynamical mean-field theory.&lt;/p&gt;&#xA;&lt;p&gt;Having said this, a typical approach to model paramagnetism in DFT is to build a large supercell of the material and to place randomly oriented magnetic moments on each atom. I have never explored these calculations in detail, so others may be able to comment on the merits of this approximation.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-01-19T19:58:52.917" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4165" PostTypeId="1" AcceptedAnswerId="4168" CreationDate="2021-01-20T00:23:03.807" Score="6" ViewCount="208" Body="&lt;p&gt;Anyone here uses Quantum Espresso through Maestro can tell me a bit more about the calculation panel setting:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2vDvv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2vDvv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I understand that &lt;code&gt;-npools&lt;/code&gt; option must be divisible by the number of processors (threads). But I don't really understand the &lt;code&gt;-ntg&lt;/code&gt; option. I am running some geometry optimization with &lt;span class=&quot;math-container&quot;&gt;$4 \times 4 \times 1$&lt;/span&gt; kpoints but certain setting cause the calculation to fail. The job will get submitted, but I would get back an error like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine divide_et_impera (1):&#xA;     some nodes have no k-points&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does &lt;code&gt;-ntg&lt;/code&gt; depend on the number of kpoints you use? And if you can also tell me how much more the &lt;code&gt;simultaneous jobs&lt;/code&gt; options speed up the calculation then that would be greatly appreciated! I have tried to increase the &lt;code&gt;simultaneous jobs&lt;/code&gt; but it doesn't seems to really speed up the calculation... maybe it has to do with how I specified other paramters (-npool, -ntg, etc. )&lt;/p&gt;&#xA;&lt;br&gt; &#xA;&lt;p&gt;I am trying to find the best way to speed-up the calculation, but so far it has been trials and errors. I would like to understand this setting more, and know how to speed-up my calculation.&lt;/p&gt;&#xA;" OwnerUserId="1711" LastEditorUserId="1711" LastEditDate="2021-01-20T00:39:04.050" LastActivityDate="2021-01-20T12:13:39.513" Title="Understanding QuantumEspresso Toolbox through Maestro" Tags="|software|quantum-espresso|high-performance-computing|geometry-optimization|schrodinger-software|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4166" PostTypeId="2" ParentId="4163" CreationDate="2021-01-20T00:37:14.153" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Is there a software compatible with VASP that can do that?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can use &lt;a href=&quot;http://vaspkit.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT tool&lt;/a&gt;, which can read your POSCAR to generate a k-path for the band structure plot. [vaspkit&lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt;3&lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt;302].&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to generate or create the correct KPOINTS ( K-PATH) file for a 4x4x1 supercell bandstructure calculation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Except for the VASPKIT tool, you can use this online k-path generator (Of course, you should tell it what your structure is):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://materials.duke.edu/awrapper.html&quot; rel=&quot;noreferrer&quot;&gt;http://materials.duke.edu/awrapper.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-20T01:21:15.153" LastActivityDate="2021-01-20T01:21:15.153" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4167" PostTypeId="1" CreationDate="2021-01-20T08:12:45.697" Score="16" ViewCount="349" Body="&lt;p&gt;I want to calculate the Chern number of a surface of 3D time reversal insulator. I know the 3D topological insulator is characterized by the Z2 index annd that the Chern number can be used to characterize the 2D cases and see whether the system has non trivial edge state if it broke the time reversal symmetry. But is it possible if I want the calculate the Chern number of a specific 2D plane in Brillouin zone of a 3D structure?&lt;/p&gt;&#xA;&lt;p&gt;The reason why I ask this is because I wrote a code to calculate Chern number of specific plane in brillouin zone of a 3D tight-binding structure from Wannier90 (I used the &lt;code&gt;wannier90_hr.dat&lt;/code&gt; file to generate the tight binding matrix and solve the eigenvector directly to calculate the chern number).&lt;/p&gt;&#xA;&lt;p&gt;Since the system is time reversal invariant, I expected that the Chern number should be equal to 0 in every plane of the Brillouin zone. I found some non integer nonsense result, but when I work my code in 2D model, I found it is completely correct. So I’m thinking whether my concept is wrong, whether it is nonsense to use this calculation on 2D plane of a 3D structure.&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="7" LastEditDate="2022-01-13T02:13:39.680" LastActivityDate="2022-01-13T02:13:39.680" Title="Calculating the Chern number on a 2D surface of a 3D insulator" Tags="|band-structure|topological-insulators|tight-binding|wannier90|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4168" PostTypeId="2" ParentId="4165" CreationDate="2021-01-20T12:13:39.513" Score="3" Body="&lt;p&gt;From the MAESTRO help system we got that the calculation is run using the driver &lt;strong&gt;periodic_dft_driver.py&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;usage: $SCHRODINGER/run periodic_dft_gui_dir/periodic_dft_driver.py&#xA;       [-h] -cfg_file CFG_FILE [-TPP THREADS] [-nimage NIMAGE]&#xA;       [-npools NPOOLS] [-ntg NTG | -nband NBAND] [-qargs QARGS]&#xA;       [-HOST &amp;lt;hostname&amp;gt;]&#xA;       input_file&#xA;&#xA;Driver that runs Quantum ESPRESSO workflows. Copyright Schrodinger, LLC. All&#xA;rights reserved.&#xA;&#xA;positional arguments:&#xA;  input_file          Input structures.&#xA;&#xA;optional arguments:&#xA;  -h, -help           Show this help message and exit.&#xA;  -cfg_file CFG_FILE  Path to the config file. (default: None)&#xA;  -TPP THREADS        Number of threads to use for each job. (default: 1)&#xA;  -qargs QARGS        Set arguments to pass to the queue manager. (default:&#xA;                      None)&#xA;&#xA;Quantum ESPRESSO parallel options:&#xA;  -nimage NIMAGE      Number of images (points in the configuration space)&#xA;                      (default: 1)&#xA;  -npools NPOOLS      Number of K-point groups to run in parallel (default: 1)&#xA;  -ntg NTG            Number of task groups to run in parallel (default: None)&#xA;  -nband NBAND        Number of bands to run in parallel (default: None)&#xA;&#xA;Job Control Options:&#xA;  -HOST &amp;lt;hostname&amp;gt;    Run job remotely on the indicated host entry. (default:&#xA;                      localhost)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Look for slides 10-21 for parallel options in &lt;a href=&quot;https://materials.prace-ri.eu/497/7/QE__main_strategies_of_parallelization_and_levels_of_parallelisms.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; document.&lt;/p&gt;&#xA;&lt;h3&gt;About k-points and &lt;span class=&quot;math-container&quot;&gt;$n_{pools}$&lt;/span&gt;:&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;k-point parallelization&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the simulation consists in different k-points, those can be distributed among &lt;span class=&quot;math-container&quot;&gt;$n_{pools}$&lt;/span&gt; pools of CPUs.&lt;/p&gt;&#xA;&lt;p&gt;K-points are typically independents: the amount of communications is small&lt;/p&gt;&#xA;&lt;p&gt;When there is a large number of k-points this layer can strongly enhance&#xA;the scalability&lt;/p&gt;&#xA;&lt;p&gt;By definition, &lt;span class=&quot;math-container&quot;&gt;$n_{pools}$&lt;/span&gt; must be a divisor of the total&#xA;number of k-points:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mpirun –np 64 pw.x –npool 4 –input inputfile.inp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;About task-group parallelization and &lt;span class=&quot;math-container&quot;&gt;$ntg$&lt;/span&gt;&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Each plane-wave group of processors is split into &lt;span class=&quot;math-container&quot;&gt;$n_{task}$&lt;/span&gt; task groups of &lt;span class=&quot;math-container&quot;&gt;$n_{FFT}$&lt;/span&gt; processors, with &lt;span class=&quot;math-container&quot;&gt;$n_{task} \times n_{FFT}= n_{PW}$&lt;/span&gt;;&lt;/p&gt;&#xA;&lt;p&gt;each task group takes care of the FFT over &lt;span class=&quot;math-container&quot;&gt;$N_e/n_t$&lt;/span&gt; states.&lt;/p&gt;&#xA;&lt;p&gt;Used to extend scalability of FFT parallelization.&lt;/p&gt;&#xA;&lt;p&gt;Example for 1024 processors&#xA;–divided into &lt;span class=&quot;math-container&quot;&gt;$n_{pool}= 4$&lt;/span&gt; pools of &lt;span class=&quot;math-container&quot;&gt;$n_{PW} = 256$&lt;/span&gt; processors,&#xA;–divided into &lt;span class=&quot;math-container&quot;&gt;$n_{task} = 8$&lt;/span&gt; tasks of &lt;span class=&quot;math-container&quot;&gt;$n_{FFT} = 32$&lt;/span&gt; processors each;&#xA;–Subspace diagonalization performed on a subgroup of &lt;span class=&quot;math-container&quot;&gt;$n_{diag} = 144$&lt;/span&gt; processors:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mpirun –np 1024 pw.x –npool 4 –ntg 8 –ndiag 144 –input inputfile.inp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;About speeding up your calculations, the last 4 slides are about the QE scalability and &lt;a href=&quot;http://www.max-centre.eu/codes-max/quantum-espresso&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; link can help.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-20T12:13:39.513" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4169" PostTypeId="1" AcceptedAnswerId="4171" CreationDate="2021-01-20T14:24:02.727" Score="11" ViewCount="957" Body="&lt;p&gt;&lt;strong&gt;The first Hohenberg-Kohn (HK) theorem&lt;/strong&gt;: The external potential &lt;span class=&quot;math-container&quot;&gt;$v(\vec{r})$&lt;/span&gt; is determined, within a trivial additive constant, by the ground-state electron density &lt;span class=&quot;math-container&quot;&gt;$\rho(\vec{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From basic quantum mechanics, we know that: &lt;span class=&quot;math-container&quot;&gt;$v(\vec{r})\rightarrow \hat{H} \rightarrow \psi_0\rightarrow \rho$&lt;/span&gt;. Accoridng to the first HK theorem, we can further know that &lt;span class=&quot;math-container&quot;&gt;$\rho \rightarrow v(\vec{r})\rightarrow \hat{H} \rightarrow \psi_0,\psi_1,\cdots$&lt;/span&gt;. In essence, the first HK theorem proves one-to-one mapping between the external potentials and the ground-state densities &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; in many-electron systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The second HK theorem&lt;/strong&gt;: There exists a universal functional of the density, &lt;span class=&quot;math-container&quot;&gt;$F_{HK}[\rho']$&lt;/span&gt;, such that for any &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representable density (&lt;span class=&quot;math-container&quot;&gt;$\textit{i.e.}$&lt;/span&gt;, any density that comes from some wavefunction for an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron system) &lt;span class=&quot;math-container&quot;&gt;$\rho(\vec{r})$&lt;/span&gt;, which yields a given number of electrons &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, the energy functional is,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E[\rho'] = F_{HK}[\rho']+\int \rho'(\vec{r})v(\vec{r}) d\vec{r} \geq E_g \tag{1} $$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$E_g$&lt;/span&gt; is the ground-state energy and the equality holds when the density &lt;span class=&quot;math-container&quot;&gt;$\rho'(\vec{r})$&lt;/span&gt; is the, possibly degenerate, ground-state density &lt;span class=&quot;math-container&quot;&gt;$\rho_0'(\vec{r})$&lt;/span&gt; for the external potential &lt;span class=&quot;math-container&quot;&gt;$v(\vec{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From the two statements, I can't see any connection between the two theorems. So what's the relation between the two theorems? If &lt;span class=&quot;math-container&quot;&gt;$F_{HK}(\rho')$&lt;/span&gt; is the functional of the ground-state density, I can build a connection between the two theorems. But the density in &lt;span class=&quot;math-container&quot;&gt;$F_{HK}[\rho]$&lt;/span&gt; is not necessary ground-state density.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;About the first HK theorem:&#xA;&lt;a href=&quot;http://unige.ch/sciences/chifi/wesolowski/public_html/dft_epfl_2016/part_I/dftepfl_part_II.pdf&quot; rel=&quot;noreferrer&quot;&gt;http://unige.ch/sciences/chifi/wesolowski/public_html/dft_epfl_2016/part_I/dftepfl_part_II.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;About the second HK theorem: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B9780128136515000048?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/B9780128136515000048?via%3Dihub&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-21T01:40:38.420" LastActivityDate="2021-01-21T01:40:38.420" Title="What's the relationship between the first HK theorem and the second HK theorem?" Tags="|density-functional-theory|kohn-sham|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4170" PostTypeId="2" ParentId="4169" CreationDate="2021-01-20T16:00:39.580" Score="6" Body="&lt;p&gt;A formal connection is that the first theorem is used in the proof of the second one. Indeed, the second is a translation of the principle that &lt;span class=&quot;math-container&quot;&gt;$E[\Psi']$&lt;/span&gt; has a minimum at the correct ground state wave function &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;, using the one-to-one correspondence &lt;span class=&quot;math-container&quot;&gt;$\rho \leftrightarrow \Psi$&lt;/span&gt; known from the first theorem.&lt;/p&gt;&#xA;&lt;p&gt;The derivation can be found in the &lt;a href=&quot;https://journals.aps.org/pr/pdf/10.1103/PhysRev.136.B864&quot; rel=&quot;noreferrer&quot;&gt;original paper by Kohn and Hohenberg&lt;/a&gt; (part I-2.). It's quite short and easy to read, so it's worth a look.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-01-20T16:00:39.580" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4171" PostTypeId="2" ParentId="4169" CreationDate="2021-01-20T16:03:12.653" Score="11" Body="&lt;p&gt;Using your notation, the definition for the universal functional is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{HK}[\rho] = \left&amp;lt; \psi_0[\rho] \right| \hat{T} + \hat{W} \left| \psi_0[\rho] \right&amp;gt;,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{W}$&lt;/span&gt; are kinetic and electron-electron interaction operators, respectively. This definition is possible because of the one-to-one mapping between densities and their corresponding ground state wavefunctions (i.e., because &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt; is a functional of &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;), which I believe is the connection you are seeking.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-01-20T16:14:39.907" LastActivityDate="2021-01-20T16:14:39.907" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4172" PostTypeId="2" ParentId="4163" CreationDate="2021-01-20T16:36:01.890" Score="10" Body="&lt;p&gt;Imagine that we have a supercell that is related to a primitive cell by the following supercell matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}\tag{1}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33} \\&#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Consider a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point with coordinates &lt;span class=&quot;math-container&quot;&gt;$(k_{p_1},k_{p_2},k_{p_3})$&lt;/span&gt; in terms of primitive cell reciprocal lattice vectors. Then the same &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point in terms of the supercell reciprocal lattice vectors has the following coordinates:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}\tag{2}&#xA;k_{s_1} \\&#xA;k_{s_2} \\&#xA;k_{s_3}&#xA;\end{pmatrix}=&#xA;\begin{pmatrix}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33} \\&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;k_{p_1} \\&#xA;k_{p_2} \\&#xA;k_{p_3}&#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore, if you want to have the same path as you had in the primitive cell, you need to apply the correct supercell matrix to the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in the original path. In your case, the supercell matrix is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}\tag{3}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33} \\&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;4 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; 4 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 1 \\&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;so all you need to do is to multiply the first two coordinates of every &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point by &lt;span class=&quot;math-container&quot;&gt;$4$&lt;/span&gt;, and leave the third one unchanged. From a more conceptual point of view, when you build a supercell in real space, then the Brillouin zone in reciprocal space is correspondingly smaller. This means that in terms of the reciprocal lattice vectors of the supercell Brillouin zone, you need to travel further to get to the same point.&lt;/p&gt;&#xA;&lt;p&gt;The resulting band structure will now cover the same path as that covered by the original primitive cell band structure. You will get the original bands you had and, due to band folding in the supercell, you will get a large number of additional bands.&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2021-01-20T18:55:23.120" LastActivityDate="2021-01-20T18:55:23.120" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4173" PostTypeId="2" ParentId="4143" CreationDate="2021-01-20T17:45:03.423" Score="5" Body="&lt;p&gt;&lt;strong&gt;Note&lt;/strong&gt;: I have corrected some omissions from my initial answer to avoid any confusion. For a rigorous explanation of the process, I would recommend looking at Susi's answer.&lt;/p&gt;&#xA;&lt;p&gt;The projection process for MOs is actually fairly straightforward. In the following, let &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; be the dimension of the new basis, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; the dimension of the old. Even though getting a guess should only require projecting the occupied orbitals, I will show the steps assuming you are projecting all the MOs.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Projection &lt;span class=&quot;math-container&quot;&gt;$$\mathbf{C}_{\text{new}(m\times n)}=\mathbf{S}^{-1}_{\text{new}(m\times m)}\mathbf{M}_{(m\times n)}\mathbf{C}_{\text{old}(n\times n)}$$&lt;/span&gt; Here &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}$&lt;/span&gt; is the mixed overlap matrix for the two bases, i.e. &lt;span class=&quot;math-container&quot;&gt;$M_{ij}=\langle\psi_i|\phi_j\rangle$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; functions in the new basis and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; in the old. I don't have a full explanation of why this gives the least-squares projection, but it makes a certain amount of intuitive sense: the mixed overlap tells you how similar elements of each basis are, so this should say roughly say how much of the space of an old basis function is represented by a new basis function. In Gaussian, a matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{U}$&lt;/span&gt; is also left multiplied in this transformation. This matrix is derived from a Cholesky decomposition and is used to remove linear dependencies from the new basis.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Orthogonalization &lt;span class=&quot;math-container&quot;&gt;$$\mathbf{C}'_{\text{new}(m\times n)}=\mathbf{C}_{\text{new}(m\times n)}\mathbf{Q}^{-1/2}_{\text{new}(n\times n)}$$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$$\mathbf{Q}=\mathbf{C}^T_{\text{new}(n\times m)}\mathbf{C}_{\text{new}(m\times n)}$$&lt;/span&gt;&#xA;This step ensures the new MOs are orthogonal to each other (try multiplying out &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}'^T\mathbf{C}'$&lt;/span&gt; to see that it gives the identity matrix). The reason we form &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt; is that we can't directly form a unique inverse for &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}_\text{new}$&lt;/span&gt; since it is rectangular.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Create additional orbitals:&#xA;If we want to have a full set of &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; MOs for the new basis, we can simply generate  additional orthogonal vectors from the projected orbitals using (for example) Gram-Schmidt orthogonalization.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-01-20T19:10:29.797" LastActivityDate="2021-01-20T19:10:29.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4174" PostTypeId="2" ParentId="392" CreationDate="2021-01-20T17:46:52.383" Score="8" Body="&lt;h1&gt;2020 Furness et al: r&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;SCAN functional&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1192/5&quot;&gt;SCAN functional&lt;/a&gt; is the most recent meta-GGA functional constructed from first principles, which satisfies all known bounds. However, SCAN is also numerically pathological: getting converged energies requires huge quadrature grids, and constructing pseudopotentials is difficult. This motivated the construction of the regularized SCAN (rSCAN) functional of Bartók and Yates in &lt;a href=&quot;https://doi.org/10.1063/1.5094646&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 150, 161101 (2019)&lt;/a&gt;, which eliminated the numerical instabilities in SCAN.&lt;/p&gt;&#xA;&lt;p&gt;The r&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;SCAN functional, published in &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpclett.0c02405&quot; rel=&quot;noreferrer&quot;&gt;J. Phys. Chem. Lett. 11,  8208 (2020)&lt;/a&gt; builds upon rSCAN, but restores some of the exact constraints of SCAN. In addition to being numerically stable and thereby faster than SCAN, r&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;SCAN has been found to yield spectacular performance, see e.g. &lt;a href=&quot;https://chemrxiv.org/articles/preprint/r2SCAN-3c_An_Efficient_Swiss_Army_Knife_Composite_Electronic-Structure_Method/13333520/2&quot; rel=&quot;noreferrer&quot;&gt;recent work by Grimme and coworkers&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-01-20T17:46:52.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4175" PostTypeId="2" ParentId="4160" CreationDate="2021-01-20T17:56:16.603" Score="3" Body="&lt;p&gt;Double hybrids contain MP2 so the basis set dependence is similar to MP2; the only thing you gain is the overall weighting factor that is used to damp the MP2 correction.&lt;/p&gt;&#xA;&lt;p&gt;The reason to use double hybrids is just to get results of better than MP2 quality at a cost similar to MP2. But, in many cases modern range-separated functionals like &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97M-V out-perform double hybrids at a fraction of their cost...&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-01-20T17:56:16.603" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4176" PostTypeId="2" ParentId="4143" CreationDate="2021-01-20T18:21:24.817" Score="8" Body="&lt;p&gt;Supplementing Nike's answer above.. This is actually quite elementary math. Let's say I have an orbital in a basis&#xA;&lt;span class=&quot;math-container&quot;&gt;$|\psi\rangle = \sum_i c_i |i\rangle$&lt;/span&gt; and I want to find the expansion in some other basis set &lt;span class=&quot;math-container&quot;&gt;$|J\rangle$&lt;/span&gt;. How do I do this?&lt;/p&gt;&#xA;&lt;p&gt;In the new basis set, one has the resolution of the identity &lt;span class=&quot;math-container&quot;&gt;$\sum_{JK} |J\rangle \langle J|K\rangle^{-1} \langle K|\approx 1$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\langle J|K\rangle^{-1}$&lt;/span&gt; denotes the element of the (pseudo)inverse overlap matrix. You can just plug this expression into the equation above to get&#xA;&lt;span class=&quot;math-container&quot;&gt;$|\psi\rangle = \sum_i c_i |i\rangle = \sum_{iJK} |J\rangle \langle J|K\rangle^{-1} \langle K| i\rangle = \sum_J c_J |J\rangle $&lt;/span&gt; from which you can read that the expansion coefficients in the new basis are given by &lt;span class=&quot;math-container&quot;&gt;$c_J = \sum_{iK} \langle J|K\rangle^{-1} \langle K| i\rangle c_i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To project a density, you can just project the orbitals one by one with the expression above; you can write this in matrix form as &lt;span class=&quot;math-container&quot;&gt;${\bf C}_1={\bf S}_{11}^{-1}{\bf S}_{12}{\bf C}_2$&lt;/span&gt; where the C's are the matrices of orbital coefficients. The orbitals may no longer be orthonormal as a result of the projection, so typically one reorthonormalizes them in the next phase before building the density matrix in the new basis set.&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;basis set guess&amp;quot; turns out to be of excellent accuracy; for instance, it was the top performer in my recent assessment of self-consistent field guesses, &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 1593 (2019)&lt;/a&gt;, where I used the single-zeta pcseg-0 basis set. If you're trying to do a SCF calculation in a large basis set, you'll probably save quite a lot of computational time by seeding it with a calculation with a smaller, reasonable basis set. (STO-3G, MINI, 3-21G etc may not be good enough for this purpose.)&lt;/p&gt;&#xA;&lt;p&gt;PS. A more elegant approach that doesn't introduce any projection errors is to compute the Fock matrix directly in the new basis with the orbitals expressed in the old basis; this approach described in &lt;a href=&quot;https://doi.org/10.1016/j.cplett.2012.02.012&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Phys. Lett. 531, 229 (2012)&lt;/a&gt; requires the evaluation of cross-basis two-electron integrals which aren't available in most quantum chemistry codes.&lt;/p&gt;&#xA;&lt;p&gt;Addendum 1: as Nike's answer states for Q-Chem, it's also possible to use the approach to project the Fock matrix between basis sets. However, this may lead to odd results. If the new basis is larger than the old one (which is the typical use case), then the null space of the old basis, i.e. any functions in the new basis that can't be represented in the old basis, will yield zero elements in the projected Fock matrix. If you had any orbitals with positive orbital energies in the guess calculation, when you diagonalize the projected Fock operator, you'll actually occupy garbage orbitals, instead, per the Aufbau principle. Projecting the orbitals is thereby a better solution.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-01-22T16:53:16.817" LastActivityDate="2021-01-22T16:53:16.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4177" PostTypeId="1" CreationDate="2021-01-20T18:54:46.023" Score="13" ViewCount="178" Body="&lt;p&gt;I just read &lt;a href=&quot;https://physics.aps.org/articles/v14/s4&quot; rel=&quot;noreferrer&quot;&gt;this synopsis in Physics&lt;/a&gt; where scientists used first-principles nuclear physics calculations to predict the stability of 700 isotopes up to iron.&lt;/p&gt;&#xA;&lt;p&gt;I didn't know that this was possible, especially for elements like iron, which would, as I understand it, a 3D strongly interacting quantum system with 50-60 particles.&lt;/p&gt;&#xA;&lt;p&gt;The article says that &lt;em&gt;ab initio&lt;/em&gt; methods are used for the nuclear physics, but are those related to the &lt;em&gt;ab initio&lt;/em&gt; methods that we use in matter modeling? Or are they just using that term in the more general sense of meaning &amp;quot;from first principles&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-01-20T18:57:38.837" LastActivityDate="2021-01-20T19:44:23.597" Title="Are nuclear ab-initio methods related to materials ab-initio methods?" Tags="|computational-chemistry|ab-initio-calculations|high-performance-computing|computational-frameworks|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4178" PostTypeId="2" ParentId="4148" CreationDate="2021-01-20T19:04:31.107" Score="5" Body="&lt;p&gt;I will assume that we are working with a Hamiltonian in some tight-binding-like position basis (where each row/column in &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is a localized orbital).&lt;/p&gt;&#xA;&lt;p&gt;Essentially the constant you are adding acts as a site-dependent potential. If it's uniform, it has no real effect. You can think of adding a bunch of different &amp;quot;shapes&amp;quot; to the potential to have different effects. For example, if you add a &lt;span class=&quot;math-container&quot;&gt;$-U$&lt;/span&gt; on one site, that's effectively attractive. If you make a pattern like &lt;span class=&quot;math-container&quot;&gt;$+U,-U,+U,-U...$&lt;/span&gt;, you can predispose the system towards some sort of pattern.&lt;/p&gt;&#xA;&lt;p&gt;Physically, these local &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;'s could correspond to any number of things. Defects or substitutions in the lattice could create isolated local potentials. Interactions with a substrate could produce potentials in some pattern. An external electric field could produce a pattern of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;'s that looks like a ramp.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-01-20T19:04:31.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4179" PostTypeId="2" ParentId="4159" CreationDate="2021-01-20T19:09:38.940" Score="3" Body="&lt;p&gt;I suspect this would be very difficult to do with DFT. A spin liquid is a very subtle magnetic state and DFT, as a method, is not usually good at describing the magnetic states of a system. Spin liquids are fairly difficult to understand and characterize even using methods that are specialized for strongly-correlated magnetism (like DMRG or QMC).&lt;/p&gt;&#xA;&lt;p&gt;Where DFT could be &lt;em&gt;useful&lt;/em&gt; is in connecting those specialized simulations, like QMC or DMRG, to an actual material. For example, QMC might be able to tell you what exchange coupling constants are likely to give rise to a spin liquid, and then DFT could help you understand what materials are likely to closely match those coupling constants.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-01-20T19:09:38.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4180" PostTypeId="2" ParentId="4177" CreationDate="2021-01-20T19:44:23.597" Score="11" Body="&lt;p&gt;There is a long history of correlation between &lt;em&gt;ab initio&lt;/em&gt; calculations for nuclear physics and &lt;em&gt;ab initio&lt;/em&gt; calculations for quantum chemistry/materials.&lt;/p&gt;&#xA;&lt;p&gt;Take coupled cluster for example, remembering that a lot of people used to say &amp;quot;CCSD(T) is the gold standard in quantum chemistry&amp;quot;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The method was initially developed by Fritz Coester and Hermann Kümmel&#xA;in the 1950s for studying &lt;strong&gt;nuclear-physics phenomena&lt;/strong&gt;, but became more&#xA;frequently used when in 1966 Jiří Čížek (and later together with Josef&#xA;Paldus) reformulated the method for electron correlation in &lt;strong&gt;atoms and molecules&lt;/strong&gt;. It is now one of the most prevalent methods in quantum&#xA;chemistry that includes electronic correlation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;The coupled cluster technique is a convenient model for many-particle wavefunctions, whether those systems are sub-atomic, atomic or super-atomic.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;One of the most beautiful things about physics is that models like the Schroedinger equation are quite &amp;quot;universal&amp;quot; and therefore it can be used to model nuclei, atoms, molecules, macro-molecules, and so on, unless you need such high-precision as to need QED (quantum electrodynamics), QFD (quantum flavordynamics: if the weak force is needed), QCD (quantum colordynamics: if the strong force is needed, usually not for what your question is about but for &lt;em&gt;&lt;strong&gt;sub&lt;/strong&gt;&lt;/em&gt;-nuclear physics), or QGD (quantum gravity). &lt;em&gt;But even if you did need QED,&lt;/em&gt; remember that QED is also universal in the same sense, and is in fact used for atomic and molecular calculations, as you can see in the references within &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/554/5&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3890/5&quot;&gt;this&lt;/a&gt;, and QED calculations would still be called &lt;em&gt;ab initio&lt;/em&gt; in the same sense as Schroedinger equation solutions are, it's just that in quantum chemistry we don't always &lt;em&gt;need&lt;/em&gt; to go beyond the Schroedinger equation.&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Additionally I would like to mention that I wrote &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1640/5&quot;&gt;here&lt;/a&gt; that a lot of the foundational development of DFT was done by particle physicists (and the second link also includes references to seminal work by particle physicist Murray Gell-Mann):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;My answers &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1329/5&quot;&gt;here&lt;/a&gt;&#xA;and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1321/5&quot;&gt;here&lt;/a&gt; also&#xA;show that much of the early DFT development was done on the uniform&#xA;electron gas, by particle physicists like Keith Brueckner and Jeffrey&#xA;Goldstone (these two were also important players in the coupled&#xA;cluster method, which is now developed and used much more by&#xA;chemists).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-01-20T19:44:23.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4181" PostTypeId="1" CreationDate="2021-01-21T07:55:02.583" Score="7" ViewCount="328" Body="&lt;p&gt;When I use &lt;code&gt;VASPKIT&lt;/code&gt; tool to generate &lt;code&gt;K-path KPOINTS&lt;/code&gt; file for Bandstructure calcualtion of a 4x4x1 supercell of a pure material, it gives a &lt;code&gt;PRIMCELL.vasp&lt;/code&gt; file (which contains the unit cell of that material) and &lt;em&gt;&lt;strong&gt;asks me to replace my original supercell with it&lt;/strong&gt;&lt;/em&gt;. BUT, when I use &lt;code&gt;VASPKIT&lt;/code&gt; with a doped supercell structure, the &lt;code&gt;PRIMCELL.vasp&lt;/code&gt; file keeps the structure a supercell and doesn't convert it to a unit cell.&lt;/p&gt;&#xA;&lt;p&gt;Could you please tell me what the meaning of that file ? and what's the difference between the two procedures ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-01-21T11:45:01.203" Title="What is the meaning of the &quot;PRIMCELL.vasp&quot; file generated by VASPKIT tool during bandstructure inputs generation?" Tags="|density-functional-theory|vasp|band-structure|supercell|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4182" PostTypeId="2" ParentId="4181" CreationDate="2021-01-21T08:48:40.683" Score="4" Body="&lt;p&gt;I assume that you are considering 2D materials. In short, you can use the undoped primitive cell to generate a k-path to plot the band structure of your &lt;span class=&quot;math-container&quot;&gt;$4\times4\times1$&lt;/span&gt; supercell with doping.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why can you do this?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rDJhL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rDJhL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-21T08:48:40.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4183" PostTypeId="2" ParentId="4181" CreationDate="2021-01-21T11:45:01.203" Score="5" Body="&lt;p&gt;I have never used &lt;code&gt;VASPKIT&lt;/code&gt;, so my answer is of a general nature.&lt;/p&gt;&#xA;&lt;p&gt;If you have a &lt;span class=&quot;math-container&quot;&gt;$4\times4\times1$&lt;/span&gt; supercell of a perfect crystal, you have redundant information because you could always rebuild the supercell starting from the primitive cell by applying a supercell matrix. My guess is that the &lt;code&gt;PRIMCELL.vasp&lt;/code&gt; file simply contains this primitive cell as a computer code will normally want to use the primitive cell, because calculations are cheaper.&lt;/p&gt;&#xA;&lt;p&gt;If you first build a &lt;span class=&quot;math-container&quot;&gt;$4\times4\times1$&lt;/span&gt; supercell of a perfect crystal, and then add a defect into the system, your new system can no longer be described as a supercell of a smaller primitive cell. I imagine this is the reason why in this case the &lt;code&gt;PRIMCELL.vasp&lt;/code&gt; file does not contain a smaller cell: no smaller cell exists that can be transformed into your actual defect cell, so you have to do your calculations in the larger defect cell.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-01-21T11:45:01.203" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4184" PostTypeId="2" ParentId="4120" CreationDate="2021-01-21T13:52:28.947" Score="3" Body="&lt;p&gt;From the standpoint of simulations, a quantum dot would be &lt;strong&gt;more like a smallish 3D system.&lt;/strong&gt; Depending on the number of atoms in the qdot, it could be simulated directly. You would simply need set up an isolated arrangement of atoms. Some DFT programs allow you to turn off periodic boundary conditions (PBC), otherwise, you might simply leave the PBC on, but make the box big enough that the interactions between neighboring qdots can be neglected.&lt;/p&gt;&#xA;&lt;p&gt;It might be more challenging to simulate a large quantum dot, one with too many atoms to directly solve using methods like DFT. These so-called mesoscale systems are challenging because they aren't well described by infinite-size approximations (like PBC), but they are too big to study as finite-size systems.&lt;/p&gt;&#xA;&lt;p&gt;I am not very familiar with any of the details of specific DFT codes (like Quantum ESPRESSO), so hopefully someone more knowledgeable can answer with the specific considerations for how to set this up.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-01-21T13:52:28.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4186" PostTypeId="1" CreationDate="2021-01-21T16:43:25.927" Score="11" ViewCount="1060" Body="&lt;p&gt;What are the software tools (if possible open source) or methods we can use for constructing a nanocluster, most preferably with high symmetry such as icosahedron, octahedron, cuboctahedron etc. ?&lt;/p&gt;&#xA;" OwnerUserId="1178" LastEditorUserId="5" LastEditDate="2021-01-22T20:43:32.260" LastActivityDate="2021-01-22T20:43:32.260" Title="How to build a nanocluster?" Tags="|software|one-topic-per-answer|software-recommendations|symmetry|nanostructures|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4187" PostTypeId="2" ParentId="4186" CreationDate="2021-01-22T07:50:10.890" Score="9" Body="&lt;p&gt;A possible tool is the ASE python package (open-source):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/cluster/cluster.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/cluster/cluster.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another tool is &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;noreferrer&quot;&gt;materials studio software&lt;/a&gt;. Unfortunately, it is not free.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-22T07:50:10.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4188" PostTypeId="2" ParentId="1699" CreationDate="2021-01-22T10:46:33.700" Score="7" Body="&lt;p&gt;The two-band theory of the Rashba effect has been explained nicely by @ProfM.&lt;/p&gt;&#xA;&lt;p&gt;I will add more information from the practical viewpoints based on first-principles DFT calculations.&lt;/p&gt;&#xA;&lt;p&gt;In real materials, there are two key points to observe the Rashba effect:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Broken inversion symmetry;&lt;/li&gt;&#xA;&lt;li&gt;Strong spin-orbit coupling (SOC).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If your system holds these two properties, you probably can observe Rashba spin splitting. Specific to 2D materials with the previous two requirements, you can go through the following procedures to verify the presence of the Rasbha effect:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Compare the band structures without/with SOC and check whether the bands are split or not.&lt;/li&gt;&#xA;&lt;li&gt;Investigate the spin projection of the split bands (also called spin texture). If the dominant contribution of spin projection is in-plane, then you can conclude that your splitting is the Rashba-type effect.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For example, the &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.97.155415&quot; rel=&quot;nofollow noreferrer&quot;&gt;two-dimensional heterostrcutres GaX/MX&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; (M = Mo, W; X = S, Se, Te)&lt;/a&gt; with the previous requirements can show Rashba effects:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/h6iSC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/h6iSC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;PS: Usually, the Rashba splitting in real materials can only be approximated by the Hamiltonian explained by @ProfM due to the existence of crystal field.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-04-05T11:20:54.847" LastActivityDate="2021-04-05T11:20:54.847" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4190" PostTypeId="2" ParentId="4186" CreationDate="2021-01-22T13:50:13.563" Score="8" Body="&lt;h1&gt;Nanocut&lt;/h1&gt;&#xA;&lt;p&gt;From its &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/src/master/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Nanocut is a program designed to cut out various objects from three&#xA;dimensional crystal structures. It is aimed to be helpful when&#xA;creating geometry input for atomistic simulations. Currently it can&#xA;create following objects:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Spherical cluster&lt;/li&gt;&#xA;&lt;li&gt;Polyhedral cluster&lt;/li&gt;&#xA;&lt;li&gt;Cylindrical cluster&lt;/li&gt;&#xA;&lt;li&gt;Spherical wire (1D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Polyhedral wire (1D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Plain slab (2D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Supercells (3D periodic)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-22T13:50:13.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4191" PostTypeId="1" CreationDate="2021-01-22T16:16:42.207" Score="5" ViewCount="124" Body="&lt;p&gt;I have been trying to find the appropriate k-point grid via convergence in quantum ESPRESSO (QE). The following is my input file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './outdir'&#xA;  verbosity = 'high'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =    3.35381&#xA;  nat = 3&#xA;  ntyp = 2&#xA;  ecutwfc = 55&#xA;  ecutrho = 650&#xA;  starting_magnetization(1) = 1&#xA;  starting_magnetization(2) = 0&#xA;  lspinorb = .true.&#xA;  noncolin = .true.&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss = 0.005d0      &#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1e-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA; -0.500000000000000   0.866025403784439   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   2.087308375869810 &#xA;ATOMIC_SPECIES&#xA;  V   50.94150  V.rel-pbe-spnl-kjpaw_psl.1.0.0.UPF&#xA;  Se   78.96000  Se.rel-pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA; Se   0.666666666666667   0.333333333333333   0.774935000000000 &#xA; Se   0.333333333333333   0.666666666666667   0.225065000000000 &#xA; V   0.000000000000000   0.000000000000000   0.000000000000000 &#xA;K_POINTS {automatic}&#xA;  6 6 6 0 0 0&#xA;      &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here when the Spin Orbit Coupling (SOC) of the material is included as given in the input file. QE is not able to calculate the stress and pressure. And indicates the following message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Computing stress (Cartesian axis) and pressure&#xA;&#xA; Message from routine stres:&#xA; noncollinear stress + GGA not implemented&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a way I could calculate the pressure and use SOC at the same time?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2021-08-14T17:35:58.733" LastActivityDate="2021-08-14T17:35:58.733" Title="Is there a way I could calculate the pressure and use SOC at the same time?" Tags="|density-functional-theory|quantum-espresso|spin-orbit-coupling|" AnswerCount="0" CommentCount="6" ClosedDate="2021-12-06T18:54:14.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="4192" PostTypeId="2" ParentId="4186" CreationDate="2021-01-22T19:56:30.480" Score="4" Body="&lt;h1&gt;Atomsk&lt;/h1&gt;&#xA;&lt;p&gt;I like to use &lt;a href=&quot;https://atomsk.univ-lille.fr&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomsk&lt;/a&gt; to build clusters.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Atomsk is a free, Open Source command-line program dedicated to the creation, manipulation, and conversion of data files for atomic-scale simulations. It supports the file formats used by many programs.&lt;/p&gt;&#xA;&lt;p&gt;Atomsk proposes options for applying elementary transformations: duplicate, rotate, deform, insert dislocations, merge several systems, create bicrystals and polycrystals, etc. These elementary tools can be combined to construct and shape a wide variety of atomic systems. To learn more, you are invited to read &lt;a href=&quot;https://atomsk.univ-lille.fr/doc.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;the documentation&lt;/a&gt;, and to follow &lt;a href=&quot;https://atomsk.univ-lille.fr/tutorials.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;the tutorials&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Atomsk: A tool for manipulating and converting atomic data files&amp;quot;&#xA;Pierre Hirel, Comput. Phys. Comm. 197 (2015) 212-219&#xA;&lt;a href=&quot;http://www.sciencedirect.com/science/article/pii/S0010465515002817&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1016/j.cpc.2015.07.012&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="878" LastActivityDate="2021-01-22T19:56:30.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4193" PostTypeId="2" ParentId="4152" CreationDate="2021-01-22T20:07:42.197" Score="2" Body="&lt;p&gt;The spin-orbit coupling is an interested phenomena very present in semiconductor physics (no heavy atoms here). It affects the behavior of electrons and is a very important property explored in the field of spintronics.&lt;/p&gt;&#xA;&lt;p&gt;For example, in this &lt;a href=&quot;http://dx.doi.org/10.1016/j.physe.2008.02.006&quot; rel=&quot;nofollow noreferrer&quot;&gt;work&lt;/a&gt;, the influence of spin-orbit coupling in the electronic band of &lt;span class=&quot;math-container&quot;&gt;$GaAs$&lt;/span&gt; is studied.&lt;/p&gt;&#xA;&lt;p&gt;Please, take a look at this seminal work of Prof. S. Das Sarma entitled&#xA;&lt;em&gt;Spintronics: Fundamentals and applications&lt;/em&gt; on the Review of Modern Physics journal (doi: &lt;a href=&quot;https://doi.org/10.1103/RevModPhys.76.323&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1103/RevModPhys.76.323&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0405528&quot; rel=&quot;nofollow noreferrer&quot;&gt;ArXiv version&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-22T20:07:42.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4194" PostTypeId="5" CreationDate="2021-01-22T20:58:09.973" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-22T20:58:09.973" LastActivityDate="2021-01-22T20:58:09.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4195" PostTypeId="4" CreationDate="2021-01-22T20:58:09.973" Score="0" Body="Questions about error analysis or uncertainty analysis, including error propagation, blocking analysis, etc." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-22T20:58:09.973" LastActivityDate="2021-01-22T20:58:09.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4196" PostTypeId="1" CreationDate="2021-01-23T02:03:20.613" Score="7" ViewCount="211" Body="&lt;p&gt;This post is inspired by this post: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12/what-correlation-effects-are-included-in-dft/21?noredirect=1#comment7299_21&quot;&gt;What correlation effects are included in DFT?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;density functional theory&lt;/a&gt; (KS-DFT) are considered to be exact and can include all correlation effects in principle. However, if we want to apply DFT to perform practical calculations, we must make some approximations to the exchange-correlation energy, such as the famous local density approximation (LDA) and generalized gradient approximation (GGA).&lt;/p&gt;&#xA;&lt;p&gt;My question is what correlation effects are included in KS-DFT with LDA and GGA?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-08-14T17:30:24.127" LastActivityDate="2021-08-18T08:30:40.780" Title="What correlation effects are included in KS-DFT with LDA and GGA?" Tags="|density-functional-theory|electron-correlation|exchange-correlation|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4197" PostTypeId="2" ParentId="3519" CreationDate="2021-01-23T10:00:53.370" Score="2" Body="&lt;p&gt;Upon the request I'm sharing the solution I came to.&lt;/p&gt;&#xA;&lt;p&gt;So, as I mentioned in the comments, I've finally make MarvinSkectch Markush enumeration feature to work properly. I don't really know what I've been doing wrong, as it just started working as intended. ChemAxon have a small tutorial on this feature. &lt;a href=&quot;https://www.youtube.com/watch?v=k8xDe1P_dgQ&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemAxon tutorial&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-01-23T10:00:53.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4198" PostTypeId="2" ParentId="3554" CreationDate="2021-01-23T12:18:39.787" Score="6" Body="&lt;p&gt;The static energy at 0K is usually the major component of the free energy (at least for crystalline substances at moderate temperatures). So I will proceed first a search based on static energy (using USPEX or otherwise) and, then, calculate free energies for the top candidates within QHA approximation and rank them again appropriately.&lt;/p&gt;&#xA;" OwnerUserId="205" LastActivityDate="2021-01-23T12:18:39.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4199" PostTypeId="1" CreationDate="2021-01-23T13:48:37.913" Score="9" ViewCount="531" Body="&lt;p&gt;I'm studying a compound &lt;span class=&quot;math-container&quot;&gt;$\ce{VSe_2}$&lt;/span&gt; using the DFT package Quantum ESPRESSO (QE). The following is the input file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './outdir'&#xA;  verbosity = 'high'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =    3.35381&#xA;  nat = 3&#xA;  ntyp = 2&#xA;  ecutwfc = 55&#xA;  ecutrho = 650&#xA;  starting_magnetization(1) = 1&#xA;  starting_magnetization(2) = 0&#xA;  lspinorb = .true.&#xA;  noncolin = .true.&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss = 0.005d0      &#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1e-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA; -0.500000000000000   0.866025403784439   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   2.087308375869810 &#xA;ATOMIC_SPECIES&#xA;  V   50.94150  V.rel-pbe-spnl-kjpaw_psl.1.0.0.UPF&#xA;  Se   78.96000  Se.rel-pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA; Se   0.666666666666667   0.333333333333333   0.774935000000000 &#xA; Se   0.333333333333333   0.666666666666667   0.225065000000000 &#xA; V   0.000000000000000   0.000000000000000   0.000000000000000 &#xA;K_POINTS {automatic}&#xA;  6 6 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I'm using a threshold of &lt;span class=&quot;math-container&quot;&gt;$10^{-8}$&lt;/span&gt;, the SCF loop doesn't converge after 100 iterations. &lt;strong&gt;Is it okay to use a lower threshold of &lt;span class=&quot;math-container&quot;&gt;$10^{-4}$&lt;/span&gt; so as to aid convergence?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;SCF output:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; estimated scf accuracy    &amp;lt;       0.00015001 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00017012 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00023876 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00015530 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00010229 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00030521 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00038586 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00035244 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00018834 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00026472 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00026759 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00035791 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00014860 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00023776 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00031980 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00023777 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00029549 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00031407 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00009668 Ry&#xA; estimated scf accuracy    &amp;lt;       0.00019794 Ry&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="1218" LastEditDate="2021-01-30T01:19:55.787" LastActivityDate="2021-01-30T01:19:55.787" Title="Should I use a lower threshold for calculations involving SOC?" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|spin-orbit-coupling|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4200" PostTypeId="2" ParentId="4199" CreationDate="2021-01-23T18:19:13.743" Score="8" Body="&lt;p&gt;I wouldn't recommend that you go above &lt;span class=&quot;math-container&quot;&gt;$10^{-8}$&lt;/span&gt;, what you have in your current calculation. With SCF calculations, you definitely need a lower convergence threshold compared to say relaxing procedures. I suspect your problem is rooted elsewhere. Try:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Lowering 'mixing-beta'&lt;/li&gt;&#xA;&lt;li&gt;Removing 'verbosity' as it just prints energy levels and takes up time, which you can after you've made you can achieve convergence.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Also, did you do an SCF calculation with SOC turned off? Did you achieve convergence then? The usual procedure is to make sure that your non-relativistic calculation can converge properly first. This means tuning 'ecutwfc' and 'K-POINTS' so that proper convergence has been achieved. Once this is done, turn on SOC and see if you still encounter the same problem.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-01-23T18:19:13.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4201" PostTypeId="1" AcceptedAnswerId="4210" CreationDate="2021-01-23T19:47:48.023" Score="15" ViewCount="483" Body="&lt;p&gt;For pedagogical reasons, I am looking for ways to calculate quantum-mechanical quantities such as &lt;span class=&quot;math-container&quot;&gt;$\langle m | \dot{m}\rangle, \langle m | \dot{n}\rangle, \langle m | \ddot{n}\rangle$&lt;/span&gt; using wavefunctions &lt;span class=&quot;math-container&quot;&gt;$m,n$&lt;/span&gt; output from DFT calculations (Quantum Espresso, specifically). The overhead dots denote derivatives.&#xA;Ideally, I would be able to calculate the Berry phase for custom loops&#xA;as well.&lt;/p&gt;&#xA;&lt;p&gt;So far, I have tried using some Python tools (z2Pack, PythTB) to try and post-process wannier90 output, but as a beginner, it doesn't seem as if these tools allow us to calculate our own matrix elements. They seem to be just for intra-level quantities such as &lt;span class=&quot;math-container&quot;&gt;$\langle m | \dot{m}\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone more-experienced have any advice on what existing software might be easiest to work with to calculate these custom-defined quantities? I would rather try messing with some software that is more likely to support these kinds of calculations. PythTB seems to be one of the best options I have, but Python may not be the best for large datasets (compared to Fortran, etc).&#xA;Thank you for your time.&lt;/p&gt;&#xA;&lt;p&gt;Edit: The issue also seems to be that several post-processing software tend to use the numerical method where one takes &lt;span class=&quot;math-container&quot;&gt;$\arg$&lt;/span&gt; of some product of complex phases corresponding to each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; point. However to do something like &lt;span class=&quot;math-container&quot;&gt;$\langle m | \dot{n}\rangle$&lt;/span&gt;, it might be better to use a central difference method to carry out the derivative of the wavefunction (as opposed to an established discretized method for the Berry phase, as in section 4.5 in Ref [1]).&lt;/p&gt;&#xA;&lt;p&gt;[1]: Tight-Binding Formalism in the Context of the PythTB Package, &lt;a href=&quot;https://www.physics.rutgers.edu/pythtb/formalism.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.physics.rutgers.edu/pythtb/formalism.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="6055" LastEditDate="2024-03-07T19:30:16.063" LastActivityDate="2024-03-07T19:30:16.063" Title="What is the best program to manipulate plane-wave DFT wavefunctions to calculate custom matrix elements?" Tags="|density-functional-theory|quantum-espresso|software-recommendations|quantum-mechanics|python|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4202" PostTypeId="2" ParentId="3615" CreationDate="2021-01-23T23:21:45.403" Score="5" Body="&lt;p&gt;Emilio Artacho's group has used Floquet theory to look at the behavior of projectiles in crystalline solids. You can read about it here (open access): &lt;a href=&quot;https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.2.033151&quot; rel=&quot;noreferrer&quot;&gt;Floquet theory for the electronic stopping of projectiles in solids&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps not exactly what you asked for, but it is an example of Floquet theory applied to electrons in condensed matter.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastActivityDate="2021-01-23T23:21:45.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4203" PostTypeId="1" CreationDate="2021-01-23T23:49:20.773" Score="15" ViewCount="519" Body="&lt;p&gt;I am looking for an open-source library that allows to passivate a structure, ideally starting from a xyz-file.&lt;/p&gt;&#xA;&lt;p&gt;QuantumATK provides a function like this. However, this is not an option at the moment.&lt;/p&gt;&#xA;&lt;p&gt;If there is no such software, how do you create passivated structures?&lt;/p&gt;&#xA;&lt;p&gt;Edit: To clarify what I mean when I say &amp;quot;passivate&amp;quot;: I mean just adding e.g. H atoms to the dangling bonds.&lt;/p&gt;&#xA;" OwnerUserId="1955" LastEditorUserId="1955" LastEditDate="2021-02-02T10:19:21.400" LastActivityDate="2021-02-04T08:11:39.907" Title="Software recommendations for passivating structures" Tags="|reference-request|software-recommendations|quantum-atk|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="4204" PostTypeId="1" CreationDate="2021-01-23T23:53:50.517" Score="9" ViewCount="322" Body="&lt;p&gt;Currently, I am working on ZnO doped with nickel and cobalt.&lt;/p&gt;&#xA;&lt;p&gt;I performed the SCF, NCF, BANDS calculation and got the results, the calculation converges without any errors.&lt;/p&gt;&#xA;&lt;p&gt;After that I used BANDS.X to get the structures of the bands (broken lines) shown below.&#xA;but the lines of the valence band look unusual.&#xA;I do not understand why, do i have to change something in the input files to have regular lines in the bands structure&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O3mZH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O3mZH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I would be grateful if anyone could help me figure out how to solve this problem&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Input files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation='scf'&#xA;    verbosity='high'&#xA;    outdir  ='./outdir0'&#xA;    prefix  = 'zno'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;&#xA;    celldm(1)                 =  21.40319287&#xA;    celldm(3)                 =  0.42031128&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  2.25000e+02&#xA;    ecutwfc                   =  2.50000e+01&#xA;    hubbard_u(1)              =  1.00000e+01&#xA;    hubbard_u(2)              =  7.00000e+00&#xA;    hubbard_u(3)              =  3.30000e+00&#xA;    hubbard_u(4)              =  6.40000e+00&#xA;    ibrav                     = 4&#xA;    lda_plus_u                = .TRUE.&#xA;    nat                       = 64&#xA;    nspin                     = 2&#xA;    ntyp                      = 4&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  0.00000e+00&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;    starting_magnetization(3) =  1.00000e+00&#xA;    starting_magnetization(4) =  1.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 1000&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 1  1  2  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-dnl-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Co     58.93320  Co.pbe-spn-rrkjus_psl.0.3.1.UPF&#xA;Ni     58.69340  Ni.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn       1.410161044   0.825995833   2.380992801&#xA;Zn      -0.005429322   1.643266003   0.000756804&#xA;O        1.411103994   0.826287146   4.186635975&#xA;O       -0.004748346   1.642515898   1.806356445&#xA;Zn      -0.005516345   3.278786045   2.381245055&#xA;Zn      -1.419971282   4.097701065   0.001850277&#xA;O       -0.002798492   3.277411927   4.186681410&#xA;O       -1.420408761   4.092914533   1.803518434&#xA;Co      -1.418796177   5.737987580   2.384585461&#xA;Zn      -2.834720550   6.547227769   0.000881320&#xA;O       -1.422621217   5.728278992   4.185274022&#xA;O       -2.839808876   6.544154464   1.803705508&#xA;Zn      -2.837557287   8.183674136   2.381283724&#xA;Zn      -4.252922611   8.999365922   0.000439200&#xA;O       -2.837160076   8.183295309   4.186352705&#xA;O       -4.252778394   8.999185384   1.806247618&#xA;Zn       4.241315211   0.825532190   2.381126062&#xA;Zn       2.826326309   1.643228258   0.000953899&#xA;O        4.242086608   0.827637833   4.187714131&#xA;O        2.826296455   1.642373986   1.806396627&#xA;Zn       2.824771427   3.281480594   2.381223601&#xA;Zn       1.410630100   4.096454188   0.000348962&#xA;O        2.829294361   3.277876925   4.186011005&#xA;O        1.408295070   4.091216703   1.805811442&#xA;Zn       1.414986914   5.731953488   2.381740527&#xA;Zn      -0.003889577   6.546816914   0.001471199&#xA;O        1.407469304   5.728334147   4.188751652&#xA;O       -0.007390107   6.544762033   1.803264178&#xA;Zn      -0.003327618   8.182005863   2.381621288&#xA;Zn      -1.420174649   8.999121824   0.000605799&#xA;O       -0.005038456   8.183109394   4.186299484&#xA;O       -1.422019740   8.999623285   1.805713335&#xA;Zn       7.074368960   0.824266725   2.381038272&#xA;Zn       5.658165161   1.641466511   0.001428145&#xA;O        7.072366692   0.826925817   4.185876987&#xA;O        5.657781142   1.643195079   1.806011335&#xA;Zn       5.660936107   3.273250277   2.380793392&#xA;Zn       4.239021566   4.101799131   0.000974597&#xA;O        5.656833118   3.276218912   4.184993975&#xA;O        4.230283881   3.987942736   1.752313988&#xA;Ni       4.556125575   5.359987165   2.507242555&#xA;Zn       2.822577415   6.549618757  -0.002501852&#xA;O        4.241256251   5.729384302   4.181685069&#xA;O        2.889746313   6.512400957   1.840699848&#xA;Zn       2.831814541   8.170887246   2.382231895&#xA;Zn       1.411768031   8.997746180   0.000157807&#xA;O        2.830565389   8.180204499   4.188372520&#xA;O        1.410158759   9.000713184   1.805698039&#xA;Zn       9.904721317   0.824048816   2.380672192&#xA;Zn       8.489987876   1.641958804   0.000861323&#xA;O        9.905515013   0.828559672   4.186395649&#xA;O        8.489434493   1.643995005   1.805707065&#xA;Zn       8.491348975   3.277332149   2.381672239&#xA;Zn       7.075554658   4.094592895  -0.001192399&#xA;O        8.487517217   3.277350003   4.187187336&#xA;O        7.079637920   4.091302394   1.804853403&#xA;Zn       7.070336637   5.730421815   2.381711957&#xA;Zn       5.657529623   6.551672595   0.003357063&#xA;O        7.061570500   5.730823283   4.183934701&#xA;O        5.626730523   6.537239405   1.818160581&#xA;Zn       5.654350538   8.182766059   2.381132006&#xA;Zn       4.240971534   8.998159127   0.002754675&#xA;O        5.659147597   8.182586948   4.186976982&#xA;O        4.243691097   8.999467758   1.805287550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation='nscf'&#xA;    verbosity='high'&#xA;    outdir  ='./outdir0'&#xA;    prefix  = 'zno'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    celldm(1)                 =  21.40319287&#xA;    celldm(3)                 =  0.42031128&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  2.25000e+02&#xA;    ecutwfc                   =  2.50000e+01&#xA;    hubbard_u(1)              =  1.00000e+01&#xA;    hubbard_u(2)              =  7.00000e+00&#xA;    hubbard_u(3)              =  3.30000e+00&#xA;    hubbard_u(4)              =  6.40000e+00&#xA;    ibrav                     = 4&#xA;    lda_plus_u                = .TRUE.&#xA;    nat                       = 64&#xA;    nbnd                      = 416&#xA;    nspin                     = 2&#xA;    ntyp                      = 4&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  0.00000e+00&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;    starting_magnetization(3) =  1.00000e+00&#xA;    starting_magnetization(4) =  1.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 1000&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;K_POINTS {automatic}&#xA; 2  2  5  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-dnl-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Co     58.93320  Co.pbe-spn-rrkjus_psl.0.3.1.UPF&#xA;Ni     58.69340  Ni.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn       1.410161044   0.825995833   2.380992801&#xA;Zn      -0.005429322   1.643266003   0.000756804&#xA;O        1.411103994   0.826287146   4.186635975&#xA;O       -0.004748346   1.642515898   1.806356445&#xA;Zn      -0.005516345   3.278786045   2.381245055&#xA;Zn      -1.419971282   4.097701065   0.001850277&#xA;O       -0.002798492   3.277411927   4.186681410&#xA;O       -1.420408761   4.092914533   1.803518434&#xA;Co      -1.418796177   5.737987580   2.384585461&#xA;Zn      -2.834720550   6.547227769   0.000881320&#xA;O       -1.422621217   5.728278992   4.185274022&#xA;O       -2.839808876   6.544154464   1.803705508&#xA;Zn      -2.837557287   8.183674136   2.381283724&#xA;Zn      -4.252922611   8.999365922   0.000439200&#xA;O       -2.837160076   8.183295309   4.186352705&#xA;O       -4.252778394   8.999185384   1.806247618&#xA;Zn       4.241315211   0.825532190   2.381126062&#xA;Zn       2.826326309   1.643228258   0.000953899&#xA;O        4.242086608   0.827637833   4.187714131&#xA;O        2.826296455   1.642373986   1.806396627&#xA;Zn       2.824771427   3.281480594   2.381223601&#xA;Zn       1.410630100   4.096454188   0.000348962&#xA;O        2.829294361   3.277876925   4.186011005&#xA;O        1.408295070   4.091216703   1.805811442&#xA;Zn       1.414986914   5.731953488   2.381740527&#xA;Zn      -0.003889577   6.546816914   0.001471199&#xA;O        1.407469304   5.728334147   4.188751652&#xA;O       -0.007390107   6.544762033   1.803264178&#xA;Zn      -0.003327618   8.182005863   2.381621288&#xA;Zn      -1.420174649   8.999121824   0.000605799&#xA;O       -0.005038456   8.183109394   4.186299484&#xA;O       -1.422019740   8.999623285   1.805713335&#xA;Zn       7.074368960   0.824266725   2.381038272&#xA;Zn       5.658165161   1.641466511   0.001428145&#xA;O        7.072366692   0.826925817   4.185876987&#xA;O        5.657781142   1.643195079   1.806011335&#xA;Zn       5.660936107   3.273250277   2.380793392&#xA;Zn       4.239021566   4.101799131   0.000974597&#xA;O        5.656833118   3.276218912   4.184993975&#xA;O        4.230283881   3.987942736   1.752313988&#xA;Ni       4.556125575   5.359987165   2.507242555&#xA;Zn       2.822577415   6.549618757  -0.002501852&#xA;O        4.241256251   5.729384302   4.181685069&#xA;O        2.889746313   6.512400957   1.840699848&#xA;Zn       2.831814541   8.170887246   2.382231895&#xA;Zn       1.411768031   8.997746180   0.000157807&#xA;O        2.830565389   8.180204499   4.188372520&#xA;O        1.410158759   9.000713184   1.805698039&#xA;Zn       9.904721317   0.824048816   2.380672192&#xA;Zn       8.489987876   1.641958804   0.000861323&#xA;O        9.905515013   0.828559672   4.186395649&#xA;O        8.489434493   1.643995005   1.805707065&#xA;Zn       8.491348975   3.277332149   2.381672239&#xA;Zn       7.075554658   4.094592895  -0.001192399&#xA;O        8.487517217   3.277350003   4.187187336&#xA;O        7.079637920   4.091302394   1.804853403&#xA;Zn       7.070336637   5.730421815   2.381711957&#xA;Zn       5.657529623   6.551672595   0.003357063&#xA;O        7.061570500   5.730823283   4.183934701&#xA;O        5.626730523   6.537239405   1.818160581&#xA;Zn       5.654350538   8.182766059   2.381132006&#xA;Zn       4.240971534   8.998159127   0.002754675&#xA;O        5.659147597   8.182586948   4.186976982&#xA;O        4.243691097   8.999467758   1.805287550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;    calculation='bands'&#xA;    verbosity='high'&#xA;    outdir  ='./outdir0'&#xA;    prefix  = 'zno'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    celldm(1)                 =  21.40319287&#xA;    celldm(3)                 =  0.42031128&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  2.25000e+02&#xA;    ecutwfc                   =  2.50000e+01&#xA;    hubbard_u(1)              =  1.00000e+01&#xA;    hubbard_u(2)              =  7.00000e+00&#xA;    hubbard_u(3)              =  3.30000e+00&#xA;    hubbard_u(4)              =  6.40000e+00&#xA;    ibrav                     = 4&#xA;    lda_plus_u                = .TRUE.&#xA;    nat                       = 64&#xA;    nbnd                      = 416&#xA;    nspin                     = 2&#xA;    ntyp                      = 4&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  0.00000e+00&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;    starting_magnetization(3) =  1.00000e+00&#xA;    starting_magnetization(4) =  1.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 1000&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&#xA;&#xA;K_POINTS {tpiba_b}&#xA;12&#xA;gG     20&#xA;M      20&#xA;K      20&#xA;gG     20&#xA;A      20&#xA;L      20&#xA;H      20&#xA;A      0&#xA;L      20&#xA;M      0&#xA;K      20&#xA;H      0&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-dnl-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Co     58.93320  Co.pbe-spn-rrkjus_psl.0.3.1.UPF&#xA;Ni     58.69340  Ni.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn       1.410161044   0.825995833   2.380992801&#xA;Zn      -0.005429322   1.643266003   0.000756804&#xA;O        1.411103994   0.826287146   4.186635975&#xA;O       -0.004748346   1.642515898   1.806356445&#xA;Zn      -0.005516345   3.278786045   2.381245055&#xA;Zn      -1.419971282   4.097701065   0.001850277&#xA;O       -0.002798492   3.277411927   4.186681410&#xA;O       -1.420408761   4.092914533   1.803518434&#xA;Co      -1.418796177   5.737987580   2.384585461&#xA;Zn      -2.834720550   6.547227769   0.000881320&#xA;O       -1.422621217   5.728278992   4.185274022&#xA;O       -2.839808876   6.544154464   1.803705508&#xA;Zn      -2.837557287   8.183674136   2.381283724&#xA;Zn      -4.252922611   8.999365922   0.000439200&#xA;O       -2.837160076   8.183295309   4.186352705&#xA;O       -4.252778394   8.999185384   1.806247618&#xA;Zn       4.241315211   0.825532190   2.381126062&#xA;Zn       2.826326309   1.643228258   0.000953899&#xA;O        4.242086608   0.827637833   4.187714131&#xA;O        2.826296455   1.642373986   1.806396627&#xA;Zn       2.824771427   3.281480594   2.381223601&#xA;Zn       1.410630100   4.096454188   0.000348962&#xA;O        2.829294361   3.277876925   4.186011005&#xA;O        1.408295070   4.091216703   1.805811442&#xA;Zn       1.414986914   5.731953488   2.381740527&#xA;Zn      -0.003889577   6.546816914   0.001471199&#xA;O        1.407469304   5.728334147   4.188751652&#xA;O       -0.007390107   6.544762033   1.803264178&#xA;Zn      -0.003327618   8.182005863   2.381621288&#xA;Zn      -1.420174649   8.999121824   0.000605799&#xA;O       -0.005038456   8.183109394   4.186299484&#xA;O       -1.422019740   8.999623285   1.805713335&#xA;Zn       7.074368960   0.824266725   2.381038272&#xA;Zn       5.658165161   1.641466511   0.001428145&#xA;O        7.072366692   0.826925817   4.185876987&#xA;O        5.657781142   1.643195079   1.806011335&#xA;Zn       5.660936107   3.273250277   2.380793392&#xA;Zn       4.239021566   4.101799131   0.000974597&#xA;O        5.656833118   3.276218912   4.184993975&#xA;O        4.230283881   3.987942736   1.752313988&#xA;Ni       4.556125575   5.359987165   2.507242555&#xA;Zn       2.822577415   6.549618757  -0.002501852&#xA;O        4.241256251   5.729384302   4.181685069&#xA;O        2.889746313   6.512400957   1.840699848&#xA;Zn       2.831814541   8.170887246   2.382231895&#xA;Zn       1.411768031   8.997746180   0.000157807&#xA;O        2.830565389   8.180204499   4.188372520&#xA;O        1.410158759   9.000713184   1.805698039&#xA;Zn       9.904721317   0.824048816   2.380672192&#xA;Zn       8.489987876   1.641958804   0.000861323&#xA;O        9.905515013   0.828559672   4.186395649&#xA;O        8.489434493   1.643995005   1.805707065&#xA;Zn       8.491348975   3.277332149   2.381672239&#xA;Zn       7.075554658   4.094592895  -0.001192399&#xA;O        8.487517217   3.277350003   4.187187336&#xA;O        7.079637920   4.091302394   1.804853403&#xA;Zn       7.070336637   5.730421815   2.381711957&#xA;Zn       5.657529623   6.551672595   0.003357063&#xA;O        7.061570500   5.730823283   4.183934701&#xA;O        5.626730523   6.537239405   1.818160581&#xA;Zn       5.654350538   8.182766059   2.381132006&#xA;Zn       4.240971534   8.998159127   0.002754675&#xA;O        5.659147597   8.182586948   4.186976982&#xA;O        4.243691097   8.999467758   1.805287550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;bands&#xA;    outdir  ='./outdir0'&#xA;    prefix  = 'zno'&#xA;  filband='bandspp.Down.dat'&#xA;  &#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="5" LastEditDate="2021-09-21T22:29:44.510" LastActivityDate="2021-09-21T22:29:44.510" Title="Band structure has unusual lines in the valence band using Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|band-structure|doping|" AnswerCount="0" CommentCount="2" ClosedDate="2021-09-22T01:37:52.060" ContentLicense="CC BY-SA 4.0" />
  <row Id="4205" PostTypeId="1" CreationDate="2021-01-24T01:18:00.710" Score="6" ViewCount="1279" Body="&lt;p&gt;I want to work with GGA +U on Quantum espresso to calculate the electronic properties of Ni Co co-doped ZnO system, but I can't figure out how to use the hp.x program for my system to calculate the Hubbard parametre for each element&lt;/p&gt;&#xA;&lt;p&gt;is there someone who can give me an example of an input and output file  of hp.x program to better understand how I work with it.&lt;/p&gt;&#xA;&lt;p&gt;my input files for &lt;code&gt;SCF&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation='scf'&#xA;    verbosity='high'&#xA;    outdir  ='./outdir0'&#xA;    prefix  = 'zno'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;&#xA;    celldm(1)                 =  21.40319287&#xA;    celldm(3)                 =  0.42031128&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  2.25000e+02&#xA;    ecutwfc                   =  2.50000e+01&#xA;    ibrav                     = 4&#xA;    lda_plus_u                = .TRUE.&#xA;    nat                       = 64&#xA;    nspin                     = 2&#xA;    ntyp                      = 4&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  0.00000e+00&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;    starting_magnetization(3) =  1.00000e+00&#xA;    starting_magnetization(4) =  1.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 1000&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 1  1  2  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-dnl-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Co     58.93320  Co.pbe-spn-rrkjus_psl.0.3.1.UPF&#xA;Ni     58.69340  Ni.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn       1.410161044   0.825995833   2.380992801&#xA;Zn      -0.005429322   1.643266003   0.000756804&#xA;O        1.411103994   0.826287146   4.186635975&#xA;O       -0.004748346   1.642515898   1.806356445&#xA;Zn      -0.005516345   3.278786045   2.381245055&#xA;Zn      -1.419971282   4.097701065   0.001850277&#xA;O       -0.002798492   3.277411927   4.186681410&#xA;O       -1.420408761   4.092914533   1.803518434&#xA;Co      -1.418796177   5.737987580   2.384585461&#xA;Zn      -2.834720550   6.547227769   0.000881320&#xA;O       -1.422621217   5.728278992   4.185274022&#xA;O       -2.839808876   6.544154464   1.803705508&#xA;Zn      -2.837557287   8.183674136   2.381283724&#xA;Zn      -4.252922611   8.999365922   0.000439200&#xA;O       -2.837160076   8.183295309   4.186352705&#xA;O       -4.252778394   8.999185384   1.806247618&#xA;Zn       4.241315211   0.825532190   2.381126062&#xA;Zn       2.826326309   1.643228258   0.000953899&#xA;O        4.242086608   0.827637833   4.187714131&#xA;O        2.826296455   1.642373986   1.806396627&#xA;Zn       2.824771427   3.281480594   2.381223601&#xA;Zn       1.410630100   4.096454188   0.000348962&#xA;O        2.829294361   3.277876925   4.186011005&#xA;O        1.408295070   4.091216703   1.805811442&#xA;Zn       1.414986914   5.731953488   2.381740527&#xA;Zn      -0.003889577   6.546816914   0.001471199&#xA;O        1.407469304   5.728334147   4.188751652&#xA;O       -0.007390107   6.544762033   1.803264178&#xA;Zn      -0.003327618   8.182005863   2.381621288&#xA;Zn      -1.420174649   8.999121824   0.000605799&#xA;O       -0.005038456   8.183109394   4.186299484&#xA;O       -1.422019740   8.999623285   1.805713335&#xA;Zn       7.074368960   0.824266725   2.381038272&#xA;Zn       5.658165161   1.641466511   0.001428145&#xA;O        7.072366692   0.826925817   4.185876987&#xA;O        5.657781142   1.643195079   1.806011335&#xA;Zn       5.660936107   3.273250277   2.380793392&#xA;Zn       4.239021566   4.101799131   0.000974597&#xA;O        5.656833118   3.276218912   4.184993975&#xA;O        4.230283881   3.987942736   1.752313988&#xA;Ni       4.556125575   5.359987165   2.507242555&#xA;Zn       2.822577415   6.549618757  -0.002501852&#xA;O        4.241256251   5.729384302   4.181685069&#xA;O        2.889746313   6.512400957   1.840699848&#xA;Zn       2.831814541   8.170887246   2.382231895&#xA;Zn       1.411768031   8.997746180   0.000157807&#xA;O        2.830565389   8.180204499   4.188372520&#xA;O        1.410158759   9.000713184   1.805698039&#xA;Zn       9.904721317   0.824048816   2.380672192&#xA;Zn       8.489987876   1.641958804   0.000861323&#xA;O        9.905515013   0.828559672   4.186395649&#xA;O        8.489434493   1.643995005   1.805707065&#xA;Zn       8.491348975   3.277332149   2.381672239&#xA;Zn       7.075554658   4.094592895  -0.001192399&#xA;O        8.487517217   3.277350003   4.187187336&#xA;O        7.079637920   4.091302394   1.804853403&#xA;Zn       7.070336637   5.730421815   2.381711957&#xA;Zn       5.657529623   6.551672595   0.003357063&#xA;O        7.061570500   5.730823283   4.183934701&#xA;O        5.626730523   6.537239405   1.818160581&#xA;Zn       5.654350538   8.182766059   2.381132006&#xA;Zn       4.240971534   8.998159127   0.002754675&#xA;O        5.659147597   8.182586948   4.186976982&#xA;O        4.243691097   8.999467758   1.805287550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and &lt;code&gt;NSCF&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation='nscf'&#xA;        verbosity='high'&#xA;        outdir  ='./outdir0'&#xA;        prefix  = 'zno'&#xA;    /&#xA;    &amp;amp;SYSTEM&#xA;        celldm(1)                 =  21.40319287&#xA;        celldm(3)                 =  0.42031128&#xA;        degauss                   =  1.00000e-02&#xA;        ecutrho                   =  2.25000e+02&#xA;        ecutwfc                   =  2.50000e+01&#xA;        ibrav                     = 4&#xA;        lda_plus_u                = .TRUE.&#xA;        nat                       = 64&#xA;        nbnd                      = 416&#xA;        nspin                     = 2&#xA;        ntyp                      = 4&#xA;        occupations               = &amp;quot;smearing&amp;quot;&#xA;        smearing                  = &amp;quot;gaussian&amp;quot;&#xA;        starting_magnetization(1) =  0.00000e+00&#xA;        starting_magnetization(2) =  0.00000e+00&#xA;        starting_magnetization(3) =  1.00000e+00&#xA;        starting_magnetization(4) =  1.00000e+00&#xA;    /&#xA;    &#xA;    &amp;amp;ELECTRONS&#xA;        conv_thr         =  1.00000e-06&#xA;        electron_maxstep = 1000&#xA;        mixing_beta      =  7.00000e-01&#xA;        startingpot      = &amp;quot;atomic&amp;quot;&#xA;        startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;    /&#xA;    K_POINTS {automatic}&#xA;     2  2  5  0 0 0&#xA;    &#xA;    ATOMIC_SPECIES&#xA;    Zn     65.39000  Zn.pbe-dnl-rrkjus_psl.1.0.0.UPF&#xA;    O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;    Co     58.93320  Co.pbe-spn-rrkjus_psl.0.3.1.UPF&#xA;    Ni     58.69340  Ni.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;    &#xA;    ATOMIC_POSITIONS {angstrom}&#xA;    Zn       1.410161044   0.825995833   2.380992801&#xA;    Zn      -0.005429322   1.643266003   0.000756804&#xA;    O        1.411103994   0.826287146   4.186635975&#xA;    O       -0.004748346   1.642515898   1.806356445&#xA;    Zn      -0.005516345   3.278786045   2.381245055&#xA;    Zn      -1.419971282   4.097701065   0.001850277&#xA;    O       -0.002798492   3.277411927   4.186681410&#xA;    O       -1.420408761   4.092914533   1.803518434&#xA;    Co      -1.418796177   5.737987580   2.384585461&#xA;    Zn      -2.834720550   6.547227769   0.000881320&#xA;    O       -1.422621217   5.728278992   4.185274022&#xA;    O       -2.839808876   6.544154464   1.803705508&#xA;    Zn      -2.837557287   8.183674136   2.381283724&#xA;    Zn      -4.252922611   8.999365922   0.000439200&#xA;    O       -2.837160076   8.183295309   4.186352705&#xA;    O       -4.252778394   8.999185384   1.806247618&#xA;    Zn       4.241315211   0.825532190   2.381126062&#xA;    Zn       2.826326309   1.643228258   0.000953899&#xA;    O        4.242086608   0.827637833   4.187714131&#xA;    O        2.826296455   1.642373986   1.806396627&#xA;    Zn       2.824771427   3.281480594   2.381223601&#xA;    Zn       1.410630100   4.096454188   0.000348962&#xA;    O        2.829294361   3.277876925   4.186011005&#xA;    O        1.408295070   4.091216703   1.805811442&#xA;    Zn       1.414986914   5.731953488   2.381740527&#xA;    Zn      -0.003889577   6.546816914   0.001471199&#xA;    O        1.407469304   5.728334147   4.188751652&#xA;    O       -0.007390107   6.544762033   1.803264178&#xA;    Zn      -0.003327618   8.182005863   2.381621288&#xA;    Zn      -1.420174649   8.999121824   0.000605799&#xA;    O       -0.005038456   8.183109394   4.186299484&#xA;    O       -1.422019740   8.999623285   1.805713335&#xA;    Zn       7.074368960   0.824266725   2.381038272&#xA;    Zn       5.658165161   1.641466511   0.001428145&#xA;    O        7.072366692   0.826925817   4.185876987&#xA;    O        5.657781142   1.643195079   1.806011335&#xA;    Zn       5.660936107   3.273250277   2.380793392&#xA;    Zn       4.239021566   4.101799131   0.000974597&#xA;    O        5.656833118   3.276218912   4.184993975&#xA;    O        4.230283881   3.987942736   1.752313988&#xA;    Ni       4.556125575   5.359987165   2.507242555&#xA;    Zn       2.822577415   6.549618757  -0.002501852&#xA;    O        4.241256251   5.729384302   4.181685069&#xA;    O        2.889746313   6.512400957   1.840699848&#xA;    Zn       2.831814541   8.170887246   2.382231895&#xA;    Zn       1.411768031   8.997746180   0.000157807&#xA;    O        2.830565389   8.180204499   4.188372520&#xA;    O        1.410158759   9.000713184   1.805698039&#xA;    Zn       9.904721317   0.824048816   2.380672192&#xA;    Zn       8.489987876   1.641958804   0.000861323&#xA;    O        9.905515013   0.828559672   4.186395649&#xA;    O        8.489434493   1.643995005   1.805707065&#xA;    Zn       8.491348975   3.277332149   2.381672239&#xA;    Zn       7.075554658   4.094592895  -0.001192399&#xA;    O        8.487517217   3.277350003   4.187187336&#xA;    O        7.079637920   4.091302394   1.804853403&#xA;    Zn       7.070336637   5.730421815   2.381711957&#xA;    Zn       5.657529623   6.551672595   0.003357063&#xA;    O        7.061570500   5.730823283   4.183934701&#xA;    O        5.626730523   6.537239405   1.818160581&#xA;    Zn       5.654350538   8.182766059   2.381132006&#xA;    Zn       4.240971534   8.998159127   0.002754675&#xA;    O        5.659147597   8.182586948   4.186976982&#xA;    O        4.243691097   8.999467758   1.805287550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="5" LastEditDate="2021-01-24T02:09:34.503" LastActivityDate="2021-01-24T02:09:34.503" Title="How to use hp.x in Quantum ESPRESSO to calculate Hubbard parameter" Tags="|density-functional-theory|quantum-espresso|model-hamiltonians|dft-u|hubbard-model|" AnswerCount="0" CommentCount="3" ClosedDate="2021-08-14T20:09:31.263" ContentLicense="CC BY-SA 4.0" />
  <row Id="4206" PostTypeId="5" CreationDate="2021-01-24T02:15:28.243" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.synopsys.com/silicon/quantumatk.html&lt;/a&gt; (main website)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://docs.quantumatk.com/manual/Introduction.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.quantumatk.com/manual/Introduction.html&lt;/a&gt; (documentation)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-24T02:15:28.243" LastActivityDate="2021-01-24T02:15:28.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4207" PostTypeId="4" CreationDate="2021-01-24T02:15:28.243" Score="0" Body="Questions about QuantumATK." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-24T02:15:28.243" LastActivityDate="2021-01-24T02:15:28.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4208" PostTypeId="2" ParentId="467" CreationDate="2021-01-24T19:07:18.687" Score="13" Body="&lt;h1&gt;Crystal Impact Diamond&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.crystalimpact.com/diamond/&quot; rel=&quot;noreferrer&quot;&gt;Crystal Impact Diamond&lt;/a&gt;, despite being a commercial product, offers a &lt;a href=&quot;https://www.crystalimpact.com/diamond/download.htm&quot; rel=&quot;noreferrer&quot;&gt;free demo-version&lt;/a&gt;.&#xA;One can import a structure, adjust its appearance and use &lt;a href=&quot;https://en.wikipedia.org/wiki/Comparison_of_screencasting_software&quot; rel=&quot;noreferrer&quot;&gt;screen capturing software&lt;/a&gt; for saving the image/animation.&lt;/p&gt;&#xA;&lt;p&gt;Import of the following files is supported: DIAMDOC, DSF, EDF, DS1, CFG, CIF, CRY, CSD, DAT, PDB, ENT, INS, RES, DAT, IDF, KPL, XYZ, EMO, MOL, MOL2, MDL, CSSR.&lt;/p&gt;&#xA;&lt;p&gt;From Diamond Help Library shipped with version 4.6.4 (stand 2014-10-28):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;h3&gt;Limitations of the Demonstration Version&lt;/h3&gt;&#xA;&lt;p&gt;Note: It depends on the license file, whether Diamond runs in full or in demonstration mode (with the limitations mentioned below).&lt;/p&gt;&#xA;&lt;p&gt;This article informs you about limitations of Diamond running in demonstration mode as compared with Diamond running as full version. &lt;strong&gt;This information is not valid for the full version of Diamond.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The demonstration version is identical with the full version except of the restrictions mentioned below:&lt;/p&gt;&#xA;&lt;p&gt;In case of trouble when using Diamond, please pay attention to the following hints:&lt;/p&gt;&#xA;&lt;h3&gt;No saving&lt;/h3&gt;&#xA;&lt;p&gt;Changes in structure documents cannot be saved in the original file formats of Diamond versions 3 and 4 (the Diamond Document format, &amp;quot;diamdoc&amp;quot;) and the Diamond Structure File format (&amp;quot;DSF&amp;quot;), which has been used by version 2 and 1.x of Diamond.&lt;/p&gt;&#xA;&lt;p&gt;That means, whenever you call one of the functions that save the current structure document either with the &amp;quot;old&amp;quot; file name (&lt;strong&gt;File/Save&lt;/strong&gt;) or with a new file name (&lt;strong&gt;File/Save as...&lt;/strong&gt;), this will fail. Instead, a message box will remember you of this restriction.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, the function &amp;quot;&lt;strong&gt;File/Save all&lt;/strong&gt;&amp;quot; is not available for this reason.&lt;/p&gt;&#xA;&lt;p&gt;If you close a structure document window - either by closing the window, by using the &amp;quot;Close all&amp;quot; command from the &amp;quot;Window&amp;quot; menu, or by closing the application window of Diamond -, this will be closed immediately, even if the structure document has been changed or is new. That means, the usual prompt (&amp;quot;Save modifications in...?&amp;quot; - Yes/No/Cancel) will not appear!&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;Auto Save&amp;quot; function - which you can find on the Desktop tab of the Options dialog (Tools/Options) will not work, too.&lt;/p&gt;&#xA;&lt;h3&gt;&amp;quot;Diamond Demonstration Version&amp;quot; banner&lt;/h3&gt;&#xA;&lt;p&gt;A banner with &amp;quot;Diamond Demonstration Version&amp;quot; will be written into saved bitmaps, Windows Metafiles, and printouts.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gaMnD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gaMnD.png&quot; alt=&quot;Crystal Impact Diamond - main window screenshot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="724" LastActivityDate="2021-01-24T19:07:18.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4209" PostTypeId="1" CreationDate="2021-01-24T22:45:52.920" Score="13" ViewCount="550" Body="&lt;p&gt;I am new to this field, so there is a chance that I am mixing two entirely different concepts together, but it seems to be that static correlation and finite-temperature smearing in DFT are somehow related.&lt;/p&gt;&#xA;&lt;p&gt;As I have understood static correlation comes into existence when the HOMO-LUMO gap is small, so that the ground state and the excited state have energies close to each other. This means one configuration (i.e. one slater determinant) is not good enough to describe the system, and multi-configurational methods have to be used.&lt;/p&gt;&#xA;&lt;p&gt;Finite-temperature smearing (which I have seen mostly in DFT codes) is again used in cases where the HOMO and LUMO levels are close in energy. As they are close in energy they can exchange positions during the SCF iterations, making it difficult to attain convergence. So, the energy levels are allowed to have fractional populations, and the electrons are smeared across orbitals with some scheme like Fermi-Dirac. This fixes the problem (only the SCF convergence or some other problem I am not sure).&lt;/p&gt;&#xA;&lt;p&gt;Now they both look similar to me in that they are attempting to solve the same problem. Intuitively, the electron-smearing looks like a cheap way to represent the average state of a multi-configuration system.&lt;/p&gt;&#xA;&lt;p&gt;So, is there any relation between these two? If so, then can electron-smearing return the static correlation energy? If not, then how/why are they different?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt;: I found this paper by Grimme et. al. (&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.201501887&quot; rel=&quot;noreferrer&quot;&gt;https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.201501887&lt;/a&gt;), where finite temperature DFT is used to visualise static correlation in molecules. However, that paper only deals with visualising the fractional orbital density, but does not go into detail about the relation between correlation and temperature smearing, so my question still remains.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-01-26T21:52:40.477" LastActivityDate="2022-05-17T14:40:18.683" Title="Is there any relation between static correlation and finite-temperature smearing?" Tags="|density-functional-theory|electron-correlation|orbitals|multi-reference|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4210" PostTypeId="2" ParentId="4201" CreationDate="2021-01-24T23:35:21.410" Score="7" Body="&lt;p&gt;You can use QE.6xxx with the support of the hdf5 library. To realize that purpose, you should add the following command when you compile QE:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;--with-hdf5=yes&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;or take a look at the official guide.&lt;/p&gt;&#xA;&lt;p&gt;Then the saved wavefunction can be manipulated with the python package h5py.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import h5py&#xA;read_wf=h5py.File(&amp;quot;wfc1.hdf5&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-03T09:19:26.437" LastActivityDate="2021-02-03T09:19:26.437" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4211" PostTypeId="1" CreationDate="2021-01-25T06:24:10.130" Score="5" ViewCount="48" Body="&lt;p&gt;I wonder why this phenomenon occurs:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Unlike unextended screw dislocations, the extended screw dislocations&#xA;define a specific slip plane, the {111} plane of the fault and it&#xA;will be constrained to move in this plane.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1893" LastEditorUserId="5" LastEditDate="2021-01-25T19:22:53.160" LastActivityDate="2021-01-25T19:22:53.160" Title="A doubt about extended dislocation" Tags="|band-structure|condensed-matter|physical-properties-of-materials|materials-engineering|metals|" AnswerCount="0" CommentCount="3" ClosedDate="2021-08-14T20:09:13.643" ContentLicense="CC BY-SA 4.0" />
  <row Id="4212" PostTypeId="1" AcceptedAnswerId="4213" CreationDate="2021-01-25T12:46:14.167" Score="12" ViewCount="813" Body="&lt;p&gt;I have some general questions about doing the structure relaxation of a thin film structure in VASP. I want to study the how the band structure evolves as we increase the number of layers of the material. The spin-orbit coupling (SOC) was included in the calculation, and I encounter the following question.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Should I turn the ISYM = 0 to also change the shape of the unit cell during the structure relaxation?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Should I include the SOC during the relaxation?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I saw some people doing this structure relaxation will fix the bottom layer of the slab by using the selective dynamic option, when should I use this technique?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-01-26T13:55:46.947" LastActivityDate="2021-01-26T13:55:46.947" Title="Structure relaxation of a thin film structure in VASP" Tags="|density-functional-theory|vasp|cell-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4213" PostTypeId="2" ParentId="4212" CreationDate="2021-01-25T13:13:34.383" Score="11" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Should I turn the ISYM = 0 to also change the shape of the unit cell during the structure relaxation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In essence, you are asking how to build a slab model. One special point is that you should add a large vacuum layer (here I assume that direction is along [001]). The relaxation of the slab model is limited to (100) and (010), so you can't change the shape. Namely, if want to use ISIF=3, you should modify the source file [constr_cell_relax.F] and re-compile your VASP.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Should I include the SOC during the relaxation?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In general, the SOC can be ignored in relaxation.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I saw some people doing this structure relaxation will fix the bottom layer of the slab by using the selective dynamic option, when should I use this technique?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When you study the surface science.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-25T13:13:34.383" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4214" PostTypeId="1" CreationDate="2021-01-25T16:55:58.287" Score="10" ViewCount="157" Body="&lt;p&gt;I'm thinking about doing some computational research about pyrazoline oxidation in chlorinated solvents under light. I've found plausible mechanism (&lt;a href=&quot;https://doi.org/10.1016/j.tetlet.2019.07.023&quot; rel=&quot;nofollow noreferrer&quot;&gt;article&lt;/a&gt;) that involves single electron transfer from the molecule of pyrazoline to dichloroethane (DCE).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Eoglg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Eoglg.png&quot; alt=&quot;Pyrazoline oxydation mechanism&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My main concern is about the second step, as there is electron transfer and change in multiplicity. I'm thinking about broken-symmetry DFT or multi-rerference methods, but I have no experience in them, so I'm not sure about it. What are the approaches to model such types of reactions? (I assume it has something to do with Marcus theory)&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-12-25T22:06:53.843" LastActivityDate="2021-12-25T22:06:53.843" Title="Calculating single electron transfer" Tags="|computational-chemistry|ab-initio-calculations|electronic-structure|molecular-modeling|reaction-mechanism|" AnswerCount="0" CommentCount="6" ClosedDate="2023-02-07T04:12:58.393" ContentLicense="CC BY-SA 4.0" />
  <row Id="4215" PostTypeId="2" ParentId="4209" CreationDate="2021-01-26T01:50:08.040" Score="11" Body="&lt;p&gt;This is a nice thought, but the two are not actually related. In principle, static correlation is completely accounted for in the exchange-correlation functional of Kohn-Sham DFT and there is no need for any mixing of the Kohn-Sham states, in fact it would lead to an incorrect result. In &lt;em&gt;practice&lt;/em&gt;, the exchange-correlation functional is approximated and so static correlation is not fully captured. You could take the Kohn-Sham states as a basis in which to perform a wavefunction-based correlated many-body quantum mechanical method, in which case your electronic states could be represented as a set of partial occupancies of the Kohn-Sham states, but that is not why (or how) partial occupancies arise in Kohn-Sham DFT. (NB partial occupancies can also be used in time-dependent DFT to express excited states in the basis of the original Kohn-Sham states.)&lt;/p&gt;&#xA;&lt;p&gt;There are three main reasons why partial occupancies are often used in Kohn-Sham DFT -- strictly speaking, &lt;em&gt;Mermin&lt;/em&gt;-Kohn-Sham DFT, since it entails Mermin's extension and modification to the Kohn-Sham energy functional:&lt;/p&gt;&#xA;&lt;h2&gt;SCF instabilities&lt;/h2&gt;&#xA;&lt;p&gt;If the Kohn-Sham valence band/HOMO and conduction band/LUMO are close (especially if they are degenerate) then the system can be unstable with respect to the occupation of those states. As a simple example, suppose we have a 2-state system with states A and B. Suppose we start with A occupied, and the particle density comes entirely from state A,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho(\vec{r})=\rho_A(\vec{r})=\vert\psi_A(\vec{r})\vert^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We now construct the Kohn-Sham potential and hence the Hamiltonian, and evaluate the energy expectation values of the two states,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_A = \langle \psi_A \vert \hat{H}[\rho_A] \vert \psi_A\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_B = \langle \psi_B \vert \hat{H}[\rho_A] \vert \psi_B\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is perfectly possible that &lt;span class=&quot;math-container&quot;&gt;$E_B&amp;lt;E_A$&lt;/span&gt;, in which case we now realise that it is state B which should have been occupied, and thus compute the density as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho(\vec{r})=\rho_B(\vec{r})=\vert\psi_B(\vec{r})\vert^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now we recalculate the energy expectation values with the new Hamiltonian,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E^\prime_A = \langle \psi_A \vert \hat{H}[\rho_B] \vert \psi_A\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E^\prime_B = \langle \psi_B \vert \hat{H}[\rho_B] \vert \psi_B\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is it still true that state B is a lower-energy state than A, i.e. &lt;span class=&quot;math-container&quot;&gt;$E^\prime_B &amp;lt; E^\prime_A$&lt;/span&gt;? Not necessarily!&lt;/p&gt;&#xA;&lt;p&gt;If in fact &lt;span class=&quot;math-container&quot;&gt;$E^\prime_A &amp;lt; E^\prime_B$&lt;/span&gt; then we would conclude that A is the lower energy state, and that it is state A which should contribute to the density -- we are right back where we started! This phenomenon is called &lt;em&gt;occupancy sloshing&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This sloshing instability can be quenched by using an eigenvalue smearing function and partial occupancies, just as happens in real systems at finite temperature; however, there is no need for this energy smearing to actually correspond to any physical temperature. The Fermi-Dirac smearing function has quite a long tail, and leads to fractionally occupied states across a wide energy range, which in turn requires a large number of extra states to be computed. For this reason, it is common to use smearing functions which decay more rapidly, such as Gaussians.&lt;/p&gt;&#xA;&lt;h2&gt;Brillouin Zone sampling&lt;/h2&gt;&#xA;&lt;p&gt;A second reason why partial occupancies are sometimes used is in periodic systems such as materials, where the Kohn-Sham states form bands and the Brillouin zone must be sampled. A common method to do this is with a Monkhorst-Pack (or Chadi-Cohen) mesh of &amp;quot;k-points&amp;quot;, and the Kohn-Sham eigenvalues are sampled at these reciprocal-space points. These eigenvalues are taken to be representative of the energy expectation values across the small region of the Brillouin Zone centred on that k-point.&lt;/p&gt;&#xA;&lt;p&gt;If the valence and conduction Kohn-Sham bands cross in energy somewhere in the Brillouin zone, it will not usually occur on one of the sampled k-points. When determining which of the Kohn-Sham states A or B is occupied, the correct answer is neither A nor B, but that one is occupied for part of the region and the other for the remaining part -- in other words, they are fractionally occupied. Since we do not know how the states behave away from these sampling points, it is common to use a Gaussian smearing function as an indicator of the probable occupation.&lt;/p&gt;&#xA;&lt;p&gt;(NB an alternative is to try to interpolate the Kohn-Sham eigenvalues across the Brillouin zone, which is the approach underlying the tetrahedron integration methods.)&lt;/p&gt;&#xA;&lt;p&gt;Since this problem arises from the finite k-point sampling, using a denser sampling mesh allows a smaller energy broadening to be used.&lt;/p&gt;&#xA;&lt;h2&gt;Finite-temperature simulations&lt;/h2&gt;&#xA;&lt;p&gt;A third case where partial occupancies are used is when the phenomenon being modelled only occurs at finite Kohn-Sham temperature, and in this case a Fermi-Dirac smearing function &lt;em&gt;is&lt;/em&gt; usually applied. Since typical &amp;quot;physical&amp;quot; temperatures lead to rather small thermal broadening (typically a tenth of the usual smearing width) the Fermi-Dirac function is sometimes convolved with a broader Gaussian function, akin to &lt;span class=&quot;math-container&quot;&gt;$0~K$&lt;/span&gt; simulations.&lt;/p&gt;&#xA;&lt;p&gt;Note that the Kohn-Sham states are not actually electronic (or quasi-particle) states, they are fictitious auxiliary states. They are often used as approximations to the electronic states, and it is in this context that a physical finite-temperature smearing is justifiable. However, there is no requirement that the temperature-dependence of the Kohn-Sham states reflects the temperature-dependence of the electronic states.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-01-26T01:50:08.040" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4216" PostTypeId="1" AcceptedAnswerId="4217" CreationDate="2021-01-26T11:28:15.270" Score="10" ViewCount="490" Body="&lt;p&gt;hope you are doing well.&#xA;I am trying to study the electronic properties of ZnO doped with transition metals (Co, Ni, Fe) using DFT calculation, I am a beginner on DFT calculation using quantum espresso. After running multiple test with increasing the 'ecutwfc' (kinetic energy cutoff for wavefunctions) and 'conv_thr' (convergence threshold) in my input files I get almost the same total energy.&lt;/p&gt;&#xA;&lt;p&gt;I want to know please how can I make sure that my SCF calculation are correct?&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your help.&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="243" LastEditDate="2021-01-26T13:08:30.433" LastActivityDate="2021-01-26T13:08:30.433" Title="How to make sure that my SCF calculation is correct?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|self-consistent-field|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4217" PostTypeId="2" ParentId="4216" CreationDate="2021-01-26T12:15:15.963" Score="12" Body="&lt;ul&gt;&#xA;&lt;li&gt;First, make sure that the structure is correct.&lt;/li&gt;&#xA;&lt;li&gt;Second, make sure that the structure is relaxed.&lt;/li&gt;&#xA;&lt;li&gt;Third, make sure that all the parameters in your input card are reasonable and the used pseudopotentials are matched with your structure.&lt;/li&gt;&#xA;&lt;li&gt;Fourth, make sure that the self-consistent loop is complete, namely, the convergence threshold of the electronic step is reached.&lt;/li&gt;&#xA;&lt;li&gt;Fifth, compare the total energy with other published results or the electronic structure (band structure/density of states) based on your converged charge density.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-26T12:15:15.963" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4218" PostTypeId="2" ParentId="878" CreationDate="2021-01-26T19:39:43.470" Score="6" Body="&lt;h2&gt;Visualsation of chemical shielding tensors&lt;/h2&gt;&#xA;&lt;p&gt;We just developed a new method that might be used as an alternative. It is denoted visualisation of chemical shielding tensors (VIST). The preprint is &lt;a href=&quot;https://dx.doi.org/10.26434/chemrxiv.13580885&quot; rel=&quot;noreferrer&quot;&gt;available here&lt;/a&gt;. The idea is that we compute the eigenvectors of the chemical shielding tensor at different points in space and visualise them as little dumb-bells. This representation shows local variations and anisotropy in the shielding, which provides information about local aromaticity.&lt;/p&gt;&#xA;&lt;p&gt;The method will be released within &lt;a href=&quot;https://theodore-qc.sourceforge.io/&quot; rel=&quot;noreferrer&quot;&gt;TheoDORE&lt;/a&gt;. So far, only Gaussian is interfaced but we will certainly add different programs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q82iH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q82iH.png&quot; alt=&quot;Visualisation of chemical shielding tensors&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2021-01-26T19:39:43.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4219" PostTypeId="1" CreationDate="2021-01-27T05:02:55.223" Score="6" ViewCount="146" Body="&lt;p&gt;I did a band structure calculation of a thin film structure with different number of atomic layers. I found that the original bulk gap was shifted upward and the Fermi level was shifted downward no matter how many layer I added. I thought this is due to the terminations layer containing some dangling bond, but I’m not sure whether it is the cases. The software I used is VASP. Is there anyway to avoid this?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-01-27T06:43:04.187" LastActivityDate="2021-01-27T06:43:04.187" Title="Fermi level shift downward in the thin film structure" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4220" PostTypeId="2" ParentId="4219" CreationDate="2021-01-27T06:28:46.347" Score="5" Body="&lt;p&gt;You have a band gap in this system?  If so, the fermi level should be ill defined in VASP.  I believe you can use codes such as &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465506001305&quot; rel=&quot;noreferrer&quot;&gt;BoltzTraP&lt;/a&gt; to investigate the relevant properties but I believe VASP defines the fermi energy as the top of the valence band.  The absolute position of the fermi level must be corrected by looking at the energy of the vacuum in a slab calculation.  I believe you can use the LOCPOT file for this.  You also mention the bulk gap shifts upwards, keep in mind that these energies can also be defined fairly arbitrarily.  Determining the absolute position of the valence and conductance band is a fairly complicated task.&lt;/p&gt;&#xA;&lt;p&gt;In simple terms, I would be hesitant to look too deeply into the fermi level in a semiconductor in VASP.  The changes you are seeing might be due to problems with the absolute energy reference and definition of the fermi level.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-01-27T06:28:46.347" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4221" PostTypeId="1" CreationDate="2021-01-27T06:51:35.273" Score="5" ViewCount="66" Body="&lt;p&gt;I do understand how static strain aging occurs and why the yield point comes back if ample time is allotted after a loading and unloading cycles primarily due to diffusion of substitutional and interstitial impurities in the form of Nitrogen and Carbon.However I do not understand how dynamic strain aging(Portvein -LeChatelier effect) works.Particularly the phenomenon and also the mechanism and properties behind it.A detailed explanation behind this will be highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1893" LastEditorUserId="5" LastEditDate="2021-08-14T17:18:54.660" LastActivityDate="2021-08-14T17:18:54.660" Title="What's the difference between dynamic and static strain aging?" Tags="|condensed-matter|crystallography|physical-properties-of-materials|solid-state-physics|" AnswerCount="0" CommentCount="1" ClosedDate="2021-11-29T19:02:12.163" ContentLicense="CC BY-SA 4.0" />
  <row Id="4222" PostTypeId="1" AcceptedAnswerId="4225" CreationDate="2021-01-27T07:40:53.740" Score="7" ViewCount="1332" Body="&lt;p&gt;I want to conduct &lt;code&gt;GGA+U&lt;/code&gt; calculations using &lt;code&gt;Duradev's&lt;/code&gt; approach in &lt;code&gt;VASP&lt;/code&gt; code on a &lt;code&gt;ferromagnetic material&lt;/code&gt; &lt;em&gt;&lt;strong&gt;without any prior knowledge of experimental data&lt;/strong&gt;&lt;/em&gt;. Could you please guide me to how to arrive to the exact &lt;code&gt;(U-J)&lt;/code&gt; value? What are the detailed steps to do that?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-01-27T21:31:43.993" LastActivityDate="2021-01-27T21:31:43.993" Title="How to determine the value of the difference (U-J) in &quot;Dudarev's approach&quot; for GGA+U calculation using the VASP?" Tags="|vasp|magnetism|dft-u|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4223" PostTypeId="1" CreationDate="2021-01-27T10:35:23.903" Score="11" ViewCount="87" Body="&lt;p&gt;The main aim of my venture is to study the effect of the presence of surface ions on the band structure of Si slab using Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;I've tried to use &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwi9i9G99LvuAhUFzTgGHUK3AZQQFjAAegQIAhAD&amp;amp;url=http%3A%2F%2Fiqmol.org%2F&amp;amp;usg=AOvVaw3ttI4KFA8PlXEyWDISybAm&quot; rel=&quot;noreferrer&quot;&gt;iQmol&lt;/a&gt; to attach ligands to the surface. The ligands include &lt;span class=&quot;math-container&quot;&gt;$H^{-1}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$F^{-1}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$Cl^{-1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Br^{-1}$&lt;/span&gt; .&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is that the normal procedure? or is there some proper way (or code) to attach ligands.?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1944" LastActivityDate="2021-01-27T17:23:54.097" Title="How can I properly attach ligands to a surface?" Tags="|density-functional-theory|quantum-espresso|band-structure|surfaces|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4224" PostTypeId="1" CreationDate="2021-01-27T11:45:09.883" Score="9" ViewCount="603" Body="&lt;p&gt;This is a follow-up question to my question posted &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4199/can-i-use-a-higher-threshold-for-calculations-involving-spin-orbit-coupling-soc&quot;&gt;here&lt;/a&gt;. I've been trying to study the effects of spin-orbit coupling (SOC) on the band structure of ferromagnetic (FM) material VSe&lt;span class=&quot;math-container&quot;&gt;$_{2}$&lt;/span&gt;. The input file for the SCF calculation using Quantum ESPRESSO (QE) is given below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './outdir'&#xA;  verbosity = 'high'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =    3.35381&#xA;  nat = 3&#xA;  ntyp = 2&#xA;  ecutwfc = 55&#xA;  ecutrho = 650&#xA;  starting_magnetization(1) = 1&#xA;  starting_magnetization(2) = 0&#xA;  lspinorb = .true.&#xA;  noncolin = .true.&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss = 0.005d0      &#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1e-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA; -0.500000000000000   0.866025403784439   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   2.087308375869810 &#xA;ATOMIC_SPECIES&#xA;  V   50.94150  V.rel-pbe-spnl-kjpaw_psl.1.0.0.UPF&#xA;  Se   78.96000  Se.rel-pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA; Se   0.666666666666667   0.333333333333333   0.774935000000000 &#xA; Se   0.333333333333333   0.666666666666667   0.225065000000000 &#xA; V   0.000000000000000   0.000000000000000   0.000000000000000 &#xA;K_POINTS {automatic}&#xA;  6 6 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This did not converge when I consider the starting_magnetization of Vanadium to be 1 but converges when I assign a starting magnetization of 0 to Vanadium.&lt;/p&gt;&#xA;&lt;p&gt;And I couldn't find any example of SOC being considered for Magnetic systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So is it necessary to start with a starting_magnetization of zero for magnetic systems while considering SOC?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="1218" LastEditDate="2021-02-04T04:14:25.640" LastActivityDate="2021-02-04T04:14:25.640" Title="Can we consider SOC in FM materials using QE?" Tags="|density-functional-theory|quantum-espresso|magnetism|spin-orbit-coupling|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4225" PostTypeId="2" ParentId="4222" CreationDate="2021-01-27T11:49:25.737" Score="3" Body="&lt;p&gt;In short, the &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; values can be calculated with fully &lt;span class=&quot;math-container&quot;&gt;$\textit{ab}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\textit{initio}$&lt;/span&gt; constrained random phase approximation (cRPA method).&lt;/p&gt;&#xA;&lt;p&gt;About the theory of the constrained random phase approximation, you can refer the following paper: section II (B).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.075003&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.075003&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;About the computational details, you can refer to this vaspwiki example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/CRPA_of_SrVO3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/CRPA_of_SrVO3&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-01-27T11:49:25.737" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4226" PostTypeId="2" ParentId="4224" CreationDate="2021-01-27T14:11:58.320" Score="2" Body="&lt;p&gt;As a beginner and to the best of my knowledge&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;spin-orbit coupling is irrelevant to the magnetic properties.&lt;/li&gt;&#xA;&lt;li&gt;Spin-orbit coupling is related to relativity which is increasingly&#xA;important for heavier for elements around Krypton and onward, and&#xA;also if you're aiming for high precision.&lt;/li&gt;&#xA;&lt;li&gt;For convergence, try to  increase electron_maxstep &amp;gt;&amp;gt; 100 (maximum&#xA;number of iterations in a scf step). and set conv_thr (Convergence threshold for selfconsistency) to the default value 1e-6.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1905" LastActivityDate="2021-01-27T14:11:58.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4227" PostTypeId="1" CreationDate="2021-01-27T15:04:28.910" Score="5" ViewCount="33" Body="&lt;p&gt;I've got synchrotron X-ray powder diffraction data where nice mesostructure diffraction peaks are observed at a very low angles. Does anybody know how to gain relevant information from these data? Does there exist an &lt;em&gt;ad hoc&lt;/em&gt; software to manage/fit these data?&lt;/p&gt;&#xA;&lt;p&gt;As observed by TEM, the mesostructure is constituted of almost circular very thin lamellae forming a sort of chain containing tens of these lamellae.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastEditorUserId="5" LastEditDate="2021-08-14T17:14:10.910" LastActivityDate="2021-08-14T17:14:10.910" Title="Fitting of mesostructure diffraction peaks" Tags="|software-recommendations|x-ray-diffraction|mesoscopic-physics|" AnswerCount="0" CommentCount="3" ClosedDate="2021-09-22T01:38:12.387" ContentLicense="CC BY-SA 4.0" />
  <row Id="4228" PostTypeId="2" ParentId="4223" CreationDate="2021-01-27T17:23:54.097" Score="4" Body="&lt;p&gt;Just some thoughts...&lt;/p&gt;&#xA;&lt;p&gt;All depends on what type of study do you want to do.&lt;/p&gt;&#xA;&lt;p&gt;An aside note: studying the interaction or behavior of a ligand attached to a surface is different to study the passivation of that surface with the same ligand.&lt;/p&gt;&#xA;&lt;p&gt;For only one ligand, you can search the surface for symmetry sites and then, manually (just adding it to a distance lower than &lt;span class=&quot;math-container&quot;&gt;$1.5\overset{\circ}{\mathrm{A}}$&lt;/span&gt;), attach the ligand in each site (for covalent bond). In case of noncovalent bond, you can manually put the ligand separated from the surface a distance, and then do several calculations on which you decrease that distance. This will with you the potential energy interaction curve as a function of the ligand-surface distance. Then, you can put the ligand in the position that gave the minimum energy and run a geometry optimization.&lt;/p&gt;&#xA;&lt;p&gt;For several ligands, you can use software like&lt;/p&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;http://m3g.iqm.unicamp.br/packmol/home.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;Packmol&lt;/a&gt;:&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;PACKMOL creates an initial point for molecular dynamics simulations by packing&#xA;molecules in defined regions of space. The packing guarantees that&#xA;short range repulsive interactions do not disrupt the simulations.&lt;/p&gt;&#xA;&lt;p&gt;The great variety of types of spatial constraints that can be&#xA;attributed to the molecules, or atoms within the molecules, makes it&#xA;easy to create ordered systems, such as lamellar, spherical or tubular&#xA;lipid layers.&lt;/p&gt;&#xA;&lt;p&gt;The user must provide only the coordinates of one molecule of each&#xA;type, the number of molecules of each type and the spatial constraints&#xA;that each type of molecule must satisfy.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://github.com/grimme-lab/crest&quot; rel=&quot;nofollow noreferrer&quot;&gt;CREST&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A tool for the automatized exploration of the low-energy chemical structure&#xA;space normally not consisting of any covalent bond break/formation. As&#xA;its name implies, the main application of CREST is the generation of&#xA;conformer ensembles with an algorithm called iMTD-GC, but other&#xA;related applications, such as the screening of different noncovalently&#xA;bound aggregates, or the screening for different protonation sites are&#xA;also implemented.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-01-27T17:23:54.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4229" PostTypeId="2" ParentId="4222" CreationDate="2021-01-27T18:34:15.813" Score="5" Body="&lt;p&gt;Your question isn't quite clear. The Hubbard U/J strictly speaking, depends on a lot of factors - the Hubbard manifold, lattice parameters etc. The values are typically non-transferrable. For example, material A could have a Hubbard 'U' of 4.7 eV whereas material B could have a Hubbard 'U' of 8 eV. There are rigorous way to calculate the value of U/J from first-principles methods, either using a linear-response approach (DFPT), CRPA (constrained-Random phase approximation), LMFTO (Linear muffin tin orbitals) etc.&lt;/p&gt;&#xA;&lt;p&gt;But you need to ask yourself the question, do you want to rigorously calculate the Hubbard U? In some instances, you can do a literature review and find out the range of Hubbard U being used for your material. You can adopt that value and see how your results compare (band-structure, lattice parameters etc).&lt;/p&gt;&#xA;&lt;p&gt;If you chose to just implement a value in your calculation, it is straight-forward. The scheme that you mention is the rotationally invariant scheme - the basis set that describes the occupation matrix has only diagonal elements. This means that you need to specify only one value called &lt;span class=&quot;math-container&quot;&gt;$U_{eff} = U - J $&lt;/span&gt;. So, the input will basically take in &lt;span class=&quot;math-container&quot;&gt;$U_{eff}$&lt;/span&gt;. You don't need to worry about 'J' values. If a DFT paper on the same system reports that they used a value of U=3 eV, you could just adopt the same value and see how your results compare.&lt;/p&gt;&#xA;&lt;p&gt;In the non-rotationally invariant scheme however, you need to mention both U and J explicitly. J, which is inter-site exchange, is typically taken to be 0-20% of U, as a thumb rule in first-principles calculations (Don't quote me on this one, but this is what my P.I. used to say, and what I observed in most calculations)&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-01-27T18:34:15.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4230" PostTypeId="2" ParentId="4222" CreationDate="2021-01-27T19:14:47.350" Score="2" Body="&lt;p&gt;I will present yet another approach.  You know what properties you care about, all you need is to somehow calculate your system without a U value in a correct way.  For example, you may be able to do hybrid functional calculations with HSE06 or HSEsol(HSE06 with PBEsol instead of PBE) that give good agreement with experiments in general.  This can then be used as a starting point to fit the PBE+U or PBEsol+U calculations.&lt;/p&gt;&#xA;&lt;p&gt;For example, if you can expect HSE06 to provide good results you can run an HSE06 calculation to determine band gap/lattice constants etc.  You can then run PBE+U calculations with a range of U values for relevant states(transition metal d states / oxygen p states).  Then it is simply a matter of finding the best fit for your bandgap etc.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2021-01-27T19:24:38.143" LastActivityDate="2021-01-27T19:24:38.143" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4231" PostTypeId="2" ParentId="693" CreationDate="2021-01-28T11:51:01.907" Score="7" Body="&lt;p&gt;The definition of fast and slow is a bit complicated.&lt;/p&gt;&#xA;&lt;p&gt;I just tried an organic molecule with about 100 atoms and ran two jobs: One with def2-TZVP (1647 AO basis sets, 1872 CAOs) and one with cc-pVTZ (1938 AOs, 2205 CAOs). Pure Hartree-Fock single-point energy calculation, both jobs needed 13 SCF iterations.&lt;/p&gt;&#xA;&lt;p&gt;Timings: def2-TZVP 31 minutes, cc-pVTZ 44 minutes&lt;/p&gt;&#xA;&lt;p&gt;Same job but with RI-DFT using PBE functional:&lt;/p&gt;&#xA;&lt;p&gt;Timings: def2-TZVP 81 seconds (15 iterations), cc-pVTZ 94 seconds (13 iterations)&lt;/p&gt;&#xA;&lt;p&gt;So, yes, Dunning basis sets are slower, but for real-life applications the difference is not really grave. Although Susi is of course right that for heavy elements and really large basis sets things are worse...&lt;/p&gt;&#xA;" OwnerUserId="1997" LastActivityDate="2021-01-28T11:51:01.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4232" PostTypeId="2" ParentId="1053" CreationDate="2021-01-28T14:04:39.777" Score="9" Body="&lt;h3&gt;Psi4NumPy&lt;/h3&gt;&#xA;&lt;p&gt;First of all, thanks @uhoh for pointing me towards this question.&lt;/p&gt;&#xA;&lt;p&gt;And as an answer (or rather different P.O.V), I want to suggest taking another look in the direction of PSI4 mainly PSI4NUMPY.&lt;/p&gt;&#xA;&lt;p&gt;LINK: &lt;a href=&quot;https://github.com/psi4/psi4numpy&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/psi4/psi4numpy&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I was recently suggested to this amazing git on my &lt;a href=&quot;https://www.reddit.com/r/comp_chem/comments/l451vf/python_based_geometrical_optimization_of_water/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Reddit post&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PSI4NUMPY contains literally a lot of python codes along with a very good explanation.&lt;br /&gt;&#xA;Psi4, I agree can be a little heavy but if you have Conda installed, it is not that difficult to install and run (as suggested by @Kevin J. M.).&lt;/p&gt;&#xA;&lt;p&gt;Best of luck!&lt;/p&gt;&#xA;" OwnerUserId="2000" LastEditorUserId="5" LastEditDate="2021-01-29T02:45:26.963" LastActivityDate="2021-01-29T02:45:26.963" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4234" PostTypeId="1" AcceptedAnswerId="4301" CreationDate="2021-01-29T12:43:10.127" Score="7" ViewCount="1484" Body="&lt;p&gt;I am trying to discover the fractal dimension of the image of the following dendrite that was obtained by SEM (scanning electron microscope) by the box-counting method (Python). I found this code on the Internet &lt;a href=&quot;https://francescoturci.net/2016/03/31/box-counting-in-numpy/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I tried to place the image to obtain the fractal dimension but it gave me 1.999872162725305, which does not coincide with the literature, as the literature says that usually the fractal dimensions of these structures must be below 1.80. The image found on the site as an example is the Sierpinski triangle whose fractal dimension is log (3)/log (2) and the code gives the right value, but the image has RGB colors and my SEM image is black and white. Is that the reason influencing the wrong result? How can I correct the code in order to obtain a fractal dimension below 1.80 as is supposed? Best regards.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import pylab as pl&#xA; &#xA;def rgb2gray(rgb):&#xA;    r, g, b = rgb[:,:,0], rgb[:,:,1], rgb[:,:,2]&#xA;    gray = 0.2989 * r + 0.5870 * g + 0.1140 * b&#xA;    return gray&#xA; &#xA;image=rgb2gray(pl.imread(&amp;quot;dendrite.png&amp;quot;))&#xA;# finding all the non-zero pixels&#xA;pixels=[]&#xA;for i in range(image.shape[0]):&#xA;    for j in range(image.shape[1]):&#xA;        if image[i,j]&amp;gt;0:&#xA;            pixels.append((i,j))&#xA; &#xA;Lx=image.shape[1]&#xA;Ly=image.shape[0]&#xA;print (Lx, Ly)&#xA;pixels=pl.array(pixels)&#xA;print (pixels.shape)&#xA; &#xA;# computing the fractal dimension&#xA;#considering only scales in a logarithmic list&#xA;scales=np.logspace(0.01, 1, num=10, endpoint=False, base=2)&#xA;Ns=[]&#xA;# looping over several scales&#xA;for scale in scales:&#xA;    print (&amp;quot;======= Scale :&amp;quot;,scale)&#xA;    # computing the histogram&#xA;    H, edges=np.histogramdd(pixels, bins=(np.arange(0,Lx,scale),np.arange(0,Ly,scale)))&#xA;    Ns.append(np.sum(H&amp;gt;0))&#xA; &#xA;# linear fit, polynomial of degree 1&#xA;coeffs=np.polyfit(np.log(scales), np.log(Ns), 1)&#xA; &#xA;pl.plot(np.log(scales),np.log(Ns), 'o', mfc='none')&#xA;pl.plot(np.log(scales), np.polyval(coeffs,np.log(scales)))&#xA;pl.xlabel('log &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;')&#xA;pl.ylabel('log N')&#xA;pl.savefig('sierpinski_dimension.pdf')&#xA; &#xA;print (&amp;quot;The Hausdorff dimension is&amp;quot;, -coeffs[0]) #the fractal dimension is the OPPOSITE of the fitting coefficient&#xA;np.savetxt(&amp;quot;scaling.txt&amp;quot;, list(zip(scales,Ns)))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;SEM image (dendrite.png):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DHVb7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DHVb7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastActivityDate="2021-02-06T20:15:25.560" Title="Fractal dimension (SEM image) using the box-counting method" Tags="|python|fractals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4235" PostTypeId="1" AcceptedAnswerId="4237" CreationDate="2021-01-29T20:43:45.947" Score="7" ViewCount="47" Body="&lt;p&gt;I tested MM calculation of a benzene molecule with Tinker. The following is the xyz file used for the input.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;         12  molden generated tinker .xyz (oplsaa param.)&#xA;  1  C     0.000000    1.402720    0.000000     90   2   3  11&#xA;  2  H     0.000000    2.490290    0.000000     91   1&#xA;  3  C    -1.214790    0.701360    0.000000     90   1   4   5&#xA;  4  H    -2.156660    1.245150    0.000000     91   3&#xA;  5  C    -1.214790   -0.701360    0.000000     90   3   6   7&#xA;  6  H    -2.156660   -1.245150    0.000000     91   5&#xA;  7  C     0.000000   -1.402720    0.000000     90   5   8   9&#xA;  8  H     0.000000   -2.490290    0.000000     91   7&#xA;  9  C     1.214790   -0.701360    0.000000     90   7  10  11&#xA; 10  H     2.156660   -1.245150    0.000000     91   9&#xA; 11  C     1.214790    0.701360    0.000000     90   1   9  12&#xA; 12  H     2.156660    1.245150    0.000000     91  11&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I ran &lt;code&gt;ANALYZE&lt;/code&gt; binary with this file and oplsaa.prm using the D option and then it gives me the details of each interaction.&lt;/p&gt;&#xA;&lt;p&gt;The charge-charge interactions are given as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Charge          1-C        6-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          1-C        7-C            -0.12  -0.12     2.8054      0.7827&#xA;Charge          1-C        8-H            -0.12   0.12     3.8930     -1.1280&#xA;Charge          1-C       10-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          2-H        4-H             0.12   0.12     2.4903      0.8817&#xA;Charge          2-H        5-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          2-H        6-H             0.12   0.12     4.3133      1.0181&#xA;Charge          2-H        7-C             0.12  -0.12     3.8930     -1.1280&#xA;Charge          2-H        8-H             0.12   0.12     4.9806      0.8817&#xA;Charge          2-H        9-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          2-H       10-H             0.12   0.12     4.3133      1.0181&#xA;Charge          2-H       12-H             0.12   0.12     2.4903      0.8817&#xA;Charge          3-C        8-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          3-C        9-C            -0.12  -0.12     2.8054      0.7827&#xA;Charge          3-C       10-H            -0.12   0.12     3.8930     -1.1280&#xA;Charge          3-C       12-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          4-H        6-H             0.12   0.12     2.4903      0.8817&#xA;Charge          4-H        7-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          4-H        8-H             0.12   0.12     4.3133      1.0181&#xA;Charge          4-H        9-C             0.12  -0.12     3.8930     -1.1280&#xA;Charge          4-H       10-H             0.12   0.12     4.9806      0.8817&#xA;Charge          4-H       11-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          4-H       12-H             0.12   0.12     4.3133      1.0181&#xA;Charge          5-C       10-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          5-C       11-C            -0.12  -0.12     2.8054      0.7827&#xA;Charge          5-C       12-H            -0.12   0.12     3.8930     -1.1280&#xA;Charge          6-H        8-H             0.12   0.12     2.4903      0.8817&#xA;Charge          6-H        9-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          6-H       10-H             0.12   0.12     4.3133      1.0181&#xA;Charge          6-H       11-C             0.12  -0.12     3.8930     -1.1280&#xA;Charge          6-H       12-H             0.12   0.12     4.9806      0.8817&#xA;Charge          7-C       12-H            -0.12   0.12     3.4150     -0.6430&#xA;Charge          8-H       10-H             0.12   0.12     2.4903      0.8817&#xA;Charge          8-H       11-C             0.12  -0.12     3.4150     -0.6430&#xA;Charge          8-H       12-H             0.12   0.12     4.3133      1.0181&#xA;Charge         10-H       12-H             0.12   0.12     2.4903      0.8817&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thus, There are only 36 interactions. I thought that the total number of interactions would be 12*11/2=66, but it is a much smaller number. The number of vdW interactions is also the same, 36. What is going on? It is an isolated molecule, so I believe that there's no cutoff issue.&lt;/p&gt;&#xA;" OwnerUserId="1789" LastEditorUserId="5" LastEditDate="2021-01-29T21:55:35.960" LastActivityDate="2021-01-30T00:43:16.397" Title="The number of long-range interaction pairs in Tinker" Tags="|software|computational-chemistry|molecular-mechanics|tinker|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4236" PostTypeId="2" ParentId="3837" CreationDate="2021-01-29T22:39:47.507" Score="4" Body="&lt;p&gt;Just as in normal MD, there are different integration schemes for PIMD. Here's one that I think has a pretty clear description from an algorithmic perspective: &lt;a href=&quot;https://doi.org/10.1063/1.3489925&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.3489925&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The PILE-L algorithm described in that has been implemented in OpenMM. Most of the implementation is in &lt;a href=&quot;https://github.com/openmm/openmm/blob/fce26088352b1d5e650b93a8d1e5a57587ae1f64/plugins/rpmd/platforms/reference/src/ReferenceRpmdKernels.cpp&quot; rel=&quot;nofollow noreferrer&quot;&gt;ReferenceRpmdKernels.cpp&lt;/a&gt;, but other parts of the plugin may also be useful. And, of course, since this is part of a large package, it isn't the simplest implementation possible.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-01-29T22:39:47.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4237" PostTypeId="2" ParentId="4235" CreationDate="2021-01-30T00:43:16.397" Score="5" Body="&lt;p&gt;The charge-charge interactions are only including things which aren't &amp;quot;bonded&amp;quot;, this includes angles, and sometimes 1,4 Torsions. This is because the electrostatic interaction is already included in the parameterization of those potentials.&lt;/p&gt;&#xA;&lt;p&gt;So in your data, this is why we see charge-charge parameters between carbon and a bunch of hydrogens, because they aren't bonded.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-01-30T00:43:16.397" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4238" PostTypeId="2" ParentId="4224" CreationDate="2021-01-30T01:02:13.390" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;And I couldn't find any example of SOC being considered for Magnetic systems.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;There are many examples that consider the effect of SOC in magnetic systems. For example, &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5129311&quot; rel=&quot;nofollow noreferrer&quot;&gt;the monolayer LaBr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; in this paper&lt;/a&gt;, in which the author compares the band structures for three cases as follows:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/tXZw6.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tXZw6.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A bulk case also could be found in this paper: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.122.206401&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. Lett. 122, 206401&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;So is it necessary to start with a starting_magnetization of zero for magnetic systems while considering SOC?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In short, the answer is NO.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The magnetic materials usually are calculated with spin-polarized mode (collinear), in which the electrons are classified into spin-up and spin-down and you only assign the initial magnetic momentum for each atom (just a number).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;However, &lt;strong&gt;for magnetic materials with heavy atoms, you should do the noncollinear magnetic calculations,&lt;/strong&gt; in which you should open the tag of SOC and set the initial magnetic momentum for each atom (a &lt;span class=&quot;math-container&quot;&gt;$1 \times 3$&lt;/span&gt; vector) at the same time.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You may take a look at the explanation about &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/MAGMOM&quot; rel=&quot;nofollow noreferrer&quot;&gt;the initial magnetization in vaspwiki.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For QE, you could take a look at the following tutorial to do noncollinear magnetic calculations:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=AxfW1iSaz_U&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=AxfW1iSaz_U&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-01-30T01:24:22.867" LastActivityDate="2021-01-30T01:24:22.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4240" PostTypeId="1" CreationDate="2021-01-30T16:46:27.240" Score="6" ViewCount="43" Body="&#xA;&lt;p&gt;Is there any simulation program (for example a DFT package) to determine the variation of magnetization M(T) for &lt;a href=&quot;https://en.wikipedia.org/wiki/Magnetic_semiconductor&quot; rel=&quot;nofollow noreferrer&quot;&gt;dilute magnetic semiconductors&lt;/a&gt; or doped semiconductors with different concentrations of dopants?&lt;/p&gt;&#xA;&lt;p&gt;Any suggestion would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="5" LastEditDate="2021-08-14T17:01:39.307" LastActivityDate="2021-08-14T17:01:39.307" Title="Is it possible to calculate the variation of magnetization M(T) for a diluted magnetic semiconductor?" Tags="|density-functional-theory|software-recommendations|magnetism|physical-properties-of-materials|" AnswerCount="0" CommentCount="2" ClosedDate="2022-01-13T04:20:07.917" ContentLicense="CC BY-SA 4.0" />
  <row Id="4241" PostTypeId="1" AcceptedAnswerId="4244" CreationDate="2021-01-30T18:26:47.107" Score="10" ViewCount="195" Body="&lt;p&gt;I've run an IRC (intrinsic reaction coordinates) calculation from my TS (transition state) and got two minima for each side. I am concerned about them.&lt;/p&gt;&#xA;&lt;p&gt;One of them took about 100 steps to be achieved and looks reasonable. But the other is only one step from a TS and doesn't look reasonable, it more resembles a TS itself rather than the product although it lies about 15 kcal/mol lower.&lt;/p&gt;&#xA;&lt;p&gt;So, do I need to optimize the structures I've got from IRC or can I just take their energies?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-01-30T18:29:56.367" LastActivityDate="2021-01-30T18:50:54.617" Title="A concern about IRC results" Tags="|density-functional-theory|gaussian|reaction-mechanism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4242" PostTypeId="5" CreationDate="2021-01-30T18:33:24.053" Score="0" Body="&lt;p&gt;Documentation for OPS at &lt;a href=&quot;http://openpathsampling.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://openpathsampling.org&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="2004" LastEditDate="2021-01-30T22:16:06.417" LastActivityDate="2021-01-30T22:16:06.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4243" PostTypeId="4" CreationDate="2021-01-30T18:33:24.053" Score="0" Body="Questions about the OpenPathSampling (OPS) software for path sampling methods, such as transition path sampling (TPS) and transition interface sampling (TIS). " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-01-30T18:33:24.053" LastActivityDate="2021-01-30T18:33:24.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4244" PostTypeId="2" ParentId="4241" CreationDate="2021-01-30T18:50:54.617" Score="7" Body="&lt;p&gt;I'm surprised that a single geometry step could result in a converged structure that's 15 kcal/mol lower in energy. That is odd, although not impossible. I would recommend carrying out a frequency calculation on the structure. It should, of course, have no imaginary modes. I'd also consider running a &amp;quot;regular&amp;quot; geometry optimization on the resulting structure to make sure that it's not some artifact of the optimization algorithm associated with the IRC calculation. If both of those point to this indeed being a local minimum, then perhaps this is just a very early or late TS closely resembling the reactant or product, respectively. This is not terribly unusual. As a final note, if your system can exhibit multiple plausible spin multiplicities, make sure that you have found the ground state solution for the reactant, TS, and product.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-01-30T18:50:54.617" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4245" PostTypeId="1" CreationDate="2021-01-30T20:12:45.357" Score="12" ViewCount="1513" Body="&lt;p&gt;I am performing an MD simulation involving solid metal. The system is in the NVT ensemble, and I am using the Langevin thermostat (fix Langevin in LAMMPS) to enforce this.&lt;/p&gt;&#xA;&lt;p&gt;I have previously used the Langevin thermostat on ions present in an implicit solvent. The damping parameter was straightforward to set, because I was able to connect it to the viscosity of the fluid.&lt;/p&gt;&#xA;&lt;p&gt;However, I am trying to understand what the analog of viscosity would be for the atomic sites making up a solid metal. Does anyone have experience/pointers with determining an appropriate Langevin damping constant in this case?&lt;/p&gt;&#xA;" OwnerUserId="599" LastEditorUserId="5" LastEditDate="2021-02-20T00:15:38.040" LastActivityDate="2021-05-03T18:27:36.727" Title="Selection of appropriate Langevin damping parameter for MD of solid metal" Tags="|molecular-dynamics|lammps|physical-properties-of-materials|statistical-thermodynamics|thermodynamics|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4246" PostTypeId="1" AcceptedAnswerId="4248" CreationDate="2021-01-31T09:11:03.477" Score="9" ViewCount="515" Body="&lt;p&gt;I want to perform &lt;code&gt;HSEsol (PBEsol + HSE06)&lt;/code&gt; calculation on a material (&lt;em&gt;&lt;strong&gt;monolayer&lt;/strong&gt;&lt;/em&gt;) that doesn't have experimental data available. Could you please tell me how to implement this in the &lt;code&gt;INCAR&lt;/code&gt; file for relaxation purposes ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-01-31T18:07:38.840" Title="How to perform HSEsol in VASP calculations?" Tags="|density-functional-theory|vasp|magnetism|hse06|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4247" PostTypeId="1" CreationDate="2021-01-31T09:55:37.970" Score="7" ViewCount="161" Body="&lt;p&gt;I have a material that contains the transition metal element Sc [3&lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;1], and I want to know your opinions if there will be a difference between GGA and GGA+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; calculation. Knowing that the other elements in the material don't have d orbitals (just s and p).&lt;/p&gt;&#xA;&lt;p&gt;Note: I  haven't yet performed the GGA+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; calculation due to the absence of the &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; value in the literature.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-02-05T00:56:54.377" LastActivityDate="2021-02-05T01:01:48.867" Title="Will there be a difference between GGA and GGA+$U$ for material with Sc element involved?" Tags="|density-functional-theory|vasp|magnetism|dft-u|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4248" PostTypeId="2" ParentId="4246" CreationDate="2021-01-31T17:57:54.567" Score="9" Body="&lt;p&gt;You want the following flags in your INCAR to specify HSEsol:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GGA = PS&#xA;LHFCALC = .TRUE.&#xA;HFSCREEN = 0.2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also recommend setting &lt;code&gt;Algo = All&lt;/code&gt; for smoother SCF convergence. The VASP manual &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LASPH&quot; rel=&quot;noreferrer&quot;&gt;suggests&lt;/a&gt; setting &lt;code&gt;LASPH=.TRUE.&lt;/code&gt; as well for hybrid calculations, but that's a decision for you to make.&lt;/p&gt;&#xA;&lt;p&gt;In the future, if you are ever curious about how to define a given density functional, you can check out all the pre-defined recipes in the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt;. The example for HSEsol is &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/calculators/vasp/create_input.py#L891&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-01-31T18:07:38.840" LastActivityDate="2021-01-31T18:07:38.840" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4249" PostTypeId="1" CreationDate="2021-01-31T18:27:01.243" Score="7" ViewCount="147" Body="&lt;p&gt;Lattice dynamics codes like &lt;code&gt;phonopy&lt;/code&gt; output vibrational frequencies at q-points. Can we get data of vibrational frequencies for each of the atoms in the supercell? (Real and/vs. reciprocal space has always been difficult to grasp.)&lt;/p&gt;&#xA;&lt;p&gt;I understand that phonons are collective lattice vibrations, but it is after all the individual atoms and bonds that vibrate. If the partial density of states (PDoS) is the answer to this question then how do we know which frequencies will be occupied? Also, can it be said that the total DoS is for phonons (lattice (atoms + bonds)) and the PDoS is for atoms?&lt;/p&gt;&#xA;&lt;p&gt;Apologies for the multiple questions, but, I suppose, they are the same question asked differently.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Optional&lt;/strong&gt;&lt;/em&gt; (Motivation behind this question): I wish to design a supercell (DFT) representing a random solid solution. I would like for it to be such that most atoms have more phonon density of states at lower frequencies. The procedure I thought of following was to try out different arrangements (supercells) and study the partial density of states for each of those arrangements. From all of that data, I wanted to figure a way to construct a supercell that could be considered optimal with the objective of more low-frequency vibrations in mind.&lt;/p&gt;&#xA;&lt;p&gt;I thought of two approaches. One, where I explore &lt;a href=&quot;http://www.cohp.de/?fbclid=IwAR1fWhqKiK1lU34RTB0k-QDM7znRzli-lTVOt75xb62PiA9p_HdZEdtB3XQ&quot; rel=&quot;nofollow noreferrer&quot;&gt;orbital overlap between atoms&lt;/a&gt; which I've to read more about. Another, to somehow figure how much and how far each atom vibrates given the chemical environment in its vicinity. This question was motivated by the second approach.&lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="116" LastEditDate="2021-02-05T21:33:29.063" LastActivityDate="2021-02-21T20:19:40.530" Title="Can we translate vibrational frequencies at q-points to vibrational frequencies of atoms?" Tags="|phonons|vibrations|phonopy|phonon-density-of-state|q-points|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4251" PostTypeId="1" AcceptedAnswerId="4280" CreationDate="2021-02-01T15:03:14.023" Score="10" ViewCount="4724" Body="&lt;p&gt;I was trying to understand some indicators about the stability of materials (that basically tell you whether it can be synthesized or not.. right?).&lt;/p&gt;&#xA;&lt;p&gt;Specifically, I'm trying to link the knowledge of formation energy and energy above convex hull.&lt;/p&gt;&#xA;&lt;p&gt;Can you explain me a little better and eventually make some examples of value ranges for these two parameters (formation energy and energy above convex hull)?&lt;/p&gt;&#xA;&lt;p&gt;I'm asking because I'm trying to put up some datasets to work with but still have little domain knowledge.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="2017" LastEditorUserId="2017" LastEditDate="2021-02-01T15:32:56.893" LastActivityDate="2021-02-04T20:25:17.913" Title="Formation energy and Energy above convex hull as indicators of stability" Tags="|computational-chemistry|materials-informatics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4252" PostTypeId="1" CreationDate="2021-02-01T20:57:05.640" Score="11" ViewCount="3402" Body="&lt;p&gt;Does it matter which ensemble you use for a molecular dynamics simulation? Shouldn't they in principle give the same results? Why, historically, was it hard (and desirable) to develop simulations in ensembles other than the microcanonical (NVE) ensemble?&lt;/p&gt;&#xA;" OwnerUserId="2018" LastActivityDate="2021-02-01T22:17:03.947" Title="Which ensemble to use for a molecular dynamics simulation?" Tags="|molecular-dynamics|statistical-thermodynamics|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4253" PostTypeId="2" ParentId="4252" CreationDate="2021-02-01T22:02:02.127" Score="11" Body="&lt;p&gt;It's very hard to answer this definitively unless you are a bit more specific.&lt;/p&gt;&#xA;&lt;p&gt;However, to speak somewhat generally, it is the case that NVE and NVT ensembles become equivalent in certain thermodynamic limits (namely an infinite number of particles). In practice, however, one chooses the ensemble based on the free energy you are interested in sampling, or the experiment you are interested in comparing to.&lt;/p&gt;&#xA;&lt;p&gt;If you are modelling a gas-phase reaction, you probably want the NVE ensemble. Unless there is a buffer gas, then you probably want the NVT. If the process takes place in the liquid phase, you probably want NPT. In my experience, though, it is very rare that NVT and NPT simulations are not both carried out if you know you care about the NPT simulation. They don't tend to give all that different of results for the most part.&lt;/p&gt;&#xA;&lt;p&gt;It also depends a lot on what you are calculating. For instance, if you want to simulate the infrared spectrum of a liquid, then you will probably equilibrate the system in the NVT ensemble at your desired temperature and then carry out an NVE simulation beginning from that equilibrated state. This is because thermostats are designed to de-correlate velocities which will destroy your spectrum calculated from correlation functions.&lt;/p&gt;&#xA;&lt;p&gt;If you are explicitly calculating free energies, then you just choose your ensemble for the free energy you want to compare to. NVE gives you back the internal energy. NVT gives you back the helmholtz free energy. NPT gives you back the Gibbs free energy.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why, historically, was it hard (and desirable) to develop simulations in ensembles other than the microcanonical (NVE) ensemble&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You would have to provide some reference for this, because it seems somewhat doubtful to me that it was ever difficult to develop NVT simulations. As far as I can tell, some of the first MD simulations knew they needed to do something with the velocities in order to keep the temperature constant throughout a simulation. As time went one, more sophisticated thermostats were developed, and it was shown more rigorously that give the right fluctuations to actually sample the canonical ensemble. I don't think this idea was ever particularly difficult to understand though.&lt;/p&gt;&#xA;&lt;p&gt;As to why it was desriable to sample other ensembles, I think that is because it was obvious to people that their MD simulations were not at the appropriate thermodynamic limits as to make ensembles equivalent. Even in modern simulations with many particles and periodic boundary conditions, one will usually get different results depending on the ensemble you choose to use. So, it is desirable to develop different ensembles because MD is not easily capable of reaching the same limits which exist in nature.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-02-01T22:02:02.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4254" PostTypeId="2" ParentId="4252" CreationDate="2021-02-01T22:03:57.373" Score="5" Body="&lt;p&gt;Ensembles are essentially artificial constructs. In the thermodynamic limit (for an infinite system size) and as long as we avoid the neighborhood of phase transitions it is generally believed that there is an equivalence between ensembles.&lt;/p&gt;&#xA;&lt;p&gt;A consequence of the equivalence of ensembles is that the basic thermodynamic properties of a model system may be calculated as averages in any convenient ensemble.&lt;/p&gt;&#xA;&lt;p&gt;For more details, &amp;quot;Computer Simulation of Liquids&amp;quot; by Allen and Tildesley.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-02-01T22:03:57.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4255" PostTypeId="2" ParentId="4252" CreationDate="2021-02-01T22:08:17.850" Score="7" Body="&lt;p&gt;It definitely can matter. The best thing to do is to consider the experiment you are comparing to, even if that experiment hasn't actually been done yet. In many cases, that means you want to run dynamics in the NPT ensemble (since bench experiments tend to be at fixed pressure and temperature).&lt;/p&gt;&#xA;&lt;p&gt;Here's an example where we &lt;em&gt;know&lt;/em&gt; we won't get the same results between NVE and NVT: Consider the calculation of the rate (we can do this in 1D), but assume that the barrier height is just below the total energy for the NVE ensemble. The rate is 0: it can never cross the barrier.&lt;/p&gt;&#xA;&lt;p&gt;However, in NVT with an average energy equal to the energy of your NVE ensemble, the rate will &lt;em&gt;not&lt;/em&gt; be zero! Sometimes the thermal energy is enough to push you over the barrier.&lt;/p&gt;&#xA;&lt;p&gt;I think I've already covered why it is desirable (we want to compare with experiment!) I'm not sure I'd describe as being all that hard to do, but:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Thermostats and barostats came after NVE because we've had Newton's equations since long before modern statistical mechanics. Newton's ideas were necessary to inspire people like Boltzmann, not to mention the early computational chemists.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Dynamics with a thermostat or barostat aren't actually &amp;quot;real.&amp;quot; They're modeling what should be many different trajectories (or a much larger system) by using only one trajectory. This is how you get problems like the lack of ergodicity in Nosé-Hoover on the harmonic oscillator.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Should you worry that you're using an NVT integrator to model a system that is really NVE? Typically only if your system is small/gas phase. Larger condensed phase system have enough chaos that it doesn't matter.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-02-01T22:17:03.947" LastActivityDate="2021-02-01T22:17:03.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4256" PostTypeId="1" CreationDate="2021-02-02T07:48:26.477" Score="6" ViewCount="128" Body="&lt;p&gt;I have conducted HSEsol relaxation on a monolayer unit cell of 3 atoms using VASP, with the settings below :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE = 2&#xA;&#xA;# Self Consistent Calculation step:&#xA;ISTART = 0&#xA;ICHARG = 2&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 600 eV&#xA;EDIFF = 1.0E-7&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;ALGO = Normal&#xA;LCHARG = .FALSE.&#xA;LWAVE = .FALSE.&#xA;&#xA;#Relaxation:&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;IBRION = 2&#xA;ISIF = 3&#xA;NSW = 100&#xA;EDIFFG = -0.001&#xA;GGA COMPAT = .FALSE.&#xA;NBANDS = 24&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 1*2.0 2*0.0&#xA;LASPH      = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;AMIX     = 0.2&#xA;BMIX     = 0.00001&#xA;AMIX_MAG = 0.8&#xA;BMIX_MAG = 0.00001&#xA;&#xA;#HSEsol:&#xA;GGA = PS&#xA;LHFCALC = .TRUE.&#xA;HFSCREEN = 0.2&#xA;PRECFOCK=Fast    &#xA;&#xA;K-mesh&#xA;0&#xA;G&#xA;6 6 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you think that these settings are accurate enough to continue with them ? Should I increase &lt;code&gt;PRECFOCK&lt;/code&gt; to &lt;code&gt;Normal&lt;/code&gt; or No ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-02-02T18:15:36.483" LastActivityDate="2021-02-02T18:15:36.483" Title="Are these settings for HSEsol accurate enough?" Tags="|density-functional-theory|vasp|magnetism|hse06|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4257" PostTypeId="1" CreationDate="2021-02-02T09:37:25.147" Score="9" ViewCount="248" Body="&lt;p&gt;I have plotted the density of states (DOS) for my System with Hydrogen-rich and hydrogen lean &lt;a href=&quot;https://i.stack.imgur.com/SpN2H.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SpN2H.png&quot; alt=&quot;See Figure&quot; /&gt;&lt;/a&gt;. When the system is Hydrogen lean, the valence band maximum (HOMO) shifted towards Fermi level and bandgap of the system decreased.&#xA;How I can explain this DOS in terms of pi, pi*, sigma, sp3, sp2, localization, and delocalization of charge?&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-07-28T16:35:07.587" LastActivityDate="2021-07-28T16:35:07.587" Title="How to analyze density of states?" Tags="|density-of-states|hydrogen-bonds|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4258" PostTypeId="1" AcceptedAnswerId="8540" CreationDate="2021-02-02T09:41:31.153" Score="6" ViewCount="1328" Body="&lt;p&gt;I want to calculate the redox potential for a molecule in water using Gaussian. I found a tutorial at &lt;a href=&quot;http://ursula.chem.yale.edu/%7Ebatista/classes/tutorials/redoxpotentials.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, but I'm got confused about the units at the end.&lt;/p&gt;&#xA;&lt;p&gt;They have a result for the Gibbs Free Energy of solvation of &lt;span class=&quot;math-container&quot;&gt;$-532680$&lt;/span&gt;, but I am not sure if it is in Volts or Hartrees. The tutorial says it is all in Hartree, but at the end, they compare with a value in Volts.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://ursula.chem.yale.edu/%7Ebatista/classes/tutorials/redoxpotentials.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tutorial on Ab Initio Redox Potential Calculations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="7" LastEditDate="2022-01-12T15:08:26.987" LastActivityDate="2022-01-12T16:25:17.497" Title="Units of energy in Gaussian" Tags="|density-functional-theory|gaussian|redox|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4259" PostTypeId="2" ParentId="4258" CreationDate="2021-02-02T09:47:55.400" Score="4" Body="&lt;p&gt;As far as I know, Gaussian outputs energy in Hartrees if other is not stated explictly.&lt;/p&gt;&#xA;&lt;p&gt;Also the tutorial says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The values obtained in Gaussian forthis exercise are in Hartree.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So, I think it should be in Hartrees.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-02-02T09:47:55.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4260" PostTypeId="1" CreationDate="2021-02-02T10:20:57.160" Score="5" ViewCount="1529" Body="&lt;p&gt;I am &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0966979509000892&quot; rel=&quot;noreferrer&quot;&gt;following this paper&lt;/a&gt; to calculate the formation enthalpy of MgCu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, in which the formation enthalpy is defined as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/y1TP0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y1TP0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(Mg&lt;span class=&quot;math-container&quot;&gt;$_x$&lt;/span&gt;X&lt;span class=&quot;math-container&quot;&gt;$_y$&lt;/span&gt;) is the total energy of the compound, and &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(Mg) and &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(X) are the total energies of pure elements in their stable structures. Since the influence of pressure on the condensed phases is ignored and the energies are calculated at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K without any entropic contributions, the energy of formation is taken to be the enthalpy of formation.&lt;/p&gt;&#xA;&lt;p&gt;Based on this, I calculated the formation enthalpy of MgCu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. The calculation flow is shown below:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The ground state energy for &lt;a href=&quot;https://materialsproject.org/materials/mp-1038/&quot; rel=&quot;noreferrer&quot;&gt;the conventional cell of bulk MgCu&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;&lt;/a&gt; with Fd&lt;span class=&quot;math-container&quot;&gt;$\bar{3}$&lt;/span&gt;m space group:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(MgCu2)=-.75231981E+02 (eV)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The ground state energy for the conventional cell of bulk Mg with P6&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;/mmc space group:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(Mg)=-.30124735E+01 (eV)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The ground state energy for the conventional cell of bulk Cu with Fm&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;m space group:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(Cu)=-.14921761E+02 (eV)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Then the enthalpy of formation is estimated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta E_f$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(MgCu2) - &lt;span class=&quot;math-container&quot;&gt;$\dfrac{1}{3}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(Mg) - &lt;span class=&quot;math-container&quot;&gt;$\dfrac{2}{3}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; (Cu) = -64.2799825 (eV)&lt;/p&gt;&#xA;&lt;p&gt;In the reference paper, the unit kJ/mol is utilized. Due to &lt;a href=&quot;http://www.colby.edu/chemistry/PChem/Hartree.html&quot; rel=&quot;noreferrer&quot;&gt;1eV=96 kJ/mol&lt;/a&gt;, then the enthalpy of formation in kJ/mol is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta E_f$&lt;/span&gt; = -64.2799825 (eV) = -6170.87832 (kJ/mol)&lt;/p&gt;&#xA;&lt;p&gt;which is very different from the result of the reference paper:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/hHTBg.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hHTBg.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I am missing?&lt;/p&gt;&#xA;&lt;p&gt;PS: the lattice constants for all structures are kept the same and all results are also calculated by VASP package with consistent parameters.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-03T11:19:18.527" Title="How to calculate the enthalpy of formation?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4261" PostTypeId="2" ParentId="4260" CreationDate="2021-02-02T12:53:37.813" Score="6" Body="&lt;p&gt;I haven't been able to resolve everything, but here are some thoughts.&lt;/p&gt;&#xA;&lt;p&gt;First, the form of Equation (1) assumes the energies are given on a per atom basis.&lt;/p&gt;&#xA;&lt;p&gt;Second, try comparing the Materials Project energies against your energies. For example, with 24-, 2-, and 4-atom cells for MgCu2, Mg, and Cu, respectively:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MgCu2:  &lt;a href=&quot;https://materialsproject.org/materials/mp-1038/#calculation-summary&quot; rel=&quot;nofollow noreferrer&quot;&gt;-3.3975&lt;/a&gt; &lt;strong&gt;vs.&lt;/strong&gt; -3.1347 [= -75.231981 / 24] eV/atom;&lt;/li&gt;&#xA;&lt;li&gt;Mg:        &lt;a href=&quot;https://materialsproject.org/materials/mp-153/#calculation-summary&quot; rel=&quot;nofollow noreferrer&quot;&gt;-1.5908&lt;/a&gt; &lt;strong&gt;vs.&lt;/strong&gt; -1.5062 [= -3.0124735 / 2] eV/atom;&lt;/li&gt;&#xA;&lt;li&gt;Cu:        &lt;a href=&quot;https://materialsproject.org/materials/mp-30/#calculation-summary&quot; rel=&quot;nofollow noreferrer&quot;&gt;-4.0992&lt;/a&gt; &lt;strong&gt;vs.&lt;/strong&gt; -3.7304 [= -14.921761 / 4] eV/atom.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;All three agree reasonably well.&lt;/p&gt;&#xA;&lt;p&gt;Finally, note that inserting the Materials Project energies into Equation (1) yields -0.134 eV/atom, matching the Materials Project formation energy given for MgCu2. Doing the same for your energies yields -0.146 eV/atom. &lt;em&gt;However&lt;/em&gt;, these values convert to -12.9 kJ/mol-atoms and -14.0 kJ/mol-atoms, respectively, which makes me a little skeptical of the -4.75 kJ/mol-atoms given in the paper.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-02-03T11:19:18.527" LastActivityDate="2021-02-03T11:19:18.527" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4262" PostTypeId="2" ParentId="4256" CreationDate="2021-02-02T12:59:29.637" Score="4" Body="&lt;p&gt;This is the common case of needing to do convergence tests, but lets estimate based on prior experience.  Your ENCUT is probably high enough, 600 is almost surely greater than ENMAX depending on what elements you are using.  Your KPOINTS are also sufficient for geometry relaxation at the HSEsol level in my experience, even for really small structures.&lt;/p&gt;&#xA;&lt;p&gt;Obviously you will use a higher number of k points for the band structure since you need to trace the band path, so I won't address that as a lack of convergence.  You will also need to increase k points for the density of states, probably.  Without seeing a structure, I can say that there is a good chance it is worth the time to do the finest grid of k points you can afford to do.  If this is doable for geometry relaxation, I strongly suspect that you can afford more time for the density of states.&lt;/p&gt;&#xA;&lt;p&gt;Finally, EDIFF is probably overconverged.  A value of 1.0E-5 is probably sufficient for a geometry relaxation, you can rerun with 1.0E-7 afterwards to make sure nothing significantly changes.  I am also unsure that you need GGA_COMPAT, I think it defaults to false.  The mixer settings should also probably not be changed unless you have an issue.  Before trying those mixing settings, try ALGO=All first.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-02-02T12:59:29.637" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4263" PostTypeId="1" CreationDate="2021-02-02T18:54:38.360" Score="11" ViewCount="385" Body="&lt;p&gt;When doing a computer simulation, what’s the best way to prepare a starting configuration to avoid biasing your results?&lt;/p&gt;&#xA;&lt;p&gt;The book &lt;em&gt;Computer Simulation of Liquids&lt;/em&gt; suggests putting the molecules on an fcc lattice, but is that optimal?&lt;/p&gt;&#xA;&lt;p&gt;I know there are programs like PACKMOL that try to pack the molecules in a more or less random starting configuration.&lt;/p&gt;&#xA;&lt;p&gt;Or, as I've been told, should you set up the initial configuration using one of the previously mentioned methods (which one?) and run it at high temperature and then cool it down (if so why, how high, and how exactly should you cool it down)?&lt;/p&gt;&#xA;&lt;p&gt;Finally, how does the answer vary based on the type of system you wish to simulate, e.g., molecular liquid, polymer, protein, ...?&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastActivityDate="2021-02-06T18:50:30.800" Title="Starting configuration for a molecular simulation" Tags="|molecular-dynamics|monte-carlo|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4264" PostTypeId="2" ParentId="4263" CreationDate="2021-02-02T19:31:54.953" Score="10" Body="&lt;p&gt;All depends on what are you working on.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When doing a computer simulation, what’s the best way to prepare a starting configuration to avoid biasing your results?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If working with molecules in gas phase (isolated systems):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;you can draw them in your favorite program, save them as 3D model, and then do a simple Molecular Mechanics geometry optimization.&lt;/li&gt;&#xA;&lt;li&gt;you can download the file with the structure from an online databases. Some of them already have the structure in 3D, but some has in 2D (smile format, for example). In the later case, you have to convert to 3D and do a geometry optimization.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you are interested in working with molecules in solid phase (periodic systems):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;search for crystallographic information in online databases.&lt;/li&gt;&#xA;&lt;li&gt;obtain the 3D structure (see above), and use specialized software that generate random crystals that uses as inputs the molecules and the crystal information.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The book Computer Simulation of Liquids suggests putting the molecules on an fcc lattice, but is that optimal?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you are working with isolated system, the answer is no.&#xA;If you are working with periodic system, does your system has a FCC symmetry? If yes, ok. If not, then, no, it is not optimal.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I know there are programs like PACKMOL that try to pack the molecules in a more or less random starting configuration.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The idea behind PACKMOL is not pack molecules. The idea is to help setting an initial structure file for running molecular dynamics simulations for specific systems.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Or, as I've been told, should you set up the initial configuration using one of the previously mentioned methods (which one?) and run it at high temperature and then cool it down (if so why, how high, and how exactly should you cool it down)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Again, all depends on what are you working on. For example, if you need the electronic structure of a molecule (molecular orbitals, electron density, charges, electrostatic potential), you don't need to run any simulation like that.&#xA;If you are studying how a group of molecules crystalize or how a system of magnetic particles (spins) behave, then, yes, it is useful.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Finally, how does the answer vary based on the type of system you wish to simulate, e.g., molecular liquid, polymer, protein, ...?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As wrote above, the correct answer strongly depends on what you want.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-02-02T19:31:54.953" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4265" PostTypeId="2" ParentId="4257" CreationDate="2021-02-02T21:43:06.650" Score="4" Body="&lt;p&gt;In order to do that, you need to use the Partial Density of States (PDOS) were you can have the contribution of each atom/orbital to the DOS.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-02-02T21:43:06.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4266" PostTypeId="1" AcceptedAnswerId="4271" CreationDate="2021-02-02T22:27:21.613" Score="10" ViewCount="1538" Body="&lt;p&gt;Following the answer to my question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4201/what-is-the-best-program-to-manipulate-numerical-dft-wavefunctions-to-calculate&quot;&gt;What is the best program to manipulate numerical DFT wavefunctions to calculate custom matrix elements?&lt;/a&gt;,&#xA;I compiled Quantum ESPRESSO with the hdf5 flag on, and now have wfcX.hdf5 output for each K point labeled by X. When I analyze these .hdf5 files in Python, it appears to be an array with 'Miller Indices' and 'evc' values (which are wavefunctions). These evcs are given as an array (row vector with size (1, 10000) for instance). However, this confuses me for two reasons, because:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;All entries of evc are real numbers. I expected wavefunctions to&#xA;be complex numbers in general. When I used pw_export.x with an earlier version of Quantum ESPRESSO, I got index.xml, which gives eigenvectors as a list of 2-column rows (columns that I assumed corresponded to the real and imaginary parts of the eigenvector).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There are many rows for the wavefunction of a single k point. I expected just one complex-valued wavefunction per k point. When I plotted the 1D array 'evc', I saw something like a highly oscillating function that was peaked at the origin but then looked as if it converged to 0 (as in the picture below). This makes me question whether these are just results of iterations until convergence was reached.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/obksr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/obksr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Could anyone clarify for me what's going on? If this evc isn't what I want, how do I get the eigenvector at each k point? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-02-05T02:09:27.473" LastActivityDate="2021-02-05T02:09:27.473" Title="How to understand the wavefunction outputed by QE with HDF5 format?" Tags="|quantum-espresso|ab-initio-calculations|high-performance-computing|python|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4267" PostTypeId="1" AcceptedAnswerId="4295" CreationDate="2021-02-03T01:17:02.593" Score="10" ViewCount="358" Body="&lt;p&gt;I started playing with the &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;XTB program&lt;/a&gt; (XTB is developed by Prof. Grimme group's, is based on tight binding and uses the &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/gfnff.html&quot; rel=&quot;noreferrer&quot;&gt;GFN force field&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: How can I calculate/plot the molecular orbitals?&lt;/strong&gt;&#xA;I just found the inputs needed to calculate but not how to export in order to plot.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-02-03T11:37:27.810" LastActivityDate="2021-02-06T01:18:35.827" Title="How to calculate/plot molecular orbitals with XTB?" Tags="|orbitals|xtb|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4268" PostTypeId="2" ParentId="4257" CreationDate="2021-02-03T06:08:40.420" Score="9" Body="&lt;p&gt;As noted by @Camps, you can gain a lot of information from a projected density of states by looking at the contribution of a given orbital. However, it won't directly tell you a  lot of information about &amp;quot;bonding character,&amp;quot; as you mention in your follow-up comment.&lt;/p&gt;&#xA;&lt;p&gt;If you are specifically interested in &amp;quot;bonding character&amp;quot; when using a plane-wave DFT code, you're going to need to carry out a population analysis dedicated to such a task. Arguably, your best bet would be to carry out a Crystal Orbital Hamilton Population (COHP) analysis using &lt;a href=&quot;http://www.cohp.de/&quot; rel=&quot;noreferrer&quot;&gt;LOBSTER&lt;/a&gt;. Another option that can provide similar orbital-based information is a periodic Natural Bonding Orbital (NBO) analysis, as implemented in &lt;a href=&quot;https://github.com/jrschmidt2/periodic-NBO&quot; rel=&quot;noreferrer&quot;&gt;this code&lt;/a&gt;. There is also the Solid State Adaptive Natural Density Partitioning (SSAdNDP) method, as implemented &lt;a href=&quot;http://ion.chem.usu.edu/%7Eboldyrev/ssadndp.php&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-02-03T08:00:54.110" LastActivityDate="2021-02-03T08:00:54.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4269" PostTypeId="1" CreationDate="2021-02-03T08:17:24.760" Score="10" ViewCount="2480" Body="&lt;p&gt;I could not find any good source for this type of calculation. I'd be very appreciated if someone who is experienced with that to show it step by step&lt;/p&gt;&#xA;" OwnerUserId="1684" LastActivityDate="2024-02-15T20:56:53.380" Title="How to carry out HSE06+SOC band structure calculation using VASP?" Tags="|density-functional-theory|vasp|hse06|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4270" PostTypeId="2" ParentId="4269" CreationDate="2021-02-03T09:10:44.107" Score="15" Body="&lt;p&gt;I assume that your structure is fully relaxed.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(I) Self-consistent field calculation at DFT-PBE level with spin-orbit coupling (SOC) to obtain the converged charge density.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SOC related tags:&#xA; LSORBIT=.TRUE.&#xA; SAXIS= 0 0 1&#xA; ISYM=0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(II) Usual band calculation at DFT-PBE level with SOC by reading the converged charge density at step I. Note that the k-sampling assigned in KPOINTS can be found in OUTCAR and used in a subsequent step.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;grep &amp;quot;k-points in reciprocal lattice and weights&amp;quot; OUTCAR -A n (n is the total k points in your band path.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(III) Self-consistent field calculation at HSE06 level with SOC by reading the converged charge density at step I.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#HSE06 related tags:&#xA; LHFCALC = .TRUE.&#xA; HFSCREEN = 0.2&#xA; ALGO = Damped&#xA; TIME = 0.4&#xA; PRECFOCK=F&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(IV) Non-self-consistent field calculation at HSE06 level with SOC by reading the converged wave function at step III. ( One special point is we first need to move the IBZKPT at step III to the KPOINTS file and also add the k-points read from OUTCAR at step II to this KPOINTS file with zero weight.)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#HSE06 related tags:&#xA; LHFCALC = .TRUE.&#xA; HFSCREEN = 0.2&#xA; ALGO = Normal&#xA; TIME = 0.4&#xA; PRECFOCK=F&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(V) Read the EIGENVALUE to plot bandstructure (You can make a comparison with the result of step II). Note that the EIGENVALUE from SCF  IBZKPT at step III needs to be excluded. For this step, you may take a look at this post: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3666/how-to-remove-hse06-bandstructure-fake-k-points-from-vasprun-xml-file/3683#3683&quot;&gt;How to remove the fake k-points from vasprun.xml file in the calculation of HSE06 band structure?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ref: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2023-03-30T03:20:12.767" LastActivityDate="2023-03-30T03:20:12.767" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4271" PostTypeId="2" ParentId="4266" CreationDate="2021-02-03T10:33:17.013" Score="9" Body="&lt;ul&gt;&#xA;&lt;li&gt;The DATASET &amp;quot;MillerIndices&amp;quot; stores the vectors of reciprocal space, namely &lt;span class=&quot;math-container&quot;&gt;$n_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$n_2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$n_3$&lt;/span&gt; in following equation:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\dfrac{1}{\sqrt{V}}e^{i\vec{G}\cdot\vec{r}}=\dfrac{1}{\sqrt{V}}e^{i(n_1 \vec{a}_1+n_2\vec{b}_2+n_3\vec{b}_3)\cdot\vec{r}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I assume that you have &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; plane waves, then the data space should be &lt;span class=&quot;math-container&quot;&gt;$(m,3)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;As you said, the DATASET &amp;quot;evc&amp;quot; stores the wave function.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I further assume you have &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; bands, then the data space should be &lt;span class=&quot;math-container&quot;&gt;$n \times (m \times 2)$&lt;/span&gt; array. Due to the HDF5 library can't support the type of complex number, then the complex number generated by QE is stored as two neighborhood real numbers.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The wave function in real space is calculated as follows:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{n\vec{k}}(\vec{r})=\dfrac{1}{\sqrt{V}}\sum_{\vec{G}}c_{n\vec{k}}(\vec{G}) e^{i(\vec{k}+\vec{G})\cdot\vec{r}}$$&lt;/span&gt;&#xA;in which&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{G}=n_1\vec{b}_1+n_2\vec{b}_2+n_3\vec{b}_3$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{k}=k_1\vec{b}_1+k_2\vec{b}_2+k_3\vec{b}_3$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{r}=r_1\vec{a}_1+r_2\vec{a}_2+r_3\vec{a}_3$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;May it helps.&lt;/p&gt;&#xA;&lt;h2&gt;UPDATE from Question Author:&lt;/h2&gt;&#xA;&lt;p&gt;I found the following data structure for output hdf5 files here: &lt;a href=&quot;https://gitlab.com/QEF/q-e/snippets/1869219&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/snippets/1869219&lt;/a&gt;. I believe this makes a complete answer.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;HDF5 &amp;quot;wfc17.hdf5&amp;quot; {&#xA;GROUP &amp;quot;/&amp;quot; {&#xA;   ATTRIBUTE &amp;quot;gamma_only&amp;quot; {&#xA;      DATATYPE  H5T_STRING {&#xA;         STRSIZE 7;&#xA;         STRPAD H5T_STR_SPACEPAD;&#xA;         CSET H5T_CSET_ASCII;&#xA;         CTYPE H5T_C_S1;&#xA;      }&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): &amp;quot;.FALSE.&amp;quot;&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;igwx&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 4572&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;ik&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 17&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;ispin&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 1&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;nbnd&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 36&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;ngw&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 4840&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;npol&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 1&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;scale_factor&amp;quot; {&#xA;      DATATYPE  H5T_IEEE_F64LE&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): 1&#xA;      }&#xA;   }&#xA;   ATTRIBUTE &amp;quot;xk&amp;quot; {&#xA;      DATATYPE  H5T_ARRAY { [3] H5T_IEEE_F64LE }&#xA;      DATASPACE  SCALAR&#xA;      DATA {&#xA;      (0): [ 0, 0.130217, 0.10252 ]&#xA;      }&#xA;   }&#xA;   DATASET &amp;quot;MillerIndices&amp;quot; {&#xA;      DATATYPE  H5T_STD_I32LE&#xA;      DATASPACE  SIMPLE { ( 4572, 3 ) / ( 4572, 3 ) }&#xA;      ATTRIBUTE &amp;quot;bg1&amp;quot; {&#xA;         DATATYPE  H5T_ARRAY { [3] H5T_IEEE_F64LE }&#xA;         DATASPACE  SCALAR&#xA;         DATA {&#xA;         (0): [ 0.67663, 0.390652, -0 ]&#xA;         }&#xA;      }&#xA;      ATTRIBUTE &amp;quot;bg2&amp;quot; {&#xA;         DATATYPE  H5T_ARRAY { [3] H5T_IEEE_F64LE }&#xA;         DATASPACE  SCALAR&#xA;         DATA {&#xA;         (0): [ 0, 0.781305, 0 ]&#xA;         }&#xA;      }&#xA;      ATTRIBUTE &amp;quot;bg3&amp;quot; {&#xA;         DATATYPE  H5T_ARRAY { [3] H5T_IEEE_F64LE }&#xA;         DATASPACE  SCALAR&#xA;         DATA {&#xA;         (0): [ 0, -0, 0.615118 ]&#xA;         }&#xA;      }&#xA;      ATTRIBUTE &amp;quot;doc&amp;quot; {&#xA;         DATATYPE  H5T_STRING {&#xA;            STRSIZE 77;&#xA;            STRPAD H5T_STR_SPACEPAD;&#xA;            CSET H5T_CSET_ASCII;&#xA;            CTYPE H5T_C_S1;&#xA;         }&#xA;        DATASPACE  SCALAR&#xA;         DATA {&#xA;         (0): &amp;quot;Miller Indices of the wave-vectors, same ordering as wave-function components&amp;quot;&#xA;         }&#xA;      }&#xA;   }&#xA;   DATASET &amp;quot;evc&amp;quot; {&#xA;      DATATYPE  H5T_IEEE_F64LE&#xA;      DATASPACE  SIMPLE { ( 36, 9144 ) / ( 36, 9144 ) }&#xA;      ATTRIBUTE &amp;quot;doc:&amp;quot; {&#xA;         DATATYPE  H5T_STRING {&#xA;            STRSIZE 145;&#xA;            STRPAD H5T_STR_SPACEPAD;&#xA;            CSET H5T_CSET_ASCII;&#xA;            CTYPE H5T_C_S1;&#xA;         }&#xA;         DATASPACE  SCALAR&#xA;         DATA {&#xA;         (0): &amp;quot;Wave Functions, (npwx,nbnd), each contiguous line represents a wave function,  each complex coefficient is given by a couple of contiguous floats&amp;quot;&#xA;         }&#xA;      }&#xA;   }&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-05T00:07:14.667" LastActivityDate="2021-02-05T00:07:14.667" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4272" PostTypeId="1" CreationDate="2021-02-03T11:53:18.990" Score="12" ViewCount="250" Body="&lt;p&gt;Following this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4267/24&quot;&gt;question&lt;/a&gt;, I am interested now in plotting the electrostatic potential as calculated with the &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;XTB program&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I found how to set up the calculation but as a result, I got three files that I don't now how to work with.&lt;/p&gt;&#xA;&lt;p&gt;After using the water molecule as input, I got the following.&lt;/p&gt;&#xA;&lt;p&gt;One file with extension &lt;code&gt;cosmo&lt;/code&gt;, and with content like this (the information was truncated) (file#1):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;span class=&quot;math-container&quot;&gt;$coord_car&#xA;!BIOSYM archive 3&#xA;coordinates from COSMO calculation&#xA;X1       0.00000000000000      0.00000000000000     -0.38936114592126 COSM 1 o  O  0.000&#xA;X1       0.76298445773092      0.00000000000000      0.19468057296063 COSM 1 h  H  0.000&#xA;X1      -0.76298445773092      0.00000000000000      0.19468057296063 COSM 1 h  H  0.000&#xA;end&#xA;$&lt;/span&gt;segment_information&#xA;  1  1      0.00000000000000      1.57591099445267     -0.38936114534154     -0.00427604048599       1.15440000000000      -0.00427604048599 0.000&#xA;  2  1      0.00000000000000     -1.57591099445267     -0.38936114534154     -0.00427604048599       1.15440000000000      -0.00427604048599 0.000&#xA;  3  1      0.00000000000000      0.00000000000000     -1.96527216096131     -0.00835503339507       1.15440000000000      -0.00835503339507 0.000&#xA;  4  1      0.90985266971617      0.90985266971617     -1.29921378330708     -0.00590986896571       1.19439000000000      -0.00590986896571 0.000&#xA;  5  1     -0.90985266971617      0.90985266971617     -1.29921378330708     -0.00590986896571       1.19439000000000      -0.00590986896571 0.000&#xA;  6  1      0.90985266971617     -0.90985266971617     -1.29921378330708     -0.00590986896571       1.19439000000000      -0.00590986896571 0.000&#xA;  7  1     -0.90985266971617     -0.90985266971617     -1.29921378330708     -0.00590986896571       1.19439000000000      -0.00590986896571 0.000&#xA;  8  1      0.58246117666392      0.58246117666392     -1.73285412163484     -0.00756025907295       1.11106000000000      -0.00756025907295 0.000&#xA;  9  1     -0.58246117666392      0.58246117666392     -1.73285412163484     -0.00756025907295       1.11106000000000      -0.00756025907295 0.000&#xA; 10  1      0.58246117666392     -0.58246117666392     -1.73285412163484     -0.00756025907295       1.11106000000000      -0.00756025907295 0.000&#xA; 11  1     -0.58246117666392     -0.58246117666392     -1.73285412163484     -0.00756025907295       1.11106000000000      -0.00756025907295 0.000&#xA; 12  1      0.58246117666392      1.34349300804394     -0.97182234317255     -0.00582141940573       1.11106000000000      -0.00582141940573 0.000&#xA; 13  1     -0.58246117666392      1.34349300804394     -0.97182234317255     -0.00582141940573       1.11106000000000      -0.00582141940573 0.000&#xA;... ... ... ...&#xA;... ... ... ...&#xA;133  3     -0.76298444255169     -0.51862162360869      1.47976456641237      0.00547473780238       1.18123000000000       0.00547473780238 0.000&#xA;134  3     -0.76298444255169      1.28508395669919      0.71330221215478      0.00283726645472       1.18123000000000       0.00283726645472 0.000&#xA;135  3     -0.76298444255169     -1.28508395669919      0.71330221215478      0.00283726645472       1.18123000000000       0.00283726645472 0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The other file with &lt;code&gt;dat&lt;/code&gt; extension (also truncated) (file#2):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 0.0000000000E+00  0.2978039900E+01 -0.7357858600E+00   -0.04276040&#xA; 0.0000000000E+00 -0.2978039900E+01 -0.7357858600E+00   -0.04276040&#xA; 0.0000000000E+00  0.0000000000E+00 -0.3713825800E+01   -0.08355033&#xA; 0.1719372200E+01  0.1719372200E+01 -0.2455158000E+01   -0.05909869&#xA;-0.1719372200E+01  0.1719372200E+01 -0.2455158000E+01   -0.05909869&#xA; 0.1719372200E+01 -0.1719372200E+01 -0.2455158000E+01   -0.05909869&#xA;-0.1719372200E+01 -0.1719372200E+01 -0.2455158000E+01   -0.05909869&#xA; 0.1100692000E+01  0.1100692000E+01 -0.3274619400E+01   -0.07560259&#xA;-0.1100692000E+01  0.1100692000E+01 -0.3274619400E+01   -0.07560259&#xA; 0.1100692000E+01 -0.1100692000E+01 -0.3274619400E+01   -0.07560259&#xA;-0.1100692000E+01 -0.1100692000E+01 -0.3274619400E+01   -0.07560259&#xA; 0.1100692000E+01  0.2538833600E+01 -0.1836477900E+01   -0.05821419&#xA;-0.1100692000E+01  0.2538833600E+01 -0.1836477900E+01   -0.05821419&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;An the last file, has &lt;em&gt;profile&lt;/em&gt; added to the input filename, and has just a few numbers like (file#3):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; -8.529722818781735E-002   2.24382421000418     &#xA; -6.879101666201869E-002   4.48764842000836     &#xA; -5.228480513622003E-002   5.38517810401003     &#xA; -3.577859361042138E-002   6.28270778801170     &#xA; -1.927238208462272E-002  0.897529684001672     &#xA; -2.766170558824065E-003   7.18023747201337     &#xA;  1.374004096697459E-002   5.38517810401003     &#xA;  3.024625249277324E-002   10.7703562080201     &#xA;  4.675246401857190E-002   13.4629452600251     &#xA;  6.325867554437055E-002   4.48764842000836     &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-08-14T16:59:39.890" LastActivityDate="2023-02-17T10:37:00.277" Title="How to plot the electrostatic potential calculated with XTB?" Tags="|electrostatic|xtb|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4273" PostTypeId="1" CreationDate="2021-02-03T13:01:26.417" Score="7" ViewCount="98" Body="&lt;p&gt;In regression models to predict chemical compounds' activities, fingerprints are often used as features. &lt;strong&gt;Should one normalize a fingerprint feature to be in the 0-1 range?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2021-02-03T14:49:02.913" LastActivityDate="2021-02-03T14:49:02.913" Title="Should one normalize the &quot;features&quot; in binary fingerprints?" Tags="|molecular-modeling|machine-learning|" AnswerCount="0" CommentCount="2" ClosedDate="2021-09-05T23:11:30.257" ContentLicense="CC BY-SA 4.0" />
  <row Id="4274" PostTypeId="1" CreationDate="2021-02-04T07:08:11.617" Score="0" ViewCount="328" Body="&lt;p&gt;C60 can refer to any substance composed of molecules with 60 carbon atoms. Buckminsterfullerene on the other hand is specifically the substance composed of soccer ball shape molecules with 60 carbon atoms arranged in a face centered cubic arrangement. According to my question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1473/how-ductile-is-c60&quot;&gt;How ductile is C60?&lt;/a&gt;, if buckminsterfullerene can keep being pulled thinner and thinner like gold, it might be a really good structural material. However, if it's not chemically stable, there is no use in using it even if it can keep being pulled thinner and thinner like gold. So my question is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Has it been proven that buckminsterfullerene is stable?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="5" LastEditDate="2021-02-04T18:50:07.430" LastActivityDate="2021-02-09T07:24:57.697" Title="Has there been any research on the stability of buckminsterfullerene?" Tags="|molecular-modeling|quantum-chemistry|nanostructures|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4275" PostTypeId="2" ParentId="4203" CreationDate="2021-02-04T07:58:14.660" Score="7" Body="&lt;p&gt;There are actually quite a number of tools that can be used to passivate a structure. They all work differently, and none are perfect at what they do. If you're dealing with organic molecules, these codes will work far better than if you're dealing with inorganic complexes.&lt;/p&gt;&#xA;&lt;p&gt;Here is a list of some tools you may be interested in:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://pymol.org/2/&quot; rel=&quot;noreferrer&quot;&gt;PyMOL&lt;/a&gt; has an &lt;a href=&quot;https://pymolwiki.org/index.php/H_Add&quot; rel=&quot;noreferrer&quot;&gt;H Add&lt;/a&gt; function. PyMOL accepts many kinds of formats. Commercial software with a free academic license.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; has an option for automatically adding H atoms to a structure, as described &lt;a href=&quot;https://avogadro.cc/docs/menus/build-menu/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Free and open-source.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.olexsys.org/&quot; rel=&quot;noreferrer&quot;&gt;Olex&lt;/a&gt; has a similar command as PyMOL called &lt;code&gt;hadd&lt;/code&gt;, as described &lt;a href=&quot;http://crystals.otterbein.edu/teaching/docs/olex2_quick_ref.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. This program is widely used when dealing with CIFs. Free software.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://kinemage.biochem.duke.edu/software/reduce.php&quot; rel=&quot;noreferrer&quot;&gt;Reduce&lt;/a&gt;, &lt;a href=&quot;https://www.cgl.ucsf.edu/chimera/docs/ContributedSoftware/addh/addh.html&quot; rel=&quot;noreferrer&quot;&gt;Chimera&lt;/a&gt;, and &lt;a href=&quot;http://openmopac.net/manual/Adding_Hydrogen_atoms.html&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt; can all be used to automatically add H atoms to PDB structures. Free software (for non-commercial users).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;noreferrer&quot;&gt;Quantum ATK&lt;/a&gt; has a &lt;a href=&quot;https://docs.quantumatk.com/tutorials/builder_manual/builder_plugins/builder_plugins.html&quot; rel=&quot;noreferrer&quot;&gt;passivate option&lt;/a&gt;. Commercial software.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://crystalmaker.com/&quot; rel=&quot;noreferrer&quot;&gt;CrystalMaker&lt;/a&gt; has an option for automatically adding H atoms in its Molecule Builder utility, as listed &lt;a href=&quot;http://crystalmaker.com/crystalmaker/specs/index.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. Commercial software.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;noreferrer&quot;&gt;Materials Studio&lt;/a&gt; has an option for automatically adding H atoms. Commercial software.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are likely many, many others.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-02-04T08:11:39.907" LastActivityDate="2021-02-04T08:11:39.907" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4276" PostTypeId="1" CreationDate="2021-02-04T08:43:45.770" Score="5" ViewCount="89" Body="&lt;p&gt;I know how to cleave surfaces with integer Miller indices, however I wonder how I could cleave a &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{3} \times \sqrt{3}) R30$&lt;/span&gt; reconstruction of &lt;span class=&quot;math-container&quot;&gt;$(001)\,\, 4H-SiC$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have found a nice link to O-lattice theory here,&#xA;&lt;a href=&quot;https://www.tf.uni-kiel.de/matwis/amat/def_en/kap_7/backbone/r7_3_1.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.tf.uni-kiel.de/matwis/amat/def_en/kap_7/backbone/r7_3_1.html&lt;/a&gt;&#xA;but I thought there might be a script out there for this purpose.&lt;/p&gt;&#xA;&lt;p&gt;I am currently trying my chances with VESTA!&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your help,&#xA;Roozbeh&lt;/p&gt;&#xA;" OwnerUserId="1963" LastEditorUserId="5" LastEditDate="2021-02-04T15:46:00.210" LastActivityDate="2021-02-04T18:15:23.937" Title="SiC surface reconstruction" Tags="|software-recommendations|surfaces|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4277" PostTypeId="2" ParentId="4274" CreationDate="2021-02-04T16:19:41.940" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Has there been any research on the stability of buckminsterfullerene?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There is, for example, this paper with title &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0009261403017883&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Stability of Buckminsterfullerene, C60&amp;quot;&lt;/a&gt;. It has almost 100 citations.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Has it been proven that buckminsterfullerene is stable?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Stable buckyballs have been made experimentally, and they were also predicted theoretically &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Fullerene#History&quot; rel=&quot;noreferrer&quot;&gt;as far back as the 1960s&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;They are one of the most stable compounds known of that size, and form with an icosohedral symmetry.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-04T16:19:41.940" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4278" PostTypeId="2" ParentId="4276" CreationDate="2021-02-04T18:15:23.937" Score="5" Body="&lt;p&gt;The reconstructed &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{3} \times \sqrt{3})R30$&lt;/span&gt; surface unit cell can be obtained by first applying the rotation matrix&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ \begin{pmatrix}    1.0 &amp;amp; 2.0 &amp;amp; 0.0 \\   -1.0 &amp;amp; 1.0 &amp;amp; 0.0 \\    0.0 &amp;amp; 0.0 &amp;amp; 1.0  &#xA; \end{pmatrix}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;to the primitive bulk unit cell, and then the reconstructed &lt;span class=&quot;math-container&quot;&gt;$(001)$&lt;/span&gt; surface can be cleaved from this unit cell, or the other way around.&lt;/p&gt;&#xA;&lt;p&gt;top view of the primitive&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KGcxE.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KGcxE.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and reconstructed surface&#xA;&lt;a href=&quot;https://i.stack.imgur.com/noKNA.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/noKNA.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Cheers, Roozbeh&lt;/p&gt;&#xA;" OwnerUserId="1963" LastActivityDate="2021-02-04T18:15:23.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4279" PostTypeId="1" AcceptedAnswerId="4281" CreationDate="2021-02-04T19:11:18.833" Score="9" ViewCount="394" Body="&lt;p&gt;Firstly, sorry if this question is too basic for this community but seriously I couldn't find any answer. Does it mean the multiplication of the in-plane lattice constants? For example, lets say following geometry file belongs the graphene.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C: Graphite Lattice&#xA;1.0&#xA; +2.4410462393  +0.0000000000  +0.0000000000 &#xA; -1.2205231197  +2.1140080551  +0.0000000000 &#xA; +0.0000000000  +0.0000000000 +10.0000000000 &#xA;  2&#xA;Cartesian&#xA; +0.0000000000  +0.0000000000  +0.0000000000 &#xA; +0.0000000000  +1.4093387034  +0.0000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So its formula unit surface area is: &lt;code&gt;2.4410462393 x 2.4410462393 = 5.958706742400672&lt;/code&gt;. Am I right? If I'm wrong I'd be very appreciated for the correct logic.&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2021-02-06T02:53:54.090" LastActivityDate="2021-02-06T02:53:54.090" Title="What is the &quot;formula unit surface area&quot;?" Tags="|density-functional-theory|geometry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4280" PostTypeId="2" ParentId="4251" CreationDate="2021-02-04T20:25:17.913" Score="7" Body="&lt;p&gt;Basically, convex hull is a plot of formation energy with respect to the composition which connects phases that are lower in energy than any other phases or a linear combination of phases at that composition. Phases that lie on the convex hull are thermodynamically stable and the ones above it are either metastable or unstable. This plot can only give an idea about the stability of the structure at 0 K. Higher temperature calculation (Phonopy is one of the codes) can assure the stability of the given structure at the working temperature (mostly greater than 0 K).&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2021-02-04T20:25:17.913" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4281" PostTypeId="2" ParentId="4279" CreationDate="2021-02-04T22:44:30.250" Score="9" Body="&lt;p&gt;In the paper you linked, the relevant phrase is &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$A_{\mathrm{fu}}$&lt;/span&gt; is the per formula unit total surface area of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{TiS_2}$&lt;/span&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;per formula unit surface area&amp;quot; part is equivalent to &amp;quot;surface area per formula unit.&amp;quot; So, the full surface area divided by the number of formula units.&lt;/p&gt;&#xA;&lt;p&gt;For the graphene example, it would be half the in-plane surface area of the cell,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{1}{2} \, \mathbf{a}_1 \times \mathbf{a}_2 \approx \frac{1}{2} (2.441)^2 \sin(60\deg) \approx 2.58 ,&#xA;$$&lt;/span&gt;&#xA;because the cell contains two formula units.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-02-05T10:14:59.760" LastActivityDate="2021-02-05T10:14:59.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4282" PostTypeId="2" ParentId="4247" CreationDate="2021-02-05T01:01:48.867" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Will there be a difference between GGA and GGA+ for material with Sc element involved?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The answer is YES as @Andrew Rosen said.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I haven't yet performed the GGA+ calculation due to the absence of the  value in the literature.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You can take a look at &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acsami.8b14037&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper and its supporting materials&lt;/a&gt; and find the &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; value for Sc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-05T01:01:48.867" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4283" PostTypeId="1" AcceptedAnswerId="4285" CreationDate="2021-02-05T10:51:54.673" Score="8" ViewCount="1364" Body="&lt;p&gt;What is the best way to find the binding energy for exciton using &lt;code&gt;VASP&lt;/code&gt;?&#xA;I have heard about the method of calculating it through the dielectric tensor with local field effects and effective masses, but I'm not sure. The computational resources do not allow me to perform the GW-BSE calculations.&#xA;Thank you in advance for your help.&lt;/p&gt;&#xA;" OwnerUserId="1216" LastEditorUserId="1218" LastEditDate="2021-04-05T11:36:21.560" LastActivityDate="2021-04-05T11:36:21.560" Title="How can I find the binding energy for exciton (optical gap) with VASP?" Tags="|vasp|binding-energy|exciton|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4284" PostTypeId="1" AcceptedAnswerId="4288" CreationDate="2021-02-05T12:50:53.523" Score="11" ViewCount="2681" Body="&lt;p&gt;I am right now using the PySCF for some quantum chemistry problems. I need to get the parameters, which are labeled &lt;span class=&quot;math-container&quot;&gt;$h_{ij}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_{ijkl}$&lt;/span&gt;. How can I get this done with PySCF?&lt;/p&gt;&#xA;" OwnerUserId="2043" LastEditorUserId="7" LastEditDate="2021-07-09T17:11:12.303" LastActivityDate="2022-05-07T08:16:59.923" Title="How are 1-electron and 2-electron integrals done in PySCF?" Tags="|integrals|pyscf|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4285" PostTypeId="2" ParentId="4283" CreationDate="2021-02-05T14:36:58.743" Score="7" Body="&lt;p&gt;The model you are describing corresponds to a Wannier-Mott exciton and the binding energy is approximated by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;E_{\mathrm{B}}=\frac{\mu}{\epsilon^2_{\infty}}R,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the reduced mass of the electron and hole, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{\infty}$&lt;/span&gt; is the high frequency dielectric constant, and &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is the Rydberg constant. You can in principle construct all necessary parameters from a VASP calculation.&lt;/p&gt;&#xA;&lt;p&gt;This model is appropriate for materials with a large dielectric response that leads to weak electron-hole interactions and large excitons spanning multiple primitive cells. If you have a system with poor dielectric screening (e.g. an organic semiconductor), then excitons are strongly bound and highly localized, and this model will not provide a good description.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-02-05T14:36:58.743" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4286" PostTypeId="2" ParentId="4258" CreationDate="2021-02-05T17:02:28.940" Score="5" Body="&lt;p&gt;Unfortunately, not able to comment yet, but &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/jp811388w&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2009&lt;/strong&gt;, &lt;em&gt;113&lt;/em&gt;, 6745.&lt;/a&gt; is a nice reference, especially if you are interested in metal complexes, which your example seems to deal with.&lt;/p&gt;&#xA;&lt;p&gt;Some key points:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You can profit from error cancelations by referencing against calculations for a system like Fc/Fc+.&lt;/li&gt;&#xA;&lt;li&gt;You usually find a systematic error for a particular DFT method. Hence, if you have known standard reduction potentials for similar systems, you could use them for a linear fit.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2044" LastActivityDate="2021-02-05T17:02:28.940" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4287" PostTypeId="1" AcceptedAnswerId="4289" CreationDate="2021-02-05T17:55:50.823" Score="11" ViewCount="340" Body="&lt;p&gt;I've recently made myself more familiar with Laughlin and Pines' &amp;quot;quantum protectorate&amp;quot; arguments (&lt;a href=&quot;https://www.pnas.org/content/pnas/97/1/28.full.pdf&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0002281&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;), which seems built on Anderson's famous &lt;em&gt;More is Different&lt;/em&gt; article (&lt;a href=&quot;https://science.sciencemag.org/content/177/4047/393&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;). This does seem in disagreement with Dirac's 1929 sentiments, (&lt;a href=&quot;https://royalsocietypublishing.org/doi/pdf/10.1098/rspa.1929.0094&quot; rel=&quot;noreferrer&quot;&gt;4&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The underlying physical laws necessary for the mathematical theory of&#xA;a large part of physics and the whole of chemistry are thus completely&#xA;known, and the difficulty is only that the exact application of these&#xA;laws leads to equations much too complicated to be soluble. It&#xA;therefore becomes desirable that approximate practical methods of&#xA;applying quantum mechanics should be developed, which can lead to an&#xA;explanation of the main features of complex atomic systems without too&#xA;much computation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(though I know not everyone agrees with this, e.g. &lt;a href=&quot;https://chemistry.stackexchange.com/questions/50681/is-it-true-that-all-of-the-physical-laws-and-mathematics-needed-to-describe-chem&quot;&gt;this chemistry SE thread&lt;/a&gt;) and perhaps these arguments are still considered speculative. However, there are a few mentions of the failures of &lt;em&gt;ab initio&lt;/em&gt; methods (which seems quite reductionist to me), and it seems implied that they cannot be enough to predict some effects in condensed matter, especially superconductivity.&lt;/p&gt;&#xA;&lt;p&gt;My question is, &lt;strong&gt;to what extent is this true, and how would one typically try to model matter that is in some &amp;quot;protectorate,&amp;quot; e.g. superconductivity?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In these cases, are &lt;em&gt;ab initio&lt;/em&gt; methods not suitable (and say, even with incredible computing power, still not suitable?)? Would (for example) renormalisation group methods be more reliable than &lt;em&gt;ab initio&lt;/em&gt; methods? If they fail, is this a failure of our reductionist model (&amp;quot;theory of everything&amp;quot;), or is it a failure of our approximations in solving the reductionist model? Is there reason to believe that we can't, for example, recover the Josephson effect (which relies on spontaneous symmetry breaking) by direct solution of the Schrödinger equation (with our technology, but also in principle, i.e. if we imagine a world where we can solve such a large system with FCI/QMC)? Similarly, on the more extreme &amp;quot;patently absurd&amp;quot; end, protein functionality and the human brain: these are obviously inaccessible just in terms of computing power, though I suppose asking questions about &lt;em&gt;ab initio&lt;/em&gt; neuroscience quickly turns into poppycock.&lt;/p&gt;&#xA;" OwnerUserId="1522" LastEditorUserId="1522" LastEditDate="2021-02-05T23:45:45.567" LastActivityDate="2021-02-05T23:45:45.567" Title="&quot;Quantum protectorates&quot; and the limits of grand unified theories" Tags="|ab-initio-calculations|superconductivity|soft-question|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4288" PostTypeId="2" ParentId="4284" CreationDate="2021-02-05T18:50:22.050" Score="14" Body="&lt;p&gt;While &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2181/5&quot;&gt;this earlier question on our site&lt;/a&gt; was asking why fewer 2e- integrals were printed by PySCF than expected, and your question is simply asking how to calculate the 1e- and 2e- integrals in the first place (so the two questions are not duplicated), that question gave an excellent example for how to print the 2e- integrals for the He atom in a 6-31g basis set:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto&#xA;mol = gto.M(atom='He 0 0 0', basis='6-31g')&#xA;eri = mol.intor('int2e', aosym='s8')&#xA;print(eri)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Similarly you can get the 1e- integrals by changing &lt;code&gt;int2e&lt;/code&gt; to &lt;code&gt;int1e&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-05T18:50:22.050" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4289" PostTypeId="2" ParentId="4287" CreationDate="2021-02-05T19:32:10.420" Score="10" Body="&lt;p&gt;It's a very good question, and we may get several answers here from people with various different perspectives, but here is mine:&lt;/p&gt;&#xA;&lt;p&gt;In &lt;em&gt;&lt;strong&gt;every&lt;/strong&gt;&lt;/em&gt; case so far where we are certain that computations have been done thoroughly enough, known quantum field theories have been able to reproduce experiments when gravity is not strong enough to play a role. For example, QED (quantum electrodynamics) is a quantum field theory, and from it we can &amp;quot;derive&amp;quot; both the Schrödinger equation and Dirac equation, as the first and second terms of an expansion of operators proportional to different powers of the fine structure constant. Another example of a quantum field theory is QFD (quantum flavordynamics) which is able to treat the electro-weak force, and hasn't yet failed to do so for any experiments which were simple enough to reproduce with present-day computing power and human desire. Likewise the same can be said of QCD (quantum chromodynamics, or quantum colordynamics) for the strong force.&lt;/p&gt;&#xA;&lt;p&gt;So you asked whether or not our known quantum field theories (such as QED, QFD, QCD) can successfully predict superconductivity and consciousness of the brain if we had access to enough computing power and motivation to do so. It's an interesting question, but one for philosophy, because it is not possible to test it using the scientific method, because we do not have enough computing power to run such an experiment (we do have the capability to do laboratory experiments that observe superconductivity, but we don't have enough computing power to properly conduct the experiment on the other front, which is to see if completely thorough &lt;em&gt;ab initio&lt;/em&gt; calculations will match the laboratory experiment).&lt;/p&gt;&#xA;&lt;p&gt;I do not see any reason why superconductivity should not be possible to predict with an &lt;em&gt;ab initio&lt;/em&gt; calculation if we had enough computing power, but &lt;em&gt;ab initio&lt;/em&gt; calculations are so far away from being able to treat systems with so many electrons &lt;em&gt;without making a lot of approximations&lt;/em&gt;, so we really do not know whether or not something comes up that we've missed in QED for example. From an Occam's razor perspective, I would be surprised if we were missing something in quantum theory which is needed in order to predict superconductivity, because if we were missing something then &lt;em&gt;why (does it seem like) it is only superconductivity that we can't predict?&lt;/em&gt; But that is a question for philosophy. There was a related question that was asked by one of the moderators in this community, and it is not surprising that it didn't get an answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1755/5&quot;&gt;What&amp;#39;s the largest system we can study based on &amp;quot;fundamental limits to computation&amp;quot;?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As for human consciousness, we have to first know what it is, before we can try to predict it using an &lt;em&gt;ab initio&lt;/em&gt; method. So in that case, &lt;strong&gt;yes we do need more than just the laws of quantum physics (and maybe also gravity), in order to predict human consciousness, because we &lt;em&gt;also&lt;/em&gt; have to know what it is that the calculation is looking for&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-05T19:39:30.833" LastActivityDate="2021-02-05T19:39:30.833" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4290" PostTypeId="1" CreationDate="2021-02-05T20:16:32.913" Score="4" ViewCount="580" Body="&lt;p&gt;I have been studying a magnetic material with SoC taken into consideration. The main aim was to obtain the band structure.&lt;/p&gt;&#xA;&lt;p&gt;when I use &lt;code&gt;spin_component = 1&lt;/code&gt; in the &lt;strong&gt;bands.x&lt;/strong&gt; input file, I get a bands.dat file containing the bands for the spinup configuration.&lt;/p&gt;&#xA;&lt;p&gt;But on using &lt;code&gt;spin_component = 2&lt;/code&gt;, it throws the following error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine punch_bands (1):&#xA;     incorrect spin_component&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I found this discussion on the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_BANDS.html#idm22&quot; rel=&quot;nofollow noreferrer&quot;&gt;pw-Forum&lt;/a&gt;, in which it was stated that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In the spin-orbit case starting with zero starting_magnetization on&#xA;all atoms imposes time reversal symmetry. The magnetization is never&#xA;calculated and kept zero (the internal variable domag is .FALSE.).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;So is there a way to obtain the spin-polarized bandstructure in Quantum ESPRESSO whilst taking into consideration Spin-Orbit Coupling?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2021-02-05T23:10:47.280" Title="How can I obtain seperate spin-up and spin-down bands while considering Spin Orbit Coupling in Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|magnetism|spin-orbit-coupling|spin-polarization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4291" PostTypeId="1" AcceptedAnswerId="4619" CreationDate="2021-02-05T20:37:17.817" Score="5" ViewCount="252" Body="&lt;p&gt;I have noticed that for certain Hessian calculations that I run with GAMESS(US), the IR intensities are not produced in the log file. Below I have an example input card (without the molecule $DATA group) of a Hessian calculation I ran that didn't produce the IR intensities only the vibrational frequencies (also given below).&lt;/p&gt;&#xA;&lt;p&gt;Why is this the case and how can I resolve it?&lt;/p&gt;&#xA;&lt;p&gt;Input Card&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$CONTRL SCFTYP=UHF MULT=1 NPRINT=0 COORD=UNIQUE &#xA;RUNTYP=HESSIAN ICUT=12 ITOL=25 DFTTYP=BLYP      &#xA;MAXIT=200 QMTTOL=1E-7 ICHARG=0 ISPHER=1 $END    &#xA;$SYSTEM MWORDS=800 MEMDDI=800 $END              &#xA;$STATPT OPTTOL=1E-6 NSTEP=200 $END              &#xA;$FORCE METHOD=FULLNUM NVIB=2 PROJCT=.TRUE. $END &#xA;$SCF DIRSCF=.TRUE. FDIFF=.FALSE. CONV=1d-7 $END &#xA;$DFT JANS=2 $END                                &#xA;$BASIS GBASIS=ACCQ $END                         &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Frequency Output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;FREQUENCIES IN CM**-1, IR INTENSITIES IN DEBYE**2/AMU-ANGSTROM**2,&#xA;REDUCED MASSES IN AMU.&#xA;&#xA;                       1           2           3           4           5&#xA;   FREQUENCY:         0.00        0.00        0.00        0.00        0.00  &#xA;    SYMMETRY:         B2          B2          B2          B2          B2  &#xA;REDUCED MASS:      1.45984     5.02837    27.97693     1.31228     1.81766&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note, that normally the output would also include the IR intensities for each frequency.&lt;/p&gt;&#xA;" OwnerUserId="65" LastEditorUserId="7" LastEditDate="2021-07-12T01:38:17.690" LastActivityDate="2021-07-12T01:38:17.690" Title="GAMESS(US) Hessian calculation sometimes does not produce the IR intensities" Tags="|spectroscopy|vibrations|gamess|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4292" PostTypeId="2" ParentId="692" CreationDate="2021-02-05T20:45:21.417" Score="2" Body="&lt;h2&gt;GAMESS&lt;/h2&gt;&#xA;&lt;p&gt;Most parts of &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GAMESS&lt;/a&gt; are parallelised with MPI (including SCF), and can run on multiple CPUs. The parallel SCF runs entirely on replicated memory, however other parallel algorithms such as MP2, CCSD etc. use distributed memory. GAMESS is free, and you can also access the source code. Some parts of the GAMESS are also parallelised with OpenMP like the recently implemented RI-CCSD module. GAMESS can run on multiple nodes.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-02-05T21:02:51.313" LastActivityDate="2021-02-05T21:02:51.313" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4293" PostTypeId="2" ParentId="4290" CreationDate="2021-02-05T23:10:47.280" Score="2" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are considering SOC, which means the noncolinear calculations are performed. I assume that the eigenstate of the Kohn-Sham equation is labeled by &lt;span class=&quot;math-container&quot;&gt;$|atom, k, orbital, spin \rangle$&lt;/span&gt;. To obtain a spin-polarized band structure, you should do a fat band analysis with the consideration of the different spin components:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle atom, k, orbital, spin|s_x \rangle$&lt;/span&gt; (plus=left;minusright)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle atom, k, orbital, spin|s_y \rangle$&lt;/span&gt; (plus=front;minus=back)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle atom, k, orbital, spin|s_z \rangle$&lt;/span&gt; (plus=up;minus=down)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You may take a look at my answer for this post: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1791/properties-that-can-be-deduced-from-band-structure-and-dos/2396#2396&quot;&gt;Properties that can be deduced from Band structure and DOS&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For your question, the key problem is to output band structure with projection to spin. The same function is realized with &lt;a href=&quot;https://www.vasp.at/wiki/wiki/index.php/LORBIT&quot; rel=&quot;nofollow noreferrer&quot;&gt;LORBIT=11&lt;/a&gt; in VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-05T23:10:47.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4294" PostTypeId="1" AcceptedAnswerId="4296" CreationDate="2021-02-06T00:20:42.887" Score="14" ViewCount="966" Body="&lt;p&gt;This question is related to (and was originally asked in) &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4287/quantum-protectorates-and-the-limits-of-grand-unified-theories&quot;&gt;another post about &amp;quot;quantum protectorates&amp;quot; I made here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Ab initio&lt;/em&gt; methods are nice because they directly solve a sort of &amp;quot;theory of everything&amp;quot; for many-body systems, and they are systematically improvable. However, having been part of a physics department I rarely ever saw them used at all before moving to chemistry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;At what point do we abandon &lt;em&gt;ab initio&lt;/em&gt; methods?&lt;/strong&gt; I have typically thought the main reason other methods are used is because of computational constraints. I have also heard that &lt;em&gt;ab initio&lt;/em&gt; methods tend to fail in strongly correlated systems (as does DFT), and just about everyone I know who works in this area relies on renormalisation methods. Thijssen's &lt;em&gt;Computational Physics&lt;/em&gt; textbook also briefly discusses &lt;em&gt;ab initio&lt;/em&gt; vs semi-empirical methods,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A distinction can be made between ab initio methods, which use no&#xA;experimental input, and semi-empirical methods, which do. The latter&#xA;should not be considered as mere fitting procedures: by fitting a few&#xA;numbers to a few experimental data, many new results may be predicted,&#xA;such as full band structures. Moreover, the power of ab initio methods&#xA;should not be exaggerated: there are always approximations inherent&#xA;to them, in particular the reliance on the Born–Oppenheimer&#xA;approximation separating the electronic and nuclear motion, and often&#xA;the local density approximation for exchange and correlation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So when do we know when and when not to use &lt;em&gt;ab initio&lt;/em&gt; methods? The list of potential reasons I have come up with are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;Ab initio&lt;/em&gt; methods tend to be much slower.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Ab initio&lt;/em&gt; methods are better for small systems (i.e. they don't scale nicely), although I have heard that very large systems have been solved with them, and there do exist periodic methods, so I do not know how true this is.&lt;/li&gt;&#xA;&lt;li&gt;There are extra approximations in any &lt;em&gt;ab initio&lt;/em&gt; calculation in order to make the many-body Schrödinger equation tractable. For many applications, these approximations (especially the Born-Oppenheimer approximation) are unacceptable.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Ab initio&lt;/em&gt; methods do not capture the physics of strongly correlated systems properly for some reason.&lt;/li&gt;&#xA;&lt;li&gt;Model Hamiltonians are simpler and tend to be &amp;quot;baked&amp;quot; for the problem at hand, and therefore results are easier to interpret, especially for a scientist who is used to working with it.&lt;/li&gt;&#xA;&lt;li&gt;Physicists are not so familiar with them (compared to chemists, say), so the current paradigm of condensed matter physics does not involve &lt;em&gt;ab initio&lt;/em&gt; methods.&lt;/li&gt;&#xA;&lt;li&gt;Maybe there is some deep reason about &amp;quot;quantum protectorates&amp;quot; and how the many-body Schrödinger equation is not sufficient to describe some systems, and a &amp;quot;higher&amp;quot; theory is needed (this seems quite philosophical and hard to prove, though).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1522" LastEditorUserId="5" LastEditDate="2021-02-06T04:30:32.460" LastActivityDate="2021-02-06T16:17:47.220" Title="When do we abandon ab initio methods?" Tags="|ab-initio-calculations|quantum-chemistry|condensed-matter|model-hamiltonians|electron-correlation|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4295" PostTypeId="2" ParentId="4267" CreationDate="2021-02-06T01:18:35.827" Score="11" Body="&lt;p&gt;I think the &lt;code&gt;--molden&lt;/code&gt; flag should give you a molden file with the orbitals.&lt;/p&gt;&#xA;" OwnerUserId="2044" LastActivityDate="2021-02-06T01:18:35.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4296" PostTypeId="2" ParentId="4294" CreationDate="2021-02-06T05:54:02.223" Score="19" Body="&lt;p&gt;There's three scenarios that come to my mind, for when &lt;em&gt;ab initio&lt;/em&gt; methods get abandoned:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The cost becomes prohibitive (e.g. too many electrons)&lt;/li&gt;&#xA;&lt;li&gt;The insight is lost&lt;/li&gt;&#xA;&lt;li&gt;It is simply not required for what we want to do&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Prohibitive cost:&lt;/strong&gt; If solving the Schrödinger equation (for example) is no longer possible, we may very well still wish we could solve the Schrödinger equation, but we are unfortunately forced to make simplifications. For example, you can switch to a Hückel model of the Hamiltonian, and the benefits and uses of  Hückel theory were discussed in this mini-publication that Etienne Palos wrote for his answer to this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/50/5&quot;&gt;Where is the extended H&amp;#252;ckel method (EHM) still used today?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Insight is lost:&lt;/strong&gt;  A major disadvantage of &lt;em&gt;ab initio&lt;/em&gt; methods, is akin to the disadvantage of solving a differential equation, or finding the eigenvalues of a matrix numerically rather than analytically. When you solve a differential equation or find matrix eigenvalues analytically, you can see explicitly the dependence of the answer on each parameter. For example if the lowest eigenvalue of a matrix is &lt;span class=&quot;math-container&quot;&gt;$\lambda = \frac{5D^2}{\sqrt{\pi}}$&lt;/span&gt; for some diffusion constant &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;, then not only can you now calculate the answer for various other values of &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; easily, you can also see right away that &lt;span class=&quot;math-container&quot;&gt;$\lambda = \mathcal{O}(D^2)$&lt;/span&gt; which can be a very powerful thing to know. To find the eigenvalue numerically you will need to substitute a number for &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; and then you'll just get a number such as &lt;span class=&quot;math-container&quot;&gt;$\lambda=5.22195$&lt;/span&gt;. To discover the &lt;span class=&quot;math-container&quot;&gt;$D^2$&lt;/span&gt; dependence, you will have to re-do the calculation for many other values of &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;. But there is an advantage to numerically finding the eigenvalue, and that is that you can do this for arbitrary diagonalizable matrices of size &lt;span class=&quot;math-container&quot;&gt;$1000\times 1000$&lt;/span&gt; (for example) extremely quickly (so perhaps re-consider your first statement, that &lt;em&gt;ab initio&lt;/em&gt; methods are &amp;quot;slow&amp;quot;) whereas it in general would be impossible to solve the problem analytically. The situation is very similar for model Hamiltonians vs &lt;em&gt;ab initio&lt;/em&gt; treatments: when you solve for the ground state energy of a 50-electron Schrödinger equation, you just get a number, but if you do this for an exactly solvable Ising or Hubbard Hamiltonian, you might get a &lt;em&gt;&lt;strong&gt;formula&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Not required:&lt;/strong&gt;  &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct501066k&quot; rel=&quot;noreferrer&quot;&gt;In this paper in the field of &amp;quot;quantum biology&amp;quot;&lt;/a&gt;, I modeled &lt;em&gt;quantum mechanically&lt;/em&gt; the FMO pigment-protein complex, which contains 24 fairly large molecules called chromophores, embedded within a protein which is dissolved in water. The system contains thousands of particles. Did I solve the Schrödinger equation for thousands of particles? No, because the purpose was to study the rate of energy transfer from the first chromophore to three specific &amp;quot;end&amp;quot; chromophores and it could easily be done in the following way: each of the 24 chromophores can either be in its ground state or electronic excited state, but there is exactly enough energy in the system for only one of the chromophores to be excited at any given point in time, so we can ignore ground states that have zero excitations and we can ignore the second, third, fourth, etc. excited states. We therefore have a single-excitation subspace of 24 possible states (one for each possible chromophore containing the single excitation). Each of these states has an energy relative to the lowest one: these are diagonals of my single-excitation model Hamiltonian. There's a tunelling amplitude between each pair of states: these are the off-diagonals of my single-excitation model Hamiltonian. The vibrations of the protein and water around the chromophores will certainly affect the dynamics of energy transfer, and these involve thousands of atoms, but we roughly know the &amp;quot;spectral distribution functions&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$J_m(\omega)$&lt;/span&gt; for each single-excitation state &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$J_m(\omega)$&lt;/span&gt; tells us how strongly state &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; interacts with vibrations of frequency &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;. We then have a &lt;span class=&quot;math-container&quot;&gt;$24 \times 24$&lt;/span&gt; matrix describing the electronic degrees of freedom and twenty-four &lt;span class=&quot;math-container&quot;&gt;$J(\omega)$&lt;/span&gt; functions describing the effect of nuclear vibrations on these, and we use the numerically exact Feynman-Vernon equation to calculate how the excitation evolves. If we tried to solve the entire problem &lt;em&gt;ab initio&lt;/em&gt; we could get much more detailed information about the system's wavefunction, but we really do not need those details in this case, and &lt;em&gt;&lt;strong&gt;the difference we would get for the overall result would unlikely provide any further valuable information to the study.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'd like now to try to address some of the comments in your question:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I would try not to get to caught up about &amp;quot;differences&amp;quot; between &amp;quot;physicists&amp;quot; and &amp;quot;chemists&amp;quot; here. It is not true that &amp;quot;physicists&amp;quot; do not do &lt;em&gt;ab initio&lt;/em&gt; calculations, for example &lt;a href=&quot;https://scholar.google.com/citations?user=o4hcEbMAAAAJ&amp;amp;hl=th&quot; rel=&quot;noreferrer&quot;&gt;Krzysztof Pachucki does some of the most high-precision &lt;em&gt;ab initio&lt;/em&gt; atomic calculations in the world&lt;/a&gt;, and also some molecular &lt;em&gt;ab initio&lt;/em&gt; calculations, but more people would call him a &amp;quot;physicist&amp;quot; than a &amp;quot;chemist&amp;quot; (his degrees are also all in physics and he's in a physics department). Likewise &lt;a href=&quot;http://athena.uwindsor.ca/units/physics/PhyFac.nsf/4d0dd4c97c84860a05256869005b0361/da9ea7083bd12c13052568790066c5ea?OpenDocument&quot; rel=&quot;noreferrer&quot;&gt;Gordon W. F. Drake&lt;/a&gt;, who was the &amp;quot;Editor in Chief&amp;quot; of Physical Review A for decades, also got all his degrees in physics, worked in physics departments for his entire career, and was elected an APS Fellow but probably was never even considered for an ACS Fellow designation, does &lt;em&gt;ab initio&lt;/em&gt; calculations on atoms, as do a fair number of other atomic physicists.&lt;/li&gt;&#xA;&lt;li&gt;On another front, &lt;em&gt;ab initio&lt;/em&gt; methods are getting popular as a more rigorous way to study high-Tc superconductive materials in a first-principles way, see for example:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/1803.07026&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;New superexchange paths due to breathing-enhanced hopping in corner-sharing cuprates&amp;quot;&lt;/a&gt; and,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/nature11770&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Towards an exact description of electronic wavefunctions in real solids&amp;quot;&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;There are extra approximations in any ab initio calculation in order to make the many-body Schrödinger equation tractable. For many applications, these approximations (especially the Born-Oppenheimer approximation) are unacceptable.&amp;quot; That's not really true. We do non-Born-Oppenheimer &lt;em&gt;ab initio&lt;/em&gt; calculations frequently: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3889/5&quot;&gt;Are there examples of ab initio predictions on small molecules without the &amp;quot;major approximations&amp;quot;?&lt;/a&gt;. There's excellent review papers on the subject by Ludwik Adamowicz, for example:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2003/CP/B211193D#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Non-Born–Oppenheimer calculations of atoms and molecules&amp;quot;&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/cr200419d&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Born–Oppenheimer and Non-Born–Oppenheimer, Atomic and Molecular Calculations with Explicitly Correlated Gaussians&amp;quot;&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;Ab initio methods do not capture the physics of strongly correlated systems properly for some reason.&amp;quot; Who said so? The &lt;em&gt;ab initio&lt;/em&gt; method called CASSCF is used to (accurately) treat strong correlation in thousands of studies, and it is such a popular method that it's implemented in several open source software packages: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/414/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;Maybe there is some deep reason about &amp;quot;quantum protectorates&amp;quot; and how the many-body Schrödinger equation is not sufficient to describe some systems, and a &amp;quot;higher&amp;quot; theory is needed (this seems quite philosophical and hard to prove, though).&amp;quot; If that's the case, what makes you think your model Hamiltonian such as an Ising or Hubbard Hamiltonian, will work? Those model Hamiltonians are just approximations of the Hamiltonian that Schrödinger told us. &lt;em&gt;ab initio&lt;/em&gt; methods try to solve the &amp;quot;true&amp;quot; the Schrödinger equation, whereas model Hamiltonians approximate it a bit first, then solve.&lt;/li&gt;&#xA;&lt;li&gt;Just because it's in a book doesn't mean it's true. That quote alone is enough to tell us that the book's author is biased against &lt;em&gt;ab initio&lt;/em&gt; methods, and doesn't even quite know what they are. It is not correct that &amp;quot;there are always approximations inherent to them, in particular the reliance on the Born–Oppenheimer approximation&amp;quot; as I already showed above two review papers on non-Born-Oppenheimer &lt;em&gt;ab initio&lt;/em&gt; calculations. The author then goes on to say &amp;quot;and often the local density approximation for exchange and correlation&amp;quot; as if the GGA and meta-GGA and other DFT functionals that are not LDA are not approximations? Also, density functionals are almost always fitted to experimental data so a very large number of people don't consider density functional calculations to be &lt;em&gt;ab initio&lt;/em&gt;, see: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/518/5&quot;&gt;Can DFT be considered an ab initio method?&lt;/a&gt; and &lt;a href=&quot;https://chemistry.stackexchange.com/q/33764/27342&quot;&gt;Is density functional theory an ab initio method?&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-06T16:17:47.220" LastActivityDate="2021-02-06T16:17:47.220" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4297" PostTypeId="1" CreationDate="2021-02-06T06:47:11.717" Score="13" ViewCount="143" Body="&lt;p&gt;It is well-established that within the DFT+&lt;em&gt;U&lt;/em&gt; framework, one can achieve several self-consistent solutions with greatly varying energies for the same exact magnetic ordering. In 2010, &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.195128&quot; rel=&quot;noreferrer&quot;&gt;Meredig et al.&lt;/a&gt; showed that a relatively simple &amp;quot;&lt;em&gt;U&lt;/em&gt;-ramping&amp;quot; method could be employed to more easily identify the true ground state solution for troublesome DFT+&lt;em&gt;U&lt;/em&gt; cases.&lt;/p&gt;&#xA;&lt;p&gt;Since it has been over a decade since the aforementioned paper, is this still considered to be the optimal approach when carrying out DFT+&lt;em&gt;U&lt;/em&gt; calculations? Are there any other methods commonly used to identify the ground state solution when carrying out DFT+&lt;em&gt;U&lt;/em&gt; calculations?&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2022-01-29T22:35:17.627" LastActivityDate="2022-01-29T22:35:17.627" Title="Handling multiple self-consistent solutions with DFT+U" Tags="|density-functional-theory|magnetism|self-consistent-field|dft-u|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4298" PostTypeId="1" AcceptedAnswerId="4307" CreationDate="2021-02-06T18:37:25.137" Score="10" ViewCount="929" Body="&lt;p&gt;I am a bit confused about the notions of exchange in the Hartree-Fock and Kohn-Sham Density Functional Theory schemes.&lt;/p&gt;&#xA;&lt;p&gt;In Hartree-Fock, one just writes down the many-electron wavefunction as a hartree-product. This does not capture any correlation effects since each electron is treated to be independent of each other.&lt;/p&gt;&#xA;&lt;p&gt;In Kohn-Sham DFT, what is generally mentioned in many texts (for example, this one &lt;a href=&quot;https://www.springer.com/gp/book/9783642140891&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;), is if you set correlation to zero, you recover the ground state energy and density corresponding to Hartree-Fock.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;My first question is, how different is 'exchange' in the HF scheme and the &lt;span class=&quot;math-container&quot;&gt;$E_x$&lt;/span&gt; term (assume you separate &lt;span class=&quot;math-container&quot;&gt;$E_{xc}$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$E_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_c$&lt;/span&gt;) in the KS-DFT scheme?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The term 'exact exchange' is often used in the context of Hybrid Functional calculations. Is this the same as the condition I initially mentioned (i.e. Set correlation=0 in the KS-DFT scheme).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="770" LastActivityDate="2021-02-07T17:29:56.057" Title="'Exchange' in Hartree-Fock and Kohn-Sham DFT" Tags="|kohn-sham|hartree-fock|exchange-correlation|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4299" PostTypeId="2" ParentId="4263" CreationDate="2021-02-06T18:50:30.800" Score="5" Body="&lt;p&gt;In order to perform a molecular dynamics simulation, you need to equilibrate the system before you can get good statistics.&lt;/p&gt;&#xA;&lt;p&gt;In principle, you can use any starting point, since the simulation should be ergodic; however, this will mean that the equilibration time will be very long.&lt;/p&gt;&#xA;&lt;p&gt;Placing the molecules on a lattice is a simple way to form the starting point, but it may also be very far from equilibrium: if you want to simulate a mixed liquid, but your molecules don't have uniform shape (e.g. size in one dimension is much bigger in the two other ones), your initial lattice will be quite far from the one you're targeting at equilibrium, which will have an uniform shape.&lt;/p&gt;&#xA;&lt;p&gt;The idea in PACKMOL is to obtain a randomized starting structure. This will allow for a much faster equilibration, since you can e.g. form the initial structure in a simulation cell that already has a density that is close to the equilibrated one, at the wanted temperature and pressure.&lt;/p&gt;&#xA;&lt;p&gt;Now, let's assume you have a starting configuration. The next thing to do is to equilibrate it. Like you said, there are many ways to accomplish this. Generally, one runs the initial simulation at high temperature, since this will allow the system to escape any local minima. If the density is already close to correct, the initial equilibration can be run at constant volume. Otherwise, as far as I understand, it is common practice to run the initial equilibration at a large pressure. The idea is again to allow the system to &amp;quot;mix&amp;quot; faster, so that the equilibration takes less CPU time.&lt;/p&gt;&#xA;&lt;p&gt;What is the right temperature (and pressure)? This probably depends a lot on what you are trying to do. Obviously, there are a few practical issues to keep in mind. You don't want to set the temperature or pressure so high that you need to decrease your time step, since this would beat the purpose of speeding up the equilibration. You also don't want your system to dissociate; however, since molecular MD potentials often don't allow dissociation due to harmonic potentials, this may not be a big issue. The specifics will depend on your system, and what you are trying to accomplish. For instance, if you are simulating a protein in a given a given folding pattern, increasing the temperature and pressure for the protein may be a bad idea. The pressure, in turn, should be high enough so that the system does not evaporate, i.e. that the density does not decrease a lot.&lt;/p&gt;&#xA;&lt;p&gt;Once you have run the initial equilibration of the system at high temperature and pressure, you can start the production run. However, since the temperature and pressure/volume will change, you should discard the initial part of the simulation from the analysis. Key quantities to look at are the different parts of the energy, density, etc; you should only look at the part of the simulation where these are oscillating around the equilibrated value.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-06T18:50:30.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4300" PostTypeId="2" ParentId="1176" CreationDate="2021-02-06T19:07:19.847" Score="9" Body="&lt;p&gt;Apart from methods (1) and (2) mentioned in the question, the third method I found to be pretty viable under certain conditions. The procedure involves mathematical interpolation of the bands, so I have to caution the reader that this is not completely rigorous like Wannier interpolation, which retains the nature of the wave-functions generated from the SCF calculation. That being said, I'm pleasantly surprised by how well the &lt;a href=&quot;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap2/&quot; rel=&quot;noreferrer&quot;&gt;BoltzTrap2 code&lt;/a&gt; handles interpolation, along with degeneracies.&lt;/p&gt;&#xA;&lt;p&gt;The procedure is as follows:&lt;/p&gt;&#xA;&lt;p&gt;i) Perform a self-consistent calculation with HSE turned on. The 'q' mesh (or Fock grid) that you choose for the calculation will affect the final band-structure. Typically, for big systems, one would not be able to choose a Fock grid that is commensurate with your K-grid. For instance, I worked on a 2D semiconductor with around 100 electrons in the system. My K-mesh was 12x9x1. In this case, I experimented with 'q' meshes of 1x1x1, 4x3x1 and 12x9x1. As one might imagine, the ideal choice would be 12x9x1 for the 'q' mesh since its commensurate with the K-grid. But this is very computationally heavy. My band-structure calculations, surprisingly, were somewhat converged at the 4x3x1 'q' mesh itself the band-gap difference with the commensurate mesh was around 0.05 eV. The bottom-line here is, the density of the 'q' mesh will affect the precision of the band-structure calculation since the basis is mathematical (for the Wannier method, this is not the case).&lt;/p&gt;&#xA;&lt;p&gt;ii) Install &lt;em&gt;BoltzTrap2&lt;/em&gt;. Rename the SCF input and output files as &lt;em&gt;prefix.nscf.in&lt;/em&gt; and &lt;em&gt;prefix.nscf.out&lt;/em&gt; . This needs to be done because the code takes in file names which are specified in the above format.&lt;/p&gt;&#xA;&lt;p&gt;iii) Run the '&lt;em&gt;qe2boltz.py&lt;/em&gt;' file to convert the QE input to a format that's readable by BoltzTrap2:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;python qe2boltz.py prefix pw fermi f&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Replace 'f' here with the value of the Fermi level printed in your SCF output.&lt;/p&gt;&#xA;&lt;p&gt;iv) Run the bands interpolation using&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; btp2 -vv interpolate -m 'n'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where 'n' decides how fine your interpolation needs to be for the band-structure. Typically, values of 1000-2000 should be good enough.&lt;/p&gt;&#xA;&lt;p&gt;v) Plot the bands using the plotbands command.&lt;/p&gt;&#xA;&lt;p&gt;For any logistical issues, the &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/home&quot; rel=&quot;noreferrer&quot;&gt;BoltzTrap code documentation&lt;/a&gt; and also this &lt;a href=&quot;https://blog.levilentz.com/boltztrap-tutorial-for-quantum-espresso/&quot; rel=&quot;noreferrer&quot;&gt;tutorial&lt;/a&gt; might be helpful.&lt;/p&gt;&#xA;" OwnerUserId="770" LastActivityDate="2021-02-06T19:07:19.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4301" PostTypeId="2" ParentId="4234" CreationDate="2021-02-06T20:15:25.560" Score="3" Body="&lt;p&gt;As stated in my comment, the easiest thing to look at is the contrast of the image.  It seems you were able to change the background to prevent the code from detecting the shape incorrectly.&lt;/p&gt;&#xA;&lt;p&gt;You can post process these images in programs such as paint.net, gimp, photoshop, etc.  Changing the image from grayscale to black and white is probably the best thing to do.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-02-06T20:15:25.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4302" PostTypeId="1" AcceptedAnswerId="4304" CreationDate="2021-02-06T21:56:16.950" Score="9" ViewCount="306" Body="&lt;p&gt;When an SCF calculation is done in a QM program, the MO coefficients of the solution are printed into the output. Now, graphical softwares can plot 3D molecular orbitals from these coefficients, presumably by combining the basis set and the coefficients.&lt;/p&gt;&#xA;&lt;p&gt;This is the first part of the output of an RHF/MIDI calculation on an &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt; molecule with GAMESS(US):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;          ------------&#xA;          EIGENVECTORS&#xA;          ------------&#xA;&#xA;                      1          2          3          4          5&#xA;                  -20.4191    -1.3388    -0.6850    -0.5393    -0.4837&#xA;                     A          A          A          A          A   &#xA;    1  O  1  S    0.989154  -0.220275  -0.001184   0.079432  -0.000000&#xA;    2  O  1  S    0.065271   0.487564   0.002152  -0.177885  -0.000000&#xA;    3  O  1  S   -0.034882   0.438551   0.006441  -0.333617  -0.000000&#xA;    4  O  1  X    0.001409   0.036986   0.314950   0.210975   0.164841&#xA;    5  O  1  Y   -0.000292  -0.007466  -0.121285  -0.044237   0.484575&#xA;    6  O  1  Z    0.002563   0.069802  -0.193015   0.375649  -0.035515&#xA;    7  O  1  X   -0.002020   0.037929   0.308448   0.249550   0.207751&#xA;    8  O  1  Y    0.000419  -0.007817  -0.118676  -0.052406   0.610715&#xA;    9  O  1  Z   -0.003659   0.069385  -0.187599   0.443221  -0.044760&#xA;   10  H  2  S    0.000324   0.134487   0.264755   0.153642  -0.000000&#xA;   11  H  2  S    0.006519   0.005342   0.148311   0.110818  -0.000000&#xA;   12  H  3  S    0.000260   0.138002  -0.267972   0.150940  -0.000000&#xA;   13  H  3  S    0.006664   0.004777  -0.147661   0.106685  -0.000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The basis set is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; O         &#xA;&#xA;      1   S       1           281.8665800    0.069059895330&#xA;      1   S       2            42.4160000    0.393159473412&#xA;      1   S       3             9.0956200    0.665669054983&#xA;&#xA;      2   S       4            11.4660300   -0.145056191626&#xA;      2   S       5             0.8878600    1.044738808830&#xA;&#xA;      3   S       6             0.2788000    1.000000000000&#xA;&#xA;      4   P       7             8.0472400    0.226466081004&#xA;      4   P       8             1.6684200    0.868524024343&#xA;&#xA;      5   P       9             0.3725100    1.000000000000&#xA;&#xA; H         &#xA;&#xA;      6   S      10             4.5018000    0.156285427224&#xA;      6   S      11             0.6814440    0.904690578596&#xA;&#xA;      7   S      12             0.1513980    1.000000000000&#xA;&#xA; H         &#xA;&#xA;      8   S      13             4.5018000    0.156285427224&#xA;      8   S      14             0.6814440    0.904690578596&#xA;&#xA;      9   S      15             0.1513980    1.000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;At this point, I don't know how to combine the coefficients with the primitives in the basis set. Clearly the symbols on the left side of the MO coefficients indicate S, p&lt;sub&gt;x&lt;/sub&gt;, p&lt;sub&gt;y&lt;/sub&gt;, p&lt;sub&gt;z&lt;/sub&gt;... etc orbitals. So, according to the output, Oxygen should have 3 S, then 3 P and then 3 P orbitals. But the basis set has 6 S and 3 P functions. So I don't know which basis primitives correspond to which AO name (i.e. s, p&lt;sub&gt;x&lt;/sub&gt; etc.).&lt;/p&gt;&#xA;&lt;p&gt;Could someone help me understand how the final MOs are constructued from the coefficients and the basis set?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-02-07T07:37:24.820" LastActivityDate="2021-02-07T07:37:24.820" Title="How are molecular orbitals constructed from the coefficients and basis set?" Tags="|software|basis-sets|gamess|orbitals|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4303" PostTypeId="1" CreationDate="2021-02-07T05:29:02.317" Score="10" ViewCount="396" Body="&lt;p&gt;I did a TDDFT calculation using B3LYP functional and ground state optimized structure in NWCHEM. The TDDFT portion of the output is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;----------------------------------------------------------------------------&#xA;  Root   1 singlet a              0.124505160 a.u.                3.3880 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -0.67477   Y -0.16090   Z -0.00926&#xA;     Transition Moments   XX -3.72551  XY  0.33692  XZ  0.29211&#xA;     Transition Moments   YY  1.03517  YZ -0.47531  ZZ  0.23052&#xA;     Dipole Oscillator Strength                    0.0399490230&#xA;     Electric Quadrupole                           0.0000000711&#xA;     Magnetic Dipole                               0.0000000066&#xA;     Total Oscillator Strength                     0.0399491007&#xA; &#xA;     Occ.  118  a   ---  Virt.  119  a   -0.98715 X&#xA;     Occ.  118  a   ---  Virt.  120  a    0.09973 X&#xA;     Occ.  118  a   ---  Virt.  121  a    0.09163 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   2 singlet a              0.137354088 a.u.                3.7376 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -0.76724   Y -0.18948   Z -0.00938&#xA;     Transition Moments   XX -0.14340  XY  0.42578  XZ  0.40121&#xA;     Transition Moments   YY -3.78588  YZ -0.70760  ZZ  0.22932&#xA;     Dipole Oscillator Strength                    0.0571987020&#xA;     Electric Quadrupole                           0.0000000795&#xA;     Magnetic Dipole                               0.0000001012&#xA;     Total Oscillator Strength                     0.0571988827&#xA; &#xA;     Occ.  117  a   ---  Virt.  119  a    0.06721 X&#xA;     Occ.  118  a   ---  Virt.  119  a   -0.08427 X&#xA;     Occ.  118  a   ---  Virt.  120  a   -0.97488 X&#xA;     Occ.  118  a   ---  Virt.  121  a    0.16187 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   3 singlet a              0.146507598 a.u.                3.9867 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -1.29377   Y -0.16851   Z -0.08944&#xA;     Transition Moments   XX -3.80151  XY -0.41951  XZ  0.03490&#xA;     Transition Moments   YY -2.01247  YZ -0.69574  ZZ  0.28749&#xA;     Dipole Oscillator Strength                    0.1670425890&#xA;     Electric Quadrupole                           0.0000000814&#xA;     Magnetic Dipole                               0.0000000321&#xA;     Total Oscillator Strength                     0.1670427025&#xA; &#xA;     Occ.  117  a   ---  Virt.  119  a    0.46050 X&#xA;     Occ.  118  a   ---  Virt.  119  a   -0.10314 X&#xA;     Occ.  118  a   ---  Virt.  120  a   -0.09062 X&#xA;     Occ.  118  a   ---  Virt.  121  a   -0.85863 X&#xA;     Occ.  118  a   ---  Virt.  122  a   -0.06947 X&#xA;     Occ.  118  a   ---  Virt.  124  a   -0.08528 X&#xA;     Occ.  118  a   ---  Virt.  126  a   -0.06728 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   4 singlet a              0.148144715 a.u.                4.0312 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X  0.71163   Y  0.25036   Z -0.00906&#xA;     Transition Moments   XX -0.55692  XY -1.07219  XZ -0.77683&#xA;     Transition Moments   YY  3.20588  YZ  0.77510  ZZ -0.25256&#xA;     Dipole Oscillator Strength                    0.0562132776&#xA;     Electric Quadrupole                           0.0000001164&#xA;     Magnetic Dipole                               0.0000002325&#xA;     Total Oscillator Strength                     0.0562136265&#xA; &#xA;     Occ.  117  a   ---  Virt.  119  a    0.87602 X&#xA;     Occ.  118  a   ---  Virt.  120  a    0.12925 X&#xA;     Occ.  118  a   ---  Virt.  121  a    0.44044 X&#xA;     Occ.  118  a   ---  Virt.  122  a    0.08258 X&#xA;     Occ.  118  a   ---  Virt.  124  a    0.07882 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   5 singlet a              0.154029225 a.u.                4.1914 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X  1.06235   Y -1.10313   Z -0.02692&#xA;     Transition Moments   XX 12.18774  XY  1.28925  XZ  0.69277&#xA;     Transition Moments   YY-12.48775  YZ  0.01961  ZZ -0.04038&#xA;     Dipole Oscillator Strength                    0.2409235301&#xA;     Electric Quadrupole                           0.0000030040&#xA;     Magnetic Dipole                               0.0000000646&#xA;     Total Oscillator Strength                     0.2409265987&#xA; &#xA;     Occ.  116  a   ---  Virt.  119  a    0.08704 X&#xA;     Occ.  116  a   ---  Virt.  121  a    0.05730 X&#xA;     Occ.  116  a   ---  Virt.  126  a   -0.06016 X&#xA;     Occ.  117  a   ---  Virt.  119  a    0.05311 X&#xA;     Occ.  117  a   ---  Virt.  121  a   -0.11048 X&#xA;     Occ.  118  a   ---  Virt.  121  a    0.09638 X&#xA;     Occ.  118  a   ---  Virt.  122  a   -0.96960 X&#xA;     Occ.  118  a   ---  Virt.  126  a    0.05824 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   6 singlet a              0.160861901 a.u.                4.3773 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X  0.03641   Y -0.03873   Z  0.00124&#xA;     Transition Moments   XX  4.34168  XY  0.32728  XZ  0.54758&#xA;     Transition Moments   YY -3.07040  YZ -0.31294  ZZ  0.02520&#xA;     Dipole Oscillator Strength                    0.0003032394&#xA;     Electric Quadrupole                           0.0000003184&#xA;     Magnetic Dipole                               0.0000001208&#xA;     Total Oscillator Strength                     0.0003036786&#xA; &#xA;     Occ.  117  a   ---  Virt.  120  a   -0.96655 X&#xA;     Occ.  117  a   ---  Virt.  122  a    0.07250 X&#xA;     Occ.  118  a   ---  Virt.  120  a    0.05042 X&#xA;     Occ.  118  a   ---  Virt.  123  a    0.17409 X&#xA;     Occ.  118  a   ---  Virt.  124  a   -0.10164 X&#xA;     Occ.  118  a   ---  Virt.  126  a    0.05475 X&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For my molecule experimental absorbance is at 321 nm or 3.8624 eV.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is that from my output which root should I compare with the experimental value?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do I need to consider oscillator strength or I should take the root 1 value?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="2052" LastEditorUserId="5" LastEditDate="2021-02-08T23:00:15.220" LastActivityDate="2021-02-10T10:08:53.540" Title="Understanding absorption spectra using TDDFT calculation in NWCHEM" Tags="|td-dft|nwchem|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4304" PostTypeId="2" ParentId="4302" CreationDate="2021-02-07T06:12:39.023" Score="8" Body="&lt;p&gt;Things are more clear to me when I look at the basis set in CFOUR format, because of the information at the top which tells me how many primitives and how many &lt;a href=&quot;https://en.wikipedia.org/wiki/Gaussian_orbital#Mathematical_form&quot; rel=&quot;noreferrer&quot;&gt;contractions&lt;/a&gt; there are for each type of orbital:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O:MIDI&#xA;Huzinaga MIDI&#xA;&#xA;2&#xA;0 1&#xA;3 2&#xA;6 3&#xA;&#xA;281.86658 42.416000 9.0956200 11.46603 0.887860 0.278800 &#xA;&#xA;0.069060  0.000000 0.00000000 &#xA;0.393159  0.000000 0.00000000 &#xA;0.665669  0.000000 0.00000000 &#xA;0.000000 -0.080820 0.00000000 &#xA;0.000000  0.582090 0.00000000 &#xA;0.000000  0.000000 1.00000000 &#xA;&#xA;8.047240 1.668420 0.372510 &#xA;&#xA;0.124271 0.00000000 &#xA;0.476594 0.00000000 &#xA;0.000000 1.00000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm going to use the &lt;code&gt;%&lt;/code&gt; symbol to add comments on the numbers at the top, to explain what they mean (but adding comments like this won't work if you actually did this to your &lt;code&gt;GENBAS&lt;/code&gt; file in CFOUR):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2   % # of types of orbitals = 2 (S and P).&#xA;0 1 % 0 = S, 1 = P, 2 = D, 3 = F, etc.&#xA;3 2 % 3 contractions for S, 2 contractions for Px, 2 for Py, 2 for Pz&#xA;6 3 % 6 primitives for S,   3 primitives for Px,   3 for Py, 3 for Pz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This explains why the basis set in GAMESS(US) format is showing 6 primitives for S and 3 primitives for P, but in your final eigenvectors, we now consider the contractions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;3 for S&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2 for Px&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2 for Py&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2 for Pz&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This is exactly what your output shows!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-07T06:32:14.273" LastActivityDate="2021-02-07T06:32:14.273" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4306" PostTypeId="1" CreationDate="2021-02-07T17:16:26.707" Score="10" ViewCount="526" Body="&lt;p&gt;I was wondering if the underlying dynamics of a full atomistic trajectory of a peptide molecule are Markovian.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note added after the first two answers:&lt;/strong&gt;&#xA;I assumed that they were Markovian, as they are simulation of a physical system, but the underlying dynamics and the interactions of atoms change as the molecule's configuration falls into different conformations as time progresses. This makes me think that it may be non-Markovian.&lt;/p&gt;&#xA;&lt;p&gt;PS: Note that the questions the trajectories in the 3D space, not their projection on the configuration space.&lt;/p&gt;&#xA;" OwnerUserId="1241" LastEditorUserId="5" LastEditDate="2021-03-09T23:11:21.567" LastActivityDate="2021-03-09T23:11:21.567" Title="Is the dynamics of a peptide molecule Markovian?" Tags="|molecular-dynamics|markovianity|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4307" PostTypeId="2" ParentId="4298" CreationDate="2021-02-07T17:29:56.057" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;In Hartree-Fock, one just writes down the many-electron wavefunction as a hartree-product. This does not capture any correlation effects since each electron is treated to be independent of each other.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;No, the Hartree-Fock many electron wave function is a single Slater determinant, which is completely antisymmetric to the exchange of two electrons and thereby satisfies the Pauli principle.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In Kohn-Sham DFT, what is generally mentioned in many texts (for example, this one [1]), is if you set correlation to zero, you recover the ground state energy and density corresponding to Hartree-Fock.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;False. The concept of &amp;quot;exchange&amp;quot; is somewhat ill-defined in DFT, since the definition is inherently based on the Hartree-Fock wave function. Running an exchange-only Kohn-Sham calculation can give you a variety of results, depending on which density functional approximation you use for the exchange; remember, there is no correct choice for this!&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;My first question is, how different is 'exchange' in the HF scheme and the Ex term (assume you separate Exc into Ex and Ec) in the KS-DFT scheme?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This depends on the functional. If you use LDA exchange, you will get different results. Same with GGA and meta-GGA functionals. If and only if you pick the exchange part as Hartree-Fock exchange (which few functionals do as full Hartree-Fock is often too much), will you get behavior that matches Hartree-Fock in the lack of correlation.&lt;/p&gt;&#xA;&lt;p&gt;Note: This is only in the case you are running a generalized Kohn-Sham calculation, where the exact exchange is evaluated the same way as in Hartree-Fock.&lt;/p&gt;&#xA;&lt;p&gt;However, you could also run the calculation with an optimized effective potential (OEP), which is a local, scalar potential &lt;span class=&quot;math-container&quot;&gt;$V({\bf r})$&lt;/span&gt; experienced by all electrons at variance to Hartree-Fock in which the occupied orbitals experience different potentials; again, you would see differences to Hartree-Fock.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The term 'exact exchange' is often used in the context of Hybrid Functional calculations. Is this the same as the condition I initially mentioned (i.e. Set correlation=0 in the KS-DFT scheme).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is a term to watch out for, since it may mean either the generalized Kohn-Sham scheme in which the potential is orbital dependent, or the OEP scheme in which all orbitals experience the same potential.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-07T17:29:56.057" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4308" PostTypeId="1" CreationDate="2021-02-07T18:42:08.140" Score="8" ViewCount="138" Body="&lt;p&gt;I am trying to do a simple ground state energy calculation of methane molecule using the Octopus (TDDFT) code. The example is already available in the octopus manual.                                           &lt;a href=&quot;https://octopus-code.org/wiki/Tutorial:Total_energy_convergence&quot; rel=&quot;noreferrer&quot;&gt;Here is the link&lt;/a&gt;.                       As per the manual, the total converged energy for CH4 molecule is -219.01537542 eV. When I am repeating the calculation with the same input file, the output is  -138.66600447 eV. The different versions of the code may be one of reasons (I am using octopus-10.0), but the difference between the energies is very high. I am attaching the log file and the output file for your reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**LOG FILE**&#xA;************************** Calculation Mode **************************&#xA;Input: [CalculationMode = gs]&#xA;**********************************************************************&#xA;&#xA;Input: [PseudopotentialSet = standard]&#xA;Reading Coordinates from Coordinates block&#xA;&#xA;****************************** Species *******************************&#xA;  Species 'C'&#xA;    type             : pseudopotential&#xA;    file             : '/usr/local/share/octopus/pseudopotentials/PSF/C.psf'&#xA;    file format      : PSF&#xA;    valence charge   : 4.0&#xA;    atomic number    :   6&#xA;    form on file     : semilocal&#xA;    orbital origin   : calculated&#xA;    lmax             : 1&#xA;    llocal           : 0&#xA;    projectors per l : 1&#xA;    total projectors : 1&#xA;    application form : kleinman-bylander&#xA;    orbitals         : 16&#xA;    bound orbitals   :  4&#xA;&#xA;  Species 'H'&#xA;    type             : pseudopotential&#xA;    file             : '/usr/local/share/octopus/pseudopotentials/PSF/H.psf'&#xA;    file format      : PSF&#xA;    valence charge   : 1.0&#xA;    atomic number    :   1&#xA;    form on file     : semilocal&#xA;    orbital origin   : calculated&#xA;    lmax             : 0&#xA;    llocal           : 0&#xA;    projectors per l : 1&#xA;    total projectors : 0&#xA;    application form : local&#xA;    orbitals         : 16&#xA;    bound orbitals   :  1&#xA;&#xA;***************************** Symmetries *****************************&#xA;Symmetry elements : 4*(C3) 3*(C2) 3*(S4) 6*(sigma)&#xA;Symmetry group    : Td&#xA;**********************************************************************&#xA;&#xA;Input: [SpinComponents = unpolarized]&#xA;Input: [SmearingFunction = semiconducting]&#xA;Input: [SymmetrizeDensity = no]&#xA;&#xA;******************************* States *******************************&#xA;Total electronic charge  =        8.000&#xA;Number of states         =        4&#xA;States block-size        =        4&#xA;**********************************************************************&#xA;&#xA;Input: [CurvMethod = curv_uniform]&#xA;Input: [DerivativesStencil = stencil_star]&#xA;&#xA;************************** Parallelization ***************************&#xA;Info: Octopus will run in *serial*&#xA;**********************************************************************&#xA;&#xA;Info: Generating weights for finite-difference discretization of x-gradient&#xA;Info: Generating weights for finite-difference discretization of y-gradient&#xA;Info: Generating weights for finite-difference discretization of z-gradient&#xA;Info: Generating weights for finite-difference discretization of Laplacian&#xA;&#xA;******************************** Grid ********************************&#xA;Simulation Box:&#xA;  Type = minimum&#xA;  Radius  [A] =   3.500&#xA;  Octopus will run in 3 dimension(s).&#xA;  Octopus will treat the system as periodic in 0 dimension(s).&#xA;Main mesh:&#xA;  Spacing [A] = ( 0.220, 0.220, 0.220)    volume/point [A^3] =      0.01065&#xA;  # inner mesh =      31525&#xA;  # total mesh =      51605&#xA;  Grid Cutoff [eV] =   776.921749    Grid Cutoff [Ry] =    57.102700&#xA;**********************************************************************&#xA;&#xA;Info: states-block size = 1.6 MiB&#xA;Input: [StatesPack = yes]&#xA;Input: [StatesOrthogonalization = cholesky_serial]&#xA;Info: the XCFunctional has been selected to match the pseudopotentials&#xA;      used in the calculation.&#xA;&#xA;**************************** Theory Level ****************************&#xA;Input: [TheoryLevel = dft]&#xA;&#xA;Exchange-correlation:&#xA;  Exchange&#xA;    Slater exchange (LDA)&#xA;    [1] P. A. M. Dirac, Math. Proc. Cambridge Philos. Soc. 26, 376 (1930)&#xA;  Correlation&#xA;    Perdew &amp;amp; Zunger (Modified) (LDA)&#xA;&#xA;Input: [SICCorrection = sic_none]&#xA;**********************************************************************&#xA;&#xA;&#xA;****************************** Hartree *******************************&#xA;Input: [DressedOrbitals = no]&#xA;The chosen Poisson solver is 'interpolating scaling functions'&#xA;**********************************************************************&#xA;&#xA;Input: [FilterPotentials = filter_TS]&#xA;Info: Pseudopotential for C&#xA;  Radii for localized parts:&#xA;    local part     =  1.4 A&#xA;    non-local part =  1.0 A&#xA;    orbitals       =  4.8 A&#xA;&#xA;Info: Pseudopotential for H&#xA;  Radii for localized parts:&#xA;    local part     =  1.0 A&#xA;    non-local part =  0.0 A&#xA;    orbitals       =  4.6 A&#xA;&#xA;Input: [RelativisticCorrection = non_relativistic]&#xA;Input: [DFTULevel = dft_u_none]&#xA;&#xA;****************** Approximate memory requirements *******************&#xA;Mesh&#xA;  global  :       1.0 MiB&#xA;  local   :       1.2 MiB&#xA;  total   :       2.2 MiB&#xA;&#xA;States&#xA;  real    :       1.6 MiB (par_kpoints + par_states + par_domains)&#xA;  complex :       3.1 MiB (par_kpoints + par_states + par_domains)&#xA;&#xA;**********************************************************************&#xA;&#xA;Info: Generating external potential&#xA;      done.&#xA;Info: Octopus initialization completed.&#xA;Info: Starting calculation mode.&#xA;Info: Allocating ground state wave-functions&#xA;Info: Blocks of states&#xA;      Block       1 contains       4 states:       1 -       4&#xA;Info: Ground-state allocation done.&#xA;&#xA;** Warning:&#xA;**   Could not find 'restart/gs' directory for restart.&#xA;**   No restart information will be read.&#xA;&#xA;&#xA;** Warning:&#xA;**   Unable to read wavefunctions.&#xA;**   Starting from scratch!&#xA;&#xA;Input: [MixField = potential] (what to mix during SCF cycles)&#xA;Input: [MixingScheme = broyden]&#xA;&#xA;**************************** Eigensolver *****************************&#xA;Input: [Eigensolver = cg]&#xA;Input: [Preconditioner = pre_filter]&#xA;Input: [PreconditionerFilterFactor = 0.5000]&#xA;Input: [SubspaceDiagonalization = standard]&#xA;**********************************************************************&#xA;&#xA;Input: [EigensolverSkipKpoints = no]&#xA;Input: [LCAOStart = lcao_states]&#xA;Input: [LCAOScaleFactor = 1.000]&#xA;Input: [LCAOMaximumOrbitalRadius = 10.58 A]&#xA;Info: Single-precision storage for     4 extra orbitals will be allocated.&#xA;Info: Unnormalized total charge =      7.997443&#xA;Info: Renormalized total charge =      8.000000&#xA;Info: Setting up Hamiltonian.&#xA;Info: Performing initial LCAO calculation with      8 orbitals.&#xA;Info: Getting Hamiltonian matrix elements.&#xA;ETA: .......1......2.......3......4......5.......6......7.......8......9......0&#xA;Eigenvalues [eV]&#xA; #st  Spin   Eigenvalue      Occupation&#xA;   1   -- ************       2.000000&#xA;   2   -- ************       2.000000&#xA;   3   -- ************       2.000000&#xA;   4   -- ************       2.000000&#xA;Info: Ground-state restart information will be written to 'restart/gs'.&#xA;Info: SCF using real wavefunctions.&#xA;Info: Starting SCF iteration.&#xA;ETA: .......1......2.......3......4......5.......6......7.......8......9......0&#xA;&#xA;*********************** SCF CYCLE ITER #    1 ************************&#xA; etot  = -1.52078533E+02 abs_ev   =  1.19E+08 rel_ev   =  2.66E+06&#xA; ediff =       -5.59E+00 abs_dens =  3.63E+00 rel_dens =  4.54E-01&#xA;Matrix vector products:      8&#xA;Converged eigenvectors:      0&#xA;&#xA;#  State  Eigenvalue [eV]  Occupation    Error&#xA;      1      -13.785511    2.000000   (3.4E-01)&#xA;      2       -8.680159    2.000000   (4.1E-01)&#xA;      3       -0.798552    2.000000   (3.8E-01)&#xA;      4        0.777761    2.000000   (3.3E-01)&#xA;&#xA;Density of states:&#xA;&#xA;----------------------------------------------------------------------&#xA;----------------------------------------------------------------------&#xA;&#xA;Elapsed time for SCF step     1:          0.09&#xA;**********************************************************************&#xA;&#xA;ETA: .......1......2.......3......4......5.......6......7.......8......9......0&#xA;&#xA;*********************** SCF CYCLE ITER #    2 ************************&#xA; etot  = -1.48054766E+02 abs_ev   =  4.02E+00 rel_ev   =  9.83E-02&#xA; ediff =        1.48E-01 abs_dens =  1.09E-14 rel_dens =  1.36E-15&#xA;Matrix vector products:      8&#xA;Converged eigenvectors:      0&#xA;&#xA;#  State  Eigenvalue [eV]  Occupation    Error&#xA;      1      -12.755744    2.000000   (3.3E-01)&#xA;      2       -8.213151    2.000000   (4.2E-01)&#xA;      3       -0.790464    2.000000   (3.7E-01)&#xA;      4        1.284781    2.000000   (3.4E-01)&#xA;&#xA;Density of states:&#xA;&#xA;----------------------------------------------------------------------&#xA;----------------------------------------------------------------------&#xA;&#xA;ETA: .......1......2.......3......4......5.......6......7.......8......9......0&#xA;&#xA;*********************** SCF CYCLE ITER #    3 ************************&#xA; etot  = -1.38666004E+02 abs_ev   =  9.39E+00 rel_ev   =  2.97E-01&#xA; ediff =        3.45E-01 abs_dens =  1.88E-14 rel_dens =  2.35E-15&#xA;Matrix vector products:      8&#xA;Converged eigenvectors:      0&#xA;&#xA;#  State  Eigenvalue [eV]  Occupation    Error&#xA;      1      -10.617759    2.000000   (3.1E-01)&#xA;      2       -7.350349    2.000000   (4.5E-01)&#xA;      3       -0.625441    2.000000   (3.8E-01)&#xA;      4        2.813351    2.000000   (3.8E-01)&#xA;&#xA;Density of states:&#xA;&#xA;----------------------------------------------------------------------&#xA;----------------------------------------------------------------------&#xA;&#xA;Elapsed time for SCF step     3:          0.12&#xA;*********************************************************************&#xA;Info: SCF converged in    3 iterations&#xA;&#xA;** Warning:&#xA;**   Some of the states are not fully converged!&#xA;&#xA;Info: Finished writing information to 'restart/gs'.&#xA;&#xA;             Octopus emitted 3 warnings.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;**OUTPUT**&#xA;&#xA;******************************** Grid ********************************&#xA;Simulation Box:&#xA;  Type = minimum&#xA;  Radius  [A] =   3.500&#xA;  Octopus will run in 3 dimension(s).&#xA;  Octopus will treat the system as periodic in 0 dimension(s).&#xA;Main mesh:&#xA;  Spacing [A] = ( 0.220, 0.220, 0.220)    volume/point [A^3] =      0.01065&#xA;  # inner mesh =      31525&#xA;  # total mesh =      51605&#xA;  Grid Cutoff [eV] =   776.921749    Grid Cutoff [Ry] =    57.102700&#xA;**********************************************************************&#xA;&#xA;&#xA;***************************** Symmetries *****************************&#xA;Symmetry elements : 4*(C3) 3*(C2) 3*(S4) 6*(sigma)&#xA;Symmetry group    : Td&#xA;**********************************************************************&#xA;&#xA;&#xA;**************************** Theory Level ****************************&#xA;Input: [TheoryLevel = dft]&#xA;&#xA;Exchange-correlation:&#xA;  Exchange&#xA;    Slater exchange (LDA)&#xA;    [1] P. A. M. Dirac, Math. Proc. Cambridge Philos. Soc. 26, 376 (1930)&#xA;  Correlation&#xA;    Perdew &amp;amp; Zunger (Modified) (LDA)&#xA;&#xA;Input: [SICCorrection = sic_none]&#xA;**********************************************************************&#xA;&#xA;SCF converged in    3 iterations&#xA;&#xA;Some of the states are not fully converged!&#xA;Eigenvalues [eV]&#xA; #st  Spin   Eigenvalue      Occupation&#xA;   1   --   -10.617759       2.000000&#xA;   2   --    -7.350349       2.000000&#xA;   3   --    -0.625441       2.000000&#xA;   4   --     2.813351       2.000000&#xA;&#xA;Energy [eV]:&#xA;      Total       =      -138.66600447&#xA;      Free        =      -138.66600447&#xA;      -----------&#xA;      Ion-ion     =       236.08498119&#xA;      Eigenvalues =       -31.56039516&#xA;      Hartree     =       367.70074449&#xA;      Int[n*v_xc] =      -104.40563731&#xA;      Exchange    =       -69.09214325&#xA;      Correlation =       -10.80334008&#xA;      vanderWaals =         0.00000000&#xA;      Delta XC    =         0.00000000&#xA;      Entropy     =         0.00000000&#xA;      -TS         =        -0.00000000&#xA;      Photon ex.  =         0.00000000&#xA;      Kinetic     =       233.69335590&#xA;      External    =      -896.24957644&#xA;      Non-local   =       -56.82391015&#xA;      Int[n*v_E]  =         0.00000000&#xA;&#xA;Dipole:                 [A]          [Debye]&#xA;      &amp;lt;x&amp;gt; =   -1.28092E+00     -6.15254E+00&#xA;      &amp;lt;y&amp;gt; =    3.40491E-01      1.63545E+00&#xA;      &amp;lt;z&amp;gt; =   -3.29699E-01     -1.58361E+00&#xA;&#xA;Convergence:&#xA;      abs_dens =  1.88070103E-14 ( 0.00000000E+00)&#xA;      rel_dens =  2.35087629E-15 ( 1.00000000E-06)&#xA;      abs_ev =  3.45030665E-01 ( 0.00000000E+00) [eV]&#xA;      rel_ev =  2.97485561E-01 ( 0.00000000E+00)&#xA;&#xA;Forces on the ions [eV/A]&#xA; Ion                        x              y              z&#xA;   1         C   0.362937E+02  -0.275830E+02   0.116276E+02&#xA;   2         H   0.170877E+02   0.757380E+01   0.150166E+02&#xA;   3         H  -0.650774E+01  -0.134651E+02   0.129681E+02&#xA;   4         H   0.147686E+02  -0.112452E+02  -0.725906E+01&#xA;   5         H  -0.142230E+02   0.106085E+02  -0.154793E+02&#xA; ----------------------------------------------------------&#xA; Max abs force   0.362937E+02   0.275830E+02   0.154793E+02&#xA;   Total force   0.474192E+02  -0.341111E+02   0.168739E+02&#xA;  Total torque  -0.635395E+00  -0.162418E+00   0.317413E+01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where am I going wrong?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="1178" LastEditorUserId="5" LastEditDate="2021-08-14T16:56:57.800" LastActivityDate="2021-08-14T16:56:57.800" Title="What could be the possible causes of the energy difference in the following calculation using Octopus (TDDFT) code?" Tags="|software|td-dft|octopus|" AnswerCount="0" CommentCount="3" ClosedDate="2021-10-29T17:51:26.577" ContentLicense="CC BY-SA 4.0" />
  <row Id="4309" PostTypeId="2" ParentId="4306" CreationDate="2021-02-07T19:12:20.480" Score="8" Body="&lt;p&gt;If considering the full phase space, equilibrium classical MD (with a stochastic thermostat) is Markovian. The probability of going to another microstate (phase space point) is fully determined by the current positions and velocities. That probability is defined by your MD integrator. Since it is a mathematical property, it is true for any time step size. Time steps that are too large could mean that the trajectory wouldn't be a good model of physical reality; MD as an algorithm is what is Markovian.&lt;/p&gt;&#xA;&lt;p&gt;On the caveats I listed:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Without the full phase space (i.e., if you ignore velocities and only map coordinates, or some subset of the coordinates) then you may lose the Markovianity. This can be true of any Markovian process, though. Reducing dimensionality is hard.&lt;/li&gt;&#xA;&lt;li&gt;Non-equilibrium dynamics can introduce a time dependence on the transition probabilities, which breaks the Markov assumption in a formal sense.&lt;/li&gt;&#xA;&lt;li&gt;If you don't have a stochastic component to your integration scheme, then it isn't a stochastic process, and therefore Markov theory doesn't apply.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, there's a related question that might be more your interest: Can Markov models be used to represent the dynamics of conformational transitions in a peptide? The answer to that is often yes, but with some different reasoning. There's a whole field of people developing Markov state models from classical MD.&lt;/p&gt;&#xA;&lt;p&gt;Here are a couple of papers on that, both with examples using peptides:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1063/1.3565032&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.3565032&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1063/1.2714538&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.2714538&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The big difference is in the definition of your states. You will want a coarser discretization than &amp;quot;every possible point in phase space.&amp;quot; You'll also want to introduce a lag time: essentially, the number of MD time steps that you combine to call one &amp;quot;step&amp;quot; in your Markov process. Transitions between states are only become Markovian after sufficient lag time.&lt;/p&gt;&#xA;&lt;p&gt;You'll often hear about &amp;quot;implied timescales&amp;quot; in Markov state modeling. This is a measure of how quickly the process will reach equilibrium. If you increase the lag time in a Markovian process, the implied timescales should not change. This is often used as a check on a Markov state model, but it's important to remember that the implication is actually the other way: Markovian implies independence with respect to lag time, not vice versa.&lt;/p&gt;&#xA;&lt;p&gt;Aside (added after comment from OP): In condensed phase systems, you can often treat the saved trajectory positions as an approximation to Brownian motion (which is certainly Markovian). This is because there's big difference between the time step used in the dynamics (order of femtosecond) and the frequency at which frames are saved to disk (usually picoseconds or longer), and condensed phase systems are chaotic. General argument: by the time there's no memory of the initial velocities (i.e., if the velocity autocorrelation function has decayed to zero), the initial velocities might as well have been random.&lt;/p&gt;&#xA;&lt;p&gt;That's far from a proof that it is Markovian, but the argument is that if the velocities don't matter, then positions might as well be &amp;quot;the full universe&amp;quot;, as &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4311/2004&quot;&gt;Nike Dattani's answer&lt;/a&gt; discusses.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-02-08T17:08:51.180" LastActivityDate="2021-02-08T17:08:51.180" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4310" PostTypeId="2" ParentId="4303" CreationDate="2021-02-07T22:14:36.437" Score="5" Body="&lt;p&gt;You should consider the states (roots) with non-zero oscillator strength. It means that the transition from the ground to excited state is allowed by the transition dipole moment rule. So, in your case root number 3 is the first excited state with oscillator strength of 0.16, whilst root number 5 is the second excited state with oscillator strength of 0.24. So in your case, if you want to compare with the experimental value (3.8624 eV), it will be root number 3. For computing the emission spectra of a molecule you do need to optimise the excited state geometry first. Once you optimise the excited state geometry, then you can do the same procedure. For computing the fluorescence do optimise the lowest singlet excited state, whilst for computing the phosphorescence do optimise the lowest triplet excited state. Remember the Kasha's rule.&lt;/p&gt;&#xA;" OwnerUserId="159" LastEditorUserId="159" LastEditDate="2021-02-10T10:08:53.540" LastActivityDate="2021-02-10T10:08:53.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4311" PostTypeId="2" ParentId="4306" CreationDate="2021-02-07T22:57:07.883" Score="9" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Warning:&lt;/strong&gt; In the physical literature the epithet &amp;quot;Markov&amp;quot; is often used with regrettable looseness. The term has a magical appeal, which invites itself in an intuitive sense not covered by the definition. [...] it is meaningless to ask whether or not it is Markovian, unless one specifies the variables to be used for its description.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That warning is a quote from one of the most famous books in matter modeling: &lt;a href=&quot;https://www.sciencedirect.com/book/9780444529657/stochastic-processes-in-physics-and-chemistry&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Stochastic Processes in Physics and Chemistry&amp;quot;&lt;/a&gt; by &lt;a href=&quot;https://en.wikipedia.org/wiki/Nico_van_Kampen&quot; rel=&quot;noreferrer&quot;&gt;Nico van Kampen&lt;/a&gt;. The book has 15967 citations on Google Scholar at the moment, and that specific quote has been reused elsewhere, such as &lt;a href=&quot;https://www.math.uwaterloo.ca/%7Emscott/Little_Notes.pdf&quot; rel=&quot;noreferrer&quot;&gt;in this free PDF book&lt;/a&gt; on Pg. 51.&lt;/p&gt;&#xA;&lt;p&gt;When a process is Markovian, it essentially means that the &lt;a href=&quot;https://en.wikipedia.org/wiki/Probability_density_function&quot; rel=&quot;noreferrer&quot;&gt;probability density function&lt;/a&gt; at time &lt;span class=&quot;math-container&quot;&gt;$t_{n+1}$&lt;/span&gt; can entirely be obtained from the function's current value at &lt;span class=&quot;math-container&quot;&gt;$t_n$&lt;/span&gt;, and does not depend explicitly on previous times such as &lt;span class=&quot;math-container&quot;&gt;$t_{n-1}, t_{n-2},$&lt;/span&gt; etc. It has &lt;strong&gt;no memory&lt;/strong&gt; of the past.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The definition can be generalized beyond just probability distribution functions, because (for example) in quantum mechanics we have the &lt;em&gt;density matrix&lt;/em&gt; where the &lt;em&gt;diagonals&lt;/em&gt; are probabilities, but the off-diagonals are something that doesn't even exist in classical theory. If the density matrix evolves like:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\rho(t_{n+1}) = e^{-\frac{\textrm{i}}{\hbar}Ht_{n+1}}\rho(t_n)e^{\frac{\textrm{i}}{\hbar}Ht_{n+1}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;then the evolution we can obtain &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n+1})$&lt;/span&gt; from only &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n})$&lt;/span&gt;. Then we can obtain &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n+2})$&lt;/span&gt; from only &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n+1})$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n+3})$&lt;/span&gt; from only &lt;span class=&quot;math-container&quot;&gt;$\rho(t_{n+2})$&lt;/span&gt;, and what we get is a &lt;em&gt;&lt;strong&gt;Markov chain.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we ignore gravity (for which we don't yet have a quantum theory), we can say that the whole universe undergoes Markovian evolution according to Eq. (1). But if we want to look at a sub-system of the universe (such as a peptide molecule), then we cannot just calculate &lt;span class=&quot;math-container&quot;&gt;$\rho_{\textrm{subsystem}}(t_{n+1})$&lt;/span&gt; by just knowing &lt;span class=&quot;math-container&quot;&gt;$\rho_{\textrm{subsystem}}$&lt;/span&gt; at some previous time such as &lt;span class=&quot;math-container&quot;&gt;$t_{n}$&lt;/span&gt;, the evolution of &lt;span class=&quot;math-container&quot;&gt;$\rho_{\textrm{subsystem}}$&lt;/span&gt; will require starting at &lt;span class=&quot;math-container&quot;&gt;$\rho_{\textrm{subsystem}}(t=0)$&lt;/span&gt; and doing a &lt;em&gt;&lt;strong&gt;Feynman integral&lt;/strong&gt;&lt;/em&gt; over all the history of what the rest of the universe did to the subsytem (for example, see Eq. 8 of &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465513002294&quot; rel=&quot;noreferrer&quot;&gt;my paper&lt;/a&gt; which described an open source MATLAB code to easily calculate this Feynman integral).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So neglecting gravity, quantum mechanics tells us that the evolution of the universe is Markovian, and the evolution of any sub-system of the universe (such as a peptide molecule) that is not completely isolated from the influence of any other part of the universe, undergoes non-Markovian evolution.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here the variable to which I'm referring is the density matrix. Since non-Markovian dynamics can be hard to calculate, we often &lt;em&gt;&lt;strong&gt;approximate&lt;/strong&gt;&lt;/em&gt; the dynamics by a Markovian master equation but this is an &lt;em&gt;&lt;strong&gt;approximation&lt;/strong&gt;&lt;/em&gt; to the true non-Markovian dynamics of any system that is not the entire universe (including vacuum vibrations in QED) itself.&lt;/p&gt;&#xA;&lt;p&gt;Now in classical MD, which is an approximation of quantum dynamics, but good enough for most studies (!), the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4309/5&quot;&gt;answer by dwhswenson&lt;/a&gt; points out that if considering the full phase space (analogous to the full universe, in my above description), then the probability of going to another state follows Markovian dynamics in that it only depends on the current state (positions and velocities of all particles, notices that the we are specifying all the &amp;quot;variables&amp;quot; that van Kampen warns us to make sure we specify!). Notice also that any slight influence from outside a subsystem (i.e. from the rest of the universe) can bring the subsystem out of its equilibrium, and that his answer also says that for this non-equilibrium dynamics, the Markov approximation is no longer valid. Regarding the rest of his answer, it's certainly possible very often to approximate dynamics by a Markov process, and whether or not these approximations are sufficient for your purposes will depend on your specific study.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-07T22:57:07.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4312" PostTypeId="5" CreationDate="2021-02-08T04:33:48.830" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://octopus-code.org/wiki/Main_Page&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://octopus-code.org/wiki/Main_Page&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-08T04:33:48.830" LastActivityDate="2021-02-08T04:33:48.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4313" PostTypeId="4" CreationDate="2021-02-08T04:33:48.830" Score="0" Body="For questions about the TD-DFT code Octopus" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-08T04:33:48.830" LastActivityDate="2021-02-08T04:33:48.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4314" PostTypeId="1" AcceptedAnswerId="4333" CreationDate="2021-02-08T10:08:22.137" Score="4" ViewCount="196" Body="&lt;p&gt;I try to compute the unit cell energy of the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti2CO2}$&lt;/span&gt; MXene with NWchem.&lt;/p&gt;&#xA;&lt;p&gt;Computing the 1x1 supercell with 4x4x1 K-points grid I got -1875 Ha.&lt;/p&gt;&#xA;&lt;p&gt;Computing the 2x2 supercell with 2x2x1 K-points grid I got -7502 Ha, that means -1875.5 Ha per unit cell.&lt;/p&gt;&#xA;&lt;p&gt;I understand, that for useful results convergence should be reached with K-points and the basis set. But here I just want to understand the source of the 0.5 Ha discrepancy. Previously I thought, that NxM supercell is equivalent to NxM K-points grid. Apparently it is not true. What is the source of such a significant difference?&lt;/p&gt;&#xA;&lt;p&gt;Here are the NWchem inputs:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;1x1 supercell with 4x4x1 K-points&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;title &amp;quot;nwtest&amp;quot;&#xA;&#xA;permanent_dir /home/pvst/prg/regr/nwtest&#xA;&#xA;scratch_dir /home/pvst/prg/regr/nwtest&#xA;&#xA;start nwtest&#xA;&#xA;geometry units angstrom nocenter noautosym noautoz&#xA;  system crystal units angstrom&#xA;    lattice_vectors&#xA;      3.0136139399999999e+00 0.0000000000000000e+00 0.0000000000000000e+00&#xA;      -1.5068069700000000e+00 2.6098661399999998e+00 0.0000000000000000e+00&#xA;      0.0000000000000000e+00 0.0000000000000000e+00 3.0000000000000000e+01&#xA;  end&#xA;  Ti 3.4287223190009325e-01 6.5239607890387818e-01 2.1337608300333333e-01&#xA;  Ti 6.7638044023217136e-01 3.1914803561534388e-01 1.2846060203666668e-01&#xA;  C  9.5644354566451414e-03 9.8572931602538050e-01 1.7248868730000000e-01&#xA;  O  6.7625413136791823e-01 3.1911195292184602e-01 2.4912464496666664e-01&#xA;  O  3.4304300093474527e-01 6.5247955598213170e-01 9.7693002513333335e-02&#xA;end&#xA;&#xA;basis noprint&#xA;   * library 3-21g&#xA;end&#xA;&#xA;dft&#xA;  maxiter 2000&#xA;  xc revpbe&#xA;  mult 1&#xA;end&#xA;nwpw&#xA;  monkhorst-pack 4 4 1&#xA;  mult 1&#xA;end&#xA;&#xA;&#xA;&#xA;task dft gradient&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;2x2 supercell with 2x2x1 K-points&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;title &amp;quot;nwtest&amp;quot;&#xA;&#xA;permanent_dir /home/pvst/prg/regr/nwtest&#xA;&#xA;scratch_dir /home/pvst/prg/regr/nwtest&#xA;&#xA;start nwtest&#xA;&#xA;geometry units angstrom nocenter noautosym noautoz&#xA;  system crystal units angstrom&#xA;    lattice_vectors&#xA;      6.0272278799999999e+00 0.0000000000000000e+00 0.0000000000000000e+00&#xA;      -3.0136139399999999e+00 5.2197322799999997e+00 0.0000000000000000e+00&#xA;      0.0000000000000000e+00 0.0000000000000000e+00 3.0000000000000000e+01&#xA;  end&#xA;  Ti 1.7143611595004662e-01 3.2619803945193909e-01 2.1337608300333333e-01&#xA;  Ti 3.3819022011608568e-01 1.5957401780767194e-01 1.2846060203666668e-01&#xA;  C  4.7822177283225707e-03 9.9286465801269030e-01 1.7248868730000000e-01&#xA;  O  3.3812706568395912e-01 1.5955597646092301e-01 2.4912464496666664e-01&#xA;  O  1.7152150046737263e-01 3.2623977799106585e-01 9.7693002513333335e-02&#xA;  Ti 1.7143611595004657e-01 8.2619803945193904e-01 2.1337608300333333e-01&#xA;  Ti 3.3819022011608568e-01 6.5957401780767189e-01 1.2846060203666668e-01&#xA;  C  4.7822177283225655e-03 4.9286465801269025e-01 1.7248868730000000e-01&#xA;  O  3.3812706568395912e-01 6.5955597646092301e-01 2.4912464496666664e-01&#xA;  O  1.7152150046737266e-01 8.2623977799106596e-01 9.7693002513333335e-02&#xA;  Ti 6.7143611595004660e-01 3.2619803945193909e-01 2.1337608300333333e-01&#xA;  Ti 8.3819022011608557e-01 1.5957401780767194e-01 1.2846060203666668e-01&#xA;  C  5.0478221772832266e-01 9.9286465801269030e-01 1.7248868730000000e-01&#xA;  O  8.3812706568395923e-01 1.5955597646092301e-01 2.4912464496666664e-01&#xA;  O  6.7152150046737269e-01 3.2623977799106585e-01 9.7693002513333335e-02&#xA;  Ti 6.7143611595004660e-01 8.2619803945193904e-01 2.1337608300333333e-01&#xA;  Ti 8.3819022011608579e-01 6.5957401780767189e-01 1.2846060203666668e-01&#xA;  C  5.0478221772832255e-01 4.9286465801269025e-01 1.7248868730000000e-01&#xA;  O  8.3812706568395923e-01 6.5955597646092301e-01 2.4912464496666664e-01&#xA;  O  6.7152150046737269e-01 8.2623977799106596e-01 9.7693002513333335e-02&#xA;end&#xA;&#xA;basis noprint&#xA;   * library 3-21g&#xA;end&#xA;&#xA;dft&#xA;  maxiter 2000&#xA;  xc revpbe&#xA;  mult 1&#xA;end&#xA;nwpw&#xA;  monkhorst-pack 2 2 1&#xA;  mult 1&#xA;end&#xA;&#xA;&#xA;&#xA;task dft gradient&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="277" LastEditorUserId="5" LastEditDate="2021-02-12T07:04:39.663" LastActivityDate="2021-02-13T05:22:47.237" Title="Energy per unit cell in NWChem differs for different supercells despite the same k-points density" Tags="|density-functional-theory|k-points|nwchem|supercell|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4315" PostTypeId="2" ParentId="2182" CreationDate="2021-02-08T15:19:53.320" Score="4" Body="&lt;p&gt;Alanine dipeptide (AD) is a very small system with only 3 residues (2 of which are capping residues). If you're looking for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; helix or &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; sheet structures, they do not exist in such a small system. The &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; helix, for example, is generally defined by the existence of hydrogen bonds between backbone atoms of residues &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$i+4$&lt;/span&gt;. Many software packages won't assign any labels to such small systems, since secondary structure requires a little more context.&lt;/p&gt;&#xA;&lt;p&gt;There are a few different terms for the conformational states of AD: you'll see &lt;span class=&quot;math-container&quot;&gt;$\alpha_R$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_{7eq}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_{7ax}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_L$&lt;/span&gt;, etc. There are challenges with creating general software to label these kinds of conformational states. First, the software would need to know whether your simulations were gas phase or solvated. This has a large effect on the stable states of AD. The locations of the minima also change depending on the force field. If I recall correctly, &lt;span class=&quot;math-container&quot;&gt;$\psi=0$&lt;/span&gt;; &lt;span class=&quot;math-container&quot;&gt;$\phi\approx-100$&lt;/span&gt; degrees is near the free energy maximum of a transition barrier in AMBER96, but near a stable state (free energy minimum) in AMBER99SB-ILDN! So without more information about your simulation, it would be impossible for any software to determine the states.&lt;/p&gt;&#xA;&lt;p&gt;As a practical matter, the way I usually go about labeling states in such a system is to write a small bit of Python. Tools like &lt;a href=&quot;https://mdtraj.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDTraj&lt;/a&gt;, &lt;a href=&quot;https://amber-md.github.io/pytraj&quot; rel=&quot;nofollow noreferrer&quot;&gt;pytraj&lt;/a&gt;, and &lt;a href=&quot;https://www.mdanalysis.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDAnalysis&lt;/a&gt; make it easy to extract the Ramachandran angles. For AD, you can probably figure out state boundaries by eye after plotting in the Ramachandran plane (or look at an existing free energy diagram for your force field, since AD is so well-studied).&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-02-08T15:19:53.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4316" PostTypeId="1" CreationDate="2021-02-08T15:57:33.137" Score="5" ViewCount="279" Body="&lt;p&gt;Let's say I optimized geometry with PBE+D3. I want to carry out band structure calculation with HSE06, should I add the dispersion correction to the band structure calculation or not?&lt;/p&gt;&#xA;&lt;p&gt;I tried both and in two cases I got the equivalent band structures. So;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\textrm{Graphene}_{GO}^{\textrm{PBE-D3}} + \textrm{Graphene}_{BS}^{\textrm{HSE06-D3}} = \textrm{Graphene}_{GO}^{\textrm{PBE-D3}} + \textrm{Graphene}_{BS}^{\textrm{HSE06}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I assume that dispersion correction affects bandstructure due to optimized geometry. So it really does not have any effect on a single point band structure calculation. If it's like that why in some papers, it shows for example as: &lt;code&gt;PBE+D3&lt;/code&gt; or &lt;code&gt;HSE06+D3&lt;/code&gt;. If I just use dispersion correction at the geometry optimization level, still can I put &lt;code&gt;HSE06+D3&lt;/code&gt; on the figure, or should I add the dispersion correction to the band structure calculation even it does not have any effect.&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2021-02-08T17:55:55.123" LastActivityDate="2021-02-13T22:27:34.607" Title="Dispersion correction and band structure" Tags="|density-functional-theory|geometry-optimization|dispersion-correction|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4317" PostTypeId="1" CreationDate="2021-02-09T01:29:11.193" Score="16" ViewCount="1850" Body="&lt;p&gt;In very recent years, exciton physics has been intensively explored as the emergence of &lt;a href=&quot;https://en.wikipedia.org/wiki/Two-dimensional_materials&quot; rel=&quot;noreferrer&quot;&gt;2D materials&lt;/a&gt;. Exciton is a bound electron-hole pair and is bosonic, namely hosting an integer spin.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;My first question is what the integer spin is? We all know the spin of an electron is &lt;span class=&quot;math-container&quot;&gt;$\dfrac{1}{2}$&lt;/span&gt; and the hole will hold a positive charge compared to the kicked electron. Can we consider that the spin of the hole will be &lt;span class=&quot;math-container&quot;&gt;$-\dfrac{1}{2}$&lt;/span&gt; and the exciton holds an integer spin &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;My second question is how the formation of the exciton is affected by the spin of electrons? For example, the following figure from &lt;a href=&quot;https://www.nature.com/articles/s41699-018-0074-2&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; indicates that the spin is closely related to the formation of the exciton.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;My third question is how can we demonstrate these spin-related exciton landscapes with first-principles calculations?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QdHQ8.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QdHQ8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-02-09T04:04:47.833" LastActivityDate="2022-07-11T13:37:37.070" Title="How to understand the spin of exciton?" Tags="|ab-initio-calculations|excited-states|spin|quantum-dots|exciton|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4318" PostTypeId="2" ParentId="4317" CreationDate="2021-02-09T03:27:12.593" Score="16" Body="&lt;p&gt;As you mentioned in the question, excitons are indeed bound electron-hole pairs. They are often considered to be the signature of optical spectra in insulating solids. Adding onto the comment by tmph, there are two types of excitons: opposite spins of electrons will lead to a dark exciton with S=0 (since it doesn't allow for momentum conservation). Same spin of electrons will lead to a bright exciton with S=1 (since it allows for recombination). Therefore the electronic band-structure can often serve as an indicator for optical selection rules of excitons. The dipole strength (that dictates the relative strength of 'bright' or 'dark') is a term that is basically a superposition of dipoles from DFT (read: Fermi's golden rule). The dark exciton is not trivial though, it has been observed in experiments like &lt;a href=&quot;https://science.sciencemag.org/content/370/6521/1199.abstract&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the third part of your question, the method of choice to model excitons seems to be the GW-BSE method, since the exciton itself is inherently an excited state. But the mean-field starting point is Kohn-Sham DFT in most GW-BSE calculations.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Thanks to Anyon for pointing out a class of excitons with S=2 occurring in certain semiconductors, this should potentially be considered as well.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="683" LastEditDate="2021-02-09T04:40:41.980" LastActivityDate="2021-02-09T04:40:41.980" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="4319" PostTypeId="1" CreationDate="2021-02-09T10:49:13.873" Score="8" ViewCount="1316" Body="&lt;p&gt;I am trying to perform NBO analysis with relaxed density matrix with the open-source program JANPA. I am following the guide &lt;a href=&quot;https://sourceforge.net/p/janpa/wiki/OrcaExamples/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The first step is to get the NBO input .47 file from Orca v4.2.1. The guide says that I should request NBO analysis with Orca in absence of the actual NBO executable to get the .47 file.&lt;/p&gt;&#xA;&lt;p&gt;So I set the GENEXE and NBOEXE environment variables to dummy exe files that don't do anything when called. However, in spite of this, I cannot see the .47 file anywhere on the disk.&lt;/p&gt;&#xA;&lt;p&gt;How do I generate the file required for NBO analysis? Any help is appreciated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt;: The input file I am using is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! RHF SP def2-SVP NPA &#xA;&#xA;* xyz 0 1&#xA;   C       -1.54056        0.93336        0.00000&#xA;   H       -0.47056        0.93336        0.00000&#xA;   H       -1.89722       -0.02889       -0.30294&#xA;   H       -1.89722        1.67683       -0.68186&#xA;   H       -1.89723        1.15213        0.98480&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am setting the environment variables with&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set GENEXE=C:\Users\Public\Orca4.1\orca\gennbo.exe&#xA;set NBOEXE=C:\Users\Public\Orca4.1\orca\nbo6.exe&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Both nbo6.exe and gennbo.exe are dummy executables that don't do anything when executed.&#xA;Note that the Orca version is 4.2.1 even though the directory name is 4.1.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-02-19T19:13:43.323" LastActivityDate="2021-02-19T19:13:43.323" Title="How to get the .47 file from ORCA for natural bonding orbital analysis" Tags="|quantum-chemistry|software-assistance|orca|orbitals|population-analysis|" AnswerCount="1" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4320" PostTypeId="5" CreationDate="2021-02-09T10:52:14.263" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-02-09T10:52:14.263" LastActivityDate="2021-02-09T10:52:14.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4321" PostTypeId="4" CreationDate="2021-02-09T10:52:14.263" Score="0" Body="For questions about population analysis methods, such as Mulliken, Lowdin, Mayer, NPA, Bader etc." OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-02-09T17:45:17.803" LastActivityDate="2021-02-09T17:45:17.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4322" PostTypeId="1" CreationDate="2021-02-10T03:31:25.010" Score="6" ViewCount="1811" Body="&lt;p&gt;I am following Justin Lemkul's GROMACS simulation given on this &lt;a href=&quot;http://www.mdtutorials.com/gmx/umbrella/index.html&quot; rel=&quot;noreferrer&quot;&gt;website here for GROMACS&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I believe I have followed the process to the T. I would like to mention that in the &amp;quot;Generate Topology&amp;quot; section of the tutorial, he says to include&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#ifdef POSRES_B&#xA;#include &amp;quot;posre_Protein_chain_B.itp&amp;quot;&#xA;#endif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, this was already present in my posre_Protein_chain_B.itp file. However this statement was also present in my posre_Protein_chain_A.itp, posre_Protein_chain_C.itp, posre_Protein_chain_D.itp, posre_Protein_chain_E.itp files. For example,&#xA;posre_Protein_chain_A.itp had&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#ifdef POSRES_A&#xA;#include &amp;quot;posre_Protein_chain_A.itp&amp;quot;&#xA;#endif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in it. I have commented them out, so it now looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; #ifdef POSRES_A&#xA;; #include &amp;quot;posre_Protein_chain_A.itp&amp;quot;&#xA;; #endif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Furthermore, every time I was asked to choose for N-terminus, I hit option 2: None, and everytime I was asked to choose a C-terminus, I hit option 0: COO-. This resulted in the system having a net negative charge I believe.&lt;/p&gt;&#xA;&lt;p&gt;I don't think I have deviated anywhere else in this simulation. However, I am getting the error message in the attachment when I run&lt;/p&gt;&#xA;&lt;p&gt;gmx grompp -f ions.mdp -c solv.gro -p topol.top -o ions.tpr&lt;/p&gt;&#xA;&lt;p&gt;After running this command I received the following error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GROMACS is free software; you can redistribute it and/or modify it&#xA;under the terms of the GNU Lesser General Public License&#xA;as published by the Free Software Foundation; either version 2.1&#xA;of the License, or (at your option) any later version.&#xA;&#xA;GROMACS:      gmx grompp, version 2020.5&#xA;Executable:   /home/satyend/.local/bin/gmx&#xA;Data prefix:  /home/satyend/.local&#xA;Working dir:  /home/satyend/software/gromacs_gpu/umbrella-sampling-protofibril&#xA;Command line:&#xA;  gmx grompp -f ions.mdp -c solv.gro -p topol.top -o ions.tpr&#xA;&#xA;Ignoring obsolete mdp entry 'ns_type'&#xA;&#xA;NOTE 1 [file ions.mdp]:&#xA;  With Verlet lists the optimal nstlist is &amp;gt;= 10, with GPUs &amp;gt;= 20. Note&#xA;  that with the Verlet scheme, nstlist has no effect on the accuracy of&#xA;  your simulation.&#xA;&#xA;Setting the LD random seed to 2139084382&#xA;Generated 165 of the 1596 non-bonded parameter combinations&#xA;Excluding 3 bonded neighbours molecule type 'Protein_chain_A'&#xA;Excluding 3 bonded neighbours molecule type 'Protein_chain_B'&#xA;Excluding 3 bonded neighbours molecule type 'Protein_chain_C'&#xA;Excluding 3 bonded neighbours molecule type 'Protein_chain_D'&#xA;Excluding 3 bonded neighbours molecule type 'Protein_chain_E'&#xA;Excluding 2 bonded neighbours molecule type 'SOL'&#xA;&#xA;WARNING 1 [file topol.top, line 54]:&#xA;  The GROMOS force fields have been parametrized with a physically&#xA;  incorrect multiple-time-stepping scheme for a twin-range cut-off. When&#xA;  used with a single-range cut-off (or a correct Trotter&#xA;  multiple-time-stepping scheme), physical properties, such as the density,&#xA;  might differ from the intended values. Since there are researchers&#xA;  actively working on validating GROMOS with modern integrators we have not&#xA;  yet removed the GROMOS force fields, but you should be aware of these&#xA;  issues and check if molecules in your system are affected before&#xA;  proceeding. Further information is available at&#xA;  https://redmine.gromacs.org/issues/2884 , and a longer explanation of our&#xA;  decision to remove physically incorrect algorithms can be found at&#xA;  https://doi.org/10.26434/chemrxiv.11474583.v1 .&#xA;&#xA;&#xA;NOTE 2 [file topol.top, line 54]:&#xA;  System has non-zero total charge: -10.000000&#xA;  Total charge should normally be an integer. See&#xA;  http://www.gromacs.org/Documentation/Floating_Point_Arithmetic&#xA;  for discussion on how close it should be to an integer.&#xA;  &#xA;&#xA;&#xA;Number of degrees of freedom in T-Coupling group rest is 67749.00&#xA;&#xA;NOTE 3 [file ions.mdp]:&#xA;  You are using a plain Coulomb cut-off, which might produce artifacts.&#xA;  You might want to consider using PME electrostatics.&#xA;&#xA;&#xA;&#xA;There were 3 notes&#xA;&#xA;There was 1 warning&#xA;&#xA;-------------------------------------------------------&#xA;Program:     gmx grompp, version 2020.5&#xA;Source file: src/gromacs/gmxpreprocess/grompp.cpp (line 2353)&#xA;&#xA;Fatal error:&#xA;Too many warnings (1).&#xA;If you are sure all warnings are harmless, use the -maxwarn option.&#xA;&#xA;For more information and tips for troubleshooting, please check the GROMACS&#xA;website at http://www.gromacs.org/Documentation/Errors&#xA;-------------------------------------------------------&#xA;Analysing residue names:&#xA;There are:   135    Protein residues&#xA;There are: 10727      Water residues&#xA;Analysing Protein...&#xA;This run will generate roughly 3 Mb of data&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the link to the &lt;code&gt;ions.mdp&lt;/code&gt; file Dr. Lemkul has provided: &lt;a href=&quot;http://www.mdtutorials.com/gmx/umbrella/Files/ions.mdp&quot; rel=&quot;noreferrer&quot;&gt;http://www.mdtutorials.com/gmx/umbrella/Files/ions.mdp&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What is going wrong here? I feel like I am running around in circles with this tutorial...&lt;/p&gt;&#xA;&lt;p&gt;I appreciate any advice you have to offer!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-06-30T04:00:55.643" Title="Error in GROMACS for adding ions to a solution" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4323" PostTypeId="1" CreationDate="2021-02-10T03:57:22.093" Score="10" ViewCount="741" Body="&lt;p&gt;I did a TDDFT calculation to get the emission spectra of my molecule. Here are the first five roots for the emission calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ----------------------------------------------------------------------------&#xA;  Root   1 singlet a              0.093596388 a.u.                2.5469 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -0.01267   Y  0.11330   Z -0.00853&#xA;     Transition Moments   XX -0.17432  XY -0.11698  XZ  0.08725&#xA;     Transition Moments   YY  0.50038  YZ  0.04076  ZZ -0.00276&#xA;     Dipole Oscillator Strength                    0.0008155382&#xA;     Electric Quadrupole                           0.0000000006&#xA;     Magnetic Dipole                               0.0000000172&#xA;     Total Oscillator Strength                     0.0008155561&#xA; &#xA;     Occ.  118  a   ---  Virt.  119  a   -0.99690 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   2 singlet a              0.125536009 a.u.                3.4160 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -1.40368   Y -0.22255   Z -0.09172&#xA;     Transition Moments   XX -0.86565  XY  0.08026  XZ  0.72579&#xA;     Transition Moments   YY -4.46850  YZ -0.97403  ZZ  0.39936&#xA;     Dipole Oscillator Strength                    0.1697471134&#xA;     Electric Quadrupole                           0.0000000828&#xA;     Magnetic Dipole                               0.0000000989&#xA;     Total Oscillator Strength                     0.1697472950&#xA; &#xA;     Occ.  118  a   ---  Virt.  120  a    0.95252 X&#xA;     Occ.  118  a   ---  Virt.  121  a    0.28877 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   3 singlet a              0.130233593 a.u.                3.5438 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X  0.04368   Y  0.07607   Z  0.00812&#xA;     Transition Moments   XX  0.21272  XY -0.14124  XZ  0.00845&#xA;     Transition Moments   YY  0.21031  YZ -0.10142  ZZ -0.01092&#xA;     Dipole Oscillator Strength                    0.0006738052&#xA;     Electric Quadrupole                           0.0000000006&#xA;     Magnetic Dipole                               0.0000000089&#xA;     Total Oscillator Strength                     0.0006738146&#xA; &#xA;     Occ.  117  a   ---  Virt.  119  a   -0.99558 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   4 singlet a              0.135112905 a.u.                3.6766 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -1.61404   Y -0.10037   Z -0.10533&#xA;     Transition Moments   XX -0.92285  XY -0.71420  XZ  0.79973&#xA;     Transition Moments   YY -3.91548  YZ -1.09555  ZZ  0.35107&#xA;     Dipole Oscillator Strength                    0.2365653107&#xA;     Electric Quadrupole                           0.0000000939&#xA;     Magnetic Dipole                               0.0000000166&#xA;     Total Oscillator Strength                     0.2365654212&#xA; &#xA;     Occ.  118  a   ---  Virt.  120  a    0.27816 X&#xA;     Occ.  118  a   ---  Virt.  121  a   -0.94577 X&#xA;     Occ.  118  a   ---  Virt.  122  a   -0.12569 X&#xA;  ----------------------------------------------------------------------------&#xA;  Root   5 singlet a              0.144664128 a.u.                3.9365 eV &#xA;  ----------------------------------------------------------------------------&#xA;     Transition Moments    X -1.29163   Y  1.43040   Z  0.11014&#xA;     Transition Moments   XX-13.39872  XY  1.41335  XZ -0.50657&#xA;     Transition Moments   YY 14.47237  YZ  0.64851  ZZ  0.27558&#xA;     Dipole Oscillator Strength                    0.3593917443&#xA;     Electric Quadrupole                           0.0000031743&#xA;     Magnetic Dipole                               0.0000000937&#xA;     Total Oscillator Strength                     0.3593950123&#xA; &#xA;     Occ.  117  a   ---  Virt.  120  a   -0.06248 X&#xA;     Occ.  117  a   ---  Virt.  121  a    0.07336 X&#xA;     Occ.  118  a   ---  Virt.  121  a   -0.11547 X&#xA;     Occ.  118  a   ---  Virt.  122  a    0.97589 X&#xA;     Occ.  118  a   ---  Virt.  123  a   -0.05942 X&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For my case, experimental emission is at 492 nm or 2.52 eV. In this case which root should I take to compare with the experiment? Should I always take the first root following the Kasha's rule?&lt;/p&gt;&#xA;" OwnerUserId="2052" LastEditorUserId="5" LastEditDate="2021-08-14T16:55:19.170" LastActivityDate="2021-08-15T07:04:05.517" Title="Understanding emission spectra using TDDFT calculation" Tags="|computational-chemistry|td-dft|spectroscopy|nwchem|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4324" PostTypeId="1" CreationDate="2021-02-10T05:31:07.520" Score="10" ViewCount="392" Body="&lt;p&gt;From what I read, the correlation energy can be grouped as static correlation and dynamic correlation. Another way to group them is Fermi correlation and Coulomb correlation.&lt;/p&gt;&#xA;&lt;p&gt;Is there any link between the two groupings? Someone told me static correlation is &lt;strong&gt;mainly&lt;/strong&gt; Fermi correlation, and dynamic correlation is &lt;strong&gt;mainly&lt;/strong&gt; Coulomb correlation, is it true? If so, what is the different part from the &amp;quot;&lt;strong&gt;main&lt;/strong&gt;&amp;quot; part?&lt;/p&gt;&#xA;" OwnerUserId="2066" LastEditorUserId="5" LastEditDate="2021-02-10T07:37:10.910" LastActivityDate="2021-02-10T18:54:04.563" Title="How does static correlation differ from Fermi correlation, and how does dynamic correlation differ from Coulomb correlation?" Tags="|electron-correlation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4325" PostTypeId="2" ParentId="4324" CreationDate="2021-02-10T18:54:04.563" Score="9" Body="&lt;p&gt;&lt;em&gt;These two terms are quite rigorous in the way they're defined and used:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Fermi correlation:&lt;/strong&gt; This is the correlation found in the electron exchange term in a Hartree-Fock calculation, describes the correlation between electrons with parallel spins, and prevents two parallel-spin electrons from being found at the same location.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Coulomb correlation:&lt;/strong&gt; This is the correlation between any two electrons regardless of whether the spins are parallel or not, since any two charged particles will experience a Coulomb repulsion based on the distance between them.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;These two terms are often used more loosely:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Static correlation:&lt;/strong&gt; This is the correlation associated with a mean-field-type SCF (self-consistent-field) calculation. For example, HF-SCF or &lt;a href=&quot;https://chemistry.stackexchange.com/a/99301/27342&quot;&gt;MCSCF&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Dynamic correlation:&lt;/strong&gt; This is correlation associated with the &amp;quot;movement&amp;quot; of electrons, and is usually  associated with post-SCF calculations such as configuration-interaction or coupled-cluster calculations.&lt;/p&gt;&#xA;&lt;p&gt;It is usually said that when doing a Hartree-Fock SCF calculation, you only get static correlation, and therefore all of the Fermi correlation from the Hartree-Fock SCF is associated with static correlation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;However,&lt;/em&gt; if you're doing an MCSCF calculation, it is still said that you are getting static correlation, but it would seem that there is much more to this static correlation than what you would get from a Hartree-Fock SCF calculation, and the Fermi correlation would seem to constitute a much smaller percentage of the overall static correlation.&lt;/p&gt;&#xA;&lt;p&gt;The terms &amp;quot;static&amp;quot; and &amp;quot;dynamic&amp;quot; correlation can be confusing though, because in an MCSCF calculation, for example a CASSCF calculation, you're doing FCI in the CAS at every step of the SCF, and I mentioned earlier that configuration interaction gives you dynamic correlation, but often (for example &lt;a href=&quot;https://en.wikipedia.org/wiki/Electronic_correlation&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) it is said that MCSCF does not give dynamic correlation. Furthermore, there's SCF-type methods such as pCCD (pair coupled cluster doubles), which is also known by some as &lt;a href=&quot;https://theochem.github.io/horton/2.0.2/user_estruct_ap1rog.html&quot; rel=&quot;noreferrer&quot;&gt;AP1roG&lt;/a&gt; that recover a significant amount of correlation (in the case of pCCD/AP1roG, the energies obtained can match those of DOCI, or doubly-occupied configuration interaction, which is FCI but with all spatial orbitals always doubly occupied in all considered interacting configurations, to within 1 micro-hartree of the exact DOCI energy). When something like pCCD/AP1roG agrees with DOCI up to the micro-hartree digit, it must include dynamic correlation, but I'm not sure where to draw the line between static and dynamic correlation in this case because we don't have something like a Hartree-Fock reference.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-10T18:54:04.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4326" PostTypeId="1" AcceptedAnswerId="4329" CreationDate="2021-02-10T21:29:11.893" Score="8" ViewCount="183" Body="&lt;p&gt;My question is a little bit general. I want to study a 2D monolayer material which hasn't any experimental data available, just some first principles DFT works using PBE, LDA and HSE06 (for band structure). I want to focus on structural, electronic and magnetic properties.&#xA;Could you please tell me about the steps to follow, since in the absence of experimental data it is hard to validate results. Should I just make GGA PBE based calculations ? I'd like to know how to begin to arrive to some good logical results.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-02-18T13:46:59.083" Title="How to study a new material without any experimental data about it?" Tags="|density-functional-theory|vasp|magnetism|physical-properties-of-materials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4327" PostTypeId="1" AcceptedAnswerId="4368" CreationDate="2021-02-11T05:29:11.647" Score="10" ViewCount="272" Body="&lt;p&gt;I'm extremely new to the Wannier90 code. I was planning to install it on a workstation I have but I would be using the cores to run calculations using Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;I have a few quad core i5 PC's. &lt;strong&gt;So would installing the wannier90 code on those be a good move?&lt;/strong&gt; I'm mostly working with primitive unit cells which would have at most 10 atoms.&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="7" LastEditDate="2021-07-30T20:21:21.287" LastActivityDate="2021-07-30T20:21:21.287" Title="Is Wannier 90 computationally expensive to run?" Tags="|density-functional-theory|high-performance-computing|wannier90|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4328" PostTypeId="1" CreationDate="2021-02-11T05:44:27.253" Score="6" ViewCount="42" Body="&lt;p&gt;I need to calculate excess entropy of mixing for a particular system of alloy. The excess entropy of mixing is dependent on temperature and it takes into account this temperature dependence by using atomic packing fraction. I wanted to know once the alloy solidifies, will there be any change in the atomic packing fraction on reducing the temperature?&lt;/p&gt;&#xA;" OwnerUserId="2071" LastActivityDate="2021-02-11T05:44:27.253" Title="Atomic Packing Fraction" Tags="|crystal-structure|entropy|atomic-physics|" AnswerCount="0" CommentCount="1" ClosedDate="2021-06-24T14:16:47.647" ContentLicense="CC BY-SA 4.0" />
  <row Id="4329" PostTypeId="2" ParentId="4326" CreationDate="2021-02-11T07:51:55.920" Score="11" Body="&lt;h1&gt;Structural:&lt;/h1&gt;&#xA;&lt;p&gt;You should investigate the stability of your structure. In detail, you should verify:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Dynamical stability: phonon spectrum.&lt;/li&gt;&#xA;&lt;li&gt;Thermal stability: molecular dynamics (MD) simulations&lt;/li&gt;&#xA;&lt;li&gt;Mechanical stability: elastic constants &lt;span class=&quot;math-container&quot;&gt;$\Rightarrow$&lt;/span&gt; Born criteria&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Electronic:&lt;/h1&gt;&#xA;&lt;p&gt;Band structure and density of states calculations. Maybe you should compare the following three kinds of band structures：&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Standard calculation;&lt;/li&gt;&#xA;&lt;li&gt;Spin-polarized calculation;&lt;/li&gt;&#xA;&lt;li&gt;Noncolinear calculation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Magnetic:&lt;/h1&gt;&#xA;&lt;p&gt;Two things you should consider with first-principles calculations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Magnetic anisotropy energy (MAE): This is very important for the screening of 2D magnetic materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Curie temperature: This is important for device application.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The following are two typical references about 2D magnetic materials:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5129311?journalCode=apl&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/abs/10.1063/1.5129311?journalCode=apl&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acsami.8b14037&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acsami.8b14037&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-18T13:46:59.083" LastActivityDate="2021-02-18T13:46:59.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4331" PostTypeId="1" CreationDate="2021-02-11T22:33:05.500" Score="6" ViewCount="119" Body="&lt;p&gt;In so many papers I see that they carry out soc band structure calculations with much higher kgrid than used for the geometry optimization. Whats the logic behind that?&lt;/p&gt;&#xA;" OwnerDisplayName="user1263" LastEditorUserId="5" LastEditDate="2021-02-15T03:17:04.107" LastActivityDate="2021-02-15T03:17:04.107" Title="Does SOC band structure calculations require higher number of k-grids?" Tags="|density-functional-theory|band-structure|k-points|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4332" PostTypeId="2" ParentId="4331" CreationDate="2021-02-12T01:26:46.497" Score="4" Body="&lt;p&gt;Without knowing the specifics of the paper, I can give some general advice.  It tends to be the other way around, geometry optimization tends to not require as fine of a kgrid and often it is reduced for computational savings.&lt;/p&gt;&#xA;&lt;p&gt;Fine kgrids are generally speaking required for accurate electronic structure properties, while geometries tend to converge to the accuracy needed even with fairly coarse kgrids.  It is also worth noting that with particularly large unit cells, you can get away with using just the gamma point for geometries sometimes but this would leave you with no band structure.  Band structures often require a larger number of kpoints because you are tracing paths between high symmetry points in the Brillouin zone.  This will be largely independent of cell size unless you use some sort of band unfolding procedure.&lt;/p&gt;&#xA;&lt;p&gt;Maybe someone else can speak about your exact question, but I suspect this increase in kpoints is not directly related to SOC band structure calculations.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-02-12T01:26:46.497" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4333" PostTypeId="2" ParentId="4314" CreationDate="2021-02-12T06:28:07.273" Score="5" Body="&lt;p&gt;It turns out, that NWchem do not support K-points with Gaussian basis. The &lt;code&gt;nwpw&lt;/code&gt; section in my input files, that contains the K-point grid specification, actually configures another calculation (with plane-wave basis) that is never launched by the &lt;code&gt;task&lt;/code&gt; directive.&lt;/p&gt;&#xA;&lt;p&gt;Summing up, with NWchem you can use either K-points with plane-waves, or a supercell with Gaussian basis. But even with a supercell &lt;a href=&quot;https://github.com/nwchemgit/nwchem/issues/322&quot; rel=&quot;nofollow noreferrer&quot;&gt;you can't get periodic boundaries with Gaussian basis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Thanks to Eric Bylaska and Edoardo Aprà for bold hints &lt;a href=&quot;https://groups.google.com/g/nwchem-forum/c/CYQeUO-zZv0/m/umdMU0dRBQAJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="277" LastEditorUserId="277" LastEditDate="2021-02-13T05:22:47.237" LastActivityDate="2021-02-13T05:22:47.237" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4334" PostTypeId="1" CreationDate="2021-02-12T09:07:26.793" Score="8" ViewCount="86" Body="&lt;p&gt;I'm studying a mechanism of aromatic substitution of fluorine which proceeds via an intermediate.&lt;/p&gt;&#xA;&lt;p&gt;I'm searching for a transition state using a relaxed surface scan, then I optimize the TS and perform an IRC (intrinsic reaction coordinate) calculation to verify the products. The problem is that the intermediate (that I get from the IRC) has nearly the same energy as the TS (about 1 kcal/mol lower), which doesn't seem right.&lt;/p&gt;&#xA;&lt;p&gt;I assume that the intermediate geometry is wrong because the IRC makes 2-3 steps towards it and stops, saying the minimum was reached. &lt;strong&gt;How can I verify that an IRC gives correct results?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-09-05T23:34:35.203" LastActivityDate="2021-09-05T23:34:35.203" Title="Troubleshooting mechanistic calculation: Transition state energy and intermediate energy too close" Tags="|density-functional-theory|transition-state|reaction-mechanism|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-29T17:48:03.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="4335" PostTypeId="1" CreationDate="2021-02-12T10:09:49.377" Score="13" ViewCount="1885" Body="&lt;p&gt;I'm a new VASP user, especially for the band structure calculations. I see that KPOINTS files are different for the GO/SP calculations and band calculations.&lt;/p&gt;&#xA;&lt;p&gt;For example in &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_bandstructure&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; it shows KPOINTS file as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;k-points for bandstructure L-G-X-U K-G&#xA; 10&#xA;line&#xA;reciprocal&#xA;  0.50000  0.50000  0.50000    1&#xA;  0.00000  0.00000  0.00000    1&#xA;&#xA;  0.00000  0.00000  0.00000    1&#xA;  0.00000  0.50000  0.50000    1&#xA;&#xA;  0.00000  0.50000  0.50000    1&#xA;  0.25000  0.62500  0.62500    1&#xA;&#xA;  0.37500  0.7500   0.37500    1&#xA;  0.00000  0.00000  0.00000    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I totally understand the path but the thing confuses me is the 10. How does it choose this 10? In the first step (standard DFT run) it used following KPOINTS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4x4x4&#xA; 0&#xA;G&#xA; 4 4 4&#xA; 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does it basically took a value that close to sum of kpoints from first step? In other words, let's say I choose 12 12 4 kgrid for the first step. Do I need to put something like 25 for the following band calculation?&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2021-02-12T23:47:57.413" LastActivityDate="2021-02-15T08:21:14.773" Title="k-points value in KPOINTS file for the VASP band calculation" Tags="|density-functional-theory|band-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4336" PostTypeId="1" AcceptedAnswerId="4354" CreationDate="2021-02-12T11:33:49.067" Score="9" ViewCount="529" Body="&lt;p&gt;I am trying to do MBJLDA calculation for bandstructure for WS2 monolayer unit cell using VASP and following the method provided here : &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1997/band-structure-mbj-lda-using-vasp&quot;&gt;Band Structure mBJ-LDA using Vasp&lt;/a&gt;, but I am getting an error message.&#xA;The INPUTS are below:&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ENCUT=600&#xA;PREC = Accurate&#xA;EDIFF=1E-6&#xA;NELM=300&#xA;ISMEAR=-5&#xA;&#xA;###MBJ:&#xA;METAGGA=MBJ&#xA;LASPH=.TRUE.&#xA;LMAXMIX=4&#xA;GGA=CA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;LDA POTCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  PAW W_pv 06Nov2007                     &#xA;   TITEL  = PAW W_pv 06Nov2007&#xA;  PAW S 27Mar2009                        &#xA;   TITEL  = PAW S 27Mar2009&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; W2S4                                   &#xA;   1.00000000000000     &#xA;     3.1912863255000001    0.0000000000000000    0.0000000000000000&#xA;    -1.5956425563000001    2.7637348281000000    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   20.1269199999999984&#xA;   W    S &#xA;     1     2&#xA;Direct&#xA;  0.6666670084824631  0.3333329922369330  0.5000000000000000&#xA;  0.3333330949386806  0.6666670699615054  0.4218851941843354&#xA;  0.3333330949386806  0.6666670699615054  0.5781148058156645&#xA; &#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;The calculations was based on SCF-PBE WAVECAR&lt;/strong&gt;.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/J7Pdu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/J7Pdu.png&quot; alt=&quot;ERROR&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-02-15T08:20:19.393" LastActivityDate="2021-11-09T13:31:19.747" Title="What is the source of error in this mBJ-LDA calculation?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4337" PostTypeId="2" ParentId="4335" CreationDate="2021-02-12T14:04:19.600" Score="9" Body="&lt;p&gt;The &amp;quot;10&amp;quot; indicates the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points that will be calculated along each path segment. For example, the first path segment from &lt;span class=&quot;math-container&quot;&gt;$(0.5,0.5,0.5)$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt; will contain 10 points, and similarly for all other segments. You have &lt;span class=&quot;math-container&quot;&gt;$4$&lt;/span&gt; line segments in your example, so you will end up with a total of &lt;span class=&quot;math-container&quot;&gt;$40$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points.&lt;/p&gt;&#xA;&lt;p&gt;As to its value, you can choose a larger value if you want a finer resolution in your band structure, or a smaller value for coarser resolution. What you need will depend on what quantity you are interested in.&lt;/p&gt;&#xA;&lt;p&gt;You can read more details about the KPOINTS file here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/KPOINTS&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/KPOINTS&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-02-12T14:04:19.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4338" PostTypeId="1" AcceptedAnswerId="4343" CreationDate="2021-02-12T21:30:17.593" Score="5" ViewCount="964" Body="&lt;p&gt;I am using VASP for the first time and do not know how to do convergence tests. How are convergence tests done in VASP and how do we get two plots of Encut and k-points with respect to total energy? I want to do these things for the &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt; material.&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-02-15T03:17:52.223" LastActivityDate="2021-02-15T03:17:52.223" Title="How to do VASP convergence tests, and how to get two plots of Encut and k-points wrt to total energy? I want to do convergence for Mg2Si" Tags="|vasp|convergence-test|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4339" PostTypeId="2" ParentId="4314" CreationDate="2021-02-12T23:35:59.363" Score="2" Body="&lt;p&gt;No, the Gaussian basis module of NWChem does not support periodic boundary conditions. The calculation described here did not stop because of a bug in the code. The bug and the fix are described in this &lt;a href=&quot;https://github.com/nwchemgit/nwchem/issues/322&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github issue&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerDisplayName="user2076" LastEditorUserId="5" LastEditDate="2021-02-12T23:43:43.363" LastActivityDate="2021-02-12T23:43:43.363" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4340" PostTypeId="2" ParentId="4316" CreationDate="2021-02-13T21:16:21.227" Score="3" Body="&lt;p&gt;@Xivi76 is correct. Dispersion corrections have no direct influence on the band structure. As such, there is no need to add the D3 correction on your HSE06 static calculation if you're only interested in the band structure. Nonetheless, some people include the D3 correction because the dispersion correction is basically free, and it's consistent with the use of dispersion corrections during the geometry optimization. It won't make a difference though unless you're interested in other properties (e.g. absolute energy, force).&lt;/p&gt;&#xA;&lt;p&gt;As for your question &amp;quot;If I just use dispersion correction at the geometry optimization level, still can I put HSE06+D3 on the figure,&amp;quot; the answer is you should report exactly what you used. If you didn't use D3 with HSE06, don't mention it. Your level of theory here is HSE06//PBE-D3(BJ).&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-02-13T22:27:34.607" LastActivityDate="2021-02-13T22:27:34.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4341" PostTypeId="1" AcceptedAnswerId="4374" CreationDate="2021-02-14T22:39:12.090" Score="14" ViewCount="951" Body="&lt;p&gt;Let's say I want to run a simulation for benzene in GROMACS using parameters from a certain force-field. I logged on to the Automated Topology Builder, I looked up benzene, and I found an ITP file for benzene, and a structure (pdb) file for benzene.&lt;/p&gt;&#xA;&lt;p&gt;In the ITP file, they mention:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;bonded and van der Waals parameters were taken from GROMOS54A7 parameter set.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This sentence makes me think that the parameters they have provided can only be used when I am using the GROMOS54A7 forcefield.&lt;/p&gt;&#xA;&lt;p&gt;So my topology file has the statement&#xA;&lt;code&gt;#include GROMOS54A7_ATB.ff&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, what if I want to run a simulation for benzene in CHARMM or OPLSS or some other forcefield in GROMACS?&lt;/strong&gt; Do I have to manually construct the &lt;code&gt;.itp&lt;/code&gt; file, with the right atom types, and everything? Or is there a database where I can get the data from to use in my simulation?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-02-14T23:33:32.743" LastActivityDate="2021-03-28T10:06:27.853" Title="Finding parameters for a molecule in various forcefields" Tags="|gromacs|databases|forcefields|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4342" PostTypeId="2" ParentId="4335" CreationDate="2021-02-15T02:44:15.907" Score="3" Body="&lt;p&gt;Supplement some information to @ProfM's answer. Just for the logic.&lt;/p&gt;&#xA;&lt;p&gt;The first step with uniform k-mesh, such as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  4x4x4&#xA;  0&#xA;  G&#xA;  4 4 4&#xA;  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;is to perform a self-consistent calculation to obtain converged charge density and wavefunction. (It is not hard to understood that why the charge density must sample the whole Brillouin zone.)&lt;/p&gt;&#xA;&lt;p&gt;The second step with a line-mode k-sampling, such as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;k-points for bandstructure L-G-X-U K-G&#xA;10&#xA;line&#xA;reciprocal&#xA;0.50000  0.50000  0.50000    1&#xA;0.00000  0.00000  0.00000    1&#xA;&#xA;0.00000  0.00000  0.00000    1&#xA;0.00000  0.50000  0.50000    1&#xA;&#xA;0.00000  0.50000  0.50000    1&#xA;0.25000  0.62500  0.62500    1&#xA;&#xA;0.37500  0.7500   0.37500    1&#xA;0.00000  0.00000  0.00000    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;is to print the eigenvalue along the symmetric k-path based on the converged charge density or wavefunction from your first step, which is a post-process compared to step I. You can think line-mode k-mesh just extracts some pivotal information from the uniform k-mesh.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-15T08:21:14.773" LastActivityDate="2021-02-15T08:21:14.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4343" PostTypeId="2" ParentId="4338" CreationDate="2021-02-15T02:55:26.803" Score="3" Body="&lt;p&gt;You can find @Andrew Rosen's nice answer from this post:&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1896/k-points-and-encut-convergence-tests-before-or-after-relaxation&quot;&gt;k-points and ENCUT convergence tests before or after relaxation?&lt;/a&gt;, as @Xixi76 suggested.&lt;/p&gt;&#xA;&lt;p&gt;Besides, you can read this nice tutorial: &lt;a href=&quot;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It should be emphasized that the convergence test is one of the most important steps to obtain physical results.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-15T02:55:26.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4344" PostTypeId="2" ParentId="4331" CreationDate="2021-02-15T03:09:49.280" Score="1" Body="&lt;p&gt;I can't understand what your logic is. The geometry optimization will use uniform k-mesh and the band calculation with SOC will use in general use the line-mode to plot the eigenvalue along the assigned k-path.&lt;/p&gt;&#xA;&lt;p&gt;Due to the band calculation is a post-process, you of course can use a denser uniform k-mesh to plot smooth 3D band structure based on your previous converged self-consistent calculation with a suitable uniform k-mesh. Are you asking this?&lt;/p&gt;&#xA;&lt;p&gt;Maybe you should link a paper to explain in detail your question.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-15T03:09:49.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4345" PostTypeId="1" AcceptedAnswerId="4348" CreationDate="2021-02-15T17:21:50.910" Score="8" ViewCount="636" Body="&lt;p&gt;I'm new to gaussian16. The wave function file that I obtain as a result of the &amp;quot;Energy&amp;quot; calculation. It consists of five distinct parts :&lt;/p&gt;&#xA;&lt;p&gt;PART 1 :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Title Card Required&#xA;GAUSSIAN            324 MOL ORBITALS   2708 PRIMITIVES       97 NUCLEI&#xA;  Si   1    (CENTRE  1)   6.86295613  0.23147639  5.47001264  CHARGE = 14.0&#xA;  Si   2    (CENTRE  2)   5.29993719 -3.72919681  6.83173983  CHARGE = 14.0&#xA;  H    3    (CENTRE  3)   5.41343792 -3.79385190  9.68076275  CHARGE =  1.0&#xA;  Si   4    (CENTRE  4)   4.46330820  3.56746473  7.22907743  CHARGE = 14.0&#xA;  H    5    (CENTRE  5)   4.58878035  3.34950371 10.06998397  CHARGE =  1.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PART 2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CENTRE ASSIGNMENTS    1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1&#xA;CENTRE ASSIGNMENTS    1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1&#xA;CENTRE ASSIGNMENTS    1  1  1  1  1  1  1  1  1  1  2  2  2  2  2  2  2  2  2  2&#xA;CENTRE ASSIGNMENTS    2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2&#xA;CENTRE ASSIGNMENTS    2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PART 3:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TYPE ASSIGNMENTS      1  1  1  1  1  1  1  1  1  1  1  1  1  1  2  3  4  2  2  2&#xA;TYPE ASSIGNMENTS      2  3  3  3  3  4  4  4  4  2  2  3  3  4  4  2  3  4  2  3&#xA;TYPE ASSIGNMENTS      4  2  3  4  5  6  7  8  9 10  1  1  1  1  1  1  1  1  1  1&#xA;TYPE ASSIGNMENTS      1  1  1  1  2  3  4  2  2  2  2  3  3  3  3  4  4  4  4  2&#xA;TYPE ASSIGNMENTS      2  3  3  4  4  2  3  4  2  3  4  2  3  4  5  6  7  8  9 10&#xA;TYPE ASSIGNMENTS      1  1  1  1  1  2  3  4  1  1  1  1  1  1  1  1  1  1  1  1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PART 4 :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EXPONENTS  0.6937923D+05 0.1035494D+05 0.2333880D+04 0.6571430D+03 0.2143011D+03&#xA;EXPONENTS  0.7762917D+02 0.7762917D+02 0.3063081D+02 0.1280129D+02 0.3926866D+01&#xA;EXPONENTS  0.1452343D+01 0.2562340D+00 0.9427900D-01 0.3310000D-01 0.3310000D-01&#xA;EXPONENTS  0.3310000D-01 0.3310000D-01 0.3354832D+03 0.7890037D+02 0.2498815D+02&#xA;EXPONENTS  0.9219711D+01 0.3354832D+03 0.7890037D+02 0.2498815D+02 0.9219711D+01&#xA;EXPONENTS  0.3354832D+03 0.7890037D+02 0.2498815D+02 0.9219711D+01 0.3621140D+01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PART 5 :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MO    1     MO 0.0        OCC NO =    2.0000000  ORB. ENERGY =  -88.045000&#xA;  0.54292513D-06  0.10216068D-05  0.17513525D-05  0.27212108D-05  0.36356801D-05&#xA;  0.24347030D-05 -0.36986557D-05 -0.64984769D-05 -0.13323768D-05  0.15180200D-04&#xA; -0.19600424D-04  0.13064999D-04 -0.44728852D-04  0.43896804D-03 -0.12159648D-03&#xA; -0.10705784D-04 -0.73420297D-04  0.15345865D-03  0.19361470D-03  0.19596257D-03&#xA;  0.14179220D-03  0.17721962D-04  0.22359327D-04  0.22630469D-04  0.16374677D-04&#xA; -0.49212505D-05 -0.62090107D-05 -0.62843046D-05 -0.45471200D-05 -0.12107196D-03&#xA; -0.27352130D-04 -0.13919488D-04 -0.31446392D-05  0.26955651D-05  0.60897211D-06&#xA;  0.70506239D-04  0.81202401D-05 -0.22236135D-05 -0.45223544D-04 -0.55646122D-05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there any resource on how to interpret the quantities in each part?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2021-02-15T17:34:06.497" LastActivityDate="2023-07-10T14:43:13.110" Title="How do I interpret the Gaussian16 wavefunction file?" Tags="|gaussian|orbitals|wavefunctions|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4346" PostTypeId="1" CreationDate="2021-02-15T17:32:29.920" Score="6" ViewCount="69" Body="&lt;p&gt;How can density of state effective mass and transport effective mass can be defined to calculate conductivity for a cubic system with parabolic but anisotropic dispersion relation? What will be the value of both for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-09-05T23:05:19.547" LastActivityDate="2021-09-05T23:05:19.547" Title="Value of density of state effective mass and transport effective mass to calculate conductivity" Tags="|condensed-matter|physical-properties-of-materials|transport|" AnswerCount="0" CommentCount="6" ClosedDate="2021-09-07T03:06:23.393" ContentLicense="CC BY-SA 4.0" />
  <row Id="4347" PostTypeId="2" ParentId="4341" CreationDate="2021-02-15T20:07:56.273" Score="5" Body="&lt;p&gt;You might want to have a look at &lt;a href=&quot;https://pypi.org/project/acpype/&quot; rel=&quot;noreferrer&quot;&gt;acpype&lt;/a&gt; which is compatible with GAFF and AMBER-based force fields and probably others.&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2021-02-15T20:07:56.273" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4348" PostTypeId="2" ParentId="4345" CreationDate="2021-02-15T21:15:54.767" Score="9" Body="&lt;p&gt;I have yet to find a source that lays this out explicitly, but from the examples I could find, it is not too hard to infer the meaning of these sections.&lt;/p&gt;&#xA;&lt;p&gt;To start with (and possibly point you in the right direction to look for more information), this type of *.wfn file was developed as the input format for &lt;a href=&quot;https://www.chemistry.mcmaster.ca/aimpac/imagemap/imagemap.htm&quot; rel=&quot;noreferrer&quot;&gt;AIMPAC&lt;/a&gt; and quickly spread to be used as an output format for a number of electronic structure programs (e.g. Gaussian, Q-Chem, GAMESS) and an input format for wavefunction analysis (e.g. Multiwfn). So this format isn't particular to Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;To give another/smaller example to work from, I'll pull sections from a wavefunction file I found with a &lt;a href=&quot;https://github.com/ecbrown/aimpac/blob/master/hco2.wfn&quot; rel=&quot;noreferrer&quot;&gt;fork of AIMPAC&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Section 1&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;Formate anion 6-31++G**                                                         &#xA;GAUSSIAN             12 MOL ORBITALS    104 PRIMITIVES        4 NUCLEI&#xA;  C    1    (CENTRE  1)   0.00000000  0.00000000  0.57942804  CHARGE =  6.0&#xA;  O    2    (CENTRE  2)   0.00000000  2.11695431 -0.38686460  CHARGE =  8.0&#xA;  O    3    (CENTRE  3)   0.00000000 -2.11695431 -0.38686460  CHARGE =  8.0&#xA;  H    4    (CENTRE  4)   0.00000000  0.00000000  2.71326541  CHARGE =  1.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first line is a title card and just below that I believe it records that the orbitals discussed below are Gaussian type, not that the data was produced by Gaussian.&#xA;The rest of the line tells you the number of molecular orbitals, the number of primitive Gaussian basis function, and the number of nuclei in your molecule. The follow lines give the element symbol, a number label for each center, their (presumably) Cartesian coordinates, and the charge of the nuclei.&lt;/p&gt;&#xA;&lt;h3&gt;Section 2&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;CENTRE ASSIGNMENTS    1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1&#xA;CENTRE ASSIGNMENTS    1  1  1  1  1  1  1  1  1  1  1  1  2  2  2  2  2  2  2  2&#xA;CENTRE ASSIGNMENTS    2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2  2&#xA;CENTRE ASSIGNMENTS    2  2  2  2  3  3  3  3  3  3  3  3  3  3  3  3  3  3  3  3&#xA;CENTRE ASSIGNMENTS    3  3  3  3  3  3  3  3  3  3  3  3  3  3  3  3  4  4  4  4&#xA;CENTRE ASSIGNMENTS    4  4  4  4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The previous section mentioned the number of primitives (104). This section tells you which center each of these primitives belongs to. For example, the eight &amp;quot;4&amp;quot; at the end tell you there are 8 primitives associated with the 4th center (H).&lt;/p&gt;&#xA;&lt;h3&gt;Section 3&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;TYPE ASSIGNMENTS      1  1  1  1  1  1  1  1  1  2  2  2  3  3  3  4  4  4  1  2&#xA;TYPE ASSIGNMENTS      3  4  1  2  3  4  5  6  7  8  9 10  1  1  1  1  1  1  1  1&#xA;TYPE ASSIGNMENTS      1  2  2  2  3  3  3  4  4  4  1  2  3  4  1  2  3  4  5  6&#xA;TYPE ASSIGNMENTS      7  8  9 10  1  1  1  1  1  1  1  1  1  2  2  2  3  3  3  4&#xA;TYPE ASSIGNMENTS      4  4  1  2  3  4  1  2  3  4  5  6  7  8  9 10  1  1  1  1&#xA;TYPE ASSIGNMENTS      1  2  3  4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now that we know to which centers the primitives belong, we need to know what type of Gaussian these are (e.g. &lt;span class=&quot;math-container&quot;&gt;$\mathrm{s, p_x, p_y, p_z, d_{xx}, d_{xy}}$&lt;/span&gt;, etc). I don't know the exact correspondence, but it seems to be&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathrm{s}=1$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathrm{p}=2-4$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathrm{d}=5-10$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the *.wfx format (based on *.wfn, see below), I can confirm that&#xA;1=S, 2=PX, 3=PY, 4=PZ, 5=DXX, 6=DYY, 7=DZZ, 8=DXY, 9=DXZ, 10=DYZ, where the format seems to assume Cartesian rather than spherical Gaussians.&lt;/p&gt;&#xA;&lt;h3&gt;Section 4&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;EXPONENTS  0.3047525E+04 0.4573695E+03 0.1039487E+03 0.2921016E+02 0.9286663E+01&#xA;EXPONENTS  0.3163927E+01 0.7868272E+01 0.1881289E+01 0.5442493E+00 0.7868272E+01&#xA;EXPONENTS  0.1881289E+01 0.5442493E+00 0.7868272E+01 0.1881289E+01 0.5442493E+00&#xA;EXPONENTS  0.7868272E+01 0.1881289E+01 0.5442493E+00 0.1687145E+00 0.1687145E+00&#xA;EXPONENTS  0.1687145E+00 0.1687145E+00 0.4380000E-01 0.4380000E-01 0.4380000E-01&#xA;EXPONENTS  0.4380000E-01 0.8000000E+00 0.8000000E+00 0.8000000E+00 0.8000000E+00&#xA;EXPONENTS  0.8000000E+00 0.8000000E+00 0.5484672E+04 0.8252349E+03 0.1880470E+03&#xA;EXPONENTS  0.5296450E+02 0.1689757E+02 0.5799635E+01 0.1553962E+02 0.3599934E+01&#xA;EXPONENTS  0.1013762E+01 0.1553962E+02 0.3599934E+01 0.1013762E+01 0.1553962E+02&#xA;EXPONENTS  0.3599934E+01 0.1013762E+01 0.1553962E+02 0.3599934E+01 0.1013762E+01&#xA;EXPONENTS  0.2700058E+00 0.2700058E+00 0.2700058E+00 0.2700058E+00 0.8450000E-01&#xA;EXPONENTS  0.8450000E-01 0.8450000E-01 0.8450000E-01 0.8000000E+00 0.8000000E+00&#xA;EXPONENTS  0.8000000E+00 0.8000000E+00 0.8000000E+00 0.8000000E+00 0.5484672E+04&#xA;EXPONENTS  0.8252349E+03 0.1880470E+03 0.5296450E+02 0.1689757E+02 0.5799635E+01&#xA;EXPONENTS  0.1553962E+02 0.3599934E+01 0.1013762E+01 0.1553962E+02 0.3599934E+01&#xA;EXPONENTS  0.1013762E+01 0.1553962E+02 0.3599934E+01 0.1013762E+01 0.1553962E+02&#xA;EXPONENTS  0.3599934E+01 0.1013762E+01 0.2700058E+00 0.2700058E+00 0.2700058E+00&#xA;EXPONENTS  0.2700058E+00 0.8450000E-01 0.8450000E-01 0.8450000E-01 0.8450000E-01&#xA;EXPONENTS  0.8000000E+00 0.8000000E+00 0.8000000E+00 0.8000000E+00 0.8000000E+00&#xA;EXPONENTS  0.8000000E+00 0.1873114E+02 0.2825394E+01 0.6401217E+00 0.1612778E+00&#xA;EXPONENTS  0.3600000E-01 0.1100000E+01 0.1100000E+01 0.1100000E+01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This section now tells us what the orbital exponent is for each of these primitives. You can verify this by looking on the basis set exchange to see what the exponents are for &lt;a href=&quot;https://www.basissetexchange.org/basis/6-31%2B%2Bg_st__st_/format/gaussian94/?version=1&amp;amp;elements=1,6,8&quot; rel=&quot;noreferrer&quot;&gt;6-31++G**&lt;/a&gt; for H, C, and O. Gaussian format has the exponent of each primitive in the first column (note that 6-31g and related basis sets are sometimes written with the label 'SP', which just means you have s and 3 p primitives that all have the same exponent).&lt;/p&gt;&#xA;&lt;h3&gt;Section 5&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;MO  1       MO  0.        OCC NO =    2.0000000  ORB. ENERGY = -20.2999736&#xA; -0.12188442E-13 -0.22485295E-13 -0.36298238E-13 -0.47249521E-13 -0.40318102E-13&#xA; -0.13920872E-13 -0.41960794E-12 -0.19339692E-12  0.54230514E-12 -0.39273770E-15&#xA; -0.30112636E-15 -0.15028316E-15  0.29917662E-03  0.22938966E-03  0.11448152E-03&#xA; -0.63478413E-13 -0.48671221E-13 -0.24290350E-13  0.22529127E-12  0.13071387E-15&#xA;  0.10185809E-03 -0.62728986E-13  0.10023463E-12 -0.29802626E-16  0.15830967E-04&#xA; -0.98332270E-14 -0.24693743E-12 -0.14752123E-11 -0.25765489E-12  0.18297189E-14&#xA; -0.66615675E-15  0.54705851E-03  0.58494882E+00  0.10766181E+01  0.17421713E+01&#xA;  0.22901329E+01  0.19642337E+01  0.67160487E+00 -0.91594649E-02 -0.40869354E-02&#xA;  0.12068775E-01  0.13518265E-14  0.10415094E-14  0.45727874E-15 -0.28829800E-02&#xA; -0.22211807E-02 -0.97521795E-03  0.12404677E-02  0.95571350E-03  0.41960970E-03&#xA;  0.87774840E-03 -0.32212280E-15  0.15512643E-03 -0.10153969E-03 -0.16545660E-03&#xA;  0.61506469E-16 -0.37903054E-05 -0.37038128E-05 -0.33187344E-02 -0.31410279E-02&#xA; -0.33038069E-02  0.74824127E-15 -0.24267011E-15  0.10744751E-03 -0.58494882E+00&#xA; -0.10766181E+01 -0.17421713E+01 -0.22901329E+01 -0.19642337E+01 -0.67160487E+00&#xA;  0.91594649E-02  0.40869354E-02 -0.12068775E-01  0.12737899E-14  0.98138644E-15&#xA;  0.43088151E-15 -0.28829800E-02 -0.22211807E-02 -0.97521795E-03 -0.12404677E-02&#xA; -0.95571350E-03 -0.41960970E-03 -0.87774839E-03 -0.13253444E-15  0.15512643E-03&#xA;  0.10153969E-03  0.16545660E-03  0.23148336E-16 -0.37903054E-05  0.37038128E-05&#xA;  0.33187344E-02  0.31410279E-02  0.33038069E-02 -0.14848270E-16 -0.68315079E-15&#xA;  0.10744751E-03 -0.34702469E-13 -0.58861956E-13 -0.67012256E-13  0.22566017E-13&#xA; -0.31113147E-14  0.92067613E-15 -0.20220193E-03  0.19169822E-12&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Finally, we have the specification for the MOs; here I just list the first one, but there should be 12 in total to specify all 12 Molecular Orbitals. These specifications list the occupation number and orbital energy, as well as the MO coefficients which tell you how to form the MOs from the primitives.&lt;/p&gt;&#xA;&lt;p&gt;As you have already seen, this format is a little terse and it can be somewhat unclear what the sections mean at a glance. Gaussian can also produce a newer version in the &lt;a href=&quot;http://aim.tkgristmill.com/wfxformat.html&quot; rel=&quot;noreferrer&quot;&gt;*.wfx format&lt;/a&gt;, which labels each section with a little tag and can be extended to include additional wavefunction features.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-02-16T18:53:52.410" LastActivityDate="2021-02-16T18:53:52.410" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4349" PostTypeId="1" CreationDate="2021-02-15T22:53:32.777" Score="10" ViewCount="99" Body="&lt;p&gt;Is it possible to read a complex potential into CP2K? I have generated a potential using FDTD at a given frequency, which results in a complex result. The potential is to be read in to a real time propagation method as a static background potential.&lt;/p&gt;&#xA;" OwnerUserId="1451" LastEditorUserId="5" LastEditDate="2021-02-28T00:18:01.793" LastActivityDate="2021-04-25T00:34:29.483" Title="Reading complex potential into CP2K" Tags="|td-dft|cp2k|interatomic-potentials|software-input-file-request|finite-difference-time-domain|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4350" PostTypeId="1" CreationDate="2021-02-16T02:01:35.590" Score="-4" ViewCount="131" Body="&lt;p&gt;I read that brittle materials tend to have an observed strength much less than its theoretical strength because they tend to have surface cracks and whatever tension is applied gets greatly magnified at the tip of the crack. I once saw a web page that said it was predicted that glass has a theoretical strength of 31 GPa.&lt;/p&gt;&#xA;&lt;p&gt;Apparently, people seem to think only nanotubes can be made strong enough for a space elevator and graphite can't. More details can be seen in this question's edit history, but what I wonder is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Has there been research on improving the strength of graphene-based materials?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="5" LastEditDate="2021-02-16T21:08:51.780" LastActivityDate="2021-02-19T02:15:36.803" Title="Has there been research on improving the strength of graphene-based materials?" Tags="|physical-properties-of-materials|materials-engineering|mechanical-properties|graphene|nanostructures|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4351" PostTypeId="2" ParentId="4319" CreationDate="2021-02-16T06:53:25.147" Score="7" Body="&lt;p&gt;All files are always created in the run directory where ORCA runs.&#xA;I specifically did not want to deal with environment variables and path names and all that.&#xA;Hope that helps!&#xA;best wishes,&#xA;Frank Neese&lt;/p&gt;&#xA;" OwnerUserId="2083" LastEditorUserId="5" LastEditDate="2021-02-16T15:25:53.447" LastActivityDate="2021-02-16T15:25:53.447" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4352" PostTypeId="1" CreationDate="2021-02-16T08:25:37.567" Score="5" ViewCount="545" Body="&lt;p&gt;This a follow-up question to my previous &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4345/how-do-i-interpret-the-gaussian16-wavefunction-file&quot;&gt;question&lt;/a&gt;. And as per the answer one could create M.O orbitals from the primitives.&lt;/p&gt;&#xA;&lt;p&gt;As a new user of Gaussian, &lt;strong&gt;is there any method (or algorithm) to followed so as to create the MO's from the wave function file?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;NOTE : I wanted to obtain the wave function for doing further calculations with it. Hence I'm not looking for a visualization software.&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2021-09-05T23:07:25.020" LastActivityDate="2021-09-05T23:07:25.020" Title="How can I calculate and plot the molecular orbitals (MO's) from the Gaussian wavefunction file?" Tags="|density-functional-theory|gaussian|orbitals|wavefunctions|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-29T17:21:04.957" ContentLicense="CC BY-SA 4.0" />
  <row Id="4353" PostTypeId="1" AcceptedAnswerId="4358" CreationDate="2021-02-16T12:18:11.253" Score="6" ViewCount="470" Body="&lt;p&gt;I am using VASP to calculate material properties. I want to know how to extract the lattice parameters from my cells automatically with a script. I know about the method with VESTA (described here &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1808/how-to-extract-lattice-constants-a-and-c-from-relaxed-hexagonal-structure-using&quot;&gt;How to extract lattice constants a and c from relaxed hexagonal structure using VASP?&lt;/a&gt;), but doing this manually for every composition takes way too much time.&lt;/p&gt;&#xA;&lt;p&gt;Since I am familiar with &lt;code&gt;bash&lt;/code&gt; from running my calculations I would like to use a &lt;code&gt;bash&lt;/code&gt;-script that calculates a, b, c, α, β, and γ from the relaxed CONTCAR file that I can loop over my directories. Is this possible to do in &lt;code&gt;bash&lt;/code&gt; or do I need to resort to &lt;code&gt;python&lt;/code&gt; or something similar?&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;as requested, an example would be this CONTCAR file. Since there are 64 individual atoms and the the relevant lines are 2-5 in all cases, I am omitting the lines at the bottom. This is a supercell, which means the lattice parameters are multiplied, but the script should not need to address that.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2x2x2 supercell ternary nitride         &#xA;1.00000000000000     &#xA; 8.3651760123584129    0.0104817210801190   -0.0093895223039569&#xA; 0.0104823789019837    8.3504089378499629   -0.0085602185310777&#xA;-0.0093916727121912   -0.0085617113679278    8.3470735253222390&#xA;Al   Ti   N &#xA;16    16    32&#xA;Direct&#xA;0.0003223292397248  0.9972239351012413  0.0011915008883630&#xA;0.4991700057920037  0.9984995833496634  0.5000934141482651&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A preferred output for this cell would then be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 8.36519 8.35042 8.34708 90.1176 90.1289 89.8562&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;for a, b, c, α, β, and γ. Separation by tabs, commas, or semicolons would also be acceptable.&lt;/p&gt;&#xA;" OwnerUserId="2084" LastEditorUserId="2084" LastEditDate="2021-02-17T09:00:42.033" LastActivityDate="2021-02-17T13:42:08.097" Title="Bash script to extract lattice parameters from CONTCAR" Tags="|density-functional-theory|vasp|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4354" PostTypeId="2" ParentId="4336" CreationDate="2021-02-16T15:51:01.160" Score="6" Body="&lt;p&gt;I assume that:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You really care about is how to calculate the MBJ band structure of monolayer WS2.&lt;/li&gt;&#xA;&lt;li&gt;You can follow the linked answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1997/mbj-lda-band-structure-calculation-using-vasp&quot;&gt;mBJ-LDA band structure calculation using VASP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For monolayer, it is very hard/tricky to converge at MBJ self-consistent calculation. Usually, one possible way is you can obtain the CMBJ=XXX from its bulk counterpart.&lt;/p&gt;&#xA;&lt;p&gt;I have tried this but get unsatisfactory result:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Bulk WS2 (SOC is ignored!):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE band:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/oQmHx.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oQmHx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;MBJ band:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/hafSh.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hafSh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep CMBJ OUTCAR ====&amp;gt; CMBJ=1.2327&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Monolayer WS2:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE result:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/yTjls.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yTjls.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;MBJ result:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/tHkLW.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tHkLW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;INCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt; ### Read PBE wavefunction&#xA; ISTART=1&#xA; ICHARG=0&#xA; ENCUT=400&#xA; EDIFF=1E-6&#xA; NELM=300&#xA; ISMEAR=-5&#xA;&#xA; ###MBJ:&#xA; METAGGA=MBJ&#xA; LASPH=.TRUE.&#xA; LMAXMIX=4&#xA; GGA=CA&#xA; CMBJ=1.2327&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This unsatisfactory result may be related to the badly converged MBJ self-consistent calculation. Unfortunately, I haven't found any solutions for this (still trying...).&lt;/p&gt;&#xA;&lt;p&gt;By the way, the system contains only three atoms, why not using the HSE06 method?&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-16T15:51:01.160" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4355" PostTypeId="1" AcceptedAnswerId="4359" CreationDate="2021-02-16T19:35:20.537" Score="2" ViewCount="144" Body="&lt;p&gt;According to &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0925963500004568#:%7E:text=A%20new%20carbon%20modification%20having,a%20metallic%20form%20of%20&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, carbon has a face centered cubic phase which is a metallic form. My question is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Has it been researched whether face centered cubic carbon is stable?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Reasons why I'm interested in this question can be found in the edit history of this post.&lt;/p&gt;&#xA;" OwnerUserId="1014" LastEditorUserId="5" LastEditDate="2021-02-16T20:58:05.390" LastActivityDate="2021-03-05T23:46:10.780" Title="Has it been researched whether face centered cubic carbon is stable?" Tags="|physical-properties-of-materials|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4356" PostTypeId="1" AcceptedAnswerId="8561" CreationDate="2021-02-16T21:48:48.460" Score="9" ViewCount="1003" Body="&lt;p&gt;Since I have started working on &lt;em&gt;&lt;strong&gt;monolayers&lt;/strong&gt;&lt;/em&gt; I was using the &lt;code&gt;ISIF=3&lt;/code&gt; tag for relaxation, this was after recompiling VASP with the modified &amp;quot;&lt;code&gt;constr_cell_relax.F&lt;/code&gt;&amp;quot; file. There was no problem in relaxing pure materials, but with the doping of 4x4x1 supercells I don't get convergence in relaxation and the calculations are taking too too much time.&#xA;On the other hand my friend is using the tag &lt;code&gt;ISIF=4&lt;/code&gt; and he is getting always converged results.&lt;/p&gt;&#xA;&lt;p&gt;Now I am a little bit confused with which tag should be used, since I think that &lt;em&gt;&lt;strong&gt;because of vacuum along the c axis there should be no relaxation along it&lt;/strong&gt;&lt;/em&gt;, so &lt;code&gt;ISIF=4&lt;/code&gt; tag shouldn't be used. I want to know your opinions, especially if you have worked on relaxing doped monolayers.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-09-05T23:11:33.453" LastActivityDate="2022-01-14T08:08:07.990" Title="In VASP, which option is better for monolayer relaxation: ISIF=3 or ISIF=4?" Tags="|density-functional-theory|vasp|cell-optimization|monolayer|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4357" PostTypeId="2" ParentId="4353" CreationDate="2021-02-17T04:29:07.527" Score="6" Body="&lt;p&gt;Of course, you can use python. For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;CONTCAR template:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GeTe&#xA;1.00000000000000&#xA;4.2642961037835692   -0.0182827012387123   -0.0127716218381237&#xA;2.2215279123437899    3.6399683038796313   -0.0127716218406244&#xA;2.2215279123442269    1.2405016904345516    3.4220882400997064&#xA;Ge   Te&#xA;1     1&#xA;Direct&#xA;-0.0008620876194062 -0.0008620876194055 -0.0008620876194060&#xA; 0.5218621726194035  0.5218621076194079  0.5218621136194089&#xA;&#xA; 0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA; 0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Lattice parameters from VESTA:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a =  4.26435 Å      α = 58.8490° &#xA;b =  4.26435 Å      β = 58.8490°&#xA;c =  4.26435 Å      γ = 58.8490°&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Python script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;with open(&amp;quot;CONTCAR&amp;quot;,&amp;quot;r&amp;quot;) as f:&#xA;    lines=f.readlines()&#xA;&#xA;lat_mat=np.zeros((3,3))&#xA;for i in range(3):&#xA;    lat_mat[i,:]=list(map(float,lines[2+i].strip().split()))&#xA;&#xA;a=np.sqrt(np.sum(lat_mat[0,:]**2))&#xA;b=np.sqrt(np.sum(lat_mat[1,:]**2))&#xA;c=np.sqrt(np.sum(lat_mat[2,:]**2))&#xA;print(a,b,c)&#xA;&#xA;alpha = np.arccos(np.dot(lat_mat[1,:],lat_mat[2,:])/b/c)*360/2/np.pi&#xA;beta  = np.arccos(np.dot(lat_mat[0,:],lat_mat[2,:])/a/c)*360/2/np.pi&#xA;gamma = np.arccos(np.dot(lat_mat[0,:],lat_mat[1,:])/a/b)*360/2/np.pi&#xA;print(alpha,beta,gamma)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Python output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4.26435442150775   4.264354421585447  4.264354421518477&#xA;&#xA;58.84900754415152  58.84900754404418  58.849007544603154&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You may realize this with a bash script. Also, the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;atomic simulation environment (ASE)&lt;/a&gt; can do this.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-17T10:39:51.983" LastActivityDate="2021-02-17T10:39:51.983" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4358" PostTypeId="2" ParentId="4353" CreationDate="2021-02-17T13:42:08.097" Score="9" Body="&lt;p&gt;I'd recommend &lt;a href=&quot;https://gitlab.com/ase/ase&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;, a ready solution not to re-invent the wheel and ensure all the boundary cases are properly handled. Also this code will be easier to maintain in future:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import sys&#xA;&#xA;from ase.io.vasp import read_vasp&#xA;from ase.geometry import cell_to_cellpar&#xA;&#xA;&#xA;try:&#xA;    ase_obj = read_vasp(sys.argv[1])&#xA;except IndexError:&#xA;    sys.exit('A CIF path must be given!')&#xA;&#xA;print(&amp;quot;%.5f %.5f %.5f %.4f %.4f %.4f&amp;quot; % tuple(&#xA;    cell_to_cellpar(ase_obj.cell)&#xA;))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you want to extract rather the conventional cell, not primitive, try to apply &lt;a href=&quot;https://github.com/spglib/spglib&quot; rel=&quot;noreferrer&quot;&gt;spglib&lt;/a&gt; in between:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import sys&#xA;&#xA;from ase.io.vasp import read_vasp&#xA;from ase import Atoms&#xA;from ase.geometry import cell_to_cellpar&#xA;import spglib&#xA;&#xA;&#xA;try:&#xA;    ase_obj = read_vasp(sys.argv[1])&#xA;except IndexError:&#xA;    sys.exit('A CIF path must be given!')&#xA;&#xA;cell, scaled_pos, numbers = spglib.standardize_cell(ase_obj, to_primitive=False)&#xA;&#xA;ase_obj = Atoms(&#xA;    scaled_positions=scaled_pos,&#xA;    numbers=numbers,&#xA;    cell=cell,&#xA;    pbc=True&#xA;)&#xA;print(&amp;quot;%.5f %.5f %.5f %.4f %.4f %.4f&amp;quot; % tuple(&#xA;    cell_to_cellpar(ase_obj.cell)&#xA;))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1750" LastActivityDate="2021-02-17T13:42:08.097" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4359" PostTypeId="2" ParentId="4355" CreationDate="2021-02-17T15:20:19.590" Score="6" Body="&lt;p&gt;One of the papers citing the paper you linked is &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0008622304000545&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper &lt;/a&gt;: G. Murrieta, A. Tapia, and R. de Coss, Structural stability of carbon in the face-centered-cubic (Fm&lt;span class=&quot;math-container&quot;&gt;$\bar{3}$&lt;/span&gt;m) phase, Carbon &lt;strong&gt;4&lt;/strong&gt;, 771-774 (2004). It concludes with:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In order to evaluate the structural stability of the fcc&#xA;phase of carbon, we have calculated the total energy as a function of the isotropic, tetragonal, and trigonal&#xA;deformations for bulk fcc carbon using the full-potential&#xA;LAPW method. We find that the total energy shows a&#xA;minimum for the isotropic deformation, but exhibits&#xA;maxima for the tetragonal and trigonal deformations.&#xA;This means that the bulk fcc structure is not a true&#xA;metastable phase of carbon. It is likely that the interaction with the substrate and impurities contribute to&#xA;stabilize the fcc structure in the existing fcc carbon thin&#xA;films on diamond. However, the exact nature of these&#xA;interactions remains unknown.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you're interested, I would recommend further exploring the citation tree. There seems to be other studies addressing the structure and stability also from an experimental perspective.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="5" LastEditDate="2021-02-17T18:41:40.803" LastActivityDate="2021-02-17T18:41:40.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4360" PostTypeId="1" CreationDate="2021-02-17T22:06:53.460" Score="10" ViewCount="886" Body="&lt;p&gt;I am studying the magnetic properties of bulk ZnO, so I am doping it with transition metal elements in order to observe the magnetic spectrum. I replace a Zn atom with a transition metal element at different positions (first nearest neighbor, second nearest neighbor ...) at different concentrations. So the distance between atoms is very important in this study.&#xA;The problem is I don't know how to relax my structure because after the &lt;code&gt;vc-relax&lt;/code&gt; calculation all the atoms change the position and the transition element which I consider as the second-neighbor becomes the first-neighbor!  I don't know exactly how can I optimize my structure?&lt;/p&gt;&#xA;&lt;p&gt;In the attachment below, the Vanadium atom is chosen to be the second neighbor of the other vanadium atom (here I have dopped with two vanadium atoms) but after the vc-relax the position changes in a way that it becomes the first nearest neighbor!&#xA;Does the optimization of cell parameters (i.e running test convergence on a and c parameters) is enough even if it is a supercell?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EDa0o.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EDa0o.png&quot; alt=&quot;Doped Zinc oxide&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2092" LastEditorUserId="7" LastEditDate="2021-02-18T16:25:08.560" LastActivityDate="2021-02-22T23:12:19.970" Title="Can I do a &quot;constrained&quot; geometry optimization in Quantum ESPRESSO, such that certain dopants appear in certain positions even after relaxation?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|geometry-optimization|structure|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4361" PostTypeId="1" AcceptedAnswerId="8652" CreationDate="2021-02-18T13:11:50.583" Score="7" ViewCount="242" Body="&lt;p&gt;I'm trying to calculate the stability of the product of a &lt;a href=&quot;https://en.wikipedia.org/wiki/Coordinate_covalent_bond&quot; rel=&quot;nofollow noreferrer&quot;&gt;coordinate bonding&lt;/a&gt; process of molecules A and B in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Polarizable_continuum_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;polarizable continuum solvent model&lt;/a&gt; (PCM, solvent set to water).&lt;br/&gt;&#xA;I'm getting energies that (at first sight) don't agree with experiment, so I'd like to check things with the readers here to make sure I didn't make any obvious mistakes.&lt;/p&gt;&#xA;&lt;p&gt;In the molecular process, a part of A is removed (say A - A1 → A0) before having B bind to what remains (A0) where the fragment A1 was removed.  Let's call the final supermolecule C.&lt;br/&gt;&#xA;The fragments A1 (once removed) and B belong to an ambient &amp;quot;reservoir&amp;quot; -- we assume no interaction between them.&lt;/p&gt;&#xA;&lt;p&gt;I understood this to mean that I only need to calculate the changes of energy through two reactions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A → A0 + A1&lt;/li&gt;&#xA;&lt;li&gt;A0 + B → C&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here are the specifics of the calculations I did.&#xA;I used Gaussian 16 for DFT with the settings &lt;code&gt;PBE-D3(BJ)/Def2SVP&lt;/code&gt; and &lt;code&gt;SCRF(PCM)&lt;/code&gt; to optimize the geometries of A, A0, A1, B, and C, all separately.&lt;/p&gt;&#xA;&lt;p&gt;Next, I defined the fragments A={A0, A1} and C={A0, B} to additionally calculate the counterpoise corrections for &lt;a href=&quot;https://en.wikipedia.org/wiki/Basis_set_superposition_error&quot; rel=&quot;nofollow noreferrer&quot;&gt;BSSE&lt;/a&gt;.&#xA;Since &lt;code&gt;counterpoise&lt;/code&gt; and &lt;code&gt;SCRF&lt;/code&gt; can't go together (at least in g16), I calculated the corrections (single-point, no further optimization) using only the geometries of A and C that were optimized from the last step while &lt;strong&gt;not&lt;/strong&gt; using the &lt;code&gt;SCRF(PCM)&lt;/code&gt; command in this step.&lt;/p&gt;&#xA;&lt;p&gt;After all this, the relative energies came out as&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A + (192.5 kJ/mol) → A0 + A1&lt;/li&gt;&#xA;&lt;li&gt;A0 + B → C + (162.1 kJ/mol)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;which seem to mean that A is 30.4 kJ/mol more stable than C.&lt;/p&gt;&#xA;&lt;p&gt;But my experiment somehow suggests that it favors the formation of C after having started from A.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;So before I go into theorizing about any intermediate processes that I may have overlooked, can anyone point out any obvious mistake (either with concepts or software) that I may have made?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance-&lt;/p&gt;&#xA;" OwnerUserId="1363" LastEditorUserId="5" LastEditDate="2021-09-05T23:13:02.627" LastActivityDate="2022-02-06T04:33:09.720" Title="Two-stage unbinding &amp; binding energies with DFT" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|gaussian|implicit-solvent|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4362" PostTypeId="1" AcceptedAnswerId="4364" CreationDate="2021-02-18T15:52:30.423" Score="9" ViewCount="281" Body="&lt;p&gt;I am trying to calculate normal modes frequency matrix using HESSIAN calculation in GAMESS. Since we know that number of normal modes for a non-linear molecule is 3N-5 where N is the number of atoms. So the expected size of the normal modes matrix is 3N x (3N-5). However, the normal mode matrix obtained from GAMESS output is of the size 3N x 3N. My suspicion is that the extra 5 modes are irrelevant. Could you help in eliminating the irrelevant modes present in the normal modes matrix?&lt;/p&gt;&#xA;" OwnerUserId="2095" LastEditorUserId="5" LastEditDate="2021-02-18T20:32:20.960" LastActivityDate="2021-02-18T20:32:20.960" Title="Mismatched number of normal modes calculation in GAMESS" Tags="|vibrations|gamess|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4363" PostTypeId="1" AcceptedAnswerId="4367" CreationDate="2021-02-18T16:01:34.573" Score="6" ViewCount="906" Body="&lt;p&gt;Currently I met a problem when I calculate the surface state of a topologically non-trivial thin film system. I did a DFT calculation and fit the result with wannier function. The fitting looks pretty good around the band gap region. Then I use tight binding to calculate the surface state. I found that the band structure along -X -&amp;gt; G -&amp;gt; X  didn't preserve the time reversal symmetry (E(k) is not equal to E(-k) and it become a trivial edge state. For a system without magnetisation and external B-field, the time reversal symmetry can be preserved. So the relation of E(k) = E(-k) should be always true? I can't find any reason for my result. Is there any people who did similar things before and have some suggestion ?&lt;/p&gt;&#xA;&lt;p&gt;For the band gap region:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7l9GPl.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7l9GPl.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The surface state was shown in below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/W4K9A.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/W4K9A.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;For the notation of R in the surface state plot, it is -X. So it is the plot from -X -&amp;gt; G -&amp;gt; X. and it didn't contain the time reversal symmetry.&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="621" LastEditDate="2021-02-19T09:48:46.317" LastActivityDate="2023-05-13T13:13:28.563" Title="Calculating the surface state with Wannier tools" Tags="|density-functional-theory|band-structure|surfaces|tight-binding|wannier90|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4364" PostTypeId="2" ParentId="4362" CreationDate="2021-02-18T18:50:57.690" Score="8" Body="&lt;p&gt;Firstly, a minor correction: a non-linear molecule has &lt;strong&gt;3N-6&lt;/strong&gt; normal modes, not 3N-5 modes. Linear molecules have &lt;strong&gt;3N-5&lt;/strong&gt; normal modes.&lt;/p&gt;&#xA;&lt;p&gt;GAMESS automatically prints out some values in normal coordinate analysis section with the labels &lt;code&gt;TRANS. SAYVETZ&lt;/code&gt; and &lt;code&gt;ROT. SAYVETZ&lt;/code&gt;. If the total value of &lt;code&gt;ROT SAYVETZ&lt;/code&gt; is high, that mode can be identified as a rotation. You will usually find three modes where the value is much higher than the other modes. Similarly, you will also find three modes where the &lt;code&gt;TRANS. SAYVETZ&lt;/code&gt; values are higher than the other modes—these are the translational modes.&lt;/p&gt;&#xA;&lt;p&gt;Take for example, the following hessian calculation for a methane molecule with RHF/STO-3G:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                            1           2           3           4           5&#xA;       FREQUENCY:        17.63       13.88       13.41        0.01        0.02  &#xA;        SYMMETRY:         A           A           A           A           A   &#xA;    REDUCED MASS:      1.00783     1.00783     1.00783     3.20626     3.20625&#xA;    IR INTENSITY:      0.00000     0.00000     0.00000     0.00000     0.00000&#xA;&#xA;  1   C            X -0.00000062  0.00000165 -0.00000383  0.24972074 -0.00350567&#xA;                   Y  0.00010786  0.00006334  0.00038252  0.00369972  0.12078890&#xA;                   Z  0.00010115 -0.00026452 -0.00014254  0.00196065  0.21857645&#xA;  2   H            X -0.00000834  0.00000588  0.00000001  0.24972074 -0.00350564&#xA;                   Y  0.10072063 -0.21370832  0.56275746  0.00370176  0.12042435&#xA;                   Z  0.50092706 -0.28645159 -0.19853368  0.00195808  0.21811549&#xA;  3   H            X  0.01624197  0.13411438 -0.55903118  0.24971826 -0.00327108&#xA;                   Y -0.10569085 -0.03585727 -0.21488136  0.00369986  0.12087293&#xA;                   Z -0.47274098 -0.35855637 -0.05174247  0.00196502  0.21857135&#xA;  4   H            X -0.42497218  0.20048610  0.33156599  0.24972356 -0.00318826&#xA;                   Y  0.26760422  0.51780259 -0.07120695  0.00369558  0.12106658&#xA;                   Z -0.07647050  0.22917175  0.10076290  0.00196046  0.21877700&#xA;  5   H            X  0.40873302 -0.33459136  0.22742554  0.24972024 -0.00405763&#xA;                   Y -0.26220197 -0.26797649 -0.27511402  0.00370167  0.12079171&#xA;                   Z  0.04869166  0.41482209  0.14894743  0.00195904  0.21884190&#xA;&#xA; TRANS. SAYVETZ    X -0.00001299  0.00003496 -0.00008587  4.00334788 -0.05620032&#xA;                   Y  0.00172967  0.00102261  0.00615760  0.05931125  1.93640304&#xA;                   Z  0.00162428 -0.00419627 -0.00228068  0.03143177  3.50406459&#xA;               TOTAL  0.00237281  0.00431922  0.00656695  4.00391059  4.00390857&#xA;&#xA;   ROT. SAYVETZ    X -1.83361199 -2.71960126 -0.70573303  0.00002107 -0.00095138&#xA;                   Y -2.75454586  1.57410354  1.09118835  0.00001413  0.00253515&#xA;                   Z  0.55339513 -1.17579963  3.09322769  0.00001122 -0.00200507&#xA;               TOTAL  3.35498167  3.35507641  3.35511679  0.00002774  0.00336933&#xA;&#xA;                            6           7           8           9          10&#xA;       FREQUENCY:         0.02     1675.67     1675.71     1675.76     1903.68  &#xA;        SYMMETRY:         A           A           A           A           A   &#xA;    REDUCED MASS:      3.20624     1.17145     1.17144     1.17144     1.00783&#xA;    IR INTENSITY:      0.00000     0.15729     0.15726     0.15732     0.00000&#xA;&#xA;  1   C            X -0.00228962  0.02051160 -0.10602996 -0.03230322  0.00000583&#xA;                   Y  0.21857303 -0.01433194  0.03003937 -0.10769565 -0.00000247&#xA;                   Z -0.12082370 -0.10991319 -0.02370384  0.00801459  0.00000863&#xA;  2   H            X -0.00228962  0.01934522 -0.10005879 -0.03047736  0.00001134&#xA;                   Y  0.21779885  0.07075199 -0.14825981  0.53174540 -0.12291500&#xA;                   Z -0.12038398  0.54258678  0.11697000 -0.03957536 -0.48268961&#xA;  3   H            X -0.00148401 -0.10877382  0.39011099  0.33553048 -0.00818422&#xA;                   Y  0.21896760  0.09146521  0.21886006  0.04723247  0.11165411&#xA;                   Z -0.12039232  0.53775742  0.03032550  0.07487384  0.48525943&#xA;  4   H            X -0.00289646  0.09903687  0.51205228  0.06694073 -0.40256538&#xA;                   Y  0.21826225  0.23367102 -0.15755299  0.45641880  0.28658560&#xA;                   Z -0.12114100 -0.00009411  0.14777796  0.21105006 -0.06256500&#xA;  5   H            X -0.00248834 -0.25383642  0.46037640  0.01263521  0.41066886&#xA;                   Y  0.21926322 -0.22524028 -0.27072112  0.24691727 -0.27529527&#xA;                   Z -0.12137747  0.22846769 -0.01283586 -0.34177702  0.05989237&#xA;&#xA; TRANS. SAYVETZ    X -0.03670555 -0.00000006  0.00000030  0.00000009 -0.00000000&#xA;                   Y  3.50400963  0.00000001 -0.00000018  0.00000029  0.00000000&#xA;                   Z -1.93696102  0.00000022  0.00000004 -0.00000018 -0.00000000&#xA;               TOTAL  4.00390419  0.00000022  0.00000036  0.00000035  0.00000000&#xA;&#xA;   ROT. SAYVETZ    X  0.00346439 -0.00000688  0.00001430 -0.00005114  0.00000983&#xA;                   Y -0.00241844 -0.00006552  0.00007507  0.00000286  0.00000699&#xA;                   Z -0.00425789 -0.00000799  0.00015751 -0.00000316  0.00000177&#xA;               TOTAL  0.00599838  0.00006636  0.00017507  0.00005131  0.00001219&#xA;&#xA;                           11          12          13          14          15&#xA;       FREQUENCY:      1903.72     3526.08     3786.75     3786.81     3786.86  &#xA;        SYMMETRY:         A           A           A           A           A   &#xA;    REDUCED MASS:      1.00783     1.00783     1.10831     1.10832     1.10832&#xA;    IR INTENSITY:      0.00000     0.00000     0.01106     0.01105     0.01103&#xA;&#xA;  1   C            X  0.00001099 -0.00000009  0.02677698 -0.08574373  0.01340844&#xA;                   Y  0.00000823  0.00000918 -0.00066764 -0.01423712 -0.08970002&#xA;                   Z  0.00000259 -0.00000864 -0.08678066 -0.02634660  0.00482855&#xA;  2   H            X  0.00001730  0.49805561 -0.24145237  0.77303200 -0.12085446&#xA;                   Y  0.48260611 -0.00000580 -0.00002679 -0.00061172 -0.00383651&#xA;                   Z -0.12293992  0.00000780 -0.00371796 -0.00111509  0.00020558&#xA;  3   H            X  0.46943007 -0.16599274  0.02915648  0.06043341 -0.26459559&#xA;                   Y  0.16350986  0.45692960 -0.07713260 -0.17706917  0.72611878&#xA;                   Z -0.02974730 -0.10794079  0.01450202  0.04055924 -0.17223007&#xA;  4   H            X -0.24187554 -0.16604034 -0.26187415  0.02244575  0.07363741&#xA;                   Y -0.38436659 -0.13502778 -0.21392745  0.02062641  0.05558323&#xA;                   Z -0.20467169  0.44980727  0.70880064 -0.07187413 -0.19772872&#xA;  5   H            X -0.22770271 -0.16602146  0.15534115  0.16502476  0.15216060&#xA;                   Y -0.26184739 -0.32200543  0.29903632  0.32657340  0.29017729&#xA;                   Z  0.35732809 -0.34177157  0.31369786  0.34613446  0.31226050&#xA;&#xA; TRANS. SAYVETZ    X -0.00000000 -0.00000005  0.00000000 -0.00000000 -0.00000000&#xA;                   Y  0.00000000 -0.00000015  0.00000000  0.00000001 -0.00000001&#xA;                   Z -0.00000000 -0.00000011  0.00000002  0.00000001  0.00000003&#xA;               TOTAL  0.00000000  0.00000019  0.00000002  0.00000001  0.00000004&#xA;&#xA;   ROT. SAYVETZ    X -0.00000431  0.00000009 -0.00003050 -0.00001171 -0.00001387&#xA;                   Y  0.00000157  0.00000004  0.00000835  0.00001245  0.00000426&#xA;                   Z -0.00000777 -0.00000002 -0.00000454 -0.00000416  0.00001240&#xA;               TOTAL  0.00000902  0.00000010  0.00003195  0.00001759  0.00001908&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Look at the &lt;code&gt;TOTAL&lt;/code&gt; value for &lt;code&gt;TRANS. SAYVETZ&lt;/code&gt; and &lt;code&gt;ROT. SAYVETZ&lt;/code&gt; for the first 6 modes. You can immediately see that modes 1,2 and 3 are rotational modes whereas 4,5 and 6 are translational modes. This leaves us with &lt;span class=&quot;math-container&quot;&gt;$\mathrm{15-6=9}$&lt;/span&gt; normal vibrational modes.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;There are better ways of doing this. One is to use the &lt;code&gt;PROJCT=.TRUE.&lt;/code&gt; option in the &lt;code&gt;$FORCE&lt;/code&gt; section. If the molecule is at a stationary point i.e. optimized, then the program will try to automatically detect the rotational and vibrational modes, and then it will set those modes to zero.&lt;/p&gt;&#xA;&lt;p&gt;This is the top half of the same calculation on methane, with &lt;code&gt;PROJCT=.TRUE.&lt;/code&gt; added:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                            1           2           3           4           5&#xA;       FREQUENCY:         0.00        0.00        0.00        0.00        0.00  &#xA;        SYMMETRY:         A           A           A           A           A   &#xA;    REDUCED MASS:      1.69869     1.80186     1.73447     1.50339     1.20902&#xA;    IR INTENSITY:      0.00000     0.00000     0.00000     0.00000     0.00000&#xA;&#xA;  1   C            X  0.18544520 -0.06453281 -0.05424004  0.10323087  0.00731683&#xA;                   Y  0.04925272  0.18950956  0.04481326 -0.07303356  0.00934898&#xA;                   Z -0.01355662  0.00338180  0.18210652  0.11830950  0.12246754&#xA;  2   H            X  0.18543884 -0.06453163 -0.05424640  0.10323472  0.00732201&#xA;                   Y  0.17102362  0.54645964 -0.12047768  0.19706661 -0.01669391&#xA;                   Z  0.30594469 -0.06047719  0.50480017 -0.07937287 -0.13871332&#xA;  3   H            X  0.14296863 -0.40589743  0.16736579 -0.18745463 -0.02538987&#xA;                   Y -0.03158358  0.07880458  0.12489341 -0.10130832 -0.08197398&#xA;                   Z -0.29043848  0.05967641  0.18032955  0.44561985 -0.21383067&#xA;  4   H            X -0.07005260  0.08990000 -0.39044048  0.35496230  0.23609947&#xA;                   Y  0.17634788  0.03606998 -0.00419087 -0.42034225  0.43466668&#xA;                   Z -0.06971641  0.01432464  0.04328714  0.10696653  0.33461067&#xA;  5   H            X  0.48341172  0.12243297  0.06032215  0.14221914 -0.18874644&#xA;                   Y -0.11876257  0.09670174  0.17901903  0.03242832 -0.29856752&#xA;                   Z  0.00000000  0.00000000  0.00000000  0.00000000  0.50784215&#xA;&#xA; TRANS. SAYVETZ    X  2.97291332 -1.03450939 -0.86957749  1.65496336  0.11731634&#xA;                   Y  0.78959978  3.03808233  0.71840554 -1.17084448  0.14991190&#xA;                   Z -0.21731384  0.05421128  2.91939491  1.89663038  1.96335287&#xA;               TOTAL  3.08365152  3.20984311  3.12971855  2.77614613  1.97255955&#xA;&#xA;   ROT. SAYVETZ    X -1.02133456  0.20985148  0.63412701  1.56702735 -2.53776525&#xA;                   Y -1.75722268  0.35123915 -1.77483533  1.08722959  1.43654908&#xA;                   Z  0.66974877  1.96336847 -0.90916933  1.48569414 -0.14327855&#xA;               TOTAL  2.13998114  2.00554789  2.09254544  2.41762900  2.91966684&#xA;&#xA;                            6           7           8           9          10&#xA;       FREQUENCY:         0.00     1675.67     1675.71     1675.76     1903.68  &#xA;        SYMMETRY:         A           A           A           A           A   &#xA;    REDUCED MASS:      1.42881     1.17145     1.17144     1.17144     1.00783&#xA;    IR INTENSITY:      0.00000     0.15729     0.15726     0.15732     0.00000&#xA;&#xA;  1   C            X  0.10085354  0.02051281 -0.10602969 -0.03230341  0.00000583&#xA;                   Y  0.12887488 -0.01433217  0.03003943 -0.10769562 -0.00000247&#xA;                   Z -0.00495326 -0.10991295 -0.02370508  0.00801445  0.00000863&#xA;  2   H            X  0.10085825  0.01934637 -0.10005854 -0.03047754  0.00001134&#xA;                   Y -0.23012421  0.07075461 -0.14828865  0.53174574 -0.12291536&#xA;                   Z -0.23844365  0.54257359  0.11698974 -0.03957411 -0.48268833&#xA;  3   H            X  0.37964396 -0.10878236  0.39013836  0.33553069 -0.00818369&#xA;                   Y  0.28531794  0.09146253  0.21886997  0.04723477  0.11165381&#xA;                   Z  0.22859715  0.53776212  0.03032439  0.07488276  0.48525737&#xA;  4   H            X  0.21437181  0.09904228  0.51203315  0.06694147 -0.40256659&#xA;                   Y  0.09528755  0.23367074 -0.15753935  0.45641011  0.28658735&#xA;                   Z  0.02686809 -0.00009233  0.14777372  0.21104766 -0.06256492&#xA;  5   H            X -0.29147235 -0.25384877  0.46036440  0.01263656  0.41066955&#xA;                   Y  0.36500460 -0.22523712 -0.27071632  0.24692273 -0.27529636&#xA;                   Z -0.03684942  0.22847129 -0.01283556 -0.34178301  0.05989307&#xA;&#xA; TRANS. SAYVETZ    X  1.61680082  0.00000000  0.00000000 -0.00000000 -0.00000000&#xA;                   Y  2.06601817 -0.00000000 -0.00000000  0.00000000  0.00000000&#xA;                   Z -0.07942214 -0.00000000  0.00000000 -0.00000000  0.00000000&#xA;               TOTAL  2.62464928  0.00000000  0.00000000  0.00000000  0.00000000&#xA;&#xA;   ROT. SAYVETZ    X  0.93345047 -0.00000000 -0.00000000 -0.00000000  0.00000000&#xA;                   Y  1.28415215 -0.00000000  0.00000000 -0.00000000 -0.00000000&#xA;                   Z -1.97460041  0.00000000  0.00000000 -0.00000000 -0.00000000&#xA;               TOTAL  2.53365809  0.00000000  0.00000000  0.00000000  0.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, frequencies of modes 1-6 have been set to zero, as GAMESS identified them as rotational and translational modes. However, this projection method is not particularly reliable, and might fail. Also, it cannot be used if the molecule is not at a stationary point (it will set one vibrational mode to the direction of the gradient).&lt;/p&gt;&#xA;&lt;p&gt;So, an alternative is to use internal coordinates and use &lt;code&gt;PURIFY=.TRUE.&lt;/code&gt; in the &lt;code&gt;$FORCE&lt;/code&gt; section. Using internal coordinates in GAMESS is a real pain. If your molecule does not have weak interactions i.e. all bonds are traditional covalent bonds then adding &lt;code&gt;NZVAR=1&lt;/code&gt; in &lt;code&gt;$CONTRL&lt;/code&gt; and using &lt;code&gt;$ZMAT DLC=.TRUE. AUTO=.TRUE. $END&lt;/code&gt; will work. Otherwise, you have to define the weak bonds with &lt;code&gt;NONVDW&lt;/code&gt; in &lt;code&gt;$ZMAT&lt;/code&gt;. You should look into the GAMESS manual for more detailed explanations.&lt;/p&gt;&#xA;&lt;p&gt;Setting &lt;code&gt;PURIFY=.TRUE.&lt;/code&gt; with internal coordinates will also have the same effect, it will set the rotational and translational modes to zero.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-02-18T18:50:57.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4365" PostTypeId="1" CreationDate="2021-02-18T19:07:18.253" Score="7" ViewCount="221" Body="&lt;p&gt;I am trying to use Quantum ESPRESSO to &lt;strong&gt;manually&lt;/strong&gt; calculate the Berry phase using the Berry connection, due to evolution along a closed loop in k-space. I want to do this manually instead of using existing methods such as the lberry tag, polarization, etc.&lt;/p&gt;&#xA;&lt;p&gt;So far, I defined a custom circular path in &lt;code&gt;K_POINTS&lt;/code&gt; (using the equation of a circle parameterized by a single variable, for example). Then, I run an SCF calculation and use the output .hdf5 files (one file per k-point sampled) to extract wavefunction data. I sum all the plane wave basis coefficients at each k-point, per band, to get a single wavefunction vector &lt;span class=&quot;math-container&quot;&gt;$|\phi_n\rangle(k)$&lt;/span&gt; at the point &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; for each band &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, when I try to use a difference method to numerically calculate the Berry phase of the loop using the gauge-dependent Berry connection &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_n | \frac{d}{dt} \phi_n \rangle$&lt;/span&gt;, I end up with nonsense.&lt;/p&gt;&#xA;&lt;p&gt;I learnt that this was because the gauge at each k-point is different, whereas the Berry phase can be calculated this way only if the gauge is consistent along the loop. To clarify, this gauge choice can come from the quantum adiabatic theorem and boils down to an arbitrary complex phase that multiplies the wavefunction: &lt;span class=&quot;math-container&quot;&gt;$e^{i \theta(k)}|\phi_n\rangle(k)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\theta(k)$&lt;/span&gt; is a smooth &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-dependent function. Physical observables are gauge-independent and do not depend on this arbitrary phase (such as the Berry phase when calculated from the Berry curvature area integral, which is what I think is used by built-in polarization calculations). Note that calculating the Berry phase using the Berry connection comes with a &lt;span class=&quot;math-container&quot;&gt;$2\pi n, n\in \mathbb{Z}$&lt;/span&gt; ambiguity. I want to calculate the phase this way because I want to calculate this ambiguity.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So, how do I fix the gauge?&lt;/strong&gt; I have seen some works that say they &amp;quot;fix the gauge&amp;quot; to the so-called hydrogenic gauge (i.e. no gauge singularities at the band edge, etc). However, I do not know how to fix the gauge at all (whether to the hydrogenic gauge or not). Any advice?&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-09-05T23:14:18.560" LastActivityDate="2021-09-05T23:14:18.560" Title="How to fix gauge in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|condensed-matter|berry-phase|" AnswerCount="0" CommentCount="11" ClosedDate="2022-08-23T22:17:23.890" ContentLicense="CC BY-SA 4.0" />
  <row Id="4366" PostTypeId="2" ParentId="4350" CreationDate="2021-02-19T02:15:36.803" Score="3" Body="&lt;p&gt;There has indeed been quite a lot of research in this area, as is readily uncovered by  searching for &amp;quot;improving the strength of graphene&amp;quot; in your search engine of choice; for example, this 2017 review &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0079642517300968&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/S0079642517300968&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Graphene is often highlighted as having high mechanical strength, but this usually refers to its tensile strength and is not always the critical factor in mechanical applications. Do you only need the material to support tension, or also compression? What about shear stress? Some relevant considerations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Graphene is a 2D material, only a single atom thick, so in order for it to be useful for macroscopic applications requiring high tensile strength, many sheets would need to be used.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Graphene sheets only interact very weakly, via van der Waals interactions. The sheets can slide very easily (which is why graphite is so good for pencils, lubrication etc) and cannot support even moderate shear stresses (in the out-of-plane direction). If you need high shear strength, then you need to do something to the graphene sheets, for example induce corrugation: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0008622320306230&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/S0008622320306230&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Real graphene sheets are not infinite, they have edges. These edges are chemically reactive and need to be passivated or they will reconstruct. One alternative is to fold the sheet so that, for example, the left-hand edge wraps over and binds to the right-hand edge. This can maintain the pristine structure and high tensile strength of the graphene. The resultant structure is a carbon nanotube, which is one reason why these are of interest in mechanical applications.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Graphene sheets are strong under tension, but buckle easily under compression (nanotubes are stronger in this respect).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Pristine, single-crystal graphene is difficult to create in large quantities, e.g. using CVD, and polycrystalline graphene has a much wider spread of mechanical strengths. Not all of the defects and grains are detrimental, but understanding the nanostructure and implications is challenging for modelling due to the long-range interactions between point defects and the extremely soft flexural phonon modes which lead to large thermal effects (see e.g. &lt;a href=&quot;https://www.nature.com/articles/nphys3183&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/nphys3183&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are many, many more studies in this area, both experimental and modelling, but I hope this has given you a flavour of it at least.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-02-19T02:15:36.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4367" PostTypeId="2" ParentId="4363" CreationDate="2021-02-19T12:49:25.243" Score="4" Body="&lt;p&gt;Wannier90 might not be good at preserving the symmetry. But they probably include a few new methods to enforce symmetry in Wannier90.v.3.1.0. Maybe you can check this.&#xA;&lt;a href=&quot;http://www.wannier.org/features/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.wannier.org/features/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also, WannierTools can symmetrize the hr.dat, but from my personal experience it sometimes gives you worse results than the original hr.dat.&#xA;&lt;a href=&quot;http://www.wanniertools.com/symmetrization.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.wanniertools.com/symmetrization.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1022" LastActivityDate="2021-02-19T12:49:25.243" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4368" PostTypeId="2" ParentId="4327" CreationDate="2021-02-19T17:29:02.173" Score="4" Body="&lt;p&gt;Wannier90 should still scale cubically with size of the supercell, same as pw.x on Quantum ESPRESSO. Regarding the number of iterations needed, it depends on your system. Assuming you are generating MLWFs (Maximally Localized Wannier Functions) first, the number of iterations required to converge depends on the parameters in your system, like K-Points. Look at Table 1 in this &lt;a href=&quot;https://arxiv.org/pdf/0708.0650.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;document&lt;/a&gt; [2] for an idea of the relative time-scales for the wannier procedure for bulk silicon. You control the number of iterations using the &lt;em&gt;num_iter&lt;/em&gt; tag. But as you might imagine, you can't set this tag to an arbitrarily low value. The correct method should be to set this to a high enough number so that the amount of spread '&lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt;' in k-space is low. This is indicated by the Im/Re ratio printed in the output.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Mostofi, Arash A., et al. &amp;quot;wannier90: A tool for obtaining maximally-localised Wannier functions.&amp;quot; Computer physics communications 178.9 (2008): 685-699.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/pdf/0708.0650.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/0708.0650.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-02-19T17:29:02.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4369" PostTypeId="1" CreationDate="2021-02-19T20:06:37.530" Score="7" ViewCount="1696" Body="&lt;p&gt;I am trying to sort a set of Cu atoms in a fcc (non primitive) crystal structure according to their Z cordinate. I am using &lt;code&gt;ase.build.sort&lt;/code&gt; to do this with the help of doccumentation. The doccumentation says that for &lt;code&gt;ase.build.sort(atoms, tags=None)&lt;/code&gt;, it will return a new &lt;code&gt;Atoms&lt;/code&gt; object with sorted atomic order. The default is to order according to chemical symbols, but if tags is not &lt;code&gt;None&lt;/code&gt;, it will be used instead.&lt;/p&gt;&#xA;&lt;p&gt;But there is no clue given how to sort in some different manner (not according to chemical symbols).&lt;/p&gt;&#xA;&lt;p&gt;Here is my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import os&#xA;import numpy&#xA;import ase&#xA;import ase.io&#xA;import ase.build&#xA;import ase.visualize&#xA;&#xA;from ase.build import bulk&#xA;from ase.build.tools import sort&#xA;&#xA;Cu=ase.build.bulk('Cu','fcc',a=3.6, cubic=True)&#xA;surface=ase.build.surface(Cu,(1,1,1),4,vacuum=15)&#xA;&#xA;from ase.build import bulk&#xA;from ase.build.tools import sort&#xA;&#xA;surface_sorted = sort(surface,tag=)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What should I put in the tag so that I can get it sorted according to z coordinates?&lt;/p&gt;&#xA;" OwnerUserId="2104" LastEditorUserId="5" LastEditDate="2021-02-19T21:12:47.453" LastActivityDate="2021-02-19T22:08:22.657" Title="How to sort using ase.build.sort?" Tags="|software-assistance|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4370" PostTypeId="5" CreationDate="2021-02-19T20:10:46.107" Score="0" Body="&lt;p&gt;Website: &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialsproject.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-19T20:10:46.107" LastActivityDate="2021-02-19T20:10:46.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4371" PostTypeId="4" CreationDate="2021-02-19T20:10:46.107" Score="0" Body="Questions about The Materials Project (https://materialsproject.org/)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-19T20:10:46.107" LastActivityDate="2021-02-19T20:10:46.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4372" PostTypeId="5" CreationDate="2021-02-19T20:58:57.233" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen_theoretical_materials_chemistry/boltztrap/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-19T20:58:57.233" LastActivityDate="2021-02-19T20:58:57.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4373" PostTypeId="4" CreationDate="2021-02-19T20:58:57.233" Score="0" Body="Questions about BoltzTraP, the software for calculating Boltzmann Transport Properties." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-19T20:58:57.233" LastActivityDate="2021-02-19T20:58:57.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4374" PostTypeId="2" ParentId="4341" CreationDate="2021-02-19T21:00:15.773" Score="8" Body="&lt;p&gt;Running simulations with small molecules is one thing that I found quite difficult especially because most online guides/tutorials are focused on proteins. So, here's a rough idea of what to do:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Getting forcefield parameters&lt;/strong&gt;: Your question is about this, so I will give a detailed explanation. There are many forcefields to choose from, e.g. MMFF94, UFF, CgenFF, GAFF, OPLS-AA etc. Which one you use depends on what you are trying to study. Some general forcefields have been parameterized to be compatible with protein force fields, for example CgenFF with CHARMM36, GAFF with Amber as you can probably guess. I am by no means an expert on this topic, so I will advise you to look through the literature for which force field (or combination) will suit your purpose the best.&lt;/p&gt;&#xA;&lt;p&gt;Getting parameters in a gromacs compatible format can also be tricky. There is a guide on how to do that with some popular forcefields &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/02_topology.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. For the sake of being a complete answer, I will summarize the information briefly:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;GAFF - You can use &lt;a href=&quot;https://ambermd.org/AmberTools.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;Antechamber&lt;/a&gt; with the python module acpype (which has been mentioned in the other answer) to generate gromacs compatible topology files.&lt;/li&gt;&#xA;&lt;li&gt;CHARMM - For this you can use the CgenFF official website (&lt;a href=&quot;https://cgenff.umaryland.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://cgenff.umaryland.edu/&lt;/a&gt;) or as it was known earlier, paramchem.org. This site produces parameters in the form of .str files which have to converted to gromacs compatible format using the cgenff_charmm2gmx.py python script which is available &lt;a href=&quot;http://mackerell.umaryland.edu/charmm_ff.shtml#gromacs&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;GROMOS - &lt;a href=&quot;https://atb.uq.edu.au/index.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;ATB&lt;/a&gt; can generate gromacs compatible files.&lt;/li&gt;&#xA;&lt;li&gt;OPLS-AA - The &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;LigParGen&lt;/a&gt; server from Jorgensen group produces gromacs compatible files.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There is also another server called &lt;a href=&quot;https://www.swissparam.ch&quot; rel=&quot;nofollow noreferrer&quot;&gt;swissparam&lt;/a&gt; which can generate parameters for small molecules, however it takes most of the bonding and charge parameters from Merck Molecular Force Field, and Van der Waals parameters from CHARMM22. The parameters are supposed to be compatible with CHARMM protein forcefield, but I have never used it with a protein so I can't be sure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Running the simulations&lt;/strong&gt;: In the question you have written that you already have a topology file. For other readers of this answer, a standard gromacs topology file would look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; Include forcefield parameters&#xA;#include &amp;quot;charmm36-jul2020.ff/forcefield.itp&amp;quot;&#xA;; Include small molecule parameters&#xA;#include &amp;quot;ligand.itp&amp;quot;&#xA;&#xA;; Include TIP3P water topology&#xA;#include &amp;quot;charmm36-jul2020.ff/tip3p.itp&amp;quot;&#xA;&#xA;;Include topology for ions&#xA;#include &amp;quot;charmm36-jul2020.ff/ions.itp&amp;quot;&#xA;&#xA;[ system ]&#xA;;Name&#xA;small molecules&#xA;&#xA;[ molecules ]&#xA;; Compound        #mols&#xA;LIG                 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here I have named the small molecule (in your case benzene) as LIG, and its parameters are stored in the &lt;code&gt;ligand.itp&lt;/code&gt; file (which you can get from swissparam, or after converting the str file from CgenFF website).&lt;/p&gt;&#xA;&lt;p&gt;Also note that you don't always need to include the original forcefield parameter files as you have done in the question. If the .itp files say that the &lt;code&gt;&amp;quot;parameters were taken&amp;quot;&lt;/code&gt; that means they are already present in the .itp files. However, different forcefields use different combining rules, which are defined in the &lt;code&gt;forcefield.itp&lt;/code&gt; for that forcefield, so it has to be included. In my case, I included the ion and tip3p water topolgy because I needed them later. The &lt;code&gt;forcefield.itp&lt;/code&gt; is also required for the tip3p water parameters.&lt;/p&gt;&#xA;&lt;p&gt;After you have the topology and parameters, you can then run gromacs as usual.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-03-28T10:06:27.853" LastActivityDate="2021-03-28T10:06:27.853" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4375" PostTypeId="2" ParentId="4369" CreationDate="2021-02-19T22:08:22.657" Score="8" Body="&lt;p&gt;The following code should create a Cu surface and sort it by z index.  We do this by providing tags for the positions of the atoms.  &lt;code&gt;[:, 2]&lt;/code&gt; allows us to select the z position of all atoms.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import bulk, surface&#xA;from ase.build.tools import sort&#xA;&#xA;Cu = ase.build.bulk('Cu', 'fcc', a=3.6, cubic=True)&#xA;surface = ase.build.surface(Cu, (1,1,1), 4, vacuum=15)&#xA;&#xA;surface_sorted = sort(surface, tags=surface.positions[:, 2])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-02-19T22:08:22.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4376" PostTypeId="1" CreationDate="2021-02-20T00:23:01.717" Score="10" ViewCount="138" Body="&lt;p&gt;&lt;a href=&quot;https://www.researchgate.net/post/How_to_find_the_percentage_of_spin-polarization_quantitatively_in_Quantum_Espresso&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cross-posted on ResearchGate&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am investigating a near half-metallic / high-spin polarization material. I ran an SCF calculation with &lt;code&gt;nspin = 2&lt;/code&gt;, with some starting magnetization. So now I wonder how to find the &lt;strong&gt;exact percentage&lt;/strong&gt; of spin-polarization (%SP). I have already done PDOS calculation, and from that I can clearly &amp;quot;see&amp;quot; it's nearly half-metallic, but I don't know how to extract the %SP.&lt;/p&gt;&#xA;&lt;p&gt;Is it mentioned somewhere in the output file after the SCF, or do I need it to extrapolate it somehow? Please help. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="603" LastEditorUserId="5" LastEditDate="2021-05-17T16:11:01.280" LastActivityDate="2021-05-17T17:47:27.307" Title="How do I get exact percentage of spin-polarization in Quantum ESPRESSO?" Tags="|quantum-espresso|spin-polarization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4377" PostTypeId="1" AcceptedAnswerId="4378" CreationDate="2021-02-20T04:01:52.497" Score="6" ViewCount="194" Body="&lt;p&gt;I am trying to use pseudopotentials to model scattering from heavy molecules.&lt;/p&gt;&#xA;&lt;p&gt;However, I am confused by some of the terminologies of pseudopotentials/ECPs:&lt;/p&gt;&#xA;&lt;p&gt;Norm-conserving according to Wikipedia and other sources are the potentials which obey a few mathematical conditions and seem to find a compromise between transferrability and softness.&lt;/p&gt;&#xA;&lt;p&gt;However, I do not understand what is meant by shape consistent and energy consistent pseudopotentials and would like some sort of basic description about them.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-02-20T05:44:33.383" LastActivityDate="2021-02-25T19:06:16.713" Title="What is the meaning of energy-consistent and shape-consistent in the context of pseudopotentials?" Tags="|molecular-modeling|quantum-chemistry|pseudopotentials|terminology|relativistic|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4378" PostTypeId="2" ParentId="4377" CreationDate="2021-02-20T05:34:21.230" Score="6" Body="&lt;p&gt;This 2017 paper titled &amp;quot;&lt;a href=&quot;https://arxiv.org/abs/1705.05257&quot; rel=&quot;nofollow noreferrer&quot;&gt;Shape and Energy Consistent Pseudopotentials for Correlated Electron systems&lt;/a&gt;&amp;quot; defines energy-consistent psuedopotentials this way:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;A combined reproduction of core scattering, core polarisation, and&#xA;atomic excitation energies allows the generation of a new&#xA;pseudopotential from correlated electron calculations, referred to as&#xA;an energy consistent correlated electron pseudopotential (eCEPP).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;where by &amp;quot;reproduction&amp;quot;, the abstract hints that they compare results using the pseudopotential to all-electron results. This means that they do calculations for  core scattering, core polarization, and atomic excitation, all with every electron correlated, and then they do the same calculations but with the pseudopotential taking care of most of the electron correlation, and after comparing the two, if the psuedopotential method gives the same results as the all-electron calculation, then it is labelled as &amp;quot;energy-consistent&amp;quot;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Unfortunately that article does in my opinion, not as good of a job at defining what a shape-consistent pseudopotential is, but thanks to that, I had to look for a better resource to show you, and arrived at this 1999 paper (&amp;quot;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0301010498002432&quot; rel=&quot;nofollow noreferrer&quot;&gt;On the accuracy of averaged relativistic shape-consistent&#xA;pseudopotentials&amp;quot;&lt;/a&gt;) which defines both shape-consistent pseudopotentials and &amp;quot;energy-adjusted&amp;quot; pseudopotentials which gives some perspective on how the terminology can vary slightly from paper to paper. The &amp;quot;energy-adjusted pseudopotentials&amp;quot; or EAPP are described in the following way:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The EAPP are based on quantum mechanical observables (atomic&#xA;excitations, ionization energies, etc. and the starting point is&#xA;either a quasi-relativistic or a 4-component all-electron&#xA;calculation.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So again, they are comparing energies from relativistic all-electron calculations to energies obtained with the pseudopotential, but the specific energies that are being compared are not necessarily exactly the same from paper to paper.&lt;/p&gt;&#xA;&lt;p&gt;They also describe shape-consistent pseudopotentials or SCPPs, and as suspected in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4377/what-is-the-meaning-of-energy-consistent-and-shape-consistent-in-the-context-of#comment7638_4377&quot;&gt;my initial comment&lt;/a&gt;, this has to do with the accuracy of the shape of the wavefunction:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In contrast to the previous method, the SCPP are based on orbital properties&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'll also mention that &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1588/5&quot;&gt;this answer by Susi Lehtola&lt;/a&gt; points out that energy-consistent PPs are shape-consistent, but shape-consistent PPs are not necessarily energy-consistent, and refers the reader to this excellent review paper: &amp;quot;&lt;a href=&quot;https://scihub.wikicn.top/10.1002/cphc.201100387&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Pseudopotential Approximation in Electronic Structure Theory&lt;/a&gt;.&amp;quot;  That paper describes shape-consistent potentials in the following way:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;If the pseudopotential parameters are fitted in such a way that the&#xA;valence orbitals of different symmetries reproduce to a high accuracy&#xA;the corresponding all-electron orbitals from a certain cut-off&#xA;(valence) radius &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt; onwards with matching orbital energies, we obtain&#xA;shape-consistent pseudopotentials.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-02-25T19:06:16.713" LastActivityDate="2021-02-25T19:06:16.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4379" PostTypeId="1" CreationDate="2021-02-20T06:39:02.453" Score="13" ViewCount="363" Body="&lt;p&gt;During the geometry optimization of the ground state of a molecule, we try to optimize the energy&#xA;gradient with respect to the nuclear positions such that the system remains in its lowest energy&#xA;state.&#xA;Nowadays, excited state geometry optimization is available in many codes for example nwchem, gamess etc.&#xA;My question is when we do an excited state geometry optimization what are we optimizing?&#xA;How the energy gradient differ in this case compared to the ground state?&lt;/p&gt;&#xA;" OwnerUserId="2052" LastActivityDate="2021-02-20T20:59:00.830" Title="Excited state energy gradient during geometry optimization of a target excited state" Tags="|computational-chemistry|geometry-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4380" PostTypeId="2" ParentId="127" CreationDate="2021-02-20T09:17:02.787" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Many DFT codes use pseudopotentials (for the core electrons) and basis set functions (for the valence electrons) in order to solve the Schrodinger equation. This because simulates each electron wavefunction is very costly.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The key of KS-DFT is to solve the Kohn-Sham equation. Basically, there are four main classifications in terms of the used basis. You may take a look at this post:&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1979/when-are-atomic-orbital-basis-rather-than-plane-wave-methods-appropriate-in-pe/3490#3490&quot;&gt;When are atomic-orbital-basis (rather than plane-wave) methods appropriate in periodic DFT?&lt;/a&gt;. In general, the electrons are partitioned into core and valence electrons and the core electrons are treated with pseudopotential method only when you use the plane-wave basis. &lt;strong&gt;The reason is that the wavefunction of the core electrons are oscillating strongly and there are many nodes closed to nuclei, which means you should use many plane waves to expand it and hence lead to prohibitive computational cost.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When should I include semi-core electrons in DFT calculations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This assumes that you are using a plane-wave type Kohn-Sham solver, such as VASP, in which the partition of valence and core electrons is decided when generating pseudopotential. There are two situations you need to include semi-core electrons (maybe I am missing some situations):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If you want to study the spectral properties of core electrons, you should use the pseudopotential with the inclusion of semi-core electrons.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you want to perform GW calculations, you will use the pseudopotential with semi-core electrons.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-20T09:17:02.787" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4381" PostTypeId="1" AcceptedAnswerId="4382" CreationDate="2021-02-20T10:21:03.397" Score="10" ViewCount="1083" Body="&lt;p&gt;I want to calculate the &lt;code&gt;formation energy&lt;/code&gt; of &lt;em&gt;&lt;strong&gt;WS2 monolayer&lt;/strong&gt;&lt;/em&gt; unit cell using &lt;code&gt;VASP&lt;/code&gt;. I am wandering if you could show me &lt;em&gt;the detailed calculation steps&lt;/em&gt; in &lt;code&gt;VASP&lt;/code&gt; to do that for WS2 or any monolayer.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-02-21T22:45:07.317" Title="How to calculate the formation energy of a monolayer using VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4382" PostTypeId="2" ParentId="4381" CreationDate="2021-02-20T14:16:51.030" Score="10" Body="&lt;p&gt;I am not sure whether there is a special point about monolayer. The steps to calculate the formation energy are following (This is suitable for bulk materials):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculate the total energy of primitive monolayer WS2: &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(WS2)&lt;/li&gt;&#xA;&lt;li&gt;Calculate the total energy per atom for the lowest-energy configuration bulk S: &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(S)&lt;/li&gt;&#xA;&lt;li&gt;Calculate the total energy per atom for the lowest-energy configuration bulk W: &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;(W)&lt;/li&gt;&#xA;&lt;li&gt;Estimate the formation energy: &lt;span class=&quot;math-container&quot;&gt;$$\Delta E_f=E(\text{WS2})-\dfrac{1}{3}E(\text{W})-\dfrac{2}{3}E(\text{S}).$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Reference paper: &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0966979509000892&quot; rel=&quot;noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/abs/pii/S0966979509000892&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-21T22:45:07.317" LastActivityDate="2021-02-21T22:45:07.317" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4383" PostTypeId="1" AcceptedAnswerId="4384" CreationDate="2021-02-20T19:23:51.997" Score="17" ViewCount="2489" Body="&lt;p&gt;When creating molecular orbitals via the linear combination of atomic orbitals method I am told that Slater orbitals provide a more accurate representation whilst Gaussian orbitals are computationally more straightforward to integrate (two-electron integrals for instance), since the product of Gaussians is another Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;However, the Slater-type orbital can itself be approximated by a linear combination of  a few Gaussians. This means when we represent the integrals we do so via many more basis functions than if we were to use Slater-type orbitals, however my supervisor assures me that despite there being a higher number of functions when using Gaussian-type orbitals (compared to Slater) the Gaussian-type orbitals' far simpler integration makes it substantially more computationally efficient.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering if there was anyone who could provide me with a source or some data that quantifies just how much more computationally efficient doing Hartree-Fock calculations with Gaussian-type orbitals is than using Slater-type orbitals.&lt;/p&gt;&#xA;&lt;p&gt;According to Wikipedia:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The speedup by 4—5 orders of magnitude compared to Slater orbitals&#xA;more than outweighs the extra cost entailed by the larger number of&#xA;basis functions generally required in a Gaussian calculation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However, the Wikipedia article does not give a reference for this and I was just wondering if this is actually an accurate statement and any evidence for this would be really helpful. I could not find any sources that verified this and was wondering if anyone knew of such a source.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-02-20T20:00:28.523" LastActivityDate="2024-01-25T10:38:37.467" Title="Gaussian-type orbitals vs Slater-type orbitals in terms of computational efficiency" Tags="|molecular-modeling|electronic-structure|quantum-chemistry|basis-sets|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4384" PostTypeId="2" ParentId="4383" CreationDate="2021-02-20T20:43:50.707" Score="15" Body="&lt;p&gt;&lt;strong&gt;Your supervisor is correct that in almost all practical cases in quantum chemistry, the cost savings of using Gaussian-type orbitals far outweigh the disadvantages of needing more orbitals.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;First of all, there is a bit of a misconception that Slater-type orbitals are far more accurate. The motivation for using Slater-type orbitals is due to their resemblance to the known shape of the wavefunction for the &lt;em&gt;&lt;strong&gt;hydrogen atom&lt;/strong&gt;&lt;/em&gt; which is essentially the only system for which we can access the solution to the non-relativistic Schroedinger equation (without other bells and whistles) analytically. Slater-type orbitals are &lt;em&gt;&lt;strong&gt;not much better&lt;/strong&gt;&lt;/em&gt; than Gaussian-type orbitals for calculating the frozen-core electron correlation energy of benzene, for example, where the &lt;em&gt;theoretical&lt;/em&gt; motivation for using them based on the analytic solution to the H-atom Schroedinger equation is not nearly as relevant.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps the best data that justifies the use of Gaussian-type orbitals over Slater-type orbitals, is the fact that almost everyone in quantum chemistry and even in atomic physics, uses them. The ADF software uses Slater-type orbitals and is aimed at fairly large systems with DFT, but since you mentioned Hartree-Fock I'll speak from the perspective of smaller systems (containing a few atoms) where we aim for &lt;a href=&quot;/questions/tagged/high-precision&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;high-precision&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;high-precision&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-high-precision-tooltip-container&quot;&gt;high-precision&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the realm of high-accuracy wavefunction-based &lt;em&gt;ab initio&lt;/em&gt; calculations, &lt;a href=&quot;https://scholar.google.com/citations?user=4mRmdSAAAAAJ&amp;amp;hl=en&amp;amp;oi=sra&quot; rel=&quot;nofollow noreferrer&quot;&gt;Michal Lesiuk&lt;/a&gt; and co-workers have in recent years put some &lt;em&gt;&lt;strong&gt;serious&lt;/strong&gt;&lt;/em&gt; effort into &amp;quot;re-examining&amp;quot; the option of using Slater-type orbitals. At first sight, their paper &amp;quot;&lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.91.012510&quot; rel=&quot;nofollow noreferrer&quot;&gt;Reexamination of the calculation of two-center, two-electron integrals over Slater-type orbitals. III. Case study of the beryllium dimer&lt;/a&gt;&amp;quot; seemed to show evidence that Slater-type orbitals gave a better result for the well depth of the &lt;span class=&quot;math-container&quot;&gt;$\ce{Be2}$&lt;/span&gt; potential than any previous calculation: their calculated energy with Slater-type orbitals was 929.0±1.9 cm&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt; and the empirical result that they compared to was 929.7±2.0 cm&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt;. &lt;em&gt;&lt;strong&gt;However,&lt;/strong&gt;&lt;/em&gt; that empirical result was based on an older paper that had a major error (the author's didn't know that &lt;span class=&quot;math-container&quot;&gt;$\ce{Be2}$&lt;/span&gt; has one more vibrational level before the molecule dissociated). A more careful analysis by two different groups, who both used different models to fit the experimental data, arrived at empirical values for this energy to be 934.8±0.3 cm&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt; and 935.0±0.3 cm&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt;, and guess what: &lt;a href=&quot;https://pubs.rsc.org/en/Content/ArticleLanding/CP/2011/C1CP22417D#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;That's the answer that Gaussian-type orbitals predicted several years earlier when Jacek Koput used an aug-cc-pCV7Z(i) basis set on the same system&lt;/a&gt; and got an energy of 935 cm&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have worked with the authors of the Slater-type orbital paper, and can say that they are an extremely competent group when it comes to high-precision computational spectroscopy and their work has a tendency to be truly state-of-the-art, so when their series of three consecutive papers on reexamining the use of Slater-type orbitals ends in a paper that gives a lower-accuracy result than a calculation from several years earlier using GTOs, I'm confident in saying that GTOs are the way to go.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;There's much more that can be said on this topic, and I don't want this answer to get too much longer, but I'll conclude with a few more points in this paragraph. Not all quantum chemistry software has implemented STOs, so it might be less convenient to work with them even if they have some advantages. Furthermore, the integrals (whether GTO or STO) are often not the biggest issue for a quantum chemistry calculation, since the FCI problem is even harder, so we can pay the price to switch from GTOs to STOs since that price is smaller than the price of FCI, but we will gain very little compared to the other errors we'll have in the calculation (due to approximating FCI, due to still being far from the basis-set limit, due to ignoring Born-Oppenheimer breakdown, etc.), and this is a major reason to avoid the inconvenience of switching to STOs.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-01-25T10:38:37.467" LastActivityDate="2024-01-25T10:38:37.467" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4385" PostTypeId="2" ParentId="4379" CreationDate="2021-02-20T20:59:00.830" Score="6" Body="&lt;p&gt;There's many reasons why we may want to optimize the geometry of an excited electronic state, for example the upper state in this figure from &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853&quot; rel=&quot;noreferrer&quot;&gt;my 2011 spectroscopy paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AQVMH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AQVMH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My question is when we do an excited state geometry optimization what are we optimizing? How the energy gradient differ in this case compared to the ground state?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;We are again optimizing the electronic energy as a function of nuclear coordinates. In the above diagram, we'd be optimizing &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; with respect to the internuclear distance &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. In terms of the actual implementation of the energy gradients, remember that to calculate electronic excited states you have to use excited state methods such as EOM-CCSD instead of vanilla CCSD, for which the implementation is a bit more complicated but not too uncommon nowadays.&lt;/p&gt;&#xA;&lt;p&gt;In my above example, if spatial symmetry constraints where you specify occupation numbers in spatial orbitals in a point group bigger than &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt;&#xA;are possible in your electronic structure software, then the upper state in that figure can actually be treated as the &amp;quot;ground state&amp;quot; in that particular spatial symmetry, but if you want the &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;-state or &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt;-state in the below figure for the CO molecule, then you will have to use an excited state method such as EOM-CCSD:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eGZ6X.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eGZ6X.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-20T20:59:00.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4386" PostTypeId="2" ParentId="4030" CreationDate="2021-02-21T00:55:38.470" Score="6" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In short, you can't completely believe the data supported by the Materials Project.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Specific to &lt;a href=&quot;https://materialsproject.org/materials/mp-19092/&quot; rel=&quot;noreferrer&quot;&gt;the Co2W2O8 entry&lt;/a&gt;, there are many self-contradictory points shown on their webpage. This can be seen easily when you take a look at the &lt;code&gt;INCAR&lt;/code&gt; and &lt;code&gt;POSCAR&lt;/code&gt; files downloaded from their website:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;h3&gt;INCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;ALGO = Fast&#xA;EDIFF = 0.0006000000000000001&#xA;ENCUT = 520&#xA;IBRION = 2&#xA;ISIF = 3&#xA;ISMEAR = -5&#xA;ISPIN = 2&#xA;LASPH = True&#xA;LDAU = True&#xA;LDAUJ = 0 0 0&#xA;LDAUL = 2 2 0&#xA;LDAUPRINT = 1&#xA;LDAUTYPE = 2&#xA;LDAUU = 3.32 6.2 0&#xA;LMAXMIX = 6&#xA;LORBIT = 11&#xA;LREAL = Auto&#xA;LWAVE = False&#xA;MAGMOM = 2*0.6 2*5.0 8*0.6&#xA;NELM = 100&#xA;NSW = 99&#xA;PREC = Accurate&#xA;SIGMA = 0.05 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;h3&gt;POSCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;Co2 W2 O8&#xA;1.0&#xA;4.700949 0.000000 -0.062527&#xA;0.000000 5.766850 0.000000&#xA;0.000000 0.000000 5.061702&#xA;Co W O&#xA;2 2 8&#xA;direct&#xA;0.500000 0.342041 0.250000 Co&#xA;0.500000 0.657959 0.750000 Co&#xA;0.000000 0.827445 0.250000 W&#xA;0.000000 0.172555 0.750000 W&#xA;0.259471 0.374817 0.899680 O&#xA;0.740529 0.374817 0.600320 O&#xA;0.259471 0.625183 0.399680 O&#xA;0.740529 0.625183 0.100320 O&#xA;0.217971 0.108689 0.431476 O&#xA;0.782029 0.891311 0.568524 O&#xA;0.217971 0.891311 0.931476 O&#xA;0.782029 0.108689 0.068524 O&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It seems this &lt;code&gt;INCAR&lt;/code&gt; will be used to relax the structure in FM spin-polarized mode (ISPIN=2, MAGMOM = 2&lt;em&gt;0.6 2&lt;/em&gt;5.0 8*0.6). However, the website shows the magnetic ordering is AFM.&lt;/li&gt;&#xA;&lt;li&gt;What's more, the main initial magnetic moment should be placed on &lt;code&gt;Co&lt;/code&gt; atoms rather than &lt;code&gt;W&lt;/code&gt; atoms.&lt;/li&gt;&#xA;&lt;li&gt;If you use &lt;code&gt;ISMEAR&lt;/code&gt;=-5, it is not necessary to set &lt;code&gt;SIGMA&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Return to the disagreement between the band structure and density of states (DOS) disagreement. I think the bandgap of 2.283 eV shown on their webpage is read from the DOS. However, the band structure and DOS are not completely exhibited no matter what the data are calculated with AFM or FM spin-polarized mode. I mean there should be two spin channels in their band structure and DOS.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Therefore, I strongly suggest you do some own calculations with the structure supported by the Materials Project to obtain reasonable results.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-21T13:55:25.573" LastActivityDate="2021-02-21T13:55:25.573" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4387" PostTypeId="1" AcceptedAnswerId="4809" CreationDate="2021-02-21T07:04:52.383" Score="14" ViewCount="519" Body="&lt;p&gt;So I am aware that a norm-conserving pseudopotential enforces the conditions that:&lt;/p&gt;&#xA;&lt;p&gt;Inside the cut-off radius, the norm of each pseudo-wavefunction is identical to its corresponding all-electron wavefunction and all-electron and pseudo wavefunctions are identical outside the cut-off radius.&lt;/p&gt;&#xA;&lt;p&gt;My question is why is the norm-conserving pseudopotential such a generally used and important pseudopotential that it is often referred to in the literature.&lt;/p&gt;&#xA;&lt;p&gt;I initially assumed that it was because it was some sort of compromise between a pseudopotential that has a good level of softness and is also quite transferable. I must stress that from what I have read it seems like Norm-conserving pseudopotentials have a high level of transferability (why this is the case I am still unsure so any explanation would be greatly appreciated) but I am unsure if Norm-conserving also implies it has an acceptable level of softness (the papers I have read have not been too clear on this point, or perhaps I have not fully understood what I have read.)&lt;/p&gt;&#xA;&lt;p&gt;Apologies if what I have written is unclear or does not make much sense as I am very new to this topic.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastActivityDate="2021-04-26T18:46:44.580" Title="Why are Norm-conserving Pseudopotentials considered so important?" Tags="|molecular-modeling|quantum-chemistry|pseudopotentials|electron-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4388" PostTypeId="1" CreationDate="2021-02-21T17:45:02.790" Score="8" ViewCount="224" Body="&lt;p&gt;I have a material that can crystallize in either a cubic or tetragonal polymorph depending on the synthesis. I used DFPT in VASP and calculated the phonon band structures. I see that the cubic has all positive frequencies, while the tetragonal has some negative (imaginary) frequencies. This leads me to believe that the cubic phase is at a local minimum on the potential energy surface, while the tetragonal is at a saddle point.&lt;/p&gt;&#xA;&lt;p&gt;I thought the tetragonal might be stabilized by entropic contributions at finite temperature, so I used phonopy to plot the thermal properties. I was looking at the Helmholtz free energy vs temperature, and surprisingly at 0 K, the free energy of the tetragonal phase is slightly lower than the cubic. Once the temperature increases, a crossover happens, and the free energy of the cubic becomes lower.&lt;/p&gt;&#xA;&lt;p&gt;My question is: why is the free energy of the tetragonal phase at 0 K lower than the cubic, when the tetragonal phase has negative phonon frequencies and the cubic does not?&lt;/p&gt;&#xA;" OwnerUserId="979" LastEditorUserId="5" LastEditDate="2021-09-05T23:15:49.430" LastActivityDate="2021-09-06T11:19:16.873" Title="Phonon frequencies and free energy with respect to polymorphs" Tags="|vasp|phonons|phonopy|dfpt|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4389" PostTypeId="2" ParentId="4249" CreationDate="2021-02-21T20:19:40.530" Score="3" Body="&lt;p&gt;As known [1], the eigenvalues of the dynamical Hessian matrix represent the phonon frequencies, whereas the eigenvectors represent the particular atomic displacement patterns contributing to the vibrations. Therefore you might be interested in analyzing the eigenvectors and building the atomic visualizations based on them. In many cases (especially in the complex systems) you'll find out that the certain phonons are caused by the displacements only of the certain atoms. There are some tools online [2, 3, 4] illustrating this idea.&lt;/p&gt;&#xA;&lt;p&gt;Concerning your supercell construction, given the types of the atoms and the crystalline symmetry remains the same, your task is unfeasible, since you cannot &amp;quot;shift&amp;quot; the total phonon density of states to the lower frequencies for the same structure, irrelevant of the supercell chosen. However if you can vary the symmetry and the atomic content, this is possible.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;[1] see e.g. Maradudin, Theory of lattice dynamics in the harmonic&#xA;approximation, Academic, New York (1971)&lt;/li&gt;&#xA;&lt;li&gt;[2]&#xA;&lt;a href=&quot;https://www.materialscloud.org/work/tools/interactivephonon&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.materialscloud.org/work/tools/interactivephonon&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;[3]&#xA;&lt;a href=&quot;http://crysplot.crystalsolutions.eu/web_pages_yves3/vibration.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://crysplot.crystalsolutions.eu/web_pages_yves3/vibration.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;[4] &lt;a href=&quot;https://www.crystal.unito.it/animations-of-vibrational-modes.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.crystal.unito.it/animations-of-vibrational-modes.php&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1750" LastActivityDate="2021-02-21T20:19:40.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4390" PostTypeId="1" AcceptedAnswerId="4391" CreationDate="2021-02-22T06:50:01.293" Score="8" ViewCount="858" Body="&lt;p&gt;I am trying to use a program such as Vesta or Avogadro to build a super cell from a .cif file for a molecular crystal. In neither program can I seem to figure out how to order the output of the coordinates. For example, I would like atom1-molecule1, atom2-molecule1, atom3-molecule1, followed by atom1-molecule2, atom2-molecule2, atom3-molecule2, etc., but I cannot seem to do so. How do I do this? It seems I can sort by x, y, z, or element type, but not by molecule, which I don't understand. If not with these tools, is there some other one to use?&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorDisplayName="user2026" LastEditDate="2021-02-22T06:55:19.540" LastActivityDate="2021-02-22T16:16:24.067" Title="Extracting the coordinates of a super cell in Vesta or Avogadro" Tags="|vesta|cif|avogadro|supercell|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4391" PostTypeId="2" ParentId="4390" CreationDate="2021-02-22T07:25:06.023" Score="6" Body="&lt;p&gt;One option is to use the Atomic Simulation Environment's &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html#ase.build.sort&quot; rel=&quot;noreferrer&quot;&gt;sort function&lt;/a&gt;. The function &lt;code&gt;ase.build.sort()&lt;/code&gt; takes a required &lt;code&gt;Atoms&lt;/code&gt; object (e.g. the supercell of the original CIF) and an optional &lt;code&gt;tags&lt;/code&gt; argument that allows you to sort however you wish. It's then just up to you to find out how to flag each individual molecule in the order that you'd like.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-02-22T07:25:06.023" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4392" PostTypeId="1" AcceptedAnswerId="4393" CreationDate="2021-02-22T07:26:27.050" Score="12" ViewCount="1130" Body="&lt;p&gt;As the title suggests, my question is fundamental - How reliable are the total energy values from Kohn-Sham Density Functional Theory, and why. I acknowledge that absolute values of energies are useless, but relative values are often used to compute several quantities across different applications. For instance:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Atomization Energies - For a simple molecule AB, the atomization energy can be calculated directly from &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt; - &lt;span class=&quot;math-container&quot;&gt;$E_{A}$&lt;/span&gt; - &lt;span class=&quot;math-container&quot;&gt;$E_{B}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Magnetic materials - Difference of total energy values for systems in different spin configurations (say FM and AFM), can indicate which magnetic configuration is more stable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;To word my question differently: There are many more applications where total energies are used. What I find weird is many research works rarely delve into the validity of this quantity. &lt;strong&gt;Why is one able to do this?&lt;/strong&gt; Note: I also acknowledge that there might be functional-dependent errors in calculation of these quantities, but my question is not about that. Instead, my question is more generic.&lt;/p&gt;&#xA;" OwnerUserId="770" LastEditorUserId="5" LastEditDate="2021-02-22T14:57:09.963" LastActivityDate="2021-03-19T10:15:42.850" Title="Total energy from KS-DFT: How reliable is it and why?" Tags="|density-functional-theory|kohn-sham|functional|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4393" PostTypeId="2" ParentId="4392" CreationDate="2021-02-22T11:19:46.710" Score="13" Body="&lt;p&gt;The main issue here is that the calculated energy is a potential energy, that's why the absolute value is useless.&#xA;As potential energy always depends on a reference system, you can only use the absolute value in comparison (as you do the calculations using exactly the same conditions) or in quantities that are obtained by substractions of these energies like binding energies or the examples you gave.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-02-22T11:19:46.710" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4394" PostTypeId="1" AcceptedAnswerId="4402" CreationDate="2021-02-22T15:19:47.077" Score="7" ViewCount="2301" Body="&lt;p&gt;I want to run molecular dynamics (MD) simulations with VASP for Mg2Si to investigate the simulation time vs &lt;code&gt;ENCUT&lt;/code&gt; and &lt;code&gt;KPOINTS&lt;/code&gt;, but I do not know how to set INCAR tags for example for the first run if &lt;code&gt;ENCUT&lt;/code&gt; = 500 eV with 100fs time then should I change the value of &lt;code&gt;ENCUT&lt;/code&gt; and time for the second run? What parameters of &lt;code&gt;INCAR&lt;/code&gt; will remain the same to compare &lt;code&gt;ENCUT&lt;/code&gt; with simulation time and to get one plot of energy convergence? If the first run goes well should I change my &lt;code&gt;POSCAR&lt;/code&gt; too for the second run as input?&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-02-23T01:50:28.583" LastActivityDate="2021-02-23T07:26:20.373" Title="Molecular Dynamics Simulations in VASP" Tags="|vasp|molecular-dynamics|ab-initio-calculations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4395" PostTypeId="2" ParentId="4390" CreationDate="2021-02-22T16:16:24.067" Score="3" Body="&lt;p&gt;This is in Avogadro 1.2.0. I will check behavior on Avogadro 2 later:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;File -&amp;gt; Open -&amp;gt; &lt;em&gt;Choose your cif file&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;Build -&amp;gt; Super Cell Builder -&amp;gt; &lt;em&gt;Choose the number of repeats&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;File -&amp;gt; Save As -&amp;gt; &lt;em&gt;Choose desired file type (XYZ and PDB work. Avogadro 1.2.0 seems to lock up on my system when I try to write mol2 files by this procedure.&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I would guess that maybe you tried this already, so maybe there is some problem with related to the cif file you are using. If the above doesn't work, maybe you could try with another cif file.&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2021-02-22T16:16:24.067" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4396" PostTypeId="2" ParentId="1472" CreationDate="2021-02-22T16:30:12.183" Score="4" Body="&lt;p&gt;This response comes late, but I hope you or other readers will find it useful.&#xA;Regarding your question on how to derive MCTDH equations (directly) from the time-dependent Schrödinger equation (SE), I would add the following comments.&lt;/p&gt;&#xA;&lt;p&gt;The SE is exact in the full Hilbert space, but for numerical simulations, you need to choose a finite (usually small) working subspace, which is imposed by the form of your ansatz. Since the solution of the SE lies in the full Hilbert space, you cannot generally solve the SE in this working subspace. This means that the coupled MCTDH equations are not equivalent to the SE, and cannot be derived unambiguously from the SE.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can minimize the error of your approximate solution with respect to the parameters used in your ansatz. The time-dependent variational principle (TDVP) is the tool that does that by projecting the SE error on the correct tangent space.&#xA;Therefore, one must distinguish between the exact SE and its approximate version coming out of the TDVP, and I believe the answer to your question is in the application of the TDVP.&lt;/p&gt;&#xA;&lt;p&gt;The projection done by the TDVP is otherwise equivalently achieved using a linear projection of the SE only when the parameterization is &amp;quot;linear&amp;quot;, as it is the case for the time-dependent parameters &lt;span class=&quot;math-container&quot;&gt;$a_{j_1⋯j_n}$&lt;/span&gt; (the expansion coefficients in the basis of the configurations). Hence, your comment on eq.4 being &amp;quot;derived simply by projection&amp;quot;.&#xA;However, the projection is more complicated for a &amp;quot;non-linear&amp;quot; parameterization, and MCTDH employs such a non-linear parameterization in the expression of the time-dependent SPFs. Hence, the resulting equation of motion for the SPFs are not simple projections of the SE but are obtained using the TDVP.&lt;/p&gt;&#xA;&lt;p&gt;Thus, the answer to your question would be that MCTDH equations cannot be derived directly from the SE. You need to use the SE in combination with the TDVP to correctly project on the tangent space corresponding to your ansatz. I hope this answer helps you, and if you are interested in more details, I suggest you the following documents to read:&lt;/p&gt;&#xA;&lt;p&gt;P. Kramer, M. Saraceno: Geometry of the Time-Dependent Variational Principle in Quantum Mechanics (1981)&lt;/p&gt;&#xA;&lt;p&gt;A. Raab: Chem. Phys. Lett. 319, 674 (2000)&lt;/p&gt;&#xA;&lt;p&gt;L. Hackl, T. Guaita, T. Shi, J. Haegeman, E. Demler et al.: arXiv:2004.01015 (2020)&lt;/p&gt;&#xA;" OwnerUserId="2127" LastActivityDate="2021-02-22T16:30:12.183" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4397" PostTypeId="2" ParentId="127" CreationDate="2021-02-22T16:34:49.770" Score="4" Body="&lt;p&gt;You are making an approximation by including the semicore states in the pseudopotential. Like the name suggests, semicore states aren't really core states; they lie higher up in energy so they may not always be spectators.&lt;/p&gt;&#xA;&lt;p&gt;To decide whether to include the semicore states, you should compare the results of calculations with and without the semicore states in the valence. If both procedures lead to the same result, this means the semicore states don't play an important role in your study. If including the semicore states changes the results, it means that you should include them in the calculation, since the frozen-core approximation does not hold for them.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-22T16:34:49.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4398" PostTypeId="2" ParentId="1471" CreationDate="2021-02-22T19:06:45.497" Score="5" Body="&lt;p&gt;I believe that Eq.13 of the same reference is the construction you are asking about. Since MCTDH is an initial value problem, you have to construct the SPFs at the initial time by choosing the initial value of the time-dependent coefficients &lt;span class=&quot;math-container&quot;&gt;$a^{(\kappa)}_{kj}$&lt;/span&gt; and then MCTDH will propagate these coefficients.&#xA;Then your question becomes &amp;quot;how to construct the SPFs at initial time?&amp;quot;, which is up to you when you choose your initial condition.&lt;/p&gt;&#xA;&lt;p&gt;The only constraint is that you need to choose the coefficients so that the SPFs are initially orthonormalized (the MCTDH propagation retains the orthonormalization).&#xA;This amounts to choose the coefficients such that&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{1}&#xA;\sum_{lm}(a^{(\kappa)}_{lj})^*\langle \chi^{(\kappa)}_l | \chi^{(\kappa)}_m \rangle a^{(\kappa)}_{mk}=\delta_{jk},&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\delta_{jk}$&lt;/span&gt; is the Kronecker delta.&#xA;If the primitive basis is already orthonormal, &lt;span class=&quot;math-container&quot;&gt;$\langle \chi^{(\kappa)}_l | \chi^{(\kappa)}_m \rangle=\delta_{lm}$&lt;/span&gt;, the coefficients just represent an ensemble of orthonormalized vectors, but if the primitive basis is not orthonormal, you will have to use your favorite orthonormalization scheme (e.g. Gram–Schmidt or using a singular value decomposition among others).&lt;/p&gt;&#xA;&lt;p&gt;The initial wavefunction is very often chosen as a single Hartree product of physically &amp;quot;meaningful&amp;quot; SPFs, where the &amp;quot;meaningful&amp;quot; part comes from what you want to achieve with your propagation (e.g. a product of 1-dimensional Gaussian functions).&#xA;Another possibility is to use the eigenstate of some other operator (e.g. a zeroth order Hamiltonian), which could be obtained from a previous MCTDH calculation (e.g. a relaxation).&lt;/p&gt;&#xA;&lt;p&gt;So, the answer is that the construction is up to your initial conditions as long as you make sure that the SPFs are initially orthonormalized.&#xA;I would recommend reading chapter 3 and 5 of the following book:&lt;/p&gt;&#xA;&lt;p&gt;H.-D. Meyer, F. Gatti, G. A. Worth: Multidimensional Quantum Dynamics (2009)&lt;/p&gt;&#xA;&lt;p&gt;or the following review, which can be found at the website of the MCTDH developers (&lt;a href=&quot;https://www.pci.uni-heidelberg.de/cms/mctdh.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;pci.uni-heidelberg.de/cms/mctdh.html&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;M. H. Beck, A. Jäckle, G. A. Worth, H.-D. Meyer: Phys. Rep. 324, 1 (2000)&lt;/p&gt;&#xA;&lt;p&gt;I hope this message answers your question.&lt;/p&gt;&#xA;" OwnerUserId="2127" LastEditorUserId="5" LastEditDate="2021-02-22T19:40:18.010" LastActivityDate="2021-02-22T19:40:18.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4399" PostTypeId="2" ParentId="4392" CreationDate="2021-02-22T19:23:08.307" Score="10" Body="&lt;p&gt;Your question is on absolute energies, but all of your physical examples are relative energies. One could also add properties to the list; however, these are again not determined by the &lt;em&gt;total&lt;/em&gt; energy, but rather as its derivatives with respect to some perturbation... which are again energy differences, just now between the perturbed and unperturbed system. This means that lots of systematical errors in the absolute energy end up cancelling in most situations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-22T19:23:08.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4400" PostTypeId="1" AcceptedAnswerId="4409" CreationDate="2021-02-22T20:21:37.147" Score="17" ViewCount="2125" Body="&lt;p&gt;My question is inspired by &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4324/how-does-static-correlation-differ-from-fermi-correlation-and-how-does-dynamic&quot;&gt;this&lt;/a&gt; question and also &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4209/is-there-any-relation-between-static-correlation-and-finite-temperature-smearing&quot;&gt;this&lt;/a&gt; one. I have come across the term static correlation multiple times. &lt;em&gt;Introduction to Computational Chemistry&lt;/em&gt; by Frank Jensen describes static (or non-dynamic) correlation as:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The non-dynamical part is associated withelectrons avoiding each other on a more “permanent” basis, such as those occupying different spatial orbitals. The latter is also sometimes called a near-degeneracy effect, as it becomes important for systems where different orbitals (configurations) have similar energies.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have come across many other definitions. My understanding is that static correlation happens when HOMO and LUMO of a chemical species are close together, so that it cannot be represented by one Slater determinant. A Slater determinant, of course, represents one electron configuration, so it makes sense in a way that if the levels are close together, more than one electron configuration can become dominant.&lt;/p&gt;&#xA;&lt;p&gt;But I cannot understand what it physically means. Let's say we have a molecule A which has static correlation effects and it has two dominant configurations. So, would that mean that some A molecules are in one electronic configuration and the other A molecules are in another configuration at one moment? Or does it mean that each A molecule exists as a mix of the two configurations?&lt;/p&gt;&#xA;&lt;p&gt;The first concept I can wrap my head around, but the second one confuses me. If a molecule is a mix of two configurations, then how do we calculate its spin multiplicity (I think CASSCF calculations in Orca print out spin)? How would we calculate ionization energies, if the electron is present in different orbitals simultaneosuly? Are orbital occupation numbers fractional? And finally, what does Frank Jensen mean when he says electrons avoid each other on a &amp;quot;permanent&amp;quot; basis?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-02-25T18:21:07.257" Title="What is static correlation, actually?" Tags="|electron-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4401" PostTypeId="2" ParentId="4360" CreationDate="2021-02-22T22:16:55.940" Score="6" Body="&lt;p&gt;Yes, you can! In the Quantum ESPRESSO input file, in the &amp;quot;ATOMIC_POSITIONS&amp;quot; card, you have to present the atom name and its coordinates, something like:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ATOMIC_POSITIONS {crystal}&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Atom_name  x_atom  y_atom  z_atom&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There are three default variables: if_pos(1), if_pos(2), and if_pos(3) set to unity, acting as weights for the force. So to keep the atomic position unchanged during the relaxation process, change them to zero (for the atoms you want to keep still). Something like this:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ATOMIC_POSITIONS {crystal}&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Atom_name  x_atom  y_atom  z_atom 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="389" LastEditorUserId="389" LastEditDate="2021-02-22T23:12:19.970" LastActivityDate="2021-02-22T23:12:19.970" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4402" PostTypeId="2" ParentId="4394" CreationDate="2021-02-23T01:46:50.767" Score="3" Body="&lt;h2&gt;MD input card for H2O molecule:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt; # General tags&#xA; PREC   = Normal    &#xA; ENCUT  = 400   &#xA; ALGO   = Fast  &#xA; LREAL  = Auto  &#xA; ISMEAR = 0         # Gaussian smearing &#xA; SIGMA  = 0.05      &#xA; ISYM   = 0         # Symmetry off  &#xA;&#xA; # MD related   &#xA; IBRION = 0         # MD    &#xA; POTIM  = 0.5       # Time step=0.5 fs&#xA; NSW    = 100       # Number of ionic steps &#xA; TEBEG  = 400       # Start temperature         &#xA; TEEND  = 400       # Final temperature     &#xA; SMASS  = 0         # Canonical (Nose-Hoover) thermostat    &#xA; POMASS = 16.0  2.0 # Deuterium mass for Hydrogen   &#xA;&#xA; # Don’t write WAVECAR or CHGCAR    &#xA; LWAVE  = F     &#xA; LCHARG = F &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;KPOINTS card for H2O molecule:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt; KPOINTS (Gamma-only)   &#xA;  0 &#xA; Gamma  &#xA; 1  1   1   &#xA; 0  0   0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ref1: &lt;a href=&quot;https://wiki.bnl.gov/CFN-Computation/images/3/3f/Tutorial6.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.bnl.gov/CFN-Computation/images/3/3f/Tutorial6.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Ref2: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/H2O_molecular_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/H2O_molecular_dynamics&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Ref3: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Standard_MD&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Standard_MD&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-23T07:26:20.373" LastActivityDate="2021-02-23T07:26:20.373" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4403" PostTypeId="1" AcceptedAnswerId="4404" CreationDate="2021-02-23T11:09:38.133" Score="13" ViewCount="539" Body="&lt;p&gt;I’m planning to run a calculation of single electron transfer where my system goes from singlet to triplet biradical (presumably). So I’m wondering how to decide if I need to use milticonfigurational methods (as biradicals are often considered multirefernce systems) or not.&lt;/p&gt;&#xA;&lt;p&gt;I have seen this question which talks about how to determine &lt;em&gt;a priori&lt;/em&gt; whether or not something has multireference character: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/19/5&quot;&gt;How to determine, a priori, whether a compound has multireference character?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In my case, I'm willing to do a bit of work (not just an &lt;em&gt;a priori&lt;/em&gt; estimation), and the only thing I could think of is running something like MCSCF and see if other configurations have any substantial weight or not (here comes the problem of choosing the right active space).&lt;/p&gt;&#xA;&lt;p&gt;The other approach I'm thinking of is finding minimal energy crossing point (MECP) using DFT for singlet (before electron transfer) and triplet (after electron transfer) states, which is more black-box approach.&lt;/p&gt;&#xA;&lt;p&gt;So, which way is more correct and methodologically appropriate?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-02-23T20:21:24.533" LastActivityDate="2021-02-23T20:21:24.533" Title="What is a good practical way to determine whether or not I need to use a multiconfigurational method?" Tags="|ab-initio-calculations|electronic-structure|quantum-chemistry|coupled-cluster|multi-reference|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4404" PostTypeId="2" ParentId="4403" CreationDate="2021-02-23T20:19:27.180" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;which way is more correct and methodologically appropriate?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Nothing is more &amp;quot;correct&amp;quot; or less correct, but there's certainly advantages and disadvantages. MCSCF calculations such as CASSCF calculations, can take a bit more mental energy if you want to make sure your active space is appropriate, but on the other hand, the result could be much more reliable than a black-box approach using DFT.&lt;/p&gt;&#xA;&lt;p&gt;There is a third way which is perhaps better though. My default procedure for testing multiconfigurationality is to use &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;noreferrer&quot;&gt;FCIQMC&lt;/a&gt;: We can put a population of walkers on the Hartree-Fock determinant and then let the simulation run, and &lt;em&gt;within seconds&lt;/em&gt; that population of walkers will spread to the other dominant configurations. We can then stop the calculation and see the populations on each determinant, and then decide things in the same way that you were suggesting, but we never needed to define an active space. The procedure is completely black-box. Another way to do this is using the HCI (heat-bath configuration interaction) approach instead of FCIQMC, or HCI can even be used as the excitation generator for the FCIQMC calculation.&lt;/p&gt;&#xA;&lt;p&gt;However, you might not have an FCIQMC or HCI code installed yet, and maybe you want to use software with which you're already comfortable and familiar. In that case you can just do a coupled cluster calculation and look at the T1 diagnostic.  First of all, if it's unusually difficult to converge the coupled cluster calculation, it can be because the system is multiconfigurational. If it's not too hard to converge the calculation but the T1 diagnostic is large, it is a sign that the system is not well represented by the dominant single configuration. A guideline is given in &lt;a href=&quot;https://cefrc.princeton.edu/sites/cefrc/files/Files/2010%20Lecture%20Notes/Stephen%20Klippenstein/SJK-Wed-Lecture.pdf&quot; rel=&quot;noreferrer&quot;&gt;this PDF lecture&lt;/a&gt; where it is suggested that the T1 diagnostic should be &amp;lt;0.02 for closed shell systems, &amp;lt;0.03 for radicals, and anything &amp;gt;0.06 is a &amp;quot;catastrophe&amp;quot; for single-configurational methods like coupled cluster. The T1 diagnostic is usually written after a black-box coupled cluster calculation, and if it's not, you can instead look at the cluster amplitudes and decide multiconfigurationality in the same way you were considering to do it with an MCSCF calculation (the crucial difference being that you don't have to choose an active space for standard coupled cluster calculations, and the process is usually quite fast and black-box unless the molecule is too big, but if it's too big then your MCSCF calculation won't be very easy either).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-23T20:19:27.180" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4405" PostTypeId="1" CreationDate="2021-02-23T23:16:38.153" Score="12" ViewCount="174" Body="&lt;p&gt;From the literature as well as the answer to the question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4377/what-is-the-meaning-of-energy-consistent-and-shape-consistent-in-the-context-of?noredirect=1#comment7639_4377&quot;&gt;What is the meaning of energy-consistent and shape-consistent in the context of pseudopotentials?&lt;/a&gt; I can see that the key difference between these two types of pseudopotential is based on how they are fitted.&lt;/p&gt;&#xA;&lt;p&gt;I can also see that energy consistent pseudopotentials provide more accurate information concerning the energy of the atoms/molecules however shape consistent ones are a lot easier to construct. Additionally, it seems that that energy consistent are also shape-consistent but the reverse is not necessarily true.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering if anyone knew of any more advantages/disadvantages of these types of pseudopotentials.  If one could elaborate on the typical circumstances when one pseudopotential may be preferable to the other that would also be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-02-24T03:26:19.917" LastActivityDate="2021-02-25T19:20:25.503" Title="What are some of the advantages and disadvantages when using shape consistent pseudopotentials as compared to energy consistent pseduopotentials" Tags="|molecular-modeling|electronic-structure|quantum-chemistry|pseudopotentials|relativistic|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4407" PostTypeId="1" AcceptedAnswerId="4411" CreationDate="2021-02-24T05:49:26.343" Score="12" ViewCount="196" Body="&lt;p&gt;I was reading &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.111.073003&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; which basically outlines the two main types of errors that one encounters in Kohn-Sham DFT : Density-based errors and Functional-based errors. I understand the practical differences between these two: The former refers to the case where the electron density generated through the self-iterative process, is one of poor quality. The latter is just a reflection of the fact that in practice, we sort to approximate functionals and this can lead to errors. My doubt is regarding how one could pin down the nature of error in a DFT calculation. Let us confine ourselves to analyzing the functional error. From what I gather, this seems to be the general procedure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Perform an SCF calculation for a system with a given functional (say for example, LDA)&lt;/li&gt;&#xA;&lt;li&gt;Fix the charge density from the LDA calculation, but now use a different functional (say, PBE) and do another SCF calculation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If one observes qualitatively different results between these two steps, then it should imply that the error is inherently functional-based. This is because in one case we perform LDA calculations with the LDA density and in the other, PBE calculations with the LDA density.&lt;/p&gt;&#xA;&lt;p&gt;My doubt is as follows: How are these two cases different putting into context the H-K theorems? One of the H-K theorems state that the ground state energy is a unique functional of the density. Doesn't this mean that fixing a density is equivalent to fixing the potential?&lt;/p&gt;&#xA;&lt;p&gt;I'm looking forward to your inputs on this.&lt;/p&gt;&#xA;" OwnerUserId="770" LastActivityDate="2021-02-25T18:38:05.780" Title="Procedure to classify errors in Kohn-Sham DFT" Tags="|density-functional-theory|kohn-sham|functional|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4408" PostTypeId="2" ParentId="4407" CreationDate="2021-02-24T11:32:02.883" Score="7" Body="&lt;p&gt;Let's assume you calculated the density, &lt;span class=&quot;math-container&quot;&gt;$\rho,$&lt;/span&gt; 100% correctly.&lt;/p&gt;&#xA;&lt;p&gt;Now, you have the task to &amp;quot;correlate&amp;quot; it with the energy. This correlation is the functional &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's suppose that the unknown best functional is &lt;span class=&quot;math-container&quot;&gt;$F[\rho]=a \times \rho^\alpha + b \times \rho^\beta$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you are using &lt;span class=&quot;math-container&quot;&gt;$E[\rho] = a \times \rho^\alpha + b \times \rho^\gamma$&lt;/span&gt; your calculations has an error due to the difference between the parameter &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, the challenge is not only to calculate the density correctly but also known the correct functional that relate both quantities. Only in this paper&lt;sup&gt;1&lt;/sup&gt;, they used 83 functionals!&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;em&gt;A look at the density functional theory zoo with the advanced GMTKN55 database for general main group thermochemistry, kinetics and noncovalent interactions&lt;/em&gt;. Goerigk, L., &lt;em&gt;et al.&lt;/em&gt; Phys. Chem. Chem. Phys., 2017,19, 32184-32215 (doi: &lt;a href=&quot;https://doi.org/10.1039/C7CP04913G&quot; rel=&quot;noreferrer&quot;&gt;10.1039/C7CP04913G&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-02-24T11:32:02.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4409" PostTypeId="2" ParentId="4400" CreationDate="2021-02-25T18:21:07.257" Score="12" Body="&lt;p&gt;We know that the many-electron wave function has to be antisymmetric with respect to the exchange of two electrons:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\Psi (x_1,x_2,\dots,x_i,\dots,x_j,\dots)=-\Psi (x_1,x_2,\dots,x_j,\dots,x_i,\dots)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This symmetry is satisfied by Slater determinants a.k.a. electron configurations, so the wave function can be written in terms of them as&#xA;&lt;span class=&quot;math-container&quot;&gt;$|\Psi\rangle = \sum_I C_I |I\rangle$&lt;/span&gt;. Since determinants are orthonormal, &lt;span class=&quot;math-container&quot;&gt;$\langle I | J \rangle = \delta_{IJ}$&lt;/span&gt;, the wave function is normalized if &lt;span class=&quot;math-container&quot;&gt;$\sum_I C_I^2 =1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Each Slater determinant is defined by a set of orbitals that are occupied. The orbital basis can be chosen in many ways, but Hartree-Fock orbitals are a traditional choice. The Hartree-Fock determinant is the one where you occupy the orbitals with the lowest orbital energies; the orbitals themselves are defined by minimizing the expectation energy for the wave function.&lt;/p&gt;&#xA;&lt;p&gt;One can also build more sophisticated wave functions on top of the Hartree-Fock reference as&#xA;&lt;span class=&quot;math-container&quot;&gt;$|\Psi\rangle = C_0 |0\rangle + \sum_S C_S |S\rangle + \sum_D C_D |D\rangle + \sum_T C_T |T\rangle + \dots $&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$|0\rangle$&lt;/span&gt; is the Hartree-Fock determiant, and S, D, T denote singly, doubly, and triply excited determinants from the Hartree-Fock reference determinant. This approach is called configuration interaction theory. If you only include singles and doubles, you get configuration interaction singles and doubles (CISD); if you include all excitations, you have full configuration interaction (FCI). You can also only include excitations within a subset of the orbitals; this gives you the complete active space (CAS) model.&lt;/p&gt;&#xA;&lt;p&gt;In cases where the wave function is single reference, i.e., &lt;span class=&quot;math-container&quot;&gt;$C_0 \approx 1 \iff C_0^2 \gg \sum_{I&amp;gt;0} C_I^2$&lt;/span&gt; &lt;strong&gt;in the exact i.e. FCI wave function&lt;/strong&gt;, the Hartree-Fock reference is qualitatively correct, and you can compute very accurate wave functions with e.g. the coupled cluster method.&#xA;In contrast, cases where &lt;span class=&quot;math-container&quot;&gt;$C_0$&lt;/span&gt; is not large are known as multireference a.k.a. strongly correlated a.k.a. systems dominated by static correlation. Here, the electronic configurations become entangled either via small energy gaps &lt;strong&gt;or large exchange integrals&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A standard example is the Cr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule - a poster child for strongly correlated systems - where &lt;span class=&quot;math-container&quot;&gt;$C_0 \approx 10^{-4}$&lt;/span&gt; for the Hartree-Fock wave function, so Hartree-Fock orbitals are spectacularly bad. Taking the orbitals from density functional calculations often lead to much better results; for Cr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; IIRC one gets something like &lt;span class=&quot;math-container&quot;&gt;$C_0 \approx 0.6$&lt;/span&gt;, which is still very strongly correlated. Examining the nature of the correlations via a cluster decomposition reveals that the correlations in Cr&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; are highly non-trivial; see  &lt;a href=&quot;https://doi.org/10.1063/1.4996044&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 147, 154105 (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note that instead of taking the orbitals from Hartree-Fock or density functional calculations, the &amp;quot;correct&amp;quot; way is to relax the orbitals for the used many-electron wave function, instead. For CAS this gives the CAS self-consistent field method, CASSCF, which can be contrasted to &amp;quot;single-point&amp;quot; CAS-CI calculations at fixed orbitals.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Let's say we have a molecule A which has static correlation effects and it has two dominant configurations. So, would that mean that some A molecules are in one electronic configuration and the other A molecules are in another configuration at one moment? Or does it mean that each A molecule exists as a mix of the two configurations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This means that the many-electron wave function for molecule A will be a superposition of the two configurations: &lt;span class=&quot;math-container&quot;&gt;$|\Psi\rangle = C_1 |1\rangle + C_2 |2\rangle$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$|C_1| \gg 0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|C_2| \gg 0$&lt;/span&gt;. You may even have &lt;span class=&quot;math-container&quot;&gt;$|C_1| = 2^{-1/2} = |C_2|$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If a molecule is a mix of two configurations, then how do we calculate its spin multiplicity (I think CASSCF calculations in Orca print out spin)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The spin multiplicity is actually trivial: the Hamiltonian commutes with &lt;span class=&quot;math-container&quot;&gt;$\hat{S}_z$&lt;/span&gt;, so your two configurations 1 and 2 have to have the same multiplicity i.e. the same number of alpha electrons and beta electrons in order to mix in the wave function.&lt;/p&gt;&#xA;&lt;p&gt;The expectation value of the total spin, &lt;span class=&quot;math-container&quot;&gt;$\langle \hat{S}^2 \rangle$&lt;/span&gt; is more complicated. A proper eigenfunction satisfies &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2 \Psi_S = S(S+1) \Psi_S$&lt;/span&gt;, and it also has &lt;span class=&quot;math-container&quot;&gt;$2S+1$&lt;/span&gt; possible z projections: &lt;span class=&quot;math-container&quot;&gt;$\hat{S}_z \Psi_S = S_z \Psi_S$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$S_z \in [-S, -S+1, ..., S-1, S]$&lt;/span&gt;. Since you know the many-electron wave function, you can just go ahead and compute the value of &lt;span class=&quot;math-container&quot;&gt;$\langle \hat{S}^2 \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It is important to note that states with different  &lt;span class=&quot;math-container&quot;&gt;$\langle \hat{S}^2 \rangle$&lt;/span&gt; can appear in your calculation for a given &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt;: the state you get may not be the one you wanted! For instance, if you're looking for a singlet, you might get a quintet wave function instead!&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How would we calculate ionization energies, if the electron is present in different orbitals simultaneosuly?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Easy, just the way you would do it in any other method. You calculate the neutral molecule and its cation, and substract the total energies. For electron affinities you'd do the anion and the neutral.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Are orbital occupation numbers fractional?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is a bit tricky, since the one-electron density matrix may not even be diagonal! If you diagonalize the matrix, you get natural orbitals, and they do have fractional occupation numbers. But, orbitals don't really have much meaning when you go beyond the self-consistent field level of theory.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;And finally, what does Frank Jensen mean when he says electrons avoid each other on a &amp;quot;permanent&amp;quot; basis?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'm not sure what this is referring to; however, once you allow for multiple configurations in the wave function, you are also allowing the electrons more variational freedom.&lt;/p&gt;&#xA;&lt;p&gt;If you look at Hartree-Fock, the probability to find an electron at &lt;span class=&quot;math-container&quot;&gt;${\bf r}$&lt;/span&gt; and an electron of opposite spin at &lt;span class=&quot;math-container&quot;&gt;${\bf r}'$&lt;/span&gt; is independent of the distance &lt;span class=&quot;math-container&quot;&gt;$|{\bf r}-{\bf r}'|$&lt;/span&gt;. This means it is possible to find two electrons arbitrarily close together, even though the Coulomb interaction blows up. When you include more configurations, this probability decays when &lt;span class=&quot;math-container&quot;&gt;$|{\bf r}-{\bf r}'|$&lt;/span&gt; is small, that is, the electrons avoid each other. A similar argument also holds for same-spin electrons; however, the error in Hartree-Fock is much smaller in this case because of the Pauli exclusion principle, so same-spin correlation energy is very small compared to the opposite-spin correlation energy.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-25T18:21:07.257" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4410" PostTypeId="2" ParentId="4405" CreationDate="2021-02-25T18:24:03.013" Score="5" Body="&lt;p&gt;Shape consistent pseudopotentials are just commonly used for some reason, even though energy consistent pseudopotentials are &amp;quot;the right way to do it&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The reason why shape consistent pseudopotentials keep on being used is that the errors in the density functional approximations themselves are so large that the extra error from the pseudopotentials can be disregarded.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-25T18:24:03.013" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4411" PostTypeId="2" ParentId="4407" CreationDate="2021-02-25T18:38:05.780" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;From what I gather, this seems to be the general procedure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Perform an SCF calculation for a system with a given functional (say for example, LDA)&lt;/li&gt;&#xA;&lt;li&gt;Fix the charge density from the LDA calculation, but now use a different functional (say, PBE) and do another SCF calculation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This wouldn't be density-corrected DFT; this is just using the LDA orbitals as a guess for a self-consistent PBE calculation. What you want is to do a single-shot calculation i.e. evaluate the PBE functional with the LDA density, and contrast it to the value you get for PBE with an optimal electron density.&lt;/p&gt;&#xA;&lt;p&gt;Also, LDA and PBE are quite close, since they are both pure density functionals and thereby are both extremely prone to self-interaction errors. Instead, one typically compares self-consistent DFT to DFT evaluated with Hartree-Fock orbitals. The whole point of density-corrected DFT is that in some cases one can get much better results from density functional approximations if one just uses a better density.&lt;/p&gt;&#xA;&lt;p&gt;Hartree-Fock is often used as reference since it is free of self interaction. Alternatively, one can also use electron densities from higher-level ab initio methods than Hartree-Fock in case the Hartree-Fock density is far from correct.&lt;/p&gt;&#xA;&lt;p&gt;There are several more recenty papers from Burke and coworkers on the topic where some of your unclarities may be explained, e.g. &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.8b02855&quot; rel=&quot;noreferrer&quot;&gt;J. Phys. Chem. Lett. 9, 6385 (2018)&lt;/a&gt; and  &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.9b00826&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 6636 (2019)&lt;/a&gt;. A benchmark on the topic has also just been published by Jan Martin: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c01055&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput., in press (2021)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-02-25T18:38:05.780" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4412" PostTypeId="1" CreationDate="2021-02-25T19:08:14.957" Score="12" ViewCount="737" Body="&lt;p&gt;I've recently written a simple code to numerically compute the Hessian of some function (at a point). Most electronic structure packages will compute the Hessian and then project out the translations and rotations. I have tried to look up how one actually does this, but I can't find any good information really.&lt;/p&gt;&#xA;&lt;p&gt;I feel like this should be pretty simple, so I feel a bit silly for not knowing how to do it, but if someone can provide some mathematical detail on how to project out the translational and rotational modes, that would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-09-05T23:28:27.887" LastActivityDate="2021-09-06T05:55:00.313" Title="How does one project out the translations and rotations from a Hessian?" Tags="|electronic-structure|quantum-chemistry|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="4413" PostTypeId="2" ParentId="4405" CreationDate="2021-02-25T19:20:25.503" Score="6" Body="&lt;p&gt;The advantages and disadvantages are discussed in &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cphc.201100387&quot; rel=&quot;noreferrer&quot;&gt;this review paper&lt;/a&gt; which was cited in Susi Lehtola's answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1521/what-are-the-types-of-pseudopotentials/1588#1588&quot;&gt;What are the types of pseudopotentials?&lt;/a&gt; and then again in my answr to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4377/what-is-the-meaning-of-energy-consistent-and-shape-consistent-in-the-context-of/4378#4378&quot;&gt;What is the meaning of energy-consistent and shape-consistent in the context of pseudopotentials?&lt;/a&gt;. My quotes below will be from that review paper:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages of shape-consistent PPs:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;This technique has the disadvantage that it requires inversion of the&#xA;Fock equation to produce angular-momentum-dependent pseudopotentials,&#xA;resulting in a large number of Gaussian fitting functions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The author then mentions that this disadvantage can be overcome by directly fitting to the shape of the valence orbital, and such PPs are sometimes called &amp;quot;compact effective core potentials&amp;quot; or CEPs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages of shape-consistent PPs:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Shape-consistent pseudopotentials have the advantage that the fitting technique used is fast and efficient.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However the author then says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;energy-consistent pseudopotentials choosing a rather large valence spectrum in the fit procedure fulfil the shape-consistent requirement extremely well (not&#xA;necessarily vice versa) if the spectrum is accurately adjusted&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Final remarks:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As Susi's answer to the present question, and to this one: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1521/what-are-the-types-of-pseudopotentials/1588#1588&quot;&gt;What are the types of pseudopotentials?&lt;/a&gt;, says: energy-consistent PPs can fulfill the shape-consistent requirement very well while also providing accurate energies, whereas shape-consistent PPs may not provide accurate energies, so the best energy-consistent PPs will often be preferable for all-around accuracy over any &amp;quot;shape-consistent PP&amp;quot; in the literature.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-02-25T19:20:25.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4415" PostTypeId="1" AcceptedAnswerId="4416" CreationDate="2021-02-26T07:06:13.350" Score="12" ViewCount="3641" Body="&lt;p&gt;I want to do single point energy calculations in VASP for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt; so what should be initial steps to do? What are tags required in &lt;code&gt;INCAR&lt;/code&gt; sufficient to do this calculation?&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any help.&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="142" LastEditDate="2023-04-05T09:38:13.517" LastActivityDate="2023-04-05T09:38:13.517" Title="How to run single point energy calculation on Mg2Si in VASP" Tags="|vasp|software-input-file-request|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4416" PostTypeId="2" ParentId="4415" CreationDate="2021-02-26T07:27:38.770" Score="12" Body="&lt;p&gt;I assume that you have relaxed your geometry structure. The single point energy calculation also called the self-consistent field calculation (SCFC), the central quantities outputted by it are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Total energy&lt;/li&gt;&#xA;&lt;li&gt;Charge density&lt;/li&gt;&#xA;&lt;li&gt;Wavefunction&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In particular, the charge density and the wavefunction are the two key quantities to perform non-self-consistent calculations, such as band structure, the density of states so on.&lt;/p&gt;&#xA;&lt;p&gt;A general &lt;code&gt;INCAR&lt;/code&gt; for SCF in VASP can be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    System=:&#xA;    ISTART=0        #startjob: 0-new 1-cont 2-samecut&#xA;    ICHARG=2        #charge: 1-file 2-atom 10-const&#xA;    ENCUT=450       #energy cutoff in eV&#xA;    EDIFF=1E-5      #stopping-criterion for electronic upd.&#xA;    NELM=300        #nr. of electronic steps&#xA;    ISMEAR=0        #part. occupancies: -5 Blochl -4-tet -1-fermi 0-gaus 0 MP&#xA;    SIGMA=0.01      #broadening in eV -4-tet -1-fermi 0-gaus&#xA;    IALGO=38        #algorithm&#xA;    #LREAL=Auto     #Auto for large cell, False for small cell&#xA;&#xA;    #Magnetic and SOC related tags&#xA;    #ISPIN=2              #spin polarized calculation (2-yes 1-no)&#xA;    #MAGMOM=15*0 17*0     #initial magnetization&#xA;    #LSORBIT=.TRUE.       #switches on SOC and sets LNONCOLLINEAR= .TRUE.&#xA;    #SAXIS= 0 0 1         #quantisation axis for spin&#xA;    #ISYM=0               #symmetry: 0-nonsym 1-usesym&#xA;&#xA;    Output:&#xA;    LCHARG=.True.         #create CHGCAR&#xA;    LWAVE=.True.          #create WAVECAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you want firstly to relax the structure, you should add the following tags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   #Dynamic:&#xA;   ISIF=3&#xA;   IBRION=2&#xA;   NSW=300 &#xA;   EDIFFG=-0.005&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can check the meaning of each tag in &lt;code&gt;INCAR&lt;/code&gt; from &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;noreferrer&quot;&gt;vaspwiki&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-02-26T12:00:00.880" LastActivityDate="2021-02-26T12:00:00.880" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4417" PostTypeId="1" AcceptedAnswerId="4419" CreationDate="2021-02-26T10:03:36.303" Score="7" ViewCount="1838" Body="&lt;p&gt;I have created a band structure for 3x3x1 doped-supercell using &lt;code&gt;VASP&lt;/code&gt;, and I obtained the figure below. Now I want to do band-unfolding. What are the simplest ways to do that ?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/pQU4X.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pQU4X.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-02-26T10:36:51.380" LastActivityDate="2021-02-26T11:28:26.697" Title="How to perform band-structure unfolding in VASP?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4418" PostTypeId="2" ParentId="4417" CreationDate="2021-02-26T11:08:42.433" Score="6" Body="&lt;h3&gt;BandUP: Band Unfolding code for Plane-wave based calculations&lt;/h3&gt;&#xA;&lt;p&gt;This software can help you. From the developers site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;BandUP is a code that allows you to obtain a primitive cell representation of the band structure of systems simulated using supercells. The unfolding of the bands is performed as described in the following papers:&lt;/p&gt;&#xA;&lt;p&gt;Paulo V. C. Medeiros, Sven Stafström and Jonas Björk, &lt;a href=&quot;http://dx.doi.org/10.1103/PhysRevB.89.041407&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B 89,&#xA;041407(R) (2014)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Paulo V. C. Medeiros, Stepan S. Tsirkin, Sven Stafström and Jonas&#xA;Björk, &lt;a href=&quot;http://dx.doi.org/10.1103/PhysRevB.91.041116&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. B 91, 041116(R) (2015)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Information about the code: &lt;a href=&quot;http://www.ifm.liu.se/theomod/compphys/band-unfolding/&quot; rel=&quot;noreferrer&quot;&gt;http://www.ifm.liu.se/theomod/compphys/band-unfolding/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And source code ready to download: &lt;a href=&quot;https://github.com/band-unfolding/bandup&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/band-unfolding/bandup&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-02-26T11:08:42.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4419" PostTypeId="2" ParentId="4417" CreationDate="2021-02-26T11:28:26.697" Score="7" Body="&lt;p&gt;From the &lt;span class=&quot;math-container&quot;&gt;$3 \times 3 \times 1$&lt;/span&gt; supercell and the &lt;span class=&quot;math-container&quot;&gt;$\Gamma-M-K-\Gamma$&lt;/span&gt; path, I assume that you are investigating the band structure of a two-dimensional material with a hexagonal structure. Therefore, maybe the simplest way that you can follow immediately is using the &lt;a href=&quot;https://vaspkit.com/index.html&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT&lt;/a&gt; package.&lt;/p&gt;&#xA;&lt;p&gt;Coincidently, the example tutorial is about monolayer MoS2: &lt;a href=&quot;https://vaspkit.com/tutorials.html#band-unfolding&quot; rel=&quot;noreferrer&quot;&gt;https://vaspkit.com/tutorials.html#band-unfolding&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-26T11:28:26.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4420" PostTypeId="2" ParentId="3849" CreationDate="2021-02-26T14:44:07.520" Score="7" Body="&lt;p&gt;Keep in mind that many if not most proteins have multiple quasi-stable conformations, so their 3D structure is not actually a single conformation but rather a Markov matrix of conformations, with probabilities of a given conformation and probabilities of transition from each conformation to its neighbors varying according to temperature, pH, and other factors.&lt;/p&gt;&#xA;" OwnerUserId="2139" LastActivityDate="2021-02-26T14:44:07.520" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4421" PostTypeId="1" AcceptedAnswerId="4422" CreationDate="2021-02-27T11:57:01.500" Score="11" ViewCount="725" Body="&lt;p&gt;I want to investigate the comparison of Total Energy per cell with respect to the number of &lt;code&gt;KPOINTS&lt;/code&gt; in the irreducible part of the Brillouin zone but I do not know how to calculate the number of &lt;code&gt;KPOINTS&lt;/code&gt; with grid size for e.g  3* 3 *3 what will be no. of &lt;code&gt;KPOINTS&lt;/code&gt; for even or odd no. of k-mesh?&lt;/p&gt;&#xA;&lt;p&gt;Thanks for the help!&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-19T10:20:52.257" LastActivityDate="2021-03-19T10:20:52.257" Title="Number of KPOINTS in irreducible part of Brillouin zone" Tags="|vasp|k-points|brillouin-zone|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4422" PostTypeId="2" ParentId="4421" CreationDate="2021-02-27T12:58:49.790" Score="11" Body="&lt;p&gt;It is not necessary to care about the total energy versus the number of k points in irreducible reciprocal space, which is closely related to the symmetry of the investigated structure. Of course, you can always read it from &lt;code&gt;IBZKPT&lt;/code&gt; with a self-consistent run or any other run using VASP. Also, the printed number in &lt;code&gt;IBZKPT&lt;/code&gt; is related to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISYM&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ISYM&lt;/code&gt;&lt;/a&gt; tag.&lt;/p&gt;&#xA;&lt;p&gt;I assume what you really care about is the total energy versus k-sampling. About the convergence tests with VASP, namely total energy versus cut-off energy and also versus k-sampling, I strongly suggest you to take a look at this tutorial: &lt;a href=&quot;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&quot; rel=&quot;noreferrer&quot;&gt;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-27T12:58:49.790" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4423" PostTypeId="2" ParentId="3882" CreationDate="2021-02-28T06:25:16.483" Score="5" Body="&lt;p&gt;So I've used Gaussian as it is one of the few codes that can calculate hyperpolarizability for a lot of DFT functionals.&lt;/p&gt;&#xA;&lt;p&gt;My input is very staightforward, hope it will help someone.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%NProcShared=24&#xA;%mem=192Gb&#xA;%Chk=optfreq.chk&#xA;#P B3LYP/Def2TZVP Opt Freq&#xA;&#xA; Optfreq&#xA;&#xA;0 1&#xA;*Here goes initial geometry*&#xA;&#xA;--Link1--&#xA;%NProcShared=24&#xA;%mem=192Gb&#xA;%OldChk=optfreq.chk&#xA;%Chk=polar.chk&#xA;#P M062X/aug-cc-pVDZ Guess=Read Geom=Checkpoint GFINPUT POP(Regular, NBO)  Polar&#xA;&#xA; Polar&#xA;&#xA;0 1&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-02-28T06:25:16.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4424" PostTypeId="2" ParentId="3834" CreationDate="2021-02-28T10:32:43.503" Score="7" Body="&lt;h3&gt;Cut a surface with ASE:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;  from ase.io import read,write&#xA;  from ase.build import surface&#xA;&#xA;  A=read('Input_Your_Strcuture.cif',format='cif')  ### format can be vasp.&#xA;  B=surface(A,(-1,0,1),1,vacuum=15)&#xA;  write('Output_Your_Surface.vasp',ou_struct,format='vasp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Reference: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Reconstruct your surface with VESTA:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Open your structure with VESTA.&lt;/li&gt;&#xA;&lt;li&gt;Go to &amp;quot;Edit ==&amp;gt; Edit Data==&amp;gt;Unit Cell==&amp;gt;Transformation&amp;quot; and then enter the transformation matrix:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6P56T.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6P56T.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that you need only to fill in &lt;span class=&quot;math-container&quot;&gt;$P_{11}，P_{12}，P_{21}, P_{22}$&lt;/span&gt; (I assume the vacuum is along &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; direction) because you are considering the surface reconstruction.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Reference: &lt;a href=&quot;https://www.youtube.com/watch?v=qnbKn4QZdl8&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=qnbKn4QZdl8&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PS: For another conventional option, you may realize both with the &lt;a href=&quot;https://pymatgen.org/pymatgen.core.surface.html&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; package, but I'm not so familiar with it.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-02-28T10:32:43.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4425" PostTypeId="2" ParentId="3818" CreationDate="2021-02-28T21:44:14.487" Score="5" Body="&lt;h2&gt;Radiation stability&lt;/h2&gt;&#xA;&lt;p&gt;In some applications or environments (e.g. fission/fusion reactors, space, sterilization of packaging), radiation effects are highly important and can cause &lt;a href=&quot;https://en.wikipedia.org/wiki/Radiation_damage&quot; rel=&quot;noreferrer&quot;&gt;significant damage&lt;/a&gt; to, or changed properties of, materials. In other cases, radiation-induced changes of properties are in fact desired. For example, polymers are often irradiated to induce crosslinking for superior qualities. Now, both long-term radiation stability of e.g. reactor materials, and such manufacturing methods can be modeled. However, accurately modeling these radiation processes can be very challenging, because the problem can involve everything from initial defect formation to dislocation dynamics to continuum mechanics.&lt;/p&gt;&#xA;&lt;p&gt;To quote a review article,&#xA;&lt;a href=&quot;http://dx.doi.org/10.1038/nphys3735&quot; rel=&quot;noreferrer&quot;&gt;J. Knaster, A. Moeslang &amp;amp; T. Muroga, &lt;em&gt;Materials research for fusion,&lt;/em&gt; Nature Physics, vol. &lt;strong&gt;12&lt;/strong&gt;, 424–434 (2016)&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The effects of irradiation on a material’s microstructure and properties are a classic example of an inherently multiscale phenomenon, as schematically illustrated in Fig. 3a. Length scales of relevant processes range from ∼1 Å to structural-component lengths, spanning more than 12 orders of magnitude. In turn, the relevant timescales cover more than 22 orders of magnitude, with the shortest being in the femtosecond range.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They also write (bracketed comment added by me):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Today, a multiscale approach, based on both computational materials science and high-resolution experimental validation, is used to understand the controlling mechanisms and processes of irradiated structural materials. Figure 3b [shown below] illustrates the hierarchical multiscale modelling methodology, which typically combines &lt;em&gt;ab initio&lt;/em&gt;&#xA;structure calculations on the atomic scale, molecular dynamics&#xA;simulations, kinetic Monte Carlo simulations, discrete dislocation dynamics, and rate theory with continuum calculations including thermodynamics and kinetics, as well as phase field calculations. &lt;em&gt;Ab initio&lt;/em&gt; methods are required to calculate the most stable defect–cluster configurations, their dissociation energies, or the most likely lattice diffusion paths. Results of &lt;em&gt;ab initio&lt;/em&gt; studies can be used as input for molecular dynamics, kinetic Monte Carlo, rate field theory and thermodynamics calculations. Additional links&#xA;between different simulation methods are indicated by the arrows&#xA;in Fig. 3b.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DrFBe.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DrFBe.png&quot; alt=&quot;Fig. 3b from Knaster et al. (2016)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think that, in most cases, &lt;em&gt;ab initio&lt;/em&gt; methods for these problems means density-functional theory methods. A relevant review article is &lt;a href=&quot;https://doi.org/10.1146/annurev-matsci-071312-121626&quot; rel=&quot;noreferrer&quot;&gt;S.L. Dudarev, &lt;em&gt;Density Functional Theory Models for Radiation Damage,&lt;/em&gt; Annual Review of Materials Research, vol. &lt;strong&gt;43&lt;/strong&gt;, 35-61 (2013)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-02-28T21:44:14.487" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4426" PostTypeId="1" CreationDate="2021-03-01T11:21:33.773" Score="7" ViewCount="1238" Body="&lt;p&gt;I am trying to observe the effect of the electric field on 2D materials. I applied electric field by introducing three tags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LDIPOL = .TRUE.&#xA;IDIPOL = 3   # for Z direction&#xA;EFIELD = X   # eV/A**&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in INCAR, first in SCF and then in band structure calculation (NSCF).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Those are the same three lines (except in a different order), as what Tristan Maxson suggested in his answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1700/5.&quot;&gt;Electric Field Calculations in VASP&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I could not get the reported results. Am I doing something wrong?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am not getting any error&lt;/strong&gt;, I am just unable to report the &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp512993y&quot; rel=&quot;nofollow noreferrer&quot;&gt;published data&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I applied electric field on stanene. After relaxing stanene with &lt;code&gt;ISIF =4&lt;/code&gt;, I used &lt;code&gt;EFIELD&lt;/code&gt; tags in sc and then in bands (&lt;code&gt;ISTART =1, ICHARG = 11&lt;/code&gt;) calculations. For zero electric field, I am getting bandgap around 73.6 meV which is the same as reported. But as the electric field increases, the mismatch between values occurs. Like for E = 0.001eV/A, I am getting 71.1 meV and the reported one is 76.3 meV. For E = 1.0eV/A, I get 66.216 meV, and reported one is 318.3 meV&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;POSCAR:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Sn&#xA;&#xA;   1.0000000000000000&#xA;&#xA;     4.6730959813628878   -0.0000000228025768   -0.0000000000000001&#xA;     2.3365474619415303    4.0470201968368267    0.0000000000000001&#xA;    -0.0000000000000006    0.0000000000000005   19.2995674192802440&#xA;   Sn&#xA;    &#xA;    2&#xA;&#xA;Direct&#xA;&#xA; -0.0000000000000000  0.0000000000000000  0.4986167295676965    &#xA;  0.3333332607201882  0.3333333333333357  0.4545313204323064&#xA;  0.00000000E+00      0.00000000E+00      0.00000000E+00&#xA;  0.00000000E+00      0.00000000E+00      0.00000000E+00&#xA;                                                 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2177" LastEditorUserId="7" LastEditDate="2021-03-15T20:34:08.070" LastActivityDate="2021-03-15T20:41:30.040" Title="VASP error when trying to do calculations in the presence of an electric field" Tags="|density-functional-theory|vasp|electronic-structure|electric-field|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4427" PostTypeId="2" ParentId="4026" CreationDate="2021-03-01T20:10:40.550" Score="3" Body="&lt;p&gt;There are many reasons behind not converging. Sometimes structure doesn't converge if you describe them wrong. So, in my opinion, the best way to converge a structure is to study it clearly. Moreover, this convergence also varies for observing different properties too.&#xA;One common trick is to check smearing in your system.&#xA;For your system check if it converges for &amp;quot;gaussian&amp;quot; or any other smearing.&#xA;Another reason for not converging is the lack of an appropriate k point mesh grid for your system. Increasing the K point mesh grid may improve the convergence in less iteration though it consumes more computing time. You need to be careful choosing the k point mesh grid if it supports your system. Another thing you can do is to increase iteration from default. Also, you can change the pseudopotential type.&lt;/p&gt;&#xA;" OwnerUserId="1200" LastActivityDate="2021-03-01T20:10:40.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4428" PostTypeId="2" ParentId="4426" CreationDate="2021-03-02T01:38:29.963" Score="5" Body="&lt;p&gt;I assume that you have relaxed your geometry structure and can perform the VASP calculation. And I support the necessary input cards for SCF and NSCF calculations below.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;SCF calculation to obtain the converged charge density and wavefunction:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#General:&#xA;ISTART=0&#xA;ICHARG=2&#xA;ENCUT=450&#xA;EDIFF=1E-9&#xA;NELM=300&#xA;ISMEAR=-5&#xA;#SIGMA=0.05&#xA;IALGO=38&#xA;&#xA;#Electric Field:&#xA;IDIPOL=3&#xA;LDIPOL=.TRUE.&#xA;EFIELD=0.2    # eV/Angstrom&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;NSCF calculation to obtain bandstructure by reading previous charge density:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#General:&#xA;ISTART=0&#xA;ICHARG=11&#xA;ENCUT=450&#xA;EDIFF=1E-9&#xA;NELM=300&#xA;ISMEAR=0&#xA;SIGMA=0.05&#xA;IALGO=38&#xA;&#xA;#Electric Field:&#xA;IDIPOL=3&#xA;LDIPOL=.TRUE.&#xA;EFIELD=0.2    # eV/Angstrom&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-03-15T20:29:47.807" LastActivityDate="2021-03-15T20:29:47.807" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4430" PostTypeId="1" CreationDate="2021-03-02T06:36:55.557" Score="8" ViewCount="61" Body="&lt;p&gt;The experimental study shows that Density of state effective mass is calculated at 300K while in theoretical study DFT yield Density of state effective mass at 0K. Why there is so much temperature difference between both and how this is reasonable?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-10-19T20:45:45.447" LastActivityDate="2021-10-19T20:45:45.447" Title="Effect of temperature on density of states effective mass" Tags="|density-functional-theory|density-of-states|" AnswerCount="0" CommentCount="2" ClosedDate="2021-10-19T20:49:30.240" ContentLicense="CC BY-SA 4.0" />
  <row Id="4431" PostTypeId="1" CreationDate="2021-03-02T11:02:24.823" Score="8" ViewCount="166" Body="&lt;p&gt;I have calculated the exciton wave functions using the GW-BSE method:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}|S\rangle = \sum_{cv\mathbf{k}} A_{cv\mathbf{k}} |cv\mathbf{k}\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; for conduction and &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; for valence states. Now, I would like to calculate the exciton center-of-mass group velocity &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_S$&lt;/span&gt; in the limit of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}\rightarrow \mathbf{0}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt; the center-of-mass momentum). As for a single electron-hole pair, the exciton velocity can be approximated as the average of the electron and hole velocities. I'm wondering if there exists similar relation like &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_S \sim \sum_{cv\mathbf{k}} |A_{cv\mathbf{k}}|^2 ( \mathbf{v}_{c\mathbf{k}} + \mathbf{v}_{v\mathbf{k}} )/2$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2021-03-03T07:12:55.210" LastActivityDate="2021-03-03T07:12:55.210" Title="How to evaluate the exciton velocity?" Tags="|density-functional-theory|gw-bse|exciton|yambo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4432" PostTypeId="2" ParentId="3926" CreationDate="2021-03-02T17:00:22.307" Score="7" Body="&lt;p&gt;The brief answer, remodeled from the comments earlier given:  See the entries of COD, &lt;a href=&quot;https://www.crystallography.net/cod/4331895.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.crystallography.net/cod/4331895.html&lt;/a&gt;, and their #4331896, #7220156, and #7220157 -- all coordinated with Al, and all (more or less) dish-like flat:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YVAnG.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YVAnG.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;https://www.crystallography.net/cod/4331895.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;credit to COD&lt;/a&gt;, entry #4331895).&lt;/p&gt;&#xA;&lt;p&gt;This is because the ligand is engaged in complexation of the Al in the centre.  This fixation prevents much of the possible distortion of an empty ligand if a website constructs a 3D model from scratch with some (computationally cheap) force field to identify &lt;em&gt;one&lt;/em&gt; plausible conformer.  Of course the two (here randomly attributed) protons in the centre equally want to minimize steric interaction, too:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZTpId.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZTpId.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(based on the conformation of &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/compound/5282330#section=Crystal-Structures&quot; rel=&quot;nofollow noreferrer&quot;&gt;PubChem's .sdf&lt;/a&gt; about entry #5282330)&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;If you are interested into the coordinates &lt;em&gt;experimentally determined&lt;/em&gt;, I would suggest to consult a crystallographic database. If you are within a university, CCDC's &lt;a href=&quot;https://www.ccdc.cam.ac.uk/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CSD database&lt;/a&gt; may be one resource much more comfortable to search than &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; because of its interfaces including &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/conquest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;conquest&lt;/a&gt;, and &lt;a href=&quot;https://downloads.ccdc.cam.ac.uk/documentation/API/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CSD Python API&lt;/a&gt; (&lt;a href=&quot;https://downloads.ccdc.cam.ac.uk/documentation/API/descriptive_docs/primer.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;a primer&lt;/a&gt;, the CCDC moderated &lt;a href=&quot;https://www.ccdc.cam.ac.uk/forum/csd_python_api/&quot; rel=&quot;nofollow noreferrer&quot;&gt;user forum&lt;/a&gt; (since July 2021 &lt;em&gt;read-only&lt;/em&gt;)).  The  structures may be exported in the &lt;code&gt;.cif&lt;/code&gt; format; if you are fine with loosing some of information, however, exports as &lt;code&gt;.pdb&lt;/code&gt;, &lt;code&gt;.mol2&lt;/code&gt;, &lt;code&gt;.xyz&lt;/code&gt; and SMILES strings are equally among the offered formats which may be processed further, e.g., by &lt;a href=&quot;https://github.com/openbabel/openbabel&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenBabel&lt;/a&gt;.  Compared to other chemistry relevant databases, and taking into account the broad scope of applications, it is a smaller yet well affordable databases.  Often, research groups join each other under stewardship of a library to purchase e.g., 5 FTE at once, and subsequently share IT infrastructure and  license fees.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Complementary&lt;/em&gt; to CSD (about small organic and organometallic), and &lt;a href=&quot;https://www.psds.ac.uk/icsd&quot; rel=&quot;nofollow noreferrer&quot;&gt;ICSD&lt;/a&gt; about inorganic materials is the &lt;a href=&quot;https://www.crystallography.net/cod/&quot; rel=&quot;nofollow noreferrer&quot;&gt;COD&lt;/a&gt; with some overlap of coverage with the two former. Their access policies differ from the former and actively encourage share and mirroring of the data.  There is are GUIs to search in this repository (e.g., &lt;a href=&quot;https://www.crystallography.net/cod/search.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;by text&lt;/a&gt;, or &lt;a href=&quot;https://www.crystallography.net/cod/jsme_search.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;structure&lt;/a&gt;) but equally offers &lt;a href=&quot;https://wiki.crystallography.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;an API&lt;/a&gt; and a number of helper programs (&lt;a href=&quot;https://wiki.crystallography.net/cod-tools/&quot; rel=&quot;nofollow noreferrer&quot;&gt;cod-tools&lt;/a&gt;) like &lt;code&gt;codcif2sfd&lt;/code&gt; to convert a  &lt;code&gt;.cif&lt;/code&gt; into a chemically healed &lt;code&gt;.sdf&lt;/code&gt; to support programs like &lt;a href=&quot;http://openmolecules.org/datawarrior/datafiles.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;DataWarrior&lt;/a&gt; as optional add-on.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="1206" LastEditDate="2021-11-01T12:10:29.390" LastActivityDate="2021-11-01T12:10:29.390" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4433" PostTypeId="1" AcceptedAnswerId="4439" CreationDate="2021-03-02T17:09:28.113" Score="6" ViewCount="304" Body="&lt;p&gt;I would like some suggestions on how to do structural relaxation (while I'm at it, let me list some synonyms for search exposure - geometry optimization, structural refinement, energy minimization etc) using molecular mechanics (force fields) that preserves space group symmetry.&lt;/p&gt;&#xA;&lt;p&gt;A typical workflow that I'm thinking of is to start by generating a structure data file (eg. cif, but later easily converted to input data for various packages) with a reasonable crystalline arrangement of atoms, usually &amp;lt;1000 in number and having some spatial symmetry higher than P1.  Then I would refine the structures with atomistic simulations at various levels of accuracy (ranging from mol mech to DFT on a HPC cluster if need be) until they compare reasonably with experimental data which I already have for similar structures, in which one of the elements is substituted with another in the same group on the periodic table.&lt;/p&gt;&#xA;&lt;p&gt;I have so far tried using LAMMPS, GROMACS, Forcite (a module in Materials Studio) and was able to put together bare minimal input files for each of their structural relaxation routines, without spending too much time going through their thick manuals to see if they have the exact options/functions that I need.  Under default settings (with say, the DREIDING force field), they all seemed to break initial symmetries, maybe because of some thermostat that causes random displacements.&lt;br/&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I feel that the need for this kind of (symmetry-respecting relaxation) task at low level is fairly common and there's gotta be some standard, straightforward way to do this on an ordinary desktop workstation.  I know that DFT packages like Quantum Espresso or VASP do this kind of relaxation by default, mainly because thermostats aren't part of their standard routines.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone save me some web-searching/manual-reading time by pointing me to the right direction/tool?&lt;br/&gt;&lt;/p&gt;&#xA;&lt;p&gt;(This question may very well boil down to asking how to turn off the thermostat...)&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="1363" LastEditorUserId="5" LastEditDate="2021-03-04T15:43:55.597" LastActivityDate="2021-03-04T16:18:04.817" Title="Symmetry-preserving low-level structural relaxation" Tags="|software-recommendations|geometry-optimization|forcefields|molecular-mechanics|semi-empirical-method|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4434" PostTypeId="1" CreationDate="2021-03-02T19:17:07.923" Score="6" ViewCount="405" Body="&lt;p&gt;I want to calculate the difference in Gibbs free energies between a&#xA;Zr-Cu-Al liquid (composition - Zr 65 Cu 27.5 Al 7.5 at%) and the CuZr2&#xA;solid phase as a function of temperature (300 - 1000 K). In the system I am modelling, I assume solid &lt;span class=&quot;math-container&quot;&gt;$\ce{CuZr2}$&lt;/span&gt; precipitates out of Zr-Cu-Al liquid and I want to calculate the driving energy for the crystallization event by using parallel tangent construction.&lt;/p&gt;&#xA;&lt;p&gt;I found the thermodynamic description of Al-Cu-Zr system by the CALPHAD approach in&#xA;.TDB format (source file and publication are available). Could someone please advise me about how to do these calculations using either Thermocalc (free academic version) or OpenCALPHAD? Thanks in advance for your time.&lt;/p&gt;&#xA;" OwnerUserId="2180" LastEditorUserId="5" LastEditDate="2021-03-02T19:21:39.833" LastActivityDate="2021-03-04T15:33:46.753" Title="Thermo-calc: Calculate precipitation driving force by parallel tangent construction" Tags="|condensed-matter|thermodynamics|thermo-calc|phase-transitions|calphad|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4435" PostTypeId="1" CreationDate="2021-03-02T19:42:32.197" Score="10" ViewCount="167" Body="&lt;p&gt;Virtual screening , protein ligand docking,  MD simulation, FEP free energy calculations and the QM/MM approach have all been widely applied in optimization for drug discovery.&lt;/p&gt;&#xA;&lt;p&gt;Which drugs that have been recently developed involved any of those methods in their development?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2021-03-02T19:55:12.373" LastActivityDate="2021-03-19T10:45:40.120" Title="What novel drugs are developed via CADD?" Tags="|molecular-dynamics|reference-request|computational-chemistry|docking|drug-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4436" PostTypeId="1" AcceptedAnswerId="4455" CreationDate="2021-03-03T04:44:40.587" Score="11" ViewCount="339" Body="&lt;p&gt;I have been trying to simulate benzene in OPLSS-AA forcefield as per this paper: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct2002122&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/ct2002122&lt;/a&gt;. I have been at a loss, since I believe I have everything running as per the paper, except for the vdw and coulombic cutoffs, but I am not generating the results the paper is showing.&lt;/p&gt;&#xA;&lt;p&gt;My simulation is running bug-free on GROMACS, however, I am not getting the results they are showing. I energy minimized my system, performed an NVT equilibration for 50 ps, then I performed an NPT equilibration for a 100 ps. Then I did a production run for 5 ns.&lt;/p&gt;&#xA;&lt;p&gt;I have rcoulomb = rvdw = 1.3 in my simulation. That is because GROMACS does not allow twin cutoff ranges anymore.&lt;/p&gt;&#xA;&lt;p&gt;My density is coming out in the neighborhood of 823 kg/m3 when it should be around 867 kg/m3.&lt;/p&gt;&#xA;&lt;p&gt;I obtained my GRO and ITP file from LigParGen server, however, the charges on the LigParGen Server were different from the charges in the paper, so I changed them.&lt;/p&gt;&#xA;&lt;p&gt;The only thing the paper hasn't provided are the harmonic bond and angle potential coefficients, and torsional coefficients.&lt;/p&gt;&#xA;&lt;p&gt;I am really stuck as to how to go about this problem. Where could my bug be lying?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;For the sake of completeness, I have attached my primary input files.&#xA;This is my .gro file (coordinate):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LIGPARGEN GENERATED GRO FILE&#xA;   12&#xA;    1UNK    C00    1   0.100   0.100   0.000&#xA;    1UNK    C01    2  -0.040   0.100   0.000&#xA;    1UNK    C02    3  -0.109   0.100   0.121&#xA;    1UNK    C03    4  -0.039   0.100   0.242&#xA;    1UNK    C04    5   0.100   0.100   0.241&#xA;    1UNK    C05    6   0.170   0.100   0.121&#xA;    1UNK    H06    7   0.154   0.100  -0.094&#xA;    1UNK    H07    8  -0.094   0.100  -0.094&#xA;    1UNK    H08    9  -0.218   0.100   0.121&#xA;    1UNK    H09   10  -0.093   0.100   0.336&#xA;    1UNK    H0A   11   0.155   0.100   0.335&#xA;    1UNK    H0B   12   0.278   0.100   0.121&#xA;   1.00000   1.00000   1.00000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is my .itp file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;;&#xA;; GENERATED BY LigParGen Server&#xA;; Jorgensen Lab @ Yale University&#xA;;&#xA;[ atomtypes ]&#xA;  opls_804  C804    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_803  C803    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_811  H811     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_809  H809     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_810  H810     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_805  C805    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_802  C802    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_806  H806     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_808  H808     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_800  C800    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_807  H807     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_801  C801    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;[ moleculetype ]&#xA;; Name               nrexcl&#xA;UNK                   3&#xA;[ atoms ]&#xA;;   nr       type  resnr residue  atom   cgnr     charge       mass&#xA;     1   opls_800      1    UNK   C00      1    -0.115    12.0110&#xA;     2   opls_801      1    UNK   C01      1    -0.115    12.0110&#xA;     3   opls_802      1    UNK   C02      1    -0.115    12.0110&#xA;     4   opls_803      1    UNK   C03      1    -0.115    12.0110&#xA;     5   opls_804      1    UNK   C04      1    -0.115    12.0110&#xA;     6   opls_805      1    UNK   C05      1    -0.115    12.0110&#xA;     7   opls_806      1    UNK   H06      1     0.115     1.0080&#xA;     8   opls_807      1    UNK   H07      1     0.115     1.0080&#xA;     9   opls_808      1    UNK   H08      1     0.115     1.0080&#xA;    10   opls_809      1    UNK   H09      1     0.115     1.0080&#xA;    11   opls_810      1    UNK   H0A      1     0.115     1.0080&#xA;    12   opls_811      1    UNK   H0B      1     0.115     1.0080&#xA;[ bonds ]&#xA;    2     1     1      0.1400 392459.200&#xA;    3     2     1      0.1400 392459.200&#xA;    4     3     1      0.1400 392459.200&#xA;    5     4     1      0.1400 392459.200&#xA;    6     1     1      0.1400 392459.200&#xA;    7     1     1      0.1080 307105.600&#xA;    8     2     1      0.1080 307105.600&#xA;    9     3     1      0.1080 307105.600&#xA;   10     4     1      0.1080 307105.600&#xA;   11     5     1      0.1080 307105.600&#xA;   12     6     1      0.1080 307105.600&#xA;    6     5     1      0.1400 392459.200&#xA;&#xA;[ angles ]&#xA;;  ai    aj    ak funct            c0            c1            c2            c3&#xA;    1     2     3     1    120.000    527.184&#xA;    2     3     4     1    120.000    527.184&#xA;    3     4     5     1    120.000    527.184&#xA;    2     1     6     1    120.000    527.184&#xA;    2     1     7     1    120.000    292.880&#xA;    1     2     8     1    120.000    292.880&#xA;    2     3     9     1    120.000    292.880&#xA;    3     4    10     1    120.000    292.880&#xA;    4     5    11     1    120.000    292.880&#xA;    1     6    12     1    120.000    292.880&#xA;    6     5    11     1    120.000    292.880&#xA;    6     1     7     1    120.000    292.880&#xA;    5     6    12     1    120.000    292.880&#xA;    5     4    10     1    120.000    292.880&#xA;    1     6     5     1    120.000    527.184&#xA;    4     3     9     1    120.000    292.880&#xA;    4     5     6     1    120.000    527.184&#xA;    3     2     8     1    120.000    292.880&#xA;&#xA;[ dihedrals ]&#xA;; IMPROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    12     6     1     5    4        180.000     10.460     2&#xA;    11     5     4     6    4        180.000     10.460     2&#xA;    10     4     3     5    4        180.000     10.460     2&#xA;     9     3     2     4    4        180.000     10.460     2&#xA;     8     2     1     3    4        180.000     10.460     2&#xA;     7     1     2     6    4        180.000     10.460     2&#xA;&#xA;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    4    3    2    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    5    4    3    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    6    1    2    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    4    5    6    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    6    5    4    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    5    6    1    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    1    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    7    1    6    5        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    6    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    5    6        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    4    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    5    4        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    2    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    7    1    2    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    1    6        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    3    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    3    4        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    4    5        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    3    9        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    1    7        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    5   11        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    2    8        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    1    7        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    4   10        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;&#xA;[ pairs ]&#xA;     1     4    1&#xA;     2     5    1&#xA;     3     6    1&#xA;     3     7    1&#xA;     1     9    1&#xA;     5     7    1&#xA;     4     8    1&#xA;     2    10    1&#xA;     1    11    1&#xA;     6     8    1&#xA;     5     9    1&#xA;     3    11    1&#xA;     2    12    1&#xA;     7     8    1&#xA;     6    10    1&#xA;     4    12    1&#xA;     8     9    1&#xA;     9    10    1&#xA;     7    12    1&#xA;    10    11    1&#xA;    11    12    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is my topol.top file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; include forcefield parameters&#xA;#include &amp;quot;oplsaa.ff/forcefield.itp&amp;quot;&#xA;&#xA;; Include mol topology&#xA;#include &amp;quot;UNK_5D626B_rev.itp&amp;quot;&#xA;&#xA;[ system ]&#xA;; Name&#xA;liquid-benzene-simulation&#xA;&#xA;[ molecules ]&#xA;;compound   number of molecules&#xA;UNK        600&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this is my final production run &lt;code&gt;md.mdp&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;title                   = liquid benzene oplss simulation&#xA;; Run parameters&#xA;integrator              = md        ; leap-frog integrator&#xA;nsteps                  = 5000000    ; 1 * 1000000 = 1000 ps (1 ns)&#xA;dt                      = 0.001     ; 1 fs&#xA;; Output control&#xA;nstxout                 = 0         ; suppress bulky .trr file by specifying&#xA;nstvout                 = 0         ; 0 for output frequency of nstxout,&#xA;nstfout                 = 0         ; nstvout, and nstfout&#xA;nstenergy               = 5000      ; save energies every 5.0 ps&#xA;nstlog                  = 5000      ; update log file every 5.0 ps&#xA;nstxout-compressed      = 5000      ; save compressed coordinates every 5.0 ps&#xA;compressed-x-grps       = System    ; save the whole system&#xA;; Bond parameters&#xA;continuation            = yes       ; Restarting after NPT&#xA;constraint_algorithm    = lincs     ; holonomic constraints&#xA;constraints             = h-bonds   ; bonds involving H are constrained&#xA;lincs_iter              = 1         ; accuracy of LINCS&#xA;lincs_order             = 4         ; also related to accuracy&#xA;; Neighborsearching&#xA;cutoff-scheme           = Verlet    ; Buffered neighbor searching&#xA;ns_type                 = grid      ; search neighboring grid cells&#xA;nstlist                 = 10        ; 20 fs, largely irrelevant with Verlet scheme&#xA;rcoulomb                = 1.3       ; short-range electrostatic cutoff (in nm)&#xA;rvdw                    = 1.3       ; short-range van der Waals cutoff (in nm)&#xA;; Electrostatics&#xA;coulombtype             = PME       ; Particle Mesh Ewald for long-range electrostatics&#xA;pme_order               = 8         ; order-8 interpolation&#xA;fourierspacing          = 0.12      ; grid spacing for FFT&#xA;; Temperature coupling is on&#xA;tcoupl                  = V-rescale             ; modified Berendsen thermostat&#xA;tc-grps                 = System                ; two coupling groups - more accurate&#xA;tau_t                   = 0.5                   ; time constant, in ps&#xA;ref_t                   = 298                   ; reference temperature, one for each group, in K&#xA;; Pressure coupling is on&#xA;pcoupl                  = Parrinello-Rahman     ; Pressure coupling on in NPT&#xA;pcoupltype              = isotropic             ; uniform scaling of box vectors&#xA;tau_p                   = 2.0                   ; time constant, in ps&#xA;ref_p                   = 1.0                   ; reference pressure, in bar&#xA;compressibility         = 4.5e-5                ; isothermal compressibility of water, bar^-1&#xA;; Periodic boundary conditions&#xA;pbc                     = xyz       ; 3-D PBC&#xA;; Dispersion correction&#xA;DispCorr                = Ener  ; account for cut-off vdW scheme&#xA;; Velocity generation&#xA;gen_vel                 = no        ; Velocity generation is off&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My nvt equilibration mdp:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;title                   = liquid benzene nvt equilibration &#xA;; define                  = -DPOSRES  ; position restrain the protein&#xA;; Run parameters&#xA;integrator              = md        ; leap-frog integrator&#xA;nsteps                  = 50000     ; 2 * 50000 = 100 ps&#xA;dt                      = 0.002     ; 2 fs&#xA;; Output control&#xA;nstxout                 = 500       ; save coordinates every 1.0 ps&#xA;nstvout                 = 500       ; save velocities every 1.0 ps&#xA;nstenergy               = 500       ; save energies every 1.0 ps&#xA;nstlog                  = 500       ; update log file every 1.0 ps&#xA;; Bond parameters&#xA;continuation            = no        ; first dynamics run&#xA;constraint_algorithm    = lincs     ; holonomic constraints &#xA;constraints             = h-bonds   ; bonds involving H are constrained&#xA;lincs_iter              = 1         ; accuracy of LINCS&#xA;lincs_order             = 4         ; also related to accuracy&#xA;; Nonbonded settings &#xA;cutoff-scheme           = Verlet    ; Buffered neighbor searching&#xA;ns_type                 = grid      ; search neighboring grid cells&#xA;nstlist                 = 10        ; 20 fs, largely irrelevant with Verlet&#xA;rcoulomb                = 1.0       ; short-range electrostatic cutoff (in nm)&#xA;rvdw                    = 1.0       ; short-range van der Waals cutoff (in nm)&#xA;DispCorr                = EnerPres  ; account for cut-off vdW scheme&#xA;; Electrostatics&#xA;coulombtype             = PME       ; Particle Mesh Ewald for long-range electrostatics&#xA;pme_order               = 4         ; cubic interpolation&#xA;fourierspacing          = 0.16      ; grid spacing for FFT&#xA;; Temperature coupling is on&#xA;tcoupl                  = V-rescale             ; modified Berendsen thermostat&#xA;tc-grps                 = System                ; one coupling groups - more accurate&#xA;tau_t                   = 0.1               ; time constant, in ps&#xA;ref_t                   = 298               ; reference temperature, one for each group, in K&#xA;; Pressure coupling is off&#xA;pcoupl                  = no        ; no pressure coupling in NVT&#xA;; Periodic boundary conditions&#xA;pbc                     = xyz       ; 3-D PBC&#xA;; Velocity generation&#xA;gen_vel                 = yes       ; assign velocities from Maxwell distribution&#xA;gen_temp                = 300       ; temperature for Maxwell distribution&#xA;gen_seed                = -1        ; generate a random seed&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My npt equilibration file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;title                   = liquid-benzene-simulation&#xA;; define                  = -DPOSRES  ; position restrain the protein&#xA;; Run parameters&#xA;integrator              = md        ; leap-frog integrator&#xA;nsteps                  = 100000     ; 1 * 100000 = 100 ps&#xA;dt                      = 0.001     ; 1 fs&#xA;; Output control&#xA;nstxout                 = 500       ; save coordinates every 1.0 ps&#xA;nstvout                 = 500       ; save velocities every 1.0 ps&#xA;nstenergy               = 500       ; save energies every 1.0 ps&#xA;nstlog                  = 500       ; update log file every 1.0 ps&#xA;; Bond parameters&#xA;continuation            = yes       ; Restarting after NVT &#xA;constraint_algorithm    = lincs     ; holonomic constraints &#xA;constraints             = h-bonds   ; bonds involving H are constrained&#xA;lincs_iter              = 1         ; accuracy of LINCS&#xA;lincs_order             = 4         ; also related to accuracy&#xA;; Nonbonded settings &#xA;cutoff-scheme           = Verlet    ; Buffered neighbor searching&#xA;ns_type                 = grid      ; search neighboring grid cells&#xA;nstlist                 = 10        ; 20 fs, largely irrelevant with Verlet scheme&#xA;rcoulomb                = 1.0       ; short-range electrostatic cutoff (in nm)&#xA;rvdw                    = 1.0       ; short-range van der Waals cutoff (in nm)&#xA;DispCorr                = EnerPres  ; account for cut-off vdW scheme&#xA;; Electrostatics&#xA;coulombtype             = PME       ; Particle Mesh Ewald for long-range electrostatics&#xA;pme_order               = 4         ; cubic interpolation&#xA;fourierspacing          = 0.16      ; grid spacing for FFT&#xA;; Temperature coupling is on&#xA;tcoupl                  = V-rescale             ; modified Berendsen thermostat&#xA;tc-grps                 = System                ; two coupling groups - more accurate&#xA;tau_t                   = 0.1                   ; time constant, in ps&#xA;ref_t                   = 298                   ; reference temperature, one for each group, in K&#xA;; Pressure coupling is on&#xA;pcoupl                  = Parrinello-Rahman     ; Pressure coupling on in NPT&#xA;pcoupltype              = isotropic             ; uniform scaling of box vectors&#xA;tau_p                   = 2.0                   ; time constant, in ps&#xA;ref_p                   = 1.0                   ; reference pressure, in bar&#xA;compressibility         = 4.5e-5                ; isothermal compressibility of water, bar^-1&#xA;refcoord_scaling        = com&#xA;; Periodic boundary conditions&#xA;pbc                     = xyz       ; 3-D PBC&#xA;; Velocity generation&#xA;gen_vel                 = no        ; Velocity generation is off &#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2021-03-03T16:48:12.227" LastActivityDate="2021-03-06T21:44:12.850" Title="Unable to recreate data for benzene from paper in GROMACS 2020.5" Tags="|molecular-dynamics|molecular-modeling|gromacs|software-assistance|reproducing-data-from-papers|" AnswerCount="1" CommentCount="10" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4437" PostTypeId="2" ParentId="4431" CreationDate="2021-03-03T06:59:24.363" Score="7" Body="&lt;p&gt;Not a direct answer to your proposed approximation to the exciton group velocity as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}\to0$&lt;/span&gt;, but just wanted to point out that the latest version of Yambo supports the calculation of exciton dispersions, from which you can then calculate the exciton velocity at any &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt;. Here are the details: &lt;a href=&quot;http://www.yambo-code.org/wiki/index.php?title=How_to_analyse_excitons#Interpolate_exciton_dispersion_.28only_in_Yambo_5.x.29&quot; rel=&quot;noreferrer&quot;&gt;Yambo 5: exciton dispersion&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-03-03T06:59:24.363" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4438" PostTypeId="2" ParentId="4433" CreationDate="2021-03-03T23:30:35.700" Score="7" Body="&lt;p&gt;ASE has a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html#the-fixsymmetry-class&quot; rel=&quot;nofollow noreferrer&quot;&gt;FixSymmetry&lt;/a&gt; constraint that preserves spacegroup symmetries. It works with a variety of &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;structure optimization algorithms&lt;/a&gt;. You could use LAMMPS as the engine or one of the many other &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/calculators/calculators.html#module-ase.calculators&quot; rel=&quot;nofollow noreferrer&quot;&gt;calculators&lt;/a&gt;, including some DFT options.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-03-04T16:18:04.817" LastActivityDate="2021-03-04T16:18:04.817" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4439" PostTypeId="2" ParentId="4433" CreationDate="2021-03-04T12:00:45.443" Score="5" Body="&lt;h2&gt;GULP&lt;/h2&gt;&#xA;&lt;p&gt;GULP (&lt;strong&gt;G&lt;/strong&gt;eneral &lt;strong&gt;U&lt;/strong&gt;tility &lt;strong&gt;L&lt;/strong&gt;attice &lt;strong&gt;P&lt;/strong&gt;rogram) uses specific forcefields for different type of systems and it is designed to work with periodic conditions. Also, it has defined several type of potential models for two-body (Buckingham, Lennard-Jones, Morse, etc.), three-body (Three-body harmonic, Axilrod-Teller, Stillinger-Weber, etc.), four-body, six-body and many-body interactions.&lt;/p&gt;&#xA;&lt;p&gt;From its &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;GULP is a program for performing a variety of types of simulation on materials using boundary conditions of 0-D (molecules and clusters), 1-D (polymers), 2-D (surfaces, slabs and grain boundaries), or 3-D (periodic solids). The focus of the code is on analytical solutions, through the use of lattice dynamics, where possible, rather than on molecular dynamics.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the on-line &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/help/help_52_txt.html&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt;, you will find several options that control how the symmetry of the system can be treated.&lt;/p&gt;&#xA;&lt;p&gt;GULP is available for free for academic use by anyone with a valid University email account.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-03-04T12:00:45.443" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4440" PostTypeId="1" CreationDate="2021-03-04T15:20:13.287" Score="5" ViewCount="333" Body="&lt;p&gt;I installed the module LAMMPS by using this command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;conda install -c conda-forge lammps&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want to import LAMMPS to python code, but it says:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; import lammps&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;ModuleNotFoundError: No module named 'lammps'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Anyone can tell me how to import lammps to python.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2021-03-05T06:15:51.460" LastActivityDate="2021-03-05T06:15:51.460" Title="Cannot import both numpy and LAMMPS to python after installing with conda" Tags="|lammps|python|software-assistance|" AnswerCount="0" CommentCount="9" ClosedDate="2021-06-23T22:11:37.333" ContentLicense="CC BY-SA 4.0" />
  <row Id="4441" PostTypeId="1" CreationDate="2021-03-04T15:20:21.597" Score="5" ViewCount="78" Body="&lt;p&gt;I'm thinking of running MD simulation of poling process (heating and cooling in external electric field) of host-guest polymer system: organic chromophore in polymer matrix (PMMA or polycarbonate).&lt;/p&gt;&#xA;&lt;p&gt;So, I'm trying to find how to build the system. I've found that Packmol can be used to randomly place prebuilt polymer chains but I don't understand how can I introduce my chromophore (I also need to control polymer density and chromophore weight content).&lt;/p&gt;&#xA;&lt;p&gt;What tools can you recommend for building such systems and feeding them to some MD code (at the moment I'm considering GROMACS, LAMMPS or CP2k, but I'm not sure)?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-03-23T14:58:46.747" Title="Bulding host-guest polymer system for molecular dynamics" Tags="|molecular-dynamics|molecular-modeling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4442" PostTypeId="2" ParentId="4434" CreationDate="2021-03-04T15:33:46.753" Score="5" Body="&lt;p&gt;Thermo-Calc's &lt;code&gt;DGM&lt;/code&gt; is the normalized parallel tangent driving force per mole of components. To be able to compute the driving force of a phase, it must be set to &amp;quot;dormant&amp;quot; status so that it cannot become stable, but the driving force can still be computed.&lt;/p&gt;&#xA;&lt;p&gt;Here's an example macro of how this could be done in Thermo-Calc:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;@@ These commands can be copied into console mode or saved as a macro (.TCM) file&#xA;@@ Load your database and get the data for your system&#xA;go database_retrieval&#xA;@@ the next command will open a file dialog to pick your TDB file&#xA;switch user&#xA;&#xA;define-elements AL CU ZR&#xA;get-data&#xA;&#xA;@@ Go to poly-3 module to do calculations&#xA;go poly-3&#xA;@@ Set conditions for the fixed values&#xA;set-condition n=1 P=101325 X(CU)=0.275 X(AL)=0.075&#xA;@@ Set temperature axis variable, accept default step size&#xA;set-axis-variable 1 T 300 1000 ,&#xA;&#xA;@@ Make all phases dormant except for the liquid phase&#xA;@@ We first make all phases dormant (so we don't need to specify all solid phases manually)&#xA;change-status phase *=dormant&#xA;@@ Then make liquid entered with a phase amount of 1&#xA;@@ If your liquid has a phase name that is not LIQUID, then change that here&#xA;change-status phase LIQUID=entered 1&#xA;&#xA;@@ Perform a normal step calculation to step in your axis variable (temperature)&#xA;step normal&#xA;&#xA;@@ Plot using POST&#xA;POST&#xA;set-diagram-axis x T&#xA;@@ Assuming your phase is named CUZR2, set the Y-axis to plot DGM(CUZR2)&#xA;@@ Note that DGM is the normalized driving force per mole of components (normalized by RT)&#xA;set-diagram-axis y DGM(CUZR2)&#xA;@@ If you want to plot driving forces for all phases, you can use DGM(*)&#xA;@@set-diagram-axis y DGM(*) *&#xA;@@ Set the curve labeling to option F to get each phase to be labeled with a color and make a legend&#xA;set-label-curve-option F&#xA;plot&#xA;&#xA;@@ Return control to the user if run from a macro&#xA;set-interactive&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-03-04T15:33:46.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4443" PostTypeId="1" CreationDate="2021-03-04T18:16:53.760" Score="14" ViewCount="211" Body="&lt;p&gt;Time-dependent Density Functional Theory has been around for quite a while now, seeing &lt;a href=&quot;https://doi.org/10.1103%2FPhysRevLett.52.997&quot; rel=&quot;noreferrer&quot;&gt;Density-Functional Theory for Time-Dependent Systems&lt;/a&gt;, and so it has been developed extensively, implemented in major codes, and succeeded by more modern and accurate methods that may be used in research.&lt;/p&gt;&#xA;&lt;p&gt;However, TD-DFT is still more efficient than some of those methods, and it is most likely very well regarded still in the fields of photophysics and photochemistry.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to make sense of its capabilities and limitations, particularly in the fields of photophysics and photochemistry.&lt;/p&gt;&#xA;&lt;p&gt;What are some &lt;em&gt;key references&lt;/em&gt; where TD-DFT successfully predicted or reproduced an important result in photochemistry?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2021-10-19T20:53:57.880" LastActivityDate="2022-07-19T15:50:12.070" Title="Is there an example in which TD-DFT was successful in describing photophysical or photochemical processes?" Tags="|density-functional-theory|reference-request|quantum-chemistry|td-dft|photochemistry|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4444" PostTypeId="1" CreationDate="2021-03-04T20:58:45.217" Score="8" ViewCount="1097" Body="&lt;p&gt;Apparently, my input parameters are not good for geometry relaxation of 2D materials using &lt;code&gt;VASP&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EDIFFG = 1E-2&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;&#xA;ENCUT = 337&#xA;&#xA;NSW = 100&#xA;ISIF = 3&#xA;IBRION = 2&#xA;&#xA;#SCAN-RVV10&#xA;METAGGA  = SCAN&#xA;LUSE_VDW = .TRUE.&#xA;BPARAM = 15.7&#xA;LASPH = .TRUE.&#xA;&#xA;NPAR = 32&#xA;KPAR = 12&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What am I doing wrong? Is ISIF=3 not a good idea for 2D materials? Or is it impossible to use implemented geometry optimization procedures for 2D materials with &lt;code&gt;VASP&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="1218" LastEditDate="2021-04-03T14:10:11.560" LastActivityDate="2021-04-05T08:35:23.313" Title="What are the input parameters of VASP for 2D material geometry optimization?" Tags="|density-functional-theory|vasp|geometry-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4445" PostTypeId="1" AcceptedAnswerId="4471" CreationDate="2021-03-04T21:43:15.020" Score="11" ViewCount="438" Body="&lt;p&gt;I need to calculate the DFT energy given the density of another level of theory, for example Hartree Fock.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E[\rho_{HF}]$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is sometimes used to fix various electron delocalization errors in conjugated molecules, such as what is done here to fix torsional barriers in isomerization reactions &lt;a href=&quot;https://arxiv.org/pdf/2102.06842.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/pdf/2102.06842.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This of course means that there is no SCF procedure done.&lt;/p&gt;&#xA;&lt;p&gt;How can I do this in various codes? I am specifically interested in input examples for Q-Chem, but if you know of a way to do it for other codes that could be useful for others. The linked paper uses ORCA.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-03-10T03:50:05.860" Title="How to calculate DFT energy with density from another level of theory?" Tags="|density-functional-theory|q-chem|orca|software-input-file-request|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4446" PostTypeId="2" ParentId="4445" CreationDate="2021-03-05T01:40:13.697" Score="14" Body="&lt;p&gt;Incidentally, I initiated some discussions along these lines in these questions  for HF-DFT (also called 'density-corrected' DFT) &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4407/procedure-to-classify-errors-in-kohn-sham-dft&quot;&gt;here&lt;/a&gt;,&#xA;and &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4298/exchange-in-hartree-fock-and-kohn-sham-dft&quot;&gt;here&lt;/a&gt;. I'm familiar with Quantum ESPRESSO, so I can detail a procedure with QE. If you want to generate a Hartree-Fock density, you can just turn on a hybrid functional (say HSE06) and turn up the fraction of exact exchange to 1. This can be done by setting  &lt;code&gt;exx_fraction = 1&lt;/code&gt;. This way, the generated Hartree-Fock density albeit in a Kohn-Sham scheme (i.e. KS eigenvalues and orbitals), should coincide with the energy and density of a calculation involving self-consistent hartree-fock orbitals.&lt;/p&gt;&#xA;&lt;p&gt;You can then use this density as the starting point, and turn on your regular functionals (say PBE, LDA etc).&lt;/p&gt;&#xA;" OwnerUserId="770" LastActivityDate="2021-03-05T01:40:13.697" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4447" PostTypeId="1" CreationDate="2021-03-05T11:35:16.993" Score="11" ViewCount="243" Body="&lt;p&gt;I study molecules weakly bound to nanoclusters and surfaces.&#xA;During geometry optimization, I often run into problems like for example a small metal cluster behave nicely and has a given, stable geometry for 90% of the calculations, then in the remaining 10% of cases, it reorganizes to some other geometry. On one hand, these problems are expected as there are several different stability points around, often with relatively low transition barrier, on the other hand, it is rather annoying when changing a functional or basis set, or something minor chemical change induces such a transformation and makes impossible any comparison between geometries. One can use a geometry constrain to fix the geometry every time, but I feel kind of uneasy about it.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering if there is an easy way to introduce an extra force, similarly like biases can be introduced in MD simulations to do meta-dynamics, so it smoothly lowers the energy of a given geometry and ideally makes it stable. Technicalities: I am using molecular codes (Gaussian, ORCA) for such calculations at the DFT level.&lt;/p&gt;&#xA;" OwnerUserId="91" LastEditorUserId="5" LastEditDate="2021-09-21T22:43:31.820" LastActivityDate="2021-11-16T04:33:14.150" Title="Using &quot;soft&quot; constraints / bias in geometry optimization?" Tags="|density-functional-theory|gaussian|geometry-optimization|geometry|orca|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4448" PostTypeId="1" AcceptedAnswerId="4449" CreationDate="2021-03-05T12:07:26.943" Score="10" ViewCount="315" Body="&lt;p&gt;I'm using SCAN-RVV10 to optimize the hexagonal-BN but the optimized geometry doesn't look true as the calculated interlayer distance is far smaller than the experimental value(exp=3.35 Aangstrom, calc=3.20 Angstrom). (SCAN-RVV10 is known as one of the best methods which take into account missing van der Waals interactions.)&lt;/p&gt;&#xA;&lt;p&gt;My input parameters:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EDIFF = 1E-6&#xA;EDIFFG = -1E-2&#xA;&#xA;ISMEAR = 0 ; SIGMA = 0.05&#xA;&#xA;ENCUT = 600&#xA;&#xA;NSW = 100&#xA;ISIF = 3&#xA;IBRION = 2&#xA;&#xA;METAGGA  = SCAN&#xA;LUSE_VDW = .TRUE.&#xA;BPARAM = 15.7&#xA;LASPH = .TRUE.&#xA;&#xA;NPAR = 32&#xA;KPAR = 16&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What am I doing wrong? Is there any published interlayer distance for bulk hBN and/or Graphite interlayer distance calculated using SCAN-RVV10?&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="1218" LastEditDate="2021-04-05T11:27:29.760" LastActivityDate="2021-04-05T11:27:29.760" Title="SCAN-RVV10 geometry optimization" Tags="|density-functional-theory|vasp|geometry-optimization|dispersion-correction|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4449" PostTypeId="2" ParentId="4448" CreationDate="2021-03-05T18:44:53.940" Score="10" Body="&lt;p&gt;Imagine you have a (hypothetical) method that can &lt;em&gt;exactly&lt;/em&gt; capture the van der Waals interaction. Then when you do a geometry optimization, you are neglecting the quantum and thermal fluctuations of the atoms, and you end up with what is called the static lattice approximation. As quantum and thermal fluctuations tend to expand the lattice, then you would expect that an exact method would predict a geometry that &lt;em&gt;underestimates&lt;/em&gt; the experimental lattice parameters. This is true if experiments are performed at room temperature, but it is also true even if they are performed at zero temperature because of quantum fluctuations.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, layered van der Waals compounds tend to have a relatively large thermal expansion coefficient along the stacking direction, so for these compounds you would expect an even larger underestimation between an exact van der Waals calculation and experiment.&lt;/p&gt;&#xA;&lt;p&gt;Putting this together, if you have an approximate van der Waals method that exactly reproduces the experimental lattice parameter, then the van der Waals approximate method is in fact not that good because when you added the quantum and thermal fluctuations, you would end up &lt;em&gt;overestimating&lt;/em&gt; the lattice parameter. On the other hand, if you have a van der Waals approximate method that slightly underestimates the lattice parameter, then that has a good chance of being a better approximation, because adding quantum and thermal fluctuations would take you closer to the experimental value. To confirm this, you should calculate the effects of thermal expansion, for example using the quasiharmonic approximation.&lt;/p&gt;&#xA;&lt;p&gt;I have no experience in SCAN-RVV10, but underestimating the lattice parameter by 0.15 Angstrom (I am guessing the units here because you did not provide them), actually sounds pretty good.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-03-05T18:44:53.940" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4450" PostTypeId="1" CreationDate="2021-03-06T04:44:16.563" Score="9" ViewCount="417" Body="&lt;p&gt;I want to run a classical molecular dynamics simulation on silicane using LAMMPS. Since I don't have access to any HPC nor do I have a powerful desktop PC, I'm planning on making the system small. By small, I mean something like a 4x4 silicane cell (32 atoms:16 Si and 16 H). A paper I read, which was on a DFT study, used this cell size.&lt;/p&gt;&#xA;&lt;p&gt;Although I'm just about to start with LAMMPS, I've seen videos where LAMMPS was used for crystal cells with around 1000 atoms so I'm kind of certain the system I want to play with is small. But will there be any drawbacks to using LAMMPS for a system this small?&lt;/p&gt;&#xA;" OwnerUserId="347" LastActivityDate="2021-03-06T12:22:45.257" Title="Using LAMMPS for a small system" Tags="|molecular-dynamics|lammps|supercell|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4452" PostTypeId="2" ParentId="4450" CreationDate="2021-03-06T12:22:45.257" Score="8" Body="&lt;p&gt;There are a couple of potential problems. First, the assumption of periodic simulations is that your box size is large enough that there is no effect on an atom from its nearest periodic replica. I come from the world of biomolecular simulations, where we typically &amp;quot;pad&amp;quot; our proteins with at least 1 nm of water. I would guess that your entire proposed simulation box is not much more than 1 nm to a side, so you might get some really weird dynamics from atoms that &amp;quot;see&amp;quot; their periodic images.&lt;/p&gt;&#xA;&lt;p&gt;Second, even if your simulation is big enough to avoid that, there can be finite size effects in the properties of the materials you're studying. That is to say, whatever observable you try to calculate may actually depend on the size of the box. (In some cases, such as diffusion in liquids, this can be used to extrapolate to the bulk limit by simulating at several sizes.) This is even a risk in the large-scale production simulations for publications, but at very small box sizes the effects will be more pronounced.&lt;/p&gt;&#xA;&lt;p&gt;Solution: You're probably underestimating the power of your hardware. I regularly run simulations of 1500-2000 atoms on my 5 year old laptop (using molecular mechanics). It's fast enough that I can use these systems to test the methods I develop, and (given my choice of system) &amp;quot;real&amp;quot; enough that when it comes time to publish, it's considered an acceptable test of the method.&lt;/p&gt;&#xA;&lt;p&gt;You might be interested in these old LAMMPS benchmarks: &lt;a href=&quot;https://lammps.sandia.gov/bench.html&quot; rel=&quot;noreferrer&quot;&gt;https://lammps.sandia.gov/bench.html&lt;/a&gt;. For example, under &amp;quot;metallic solid,&amp;quot; the 1-processor tests say that a Linux desktop in 2012 ran 100 steps of 32000 atoms in under 6 seconds. The protein example is a bit slower, coming in at 36 seconds on that computer.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-03-06T12:22:45.257" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4453" PostTypeId="1" AcceptedAnswerId="4470" CreationDate="2021-03-05T19:10:41.333" Score="9" ViewCount="481" Body="&lt;p&gt;I'm studying the quantum chemistry calculation and now trying to implement the basic methods.&lt;/p&gt;&#xA;&lt;p&gt;For example, given a water molecule,&#xA;&lt;span class=&quot;math-container&quot;&gt;$M = {(\ce{O}, R_\ce{O}), (\ce{H}, R_\ce{H}), (\ce{H}, R_\ce{H})}$&lt;/span&gt;,&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R = [X, Y, Z]$&lt;/span&gt; is the atomic position,&#xA;the Cartesian Gaussian-type orbital &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; on &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;,&#xA;where &lt;span class=&quot;math-container&quot;&gt;$r = [x, y, z]$&lt;/span&gt; is an arbitrary position, can be written as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi(r) = N (x-X)^l (y-Y)^m (z-Z)^n \exp(-\alpha ||r-R||^2),$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the normalization term,&#xA;&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is the orbital exponent,&#xA;and &lt;span class=&quot;math-container&quot;&gt;$||r-R||$&lt;/span&gt; is the distance between &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;.&#xA;The term of &lt;span class=&quot;math-container&quot;&gt;$(x-X)^l (y-Y)^m (z-Z)^n$&lt;/span&gt; is the Cartesian harmonics.&lt;/p&gt;&#xA;&lt;p&gt;However, I believe that, because a water molecule can be described by any Cartesian coordinates if all the atomic distances (i.e., &lt;span class=&quot;math-container&quot;&gt;$\ce{O-H}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{O-H}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\ce{H-H}$&lt;/span&gt;) are correct, &lt;span class=&quot;math-container&quot;&gt;$\psi(r)$&lt;/span&gt; can not be determined to a single value.&lt;/p&gt;&#xA;&lt;p&gt;For example, the following two Cartesian coordinates represent the same water molecule.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O 0.00000 0.00000 0.11779&#xA;H 0.00000 0.75545 -0.47116&#xA;H 0.00000 -0.75545 -0.47116&#xA;&#xA;O -0.034 0.978 0.0076&#xA;H 0.065 0.021 0.0015&#xA;H 0.87 1.30 0.00069&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, &lt;span class=&quot;math-container&quot;&gt;$\psi(r)$&lt;/span&gt; is different because the above equation has the term of &lt;span class=&quot;math-container&quot;&gt;$(x-X)^l (y-Y)^m (z-Z)^n$&lt;/span&gt;. If the equation has only the distance term (i.e., &lt;span class=&quot;math-container&quot;&gt;$\exp(-\alpha ||r-R||^2)$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$\psi(r)$&lt;/span&gt; has always the same value and I can implement this very easily only using the distance matrix.&lt;/p&gt;&#xA;&lt;p&gt;How can I deal with this problem and implement the Cartesian harmonics?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Postscript&lt;/strong&gt;: Of course, I know the spherical harmonics but I believe that even if the angles, θ and φ, are used, the problem is the same; how can I determine the θ and φ or the orientation of the 2px (2py or 2pz) orbital of each atom in a molecule? For example, in the following figure, specifically how can I determine the 2px of the H orbital in a water molecule? Of course, I know the 2px (2py or 2pz) is along with the H-O bond in this case; however, how can I determine the θ, φ, and orientation of 2px, 2py, and 2pz orbitals of each atom in arbitrary other more complex molecule and calculate the LCAO?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fEPFC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fEPFC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2189" OwnerDisplayName="Lin Lin" LastEditorUserId="2189" LastEditDate="2021-03-16T14:13:51.793" LastActivityDate="2021-03-16T22:49:27.850" Title="How can I implement the Cartesian harmonics?" Tags="|molecular-modeling|quantum-chemistry|mathematical-modeling|orbitals|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4454" PostTypeId="1" CreationDate="2021-03-06T20:11:03.793" Score="4" ViewCount="181" Body="&lt;p&gt;I tried &lt;code&gt;IVDW = 2202&lt;/code&gt; for MBD as mentioned on the website but I got the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INITWF: ERROR, W inconsistently dimensioned:  1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I think some other keywords are missing but it does not mention them on the website. Any suggestions are welcome.&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2021-03-07T00:26:04.220" LastActivityDate="2021-03-07T00:26:04.220" Title="What are the TS, MBD keywords for new (5.4.+) VASP versions?" Tags="|density-functional-theory|vasp|dispersion-correction|" AnswerCount="0" CommentCount="4" ClosedDate="2021-06-23T22:08:01.043" ContentLicense="CC BY-SA 4.0" />
  <row Id="4455" PostTypeId="2" ParentId="4436" CreationDate="2021-03-06T21:44:12.850" Score="5" Body="&lt;p&gt;Thanks to the generous time and comments of @ShoubhikRMaiti, I was able to recreate the simulation.&lt;/p&gt;&#xA;&lt;p&gt;The problem in my code was 2-fold: I was using the topology filed created by LigParGen, which had different charges on the C and H atoms in my simulation as in the paper. I did not think to check LigParGen's output, and that is my own fault.&lt;/p&gt;&#xA;&lt;p&gt;Also, I was using LINCS constraint on only the H-bonds in my simulation, when instead I was supposed to be using LINCS constraint on all-bonds in my simulation. This led to almost a perfect reproduction of the properties mentioned in the paper.&lt;/p&gt;&#xA;&lt;p&gt;Thank you everyone who chipped in!!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-03-06T21:44:12.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4456" PostTypeId="1" CreationDate="2021-03-07T08:35:13.190" Score="8" ViewCount="943" Body="&lt;p&gt;In most DFT codes like QE and VASP, spin-orbit coupling (SOC) can be incorporated by employing fully relativistic pseudopotentials. My question is with regard to the implementation of SOC among different functionals. If one believes that using a fully relativistic PP is equivalent to solving the Dirac equation, are the results simply transferrable between different functionals?&lt;/p&gt;&#xA;&lt;p&gt;For example, let us say I calculate the total energy from DFT-PBE with SOC off and then turned on. The difference in these two configurations should give me the amount of SOC for my system. Now, if I perform DFT-LDA on the same system, should I expect just the same amount of SOC? My main concern here is because we use different pseudopotentials.&lt;/p&gt;&#xA;" OwnerUserId="770" LastActivityDate="2021-03-09T13:33:16.233" Title="Regarding spin-orbit coupling on DFT codes" Tags="|density-functional-theory|functional|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4457" PostTypeId="1" AcceptedAnswerId="4461" CreationDate="2021-03-07T15:54:37.657" Score="5" ViewCount="780" Body="&lt;p&gt;I am trying to use ASE (Atomic Simulation Environment) to build a supercell of some molecular crystals and then output the result to a file with the atoms given in a specified order for each molecule, followed by the second molecule, and so on.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;When I import the .cif files, I get the following warnings (below). What should I do about them?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;UserWarning: crystal system 'monoclinic' is not interpreted for space group Spacegroup(14, setting=1). This may result in wrong setting!&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;UserWarning: crystal system 'orthorhombic' is not interpreted for space group Spacegroup(36, setting=1). This may result in wrong setting!&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The cif file for the two crystal structures is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;_audit_creation_method     SHELXL&#xA;_journal_date_recd_electronic     2002-06-07&#xA;_journal_date_accepted     2002-09-25&#xA;_journal_name_full     'Acta Crystallographica, Section B'&#xA;_journal_year     2002&#xA;_journal_volume     58&#xA;_journal_issue      6&#xA;_journal_page_first     1005&#xA;_journal_page_last     1010&#xA;_journal_paper_category     FA&#xA;_chemical_name_systematic     'acetonitrile'&#xA;_chemical_name_common     ?&#xA;_chemical_formula_moiety     'C2 H3 N'&#xA;_chemical_formula_sum     'C2 H3 N'&#xA;_chemical_formula_structural     'C H3 C N'&#xA;_chemical_formula_analytical     ?&#xA;_chemical_formula_weight     41.05&#xA;_chemical_melting_point     ?&#xA;_symmetry_cell_setting     'orthorhombic'&#xA;_symmetry_space_group_name_H-M     'C m c 21'&#xA;_symmetry_space_group_name_Hall     'C 2c -2'&#xA;loop_&#xA;    _symmetry_equiv_pos_as_xyz&#xA;    'x, y, z'&#xA;    '-x, -y, z+1/2'&#xA;    '-x, y, z'&#xA;    'x, -y, z+1/2'&#xA;    'x+1/2, y+1/2, z'&#xA;    '-x+1/2, -y+1/2, z+1/2'&#xA;    '-x+1/2, y+1/2, z'&#xA;    'x+1/2, -y+1/2, z+1/2'&#xA;_cell_length_a     6.1870(10)&#xA;_cell_length_b     5.282(3)&#xA;_cell_length_c     7.887(4)&#xA;_cell_angle_alpha     90.00&#xA;_cell_angle_beta     90.00&#xA;_cell_angle_gamma     90.00&#xA;_cell_volume     257.7(2)&#xA;_cell_formula_units_Z     4&#xA;_cell_measurement_reflns_used     25&#xA;_cell_measurement_theta_min     5.68&#xA;_cell_measurement_theta_max     20.11&#xA;_cell_measurement_temperature     206(2)&#xA;_exptl_crystal_description     'cylinder'&#xA;_exptl_crystal_colour     'colourless'&#xA;_exptl_crystal_size_max     1.2&#xA;_exptl_crystal_size_mid     0.5&#xA;_exptl_crystal_size_min     0.3&#xA;_exptl_crystal_size_rad     0.15&#xA;_exptl_crystal_density_diffrn     1.058&#xA;_exptl_crystal_density_meas     ?&#xA;_exptl_crystal_density_method     ?&#xA;_exptl_crystal_F_000     88&#xA;_exptl_absorpt_coefficient_mu     0.069&#xA;_exptl_absorpt_correction_type     'none'&#xA;_exptl_absorpt_correction_T_min     ?&#xA;_exptl_absorpt_correction_T_max     ?&#xA;_exptl_special_details&#xA;;&#xA; ?&#xA;;&#xA;_diffrn_ambient_temperature     206(2)&#xA;_diffrn_radiation_type     MoK\a&#xA;_diffrn_radiation_wavelength     0.71073&#xA;_diffrn_radiation_source     'fine-focus sealed tube'&#xA;_diffrn_radiation_monochromator     graphite&#xA;_diffrn_measurement_device     'Nonius CAD4 diffractometer'&#xA;_diffrn_measurement_method     '\w--2\q'&#xA;_diffrn_reflns_number     136&#xA;_diffrn_reflns_av_R_equivalents     0.0000&#xA;_diffrn_reflns_av_sigmaI/netI     0.0473&#xA;_diffrn_reflns_theta_min     5.06&#xA;_diffrn_reflns_theta_max     24.91&#xA;_diffrn_reflns_theta_full     24.91&#xA;_diffrn_measured_fraction_theta_max     0.99&#xA;_diffrn_measured_fraction_theta_full     0.99&#xA;_diffrn_reflns_limit_h_min     0&#xA;_diffrn_reflns_limit_h_max     7&#xA;_diffrn_reflns_limit_k_min     0&#xA;_diffrn_reflns_limit_k_max     6&#xA;_diffrn_reflns_limit_l_min     -9&#xA;_diffrn_reflns_limit_l_max     0&#xA;_diffrn_standards_number     'none'&#xA;_diffrn_standards_interval_count     'none'&#xA;_diffrn_standards_interval_time     'none'&#xA;_diffrn_standards_decay_%     'none'&#xA;_refine_special_details&#xA;;&#xA; Refinement of F^2^ against ALL reflections.  Weighted R-factors wR and&#xA; goodnesses of fit S are based on F^2^, conventional R-factors R are based&#xA; on F, with F set to zero for negative F^2^. The threshold_expression of&#xA; F^2^ &amp;gt; 2sigma(F^2^) is used only for calculating R_factors(gt) etc. and is&#xA; not relevant to the choice of reflections for refinement.  R-factors based&#xA; on F^2^ are statistically about twice as large as those based on F, and R-&#xA; factors based on ALL data will be even larger.&#xA;;&#xA;_reflns_number_total     136&#xA;_reflns_number_gt     99&#xA;_reflns_threshold_expression     'I&amp;gt;2\s(I)'&#xA;_refine_ls_structure_factor_coef     Fsqd&#xA;_refine_ls_matrix_type     full&#xA;_refine_ls_R_factor_all     0.0891&#xA;_refine_ls_R_factor_gt     0.0580&#xA;_refine_ls_wR_factor_all     0.1899&#xA;_refine_ls_wR_factor_ref     0.1492&#xA;_refine_ls_goodness_of_fit_all     1.200&#xA;_refine_ls_goodness_of_fit_ref     1.155&#xA;_refine_ls_restrained_S_all     1.200&#xA;_refine_ls_restrained_S_obs     1.155&#xA;_refine_ls_number_reflns     136&#xA;_refine_ls_number_parameters     26&#xA;_refine_ls_number_restraints     0&#xA;_refine_ls_hydrogen_treatment     'refall'&#xA;_refine_ls_weighting_scheme     calc&#xA;_refine_ls_weighting_details&#xA;              'w=1/[\s^2^(Fo^2^)+(0.0888P)^2^+0.1685P] where P=(Fo^2^+2Fc^2^)/3'&#xA;_atom_sites_solution_hydrogens     difmap&#xA;_atom_sites_solution_primary     direct&#xA;_atom_sites_solution_secondary     difmap&#xA;_refine_ls_shift/su_max     0.037&#xA;_refine_ls_shift/su_mean     0.001&#xA;_refine_diff_density_max     0.176&#xA;_refine_diff_density_min     -0.172&#xA;_refine_ls_extinction_method     SHELXL&#xA;_refine_ls_extinction_coef     0.01(7)&#xA;_refine_ls_extinction_expression&#xA;                                  'Fc^*^=kFc[1+0.001xFc^2^\l^3^/sin(2\q)]^-1/4^'&#xA;_refine_ls_abs_structure_details&#xA;                                    'Flack H D (1983), Acta Cryst. A39, 876-881'&#xA;_refine_ls_abs_structure_Flack     -10(10)&#xA;loop_&#xA;    _atom_type_symbol&#xA;    _atom_type_description&#xA;    _atom_type_scat_dispersion_real&#xA;    _atom_type_scat_dispersion_imag&#xA;    _atom_type_scat_source&#xA;    'C' 'C' 0.0033 0.0016&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'H' 'H' 0.0000 0.0000&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'N' 'N' 0.0061 0.0033&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;_computing_data_collection     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_cell_refinement     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_data_reduction     'CADAK (Savariault,1991)'&#xA;_computing_structure_solution     'SHELXS-96 (Sheldrick, 1990)'&#xA;_computing_structure_refinement     'SHELXL-96 (Sheldrick, 1996)'&#xA;_computing_molecular_graphics     'ORTEP III (Burnett &amp;amp; Johnson, 1996)'&#xA;_computing_publication_material     'SHELXL-96 (Sheldrick, 1996)'&#xA;loop_&#xA;    _atom_site_label&#xA;    _atom_site_fract_x&#xA;    _atom_site_fract_y&#xA;    _atom_site_fract_z&#xA;    _atom_site_U_iso_or_equiv&#xA;    _atom_site_thermal_displace_type&#xA;    _atom_site_calc_flag&#xA;    _atom_site_refinement_flags&#xA;    _atom_site_occupancy&#xA;    _atom_site_disorder_group&#xA;    _atom_site_type_symbol&#xA;    N 0.0000 0.4380(14) -0.0974(18) 0.070(3) Uani d S 1 . N&#xA;    C1 0.0000 0.0776(15) 0.1243(18) 0.053(2) Uani d S 1 . C&#xA;    C2 0.0000 0.2762(16) 0.0000 0.053(2) Uani d S 1 . C&#xA;    H1 0.0000 -0.104(15) 0.080(12) 0.07(3) Uiso d S 1 . H&#xA;    H2 0.149(11) 0.087(9) 0.201(8) 0.083(19) Uiso d . 1 . H&#xA;loop_&#xA;    _atom_site_aniso_label&#xA;    _atom_site_aniso_U_11&#xA;    _atom_site_aniso_U_22&#xA;    _atom_site_aniso_U_33&#xA;    _atom_site_aniso_U_12&#xA;    _atom_site_aniso_U_13&#xA;    _atom_site_aniso_U_23&#xA;    N 0.070(5) 0.069(6) 0.070(6) 0.000 0.000 0.014(4)&#xA;    C1 0.058(5) 0.050(4) 0.052(5) 0.000 0.000 0.008(5)&#xA;    C2 0.035(3) 0.067(4) 0.058(4) 0.000 0.000 -0.011(5)&#xA;_geom_special_details&#xA;;&#xA; All esds (except the esd in the dihedral angle between two l.s. planes)&#xA; are estimated using the full covariance matrix.  The cell esds are taken&#xA; into account individually in the estimation of esds in distances, angles&#xA; and torsion angles; correlations between esds in cell parameters are only&#xA; used when they are defined by crystal symmetry.  An approximate (isotropic)&#xA; treatment of cell esds is used for estimating esds involving l.s. planes.&#xA;;&#xA;loop_&#xA;    _geom_bond_atom_site_label_1&#xA;    _geom_bond_atom_site_label_2&#xA;    _geom_bond_site_symmetry_2&#xA;    _geom_bond_distance&#xA;    _geom_bond_publ_flag&#xA;    N C2 . 1.149(12) yes&#xA;    C1 C2 . 1.436(12) yes&#xA;    C1 H1 . 1.02(8) yes&#xA;    C1 H2 . 1.11(7) yes&#xA;loop_&#xA;    _geom_angle_atom_site_label_1&#xA;    _geom_angle_atom_site_label_2&#xA;    _geom_angle_atom_site_label_3&#xA;    _geom_angle_site_symmetry_1&#xA;    _geom_angle_site_symmetry_3&#xA;    _geom_angle&#xA;    _geom_angle_publ_flag&#xA;    C2 C1 H1 . . 117(6) yes&#xA;    C2 C1 H2 . . 110(3) yes&#xA;    H1 C1 H2 . . 103(4) yes&#xA;    N C2 C1 . . 178.9(12) yes&#xA;data_II&#xA;_audit_creation_method     SHELXL&#xA;_chemical_name_systematic     'acetonitrile'&#xA;_chemical_name_common     ?&#xA;_chemical_formula_moiety     'C2 H3 N'&#xA;_chemical_formula_sum     'C2 H3 N'&#xA;_chemical_formula_structural     'C H3 C N'&#xA;_chemical_formula_analytical     ?&#xA;_chemical_formula_weight     41.05&#xA;_chemical_melting_point     ?&#xA;_symmetry_cell_setting     'monoclinic'&#xA;_symmetry_space_group_name_H-M     'P 21/c'&#xA;_symmetry_space_group_name_Hall     '-P 2ybc'&#xA;loop_&#xA;    _symmetry_equiv_pos_as_xyz&#xA;    'x, y, z'&#xA;    '-x, y+1/2, -z+1/2'&#xA;    '-x, -y, -z'&#xA;    'x, -y-1/2, z-1/2'&#xA;_cell_length_a     4.102(3)&#xA;_cell_length_b     8.244(7)&#xA;_cell_length_c     7.970(7)&#xA;_cell_angle_alpha     90.00&#xA;_cell_angle_beta     100.10(10)&#xA;_cell_angle_gamma     90.00&#xA;_cell_volume     265.3(4)&#xA;_cell_formula_units_Z     4&#xA;_cell_measurement_reflns_used     25&#xA;_cell_measurement_theta_min     5.20&#xA;_cell_measurement_theta_max     21.48&#xA;_cell_measurement_temperature     201(2)&#xA;_exptl_crystal_description     'cylinder'&#xA;_exptl_crystal_colour     'colourless'&#xA;_exptl_crystal_size_max     1.2&#xA;_exptl_crystal_size_mid     0.5&#xA;_exptl_crystal_size_min     0.3&#xA;_exptl_crystal_size_rad     0.15&#xA;_exptl_crystal_density_diffrn     1.028&#xA;_exptl_crystal_density_meas     ?&#xA;_exptl_crystal_density_method     ?&#xA;_exptl_crystal_F_000     88&#xA;_exptl_absorpt_coefficient_mu     0.067&#xA;_exptl_absorpt_correction_type     'none'&#xA;_exptl_absorpt_correction_T_min     ?&#xA;_exptl_absorpt_correction_T_max     ?&#xA;_exptl_special_details&#xA;;&#xA; ?&#xA;;&#xA;_diffrn_ambient_temperature     201(2)&#xA;_diffrn_radiation_type     MoK\a&#xA;_diffrn_radiation_wavelength     0.71073&#xA;_diffrn_radiation_source     'fine-focus sealed tube'&#xA;_diffrn_radiation_monochromator     'graphite'&#xA;_diffrn_measurement_device     'Nonius CAD4 diffractometer'&#xA;_diffrn_measurement_method     '\w--2\q'&#xA;_diffrn_reflns_number     376&#xA;_diffrn_reflns_av_R_equivalents     0.0571&#xA;_diffrn_reflns_av_sigmaI/netI     0.0591&#xA;_diffrn_reflns_theta_min     3.58&#xA;_diffrn_reflns_theta_max     21.89&#xA;_diffrn_reflns_theta_full     21.89&#xA;_diffrn_measured_fraction_theta_max     0.99&#xA;_diffrn_measured_fraction_theta_full     0.99&#xA;_diffrn_reflns_limit_h_min     0&#xA;_diffrn_reflns_limit_h_max     4&#xA;_diffrn_reflns_limit_k_min     0&#xA;_diffrn_reflns_limit_k_max     8&#xA;_diffrn_reflns_limit_l_min     -8&#xA;_diffrn_reflns_limit_l_max     8&#xA;_diffrn_standards_number     'none'&#xA;_diffrn_standards_interval_count     'none'&#xA;_diffrn_standards_interval_time     'none'&#xA;_diffrn_standards_decay_%     'none'&#xA;_refine_special_details&#xA;;&#xA; Refinement of F^2^ against ALL reflections.  Weighted R-factors wR and&#xA; goodnesses of fit S are based on F^2^, conventional R-factors R are based&#xA; on F, with F set to zero for negative F^2^. The threshold_expression of&#xA; F^2^ &amp;gt; 2sigma(F^2^) is used only for calculating R_factors(gt) etc. and is&#xA; not relevant to the choice of reflections for refinement.  R-factors based&#xA; on F^2^ are statistically about twice as large as those based on F, and R-&#xA; factors based on ALL data will be even larger.&#xA;;&#xA;_reflns_number_total     324&#xA;_reflns_number_gt     202&#xA;_reflns_threshold_expression     'I&amp;gt;2\s(I)'&#xA;_refine_ls_structure_factor_coef     Fsqd&#xA;_refine_ls_matrix_type     full&#xA;_refine_ls_R_factor_all     0.1051&#xA;_refine_ls_R_factor_gt     0.0472&#xA;_refine_ls_wR_factor_all     0.1504&#xA;_refine_ls_wR_factor_ref     0.1106&#xA;_refine_ls_goodness_of_fit_all     1.137&#xA;_refine_ls_goodness_of_fit_ref     1.107&#xA;_refine_ls_restrained_S_all     1.137&#xA;_refine_ls_restrained_S_obs     1.107&#xA;_refine_ls_number_reflns     324&#xA;_refine_ls_number_parameters     41&#xA;_refine_ls_number_restraints     0&#xA;_refine_ls_hydrogen_treatment     'refall'&#xA;_refine_ls_weighting_scheme     calc&#xA;_refine_ls_weighting_details&#xA;              'w=1/[\s^2^(Fo^2^)+(0.0360P)^2^+0.1879P] where P=(Fo^2^+2Fc^2^)/3'&#xA;_atom_sites_solution_hydrogens     difmap&#xA;_atom_sites_solution_primary     direct&#xA;_atom_sites_solution_secondary     difmap&#xA;_refine_ls_shift/su_max     0.000&#xA;_refine_ls_shift/su_mean     0.000&#xA;_refine_diff_density_max     0.169&#xA;_refine_diff_density_min     -0.168&#xA;_refine_ls_extinction_method     SHELXL&#xA;_refine_ls_extinction_coef     0.07(4)&#xA;_refine_ls_extinction_expression&#xA;                                  'Fc^*^=kFc[1+0.001xFc^2^\l^3^/sin(2\q)]^-1/4^'&#xA;loop_&#xA;    _atom_type_symbol&#xA;    _atom_type_description&#xA;    _atom_type_scat_dispersion_real&#xA;    _atom_type_scat_dispersion_imag&#xA;    _atom_type_scat_source&#xA;    'C' 'C' 0.0033 0.0016&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'H' 'H' 0.0000 0.0000&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'N' 'N' 0.0061 0.0033&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;_computing_data_collection     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_cell_refinement     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_data_reduction     'CADAK (Savariault,1991)'&#xA;_computing_structure_solution     'SHELXS-96 (Sheldrick, 1990)'&#xA;_computing_structure_refinement     'SHELXL-96 (Sheldrick, 1996)'&#xA;_computing_molecular_graphics     'ORTEP III (Burnett &amp;amp; Johnson, 1996)'&#xA;_computing_publication_material     'SHELXL-96 (Sheldrick, 1996)'&#xA;loop_&#xA;    _atom_site_label&#xA;    _atom_site_fract_x&#xA;    _atom_site_fract_y&#xA;    _atom_site_fract_z&#xA;    _atom_site_U_iso_or_equiv&#xA;    _atom_site_thermal_displace_type&#xA;    _atom_site_calc_flag&#xA;    _atom_site_refinement_flags&#xA;    _atom_site_occupancy&#xA;    _atom_site_disorder_group&#xA;    _atom_site_type_symbol&#xA;    N 0.4547(9) 0.2657(5) 0.4613(4) 0.0710(15) Uani d . 1 . N&#xA;    C1 0.0949(12) 0.4579(6) 0.2478(6) 0.0586(14) Uani d . 1 . C&#xA;    C2 0.2946(9) 0.3498(5) 0.3672(5) 0.0507(13) Uani d . 1 . C&#xA;    H1 -0.108(11) 0.402(5) 0.166(5) 0.089(14) Uiso d . 1 . H&#xA;    H2 0.233(11) 0.518(6) 0.186(6) 0.113(18) Uiso d . 1 . H&#xA;    H3 -0.050(11) 0.538(6) 0.301(5) 0.103(16) Uiso d . 1 . H&#xA;loop_&#xA;    _atom_site_aniso_label&#xA;    _atom_site_aniso_U_11&#xA;    _atom_site_aniso_U_22&#xA;    _atom_site_aniso_U_33&#xA;    _atom_site_aniso_U_12&#xA;    _atom_site_aniso_U_13&#xA;    _atom_site_aniso_U_23&#xA;    N 0.076(3) 0.070(3) 0.064(2) 0.005(2) 0.0028(18) 0.008(2)&#xA;    C1 0.058(3) 0.060(3) 0.055(3) 0.005(2) 0.001(2) 0.008(2)&#xA;    C2 0.056(2) 0.050(3) 0.047(2) -0.007(2) 0.0101(19) -0.009(2)&#xA;_geom_special_details&#xA;;&#xA; All esds (except the esd in the dihedral angle between two l.s. planes)&#xA; are estimated using the full covariance matrix.  The cell esds are taken&#xA; into account individually in the estimation of esds in distances, angles&#xA; and torsion angles; correlations between esds in cell parameters are only&#xA; used when they are defined by crystal symmetry.  An approximate (isotropic)&#xA; treatment of cell esds is used for estimating esds involving l.s. planes.&#xA;;&#xA;loop_&#xA;    _geom_bond_atom_site_label_1&#xA;    _geom_bond_atom_site_label_2&#xA;    _geom_bond_site_symmetry_2&#xA;    _geom_bond_distance&#xA;    _geom_bond_publ_flag&#xA;    N C2 . 1.141(5) yes&#xA;    C1 C2 . 1.448(6) yes&#xA;    C1 H1 . 1.07(5) yes&#xA;    C1 H2 . 0.96(5) yes&#xA;    C1 H3 . 1.03(5) yes&#xA;loop_&#xA;    _geom_angle_atom_site_label_1&#xA;    _geom_angle_atom_site_label_2&#xA;    _geom_angle_atom_site_label_3&#xA;    _geom_angle_site_symmetry_1&#xA;    _geom_angle_site_symmetry_3&#xA;    _geom_angle&#xA;    _geom_angle_publ_flag&#xA;    C2 C1 H1 . . 115(2) yes&#xA;    C2 C1 H2 . . 110(3) yes&#xA;    H1 C1 H2 . . 112(3) yes&#xA;    C2 C1 H3 . . 115(2) yes&#xA;    H1 C1 H3 . . 95(3) yes&#xA;    H2 C1 H3 . . 108(4) yes&#xA;    N C2 C1 . . 179.3(4) yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user2026" LastEditorDisplayName="user2026" LastEditDate="2021-03-08T20:09:33.917" LastActivityDate="2021-03-09T05:45:23.137" Title="ASE: why do I get warnings about &quot;monoclinic&quot; and &quot;orthorhombic&quot; not being interpreted?" Tags="|crystal-structure|crystallography|cif|atomic-simulation-environment|supercell|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4458" PostTypeId="1" AcceptedAnswerId="4467" CreationDate="2021-03-07T23:11:49.933" Score="12" ViewCount="242" Body="&lt;p&gt;I am using an open source python package openmmtools to run a simple molecular simulation problem using the metropolis algorithm.&lt;/p&gt;&#xA;&lt;p&gt;I first load a default system of particles (alanine-dipeptide in vacuum), add some uniform random disturbance to every position, then let the algorithm run to see if it brings me back to the starting system position.&lt;/p&gt;&#xA;&lt;p&gt;It looks like the metropolis moves decrease energy, as expected, but do not decrease the euclidean distance of each particle back to its starting position. Euclidean distance is just a sum of all the particle positions at any given state. The following graph is what I see when I measure these quantities. The big initial jump is when I add a disturbance to the positions of every particle in the system. I have even subtracted the mean of the particle positions from each particle to make sure that it isn't just that the entire system is shifting away from the starting position.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/u7elv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/u7elv.png&quot; alt=&quot;distance and energy during metropolis algorithm for simulation of 22 molecule system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why do the Euclidean distances of each particle not decrease with the energy. In fact, they seem to increase as the simulation continues, which means the particles are growing farther and farther apart, which doesn't seem right. I know the molecule isn't rotating, since I'm drawing the state at each timestep as a 3D scatter plot and can see that it isn't.&lt;/p&gt;&#xA;&lt;p&gt;I expect is something very silly on my end. I hope the confusion is clear.&lt;/p&gt;&#xA;&lt;p&gt;Here's the code that gave me this graph, just in case.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from openmmtools import mcmc, testsystems, states, cache&#xA;from simtk import openmm&#xA;from simtk import unit&#xA;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;&#xA;# user parameters&#xA;timesteps = 100&#xA;draw_init_final_positions = False&#xA;plot_distance_energy = True&#xA;&#xA;&#xA;class AddGaussianVector(mcmc.MetropolizedMove):&#xA;    def __init__(self, **kwargs):&#xA;        super(AddGaussianVector, self).__init__(**kwargs)&#xA;&#xA;    def _propose_positions(self, initial_positions):&#xA;        # displacement = unit.Quantity(np.array([1, 1, 1]), initial_positions.unit)&#xA;        mean, var = 0, .1&#xA;        x_prop, y_prop, z_prop = np.random.normal(mean, var), np.random.normal(mean, var), np.random.normal(mean, var)&#xA;        displacement = unit.Quantity(np.array([x_prop, y_prop, z_prop]), initial_positions.unit)&#xA;        return initial_positions + displacement&#xA;&#xA;&#xA;def distance(x, correct):&#xA;    for k in range(3):&#xA;        x[:, k] -= np.mean(x[:, k])&#xA;        correct[:, k] -= np.mean(correct[:, k])&#xA;    noise = np.subtract(x, correct)&#xA;    return np.sqrt(np.sum(np.square(noise)))&#xA;&#xA;platform = openmm.Platform.getPlatformByName('CUDA')&#xA;cache.global_context_cache.platform = platform&#xA;&#xA;# Create the initial state (thermodynamic and microscopic) for an alanine dipeptide system in vacuum.&#xA;alanine = testsystems.AlanineDipeptideVacuum()&#xA;sampler_state = states.SamplerState(alanine.positions)&#xA;thermodynamic_state = states.ThermodynamicState(alanine.system, 300 * unit.kelvin)&#xA;e, d = [], []&#xA;context_cache = cache.global_context_cache&#xA;context, unused_integrator = context_cache.get_context(thermodynamic_state)&#xA;sampler_state.apply_to_context(context, ignore_velocities=True)&#xA;e.append(thermodynamic_state.reduced_potential(context))&#xA;d.append(distance(sampler_state.positions.copy(), sampler_state.positions.copy()))&#xA;&#xA;# draw initial sampler_state&#xA;if draw_init_final_positions:&#xA;    plt.figure(1)&#xA;    ax = plt.axes(projection='3d')&#xA;    xdata = sampler_state.positions[:, 0]&#xA;    ydata = sampler_state.positions[:, 1]&#xA;    zdata = sampler_state.positions[:, 2]&#xA;    ax.scatter3D(xdata, ydata, zdata, cmap='Greens')&#xA;    plt.title('Initial particle conformation')&#xA;&#xA;&#xA;noise = np.zeros((sampler_state.n_particles, 3))&#xA;correct_state = sampler_state.positions.copy()&#xA;for i, molecule in enumerate(sampler_state.positions):&#xA;&#xA;    # add noise to correct state&#xA;    noise_low, noise_high = -1, 1&#xA;    sampler_state.positions[i][0] += unit.quantity.Quantity(value= np.random.uniform(noise_low, noise_high), unit=unit.nanometer)&#xA;    sampler_state.positions[i][1] += unit.quantity.Quantity(value= np.random.uniform(noise_low, noise_high), unit=unit.nanometer)&#xA;    sampler_state.positions[i][2] += unit.quantity.Quantity(value= np.random.uniform(noise_low, noise_high), unit=unit.nanometer)&#xA;&#xA;print('Correct_state: ', correct_state)&#xA;print('Noisey_state', sampler_state.positions.copy())&#xA;print('INITIAL DIST AND ENERGY: {} nm {} energy'.format(d[0], e[0]))&#xA;&#xA;sampler_state.apply_to_context(context, ignore_velocities=True)&#xA;e.append(thermodynamic_state.reduced_potential(context))&#xA;&#xA;&#xA;# Create an update MCMC move that brings us back to the initial configuration.&#xA;current_state = sampler_state.positions.copy()&#xA;total_accepted, total_proposed = 0, 0&#xA;&#xA;print('TOTAL PARTICLES: ', sampler_state.n_particles)&#xA;for ii in range(timesteps):&#xA;    for jj in range(sampler_state.n_particles):&#xA;        move = AddGaussianVector(atom_subset=[jj])&#xA;        move.apply(thermodynamic_state, sampler_state)&#xA;        if move.n_accepted == 1:&#xA;            total_accepted += 1&#xA;        total_proposed += 1&#xA;&#xA;    current_state = sampler_state.positions.copy()&#xA;    # measure euclidean distance&#xA;    d.append(distance(current_state, correct_state))&#xA;&#xA;    # measure energy&#xA;    sampler_state.apply_to_context(context, ignore_velocities=True)&#xA;    e.append(thermodynamic_state.reduced_potential(context))&#xA;&#xA;fig, ((ax1),(ax2)) = plt.subplots(2, 1, sharex=True)&#xA;ax1.plot(d, label='Euclidean dist')&#xA;ax1.set_title('Euclidean Distance to ground state')&#xA;ax1.set_ylabel('Euclidean Distance (nm)')&#xA;ax2.plot(e, label='Energy')&#xA;ax2.set_yscale('log')&#xA;ax2.set_title('Energy of conformation')&#xA;ax2.set_xlabel('Timesteps')&#xA;ax2.set_ylabel('Energy')&#xA;ax2.text(2, 10, r'Original Energy {}'.format(e[0]), fontsize=15)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Edit: I've tried visualizing it as per a comment. I'm not sure if anything particular sticks out. The gif begins when the bottom left axis starts at -0.5.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q9CH1.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q9CH1.gif&quot; alt=&quot;particles of alenine dipeptide as metropolis moves are applied&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2190" LastEditorUserId="52" LastEditDate="2021-03-09T05:40:13.653" LastActivityDate="2021-03-11T10:52:32.643" Title="Metropolis algorithm reduces energy in molecular simulation, but does not decrease euclidean distance" Tags="|molecular-dynamics|python|open-source|monte-carlo|from-chem-se|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4459" PostTypeId="1" CreationDate="2021-03-08T01:34:09.280" Score="8" ViewCount="243" Body="&lt;p&gt;I am trying to reproduce the 2D SAXS interference pattern of bulk water via &lt;em&gt;ab initio&lt;/em&gt; MD methods as shown in the figure below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wNluN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wNluN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The main aim is to recreate figure (a) via averaging MD configurations of bulk water. To do this. I ran QM/MM simulations of water in CP2K to get the electron density of bulk water. The water molecules were selected so as to create a spherical volume in the middle of the simulation box.&lt;/p&gt;&#xA;&lt;p&gt;The structure factor &lt;span class=&quot;math-container&quot;&gt;$S_{\vec{G}}$&lt;/span&gt; can be written as the fourier transform of the electron density:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ n_{\vec{G}} = \frac{1}{V}\sum\limits_j e^{-i\vec{G}\cdot\vec{r}_j}\int n_j\left(\vec{r}'\right)e^{-i\vec{G}\cdot\vec{r'}}d\vec{r}'\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation} S_{\vec{G}} =Vn_{\vec{G}} = \sum\limits_j f_j\left(G\right)e^{-i\vec{G}\cdot\vec{r}_j}, \tag{2}\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;so the simplest way to reproduce the above figure seem to be to perform the fourier transform of the electron density cube files obtained from the MD simulations and average them over multiple configurations. However in my case, I am getting a spike in the q-space corresponding to the center zero frequency.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/qGs9x.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qGs9x.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does anyone here has any experience with this type of scenario or has tried to replicate the SXRS spectra of water?&lt;/strong&gt; Any suggestions would be helpful.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2021-09-21T22:36:22.523" LastActivityDate="2021-09-21T22:36:22.523" Title="How to reproduce 2D small-angle X-ray scattering (SAXS) interferogram of water via ab-initio MD methods?" Tags="|molecular-dynamics|ab-initio-calculations|spectroscopy|x-ray-diffraction|water|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4460" PostTypeId="1" AcceptedAnswerId="4462" CreationDate="2021-03-08T15:27:47.663" Score="7" ViewCount="1123" Body="&lt;p&gt;I want to calculate the formation energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt; using VASP. What should be the initial steps to perform this run? What &lt;code&gt;INCAR&lt;/code&gt; tags are required? Any help would be appreciated. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-09T11:18:23.063" LastActivityDate="2021-03-09T11:18:23.063" Title="VASP input file for formation energy calculation" Tags="|density-functional-theory|vasp|software-input-file-request|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4461" PostTypeId="2" ParentId="4457" CreationDate="2021-03-09T05:45:23.137" Score="6" Body="&lt;p&gt;As far as I understand, this warning can be safely ignored. While parsing a cif structure, the &lt;code&gt;get_spacegroup()&lt;/code&gt; function in the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/_modules/ase/io/cif.html&quot; rel=&quot;noreferrer&quot;&gt;cif parser&lt;/a&gt; of ASE, checks whether the space group evaluated by ASE is consistent with the cell symmetry mentioned in the cif file. The relevant part of the function is shown below:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;if setting_name:&#xA;            no = Spacegroup(spacegroup).no&#xA;            if no in rhombohedral_spacegroups:&#xA;                if setting_name == 'hexagonal':&#xA;                    setting = 1&#xA;                elif setting_name in ('trigonal', 'rhombohedral'):&#xA;                    setting = 2&#xA;                else:&#xA;                    warnings.warn(&#xA;                        'unexpected crystal system %r for space group %r' % (&#xA;                            setting_name, spacegroup))&#xA;            # FIXME - check for more crystal systems...&#xA;            else:&#xA;                warnings.warn(&#xA;                    'crystal system %r is not interpreted for space group %r. '&#xA;                    'This may result in wrong setting!' % (&#xA;                        setting_name, spacegroup))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, &lt;code&gt;setting_name&lt;/code&gt; denotes the cell symmetry setting mentioned in the cif file and &lt;code&gt;no&lt;/code&gt; is the space group of the structure as evaluated by ASE. As can be seen &lt;strong&gt;this check has been currently implemented only for rhombohedral crystal systems&lt;/strong&gt; and for any other crystal systems it shows the warning in the question (notice the comment: &lt;code&gt;# FIXME - check for more crystal systems...&lt;/code&gt;). When the checks are implemented for other crystal symmetries the warnings will also go away.&lt;/p&gt;&#xA;&lt;p&gt;For the warnings in the question, it can be manually verified that the spacegroup numbers are consistent with the cell symmetry mentioned in the cif file. For eg, from &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_space_groups&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2021-03-09T05:45:23.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4462" PostTypeId="2" ParentId="4460" CreationDate="2021-03-09T11:17:43.567" Score="3" Body="&lt;p&gt;If your structure is relaxed. The total energy can be calculated with a self-consistent calculation.&lt;/p&gt;&#xA;&lt;p&gt;An &lt;code&gt;INCAR&lt;/code&gt; template you may refer to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System:&#xA;ISTART=0 &#xA;ICHARG=2  &#xA;ENCUT=500   &#xA;EDIFF=1E-6    &#xA;NELM=300  &#xA;ISMEAR=0   &#xA;SIGMA=0.05       &#xA;IALGO=38    &#xA;&#xA;##Spin-related&#xA;#ISPIN=2  &#xA;#MAGMOM=17*0        &#xA;#LSORBIT=.TRUE.      &#xA;#SAXIS= 0 0 1     &#xA;#ISYM=0   &#xA;&#xA;##Output:&#xA;LCHARG=.TRUE.&#xA;LWAVE=.TRUE.  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS: For the formation energy calculation, you need to find the lowest-energy configuration of bulk Mg and Si.&lt;/p&gt;&#xA;&lt;p&gt;And this post also may helpful: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4381/how-to-calculate-the-formation-energy-of-a-monolayer-using-vasp/4382#4382&quot;&gt;How to calculate the formation energy of a monolayer using VASP?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-09T11:17:43.567" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4463" PostTypeId="2" ParentId="4456" CreationDate="2021-03-09T13:33:16.233" Score="2" Body="&lt;p&gt;VASP with the PAW method can't take a fully relativistic effect, which can be taken into account only by solving the Dirac equation. The SOC effect in the PAW method is included with the following perturbed Hamiltonian (zeroth-order-regular approximation):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_{SO}^{\alpha\beta}=-\dfrac{\hbar^2}{(2m_ec)^2} \dfrac{K(r)}{r}\dfrac{dV(r)}{dr}\vec{\sigma}^{\alpha\beta}\cdot\vec{L} \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the angular momentum operators &lt;span class=&quot;math-container&quot;&gt;$\vec{L}$&lt;/span&gt; is defined as&#xA;&lt;span class=&quot;math-container&quot;&gt;$\vec{L}=\vec{r}\times \vec{p}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma=(\sigma_x, \sigma_y, \sigma_z)$&lt;/span&gt; are the &lt;span class=&quot;math-container&quot;&gt;$(2 \times 2)$&lt;/span&gt; Pauli spin matrices, &lt;span class=&quot;math-container&quot;&gt;$V(\vec{r})$&lt;/span&gt; is the spherical part of the effective all-electron (AE) potential within the PAW sphere, and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$K(\vec{r})=\left(1-\dfrac{V(\vec{r})}{2m_e c^2} \right)^{-2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Reference: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.93.224425&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. B 93, 224425&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Take the bulk Bi2Te3 as an example, I test what you are asking.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE Potentials:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TITEL  = PAW_PBE Bi 08Apr2002&#xA;TITEL  = PAW_PBE Te 08Apr2002&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE total energy without SOC (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E0= -.18384597E+02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE total energy with SOC (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E0= -.19687316E+02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE energy difference (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-1.302718&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;LDA Potentials:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  TITEL  = PAW Bi 03Oct2001&#xA;  TITEL  = PAW Te 03Oct2001&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;LDA total energy without SOC (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  E0= -.21427747E+02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;LDA total energy with SOC (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  E0= -.22785609E+02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;LDA energy difference (eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  -1.3578620&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There is a difference here.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-09T13:33:16.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4464" PostTypeId="2" ParentId="467" CreationDate="2021-03-09T14:48:15.177" Score="13" Body="&lt;h2&gt;VESTA&lt;/h2&gt;&#xA;&lt;p&gt;You can try VESTA.&#xA;It is good, lightweight and works on Windows and Linux platforms.&#xA;It is good for viewing and production level image quality manipulation.&#xA;&lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;noreferrer&quot;&gt;https://jp-minerals.org/vesta/en/download.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="5" LastEditDate="2021-03-09T15:46:32.670" LastActivityDate="2021-03-09T15:46:32.670" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4465" PostTypeId="1" AcceptedAnswerId="4821" CreationDate="2021-03-09T17:31:17.173" Score="10" ViewCount="149" Body="&lt;p&gt;I am currently reading this &lt;a href=&quot;https://doi.org/10.1063/1.2938860&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper by Noid et. al.&lt;/a&gt; on the rigorous bridge between atomistic and coarse-grained simulations.&lt;/p&gt;&#xA;&lt;p&gt;In the paper, he defined a linear map from the atomistic coordinates and momenta &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}^n, \mathbf{p}^n$&lt;/span&gt; to the coarse-grained coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}^N, \mathbf{P}^N$&lt;/span&gt;. He then defined the Hamiltonian for both frames of reference, &lt;span class=&quot;math-container&quot;&gt;$h\, (\text{all-atom}),H \,(\text{CG})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The part of the paper I don't understand is when they evaluate the forces on the CG model (equations 22-26).&#xA;They write,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\tag{1} &#xA;\mathbf{F}_I(\mathbf{R}^N) &amp;amp;= -\frac{\partial U (\mathbf{R}^N)}{\partial \mathbf{R}_I} \\ &#xA;\tag{2}&#xA;                           &amp;amp;= \frac{k_BT}{z(\mathbf{R}^N)}\frac{\partial z(\mathbf{R}^n)}{\partial \mathbf{R}_I} &#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{3}&#xA;\frac{k_BT}{z(\mathbf{R}^N)} \int d\mathbf{r}^n e^{-u(\mathbf{r}^n)/k_BT}\prod_{J\neq I} \delta (M_{RJ}(r^n)-\mathbf{R}_J)\frac{\partial}{\partial \mathbf{R}_I}\delta \left( \sum _{i\in \mathcal{I}_I } c_{Ii}\mathbf{r}_i-\mathbf{R}_I\right)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is the part that confuses me. I know that:&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{R}_I = \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i\tag{4}\label{4}$$&lt;/span&gt;&#xA;So shouldn't &lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial X}{\partial \mathbf{R}_I} = \sum _{i\in \mathcal{I}_I} \frac{\partial X}{\partial \mathbf{r}_i} \frac{\partial \mathbf{r}_i}{\mathbf{R}_I} = \sum _{i\in \mathcal{I}_I}\frac{\partial X}{\partial \mathbf{r}_i}\frac{1}{c_{Ii}}\tag{5}$$&lt;/span&gt;&#xA;be the case?&#xA;However, equation 23 simply states that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial}{\partial \mathbf{R}_I} \delta \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right) = -\frac{1}{c_{Ik}} \frac{\partial }{\partial \mathbf{r}_k} \delta \left(\sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I\right)\tag{6}\label{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How does this equation work?&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, I don't understand how they perform integration by parts on the higher-dimensional integral they have here, and arrive at the equation that they do. I would greatly appreciate it if someone could help me reach equation 26 from  equation 22 in the paper.&lt;/p&gt;&#xA;&lt;p&gt;I appreciate any advice that you may have!!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="7" LastEditDate="2021-07-19T15:14:00.273" LastActivityDate="2022-06-01T03:07:49.517" Title="Understanding the rigorous bridge between atomistic and coarse-grained simulations" Tags="|molecular-dynamics|statistical-thermodynamics|reproducing-data-from-papers|coarse-grained|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4466" PostTypeId="1" CreationDate="2021-03-09T17:39:11.167" Score="5" ViewCount="388" Body="&lt;p&gt;I implemented the &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0503172&quot; rel=&quot;nofollow noreferrer&quot;&gt;standard numerical algorithm&lt;/a&gt; for calculating the Berry curvature in MATLAB. For a given 2D system, I can visualize the Berry curvature over parameter space. If I sum the Berry curvature at all points in a region of parameter space, I am effectively taking the Berry curvature area integral inside this region. If this region is the entire Brillouin zone, I get the first Chern number.&lt;/p&gt;&#xA;&lt;p&gt;Due to Stokes' theorem, this area integral is nothing but the gauge-invariant Berry phase due to adiabatic traversal along a parameter space loop bordering this region. In other words, in the absence of gauge singularities, the Berry curvature &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; area integral is equal to the Berry connection &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; line integral:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\oint A = \iint F. \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For my question, consider a graphene-like system where the energy dispersion is degenerate at isolated Dirac points. It is known that the third component of the Berry curvature vanishes everywhere except at the Dirac points, where it diverges to infinity. So, people do not seem to define the Chern number in gapless systems because the Berry curvature is not well-defined. However, they have no problem using the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; integral to calculate the Berry phase around the degeneracy. This phase has even been experimentally detected in graphene, Weyl, etc systems.&lt;/p&gt;&#xA;&lt;p&gt;The numerical scheme requires shifting the discretized parameter space by a small factor to keep the Berry curvature from blowing up numerically.&#xA;Due to this, when I plot the Berry curvature over parameter/k-space, I see the Berry curvature peaked sharply near the Dirac points (instead of diverging to infinity). However, my issue is that I don't understand why this finite peak correctly gives the expected Berry phase. Summing &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; in the vicinity of this peak correctly gives the &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; Berry phase expected around the degeneracy. Yet, this peak seems to be a consequence of the numerical method (i.e. shifting by a small factor).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why does this ill-defined Berry curvature give the correct Berry phase around a degeneracy, seemingly as a consequence of the numerical scheme?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-09-21T22:33:30.817" LastActivityDate="2021-09-21T22:33:30.817" Title="Why does numerical computation of Berry curvature give me a correct Berry phase when it is supposed to diverge?" Tags="|condensed-matter|quantum-mechanics|solid-state-physics|topological-insulators|berry-phase|" AnswerCount="0" CommentCount="9" ClosedDate="2022-08-23T22:17:48.870" ContentLicense="CC BY-SA 4.0" />
  <row Id="4467" PostTypeId="2" ParentId="4458" CreationDate="2021-03-09T19:10:46.690" Score="9" Body="&lt;p&gt;Most of the problem here appears to be because constraints in the test system default to &lt;code&gt;app.HBonds&lt;/code&gt;, which means all bonds to hydrogen atoms are constrained. Something goes very weird when you force a large, unphysical change on the system, and then try to apply HBond constraints (it looks to me like it isn't even constraining HBonds to the unphysical lengths; there's probably a limitation in the constraint algorithm).&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, by creating the test system with:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;alanine = testsystems.AlanineDipeptideVacuum(constraints=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I got following at frames 0, 25, and 100:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EbjRPt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EbjRPt.png&quot; alt=&quot;Frame 0&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/eJYrst.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eJYrst.png&quot; alt=&quot;Frame 25&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/bo1sQt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bo1sQt.png&quot; alt=&quot;Frame 100&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That's starting to look a decent bit like alanine dipeptide. Here's the 'distance' plot:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cSqEe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cSqEe.png&quot; alt=&quot;distance&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;By the way, you may be making another assumption that isn't quite true: don't assume that the distance will go to zero. You've done nothing to align your atoms with the reference structure. I think what you're really wanting to look at is a root-mean-square-deviation (RMSD) calculation, which would include that alignment. Tools like &lt;a href=&quot;http://mdtraj.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDTraj&lt;/a&gt; and &lt;a href=&quot;https://www.mdanalysis.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDAnalysis&lt;/a&gt; implement RMSD and related algorithms.&lt;/p&gt;&#xA;&lt;p&gt;As suggested in the comments, it's easier to see what was going wrong if you use a tool that is designed for visualizing chemical structures, instead of just a 3D scatterplot. Much of the backbone is in place even with constraints. Godzilla mentions &lt;a href=&quot;https://pymol.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyMOL&lt;/a&gt; in the comment. I used &lt;a href=&quot;http://nglviewer.org/nglview/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NGLView&lt;/a&gt;. Here's what I saw with constraints after 100 steps:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EkDeFm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EkDeFm.png&quot; alt=&quot;with_constraints&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The bonds to hydrogens are clearly all wrong, but the heavy atoms look pretty much like alanine dipeptide. Having the atom colors (and, in my notebook, the atom labels when I hover over them) makes it much easier to diagnose the issue.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Addendum: To get from a list of positions to a visualization in NGLView, the process I used is: data &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; MDTraj &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; NGLView. The data you need is a list of snapshot coordinates, so I modified the OP code to save &lt;code&gt;current_state&lt;/code&gt; at every frame in a list called &lt;code&gt;trajectory&lt;/code&gt; (same as how energies are saved in &lt;code&gt;e&lt;/code&gt; and distances saved in &lt;code&gt;d&lt;/code&gt;). From there it is really easy, because OpenMMTools test systems are designed to integrate with MDTraj (and so is NGLView):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import mdtraj as md&#xA;import nglview as nv&#xA;&#xA;# alanine is the openmmtools testsystem&#xA;# trajectory is a list or np.array with shape (n_frames, n_atoms, 3)&#xA;# no explicit units; values in nm&#xA;traj = md.Trajectory(trajectory, topology=alanine.mdtraj_topology)&#xA;view = nv.show_mdtraj(traj)&#xA;view  # return the view so it is shown in notebook&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# get the image for a specific frame number&#xA;view.frame=25&#xA;view.download_image(&amp;quot;frame25.gif&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A few points on that:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Installing NGLView for classic Jupyter notebook often requires the command &lt;code&gt;jupyter-nbextension enable nglview --py --sys-prefix&lt;/code&gt; after a conda/pip install to enable it. Installing NGLView in Jupyter Lab is a little messier (see &lt;a href=&quot;https://github.com/nglviewer/nglview/blob/2cd42979e0c39c163b6728f59ffea6e9d8cd56db/devtools/nglview-jupyterlab.sh&quot; rel=&quot;nofollow noreferrer&quot;&gt;this script&lt;/a&gt;; currently [March 2021] NGLView does not yet work with Jupyter Lab 3.0).&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;topology&lt;/code&gt; is how MDTraj knows what each atom is and what bonds there are. I think that some bonds are not shown because either MDTraj or NGLView refuses to believe that they could actually be bonds, based on the initial configuration. If you weren't using OpenMMTools, you could get an MDTraj topology from an OpenMM topology with &lt;code&gt;md.Topology.from_openmm&lt;/code&gt;, or you could save to a file that contains topology information and load that in MDTraj with &lt;code&gt;md.load(filename)&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;You could use other visualization tools (PyMOL, VMD, etc) by using &lt;code&gt;traj.save('filename.pdb')&lt;/code&gt; and loading the PDB trajectory in the other tool. (I suggest PDB here because it includes topology information and is widely supported; many other formats are more efficient on disk but require a separate file for topology.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-03-11T10:52:32.643" LastActivityDate="2021-03-11T10:52:32.643" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4468" PostTypeId="5" CreationDate="2021-03-09T23:11:52.650" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-09T23:11:52.650" LastActivityDate="2021-03-09T23:11:52.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4469" PostTypeId="4" CreationDate="2021-03-09T23:11:52.650" Score="0" Body="Questions about Markovianity and non-Markovianity." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-09T23:11:52.650" LastActivityDate="2021-03-09T23:11:52.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4470" PostTypeId="2" ParentId="4453" CreationDate="2021-03-10T03:21:42.427" Score="6" Body="&lt;p&gt;The question is not very well-posed. However, the question appears to be about whether rotational invariance is honored by LCAO calculations.&lt;/p&gt;&#xA;&lt;p&gt;The old-time approach is to use Cartesian basis functions. Translating our origin to the nucleus, we can write the Cartesian basis functions in the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$\psi({\bf r}) = N x^k y^l z^m \exp(-\alpha r^2)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\lambda:=k+l+m$&lt;/span&gt; is the angular momentum of the function.&lt;/p&gt;&#xA;&lt;p&gt;Basis functions are added one shell at a time: there is one cartesian S function with &lt;span class=&quot;math-container&quot;&gt;$(k,l,m)=(0,0,0)$&lt;/span&gt;, three P functions with &lt;span class=&quot;math-container&quot;&gt;$(1,0,0)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0,1,0)$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$(0,0,1)$&lt;/span&gt;, and six D functions: &lt;span class=&quot;math-container&quot;&gt;$(2,0,0)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0,2,0)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0,0,2)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(1,1,0)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(1,0,1)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(0,1,1)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;While Cartesian functions were used in the early days of quantum chemistry, and form part of e.g. the infamous 6-31G* basis set, they have mostly fallen out of use, since they contain angular degeneracies, the number of which increases rapidly in the angular momentum.&lt;/p&gt;&#xA;&lt;p&gt;What are these degeneracies? We know that spherical harmonics &lt;span class=&quot;math-container&quot;&gt;$Y_l^m$&lt;/span&gt;, or equivalently their real counterparts &lt;span class=&quot;math-container&quot;&gt;$Y_{lm}$&lt;/span&gt; form a complete set of angular distributions. For S states we have &lt;span class=&quot;math-container&quot;&gt;$Y_{00}$&lt;/span&gt;, for P states we have &lt;span class=&quot;math-container&quot;&gt;$Y_{1,-1}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_{1,0}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Y_{1,1}$&lt;/span&gt;, and for D states we have &lt;span class=&quot;math-container&quot;&gt;$Y_{2,-2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_{2,-1}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_{2,0}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_{2,1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Y_{2,2}$&lt;/span&gt;. That is, for S or P functions it doesn't matter if you use cartesians or pure spherical harmonics; but for D it starts to matter: we have 6 cartesians but only 5 pure angular functions.&lt;/p&gt;&#xA;&lt;p&gt;If you write out &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; in spherical harmonics (you can find the expressions in the literature), you can use the closure properties to derive what the angular form for &lt;span class=&quot;math-container&quot;&gt;$x^k y^l z^m$&lt;/span&gt; is. However, it's pretty simple to see that if you combine three of the six D functions &lt;span class=&quot;math-container&quot;&gt;$(2,0,0) + (0,2,0) + (0,0,2)$&lt;/span&gt; you get &lt;span class=&quot;math-container&quot;&gt;$x^2 + y^2 + z^2 = r^2$&lt;/span&gt; which is an S function, &lt;span class=&quot;math-container&quot;&gt;$Y_{00}$&lt;/span&gt;. This means that the cartesian D shell is formed of the 5 pure D functions, and a S-type contaminant.&lt;/p&gt;&#xA;&lt;p&gt;In quantum chemical calculations, the pure basis turns out to be of the form &lt;span class=&quot;math-container&quot;&gt;$\psi({\bf r}) = N r^l Y_{lm} \exp(-\alpha r^2)$&lt;/span&gt;. This is very convenient, since one can express the solid harmonics &lt;span class=&quot;math-container&quot;&gt;$Y_{lm}$&lt;/span&gt; in terms of the cartesian functions. You can find a table &lt;a href=&quot;http://en.wikipedia.org/wiki/Solid_spherical_harmonics&quot; rel=&quot;nofollow noreferrer&quot;&gt;on Wikipedia&lt;/a&gt;, but it is also quite simple to program up the bare equations to get the translation for arbitrary angular momentum. The transformation has also been discussed by Schlegel and Frisch in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.560540202&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 54, 83 (1995)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, finally.. why are LCAO electronic structure calculations rotationally invariant?&lt;span class=&quot;math-container&quot;&gt;$^*$&lt;/span&gt; No matter how you rotate the molecule, the spherical harmonics span the same angular degrees of freedom: e.g. when you rotate &lt;span class=&quot;math-container&quot;&gt;$Y_{10}$&lt;/span&gt; into a new coordinate system, it is still expressible in terms of &lt;span class=&quot;math-container&quot;&gt;$Y_{10}$&lt;/span&gt;,  &lt;span class=&quot;math-container&quot;&gt;$Y_{1,-1}$&lt;/span&gt; and  &lt;span class=&quot;math-container&quot;&gt;$Y_{11}$&lt;/span&gt;; the expansion coefficients are given by the so-called Wigner's &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; matrix. This means you will always get the same energy regardless of how you rotate your system; the individual components of the wave function will just change.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^*$&lt;/span&gt; Rotational invariance doesn't hold fully for e.g. density functional calculations, since the quadrature grids employed to integrate the density functional are not rotationally invariant. The error can, however, be made insignificantly small by using a large enough quadrature grid. This error is also removed by default by transforming the molecule into a standard orientation; see &lt;a href=&quot;https://doi.org/10.1016/0009-2614(93)80125-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Phys. Lett. 209, 506 (1993)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Addendum based on postscript: sounds like your problem is just not understanding how the molecular orbitals are defined. You don't need to try to align the orbitals; they arise automatically by solving the self-consistent field equations. The molecular orbitals are linear combinations of the atomic orbitals, so they'll automatically figure out what is the best combination. There are no atomic orbitals in a molecule, they're just basis functions used in the expansion, the coefficients of which are found by minimizing the total energy of the resulting wave function.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-03-16T22:49:27.850" LastActivityDate="2021-03-16T22:49:27.850" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4471" PostTypeId="2" ParentId="4445" CreationDate="2021-03-10T03:50:05.860" Score="5" Body="&lt;p&gt;So this question is related to the recent discussion in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4407/procedure-to-classify-errors-in-kohn-sham-dft&quot;&gt;Procedure to classify errors in Kohn-Sham DFT&lt;/a&gt; where I already gave the general procedure: get the density from some level of theory, and use it to run a single-point DFT calculation.&lt;/p&gt;&#xA;&lt;p&gt;This question was about how to do this in Q-Chem; it's actually quite simple. Here's an example input for a calculation on the water molecule, where I first run Hartree-Fock to get the reference density, and then read in the wave function to a calculation with the PBE functional&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;span class=&quot;math-container&quot;&gt;$molecule&#xA;0 1&#xA;O        0.000000    0.000000    0.117790 &#xA;H        0.000000    0.755453   -0.471161 &#xA;H        0.000000   -0.755453   -0.471161 &#xA;$&lt;/span&gt;end&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$rem&#xA;basis pcseg-2&#xA;method hf&#xA;$&lt;/span&gt;end&#xA;&#xA;@@@&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$molecule&#xA;read&#xA;$&lt;/span&gt;end&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$rem&#xA;basis pcseg-2&#xA;scf_guess read&#xA;method pbe&#xA;max_scf_cycles 0&#xA;$&lt;/span&gt;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Setting the maximum number of SCF cycles to 0 in Q-Chem means that the program will just evaluate a single-point energy without changing the orbitals. The output for the second part of the job is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; The restricted Kohn-Sham energy will be evaluated&#xA; The orbitals will not be altered&#xA; Exchange:  PBE      Correlation:  PBE&#xA; Using SG-1 standard quadrature grid&#xA; Using Q-Chem read-in guess as SCF_GUESS READ specified.&#xA;&#xA;Avoiding writing the new MOs to disk !!! &#xA; ---------------------------------------&#xA;  Cycle       Energy         DIIS Error&#xA; ---------------------------------------&#xA;    1     -76.3736280198      6.70E-03 Convergence criterion met&#xA; ---------------------------------------&#xA; SCF time:  CPU 0.17 s  wall 0.17 s&#xA; SCF   energy in the final basis set = -76.37362802&#xA; Total energy in the final basis set = -76.37362802&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you also need the converged PBE energy, removing the line that sets &lt;code&gt;max_scf_cycles&lt;/code&gt; to zero leads to the following output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Exchange:  PBE      Correlation:  PBE&#xA; Using SG-1 standard quadrature grid&#xA; A restricted SCF calculation will be&#xA; performed using DIIS&#xA; SCF converges when DIIS error is below 1.0e-05&#xA; ---------------------------------------&#xA;  Cycle       Energy         DIIS error&#xA; ---------------------------------------&#xA;    1     -76.3736280198      6.70e-03  &#xA;    2     -76.3810410874      4.41e-04  &#xA;    3     -76.3810699365      3.92e-04  &#xA;    4     -76.3811039575      2.38e-04  &#xA;    5     -76.3811190178      2.47e-05  &#xA;    6     -76.3811192100      3.84e-07  Convergence criterion met&#xA; ---------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since the DIIS error is quite small in the first iteration, and the convergence is very rapid after that, you see that the HF density is a pretty good guess for the PBE functional; this was one of the findings in my assessment of initial guesses, &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 1593 (2019)&lt;/a&gt;. You also see that optimizing the electron density lowers the energy by 7.5 &lt;span class=&quot;math-container&quot;&gt;$mE_h$&lt;/span&gt;, but this is how you would also reintroduce the density errors.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-03-10T03:50:05.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4472" PostTypeId="1" AcceptedAnswerId="4473" CreationDate="2021-03-10T11:47:07.843" Score="7" ViewCount="178" Body="&lt;p&gt;I want to do band structure calculation of Magnesium silicide for GGA  in &lt;code&gt;VASP&lt;/code&gt;. Can anyone please help how to do this by setting initial &lt;code&gt;INCAR&lt;/code&gt; tags and &lt;code&gt;KPOINTS&lt;/code&gt; file?&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-03-24T03:22:16.183" LastActivityDate="2022-09-08T02:28:08.203" Title="Band structure calculation" Tags="|density-functional-theory|vasp|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4473" PostTypeId="2" ParentId="4472" CreationDate="2021-03-10T13:01:55.093" Score="6" Body="&lt;p&gt;I assume your structure is relaxed.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The 1st step: self-consistent calculation to obtain converged charge density (uniform K mesh).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The 2nd step: non-self-consistent calculation to obtain the eigenvalue along a high symmetry path by reading previous converged charge density.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PS: you can generate the high symmetry path with &lt;a href=&quot;https://vaspkit.com/tutorials.html#pre-process-band-structure-pure-functional&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-10T13:01:55.093" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4474" PostTypeId="1" AcceptedAnswerId="4476" CreationDate="2021-03-03T07:30:22.187" Score="10" ViewCount="4417" Body="&lt;p&gt;I want to make a python script that will load an xyz file. From the xyz parameters, I need to find the distance between atoms, angle and dihedral between atoms.&lt;br /&gt;&#xA;If I have a xyz coordinate in this matrix form:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4&#xA;test&#xA;O 0.0 0.0 0.0&#xA;H 1.0 0.0 0.0&#xA;H 0.0 1.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I want to find the bond parameters by simply using pythagoras formula using only the indices of the matrix. If I need to find the OH distance, I can give the indices and the value will come up.&lt;br /&gt;&#xA;Now this is easy for a small system, It will get tiresome for a large one.&#xA;This is why I want to use a small script, that can load a xyz file, set index and allow user to find the bond parameters.&lt;/p&gt;&#xA;" OwnerUserId="2194" OwnerDisplayName="Prasanta Bandyopadhyay" LastActivityDate="2021-03-13T05:14:12.663" Title="How to make a python code that can read a .xyz file and find distance, angle and dihedral angle between atoms?" Tags="|python|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4475" PostTypeId="2" ParentId="4474" CreationDate="2021-03-03T08:19:34.090" Score="12" Body="&lt;p&gt;It helps to know that in computational chemistry the collection of distance, angle and dihedral coordinates is collectively known as &amp;quot;z-matrix coordinates&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Unless you care to &lt;a href=&quot;https://en.wikipedia.org/wiki/Reinventing_the_wheel&quot; rel=&quot;noreferrer&quot;&gt;reinvent the wheel&lt;/a&gt; (which is not a bad exercise), it suffices to perform a web search for &amp;quot;python internal to zmatrix coordinates&amp;quot;.  For instance, the &amp;quot;&lt;a href=&quot;https://chemcoord.readthedocs.io/en/v2.0.4/&quot; rel=&quot;noreferrer&quot;&gt;chemcoord&lt;/a&gt;&amp;quot; python library claims to be capable of performing the desired transformation. &lt;a href=&quot;https://nbviewer.jupyter.org/github/mcocdawc/chemcoord/blob/v2.0.4/Tutorial/Zmat.ipynb&quot; rel=&quot;noreferrer&quot;&gt;Tutorials are available&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="120" OwnerDisplayName="Buck Thorn" LastActivityDate="2021-03-03T08:19:34.090" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4476" PostTypeId="2" ParentId="4474" CreationDate="2021-03-03T19:18:22.507" Score="13" Body="&lt;p&gt;Assuming that you know how to calculate the dihedral angle algebraically, this python 3 code can be used. The data is from the xray structure of insulin 2INS. The angle is 136.7 degrees.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Dihedral angles&#xA;phecd1 = np.array([ -7.497, 20.877, -0.865]) # xyz from 2INS.pdb  atom 349&#xA;phecd2 = np.array([ -5.644, 21.663,  0.493]) # atom 350 &#xA;tyrcd1 = np.array([ -4.106, 13.747,  5.282]) # atom 360  &#xA;tyrcd2 = np.array([ -1.869, 14.466,  4.723]) # atom 361  &#xA;vec_a = phecd2 - phecd1 &#xA;vec_b = tyrcd1 - phecd2  &#xA;vec_c = tyrcd2 - tyrcd1 &#xA;&#xA;m = np.cross(vec_a,vec_b)&#xA;n = np.cross(vec_b,vec_c)&#xA;psi = np.sign(np.dot(vec_a,n))*np.arccos(np.dot(n,m)/( np.sqrt(np.dot(n,n)) *np.sqrt(np.dot(m,m)) ) )&#xA;print('{:s}{:6.2f}{:s}'.format('dihedral angle =',psi*180/np.pi,' degrees') )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xPdl8m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xPdl8m.png&quot; alt=&quot;dihedral angle &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="porphyrin" LastActivityDate="2021-03-03T19:18:22.507" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4477" PostTypeId="1" AcceptedAnswerId="4648" CreationDate="2021-03-11T03:48:36.700" Score="12" ViewCount="497" Body="&lt;p&gt;I am trying to build a supercell of the following (below) molecular crystal from its .cif file. How do I sort a supercell here according to each molecule in the supercell? I'm not tethered to a specific software to do this, just something that works as I want it to.&lt;/p&gt;&#xA;&lt;p&gt;I have tried using ASE, Vesta, and Avogadro to do this, without success, along with the pymatgen suggestion below. It seems that these software are better set up to do this for an ionic crystal rather than a supercell of a molecule. For example, in the Atomic Simulation Environment (ASE), when I use &lt;code&gt;get_chemical_symbols()&lt;/code&gt;, I see more atoms than there are in a single molecule. Furthermore, I do not know how to distinguish between the carbon bonded to the hydrogens and the central carbon (molecule is CH3CN). What I want is an output file (say, .xyz) with all of the atoms, in a specified order (say, H, H, H, methyl carbon, nitrile carbon, N), for molecule 1 in the supercell, followed by all of the atoms in the same specified order, for molecule 2, and so on.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;data_I&#xA;_audit_creation_method     SHELXL&#xA;_journal_date_recd_electronic     2002-06-07&#xA;_journal_date_accepted     2002-09-25&#xA;_journal_name_full     'Acta Crystallographica, Section B'&#xA;_journal_year     2002&#xA;_journal_volume     58&#xA;_journal_issue      6&#xA;_journal_page_first     1005&#xA;_journal_page_last     1010&#xA;_journal_paper_category     FA&#xA;_chemical_name_systematic     'acetonitrile'&#xA;_chemical_name_common     ?&#xA;_chemical_formula_moiety     'C2 H3 N'&#xA;_chemical_formula_sum     'C2 H3 N'&#xA;_chemical_formula_structural     'C H3 C N'&#xA;_chemical_formula_analytical     ?&#xA;_chemical_formula_weight     41.05&#xA;_chemical_melting_point     ?&#xA;_symmetry_cell_setting     'monoclinic'&#xA;_symmetry_space_group_name_H-M     'P 21/c'&#xA;_symmetry_space_group_name_Hall     '-P 2ybc'&#xA;loop_&#xA;    _symmetry_equiv_pos_as_xyz&#xA;    'x, y, z'&#xA;    '-x, y+1/2, -z+1/2'&#xA;    '-x, -y, -z'&#xA;    'x, -y-1/2, z-1/2'&#xA;_cell_length_a     4.102(3)&#xA;_cell_length_b     8.244(7)&#xA;_cell_length_c     7.970(7)&#xA;_cell_angle_alpha     90.00&#xA;_cell_angle_beta     100.10(10)&#xA;_cell_angle_gamma     90.00&#xA;_cell_volume     265.3(4)&#xA;_cell_formula_units_Z     4&#xA;_cell_measurement_reflns_used     25&#xA;_cell_measurement_theta_min     5.20&#xA;_cell_measurement_theta_max     21.48&#xA;_cell_measurement_temperature     201(2)&#xA;_exptl_crystal_description     'cylinder'&#xA;_exptl_crystal_colour     'colourless'&#xA;_exptl_crystal_size_max     1.2&#xA;_exptl_crystal_size_mid     0.5&#xA;_exptl_crystal_size_min     0.3&#xA;_exptl_crystal_size_rad     0.15&#xA;_exptl_crystal_density_diffrn     1.028&#xA;_exptl_crystal_density_meas     ?&#xA;_exptl_crystal_density_method     ?&#xA;_exptl_crystal_F_000     88&#xA;_exptl_absorpt_coefficient_mu     0.067&#xA;_exptl_absorpt_correction_type     'none'&#xA;_exptl_absorpt_correction_T_min     ?&#xA;_exptl_absorpt_correction_T_max     ?&#xA;_exptl_special_details&#xA;;&#xA; ?&#xA;;&#xA;_diffrn_ambient_temperature     201(2)&#xA;_diffrn_radiation_type     MoK\a&#xA;_diffrn_radiation_wavelength     0.71073&#xA;_diffrn_radiation_source     'fine-focus sealed tube'&#xA;_diffrn_radiation_monochromator     'graphite'&#xA;_diffrn_measurement_device     'Nonius CAD4 diffractometer'&#xA;_diffrn_measurement_method     '\w--2\q'&#xA;_diffrn_reflns_number     376&#xA;_diffrn_reflns_av_R_equivalents     0.0571&#xA;_diffrn_reflns_av_sigmaI/netI     0.0591&#xA;_diffrn_reflns_theta_min     3.58&#xA;_diffrn_reflns_theta_max     21.89&#xA;_diffrn_reflns_theta_full     21.89&#xA;_diffrn_measured_fraction_theta_max     0.99&#xA;_diffrn_measured_fraction_theta_full     0.99&#xA;_diffrn_reflns_limit_h_min     0&#xA;_diffrn_reflns_limit_h_max     4&#xA;_diffrn_reflns_limit_k_min     0&#xA;_diffrn_reflns_limit_k_max     8&#xA;_diffrn_reflns_limit_l_min     -8&#xA;_diffrn_reflns_limit_l_max     8&#xA;_diffrn_standards_number     'none'&#xA;_diffrn_standards_interval_count     'none'&#xA;_diffrn_standards_interval_time     'none'&#xA;_diffrn_standards_decay_%     'none'&#xA;_refine_special_details&#xA;;&#xA; Refinement of F^2^ against ALL reflections.  Weighted R-factors wR and&#xA; goodnesses of fit S are based on F^2^, conventional R-factors R are based&#xA; on F, with F set to zero for negative F^2^. The threshold_expression of&#xA; F^2^ &amp;gt; 2sigma(F^2^) is used only for calculating R_factors(gt) etc. and is&#xA; not relevant to the choice of reflections for refinement.  R-factors based&#xA; on F^2^ are statistically about twice as large as those based on F, and R-&#xA; factors based on ALL data will be even larger.&#xA;;&#xA;_reflns_number_total     324&#xA;_reflns_number_gt     202&#xA;_reflns_threshold_expression     'I&amp;gt;2\s(I)'&#xA;_refine_ls_structure_factor_coef     Fsqd&#xA;_refine_ls_matrix_type     full&#xA;_refine_ls_R_factor_all     0.1051&#xA;_refine_ls_R_factor_gt     0.0472&#xA;_refine_ls_wR_factor_all     0.1504&#xA;_refine_ls_wR_factor_ref     0.1106&#xA;_refine_ls_goodness_of_fit_all     1.137&#xA;_refine_ls_goodness_of_fit_ref     1.107&#xA;_refine_ls_restrained_S_all     1.137&#xA;_refine_ls_restrained_S_obs     1.107&#xA;_refine_ls_number_reflns     324&#xA;_refine_ls_number_parameters     41&#xA;_refine_ls_number_restraints     0&#xA;_refine_ls_hydrogen_treatment     'refall'&#xA;_refine_ls_weighting_scheme     calc&#xA;_refine_ls_weighting_details&#xA;              'w=1/[\s^2^(Fo^2^)+(0.0360P)^2^+0.1879P] where P=(Fo^2^+2Fc^2^)/3'&#xA;_atom_sites_solution_hydrogens     difmap&#xA;_atom_sites_solution_primary     direct&#xA;_atom_sites_solution_secondary     difmap&#xA;_refine_ls_shift/su_max     0.000&#xA;_refine_ls_shift/su_mean     0.000&#xA;_refine_diff_density_max     0.169&#xA;_refine_diff_density_min     -0.168&#xA;_refine_ls_extinction_method     SHELXL&#xA;_refine_ls_extinction_coef     0.07(4)&#xA;_refine_ls_extinction_expression&#xA;                                  'Fc^*^=kFc[1+0.001xFc^2^\l^3^/sin(2\q)]^-1/4^'&#xA;loop_&#xA;    _atom_type_symbol&#xA;    _atom_type_description&#xA;    _atom_type_scat_dispersion_real&#xA;    _atom_type_scat_dispersion_imag&#xA;    _atom_type_scat_source&#xA;    'C' 'C' 0.0033 0.0016&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'H' 'H' 0.0000 0.0000&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'N' 'N' 0.0061 0.0033&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;_computing_data_collection     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_cell_refinement     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_data_reduction     'CADAK (Savariault,1991)'&#xA;_computing_structure_solution     'SHELXS-96 (Sheldrick, 1990)'&#xA;_computing_structure_refinement     'SHELXL-96 (Sheldrick, 1996)'&#xA;_computing_molecular_graphics     'ORTEP III (Burnett &amp;amp; Johnson, 1996)'&#xA;_computing_publication_material     'SHELXL-96 (Sheldrick, 1996)'&#xA;loop_&#xA;    _atom_site_label&#xA;    _atom_site_fract_x&#xA;    _atom_site_fract_y&#xA;    _atom_site_fract_z&#xA;    _atom_site_U_iso_or_equiv&#xA;    _atom_site_thermal_displace_type&#xA;    _atom_site_calc_flag&#xA;    _atom_site_refinement_flags&#xA;    _atom_site_occupancy&#xA;    _atom_site_disorder_group&#xA;    _atom_site_type_symbol&#xA;    N 0.4547(9) 0.2657(5) 0.4613(4) 0.0710(15) Uani d . 1 . N&#xA;    C1 0.0949(12) 0.4579(6) 0.2478(6) 0.0586(14) Uani d . 1 . C&#xA;    C2 0.2946(9) 0.3498(5) 0.3672(5) 0.0507(13) Uani d . 1 . C&#xA;    H1 -0.108(11) 0.402(5) 0.166(5) 0.089(14) Uiso d . 1 . H&#xA;    H2 0.233(11) 0.518(6) 0.186(6) 0.113(18) Uiso d . 1 . H&#xA;    H3 -0.050(11) 0.538(6) 0.301(5) 0.103(16) Uiso d . 1 . H&#xA;loop_&#xA;    _atom_site_aniso_label&#xA;    _atom_site_aniso_U_11&#xA;    _atom_site_aniso_U_22&#xA;    _atom_site_aniso_U_33&#xA;    _atom_site_aniso_U_12&#xA;    _atom_site_aniso_U_13&#xA;    _atom_site_aniso_U_23&#xA;    N 0.076(3) 0.070(3) 0.064(2) 0.005(2) 0.0028(18) 0.008(2)&#xA;    C1 0.058(3) 0.060(3) 0.055(3) 0.005(2) 0.001(2) 0.008(2)&#xA;    C2 0.056(2) 0.050(3) 0.047(2) -0.007(2) 0.0101(19) -0.009(2)&#xA;_geom_special_details&#xA;;&#xA; All esds (except the esd in the dihedral angle between two l.s. planes)&#xA; are estimated using the full covariance matrix.  The cell esds are taken&#xA; into account individually in the estimation of esds in distances, angles&#xA; and torsion angles; correlations between esds in cell parameters are only&#xA; used when they are defined by crystal symmetry.  An approximate (isotropic)&#xA; treatment of cell esds is used for estimating esds involving l.s. planes.&#xA;;&#xA;loop_&#xA;    _geom_bond_atom_site_label_1&#xA;    _geom_bond_atom_site_label_2&#xA;    _geom_bond_site_symmetry_2&#xA;    _geom_bond_distance&#xA;    _geom_bond_publ_flag&#xA;    N C2 . 1.141(5) yes&#xA;    C1 C2 . 1.448(6) yes&#xA;    C1 H1 . 1.07(5) yes&#xA;    C1 H2 . 0.96(5) yes&#xA;    C1 H3 . 1.03(5) yes&#xA;loop_&#xA;    _geom_angle_atom_site_label_1&#xA;    _geom_angle_atom_site_label_2&#xA;    _geom_angle_atom_site_label_3&#xA;    _geom_angle_site_symmetry_1&#xA;    _geom_angle_site_symmetry_3&#xA;    _geom_angle&#xA;    _geom_angle_publ_flag&#xA;    C2 C1 H1 . . 115(2) yes&#xA;    C2 C1 H2 . . 110(3) yes&#xA;    H1 C1 H2 . . 112(3) yes&#xA;    C2 C1 H3 . . 115(2) yes&#xA;    H1 C1 H3 . . 95(3) yes&#xA;    H2 C1 H3 . . 108(4) yes&#xA;    N C2 C1 . . 179.3(4) yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user2026" LastEditorDisplayName="user2026" LastEditDate="2021-03-22T00:26:55.673" LastActivityDate="2021-05-11T06:43:27.037" Title="How to sort a supercell for a molecular crystal?" Tags="|crystal-structure|crystallography|cif|atomic-simulation-environment|supercell|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4478" PostTypeId="1" AcceptedAnswerId="4496" CreationDate="2021-03-11T07:48:40.973" Score="7" ViewCount="211" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1055/201&quot;&gt;@Nike Dattani's answer&lt;/a&gt; to &lt;em&gt;How to “get my feet wet” in Density Functional Theory by simulating a water molecule using Python&lt;/em&gt; recommends SlowQuant. I've used the &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/install.html&quot; rel=&quot;noreferrer&quot;&gt;install instructions&lt;/a&gt; for Linux on my MacOS and it &lt;em&gt;seems&lt;/em&gt; to work.&lt;/p&gt;&#xA;&lt;p&gt;Initially the tests failed because &lt;code&gt;factorial2&lt;/code&gt; has been moved from &lt;code&gt;scipy.misc&lt;/code&gt; to &lt;code&gt;scipy.special&lt;/code&gt;. I edited &lt;code&gt;MIpython.py&lt;/code&gt; and &lt;code&gt;BasisSet.py&lt;/code&gt; adding &lt;code&gt;import scipy.special as spe&lt;/code&gt; and changing &lt;code&gt;scp.factorial2&lt;/code&gt; to &lt;code&gt;spe.factorial2&lt;/code&gt; in three places in each file and all tests now pass, and I get the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ python SlowQuant.py H2O.csv settingExample.csv&#xA;&#xA;0.1089320182800293 INTEGRALS&#xA;Iter     Eel&#xA;1    -66.7536308450      -58.7512637840       6.71128773e+01      6.57412977e+00&#xA;2    -85.6091201524      -77.6067530914      -1.88554893e+01      6.02202187e+00      7.40515875e-01&#xA;3    -86.6677593084      -78.6653922474      -1.05863916e+00      1.07013952e-01      7.40515875e-01&#xA;0.006840229034423828 HF&#xA;4.0531158447265625e-06 PROPERTIES&#xA;2.1457672119140625e-06 Perturbation&#xA;2.1457672119140625e-06 QFIT&#xA;9.5367431640625e-07 CI&#xA;2.1457672119140625e-06 CC&#xA;0.1327359676361084 Execution time&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So while I've been &lt;em&gt;splashed&lt;/em&gt; my feet are not fully wet yet.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What are the next steps to obtaining a 3D distribution of electronic charge in the molecule? This is all new to me.&lt;/p&gt;&#xA;&lt;p&gt;I have seen &lt;a href=&quot;https://en.wikipedia.org/wiki/Mulliken_population_analysis&quot; rel=&quot;noreferrer&quot;&gt;Mulliken charges&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Localized_molecular_orbitals#Pipek-Mezey&quot; rel=&quot;noreferrer&quot;&gt;Löwdin charges&lt;/a&gt; mentioned in the &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/Properties.html#mulliken-charges&quot; rel=&quot;noreferrer&quot;&gt;properties&lt;/a&gt; page of the documentation, perhaps something like this is what I'm after?&lt;/p&gt;&#xA;&lt;p&gt;But when I added a line at the bottom of the script, I just got an error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;10;;;&#xA;1;1.63803684;1.136548823;0.0&#xA;8;0.0;-0.143225817;0.0&#xA;1;-1.63803684;1.136548823;0.0&#xA;Charge;Mulliken;;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;SlowQuant.py&amp;quot;, line 95, in &amp;lt;module&amp;gt;&#xA;    results = run(mol, set)&#xA;  File &amp;quot;SlowQuant.py&amp;quot;, line 58, in run&#xA;    basis = BS.bassiset(input, set['basisset'])&#xA;  File &amp;quot;/your-name-here/SlowQuant/slowquant/basissets/BasisSet.py&amp;quot;, line 195, in bassiset&#xA;    if basisload[j+1,0] == 'FOR' and writecheck == 1:&#xA;IndexError: index 176 is out of bounds for axis 0 with size 176&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Ultimately I hope to draw some imaginary electric field lines myself and that's a challenge and topic of its own, but for right now I just need a way to get charge density per unit volume.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2021-03-11T08:06:42.673" LastActivityDate="2022-09-27T06:54:45.333" Title="How to obtain electron charge density per unit volume about a water molecule using SlowQuant?" Tags="|density-functional-theory|python|charge-density|water|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4479" PostTypeId="1" AcceptedAnswerId="4482" CreationDate="2021-03-11T17:57:30.067" Score="8" ViewCount="322" Body="&lt;p&gt;I am facing some problems in performing &lt;code&gt;HESSIAN&lt;/code&gt; analysis on excited states of molecules: I am testing it out with CO. My input file to GAMESS is pasted below. Could you help me figure out why I am getting the error:  &lt;code&gt;ERROR! THERE ARE NOT 5 OR 6 TRANS/ROT MODES NUM T/R&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Here's the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=N31 NGAUSS=6  NDFUNC=1 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE CCTYP=EOM-CCSD $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT  OPTTOL=0.0001 NSTEP=20 HSSEND=.T. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$FORCE METHOD=FULLNUM VIBSIZ=0.001 VIBANL=.TRUE. PURIFY=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$eominp nstate(1)=1,0,0,0,0,0,0,0 iroot(1)=1 ccprpe=.true.&#xA;         minit=2 noact=3 nuact=5 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;Title&#xA;C1&#xA;C     6.0     0.60190     0.00000    -0.00040&#xA;O     8.0    -0.59510     0.00000     0.00010&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2095" LastEditorUserId="5" LastEditDate="2021-03-11T19:35:00.317" LastActivityDate="2021-03-11T21:15:51.770" Title="Optimization and vibrational analysis of excited state CO using GAMESS" Tags="|vibrations|gamess|excited-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4480" PostTypeId="1" AcceptedAnswerId="4485" CreationDate="2021-03-11T19:10:00.760" Score="10" ViewCount="518" Body="&lt;p&gt;Some references mentioned that the calculation of &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; topological invariant of a crystal can be greatly simplified if the crystal contains inversion symmetry. But it involves the calculation of the parity of the occupied band at a specific TRIM point. I have a very basic question about this:&lt;/p&gt;&#xA;&lt;p&gt;If I have a tight binding Hamiltonian obtained by fitting the data from a first principles calculation, how can we calculate the parity of the occupied band at particular TRIM point?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-03-11T19:23:18.440" LastActivityDate="2021-03-12T11:02:29.250" Title="How to calculate the parity of a band at a particular point in Brillouin zone" Tags="|density-functional-theory|band-structure|topological-insulators|tight-binding|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4481" PostTypeId="1" CreationDate="2021-03-11T19:25:00.600" Score="5" ViewCount="47" Body="&lt;p&gt;I have a solid with PBC (periodic boundary conditions) and I want to perform a DFT simulation. I use GTO as the basis. In a &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/ct800329m&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; I read, I can transform the GTO to a Bloch function (crystalline Gaussian-type AOs):&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://latex.codecogs.com/gif.latex?%5Cchi%5E%7B(Crystall)%7D_%7B%5Cnu%5Cvec%7Bk%7D%7D(%5Cvec%7Br%7D)=%5Cfrac%7B1%7D%7B%5Csqrt%7BK%7D%7D%5Csum_%7BA%7D%5Csum_%7B%5Cvec%7BT%7D%7De%5E%7Bi%5Cvec%7Bk%7D%5Ccdot&amp;amp;space;%5Cvec%7BT%7D%7Dd_%7BA,%5Cnu%7D%5E%7B%5Cvec%7Bk%7D%7D%5Cchi_%7B%5Cnu%7D%5E%7BGTO%7D(%5Cvec%7Br%7D-%5Cvec%7Br%7D_%7BA%7D-%5Cvec%7BT%7D)&quot; alt=&quot;&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the equation &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; denotes the reciprocal lattice vector and &lt;span class=&quot;math-container&quot;&gt;$\chi_{\nu}^{GTO}$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;-th Gaussian-type orbital which center is displaced from the unit cell at &lt;span class=&quot;math-container&quot;&gt;$\vec{T}$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\vec{r}_A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the input file (whether using CP2K, ABINIT, or something else) I can set a cut-off value for the kinetic energy. But what does the value mean in such a case? What does the formula look like?&lt;/p&gt;&#xA;&lt;p&gt;For example in CP2K:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;MGRID&#xA;  NGRIDS 5&#xA;  CUTOFF 500&#xA;  REL_CUTOFF 60&#xA;&amp;amp;END MGRID&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I know in the case with plane waves as basic functions it would be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}\frac{\vec{k}+\vec{G}}{2}&amp;lt;E_{cut},$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\vec{G}$&lt;/span&gt; is the vector of the reciprocal lattice. Is it correct to transform the lattice vector &lt;span class=&quot;math-container&quot;&gt;$\vec{T}$&lt;/span&gt; of the real space as in Eq. 3 below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_i=2\pi \frac{T_j\times T_k}{T_i\cdot(T_j\times T_k)}.\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and then plug it into the formula?&lt;/p&gt;&#xA;" OwnerUserId="1469" LastEditorUserId="5" LastEditDate="2021-03-11T19:37:58.810" LastActivityDate="2021-03-11T19:37:58.810" Title="Kinetic energy cut-off for Gaussian-type orbitals when applying periodic boundary conditions" Tags="|density-functional-theory|cp2k|orbitals|periodic-boundary-conditions|abinit|" AnswerCount="0" CommentCount="8" ClosedDate="2021-06-23T22:13:38.617" ContentLicense="CC BY-SA 4.0" />
  <row Id="4482" PostTypeId="2" ParentId="4479" CreationDate="2021-03-11T21:15:51.770" Score="6" Body="&lt;p&gt;I cannot see your output file, but I am pretty sure that the program is running into an error when starting the optimization i.e. when it is trying to generate the guess hessian.&lt;/p&gt;&#xA;&lt;p&gt;You are using Cartesian coordinates for optimization, and GAMESS by default will attempt to eliminate the rotational and translational modes from the guess hessian, before the optimization starts. The algorithm that does this sometimes runs into problems. For non-linear molecules, there should be 6 rot./trans. modes, and for linear molecules 5 rot./trans. modes. If the algorithm cannot find 5 or 6 modes which match its criteria, then it throws this error and GAMESS stops.&lt;/p&gt;&#xA;&lt;p&gt;There are two ways to solve this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;You can use internal coordinates to optimize. In this case, to do this, you need to add &lt;code&gt;NZVAR=1&lt;/code&gt; in &lt;code&gt;$CONTRL&lt;/code&gt; and also add &lt;code&gt;$ZMAT DLC=.t. AUTO=.t. $END&lt;/code&gt; which will instruct the program to use internal coordinates, and generate delocalized internal coordinates, respectively. The guess hessian will be generated in internal coordinates from the start, removing the need to eliminate rot./trans. modes.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You can force the optimization to proceed without eliminating the rot./trans. modes. Add &lt;code&gt;PROJCT=.f.&lt;/code&gt; in &lt;code&gt;$STATPT&lt;/code&gt; for this. I have done this a few times, and haven't seen any problems so far, but you should be careful.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I would recommend the first choice in general, because optimizations in internal coordinates are often faster. Of course, in this case your molecule is so small that you probably won't notice the difference.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-03-11T21:15:51.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4483" PostTypeId="1" CreationDate="2021-03-11T22:50:49.833" Score="9" ViewCount="376" Body="&lt;p&gt;I am getting myself acquainted with &lt;a href=&quot;http://www.wanniertools.com/installation.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wannier Tools&lt;/a&gt;. Wannier Tools requires two inputs, a &lt;code&gt;wt.in&lt;/code&gt; file, and a &lt;code&gt;.dat&lt;/code&gt; file. This &lt;code&gt;.dat&lt;/code&gt; file should have the structure explained in the &lt;a href=&quot;http://www.wanniertools.com/input.html#wannier90-dat&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt;. This file may be parsed from other DFT software (such as Quantum ESPRESSO via Wannier90). However, it may also be generated manually, as the developers do in an example using a Python file.&lt;/p&gt;&#xA;&lt;p&gt;I am going to focus on their implementation of the 2D Haldane model for the QAHE [1] (&lt;a href=&quot;https://github.com/quanshengwu/wannier_tools/tree/master/examples/Haldane_model&quot; rel=&quot;nofollow noreferrer&quot;&gt;link to implementation&lt;/a&gt;). My issue is that I do not understand how they went from the tight-binding model to getting the matrix elements of the Hamiltonian. &lt;strong&gt;In particular, I do not understand why they use 7 points, and why each point gives each matrix element.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the tight-binding model in first quantization [2] (I used another source because the original work only gives a Hamiltonian in k-space):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}=t\sum_{\langle i,j\rangle}|i\rangle\langle j|+t_2\sum_{\langle\langle i,j\rangle\rangle}|i\rangle\langle j|+M\bigg[\sum_{i\in A}|i\rangle\langle i|-\sum_{j\in B}|j\rangle\langle j|\bigg]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is part of an example Python file that they use to generate the .dat file. They use &lt;code&gt;m&lt;/code&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;, &lt;code&gt;phi&lt;/code&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;, and &lt;code&gt;t1&lt;/code&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Chern = 1&#xA;m=0.2; phi= np.pi/2.0; t1=1.0; t2=m/3.0/np.sqrt(3)*2.0;&#xA;&#xA;# maximum dimension for hr matrix&#xA;ndim = 2 &#xA;nrpts = 7&#xA;num_patom=2&#xA;&#xA;# hr matrix &#xA;norbs = num_patom*1&#xA;hmnr= np.zeros((norbs,norbs,nrpts),dtype = np.complex128)&#xA;&#xA;# WS points&#xA;irvec   = np.zeros((3,nrpts),dtype = np.int32)&#xA;&#xA;# degeneracy&#xA;dege   = np.zeros((nrpts),dtype = np.int32)+1&#xA;&#xA;&#xA;# complex unit&#xA;zi=1j&#xA;&#xA;ir= 0&#xA;irvec[0, ir]= 0&#xA;irvec[1, ir]= 0&#xA;hmnr[0, 0, ir]=  m&#xA;hmnr[1, 1, ir]= -m&#xA;hmnr[0, 1, ir]=  t1&#xA;hmnr[1, 0, ir]=  t1&#xA;&#xA;# 1 0 &#xA;ir= ir+1&#xA;irvec[0, ir]= 1&#xA;irvec[1, ir]= 0&#xA;hmnr[0, 0, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;hmnr[0, 1, ir]= t1&#xA;&#xA;# 0 1 &#xA;ir= ir+1&#xA;irvec[0, ir]= 0&#xA;irvec[1, ir]= 1&#xA;hmnr[0, 0, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;hmnr[1, 0, ir]= t1&#xA;&#xA;# 1 1 &#xA;ir= ir+1&#xA;irvec[0, ir]= 1&#xA;irvec[1, ir]= 1&#xA;hmnr[0, 0, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;&#xA;#-1 0 &#xA;ir= ir+1&#xA;irvec[0, ir]=-1&#xA;irvec[1, ir]= 0&#xA;hmnr[0, 0, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;hmnr[1, 0, ir]= t1&#xA;&#xA;# 0-1 &#xA;ir= ir+1&#xA;irvec[0, ir]= 0&#xA;irvec[1, ir]=-1&#xA;hmnr[0, 0, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;hmnr[0, 1, ir]= t1&#xA;&#xA;#-1-1 &#xA;ir= ir+1&#xA;irvec[0, ir]=-1&#xA;irvec[1, ir]=-1&#xA;hmnr[0, 0, ir]= (np.cos(phi)-zi*np.sin(phi)) *t2&#xA;hmnr[1, 1, ir]= (np.cos(phi)+zi*np.sin(phi)) *t2&#xA;&#xA;&#xA;#print &amp;quot;dump hr.dat...&amp;quot;&#xA;with open('Haldane_hr.dat','w') as f:&#xA;    line=&amp;quot;Haldane model with m=&amp;quot;+str(m)+&amp;quot;, phi=&amp;quot;+str(phi/np.pi)+&amp;quot;pi, t1=&amp;quot;+str(t1)+&amp;quot;, t2=&amp;quot;+str(t2)+&amp;quot;Ref:Physical Review Letters 61, 18(1988)&amp;quot;+'\n'&#xA;    f.write(line)&#xA;    nl = np.int32(np.ceil(nrpts/15.0))&#xA;    f.write(str(norbs)+'\n')&#xA;    f.write(str(nrpts)+'\n')&#xA;    for l in range(nl):&#xA;        line=&amp;quot;    &amp;quot;+'    '.join([str(np.int32(i)) for i in dege[l*15:(l+1)*15]])&#xA;        f.write(line)&#xA;        f.write('\n')&#xA;    for irpt in range(nrpts):&#xA;        rx = irvec[0,irpt];ry = irvec[1,irpt];rz = irvec[2,irpt]&#xA;        for jatomorb in range(norbs):&#xA;            for iatomorb in range(norbs):&#xA;               rp =hmnr[iatomorb,jatomorb,irpt].real&#xA;               ip =hmnr[iatomorb,jatomorb,irpt].imag&#xA;               line=&amp;quot;{:8d}{:8d}{:8d}{:8d}{:8d}{:20.10f}{:20.10f}\n&amp;quot;.format(rx,ry,rz,jatomorb+1,iatomorb+1,rp,ip)    &#xA;               f.write(line)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Current understanding&lt;/h2&gt;&#xA;&lt;p&gt;I am not sure what the seven cases indicated by comments &lt;code&gt;# 1 0, #-1 0, etc&lt;/code&gt; are. However, I figured they corresponded to real space &lt;span class=&quot;math-container&quot;&gt;$(x,y)$&lt;/span&gt; points because there are 7 such code blocks, and there is &lt;code&gt;nrpts = 7&lt;/code&gt;. Assuming that each &lt;code&gt;hmnr&lt;/code&gt; value corresponds to a matrix element of the Hamiltonian (i.e. it can be a hopping, on-site energy, etc), I do not see why we need 7 points when we could have used 4 to capture all on-site, NN and NNN potentials/interactions. Indeed, it appears as if 3 of these code blocks have values identical to another block. So, why 7? It makes the resulting matrix larger...&lt;/p&gt;&#xA;&lt;p&gt;Next, I figured that the &lt;span class=&quot;math-container&quot;&gt;$\cos\phi \pm i \sin\phi$&lt;/span&gt; came from the Peierls substitution for the NNN hopping parameter &lt;span class=&quot;math-container&quot;&gt;$t_2 \rightarrow t_2 e^{\pm i \phi} = t_2 (\cos\phi \pm i \sin\phi)$&lt;/span&gt;. This checks out.&lt;/p&gt;&#xA;&lt;p&gt;But, what still doesn't make sense is how each of the 7 points makes them assign only some matrix elements. To illustrate this, I annotated the initial code block with my interpretation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ir=0  #a number that iterates through all 7 points&#xA;irvec[0, ir]=0 #set x coordinate of point to 0&#xA;irvec[1, ir]=0 #set y coordinate of point to 0&#xA;hmnr[0, 0, ir]=m #set (0,0) Hamiltonian matrix element value to +m&#xA;hmnr[1, 1, ir]=-m #set (1,1) Hamiltonian matrix element value to -m&#xA;hmnr[0, 1, ir]=t1 #set (0,1) Hamiltonian matrix element value to t1&#xA;hmnr[1, 0, ir]=t1 #set (1,0) Hamiltonian matrix element value to t1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I took this to mean that the Hamiltonian at this point is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{bmatrix}&#xA;\langle m | H_{00} | m \rangle &amp;amp; \langle m | H_{01} | n \rangle \\&#xA;\langle n | H_{10} | m \rangle &amp;amp; \langle n | H_{11} | n \rangle &#xA;\end{bmatrix}&#xA;=&#xA;\begin{bmatrix}&#xA;m &amp;amp; t_1 \\&#xA;t_1  &amp;amp; -m &#xA;\end{bmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But, how exactly do they determine the values assigned to each matrix element? In addition to the above, I don't understand why the point &lt;span class=&quot;math-container&quot;&gt;$(0,1)$&lt;/span&gt; gives&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{bmatrix}&#xA;t_2 (\cos\phi + i \sin\phi) &amp;amp; 0 \\&#xA;t_1  &amp;amp; t_2 (\cos\phi - i \sin\phi)&#xA;\end{bmatrix}. &#xA;$$&lt;/span&gt;&#xA;What justifies setting the &lt;span class=&quot;math-container&quot;&gt;$\langle m | H_{01} | n \rangle$&lt;/span&gt; element to 0? Clearly, I have either misinterpreted what the code stands for, or just don't understand what's going on. I also considered interpreting aforementioned seven points as pairs of values of &lt;span class=&quot;math-container&quot;&gt;$(i,j)$&lt;/span&gt; or some other vector. But it's very hard to decrypt this without knowing too well the context the authors wrote this in. So, any help would be appreciated!&lt;/p&gt;&#xA;&lt;p&gt;I tried comparing this syntax with other tools such as PythTB and TBmodels, but they don't match too well with this syntax.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;F. D. M. Haldane Phys. Rev. Lett. 61, 2015 &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.61.2015&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Michel Fruchart and David Carpentier, &lt;a href=&quot;https://arxiv.org/abs/1310.0255&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/1310.0255&lt;/a&gt; &lt;a href=&quot;https://arxiv.org/ct?url=https%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.crhy.2013.09.013&amp;amp;v=bd6ad254&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="7" LastEditDate="2021-12-01T18:49:54.010" LastActivityDate="2021-12-01T18:49:54.010" Title="How to interpret WannierTools Python code that generates tight-binding model in the wannier90_hr.dat format?" Tags="|density-functional-theory|python|model-hamiltonians|tight-binding|wannier90|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-13T19:18:06.263" ContentLicense="CC BY-SA 4.0" />
  <row Id="4484" PostTypeId="1" CreationDate="2021-03-11T23:23:42.893" Score="5" ViewCount="950" Body="&lt;p&gt;&lt;strong&gt;This question has an answer on the Chemistry Stack Exchange: &lt;a href=&quot;https://chemistry.stackexchange.com/a/58613/27342&quot;&gt;Understanding group theory easily and quickly&lt;/a&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Anyone wishing to add alternative or additional perspectives that aren't already covered in the answer there, can write a comment saying so and the question can be re-opened.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Take the &lt;span class=&quot;math-container&quot;&gt;$C_{3v}$&lt;/span&gt; group as an example, which character table is shown below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pHJxA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pHJxA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What's the meaning of linear functions, quadratic functions, and cubic functions for different irreducible representations? And what's the connection between different columns? More generally, what's the information contained in the character table?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-03-12T20:15:25.640" LastActivityDate="2021-03-30T14:37:29.307" Title="What's the information contained in a character table of a group?" Tags="|mathematical-modeling|symmetry|space-groups|" AnswerCount="0" CommentCount="4" ClosedDate="2021-03-30T15:20:01.720" ContentLicense="CC BY-SA 4.0" />
  <row Id="4485" PostTypeId="2" ParentId="4480" CreationDate="2021-03-12T11:02:29.250" Score="6" Body="&lt;p&gt;Consider the energy eigenstate &lt;span class=&quot;math-container&quot;&gt;$|\psi_{n\mathbf{k}}\rangle$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the band you are interested in and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; is wave vector of the TRIM point. Then, if the system has inversion symmetry, these energy eigenstates are also eigenstates of the parity operator &lt;span class=&quot;math-container&quot;&gt;$\hat{\pi}$&lt;/span&gt;. This means that to determine the parity of that state, you can calculate the expectation value of the parity operator with respect to the energy eigenstate:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle\psi_{n\mathbf{k}}|\hat{\pi}|\psi_{n\mathbf{k}}\rangle&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This can only be &lt;span class=&quot;math-container&quot;&gt;$\pm1$&lt;/span&gt;, and the parity is &amp;quot;even&amp;quot; for &lt;span class=&quot;math-container&quot;&gt;$+1$&lt;/span&gt; and &amp;quot;odd&amp;quot; for &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-03-12T11:02:29.250" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4486" PostTypeId="1" AcceptedAnswerId="4489" CreationDate="2021-03-12T12:18:38.153" Score="13" ViewCount="682" Body="&lt;p&gt;I am trying to do DFT calculations on ethanol adsorbed on Pd, both surfaces 111 and 100. I have the &lt;code&gt;cif&lt;/code&gt; file from the database and also I have built the new unit cell that explicitly shows face 111.&lt;/p&gt;&#xA;&lt;p&gt;I need to slab of Pd, one of 100, the other 111, made by 5 layers of metal, 9 atoms per layer. I have tried with &lt;code&gt;VESTA&lt;/code&gt; (with this software I have obtained the new unit cell), but I cannot reproduce the slabs from the reference article, both in number and in geometry. Do you have a sort of guide/recipe idiot-proof to prepare correctly a slab for DFT simulations?&lt;/p&gt;&#xA;" OwnerUserId="2199" OwnerDisplayName="TheOldJonny" LastEditorUserId="1218" LastEditDate="2021-03-13T13:37:41.607" LastActivityDate="2021-03-13T13:37:41.607" Title="How to cut properly a slab from a cif file?" Tags="|crystal-structure|density-functional-theory|crystallography|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4487" PostTypeId="1" CreationDate="2021-03-12T17:58:19.480" Score="7" ViewCount="337" Body="&lt;p&gt;I'm trying to perform ab-initio MD on polymer system.&lt;/p&gt;&#xA;&lt;p&gt;I've built single chain of polycarbonate (PC) with the length of ~40 angstroms and now I'm building initial configuration. I've calculated how much of this chains are needed to achieve the experimental density of PC and tried to pack it with Packmol in cube 50x50x50 angstroms.&lt;/p&gt;&#xA;&lt;p&gt;It fails to make good enough packing, so what are the usual protocols to pack polymer system to experimental density?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-04-02T16:56:32.023" Title="Molecular dynamics: how to pack system for desired density" Tags="|molecular-dynamics|polymers|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4488" PostTypeId="2" ParentId="4477" CreationDate="2021-03-12T19:54:38.880" Score="5" Body="&lt;p&gt;I don't know if this is exactly what you want to do, but &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;pymatgen&lt;/code&gt;&lt;/a&gt; may be able to help (disclosure, I am a developer of this package).&lt;/p&gt;&#xA;&lt;p&gt;See this example code below for your example input file:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymatgen.core.structure import Structure, Molecule&#xA;from pymatgen.analysis.graphs import StructureGraph&#xA;from pymatgen.analysis.local_env import JmolNN&#xA;&#xA;# load the molecular crystal from a CIF file&#xA;# if a single CIF file contains multiple structures, &#xA;# you will need to use pymatgen.io.cif.CifParser(your_file).get_structures() instead&#xA;acetonitrile = Structure.from_file(&amp;quot;acetonitrile.cif&amp;quot;)&#xA;&#xA;# attempt to guess the bonds present using a bonding strategy&#xA;# (here JmolNN but others are available)&#xA;# this creates a StructureGraph&#xA;sg = StructureGraph.with_local_env_strategy(acetonitrile, JmolNN())&#xA;&#xA;# now extract individual molecules, which are isolated subgraphs&#xA;# (i.e. groups of atoms not connected to each other)&#xA;molecules = sg.get_subgraphs_as_molecules()&#xA;&#xA;# this gives a list of molecules&#xA;# here, there is only a single unique subgraph so only one is returned&#xA;&#xA;print(molecules[0])&#xA;# Molecule Summary&#xA;# Site: H (-1.5303, 0.3235, -1.2207)&#xA;# Site: C (-0.7109, 0.7843, -0.7147)&#xA;# Site: H (-1.2961, 1.4446, -0.1864)&#xA;# Site: C (0.0955, -0.1069, 0.0933)&#xA;# Site: N (0.7421, -0.8002, 0.7281)&#xA;# Site: H (-0.1532, 1.2798, -1.3066)&#xA;&#xA;# you can then sort the sites according to whatever logic you want,&#xA;# and create a new Molecule object from the sorted sites&#xA;new_molecule = Molecule.from_sites(sorted(molecules[0], key=lambda site: site.species))&#xA;print(new_molecule)&#xA;&#xA;# Molecule Summary&#xA;# Site: N (0.7421, -0.8002, 0.7281)&#xA;# Site: C (-0.7109, 0.7843, -0.7147)&#xA;# Site: C (0.0955, -0.1069, 0.0933)&#xA;# Site: H (-1.5303, 0.3235, -1.2207)&#xA;# Site: H (-1.2961, 1.4446, -0.1864)&#xA;# Site: H (-0.1532, 1.2798, -1.3066)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope this helps!&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2021-03-12T19:54:38.880" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4489" PostTypeId="2" ParentId="4486" CreationDate="2021-03-13T02:42:16.070" Score="9" Body="&lt;p&gt;You can use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;ASE.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For your case, I assume you are using the &lt;a href=&quot;https://materialsproject.org/materials/mp-2/#&quot; rel=&quot;noreferrer&quot;&gt;Pd crystal structure with space group 225.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sGLqJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sGLqJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Cut the (111) surface with ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;from ase.build import surface&#xA;&#xA;####================================================&#xA;A=read('Pd_mp-2_conventional_standard.cif',format='cif')&#xA;B=surface(A,(1,1,1),5,vacuum=10)&#xA;write('111.vasp',B,format='vasp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The 111 slab with five atomic layers:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HWjt1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HWjt1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To obtain 9 atoms in each layer you may need to make a matrix transformation with &lt;code&gt;VESTA&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-13T02:51:55.657" LastActivityDate="2021-03-13T02:51:55.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4490" PostTypeId="2" ParentId="4474" CreationDate="2021-03-13T02:44:27.687" Score="8" Body="&lt;p&gt;Here is an example for &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;Open Babel 3&lt;/a&gt; in Python 3.8. It's not really that pythonic, but you can make use of powerful features like &lt;a href=&quot;https://www.daylight.com/dayhtml/doc/theory/theory.smarts.html&quot; rel=&quot;noreferrer&quot;&gt;SMARTS pattern&lt;/a&gt; and have the support for pretty much any chemical  file format.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from openbabel import openbabel as ob&#xA;&#xA;obconv = ob.OBConversion()&#xA;obconv.SetInFormat('xyz')&#xA;mol = ob.OBMol()&#xA;obconv.ReadFile(mol, 'test.xyz')&#xA;obsmarts = ob.OBSmartsPattern()&#xA;# Get O-H bonds&#xA;obsmarts.Init('O[H]')&#xA;if obsmarts.Match(mol):&#xA;    for match in obsmarts.GetUMapList():&#xA;        bond = mol.GetBond(*match)&#xA;        print(f'R{match} =', bond.GetLength())&#xA;# Get H-O-H angles&#xA;obsmarts.Init('[H]O[H]')&#xA;if obsmarts.Match(mol):&#xA;    for match in obsmarts.GetUMapList():&#xA;        print(f'A{match} =', mol.GetAngle(*(mol.GetAtom(i) for i in match)))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2044" LastActivityDate="2021-03-13T02:44:27.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4491" PostTypeId="1" AcceptedAnswerId="4508" CreationDate="2021-03-13T03:35:29.873" Score="11" ViewCount="587" Body="&lt;p&gt;Given the 3D structure of a molecule (&lt;em&gt;e.g.&lt;/em&gt; as &lt;code&gt;*.mol&lt;/code&gt;) and a probe radius &lt;code&gt;r&lt;/code&gt;, I want to calculate the solvent excluded surface (SES) and the excluded volume enclosed by it. Note the difference between SAS and SES:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/i0MVJm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/i0MVJm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm looking for a command line program, C/C++ or Python library that can accomplish such a task.&lt;/p&gt;&#xA;" OwnerUserId="2044" LastEditorUserId="5" LastEditDate="2021-03-15T18:15:31.980" LastActivityDate="2023-04-26T20:37:16.280" Title="Programs/Libraries for calculating solvent excluded surface and excluded volume" Tags="|software|one-topic-per-answer|software-recommendations|python|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4492" PostTypeId="2" ParentId="4474" CreationDate="2021-03-13T05:14:12.663" Score="6" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/leeping/geomeTRIC&quot; rel=&quot;noreferrer&quot;&gt;GeomeTRIC&lt;/a&gt; and &lt;a href=&quot;https://github.com/ZimmermanGroup/pyGSM&quot; rel=&quot;noreferrer&quot;&gt;pyGSM&lt;/a&gt; have this capability for internal coordinates&lt;/p&gt;&#xA;&lt;p&gt;In pyGSM this looks like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pygsm.utilities.manage_xyz import read_xyz,xyz_to_np&#xA;from pygsm.coordinate_systems.slots import Distance,Angle,Dihedral&#xA;&#xA;bond = Distance(0,1)&#xA;angle = Angle(0,1,2)&#xA;dihedral=Dihedral(0,1,2,3)&#xA;&#xA;geom = read_xyz('ethylene.xyz')&#xA;xyz = xyz_to_np(geom)&#xA;&#xA;bond_value = bond.value(xyz)&#xA;angle_value = angle.value(xyz)&#xA;dihedral_value = dihedral.value(xyz)&#xA;&#xA;print(bond_value,angle_value,dihedral_value)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-03-13T05:14:12.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4493" PostTypeId="2" ParentId="414" CreationDate="2021-03-13T19:52:52.437" Score="6" Body="&lt;h2&gt;GAMESS&lt;/h2&gt;&#xA;&lt;p&gt;GAMESS (&lt;a href=&quot;https://www.msg.chem.iastate.edu/GAMESS/&quot; rel=&quot;noreferrer&quot;&gt;https://www.msg.chem.iastate.edu/GAMESS/&lt;/a&gt;) has an MCSCF module, which can perform CASSCF. For generating configurations it can use determinants, or configuration state functions (CSFs). There are first order, quasi-second order, full newton-raphson and other convergers for the iterations. GAMESS can also perform full second order CI.&lt;/p&gt;&#xA;&lt;p&gt;GAMESS documentation has a section on how to do MCSCF calculations.&lt;/p&gt;&#xA;&lt;p&gt;GAMESS is free to obtain, and you can also access its source code, but strictly speaking, it is not open-source because its license is proprietary.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-03-13T19:52:52.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4494" PostTypeId="1" AcceptedAnswerId="4495" CreationDate="2021-03-11T16:46:58.683" Score="10" ViewCount="541" Body="&lt;p&gt;I am currently working with Molpro, to which I am completely new, trying to run some calculations on &lt;span class=&quot;math-container&quot;&gt;$\ce{PdO}$&lt;/span&gt;. From literature I have gathered that the ground state is given by &lt;span class=&quot;math-container&quot;&gt;$^3\Sigma^-$&lt;/span&gt; state, which translates to a &lt;span class=&quot;math-container&quot;&gt;$^3A_2$&lt;/span&gt; state in the &lt;span class=&quot;math-container&quot;&gt;$C_{2\mathrm{v}}$&lt;/span&gt; point group, or a wave function card &lt;code&gt;{wf,54,4,2,0}&lt;/code&gt;. Moreover, the literature gives a possible active space of (&lt;span class=&quot;math-container&quot;&gt;$4a_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2b_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2b_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$1a_2$&lt;/span&gt;). I now want to run a CASSCF calculation using this active space, but I am not sure how to determine the occupied (&lt;code&gt;OCC&lt;/code&gt;) and closed shell (&lt;code&gt;CLOSED&lt;/code&gt;) orbitals.&lt;/p&gt;&#xA;&lt;p&gt;How do I determine these values in general?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So I have been working on this a little more, and maybe I have found an approach that could work. I can run a simple HF calculation and get a set of orbitals whereby Molpro gives me the corresponding IRREPS. In the case for &lt;span class=&quot;math-container&quot;&gt;$\ce{PdO}$&lt;/span&gt; I get a set of occupied orbitals (&lt;span class=&quot;math-container&quot;&gt;$13a_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$7b_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$6b_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2a_2$&lt;/span&gt;), whereby two are singly occupied. To get my desired active space of (&lt;span class=&quot;math-container&quot;&gt;$4a_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2b_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2b_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$1a_2$&lt;/span&gt;), I would simply have to close orbitals according to (&lt;span class=&quot;math-container&quot;&gt;$9a_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$5b_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$4b_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$1a_2$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Is this a sensible approach?&lt;/p&gt;&#xA;" OwnerUserId="2205" OwnerDisplayName="ABCCHEM" LastEditorUserId="5" LastEditDate="2021-03-13T22:49:34.033" LastActivityDate="2021-03-14T03:04:20.883" Title="How to determine occupied and closed orbitals for a Molpro CASSCF calculation?" Tags="|software|quantum-chemistry|molpro|casscf|multi-reference|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4495" PostTypeId="2" ParentId="4494" CreationDate="2021-03-14T00:20:13.323" Score="4" Body="&lt;p&gt;The occupied orbital pattern of &lt;code&gt;13 7 6 2&lt;/code&gt; that you got from your Hartree-Fock calculation is not unique. For example, I've just run an RHF calculation on PdO with the ANO-RCC basis set and got a different occupancy pattern compared to you:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Final alpha occupancy:  14   6   6   2&#xA; Final beta  occupancy:  14   5   5   2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I would recommend to find the experimental ground state configuration, which is something that for most diatomic molecules is not too hard to find. For example, here's an unpublished table from a project I worked on with an undergraduate student:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/A3do0.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/A3do0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1247/5&quot;&gt;You cannot rely on theory (in general) to arrive at the ground state configuration, even for a simpler (homonuclear) diatomic molecule like &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe2}$&lt;/span&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There is another complication, which is that, while the best basis sets for diatomic molecules like PdO are arguably the correlation-consistent basis sets, there are no correlation-consistent basis sets for Pd, so many of the electrons will be treated by a pseudopotential (and therefore not treated in the normal way).&lt;/p&gt;&#xA;&lt;p&gt;If you want to pick the occupied orbitals based on your (non-unique!) HF calculation, then you can proceed with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{casscf&#xA; closed,9,5,4,1&#xA; occ,4,2,2,1&#xA; wf,54,4,2,0};      &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I would highly recommend surveying the literature first to see if the experimental ground state configuration is known, and otherwise doing a systematic study to decide which theory calculation is the one on which you wish to rely (already your HF calculation disagrees with mine!).&lt;/p&gt;&#xA;&lt;p&gt;I may be able to help you more if it turns out we need to determine the occupation numbers based on theory alone, but we'd have to also make sure we're using the same basis set and bond length.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-14T03:04:20.883" LastActivityDate="2021-03-14T03:04:20.883" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4496" PostTypeId="2" ParentId="4478" CreationDate="2021-03-14T15:55:36.487" Score="9" Body="&lt;p&gt;&lt;strong&gt;Firstly regarding the SlowQuant problems:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the version of SlowQuant you are using, the program takes two files as input.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The molecules file with the coordinates, number of electrons, and atom IDs.&lt;/li&gt;&#xA;&lt;li&gt;The settings file, see; &lt;a href=&quot;https://slowquant.readthedocs.io/en/latest/Examples.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://slowquant.readthedocs.io/en/latest/Examples.html&lt;/a&gt;. It is in the settings file you would want to add &amp;quot;Charge;Mulliken&amp;quot;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If you have any problems with the code I can be reached by PM on &lt;a href=&quot;https://www.reddit.com/user/ErikRK&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.reddit.com/user/ErikRK&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also if you want to add any features or have any bug fixed feel free to make a pull request on &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/erikkjellgren/SlowQuant&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Secondly you the charge density&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Mulliken charges and Lowdin charges is not quite what you are looking for.&lt;/p&gt;&#xA;&lt;p&gt;If you want the charge density of the electrons in a point in space, this is what we also know as the electron density, and it is defined as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\rho\left(\boldsymbol{r}\right)=\sum_{pq}\Omega_{pq}\left(\boldsymbol{r}\right)D_{pq}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is the density matrix and  &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; is the overlap distribution of two atomic orbitals and given as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Omega_{pq}(\boldsymbol{r}) = \phi_p(\boldsymbol{r})\phi_q(\boldsymbol{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You will therefore have to evaluate the value of the basis functions in a point in space, and then weight them by the molecular orbital coefficients.&lt;/p&gt;&#xA;" OwnerUserId="210" LastEditorUserId="142" LastEditDate="2022-09-27T06:54:45.333" LastActivityDate="2022-09-27T06:54:45.333" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4497" PostTypeId="1" CreationDate="2021-03-14T20:38:41.410" Score="7" ViewCount="90" Body="&lt;p&gt;I have been using Quantum ESPRESSO, specifically the &lt;code&gt;pp.x&lt;/code&gt; module to&#xA;study interactions via charge density plots. The process is slow as&#xA;for crystals containing complex &lt;a href=&quot;https://en.wikipedia.org/wiki/Zintl_phase&quot; rel=&quot;nofollow noreferrer&quot;&gt;Zintl phases&lt;/a&gt;, I need to take planes&#xA;along with different Miller indices and study the charge density contour&#xA;plots along those planes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So is there a software similar to &lt;a href=&quot;http://aim.tkgristmill.com/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;AIM&lt;/a&gt;, which can be used to study interactions in crystals?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="2206" LastEditorUserId="5" LastEditDate="2021-10-19T20:42:15.407" LastActivityDate="2021-10-19T20:42:15.407" Title="Is there a software package to analyse interactions in crystals?" Tags="|density-functional-theory|quantum-espresso|software-recommendations|orbitals|molecular-interactions|" AnswerCount="0" CommentCount="3" ClosedDate="2021-10-19T20:48:26.800" ContentLicense="CC BY-SA 4.0" />
  <row Id="4498" PostTypeId="1" AcceptedAnswerId="4499" CreationDate="2021-03-14T21:30:30.117" Score="13" ViewCount="2470" Body="&lt;p&gt;What is the package used for visualization of spin density isosurfaces in VASP like the ones shown below? A simple example/tutorial would be very appreciated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aYW3Z.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aYW3Z.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-03-15T00:17:32.267" LastActivityDate="2021-07-13T00:36:07.883" Title="How to visualize spin density isosurfaces?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4499" PostTypeId="2" ParentId="4498" CreationDate="2021-03-15T00:30:52.493" Score="10" Body="&lt;p&gt;You can use the packages &lt;a href=&quot;https://vaspkit.com/tutorials.html#density-related&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASPKIT&lt;/a&gt; and &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt; to realize this. Here I just outline the whole flow to obtain spin-related density. I assume you are considering magnetic materials.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Relax your structure in spin-polarized mode (&lt;code&gt;ISPIN=2&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Self-consistent calculation with your relaxed structure in the spin-polarized mode. Remember to output the &lt;code&gt;CHGCAR&lt;/code&gt; file, which contains the information of charge density and also spin density.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the VASPKIT to extract the data stored in &lt;code&gt;CHGCAR&lt;/code&gt; file [vaspkit==&amp;gt; option 31]:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;311: output charge density: &lt;code&gt;CHARGE.vasp&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;312: output spin density: &lt;code&gt;SPIN.vasp&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;313: output spin-up and spin-down separately: &lt;code&gt;SPIN_UP.vasp&lt;/code&gt; and &lt;code&gt;SPIN_DW.vasp&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Visualize these output files &lt;code&gt;XXX.vasp&lt;/code&gt; with &lt;code&gt;VESTA&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="206" LastEditDate="2021-07-13T00:36:07.883" LastActivityDate="2021-07-13T00:36:07.883" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4500" PostTypeId="1" AcceptedAnswerId="4502" CreationDate="2021-03-15T10:48:08.173" Score="7" ViewCount="1773" Body="&lt;p&gt;I want to test different exchange correlational functional on Magnesium silicide to investigate the electronic properties. For example, if I have the &lt;code&gt;POTCAR&lt;/code&gt; library for various pseudopotentials of Mg and Si where we can specify the type of functional from the title/header let's say PBE. How can I change this PBE to PW91 in INCAR to see the effect? The following screencast is my &lt;code&gt;INCAR&lt;/code&gt; for structure relaxation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jkHhn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jkHhn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-15T22:44:16.790" LastActivityDate="2021-03-15T22:45:59.733" Title="How to set different exchange correlational functionals in VASP?" Tags="|vasp|exchange-correlation|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4501" PostTypeId="1" CreationDate="2021-03-15T12:16:57.067" Score="21" ViewCount="3970" Body="&lt;p&gt;I have seen in many presentations and publications, things like &lt;strong&gt;a human on a molecule&lt;/strong&gt; (for example). What software can do this? It's for a presentation I'm doing.&lt;/p&gt;&#xA;" OwnerUserId="1684" LastEditorUserId="5" LastEditDate="2021-03-16T19:13:38.003" LastActivityDate="2021-03-17T02:43:29.480" Title="What software will allow me to combine two images?" Tags="|software|one-topic-per-answer|software-recommendations|" AnswerCount="5" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4502" PostTypeId="2" ParentId="4500" CreationDate="2021-03-15T12:23:14.013" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How can I change this PBE to PW91 in INCAR to see the effect?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;According to the element order of your &lt;code&gt;POSCAR&lt;/code&gt;, concatenate the different &lt;code&gt;POTCAR&lt;/code&gt;s in the GGA pseudopotentials library to generate the final &lt;code&gt;POTCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Set the GGA tag in &lt;code&gt;INCAR&lt;/code&gt; (All other tags in your screencast is OK to me.):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;PBE (default):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GGA=PE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PW91&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GGA=91&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PBEsol:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GGA=PS&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;More settings can refer to this link: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/GGA&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/GGA&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-15T22:45:59.733" LastActivityDate="2021-03-15T22:45:59.733" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4505" PostTypeId="1" CreationDate="2021-03-15T13:26:31.193" Score="8" ViewCount="474" Body="&lt;p&gt;I have an xyz file upon which after processing in Python, I determine bonds between different atoms. What would be the correct file type that I can write to visualize this bond information in VMD?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastEditorUserId="5" LastEditDate="2021-03-15T23:23:59.897" LastActivityDate="2021-03-16T00:25:33.607" Title="File type to write bond information" Tags="|vmd|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4506" PostTypeId="2" ParentId="4505" CreationDate="2021-03-15T14:05:06.780" Score="8" Body="&lt;p&gt;In the &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/current/ug/node26.html&quot; rel=&quot;noreferrer&quot;&gt;VMD user guide&lt;/a&gt; different file formats natively handled by VMD are specified, including &lt;code&gt;PSF&lt;/code&gt; and &lt;code&gt;PARM&lt;/code&gt; that can both contain bond connectivity:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;PSF and PARM files contain atoms, residues, segment names, residue types, atomic mass and charge, and the bond connectivity.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Depending on how your atoms and bonds are represented in python, you may choose to use &lt;a href=&quot;https://parmed.github.io/ParmEd/html/readwrite.html&quot; rel=&quot;noreferrer&quot;&gt;the file input/output functions of the ParmEd library&lt;/a&gt; which &lt;a href=&quot;https://parmed.github.io/ParmEd/html/api/parmed/parmed.formats.psf.html?highlight=psf#module-parmed.formats.psf&quot; rel=&quot;noreferrer&quot;&gt;include support for PSF files&lt;/a&gt; (or any other library that supports it).&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-03-15T14:05:06.780" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4507" PostTypeId="1" CreationDate="2021-03-15T14:08:18.823" Score="5" ViewCount="971" Body="&lt;p&gt;I want to set the &lt;code&gt;RWIGS&lt;/code&gt; value in the &lt;code&gt;INCAR&lt;/code&gt; file for the investigation of the density of states (DOS) of &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt; so what should be the value of &lt;code&gt;RWIGS&lt;/code&gt; and &lt;code&gt;LORBIT&lt;/code&gt; as well for DOS?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-16T08:16:08.733" LastActivityDate="2021-03-17T01:22:05.633" Title="What is the RWIGS value for the DOS calculation in VASP?" Tags="|vasp|density-of-states|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4508" PostTypeId="2" ParentId="4491" CreationDate="2021-03-15T18:07:55.763" Score="8" Body="&lt;h3&gt;MSMS&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://mgl.scripps.edu/people/sanner/html/msms_man.html&quot; rel=&quot;noreferrer&quot;&gt;MSMS&lt;/a&gt; is a rather old (1996) command line tool that computes the Solvent Excluded Surface (SES). It is wrapped in a python module in &lt;a href=&quot;http://mgltools.scripps.edu/packages/MSMS/?searchterm=msms&quot; rel=&quot;noreferrer&quot;&gt;mgtool&lt;/a&gt; or in &lt;a href=&quot;https://openstructure.org/docs/1.3/bindings/msms/&quot; rel=&quot;noreferrer&quot;&gt;openstructure&lt;/a&gt; which may be more convenient to use.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="5" LastEditDate="2021-03-15T18:15:45.417" LastActivityDate="2021-03-15T18:15:45.417" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4509" PostTypeId="1" CreationDate="2021-03-15T18:33:59.793" Score="5" ViewCount="237" Body="&lt;p&gt;I am newbie to DFT and I am trying to understand the different input parameters in the VASP POSCAR file of bulk silicon system, provided in the examples &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Fcc_Si&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. I am trying to find the lattice constant of Silicon. My question is the following:&lt;/p&gt;&#xA;&lt;p&gt;Do I need to know the lattice structure of silicon beforehand to perform this calculation? Can't I give a different unit cell structure (lines 3, 4 and 5 in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Fcc_Si&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;) and still arrive at the same lattice constant?&lt;/p&gt;&#xA;" OwnerUserId="2196" LastEditorUserId="5" LastEditDate="2021-03-15T19:21:20.477" LastActivityDate="2021-03-15T19:29:36.050" Title="Regarding POSCAR file for bulk Silicon" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4510" PostTypeId="2" ParentId="4507" CreationDate="2021-03-15T19:05:09.023" Score="4" Body="&lt;p&gt;For calculating DOS in VASP, Relaxed the structure first using &lt;code&gt;ISIF=3&lt;/code&gt; (volume and atom position relaxation) followed by SCF calculation for generating charge density.&lt;/p&gt;&#xA;&lt;p&gt;In the third calculation use &lt;code&gt;LORBIT=11/12&lt;/code&gt; with &lt;code&gt;ISTART=11&lt;/code&gt;. VASP ignores &lt;code&gt;RWIGS&lt;/code&gt; parameter for &lt;code&gt;LORBIT&amp;gt;=10&lt;/code&gt;,hence no need to change that.&lt;/p&gt;&#xA;&lt;p&gt;Use the &lt;code&gt;ISMEAR&lt;/code&gt; parameter wisely.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2021-03-15T19:19:42.787" LastActivityDate="2021-03-15T19:19:42.787" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4511" PostTypeId="2" ParentId="4509" CreationDate="2021-03-15T19:29:36.050" Score="3" Body="&lt;p&gt;The given example deals with with fitting energy and volume (or lattice parameter). The minima for this relation will give equilibrium lattice parameter where energy of the system is lowest. Example have taken primitive lattice vector of FCC as only one atom is needed for calculation, hence calculation is faster.&#xA;For your second query, you can also choose FCC conventional cell with 4 atom, and theoretically you should have end at same result.&#xA;Do I need to know lattice parameter before hand? My answer is yes, we should have rough idea about equilibrium. It will save your lot of time and if you are doing volume relaxation &lt;code&gt;ISIF=3&lt;/code&gt; for any complex system, starting point far from equilibrium may lead to some other minima.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-03-15T19:29:36.050" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4512" PostTypeId="2" ParentId="4501" CreationDate="2021-03-15T19:35:17.523" Score="19" Body="&lt;h1&gt;GIMP&lt;/h1&gt;&#xA;&lt;p&gt;Whereas Adobe Photoshop has become so famous as a photo editing software, that we often use the term &amp;quot;photoshopped&amp;quot; to describe an image that's been edited, it is very expensive and &lt;a href=&quot;https://www.gimp.org&quot; rel=&quot;noreferrer&quot;&gt;GIMP&lt;/a&gt; is often called &amp;quot;the free Photoshop&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;Free and open source&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;Works on Linux, MacOS, Windows.&lt;/li&gt;&#xA;&lt;li&gt;Easy to install: &lt;code&gt;sudo apt-get install gimp&lt;/code&gt; is all you need in Linux!&lt;/li&gt;&#xA;&lt;li&gt;Well established (first released in 1996)&lt;/li&gt;&#xA;&lt;li&gt;Still highly active in development (&lt;a href=&quot;https://gitlab.gnome.org/GNOME/gimp/activity&quot; rel=&quot;noreferrer&quot;&gt;a commit was pushed 4 days ago on Git&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Like many open-source alternatives to commercial software, it isn't quite as refined as Adobe Photoshop (consider the difference between LibreOffice vs Microsoft Office).&lt;/li&gt;&#xA;&lt;li&gt;Heavyweight: it's a rather large software which will take a lot of time to open (similar to MATLAB).&lt;/li&gt;&#xA;&lt;li&gt;It's not designed specifically for chemistry, it's a general purpose image editing software.&lt;/li&gt;&#xA;&lt;li&gt;Big learning curve: it can take longer to figure out how to use it, compared to simpler programs like Microsoft Paint, or software that is specific for making chemistry figures. The time you spend on learning GIMP will not be a waste though, since GIMP is very powerful for being able to do all sorts of other image work (in the same league as Adobe Photoshop).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-17T02:41:34.930" LastActivityDate="2021-03-17T02:41:34.930" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4513" PostTypeId="2" ParentId="4501" CreationDate="2021-03-15T19:51:21.800" Score="20" Body="&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;http://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;noreferrer&quot;&gt;VMD&lt;/a&gt;&lt;/strong&gt; can load STL files in text (ASCII) format. Here's how I produced the image below:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Downloaded STL file of &lt;a href=&quot;https://en.wikipedia.org/wiki/STL_(file_format)#/media/File:Utah_teapot_(solid).stl&quot; rel=&quot;noreferrer&quot;&gt;teapot from Wikipedia&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;This STL file is in binary format, so I used &lt;a href=&quot;https://www.meshlab.net/&quot; rel=&quot;noreferrer&quot;&gt;MeshLab&lt;/a&gt; to convert it into text format. I opened MeshLab and did File -&amp;gt; Import Mesh and selected the file Utah_teapot_(solid).stl. I then did File -&amp;gt; Export Mesh As and unchecked &amp;quot;Binary encoding&amp;quot; after selecting the file name.&lt;/li&gt;&#xA;&lt;li&gt;The resulting text STL file can be read directed by VMD (New Molecule -&amp;gt; Determine file type: STL Stereolithography Triangle Mesh). You can then load your molecules (New Molecule again) and move them around using Mouse -&amp;gt; Move -&amp;gt; Fragment. &lt;strong&gt;Fun!&lt;/strong&gt; I then used a high quality renderer (File -&amp;gt; Render... -&amp;gt; Tachyon-OSPRay (interactive)).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The advantage of this over image manipulation is that the molecules and objects are in the same 3D scene and that can be reflected in the lighting. &lt;strong&gt;For instance, the propane molecule casts a shadow on the teapot.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;MeshLab can be installed in Ubuntu by &amp;quot;sudo apt install meshlab&amp;quot;. It can probably be easily installed on other platforms as well.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3NrT8m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3NrT8m.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="5" LastEditDate="2021-03-16T20:36:41.413" LastActivityDate="2021-03-16T20:36:41.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4514" PostTypeId="1" AcceptedAnswerId="4578" CreationDate="2021-03-15T21:50:45.640" Score="11" ViewCount="1515" Body="&lt;p&gt;I am simulating a droplet of water with &lt;code&gt;GROMACS&lt;/code&gt;. The droplet consists of about 200 TIP3P water molecules and is placed near the center of a large, mostly empty box (so that it behaves like a free droplet in a vacuum, in spite of periodic boundary conditions. I had to do this as &lt;code&gt;GROMACS2021&lt;/code&gt; does not allow a simulation without PBC).&lt;/p&gt;&#xA;&lt;p&gt;Now, I have to calculate the radial distribution function of the oxygen atoms and hydrogen atoms from the center of mass of the whole unit cell. However, I am not sure how to do this with &lt;code&gt;gmx rdf&lt;/code&gt;. The documentation on the RDF module is minimal, and not clear at all.&lt;/p&gt;&#xA;&lt;p&gt;I tried to run this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx rdf -f md.xtc -s md.tpr -n index.ndx -o com-O.xvg -ref &amp;quot;com of group 0&amp;quot; -sel 3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the index.ndx file, group 0 is System, group 3 is O atoms. However, this gave a graph that looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xlYGm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xlYGm.png&quot; alt=&quot;com-O rdf&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The graph is very squiggly, and I expected a smoother graph.&lt;/p&gt;&#xA;&lt;p&gt;I have also tried to use &lt;code&gt;-ref 0 -selrpos dyn_mol_com&lt;/code&gt; but that gives a graph even more uneven.&lt;/p&gt;&#xA;&lt;p&gt;So my question is what commands should I use with &lt;code&gt;gmx rdf&lt;/code&gt; to get the rdf, and whether my graph looks ok or not?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; I have already gone through these two pages: &lt;a href=&quot;https://manual.gromacs.org/documentation/5.1/onlinehelp/gmx-rdf.html&quot; rel=&quot;noreferrer&quot;&gt;gmx rdf&lt;/a&gt; and &lt;a href=&quot;https://manual.gromacs.org/documentation/5.1/onlinehelp/selections.html&quot; rel=&quot;noreferrer&quot;&gt;selection syntax and usage&lt;/a&gt;, but I cannot understand what they mean. Please don't redirect me to those pages!&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1218" LastEditDate="2021-03-18T10:59:03.473" LastActivityDate="2021-03-25T02:14:25.303" Title="How do I calculate the radial distribution function from the centre of mass of unit cell in GROMACS?" Tags="|molecular-dynamics|gromacs|radial-distribution-function|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4515" PostTypeId="1" AcceptedAnswerId="4521" CreationDate="2021-03-15T22:09:21.130" Score="10" ViewCount="565" Body="&lt;p&gt;I'm interested in writing a simple program (as an exercise) that takes an FCIDUMP file (e.g. from a Molpro calculation) and can determine FCI matrix elements (e.g. to construct the entire FCI matrix to diagonalise, or to use in FCIQMC). I would like to know how to do it so that I can program it myself.&lt;/p&gt;&#xA;&lt;p&gt;Reading in the FCIDUMP file itself is just an exercise in programming (and can be done in one line with pySCF: &lt;code&gt;pyscf.tools.fcidump.read(&amp;quot;fcidump_file&amp;quot;, molpro_orbsym=True)&lt;/code&gt;), so let's start with all the integrals given &lt;span class=&quot;math-container&quot;&gt;$(\psi_i\psi_j|\psi_k\psi_l)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$h_{ij}$&lt;/span&gt;, as well as the extra parameters in the first block (which I am less sure how to use). &lt;strong&gt;How does one calculate the (FCI) Hamiltonian matrix element &lt;span class=&quot;math-container&quot;&gt;$H_{ij}$&lt;/span&gt; given these values?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm aware of the Slater-Condon rules and know they will be needed here, but I'm not sure how to generate a general matrix element from these values, or how the parameters that come before the integrals are useful (presumably &lt;code&gt;ORBSYM&lt;/code&gt; can reduce the size of the matrix).&lt;/p&gt;&#xA;" OwnerUserId="1522" LastEditorUserId="5" LastEditDate="2021-03-15T22:13:27.290" LastActivityDate="2022-08-09T17:14:57.930" Title="How to calculate FCI matrix elements from an FCIDUMP file" Tags="|software|ab-initio-calculations|fcidump|full-configuration-interaction|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4516" PostTypeId="2" ParentId="4501" CreationDate="2021-03-15T22:53:48.067" Score="15" Body="&lt;h1&gt;Adobe Dimension&lt;/h1&gt;&#xA;&lt;p&gt;Adobe dimension is the premier paid software for 3-dimensional design. It can read in STL files and give them a texture, and incorporate the light source from the background light.&lt;/p&gt;&#xA;&lt;p&gt;The tutorial I watched to make this is &lt;a href=&quot;https://helpx.adobe.com/dimension/how-to/3d-design.html?playlist=/services/playlist.helpx/products:SG_DIMENSION/learn-path:get-started/set-header:ccx-designer/playlist:orientation/en_us.json&amp;amp;ref=helpx.adobe.com&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0Xr4om.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0Xr4om.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-03-16T20:36:29.980" LastActivityDate="2021-03-16T20:36:29.980" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4517" PostTypeId="5" CreationDate="2021-03-15T23:01:40.087" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-15T23:01:40.087" LastActivityDate="2021-03-15T23:01:40.087" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4518" PostTypeId="4" CreationDate="2021-03-15T23:01:40.087" Score="0" Body="Questions about radial distributions functions: g(r)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-15T23:01:40.087" LastActivityDate="2021-03-15T23:01:40.087" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4519" PostTypeId="2" ParentId="4501" CreationDate="2021-03-15T23:44:34.530" Score="22" Body="&lt;h1&gt;Blender&lt;/h1&gt;&#xA;&lt;p&gt;I usually do 3D images with molecules using &lt;a href=&quot;https://www.blender.org&quot; rel=&quot;noreferrer&quot;&gt;Blender&lt;/a&gt;. You can export your molecule 3D model with a chemistry visualization program (such as vmd or jmol) into Blender (I usually do it using OBJ files, it just needs a couple of adjustments after the import), OR you can write your own python loader from within Blender (harder to do, but possible). It is NOT an easy route, Blender is a complex program that takes years to master, but it definitely gives amazing results if you put time into it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Y764xm.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Y764xm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="858" LastEditorUserId="5" LastEditDate="2021-03-17T02:43:29.480" LastActivityDate="2021-03-17T02:43:29.480" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4520" PostTypeId="2" ParentId="4505" CreationDate="2021-03-16T00:25:33.607" Score="7" Body="&lt;p&gt;I usually use &lt;strong&gt;mol2&lt;/strong&gt; or &lt;strong&gt;psf&lt;/strong&gt; formats to explicitly include bonds. mol2 works with many other programs (Avogadro, OpenBabel), while psf files are good for anything in CHARMM world (CHARMM, NAMD). The psf capabilities of VMD are good since it lives in CHARMM world as well.&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2021-03-16T00:25:33.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4521" PostTypeId="2" ParentId="4515" CreationDate="2021-03-16T00:49:36.780" Score="11" Body="&lt;p&gt;Let's go back to the original paper where the &lt;a href=&quot;/questions/tagged/fcidump&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;fcidump&amp;#39;&quot; rel=&quot;tag&quot;&gt;fcidump&lt;/a&gt; format was first proposed: &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0010465589900337&quot; rel=&quot;nofollow noreferrer&quot;&gt;A determinant based full configuration interaction program&lt;/a&gt; by Peter Knowles (lead author of the MOLPRO program, along with Hans-Joachim Werner) and Nick Handy in 1989. This algorithm is still used by a lot of people today, and is considered one of the most efficient ways to do FCI. Some people call this a &lt;strong&gt;string-based&lt;/strong&gt; approach.&lt;/p&gt;&#xA;&lt;p&gt;In a &amp;quot;string-based&amp;quot; approach, Slater determinants are represented by a binary string, such as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;|\Phi\rangle =|11111111110010000000000000\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the 1s, 2s, 2px, 2py, and 2pz orbitals are all doubly occupied (the first 10 ones), and the 3s orbital is completely empty, then the 3px orbital has one electron, then everything else in the basis set is empty. This is a single-excitation of the HF determinant which would look like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;|\textrm{HF}\rangle = |11111111111000000000000000\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can now enumerate all possible &amp;quot;strings&amp;quot; that you wish to allow, based on your molecule's spatial symmetry and spin symmetry (for example), and label these determinants as &lt;span class=&quot;math-container&quot;&gt;$|\Phi_i\rangle$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; goes from 1 (for the reference determinant, which is usually the Hartree-Fock determinant) to the number of determinants in your list.&lt;/p&gt;&#xA;&lt;p&gt;Now, the question you ask is how to get the matrix elements:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;H_{ij} = \langle \Phi_i|\hat{H} |\Phi_j \rangle, &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for the following Hamiltonian operator:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}\hat{H} = \sum_{pq} h_{pq} \hat{a}_p^\dagger \hat{a}_q + \frac12 \sum_{pqrs} h_{pqrs} \hat{a}_p^\dagger \hat{a}_q^\dagger \hat{a}_r \hat{a}_s + \hat{H}_\textrm{nuc}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You have all the one-electron integrals &lt;span class=&quot;math-container&quot;&gt;$H_{pq}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H_{pqrs}$&lt;/span&gt; from the &lt;code&gt;FCIDUMP&lt;/code&gt; file already, so now you just have to apply the creation and annihilation operators to the bit-strings, remembering that single-excitations will remove an electron (i.e. a 1 in the bit-string) from its present orbital and place it into one of the unoccupied orbitals (i.e. a 0 in the bit-string), and a double-excitation will do this twice.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I would not recommend doing this for a large basis set or a large number of electrons, because your number of matrix elements will explode &lt;em&gt;very&lt;/em&gt; quickly.&lt;/li&gt;&#xA;&lt;li&gt;I would also recommend that while writing a program to do this can be a good exercise for a beginner, it would be best to stick to a well-established software  if you want to do any serious calculations, rather than re-inventing the wheel.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In your question you said that you might try to implement FCIQMC. If so, please do not store the whole &lt;span class=&quot;math-container&quot;&gt;$H_{ij}$&lt;/span&gt;. The whole point of FCIQMC is that you &lt;em&gt;&lt;strong&gt;do not&lt;/strong&gt;&lt;/em&gt; store the whole FCI matrix, but you effectively only use parts of it as they are needed. There's an open source FCIQMC code called NECI (N-electron Configuration Interaction) which can be downloaded from GitHub &lt;a href=&quot;https://github.com/ghb24/NECI_STABLE&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and there's also &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;nofollow noreferrer&quot;&gt;a paper about it&lt;/a&gt; for which I'm a co-author. There's a lot of work that went into  this software, so again, be careful to &lt;em&gt;balance&lt;/em&gt; your education journey with practicality in trying to accomplish research goals.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5815" LastEditDate="2022-08-09T17:14:57.930" LastActivityDate="2022-08-09T17:14:57.930" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4522" PostTypeId="2" ParentId="4507" CreationDate="2021-03-16T08:52:44.833" Score="3" Body="&lt;p&gt;Just add more information to @Pranav Kumar's answer.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is the RWIGS value for the density of states calculation in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;In short, RWIGS specifies the Wigner-Seitz radius for each atom type. The default value for this tag can be read from the &lt;code&gt;POTCAR&lt;/code&gt;. If you have not any prior knowledge about your system, for example, the charge distribution around each atom, I strongly suggest you just use the default radius. If you do want to know how to set manually it, you may need to understand how the PAW method adopted by the &lt;code&gt;VASP&lt;/code&gt; package works.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Always take a first look at the official explanation about the tag used by &lt;code&gt;INCAR&lt;/code&gt; from &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspwiki&lt;/a&gt;. For example, you can find an explanation of the &lt;code&gt;RWIGS&lt;/code&gt; tag: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/RWIGS&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/RWIGS&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;what should be the value of RWIGS and LORBIT as well for DOS?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The relation between RWIGS and LORBIT also can be found in &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LORBIT&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspwiki&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5rJ1K.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5rJ1K.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If you just want to calculate the DOS, you can simply follow @pranav kumar's strategy:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Self-consistent-field (SCF) calculation to obtain converged charge density.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Non-self-consistent-field (NSCF) calculation by reading SCF charge density to calculated DOS.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The general DOS-related tags used in &lt;code&gt;INCAR&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#DOS-related:&#xA;  LORBIT=11&#xA;  #RWIGS=R(Mg) R(Si)    ## fill two real number&#xA;  EMIN=-20&#xA;  EMAX=15&#xA;  NEDOS=2000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-17T01:22:05.633" LastActivityDate="2021-03-17T01:22:05.633" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4523" PostTypeId="2" ParentId="4501" CreationDate="2021-03-16T21:37:21.127" Score="12" Body="&lt;h1&gt;SAMSON&lt;/h1&gt;&#xA;&lt;p&gt;SAMSON, the molecular design platform, can do this in a few clicks with a Pro plan (see image below), by letting you import textured OBJ files into the document. The website is &lt;a href=&quot;https://www.samson-connect.net&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The standard plan also lets you &lt;em&gt;export&lt;/em&gt; textured OBJ files, so you can import molecules (e.g. PDB files) into SAMSON, choose visual representations for them (van der Waals, secondary structure, etc.) and export these as textured OBJ files (which will preserve colors) that you will then import in e.g. Blender.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QrgSs.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QrgSs.jpg&quot; alt=&quot;SAMSON&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2213" LastEditorUserId="2213" LastEditDate="2021-03-16T22:06:12.703" LastActivityDate="2021-03-16T22:06:12.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4524" PostTypeId="1" AcceptedAnswerId="4560" CreationDate="2021-03-17T09:47:08.077" Score="8" ViewCount="118" Body="&lt;p&gt;I have compiled the &lt;strong&gt;Bandup&lt;/strong&gt; software using this command : &lt;code&gt;./build -compiler gfortran&lt;/code&gt;. After that, I tried to follow the tutorial inside the directory &lt;code&gt;bandup-master/tutorial/VASP/example_2_bulk_Si&lt;/code&gt;. The second step gave me this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/home/e/bjm42/bin/bandup&amp;quot;, line 73, in &amp;lt;module&amp;gt;&#xA;    run_requested_task(args)&#xA;  File &amp;quot;/home/e/bjm42/source/bandup/src/python_interface/bandupy/runners.py&amp;quot;, line 73, in run_requested_task&#xA;    run_pre_bandup_tool(args)&#xA;  File &amp;quot;/home/e/bjm42/source/bandup/src/python_interface/bandupy/runners.py&amp;quot;, line 54, in run_pre_bandup_tool&#xA;    sys.stdout.write(line)&#xA;TypeError: write() argument must be str, not bytes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you know how to solve it?&#xA;Can I unfold bandstructure directly with Bandup without going through the steps mentionned in the tutorial?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-03-19T23:24:51.510" LastActivityDate="2021-03-19T23:24:51.510" Title="How to solve this Bandup software problem?" Tags="|density-functional-theory|vasp|band-structure|software-assistance|bandup|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4525" PostTypeId="1" AcceptedAnswerId="4529" CreationDate="2021-03-17T11:57:34.697" Score="7" ViewCount="1617" Body="&lt;p&gt;I am searching of how to set the tags NCORE, KPAR and NBANDS on a specific systems to speed up calculations. Could you please tell me the rules to follow ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-03-18T05:22:42.293" Title="How to set NCORE, KPAR and NBANDS to speed up calculations on VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4526" PostTypeId="1" CreationDate="2021-03-17T13:17:06.133" Score="10" ViewCount="3163" Body="&lt;p&gt;It's as the title of the question states. To be specific, I'm wondering if there are any free online repositories where I can download (.csv or .txt. or .xsl) files for x-ray diffraction (XRD) data.&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="5" LastEditDate="2021-03-17T19:24:28.853" LastActivityDate="2021-03-20T12:11:32.213" Title="Is there a free online repository where I can download X-ray diffraction (XRD) data?" Tags="|spectroscopy|databases|x-ray-diffraction|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4527" PostTypeId="1" AcceptedAnswerId="4546" CreationDate="2021-03-17T14:47:44.270" Score="6" ViewCount="105" Body="&lt;p&gt;In a course on the mechanical properties of materials, I have been asked to do a paper on the &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Finite_element_method&quot; rel=&quot;noreferrer&quot;&gt;Finite Element Method&lt;/a&gt;&amp;quot; to improve my current grade.&lt;/p&gt;&#xA;&lt;p&gt;However, most of the resources I find on the Internet explain theoretical frameworks, with complex mathematics that I do not understand.&lt;/p&gt;&#xA;&lt;p&gt;Do you know of any book or website that explains this method in a simple way? In short, that focuses, above all, on the applications for a materials engineer and that provides, if possible, a simple theoretical framework, which can be understood without the need for external help or almost impossible mathematics.&lt;/p&gt;&#xA;" OwnerUserId="1744" LastActivityDate="2021-03-19T09:43:36.260" Title="Books and online resources to get me started in the finite element method (FEM)" Tags="|mathematical-modeling|mechanical-properties|finite-element-analysis|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4528" PostTypeId="2" ParentId="4527" CreationDate="2021-03-17T17:56:20.147" Score="5" Body="&lt;p&gt;I recommend you to visit and go through the COMSOL Multiphysics &lt;a href=&quot;https://www.comsol.com/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;COMSOL software is based on finite element method (FEM) with applications in several areas of Physics. In the site, you can request a demonstration of the software (so you will have the experience to use FEM in practice) and also can visit the &lt;a href=&quot;https://www.comsol.com/events/webinars&quot; rel=&quot;noreferrer&quot;&gt;WEBMINARS&lt;/a&gt; section that is full of applications with very useful discussions.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-03-17T17:56:20.147" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4529" PostTypeId="2" ParentId="4525" CreationDate="2021-03-18T05:13:14.517" Score="6" Body="&lt;p&gt;Well This question is very much demanding for all user, How to reduce calculation time without loosing accuracy of calculation. There are several ways suggested by various VASP user but at the end it all depends on the architecture of the machine.&#xA;Factor that need to be addressed first are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Number of CPU per node&lt;/li&gt;&#xA;&lt;li&gt;Number of Node available&lt;/li&gt;&#xA;&lt;li&gt;whether GPU available&lt;/li&gt;&#xA;&lt;li&gt;Communication between node&lt;/li&gt;&#xA;&lt;li&gt;Intel vs open libraries&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Hence its bit tricky to answer fully that how much resource I need for  optimum result. one can easily benchmark their  cluster/machine by simple scf calculation. or just follow &lt;a href=&quot;https://github.com/JMSkelton/VASP-GPU-Benchmarking&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/JMSkelton/VASP-GPU-Benchmarking&lt;/a&gt;.&#xA;Let me discuss what is commonly observed results,&#xA;&lt;code&gt;KPAR&lt;/code&gt;= number of nodes,&#xA;&lt;code&gt;AlGO&lt;/code&gt;=Fast (RMM-DIS also fails in many complex system)&#xA;&lt;code&gt;NCORE&lt;/code&gt;= determines how many cores work on one orbital (Try 4,8, up to number of core per node to find optimal)&#xA;Generally NCORE=8 or 16 is enough.&#xA;&lt;code&gt;NPLANE&lt;/code&gt;,&lt;code&gt;NSIM&lt;/code&gt;,&lt;code&gt;NBANDS&lt;/code&gt; are three other parameter you can play in your system but keep checking on amount of memory calculation is demanding.&#xA;There are several studies has been done on this&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nsc.liu.se/%7Epla/blog/archives/&quot; rel=&quot;noreferrer&quot;&gt;https://www.nsc.liu.se/~pla/blog/archives/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nvidia.com/en-us/data-center/gpu-accelerated-applications/vasp/&quot; rel=&quot;noreferrer&quot;&gt;https://www.nvidia.com/en-us/data-center/gpu-accelerated-applications/vasp/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.hector.ac.uk/support/documentation/software/vasp/benchmark/&quot; rel=&quot;noreferrer&quot;&gt;http://www.hector.ac.uk/support/documentation/software/vasp/benchmark/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2021-03-18T05:22:42.293" LastActivityDate="2021-03-18T05:22:42.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4530" PostTypeId="1" AcceptedAnswerId="4540" CreationDate="2021-03-18T08:28:59.973" Score="25" ViewCount="4412" Body="&lt;p&gt;Geometry optimization using density functional theory (DFT) is done by moving the atoms of a molecule to get the most stable structure with the lowest possible ground state energy. My question is what are the equations involved in this procedure? Where are the electrons in this step?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-21T07:43:50.173" LastActivityDate="2021-03-22T10:01:03.327" Title="Geometry optimization: what happens in the algorithm?" Tags="|density-functional-theory|geometry-optimization|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4531" PostTypeId="1" AcceptedAnswerId="4535" CreationDate="2021-03-18T09:40:31.313" Score="8" ViewCount="164" Body="&lt;p&gt;I found in the literature that the formation energy of doped supercell (e.g.: &lt;code&gt;4x4x1 supercell with one dopant atom&lt;/code&gt;) has many formulas, and the most common one is :&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{\textrm{form}}=E_{\textrm{total}}-E_{\textrm{defect}}-E_{\textrm{TM}}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;What do they mean by &lt;span class=&quot;math-container&quot;&gt;$E_{\textrm{TM}}$&lt;/span&gt;? is it the energy of the dopant in its &lt;strong&gt;bulk stable phase&lt;/strong&gt; ? or the energy of the dopant in &lt;strong&gt;isolated form&lt;/strong&gt;?&lt;/li&gt;&#xA;&lt;li&gt;How to calculate the energy of the &lt;strong&gt;&lt;code&gt;Mn&lt;/code&gt;&lt;/strong&gt; element in its bulk stable phase in &lt;code&gt;VASP&lt;/code&gt;?&lt;/li&gt;&#xA;&lt;li&gt;How to simulate and calculate the energy of an isolated atom in &lt;code&gt;VASP&lt;/code&gt;?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;&lt;p&gt;Reference paper : &lt;a href=&quot;https://doi.org/10.1016/j.apsusc.2019.144367&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1016/j.apsusc.2019.144367&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-03-18T20:36:00.927" LastActivityDate="2021-03-18T20:36:00.927" Title="How to calculate E_TM in the formation energy formulas?" Tags="|density-functional-theory|vasp|formation-energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4532" PostTypeId="2" ParentId="4530" CreationDate="2021-03-18T10:24:14.410" Score="19" Body="&lt;p&gt;First, realize that optimization is a general thing that can be done for all types of problems.&lt;/p&gt;&#xA;&lt;p&gt;In the geometry optimization of atoms and molecules, what we want to find is the configuration of the nuclei which is a minima on the potential energy surface.&#xA;In other words, we want to find the positions, x which satisfy:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\min(E[x])$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Secondly, the quantum mechanical energy of a molecule is dependent on the positions of the electrons and parameterically dependent on the position of the nuclei E[r,x] where r are the positions of the electrons. This is known as the &lt;a href=&quot;https://web.northeastern.edu/afeiguin/phys5870/phys5870/node9.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Born-Oppenheimer approximation&lt;/a&gt;. So when we are dealing with geometry optimization we don't care where the electrons are because we can assume they are in their proper places for that geometry. In fact we can use molecular mechanics to give us the energy and there are no electrons in that model, only internuclear potentials.&lt;/p&gt;&#xA;&lt;p&gt;There are many algorithms to find the minimum energy geometry. One of the most popular is a second order method called Newton-Raphson which constructs a local quadratic approximation to the potential energy surface:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E(x) = E(x_{0}) + g_0^T\Delta x + 1/2\Delta x^TH_0\Delta x $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; is the gradient (dE/dx) at &lt;span class=&quot;math-container&quot;&gt;$x_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; is the Hessian (d^2E/dx^2) at &lt;span class=&quot;math-container&quot;&gt;$x_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Delta x = x-x_0$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So technically this is the equation which is &amp;quot;solved&amp;quot; when you are doing a geometry optimization. But there are many other ways of solving it as well, for example see my other answer here:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1069/52&quot;&gt;https://mattermodeling.stackexchange.com/a/1069/52&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a good overview of geometry optimization I recommend &lt;em&gt;Geometry optimization&lt;/em&gt; by H. B. Schlegel in Wiley Interdisciplinary Reviews: Computational Molecular Science (WIREs Comput Mol Sci, 2011, 790–809; &lt;a href=&quot;https://doi.org/10.1002/wcms.34&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi 10.1002/wcms.34&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="142" LastEditDate="2021-03-22T10:01:03.327" LastActivityDate="2021-03-22T10:01:03.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4533" PostTypeId="2" ParentId="4530" CreationDate="2021-03-18T12:21:10.570" Score="19" Body="&lt;p&gt;To add to the other answer, the energy of a molecule (or any chemical species) can be expressed as a function of the coordinates of the atoms. Most softwares convert the 3N cartesian coordinates into internal coordinates (3N-6 for non-linear molecules, 3N-5 for linear), removing the rotational and translational degrees of freedom. Usually, the optimization is done in internal coordinates by most QM softwares. Internal coordinates mean bonds, angles, dihedrals etc.&lt;/p&gt;&#xA;&lt;p&gt;If we have a set of coordinates &lt;span class=&quot;math-container&quot;&gt;$x_1, x_2, x_3, .... ,x_n$&lt;/span&gt;, then we can carry out the SCF procedure for that set of coordinates (i.e. Born-Oppenheimer approx.). The energy is then a function of the coordinates: &lt;span class=&quot;math-container&quot;&gt;$$E=f(x_1,x_2,x_3,...,x_n)$$&lt;/span&gt;&#xA;This is an &lt;a href=&quot;https://en.wikipedia.org/wiki/Mathematical_optimization&quot; rel=&quot;noreferrer&quot;&gt;optimization problem&lt;/a&gt;, i.e. we seek to minimize E by varying the variables &lt;span class=&quot;math-container&quot;&gt;$x_1, x_2,..., x_n$&lt;/span&gt;. There are a lot of algorithms that do this. Newton-Raphson (NR) has been mentioned. It is an efficient algorithm, however it needs accurate second derivatives (hessian). The second derivatives are time-consuming to calculate, so most QM codes use what are known are &lt;a href=&quot;https://en.wikipedia.org/wiki/Quasi-Newton_method&quot; rel=&quot;noreferrer&quot;&gt;quasi-Newton&lt;/a&gt; methods.&lt;/p&gt;&#xA;&lt;p&gt;These methods require only accurate gradient (first derivatives), and an approximate (guess) hessian. The gradient can be calculated directly from the SCF solution, so these quasi-Newton methods are much faster. Examples of quasi-Newton algorithms include &lt;a href=&quot;https://en.wikipedia.org/wiki/Broyden%E2%80%93Fletcher%E2%80%93Goldfarb%E2%80%93Shanno_algorithm&quot; rel=&quot;noreferrer&quot;&gt;BFGS&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Limited-memory_BFGS&quot; rel=&quot;noreferrer&quot;&gt;L-BFGS&lt;/a&gt;, Rational Function Optimization(&lt;a href=&quot;http://klingon.uab.es/prat/Thesis/node29.html&quot; rel=&quot;noreferrer&quot;&gt;RFO&lt;/a&gt;) etc.&lt;/p&gt;&#xA;&lt;p&gt;The optimization procedure is iterative. In quasi-Newton methods, the hessian matrix is also updated after each step in optimization. Note that instead of guessing the hessian, we can also calculate it and that will lead to quicker convergence.&lt;/p&gt;&#xA;&lt;p&gt;So in brief, the general steps of optimization are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Start with a set of coordinates&lt;/li&gt;&#xA;&lt;li&gt;Carry out SCF and get the energy, gradient (optionally hessian)&lt;/li&gt;&#xA;&lt;li&gt;Feed the gradient and hessian into the optimizer algorithm, which will then tell how to vary the coordinates to go towards the minimum (this is called a step)&lt;/li&gt;&#xA;&lt;li&gt;Check if the step is too large, if yes then scale it down (optional)&lt;/li&gt;&#xA;&lt;li&gt;Take the step (i.e. change the coordinates)&lt;/li&gt;&#xA;&lt;li&gt;Update the hessian&lt;/li&gt;&#xA;&lt;li&gt;Go to step 1&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The optimization procedure iterates through these steps until a certain criteria for convergence is reached. Usually this criteria would be that the gradient is lower than a certain threshold (close to zero), or the next step size is lower than a certain value etc. This type of optimization is usually done in QM softwares like Gaussian, GAMESS, Orca etc.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, there are modified versions of NR such as Eigenvector Following (EF) algorithm, which can use accurate hessian to actually move towards maxima (transition states).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;In molecular dynamics, usually the system is so large that even storing the guess hessian is problematic. So, first-order optimizer algorithms are used e.g.- Conjugate gradient, Steepest descent etc. These optimizers do not require the hessian at all, and only work with the gradient. Therefore, they are slower to converge than second order methods. However, that's okay for MD as the energy/gradient calculation steps are much much faster than SCF calculation.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Edit: In your question, you have asked about the electrons. To make things clear, there are two separate things here—one is the optimization procedure and the other is the SCF. The optimization procedure needs only the coordinates, the gradient and the hessian and nothing else. It has nothing to do with electrons. The SCF part is where the energy, gradient (and hessian) is calculated keeping the coordinates fixed. The SCF equations (e.g. Hartree-Fock) will involve the electrons.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-03-18T22:46:14.063" LastActivityDate="2021-03-18T22:46:14.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4534" PostTypeId="1" AcceptedAnswerId="4536" CreationDate="2021-03-18T13:46:07.177" Score="10" ViewCount="336" Body="&lt;p&gt;Since the discovery of graphene in 2004, two-dimensional (2D) materials have been a hot topic in the community of condensed matter physics, which can be considered as the candidate for next-generation electronics and also as an important platform to demonstrate interesting physics.&lt;/p&gt;&#xA;&lt;p&gt;Almost 20 years have gone by, what're the big things that happened in this field, for example in nanoelectronics, and what's the challenge for the future?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-03-18T14:09:07.573" LastActivityDate="2021-03-18T16:38:31.223" Title="What's the past and future of 2D materials since graphene?" Tags="|condensed-matter|2d-lattice|graphene|nanostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4535" PostTypeId="2" ParentId="4531" CreationDate="2021-03-18T15:00:18.700" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What do they mean by ETM? is it the energy of the dopant in its bulk stable phase ? or the energy of the dopant in isolated form?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It is the energy of the transition metal element in its isolate form.&#xA;A similar problem can be seen &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3491/24&quot;&gt;here&lt;/a&gt;.&#xA;The energetic calculations can be seen &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/378/24&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1004/24&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to calculate the energy of the Mn element in its bulk stable phase in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You need the CIF (crystallographic Information File) with details of the crystal structure for &lt;span class=&quot;math-container&quot;&gt;$\ce{Mn}$&lt;/span&gt; (you can obtain it from the &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; site). Then, you create the POSCAR input file where you add the calculation info (energy/mesh cutoff, exchange correlation functional, etc.)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How to simulate and calculate the energy of an isolated atom in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can create an input file with only one atom (without crystal information) or create a (fake) crystal with only one atom in its center.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-03-18T15:07:34.157" LastActivityDate="2021-03-18T15:07:34.157" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4536" PostTypeId="2" ParentId="4534" CreationDate="2021-03-18T16:38:31.223" Score="10" Body="&lt;p&gt;Actually, if you allow for quasi-2D systems, graphene has had a recent renaissance starting with the &lt;a href=&quot;https://www.nature.com/articles/nature26154&quot; rel=&quot;noreferrer&quot;&gt;experimental discovery&lt;/a&gt; of correlated states in &lt;a href=&quot;https://physics.aps.org/articles/v12/12?&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;magic angle&amp;quot; twisted bilayer graphene&lt;/a&gt;, which was originally predicted by &lt;a href=&quot;https://www.pnas.org/content/108/30/12233&quot; rel=&quot;noreferrer&quot;&gt;Bistritzer and MacDonald&lt;/a&gt;. By stacking two graphene layers with a relative twist, new structures with very long periodicity can be generated. At certain &amp;quot;magic&amp;quot; angles, flat bands appear, where interaction effects can be strong and generate new interesting phases. More generally, such &lt;a href=&quot;https://www.nature.com/articles/s41578-021-00284-1&quot; rel=&quot;noreferrer&quot;&gt;moiré materials&lt;/a&gt; offer a lot of tunability. I'm not sure if they're very useful for applications since at least graphene is very sensitive to the twist angle, but they do provide an exciting and tunable experimental platform to study Hubbard physics and topological states. An inherent challenge to the modeling of these systems  is that the superlattice unit cells is large. Some others are outlined &lt;a href=&quot;https://www.nature.com/articles/s41563-020-00840-0&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There is also plenty of activity in transition metal dichalcogenides (&amp;quot;TMDs&amp;quot;), van der Waals magnets such as &lt;a href=&quot;https://www.nature.com/articles/nature22391?sf86685293=1&quot; rel=&quot;noreferrer&quot;&gt;CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;&lt;/a&gt;, and &lt;a href=&quot;https://en.wikipedia.org/wiki/MXenes&quot; rel=&quot;noreferrer&quot;&gt;MXenes&lt;/a&gt;. &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acsnano.5b05556&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a 2015 review on 2D materials beyond graphene. One of the practical challenges with 2Ds TMDs is a large contact resistance that so far seems to limit their usefulness for electronics. I'm not sure what the other challenges are. However, similar to graphene mentioned above, many of these materials are now being investigated in few-layer systems, where there may be interesting stacking-dependent behavior and moiré physics.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-03-18T16:38:31.223" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4537" PostTypeId="2" ParentId="4526" CreationDate="2021-03-18T22:39:49.983" Score="6" Body="&lt;p&gt;The &lt;a href=&quot;http://crystallography.net/cod/index.php&quot; rel=&quot;noreferrer&quot;&gt;Crystallography Open Database&lt;/a&gt; is a good database of experimental crystal structures, take a look at their .hkl files which contain &lt;a href=&quot;https://www.iucr.org/education/pamphlets/3/full-text&quot; rel=&quot;noreferrer&quot;&gt;structure factors&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://materialsproject.org&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt;, a computational database, also calculations X-ray diffraction patterns and absorption patterns (disclosure, I'm on the Materials Project staff).&lt;/p&gt;&#xA;&lt;p&gt;You can also generate your own once you have a crystal structure, many tools exist to generate a diffraction pattern, for example &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt; using the &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.diffraction.xrd.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;XRDCalculator&lt;/code&gt;&lt;/a&gt;, though these will need to be artificially broadened if you want something that looks like an experimental pattern.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2021-03-18T22:39:49.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4538" PostTypeId="1" CreationDate="2021-03-18T23:21:30.017" Score="34" ViewCount="9685" Body="&lt;p&gt;When I started studying computational chemistry (&lt;em&gt;circa&lt;/em&gt; 2007), my supervisor used to tell me about the controversy surrounding Gaussian, Inc. regarding the banning of researchers involved in the development of competing software (there is a very famous &lt;a href=&quot;https://www.nature.com/articles/429231a&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; in Nature about that). He didn't care much about it, said it was possibly a hoax and openly defied Gaussian's licensing terms because he thought he would not be punished and that the scientists who created the anonymous website &lt;em&gt;bannedbygaussian.org&lt;/em&gt; were just disseminators of fake news.&lt;/p&gt;&#xA;&lt;p&gt;Eventually came the day  when my advisor published an article in which he compared the computational efficiency of Spartan with that of Gaussian in simulating a PAH he was studying. A few months later, he was surprised to receive a notification (when it was time to renew the license, if I remember correctly) that both he and his coworkers were no longer allowed to use Gaussian. At the time he was already retiring and was not too worried (he died in 2018). However, he deeply regretted doubting the anonymous community of scientists who created &lt;em&gt;bannedbygaussian.org&lt;/em&gt;. By that time, I had just left the academic world, but in any case I promised myself that I would not use Gaussian software anymore.&lt;/p&gt;&#xA;&lt;p&gt;Long story short, recently I am considering returning to computational chemistry studies and I am not aware of software that can replace Gaussian. As I have not been in contact with matter modeling for many years, I would like a &lt;strong&gt;suggestion&lt;/strong&gt; from the community so as not to have to break my promise, honoring my late advisor.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="2210" LastEditorUserId="5" LastEditDate="2021-03-18T23:47:55.143" LastActivityDate="2021-03-20T10:27:27.580" Title="What is a good replacement for Gaussian?" Tags="|software|quantum-chemistry|software-recommendations|gaussian|open-source|" AnswerCount="5" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4539" PostTypeId="2" ParentId="4538" CreationDate="2021-03-18T23:32:59.777" Score="25" Body="&lt;h1&gt;ORCA&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Official website: &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/portal&quot; rel=&quot;noreferrer&quot;&gt;https://orcaforum.kofo.mpg.de/app.php/portal&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What is ORCA?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ORCA is a general-purpose quantum chemistry program package that features virtually all modern electronic structure methods (density functional theory, many-body perturbation, and coupled-cluster theories, and multireference and semiempirical methods). It is a flexible, efficient, and easy-to-use general-purpose tool for quantum chemistry with specific emphasis on spectroscopic properties of open-shell molecules. It features a wide variety of standard quantum chemical methods ranging from semiempirical methods to DFT to single- and multireference correlated ab initio methods. It can also treat environmental and relativistic effects.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ORCA uses standard Gaussian basis functions and is fully parallelized. Due to the user-friendly style, ORCA is considered to be a helpful tool not only for computational chemists but also for chemists, physicists, and biologists that are interested in developing the full information content of their experimental data with help of calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Which can ORCA do?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;geometry optimizations;&lt;/li&gt;&#xA;&lt;li&gt;spectroscopic parameters;&lt;/li&gt;&#xA;&lt;li&gt;Hartree Fock, DFT...&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PS: You can find more choices from &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;this Wikipedia link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-03-19T03:20:36.127" LastActivityDate="2021-03-19T03:20:36.127" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4540" PostTypeId="2" ParentId="4530" CreationDate="2021-03-18T23:57:44.327" Score="17" Body="&lt;h2&gt;GDIIS (Geometry Direct Inversion in Iterative Subspace)&lt;/h2&gt;&#xA;&lt;p&gt;This is a &lt;em&gt;&lt;strong&gt;very&lt;/strong&gt;&lt;/em&gt; popular method, implemented in almost all the major quantum chemistry software packages, which is quite different from the quasi-Newton and related approaches mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4533/5&quot;&gt;Shoubhik's excellent answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;DIIS was originally &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.540030413&quot; rel=&quot;noreferrer&quot;&gt;published in 1982 by Peter Pulay&lt;/a&gt; for accelerating SCF convergence, and has become the default method for SCF convergence (and also the convergence of many other things now, such as coupled cluster equations) in almost every electronic structure software I know, including (each link takes you to the software's DIIS page in the documentation, just search &amp;quot;DIIS&amp;quot;) &lt;a href=&quot;https://www.molpro.net/info/2015.1/doc/manual/node354.html&quot; rel=&quot;noreferrer&quot;&gt;MOLPRO&lt;/a&gt;, &lt;a href=&quot;https://psicode.org/psi4manual/master/autodir_options_c/module__scf.html&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt;, &lt;a href=&quot;https://manual.q-chem.com/4.3/sect0080.html&quot; rel=&quot;noreferrer&quot;&gt;Q-Chem&lt;/a&gt;, &lt;a href=&quot;http://slater.chemie.uni-mainz.de/cfour/index.php?n=Main.ListOfKeywordsInAlphabeticalOrder&quot; rel=&quot;noreferrer&quot;&gt;CFOUR&lt;/a&gt;, &lt;a href=&quot;https://www.mrcc.hu/MRCC/manual/pdf/manual.pdf&quot; rel=&quot;noreferrer&quot;&gt;MRCC&lt;/a&gt;, etc.&lt;/p&gt;&#xA;&lt;p&gt;In 1984, Csaszar and Pulay published a paper titled &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022286084871987&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Geometry optimization by direct inversion in the iterative subspace&amp;quot;&lt;/a&gt;, which has now known as &amp;quot;Geometry DIIS&amp;quot; or &amp;quot;GDIIS&amp;quot;. The original paper is surprisingly simple, being only 4 pages (including all references!) of easy-to-follow steps, &lt;strong&gt;all of which I will summarize here, in the same notation as in the original paper&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;p&gt;Geometries &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}_i$&lt;/span&gt; generated in the first &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; cycles (each labeled by the index &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;) are used to generate an improved geometry for the &lt;span class=&quot;math-container&quot;&gt;$(m+1)^{\textrm{th}}$&lt;/span&gt; cycle, in the following way:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\mathbf{x}_{m+1} = \sum_{i=1}^m c_i \mathbf{x}_i - \mathbf{H}^{-1}\left(\sum_{i=1}^m c_i\mathbf{g}_{i} &#xA;  \right),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{g}_i$&lt;/span&gt; is the gradient vector at iteration &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{H}$&lt;/span&gt; is the Hessian matrix or an approximation to it, and the &lt;span class=&quot;math-container&quot;&gt;$c_i$&lt;/span&gt; coefficients are obtained by simple linear algebra:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix} &#xA;  \langle \mathbf{e}_1 | \mathbf{e}_1\rangle  &amp;amp; \cdots    &amp;amp; \langle \mathbf{e}_1 | \mathbf{e}_m\rangle &amp;amp; 1\\ &#xA;  \vdots  &amp;amp; \ddots    &amp;amp; \vdots  &amp;amp; \vdots\\&#xA;  \langle \mathbf{e}_m | \mathbf{e}_1\rangle  &amp;amp; \cdots    &amp;amp; \langle \mathbf{e}_m | \mathbf{e}_m\rangle &amp;amp; 1\\ &#xA;1 &amp;amp; \cdots &amp;amp; 1 &amp;amp; 0\\ &#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;c_1 \\ \vdots \\ c_m \\ -\lambda &#xA;\end{pmatrix} &#xA;= &#xA;\begin{pmatrix}&#xA;0 \\ \vdots \\ 0 \\ -\lambda &#xA;\end{pmatrix},\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; being the Lagrange multiplier and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{e}_i$&lt;/span&gt; being the error between &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}_i$&lt;/span&gt; and the &amp;quot;true&amp;quot; final geometry &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}_f$&lt;/span&gt;, which &lt;em&gt;in the case of a quadratic energy function&lt;/em&gt; can be obtained by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{e}_i = -\mathbf{H}^{-1}\mathbf{g}_i.\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;That's it!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you're interested in more detail I will also say:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;&lt;strong&gt;The reason why we are solving Eq. 2&lt;/strong&gt;&lt;/em&gt; is because we want &lt;span class=&quot;math-container&quot;&gt;$\sum c_i = 1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sum c_i \mathbf{e}_i$&lt;/span&gt;. &lt;/li&gt;&#xA;&lt;li&gt;You can get faster convergence if &lt;span class=&quot;math-container&quot;&gt;$\mathbf{H}$&lt;/span&gt; is updated at each iteration, so we could replace it with &lt;span class=&quot;math-container&quot;&gt;$\mathbf{H}_i$&lt;/span&gt; in all of the above.&lt;/li&gt;&#xA;&lt;li&gt;You don't need to include &lt;em&gt;all&lt;/em&gt; previous &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}_i$&lt;/span&gt;. To save RAM and cost you can choose to use only the last few geometries, or perhaps only the geometries that are within some threshold of the most recent (ideally most accurate) geometry.&lt;/li&gt;&#xA;&lt;li&gt;Although the energy landscape is not &lt;em&gt;exactly&lt;/em&gt; quadratic, every differential function with a minimum has a quadratic approximation near the minimum (e.g. the quadratic Taylor polynomial), so the approximation in Eq. 3 is quite accurate if the geoemtry at the &lt;span class=&quot;math-container&quot;&gt;$i^{\textrm{th}}$&lt;/span&gt;  iteration is close enough to the minimum (it doesn't even have to be very &amp;quot;close&amp;quot; to the minimum, just enough that energy landscape looks quadratic there).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T09:29:01.050" LastActivityDate="2021-03-19T09:29:01.050" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4541" PostTypeId="2" ParentId="4538" CreationDate="2021-03-19T00:35:36.400" Score="24" Body="&lt;h1&gt;OpenMOLCAS&lt;/h1&gt;&#xA;&lt;p&gt;MOLCAS is now in it's 5th decade! The first version was written in the 1980s by the group of &lt;a href=&quot;https://www.molcas.org/roos.html&quot; rel=&quot;noreferrer&quot;&gt;Bjorn Roos&lt;/a&gt;, one of history's giants in quantum chemistry. It can do many of the things most mainstream quantum chemistry packages can do: integrals, Hartree-Fock, DFT, MP2, coupled cluster, geometry optimization, etc., and while it can do &amp;quot;single-reference quantum chemistry&amp;quot; about as well as the other mainstream packages (or in many cases even better, which I'll mention later in this answer!), it has also been very popular in the &amp;quot;multi-reference&amp;quot; community because of its implementations of CASSCF, RASSCF, GASSCF, CASPT2, RASPT2, etc. (in addition to MRCI). The original lead developer of MOLCAS (Bjorn Roos) also happened to be a pioneering force behind the initial development of a lot of those methods in the first place, see the answer here for more information on that: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/421/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt;. Additionally, it can do QM/MM (molecular dynamics with quantum effects included) and supports solvent models like COSMO, so it's not only useful for small molecules but also proteins and other macromolecules.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free, open source, and open development (&lt;a href=&quot;https://gitlab.com/Molcas/OpenMolcas&quot; rel=&quot;noreferrer&quot;&gt;here's the Git page&lt;/a&gt;) since 2017!&lt;/li&gt;&#xA;&lt;li&gt;While free, it has the &amp;quot;quality&amp;quot; of an expensive commercial package like GAUSSIAN, since it was commercial for decades.&lt;/li&gt;&#xA;&lt;li&gt;Big user community, big development community worldwide, decades of history but with lots of work done to keep it modern and up-to-date.&lt;/li&gt;&#xA;&lt;li&gt;Has multiple interfaces to use advanced and modern state-of-the-art methods which have been developed recently and are still being developed, for example you can do:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;FCIQMC (via the interface to NECI)&lt;/li&gt;&#xA;&lt;li&gt;DMRG (via the interfaces to several DMRG codes: Block, QCMaquis, CheMPS2)&lt;/li&gt;&#xA;&lt;li&gt;Uncontracted MRCI, MR-ACPF, MR-AQCC (via the interface to COLUMBUS)&lt;/li&gt;&#xA;&lt;li&gt;Molecular Dynamics with Surface Hopping (via the interface to &lt;a href=&quot;https://sharc-md.org/&quot; rel=&quot;noreferrer&quot;&gt;SHARC&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;There's GUI tools such as &lt;a href=&quot;https://sourceforge.net/projects/luscus/&quot; rel=&quot;noreferrer&quot;&gt;LUSCUS&lt;/a&gt;, &lt;a href=&quot;http://www.uc3.uu.se/research/molgui-a-graphical-user-interface-for-molcas&quot; rel=&quot;noreferrer&quot;&gt;MolGUI&lt;/a&gt;, &lt;a href=&quot;http://www.molcas.org/GV/&quot; rel=&quot;noreferrer&quot;&gt;GV&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Even for basic things like integrals, and geometry optimization&lt;/strong&gt;, which every competing code needs: MOLCAS and OpenMOLCAS have the best-quality software. For example the commercial software MOLPRO (known as one of the fastest and most well-developed programs for electronic structure) uses the &lt;code&gt;SEWARD&lt;/code&gt; routine by Roland Lindh (current lead developer of MOLCAS) which was originally written for MOLCAS, because it might be the fastest code for integrals written, and allows basis sets with angular momentum far higher than most other packages. Likewise, for geometry optimization, MOLCAS has advanced features which were again borrowed in the MOLPRO package.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T15:36:35.230" LastActivityDate="2021-03-19T15:36:35.230" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4542" PostTypeId="1" AcceptedAnswerId="4558" CreationDate="2021-03-19T01:41:30.557" Score="7" ViewCount="275" Body="&lt;p&gt;While studying the variational method in McQuarrie's Quantum Chemistry, I came across the following problem: to relate the difference between an approximation &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and the exact ground-state wave function &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt; with the difference between the approximate energy &lt;span class=&quot;math-container&quot;&gt;$E=\int\phi^* \hat H \phi \, \text{d} \tau$&lt;/span&gt; and the ground-state energy &lt;span class=&quot;math-container&quot;&gt;$E_0=\int\psi_0^* \hat H \psi_0 \, \text{d} \tau$&lt;/span&gt;. For instance, if I know that &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt; differ by at most, say, &lt;span class=&quot;math-container&quot;&gt;$O(\epsilon)$&lt;/span&gt; over all space, can I say that &lt;span class=&quot;math-container&quot;&gt;$E-E_0 \approx O(\epsilon)$&lt;/span&gt;? &lt;/p&gt;&#xA;&lt;p&gt;It is intuitive to think that the better approximation &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; is, the better the energy approximation gets, but I cannot prove this. In Chemistry SE, I was told to look at this &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jchemed.8b00959&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, but it does not quite solve the problem.&lt;/p&gt;&#xA;&lt;p&gt;Without loss of generality, suppose &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt; normalized. By writing &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; as a linear combination of &lt;span class=&quot;math-container&quot;&gt;$\psi_n$&lt;/span&gt;, we get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi=\sum_{n=0}^{\infty} c_n\psi_n,\tag{1}&#xA;$$&lt;/span&gt;&#xA;such that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sum_{n=0}^{\infty} c_n^* c_n=1\tag{2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat H \phi=\sum_{n=0}^{\infty} c_n\hat H\psi_n = \sum_{n=0}^{\infty} c_nE_n\psi_n,\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;hence:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E=\int\phi^* \hat H \phi \, \text{d} \tau=\sum_{n=0}^{\infty} c_n^* c_nE_n\tag{4}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From here, I can easily show that &lt;span class=&quot;math-container&quot;&gt;$E \geq E_0$&lt;/span&gt; (since &lt;span class=&quot;math-container&quot;&gt;$|c_0|^2 =1- \sum_{n=1}^{\infty}|c_n|^2$&lt;/span&gt;), but how can I estimate the difference between the approximate energy and the ground-state energy?&lt;/p&gt;&#xA;" OwnerUserId="2210" LastEditorUserId="5" LastEditDate="2021-03-19T20:06:41.203" LastActivityDate="2021-03-21T03:25:54.910" Title="How is the error in a wavefunction related to the error in energy?" Tags="|quantum-chemistry|quantum-mechanics|from-phys-se|variational-principle|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4543" PostTypeId="2" ParentId="4538" CreationDate="2021-03-19T02:17:31.780" Score="16" Body="&lt;h1&gt;GAMESS&lt;/h1&gt;&#xA;&lt;p&gt;For many researchers, GAMESS is the &amp;quot;natural&amp;quot; substitute for GAUSSIAN. Developed and maintained by the group of prof. Gordon (also a banned GAUSSIAN user, see image below).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Official website: &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/index.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.msg.chem.iastate.edu/gamess/index.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;What is GAMESS:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;GAMESS is a program for ab initio molecular quantum chemistry. Briefly, GAMESS can compute SCF wavefunctions ranging from RHF, ROHF, UHF, GVB, and MCSCF. Correlation corrections to these SCF wavefunctions include Configuration Interaction, second order perturbation Theory, and Coupled-Cluster approaches, as well as the Density Functional Theory approximation. Excited states can be computed by CI, EOM, or TD-DFT procedures. Nuclear gradients are available, for automatic geometry optimization, transition state searches, or reaction path following.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;What can GAMESS does?&#xA;(full list of capabilities &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/GAMESS_Manual/docs-intro.txt&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculates RHF, UHF, ROHF, GVB, or MCSCF self-consistent field molecular wavefunctions.&lt;/li&gt;&#xA;&lt;li&gt;Calculates the electron correlation energy correction for these SCF wavefunctions using a) Density Functional Theory (DFT), b) Valence Bond Theory (VB) c) Configuration Interaction (CI), c) Many Body Perturbation Theory (MP2), e) coupled-cluster (CC) or Equation of Motion CC (EOM-CC) methodologies. f) for MCSCF, generates R12 basis set corrections by an interface to the MPQC package.&lt;/li&gt;&#xA;&lt;li&gt;Calculates semi-empirical MNDO, AM1, or PM3 models using RHF, UHF, ROHF, or GVB wavefunctions.&lt;/li&gt;&#xA;&lt;li&gt;Computes the energy hessian, and thus normal modes, vibrational frequencies, and IR intensities.  Raman activities are a follow-up option.&lt;/li&gt;&#xA;&lt;li&gt;Computes excited state energies, wavefunctions, and transition dipole moments at various levels.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;License agreement: &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/License_Agreement.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.msg.chem.iastate.edu/gamess/License_Agreement.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It has versions for Linux (ARM and x86_64 processors), MacOS X, and Windows among others.&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/wn3wr.png&quot; height=&quot;310&quot;&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-03-19T03:20:45.690" LastActivityDate="2021-03-19T03:20:45.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4544" PostTypeId="2" ParentId="4491" CreationDate="2021-03-19T07:06:18.337" Score="10" Body="&lt;h2&gt;EDTSurf&lt;/h2&gt;&#xA;&lt;p&gt;EDTSurf[1] is a common and reasonably well regarded approach. The source code is available at &lt;a href=&quot;https://zhanglab.ccmb.med.umich.edu/EDTSurf/&quot; rel=&quot;noreferrer&quot;&gt;https://zhanglab.ccmb.med.umich.edu/EDTSurf/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tested the mac version and it worked with the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./EDTSurf_mac -i kras.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which outputs &lt;code&gt;kras.ply&lt;/code&gt;. A slight hiccup is the website describes different command line arguments - but the default is the SES. You'll see they have windows and linux versions, too.&lt;/p&gt;&#xA;&lt;p&gt;Assuming you're comfortable with python, you could then visualize the output with Open3D:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import open3d as o3d&#xA;mesh = o3d.io.read_triangle_mesh(&amp;quot;./kras.ply&amp;quot;)&#xA;o3d.visualization.draw_geometries([mesh])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, for volume. Volume of the SES is difficult to calculate exactly, but the volume of a mesh is trivial to calculate. Open3D has a &lt;code&gt;get_volume&lt;/code&gt; method:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mesh.get_volume()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;unfortunately that froze my jupyter notebook every time - you may have better luck with a fresh install.&lt;/p&gt;&#xA;&lt;p&gt;But the following will also work:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;verts = np.array(mesh.vertices)&#xA;faces = np.array(mesh.triangles)&#xA;&#xA;def signed_vol_of_triangle(p1, p2, p3):&#xA;    v321 = p3[0]*p2[1]*p1[2]&#xA;    v231 = p2[0]*p3[1]*p1[2]&#xA;    v312 = p3[0]*p1[1]*p2[2]&#xA;    v132 = p1[0]*p3[1]*p2[2]&#xA;    v213 = p2[0]*p1[1]*p3[2]&#xA;    v123 = p1[0]*p2[1]*p3[2]&#xA;    return (1 / 6)*(-v321 + v231 + v312 - v132 - v213 + v123)&#xA;&#xA;&#xA;def make_vol(pts):&#xA;    return signed_vol_of_triangle(pts[0], pts[1], pts[2])&#xA;&#xA;print(sum([make_vol(v) for v in verts[faces]]))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In short, this loops through each triangle in the mesh and calculates the signed volume of the triangular prism with the fourth point at the origin. The theory behind this is in [2], and I used the implementation in this SO answer which you might want to also consult: &lt;a href=&quot;https://stackoverflow.com/a/1568551/3089865&quot;&gt;https://stackoverflow.com/a/1568551/3089865&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;While I haven't rigorously tested that volume-calculating approach for correctness, it returns &lt;code&gt;21058.959617488006&lt;/code&gt; angstrom cubed, which seems reasonable to me (~21 nm^3) given KRAS fits in a ~4x3x3nm box.&lt;/p&gt;&#xA;&lt;p&gt;[1] Xu, Dong, Hua Li, and Yang Zhang. &amp;quot;Protein depth calculation and the use for improving accuracy of protein fold recognition.&amp;quot; Journal of Computational Biology 20.10 (2013): 805-816.&lt;/p&gt;&#xA;&lt;p&gt;[2]Zhang, Cha, and Tsuhan Chen. &amp;quot;Efficient feature extraction for 2D/3D objects in mesh representation.&amp;quot; Proceedings 2001 International Conference on Image Processing (Cat. No. 01CH37205). Vol. 3. IEEE, 2001.&lt;/p&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="1609" LastEditDate="2021-03-19T16:20:10.800" LastActivityDate="2021-03-19T16:20:10.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4545" PostTypeId="1" AcceptedAnswerId="4551" CreationDate="2021-03-19T08:44:44.013" Score="8" ViewCount="485" Body="&lt;p&gt;Let's consider an example of a &lt;code&gt;3x3x1 supercell of WS2 monolayer&lt;/code&gt; which has 9 &lt;strong&gt;W&lt;/strong&gt; atoms. If we substitute two of them with 2 dopants, the concentration will be 2/9 which equals approximately 22%. Will this still be called doping? Is it OK to go for it?. If no, what is the maximum concentration allowed for doping?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-03-19T12:58:31.993" LastActivityDate="2021-03-19T13:12:46.287" Title="What is the maximum allowed doping concentration?" Tags="|density-functional-theory|vasp|doping|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4546" PostTypeId="2" ParentId="4527" CreationDate="2021-03-19T09:43:36.260" Score="5" Body="&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=C6X9Ry02mPU&quot; rel=&quot;noreferrer&quot;&gt;Here is a short video tutorial&lt;/a&gt; to explain the following points about FEM:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Why study FEM&lt;/li&gt;&#xA;&lt;li&gt;Engineering systems and FEM&lt;/li&gt;&#xA;&lt;li&gt;What is FEM?&lt;/li&gt;&#xA;&lt;li&gt;Layman's explanation&lt;/li&gt;&#xA;&lt;li&gt;Mathematical treatment&lt;/li&gt;&#xA;&lt;li&gt;The power of FEM&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-19T09:43:36.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4547" PostTypeId="2" ParentId="4392" CreationDate="2021-03-19T10:15:42.850" Score="1" Body="&lt;p&gt;In fact, in some situations, if you are chasing &amp;quot;chemical accuracy&amp;quot; (1 kcal/mol &lt;span class=&quot;math-container&quot;&gt;$\approx$&lt;/span&gt; 40 meV/atom) you do need total energy calculation beyond DFT. For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Total energy differences with ”chemical accuracy”: Atomization, formation energies, reaction barriers, etc.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Van der Waals interactions.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Bandstructure of metals and largish gap systems, and some problematic cases&#xA;in-between.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To obtain the total energy beyond DFT, you usually need to consider the total energy at the RPA level. The following screencast is summarized from this paper: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.056401&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Harl and G. Kresse, PRL 103, 056401 (2009)&lt;/a&gt;, from which you can see the RPA total energy calculations are more in good agreement with the experimental data than the PBE total energy calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1l5qH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1l5qH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For more information, you can take a look at &lt;a href=&quot;https://www.nersc.gov/assets/Uploads/VASP-Webinar-RPA.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this slide.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-19T10:15:42.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4548" PostTypeId="2" ParentId="4435" CreationDate="2021-03-19T10:38:34.510" Score="4" Body="&lt;p&gt;In my opinion, there are no new drug molecules totally designed by computer. These designed drug molecules with CADD must be tested with many experiments.&lt;/p&gt;&#xA;&lt;p&gt;Here is a review paper about the current and future of CADD: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B978012816125800002X&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/B978012816125800002X&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And take a look at Wikipedia: &lt;a href=&quot;https://en.wikipedia.org/wiki/Drug_design&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Drug_design&lt;/a&gt;. There are many cases in which CADD helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-19T10:45:40.120" LastActivityDate="2021-03-19T10:45:40.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4549" PostTypeId="2" ParentId="4538" CreationDate="2021-03-19T11:58:01.210" Score="17" Body="&lt;h1&gt;Psi4&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt; is a &lt;a href=&quot;https://github.com/psi4/psi4/&quot; rel=&quot;noreferrer&quot;&gt;fully open-source&lt;/a&gt; quantum chemistry package that is gaining a lot of interest in my community (computational) combustion chemistry.&#xA;Here is the &lt;a href=&quot;https://psicode.org/psi4manual/1.3.2/index.html&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt; for the latest release: it has most, if not all, of the theoretical methods (HF, DFT, CC,...) and also lots of interfaces and integrates into C++ and Python (sadly no Fortran).&lt;/p&gt;&#xA;&lt;p&gt;The bonus on it being open-source is that it eliminates licensing headaches while also making it far easier to interact with the developers (or make our own contributions) and integrate it into other toolchains, e.g. running Psi4 automatically (integration in-progress into &lt;a href=&quot;https://reactionmechanismgenerator.github.io/ARC/index.html&quot; rel=&quot;noreferrer&quot;&gt;ARC&lt;/a&gt;) in the context of &lt;a href=&quot;https://rmg.mit.edu/&quot; rel=&quot;noreferrer&quot;&gt;automatically generating mechanisms&lt;/a&gt; (&lt;a href=&quot;https://dana.net.technion.ac.il/software/&quot; rel=&quot;noreferrer&quot;&gt;overview&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="2228" LastActivityDate="2021-03-19T11:58:01.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4550" PostTypeId="2" ParentId="4545" CreationDate="2021-03-19T12:44:45.483" Score="7" Body="&lt;p&gt;Let me start with this, I have a FCC unit cell with one light impurity at interstitial. Is it enough for solution energy of impurity or I have to take larger cell (2x2x2). If I am taking 1 periodic unit cell then concentration is 20%, if later case case then it is 3.03% .First thing we need to consider whether interstitials are interacting with each other or not. Interaction may occur from periodic boundary condition or within same simulation cell. you can verify this by checking your solution energy in different size simulation cell.Basically if your solution energy is not changing means individual doping are independent and not affecting already present defect(interstitial). Other way to check this is to analyze PDOS, and it is easy to notice that in case of interaction between dopants peak broadening or shifting occurs.&#xA;Now you consider whether your doping is changing system characteristics or not will put a limit on solubility/concentration. Even we are doing computer simulation and we have multiple option for a dopant to be inside system doesn't mean that basic characteristics of host material or system should change drastically, if it happen then we are analyzing some other system. Apart from this kindly check your mechanical and dynamical stability of system if possible.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-03-19T12:44:45.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4551" PostTypeId="2" ParentId="4545" CreationDate="2021-03-19T13:12:46.287" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What is the maximum allowed doping concentration?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It really depends on what you want to study. The doping concentration can be changed from 0 to &lt;span class=&quot;math-container&quot;&gt;$100\%$&lt;/span&gt;. Taking the primitive monolayer of MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; as an example, if you substitute the &lt;strong&gt;S&lt;/strong&gt; atom with &lt;strong&gt;Se&lt;/strong&gt;, then you obtain the MoSSe alloy (alloy engineering method in the field of 2D materials), which can be viewed as &lt;span class=&quot;math-container&quot;&gt;$50\%$&lt;/span&gt; doping concentration. Furthermore, if you substitute &lt;strong&gt;Mo&lt;/strong&gt; with &lt;strong&gt;W&lt;/strong&gt; then you actually realize the &lt;span class=&quot;math-container&quot;&gt;$100\%$&lt;/span&gt; doping concentration. But that makes no sense, you just calculate WS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; monolayer. For other doping concentrations, you may need to build a supercell. Importantly, how to build the supercell is dependent on what you want to study.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-03-19T13:12:46.287" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4552" PostTypeId="1" CreationDate="2021-03-19T15:32:58.287" Score="6" ViewCount="161" Body="&lt;p&gt;The charge density (electron distribution) is calculated self-consistently by employing DFT, so a question arises here: &lt;strong&gt;where are the atoms located,  or are their positions fixed?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-03-19T15:43:15.997" LastActivityDate="2021-03-19T16:58:25.737" Title="Where are the atoms located in a charge density calculation using DFT?" Tags="|density-functional-theory|charge-density|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4553" PostTypeId="5" CreationDate="2021-03-19T15:43:38.437" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T15:43:38.437" LastActivityDate="2021-03-19T15:43:38.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4554" PostTypeId="4" CreationDate="2021-03-19T15:43:38.437" Score="0" Body="Questions about charge density." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T15:43:38.437" LastActivityDate="2021-03-19T15:43:38.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4555" PostTypeId="1" CreationDate="2021-03-19T15:57:48.257" Score="13" ViewCount="2114" Body="&lt;p&gt;I have plotted the density of states using GGA-PBE exchange correlation functional for magnesium silcide but I really do not know what the equations involved are in this process, and how they relate to DFT?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/90qds.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/90qds.png&quot; alt=&quot;Density of States Plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="6055" LastEditDate="2023-03-06T12:17:09.027" LastActivityDate="2023-03-06T12:17:09.027" Title="What does a density of states (DOS) plot show?" Tags="|density-functional-theory|solid-state-physics|density-of-states|terminology|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4556" PostTypeId="2" ParentId="4552" CreationDate="2021-03-19T16:58:25.737" Score="3" Body="&lt;p&gt;The atom is divided in three parts: the nuclei, the core electrons and the valence electrons. Each one is treated in a different way.&lt;/p&gt;&#xA;&lt;p&gt;You can do two type of calculation when talking about the system geometry: single-point calculation and geometry optimization.&lt;/p&gt;&#xA;&lt;p&gt;In the case of single-point, the nuclei positions are keep fixed and only the electrons are allowed to move.&lt;/p&gt;&#xA;&lt;p&gt;In the case of geometry optimization, the nuclei positions and the electrons are all allowed to move. A description about how the geometry of the system is optimized is described &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4530/24&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;where are the atoms located, or are their positions fixed?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As mentioned above, the atoms are divided (nuclei+electrons): the nuclei are keep fixed (single-point) or allowed to move (geometry optimization), depending of your needs. The electrons are always moving, delocalized.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-03-19T16:58:25.737" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4557" PostTypeId="2" ParentId="4555" CreationDate="2021-03-19T17:07:00.420" Score="4" Body="&lt;p&gt;From the &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_of_states&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wiki&lt;/a&gt; page, the density of states (DOS):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In solid state physics and condensed matter physics, the density of states (DOS) of a system describes the proportion of states that are to be occupied by the system at each energy. The density of states is defined as &lt;span class=&quot;math-container&quot;&gt;$D(E) = N(E)/V$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$N(E)\delta E$&lt;/span&gt; is the number of states in the system of volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; whose energies lie in the range from &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E + \delta E$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The DOS is not directly linked to DFT, it is a solid state concept about how the electrons are energetically distributed. The DFT is the method used to calculate it (there are other method that can be used).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-03-19T21:34:58.393" LastActivityDate="2021-03-19T21:34:58.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4558" PostTypeId="2" ParentId="4542" CreationDate="2021-03-19T19:33:48.563" Score="6" Body="&lt;p&gt;You can, in fact, do better as the answer to &lt;a href=&quot;https://physics.stackexchange.com/q/620877/49107&quot;&gt;this Physics.SE question of yours&lt;/a&gt; indicates, assuming you're after an asymptotic expression. I haven't read the book you mention, but if you're familiar with the bra-ket notation, I recommend the discussion of variational methods in Sakurai's &lt;em&gt;Modern Quantum Mechanics&lt;/em&gt;. The following will be based on Sakurai's approach, but adapted  to address the questions I think you're asking.&lt;/p&gt;&#xA;&lt;p&gt;Let &lt;span class=&quot;math-container&quot;&gt;$\{|\psi_n\rangle\}$&lt;/span&gt; be an orthonormal basis, where &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt; is the true ground state. We consider a trial wave function (ket) &lt;span class=&quot;math-container&quot;&gt;$|\phi\rangle=|\psi_0\rangle + |\delta \phi\rangle$&lt;/span&gt;, and express it in the energy eigenstate basis,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\phi\rangle=\sum_{n=0}^{N} c_n|\psi_n\rangle \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\sum_{n=0}^{N} |c_n|^2=1$&lt;/span&gt;, such that &lt;span class=&quot;math-container&quot;&gt;$\delta \phi= \sum_{n=1}^N c_n |\psi_n\rangle$&lt;/span&gt;. Here &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the dimension of the Hilbert space. You may take &lt;span class=&quot;math-container&quot;&gt;$N\rightarrow \infty$&lt;/span&gt; as in your question, but a finite dimension allows a clearer discussion of the difference between the wave functions.&lt;/p&gt;&#xA;&lt;p&gt;The energy in the trial wave function is (since &lt;span class=&quot;math-container&quot;&gt;$|\phi\rangle$&lt;/span&gt; is normalized)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}\tag{2}&#xA;E &amp;amp;= \langle \phi | \hat{H} | \phi\rangle = \left( \langle \psi_0| + \langle \delta\phi| \right) \hat{H} \left( |\psi_0\rangle + | \delta \phi\rangle\right)\\\tag{3}&#xA;&amp;amp;= \langle \psi_0| \hat{H} |\psi_0\rangle + \langle \psi_0| \hat{H} | \delta \phi\rangle + \langle \delta\phi|  \hat{H}  |\psi_0\rangle + \langle \delta\phi| \hat{H} | \delta \phi\rangle\\&#xA;&amp;amp;= E_0 + \langle \delta\phi| \hat{H} | \delta \phi\rangle, \tag{4}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;where we used that &lt;span class=&quot;math-container&quot;&gt;$|\delta \phi\rangle$&lt;/span&gt; is orthogonal to &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt;.  Thus the difference between the approximate and exact ground state energies can be written&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\delta E = E -E_0 = \langle \delta\phi| \hat{H} | \delta \phi\rangle = \sum_{n=1}^N E_n |c_n|^2. \tag{5}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, if we think about &lt;span class=&quot;math-container&quot;&gt;$|\phi\rangle$&lt;/span&gt; as a (long?) vector, where each element corresponds to &lt;span class=&quot;math-container&quot;&gt;$c_n$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$n=0,1,2,\dots$&lt;/span&gt;), the difference between &lt;span class=&quot;math-container&quot;&gt;$|\psi\rangle$&lt;/span&gt; and the exact ground state can be written&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\delta\phi\rangle = |\phi\rangle - |\psi_0\rangle = (0, c_1, c_2, c_3, \dots, c_N). \tag{6}&#xA;$$&lt;/span&gt;&#xA;You now have to decide how you want to define the meaning of &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt; differ by at most &lt;span class=&quot;math-container&quot;&gt;$O(\epsilon)$&lt;/span&gt;&amp;quot;. (There are many distance metrics for Hilbert spaces.) One simple way is to directly say that the largest element (&lt;span class=&quot;math-container&quot;&gt;$c_{n_0}$&lt;/span&gt;, say) of the &lt;span class=&quot;math-container&quot;&gt;$|\delta \phi\rangle$&lt;/span&gt; vector is &lt;span class=&quot;math-container&quot;&gt;$O(\epsilon)$&lt;/span&gt;. Alternatively, we can require&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sqrt{\langle \delta \phi | \delta \phi \rangle} = \sqrt{\sum_{n=1}^N |c_n|^2} = \sqrt{1-|c_0|^2} = \mathcal{O} (\epsilon), \tag{7}&#xA;$$&lt;/span&gt;&#xA;which is achieved if &lt;span class=&quot;math-container&quot;&gt;$|c_n|\lesssim \mathcal{O}(\epsilon)\quad \forall n&amp;gt;0$&lt;/span&gt;. In both cases we find&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\delta E = \sum_{n=1}^N E_n |c_n|^2 \lesssim \sum_{n=1}^N E_n \mathcal{O}\left(\epsilon^2\right). \tag{8}&#xA;$$&lt;/span&gt;&#xA;If the spectrum of &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; is bounded (i.e. each &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt; is finite), &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt; can be treated as a constant that is unimportant for asymptotic properties, yielding&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\delta E \sim \sum_{n=1}^N \mathcal{O}\left(\epsilon^2\right) = \mathcal{O}\left(\epsilon^2\right). \tag{9}&#xA;$$&lt;/span&gt;&#xA;Thus, an error &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(\epsilon)$&lt;/span&gt; in the trial wave function leads to an energy error that scales as &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}(\epsilon^2)$&lt;/span&gt;. Note, however, that this expression is not itself useful to estimate the &lt;strong&gt;magnitude&lt;/strong&gt; of the energy difference, which depends non-universally on &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt;. A trivial way to see this is to simply multiply &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; by some large number, which will affect the energy difference in Eq. (5), but not the difference between states in Eq. (6). Neither will it change the error in Eq. (9). If you need the magnitude of &lt;span class=&quot;math-container&quot;&gt;$\delta E$&lt;/span&gt;, you'll want to know &lt;span class=&quot;math-container&quot;&gt;$E_0$&lt;/span&gt; independently, e.g. from experiment or some other theoretical technique (but if you have another theoretical technique, using a variational one might be unnecessary). The real utility of the variational method comes from the fact that you can just guess trial wave functions until you're tired, pick the one with lowest energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, and be sure that it's the best approximation of &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt; that you've tried so far.&lt;/p&gt;&#xA;&lt;p&gt;To avoid confusion, perhaps it's worth mentioning that the overall units of Eqs. (8,9) are the same. In (9) I've absorbed the units of energy into the &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}$&lt;/span&gt;, whereas &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}$&lt;/span&gt; is dimensionless in (8). This is common practice, since &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}$&lt;/span&gt; is used as a shorthand.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2021-03-19T20:05:39.377" LastActivityDate="2021-03-19T20:05:39.377" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4559" PostTypeId="1" AcceptedAnswerId="4564" CreationDate="2021-03-19T20:28:03.730" Score="30" ViewCount="1279" Body="&lt;p&gt;Perhaps a stupid question, but.. &lt;strong&gt;what is matter modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've never heard of it, and a google search just returns news articles about this site that seem to assume you already know what it is.  I can't even find a Wikipedia article!&lt;/p&gt;&#xA;" OwnerUserId="2234" LastEditorUserId="1218" LastEditDate="2021-03-20T11:01:24.227" LastActivityDate="2021-03-20T11:01:24.227" Title="What is matter modeling?" Tags="|terminology|history|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4560" PostTypeId="2" ParentId="4524" CreationDate="2021-03-19T22:54:55.047" Score="4" Body="&lt;p&gt;I think your problem was solved in &lt;a href=&quot;https://github.com/band-unfolding/bandup/pull/7&quot; rel=&quot;nofollow noreferrer&quot;&gt;this pull request&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It is not merged yet because it breaks backward compatibility with python3.6 and lower. But if you use 3.7 or higher, you may try to install from that PR, and it should work. If it does not, please report the problem in the comments to that pull request.&lt;/p&gt;&#xA;&lt;p&gt;You can also ask questions related to the Bandup code on Github in the Issues and in the Comments on Pull Requests in the corresponding repository. That place is now actively monitored by the developers (including me) and other users.&lt;/p&gt;&#xA;" OwnerUserId="2235" LastEditorUserId="5" LastEditDate="2021-03-19T23:24:09.403" LastActivityDate="2021-03-19T23:24:09.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4561" PostTypeId="5" CreationDate="2021-03-19T23:30:35.540" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;Website: &lt;a href=&quot;https://www.ifm.liu.se/theomod/compphys/band-unfolding/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ifm.liu.se/theomod/compphys/band-unfolding/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;GitHub: &lt;a href=&quot;https://github.com/band-unfolding/bandup&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/band-unfolding/bandup&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T23:30:35.540" LastActivityDate="2021-03-19T23:30:35.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4562" PostTypeId="4" CreationDate="2021-03-19T23:30:35.540" Score="0" Body="Questions about BandUP, the band unfolding software for plane-wave based calculations." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-03-19T23:30:35.540" LastActivityDate="2021-03-19T23:30:35.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4563" PostTypeId="2" ParentId="4559" CreationDate="2021-03-19T23:46:16.603" Score="11" Body="&lt;p&gt;First of all, we assume the matter is constituted by nuclei and electrons, as illustrated by the following figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/keOSX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/keOSX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Mathematically, the matter is mapped into the following Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=T_e + T_n + V_{ee} + V_{nn} + V_{en} \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is called the &lt;strong&gt;standard model&lt;/strong&gt; of condensed matter physics. In principle, all information (ground state/excited state/nonequilibrium state properties) about the matter encoded in this Hamiltonian can be extracted from it just by solving the following Schrodinger equation (SE):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H \psi =E \psi \tag{2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In general, you can say matter modeling is to solve the SE of matter to capture the relative properties. Unfortunately, Eq.(2) is a notorious quantum many-body problem and hardly solvable. Therefore, different approximation schemes have been developed.&lt;/p&gt;&#xA;&lt;p&gt;Based on the mass difference between nucleon and electron, Born and Oppenheimer introduce the BO approximation to separate the nucleon degree of freedom (DOF) and electron DOF:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Nucleon DOF:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_n=T_{n}+V_{nn} \tag{3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Electron DOF:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H_e=T_{e} + V_{ee} + V_{en} \tag{4} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Eq.(3) for nucleon DOF is usually treated classically with the total force are calculated by DFT:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Molecular dynamics method;&lt;/li&gt;&#xA;&lt;li&gt;Density functional perturbation theory;&lt;/li&gt;&#xA;&lt;li&gt;.....&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Eq.(4) for electron DOF is solved by many first-principles schemes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Density Functional Theory (ground-state properties)&lt;/li&gt;&#xA;&lt;li&gt;GW method (excited state properties)&lt;/li&gt;&#xA;&lt;li&gt;BSE (excited state properties)&lt;/li&gt;&#xA;&lt;li&gt;DFT+NEGF (nonequilibrium properties)&lt;/li&gt;&#xA;&lt;li&gt;...&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These are what matter modeling is doing in practice! In short, matter modeling means solving the SE with different approximation schemes to decode the information contained in matter Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-20T04:40:46.730" LastActivityDate="2021-03-20T04:40:46.730" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4564" PostTypeId="2" ParentId="4559" CreationDate="2021-03-20T00:26:57.827" Score="26" Body="&lt;h3&gt;&amp;quot;Matter modeling&amp;quot; is a term that was coined by Stack Exchangers!&lt;/h3&gt;&#xA;&lt;p&gt;That's why the words &amp;quot;matter&amp;quot; and &amp;quot;modeling&amp;quot; next to each other, don't seem to exist in &lt;em&gt;&lt;strong&gt;any&lt;/strong&gt;&lt;/em&gt; of the results in a Google search of &amp;quot;Matter Modeling&amp;quot;, apart from this Stack Exchange site, Adam Iaizzi's blog post about this SE site, and &lt;em&gt;maybe&lt;/em&gt; our community's &lt;a href=&quot;https://www.facebook.com/search/top?q=Matter%20Modeling%20Stack%20Exchange&quot; rel=&quot;noreferrer&quot;&gt;Facebook group&lt;/a&gt; but for some reason the last one didn't show up in my Google search just now.&lt;/p&gt;&#xA;&lt;p&gt;Basically, people trying to model physical matter (materials, molecules, atoms, nuclei, etc.) have so much in common. All of this type of matter is described by the Schrödinger equation, or if modeling on a much more macroscopic scale: by Newton's second law. So we are all basically &lt;em&gt;&lt;strong&gt;writing&lt;/strong&gt;&lt;/em&gt; or &lt;em&gt;&lt;strong&gt;running&lt;/strong&gt;&lt;/em&gt;  computer programs to solve Schrödinger equations (or Kohn-Sham equations for those using the mathematically equivalent &lt;a href=&quot;/questions/tagged/density-functional-theory&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;density-functional-theory&amp;#39;&quot; rel=&quot;tag&quot;&gt;density-functional-theory&lt;/a&gt;) or Newton's equations to study some phenomena about matter. Some of us might not be coding or computing, but instead are deriving equations (mathematics) or studying the computational complexity of an algorithm (theoretical computer science) for the modeling of matter (see &lt;a href=&quot;/questions/tagged/mathematical-modeling&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;mathematical-modeling&amp;#39;&quot; rel=&quot;tag&quot;&gt;mathematical-modeling&lt;/a&gt; and &lt;a href=&quot;/questions/tagged/algorithms&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;algorithms&amp;#39;&quot; rel=&quot;tag&quot;&gt;algorithms&lt;/a&gt;). Some might be using &lt;a href=&quot;/questions/tagged/machine-learning&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;machine-learning&amp;#39;&quot; rel=&quot;tag&quot;&gt;machine-learning&lt;/a&gt;, or maybe even doing &lt;a href=&quot;/questions/tagged/experimental&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;experimental&amp;#39;&quot; rel=&quot;tag&quot;&gt;experimental&lt;/a&gt; research but need help in analyzing or interpreting the data, or a modeler might be comparing theory to experiment and may have an &lt;a href=&quot;/questions/tagged/experimental&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;experimental&amp;#39;&quot; rel=&quot;tag&quot;&gt;experimental&lt;/a&gt; question for that reason.&lt;/p&gt;&#xA;&lt;p&gt;There's a lot of &lt;a href=&quot;/questions/tagged/software&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;software&amp;#39;&quot; rel=&quot;tag&quot;&gt;software&lt;/a&gt; we use (dozens and dozens of software packages), and many of them had their own independent forums requiring users to register a username and password for each one, and sometimes a question on the &lt;a href=&quot;/questions/tagged/vasp&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;vasp&amp;#39;&quot; rel=&quot;tag&quot;&gt;vasp&lt;/a&gt; forum could better be answered by a &lt;a href=&quot;/questions/tagged/quantum-espresso&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;quantum-espresso&amp;#39;&quot; rel=&quot;tag&quot;&gt;quantum-espresso&lt;/a&gt; user because some software can do certain types of calculations which others don't. Physics.SE, Chemistry.SE, QuantumComputing.SE, ComputationalScience.SE, ComputerScience.SE, TheoreticalCS.SE, ArtificialIntelligence.SE, Statistics.SE, Engineering.SE, Mathematics.SE, MathOverflow and others had matter modeling questions &lt;em&gt;&lt;strong&gt;sprinkled&lt;/strong&gt;&lt;/em&gt; across them, but it was spread out and never all in one place. We also do a lot of &lt;a href=&quot;/questions/tagged/high-performance-computing&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;high-performance-computing&amp;#39;&quot; rel=&quot;tag&quot;&gt;high-performance-computing&lt;/a&gt; which is on-topic but very &amp;quot;niche&amp;quot; on AskUbuntu, StackOverflow, Linux&amp;amp;Unix, ServerFault, etc. (see this deleted &lt;a href=&quot;https://meta.stackexchange.com/q/327714/391772&quot;&gt;Meta SE question&lt;/a&gt; if you have enough reputation there!). This was discussed on &lt;a href=&quot;https://area51.meta.stackexchange.com/q/29831/190792&quot;&gt;Area51&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The name of our site began as &amp;quot;Materials Modeling SE&amp;quot;, which &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/110/5&quot;&gt;does&lt;/a&gt; have a Wikipedia page and a &lt;em&gt;little&lt;/em&gt; bit of information available online, and while you can argue (for example) that atoms are made of &amp;quot;sub-atomic material&amp;quot;, the word material often refers to solid  materials (see our tag &lt;a href=&quot;/questions/tagged/solid-state-physics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;solid-state-physics&amp;#39;&quot; rel=&quot;tag&quot;&gt;solid-state-physics&lt;/a&gt;) which is a bit too specific to describe this community.&lt;/p&gt;&#xA;&lt;p&gt;We discussed what we should call ourselves, twice on Area51:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://area51.meta.stackexchange.com/q/31121/190792&quot;&gt;Discussion about the name for Materials/Matter Modeling&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://area51.meta.stackexchange.com/q/31085/190792&quot;&gt;What should this site be called?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and then again when the site entered Private Beta:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.meta.stackexchange.com/q/96/5&quot;&gt;&lt;em&gt;&lt;strong&gt;Better late than too late: Could a single word substitution in our name, be at least considered?&lt;/strong&gt;&lt;/em&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Did we really just make up a new term?&lt;/h3&gt;&#xA;&lt;p&gt;Even outside of Stack Exchange, pre-cursors started to pop up around the world, as &lt;a href=&quot;https://mattermodeling.meta.stackexchange.com/a/102/5&quot;&gt;this answer&lt;/a&gt; points out that a relatively new &lt;em&gt;&lt;strong&gt;journal&lt;/strong&gt;&lt;/em&gt; called &lt;a href=&quot;https://www.cell.com/matter/home&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Matter&amp;quot;&lt;/a&gt; was launched as a sister journal to &amp;quot;Cell&amp;quot; and &amp;quot;Chem&amp;quot;, and Alan Aspuru-Guzik, an always creative and forward-thinking scientist who did computational research for both molecules and solid-state materials, renamed his research group the &lt;a href=&quot;https://www.matter.toronto.edu/&quot; rel=&quot;noreferrer&quot;&gt;Matter Lab&lt;/a&gt; when he moved from Harvard to Toronto, and he took the domain matter.toronto.edu (we also wanted matter.stackexchange.com but spent all our energy on changing &amp;quot;Materials Modeling&amp;quot; to &amp;quot;Matter Modeling&amp;quot; so we postponed that feature request for later!).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-03-20T00:26:57.827" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4565" PostTypeId="2" ParentId="4538" CreationDate="2021-03-20T10:27:27.580" Score="9" Body="&lt;h1&gt;NWChem&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Official website: &lt;a href=&quot;https://nwchemgit.github.io/&quot; rel=&quot;noreferrer&quot;&gt;https://nwchemgit.github.io/&lt;/a&gt; and &lt;a href=&quot;https://www.nwchem-sw.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.nwchem-sw.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;It is &lt;a href=&quot;https://github.com/nwchemgit/nwchem&quot; rel=&quot;noreferrer&quot;&gt;open source&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Description:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NWChem software can handle:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Biomolecules, nanostructures, and solid-state&lt;/li&gt;&#xA;&lt;li&gt;From quantum to classical, and all combinations&lt;/li&gt;&#xA;&lt;li&gt;Ground and excited-states&lt;/li&gt;&#xA;&lt;li&gt;Gaussian basis functions or plane-waves&lt;/li&gt;&#xA;&lt;li&gt;Scaling from one to thousands of processors&lt;/li&gt;&#xA;&lt;li&gt;Properties and relativistic effects&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Brief list of capabilities: (full list &lt;a href=&quot;https://nwchemgit.github.io/Capabilities.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Both Gaussian type and plain wave basis sets.&lt;/li&gt;&#xA;&lt;li&gt;Calculations on periodic systems&lt;/li&gt;&#xA;&lt;li&gt;Energies and analytic gradients for RHF, UHF, ROHF, DFT, R-MP2, U-MP2, CASSCF&lt;/li&gt;&#xA;&lt;li&gt;Analytic second derivatives for RHF, UHF and R-DFT&lt;/li&gt;&#xA;&lt;li&gt;Excited state calculations (CIS, TDHF, TDDFT)&lt;/li&gt;&#xA;&lt;li&gt;Energies with iterative CCSD, CCSDT, CCSDTQ (also EOM-CC) for RHF, UHF and ROHF&lt;/li&gt;&#xA;&lt;li&gt;RI-MP2 for RHF and UHF references&lt;/li&gt;&#xA;&lt;li&gt;Vibrational SCF and DFT for anharmonic corrections&lt;/li&gt;&#xA;&lt;li&gt;Conductor Like Screening Model (COSMO) solvation&lt;/li&gt;&#xA;&lt;li&gt;ONIOM hybrid calculations&lt;/li&gt;&#xA;&lt;li&gt;Molecular dynamics(MD) and hybrid QM/MM calculations&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-03-20T10:27:27.580" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4566" PostTypeId="2" ParentId="4526" CreationDate="2021-03-20T12:11:32.213" Score="4" Body="&lt;p&gt;For x-ray diffraction and Raman spectroscopy data of minerals, you may try &lt;a href=&quot;https://rruff.info/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://rruff.info/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;According to their site, &amp;quot;The RRUFF™ Project is creating a complete set of high quality spectral data from well characterized minerals and is developing the technology to share this information with the world. Our collected data provides a standard for mineralogists, geoscientists, gemologists and the general public for the identification of minerals both on earth and for planetary exploration.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="205" LastActivityDate="2021-03-20T12:11:32.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4567" PostTypeId="1" AcceptedAnswerId="4584" CreationDate="2021-03-20T18:53:13.093" Score="10" ViewCount="692" Body="&lt;p&gt;I have been using RDKit to generate 3D coordinates, cleaning-up the structures using a general-purpose force field as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; (1) Adding hydrogens: AllChem.AddHs&#xA; (2) Compute 3D coordinates: AllChem.EmbedMolecule&#xA; (3) Clean-up with force field: AllChem.MMFFOptimizeMolecule&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;But I would like to take into account different solvents so that the 3D structure more closely resembles in vitro activity. For example, an in vitro screen where small molecules are diluted in (1) DMSO or (2) ethanol or (3) water.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I know that Psi4 can estimate properties in different solvents. But I have been unable to find a python library that generates an actual 3D structure that's optimized for solvents (e.g. a solvent-specific force field that would be applied after the 3D coordinates have been computed as in the RDKit example above).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Any help/suggestions on how to do this, exporting a .mol/.sdf file (preferably using python) would be much appreciated.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2241" LastEditorUserId="5" LastEditDate="2021-03-24T03:04:55.643" LastActivityDate="2021-03-24T09:54:40.830" Title="Computing optimized 3D structures in python that take solvent into account" Tags="|computational-chemistry|python|rdkit|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4570" PostTypeId="1" CreationDate="2021-03-21T14:00:39.120" Score="10" ViewCount="1419" Body="&lt;p&gt;I downloaded the latest version of Avogadro2 (1.91.0), but it appears I can't open a .cif file in this software. Is there a way around this? In an earlier version of Avogadro, I remember being able to open a .cif file.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastActivityDate="2021-03-22T19:01:03.853" Title="How to import a .cif file into Avogadro 2?" Tags="|crystal-structure|crystallography|avogadro|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4571" PostTypeId="1" CreationDate="2021-03-22T05:44:37.417" Score="5" ViewCount="422" Body="&lt;p&gt;I have been attempting for some time to evaluate the binary Diffusion coefficient of argon in a gas mixture with neon. From the literature, this property can be measured using the velocity autocorrelation function as stated from this equation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6CWSm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6CWSm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From my understanding, this variation of the VACF uses the total velocity of the Argon atoms. In other words, the autocorrelation is done on the sum of all-atom velocities rather than evaluating the VACF for each individual atom. But so far I have not been able to compute an appropriate autocorrelation curve.&lt;/p&gt;&#xA;&lt;p&gt;My method thus far has been to compute the sum of velocities for all argon atoms at each timestep and auto-correlate this data using the following algorithm:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eFBPO.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eFBPO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The product of this method has been a quick descending curve, but rather than fluctuating around zero as t increases large fluctuations arise towards the end of the curve.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know if anyone has any resources or information on how to properly calculate this version of the VACF that would be kind to share.&lt;/p&gt;&#xA;&lt;p&gt;Thank You!&lt;/p&gt;&#xA;&lt;p&gt;JG.&lt;/p&gt;&#xA;" OwnerUserId="2244" LastActivityDate="2021-03-24T03:49:23.907" Title="Calculating Velocity autocorrelation function for Binary Diffusion Coefficient" Tags="|molecular-dynamics|lammps|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4572" PostTypeId="2" ParentId="560" CreationDate="2021-03-22T09:08:00.207" Score="7" Body="&lt;h2&gt;GUI4dft - A SIESTA oriented GUI&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/sozykinsa/GUI4dft&quot; rel=&quot;noreferrer&quot;&gt;GUI4dft&lt;/a&gt; is a new  Graphical User Interface for Density Functional Theory  for users of SIESTA. GUI4dft is written in Python language, falls under an MIT license and is a free cross-platform software.  GUI4dft allows the user to work with standard SIESTA files and prepare manuscript-quality figures of the atomic structure and properties such as three-dimensional charge density distributions, DOS, PDOS, and band structure. The program is cross-platform due to the fact that it is written in Python 3 and uses the PyQt5, OpenGL, Scipy, Numpy and Scikit-image  &lt;a href=&quot;https://github.com/sozykinsa/GUI4dft&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; modules available in major operating systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vn9bz.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vn9bz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2021.107843&quot; rel=&quot;noreferrer&quot;&gt;Sozykin, S. A. &amp;quot;GUI4dft—A SIESTA oriented GUI.&amp;quot; Computer Physics Communications 262 (2021): 107843&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastActivityDate="2021-03-22T09:08:00.207" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4573" PostTypeId="1" CreationDate="2021-03-22T11:46:39.853" Score="8" ViewCount="1881" Body="&lt;p&gt;I want to search for a value in the VASP &lt;code&gt;OUTCAR&lt;/code&gt; file i.e the format of the line should be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Volume of Typ   1:     98.5 %&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What command line should I type in &lt;code&gt;OUTCAR&lt;/code&gt; to go for a specific line or word?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-03-24T17:33:01.500" LastActivityDate="2021-04-05T06:13:23.183" Title="How do I search for a particular string in Linux?" Tags="|vasp|high-performance-computing|" AnswerCount="4" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4574" PostTypeId="2" ParentId="4573" CreationDate="2021-03-22T12:33:09.157" Score="15" Body="&lt;p&gt;The &lt;code&gt;OUTCAR&lt;/code&gt; is a text file. Therefore, you can use the &lt;code&gt;grep&lt;/code&gt; command to grab what you want to search for.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Print the current line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep  &amp;quot;key_information_string&amp;quot; OUTCAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Print more lines below the current line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep  &amp;quot;key_information_string&amp;quot; OUTCAR -A n&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Print more lines above the current line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep  &amp;quot;key_information_string&amp;quot; OUTCAR -B n&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; represents the number of lines you want to print, such as 5.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-25T00:08:07.570" LastActivityDate="2021-03-25T00:08:07.570" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4576" PostTypeId="2" ParentId="4487" CreationDate="2021-03-22T16:46:38.213" Score="5" Body="&lt;p&gt;Finally, I just used simulated annealing of NPT ensemble: heated it above glass transition temperature and cooled back down. It equilibrated to the density very close to experimental.&lt;/p&gt;&#xA;&lt;p&gt;Hope my experience will help someone.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;UPD:&lt;/strong&gt; Equilibrating the system at very high pressure (I used 1000 bar) also work fine in difficult cases.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="1432" LastEditDate="2021-04-02T16:56:32.023" LastActivityDate="2021-04-02T16:56:32.023" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4577" PostTypeId="2" ParentId="4570" CreationDate="2021-03-22T19:01:03.853" Score="6" Body="&lt;p&gt;&lt;strong&gt;tldr; Try one of the [nightly builds]&lt;/strong&gt;(&lt;a href=&quot;https://nightly.link/OpenChemistry/avogadrolibs/workflows/build_cmake/master&quot; rel=&quot;noreferrer&quot;&gt;https://nightly.link/OpenChemistry/avogadrolibs/workflows/build_cmake/master&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Avogadro uses Open Babel to read CIF files, and unfortunately, OB versions before v3 would break molecules such that all atoms fit within the unit cell. Typically, most people would rather have a contiguous molecule even if it goes through a unit cell. So for molecular crystals, I'd &lt;em&gt;highly&lt;/em&gt; recommend using Avogadro2 betas.&lt;/p&gt;&#xA;&lt;p&gt;(To be honest, that's what I use everyday - and I'd rather get complaints or bug reports than 1.2, which would be essentially impossible to fix.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ut8Vjm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ut8Vjm.png&quot; alt=&quot;unit cell of aspirin&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, it seems as if binaries weren't built for the 1.93 beta of Avogadro2. (It's marked as beta because it doesn't have all the features from the 1.x series yet.)&lt;/p&gt;&#xA;&lt;p&gt;My goal is to get a 1.94 release out soon, but GitHub has automated builds available through nightly.link:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://nightly.link/OpenChemistry/avogadrolibs/workflows/build_cmake/master/macOS.dmg.zip&quot; rel=&quot;noreferrer&quot;&gt;Mac&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://nightly.link/OpenChemistry/avogadrolibs/workflows/build_cmake/master/Win64.exe.zip&quot; rel=&quot;noreferrer&quot;&gt;Win64&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://nightly.link/OpenChemistry/avogadrolibs/workflows/build_cmake/master/Ubuntu2004.tar.gz.zip&quot; rel=&quot;noreferrer&quot;&gt;Ubuntu 20.04&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-03-22T19:01:03.853" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4578" PostTypeId="2" ParentId="4514" CreationDate="2021-03-23T00:18:01.927" Score="9" Body="&lt;p&gt;Here's an approach calculating it by hand with &lt;code&gt;numpy&lt;/code&gt;. The coordinates are loaded from the trajectory using &lt;code&gt;mdtraj&lt;/code&gt; in python:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;#imports:&#xA;import mdtraj as md&#xA;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;#load trajectory:&#xA;traj = md.load('traj.dcd', top='solvated.pdb')&#xA;##You would write this:&#xA;##traj = md.load_xtc('md.xtc', top='top.gro')&#xA;&#xA;#select oxygen atom indices:&#xA;oxy = traj.top.select('name O')&#xA;&#xA;#calculate masses of all atoms:&#xA;masses = np.array([i.element.mass for i in traj.topology.atoms])&#xA;&#xA;&#xA;#iterate through all frames and save the distances of each atom to the centre of mass:&#xA;d = list()&#xA;for frame in traj.xyz:&#xA;    oxy_coords = frame[oxy]&#xA;    #COM of whole system:&#xA;    centre_of_mass = np.average(frame, axis=0, weights=masses)&#xA;    #COM of just the oxygens:&#xA;    #centre_of_mass = oxy_coords.mean(0)&#xA;    vectors = (oxy_coords - centre_of_mass)&#xA;    distances = np.linalg.norm(vectors, axis=1)&#xA;    d += list(distances)&#xA;&#xA;##Take a histogram:&#xA;counts, lengths = np.histogram(d,bins=10)&#xA;#normalize 'counts' by averaging across the number of trajectory frames:&#xA;counts = counts / len(traj)&#xA;#calculate the volume of each spherical shell:&#xA;shell_volumes = 4/3*np.pi* ( lengths[1:]**3 - lengths[:-1]**3 )&#xA;#normalize 'counts' by the volume of each shell:&#xA;counts = counts / shell_volumes&#xA;&#xA;#plot:&#xA;plt.plot( (lengths[:-1]+lengths[1:])/2, &#xA;           counts , '-o' )&#xA;plt.ylabel('Number density per nm^3')&#xA;plt.xlabel('r (nm)')&#xA;plt.axhline(33.6, label='Waters per cubic nm\nat room temp and pressure', c='k')&#xA;plt.legend()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried this on an example trajectory and it returns the graph below, which has number density ~33, which is what you would expect at room temperature and pressure. Note that I extracted a water droplet from a simulation of a periodic liquid system with a barostat, so your result will be different if you used a water droplet as the simulation system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AOo0b.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AOo0b.png&quot; alt=&quot;rdf&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="2225" LastEditDate="2021-03-25T02:14:25.303" LastActivityDate="2021-03-25T02:14:25.303" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4579" PostTypeId="2" ParentId="4441" CreationDate="2021-03-23T02:38:55.660" Score="3" Body="&lt;p&gt;At the moment I have a workflow like this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I draw my structures,&lt;/li&gt;&#xA;&lt;li&gt;generate geometry with Avogadro,&lt;/li&gt;&#xA;&lt;li&gt;build the topology using &lt;a href=&quot;http://polypargen.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PolyParGen&lt;/a&gt; and &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;LigParGen&lt;/a&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;assemble the system using &lt;em&gt;genconf&lt;/em&gt; and &lt;em&gt;insert-molecules&lt;/em&gt; tools from Gromacs.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It's not perfect, but it works.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-03-23T14:58:46.747" LastActivityDate="2021-03-23T14:58:46.747" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4580" PostTypeId="1" CreationDate="2021-03-23T03:38:15.543" Score="12" ViewCount="778" Body="&lt;p&gt;I'm running a MD simulation (in Gromacs) of dye molecules incorporated into polymer to determine how that system responds to external electric field.&lt;/p&gt;&#xA;&lt;p&gt;There are two order parameters that are used to describe such systems: &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;\cos\theta&amp;gt;$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;\cos^3\theta&amp;gt;$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; being the angle between dipole moment of dye molecule and the direction of electric field, and averaging is over the ensemble of dye molecules.&lt;/p&gt;&#xA;&lt;p&gt;I'm thinking of writing a script, that will find 3 specific atoms in each dye molecule, and with a help of linear algebra will determine orientation of that molecule. That way, assuming the dipole moment isn't changing during MD run, I'll be able to calculate that parameters.&lt;/p&gt;&#xA;&lt;p&gt;The problem is I'm not very good in linear algebra and programming, so I'm wondering is there any software that can calculate such parameters?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-04-08T04:03:55.627" LastActivityDate="2021-04-15T03:27:36.947" Title="Analyzing MD trajectory: molecule orientation" Tags="|molecular-dynamics|software-recommendations|gromacs|electric-field|dipole|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4581" PostTypeId="2" ParentId="4573" CreationDate="2021-03-23T05:01:16.833" Score="14" Body="&lt;p&gt;&lt;strong&gt;Use &lt;code&gt;rg&lt;/code&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you have a significant size file or file(s) to search, do yourself a favor and choose one of the many significantly faster alternatives to &lt;code&gt;grep&lt;/code&gt;, the de facto fastest being &lt;a href=&quot;https://github.com/BurntSushi/ripgrep&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ripgrep&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Specific values&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;# literal string&#xA;rg &amp;lt;options&amp;gt; 'Volume of Typ   1:     98.5 %'     path/to/file/or/directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;# any value for the key&#xA;rg &amp;lt;options&amp;gt; 'Volume of Typ   1:'                path/to/file/or/directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;# any numeric value&#xA;rg &amp;lt;options&amp;gt; 'Volume of Typ   1:\s*\d+\.?\d*'    path/to/file/or/directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;# any numeric percentage&#xA;rg &amp;lt;options&amp;gt; 'Volume of Typ   1:\s*\d+\.?\d*\s%' path/to/file/or/directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where &lt;code&gt;&amp;lt;options&amp;gt;&lt;/code&gt; are any additional parameters you want to pass (may be omitted).&lt;br /&gt;&#xA;The &lt;code&gt;path&lt;/code&gt; argument may be omitted as well, it defaults to the current working directory.&lt;br /&gt;&#xA;Obviously, you could make the search parameter for the key a pattern too.&lt;/p&gt;&#xA;&lt;p&gt;N.B. The syntax is the same for &lt;code&gt;grep&lt;/code&gt; (or &lt;code&gt;ag&lt;/code&gt;, or the like).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Selection&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you wanted to &lt;em&gt;select&lt;/em&gt; the values only (as in strip the key and unit / suffix), &lt;code&gt;sed&lt;/code&gt; is an option:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;cat path/to/file | sed -en 's!^Volume of Typ\s*1:\s*\([0-9]*\.[0-9]*\).*$!\1!gp'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;At this point, you've got &lt;strong&gt;a list of line-terminated, matched values&lt;/strong&gt; on your screen.&lt;br /&gt;&#xA;Neato, no more noise!&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Next&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Other than looking at the output on screen, you could:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;store it in another file &lt;code&gt;&amp;lt;previous_command&amp;gt; &amp;gt; path/to/values.csv&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;pipe it to the next command (e.g. to visualize the values):&lt;br /&gt;&#xA;&lt;code&gt;&amp;lt;previous_command&amp;gt; | awk '{print NR &amp;quot; &amp;quot; $0}' | gnuplot -p -e &amp;quot;plot '&amp;lt;cat'&amp;quot;&lt;/code&gt;&lt;br /&gt;&#xA;(Exercise left to the avid reader: The extraction of the &lt;code&gt;Typ n&lt;/code&gt; type number to plot on the x-axis, instead of the running index &lt;code&gt;NR&lt;/code&gt;.)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Narrower conditions are obviously possible.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tips&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Single quoted &lt;code&gt;'&lt;/code&gt; strings make regexes in the shell significantly easier to type.&lt;/li&gt;&#xA;&lt;li&gt;Use a better delimiter for &lt;code&gt;sed&lt;/code&gt; than the often cited &lt;code&gt;/&lt;/code&gt;, &lt;code&gt;!&lt;/code&gt; for instance.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.freebsd.org/cgi/man.cgi?query=rg&amp;amp;apropos=0&amp;amp;sektion=0&amp;amp;manpath=FreeBSD+12.2-RELEASE+and+Ports&amp;amp;arch=default&amp;amp;format=html&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;man rg&lt;/code&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.freebsd.org/cgi/man.cgi?query=sed&amp;amp;sektion=&amp;amp;n=1&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;man sed&lt;/code&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.regular-expressions.info/&quot; rel=&quot;nofollow noreferrer&quot;&gt;regular expressions&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://regex101.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;online regex debugger&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Bonus: &lt;code&gt;sed&lt;/code&gt; breakdown&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;cat path/to/file | sed -en 's!^Volume of Typ\s*1:\s*\([0-9]*\.[0-9]*\).*$!\1!gp'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;cat&lt;/code&gt;&lt;sup&gt;1&lt;/sup&gt; reads the file from disk and prints its contents to &lt;code&gt;stdout&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;|&lt;/code&gt; is a &lt;a href=&quot;https://en.wikipedia.org/wiki/Pipeline_(Unix)&quot; rel=&quot;nofollow noreferrer&quot;&gt;pipe&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;sed&lt;/code&gt; is a &lt;strong&gt;s&lt;/strong&gt;tream &lt;strong&gt;ed&lt;/strong&gt;itor:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the &lt;code&gt;-e&lt;/code&gt; flag isn't strictly necessary, it's just there to allow for possibly multiple &amp;quot;script&amp;quot; inputs at once&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;-n&lt;/code&gt; suppresses output (get rid of non-matching lines)&lt;/li&gt;&#xA;&lt;li&gt;the script argument decodes as &lt;code&gt;s!&amp;lt;search_pattern&amp;gt;!&amp;lt;replacement&amp;gt;!&amp;lt;flags&amp;gt;&lt;/code&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;wherein &lt;code&gt;&amp;lt;search_pattern&amp;gt;&lt;/code&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;^&lt;/code&gt; beginning of the line&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Volume of Typ&lt;/code&gt; literal string to be matched&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;\s*&lt;/code&gt; any number of whitespaces&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;:&lt;/code&gt; literal string to be matched&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;\s*&lt;/code&gt; any number of whitespaces&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;(...)&lt;/code&gt; group that may be referenced (no effect on matching)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;[0-9]*&lt;/code&gt; any number of digits (character class with a &lt;code&gt;*&lt;/code&gt; quantifier)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;\.&lt;/code&gt; an escaped, literal period (&lt;code&gt;.&lt;/code&gt; has a logical meaning in regular expressions)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;wherein &lt;code&gt;&amp;lt;replacement&amp;gt;&lt;/code&gt; is &lt;code&gt;\1&lt;/code&gt;, a &lt;em&gt;backreference&lt;/em&gt; to the group &lt;code&gt;(...)&lt;/code&gt; above&lt;/li&gt;&#xA;&lt;li&gt;wherein the &lt;code&gt;&amp;lt;flags&amp;gt;&lt;/code&gt; are:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;g&lt;/code&gt; apply globally (you want more than one match)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;p&lt;/code&gt; print matches to &lt;code&gt;stdout&lt;/code&gt; (we had negated &lt;em&gt;all&lt;/em&gt; output with &lt;code&gt;-n&lt;/code&gt; earlier to get rid of non-matching lines)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; For the sake of completeness: &lt;code&gt;cat&lt;/code&gt;'s actual purpose is text (or file) con&lt;em&gt;cat&lt;/em&gt;enation and it takes any number of arguments. Most of its invocations in its lifetime have certainly been with one argument to read a file.&lt;/p&gt;&#xA;" OwnerUserId="2246" LastEditorUserId="2246" LastEditDate="2021-03-24T04:24:45.687" LastActivityDate="2021-03-24T04:24:45.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4582" PostTypeId="2" ParentId="1548" CreationDate="2021-03-23T20:17:42.867" Score="8" Body="&lt;p&gt;The equation in your question, be it Heisenberg or Ising exchange, can be calculated by Energy mapping analysis. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;This&lt;/a&gt; has to be the most popular paper that discusses this technique. Basically, you consider different spin configurations and map the exchange 'J' into the total energy values from DFT.&lt;/p&gt;&#xA;&lt;p&gt;In the simplest form, if you have two magnetic atoms in your unit cell, there are four possible spin configurations - &lt;span class=&quot;math-container&quot;&gt;$\uparrow$$\uparrow$&lt;/span&gt; , &lt;span class=&quot;math-container&quot;&gt;$\uparrow$$\downarrow$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\downarrow$$\uparrow$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$\downarrow$$\downarrow$&lt;/span&gt;, denoted by &lt;span class=&quot;math-container&quot;&gt;$E_1, E_2, E_3, E_4$&lt;/span&gt; respectively. The exchange 'J' can be estimated as  &lt;span class=&quot;math-container&quot;&gt;$1/4* (E_1 - E_2 - E_3 + E_4$&lt;/span&gt;). Now, the energy values for the four different configurations are just the total energy values from your DFT calculation. Typically, you would need to constrain your magnetization on the magnetic atoms in your DFT package. If you want to include anisotropic exchange, you need to consider spin-orbit coupling as well.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-03-23T20:17:42.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4583" PostTypeId="1" CreationDate="2021-03-23T20:33:28.083" Score="6" ViewCount="282" Body="&lt;p&gt;I am trying to calculate the formation energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg2Si}$&lt;/span&gt; and for the calculation of lowest energy configuration of Bulk &lt;span class=&quot;math-container&quot;&gt;$\ce{Si}$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$E(\ce{Si})$&lt;/span&gt; and bulk Mg &lt;span class=&quot;math-container&quot;&gt;$E(\ce{Mg})$&lt;/span&gt;. I have opted for both structures from the Materials Project with the same space group Fm3m. I am wondering that if I change the space group of both i.e by employing different structures from another space group formation energy changes drastically. For the same space group, the value of formation energy does not match with previous results.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How will I decide the correct prediction of bulk materials (Mg, Si)?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="1218" LastEditDate="2021-03-23T23:27:35.863" LastActivityDate="2021-03-24T08:08:12.273" Title="Formation energy calculation" Tags="|vasp|formation-energy|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4584" PostTypeId="2" ParentId="4567" CreationDate="2021-03-23T21:39:11.947" Score="7" Body="&lt;p&gt;From reading your comments, and the question, you want to generate optimized structures of small bioactive molecules in solvents, but it has to be fast. I would definitely recommend using semi-empirical methods, because that would give you the best of both worlds. The calculation will be faster than DFT, and you can use those methods with relatively accurate implicit solvation models.&lt;/p&gt;&#xA;&lt;p&gt;Here I have covered three softwares, with several semi-empirical methods, and one force-field based method:&lt;/p&gt;&#xA;&lt;h3&gt;MOPAC&lt;/h3&gt;&#xA;&lt;p&gt;MOPAC has loads of semi-empirical methods, prominent among them being PM3 (old), PM6 (newer), PM6-DH+ (empirical dispersion and hydrogen bonding) etc. MOPAC uses the COSMO model for implicit solvation. In the input file, you have to put the keyword &lt;code&gt;EPS=78.6&lt;/code&gt; to specify the dielectric constant of the solvent (default 78.6 for water). The MOPAC manual &lt;a href=&quot;http://openmopac.net/manual/cosmo.html&quot; rel=&quot;noreferrer&quot;&gt;recommends&lt;/a&gt; that you use EF algorithm for optimizing with solvent, instead of the default L-BFGS.&lt;/p&gt;&#xA;&lt;p&gt;As a test, I optimized an esomeprazole molecule (sdf file obtained from PubChem) on my laptop (Intel core i3, 2.2 GHz 4 core) with PM6/water. It took 8.53 seconds for the optimization to finish (multi-threaded run).&lt;/p&gt;&#xA;&lt;h3&gt;GAMESS&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/&quot; rel=&quot;noreferrer&quot;&gt;GAMESS&lt;/a&gt; can use PM3, AM1 and RM1 semi-empirical methods officially. However, PM6 and PM6-D3H+ (D3 dispersion and hydrogen bond corrected) methods are also implemented for elements until fluorine (unofficially). All the semi-empirical methods are interfaced with SMD solvation model (which is more accurate than COSMO as it also includes non-electrostatic contributions to solvation). See &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5047273&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; paper for details of the implementation. For example, with PM3/SMD the RMS error for solvation energy is 2.8 kcal/mol (neutral solute), so the method is quite accurate. To use this you have to specify &lt;code&gt;$BASIS GBASIS=PM3 $END&lt;/code&gt; and &lt;code&gt;$PCM SOLVNT=WATER SMD=.T. $END&lt;/code&gt;. For the other solvents, use &lt;code&gt;SOLVNT=DMSO&lt;/code&gt; or &lt;code&gt;SOLVNT=ETHANOL&lt;/code&gt; instead.&lt;/p&gt;&#xA;&lt;p&gt;I redid the same optimization of esomeprazole on GAMESS and it took 3.8 minutes on 4 cores. This is probably because the implementation of semi-empirical methods in GAMESS is slightly slower itself, also because GAMESS uses different criteria for convergence of optimization and SMD is slightly more demanding.&lt;/p&gt;&#xA;&lt;h3&gt;XTB&lt;/h3&gt;&#xA;&lt;p&gt;XTB is uses a semi-empirical tight-binding approach. There are three parameterizations—GFN0-xTB, GFN1-xTB, GFN2-xTB, each newer than the last. XTB is &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;open-source&lt;/a&gt;, so you will have to compile it. It has analytical linearized Poisson-Boltzmann(alpb) implicit solvation. According to the official &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/gbsa.html&quot; rel=&quot;noreferrer&quot;&gt;manual&lt;/a&gt;, DMSO and water are available, ethanol is not mentioned. However, from my test, the latest version seems to be able to run with ethanol solvation as well.&lt;/p&gt;&#xA;&lt;p&gt;XTB is run from command line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;xtb.exe --alpb water --opt -P 4 --gfn 2 esomeprazole.sdf &amp;gt; out.log&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This uses GFN2 parameters with water solvation and 4 cores. The calculation took 7.346 second on my laptop.&lt;/p&gt;&#xA;&lt;p&gt;For the other solvents, use &lt;code&gt;--alpb dmso&lt;/code&gt; and &lt;code&gt;--alpb ethanol&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The XTB software also contains a &lt;strong&gt;polarizable force field&lt;/strong&gt; GFN-FF, which can also be run with implicit solvation. I am not sure how accurate it is, but the optimization of esomeprazole takes 0.445 seconds, a significant gain in speed. To use the force field, you have to use &lt;code&gt;--gfnff&lt;/code&gt; instead of &lt;code&gt;--gfn 2&lt;/code&gt; in the command line.&lt;/p&gt;&#xA;&lt;h3&gt;Running with Python&lt;/h3&gt;&#xA;&lt;p&gt;I have limited knowledge of Python, so I can't help much here. For MOPAC and GAMESS, you can use the python package &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/about.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;. It is supposed to be able to interface to the  softwares directly. ASE can also write input files, so use that if the interface does not work. As XTB is used from the command-line and can read sdf files, you can directly use &lt;code&gt;os.subprocess.run()&lt;/code&gt;. XTB automatically outputs the optimized geometry in the same format as input (.sdf here).&lt;/p&gt;&#xA;&lt;p&gt;Not all semi-empirical methods are well-parallelized. MOPAC and XTB uses thread-based parallelization, whereas GAMESS uses an MPI-based one. I assume you are using a cluster for your calculations. It would probably be the most efficient if you ran each calculation on one core, and parallelized the handling of different molecules. You could use something like &lt;a href=&quot;https://mpi4py.readthedocs.io/en/stable/&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;mpi4py&lt;/code&gt;&lt;/a&gt; for this. Also check if the software you are using allows multiple instances to be launched at the same time. On my laptop, XTB can do this, but I have not tested GAMESS or MOPAC.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-03-24T09:54:40.830" LastActivityDate="2021-03-24T09:54:40.830" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4585" PostTypeId="2" ParentId="4571" CreationDate="2021-03-24T03:49:23.907" Score="3" Body="&lt;p&gt;It sounds like you're trying to calculate the autocorrelation function at all times from your trajectory. If you have a trajectory with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; frames, you won't have good statistics in an ACF for all frames.&lt;/p&gt;&#xA;&lt;p&gt;The reason the ACF decays to zero is because nonzero values from many decorrelated (essentially random) contributions average to zero. Looking at your second equation, note that for &lt;span class=&quot;math-container&quot;&gt;$t=1$&lt;/span&gt;, you'll have &lt;span class=&quot;math-container&quot;&gt;$N-1$&lt;/span&gt; contributions to calculate &lt;span class=&quot;math-container&quot;&gt;$C_{VV}(1)$&lt;/span&gt;: product of velocities at times &lt;span class=&quot;math-container&quot;&gt;$(0, 1)$&lt;/span&gt;, at times &lt;span class=&quot;math-container&quot;&gt;$(1, 2)$&lt;/span&gt;, etc. However, for &lt;span class=&quot;math-container&quot;&gt;$C_{VV}(N)$&lt;/span&gt; there is only one contribution: &lt;span class=&quot;math-container&quot;&gt;$(0, N)$&lt;/span&gt;. This is probably the source of the noise, and this is expected. Frequently, an ACF is only calculated for a very small fraction of the total trajectory length.&lt;/p&gt;&#xA;&lt;p&gt;Note that this is an aspect of correlation functions in general; this is not specific to the problem of binary diffusion.&lt;/p&gt;&#xA;&lt;p&gt;By the way, the computational cost of the algorithm you're using scales as the number of frames times the number of points that you calculate the ACF for. If you're calculating the ACF for many points, this can be expensive, and you might be interested in the fast Fourier transform approach. Allen &amp;amp; Tildesley's book &amp;quot;Computer Simulation of Liquids&amp;quot; has a great description of it (in fact, I think the whole discussion of correlation functions in that book is excellent).&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-03-24T03:49:23.907" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4586" PostTypeId="2" ParentId="4573" CreationDate="2021-03-24T05:47:31.413" Score="3" Body="&lt;p&gt;To search for all the strings in all of the files in current folder you would use simply:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep string *&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or in subfolder:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep string subfolder/*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Unfortunately recursion is not possible so you can only search one folder at the time.&lt;/p&gt;&#xA;" OwnerUserId="2254" LastActivityDate="2021-03-24T05:47:31.413" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4588" PostTypeId="2" ParentId="4583" CreationDate="2021-03-24T08:08:12.273" Score="5" Body="&lt;p&gt;Basically, for obtaining the formation energy we need to calculate the energy of the individual phases at their ground state structure.&#xA;For example in your case you have to consider Si and Mg in their ground state i.e. diamond cubic (Fd-3m) and hcp (P63/mmc), respectively.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2021-03-24T08:08:12.273" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4589" PostTypeId="1" CreationDate="2021-03-24T19:52:19.960" Score="8" ViewCount="295" Body="&lt;p&gt;In publications, I usually see the statement &lt;strong&gt;&amp;quot;A  dense  k-mesh  of 40,000  k-points  was  used  in  the  Brillouin  zone&amp;quot;&lt;/strong&gt;. An example of this is &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2214785318302736&quot; rel=&quot;noreferrer&quot;&gt;in this paper&lt;/a&gt;. But in the paper they have used a k-point grid of 8x8x8 and 9x9x9 for the SCF calculation.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;How do they arrive at the number &amp;quot;40000&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;Thanks :)&lt;/p&gt;&#xA;" OwnerUserId="2206" LastEditorUserId="5" LastEditDate="2021-03-24T20:13:59.350" LastActivityDate="2021-03-25T00:05:30.597" Title="&quot;A dense k mesh of 40,000 k points was used in the Brillouin zone&quot;. How is this number obtained?" Tags="|density-functional-theory|k-points|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4591" PostTypeId="2" ParentId="4589" CreationDate="2021-03-24T23:59:56.760" Score="8" Body="&lt;p&gt;The computational content of the cited paper includes two parts:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;DFT calculations (such as band structures) with QE;&lt;/li&gt;&#xA;&lt;li&gt;Transport calculations (such as Seebeck coefficients) with BoltzTraP based on DFT calculations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$8 \times 8 \times 8$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$9 \times 9 \times 9$&lt;/span&gt; are chosen for DFT calculations. However, the dense k-mesh with &lt;span class=&quot;math-container&quot;&gt;$40000$&lt;/span&gt; points in the first Brillouin zone is for transport calculation. Why transport calculation needs so dense k-mesh is related to the semiclassical method that BoltzTraP adopted.&lt;/p&gt;&#xA;&lt;p&gt;You may take a look at the computational method of this paper also calculated with BoltzTraP:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4953063&quot; rel=&quot;noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.4953063&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-03-25T00:05:30.597" LastActivityDate="2021-03-25T00:05:30.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4592" PostTypeId="1" AcceptedAnswerId="4594" CreationDate="2021-03-25T13:51:38.200" Score="8" ViewCount="859" Body="&lt;p&gt;I have read this paper many times: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.196802&quot; rel=&quot;noreferrer&quot;&gt;Coupled Spin and Valley Physics in Monolayers of MoS2 and Other Group-VI Dichalcogenides.&lt;/a&gt; Interestingly, this paper is also discussed many times in this community, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1728/separation-of-valence-bands-in-transition-metal-dichalcogenides-tmds/3829#3829&quot;&gt;Separation of valence bands in transition metal dichalcogenides (TMDs)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1770/how-to-derive-the-effective-hamiltonian-of-two-dimensional-tmdcs-monolayers&quot;&gt;How to derive the effective Hamiltonian of two-dimensional TMDCs monolayers?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;One of the most important conclusions is the spin-dependent optical transition. However, the authors claim that [&lt;strong&gt;optical field couples only to the orbital part of the wave function and spin is conserved in the optical transitions&lt;/strong&gt;]. Therefore, the spin-dependent transitions are realized by the spin-valley coupling that I have understood.&lt;/p&gt;&#xA;&lt;p&gt;Here my confusing part is about why we can't change the spin angular momentum of electrons with the external optical field? For example, assume that the left circular polarization light, carried a spin angular momentum &lt;span class=&quot;math-container&quot;&gt;$\hbar$&lt;/span&gt;, is absorbed by an electron with spin angular momentum &lt;span class=&quot;math-container&quot;&gt;$-\dfrac{1}{2}\hbar$&lt;/span&gt;, then the energy of the photon is eaten by the electron, but where is the spin angular momentum of the photon if we think the electron spin is conserved? Is it transferred to the orbital angular momentum of the electron? How?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-03-26T20:12:49.023" LastActivityDate="2021-03-26T20:12:49.023" Title="Why can't we change the spin angular momentum of electrons with an external optical field?" Tags="|dichalcogenides|optical-properties|spin|spin-polarization|exciton|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4593" PostTypeId="1" AcceptedAnswerId="4623" CreationDate="2021-03-25T15:31:34.017" Score="5" ViewCount="994" Body="&lt;p&gt;We can obtain a energy band structure of a crystal from a DFT calculation in Vasp. Each point in each band represents an energy eigenvalue with a corresponding wave function from the Schrödinger equation. I want to choose a specific K-point in the Brillouin zone for a specific band and investigate the symmetry of the corresponding wave function.&lt;/p&gt;&#xA;&lt;p&gt;Supposedly, I can obtain the wave function from the &lt;code&gt;WAVECAR&lt;/code&gt; file. It should yield a number of coefficients which can be used to construct the wave function from the basis functions used in the calculations. However, I do not need the full wave function. I only want to know the symmetry of the function. If my basis was small, I could easily identify the symmetry by inspection, but with hundreds (?) of coefficients this seems difficult.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I find the symmetry of the wave function from my VASP calculation?&lt;/strong&gt; Please, also let me know if it seems like I am asking the wrong question.&lt;/p&gt;&#xA;" OwnerUserId="1490" LastEditorUserId="5" LastEditDate="2021-03-25T15:40:01.870" LastActivityDate="2021-03-30T12:15:15.827" Title="How do I extract the wave function from a VASP calculation?" Tags="|vasp|crystallography|symmetry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4594" PostTypeId="2" ParentId="4592" CreationDate="2021-03-25T16:40:29.433" Score="9" Body="&lt;p&gt;This has already been asked in several forms in Physics Stack Exchange. Within the semi-classical 'electric dipole' approximation, only the electric field of light interacts with the electron. The effect of magnetic field is usually very weak except for a few cases like highly concentrated pulses etc. Magnetic field can flip spins, in a process called 'spin-flip'. There are experimental cases reported, the most famous being the 21cm astronomical limit. I wrote a more comprehensive answer &lt;a href=&quot;https://physics.stackexchange.com/questions/551123/selections-rules-for-spin/551185#551185&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="683" LastEditDate="2021-03-25T16:46:10.963" LastActivityDate="2021-03-25T16:46:10.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4595" PostTypeId="1" AcceptedAnswerId="4600" CreationDate="2021-03-25T20:19:57.417" Score="6" ViewCount="235" Body="&lt;p&gt;I am trying to optimize the geometry of excited state NH3 and get the corresponding normal modes for excited states. I am trying to get the frequencies as mentioned in &lt;a href=&quot;https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-018-0152-9/MediaObjects/41586_2018_152_MOESM1_ESM.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this reference&lt;/a&gt;. They claim to use CC2/TZVPP for calculations. I am trying to re-create their results with my script but there is a big mismatch between the values they report and I am getting.&lt;/p&gt;&#xA;&lt;p&gt;Their reported values:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5j7fA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5j7fA.png&quot; alt=&quot;Normal mode frequencies for excited state of NH3&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am able to get their ground state frequencies but not the excited state.&#xA;My GAMESS script for excited state calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!   File created for NH3 Excited states&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=TZV $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE CCTYP=CCD $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT  OPTTOL=0.0001 NSTEP=20 HSSEND=.T. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$FORCE METHOD=FULLNUM VIBSIZ=0.001 VIBANL=.TRUE. PURIFY=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$eominp nstate(1)=1,0,0,0,0,0,0,0 iroot(1)=2 ccprpe=.true.&#xA;         minit=2 noact=3 nuact=5 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;Title&#xA;C1&#xA;N     7.0    -0.00000    -0.00000     0.05500&#xA;H     1.0    -0.01280    -0.96010    -0.25500&#xA;H     1.0     0.83790     0.46900    -0.25500&#xA;H     1.0    -0.82510     0.49110    -0.25500&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The resultant frequencies that I get after running this is:&#xA;&lt;code&gt;{364.17, 1680.03, 1686.99, 3658.94, 3866.18, 3867.96}&lt;/code&gt;&#xA;Could you help in fixing the issue?&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;Based on one of the answers, I updated the input file. Resulting frequencies with EOM-CCSD and TZVPP basis functions are,&#xA;&lt;code&gt;{237.63, 875.84, 982.98, 3508.41, 3524.99, 3533.73}&lt;/code&gt;&#xA;Still way off than what is being reported. But it looks like moving in the right direction.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!   File created for NH3 Excited states&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=TZVPP $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE CCTYP=EOM-CCSD $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT  OPTTOL=0.0001 NSTEP=20 HSSEND=.T. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$FORCE METHOD=FULLNUM VIBSIZ=0.001 VIBANL=.TRUE. PURIFY=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$eominp nstate(1)=1,0,0,0,0,0,0,0 iroot(1)=2 ccprpe=.true.&#xA;         minit=2 noact=3 nuact=5 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;Title&#xA;C1&#xA;N     7.0    -0.00000    -0.00000     0.05500&#xA;H     1.0    -0.01280    -0.96010    -0.25500&#xA;H     1.0     0.83790     0.46900    -0.25500&#xA;H     1.0    -0.82510     0.49110    -0.25500&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2095" LastEditorUserId="2095" LastEditDate="2021-03-26T04:29:04.767" LastActivityDate="2021-03-26T16:27:37.283" Title="Excited state normal mode frequency doesn't match for NH3" Tags="|vibrations|software-assistance|spectroscopy|gamess|excited-states|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4596" PostTypeId="2" ParentId="4595" CreationDate="2021-03-25T22:51:08.950" Score="5" Body="&lt;p&gt;I can see two major problems:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;CCD != CC2 and I'm not certain if CC2 is available in GAMESS. &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/000926149500841Q&quot; rel=&quot;nofollow noreferrer&quot;&gt;CC2&lt;/a&gt; is an approximation of CCSD, which is available in GAMESS. You may be able to use this since &lt;span class=&quot;math-container&quot;&gt;$\ce{NH3}$&lt;/span&gt; is a fairly small molecule, though I don't know how time consuming this will be relative to your initial CCD calculation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;TZV != TZVPP. The &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2005/CP/b508541a#!divAbstract&quot; rel=&quot;nofollow noreferrer&quot;&gt;def2-TZVPP&lt;/a&gt; basis set has two sets of polarization functions added to it relative to def2-TZV (&lt;code&gt;TZV&lt;/code&gt; denotes an &lt;a href=&quot;http://myweb.liu.edu/%7Enmatsuna/gamess/input/BASIS.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;entirely different basis set&lt;/a&gt; in GAMESS). The def2 basis sets are actually not available by default in GAMESS and must be pulled from an external source (the &lt;code&gt;KTZV&lt;/code&gt; and &lt;code&gt;KTZVPP&lt;/code&gt; in GAMESS are the older def basis sets). Using a different basis set will significantly affect the results.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I haven't used GAMESS, so there could be other issues with your input.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-03-26T16:27:37.283" LastActivityDate="2021-03-26T16:27:37.283" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4597" PostTypeId="2" ParentId="4592" CreationDate="2021-03-26T01:15:40.990" Score="5" Body="&lt;p&gt;I think the claim assumes linear polarization of the light which has zero angular momentum. For circularly polarized light, the spin of the electron should be flipped. (e.g. Appl. Phys. Lett. 114, 041104 (2019)) Indeed, it has a probability issue as explained by @Xivi76.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2021-03-26T08:51:02.503" LastActivityDate="2021-03-26T08:51:02.503" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4598" PostTypeId="1" CreationDate="2021-03-26T05:08:14.933" Score="6" ViewCount="169" Body="&lt;p&gt;The cohesive energy of a pure material is generally termed as the energy of a unit cell divided by the number of atoms. what will be cohesive energy of an alloy in LAMMPS? I am running LAMMPS for &lt;span class=&quot;math-container&quot;&gt;$\ce{UO2}$&lt;/span&gt; with different potentials and found that the total energy of the system is different for different potentials, but the lattice parameter matches well.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2021-10-19T20:55:34.637" LastActivityDate="2021-10-19T20:55:34.637" Title="What will be the cohesive energy of an alloy in LAMMPS?" Tags="|molecular-dynamics|lammps|metals|metal-complexes|" AnswerCount="0" CommentCount="10" ClosedDate="2022-01-13T05:24:49.860" ContentLicense="CC BY-SA 4.0" />
  <row Id="4599" PostTypeId="2" ParentId="4592" CreationDate="2021-03-26T09:54:58.833" Score="6" Body="&lt;p&gt;well, you certainly can change the spin of an electron through acting on its orbital motion with the electric field. It is called &amp;quot;spin-orbit coupling&amp;quot; (SOC) and a lot of magneto-optical and opto-magnetic (inverse) effects completely rely on it. You might want to look at papers discussing all-optical magnetization switching with circularly polarized light in various materials using, e.g. inverse Faraday effect. Further, spin-orbit coupling is the only way to couple spin and light in a hamiltonian. Theorists who calculate interactions of optical fields and spins often calculate (and show in their papers) no-SOC cases where they artificially set the SOC strength to 0 and demonstrate that the effect they were interested in vanishes.&#xA;Yet, the reason why it is difficult to flip electron&amp;quot;s spin with light is that, well, SOC is usually (in common materials) not very strong. If you go down the periodic table, SOC increases rapidly, and heavy rare-earths might be the systems where optical spin-flip transitions are to be looked for.&lt;/p&gt;&#xA;" OwnerUserId="2287" LastActivityDate="2021-03-26T09:54:58.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4600" PostTypeId="2" ParentId="4595" CreationDate="2021-03-26T12:08:57.760" Score="5" Body="&lt;p&gt;This is not a full answer, because it does not solve the problem. But I hope to shed some light on why you are not getting the correct frequencies.&lt;/p&gt;&#xA;&lt;p&gt;Short answer: &lt;strong&gt;I suspect there is a bug in GAMESS&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Long answer:&lt;/p&gt;&#xA;&lt;p&gt;First of all I would advise you to go through the manual of GAMESS. There are lots of  problems in the input file, and most of them can be easily fixed by looking at the manual.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You are using EOM-CCSD, so you have to use &lt;code&gt;CCTYP=EOM-CCSD&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;This method does not have analytic gradients, so you &lt;strong&gt;must&lt;/strong&gt; add &lt;code&gt;NUMGRD=.t.&lt;/code&gt; in &lt;code&gt;$CONTRL&lt;/code&gt;. Your input file as of now, calculates the analytic gradient of the RHF part only, and produces the wrong result. (EOM-CCSD calculation has three parts—ground state RHF, ground state CCSD, excited state EOM-CCSD)&lt;/li&gt;&#xA;&lt;li&gt;You cannot use &lt;code&gt;PURIFY=.t.&lt;/code&gt; without internal coordinates! Since you are using Cartesian coordinates, the correct keyword is &lt;code&gt;PROJCT=.t.&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;The basis set and method problem has been already mentioned in the answer by @Tyberius. The basis set you are looking for is def2-TZVPP, which is not available in GAMESS. (&lt;code&gt;GBASIS=KTZVPP&lt;/code&gt; is not the same basis) . You will have to input it from outside. (As a blatant self-plug, I have written a blog post about using outside basis sets &lt;a href=&quot;https://shoubhikrmaiti.medium.com/introduction-to-molecular-modelling-part-7-basis-sets-in-gamess-bde74c63320&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. It's too long to write here anyways)&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;nstate(1)=1,0,0,0,0,0,0,0&lt;/code&gt; keyword request for only one symmetric excited state. You should &lt;strong&gt;use&lt;/strong&gt; &lt;code&gt;iroot(1)=1,1&lt;/code&gt;. The first number in &lt;code&gt;iroot(1)=&lt;/code&gt;indicates the symmetry (&lt;code&gt;1&lt;/code&gt; for completely symmetric i.e. &lt;code&gt;A&lt;/code&gt;). The second number indicates the state (&lt;code&gt;1&lt;/code&gt; for first excited state). (Your current input file requests a state that does not exist)&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;ccprpe=.true.&lt;/code&gt; keyword calculates the EOM-CCSD density matrix for properties. Unless you need properties (like dipole moment etc.) I would suggest you turn this off. Remember, the density matrix is calculated at every stage of geometry optimization and numerical differentiaion for gradient, so it's clearly wasting cpu resources.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, GAMESS cannot run numerical optimizations and numerical hessians in the same run (i.e. you cannot use &lt;code&gt;HSSEND=.t.&lt;/code&gt; with &lt;code&gt;NUMGRD=.t.&lt;/code&gt;). Therefore, you have to optimize first, with &lt;code&gt;NUMGRD=.t.&lt;/code&gt;, then take that optimized structure and then calculate its hessian with &lt;code&gt;RUNTYP=HESSIAN&lt;/code&gt; and &lt;code&gt;METHOD=FULLNUM&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Even after fixing all of this, when I try to calculate the hessian of the excited &lt;span class=&quot;math-container&quot;&gt;$\ce{NH3}$&lt;/span&gt;, I get 3 imaginary frequencies. Which is odd, because I just optimized it! I believe the numeric hessian code of GAMESS is not using the EOM-CCSD first excited state energy values, but is instead using the ground state CCSD or RHF energy values for calculating the hessian. I am not completely sure if this is a bug, or whether some keyword needs to be changed. The good news is that at least the gradient calculation run correctly (I am getting a planar optimized structure for the excited state).&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-03-26T13:39:24.580" LastActivityDate="2021-03-26T13:39:24.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4601" PostTypeId="1" CreationDate="2021-03-26T15:16:24.613" Score="5" ViewCount="115" Body="&lt;p&gt;By definition, the surface energy of a thin film or a slab model is defined as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma = \frac{1}{2A}(E_{slab} - N\cdot E_{bulk})&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of atoms in the thin film and &lt;span class=&quot;math-container&quot;&gt;$E_{bulk}$&lt;/span&gt; corresponds to the average energy of the atom in its bulk phase. I should expect that the surface energy of the slab converge to certain value when I keep increasing the number of layers but what I found is the surface energy of my system increases linearly. I think this is unreasonable. Is there anyone who met this problem before?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="1875" LastEditDate="2021-03-27T03:16:29.810" LastActivityDate="2021-04-05T03:28:48.280" Title="Divergence behaviour of surface energy" Tags="|density-functional-theory|vasp|surfaces|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4602" PostTypeId="1" AcceptedAnswerId="4605" CreationDate="2021-03-26T17:04:01.583" Score="16" ViewCount="2871" Body="&lt;p&gt;I want to estimate the lifetime of an electronic excited state. Lets assume there is only radiative coupling via spontaneous emission from this state to the ground state. I can optimize the excited state, for example the S1 state and calculate the transition dipole moment to the ground state at this S1 equilibrium geometry. &lt;strong&gt;Can I calculate an estimate for the lifetime of this state from these values?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="2289" LastEditorUserId="5" LastEditDate="2021-03-27T04:15:02.633" LastActivityDate="2021-03-30T22:12:53.743" Title="Can you estimate the electronic excited state lifetime of a molecule?" Tags="|spectroscopy|excited-states|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4603" PostTypeId="2" ParentId="4602" CreationDate="2021-03-26T17:35:16.790" Score="8" Body="&lt;p&gt;Fermi golden rule should give you the transition probability (per time), from which you should be able to estimate the lifetime. You should know of be able to estimate the density of states in the final (ground) state, of course.&lt;/p&gt;&#xA;" OwnerUserId="2287" LastActivityDate="2021-03-26T17:35:16.790" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4604" PostTypeId="1" CreationDate="2021-03-26T18:59:20.797" Score="10" ViewCount="172" Body="&lt;p&gt;I have the following question: I am currently studying the electrocatalytic &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt; reduction reaction &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Electrochemical_reduction_of_carbon_dioxide#Electrocatalysis&quot; rel=&quot;nofollow noreferrer&quot;&gt;(CO2RR)&lt;/a&gt; on &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}$&lt;/span&gt; materials using periodic DFT calculations and I am using the Computational Hydrogen Electrode &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp047349j&quot; rel=&quot;nofollow noreferrer&quot;&gt;(CHE)&lt;/a&gt; model to describe the proton electron transfer reactions, as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ce{CO2^* +e- + H+ → COOH^*}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta G= G(\ce{COOH^*})-G(*)-G(CO2)-G(e^- + \ce{H+})=G(\ce{COOH^*})-G(*)-G(\ce{CO2})-\frac{1}{2}G(\ce{H2}\text{(gas)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Nonetheless, I would like to ask how to describe reactions where I have only an electron transfer for example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\ce{COOH^* +e- → COOH- (aq)}+ *.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do I add calculate the Gibbs free energy of the electron added, as well as how I add the extra electron to the &lt;span class=&quot;math-container&quot;&gt;$\ce{COOH-}$&lt;/span&gt; (aq)?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="2291" LastEditorUserId="7" LastEditDate="2021-10-31T00:10:21.350" LastActivityDate="2021-10-31T00:10:21.350" Title="Single electron transfer periodic DFT in VASP" Tags="|density-functional-theory|vasp|electronic-transport|free-energy|" AnswerCount="0" CommentCount="4" ClosedDate="2022-01-26T14:45:00.417" ContentLicense="CC BY-SA 4.0" />
  <row Id="4605" PostTypeId="2" ParentId="4602" CreationDate="2021-03-26T20:46:02.800" Score="10" Body="&lt;p&gt;&lt;strong&gt;tldr; it's related to the excitation energy&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The lifetime of an excited molecule assuming there are no non-radiative pathways, is related to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Einstein_coefficients&quot; rel=&quot;nofollow noreferrer&quot;&gt;Einstein A coefficient&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\left(\frac{dn_2}{dt}\right)_\mathrm{spontaneous} = -A_{21}n_2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$n_2$&lt;/span&gt; is the population of the excited-state.&lt;/p&gt;&#xA;&lt;p&gt;I used this reference to get the following equations: J. Braz. Chem. Soc., Vol. 23, No. 12, 2237-2247, 2012. But there probably exists a much more formal derivation elsewhere.&lt;/p&gt;&#xA;&lt;p&gt;In short it's possible to calculate the radiative lifetime by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A_{21} = \frac{1}{\tau_\mathrm{rad}} = 2.142995\times10^{10}|\langle\Psi_1|\mu|\Psi_2\rangle|^2\times E^3_{ve}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$A_{21}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\tau_\mathrm{rad}$&lt;/span&gt; have units, &lt;span class=&quot;math-container&quot;&gt;$\mathrm{s}^{-1}$&lt;/span&gt; and s, respectively, &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; represents the transition moment operator, and the vertical energy &lt;span class=&quot;math-container&quot;&gt;$E_{ve}$&lt;/span&gt; is in atomic units, &lt;span class=&quot;math-container&quot;&gt;$\Psi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Psi_2$&lt;/span&gt; are the ground and excited-state.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="878" LastEditDate="2021-03-30T22:12:53.743" LastActivityDate="2021-03-30T22:12:53.743" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4607" PostTypeId="1" AcceptedAnswerId="4613" CreationDate="2021-03-27T03:39:29.827" Score="9" ViewCount="4179" Body="&lt;p&gt;Given a SMILES string for a molecule, I want to know the elements in the molecule, I then send this to basis_set_exchange to get a &amp;quot;custom&amp;quot; basis set for use in Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;This seems like something that &lt;a href=&quot;https://www.rdkit.org/&quot; rel=&quot;noreferrer&quot;&gt;RDKit&lt;/a&gt; can do, or &lt;a href=&quot;https://pypi.org/project/PubChemPy/1.0/&quot; rel=&quot;noreferrer&quot;&gt;PubChem&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I do know that given a molecular formula, like &amp;quot;H2O&amp;quot; &lt;a href=&quot;https://pypi.org/project/molmass/&quot; rel=&quot;noreferrer&quot;&gt;molmass&lt;/a&gt; can return the elements. So, it would also suffice to have a program that simply takes a SMILES string and returns a molecular formula, then use molmass to get the elements.&lt;/p&gt;&#xA;&lt;p&gt;However, this seems like such a trivial exercise, it must already be done. I don't want to make my own script for converting a SMILES to its elements just because I don't want to have to worry about corner cases or reinvent a wheel.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-03-27T06:13:41.383" LastActivityDate="2021-03-27T17:42:30.393" Title="Python program that returns elements from a SMILE string" Tags="|python|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4608" PostTypeId="2" ParentId="4602" CreationDate="2021-03-27T05:36:46.960" Score="11" Body="&lt;p&gt;The &lt;strong&gt;Einstein A coefficient&lt;/strong&gt; (as mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4605/5&quot;&gt;Cody's answer&lt;/a&gt;) tells you the probability per unit time of spontaneous radiative decay from an excited state to a lower state.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;Fermi golden rule&lt;/strong&gt; (as mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4603/5&quot;&gt;sleepy's answer&lt;/a&gt;) also gives a probability per unit time to transition from a specific state, but the destination is &lt;em&gt;usually&lt;/em&gt; a group of states in a continuum (not just one discrete state lower than the initial state). It's possible to use Fermi's golden rule for the case where the final state is also just one specific state (not a group of states in a continuum), but you will see this discussed less often than the  first case.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;A third and much less well-known way&lt;/strong&gt;, was used in my paper on &amp;quot;&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3264688&quot; rel=&quot;noreferrer&quot;&gt;The radiative lifetime of &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(2p)$&lt;/span&gt;&lt;/a&gt;&amp;quot;. We didn't know this when we published the paper, but 2 years later a &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.84.052502&quot; rel=&quot;noreferrer&quot;&gt;paper was published by a completely different group&lt;/a&gt; saying that we had determined the radiatime lifetime more accurately than any previously determined empirical value, by an order of magnitude (we had no idea that we'd done that until we saw this paper come up 2 years later, otherwise maybe we would have submitted to a different journal!). Our success was due in part to making use of fairly high-accuracy experimental data, but no experimental data is necessary for this procedure. The method is as follows, and I'll explain it for the radiative lifetime of an atom, but &lt;strong&gt;it can also be used for molecules:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above paper's analysis was a bit more complicated because spin-orbit (SO) coupling was treated, but the main procedure is the same whether or not the fine-structure and other added complexities associated with SO coupling are included. Consider the ground state of &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; which dissociates into two ground-state (S-state for &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}$&lt;/span&gt;) atoms: &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(S)+\ce{Li}(S)$&lt;/span&gt;, and an excited state of &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; which dissociates into one ground-satte atom and one excited-state atom: &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(S)+\ce{Li}(P)$&lt;/span&gt;. The long-range potential energy function between the two pieces is given by &lt;span class=&quot;math-container&quot;&gt;$C_3/r^3$&lt;/span&gt; rather than the typical Van der Waals or London dispersion form of &lt;span class=&quot;math-container&quot;&gt;$C_6/r^6$&lt;/span&gt;. The radiative lifetime of the &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(P)$&lt;/span&gt; atoms is given by (see Eq. 37 of the paper, and &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is the excitation energy between &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(S)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}(P)$&lt;/span&gt;, which is similar to what we saw in Cody's answer):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\tau = \frac{3}{4\pi c}\frac{\left(\lambda / 2\pi\right)^3}{C_3}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$C_3$&lt;/span&gt; can be calculated entirely &lt;em&gt;ab initio&lt;/em&gt; as in Eq. 47 of &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.79.062712&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, or you can do an &lt;em&gt;ab initio&lt;/em&gt; calculation of the potential energy curve of an excited state &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; molecule and fit it from there. In this way, &lt;strong&gt;the chemistry of a molecule is used to obtain a fundamental atomic property.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So by taking an excited system (the &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;-state of &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}$&lt;/span&gt; atom in the above exmaple, but it could also be the S1 molecule in your question), and seeing how it interacts with a ground-state version of that system a long distance away, &lt;strong&gt;you can get the radiative lifetime of the excited system.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-03-27T05:36:46.960" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4609" PostTypeId="2" ParentId="4607" CreationDate="2021-03-27T06:19:16.273" Score="9" Body="&lt;h2&gt;Pybel&lt;/h2&gt;&#xA;&lt;p&gt;Pybel is good for this type of task &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/UseTheLibrary/Python_PybelAPI.html&quot; rel=&quot;noreferrer&quot;&gt;https://open-babel.readthedocs.io/en/latest/UseTheLibrary/Python_PybelAPI.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pybel&#xA;global __ATOM_LIST__&#xA; __ATOM_LIST__ = \ &#xA;      ['h',  'he',                                                                                                                                                                                                                                                 &#xA;      'li', 'be', 'b',  'c',  'n',  'o',  'f',  'ne',&#xA;      'na', 'mg', 'al', 'si', 'p',  's',  'cl', 'ar',&#xA;      'k',  'ca', 'sc', 'ti', 'v ', 'cr', 'mn', 'fe', 'co', 'ni', 'cu',&#xA;      'zn', 'ga', 'ge', 'as', 'se', 'br', 'kr',&#xA;      'rb', 'sr', 'y',  'zr', 'nb', 'mo', 'tc', 'ru', 'rh', 'pd', 'ag',&#xA;      'cd', 'in', 'sn', 'sb', 'te', 'i',  'xe',&#xA;      'cs', 'ba', 'la', 'ce', 'pr', 'nd', 'pm', 'sm', 'eu', 'gd', 'tb', 'dy',&#xA;      'ho', 'er', 'tm', 'yb', 'lu', 'hf', 'ta', 'w',  're', 'os', 'ir', 'pt',&#xA;      'au', 'hg', 'tl', 'pb', 'bi', 'po', 'at', 'rn',&#xA;      'fr', 'ra', 'ac', 'th', 'pa', 'u',  'np', 'pu']&#xA;&#xA;mol = pybel.readstring(&amp;quot;smi&amp;quot;, smi)&#xA;numbers = [atom.atomicnum for atom in mol]&#xA;&#xA;def from_number_to_element(i):&#xA;    return __ATOM_LIST__[i-1].capitalize()&#xA;&#xA;names= [ from_number_to_element(i) for i in numbers]&#xA;    &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-03-27T06:19:16.273" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4610" PostTypeId="1" CreationDate="2021-03-27T13:56:32.280" Score="8" ViewCount="619" Body="&lt;p&gt;We use quasi-harmonic approximation using &lt;code&gt;VASP-Phonopy&lt;/code&gt;. In whole calculation we only assume Free energy as function of volume but in case of HCP material which have different coefficient of linear expansion along &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; direction creates a scenario that free energy is function of both volume and c/a ratio. As 'phonopy' doen't have such features to include c/a ratio effect, hence any discussion will be highly appreciated?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-03-27T23:06:10.723" Title="Calculation of linear coefficient of thermal expansion using VASP-Phonopy for Hexagonal material" Tags="|vasp|phonopy|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4611" PostTypeId="1" CreationDate="2021-03-27T14:06:20.323" Score="11" ViewCount="201" Body="&lt;p&gt;When 2D compounds have a dipole, the potential distribution becomes linear (the left panel of the figure). After considering the dipole correction, the potential has two plateau regions in the vacuum (the right panel of the figure), rather than one. How can we determine the vacuum potential from the potential distribution curve? Physically speaking, we can either use the right- or left-side vacuum potential, or average them?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bP5wS.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bP5wS.jpg&quot; alt=&quot;point.1, 2, 47 &amp;amp; 48 are different configurations of the same material with some thermal distortions&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1022" LastEditorUserId="5" LastEditDate="2021-10-19T20:51:03.420" LastActivityDate="2022-01-26T21:40:45.920" Title="Methods to determine the vacuum level in 2D compounds in the presence of dipoles" Tags="|reference-request|solid-state-physics|dipole|vacuum-potential|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4612" PostTypeId="1" AcceptedAnswerId="4643" CreationDate="2021-03-27T16:35:20.693" Score="6" ViewCount="425" Body="&lt;p&gt;I am working on HP workstation with :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;128 GB of RAM&lt;/li&gt;&#xA;&lt;li&gt;INTEL(R) XEON E5-2620 V3 with 12 cores&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;What are the best settings of &lt;code&gt;NCORE&lt;/code&gt;, &lt;code&gt;KPAR&lt;/code&gt;, etc. to speed up calculations on this computer?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="7" LastEditDate="2021-07-30T20:23:31.623" LastActivityDate="2021-07-30T20:23:31.623" Title="What is the best setting for this workstation to speed up VASP calculations?" Tags="|vasp|high-performance-computing|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4613" PostTypeId="2" ParentId="4607" CreationDate="2021-03-27T17:42:30.393" Score="11" Body="&lt;h2&gt;RDKit&lt;/h2&gt;&#xA;&lt;p&gt;This is pretty easy to do in RDKit. If you want the molecular formula, you can just use &lt;code&gt;CalcMolFormula()&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.rdMolDescriptors import CalcMolFormula&#xA;&#xA;# e.g. cysteine&#xA;mol = Chem.MolFromSmiles(&amp;quot;C([C@@H](C(=O)O)N)S&amp;quot;)&#xA;formula = CalcMolFormula(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is also very easy to get all of the unique heteroatoms:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;&#xA;# e.g. cysteine&#xA;mol = Chem.MolFromSmiles(&amp;quot;C([C@@H](C(=O)O)N)S&amp;quot;)&#xA;hetatms = {atom.GetSymbol() for atom in mol.GetAtoms()}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="710" LastActivityDate="2021-03-27T17:42:30.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4614" PostTypeId="2" ParentId="4610" CreationDate="2021-03-27T23:06:10.723" Score="6" Body="&lt;p&gt;You can minimize the free energy F(a,c) as a function of (a,c), which is simply high school math. An example is provided in the section III (A) of the Supplementary Material of Phys. Rev. B 100, 161101(R) (2019):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prb/supplemental/10.1103/PhysRevB.100.161101/supplemental.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prb/supplemental/10.1103/PhysRevB.100.161101/supplemental.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1022" LastActivityDate="2021-03-27T23:06:10.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4615" PostTypeId="1" AcceptedAnswerId="4616" CreationDate="2021-03-28T14:01:48.400" Score="15" ViewCount="2136" Body="&lt;p&gt;I built a supercell of a molecular crystal and wish to write an .xyz file in ASE. How do I do that? The molecule has three different types of elements, C, H, and N.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastActivityDate="2022-10-03T19:06:11.107" Title="How do you write an .xyz file in the Atomic Simulation Environment?" Tags="|crystallography|atomic-simulation-environment|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4616" PostTypeId="2" ParentId="4615" CreationDate="2021-03-28T14:40:32.800" Score="14" Body="&lt;p&gt;Assuming you have an atoms object, all you need to do is call the &amp;quot;write&amp;quot; function.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;&#xA;supercell = Atoms()&#xA;supercell.write(&amp;quot;supercell.xyz&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2021-03-29T15:55:53.067" LastActivityDate="2021-03-29T15:55:53.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4617" PostTypeId="2" ParentId="2172" CreationDate="2021-03-28T17:49:51.713" Score="13" Body="&lt;p&gt;We performed some timing benchmarks as part of our recent paper, albeit not on molecular dynamics:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://doi.org/10.1002/qua.26381&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Assessing conformer energies using electronic structure and machine learning methods&amp;quot; &lt;em&gt;Int J Quantum Chem.&lt;/em&gt; &lt;strong&gt;2020&lt;/strong&gt;; 121:e26381&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/n60fRm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/n60fRm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It was a bit controversial, since we compared single-core CPU times and not in batch mode. Once the ML method runs the model, it's faster - although we saw speedups of ~70-100x for both ML and force field methods.&lt;/p&gt;&#xA;&lt;p&gt;No doubt ML methods are faster on GPU, but tuned force fields are as well.&lt;/p&gt;&#xA;&lt;p&gt;It seems hard to imagine an ML method that's truly &lt;em&gt;&lt;strong&gt;faster&lt;/strong&gt;&lt;/em&gt; than a good implementation of a force field. Most force field terms are intentionally designed to use only a few arithmetic operations (e.g. bonding terms require distance and a harmonic potential). As such, they can be highly optimized for both GPU and CPU implementations.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, ML methods can clearly do a more accurate job with empirically fitting  (e.g, non-bonded interactions). I suspect more hybrid methods will appear over time.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-03-28T17:49:51.713" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4618" PostTypeId="1" CreationDate="2021-03-28T23:34:02.763" Score="15" ViewCount="694" Body="&lt;p&gt;I am trying to take into account periodic boundary conditions for non-orthorhombic unit cells.&lt;/p&gt;&#xA;&lt;p&gt;I have the atomic coordinates for a monoclinic super cell with the following lattice vectors output by the Atomic Simulation Environment:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Lattice=&amp;quot;32.816 0.0 0.0 0.0 32.976 0.0 -5.5906912278125445 0.0 31.38596137758504&amp;quot;&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;which I take to be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;A1 = [32.816, 0.0, 0.0];&#xA;B1 = [0.0, 32.976, 0.0];&#xA;C1 = [-5.5906912278125445, 0.0, 31.38596137758504];&#xA;h = [A1;B1;C1];&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By multiplying the position vectors by the inverse of the matrix &lt;code&gt;h&lt;/code&gt;, I took a coordinate transformation to obtain fractional coordinates, and now am trying to incorporate the minimum image convention:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DX = DX - floor(DX);&#xA;DY = DY - floor(DY);&#xA;DZ = DZ - floor(DZ);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;before doing the back transform and then calculating distance in the standard way.&lt;/p&gt;&#xA;&lt;p&gt;Here the lattice is not quite 0 to L due to the value of -5.5906912278125445 in one of the dimensions, and the coordinate transformation preserves this discrepancy when converting everything to fractional coordinates, i.e., DX, DY, and DZ are not 0-1. How do I incorporate the minimum image convention in this case? I'd be grateful for some insight about how to do this properly!&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorDisplayName="user2026" LastEditDate="2021-04-03T14:53:21.407" LastActivityDate="2023-09-18T16:07:53.150" Title="Minimum image convention for non-orthorhombic unit cells" Tags="|molecular-dynamics|crystallography|periodic-boundary-conditions|minimum-image-convention|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4619" PostTypeId="2" ParentId="4291" CreationDate="2021-03-29T03:28:28.717" Score="5" Body="&lt;p&gt;I was able to figure out what was going wrong, but forgot to check back here and leave an answer if none were give.&lt;/p&gt;&#xA;&lt;p&gt;@ShoubhikRMaiti should be credited with helping me figure this out. From this comment&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Also, may I ask why you are using fully numeric differentiation? U-BLYP has analytic hessian programmed into the code.&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I was curious to try removing this from the input card to see if that resolved the issue. That is exactly what was needed. I can't explain it, but if fully numerical differentiation is used for the Hessian it will not print out infrared intensities along with the vibrational frequencies.&lt;/p&gt;&#xA;" OwnerUserId="65" LastActivityDate="2021-03-29T03:28:28.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4620" PostTypeId="2" ParentId="3610" CreationDate="2021-03-30T04:39:22.763" Score="8" Body="&lt;p&gt;The main advantage that MD has is that alot more people have worked on algorithm efficiency. The state of the art codes for MD are really state of the art. Monte Carlo algorithms are fairly primitive in comparison, and many folks just write their own codes.&lt;/p&gt;&#xA;&lt;p&gt;Monte Carlo is better at sampling because it need not follow Newton's equations of motion. If a molecule is stuck in a potential energy well, it may not change conformation for a long time in MD, but MC could flip the torsion barrier with ease.&lt;/p&gt;&#xA;&lt;p&gt;A point that I hold dear to my heart is that it isn't that MC and MD yield the same, correct results, for ergodic systems, but rather, MC is always right, and MD is correct for ergodic systems.&lt;/p&gt;&#xA;&lt;p&gt;A huge advantage for molecular dynamics is that it is easily parallelizable(MC is only trivially parallelizable). Every step in MD, each atom must have its forces computed, and this can be done in parallel. In Monte Carlo, you are generally only moving one particle at a time. The cost per move is lower, but you must wait until one move is done before another particle is moved (you can move multiple particles at a time, but, you end up failing a high % of moves).&lt;/p&gt;&#xA;&lt;p&gt;Another advantage of molecular dynamics is sampling complex molecules. I know I said MC samples better, but for really large molecules it gets hard to sample, for instance, torsional rotations, since a rotation in the center of the molecule would swing its end points really far out and guaranteed result in a failed move. There are clever algorithms to get around this, but it is ridiculously simple in MD. You have to be very clever in MC.&lt;/p&gt;&#xA;&lt;p&gt;One thing that is a disadvantage for MD is using barostats and thermostats. Keeping Temperature and/or pressure constant in MC is rediculously simple, and actually very hard in MD. People joke that MD is just solving Newton's equations of motion, which is a first year physics problem. That is only true in the constant energy ensemble. Once you have to keep temperature constant and/or pressure, the algorithms quickly escalate. The simple algorithms rarely yield the rigorously correct ensemble, thus, you need the more complicated ones.&lt;/p&gt;&#xA;&lt;p&gt;In the end, for simple systems both MC and MD are simple. For simple systems at constant temperature and pressure, MD is harder due to the thermostats and barostats. For complex molecules MD is easier since you don't need complex regrowth/configurational bias/advanced torsion sampling algorithms. I don't know what is harder to truly understand, thermostats/barostats or complex molecule sampling in MC.&lt;/p&gt;&#xA;&lt;p&gt;IN the current state of the field, the hard brain work is done for us if we use MD. This is not so much the case for MC, and MC algorithms, if they do some of the advanced sampling, are usually written by people who are first scientists, second coders, so they are not all that fast. GROMACS, for instance, is  blazing fast, because it has had a team of people working for decades now on making it fast.&lt;/p&gt;&#xA;&lt;p&gt;I will add some references to this. For instance Jorgensen has found that for complex molecules MC is pound for pound more efficient, but, his program is not free.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2021-03-30T04:39:22.763" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4621" PostTypeId="1" AcceptedAnswerId="4640" CreationDate="2021-03-30T09:10:21.400" Score="9" ViewCount="118" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3849/deepmind-just-announced-a-breakthrough-in-protein-folding-what-are-the-conseque&quot;&gt;It seems&lt;/a&gt; that the prediction of protein folding is a pretty advanced area. Are there options based on some &lt;a href=&quot;https://en.wikipedia.org/wiki/Global_distance_test&quot; rel=&quot;nofollow noreferrer&quot;&gt;GDT&lt;/a&gt;-like measure? For me, it has relevance in connection with the origin of life (cf. &lt;a href=&quot;https://en.wikipedia.org/wiki/RNA_world&quot; rel=&quot;nofollow noreferrer&quot;&gt;RNA world&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="2292" LastEditorUserId="5" LastEditDate="2021-04-17T20:38:36.003" LastActivityDate="2021-04-17T20:38:56.130" Title="What software is a software for RNA tertiary structure prediction?" Tags="|software|one-topic-per-answer|software-recommendations|structural-biology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4622" PostTypeId="1" AcceptedAnswerId="4627" CreationDate="2021-03-30T10:16:21.243" Score="10" ViewCount="388" Body="&lt;p&gt;Is there an ab-initio calculation of electronic structure that does not involve self-consistent iteration?&#xA;What I mean by self-consistent iteration is the iteration to solve the equation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{y} = \mathbf{f}(\mathbf{y}, p),&#xA;$$&lt;/span&gt;&#xA;for some parameters &lt;span class=&quot;math-container&quot;&gt;$\mathbf{y}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="882" LastEditorUserId="5" LastEditDate="2021-03-30T16:52:31.613" LastActivityDate="2021-04-05T20:08:37.603" Title="Electronic structure calculations without SCF?" Tags="|ab-initio-calculations|self-consistent-field|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4623" PostTypeId="2" ParentId="4593" CreationDate="2021-03-30T12:15:15.827" Score="6" Body="&lt;p&gt;It seems you are looking for a package to compute the irreducible representation of electronic states computed by VASP. This has been recently developed:&lt;/p&gt;&#xA;&lt;p&gt;J. Gao J, Wu Q, Persson C, Z. Wang. Irvsp: to obtain irreducible representations of electronic states in the VASP. Comput. Phys. Comm. 261, 107760 (2021). &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2020.107760&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.cpc.2020.107760&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;And the code is provided on github: &lt;a href=&quot;https://github.com/zjwang11/irvsp&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/zjwang11/irvsp&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2237" LastActivityDate="2021-03-30T12:15:15.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4625" PostTypeId="1" CreationDate="2021-03-30T14:33:10.503" Score="9" ViewCount="2564" Body="&lt;p&gt;I'm performing MD simulations, using NPT ensemble. The problem is that the pressure fluctuates severely and doesn't average at required level.&lt;/p&gt;&#xA;&lt;p&gt;For example, I set the pressure at 1 bar and it averages around -60 bar jumping from -500 to 500 bar during the run.&lt;/p&gt;&#xA;&lt;p&gt;I'm using Parrinello-Rahman barostat with &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; parameter equal to 20 ps. I've tried to adjust &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;, but nothing changed.&lt;/p&gt;&#xA;&lt;p&gt;Here is the part of mdp file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Pcoupl                   = Parrinello-Rahman&#xA;Pcoupltype               = isotropic&#xA;tau_p                    = 20&#xA;compressibility          = 3e-5&#xA;ref_p                    = 1.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is this an important thing to consider if density and temperature looks OK?&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="7" LastEditDate="2021-04-04T01:39:20.733" LastActivityDate="2021-04-04T01:39:20.733" Title="Large pressure fluctuations in molecular dynamics" Tags="|molecular-dynamics|gromacs|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4627" PostTypeId="2" ParentId="4622" CreationDate="2021-03-30T16:51:37.190" Score="11" Body="&lt;p&gt;Yes! The Schroedinger equation for a molecule is just a differential equation, so you can solve it numerically &amp;quot;on a grid&amp;quot; or in &amp;quot;real-space&amp;quot;, and there is a review paper on the topic: &amp;quot;&lt;a href=&quot;https://pubs.rsc.org/en/journals/articlecollectionlanding?sercode=cp&amp;amp;themeid=965b361c-f995-4ff6-9c3d-93801c039a55.&quot; rel=&quot;noreferrer&quot;&gt;Real-space numerical grid methods in quantum chemistry&lt;/a&gt;&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;You can also simply model the wavefunction &lt;span class=&quot;math-container&quot;&gt;$|\psi\rangle$&lt;/span&gt; with some formula, and estimate the energy using:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;E \le \frac{\langle \psi | \hat{H} | \psi \rangle}{\langle \psi| \psi \rangle },&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and keep adjusting the parameters in your model for &lt;span class=&quot;math-container&quot;&gt;$|\psi \rangle$&lt;/span&gt; until your estimate of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; no longer gets lower. This is called the &amp;quot;variational method&amp;quot; and does not require a self-consistent-(mean)field.&lt;/p&gt;&#xA;&lt;p&gt;Every example in the following answers, uses the variational method without an &amp;quot;SCF&amp;quot; calculation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/555/5&quot;&gt;How accurate are the most accurate calculations?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2306/5&quot;&gt;High precision helium energy&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3889/5&quot;&gt;Are there examples of ab initio predictions on small molecules without the &amp;quot;major approximations&amp;quot;?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The list may grow, without anyone remembering to add new examples to this answer, so I recommend you look at the &lt;a href=&quot;/questions/tagged/high-precision&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;high-precision&amp;#39;&quot; rel=&quot;tag&quot;&gt;high-precision&lt;/a&gt; tag!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-03-30T16:51:37.190" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4628" PostTypeId="1" CreationDate="2021-03-30T17:19:49.300" Score="11" ViewCount="142" Body="&lt;p&gt;In &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1367-2630/18/8/083047&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper (open access), the authors used Fourier series with most general wave equation to find the dispersion relation. I am presenting some main equations as snippets to depict their solution. We want to solve for &lt;span class=&quot;math-container&quot;&gt;$u(x,t)$&lt;/span&gt; in the following wave equation (Eq. (1) in the paper):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{1}&#xA;\frac{\partial}{\partial x}\left[ E(x,t)\frac{\partial}{\partial x} u(x,t) \right]-\frac{\partial}{\partial t}\left[ \rho(x,t)\frac{\partial}{\partial t} u(x,t) \right]=0.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So we expand or represent the quantities using Fourier series:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2} E(x,t)=\sum_{p=-\infty}^\infty E_{p}e^{ip(\omega_mt-k_mx)}, $$&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3} \rho(x,t)=\sum_{p=-\infty}^\infty \rho_{p}e^{ip(\omega_mt-k_mx)}, $$&lt;/span&gt;&#xA;both having periodicty of &lt;span class=&quot;math-container&quot;&gt;$\omega_m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_m$&lt;/span&gt; for time and space.&#xA;Now we assume a general solution (Floquet form) for &lt;span class=&quot;math-container&quot;&gt;$u(x,t)$&lt;/span&gt; as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4} u(x,t)=e^{i(\omega t-kx)} \sum_{n=-\infty}^\infty u_{n}e^{in(\omega_mt-k_mx)}, $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and plug everything in the wave-equation. The authors say that using orthogonality we directly have the equation (9 in the paper):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5} \sum_{n=-\infty}^\infty [(k+nk_m)(k+pk_m)]E_{p-n}u_n = \sum_{n=-\infty}^\infty [(\omega+n\omega_m)(\omega+p\omega_m)]\rho_{p-n}u_n.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then they say that it can be &amp;quot;&lt;strong&gt;recast&lt;/strong&gt;&amp;quot; in the form (Eq. 11 in paper):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{6} (\omega^2 \hat{L}_2 + \omega \hat{L}_1 + \hat{L}_0)\vec{u}=0, $$&lt;/span&gt;&#xA;which is a matrix equation in &lt;span class=&quot;math-container&quot;&gt;$\vec{u}$&lt;/span&gt;  and connects &lt;span class=&quot;math-container&quot;&gt;$u_n$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$u_{n−1}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$u_{n+1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;How can Eq. 5 be cast in Eq. 6 given that Eq. 5 does not have a relation between &lt;span class=&quot;math-container&quot;&gt;$u_n$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$u_{n−1}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$u_{n+1}$&lt;/span&gt;? It only has two independent sums on both sides. They do not have different phases on both side to shift a phase term and take common summation to relate these.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="287" LastEditorUserId="5" LastEditDate="2021-10-30T20:19:52.117" LastActivityDate="2021-10-30T20:19:52.117" Title="How to solve general wave equation and dispersion relation using Fourier series?" Tags="|mathematical-modeling|from-phys-se|plane-waves|reproducing-data-from-papers|fourier-transform|" AnswerCount="0" CommentCount="2" ClosedDate="2022-01-11T20:37:20.163" ContentLicense="CC BY-SA 4.0" />
  <row Id="4629" PostTypeId="2" ParentId="4622" CreationDate="2021-03-30T17:46:03.393" Score="8" Body="&lt;p&gt;One can solve SCF-like problems (e.g. KS-DFT/HF) by directly minimizing the energy with respect to the MO coefficients, rather than actually performing self-consistent iterations. This was done recently in &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c00772&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 2021, 17, 1, 151–169&lt;/a&gt;, where they modeled the energy landscape (distribution of minima and saddle points) for &lt;span class=&quot;math-container&quot;&gt;$\ce{H4}$&lt;/span&gt;. The trick to this, as described in the paper, is finding an appropriate parameterization of the MO coefficients such that your minimization procedure is always moving among feasible solutions. This sort of optimization is one way in which you can find a higher energy SCF minima, which have been used as starting points for calculating excited states of a molecule.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-03-30T17:46:03.393" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4630" PostTypeId="2" ParentId="4580" CreationDate="2021-03-31T04:06:05.467" Score="9" Body="&lt;p&gt;So, with a lot of tries and errors I've found out how to perform such analysis. I'm using a library for Python called MDAnalysis. It can load Gromacs topologies and extract charges from them. Using them dipole moment for each molecule can be easily calculated and ordering parameters can be calculated from it.&lt;/p&gt;&#xA;&lt;p&gt;Here is the code. It may not be perfect, but it gives &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;\cos \theta&amp;gt;$&lt;/span&gt; values consistent with the literature.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import MDAnalysis as md&#xA;import numpy as np&#xA;&#xA;u=md.Universe('topol.top', '50ns/dr1.pdb', topology_format='ITP')&#xA;&#xA;mean_cos_theta = []&#xA;mean_cos3_theta = []&#xA;&#xA;z_unit = np.array([0,0,1])&#xA;&#xA;for ts in u.trajectory:&#xA;    mean_cos_theta_frame = []&#xA;    mean_cos3_theta_frame = []&#xA;    for res in u.residues:&#xA;        dipole_moment = np.array([0,0,0])&#xA;&#xA;        for atom in res.atoms:&#xA;            dipole_moment = dipole_moment + atom.charge*atom.position&#xA;        &#xA;        cos_theta = np.dot(z_unit, dipole_moment)/np.linalg.norm(dipole_moment)&#xA;        mean_cos_theta_frame.append(cos_theta)&#xA;        mean_cos3_theta_frame.append(cos_theta**3)&#xA;        &#xA;    mean_cos_theta.append(np.mean(mean_cos_theta_frame))&#xA;    mean_cos3_theta.append(np.mean(mean_cos3_theta_frame))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="1432" LastEditDate="2021-04-15T03:27:36.947" LastActivityDate="2021-04-15T03:27:36.947" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4632" PostTypeId="1" AcceptedAnswerId="4637" CreationDate="2021-03-31T15:22:47.277" Score="7" ViewCount="272" Body="&lt;p&gt;I have ran a Nudged Elastic Band (NEB) calculation using QuantumEspresso through &lt;strong&gt;Maestro&lt;/strong&gt; to find the potential transition state. Within Maestro there is an option where you can select for NEB type calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KZreX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KZreX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I used 5 images altogether (1 reactant, 1 product, and 3 extrapolated images). I believe that one of the output images (the third one specifically)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zmd9T.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zmd9T.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;is the transition state. However, from my understanding, to verify this is indeed the transition state, one must calculate the vibrational frequency to determine whether there is one negative (hence imaginary) frequency as this indicate that I have a first order saddle point.&lt;/p&gt;&#xA;&lt;h3&gt;How do I do this frequency analysis within Maestro?&lt;/h3&gt;&#xA;&lt;p&gt;Is there an option where I can quickly select one of the output images and run a frequency analysis on it?&lt;/p&gt;&#xA;&lt;p&gt;I have poke around a bit and found that there is an option to do a &lt;strong&gt;phonon&lt;/strong&gt; calculation, is this the right thing to do?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XJpD9.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XJpD9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I just want to determine whether one of the image I have is a transition state. So if there are other ways to do this, I am all ear!&lt;/p&gt;&#xA;&lt;p&gt;Thank you for you time.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disclaimer:&lt;/strong&gt; I am no computational chemist nor an expert with Maestro. So forgive me if whatever I said is wrong and what I asked is naive.&lt;/p&gt;&#xA;" OwnerUserId="1711" LastActivityDate="2021-04-01T13:57:38.950" Title="Vibrational frequency analysis for NEB result through Maestro" Tags="|quantum-espresso|computational-chemistry|quantum-chemistry|transition-state|schrodinger-software|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4633" PostTypeId="1" CreationDate="2021-04-01T06:22:18.383" Score="12" ViewCount="297" Body="&lt;p&gt;I need to simulate a salt diluted in a liquid electrolyte. My experience is with LAMMPS, but so far I only had coarse grained toy models, and setting up the force field was straightforward. Now I have a real molecule (&amp;gt;20 atoms), which I optimized quantum mechanically with MP2 and I have tried to run various tools to automatically get the parameters: VMD/topotool, ATB+moltemplate. Nothing really works and I need to tweak too many parameters by hand. So I am wondering whether or not to use an all-atoms MD software such as Amber or Gromacs. Which force field would be the best candidate for my study case considering the physical system? which one is more easy to use when it comes to infer the force field from QM results?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2021-04-06T18:21:59.960" Title="What is the most appropriate (and easy-to-use) all-atoms force field for liquid electrolytes?" Tags="|molecular-dynamics|computational-chemistry|forcefields|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4634" PostTypeId="2" ParentId="4633" CreationDate="2021-04-01T10:49:46.417" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Which force field would be the best candidate for my study case considering the physical system?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The &lt;strong&gt;O&lt;/strong&gt;ptimized &lt;strong&gt;P&lt;/strong&gt;otentials for &lt;strong&gt;L&lt;/strong&gt;iquid &lt;strong&gt;S&lt;/strong&gt;imulations (OPLS) force field can be a possible solution. It was developed with liquids in mind. The main developer is professor &lt;a href=&quot;https://chem.yale.edu/people/william-jorgensen&quot; rel=&quot;noreferrer&quot;&gt;William Jorgensen&lt;/a&gt;, from Yale University.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;which one is more easy to use when it comes to infer the force field from QM results?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I cannot answer this question directly because I never did such calculations, but the functional form looks straight forward to be parametrized from QM calculations.&#xA;A rapid information can be obtained from the Wiki &lt;a href=&quot;https://en.wikipedia.org/wiki/OPLS&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt; and details about it from the reporting paper:&lt;/p&gt;&#xA;&lt;p&gt;William L. Jorgensen, David S. Maxwell, and Julian Tirado-Rives. Development and &lt;em&gt;Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids&lt;/em&gt; J. Am. Chem. Soc. 118 (45): 11225–11236 (1996). DOI: &lt;a href=&quot;https://doi.org/10.1021/ja9621760&quot; rel=&quot;noreferrer&quot;&gt;10.1021/ja9621760&lt;/a&gt;. CiteSeerX &lt;a href=&quot;https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.334.2959&quot; rel=&quot;noreferrer&quot;&gt;10.1.1.334.2959&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-01T10:49:46.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4635" PostTypeId="1" CreationDate="2021-04-01T11:02:41.743" Score="13" ViewCount="1930" Body="&lt;p&gt;A group of researchers in my university (including me), started to study the possibility to move to cloud computing services in order to run our simulations.&lt;/p&gt;&#xA;&lt;p&gt;The simulation areas include condensed matter physics, particle physics, quantum field theory, soft condensed matter, statistical physics, etc.&lt;/p&gt;&#xA;&lt;p&gt;We have zero experience with it.&lt;/p&gt;&#xA;&lt;p&gt;The question is: &lt;strong&gt;Are there reliable cloud computing services for matter modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;By reliable, I mean that their performance (CPU/GPU use, RAM use, hard drive speed) is similar to a local computer, with lower degradation (as many of them use virtual machines).&#xA;As the demands are very heterogeneous, at first glance, we are thinking in bare iron system in order to install/configure different software for running the simulations. About the hardware, it is desirable to have both CPUs and GPUs access.&lt;/p&gt;&#xA;&lt;p&gt;To distinguish this question from these ones:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1515/5&quot;&gt;Supercomputers around the world&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1613/5&quot;&gt;Supercomputers around the world, which allow access for researchers outside the country&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;where access is usually not just granted to anyone who pays for it, perhaps you can suggest commercial services here.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="85" LastEditDate="2021-06-03T12:21:09.173" LastActivityDate="2021-06-26T03:14:57.767" Title="What are some cloud services for computing?" Tags="|one-topic-per-answer|high-performance-computing|cloud-computing|" AnswerCount="5" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4636" PostTypeId="2" ParentId="4635" CreationDate="2021-04-01T12:12:21.183" Score="11" Body="&lt;h1&gt;Materials Square (MatSQ)&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.materialssquare.com/&quot; rel=&quot;noreferrer&quot;&gt;Materials Square (MatSQ)&lt;/a&gt; is a web-based simulation platform providing an interface, workflow, and  pay-as-you-go cloud server for material simulations. It supports DFT, MD and CALPHAD calculations.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Provides a free 3D atomic structure-modeling interface supporting most structure types.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3keel.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3keel.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Support density functional theory calculations of Electronic Structure, Phonon, reaction path and optical properties using Quantum ESPRESSO.&lt;/li&gt;&#xA;&lt;li&gt;MD simulations include a GUI for LAMMPS and can analyze physical movements of atoms at finite temperature, thermal, optical and mechanical properties.&lt;/li&gt;&#xA;&lt;li&gt;Pricing ranges from pay-per-use of $0.25 per core hour to UNLIMITED plans.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vQgJE.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vQgJE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://beta.materialssquare.com/wp-content/uploads/2020/11/catalog-materials-square-2020-nov-web.pdf&quot; rel=&quot;noreferrer&quot;&gt;Materials Square Brochure&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastActivityDate="2021-04-01T12:12:21.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4637" PostTypeId="2" ParentId="4632" CreationDate="2021-04-01T13:57:38.950" Score="4" Body="&lt;p&gt;Based on what you have said, a phonon calculation is likely what you want.  You should see imaginary frequencies in the output if you do infact have a transition state.  You may need stricter convergence for the phonon calculation than the geometry relaxation.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-04-01T13:57:38.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4638" PostTypeId="1" AcceptedAnswerId="4642" CreationDate="2021-04-01T16:15:19.847" Score="6" ViewCount="651" Body="&lt;p&gt;I am wondering what is the meaning of &lt;code&gt;EATOM&lt;/code&gt; tag in the &lt;code&gt;POTCAR&lt;/code&gt; files of VASP. What is its relationship with the energy of an isolated atom ? is it the same ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-04-02T03:54:49.400" Title="What is the meaning of EATOM tag in the POTCAR files of VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4639" PostTypeId="2" ParentId="4635" CreationDate="2021-04-01T16:25:48.090" Score="10" Body="&lt;p&gt;&lt;strong&gt;Amazon Web Services (AWS)&lt;/strong&gt; and &lt;strong&gt;Google Cloud&lt;/strong&gt; can be used for the running simulations and I've used both. I applied to a few grant programs a while back where part of the award included AWS or Google Cloud credits. I think the credits were donated to the funding agencies by the respective companies to encourage more use of those services in science and engineering.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, it was pretty easy to put together an environment to run LAMMPS on both these services. The cores themselves were not that fast, but the environments were well suited for running &lt;strong&gt;replica exchange&lt;/strong&gt; calculations with large numbers of replicas (50 to hundreds). The communication between the &amp;quot;virtual CPUs (vCPUs)&amp;quot; was sufficiently fast that I didn't see any performance degradation between serial runs and replica exchange. That said, exchanges were only attempted every 1000 steps (~3 minutes of real time) in my simulations, so communication would have had to be really slow to see a major impact.&lt;/p&gt;&#xA;&lt;p&gt;I haven't used them since preparing the those grant applications since the cost seemed somewhat high compared to buying a workstation computer and running it for years.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-04-01T16:32:56.483" LastActivityDate="2021-04-01T16:32:56.483" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4640" PostTypeId="2" ParentId="4621" CreationDate="2021-04-01T16:39:08.607" Score="6" Body="&lt;h3&gt;Rosetta&lt;/h3&gt;&#xA;&lt;p&gt;The protein modeling program &lt;strong&gt;Rosetta&lt;/strong&gt; includes RNA structure prediction functionality. I think the most up-to-date tool is the &lt;a href=&quot;https://new.rosettacommons.org/docs/latest/FARFAR2&quot; rel=&quot;nofollow noreferrer&quot;&gt;FARFAR2 protocol&lt;/a&gt;. You can try it out through the &lt;a href=&quot;https://rosie.rosettacommons.org/farfar2/submit&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rosie FARFAR2 server&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="5" LastEditDate="2021-04-17T20:38:56.130" LastActivityDate="2021-04-17T20:38:56.130" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4641" PostTypeId="2" ParentId="4625" CreationDate="2021-04-01T17:33:50.367" Score="7" Body="&lt;p&gt;&lt;strong&gt;Large pressure fluctuations are normal for nanoscale simulations of aqueous solutions (and other condensed systems without a gas phase).&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Pressure fluctuations are usually enormous in simulations of aqueous solutions because water is nearly incompressible.&lt;/p&gt;&#xA;&lt;p&gt;Let's say your system is a cube of water &lt;span class=&quot;math-container&quot;&gt;$(2~\mathrm{nm})^3$&lt;/span&gt;. Smaller systems will have larger fluctuations. At equilibrium, the variance of the pressure (its &lt;a href=&quot;https://en.wikipedia.org/wiki/Thermal_fluctuations&quot; rel=&quot;nofollow noreferrer&quot;&gt;fluctuation&lt;/a&gt;) is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\sigma_P^2 = -kT \left( \frac{\partial P}{\partial V} \right)_S = \frac{kT}{\kappa_S V},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\kappa_S$&lt;/span&gt; is the isentropic compressibility.&#xA;&lt;a href=&quot;https://en.wikipedia.org/wiki/Compressibility&quot; rel=&quot;nofollow noreferrer&quot;&gt;The isentropic compressibility is related&lt;/a&gt; to the density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and speed of sound (&lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;) by &lt;span class=&quot;math-container&quot;&gt;$\kappa_S = 1/(\rho c^2)$&lt;/span&gt;, so&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}\sigma_P^2 = \frac{\rho c^2 k T}{V}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The standard deviation of the pressure should then be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}\sigma_P = \sqrt{\frac{\rho c^2 k T}{V}}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Taking the values for water near standard conditions &lt;span class=&quot;math-container&quot;&gt;$\rho=997~\mathrm{kg/m^3}, c=1500~\mathrm{m/s}, T=298.15~\mathrm{K}$&lt;/span&gt; and using GNU units,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;units 'sqrt(997*kg/m^3*(1500*m/s)^2*k*298*K/((2*nm)^3))' 'bar'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get &lt;span class=&quot;math-container&quot;&gt;$\sigma_P \approx 340~\mathrm{bar}$&lt;/span&gt;. So the fluctuation of &lt;span class=&quot;math-container&quot;&gt;$\pm500~\mathrm{bar}$&lt;/span&gt; is pretty reasonable.&lt;/p&gt;&#xA;&lt;p&gt;You say you get a mean pressure of &lt;span class=&quot;math-container&quot;&gt;$-60~\mathrm{bar}$&lt;/span&gt;. What is the uncertainty in that calculation? The uncertainty of the mean pressure can be estimated by&#xA;&lt;span class=&quot;math-container&quot;&gt;$\delta P = \sigma_P/\sqrt{N}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of independent data points for the pressure. So the number of independent (uncorrelated) data points you need to get to get the uncertainty &lt;span class=&quot;math-container&quot;&gt;$\delta P &amp;lt; 60~\mathrm{bar}$&lt;/span&gt; is given by &lt;span class=&quot;math-container&quot;&gt;$N=\sigma_P^2/\delta P^2 \approx 30$&lt;/span&gt;. How long was your simulation? What is the autocorrelation time of the pressure (which determines the number of independent pressure values you have).&lt;/p&gt;&#xA;&lt;p&gt;My guess is that your results are statistically consistent with a mean pressure of &lt;span class=&quot;math-container&quot;&gt;$1~\mathrm{bar}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, for most molecular interactions in water, pressure–volume work (&lt;span class=&quot;math-container&quot;&gt;$p~\mathrm{d}V$&lt;/span&gt;) is negligible, so you don't have to worry much about the exact pressure as long as you don't have any weird vacuum bubbles that sometimes appear in simulations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Aside:&lt;/strong&gt; You might say, I'm using a barostat, shouldn't it force the pressure be constant? First, you have to realize that the instantaneous pressure is not well-defined and there isn't a unique way to calculate it. Some barostats might make some measures of instantaneous pressure constant, but this isn't true for the barostat I usually use. The likewise is true for thermostats. Instantaneous temperature is usually calculated from the average kinetic energy of a single simulation frame, which doesn't necessarily correspond to the thermodynamic temperature. Consider that a system with no momentum degrees of freedom (and no kinetic energy) can still have a thermodynamic temperature (e.g. the Ising model).&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-04-02T17:38:13.697" LastActivityDate="2021-04-02T17:38:13.697" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4642" PostTypeId="2" ParentId="4638" CreationDate="2021-04-02T03:54:49.400" Score="2" Body="&lt;p&gt;&lt;code&gt;EATOM&lt;/code&gt; is not considered as energy of isolated atom, you can check energy by taking large (10x10x10) simulation box. This tag has no use for general user as this is mainly used by developers during pseudo-potential creation.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-04-02T03:54:49.400" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4643" PostTypeId="2" ParentId="4612" CreationDate="2021-04-02T05:44:16.147" Score="4" Body="&lt;p&gt;How to choose these parameters is dependent on your system, which may need to test to find the most optimized computational strategy.&lt;/p&gt;&#xA;&lt;p&gt;Here is a good tutorial to talk about these setting: &lt;a href=&quot;https://www.nsc.liu.se/support/Events/VASP_workshop_2020/seminar3.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nsc.liu.se/support/Events/VASP_workshop_2020/seminar3.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;NCORE:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/K8BPh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/K8BPh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;NPAR:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tgZDo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tgZDo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;KPAR:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mFn1x.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mFn1x.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-02T05:44:16.147" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4644" PostTypeId="1" CreationDate="2021-04-02T06:40:11.383" Score="3" ViewCount="183" Body="&lt;p&gt;I have downloaded the diglyme molecule from the ATB server (&lt;a href=&quot;http://atb.uq.edu.au/molecule.py?molid=34570#panel-md&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://atb.uq.edu.au/molecule.py?molid=34570#panel-md&lt;/a&gt;)&#xA;Two files are available: a PDB file and a topology ITP/RTP file.&#xA;The name of the molecule is 9AZR, and so is called the residue in the topology file.&#xA;Unfortunately there is not a forum/manual yet from ATB.&lt;/p&gt;&#xA;&lt;p&gt;I would like to use these to run in GROMACS but I am pretty confused since the 9AZR residue in unknown.&#xA;$ gmx pdb2gmx -f atb.pdb&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...&#xA;Fatal error: &amp;gt; Residue '9AZR' not found in residue topology database&#xA;…&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Other molecules, respectively 348621 and 705000, will contain UYKS and PEZE as “residue”.&#xA;None of this is recognized by pdb2gmx from GROMACS.&#xA;Shall I define them myself? Or shall I specify their value/reference database?&#xA;Could I find some explanatory material/tutorial on this subject?&lt;/p&gt;&#xA;&lt;p&gt;I found this previous discussion very useful: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4341/finding-parameters-for-a-molecule-in-various-forcefields&quot;&gt;Finding parameters for a molecule in various forcefields&lt;/a&gt;&#xA;especially for suggesting LigParGen as a way around: &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://zarbi.chem.yale.edu/ligpargen/&lt;/a&gt;&#xA;but this will work only for limited cases (OPLS-AA) and ultimately I would like to understand what I am getting wrong here, since GROMACS is supposed to be the native FF ATB was meant to.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your support&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2021-04-02T11:32:55.357" Title="Missing residues in ATB downloaded pdb/rtp files" Tags="|molecular-dynamics|gromacs|forcefields|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4645" PostTypeId="1" AcceptedAnswerId="4647" CreationDate="2021-04-02T07:10:36.093" Score="4" ViewCount="857" Body="&lt;p&gt;The figure below shows the spin density isosurfaces of 3x3x1 ScS2 monolayer supercell doped with Mn atoms. This figure was generated using &lt;code&gt;VASPKIT&lt;/code&gt; and &lt;code&gt;VESTA&lt;/code&gt;, with an isosurface level of 0.001 electron/Angstrom&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How to interpret this figure below? And what is the meaning of the blue and yellow color around atoms?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CiBwM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CiBwM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-04-02T12:14:08.413" LastActivityDate="2021-04-02T12:25:27.710" Title="How to interpret spin density isosurface figures?" Tags="|density-functional-theory|vasp|spin|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4646" PostTypeId="2" ParentId="4644" CreationDate="2021-04-02T11:32:55.357" Score="1" Body="&lt;p&gt;The error is due that &lt;em&gt;9AZR&lt;/em&gt; is not a standard residue name.&lt;/p&gt;&#xA;&lt;p&gt;I recommend you to use the web services &lt;a href=&quot;https://charmm-gui.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;CHARMM-GUI&lt;/a&gt;. In the left menu, go to Input Generator. There you can generate the topology file as well the input files for different molecular dynamics software (including NAMD, GROMACS, etc.)&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-02T11:32:55.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4647" PostTypeId="2" ParentId="4645" CreationDate="2021-04-02T12:25:27.710" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How to interpret this figure below? And what is the meaning of the blue and yellow color around atoms?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This figure basically tells you the probability that you can find spin-up and spin-down electrons. If I assume the yellow color represents the spin-up electrons, then the blue color (seems like cyan) will represent spin-down electrons. From your figure, we can see the spin-up electrons are dominant and the spin-down electrons are ignorable, which means you obtain a 2D FM monolayer.&lt;/p&gt;&#xA;&lt;p&gt;You may take a look at this paper: &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2017/TC/C7TC02664A#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2017/TC/C7TC02664A#!divAbstract&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RXnqK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RXnqK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-02T12:25:27.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4648" PostTypeId="2" ParentId="4477" CreationDate="2021-04-02T19:01:31.653" Score="1" Body="&lt;p&gt;&lt;strong&gt;ASE&lt;/strong&gt; can be used to achieve what you require. Basically we need to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Read the structure.&lt;/li&gt;&#xA;&lt;li&gt;Determine the molecules using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/neighborlist.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;neighborlist&lt;/a&gt; class in ASE.&lt;/li&gt;&#xA;&lt;li&gt;Sort each of the molecules in the required manner using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html#ase.build.sort&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.build.sort&lt;/code&gt;&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The following code does this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase.io import read, write&#xA;from ase import Atoms, neighborlist&#xA;from ase.build import sort&#xA;from scipy import sparse                                                   &#xA;&#xA;acetonitrile = read(&amp;quot;acetonitrile.cif&amp;quot;) # Read the structure&#xA;&#xA;# Determine the indices of each molecule using neighborlists&#xA;cutoff = neighborlist.natural_cutoffs(acetonitrile)&#xA;nl = neighborlist.build_neighbor_list(acetonitrile, cutoffs=cutoff)&#xA;connmat = nl.get_connectivity_matrix(False) # Connectivity matrix&#xA;# n_components contains number of molecules&#xA;# component_list contains molecule number of each atom in the system&#xA;n_components, component_list = sparse.csgraph.connected_components(connmat)&#xA;&#xA;# Sorting based on the molecule index first (`component_list`)&#xA;# and then by chemical symbol of the atom&#xA;sortedacetonitrile = sort(&#xA;        acetonitrile,&#xA;        tags=[(component_list[i]*10) + ['H','C','N'].index(s)&#xA;            for i,s in enumerate(acetonitrile.get_chemical_symbols())]&#xA;        )&#xA;&#xA;# Write to file&#xA;write(&amp;quot;sortedacetonitrile.xyz&amp;quot;, sortedacetonitrile)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Code to determine molecules was taken from an &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/neighborlist.html#ase.neighborlist.get_connectivity_matrix&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt; in the ASE website.&lt;/p&gt;&#xA;&lt;p&gt;The resulting XYZ file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;24&#xA;Lattice=&amp;quot;4.102 0.0 0.0 0.0 8.244 0.0 -1.3976728069531361 0.0 7.84649034439626&amp;quot; Properties=species:S:1:pos:R:3:spacegroup_kinds:I:1 spacegroup=&amp;quot;P 21/c&amp;quot; unit_cell=conventional occupancy=&amp;quot;_JSON {\&amp;quot;0\&amp;quot;: {\&amp;quot;N\&amp;quot;: 1}, \&amp;quot;1\&amp;quot;: {\&amp;quot;C\&amp;quot;: 1}, \&amp;quot;2\&amp;quot;: {\&amp;quot;C\&amp;quot;: 1}, \&amp;quot;3\&amp;quot;: {\&amp;quot;H\&amp;quot;: 1}, \&amp;quot;4\&amp;quot;: {\&amp;quot;H\&amp;quot;: 1}, \&amp;quot;5\&amp;quot;: {\&amp;quot;H\&amp;quot;: 1}}&amp;quot; pbc=&amp;quot;T T T&amp;quot;&#xA;H        3.42697031       3.31408800       1.30251740        3&#xA;H        0.69579886       4.27039200       1.45944720        4&#xA;H        3.47620049       4.43527200       2.36179359        5&#xA;C        0.04293648       3.77492760       1.94436031        1&#xA;C        0.69522375       2.88375120       2.88123125        2&#xA;N        1.22043293       2.19043080       3.61958600        0&#xA;H       -0.02380672       7.43608800       2.62072778        3&#xA;H        2.70736474       0.14839200       2.46379797        4&#xA;H       -0.07303689       0.31327200       1.56145158        5&#xA;C        3.36022712       7.89692760       1.97888486        1&#xA;C        2.70793985       7.00575120       1.04201392        2&#xA;N        2.18273066       6.31243080       0.30365918        0&#xA;H       -0.72264312       4.92991200       6.54397295        3&#xA;H        2.00852834       3.97360800       6.38704314        4&#xA;H       -0.77187329       3.80872800       5.48469675        5&#xA;C        2.66139071       4.46907240       5.90213004        1&#xA;C        2.00910345       5.36024880       4.96525909        2&#xA;N        1.48389426       6.05356920       4.22690435        0&#xA;H        2.72813391       0.80791200       5.22576257        3&#xA;H       -0.00303755       8.09560800       5.38269238        4&#xA;H        2.77736408       7.93072800       6.28503877        5&#xA;C       -0.65589993       0.34707240       5.86760548        1&#xA;C       -0.00361266       1.23824880       6.80447643        2&#xA;N        0.52159653       1.93156920       7.54283117        0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="85" LastEditorUserId="85" LastEditDate="2021-05-11T06:43:27.037" LastActivityDate="2021-05-11T06:43:27.037" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4649" PostTypeId="2" ParentId="3992" CreationDate="2021-04-03T15:01:18.053" Score="5" Body="&lt;p&gt;As a good starting, you may take a look at this classical paper and its supplementary material:&#xA;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.117.097601&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.117.097601&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here I just show some general steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/LCALCPOL&quot; rel=&quot;noreferrer&quot;&gt;Calculate the polarization&lt;/a&gt; (I assume that you can use the VASP package):&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate the &lt;span class=&quot;math-container&quot;&gt;$A, B, C, D$&lt;/span&gt; of Landau-Ginzburg expansion:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E= \sum_i \dfrac{A}{2}(P_i^2)+\dfrac{B}{4}(P_i^4)+\dfrac{C}{6}(P_i^6)+\sum_{\langle i,j\rangle}\dfrac{D}{2}(P_i-P_j)^2 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Calculate the Curie temperature with AIMD or Monte-Carlo method (optional for your question).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-03T15:01:18.053" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4650" PostTypeId="2" ParentId="4625" CreationDate="2021-04-03T16:43:23.950" Score="3" Body="&lt;h2&gt;Thermodynamics is being bossy?&lt;/h2&gt;&#xA;&lt;p&gt;After discussions in the chatroom I don't see anything wrong with your simulation settings. I think the culprit is phase equilibria.&lt;/p&gt;&#xA;&lt;p&gt;Either your system wants to be in two phases, or, it wants to be a single phase but you are starting with a box size large enough (density low enough) that you start with two phases and even after 10-50 ns runs, do not truly equilibrate.&lt;/p&gt;&#xA;&lt;p&gt;If the problem is the latter, that you are starting with two phases and not converging to 1, the solution is simple: start with a higher density so that you start as a liquid system, and then hopefully, never leave - and this was noted by  WaterMolecule.&lt;/p&gt;&#xA;&lt;p&gt;If the problem is that at P=1 bar your system wants to be in two phases, that may explain why the pressure is so wild. An NPT should be able to accommodate multiple phases, but, it may take a long time. I am not a big fan of two phases in 1 simulation box, but your molecules are likely too big for Gibbs Ensemble, and the best method for MD phase equilibria won't be published by some colleagues of mine for a couple more months.&lt;/p&gt;&#xA;&lt;p&gt;An interesting question is whether there should be 2 phases or 1 at these conditions? The force-field appears to think that state point is at the least, close to a phase boundary. Force-fields are often wrong though, so that in itself would be good for you to know.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2021-04-03T16:43:23.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4651" PostTypeId="2" ParentId="1629" CreationDate="2021-04-04T12:27:18.367" Score="7" Body="&lt;h1&gt;Questaal&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Questaal is a first-principles DFT solver based on the LMTO basis (different from Wien2k answered by @ProfM), which is interfaced with the Continuous-Time Quantum Monte Carlo solver, developed by K. Haule and coworkers, for DMFT.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Website: &lt;a href=&quot;https://www.questaal.org/about/questaal/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.questaal.org/about/questaal/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Description from official website:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When localized electronic orbitals (d- or f- type) participate in the states near the Fermi level, the effect of electronic correlation can not be included as a small perturbation (RPA) and more accurate methods have to be invoked. The Questaal code has been interfaced with the Continuous-Time Quantum Monte Carlo solver developed by K. Haule and coworkers. This couples the QSGW description of the lattice with state-of-the-art Dynamical Mean Field Theory approaches. This code requires that Haule’s CTQMC be installed. The interface to that code is &lt;code&gt;lmfdmft&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2021-06-14T02:39:10.473" LastActivityDate="2021-06-14T02:39:10.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4652" PostTypeId="1" CreationDate="2021-04-04T17:51:30.990" Score="7" ViewCount="636" Body="&lt;p&gt;When building a supercell for a molecular crystal with the Atomic Simulation Environment, it seems that the program takes into account periodic boundary conditions when replicating the unit cell. &lt;strong&gt;How do I discard all molecules that wrap around the boundaries?&lt;/strong&gt; (It seems that taking into account the boundary conditions for non-orthorhombic cells is non-trivial, so I'd like to avoid it if possible!)&lt;/p&gt;&#xA;&lt;p&gt;Please note the question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4477/how-to-sort-a-supercell-for-a-molecular-crystal&quot;&gt;here&lt;/a&gt; that this follows up on. The .cif file that I am using is reproduced below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT:&lt;/strong&gt; When I try as a test the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase.io import read, write&#xA;unitcell = read(&amp;quot;mycif.cif&amp;quot;)&#xA;unitcell.set_pbc((False,False,False))&#xA;supercell = unitcell*(8,4,4)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I still get unconnected atoms at the boundaries. &lt;strong&gt;Any idea about how to resolve this?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;data_I&#xA;_audit_creation_method     SHELXL&#xA;_journal_date_recd_electronic     2002-06-07&#xA;_journal_date_accepted     2002-09-25&#xA;_journal_name_full     'Acta Crystallographica, Section B'&#xA;_journal_year     2002&#xA;_journal_volume     58&#xA;_journal_issue      6&#xA;_journal_page_first     1005&#xA;_journal_page_last     1010&#xA;_journal_paper_category     FA&#xA;_chemical_name_systematic     'acetonitrile'&#xA;_chemical_name_common     ?&#xA;_chemical_formula_moiety     'C2 H3 N'&#xA;_chemical_formula_sum     'C2 H3 N'&#xA;_chemical_formula_structural     'C H3 C N'&#xA;_chemical_formula_analytical     ?&#xA;_chemical_formula_weight     41.05&#xA;_chemical_melting_point     ?&#xA;_symmetry_cell_setting     'monoclinic'&#xA;_symmetry_space_group_name_H-M     'P 21/c'&#xA;_symmetry_space_group_name_Hall     '-P 2ybc'&#xA;loop_&#xA;    _symmetry_equiv_pos_as_xyz&#xA;    'x, y, z'&#xA;    '-x, y+1/2, -z+1/2'&#xA;    '-x, -y, -z'&#xA;    'x, -y-1/2, z-1/2'&#xA;_cell_length_a     4.102(3)&#xA;_cell_length_b     8.244(7)&#xA;_cell_length_c     7.970(7)&#xA;_cell_angle_alpha     90.00&#xA;_cell_angle_beta     100.10(10)&#xA;_cell_angle_gamma     90.00&#xA;_cell_volume     265.3(4)&#xA;_cell_formula_units_Z     4&#xA;_cell_measurement_reflns_used     25&#xA;_cell_measurement_theta_min     5.20&#xA;_cell_measurement_theta_max     21.48&#xA;_cell_measurement_temperature     201(2)&#xA;_exptl_crystal_description     'cylinder'&#xA;_exptl_crystal_colour     'colourless'&#xA;_exptl_crystal_size_max     1.2&#xA;_exptl_crystal_size_mid     0.5&#xA;_exptl_crystal_size_min     0.3&#xA;_exptl_crystal_size_rad     0.15&#xA;_exptl_crystal_density_diffrn     1.028&#xA;_exptl_crystal_density_meas     ?&#xA;_exptl_crystal_density_method     ?&#xA;_exptl_crystal_F_000     88&#xA;_exptl_absorpt_coefficient_mu     0.067&#xA;_exptl_absorpt_correction_type     'none'&#xA;_exptl_absorpt_correction_T_min     ?&#xA;_exptl_absorpt_correction_T_max     ?&#xA;_exptl_special_details&#xA;;&#xA; ?&#xA;;&#xA;_diffrn_ambient_temperature     201(2)&#xA;_diffrn_radiation_type     MoK\a&#xA;_diffrn_radiation_wavelength     0.71073&#xA;_diffrn_radiation_source     'fine-focus sealed tube'&#xA;_diffrn_radiation_monochromator     'graphite'&#xA;_diffrn_measurement_device     'Nonius CAD4 diffractometer'&#xA;_diffrn_measurement_method     '\w--2\q'&#xA;_diffrn_reflns_number     376&#xA;_diffrn_reflns_av_R_equivalents     0.0571&#xA;_diffrn_reflns_av_sigmaI/netI     0.0591&#xA;_diffrn_reflns_theta_min     3.58&#xA;_diffrn_reflns_theta_max     21.89&#xA;_diffrn_reflns_theta_full     21.89&#xA;_diffrn_measured_fraction_theta_max     0.99&#xA;_diffrn_measured_fraction_theta_full     0.99&#xA;_diffrn_reflns_limit_h_min     0&#xA;_diffrn_reflns_limit_h_max     4&#xA;_diffrn_reflns_limit_k_min     0&#xA;_diffrn_reflns_limit_k_max     8&#xA;_diffrn_reflns_limit_l_min     -8&#xA;_diffrn_reflns_limit_l_max     8&#xA;_diffrn_standards_number     'none'&#xA;_diffrn_standards_interval_count     'none'&#xA;_diffrn_standards_interval_time     'none'&#xA;_diffrn_standards_decay_%     'none'&#xA;_refine_special_details&#xA;;&#xA; Refinement of F^2^ against ALL reflections.  Weighted R-factors wR and&#xA; goodnesses of fit S are based on F^2^, conventional R-factors R are based&#xA; on F, with F set to zero for negative F^2^. The threshold_expression of&#xA; F^2^ &amp;gt; 2sigma(F^2^) is used only for calculating R_factors(gt) etc. and is&#xA; not relevant to the choice of reflections for refinement.  R-factors based&#xA; on F^2^ are statistically about twice as large as those based on F, and R-&#xA; factors based on ALL data will be even larger.&#xA;;&#xA;_reflns_number_total     324&#xA;_reflns_number_gt     202&#xA;_reflns_threshold_expression     'I&amp;gt;2\s(I)'&#xA;_refine_ls_structure_factor_coef     Fsqd&#xA;_refine_ls_matrix_type     full&#xA;_refine_ls_R_factor_all     0.1051&#xA;_refine_ls_R_factor_gt     0.0472&#xA;_refine_ls_wR_factor_all     0.1504&#xA;_refine_ls_wR_factor_ref     0.1106&#xA;_refine_ls_goodness_of_fit_all     1.137&#xA;_refine_ls_goodness_of_fit_ref     1.107&#xA;_refine_ls_restrained_S_all     1.137&#xA;_refine_ls_restrained_S_obs     1.107&#xA;_refine_ls_number_reflns     324&#xA;_refine_ls_number_parameters     41&#xA;_refine_ls_number_restraints     0&#xA;_refine_ls_hydrogen_treatment     'refall'&#xA;_refine_ls_weighting_scheme     calc&#xA;_refine_ls_weighting_details&#xA;              'w=1/[\s^2^(Fo^2^)+(0.0360P)^2^+0.1879P] where P=(Fo^2^+2Fc^2^)/3'&#xA;_atom_sites_solution_hydrogens     difmap&#xA;_atom_sites_solution_primary     direct&#xA;_atom_sites_solution_secondary     difmap&#xA;_refine_ls_shift/su_max     0.000&#xA;_refine_ls_shift/su_mean     0.000&#xA;_refine_diff_density_max     0.169&#xA;_refine_diff_density_min     -0.168&#xA;_refine_ls_extinction_method     SHELXL&#xA;_refine_ls_extinction_coef     0.07(4)&#xA;_refine_ls_extinction_expression&#xA;                                  'Fc^*^=kFc[1+0.001xFc^2^\l^3^/sin(2\q)]^-1/4^'&#xA;loop_&#xA;    _atom_type_symbol&#xA;    _atom_type_description&#xA;    _atom_type_scat_dispersion_real&#xA;    _atom_type_scat_dispersion_imag&#xA;    _atom_type_scat_source&#xA;    'C' 'C' 0.0033 0.0016&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'H' 'H' 0.0000 0.0000&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;    'N' 'N' 0.0061 0.0033&#xA;                         'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;_computing_data_collection     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_cell_refinement     'CAD4-EXPRESS (Enraf-Nonius, 1993)'&#xA;_computing_data_reduction     'CADAK (Savariault,1991)'&#xA;_computing_structure_solution     'SHELXS-96 (Sheldrick, 1990)'&#xA;_computing_structure_refinement     'SHELXL-96 (Sheldrick, 1996)'&#xA;_computing_molecular_graphics     'ORTEP III (Burnett &amp;amp; Johnson, 1996)'&#xA;_computing_publication_material     'SHELXL-96 (Sheldrick, 1996)'&#xA;loop_&#xA;    _atom_site_label&#xA;    _atom_site_fract_x&#xA;    _atom_site_fract_y&#xA;    _atom_site_fract_z&#xA;    _atom_site_U_iso_or_equiv&#xA;    _atom_site_thermal_displace_type&#xA;    _atom_site_calc_flag&#xA;    _atom_site_refinement_flags&#xA;    _atom_site_occupancy&#xA;    _atom_site_disorder_group&#xA;    _atom_site_type_symbol&#xA;    N 0.4547(9) 0.2657(5) 0.4613(4) 0.0710(15) Uani d . 1 . N&#xA;    C1 0.0949(12) 0.4579(6) 0.2478(6) 0.0586(14) Uani d . 1 . C&#xA;    C2 0.2946(9) 0.3498(5) 0.3672(5) 0.0507(13) Uani d . 1 . C&#xA;    H1 -0.108(11) 0.402(5) 0.166(5) 0.089(14) Uiso d . 1 . H&#xA;    H2 0.233(11) 0.518(6) 0.186(6) 0.113(18) Uiso d . 1 . H&#xA;    H3 -0.050(11) 0.538(6) 0.301(5) 0.103(16) Uiso d . 1 . H&#xA;loop_&#xA;    _atom_site_aniso_label&#xA;    _atom_site_aniso_U_11&#xA;    _atom_site_aniso_U_22&#xA;    _atom_site_aniso_U_33&#xA;    _atom_site_aniso_U_12&#xA;    _atom_site_aniso_U_13&#xA;    _atom_site_aniso_U_23&#xA;    N 0.076(3) 0.070(3) 0.064(2) 0.005(2) 0.0028(18) 0.008(2)&#xA;    C1 0.058(3) 0.060(3) 0.055(3) 0.005(2) 0.001(2) 0.008(2)&#xA;    C2 0.056(2) 0.050(3) 0.047(2) -0.007(2) 0.0101(19) -0.009(2)&#xA;_geom_special_details&#xA;;&#xA; All esds (except the esd in the dihedral angle between two l.s. planes)&#xA; are estimated using the full covariance matrix.  The cell esds are taken&#xA; into account individually in the estimation of esds in distances, angles&#xA; and torsion angles; correlations between esds in cell parameters are only&#xA; used when they are defined by crystal symmetry.  An approximate (isotropic)&#xA; treatment of cell esds is used for estimating esds involving l.s. planes.&#xA;;&#xA;loop_&#xA;    _geom_bond_atom_site_label_1&#xA;    _geom_bond_atom_site_label_2&#xA;    _geom_bond_site_symmetry_2&#xA;    _geom_bond_distance&#xA;    _geom_bond_publ_flag&#xA;    N C2 . 1.141(5) yes&#xA;    C1 C2 . 1.448(6) yes&#xA;    C1 H1 . 1.07(5) yes&#xA;    C1 H2 . 0.96(5) yes&#xA;    C1 H3 . 1.03(5) yes&#xA;loop_&#xA;    _geom_angle_atom_site_label_1&#xA;    _geom_angle_atom_site_label_2&#xA;    _geom_angle_atom_site_label_3&#xA;    _geom_angle_site_symmetry_1&#xA;    _geom_angle_site_symmetry_3&#xA;    _geom_angle&#xA;    _geom_angle_publ_flag&#xA;    C2 C1 H1 . . 115(2) yes&#xA;    C2 C1 H2 . . 110(3) yes&#xA;    H1 C1 H2 . . 112(3) yes&#xA;    C2 C1 H3 . . 115(2) yes&#xA;    H1 C1 H3 . . 95(3) yes&#xA;    H2 C1 H3 . . 108(4) yes&#xA;    N C2 C1 . . 179.3(4) yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user2026" LastEditorUserId="5" LastEditDate="2021-04-23T21:14:36.847" LastActivityDate="2021-04-24T06:44:06.410" Title="How to discard molecules at the boundary in the Atomic Simulation Environment (ASE)?" Tags="|molecular-dynamics|crystallography|atomic-simulation-environment|periodic-boundary-conditions|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4653" PostTypeId="1" CreationDate="2021-04-05T03:23:31.317" Score="10" ViewCount="80" Body="&lt;p&gt;Given a tight binding matrix of a thin film system with a few atomic layers, is it possible to construct a tight binding matrix of higher atomic layers thin film from the lower one? For example, I have a 4 atomic layers tight binding matrix from the fitting of a DFT calculation, is it possible to use this matrix and construct a 10 atomic layers thin film tight binding matrix?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-10-30T20:21:53.057" LastActivityDate="2022-09-12T17:14:51.733" Title="Is it possible to construct a tight binding matrix of high atomic layer thin film from the lower one?" Tags="|density-functional-theory|band-structure|tight-binding|wannier90|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4654" PostTypeId="2" ParentId="4601" CreationDate="2021-04-05T03:28:48.280" Score="2" Body="&lt;p&gt;I found the answer already. As the inconsistent calculation between the bulk and the thin film in the DFT calculation process. A small error term will generate a diverge behaviour in the surface energy as I increase the thickness of the slab. One way to fix this issue is to use the data from my thin film calculation to extrapolate the bulk energy without doing an extra isolated calculation on the bulk. Two way was commonly used, they are Linear fitting and Boettger method.&lt;/p&gt;&#xA;&lt;p&gt;Welcome to discuss this issue and point me out if there is anything unclear.&lt;/p&gt;&#xA;&lt;p&gt;Reference:&#xA;Boettger J C 1994 Phys. Rev. B 49 16 798&lt;/p&gt;&#xA;&lt;p&gt;Fiorentini V and Methfessel M 1996 J. Phys.: Condens. Matter 8 6525&lt;/p&gt;&#xA;" OwnerUserId="621" LastActivityDate="2021-04-05T03:28:48.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4655" PostTypeId="2" ParentId="4573" CreationDate="2021-04-05T06:13:23.183" Score="3" Body="&lt;p&gt;If you open with vim, you can find it by following command line.&lt;/p&gt;&#xA;&lt;p&gt;vim OUTCAR and input '?Volume of Type' or '/Volume of Type', press n or N to find previous one next one with string 'Volume of Type'.&lt;/p&gt;&#xA;" OwnerUserId="3331" LastActivityDate="2021-04-05T06:13:23.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4656" PostTypeId="2" ParentId="2022" CreationDate="2021-04-05T06:24:59.900" Score="5" Body="&lt;p&gt;There is a patch of vasp used to fix any axis. For a monolayer materials, to fix c-axis is a good choice.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/Chengcheng-Xiao/VASP_OPT_AXIS&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Chengcheng-Xiao/VASP_OPT_AXIS&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When you want to optimize n-layer materials (n=2,3,4,5), Van der Waals (vdW) correction needs to be added in INCAR to condider the interaction between two layers. Usually I use IVDW = 11 to describe van der Waals interactions in my calculation.&lt;/p&gt;&#xA;" OwnerUserId="3331" LastEditorUserId="3331" LastEditDate="2021-04-05T08:32:32.090" LastActivityDate="2021-04-05T08:32:32.090" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4657" PostTypeId="1" CreationDate="2021-04-05T07:51:29.140" Score="4" ViewCount="1098" Body="&lt;p&gt;Since the effect of spin-orbit coupling plays an important role in a topological insulator, How to change the spin-orbit coupling strength in &lt;code&gt;VASP&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MOASR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MOASR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3331" LastEditorUserId="1218" LastEditDate="2021-04-05T11:08:51.293" LastActivityDate="2021-04-05T11:08:51.293" Title="How to change the spin-orbit coupling strength in VASP?" Tags="|vasp|spin-orbit-coupling|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4658" PostTypeId="2" ParentId="1629" CreationDate="2021-04-05T08:01:03.187" Score="9" Body="&lt;p&gt;&lt;strong&gt;DCore&lt;/strong&gt;: integrated &lt;strong&gt;D&lt;/strong&gt;MFT software for &lt;strong&gt;Cor&lt;/strong&gt;related &lt;strong&gt;e&lt;/strong&gt;lectrons&lt;/p&gt;&#xA;&lt;p&gt;DCore is aimed at model calculations and ab-initio calculations by the dynamical mean-field theory (DMFT). This package consists of programs with text-based and hdf5-based interface. These programs enable users to perform DMFT calculations and analyze results without writing computer code.&lt;/p&gt;&#xA;&lt;p&gt;Website:&lt;a href=&quot;https://issp-center-dev.github.io/DCore/master/contents.html&quot; rel=&quot;noreferrer&quot;&gt;https://issp-center-dev.github.io/DCore/master/contents.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Several examples:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lZeKm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lZeKm.png&quot; alt=&quot;Several examples have been&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TRIQS&lt;/strong&gt;: &lt;strong&gt;T&lt;/strong&gt;oolbox for &lt;strong&gt;R&lt;/strong&gt;esearch on &lt;strong&gt;I&lt;/strong&gt;nteracting &lt;strong&gt;Q&lt;/strong&gt;uantum &lt;strong&gt;S&lt;/strong&gt;ystems&lt;/p&gt;&#xA;&lt;p&gt;Based on the TRIQS toolkit, several full-fledged applications are also available. They allow for example to solve a generic quantum impurity model or to run a complete DFT+DMFT calculation.&lt;/p&gt;&#xA;&lt;p&gt;Developed in a collaboration between IPhT Saclay and Ecole Polytechnique since 2005, the TRIQS library and applications have allowed us to address questions as diverse as:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Momentum-selective aspects on cuprate superconductors (with various cluster DMFT methods)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Degree of correlation in iron-based superconductors (within an DFT+DMFT approach)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Fermionic Mott transition and exploration of Sarma phase in cold-atoms&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;website:&lt;a href=&quot;https://triqs.github.io/triqs/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;https://triqs.github.io/triqs/latest/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3331" LastEditorUserId="3331" LastEditDate="2021-06-14T02:09:07.467" LastActivityDate="2021-06-14T02:09:07.467" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4659" PostTypeId="2" ParentId="4657" CreationDate="2021-04-05T08:26:29.630" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How to change the spin-orbit coupling strength in VASP?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Firstly, one can't realize this just by changing the input parameters in the &lt;code&gt;INCAR&lt;/code&gt; for &lt;code&gt;VASP&lt;/code&gt;. To tune the strength of spin-orbit coupling in &lt;code&gt;VASP&lt;/code&gt;, you need to modify the source file &lt;code&gt;vasp_source_code_path/src/relativistic.F&lt;/code&gt; and recompile it. For example, if you want to reduce the strength to half you can just multiply &lt;code&gt;0.5d0&lt;/code&gt; to the &lt;span class=&quot;math-container&quot;&gt;$L \cdot S$&lt;/span&gt; term in line 129 of &lt;code&gt;relativistic.F&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;       DO I=0,1&#xA;       DO J=0,1&#xA;       DO M =1,2*LL+1&#xA;       DO MP=1,2*LL+1&#xA;          DLLMM(LMP+MP-1,LM+M-1,J+2*I+1)=DLLMM(LMP+MP-1,LM+M-1,J+2*I+1)+ &amp;amp;&#xA;          0.5d0*SUM*LS(M,MP,I+2*J+1,LL)   !!!line 129 relativistic.F file&#xA;       END DO&#xA;       END DO&#xA;       END DO&#xA;       END DO&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that you need to use the recompiled &lt;span class=&quot;math-container&quot;&gt;$vasp_ncl$&lt;/span&gt; to run your calculation. As a benchmark, if you multiply &lt;code&gt;0.0d0&lt;/code&gt; to the &lt;span class=&quot;math-container&quot;&gt;$L \cdot S$&lt;/span&gt; term in line 129 of &lt;code&gt;relativistic.F&lt;/code&gt; then you will receive the same result as the result obtained with &lt;code&gt;vasp_std&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PS1: The answer is for the vasp.5.4.4.&lt;/p&gt;&#xA;&lt;p&gt;PS2: You may take a look at &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.93.224425&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; about the implementation of spin-orbit coupling in &lt;code&gt;VASP&lt;/code&gt;. Or you may take a look at this post in matter modeling: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4456/regarding-spin-orbit-coupling-on-dft-codes/4463#4463&quot;&gt;Regarding spin-orbit coupling on DFT codes&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-05T08:26:29.630" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="4660" PostTypeId="2" ParentId="4444" CreationDate="2021-04-05T08:35:23.313" Score="3" Body="&lt;p&gt;Fix c-axis and ISIF = 3 can be used to optimize monolayer.&lt;/p&gt;&#xA;&lt;p&gt;how to fix c-axis see following link:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4656/3331&quot;&gt;https://mattermodeling.stackexchange.com/a/4656/3331&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3331" LastActivityDate="2021-04-05T08:35:23.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4661" PostTypeId="1" AcceptedAnswerId="4667" CreationDate="2021-04-05T09:39:39.450" Score="10" ViewCount="239" Body="&lt;p&gt;I am writing my own DFT code using Gaussian basis and now I am writing the periodic boundary conditions (PBC).&#xA;What integration grid people usually use for Gaussian basis PBC (+ reference please)?&#xA;For isolated molecules, I used the SG3 integration grid with Becke's scheme to combine multi-atomic grids.&lt;/p&gt;&#xA;" OwnerUserId="882" LastActivityDate="2023-09-09T12:53:52.823" Title="DFT xc integration grid for periodic boundary conditions" Tags="|density-functional-theory|exchange-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4662" PostTypeId="2" ParentId="4618" CreationDate="2021-04-05T11:01:56.177" Score="8" Body="&lt;p&gt;There is a &lt;a href=&quot;https://gist.github.com/kain88-de/d004620a57b08e45812b7f5108a375d7&quot; rel=&quot;nofollow noreferrer&quot;&gt;nice explanation here&lt;/a&gt; outlining the difficulties for the minimum image convention in triclinic cells.&lt;/p&gt;&#xA;&lt;p&gt;It describes an &lt;strike&gt;exact&lt;/strike&gt; approach (edit: see discussion below), as well an approximate algorithm (referencing &lt;a href=&quot;https://pure.rug.nl/ws/portalfiles/portal/2839530/03_c3.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;appendix C here&lt;/a&gt; and &lt;a href=&quot;https://global.oup.com/academic/product/statistical-mechanics-theory-and-molecular-simulation-9780198525264?cc=de&amp;amp;lang=en&amp;amp;&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tuckerman appendix B&lt;/a&gt;) used by many major molecular dynamics codes. &lt;a href=&quot;https://github.com/MDAnalysis/mdanalysis/issues/1475&quot; rel=&quot;nofollow noreferrer&quot;&gt;This related discussion&lt;/a&gt; is also useful.&lt;/p&gt;&#xA;&lt;p&gt;There is also &lt;a href=&quot;https://scicomp.stackexchange.com/questions/3107/minimum-image-convention-for-triclinic-unit-cell&quot;&gt;this question&lt;/a&gt; from the SciComp stack exchange.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2023-09-18T16:07:53.150" LastActivityDate="2023-09-18T16:07:53.150" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4663" PostTypeId="2" ParentId="1601" CreationDate="2021-04-05T11:49:50.607" Score="3" Body="&lt;h3&gt;Coherent Potential Approximation (CPA) Method.&lt;/h3&gt;&#xA;&lt;p&gt;This method is implemented successfully in the first-principles matter modeling packages &lt;a href=&quot;https://www.questaal.org/about/questaal/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Questaal&lt;/a&gt; and &lt;a href=&quot;https://emto.gitlab.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;EMTO&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can find a general introduction about &lt;a href=&quot;https://en.wikipedia.org/wiki/Coherent_potential_approximation&quot; rel=&quot;nofollow noreferrer&quot;&gt;CPA on Wikipedia&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-04-05T13:15:50.610" LastActivityDate="2021-04-05T13:15:50.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4664" PostTypeId="1" CreationDate="2021-04-05T14:46:03.200" Score="10" ViewCount="106" Body="&lt;p&gt;I'm making a topological analysis of a nanotube interacting with some metals.&lt;/p&gt;&#xA;&lt;p&gt;The steps for the calculations were:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Optimizing the geometry (I am using &lt;a href=&quot;https://siesta-project.org/siesta/&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt; code).&lt;/li&gt;&#xA;&lt;li&gt;Obtain the electronic density for the final relaxed structure (in cube format with the help of DENCHAR utility that is part of the SIESTA distribution): density files for total electron density (RHO), spin up electron density (RHO.UP) and spin down electron density (RHO.DOWN).&lt;/li&gt;&#xA;&lt;li&gt;Run topological analysis with &lt;a href=&quot;https://aoterodelaroza.github.io/critic2/&quot; rel=&quot;noreferrer&quot;&gt;CRITIC2&lt;/a&gt;&lt;sup&gt;1,2&lt;/sup&gt; software.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For the three metals under study, I got a bond critical point from the RHO file.&lt;br /&gt;&#xA;When analyzing the RHO.UP and RHO.DOWN files, for two metals I got two critical points (one for each spin). But for one metal, I only got one bond critical point.&lt;/p&gt;&#xA;&lt;p&gt;As the recommended way to run topological studies is using the wavefunction directly instead the electron density, I run the topological analysis from density files with different grid size.&lt;/p&gt;&#xA;&lt;p&gt;The question: &lt;strong&gt;Can I have a bond formed for only one spin?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; A.Otero-de-la-Roza, M.A.Blanco, A. Martín Pendás, Víctor Luaña. &lt;em&gt;Critic: a new program for the topological analysis of solid-state electron densities&lt;/em&gt;, Computer Physics Communications&#xA;Volume 180, Issue 1, January 2009, Pages 157-166. DOI: &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2008.07.018&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2008.07.018&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt; A.Otero-de-la-Roza, Erin R.Johnson, Víctor Luaña, &lt;em&gt;Critic2: A program for real-space analysis of quantum chemical interactions in solids&lt;/em&gt;, Computer Physics Communications&#xA;Volume 185, Issue 3, March 2014, Pages 1007-1018. DOI:&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2013.10.026&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2013.10.026&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-07-03T17:01:38.850" LastActivityDate="2021-07-03T17:01:38.850" Title="Can I have a bond formed for only one spin?" Tags="|solid-state-physics|spin|siesta|nanostructures|electron-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4665" PostTypeId="1" AcceptedAnswerId="4739" CreationDate="2021-04-05T19:05:41.860" Score="9" ViewCount="136" Body="&lt;p&gt;This question is a follow-up to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4621/what-software-is-the-best-choice-for-rna-tertiary-structure-prediction&quot;&gt;this previous question&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have learnt there that there are reasonable ways to predict RNA &lt;em&gt;tertiary structure&lt;/em&gt;. Here I inquire about how to predict RNA &lt;em&gt;secondary structure&lt;/em&gt;. I have only heard about the ViennaRNA Package, and there is a &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_RNA_structure_prediction_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;list&lt;/a&gt; of software on Wikipedia. I like the &lt;a href=&quot;https://en.wikipedia.org/wiki/Global_distance_test&quot; rel=&quot;nofollow noreferrer&quot;&gt;GDT&lt;/a&gt; measure. Again, for me, it has relevance in connection with the origin of life (cf. &lt;a href=&quot;https://en.wikipedia.org/wiki/RNA_world&quot; rel=&quot;nofollow noreferrer&quot;&gt;RNA world&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="2292" LastEditorUserId="2292" LastEditDate="2021-04-17T09:38:58.287" LastActivityDate="2021-04-17T17:11:05.450" Title="What software can do RNA secondary structure prediction?" Tags="|software|one-topic-per-answer|software-recommendations|structural-biology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4666" PostTypeId="2" ParentId="4664" CreationDate="2021-04-05T19:55:44.337" Score="5" Body="&lt;p&gt;Yes, see e.g. the hydrogen molecule cation.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-04-05T19:55:44.337" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4667" PostTypeId="2" ParentId="4661" CreationDate="2021-04-05T19:56:43.563" Score="7" Body="&lt;p&gt;Exactly the same grids as for molecules, i.e. Becke grids. You just need to take the periodic boundary conditions into account when building the grid weights.&lt;/p&gt;&#xA;&lt;p&gt;edit: e.g. PySCF has both molecules and periodic boundary conditions with Gaussian basis sets, and is in my experience a pretty fast code that is also easy to install.&lt;/p&gt;&#xA;&lt;p&gt;See the pyscf documentation for info. Note: as usual for LCAO programs, PySCF implements PBC in 0, 1, 2, and 3 dimensions.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-09-09T12:53:52.823" LastActivityDate="2023-09-09T12:53:52.823" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4668" PostTypeId="2" ParentId="4622" CreationDate="2021-04-05T20:08:37.603" Score="4" Body="&lt;p&gt;As has already been pointed out by Tyberius and Nike Dattani, a commonly-used alternative to the self-consistent field method is to use direct minimization methods for the energy, where the SCF problem is reformulated as a minimization in terms of the molecular orbitals (MOs) / MO coefficients. You can read about both approaches in our recent review paper, &lt;a href=&quot;https://www.mdpi.com/1420-3049/25/5/1218&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;. Several recent fully numerical approaches also solve the SCF problem using iterative integral equations with the Helmholtz kernel, where you obtain updated orbitals from the current ones through numerical quadrature.&lt;/p&gt;&#xA;&lt;p&gt;The connection between the two is that when you write the energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; in terms of the orbitals &lt;span class=&quot;math-container&quot;&gt;${\mathbf C}$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$$E=E(\mathbf{C})$$&lt;/span&gt;&#xA;you can either minimize this directly with respect to your parameters &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt;, or set the variation with respect to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}$&lt;/span&gt; to zero that gives you the SCF equations. In either approach, you have to maintain orbital orthonormality with Lagrange multipliers, which give you the orbital energies. Moreover, both approaches require an iterative solution.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-04-05T20:08:37.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4669" PostTypeId="2" ParentId="3892" CreationDate="2021-04-06T01:19:56.430" Score="8" Body="&lt;p&gt;The previous answers are good responses, especially the one from Guy Moore. However, I'd like to recommend two more solutions: &lt;a href=&quot;https://github.com/Volkov-da/curie_calculator&quot; rel=&quot;nofollow noreferrer&quot;&gt;curie_calculator&lt;/a&gt; and &lt;a href=&quot;https://github.com/golddoushi/mcsolver&quot; rel=&quot;nofollow noreferrer&quot;&gt;mcsolver&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;mcsolver&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A user friendly and efficient tool implementing Monte Carlo simulations to estimate Curie/Neel temperature. Supports multiple occasions, e.g. standard ferromagnetic/anti-ferromagnetic systems, DMI, Kiteav non-diagonal exchange interactions, dipole-dipole long-range couplings, with external fields.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can either choose the Windows version or python package. Both of them need same input file.&lt;/p&gt;&#xA;&lt;h3&gt;How to define parameters?&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Define the three lattice vectors of primitive cell.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Define all basic spins in primitive cell, note that the fractional coordinates are supposed. Ani represents the single-ion anisotropies in xyz directions (It is useless in Ising model, and only former two are used in XY model). As well as, note that the units of anisotropies are in Kelvin.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Define all exchange interactions (bonds). There are nine matrix elements for one &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; (i.e. &lt;span class=&quot;math-container&quot;&gt;$J_{xx}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{yy}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{zz}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{xy}$&lt;/span&gt;, etc.). Each element describes the coupling between two components of spins. For example, a basic bond term can be expressed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_1\cdot J\cdot S_2 = S_{1x}J_{xx}S_{2x} + S_{1y}J_{yy}S_{2y} + S_{1z}J_{zz}S_{2z} + S_{1x}J_{xy}S_{2y} + ...$$&lt;/span&gt;&#xA;For the Ising model, since only one component is available for each spin, only the first element &lt;span class=&quot;math-container&quot;&gt;$J_{xx}$&lt;/span&gt; is used. As well as for the XY model, only &lt;span class=&quot;math-container&quot;&gt;$J_{xx}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{yy}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{xy}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_{yz}$&lt;/span&gt; are used.&#xA;In this step, you can click one of the bonds to review the actual linking in lattice on the view panel. Activated bond is depicted with bold and yellow line while others are green. You may drag the left/right mouse button to rotate and expand/shrink the model shown in the view panel.&#xA;By the way, these parameters can be obtained via fitting experimental spin-wave spectra or DFT calculations. One of the general method for calculating anisotropic bonds and orbitals was introduced in Zhang et. al.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; 10.1021/acs.jpclett.0c01911.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Define other parameters, including&#xA;the start and end temperatures, number of temperature interpolations (for the temperature scanning)&#xA;the start, end and number of samplings for external field (for the magnetic field scanning).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;nthermal&lt;/code&gt; is the total steps to make system enter balanced states&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;nsweep&lt;/code&gt; is the total steps involved in measuring&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;tau&lt;/code&gt; denotes the MC updates for each step&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;xAxis&lt;/code&gt; denotes the physical quantity put in x-axis of right-hand Result viewer, it can be either T(for illustration of M-T curve) or H (for illustration of hysteresis loop) model type, algorithm (only Metropolis and Wolff are supported now).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;nFrame&lt;/code&gt; is the number of output spin configurations, using for illustrating spin configurations in equilibrium or non-equilibrium states.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Set &lt;code&gt;spin_i&lt;/code&gt; and &lt;code&gt;spin_j&lt;/code&gt; and the lattice vector between them, for correlation measurements. (if &lt;code&gt;spin_i=spin_j&lt;/code&gt; and &lt;code&gt;overLat=0 0 0&lt;/code&gt;, then you will get susceptibility for &lt;code&gt;spin_i&lt;/code&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Set the core resources for parallel calculation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(Optional) Save current parameters into file.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Click the startMC button to start.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Wait for the diagram update in the right panel. Afterward, you can find a file result.txt in the root directory of mcsolver, there are many useful information including the averaged spin (on &lt;code&gt;spin_i&lt;/code&gt; and &lt;code&gt;spin_j&lt;/code&gt; defined in step 5), correlation between &lt;code&gt;spin_i&lt;/code&gt; and &lt;code&gt;spin_j&lt;/code&gt;, internal energy, specific heat capacity, and Binder cumulant U4, etc. If you handle the sims with more than one cores then the results may not be ordered according to temperature, however, the correspondences in every line are ok.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A detailed tutorial of mcsolver have been given in its README file.&#xA;To repeat the &lt;span class=&quot;math-container&quot;&gt;$\ce{CrI3}$&lt;/span&gt; case in samples directory is a good choice.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Liang Liu, Songsong Chen, Zezhou Lin, and Xi Zhang* J. Phys. Chem. Lett. 2020, 11, 18, 7893–7900 &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.0c01911&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acs.jpclett.0c01911&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3331" LastEditorUserId="7" LastEditDate="2021-05-06T15:12:38.293" LastActivityDate="2021-05-06T15:12:38.293" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4670" PostTypeId="1" CreationDate="2021-04-06T14:01:35.780" Score="9" ViewCount="329" Body="&lt;p&gt;I'm doing a polarization calculation for the first time.  To specify one of the input parameters (the &amp;quot;reference point&amp;quot;) correctly, I have to figure out if my system is &amp;quot;charged.&amp;quot;  If it is not charged, I don't have to worry about the reference point.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Could anyone please help ensure I understand what &amp;quot;charged&amp;quot; means in this context?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;On one hand, I understand that a system made up of water molecules (for example) is not charged.  But if some of the water molecules dissociate or we add salt that ends up as Cl- and a corresponding +1 ion, I'm not sure. I.e., &lt;strong&gt;does &amp;quot;charged system&amp;quot; refer to the entire system or does it mean that we need to account for what's going on locally inside the system?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1035" LastEditorUserId="5" LastEditDate="2021-10-30T20:23:40.733" LastActivityDate="2021-11-01T17:32:40.023" Title="What is a &quot;charged system&quot; in this specific context?" Tags="|cp2k|charge-polarization-model|polarizability|charged-molecules|dipole|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4671" PostTypeId="2" ParentId="4633" CreationDate="2021-04-06T18:21:59.960" Score="6" Body="&lt;h2&gt;I would recommend GAFF or OPLS/A&lt;/h2&gt;&#xA;&lt;p&gt;Camps has outlined the OPLS FF, so I won't elaborate very much, but to say that when using &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;noreferrer&quot;&gt;LigParGen&lt;/a&gt;, a nice feature is that forcefields are made for many different MD programs such as openMM, Gromacs, CHARMM and others, so it is pretty easy. If you email Jorgensen, you can get a version of LigParGen that you can use on your own computer rather than having to use a web browser.&lt;/p&gt;&#xA;&lt;p&gt;I also recommend the &lt;strong&gt;General Amber Force-Field (GAFF)&lt;/strong&gt;. It relies on using a program called Antechamber to make the intermolecular parameters from a lookup table, so geometry optimization does not matter - but, you then either make partial charges from restrained electrostatic potential (RESP) calculations, which does depend on the geometry, or AM1-BCC, which does not depend on the geometry you provide, but to a degree, depends on the conformer you provide. Part of AM1-BCC is that first it optimized geometry using AM1 which is semi-empirical and not all that accurate, but the BCC part is a correction, so they are usually okayish.&lt;/p&gt;&#xA;&lt;p&gt;Antechamber is easyish to use.&lt;/p&gt;&#xA;&lt;p&gt;I would avoid doing QM calculations for intermolecular parameters such as bonds, angles, torsions unless you really know what you are doing.&lt;/p&gt;&#xA;&lt;p&gt;Here is a tutorial on GAFF and Ionic Liquids by David Case, a developer of AMBER&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://ambermd.org/tutorials/advanced/tutorial15/Tutorial2.xhtml&quot; rel=&quot;noreferrer&quot;&gt;GAFF tutorial for Ionic Liquids&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are some publications of Ionic Liquids with GAFF&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcb.5b00689&quot; rel=&quot;noreferrer&quot;&gt;The General AMBER Force Field GAFF can accurately calculate... ionic liquids&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4922442&quot; rel=&quot;noreferrer&quot;&gt;Interaction and Dynamics of ionic liquids...&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have also used GAFF for Ionic Liquids, but do not have a publication out yet, but will, one day, I keep telling myself... I can say that it works.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2021-04-06T18:21:59.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4672" PostTypeId="1" AcceptedAnswerId="4674" CreationDate="2021-04-07T06:19:11.643" Score="8" ViewCount="71" Body="&lt;p&gt;I like to perform a DFT Study on Tetramethylthiuramdisulfid. So I made a structure optimization for my start structur with PW6B95D3/aug-cc-pvtz to get a good structure to begin my dihedral scan to get a PES. The optimization terminated without errors, so I set up my 2 dimension scan. To get the result in a reasonable time, I worked with the combination of b3lyp/6-311++g(df,3p). The scan terminated also without any errors but when I visualize the structures there are a lot of conformers which &amp;quot;break&amp;quot; the disulfide bridge in the middle of the molecule.&#xA;This is the job file for my scan job of Tetramethylthiuramdisulfid&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%rwf=Tetramethylthiuramdisulfid.rwf&#xA;%NoSave&#xA;%chk=Tetramethylthiuramdisulfid.chk&#xA;#p opt=modredundant b3lyp/6-311++g(df,3p) nosymm&#xA;&#xA;Tetramethylthiuramdisulfid&#xA;&#xA;0 1&#xA;C                 -1.74592187   -0.85849184   -3.04571889&#xA;H                 -1.40943008   -1.30350450   -3.97938373&#xA;H                 -2.02299710    0.17009508   -3.24009808&#xA;H                 -2.59989913   -1.40635258   -2.66575731&#xA;C                 -0.71925406   -2.00684947   -1.11257147&#xA;H                  0.28707357   -2.34094083   -0.90110803&#xA;H                 -1.26310648   -2.82213958   -1.57474097&#xA;H                 -1.21061914   -1.72818310   -0.18319845&#xA;N                 -0.69637471   -0.89790505   -2.04320925&#xA;C                  0.24194475    0.03232282   -2.07621742&#xA;S                  0.48458418    1.13895429   -3.28209220&#xA;S                  1.50073028    0.30966253   -0.86090974&#xA;S                  1.25923450   -0.62165388    0.97873412&#xA;C                 -0.11055416    0.26088441    1.73601358&#xA;S                 -1.19921450    1.13723172    0.86384763&#xA;N                 -0.17557323    0.07031831    3.05850714&#xA;C                  0.82479554   -0.69237907    3.78321945&#xA;H                  0.64244558   -0.58545917    4.84382283&#xA;H                  0.78278163   -1.74952893    3.52785139&#xA;H                  1.82221281   -0.32440612    3.56290405&#xA;C                 -1.30366309    0.62423516    3.78483310&#xA;H                 -1.30718364    1.70769026    3.71156759&#xA;H                 -2.23638330    0.26687372    3.35848443&#xA;H                 -1.23069336    0.32351632    4.82194412&#xA;&#xA;D 16 14 13 12 S 11 30.0&#xA;D 14 13 12 10 S 11 30.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is the job running well and the visualization has a problem made by gaussview? I read earlier that sometimes gaussview can not show binding proper. Or do I need more functions for my basisset? To simulate the disulfide bridge better?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="1380" LastEditDate="2021-04-07T16:25:39.270" LastActivityDate="2021-04-08T09:27:24.213" Title="PES of Tetramethylthiuramdisulfid / Problem with Disulfidbridge" Tags="|density-functional-theory|basis-sets|gaussian|potential-energy-surface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4673" PostTypeId="1" AcceptedAnswerId="4675" CreationDate="2021-04-07T07:07:12.210" Score="6" ViewCount="72" Body="&lt;p&gt;I am looking to study Berry phase-like phenomena in an un-gapped material model. However, I am having trouble finding a widely-used 4-band model with analytic expressions for wavefunctions and energies. I am looking to compare results from numerical methods vs analytical ones; and would ideally already have these models in terms of k-space variables in some reasonable basis. Ultimately, I want to toy with this model by changing its diagonal values and seeing how bands 'invert'.&lt;/p&gt;&#xA;&lt;p&gt;The closest I got was some effective Hamiltonians for bilayer graphene in &lt;a href=&quot;https://arxiv.org/pdf/1205.6953.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/1205.6953.pdf&lt;/a&gt; (such as equation 76). However, solving for wavefunctions took a while using Mathematica, and led to messy-looking algebraic expressions. Isn't there a simpler model out there, of theoretical value? Or just a model that justifies using not-so-simple expressions?&#xA;I would find any appropriate 4-band condensed matter models very useful! Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-04-08T03:41:06.837" LastActivityDate="2021-04-08T03:41:06.837" Title="Example of a standard/archetypal/simple 4-band un-gapped condensed matter model with analytic results?" Tags="|condensed-matter|quantum-mechanics|model-hamiltonians|solid-state-physics|berry-phase|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4674" PostTypeId="2" ParentId="4672" CreationDate="2021-04-07T09:02:09.337" Score="7" Body="&lt;p&gt;Without seeing the result of the scan, my guess would be that it is a visualization problem with gaussview, and it has nothing to do with the calculation. Gaussview detects bonds by the distance between two atoms, and sometimes it does not show up, even though the distance is right.&lt;/p&gt;&#xA;&lt;p&gt;You can try two things—first, in the frames where you can't see the bonds, check the S-S distance: if it's the same as the other frames where the bond is showing, then your calculation is right. Second, you can use another visualisation software, and see if it renders the bond.&lt;/p&gt;&#xA;&lt;p&gt;I don't think that your basis set is so bad that your S-S covalent bond will break, that would not happen even with smaller basis sets than what you have used. Although adding an extra d-polarization function wouldn't hurt, but that's just my personal opinion.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-08T09:27:24.213" LastActivityDate="2021-04-08T09:27:24.213" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4675" PostTypeId="2" ParentId="4673" CreationDate="2021-04-07T14:46:31.787" Score="4" Body="&lt;p&gt;The Bernevig-Hughes-Zhang (BHZ) model for topological insulators comes to mind, see e.g. &lt;a href=&quot;https://topocondmat.org/w6_3dti/bhz.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this pedagogical introduction&lt;/a&gt; or the &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.83.1057&quot; rel=&quot;nofollow noreferrer&quot;&gt;review by Qi and Zhang&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/1008.2026&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv link here&lt;/a&gt;). It's often justified to set the block-off-diagonal terms zero, as was done in the &lt;a href=&quot;https://science.sciencemag.org/content/314/5806/1757&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; introducing the model (&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0611399&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version here&lt;/a&gt;), which simplifies analytical calculations considerably (it essentially becomes two two-band problems) but isn't expected to modify topological properties. This argument is made at least in the book by Bernevig and Hughes, and possibly also elsewhere.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-04-07T14:46:31.787" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4676" PostTypeId="1" AcceptedAnswerId="4677" CreationDate="2021-04-07T17:49:56.940" Score="8" ViewCount="172" Body="&lt;p&gt;A while ago I wrote a simple program that takes in an &lt;code&gt;FCIDUMP&lt;/code&gt; file (generated by &lt;code&gt;MOLRPO&lt;/code&gt;) and can determine matrix elements (or construct the whole FCI matrix), with the help of this forum in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4515/how-to-calculate-fci-matrix-elements-from-an-fcidump-file&quot;&gt;this thread&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, I didn't use any of the values at the top of the file, except for &lt;code&gt;NORB&lt;/code&gt; and &lt;code&gt;NELEC&lt;/code&gt; (which in the string representation were just half the length of the string and the number of ones). Presumably these serve to reduce the size of the matrix somehow (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1684/how-is-group-theory-used-to-deduce-which-of-these-integrals-are-equal-to-0&quot;&gt;maybe something with group theory&lt;/a&gt;), or have something to do with the irrep of the determinants. &lt;strong&gt;What do these parameters mean?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Perhaps it would also be helpful to work with an example, like the minimal STO-3G basis H2 (separation 1.4 bohr), if I use my program (which is hopefully correct...) I get an FCI matrix:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[-1.83100004  0.          0.          0.          0.          0.18125791]&#xA; [ 0.         -1.24609329  0.          0.          0.          0.        ]&#xA; [ 0.          0.         -1.06483537  0.18125791  0.          0.        ]&#xA; [ 0.          0.          0.18125791 -1.06483537  0.          0.        ]&#xA; [ 0.          0.          0.          0.         -1.24609329  0.        ]&#xA; [ 0.18125791  0.          0.          0.          0.         -0.25370925]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I know from Szabo and Ostlund (e.g. using pg 162) that this is reduced to&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[-1.8310000369984170       0.18125779940066075]&#xA; [0.18125779940066075      -0.25371106084836703]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How do I get here given the following?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NORB=  2,NELEC=  2,MS2= 0,&#xA;ORBSYM=1,5,&#xA;ISYM=1,&#xA;OCC=  1,  0,  0,  0,  0,  0,  0,  0,&#xA;CLOSED=  1,  0,  0,  0,  0,  0,  0,  0,&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And do the parameters give any extra information besides what is in the matrix?&lt;/p&gt;&#xA;" OwnerUserId="1522" LastEditorUserId="1522" LastEditDate="2021-04-08T15:11:03.400" LastActivityDate="2021-04-08T15:11:03.400" Title="What do the parameters at the top of an FCIDUMP file mean?" Tags="|software|ab-initio-calculations|molpro|fcidump|full-configuration-interaction|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4677" PostTypeId="2" ParentId="4676" CreationDate="2021-04-08T01:39:22.290" Score="6" Body="&lt;p&gt;&lt;code&gt;MS2&lt;/code&gt; is related to the spin. Specifically, it is the number of unpaired electrons. Your molecule is a singlet, which is why it says &lt;code&gt;0&lt;/code&gt;.&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ORBSYM&lt;/code&gt; is the list of symmetries for each orbital. In this case &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; is in &lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt; but almost all electronic structure codes do not support non-Abelian groups, so instead we would almost always use &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;. The &lt;code&gt;FCIDUMP&lt;/code&gt; format was invented by Peter Knowles, and the writing and reading of &lt;code&gt;FCIDUMP&lt;/code&gt; files would have been implemented in MOLPRO long before other software, so assuming this &lt;code&gt;FCIDUMP&lt;/code&gt; was written by MOLPRO, you can figure out what the &lt;code&gt;1&lt;/code&gt; and &lt;code&gt;5&lt;/code&gt; mean from the &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; table &lt;a href=&quot;https://www.molpro.net/info/current/doc/manual/node36.html&quot; rel=&quot;noreferrer&quot;&gt;here (Table 2)&lt;/a&gt;. This tells us that the first molecular orbital is of type &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt; and the second is of type &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;. That makes sense because in your minimal basis set with only 2 spatial orbitals, you have &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma^*$&lt;/span&gt; bonding and anti-bonding orbitals. You mentioned PySCF in the other question, and unfortunately &lt;a href=&quot;https://sunqm.github.io/pyscf/symm.html&quot; rel=&quot;noreferrer&quot;&gt;they have a different convention&lt;/a&gt; for labeling the irreps of &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;, in which &lt;span class=&quot;math-container&quot;&gt;$A_g=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B_{1u}=5$&lt;/span&gt;, which is not what you have in your &lt;code&gt;FCIDUMP&lt;/code&gt;, perhaps because you didn't use PySCF to print the &lt;code&gt;FCIDUMP&lt;/code&gt;, or because the PySCF documentation has an error. My open source &lt;a href=&quot;https://github.com/HPQC-LABS/QC_CheatSheet/blob/master/symmetry&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Quantum Chemistry Cheat Sheet&amp;quot;&lt;/a&gt; will help you translate between the languages of many of the most popular electronic structure programs, and here I'll just copy and paste from there the relevant information for &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; since you're dealing with &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;th&gt;irrep&lt;/th&gt;&#xA;&lt;th&gt;MOLPRO&lt;/th&gt;&#xA;&lt;th&gt;MRCC&lt;/th&gt;&#xA;&lt;th&gt;CFOUR&lt;/th&gt;&#xA;&lt;th&gt;PySCF&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;td&gt;6&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;7&lt;/td&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;6&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;8&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;7&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$d_{xy}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{1g}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$d_{xz}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{2g}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;6&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;7&lt;/td&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$d_{yz}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{3g}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;7&lt;/td&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;6&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$d_z^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$d_{x^2-y^2}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$f_{xyz}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$A_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;8&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;td&gt;8&lt;/td&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;By the way if you don't like how the &lt;span class=&quot;math-container&quot;&gt;$d_{x^2 - y^2}$&lt;/span&gt; orbital turns out in the table, you might consider supporting &lt;a href=&quot;https://meta.stackexchange.com/a/357525/391772&quot;&gt;my feature request to fix that bug&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ISYM&lt;/code&gt; is the overall symmetry of the molecule. &lt;span class=&quot;math-container&quot;&gt;$A_g \times B_{1u} = A_g$&lt;/span&gt;, which was labeled as &lt;code&gt;1&lt;/code&gt; in the program that you used to print that &lt;code&gt;FCIDUMP&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;OCC&lt;/code&gt; are the occupied orbitals for each irrep of the point group, which in this case is &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; so there's 8 entries there. Only an &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt; orbital is occupied, so the entries for all other irreps is &lt;code&gt;0&lt;/code&gt;, and the &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt; irrep has only one occupied orbital, which is the &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; bonding orbital, so we have a &lt;code&gt;1&lt;/code&gt; there. &lt;strong&gt;This means the anti-bonding &lt;span class=&quot;math-container&quot;&gt;$\sigma^*$&lt;/span&gt; orbital does not have any electrons in it.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;CLOSED&lt;/code&gt; are the closed orbitals, with the same convention as &lt;code&gt;OCC&lt;/code&gt;. Since there's 2 electrons in the one occupied orbital, we have a &amp;quot;closed&amp;quot; orbital. It would be open if it didn't have 2 electrons in it.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-08T01:39:22.290" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4678" PostTypeId="1" CreationDate="2021-04-08T02:38:59.560" Score="8" ViewCount="119" Body="&lt;p&gt;I am looking to study Berry phase-like phenomena in a &lt;strong&gt;gapped&lt;/strong&gt; 4-band material model. In particular, I want to numerically and analytically calculate the Abelian Berry curvature integral of each band over some region of k-space. It should be easy to calculate the Chern number of this system.&lt;/p&gt;&#xA;&lt;p&gt;However, I am having trouble finding a widely-used 4-band model with analytic expressions for wavefunctions and energies. I am looking to compare results from numerical methods vs analytical ones; and would ideally already have these models in terms of k-space variables in some reasonable basis. &lt;strong&gt;Ultimately, I want to toy with this model by changing its diagonal values to see how bands 'invert' after a gap-closing, and how their Berry curvatures change accordingly. Ideally, it would be easy to see edge states in a domain-wall-like setup, due to varying of an x-dependent diagonal/potential factor.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I first tried the BHZ model for the Z2 invariant (as recommended by the answer to this poorly-asked previous attempt of this question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4673/example-of-an-standard-archetypal-simple-4-band-un-gapped-condensed-matter-model&quot;&gt;here&lt;/a&gt;). However, the band degeneracies make it hard to study what I want to study: the Abelian Berry curvature is not well-defined; and when I tune the diagonal with some constant to force it to &amp;quot;gap&amp;quot;, the band crossings are too complicated. For example, the gap can close at several points besides the Gamma point.&lt;/p&gt;&#xA;&lt;p&gt;The closest I got was some effective Hamiltonians for bilayer graphene in &lt;a href=&quot;https://arxiv.org/pdf/1205.6953.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this PDF&lt;/a&gt; (such as equation 76). However, solving for wavefunctions took a while using Mathematica, and led to messy-looking algebraic expressions. Isn't there a simpler model out there, of theoretical value? Or just a model that justifies using not-so-simple expressions? I would find any appropriate 4-band condensed matter models very useful! Even suggestions for a simple/absurd toy model with potential nontrivial topology are welcome.&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-11-30T20:54:22.253" LastActivityDate="2021-11-30T20:54:22.253" Title="Example of a standard/archetypal/simple 4-band gapped condensed matter model with analytic results?" Tags="|condensed-matter|model-hamiltonians|solid-state-physics|topological-insulators|berry-phase|" AnswerCount="0" CommentCount="8" ClosedDate="2022-08-23T22:18:41.443" ContentLicense="CC BY-SA 4.0" />
  <row Id="4679" PostTypeId="1" CreationDate="2021-04-08T16:21:06.520" Score="10" ViewCount="369" Body="&lt;p&gt;I am new to DFT, especially in doing DFT for magnetic materials. I recently came across this &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.1999631#header&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; which indicated the calculation of the J value in the case of antiferromagentic materials as per the formula.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{HS}- E_{BS} = -J(2S_{1}S_{2}-S_{2}) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The paper describes the terms as  follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{HS}$&lt;/span&gt; : Energy of the triple state {High Spin}: I have calculated&#xA;this by constrained magnetization method in Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{BS}$&lt;/span&gt; : Energy of the Broken symmetry state {Low spin}: I have&#xA;doubts regarding what this is; I do believe its the anti-ferromagnetic&#xA;state {total magnetization = zero}. &lt;strong&gt;Correct me if Im wrong!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$S_{1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S_{2}$&lt;/span&gt; in the paper : where &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; are the&#xA;total spins of the paramagnetic centers and &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt;&amp;gt;&lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; has been&#xA;assumed for heterodinuclear complexes using the Heisenberg&#xA;Hamiltonian. &lt;strong&gt;I didnt quite understand this : How can I calculate&#xA;this?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Thank you in Advance!!&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2021-04-09T05:01:30.900" LastActivityDate="2021-05-16T21:57:28.200" Title="How can I calculate the J value in an antiferromagnetic material?" Tags="|density-functional-theory|magnetism|condensed-matter|model-hamiltonians|spin-exchange|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4680" PostTypeId="1" AcceptedAnswerId="4700" CreationDate="2021-04-09T01:14:21.323" Score="13" ViewCount="965" Body="&lt;p&gt;Based on HK's two theorems, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;density functional theory&lt;/a&gt; was built. Because one can't find the universal energy functional &lt;span class=&quot;math-container&quot;&gt;$F_{HK}[n(r)]$&lt;/span&gt;, Kohn and Sham further proposed the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kohn%E2%80%93Sham_equations&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kohn-Sham ansatz&lt;/a&gt;: mapping the interacting many-electron system to a noninteracting many-electron system (KS reference system) by keeping the ground-state electron density fixed. With that, the kinetic energy functional can be expressed with the help of the KS reference system. The variation of total energy functional respect to density &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; will result in the famous single-particle Schr&lt;span class=&quot;math-container&quot;&gt;$\ddot{\text{o}}$&lt;/span&gt;dinger-like equation (KS equation):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\left[ -\dfrac{1}{2}\nabla^2+V_{ext}+V_{hartree}+V_{xc} \right]\psi_i(\vec{r})=E_i\psi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This equation is derived based on the KS reference system, which is a noninteracting one. Then what does the &lt;span class=&quot;math-container&quot;&gt;$V_{hartree}$&lt;/span&gt; term describe? Does it still describe the electron-electron interaction of the original interacting many-electron system? If so, how can we say that the KS equation is describing a noninteracting many-electron system? Or more directly:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What's the difference for the Hartree term between the original interacting many-electron system and the noninteracting KS reference system?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-04-11T04:41:57.803" LastActivityDate="2021-04-14T22:16:09.110" Title="How can we say that the KS equation is describing a noninteracting many-electron system?" Tags="|density-functional-theory|condensed-matter|quantum-mechanics|kohn-sham|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4681" PostTypeId="1" CreationDate="2021-04-09T02:38:45.273" Score="13" ViewCount="152" Body="&lt;p&gt;I am looking for a list of programs that support structure relaxations via molecular mechanics (e.g. via UFF) with the following conditions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The program is free (free with an academic license is okay)&lt;/li&gt;&#xA;&lt;li&gt;It works on materials with periodic boundary conditions&lt;/li&gt;&#xA;&lt;li&gt;It can read/write CIF&lt;/li&gt;&#xA;&lt;li&gt;It has a GUI&lt;/li&gt;&#xA;&lt;li&gt;It supports automatic bond-typing that can be adjusted via the GUI if desired&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;An example of a commercial program that can do this is Materials Studio. I'm looking for free alternatives, however.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-04-09T02:43:46.683" LastActivityDate="2021-04-26T19:22:36.563" Title="GUI-based force field optimization with bond-typing" Tags="|one-topic-per-answer|software-recommendations|" AnswerCount="1" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="4682" PostTypeId="2" ParentId="4680" CreationDate="2021-04-09T03:29:14.177" Score="12" Body="&lt;p&gt;First of all, let me emphasize that it is more appropriate to speak of KS equations (plural), which you correctly denoted by an index &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; in your post. This index goes over all KS orbitals (i.e. single-particle wavefunctions) of the system. Additionally, as you mentioned, these equations have the same form as the single-particle Schrödinger equation. And combined that is the reason why density-functional theory (DFT) is said to be a noninteracting theory.&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless, &lt;strong&gt;exchange and correlation&lt;/strong&gt; (xc) &lt;strong&gt;effects are effectively taken into account through the energy functional&lt;/strong&gt; that can be computed self-consistently in order to resemble the true quantum-mechanical state,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{1}&#xA;\Psi(\vec{r}_1\sigma_1,\vec{r}_2\sigma_2, ...,\vec{r}_N\sigma_N),&#xA;\end{equation}&lt;/span&gt;&#xA;that can be described by a many-particle wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Concerning the &lt;strong&gt;form of &lt;span class=&quot;math-container&quot;&gt;$V_{hartree}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt;&lt;/strong&gt;, assume we can determine the KS orbitals &lt;span class=&quot;math-container&quot;&gt;$\{\psi_i\}$&lt;/span&gt; with eigenenergies &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt; below the Fermi energy, that allows us to express the electronic density as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{2}&#xA;n(\vec{r}) = \sum_{i=1}^N \psi^*_i(\vec{r})\psi_i(\vec{r}).&#xA;\end{equation}&lt;/span&gt;&#xA;Then, it is convenient to split the electron-electron interaction &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; into the Hartree term &lt;span class=&quot;math-container&quot;&gt;$U_{hartree}$&lt;/span&gt; and the remainder &lt;span class=&quot;math-container&quot;&gt;$U_{xc}$&lt;/span&gt;. That is because the Hartree potential &lt;span class=&quot;math-container&quot;&gt;$V_{hartree}$&lt;/span&gt; &lt;em&gt;explicitly depends on the electron density&lt;/em&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{3}&#xA;V_{hartree} = 2 \int \text{d} \vec{r}' \frac{n(\vec{r}')}{|\vec{r} - \vec{r}'|}.&#xA;\end{equation}&lt;/span&gt;&#xA;Mind, that also the kinetic energy is split into the kinetic energy of the noninteracting system &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt; and the remainder &lt;span class=&quot;math-container&quot;&gt;$T_{xc}$&lt;/span&gt;. The &lt;em&gt;xc energy functional&lt;/em&gt; collects these terms:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{4}&#xA;E_{xc}[n]=T_{xc}[n] + U_{xc}[n].&#xA;\end{equation}&lt;/span&gt;&#xA;Finally, the &lt;em&gt;xc potential&lt;/em&gt; is obtained via variation w.r.t. the electron density:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{5}&#xA;V_{xc}(\vec{r})=\frac{\delta E_{xc}[n(\vec{r})]}{\delta n(\vec{r})} .&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Units etc. as in J. Kübler, &lt;em&gt;Theory of Itinerant Electron Magnetism&lt;/em&gt; (Oxford University Press, 2017)&lt;/p&gt;&#xA;" OwnerUserId="2237" LastEditorUserId="2237" LastEditDate="2021-04-09T06:17:12.220" LastActivityDate="2021-04-09T06:17:12.220" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4683" PostTypeId="1" CreationDate="2021-04-09T04:41:08.810" Score="9" ViewCount="169" Body="&lt;p&gt;I am studying point defects in hBN using Quantum ESPRESSO. It is not clear if electron spin-spin interactions are typically/can be included in DFT calculations. I understand that spin-orbit interactions can be included in the calculation by performing a noncollinear calculation with &lt;code&gt;lspinorb = .true.&lt;/code&gt;. I have also found some papers which discuss zero-field-splitting, but cannot find much information about magnetic dipole-dipole interactions. It would make sense to me if the interaction was included in the functional, but it appears that only the Coulomb interaction is considered (I am using the HSE functional). Perhaps spin-polarized calculations somehow include the spin-spin interaction?&lt;/p&gt;&#xA;" OwnerUserId="3358" LastEditorUserId="5" LastEditDate="2021-04-09T04:58:07.567" LastActivityDate="2021-04-09T18:59:22.343" Title="Are electron dipolar spin-spin interactions included in DFT calculations?" Tags="|density-functional-theory|quantum-espresso|dipole|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4684" PostTypeId="2" ParentId="4683" CreationDate="2021-04-09T18:59:22.343" Score="5" Body="&lt;p&gt;No. Magnetic dipole interactions are not included in DFT. In solids, this effect is usually very weak. If you want to calculate it, you can just solve the contribution to the Hamiltonian analytically. Just write a code which takes in the moment, distances between magnetic atoms in expression 1 (&lt;a href=&quot;https://en.wikipedia.org/wiki/Magnetic_dipole%E2%80%93dipole_interaction&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Magnetic_dipole%E2%80%93dipole_interaction&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-04-09T18:59:22.343" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4685" PostTypeId="1" AcceptedAnswerId="4688" CreationDate="2021-04-10T08:08:16.863" Score="5" ViewCount="390" Body="&lt;p&gt;I have read in the article at the reference below that :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the Mn substitution leads to localized states (impurity bands) within the band gap. The Mn 3d orbitals split into a single a&lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt; (d&lt;span class=&quot;math-container&quot;&gt;$_{z^2}$&lt;/span&gt;) state and two twofold degenerate e&lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt; (d&lt;span class=&quot;math-container&quot;&gt;$_{xz/x^2-y^2}$&lt;/span&gt;) and e&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; (d&lt;span class=&quot;math-container&quot;&gt;$_{xz/yz}$&lt;/span&gt;) since the Mn atom under the crystal field has a C3v symmetry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;My question is what is the meaning of a&lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt;, e&lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt; and e&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; states? What do they refer to?&lt;/p&gt;&#xA;&lt;p&gt;Reference paper : 10.1039/c4cp00247d&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="671" LastEditDate="2021-04-10T17:33:30.480" LastActivityDate="2021-04-10T17:33:30.480" Title="What is the meaning of these d states names?" Tags="|density-functional-theory|dos|doping|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4686" PostTypeId="1" CreationDate="2021-04-10T08:09:50.223" Score="9" ViewCount="1938" Body="&lt;p&gt;I did a calculation on a bulk system with DFT and fit it with the tight binding matrix with wannier90. There is question on this. I try to write my own code to construct a slab tight binding matrix from this bulk matrix. But I can't find any documentation mention how the orbital basis was arrange in this matrix. (for example, I don't know which column correspond to particular orbital and particular atom.) I can only obtain the energy spectrum from it. Is there anyone who did this before ?&lt;/p&gt;&#xA;" OwnerUserId="621" LastActivityDate="2021-04-11T04:01:57.483" Title="Data format of wannier90_hr.dat from wannier90" Tags="|density-functional-theory|tight-binding|wannier90|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4687" PostTypeId="2" ParentId="4686" CreationDate="2021-04-10T10:08:42.090" Score="8" Body="&lt;p&gt;The following code is a python function to read the &lt;code&gt;wannier90_hr.dat&lt;/code&gt;, from which you should figure out its data structure.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def read_hamiltonian(path):&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Read hopping matrix element from the wannier90 output file:wannier90_hr.dat&#xA;    wan_num: number of wannier functions&#xA;    wsc_num: number of wigner-sitez cells&#xA;    wsc_count: variables related to degeneracy&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;    with open(path,&amp;quot;r&amp;quot;) as f:&#xA;        lines=f.readlines()&#xA;&#xA;    wan_num=int(lines[1]); wsc_num=int(lines[2])&#xA;    ski_row_num=int(np.ceil(wsc_num/15.0))      # skip row numbers&#xA;    wsc_count=[]&#xA;    for i in range(ski_row_num):&#xA;        wsc_count.extend(list(map(int,lines[i+3].split())))&#xA;&#xA;    wsc_tot=np.zeros((wan_num**2*wsc_num,3))&#xA;    tem_tot=np.zeros((wan_num**2*wsc_num,2))&#xA;    for i in range(wan_num**2*wsc_num):&#xA;        wsc_tot[i,:]=list(map(int,lines[3+ski_row_num+i].split()[:3]))&#xA;        tem_tot[i,:]=list(map(float,lines[3+ski_row_num+i].split()[5:]))&#xA;&#xA;    wsc_idx=wsc_tot[0:-1:wan_num**2,:]   # the translational vector between wigner-sitez cells&#xA;    hop_mat=np.reshape(tem_tot[:,0]+1j*tem_tot[:,1],[wan_num,wan_num,wsc_num],order='F')&#xA;&#xA;    return hop_mat,wsc_idx,wsc_count,wan_num&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To run this function, just input the path to &lt;code&gt;wannier90_hr.dat&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;PS: this function is tested only for the &lt;code&gt;Wannier1.2&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-10T10:08:42.090" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4688" PostTypeId="2" ParentId="4685" CreationDate="2021-04-10T10:37:34.240" Score="7" Body="&lt;p&gt;The following screencast is from the cited paper (Seems there is a typo in the description):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EqMdp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EqMdp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-orbitals of Mn atoms are split into three groups due to the &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4817409&quot; rel=&quot;noreferrer&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$C_{3v}$&lt;/span&gt; point group symmetry&lt;/a&gt;, which is a general conclusion from the &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;noreferrer&quot;&gt;crystal field theory&lt;/a&gt; based on group theory.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/llYgK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/llYgK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$e_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$e_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$a_1$&lt;/span&gt; are the symbols of the corresponding irreducible representation from group theory.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-04-10T10:37:34.240" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4689" PostTypeId="5" CreationDate="2021-04-10T13:38:11.840" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-04-10T13:38:11.840" LastActivityDate="2021-04-10T13:38:11.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4690" PostTypeId="4" CreationDate="2021-04-10T13:38:11.840" Score="0" Body="For questions related to the program wannier90, a program that calculates maximally localized Wannier Functions" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-11T17:22:48.707" LastActivityDate="2021-04-11T17:22:48.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4691" PostTypeId="2" ParentId="4685" CreationDate="2021-04-10T17:31:10.087" Score="6" Body="&lt;p&gt;To add to Jack's answer, I'll point out that the &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; etc. labels are symmetry labels of the orbitals in an irreducible representation (irrep). They are lower-case versions of their corresponding &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_character_tables_for_chemically_important_3D_point_groups#Notation&quot; rel=&quot;noreferrer&quot;&gt;Mulliken symbols&lt;/a&gt; found in &lt;a href=&quot;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=403&amp;amp;option=4&quot; rel=&quot;noreferrer&quot;&gt;character tables&lt;/a&gt;. There are four letters that tend to show up in &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-orbital systems:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt;, indicating two-fold degeneracy&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;, indicating three-fold degeneracy&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;, indicating non-degeneracy (or single degeneracy). &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;) is picked if the irrep is symmetric (anti-symmetric) with respect to rotation about the principal axis. In addition, &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is picked if there's no well-defined &lt;span class=&quot;math-container&quot;&gt;$C_n$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$S_n$&lt;/span&gt; operation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the case of &lt;span class=&quot;math-container&quot;&gt;$C_\mathrm{3v}$&lt;/span&gt; you can take the principal axis to be &lt;span class=&quot;math-container&quot;&gt;$\hat{z}$&lt;/span&gt;, in which case it's clear that &lt;span class=&quot;math-container&quot;&gt;$d_{z^2}$&lt;/span&gt; must transform symmetrically, and should be labeled &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For non-degenerate irreps (&lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;), the subscripts &lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; indicate symmetry and anti-symmetry, respectively, under rotation about a non-principal axis (perpendicular to the principal axis). In case of multidimensional representations (&lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;), the numerical subscript is used to distinguish between inequivalent irreps that aren't separated under other rules.&lt;/p&gt;&#xA;&lt;p&gt;Finally, you also asked about the &lt;span class=&quot;math-container&quot;&gt;$t_{2g}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$e_g$&lt;/span&gt; orbitals that show up in e.g. an octahedral environment. Here, the subscript &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; indicates the wave function is symmetric around an inversion center. &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; comes from the German word &amp;quot;gerade&amp;quot;, meaning even. This can be contrasted with the subscript &lt;span class=&quot;math-container&quot;&gt;$u$&lt;/span&gt; for &amp;quot;ungerade&amp;quot;, indicating antisymmetry around the inversion center.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-04-10T17:31:10.087" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4692" PostTypeId="2" ParentId="4686" CreationDate="2021-04-11T00:30:47.000" Score="6" Body="&lt;p&gt;You can read the wanniertools code. In wanniertools, to calculate surface state, they write a surfstate subroutine in surfstate.f90 file. The slab Hamiltonian is restructured from a bulk Hamiltonian in ham_qlayer2qlayer.f90 file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;enter code here&#xA; ! This is a fortran code.&#xA; ! H00 Hamiltonian between nearest neighbour-quintuple-layers&#xA; ! the factor 2 is induced by spin&#xA;&#xA; ! to read the matrix from hr file&#xA; Hij=0.0d0&#xA; do iR=1,Nrpts&#xA;    ia=irvec(1,iR)&#xA;    ib=irvec(2,iR)&#xA;    ic=irvec(3,iR)&#xA;&#xA;    call latticetransform(ia, ib, ic, new_ia, new_ib, new_ic)&#xA;&#xA;    inew_ic= int(new_ic)&#xA;    if (abs(new_ic).le.ijmax)then&#xA;       kdotr=k(1)*new_ia+ k(2)*new_ib&#xA;       ratio=cos(2d0*pi*kdotr)+zi*sin(2d0*pi*kdotr)&#xA;&#xA;       Hij(inew_ic, 1:Num_wann, 1:Num_wann )&amp;amp;&#xA;       =Hij(inew_ic, 1:Num_wann, 1:Num_wann )&amp;amp;&#xA;       +HmnR(:,:,iR)*ratio/ndegen(iR)&#xA;    endif&#xA;&#xA; enddo&#xA;&#xA; H00new=0.0d0&#xA; H01new=0.0d0&#xA;&#xA; ! nslab's principle layer &#xA; ! H00new&#xA; do i=1,Np&#xA; do j=1,Np&#xA;    if (abs(i-j).le.(ijmax)) then&#xA;      H00new(Num_wann*(i-1)+1:Num_wann*i,Num_wann*(j-1)+1:Num_wann*j)&amp;amp;&#xA;            =Hij(j-i,:,:)&#xA;    endif&#xA; enddo&#xA; enddo&#xA;&#xA; ! H01new&#xA; do i=1,Np&#xA; do j=Np+1,Np*2&#xA;    if (j-i.le.ijmax) then&#xA;       H01new(Num_wann*(i-1)+1:Num_wann*i,&amp;amp;&#xA;           Num_wann*(j-1-Np)+1:Num_wann*(j-Np))=Hij(j-i,:,:)&#xA;    endif&#xA; enddo&#xA; enddo&#xA;&#xA; do i=1,Ndim&#xA; do j=1,Ndim&#xA;    if(abs(H00new(i,j)-conjg(H00new(j,i))).ge.1e-4)then&#xA;   !  write(stdout,*)'there are something wrong with ham_qlayer2qlayer'&#xA;   !stop&#xA;    endif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To download the code: &lt;a href=&quot;https://github.com/quanshengwu/wannier_tools&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/quanshengwu/wannier_tools&lt;/a&gt;&lt;br /&gt;&#xA;To read the manual: &lt;a href=&quot;http://www.wanniertools.com/&quot; rel=&quot;noreferrer&quot;&gt;http://www.wanniertools.com/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3331" LastEditorUserId="3331" LastEditDate="2021-04-11T04:01:57.483" LastActivityDate="2021-04-11T04:01:57.483" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4693" PostTypeId="1" AcceptedAnswerId="4719" CreationDate="2021-04-11T08:01:26.730" Score="11" ViewCount="692" Body="&lt;p&gt;I have performed a Gaussian16 calculation to explore the size-consistency problem for the CISD method. The system I am studying is the water dimer and the results are not what I expected at first. I have computed the energy of the dimer for both models (single point calculation) where the two monomers are 100 Å away and the energy of the monomer.&lt;/p&gt;&#xA;&lt;p&gt;I wanted to compute the difference between those energies for both methods as two times the energy of the monomer and the energy of the dimer. If a method is size-consistent, the difference should be zero. These are my results:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{lrr}&#xA;\hline&#xA;\text{Quantity}  &amp;amp; \text{CCSD} &amp;amp; \text{CISD} \\&#xA;\hline&#xA;\text{Monomer energy}/\pu{Ha}  &amp;amp; -75.013  &amp;amp; -75.012  \\&#xA;\text{Dimer energy}/\pu{Ha}    &amp;amp; -150.030 &amp;amp; -150.026 \\&#xA;\text{Abs. difference}/\pu{Ha} &amp;amp; 0.004    &amp;amp; 0.002    \\&#xA;\hline&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have been reading many articles and papers and what I expected is that CISD is not size-consistent for a system of more than two electrons while CCSD is size-consistent.&lt;/p&gt;&#xA;&lt;p&gt;However, the value of the difference is larger in the case of CCSD, what makes me think that it is telling me that CCSD is less size-consistent for my problem than CISD. Am I wrong? What do these values mean?&lt;/p&gt;&#xA;&lt;p&gt;This is the code I used in Gaussian for the distanced monomers:&lt;/p&gt;&#xA;&lt;p&gt;CISD&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p CISD SP&#xA;&#xA;water dimer CISD SP&#xA;&#xA;0  1&#xA;O&#xA;H  1  r2&#xA;H  1  r3  2  a3&#xA;O  2  r4  1  a4  3  d4&#xA;H  4  r5  2  a5  1  d5&#xA;H  4  r6  2  a6  1  d6&#xA;Variables:&#xA;r2= 0.9700&#xA;r3= 0.9700&#xA;a3= 108.00&#xA;r4= 100.0000&#xA;a4= 175.00&#xA;d4= 179.97&#xA;r5= 0.9700&#xA;a5= 110.00&#xA;d5= 300.00&#xA;r6= 0.9700&#xA;a6= 110.00&#xA;d6=  50.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;CCSD&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p CCSD SP&#xA;&#xA;water dimer CCSD SP&#xA;&#xA;0  1&#xA;O&#xA;H  1  r2&#xA;H  1  r3  2  a3&#xA;O  2  r4  1  a4  3  d4&#xA;H  4  r5  2  a5  1  d5&#xA;H  4  r6  2  a6  1  d6&#xA;Variables:&#xA;r2= 0.9700&#xA;r3= 0.9700&#xA;a3= 108.00&#xA;r4= 100.0000&#xA;a4= 175.00&#xA;d4= 179.97&#xA;r5= 0.9700&#xA;a5= 110.00&#xA;d5= 300.00&#xA;r6= 0.9700&#xA;a6= 110.00&#xA;d6=  50.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="1522" LastEditDate="2021-04-13T22:03:19.947" LastActivityDate="2021-04-15T00:30:14.093" Title="CCSD and CISD size-consistency problem" Tags="|quantum-chemistry|gaussian|coupled-cluster|configuration-interaction|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4694" PostTypeId="2" ParentId="4693" CreationDate="2021-04-11T17:16:46.827" Score="6" Body="&lt;p&gt;CISD is not size-consistent for more than two electrons, and CCSD is &lt;em&gt;&lt;strong&gt;size-consistent&lt;/strong&gt;&lt;/em&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1329/5&quot;&gt;size-extensive&lt;/a&gt; for any number of electrons.&lt;/p&gt;&#xA;&lt;p&gt;With CCSD, if you calculate the &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; energy for a bond length of 1000 Å, you should get the same thing as you would get by calculating the energy of a &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}$&lt;/span&gt; atom and multiplying it by two, and this would work for all &amp;quot;dimers&amp;quot; as long as the bond length is large enough, but will not always work with CISD.&lt;/p&gt;&#xA;&lt;p&gt;In your case, the &amp;quot;dimer&amp;quot; is not of two atoms, but is of two molecules. I suppose an atom and a molecule are not much different, in that they are both just many-electron systems (ignoring cases like the H atom or its cation), though there is the difference that one's geometry is typically treated as just a point, versus the other one having a more complicated geometry (the impact of this should get smaller as the distance between the two &amp;quot;monomers&amp;quot; gets larger though).&lt;/p&gt;&#xA;&lt;p&gt;Here is what I would recommend:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Try again after switching from 100 Å to 1000 Å.&lt;/li&gt;&#xA;&lt;li&gt;Tell us your basis set and give us the &lt;code&gt;XYZ&lt;/code&gt; or &lt;code&gt;ZMAT&lt;/code&gt; file so that we can double-check to see that we're getting the same problem (perhaps also tell us if you're using RHF or UHF and RCCSD or UCCSD, etc.).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Also: why is your CCSD energy exactly the same as your CISD energy? Something must be wrong, and simply fixing this may fix your problem.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-11T17:16:46.827" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4695" PostTypeId="5" CreationDate="2021-04-11T20:09:15.953" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-04-11T20:09:15.953" LastActivityDate="2021-04-11T20:09:15.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4696" PostTypeId="4" CreationDate="2021-04-11T20:09:15.953" Score="0" Body="For questions involving materials showing anti-ferromagnetism, or anti-ferromagnetic coupling of electrons." OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-13T04:04:28.337" LastActivityDate="2021-04-13T04:04:28.337" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4697" PostTypeId="1" AcceptedAnswerId="4754" CreationDate="2021-04-11T20:41:11.600" Score="4" ViewCount="207" Body="&lt;p&gt;While studying statistical thermodynamics I came across the partition functions, which connect the quantum world to the macroscopic world. I understand that partition functions are used to calculate the thermodynamic properties of the system such as Gibbs free energy. The total partition function contains contributions from translational, rotational, vibrational and electronic partition functions (in the weak coupling limit).&lt;/p&gt;&#xA;&lt;p&gt;The electronic partition function for n-levels is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}q_{elec}=\sum^n_i g_i e^{-\beta\varepsilon_i}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\beta=\frac{1}{k_\text{B}T}$&lt;/span&gt;;  &lt;span class=&quot;math-container&quot;&gt;$g_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_i$&lt;/span&gt; represent the degeneracy and energy of the i-th energy level.&lt;/p&gt;&#xA;&lt;p&gt;Now, obviously for most closed shell organic molecules the first excited state is too high in energy so the contribution to the sum would be very low, and we can neglect them. The partition function will consist of contribution from only the ground state energy level.&lt;/p&gt;&#xA;&lt;p&gt;When I read the thermochemistry &lt;a href=&quot;https://gaussian.com/thermo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; of Gaussian16, it mentions that Gaussian always assumes that the first and higher excited states are inaccessible so neglects their contribution. &lt;strong&gt;This works for organic molecules, but what happens when the excited states are closer in energy to the ground state, for example in open-shell molecules or in atoms?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is where everything becomes confusing to me. If I understand correctly, when the first or higher excited states are closer in energy to the ground state, the Hartree-Fock single determinant solution is not good enough. We use multi-configurational methods (such as CASSCF) where we generate excited determinants and consider the molecule's electronic state as a superposition of the different determinants (weighted by their energies?). So this means the solution itself contains contributions from the low-lying excited states.&lt;/p&gt;&#xA;&lt;p&gt;I might be wrong here, but I think the energy levels obtained from CASSCF calculations are obtained as an average of all the determinants, and have partial occupation numbers reflecting the excited state contributions.&lt;/p&gt;&#xA;&lt;p&gt;So, &lt;strong&gt;what happens when we do the thermochemistry calculation on a multi-configurational system? Does that mean the electronic partition function term is already included in the SCF energy?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does this type of thermochemistry calculation actually make sense?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Linked question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4699/casscf-and-thermochemistry-effect-of-excited-determinants-on-rotational-and-vibr&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-12T09:06:27.953" LastActivityDate="2021-04-20T02:43:31.393" Title="Excited determinants, electronic partition function and thermochemistry calculation" Tags="|software|statistical-thermodynamics|thermodynamics|multi-reference|casscf|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4698" PostTypeId="2" ParentId="2269" CreationDate="2021-04-11T22:35:54.993" Score="1" Body="&lt;h3&gt;Advantage for QMC:&lt;/h3&gt;&#xA;&lt;p&gt;While this question is quite open ended due to there being at least &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;15 different types of QMC&lt;/a&gt;, one thing that all 15 of those methods have in common is that as far as I know they can all be restarted when the calculation has to stop for whatever reason. Since you pointed out that ACFDT-RPA calculations cannot be restarted, the ability to restart a calculation provides us with at least one advantage that QMC has over ACFDT-RPA.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-11T22:35:54.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4699" PostTypeId="1" AcceptedAnswerId="4703" CreationDate="2021-04-12T09:05:39.330" Score="4" ViewCount="104" Body="&lt;p&gt;So this question is linked to the other &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4697/excited-determinants-electronic-partition-function-and-thermochemistry-calculat&quot;&gt;question&lt;/a&gt; I asked about the electronic patition function and CASSCF. When calculating thermochemical data (e.g. Gibbs Free energy) the partition functions are calculated. This includes the vibrational and rotational partition functions along with the electronic and translational terms.&lt;/p&gt;&#xA;&lt;p&gt;Now when we use CASSCF, we are using multiple determinants, which can be considered as low lying excited states of the molecule. My first thought was that considering excited states would mean the electronic partition function term is now included in the SCF energy (which is what my earlier question is about).&lt;/p&gt;&#xA;&lt;p&gt;But what happens to the other degrees of freedom? For example, the vibrational modes are obvioulsy calculated based on the CASSCF solution, so it contains the contribution of the vibrational modes of the excited states. &lt;strong&gt;Does this type of calculation actually make sense&lt;/strong&gt;?&lt;/p&gt;&#xA;&lt;p&gt;In my lectures, what my professor told us is that we take the ground state, and then we calculate all the partition functions independently based on the ground state. &lt;strong&gt;So what happens when the contribution of excited determinants are included in the vibrational and rotational terms&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-04-15T06:27:34.493" Title="CASSCF and thermochemistry—effect of excited determinants on rotational and vibrational modes" Tags="|statistical-thermodynamics|thermodynamics|casscf|multi-reference|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4700" PostTypeId="2" ParentId="4680" CreationDate="2021-04-12T10:55:18.637" Score="9" Body="&lt;p&gt;As you note, the interacting electrons and the Kohn-Sham non-interacting electrons have the same density. How is this possible when the Hamiltonians for the two systems are so different?&lt;/p&gt;&#xA;&lt;p&gt;The answer is that the Kohn-Sham potential—the potential felt by the non-interacting electrons—is constructed very carefully. Namely, if we want to remove electron-electron interactions but preserve the electron density, we must add &lt;span class=&quot;math-container&quot;&gt;$v_{Hartree}+v_{xc}$&lt;/span&gt; to the original external potential:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;v_{KS} = v_{ext}+v_{Hartree}+v_{xc} .&#xA;$$&lt;/span&gt;&#xA;See the Kohn-Sham paper for the derivation.&lt;/p&gt;&#xA;&lt;p&gt;Turning now to your main question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What's the difference for the Hartree term between the original interacting many-electron system and the noninteracting KS reference system?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the original &lt;strong&gt;interacting system&lt;/strong&gt;, the Hartree term accounts for electron-electron interactions, and it is a prominent contribution to the total electron-electron interaction. It is completely separate from the external potential term.&lt;/p&gt;&#xA;&lt;p&gt;In the &lt;strong&gt;non-interacting system&lt;/strong&gt;, there are no electron-electron interactions, and the Hartree potential appears in the effective external potential. Moreover, it appears purely as a consequence of electron-electron interactions &lt;em&gt;in the original system,&lt;/em&gt; and its purpose here is to keep the electron densities of the two systems identical. Why? So that we may ultimately obtain the non-interacting kinetic energy &lt;em&gt;for that density&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, one might ask: practically, how can &lt;span class=&quot;math-container&quot;&gt;$v_{KS}$&lt;/span&gt; depend on the electron density? Answer: the Kohn-Sham equations must be solved &lt;em&gt;self-consistently&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-04-14T22:16:09.110" LastActivityDate="2021-04-14T22:16:09.110" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4701" PostTypeId="1" AcceptedAnswerId="4708" CreationDate="2021-04-12T20:16:47.337" Score="9" ViewCount="2569" Body="&lt;p&gt;I am trying to perform the pressure-induced DFT calculations in Quantum ESPRESSO. For this, I have calculated the lattice constant of the cubic structure by &lt;code&gt;vc-relax&lt;/code&gt; calculation. Then I tried to reduce to lattice constant slightly (say 5%,10%) keeping the other parameters constant to see how reducing the lattice constants affects the band structure of the crystal.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Doubts&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;p&gt;As far as I understand, reducing the lattice constant will have the same effect as applying the external pressure on the crystal. &lt;strong&gt;Am I thinking it correctly in view of DFT calculations or there is already provided executables in Quantum ESPRESSO to perform pressure applied DFT calculations on a given system?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also when I am trying to decrease the lattice constant of crystal from the actual lattice constant, its, structure gets distorted. Below I have attached two images of the same crystal with actual and 10% reduced lattice constant:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Actual lattice constant: 5.7981 Angstrom&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LJZUD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LJZUD.png&quot; alt=&quot;Mn2CoGa_actual&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;10% reduced lattice constant: 5.218 Angstrom&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bNPQD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bNPQD.png&quot; alt=&quot;Mn2CoGa_distorted&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The distorted structure can be easily seen in the second image with a reduced lattice constant.&lt;/p&gt;&#xA;&lt;p&gt;Now I am wondering, &lt;strong&gt;how can I perform DFT calculations by applying external pressure? Since reducing the lattice constant corrupts the actual structure. Should I go any other way?&lt;/strong&gt;&lt;br /&gt;&#xA;Please clarify my doubts.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The PWscf input files can be found &lt;a href=&quot;https://github.com/UJ5/Modeling_Matters/tree/master/4701&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/strong&gt;  and in the &lt;code&gt;code&lt;/code&gt; blocks below:&lt;/p&gt;&#xA;&lt;p&gt;10% reduced lattice:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                       title = 'Mn2CoGa' ,&#xA;                 calculation = 'scf' ,&#xA;                      outdir = '.' ,&#xA;                  pseudo_dir = '.' ,&#xA;                    &#xA;                      prefix = 'Mn2CoGa' ,&#xA;               etot_conv_thr = 1.0D-6 ,&#xA;               forc_conv_thr = 1.0D-6 ,&#xA;                     tstress = .true. ,&#xA;                     tprnfor = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 9.861191964,&#xA;                         nat = 4,&#xA;                        ntyp = 3,&#xA;                     ecutwfc = 200 ,&#xA;                     ecutrho = 2000 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.01 ,&#xA;                    smearing = 'marzari-vanderbilt' ,&#xA;                       nspin = 2 ,&#xA;   starting_magnetization(1) = -0.167,&#xA;   starting_magnetization(2) = -0.083,&#xA;   starting_magnetization(3) =  0.005,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Mn   54.93804  mn_pbe_v1.5.uspp.F.UPF &#xA;   Co   58.93319  Co_pbe_v1.2.uspp.F.UPF &#xA;   Ga   69.72300  Ga.pbe-dn-kjpaw_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Co      0.500000000    0.500000000    0.500000000    &#xA;   Mn      0.250000000    0.250000000    0.250000000    &#xA;   Ga      0.750000000    0.750000000    0.750000000    &#xA;   Mn      0.000000000    0.000000000    0.000000000     &#xA;K_POINTS automatic &#xA; 12 12 12 0 0 0 &#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;5% reduced lattice:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                       title = 'Mn2CoGa' ,&#xA;                 calculation = 'scf' ,&#xA;                      outdir = '.' ,&#xA;                  pseudo_dir = '.' ,&#xA;                    &#xA;                      prefix = 'Mn2CoGa' ,&#xA;               etot_conv_thr = 1.0D-6 ,&#xA;               forc_conv_thr = 1.0D-6 ,&#xA;                     tstress = .true. ,&#xA;                     tprnfor = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 10.40903596,&#xA;                         nat = 4,&#xA;                        ntyp = 3,&#xA;                     ecutwfc = 300 ,&#xA;                     ecutrho = 3000 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.01 ,&#xA;                    smearing = 'marzari-vanderbilt' ,&#xA;                       nspin = 2 ,&#xA;   starting_magnetization(1) = -0.167,&#xA;   starting_magnetization(2) = -0.083,&#xA;   starting_magnetization(3) =  0.005,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Mn   54.93804  mn_pbe_v1.5.uspp.F.UPF &#xA;   Co   58.93319  Co_pbe_v1.2.uspp.F.UPF &#xA;   Ga   69.72300  Ga.pbe-dn-kjpaw_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Co      0.500000000    0.500000000    0.500000000    &#xA;   Mn      0.250000000    0.250000000    0.250000000    &#xA;   Ga      0.750000000    0.750000000    0.750000000    &#xA;   Mn      0.000000000    0.000000000    0.000000000     &#xA;K_POINTS automatic &#xA; 20 20 20 0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Actual lattice:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;                       title = 'Mn2CoGa' ,&#xA;                 calculation = 'scf' ,&#xA;                      outdir = '.' ,&#xA;                  pseudo_dir = '.' ,&#xA;                    &#xA;                      prefix = 'Mn2CoGa' ,&#xA;               etot_conv_thr = 1.0D-6 ,&#xA;               forc_conv_thr = 1.0D-6 ,&#xA;                     tstress = .true. ,&#xA;                     tprnfor = .true. ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 10.95687996,&#xA;                         nat = 4,&#xA;                        ntyp = 3,&#xA;                     ecutwfc = 200 ,&#xA;                     ecutrho = 2000 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.01 ,&#xA;                    smearing = 'marzari-vanderbilt' ,&#xA;                       nspin = 2 ,&#xA;   starting_magnetization(1) = -0.167,&#xA;   starting_magnetization(2) = -0.083,&#xA;   starting_magnetization(3) =  0.005,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Mn   54.93804  mn_pbe_v1.5.uspp.F.UPF &#xA;   Co   58.93319  Co_pbe_v1.2.uspp.F.UPF &#xA;   Ga   69.72300  Ga.pbe-dn-kjpaw_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Co      0.500000000    0.500000000    0.500000000    &#xA;   Mn      0.250000000    0.250000000    0.250000000    &#xA;   Ga      0.750000000    0.750000000    0.750000000    &#xA;   Mn      0.000000000    0.000000000    0.000000000     &#xA;K_POINTS automatic &#xA; 12 12 12 0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1361" LastEditDate="2021-04-13T04:01:30.793" LastActivityDate="2021-04-13T06:15:05.883" Title="Pressure applied DFT calculations in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|lattice-dynamics|cell-optimization|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4702" PostTypeId="1" CreationDate="2021-04-12T20:33:44.757" Score="22" ViewCount="3134" Body="&lt;p&gt;Does anyone know of a company with a cloud-based service which takes some representation of a molecule as an input, and then somehow solves the Schrödinger equation to some level of accuracy and reasonable time frame, then spits out the energy levels of orbitals as outputs?&lt;/p&gt;&#xA;&lt;p&gt;My guess is that no company does this today, but I might be wrong.&lt;/p&gt;&#xA;" OwnerUserId="3392" LastEditorUserId="5" LastEditDate="2021-04-13T14:05:38.110" LastActivityDate="2022-05-03T21:35:02.727" Title="Solving the Schrödinger equation as a service?" Tags="|density-functional-theory|ab-initio-calculations|one-topic-per-answer|high-performance-computing|from-chem-se|" AnswerCount="4" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="4703" PostTypeId="2" ParentId="4699" CreationDate="2021-04-12T21:40:38.100" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;So what happens when the contribution of excited determinants are included in the vibrational and rotational terms?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Nothing, except that the Hessian and/or gradient are more difficult to evaluate, for example see coupled-perturbed Hartree-Fock.&lt;/p&gt;&#xA;&lt;p&gt;I think maybe your confusion is arising because the excited determinants are not exactly excited-states. A multi-electron wave function can be solved exactly within the basis of determinants:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\Psi(r_1,r_2, ...,r_N)= \sum_i c_i \psi_i $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt; are the Slater determinants of the ground, and &amp;quot;excited&amp;quot; electronic configuration.&lt;/p&gt;&#xA;&lt;p&gt;These excited electronic configurations should not be confused for excited-states however, because the real excited electronic state is also composed of the same type of sum.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-04-12T21:53:58.670" LastActivityDate="2021-04-12T21:53:58.670" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4704" PostTypeId="1" CreationDate="2021-04-13T00:10:31.237" Score="10" ViewCount="263" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zyMsS.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zyMsS.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;How can i displace my structure along a particular normal mode, without coupling to other modes ? Rather than a exact mathematical procedure, I am more interested in a software/script/package that can help me accomplish it.&lt;/p&gt;&#xA;&lt;p&gt;For the kind of computations I am doing just displacing along modes in cartesians isn't accurate because modes involving bending and angles lead to bond stretching. For example,the descriptin of  rotational mode of methyl group in cartesian cant be used for displacements as it leads to stretching of CH bonds&lt;/p&gt;&#xA;&lt;p&gt;I have a pseudo-process in my mind. A frequency computation in Gaussian gives me the normal modes in both cartesian displacements and redundant internals. My aim is to displacement along modes in redundant internals and then back-transform to cartesian coordinates. I beleive this should be possible as Gaussain must store the transforming matrixes somewhere( &lt;em&gt;after all, it does this during optimizations&lt;/em&gt;), but I have not been able to accomplish this even after rummagging through all iops.&lt;/p&gt;&#xA;&lt;p&gt;More importantly, I think this kind of task is quite standard (&lt;em&gt;for decades !&lt;/em&gt;) and there surely must be an efficient way to do this.&lt;/p&gt;&#xA;&lt;p&gt;So, If anyone here can advise me or point me towards the right direction.&lt;/p&gt;&#xA;" OwnerUserId="3393" LastEditorUserId="3393" LastEditDate="2021-04-13T09:34:32.220" LastActivityDate="2021-04-14T11:39:54.173" Title="How to generate accurate displacements along normal modes?" Tags="|computational-chemistry|gaussian|vibrations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4705" PostTypeId="2" ParentId="4701" CreationDate="2021-04-13T01:25:08.373" Score="5" Body="&lt;p&gt;In your case, the crystallographic axes look to be equivalent, so just use 'relax' to start with. This will fix the lattice constants (equivalent to applying pressure) but will move the atoms around - make sure you modify the lattice parameter to reflect the 5%  strain, 10% strain etc. Then, perform your SCF calculation.&lt;/p&gt;&#xA;&lt;p&gt;If your crystallographic axes are inequivalent, you need to make use of &lt;code&gt;cell_dofree&lt;/code&gt;. You need to decide along which axis you want to apply pressure. If say, you apply along 'x', then you will need to relax the cell along the other two directions. Hence, you will be required to set &lt;code&gt;cell_dofree='yz'&lt;/code&gt;. In this case, you would use the &lt;code&gt;vc-relax&lt;/code&gt; tag.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-04-13T01:25:08.373" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4706" PostTypeId="2" ParentId="4702" CreationDate="2021-04-13T01:44:24.977" Score="16" Body="&lt;h1&gt;SciCalQ&lt;/h1&gt;&#xA;&lt;p&gt;The company does more than solving the Schroedinger equation. From its &lt;a href=&quot;https://www.scicalq.com/computational-chemistry-service/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;SciCalQ’s solid background in computational chemistry and quantum physics own extensive experiences in solving practical and academic problems with scientific computing.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They do:&lt;/p&gt;&#xA;&lt;h3&gt;Density Functional Theory (DFT) Computation&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Geometric Configuration: Bond length, bond angle, lattice parameters, stable configuration, surface reconstruction, defects, vacancies, active sites, etc.&lt;/li&gt;&#xA;&lt;li&gt;Electronic Properties: HOMO/LUMO , energy band structure, conduction band, valence band position, DOS, electron cloud density, carrier mobility, Fermi level, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Molecular dynamics (MD)&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Force Field for MD: Force field describes the interactions in/between moleculars in molecular dynamics simulations. We can obtain accurate force field for users.&lt;/li&gt;&#xA;&lt;li&gt;Binding Free Energy: Predicting the binding free energy of ligands to macromolecules can have great practical values in drugs discovery. We rovide one-stop service to finish this prediction.&lt;/li&gt;&#xA;&lt;li&gt;Bio-related Simulation: Polysaccharide molecular docking, molecular surface calculation, biological enzyme catalysis calculation, protein interaction analysis, transmembrane transport mechanism calculation, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For ordering, you need to fill a web form where you:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Discuss one by one according to the system and properties you need to calculate.&lt;/li&gt;&#xA;&lt;li&gt;Describe the system and intermediate process you need to calculate in detail (may be conjecture), and provide relevant literature.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-04-13T14:04:07.563" LastActivityDate="2021-04-13T14:04:07.563" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4707" PostTypeId="2" ParentId="4702" CreationDate="2021-04-13T02:35:12.390" Score="13" Body="&lt;h1&gt;Protheragen&lt;/h1&gt;&#xA;&lt;p&gt;Protheragen offers a &lt;a href=&quot;https://aimed.protheragen.com/quantum-chemistry-service.html&quot; rel=&quot;noreferrer&quot;&gt;Quantum Chemistry Service&lt;/a&gt; which includes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ECD calculation service (absolute configuration determination)&lt;/li&gt;&#xA;&lt;li&gt;Quantitative calculations (quantum chemical calculations)&lt;/li&gt;&#xA;&lt;li&gt;QM, QM/MM, QM/MD&lt;/li&gt;&#xA;&lt;li&gt;Catalytic reaction mechanism calculation&lt;/li&gt;&#xA;&lt;li&gt;Transition state search and energy calculation&lt;/li&gt;&#xA;&lt;li&gt;Chemical reaction pathway and potential energy surface calculation&lt;/li&gt;&#xA;&lt;li&gt;Spectrum calculation, resonance frequency calculation&lt;/li&gt;&#xA;&lt;li&gt;Calculation of thermodynamic properties&lt;/li&gt;&#xA;&lt;li&gt;Enzyme catalytic mechanism simulation&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The price is not made readily available, but they have a contact form on the website that I linked at the beginning of this answer, where you can discuss your project and pricing with them.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-13T02:35:12.390" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4708" PostTypeId="2" ParentId="4701" CreationDate="2021-04-13T06:15:05.883" Score="11" Body="&lt;p&gt;I would not recommend applying external hydrostatic pressure by changing the lattice parameter by hand. This is because fixing the lattice parameters by hand may lead to the incorrect structure. For example, the system may have a pressure-induced structural phase transition that may change it from cubic to tetragonal, and by fixing the lattice parameters by hand you would miss this.&lt;/p&gt;&#xA;&lt;p&gt;Most DFT codes have the functionality to minimize the enthalpy &lt;span class=&quot;math-container&quot;&gt;$H=U+PV$&lt;/span&gt; of the system (rather than the usual internal energy), so that you can directly relax the structure under an externally applied hydrostatic pressure. This is in fact a minor addition that does not really affect computational cost because all you need to do is to add the &lt;span class=&quot;math-container&quot;&gt;$PV$&lt;/span&gt; term, which is trivial to evaluate. With this approach, you have a better change of identifying any structural phase transitions.&lt;/p&gt;&#xA;&lt;p&gt;While I have done this multiple times with other codes, I have not done it with Quantum Espresso. However, a quick search through their documentation suggests that the keyword &lt;code&gt;press&lt;/code&gt; is what you are looking for. You can find the details in this &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I would also like to add that the discussion above about structural phase transitions associated with changes in lattice parameters also applies to internal coordinates. You mention that by changing the lattice parameter the structure &amp;quot;gets corrupted&amp;quot; because there is an internal distortion of the atoms. I would encourage you to reconsider this approach: it may well be that the structure undergoes a structural phase transition under hydrostatic pressure. Therefore, I would not consider a distortion an &amp;quot;error&amp;quot;, what you should do is to compare the enthalpy of the distorted structure with that of the undistorted one under the same pressure conditions, and then the lowest enthalpy one is the most favorable one.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-04-13T06:15:05.883" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4709" PostTypeId="2" ParentId="4635" CreationDate="2021-04-13T23:23:28.163" Score="9" Body="&lt;p&gt;Molecular Quantum Chemistry via &lt;strong&gt;WebMO&lt;/strong&gt; on &lt;strong&gt;Google Cloud&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It's fairly easy to run Linux-based programs on Google Cloud. The WebMO interface gives a &lt;a href=&quot;https://www.webmo.net/support/sitcGCP.html&quot; rel=&quot;noreferrer&quot;&gt;tutorial&lt;/a&gt; on installing on GCP including molecular quantum chemistry programs.&lt;/p&gt;&#xA;&lt;p&gt;Supported tools include open source and &amp;quot;free binary&amp;quot; programs, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Psi4&lt;/li&gt;&#xA;&lt;li&gt;Orca&lt;/li&gt;&#xA;&lt;li&gt;GAMESS&lt;/li&gt;&#xA;&lt;li&gt;NWChem&lt;/li&gt;&#xA;&lt;li&gt;Mopac&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As mentioned in another answer, costs are higher than a dedicated workstation or cluster, but if you're performing occasional calculations, it might be worthwhile.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-04-13T23:23:28.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4710" PostTypeId="1" CreationDate="2021-04-14T03:04:40.257" Score="8" ViewCount="234" Body="&lt;p&gt;(Note: an earlier version of this question had been asked on &lt;a href=&quot;https://physics.stackexchange.com/questions/621460/can-classical-spin-glass-problems-be-solved-exactly-in-a-more-efficient-way-than&quot;&gt;Phys.SE&lt;/a&gt; before)&lt;/p&gt;&#xA;&lt;p&gt;It is known that finding the ground state of classical spin glasses is NP-hard: it will take (at least) an exponential amount of effort with respect to system size &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;. But not all kinds of exponentially hard  are the same, of course.&lt;/p&gt;&#xA;&lt;p&gt;Now, take the XY-model for example, which has both a quantum and a classical version. For the quantum version, the Hilbert size is &lt;span class=&quot;math-container&quot;&gt;$2^N$&lt;/span&gt; (each site is described by 2x2 Pauli matrices) and because quantum mechanics is linear, the Hamiltonian can be exactly diagonalized to get the (in general, entangled) ground state.&lt;/p&gt;&#xA;&lt;p&gt;For the classical XY this construction cannot be made: there is one continuous variable &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;. With discretisation, it has &lt;span class=&quot;math-container&quot;&gt;$M_\theta$&lt;/span&gt; values to be considered at every size, yielding a complexity of &lt;span class=&quot;math-container&quot;&gt;$M_\theta^N$&lt;/span&gt; when one wants to try out all the possibilities?&lt;/p&gt;&#xA;&lt;p&gt;Does this mean that the classical XY model is more complex than the quantum one?&lt;/p&gt;&#xA;&lt;p&gt;Of course, there are monte carlo techniques but they are probabilistic and rely on careful tuning of the temperature; which is much more clumsy than the exact diagonalization of the quantum case.&lt;/p&gt;&#xA;" OwnerUserId="1409" LastActivityDate="2021-04-14T10:10:22.443" Title="What's the most efficient way to obtain the ground state of spin models exactly?" Tags="|model-hamiltonians|ising-model|spin-models|heisenberg-model|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4711" PostTypeId="1" CreationDate="2021-04-14T05:13:12.787" Score="15" ViewCount="3268" Body="&lt;p&gt;For quantum many body problem, there is a common terminology “strong correlated systems” that appears in different context. However, it seems that the definition of it is ambiguous and sometimes inconsistent in different field of study. My question is that is there an unequivocal, universal definition of “strong correlated systems”?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2021-04-14T15:25:28.917" LastActivityDate="2021-04-15T07:16:33.467" Title="What does “strongly correlated” mean?" Tags="|quantum-chemistry|condensed-matter|quantum-mechanics|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4712" PostTypeId="2" ParentId="4693" CreationDate="2021-04-14T05:35:20.870" Score="2" Body="&lt;p&gt;The issue might be numerical as well. At theory level, CCSD could be rigorously prove to be size extensive. However, in practice, when one solves CC residue equation numerically, there is some convergence threshold that affect the accuracy of the result. Math is always simple and graceful but numerics can be complicated and nesty&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2021-04-14T05:35:20.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4714" PostTypeId="2" ParentId="4711" CreationDate="2021-04-14T09:02:59.257" Score="11" Body="&lt;p&gt;Here I assume that we are focus on the condensed matter system which is composed of nuclei and electrons with the fundamental force: &lt;code&gt;Coulomb Force&lt;/code&gt;. Furthermore, I just discuss the electron degree of freedom.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A naive (wrong) answer: The interaction gets stronger when electron density is higher.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The Coulomb interaction is proportional to &lt;span class=&quot;math-container&quot;&gt;$\dfrac{1}{r}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the separation between two electrons. Higher density means that the average&#xA;the separation between electrons is smaller, so higher density means stronger interaction.&lt;/p&gt;&#xA;&lt;p&gt;Take the electron gas as an example, the average distance &lt;span class=&quot;math-container&quot;&gt;$r_s$&lt;/span&gt; between electrons can be estimated as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\dfrac{N}{V} \equiv \dfrac{4}{3}\pi r_s^3 \tag{1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\dfrac{V}{N}$&lt;/span&gt; is the average volume occupied by one electron, and the density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$n=\dfrac{N}{V} \tag{2}$$&lt;/span&gt;&#xA;Thus:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$r_s=(\dfrac{3}{4\pi n})^{1/3} \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, the average Coulomb interaction one electron feels can be estimated as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\dfrac{E_{int}}{N} \propto \dfrac{e^2}{r_s} \propto n^{1/3} \tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore, the smaller &lt;span class=&quot;math-container&quot;&gt;$r_s$&lt;/span&gt; (or high density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) means stronger interaction or strong correlation.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;However, the truth is the opposite. Because the electronic Hamiltonian is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H_{ele}=H_{k}+H_{int} \tag{5}$$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;We need to compare interaction (&lt;span class=&quot;math-container&quot;&gt;$H_{int}$&lt;/span&gt;) with the kinetic energy (&lt;span class=&quot;math-container&quot;&gt;$H_k$&lt;/span&gt;) to determine whether we have a strongly correlated system or a weakly correlated&#xA;system. The strong correlation means &lt;span class=&quot;math-container&quot;&gt;$H_{int} \gg H_k $&lt;/span&gt; (electrons are correlated with each other) and the weak correlation mean &lt;span class=&quot;math-container&quot;&gt;$H_k \gg H_{int}$&lt;/span&gt; (electrons are almost free in space).&lt;/p&gt;&#xA;&lt;p&gt;We can also make a qualitative estimation for the total kinetic energy. The total kinetic energy &lt;span class=&quot;math-container&quot;&gt;$E_k$&lt;/span&gt; in a Fermi gas is also a function of &lt;span class=&quot;math-container&quot;&gt;$r_s$&lt;/span&gt; or density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{k}=2V\int_{\epsilon \ll \epsilon_F} \dfrac{d^3k}{(2\pi)^3} \dfrac{k^2}{2m}=2V \int_0^{k_F} \dfrac{k^4 dk}{4 \pi^2 m}=\dfrac{Vk_F^5}{10 \pi^2 m} \tag{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The total particle number &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$N=2V\int_{\epsilon \ll \epsilon_F} \dfrac{d^3k}{(2\pi)^3} = 2V \int_0^{k_F} \dfrac{k^2dk}{2 \pi^2 m} = \dfrac{Vk_F^3}{3 \pi^2} \tag{7}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus the total kinetic energy per electron is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \dfrac{E_k}{N} = \dfrac{\dfrac{Vk_F^5}{10 \pi^2 m}}{\dfrac{Vk_F^3}{3 \pi^2}} = \dfrac{3k_F^2}{10m} \propto \dfrac{1}{mr_s^2} \tag{8}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that from Eq.&lt;span class=&quot;math-container&quot;&gt;$(7)$&lt;/span&gt; we can derive that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$k_F=(3\pi^2 \dfrac{N}{V})^{1/3}=(3\pi^2 n)^{1/3} \tag{9}$$&lt;/span&gt;&#xA;which allows us to build a connection between &lt;span class=&quot;math-container&quot;&gt;$k_F$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_s$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, the ratio between kinetic energy and interaction energy is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \dfrac{E_{int}}{E_k} ~\propto \dfrac{e^2/r_s}{1/mr_s^2} = \dfrac{r_s}{a_0} \tag{10}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$a_0=\dfrac{1}{me^2}=0.529 \text{Angstrom}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When &lt;span class=&quot;math-container&quot;&gt;$r_s \gg a_0$&lt;/span&gt; (low density), we have a strongly correlated system with the energy of interactions greater than kinetic energy.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When &lt;span class=&quot;math-container&quot;&gt;$r_s \ll a_0$&lt;/span&gt; (high density), we have a weakly correlated system with kinetic energy greater than interaction.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In summary, we need to compare interaction (&lt;span class=&quot;math-container&quot;&gt;$H_{int}$&lt;/span&gt;) with the kinetic energy (&lt;span class=&quot;math-container&quot;&gt;$H_k$&lt;/span&gt;) to determine whether we have a strongly correlated system or a weakly correlated system.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ref1: &lt;a href=&quot;https://www.youtube.com/watch?v=7SepOSfG-To&amp;amp;t=3915s&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=7SepOSfG-To&amp;amp;t=3915s&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Ref2: &lt;a href=&quot;http://www-personal.umich.edu/%7Esunkai/teaching/Fall_2013/chapter2.pdf&quot; rel=&quot;noreferrer&quot;&gt;http://www-personal.umich.edu/~sunkai/teaching/Fall_2013/chapter2.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;==========================================================================&lt;/p&gt;&#xA;&lt;h2&gt;A mathematical definition from the viewpoint of statistical mechanics:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The correlation function &lt;span class=&quot;math-container&quot;&gt;$\langle A B \rangle$&lt;/span&gt; (here &lt;span class=&quot;math-container&quot;&gt;$\langle \cdots \rangle$&lt;/span&gt; means statistical average) can be approximated as &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle \langle B \rangle$&lt;/span&gt;, then you obtain a weak correlation system;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The correlation function &lt;span class=&quot;math-container&quot;&gt;$\langle A B \rangle$&lt;/span&gt; can not be approximated as &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle \langle B \rangle$&lt;/span&gt;, then you obtain a strong correlation system;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-04-15T07:16:33.467" LastActivityDate="2021-04-15T07:16:33.467" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4715" PostTypeId="2" ParentId="4710" CreationDate="2021-04-14T10:10:22.443" Score="3" Body="&lt;h2&gt;No, the quantum version is not simpler&lt;/h2&gt;&#xA;&lt;p&gt;There are many ways to find the ground state of an arbitrary quantum system. Quantum Monte Carlo (QMC), Density Matrix Renormalization Group (DMRG), et. al., but if you want an &lt;strong&gt;exact&lt;/strong&gt; solution, you need either some very clever analytical approach (only available for special cases), or you need to do exact diagonalization.&lt;/p&gt;&#xA;&lt;p&gt;I'll write my answer in terms of the quantum &lt;span class=&quot;math-container&quot;&gt;$S=\frac{1}{2}$&lt;/span&gt; Heisenberg model because I have more experience with that. Each site is a two-state quantum system, so the total Hilbert space is of size &lt;span class=&quot;math-container&quot;&gt;$2^N$&lt;/span&gt;. However, this is a &lt;em&gt;quantum&lt;/em&gt; system, not an Ising model, so the ground state is a complex &lt;em&gt;vector&lt;/em&gt; of size &lt;span class=&quot;math-container&quot;&gt;$2^N$&lt;/span&gt;. (There are some simplifications that probably reduce this number for the XY model, but it will still be exponential in &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;If you need the full solution then you have to diagonalize the &lt;span class=&quot;math-container&quot;&gt;$2^N \times 2^N$&lt;/span&gt; Hamiltonian. That has computational cost proportional to &lt;span class=&quot;math-container&quot;&gt;$(2^N)^3$&lt;/span&gt;. In addition to being very computationally intensive to evaluate, even for very modest systems (such as a spin chain of length 20), even constructing these matrices becomes incredicbly computationally expensive, and it can be a challenge to even store them in memory. (A double-precision complex number takes up 8 bytes of memory, so the Hamiltonian for a L=16 chain would require 34 GB of memory).&lt;/p&gt;&#xA;&lt;h2&gt;Save time with symmetries&lt;/h2&gt;&#xA;&lt;p&gt;Most Hamiltonians have some obvious symmetries that can exploited to reduce the size of the matrix that must be diagonalized, such as total magnetization, translational symmetry, spin-inversion symmetry, reflection symmetry, etc. Implementing these can allow larger systems to be studied. These procedures are described in detail in Sandvik &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1101.3281&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Save time with Lanczos diagonalization&lt;/h2&gt;&#xA;&lt;p&gt;Lanczos diagonalization is an iterative technique to get the ground state and first few excited states from a Hamiltonian that is much faster and less memory intensive than full diagonalization. In practice, the ground state energy and eigenstate can usually be calculated to numerical precision (effectively exact), but it can't easily tell degenerate ground states apart. See Sandvik &lt;a href=&quot;https://arxiv.org/abs/1101.3281&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1101.3281&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-04-14T10:10:22.443" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4716" PostTypeId="2" ParentId="4704" CreationDate="2021-04-14T11:39:54.173" Score="5" Body="&lt;p&gt;Well, I found a dirty way to do with Gaussian itself. I make the computtaion print the normal modes in redundant internals with &lt;strong&gt;IntModes&lt;/strong&gt; option.&lt;/p&gt;&#xA;&lt;p&gt;To displace the structure along the normal modes in redundant internals, I use the GIC section and manually specify the values of the redundant internals. Then I submit a pseudo-computaion(hf/sto-3G) to gaussian.&lt;/p&gt;&#xA;&lt;p&gt;Before doing the computtaion gaussian prints the displaced structure in Cartesians.&lt;/p&gt;&#xA;&lt;p&gt;I still feel this is quite ugly, and there must be a proper way to accomplish this.&lt;/p&gt;&#xA;" OwnerUserId="3393" LastActivityDate="2021-04-14T11:39:54.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4717" PostTypeId="2" ParentId="4711" CreationDate="2021-04-14T18:58:41.617" Score="9" Body="&lt;p&gt;Here is my summary of definition of strong correlated systems in different context.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For ab initio electronic structure Hamiltonian&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The eigen value of the system can not be well approximated by single slater determinate approach (Hartree Fock or DFT). These system normally has large coefficient in there configurational interaction (CI) expansion. For some cases, if the system has close lying eigen states, a multi-reference scheme need to be applied.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For non-adiabatic nuclear dynamics&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In these systems, Born-Oppenheimer approximation is invalid and the coupling between electronic structure and vibrational mode is known as non-adiabatic coupling. These coupling serves as off-diagonal matrix element in their model Hamiltonian represented in H.O. basis. When the dynamics behavior of these system deviate largely from the Born-Oppenheimer approximation, we treat it as strongly correlated systems.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For spin Hamiltonian&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;When the eigen state of the system can not be well approximated using mean field approach and interaction between neighbours spin need to be considered and the exchange integrals of these coupling terms are normally very large.&lt;/p&gt;&#xA;&lt;p&gt;These are some examples for strongly correlated systems in different context. I think there are some common features here.&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2021-04-14T18:58:41.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4718" PostTypeId="2" ParentId="4711" CreationDate="2021-04-14T23:58:36.090" Score="9" Body="&lt;p&gt;You got it completely correct when you said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;it seems that the definition of it is ambiguous and sometimes inconsistent in different field of study.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As the other answers show, it's a bit of a &amp;quot;loose&amp;quot; term that can be used in slightly different ways depending on the sub-field of Matter Modeling in which the term is being used.&lt;/p&gt;&#xA;&lt;p&gt;This might not be too surprising, because the word &amp;quot;strong&amp;quot; is a relative term too: to be &amp;quot;strong&amp;quot; or &amp;quot;weak&amp;quot; depends on who you're comparing yourself to. It's not like  &amp;quot;longitudinal waves&amp;quot; and &amp;quot;transverse waves&amp;quot; where a wave is either one or the other, the &amp;quot;strongest&amp;quot; human can still be weaker than one of the &amp;quot;weakest&amp;quot; train engines.&lt;/p&gt;&#xA;&lt;p&gt;This reminds me of a previous question that was asked here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4400/5&quot;&gt;What is static correlation, actually?&lt;/a&gt; We like to use the words &amp;quot;static correlation&amp;quot; and &amp;quot;dynamic correlation&amp;quot; to assist us in describing different &amp;quot;types&amp;quot; of correlation that come up in our calculations, and this sometimes creates confusion for people that are trying to calculate the same thing using completely different methods (e.g. direct solving of the Schroedinger equation rather than first doing an SCF calculation then a post-SCF calculation to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1685/5&quot;&gt;add dynamic correlation&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;To answer the question of what &amp;quot;strong correlation&amp;quot; means, we can start first with the definition of &amp;quot;correlation&amp;quot;, which is a term that was originally used in statistics, before it was brought to quantum mechanics (though the statistics of measurements on an entangled system will be correlated in exactly the way statisticians use the term). For &lt;a href=&quot;/questions/tagged/electron-correlation&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;electron-correlation&amp;#39;&quot; rel=&quot;tag&quot;&gt;electron-correlation&lt;/a&gt;, you can try to categorize the correlations between electrons as being &amp;quot;weak&amp;quot; or &amp;quot;strong&amp;quot;, but there will be systems with weaker or stronger electron correlation.&lt;/p&gt;&#xA;&lt;p&gt;In the world of doing &lt;em&gt;ab initio&lt;/em&gt; calculations by using &amp;quot;SCF + post-SCF&amp;quot; methods, systems with &amp;quot;strong correlation&amp;quot; tend to need many determinants in the SCF part of the calculation (i.e. a big active space in a CASSCF+PT2 calculation), but this is not the only way the term is being used. It's sometimes better to avoid terms that are &amp;quot;ambiguous&amp;quot; as you called it in your question, and instead be precise about what specifically you're conveying: for example, &lt;strong&gt;instead of saying &amp;quot;the system is strongly correlated&amp;quot;, a more precise statement would be &amp;quot;the 1000 most dominant determinants all have the same weight in the FCI expansion&amp;quot;&lt;/strong&gt;.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-14T23:58:36.090" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4719" PostTypeId="2" ParentId="4693" CreationDate="2021-04-15T00:30:14.093" Score="4" Body="&lt;p&gt;Your CISD and CCSD energies are practically the same, since you have not defined a basis set. It appears Gaussian still defaults to STO-3G in this case, although it is a minimal basis set, which usually do not yield even qualitatively correct results even at the SCF level of theory.&lt;/p&gt;&#xA;&lt;p&gt;To be reliable, a post-HF calculation should employ basis sets of at least triple- to quadruple-zeta quality, preferably with extrapolation to the complete basis set limit.&lt;/p&gt;&#xA;&lt;p&gt;Repeating the calculations in a non-minimal basis set gives me a CISD/cc-pVDZ energy of -152.44051461, and a CCSD/cc-pVDZ energy of -152.47534355; so you already see clearly that the CCSD energy is lower than the CISD one. Going to larger basis sets will result in a better capture of correlation energy (although the Hartree-Fock energy will also go down), and the difference between CCSD and CISD may still increase.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-04-15T00:30:14.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4720" PostTypeId="2" ParentId="4699" CreationDate="2021-04-15T06:27:34.493" Score="0" Body="&lt;p&gt;In some cases, we need to consider vibrational - rotational coupling. But this effect is normally weak since the rotational energy level (~1e-4 eV)is much smaller comparing with vibrational energy level (~1e-1 eV). Rotational energy level is normally serves as fine structures in a high resolution photo-electron spectra and this effect is normally so weak that can be ignored for the photo-electron spectra of a poly-atomic system.&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2021-04-15T06:27:34.493" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4721" PostTypeId="1" AcceptedAnswerId="4722" CreationDate="2021-04-15T12:12:32.330" Score="9" ViewCount="393" Body="&lt;p&gt;Let's say I want to calculate the energy spectrum of Heisenberg model:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ H = J \sum \limits_{\langle i,j \rangle} \vec S_i \cdot \vec S_j -g ~\mu_B \sum \limits_{i} \vec S_i \cdot \vec B$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but value of &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is given as &lt;span class=&quot;math-container&quot;&gt;$J/k_B= 20 ~K $&lt;/span&gt; (kelvin). now If I put &lt;span class=&quot;math-container&quot;&gt;$J= 20 * 1.38* 10^{−23} $&lt;/span&gt; joule in &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and find the energy eigenvalues numerically by diagonalizing , then I may not get correct results because of such a low &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Can I do it in following way:&lt;/p&gt;&#xA;&lt;p&gt;By Converting H in kelvin unit: Keeping J as 20 K and &lt;span class=&quot;math-container&quot;&gt;$ \mu_B = 0.671 ~ K ~T^{-1}$&lt;/span&gt; and B in &lt;span class=&quot;math-container&quot;&gt;$T $&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; =Tesla). then Calculated Energy will be in &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; unit, next I can convert it back to joule or eV.&lt;/p&gt;&#xA;&lt;p&gt;Am I correct or any better way ?&lt;/p&gt;&#xA;" OwnerUserId="1715" LastEditorUserId="5" LastEditDate="2022-12-21T14:44:33.390" LastActivityDate="2022-12-21T14:44:33.390" Title="Proper handling of change of units in numerical calculations" Tags="|model-hamiltonians|" AnswerCount="1" CommentCount="0" ClosedDate="2023-07-12T07:23:10.450" ContentLicense="CC BY-SA 4.0" />
  <row Id="4722" PostTypeId="2" ParentId="4721" CreationDate="2021-04-15T13:48:28.987" Score="9" Body="&lt;p&gt;You're correct, but there's also an easier way. I tend to rephrase such problems in terms of an overall energy scale and a ratio, e.g.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H=J\left[ \sum \limits_{\langle i,j \rangle} \vec S_i \cdot \vec S_j -\frac{g ~\mu_B}{J} \sum \limits_{i} \vec S_i \cdot \vec B \right] = J\left[ \sum \limits_{\langle i,j \rangle} \vec S_i \cdot \vec S_j -\alpha \sum \limits_{i} \vec S_i \cdot \vec B \right]&#xA;$$&lt;/span&gt;&#xA;Then I usually set &lt;span class=&quot;math-container&quot;&gt;$J=1$&lt;/span&gt; in the numerical calculations (that is, solve the dimensionless Hamiltonian inside the square brackets), and only worry about converting back afterwards. And converting to whatever units of &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; you prefer is easy, since it's just a multiplicative factor.&lt;/p&gt;&#xA;&lt;p&gt;This approach also has the benefit of making it easy to directly compare one's results with already published literature. Many papers on model Hamiltonians are about the Hamiltonian itself, not some experimental system, and so they present data either in units where &lt;span class=&quot;math-container&quot;&gt;$J=1$&lt;/span&gt; or in units of &lt;span class=&quot;math-container&quot;&gt;$\epsilon/J$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2021-04-15T14:11:48.917" LastActivityDate="2021-04-15T14:11:48.917" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4723" PostTypeId="2" ParentId="4635" CreationDate="2021-04-15T20:14:51.093" Score="8" Body="&lt;h1&gt;Hetzner&lt;/h1&gt;&#xA;&lt;p&gt;If you know you will continuously need a powerful computer for the next 1-2 years, consider &lt;a href=&quot;https://www.hetzner.com/dedicated-rootserver/matrix-ax&quot; rel=&quot;noreferrer&quot;&gt;renting a bare-metal server from Hetzner&lt;/a&gt;.&#xA;You can rent a 32 core 2nd generation AMD EPYC server with 256 GB of RAM and a fast SSD for about 200 EUR/month. No traffic fees.&lt;/p&gt;&#xA;&lt;p&gt;You get remote access to a blank machine, and you are free to install whatever OS and software you need, no virtualization overhead or other restrictions.&lt;/p&gt;&#xA;&lt;p&gt;There are other configurations to choose from, but the AMD boxes are usually the better value.&lt;/p&gt;&#xA;&lt;p&gt;PS: The 32 core box I mentioned is seriously powerful when it comes to CPU compute. You can expect Linpack perfomance in excess of 1 TFLOPS, as the 24 core model of the same family can do 1 TFLOPS +/- 10%.&lt;/p&gt;&#xA;&lt;p&gt;One thing you need to watch out for is the number of memory modules! If you rent a server with less than half of the maximum memory capacity, some of the memory channels will be left unpopulated, which may have a negative impact on performance.&lt;/p&gt;&#xA;&lt;p&gt;So for the EPYC server I would recommend exactly 256 GB of RAM, or if (for your applications) that is not enough to go with 32 cores, then 512 GB would be the next good option.&lt;/p&gt;&#xA;" OwnerUserId="3410" LastEditorUserId="3410" LastEditDate="2021-04-15T21:39:33.160" LastActivityDate="2021-04-15T21:39:33.160" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4724" PostTypeId="1" AcceptedAnswerId="4727" CreationDate="2021-04-15T20:43:28.960" Score="12" ViewCount="852" Body="&lt;p&gt;In the LS coupling scheme, L, S and J are good quantum numbers; whereas in jj-coupling scheme, j&lt;sub&gt;1&lt;/sub&gt;, j&lt;sub&gt;2&lt;/sub&gt; and J are good quantum numbers. I have learnt how to get the term symbols for LS coupling, and for jj-coupling for a particular electronic configuration. However, what I can't figure out is how the term symbols from each of these schemes are related to each other. None of the textbooks I have cover this topic in any way.&lt;/p&gt;&#xA;&lt;p&gt;For example, in case of a &lt;span class=&quot;math-container&quot;&gt;$\mathrm{p^2}$&lt;/span&gt; configuration, the LS terms are &lt;span class=&quot;math-container&quot;&gt;$\mathrm{^1S_0, ^1D_2, ^3P_2,  ^3P_1, ^3P_0}$&lt;/span&gt;, and the corresponding jj-terms are &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_0, (3/2,3/2)_2, (3/2,1/2)_2, (3/2,1/2)_1, (1/2,1/2)_0~$&lt;/span&gt; respectively. The LS terms are more useful when the atomic number is low e.g. C, whereas the jj terms are more useful when the atomic number is high e.g. Pb.&lt;/p&gt;&#xA;&lt;p&gt;How do I know which LS terms are related to which jj-terms? (Obviously, we can look at the J and identify some terms but that does not work for every term)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aZNx4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aZNx4.png&quot; alt=&quot;LS to jj-coupling low Z to high Z&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, from the diagram we can tell that &lt;span class=&quot;math-container&quot;&gt;$\mathrm{^1S_0}$&lt;/span&gt; is the LS-term that corresponds to &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_0$&lt;/span&gt; in jj-term.&lt;/p&gt;&#xA;&lt;p&gt;[P.S. I would also be happy if you could recommend a book where I can read around this topic]&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-16T09:41:06.273" LastActivityDate="2021-04-16T18:19:27.187" Title="How to determine which levels correspond to each other in LS coupling and jj-coupling?" Tags="|quantum-mechanics|spectroscopy|spin-orbit-coupling|from-chem-se|atomic-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4725" PostTypeId="5" CreationDate="2021-04-15T20:51:20.450" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-15T20:51:20.450" LastActivityDate="2021-04-15T20:51:20.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4726" PostTypeId="4" CreationDate="2021-04-15T20:51:20.450" Score="0" Body="Questions about atomic physics." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-15T20:51:20.450" LastActivityDate="2021-04-15T20:51:20.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4727" PostTypeId="2" ParentId="4724" CreationDate="2021-04-15T22:47:25.420" Score="12" Body="&lt;p&gt;In the jj-representation, each electron from &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; will have:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{l}_i$&lt;/span&gt; (orbital angular momentum),&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{s}_i$&lt;/span&gt; (spin angular momentum), and&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\vec{j}_i=\vec{l}_i + \vec{s}_i$&lt;/span&gt; (total angular momentum).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In your example we have &lt;span class=&quot;math-container&quot;&gt;$N=2$&lt;/span&gt; and both electrons are &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;-type so we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;{l}_1=1,~~~~~~~{l}_2=1.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's also assign the spins for each electron as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;{s}_1=1/2,~~~~~~~{s}_2=1/2.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We now have the following possibilities for &lt;span class=&quot;math-container&quot;&gt;${j}_i$&lt;/span&gt;:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;~&amp;amp;|l_i - s_i| \tag{3}\\&#xA;~&amp;amp;~~~~~~~ |l_i - s_i| +1 \tag{4}\\&#xA;~&amp;amp; ~\vdots \tag{5}\\&#xA;~&amp;amp; ~l_i + s_i. \tag{6}\\&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Plugging in &lt;span class=&quot;math-container&quot;&gt;$l_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$s_i$&lt;/span&gt; we get the following possibilities for &lt;span class=&quot;math-container&quot;&gt;$j_i$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{7}&#xA;j_i = 1/2 , ~~~~~~~j_i=3/2.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore we have 4 possibilities for the &lt;span class=&quot;math-container&quot;&gt;$(j_1,j_2)$&lt;/span&gt; pair:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{8}&#xA;(1/2,1/2),(1/2,3/2),(3/2,1/2),(3/2,3/2).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;These are all included in your example. Let's now look at the total &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; values, which come from adding up the total angular momenta &lt;span class=&quot;math-container&quot;&gt;$j_i$&lt;/span&gt; from each of the electrons. Since we have only 2 electrons, &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; can be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;~&amp;amp;|j_1 - j_2| \tag{9}\\&#xA;~&amp;amp;~~~~~~~ |j_1 - j_2| +1 \tag{10}\\&#xA;~&amp;amp; ~\vdots \tag{11}\\&#xA;~&amp;amp; ~j_1 + j_2. \tag{12}\\&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So the possible &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; values in our case are (even including  some which you can eliminate due to the Pauli exclusion principle):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;for &lt;span class=&quot;math-container&quot;&gt;$(1/2,1/2)$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$J=0$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;, which means we can have &lt;span class=&quot;math-container&quot;&gt;$(1/2,1/2)_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(1/2,1/2)_1$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;for &lt;span class=&quot;math-container&quot;&gt;$(1/2,3/2)$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$J=1$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;, which means we can have &lt;span class=&quot;math-container&quot;&gt;$(1/2,3/2)_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(1/2,3/2)_2$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;for &lt;span class=&quot;math-container&quot;&gt;$(3/2,1/2)$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$J=1$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;, which means we can have &lt;span class=&quot;math-container&quot;&gt;$(3/2,1/2)_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(3/2,1/2)_2$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;for &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$J=0,1,2,3$&lt;/span&gt;, so: &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_3$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For the LS-representation, we have the total orbital angular momentum:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{13}&#xA;\vec{L}=\vec{l}_1 + \vec{l}_2,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and total spin angular momentum:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{14}&#xA;\vec{S}=\vec{s}_1 + \vec{s}_2.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The possible values of &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;~&amp;amp;|l_1 - l_2| \tag{15}\\&#xA;~&amp;amp;~~~~~~~ |l_1 - l_2| +1 \tag{16}\\&#xA;~&amp;amp; ~\vdots \tag{17}\\&#xA;~&amp;amp; ~l_1 + l_2, \tag{18}\\&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and we have the same structure for &lt;span class=&quot;math-container&quot;&gt;$\vec{S}$&lt;/span&gt;.&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;To correspond term symbols from the LS-representation with term symbols from the jj-representation, you can assign each electron an &lt;span class=&quot;math-container&quot;&gt;$\vec{l}_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{s}_i$&lt;/span&gt; and work out the corresponding &lt;span class=&quot;math-container&quot;&gt;$\vec{j}_i,J,L$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; values.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, in &lt;span class=&quot;math-container&quot;&gt;$(3/2,3/2)_0$&lt;/span&gt; we have an overall total angular momentum of &lt;span class=&quot;math-container&quot;&gt;$J=0$&lt;/span&gt; despite each individual electron having a total angular momentum of &lt;span class=&quot;math-container&quot;&gt;$j_i=3/2$&lt;/span&gt;. The only way that can happen when each electron has &lt;span class=&quot;math-container&quot;&gt;$l_i=1$&lt;/span&gt; (since you wanted them to both be &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;) and the same principal quantum number, is if the spins are in opposite directions: i.e. the singlet state &lt;span class=&quot;math-container&quot;&gt;$^1 S_0$&lt;/span&gt; rather than the other &lt;span class=&quot;math-container&quot;&gt;$J=$&lt;/span&gt; option which was &lt;span class=&quot;math-container&quot;&gt;$^3P_0$&lt;/span&gt;. In the other &lt;span class=&quot;math-container&quot;&gt;$J=0$&lt;/span&gt; case, which is &lt;span class=&quot;math-container&quot;&gt;$(1/2,1/2)_0$&lt;/span&gt;, when &lt;span class=&quot;math-container&quot;&gt;$l_i=1$&lt;/span&gt; the only way to get &lt;span class=&quot;math-container&quot;&gt;$j_i=1/2$&lt;/span&gt; is for &lt;span class=&quot;math-container&quot;&gt;$\vec{s}_i=-1/2$&lt;/span&gt; meaning that both spins are the same, and hence the triplet &lt;span class=&quot;math-container&quot;&gt;$^3 P_0$&lt;/span&gt; rather than the &lt;span class=&quot;math-container&quot;&gt;$^1 S_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-16T18:19:27.187" LastActivityDate="2021-04-16T18:19:27.187" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4728" PostTypeId="1" AcceptedAnswerId="4729" CreationDate="2021-04-15T23:07:49.450" Score="4" ViewCount="196" Body="&lt;p&gt;I wonder how to use this panel to validate docking? I tried and the results are a disaster:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XQ5Cp.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XQ5Cp.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="5" LastEditDate="2021-04-16T01:23:34.067" LastActivityDate="2021-04-16T01:23:34.067" Title="How to compare structural results by superposition and compute RMSD to validate docking?" Tags="|docking|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4729" PostTypeId="2" ParentId="4728" CreationDate="2021-04-16T01:01:08.403" Score="4" Body="&lt;p&gt;Here are the steps to validate your docking protocol (not your docking results):&lt;br /&gt;&#xA;(Note: this is one way to do the validation, not the only one)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Download a crystal structure of a complex (ligand/substrate + protein) from Protein Data Bank server.&lt;br /&gt;&#xA;Note: It is recommended to use the same protein (not necessarily the same structure) you used in your docking.&lt;/li&gt;&#xA;&lt;li&gt;Do a re-docking using the ligand/protein you downloaded under the same conditions you did your docking.&lt;/li&gt;&#xA;&lt;li&gt;Use the ligand pose from the downloaded complex as your reference structure.&lt;/li&gt;&#xA;&lt;li&gt;Align the reference structure with all the poses you obtain in the re-docking (or at least, the best scored poses).&lt;/li&gt;&#xA;&lt;li&gt;Calculate the RMSD between the reference structure and the selected poses.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;From the Panel you show:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You can add all the re-docking poses to the Workspace or just select them in the project table. If added to the workspace, chose the &lt;strong&gt;Workspace&lt;/strong&gt; option (if selecting the project table, the other option).&lt;/li&gt;&#xA;&lt;li&gt;Select the reference structure from the crystal structure you downloaded.&lt;/li&gt;&#xA;&lt;li&gt;Under RMSD option, select &lt;strong&gt;Compute without changing structures&lt;/strong&gt;, to keep all the structures as they are (without changing their conformation). The other option will only add the RMSD to a column in the project table.&lt;/li&gt;&#xA;&lt;li&gt;Under the &lt;strong&gt;Choose method&lt;/strong&gt;, select the one corresponding to the whole structures (all atoms).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To conclude that the docking protocol is reliable, the desired max(RMSD) should be below &lt;span class=&quot;math-container&quot;&gt;$2.0 \overset{\circ}{\mathrm{A}}$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-04-16T01:12:39.223" LastActivityDate="2021-04-16T01:12:39.223" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4730" PostTypeId="1" AcceptedAnswerId="4731" CreationDate="2021-04-16T16:35:58.470" Score="8" ViewCount="243" Body="&lt;p&gt;I want to use the formation energy formula used by the article in the picture below. The authors have used the term &lt;code&gt;S or Sn-rich environment&lt;/code&gt;. What is the meaning of this? How it is related to the calculation of formation energy?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KCQ7k.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KCQ7k.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Reference paper : &lt;a href=&quot;https://doi.org/10.1063/1.5022151&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1063/1.5022151&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-04-21T00:54:22.933" LastActivityDate="2021-04-21T00:54:22.933" Title="What is the meaning of element-rich environment in calculating formation energy?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4731" PostTypeId="2" ParentId="4730" CreationDate="2021-04-16T18:26:53.877" Score="6" Body="&lt;p&gt;How rich the environment is in &lt;span class=&quot;math-container&quot;&gt;$\ce{Sn}$&lt;/span&gt; vs &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt; affects the chemical potential &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{Sn}$&lt;/span&gt; as described in Section IIIA of the linked paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{Sn}$&lt;/span&gt; for the Sn-rich environment is equal to &lt;span class=&quot;math-container&quot;&gt;$E_\ce{Sn}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$E_\ce{Sn}$&lt;/span&gt; is the total energy of Sn per atom in the diamond crystal structure.&lt;/p&gt;&#xA;&lt;p&gt;... &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{Sn}$&lt;/span&gt; can be calculated for the S-rich&#xA;environment as &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{Sn}= E_\ce{SnS}-E_\ce{S}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(Note &lt;span class=&quot;math-container&quot;&gt;$E_\ce{SnS}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_\ce{S}$&lt;/span&gt; in the quote above are the energy per formula unit and atom respectively).&#xA;As your image shows, the formation energy depends on &lt;span class=&quot;math-container&quot;&gt;$\mu_\ce{Sn}$&lt;/span&gt;, so it also depends on how rich the environment is in &lt;span class=&quot;math-container&quot;&gt;$\ce{Sn}$&lt;/span&gt; vs &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Richness here is just referring to how abundant a given element is in the surroundings. This won't change the simulations of the monolayer, but it does affect the formation energy. This is because in an Sn-rich environment, you are not just producing a lone Sn atom when you remove it from SnS. Rather, you are implicitly incorporating it into bulk metallic Sn, which has different energetics. For an S-rich environment, they assume the Sn is instead producing a site of SnS at the expense of a site from bulk S. So depending on the environment, the overall formation process is different.&lt;/p&gt;&#xA;&lt;p&gt;If you aren't concerned about the environment effects, you could use the same definition for the chemical potential as was used for the doping transition metal (e.g. the energy of one isolated atom). They actually do this earlier in the linked paper, where they compute vacancy formation energies for SnS either using the environment affected chemical potentials or just the energy of a lone atom.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-17T14:13:35.247" LastActivityDate="2021-04-17T14:13:35.247" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4732" PostTypeId="1" AcceptedAnswerId="4733" CreationDate="2021-04-16T14:33:40.493" Score="7" ViewCount="655" Body="&lt;p&gt;I am running a TS computation in Gaussian 16. It performs several steps.&lt;/p&gt;&#xA;&lt;p&gt;At the end of each there is a summary on whether &lt;code&gt;Maximum Force&lt;/code&gt;, &lt;code&gt;RMS Force&lt;/code&gt;, &lt;code&gt;Maximum Displacement&lt;/code&gt; and &lt;code&gt;RMS Displacement&lt;/code&gt; have converged. The thing is that in several of my computations the second-last step reports all 4 converged and in the last step always one or two are not longer converged.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why is that? Does that mean I can take the second last step parameters and use them?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="3416" OwnerDisplayName="Bpi" LastEditorUserId="5" LastEditDate="2021-04-25T03:07:18.580" LastActivityDate="2021-04-25T03:07:18.580" Title="Gaussian: Transition state convergence question" Tags="|gaussian|geometry-optimization|from-chem-se|transition-state|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4733" PostTypeId="2" ParentId="4732" CreationDate="2021-04-16T19:57:24.297" Score="5" Body="&lt;p&gt;Are you doing an &lt;code&gt;opt&lt;/code&gt; and &lt;code&gt;freq&lt;/code&gt; calculation? In Gaussian, the &lt;code&gt;opt&lt;/code&gt; keyword uses an approximate Hessian to determine the displacement at each step. The &lt;code&gt;freq&lt;/code&gt; keyword will recalculate these displacements using the actual Hessian for that level of theory and sometimes you will find that they are no longer below the threshold. This can mean that your structure is not fully converged.&lt;/p&gt;&#xA;&lt;p&gt;To ensure that the optimization is actually fully converged, you can include the keyword &lt;code&gt;opt(RecalcFC=N)&lt;/code&gt; in your calculation to make it use the actual Hessian in the optimization every &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; steps.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-04-16T19:57:24.297" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4734" PostTypeId="1" AcceptedAnswerId="4738" CreationDate="2021-04-16T22:07:46.860" Score="7" ViewCount="4274" Body="&lt;p&gt;I want to convert several molecules from &lt;code&gt;sdf&lt;/code&gt; format to &lt;code&gt;pdbqt&lt;/code&gt; using OpenBabel.&lt;/p&gt;&#xA;&lt;p&gt;However, I can't find &lt;code&gt;pdbqt&lt;/code&gt; format neither in the output format options nor in the input.&lt;/p&gt;&#xA;&lt;p&gt;I tried reinstalling MGLTools, as it has AutoDock, but the issue remains.&lt;/p&gt;&#xA;" OwnerUserId="3415" OwnerDisplayName="RoyBatty" LastEditorUserId="5" LastEditDate="2021-04-17T06:25:10.350" LastActivityDate="2021-04-21T02:14:07.013" Title="Converting SDF to PDBQT using OpenBabel" Tags="|software|software-assistance|avogadro|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4735" PostTypeId="1" CreationDate="2021-04-17T06:38:11.447" Score="8" ViewCount="444" Body="&lt;p&gt;I am trying to store hydrogen in a hydrocarbon.&#xA;The example can be taken as cyclohexane (&lt;span class=&quot;math-container&quot;&gt;$\ce{C6H12}$&lt;/span&gt;) which is in a hydrogen-rich state. Its hydrogen-lean state is Benzene.&lt;/p&gt;&#xA;&lt;p&gt;I want to calculate the volumetric energy density of cyclohexane.&lt;/p&gt;&#xA;&lt;p&gt;The reported value of &lt;a href=&quot;https://en.wikipedia.org/wiki/Cyclohexane&quot; rel=&quot;nofollow noreferrer&quot;&gt;density on Wikipedia&lt;/a&gt; is 0.7739 g/mL for the liquid and 0.996 g/mL for the solid, along with a note:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Except where otherwise noted, data are given for materials in their standard state (at 25 °C [77 °F], 100 kPa).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The molar mass of cyclohexane is 84.16 g/mol.&lt;/p&gt;&#xA;&lt;p&gt;I could not understand how to calculate the density value as given on the above mention Wikipedia page.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-04-20T21:06:25.340" LastActivityDate="2021-04-20T21:36:44.123" Title="How to calculate the volumetric energy density of a molecule?" Tags="|molecular-dynamics|molecular-modeling|physical-properties-of-materials|experimental|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4736" PostTypeId="1" AcceptedAnswerId="4740" CreationDate="2021-04-17T12:56:45.500" Score="12" ViewCount="305" Body="&lt;p&gt;I am currently looking for an efficient way to detect common functional groups - that is, characterize whether a molecule is an alcohol, an aromatic compound, etc. - in a larger database consisting of xyz geometry files. Is there an existing tool out there that could do this task?&lt;/p&gt;&#xA;&lt;p&gt;I am aware that the task is not well-defined, since connectivity between different atoms is always up to some empiricism in an xyz file. Moreover, the definition of functional groups is also not super obvious. However, I am aware of tools that would categorize a structure based on a connectivity matrix (such as &lt;a href=&quot;https://homepage.univie.ac.at/norbert.haider/cheminf/cmmm.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;checkmol&lt;/a&gt;), and converting an xyz file to a connectivity matrix should also be a solved issue (for example all visualization softwares seem to do it). It might also be very well possible that such operation is contained in OpenBabel or a similar bundle, I am just not completely familiar with these tools, and I would rather not invest days, or weeks, writing scripts that might already be out there.&lt;/p&gt;&#xA;&lt;p&gt;Has someone worked on a problem like this, or do you know how to automatically detect functional groups from Cartesian geometry?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Based on the excellent answer below, I've compiled a rudimentary Bash script that sort of does what I wanted it to do. I am sharing it now, as it might be helpful for others&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;XYZ_DIR=/directory_to_xyz&#xA;MOLDIR=/output_of_mols&#xA;GROUPDIR=/output_of_groups&#xA;&#xA;for file in &lt;span class=&quot;math-container&quot;&gt;$XYZ_DIR/*xyz; do&#xA;  obabel $&lt;/span&gt;file -omol -O &lt;span class=&quot;math-container&quot;&gt;${file%.xyz}.mol 2&amp;gt; &amp;gt;(grep -v &quot;onvert&quot;)&#xA;  ./checkmol $&lt;/span&gt;{file%.xyz}.mol &amp;gt; &lt;span class=&quot;math-container&quot;&gt;${file%.xyz}.groups&#xA;  mv $&lt;/span&gt;{file%.xyz}.mol &lt;span class=&quot;math-container&quot;&gt;$MOLDIR/&#xA;  mv $&lt;/span&gt;{file%.xyz}.groups $GROUPDIR&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that the OpenBabel output has been supressed when the conversion is succesfull so as not to clutter the screen.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastEditorDisplayName="user430" LastEditDate="2021-04-20T09:29:07.687" LastActivityDate="2021-06-01T13:10:16.753" Title="Functional group detection from geometry" Tags="|software|molecular-modeling|geometry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4737" PostTypeId="1" AcceptedAnswerId="4745" CreationDate="2021-04-17T15:56:52.930" Score="11" ViewCount="425" Body="&lt;p&gt;What is the meaning of spin-splitting energy &lt;a href=&quot;https://doi.org/10.1063/1.5022151&quot; rel=&quot;nofollow noreferrer&quot;&gt;as described here&lt;/a&gt;?&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-04-20T20:57:35.287" LastActivityDate="2021-11-13T19:15:50.717" Title="What do we mean by spin-splitting energy?" Tags="|density-of-states|transition-metals|spin|crystal-field|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4738" PostTypeId="2" ParentId="4734" CreationDate="2021-04-17T16:02:21.593" Score="7" Body="&lt;p&gt;Please, check the version of OpenBabel you are using. At least, version 3.1.0 has the &lt;code&gt;pdbqt&lt;/code&gt; format implemented:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# obabel -v&#xA;No input file or format spec or possibly a misplaced option.&#xA;Most options must come after the input files. (-i -o -O -m can be anywhwere.)&#xA;&#xA;Open Babel 3.1.0 -- Jan 11 2021 -- 11:51:22&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# obabel -L formats&#xA;abinit -- ABINIT Output Format [Read-only]&#xA;acesin -- ACES input format [Write-only]&#xA;acesout -- ACES output format [Read-only]&#xA;acr -- ACR format [Read-only]&#xA;adf -- ADF cartesian input format [Write-only]&#xA;adfband -- ADF Band output format [Read-only]&#xA;adfdftb -- ADF DFTB output format [Read-only]&#xA;adfout -- ADF output format [Read-only]&#xA;alc -- Alchemy format&#xA;aoforce -- Turbomole AOFORCE output format [Read-only]&#xA;arc -- Accelrys/MSI Biosym/Insight II CAR format [Read-only]&#xA;ascii -- ASCII format [Write-only]&#xA;axsf -- XCrySDen Structure Format [Read-only]&#xA;bgf -- MSI BGF format&#xA;box -- Dock 3.5 Box format&#xA;bs -- Ball and Stick format&#xA;c09out -- Crystal 09 output format [Read-only]&#xA;c3d1 -- Chem3D Cartesian 1 format&#xA;c3d2 -- Chem3D Cartesian 2 format&#xA;cac -- CAChe MolStruct format [Write-only]&#xA;caccrt -- Cacao Cartesian format&#xA;cache -- CAChe MolStruct format [Write-only]&#xA;cacint -- Cacao Internal format [Write-only]&#xA;can -- Canonical SMILES format&#xA;car -- Accelrys/MSI Biosym/Insight II CAR format [Read-only]&#xA;castep -- CASTEP format [Read-only]&#xA;ccc -- CCC format [Read-only]&#xA;cdjson -- ChemDoodle JSON&#xA;cdx -- ChemDraw binary format [Read-only]&#xA;cdxml -- ChemDraw CDXML format&#xA;cht -- Chemtool format [Write-only]&#xA;cif -- Crystallographic Information File&#xA;ck -- ChemKin format&#xA;cml -- Chemical Markup Language&#xA;cmlr -- CML Reaction format&#xA;cof -- Culgi object file format&#xA;com -- Gaussian Input [Write-only]&#xA;confabreport -- Confab report format [Write-only]&#xA;CONFIG -- DL-POLY CONFIG&#xA;CONTCAR -- VASP format&#xA;CONTFF -- MDFF format&#xA;copy -- Copy raw text [Write-only]&#xA;crk2d -- Chemical Resource Kit diagram(2D)&#xA;crk3d -- Chemical Resource Kit 3D format&#xA;csr -- Accelrys/MSI Quanta CSR format [Write-only]&#xA;cssr -- CSD CSSR format [Write-only]&#xA;ct -- ChemDraw Connection Table format&#xA;cub -- Gaussian cube format&#xA;cube -- Gaussian cube format&#xA;dallog -- DALTON output format [Read-only]&#xA;dalmol -- DALTON input format&#xA;dat -- Generic Output file format [Read-only]&#xA;dmol -- DMol3 coordinates format&#xA;dx -- OpenDX cube format for APBS&#xA;ent -- Protein Data Bank format&#xA;exyz -- Extended XYZ cartesian coordinates format&#xA;fa -- FASTA format&#xA;fasta -- FASTA format&#xA;fch -- Gaussian formatted checkpoint file format [Read-only]&#xA;fchk -- Gaussian formatted checkpoint file format [Read-only]&#xA;fck -- Gaussian formatted checkpoint file format [Read-only]&#xA;feat -- Feature format&#xA;fh -- Fenske-Hall Z-Matrix format [Write-only]&#xA;fhiaims -- FHIaims XYZ format&#xA;fix -- SMILES FIX format [Write-only]&#xA;fps -- FPS text fingerprint format (Dalke) [Write-only]&#xA;fpt -- Fingerprint format [Write-only]&#xA;fract -- Free Form Fractional format&#xA;fs -- Fastsearch format&#xA;fsa -- FASTA format&#xA;g03 -- Gaussian Output [Read-only]&#xA;g09 -- Gaussian Output [Read-only]&#xA;g16 -- Gaussian Output [Read-only]&#xA;g92 -- Gaussian Output [Read-only]&#xA;g94 -- Gaussian Output [Read-only]&#xA;g98 -- Gaussian Output [Read-only]&#xA;gal -- Gaussian Output [Read-only]&#xA;gam -- GAMESS Output [Read-only]&#xA;gamess -- GAMESS Output [Read-only]&#xA;gamin -- GAMESS Input&#xA;gamout -- GAMESS Output [Read-only]&#xA;gau -- Gaussian Input [Write-only]&#xA;gjc -- Gaussian Input [Write-only]&#xA;gjf -- Gaussian Input [Write-only]&#xA;got -- GULP format [Read-only]&#xA;gpr -- Ghemical format&#xA;gr96 -- GROMOS96 format [Write-only]&#xA;gro -- GRO format&#xA;gukin -- GAMESS-UK Input&#xA;gukout -- GAMESS-UK Output&#xA;gzmat -- Gaussian Z-Matrix Input&#xA;hin -- HyperChem HIN format&#xA;HISTORY -- DL-POLY HISTORY [Read-only]&#xA;inchi -- InChI format&#xA;inchikey -- InChIKey [Write-only]&#xA;inp -- GAMESS Input&#xA;ins -- ShelX format [Read-only]&#xA;jin -- Jaguar input format&#xA;jout -- Jaguar output format [Read-only]&#xA;k -- Compare molecules using InChI [Write-only]&#xA;lmpdat -- The LAMMPS data format [Write-only]&#xA;log -- Generic Output file format [Read-only]&#xA;lpmd -- LPMD format&#xA;mae -- Maestro format&#xA;maegz -- Maestro format&#xA;mcdl -- MCDL format&#xA;mcif -- Macromolecular Crystallographic Info&#xA;MDFF -- MDFF format&#xA;mdl -- MDL MOL format&#xA;ml2 -- Sybyl Mol2 format&#xA;mmcif -- Macromolecular Crystallographic Info&#xA;mmd -- MacroModel format&#xA;mmod -- MacroModel format&#xA;mna -- Multilevel Neighborhoods of Atoms (MNA) [Write-only]&#xA;mol -- MDL MOL format&#xA;mol2 -- Sybyl Mol2 format&#xA;mold -- Molden format&#xA;molden -- Molden format&#xA;molf -- Molden format&#xA;molreport -- Open Babel molecule report [Write-only]&#xA;moo -- MOPAC Output format [Read-only]&#xA;mop -- MOPAC Cartesian format&#xA;mopcrt -- MOPAC Cartesian format&#xA;mopin -- MOPAC Internal&#xA;mopout -- MOPAC Output format [Read-only]&#xA;mp -- Molpro input format [Write-only]&#xA;mpc -- MOPAC Cartesian format&#xA;mpd -- MolPrint2D format [Write-only]&#xA;mpo -- Molpro output format [Read-only]&#xA;mpqc -- MPQC output format [Read-only]&#xA;mpqcin -- MPQC simplified input format [Write-only]&#xA;mrv -- Chemical Markup Language&#xA;msi -- Accelrys/MSI Cerius II MSI format [Read-only]&#xA;msms -- M.F. Sanner's MSMS input format [Write-only]&#xA;nul -- Outputs nothing [Write-only]&#xA;nw -- NWChem input format [Write-only]&#xA;nwo -- NWChem output format [Read-only]&#xA;orca -- ORCA output format [Read-only]&#xA;orcainp -- ORCA input format [Write-only]&#xA;out -- Generic Output file format [Read-only]&#xA;outmol -- DMol3 coordinates format&#xA;output -- Generic Output file format [Read-only]&#xA;paint -- Painter format [Write-only]&#xA;pc -- PubChem format [Read-only]&#xA;pcjson -- PubChem JSON&#xA;pcm -- PCModel Format&#xA;pdb -- Protein Data Bank format&#xA;pdbqt -- AutoDock PDBQT format&#xA;png -- PNG 2D depiction&#xA;pointcloud -- Point cloud on VDW surface [Write-only]&#xA;pos -- POS cartesian coordinates format [Read-only]&#xA;POSCAR -- VASP format&#xA;POSFF -- MDFF format&#xA;pov -- POV-Ray input format [Write-only]&#xA;pqr -- PQR format&#xA;pqs -- Parallel Quantum Solutions format&#xA;prep -- Amber Prep format [Read-only]&#xA;pwscf -- PWscf format [Read-only]&#xA;qcin -- Q-Chem input format [Write-only]&#xA;qcout -- Q-Chem output format [Read-only]&#xA;report -- Open Babel report format [Write-only]&#xA;res -- ShelX format [Read-only]&#xA;rinchi -- RInChI [Write-only]&#xA;rsmi -- Reaction SMILES format&#xA;rxn -- MDL RXN format&#xA;sd -- MDL MOL format&#xA;sdf -- MDL MOL format&#xA;siesta -- SIESTA format [Read-only]&#xA;smi -- SMILES format&#xA;smiles -- SMILES format&#xA;smy -- SMILES format using Smiley parser [Read-only]&#xA;stl -- STL 3D-printing format [Write-only]&#xA;svg -- SVG 2D depiction [Write-only]&#xA;sy2 -- Sybyl Mol2 format&#xA;t41 -- ADF TAPE41 format [Read-only]&#xA;tdd -- Thermo format&#xA;text -- Read and write raw text&#xA;therm -- Thermo format&#xA;tmol -- TurboMole Coordinate format&#xA;txt -- Title format&#xA;txyz -- Tinker XYZ format&#xA;unixyz -- UniChem XYZ format&#xA;VASP -- VASP format&#xA;vmol -- ViewMol format&#xA;wln -- Wiswesser Line Notation [Read-only]&#xA;xed -- XED format [Write-only]&#xA;xml -- General XML format [Read-only]&#xA;xsf -- XCrySDen Structure Format [Read-only]&#xA;xyz -- XYZ cartesian coordinates format&#xA;yob -- YASARA.org YOB format&#xA;zin -- ZINDO input format [Write-only]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-17T16:02:21.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4739" PostTypeId="2" ParentId="4665" CreationDate="2021-04-17T17:11:05.450" Score="3" Body="&lt;p&gt;In the Wikipedia link you provided, there are several packages capable to predict the RNA secondary structure already including pseudoknot prediction. Also, the links to the source code, executable or webserver are given. All of them start from sequence data.&lt;/p&gt;&#xA;&lt;p&gt;My suggestion is to use a service like &lt;a href=&quot;http://iimcb.genesilico.pl/comparna/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CompaRNA&lt;/a&gt; that benchmark different methods/software used to predict the secondary RNA structure, always using  experimental deposited structures in &lt;a href=&quot;https://www.wwpdb.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDB&lt;/a&gt; and &lt;a href=&quot;http://www.rnasoft.ca/strand/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RNAstrand&lt;/a&gt; servers to prepare the datasets.&lt;br /&gt;&#xA;Article: Tomasz Puton, Lukasz P. Kozlowski, Kristian M. Rother, Janusz M. Bujnicki, &lt;em&gt;CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction&lt;/em&gt;, &lt;strong&gt;Nucleic Acids Research&lt;/strong&gt;, 41, 4307–4323 (2013), &lt;a href=&quot;https://doi.org/10.1093/nar/gkt101&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1093/nar/gkt101&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Answering your question, take a look at this package that uses neural networks instead sequence data:&lt;/p&gt;&#xA;&lt;h2&gt;bpRNA: Large-scale Automated Annotation and Analysis of RNA Secondary Structure&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The code is available here as a perl script called &amp;quot;bpRNA.pl&amp;quot;. To use&#xA;the bpRNA script, one needs a bpseq file or dot-bracket file as&#xA;input.It should automatically detect input file format. The output of&#xA;the bpRNA is a &amp;quot;structure type&amp;quot; file with all the details on segments,&#xA;stems, hairpins, bulges, internal loops, multiloops, and pseudoknots.&#xA;The structure type file has the same filebase as the input, and with&#xA;the extension &amp;quot;.st&amp;quot;. Moreover, bpRNA provides efficient dotbracket&#xA;notations and other structural representations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Github repo: &lt;a href=&quot;https://github.com/hendrixlab/bpRNA&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/hendrixlab/bpRNA&lt;/a&gt;&lt;br /&gt;&#xA;Article: Singh, J., Hanson, J., Paliwal, K. et al. &lt;em&gt;RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning&lt;/em&gt;. &lt;strong&gt;Nat Commun&lt;/strong&gt; 10, 5407 (2019). &lt;a href=&quot;https://doi.org/10.1038/s41467-019-13395-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/s41467-019-13395-9&lt;/a&gt;&lt;br /&gt;&#xA;PDF: &lt;a href=&quot;https://www.nature.com/articles/s41467-019-13395-9.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/s41467-019-13395-9.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-17T17:11:05.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4740" PostTypeId="2" ParentId="4736" CreationDate="2021-04-17T20:35:29.233" Score="10" Body="&lt;p&gt;You can probably do it with only OpenBabel or RDKit using SMARTS search strings, but you can get a much easier solution if you combine OpenBabel with checkmol (which you have mentioned in the question).&lt;/p&gt;&#xA;&lt;p&gt;First, convert the &lt;code&gt;.xyz&lt;/code&gt; file into a &lt;code&gt;.mol&lt;/code&gt; file that checkmol can recognize. This can be done with Openbabel which can automatically detect bonds from 3D coordinates:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel input.xyz -omol -O output.mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then use checkmol on the generated &lt;code&gt;.mol&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;checkmol -e output.mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;-e&lt;/code&gt; flag gives you the names of the functional groups in English (as in &amp;quot;carboxylic acid&amp;quot;, &amp;quot;lactam&amp;quot; etc.). If you want to use that output somewhere else, you can use the &lt;code&gt;-c&lt;/code&gt; flag instead, which will return codes of each functional group. The table of functional groups and their codes can be found &lt;a href=&quot;https://homepage.univie.ac.at/norbert.haider/cheminf/fgtable.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.  (link obtained from checkmol homepage)&lt;/p&gt;&#xA;&lt;p&gt;For example, running the programs on penicilin gives:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;obabel penicilin.xyz -omol -O penicilin.mol&#xA;&#xA;&amp;gt;checkmol -e penicilin.mol&#xA;&#xA;hemithioaminal&#xA;carboxylic acid&#xA;secondary carboxylic acid amide&#xA;tertiary carboxylic acid amide&#xA;lactam&#xA;aromatic compound&#xA;heterocyclic compound&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;If you have a large number of &lt;code&gt;.xyz&lt;/code&gt; files to process, then you can automate them with a shell/batch script. On Windows, you can use something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@echo off&#xA;for /f %%f in ('dir /b .\*.xyz') do @(&#xA;echo Converting %%f to %%~nf.mol&#xA;obabel .\%%f -omol -O .\%%~nf.mol &amp;gt;NUL 2&amp;gt;NUL&#xA;echo Writing functional group codes to %%~nf.txt &#xA;checkmol -c .\%%~nf.mol &amp;gt; .\%%~nf.txt&#xA;erase /Q .\%%~nf.mol &amp;gt;NUL)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Save this as a &lt;code&gt;.bat&lt;/code&gt; file, and then run it inside the folder with &lt;code&gt;.xyz&lt;/code&gt; files. It will convert each file into &lt;code&gt;.mol&lt;/code&gt;, then use checkmol on it, save the functional group codes in a &lt;code&gt;.txt&lt;/code&gt; file and then erase the &lt;code&gt;.mol&lt;/code&gt; file. The &lt;code&gt;&amp;gt;NUL&lt;/code&gt; and &lt;code&gt;2&amp;gt;NUL&lt;/code&gt; flags suppress stdout and stderr (i.e. output and error output) respectively. I added this as OpenBabel for some reason gives a lot of warnings during conversion, even though the &lt;code&gt;.mol&lt;/code&gt; file is created successfully. If you are getting unknown errors, then remove those flags to see full output.&lt;/p&gt;&#xA;&lt;p&gt;(Of course, the openbabel and checkmol executable has to be in PATH for the script to work)&lt;/p&gt;&#xA;&lt;p&gt;I don't know much about Linux and Mac OS scripting so I can't help there.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;OpenBabel: &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://openbabel.org/wiki/Main_Page&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Checkmol: &lt;a href=&quot;https://homepage.univie.ac.at/norbert.haider/cheminf/cmmm.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://homepage.univie.ac.at/norbert.haider/cheminf/cmmm.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-01T13:10:16.753" LastActivityDate="2021-06-01T13:10:16.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4741" PostTypeId="1" AcceptedAnswerId="7054" CreationDate="2021-04-17T21:15:12.047" Score="11" ViewCount="120" Body="&lt;p&gt;What are the signs (if any) in DOS plots that tell us whether we have a big or small crystal-field splitting energy, or spin-splitting energy?  I already asked and got an answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4737/5&quot;&gt;What do we mean by spin-splitting energy?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am asking in the context of &lt;a href=&quot;https://doi.org/10.1063/1.5022151&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; which discusses a comparison between spin-splitting energy and &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;crystal field splitting&lt;/a&gt; energy, and shows multiple DOS plots.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-10-30T20:27:59.760" LastActivityDate="2021-11-13T19:20:02.797" Title="Can crystal field splitting energy or spin-splitting energy be detected in a density-of-states plot? How?" Tags="|density-of-states|transition-metals|spin|crystal-field|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4742" PostTypeId="2" ParentId="4737" CreationDate="2021-04-17T22:23:02.753" Score="8" Body="&lt;p&gt;The word &amp;quot;splitting&amp;quot; seems to occur only in one sentence, over the course of the entire paper that you referenced:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The d-orbital spin-splitting energy is stronger than the weak crystal field splitting energy of the S ligand around the TM atoms&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I can see why you had to ask this question here, because when I search &lt;a href=&quot;https://www.google.com/search?q=%22d-orbital+spin-splitting%22&amp;amp;biw=1823&amp;amp;bih=898&amp;amp;ei=DVp7YKyMLcLwsAW4jZj4Dg&amp;amp;oq=%22d-orbital+spin-splitting%22&amp;amp;gs_lcp=Cgdnd3Mtd2l6EANQv8EEWIXCBGDuwwRoAXAAeACAAV-IAYYCkgEBM5gBAKABAaoBB2d3cy13aXrAAQE&amp;amp;sclient=gws-wiz&amp;amp;ved=0ahUKEwjsxvCWo4bwAhVCOKwKHbgGBu8Q4dUDCA4&amp;amp;uact=5&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;d-orbital spin-splitting&amp;quot;&lt;/a&gt; in quotes (so that we're searching for that exact phrase), only two results come up: &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/abdb12&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.78.134421&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; (the same happens if I replace either of the hyphens with spaces.&lt;/p&gt;&#xA;&lt;p&gt;The phrase &amp;quot;d-orbital splitting&amp;quot; doesn't show up much either, but at least it shows up &lt;a href=&quot;https://chem.libretexts.org/Courses/Saint_Marys_College_Notre_Dame_IN/CHEM_431%3A_Inorganic_Chemistry_(Haas)/CHEM_431_Readings/11%3A_Ligand_Field_Theory_(LFT)_and_Crystal_Field_Theory_(CFT)_of_Octahedral_Complexes/11.04%3A_The_Effect_of_the_Metal_Ion_on_d-Orbital_Splitting&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; where the splitting discussed is &lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt; which is actually the &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;noreferrer&quot;&gt;crystal field splitting energy&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In this particular paper, it seems that what they're referring to when they say &amp;quot;d-orbital spin-splitting energy&amp;quot; is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin_states_(d_electrons)#High-spin_vs._low-spin&quot; rel=&quot;noreferrer&quot;&gt;difference in energy between the high-spin and low-spin configurations&lt;/a&gt;. The paper goes on to say that because the d-orbital spin-splitting energy is stronger (i.e. larger) than the weak (i.e. small) crystal field splitting energy (&lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt;), the system is said to be in the &amp;quot;high-spin state&amp;quot;. This would make sense since high-spin states are sometimes characterized as having a small &lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt;, for example, in the Wikipedia page in the last link I provided, it shows &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt; small&amp;quot; for the high-spin states:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Cycfd.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cycfd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt; large&amp;quot; for the low-spin states:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/F5dfZ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/F5dfZ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My reading of the relevant paragraph suggests to me that the authors made this conclusion about the &amp;quot;d-orbital spin-splitting&amp;quot; being larger than the crystal field splitting of &lt;span class=&quot;math-container&quot;&gt;$\Delta_0$&lt;/span&gt; based on Table II, rather than any of the DOS figures. So perhaps the readers are not expected to deduce this by looking at the DOS plots as you ask how to do, but it could be possible, and that's why this nice Q/A system allows us to get answers from multiple people .&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-17T22:23:02.753" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4743" PostTypeId="1" AcceptedAnswerId="4748" CreationDate="2021-04-18T00:41:45.877" Score="5" ViewCount="66" Body="&lt;p&gt;Since metals, metalloids, non-metals, and composites, have differing characteristics, plug-and-play methods, so to speak, would be useful.&lt;/p&gt;&#xA;&lt;p&gt;Also, as it’s well known that a moving electrical field generates a magnetic field, and vice-versa, finding ways to reduce that complexity while retaining a reasonable level of correctness would be highly useful.&lt;/p&gt;&#xA;" OwnerUserId="3417" LastActivityDate="2021-04-20T01:02:54.210" Title="What are the more efficient, or easier, methods of handling electromagnetic interactions?" Tags="|molecular-modeling|molecular-interactions|electric-field|atomistic-simulation|magnetic-field|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4744" PostTypeId="2" ParentId="1551" CreationDate="2021-04-18T05:51:48.793" Score="7" Body="&lt;p&gt;The answer by Anyon does not address how to calculate the form of the Slater-Koster two-center integrals (2CI) but rather how to determine the direction cosines that appear in the 2CI's (the &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;'s in things like &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}lm*(sd\sigma)$&lt;/span&gt;, but not the &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt;). I am currently trying to explicitly perform the same calculation to include in my comps so I can sympathize with your frustration in the lack of clarity in the literature...&lt;/p&gt;&#xA;&lt;p&gt;Any who, the most explicit reference I have found that explains how to actually calculate the SK-matrix elements is in this paper (Takegahara et al 1980 J. Phys. C: Solid State Phys. 13 583, Slater-Koster tables for f electrons) where Takegahara extends the original SK table to f electrons.&lt;/p&gt;&#xA;&lt;p&gt;The fundamental strategy he invokes, which is very tedious, is to calculate the form of hopping elements along the bond direction and then rotate it into a generic orientation to make use of the l,m,n- direction cosines we are familiar with.&lt;/p&gt;&#xA;&lt;p&gt;Sorry that this is less of an answer and more of a comment, I don't have enough reputation to post any other way.&lt;/p&gt;&#xA;" OwnerUserId="3405" LastEditorUserId="5" LastEditDate="2021-04-18T06:07:33.773" LastActivityDate="2021-04-18T06:07:33.773" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4745" PostTypeId="2" ParentId="4737" CreationDate="2021-04-18T17:07:18.443" Score="5" Body="&lt;p&gt;I see now how your initial questions were related, as they all fall under the scope of crystal field theory. I wrote a bit about this in a &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3860/7&quot;&gt;previous answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;At least in the context of molecular crystal field theory, you will usually see the phrase &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Supplemental_Modules_(Physical_and_Theoretical_Chemistry)/Electronic_Structure_of_Atoms_and_Molecules/Electronic_Configurations/Spin_Pairing_Energy&quot; rel=&quot;nofollow noreferrer&quot;&gt;pairing energy&lt;/a&gt; rather than &amp;quot;spin-splitting&amp;quot;. The distinction is basically just the direction, where the pairing energy is the penalty for having electrons share the same spatial orbital and the spin-splitting energy would be the increased stability from separating a pair.&lt;/p&gt;&#xA;&lt;p&gt;I don't believe the spin-splitting or field splitting can be read from the DOS. The way they are mentioned in the paper seems to suggest they are giving a qualitative explanation for seeing all the compounds in high spin configurations. The &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Spectrochemical_series&quot; rel=&quot;nofollow noreferrer&quot;&gt;spectrochemical series&lt;/a&gt; gives an ordering of ligands based on how much field splitting they should cause. Since &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt; is known to be a weak-field ligand, it makes sense that the spin splitting energy would be larger than the field splitting, leading to high spin configurations.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-13T19:15:50.717" LastActivityDate="2021-11-13T19:15:50.717" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4746" PostTypeId="2" ParentId="2473" CreationDate="2021-04-19T02:11:31.683" Score="5" Body="&lt;p&gt;Just to provide an answer to this question, my conclusion after all this is that in general, there is unfortunately not a great answer. I likely put too many constraints on the question.&lt;/p&gt;&#xA;&lt;p&gt;As noted in &lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Thirty Years of DFT&amp;quot;&lt;/a&gt; from the Head-Gordon group, ωB97X-V and the more expensive ωB97M-V are both excellent options for many tasks but are not widely available outside of Q-Chem at the time of writing. On the Minnesota functional side of things, revM06 and MN15 have addressed some of their older grid and SCF convergence-related challenges. Unfortunately, ORCA doesn't support analytical Hessians for meta-(hybrid) GGAs, but at least MN15 is in the current release of Gaussian. This isn't even getting into the topic of spin states. That's a whole other can of worms.&lt;/p&gt;&#xA;&lt;p&gt;For now, it's a bit of a free-for-all depending on the code you have access to, but I'm hopeful in the future that ωB97M-V and ωB97X-V will become more widely available in DFT codes. Perhaps in a year or two when someone sees this post, they'll be able to provide a more definitive answer.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-04-19T02:11:31.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4748" PostTypeId="2" ParentId="4743" CreationDate="2021-04-19T07:23:00.223" Score="4" Body="&lt;p&gt;You could simplify long range interaction by reducing precision with range. Useful algorithm for it is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Barnes%E2%80%93Hut_simulation&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Barnes%E2%80%93Hut_simulation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is usually used for gravity, but it can be applied for other forces too. With it you can do something better than just to ignore long range interaction, as is usually done, especially important with magnetic fields at larger scale.&lt;/p&gt;&#xA;" OwnerUserId="1690" LastEditorUserId="1690" LastEditDate="2021-04-20T01:02:54.210" LastActivityDate="2021-04-20T01:02:54.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4749" PostTypeId="1" CreationDate="2021-04-19T08:42:33.067" Score="6" ViewCount="745" Body="&lt;p&gt;I have to validate one of my docking protocol but I haven't a co-crystalized ligand. There is a way to validate it? Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="24" LastEditDate="2021-04-19T09:35:32.247" LastActivityDate="2022-10-18T16:12:14.190" Title="How can I validate docking result without a co-crystallized ligand?" Tags="|docking|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4750" PostTypeId="1" CreationDate="2021-04-19T09:38:19.073" Score="5" ViewCount="416" Body="&lt;p&gt;I performed a molecular docking and when I tried to validate it, the RMSD values are over &lt;span class=&quot;math-container&quot;&gt;$3 \overset{\circ}{\mathrm{A}}$&lt;/span&gt;. I don't understand how I can fix it. Could someone help me?&#xA;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="1380" LastEditDate="2021-04-19T18:02:07.297" LastActivityDate="2021-04-19T18:02:07.297" Title="Docking validation RMSD over 3, How can I fix it?" Tags="|docking|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4751" PostTypeId="2" ParentId="4749" CreationDate="2021-04-19T09:53:35.483" Score="4" Body="&lt;h2&gt;Using different score functions&lt;/h2&gt;&#xA;&lt;p&gt;One way to validate the docking results is scoring your poses using a different score function. You will need to use one of this two methods:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Use another docking software: in this case you have to do a score-in-place procedure, i.e. not re-docking your ligands, just score the poses. For example, if you work with GLIDE (that is the software that do the docking in the Schrodinger suite, not MAESTRO), you can use &lt;a href=&quot;http://vina.scripps.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AUTODOCK-VINA&lt;/a&gt;, &lt;a href=&quot;https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/pharmazie-und-biochemie/teilbereich-pharmazie-pharmazeutisches-institut/pharmazeutische-chemie/pd-dr-t-exner/research/plants/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PLANTS&lt;/a&gt;, &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-discovery/components/gold/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GOLD&lt;/a&gt;, etc.&lt;/li&gt;&#xA;&lt;li&gt;Use scoring software: these software have the only purpose to score the poses using score functions obtained from experimental data. Examples are &lt;a href=&quot;https://www.ics.uci.edu/%7Edock/manuals/xscore1.1_manual/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;XSCORE&lt;/a&gt;, &lt;a href=&quot;https://weilab.math.msu.edu/AGL-Score/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AGL-SCORE&lt;/a&gt;, &lt;a href=&quot;https://github.com/sirimullalab/DLSCORE&quot; rel=&quot;nofollow noreferrer&quot;&gt;DLSCORE&lt;/a&gt;, etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you obtain the same pose rank using a different score functions, then your docking results are good (without any bias due to the software used)&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-19T09:53:35.483" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4752" PostTypeId="2" ParentId="4750" CreationDate="2021-04-19T10:04:34.667" Score="5" Body="&lt;p&gt;You cannot &amp;quot;fix&amp;quot; it.&lt;/p&gt;&#xA;&lt;p&gt;As a RMSD value is considered good below &lt;span class=&quot;math-container&quot;&gt;$2 \overset{\circ}{\mathrm{A}}$&lt;/span&gt;, you can try one of this two methods to obtain better RMSD:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Repeat the docking calculation several times. In general, docking software start the search from a generated conformer population. If you run it several times, this initial population will be different, so, the starting point will be different producing different results.&lt;/li&gt;&#xA;&lt;li&gt;Change your docking software. Some times the score function of the docking software was tailored from a family of protein. Using a protein from different family can return bad results.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-19T10:04:34.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4753" PostTypeId="1" AcceptedAnswerId="4779" CreationDate="2021-04-19T11:44:34.777" Score="7" ViewCount="2345" Body="&lt;p&gt;I am wondering if you could show me how to use gnuplot to draw bandstructure and DOS plots starting from VASP outputs. If you have any scripts please share them with us.&#xA;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-04-19T19:56:08.437" LastActivityDate="2021-04-22T19:05:12.917" Title="How to use gnuplot to draw Bandstructure and DOS from VASP outputs?" Tags="|vasp|visualization-software|gnuplot|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4754" PostTypeId="2" ParentId="4697" CreationDate="2021-04-20T02:43:31.393" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;This works for organic molecules, but what happens when the excited states are closer in energy to the ground state, for example in open-shell molecules or in atoms?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If there's excited states close to the ground state, the approximation you said Gaussian uses, where excited state contributions are neglected, seems not to be such a great idea anymore. You would now want to include the close-lying excited states. There's plenty of methods that will give you excited state energies, for example &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/194/5&quot;&gt;EOM-CC and STEOM-CC&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;This is where everything becomes confusing to me. If I understand correctly, when the first or higher excited states are closer in energy to the ground state, the Hartree-Fock single determinant solution is not good enough.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When it comes to calculating energies, a single HF determinant is not good enough, even when the first excited state is far away from the ground state. &lt;strong&gt;This is because of the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4325/5&quot;&gt;correlation energy&lt;/a&gt; missed by using HF alone.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;We use multi-configurational methods (such as CASSCF) where we generate excited determinants and consider the molecule's electronic state as a superposition of the different determinants (weighted by their energies?).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's true that CASSCF is an example of a multi-configurational method, and that the molecular state after a CASSCF calculation will be a superposition of various determinants, but they are not weighted by their energies, they are weighted by coefficients that are optimized by the variational principal.&lt;/p&gt;&#xA;&lt;p&gt;There's more than one component of a CASSCF calculation, there's the CAS-CI (CAS-configuration-interaction) calculation where you calculate FCI (full configuration interaction) within an active space (for example all possible excitations from the HF determinant, involving &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; electrons and &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; orbitals); then you do an SCF iteration where you rotate the orbitals to get an even lower energy, then you do another CAS-CI calculation with the rotated orbitals, then you rotate the orbitals again and so on, until you get convergence to your desired precision.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;So this means the solution itself contains contributions from the low-lying excited states.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To get the ground state energy as accurately as possible from a variational calculation, you'll want your wavefunction ansatz to be as flexible as possible, which means including as many determinants as possible if you're modeling it as a linear combination of Slater determinants. Therefore, accurate ground state energies calculated this way, will use a &amp;quot;model&amp;quot; for the wavefunction which certainly contain more than one determinant.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I might be wrong here, but I think the energy levels obtained from CASSCF calculations are obtained as an average of all the determinants,&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The word &amp;quot;average&amp;quot; is not the &lt;em&gt;best&lt;/em&gt; word here. I'd say that the wavefunction is a linear combination of Slater determinants though. This is also not only true for CASSCF but also for other methods such as CISD which is considered a &amp;quot;single reference method&amp;quot;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;and have partial occupation numbers reflecting the excited state contributions.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The CASSCF (and CISD) density matrices will have non-zero occupation numbers for Slater determinants which include &amp;quot;excitations&amp;quot; from the Hartree-Fock (or reference) configuration.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;So, what happens when we do the thermochemistry calculation on a multi-configurational system? Does that mean the electronic partition function term is already included in the SCF energy?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The phrase &amp;quot;multiconfigurational system&amp;quot; is maybe not the best to use here. All molecules have some multiconfigurational character when modeling the wavefunction as a sum of Slater determinants, unless perhaps you had some magical basis.&lt;/p&gt;&#xA;&lt;p&gt;In your question you gave a formula for the partition function. All you need in order to evaluate that formula, are the energies and number of states at each energy level (the latter being what you call you the &amp;quot;degeneracies&amp;quot;). You can calculate all of the energies using something like EOM-CCSD or STEOM-CCSD (and this method will also allow you to determine the &amp;quot;degeneracies&amp;quot;). &lt;strong&gt;When you get the energies from a EOM-CCSD or STEOM-CCSD calculation, each of these energies will include contributions from several Slater determinants.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Does this type of thermochemistry calculation actually make sense?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think you were over-complicating things for yourself, which lead to some confusion. The formula you presented is simple, and to evaluate it, you just need the energies from a method such as EOM-CCSD or STEOM-CCSD, which calculates several excited state energies. Each of these excited state energies will be calculated based on a wavefunction ansatz which involves more than one Slater determinant, but that's okay because even ground state calculations will need more than one Slater determinant if we want a decent accuracy (especially when  &amp;quot;correlation energy&amp;quot; is a large contribution to the overall energy).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-20T02:43:31.393" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4755" PostTypeId="2" ParentId="879" CreationDate="2021-04-20T04:56:39.183" Score="4" Body="&lt;p&gt;I do not think the server setup is the problem &lt;em&gt;per se&lt;/em&gt;.  By default, IQmol is setup to submit jobs to a server that is owned by Q-Chem and those jobs are time-limited at 5-10 min.  (The precise limit has varied over time.)  The &lt;code&gt;job failed to finish&lt;/code&gt; error reflects this limit.&lt;/p&gt;&#xA;&lt;p&gt;That said, I am a bit surprised that &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; frequencies failed to finish. Is it possible that you are either:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(a) using a large basis set, or&lt;/li&gt;&#xA;&lt;li&gt;(b) using a functional that lacks analytic 2nd derivatives, thus defaulting to finite-difference frequencies?  I tried this just now and was successfully able to compute frequencies for &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; at the B3LYP/6-31G level in a few seconds, well under the time limit.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In any case, the free IQmol server is intended primarily for demonstration purposes and for longer jobs you would need to purchase a Q-Chem license.  IQmol can then be configured to submit jobs to local hardware.&lt;/p&gt;&#xA;" OwnerUserId="3424" LastEditorUserId="5" LastEditDate="2021-04-21T02:47:52.707" LastActivityDate="2021-04-21T02:47:52.707" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4757" PostTypeId="1" CreationDate="2021-04-20T16:46:18.053" Score="19" ViewCount="5589" Body="&lt;p&gt;I want to make a python script that will load an xyz file. From the xyz parameters, I need to find the distance between atoms, angle and dihedral between atoms.&lt;/p&gt;&#xA;&lt;p&gt;The file xyz have this structure:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 60  Buckminsterfullerene  (C60 Bucky Ball)&#xA; 1  C      0.56182991    1.03720708   -3.34153745     2     2     6    16&#xA; 2  C     -0.02867841   -0.20922332   -3.53733326     2     1     3    15&#xA; 3  C      0.68868170   -1.41687735   -3.17419275     2     2     4     7&#xA; 4  C      1.96798784   -1.33001731   -2.62971513     2     3     5     8&#xA; 5  C      2.58298268   -0.03190141   -2.42580025     2     4     6    12&#xA; 6  C      1.89418484    1.12766893   -2.77448204     2     1     5    11&#xA; 7  C     -0.26911535   -2.36054907   -2.62920302     2     3     9    21&#xA; 8  C      2.34254586   -2.18322716   -1.51766993     2     4    10    19&#xA; 9  C      0.09052931   -3.17978756   -1.56143494     2     7    10    43&#xA;10  C      1.42288437   -3.08932569   -0.99437947     2     8     9    36&#xA;11  C      1.93147043    2.28439304   -1.89955106     2     6    14    20&#xA;12  C      3.33762840   -0.08283139   -1.18772874     2     5    13    19&#xA;13  C      3.37342937    1.02783673   -0.34763393     2    12    14    32&#xA;14  C      2.65606922    2.23549084   -0.71077448     2    11    13    26&#xA;15  C     -1.42982841   -0.40652370   -3.21677674     2     2    17    21&#xA;16  C     -0.22432522    2.13802273   -2.81706602     2     1    18    20&#xA;17  C     -2.18468203    0.65046195   -2.71318765     2    15    18    27&#xA;18  C     -1.56968716    1.94857800   -2.50927274     2    16    17    22&#xA;19  C      3.18903027   -1.41242386   -0.62647337     2     8    12    34&#xA;20  C      0.62215914    2.90882602   -1.92586946     2    11    16    23&#xA;21  C     -1.57842655   -1.73611615   -2.65552140     2     7    15    29&#xA;22  C     -2.12435266    2.52208091   -1.29751971     2    18    24    28&#xA;23  C      0.08957811    3.45949446   -0.76236333     2    20    24    25&#xA;24  C     -1.31157175    3.26219407   -0.44180686     2    22    23    37&#xA;25  C      0.84422386    3.40856444    0.47570821     2    23    26    42&#xA;26  C      2.10140370    2.80899380    0.50097868     2    14    25    31&#xA;27  C     -3.11943529    0.42168510   -1.62746090     2    17    28    30&#xA;28  C     -3.08214969    1.57840920   -0.75252997     2    22    27    39&#xA;29  C     -2.47596183   -1.95578408   -1.61302381     2    21    30    44&#xA;30  C     -3.26211692   -0.85496848   -1.08855240     2    27    29    40&#xA;31  C      2.47596171    1.95578403    1.61302382     2    26    32    46&#xA;32  C      3.26211681    0.85496841    1.08855240     2    13    31    33&#xA;33  C      3.11943527   -0.42168513    1.62746090     2    32    34    57&#xA;34  C      3.08214970   -1.57840928    0.75252996     2    19    33    35&#xA;35  C      2.12435273   -2.52208091    1.29751964     2    34    36    56&#xA;36  C      1.31157182   -3.26219401    0.44180679     2    10    35    47&#xA;37  C     -1.42288432    3.08932572    0.99437953     2    24    38    42&#xA;38  C     -2.34254574    2.18322716    1.51766996     2    37    39    52&#xA;39  C     -3.18903022    1.41242378    0.62647331     2    28    38    41&#xA;40  C     -3.37342947   -1.02783679    0.34763388     2    30    41    48&#xA;41  C     -3.33762837    0.08283136    1.18772868     2    39    40    49&#xA;42  C     -0.09052935    3.17978761    1.56143497     2    25    37    45&#xA;43  C     -0.84422391   -3.40856443   -0.47570819     2     9    44    47&#xA;44  C     -2.10140382   -2.80899386   -0.50097868     2    29    43    48&#xA;45  C      0.26911532    2.36054910    2.62920311     2    42    46    54&#xA;46  C      1.57842653    1.73611617    2.65552148     2    31    45    60&#xA;47  C     -0.08957818   -3.45949441    0.76236329     2    36    43    53&#xA;48  C     -2.65606930   -2.23549092    0.71077442     2    40    44    50&#xA;49  C     -2.58298263    0.03190137    2.42580019     2    41    51    52&#xA;50  C     -1.93147042   -2.28439306    1.89955101     2    48    51    53&#xA;51  C     -1.89418482   -1.12766893    2.77448197     2    49    50    58&#xA;52  C     -1.96798776    1.33001737    2.62971509     2    38    49    54&#xA;53  C     -0.62215921   -2.90882598    1.92586939     2    47    50    55&#xA;54  C     -0.68868164    1.41687744    3.17419279     2    45    52    59&#xA;55  C      0.22432525   -2.13802261    2.81706605     2    53    56    58&#xA;56  C      1.56968719   -1.94857793    2.50927279     2    35    55    57&#xA;57  C      2.18468202   -0.65046198    2.71318771     2    33    56    60&#xA;58  C     -0.56182981   -1.03720706    3.34153744     2    51    55    59&#xA;59  C      0.02867849    0.20922332    3.53733334     2    54    58    60&#xA;60  C      1.42982839    0.40652370    3.21677684     2    46    57    59&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does anyone know how to do this?&lt;/p&gt;&#xA;" OwnerUserId="3429" LastEditorUserId="5" LastEditDate="2023-04-11T01:22:00.340" LastActivityDate="2023-08-28T15:39:36.340" Title="Convert XYZ coordinates to Z-matrix" Tags="|python|crystallography|geometry|programming|software-online-tools|" AnswerCount="7" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4758" PostTypeId="2" ParentId="4757" CreationDate="2021-04-20T17:10:15.467" Score="17" Body="&lt;h2&gt;ASE&lt;/h2&gt;&#xA;&lt;p&gt;The ASE library has an &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;atom object&lt;/a&gt;  with built-in &lt;code&gt;get_angle&lt;/code&gt;, &lt;code&gt;get_dihedral&lt;/code&gt; and &lt;code&gt;get_distance&lt;/code&gt; methods that do just that.&lt;/p&gt;&#xA;&lt;p&gt;Here's an example script inspired by &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7114/1609&quot;&gt;rsdel's answer&lt;/a&gt; which uses ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;import io      &#xA;&#xA;xyz_file = &amp;quot;&amp;quot;&amp;quot;60&#xA;            Buckminsterfullerene  (C60 Bucky Ball)&#xA;            C      0.56182991    1.03720708   -3.34153745   &#xA;            C     -0.02867841   -0.20922332   -3.53733326   &#xA;            C      0.68868170   -1.41687735   -3.17419275   &#xA;            C      1.96798784   -1.33001731   -2.62971513   &#xA;            C      2.58298268   -0.03190141   -2.42580025   &#xA;            C      1.89418484    1.12766893   -2.77448204   &#xA;            C     -0.26911535   -2.36054907   -2.62920302   &#xA;            C      2.34254586   -2.18322716   -1.51766993   &#xA;            C      0.09052931   -3.17978756   -1.56143494   &#xA;            C      1.42288437   -3.08932569   -0.99437947   &#xA;            C      1.93147043    2.28439304   -1.89955106   &#xA;            C      3.33762840   -0.08283139   -1.18772874   &#xA;            C      3.37342937    1.02783673   -0.34763393   &#xA;            C      2.65606922    2.23549084   -0.71077448   &#xA;            C     -1.42982841   -0.40652370   -3.21677674   &#xA;            C     -0.22432522    2.13802273   -2.81706602   &#xA;            C     -2.18468203    0.65046195   -2.71318765   &#xA;            C     -1.56968716    1.94857800   -2.50927274   &#xA;            C      3.18903027   -1.41242386   -0.62647337   &#xA;            C      0.62215914    2.90882602   -1.92586946   &#xA;            C     -1.57842655   -1.73611615   -2.65552140   &#xA;            C     -2.12435266    2.52208091   -1.29751971   &#xA;            C      0.08957811    3.45949446   -0.76236333   &#xA;            C     -1.31157175    3.26219407   -0.44180686   &#xA;            C      0.84422386    3.40856444    0.47570821   &#xA;            C      2.10140370    2.80899380    0.50097868   &#xA;            C     -3.11943529    0.42168510   -1.62746090   &#xA;            C     -3.08214969    1.57840920   -0.75252997   &#xA;            C     -2.47596183   -1.95578408   -1.61302381   &#xA;            C     -3.26211692   -0.85496848   -1.08855240   &#xA;            C      2.47596171    1.95578403    1.61302382   &#xA;            C      3.26211681    0.85496841    1.08855240   &#xA;            C      3.11943527   -0.42168513    1.62746090   &#xA;            C      3.08214970   -1.57840928    0.75252996   &#xA;            C      2.12435273   -2.52208091    1.29751964   &#xA;            C      1.31157182   -3.26219401    0.44180679   &#xA;            C     -1.42288432    3.08932572    0.99437953   &#xA;            C     -2.34254574    2.18322716    1.51766996   &#xA;            C     -3.18903022    1.41242378    0.62647331   &#xA;            C     -3.37342947   -1.02783679    0.34763388   &#xA;            C     -3.33762837    0.08283136    1.18772868   &#xA;            C     -0.09052935    3.17978761    1.56143497   &#xA;            C     -0.84422391   -3.40856443   -0.47570819   &#xA;            C     -2.10140382   -2.80899386   -0.50097868   &#xA;            C      0.26911532    2.36054910    2.62920311   &#xA;            C      1.57842653    1.73611617    2.65552148   &#xA;            C     -0.08957818   -3.45949441    0.76236329   &#xA;            C     -2.65606930   -2.23549092    0.71077442   &#xA;            C     -2.58298263    0.03190137    2.42580019   &#xA;            C     -1.93147042   -2.28439306    1.89955101   &#xA;            C     -1.89418482   -1.12766893    2.77448197   &#xA;            C     -1.96798776    1.33001737    2.62971509   &#xA;            C     -0.62215921   -2.90882598    1.92586939   &#xA;            C     -0.68868164    1.41687744    3.17419279   &#xA;            C      0.22432525   -2.13802261    2.81706605   &#xA;            C      1.56968719   -1.94857793    2.50927279   &#xA;            C      2.18468202   -0.65046198    2.71318771   &#xA;            C     -0.56182981   -1.03720706    3.34153744   &#xA;            C      0.02867849    0.20922332    3.53733334   &#xA;            C      1.42982839    0.40652370    3.21677684  &#xA;            &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;#read xyz file&#xA;atom = ase.io.read(io.StringIO(xyz_file), format = 'xyz')&#xA;&#xA;# Take some example indices&#xA;i, j, k, l = 0, 1, 2, 3&#xA;&#xA;# Distances&#xA;# between two indices &#xA;atom.get_distance(i, j)&#xA;# between all atoms (distance matrix)&#xA;atom.get_all_distances()&#xA;&#xA;# Angles&#xA;atom.get_angle(i, j, k)&#xA;&#xA;# Dihedrals&#xA;atom.get_dihedral(i, j, k, l)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="1609" LastEditDate="2023-08-28T15:39:36.340" LastActivityDate="2023-08-28T15:39:36.340" CommentCount="4" CommunityOwnedDate="2023-04-19T00:26:10.100" ContentLicense="CC BY-SA 4.0" />
  <row Id="4759" PostTypeId="2" ParentId="4757" CreationDate="2021-04-20T18:10:20.323" Score="16" Body="&lt;h3&gt;Easiest free tool to do this (no download necessary):&lt;/h3&gt;&#xA;&lt;p&gt;What you are describing, is the conversion from XYZ format to ZMAT format. How to do this, has been asked &lt;a href=&quot;https://chemistry.stackexchange.com/q/135524/27342&quot;&gt;here&lt;/a&gt; on the Chemistry Stack Exchange, and &lt;a href=&quot;https://chemistry.stackexchange.com/a/135525/27342&quot;&gt;my answer&lt;/a&gt; was to use &lt;a href=&quot;https://www.webqc.org/molecularformatsconverter.php&quot; rel=&quot;noreferrer&quot;&gt;this free tool&lt;/a&gt; in which you just copy and paste the 3 spatial coordinates along with the name of the element, for each row of the XYZ file. I have done it for you and provided the ZMAT file at the bottom of this answer.&lt;/p&gt;&#xA;&lt;h3&gt;A python code to do this (requires downloading the code):&lt;/h3&gt;&#xA;&lt;p&gt;There's many such tools available for free online, including this &lt;a href=&quot;https://github.com/robashaw/geomConvert&quot; rel=&quot;noreferrer&quot;&gt;Python program&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;&lt;strong&gt;If for some reason you want to code this in Python yourself:&lt;/strong&gt;&lt;/h3&gt;&#xA;&lt;p&gt;If you don't want to use one of the above free tools, and don't even want to look at the how it was done in the free Python code I mentioned, then still the procedure is doable (though a bit tedious).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Distances:&lt;/strong&gt; Calculate the Euclidean distances between each pair of coordinates in your molecule. Your molecule is &lt;span class=&quot;math-container&quot;&gt;$\ce{C60}$&lt;/span&gt; so you have &lt;span class=&quot;math-container&quot;&gt;${{60}\choose{2}}= 1770$&lt;/span&gt; distances between atoms, which will be calculated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{ij} = \sqrt{(x_i-x_j)^2 + (y_i -y_j)^2 - (z_i - z_j)^2}\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for each of the 1770 pairs &lt;span class=&quot;math-container&quot;&gt;$(i,j)$&lt;/span&gt; in your XYZ file. Because of symmetry (i.e. you know in &lt;span class=&quot;math-container&quot;&gt;$\ce{C60}$&lt;/span&gt; that some bond lengths are expected to be exactly the same) the number of calculations that your Python program has to do, can be greatly reduced, but calculating 1770 distances will take so little time in Python that you don't need to worry about this if computation time is your concern.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Angles within planes:&lt;/strong&gt; For every three atoms, there's three angles, which you can obtain using the &lt;a href=&quot;https://www.mathsisfun.com/algebra/trig-cosine-law.html&quot; rel=&quot;noreferrer&quot;&gt;cosine law&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Dihedral angles:&lt;/strong&gt; For every four atoms, there's dihedral angles between the planes formed by each possible set of three atoms, and there's again &lt;a href=&quot;https://study.com/academy/lesson/dihedral-angle-definition-calculation.html&quot; rel=&quot;noreferrer&quot;&gt;a formula to obtain these angles&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Using geometry to reduce the number of necessary calculations:&lt;/strong&gt; For each subset of three atoms, you only need to calculate 2 bond lengths and 1 angle (for example), not all 3 bond lengths and all 3 angles. Similar rules exist for larger numbers of atoms, and that is why the ZMAT format for &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; atoms &lt;strong&gt;only requires &lt;span class=&quot;math-container&quot;&gt;$(n-1)$&lt;/span&gt; distances, &lt;span class=&quot;math-container&quot;&gt;$(n-2)$&lt;/span&gt; angles within planes, and &lt;span class=&quot;math-container&quot;&gt;$(n-3)$&lt;/span&gt; dihedral angles.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Conversion of your XYZ to ZMAT using the online tool I recommended:&lt;/h3&gt;&#xA;&lt;p&gt;This is the result I get from my recommended solution, which is once again &lt;a href=&quot;https://www.webqc.org/molecularformatsconverter.php&quot; rel=&quot;noreferrer&quot;&gt;this online tool&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    60&#xA;C   1&#xA;C   1 1.393&#xA;C   2 1.451  1 120.000&#xA;C   3 1.393  2 120.000  1   0.0&#xA;C   4 1.451  3 120.000  2 360.0&#xA;C   5 1.393  4 120.000  3 360.0&#xA;C   3 1.451  2 108.000  1 142.6&#xA;C   4 1.451  3 120.000  2 138.2&#xA;C   7 1.393  3 120.000  2 217.4&#xA;C   8 1.393  4 120.000  3 360.0&#xA;C   6 1.451  5 120.000  4 138.2&#xA;C   5 1.451  4 108.000  3 142.6&#xA;C  12 1.393  5 120.000  4 217.4&#xA;C  11 1.393  6 120.000  5 360.0&#xA;C   2 1.451  1 120.000  3 138.2&#xA;C   1 1.451  2 120.000  3 221.8&#xA;C  15 1.393  2 120.000  1 360.0&#xA;C  16 1.393  1 120.000  2 360.0&#xA;C   8 1.451  4 108.000  3 217.4&#xA;C  16 1.451  1 108.000  2 142.6&#xA;C   7 1.451  3 108.000  2   0.0&#xA;C  18 1.451 16 120.000  1 138.2&#xA;C  20 1.393 16 120.000  1 217.4&#xA;C  22 1.393 18 120.000 16 360.0&#xA;C  23 1.451 20 120.000 16 138.2&#xA;C  25 1.393 23 120.000 20 360.0&#xA;C  17 1.451 15 120.000  2 221.8&#xA;C  27 1.451 17 108.000 15 142.6&#xA;C  21 1.393  7 120.000  3 217.4&#xA;C  27 1.393 17 120.000 15 360.0&#xA;C  26 1.451 25 120.000 23 221.8&#xA;C  13 1.451 12 120.000  5 138.2&#xA;C  32 1.393 13 120.000 12 360.0&#xA;C  19 1.393  8 120.000  4 142.6&#xA;C  34 1.451 19 120.000  8   0.0&#xA;C  35 1.393 34 120.000 19 360.0&#xA;C  24 1.451 22 120.000 18 221.8&#xA;C  37 1.393 24 120.000 22   0.0&#xA;C  28 1.393 27 120.000 17 217.4&#xA;C  30 1.451 27 120.000 17 138.2&#xA;C  40 1.393 30 120.000 27 360.0&#xA;C  37 1.451 24 108.000 22 142.6&#xA;C   9 1.451  7 120.000  3 138.2&#xA;C  43 1.393  9 120.000  7   0.0&#xA;C  42 1.393 37 120.000 24 217.4&#xA;C  31 1.393 26 120.000 25 360.0&#xA;C  43 1.451  9 108.000  7 217.4&#xA;C  44 1.451 43 120.000  9 221.8&#xA;C  41 1.451 40 120.000 30 221.8&#xA;C  48 1.393 44 120.000 43 360.0&#xA;C  49 1.393 41 120.000 40   0.0&#xA;C  38 1.451 37 120.000 24 138.2&#xA;C  47 1.393 43 120.000  9 142.6&#xA;C  52 1.393 38 120.000 37   0.0&#xA;C  53 1.451 47 120.000 43 221.8&#xA;C  55 1.393 53 120.000 47 360.0&#xA;C  56 1.451 55 120.000 53 138.2&#xA;C  55 1.451 53 108.000 47 142.6&#xA;C  58 1.393 55 120.000 53 217.4&#xA;C  57 1.393 56 120.000 55   0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To get this, copy and paste the XYZ file (in the correct format!) and set the input file type to &amp;quot;&lt;code&gt;xyz&lt;/code&gt;&amp;quot; and output file type to &amp;quot;&lt;code&gt;fh -- Fenske Hall Z-Matrix format&lt;/code&gt;&amp;quot;. The tool seems to be a bit flaky for 60 atoms, but with some trial and error by removing lines and adding them back, I managed to get it to work.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-22T20:56:02.493" LastActivityDate="2021-04-22T20:56:02.493" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4760" PostTypeId="5" CreationDate="2021-04-20T18:11:40.793" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-20T18:11:40.793" LastActivityDate="2021-04-20T18:11:40.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4761" PostTypeId="4" CreationDate="2021-04-20T18:11:40.793" Score="0" Body="Questions about programming." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-20T18:11:40.793" LastActivityDate="2021-04-20T18:11:40.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4762" PostTypeId="5" CreationDate="2021-04-20T19:58:11.340" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T19:58:11.340" LastActivityDate="2021-04-20T19:58:11.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4763" PostTypeId="4" CreationDate="2021-04-20T19:58:11.340" Score="0" Body="For questions about constructing or interpreting density of states (DOS) plots" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T19:58:11.340" LastActivityDate="2021-04-20T19:58:11.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4764" PostTypeId="5" CreationDate="2021-04-20T20:11:31.253" Score="0" Body="&lt;p&gt;Atomic orbitals (AOs) are a commonly used basis to represent the electronic state of molecule or solid. There are a variety of common mathematical forms for these orbitals, most notably Gaussian and Slater orbitals. In solving SCF equations, one produces a set of Molecular orbitals (MOs). These MOs often play a role in forming a basis for Post-HF electronic structure methods.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T20:11:31.253" LastActivityDate="2021-04-20T20:11:31.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4765" PostTypeId="4" CreationDate="2021-04-20T20:11:31.253" Score="0" Body="For questions about properties and types of orbitals" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T20:11:31.253" LastActivityDate="2021-04-20T20:11:31.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4766" PostTypeId="5" CreationDate="2021-04-20T20:15:10.073" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T20:15:10.073" LastActivityDate="2021-04-20T20:15:10.073" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4767" PostTypeId="4" CreationDate="2021-04-20T20:15:10.073" Score="0" Body="For questions about electronic structures methods that use excitations from multiple references to model correlation. These are often prefixed with MR (e.g. MR-CC, MR-CI, MR-PT)" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-20T20:15:10.073" LastActivityDate="2021-04-20T20:15:10.073" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4768" PostTypeId="1" AcceptedAnswerId="4769" CreationDate="2021-04-17T10:36:10.623" Score="7" ViewCount="537" Body="&lt;p&gt;I am running frequency computation with &lt;code&gt;geom=connectivity&lt;/code&gt; in Gaussian. It all converges now but at the very end of the last convergence it says:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Test job not archived.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have been googling around and I can't find the explanation of what that is supposed to mean.&#xA;Can someone share some light in this?&lt;/p&gt;&#xA;" OwnerUserId="3416" OwnerDisplayName="Bpi" LastEditorUserId="5" LastEditDate="2021-04-25T03:07:09.557" LastActivityDate="2021-04-25T03:07:09.557" Title="What does &quot;Test job not archived&quot; mean?" Tags="|computational-chemistry|gaussian|from-chem-se|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4769" PostTypeId="2" ParentId="4768" CreationDate="2021-04-17T13:19:09.323" Score="10" Body="&lt;p&gt;You are probably running a combined optimisation and frequency job in Gaussian. (I discourage that, but that's a different issue.)&lt;/p&gt;&#xA;&lt;p&gt;The line means that the calculation preceding it has been run as a test calculation, see &lt;a href=&quot;https://gaussian.com/test&quot; rel=&quot;noreferrer&quot;&gt;https://gaussian.com/test&lt;/a&gt;. An archive entry has not been created. The reasons may be multiple and depend on the actual input file. That's probably the optimisation part. (I'm guessing here, because I do not know your input file.)&lt;/p&gt;&#xA;&lt;p&gt;Usually archive entries are only produced for single point calculations. For optimisations there is probably a final iteration, which will have an archive entry at the end of the output.&lt;/p&gt;&#xA;&lt;p&gt;An ordinary frequency calculation should trigger an archive entry at the end of the output of the job.&lt;/p&gt;&#xA;" OwnerUserId="49" OwnerDisplayName="Martin - マーチン" LastActivityDate="2021-04-17T13:19:09.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4770" PostTypeId="5" CreationDate="2021-04-20T20:49:12.047" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-20T20:49:12.047" LastActivityDate="2021-04-20T20:49:12.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4771" PostTypeId="4" CreationDate="2021-04-20T20:49:12.047" Score="0" Body="Questions about software in the form of online tools or web apps: Basically software that can be run in a web browser without downloading anything." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-20T20:49:12.047" LastActivityDate="2021-04-20T20:49:12.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4772" PostTypeId="2" ParentId="4735" CreationDate="2021-04-20T21:36:44.123" Score="4" Body="&lt;p&gt;The values that you quoted for the densities in the liquid and solid phases, were most likely obtained from experiments, in the following very simple way:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(1) take exactly 1 liter of the substance&lt;/li&gt;&#xA;&lt;li&gt;(2) measure it's mass in grams&lt;/li&gt;&#xA;&lt;li&gt;(3) the density in units of g/L is simply the result of the measurement in step (2)&lt;/li&gt;&#xA;&lt;li&gt;(4) divide the result in step (3) by 1000 to get the density in units of g/mL.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You mentioned the molar mass of the substance as being 84.16 g/mol, which is the mass if you have exactly 6.02214076 × 10&lt;sup&gt;23&lt;/sup&gt; copies of the molecule.&lt;/p&gt;&#xA;&lt;p&gt;It's not very easy to &amp;quot;calculate&amp;quot; the density of a substance knowing only the chemical formula and the molar mass, because you would have to know &lt;strong&gt;how much space a certain amount of the substance occupies.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The best way to find out how much space a certain amount of a substance takes up, would probably be to do a molecular dynamics simulation. Here you would start with  thousands (for example) of copies of the molecule, in some initial configuration, which you can get using the software &lt;a href=&quot;https://m3g.iqm.unicamp.br/packmol/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PACKMOL&lt;/a&gt;. Then you would set the temperature and pressure (perhaps to 25°C and 100 kPa in this case, according to the quote in your question, but I suspect you might actually have to find out where those density values were obtained and choose the values of temperature and pressure based on what they were when those numbers were measured, since it's unlikely that the substance is both liquid and solid at the same temperature+pressure).&lt;/p&gt;&#xA;&lt;p&gt;Then you would use a software such as LAMMPS or GROMACS (just to name a couple examples) with some choice of forcefield, to see the effect of Newton's 2nd law on the system in that forcefield (i.e. &lt;strong&gt;how the molecules will push and pull each other until they get comfortable with the amount of personal space they have&lt;/strong&gt;). Eventually when the system reaches equilibrium, you will have some idea about how much space that number of molecules of your substance takes up at that temperature and pressure. Then you can do the same simulation with more and more molecules in your simulation, until you converge on a value for the number of molecules/volume. This final number of molecules/volume will be quite accurate &lt;strong&gt;under two main assumptions&lt;/strong&gt;: the forces between the molecules are given by the forcefield that you chose, and the dynamics of the system follows Newton's second law rather than the time-dependent Schroedinger equation or something more accurate but more complicated that you would get from a more advanced quantum field theory).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Once you have the number of molecules/volume, you can finally use that molar mass of 84.16 g/mol that you correctly looked up, and get the mass/volume!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You will probably have to do this procedure twice: once for the temperature+pressure for the liquid phase and once for the temperature+pressure for the solid phase.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;It would be very nice if there was a theory that could allow you to estimate the volume of a substance based on the chemical formula, so that you wouldn't have to run this type of &amp;quot;brute force simulation&amp;quot; known as &amp;quot;molecular dynamics&amp;quot; to get an estimate of the volume of a substance.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-20T21:36:44.123" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4773" PostTypeId="1" CreationDate="2021-04-21T00:08:19.813" Score="8" ViewCount="5602" Body="&lt;p&gt;There isn't that many tutorials on Atomic Simulation Environment on the net and among those I saw, the atoms object is always built explicitly within Python.&lt;/p&gt;&#xA;&lt;p&gt;What if I have a data file containing the coordinate positions of each element in a particular material: Let's say either a CIF or an XYZ or LAMMPS data file of a 4 x 4 cell of molybdenum disulfide.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do I read this into the atoms object in ASE?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="5" LastEditDate="2021-04-21T00:42:57.220" LastActivityDate="2021-04-21T15:24:07.807" Title="Read a data file into the atoms object in ASE" Tags="|atomic-simulation-environment|software-usage|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4774" PostTypeId="5" CreationDate="2021-04-21T00:43:46.837" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-21T00:43:46.837" LastActivityDate="2021-04-21T00:43:46.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4775" PostTypeId="4" CreationDate="2021-04-21T00:43:46.837" Score="0" Body="Questions about how to use a matter modeling software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-21T00:43:46.837" LastActivityDate="2021-04-21T00:43:46.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4776" PostTypeId="2" ParentId="4734" CreationDate="2021-04-21T02:14:07.013" Score="2" Body="&lt;p&gt;Go here, no need to install, use on the web &lt;a href=&quot;http://www.cheminfo.org/Chemistry/Cheminformatics/FormatConverter/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.cheminfo.org/Chemistry/Cheminformatics/FormatConverter/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3433" LastActivityDate="2021-04-21T02:14:07.013" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4777" PostTypeId="1" AcceptedAnswerId="4780" CreationDate="2021-04-21T08:35:35.017" Score="8" ViewCount="401" Body="&lt;p&gt;I am trying to plot &lt;code&gt;SPIN DENSITY&lt;/code&gt; isosurfaces using VESTA. I have used &lt;code&gt;vaspkit&lt;/code&gt; option &lt;strong&gt;312&lt;/strong&gt; to create &lt;code&gt;SPIN.vasp&lt;/code&gt; file which contains spin density from the &lt;code&gt;CHGCAR&lt;/code&gt;. Now, when I import data to VESTA it shows the window below to convert or not convert data.&lt;/p&gt;&#xA;&lt;p&gt;My question is : &lt;em&gt;What is the unit of data in CHGCAR ? and which option should I pick to plot isosurfaces in &lt;strong&gt;e/Ang³&lt;/strong&gt; unit.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bMH2T.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bMH2T.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-04-30T18:35:26.633" LastActivityDate="2021-04-30T18:35:26.633" Title="When import volumetric data (spin density of CHGCAR) to VESTA which option should we pick here?" Tags="|density-functional-theory|vasp|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4778" PostTypeId="1" AcceptedAnswerId="4795" CreationDate="2021-04-21T10:05:42.440" Score="4" ViewCount="151" Body="&lt;p&gt;How can I perform a score-in-place procedure with autodock to validate ma glide docking? It is a new software for me and I don't Know how to use it and how to proceed. Thanks in advance for help.&lt;/p&gt;&#xA;" OwnerUserId="626" LastEditorUserId="5" LastEditDate="2021-04-21T19:29:40.703" LastActivityDate="2021-04-23T13:01:48.100" Title="Procedure to validate glide docking without a reference ligand on Autodock vina" Tags="|docking|autodock|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4779" PostTypeId="2" ParentId="4753" CreationDate="2021-04-21T11:28:17.387" Score="5" Body="&lt;p&gt;I will share here the script I use to plot bands/DOS/PDOS from SIESTA output.&lt;/p&gt;&#xA;&lt;p&gt;After working with thee raw output from SIESTA, if a spin polarized calculation was done, we have two files (one for each spin) for the bands in the form:&lt;br /&gt;&#xA;(the file consist in three columns with &lt;em&gt;k energy spin&lt;/em&gt;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# GNUBANDS: Utility for SIESTA to transform bands output into Gnuplot format&#xA;#&#xA;#                                                  Emilio Artacho, Feb. 1999&#xA;#                                                   Alberto Garcia, May 2012&#xA;#                                         Nick Papior, April 2013, July 2016&#xA;# --------------------------------------------------------------------------&#xA;# Only bands for spin 2&#xA;# E_F               =    -2.9812&#xA;# k_min, k_max      =     0.0000    0.1300&#xA;# E_min, E_max      =    -6.1000   -0.1000&#xA;# Nbands, Nspin, Nk =   1575     2   201&#xA;# Using min_band, max_band =      1  1575&#xA;# Total number of bands =   1575&#xA;#&#xA;#        k            E[eV]&#xA;# --------------------------------------------------------------------------&#xA;&#xA;      0.094253     -6.098700  2&#xA;      0.094903     -6.097100  2&#xA;      0.095553     -6.095400  2&#xA;      0.096203     -6.093800  2&#xA;      0.096853     -6.092200  2 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the DOS/PDOS:&lt;br /&gt;&#xA;(the file consist in three column with &lt;em&gt;energy DOS_spin_up DOS_spin_down&lt;/em&gt;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#&#xA;#    Energy          spin 1        spin2&#xA;#&#xA;   -6.9999925    12.14227672    12.02303660&#xA;   -6.9919845    11.73120115    11.76512099&#xA;   -6.9839765    11.48849750    11.61787403&#xA;   -6.9759685    11.43686413    11.57040674&#xA;   -6.9679605    11.56064946    11.60338643&#xA;   -6.9599525    11.81124343    11.69537446 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The script I used is (output to PDF):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;##########################################################&#xA;#                                                        #&#xA;#  Input data para fazer os gráficos, escalas de forma   #&#xA;#  automatica                                            #&#xA;#                                                        #&#xA;##########################################################&#xA;&#xA;# Dados nomes dos arquivos&#xA;BANDS_PRISTINE_down = &amp;quot;BN-puro-b-down.dat&amp;quot;&#xA;BANDS_PRISTINE_up = &amp;quot;BN-puro-b-up.dat&amp;quot;&#xA;BANDS_METAL_down = &amp;quot;BN-Ni-p5-b-down.dat&amp;quot;&#xA;BANDS_METAL_up = &amp;quot;BN-Ni-p5-b-up.dat&amp;quot;&#xA;DOS_TOTAL = &amp;quot;BN-Ni-p5-d-DOS.dat&amp;quot;&#xA;&#xA;# Dados escalas graficos&#xA;ENERGY_min = -6.1096&#xA;ENERGY_max = -0.1096&#xA;K_min = 0.0&#xA;K_max = 0.13&#xA;FERMI_PRISTINE = -4.257&#xA;FERMI_METAL = -2.9812&#xA;DOS_min = -48 &#xA;DOS_max = 44&#xA;PDOSNANO_min = -1.2 &#xA;PDOSNANO_max = 1.0&#xA;PDOSMETAL_min = -12 &#xA;PDOSMETAL_max = 14&#xA;&#xA;&#xA;set terminal pdf font &amp;quot;Helvetica,9&amp;quot; enhanced color&#xA;set output &amp;quot;BANDS-DOS-PDOS-BN-Ni-p5.pdf&amp;quot;&#xA;load 'multiplot.gp'&#xA;&#xA;eval(init_margins(0.045, 0.98, 0.05, 0.94, 0.035, 0.08, 1, 5))&#xA;#                 left,  right, bottom, top, dx, dy, rows, cols&#xA;set multiplot&#xA;&#xA;&#xA;# Para definir os tipos de dash&#xA;set termoption dash&#xA;set for [i=1:5] linetype i dt i&#xA;show style line&#xA;set key off # texto associado a data no grafico&#xA;set key below&#xA;&#xA;&#xA;&#xA;# Grafico 1&#xA;# Bandas BN puro&#xA;eval(set_margins(1,1))&#xA;set title &amp;quot;(a) BN pristine&amp;quot; offset 0.0, -0.5&#xA;set ylabel 'Energy (eV)' offset 1.0, 0.0&#xA;set mytics 2&#xA;set xtics (&amp;quot;{/Symbol G}&amp;quot;  K_min, &amp;quot;Z&amp;quot;  K_max) offset 0.0, 0.5&#xA;set arrow 1 from K_min,FERMI_PRISTINE to K_max,FERMI_PRISTINE nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5&#xA;&#xA;# Legenda bandas&#xA;# Down&#xA;set arrow 5 from 0,-6.5 to 0.035,-6.5 nohead lt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5&#xA;set arrow 55 from 0.045,-6.4 to 0.045,-6.6 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Down&#xA;# Legenda bandas&#xA;# Up&#xA;set arrow 6 from 0.065,-6.5 to 0.1,-6.5 nohead lt 2 lc rgb &amp;quot;red&amp;quot; lw 1.5&#xA;set arrow 66 from 0.11,-6.6 to 0.11,-6.4 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Up&#xA;&#xA;# Legenda Fermi&#xA;set arrow 7 from 0.135,-6.5 to 0.170,-6.5 nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5&#xA;set label 1 &amp;quot;E_F&amp;quot; at 0.175,-6.5&#xA;set yrange [ENERGY_min:ENERGY_max]&#xA;plot BANDS_PRISTINE_down with lines lt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 title &amp;quot;&amp;quot;, \&#xA;     BANDS_PRISTINE_up with lines lt 2 lc rgb &amp;quot;red&amp;quot; lw 1.5 title &amp;quot;&amp;quot;&#xA;unset arrow 3&#xA;unset arrow 5&#xA;unset arrow 55&#xA;unset arrow 6&#xA;unset arrow 66&#xA;unset arrow 7&#xA;unset label 1&#xA;&#xA;# Grafico 2&#xA;# Bandas BN-Ni-p5&#xA;eval(set_margins(2,1))&#xA;unset ylabel&#xA;set title &amp;quot;(b) BN+Ni(p5)&amp;quot;&#xA;set ytics&#xA;set ytics format &amp;quot; &amp;quot; # Remove os labels, deixando somente os ticks&#xA;set xtics (&amp;quot;{/Symbol G}&amp;quot;  K_min, &amp;quot;Z&amp;quot;  K_max) offset 0.0, 0.5&#xA;set arrow 1 from K_min,FERMI_METAL to K_max,FERMI_METAL nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5 # FERMI&#xA;set yrange [ENERGY_min:ENERGY_max]&#xA;plot BANDS_METAL_down with lines lt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 title &amp;quot;&amp;quot;, \&#xA;     BANDS_METAL_up with lines lt 2 lc rgb &amp;quot;red&amp;quot; lw 1.5 title &amp;quot;&amp;quot;&#xA;unset arrow 3&#xA;&#xA;&#xA;# Grafico 3&#xA;# DOS total&#xA;eval(set_margins(3,1))&#xA;unset ylabel&#xA;set title &amp;quot;(c) TDOS&amp;quot;&#xA;unset ytics&#xA;unset xtics&#xA;set ytics format &amp;quot; &amp;quot; &#xA;set xtics (gprintf(&amp;quot;%1.1f&amp;quot;,DOS_min)  DOS_min, gprintf(&amp;quot;%1.1f&amp;quot;,DOS_max)  DOS_max) offset 0.0, 0.5&#xA;set arrow 1 from DOS_min,FERMI_METAL to DOS_max,FERMI_METAL nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5&#xA;set arrow 2 from 0,ENERGY_min to 0,ENERGY_max nohead dt 1 lc rgb &amp;quot;gray&amp;quot; lw 1.5&#xA;a_xmin = DOS_min - 0.17 * DOS_min&#xA;a_xmax = DOS_max - 0.17 * DOS_max&#xA;set arrow 3 from a_xmin,-5.8 to a_xmin,-6.0 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Down&#xA;set arrow 4 from a_xmax,-6.0 to a_xmax,-5.8 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Up&#xA;set yrange [ENERGY_min:ENERGY_max]&#xA;set xrange [DOS_min:DOS_max]&#xA;plot DOS_TOTAL using (-$3):1 with lines lt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 title &amp;quot;&amp;quot;, \&#xA;      DOS_TOTAL using 2:1 with lines lt 1 lc rgb &amp;quot;red&amp;quot; lw 1.5 title &amp;quot;&amp;quot;&#xA;unset arrow 3&#xA;unset arrow 4&#xA;&#xA;&#xA;# Grafico 4&#xA;# PDOS atomos do BN que interagem&#xA;eval(set_margins(4,1))&#xA;unset ylabel&#xA;set title &amp;quot;(d) PDOS nanotube&amp;quot;&#xA;unset ytics&#xA;set ytics format &amp;quot; &amp;quot; &#xA;set xtics (gprintf(&amp;quot;%1.1f&amp;quot;,PDOSNANO_min)  PDOSNANO_min, gprintf(&amp;quot;%1.1f&amp;quot;,PDOSNANO_max)  PDOSNANO_max) offset 0.0, 0.5&#xA;set arrow 1 from PDOSNANO_min,FERMI_METAL to PDOSNANO_max,FERMI_METAL nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5&#xA;set arrow 2 from 0,-6.1 to 0,-0.1 nohead dt 1 lc rgb &amp;quot;gray&amp;quot; lw 1.5&#xA;a_xmin = PDOSNANO_min - 0.17 * PDOSNANO_min&#xA;a_xmax = PDOSNANO_max - 0.17 * PDOSNANO_max&#xA;set arrow 3 from a_xmin,-5.8 to a_xmin,-6.0 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Down&#xA;set arrow 4 from a_xmax,-6.0 to a_xmax,-5.8 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Up&#xA;set yrange [ENERGY_min:ENERGY_max]&#xA;set xrange [PDOSNANO_min:PDOSNANO_max]&#xA;plot &amp;quot;BN-Ni-p5-d-B95.dat&amp;quot; using (-&lt;span class=&quot;math-container&quot;&gt;$3):1 with lines lt 1 lc rgb &quot;brown&quot; lw 1.5 title &quot;B_{95}+B_{102}&quot;, \&#xA;     &quot;BN-Ni-p5-d-B95.dat&quot; using 2:1 with lines lt 1 lc rgb &quot;brown&quot; lw 1.5 title &quot;&quot;, \&#xA;     &quot;BN-Ni-p5-d-B102.dat&quot; using (-$&lt;/span&gt;3):1 with lines lt 1 lc rgb &amp;quot;brown&amp;quot; lw 1.5 title &amp;quot;&amp;quot;, \&#xA;     &amp;quot;BN-Ni-p5-d-B102.dat&amp;quot; using 2:1 with lines lt 1 lc rgb &amp;quot;brown&amp;quot; lw 1.5 title &amp;quot;&amp;quot;, \&#xA;     &amp;quot;BN-Ni-p5-d-N86.dat&amp;quot; using (-$3):1 with lines lt 1 lc rgb &amp;quot;dark-yellow&amp;quot; lw 1.5 title &amp;quot;N_{86}&amp;quot;, \&#xA;     &amp;quot;BN-Ni-p5-d-N86.dat&amp;quot; using 2:1 with lines lt 1 lc rgb &amp;quot;dark-yellow&amp;quot; lw 1.5 title &amp;quot;&amp;quot;&#xA;unset arrow 3&#xA;unset arrow 4&#xA;&#xA;&#xA;# Grafico 5&#xA;# PDOS Metal&#xA;eval(set_margins(5,1))&#xA;unset ylabel&#xA;set title &amp;quot;(e) PDOS metal&amp;quot;&#xA;set ytics&#xA;set ytics format &amp;quot; &amp;quot; &#xA;set xtics (gprintf(&amp;quot;%1.1f&amp;quot;,PDOSMETAL_min)  PDOSMETAL_min, gprintf(&amp;quot;%1.1f&amp;quot;,PDOSMETAL_max)  PDOSMETAL_max) offset 0.0, 0.5&#xA;set arrow 1 from PDOSMETAL_min,FERMI_METAL to PDOSMETAL_max,FERMI_METAL nohead dt 2 lc rgb &amp;quot;green&amp;quot; lw 1.5&#xA;set arrow 2 from 0,-6.1 to 0,-0.1 nohead dt 1 lc rgb &amp;quot;gray&amp;quot; lw 1.5&#xA;a_xmin = PDOSMETAL_min - 0.17 * PDOSMETAL_min&#xA;a_xmax = PDOSMETAL_max - 0.17 * PDOSMETAL_max&#xA;set arrow 3 from a_xmin,-5.8 to a_xmin,-6.0 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Down&#xA;set arrow 4 from a_xmax,-6.0 to a_xmax,-5.8 head nofilled size screen 0.03,15 dt 1 lc rgb &amp;quot;black&amp;quot; lw 1.5 # Up&#xA;set yrange [ENERGY_min:ENERGY_max]&#xA;set xrange [PDOSMETAL_min:PDOSMETAL_max]&#xA;plot &amp;quot;BN-Ni-p5-d-Ni-3d.dat&amp;quot; using (-&lt;span class=&quot;math-container&quot;&gt;$3):1 with lines lt 1 lc rgb '#440154' lw 1.5 title &quot;3d Ni&quot;, \&#xA;     &quot;BN-Ni-p5-d-Ni-3d.dat&quot; using 2:1 with lines lt 1 lc rgb '#440154' lw 1.5 title &quot;&quot;, \&#xA;     &quot;BN-Ni-p5-d-Ni-4s.dat&quot; using (-$&lt;/span&gt;3):1 with lines lt 1 lc rgb '#f89441' lw 1.5 title &amp;quot;4s Ni&amp;quot;, \&#xA;     &amp;quot;BN-Ni-p5-d-Ni-4s.dat&amp;quot; using 2:1 with lines lt 1 lc rgb &amp;quot;orange&amp;quot; lw 1.5 title &amp;quot;&amp;quot;&#xA;&#xA;# '#440154' ==&amp;gt; dark purple&#xA;# '#f89441' ==&amp;gt; dark orange&#xA;&#xA;unset multiplot&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the multiplot script:&lt;br /&gt;&#xA;(used to have more than one graph)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;init_margins(left, right, bottom, top, dx, dy, rows, cols) = \&#xA;  sprintf('left_margin = %f; right_margin = %f; top_margin = %f; bottom_margin = %f; ', left, right, top, bottom) . \&#xA;  sprintf('col_count = %d; row_count = %d; gap_size_x = %f; gap_size_y = %f', cols, rows, dx, dy)&#xA;&#xA;get_lmargin(col) = (left_margin + (col - 1) * (gap_size_x + ((right_margin - left_margin)-(col_count - 1) * gap_size_x)/col_count))&#xA;get_rmargin(col) = (left_margin + (col - 1) * gap_size_x + col * ((right_margin - left_margin)-(col_count - 1) * gap_size_x)/col_count)&#xA;get_tmargin(row) = (top_margin  - (row - 1) * gap_size_y - (row-1) * ((top_margin - bottom_margin  - gap_size_y * row_count) / row_count))&#xA;get_bmargin(row) = (top_margin  - (row - 1) * gap_size_y -  row    * ((top_margin - bottom_margin  - gap_size_y * row_count) / row_count))&#xA;set_margins(col, row) = \&#xA;  sprintf('set lmargin at screen %f;', get_lmargin(col)) . \&#xA;  sprintf('set rmargin at screen %f;', get_rmargin(col)) . \&#xA;  sprintf('set tmargin at screen %f;', get_tmargin(row)) . \&#xA;  sprintf('set bmargin at screen %f;', get_bmargin(row))          &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My final figure:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/sf1M9.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sf1M9.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-21T11:28:17.387" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4780" PostTypeId="2" ParentId="4777" CreationDate="2021-04-21T13:11:11.887" Score="5" Body="&lt;p&gt;This is a bit of a boring answer, but chances are you normally want to replace the current data and do nothing.  The operation can be used to add or subtract densities to visualize charge differences, but if you just want to plot a spin density you can likely just use replace.&lt;/p&gt;&#xA;&lt;p&gt;You also probably do not need to convert the units since most VASP-like tools tend to use angstroms and I am assuming vaspkit does not decide to do a unit conversion away from angstrom.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-04-21T13:11:11.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4781" PostTypeId="2" ParentId="4773" CreationDate="2021-04-21T15:24:07.807" Score="12" Body="&lt;p&gt;Reading coordinates from a file is a very simple task with ASE. The following code reads the three different file types into an &lt;code&gt;Atoms&lt;/code&gt; object:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;lammps = io.read('mos2.pos',format='lammps-data')&#xA;cif = io.read('mos2.cif')&#xA;xyz = io.read('mos2.xyz') &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;ASE can detect certain file formats from the ending, like in the case of .cif and .xyz. For the lammps file the format needs to be set explicitly.&lt;/p&gt;&#xA;&lt;p&gt;The formats that ASE natively supports are documented here:&#xA;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/io.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/io/io.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And some format specific options are listed here:&#xA;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the file contains multiple sets of coordinates &lt;code&gt;index&lt;/code&gt; can be used to select a certain one or a selection.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;xyz_last = io.read('mos2.xyz',index='-1') &#xA;xyz_all = io.read('mos2.xyz',index=':') &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="295" LastActivityDate="2021-04-21T15:24:07.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4782" PostTypeId="5" CreationDate="2021-04-21T19:30:13.800" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/AutoDock&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/AutoDock&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-21T19:30:13.800" LastActivityDate="2021-04-21T19:30:13.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4783" PostTypeId="4" CreationDate="2021-04-21T19:30:13.800" Score="0" Body="Questions about the software AutoDock." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-21T19:30:13.800" LastActivityDate="2021-04-21T19:30:13.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4784" PostTypeId="1" AcceptedAnswerId="4804" CreationDate="2021-04-21T21:25:49.237" Score="6" ViewCount="124" Body="&lt;p&gt;As I understand it, a given CALPHAD database is essentially just a set of equations that model the Gibbs free energy of each phase within a given alloy system (set of elements). Typically, the main way ThermoCalc, or any other CALPHAD implementation, works is that the user inputs the thermodynamic conditions (e.g. elements and their fractions and temperature), ThermoCalc then numerically solves for the convex hull defined by the database equations mentioned above, and then returns the equilibrium phases and phase fractions.&lt;/p&gt;&#xA;&lt;p&gt;This usually works well. However, sometimes you may only be interested in materials with a certain phase, or combination of phases (e.g. only BCC and FCC in equilibrium, or a single phase region of only HCP, etc.). In this case the method described above is very annoying because you essentially have to guess and check different compositions until you find one with the desired phases. This can be very slow, so I want to know if there is a way to use CALPHAD in the reverse way.&lt;/p&gt;&#xA;&lt;p&gt;Specifically, my question is: if you had access to the database equations for a given alloy system, could you analytically solve (and thus solve quickly) for the conditions (i.e. temperatures and compositions) that would produce the phase combination that you desire? Bonus points if you can point me to a paper where this was demonstrated!&lt;/p&gt;&#xA;&lt;p&gt;I am aware that getting access to these equations is not feasible for most databases because the equations are essentially the intellectual property, and database creators would be stupid to give that out to users. However, I just want to know if this is theoretically possible, because I am developing algorithms to approximate a phase region of interest using the guess and check method, but I want to know if my algos are actually necessary.&lt;/p&gt;&#xA;" OwnerUserId="1410" LastActivityDate="2021-04-24T00:06:54.827" Title="Is it possible to analytically solve for a particular phase region of a CALPHAD database? (instead of guessing and checking)" Tags="|thermodynamics|gibbs-free-energy|calphad|thermo-calc|phase-diagram|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4785" PostTypeId="1" CreationDate="2021-04-22T03:56:07.437" Score="7" ViewCount="246" Body="&lt;p&gt;I have been playing with a polymer called glyme, and I have run Tinker analyze on it to get OPLS-AA parameters for it. I have attached the output parameter file to this post.&lt;/p&gt;&#xA;&lt;p&gt;My question is, how do I go from the parameters given in the Tinker parameter file (ff.out) under &amp;quot;Improper Torsion Parameters&amp;quot; and &amp;quot;Torsional Angle Parameters&amp;quot; and translate those into a GROMACS topology file (UNL_4E9C7F.itp)? Both of these files are for benzene. Getting the bond and angle constants was a simple unit change but how does it work for the IMPROPER DIHEDRAL ANGLES?&lt;/p&gt;&#xA;&lt;p&gt;The Improper Torsion Parameters according to the Tinker file are:&lt;/p&gt;&#xA;&lt;p&gt;Amplitude = 1.667, Phase = 180.0, Periodicity = 2&lt;/p&gt;&#xA;&lt;p&gt;Under IMPROPER DIHEDRAL ANGLES, I see that:&lt;/p&gt;&#xA;&lt;p&gt;Phase = 180.0, Phase = 180.0, Periodicity = 2&lt;/p&gt;&#xA;&lt;p&gt;However, how do I make the change?&#xA;Similarly, for IMPROPER DIHEDRAL ANGLES, is there a way to convert the Torsional Angle Parameters?&#xA;I would appreciate any advice you have for me!&lt;/p&gt;&#xA;&lt;p&gt;this is the tinker file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;     ######################################################################&#xA;   ##########################################################################&#xA;  ###                                                                      ###&#xA; ###            Tinker  ---  Software Tools for Molecular Design            ###&#xA; ##                                                                          ##&#xA; ##                       Version 8.8.3  November 2020                       ##&#xA; ##                                                                          ##&#xA; ##               Copyright (c)  Jay William Ponder  1990-2020               ##&#xA; ###                           All Rights Reserved                          ###&#xA;  ###                                                                      ###&#xA;   ##########################################################################&#xA;     ######################################################################&#xA;&#xA;&#xA; Interactions and Sites :&#xA;&#xA; Atomic Sites                                  12&#xA; Bond Stretches                                12&#xA; Angle Bends                                   18&#xA; Improper Torsions                             18&#xA; Torsional Angles                              24&#xA; Van der Waals Sites                           12&#xA; Atomic Partial Charges                        12&#xA;&#xA; Atom Definition Parameters :&#xA;&#xA;   Atom  Symbol  Type  Class  Atomic   Mass  Valence  Description&#xA;&#xA;     1     C       90     48     6    12.011    3     Aromatic C              &#xA;     2     C       90     48     6    12.011    3     Aromatic C              &#xA;     3     C       90     48     6    12.011    3     Aromatic C              &#xA;     4     C       90     48     6    12.011    3     Aromatic C              &#xA;     5     C       90     48     6    12.011    3     Aromatic C              &#xA;     6     C       90     48     6    12.011    3     Aromatic C              &#xA;     7     H       91     49     1     1.008    1     Aromatic H-C            &#xA;     8     H       91     49     1     1.008    1     Aromatic H-C            &#xA;     9     H       91     49     1     1.008    1     Aromatic H-C            &#xA;    10     H       91     49     1     1.008    1     Aromatic H-C            &#xA;    11     H       91     49     1     1.008    1     Aromatic H-C            &#xA;    12     H       91     49     1     1.008    1     Aromatic H-C            &#xA;&#xA; Bond Stretching Parameters :&#xA;&#xA;          Atom Numbers                         KS       Bond&#xA;&#xA;     1        1     2                      469.000    1.4000&#xA;     2        1     6                      469.000    1.4000&#xA;     3        1     7                      367.000    1.0800&#xA;     4        2     3                      469.000    1.4000&#xA;     5        2     8                      367.000    1.0800&#xA;     6        3     4                      469.000    1.4000&#xA;     7        3     9                      367.000    1.0800&#xA;     8        4     5                      469.000    1.4000&#xA;     9        4    10                      367.000    1.0800&#xA;    10        5     6                      469.000    1.4000&#xA;    11        5    11                      367.000    1.0800&#xA;    12        6    12                      367.000    1.0800&#xA;&#xA; Angle Bending Parameters :&#xA;&#xA;             Atom Numbers                      KB      Angle   Fold    Type&#xA;&#xA;     1        2     1     6                 63.000   120.000&#xA;     2        2     1     7                 35.000   120.000&#xA;     3        6     1     7                 35.000   120.000&#xA;     4        1     2     3                 63.000   120.000&#xA;     5        1     2     8                 35.000   120.000&#xA;     6        3     2     8                 35.000   120.000&#xA;     7        2     3     4                 63.000   120.000&#xA;     8        2     3     9                 35.000   120.000&#xA;     9        4     3     9                 35.000   120.000&#xA;    10        3     4     5                 63.000   120.000&#xA;    11        3     4    10                 35.000   120.000&#xA;    12        5     4    10                 35.000   120.000&#xA;    13        4     5     6                 63.000   120.000&#xA;    14        4     5    11                 35.000   120.000&#xA;    15        6     5    11                 35.000   120.000&#xA;    16        1     6     5                 63.000   120.000&#xA;    17        1     6    12                 35.000   120.000&#xA;    18        5     6    12                 35.000   120.000&#xA;&#xA; Improper Torsion Parameters :&#xA;&#xA;                 Atom Numbers           Amplitude, Phase and Periodicity&#xA;&#xA;     1        2     6     1     7               1.667   180.0   2&#xA;     2        6     7     1     2               1.667   180.0   2&#xA;     3        7     2     1     6               1.667   180.0   2&#xA;     4        1     3     2     8               1.667   180.0   2&#xA;     5        3     8     2     1               1.667   180.0   2&#xA;     6        8     1     2     3               1.667   180.0   2&#xA;     7        2     4     3     9               1.667   180.0   2&#xA;     8        4     9     3     2               1.667   180.0   2&#xA;     9        9     2     3     4               1.667   180.0   2&#xA;    10        3     5     4    10               1.667   180.0   2&#xA;    11        5    10     4     3               1.667   180.0   2&#xA;    12       10     3     4     5               1.667   180.0   2&#xA;    13        4     6     5    11               1.667   180.0   2&#xA;    14        6    11     5     4               1.667   180.0   2&#xA;    15       11     4     5     6               1.667   180.0   2&#xA;    16        1     5     6    12               1.667   180.0   2&#xA;    17        5    12     6     1               1.667   180.0   2&#xA;    18       12     1     6     5               1.667   180.0   2&#xA;&#xA; Torsional Angle Parameters :&#xA;&#xA;                 Atom Numbers           Amplitude, Phase and Periodicity&#xA;&#xA;     1        6     1     2     3       7.250 180/2&#xA;     2        6     1     2     8       7.250 180/2&#xA;     3        7     1     2     3       7.250 180/2&#xA;     4        7     1     2     8       7.250 180/2&#xA;     5        2     1     6     5       7.250 180/2&#xA;     6        2     1     6    12       7.250 180/2&#xA;     7        7     1     6     5       7.250 180/2&#xA;     8        7     1     6    12       7.250 180/2&#xA;     9        1     2     3     4       7.250 180/2&#xA;    10        1     2     3     9       7.250 180/2&#xA;    11        8     2     3     4       7.250 180/2&#xA;    12        8     2     3     9       7.250 180/2&#xA;    13        2     3     4     5       7.250 180/2&#xA;    14        2     3     4    10       7.250 180/2&#xA;    15        9     3     4     5       7.250 180/2&#xA;    16        9     3     4    10       7.250 180/2&#xA;    17        3     4     5     6       7.250 180/2&#xA;    18        3     4     5    11       7.250 180/2&#xA;    19       10     4     5     6       7.250 180/2&#xA;    20       10     4     5    11       7.250 180/2&#xA;    21        4     5     6     1       7.250 180/2&#xA;    22        4     5     6    12       7.250 180/2&#xA;    23       11     5     6     1       7.250 180/2&#xA;    24       11     5     6    12       7.250 180/2&#xA;&#xA; Van der Waals Parameters :&#xA;&#xA;          Atom Number       Size   Epsilon   Size 1-4   Eps 1-4   Reduction&#xA;&#xA;     1        1           3.5500    0.0700&#xA;     2        2           3.5500    0.0700&#xA;     3        3           3.5500    0.0700&#xA;     4        4           3.5500    0.0700&#xA;     5        5           3.5500    0.0700&#xA;     6        6           3.5500    0.0700&#xA;     7        7           2.4200    0.0300&#xA;     8        8           2.4200    0.0300&#xA;     9        9           2.4200    0.0300&#xA;    10       10           2.4200    0.0300&#xA;    11       11           2.4200    0.0300&#xA;    12       12           2.4200    0.0300&#xA;&#xA; Atomic Partial Charge Parameters :&#xA;                                             Neighbor   Cutoff&#xA;          Atom Number             Charge       Site      Site&#xA;&#xA;     1        1                  -0.1150&#xA;     2        2                  -0.1150&#xA;     3        3                  -0.1150&#xA;     4        4                  -0.1150&#xA;     5        5                  -0.1150&#xA;     6        6                  -0.1150&#xA;     7        7                   0.1150&#xA;     8        8                   0.1150&#xA;     9        9                   0.1150&#xA;    10       10                   0.1150&#xA;    11       11                   0.1150&#xA;    12       12                   0.1150&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is itp file I obtained from LigParGen:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;;&#xA;; GENERATED BY LigParGen Server&#xA;; Jorgensen Lab @ Yale University &#xA;;&#xA;[ atomtypes ]&#xA;  opls_804  C804    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_803  C803    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_811  H811     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_809  H809     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_810  H810     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_805  C805    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_802  C802    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_806  H806     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_808  H808     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_800  C800    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;  opls_807  H807     1.0080     0.000    A    2.42000E-01   1.25520E-01&#xA;  opls_801  C801    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;[ moleculetype ]&#xA;; Name               nrexcl&#xA;UNL                   3&#xA;[ atoms ]&#xA;;   nr       type  resnr residue  atom   cgnr     charge       mass  &#xA;     1   opls_800      1    UNL   C00      1    -0.1374    12.0110 &#xA;     2   opls_801      1    UNL   C01      1    -0.1375    12.0110 &#xA;     3   opls_802      1    UNL   C02      1    -0.1374    12.0110 &#xA;     4   opls_803      1    UNL   C03      1    -0.1372    12.0110 &#xA;     5   opls_804      1    UNL   C04      1     -0.137    12.0110 &#xA;     6   opls_805      1    UNL   C05      1    -0.1371    12.0110 &#xA;     7   opls_806      1    UNL   H06      1     0.1374     1.0080 &#xA;     8   opls_807      1    UNL   H07      1     0.1374     1.0080 &#xA;     9   opls_808      1    UNL   H08      1     0.1374     1.0080 &#xA;    10   opls_809      1    UNL   H09      1     0.1374     1.0080 &#xA;    11   opls_810      1    UNL   H0A      1      0.137     1.0080 &#xA;    12   opls_811      1    UNL   H0B      1      0.137     1.0080 &#xA;[ bonds ]&#xA;    2     1     1      0.1400 392459.200&#xA;    3     2     1      0.1400 392459.200&#xA;    4     3     1      0.1400 392459.200&#xA;    5     4     1      0.1400 392459.200&#xA;    6     1     1      0.1400 392459.200&#xA;    7     1     1      0.1080 307105.600&#xA;    8     2     1      0.1080 307105.600&#xA;    9     3     1      0.1080 307105.600&#xA;   10     4     1      0.1080 307105.600&#xA;   11     5     1      0.1080 307105.600&#xA;   12     6     1      0.1080 307105.600&#xA;    6     5     1      0.1400 392459.200&#xA;&#xA;[ angles ]&#xA;;  ai    aj    ak funct            c0            c1            c2            c3 &#xA;    1     2     3     1    120.000    527.184&#xA;    2     3     4     1    120.000    527.184&#xA;    3     4     5     1    120.000    527.184&#xA;    2     1     6     1    120.000    527.184&#xA;    2     1     7     1    120.000    292.880&#xA;    1     2     8     1    120.000    292.880&#xA;    2     3     9     1    120.000    292.880&#xA;    3     4    10     1    120.000    292.880&#xA;    4     5    11     1    120.000    292.880&#xA;    1     6    12     1    120.000    292.880&#xA;    6     5    11     1    120.000    292.880&#xA;    6     1     7     1    120.000    292.880&#xA;    5     6    12     1    120.000    292.880&#xA;    5     4    10     1    120.000    292.880&#xA;    1     6     5     1    120.000    527.184&#xA;    4     3     9     1    120.000    292.880&#xA;    4     5     6     1    120.000    527.184&#xA;    3     2     8     1    120.000    292.880&#xA;&#xA;[ dihedrals ]&#xA;; IMPROPER DIHEDRAL ANGLES &#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    12     6     1     5    4        180.000     10.460     2  &#xA;    11     5     4     6    4        180.000     10.460     2  &#xA;    10     4     3     5    4        180.000     10.460     2  &#xA;     9     3     2     4    4        180.000     10.460     2  &#xA;     8     2     1     3    4        180.000     10.460     2  &#xA;     7     1     2     6    4        180.000     10.460     2  &#xA;&#xA;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    4    3    2    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    5    4    3    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    6    1    2    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    4    5    6    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    6    5    4    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    5    6    1    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    1    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    7    1    6    5        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    6    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    5    6        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    4    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    5    4        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    2    1        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    7    1    2    3        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    1    6        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    3    2        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    3    4        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    4    5        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   10    4    3    9        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    1    7        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   12    6    5   11        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    9    3    2    8        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;    8    2    1    7        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;   11    5    4   10        3      30.334   0.000  -30.334  -0.000  -0.000   0.000&#xA;&#xA;[ pairs ]&#xA;     1     4    1&#xA;     2     5    1&#xA;     3     6    1&#xA;     3     7    1&#xA;     1     9    1&#xA;     5     7    1&#xA;     4     8    1&#xA;     2    10    1&#xA;     1    11    1&#xA;     6     8    1&#xA;     5     9    1&#xA;     3    11    1&#xA;     2    12    1&#xA;     7     8    1&#xA;     6    10    1&#xA;     4    12    1&#xA;     8     9    1&#xA;     9    10    1&#xA;     7    12    1&#xA;    10    11    1&#xA;    11    12    1&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-04-26T18:12:37.640" Title="How to go from Tinker parameter file to GROMACS topology file for improper and proper dihedrals?" Tags="|gromacs|forcefields|tinker|" AnswerCount="1" CommentCount="7" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4786" PostTypeId="5" CreationDate="2021-04-22T03:59:49.670" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Tinker_(software)&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Tinker_(software)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-22T03:59:49.670" LastActivityDate="2021-04-22T03:59:49.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4787" PostTypeId="4" CreationDate="2021-04-22T03:59:49.670" Score="0" Body="Questions about the TINKER software for molecular dynamics." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-22T03:59:49.670" LastActivityDate="2021-04-22T03:59:49.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4788" PostTypeId="2" ParentId="4753" CreationDate="2021-04-22T18:56:25.363" Score="6" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ruMMS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ruMMS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;Let start with &lt;code&gt;p4vasp&lt;/code&gt;&lt;br /&gt;&#xA;&lt;code&gt;p4vasp&lt;/code&gt; is postprocessing tool for VASP output written in python and some C++.&#xA;It is very easy to install and you can check in its official website &lt;a href=&quot;http://www.p4vasp.at/#/home&quot; rel=&quot;noreferrer&quot;&gt;http://www.p4vasp.at/#/home&lt;/a&gt; &lt;br /&gt;&#xA;For ploting band structure or DOS , this package need &lt;code&gt;vasprun.xml&lt;/code&gt; as input which is output of &lt;code&gt;VASP&lt;/code&gt;. Once we load input, it will automatically show DOS or you can click on DOS menu.&#xA;For local density of states or bands , drop down menu electronic and select local DOS and band control. You can select different atoms and orbital to add in plot. Export output in dat file or &lt;code&gt;xmgrace&lt;/code&gt; file (nice free plotting tool). You can also select each atom for local band and DOS using GUI.&#xA;Nice tutorial link: &lt;a href=&quot;https://youtu.be/RYziHtNFaPs&quot; rel=&quot;noreferrer&quot;&gt;https://youtu.be/RYziHtNFaPs&lt;/a&gt; &lt;br /&gt;&#xA;&lt;a href=&quot;https://youtu.be/ohDguVFDPlc&quot; rel=&quot;noreferrer&quot;&gt;https://youtu.be/ohDguVFDPlc&lt;/a&gt; &lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/fQWLE.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fQWLE.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;code&gt;Vaspkit&lt;/code&gt; is another alternative for p4vasp. &lt;br /&gt;&#xA;It is nice package for both preprocessing and postprocessing with VASP.&#xA;We can generate high symmetry K-Points for band calculation, we can write INCAR, KPOINTS file for input to calculation.&#xA;It reads &lt;code&gt;PROCAR&lt;/code&gt; file as input and gives output in simple form x y column inside dat file which can be used in xmgrace / gnuplot or other.&#xA;Kindly check documentation of vaspkit&#xA;&lt;a href=&quot;https://vaspkit.com/&quot; rel=&quot;noreferrer&quot;&gt;https://vaspkit.com/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mFv3N.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mFv3N.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2021-04-22T19:05:12.917" LastActivityDate="2021-04-22T19:05:12.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4789" PostTypeId="2" ParentId="2163" CreationDate="2021-04-22T19:06:57.293" Score="5" Body="&lt;p&gt;I solved the problem via a simple change in a directory name:&lt;/p&gt;&#xA;&lt;p&gt;When I installed Avogadro2 (1.93.0-3) in Linux Mint 20.1 Xfce (based on Ubuntu 20.04), it installed the auxiliary files (including the input generators) in the following directory:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;/home/user/.local/share/OpenChemistry/Avogadro/other&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, the Avogadro2 application looks in the following directory for the input generators:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;/home/user/.local/share/OpenChemistry/Avogadro/commands&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore, I changed the name of the &amp;quot;other&amp;quot; directory to &amp;quot;commands&amp;quot;. With this change, the Extensions menu now included the input generators.&lt;/p&gt;&#xA;" OwnerUserId="3441" LastEditorUserId="5" LastEditDate="2021-04-22T19:35:42.137" LastActivityDate="2021-04-22T19:35:42.137" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4790" PostTypeId="1" AcceptedAnswerId="6994" CreationDate="2021-04-23T04:05:02.200" Score="8" ViewCount="400" Body="&lt;p&gt;I have designed a molecule using hydrocarbons A and B. I am getting the formation energy slightly positive (~0.04 eV). As per  my experience, any positive formation energy means that the designed molecule will be not stable. Is there any way to synthesize a molecule for which the theoretical formation energy was predicted to be positive?&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-10-30T20:29:00.220" LastActivityDate="2021-11-01T05:31:55.043" Title="If a molecule's theoretical formation energy is positive, can it still be synthesized?" Tags="|molecular-modeling|thermodynamics|experimental|formation-energy|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4792" PostTypeId="1" CreationDate="2021-04-23T07:59:06.880" Score="4" ViewCount="68" Body="&lt;p&gt;The purpose is for me to develop a deeper understanding of speech production and how distinct features that identify a phenome are produced.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;ab initio&lt;/em&gt; models based on classical &amp;amp; statistical mechanics are preferable.&lt;/p&gt;&#xA;" OwnerUserId="3444" LastEditorUserId="5" LastEditDate="2021-04-23T17:11:09.200" LastActivityDate="2021-04-26T18:12:32.713" Title="Has there been any work done on fluid dynamic or acoustic modeling of the human oral (or nasal) cavity?" Tags="|reference-request|ab-initio-calculations|statistical-thermodynamics|biomaterials|fluid-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4793" PostTypeId="1" AcceptedAnswerId="4794" CreationDate="2021-04-23T10:57:34.973" Score="6" ViewCount="514" Body="&lt;p&gt;I have calculated and plotted the DOS for a doped monolayer 3x3x1 supercell. I want to make the plot more smooth and add more points around Fermi level.&#xA;Knowing that these are my settings for the INCAR :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE = 6&#xA;KPAR = 5&#xA;# DOS&#xA;ICHARG = 11&#xA;IBRION = -1&#xA;NSW = 0&#xA;LORBIT = 11&#xA;NEDOS = 2001&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 600 eV&#xA;EDIFF = 1.0E-6&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;ALGO = Normal&#xA;ADDGRID=.TRUE.&#xA;&#xA;#Relaxation:&#xA;ISMEAR = -5&#xA;#SIGMA = 0.05&#xA;EDIFFG = -0.01&#xA;GGA COMPAT = .FALSE.&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 7*0.0 18*0.0 2*5.0&#xA;LASPH = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;AMIX     = 0.2&#xA;BMIX     = 0.00001&#xA;AMIX_MAG = 0.8&#xA;BMIX_MAG = 0.00001&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And KPOINTS :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;15x15x1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2yXhE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2yXhE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-04-23T15:49:43.553" LastActivityDate="2021-04-23T15:49:43.553" Title="How to make this DOS plot more smooth and add more points around Fermi level?" Tags="|density-functional-theory|vasp|density-of-states|dos|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4794" PostTypeId="2" ParentId="4793" CreationDate="2021-04-23T12:39:13.387" Score="3" Body="&lt;p&gt;To smooth the curve, you need to change (increase) the value of &lt;code&gt;NEDOS&lt;/code&gt; as it represents the number of grid points to plot (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/NEDOS&quot; rel=&quot;nofollow noreferrer&quot;&gt;source&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;As the DOS plot is done using a homogeneous grid, if you want the curve more defined around the Fermi level, you need to narrow the energy interval around it defining the values of &lt;code&gt;EMIN&lt;/code&gt; and &lt;code&gt;EMAX&lt;/code&gt; (look for the definition of &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EMIN&quot; rel=&quot;nofollow noreferrer&quot;&gt;EMIN&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EMAX&quot; rel=&quot;nofollow noreferrer&quot;&gt;EMAX&lt;/a&gt;) .&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-23T12:39:13.387" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4795" PostTypeId="2" ParentId="4778" CreationDate="2021-04-23T13:01:48.100" Score="2" Body="&lt;p&gt;You need to use the advanced option &lt;code&gt;--score_only&lt;/code&gt; which means:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; score only - search space can be omitted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To get info about advanced options you run &lt;code&gt;vina --help_advanced&lt;/code&gt; that will return:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Input:&#xA;  --receptor arg                        rigid part of the receptor (PDBQT)&#xA;  --flex arg                            flexible side chains, if any (PDBQT)&#xA;  --ligand arg                          ligand (PDBQT)&#xA;&#xA;Search space (required):&#xA;  --center_x arg                        X coordinate of the center&#xA;  --center_y arg                        Y coordinate of the center&#xA;  --center_z arg                        Z coordinate of the center&#xA;  --size_x arg                          size in the X dimension (Angstroms)&#xA;  --size_y arg                          size in the Y dimension (Angstroms)&#xA;  --size_z arg                          size in the Z dimension (Angstroms)&#xA;&#xA;Output (optional):&#xA;  --out arg                             output models (PDBQT), the default is&#xA;                                        chosen based on the ligand file name&#xA;  --log arg                             optionally, write log file&#xA;&#xA;Advanced options (see the manual):&#xA;  --score_only                          score only - search space can be&#xA;                                        omitted&#xA;  --local_only                          do local search only&#xA;  --randomize_only                      randomize input, attempting to avoid&#xA;                                        clashes&#xA;  --weight_gauss1 arg (=-0.035579)      gauss_1 weight&#xA;  --weight_gauss2 arg (=-0.005156)      gauss_2 weight&#xA;  --weight_repulsion arg (=0.84024500000000002)&#xA;                                        repulsion weight&#xA;  --weight_hydrophobic arg (=-0.035069000000000003)&#xA;                                        hydrophobic weight&#xA;  --weight_hydrogen arg (=-0.58743900000000004)&#xA;                                        Hydrogen bond weight&#xA;  --weight_rot arg (=0.058459999999999998)&#xA;                                        N_rot weight&#xA;&#xA;Misc (optional):&#xA;  --cpu arg                             the number of CPUs to use (the default&#xA;                                        is to try to detect the number of CPUs&#xA;                                        or, failing that, use 1)&#xA;  --seed arg                            explicit random seed&#xA;  --exhaustiveness arg (=8)             exhaustiveness of the global search&#xA;                                        (roughly proportional to time): 1+&#xA;  --num_modes arg (=9)                  maximum number of binding modes to&#xA;                                        generate&#xA;  --energy_range arg (=3)               maximum energy difference between the&#xA;                                        best binding mode and the worst one&#xA;                                        displayed (kcal/mol)&#xA;&#xA;Configuration file (optional):&#xA;  --config arg                          the above options can be put here&#xA;&#xA;Information (optional):&#xA;  --help                                display usage summary&#xA;  --help_advanced                       display usage summary with advanced&#xA;                                        options&#xA;  --version                             display program version&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-23T13:01:48.100" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4796" PostTypeId="5" CreationDate="2021-04-23T15:41:48.547" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-04-23T15:41:48.547" LastActivityDate="2021-04-23T15:41:48.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4797" PostTypeId="4" CreationDate="2021-04-23T15:41:48.547" Score="0" Body="Questions about dipoles or dipole moments" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-04-25T00:34:48.243" LastActivityDate="2021-04-25T00:34:48.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4798" PostTypeId="5" CreationDate="2021-04-23T17:16:41.450" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-23T17:16:41.450" LastActivityDate="2021-04-23T17:16:41.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4799" PostTypeId="4" CreationDate="2021-04-23T17:16:41.450" Score="0" Body="Questions about fluid dynamics." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-23T17:16:41.450" LastActivityDate="2021-04-23T17:16:41.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4800" PostTypeId="2" ParentId="3785" CreationDate="2021-04-23T17:53:33.563" Score="5" Body="&lt;p&gt;I don't have access to TC-Python, so I can't offer advice on how to use the API specifically. This is more of a workaround than a direct way to get Thermo-Calc to tell you whether the phase is ordered or disordered.&lt;/p&gt;&#xA;&lt;p&gt;Are you able to get the site fractions from an equilibrium calculation? In console mode, you can use the &lt;code&gt;Y(CR,BCC_B2#2)&lt;/code&gt; syntax. My understanding is that you can use console mode syntax in TC-Python, but I'm not sure if this particular property is supported. If you can get the site fractions for each species, it is pretty easy to write your own function to quantify whether a phase is ordered or disordered.&lt;/p&gt;&#xA;&lt;p&gt;I have written a function that does this for site fractions from &lt;a href=&quot;https://pycalphad.org&quot; rel=&quot;noreferrer&quot;&gt;pycalphad&lt;/a&gt; &lt;a href=&quot;https://github.com/pycalphad/scheil/blob/a08d0db5b2e1636a53b2743a5938c9bf6f44a2cb/scheil/utils.py#L32&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, which I adapted below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import itertools&#xA;import numpy as np&#xA;def is_ordered(site_fracs, symmetric_subl_idx):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Return True if the site fraction configuration is ordered&#xA;&#xA;    Parameters&#xA;    ----------&#xA;    site_fracs : list[list[float]]&#xA;        Nested site fraction lists. Each inner list must sum to unity.&#xA;    symmetric_subl_idx : list[list[int]]&#xA;        List of sets of symmetrically equivalent sublattice indexes (as a list).&#xA;        If sublattices at index 0 and index 1 are symmetric, as index 2 and&#xA;        index 3, then the symmetric_subl_idx will be [[0, 1], [2, 3]].&#xA;&#xA;    Returns&#xA;    -------&#xA;    bool&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    # For each set of symmetrically equivalent sublattices&#xA;    for symm_subl in symmetric_subl_idx:&#xA;        # Check whether the site fractions of each pair of symmetrically&#xA;        # equivalent sublattices are ordered or disordered&#xA;        for subl_idx1, subl_idx2 in itertools.combinations(symm_subl, 2):&#xA;            # A phase is ordered if any pair of sublattices does not have&#xA;            # equal (within numerical tolerance) site fractions&#xA;            pair_is_ordered = np.any(~np.isclose(site_fracs[subl_idx1], site_fracs[subl_idx2]))&#xA;            if pair_is_ordered:&#xA;                return True&#xA;    return False&#xA;&#xA;&#xA;# For your case, I assume that the sublattice model for BCC_B2 has two substitutional&#xA;# sublattices and one interstitial sublatticewith the model (Cr,Fe)(Cr,Fe)(C,VA), with&#xA;# VA being vacancy. The first and second sublattices are symmetrically equivalent.&#xA;# The third sublattice is only equivalent to itself.&#xA;symmetric_subl_idxs = [[0, 1], [2]]  # note: [[0, 1]] would do the same thing.&#xA;&#xA;# Making up a possible disordered configuration of site fractions:&#xA;# You would construct these from TC-Python, looping over the sublattices and&#xA;# species in each sublattice&#xA;disordered_site_fracs = [[0.25, 0.75], [0.25, 0.75], [0.001, 0.999]]&#xA;print(is_ordered(disordered_site_fracs, symmetric_subl_idxs))  # False&#xA;&#xA;# Making up a possible ordered configuration of site fractions:&#xA;ordered_site_fracs = [[0.5, 0.5], [0.25, 0.75], [0.001, 0.999]]&#xA;print(is_ordered(ordered_site_fracs, symmetric_subl_idxs))  # True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-04-23T17:53:33.563" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4801" PostTypeId="1" AcceptedAnswerId="4803" CreationDate="2021-04-23T17:59:28.243" Score="9" ViewCount="313" Body="&lt;p&gt;I am trying to obtain the Raman spectra of a graphene structure using Gaussian. I used the input below, but when I did it, I got this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;No perturbation frequencies on chk file.&#xA;Error termination via Lnk1e in /usr/local/g09/l101.exe at Fri Apr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I got this error using the following input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=go40r.chk &#xA;%nproc=2 &#xA;#B3LYP/6-31+G(d,p) OPT=tight P GFINPUT POP(FULL, NBO) &#xA;&#xA;go40r&#xA;&#xA;0 1&#xA;C  &#xA;C   1 B1&#xA;C   2 B2 1 A2&#xA;C   3 B3 2 A3 1 D3&#xA;C   4 B4 3 A4 2 D4&#xA;C   1 B5 2 A5 3 D5&#xA;C   2 B6 1 A6 3 D6&#xA;C   7 B7 2 A7 1 D7&#xA;C   8 B8 7 A8 2 D8&#xA;C   1 B9 2 A9 3 D9&#xA;C   4 B10 3 A10 2 D10&#xA;C   11 B11 4 A11 3 D11&#xA;C   12 B12 11 A12 4 D12&#xA;C   5 B13 4 A13 3 D13&#xA;C   7 B14 2 A14 1 D14&#xA;C   15 B15 7 A15 2 D15&#xA;C   16 B16 15 A16 7 D16&#xA;C   17 B17 16 A17 15 D17&#xA;C   18 B18 17 A18 16 D18&#xA;C   8 B19 7 A19 2 D19&#xA;C   20 B20 8 A20 7 D20&#xA;C   21 B21 20 A21 8 D21&#xA;C   22 B22 21 A22 20 D22&#xA;C   12 B23 11 A23 4 D23&#xA;C   24 B24 12 A24 11 D24&#xA;C   25 B25 24 A25 12 D25&#xA;C   26 B26 25 A26 24 D26&#xA;C   19 B27 18 A27 17 D27&#xA;C   28 B28 19 A28 18 D28&#xA;C   20 B29 8 A29 7 D29&#xA;C   30 B30 20 A30 8 D30&#xA;C   23 B31 22 A31 21 D31&#xA;C   32 B32 23 A32 22 D32&#xA;C   33 B33 32 A33 23 D33&#xA;C   34 B34 33 A34 32 D34&#xA;C   35 B35 34 A35 33 D35&#xA;C   36 B36 35 A36 34 D36&#xA;C   37 B37 36 A37 35 D37&#xA;C   38 B38 37 A38 36 D38&#xA;C   39 B39 38 A39 37 D39&#xA;H   35 B40 34 A40 33 D40&#xA;H   32 B41 23 A41 22 D41&#xA;H   33 B42 32 A42 23 D42&#xA;H   37 B43 36 A43 35 D43&#xA;H   25 B44 24 A44 12 D44&#xA;H   26 B45 25 A45 24 D45&#xA;H   28 B46 19 A46 18 D46&#xA;H   29 B47 28 A47 19 D47&#xA;H   18 B48 17 A48 16 D48&#xA;H   16 B49 15 A49 7 D49&#xA;H   30 B50 20 A50 8 D50&#xA;H   31 B51 30 A51 20 D51&#xA;H   21 B52 20 A52 8 D52&#xA;H   22 B53 21 A53 20 D53&#xA;H   39 B54 38 A54 37 D54&#xA;H   40 B55 39 A55 38 D55&#xA;&#xA;B1        1.41177&#xA;B2        1.41295&#xA;A2      119.98439&#xA;B3        1.41285&#xA;A3      120.02300&#xA;D3      359.88058&#xA;B4        1.41175&#xA;A4      119.99057&#xA;D4      359.77830&#xA;B5        1.41290&#xA;A5      119.99238&#xA;D5        0.34142&#xA;B6        1.41290&#xA;A6      120.01912&#xA;D6      179.95462&#xA;B7        1.41414&#xA;A7      120.03930&#xA;D7      359.80024&#xA;B8        1.41358&#xA;A8      119.94352&#xA;D8      359.90509&#xA;B9        1.41300&#xA;A9      120.01294&#xA;D9      180.34989&#xA;B10        1.41296&#xA;A10      119.99598&#xA;D10      179.76786&#xA;B11        1.41413&#xA;A11      120.03734&#xA;D11      179.89294&#xA;B12        1.41354&#xA;A12      119.94769&#xA;D12      359.82161&#xA;B13        1.41292&#xA;A13      120.01970&#xA;D13      180.29457&#xA;B14        1.41129&#xA;A14      119.97589&#xA;D14      179.83498&#xA;B15        1.40285&#xA;A15      119.35258&#xA;D15        0.29996&#xA;B16        1.40322&#xA;A16      121.32382&#xA;D16      359.93274&#xA;B17        1.40332&#xA;A17      121.27813&#xA;D17      179.71361&#xA;B18        1.40273&#xA;A18      121.32569&#xA;D18      179.87613&#xA;B19        1.41278&#xA;A19      120.06092&#xA;D19      179.95552&#xA;B20        1.40107&#xA;A20      119.33056&#xA;D20      179.80615&#xA;B21        1.39666&#xA;A21      120.67180&#xA;D21      359.96428&#xA;B22        1.40103&#xA;A22      120.67762&#xA;D22        0.15329&#xA;B23        1.41286&#xA;A23      120.05583&#xA;D23      179.84519&#xA;B24        1.40105&#xA;A24      119.32316&#xA;D24      179.87580&#xA;B25        1.39659&#xA;A25      120.68072&#xA;D25      359.92279&#xA;B26        1.40104&#xA;A26      120.67254&#xA;D26        0.14721&#xA;B27        1.40158&#xA;A27      121.36287&#xA;D27      179.84608&#xA;B28        1.39652&#xA;A28      120.74632&#xA;D28      179.81120&#xA;B29        1.40059&#xA;A29      119.27195&#xA;D29      359.83159&#xA;B30        1.39666&#xA;A30      120.65210&#xA;D30        0.22528&#xA;B31        1.40061&#xA;A31      121.39961&#xA;D31      179.91178&#xA;B32        1.39654&#xA;A32      120.65205&#xA;D32      180.22200&#xA;B33        1.40147&#xA;A33      120.74964&#xA;D33      359.91459&#xA;B34        1.40284&#xA;A34      121.36854&#xA;D34      179.81197&#xA;B35        1.40327&#xA;A35      121.32627&#xA;D35      179.85391&#xA;B36        1.40328&#xA;A36      121.27870&#xA;D36      179.88190&#xA;B37        1.40275&#xA;A37      121.32814&#xA;D37      179.71558&#xA;B38        1.40142&#xA;A38      121.36666&#xA;D38      179.99510&#xA;B39        1.39656&#xA;A39      120.74836&#xA;D39      179.71837&#xA;B40        1.08867&#xA;A40      119.29257&#xA;D40      359.88468&#xA;B41        1.08779&#xA;A41      120.47089&#xA;D41        0.14693&#xA;B42        1.08792&#xA;A42      118.78881&#xA;D42      179.92492&#xA;B43        1.08877&#xA;A43      119.37359&#xA;D43      359.79177&#xA;B44        1.08786&#xA;A44      120.45392&#xA;D44      179.97938&#xA;B45        1.08779&#xA;A45      118.86254&#xA;D45      180.07978&#xA;B46        1.08788&#xA;A46      120.46344&#xA;D46      359.81812&#xA;B47        1.08776&#xA;A47      118.87953&#xA;D47      179.99486&#xA;B48        1.08871&#xA;A48      119.37453&#xA;D48      359.85308&#xA;B49        1.08873&#xA;A49      119.29517&#xA;D49      179.86108&#xA;B50        1.08778&#xA;A50      120.47105&#xA;D50      180.14583&#xA;B51        1.08784&#xA;A51      118.79021&#xA;D51      179.91749&#xA;B52        1.08778&#xA;A52      120.46471&#xA;D52      180.03631&#xA;B53        1.08777&#xA;A53      118.86016&#xA;D53      180.08633&#xA;B54        1.08797&#xA;A54      120.46401&#xA;D54      359.77153&#xA;B55        1.08782&#xA;A55      118.87871&#xA;D55      180.04494 &#xA;&#xA;--Link1--&#xA;%chk=go40r.chk &#xA;%nproc=2 &#xA;#p B3LYP/6-31+G(d,p) scf=xqc  &#xA;geom=allcheck int=ultrafine freq=raman CPHF=(RdFreq,Grid=Ultrafine)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What am I doing wrong?&lt;/p&gt;&#xA;" OwnerUserId="3448" OwnerDisplayName="Bruno" LastEditorUserId="1380" LastEditDate="2021-04-23T21:46:34.630" LastActivityDate="2021-04-23T21:46:34.630" Title="Problem obtaining a Raman spectra of a graphene structure" Tags="|computational-chemistry|gaussian|spectroscopy|from-chem-se|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4802" PostTypeId="1" CreationDate="2021-04-23T18:29:33.570" Score="8" ViewCount="218" Body="&lt;p&gt;Regarding input generators for a Linux (Linux Mint 20.1 Xfce) version of Avogadro2, I have managed to get this working using the Flatpak version and copying the input generator python scripts from another version of Avogadro to &lt;code&gt;/home/user/openchemistry/avogadrogenerators&lt;/code&gt;. This enables me to generate QM input files and save them to disk.&lt;/p&gt;&#xA;&lt;p&gt;Now that this is working, it would be good to be able to submit QM jobs directly from Avogadro, but when this is attempted, &lt;strong&gt;I get an error,&lt;/strong&gt; &lt;code&gt;&amp;quot;Cannot connect to MoleQueue&amp;quot;&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there any updates regarding when this feature will be available in Avogadro and/or how it could be implemented by the end-user?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3441" LastEditorUserId="5" LastEditDate="2021-04-25T00:11:11.487" LastActivityDate="2021-04-26T19:55:47.273" Title="Avogadro for Linux -- Input Generators and Submitting Job to QM software?" Tags="|quantum-chemistry|software-assistance|avogadro|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4803" PostTypeId="2" ParentId="4801" CreationDate="2021-04-23T18:49:40.210" Score="9" Body="&lt;p&gt;Since you include the command &lt;code&gt;cphf=RdFreq&lt;/code&gt;, Gaussian expects you to have entered a perturbation frequency after the rest of the input. You need to specify a frequency in order to compute dynamic properties. Here is how it would look for your case. Note you can specify the perturbation in a couple different units (nm, au,etc).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--Link1--&#xA;%chk=go40r.chk &#xA;%nproc=2 &#xA;#p B3LYP/6-31+G(d,p) scf=xqc  &#xA;geom=allcheck int=ultrafine freq=raman CPHF=(RdFreq,Grid=Ultrafine)&#xA;&#xA;589nm&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You could remove this keyword and just compute static Raman scattering activities if you don't have a particular perturbation in mind. However, if you are trying to compare with an experiment and compute a matching Raman intensity, you need to include the incident light frequency used by the spectrometer, since the intensities have an &lt;span class=&quot;math-container&quot;&gt;$\nu_L^4$&lt;/span&gt; dependence on the frequency of the laser used.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-04-23T18:49:40.210" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4804" PostTypeId="2" ParentId="4784" CreationDate="2021-04-23T19:12:09.670" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;if you had access to the database equations for a given alloy system, could you analytically solve (and thus solve quickly) for the conditions (i.e., temperatures and compositions) that would produce the phase combination that you desire?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Generally, the answer to this question is no. If we knew how to predict which phases were stable analytically without minimizing the Gibbs energy, we wouldn't need to do the Gibbs energy minimization.&lt;/p&gt;&#xA;&lt;p&gt;That being said, it may be possible for the existing software tools to help you do what you want.&lt;/p&gt;&#xA;&lt;p&gt;Thermo-Calc and OpenCalphad are very flexible in the conditions you can write. If you can express what you want using thermodynamic conditions, these tools are a great choice and are very powerful. For example, you can fix the amount of a phase, e.g. set the phase amount of HCP to 0, and fix the pressure and number of moles and step over temperatures and compositions to determine the HCP zero phase fraction line. This is actually how phase diagram mapping is implemented in those software tools. I'm pretty some of the other software packages support these conditions as well, Thermo-Calc and OpenCalphad are just the ones I have experience with.&lt;/p&gt;&#xA;&lt;p&gt;However, it sounds like you are more interested in screening particular regions of phase stability or perhaps a property of interest. To my knowledge, this is not easy in the software that I previously mentioned. In &lt;a href=&quot;https://pycalphad.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;pycalphad&lt;/a&gt; it is relatively easy, but there's no getting around actually doing the calculations.&lt;/p&gt;&#xA;&lt;p&gt;Here's an example I put together (using pycalphad version 0.8.4) for finding the regions in Al-Zn where FCC and HCP are stable. I have a Jupyter Notebook rendered in a &lt;a href=&quot;https://gist.github.com/bocklund/29c60463d477bab05dfdb8d2c40beaf0&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub gist&lt;/a&gt;, but the code is here for archival purposes.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import matplotlib.pyplot as plt&#xA;from pycalphad import Database, binplot, equilibrium&#xA;import pycalphad.variables as v&#xA;&#xA;# Load database and choose the phases that will be considered&#xA;dbf = Database('alzn_mey.tdb')&#xA;components = ['AL', 'ZN', 'VA']&#xA;phases = ['LIQUID', 'FCC_A1', 'HCP_A3']&#xA;conditions = {v.X('ZN'):(0,1,0.02), v.T: (300, 1000, 10), v.P:101325, v.N: 1}&#xA;&#xA;# Compute the phase diagram&#xA;binplot(dbf, components, phases, conditions)&#xA;plt.show()&#xA;&#xA;# Perform an equilibrim calculation in a multi-dimensional grid over all the conditions&#xA;eq_result = equilibrium(dbf, components, phases, conditions)&#xA;&#xA;mask_cond = (eq_result.Phase.isin('FCC_A1').sum(dim='vertex') == 1) &amp;amp; (eq_result.Phase.isin('HCP_A3').sum(dim='vertex') == 1)&#xA;X_ZN = eq_result.X_ZN.where(mask_cond).transpose(*mask_cond.dims)&#xA;T = eq_result.T.where(mask_cond).transpose(*mask_cond.dims)&#xA;plt.scatter(X_ZN, T, c='blue', s=2)&#xA;&#xA;plt.title('Two-phase FCC and HCP')&#xA;plt.xlabel('X(ZN)')&#xA;plt.ylabel('Temperature (K)')&#xA;&#xA;plt.xlim(0, 1)&#xA;plt.ylim(conditions[v.T][0], conditions[v.T][1])&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This produces the following plots of the phase diagram and the points where FCC and HCP are stable:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5NBz7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5NBz7.png&quot; alt=&quot;Al-Zn phase diagram&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HNWWC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HNWWC.png&quot; alt=&quot;Al-Zn fcc and hcp stable&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;pycalphad returns results from &lt;code&gt;equilibrium&lt;/code&gt; in &lt;a href=&quot;https://xarray.pydata.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;xarray&lt;/a&gt; &lt;code&gt;Dataset&lt;/code&gt; objects. &lt;code&gt;xarray&lt;/code&gt; is very powerful and can do very advanced masking and indexing operations. We have documented how pycalphad structures the &lt;code&gt;Dataset&lt;/code&gt; objects &lt;a href=&quot;https://pycalphad.org/docs/latest/examples/UsingCalculationResults.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, which includes some of the data you get from default from a pycalphad calculation.&lt;/p&gt;&#xA;&lt;p&gt;Full disclosure: I am a developer of pycalphad.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="1179" LastEditDate="2021-04-24T00:06:54.827" LastActivityDate="2021-04-24T00:06:54.827" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4805" PostTypeId="2" ParentId="4757" CreationDate="2021-04-24T04:38:47.990" Score="16" Body="&lt;h1&gt;Open Babel&lt;/h1&gt;&#xA;&lt;p&gt;First, the command-line version:&#xA;&lt;code&gt;obabel c60.xyz -oreport&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Yields:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;All interatomic distances&lt;/li&gt;&#xA;&lt;li&gt;All bond angles&lt;/li&gt;&#xA;&lt;li&gt;All connected torsions&lt;/li&gt;&#xA;&lt;li&gt;Also, partial charges&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INTERATOMIC DISTANCES&#xA;&#xA;              C   1      C   2      C   3      C   4      C   5      C   6&#xA;              ------------------------------------------------------------------&#xA;   C   1    0.0000 &#xA;   C   2    1.4534     0.0000 &#xA;   C   3    2.3516     1.4534     0.0000 &#xA;   C   4    2.3516     2.3516     1.4534     0.0000 &#xA;   C   5    1.4534     2.3516     2.3516     1.4534     0.0000 &#xA;   C   6    2.4673     3.5759     3.5759     2.4673     1.3955     0.0000 &#xA;   C   7    3.6940     4.5105     4.1143     2.8488     2.4673     1.4534 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But if you want to do it in Python, you can easily do this through the &lt;code&gt;openbabel&lt;/code&gt; or &lt;code&gt;pybel&lt;/code&gt; modules. I posted a script we've used for &lt;a href=&quot;https://gist.github.com/ghutchis/0980e8faf51be56780af469ccb0e3311&quot; rel=&quot;noreferrer&quot;&gt;basic machine learning representations&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Key calls:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;for bond in ob.OBMolBondIter(mol.OBMol):&lt;/code&gt; # Loop through bonds&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;for pair in ob.OBMolPairIter(mol.OBMol):&lt;/code&gt; # Loop through non-bonded pairs of atoms&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;for angle in ob.OBMolAngleIter(mol.OBMol):&lt;/code&gt; # Loop through angles&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;for torsion in ob.OBMolTorsionIter(mol.OBMol):&lt;/code&gt; # Loop through torsions&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You could use a slightly different loop if you didn't want to separate bonded and non-bonded atoms, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for idx1 in range(1, mol.OBMol.NumAtoms() + 1): # OB counts atoms from 1&#xA;    a = mol.OBMol.GetAtom(idx1)&#xA;    for idx2 in range(idx1 + 1, mol.OBMol.NumAtoms() + 1):&#xA;        b = mol.OBMol.GetAtom(idx2)&#xA;        # calculate distance, whatever&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-04-24T04:38:47.990" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4806" PostTypeId="2" ParentId="4652" CreationDate="2021-04-24T06:44:06.410" Score="3" Body="&lt;p&gt;For an atom in the boundary, the distance with all other atoms of the molecule it is part of will be different based on whether we take into account minimum image convention (MIC) or not. Thus we can,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;first identify the indices of all the molecules in the structure and&lt;/li&gt;&#xA;&lt;li&gt;then exclude the molecules for which any of the distance is different if MIC is considered or not.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;See the following code for an example of this using ASE. The code to determine indices of molecules is the same as a &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4648/85&quot;&gt;previous answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;from ase.io import read, write&#xA;from ase import Atoms, neighborlist&#xA;from scipy import sparse&#xA;&#xA;supercell = read(&amp;quot;mycif.cif&amp;quot;)*(8,4,4) # Read the structure&#xA;&#xA;# Determine the indices of each molecule using neighborlists&#xA;cutoff = neighborlist.natural_cutoffs(supercell)&#xA;nl = neighborlist.build_neighbor_list(supercell, cutoffs=cutoff)&#xA;connmat = nl.get_connectivity_matrix(False) # Connectivity matrix&#xA;# n_components contains number of molecules&#xA;# component_list contains molecule number of each atom in the system&#xA;n_components, component_list = sparse.csgraph.connected_components(connmat)&#xA;&#xA;# Get symbols array of atoms&#xA;origsymbols = np.array(supercell.get_chemical_symbols())&#xA;&#xA;# Excluding atoms in the boundary&#xA;ind_selected = [] # List to store selected indices&#xA;for i in range(n_components): # For each molecule&#xA;    ind = np.where(component_list == i)[0] # Find indices of atoms in molecule&#xA;    # Based on MIC, if any atoms are in the boudary exclude the molecule&#xA;    if (supercell.get_distances(ind[0],ind) != supercell.get_distances(ind[0],ind, mic=True)).any():&#xA;        continue&#xA;    ind_selected += ind.tolist() # Append selected indices to list&#xA;&#xA;# Positions and symbols of selected indices&#xA;pos_selected = supercell.positions[ind_selected]&#xA;symbols_selected = origsymbols[ind_selected]&#xA;&#xA;# Build Atoms object excluding atoms in boundaries&#xA;finalsupercell = Atoms(&#xA;        positions=pos_selected,&#xA;        cell=supercell.cell,&#xA;        symbols=symbols_selected,&#xA;        pbc=supercell.pbc)&#xA;&#xA;# Write to file&#xA;write(&amp;quot;finalsupercell.xyz&amp;quot;, finalsupercell)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="85" LastActivityDate="2021-04-24T06:44:06.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4807" PostTypeId="2" ParentId="3864" CreationDate="2021-04-24T23:41:40.140" Score="3" Body="&lt;p&gt;You left off a key phrase from the paper. Noncentrosymmetric systems with time reversal symmetry don't have &lt;em&gt;nonreciprocal&lt;/em&gt; linear response. Linear response on its own doesn't have this property. For example Electric Polarizability is the linear response of the dipole to a change in the electric field and this in general is nonzero for noncentrosymmetric and centrosymmetric systems. Nonreciprocal linear response seems to look at the difference in linear response for perturbations with opposite helicity/chirality/handedness. Reversing time also reverses the direction and helicity of the wavevector, so time reversal symmetry is related to this. So I would think the nonreciprocal polarizability would be zero, since using left vs right circularly polarized light should make no difference.&lt;/p&gt;&#xA;&lt;p&gt;As to why nonreciprocal linear response is forbidden (at least, as mentioned in the paper, for the diagonal elements). This comes from these Onsager reciprocal relations, which relates some linear response function to a similar, time reversed response function: &lt;span class=&quot;math-container&quot;&gt;$$\tag{1}K_{AB}(q)=\epsilon_A\epsilon_BK_{BA}(-q)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This just says that the response function for operators A and B (A input, B output) is equal to the response function for B and A (B input, A output) with the wavevector flipped and the sign flipped based on the time symmetry of A and B. For a diagonal element (say xx), reversing the order of A and B doesn't matter (it's still the xx element of the same tensor) and assuming time reversal symmetry for each operator, this reduces to &lt;span class=&quot;math-container&quot;&gt;$$\tag{2}K_{A_xB_x}(q)-K_{A_xB_x}(-q)=0$$&lt;/span&gt;&#xA;This is exactly the nonreciprocal response for this element, so we can see that it will always vanish for a diagonal element. For an  off-diagonal (say xy), reversing the order of A and B does matter (the reciprocal theorem relates the xy and time reversed yx elements of the tensor) &lt;span class=&quot;math-container&quot;&gt;$$\tag{3}K_{A_xB_y}(q)-K_{B_yA_x}(-q)=0$$&lt;/span&gt; For the nonreciprocal response to be zero, the second term would be &lt;span class=&quot;math-container&quot;&gt;$K_{B_xA_y}(-q)$&lt;/span&gt;. The relation doesn't say anything about the nonreciprocal linear response in this case, so in general these elements will be nonzero.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-26T02:57:13.770" LastActivityDate="2021-04-26T02:57:13.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4808" PostTypeId="2" ParentId="4349" CreationDate="2021-04-25T00:34:29.483" Score="1" Body="&lt;p&gt;If I'm interpreting the &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/EXTERNAL_POTENTIAL.html#list_FUNCTION&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; correctly, it is not possible to define a complex external potential in CP2K. It specifies that the &lt;code&gt;VALUES&lt;/code&gt; keyword to define the corresponding &lt;code&gt;PARAMETERS&lt;/code&gt; of your potential has to be real. I don't know anything about the internal code of CP2K, so I don't know if this would be a simple modification of the code to accept complex inputs in this function or a more extensive overall of the code to handle complex values throughout.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-04-25T00:34:29.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4809" PostTypeId="2" ParentId="4387" CreationDate="2021-04-25T03:28:57.623" Score="10" Body="&lt;p&gt;I think the best place to start is the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;original paper&lt;/a&gt;¹ proposing norm conserving pseudopotentials (NCPPs). It's very short and gives a nice explanation of why they were developed. I'll just give a brief summary here.&lt;/p&gt;&#xA;&lt;p&gt;Norm conservation (specifically of the charge density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;) ensures that the electrostatic potential for &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_c$&lt;/span&gt; is accurate as a result of Gauss' Flux Theorem &lt;span class=&quot;math-container&quot;&gt;$\nabla^2V_E=\frac{\rho}{\epsilon_0}$&lt;/span&gt;. Matching the electrostatic potential makes these pseudopotentials more physically consistent and thus transferable.&lt;/p&gt;&#xA;&lt;p&gt;Norm conservation also affects how well the scattering behavior of an atom is reproduced:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$2\pi[(r\phi)^2\frac{d}{d\epsilon}\frac{d}{dr}\ln(\phi)]_R=4\pi\int_0^R r^2\phi^2dr$$&lt;/span&gt;&#xA;The logarithmic derivative of the wavefunction is related to the scattering phase shift and energy derivative then gives the linear change in this scattering as the energy varies from the atomic energy. The right hand side is the norm-conservation condition in a shell of radius R. This means that norm conservation reduces the error in scattering behavior when using these pseudopotentials in different contexts than the bare atom they were defined from.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;D. R. Hamann, M. Schlüter, and C. Chiang Phys. Rev. Lett. 43, 1494 (1979)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-04-26T18:46:44.580" LastActivityDate="2021-04-26T18:46:44.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4810" PostTypeId="1" CreationDate="2021-04-25T10:42:20.867" Score="7" ViewCount="80" Body="&lt;p&gt;Using first principles methods (quantum espresso code) I would like to find   if a monolayer of a material is flat or buckled.  Using the van der Waals interaction in the calculation I found that the buckled configuration has the lowest energy whereas based on the literature it should be the flat one?&lt;/p&gt;&#xA;" OwnerUserId="3450" LastEditorUserId="792" LastEditDate="2021-04-25T11:09:52.317" LastActivityDate="2021-04-26T00:02:12.557" Title="How to determine the more stable configuration between a flat and a buckled monolayer with DFT?" Tags="|density-functional-theory|quantum-espresso|structure|2d-lattice|monolayer|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4811" PostTypeId="1" CreationDate="2021-04-25T11:10:28.430" Score="15" ViewCount="3358" Body="&lt;p&gt;I want to build a rough atom interaction simulator, where pushes two (or more) atoms toward each other and they should behave physically correctly: attract, bond or repel with some force. So that is what I need to calculate.&lt;/p&gt;&#xA;&lt;p&gt;I have been looking into ionic and covalent bonds theory and that helps.&lt;/p&gt;&#xA;&lt;p&gt;But still I do don't understand how to calculate the final outcome based on the colliding atoms' types and forces with which they are pushed towards each other.&lt;/p&gt;&#xA;&lt;h2&gt;Input:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Atom X: and its electronic properties and movement force,&lt;/li&gt;&#xA;&lt;li&gt;Atom Y: and its electronic properties and movement force,&lt;/li&gt;&#xA;&lt;li&gt;Distance between them&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;Outcome:&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;new force for X and Y + rough changes in electronic properties (bonds etc.)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I got advice to look into the &amp;quot;Morse potential&amp;quot;, but reading trough the Wikipedia article is a bit like reading rocket science for me and I can't really 100% associate it with my case. And I think it's mostly about molecules. Is it really also possible to calculate a rough outcome of two colliding molecules (taking some average forces?)?&lt;/p&gt;&#xA;&lt;p&gt;Any help is appreciated!&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2021-04-27T22:58:05.717" LastActivityDate="2021-04-27T22:58:05.717" Title="How do I simulate the interaction between two atoms?" Tags="|molecular-dynamics|ab-initio-calculations|from-phys-se|soft-question|interatomic-potentials|" AnswerCount="6" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4812" PostTypeId="1" CreationDate="2021-04-25T13:03:51.287" Score="4" ViewCount="103" Body="&lt;p&gt;I am interested in the theoretical study of optical anisotropy (birefringence, dichroism etc.) of different materials. I have seen DFT works studying optical anisotropy from the calculation of dielectric function (An &lt;a href=&quot;https://doi.org/10.1016/j.jpcs.2008.01.017&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt;). However DFT is a ground-state theory and is not considered the best for optical studies. My question.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the different methods available for the study of optical anisotropy and how do they compare with DFT?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2021-04-25T20:12:05.847" Title="Optical anisotropy from first-principles" Tags="|density-functional-theory|one-topic-per-answer|optical-properties|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4813" PostTypeId="2" ParentId="4811" CreationDate="2021-04-25T16:52:07.873" Score="10" Body="&lt;p&gt;In order to simulate two atom interaction, you have different path to follow.&lt;/p&gt;&#xA;&lt;p&gt;One is to use Density Functional Theory (DFT) or &lt;em&gt;ab initio&lt;/em&gt;, make a script where the distance of the atoms is decreasing, and for each distance, you calculate the system energy. The image below is the result of such calculation but between a metal atom and a carbon nanotube&lt;sup&gt;1&lt;/sup&gt;. You can use this for atom-atom, atom-system or system-system. This approach is a parameter free method and is independent of other theories.&lt;/p&gt;&#xA;&lt;p&gt;For your simulator, and to get more accurate and faster results, I recommend to use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Semi-empirical_quantum_chemistry_method&quot; rel=&quot;noreferrer&quot;&gt;semi-empirical&lt;/a&gt; method implemented in software like &lt;a href=&quot;http://openmopac.net&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt; (free).&lt;/p&gt;&#xA;&lt;p&gt;The other way is to use force-field implementation. In this case, you will need o use the &amp;quot;best&amp;quot; potential that represents each type of system. One example is the Morse potential you mention, but there many are others (take a look at the &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/models.cfm&quot; rel=&quot;noreferrer&quot;&gt;GULP&lt;/a&gt; page, for example. The force-field (or potentials) are full of parameters that, in general, are obtained from calculations as described above or when possible, from experimental data.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Pnoi4.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Pnoi4.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; M. Bastos, I. Camps, &lt;em&gt;First-principles calculations of nickel, cadmium, and lead adsorption on a single-walled (10,0) carbon nanotube&lt;/em&gt;. J Mol Model (2014) 20:2094 DOI: &lt;a href=&quot;https://dx.doi.org/10.1007/s00894-014-2094-y&quot; rel=&quot;noreferrer&quot;&gt;10.1007/s00894-014-2094-y&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-25T16:52:07.873" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4814" PostTypeId="2" ParentId="2226" CreationDate="2021-04-25T17:17:26.447" Score="4" Body="&lt;p&gt;The &lt;a href=&quot;https://siesta-project.org/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SIESTA&lt;/a&gt; code has a branch (rel-Max-2) developed by researchers from Max Plank institute that include the calculations of forces and real-time TDDFT.&lt;/p&gt;&#xA;&lt;p&gt;The TDDFT is merged into the main development branch and will be released in versions newer than 4.1 (i.e. 4.2 or 5.0).&lt;/p&gt;&#xA;&lt;p&gt;To download it, go to the Gitlab page: &lt;a href=&quot;https://gitlab.com/siesta-project/siesta/-/tree/rel-MaX-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/siesta-project/siesta/-/tree/rel-MaX-2&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="887" LastEditDate="2021-04-26T11:41:25.880" LastActivityDate="2021-04-26T11:41:25.880" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4815" PostTypeId="2" ParentId="4812" CreationDate="2021-04-25T20:12:05.847" Score="5" Body="&lt;p&gt;As something of a frame challenge, I would argue that DFT should be suitable for these kinds of calculations. At least for molecules, DFT is probably the most common way to compute circular birefringence and circular dichroism and it seems to give reasonable agreement with experiment. When more accurate calculations are needed, CCSD calculations are used, but their scaling would likely make them infeasible for use on materials.&lt;/p&gt;&#xA;&lt;p&gt;DFT also does seem to be used for optical anisotropy of materials. I have included references to some papers below that do so. I would note the first reference in particular, which is recent, open-access, and shows a favorable comparison with experiment.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ermolaev, G.A. et al. Giant optical anisotropy in transition metal dichalcogenides for next-generation photonics. Nat Commun 12, 854 (2021). &lt;a href=&quot;https://doi.org/10.1038/s41467-021-21139-x&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/s41467-021-21139-x&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;G.Y. Guo, et al. Linear and nonlinear optical properties of carbon nanotubes from first-principles calculations, Phys. Rev. B 69, 205416 (2004) &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.69.205416&quot; rel=&quot;noreferrer&quot;&gt;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.69.205416&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;L. Uba, et al. Giant magneto-optical anisotropy in Fe/Au monoatomic multilayer, Solid State Communications 114 (2000) &lt;a href=&quot;https://doi.org/10.1016/S0038-1098(00)00080-6&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/S0038-1098(00)00080-6&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-04-25T20:12:05.847" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4816" PostTypeId="2" ParentId="4811" CreationDate="2021-04-25T20:41:32.000" Score="14" Body="&lt;p&gt;&lt;strong&gt;EDIT&lt;/strong&gt; Doing what you want is hard! You will need a full quantum mechanics based simulation. This is unlikely to be something you can build yourself at the current time.&lt;/p&gt;&#xA;&lt;p&gt;Based on your new additions to the question what you need is Car-Parrinello or Born Oppenheimer MD. These essentially automate the idea of do a quantum electronic structure calculation, take the derivatives of the potential energy landscape with respect to nuclear coordinates to calculate forces, update the nuclear position, rinse and repeat. The difference is BOMD essentially forgets and resolves the entire electronic structure each time step while cpmd tries to calculate how the electronic structure changes (though due to this requires far lower time steps).&lt;/p&gt;&#xA;&lt;p&gt;Free software does exist out there to do this, but learning how to use it is not always straight forward. A quick google brings up &lt;a href=&quot;https://www.cp2k.org/quickstep&quot; rel=&quot;noreferrer&quot;&gt;cp2k&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;More generally the question of computationally modelling exactly how atoms come together is unfortunately a very complex quantum mechanical mess, typically reserved for the fourth or fifth year of a chemistry degree. Forget about two atoms, we are unable to completely solve the problems of one atom with two electrons! While less accurate, non quantum, ways to calculate interactions do exist, these are typically not able to form or break bonds which seems to be what you are interested in. Typically uses are instead protein folding, measuring the energy of crystal structures or modding solvent molecules interacting around a solute (essentially where there are simply too many atoms and the quantum treatment is too slow)&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Based on old question&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;@Camps answer is the most accurate way to go, however from your question I'm assuming complete accuracy is not what you're looking for (if it is something like &lt;a href=&quot;https://en.wikipedia.org/wiki/M%C3%B8ller%E2%80%93Plesset_perturbation_theory&quot; rel=&quot;noreferrer&quot;&gt;MP2&lt;/a&gt; or &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory&quot; rel=&quot;noreferrer&quot;&gt;DFT&lt;/a&gt; is the way to go, for this you will need a quantum chemistry program, &lt;a href=&quot;https://psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;Psi4&lt;/a&gt; is quick to install and free).&lt;/p&gt;&#xA;&lt;p&gt;If however even the morse potential is too complex can I recommend the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;noreferrer&quot;&gt;Lennard-Jones&lt;/a&gt;? Anything simpler (ie using just electrostatics and kinetic energy) and you're just bouncing charged spheres off each other. Essentially this ignores electrostatics (atoms are neutral overall) and only models dispersion and Pauli repulsion. In simple terms dispersion is due to the fact that the electrons moving round each atom aren't always perfectly evenly distributed, at times they will be more on one side or the other which produces an instantaneous dipole. The direction of this dipole is essentially random but as it is lower energy for both atoms to have attracting instantaneous dipoles they will tend to do so on average giving a weak attractive interaction that tends to scale with one over the seperation distance to the sixth power. (a more accurate description is given by inter molecular perturbation theory, I can't find a nice simple description of this though). Pauli repulsion occurs due to the quantum mechanics of electrons. You may have heard of the Pauli exclusion principle which simply states that two electrons can not be in the same state at the same time, this means as we push two atoms together the electrons will tend to shift towards the outsides of the forming bonds, leaving two positively charged hemispheres being pushed towards each other, which of course leads to repulsion. (Again for more accuracy a full quantum description is needed, and falls out of the fact that due to electrons being fermions their wave function must change sign of we swap two of them).&lt;/p&gt;&#xA;&lt;p&gt;In order to use the LJ potential you will need two constants that determine the strength of the dispersion and repulsion between your atoms/molecules, a list is available &lt;a href=&quot;https://link.springer.com/content/pdf/bbm%3A978-1-4757-1696-2%2F1.pdf&quot; rel=&quot;noreferrer&quot;&gt;in table B2 here&lt;/a&gt;.&#xA;If your two atoms are of different types the geometric mean of the parameters is and often used approximation.&lt;/p&gt;&#xA;&lt;p&gt;If dealing with ions add the Coulomb force on top of this.&lt;/p&gt;&#xA;&lt;p&gt;To convert the potential to a force simply take the negative differential. To model its effect you will probably want some sort of discrete time step algorithm such as the Verlet algorithm.&lt;/p&gt;&#xA;&lt;p&gt;More generally the question of computationally modelling exactly how atoms come together is unfortunately a very complex quantum mechanical mess, typically reserved for the fourth or fifth year of a chemistry degree. Forget about two atoms, we are unable to completely solve the problems of one atom with two electrons! While less accurate, non quantum, ways to calculate interactions do exist, these are typically not able to form or break bonds which seems to be what you are interested in. Typically uses are instead protein folding, measuring the energy of crystal structures or modding solvent molecules interacting around a solute (essentially where there are simply too many atoms and the quantum treatment is too slow) The LJ potential is probably the simplest of these.&lt;/p&gt;&#xA;" OwnerUserId="3454" LastEditorUserId="3454" LastEditDate="2021-04-26T07:54:23.713" LastActivityDate="2021-04-26T07:54:23.713" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4817" PostTypeId="2" ParentId="4811" CreationDate="2021-04-25T21:32:21.533" Score="13" Body="&lt;p&gt;How to proceed depends on how accurate you want the outcome. Throughout my answer I will provide blue buttons which demonstrate that there's entire tags in our community to address certain aspects of the simulation.&lt;/p&gt;&#xA;&lt;p&gt;What you are describing is (essentially) what we call &lt;a href=&quot;/questions/tagged/molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;molecular-dynamics&lt;/a&gt; even though you're dealing with atoms rather than molecules. In MD (molecular dynamics) simulations, we start with exactly what you have as the input: the initial substances (in your case atoms, but often they are molecules or something else), the distance between them (what we would call &amp;quot;&lt;a href=&quot;/questions/tagged/geometry&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;geometry&amp;#39;&quot; rel=&quot;tag&quot;&gt;geometry&lt;/a&gt;&amp;quot;), and the forces between them (what we would call &amp;quot;&lt;a href=&quot;/questions/tagged/forcefields&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;forcefields&amp;#39;&quot; rel=&quot;tag&quot;&gt;forcefields&lt;/a&gt;&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;A classical MD code like &lt;a href=&quot;/questions/tagged/lammps&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; rel=&quot;tag&quot;&gt;lammps&lt;/a&gt; or &lt;a href=&quot;/questions/tagged/gromacs&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gromacs&amp;#39;&quot; rel=&quot;tag&quot;&gt;gromacs&lt;/a&gt; or &lt;a href=&quot;/questions/tagged/cp2k&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cp2k&amp;#39;&quot; rel=&quot;tag&quot;&gt;cp2k&lt;/a&gt; will take care of this for you, and a software like &lt;a href=&quot;https://m3g.iqm.unicamp.br/packmol/&quot; rel=&quot;noreferrer&quot;&gt;PACKMOL&lt;/a&gt; can help you set up the initial geometry in a format that the MD software packages will understand, and since you're talking about bonding, an appropriate force-field for you might be &lt;a href=&quot;https://en.wikipedia.org/wiki/ReaxFF&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF&lt;/a&gt;. With the geometry (perhaps from PACKMOL) and force-field (perhaps ReaxFF) the classical MD software will simply evolve the system using Newton's 2nd law (F = ma) on each individual atom or molecule in your system. &lt;strong&gt;You can run the simulation after choosing a temperature, pressure, and amount of time for that you wish to simulate the system (e.g. in picoseconds), and the output will be the new geometry, at which the forces will be different (depending on the force-field you're using).&lt;/strong&gt; If your output is for example in &lt;a href=&quot;https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system&quot; rel=&quot;noreferrer&quot;&gt;SMILES&lt;/a&gt; format, most software will be able to detect whether a bond has been formed or not based on the geometry, and while this &amp;quot;classical MD&amp;quot; approach involves a lot of empirical data built into the forcefields and the deciding of whether or not bonds have been formed, and a lot of approximations (again in the forcefield and in using Newton's 2nd law rather than the time-dependent Schroedinger equation) it is enough for most cases.&lt;/p&gt;&#xA;&lt;p&gt;If you want a more accurate simulation, you could do &lt;a href=&quot;/questions/tagged/quantum-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;quantum-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;quantum-dynamics&lt;/a&gt; or semi-classical dynamics or other things instead of using Newton's 2nd law (which is classical rather than quantum-mechanical), but I don't recommend any of that for a beginner (you said your don't understand the Morse potential so I'm calling you a beginner ).  You could also do &lt;a href=&quot;/questions/tagged/ab-initio&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;ab-initio&amp;#39;&quot; rel=&quot;tag&quot;&gt;ab-initio&lt;/a&gt; calculations or &lt;a href=&quot;/questions/tagged/ab-initio-molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;ab-initio-molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;ab-initio-molecular-dynamics&lt;/a&gt; instead of empirically determined force-fields if you want to re-calculate the forces at each new geometry during the simulation, but again, I would not recommend this for a beginner. &lt;strong&gt;Once you're able to get classical MD done with an empirical force-field, then you can start considering whether or not you want to improve the accuracy of the calculation.&lt;/strong&gt; You're welcome to ask more follow-up questions if you get stuck along the way, and if you want to learn more about the Morse potential or something else, you can ask separate questions about that!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-25T21:32:21.533" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="4818" PostTypeId="2" ParentId="4810" CreationDate="2021-04-25T23:21:05.293" Score="5" Body="&lt;p&gt;You can safely use a dispersion corrected DFT method for 2D systems if your vacuum space is large enough, but there is another issue that must be explained.&lt;/p&gt;&#xA;&lt;p&gt;Most of the current dispersion correction methods such as DFT-D(Grimmes D2/D3/D4), TS, MBD, etch methods are overestimating interlayer interaction, exfoliation energies. They are not safe to use if you are trying to decide if a structure is more stable with just few meVs.&lt;/p&gt;&#xA;&lt;p&gt;If you are going to use dispersion correction anyway, I'd suggest you use &lt;a href=&quot;https://www.vasp.at/wiki/index.php/VdW-DF_functional_of_Langreth_and_Lundqvist_et_al.&quot; rel=&quot;noreferrer&quot;&gt;SCAN+rVV10&lt;/a&gt; or &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ACFDT/RPA_calculations&quot; rel=&quot;noreferrer&quot;&gt;ACFDT-RPA&lt;/a&gt;. ACFDT-RPA is considered the fifth rung method on Jacob's Ladder and is computationally very expensive. SCAN-rVV10, on the other hand, got so much attention lately due to its ACFDT-RPA like results for layered materials just with METAGGA level!&lt;/p&gt;&#xA;" OwnerDisplayName="user3455" LastEditorDisplayName="user3455" LastEditDate="2021-04-26T00:02:12.557" LastActivityDate="2021-04-26T00:02:12.557" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4819" PostTypeId="2" ParentId="4811" CreationDate="2021-04-26T09:05:34.747" Score="11" Body="&lt;p&gt;Generally speaking, most work in molecular dynamics tries to simulate how &lt;em&gt;actual&lt;/em&gt; molecules behave (i.e. quantum mechanics) and it doesn't sound like you want to go down that rabbit hole. I completely agree, but I'll begin with a disclaimer that looking up &amp;quot;molecular dynamics&amp;quot; probably won't turn up the kind of results you want.&lt;/p&gt;&#xA;&lt;p&gt;Since your comments describe wanting a simple simulation based on kinetic energy, forces and collisions (i.e. Newtonian mechanics), it will probably be more helpful to look into more general numerical simulations of Newtonian mechanics.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The type of model you are thinking of is &lt;em&gt;very&lt;/em&gt; similar to how Newtonian gravity is usually modeled. They are basically identical from a programming perspective, the only difference is that charges are signed (so you can have repulsion as well as attraction).&lt;/p&gt;&#xA;&lt;p&gt;The simplest way to approach this kind of problem is with numerical integration - set up your initial conditions &lt;span class=&quot;math-container&quot;&gt;$x(0)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$v(0)$&lt;/span&gt;, then update both little bit in each time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt;. The most basic form is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ v_x(t + \Delta t) = v_x(t) + a_x(t) \Delta t $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ x(t + \Delta t) = x(t) + v_x(t) \Delta t $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I used the x-axis here, but you can update the y and z components the same way. This is a &lt;em&gt;really&lt;/em&gt; crude numerical integrator (Euler's method) but it's a good start to understand the concept. Once you feel comfortable with it, you can use more advanced, accurate numerical integration schemes.&lt;/p&gt;&#xA;&lt;p&gt;This acceleration function is really general and you can include as many relevant terms as you see fit. To capture the force of the electric field, you can calculate the acceleration using Coulomb's law, but you can expand it with additional components (e.g. the force generated by the Lennard-Jones potential).&lt;/p&gt;&#xA;&lt;p&gt;The process to calculate acceleration is typically to calculate the net force on a particle, then divide by its mass to get its acceleration. Again, this is essentially how gravitational acceleration is calculated (so feel free to refer to that material for guidance).&lt;/p&gt;&#xA;&lt;p&gt;If you want a (really, really) simple model of molecules, you can treat them using rigid body dynamics. You start off by calculating the force on each atom in exactly the same way, then combine those into a net force and torque on each molecule. This can give you a more sophisticated charge distribution than simple spheres (though it will complicate accurate collision detection).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Collisions are more complex but can be simplified if you treat them as a collision of two spheres. At that point it's really a 2D ball collision detection problem - I'll refer to other SE questions for how to handle that.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://stackoverflow.com/questions/345838/ball-to-ball-collision-detection-and-handling?rq=1&quot;&gt;https://stackoverflow.com/questions/345838/ball-to-ball-collision-detection-and-handling?rq=1&lt;/a&gt;&#xA;&lt;a href=&quot;https://stackoverflow.com/questions/35211114/2d-elastic-ball-collision-physics&quot;&gt;https://stackoverflow.com/questions/35211114/2d-elastic-ball-collision-physics&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This can be a really tricky problem when you are dealing with discrete jumps in time (what if the particles &lt;em&gt;would have&lt;/em&gt; collided in between those steps?). Funnily enough, it helps that Euler's method is so bad - it will force you to use a small &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; so you'll catch more collisions, but you'll still miss some unless you implement some clever methods to handle intermediate collisions.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Once you've implemented these - congratulations! You've coded a simple model of classical particles. There are plenty of ways to improve it:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;This numerical integrator is terrible (see: Runge-Kutta 4 or symplectic integration)&lt;/li&gt;&#xA;&lt;li&gt;It won't support too many particles (see: Barnes-Hut or fast multipole methods)&lt;/li&gt;&#xA;&lt;li&gt;The collision detection could be dramatically improved (see: particle-particle collisions)&lt;/li&gt;&#xA;&lt;li&gt;Include simplified approximations of bonding potential (see: Max's answer, Lennard-Jones potential)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;To name a few, but you've taken your first step towards a functional model of classical charged particles. Over time you can refine this simulation, better approximate their interactions and perhaps even go down that quantum rabbit hole.&lt;/p&gt;&#xA;" OwnerUserId="3458" LastEditorUserId="3458" LastEditDate="2021-04-26T18:45:39.993" LastActivityDate="2021-04-26T18:45:39.993" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4820" PostTypeId="2" ParentId="4811" CreationDate="2021-04-26T15:02:34.193" Score="8" Body="&lt;p&gt;One thing to be absolutely clear from the beginning is that there is no &lt;em&gt;simple&lt;/em&gt; theory of the chemical bonding between two atoms. We do understand a whole lot about the physics that goes into this process, but the physical understanding is not really transformable to formulas that could be reasonably evaluated. Hell, theoretical physicists are still working on fully understanding the energy of a single hydrogen atom.&lt;/p&gt;&#xA;&lt;p&gt;Since the cutting-edge physics knowledge can not be transformed into real simulations, one always needs to draw the line somewhere and make approximations. The branch of science that deals with these approximations is called &lt;em&gt;quantum chemistry&lt;/em&gt;. Quantum chemists know a plethora of different theories and levels of abstractions, and based on the problem in hand they can set up a model. Sadly, there's also no simple recipe on how to choose a model, this all comes down to personal experience (and, in many cases, preference). So this is the second thing to consider: not only the physics can not be accurately described, often the approximations themselves require a good deal of understanding.&lt;/p&gt;&#xA;&lt;p&gt;Developing the theoretical understanding to apply proper quantum chemical method usually takes years of studying, and includes a lot of pitfalls. To avoid this, I agree with the suggestion of your friend to try using a simplified potential, such as a Morse curve.&lt;/p&gt;&#xA;&lt;p&gt;There's two main advantages to using a Morse curve as I see:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The function that describes the interaction is simple enough that you can focus on the numerical implementation as well as the physics you learn from doing the simulation;&lt;/li&gt;&#xA;&lt;li&gt;The parameters that go into the curve are experimentally determined, so you are poised to get good results even without really understanding the theory.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;It is a rather unintuitive, but nevertheless true fact that describing the movement of atoms as &lt;strong&gt;classical&lt;/strong&gt; particles moving in the potential energy field of each other is a good approximation. This means that all you have to do to get a realistic simulation is to take your two atoms, select their initial position and momenta (a lot of science goes into this step too, but I guess you can set them randomly as long as you stay close to the equilibrium energy), then solve the classical equations of motion. This is a relatively simple task to do - I usually assign this to my students as homework. A quick Google search also yielded me &lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.4943696&quot; rel=&quot;noreferrer&quot;&gt;this manuscript,&lt;/a&gt; which seems to go into a bit more technical details, but I haven't read it myself so I can't vouch for it.&lt;/p&gt;&#xA;&lt;p&gt;If, for some reason, you don't take my word for the fact that atoms can be modeled classically, you are also free to work with them as quantum mechanical object. Morse potential is also great for this task, since it's eigenvalues and eigenstates are known, so you don't have to bother with implementing anything, you can take a pen and a paper an write down the equation of motion of the system. From this, you can extract all interesting properties - the limit here is your experience with the formalism of quantum mechanics.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT:&lt;/strong&gt;&#xA;Reading through the other answers I can see that different molecular dynamics codes had been suggested. While it is always helpful to use existing tools, and they do have wonderful dynamical theories implemented, it is important to keep in mind that out-of-the-box MD usually handles chemical reactivity pretty badly, which seems to be the thing OP is interested in. Because of this, having a better potential (or Hamiltonian, or force field, of however you want to call it) is more important than having good dynamical simulation power. This being said, the popular MD tools sometimes have good &lt;strong&gt;reactive force fields&lt;/strong&gt; implemented, which could work wonderfully here, but they are usually not that straightforward to use.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastEditorDisplayName="user430" LastEditDate="2021-04-26T15:09:00.130" LastActivityDate="2021-04-26T15:09:00.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4821" PostTypeId="2" ParentId="4465" CreationDate="2021-04-26T15:17:31.840" Score="6" Body="&lt;p&gt;Before working through the equations, I'll try to explain the logic behind what they are doing. It helps to think of think of their process backwards and assume they want an expression like equation 26:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{F}_I(\mathbf{R}^N)=\langle\mathcal{F}_I(\mathbf{r}^n)\rangle_{\mathbf{R}^N} \tag{7}\label{7}$$&lt;/span&gt; where the left-hand side is the coarse-grained forces and the right is some average of the atomistic forces in the form described in equation 28 of the paper:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle \mathcal{F}_I(\mathbf{r}^n)\rangle_{\mathbf{R}^N}=\frac{\int d\mathbf{r}^n e^{-u(\mathbf{r}^n)/k_BT} \delta (\mathbf{M}_{\mathbf{R}}(r^n)-\mathbf{R}^N)\mathcal{F}_I(\mathbf{r}^n)}{\int d\mathbf{r}^n e^{-u(\mathbf{r}^n)/k_BT} \delta (\mathbf{M}_{\mathbf{R}}(r^n)-\mathbf{R}^N)}\tag{8}\label{8}$$&lt;/span&gt; As written, equation 22 already has this denominator, which is simply &lt;span class=&quot;math-container&quot;&gt;$z(\mathbf{R}^N)$&lt;/span&gt;. One way to get the numerator in the correct form would be if we could move the derivative that is acting on the delta function to instead act on the exponential. This would bring down a factor proportional to &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial u(\mathbf{r}^n)}{\partial \mathbf{r}^n}$&lt;/span&gt; and allow the product of individual delta functions of each &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}_{\mathbf{R}_{I}}$&lt;/span&gt; to be rewritten as a single delta function of the vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}_{\mathbf{R}}$&lt;/span&gt;. We could make this move via integration by parts, but we want to be moving an atomistic derivative (&lt;span class=&quot;math-container&quot;&gt;$\frac{\partial}{\partial \mathbf{r}_i}$&lt;/span&gt; ) rather than a coarse-grained derivative (&lt;span class=&quot;math-container&quot;&gt;$\frac{\partial}{\partial \mathbf{R}_I}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The expression for equation 23 (your equation \ref{6}) isn't obtained directly from the chain rule. Your equation \ref{4} is incorrect, as its not &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_I$&lt;/span&gt; that is a function of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt;, but rather the mapping operator &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}_{\mathbf{R}_{I}}$&lt;/span&gt;, which in the integral we constrain to be equal to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_I$&lt;/span&gt; through the Dirac deltas.  This subtle point means that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_I$&lt;/span&gt; is constant with respect to differentiation by &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt; and vice versa. To obtain equation 23, we compare the derivatives, which can be individually evaluated using the chain rule:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}\frac{\partial}{\partial \mathbf{R}_I} \delta \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)&amp;amp;=\delta' \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)\frac{\partial}{\partial \mathbf{R}_I}\left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)\\&amp;amp;=-\delta' \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)\end{align}\tag{9}\label{9}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}\frac{\partial}{\partial \mathbf{r}_k} \delta \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)&amp;amp;=\delta' \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)\frac{\partial}{\partial \mathbf{r}_k}\left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right)\\&amp;amp;=c_{Ik}\delta' \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right) \end{align}\tag{10}\label{10}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where we can see that a factor of &lt;span class=&quot;math-container&quot;&gt;$-\frac{1}{c_{Ik}}$&lt;/span&gt; is need to make equation \ref{10} equal to equation \ref{9}.&lt;/p&gt;&#xA;&lt;p&gt;So this gives us an atomistic derivative, but getting to equation 26 requires one more tiny correction. If we just proceeded from here, partial integration would lead to the derivative being applied to the exponential, but also to all the other dirac deltas that depend on &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_k$&lt;/span&gt;. To fix this issue, they ensure that the derivative they are taking applies to only one coarse-grained site/dirac delta by defining the set &lt;span class=&quot;math-container&quot;&gt;$\mathcal{S}_I$&lt;/span&gt; of atoms specific to site &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and corresponding coefficients (given in equation 24 of the paper) such that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sum_{j\in S_I}d_{Ij}=1\tag{11}$$&lt;/span&gt;&#xA;This allows us to rewrite the relation in equation 23 as equation 25:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial}{\partial \mathbf{R}_I} \delta \left( \sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I \right) = -\sum_{j\in S_I}\frac{d_{Ij}}{c_{Ij}} \frac{\partial }{\partial \mathbf{r}_j} \delta \left(\sum _{i\in \mathcal{I}_I} c_{Ii}\mathbf{r}_i - \mathbf{R}_I\right)\tag{12}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Shifting this sum of derivatives to the exponential via partial integration puts the numerator in a form matching equation 28 (equation \ref{8} here) with (equation 27 in the paper)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{F}_I(\mathbf{r}^n)=\sum_{j\in S_I}\frac{d_{Ij}}{c_{Ij}}\mathbf{f}_j(\mathbf{r}^n)\tag{13}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{f}_j(\mathbf{r}^n)=-\frac{\partial u(\mathbf{r}^n)}{\partial \mathbf{r}_j}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-06-01T03:07:49.517" LastActivityDate="2022-06-01T03:07:49.517" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4822" PostTypeId="2" ParentId="3629" CreationDate="2021-04-26T15:34:30.470" Score="3" Body="&lt;p&gt;An interesting, rather open-ended question. The fact that we don't really have a proper understanding of the mechanism that results in the taste, combined with the fact that taste is also different from individual to individual makes it borderline impossible to set up a good physical model for this question.&lt;/p&gt;&#xA;&lt;p&gt;However, this has never stopped cheminformaticians before. There's a vast majority of properties, more and less abstract ones, that can be correlated to known properties of the molecules (so-called descriptors). For example you will find a lot of equation that let's you characterize the efficiency of a drug molecule if you know for example its size, water/octanol solubility ratio, acidity constants and similar &lt;em&gt;descriptors&lt;/em&gt;. This problem of finding drug efficiency from these rather simple quantities shows that predicting taste should indeed be possible.&lt;/p&gt;&#xA;&lt;p&gt;So how could someone do this? First of all, since you don't have a physical/chemical theory, you need a somewhat reliable dataset - this is actually available. If you have your data ready, you should select a set of good descriptors, either by using serious statistical tests, or using your own intuition. Then you need to establish a relationship between the descriptors and the predicted properties. This step is usually done using a variety of machine learning tools.&lt;/p&gt;&#xA;&lt;p&gt;In fact, a quick Googling shows me that this approach had recently been taken up in the literature, and taste prediction of a chemical compound does exist: look &lt;a href=&quot;https://www.biorxiv.org/content/10.1101/426692v1.full.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here,&lt;/a&gt; or &lt;a href=&quot;https://www.nature.com/articles/s41598-017-12359-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; for example.&lt;/p&gt;&#xA;&lt;p&gt;I hope I explained the idea in layman's terms well enough that you can understand the point of these publications as well as search for similar ones yourself.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastActivityDate="2021-04-26T15:34:30.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4823" PostTypeId="2" ParentId="4785" CreationDate="2021-04-26T18:07:29.223" Score="5" Body="&lt;p&gt;This is actually a straightforward problem about unit conversions and careful manipulation based on the functional forms of the potential we want.&lt;/p&gt;&#xA;&lt;p&gt;To go from the Improper Torsion Parameters to the Improper Dihedral in GROMACS, simply do the following transformation on the amplitude:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\textrm{ampl}\times 4.184\times n/2~$&lt;/span&gt;&#xA;where 4.184 is the unit conversion factor from kcal to kJ, and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the number of times that torsion is repeated in the table.&lt;/p&gt;&#xA;&lt;p&gt;To go from the Torsional Angle Parameters to the GROMACS itp file, make the changes as per the ones given in the &lt;a href=&quot;https://manual.gromacs.org/documentation/2020-beta3/reference-manual/functions/bonded-interactions.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS page, equations 33&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{split}\displaystyle&#xA;\begin{eqnarray}&#xA;\displaystyle C_0&amp;amp;=&amp;amp;F_2 + \frac{1}{2} (F_1 + F_3)\tag{1}\\&#xA;\displaystyle C_1&amp;amp;=&amp;amp;\frac{1}{2} (- F_1 + 3 \, F_3)\tag{2}\\&#xA;\displaystyle C_2&amp;amp;=&amp;amp; -F_2 + 4 \, F_4\tag{3}\\&#xA;\displaystyle C_3&amp;amp;=&amp;amp;-2 \, F_3\tag{4}\\&#xA;\displaystyle C_4&amp;amp;=&amp;amp;-4 \, F_4\tag{5}\\&#xA;\displaystyle C_5&amp;amp;=&amp;amp;0\tag{6}.&#xA;\end{eqnarray}\end{split}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-04-26T18:12:37.640" LastActivityDate="2021-04-26T18:12:37.640" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4824" PostTypeId="2" ParentId="4792" CreationDate="2021-04-26T18:12:32.713" Score="3" Body="&lt;p&gt;The paper bellow can give you some insides. Using a Computer Tomography recording, they build a 3D model for computer simulation using FEM (Finite Element Method) and then do a 3D printing.&lt;/p&gt;&#xA;&lt;p&gt;The article:&lt;br /&gt;&#xA;T. Vampola, J. Horáček, V. Radolf, J. G. Švec, and A. Laukkanen, &lt;em&gt;Influence of nasal cavities on voice quality: Computer simulations and experiments&lt;/em&gt;, J. Acoust. Soc. Am. &lt;strong&gt;148&lt;/strong&gt; 3218-3231 (2020) DOI: &lt;a href=&quot;https://doi.org/10.1121/10.0002487&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1121/10.0002487&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The abstract:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Nasal cavities are known to introduce antiresonances (dips) in the&#xA;sound spectrum reducing the acoustic power ofthe voice. In this study,&#xA;a three-dimensional (3D) finite element (FE) model of the vocal tract&#xA;(VT) of one femalesubject was created for vowels [a:] and [i:] without&#xA;and with a detailed model of nasal cavities based on CT(Computer&#xA;Tomography) images. The 3D FE models were then used for analyzing the&#xA;resonances, antiresonancesand the acoustic pressure response spectra&#xA;of the VT. The computed results were compared with the measurementsof&#xA;a VT model for the vowel [a:], obtained from the FE model by 3D&#xA;printing. The nasality affects mainly the lowestformant frequency and&#xA;decreases its peak level. The results confirm the main effect of&#xA;nasalization, i.e., that soundpressure level decreases in the&#xA;frequency region of the formantsF1–F2and emphasizes the frequency&#xA;region of theformantsF3–F5around the singer’s formant cluster.&#xA;Additionally, many internal local resonances in the nasal andparanasal&#xA;cavities were found in the 3D FE model. Their effect on the acoustic&#xA;output was found to be minimal, butaccelerometer measurements on the&#xA;walls of the 3D-printed model suggested they could contribute to&#xA;structure vibra-tions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-26T18:12:32.713" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4825" PostTypeId="2" ParentId="4811" CreationDate="2021-04-26T18:50:12.847" Score="7" Body="&lt;h3&gt;The simplest possible atomic simulation: a noble gas&lt;/h3&gt;&#xA;&lt;p&gt;As explained by &lt;strong&gt;Nike Dattani&lt;/strong&gt;, what method you use depends on what you want to simulate and why. He gives you a good roadmap for what method to choose based on what you want to do.&lt;/p&gt;&#xA;&lt;p&gt;I wanted to take a different perspective. If you're familiar with writing code and want to program the simulation yourself, then the easiest atomic system that you can simulate with any reasonable accuracy is a noble gas system. Below is code I wrote in Python for a classical molecular dynamics simulation of &lt;strong&gt;liquid neon&lt;/strong&gt; (using the Lennard-Jones interaction model). The output is a multi-frame PDB file that can be visualized in software such as VMD. The system has periodic boundary conditions. (These are commonly used in simulations and may be confusing to understand at first. You can read about them. They mean that neon atoms exiting the right side of the cubic system will reenter at the left side and so forth for all six sides.)&lt;/p&gt;&#xA;&lt;p&gt;First, I set the initial positions and velocities of the atoms. And then I run 10000 simulation steps (see the MAIN SIMULATION LOOP). In each step, the net force on each neon atom is computed from the positions of all other atoms using the Lennard-Jones formula. All atoms are then moved forward in time using an approximate time-integration method (explained by the answer of &lt;strong&gt;Gumbercules&lt;/strong&gt;). Each step represents 10 fs of simulated time. The result is a three-dimensional movie of the droplet of neon (in the PDB file).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note this code is meant to be pedagogical and is &lt;em&gt;not&lt;/em&gt; optimized.&lt;/strong&gt; There are many tricks that can be used to make it run faster for systems of more atoms (and are implemented in codes like LAMMPS and Gromacs). People have spent decades optimizing these codes for molecular simulations, so you are better off using their codes for anything serious.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import math&#xA;import random&#xA;&#xA;# Parameters&#xA;num_atoms = 20&#xA;steps = 10000&#xA;out_file = 'sim_neon.pdb'&#xA;write_period = 10; # Number of steps between trajectory writing&#xA;&#xA;temper = 26.0; # en K&#xA;box = (40.0, 40.0, 40.0); # in Å&#xA;timestep = 10.0; # timestep in fs&#xA;lj_r = 3.06; # in Å for neon&#xA;lj_e = 0.08545; # in kcal/mol for neon&#xA;time_factor = 48.88821; # sqrt(angstrom^2*Da/(kcal/mol))&#xA;mass = 20.017970; # masa de neon en &#xA;boltz = 0.001987191; # kcal/mol/K&#xA;&#xA;&#xA;# Pre-computed values&#xA;dt = timestep/time_factor&#xA;dt2 = dt*dt&#xA;v0 = math.sqrt(boltz*temper/mass)&#xA;lj_r6 = lj_r**6&#xA;lj_r12 = lj_r**12&#xA;&#xA;# -0.5*l &amp;lt;= x &amp;lt;= 0.5*l&#xA;def wrap_periodic(x,l):&#xA;    imagen = math.floor(x/l)&#xA;    x -= imagen*l&#xA;    if x &amp;gt;= 0.5*l: x -= l&#xA;    return x&#xA;&#xA;def wrap3(position,box_size):&#xA;    r=[]&#xA;    for c in range(3):&#xA;        r.append(wrap_periodic(position[c],box_size[c]))&#xA;    return r&#xA;&#xA;def write_frame(output,pos,box):&#xA;    name = 'NE'&#xA;    resname = 'NE'&#xA;    chain = 'A'&#xA;    segname = 'A'&#xA;    # Write the box size&#xA;    output.write('CRYST1 %8.3f %8.3f %8.3f  90.00  90.00  90.00 P 1           1\n' % (box[0], box[1], box[2]))&#xA;    for i in range(len(pos)):&#xA;        resid = i + 1&#xA;        r = wrap3(pos[i],box)&#xA;        output.write('ATOM  %5d  %-3s %-4s%s%4d    %8.3f%8.3f%8.3f %5.2f %5.2f      %-4s\n' % (i+1, name, resname, chain, resid, r[0], r[1], r[2], 1.0, 1.0, segname))&#xA;        &#xA;    output.write('END\n')&#xA;&#xA;    &#xA;    &#xA;def interact_lj(pi,pj):&#xA;    rij = wrap3([ pj[0]-pi[0], pj[1]-pi[1], pj[2]-pi[2] ], box)&#xA;    dist2 = rij[0]*rij[0] + rij[1]*rij[1] + rij[2]*rij[2]&#xA;&#xA;    # force and potential energy for Lennard-Jones interaction (12-6)&#xA;    dist6 = dist2**3&#xA;    dist12 = dist6**2&#xA;    dist8 = dist6*dist2&#xA;    dist14 = dist12*dist2&#xA;    f_r = -12.0*lj_e*(lj_r12/dist14 - lj_r6/dist8)&#xA;    ener = lj_e*(lj_r12/dist12 - 2.0*lj_r6/dist6)&#xA;&#xA;    f=[]&#xA;    for c in range(3): f.append(f_r*rij[c])&#xA;&#xA;    # Return energy and force&#xA;    return (ener, f)&#xA;&#xA;    &#xA;def main():&#xA;    # Initial positions&#xA;    pos = []&#xA;    vel0 = []&#xA;    momentum = [0.0, 0.0, 0.0];&#xA;    d = 1.0*lj_r&#xA;    dx = -0.2*box[0]+0.5*d&#xA;    dy = -0.2*box[1]+0.5*d&#xA;    dz = -0.2*box[2]+0.5*d&#xA;    for i in range(num_atoms):&#xA;        dx += d&#xA;        if dx &amp;gt; 0.2*box[0]-0.5*d:&#xA;            dx = -0.2*box[0]+0.5*d&#xA;            dy += d&#xA;        if dy &amp;gt; 0.2*box[1]-0.5*d:&#xA;            dx = -0.2*box[0]+0.5*d&#xA;            dy = -0.2*box[1]+0.5*d&#xA;            dz += d&#xA;&#xA;        # Initial position.&#xA;        pos.append([dx, dy, dz])&#xA;        # Random velocity based on temperature&#xA;        vel0.append([random.gauss(0,v0), random.gauss(0,v0), random.gauss(0,v0)])&#xA;        # Sum the momentum&#xA;        for c in range(3):&#xA;            momentum[c] += mass*vel0[i][c]&#xA;        &#xA;    # Remove any initial net momentum&#xA;    residual_mom = [];&#xA;    for c in range(3):&#xA;        residual_mom.append(momentum[c]/num_atoms)&#xA;    for i in range(num_atoms):&#xA;        for c in range(3):&#xA;            vel0[i][c] -= residual_mom[c]/mass&#xA;&#xA;    # Infer the previous step (use Euler algorithm to start Verlet)&#xA;    pos_prev = []&#xA;    force = []&#xA;    for i in range(num_atoms):&#xA;        force.append([0.0, 0.0, 0.0])&#xA;        p = []&#xA;        for c in range(3):&#xA;            p.append(pos[i][c] - vel0[i][c]*dt)&#xA;        pos_prev.append(p)&#xA;            &#xA;    # Write the first frame&#xA;    output = open(out_file,'w')&#xA;    write_frame(output,pos,box)&#xA;&#xA;    # MAIN SIMULATION LOOP&#xA;    for step in range(steps):&#xA;        # Zero the forces&#xA;        for i in range(num_atoms):&#xA;            for c in range(3):&#xA;                force[i][c] = 0.0&#xA;           &#xA;        # Calculate interaction forces&#xA;        ener_pot = 0.0&#xA;        for i in range(num_atoms):&#xA;            for j in range(i+1,num_atoms):&#xA;                (e,f) = interact_lj(pos[i],pos[j])&#xA;                ener_pot += e&#xA;                for c in range(3):&#xA;                    force[i][c] += f[c]&#xA;                    force[j][c] -= f[c]&#xA;&#xA;        # Do Verlet integration&#xA;        pos_next = []&#xA;        for i in range(num_atoms):&#xA;            p = []&#xA;            for c in range(3):&#xA;                p.append(2.0*pos[i][c] - pos_prev[i][c] + force[i][c]/mass*dt2)&#xA;            pos_next.append(p)&#xA;            &#xA;        # Calculate the kinetic energy&#xA;        ener_kin = 0.0&#xA;        for i in range(num_atoms):&#xA;            v = []&#xA;            for c in range(3):&#xA;                v.append((pos_next[i][c] - pos_prev[i][c])/(2.0*dt))&#xA;            ener_kin += 0.5*mass*(v[0]**2 + v[1]**2 + v[2]**2)&#xA;        ener_total = ener_pot + ener_kin&#xA;        mean_temper = 2.0*ener_kin/(3*boltz*(num_atoms-1))&#xA;&#xA;                &#xA;        # Cycle the variables&#xA;        pos_prev = pos&#xA;        pos = pos_next&#xA;        &#xA;        # Write the current frame&#xA;        if step % write_period == 0:&#xA;            write_frame(output,pos,box)&#xA;            print(&amp;quot;step %9d  ener_total %9.4f  mean_temper %8.3f&amp;quot; % (step,ener_total,mean_temper))&#xA;    &#xA;    output.close()&#xA;&#xA;# main    &#xA;if __name__ == '__main__':&#xA;    main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-04-27T13:55:57.470" LastActivityDate="2021-04-27T13:55:57.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4826" PostTypeId="1" CreationDate="2021-04-26T18:52:54.530" Score="12" ViewCount="2989" Body="&lt;p&gt;I have been looking into Lennard-Jones Potential and Morse potential. And what the formulas do is to calculate a potential and the 'well depth' and 'distance at which the intermolecular potential between the two particles is zero' and these are &lt;strong&gt;known&lt;/strong&gt; input parameters. So I guess I am looking at the wrong place. Because I want to take two atoms (with they properties) and calculate bonding length and as well the energy at a given distance. How do I do that? It doesn't have to be very precise.&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;P.S. I am building a sandbox-game-like application with c++. All interaction calculations happen on fly (at least ones that can't be cached). Using 3rd party executables is therefore not an option.&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2021-04-27T14:07:42.993" LastActivityDate="2021-04-27T19:19:18.863" Title="How may I calculate the bond length between two atoms?" Tags="|ab-initio-calculations|soft-question|interatomic-potentials|" AnswerCount="6" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="4827" PostTypeId="2" ParentId="3959" CreationDate="2021-04-26T18:57:39.663" Score="3" Body="&lt;h2&gt;Machine Learning&lt;/h2&gt;&#xA;&lt;p&gt;There are several examples about how Machine Learning is been used in Quantum Chemistry. Here I bring two of them that are directly related with QM/MM calculations.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;L. Böselt, M. Thürlemann, and S. Riniker. &lt;em&gt;Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems&lt;/em&gt;, (2021) DOI: &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c01112&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1021/acs.jctc.0c01112&lt;/a&gt;, &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.0c01112&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDF&lt;/a&gt;. &lt;strong&gt;Abstract&lt;/strong&gt;: Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD simulations are computationally expensive compared to fully classical simulations as all valence electrons are treated explicitly and a self-consistent field (SCF) procedure is required. Recently, approaches have been proposed to replace the QM description with machine-learned (ML) models. However, condensed-phase systems pose a challenge for these approaches due to long-range interactions. Here, we establish a workflow, which incorporates the MM environment as an element type in a high-dimensional neural network potential (HDNNP). The fitted HDNNP describes the potential-energy surface of the QM particles with an electrostatic embedding scheme. Thus, the MM particles feel a force from the polarized QM particles. To achieve chemical accuracy, we find that even simple systems require models with a strong gradient regularization, a large number of data points, and a substantial number of parameters. To address this issue, we extend our approach to a Δ-learning scheme, where the ML model learns the difference between a reference method (density functional theory (DFT)) and a cheaper semiempirical method (density functional tight binding (DFTB)). We show that such a scheme reaches the accuracy of the DFT reference method while requiring significantly less parameters. Furthermore, the Δ-learning scheme is capable of correctly incorporating long-range interactions within a cutoff of 1.4 nm. It is validated by performing MD simulations of retinoic acid in water and the interaction between S-adenoslymethioniat and cytosine in water. The presented results indicate that Δ-learning is a promising approach for (QM)ML/MM MD simulations of condensed-phase systems.&lt;/li&gt;&#xA;&lt;li&gt;T. Morawietz, N. Artrith, &lt;em&gt;Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications&lt;/em&gt;. J Comput Aided Mol Des 35, 557–586 (2021). DOI: &lt;a href=&quot;https://doi.org/10.1007/s10822-020-00346-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1007/s10822-020-00346-6&lt;/a&gt;. &lt;a href=&quot;https://link.springer.com/content/pdf/10.1007/s10822-020-00346-6.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDF&lt;/a&gt;. &lt;strong&gt;Abstract&lt;/strong&gt;: Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in the use of machine learning (ML) methods for accelerated simulations based on a quantum mechanical (QM) description of the system. We show how recent progress in ML methods has dramatically extended the applicability range of conventional QM-based simulations, allowing to calculate industrially relevant properties with enhanced accuracy, at reduced computational cost, and for length and time scales that would have otherwise not been accessible. We illustrate the benefits of ML-accelerated atomistic simulations for industrial R&amp;amp;D processes by showcasing relevant applications from two very different areas, drug discovery (pharmaceuticals) and energy materials. Writing from the perspective of both a molecular and a materials modeling scientist, this review aims to provide a unified picture of the impact of ML-accelerated atomistic simulations on the pharmaceutical, chemical, and materials industries and gives an outlook on the exciting opportunities that could emerge in the future.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-26T18:57:39.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4828" PostTypeId="1" CreationDate="2021-04-26T19:10:19.923" Score="8" ViewCount="137" Body="&lt;p&gt;I am trying to write an itp file for the compound 1,2-diethoxyethance (CCOCCOCC).I used tinker analyze to obtain the parameter file, f2.out, which I have attached to this post. In order to check if my procedure was right, I downloaded an itp file from LigParGen (UNL_6B2B1D.itp).&lt;/p&gt;&#xA;&lt;p&gt;Every parameter in my topology file (topol.itp) matched with the parameters from LigParGen, except the dihedrals with hydrogen.&lt;/p&gt;&#xA;&lt;p&gt;The formulae I used to go from the Torsional Angle Parameters in tinker were the ones given in the GROMACS page: &lt;a href=&quot;https://manual.gromacs.org/documentation/2020-beta3/reference-manual/functions/bonded-interactions.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://manual.gromacs.org/documentation/2020-beta3/reference-manual/functions/bonded-interactions.html&lt;/a&gt;, equation block 33.&lt;/p&gt;&#xA;&lt;p&gt;If I look at the torsional angle parameters for torsion #11 in f2.out:&lt;/p&gt;&#xA;&lt;p&gt;7   2   6   9   -0.521   0/1   -2.018   180/2   1.996   0/3&lt;/p&gt;&#xA;&lt;p&gt;So, &lt;span class=&quot;math-container&quot;&gt;$F_1 = -0.521, F_2 = -2.018, F_3 = 1.996, F_4 = 0$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I use the GROMACS formula:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;c_0 = (F_2+(F_1+F_3)/2)\times4.184 = -5.358\\&#xA;c_1 = 0.5\times(-F_1+3F_3)\times 4.184 = 13.617\\&#xA;c_2 = (-F_2 + 4F_4)\times 4.184 = 8.443\\&#xA;c_3 = -2F_3\times4.184 = -16.7025\\&#xA;c_4 = -4F_4 = 0\\&#xA;c_5 = 0\\&#xA;$$&lt;/span&gt;&#xA;However, I look at the UNL file, I see that:&lt;/p&gt;&#xA;&lt;p&gt;7 2 6 9 3 1.590 4.770 0.000 -6.360 -0.000 0.000&lt;/p&gt;&#xA;&lt;p&gt;Clearly, the &lt;span class=&quot;math-container&quot;&gt;$c_i$&lt;/span&gt; don't match.&#xA;Why is this the case? Where am I going wrong? Every other torsion matches the formula given in block 33 of the gromacs manual page.&#xA;I would appreciate any advice you have.&lt;/p&gt;&#xA;&lt;p&gt;Some relevant lines from f2.out (I have added ## to show the lines I have used above):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Torsional Angle Parameters :&#xA;&#xA;                 Atom Numbers           Amplitude, Phase and Periodicity&#xA;&#xA;     1        3     1     2     6       0.468   0/3&#xA;     2        3     1     2     7       0.300   0/3&#xA;     3        3     1     2     8       0.300   0/3&#xA;     4        4     1     2     6       0.468   0/3&#xA;     5        4     1     2     7       0.300   0/3&#xA;     6        4     1     2     8       0.300   0/3&#xA;     7        5     1     2     6       0.468   0/3&#xA;     8        5     1     2     7       0.300   0/3&#xA;     9        5     1     2     8       0.300   0/3&#xA;    10        1     2     6     9       0.650   0/1  -0.250 180/2   0.670   0/3&#xA;    11        7     2     6     9      -0.521   0/1  -2.018 180/2   1.996   0/3 ##&#xA;    12        8     2     6     9      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    13        2     6     9    10       0.650   0/1  -0.250 180/2   0.670   0/3&#xA;    14        2     6     9    11      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    15        2     6     9    12      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    16        6     9    10    13      -0.550   0/1&#xA;    17        6     9    10    14       0.468   0/3&#xA;    18        6     9    10    15       0.468   0/3&#xA;    19       11     9    10    13       0.468   0/3&#xA;    20       11     9    10    14       0.300   0/3&#xA;    21       11     9    10    15       0.300   0/3&#xA;    22       12     9    10    13       0.468   0/3&#xA;    23       12     9    10    14       0.300   0/3&#xA;    24       12     9    10    15       0.300   0/3&#xA;    25        9    10    13    16       0.650   0/1  -0.250 180/2   0.670   0/3&#xA;    26       14    10    13    16      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    27       15    10    13    16      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    28       10    13    16    17       0.650   0/1  -0.250 180/2   0.670   0/3&#xA;    29       10    13    16    18      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    30       10    13    16    19      -0.521   0/1  -2.018 180/2   1.996   0/3&#xA;    31       13    16    17    20       0.468   0/3&#xA;    32       13    16    17    21       0.468   0/3&#xA;    33       13    16    17    22       0.468   0/3&#xA;    34       18    16    17    20       0.300   0/3&#xA;    35       18    16    17    21       0.300   0/3&#xA;    36       18    16    17    22       0.300   0/3&#xA;    37       19    16    17    20       0.300   0/3&#xA;    38       19    16    17    21       0.300   0/3&#xA;    39       19    16    17    22       0.300   0/3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Relvant lines from UNL_6B2B1D.itp (have added semicolons to denote the line I have mentioned above:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;   10    9    6    2        3       1.715   2.845   1.046  -5.607  -0.000   0.000&#xA;   17   16   13   10        3       1.715   2.845   1.046  -5.607  -0.000   0.000&#xA;    9    6    2    1        3       1.715   2.845   1.046  -5.607  -0.000   0.000&#xA;   16   13   10    9        3       1.715   2.845   1.046  -5.607  -0.000   0.000&#xA;    9    6    2    8        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;   16   13   10   15        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;    9    6    2    7        3       1.590   4.770   0.000  -6.360  -0.000   0.000 ;;;;;&#xA;   16   13   10   14        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;    8    2    1    4        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   15   10    9   12        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;    7    2    1    3        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;    7    2    1    4        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   20   17   16   19        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;    7    2    1    5        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   15   10    9   11        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   14   10    9   12        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;    8    2    1    3        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;    8    2    1    5        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   21   17   16   19        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   22   17   16   18        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   21   17   16   18        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   14   10    9   11        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   20   17   16   18        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   22   17   16   19        3       0.628   1.883   0.000  -2.510  -0.000   0.000&#xA;   21   17   16   13        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   15   10    9    6        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   22   17   16   13        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   20   17   16   13        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   14   10    9    6        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   18   16   13   10        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;   19   16   13   10        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;   12    9    6    2        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;   11    9    6    2        3       1.590   4.770   0.000  -6.360  -0.000   0.000&#xA;    6    2    1    5        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   13   10    9   12        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;    6    2    1    4        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;    6    2    1    3        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   13   10    9   11        3       0.979   2.937   0.000  -3.916  -0.000   0.000&#xA;   13   10    9    6        3      -1.151   1.151   0.000  -0.000  -0.000   0.000&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-11-29T21:00:31.597" LastActivityDate="2021-11-29T21:00:31.597" Title="How to go from tinker parameters to a GROMACS itp file, specifically for dihedrals?" Tags="|gromacs|tinker|" AnswerCount="0" CommentCount="4" ClosedDate="2021-11-29T19:24:56.407" ContentLicense="CC BY-SA 4.0" />
  <row Id="4829" PostTypeId="2" ParentId="4681" CreationDate="2021-04-26T19:22:36.563" Score="7" Body="&lt;h2&gt;GDIS&lt;/h2&gt;&#xA;&lt;p&gt;I think GDIS accomplishes your conditions. As it is an interface (like Material Studio) you will need to install some packages to run the tasks. As you are interested in using molecular mechanics (with UFF), I recommend to install also the &lt;a href=&quot;https://gulp.curtin.edu.au/gulp/&quot; rel=&quot;noreferrer&quot;&gt;GULP&lt;/a&gt; package, specialized in molecular dynamics and in lattice dynamics.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;GDIS is a GTK based program for the display and manipulation of&#xA;isolated molecules and periodic systems. It is in development, but is&#xA;nonetheless fairly functional.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It has the following features:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Support for several file types (CIF, BIOSYM, XYZ, XTL, MARVIN, and GULP)&lt;/li&gt;&#xA;&lt;li&gt;OpenGL rendering (requires gtkglarea)&lt;/li&gt;&#xA;&lt;li&gt;Assorted tools for visualization (measurements, ribbons, polyhedral display)&lt;/li&gt;&#xA;&lt;li&gt;Useful manipulation tools, including matrix transformations and periodic image display.&lt;/li&gt;&#xA;&lt;li&gt;Powerful surface generation and crystal morphology tools.&lt;/li&gt;&#xA;&lt;li&gt;Animation of BIOSYM and GULP trajectory files&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;GDIS also allows you to perform the following functions through other packages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Model rendering (courtesy of POVRay)&lt;/li&gt;&#xA;&lt;li&gt;Energy minimization (courtesy of GULP)&lt;/li&gt;&#xA;&lt;li&gt;Morphology calculation (courtesy of cdd)&lt;/li&gt;&#xA;&lt;li&gt;Space group processing (courtesy of SgInfo)&lt;/li&gt;&#xA;&lt;li&gt;View the Periodic Table (courtesy of GPeriodic)&lt;/li&gt;&#xA;&lt;li&gt;Load additional filetypes, such as PDB (courtesy of Babel)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Site: &lt;a href=&quot;http://gdis.seul.org/&quot; rel=&quot;noreferrer&quot;&gt;http://gdis.seul.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-26T19:22:36.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4830" PostTypeId="2" ParentId="4826" CreationDate="2021-04-26T19:40:52.107" Score="12" Body="&lt;p&gt;The only proper way to do it &lt;em&gt;ab initio&lt;/em&gt; is to calculate the energy (E) for various internuclear distances (R) and then to &lt;em&gt;approximate&lt;/em&gt; the equilibrium bond length by choosing the distance which has the lowest energy, &lt;em&gt;or&lt;/em&gt; by fitting the E(R) points to something like a Morse potential (which is decent for short-distances), Lennard-Jones potential (which is decent for large distances), or the one that I helped invent: &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential&quot; rel=&quot;noreferrer&quot;&gt;Morse/Long-range potential&lt;/a&gt; (which works for both short and long-distances because mathematically it can be a Morse potential for short distances and Lennard-Jones potential for long ones!).&lt;/p&gt;&#xA;&lt;p&gt;People have attempted to come up with &amp;quot;heuristic&amp;quot; ways to get the bond length in a more &amp;quot;direct&amp;quot; way (for example Ian Miller in some unpublished work that I can ask him to share with you), but there is not yet any successful theory that will work even qualitatively for most of the elements in the periodic table. &lt;strong&gt;You are best off with the approach described in paragraph 1, and thanks to a lot of easy-to-use free/open-source software, it's not too hard now, for example in ORCA:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! UHF OPT def2-QZVPP &#xA;%geom Scan &#xA;B 0 1 = 0.3, 1.3, 30&#xA;end&#xA;end&#xA;&#xA;* xyz 0 1&#xA;   H       -4.61685        1.79381        0.00000&#xA;   H       -4.14986        1.26166        0.00000&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;will give you the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; potential energy surface, from which you can find the equilibrium bond length as described in my firt paragraph (see &lt;a href=&quot;https://chemistry.stackexchange.com/a/145970/27342&quot;&gt;Shoubhik's answer here for more detail&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="1380" LastEditDate="2021-04-27T09:01:11.383" LastActivityDate="2021-04-27T09:01:11.383" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4831" PostTypeId="2" ParentId="4802" CreationDate="2021-04-26T19:50:44.470" Score="10" Body="&lt;p&gt;I am the person who package Avogadro2 as Flatpak. Stumble upon this thread randomly. I was not aware about this issue when I just randomly clicking on things. Not Avogadro power user, just software packager.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, we are looking into that, but will probably take some time, since there is no detail error for us to work with at the moment.&lt;/p&gt;&#xA;&lt;p&gt;I suspect that Flatpak sandboxing might prevent some communication between them, but even permitting many permissions, I still could not get it to work.&lt;/p&gt;&#xA;&lt;p&gt;For now, suggest you compile from source. The Flatpak manifest (contain instructions for Flatpak builder to build Avogadro2 from source) should give you all info on what and how to install stuff. &lt;a href=&quot;https://github.com/flathub/org.openchemistry.Avogadro2/blob/master/org.openchemistry.Avogadro2.yaml&quot; rel=&quot;noreferrer&quot;&gt;Here you can find it on GitHub&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You might also find interesting this &lt;a href=&quot;https://discuss.avogadro.cc/t/flatpak-do-molequeue-need-network-access/3492/5&quot; rel=&quot;noreferrer&quot;&gt;thread on the Avogadro forum&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Sorry for the inconvenience.&lt;/p&gt;&#xA;" OwnerUserId="3466" LastEditorUserId="5" LastEditDate="2021-04-26T19:55:47.273" LastActivityDate="2021-04-26T19:55:47.273" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4832" PostTypeId="2" ParentId="1665" CreationDate="2021-04-27T03:12:14.017" Score="4" Body="&lt;p&gt;For calculating the MP2 energy from the Hartree-Fock, as mentioned in the comments, single excitations don't contribute due to &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Brillouin%27s_theorem&quot; rel=&quot;nofollow noreferrer&quot;&gt;Brillouin's theorem&lt;/a&gt;, which states that the Hamiltonian matrix elements between the optimized HF ground state and any singly excited determinant are explicitly zero.&lt;/p&gt;&#xA;&lt;p&gt;There is no such restriction if we were to compute a perturbed energy for a DFT wavefunction, so in principle single excitations should contribute. However, when Perturbation Theory-Kohn Sham (PT-KS) was initially attempted¹, it produced spuriously low energies, with the error being traced to the single excitation energy. They attribute this to the single excitation energy being negative definite and having occupied-virtual orbital energy differences in the denominator, which tend to be underestimated by DFT.&lt;/p&gt;&#xA;&lt;p&gt;Since double hybrid DFT is already semiempirical due to the parameter fitting for the HF exchange, DFT xc, and MP2 correlation, it made sense to neglect these single excitations that had already proven problematic rather than proceed with the nonempirical form of the PT contribution.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;P. Mori-Sanchez, Q. Wu, and W. Yang, J. Chem. Phys. 123, 062204&#xA;(2005)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-04-27T03:16:27.833" LastActivityDate="2021-04-27T03:16:27.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4834" PostTypeId="1" AcceptedAnswerId="4848" CreationDate="2021-04-27T09:21:54.183" Score="10" ViewCount="139" Body="&lt;p&gt;In my bachelor thesis, I compare simulated IR-spectra computed by different basis sets. The simulated spectra from sets like cc-pVTZ and cc-pVQZ are too similar to compare them by plotting them next to each other. That's why my supervisor asks me to create a differential spectrum from these spectra. I try to subtract one from the other, but the x-axes don't align, because I scaled them with different scaling factors. When I subtract them without scaling I get a similar result. In both cases, the miss alignment of the peaks results in a jump from positive to negative values and vice versa in the differential spectra.&lt;/p&gt;&#xA;&lt;p&gt;I wonder if there is a way to create a differential spectrum from two simulated spectra computed with different basis sets.&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;To give you a better understanding of my problem I upload my spectra. All spectra are not scaled with scaling factors.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LUr3v.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LUr3v.png&quot; alt=&quot;spectrum red&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This spectrum (red) was computed with B3LYP/6-31G**.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/L2Mvr.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/L2Mvr.png&quot; alt=&quot;spectrum blue&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This spectrum (blue) was computed with B3LYP/6-311++G**.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aHZGf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aHZGf.png&quot; alt=&quot;spectrum blue-red&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That was my try to subtract the blue spectrum from the red spectrum.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tWal0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tWal0.png&quot; alt=&quot;spectrum blue/red&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here I divided the blue spectrum by the red spectrum like Cavenfish said.&lt;/p&gt;&#xA;&lt;p&gt;I want to show how much higher or lower the intensity is in the red spectrum compared to the blue spectrum. In my understanding I should have intense peaks when the difference is high and peaks with low intensity when the difference between the peak intensities is small.&lt;/p&gt;&#xA;" OwnerUserId="1682" LastEditorUserId="5" LastEditDate="2021-04-28T18:46:24.340" LastActivityDate="2021-04-29T13:57:44.653" Title="How to create a differential spectrum from two simulated spectra, calculated by two different basis sets?" Tags="|computational-chemistry|basis-sets|spectroscopy|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4836" PostTypeId="2" ParentId="4826" CreationDate="2021-04-27T11:32:37.660" Score="7" Body="&lt;p&gt;Unfortunately the answer to this question is much the same as your last one. What you are trying to do is hard. Very hard. Creating this would be PhD if not postdoc work and doing it well could well win you a nobel prize. From the comments you've made in this and your other question you do not appear to be a specialist in either physics or chemistry, and thus as much as I hat to say this this is &lt;strong&gt;not&lt;/strong&gt; something you can do at the moment. If this is really something you want to do getting a physical chemistry and/or a physics degree is the best way to go.&lt;/p&gt;&#xA;&lt;p&gt;So writing something yourself aside let's have a quick look at the practicalities. To predict bonds you need to a accurately model electron density of wavefavefunctions. You can not just use simple &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Lewis_structure&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lewis Structure&lt;/a&gt; type models. So we need &lt;em&gt;an initio&lt;/em&gt; or&#xA;DFT calculations. How practical would it be to use these in the type of program you are describing?&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately not at all. In order to predict bond lengths these systems work by optimising an initial system to find its lowest energy, performing a full quantum electronic structure calculation at each step. They are far to slow. For just one or two atoms they are reasonably fast, on my reasonably high end consumer grade PC they will run in a few seconds. The problem is that the scaling of these types of calculations is quite horrendous. The best scaling is DFT of Hartree Fock. These scale like the size of the system to the fourth power. So let's go from two molecules to say 500. Now instead of a few seconds were looking at just under 2000 years. Of course we can get round this using supercomputers, but that's hardly practical for a game (and there is still a limit, for example we can't really run full QM calculations on proteins). In order to model a visible amount of matter you would need on the order of ten to the twenty fourth power atoms. This is simply impossible to model.&lt;/p&gt;&#xA;&lt;p&gt;Using classical force fields are also an option. These are much faster but will not model bond breaking and forming. Also by the time you get to visible quantities of atoms it will still be too slow.&lt;/p&gt;&#xA;&lt;p&gt;Your best approach is probably to just forget about trying to predict bonds and instead just use a lookup table of something like A bonded to B has length X, energy Y, forms at distance Z with probability P and has probability P' of breaking. Obviously you can make A and B multi atom clusters to improve accuracy, but this will also make your lookup table much larger. Trawling the &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/csd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CSD&lt;/a&gt; would probably be the easiest way to get started.&lt;/p&gt;&#xA;&lt;p&gt;Download a large number of CIF files, these contain information about what atoms are present in a crystal, where they are and how that are bonded. It's all just text so reasonably understandable. Iterate through them and calculate the average bond lengths for atom pairs. Bond energies tend to be on the order of a few hundred kJ/mol. You can probably approximate them as &amp;lt;a few hundred kJ/mol&amp;gt; plus some function of bond length. A 1/r type dependence seems reasonable but you'll have to play with it and see what works well (Incase it's not obvious we've left accurate modeling well behind now). As for capture distance, the sum of the Van Der walls radii is probably reasonable. Bond breaking probability can probably be approximated with boltzman style terms (that is &lt;span class=&quot;math-container&quot;&gt;$P_{break} = e^\frac{-E_{bond}}{RT}$&lt;/span&gt;, again the constants  will require tuning to produce something that looks reasonable, -(E&lt;span class=&quot;math-container&quot;&gt;$_{bond}$&lt;/span&gt; - E&lt;span class=&quot;math-container&quot;&gt;$_k)$&lt;/span&gt; might work well on the numerator instead). Bond formation could be something like 1-P&lt;span class=&quot;math-container&quot;&gt;$_{break}$&lt;/span&gt;. You could also run quantum calculations for all possible pairs (or higher order clusters) of atoms or hit the literature to look up experimental bond strengths for greater accuracy.&lt;/p&gt;&#xA;&lt;p&gt;Note the heavy use of probably, this will not produce anything remotely accurate or predictive, but with a bit of tweaking could look reasonable. You'll obviously need some kind of long range interactions as well (here an LJ potential plus some numeric integration to update positions and speeds each time step as in the other answers is probably what you'll want) and the check all pairs of atoms against the table to see if they bond. Tuning this will be all about making something that looks good in your game and is something you will have to do yourself.&lt;/p&gt;&#xA;" OwnerUserId="3454" LastEditorUserId="3454" LastEditDate="2021-04-27T17:43:18.497" LastActivityDate="2021-04-27T17:43:18.497" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="4837" PostTypeId="2" ParentId="4826" CreationDate="2021-04-27T15:16:47.943" Score="6" Body="&lt;p&gt;I don't know why you need atom-atom interactions in a sandbox game. My only guess is that you want to simulate or visualize the movement of molecules of some kind in real time. If your system is large i.e. more than ~20 atoms, you have to resort to molecular dynamics to get reasonable speed. This has already been covered in detail in Max's &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4836/1380&quot;&gt;answer&lt;/a&gt;, so I will not go into that.&lt;/p&gt;&#xA;&lt;p&gt;Instead, I will try to write about how you can implement that in your code. There are already some open-source codes that have C++ API that you can use for molecular dynamics; for example, &lt;a href=&quot;https://github.com/sbischoff-ai/simple-molecular-dynamics&quot; rel=&quot;noreferrer&quot;&gt;simple-molecular-dynamics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you need a robust library for molecular dynamics (MD) simulation, you can use LAMMPS which can be compiled as a C library and called from another software (see &lt;a href=&quot;https://lammps.sandia.gov/doc/Library.html&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS library interfaces&lt;/a&gt;). However, LAMMPS is a dedicated MD code with a large number of features, so it might be overkill for your purposes.&lt;/p&gt;&#xA;&lt;p&gt;Finally, an option that I think might be the best for your purpose is to the software &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;noreferrer&quot;&gt;XTB&lt;/a&gt;. It is an open-source software that exposes a C API for running calculations. The software has the option to use polarizable GFN-FF forcefield which is quite fast. The documentation of the API and an example use is given &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/capi.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. If the API is too complicated to work, then just take the easy route and run the compiled executable with &lt;code&gt;system()&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;These are all open source codes under GNU public license, so there should be no issue with you including them in your program, as long as you acknowledge the original author.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-04-27T15:16:47.943" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4838" PostTypeId="2" ParentId="4826" CreationDate="2021-04-27T17:33:49.070" Score="5" Body="&lt;h2&gt;Get your parameters from an existing force field (UFF? ReaxFF?)&lt;/h2&gt;&#xA;&lt;p&gt;People in the molecular dynamics world use established &lt;strong&gt;force fields&lt;/strong&gt; to describe forces between different types of atoms. These force fields are mathematical functions that have &lt;strong&gt;parameters like bond lengths&lt;/strong&gt;, bond angles, dihedrals, van der Waals radii, etc. Usually these parameters are obtained by optimization to match quantum mechanical calculations or experimental data. &lt;strong&gt;Making a good force field requires decades of work!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;UFF&lt;/h2&gt;&#xA;&lt;p&gt;The simplest force field to implement that might do what you want is the &lt;a href=&quot;https://doi.org/10.1021/ja00051a040&quot; rel=&quot;nofollow noreferrer&quot;&gt;UFF&lt;/a&gt;. The mathematical form is fairly simple and each type of atom has only a few parameters. However, it's generally regarded as pretty inaccurate, but it covers almost all elements and probably would be good enough for a sandbox game.&lt;/p&gt;&#xA;&lt;p&gt;UFF is implemented in the &lt;a href=&quot;https://github.com/rdkit/rdkit/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDKit&lt;/a&gt; cheminformatics Python/C++ code. You can find the code implementing it &lt;a href=&quot;https://github.com/rdkit/rdkit/tree/b208da471f8edc88e07c77ed7d7868649ac75100/Code/ForceField/UFF&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VXj2i.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VXj2i.png&quot; alt=&quot;Some UFF parameters&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;ReaxFF&lt;/h2&gt;&#xA;&lt;p&gt;I think the best thing for your sandbox game would be to use &lt;strong&gt;ReaxFF&lt;/strong&gt;, which would allow you to represent chemical reactions with a lot of different molecules and substances. The mathematical formulas describing the interatomic potential energies in this force field are very complex (and then you have to differentiate them to get the forces). See the supporting information of &lt;a href=&quot;https://doi.org/10.1021/jp709896w&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chenoweth, van Duin and Goddard&lt;/a&gt;. Luckily there is a free and open source (GPL'd) implementation of this force field. See the &lt;a href=&quot;https://lammps.sandia.gov/&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS&lt;/a&gt; code. The implementation of the force field terms are included in the &lt;a href=&quot;https://github.com/lammps/lammps/blob/master/src/USER-REAXC/reaxc_valence_angles.cpp&quot; rel=&quot;nofollow noreferrer&quot;&gt;reaxc_*.cpp&lt;/a&gt; files. Various parameters for this force field exist and some are included with LAMMPS in the examples/reaxc directory. Parameters for compounds of H, C, O, and N can be found in the supporting information of this &lt;a href=&quot;https://doi.org/10.1021/jp108642r&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. Here's the thing though, this force field consists of hundreds of parameters. There isn't just one &amp;quot;bond length&amp;quot;, but many different values that describe bonding and nonbonded interactions in a rather complex way. There are quite a few different ReaxFF parameter sets floating around and they encode a lot of information about how chemistry works.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-04-27T19:19:18.863" LastActivityDate="2021-04-27T19:19:18.863" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4839" PostTypeId="2" ParentId="4826" CreationDate="2021-04-27T18:09:48.420" Score="3" Body="&lt;p&gt;I don't think you are looking for anything too physically correct so I think for your purposes, you can get away with a simple morse model.&lt;/p&gt;&#xA;&lt;p&gt;Consider which elements you would like to use, hopefully you can restrict it to basic organic elements such as C,O,N,H,Cl,B and consider which elements that need to be able to bond together. Prepare a table such that you can look up bonds in the format of &amp;quot;bond_distance[&amp;quot;C&amp;quot;][&amp;quot;O&amp;quot;]&amp;quot; with some bond distance calculated or looked up.  You can probably look up common bond distances or just find a structure with that type of bond and call it good enough.&lt;/p&gt;&#xA;&lt;p&gt;The problem comes when you want to model a correcting force such that you create something that looks like a morse potential.  The bottom of the well will be found at that bond_distance discussed before, but the shape of the potential is harder to determine without proper calculations.  You will need to fit a well depth and an alpha parameter which determines the well width.&lt;/p&gt;&#xA;&lt;p&gt;To be honest, if you do not need a physically correct system you might just play around with these parameters and find something that works well.  You might be able to assume all elements have similar values and it works for your game.  If you want to get more accurate numbers you may need to find a computational researcher to run a dataset for you (but this might cost you).&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-04-27T18:09:48.420" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4840" PostTypeId="2" ParentId="4826" CreationDate="2021-04-27T18:14:51.183" Score="4" Body="&lt;p&gt;The most trivial model to estimate bond lengths between two atoms is probably a simple sum of Van-der-Waals Radii. Just load a table with Van-der-Waals Radii and take the equilibrium distance for two atoms as the sum of the Van-der-Waals Radii of both atoms. This is by no means accurate but for the intention of the poster it might suffice.&lt;/p&gt;&#xA;&lt;p&gt;If this is still too complicated, you can take as a poor thumb of rule (with many exceptions in reality) that the Van der Waals radius decreases for atoms in a period and while it increases in a group and build a function that maps the atomic number to a Van der Waals radius following this rule of thumb.&lt;/p&gt;&#xA;&lt;p&gt;I endorse this of course in no way for actual quantitative scientific work. And other answers have already explained the proper scientific approach to this question which are preferable by any means.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Van_der_Waals_radius&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Van_der_Waals_radius&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2289" LastActivityDate="2021-04-27T18:14:51.183" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4841" PostTypeId="1" CreationDate="2021-04-27T23:36:20.440" Score="8" ViewCount="792" Body="&lt;p&gt;I am trying to follow the following: &lt;a href=&quot;https://peterschindler.github.io/&quot; rel=&quot;noreferrer&quot;&gt;https://peterschindler.github.io/&lt;/a&gt;&#xA;This is searchable on the internet and it shows how to use GPAW as an ASE calculator. The installation is done by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!apt install ase&#xA;!apt install gpaw&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After the installation is finished, I tried running the cell below it:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms #The Atoms object is used to define and work with atomic structure in ASE &#xA;from ase.io import read, write #The ase.io module is used to read and write crystal/molecular structure files&#xA;from gpaw import GPAW, PW #GPAW will be our main DFT calculator and PW is the plane wave mode&#xA;&#xA;h2 = Atoms('H2', [(0, 0, 0), (0, 0, 0.74)])&#xA;h2.center(vacuum=2.5)&#xA;&#xA;calc = GPAW(xc='LDA', &#xA;            kpts=(1,1,1), &#xA;            mode=PW(500), &#xA;            txt='h2.txt')&#xA;&#xA;h2.set_calculator(calc)&#xA;&#xA;print(h2.get_potential_energy())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I got the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;ModuleNotFoundError                       Traceback (most recent call last)&#xA;&amp;lt;ipython-input-6-bf8aeb87a66d&amp;gt; in &amp;lt;module&amp;gt;()&#xA;      1 from ase import Atoms #The Atoms object is used to define and work with atomic structure in ASE&#xA;      2 from ase.io import read, write #The ase.io module is used to read and write crystal/molecular structure files&#xA;----&amp;gt; 3 from gpaw import GPAW, PW #GPAW will be our main DFT calculator and PW is the plane wave mode&#xA;      4 &#xA;      5 h2 = Atoms('H2', [(0, 0, 0), (0, 0, 0.74)])&#xA;&#xA;3 frames&#xA;/usr/lib/python3/dist-packages/gpaw/utilities/__init__.py in &amp;lt;module&amp;gt;()&#xA;     11 from numpy import linalg&#xA;     12 &#xA;---&amp;gt; 13 import _gpaw&#xA;     14 from gpaw import debug&#xA;     15 &#xA;&#xA;ModuleNotFoundError: No module named '_gpaw'&#xA;&#xA;---------------------------------------------------------------------------&#xA;NOTE: If your import is failing due to a missing package, you can&#xA;manually install dependencies using either !pip or !apt.&#xA;&#xA;To view examples of installing some common dependencies, click the&#xA;&amp;quot;Open Examples&amp;quot; button below.&#xA;---------------------------------------------------------------------------&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How do I resolve this?&lt;/p&gt;&#xA;&lt;p&gt;P.S.&lt;/p&gt;&#xA;&lt;p&gt;I already tried using pip install instead. Still gives the same error.&lt;/p&gt;&#xA;&lt;p&gt;I also tried doing the test calculation found on this page: &lt;a href=&quot;https://pypi.org/project/gpaw/&quot; rel=&quot;noreferrer&quot;&gt;https://pypi.org/project/gpaw/&lt;/a&gt;: &lt;code&gt; ! gpaw test&lt;/code&gt; but it gave the same error: no module _gpaw&lt;/p&gt;&#xA;&lt;p&gt;I also tried opening the file located at: /usr/lib/python3/dist-packages/gpaw/utilities/&lt;strong&gt;init&lt;/strong&gt;.py  and although I'm not sure if it's the right thing to do, I tried replacing all keywords &lt;code&gt;_gpaw&lt;/code&gt; with just &lt;code&gt;gpaw&lt;/code&gt;but then it just results in many other errors referring to some attribute not being defined.&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="5" LastEditDate="2021-04-28T18:44:59.480" LastActivityDate="2021-04-28T18:44:59.480" Title="problem using GPAW in Google Colab" Tags="|atomic-simulation-environment|gpaw|cloud-computing|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4842" PostTypeId="5" CreationDate="2021-04-28T01:51:45.057" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-28T01:51:45.057" LastActivityDate="2021-04-28T01:51:45.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4843" PostTypeId="4" CreationDate="2021-04-28T01:51:45.057" Score="0" Body="Questions about computing in the cloud, for example with Google Colab." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-28T01:51:45.057" LastActivityDate="2021-04-28T01:51:45.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4844" PostTypeId="1" AcceptedAnswerId="4847" CreationDate="2021-04-28T09:41:21.060" Score="8" ViewCount="470" Body="&lt;p&gt;I want to perform a Molecular Docking between some ligands and a protein in different pH conditions.&lt;/p&gt;&#xA;&lt;p&gt;For this, I calculated the distance between atoms in different pH concentrations for the ligands, using the software Avogadro.&lt;/p&gt;&#xA;&lt;p&gt;I would like to do the same with my protein, that is, get the structure and its protonation state for two different pHs.&lt;/p&gt;&#xA;&lt;p&gt;Is there any software that allows me to do that?&lt;/p&gt;&#xA;" OwnerUserId="3415" LastEditorUserId="5" LastEditDate="2021-04-28T18:40:34.030" LastActivityDate="2021-04-28T18:40:34.030" Title="Chimera or other software to perform protonation states of a protein" Tags="|one-topic-per-answer|software-recommendations|proteins|docking|avogadro|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4845" PostTypeId="1" AcceptedAnswerId="4858" CreationDate="2021-04-28T10:25:42.400" Score="9" ViewCount="3432" Body="&lt;p&gt;So in my last question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4826/how-may-i-calculate-the-bond-length-between-two-atoms/4836?noredirect=1#comment9658_4836&quot;&gt;How may I calculate the bond length between two atoms?&lt;/a&gt; I mentioned that I want to use Lennard-Jones Potential to simulate atom/molecule interaction for my sandbox-game-like application. However to use this I need to know ϵ and σ which are unique for each atom pair. I think the best advised idea (performance wise) is to generate a lookup table that lists ϵ and σ for every atom pair. It would be 13,924 records, which is okay. Now the question is what software could I use to fetch this data:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H+C | ϵ = x | σ = y&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2021-04-29T19:37:03.833" LastActivityDate="2021-04-29T19:37:03.833" Title="How to create a lookup table of ϵ and σ values for Lennard-Jones Potentials?" Tags="|software-recommendations|interatomic-potentials|" AnswerCount="4" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4846" PostTypeId="2" ParentId="4845" CreationDate="2021-04-28T12:02:17.043" Score="11" Body="&lt;p&gt;My recommendation is to you look at the force-fields data from software that implement Molecular Mechanics.&lt;/p&gt;&#xA;&lt;p&gt;One example: at the Github site from the &lt;a href=&quot;https://github.com/materialsproject/pymatgen&quot; rel=&quot;noreferrer&quot;&gt;PYMATGEN&lt;/a&gt; project, you can get some library potentials files (in this case, used by &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/&quot; rel=&quot;noreferrer&quot;&gt;GULP&lt;/a&gt; package).&lt;br /&gt;&#xA;For the &lt;a href=&quot;https://core.ac.uk/download/pdf/4889535.pdf&quot; rel=&quot;noreferrer&quot;&gt;DREIDING&lt;/a&gt; force-field, you have a file with data with bond, torsions and Lennard-Jones parameters:&#xA;(note: there are other force-fields available like UFF, for example).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lennard epsilon 12 6 kcal x13 geometric all&#xA;0.0 12.5&#xA;hydrogen-bond kcal 12 10 4 taper dreiding&#xA;H_     N_3   N_3  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_2   N_3  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_2   N_2  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_R   N_3  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_R   N_2  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_R   N_R  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H_     N_1   N_3  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;...&#xA;...&#xA;...&#xA;H___b  I_    S_3  3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H___b  I_    F_   3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H___b  I_    Cl   3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H___b  I_    Br   3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;H___b  I_    I_   3741298.1709492207 593660.5362167358 105.0 115.0 &amp;amp;&#xA;  0.0 3.0 0.0 3.0 0.0 5.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-28T12:02:17.043" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4847" PostTypeId="2" ParentId="4844" CreationDate="2021-04-28T12:15:14.910" Score="8" Body="&lt;h2&gt;H++&lt;/h2&gt;&#xA;&lt;p&gt;H++ is a web service that permits to protonate your macromolecules using using different pH conditions.&lt;/p&gt;&#xA;&lt;p&gt;From its &lt;a href=&quot;http://biophysics.cs.vt.edu/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;H++ is an automated system that computes pK values of ionizable groups&#xA;in macromolecules and adds missing hydrogen atoms according to the&#xA;specified pH of the environment. Given a (PDB) structure file on&#xA;input, H++ outputs the completed structure in several common formats&#xA;(PDB, PQR, AMBER inpcrd/prmtop) and provides a set of tools for&#xA;analysis of electrostatic-related molecular properties.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-28T12:15:14.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4848" PostTypeId="2" ParentId="4834" CreationDate="2021-04-28T16:10:20.297" Score="7" Body="&lt;p&gt;If the peaks shift inconsistently, you will never fix this with scaling factors etc.  Consider if you can make a table of peak assignments with relative shifts + maximum peak heights instead.  However, you can still present either of your spectra that you have calculated (subtracted or divided) if it helps you visually present an argument.&lt;/p&gt;&#xA;&lt;p&gt;Your calculated spectra by DFT is likely not a calculated spectra, it is a calculation of excitations wavelengths and oscillator strengths.  Your visualization tool such as GaussView is likely doing gaussian broadening on things, so you can get this table of data directly from your output rather than having to look on the graph.  This method can also be used for UV-VIS (from TD-DFT) not just IR/Raman.&lt;/p&gt;&#xA;&lt;p&gt;Use whatever representation best allows for you to compare things.  Graphs are nice, but sometimes a table of deltas can be more descriptive to see trends.  You can also make a plot of experimental expectation vs DFT results like the plot below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7V9Cm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7V9Cm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-04-29T13:57:44.653" LastActivityDate="2021-04-29T13:57:44.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4849" PostTypeId="2" ParentId="4841" CreationDate="2021-04-28T16:23:38.160" Score="7" Body="&lt;p&gt;I hope it's okay to &amp;quot;self-answer&amp;quot;. So I also posted this question in the GPAW mailing list and one of the users in the mailing list who go by the handle mazay0 offered a different means of installing gpaw as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!apt install python3-mpi4py cython3 libxc-dev gpaw-data&#xA;!pip -q install gpaw pymatgen==2019.12.22&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This one worked. Although, I still don't have any idea why this one works while the shorter way doesn't. I'm not really good with bash commands (Maybe someone can explain(?)).&lt;/p&gt;&#xA;&lt;p&gt;As per the comment above, it seems other people have also stumbled on this problem. The code snippet above seemed to do the trick in my case.&lt;/p&gt;&#xA;" OwnerUserId="347" LastActivityDate="2021-04-28T16:23:38.160" CommentCount="3" CommunityOwnedDate="2021-04-28T19:42:41.270" ContentLicense="CC BY-SA 4.0" />
  <row Id="4850" PostTypeId="1" CreationDate="2021-04-28T16:46:43.557" Score="6" ViewCount="52" Body="&lt;p&gt;I want to know the protonation state of the intermembrane subunit of a protein.&lt;/p&gt;&#xA;&lt;p&gt;For that, I need to know the pH, so given that small molecules can cross the lipid bilayer, could we assume intracellular and intermembrane pH is the same?&lt;/p&gt;&#xA;" OwnerUserId="3415" LastEditorUserId="5" LastEditDate="2021-07-07T18:59:49.777" LastActivityDate="2021-07-08T06:54:47.987" Title="Can we assume that the intraceullular pH and intermembrane pH are the same when calculating the protonation state of a protein subunit?" Tags="|molecular-dynamics|proteins|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4851" PostTypeId="1" CreationDate="2021-04-28T16:59:20.440" Score="7" ViewCount="120" Body="&lt;p&gt;I want to calculate the band parity at some TRIM (time-reversal invariant momentum) point in Brillouin zone. Parity was defined as the eigenvalue of the inversion operator. My question is how to construct the matrix representation of the parity operator to calculate the band parity at a TRIM point given a crystal and the tight binding matrix?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-07-07T19:02:25.563" LastActivityDate="2021-07-07T19:02:25.563" Title="Construct a parity operator at a TRIM point?" Tags="|band-structure|mathematical-modeling|symmetry|tight-binding|brillouin-zone|" AnswerCount="0" CommentCount="4" ClosedDate="2022-01-13T02:10:07.450" ContentLicense="CC BY-SA 4.0" />
  <row Id="4852" PostTypeId="2" ParentId="4834" CreationDate="2021-04-28T19:02:29.327" Score="6" Body="&lt;p&gt;Notice that after you divided the blue spectrum's values by the red spectrum's values, you got something that looks almost exactly like the red spectrum, but with much smaller numerical values. What you may like to do now is to use a peak alignment tool such as the &lt;a href=&quot;https://www.mathworks.com/help/signal/ref/alignsignals.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;alignsignals&lt;/code&gt; function&lt;/a&gt; in MATLAB's Signal Processing Toolbox or any of the many tools for aligning peaks (there's even some programs that allow you to do this in a GUI by dragging and dropping one spectrum over the other until the peaks are aligned: if you need &lt;a href=&quot;/questions/tagged/software-recommendations&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;software-recommendations&amp;#39;&quot; rel=&quot;tag&quot;&gt;software-recommendations&lt;/a&gt; on how to do this, you can ask a new question here with that tag!).&lt;/p&gt;&#xA;&lt;p&gt;Once you have the peaks aligned, you the issue of your difference in spectra having sharp negative to positive transitions will be expected to improve significantly.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore you can &amp;quot;normalize&amp;quot; the data by dividing &lt;em&gt;&lt;strong&gt;both&lt;/strong&gt;&lt;/em&gt; spectra by the largest value in its own spectrum, which will make the tallest peak in each spectrum have the same height, but then the other peaks may be overcompensated, so whether or not you want to do this last step is up to you, and will probably depend on how satisfied you get with the result after applying my suggestion of using a peak alignment tool.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-04-28T19:02:29.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4853" PostTypeId="2" ParentId="4845" CreationDate="2021-04-29T00:26:44.840" Score="15" Body="&lt;h2&gt;Lennard-Jones combining rules&lt;/h2&gt;&#xA;&lt;p&gt;Most force fields define a single σ and ε for each atom and calculate them for combinations using &lt;a href=&quot;https://en.wikipedia.org/wiki/Combining_rules#Lorentz-Berthelot_rules&quot; rel=&quot;noreferrer&quot;&gt;Lorentz-Berthelot combining rules&lt;/a&gt;. These rules specify a arithmetic mean for σ and a geometric mean for ε:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sigma_{ij} = \frac{1}{2}\left( \sigma_i + \sigma_j \right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\epsilon_{ij} = \sqrt{\epsilon_i \epsilon_j}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This reduces the number of parameters you need. Amber and CHARMM force fields use these rules, while OPLS uses the geometric mean for σ as well as for ε.&lt;/p&gt;&#xA;&lt;p&gt;However, for force fields for organic molecules, there are usually more than one type (with different LJ σ and ε values) for each element. Below is an example that I got from &amp;quot;ffnonbonded.itp&amp;quot; of the &lt;a href=&quot;http://mackerell.umaryland.edu/charmm_ff.shtml#gromacs&quot; rel=&quot;noreferrer&quot;&gt;Gromacs format parameter files for the CHARMM force field&lt;/a&gt;. σ and ε values are in nm and kJ/mol, respectively. &lt;strong&gt;This force field is mostly intended for biomolecules and drug-like molecules and will produce meaningless results when used outside this context.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  type  atnum sigma     epsilon  (description of the atom type)&#xA;    AG  47    0.26326   19.07904 (silver metal)&#xA;    AL  13    0.26059   16.81968 (aluminum metal)&#xA;  ALG1  13    0.35636    2.71960 (aluminum tetrafluoride)&#xA;  ALSI  13    0.39200    2.71960 (aluminum in aluminosilicates)&#xA;    AU  79    0.26290   22.13336 (gold metal)&#xA;   BAR  56    0.33676    0.62760 (Ba2+ ion)&#xA; BG201   5    0.45436    0.15899 (boron in boronic acid)&#xA; BRGA1  35    0.35101    2.00832 (organic bromine bromoethane-like)&#xA; BRGA2  35    0.36527    2.21752 (organic bromine 1,1-dibromoethane)&#xA;     C   6    0.35636    0.46024 (peptide carbonyl carbon)&#xA;    CA   6    0.35501    0.29288 (phenyl carbon)&#xA;   CAD  48    0.24179    0.50208 (cadmium (II) cation)&#xA;   CAI   6    0.35458    0.30543 (aromatic C next to CPT in tryptophan)&#xA;   CAL  20    0.24357    0.50208 (Ca+2 ion)&#xA;    CC   6    0.35636    0.29288 (carbonyl C, side chains of Asn, Asp, Gln, Glu amino acids)&#xA;    CS   6    0.39200    0.46024 (thiolate carbon)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, there are different Lennard-Jones parameters based on the chemical environment of the atom. &lt;strong&gt;You will not be able to do anything useful with these parameters without putting the atoms in their expected context and implementing the other terms in the force field.&lt;/strong&gt; The closest thing to a contextless force field that exists is ReaxFF and it needs to be quite complicated to handle the complexity of atomic interactions.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-04-29T00:36:09.840" LastActivityDate="2021-04-29T00:36:09.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4854" PostTypeId="1" AcceptedAnswerId="4924" CreationDate="2021-04-29T01:06:51.147" Score="12" ViewCount="561" Body="&lt;p&gt;In order to obtain molecular dynamics (MD) simulations trajectory for computing phonon dispersion relation at finite temperature, I performed NVT MD simulation using VASP for my target system.&lt;/p&gt;&#xA;&lt;p&gt;Here is the temperature &amp;amp; total free energy profile I obtained (temperature in the unit of Kelvin, and total free energy in the unit of eV, the simulation timestep is 1 fs).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/e1Zsgl.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e1Zsgl.jpg&quot; alt=&quot;t/e profile&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Clearly, there is something wrong with my simulation, the temperature keeps fluctuating over a wide range, while the total free energy is constantly decreasing. I have optimized my structure using the standard conjugate gradient method before MD simulation (under the same accuracy level).&lt;/p&gt;&#xA;&lt;p&gt;What does this temperature &amp;amp; total free energy profile mean? Should I let it run for a bit longer until the total free energy converges?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastEditorUserId="1483" LastEditDate="2021-04-29T02:33:36.503" LastActivityDate="2021-05-03T17:21:13.097" Title="What does this temperature &amp; total free energy profile mean (obtained from VASP NVT molecular dynamics simulations)?" Tags="|density-functional-theory|vasp|molecular-dynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4855" PostTypeId="2" ParentId="4845" CreationDate="2021-04-29T04:24:56.017" Score="10" Body="&lt;p&gt;Keep the following things in mind:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The Lennard-Jones potential will not give you chemical bonding&lt;/li&gt;&#xA;&lt;li&gt;Morse parameters can only really be found for pairs of atoms that form diatomic molecules, as it does not describe polyatomic structures.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am not exactly sure what you want, as you have received almost a dozen really good ideas in your previous questions, but none of them really fits your needs. If you have the background you can probably appreciate the work of &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2004/cp/b316403a#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;this group&lt;/a&gt;, who probably do exactly what you want: take a larger amount of atoms, and just let them do their thing. However, such a simulation is not really possible in general, and it needs explicit potential energy surfaces for all the species involved.&lt;/p&gt;&#xA;&lt;p&gt;You could also use the reactive force fields as many people (including me) have already suggested. However, if you can't use them, then I don't think what you are asking is possible. I don't know about any formula that could parametrize chemical bonding between arbitrary atoms. I just don't think such thing exists.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastEditorUserId="5" LastEditDate="2021-04-29T05:14:32.703" LastActivityDate="2021-04-29T05:14:32.703" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4856" PostTypeId="1" CreationDate="2021-04-29T09:01:26.297" Score="9" ViewCount="779" Body="&lt;p&gt;Please, help me to understand the problem. I calculated the elastic constants for the beta PHB (Space group P3221 (154)), it has to show the reduced elastic constant matrix (six), however, &lt;code&gt;VASP&lt;/code&gt; calculated me 7 constants for the trigonal symmetry point group 3 (I used &lt;code&gt;IBRION=6&lt;/code&gt;, &lt;code&gt;ISIF =3&lt;/code&gt;, &lt;code&gt;NFREE=2&lt;/code&gt; and &lt;code&gt;POMIT =0.015&lt;/code&gt;). I really don't have any idea why maybe anyone has the same problem? I attached my &lt;code&gt;POSCAR&lt;/code&gt; file of beta PHB below. Thank you in advance!&lt;/p&gt;&#xA;&lt;p&gt;My &lt;code&gt;iNCAR&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PREC    = Accurate&#xA;ENCUT   = 520&#xA;EDIFF   = 1e-6&#xA;IBRION  = 6&#xA;NFREE   = 2&#xA;ISIF    = 3&#xA;ISYM    = 2&#xA;POTIM   = 0.03&#xA;NSW     = 1&#xA;ISMEAR  = 0&#xA;SIGMA   = 0.1&#xA;ALGO    = Normal&#xA;IALGO   = 48&#xA;ISTART  = 0&#xA;LPLANE  = .TRUE.&#xA;LCHARG  = .FALSE.&#xA;LWAVE   = .FALSE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My &lt;code&gt;POSCAR&lt;/code&gt; :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;betaPHB                                 &#xA;   1.00000000000000     &#xA;     9.8451449602803063   -0.0000000000135996    0.0000000000000000&#xA;    -4.9225724801283759    8.5261456395240547    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    4.7787902416829580&#xA;   C    O    H &#xA;    12     6    18&#xA;Direct&#xA;  0.4473348233320940  0.0098405107170283  0.6760647908616504&#xA; -0.0098405007170275  0.4374943136150696  0.3427314468616541&#xA;  0.5625056563849357  0.5526651466679172  0.0093981238616490&#xA;  0.3366105966273176  0.9865190814127033  0.9194381388236403&#xA;  0.0134809465872924  0.3500915452146104  0.5861048248236396&#xA;  0.6499084547853901  0.6633893733726792  0.2527714818236401&#xA;  0.3529941479661700  0.9450538256463469  0.4095367091398003&#xA;  0.0549461813536503  0.4079403223198091  0.0762033731398051&#xA;  0.5920596476801820  0.6470058220338273  0.7428700221398052&#xA;  0.2595370428953800  0.0867656901155276  0.8956333322755682&#xA;  0.9132342808844670  0.1727713537798490  0.5623000192755711&#xA;  0.8272286462201509  0.7404629871046158  0.2289666612755733&#xA;  0.4289822938404916  0.0307095082417344  0.1799468951856006&#xA;  0.9692905017582659  0.3982727945987476  0.8466135811855999&#xA;  0.6017272054012526  0.5710177061595080  0.5132802081855978&#xA;  0.2217465615454436  0.8287633736506727  0.4032896651433156&#xA;  0.1712366113493296  0.3929831728947801  0.0699563291433201&#xA;  0.6070168271052196  0.7782534534545532  0.7366229781433196&#xA;  0.5360727369674801  0.1339552292303300  0.6484256472182774&#xA;  0.8660447627696694  0.4021175007371532  0.3150923032182820&#xA;  0.5978824992628468  0.4639272630325195  0.9817589602182746&#xA;  0.5084713038609513  0.9437122479440904  0.7170050087321858&#xA;  0.0562877230559037  0.5647590559168535  0.3836716647321826&#xA;  0.4352409730831384  0.4915286961390490  0.0503383407321812&#xA;  0.2476974100787215  0.8620678575193049  0.9347039188362016&#xA;  0.1379321714807079  0.3856295665594249  0.6013706048362009&#xA;  0.6143704334405750  0.7523025749212737  0.2680372618362011&#xA;  0.1875979130778683  0.0556088716245804  0.7051825810070412&#xA;  0.9443911253754161  0.1319890374532876  0.3718492370070449&#xA;  0.8680109625467131  0.8124020869221317  0.0385159130070434&#xA;  0.1827452577710241  0.0681168022337463  0.0754234213029564&#xA;  0.9318831687662399  0.1146284565372744  0.7420901073029557&#xA;  0.8853715284627206  0.8172547562289704  0.4087567643029560&#xA;  0.3478634616025427  0.2118811433998376  0.8853498234737521&#xA;  0.7881188266001669  0.1359823182027122  0.5520165094737514&#xA;  0.8640177107972945  0.6521365383974570  0.2186831514737536&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3486" LastEditorUserId="5" LastEditDate="2021-05-02T20:41:00.710" LastActivityDate="2021-05-05T11:48:17.253" Title="Why VASP calculates the elastic constant for another trigonal space group?" Tags="|density-functional-theory|vasp|physical-properties-of-materials|polymers|elasticity|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4857" PostTypeId="2" ParentId="2344" CreationDate="2021-04-29T10:21:42.183" Score="8" Body="&lt;p&gt;The MBD-NL method is an improvement of the 'traditional' MBD (sometimes called MBD@rsSCS) approach, which is quite a bit different from the TS method you've asked. So in order to really appreciate what the MBD-NL method entails, we first need to clarify what even are MBD and TS methods. I will try to point out the main ideas, however to get a full understanding, readong the papers from the group would be beneficial. I understand you've already tried to do that, and it is also my experience that the papers from the groups are relatively unclear. I've &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/26/21/213202/meta&quot; rel=&quot;noreferrer&quot;&gt;this one to be relatively instructive&lt;/a&gt; about MBD. It could also be helpful to look at Ph.D. theses from the group as they might be more instructive, they are available &lt;a href=&quot;https://www.tcpunilu.com//phdtheses-dev&quot; rel=&quot;noreferrer&quot;&gt;here.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;The TS approach&lt;/h2&gt;&#xA;&lt;p&gt;As you are probably well aware, the idea between all of the methods to be discussed is to add van der Waals correlation energies to DFT calculations. Most DFT functionals are simply incapable of modeling van der Waals effect, because the functionals only depend on local quantities, while van der Waals enegies need nonlocal electron correlation description (think: two-point correlation functions). One way to 'fix' this issue is to calculate the dispersion energy correction coarse-grained on atoms. These atomic approaches (such as the DFT-D3 already mentioned in one of the comments) usually all lead to a similar equation&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_{\mathrm{disp}} = - \frac12 \sum_{p \neq q} \frac{C_6^{pq}}{R_6^{pq}},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;that is, you can get part of the missing correlation energy if you calculate pairwise interaction between the atoms using the &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; coefficient (you might look &lt;a href=&quot;https://chemistry.stackexchange.com/questions/27803/why-are-c6-dispersion-forces-named-c6&quot;&gt;at this question for more information here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The main question is then: what is the &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; coefficient of an atom in a molecule? Up to this point, most pairwise atomic methods agree, and this is the point where they start to diverge.The Tkatchenko-Scheffler (TS) method starts from the idea that each atom can be considered a Drude oscillator (that is, a harmonic oscillator with a charge, representing the fact that the potential energy is supposed to have a minimum at some distance from the nucleus after all, so a Taylor expansion there would yield a harmonic oscillator). This idea is relatively useful, and ideed the equation for the dispersion coefficient can also be derived from interacting harmonic oscillators (see the paper I've linked in the beginning). In order to get the &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; coefficient of a given interaction, the so-called Casimir-Polder formula is then used&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ C_6^{pq} = \frac{3}{\pi} \int_0^{\infty} \mathrm{d} \omega \alpha_p(i \omega) \alpha_q(i \omega) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So then if we have the (dipole) polarizabilities of the atoms in your system, we can calculate everything. The main insight of the TS method is the idea to calculate the polarizability of atoms in the molecules (or solid state) by re-scaling the free atomic polarizability by calculating the relative volume of the atom in the molecule to the free atomic volume&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \alpha = \frac{V}{V_{\mathrm{free}}} \alpha_{\mathrm{free}} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So then all you have to do is calculate the atomic volume in your system in question, which you can done however you want to do. Usually it's done with the so-called Hirshfeld partitioning.&lt;/p&gt;&#xA;&lt;p&gt;So, in conclusion, the TS method does the following things:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Runs a 'normal' DFT calculation to get the electron density &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;This electron density is then partitioned to atoms using for example a Hirshfeld scheme.&lt;/li&gt;&#xA;&lt;li&gt;From the partitioned electron density, you can define a 'bound' atomic volume, which, together with the known free atomic parameters, gives you the polarizability of your atoms.&lt;/li&gt;&#xA;&lt;li&gt;Modeling the atoms with harmonic oscillators to account for the frequency dependence, the Casimir-Polder integral is carried out.&lt;/li&gt;&#xA;&lt;li&gt;Having obtained the &lt;span class=&quot;math-container&quot;&gt;$C_6^{pq}$&lt;/span&gt; coefficients for all interacting pairs, you get the TS correction to the van der Waals energy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;The MBD approach&lt;/h2&gt;&#xA;&lt;p&gt;The TS approach has been a huge success in describing van der Waals energies in DFT, however it has some shortcomings: only pairwise interactions are accounted for; and when calculating the polarizability, only the local electron density is considered. Many-body dispersion was intended to fix these issues by considering non-pairwise interactions as well as long-range screening effects.&lt;/p&gt;&#xA;&lt;p&gt;The main idea is the following: you first do a TS calculation, which then basically gives you parameters for the Drude oscillator model of your atoms. Now that you've done that, you don't have to worry about the exact chemical nature of your system, you only have a bunch of interacting oscillating dipoles. These dipoles will then interact with each other, and this interaction is described by the dipole-dipole coupling tensor &lt;span class=&quot;math-container&quot;&gt;$T_{ab}(r)$&lt;/span&gt;. For more mathematical details, I suggest you look at page 8 of &lt;a href=&quot;https://arxiv.org/pdf/1608.04970.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;. In practice, the self-consistent screening is done by solving the following Dyson-like equation&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \alpha_{a,\mathrm{MBD}}(i \omega) = \alpha_{a,\mathrm{TS}}(i \omega) - \alpha_{a,\mathrm{TS}}(i \omega) T_{ab} \alpha_{b,\mathrm{MBD}}(i \omega) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we solve this equation self-consistently, we will end up with dipole polarizabilities that contain the screening from all other oscillators in your system. To get an energy, we then give a Hamiltonian, in quantum mechanical sense, for the whole system&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ H = -\frac12 \sum_n \nabla^2_n + \frac12 \sum_n \omega_n \mu_n^2 + \sum_{p \neq q} \omega_p \omega_q \mu_p T \mu_q, $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where we take &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; to be the massless normal coordinates we usually define for an ensemble of oscillators. The last term then contains a &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; interaction tensor, which describes the interaction between Drude oscillators - the exact details are found in the paper linked above.&lt;/p&gt;&#xA;&lt;p&gt;For this Hamiltonian, if we find the energies &lt;span class=&quot;math-container&quot;&gt;$\lambda_m$&lt;/span&gt;, then the correlation energy correction will be given as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_{\mathrm{corr}} = \frac12 \sum_m^{3N} \sqrt{\lambda_m}-\frac32 \sum_m^N \omega_m  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is the main idea of MBD, and this algorithm outlined here is sometimes called MBD@rsSCS, if the self-consistent screening is done in real space.&lt;/p&gt;&#xA;&lt;h2&gt;MBD-NL&lt;/h2&gt;&#xA;&lt;p&gt;So now we understand that TS puts non-interacting dipoles on the atomic position, and MBD couples these dipoles. What is MBD-NL then? In fact, it is just a small modification of the MBD scheme outlined above. As I've said, in MBD (or rather, already in TS), you need to partition the electron density to atoms in order to define atomic properties. Originally, Hirshfeld partitioning was used, which is convenient to use, and it is a mathematically nice operation, however it is not build on any real physical picture. Because of this, if you want to reproduce reference data with the TS method, you don't really get good result with the Hirshfeld scheme (look at Fig. 1. &lt;a href=&quot;https://arxiv.org/pdf/1910.03073.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Realizing these shortcomings, the MBD-NL approach set up some physical checks in the algorithm, namely&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Instead of partitioning the electron density with a Hirshfeld approach, the polarizability itself is being partitioned, based on the VV10 (Vydrov and van Voorhis) formula&lt;/li&gt;&#xA;&lt;li&gt;Some technical parameters used in the MBD implementation were re-designed, for example the cutoff functions were fit to more physical systems; and the van der Waals radii were re-evaluated based on new theoretical progress.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;However, these modifications do not affect the main MBD idea, it just makes parametrizing the Hamiltonian slightly better. So to answer your question, the methodological difference between TS and MBD-NL is approximately is the same as between TS and MBD, namely the fact that MBD contains long-range screening as well as many-body interaction terms in the correction.&lt;/p&gt;&#xA;&lt;h2&gt;Technical notes&lt;/h2&gt;&#xA;&lt;p&gt;If you are interested in trying MBD, it is already implemented in many different DFT codes (VASP,AIMS,Q-Chem,Quantum Espresso just to name a few), but a direct Python and Fortran interface is also available in a library called &lt;a href=&quot;https://github.com/libmbd/libmbd&quot; rel=&quot;noreferrer&quot;&gt;LibMBD&lt;/a&gt;. Sadly the documentation of this code is also a bit lackluster, however based on some insider information I've heard there's a technical paper being currently written on this library which will (hopefully) explain why and how it works, as well I think there's also a more practical paper being worked on that would show how to actually use it in real DFT calculations. However, I am not too sure about these information, so take it with a grain of salt.&lt;/p&gt;&#xA;" OwnerDisplayName="user430" LastActivityDate="2021-04-29T10:21:42.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4858" PostTypeId="2" ParentId="4845" CreationDate="2021-04-29T14:48:33.990" Score="9" Body="&lt;h1&gt;Universal Lennard-Jones&lt;/h1&gt;&#xA;&lt;p&gt;In addition to the answer on &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4853/30&quot;&gt;combining rules&lt;/a&gt;, there are some &amp;quot;universal&amp;quot; Lennard-Jones parameters, published by &lt;a href=&quot;https://doi.org/10.25950/962b4967&quot; rel=&quot;noreferrer&quot;&gt;Elliott and Akerson&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://openkim.org/&quot; rel=&quot;noreferrer&quot;&gt;OpenKIM&lt;/a&gt; project is an Open Knowledgebase of Interatomic Models. It's integrated into a variety of simulation codes and allows you to pick out parameters for force field and interatomic potential simulations of materials.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://doi.org/10.25950/962b4967&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Universal&amp;quot; Lennard-Jones model&lt;/a&gt; includes &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; parameters for every element:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;[It] was automatically fit using Lorentz-Berthelot mixing rules. It reproduces the dimer equilibrium separation (covalent radii) and the bond dissociation energies. It has not been fitted to other physical properties and its ability to model structures other than dimers is unknown.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;While more specific atom types will certainly produce more accurate parameters (e.g., specialized kinds of carbon atoms), these may be a useful starting point.&lt;/p&gt;&#xA;&lt;p&gt;They also have a &lt;a href=&quot;https://kliff.readthedocs.io/en/stable/auto_examples/example_lennard_jones.html#tut-lj&quot; rel=&quot;noreferrer&quot;&gt;tutorial on automated fitting&lt;/a&gt; a Lennard-Jones model if you wish to tweak the parameters.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2021-04-29T19:31:48.963" LastActivityDate="2021-04-29T19:31:48.963" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4859" PostTypeId="1" AcceptedAnswerId="4872" CreationDate="2021-04-29T19:02:29.053" Score="9" ViewCount="182" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FI76B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FI76B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's say I have a compound shown above (SMILES: &lt;code&gt;CCC(F)(F)F&lt;/code&gt;), and I want to exclude the trifluoromethyl group with SMARTS, how would I do that? I have tried &lt;code&gt;[CX4;!$(C(F)(F)F)]&lt;/code&gt; but it does not exclude &lt;code&gt;C(F)(F)F&lt;/code&gt; according to RDKit:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule = Chem.MolFromSmiles('CCC(F)(F)F')&#xA;pattern = Chem.MolFromSmarts('[CX4;!$(C(F)(F)F)]')&#xA;molecule.HasSubstructMatch(pattern) --&amp;gt; expected False, but returns True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I think the recursive portion is written incorrectly but I'm not sure how to correct it.&lt;/p&gt;&#xA;" OwnerUserId="3487" LastEditorUserId="1380" LastEditDate="2021-05-01T11:14:37.360" LastActivityDate="2021-05-01T11:55:29.483" Title="Excluding certain sp3-hybridized carbons with SMARTS" Tags="|rdkit|smiles|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4860" PostTypeId="5" CreationDate="2021-04-29T19:42:43.130" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-29T19:42:43.130" LastActivityDate="2021-04-29T19:42:43.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4861" PostTypeId="4" CreationDate="2021-04-29T19:42:43.130" Score="0" Body="Questions about or relating to SMILES (simplified molecular-input line-entry system) or related things such as SMARTS." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-04-29T19:42:43.130" LastActivityDate="2021-04-29T19:42:43.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4862" PostTypeId="1" AcceptedAnswerId="4863" CreationDate="2021-04-29T21:05:58.250" Score="5" ViewCount="3048" Body="&lt;p&gt;I'm performing a molecular docking using a trans-membrane protein and several ligands.&lt;/p&gt;&#xA;&lt;p&gt;For the first ligand, the best conformation gave a binding energy of 110 kcal/mole, being 50 kcal/mole the binding energy for the second conformation.&lt;/p&gt;&#xA;&lt;p&gt;However, these values ​​have no meaning without a frame of reference. Is there a basic rule of thumb to keep in mind to know if our results seem consistent and is it worth further investigation?&lt;/p&gt;&#xA;&lt;p&gt;This question also arises as I remember watching a tutorial where the binding energy was of -5 (?), but then again I don´t remember the units for this docking.&lt;/p&gt;&#xA;" OwnerUserId="3415" LastEditorUserId="5" LastEditDate="2021-04-29T21:11:33.273" LastActivityDate="2021-04-30T01:37:57.280" Title="How to interpret the affinity in a protein docking - ligand" Tags="|docking|proteins|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4863" PostTypeId="2" ParentId="4862" CreationDate="2021-04-30T01:37:57.280" Score="4" Body="&lt;p&gt;In a molecular docking, the affinity between a protein and a ligand is determined using what is called &lt;em&gt;score functions&lt;/em&gt;. Each docking software has its own score function. These score functions are created/modified by the software developers and, in principle, they are not interchangeable: you can not compare two docking studies made with different docking software.&lt;/p&gt;&#xA;&lt;p&gt;There are score functions (like those from &lt;a href=&quot;https://www.schrodinger.com/products/glide&quot; rel=&quot;nofollow noreferrer&quot;&gt;GLIDE&lt;/a&gt; and &lt;a href=&quot;http://vina.scripps.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AUTODOCK&lt;/a&gt;) that roughly represent the ligand/protein binding energy. In both cases, the score functions are in units of kcal/mol (or energy/mol) and the lower the value is, the better the docking is.&lt;/p&gt;&#xA;&lt;p&gt;Other score functions like ChemPLP (used in &lt;a href=&quot;https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/pharmazie-und-biochemie/teilbereich-pharmazie-pharmazeutisches-institut/pharmazeutische-chemie/pd-dr-t-exner/research/plants/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PLANTS&lt;/a&gt; and &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-discovery/components/gold/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GOLD&lt;/a&gt; software) are dimensionless and don't have a direct physical/chemical meaning. In this case, the lower values also represent the best docking.&lt;/p&gt;&#xA;&lt;p&gt;There are also docking software were the score function return positive value, where higher (positive) score represents a better docking pose.&lt;/p&gt;&#xA;&lt;p&gt;The score functions are designed in order to take into account different interactions types between the ligand and the protein. These interactions include electrostatic, hydrophobic, hydrophilic, and hydrogen interactions, for example. They can also be designed using a set of experimental binding data (&lt;span class=&quot;math-container&quot;&gt;$IC_{50}$&lt;/span&gt;, inhibition constant -&lt;span class=&quot;math-container&quot;&gt;$k_i$&lt;/span&gt;-, for example). The &lt;a href=&quot;https://www.ics.uci.edu/%7Edock/manuals/xscore1.1_manual/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;X-SCORE&lt;/a&gt; function is one that include three empirical scoring functions.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-30T01:37:57.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4864" PostTypeId="1" CreationDate="2021-04-30T04:26:01.633" Score="9" ViewCount="369" Body="&lt;p&gt;I want to calculate the band structure of a protein molecule.&#xA;How can I do it using Siesta of Gaussian?&lt;/p&gt;&#xA;&lt;p&gt;I am thinking about QE/VASP as the number of atoms are 600 and computationally it is not possible with QE/VASP.&#xA;I am also not sure whether one can calculate if using any software or not.&lt;/p&gt;&#xA;&lt;p&gt;Your suggestions will be highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="789" LastActivityDate="2021-04-30T12:25:22.260" Title="How to calculate the band structure of a protein molecule" Tags="|band-structure|molecular-modeling|gaussian|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4865" PostTypeId="1" CreationDate="2021-04-30T06:46:31.020" Score="8" ViewCount="87" Body="&lt;p&gt;I'm trying to study the electronic structure of a 1D antiferromagnetic (in which the spin is associated with copper atoms) system, via spin-polarized calculations.&lt;/p&gt;&#xA;&lt;p&gt;The unit cell dimensions are provided below (in Angstroms and degrees):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;_cell_length_a                         9.043546&#xA;_cell_length_b                         9.043546&#xA;_cell_length_c                         13.972318&#xA;_cell_angle_alpha                      106.841789&#xA;_cell_angle_beta                       106.841789&#xA;_cell_angle_gamma                      41.484879&#xA;_cell_volume                           719.729328&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;So is it necessary to perform band unfolding if I'm taking into account the magnetic unit cell&lt;/strong&gt; which consists of two primitive unit cells (one with a spin-up state associated with the Cu atom it&#xA;contains and the other with a Cu atom in the spin-down state)?&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2021-11-05T15:27:18.703" LastActivityDate="2021-11-05T15:27:18.703" Title="Band unfolding for magnetic systems" Tags="|band-structure|magnetism|transition-metals|" AnswerCount="0" CommentCount="6" ClosedDate="2021-11-06T14:20:25.337" ContentLicense="CC BY-SA 4.0" />
  <row Id="4866" PostTypeId="2" ParentId="4864" CreationDate="2021-04-30T12:09:21.217" Score="12" Body="&lt;p&gt;Band structure is a concept for periodic system only. As proteins are not periodic structures, they don't have electronic bands.&lt;/p&gt;&#xA;&lt;p&gt;The fact that you can download a PDB file (or a CIF file) with information about the crystal, it is just due to one of the ways we found to determine the protein structure that is crystalizing the protein and then using single crystal &lt;a href=&quot;https://en.wikipedia.org/wiki/X-ray_crystallography&quot; rel=&quot;noreferrer&quot;&gt;X-ray crystallography&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Very recently, a new technique called &lt;a href=&quot;https://en.wikipedia.org/wiki/Cryogenic_electron_microscopy&quot; rel=&quot;noreferrer&quot;&gt;cryogenic electron microscopy&lt;/a&gt; (cryo-EM) is been using as another way to determine the protein structure without the need of passing through the crystallization process.&lt;/p&gt;&#xA;&lt;p&gt;In case o non periodic system the molecular orbitals are used instead the electronic bands.&lt;/p&gt;&#xA;&lt;p&gt;Even molecular orbitals are difficult to calculate for proteins due the high number of atoms (more than 1000 atoms), which make impracticable to use any DFT/&lt;em&gt;ab initio&lt;/em&gt; software for the task.&lt;/p&gt;&#xA;&lt;p&gt;But, you can use semi-empirical software like &lt;a href=&quot;http://openmopac.net/&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt; that has implemented a function called &lt;a href=&quot;http://openmopac.net/manual/mozyme.html&quot; rel=&quot;noreferrer&quot;&gt;MOZYME&lt;/a&gt; to do electronic calculations for proteins. Also, you can use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fragment_molecular_orbital&quot; rel=&quot;noreferrer&quot;&gt;fragment molecular orbital&lt;/a&gt; method (FMO), implemented in software like &lt;a href=&quot;https://www.msg.chem.iastate.edu/&quot; rel=&quot;noreferrer&quot;&gt;GAMESS-US&lt;/a&gt; where you can use DFT/&lt;em&gt;ab initio&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another way is ti use Quantum Mechanic/Molecular Mechanic (QM/MM), where you divide your protein in two regions: one (smaller, few residues) where you use a quantum mechanic method and the other one (the rest of the protein) where you use molecular mechanics.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-04-30T12:25:22.260" LastActivityDate="2021-04-30T12:25:22.260" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4867" PostTypeId="1" CreationDate="2021-04-30T14:55:25.303" Score="13" ViewCount="9653" Body="&lt;p&gt;I'm new to DFT. Can you please help me to understand DOS and PDOS (projected density of states) in simple wording? I only want to know some basics of these terms and how they are linked to DFT.&lt;/p&gt;&#xA;" OwnerUserId="3491" LastEditorUserId="5" LastEditDate="2021-04-30T15:36:21.257" LastActivityDate="2021-05-02T09:32:59.960" Title="What is the difference between DOS and PDOS?" Tags="|density-functional-theory|quantum-espresso|density-of-states|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4868" PostTypeId="2" ParentId="4867" CreationDate="2021-04-30T16:39:04.567" Score="11" Body="&lt;p&gt;From the Wiki (a good starting point):&lt;/p&gt;&#xA;&lt;p&gt;DOS (Density of State):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In solid state physics and condensed matter physics, the density of&#xA;states (DOS) of a system describes the proportion of states that are&#xA;to be occupied by the system at each energy. The density of states is&#xA;defined as &lt;span class=&quot;math-container&quot;&gt;$D ( E ) = N ( E ) / V$&lt;/span&gt; , where &lt;span class=&quot;math-container&quot;&gt;$N ( E ) \delta E$&lt;/span&gt;  is the number of states in&#xA;the system of volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; whose energies lie in the&#xA;range from &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$E + \delta E$&lt;/span&gt;. It is mathematically represented as a distribution by a&#xA;probability density function, and it is generally an average over the&#xA;space and time domains of the various states occupied by the system.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;PDOS (Projected Density o States)&lt;br /&gt;&#xA;Gives the projection of particular orbital of particular atom on the density of states. So, if you sum over all the projections, you will have the total density of state, or simple, the DOS.&lt;/p&gt;&#xA;&lt;p&gt;As wrote at the beginning, both concepts are related with how the energy states are distributed. DFT is not directly related with those concepts. DFT if a quantum mechanic method used to determine the quantum properties of the system using a functional of the energy. You can use other method to calculate both DOS and PDOS.&lt;/p&gt;&#xA;&lt;p&gt;As an example, the article below, is related to calculations of projected density of state with ONETEP software:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;J. Aarons, L. G. Verga, N. D. M. Hine and C-K Skylaris. &lt;em&gt;Atom-projected and angular momentum resolved density of states in the ONETEP code&lt;/em&gt;. Electron. Struct.1 035002 (2019). DOI: &lt;a href=&quot;https://doi.org/10.1088/2516-1075/ab34f5&quot; rel=&quot;noreferrer&quot;&gt;10.1088/2516-1075/ab34f5&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-04-30T16:39:04.567" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4870" PostTypeId="2" ParentId="4867" CreationDate="2021-05-01T00:44:18.400" Score="7" Body="&lt;p&gt;Basically, the central job of KS-DFT is to solve self-consistently the following non-colinear KS equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\left[ -\dfrac{1}{2}\nabla^2+v_{ks}(\vec{r}) \right]\phi_n(\vec{r})=E_n\phi_n(\vec{r})&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$v_{ks}$&lt;/span&gt; represents the KS effective potential and &lt;span class=&quot;math-container&quot;&gt;$n=(atom, orbital, k, spin)$&lt;/span&gt; the collective quantum number of the quantum state. With this minimal knowledge, we can answer your question.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;For the density of states (DOS), we are counting the quantum number &lt;span class=&quot;math-container&quot;&gt;$n=(atom, orbital, k, spin)$&lt;/span&gt; at the energy interval &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;, in which the information related to atom, orbital, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$spin$&lt;/span&gt; are integrated.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For the partial density of states (PDOS), such as the atom-resolved PDOS (here I assume there are only two kinds of atoms: A and B), we are also counting the quantum number &lt;span class=&quot;math-container&quot;&gt;$n=(atom, orbital, k, spin)$&lt;/span&gt; at the energy interval &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;. BUT at this time, we integrate the information about &lt;span class=&quot;math-container&quot;&gt;$orbital, k$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$spin$&lt;/span&gt; for A and B respectively. Finally, we will obtain the DOS plot for A and B. With the same logic, we can plot the orbital-resolved PDOS and spin-resolved PDOS.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In summary, the total DOS is counting the quantum state &lt;strong&gt;with the full consideration of the state indexes&lt;/strong&gt; at some energy interval, and the PDOS is also counting the quantum state but &lt;strong&gt;with the partial consideration of the state indexes&lt;/strong&gt; at some energy interval.&lt;/p&gt;&#xA;&lt;p&gt;PS: When are talking about the DOS, the information related to &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; always be integrated.&lt;/p&gt;&#xA;&lt;p&gt;Related: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1791/properties-that-can-be-deduced-from-band-structure-and-dos/2396#2396&quot;&gt;Properties that can be deduced from Band structure and DOS&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-05-01T00:44:18.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4871" PostTypeId="1" AcceptedAnswerId="4874" CreationDate="2021-04-15T16:10:24.297" Score="8" ViewCount="137" Body="&lt;p&gt;Molecular vibrational states associated with an adiabatic electronic state within the Born-Oppenheimer Approximation are typically defined by doing the harmonic approximation for the potential at an equilibrium geometry. This allows us to define normal coordinates in which the harmonically approximated potential is diagonal. The vibrational Hamiltonian in these coordinates is then a sum of uncoupled 1D harmonic oscillators. This allows us to obtain vibrational states of a molecule.&lt;/p&gt;&#xA;&lt;p&gt;Is there a similar procedure to obtain molecular rotational states for polyatomic molecules? How are molecular rotational states constructed/modeled?&lt;/p&gt;&#xA;" OwnerUserId="2289" OwnerDisplayName="Hans Wurst" LastEditorUserId="5" LastEditDate="2021-05-01T19:31:51.183" LastActivityDate="2021-05-02T00:02:53.540" Title="How are molecular rotational states modeled within the Born Oppenheimer Approximation for polyatomic molecules?" Tags="|quantum-mechanics|spectroscopy|from-phys-se|born-oppenheimer-approximation|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4872" PostTypeId="2" ParentId="4859" CreationDate="2021-05-01T11:55:29.483" Score="5" Body="&lt;p&gt;Your SMARTS works.&lt;/p&gt;&#xA;&lt;p&gt;To see what a SMARTS finds, it is always a good idea to depict the result.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;&#xA;patt = Chem.MolFromSmarts('[CX4;!$(C(F)(F)F)]')&#xA;&#xA;m = Chem.MolFromSmiles('CCC(F)(F)F')&#xA;&#xA;m.GetSubstructMatches(patt)&#xA;m&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NsKnZ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NsKnZ.png&quot; alt=&quot;notrifluor&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The SMARTS should find all Carbons with 4 connections (implicit Hydrogen count), but not (C(F)(F)F).&#xA;That is why &lt;code&gt;HasSubstructMatch&lt;/code&gt; returns True.&lt;/p&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2021-05-01T11:55:29.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4873" PostTypeId="1" AcceptedAnswerId="4876" CreationDate="2021-05-01T15:19:46.770" Score="26" ViewCount="3832" Body="&lt;p&gt;I have seen a general criticism of B3LYP in computational chemistry (especially with the 6-31G* basis set).  I would like to know some of the more/less obvious problems that occur when using it and what alternatives exist for that level of theory.  I am aware that it does not include vDW interactions, so I would like to avoid discussion of that unless comparing to another functional which includes it.&lt;/p&gt;&#xA;&lt;p&gt;I am looking mainly for answers in the organic/inorganic space as this is where it is used for better or worse, but would be happy to also hear about surface catalysis for this functional.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2021-05-13T01:00:00.170" LastActivityDate="2021-05-13T01:00:00.170" Title="What does B3LYP do well? What does it do badly?" Tags="|density-functional-theory|computational-chemistry|surfaces|functional|catalysis|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4874" PostTypeId="2" ParentId="4871" CreationDate="2021-05-01T23:53:42.793" Score="7" Body="&lt;h1&gt;The Hamiltonian&lt;/h1&gt;&#xA;&lt;p&gt;Just as for vibrations we have the harmonic oscillator approximation, for rotations we often use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rigid_rotor&quot; rel=&quot;noreferrer&quot;&gt;rigid rotor&lt;/a&gt; approximation, where bond lengths are fixed. Recall the rigid-rotor Hamiltonian (in this case the kinetic energy operator) for a diatomic, which is often written as follows:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\hat{H} = \hat{T} = \frac{J_x^2}{2I_x} + \frac{J_y^2}{2I_y} + \frac{J_z^2}{2I_z},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\hat{J}} = \mathbf{\hat{r}}\times \mathbf{\hat{p}}$&lt;/span&gt; is the angular momentum operator, and &lt;span class=&quot;math-container&quot;&gt;$(I_x,I_y,I_z)$&lt;/span&gt; are the diagonal elements of the moment of inertia tensor when its written in the &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{x},\mathbf{y},\mathbf{z})$&lt;/span&gt; coordinate system..&lt;/p&gt;&#xA;&#xA;&lt;p&gt;The Hamiltonian for polyatomics can be written in the same way, but instead of using the lab-fixed frame which has the fixed axes &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{x},\mathbf{y},\mathbf{z})$&lt;/span&gt;, it's easier to use a body-fixed or molecule-fixed frame with axes that rotate along with the molecule: these axes (known as the &amp;quot;principal axes&amp;quot;) will be the eigenvectors &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a},\mathbf{b},\mathbf{c})$&lt;/span&gt; of the moment of inertia tensor, and the corresopnding eigenvalues are denoted by &lt;span class=&quot;math-container&quot;&gt;$(I_a,I_b,I_c)$&lt;/span&gt;. The Hamiltonian (kinetic energy operator) is now:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\hat{H} = \hat{T} = \frac{J_a^2}{2I_a} +\frac{J_b^2}{2I_b}+\frac{J_c^2}{2I_c}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h1&gt;The solution&lt;/h1&gt;&#xA;&lt;p&gt;As you noted correctly in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4871/how-are-molecular-rotational-states-modeled-within-the-born-oppenheimer-approxim?noredirect=1#comment9731_4871&quot;&gt;your comment&lt;/a&gt; we have three quantum numbers, let's call them &lt;span class=&quot;math-container&quot;&gt;$(j,k,m)$&lt;/span&gt;. &lt;/p&gt;&#xA;&lt;p&gt;To solve the Schroedinger equation for this Hamiltonian, we can model the wavefunction in terms of the three Euler angles:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}\psi_{jkm}(\theta,\chi,\varphi) \equiv |jkm\rangle = P_{jkm}(\theta) e^{\textrm{i}k\chi}e^{\textrm{i}m\varphi},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which has the following eigenvalues for various operators:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\hat{J}^2|jkm\rangle &amp;amp;= j(j+1)|jkm\rangle, ~~~~~\left(\hat{J}^2 \equiv \hat{J}_x^2 + \hat{J}_y^2 + \hat{J}_z^2 = \hat{J}_a^2 + \hat{J}_b^2 + \hat{J}_c^2 \right), \tag{4}\\&#xA;\hat{J}_z|jkm\rangle &amp;amp;= m|jkm\rangle,\tag{5}\\&#xA;\hat{J}_c|jkm\rangle &amp;amp;=k|jkm\rangle,\tag{6}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the following results when raising your positions on the &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; ladders respectively:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\hat{J}_{m\pm}|jkm\rangle &amp;amp;=  \sqrt{(j \mp m)(j \pm m +1)}|j,k,m\pm1\rangle, ~~~~ \hat{J}_{m\pm} \equiv \hat{J}_x \pm \textrm{i}\hat{J}_y,\tag{7}\\&#xA;\hat{J}_{k\pm}|jkm\rangle &amp;amp;=\sqrt{(j \mp k)(j \pm k +1)}|j,k\pm1,m\rangle, ~~~~~~~ \hat{J}_{k\pm} \equiv \hat{J}_a \mp \textrm{i}\hat{J}_b.\tag{8}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now with the following definitions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\alpha &amp;amp;\equiv \frac{1}{4}\left( \frac{1}{I_a} + \frac{1}{I_b}\right), \tag{9}\\&#xA;\gamma &amp;amp;\equiv \frac{1}{8}\left( \frac{1}{I_a} - \frac{1}{I_b}\right),  \tag{10}\\&#xA;\beta &amp;amp;\equiv \frac{1}{2}\left( \frac{1}{I_c} - \frac{1}{2}\left(\frac{1}{I_a} + \frac{1}{I_b}\right)\right), \tag{11}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;we can write Eq (2). in the following algebraicly equivalent form for which our wavefunction ansatz &lt;span class=&quot;math-container&quot;&gt;$|jkm\rangle$&lt;/span&gt; is already an eigenvector for many cases:&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H} = \alpha \hat{J}^2 + \beta \hat{J}_c^2 + \gamma ( {\hat{J}^+}^2 +  &#xA; {\hat{J}^-}^2 ).\tag{12}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now we're ready to  get the solutions for various cases based on the symmetry present in the molecule:&lt;/p&gt;&#xA;&lt;h3&gt;Spherical top molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{CH4}$&lt;/span&gt;):&lt;/h3&gt;&#xA;&lt;p&gt;All eigenvalues of the moment of inertia tensor will be equal to each other: &lt;span class=&quot;math-container&quot;&gt;$I_a = I_b = I_c \equiv I$&lt;/span&gt;, so we have &lt;span class=&quot;math-container&quot;&gt;$\beta = \gamma = 0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha=\frac{1}{2I}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;H &amp;amp;= \frac{ J^2}{2I} \tag{13}\\&#xA;H|jkm\rangle  &amp;amp;=  \frac{j(j+1)}{2I}|jkm\rangle  \tag{14}\\\\&#xA;E&amp;amp;= \frac{ j(j+1)}{2I}  \tag{15}\\&#xA;|\psi\rangle&amp;amp;=|jkm\rangle.\tag{16}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;h3&gt;Symmetric top molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{NH3}$&lt;/span&gt;):&lt;/h3&gt;&#xA;&lt;p&gt;Two eigenvalues of the moment of inertia tensor will be equal to each other, so if we pick them to be the ones with eigenvectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}$&lt;/span&gt; we will get &lt;span class=&quot;math-container&quot;&gt;$\gamma=0$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;H &amp;amp;= \alpha J^2 + \beta J^2_c \tag{17}\\&#xA;H|jkm\rangle  &amp;amp;= \alpha j(j+1)|jkm\rangle + \beta k^2|jkm\rangle \tag{18}\\&#xA;              &amp;amp;= \left( \alpha j(j+1) + \beta k^2 \right) |jkm\rangle \tag{19}\\\\&#xA;E&amp;amp;= \alpha j(j+1) + \beta k^2  \tag{20}\\&#xA;|\psi\rangle&amp;amp;=|jkm\rangle.\tag{21}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Linear molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt;):&lt;/h3&gt;&#xA;&lt;p&gt;The situation is the same as for spherical tops. &lt;/p&gt;&#xA;&lt;h3&gt;Asymmetric top molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;):&lt;/h3&gt;&#xA;&lt;p&gt;Diagonalizing the matrix is not as simple, but it's not too bad if you use &lt;span class=&quot;math-container&quot;&gt;$J_\pm$&lt;/span&gt;  to build the Hamiltonian for each &lt;span class=&quot;math-container&quot;&gt;$(j,m)$&lt;/span&gt;  pair and for &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$-j$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;General non-symmetric molecules (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{CHBrClF}$&lt;/span&gt;):&lt;/h3&gt;&#xA;&lt;p&gt;The eigenvalues and wavefunctions would typically be obtained by numerically diagonalizing submatrices of size &lt;span class=&quot;math-container&quot;&gt;$(2j+1)$&lt;/span&gt; × &lt;span class=&quot;math-container&quot;&gt;$(2j+1)$&lt;/span&gt; .&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h1&gt;Some helpful resources:&lt;/h1&gt;&#xA;&lt;p&gt;Much of what I wrote here can be found &lt;a href=&quot;http://scienide2.uwaterloo.ca/%7Enooijen/Chem356/Polyatomic%20Harmonic%20Oscillator.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, and I also very much liked &lt;a href=&quot;https://cefrc.princeton.edu/sites/cefrc/files/Files/2015%20Lecture%20Notes/Hanson/pLecture4.pdf&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; and for the relation to the diatomic case: &lt;a href=&quot;https://ocw.mit.edu/courses/chemistry/5-61-physical-chemistry-fall-2007/lecture-notes/lecture17.pdf&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;http://hyperphysics.phy-astr.gsu.edu/hbase/molecule/rotrig.html&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T00:02:53.540" LastActivityDate="2021-05-02T00:02:53.540" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4875" PostTypeId="2" ParentId="4873" CreationDate="2021-05-02T02:01:47.343" Score="22" Body="&lt;p&gt;B3LYP is still a decent functional at its level of theory (single-hybrid functional), but you're right that there's a general criticism of it, which I largely hear in the form of people saying things like &amp;quot;all they did was B3LYP/6-31G*&amp;quot; to criticize non-experts that blindly use this combination which became the &amp;quot;default&amp;quot; in chemistry for non-expert groups for many years.&lt;/p&gt;&#xA;&lt;h3&gt;Some history about B3LYP/6-31G*&lt;/h3&gt;&#xA;&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1252/5&quot;&gt;Susi Lehtola said here&lt;/a&gt;, BLYP/6-31G* &lt;strong&gt;performed better than wavefunction-based methods for equilibrium geometries, dipole moments, harmonic vibrational frequencies and atomization energies&lt;/strong&gt; in &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.464906&quot; rel=&quot;noreferrer&quot;&gt;this 1993 paper&lt;/a&gt;. A co-author of that paper (John Pople) was the original author of Gaussian70 and would soon get the Nobel Prize, so it was a widely seen paper, and then &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/j100096a001&quot; rel=&quot;noreferrer&quot;&gt;a year later&lt;/a&gt; Mike Frisch (currently President of Gaussian) did a comparison of BLYP to B3LYP and LSDA again with 6-31G* (and one more basis set), &lt;strong&gt;which led to the B3LYP/6-31G* combination becoming widely adopted&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;But wavefunction-based methods have improved&lt;/h3&gt;&#xA;&lt;p&gt;In the above paragraph &amp;quot;wavefunction-based methods&amp;quot; referred only to MP2 and QCISD (it was 1993 after all) and if they could compare to CCSD(T) which became in the 2000s known  as the &amp;quot;gold standard of quantum chemistry&amp;quot; for about a decade, they wouldn't have found found BLYP/6-31G* or B3LYP/6-31G* to perform better. Much of what people use B3LYP/6-31G* for can be done very fast with CCSD(T)/cc-pVTZ in 2021 &lt;strong&gt;&lt;em&gt;if people just knew that, so many people find it cringeworthy when B3LYP/6-31G&lt;/em&gt; is still used.&lt;/strong&gt;*&lt;/p&gt;&#xA;&lt;h3&gt;One should consider more than one functional&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1562/5&quot;&gt;TAR86 pointed out here&lt;/a&gt;, that it's important to evaluate more than one functional for the set of molecules you're dealing with, or to look at benchmark studies which have already done this, and &lt;em&gt;most of the time&lt;/em&gt; when you see people using B3LYP/6-31* &lt;em&gt;&lt;strong&gt;they are using it  with no justification apart from it being all they know.&lt;/strong&gt;&lt;/em&gt;  This means that people can again be getting worse results than what they could have got with the same cost, simply because they didn't do a bit more research.&lt;/p&gt;&#xA;&lt;h3&gt;Functionals have also improved (answering the call for &amp;quot;alternatives&amp;quot;)&lt;/h3&gt;&#xA;&lt;p&gt;As the OP (Tristan Maxson) &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3609/5&quot;&gt;said here&lt;/a&gt;, B3LYP/6-31G* is old and there's now better options. As &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;mentioned by me here&lt;/a&gt;, a comparison of 47 functionals (2 LDA, 14 GGA, 3 meta-GGA, 23 Hybrid, 5 Double Hybrid) in an enormous dataset &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2011/cp/c0cp02984j/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;was done by Goerigk and Grimme&lt;/a&gt;. You can see in the figure below that &lt;strong&gt;B3LYP is still a very decent functional&lt;/strong&gt;, standing in the &amp;quot;middle&amp;quot; of the pack of other functionals at the same level of theory (single-hybrid), having an overall average error against CCSD(T)/experiment of slightly less than 4 kcal/mol while other single-hybrids can have average errors of a bit more than 2 kcal/mol in the best case and almost 5 kcal/mol in the worse case.&#xA;&lt;em&gt;&lt;strong&gt;But you can indeed see several other functionals at the same level of theory of B3LYP:&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/v6BBG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/v6BBG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;So even if we want to blindly use just one functional as a black-box&lt;/strong&gt;&lt;/em&gt; (without comparing against other functionals or looking for a benchmark study on the class of molecules we're dealing with), things like M06 and PW6B95 seem to work better better on average than B3LYP overall on a comprehensive dataset like the one used in the study above. They didn't use 6-31G* because some of the elements included in the dataset don't have 6-31G* sets available, but they did say that (aug-)def2-SV(P), which they did use, is usually comparable to 6-31G*.&lt;/p&gt;&#xA;&lt;h3&gt;Specific problems with B3LYP&lt;/h3&gt;&#xA;&lt;p&gt;The last section above answered your call for &amp;quot;alternatives at the same level of theory&amp;quot; so now I'd like to answer your call for:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;some of the more/less obvious problems that occur when using it&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The figure below, also from the same paper as the above figure, shows that B3LYP is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Quite good&lt;/strong&gt; compared to other single-hybrids &lt;strong&gt;for basic properties&lt;/strong&gt; (in this paper examples included atomization energies,&#xA;electron affinities, ionization potentials, proton affinities, SIE&#xA;related problems, barrier heights)&lt;/li&gt;&#xA;&lt;li&gt;A bit &lt;strong&gt;worse&lt;/strong&gt; but still &amp;quot;in the middle of the pack&amp;quot; &lt;strong&gt;for non-covalent interactions&lt;/strong&gt; (in this paper: water clusters, conformational energies, and inter- and intramolecular London-dispersion interactions)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;One of the worst overall for reaction energies&lt;/strong&gt; (in this paper examples included isomerizations, Diels–Alder reactions, ozonolyses, reactions&#xA;involving alkaline metals)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ck6ho.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ck6ho.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So &lt;strong&gt;reaction energies&lt;/strong&gt; would be one of the places to be careful about using B3LYP, in addition to RESP (Restrained Electrostatic Potential) calculations as noted in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1133/5&quot;&gt;B. Kelly's warning&lt;/a&gt; that it will cause partial charges to be added implicitly (there's a lot more details in the original answer though), and for other things such as in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4873/what-does-b3lyp-do-well-do-badly#comment9729_4873&quot;&gt;Andrew Rosen's comment&lt;/a&gt; which I would be thrilled to see turned into an answer if time permits.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="794" LastEditDate="2021-05-02T07:20:56.957" LastActivityDate="2021-05-02T07:20:56.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4876" PostTypeId="2" ParentId="4873" CreationDate="2021-05-02T03:28:28.173" Score="20" Body="&lt;p&gt;I think this review¹ by Head-Gordon is a useful supplement to Nike's answer. Its combines a review of functional development, a benchmarking of various functionals, and an explanation of the design process for the &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97 functionals. Its also open access, so its a great resource if you are interested in DFT functionals in general.&lt;/p&gt;&#xA;&lt;p&gt;They benchmarked 200 DFT functionals on a variety of different tests focused on isomerization energies (I), barrier heights (BH), thermochemistry (TC), nonconvalent dimers/clusters (NCD/NCC), and equilibrium bond energies/lengths (EBE/EBL). The datasets were also classified with a suffix indicating whether they are easy (E) or difficult (D) examples.&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/dpeWr.jpg&quot; alt=&quot;DFT functional comparison&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note the coloring of each cell gives a rough sense of how the functional compares among all 200 functionals tested, rather than just those in the table. The full list of functionals, along with the ranking/RMSD of each functional on each dataset is given in the paper. Even among the whole set, where many of the other functionals also don't explicitly account for dispersion, B3LYP tends to be in the bottom quartile for most of the datasets.&lt;/p&gt;&#xA;&lt;p&gt;What you can see is that B3LYP does fairly poorly, notably for isomerization energies and equilibrium bond length/energy. So B3LYP on its own generally doesn't do great across a wide variety of problems. However, if one is able to include dispersion corrections, in this case D3(BJ), B3LYP's performance is much improved, becoming basically on par with &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D. The only notable exception is isomerization energies where it still seems to struggle.&lt;/p&gt;&#xA;&lt;p&gt;I should also note that all the calculations were done with the def2-QZVPPD basis set and a (99,590) DFT integration grid (99 radial shells with 590 points per shell). The use of a large basis and accurate grid should make the comparison as much as possible about relative capabilities of the functionals, rather than basis set completeness. On the flip side, as has been mentioned in other answers, if you are working with certain smaller basis sets, you may obtain more favorable results than expected due to error cancellation.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;N. Mardirossian &amp;amp; M. Head-Gordon. MOLECULAR PHYSICS, 2017&#xA;VOL. 115, NO. 19, 2315-2372&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-05-03T20:47:33.917" LastActivityDate="2021-05-03T20:47:33.917" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4877" PostTypeId="1" CreationDate="2021-05-02T04:10:57.257" Score="8" ViewCount="126" Body="&lt;p&gt;In the study of 2D condensed matter systems, I have seen several kinds of band degeneracies. I call 'bands' the eigenvalues to the time-independent Schrodinger equation, solved over 2D k-space. By 'degenerate', I refer to when the eigenvalues to one eigenvector are the same as the eigenvalues of a different eigenvector at the same k-space point.&lt;/p&gt;&#xA;&lt;p&gt;I have seen bands that are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;degenerate at certain high symmetry points (such as graphene);&lt;/li&gt;&#xA;&lt;li&gt;'fully gapped' (with no degeneracies whatsoever);&lt;/li&gt;&#xA;&lt;li&gt;completely degenerate (such as the 4-band Kane-Mele model, where each pair of bands is degenerate everywhere over k-space);&lt;/li&gt;&#xA;&lt;li&gt;degenerate at non-high-symmetry points (degenerate in such ways that make them    'accidental degeneracies'?)&lt;/li&gt;&#xA;&lt;li&gt;degenerate at certain high symmetry areas (similar to 4., but also includes lines and patches of k-space)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h3&gt;My question is:&lt;/h3&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which of the above are relevant to topological effects (or coincide with those)?&lt;/strong&gt; I have seen 1-3 above pretty often, but am having trouble understanding 4 (and 5). You only need to list one to post an answer, see &lt;a href=&quot;/questions/tagged/one-topic-per-answer&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;one-topic-per-answer&amp;#39;&quot; rel=&quot;tag&quot;&gt;one-topic-per-answer&lt;/a&gt;. If there's another type of degeneracy relevant to topological effects that I didn't list above, you can explain that one too.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;Consider the attached picture, which is a random band diagram for &lt;span class=&quot;math-container&quot;&gt;$MoS_2$&lt;/span&gt; that I found online. To my understanding, people do not care about degenercies of the kind I have circled in red (i.e. of type 4 in the list above). This is because they tend to care about the physics around the 'valleys' indicated by red arrows (i.e. fully gapped, no degeneracies). They usually do this by working with an effective Hamiltonian focusing on a subspace of the complete Hilbert space. Then, for topological reasons, they might treat the entire 'bundle' of wavefunctions above and below the Fermi level (indicated by red arrows), regardless of the degeneracies circled in red.&lt;/p&gt;&#xA;&lt;p&gt;However, it seems suspicious to me that the 'degeneracies' circled are assumed to not play a role in topological properties. To paint a naive/vague picture, consider Haldane's interpretation of topologically significant degeneracies of a 2-level model as Dirac strings/wormholes that connect two otherwise-separate genus-1 tori into a genus-3 torus (second picture, taken from &lt;a href=&quot;https://physics.princeton.edu//%7Ehaldane/talks/dirac.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;these slides&lt;/a&gt;). So, I am looking for consolation/clarification on why we can simply ignore degeneracies that occur outside the regions of interest, in general topological concerns. Or if anyone sees my overall confusion, I would appreciate any guiding remarks.&lt;/p&gt;&#xA;&lt;p&gt;Note: I am more concerned about the type of 2D topology that deals with Berry-like quantities (Berry phase, curvature, Chern / valley Chern, etc).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Gph1A.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Gph1A.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Kzj6B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Kzj6B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="7" LastEditDate="2022-08-23T22:19:49.070" LastActivityDate="2022-08-23T22:19:49.070" Title="What are some types of topologically-relevant band degeneracies in contemporary 2D condensed matter research?" Tags="|band-structure|one-topic-per-answer|condensed-matter|topological-insulators|berry-phase|" AnswerCount="0" CommentCount="16" ClosedDate="2022-08-23T22:20:15.177" ContentLicense="CC BY-SA 4.0" />
  <row Id="4879" PostTypeId="5" CreationDate="2021-05-02T20:24:28.023" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:24:28.023" LastActivityDate="2021-05-02T20:24:28.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4880" PostTypeId="4" CreationDate="2021-05-02T20:24:28.023" Score="0" Body="Questions about modeling or theoretical/computational values for physical properties of materials such as ductility, Young's modulus, malleability, conductivity, specific heat capacity, density, etc. " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:24:28.023" LastActivityDate="2021-05-02T20:24:28.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4881" PostTypeId="5" CreationDate="2021-05-02T20:27:40.887" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:27:40.887" LastActivityDate="2021-05-02T20:27:40.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4882" PostTypeId="4" CreationDate="2021-05-02T20:27:40.887" Score="0" Body="Questions about molecular or lattice geometry." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:27:40.887" LastActivityDate="2021-05-02T20:27:40.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4883" PostTypeId="5" CreationDate="2021-05-02T20:28:39.503" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:28:39.503" LastActivityDate="2021-05-02T20:28:39.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4884" PostTypeId="4" CreationDate="2021-05-02T20:28:39.503" Score="0" Body="Questions about potentiology." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:28:39.503" LastActivityDate="2021-05-02T20:28:39.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4885" PostTypeId="5" CreationDate="2021-05-02T20:29:44.647" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:29:44.647" LastActivityDate="2021-05-02T20:29:44.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4886" PostTypeId="4" CreationDate="2021-05-02T20:29:44.647" Score="0" Body="Questions requesting for an input file or part of an input file in order to do a certain thing in a specific software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:29:44.647" LastActivityDate="2021-05-02T20:29:44.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4887" PostTypeId="5" CreationDate="2021-05-02T20:30:09.910" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:09.910" LastActivityDate="2021-05-02T20:30:09.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4888" PostTypeId="4" CreationDate="2021-05-02T20:30:09.910" Score="0" Body="Questions about mathematical derivations." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:09.910" LastActivityDate="2021-05-02T20:30:09.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4889" PostTypeId="5" CreationDate="2021-05-02T20:30:23.380" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:23.380" LastActivityDate="2021-05-02T20:30:23.380" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4890" PostTypeId="4" CreationDate="2021-05-02T20:30:23.380" Score="0" Body="Questions about the HSE06 functional." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:23.380" LastActivityDate="2021-05-02T20:30:23.380" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4891" PostTypeId="5" CreationDate="2021-05-02T20:30:43.060" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:43.060" LastActivityDate="2021-05-02T20:30:43.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4892" PostTypeId="4" CreationDate="2021-05-02T20:30:43.060" Score="0" Body="Questions about metals." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:43.060" LastActivityDate="2021-05-02T20:30:43.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4893" PostTypeId="5" CreationDate="2021-05-02T20:30:58.167" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:58.167" LastActivityDate="2021-05-02T20:30:58.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4894" PostTypeId="4" CreationDate="2021-05-02T20:30:58.167" Score="0" Body="Questions about plane-wave basis sets." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:30:58.167" LastActivityDate="2021-05-02T20:30:58.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4895" PostTypeId="5" CreationDate="2021-05-02T20:31:35.507" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:31:35.507" LastActivityDate="2021-05-02T20:31:35.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4896" PostTypeId="4" CreationDate="2021-05-02T20:31:35.507" Score="0" Body="Questions about spin polarization." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:31:35.507" LastActivityDate="2021-05-02T20:31:35.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4897" PostTypeId="5" CreationDate="2021-05-02T20:31:47.253" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:31:47.253" LastActivityDate="2021-05-02T20:31:47.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4898" PostTypeId="4" CreationDate="2021-05-02T20:31:47.253" Score="0" Body="Questions about reaction mechanisms." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:31:47.253" LastActivityDate="2021-05-02T20:31:47.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4899" PostTypeId="5" CreationDate="2021-05-02T20:32:08.133" Score="0" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Open source toolkit for cheminformatics&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Business-friendly BSD license&lt;/li&gt;&#xA;&lt;li&gt;Core data structures and algorithms in C++&lt;/li&gt;&#xA;&lt;li&gt;Python 3.x wrappers generated using Boost.Python&lt;/li&gt;&#xA;&lt;li&gt;Java and C# wrappers generated with SWIG&lt;/li&gt;&#xA;&lt;li&gt;2D and 3D molecular operations&lt;/li&gt;&#xA;&lt;li&gt;Descriptor generation for machine learning&lt;/li&gt;&#xA;&lt;li&gt;Molecular database cartridge for PostgreSQL&lt;/li&gt;&#xA;&lt;li&gt;Cheminformatics nodes for KNIME (distributed from the KNIME community site: &lt;a href=&quot;https://www.knime.com/rdkit&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.knime.com/rdkit&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.rdkit.org/docs/Overview.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Website&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-11-10T18:09:33.213" LastActivityDate="2021-11-10T18:09:33.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4900" PostTypeId="4" CreationDate="2021-05-02T20:32:08.133" Score="0" Body="Questions about using RDKit in matter modeling workflows." OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-11-10T18:09:33.213" LastActivityDate="2021-11-10T18:09:33.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4901" PostTypeId="5" CreationDate="2021-05-02T20:33:57.817" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:33:57.817" LastActivityDate="2021-05-02T20:33:57.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4902" PostTypeId="4" CreationDate="2021-05-02T20:33:57.817" Score="0" Body="Questions about excitions." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:33:57.817" LastActivityDate="2021-05-02T20:33:57.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4903" PostTypeId="5" CreationDate="2021-05-02T20:34:09.383" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:34:09.383" LastActivityDate="2021-05-02T20:34:09.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4904" PostTypeId="4" CreationDate="2021-05-02T20:34:09.383" Score="0" Body="Questions about elasticity of materials." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:34:09.383" LastActivityDate="2021-05-02T20:34:09.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4905" PostTypeId="5" CreationDate="2021-05-02T20:38:49.713" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:38:49.713" LastActivityDate="2021-05-02T20:38:49.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4906" PostTypeId="4" CreationDate="2021-05-02T20:38:49.713" Score="0" Body="Questions asking for benchmark CPU/GPU timings or timing comparisons." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:38:49.713" LastActivityDate="2021-05-02T20:38:49.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4907" PostTypeId="5" CreationDate="2021-05-02T20:39:01.333" Score="0" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;VMD is designed for modeling, visualization, and analysis of biological systems such as proteins, nucleic acids, lipid bilayer assemblies, etc. It may be used to view more general molecules, as VMD can read standard Protein Data Bank (PDB) files and display the contained structure. VMD provides a wide variety of methods for rendering and coloring a molecule: simple points and lines, CPK spheres and cylinders, licorice bonds, backbone tubes and ribbons, cartoon drawings, and others. VMD can be used to animate and analyze the trajectory of a molecular dynamics (MD) simulation. In particular, VMD can act as a graphical front end for an external MD program by displaying and animating a molecule undergoing simulation on a remote computer.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Website&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-11-10T18:00:58.587" LastActivityDate="2021-11-10T18:00:58.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4908" PostTypeId="4" CreationDate="2021-05-02T20:39:01.333" Score="0" Body="Questions about the Visual Molecular Dynamics (VMD) structure visualization program." OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-11-10T18:00:58.587" LastActivityDate="2021-11-10T18:00:58.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4909" PostTypeId="5" CreationDate="2021-05-02T20:39:21.920" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:39:21.920" LastActivityDate="2021-05-02T20:39:21.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4910" PostTypeId="4" CreationDate="2021-05-02T20:39:21.920" Score="0" Body="Questions about publishing. Questions in this tag will also show up in the feed for the Academia.SE main chat room." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:39:21.920" LastActivityDate="2021-05-02T20:39:21.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4911" PostTypeId="5" CreationDate="2021-05-02T20:40:18.180" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:40:18.180" LastActivityDate="2021-05-02T20:40:18.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4912" PostTypeId="4" CreationDate="2021-05-02T20:40:18.180" Score="0" Body="Questions about modeling related to COVID-19." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:40:18.180" LastActivityDate="2021-05-02T20:40:18.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4913" PostTypeId="5" CreationDate="2021-05-02T20:40:29.697" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:40:29.697" LastActivityDate="2021-05-02T20:40:29.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4914" PostTypeId="4" CreationDate="2021-05-02T20:40:29.697" Score="0" Body="Questions about Weyl semi-metals." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:40:29.697" LastActivityDate="2021-05-02T20:40:29.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4915" PostTypeId="5" CreationDate="2021-05-02T20:43:54.173" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:43:54.173" LastActivityDate="2021-05-02T20:43:54.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4916" PostTypeId="4" CreationDate="2021-05-02T20:43:54.173" Score="0" Body="Questions about optical properties." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-02T20:43:54.173" LastActivityDate="2021-05-02T20:43:54.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4917" PostTypeId="1" AcceptedAnswerId="4918" CreationDate="2021-05-02T22:00:45.000" Score="4" ViewCount="208" Body="&lt;p&gt;In &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c00455&quot; rel=&quot;nofollow noreferrer&quot;&gt;this reference&lt;/a&gt;, the author investigates electronic population dynamics from a MCTDH calculation. My question is how to generate state populations over time from an MCTDH calculation? Is there a formula for that?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2021-05-03T06:22:03.113" LastActivityDate="2021-05-03T06:22:03.113" Title="How to calculate state population from MCTDH?" Tags="|quantum-dynamics|mctdh|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4918" PostTypeId="2" ParentId="4917" CreationDate="2021-05-03T00:27:14.850" Score="6" Body="&lt;p&gt;The part of the paper where they give the formula for the populations is here:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The timedependent (TD) vibronic wavefunction of the system is computed solving the TD Schroedinger Equation. It is written as &lt;span class=&quot;math-container&quot;&gt;$|\Psi_i(\mathbf{q},t)\rangle  = \sum_i |d_i\rangle |\Psi(\mathbf{q},t)\rangle$&lt;/span&gt; so that electronic populations are simply &lt;span class=&quot;math-container&quot;&gt;$P_i(t) =  \langle \Psi_i (\mathbf{q},t) |  \Psi_i (\mathbf{q},t) \rangle$&lt;/span&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Basically you propagate the wavefunctions for each state labeled by &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; using MCTDH, and then do the inner products &lt;span class=&quot;math-container&quot;&gt;$\langle \psi_i | \psi_i \rangle$&lt;/span&gt; for each &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. &lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-03T00:27:14.850" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4919" PostTypeId="1" CreationDate="2021-05-03T07:55:11.450" Score="7" ViewCount="226" Body="&lt;p&gt;For research purpose, my team needs to use &lt;a href=&quot;https://dalcorso.github.io/thermo_pw/&quot; rel=&quot;noreferrer&quot;&gt;thermo_pw&lt;/a&gt; package for ab-initio simulations. But the issue we are running into is that we cannot find a way to install it on our computer. We are using windows as our operating system.&lt;/p&gt;&#xA;&lt;p&gt;Thermo_pw website says that it is made for linux operating systems but it may work on other OS as well.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jdVxf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jdVxf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;We have tried to install it using Gfortran for windows but it didn't work out.&lt;/p&gt;&#xA;" OwnerUserId="2085" LastEditorUserId="1380" LastEditDate="2021-05-03T09:03:06.517" LastActivityDate="2021-06-11T23:46:11.143" Title="Is it possible to install thermo_pw on windows 10?" Tags="|density-functional-theory|quantum-espresso|materials-engineering|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4920" PostTypeId="1" AcceptedAnswerId="4921" CreationDate="2021-05-03T09:50:07.177" Score="8" ViewCount="251" Body="&lt;p&gt;I've tried to calculate dispersion energies of some organometallic complexes with the  Gaussian software using &lt;code&gt;WB97XD/Gen&lt;/code&gt; (&lt;code&gt;6-311+G**/LANL2DZ&lt;/code&gt;) level of theory because I have Au as heavy metal.&lt;/p&gt;&#xA;&lt;p&gt;The calculation doesn't even start and ends by link 301 error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;The job section # opt WB97XD/gen pseudo=read&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the output's last line was&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;R6DRO: No vdw radius available for IA=79&#xA;Error termination via lnk1e in /home/pctci/g09/l301.exe&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My input file was perfectly drafted, I don't know what the problem is.&#xA;Anyone could help me please?&lt;/p&gt;&#xA;" OwnerUserId="3513" OwnerDisplayName="Yassamine" LastEditorUserId="7" LastEditDate="2021-05-03T19:36:29.387" LastActivityDate="2021-05-03T19:36:29.387" Title="Calculation of dispersion energies for organometallic complexes with Gaussian" Tags="|computational-chemistry|gaussian|dispersion-correction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4921" PostTypeId="2" ParentId="4920" CreationDate="2021-05-03T14:56:01.027" Score="8" Body="&lt;p&gt;Van der Waal's radii for all atoms in the molecule are required to compute the dispersion for &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D (this is also true for Grimme's dispersion). Unfortunately, Gaussian09 doesn't seem to have the radius for &lt;span class=&quot;math-container&quot;&gt;$\ce{Au}$&lt;/span&gt; and it is also not possible to manually enter it through the input file. The radii for the elements up through &lt;span class=&quot;math-container&quot;&gt;$\ce{Rn}$&lt;/span&gt; (atomic number 86) do seem to be available in Gaussian16 if that is an option.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-05-03T17:19:23.410" LastActivityDate="2021-05-03T17:19:23.410" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4922" PostTypeId="1" AcceptedAnswerId="5086" CreationDate="2021-05-03T15:02:20.170" Score="8" ViewCount="445" Body="&lt;p&gt;In GW-BSE calculations, people could analyze the exciton wave function &lt;span class=&quot;math-container&quot;&gt;$|S\rangle$&lt;/span&gt; by plotting the BSE eigenvector &lt;span class=&quot;math-container&quot;&gt;$A_{cv\mathbf{k}}$&lt;/span&gt; that satisfies &lt;span class=&quot;math-container&quot;&gt;$|S\rangle = \sum_{cv\mathbf{k}}A_{cv\mathbf{k}}|cv\rangle$&lt;/span&gt;. In genreal, &lt;span class=&quot;math-container&quot;&gt;$A_{cv\mathbf{k}}$&lt;/span&gt; is complex number, usually the modulus or squared modulus is plotted. I'm wondering how to add the phase information on the plot like Fig. 10 in &lt;a href=&quot;https://journals.aps.org/prb/pdf/10.1103/PhysRevB.93.235435&quot; rel=&quot;noreferrer&quot;&gt;PRB 93, 235435 (2016)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/o4GcM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/o4GcM.png&quot; alt=&quot;exciton wave function&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2021-06-03T11:05:15.803" Title="How to plot exciton wave function with phase information?" Tags="|gw-bse|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4923" PostTypeId="2" ParentId="4873" CreationDate="2021-05-03T16:37:52.377" Score="16" Body="&lt;p&gt;I don't have too much to add to the answers of Nike Dattani and Tyberius, but I think the crux is that its capabilities have been historically overestimated.&lt;/p&gt;&#xA;&lt;p&gt;One particular failing of B3LYP is that it tends to underestimate bond energies. However, since the small (and fast) 6-31G* basis set will lead to overbinding, the famous combination B3LYP/6-31G* ended up being good &amp;quot;by accident.&amp;quot; At least for small molecules, because it turns out that the performance of especially the LYP correlation part worsens in larger systems. Maybe not too surprising, since LYP is designed to reproduce correlation energy of the He atom.&lt;/p&gt;&#xA;&lt;p&gt;The general issue, then, is that even if B3LYP/6-31G* may work because of error cancellation, this is not a reliable assumption in general. After all, you want to be right for right reasons!&lt;/p&gt;&#xA;&lt;p&gt;You also ask about surface catalysis. The main issue of B3LYP in such systems, is that it is hybrid functional, which are extremely expensive to use in periodic systems. You will almost always see people use GGA or meta-GGA functionals in such systems, some of which are actually very good for such problems (but this depends strongly on the system!).&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2021-05-03T16:37:52.377" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4924" PostTypeId="2" ParentId="4854" CreationDate="2021-05-03T16:58:19.263" Score="11" Body="&lt;p&gt;In principle, temperature fluctuations are perfectly normal at the nanoscale. In fact, fluctuations are intrinsic to any ensemble. The magnitude (variance) of the fluctuations of the kinetic energy in the NVT ensemble is inversely correlated with the number of degrees of freedom, and if you have a small system, these will necessarily be large, even at equilibrium. You can, however, monitor the average temperature to check if it corresponds to the desired value.&lt;/p&gt;&#xA;&lt;p&gt;The total and potential energy should also fluctuate around some average value. If they do not do this, the system is not yet in equilibrium. I cannot directly see what is happening in your system, but a decreasing energy is not strange &lt;em&gt;per se&lt;/em&gt;. Even if you minimize a structure, this only guarantees you start from a &lt;em&gt;local&lt;/em&gt; minimum. There's no reason the MD run finds no new, deeper minima.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2021-05-03T17:21:13.097" LastActivityDate="2021-05-03T17:21:13.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4925" PostTypeId="2" ParentId="4245" CreationDate="2021-05-03T18:12:21.323" Score="8" Body="&lt;p&gt;I know it's a boring thing to say, but: &lt;strong&gt;It depends on what you want to do&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The way I use Langevin thermostats, is to ensure good equipartitioning in my setup, so that I don't have any local hotspots in the system or something like that. If heat transfer is slow in the system, &amp;quot;global&amp;quot; thermostats like Nosé-Hoover and the like will equilibrate rather slowly. In this context, the damping parameter does not really need to have physical significance, and it only determines how strongly it enforces equipartitioning. That being said, I have found that &amp;quot;1000 time steps&amp;quot; work well for this purpose. For your system, this may translate to a damping constant of &lt;strong&gt;1 ps&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you wish to model &lt;em&gt;dynamical&lt;/em&gt; properties of the system, the issue is much tougher. You correctly note that there exists a connection with the viscosity of the surrounding medium, but this doesn't make all too much sense on/inside a metal. In a liquid, diffusion and viscosity are correlated, but in metals the diffusion of point defects is actually a governed by discrete jumps. So this connection breaks down. Generally speaking I would avoid calculating dynamical properties with Langevin dynamics, and use a global thermostat instead (like &lt;code&gt;fix nvt&lt;/code&gt; or &lt;code&gt;fix temp/csvr&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;To return to the first application, there are ways to more systematically optimize the performance of the thermostat, so that it most efficiently samples thermodynamic averages. Whereas a normal Langevin thermostat (&lt;code&gt;fix langevin&lt;/code&gt; or &lt;code&gt;fix temp/csld&lt;/code&gt; in LAMMPS) adds random &lt;em&gt;white noise&lt;/em&gt; to the dynamics, you can also add &lt;em&gt;colored noise&lt;/em&gt;, using &lt;code&gt;fix gle&lt;/code&gt;. This method implements several ideas developed in the group of Michele Ceriotti. One possible application is &amp;quot;optimal sampling&amp;quot;, which guarantees optimal coupling of the thermostat to the system, but there are also options to mimic nuclear quantum effects or vibrational nonequilibrium. There is a &lt;a href=&quot;http://gle4md.org/&quot; rel=&quot;noreferrer&quot;&gt;dedicated web site&lt;/a&gt; that has all the references and documentation.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2021-05-03T18:27:36.727" LastActivityDate="2021-05-03T18:27:36.727" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4926" PostTypeId="1" AcceptedAnswerId="6350" CreationDate="2021-05-03T19:33:08.617" Score="10" ViewCount="304" Body="&lt;p&gt;I want to perform a molecular docking between several ligands and the transmembrane domain of a protein.&lt;/p&gt;&#xA;&lt;p&gt;For this protein I only have the amino acid sequence, so it's necessary to do two things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Determine which part of the aminoacid sequence belongs to the transmembrane domain (see &lt;a href=&quot;http://www.cbs.dtu.dk/services/TMHMM-2.0/&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Model the 3D structure based on this aminoacid sequence (trRosetta software)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I would like to know if this little protocol that I have established (with the two softwares) is rigorous and the conclusions of a study based on it could be taken into account.&lt;/p&gt;&#xA;" OwnerUserId="3512" LastEditorUserId="5" LastEditDate="2021-05-03T22:08:57.160" LastActivityDate="2021-07-20T08:07:03.697" Title="Protein structure prediction" Tags="|proteins|docking|protein-folding|" AnswerCount="4" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4927" PostTypeId="1" CreationDate="2021-05-03T22:34:44.993" Score="4" ViewCount="512" Body="&lt;p&gt;It is known that protonation states of the receptor and the ligand before and after the binding are a very important factor for the binding, as indicated by both experimental data and computational modeling in literature.&lt;/p&gt;&#xA;&lt;p&gt;I want to perform a molecular docking for protein-ligand varying pH, that is, changing the protonation states of the protein.&lt;/p&gt;&#xA;&lt;p&gt;My approach is to use the Chimera software to modify the protonation state of the protein and carry out a docking for each molecule (with and without protonation states). However, I do not know if this approach is complete, and although the importance of the protonation state is highlighted in the literature, I have not found a working protocol for this.&lt;/p&gt;&#xA;" OwnerUserId="3512" LastEditorUserId="5" LastEditDate="2021-05-03T22:36:29.443" LastActivityDate="2021-05-03T22:53:45.463" Title="Ligand-protein molecular docking with different protonation states" Tags="|proteins|docking|chimera-software|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4928" PostTypeId="5" CreationDate="2021-05-03T22:37:26.780" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.cgl.ucsf.edu/chimera/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.cgl.ucsf.edu/chimera/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-03T22:37:26.780" LastActivityDate="2021-05-03T22:37:26.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4929" PostTypeId="4" CreationDate="2021-05-03T22:37:26.780" Score="0" Body="Questions about or related to UCSF Chimera, the software for interactive visualization and analysis of molecular structures and related data." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-03T22:37:26.780" LastActivityDate="2021-05-03T22:37:26.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4930" PostTypeId="2" ParentId="4927" CreationDate="2021-05-03T22:53:45.463" Score="2" Body="&lt;p&gt;Your approaches looks correct.&lt;/p&gt;&#xA;&lt;p&gt;Normally, the docking are done in physiological pH, so, only one pH. Maybe this is why you didn't see any works doing what you are trying ti do. But hey, this it is a good thing: you will be the first.&lt;/p&gt;&#xA;&lt;p&gt;My only recommendation is to carry all the calculations using the same protocol: same software, same protonation method, etc.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-05-03T22:53:45.463" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4931" PostTypeId="2" ParentId="4922" CreationDate="2021-05-04T04:06:01.807" Score="2" Body="&lt;p&gt;I think these figures are plotting the square of &lt;span class=&quot;math-container&quot;&gt;$A_{vc\vec{k}}$&lt;/span&gt;, therefore no phase information is contained in these figures. Note that the figures that you are showing are marking each excitonic state with &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;, which represent exactly the square of the wave function in the problem of the hydrogen atom.&lt;/p&gt;&#xA;&lt;p&gt;The exciton character and composition in reciprocal space is given by the so-called exciton weights&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\omega_{v\vec{k}}^\lambda=\sum_c |A_{vc\vec{k}}^\lambda|^2 \tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\omega_{c\vec{k}}^\lambda=\sum_v |A_{vc\vec{k}}^\lambda|^2 \tag{1}&#xA;\end{equation}&lt;/span&gt;&#xA;which contain information about the BSE eigenvectors and represent the contributions to a given electronic transition to the &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;th solution of the BSE.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ref: &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.3.074001&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. Materials 3, 074001&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-05-04T04:06:01.807" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4932" PostTypeId="1" CreationDate="2021-05-04T05:42:07.087" Score="9" ViewCount="358" Body="&lt;p&gt;I use VASP to do my DFT calculation. I have to do a self consistent calculation to generate my CHGCAR. I want to ask is there anyway to write the KPOINTS file to generate K-meshing grid which can exactly lying in  &lt;span class=&quot;math-container&quot;&gt;$(\frac{\pi}{a} , \frac{\pi}{a}, \frac{\pi}{a})$&lt;/span&gt; point in square Brillouin zone boundary? As I used Monkhost-Pack grid, which can only guarantee that your point grid can be located at Gamma point.&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="5" LastEditDate="2021-07-12T06:40:28.963" LastActivityDate="2021-07-12T06:40:28.963" Title="How to do a Sampling on the boundary of Brillouin zone in VASP" Tags="|density-functional-theory|vasp|brillouin-zone|" AnswerCount="0" CommentCount="7" ClosedDate="2021-12-15T15:04:41.587" ContentLicense="CC BY-SA 4.0" />
  <row Id="4933" PostTypeId="1" CreationDate="2021-05-04T18:39:15.530" Score="16" ViewCount="780" Body="&lt;p&gt;While there are a few tools for &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/467/30&quot;&gt;visualizing crystal structures&lt;/a&gt;, I'm particularly curious to know tools for visualizing space group symmetry, including:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;screw axes&lt;/li&gt;&#xA;&lt;li&gt;glide planes&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I teach a class on molecular symmetry and would like to expand to teaching about space groups. It's relatively easy to depict mirror planes and inversion centers, but glide planes and screw axes are a bit harder for chemists to visualize.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2021-05-05T00:31:03.283" LastActivityDate="2021-05-05T16:12:02.767" Title="What are good tools for visualizing glide planes and screw axes?" Tags="|software-recommendations|symmetry|visualization-software|space-groups|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4934" PostTypeId="2" ParentId="4933" CreationDate="2021-05-04T23:36:01.640" Score="11" Body="&lt;h3&gt;Jmol/JSmol&lt;/h3&gt;&#xA;&lt;p&gt;Did you consider &lt;a href=&quot;http://wiki.jmol.org/index.php/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;Jmol/JSmol&lt;/a&gt;?  It is freely available for Windows / Mac / Linux, scriptable, may export what is being displayed in formats relevant to chemistry (e.g., .pdb, .sdf), as image (e.g., .png, &lt;a href=&quot;http://wiki.jmol.org/index.php/File_formats/Export#Special_image_files_PNGJ&quot; rel=&quot;noreferrer&quot;&gt;.pngj&lt;/a&gt;, [animated] .gif) and already is in use to teach symmetry in molecules and crystals. As an example, the interactive compilations by &lt;a href=&quot;https://symotter.org/&quot; rel=&quot;noreferrer&quot;&gt;Symmetry@Otterbein&lt;/a&gt; dedicate a page about a few space groups, too.  Jmol/JSmol is a default viewer of the 3D structures of the IUCr Journals, and there is a &lt;a href=&quot;http://wiki.jmol.org/index.php/Crystal_Community&quot; rel=&quot;noreferrer&quot;&gt;forum&lt;/a&gt; dedicated to its use in crystallography, too.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://scripts.iucr.org/cgi-bin/paper?S0021889810030256&quot; rel=&quot;noreferrer&quot;&gt;2010JApplCryst1250&lt;/a&gt; Hanson presents a selection of what may be achieved.  This &lt;em&gt;open access&lt;/em&gt; publication offers all the data to replicate the figures displayed in the publication as SI, too.  For example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UR20N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UR20N.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uNjFf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uNjFf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5AQIv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5AQIv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Much of this may be tried out -- just from the browser -- in a dedicated &lt;a href=&quot;https://chemapps.stolaf.edu/jmol/docs/examples-11/new0.htm&quot; rel=&quot;noreferrer&quot;&gt;test site&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In a period of extended distance learning, earlier publications in the &lt;em&gt;Journal of Chemical Education&lt;/em&gt; about this program (like &lt;a href=&quot;https://doi.org/10.1021/ed082p1736&quot; rel=&quot;noreferrer&quot;&gt;2005JChemEduc1736&lt;/a&gt;, or &lt;a href=&quot;https://doi.org/10.1021/ci700173y&quot; rel=&quot;noreferrer&quot;&gt;2007JChemEduc2475&lt;/a&gt;) may be of general interest, too.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="5" LastEditDate="2021-05-04T23:46:11.327" LastActivityDate="2021-05-04T23:46:11.327" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4935" PostTypeId="2" ParentId="4856" CreationDate="2021-05-05T11:48:17.253" Score="3" Body="&lt;p&gt;Elastic constants can be calculated using two approach, one with Energy-strain relationship and another with stress-strain relationship. The key ingredient in above two methods is energy or stress at particular mode of distortion. For example in cubic crystal which have 3 fold symmetry about body diagonal need three independent elastic parameters to define second-order elastic constants. &lt;code&gt;VASP&lt;/code&gt; algorithm  &lt;code&gt;IBRION=6&lt;/code&gt; also do the same. Some time problem of not getting elastic constants correctly depends on many parameters. Specially with large systems which consists of many number of atoms along with different atomic numbers, full volume relaxation results in difference between input and output structure. For example you can try relaxation of 4 atom aluminum unit cell and re-relaxed its supercell again with same K-space density and kinetic energy cutoff. You may get minor difference in output configuration with &lt;code&gt;ISIF=3&lt;/code&gt;(full volume and position relaxation). You can also simply check your input file symmetry using python &lt;code&gt;spglib&lt;/code&gt; library or just use &lt;code&gt;vaspkit&lt;/code&gt;. The question arises if there is minor change in symmetry, can we get same number of elastic constants as it should be. The answer is check your elastic constants values, is two elastic constants are apart by small amount, you can always say those are equal. Other way to calculate elastic constants without &lt;code&gt;VASP&lt;/code&gt; and&lt;code&gt;IBRION=6&lt;/code&gt; is just distort crystal manually based on symmetry and do only position relaxation(&lt;code&gt;ISIF=2&lt;/code&gt;) and then fit energy and distorsion by second order polynomial.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-05-05T11:48:17.253" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4936" PostTypeId="1" CreationDate="2021-05-05T15:30:17.853" Score="6" ViewCount="41" Body="&lt;p&gt;I want to perform a molecular docking between a protein of interest and several ligands. This membrane protein has a transmembrane domain composed of an alpha helix structure, which exerts it's function in a dimeric conformation, that is, by binding two identical proteins in its transmembrane domain. The crystal structure for this protein it's not available so it is necessary to design it ab initio. For this, we have the following working protocol:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Design of the monomeric 3D structure from the amino acid chain. FMAP software.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Obtaining the percentage of protein embedded in the membrane and its degrees of tilt. OMP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Design of the dimeric structure. RosettaMP&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Exploratory simulations for the selection and refinement of the dimeric model. CHARMM-GUI&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;The main problem I'm finding with this approach is that Rosetta software needs supercomputing capacity. I would like to know if there's a reliable server option for developting the dimeric structure.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3512" LastEditorUserId="5" LastEditDate="2021-05-06T02:41:31.887" LastActivityDate="2021-05-06T02:41:31.887" Title="Construction of dimeric protein models, selection and refinement" Tags="|molecular-modeling|proteins|docking|" AnswerCount="0" CommentCount="3" ClosedDate="2021-07-07T19:33:46.660" ContentLicense="CC BY-SA 4.0" />
  <row Id="4937" PostTypeId="2" ParentId="4933" CreationDate="2021-05-05T16:12:02.767" Score="5" Body="&lt;h2&gt;CCDC Mercury&lt;/h2&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.ccdc.cam.ac.uk&quot; rel=&quot;noreferrer&quot;&gt;Cambridge Crystallographic Data Centre (CCDC)&lt;/a&gt; provides a free-to-use visualization program &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/mercury/&quot; rel=&quot;noreferrer&quot;&gt;Mercury&lt;/a&gt; that offers a wide variety of features for crystal structures including, perhaps not surprisingly crystallographic symmetry.&lt;/p&gt;&#xA;&lt;p&gt;The trick, of course, is to have appropriate crystal structures to illustrate points. CCDC does provide a free &lt;a href=&quot;https://www.ccdc.cam.ac.uk/Community/educationalresources/teaching-database/&quot; rel=&quot;noreferrer&quot;&gt;teaching subset&lt;/a&gt; which includes fundamental chemistry (e.g., molecular shapes / VSEPR) and symmetry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Glide Planes&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here's a similar illustration of the &amp;quot;c&amp;quot; glide plane in maleic acid:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YCCx8.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YCCx8.png&quot; alt=&quot;Glide plane in maleic acid&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Screw Axis&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here's an illustration of chloromethane  &lt;span class=&quot;math-container&quot;&gt;$Cmc2_1$&lt;/span&gt; illustrating the multiple screw axes:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RRJwK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RRJwK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-05-05T16:12:02.767" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4938" PostTypeId="1" AcceptedAnswerId="4943" CreationDate="2021-05-05T16:15:29.277" Score="7" ViewCount="455" Body="&lt;p&gt;I am calculating the frequency dependent dielectric function of &lt;span class=&quot;math-container&quot;&gt;$\ce{SiC}$&lt;/span&gt; using VASP. After a geometry optimization, the &lt;code&gt;INCAR&lt;/code&gt; file below is used for the calculation. The tags are mostly based on the &lt;a href=&quot;https://jarvis.nist.gov/jarvisdft/&quot; rel=&quot;noreferrer&quot;&gt;JARVIS&lt;/a&gt; dielectric function database.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;AGGAC = 0.0&#xA;EDIFF = 1e-07&#xA;ENCUT = 520&#xA;IBRION = 1&#xA;ISIF = 2&#xA;ISMEAR = 0&#xA;LCHARG = False&#xA;LOPTICS = True&#xA;LORBIT = 11&#xA;LWAVE = False&#xA;NBANDS = 600&#xA;NEDOS = 5000&#xA;NELM = 400&#xA;NPAR = 8&#xA;PARAM1 = 0.1833333333&#xA;PARAM2 = 0.22&#xA;PREC = Accurate&#xA;LREAL = AUTO&#xA;LscaAWARE=.False.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After some post-processing with &lt;code&gt;p4vasp&lt;/code&gt;, I can obtain the dielectric function of &lt;span class=&quot;math-container&quot;&gt;$\ce{SiC}$&lt;/span&gt;.  Based on my calculations, the real part of the dielectric constant crosses zero around 7.7 eV (that is around 161 nm - I have converted photon energy to wavelength for comparison). This is very similar to &lt;span class=&quot;math-container&quot;&gt;$\ce{SiC}$&lt;/span&gt; dielectric function available in JARVIS database, so I believe the calculation is consistent.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that there is a large mismatch between the DFT calculation and the experimental measurement. The experimental data is provided in &lt;a href=&quot;https://www.osapublishing.org/optica/fulltext.cfm?uri=optica-3-3-339&amp;amp;id=338263#articleBody&quot; rel=&quot;noreferrer&quot;&gt;kim et al. Optica 3, 339-346 (2016)&lt;/a&gt;. Following is the comparison (first image from my calculation). According the their results the crossover wavelength is in the order of 10 &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;m. Also note the difference in y-axis magnitudes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wS8h7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wS8h7.png&quot; alt=&quot;sic dft&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/jjMLt.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jjMLt.png&quot; alt=&quot;sic exp&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why is there such a huge difference? Am I doing anything wrong?&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2021-05-07T11:50:58.467" Title="Why is there a large discrepancy between calculated frequency dependent dielectric function and experimental measurement?" Tags="|density-functional-theory|vasp|optical-properties|dielectric-constants|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4939" PostTypeId="1" CreationDate="2021-05-06T12:10:38.540" Score="10" ViewCount="577" Body="&lt;p&gt;I am mainly searching for functionals to calculate spectra of pesticides. I found the benchmark test from Goerigk and Grimme&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;, but don't understand which of the functionals suits my purpose the best. They published different functionals, which were the most accurate and robust in their study.&lt;/p&gt;&#xA;&lt;p&gt;My question is, can I use these functionals for my calculations of pesticides?&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;L. Goerigk and S. Grimme &lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; 2011, 7, 2, 291-309 &lt;a href=&quot;https://doi.org/10.1021/ct100466k&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/ct100466k&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1682" LastEditorUserId="5" LastEditDate="2021-05-06T15:43:56.940" LastActivityDate="2021-05-07T18:31:54.867" Title="Which DFT functional should I use to simulate spectra of pesticides?" Tags="|density-functional-theory|reference-request|one-topic-per-answer|computational-chemistry|functional|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4940" PostTypeId="1" AcceptedAnswerId="6617" CreationDate="2021-05-06T15:54:02.410" Score="7" ViewCount="1525" Body="&lt;p&gt;I sometimes need to remove atoms from LAMMPS datafiles by hand, removing each row that corresponds to an atomID I want to remove, then decrementing the total atom count. This causes the atom IDs to no longer be contiguous in the file.&lt;/p&gt;&#xA;&lt;p&gt;This is valid in the LAMMPS datafile specification but it causes issues for certain commands, for instance the velocity command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;velocity all create 0.01 4928459 dist gaussian&#xA;ERROR: Atom IDs must be consecutive for velocity create loop all (src/velocity.cpp:270)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Being okay with atomIDs being remapped, is there a quick way to make the atom IDs of a lammps datafile contiguous?&lt;/p&gt;&#xA;" OwnerUserId="1203" LastActivityDate="2021-08-24T02:18:23.940" Title="LAMMPS data files, making atom IDs contiguous" Tags="|molecular-modeling|lammps|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4941" PostTypeId="2" ParentId="4940" CreationDate="2021-05-06T15:54:02.410" Score="2" Body="&lt;p&gt;If you are not concerned with atomIDs being arbitrarily remapped, then you can use a molecule editor like Ovito to import the LAMMPS data file, and then re-export it as a format that doesn't store atomIDs, like the XYZ format. If you then re-import it, and re-export it as LAMMPS datafile, ovito will have to generate the atomIDs and will ensure that they are contiguous.&lt;/p&gt;&#xA;" OwnerUserId="1203" LastActivityDate="2021-05-06T15:54:02.410" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4942" PostTypeId="2" ParentId="4939" CreationDate="2021-05-06T16:29:35.450" Score="9" Body="&lt;h1&gt;B3LYP&lt;/h1&gt;&#xA;&lt;p&gt;My suggestion for you in this case is to simply use the most common funcitonal for basic properties of molecules: B3LYP.  I &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4875/5&quot;&gt;wrote in my answer here&lt;/a&gt; that B3LYP is still a decent functional overall, especially considering its relatively low cost for non-periodic systems (e.g. a pesticide molecule).&lt;/p&gt;&#xA;&lt;p&gt;The first figure in that answer is directly from the paper that you said you're asking about, and it shows that overall, B3LYP is on average:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;more accurate than all LDA and GGA functionals studied,&lt;/li&gt;&#xA;&lt;li&gt;at least as accurate as all meta-GGAs studied,&lt;/li&gt;&#xA;&lt;li&gt;is in the &amp;quot;middle of the pack&amp;quot; for single-hybrid funcitonals (&lt;strong&gt;but is far more popular and universally implemented (it will be available no matter what software you use!)&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;not as accurate as the double hybrids, but &lt;em&gt;&lt;strong&gt;far less computationally costly!&lt;/strong&gt;&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Pesticides are extremely diverse!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is such a vast range, for example pesticides for rodents (&lt;a href=&quot;https://en.wikipedia.org/wiki/Rodenticide&quot; rel=&quot;noreferrer&quot;&gt;rodenticides&lt;/a&gt;) such as the organic molecule &lt;a href=&quot;https://en.wikipedia.org/wiki/Warfarin&quot; rel=&quot;noreferrer&quot;&gt;warfarin&lt;/a&gt;, may be very different from pesticides for algae (&lt;a href=&quot;https://en.wikipedia.org/wiki/Algaecide&quot; rel=&quot;noreferrer&quot;&gt;algicides&lt;/a&gt;) such as the transition-metal-containing &lt;a href=&quot;https://en.wikipedia.org/wiki/Copper(II)_sulfate&quot; rel=&quot;noreferrer&quot;&gt;copper (II) sulphate&lt;/a&gt;. We &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2/5&quot;&gt;&lt;strong&gt;do not know a universal functional that will work well for all pesticides&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You are therefore best off in my opinion, to &amp;quot;keep it simple&amp;quot; and just use B3LYP, which is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;not too computationally expensive,&lt;/li&gt;&#xA;&lt;li&gt;is more likely to be implemented in whatever software you're using, than any other functional that has the same balance of accuracy, computational cost, and popularity,&lt;/li&gt;&#xA;&lt;li&gt;is likely the most popular functional used for individual molecules, so there's a greater likelihood for there to be literature to which you can compare (if necessary), and more people will recognize and understand what it is that you're doing.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you do choose to use something other than B3LYP, you're more likely to need to provide justification for why you're using it, but if you pick B3LYP, most people will agree that it's a decent &amp;quot;default&amp;quot; choice for studying basic properties of individual molecules. The Goerigk-Grimme paper to which you referred in your question, showed (for example in the second figure &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4873/what-does-b3lyp-do-well-what-does-it-do-badly/4875#4875&quot;&gt;in my answer here&lt;/a&gt;) that B3LYP is quite decent for everything they tested except for reaction energies, and you are not calculating reaction energies!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-05-06T16:59:17.087" LastActivityDate="2021-05-06T16:59:17.087" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="4943" PostTypeId="2" ParentId="4938" CreationDate="2021-05-06T17:15:20.017" Score="5" Body="&lt;p&gt;It's not obvious to me that you are doing anything wrong in your calculation. Your result for the crossover energy seems consistent with the literature, e.g. &lt;a href=&quot;https://doi.org/10.1063/1.369524&quot; rel=&quot;noreferrer&quot;&gt;Theodorou et al. (1999)&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1002/(SICI)1521-3951(199810)209:2%3C499::AID-PSSB499%3E3.0.CO;2-M&quot; rel=&quot;noreferrer&quot;&gt;Petalas et al. (1998)&lt;/a&gt; (the former being a computational work, and the latter a synchrotron experiment). What you should note, however, is that you are using a &lt;em&gt;very&lt;/em&gt; different scale to the Kim et al. figure you show, so the comparison you're making is inapplicable. To wit, note that &lt;span class=&quot;math-container&quot;&gt;$12.5~\mu$&lt;/span&gt;m&lt;span class=&quot;math-container&quot;&gt;$=12 500$&lt;/span&gt; nm &lt;span class=&quot;math-container&quot;&gt;$\gg 160$&lt;/span&gt; nm. That is, you're plotting UV wavelengths while Kim et al. are considering IR wavelengths. Because of the bandgap in SiC, photons would be expected to couple to electron modes in the UV case, and to phonon modes in the IR case. For a computational approach tackling the latter problem, see &lt;a href=&quot;https://doi.org/10.1016/j.physb.2018.02.023&quot; rel=&quot;noreferrer&quot;&gt;Tong et al. (2018)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2021-05-06T17:15:20.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4945" PostTypeId="2" ParentId="4939" CreationDate="2021-05-07T01:11:40.837" Score="8" Body="&lt;p&gt;A general rule of thumb: never trust results obtained with only one functional (or basis set). If two different functionals give you a similar result, then you can trust the results. If the predictions disagree by a lot, it might be that DFT does not work for your problem.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-05-07T01:11:40.837" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4946" PostTypeId="1" CreationDate="2021-05-07T04:57:44.300" Score="14" ViewCount="2184" Body="&lt;p&gt;For what I know the DFT-D3 method or similar corrections that take into account dispersion effect, add this type of contribution through calculation of atom pairwise interactions at the end of an energy calculation by simple addition.&#xA;I would like to know if I'm right,  because in this case I think it cannot affect the final geometry in a geometry optimization.&#xA;I'm asking this question because usually all these methods are benchmarked only for energy calculation and never for geometry optimization.&#xA;I hope to have explained well my answer.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="5" LastEditDate="2021-05-07T17:12:22.487" LastActivityDate="2021-05-09T00:47:39.947" Title="Are dispersion correction methods for DFT (such as D3) useful for geometry optimization?" Tags="|density-functional-theory|geometry-optimization|dispersion-correction|" AnswerCount="5" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="4947" PostTypeId="2" ParentId="4938" CreationDate="2021-05-07T11:50:58.467" Score="5" Body="&lt;p&gt;Wait, those are two very different resonances. The one at 150-200 nm is obviously of electronic origin, whereas the one at about 12 microns is related to phonon modes. There is quite a lot of experimental data on SiC properties in the infrared, so if you're looking for the experimental data in the uv range, you might want to specify the range in the search. One good way to go about it is to check at &lt;a href=&quot;https://refractiveindex.info/?shelf=main&amp;amp;book=SiC&amp;amp;page=Larruquert&quot; rel=&quot;noreferrer&quot;&gt;https://refractiveindex.info/?shelf=main&amp;amp;book=SiC&amp;amp;page=Larruquert&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="2287" LastActivityDate="2021-05-07T11:50:58.467" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4948" PostTypeId="2" ParentId="4946" CreationDate="2021-05-07T12:58:04.773" Score="10" Body="&lt;p&gt;Optimization routines typically use the negative gradient of the energy in some form to determine the displacement during an optimization step and the dispersion correction changes the energy, which changes the gradient, and thus the optimization.&lt;/p&gt;&#xA;&lt;p&gt;You may get the same result in some cases but those are special cases, in general dispersion correction does have an effect on the optimization. The effects are often very noticeable if you have large molecules or two or more monomers that are calculated together. In such cases dispersion correction can have a large effect on the optimized geometry and can be essential to get good results.&lt;/p&gt;&#xA;&lt;p&gt;Energy is simply the most common metric for benchmarks and it is easier to compare a single number than a whole geometry. However, I am not a specialist in benchmarking,  so there could be other reasons for the prevalent use of energy. But the prevalence of energy as metric in benchmarks certainly does not mean that dispersion correction has no effect on geometry.&lt;/p&gt;&#xA;" OwnerUserId="2289" LastActivityDate="2021-05-07T12:58:04.773" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4949" PostTypeId="2" ParentId="4946" CreationDate="2021-05-07T13:18:34.507" Score="13" Body="&lt;p&gt;Dispersion correction DOES affect the final geometry.&lt;/p&gt;&#xA;&lt;p&gt;The dispersion interaction is a function of geometry.  A crude approximation is to write the dispersion interaction between two neutral molecules as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta E_{\rm disp}(R)=-\frac{C_6}{R^6},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; the distance between the two entities.&lt;/p&gt;&#xA;&lt;p&gt;In some special case, like the system in which two rare gas atoms interacts with each other, the potential energy curve given by functional like B3LYP has no minimum, which is quantitatively wrong. However, if a dispersion correction is used, an acceptable energy minimum can be calculated and the geometry optimization can be done.&lt;/p&gt;&#xA;&lt;p&gt;More detailed theory is well written in Prof. Grimme's &lt;a href=&quot;https://doi.org/10.1002/wcms.30&quot; rel=&quot;noreferrer&quot;&gt;review&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="794" LastEditDate="2021-05-07T17:27:03.477" LastActivityDate="2021-05-07T17:27:03.477" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4950" PostTypeId="2" ParentId="4946" CreationDate="2021-05-07T15:02:13.973" Score="14" Body="&lt;p&gt;Yes, vdW interaction affects energies but, also, geometries. This effect is the most pronounced if a DFT method predicts an interaction in a dimer to be repulsive: a geometry optimization will then simply dissociate the dimer. Normally, any vdW correction term does not only contribute energies, but als gradients, which in turn affect geometry optimizations (or MD simulations). Although I gather from other answers that some codes do not implement gradients, which I didn't know.&lt;/p&gt;&#xA;&lt;p&gt;Proper benchmarking is hard for structures, because gas phase, zero Kelvin geometries (the thing you calculate) are hard to come by experimentally for somewhat larger molecules—unfortunately exactly the kind of systems where you would expect vdW interactions to be imporant. Nevertheless, certain benchmark sets have been proposed, one of them based on rotational constants (which can be measured, and also calculated from an optimized structure). Here's an example of such a benchmark calculation, from &lt;a href=&quot;https://doi.org/10.1039/C3CP52293H&quot; rel=&quot;noreferrer&quot;&gt;Grimme &amp;amp; Steinmetz, Phys. Chem. Chem. Phys., 2013, 15, 16031-16042&lt;/a&gt;. You can see that dispersion corrections tend to make molecules &amp;quot;smaller&amp;quot; or more compact:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2J319.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2J319.png&quot; alt=&quot;Error distribution of calculated rotational constants for different functionals, also showing the effect of dispersion corrections.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Updated versions of these test sets have also been published, and are being used more routinely. Grimme likes to use these a lot for testing his &amp;quot;low cost&amp;quot; methods, which are intended for rapid geometry optimizations in large systems. One recent example is the testing of &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0040021&quot; rel=&quot;noreferrer&quot;&gt;r&lt;sup&gt;2&lt;/sup&gt;SCAN-3c&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, if you consider molecular crystals to be &amp;quot;big molecules,&amp;quot; you can see that proper vdW treatment is important to get correct lattice constants, for example for &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4916070&quot; rel=&quot;noreferrer&quot;&gt;ice&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2021-05-07T19:25:11.680" LastActivityDate="2021-05-07T19:25:11.680" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4951" PostTypeId="2" ParentId="4939" CreationDate="2021-05-07T18:31:54.867" Score="7" Body="&lt;p&gt;If you are talking about IR or Raman spectra, then B3LYP is essentially the best choice possible. But if you are talking about UV-Vis, and if the excited states of the pesticide contain significant charge transfer character, then you must use a range-separated hybrid functional (like wB97XD) or a double hybrid functional (like B2PLYP or PWPB95). Functionals like B3LYP describe local excitations well but tend to underestimate the energies of charge transfer states (giving rise to the so-called &amp;quot;ghost states&amp;quot;), range-separated hybrids describe charge transfer states well but usually overestimate the energies of local excitations, and double hybrids do both kinds of excitations well yet at a higher cost.&lt;/p&gt;&#xA;&lt;p&gt;If your molecule is within ca. 50 atoms, and if you are using ORCA, you may also want to try STEOM-DLPNO-CCSD, which is a wavefunction method that is even more reliable than double hybrids (yet of course with an even higher cost).&lt;/p&gt;&#xA;&lt;p&gt;Finally please note that, regardless of what functional you use in the UV-Vis calculation, the geometry optimization of your molecules can always be done with B3LYP (and I especially recommend B3LYP for this purpose).&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-05-07T18:31:54.867" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4952" PostTypeId="2" ParentId="4940" CreationDate="2021-05-07T19:38:58.117" Score="3" Body="&lt;p&gt;To specifically solve the issue with the velocity command, you can use a different &lt;code&gt;loop&lt;/code&gt; style. Now, you're using the style &lt;code&gt;all&lt;/code&gt;, which requires consecutive atom ids. Other styles, like &lt;code&gt;local&lt;/code&gt; and &lt;code&gt;geom&lt;/code&gt; don't but there are reasons why they aren't the default. It is explained in the &lt;a href=&quot;https://lammps.sandia.gov/doc/velocity.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps other aspects of the simulation also require consecutive ids, but you can at least work around that particular error.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2021-05-07T19:38:58.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4953" PostTypeId="1" CreationDate="2021-05-08T04:26:19.807" Score="12" ViewCount="631" Body="&lt;p&gt;I know Gaussian 16 can do it, but are there some free programs that can?&lt;/p&gt;&#xA;&lt;p&gt;For simple excited state calculations using TD-DFT, we can use NWChem and Octopus. Can these do Franck-Condon factors?&lt;/p&gt;&#xA;" OwnerUserId="3533" LastEditorUserId="5" LastEditDate="2021-06-28T22:45:07.437" LastActivityDate="2021-06-30T22:16:14.987" Title="Is there some free software to do Frank-Condon analysis?" Tags="|one-topic-per-answer|software-recommendations|spectroscopy|open-source|free-software|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4954" PostTypeId="2" ParentId="4946" CreationDate="2021-05-08T11:05:51.217" Score="8" Body="&lt;p&gt;Additive dispersion correction methods such as D3, D3(BJ), D3(BJ)+ATM, TS, MBD@rsSCS, etc. are good for geometry optimizations. These methods find the London dispersion interactions governed interlayer distance lower than the mean relative error of 2%. On the other hand, it's a good idea to avoid using these methods for energy calculations. For example, these methods overestimate the interlayer binding and exfoliation energies of 2D materials between MRE 20% and 80%&lt;/p&gt;&#xA;&lt;p&gt;There are just a few methods available for both reliable geometry and energy calculations. High-level ACFDT-RPA (Computationally very expensive), SCAN-rVV10, and PBE-rVV10.&lt;/p&gt;&#xA;" OwnerDisplayName="user3455" LastActivityDate="2021-05-08T11:05:51.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4955" PostTypeId="2" ParentId="4946" CreationDate="2021-05-09T00:47:39.947" Score="7" Body="&lt;p&gt;&lt;strong&gt;tldr; Use dispersion correction for optimization&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I asked a &lt;a href=&quot;https://chemistry.stackexchange.com/q/57132/5017&quot;&gt;very similar question&lt;/a&gt; a few years ago. Many indications for dispersion corrections in density functional methods are for  &lt;em&gt;intermolecular&lt;/em&gt;  interactions. Clearly these  corrections  are important in such intermolecular or long-range interactions (e.g., inter-layer spacing in a material.. far from the bonding regime).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4950/30&quot;&gt;Kristof Bal's answer&lt;/a&gt; gives one insight, based on molecular rotational constants.&lt;/p&gt;&#xA;&lt;p&gt;Our group published a benchmark, considering ~6500 conformer geometries across ~650 molecules. Using high-level DLPNO-CCSD(T) / def2-TZVP energies, we found a huge increase in accuracy (from several metrics) when using dispersion correction at minuscule cost in time.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1002/qua.26381&quot; rel=&quot;noreferrer&quot;&gt;'Assessing conformer energies using electronic structure and machine learning methods' &lt;em&gt;Int. J. Quantum Chem.&lt;/em&gt; &lt;strong&gt;2020&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, the mean &lt;span class=&quot;math-container&quot;&gt;$R^2$&lt;/span&gt; correlation between B3LYP and DLPNO-CCSD(T) energies was 0.706 without dispersion and 0.920 with -D3BJ dispersion correction. Similar effects were seen with other functionals.&lt;/p&gt;&#xA;&lt;p&gt;Our conclusion is that intramolecular non-bonded interactions are handled better, reflecting medium-to-long range behavior of standard chemical functionals.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-05-09T00:47:39.947" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4956" PostTypeId="1" AcceptedAnswerId="6134" CreationDate="2021-05-09T10:50:14.623" Score="9" ViewCount="702" Body="&lt;p&gt;I am trying to calculate electronically excited states for the CO molecule, with the &lt;code&gt;aug-cc-pVTZ&lt;/code&gt; basis set, and a CASSCF calculation. &lt;a href=&quot;https://www.molpro.net/info/release/doc/quickstart/node18.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;The documentation&lt;/a&gt; describes how I select the number of orbitals in the closed and active spaces for each symmetry (in &lt;a href=&quot;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=402&amp;amp;option=4&quot; rel=&quot;nofollow noreferrer&quot;&gt;the C&lt;sub&gt;2v&lt;/sub&gt; point group&lt;/a&gt;). But I can't find information about the criteria that is used for selecting which orbitals will be the active ones in each symmetry.&lt;/p&gt;&#xA;&lt;p&gt;Using the command &lt;code&gt;orbprint,12&lt;/code&gt; I can tell that orbitals are not selected simply in increasing energy order (since some unoccupied orbitals have lower energy than the occupied ones).&lt;/p&gt;&#xA;&lt;p&gt;How does Molpro pick out orbitals for the active space? And, can I control this process if I am not happy with some particular selection?&lt;/p&gt;&#xA;&lt;p&gt;A condensed version of my input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;***,CASSCF test&#xA;&#xA;MEMORY,2,G&#xA;&#xA;GEOMETRY = {&#xA;  C&#xA;  O, C, qco&#xA;}&#xA;&#xA;basis = aug-cc-pVTZ&#xA;&#xA;dq = 0.125&#xA;DO qco = 1, 10, dq&#xA;  IF (qco.EQ.1.5) dq = 0.0625&#xA;  IF (qco.EQ.3) dq = 0.125&#xA;  IF (qco.EQ.4) dq = 0.25&#xA;  IF (qco.EQ.5) dq = 0.5&#xA;  IF (qco.EQ.6) dq = 1&#xA;&#xA;  CASSCF&#xA;    orbprint,12&#xA;    closed,2,0,0,0&#xA;    occ,6,3,3,2&#xA;    wf,14,1,0&#xA;      state,5&#xA;  &#xA;  ! Storing distance, energy, and tr-dip-mom. in memory [..]&#xA;&#xA;END DO&#xA;&#xA;! Saving all computed values to disk [..]&#xA;&#xA;---&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For nuclear distance 2.75, these are eight orbitals in each symmetry. Taken from the output file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Orbital  Occupation       Energy&#xA; 1.1        2.00000    -20.72392&#xA; 2.1        2.00000    -11.41840&#xA; 3.1        1.99027     -1.38533&#xA; 4.1        1.93048     -0.81010&#xA; 5.1        1.55554     -0.48414&#xA; 6.1        0.07730      0.43260&#xA; 7.1       -0.00000      0.06413&#xA; 8.1       -0.00000      0.08645&#xA; 1.2        1.73314     -0.55388&#xA; 2.2        0.54582     -0.05416&#xA; 3.2        0.01415      0.95790&#xA; 4.2       -0.00000      0.09084&#xA; 5.2       -0.00000      0.25216&#xA; 6.2       -0.00000      0.48245&#xA; 7.2       -0.00000      0.57317&#xA; 8.2       -0.00000      0.77930&#xA; 1.3        1.55073     -0.50443&#xA; 2.3        0.39516     -0.01699&#xA; 3.3        0.19777      0.09396&#xA; 4.3       -0.00000      0.17954&#xA; 5.3       -0.00000      0.37646&#xA; 6.3       -0.00000      0.50901&#xA; 7.3       -0.00000      0.77746&#xA; 8.3       -0.00000      1.00082&#xA; 1.4        0.00610      1.10176&#xA; 2.4        0.00353      2.22594&#xA; 3.4       -0.00000      0.47199&#xA; 4.4       -0.00000      1.09344&#xA; 5.4       -0.00000      1.21291&#xA; 6.4       -0.00000      2.37566&#xA; 7.4       -0.00000      3.10900&#xA; 8.4       -0.00000      3.49887&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3536" LastEditorUserId="3536" LastEditDate="2021-05-10T10:47:27.663" LastActivityDate="2021-06-12T11:28:55.850" Title="How does MOLPRO choose active orbitals in a CASSCF calculation?" Tags="|molpro|casscf|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4957" PostTypeId="1" AcceptedAnswerId="5003" CreationDate="2021-05-09T19:43:08.920" Score="8" ViewCount="807" Body="&lt;p&gt;I had run an SCF calculation on a crystal system in Quantum ESPRESSO and had collected the converged charge density. However, during the NSCF calculation, there is the generation of &lt;code&gt;.wfc&lt;/code&gt; files which are quite large in size to save in my system. My system is also interrupting the job due to the saturation of space available.&lt;/p&gt;&#xA;&lt;p&gt;So, I am wondering how I can handle these files, and do the density of states calculation? Do I really need these files? Can I use the &lt;code&gt;disk_io='none'&lt;/code&gt;, option to prevent &lt;code&gt;.wfc&lt;/code&gt; files from being saved on my system?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; I have uploaded the scf.in,scf.out,nscf.in,nscf.out files &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/4957&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="85" LastEditDate="2021-05-21T10:22:16.823" LastActivityDate="2021-05-21T10:22:16.823" Title="Can I run an nscf calculation in Quantum ESPRESSO with disk_io='none'?" Tags="|quantum-espresso|ab-initio-calculations|high-performance-computing|density-of-states|self-consistent-field|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="4958" PostTypeId="1" CreationDate="2021-05-10T11:35:18.507" Score="5" ViewCount="175" Body="&lt;p&gt;I am trying to compare the energies of the excited states of &lt;span class=&quot;math-container&quot;&gt;$\ce{C12H9N}$&lt;/span&gt; molecule using the CIS and CISD module implemented in the quantum chemistry package in GAMESS.&lt;/p&gt;&#xA;&lt;p&gt;While I can easily obtain the results with the CIS module, the implementation of CISD module seems difficult and my program crashes every time. It will be really helpful if anyone can let me how to calculate the excited states with singles and doubles excitation.&lt;/p&gt;&#xA;&lt;p&gt;An example would really help.&lt;/p&gt;&#xA;" OwnerUserId="3556" OwnerDisplayName="Debo Chaudhuri" LastEditorUserId="7" LastEditDate="2021-05-20T18:08:22.187" LastActivityDate="2021-05-20T18:08:22.187" Title="Calculating excited states using GAMESS CISD module" Tags="|quantum-chemistry|electronic-structure|gamess|" AnswerCount="0" CommentCount="6" ClosedDate="2021-06-23T21:38:40.103" ContentLicense="CC BY-SA 4.0" />
  <row Id="4959" PostTypeId="1" AcceptedAnswerId="4960" CreationDate="2021-05-10T17:28:19.883" Score="9" ViewCount="271" Body="&lt;p&gt;We asked a similar question somewhere else and someone advised trying here instead.&lt;/p&gt;&#xA;&lt;p&gt;How should we calculate &lt;span class=&quot;math-container&quot;&gt;$\langle A\rangle \langle A\rangle$&lt;/span&gt; from data on dipole moments?  It is a term in an equation for calculating something else.  Some example data:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;x      y      z         Total&#xA;26.78  -6.31  27.17     38.67&#xA;26.80  -5.79  27.33     38.72&#xA;26.75  -5.28  27.415    38.67&#xA;26.63  -4.79  27.41     38.52&#xA;26.45  -4.34  27.36     38.31&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;&amp;lt;&amp;gt;&lt;/code&gt; symbol means &amp;quot;average.&amp;quot;  On each row, &lt;code&gt;Total&lt;/code&gt; is the square root of the sum of squares of the &lt;code&gt;x&lt;/code&gt;, &lt;code&gt;y&lt;/code&gt; and &lt;code&gt;z&lt;/code&gt;. Each row is a new time.&lt;/p&gt;&#xA;&lt;p&gt;It is part of an expression to calculate variance &lt;span class=&quot;math-container&quot;&gt;$\big(\langle A \cdot A\rangle - \langle A\rangle \langle A\rangle\big)$&lt;/span&gt;.  We are confused because someone has suggested that &lt;code&gt;np.var(Total)&lt;/code&gt; from Python or a corresponding function from Matlab are not the way to calculate it because they eliminate any negative signs on component values and make &lt;span class=&quot;math-container&quot;&gt;$\langle A\rangle \langle A\rangle$&lt;/span&gt; too large.&lt;/p&gt;&#xA;&lt;p&gt;Is this true?  Should we use &lt;code&gt;np.mean(x)**2+np.mean(y)**2+np.mean(z)**2&lt;/code&gt; for &lt;span class=&quot;math-container&quot;&gt;$\langle A\rangle \langle A\rangle$&lt;/span&gt; instead?&lt;/p&gt;&#xA;" OwnerUserId="3559" LastEditorUserId="5" LastEditDate="2021-05-10T18:21:36.483" LastActivityDate="2021-05-11T00:18:22.077" Title="What is the right way to calculate &lt;A&gt;&lt;A&gt;?" Tags="|python|from-phys-se|dipole|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4960" PostTypeId="2" ParentId="4959" CreationDate="2021-05-11T00:18:22.077" Score="9" Body="&lt;p&gt;The dipole moment is typically a vector quantity, and the &amp;quot;&lt;a href=&quot;https://chem.libretexts.org/Bookshelves/General_Chemistry/Book%3A_General_Chemistry_Supplement_(Eames)/Valence_Bond_Theory/Dipole_Moments&quot; rel=&quot;noreferrer&quot;&gt;total dipole moment&lt;/a&gt;&amp;quot; which is the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; in your question description and the black arrow in the figure below, is the &lt;em&gt;vector sum&lt;/em&gt; of all constituent dipole moments  the system (red arrows in the figure below):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IKyIx.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IKyIx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In your case you have vectors such as: &lt;span class=&quot;math-container&quot;&gt;$26.78 \, \hat{x}   -6.31\, \hat{y} +  27.17\, \hat{z}$&lt;/span&gt;, which ought to represent the black arrow in the above figure.&lt;/p&gt;&#xA;&lt;p&gt;To get the length of the black arrow, you would calculate:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;A = \sqrt{x^2 + y^2 + z^2},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which the &lt;span class=&quot;math-container&quot;&gt;$x,y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; values correspond exactly to the x, y, and z columns in your table (I've confirmed that you have calculated at least the first one correctly).&lt;/p&gt;&#xA;&lt;p&gt;Next you want the time-averaged value of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, which is denoted by &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle$&lt;/span&gt;. Since each row in your table represents one point in time, you would simply add the values in each column and divide the totals by the number of time steps for which you have data.&lt;/p&gt;&#xA;&lt;p&gt;I did this in &lt;a href=&quot;https://octave-online.net/&quot; rel=&quot;noreferrer&quot;&gt;Octave online&lt;/a&gt; since it's the fastest way for me to do the calculation, and doesn't require importing NymPy or typing extra &lt;code&gt;np.&lt;/code&gt; characters but you can easily do it in Python too:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mean([38.67 38.72 38.67 38.52 38.31])&#xA;ans = 38.578&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Therefore we have &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle = 38.578$&lt;/span&gt; and  &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle \langle A \rangle \equiv \langle A \rangle ^2 = 38.578^2 = 1488$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Notice that &lt;span class=&quot;math-container&quot;&gt;$\langle A \rangle ^2$&lt;/span&gt; is not the same as &lt;span class=&quot;math-container&quot;&gt;$\langle A^2 \rangle$&lt;/span&gt;, as explained &lt;a href=&quot;https://en.wikipedia.org/wiki/Electric_dipole_moment#Dipole_moments_of_molecules&quot; rel=&quot;noreferrer&quot;&gt;here for the specific case of dipole moments&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-11T00:18:22.077" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4961" PostTypeId="1" AcceptedAnswerId="4962" CreationDate="2021-05-11T05:37:28.000" Score="9" ViewCount="313" Body="&lt;p&gt;I am currently learning DFTB+ using the tutorials on the official website :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Carbon Nanoribbons&lt;/strong&gt; : &lt;a href=&quot;https://dftbplus-recipes.readthedocs.io/en/latest/defect/carbon2d-elec.html#zigzag-nanoribbon&quot; rel=&quot;noreferrer&quot;&gt;https://dftbplus-recipes.readthedocs.io/en/latest/defect/carbon2d-elec.html#zigzag-nanoribbon&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Molecular Junctions&lt;/strong&gt; : &lt;a href=&quot;https://dftbplus-recipes.readthedocs.io/en/latest/transport/molecule-junction.html&quot; rel=&quot;noreferrer&quot;&gt;https://dftbplus-recipes.readthedocs.io/en/latest/transport/molecule-junction.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;How do I go about creating the geometry files for the systems used in these tutorials?&lt;/p&gt;&#xA;&lt;p&gt;So far, I have been using Avogadro for creating xyz files but I haven't created &amp;quot;planar periodic&amp;quot; structures as illustrated in the tutorials.&lt;/p&gt;&#xA;" OwnerUserId="3561" LastEditorUserId="5" LastEditDate="2021-05-11T15:36:38.940" LastActivityDate="2021-05-11T15:36:38.940" Title="How do I create geometry files for carbon nanoribbons and molecular junctions for DFTB+?" Tags="|from-chem-se|geometry|software-input-file-request|density-functional-tight-binding|dftb-plus|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4962" PostTypeId="2" ParentId="4961" CreationDate="2021-05-11T06:32:10.893" Score="7" Body="&lt;p&gt;Since you know how to use Avogadro to create XYZ files, a very simple solution to your problem is to simply create the XYZ file then use an &lt;code&gt;xyz2gen&lt;/code&gt; script to convert fron XYZ format to the GEN format you seek. &lt;a href=&quot;https://github.com/itamblyn/scripts/blob/master/dftb/dptools/bin/xyz2gen&quot; rel=&quot;noreferrer&quot;&gt;This is an example of a script that converts from XYZ to DFTB+ format&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The beauty of the GEN format of DFTB+ is that with only a few lines, you can &amp;quot;generate&amp;quot; the entire structure based on the periodicity of the system, which is specified by Cartesian lattice vectors. An excellent exercise to help you learn how this works is given at the &lt;a href=&quot;https://dftbplus-recipes.readthedocs.io/en/latest/defect/carbon2d-elec.html&quot; rel=&quot;noreferrer&quot;&gt;top&lt;/a&gt; of the first page you gave us in your question. Start at the origin and add atoms based on the vectors given: you'll find it quite cool how a 2D hexagonal lattice begins to &lt;em&gt;emerge!&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-11T06:32:10.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4964" PostTypeId="1" AcceptedAnswerId="4966" CreationDate="2021-05-11T12:59:27.463" Score="7" ViewCount="513" Body="&lt;p&gt;How may I generate Electron Density Field information using Density Functional Theory calculations? What would my required inputs be like in VASP or Quantum ESPRESSO?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-05-11T16:19:04.087" LastActivityDate="2021-05-11T19:00:12.620" Title="How to generate Electron Density Fields using DFT?" Tags="|density-functional-theory|vasp|quantum-espresso|from-chem-se|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4965" PostTypeId="1" AcceptedAnswerId="8562" CreationDate="2021-05-11T16:34:54.917" Score="8" ViewCount="151" Body="&lt;p&gt;I am considering layered oxides &lt;span class=&quot;math-container&quot;&gt;$\ce{LiCoO2}$&lt;/span&gt;. Previous papers suggested that vdW interaction should be added to get lattice parameters closer to experimental data. I would like to dope other elements to Co sites of layered &lt;span class=&quot;math-container&quot;&gt;$\ce{LiCoO2}$&lt;/span&gt; and calculate the formation energy of the doped structure. In the formula for estimating formation energy, I need to know the chemical potentials of dopant elements. For example,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\textrm{formation energy} = E(\ce{LiCo}_{1-y}\ce{Na_yO_2})-[E(\ce{LiCoO2})+yE(\ce{Na})-yE(\ce{Co})]\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The idea of adding vdW to estimate chemical potential seems to be strange, but I still wonder if I should add vdW interaction to calculate the chemical potentials of dopant elements? I found that when I add vdW interaction to calculated Na chemical potential, there is a big gap compared to results without adding vdW. For example, &lt;span class=&quot;math-container&quot;&gt;$E(\ce{Na}_{\textrm{vdwD3}})$&lt;/span&gt; = -0.385 eV, E(Na_without vdW)= -1.283eV (using same calculation parameters such as &lt;code&gt;ENCUT&lt;/code&gt;, &lt;code&gt;K-POINTS&lt;/code&gt; in VASP).&lt;/p&gt;&#xA;&lt;p&gt;Adding to the complexity is the difference in listed chemical potentials based on the phase of the compounds. For example, the chemical potential &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; of Na is listed as both 0 (solid) and 0.5 kG (liquid): &lt;a href=&quot;https://www.job-stiftung.de/index.php?data-collection&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.job-stiftung.de/index.php?data-collection&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="4515" LastEditDate="2022-07-30T14:21:46.033" LastActivityDate="2022-07-30T14:21:46.033" Title="Should I add vdW interaction to estimate chemical potential of metallic elements?" Tags="|thermodynamics|intermolecular-forces|dispersion-correction|" AnswerCount="1" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4966" PostTypeId="2" ParentId="4964" CreationDate="2021-05-11T19:00:12.620" Score="4" Body="&lt;p&gt;I am assuming you mean just the electron density (as its typically referred to in my experience).  In that case, if using VASP, you just set &lt;code&gt;LCHARG = .TRUE.&lt;/code&gt; and you can load the CHGCAR file in a program such as VESTA.&lt;/p&gt;&#xA;&lt;p&gt;You can also view the charge density of a specific band / kpoint.  &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Band_decomposed_charge_densities&quot; rel=&quot;nofollow noreferrer&quot;&gt;This page on the VASP wiki&lt;/a&gt; will help you set up your desired calculation.  This can be helpful to view the conductance / valence bands for example.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-05-11T19:00:12.620" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4967" PostTypeId="1" AcceptedAnswerId="4968" CreationDate="2021-05-12T01:55:26.787" Score="8" ViewCount="1478" Body="&lt;p&gt;I have successfully completed the SCF of doped system Ni doped ZnO using GGA+U. I have checked the SCF.out file and found  the energy value : E= -6112.0389 Ry.&lt;/p&gt;&#xA;&lt;p&gt;Hwo to calculate the formation energy of doped system using this &lt;span class=&quot;math-container&quot;&gt;$formula^1$&lt;/span&gt; ?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_f = E(doped_{ZnO}) -E_{ZnO}+2(\mu_{Zn}+\mu_{Ni}) $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where I can find the chemical value of Zn and Ni (&lt;span class=&quot;math-container&quot;&gt;$\mu_{Zn},\mu_{Ni}$&lt;/span&gt;) in my outputfil.&lt;/p&gt;&#xA;&lt;p&gt;Also I would like to know what is the minimum formation energy for a crystal to be stable?&lt;/p&gt;&#xA;&lt;p&gt;Your help will be appreciated&lt;/p&gt;&#xA;&lt;p&gt;(1). &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssb.201700098&quot; rel=&quot;noreferrer&quot;&gt;Effect of two identical 3d transition‐metal atoms M doping (M = V, Cr, Mn, Fe, Co, and Ni) on the structural, electronic, and magnetic properties of ZnO&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="5" LastEditDate="2021-05-12T02:04:16.877" LastActivityDate="2023-08-20T15:54:19.987" Title="How To calculate formation energy of Ni doped ZnO system in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|dft-u|formation-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4968" PostTypeId="2" ParentId="4967" CreationDate="2021-05-12T09:37:29.463" Score="3" Body="&lt;p&gt;Based on reference paper given above, the reference system of interest here is &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn_{22}M_{2}O_{24}}$&lt;/span&gt;.&#xA;As two &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt; atoms were substituted by transition metal (&lt;span class=&quot;math-container&quot;&gt;$M=\ce{V}, \ce{Cr}, \ce{Mn}, \ce{Fe}, \ce{Co}, \ce{Ni}).$&lt;/span&gt; Formation energy for doping is given as&#xA;&lt;span class=&quot;math-container&quot;&gt;$E_f = E(doped_{\ce{ZnO}}) -E_{\ce{ZnO}}+2(\mu_{\ce{Zn}}-\mu_{\ce{Ni}}) $&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$ E(doped_{\ce{ZnO}})$&lt;/span&gt; is total energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn_{22}M_{2}O_{24}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{\ce{ZnO}}$&lt;/span&gt; is energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn_{24}O_{24}}$&lt;/span&gt;. The chemical potentials of the &lt;span class=&quot;math-container&quot;&gt;$\ce{V}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Cr}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Mn}$&lt;/span&gt;, or &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt; are energies of single atom in the body centered cubic structure, where as in case of &lt;span class=&quot;math-container&quot;&gt;$\ce{Co}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt;, hexagonal crystal structure and face centered cubic structure were considered respectively. For &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt; they have considered considered two state, one &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt; as its elementary substance and second as &lt;span class=&quot;math-container&quot;&gt;$\mu_{\ce{Zn}}=E_{\ce{ZnO}}-\mu_{\ce{O}}$&lt;/span&gt; where  &lt;span class=&quot;math-container&quot;&gt;$\mu_{\ce{O}}$&lt;/span&gt; is energy of oxygen as elementary substance. For stability of any structure you can do mechanical(elastic constants) and dynamic stability(phonon) calculations. Based on formation energy one can say that if it is negative, such doping are more favorable.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2023-08-20T15:54:19.987" LastActivityDate="2023-08-20T15:54:19.987" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4969" PostTypeId="1" AcceptedAnswerId="4970" CreationDate="2021-05-12T11:01:54.203" Score="8" ViewCount="207" Body="&lt;p&gt;I want to create a POSCAR or CIF file file for the monolayers with the data mentioned in the table below :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lBNNR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lBNNR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Knowing that the spacegroup is : R-3 (148)&lt;/p&gt;&#xA;&lt;p&gt;Could you please create the POSCAR/CIF for these 3 monolayers and show me the way you did it?&lt;/p&gt;&#xA;&lt;p&gt;Reference paper : &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.103.075433&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.103.075433&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-05-12T19:35:07.950" LastActivityDate="2021-05-12T19:35:07.950" Title="How to create the structure file for these materials?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4970" PostTypeId="2" ParentId="4969" CreationDate="2021-05-12T11:37:42.620" Score="5" Body="&lt;ul&gt;&#xA;&lt;li&gt;MoI3:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ref: &lt;a href=&quot;http://www.2dmatpedia.org/2dmaterials/doc/2dm-699&quot; rel=&quot;noreferrer&quot;&gt;http://www.2dmatpedia.org/2dmaterials/doc/2dm-699&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Monolayer MoBr3 and MoCl3 can be obtained by modifying the structure of MoI3 with the provided parameters.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;2D materials database:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ref: &lt;a href=&quot;http://www.2dmatpedia.org/query?collection=2dmaterials&amp;amp;search_string=top-down&quot; rel=&quot;noreferrer&quot;&gt;http://www.2dmatpedia.org/query?collection=2dmaterials&amp;amp;search_string=top-down&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Related:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3881/reliability-about-the-predicted-two-dimensional-crystal-structures-based-on-dft&quot;&gt;Reliability about the predicted two-dimensional crystal structures based on DFT high-throughput calculation?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-05-12T11:37:42.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4971" PostTypeId="1" CreationDate="2021-05-12T15:45:10.070" Score="20" ViewCount="331" Body="&lt;p&gt;A &lt;b&gt;dataset&lt;/b&gt; is generally a collection of data.&lt;/p&gt;&#xA;&lt;p&gt;A &lt;b&gt;database&lt;/b&gt; is an organized collection of data, allowing different kinds of queries.&lt;/p&gt;&#xA;&lt;p&gt;A &lt;b&gt;dashboard&lt;/b&gt; is a graphical user interface that is employed to make sense of a dataset that is too large or complex to be simply visualized in a small number of plots.&lt;/p&gt;&#xA;&lt;p&gt;We all know crystallographic databases have been around for a long time, and an effort is now ongoing to include the results of materials modelling in databases too. My question is however on &lt;strong&gt;graphically navigating experimental data on molecular materials&lt;/strong&gt; beyond X-ray crystallography.&lt;/p&gt;&#xA;&lt;p&gt;I have found several specialized databases and dashboards, oriented towards accelerated materials discovery, for &amp;quot;solid state&amp;quot; (extended) materials , e.g. &lt;a href=&quot;https://www.topologicalquantumchemistry.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this topological materials database&lt;/a&gt; or this &lt;a href=&quot;http://aam.ceb.cam.ac.uk/mof-explorer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;dashboard for Metal Organic Frameworks&lt;/a&gt; (see figure 1 below). By collecting existing data, they facilitate finding trends and exploring in new directions. There are of course also many similar efforts in the pharmaceutical industry.&lt;/p&gt;&#xA;&lt;p&gt;It seems however that in other fields of chemistry and molecular materials science these tools are less common. In our group we recently manually data-mined the bibliography to build a dataset and a dashboard for &lt;a href=&quot;https://rosaleny.shinyapps.io/simdavis_dashboard/&quot; rel=&quot;nofollow noreferrer&quot;&gt;experimental data visualization in molecular nanomagnets&lt;/a&gt;  (see figure 2 below). We plan to use this to open new routes for materials modelling in this field. I am sure there have to be other examples beyond solid state materials and molecules oriented towards pharmaceutical applications, but am having a hard time finding them.&lt;/p&gt;&#xA;&lt;p&gt;Can people point towards analogous &lt;strong&gt;dashboards&lt;/strong&gt; beyond these two fields? A couple of example screenshots are included to give a graphical idea beyond the very brief definition for &lt;em&gt;dashboard&lt;/em&gt; above.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lH0dR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lH0dR.png&quot; alt=&quot;Dashboard for Metal Organic Frameworks&quot; /&gt;&lt;/a&gt;&#xA;Figure 1: Dashboard for Metal Organic Frameworks at &lt;a href=&quot;http://aam.ceb.cam.ac.uk/mof-explorer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOF Data Explorer&lt;/a&gt;. (Moghadam, P.Z., Islamoglu, T., Goswami, S. et al. Computer-aided discovery of a metal–organic framework with superior oxygen uptake. Nat Commun 9, 1378 (2018). &lt;a href=&quot;https://doi.org/10.1038/s41467-018-03892-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/s41467-018-03892-8&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ojcoc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ojcoc.png&quot; alt=&quot;Dashboard for Single Ion Magnets&quot; /&gt;&lt;/a&gt;&#xA;Figure 2: Dashboard for Single Ion Magnets at &lt;a href=&quot;https://rosaleny.shinyapps.io/simdavis_dashboard/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SIMDAVIS App&lt;/a&gt;. (Duan, Y., Rosaleny, L.E., Coutinho, J.T. et al. Data-driven design of molecular nanomagnets. Nat Commun 13, 7626 (2022). &lt;a href=&quot;https://doi.org/10.1038/s41467-022-35336-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/s41467-022-35336-9&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="198" LastEditDate="2022-12-11T05:51:27.397" LastActivityDate="2022-12-11T05:51:27.397" Title="Are there dashboards displaying experimental properties of molecular materials?" Tags="|physical-properties-of-materials|databases|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4972" PostTypeId="2" ParentId="4971" CreationDate="2021-05-12T17:04:02.923" Score="11" Body="&lt;p&gt;I'm not sure if this will exactly answer your question because dashboard is loosely defined, but I find &amp;quot;networks&amp;quot; to be a great way to represent reaction data.&lt;/p&gt;&#xA;&lt;p&gt;For example, Rxn4Chemistry categorizes reactions in a way that &amp;quot;would be too large or complex to be simply visualized in a small number of plots.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/s5Gl7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s5Gl7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://rxn4chemistry.github.io/rxnfp/tmaps/tmap_ft_10k.html&quot; rel=&quot;noreferrer&quot;&gt;https://rxn4chemistry.github.io/rxnfp/tmaps/tmap_ft_10k.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-05-12T17:04:02.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4973" PostTypeId="2" ParentId="3528" CreationDate="2021-05-12T23:29:03.460" Score="7" Body="&lt;p&gt;&lt;em&gt;This answer is partly based on the &lt;a href=&quot;https://compmatphys.epotentia.com/wp-content/uploads/2020/05/project_05b_EV-and-EOS.pdf&quot; rel=&quot;noreferrer&quot;&gt;Computational Materials Physics Course by Stefaan Cottenier&lt;/a&gt;.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Follow the steps provided below:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Prepare a text file with two columns, the first column being the unit cell volume (a.u^3 or Å^3) of each of your calculations, the second column being the corresponding total energy (Ry).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Type &lt;code&gt;ev.x&lt;/code&gt; in the terminal, which will ask you some questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;Lattice parameter or Volume are in (au, Ang)&lt;/code&gt; Type: &lt;code&gt;au&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Enter type of bravais lattice (fcc, bcc, sc, noncubic)&lt;/code&gt; The type of Bravais lattice: for FCC, BCC, and SC lattices you have to specify the lattice parameter in your input text file. For all other ‘noncubic’ lattices, this should be the volume. Type: &lt;code&gt;noncubic&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Enter type of equation of state: 1 = birch1, 2 = birch2, 3 = keane, 4 = murnaghan&lt;/code&gt;. Type: &lt;code&gt;1&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Input file&lt;/code&gt;. Type the name of your input file, e.g., &lt;code&gt;EOSInput.txt&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Output file&lt;/code&gt;. Type the name of your output file, e.g., &lt;code&gt;EOSOutput.txt&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The output file will contain the equilibrium volume, &lt;code&gt;V0&lt;/code&gt;, and the bulk modulus, &lt;code&gt;k0&lt;/code&gt;, obtained from fitting a Birch-Murnaghan equation of state through your data points. The output file looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# equation of state: birch 1st order.  chisq =   0.5885D-11&#xA;# V0 =  324.74 a.u.^3,  k0 = 3006 kbar,  dk0 =  4.17  d2k0 =  0.000  emin = -260.59336&#xA;# V0 =   48.12  Ang^3,  k0 = 300.6 GPa&#xA;&#xA;##########################################################################&#xA;# Vol.        E_calc        E_fit       E_diff    Pressure      Enthalpy&#xA;# a.u.^3        Ry           Ry            Ry        GPa           Ry&#xA;##########################################################################&#xA;  288.10    -260.54145    -260.54145    -0.00000      46.22     -259.63621&#xA;  296.70    -260.56445    -260.56445     0.00000      32.78     -259.90321&#xA;  305.47    -260.58037    -260.58037    -0.00000      20.90     -260.14641&#xA;  314.41    -260.58981    -260.58980    -0.00000      10.40     -260.36755&#xA;  323.52    -260.59331    -260.59331    -0.00000       1.14     -260.56823&#xA;  332.81    -260.59139    -260.59139     0.00000      -7.01     -260.74998&#xA;  342.27    -260.58452    -260.58452    -0.00000     -14.17     -260.91416&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2021-05-13T02:29:03.350" LastActivityDate="2021-05-13T02:29:03.350" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="4974" PostTypeId="1" CreationDate="2021-05-13T00:16:46.607" Score="11" ViewCount="125" Body="&lt;p&gt;Cross-posted &lt;a href=&quot;https://physics.stackexchange.com/questions/635887/wavefunction-magnitudes-being-degenerate-everywhere-on-parameter-space-even-thou&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Consider &lt;a href=&quot;https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/3/67057/files/2018/09/graphene_tight-binding_model-1ny95f1.pdf&quot; rel=&quot;noreferrer&quot;&gt;the usual simple 2-level gapless graphene Hamiltonian&lt;/a&gt; in momentum-space where the energy dispersion is degenerate/gapless at a Dirac point:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{1}&#xA;{\small&#xA;H(k,M)=-t \sum_{\delta} [\cos(k\cdot\delta)\sigma_x-\sin(k\cdot\delta)\sigma_y+M\sigma_z],}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is the hopping, &lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; are Pauli matrices, &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; lattice vectors and &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; an on-site potential (&lt;span class=&quot;math-container&quot;&gt;$M=0$&lt;/span&gt; for graphene).&lt;/p&gt;&#xA;&lt;p&gt;When I solve for its wavefunctions both numerically and analytically, the eigenvectors/wavefunctions themselves are complex numbers with an arbitrary complex phase (as expected, depending on the numerical software used). The complex values of the wavefunction at different points on parameter space are different, also as expected.&lt;/p&gt;&#xA;&lt;p&gt;However, I noticed that the complex magnitude of the eigenvectors are &lt;span class=&quot;math-container&quot;&gt;$(\frac{1}{\sqrt2},\frac{1}{\sqrt2})^T$&lt;/span&gt; for all values of &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt;. By 'complex magnitude', I mean: Each eigenvector &lt;span class=&quot;math-container&quot;&gt;$|\psi_i\rangle\equiv z$&lt;/span&gt; is a complex-valued vector with two row elements. Being a complex number, each element may be written as &lt;span class=&quot;math-container&quot;&gt;$|z|e^{i\theta}$&lt;/span&gt; for the complex magnitude &lt;span class=&quot;math-container&quot;&gt;$|z|$&lt;/span&gt; and complex phase &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;. So, in this case, the wavefunctions share the same normalization &lt;span class=&quot;math-container&quot;&gt;$(\frac{1}{\sqrt2},\frac{1}{\sqrt2})^T = \frac{1}{\sqrt{2}}(1,1)^T$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This does not sit well with me because, if I add a small on-site potential/mass to the graphene Hamiltonian  to gap the system (&lt;span class=&quot;math-container&quot;&gt;$M\neq0$&lt;/span&gt; above; so that the dispersion is non-degenerate everywhere on k-space), these wavefunction magnitudes change depending on &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt;. So, as expected, there is a higher magnitude at the Dirac points (as in the first picture below). But, the magnitude is constant everywhere when &lt;span class=&quot;math-container&quot;&gt;$M=0$&lt;/span&gt; (graphene, second picture), even though I expected it to be a Dirac delta function-like peak at the Dirac points.&lt;/p&gt;&#xA;&lt;p&gt;I know that Berry-quantities such as the Berry curvature cannot be defined because of the degeneracy, but I want to understand the root and significance of the degenerate wavefunction magnitudes &lt;strong&gt;everywhere in parameter space&lt;/strong&gt;. Besides the common probability interpretation (integration squared = probability = &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}$&lt;/span&gt; in this case), is there anything else about quantum mechanics / Hilbert spaces / numerical work / physics that this magnitude-observation sheds light on, keeping the issue of gapped vs gapless in perspective? Or is the observed magnitude indicative of the wavefunctions not being well-defined away from the gapless point? What I don't understand is the reason all this happens, and any insight/significance of this.&lt;/p&gt;&#xA;&lt;p&gt;First picture: Magnitude of one row element of one wavefunction in k-space when &lt;span class=&quot;math-container&quot;&gt;$M\neq0$&lt;/span&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/fYkVk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fYkVk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Second picture: Magnitude of one row element of one wavefunction in k-space when &lt;span class=&quot;math-container&quot;&gt;$M=0$&lt;/span&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/8riVJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8riVJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-11-23T21:27:10.177" LastActivityDate="2022-02-05T23:33:12.070" Title="Wavefunction magnitudes being degenerate everywhere on parameter space even though energy degeneracies occur at isolated points?" Tags="|condensed-matter|model-hamiltonians|from-phys-se|graphene|wavefunctions|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4975" PostTypeId="2" ParentId="4702" CreationDate="2021-05-13T15:52:10.110" Score="8" Body="&lt;p&gt;&lt;strong&gt;QSimulate&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;They advertise their ability to perform high throughput quantum mechanical simulations as well as large scale simulations on their web page. An e-mail address is provided for collaboration inquiries and other questions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://qsimulate.com/technology.html&quot; rel=&quot;noreferrer&quot;&gt;https://qsimulate.com/technology.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;An exemplary application is reported here:&#xA;&lt;a href=&quot;https://arxiv.org/abs/2004.08725&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/2004.08725&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="544" LastActivityDate="2021-05-13T15:52:10.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4976" PostTypeId="1" CreationDate="2021-05-14T08:10:06.137" Score="5" ViewCount="200" Body="&lt;p&gt;I studied a disordered state (FCC solid solution) and used a special quasirandom structure supercell with 32 atoms to represent the system. After relaxing it thoroughly with &lt;code&gt;VASP&lt;/code&gt;, I used &lt;code&gt;phonopy&lt;/code&gt; for the harmonic phonon calculation. Since the DFT supercell itself was big enough (32 atoms and ~6.5 angstroms along all three lattice vectors), I used a &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; supercell for the &lt;code&gt;phonopy&lt;/code&gt; calculation. I read somewhere that using a &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; supercell for phonon calculations is incorrect (no matter how big the cell is). I couldn't understand why. Is that actually the case, and if so, why?&lt;/p&gt;&#xA;" OwnerUserId="116" LastActivityDate="2021-05-14T09:19:24.400" Title="Supercell model for a disordered system in phonon calculations using the harmonic approximation" Tags="|phonons|special-quasirandom-structures|supercell|harmonic-approximation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4977" PostTypeId="2" ParentId="4976" CreationDate="2021-05-14T09:19:24.400" Score="5" Body="&lt;p&gt;If you have a system without periodicity like your disordered solid solution, then you should use a &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-point grid for a phonon calculation (equivalent to a &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; supercell). Using a larger supercell will introduce an artificial periodicity in the system.&lt;/p&gt;&#xA;&lt;p&gt;Having said this, it is still really important to converge with respect to system size in disordered systems. But what this means is that you should consider generating special quasirandom structures with more atoms in the quasirandom cell, and then for those doing again a &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; phonon calculation.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-05-14T09:19:24.400" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="4979" PostTypeId="1" CreationDate="2021-05-14T11:33:59.050" Score="8" ViewCount="163" Body="&lt;p&gt;I am trying to calculate the excited states using single reference CISD on &lt;span class=&quot;math-container&quot;&gt;$\ce{CH3OH},$&lt;/span&gt; using ORMAS' CI-X option in GAMESS. As a test example I am using the &lt;span class=&quot;math-container&quot;&gt;$\ce{CH3OH}$&lt;/span&gt; that has 2 core, 7 occ. valence, 39 empty MOs (50 AOs, 48 MOs). I am unable to understand the &lt;code&gt;$ormas&lt;/code&gt; flag in the following &lt;code&gt;ormas-meoh-cisd.inp&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!   single reference CISD on CH3OH, using ORMAS' CI-X option.&#xA;!          counting: 2 core, 7 occ. valence, 39 empty MOs (50 AOs, 48 MOs)&#xA;!          the resulting CI-SD has 53,964 Sz=0 A' determinants&#xA;!&#xA; &lt;span class=&quot;math-container&quot;&gt;$contrl scftyp=rhf cityp=ormas runtyp=energy ispher=1 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$system mwords=50 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$basis  gbasis=ccd $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$guess  guess=huckel $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$scf    dirscf=.true. $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$trans  dirtrf=.true. $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$cidet  group=Cs stsym=Ap ncore=2 nact=46 nels=14 nstate=3 $&lt;/span&gt;end&#xA; &lt;span class=&quot;math-container&quot;&gt;$ormas  nspace=2 mstart(1)=3,10 mine(1)=12,0&#xA;                                 maxe(1)=14,2 $&lt;/span&gt;end&#xA; $data&#xA;Methanol...CISD...RHF/6-31G(d) geometry&#xA;Cs&#xA;&#xA;H     1.0  -1.0616171503   0.8036449245   0.0000000000&#xA;O     8.0  -0.6870131482  -0.0653470836   0.0000000000&#xA;C     6.0   0.7093551399   0.0291827007   0.0000000000&#xA;H     1.0   1.0836641283   0.5408321444   0.8835398105&#xA;H     1.0   1.0975386849  -0.9797829903   0.0000000000&#xA; $end&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The following keywords are used in the &lt;code&gt;$ORMAS&lt;/code&gt; section:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nspace=2&#xA;mstart(1)=3,10&#xA;mine(1)=12,0&#xA;maxe(1)=14,2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I can understand the &lt;code&gt;nspace = 2&lt;/code&gt; means the active space is partitioned into doubly occupied + active and valence orbitals. However, I don't understand how the numbers pertinent to the rest of the flags in &lt;code&gt;$ORMAS&lt;/code&gt; are chosen. Any explanation would be really helpful and appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3576" OwnerDisplayName="Debopriyo Chaudhuri" LastEditorUserId="724" LastEditDate="2021-05-14T12:31:35.890" LastActivityDate="2021-06-24T14:34:53.757" Title="Excited states using ORMAS flag in GAMESS" Tags="|software|computational-chemistry|quantum-chemistry|gamess|excited-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4980" PostTypeId="1" CreationDate="2021-05-14T17:58:42.583" Score="15" ViewCount="3958" Body="&lt;p&gt;How can I create such a 3D plot using matplotlib? Like the one in Figure (a) below: &lt;a href=&quot;https://i.stack.imgur.com/rCDtD.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rCDtD.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want to create it using DFT bandstructure calculation result&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="984" LastEditDate="2021-05-14T22:45:01.930" LastActivityDate="2021-07-01T19:09:11.670" Title="How to create a 3D band structure from DFT band structure calculation?" Tags="|band-structure|python|visualization-software|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4981" PostTypeId="1" CreationDate="2021-05-14T21:11:47.823" Score="11" ViewCount="433" Body="&lt;p&gt;I am using a package called PySmiles and it is returning a dialect of SMILES for aromatic groups that uses aromatic bond symbols&#xA;e.g.&#xA;&lt;code&gt;NC:1:N:N:C:[N]1N&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;RDKit does not recognize these symbols  and it removes all the aromaticity.&lt;/p&gt;&#xA;&lt;p&gt;Interestingly, Openbabel Version 2.3.2 successfully canonicalizes this to &lt;code&gt;Nc1nncn1N&lt;/code&gt; but version 3.1.0 produces &lt;code&gt;NC1NNCN1N&lt;/code&gt; similar to what RDKit produces.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/openbabel/openbabel/issues/2368&quot; rel=&quot;noreferrer&quot;&gt;I've opened an issue on the Github Openbabel&lt;/a&gt; to address this issue but I'd like to ask it here (i.e. why does do versions 2.3.2 and 3.1.0 in OpenBabel give different results?) since this might be a general issue related to SMILES dialects.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-05-15T21:10:51.500" LastActivityDate="2021-05-18T14:16:17.667" Title="How to canonicalize SMILES written with aromatic bond symbols (:)?" Tags="|rdkit|smiles|openbabel|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4982" PostTypeId="2" ParentId="4980" CreationDate="2021-05-14T21:52:58.370" Score="11" Body="&lt;p&gt;Consider a graphene Hamiltonian, whose dispersion looks a lot like the one in your figure. Per &lt;a href=&quot;https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/3/67057/files/2018/09/graphene_tight-binding_model-1ny95f1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;these notes&lt;/a&gt;, its k-space Hamiltonian may be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H(k)=-t \sum_{\delta} [\cos(k\cdot\delta)\sigma_x-\sin(k\cdot\delta)\sigma_y],&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$k=(k_x,k_y)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; are nearest-neighbor vectors, &lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; are Pauli matrices and &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is a hopping parameter. Please see referenced notes for vectors and other details pertaining to the model.&lt;/p&gt;&#xA;&lt;h2&gt;General idea:&lt;/h2&gt;&#xA;&lt;p&gt;Per the time-independent Schrodinger equation, the energy dispersion you seek to plot comprises just the eigenvalues of the above Hamiltonian over some region of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space. I will assume that you are working with an expression for the Hamiltonian (like the one above), instead of &lt;em&gt;ab initio&lt;/em&gt; techniques. The given &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; Hamiltonian is a &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;-level Hamiltonian that yields &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; instantaneous eigenvectors/wavefunctions corresponding to &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; eigenvalues. In your figure, the sets of eigenvalues pertaining to each eigenvector are given in two different colors (red and blue).&lt;/p&gt;&#xA;&lt;p&gt;Therefore, you simply have to solve for the Hamiltonian's eigenvalues at each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point in &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space. You may do this 'analytically' (to find expressions for the eigenvalues using algebra, that you can then plug &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; points into), or 'numerically' (evaluating the Hamiltonian at each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; point first, to numerical get eigenvalues directly).&lt;/p&gt;&#xA;&lt;h2&gt;Analytic implementation:&lt;/h2&gt;&#xA;&lt;p&gt;The 'analytic' method is just using some function &lt;span class=&quot;math-container&quot;&gt;$H(k)$&lt;/span&gt; for the Hamiltonian to get an analytic expression for a different function &lt;span class=&quot;math-container&quot;&gt;$E(k)$&lt;/span&gt; of the energy. You can plug &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$E(k)$&lt;/span&gt; to plot your figure. I personally prefer using &lt;code&gt;Mathematica&lt;/code&gt; for this, because I like its in-build eigensystem-solving commands.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(* Define parameter space edges *)&#xA;BZx1=-1;BZx2=+1;BZy1=-1;BZy2=+1;&#xA;(* Define Hamiltonian *)&#xA;a = 2.46; t = 1; k = {kx, ky}; &#xA;d1 = (a/2) {1, Sqrt[3]}; d2 = (a/2) {1, -Sqrt[3]}; d3 = -a {1, &#xA;   0}; &#xA;sx = {{0, 1}, {1, 0}}; sy = {{0, -I}, {I, 0}}; (* Pauli matrices *)&#xA;hx = Cos[k.d1] + Cos[k.d2] + Cos[k.d3]; hy = &#xA; Sin[k.d1] + Sin[k.d2] + Sin[k.d3];&#xA;H[kx_, ky_] = -t (hx*sx - hy*sy);&#xA;(* Get analytic expressions for energies *)&#xA;eigenvals[kx_, ky_] = Eigenvalues[H[kx, ky]];&#xA;(* Plot *)&#xA;Show[Plot3D[eigenvals[kx, ky][[1]], {kx, BZx1, BZx2}, {ky, BZy1, BZy2}, &#xA;  PlotStyle -&amp;gt; Red], &#xA; Plot3D[eigenvals[kx, ky][[2]], {kx, BZx1, BZx2}, {ky, BZy1, BZy2}, &#xA;  PlotStyle -&amp;gt; Blue]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives you:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KTHaP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KTHaP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I can imagine that a &lt;a href=&quot;https://docs.sympy.org/dev/tutorial/matrices.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sympy (+ matplotlib)&lt;/a&gt; approach would be similar. Additionally, I would not recommend trying to solve complicated expressions this way (unless you have the computational power).&lt;/p&gt;&#xA;&lt;h2&gt;Numerical implementation:&lt;/h2&gt;&#xA;&lt;p&gt;On the other hand, the 'numerical' method requires first discretizing your &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space into a grid, and then plugging each grid point into &lt;span class=&quot;math-container&quot;&gt;$H(k)$&lt;/span&gt; to get a matrix with numbers as its entries (as opposed to algebraic expressions). You can easily solve for the eigenvalues, and plot all resulting eigenvalue points to get a figure like the one you seek. Please bear in mind that eigenvectors are generally complex-valued, and that when using the numerical approach, different programs assign different arbitrary, complex-valued phases to each entry. This is not an issue in our case, as we care only about eigenvalues (which are real if dealing with a Hermitian system). I personally prefer using &lt;code&gt;MATLAB&lt;/code&gt; or &lt;code&gt;Python&lt;/code&gt; for this approach, because they are well-suited for working with numerical datasets.&lt;/p&gt;&#xA;&lt;p&gt;The following code might look more complicated than it needs to be, but I like working with functions:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from numpy import linalg as LA&#xA;import matplotlib.pyplot as plt&#xA;&#xA;# First, define your Hamiltonian. &#xA;# The following function returns the Hamiltonian matrix for input (kx,ky).&#xA;def Hamiltonian_Graphene(kx,ky):&#xA;    a = 2.46 # Wikipedia&#xA;    t = 1&#xA;    k = np.array((kx,ky))&#xA;    d1 = (a/2)*np.array((1,np.sqrt(3)))&#xA;    d2 = (a/2)*np.array((1,-np.sqrt(3)))&#xA;    d3 = -a*np.array((1,0))&#xA;    sx = np.matrix([[0,1],[1,0]]);&#xA;    sy = np.matrix([[0,-1j],[1j,0]]);&#xA;    hx = np.cos(k@d1)+np.cos(k@d2)+np.cos(k@d3)&#xA;    hy = np.sin(k@d1)+np.sin(k@d2)+np.sin(k@d3)&#xA;    H = -t*(hx*sx - hy*sy)&#xA;    return H&#xA;&#xA;# Onto plotting the dispersion.&#xA;# The parameters m,n specify the resolution to discretize the parameter space into (e.g. break it into m=10 pieces in the kx direction).&#xA;# The parameters BZx1,BZx2,BZy1,BZy2 specify the edges of your parameter space. I used BZx1=-1,BZx2=+1,BZy1=-1,BZy2=+1 in the &#xA;def plot_dispersion(m,n,BZx1,BZx2,BZy1,BZy2):&#xA;    # Generate a mesh&#xA;    kx_range = np.linspace(BZx1, BZx2, num=m)&#xA;    ky_range = np.linspace(BZy1, BZy2, num=n)&#xA;    # Get the number of levels with a dummy call (an NxN square matrix has N levels)&#xA;    num_levels = len(Hamiltonian_Graphene(1,1))&#xA;    energies = np.zeros((m,n,num_levels)); # initialize&#xA;    # Now iterate over discretized mesh, to consider each coordinate.&#xA;    for i in range(m):&#xA;        for j in range(n):&#xA;            H = Hamiltonian_Graphene(kx_range[i],ky_range[j]); &#xA;            evals, evecs = LA.eig(H); # Numerically get eigenvalues and eigenvectors&#xA;            energies[j,i,:]=evals;&#xA;    X, Y = np.meshgrid(kx_range, ky_range) # Generate actual mesh for plotting.&#xA;    # Plot! There are several ways to style this.&#xA;    fig = plt.figure()&#xA;    ax = fig.gca(projection='3d')&#xA;    ax.axis([X.min(), X.max(), Y.min(), Y.max()])&#xA;    transparency = 0.3 #transparency&#xA;    for band in range(num_levels): &#xA;        ax.scatter3D(X, Y, energies[:,:,band], alpha=transparency, antialiased=False, label=&amp;quot;c&amp;quot;) &#xA;    plt.show()&#xA;    &#xA;# Run it!&#xA;BZx1=-1;BZx2=+1;BZy1=-1;BZy2=+1;&#xA;plot_dispersion(100,100,BZx1,BZx2,BZy1,BZy2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives you:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/N9zqS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/N9zqS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You might get an error &lt;code&gt;ComplexWarning: Casting complex values to real discards the imaginary part&lt;/code&gt;, but that is because of rounding errors in Python (and can be avoided if you use &lt;code&gt;np.eigh()&lt;/code&gt; instead of &lt;code&gt;np.eig&lt;/code&gt;, if applicable). You can try to troubleshoot ways to get rid of this, and to make resulting figures prettier. I did not include the contour plot shown at the bottom of your figure, as it basically uses the same procedure.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-07-01T19:09:11.670" LastActivityDate="2021-07-01T19:09:11.670" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4983" PostTypeId="1" CreationDate="2021-05-15T01:50:32.070" Score="8" ViewCount="138" Body="&lt;p&gt;Let's say that I have a simple domain wall system for the following &lt;a href=&quot;https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/3/67057/files/2018/09/graphene_tight-binding_model-1ny95f1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hamiltonian&lt;/a&gt; with added on-site potential &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;H(k,M)=-t \sum_{\delta} [\cos(k\cdot\delta)\sigma_x-\sin(k\cdot\delta)\sigma_y+M(x)\sigma_z],&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the on-site potential &lt;span class=&quot;math-container&quot;&gt;$M(x)=0$&lt;/span&gt;, the above is the Hamiltonian for graphene. Otherwise, &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt; gaps the gapless graphene system.&lt;/p&gt;&#xA;&lt;p&gt;In a domain-wall like setup comprising multiple unit cells, &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt; can be made to vary between, say &lt;span class=&quot;math-container&quot;&gt;$-0.5\leq M(x)\leq 0.5$&lt;/span&gt;. In this question, I will focus on the energy spectra around only one Dirac point, as shown in the figure at the end (y-axis is energy). So, I am deliberately avoiding considering the bulk / entire Brillouin zone.&#xA;In terms of Berry-phase related phenomena, we know that the sign of &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt; (i.e. &lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt;) directly affects the Berry phase (and topology).&lt;/p&gt;&#xA;&lt;p&gt;I broke my overall question down into three consecutive parts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Do the &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;lt;0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;gt;0$&lt;/span&gt; bands in this setup correspond to different 'phases'? I think of this solely due to the &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;lt;0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;gt;0$&lt;/span&gt; bands having different Berry phases being separated by a graphene phase. But I am not sure, as I am not comparing the Chern number everywhere.&lt;/li&gt;&#xA;&lt;li&gt;Does the gap closing for &lt;span class=&quot;math-container&quot;&gt;$M(x)=0$&lt;/span&gt; mean that there is an edge state connecting &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;lt;0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;gt;0$&lt;/span&gt; bands? I guess the confusion is distinguishing an edge state from a gapless point in the dispersion. Again, I am not too sure because I am not looking at spectral flow analytically (i.e. number of edge states = difference in Chern numbers on either side of domain).&lt;/li&gt;&#xA;&lt;li&gt;If this is an edge state, is it necessarily topologically protected? Besides the Chern number again, I am not sure why this would be topologically protected.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iFSO8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iFSO8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I apologize there are sub-questions here, but I thought this was better than asking three separate questions because they all are about my confusion on topologically protected edge states.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-11-23T21:27:54.903" LastActivityDate="2021-11-23T22:31:40.810" Title="Help with understanding topologically-protected edge states in domain wall systems" Tags="|condensed-matter|quantum-mechanics|topological-insulators|berry-phase|graphene|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4984" PostTypeId="1" CreationDate="2021-05-15T10:40:19.933" Score="7" ViewCount="302" Body="&lt;p&gt;I relaxed Na&lt;sub&gt;2&lt;/sub&gt;S&lt;sub&gt;2&lt;/sub&gt; molecule in QuantumEspresso and plotted the planar average of potential energy across z axis so as to find the Vacuum potential. This is the output I got : &lt;a href=&quot;https://i.stack.imgur.com/to1Uv.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/to1Uv.jpg&quot; alt=&quot;Planar average of potential  of Na2S2&quot; /&gt;&lt;/a&gt;&#xA;As you can see the vacuum potential is not constant making it impossible to calculate it. While following the same procedure for Na&lt;sub&gt;2&lt;/sub&gt;S I got the following:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/x9REO.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x9REO.jpg&quot; alt=&quot;Planar average of potential  of Na2S&quot; /&gt;&lt;/a&gt; as you can see the vacuum potential is a constant value. What could be a reason for what happened in the case of Na&lt;sub&gt;2&lt;/sub&gt;S&lt;sub&gt;2&lt;/sub&gt;? How can I solve it ?&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;&lt;p&gt;The input file for the geometry optimization of Na&lt;sub&gt;2&lt;/sub&gt;S&lt;sub&gt;2&lt;/sub&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation='relax'&#xA;title='graphene'&#xA;prefix='graphene'&#xA;restart_mode='from_scratch'&#xA;outdir='../tmp'&#xA;wf_collect=.true.&#xA;pseudo_dir='~/work/pot/'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;ibrav = 4,&#xA;a = 14.58 ,&#xA;c= 20,&#xA;nat = 4&#xA;ntyp = 2&#xA;vdw_corr = 'dft-d3'&#xA;ecutwfc = 50.0 ,&#xA;ecutrho = 250.0 ,&#xA;occupations='smearing'&#xA;smearing='gaussian'&#xA;degauss=0.001&#xA;nbnd=30&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;electron_maxstep = 200,&#xA;conv_thr = 1.0d-10 ,&#xA;/&#xA;&amp;amp;IONS&#xA;ion_dynamics = 'bfgs'&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Na 22.989 Na.pbe-spnl-kjpaw_psl.1.0.0.UPF&#xA;S 32.065 S.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (angstrom)&#xA;Na           -2.1578688813       -0.0711007913        0.0959862818&#xA;S             0.0279507567        0.7976264059        1.1138133631&#xA;S            -1.4993815540        2.3462755509        0.6717950344&#xA;Na            0.8998813708        2.9052562024       -0.0587466613&#xA;&#xA;&#xA; K_POINTS automatic&#xA;2 2 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2021-06-27T02:25:19.000" Title="Non-constant Vacuum potential" Tags="|quantum-espresso|vacuum-potential|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4985" PostTypeId="2" ParentId="4980" CreationDate="2021-05-15T19:09:52.350" Score="7" Body="&lt;p&gt;For a general case, create you input inside a loop:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Define the starting k point.&lt;/li&gt;&#xA;&lt;li&gt;Generate the k-points path.&lt;/li&gt;&#xA;&lt;li&gt;Export your input.&lt;/li&gt;&#xA;&lt;li&gt;Call and execute your DFT (using the input file generated in previous step).&lt;/li&gt;&#xA;&lt;li&gt;Read the output in the corresponding band structure file. Add the band data (1D array) to a column in a matrix.&lt;/li&gt;&#xA;&lt;li&gt;Change the starting k-point.&lt;/li&gt;&#xA;&lt;li&gt;Back to step 1.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here, the mains steps are completely dependent on the DFT software you are using.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-05-15T19:09:52.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4986" PostTypeId="2" ParentId="4980" CreationDate="2021-05-15T19:55:58.500" Score="10" Body="&lt;h1&gt;VASPKIT&lt;/h1&gt;&#xA;&lt;p&gt;VASPKIT offers a tool to plot 3D band structure using VASP. The method select K-path on a surface of the Irreducilbe Brillouin zone and calculate the K-dependent band energies on those K-points. An example 3D plot of graphene bandstructure is shown below&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Ki04x.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ki04x.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For more details refer &lt;a href=&quot;https://vaspkit.com/tutorials.html&quot; rel=&quot;noreferrer&quot;&gt;this tutorial&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A few more plots&#xA;&lt;a href=&quot;https://i.stack.imgur.com/d5eWH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/d5eWH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="88" LastEditDate="2021-05-15T20:06:37.260" LastActivityDate="2021-05-15T20:06:37.260" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4987" PostTypeId="1" AcceptedAnswerId="4997" CreationDate="2021-05-16T08:22:16.660" Score="7" ViewCount="206" Body="&lt;p&gt;Same question, rephrased:&lt;/p&gt;&#xA;&lt;p&gt;What is the procedure to take snapshots at fixed intervals while running an AIMD or DFT Simulation in VASP?&lt;/p&gt;&#xA;&lt;p&gt;OR&lt;/p&gt;&#xA;&lt;p&gt;Which parameter in the INCAR file do I modify to achieve periodic snapshots(in JPG/PNG) of atomic positions?&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2021-05-17T05:38:47.847" Title="How to take periodic snapshots while running a simulation in VASP?" Tags="|density-functional-theory|vasp|conceptual-dft|aimd|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4988" PostTypeId="2" ParentId="4971" CreationDate="2021-05-16T08:27:23.190" Score="8" Body="&lt;p&gt;You can find a list of what you are looking for, in this &lt;strong&gt;&lt;a href=&quot;https://depth-first.com/articles/2011/10/12/sixty-four-free-chemistry-databases/&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt; attached.&lt;/strong&gt;&#xA;Most of them have &lt;strong&gt;experimental properties of molecular materials&lt;/strong&gt;. I have shared a few examples below:&lt;/p&gt;&#xA;&lt;p&gt;Edited:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The &lt;a href=&quot;http://sw16.im.med.umich.edu/databases/pdbbind/index.jsp&quot; rel=&quot;noreferrer&quot;&gt;PDBbind&lt;/a&gt; database is designed to provide a collection of &lt;strong&gt;experimentally measured&lt;/strong&gt; binding affinity data (Kd, Ki, and IC50) exclusively for the protein-ligand complexes available in the Protein Data Bank (PDB). All of the binding affinity data compiled in thisdatabase are cited from original references&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://cccbdb.nist.gov/&quot; rel=&quot;noreferrer&quot;&gt;Computational Chemistry Comparison and Benchmark DataBase&lt;/a&gt; actually has &lt;strong&gt;Experimental and computational thermochemical data&lt;/strong&gt; for a selected set of 1420 gas-phase atoms and molecules. Tools for comparing experimental and computational ideal-gas thermochemical properties&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://pc1664.pharmazie.uni-marburg.de/affinity/index.php&quot; rel=&quot;noreferrer&quot;&gt;AffinDB&lt;/a&gt; provides affinity data for protein-ligand complexes of the PDB. Its purpose is to provide &lt;strong&gt;direct and free access to the experimental affinity&lt;/strong&gt; of a given complex structure. As of Thursday, October 13th, 2011, AffinDB contains 748 affinity values covering 474 different PDB complexes.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2021-05-19T05:57:53.917" LastActivityDate="2021-05-19T05:57:53.917" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="4989" PostTypeId="1" AcceptedAnswerId="4990" CreationDate="2021-05-16T11:16:58.233" Score="8" ViewCount="214" Body="&lt;p&gt;I was trying to get the charges and the topology file for this molecule (&lt;span class=&quot;math-container&quot;&gt;$\ce{C28H58O7S8}$&lt;/span&gt;).&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Ozfk3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ozfk3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I get the following error despite using the right number of hydrogens.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error:&#xA;Semi-empirical geometry optimisation failed. The most likely cause is that either: (1) the geometry was inappropriate; (2) the number of hydrogen atoms or the net charge was inappropriate. Details: *** FAILURE TO LOCATE STATIONARY POINT, SCF HAS NOT CONVERGED (seems to only fail on step 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What does it mean by inappropriate geometry? I have tried to address the steric clashes by flattening the whole polymer from a curled conformation. But both of them result in the same error. However the same structure would process easily without the benzene rings and &lt;span class=&quot;math-container&quot;&gt;$\ce{-CH3}$&lt;/span&gt; group in their places. What am I missing?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xxklo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xxklo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/0f97a.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0f97a.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2021-07-03T16:49:35.517" LastActivityDate="2021-07-03T16:49:35.517" Title="How to address the errors on Automated Topology Builder?" Tags="|molecular-dynamics|gromacs|automatic-topology-builder|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4990" PostTypeId="2" ParentId="4989" CreationDate="2021-05-16T12:35:00.580" Score="9" Body="&lt;p&gt;Did you want to draw Si instead of S? Sulfur atoms bonded to two oxygens and two carbons, like the ones you have drawn here, are at least very rare, if not non-existent. It makes much better sense if what you want is to calculate the molecule with silicons instead of sulfurs, since that will be a silicone oligomer, which looks much more natural than the molecule you are drawing here. The highly non-conventional electronic structure of the four-coordinate sulfur atoms is probably the cause of the SCF convergence failure.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-05-16T12:35:00.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4991" PostTypeId="1" CreationDate="2021-05-16T12:53:54.733" Score="12" ViewCount="697" Body="&lt;p&gt;The question is similar to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4267/49&quot;&gt;How to calculate/plot molecular orbitals with XTB?&lt;/a&gt; Hence we can produce molden files from xTB calculations, which include the molecular orbitals. How do I proceed to get localised orbitals and how would I then plot these? I am considering this as more of a visual aid that could guide further investigations or a certain narrative, than actual fact producing science. Since xTB itself is open source it would be great if there was a similar way.&lt;/p&gt;&#xA;" OwnerUserId="49" LastActivityDate="2021-05-18T18:51:05.860" Title="How to calculate and plot localised orbitals with xTB?" Tags="|orbitals|xtb|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4992" PostTypeId="1" CreationDate="2021-05-16T13:29:10.847" Score="12" ViewCount="402" Body="&lt;p&gt;Is there any database listing the experimentally-determined properties of semiconductor materials - things like Band Gap and Electron Mobility. These are easily found for common materials like Germanium or Gallium Arsenide. But what databases have systematic lists properties for materials which are currently being researched (preferably by type, such as &lt;span class=&quot;math-container&quot;&gt;$\ce{ABX2}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;These might prove very useful for computational studies (particularly Machine Learning approaches), as well as excellent references for characterization of synthesized materials.&lt;/p&gt;&#xA;" OwnerUserId="1188" LastEditorUserId="5" LastEditDate="2021-05-16T15:24:43.870" LastActivityDate="2021-06-07T15:50:11.560" Title="What are the databases of semiconductor properties?" Tags="|reference-request|one-topic-per-answer|databases|machine-learning|experimental|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="4993" PostTypeId="2" ParentId="4991" CreationDate="2021-05-16T14:50:13.710" Score="10" Body="&lt;p&gt;You can do it with Multiwfn (&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;First, &lt;a href=&quot;https://github.com/grimme-lab/xtb&quot; rel=&quot;nofollow noreferrer&quot;&gt;xTB&lt;/a&gt; has to be run with the &lt;code&gt;--molden&lt;/code&gt; directive, to output the converged molecular orbitals as a molden file. Normally xTB will produce this file with the name &lt;code&gt;molden.input&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Multiwfn is able to open this file. After opening, select option &lt;code&gt;19&lt;/code&gt; for &lt;code&gt;Orbital Localization Analysis&lt;/code&gt;. You can change various settings related to the localization procedure here, including criterion of convergence, threshold for determining 1 and 2-centre LMOs, maximum number of localization cycles etc. The option &lt;code&gt;-6&lt;/code&gt; selects the scheme for localization—default is &lt;code&gt;Pipek-Mezey with Mulliken population&lt;/code&gt;. There are also &lt;code&gt;Pipek-Mezey with Lowdin population&lt;/code&gt; and &lt;code&gt;Foster-Boys&lt;/code&gt; localization schemes available.&lt;/p&gt;&#xA;&lt;p&gt;After changing settings (or leaving them with the default options), select option &lt;code&gt;1&lt;/code&gt; to localize the occupied orbitals. (Option &lt;code&gt;2&lt;/code&gt; localizes occupied and unoccupied orbitals separately). Multiwfn will now generate a file containing the localized orbitals, named &lt;code&gt;new.fch&lt;/code&gt;. (Which can be opened and visualized with multiwfn or other programs)&lt;/p&gt;&#xA;&lt;p&gt;To test this, I localized the orbitals of methane after running a calculation with GFN2-xTB. It seems to have worked:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/i0H7C.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/i0H7C.png&quot; alt=&quot;one of the localized orbitals of CH4&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sub&gt;(This is one of the localized orbitals)&lt;/sub&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Note that this would only calculate the wavefunctions of the LMO's but not their energies. (If you see energies in visualisation software, they are probably wrong.) To get LMO energies, the Fock matrix also needs to be supplied to Multiwfn, and I am not sure if there is any way to do that with xTB.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-18T18:51:05.860" LastActivityDate="2021-05-18T18:51:05.860" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="4994" PostTypeId="1" CreationDate="2021-05-16T16:21:27.590" Score="13" ViewCount="2026" Body="&lt;p&gt;I am trying to extract XYZ coordinates from a CIF file for a molecule to use in DFT calculations. I have Mercury and Vesta installed on my computer. Whenever I open the files, I get the following structure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uVf1H.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uVf1H.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There seems to be molecular fragments and free hydrogen atoms in the molecular presentation (see the atoms marked in yellow). I understand that XRD is quite bad at locating hydrogens, and that sometimes you'll end up getting several positions of where the hydrogen is located.&lt;/p&gt;&#xA;&lt;p&gt;How should I proceed in order to clean the file? I only want to have XYZ coordinates for each atom in the molecule without the fragments, is this possible to achieve in VESTA or Mercury?&lt;/p&gt;&#xA;" OwnerUserId="3586" LastEditorUserId="7" LastEditDate="2022-03-23T00:32:49.513" LastActivityDate="2023-11-13T12:11:13.600" Title="Extracting molecular structure from CIF file using VESTA or Mercury" Tags="|crystallography|vesta|geometry|cif|mercury|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="4995" PostTypeId="5" CreationDate="2021-05-16T17:17:35.997" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Mercury_(crystallography)&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Mercury_(crystallography)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-16T17:17:35.997" LastActivityDate="2021-05-16T17:17:35.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4996" PostTypeId="4" CreationDate="2021-05-16T17:17:35.997" Score="0" Body="For the Mercury software, not the element or the planet. " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-16T17:17:35.997" LastActivityDate="2021-05-16T17:17:35.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4997" PostTypeId="2" ParentId="4987" CreationDate="2021-05-16T19:42:42.443" Score="9" Body="&lt;p&gt;There is no way to do this directly in VASP, but you can achieve this goal using the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; (ASE). With your &lt;code&gt;OUTCAR&lt;/code&gt; available, do the following:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase.io import read, write&#xA;images = read('OUTCAR',index=':') # Read in every iteration&#xA;interval = 5 # Save .png every N steps&#xA;for i, image in enumerate(images):&#xA;     if i+1 % interval == 0:&#xA;          write('image_'+str(i)+'.png',image) # Write out imamge&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-05-16T19:49:33.633" LastActivityDate="2021-05-16T19:49:33.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="4998" PostTypeId="2" ParentId="4679" CreationDate="2021-05-16T19:58:46.950" Score="4" Body="&lt;p&gt;In the attached paper they have used the broken symmetry method to calculate the exchange.&lt;/p&gt;&#xA;&lt;p&gt;Assuming that you're dealing with a 1D chain of spins. you can do this using quantum ESPRESSO via the following steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Create a 2x1x1 &lt;a href=&quot;https://www.youtube.com/watch?v=qnbKn4QZdl8&quot; rel=&quot;nofollow noreferrer&quot;&gt;super cell from your CIF file using VESTA&lt;/a&gt; (assuming that your 1d chain is along the first basis vector)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For the &lt;a href=&quot;https://www.youtube.com/watch?v=7Lcd0QD_Z7s&quot; rel=&quot;nofollow noreferrer&quot;&gt;SCF calculation using QE,&lt;/a&gt; you need to consider two cases a ferromagnetic state and an antiferromagnetic state. Here the magnetic moment on the atom (one in each unit cell) should be constrained as follows in the &amp;amp;SYSTEM name card:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For the AFM case:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  starting_magnetization(1) = 1.0&#xA;  starting_magnetization(2) = -1.0&#xA;  constrained_magnetization = 'atomic'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the FM case:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  starting_magnetization(1) = 1.0&#xA;  starting_magnetization(2) = 1.0&#xA;  constrained_magnetization = 'atomic'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;The difference in energy should give you the J value:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ J = E_{FM}-E_{AFM}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I hope this is correct!&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2021-05-16T21:57:28.200" LastActivityDate="2021-05-16T21:57:28.200" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="4999" PostTypeId="2" ParentId="4376" CreationDate="2021-05-16T20:12:56.377" Score="3" Body="&lt;p&gt;The estimate of the net electronic spin polarization is calculated using the up and down DOS values at the Fermi level using the following expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathrm{Spin \ polarization}= \frac{ABS(DOS_{UP}-DOS_{DOWN})}{(DOS_{UP}+DOS_{DOWN})}.\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This has been taken from &lt;a href=&quot;https://www.researchgate.net/post/How_to_find_the_percentage_of_spin-polarization_quantitatively_in_Quantum_Espresso&quot; rel=&quot;nofollow noreferrer&quot;&gt;this post&lt;/a&gt; on ResearchGate.&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="5" LastEditDate="2021-05-17T17:47:27.307" LastActivityDate="2021-05-17T17:47:27.307" CommentCount="7" CommunityOwnedDate="2021-05-16T20:12:56.377" ContentLicense="CC BY-SA 4.0" />
  <row Id="5000" PostTypeId="2" ParentId="4987" CreationDate="2021-05-17T05:38:47.847" Score="7" Body="&lt;p&gt;In can be done easily using python or bash script. You have to keep looking for changes in &lt;code&gt;OSZICAR&lt;/code&gt;. Whenever OSZICAR prints 'F' i.e. end of electronic self consistent loop, copy your &lt;code&gt;CONTCAR&lt;/code&gt; to other file. There is simple tool in linux system &lt;code&gt;inotify-hookable&lt;/code&gt; which will watch over change in &lt;code&gt;CONTCAR&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;    inotify-hookable -f CONTCAR -c &amp;quot;cp CONTCAR CONTCAR.new&amp;quot;&#xA;    echo &amp;quot;== $(date) : executed, continuing to monitor...&amp;quot;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;use &lt;code&gt;sudo apt-get install inotify-hookable&lt;/code&gt; to install in ubuntu or use source code.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-05-17T05:38:47.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5001" PostTypeId="2" ParentId="4994" CreationDate="2021-05-17T10:10:19.230" Score="12" Body="&lt;h1&gt;VESTA&lt;/h1&gt;&#xA;&lt;p&gt;I'm an avid user of VESTA and haven't quite used Mercury. So I'll the steps to do it in VESTA (it's quite easy though)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 1: Open your file in VESTA&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XiqRk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XiqRk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 2: Choose the selection tool in the left panel. (highlighted in&#xA;blue)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pv47h.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pv47h.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 3: Click and drag to select the atoms you want to manipulate;&#xA;Here the three top atoms&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RPhnS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RPhnS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;After selection they are highlighted in yellow&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TtFzE.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TtFzE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 4: Use the [Del] key to delete the atoms. And go to [file --&amp;gt; export]&lt;/strong&gt;&#xA;&lt;strong&gt;to export your structure.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pPJGi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pPJGi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 5: Choose the appropriate extension (in you case the .xyz&lt;/strong&gt;&#xA;&lt;strong&gt;extension) to save it as an XYZ file.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uRVPo.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uRVPo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Hope it helps :)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2021-05-17T10:10:19.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5002" PostTypeId="2" ParentId="4992" CreationDate="2021-05-17T12:19:47.497" Score="6" Body="&lt;h2&gt;Ioffe: New Semiconductor Materials. Biology systems. Characteristics and Properties&lt;/h2&gt;&#xA;&lt;p&gt;From the site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This section is intended to systematize parameters of semiconductor&#xA;compounds and heterostructures based on them. Such a WWW-archive has a&#xA;number of advantages: in particular, it enables physicists, both&#xA;theoreticians and experimentalists, to rapidly retrieve the&#xA;semiconducting material parameters they are interested in. In&#xA;addition, physical parameters -optical, electrical, mechanical, etc.-&#xA;will be presented in the framework of the electronic archive for both&#xA;the known and new semiconducting compounds. As the starting point in&#xA;creating the database served the voluminous reference book &amp;quot;Handbook&#xA;Series on Semiconductor Parameters&amp;quot; vol. 1,2 edited by M. Levinstein,&#xA;S. Rumyantsev and M. Shur, World Scientific, London, 1996, 1999. We&#xA;express sincere gratitude to M.E. Levinstein for help and attention to&#xA;this work. A great number of reference books and original papers cited&#xA;at the end of this section have been used in compiling the information&#xA;database.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Link: &lt;a href=&quot;http://matprop.ru/&quot; rel=&quot;noreferrer&quot;&gt;http://matprop.ru/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-05-17T12:19:47.497" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5003" PostTypeId="2" ParentId="4957" CreationDate="2021-05-17T17:14:47.967" Score="6" Body="&lt;p&gt;Eventually, I figured out what was wrong happening with my DFT calculation. As I understand &lt;strong&gt;now&lt;/strong&gt;, each processor saves and maintains (write recursively as the calculation progresses) its own file containing the wavefunctions (Kohn-sham orbitals), charge density, etc. This can be done in two different ways during the parallelization:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;collected&lt;/strong&gt;: all files from different processors are collected by the code to a single processor that writes them to disk, in a single file, using a format that doesn't depend upon the number of processors or their distribution. This is the default since v.6.2 for final data.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Distributed&lt;/strong&gt;: each processor writes its own file to disk in its internal format to a different file. The 'distributed' format is fast and simple, but the data so produced is readable only by a job running on the same number of processors, with the same type of parallelization, as the job who wrote the data, and if all files are on a file system that is visible to all processors (i.e., you cannot use local scratch directories: there is presently no way to ensure that the distribution of processes across processors will follow the same pattern for different jobs).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;What wrong I was doing?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When I ran the 'SCF' calculation with &lt;code&gt;npools=20&lt;/code&gt; and k-point mesh of&#xA;12* 12 * 12. This is a wrong estimation for choosing the n-pools&#xA;number. As it is mentioned in &lt;a href=&quot;https://www.quantum-espresso.org/Doc/pw_user_guide.pdf&quot; rel=&quot;noreferrer&quot;&gt;QE user guide&lt;/a&gt;(page 17) that the npools should divide the number of k-points by an integer. The file saved in this calculation was from the first method.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Then, I started running the 'NSCF' calculation on a denser k-point grid of 20 * 20 * 20 with the same 20 &lt;code&gt;npools&lt;/code&gt; again. In this case, each processor started writing its own files (method 2). It created &lt;code&gt;prefix.wfc1, prefix.wfc2, prefix.wfc3 ... prefix.wfc20&lt;/code&gt;, which took a lot of disk space.&#xA;Of course, the job will send an error when there is no disk space available to proceed the calculation with a termination.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Then, I tried to reduce the number of &lt;code&gt;npools&lt;/code&gt; from 20 to 2, which was the reason for the error I have got in my files attached to the question. If one is using the final result of last calculation to perform the second calculation then the number of pools on which next calculation is running should be the same otherwise one will get an error like pointed out by @Anoop A Nair in the comment.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;How did I solve this issue?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I ran again both 'SCF' and 'NSCF' calculation with &lt;code&gt;npools = 2&lt;/code&gt;. This time both calculations were done within 20 hours time. Previously, only 'SCF' calculation was taking around 1 day to do the job. This time it also took less space on the disk.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; One should do some experiments while choosing the optimal number of processors during the parallelization to make it resource-friendly. Also one can set &lt;code&gt;disk_io = none&lt;/code&gt;,&lt;code&gt;low&lt;/code&gt; or &lt;code&gt;medium&lt;/code&gt; to reduce the size of files being saved after the calculation.&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2021-05-17T17:14:47.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5004" PostTypeId="2" ParentId="4956" CreationDate="2021-05-18T00:01:55.303" Score="3" Body="&lt;p&gt;You fixed the occupation within symmetries by the command &amp;quot;&lt;code&gt;occ,6,3,3,2&lt;/code&gt;&amp;quot; and asked the program to make CASSCF for the lowest 5 singlet states of symmetry 1 (&lt;span class=&quot;math-container&quot;&gt;$A_1$&lt;/span&gt;). And indeed, as you see, the first 6, 3, 3, and 2 orbitals in symmetries 1, 2, 3, 4, respectively, have nonzero occupation numbers, which sum up to &lt;code&gt;6+8=14&lt;/code&gt;, the number of electrons of &lt;span class=&quot;math-container&quot;&gt;$\ce{CO}$&lt;/span&gt;. These orbitals are ordered by energy, but &lt;em&gt;&lt;strong&gt;within&lt;/strong&gt;&lt;/em&gt; symmetries, so the criterion is the orbital energy.&lt;/p&gt;&#xA;&lt;p&gt;There are many options in the CASSCF Molpro program and it is difficult to advise without knowing what you do not like in your results. You can, e.g., run a HF calculation, use these orbitals as starting orbitals and freeze some orbitals in the subsequent CASSCF calculation. Since you have a linear molecule, you probably would like to select orbitals with &amp;quot;extra&amp;quot; symmetries (i.e. differentiate between orbitals, which are e.g. in the same &lt;span class=&quot;math-container&quot;&gt;$A_1$&lt;/span&gt; representation in &lt;span class=&quot;math-container&quot;&gt;$C_{2v}$&lt;/span&gt;, but in reality they are in different representation in &lt;span class=&quot;math-container&quot;&gt;$C_{\infty v}$&lt;/span&gt;, look for the &lt;code&gt;EXTRA&lt;/code&gt; keyword in the manual). You can also restrict CSFs (so you have RAS, not CAS), by the &lt;code&gt;RESTRICT&lt;/code&gt; keyword, e.g. to single and double excitations. Another option is to play with the &lt;code&gt;MERGE&lt;/code&gt; command and to prepare initial orbitals from atomic orbitals (there is an example for a &lt;span class=&quot;math-container&quot;&gt;$\ce{NO}$&lt;/span&gt; molecule in the Molpro manual, i.e. something very similar to your molecule).&lt;/p&gt;&#xA;" OwnerUserId="479" LastEditorUserId="5" LastEditDate="2021-05-18T00:15:29.630" LastActivityDate="2021-05-18T00:15:29.630" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5005" PostTypeId="1" AcceptedAnswerId="5016" CreationDate="2021-05-18T00:54:37.687" Score="13" ViewCount="351" Body="&lt;ul&gt;&#xA;&lt;li&gt;The central equation that KS-DFT will solve is:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\left[ -\dfrac{1}{2}\nabla^2+V_{ext}+V_{hartree}+V_{xc} \right]\psi_i(\vec{r})=E_i\psi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; is approximated with LDA or GGA.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The central equation that GW will solve is:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}\left[ -\dfrac{1}{2}\nabla^2+V_{ext}+V_{hartree}+\Sigma \right]\psi_i(\vec{r})=E_i\psi_i(\vec{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the self-energy operator &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; is calculated with GW approximation.&lt;/p&gt;&#xA;&lt;p&gt;One can see the GW method is the same as KFT except for replacing &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt;. KS-DFT usually underestimates the bandgap of semiconducting materials while GW can give a satisfactory description for that. So, what's the difference between &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-05-19T21:31:30.153" Title="KS-DFT versus G0W0" Tags="|density-functional-theory|gw-bse|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5006" PostTypeId="2" ParentId="4981" CreationDate="2021-05-18T07:17:43.203" Score="7" Body="&lt;p&gt;I think it might be good to have a look at SELFIES by Alan Aspuru-Guzik and co-workers: &lt;a href=&quot;https://github.com/aspuru-guzik-group/selfies&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/aspuru-guzik-group/selfies&lt;/a&gt;&#xA;From what I remember from his talk in Girona last December, this should do better than SMILES for many systems, which you can also infer from the title of the corresponding paper: &amp;quot;Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2021-05-18T07:17:43.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5008" PostTypeId="1" CreationDate="2021-05-18T12:47:05.240" Score="13" ViewCount="947" Body="&lt;p&gt;I am a beginner in DFT. Can someone suggest a good DFT software with a GUI for simulating dipole moments and optical absorption spectra in an organic crystal? I have tried the &lt;a href=&quot;https://burai.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;Burai GUI&lt;/a&gt; of Quantum ESPRESSO, but it doesn't seem to have this functionality. I have heard about the &lt;a href=&quot;https://www.scm.com/&quot; rel=&quot;noreferrer&quot;&gt;Amsterdam modelling suite&lt;/a&gt;. Do any of you have experience with that software, or others?&lt;/p&gt;&#xA;" OwnerUserId="3602" LastEditorUserId="5" LastEditDate="2021-05-19T03:13:34.423" LastActivityDate="2021-05-19T03:13:34.423" Title="GUI for DFT calculations" Tags="|software|software-recommendations|spectroscopy|dipole|graphical-user-interface|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5009" PostTypeId="2" ParentId="4981" CreationDate="2021-05-18T14:16:17.667" Score="8" Body="&lt;p&gt;&lt;strong&gt;tldr; That SMILES is invalid&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This was &lt;a href=&quot;https://github.com/openbabel/openbabel/issues/2368#issuecomment-843053926&quot; rel=&quot;noreferrer&quot;&gt;answered on GitHub&lt;/a&gt; by Noel O'Boyle, but I wanted to provide more context.&lt;/p&gt;&#xA;&lt;p&gt;First off, versions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I had to go back and check, but Open Babel 2.3.2 was released in &lt;a href=&quot;https://github.com/openbabel/openbabel/releases/tag/openbabel-2-3-2&quot; rel=&quot;noreferrer&quot;&gt;October 2012&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/ReleaseNotes/ob300.html&quot; rel=&quot;noreferrer&quot;&gt;Version 3.0 and later&lt;/a&gt; implement the Daylight SMILES aromaticity model and have a thoroughly rewritten SMILES code (by Noel).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;So why do the different versions give different results? Because 2.3.2 has a very forgiving aromaticity model and it's wrong.&lt;/p&gt;&#xA;&lt;p&gt;In particular, as noted by Noel, SMILES defines aromaticity through atoms:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Atom aromaticity in SMILES is determined by the case of the characters, not&#xA;by the nature of the attached bonds.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Since the characters are in caps, SMILES indicates they are non-aromatic atoms.&lt;/p&gt;&#xA;&lt;p&gt;But let's not limit ourselves to Open Babel and RDKit. I tried that SMILES in ChemDraw:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JGzKUm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JGzKUm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I also tried your SMILES with the &lt;a href=&quot;https://cactus.nci.nih.gov/chemical/structure&quot; rel=&quot;noreferrer&quot;&gt;NIH resolver&lt;/a&gt;, which runs CACTVS &lt;a href=&quot;https://cactus.nci.nih.gov/chemical/structure/NC%3A1%3AN%3AN%3AC%3A%5BN%5D1N/gif&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. It returns a 404 error, in essence the SMILES is invalid.&lt;/p&gt;&#xA;&lt;p&gt;I don't know your project, but if you want to use SMILES, you should use a full toolkit like RDKit, Open Babel, or Open Eye -- they have years of testing.&lt;/p&gt;&#xA;&lt;p&gt;And depending on your needs, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5006/30&quot;&gt;SELFIES&lt;/a&gt; might work. I don't remember if it includes all features in SMILES yet, but it's designed for robust ML and has proven utility in a number of recent papers.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-05-18T14:16:17.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5010" PostTypeId="2" ParentId="5008" CreationDate="2021-05-18T15:54:59.290" Score="3" Body="&lt;p&gt;Yesterday I was browsing the &lt;a href=&quot;https://biology.gradstudies.yorku.ca/faculty/l-donaldson/&quot; rel=&quot;nofollow noreferrer&quot;&gt;webpage of the biologist Logan Donaldson&lt;/a&gt; and agree 100% with this quote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;As structural studies also have a computational component, &lt;strong&gt;a willingness to use computers (UNIX-based systems) is a must&lt;/strong&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h2&gt;Trust me: it is better to learn the command line.&lt;/h2&gt;&#xA;&lt;p&gt;I'm speaking from experience since I have had many students working with me who stubbornly tried to find GUI alternatives to all sorts of things despite me strongly recommending to use the command line over and over again. 100% of those students did not last long before eventually giving up in their quest to stay away from the command line for as long as possible: despite spending 10x as much energy on trying to get a GUI to work and on troubleshooting all the problems they encountered with GUIs, compared to the very small amount of energy they &lt;em&gt;would&lt;/em&gt; have had to spend just to learn the command line, &lt;strong&gt;they ended up having to learn the command line anyway&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I began using UNIX when I was 9 years old. It's time for you to learn it too.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-18T15:54:59.290" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="5011" PostTypeId="1" AcceptedAnswerId="6227" CreationDate="2021-05-19T06:06:06.340" Score="9" ViewCount="175" Body="&lt;p&gt;The database I am looking for may be &lt;em&gt;&lt;strong&gt;experimental, computational or user-generated data&lt;/strong&gt;&lt;/em&gt;. If I end up using the data, I will be providing the necessary citations and credits. Thank You.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2021-06-23T16:55:55.517" Title="Is there a database where one can find the Electron Density data of materials?" Tags="|density-functional-theory|vasp|databases|machine-learning|materials-informatics|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="5012" PostTypeId="1" CreationDate="2021-05-19T09:11:37.983" Score="8" ViewCount="151" Body="&lt;p&gt;I know how to create the nanowire using &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Studio&lt;/a&gt;.&#xA;The difference between the nannowire and the nanorod is the aspect ratio.&lt;/p&gt;&#xA;&lt;p&gt;But I am not sure where should I fix the width and length of the nanorod.&#xA;My system is mixer of &lt;span class=&quot;math-container&quot;&gt;$\ce{WO3}$&lt;/span&gt; (space group is &lt;span class=&quot;math-container&quot;&gt;$221$&lt;/span&gt;; Pm-3m) and WC (Space group is &lt;span class=&quot;math-container&quot;&gt;$187$&lt;/span&gt;; P-6m2).&#xA;We can see it as &lt;span class=&quot;math-container&quot;&gt;$\ce{WO_{(3-x)}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{WC_x}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Any help will be very much helpful.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="7" LastEditDate="2021-11-01T16:56:24.333" LastActivityDate="2021-11-01T16:56:24.333" Title="How to design nanorod" Tags="|materials-design|nanostructures|nanoparticles|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="5013" PostTypeId="1" AcceptedAnswerId="5017" CreationDate="2021-05-19T12:56:30.983" Score="7" ViewCount="174" Body="&lt;p&gt;When calculating complete basis set extrapolations for quantities, such as adsorption energies or binding energies, which depend on the difference between three quantities (i.e. &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{prop} = E_\textrm{AB} - E_\textrm{A} - E_\textrm{B}$&lt;/span&gt;), should the extrapolation be performed on &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{prop}$&lt;/span&gt; or the individual terms (&lt;span class=&quot;math-container&quot;&gt;$E_\textrm{AB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_\textrm{B}$&lt;/span&gt;)?&lt;/p&gt;&#xA;&lt;p&gt;Just for more information, the specific CBS extrapolation I am looking at are the default two-point extrapolation formulae, used in ORCA, for basis sets of cardinal numbers &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Y$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation*}&#xA;E^\textrm{CBS}_\textrm{HF} = E^X_\textrm{HF} - \dfrac{E^Y_\textrm{HF} - E^X_\textrm{HF}}{\exp(-\alpha \sqrt{Y}) -\exp(-\alpha \sqrt{X})}\exp(-\alpha \sqrt{X}),&#xA;\end{equation*}&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation*}&#xA;E^\textrm{CBS}_\textrm{corr} = \dfrac{X^\beta E^X_\textrm{corr} - Y^\beta E^Y_\textrm{corr}}{X^\beta - Y^\beta},&#xA;\end{equation*}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; have been parameterised for various basis sets in this &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct100396y&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1008" LastEditorUserId="1008" LastEditDate="2021-05-20T07:35:50.410" LastActivityDate="2021-05-20T08:15:32.343" Title="What quantity to perform CBS extrapolation on for adsorption/binding energies?" Tags="|ab-initio-calculations|quantum-chemistry|molecular-modeling|basis-sets|spectroscopy|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5014" PostTypeId="2" ParentId="5013" CreationDate="2021-05-19T13:50:01.307" Score="5" Body="&lt;p&gt;A lot of basis sets such as the Dunning family of basis sets (e.g. cc-pVXZ) are designed with a specific goal in mind, which is not necessarily to give the lowest energy for a certain number of orbitals, but to achieve smooth extrapolations to the CBS limit for some properties.&lt;/p&gt;&#xA;&lt;p&gt;It would be &lt;em&gt;&lt;strong&gt;very hard&lt;/strong&gt;&lt;/em&gt; to optimize a basis set so that &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt; extrapolates smoothly to the CBS limit, for every single &lt;span class=&quot;math-container&quot;&gt;$(A,B)$&lt;/span&gt; pair: even if you consider just 50 elements in the periodic table, there's 2500 pairs, and if you consider the essentially countless number of possible molecules you can make with 50 elements, you can see why basis sets would be optimized at the atomic level. In most basis set families, there's one basis set for each atom, and it's optimized using calculations only on that atom. It would be extremely rare to see a basis set optimized for an entire molecule or collection of atoms.&lt;/p&gt;&#xA;&lt;p&gt;If you extrapolate &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; to the CBS limit, then extrapolate &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; to the CBS limit, then take the difference between the extrapolated &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and the extrapolated &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt;, it may be more convenient for you and others, since your extrapolated &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; are in some sense more &amp;quot;fundamental&amp;quot; than an extrapolated &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt; value, and the same is true for extrapolating each of &lt;span class=&quot;math-container&quot;&gt;$E_A,E_B$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt; and calculating &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt; rather than extrapolating the complicated expression of &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In fact, I'm not sure what formula you would use to extrapolate &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt; itself, because most extrapolation formulas work on individual energies like &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt;. That being said, it is indeed possible that you find yourself in a situation where it's easier to get a good extrapolation for a &lt;em&gt;property&lt;/em&gt; than for individual energies.&lt;/p&gt;&#xA;&lt;p&gt;What worked very well for us in &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; in which the aim was to get an extremely accurate value for the carbon atom ionization energy, was that did a CBS extrapolation for the &lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt; atom and for the &lt;span class=&quot;math-container&quot;&gt;$\ce{C^+}$&lt;/span&gt; ion with (aug-cc-pCV5Z,aug-cc-pCV6Z), with (aug-cc-pCV6Z,aug-cc-pCV7Z), and with (aug-cc-pCV7Z,aug-cc-pCV8Z), then we &lt;em&gt;&lt;strong&gt;extrapolated the extrapolation&lt;/strong&gt;&lt;/em&gt; by fitting a curve through the 3 extrapolations: see Figure 1 of the supplementary data &lt;a href=&quot;https://github.com/HPQC-LABS/Carbon/blob/master/extra/supp.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. &lt;strong&gt;So indeed you can&lt;/strong&gt; try to fit the &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt; values for multiple basis set sizes to a curve and extrapolate that way, but the simplest and most common way would be to extrapolate &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt; using something like Eqs. 1-4 in the first link above, and then approximate the CBS limits of &lt;span class=&quot;math-container&quot;&gt;$E_{AB}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{AB} - E_A - E_B$&lt;/span&gt; based on those extrapolated values!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-19T13:56:46.723" LastActivityDate="2021-05-19T13:56:46.723" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5015" PostTypeId="1" CreationDate="2021-05-19T15:27:38.640" Score="9" ViewCount="200" Body="&lt;p&gt;I'm wondering specifically in the context of &lt;strong&gt;calculating physical properties&lt;/strong&gt; from &lt;em&gt;valence-electron-density data&lt;/em&gt; using  DFT, MD, and or ML (machine learning).&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2021-07-13T16:32:12.677" LastActivityDate="2021-07-13T16:32:12.677" Title="Is &quot;Valence Electron Density&quot; and &quot;Electron Density&quot; data of a molecule the same thing?" Tags="|density-functional-theory|molecular-dynamics|physical-properties-of-materials|machine-learning|electron-density|" AnswerCount="0" CommentCount="7" ClosedDate="2021-07-12T14:48:36.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="5016" PostTypeId="2" ParentId="5005" CreationDate="2021-05-19T18:04:33.127" Score="13" Body="&lt;p&gt;I am going to try to go systematically through your question and answer the critical bits. I may edit this answer going forward as I'm able to express my thoughts better or people point out important subtleties that I may be missing.&lt;/p&gt;&#xA;&lt;p&gt;First, in KS-DFT (without any Generalized KS (GKS) or w/e), &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; is explicitly multiplicative and local. So it is necessarily always something of the form &lt;span class=&quot;math-container&quot;&gt;$V_{xc}(\vec{r}) \psi(\vec{r})$&lt;/span&gt;. Also, &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; is static, meaning that you cannot get quasiparticle lifetimes from it. Which isn't a problem since KS states are &lt;strong&gt;not&lt;/strong&gt; quasiparticle states anyway (except some more recent GKS formulations). But the primary message right now is: KS DFT with &lt;em&gt;necessarily&lt;/em&gt; local functionals does not give you QP states. There is some fantastic work by Baerends and co. out there that goes into the details of the relations between KS states and QP states.&lt;/p&gt;&#xA;&lt;p&gt;Now, onto GW. The GW self-energy is frequency-dependent, non-Hermitian, and nonlocal (although short-ranged, it exponentially decays away for gapped systems, or finite-temperature metals, see ref 1, p 257). Given that &lt;span class=&quot;math-container&quot;&gt;$\Sigma(1, 2)=iG(1, 2)W(1^+, 2)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$1\equiv(\vec{r}_1, t_1)$&lt;/span&gt; and similarly for &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt;, you see that &lt;span class=&quot;math-container&quot;&gt;$\Sigma$&lt;/span&gt; acts between two points. It's a way (roughly) of describing 'ah yes, the electron (or more commonly, test charge) here is feeling this potential due to the rest of the material'.&lt;/p&gt;&#xA;&lt;p&gt;The GW approximation (with whatever approximation you want for &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;, typically the random phase approximation is taken for the &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; used to construct &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;) is rigorously formulated so that, given a noninteracting set of wavefunctions to act as a basis (the DFT wavefunctions, in this case), the energies it gives you are rigorously quasiparticle energies. Meaning that it will actually model (obviously to within the limitations of the approximation) addition-removal energies that you would measure using photoemission/inverse photoemission.&lt;/p&gt;&#xA;&lt;p&gt;I've really shortened many things here, and I'm sure some people here may even think I've shortened it so far as to be misleading (which I've tried not to be, but we are all human).&lt;/p&gt;&#xA;&lt;p&gt;So if you want to look more into this, here are a few of my favourite references on the matter:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Interacting Electrons Theory and Computational Approaches&lt;/strong&gt;: Martin, Reining, Ceperley. This is probably the one-stop text for an introduction to GW and the general ideas behind it, and even the specifics. The presentation is extremely pedagogical, and I personally find this text positively fantastic. Chapter 9+ has what you're looking for.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;From the Kohn–Sham band gap to the fundamental gap in solids. An integer electron approach&lt;/strong&gt;: Pedagogical review by Baerends on what the different gaps in KSDFT mean, and hopw they are related to each other. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2017/cp/c7cp02123b#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2017/cp/c7cp02123b#!divAbstract&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;The Kohn–Sham gap, the fundamental gap and the optical gap: the physical meaning of occupied and virtual Kohn–Sham orbital energies&lt;/strong&gt;: Another review by Baerends and colleagues. Very illuminating, and just generally a great read. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/cp/c3cp52547c#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2013/cp/c3cp52547c#!divAbstract&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;All three of the above resources have numerous 'aha!' moments, where connections about the physics and the formalism click, and I have personally found them extremely helpful in my journey through electronic structure.&lt;/p&gt;&#xA;" OwnerUserId="512" LastEditorUserId="512" LastEditDate="2021-05-19T21:31:30.153" LastActivityDate="2021-05-19T21:31:30.153" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5017" PostTypeId="2" ParentId="5013" CreationDate="2021-05-19T18:09:22.957" Score="5" Body="&lt;p&gt;Extrapolating &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{prop}}$&lt;/span&gt; is completely equivalent to extrapolating the individual terms. This follows simply from the fact that all &amp;quot;sensible&amp;quot; basis set extrapolation formulas are a linear combination of the finite basis set energies used for extrapolating the CBS energy. You can easily see this fact from Eqs. (3-4) of the paper posted by Nike Dattani. If the extrapolation formula tells you, e.g. &lt;span class=&quot;math-container&quot;&gt;$E_A(\mathrm{CBS}) = 1.5E_A(\mathrm{QZ}) - 0.5E_A(\mathrm{TZ})$&lt;/span&gt;, for arbitrary &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, then from you expression of &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{prop}}$&lt;/span&gt;, it must be that &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{prop}}(\mathrm{CBS}) = 1.5E_{\mathrm{prop}}(\mathrm{QZ}) - 0.5E_{\mathrm{prop}}(\mathrm{TZ})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;And I said &amp;quot;all sensible basis set extrapolation formulas&amp;quot;, because if there is a basis set extrapolation formula that is not a linear combination of the energies it uses, then the extrapolated energy is not size-consistent (although such kind of formulas do exist and are not uncommon - thank Tyberius for pointing out that!). This is because size-consistency dictates that the extrapolated energy of a system composed of two arbitrary non-interacting molecules &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; must be the sum of the extrapolated energies of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;. As the finite basis set energies of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; can adopt any value, the only way that an extrapolation formula always respects size-consistency is that it does not contain any nonlinear and/or cross terms of &lt;span class=&quot;math-container&quot;&gt;$E_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_B$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-05-20T08:15:32.343" LastActivityDate="2021-05-20T08:15:32.343" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5018" PostTypeId="1" AcceptedAnswerId="5019" CreationDate="2021-05-19T18:35:27.120" Score="25" ViewCount="3487" Body="&lt;p&gt;What are practical concerns for creating a workstation that will likely be expanded in the future to have more workstations/nodes?&lt;/p&gt;&#xA;&lt;p&gt;I am interested in running atomistic and quantum mechanical calculations.&lt;/p&gt;&#xA;&lt;p&gt;Most jobs would be 12 or fewer cores (nearly all would be 4-6 core jobs), but there would be times when many would be running simultaneously. It would be nice to control priority, but this isn't crucial.&lt;/p&gt;&#xA;&lt;p&gt;The most used software would be psi4, Gaussian, GPAW, Quantum ESPRESSO and GROMACS. These would all be run on CPU's. In the future perhaps I would try GPU's for plane wave DFT and MD, but, Gaussian basis set electronic structure programs are not well suited for GPU's, yet.&lt;/p&gt;&#xA;&lt;p&gt;My feeling is that a default Linux distribution would probably be okay, or perhaps &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1427/181&quot;&gt;Quantum Mobile&lt;/a&gt; in which case Windows would also be okay, but I don't know how well Quantum Mobile is for production runs, it advertises on desktops as educational and tutorial.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="5" LastEditDate="2021-06-15T22:03:23.427" LastActivityDate="2021-06-17T13:25:10.820" Title="Are there critical mistakes to avoid when creating a workstation (32-128 cores)?" Tags="|high-performance-computing|computational-frameworks|high-throughput|" AnswerCount="6" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5019" PostTypeId="2" ParentId="5018" CreationDate="2021-05-19T21:34:37.353" Score="22" Body="&lt;p&gt;One mistake you already described is using virtualization. Nothing is more reliable than running your code directly on your hardware, without intermediaries (even when the virtualization software and Windows are evolving each day). It will be better to have a dual-boot system if you really need Windows than virtualization.&lt;/p&gt;&#xA;&lt;p&gt;To avoid mistakes, you need to start reading the specifications of the code(s) you pretend to use.&lt;/p&gt;&#xA;&lt;p&gt;Codes that use planewaves (like QuantumEspresso, ABINIT, etc.) are known to be huge RAM consumers (and I mean, they eat LOTS of RAM). On the other hand, codes like SIESTA uses much less RAM.&lt;/p&gt;&#xA;&lt;p&gt;If running Molecular Dynamics calculations, must of the main codes used today (LAMMP, GROMACS, NAMD, DESMOND) use GPUs (and believe me, they are much more efficient than using CPUs).&lt;/p&gt;&#xA;&lt;p&gt;If the code uses hard disk extensively, you will need high capacity hard disk and even SSD drives (or SCSI) to avoid write/read delays.&lt;/p&gt;&#xA;&lt;p&gt;Finally, if you will add your workstation to a cluster, you will need a high speed network cards to avoid delays in the node-node communication.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-06-17T13:25:10.820" LastActivityDate="2021-06-17T13:25:10.820" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5020" PostTypeId="2" ParentId="5018" CreationDate="2021-05-20T00:11:36.017" Score="19" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Are there critical mistakes to avoid when creating a matter modeling workstation (32-128 cores)?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;32-128 is quite a big range since at 128 you'd be limited to non-mainstream chips like the &lt;a href=&quot;https://www.theregister.com/2021/05/19/ampere_altra_max_specs_revealed/&quot; rel=&quot;noreferrer&quot;&gt;Ampere&lt;/a&gt; and as far as I know, the most cores in an Intel processor apart from the Xeon Phi line (which was discontinued in 2020 and wasn't a conventional processor anyway) is 40 cores (80 threads). AMD has 64-core processors but AMD is far less in the &amp;quot;mainstream&amp;quot; for the type of workstation you're trying to build and you're probably better off with Intel. While it's true that AMD has their place in HPC, for example &lt;a href=&quot;https://en.wikipedia.org/wiki/Exascale_computing&quot; rel=&quot;noreferrer&quot;&gt;the $600 million El Capitan project&lt;/a&gt;, that's a custom-made system and what you'll get from the store is not going to be the same hardware that's going in El Capitan.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I would stick with 40 cores or fewer, and if you want to run more than 3 of your 12-core jobs simultaneously, perhaps get two or three 40-core workstations rather than a single node with 128 cores.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What are practical concerns for creating a workstation that will likely be expanded in the future to have more workstations/nodes?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You said &amp;quot;Most jobs would be 12 or fewer cores, but there would be times when many would be running simultaneously&amp;quot; so I would strongly recommend avoiding the complexity of making a multi-node system connected via OmniPath, InfiniBand or ethernet (which would be &lt;em&gt;much&lt;/em&gt; slower than the first two, which would unfortunately add a lot to the overall cost).&lt;/p&gt;&#xA;&lt;p&gt;At this scale (32-128 cores for multiple separate 12-core jobs) it would be best to have a few workstations rather than trying to build a multi-node supercomputer.&#xA;It's true that some research groups have a &amp;quot;cluster&amp;quot; of connected nodes, but you'd be making things &lt;em&gt;&lt;strong&gt;much&lt;/strong&gt;&lt;/em&gt; more complicated and expensive (for the inter-node connectivity). If you're running separate 12-core jobs up to 128-cores worth, that's only 10 jobs and I'd rather manage 10 jobs on &lt;em&gt;three 40-core workstations&lt;/em&gt;  or four 32-core ones than pay so much more for InfiniBand and deal with the hassle of a multi-node system.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My feeling is that a default Linux distribution would probably be okay, or perhaps Quantum Mobile in which case Windows would also be okay, but I don't know how well Quantum Mobile is for production runs, it advertises on desktops as educational and tutorial.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You said you're going to be &amp;quot;running atomistic and quantum mechanical calculations&amp;quot; for which all mainstream software is primarily tested on Linux machines, with Windows or MacOS functionality &lt;em&gt;sometimes&lt;/em&gt; possible but not guaranteed. You may consider a dual-boot with Windows &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5019/5&quot;&gt;as Camps suggested&lt;/a&gt; for the few programs for which you need Windows, or if you're really considering to expand to 128-cores then you'll need three 40-core or four 32-core processors anyway, so one can be your Windows machine and the other two Linux. Quantum Mobile and others are mentioned in this previous question we had: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1224/5&quot;&gt;Which Linux distribution is best for Matter Modeling?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-20T00:11:36.017" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5021" PostTypeId="1" CreationDate="2021-05-20T07:07:21.610" Score="11" ViewCount="1348" Body="&lt;p&gt;I ran a frequency analysis employing Gaussian 16 on MP2/6-31+G(d,p) level of theory with the keyword &lt;code&gt;iop(7/33=1)&lt;/code&gt; in order to have access to dipole derivatives with respect to the individual normal mode coordinates. An example line from the output reads&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Dipole derivative wrt mode XX:  5.93205D-01 -1.47564D+00  1.93547D-02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does anybody know in which units the dipole derivatives are actually written and can, ideally, point me at a corresponding documentation?&lt;/p&gt;&#xA;&lt;p&gt;Up to know I read it should be something like &lt;span class=&quot;math-container&quot;&gt;$\sqrt{\pu{km}/\pu{mol}}$&lt;/span&gt;, but I have no clear evidence that this is the case. I would expect something involving Debye and atomic mass unit, like &lt;span class=&quot;math-container&quot;&gt;$\pu{D}/\sqrt{\pu{u}}\,a_0$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerDisplayName="ewf" LastEditorUserId="724" LastEditDate="2021-05-20T09:01:15.867" LastActivityDate="2021-06-21T10:53:10.547" Title="What units are used in Gaussian 16 for dipole derivatives output?" Tags="|software|reference-request|computational-chemistry|gaussian|dipole|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5022" PostTypeId="1" CreationDate="2021-05-20T16:35:09.500" Score="9" ViewCount="206" Body="&lt;p&gt;Presently I am doing DFT calculations to analyse the electronic structure of a material. I got the band structure as shown in the figure. I would like to know the electrical behavior of this material. The Fermi Energy is shifted to 0 eV.&lt;a href=&quot;https://i.stack.imgur.com/iqqd3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iqqd3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5L5xn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5L5xn.png&quot; alt=&quot;Zoomed Band structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3611" LastEditorUserId="3611" LastEditDate="2021-05-21T02:50:03.537" LastActivityDate="2021-05-29T13:55:25.677" Title="What is the electrical behavior of the material with this band gap?" Tags="|density-functional-theory|band-structure|electronic-structure|" AnswerCount="1" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="5023" PostTypeId="1" CreationDate="2021-05-20T17:22:27.327" Score="9" ViewCount="431" Body="&lt;p&gt;I got hold of a CIF file for a material that I am interested in. I am trying to isolate the xyz coordinates of the molecules. However, when I open the CIF file in VESTA, I get a near-infinite periodic structure. See the attached image:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CozAa.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CozAa.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, in VESTA, if I go to &lt;code&gt;edit -&amp;gt; crystal structure -&amp;gt; systems&lt;/code&gt; and then &lt;code&gt;choose molecule&lt;/code&gt;, I can reduce the system to a molecule. However, it looks quite weird, especially in regards to side groups. I believe that two possible representations of the side groups might have gotten super-imposed on each other. See the attached picture. Is there a way to fix this?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0tER3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0tER3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the CCDC website, I was able to get a proper image of the unit cell I am looking for.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/s9r1R.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s9r1R.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The CDCC webpage with the CIF file is available in &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/Search?Ccdcid=1579467&amp;amp;DatabaseToSearch=Published&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am using VESTA and I have access to pyMOL, GaussView and the free version of Mercury. Ideally I would like to isolate the xyz coordinates of one of the dimers in the unit cell, is there an easy way to do this?&lt;/p&gt;&#xA;" OwnerUserId="3586" LastEditorUserId="85" LastEditDate="2021-06-04T10:17:13.983" LastActivityDate="2021-06-04T10:17:13.983" Title="Problems with finding the unit cell from a CIF file and extracting XYZ coordinates using a software" Tags="|crystal-structure|crystallography|vesta|mercury|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5024" PostTypeId="2" ParentId="1224" CreationDate="2021-05-20T19:03:31.960" Score="7" Body="&lt;h2&gt;OpenSUSE&lt;/h2&gt;&#xA;&lt;p&gt;It is oriented both to desktop and to servers. It has a large collection of software repositories for scientific computing in general (you can have all of GCC 7, 9, 10, 11 at the same time, module system for different versions of MPI libraries, CAD, CFD,...) and even for matter modelling in particular (&lt;a href=&quot;https://software.opensuse.org/package/gromacs&quot; rel=&quot;noreferrer&quot;&gt;GROMACS&lt;/a&gt;, &lt;a href=&quot;https://software.opensuse.org/package/lammps&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt;, &lt;a href=&quot;https://software.opensuse.org/package/quantum-espresso&quot; rel=&quot;noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt;, etc.).&lt;/p&gt;&#xA;&lt;p&gt;It supports both KDE and Gnome equally (and some more). It can be updated without re-install or one can even use the continuously-updated  Tumbleweed version.&lt;/p&gt;&#xA;" OwnerUserId="3473" LastEditorUserId="5" LastEditDate="2021-05-20T22:26:12.763" LastActivityDate="2021-05-20T22:26:12.763" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5025" PostTypeId="1" CreationDate="2021-05-20T19:40:26.620" Score="7" ViewCount="370" Body="&lt;p&gt;How can I set a different band path for VASP calculation? For example I want to plot KGMK but not GMKG for graphene?&lt;/p&gt;&#xA;" OwnerUserId="3613" LastActivityDate="2021-05-22T01:01:38.360" Title="How to choose a different band path for band structure calculation using VASP?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5026" PostTypeId="2" ParentId="5018" CreationDate="2021-05-21T06:45:18.450" Score="12" Body="&lt;p&gt;I would suggest to stay away from niche solutions and start with &lt;em&gt;one&lt;/em&gt; mainstream machine.&lt;/p&gt;&#xA;&lt;p&gt;The most direct reason is that you get much more computing power for the same money if you buy mass-produced hardware.&lt;/p&gt;&#xA;&lt;p&gt;A more indirect reason is that everything you buy next year will be 20% cheaper or faster, your choice, cumulative for each year. If you want optimal performance, cater to the jobs you want to run &lt;em&gt;now.&lt;/em&gt; In particular, as everybody knows a herd of greedy morons have created a GPU shortage. While I am not clairvoyant the situation may improve before you buy again, either because cryptocurrencies crash — in which case you'll be able to buy &lt;em&gt;real&lt;/em&gt; cheap because the market will be flooded — or because the chip supply adapts.&lt;/p&gt;&#xA;&lt;p&gt;The most long-term reason is that you'll avoid locking yourself in. If you buy in a granular fashion you can cater to the workloads as they appear. A mainstream machine will be so cheap compared to your 128 core server that you may &lt;em&gt;still&lt;/em&gt; be able to buy one next year if and when you really need it — and &lt;em&gt;not&lt;/em&gt; if you &lt;em&gt;don't.&lt;/em&gt; (I suppose you need to strike a deal with your budget director, shifting unused funds to the next year. But that's outside the scope of this question.)&lt;/p&gt;&#xA;" OwnerUserId="1617" LastEditorUserId="1617" LastEditDate="2021-05-21T13:14:15.163" LastActivityDate="2021-05-21T13:14:15.163" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5027" PostTypeId="1" AcceptedAnswerId="6251" CreationDate="2021-05-21T07:38:19.540" Score="8" ViewCount="636" Body="&lt;p&gt;I have a cubic-FCC with a=b=c and  &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;=&lt;span class=&quot;math-container&quot;&gt;$90^o$&lt;/span&gt;. As far as I understand the volume of this cubic unit cell should be a cube of the lattice constant. But this not the case I am seeing in the quantum ESPRESSO, SCF output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; bravais-lattice index     =            2&#xA; lattice parameter (alat)  =      10.9569  a.u.&#xA; unit-cell volume          =     328.8522 (a.u.)^3&#xA; number of atoms/cell      =            4&#xA; number of atomic types    =            3&#xA; number of electrons       =        60.00&#xA; number of Kohn-Sham states=           36&#xA; kinetic-energy cutoff     =     200.0000  Ry&#xA; charge density cutoff     =    2000.0000  Ry &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see that unit cell volume is not the cube of the lattice parameter. Why is it so? Am I putting any parameter wrongly?&lt;/p&gt;&#xA;&lt;p&gt;Please help with this.&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2021-05-21T14:12:22.493" LastActivityDate="2021-06-26T23:41:06.677" Title="Why volume of unit cell is not the same as cubing the lattice constant?" Tags="|density-functional-theory|quantum-espresso|lattice-dynamics|cell-optimization|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5028" PostTypeId="1" AcceptedAnswerId="5033" CreationDate="2021-05-21T17:22:55.730" Score="8" ViewCount="460" Body="&lt;p&gt;The tensile test of a material consists of subjecting a standardized specimen to an increasing axial tensile stress until it breaks. During its performance in the laboratory, we can plot a stress-strain curve, which usually has the following form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8ciPB.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8ciPB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the elastic zone, a linear relationship is found between the applied stress and the deformation undergone by the specimen. This relationship is known as Hooke's Law. On the other hand, for the plastic regime, I cannot find any mathematical model to explain it. In some books, I have found the Ramberg-Osgood equation, but they indicate that it applies mainly in the elastic limit environment.&lt;/p&gt;&#xA;&lt;p&gt;Do you know of any model for the plastic deformation region (strain hardening, necking...)?&lt;/p&gt;&#xA;" OwnerUserId="1744" LastEditorUserId="5" LastEditDate="2021-05-21T17:51:06.777" LastActivityDate="2021-06-04T21:01:26.660" Title="Mathematical models for the plastic region in the tensile test" Tags="|mathematical-modeling|physical-properties-of-materials|materials-engineering|stress-strain|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5029" PostTypeId="1" AcceptedAnswerId="5062" CreationDate="2021-05-21T18:18:15.320" Score="12" ViewCount="345" Body="&lt;p&gt;Consider &lt;a href=&quot;https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/3/67057/files/2018/09/graphene_tight-binding_model-1ny95f1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;the usual simple 2-level graphene Hamiltonian with mass&lt;/a&gt; in momentum-space where:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H(k,V)=-t \sum_{\delta} [\cos(k\cdot\delta)\sigma_x-\sin(k\cdot\delta)\sigma_y+V\sigma_z],&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is the hopping, &lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; are Pauli matrices, &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; lattice vectors and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; an on-site potential (&lt;span class=&quot;math-container&quot;&gt;$V=0$&lt;/span&gt; for graphene, where the energy dispersion is degenerate/gapless at a Dirac point).&lt;/p&gt;&#xA;&lt;p&gt;The parameter space above is 2D momentum/k-space, and the eigenvalue equation can be easily solved as I show in my answer here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4980/how-to-create-a-3d-band-structure-from-dft-band-structure-calculation/4982#4982&quot;&gt;How to create a 3D band structure from DFT band structure calculation?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, I want to numerically solve its real-space analog. I know k and real space are related to each other via Fourier transforms (&lt;a href=&quot;https://quantummechanics.ucsd.edu/ph130a/130_notes/node82.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://quantummechanics.ucsd.edu/ph130a/130_notes/node82.html&lt;/a&gt;). However, I want to plot the wavefunction amplitudes of this system along a 1D real space line where the on-site potential &lt;span class=&quot;math-container&quot;&gt;$V(x)$&lt;/span&gt; varies. So, I want to plot something like figure c) here: &lt;a href=&quot;https://arxiv.org/pdf/2005.06096.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/2005.06096.pdf&lt;/a&gt; (reproduced below):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/LWuf4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LWuf4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there a simple way to do this? I know I am being naive here, but would it be as simple as just taking the Fourier transforms of eigenvectors from the k-space method? This comes with the issue of choosing k-points corresponding to the real-space 1D line. I know that in theory, people usually change the Hamiltonian between spaces by inverting the creation/annihilation operators' spaces, etc. But is there something more straightforward numerically (something as silly as Fourier transforming the above k-space Hamiltonian)? There's also just replacing &lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$~\partial_x$&lt;/span&gt; (as in section 3.5.7 in &lt;a href=&quot;https://arxiv.org/abs/1310.0255&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/1310.0255&lt;/a&gt;), but I am just wondering whether there is something more straightforward due to numerics.&lt;/p&gt;&#xA;&lt;p&gt;Or should I come up with some other way? &lt;strong&gt;I do not wish to use DFT and ab initio techniques, just simple numerical software like Python or MATLAB.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="243" LastEditDate="2021-05-23T15:40:17.980" LastActivityDate="2021-05-28T16:59:04.810" Title="How to numerically solve real-space 1D time-independent Schrodinger equation using 2D momentum-space Hamiltonian?" Tags="|condensed-matter|python|quantum-mechanics|wavefunctions|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5030" PostTypeId="2" ParentId="5018" CreationDate="2021-05-21T18:22:05.270" Score="10" Body="&lt;p&gt;Buying an Intel CPU would be one, for sure. (unless you are buying an Ice Lake server)&lt;/p&gt;&#xA;&lt;p&gt;I think the biggest decision to make is to build a CPU box or a GPU box.&#xA;For atom-centered Gaussian basis set quantum chemistry you probably going to want a CPU box, with lots of RAM and a very fast and a high endurance SSD.&lt;/p&gt;&#xA;" OwnerUserId="3410" LastActivityDate="2021-05-21T18:22:05.270" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5031" PostTypeId="2" ParentId="1693" CreationDate="2021-05-21T20:21:58.857" Score="7" Body="&lt;p&gt;For 1D spin Hamiltons it is perfectly doable even if you code from scratch. NumPy should be sufficient. I have written DMRG codes in both Julia and python and I see no difference, this is also due to the fact that I am a newbie in Julia and my codes are far from good. However, if you are willing to use python I will suggest you to do all the algorithm level optimization first, find efficient tensor contraction order for all the contractions, write your own cheap Lanczos/Arnoldo eigensolver that saves you from building big matrices to use a Python eigensolver libraries.&lt;/p&gt;&#xA;&lt;p&gt;Currently my code for long range transverse field Ising model with 200 lattice sites and bond dimension as high as 100 can  do a  ground state search in just few minutes and all has been coded in python from the scratch.&lt;/p&gt;&#xA;" OwnerUserId="3619" LastActivityDate="2021-05-21T20:21:58.857" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5032" PostTypeId="2" ParentId="5025" CreationDate="2021-05-22T01:01:38.360" Score="8" Body="&lt;p&gt;You can use a tool called &lt;a href=&quot;https://tools.materialscloud.org/seekpath/&quot; rel=&quot;noreferrer&quot;&gt;SeeK-path&lt;/a&gt; to get the high-symmetry points for your structure using the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/POSCAR&quot; rel=&quot;noreferrer&quot;&gt;POSCAR&lt;/a&gt; file as an input. For instance, for graphene, your &lt;a href=&quot;https://www.vasp.at/wiki/index.php/POSCAR&quot; rel=&quot;noreferrer&quot;&gt;POSCAR&lt;/a&gt; could be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C&#xA;1.0&#xA;1.22800000 -2.12695839  0.00000000&#xA;1.22800000  2.12695839  0.00000000&#xA;0.00000000  0.00000000  20.&#xA;2&#xA;direct&#xA;   0.00000000  0.00000000  0.25000000&#xA;   0.33333333  0.66666667  0.25000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, &lt;a href=&quot;https://tools.materialscloud.org/seekpath/&quot; rel=&quot;noreferrer&quot;&gt;SeeK-path&lt;/a&gt; returns the coordinates for the high-symmetry points, suggests a &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; path, and even provides the suggested path in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/KPOINTS&quot; rel=&quot;noreferrer&quot;&gt;KPOINTS&lt;/a&gt;-file format for a band-structure calculation with VASP:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Special k-points for band structure&#xA;&amp;lt;...&amp;gt;  ! intersections &#xA;line-mode&#xA;reciprocal&#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;    0.5000000000     0.0000000000     0.0000000000 1    M &#xA;&#xA;&#xA;    0.5000000000     0.0000000000     0.0000000000 1    M &#xA;    0.3333333333     0.3333333333     0.0000000000 1    K &#xA;&#xA;&#xA;    0.3333333333     0.3333333333     0.0000000000 1    K &#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;&#xA;&#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;    0.0000000000     0.0000000000     0.5000000000 1    A &#xA;&#xA;&#xA;    0.0000000000     0.0000000000     0.5000000000 1    A &#xA;    0.5000000000     0.0000000000     0.5000000000 1    L &#xA;&#xA;&#xA;    0.5000000000     0.0000000000     0.5000000000 1    L &#xA;    0.3333333333     0.3333333333     0.5000000000 1    H &#xA;&#xA;&#xA;    0.3333333333     0.3333333333     0.5000000000 1    H &#xA;    0.0000000000     0.0000000000     0.5000000000 1    A &#xA;&#xA;&#xA;    0.5000000000     0.0000000000     0.5000000000 1    L &#xA;    0.5000000000     0.0000000000     0.0000000000 1    M &#xA;&#xA;&#xA;    0.3333333333     0.3333333333     0.5000000000 1    H &#xA;    0.3333333333     0.3333333333     0.0000000000 1    K &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can now adjust this file to your preference: Frist, &lt;code&gt;&amp;lt;...&amp;gt;&lt;/code&gt; needs to be replaced by the number of $\vec{k}$ points between two high-symmetry points. Second, you can change the $\vec{k}$ path, e.g., by changing the order of the high-symmetry points. For instance, if you want to plot the band structure along K–$\Gamma$–M–K with 3 x 13 $\vec{k}$ points, that yields&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K–G–M–K for graphene&#xA;13        ! intersections &#xA;line-mode&#xA;reciprocal &#xA;    0.3333333333     0.3333333333     0.0000000000 1    K &#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;&#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;    0.5000000000     0.0000000000     0.0000000000 1    M &#xA;&#xA;    0.5000000000     0.0000000000     0.0000000000 1    M &#xA;    0.3333333333     0.3333333333     0.0000000000 1    K &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2237" LastActivityDate="2021-05-22T01:01:38.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5033" PostTypeId="2" ParentId="5028" CreationDate="2021-05-22T03:20:04.903" Score="10" Body="&lt;p&gt;Plasticity is still an actively researched area. The &lt;strong&gt;Ludwik-Hollomon&lt;/strong&gt; equation is one model that is used for the strain-hardening region since it captures the convex shape of the curve using a power law:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma = K \epsilon^{n} \tag{1}$$&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is known as the &lt;em&gt;strain hardening coefficient&lt;/em&gt; or &lt;em&gt;strain hardening exponent&lt;/em&gt;. This equation only captures the relationship between the stress and strain. To model the effect of strain rate (&lt;span class=&quot;math-container&quot;&gt;$\dot{\epsilon}$&lt;/span&gt;), another factor of &lt;span class=&quot;math-container&quot;&gt;$\dot{\epsilon}^m$&lt;/span&gt; can be added to give:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma = K \epsilon^{n}\dot{\epsilon}^{m}\tag{2}$$&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; is known as the &lt;em&gt;strain rate sensitivity exponent&lt;/em&gt;. This is only a simple empirical model, and there are more (empirical or semi-empirical) models that have been proposed to capture the physics in the problem better. These models are referred to as hardening laws, and one example is &lt;strong&gt;Voce hardening&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the region beyond the Ultimate Tensile Stress (UTS), necking occurs in the material, and the behaviour of the stress-strain curve depends on the heterogeneity in the sample. This phenomenon makes the UTS a point of geometric instability. Therefore, after the onset of necking, the engineering stress-strain curve doesn't possess a lot of fundamental value.&lt;/p&gt;&#xA;&lt;p&gt;Also, note that the stress-strain curve in the question is highly exaggerated and idealised. In most engineering materials, there is no distinguishable &amp;quot;perfectly plastic&amp;quot; region. In fact, because of strain hardening, it is also not possible to &amp;quot;define&amp;quot; a yield stress purely based on how the curve changes from a linear region to a non-linear region. Rather, yield stress is defined as the stress at which one observes 2% permanent strain.&lt;/p&gt;&#xA;" OwnerUserId="22" LastEditorUserId="5" LastEditDate="2021-05-22T07:40:29.090" LastActivityDate="2021-05-22T07:40:29.090" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5034" PostTypeId="1" AcceptedAnswerId="6292" CreationDate="2021-05-15T09:08:23.840" Score="10" ViewCount="528" Body="&lt;p&gt;Lets assume we have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; Atoms and we treat them within the Born-Oppenheimer Approximation. We can calculate the adiabatic electronic groundstate potential. Lets assume we observe two local minima, denoted by &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, on this potential energy surface. Lets denote these minima nuclear coordinates as &lt;span class=&quot;math-container&quot;&gt;$R_\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R_{\beta} $&lt;/span&gt;. At each minimum we can do an harmonic approximation of the potential, centered on the corresponding minimum,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;V_\alpha(R) = V(R_\alpha)+(R-R_\alpha)^T V'_{\alpha} + 1/2(R-R_\alpha)^TV''_{\alpha}(R-R_\alpha) \tag{1}\\&#xA;V_\beta(R) = V(R_\beta)+(R-R_\alpha)^T V'_{\beta} + 1/2(R-R_\beta)^TV''_{\beta}(R-R_\beta) \tag{2}\\&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the gradent is &lt;span class=&quot;math-container&quot;&gt;$V'_\alpha=\nabla_RV(R)|_{R=R_\alpha}$&lt;/span&gt; and the Hessian &lt;span class=&quot;math-container&quot;&gt;$V''_{\alpha,nm} = \frac{\partial^2 V}{\partial R_n \partial R_m}|_{R=R_\alpha}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Since we are in a local minimum, we know that the gradients vanish,&lt;span class=&quot;math-container&quot;&gt;$V'=0$&lt;/span&gt;. For simplicities sake, we also assume that both potentials evaluated at the minimum strcucture are zero, &lt;span class=&quot;math-container&quot;&gt;$V(R_{\alpha/\beta})=0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The associated harmonic vibrational Hamiltonian in atomic units then takes on the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;H_\alpha(R) = -\frac{1}{2}\nabla^T_RM^{-1}\nabla_R + 1/2(R-R_\alpha)^TV''_\alpha(R-R_\alpha)&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is a diagonal matrix with the nuclear masses.&lt;/p&gt;&#xA;&lt;p&gt;Each harmonic potential allows the definition of vibrational normal modes and vibrational normal coordinates. The transformation to normal coordinates is defined as follows.&lt;/p&gt;&#xA;&lt;p&gt;First we define the mass weighted displacement coordinates &lt;span class=&quot;math-container&quot;&gt;$X_\alpha = M^{1/2}(R-R_\alpha)$&lt;/span&gt;, in these coordinates we have&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;H_\alpha(X_\alpha)= -\frac{1}{2}\nabla^T_{X_\alpha}\nabla_{X_\alpha} +1/2 X^T_\alpha M^{-1/2}V''_\alpha M^{-1/2} X_\alpha \tag{4}\\&#xA;H_\alpha(X_\alpha)= -\frac{1}{2}\nabla^T_{X_\alpha}\nabla_{X_\alpha} +1/2 X^T_\alpha W_\alpha  X_\alpha \tag{5}\\&#xA;\end{eqnarray}&lt;/span&gt;&#xA;with the mass weighted Hesse matrix &lt;span class=&quot;math-container&quot;&gt;$W=M^{-1/2}V''M^{-1/2}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The last step to obtain normal coordinates is the transformation to coordinates that diagonalize the mass weighted Hesse matrix. Let&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;WK = K\Lambda \tag{6}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is the matrix with eigenvectors of &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; as columns and &lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt; a diagonal matrix with corresponding eigenvalues. The required transformation is then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;X= KQ\tag{7}&#xA;$$&lt;/span&gt;&#xA;which leads to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H_\alpha(Q_\alpha)= -\frac{1}{2}\nabla^T_{Q_\alpha}\nabla_{Q_\alpha} +1/2 Q^T_\alpha \Lambda_\alpha  Q_\alpha \tag{8}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Summarized we have two different sets of transformations, one for each minimum,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;Q_\alpha = K^{-1}_\alpha M^{1/2}(R-R_\alpha)\tag{9}\\&#xA;Q_\beta = K^{-1}_\beta M^{1/2}(R-R_\beta) \tag{10}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;After this rather lengthy setup comes my question. How can I transform from one set of normal coordinates &lt;span class=&quot;math-container&quot;&gt;$Q_\alpha$&lt;/span&gt; to the other &lt;span class=&quot;math-container&quot;&gt;$Q_\beta$&lt;/span&gt; and how do I interpret this. Does that mean that I can express any molecules vibrational coordinates in the vibrational coordinates of another molecule(made from the same number and type of atoms)?&lt;/p&gt;&#xA;&lt;p&gt;Intuitively I see problems when the geometries are translated and rotated with respect to each other assuming a global cartesian coordinate system for both molecules. There should be no simple internal vibrational coordinate that could connect two such geometries but on the other hand, internal vibrational coordinates should form a complete coordinate system and allow me to express any structure with the same amount of atoms in it. I think I am missing something very obvious to reconcile this &amp;quot;contradiction&amp;quot;, which is why I need some input.&lt;/p&gt;&#xA;" OwnerUserId="2289" OwnerDisplayName="Hans Wurst" LastEditorUserId="5" LastEditDate="2021-05-22T07:37:50.367" LastActivityDate="2023-10-29T15:26:20.993" Title="Transformation between two different sets of molecular vibrational normal coordinate systems" Tags="|molecular-modeling|spectroscopy|vibrations|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5035" PostTypeId="1" AcceptedAnswerId="5036" CreationDate="2021-05-22T11:05:27.590" Score="16" ViewCount="853" Body="&lt;p&gt;For geometry optimization, most QM codes tend to use internal coordinates. Most codes also support Cartesian coordinates. I have always heard the usual &amp;quot;use Cartesian as a last resort, always use internals&amp;quot; advice.&lt;/p&gt;&#xA;&lt;p&gt;Recently I had to optimize small water clusters with Gaussian, and I found that in most cases, the optimization often stops when one of the dihedral angles goes close to &lt;span class=&quot;math-container&quot;&gt;$180^\circ$&lt;/span&gt;, with the error &amp;quot;Tors failed for dihedral&amp;quot;. My supervisor's advice was to start from the last frame where the optimization stopped (which would build a new set of coordinates I imagine). However, I found that if I used Cartesian optimization from the start, then I actually saved (my) time, which is otherwise lost in restarting the optimization, often multiple times.&lt;/p&gt;&#xA;&lt;p&gt;I also found that there were multiple types of internal coordinates, for example natural internal coordinates, Z-matrix supplied from outside, redundant internal coordinates and delocalized internal coordinates. I don't completely understand the difference between those.&lt;/p&gt;&#xA;&lt;p&gt;Another thing I noticed was that GAMESS never ran into the dihedral problem with internal coordinates, and GAMESS uses delocalized internals instead of redundant internal coordinates of Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;I found only one paper that discusses the choice of Cartesian vs redundant internals but it is very old [1]. I was able to run some small molecules on my laptop, and delocalized internals seem to be the fastest for all of them.&lt;/p&gt;&#xA;&lt;p&gt;So, my question — &lt;strong&gt;Is there any benchmark that compares the different coordinate systems for optimization, particularly the various types of internal coordinates, for small to large molecules?&lt;/strong&gt; I would also be interested to read any benchmarks that you run, so feel free to post those.&lt;/p&gt;&#xA;&lt;p&gt;Follow up question— &lt;strong&gt;Is it really that bad to use Cartesian coordinates?&lt;/strong&gt; because I found that they generally take 1-2x the time. So calling them last resort seems a bit extreme.&lt;/p&gt;&#xA;&lt;p&gt;Reference:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;H. B. Schlegel, &amp;quot;A comparison of geometry optimization with internal, cartesian, and mixed coordinates&amp;quot;, &lt;em&gt;Int. J. Quantum Chem.&lt;/em&gt;, &lt;strong&gt;44&lt;/strong&gt;, 243-252. &lt;a href=&quot;https://doi.org/10.1002/qua.560440821&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1002/qua.560440821&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-07-21T20:47:26.503" Title="Choice of coordinate system for geometry optimization" Tags="|reference-request|geometry-optimization|benchmark-timings|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5036" PostTypeId="2" ParentId="5035" CreationDate="2021-05-22T12:44:17.080" Score="19" Body="&lt;p&gt;You may want to have a look at this paper:&#xA;&amp;quot;Geometry optimization made simple with translation and rotation coordinates&amp;quot;&#xA;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4952956&quot; rel=&quot;noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.4952956&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is not a comprehensive benchmark but it does contain a few examples ranging from water clusters of 12 water molecules to small proteins. According to this paper Cartesian coordinates are on average a poor choice for small water clusters, but it seems to have a better worst-case performance than delocalized internal coordinates.&lt;/p&gt;&#xA;&lt;p&gt;Internal coordinates have numerical instabilities when some of the angles approach 180 degrees. If these angles are already linear from the very start of the optimization, the program can construct the internal coordinates in such a way that they do not include the linear angles, or at least not in a way that causes numerical instabilities. Usually problems only arise when an angle that was originally not linear becomes linear during the optimization; this does not happen very often for covalently linked systems, as you usually draw linear angles (like alkynes or nitriles) as linear from the start, but it happens more frequently for noncovalent clusters - it's very common that you draw a nonlinear hydrogen bond in your initial guess structure but which turns out to become linear (by the way, if you restart the optimization the program generates a new set of internal coordinates that avoids that new linear angle, this is why restarting the geometry optimization works). Thus, people who work with large molecules may favor internal coordinates more than people who work with noncovalent clusters (like you) do. This may be the reason why they view Cartesian coordinates as a last resort but you do not fully agree with them.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-07-15T07:56:44.697" LastActivityDate="2023-07-15T07:56:44.697" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5037" PostTypeId="5" CreationDate="2021-05-23T04:59:56.117" Score="0" Body="&lt;p&gt;These are some of the main features:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Highly flexible classes for the representation of Element, Site, Molecule, Structure objects.&lt;/li&gt;&#xA;&lt;li&gt;Extensive input/output support, including support for &lt;a href=&quot;https://vasp.at/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP&lt;/a&gt;, &lt;a href=&quot;https://www.abinit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ABINIT&lt;/a&gt;, CIF, Gaussian, XYZ, and many other file formats.&lt;/li&gt;&#xA;&lt;li&gt;Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.&lt;/li&gt;&#xA;&lt;li&gt;Electronic structure analyses, such as density of states and band structure.&lt;/li&gt;&#xA;&lt;li&gt;Integration with the Materials Project REST API, Crystallography Open Database and other external data sources.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;View details here: &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pymatgen.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="85" LastEditorUserId="85" LastEditDate="2021-05-24T13:10:10.167" LastActivityDate="2021-05-24T13:10:10.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5038" PostTypeId="4" CreationDate="2021-05-23T04:59:56.117" Score="0" Body="Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis." OwnerUserId="85" LastEditorUserId="85" LastEditDate="2021-05-24T13:09:49.747" LastActivityDate="2021-05-24T13:09:49.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5039" PostTypeId="2" ParentId="5018" CreationDate="2021-05-23T17:22:08.127" Score="10" Body="&lt;h2&gt;To invest in new hardware, just to have it crippled by Intel MKL afterwards.&lt;/h2&gt;&#xA;&lt;p&gt;This was object of &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1103/243&quot;&gt;a question&lt;/a&gt; I asked here previously.&lt;/p&gt;&#xA;&lt;p&gt;In matter modeling, it's usual for people to compile software themselves, instead of relying in precompiled binaries, so it can be tuned to the particular processor model in their machine, for example, taking advantage of more recent instruction set vector extensions like &lt;a href=&quot;https://en.wikipedia.org/wiki/Advanced_Vector_Extensions&quot; rel=&quot;noreferrer&quot;&gt;AVX&lt;/a&gt; or &lt;a href=&quot;https://en.wikipedia.org/wiki/XOP_instruction_set&quot; rel=&quot;noreferrer&quot;&gt;XOP&lt;/a&gt; to speed up calculations. By contrast, to ensure it can be run in just about every machine found in the wild, precompiled binaries rely on ancient &lt;a href=&quot;https://en.wikipedia.org/wiki/Streaming_SIMD_Extensions&quot; rel=&quot;noreferrer&quot;&gt;SSE&lt;/a&gt; extensions, for example, thus not taking advantage of the full potential of new CPU models.&lt;/p&gt;&#xA;&lt;p&gt;The Intel compilers are quite popular in the field of matter modeling, and numeric computing in general. Said that, it comes with the downside of &lt;strong&gt;sabotaging the performance&lt;/strong&gt; of machines equiped with hardware of competitors, by unreasonably refusing to use the new extensions, as explained in &lt;a href=&quot;https://en.wikipedia.org/wiki/Math_Kernel_Library&quot; rel=&quot;noreferrer&quot;&gt;this wikipedia entry&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;MKL and other programs generated by the Intel C++ Compiler and the&#xA;Intel DPC++ Compiler improve performance with a technique called&#xA;function multi-versioning: a function is compiled or written for many&#xA;of the x86 instruction set extensions, and at run-time a &amp;quot;master&#xA;function&amp;quot; uses the CPUID instruction to select a version most&#xA;appropriate for the current CPU. However, as long as the master&#xA;function detects a non-Intel CPU, it almost always chooses the most&#xA;basic (and slowest) function to use, regardless of what instruction&#xA;sets the CPU claims to support. This has netted the system a nickname&#xA;of &amp;quot;cripple AMD&amp;quot; routine since 2009. As of 2020, Intel's MKL, which&#xA;remains the numeric library installed by default along with many&#xA;pre-compiled mathematical applications on Windows (such as NumPy,&#xA;SymPy). Although relying on the MKL, MATLAB implemented a workaround&#xA;starting with Release 2020a which ensures full support for AVX2 by the&#xA;MKL also for non Intel (AMD) CPUs&lt;/p&gt;&#xA;&lt;p&gt;In older versions, setting the undocumented environment variable&#xA;MKL_DEBUG_CPU_TYPE=5 could be used to override the vendor string&#xA;dependent codepath choice and activate supported instructions up to&#xA;AVX2 on AMD processor based systems resulting in equal or even better&#xA;performance when compared to Intel CPUs. Since at least Update 1 2020,&#xA;the environment variable does not work anymore.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think the effects of this sabotage problem tends to get worse, because, as pointed by @GregorMichalicek comment to @uLoop answer, many people in the high performance and scientific computing community are switching to AMD, given the strides they made with the &lt;a href=&quot;https://en.wikipedia.org/wiki/Zen_(microarchitecture)&quot; rel=&quot;noreferrer&quot;&gt;Zen architecture&lt;/a&gt;, while Intel faces issues with their manufacturing process. But perhaps not everybody is aware of this problem, to be able to switch their compiler and linear algebra libraries accordingly, toward alternatives not biased against any hardware, specially in small research teams with no dedicated IT staff. As examples of open source linear algebra libraries, we have &lt;a href=&quot;https://en.wikipedia.org/wiki/Automatically_Tuned_Linear_Algebra_Software&quot; rel=&quot;noreferrer&quot;&gt;ATLAS&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/OpenBLAS&quot; rel=&quot;noreferrer&quot;&gt;OpenBLAS&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/BLIS_(software)&quot; rel=&quot;noreferrer&quot;&gt;BLIS&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2021-05-23T17:29:09.680" LastActivityDate="2021-05-23T17:29:09.680" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5040" PostTypeId="1" CreationDate="2021-05-23T19:36:14.170" Score="13" ViewCount="891" Body="&lt;p&gt;I would like to run some benchmark of different DFT functionals.&#xA;The most time consuming part is obviously the generation of the input files.&#xA;I'm not a programmer, but I think this could be done by writing a generic input file with geometry and parameters except for the dft functional, then another text file with a list of the functionals one wants to test. Then I think a script could generate every single input file, maybe appending to it the name of the functional.&#xA;Hope you have some scripts to share or other ideas to solve my problem.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2021-05-26T09:37:33.663" Title="Script to generate input files for benchmark purpose" Tags="|density-functional-theory|programming|" AnswerCount="3" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5041" PostTypeId="2" ParentId="5040" CreationDate="2021-05-24T01:09:11.130" Score="12" Body="&lt;p&gt;Consider the MOLPRO input file below &lt;code&gt;template.inp&lt;/code&gt;, obtained from &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/3794&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, which was used for &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3801/5&quot;&gt;a previous MMSE answer about the energy of a zinc atom&lt;/a&gt;, except now we're using DFT and I have just entered the word &lt;code&gt;functional&lt;/code&gt; instead of the actual functional being used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ***,Zn&#xA;memory 5880, M&#xA;geometry={Zn}&#xA;basis = cc-pVDZ&#xA;wf,charge=0&#xA;{df-rks,functional}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now consider the file named &lt;code&gt;batch_script.x&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sed s/functional/B3LYP/ B3LYP.inp;&#xA;sed s/functional/PBE/   PBE.inp;&#xA;sed s/functional/HSE06/ HSE06.inp;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you run the following commands in the folder containing &lt;code&gt;template.inp&lt;/code&gt; and &lt;code&gt;batch_script.x&lt;/code&gt; (the first is to make the script file executable, and the second is to run the script):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;chmod +x batch_script.x&#xA;./batch_script.x&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;your folder will contain the following three input files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;B3LYP.inp&#xA;PBE.inp&#xA;HSE06.inp&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which look exactly like the template input file shown in the beginning of this answer, but with &lt;code&gt;functional&lt;/code&gt; replaced by &lt;code&gt;B3LYP&lt;/code&gt;, &lt;code&gt;PBE&lt;/code&gt; and &lt;code&gt;HSE06&lt;/code&gt; respectively.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Explanation of the commands in the script file:&lt;/strong&gt;&lt;br&gt;&lt;/p&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;sed s/functional/B3LYP/ B3LYP.inp&lt;/code&gt; runs the program &lt;a href=&quot;https://en.wikipedia.org/wiki/Sed&quot; rel=&quot;noreferrer&quot;&gt;sed&lt;/a&gt; on &lt;code&gt;B3LYP.inp&lt;/code&gt;:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;s/functional/B3LYP/&lt;/code&gt; means &lt;em&gt;&lt;strong&gt;s&lt;/strong&gt;&lt;/em&gt;ubstitute &lt;code&gt;functional&lt;/code&gt; with &lt;code&gt;B3LYP&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;I've made the above files available on GitHub:&lt;/strong&gt; They are &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/5040&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; in the folder called &lt;code&gt;sed&lt;/code&gt;. You'll find &lt;code&gt;template.inp&lt;/code&gt;, &lt;code&gt;batch_script.x&lt;/code&gt; and the three output files that get produced when you run the &lt;code&gt;.x&lt;/code&gt; script. There's also a folder called &lt;code&gt;MATLAB&lt;/code&gt; containing the skeleton of an alternative solution I wrote.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-05-24T01:19:31.813" LastActivityDate="2021-05-24T01:19:31.813" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5042" PostTypeId="2" ParentId="5021" CreationDate="2021-05-24T11:13:50.743" Score="11" Body="&lt;p&gt;I recently had the same question. After emailing Gaussian support I was informed that the units are indeed &lt;span class=&quot;math-container&quot;&gt;$\sqrt{\text{km}/\text{mol}}$&lt;/span&gt;. From their reply I also believe that the derivatives are calculated with respect to the 3N-6 vibrational modes obtained through the application of the Sayvetz conditions as detailed in their &lt;a href=&quot;https://gaussian.com/wp-content/uploads/dl/vib.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;whitepaper&lt;/a&gt; (Paragraph after Eqn. 11).&lt;/p&gt;&#xA;&lt;p&gt;To understand why Gaussian uses these &amp;quot;odd&amp;quot; units, and how to get away from them, it's useful to look at the definition of the integrated absorption coefficient for the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th absorption band (peak) which corresponds to the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th vibrational mode&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$A_i = \frac{1}{nl}\int_{\text{band}}\ln\frac{I_0}{I}\text{d}\tilde{\nu} \ \ \ \ \ \ \ \text{[m mol}^{-1}] \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which can be obtained directly from an experimental spectrum, and where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the concentration &lt;span class=&quot;math-container&quot;&gt;$[\text{mol m}^{-3}]$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; the path length &lt;span class=&quot;math-container&quot;&gt;$[\text{m}]$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; the transmitted intensity, &lt;span class=&quot;math-container&quot;&gt;$I_0$&lt;/span&gt; the incident intensity, and &lt;span class=&quot;math-container&quot;&gt;$\tilde{\nu}$&lt;/span&gt; wavenumber &lt;span class=&quot;math-container&quot;&gt;$[\text{m}^{-1}]$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This can be calculated theoretically as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$A_i = \frac{N_\mathrm{A}d_i}{12\epsilon_0 c^2 }\left|\frac{\partial\mathbf{\mu}}{\partial Q_i}\right|_0^2 \cdot \text{kg}(\text{u}) \cdot \text{D}^{2}\text{(C}^{2}\text{ Å}^{2}) \ \ \ \ \ \ \ \text{[m mol}^{-1}]\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$N_\mathrm{A}$&lt;/span&gt; is Avogradro's constant &lt;span class=&quot;math-container&quot;&gt;$[\text{mol}^{-1}]$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d_i$&lt;/span&gt; is the degeneracy of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th mode, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_0$&lt;/span&gt; is the permittivity of free space &lt;span class=&quot;math-container&quot;&gt;$[\text{F m}^{-1}]$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; is the speed of light &lt;span class=&quot;math-container&quot;&gt;$[\text{m s}^{-1}]$&lt;/span&gt;, while the &amp;quot;derivative term&amp;quot; contains a vector of the derivatives of the electric dipole with respect to the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; components of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th (mass-weighted) normal mode coordinate (evaluated at the equilibrium geometry) &lt;span class=&quot;math-container&quot;&gt;$[\text{D Å}^{-1}\text{u}^{-1/2}]$&lt;/span&gt;. I've included the final two terms as they explicitly detail the conversion factors required to arrive at the final units of &lt;span class=&quot;math-container&quot;&gt;$[\text{m mol}^{-1}]$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\text{kg}(\text{u}) = (1.661\times10^{-27})^{-1} \text{u kg}^{-1}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\text{D}^{2}\text{(C}^{2}\text{ Å}^{2}) = (3.336\times10^{-20})^{2} \text{   C}^{2} Å^{2} \text{ D}^{-2} \tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Evaluating the purely constant terms and conversion factors (precision truncated for brevity):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{N_\mathrm{A}}{12\epsilon_0c^2} \cdot \text{kg}(\text{u}) \cdot \text{D}^{2}\text{(C}^{2}\text{ Å}^{2}) \tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\!\!\!\!\!\! = \frac{6.022\times10^{23}[\text{mol}^{-1}] \times (1.661\times10^{-27})^{-1} [\text{u kg}^{-1}] \times (3.336\times10^{-20})^{2} [\text{   C}^{2} Å^{2} \text{ D}^{-2}]}{12\times8.854\times10^{-12} [\text{F m}^{-1}]\times (2.998\times10^8 [\text{m s}^{-1}])^2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\!\!\!\!\!\!\!\!\!\!\!\!= 42.2561 \text{ km mol}^{-1} \text{u } Å^{2} \text{ D}^{-2} \tag{7}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Gaussian &lt;a href=&quot;https://gaussian.com/constants/&quot; rel=&quot;nofollow noreferrer&quot;&gt;help pages&lt;/a&gt; give this exact same conversion factor, which (I believe) means that the dipole derivatives reported by Gaussian include the constant terms. To get the true derivatives in &lt;span class=&quot;math-container&quot;&gt;$[\text{D Å}^{-1}\text{u}^{-1/2}]$&lt;/span&gt;, you need to divide the reported derivatives in &lt;span class=&quot;math-container&quot;&gt;$[\text{km}^{1/2}\text{ mol}^{-1/2}]$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\sqrt{42.2561} \text{ km}^{1/2}\text{ mol}^{-1/2} \text{u }^{1/2} Å \text{ D}^{-1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This then means that the &lt;code&gt;Intensity&lt;/code&gt; values printed by Gaussian &lt;span class=&quot;math-container&quot;&gt;$[\text{km mol}^{-1}]$&lt;/span&gt; make a bit more sense, they're the sum of the squares of the dipole derivatives &lt;span class=&quot;math-container&quot;&gt;$[\text{km}^{1/2} \text{ mol}^{-1/2}]$&lt;/span&gt; along &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Many textbooks and articles will state the &lt;span class=&quot;math-container&quot;&gt;$42.2561 \text{ km mol}^{-1} \text{u } Å^{2} \text{ D}^{-2}$&lt;/span&gt; factor verbatim, and will often exclude the relevant conversion factors (even in explicit numerical evaluations), so be warned if you venture into the literature! As an example see Bernath's Spectra of Atoms and Molecules (3rd Ed.) Eqn. 7.246.&lt;/p&gt;&#xA;&lt;p&gt;The above equations will need to be reworked if Beers Law is applied using the common logarithm rather than the natural logarithm, this amounts to a &lt;span class=&quot;math-container&quot;&gt;$1/\ln(10)$&lt;/span&gt; term in the theoretical definition of &lt;span class=&quot;math-container&quot;&gt;$A_i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As has been said, you can get the derivatives without having to include that specific &lt;code&gt;iop&lt;/code&gt; command, by looking in the formatted checkpoint (&lt;code&gt;.fchk&lt;/code&gt;) file which can be obtained by running Gaussian's &lt;code&gt;formchk&lt;/code&gt; utility on the checkpoint (&lt;code&gt;.chk&lt;/code&gt;) file. However, these numbers don't match those in the &lt;code&gt;.log&lt;/code&gt; file, as they are the derivatives with respect to single atom displacements along the x, y, and z axes. To obtain the derivatives with respect to displacements along the normal mode vectors, you first must generate the matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{L}_{\text{CART}}$&lt;/span&gt;  detailed in the whitepaper - these are the displacement vectors printed by Gaussian (though in the &lt;code&gt;.log&lt;/code&gt; file they are scaled by the square root of the reduced mass and so this scaling must be undone). Then for each mode, multiply each element of the displacement vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{L}_{\text{CART}}$&lt;/span&gt; (corresponding to the motion of a single atom in x, y, or z in a given mode) by the the associated per-atom dipole derivative vector. Finally sum up all of the contributions to the derivative from each atom in each direction for a given mode and multiply by 31.2231 to convert from &lt;span class=&quot;math-container&quot;&gt;$[\text{e u}^{1/2}]$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$[\text{ km}^{1/2}\text{ mol}^{-1/2}]$&lt;/span&gt; and obtain the same values given by the IOp command.&lt;/p&gt;&#xA;" OwnerUserId="3626" LastEditorUserId="3626" LastEditDate="2021-06-21T10:53:10.547" LastActivityDate="2021-06-21T10:53:10.547" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5043" PostTypeId="2" ParentId="5040" CreationDate="2021-05-24T12:43:05.433" Score="12" Body="&lt;p&gt;This is an alternative approach with Python scripting. For bash scripting, @NikeDattani has already posted an &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5041/1380&quot;&gt;excellent answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's say you are trying to run the input files with GAMESS. Start with a template file that may look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!  Methane with B3LYP/6-31G(d)&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=N31 NGAUSS=6 NDFUNC=1 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=ENERGY DFTTYP=B3LYP $&lt;/span&gt;END&#xA;&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;C     6.0    -5.29801     1.38743     0.00000&#xA;H     1.0    -4.22801     1.38743     0.00000&#xA;H     1.0    -5.65468     2.34391     0.32068&#xA;H     1.0    -5.65468     0.63147     0.66800&#xA;H     1.0    -5.65468     1.18690    -0.98867&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now save the template file as template.inp.&lt;/p&gt;&#xA;&lt;p&gt;This Python script will read the template file and replace &amp;quot;B3LYP&amp;quot; with names of other functionals and write new input files with the name of the functional appended.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import os&#xA;import sys&#xA;&#xA;# list of density functionals&#xA;dft_list = [&amp;quot;wB97X-D&amp;quot;, &amp;quot;M06-2X&amp;quot;, &amp;quot;MN15&amp;quot;, &amp;quot;REVM11&amp;quot;,&amp;quot;TPSS&amp;quot;]&#xA;&#xA;# optionally, read this in from a text file where the functionals&#xA;# are separated by space&#xA;&#xA;#with open(&amp;quot;dft_list.txt&amp;quot;, &amp;quot;r&amp;quot;) as dft_file_hnd:&#xA;#    dft_list=dft_file_hnd.read().replace(&amp;quot;\n&amp;quot;,&amp;quot;&amp;quot;).replace(&amp;quot;\r&amp;quot;,&amp;quot;&amp;quot;).split(&amp;quot; &amp;quot;)&#xA;&#xA;# Iterate through dft_list&#xA;if os.path.isfile(&amp;quot;template.inp&amp;quot;)==False:&#xA;    print(&amp;quot;Unable to find template file template.inp&amp;quot;)&#xA;    print(&amp;quot;Template file template.inp is required!&amp;quot;)&#xA;    print(&amp;quot;Exiting...&amp;quot;)&#xA;    sys.exit()&#xA;for functional in dft_list:&#xA;    # write the new input files as input_M06-2X.inp etc.&#xA;    # Warning! the name of the functional must not contain unusual&#xA;    # characters which cannot be used as file names&#xA;    new_file_name = &amp;quot;input_&amp;quot; + functional + &amp;quot;.inp&amp;quot;&#xA;    if os.path.isfile(new_file_name):&#xA;        print(&amp;quot;File:&amp;quot;,new_file_name,&amp;quot; already exists!&amp;quot;)&#xA;        print(&amp;quot;Please delete it before proceeding&amp;quot;)&#xA;        print(&amp;quot;Exiting...&amp;quot;)&#xA;        break&#xA;    new_file_hnd = open(new_file_name,&amp;quot;a&amp;quot;)&#xA;    with open(&amp;quot;template.inp&amp;quot;, &amp;quot;r&amp;quot;) as temp_file_hnd:&#xA;        for line in temp_file_hnd:&#xA;            # search and replace B3LYP with new functional&#xA;            line = line.replace(&amp;quot;B3LYP&amp;quot;,functional)&#xA;            # write line into new input file&#xA;            new_file_hnd.write(line)&#xA;    new_file_hnd.close()&#xA;    # run the input files with a QM program&#xA;    #output files are named output_M06-2X.log etc.&#xA;    print(&amp;quot;&amp;quot;)&#xA;    print(&amp;quot;Written &amp;quot;,new_file_name)&#xA;    out_file_name = &amp;quot;output_&amp;quot; + functional + &amp;quot;.log&amp;quot;&#xA;    print(&amp;quot;Running input file:&amp;quot;,new_file_name)&#xA;    command_string=&amp;quot;rungms &amp;quot; + new_file_name + &amp;quot; 00 1 &amp;gt;&amp;quot; + out_file_name&#xA;    os.system(command_string)&#xA;    # This runs input files with gamess.00.exe with 1 processes (uses rungms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that you can also choose to run the input files inside the same script. There are some lines for that at the bottom. The &lt;code&gt;command_string&lt;/code&gt; has to be changed depending on your QM software and OS. The QM software is invoked with &lt;code&gt;os.system()&lt;/code&gt; of python which calls the command line terminal of that OS (shell for Linux, cmd for Windows). The &lt;code&gt;os.system()&lt;/code&gt; pauses the Python script execution until the terminal returns.&lt;/p&gt;&#xA;&lt;p&gt;So, if the QM program or command you are running doesn't return until the calculation finishes then the script will run the files sequentially, as the &lt;code&gt;os.system()&lt;/code&gt; is inside the &lt;code&gt;for&lt;/code&gt; loop. However, if you are running a job submit script in an HPC or something similar to that, then the program will not pause to allow the calculation to finish, it will submit all the jobs in quick succession. Another issue with &lt;code&gt;os.system()&lt;/code&gt; is that you would have to escape backslashes for path names if you are using it on Windows (because it is based on C &lt;code&gt;system()&lt;/code&gt; IIRC). A better option might then be to use &lt;code&gt;os.subprocess.run()&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also note that the names of the functionals might be slightly different in different programs. For example in Gaussian &lt;span class=&quot;math-container&quot;&gt;$\text{M06-2X}$&lt;/span&gt; is represented as &lt;code&gt;m062x&lt;/code&gt; or &lt;code&gt;M062X&lt;/code&gt;, whereas in GAMESS it is represented as &lt;code&gt;m06-2x&lt;/code&gt; or &lt;code&gt;M06-2X&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The advantages of using Python is that it is OS-agnostic (for the most part), so it can be run on all systems. (Bash is not natively available on Windows). Another benefit is that Python is more flexible than bash, so if you need some further modification to the input files, you can do that easily. The disadvantage is obviously that you have to have Python installed.&lt;/p&gt;&#xA;&lt;p&gt;The python script, template file and sample input and output files can be found here: &lt;a href=&quot;https://github.com/ShoubhikRaj/molecular-modelling/tree/main/matter-modelling/dft-benchmark&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/ShoubhikRaj/molecular-modelling/tree/main/matter-modelling/dft-benchmark&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-26T09:37:33.663" LastActivityDate="2021-05-26T09:37:33.663" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5044" PostTypeId="2" ParentId="5040" CreationDate="2021-05-24T19:43:53.857" Score="8" Body="&lt;p&gt;To take @Shoubhik's suggestion of Python one step further, you could also consider setting up your benchmark using &lt;a href=&quot;https://snakemake.readthedocs.io/en/stable/&quot; rel=&quot;noreferrer&quot;&gt;Snakemake&lt;/a&gt;, a Python program/extension designed for building rule-based data analysis workflows. An example of this approach is the ACCDB (A Collection of Chemistry DataBases) project&lt;span class=&quot;math-container&quot;&gt;$^{1,2}$&lt;/span&gt;, which in addition to collecting geometries from a number of databases provides a simple interface to rerun these calculations with different basis sets or functionals.&lt;/p&gt;&#xA;&lt;p&gt;The disadvantage of this approach is the need to learn how to implement a snakemake procedure, which relies on knowing some Python plus additional Snakemake specific syntax. The advantage is that it provides a convenient way to quickly extend your benchmark set to include new molecules/functionals/basis sets/etc. It also can be used to control the job submission and data collection processes, entirely automating the creation of the benchmark data.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\qquad\qquad\qquad\qquad\qquad$&lt;/span&gt;&lt;a href=&quot;https://i.stack.imgur.com/jonEt.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jonEt.png&quot; alt=&quot;Pictorial representation of snakemake workflow&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From personal experience, with a decent Python background, it wasn't terribly difficult to make my own snakemake routine.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/peverati/ACCDB&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/peverati/ACCDB&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Morgante, P., Peverati, R.. J. Comput. Chem. 2019, 40, 839– 848. DOI: 10.1002/jcc.25761 (or &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/1809/1809.01707.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/ftp/arxiv/papers/1809/1809.01707.pdf&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-05-24T19:43:53.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5045" PostTypeId="1" AcceptedAnswerId="5046" CreationDate="2021-05-25T10:00:44.940" Score="12" ViewCount="1120" Body="&lt;p&gt;I was trying to compute some electronic properties for Pd using SIESTA and VASP for some computer practicals in my university, specially focused on band structure and density of states (DOS) using LDA and GGA functionals. First of all, we run convergence tests: k-point grid and energy cut-off. After that, the relaxation of the cell and the band structure and DOS were calculated. One of my professors said that it was necessary to increase the number of k-points to run the DOS calculation.&lt;/p&gt;&#xA;&lt;p&gt;Is there a reason for that? I have been reading on the internet but it seems to be a trick to obtain more accurate results.&lt;/p&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="3382" LastEditDate="2021-05-25T13:59:35.040" LastActivityDate="2021-05-25T17:19:49.760" Title="Increasing k-point grid to take DOS calculation" Tags="|density-functional-theory|vasp|electronic-structure|solid-state-physics|siesta|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5046" PostTypeId="2" ParentId="5045" CreationDate="2021-05-25T10:46:35.130" Score="12" Body="&lt;p&gt;This depends a lot on how the DOS is calculated. I don't know the options one has for this when using VASP or SIESTA, but I am aware of different approaches. The central problem is that you don't know which state at a certain k point is &amp;quot;connected&amp;quot; to some other state at another k point. When calculating a DOS you have to integrate over the Brillouin zone and therefore you have to somehow interpolate between the actually calculated k points. The eigenenergies of the states at the different k points may differ by more than what you might find reasonable for the energy-resolution of your DOS.&lt;/p&gt;&#xA;&lt;p&gt;Two approaches:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;You could say that each state contributes to the &amp;quot;energy bin&amp;quot; it is directly related to and smoothen the DOS afterwards to get rid of the artifacts due to this finite sampling. In this case you somehow have to define a parameter controlling the smoothening and this has to be related to the fineness of the sampling in the Brillouin zone. Unfortunately the relationship between the k-point sampling and the smoothing is also not direct: The band dispersion may be very different for different bands and for different materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You could assume a certain correspondence between the states at different k points and interpolate between the states in k space. This is the tetrahedron method. Unfortunately a naive approach may assume a wrong correspondence. For example if you just say that the i-th eigenvalue at some k point corresponds to the i-th eigenvalue at another k point, you ignore the possibility of band crossings. Your interpolation scheme would imply avoided crossings. To make this issue less severe you would also smoothen the DOS on the energy grid. And, of course, a finer k-point sampling would also reduce the significance of this issue.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In the end creating a nice DOS is a matter of different ingredients:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The Brillouin zone integration scheme.&lt;/li&gt;&#xA;&lt;li&gt;The k-point sampling of the Brillouin zone.&lt;/li&gt;&#xA;&lt;li&gt;The fineness of the energy grid.&lt;/li&gt;&#xA;&lt;li&gt;The smoothing of the DOS.&lt;/li&gt;&#xA;&lt;li&gt;The dispersion of the bands.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A finer k-point sampling allows the generation of a higher-quality DOS. But you also have to control the other parameters.&lt;/p&gt;&#xA;&lt;p&gt;I also described this landscape of different parameters in the documentation of the &lt;a href=&quot;https://www.flapw.de/MaX-5.1/documentation/dos/&quot; rel=&quot;noreferrer&quot;&gt;Fleur code&lt;/a&gt;.  You can find there a few example plots demonstrating the effect of changing certain aspects of the DOS generation. Of course, the parametrization may be slightly different for other codes, but the general problem should be similar.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2021-05-25T17:19:49.760" LastActivityDate="2021-05-25T17:19:49.760" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5048" PostTypeId="1" AcceptedAnswerId="5049" CreationDate="2021-05-25T19:50:20.407" Score="17" ViewCount="468" Body="&lt;p&gt;While reviewing some DFT literature, I have come across a few papers utilizing the LAPW (Linearized&#xA;Augmented Plane Wave) method, but I am interested in understanding why exactly one would use these methods as opposed to pseudopotential based methods.  It may be bias in the literature I have read, but it seems these methods are being used less in recent years or are going under a different name.&lt;/p&gt;&#xA;&lt;p&gt;My fundamental question can be posed as such,&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the LAPW method's advantages/disadvantages over psuedopotential based methods implemented in codes such as VASP?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="7" LastEditDate="2021-07-30T20:18:46.287" LastActivityDate="2021-07-30T20:18:46.287" Title="Linearized Augmented Plane Wave Method vs. Pseudopotential Methods" Tags="|density-functional-theory|reference-request|pseudopotentials|plane-waves|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5049" PostTypeId="2" ParentId="5048" CreationDate="2021-05-26T12:34:48.673" Score="20" Body="&lt;p&gt;Disclaimer: I am a developer of the &lt;a href=&quot;https://www.flapw.de&quot; rel=&quot;noreferrer&quot;&gt;Fleur code&lt;/a&gt;. I hope that I don't put too much bias into this answer. At least I try to not do that...&lt;/p&gt;&#xA;&lt;p&gt;When you want to solve the Kohn-Sham equations you have the problem that the potential has singularities at the atomic nuclei. There are different ways to deal with this. On the one hand you can make the pseudopotential approximation to get rid of the singularities and make descriptions of the Kohn-Sham states with simple basis sets possible. On the other hand you can make use of a sophisticated basis set to get a representation on the basis of a potential including the singularities.&lt;/p&gt;&#xA;&lt;p&gt;Codes like VASP or Quantum Espresso use the pseudopotential approach in combination with plane waves and projector augmented waves. The advantage of this approach is its simplicity in terms of parameters the user has to control and also in terms of development effort (with plane waves many expressions in the code are not too complex). The disadvantage is that the usage of pseudopotentials is an approximation, though a good one. Nevertheless it is difficult for the user to judge whether a result is affected or distorted by this approximation.&lt;/p&gt;&#xA;&lt;p&gt;The all-electron full-potential linearized augmented-plane-wave method (FLAPW) on the other hand uses a very sophisticated basis set. It is used (with different flavors) in codes like Wien2k, Fleur, Exciting, Elk, HiLAPW, and a few more. Like plane waves the LAPW basis is systematically convergable. With this basis and the all-electron description you have a tool to obtain the DFT answer to a given problem and with a given XC functional in a controlled way with very high precision. You can produce reference results against which you can benchmark the precision of other approaches. The downside is that the LAPW basis is controlled by more than a single parameter like what you have in plane-wave basis sets. The complexity of the basis is a high entry barrier for new users of such codes and is also connected to more effort that has to be put into calculations and the development of the code.&lt;/p&gt;&#xA;&lt;p&gt;The use cases of FLAPW codes (and other DFT codes) of course depend on their individual feature set (which is probably smaller if you have to put more effort into the development of new features). In general the strengths are wherever the results depend on details of the description, for example if tiny energy differences are involved. The all-electron description also allows for a rather direct evaluation of quantities that depend on the core electrons.&lt;/p&gt;&#xA;&lt;p&gt;Your observation that FLAPW codes are used less frequently I can only answer with my subjective observation for the Fleur code. Within the last years we worked a lot on the user friendliness of the code, the user documentation, and the stability. This is an ongoing process but we already see rising interest in the code. It may very well be that the popularity of the different codes also depends a lot on how much effort the development teams can put into such aspects. I have the impression that since a few years the awareness of the need for such development efforts grows. Not only for the Fleur code but for all DFT codes and scientific software in general. I think DFT codes with very large user communities started working on such things earlier.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2021-05-26T12:34:48.673" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5050" PostTypeId="1" CreationDate="2021-05-27T07:25:39.623" Score="6" ViewCount="130" Body="&lt;p&gt;I would like to calculate the elastic constants of beta PHB. From &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.macromol.9b00225&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. I know that it has P3221 space group. The beta PHB has upward and downward chains, which exist at one lattice site with 50% occupancy, therefore, it is really difficult to do the optimazition in VASP. The structure destroyed with using all the &lt;code&gt;ISIF&lt;/code&gt; tags. Has anyone run into the same problem? I'm not sure I did everything right, because I am not an expert in the polymer crystallography.&lt;/p&gt;&#xA;&lt;p&gt;More or less better results I obtained when I used &lt;code&gt;ISIF=7&lt;/code&gt;. My structure was destroyed at the third step. The initial 2 steps gave me the reasonable geometry in &lt;code&gt;CONTCAR&lt;/code&gt;. Please find below my &lt;code&gt;INCAR&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PREC = Accurate&#xA;ENCUT = 520&#xA;EDIFF = 1e-6 &#xA;EDIFFG = -0.02&#xA;IBRION = 2 &#xA;ISIF = 7 &#xA;ISYM = 2 &#xA;NSW = 50 &#xA;ISMEAR = 0&#xA;SIGMA = 0.1&#xA;POTIM = 0.1&#xA;PSTRESS = 0.001&#xA;NPAR = 4 &#xA;NSIM = 4 &#xA;ALGO = Normal&#xA;IALGO = 48&#xA;ISTART = 0 &#xA;LPLANE = .TRUE.&#xA;LCHARG = .FALSE.&#xA;LWAVE = .FALSE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and &lt;code&gt;POSCAR&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;New structure&#xA;1.0&#xA;        9.2200002670         0.0000000000         0.0000000000&#xA;       -4.6100001335         7.9847544541         0.0000000000&#xA;        0.0000000000         0.0000000000         4.6599998474&#xA;    C    O    H&#xA;   24   12   36&#xA;Direct&#xA;     0.459999949         0.990000010         0.669999897&#xA;     0.010000000         0.469999939         0.336666554&#xA;     0.530000031         0.540000081         0.003333231&#xA;     0.990000010         0.459999949         0.330000103&#xA;     0.469999939         0.010000000         0.663333416&#xA;     0.540000081         0.530000031         0.996666789&#xA;     0.349999934         0.970000029         0.919999897&#xA;     0.029999999         0.379999936         0.586666584&#xA;     0.620000064         0.650000095         0.253333241&#xA;     0.970000029         0.349999934         0.080000103&#xA;     0.379999936         0.029999999         0.413333446&#xA;     0.650000095         0.620000064         0.746666789&#xA;     0.349999934         0.930000007         0.409999967&#xA;     0.070000000         0.419999927         0.076666631&#xA;     0.580000043         0.650000095         0.743333280&#xA;     0.930000007         0.349999934         0.590000033&#xA;     0.419999927         0.070000000         0.923333347&#xA;     0.650000095         0.580000043         0.256666690&#xA;     0.279999942         0.089999989         0.899999857&#xA;     0.910000026         0.189999953         0.566666543&#xA;     0.810000062         0.720000029         0.233333185&#xA;     0.089999989         0.279999942         0.100000143&#xA;     0.189999953         0.910000026         0.433333486&#xA;     0.720000029         0.810000062         0.766666830&#xA;     0.439999938         0.009999998         0.179999948&#xA;     0.990000010         0.429999948         0.846666634&#xA;     0.570000052         0.560000062         0.513333261&#xA;     0.009999998         0.439999938         0.820000052&#xA;     0.429999948         0.990000010         0.153333381&#xA;     0.560000062         0.570000052         0.486666709&#xA;     0.199999973         0.829999983         0.409999967&#xA;     0.170000002         0.369999975         0.076666631&#xA;     0.629999995         0.800000012         0.743333280&#xA;     0.829999983         0.199999973         0.590000033&#xA;     0.369999975         0.170000002         0.923333347&#xA;     0.800000012         0.629999995         0.256666690&#xA;     0.559999883         0.119999982         0.639999866&#xA;     0.879999995         0.439999908         0.306666523&#xA;     0.560000122         0.440000117         0.973333180&#xA;     0.119999982         0.559999883         0.360000134&#xA;     0.439999908         0.879999995         0.693333447&#xA;     0.440000117         0.560000122         0.026666800&#xA;     0.519999862         0.909999967         0.709999859&#xA;     0.090000004         0.609999895         0.376666516&#xA;     0.390000135         0.480000138         0.043333191&#xA;     0.909999967         0.519999862         0.290000141&#xA;     0.609999895         0.090000004         0.623333454&#xA;     0.480000138         0.390000135         0.956666827&#xA;     0.239999965         0.840000033         0.919999897&#xA;     0.159999996         0.399999976         0.586666584&#xA;     0.600000024         0.760000050         0.253333241&#xA;     0.840000033         0.239999965         0.080000103&#xA;     0.399999976         0.159999996         0.413333446&#xA;     0.760000050         0.600000024         0.746666789&#xA;     0.189999968         0.059999991         0.719999909&#xA;     0.939999998         0.129999980         0.386666566&#xA;     0.870000005         0.810000062         0.053333241&#xA;     0.059999991         0.189999968         0.280000091&#xA;     0.129999980         0.939999998         0.613333404&#xA;     0.810000062         0.870000005         0.946666777&#xA;     0.209999964         0.089999989         0.100000024&#xA;     0.910000026         0.119999975         0.766666710&#xA;     0.879999995         0.790000021         0.433333367&#xA;     0.089999989         0.209999964         0.899999976&#xA;     0.119999975         0.910000026         0.233333305&#xA;     0.790000021         0.879999995         0.566666663&#xA;     0.379999936         0.219999969         0.869999886&#xA;     0.780000031         0.159999967         0.536666572&#xA;     0.840000033         0.620000064         0.203333214&#xA;     0.219999969         0.379999936         0.130000114&#xA;     0.159999967         0.780000031         0.463333458&#xA;     0.620000064         0.840000033         0.796666801&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you in advance!&lt;/p&gt;&#xA;" OwnerUserId="3486" LastEditorUserId="3486" LastEditDate="2021-05-27T09:00:16.757" LastActivityDate="2021-05-27T09:00:16.757" Title="How to optimize the geometry of beta PHB in VASP?" Tags="|vasp|crystal-structure|geometry-optimization|polymers|elasticity|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-01T18:05:32.210" ContentLicense="CC BY-SA 4.0" />
  <row Id="5052" PostTypeId="1" CreationDate="2021-05-27T17:43:50.177" Score="16" ViewCount="459" Body="&lt;p&gt;Doing matter modeling generates vast amounts of data. We might most probably be working on different projects simultaneously. We definitely will have to revisit old data for revisions, post-processing, further studies, etc. Also, we might have to go through many failed calculations to reach the final results. It is always a good practice to keep all our data even after publication. However, its quite easy to lose track of our calculations (especially looking at old calculations) unless we keep them systematically.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I have been using Medea-VASP, a propriety software with a tool called JobServer which efficiently manage the calculations and data. Here is a screenshot:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7t1KT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7t1KT.png&quot; alt=&quot;Enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How should I handle a huge number of calculations (data) efficiently and systematically while using matter modeling code?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastEditorUserId="1118" LastEditDate="2021-05-29T12:50:48.593" LastActivityDate="2021-05-29T16:08:58.073" Title="How should I organize and keep track of a huge number of calculations systematically?" Tags="|software|software-recommendations|high-performance-computing|high-throughput|matter-modeling-specific-technology|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5053" PostTypeId="1" AcceptedAnswerId="5073" CreationDate="2021-05-27T18:50:45.593" Score="13" ViewCount="3282" Body="&lt;p&gt;I want to do a convergence test of Ni using a Python script in Pyiron. Can someone please suggest how to write a script to test energy and k-mesh convergence?&lt;/p&gt;&#xA;" OwnerUserId="2075" LastEditorUserId="5" LastEditDate="2021-05-30T22:04:03.823" LastActivityDate="2021-05-30T22:04:03.823" Title="Python script for convergence test" Tags="|python|convergence-test|pyiron|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5054" PostTypeId="2" ParentId="5053" CreationDate="2021-05-27T19:38:02.140" Score="14" Body="&lt;p&gt;Here is the simple bash script for testing kpoint energy convergence for VASP you can use same logic in python but you can also use this.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in `seq  1 1 5` # change the range needed&#xA;do&#xA;cat &amp;lt;&amp;lt;EOF &amp;gt;KPOINTS&#xA;MONK #header file&#xA;0&#xA;M&#xA;$i $i $i&#xA;0 0 0&#xA;EOF&#xA;mkdir $i&#xA;cp INCAR $i/&#xA;cp POSCAR $i/&#xA;cp POTCAR $i/&#xA;cp KPOINTS $i/&#xA;cd $i&#xA;vasp-5.4.4  # This is vasp run command add mpi if needed&#xA;# post process &#xA;E=`grep 'F' OSZICAR|tail -n 1 | awk '{ print $5}'`;                &#xA;echo $i $E &amp;gt;&amp;gt;../Result.txt&#xA;cd ..&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;keep POSCAR, POTCAR, INCAR and this script in same folder&lt;br /&gt;&#xA;Execute &lt;code&gt;bash script.sh&lt;/code&gt; check Result.txt for output&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-05-27T19:38:02.140" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5055" PostTypeId="5" CreationDate="2021-05-27T21:16:30.017" Score="0" Body="&lt;p&gt;Python-based program: &lt;a href=&quot;https://pyiron.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pyiron.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="-1" LastEditorUserId="5" LastEditDate="2021-07-29T21:54:55.910" LastActivityDate="2021-07-29T21:54:55.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5056" PostTypeId="4" CreationDate="2021-05-27T21:16:30.017" Score="0" Body="Pyiron is an integrated development environment (IDE) for computational material science" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-28T02:58:57.950" LastActivityDate="2021-05-28T02:58:57.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5057" PostTypeId="2" ParentId="5052" CreationDate="2021-05-28T08:19:25.423" Score="16" Body="&lt;p&gt;Several computational workflow managers try to address exactly this problem in materials modeling. Besides helping orchestrating complex simulation workflows, they keep track of all the simulations (and how they are related) in a database.&lt;/p&gt;&#xA;&lt;p&gt;The Materials Project team uses the &lt;a href=&quot;https://materialsproject.github.io/fireworks/&quot; rel=&quot;noreferrer&quot;&gt;Fireworks&lt;/a&gt; package.&#xA;The &lt;a href=&quot;https://atomate.org/&quot; rel=&quot;noreferrer&quot;&gt;atomate&lt;/a&gt; package provides a high-level interface for the most common tasks.&lt;/p&gt;&#xA;&lt;p&gt;Another widely used workflow manager is &lt;a href=&quot;https://www.aiida.net/&quot; rel=&quot;noreferrer&quot;&gt;AiiDA&lt;/a&gt;. AiiDA focuses on keeping track of the full provenance of your simulations. That is, it will allow you to created directed acyclical graphs that go from some input like a crystal structure in a database to some complex properties like thermoelectric coefficients. You can find some examples for these graphs in the &lt;a href=&quot;https://www.materialscloud.org/explore/2dstructures/details/e34bac20-4552-4f8c-bdbf-31bcec6b14a0?nodeType=NODE&quot; rel=&quot;noreferrer&quot;&gt;Materials Cloud&lt;/a&gt;. The power is that you can &lt;a href=&quot;https://aiida-tutorials.readthedocs.io/en/latest/pages/2020_Intro_Week/sections/data.html&quot; rel=&quot;noreferrer&quot;&gt;then write queries&lt;/a&gt; to find specific parts of the database, for example, all calculations with a specific functional, a bandgap &amp;gt; 3.2 eV, and that were performed in a certain time range.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://github.com/tilde-lab/awesome-materials-informatics#software-and-products&quot; rel=&quot;noreferrer&quot;&gt;awesome materials informatics list&lt;/a&gt; list some materials specific solutions, &lt;a href=&quot;https://github.com/common-workflow-language/common-workflow-language/wiki/Existing-Workflow-systems&quot; rel=&quot;noreferrer&quot;&gt;the wiki of the common workflow language&lt;/a&gt;  lists some more general solutions.&lt;/p&gt;&#xA;" OwnerUserId="3654" LastEditorUserId="3654" LastEditDate="2021-05-29T16:08:58.073" LastActivityDate="2021-05-29T16:08:58.073" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5058" PostTypeId="2" ParentId="5053" CreationDate="2021-05-28T08:29:46.327" Score="10" Body="&lt;p&gt;This is the script I wrote for convergence testing in Quantum ESPRESSO using Bash and Python.&lt;/p&gt;&#xA;&lt;p&gt;According to &lt;a href=&quot;https://compmatphys.epotentia.com/wp-content/uploads/2020/04/project_03b_convergence-testing_no-GUI.pdf&quot; rel=&quot;noreferrer&quot;&gt;Stefaan Cottenier&lt;/a&gt;, hydrostatic pressure on a unit cell is the property tested for convergence because it is quite sensitive to numerical precision. If this property is converged with respect to the k-mesh, many other less sensitive properties will be converged, too. Remember that you have to use the &lt;code&gt;tstress&lt;/code&gt; keyword in your QE input.&lt;/p&gt;&#xA;&lt;p&gt;The script generates a new QE input file with a new k-mesh when the convergence test fails. Run &lt;code&gt;conv-test.sh&lt;/code&gt; to begin the convergence test.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(1) The Bash code: &lt;code&gt;conv-test.sh&lt;/code&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;&#xA;# Generate a text file record.txt to be used for pressure bookkeeping&#xA;touch record.txt&#xA;&#xA;# Run the QE input and pass the iteration number to the python script&#xA;for i in {1..15}&#xA;do&#xA;    pw.x -input input-&lt;span class=&quot;math-container&quot;&gt;$i.in &amp;gt; output-$&lt;/span&gt;i.out&#xA;    echo $i | python3 conv-test.py&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;(2) Python code: &lt;code&gt;conv-test.py&lt;/code&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Open &amp;quot;record.txt&amp;quot;, read all pressures stored in it from previous runs, and write them to the &amp;quot;stress&amp;quot; list  &#xA;record = open(&amp;quot;record.txt&amp;quot;, &amp;quot;r+&amp;quot;)&#xA;stress = []&#xA;for line in record:&#xA;    stress.append(float(line.strip()))&#xA;record.close()&#xA;&#xA;# Read the iteration number for the current run from the Bash script&#xA;I = input(&amp;quot;Iteration number: &amp;quot;)&#xA;i = int(I)&#xA;&#xA;# Open the output file with that current iteration number, read the pressure from it, and append it the &amp;quot;stress&amp;quot; list&#xA;F1 = open(&amp;quot;output-%d.out&amp;quot; %i, &amp;quot;r+&amp;quot;)&#xA;for line in F1:&#xA;    a0 = line.strip()&#xA;    a1 = &amp;quot; &amp;quot;.join(a0.split())&#xA;    if a1.find(&amp;quot;total stress&amp;quot;) != -1:&#xA;        a2 = a1.replace(&amp;quot;total stress (Ry/bohr**3) (kbar) P= &amp;quot;, &amp;quot;&amp;quot;)&#xA;        stress.append(float(a2))&#xA;F1.close()&#xA;&#xA;# Add the value of pressure for this current iteration to &amp;quot;record.txt&amp;quot;&#xA;if len(stress) &amp;gt;= 1:&#xA;    record = open(&amp;quot;record.txt&amp;quot;, &amp;quot;a+&amp;quot;)&#xA;    record.write(str(stress[len(stress)-1])+&amp;quot;\n&amp;quot;)&#xA;    record.close()&#xA;&#xA;try:&#xA;    # If this is the first run and &amp;quot;record.txt&amp;quot; contains a single stress value, increment the k-mesh anyway.&#xA;    if len(stress) &amp;lt;= 1:&#xA;        F1 = open(&amp;quot;input-%d.in&amp;quot; %i, &amp;quot;r+&amp;quot;)&#xA;        NewContent = &amp;quot;&amp;quot;&#xA;        for line in F1:&#xA;            NewLine = line.replace(&amp;quot;%d %d %d&amp;quot; %(i, i, i), &amp;quot;%d %d %d&amp;quot; %(i+1, i+1, i+1))&#xA;            NewContent += NewLine + &amp;quot;\n&amp;quot;&#xA;        F1.close()&#xA;        F2 = open(&amp;quot;input-%d.in&amp;quot; %(i+1), &amp;quot;w+&amp;quot;)&#xA;        F2.write(NewContent)&#xA;        F2.close()&#xA;&#xA;    # If &amp;quot;record.txt&amp;quot; contains at least two values of stress, compare the last two values ans check if they are equal within the required tolerance.&#xA;    elif round(stress[len(stress)-1], 2) - round(stress[len(stress)-2], 2) &amp;lt;= 0.001:&#xA;        F1 = open(&amp;quot;input-%d.in&amp;quot; %i, &amp;quot;r+&amp;quot;)&#xA;        NewContent = &amp;quot;&amp;quot;&#xA;        for line in F1:&#xA;            NewLine = line.replace(&amp;quot;%d %d %d&amp;quot; %(i, i, i), &amp;quot;%d %d %d&amp;quot; %(i+1, i+1, i+1))&#xA;            NewContent += NewLine + &amp;quot;\n&amp;quot;&#xA;        F1.close()&#xA;        F2 = open(&amp;quot;input-%d.in&amp;quot; %(i+1), &amp;quot;w+&amp;quot;)&#xA;        F2.write(NewContent)&#xA;        F2.close()&#xA;    # If they are equal within the required tolerance, print &amp;quot;Convergence is achieved.&amp;quot;&#xA;    else:&#xA;        print(&amp;quot;Covergence is achieved.&amp;quot;)&#xA;    print(stress)&#xA;except:&#xA;    print(&amp;quot;Program is terminated.&amp;quot;)&#xA;    exit()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Word of caution:&lt;/strong&gt; So far, the script has the following drawbacks:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It only tests convergence for cubic k-meshes.&lt;/li&gt;&#xA;&lt;li&gt;It doesn't terminates properly when convergence is achieved.&lt;/li&gt;&#xA;&lt;li&gt;It is designed for static (i.e., &lt;code&gt;scf&lt;/code&gt;) calculations. With &lt;code&gt;vc-relax&lt;/code&gt; calculations, you will have multiple pressures in the output file and the script will pick the first value while the last value is the one that should be picked. In this case, the script must be modified.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The script is experimental, so all suggestions of enhancement are welcomed.&lt;/p&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2021-05-28T09:04:22.853" LastActivityDate="2021-05-28T09:04:22.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5059" PostTypeId="2" ParentId="467" CreationDate="2021-05-28T13:46:57.843" Score="15" Body="&lt;h1&gt;iRASPA&lt;/h1&gt;&#xA;&lt;p&gt;fast &amp;amp; beautiful visualization of porous materials (but not only)&lt;/p&gt;&#xA;&lt;p&gt;Features according to &lt;a href=&quot;https://iraspa.org/iraspa/&quot; rel=&quot;noreferrer&quot;&gt;https://iraspa.org/iraspa/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;structure creation and editing,&lt;/li&gt;&#xA;&lt;li&gt;creating high-quality pictures and movies,&lt;/li&gt;&#xA;&lt;li&gt;Ambient occlusion and high-dynamic range rendering,&lt;/li&gt;&#xA;&lt;li&gt;collage of structures, (transparent) adsorption surfaces, text-annotation,&lt;/li&gt;&#xA;&lt;li&gt;cell replicas and supercells, symmetry operations like space group and primitive cell detection,&lt;/li&gt;&#xA;&lt;li&gt;screening of structures using user-defined predicates,&lt;/li&gt;&#xA;&lt;li&gt;GPU-computation of void-fraction and surface areas in a matter of seconds.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XTkRO.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XTkRO.jpg&quot; alt=&quot;iRASPA of MIL-101 (rendering 14k atoms)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-05-28T13:46:57.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5060" PostTypeId="2" ParentId="414" CreationDate="2021-05-28T13:59:25.167" Score="6" Body="&lt;h1&gt;Psi4&lt;/h1&gt;&#xA;&lt;p&gt;Psi4 (&lt;a href=&quot;https://psicode.org/&quot; rel=&quot;noreferrer&quot;&gt;https://psicode.org/&lt;/a&gt;) is another open-source alternative (LGPL).&lt;/p&gt;&#xA;&lt;p&gt;I haven't used it myself but it &lt;a href=&quot;https://psicode.org/psi4manual/master/mcscf.html&quot; rel=&quot;noreferrer&quot;&gt;supports CASSCF&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-05-28T16:24:41.640" LastActivityDate="2021-05-28T16:24:41.640" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5062" PostTypeId="2" ParentId="5029" CreationDate="2021-05-28T16:59:04.810" Score="6" Body="&lt;p&gt;As you mention, your graphene hamiltonian operates on &lt;em&gt;sites&lt;/em&gt;, i.e. it is a lattice model. Its solution therefore does not provide a wave function in real space, it provides wave function amplitudes on the graphene lattice.&lt;/p&gt;&#xA;&lt;p&gt;That said, given the amplitudes on the graphene lattice, you can create an approximate real-space wave function from an eigenstate of the lattice hamiltonian through linear combination of atomic orbitals: Place a carbon &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbital on every site and simply sum them up with the corresponding amplitudes (which can easily be done analytically).&lt;/p&gt;&#xA;&lt;p&gt;For armchair and zigzag graphene nanoribbons without onsite potential the solutions of this nearest-neighbor single-orbital tight-binding hamiltonian &lt;a href=&quot;https://doi.org/10.1088/1468-6996/11/5/054504&quot; rel=&quot;noreferrer&quot;&gt;can be obtained analytically&lt;/a&gt;. For playing around with different graphene nanoribbon shapes and on-site potentials I've found the &lt;a href=&quot;https://www.physics.rutgers.edu/pythtb/&quot; rel=&quot;noreferrer&quot;&gt;pythtb&lt;/a&gt; code very useful (e.g. I used it to create Figure 2.5 in &lt;a href=&quot;https://doi.org/10.5167/uzh-116635&quot; rel=&quot;noreferrer&quot;&gt;my Ph.D. thesis&lt;/a&gt;). You can use that to get the amplitudes on the lattice from the eigenstates of the hamiltonian and then do your postprocessing to get the wave function in real space.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7r2Tb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7r2Tb.png&quot; alt=&quot;Example of graphene wave functions&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-05-28T16:59:04.810" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5063" PostTypeId="2" ParentId="5052" CreationDate="2021-05-28T17:40:47.953" Score="10" Body="&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5057/5&quot;&gt;answer  by Kevin Jablonka&lt;/a&gt; is much more specific to matter modeling, but I wanted to point out that the screenshot example from Medea-VASP shown in the question, can be imitated almost exactly with most general schedulers (not specific to VASP) such as SLURM, PBS, LoadLeveler, Oracle Engine Grid, etc.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;squeue&lt;/code&gt; command in SLURM will give output very similar to Medea-VASP, with the following correspondence table:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Medea-VASP&lt;/th&gt;&#xA;&lt;th&gt;SLURM&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Job&lt;/td&gt;&#xA;&lt;td&gt;JOBID&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;User&lt;/td&gt;&#xA;&lt;td&gt;USER&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Queue&lt;/td&gt;&#xA;&lt;td&gt;PARTITION&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Name&lt;/td&gt;&#xA;&lt;td&gt;NAME&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Status&lt;/td&gt;&#xA;&lt;td&gt;ST&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;Here is an example of SLURM output (more information such as time started, time ended, etc. can be obtained by adding the appropriate &lt;a href=&quot;https://slurm.schedmd.com/squeue.html&quot; rel=&quot;noreferrer&quot;&gt;options for &lt;code&gt;squeue&lt;/code&gt;&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/e4aFd.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e4aFd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-05-28T17:40:47.953" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5065" PostTypeId="2" ParentId="4971" CreationDate="2021-05-29T05:36:10.990" Score="5" Body="&lt;p&gt;I gave it another try myself. In terms of databases/datasets, the best resource I found was the &lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_chemical_databases&quot; rel=&quot;nofollow noreferrer&quot;&gt;List of chemical databases in Wikipedia&lt;/a&gt;&lt;/strong&gt;. Within that rather extensive list list, in terms of &lt;em&gt;actual dashboards&lt;/em&gt; (which allow us to analyse and display the results rather than merely browsing collections of data) these are the two best examples I found:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The vast &lt;strong&gt;&lt;a href=&quot;https://comptox.epa.gov/dashboard/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CompTox Chemicals Dashboard&lt;/a&gt;&lt;/strong&gt;. These are molecular properties rather than properties of molecular materials as requested, and while it is clearly health-related it's not uniquely oriented towards pharmacological applications. An example screenshot follows, but there is so much more in this tool:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zFVM7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zFVM7.png&quot; alt=&quot;From https://upload.wikimedia.org/wikipedia/commons/c/ca/ToxCast_bioactivity_data_view_for_Bisphenol_A.png &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;The &lt;strong&gt;&lt;a href=&quot;https://www.acs.org/content/acs/en/greenchemistry/research-innovation/tools-for-green-chemistry/solvent-selection-tool.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Solvent Selection Tool&lt;/a&gt;&lt;/strong&gt;.[Diorazio et al, Org. Process Res. Dev. 2016, 20, 4, 760–773] Based on &lt;a href=&quot;https://en.wikipedia.org/wiki/Tableau_Software&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tableau&lt;/a&gt;, it's an interactive tool to facilitate solvent selection, allowing consideration of chemical functionality, physical properties, regulatory concerns, and safety/health/environmental (SHE) impact. Like the previous example, it's molecular-oriented (rather than materials-oriented), and with a focus on health considerations even if not pharmaceutically-oriented. An example screenshot follows, but, as above, there is a lot more to explore within this interactive interface:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nbY4j.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nbY4j.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="198" LastEditorUserId="5" LastEditDate="2022-07-10T08:37:54.860" LastActivityDate="2022-07-10T08:37:54.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5066" PostTypeId="2" ParentId="5022" CreationDate="2021-05-29T12:45:38.693" Score="7" Body="&lt;p&gt;The short answer is that this is a metal because of the following reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;An insulator or semiconductor features a bandgap between the occupied and the unoccupied states. For a temperature of 0K the Fermi energy discriminates between these two different occupations. This means the bandgap has to be around the Fermi level. A bandgap means that there are no states within a certain energy region. In the example from the question there is at least one band (or state) at every energy in the plotted energy window. There may be avoided crossings between two bands, but if there are other bands covering the energy region of this avoided crossing, e.g., at other k points, you have no bandgap. As a remark I would also like to add that these states do not necessarily have to show up in the band structure: Band structures cover the states along a high-symmetry path in the Brillouin zone (BZ). The band edges do not necessarily have to be found on this path. They can also be at different coordinates within the BZ. Nevertheless most of the time the band structure already gives a very good view on the electronic structure.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The avoided crossings in the example are probably artifacts of the visualization coming from connecting the i-th calculated states between the considered k points by lines. Such a visualization is sensitive to the order of the states in the underlying data files, which typically does not reflect physics. I suggest to plot band structure visualizations only with points at the calculated energy eigenvalues. Lines between the points may be misleading.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In a broader answer one may abstract from the example and consider a material with a tiny band gap at the Fermi level. Of course, there are several types of materials that come near such a situation. I would like to discuss this from the point of view of semiconductor physics:&lt;/p&gt;&#xA;&lt;p&gt;In semiconductors you have a larger bandgap and you can dope your material with certain atoms to place states within the bandgap. Typically these dopands are chosen such that these states are found near one of the band edges. In such situations there are temperatures T with a &lt;span class=&quot;math-container&quot;&gt;$k_\mathrm{B}T$&lt;/span&gt; that is at least in the same ballpark as the energy difference between the dopant states and the nearest band edge but considerably smaller than the band gap. This allows an ionization of the dopant atoms and the electrons (or holes) related to the dopant states become free charge carriers. This is practical because you can control the concentration of charge carriers within a large temperature window by the amount of doping. Within the &lt;a href=&quot;https://en.wikipedia.org/wiki/Drude_model&quot; rel=&quot;noreferrer&quot;&gt;Drude model&lt;/a&gt; the conductivity of the material &lt;span class=&quot;math-container&quot;&gt;$\sigma_0$&lt;/span&gt; is connected to this charge carrier concentration &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;   \sigma_0 = \frac{n q^2 \tau}{m},&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; is the charge of the carrier, &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; is its effective mass, and &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; its average traveling time between collisions.&lt;/p&gt;&#xA;&lt;p&gt;You have a different situation in which there are no dopant atoms but you have a very small bandgap. At a vanishing temperature such a material has no free charge carriers and therefore an insulating behavior. For finite temperatures &lt;span class=&quot;math-container&quot;&gt;$k_\mathrm{B}T$&lt;/span&gt; is at least in the same ballpark as the bandgap. If you increase the temperature starting with very small T, this will also increase the concentration of free charge carriers and with this the conductivity of the material. This is a different behavior than what you expect in metals. In metals you would expect a minimal resistivity at tiny T and an increase of the resistivity with temperature because the electron-phonon scattering would also increase. Of course, you would also have this mechanism in your situation but it would not dominate the behavior. At much higher temperatures you would observe a metal-like behavior.&lt;/p&gt;&#xA;&lt;p&gt;Let me finally mention that there are variations of the tiny bandgap situation that may be of interest when thinking about the behavior of such a system. For example you might have &lt;a href=&quot;https://en.wikipedia.org/wiki/Dirac_cone&quot; rel=&quot;noreferrer&quot;&gt;Dirac cones&lt;/a&gt; at the Fermi level. This means no bandgap but a certain dispersion of the bands. Another case may be the the presence of &lt;a href=&quot;https://en.wikipedia.org/wiki/Weyl_semimetal&quot; rel=&quot;noreferrer&quot;&gt;Weyl points&lt;/a&gt;. I will not dive into the physics of such cases.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT:&lt;/strong&gt; An additional thought: Depending on the XC functional DFT calculations typically underestimate the bandgap and sometimes predict metals even though the material actually is an insulator. Maybe the example shows such a case.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2021-05-29T13:55:25.677" LastActivityDate="2021-05-29T13:55:25.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5067" PostTypeId="5" CreationDate="2021-05-29T15:43:14.683" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-05-29T15:43:14.683" LastActivityDate="2021-05-29T15:43:14.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5068" PostTypeId="4" CreationDate="2021-05-29T15:43:14.683" Score="0" Body="For questions about graphical user interface (GUI) which is a form of user interface where the user can interact with a software or a system using interactive visual components, instead of typed commands" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-29T18:02:26.650" LastActivityDate="2021-05-29T18:02:26.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5069" PostTypeId="5" CreationDate="2021-05-29T15:46:04.383" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-05-29T15:46:04.383" LastActivityDate="2021-05-29T15:46:04.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5070" PostTypeId="4" CreationDate="2021-05-29T15:46:04.383" Score="0" Body="DFTB+ is a software package that can carry out fast quantum mechanical calculations using the Density Functional Tight-Binding method" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-29T18:02:48.173" LastActivityDate="2021-05-29T18:02:48.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5071" PostTypeId="5" CreationDate="2021-05-29T15:48:15.147" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-05-29T15:48:15.147" LastActivityDate="2021-05-29T15:48:15.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5072" PostTypeId="4" CreationDate="2021-05-29T15:48:15.147" Score="0" Body="For questions asking for recommendations of matter modelling softwares available at no cost." OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-05-30T02:13:48.563" LastActivityDate="2021-05-30T02:13:48.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5073" PostTypeId="2" ParentId="5053" CreationDate="2021-05-29T17:35:45.957" Score="14" Body="&lt;p&gt;There is an example in the pyiron documentation to calculate energy volume curves:&#xA;&lt;a href=&quot;https://pyiron.readthedocs.io/en/latest/source/notebooks/energy_volume_curve.html&quot; rel=&quot;noreferrer&quot;&gt;https://pyiron.readthedocs.io/en/latest/source/notebooks/energy_volume_curve.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And the corresponding jupyter notebook is available in the pyiron repository:&#xA;&lt;a href=&quot;https://github.com/pyiron/pyiron_atomistics/blob/master/notebooks/energy_volume_curve.ipynb&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/pyiron/pyiron_atomistics/blob/master/notebooks/energy_volume_curve.ipynb&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To adjust the energy cutoff and kpoint mesh, you can write an additional loop and update them using &lt;code&gt;job.set_encut(300.0)&lt;/code&gt; for an energy cutoff of 300.0eV and &lt;code&gt;job.set_kpoints([3,3,3])&lt;/code&gt; for a 3x3x3 kpoint mesh. Finally while the example is written for GPAW the same code works for VASP by replacing &lt;code&gt;pr.job_type.Gpaw&lt;/code&gt; with &lt;code&gt;pr.job_type.VASP&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Going one step further, there is even a youtube tutorial for calculating an energy volume curve:&#xA;&lt;a href=&quot;https://www.youtube.com/watch?v=ZCVRLS4b5YU&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=ZCVRLS4b5YU&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Best,&lt;/p&gt;&#xA;&lt;p&gt;Jan&lt;/p&gt;&#xA;" OwnerUserId="3661" LastActivityDate="2021-05-29T17:35:45.957" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5074" PostTypeId="1" AcceptedAnswerId="5075" CreationDate="2021-05-29T20:26:00.423" Score="6" ViewCount="254" Body="&lt;p&gt;The code in question is just 2 lines used to import the &amp;quot;COST507 database for light alloys&amp;quot; (downloaded from the opencalphad homepage &lt;a href=&quot;http://www.opencalphad.com/&quot; rel=&quot;noreferrer&quot;&gt;http://www.opencalphad.com/&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pycalphad import Database&#xA;db = Database('COST507.tdb')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the error it returns:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Failed while parsing:  ELEMENT Y HCP_A3 8.89059+01 5.9664E+03 4.4434E+01 &#xA;Tokens: None&#xA;&#xA;---------------------------------------------------------------------------&#xA;ParseException                            Traceback (most recent call last)&#xA;&amp;lt;ipython-input-6-84bd58f009b2&amp;gt; in &amp;lt;module&amp;gt;&#xA;      1 from pycalphad import Database&#xA;----&amp;gt; 2 db = Database('COST507.tdb')&#xA;&#xA;~\Anaconda3\envs\pycalphad_env\lib\site-packages\pycalphad\io\database.py in __new__(cls, *args)&#xA;    127             elif fname.find('\n') == -1:&#xA;    128                 # Single-line string; it's probably a filename&#xA;--&amp;gt; 129                 return cls.from_file(fname, fmt=fmt)&#xA;    130             else:&#xA;    131                 # Newlines found: probably a full database string&#xA;&#xA;~\Anaconda3\envs\pycalphad_env\lib\site-packages\pycalphad\io\database.py in from_file(fname, fmt)&#xA;    221         try:&#xA;    222             dbf = Database()&#xA;--&amp;gt; 223             format_registry[fmt.lower()].read(dbf, fd)&#xA;    224         finally:&#xA;    225             # Close file descriptors created in this routine&#xA;&#xA;~\Anaconda3\envs\pycalphad_env\lib\site-packages\pycalphad\io\tdb.py in read_tdb(dbf, fd)&#xA;    911         tokens = None&#xA;    912         try:&#xA;--&amp;gt; 913             tokens = _tdb_grammar().parseString(command)&#xA;    914             _TDB_PROCESSOR[tokens[0]](dbf, *tokens[1:])&#xA;    915         except ParseException:&#xA;&#xA;~\Anaconda3\envs\pycalphad_env\lib\site-packages\pyparsing.py in parseString(self, instring, parseAll)&#xA;   1953                 if getattr(exc, '__traceback__', None) is not None:&#xA;   1954                     exc.__traceback__ = self._trim_traceback(exc.__traceback__)&#xA;-&amp;gt; 1955                 raise exc&#xA;   1956         else:&#xA;   1957             return tokens&#xA;&#xA;~\Anaconda3\envs\pycalphad_env\lib\site-packages\pyparsing.py in parseImpl(self, instring, loc, doActions)&#xA;   3782                 return loc + 1, &amp;quot;\n&amp;quot;&#xA;   3783             else:&#xA;-&amp;gt; 3784                 raise ParseException(instring, loc, self.errmsg, self)&#xA;   3785         elif loc == len(instring):&#xA;   3786             return loc + 1, []&#xA;&#xA;ParseException: Expected {{&amp;quot;ELEMENT&amp;quot; W:(ABCD...) [Suppress:(W:(ABCD...))] [Suppress:({Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)')}...)] LineEnd} | {&amp;quot;SPECIES&amp;quot; W:(ABCD...) [Suppress:(&amp;quot;%&amp;quot;)] Group:({{W:(ABCD...) [Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)')]}}...) [{Suppress:(&amp;quot;/&amp;quot;) W:(+-01...)}] LineEnd} | {&amp;quot;TYPE_DEFINITION&amp;quot; Suppress:(&amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;) !W:( !) SkipTo:(LineEnd)} | {&amp;quot;FUNCTION&amp;quot; W:(ABCD...) {{Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)') | [&amp;quot;,&amp;quot;]...} {{SkipTo:(&amp;quot;;&amp;quot;) Suppress:(&amp;quot;;&amp;quot;) [Suppress:(&amp;quot;,&amp;quot;)]... [Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)')] Suppress:({W:(YNyn) | &amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;})}}...}} | {&amp;quot;ASSESSED_SYSTEMS&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;DEFINE_SYSTEM_DEFAULT&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;DEFAULT_COMMAND&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;DATABASE_INFO&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;VERSION_DATE&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;REFERENCE_FILE&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;ADD_REFERENCES&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;LIST_OF_REFERENCES&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;TEMPERATURE_LIMITS&amp;quot; SkipTo:(LineEnd)} | {&amp;quot;PHASE&amp;quot; W:(ABCD...) Suppress:(&amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;) !W:( !) Suppress:(&amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;) Suppress:(W:(0123...)) Group:({Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)')}...) LineEnd} | {&amp;quot;CONSTITUENT&amp;quot; W:(ABCD...) Suppress:(&amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;) Suppress:(&amp;quot;:&amp;quot;) Group:(Group:({{[Suppress:(&amp;quot;,&amp;quot;)] {W:(ABCD...) [Suppress:(&amp;quot;%&amp;quot;)]}}}...) [: Group:({{[Suppress:(&amp;quot;,&amp;quot;)] {W:(ABCD...) [Suppress:(&amp;quot;%&amp;quot;)]}}}...)]...) Suppress:(&amp;quot;:&amp;quot;) LineEnd} | {&amp;quot;PARAMETER&amp;quot; {&amp;quot;BMAGN&amp;quot; | &amp;quot;DF&amp;quot; | &amp;quot;DQ&amp;quot; | &amp;quot;G&amp;quot; | &amp;quot;GD&amp;quot; | &amp;quot;L&amp;quot; | &amp;quot;MF&amp;quot; | &amp;quot;MQ&amp;quot; | &amp;quot;NT&amp;quot; | &amp;quot;TC&amp;quot; | &amp;quot;THETA&amp;quot; | &amp;quot;V0&amp;quot; | &amp;quot;VS&amp;quot;} Suppress:(&amp;quot;(&amp;quot;) W:(ABCD...) [{Suppress:(&amp;quot;&amp;amp;&amp;quot;) W:(ABCD...)}] Suppress:(&amp;quot;,&amp;quot;) Group:(Group:({{[Suppress:(&amp;quot;,&amp;quot;)] {W:(ABCD...) [Suppress:(&amp;quot;%&amp;quot;)]}}}...) [: Group:({{[Suppress:(&amp;quot;,&amp;quot;)] {W:(ABCD...) [Suppress:(&amp;quot;%&amp;quot;)]}}}...)]...) [{Suppress:(&amp;quot;;&amp;quot;) W:(0123...)}] Suppress:(&amp;quot;)&amp;quot;) {{Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)') | [&amp;quot;,&amp;quot;]...} {{SkipTo:(&amp;quot;;&amp;quot;) Suppress:(&amp;quot;;&amp;quot;) [Suppress:(&amp;quot;,&amp;quot;)]... [Re:('[-+]?([0-9]+\\.(?!([0-9]|[eE])))|([0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?)')] Suppress:({W:(YNyn) | &amp;lt;SP&amp;gt;&amp;lt;TAB&amp;gt;&amp;lt;CR&amp;gt;&amp;lt;LF&amp;gt;})}}...}}}, found '+'  (at char 25), (line:1, col:26)&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="5" LastEditDate="2021-05-29T21:14:52.147" LastActivityDate="2021-05-30T16:41:50.783" Title="Pycalphad &quot;Failed while parsing&quot; Yttrium from light alloys database" Tags="|python|software-assistance|databases|calphad|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5075" PostTypeId="2" ParentId="5074" CreationDate="2021-05-29T22:54:36.450" Score="8" Body="&lt;p&gt;Thanks to Tyberius for pointing out one issue in the database in their comment.&lt;/p&gt;&#xA;&lt;p&gt;The pycalphad database parser is strict, but also tries to prevent ambiguities or mistakes.&lt;/p&gt;&#xA;&lt;p&gt;I made the following corrections:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Changed &lt;code&gt;ELEMENT Y HCP_A3 8.89059+01 5.9664E+03 4.4434E+01 !&lt;/code&gt; to &lt;code&gt;ELEMENT Y HCP_A3 8.89059E+01 5.9664E+03 4.4434E+01&lt;/code&gt; (adding &lt;code&gt;E&lt;/code&gt; to the exponent of the mass)&lt;/li&gt;&#xA;&lt;li&gt;Changed the parameter &lt;code&gt;PARAMETER L(B4M3,B:HF,TI;0) 298.15  !.0E-4; 6000.00 N !&lt;/code&gt; to &lt;code&gt;PARAMETER L(B4M3,B:HF,TI;0) 298.15  1.0E-4; 6000.00 N !&lt;/code&gt; (assuming that &lt;code&gt;!.0E-4&lt;/code&gt; should be &lt;code&gt;1.0E-4&lt;/code&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Commented out the following type definition because it is not yet supported by pycalphad (it will not affect correctness) &lt;code&gt;TYPE_DEF R IF(AL AND FE) THEN TDB RESTORE_PH AL5FE4 !&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Fixed several incorrectly formatted reference keys, &lt;code&gt;REF: 0&lt;/code&gt; and &lt;code&gt;REF: 3&lt;/code&gt;, (spaces are not allowed in reference keys)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can find a corrected version that works with pycalphad &lt;a href=&quot;https://gist.github.com/bocklund/c4714ddbc0500c78e6fe255a763e7550&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. I'm not sure if there's a better way to share this relatively large file in a more permanent and StackExchange-approved way.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="1179" LastEditDate="2021-05-30T16:41:50.783" LastActivityDate="2021-05-30T16:41:50.783" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="5076" PostTypeId="2" ParentId="3813" CreationDate="2021-05-31T03:59:29.720" Score="6" Body="&lt;p&gt;Depending on your calculation and how much time you want to invest in getting the best property you can, I suggest two different approaches to make this system stable:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Fully relax the geometry of the structure&lt;/strong&gt;. Some comments below your question suggest that you tried to fully relax your structure, but the structure is probably not fully relaxed if it is still mechanically unstable. In your software of choice, you may have to turn off the symmetry or break the symmetry &amp;quot;by hand&amp;quot; of the structure so that the relaxation does not constrain the relaxation to preserve the cubic symmetry (and therefore mechanical instability) of your structure.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Use the inflection detection method&lt;/strong&gt;. Some relatively recent work proposes to compute the properties of mechanically unstable structures at the limit of stability [1] - at the inflection point of the energy. Some examples of applications to pure elements are laid out by van de Walle &lt;em&gt;et al.&lt;/em&gt; [2] in a later paper with energies for mechanically unstable phases in good agreement with CALPHAD lattice stabilities. However, this method is considerably more computationally demanding than a geometry relaxation. It requires determining the softest phonon mode for several candidate geometries (with broken symmetry) between the mechanically unstable and fully relaxed states to find the geometry where the softest phonon mode has an eigenvalue of zero.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;[1] van de Walle, A., Hong, Q., Kadkhodaei, S., Sun, R., 2015. The free energy of mechanically unstable phases. Nat Commun 6, 7559. &lt;a href=&quot;https://doi.org/10.1038/ncomms8559&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/ncomms8559&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] van de Walle, A., 2018. Reconciling SGTE and ab initio enthalpies of the elements. Calphad 60, 1–6. &lt;a href=&quot;https://doi.org/10.1016/j.calphad.2017.10.008&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.calphad.2017.10.008&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-05-31T03:59:29.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5077" PostTypeId="1" AcceptedAnswerId="5081" CreationDate="2021-05-31T04:17:46.383" Score="11" ViewCount="286" Body="&lt;p&gt;What's the most efficient way to get the equilibrium phases and phase fractions for a set of alloy compositions? For context, I'm coming from Thermo-Calc/TC-Python where I would just loop through the alloy compositions and do a single equilbrium calculation. However, when I attempt to do this with pycalphad it seems quite slow. For example, here is what my code for the &amp;quot;one at a time&amp;quot; looping:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pycalphad import Database, calculate, equilibrium, variables as v&#xA;dbf = Database(&amp;quot;Cr-Fe-Ni.tdb&amp;quot;)&#xA;components = ['FE','CR', 'NI', 'VA'] &#xA;phases = ['LIQUID', 'BCC_A2', 'FCC_A1', 'SIGMA']&#xA;&#xA;#Example set of alloy compositions, normally I would want to sample more finely but I'll keep it simple for demonstration purposes&#xA;compositions = array([[0. , 0. ],&#xA;                      [0. , 0.2],&#xA;                      [0. , 0.4],&#xA;                      [0. , 0.6],&#xA;                      [0. , 0.8],&#xA;                      [0.2, 0. ],&#xA;                      [0.2, 0.2],&#xA;                      [0.2, 0.4],&#xA;                      [0.2, 0.6],&#xA;                      [0.2, 0.8],&#xA;                      [0.4, 0. ],&#xA;                      [0.4, 0.2],&#xA;                      [0.4, 0.4],&#xA;                      [0.4, 0.6],&#xA;                      [0.6, 0. ],&#xA;                      [0.6, 0.2],&#xA;                      [0.6, 0.4],&#xA;                      [0.8, 0. ],&#xA;                      [0.8, 0.2]])&#xA;&#xA;phase_data = []&#xA;for i in tqdm.tqdm(range(len(compositions)), total=len(compositions), position=0, leave=True, smoothing=0.3):&#xA;    eq_result = equilibrium(dbf, components, phases, {v.X('CR'):compositions[i,0], v.X('NI'):compositions[i,1], v.T:1000, v.P:101325})&#xA;    phase_data.append([*eq_result.NP.values.squeeze().tolist(), *eq_result.Phase.values.squeeze().tolist()])&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This takes about 15 seconds, or about 1.2 alloys evaluated per second. This seems quite slow for a ternary, and I suspect it's because I'm calling the equilibrium function each time instead of just changing the composition.&lt;/p&gt;&#xA;&lt;p&gt;I tried feeding the whole column at once (see code below), but this seemed to take the Cartesian product of the compositions, which is not what I want.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#database, phase, and composition setup is same as in above code&#xA;&#xA;eq_result = equilibrium(dbf, components, phases, {v.X('CR'):compositions[:,0], v.X('NI'):compositions[:,1], v.T:1000, v.P:101325})&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, please let me know what the better approach is. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1410" LastActivityDate="2021-06-01T15:25:14.120" Title="Pycalphad most efficient way to gather equilibirum phase data for set of alloy compositions?" Tags="|python|software-assistance|calphad|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5078" PostTypeId="1" AcceptedAnswerId="5080" CreationDate="2021-05-31T14:26:41.533" Score="11" ViewCount="1717" Body="&lt;p&gt;I am new to DFT-simulation and I wish to understand how it works behind the scene. As the title suggests I don't understand why LCAO-based codes have to define K-points and cut-off energies. I understand why they are used in Plane-Wave codes. In such codes the cut-off energy defines the max G value of the Fourier series and the k-point defines how fine the Monkhorst-Pack grid is defined. However, in LCAO we work in real space, so both parameters are not inherent to the representation used.&lt;/p&gt;&#xA;&lt;p&gt;How I understand it now, the K-point is defined to determine how fine the real-space grid is discretized, but I exactly understand how and why this is used instead of using a real-space discretization variable. If this is the case, I still don't see what purpose the Energy cut-off has.&lt;/p&gt;&#xA;&lt;p&gt;Could someone help me with this or point me in the direction of some resources on this?&lt;/p&gt;&#xA;" OwnerUserId="3670" LastEditorUserId="887" LastEditDate="2021-06-02T10:06:22.857" LastActivityDate="2021-06-02T10:06:22.857" Title="Why is Energy Cut-off and K-Point Convergence necessary in LCAO-based codes like SIESTA?" Tags="|density-functional-theory|k-points|convergence-test|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5079" PostTypeId="2" ParentId="414" CreationDate="2021-05-31T18:05:45.010" Score="5" Body="&lt;p&gt;&lt;strong&gt;DALTON&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For what I know also the &lt;a href=&quot;https://daltonprogram.org/&quot; rel=&quot;noreferrer&quot;&gt;Dalton&lt;/a&gt; suite is able to run CASSCF. It's also an open source software. You can find the tutorial to run CASSCF calculation &lt;a href=&quot;https://daltonproject.readthedocs.io/en/latest/tutorials/casscf/cas_tutorial.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2021-05-31T18:05:45.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5080" PostTypeId="2" ParentId="5078" CreationDate="2021-05-31T18:23:58.343" Score="7" Body="&lt;p&gt;The k-point discretization has the same meaning in plane wave codes as LCAO based codes. In fact, it has the same meaning in all DFT related codes. It defines the integration of the Brillouin zone. You want the integration to be good enough to capture the relevant physics (e.g. graphene with k-point sampling touching the Dirac point vs Gamma-only) but also sparse enough to allow high computational throughput.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;em&gt;mesh cutoff&lt;/em&gt; determines the plane wave cutoff of the kinetic energy, so in that sense it relates directly to the energy cutoff from plane wave codes. It defines the density of mesh-points for things such as density, XC functionals etc.&lt;/p&gt;&#xA;&lt;p&gt;What people typically refer to LCAO in terms of real-space codes is that it is capable of calculating systems so large that only the Gamma-point is necessary (thereby having only real-space components of the wavefunctions). I.e. thousands of atoms.&lt;br /&gt;&#xA;However, generally LCAO can equally well simulate condensed matter physics where Brillouin zone integrations are important.&lt;/p&gt;&#xA;&lt;p&gt;Finally let me note that the difficult thing about LCAO codes (Siesta, OpenMX etc) is not the mesh cutoff, nor the k-point sampling (they are easy to converge). It is the basis set which is important. This basis set is generally not transferable between two different chemical environments and tuning of the basis sets are important to correctly describe the physics.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Perhaps I should clarify that LCAO, generally, does &lt;em&gt;not&lt;/em&gt; work in real space. Generally the LCAO model is exactly the same as the PW codes. This is a misconception of what the &amp;quot;real space&amp;quot; refers to in LCAO codes.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-06-01T13:54:02.587" LastActivityDate="2021-06-01T13:54:02.587" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="5081" PostTypeId="2" ParentId="5077" CreationDate="2021-06-01T15:25:14.120" Score="8" Body="&lt;p&gt;In your comment, you mentioned that you may be testing many alloys (100,000s). I will assume that interested in taking more of a screening approach, rather than specifying precisely 100,000 alloys compositions.&lt;/p&gt;&#xA;&lt;p&gt;In that case, it is easy and faster to let pycalphad broadcast the conditions for you. It will skip any conditions that have independent mole fractions that sum to greater than unity, e.g. X(CR)=0.8 and X(NI)=0.8. The result that you get from &lt;code&gt;equilibrium&lt;/code&gt; is an xarray Dataset object and uses padded NumPy arrays. Floating point values (like &lt;code&gt;NP&lt;/code&gt;) will be padded with &lt;code&gt;nan&lt;/code&gt; and string values (like &lt;code&gt;Phase&lt;/code&gt;) will be padded with &lt;code&gt;''&lt;/code&gt; when no phases are present.&lt;/p&gt;&#xA;&lt;p&gt;xarray and most of the tools in the ecosystem (like matplotlib) play nicely with these padded values. Below, I give an example where equilibrium calculations are performed on a dense grid and I plot the phase fractions of FCC over the whole grid and under a constraint where the composition of Cr is under 40 at%.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pycalphad import Database, calculate, equilibrium, variables as v&#xA;import matplotlib.pyplot as plt&#xA;&#xA;dbf = Database(&amp;quot;Cr-Fe-Ni.tdb&amp;quot;)&#xA;components = ['FE','CR', 'NI', 'VA'] &#xA;phases = ['LIQUID', 'BCC_A2', 'FCC_A1', 'SIGMA']&#xA;&#xA;eq_result = equilibrium(dbf, components, phases, {v.X('CR'): (0, 1, 0.1), v.X('NI'): (0, 1, 0.1), v.T:1000, v.P:101325})&#xA;&#xA;&#xA;# verify what the Phase and NP look like by printing&#xA;# note these are multi-dimensional arrays and are padded with '' and nan, respectively&#xA;print(eq_result.Phase.values)&#xA;print(eq_result.NP.values)&#xA;&#xA;&#xA;# Plot FCC phase fractions over the whole grid&#xA;plt.figure()&#xA;plt.subplot(projection=&amp;quot;triangular&amp;quot;)  # projection provided by pycalphad&#xA;&#xA;mask = eq_result.Phase == &amp;quot;FCC_A1&amp;quot; # choose only FCC, others will be NaN&#xA;plt.scatter(&#xA;    eq_result.X_CR.where(mask).broadcast_like(mask),&#xA;    eq_result.X_NI.where(mask).broadcast_like(mask), &#xA;    c=eq_result.NP.where(mask)&#xA;)&#xA;plt.title(&amp;quot;Cr-Fe-Ni FCC Phase Fractions&amp;quot;)&#xA;plt.xlabel(&amp;quot;X(CR)&amp;quot;)&#xA;plt.ylabel(&amp;quot;X(NI)&amp;quot;)&#xA;plt.colorbar(label=&amp;quot;NP(FCC_A1)&amp;quot;)&#xA;plt.show()&#xA;&#xA;&#xA;# Plot FCC phase fractions only at compositions under 40 at% Cr&#xA;plt.figure()&#xA;plt.subplot(projection='triangular')  # projection provided by pycalphad&#xA;&#xA;# choose only FCC AND where the composition of Cr is less than 40%, others will be NaN&#xA;mask = (eq_result.Phase == 'FCC_A1') &amp;amp; (eq_result.X_CR &amp;lt; 0.4)&#xA;plt.scatter(&#xA;    eq_result.X_CR.where(mask).broadcast_like(mask),&#xA;    eq_result.X_NI.where(mask).broadcast_like(mask), &#xA;    c=eq_result.NP.where(mask)&#xA;)&#xA;plt.title(&amp;quot;Cr-Fe-Ni FCC Phase Fractions&amp;quot;)&#xA;plt.xlabel(&amp;quot;X(CR)&amp;quot;)&#xA;plt.ylabel(&amp;quot;X(NI)&amp;quot;)&#xA;plt.colorbar(label=&amp;quot;NP(FCC_A1)&amp;quot;)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This produces the following two plots:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1F1g3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1F1g3.png&quot; alt=&quot;Cr-Fe-Ni full grid&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/C3XB4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/C3XB4.png&quot; alt=&quot;Cr-Fe-Ni constrained grid&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-06-01T15:25:14.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5082" PostTypeId="1" CreationDate="2021-06-01T15:29:38.637" Score="9" ViewCount="89" Body="&lt;p&gt;Can anyone please explain to me how can I calculate the mirror Chern number of a 2D system? I will be very thankful if you can refer me to a package or software which can directly perform mirror Chern number calculations without any complex calculations. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2021-12-15T07:12:48.333" LastActivityDate="2021-12-15T07:12:48.333" Title="Software for calculating the mirror Chern number of 2D systems?" Tags="|density-functional-theory|software-recommendations|one-topic-per-answer|topological-insulators|density-functional-tight-binding|" AnswerCount="0" CommentCount="2" ClosedDate="2022-01-13T02:08:52.383" ContentLicense="CC BY-SA 4.0" />
  <row Id="5083" PostTypeId="1" AcceptedAnswerId="6119" CreationDate="2021-06-02T14:35:19.523" Score="13" ViewCount="452" Body="&lt;p&gt;I am trying to determine the melting temperature of an fcc metal as a function of pressure, which should give a liquid–solid phase diagram for this metal. For now, I'm not going to consider any polymorphs other than fcc in the solid phase. My goal is to test the thermodynamic properties of a ReaxFF potential. I am using LAMMPS. What LAMMPS features would be most helpful for this? Is parallel tempering (temperature replica exchange) useful for this?&lt;/p&gt;&#xA;&lt;p&gt;I'm aware of &lt;a href=&quot;https://doi.org/10.1140/epjp/i2013-13010-8&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; by Frenkel that says trying to simulate coexistence explicitly can be problematic.&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2021-06-10T16:18:42.070" Title="Best protocol for finding liquid–solid coexistence curve in molecular dynamics?" Tags="|lammps|phase-diagram|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5084" PostTypeId="2" ParentId="5023" CreationDate="2021-06-02T22:21:26.517" Score="10" Body="&lt;p&gt;If you haven't figured it out yet here is what I would've done using mercury to get the xyz file of the dimer. There is some disorder in the crystal structure which I think means that there are partial occupations of molecules/atoms at different positions so you need to delete them to get only one of set of the dimers in the xyz file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ScKVT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ScKVT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1Vybn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1Vybn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VIR1o.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VIR1o.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3674" LastActivityDate="2021-06-02T22:21:26.517" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5085" PostTypeId="1" CreationDate="2021-06-03T08:37:04.550" Score="7" ViewCount="84" Body="&lt;p&gt;I have been trying to simulate ZnSe zinc blende quantum dots using Quantum Espresso and its GUI BURAI. But being a beginner I am a little confused about a few things:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How do I passivate the surface, am I supposed to make a new &lt;code&gt;.cif&lt;/code&gt; file after deciding which substance I wanna use for passivation and what coordinates do I wanna place these atoms at.&lt;/li&gt;&#xA;&lt;li&gt;Do I even need passivation? I am trying to obtain optical band gaps for now.&lt;/li&gt;&#xA;&lt;li&gt;How do I apply vacuum to my quantum dot. This procedure is fairly simple for molecules but when I do the same for quantum dot(I have been trying to simulate one with 8 unit cells which make a bigger cube of sort, is this a correct way to make a quantum dot?) but when I do the same for  a qd, the atoms which are there on the cubic lattice(Zn) also move with the surface hence destroying the bonds between them and ones on the inside(Se). How do I fix this?? &lt;br /&gt;&#xA;Thanks and I am a bachelors student who has not had any proper course(except for DFT one from coursera) in this and any other addvice would be greatly appreciated.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2021-06-05T08:06:37.490" LastActivityDate="2021-06-05T08:06:37.490" Title="How to passivate the surface of ZnSe Quantum Dot and apply vacuum to it?" Tags="|density-functional-theory|quantum-espresso|quantum-dots|" AnswerCount="0" CommentCount="4" ClosedDate="2021-06-24T20:13:56.350" ContentLicense="CC BY-SA 4.0" />
  <row Id="5086" PostTypeId="2" ParentId="4922" CreationDate="2021-06-03T11:05:15.803" Score="2" Body="&lt;p&gt;Found a small script for BGW to do the plot &lt;a href=&quot;https://github.com/BerkeleyGW/bgwtools/blob/master/bgwtools/BSE/plot_envelope.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/BerkeleyGW/bgwtools/blob/master/bgwtools/BSE/plot_envelope.py&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2021-06-03T11:05:15.803" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="5087" PostTypeId="1" AcceptedAnswerId="5089" CreationDate="2021-06-03T11:35:39.953" Score="13" ViewCount="2941" Body="&lt;p&gt;I have been using both Gaussian09 and Gaussian16 recently to optimize some metal complexes. The Gaussian manual (for both versions) indicates that the maximum number of steps in a geometry optimization can be set by the keyword &lt;code&gt;maxcycles&lt;/code&gt; in &lt;code&gt;opt&lt;/code&gt;. However, for every optimization I have done, Gaussian seems to consistently ignore the value set by &lt;code&gt;maxcycles&lt;/code&gt; and sets its own max. number of steps internally.&lt;/p&gt;&#xA;&lt;p&gt;Most of the calculations I did have this route line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt=maxcycles=200 freq b3lyp/sdd geom=connectivity&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What I have noticed is that when I am minimizing the geometry, Gaussian sets maximum number of steps to &lt;code&gt;100&lt;/code&gt; (with the &lt;code&gt;maxcycles=200&lt;/code&gt;, or to &lt;code&gt;50&lt;/code&gt; if the maxcycles keyword is omitted. For transition state optimizations, the max. number of steps is set to &lt;code&gt;145&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have seen some discussions regarding this in various forums and mailing lists, but I have found no solution. I have also seen some posts claiming it is a bug, but it keeps happening in Gaussian16 too.&lt;/p&gt;&#xA;&lt;p&gt;So, my question is— &lt;strong&gt;why does Gaussian ignore the &lt;code&gt;maxcycles&lt;/code&gt; keyword and how can I fix it?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-05T09:54:50.333" LastActivityDate="2021-06-07T17:06:26.230" Title="Why does Gaussian ignore the opt=maxcycles keyword for optimizations?" Tags="|gaussian|geometry-optimization|software-assistance|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5088" PostTypeId="1" AcceptedAnswerId="9630" CreationDate="2021-06-03T13:58:17.897" Score="8" ViewCount="176" Body="&lt;p&gt;One aspect of the molecular distance geometry problem (MDGP) &lt;a href=&quot;https://www.lix.polytechnique.fr/%7Eliberti/mdgp_encopt2.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;described in this PDF&lt;/a&gt;, can be written as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Given observations of noisy distances between atoms in a molecule, estimate the values of the true distances.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;More formally: Given the datasets &lt;span class=&quot;math-container&quot;&gt;$\mathcal{D}_1,\mathcal{D}_2,\dots,\mathcal{D}_n$&lt;/span&gt; of noisy distances for the atoms defined by the points &lt;span class=&quot;math-container&quot;&gt;$\mathcal{S} = \{x_1,x_2,\dots,x_n\}$&lt;/span&gt;, estimate the &lt;span class=&quot;math-container&quot;&gt;$n \times n$&lt;/span&gt; symmetric distance matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{A} = (d_{ij})$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$d_{ij} = \lvert\lvert x_i - x_j\rvert\rvert$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$x_i \in \mathbb{R}^K$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$i,j \in \{1,2,...,n\}$&lt;/span&gt;.&lt;/p&gt;&#xA; &#xA;&lt;p&gt;Are there references that explore different noise models for the distances between atoms and references that attempt to estimate these distances?&lt;/p&gt;&#xA;" OwnerUserId="3676" LastEditorUserId="5" LastEditDate="2021-06-28T03:23:23.733" LastActivityDate="2022-09-07T12:35:00.377" Title="References related to the molecular distance geometry problem (estimating true distances based on noisy distances)" Tags="|reference-request|molecular-modeling|mathematical-modeling|geometry|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="5089" PostTypeId="2" ParentId="5087" CreationDate="2021-06-03T15:16:44.430" Score="10" Body="&lt;p&gt;This requires an additional &lt;a href=&quot;https://gaussian.com/overlay1/#iop_(1/152)&quot; rel=&quot;nofollow noreferrer&quot;&gt;IOP&lt;/a&gt; to do. It seems that Gaussian sets a separate lower and upper bound on the number of optimization steps that will be performed based on the number of coordinates and &lt;code&gt;opt(maxcycle=N)&lt;/code&gt; can only set the max value within this range, but not any higher. &lt;code&gt;IOP(1/152=N)&lt;/code&gt; changes this internal max value, allowing maxcycle to be raised as well. So  you should be able to use &lt;code&gt;# opt(maxcycles=200) iop(1/152=200) freq b3lyp/sdd geom=connectivity&lt;/code&gt; to increase the allowed number of steps.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Disclaimer&lt;/em&gt;: There is probably a reason, either physically motivated or due to the structure of the Gaussian code, why/how they set the cap on the number of steps. A large number of optimizations steps can be a sign that you started from a bad structure. It may be fine to remove the cap, but keep in mind the idea of &lt;a href=&quot;https://fs.blog/2020/03/chestertons-fence/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chesterton's Fence&lt;/a&gt; (in short, don't remove a limitation until you understand why its there). IOPs should also be used carefully, as they can conflict with other keyword options.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-07T17:06:26.230" LastActivityDate="2021-06-07T17:06:26.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5090" PostTypeId="1" CreationDate="2021-06-03T16:03:24.960" Score="18" ViewCount="727" Body="&lt;p&gt;At the University, I chose the organic chemistry path and to better understand my experimental works I started studying computational chemistry on my own. There are a lot of books in this field, but I found the book &amp;quot;Computational organic chemistry&amp;quot; by Steven Bachrach very useful as a starting point. While still explaining the theory behind every methods with a bit of mathematics, it was easy for a newbie like me to join this wonderful world thanks to the many examples reported.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know if there are similar books related to computational chemistry of solid state materials. I would like to see an answer for every book and the related upvotes to better choose between the suggested books.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="85" LastEditDate="2021-06-04T08:55:35.403" LastActivityDate="2021-06-15T16:05:51.637" Title="Good books about computational chemistry of solid state materials for newbie" Tags="|reference-request|solid-state-physics|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="5091" PostTypeId="2" ParentId="5090" CreationDate="2021-06-03T21:14:54.983" Score="11" Body="&lt;p&gt;Its a bit more on the physics side but for solid-state physics I quite liked the &amp;quot;The Oxford Solid State Basics&amp;quot;. Its a very good intro because its quite short so you can actually go through most of it unlike some others which are too long so you only end up reading a fraction of it. What is also another great thing about is that the lecture series is freely available on youtube.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=XQk25fSJkL8&amp;amp;list=PLaNkJORnlhZnC6E3z1-i7WERkferhQDzq&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=XQk25fSJkL8&amp;amp;list=PLaNkJORnlhZnC6E3z1-i7WERkferhQDzq&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3674" LastActivityDate="2021-06-03T21:14:54.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="5092" PostTypeId="2" ParentId="5018" CreationDate="2021-06-04T00:21:30.203" Score="7" Body="&lt;p&gt;One critical mistake is to invest heavily in GPUs before doing a cost/benefit analysis. A single GPU may cost $2000, which can already get you 2-3 good compute nodes. Many codes (e.g. &lt;a href=&quot;https://gaussian.com/g16/gpus.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://gaussian.com/g16/gpus.pdf&lt;/a&gt;) advertise speedups that are underwhelming: the GPU speedup should be at least an order of magnitude, when the CPU code is already close to optimal. If GPUs don't give you more performance than CPUs&lt;/p&gt;&#xA;&lt;p&gt;A major point to consider is: who are you buying the workstation for? If there are several users, it may be better to buy several cheaper units than a big compute server, since the users' needs may conflict. IIRC GROMACS is CPU bound, while quantum chemistry and plane wave calculations may have big i/o demands. If you have several users trying to run large coupled-cluster calculations simultaneously, the performance will be poor since both are trying to use the limited i/o resources.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-06-04T00:21:30.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6092" PostTypeId="1" CreationDate="2021-06-04T12:00:03.180" Score="12" ViewCount="168" Body="&lt;p&gt;I am aware of software tools such as &lt;a href=&quot;https://github.com/hackingmaterials/atomate&quot; rel=&quot;noreferrer&quot;&gt;atomate&lt;/a&gt;, but that is quite specific to crystals. There are other equally specific workflows - I think we all have our own...&lt;/p&gt;&#xA;&lt;p&gt;What I am interested in is making my own database that stores solid, liquid and gas state properties. I don't need help with the workflow, or organizing the workflow, but I will say I use python to run all of the workflow.&lt;/p&gt;&#xA;&lt;p&gt;What I am after right now, is how do I save all of the outputs in a proper database form? Should I be using pandas and saving in an excel sheet, or saving in JSON?&lt;/p&gt;&#xA;&lt;p&gt;The general scheme is that I will be calculating properties for many molecules, for instance, crystal structures or liquid state free energies of solvation. Each molecule has several properties, and these will also be added too. Some properties are scalar i.e, free energy of solvation, but others may be lattice energy using B3LYP, or PBE0 etc, so I need to be able to store almost a dictionary, just for this one property.&lt;/p&gt;&#xA;&lt;p&gt;So I am a bit lost about an efficient means for storing all of this in a robust manner... JSON, pickle file, csv... store each molecule/structure as an independent file, or all together in one big file...&lt;/p&gt;&#xA;&lt;p&gt;Sometimes I will just want to look up the properties for 1 molecule, othertimes for an array. Sometimes I will want to perform calculations using an array, so it may be a nuisance to load 1000 individual files etc.&lt;/p&gt;&#xA;&lt;p&gt;For instance I see that atomate makes use of &lt;a href=&quot;https://www.mongodb.com/&quot; rel=&quot;noreferrer&quot;&gt;MongoDB&lt;/a&gt; as its database... is this a good route?&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="5" LastEditDate="2021-06-28T02:52:56.923" LastActivityDate="2021-06-28T02:52:56.923" Title="What are good protocols for creating a database based on python?" Tags="|python|databases|" AnswerCount="0" CommentCount="8" ClosedDate="2023-02-07T03:08:03.837" ContentLicense="CC BY-SA 4.0" />
  <row Id="6093" PostTypeId="2" ParentId="5090" CreationDate="2021-06-04T13:38:09.150" Score="10" Body="&lt;p&gt;This website &lt;a href=&quot;https://compmatphys.epotentia.com/courses/computational-materials-physics/&quot; rel=&quot;noreferrer&quot;&gt;CompMatPhys&lt;/a&gt; is an excellent starting point. It is free and self paced, and the videos are really good.&lt;/p&gt;&#xA;&lt;p&gt;It was linked by Jack, as an answer to a different question. I will find it and update and link to it as well so that Jack gets his due credit.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastActivityDate="2021-06-04T13:38:09.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6094" PostTypeId="2" ParentId="5028" CreationDate="2021-06-04T21:01:26.660" Score="5" Body="&lt;p&gt;The other answer is great and comes from a viewpoint of macroscopic plasticity. I'd just like to note that another perspective on plasticity exists, a multiscale view based on following atomistic mechanisms up through the length scales to aim for an understanding of plasticity that is increasingly based on physical mechanisms. The enormous range of length scales makes this a daunting task, and it's therefore still an area of active research.&lt;/p&gt;&#xA;&lt;p&gt;Much of the research focuses on the evolution of dislocation populations, as the motion of these defects controls the plasticity of metals in many cases. At the very smallest scales, molecular dynamics simulations have been used to study the motion of individual dislocation mechanisms and even some dislocation populations [1]. These are limited to a very high strain rate due to the small time steps required during the numerical integration of Newton's laws to describe the motion of atoms.&lt;/p&gt;&#xA;&lt;p&gt;At a higher length scale, dislocations can be represented as discrete objects [2] or as part of a continuum [3]. The behaviors of dislocation populations determined through these methods can give an idea of the stress-strain response for a single crystal. Often these rules of strength evolution at the slip system scale are then incorporated into the crystal plasticity finite element method, in which multiple grains of difference orientations and morphologies can be considered in a representative volume element to give a final, overall stress-strain curve [4]. (More commonly, crystal plasticity models are fit to an existing stress-strain curve, to be used only on the same material system.)&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, a multiscale approach does not give you a unified mathematical model to describe plasticity. There are important physics to consider at multiple length scales, and you'd have to incorporate an even wider variety of mechanisms if you want to predict failure. Most researchers recognize that all computational methods are compromises and choose the best tool to investigate their specific question. Cited are some recent papers on each topic, not necessarily the best review articles to start out with.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;[1] Zepeda-Ruiz, L. A.; Stukowski, A.; Oppelstrup, T.; Bertin, N.; Barton, N. R.; Freitas, R.; Bulatov, V. V. Atomistic Insights into Metal Hardening. Nat. Mater. 2020. &lt;a href=&quot;https://doi.org/10.1038/s41563-020-00815-1&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/s41563-020-00815-1&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;[2] Akhondzadeh, Sh.; Sills, R. B.; Bertin, N.; Cai, W. Dislocation Density-Based Plasticity Model from Massive Discrete Dislocation Dynamics Database. Journal of the Mechanics and Physics of Solids 2020, 145, 104152. &lt;a href=&quot;https://doi.org/10.1016/j.jmps.2020.104152&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.jmps.2020.104152&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;[3] Xu, S.; Smith, L.; Mianroodi, J. R.; Hunter, A.; Svendsen, B.; Beyerlein, I. J. A Comparison of Different Continuum Approaches in Modeling Mixed-Type Dislocations in Al. Modelling Simul. Mater. Sci. Eng. 2019, 27 (7), 074004. &lt;a href=&quot;https://doi.org/10.1088/1361-651X/ab2d16&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1088/1361-651X/ab2d16&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;[4] Nguyen, K.; Zhang, M.; Amores, V. J.; Sanz, M. A.; Montáns, F. J. Computational Modeling of Dislocation Slip Mechanisms in Crystal Plasticity: A Short Review. Crystals 2021, 11 (1), 42. &lt;a href=&quot;https://doi.org/10.3390/cryst11010042&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.3390/cryst11010042&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1180" LastActivityDate="2021-06-04T21:01:26.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6095" PostTypeId="1" CreationDate="2021-06-05T01:08:30.983" Score="7" ViewCount="123" Body="&lt;p&gt;I want to analyze a diffraction pattern. Py4dSTEM is asking for a datacube to start with. I thought it might be able to convert an image to this format:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;py4DSTEM.io.read('tinicu.png')&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I get this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Exception: Unrecognized file extension .png.  To force reading as a particular filetype, pass the 'ft' keyword argument.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since py4DSTEM doesn't seem to work directly with images, is there any software that can convert say a png (or any other common image format) to their datacube format?&lt;/p&gt;&#xA;&lt;p&gt;Then I tried:&#xA;&lt;code&gt;py4DSTEM.io.read('tinicu.png', ft='None')&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;And I get this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  if binfactor &amp;gt; 1:&#xA;     86         assert(mem!='MEMMAP'), &amp;quot;Error: binning is not supported for memory mapping.  Either set binfactor=1 or set mem='RAM'&amp;quot;&#xA;---&amp;gt; 87     assert(ft in [None,'dm','empad','mrc_relativity','gatan_K2_bin','kitware_counted']), &amp;quot;Error: ft argument not recognized&amp;quot;&#xA;     88 &#xA;     89     if ft is None:&#xA;&#xA;AssertionError: Error: ft argument not recognized&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3679" LastEditorUserId="7" LastEditDate="2021-06-23T22:18:04.243" LastActivityDate="2021-06-23T22:18:04.243" Title="Convert standard image file format to py4DSTEM datacube?" Tags="|python|software-assistance|electron-diffraction|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-29T19:56:37.207" ContentLicense="CC BY-SA 4.0" />
  <row Id="6096" PostTypeId="1" CreationDate="2021-06-05T04:53:58.377" Score="8" ViewCount="218" Body="&lt;p&gt;I tried using the python package diffsims.  I get an image, but not a diffraction pattern I was expecting.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from matplotlib.colors import Normalize&#xA;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;import diffsims&#xA;import diffpy&#xA;import difflib&#xA;from diffpy import structure&#xA;from diffsims import generators&#xA;&#xA;x='Si_mp_149_computed.cif'   #this file was generated using pymatgen, https://materialsproject.org/materials/mp-149/#&#xA;s= structure.loadStructure(x)&#xA;Beam=generators.diffraction_generator.DiffractionGenerator(accelerating_voltage=300)  #Instantiated an object in class Diffraction Generator&#xA;diffraction_pattern=Beam.calculate_ed_data(structure=s,reciprocal_radius =15, rotation=(0,0,0),with_direct_beam=False,max_excitation_error=0.01, \&#xA;    debye_waller_factors={})&#xA;dp= diffraction_pattern.get_diffraction_pattern(size=512, sigma=2)&#xA;&#xA;plt.imshow(dp)&#xA;plt.show()&#xA;&#xA;log_dp=np.log(dp)&#xA;plt.imshow(log_dp)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/shI2h.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/shI2h.png&quot; alt=&quot;Result from code&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3680" LastEditorUserId="5" LastEditDate="2021-09-21T22:48:33.133" LastActivityDate="2021-09-22T07:54:14.460" Title="What are open source options to simulate kinematical electron diffraction patterns?" Tags="|software-recommendations|python|open-source|electron-diffraction|diffsims|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6097" PostTypeId="1" AcceptedAnswerId="6100" CreationDate="2021-06-05T09:42:39.260" Score="13" ViewCount="1376" Body="&lt;p&gt;So I am super new, although I have gotten the hang of using DFT in Quantum Espresso. I am having a problem with running the calculation for 1.6 nm ZnSe quantum dot. I haven't even gotten to calculating bands and optical properties, my laptop did six iterations, and then windows crashed for geometrical optimization. So how do I know how much power is required and how much I have. &lt;br /&gt;&#xA;Plus, any suggestions for how I can do DFT calculations using my computer because the professor I am working with does not have access to a cluster(which he had, but he doesn't anymore due to some university politics).&lt;br /&gt;&#xA;So the best configuration I have is a gaming laptop(predator) Thankss&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2023-01-25T13:49:44.693" Title="How do we know how much computational power is required for a particular calculation?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6098" PostTypeId="5" CreationDate="2021-06-05T14:16:23.510" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-06-05T14:16:23.510" LastActivityDate="2021-06-05T14:16:23.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6099" PostTypeId="4" CreationDate="2021-06-05T14:16:23.510" Score="0" Body="Questions about the information collection from the atomic structure of materials using x-rays." OwnerUserId="20" LastEditorUserId="20" LastEditDate="2021-06-06T21:41:00.770" LastActivityDate="2021-06-06T21:41:00.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6100" PostTypeId="2" ParentId="6097" CreationDate="2021-06-05T15:39:39.843" Score="16" Body="&lt;p&gt;Computational power is a relatively vague term, and can include at least three dimensions: computational time, memory consumption, and disk usage. Under this definition, it's trivial to find out how much computational power you have. The following discusses how to find out how much computational power you &lt;em&gt;need&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Computational time&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The computational time of a method usually scales as a certain power of the system size (measured in the number of atoms, or better, the number of basis functions, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;). For plane wave-based DFT single-point calculations, the computational time scales as roughly &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt;. For atomic orbital-based DFT single-point calculations using pure functionals, the time scales as about &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt; for systems within a few tens of atoms, &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; for systems with a few tens to a few hundreds of atoms or so, and &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt; for systems with thousands of atoms. For hybrid functionals, the scaling for small systems increases to &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt;, while the remaining conclusions are unchanged. For programs that explicitly use linear-scaling techniques, the time scales as &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$N \log N$&lt;/span&gt; for systems with at least thousands of atoms. Note that these are quite general statements and may only approximately hold for a given software.&lt;/p&gt;&#xA;&lt;p&gt;The above properties can be used to estimate the run time of a given DFT calculation. To do this, you perform a calculation with a small system that is sufficiently similar to the actual system you intend to study, and use the same computational settings. The system must be small enough so that you can finish the computation without much cost, yet large enough (close enough to the size of the actual system) so that the scaling exponent can still be considered as a constant. Then you extrapolate your timing to your actual system size to estimate your expected computational time.&lt;/p&gt;&#xA;&lt;p&gt;Some caveats:&lt;/p&gt;&#xA;&lt;p&gt;(1) When your calculation involves iterations, the number of iterations required to reach convergence usually increases with system size, often linearly. For example, we have recently shown (&lt;a href=&quot;https://arxiv.org/abs/2105.00205&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/2105.00205&lt;/a&gt;) that at least for some systems, the number of SCF iterations increases linearly with system size, so while a single SCF iteration scales as &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt;, the total SCF time may scale as &lt;span class=&quot;math-container&quot;&gt;$N^{3.5}$&lt;/span&gt; (it's not &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt; because the linear scaling of SCF iteration number has a non-zero intercept). With geometry optimization the number of iterations similarly scales approximately linearly with system size, at least for some systems (see, e.g., &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4952956&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.4952956&lt;/a&gt;). So, for geometry optimizations please be prepared for a &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt;-ish dependence.&lt;/p&gt;&#xA;&lt;p&gt;(2) The computational time also scales as the -1st power with the number of CPU cores, until the number of cores approaches a certain number when the computational time is hardly dependent on the number of cores (&lt;a href=&quot;https://en.wikipedia.org/wiki/Amdahl%27s_law&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Amdahl%27s_law&lt;/a&gt;). The threshold number of the number of cores varies greatly from program to program, ranging from a few tens of cores to millions.&lt;/p&gt;&#xA;&lt;p&gt;(3) If your computation eats up all of your physical memory, and you instead rely on virtual memory, the scaling will skyrocket at that point, since virtual memory is much slower than physical memory. Beyond that point, the above estimation method fails.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Memory and disk&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Memory and disk usage also scale polynomially with respect to system size, at least for DFT calculations. In DFT calculations, both memory and disk usage scale quadratically with system size. You can then use exactly the same method to estimate how much memory and disk your actual calculation will use.&lt;/p&gt;&#xA;&lt;p&gt;Besides, since you are able to run your calculation till the point it crashes, it may be beneficial to analyze why it crashed, by analyzing the output file, monitoring CPU, memory and disk usage, etc.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-01-25T13:49:44.693" LastActivityDate="2023-01-25T13:49:44.693" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6101" PostTypeId="1" AcceptedAnswerId="6102" CreationDate="2021-06-05T18:44:48.237" Score="7" ViewCount="309" Body="&lt;p&gt;In the third chapter of &lt;a href=&quot;http://www.physics.iisc.ac.in/%7Eaveek_bid/wp-content/uploads/2019/07/Vanderbilt_ch-3.pdf&quot; rel=&quot;noreferrer&quot;&gt;Vanderbilt's book&lt;/a&gt;, they discuss the so-called multiband parallel transport and provide a scheme for numerical calculations that is similar to the single band case (where the Berry phase along a closed loop may be calculated using a discretized version of &lt;span class=&quot;math-container&quot;&gt;$-\text{Im ln} \langle \Phi_N | \Phi_0\rangle$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; are the start and ending points of the loop corresponding to the same Hamiltonian - eq 3.100 on pg 106).&lt;/p&gt;&#xA;&lt;p&gt;Now, consider the multiband case (described in pages 106 to 107), and which is usually applied to systems with point degeneracies somewhere. First, they consider two neighboring points &lt;span class=&quot;math-container&quot;&gt;$k_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_1$&lt;/span&gt;, choose a set of eigenvectors to define an overlap matrix with, and use the results of its singular value decomposition to generate a unitary rotation matrix that will rotate the eigenvector(s?) at the next point to be &amp;quot;optimally aligned&amp;quot;. Then they use a similar method to calculate the multiband Berry phase.&lt;/p&gt;&#xA;&lt;p&gt;I do not understand several definitions in the problem. For ease of answering, let's consider 3-band problem in 2D (with bands labeled A,B,C), where the energy dispersion is degenerate at some points on the BZ. For example, let bands A and B touch at &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;, and bands A,B,C touch at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Now I want to calculate the phase due to &lt;span class=&quot;math-container&quot;&gt;$\langle A_N | B_0\rangle$&lt;/span&gt;. But I am stumped in the definition of the overlap matrix in eq 3.102 (&lt;span class=&quot;math-container&quot;&gt;$\tilde{M}_{mn}^{k_0,k_1}=\langle \tilde{A_{k_0}} | B_{k_1}\rangle$&lt;/span&gt;). I am lost on what exactly to choose for &lt;span class=&quot;math-container&quot;&gt;$|A\rangle,|B\rangle$&lt;/span&gt;. It seems as if these are NOT single &lt;span class=&quot;math-container&quot;&gt;$3\times 1$&lt;/span&gt; column vectors, but more like matrices.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I become lost again in going from eq. 3.102 to eq. 3.105, because both the left hand side and the right hand side are concerning point &lt;span class=&quot;math-container&quot;&gt;$k_1$&lt;/span&gt;...&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Additionally, is the difference between eqs. 3.109 and 3.110 that the latter skips the SVD and rotation entirely?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally, I want to work up to calculating the single &amp;quot;multiband Berry phases&amp;quot;/&amp;quot;Wilson loop eigenvalues&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$\phi_m$&lt;/span&gt; in eq. 3.108. I do not know what these are in bra-ket notation. Are these analogous to the usual Berry connection integral? That is, does &lt;span class=&quot;math-container&quot;&gt;$\oint \langle A | dA\rangle \rightarrow \oint \langle A | dB\rangle$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;My end goal is that I want all my wavefunctions in the region of interest to have a smooth gauge (no discontinuities in phase), with the intention of exploring the quantities &lt;span class=&quot;math-container&quot;&gt;$\langle A | dB\rangle,\langle A | dC\rangle,\langle B | dC\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I asked a similar question for the everywhere-degenerate case here: &lt;a href=&quot;https://physics.stackexchange.com/questions/618989/numerically-calculating-non-abelian-berry-curvature-definition-of-multiplet-in&quot;&gt;https://physics.stackexchange.com/questions/618989/numerically-calculating-non-abelian-berry-curvature-definition-of-multiplet-in&lt;/a&gt;, but cannot seem to extrapolate from it.&#xA;Apologies for the several questions, but they all seem to stem from a basic confusion in definitions. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-06-07T04:03:09.277" Title="Help with Definitions in Numerical Calculation of Multiband Berry Phase" Tags="|condensed-matter|python|quantum-mechanics|topological-insulators|berry-phase|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6102" PostTypeId="2" ParentId="6101" CreationDate="2021-06-07T04:03:09.277" Score="7" Body="&lt;p&gt;Question 1. eq. 3.102 defines a matrix in &amp;quot;band-space&amp;quot;, e.g. it's NxN where N = number of bands being considered. The right hand side is a regular vector inner product for fixed m,n.&lt;/p&gt;&#xA;&lt;p&gt;The vectors on the right hand side are in any basis you want, so long as they span the same Kohn-Sham/band subspace.&lt;/p&gt;&#xA;&lt;p&gt;Question 2. I'm not sure where you're lost. You say,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;First, they consider two neighboring points 0 and 1, choose a set&#xA;of eigenvectors to define an overlap matrix with, and use the results&#xA;of its singular value decomposition to generate a unitary rotation&#xA;matrix that will rotate the eigenvector(s?) at the next point to be&#xA;&amp;quot;optimally aligned&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and that's exactly what's happening.&lt;/p&gt;&#xA;&lt;p&gt;Question 3.&#xA;Answer: Yes. It's an approximation as the text says. I could be completely wrong about this, but this approximation seems like it's related to the random phase approximation. The reason they make that approximation? I guess it's because it's easier to multiply N matrices first then take ln det of that, instead of factorizing N matrices, at least if you have a large number of bands you're dealing with.&lt;/p&gt;&#xA;&lt;p&gt;Question 4.&#xA;They define the phases in 3.108. The multiband generalization here necessarily involves a diagonalization of the &amp;quot;interband unitary&amp;quot; matrix in 3.106. I'm not sure what other bra-ket quantities you need. I'm not sure at all what you're asking about when you write &lt;span class=&quot;math-container&quot;&gt;$\oint \langle A | dA\rangle \rightarrow \oint \langle A | dB\rangle$&lt;/span&gt;, but hopefully my previous comments cleared this up.&lt;/p&gt;&#xA;" OwnerUserId="1303" LastActivityDate="2021-06-07T04:03:09.277" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6103" PostTypeId="1" CreationDate="2021-06-07T12:29:22.900" Score="7" ViewCount="68" Body="&lt;p&gt;What are the different ways that a molecule can be encoded into a vector? My answer to that question would employ machine learning but maybe there are other approaches, perhaps analytical, e.g., graph theoretical. Are there specific examples in scientific literature?&lt;/p&gt;&#xA;&lt;p&gt;Would it be possible to use a molecular vectorization in many-body quantum mechanics (effectively computational quantum mechanics)? A potential example that I can offer is to use a molecular vectorization to create a mapping to the eigenvectors in the eigenvalue problem in DFT.&lt;/p&gt;&#xA;" OwnerUserId="1907" LastEditorUserId="1907" LastEditDate="2021-06-07T13:59:57.303" LastActivityDate="2021-06-07T13:59:57.303" Title="Molecular Structure Vectorization for Computational Quantum Mechanics" Tags="|molecular-modeling|mathematical-modeling|" AnswerCount="0" CommentCount="4" ClosedDate="2021-11-19T01:41:44.020" ContentLicense="CC BY-SA 4.0" />
  <row Id="6104" PostTypeId="1" CreationDate="2021-06-07T19:23:34.697" Score="4" ViewCount="97" Body="&lt;p&gt;I am a physics student, and I am working on my final year project, I am planning to simulate polymers using cellular automata. I am really struggling with this project, if someone can give me any indications, I am going to be glad.&#xA;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="3694" LastEditorUserId="5" LastEditDate="2021-06-13T02:24:41.873" LastActivityDate="2021-06-13T18:10:39.343" Title="Simulating polymers using cellular automata?" Tags="|molecular-dynamics|monte-carlo|polymers|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6105" PostTypeId="1" CreationDate="2021-06-07T20:25:00.697" Score="3" ViewCount="93" Body="&lt;p&gt;I have a crystal structure, a B20 compound. I want to make an interface of that bulk compound with left and right-hand material. Is there any python code for writing such interfaces. or for writing super cell.&lt;/p&gt;&#xA;" OwnerUserId="1124" LastEditorUserId="5" LastEditDate="2021-06-08T20:49:19.983" LastActivityDate="2021-06-08T20:49:19.983" Title="How to make left and right handed material interface using python" Tags="|python|supercell|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6106" PostTypeId="1" AcceptedAnswerId="6243" CreationDate="2021-06-07T21:12:52.897" Score="13" ViewCount="387" Body="&lt;p&gt;I'd like to use a variety of Python tools (e.g., &lt;code&gt;matplotlib&lt;/code&gt; and &lt;code&gt;Mayavi&lt;/code&gt;) to analyze orbitals plot electron density contours, etc. Most of these expect to work on &lt;code&gt;numpy&lt;/code&gt; matrices.&lt;/p&gt;&#xA;&lt;p&gt;My ideal workflow would be something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import packageX&#xA;&#xA;molecule = packageX.read('file.molden')&#xA;# specify grid options&#xA;density = packageX.calculateDensity(molecule)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Are there Python packages that make it easy to calculate electron density, spin density, and orbitals on a &lt;code&gt;NumPy&lt;/code&gt; grid?&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-06-24T22:14:57.897" Title="Generating numpy-compatible electron density from Molden / QC calculation" Tags="|quantum-chemistry|software-recommendations|python|visualization-software|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6107" PostTypeId="1" CreationDate="2021-06-08T11:11:28.873" Score="11" ViewCount="328" Body="&lt;p&gt;I am trying to obtain the optical properties of ZnSe Quantum Dots, the problem is that my geometrical optimization is not converging. I used VESTA to create the structure(there is a photo in the attached file), and now I am using Quantum Espresso along with its GUI BURAI. I think there is something wrong with the input file, I have also tried to increase the cut off WF and cutoff energy but it still does not converge. And I also tried switching between &lt;em&gt;damped-md&lt;/em&gt; and &lt;em&gt;bfgs&lt;/em&gt; but still doesn't help.&lt;br /&gt;&#xA;For the input and convergence graph(the output file is super big and I don't think it will be that useful)along with the structure, everything is given  below, &lt;br /&gt;&#xA;&lt;strong&gt;Input file&lt;/strong&gt; -&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation = &amp;quot;relax&amp;quot;&#xA;forc_conv_thr = 1.00000e-02&#xA;max_seconds = 1.72800e+05&#xA;nstep = 100&#xA;pseudo_dir = &amp;quot;C:\Users\aman\.burai\.pseudopot&amp;quot;&#xA;/&#xA;&amp;amp;SYSTEM&#xA;a = 2.50000e+01&#xA;degauss = 1.00000e-02&#xA;ecutrho = 2.25000e+02&#xA;ecutwfc = 2.50000e+01&#xA;ibrav = 1&#xA;nat = 41&#xA;ntyp = 2&#xA;occupations = &amp;quot;fixed&amp;quot;&#xA;smearing = &amp;quot;gaussian&amp;quot;&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;conv_thr = 1.00000e-04&#xA;electron_maxstep = 200&#xA;mixing_beta = 7.00000e-01&#xA;startingpot = &amp;quot;atomic&amp;quot;&#xA;startingwfc = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;ion_dynamics = &amp;quot;damp&amp;quot;&#xA;/&#xA;&amp;amp;CELL&#xA;/&#xA;K_POINTS {gamma}&#xA;ATOMIC_SPECIES&#xA;Zn 65.39000 Zn.pbe-van.UPF&#xA;Se 78.96000 Se.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn 9.907807 12.921427 10.192708&#xA;Zn 9.907807 10.050257 13.063878&#xA;Zn 12.778977 10.050257 10.192708&#xA;Zn 15.650147 12.921427 10.192708&#xA;Zn 9.907807 15.792597 13.063878&#xA;Zn 15.650147 10.050257 13.063878&#xA;Zn 15.650147 12.921427 15.935048&#xA;Zn 15.650147 15.792597 13.063878&#xA;Zn 12.778977 15.792597 15.935048&#xA;Zn 12.778977 12.921427 13.063878&#xA;Zn 12.778977 10.050257 15.935048&#xA;Zn 12.778977 15.792597 10.192708&#xA;Zn 9.907807 12.921427 15.935048&#xA;Se 14.214562 11.485842 8.757123&#xA;Se 8.472222 14.357012 11.628293&#xA;Se 11.343392 8.614672 14.499463&#xA;Se 17.085732 11.485842 11.628293&#xA;Se 11.343392 14.357012 8.757123&#xA;Se 14.214562 14.357012 17.370633&#xA;Se 14.214562 11.485842 14.499463&#xA;Se 11.343392 14.357012 14.499463&#xA;Se 14.214562 14.357012 11.628293&#xA;Se 17.085732 14.357012 14.499463&#xA;Se 14.214562 17.228182 14.499463&#xA;Se 11.343392 11.485842 17.370633&#xA;Se 11.343392 17.228182 11.628293&#xA;Se 8.472222 11.485842 8.757123&#xA;Se 17.085732 11.485842 17.370633&#xA;Se 17.085732 14.357012 8.757123&#xA;Se 8.472222 14.357012 17.370633&#xA;Se 11.343392 11.485842 11.628293&#xA;Se 14.214562 8.614672 11.628293&#xA;Se 8.472222 11.485842 14.499463&#xA;Se 11.343392 8.614672 8.757123&#xA;Se 11.343392 17.228182 17.370633&#xA;Se 14.214562 8.614672 17.370633&#xA;Se 14.214562 17.228182 8.757123&#xA;Se 17.085732 8.614672 14.499463&#xA;Se 8.472222 17.228182 14.499463&#xA;Se 17.085732 17.228182 11.628293&#xA;Se 8.472222 8.614672 11.628293&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Convergence graph&lt;/strong&gt; - &lt;a href=&quot;https://i.stack.imgur.com/5mfHp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5mfHp.png&quot; alt=&quot;Total Energy per iteration&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Structure&lt;/strong&gt; - &lt;a href=&quot;https://i.stack.imgur.com/1LQVY.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1LQVY.png&quot; alt=&quot;Structure of the Quantum Dot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2021-06-08T17:16:51.793" LastActivityDate="2021-06-09T15:49:14.397" Title="Geometrical Optimization not converging, where am I going wrong?" Tags="|density-functional-theory|quantum-espresso|quantum-dots|energy-conversion|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="6108" PostTypeId="2" ParentId="5083" CreationDate="2021-06-08T16:44:32.437" Score="4" Body="&lt;p&gt;While this is not a direct answer, it might hopefully offer some inspiration from a neighbouring field.&lt;/p&gt;&#xA;&lt;p&gt;It turns out that there is something called &lt;a href=&quot;https://en.wikipedia.org/wiki/Nucleic_acid_thermodynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;DNA melting&lt;/a&gt;. The &lt;strong&gt;DNA melting temperature&lt;/strong&gt; is defined as the temperature at which half of the DNA strands are in the random coil or single-stranded state. While not at all a true melting temperature in the conventional sense, it bears a couple of key resemblances. First, like the melting point of solids (metals, in your case), this is a thermodynamical compromise between entropy and enthalpy. Second, like the melting point of solids, these terms can be estimated computationally by considering interatomic interactions, and this is non-trivial. So maybe there is something to be learned of how people from that field have been dealing with this problem that, for them, is of great practical importance.&lt;/p&gt;&#xA;&lt;p&gt;Here is where (hopefully) the inspiration comes in: Leber et al, &amp;quot;&lt;a href=&quot;https://doi.org/10.1093/bioinformatics/bti379&quot; rel=&quot;nofollow noreferrer&quot;&gt;A fractional programming approach to efficient DNA melting temperature calculation&lt;/a&gt;&amp;quot;, &lt;em&gt;Bioinformatics&lt;/em&gt; 2005, 21, 2375–2382.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Results: As the melting temperature can be expressed as a fraction in terms of enthalpy and entropy differences of the corresponding annealing reaction, we propose to use a fractional programming algorithm, the Dinkelbach algorithm, to solve the problem. To calculate the required differences of enthalpy and entropy, the Nearest Neighbor model is applied. Using this model, the substeps of the Dinkelbach algorithm[1] in our problem setting turn out to be calculations of alignments which optimize an additive score function. Thus, the usual dynamic programming techniques can be applied. The result is an efficient algorithm to determine melting temperatures of two DNA strands, suitable for large-scale applications such as primer or probe design.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;We can also see at least one instance of people employing LAMMPS to deal with DNA melting: Svaneborg, &amp;quot;&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2012.03.005&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS framework for dynamic bonding and an application modeling DNA&lt;/a&gt;&amp;quot;, &lt;em&gt;Computer Physics Communications&lt;/em&gt; 2012, 183, 1793-1802 So maybe there is a path forward? If you have a way of estimating enthalpy and entropy for small chunks of your fcc metal as a function of pressure, perhaps this approach can lead you somewhere.&lt;/p&gt;&#xA;&lt;p&gt;[1] For more on the Dinkelbach's algorithm: You et al, &amp;quot;&lt;a href=&quot;https://doi.org/10.1016/j.compchemeng.2009.05.014&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dinkelbach's algorithm as an efficient method to solve a class of MINLP models for large-scale cyclic scheduling problems&lt;/a&gt;&amp;quot; &lt;em&gt;Computers &amp;amp; Chemical Engineering&lt;/em&gt; 2009, 33, 1879-1889.&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2021-06-08T16:44:32.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6109" PostTypeId="2" ParentId="6105" CreationDate="2021-06-08T19:40:38.567" Score="4" Body="&lt;h3&gt;CIF2Cell&lt;/h3&gt;&#xA;&lt;p&gt;(only about generating supercells)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;CIF2Cell is a tool to generate the geometrical setup for various electronic structure codes from a CIF (Crystallographic Information Framework) file. The program currently supports output for a number of popular electronic structure programs, including ABINIT, ASE, CASTEP, CP2K, CPMD, CRYSTAL09, Elk, EMTO, Exciting, Fleur, FHI-aims, Hutsepot, MOPAC, Quantum Espresso, RSPt, Siesta, SPR-KKR, VASP. Also exports some related formats like .coo, .cfg and .xyz-files. The program has been published in Computer Physics Communications 182 (2011) 1183–1186. Please cite generously.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can download the code:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Using &lt;a href=&quot;https://pypi.org/project/cif2cell/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pip&lt;/a&gt;: &lt;code&gt;pip install cif2cell&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;From SourceForge: &lt;a href=&quot;https://sourceforge.net/projects/cif2cell/files/latest/download&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://sourceforge.net/projects/cif2cell/files/latest/download&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-06-08T19:40:38.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6110" PostTypeId="1" AcceptedAnswerId="6116" CreationDate="2021-06-09T10:22:34.010" Score="8" ViewCount="148" Body="&lt;p&gt;Can NCI[1] index plots be generated starting from psi4? I'd be happy to just generate the NCI index values and mesh the isosurface myself.&lt;/p&gt;&#xA;&lt;p&gt;With a long-term goal to visualise various medicinal-chemistry interactions with quantum chemical detail, it seems like the NCI index is the simplest starting point since it relies on just the electron density. Electron density can be generated using psi4 by outputting a cube file, or by querying the wave function at various points - which is how a cube file would be generated anyway.&lt;/p&gt;&#xA;&lt;p&gt;How can one go from density to NCI index value? The second ingredient of NCI index is the reduced gradient, which might be obtained empirically with &lt;code&gt;np.gradient&lt;/code&gt; on the density. The final ingredient is the second eigenvalue of the Hessian of the electron density at each evaluated point. However &lt;code&gt;psi4&lt;/code&gt; tells me Hessians aren't available for any functional or basis set I've tried (same thing happens with dimers):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import psi4&#xA;h2o = psi4.geometry(&amp;quot;&amp;quot;&amp;quot;&#xA;O&#xA;H 1 0.96&#xA;H 1 0.96 2 104.5&#xA;&amp;quot;&amp;quot;&amp;quot;)&#xA;&#xA;nrg, wfn = psi4.energy('scf/cc-pVDZ', return_wfn=True)&#xA;wfn.compute_hessian()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RuntimeError: &#xA;Fatal Error: Analytic Hessians are not available for this wavefunction.&#xA;Error occurred in file: /Users/github/builds/conda-builds/psi4-multiout_1557977521159/work/psi4/src/psi4/libmints/wavefunction.h on line: 321&#xA;The most recent 5 function calls were:&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Alternatively the Hessian just describes the second derivative, so would calling &lt;code&gt;np.gradient&lt;/code&gt; twice on the density be equivalent? Still, the Hessian at a single grid point is just three numbers - i.e. a 1d array, which has no eigenvalue.&lt;/p&gt;&#xA;&lt;p&gt;Any tips here appreciated.&lt;/p&gt;&#xA;&lt;p&gt;[1] Revealing Noncovalent Interactions, Johnson et al &lt;a href=&quot;https://doi.org/10.1021/ja100936w&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/ja100936w&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="7" LastEditDate="2021-11-01T16:57:51.437" LastActivityDate="2021-11-01T16:57:51.437" Title="Can the NCI (noncovalent interaction) index be generated starting with psi4?" Tags="|density-functional-theory|intermolecular-forces|molecular-interactions|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6111" PostTypeId="2" ParentId="6107" CreationDate="2021-06-09T15:49:14.397" Score="5" Body="&lt;p&gt;Where was I going wrong- the quantum dot structure was not neutral. Thanks to @AnoopANair, I was able to find the problem. For anyone having a similar problem look at this video - &lt;a href=&quot;https://www.youtube.com/watch?v=KxO5uLsvkRE%5C&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=KxO5uLsvkRE\&lt;/a&gt;&#xA;I have also used 6 Hydrogen atoms which are there to neutralize the extra charge. &lt;a href=&quot;https://i.stack.imgur.com/11B9m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/11B9m.png&quot; alt=&quot;ZnSe quantum dot&quot; /&gt;&lt;/a&gt; My new quantum dot looks like this. I Hope, this helps anyone with a similar issue.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2021-06-09T15:49:14.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6112" PostTypeId="1" CreationDate="2021-06-04T10:45:34.033" Score="10" ViewCount="826" Body="&lt;p&gt;I'm trying to reproduce some results from a &lt;a href=&quot;https://arxiv.org/pdf/1809.02723.pdf&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; with fchk output files containing DFT calculations. The paper details how to produce the 3D electron density using Gaussian software, but since I don't have access to the software I have been looking around various Python packages that could accomplish the same task. I tried Open Babel but got an error message &amp;quot;The molecule has no grid&amp;quot; which I assume is due to the fact that I haven't to specify the grid structure for output — not sure how to do this either.&lt;/p&gt;&#xA;&lt;p&gt;Is there a good Python code or other tools I could use to get the 3D density?&lt;/p&gt;&#xA;" OwnerUserId="3735" OwnerDisplayName="cassandra" LastEditorUserId="5" LastEditDate="2021-06-09T17:28:42.210" LastActivityDate="2021-06-11T19:40:15.107" Title="How do you generate 3D electron density from fchk file without the Gaussian software?" Tags="|software|quantum-chemistry|multiwfn|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6113" PostTypeId="5" CreationDate="2021-06-09T17:29:17.637" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-09T17:29:17.637" LastActivityDate="2021-06-09T17:29:17.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6114" PostTypeId="4" CreationDate="2021-06-09T17:29:17.637" Score="0" Body="Questions about the Multiwfn software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-09T17:29:17.637" LastActivityDate="2021-06-09T17:29:17.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6115" PostTypeId="1" AcceptedAnswerId="6117" CreationDate="2021-06-09T19:30:42.387" Score="10" ViewCount="236" Body="&lt;p&gt;I am not a chemist, but I know how to use AMDock to predict the binding affinity of a small molecule to a protein.&lt;/p&gt;&#xA;&lt;p&gt;There is a particular target for which AMDock Vina, with its default force fields, predicts that certain molecules will dock very well. But the follow-up experiments do not show any activity.&lt;/p&gt;&#xA;&lt;p&gt;I have read a comment that it is possible to use experimental data to customise the force field in AMDock Vina. I would like to use the data from the experiments to customise the force fields that Vina is using. But I cannot find any good documentation on the subject.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone please point me to some resources?&lt;/p&gt;&#xA;" OwnerUserId="3719" LastEditorUserId="3719" LastEditDate="2021-06-10T15:14:46.677" LastActivityDate="2021-06-10T15:14:46.677" Title="Are there good tutorials that explain how to use experimental data to customise the force field in AMDock Vina?" Tags="|docking|forcefields|intermolecular-forces|autodock|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6116" PostTypeId="2" ParentId="6110" CreationDate="2021-06-09T20:22:34.797" Score="7" Body="&lt;p&gt;Not a full answer of an alternative program, but just collecting the conclusions from the comments along with some additional suggestions.&lt;/p&gt;&#xA;&lt;p&gt;It appears that &lt;code&gt;compute_gradient&lt;/code&gt; and &lt;code&gt;compute_hessian&lt;/code&gt; aren't implemented yet for wavefunction objects in Psi4. Even still, what you are interested in is the density and its gradient/hessian rather than those of the wavefunction itself.&lt;/p&gt;&#xA;&lt;p&gt;Psi4 can generate a cube file of the density, which can be done by changing the last several lines of your input to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;psi4.set_options({&amp;quot;cubeprop_tasks&amp;quot;: [&amp;quot;density&amp;quot;]})&#xA;&#xA;E, wfn = psi4.energy('scf', return_wfn=True)&#xA;psi4.cubeprop(wfn)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Other &lt;a href=&quot;https://psicode.org/psi4manual/1.3.2/cubeprop.html&quot; rel=&quot;noreferrer&quot;&gt;cube file options&lt;/a&gt;, such as the spacing or overall range of points to include, are specified in the same way.&lt;/p&gt;&#xA;&lt;p&gt;You should be able to readily extract the values to an (N,N,N) numpy array once you know the &lt;a href=&quot;http://paulbourke.net/dataformats/cube/&quot; rel=&quot;noreferrer&quot;&gt;Cube format&lt;/a&gt;. From here, you can calculate the gradient and hessian using&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grad=np.gradient(density,spacing)&#xA;hess=np.array([np.gradient(grad[i],spacing) for i in range(2)])&#xA;h_eigs=[]&#xA;for i in range(N):&#xA;    for j in range(N): &#xA;        for k in range(N):&#xA;            h=hess[:,:,i,j,k]&#xA;            h_eigs.append(np.eig(h)[0]) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which will give you a (3,N,N,N) array and a (3,3,N,N,N) array respectively. The code for the Hessian looks different because &lt;code&gt;np.gradient&lt;/code&gt; assumes all axes of the array are variables of your functions, so just doing &lt;code&gt;np.gradient(grad)&lt;/code&gt; would give you a (4,3,N,N,N) array.&lt;/p&gt;&#xA;&lt;p&gt;The last step is getting the eigenvalues of the hessian matrix at each point in space. There is probably a better way to arrange this within numpy, but this gets across the concept that you need to iterate through every grid point and collect the eigenvalues.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-09T20:37:58.463" LastActivityDate="2021-06-09T20:37:58.463" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6117" PostTypeId="2" ParentId="6115" CreationDate="2021-06-09T21:56:20.430" Score="8" Body="&lt;p&gt;Changing the force field parameters is not a good/recommended approach. This is due to the high number of parameters you have to know. Many of them, you cannot obtain from experimental data. Instead, you will need high precision methods like Density Functional Theory, Hartree-Fock, pos Hartree-Fock or semi-empirical methods to calculate them for two, three and four atoms sets.&lt;/p&gt;&#xA;&lt;p&gt;One thing that affects more the quality of the results is the score function used by the docking software instead the fore field.&lt;/p&gt;&#xA;&lt;p&gt;My recommendations are two:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Move to another docking software, like PLANTS, GOLD, GLIDE, etc.&lt;/li&gt;&#xA;&lt;li&gt;Do the docking with the program you want and them do a re-score in place using a better scoring function like ChemPLP (from PLANTS), X-SCORE (empirical scoring function) or DLSCORE (deep learning based).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-06-09T21:56:20.430" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6119" PostTypeId="2" ParentId="5083" CreationDate="2021-06-10T16:18:42.070" Score="6" Body="&lt;p&gt;I'm not an expert in this area, but I think there are currently several approaches to this, none of them undisputed. Maybe this recent paper that tests a few of those methods will provide some ideas/references for you:&lt;/p&gt;&#xA;&lt;p&gt;Zou, Y.; Xiang, S.; Dai, C. Investigation on the Efficiency and Accuracy of Methods for Calculating Melting Temperature by Molecular Dynamics Simulation. Computational Materials Science 2020, 171, 109156. &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2019.109156&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.commatsci.2019.109156&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To be honest, of the methods presented in the above paper, I've only heard of the two-phase method, where you split the simulation cell by adding a solid-liquid interface in the middle. Then using an NPH ensemble, you test a guess melting temperature and see how two phases respond. The NPH ensemble will result in a temperature change towards the actual melting temperature, so you can iterate to a good approximation of the melting temperature predicted by your interatomic potential. However, it seems like this would result in the pressure issue that your Frenkel paper discusses.&lt;/p&gt;&#xA;&lt;p&gt;I'm unfamiliar with parallel tempering; I hope someone else can address that and the LAMMPS-specific parts of your question.&lt;/p&gt;&#xA;" OwnerUserId="1180" LastActivityDate="2021-06-10T16:18:42.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6120" PostTypeId="2" ParentId="5090" CreationDate="2021-06-10T17:32:46.383" Score="5" Body="&lt;h3&gt;Title: Electronic Structure Calculations for Solids and Molecules&lt;/h3&gt;&#xA;&lt;p&gt;Author: Jorge Kohanoff&lt;br /&gt;&#xA;Year: 2006&lt;br /&gt;&#xA;ISBN: 9780521815918&lt;br /&gt;&#xA;Link: &lt;a href=&quot;http://www.cambridge.org/9780521815918&quot; rel=&quot;noreferrer&quot;&gt;http://www.cambridge.org/9780521815918&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Description:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Electronic structure problems are studied in condensed matter physics and theoretical chemistry to provide important insights into the properties of matter. This 2006 graduate textbook describes the main theoretical approaches and computational techniques, from the simplest approximations to the most sophisticated methods. It starts with a detailed description of the various theoretical approaches to calculating the electronic structure of solids and molecules, including density-functional theory and chemical methods based on Hartree-Fock theory. The basic approximations are thoroughly discussed, and an in-depth overview of recent advances and alternative approaches in DFT is given. The second part discusses the different practical methods used to solve the electronic structure problem computationally, for both DFT and Hartree-Fock approaches. Adopting a unique and open approach, this textbook is aimed at graduate students in physics and chemistry, and is intended to improve communication between these communities. It also serves as a reference for researchers entering the field.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Content:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Preface&lt;/li&gt;&#xA;&lt;li&gt;List of symbols&lt;/li&gt;&#xA;&lt;li&gt;List of acronyms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Part I. Theory:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The problem of the structure of matter&lt;/li&gt;&#xA;&lt;li&gt;The electronic problem&lt;/li&gt;&#xA;&lt;li&gt;Quantum many-body theory: chemical approaches&lt;/li&gt;&#xA;&lt;li&gt;Density function theory&lt;/li&gt;&#xA;&lt;li&gt;Exchange and correlation in DFT: approximation and their performance&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Part II. Computational Methods:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;6&quot;&gt;&#xA;&lt;li&gt;Solving the electronic problem in practice&lt;/li&gt;&#xA;&lt;li&gt;Atomic pseudopotentials&lt;/li&gt;&#xA;&lt;li&gt;Basis sets&lt;/li&gt;&#xA;&lt;li&gt;Electronic structure methods&lt;/li&gt;&#xA;&lt;li&gt;Simplified approaches to the electronic problem&lt;/li&gt;&#xA;&lt;li&gt;Diagonalization and electronic self-consistency&lt;/li&gt;&#xA;&lt;li&gt;First-principles molecular dynamics (Car-Parrinello)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Index.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/DnSUv.jpg&quot; height=&quot;350&quot;&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-06-10T17:32:46.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6121" PostTypeId="2" ParentId="6112" CreationDate="2021-06-10T23:46:08.890" Score="4" Body="&lt;p&gt;If you need to generate &lt;strong&gt;fchk&lt;/strong&gt; files for other molecules, note that you can do this with a variety of quantum chemistry programs. In addition to Gaussian, also Q-Chem, Psi4, and my ERKALE program can do this for you, the last two being freely available open-source programs.&lt;/p&gt;&#xA;&lt;p&gt;For generating grid data from a &lt;strong&gt;fchk&lt;/strong&gt; file, there is again a number of packages available for this purpose; e.g. my ERKALE program has a special tool for generating cube files but I am sure many others do as well; e.g. IQmol and Avogadro can both be used to visualize e.g. molecular orbital and electron densities directly from fchk files.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-06-10T23:46:08.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6122" PostTypeId="2" ParentId="6110" CreationDate="2021-06-11T00:07:01.750" Score="7" Body="&lt;p&gt;If you call &lt;code&gt;wfn.compute_hessian()&lt;/code&gt;, Psi4 tries to compute the nuclear Hessian which is indeed not implemented for most methods.&lt;/p&gt;&#xA;&lt;p&gt;Calling &lt;code&gt;np.gradient&lt;/code&gt; is not advisable, as it merely computes finite-difference approximations of derivatives instead of the true derivative. This is especially going to be a problem for cube files, since the resolution is poor from the beginning. A much better alternative is to compute the matrix of second derivatives analytically; this code exists in Psi4 as it is necessary for e.g. the calculation of DFT forces with GGA functionals.&lt;/p&gt;&#xA;&lt;p&gt;The electron density is given in the basis set as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n({\bf r}) = \sum_{\mu \nu} P_{\mu\nu} \chi_\mu({\bf r}) \chi_\nu({\bf r})$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\chi_\mu$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;:th basis function and &lt;span class=&quot;math-container&quot;&gt;${\mathbf P}$&lt;/span&gt; is the density matrix.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;:th component of the density gradient is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$  \partial_j n({\bf r}) = \sum_{\mu \nu} P_{\mu\nu} \left[ \chi_\mu({\bf r}) \{\partial_j \chi_\nu({\bf r})\} + \{\partial_j \chi_\mu({\bf r})\} \chi_\nu({\bf r})\right] $$&lt;/span&gt;&#xA;The &lt;span class=&quot;math-container&quot;&gt;$i,j$&lt;/span&gt; element of the density Hessian is then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \partial_i \partial_j n({\bf r}) = \sum_{\mu \nu} P_{\mu\nu}  \left[ 2 \{\partial_i \chi_\mu({\bf r})\} \{\partial_j \chi_\nu({\bf r})\} + \{\partial_i \partial_j \chi_\mu({\bf r})\} \chi_\nu({\bf r}) + \{\partial_i \partial_j \chi_\nu({\bf r})\} \chi_\mu({\bf r}) \right] $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can get the alpha and beta density matrices with &lt;code&gt;wfn.Da()&lt;/code&gt; and &lt;code&gt;wfn.Db()&lt;/code&gt;; I'm not sure how to evaluate the basis functions, their gradients and laplacians.&lt;/p&gt;&#xA;&lt;p&gt;In PySCF you can access the density matrix as &lt;code&gt;dm = mf.make_rdm1()&lt;/code&gt; and get the values of the basis functions with the &lt;code&gt;numint.eval_ao()&lt;/code&gt; function.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-06-13T13:32:02.533" LastActivityDate="2021-06-13T13:32:02.533" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6123" PostTypeId="2" ParentId="3911" CreationDate="2021-06-11T15:13:32.580" Score="11" Body="&lt;p&gt;I am the author of Chemcraft. Your job contains a 2-dimensional PES scan, and currently Chemcraft can visualize only 1-dimensional scans. I plan to implement support of 2d scans in future. It is unclear for me (please give me some advice), in what form should these scans be visualized: colored map, or 3-d surface which can be rotated, or simply the possibility to export all data in text format into other program which supports visualization of such graphs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;: A new version of Chemcraft, which can build 3d graphs, is released and can be downloaded here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chemcraftprog.com/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://chemcraftprog.com/download.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3745" LastEditorUserId="3745" LastEditDate="2021-07-22T15:55:16.010" LastActivityDate="2021-07-22T15:55:16.010" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6124" PostTypeId="2" ParentId="1615" CreationDate="2021-06-11T18:28:23.043" Score="2" Body="&lt;p&gt;As far as I know, and read &lt;a href=&quot;https://matmatch.com/learn/property/isotropy-anisotropy&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, metallic glasses akin to crystalline metals are &lt;strong&gt;isotropic&lt;/strong&gt;. To this end, if we use the script provided in the examples of LAMMPS, to what extent we can secure the results that we want, i.e Poisson Ratio, Young's modulus, etc.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;sub&gt;Note: This was an answer written originally by the person that asked the question, but since that user deleted the question, it seems we need to re-post the answer in order for the answer to exit the unanswered queue.&lt;/sub&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-11T18:28:23.043" CommentCount="0" CommunityOwnedDate="2021-06-11T18:28:23.043" ContentLicense="CC BY-SA 4.0" />
  <row Id="6125" PostTypeId="2" ParentId="6112" CreationDate="2021-06-11T18:58:08.157" Score="7" Body="&lt;p&gt;The other answers have already covered how to generate the formatted checkpoint file (.fchk). So in my answer I will attempt to explain how to use Multiwfn to get the electron densities from the .fchk file.&lt;/p&gt;&#xA;&lt;p&gt;First, download the software from &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;Then open the MultiWfn executable, and either type in the name of the &lt;code&gt;.fchk&lt;/code&gt; file and press enter, or press enter and then open the file through the GUI file selection interface.&lt;/p&gt;&#xA;&lt;p&gt;If the file is loaded successfully, it should give you the message &lt;code&gt;Loaded &amp;lt;filename&amp;gt; successfully!&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then from the Main function menu, selection option &lt;code&gt;5&lt;/code&gt; and press enter:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/29y3t.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/29y3t.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This option is for calculating parameters that have to be calculated on a 3D grid.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XCari.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XCari.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then select option &lt;code&gt;1&lt;/code&gt; for electron density. Then the program will ask you for the size of the grid required.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QkNwH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QkNwH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can choose one of the inbuilt defaults (low, medium, or high quality grids). Note that grids with more points will take a longer calculation time. The paper you mentioned in the question has used a &lt;span class=&quot;math-container&quot;&gt;$256\times 256\times 256$&lt;/span&gt; grid with a step size of &lt;span class=&quot;math-container&quot;&gt;$0.1$&lt;/span&gt; Bohr.&lt;/p&gt;&#xA;&lt;p&gt;If I have understood everything correctly (and I am not sure), then this is difficult to do in Multiwfn. Because in Multiwfn, you can either set the total number of grid points in each direction, &lt;strong&gt;or&lt;/strong&gt; you can set the step size. This is because the program usually uses an extension distance (&lt;span class=&quot;math-container&quot;&gt;$6.0$&lt;/span&gt; Bohr by default) to generate the grid. If you want to change both the number of grid points and the step size, then you might have to do some math to determine what would be the extension distance. You could try the options &lt;code&gt;5&lt;/code&gt; to &lt;code&gt;10&lt;/code&gt; and see if they work.&lt;/p&gt;&#xA;&lt;p&gt;After setting the grid size, press enter, and the program will calculate the electron density of the file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8kuDh.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8kuDh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can press &lt;code&gt;-1&lt;/code&gt; to see the isosurface graph. Select option &lt;code&gt;2&lt;/code&gt; to save the electron density as a cube file in the folder (by default it saves the file as &lt;code&gt;density.cub&lt;/code&gt;. And that's the cube file you need.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;However, in the paper, they use &lt;code&gt;cubman&lt;/code&gt; utility of Gaussian to get the difference in the electron densities between two cube files (for the same molecule calculated with different methods). Multiwfn can also do this.&lt;/p&gt;&#xA;&lt;p&gt;It doesn't need to be said that the two cube files must have the same molecule and the exact same grid parameters, otherwise the calculation wouldn't run.&lt;/p&gt;&#xA;&lt;p&gt;So, you need two cube files in the folder, like &lt;code&gt;density1.cub&lt;/code&gt; and &lt;code&gt;density2.cub&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Open Multiwfn and open one cube file. Select option &lt;code&gt;13&lt;/code&gt; i.e. &amp;quot;Process grid data&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/djnL3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/djnL3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then select &lt;code&gt;11&lt;/code&gt; for &amp;quot;Grid data calculation&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bD2F0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bD2F0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then you will be to see options for subtracting a grid file from the current grid file. (I believe the subtraction option is the one which is required, but I am not entirely sure about how Gaussian's &lt;code&gt;cubman&lt;/code&gt; works, and how cube files store data, so please check if it's a simple subtract or a square subtract)&lt;/p&gt;&#xA;&lt;p&gt;Select &lt;code&gt;4&lt;/code&gt; to subtract a grid file. The program will ask you for the other grid file. (Note that which is subtracted from which depends on which file you loaded first)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mg3Vm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mg3Vm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, you have to type in the name of the other cube file, say &lt;code&gt;density2.cub&lt;/code&gt;. Press enter, and if the calculation was successful, then you will see the message &lt;code&gt;Done, grid data has been updated&lt;/code&gt;. If the grid sizes are different it will throw an error.&lt;/p&gt;&#xA;&lt;p&gt;Then press &lt;code&gt;0&lt;/code&gt; to save the current grid data to a cube file. Enter the name of the new file, and the difference in electron densities will be saved to that. In the paper the researchers did some further calculations from this point using their own C++ programs.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The advantage of this method is that this isn't restricted to just &lt;code&gt;.fchk&lt;/code&gt; files from Gaussian. Multiwfn can open output files from many other programs like GAMESS, Orca etc. So, you can use the output of those programs to do this calculation. Note that the program needs the full SCF solution and the basis set data to calculate the density so those need to be in the file that you are opening.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-11T19:40:15.107" LastActivityDate="2021-06-11T19:40:15.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6126" PostTypeId="1" AcceptedAnswerId="6213" CreationDate="2021-06-11T23:15:31.707" Score="7" ViewCount="1753" Body="&lt;p&gt;I have been using BURAI GUI for Quantum ESPRESSO for the calculation of optical properties of ZnSe. While running calculations I observed that my laptop's GPU was not even being used and I am a bit confused. I am currently using a gaming laptop, predator which has 4 cores, 8 logical processes, and 2 GPUs (Intel and Nvidia), 16GB RAM and a few other specifications (it's not even comparable to a cluster but it is the best I have at the moment). How do I utilize my GPUs for better and faster computations?&lt;/p&gt;&#xA;&lt;p&gt;Thanks, this forum has been one of the most helpful things over the past couple of days.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-06-11T23:32:25.000" LastActivityDate="2021-06-22T00:55:56.183" Title="Running Quantum ESPRESSO on a GPU in Windows" Tags="|quantum-espresso|high-performance-computing|graphical-processing-unit|windows-operating-system|" AnswerCount="1" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="6127" PostTypeId="1" CreationDate="2021-06-11T23:23:39.233" Score="9" ViewCount="961" Body="&lt;p&gt;I have been using BURAI GUI of Quantum ESPRESSO to calculate the optical properties of ZnSe quantum dots. But first I wanted to calculate the electronic band structure. After running the calculation for about 14 hours it stopped after giving me an error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Band Structure Calculation&#xA;     Davidson diagonalization with overlap&#xA;&#xA;job aborted:&#xA;[ranks] message&#xA;&#xA;[0-1] terminated&#xA;&#xA;[2] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 2&#xA;&#xA;[3-5] terminated&#xA;&#xA;[6] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 6&#xA;&#xA;[7] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 7&#xA;&#xA;---- error analysis -----&#xA;&#xA;[2,6-7] on LAPTOP-D99BJJO0&#xA;C:\Users\aman\Desktop\quantum-espresso\BURAI1.3_Windows\exec.WIN\qe\pw.exe aborted the job. abort code 1&#xA;&#xA;---- error analysis -----&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone tell me what is wrong or how to fix this? I was able to do geometrical optimization and a DOS calculation.&lt;/p&gt;&#xA;&lt;p&gt;My input file(this might be a bit different as this is the input file from BURAI, not from QE directly)-&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;    calculation = &amp;quot;bands&amp;quot;&#xA;    max_seconds =  8.64000e+04&#xA;    pseudo_dir  = &amp;quot;C:\Users\aman\.burai\.pseudopot&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;    a           =  1.38539e+01&#xA;    degauss     =  1.00000e-02&#xA;    ecutrho     =  2.25000e+02&#xA;    ecutwfc     =  2.50000e+01&#xA;    ibrav       = 1&#xA;    nat         = 35&#xA;    nbnd        = 205&#xA;    ntyp        = 3&#xA;    occupations = &amp;quot;fixed&amp;quot;&#xA;    smearing    = &amp;quot;gaussian&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;BANDS&#xA;    lsym           = .FALSE.&#xA;    spin_component = 1&#xA;/&#xA;&#xA;K_POINTS {tpiba_b}&#xA;8&#xA;gG     20&#xA;X      20&#xA;M      20&#xA;gG     20&#xA;R      20&#xA;X      0&#xA;M      20&#xA;R      0&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-van.UPF&#xA;Se     78.96000  Se.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;H       1.00794  H.pbe-rrkjus.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn      7.163261   4.238903   4.269576&#xA;Zn      4.098923   7.142674   4.266389&#xA;Zn      4.251441   4.142784   6.677999&#xA;Zn      6.772594   4.312273   9.468335&#xA;Zn      6.711942   9.927994   4.413864&#xA;Zn      4.074000   6.686714   9.384117&#xA;Zn      9.711028   7.060839   4.380449&#xA;Zn      4.123915   9.621282   6.871968&#xA;Zn      9.802880   4.533673   6.968794&#xA;Zn      6.811607   7.039975   6.828522&#xA;Zn      7.213981   9.437939   9.452860&#xA;Zn      9.671655   6.980556   9.595348&#xA;Zn      9.644155   9.767095   6.949495&#xA;Se      2.674419   5.363344   7.968798&#xA;Se      5.568922   5.631792   5.397009&#xA;Se      8.599831   2.982074   5.664459&#xA;Se      8.523926   5.617993   2.918637&#xA;Se      2.568839   8.343381   5.616192&#xA;Se      5.601950   2.756033   8.079685&#xA;Se      5.356403   8.655122   2.951817&#xA;Se     11.285098   5.885554   5.704442&#xA;Se      5.360005  11.318916   5.769611&#xA;Se      5.319372   5.438183  10.936395&#xA;Se     11.090146   8.423789   8.311434&#xA;Se      8.352068  11.199162   8.322822&#xA;Se      8.400265   8.246833  11.137928&#xA;Se      8.212143   5.736209   8.210370&#xA;Se      8.206366   8.472694   5.570807&#xA;Se      5.427197   8.328031   8.325510&#xA;H       8.614600   5.593236   1.385394&#xA;H       5.309050   8.780542   1.421566&#xA;H       5.223669   5.383100  12.468543&#xA;H       9.110515   7.511909  12.284688&#xA;H       9.018497  12.402696   7.639490&#xA;H       8.712796   1.451241   5.722105&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-06-21T19:35:35.743" LastActivityDate="2021-10-29T17:45:55.913" Title="Error while doing a band structure calculation in Quantum ESPRESSO" Tags="|quantum-espresso|electronic-structure|software-assistance|quantum-dots|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6128" PostTypeId="5" CreationDate="2021-06-11T23:33:20.377" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-11T23:33:20.377" LastActivityDate="2021-06-11T23:33:20.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6129" PostTypeId="4" CreationDate="2021-06-11T23:33:20.377" Score="0" Body="Questions about or related to the Windows operating system when used for matter modeling." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-11T23:33:20.377" LastActivityDate="2021-06-11T23:33:20.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6130" PostTypeId="2" ParentId="4919" CreationDate="2021-06-11T23:46:11.143" Score="2" Body="&lt;p&gt;This part of your question body:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Thermo_pw website says that it is made for linux operating systems but it may work on other OS as well.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;indicates to me that the authors of the software do not guarantee that it will work on Windows. However Windows 10 actually comes with a Linux (Ubuntu) subsystem called WSL (Windows subsystem for Linux), which was mentioned in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4919/is-it-possible-to-install-thermo-pw-on-windows-10#comment9823_4919&quot;&gt;jheindel's comment&lt;/a&gt;, and also in the answers and their comments &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1220/5&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1231/5&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Specifically, &lt;em&gt;&lt;strong&gt;&lt;a href=&quot;https://docs.microsoft.com/en-us/windows/wsl/install-win10&quot; rel=&quot;nofollow noreferrer&quot;&gt;follow these instructions&lt;/a&gt;&lt;/strong&gt;&lt;/em&gt; to get the Ubuntu subsystem running on Windows 10, then install thermo_pw on it by following the instructions for installing this software with Linux. &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5010/5&quot;&gt;Sooner or later you will need to use Linux for something&lt;/a&gt;, if you intend to go far with Matter Modeling, so this may be a good first step for you!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-11T23:46:11.143" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6131" PostTypeId="2" ParentId="6104" CreationDate="2021-06-12T06:56:02.103" Score="3" Body="&lt;p&gt;Eventually, the question should be more detailed.&lt;/p&gt;&#xA;&lt;p&gt;However, for starters and in general, I would start by giving a cursory read to any wide piece of work that contains this problem, in order to get some perspective. For example in the PhD thesis &lt;a href=&quot;https://dspace.mit.edu/bitstream/handle/1721.1/33501/31019424-MIT.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cellular automata methods in mathematical physics&lt;/a&gt;, where chapter 5 is dedicated to &lt;strong&gt;Modeling Polymers with Cellular Automata&lt;/strong&gt; but there is some background that should help you get situated, such as Cellular Automata as models of nature or the question of reversibility vs dissipation. It's 25 years old but the general principles will not have changed.&lt;/p&gt;&#xA;&lt;p&gt;Once you have a good grasp on the general problem you want to solve, the system you are going to study and why the technique you want to apply can be useful, you can dig into the bibliography with some more focus, and also to select more recent works.&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2021-06-12T06:56:02.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6132" PostTypeId="2" ParentId="3792" CreationDate="2021-06-12T06:58:59.317" Score="5" Body="&lt;p&gt;The starting point of most calculations is the Born-Oppenheimer approximation, which separates the electronic and nuclear degrees of freedom. The electronic structure problem is then solved using a variety of methods (DFT, wave function methods, etc), and the nuclear problem is typically solved using the (quasi)harmonic approximation in solids.&lt;/p&gt;&#xA;&lt;p&gt;To observe a failure of the (quasi)harmonic approximation, you do not need to involve electrons directly. The (quasi)harmonic approximation assumes that the phonons are non-interacting albeit volume-dependent. This will fail when phonon-phonon interactions need to be taken into account, which can happen in a variety of cases (high temperature, light elements, structural phase transitions).&lt;/p&gt;&#xA;&lt;p&gt;The other concepts you mention involving electrons are also important, although not directly related to the (quasi)harmonic approximation. For example, electronic entropy is important in situations including warm dense matter where temperatures are &lt;em&gt;really&lt;/em&gt; high, and electron-phonon interactions are important in a variety of cases, and they allow one to go beyond the Born-Oppenheimer approximation by coupling the electronic and nuclear subsystems.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-06-12T06:58:59.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6133" PostTypeId="1" CreationDate="2021-06-12T08:33:37.530" Score="8" ViewCount="111" Body="&lt;p&gt;When I do a CASSCF calculation I can include the card &lt;code&gt;expec2,lxx,lyy,lzz&lt;/code&gt; in order to calculate the two-electron operators (in the x, y, and z-directions) for orbital angular momentum. This is &lt;a href=&quot;https://www.molpro.com/manual/doku.php?id=the_mcscf_program_multi&amp;amp;s%5B%5D=two&amp;amp;s%5B%5D=electron&amp;amp;s%5B%5D=operators#matrix_elements_over_two-electron_operators&quot; rel=&quot;noreferrer&quot;&gt;described here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, when I try to include the same instruction in an MRCI calculation the run is terminated, and the output says &amp;quot;Unknown command or directive EXPEC2&amp;quot;. So clearly this is not the right way to evaluate angular momentum in a CI calculation. But what is? There seems to be &lt;a href=&quot;https://www.molpro.com/manual/doku.php?id=the_mrci_program&amp;amp;s%5B%5D=two&amp;amp;s%5B%5D=electron&amp;amp;s%5B%5D=operators&quot; rel=&quot;noreferrer&quot;&gt;no mention of this in the manual&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3536" LastEditorUserId="5" LastEditDate="2021-06-13T20:34:03.210" LastActivityDate="2021-06-13T20:34:03.210" Title="In Molpro, how do I get the two-electron operator for angular momentum from a CI calculation?" Tags="|molpro|mrci|expectation-values|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6134" PostTypeId="2" ParentId="4956" CreationDate="2021-06-12T09:01:47.297" Score="0" Body="&lt;p&gt;&lt;em&gt;I believe my question is based on a misconception, so this is an answer according to my current understanding. Please, if you find additional misconceptions, comment below and I will try to update accordingly. Okay, let's go!&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;When you run a CASSCF calculation, note that the coefficients which are building up the orbitals are optimised at the same time as the CI coefficients. So there are no set of predefined orbitals which the calculations &lt;em&gt;picks&lt;/em&gt; from (when creating the CI expansion).&lt;/p&gt;&#xA;&lt;p&gt;Instead, what's happening is that the orbitals are optimised such that they are the best set available—for the chosen basis—to describe the &amp;quot;electron correlation&amp;quot; (i.e. the difference between the product wave-function of the Slater determinant, and the true eigenstate wave-function).&lt;/p&gt;&#xA;&lt;p&gt;This procedure does not imply that the &amp;quot;selected&amp;quot; orbitals must be the lowest energy ones. What makes the determination is instead how useful their shapes are for describing the electron correlation. Though it can be said that very high energy orbitals are probably not useful.&lt;/p&gt;&#xA;" OwnerUserId="3536" LastEditorUserId="3536" LastEditDate="2021-06-12T11:28:55.850" LastActivityDate="2021-06-12T11:28:55.850" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6135" PostTypeId="1" CreationDate="2021-06-12T13:54:13.873" Score="5" ViewCount="670" Body="&lt;p&gt;How may I carry out GW+SOC a band structure calculation using VASP? Could anyone familiar describe it step-by-step? I could not find any info regarding this on the VASP wiki.&lt;/p&gt;&#xA;" OwnerUserId="3753" LastEditorUserId="5" LastEditDate="2021-06-13T02:56:08.343" LastActivityDate="2021-06-13T07:22:55.847" Title="VASP GW+SOC band structure calculations" Tags="|density-functional-theory|band-structure|spin-orbit-coupling|gw-bse|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6136" PostTypeId="5" CreationDate="2021-06-12T18:18:03.320" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-06-12T18:18:03.320" LastActivityDate="2021-06-12T18:18:03.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6137" PostTypeId="4" CreationDate="2021-06-12T18:18:03.320" Score="0" Body="Questions about calculations with Multi-Reference Configuration Interaction (MRCI) methods." OwnerUserId="3536" LastEditorUserId="5" LastEditDate="2021-06-12T22:38:02.523" LastActivityDate="2021-06-12T22:38:02.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6138" PostTypeId="2" ParentId="6133" CreationDate="2021-06-13T02:23:39.967" Score="3" Body="&lt;p&gt;In the first sentence of this &lt;a href=&quot;https://www.molpro.com/manual/doku.php?id=introduction_to_molpro&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introduction to MOLPRO&lt;/a&gt;, MOLPRO is described as a &amp;quot;system of programs&amp;quot;, not just one program.&lt;/p&gt;&#xA;&lt;p&gt;The first link you provided is for the program called &lt;code&gt;MULTI&lt;/code&gt; for MCSCF calculations (which includes multiple &lt;a href=&quot;https://chemistry.stackexchange.com/a/99301/27342&quot;&gt;types of MCSCF&lt;/a&gt; such as CASSCF and RASSCF). The second link you provided is for the program called &lt;code&gt;MRCI&lt;/code&gt;. Each program in MOLPRO can have different authors, and you can see that the 9 papers listed in the &lt;code&gt;MULTI&lt;/code&gt; program bibliography don't overlap (not even in the years published!) with the 8 papers listed in the &lt;code&gt;MRCI&lt;/code&gt; program bibliography, except for the 1987 book chapter which is more of a review of papers previous to that. &lt;strong&gt;How things work in one MOLPRO program won't always be the same as in other MOLPRO programs.&lt;/strong&gt; Some  names of things are &lt;a href=&quot;https://en.wikipedia.org/wiki/Function_overloading&quot; rel=&quot;nofollow noreferrer&quot;&gt;overloaded&lt;/a&gt;, so that the same string is used in multiple programs, but not necessarily with exactly the same meaning.&lt;/p&gt;&#xA;&lt;p&gt;When I search &lt;code&gt;expec2&lt;/code&gt; in the documentation link you provided for the &lt;code&gt;MRCI&lt;/code&gt; program, the &lt;em&gt;only&lt;/em&gt; appearance of that string on that page occurs in a &lt;code&gt;MULTI&lt;/code&gt; command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{multi;&#xA;occ,3,1,1;frozen,1;wf,6,1;state,3;lquant,0,2,0;wf,6,4;lquant,2;&#xA;tran,lz;&#xA;expec2,lzlz;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Interestingly, they used &lt;code&gt;lzlz&lt;/code&gt; instead of &lt;code&gt;lzz&lt;/code&gt; for the &lt;span class=&quot;math-container&quot;&gt;$\hat{L}_z^2$&lt;/span&gt; operator, as described &lt;a href=&quot;https://www.molpro.com/manual/doku.php?id=program_control#one-electron_operators_and_expectation_values_gexpec&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I don't see any example of how to use &lt;code&gt;expec2&lt;/code&gt; with the &lt;code&gt;MRCI&lt;/code&gt; program, and the introduction to the &lt;code&gt;MRCI&lt;/code&gt; documentation to which you provided the link, says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The &lt;code&gt;EXPEC&lt;/code&gt; directive allows to compute expectation values over one-electron operators, and the &lt;code&gt;TRAN&lt;/code&gt; directive can be used to compute transition matrix elements for one-electron properties&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;but nothing about 2-electron properties such as the ones available in &lt;code&gt;MULTI&lt;/code&gt;  by using the &lt;code&gt;EXPEC2&lt;/code&gt; card. If you search the word &amp;quot;properties&amp;quot; in the &lt;code&gt;MRCI&lt;/code&gt; documentation, you'll find that there's a sub-section about one-electron properties, but nothing suggesting that two-electron properties are possible.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-13T02:23:39.967" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6139" PostTypeId="2" ParentId="6135" CreationDate="2021-06-13T04:37:18.617" Score="5" Body="&lt;p&gt;Here I show the typical calculation flow of GW in VASP:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;a DFT ground-state calculation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;obtain DFT virtual orbitals&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;GW calculation including LWANNIER90 TAG&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Compute Wannier functions and Obtain bandstructure by Wannier interpolation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;PS1: use &lt;code&gt;POTCAR&lt;/code&gt; like [&lt;code&gt;XXX_GW&lt;/code&gt;].&lt;/p&gt;&#xA;&lt;p&gt;PS2: If you want to include spin-orbit coupling, just add the following tags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LSORBIT=.TRUE.  &#xA;SAXIS= 0 0 1  &#xA;ISYM=0&#xA;             &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Bandstructure_of_Si_in_GW_(VASP2WANNIER90)&quot; rel=&quot;nofollow noreferrer&quot;&gt;See here for more information.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-06-13T07:22:55.847" LastActivityDate="2021-06-13T07:22:55.847" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6140" PostTypeId="1" AcceptedAnswerId="6142" CreationDate="2021-06-13T09:34:51.027" Score="10" ViewCount="1422" Body="&lt;p&gt;I have been using SIESTA code to perform some practicals in my college and I have run energy cut-off tests before calculating properties of semi-conductors or insulator. As far as I am concerned, SIESTA is a code using atomic-like basis sets, instead of plane-wave based ones. In the case of the plane-wave representation, the energy cut-off is the kinetic energy of the plane wave with highest plane-wave vector. The longer this cut-off is, the more waves will be used to represent the orbitals, the more accurate the description of the system will be...&lt;/p&gt;&#xA;&lt;p&gt;However, what is really the meaning or the physics behind this test for atomic-like basis sets?&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2021-06-13T13:44:34.030" Title="Energy cut-off test meaning in atomic-like basis functions' DFT" Tags="|density-functional-theory|convergence-test|siesta|plane-waves|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6141" PostTypeId="1" CreationDate="2021-06-13T11:38:24.007" Score="14" ViewCount="394" Body="&lt;p&gt;I have calculated the band structure of some material where the unit cell was the conventional one (i.e. the lattice vectors are orthogonal). I'm trying now to calculate the same band structure only now the unit cell is the primitive one.&lt;/p&gt;&#xA;&lt;p&gt;My question is how do I convert the fractional k-points i.e. &lt;span class=&quot;math-container&quot;&gt;$$x_1\vec{b}_1 + x_2\vec{b}_2 + x_3\vec{b}_3$$&lt;/span&gt; in the first Brillouin from the conventional cell to the primitive cell?&lt;/p&gt;&#xA;&lt;p&gt;The conventional cell is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    3.3132998943         0.0000000000         0.0000000000&#xA;    0.0000000000        10.4729995728         0.0000000000&#xA;    0.0000000000         0.0000000000         4.3740000725&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the primitive is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    1.6566492265        -5.2364998440         0.0000000000&#xA;    1.6566492265         5.2364998440         0.0000000000&#xA;    0.0000000000        -0.0000000000         4.3740000725&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;for example, what will be the equivalent of (1/2, 0, 0) in the primitive cell?&lt;/p&gt;&#xA;" OwnerUserId="3760" LastEditorUserId="5" LastEditDate="2023-03-28T21:31:29.663" LastActivityDate="2023-03-28T21:34:14.910" Title="Translating fractional coordinates resulting from conventional cell and primitive cell" Tags="|band-structure|ab-initio-calculations|geometry|brillouin-zone|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6142" PostTypeId="2" ParentId="6140" CreationDate="2021-06-13T13:44:34.030" Score="10" Body="&lt;p&gt;There is no energy cut off test for calculations that employ atomic basis sets, in general: the calculation is well-defined with just the atomic basis set.&lt;/p&gt;&#xA;&lt;p&gt;For comparison, the Gaussian-basis PySCF program implements four ways to compute the Coulomb interactions in crystalline systems:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Gaussian-basis density fitting&lt;/li&gt;&#xA;&lt;li&gt;mixed Gaussian-plane wave density fitting&lt;/li&gt;&#xA;&lt;li&gt;plane-wave density fitting&lt;/li&gt;&#xA;&lt;li&gt;exact Gaussian integrals through a range separated approach (&lt;a href=&quot;https://arxiv.org/abs/2012.07929&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/2012.07929&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As to your question, SIESTA employs pseudopotentials, and option 3 is what they use. If you look at the newest paper on the code, &lt;a href=&quot;https://doi.org/10.1063/5.0005077&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 152, 204108 (2020)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The auxiliary real-space grid is an essential ingredient of the method as it allows the efficient representation of charge densities and potentials as well as the computation of the matrix elements of the Hamiltonian that cannot be handled as two-center integrals. This grid can be seen as the reciprocal space of a set of plane waves, and its fineness is most conveniently parameterized by an energy cutoff (the “density” cutoff of plane-wave methods). There are limits to the softness of the functions that can be described with such a grid, so core electrons are not considered (although semi-core electrons usually&#xA;are), and their effect is incorporated into pseudopotentials. The real-space grid is also used to solve the Poisson equation involved in the computation of the electrostatic potential from the charge density through the use of a fast-Fourier-transform method. This means that SIESTA uses periodic boundary conditions (PBC). Non-periodic systems, such as molecules, tubes, or slabs, are treated using appropriate supercells.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This means that the plane-wave cutoff in SIESTA affects the evaluation of the Coulomb interaction. The higher the cutoff, the better SIESTA is able to describe the interaction of the atomic basis functions. With &lt;span class=&quot;math-container&quot;&gt;$E_\text{cut} \to \infty$&lt;/span&gt; you recover the exact solution in the used atomic basis set.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-06-13T13:44:34.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6143" PostTypeId="1" AcceptedAnswerId="6174" CreationDate="2021-06-13T19:36:33.267" Score="8" ViewCount="1304" Body="&lt;p&gt;So, I have started to learn NAMD because I need that for a project I will be doing in the next couple of months. I have some prior experience of MD with gromacs. I thought that since NAMD has a GUI frontend (VMD) it would be easier to learn but I am finding it much much harder to learn.&lt;/p&gt;&#xA;&lt;p&gt;For my work, I need to simulate droplets of water (basically a fixed number of water molecules in vaccum, without any periodic boundary). However, I have no idea how or where to start. All of the &lt;a href=&quot;http://www.ks.uiuc.edu/Training/Tutorials/namd-index.html&quot; rel=&quot;noreferrer&quot;&gt;tutorials&lt;/a&gt; online seems to focus primarily on proteins and how to simulate them so they are not of much help.&lt;/p&gt;&#xA;&lt;p&gt;I tried to use the VMD solvate plugin to generate a box of solvent but there does not seem to be an option to control the actual number of water molecules (something similar to &lt;code&gt;gmx solvate -maxsol 200&lt;/code&gt; from gromacs). It creates a box of water molecules, however, I don't know how to change the box to a sphere and remove the periodic boundary conditions (The water molecules does not need to be shifted because the MD run will automatically push it into a spherical shape).&lt;/p&gt;&#xA;&lt;p&gt;Finally VMD solvate seems to take the topology for water from an internal file which gives TIP3P water, however, the psf file generated does not seem to have any parameters, so I am not sure how the simulation will run.&lt;/p&gt;&#xA;&lt;p&gt;As for running the actual equilibriation, I am running into even more problems. QwikMD does not read the psf file, and I cannot figure out any way to change the boundary condition to spherical, or remove it.&lt;/p&gt;&#xA;&lt;p&gt;So, my question is: &lt;strong&gt;How do I run simulations of water in NAMD ?&lt;/strong&gt; (with the least amount of hassle)&lt;/p&gt;&#xA;&lt;p&gt;A step-by-step answer would be the most helpful, but any answer is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-14T08:12:09.577" LastActivityDate="2022-12-08T14:01:54.863" Title="How do I build and run a simulation of water molecules in NAMD?" Tags="|molecular-dynamics|software-input-file-request|vmd|namd|qwikmd|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6144" PostTypeId="5" CreationDate="2021-06-13T19:38:36.877" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2021-06-13T19:38:36.877" LastActivityDate="2021-06-13T19:38:36.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6145" PostTypeId="4" CreationDate="2021-06-13T19:38:36.877" Score="0" Body="For questions regarding NAMD (Nanoscale Molecular Dynamics), a software for molecular dynamics simulations." OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2021-06-18T17:32:19.350" LastActivityDate="2021-06-18T17:32:19.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6146" PostTypeId="5" CreationDate="2021-06-13T20:31:44.000" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.ks.uiuc.edu/Research/qwikmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.ks.uiuc.edu/Research/qwikmd/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/srep26536&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/srep26536&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-13T20:31:44.000" LastActivityDate="2021-06-13T20:31:44.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6147" PostTypeId="4" CreationDate="2021-06-13T20:31:44.000" Score="0" Body="Questions about QwikMD which connects VMD to NAMD" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-13T20:31:44.000" LastActivityDate="2021-06-13T20:31:44.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6148" PostTypeId="5" CreationDate="2021-06-13T20:34:42.520" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-13T20:34:42.520" LastActivityDate="2021-06-13T20:34:42.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6149" PostTypeId="4" CreationDate="2021-06-13T20:34:42.520" Score="0" Body="Questions about the calculations of expectations values (e.g. properties of a quantum mechanical system)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-13T20:34:42.520" LastActivityDate="2021-06-13T20:34:42.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6150" PostTypeId="2" ParentId="6141" CreationDate="2021-06-13T20:38:19.190" Score="5" Body="&lt;p&gt;I've never done this before but here is my guess of how you can do it.&lt;/p&gt;&#xA;&lt;p&gt;If the numbers you posted are the unit cell axes vectors with a vector for each column then their direct matrices are.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\mathbf{A} = \begin{bmatrix}3.31 &amp;amp; 0.00 &amp;amp; 0.00 \\&#xA;    0.00  &amp;amp;      10.47      &amp;amp;   0.00 \\&#xA;    0.00    &amp;amp;     0.00     &amp;amp;   4.37\end{bmatrix}, \qquad\qquad \mathbf{A}' = \begin{bmatrix}1.65 &amp;amp; -5.24 &amp;amp; 0.00 \\&#xA;    1.66   &amp;amp;      5.23    &amp;amp;     0.00 \\&#xA;    0.00    &amp;amp;    0.00   &amp;amp;      4.37\end{bmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From this you can get the reciprocal space vectors with&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{B} = 2\pi(\mathbf{A}^{-1})^{T}, \qquad\qquad \mathbf{B}' = 2\pi(\mathbf{A}^{-1})^{T}\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where I have included the &lt;span class=&quot;math-container&quot;&gt;$2\pi$&lt;/span&gt; to stick with the physicist definition. Then you can convert your example fractional &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\vec{x} = \begin{bmatrix}0.50 \\&#xA;    0.00 \\&#xA;    0.00\end{bmatrix}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;to a point in reciprocal space &lt;span class=&quot;math-container&quot;&gt;$\vec{G}$&lt;/span&gt; with:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\vec{G} = \mathbf{B}\vec{x}\tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;then convert that point &lt;span class=&quot;math-container&quot;&gt;$\vec{G}$&lt;/span&gt; in reciprocal space to the fractional &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point in your other reciprocal lattice.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\vec{x}' = (\mathbf{B}')^{-1}\vec{G}\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then you'll need to adjust &lt;span class=&quot;math-container&quot;&gt;$\vec{x}'$&lt;/span&gt; so it is in the first Brillouin zone. I think you can do something like this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;x^{1\mathrm{st}}_{1} &amp;amp;= x'_{1} - \mathrm{round}(x'_{1})\tag{6}\\&#xA;x^{1\mathrm{st}}_{2} &amp;amp;= x'_{2} - \mathrm{round}(x'_{2})\tag{7}\\&#xA;x^{1\mathrm{st}}_{3} &amp;amp;= x'_{3} - \mathrm{round}(x'_{3})\tag{8}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hopefully that is right.&lt;/p&gt;&#xA;" OwnerUserId="3674" LastEditorUserId="3674" LastEditDate="2021-06-13T21:12:35.420" LastActivityDate="2021-06-13T21:12:35.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6151" PostTypeId="1" AcceptedAnswerId="6212" CreationDate="2021-06-14T07:14:28.573" Score="16" ViewCount="929" Body="&lt;p&gt;What are the basic steps and methodologies used in creating inter-atomic potential (specially &lt;code&gt;EAM&lt;/code&gt;, &lt;code&gt;MEAM&lt;/code&gt; potentials) for metals with the help of DFT? Is there any tool available where specific results of DFT can be put to generate inter-atomic potentials like &lt;code&gt;EAM&lt;/code&gt;/&lt;code&gt;MEAM&lt;/code&gt; for LAMMPS?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2023-10-12T01:29:27.343" LastActivityDate="2023-10-13T08:14:40.453" Title="How may I create an interatomic potential using DFT?" Tags="|density-functional-theory|molecular-dynamics|lammps|interatomic-potentials|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6153" PostTypeId="1" CreationDate="2021-06-15T11:29:58.290" Score="8" ViewCount="2564" Body="&lt;p&gt;I am currently studying the UV-visible spectrum of ethylene using GAUSSIAN-09. I optimized the ground state(&lt;code&gt;# opt b3lyp/6-31g geom=connectivity&lt;/code&gt;) then used the logfile to calculate the energy without optimizing it (&lt;code&gt;# td=(root=10) b3lyp/6-31g geom=connectivity&lt;/code&gt;), but when I get the UV-visible spectrum from the log-file using Gaussview I do not know whether it is an absorption or emission spectrum, how can I distinguish between the two from my results?&lt;/p&gt;&#xA;&lt;p&gt;When I try to run an optimization on the excited-state(&lt;code&gt;#p opt freq=savenm td=(nstates=6,root=1) rb3lyp/6-31g(d) geom=connectivity&lt;/code&gt;), I get an error (&lt;code&gt;Error termination request processed by link 9999&lt;/code&gt;). What causes this error? How can I solve it? And is it necessary to optimize the structure in the excited state to have the UV-visible spectrum?&lt;/p&gt;&#xA;&lt;p&gt;How can we generate an absorption spectrum and an emission spectrum separately using GAUSSIAN09? What keywords do we have to add?&lt;/p&gt;&#xA;&lt;p&gt;Can you recommend articles, books, or tutorials about GAUSSIAN software?&lt;/p&gt;&#xA;" OwnerUserId="3768" LastEditorUserId="1380" LastEditDate="2021-06-15T14:10:09.917" LastActivityDate="2023-10-19T10:37:43.120" Title="Emission and absorption UV-Visible spectrum using GAUSSIAN-09" Tags="|gaussian|spectroscopy|software-assistance|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6154" PostTypeId="2" ParentId="6153" CreationDate="2021-06-15T13:37:07.960" Score="8" Body="&lt;p&gt;Roughly speaking, absorption spectra are obtained by TDDFT calculations on optimized ground-state geometries, while emission spectra are obtained by TDDFT calculations on optimized excited state geometries. These are the results of the Franck-Condon approximation, which says that there is a high probability that a molecule is near its equilibrium geometry, and electronic transitions are much faster than geometry changes of the molecule, so that during an electronic transition, the molecular geometry can be viewed as staying unchanged in the equilibrium geometry of the initial state. Since you did a ground-state geometry optimization, the spectrum is an absorption spectrum. If you want to calculate the vibronic features of the absorption spectrum, then you may also need to optimize the excited state geometry, but this is an advanced issue.&lt;/p&gt;&#xA;&lt;p&gt;With a simple &amp;quot;&lt;code&gt;Error termination request processed by link 9999&lt;/code&gt;&amp;quot; we cannot analyze the cause of the error. You should post at least a few tens of lines before this line, or better, upload the complete output file. If Gaussian aborts due to an error, the cause of the abort usually cannot be deduced solely from the last few lines, or from the last line that contains the word &amp;quot;error&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;It's beneficial to take a careful read of the descriptions of keywords and example input files on gaussian.com. I would also recommend you to refer to general quantum chemistry textbooks that are not specific to Gaussian, as many problems that you encounter when using Gaussian are in fact quantum chemistry problems that exist regardless of what software you use, rather than &amp;quot;what keyword should I use&amp;quot;-type problems that are specific to the software.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="5" LastEditDate="2021-06-15T14:28:52.150" LastActivityDate="2021-06-15T14:28:52.150" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="6155" PostTypeId="1" AcceptedAnswerId="6167" CreationDate="2021-06-15T14:28:30.447" Score="5" ViewCount="158" Body="&lt;p&gt;I have used both Gaussian09 and Gaussian16 and one thing that seemed unusual to me is that I was unable to enter any fractional number as one of the arguments for a keyword in the Gaussian input file.&lt;/p&gt;&#xA;&lt;p&gt;For example, to control the step length of the optimization procedure, the keyword is &lt;code&gt;maxstep&lt;/code&gt;. So I can enter something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#n opt=(maxstep=1) freq b3lyp/6-31G  !Runs normally&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Whereas Gaussian gives an error in reading the input file if I use a fractional number (float) as an argument of &lt;code&gt;maxstep&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#n opt=(maxstep=0.5) freq b3lyp/6-31G  !Error&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have not seen this in any other softwares. For example, GAMESS and Orca both allow non-integer values for arguments to keywords that control the optimization step size.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Why does Gaussian not allow non-integer arguments to its keywords?&lt;/strong&gt; (I haven't checked other keywords apart from maxstep, because most other keywords don't need floating point values, but the same problems seems to arise with maxstep for IRC)&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-06-15T20:42:20.557" Title="How to use fractional numbers as arguments for keywords in Gaussian input?" Tags="|gaussian|geometry-optimization|software-assistance|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6156" PostTypeId="2" ParentId="6155" CreationDate="2021-06-15T15:16:04.837" Score="5" Body="&lt;p&gt;This is a weird quirk of the Gaussian input and I am unsure why it is implemented this way.  The maxstep is given in a unit of 0.01 Bohr and it is presumed you do not wish to use a maxstep of less than 0.01 Bohr as this corresponds to about 0.005 angstroms.&lt;/p&gt;&#xA;&lt;p&gt;While I think this is a weird limitation to exist, you may consider that this is such a small distance that no practical calculations should be done with a maxstep=1 or less.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-06-15T15:16:04.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6157" PostTypeId="2" ParentId="5090" CreationDate="2021-06-15T15:21:37.087" Score="3" Body="&lt;p&gt;More from the quantum chemistry side, a general introductory textbook with a good chapter about solids:&lt;/p&gt;&#xA;&lt;h3&gt;&lt;strong&gt;Lucjan Piela: Ideas of Quantum Chemistry&lt;/strong&gt;&lt;/h3&gt;&#xA;&lt;p&gt;The book (&lt;a href=&quot;https://www.elsevier.com/books/ideas-of-quantum-chemistry/piela/978-0-444-64246-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;link here&lt;/a&gt;) has a very broad scope of topics from fundamental quantum physics to quantum chemistry, explores basic quantum chemical models such as Hartree-Fock, DFT as well as post-Hartree-Fock methods, but also includes chapters on relativistic quantum chemistry, nuclear motion, spectroscopy, chemical reactions, complex systems, &lt;strong&gt;and - on the point raised in your question - a good coverage of periodic solid state systems&lt;/strong&gt;. The many appendices cover many essential mathematical tools and tricks. Finally, the book is written in a warm tone and an extremely engaging style with anecdotes, history and future directions sprinkled in.&lt;/p&gt;&#xA;&lt;p&gt;It used to be a single book but the latest edition has two volumes. The chapter on periodic systems is in Vol. 2.&lt;/p&gt;&#xA;&lt;p&gt;It is quite expensive though so maybe inquire at a library.&lt;/p&gt;&#xA;" OwnerUserId="544" LastEditorUserId="5" LastEditDate="2021-06-15T16:05:51.637" LastActivityDate="2021-06-15T16:05:51.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6158" PostTypeId="1" CreationDate="2021-06-15T17:39:56.077" Score="5" ViewCount="130" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; topological index is usually defined in terms of the Pfaffian of the overlap matrix, as defined &lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0506581.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;by eq. 4 of Kane and Mele's&lt;/a&gt; paper:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;P(k)=\text{Pf}[\langle u_i(k) | \Theta | u_j(k) \rangle],&#xA;\tag{1}$$&lt;/span&gt;&#xA;where Pf is the Pfaffian and &lt;span class=&quot;math-container&quot;&gt;$\Theta$&lt;/span&gt; is the time reversal operator.&lt;/p&gt;&#xA;&lt;p&gt;However, &lt;a href=&quot;https://arxiv.org/pdf/1509.09016.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this review&lt;/a&gt; gives an alternative definition of the &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; index in Eq. 7 of the review, that seems rather unconventional:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\mathbb{Z}_2 = \frac{1}{2\pi}\left[ \oint_{\partial HBZ} A dk - \int_{HBZ} \Omega_z d^2k \right] (\text{mod } 2),&#xA;$$&lt;/span&gt;&#xA;where HBZ is the half-Brillouin zone, &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is the Berry connection and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; is the Berry curvature.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am not sure how the unusual definition is used in practice (is it summed over filled bands? or all bands?)&lt;/strong&gt;. The reason I am asking is because the latter, unusual form seems easier to compute numerically (unless I missed some easier trick).&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-06-21T23:17:00.427" LastActivityDate="2021-06-21T23:17:00.427" Title="Z2 topological index: Is this unconventional formula summed over just filled bands, or all bands?" Tags="|condensed-matter|topological-insulators|berry-phase|" AnswerCount="0" CommentCount="2" ClosedDate="2022-08-23T22:19:05.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="6159" PostTypeId="1" CreationDate="2021-06-02T14:48:32.310" Score="9" ViewCount="314" Body="&lt;p&gt;I am looking for common categories of graphs used in chemistry, for math research I am doing in graph theory.&lt;/p&gt;&#xA;&lt;p&gt;When I write categories, the meaning is not for graphs design or types of design, but for categories of nature-originated large graphs (like large molecules), that can be mathematically described. For example, trees, unicyclic graphs, bipartite graphs, etc.&lt;/p&gt;&#xA;&lt;p&gt;I mention it because I saw &lt;a href=&quot;https://biology.stackexchange.com/questions/84016/classes-of-graphs-used-in-biology&quot;&gt;a similar question on the Biology Stack Exhange&lt;/a&gt;, and the response there is not the meaning of the asker at all.&lt;/p&gt;&#xA;&lt;p&gt;I tried to look for scientific articles that review it but did not find any related survey.&lt;/p&gt;&#xA;" OwnerUserId="3769" OwnerDisplayName="RD7" LastEditorUserId="5" LastEditDate="2021-06-15T20:03:16.807" LastActivityDate="2021-06-23T14:17:00.850" Title="Classes of Graphs used in Chemistry" Tags="|one-topic-per-answer|molecular-modeling|mathematical-modeling|" AnswerCount="2" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="6160" PostTypeId="1" CreationDate="2021-06-15T19:08:23.977" Score="9" ViewCount="334" Body="&lt;p&gt;Eq. 19 in &lt;a href=&quot;https://arxiv.org/pdf/1310.3536.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; gives the following Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yjxlt.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yjxlt.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sigma_a, \tau_a, \eta_a$&lt;/span&gt; are respectively the spin, sublattice pseudospin and valley pseudospin respectively.&lt;/p&gt;&#xA;&lt;p&gt;Normally, I would have chosen a basis convention such as &lt;span class=&quot;math-container&quot;&gt;$\sigma_a, \tau_a, \eta_a$&lt;/span&gt; and plugged in the &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; identity matrix for terms that don't appear above. Then I would have taken the Kronecker Delta product. However, in this case, the authors explicitly define &lt;span class=&quot;math-container&quot;&gt;$(s_z,\tau_z\,\eta_z)=(\pm 1, \pm 1, \pm 1)$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$($&lt;/span&gt;up/down, sublattice A/B, valley K/K'&lt;span class=&quot;math-container&quot;&gt;$)$&lt;/span&gt; respectively. So, as a relatively inexperienced person in the field, I feel like there is some ambiguity. I am having trouble translating the above into a matrix that I can play with numerically.&#xA;Can someone help me understand the convention here?&lt;/p&gt;&#xA;&lt;p&gt;I tried two interpretations in Python. &lt;code&gt;np.kron&lt;/code&gt; takes the Kronecker product. First attempt:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Choose basis: (tau_xy, sigma_xyz), replace sz, tauz, etaz by s, tau, eta = +/- 1&#xA;# Gives 4-band model, with eye = identity and s_xyz as Pauli matrices&#xA;eta = 1; # instead of using eta_z as the Pauli z matrix&#xA;h1=h*vf*(eta*kx*np.kron(sx,eye)+ky*np.kron(sy,eye)) # e-e hoppings&#xA;h2=lSO*eta*np.kron(eye,sz)*tau # SO coupling&#xA;h3=m*np.kron(eye,sz)*tau # break TRS (AFM exchange mag.)&#xA;H = h1+h2+h3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Second:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Choose basis: (eta, sigma, tau) using Pauli matrices for all, but no +/- 1 values.&#xA;# Gives 8-band model.&#xA;h1=h*vf*(kx*np.kron(sz,np.kron(eye,sx))+ky*np.kron(eye,np.kron(eye,sy))) # e-e hoppings&#xA;h2=lSO*np.kron(sz,np.kron(sz,sz)) # SO coupling&#xA;h3=m*np.kron(eye,np.kron(sz,sz))# break TRS (AFM exchange mag.)&#xA;H = h1+h2+h3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Both of these seem to give me very weird Berry curvature fields when plotted. So, I figured I am doing something wrong. Note: I set &lt;span class=&quot;math-container&quot;&gt;$v_F = 1, \hbar=1$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-06-16T05:40:15.243" LastActivityDate="2021-06-16T05:40:15.243" Title="Help with translating Hamiltonian into matrix" Tags="|condensed-matter|mathematical-modeling|quantum-mechanics|model-hamiltonians|programming|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6161" PostTypeId="1" AcceptedAnswerId="6162" CreationDate="2021-06-15T19:11:10.197" Score="5" ViewCount="201" Body="&lt;p&gt;I'm interested in computing first and second derivatives of molecular Hamiltonians with respect to nuclear coordinates. I've been using Psi4 and PySCF to perform Hartree-Fock calculations, and I was wondering if there is any way to use these packages (or similar Python packages) to compute first and second derivatives analytically, by solving the coupled-perturbed Hartree-Fock equations?&lt;/p&gt;&#xA;" OwnerUserId="3693" LastEditorUserId="5" LastEditDate="2021-06-15T19:53:51.020" LastActivityDate="2021-06-15T20:11:24.543" Title="Calculating first and second derivatives of a molecular Hamiltonian?" Tags="|quantum-chemistry|electronic-structure|mathematical-modeling|pyscf|psi4|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6162" PostTypeId="2" ParentId="6161" CreationDate="2021-06-15T19:39:24.153" Score="5" Body="&lt;p&gt;The derivatives of a molecular Hamiltonian with respect to nuclear coordinates can be performed analytically (as you correctly pointed out), and therefore does not need PySCF or Psi4, which are programs for doing numerical calculations for things that cannot be done analytically. This is how it's done:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;H &amp;amp;= -\sum_{i}\frac{1}{2}\nabla_{i}^{2}-\sum_{i,A}\frac{Z_{A}}{\left|r_{i}-R_{A}\right|}+\sum_{A&amp;gt;B}\frac{Z_{A}Z_{B}}{\left|R_{A}-R_{B}\right|}+\sum_{i&amp;gt;j}\frac{1}{r_{ij}},\tag{1}\\&#xA;\frac{\partial H}{\partial R} &amp;amp;= \sum_{i,A}\frac{Z_{A}}{\left|r_{i}-R_{A}\right|^{2}}-\sum_{A&amp;gt;B}\frac{Z_{A}Z_{B}}{R^{2}}. \tag{2}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;More interesting is how to calculate derivatives of the energy or wavefunction. It can be done for the energy via the misappropriately named &lt;a href=&quot;https://en.wikipedia.org/wiki/Hellmann%E2%80%93Feynman_theorem&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hellmann-Feynman theorem&lt;/a&gt;, but often electronic structure programs prefer to do it in other ways. A lot of detail can be written about derivatives in electronic structure programs (for example, about linear response theory), depending on what your specific final goal is, so while the answer to &amp;quot;how to analytically calculate derivatives of a molecular Hamiltonian&amp;quot; has been given in Eq. 2 above, you might consider asking a new question with more details about the specific end goal in your project.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-15T20:11:24.543" LastActivityDate="2021-06-15T20:11:24.543" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6163" PostTypeId="1" AcceptedAnswerId="6267" CreationDate="2021-06-15T20:01:46.637" Score="7" ViewCount="260" Body="&lt;p&gt;I'm currently working on a quantum chemistry project, I am dealing with a second-quantized electronic Hamiltonian (corresponding to some molecule), written in terms of fermionic creation and annihilation operators of the form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H(R) = \displaystyle\sum_{p, q} h_{pq}(R) c_p^{\dagger} c_q + \frac{1}{2} \displaystyle\sum_{p, q, r, s} h_{pqrs}(R) c^{\dagger}_p c^{\dagger}_q c_r c_s\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is the nuclear coordinates of the molecule, and:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$h_{pq} = \displaystyle\int dx \phi_p(x)^{*} \left( -\frac{\nabla_r^2}{2} - \displaystyle\sum_{I} \frac{Z_I}{|r - R_I|} \right) \phi_q(x)\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$h_{pqrs}(R) = \displaystyle\int dx_1 dx_2 \frac{\phi_p(x_1)^{*} \phi_q(x_2)^{*} \phi_r(x_2) \phi_s(x_1)}{|r_1 - r_2|}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where each &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; is a molecular orbital, obtained from performing Hartree-Fock for the molecular Hamiltonian of interest (which depends implicitly on &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;). Computing these orbitals, and therefore the integrals, is straightforward through use of most electronic structure program suites.&lt;/p&gt;&#xA;&lt;p&gt;I am interested in calculating the first and second derivatives of &lt;span class=&quot;math-container&quot;&gt;$H(R)$&lt;/span&gt;, with respect to &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, so in effect, I need to compute the first and second derivatives of the integral outlined above. Is it possible to use PySCF or Psi4 for this task as well? I've looked around, and it seems like this problem of computing derivatives has to do with solving the coupled-perturbed Hartree-Fock equations, although I am unsure.&lt;/p&gt;&#xA;&lt;p&gt;Addendum: I did some more looking around, and it seems like GAMESS might be able to find the derivatives I'm looking for, as it can do analytical calculations of the Hessian, but I'm still unsure how to access these derivatives in the output file.&lt;/p&gt;&#xA;" OwnerUserId="3693" LastEditorUserId="5" LastEditDate="2021-06-28T00:27:25.760" LastActivityDate="2021-06-28T22:37:53.603" Title="Computing analytic derivatives of molecular Hamiltonians obtained from solving Hartree-Fock equations" Tags="|quantum-chemistry|electronic-structure|gamess|pyscf|psi4|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6164" PostTypeId="2" ParentId="6159" CreationDate="2021-06-15T20:02:59.867" Score="5" Body="&lt;h3&gt;Fullerene graphs&lt;/h3&gt;&#xA;&lt;p&gt;One example of a category of graphs that is used in chemistry is the set of &lt;a href=&quot;https://mathworld.wolfram.com/Fullerene.html&quot; rel=&quot;noreferrer&quot;&gt;Fullerene graphs&lt;/a&gt;. One Fullerene graph that is especially interesting to some chemists, is the &lt;a href=&quot;https://en.wikipedia.org/wiki/26-fullerene_graph&quot; rel=&quot;noreferrer&quot;&gt;26-Fullerene graph&lt;/a&gt;. You may also be interested in &lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-00994783/document&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; about Fullerene graphs, or the book &lt;a href=&quot;https://www.amazon.ca/Atlas-Fullerenes-P-W-Fowler/dp/0486453626&quot; rel=&quot;noreferrer&quot;&gt;An Atlas of Fullerenes&lt;/a&gt;  by theoretical chemists Patrick Fowler and David Manolopoulos.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-15T20:02:59.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6165" PostTypeId="1" AcceptedAnswerId="6166" CreationDate="2021-06-15T20:18:54.967" Score="14" ViewCount="6562" Body="&lt;p&gt;I have recently started to use Quantum ESPRESSO for evaluating different properties of ZnSe Quantum Dots. But I currently don't have access to any cluster and as I am increasing the size of calculation, my computer starts to hang and then crashes.&lt;/p&gt;&#xA;&lt;p&gt;Would it be feasible to create my own small clusters from 2 or 3 laptops that I have and somehow get them to run in parallel so I will be able to execute DFT codes more efficiently. All of the laptops I posses use Windows and that is going to be a big disadvantage, but I have read articles that it is indeed possible using Ethernet.&lt;/p&gt;&#xA;&lt;p&gt;What do you guys think, should I give this a shot?&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-06-16T16:34:07.287" LastActivityDate="2021-06-17T10:06:49.723" Title="Should I connect 2-3 laptops to form a supercomputer?" Tags="|quantum-espresso|high-performance-computing|windows-operating-system|" AnswerCount="3" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6166" PostTypeId="2" ParentId="6165" CreationDate="2021-06-15T20:41:53.607" Score="18" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Would it be feasible to create my own small clusters from 2 or 3 laptops that I have and somehow get them to run in parallel so I will be able to execute DFT codes more efficiently.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's certainly &lt;em&gt;possible&lt;/em&gt; but it would not help much at all.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If you are considering to put together three laptops (each with, say, 4 cores) to get a 12-core &amp;quot;cluster&amp;quot;, you will still be very unlikely to observe a 3x speed-up, especially due to the slow speed of Ethernet connections. HPC systems for multi-node computations use InfiniBand or Omnipath (unfortunately both very expensive compared to the scale of costs typically experienced by someone purchasing just personal laptops) instead of Ethernet, for that reason. &lt;strong&gt;You would be better off purchasing a desktop computer with 12-cores.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you're considering to put together three laptops (each with, say, 16GB of RAM) to get a 48GB &amp;quot;cluster&amp;quot;, &lt;strong&gt;you would be better off just purchasing more RAM&lt;/strong&gt; (for example, at &lt;a href=&quot;https://www.crucial.com/catalog/memory/ddr3&quot; rel=&quot;noreferrer&quot;&gt;Crucial&lt;/a&gt; you can get two 16GB DIMM sticks instead of the two 4GB or 8GB DIMM sticks that you probably have in each laptop by default) and inserting it into your laptop yourself. Unfortunately some laptops these days have the RAM soldered in, so you can't change the RAM easily, but this takes me back to the first bullet point above, where I recommend to get a desktop computer (it will not only likely have more cores, but also more space to add more RAM).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For serious HPC in academic research, it would be very expensive to purchase multiple laptops yourself and try to string them together to form a cluster. It's unfortunate that this is sometimes a struggle in science (also for people who want to do world-class experiments that require expensive lab equipment).&lt;/p&gt;&#xA;&lt;p&gt;I hope that the answers to these two questions might be able to help you:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1515/5&quot;&gt;Supercomputers around the world&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1613/5&quot;&gt;Supercomputers around the world, which allow access for researchers outside the country&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I have some computer resources at Compute Canada (CC) as part of a project, but to use them, the collaboration would have to fit within the rules of CC and the specific project proposal which I wrote for it last year.&lt;/p&gt;&#xA;&lt;p&gt;Some other threads here which might be interesting to you are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/5018/5&quot;&gt;Are there critical mistakes to avoid when creating a workstation (32-128 cores)?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1125/5&quot;&gt;Materials Modeling with Raspberry Pi?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4635/5&quot;&gt;What are some cloud services for computing?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-16T16:35:11.363" LastActivityDate="2021-06-16T16:35:11.363" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6167" PostTypeId="2" ParentId="6155" CreationDate="2021-06-15T20:42:20.557" Score="3" Body="&lt;p&gt;All keywords in Gaussian (effectively) only accept integers as arguments. Keywords are all translated into &lt;a href=&quot;https://gaussian.com/iops/&quot; rel=&quot;nofollow noreferrer&quot;&gt;IOps&lt;/a&gt; (Internal Options), which are written in the format &lt;code&gt;IOp(overlay/option=value)&lt;/code&gt; where value is always an integer. This seems to have been an early design decision to only allow integer valued options and while Gaussian is open to adding/deprecating features, their design philosophy seems very hesitant about making (potentially breaking) changes to the existing interface.&lt;/p&gt;&#xA;&lt;p&gt;As to why this decision was made, I'm not certain, but I can speculate about a few reasons.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Implicit typing: Gaussian is written in Fortran 77 and its common in language to implicitly type any variables starting with (i,j,k,l,m,n) as integers. So including floats as options would have either required adding a separate variable where float options were stored or keeping track of which options within IOp were floats and explicitly retyping them whenever they were used.&lt;/li&gt;&#xA;&lt;li&gt;Parsing: Minor, but it may just have been more of a pain to parse IOps with floats, since the format allows you to specify multiple options in one IOp section, separated by commas. Combined with some regions using the opposite convention for decimal and thousands separators, they could have thought it was more work than necessary and the design choice stuck.&lt;/li&gt;&#xA;&lt;li&gt;Limiting flexibility: the developers have some sense of what range of options should produce reasonable results and so it can sometimes be advantageous to limit options to avoid faulty values that won't necessarily crash the program, but could give unreasonable results. This is especially true if you know the program could have users who aren't necessarily electronic structure experts. For a case like the step size, they might reason that the max step only needs to be in 0.01 Bohr increments, as more precision is not needed and a smaller magnitude could lead to problems. On the other hand, the specification of the short/long range HF exchange for a hybrid functional (IOp(3/119)=MMMMMNNNNN) needs more precision and so can be specified in increments of &lt;span class=&quot;math-container&quot;&gt;$\frac{\text{MMMMM}}{10000}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\frac{\text{NNNNN}}{10000}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Setting defaults: The IOp documentation mentions that any IOp set to 0 will take on the default value. It would be slightly trickier to set a sentinel default value for a float argument, as conceivably any float could be a possible input (this is not to say its impossible, it just makes the interface slightly more complicated).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-06-15T20:42:20.557" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6168" PostTypeId="2" ParentId="6160" CreationDate="2021-06-15T21:05:27.713" Score="8" Body="&lt;p&gt;&lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/2672/2293&quot;&gt;For this type of calculation, I find MATLAB/Octave to be easier&lt;/a&gt;, at least for demonstrating what to do. You can add the &lt;code&gt;np.&lt;/code&gt; everywhere afterwards if you want to use Python.&lt;/p&gt;&#xA;&lt;p&gt;Assuming you have the following matrices already defined in your workspace:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\eta_z$&lt;/span&gt; = &lt;code&gt;eta&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\tau_x$&lt;/span&gt; = &lt;code&gt;taux&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\tau_y$&lt;/span&gt; = &lt;code&gt;tauy&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\tau_z$&lt;/span&gt; = &lt;code&gt;tauz&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$m_z$&lt;/span&gt; = &lt;code&gt;tauz&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\sigma_z$&lt;/span&gt; = &lt;code&gt;sigmaz&lt;/code&gt;,&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the following scalars:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hbar$&lt;/span&gt; = &lt;code&gt;hbar&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$v_F$&lt;/span&gt; = &lt;code&gt;v&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\lambda_{\textrm{SO}}$&lt;/span&gt; = &lt;code&gt;lambda&lt;/code&gt;,&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt; = &lt;code&gt;kx&lt;/code&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$k_y$&lt;/span&gt; = &lt;code&gt;ky&lt;/code&gt;,&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;the matrix would typically be calculated in the following manner:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eta=kron(kron(kron(eta,eye(length(mz)),eye(length(sigmaz)),eye(length(tauz)); &#xA;mz=kron(kron(eye(length(eta)),mz),eye(length(mz)+length(sigmaz)+length(tauz)))));    &#xA;sigmaz=kron(kron(eye(length(eta)+length(mz)),sigmaz),eye(length(tauz)));    &#xA;tauz=(kron(eye(length(eta)+length(mz)+length(sigmaz)),tauz)));&#xA;taux=(kron(eye(length(eta)+length(mz)+length(sigmaz)),taux)));&#xA;tauy=(kron(eye(length(eta)+length(mz)+length(sigmaz)),tauy)));&#xA;&#xA;h1 = hbar*v*(eta*kx*taux + ky*tauy);&#xA;h2 = lambda*eta*sigmaz*tauz;&#xA;h3 = mz*sigmaz*tauz;&#xA;H = h1+h2+h3;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;The is because typically:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\tau_x,\tau_z,$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\tau_y$&lt;/span&gt; would all lie in the same Hilbert space, and&lt;br&gt; &#xA;&lt;span class=&quot;math-container&quot;&gt;$\eta_z,m_z$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma_z$&lt;/span&gt; would each lie in a different Hilbert spaces to everything else.&lt;/p&gt;&#xA;&lt;p&gt;There's a lot of left and right parentheses which you'd have to be careful about matching, and since there's 6 operators involved across 4 different Hilbert spaces, this is not such a simple example. If you wanted to give a simpler example with fewer operators and types of operators, or to explicitly give each matrix, I could try to simplify my above code. The &lt;code&gt;length(operator)&lt;/code&gt; functions can probably all be replaced by &lt;code&gt;2&lt;/code&gt;, but my code works more generally for arbitrary spin (not just spin-1/2 which has eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt;1, but also spin-1 which has eigenvalues -1,0,1, etc.).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-15T21:31:30.960" LastActivityDate="2021-06-15T21:31:30.960" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6169" PostTypeId="1" CreationDate="2021-06-15T23:17:27.697" Score="12" ViewCount="119" Body="&lt;p&gt;In the field of simulation for energy storage materials, there is always a gap between theoretical calculations and demand for experimentalists. What could be directly calculated from &lt;em&gt;ab initio&lt;/em&gt; calculations (e.g. SCF energy, electron density, optimized geometry, etc.) cannot be instantly interpreted into the properties of the materials. Here the question is: What are the major properties that are relevant when material scientists are designing a novel battery? Among them, what are the properties that can be predicted by theoretical calculations of those materials?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2021-06-15T23:38:31.307" LastActivityDate="2021-06-23T21:38:05.847" Title="What are properties of interest for energy storage materials?" Tags="|ab-initio-calculations|solid-state-physics|materials-design|materials-engineering|experimental|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6170" PostTypeId="2" ParentId="6165" CreationDate="2021-06-16T16:59:24.180" Score="10" Body="&lt;p&gt;If your main limitation is the memory you can make use of old used server machines (approx. 6-10 years old). These machines usually utilize cheap DDR3 server memory chips and support quite impressive capacities (in the range of hundreds of GBs). On the other hand CPU speed is not that impressive even though they are usually dual processor and sport from 8 to 24 cores total.&lt;/p&gt;&#xA;&lt;p&gt;Take a look at HPE DL380e gen8 or HPE DL380p gen8, these are fairly common models which I am familiar with. You can find several reddit threads where people discuss setting up home labs (mostly for storage rather than computation) which can be helpful for you.&lt;/p&gt;&#xA;&lt;p&gt;For about 1000 USD you can probably buy a really powerful machine, especially since you do not need a lot of hard drives which is the main cost of a home lab. Just be sure to consult the documentation to buy the right memory chips (e.g. &lt;a href=&quot;https://support.hpe.com/hpesc/public/docDisplay?docId=emr_na-c03235277&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Also, if you want to go further, you can create a cluster of such machines. Equip them with cheap used 10Gb/25Gb/50Gb/100Gb ethernet cards, preferably with ROCE, and you can run a nice cluster. If you want a 3 machine cluster, then if you buy two port network cards, you can connect machines directly without a network switch. Otherwise, you would need to buy a used (or brand new) 10Gb/25Gb/50Gb/100Gb switch which can be more costly.&lt;/p&gt;&#xA;&lt;p&gt;Last note: beware, these machines can get really loud. They are meant to be placed in a server room, not your living room. The noise will kill you ;-)&lt;/p&gt;&#xA;" OwnerUserId="3774" LastEditorUserId="3774" LastEditDate="2021-06-17T10:06:49.723" LastActivityDate="2021-06-17T10:06:49.723" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6171" PostTypeId="1" CreationDate="2021-06-16T18:15:42.710" Score="9" ViewCount="126" Body="&lt;p&gt;I am looking for a script (preferably in Python) that will suggest (hkl) indices based on distances in an electron diffraction pattern. The crystal structure is known,i.e. I have the CIF file and know the space group.  This has already been done in Fortran, just wanted to know if it was out there in Python!  &lt;a href=&quot;https://www.phase-trans.msm.cam.ac.uk/map/crystal/programs/crystal-b.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;I was able to find a FORTRAN version&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3680" LastEditorUserId="5" LastEditDate="2021-06-28T00:24:37.490" LastActivityDate="2021-06-28T00:24:37.490" Title="Is there a script that will suggest (hkl) indices based on distances in an electron diffraction pattern for a known crystal structure?" Tags="|crystal-structure|python|crystallography|cif|diffraction|" AnswerCount="0" CommentCount="7" ClosedDate="2021-12-15T15:05:37.443" ContentLicense="CC BY-SA 4.0" />
  <row Id="6172" PostTypeId="1" AcceptedAnswerId="6176" CreationDate="2021-06-16T18:47:25.560" Score="10" ViewCount="255" Body="&lt;p&gt;It is not the first time that I stumble upon &lt;a href=&quot;https://pubmed.ncbi.nlm.nih.gov/24639263/&quot; rel=&quot;noreferrer&quot;&gt;the affirmation&lt;/a&gt; that spin and the &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; value, under DFT, has no &amp;quot;real physical meaning&amp;quot;. Why?&lt;/p&gt;&#xA;&lt;p&gt;If that is true, why are we using it all the time with UKS?&lt;/p&gt;&#xA;" OwnerUserId="557" LastEditorUserId="5" LastEditDate="2021-06-17T00:03:06.327" LastActivityDate="2021-06-17T08:48:44.833" Title="Why does the S squared value have no meaning in Density Functional Theory?" Tags="|density-functional-theory|magnetism|spin-polarization|spin-exchange|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6173" PostTypeId="2" ParentId="6165" CreationDate="2021-06-16T22:45:11.787" Score="4" Body="&lt;p&gt;Here's a few (crazy) ideas if your only goal is to make-from-old... (also joined from SO just to post this).&lt;/p&gt;&#xA;&lt;p&gt;If you're talented enough to program the system as low-level as the EEPROM/flash that the BIOS itself is loaded from, and still have reasonable control over the hardware:&lt;/p&gt;&#xA;&lt;p&gt;You could in theory make a communication path via an available RAM slot, but absolutely nothing will support this, so you'd be entirely on your own (writing your own below-BIOS level drivers for chipset, CPU, RAM and your own custom kernel and operating system, &lt;em&gt;&lt;strong&gt;plus&lt;/strong&gt;&lt;/em&gt; the software you need to run). You'd require very sound knowledge in electrical engineering, programming, reverse engineering (nobody tells you how to interface with motherboard hardware directly, that's what the BIOS is for!). Not feasible in the end.&lt;/p&gt;&#xA;&lt;p&gt;You could also communicate over PCI. This might actually work way better than my first crazy idea, but is definitely slower (though since both are theoretical, does that matter?). Again, it would require pretty good knowledge of electrical engineering (and RF now that I think about it; PCs are fast after all), and at the end of the day, the throughput probably won't be great, and certainly nowhere near supercomputer speeds.&lt;/p&gt;&#xA;&lt;p&gt;I realize this means it's not feasible, and that was the original question, but I am the level of crazy to desperately want to try both after thinking about it for a bit, and thought I'd share anyway.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: If I knew my grammar was going to be corrected I wouldn't have posted :)&lt;/p&gt;&#xA;" OwnerUserId="3776" LastEditorUserId="3776" LastEditDate="2021-06-16T23:24:26.537" LastActivityDate="2021-06-16T23:24:26.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6174" PostTypeId="2" ParentId="6143" CreationDate="2021-06-17T00:34:13.207" Score="9" Body="&lt;p&gt;One way could be as follow.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Download software &lt;a href=&quot;http://leandro.iqm.unicamp.br/m3g/packmol/home.shtml&quot; rel=&quot;noreferrer&quot;&gt;PACKMOL&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Download the examples files (&lt;a href=&quot;http://leandro.iqm.unicamp.br/m3g/packmol/examples/examples.tar.gz&quot; rel=&quot;noreferrer&quot;&gt;tar.gz&lt;/a&gt; or &lt;a href=&quot;http://leandro.iqm.unicamp.br/m3g/packmol/examples/examples.zip&quot; rel=&quot;noreferrer&quot;&gt;zip&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Modify the file &lt;em&gt;solvprotein-comment.inp&lt;/em&gt;: removing the info about the protein, and the ions and define the number of water molecules and the size of the droplet:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;#&#xA;# Protein solvated by water and ions&#xA;#&#xA;&#xA;&#xA;# All atoms from diferent molecules will be at least 2.0 Angstroms apart&#xA;# at the solution&#xA;&#xA;tolerance 2.0&#xA;&#xA;# The type of the files will be pdb &#xA;&#xA;filetype pdb&#xA;&#xA;# The name of the output file&#xA;&#xA;output solvprotein.pdb&#xA;&#xA;# The protein will be fixed with its center of mass at center of the&#xA;# box, and no rotation (the first three zeros correspond to the position&#xA;# of the center of mass and the last three correspond to the euler&#xA;# angles of rotation, in radian, relative to the position in the input&#xA;# file). &#xA;&#xA;#structure protein.pdb&#xA;#  number 0&#xA;#  fixed 0. 0. 0. 0. 0. 0.&#xA;#  centerofmass&#xA;#end structure&#xA;&#xA;# Water molecules will be put inside a sphere that contains the protein.&#xA;# There will be 16500 water molecules that will be put in a sphere&#xA;# centered in the origin, and a radius of 50. Angstroms.&#xA;&#xA;structure water.pdb&#xA;  number 300&#xA;  inside sphere 0. 0. 0. 10.&#xA;end structure&#xA;&#xA;# The ions will be put in the same region as the water molecules, so&#xA;# they will be inside the water sphere and will be solvating the protein&#xA;# as well.&#xA;&#xA;#structure CLA.pdb&#xA;#  number 0&#xA;#  inside sphere 0. 0. 0. 50.&#xA;#end structure&#xA;&#xA;#structure SOD.pdb&#xA;#  number 0&#xA;#  inside sphere 0. 0. 0. 50.&#xA;#end structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;Run the program as &lt;code&gt;packmol &amp;lt; solvprotein-comment.inp&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Go to &lt;a href=&quot;http://charmm-gui.org/&quot; rel=&quot;noreferrer&quot;&gt;charmm.gui&lt;/a&gt; server and generate the input for NAMD.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I run for three droplets with 300 water molecules and 5 (blue), 10 (cyan) and 15 (yellow) angstroms. The image are bellow.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/erQLk.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/erQLk.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-06-17T00:34:13.207" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6175" PostTypeId="1" CreationDate="2021-06-17T07:56:21.443" Score="9" ViewCount="121" Body="&lt;p&gt;We're starting to develop some calculations of the hyperfine parameters (electric field gradient, spin-rotation coupling, spin-spin coupling) with CFOUR, and we reached a limitation of the public version, which is the impossibility to get the parameters for levels other than the ground vibrational state.&lt;/p&gt;&#xA;&lt;p&gt;We wish to extend this study to v=1-4 of a closed shell &amp;quot;light&amp;quot; diatomic molecules, as well to triatomic molecules (still at relatively low energy).&lt;/p&gt;&#xA;&lt;p&gt;Which package(s) could you recommend?&lt;/p&gt;&#xA;&lt;p&gt;Possibly, the rotational constant, vibrational energies and transition intensities will be calculated.&#xA;Open-source or free packages are a plus.&lt;/p&gt;&#xA;" OwnerUserId="3784" LastEditorUserId="5" LastEditDate="2021-06-17T21:44:31.967" LastActivityDate="2021-06-18T00:24:51.843" Title="Package for computing properties of excited vibrational states" Tags="|one-topic-per-answer|software-recommendations|spectroscopy|vibrations|fine-and-hyperfine-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6176" PostTypeId="2" ParentId="6172" CreationDate="2021-06-17T08:48:44.833" Score="6" Body="&lt;p&gt;The Kohn-Sham wavefunction is the wavefunction of a hypothetical system where:&lt;/p&gt;&#xA;&lt;p&gt;(1) there is no interaction between the electrons,&lt;/p&gt;&#xA;&lt;p&gt;(2) the electrons are subject to a repulsive potential (the Hartree-exchange-correlation potential) in addition to the nuclear attraction potential, and&lt;/p&gt;&#xA;&lt;p&gt;(3) the effect of (2) effectively counterbalances the effect of (1), in the sense that the total electronic density of the hypothetical system is exactly the same with the density of the corresponding real electronic system. Usually we are talking about spin density functional theory, which not only requires the total density to be equal, but also that the alpha electronic density and the beta electronic density are both equal to their exact counterparts.&lt;/p&gt;&#xA;&lt;p&gt;As we can see, there is no requirement that the &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; value of the hypothetical system be the same as that of the real system. The corollary is that a spin-pure electronic state may correspond to a Kohn-Sham wavefunction that is spin-contaminated. And this does happen frequently, as can be shown from the following argument: imagine an exact electronic eigenstate whose &lt;span class=&quot;math-container&quot;&gt;$S=1/2$&lt;/span&gt;, and we plot its spin density. The spin density will have positive values in most parts of the space, but can adopt small negative values in certain regions (e.g. near atomic nuclei) due to spin polarization. A spin-adapted (restricted open-shell) Kohn-Sham determinant however can only give an everywhere non-negative spin density. This proves that the exact Kohn-Sham wavefunction must be spin-contaminated, so that a ROKS wavefunction is less theoretically justified than a UKS wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;That being said, the &lt;span class=&quot;math-container&quot;&gt;$\langle S^2 \rangle$&lt;/span&gt; value can still be used to characterize the reliability of a DFT calculation. This is because, while the exact DFT functional performs equally well (by definition, always exactly) for all electronic systems, essentially all approximate functionals only perform well when the exact wavefunction is mostly single-determinantal, and heuristically, the exact wavefunction is usually manifestly multi-determinantal when the corresponding Kohn-Sham wavefunction is heavily spin-contaminated. Thus, while the &lt;span class=&quot;math-container&quot;&gt;$\langle S^2 \rangle$&lt;/span&gt; value in DFT is not rigorously tied to any physically observable quantity, one can still arrive at meaningful conclusions about the reliability of a DFT calculation using the &lt;span class=&quot;math-container&quot;&gt;$\langle S^2 \rangle$&lt;/span&gt; value.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-06-17T08:48:44.833" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6177" PostTypeId="2" ParentId="6175" CreationDate="2021-06-17T21:30:32.187" Score="6" Body="&lt;h1&gt;LEVEL&lt;/h1&gt;&#xA;&lt;p&gt;Given a well-behaved electronic potential energy curve for a &lt;em&gt;diatomic&lt;/em&gt; molecule, LEVEL will &amp;quot;automatically locate and calculate expectation values&#xA;for all vibration–rotation levels&amp;quot;. This means that for any operator &lt;span class=&quot;math-container&quot;&gt;$\hat{M}$&lt;/span&gt;, you can calculate the expectation values for each vibrational level &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; and each associated rotational level &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \psi_{v,J}| \hat{M}|\psi_{v,J}\rangle, \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which means that you can certainly calculate properties for &lt;span class=&quot;math-container&quot;&gt;$v=1-4$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$J=0$&lt;/span&gt; (as well as also with higher &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; values). This program was a project that Bob Le Roy worked on since the 1960s, and had contributions from several others over the decades, including myself. The latest version available online was from 2016, so I pushed the most recent version I could find today into Github &lt;a href=&quot;https://github.com/HPQC-LABS/LEVEL&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; (let me know if you have any trouble compiling it, while I work on adding a &lt;code&gt;Makefile&lt;/code&gt; and sample input file for you).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free and open-source&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Extremely accurate&lt;/em&gt;, and &lt;em&gt;extremely fast&lt;/em&gt; (orders of magnitude faster and more black-box than other radial Schroedinger solvers I know some others have used)&lt;/li&gt;&#xA;&lt;li&gt;Widely used and with a rich history spanning several decades&lt;/li&gt;&#xA;&lt;li&gt;There's not a lot of other programs available with this type of functionality&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Only works for diatomics&lt;/li&gt;&#xA;&lt;li&gt;As you are a CFOUR user, you might be used to getting ground state vibrational properties in a much more black-box way. Here you'd have to build the electronic potential energy curve with a program like CFOUR, then enter it into LEVEL and climb a slight learning curve as you need to check convergence and such more manually in LEVEL than you would for single-point energy calculations (within a basis set and level of theory) in CFOUR.&lt;/li&gt;&#xA;&lt;li&gt;You may have to define &lt;span class=&quot;math-container&quot;&gt;$\hat{M}$&lt;/span&gt; yourself in the FORTRAN code if the particular &lt;span class=&quot;math-container&quot;&gt;$\hat{M}$&lt;/span&gt; that interests you is not available by default (since I've been using this software since about 15 years ago, I can probably help you with this if you want to collaborate).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-18T00:24:51.843" LastActivityDate="2021-06-18T00:24:51.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6178" PostTypeId="1" AcceptedAnswerId="6179" CreationDate="2021-06-17T21:56:31.143" Score="11" ViewCount="733" Body="&lt;p&gt;I'm trying to calculate dipole moments from Wannier centers for the first time and there are basics I don't understand and can't figure out from online resources.&lt;/p&gt;&#xA;&lt;p&gt;The software I'm using has a simple &amp;quot;output Wannier centers&amp;quot; option.  So I now have output, which is a file with Wannier centers and atomic positions.  My system contains many water molecules but here's a simple example for a system that has only one H2O. The &amp;quot;X&amp;quot; are Wannier centers:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;X          6.50000026       6.18706578       6.50000000&#xA;X          6.50000000       6.71337672       6.50000002&#xA;X          6.50000008       6.95339960       6.49999998&#xA;X          6.49999971       6.54636884       6.50000000&#xA;H          6.50000000       7.09480000       7.26880000&#xA;H          6.50000000       7.09480000       5.73120000&#xA;O          6.50000000       6.50000000       6.50000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Why are there four X for one H2O?  I vaguely assumed that there would be one X, corresponding to one H2O.  Do the four X correspond somehow to different molecular configuration possibilities?  I have tried to look this up but probably don't even know the right search terms.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I included &amp;quot;Wannier90&amp;quot; as a tag because it seems relevant and generates output formatted like my example but I am not using Wannier90.&lt;/p&gt;&#xA;" OwnerUserId="1035" LastActivityDate="2021-06-18T23:20:19.750" Title="I generated Wannier centers but am having trouble understanding how they relate to the atoms in my system: there are more Wannier centers than atoms?" Tags="|molecular-dynamics|molecular-modeling|dipole|wannier90|polarizability|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6179" PostTypeId="2" ParentId="6178" CreationDate="2021-06-17T23:22:06.983" Score="12" Body="&lt;p&gt;H2O has 10 electrons, two of which are oxygen 1s. This leaves you eight electrons. These eight electrons fit onto 4 spatial orbitals in a spin-restricted calculation for the singlet.&lt;/p&gt;&#xA;&lt;p&gt;Determining localized orbitals [1] (for periodic boundary conditions these are called Wannier functions), the 4 orbitals localize into two covalent OH bonds, and two lone pairs on the oxygen atom. You have obtained the centroids of these orbitals, which are determined by the expectation value &lt;span class=&quot;math-container&quot;&gt;$\langle {\bf r} \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;[1]: Note that there is more than one way to determine localized orbitals; for instance, we have proposed Pipek-Mezey Wannier functions in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.6b00809&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 2017, 13, 2, 460–474&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-06-18T23:20:19.750" LastActivityDate="2021-06-18T23:20:19.750" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6180" PostTypeId="2" ParentId="3710" CreationDate="2021-06-18T09:09:32.437" Score="5" Body="&lt;p&gt;Another option is &lt;strong&gt;ALF&lt;/strong&gt; (Algorithms for Lattice Fermions), an auxiliary-field quantum Monte Carlo package. According to its &lt;a href=&quot;https://alf.physik.uni-wuerzburg.de&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;it can simulate any Hamiltonian that can be written in terms of sums of:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;single-body operators,&lt;/li&gt;&#xA;&lt;li&gt;squares of single-body operators, and&lt;/li&gt;&#xA;&lt;li&gt;single-body operators coupled to an Ising field with given dynamics.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And you can also specify a Bravais lattice and observables, besides the package's predefined ones.&lt;/p&gt;&#xA;&lt;p&gt;Like with other QMC codes, you have to make sure your Hamiltonian doesn't have a &lt;a href=&quot;https://en.wikipedia.org/wiki/Numerical_sign_problem&quot; rel=&quot;nofollow noreferrer&quot;&gt;sign problem&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;: a more detailed description of the package can be found in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6204/625&quot;&gt;this answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disclaimer&lt;/strong&gt;: I've contributed to the package.&lt;/p&gt;&#xA;" OwnerUserId="625" LastEditorUserId="625" LastEditDate="2021-06-20T08:43:23.327" LastActivityDate="2021-06-20T08:43:23.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6181" PostTypeId="1" CreationDate="2021-05-22T16:32:36.293" Score="7" ViewCount="637" Body="&lt;p&gt;I'm trying to install something called ASE that models atomic structures. I have ASE currently installed on python 3.7, however I need to run scripts that can import and recognize ASE in an older version of python (specifically python/anaconda2.7-5.2.0). For additional trouble, ASE cannot be downloaded on any python older than 3.6. For some reason, when I switch to the older version of python to run the scripts I need, they don't recognize that ASE is downloaded. Is this because ASE is downloaded on a newer version of python? If this is the case, since I cannot download ASE onto the older version of python, how can I get the script to run?&lt;/p&gt;&#xA;&lt;p&gt;(Brand new to coding! I don't know a whole lot so sorry in advance!)&lt;/p&gt;&#xA;" OwnerDisplayName="Malena Rybacki" LastEditorUserId="5" LastEditDate="2021-06-18T14:19:03.617" LastActivityDate="2021-06-23T22:06:06.830" Title="Downloading ASE (Atomic Simulation Environment) on older versions of Python" Tags="|python|software-assistance|atomic-simulation-environment|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6182" PostTypeId="1" CreationDate="2021-06-18T12:31:11.193" Score="6" ViewCount="876" Body="&lt;p&gt;I am trying to write a tcl script to measure percentage helicity at each frame of a VMD .dcd trajectory. I found the following discussion on the VMD mailing list&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;to calculate the secondary structure for a selection at a given timestep, you should go to that timestep, and the use the command mol reanalyze top which runs that timestep through stride (among other things). Once this is done, you can access the secondary structure of an atomselect object with&#xA;$sel get structure&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have tried to implement it as follows,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set outfile [open ./percent_helix.dat w]&#xA;set lookup {H G I}&#xA;set frame_num [molinfo top get numframes]&#xA;set full [atomselect top &amp;quot;name CA&amp;quot;]&#xA;set len [llength [$full get resid]]&#xA;&#xA;for {set i 0} {&lt;span class=&quot;math-container&quot;&gt;$i &amp;lt; $&lt;/span&gt;frame_num} {incr i} {&#xA;    set helix 0&#xA;    &lt;span class=&quot;math-container&quot;&gt;$full frame i&#xA;    $&lt;/span&gt;full update&#xA;    mol reanalyze top&#xA;    set struc_string [&lt;span class=&quot;math-container&quot;&gt;$full get structure]&#xA;    foreach letter $&lt;/span&gt;lookup {&#xA;        set temp [expr {[llength [split &lt;span class=&quot;math-container&quot;&gt;$struc_string $&lt;/span&gt;letter]] - 1}]&#xA;        incr helix &lt;span class=&quot;math-container&quot;&gt;$temp&#xA;    }&#xA;    set percent [expr {double($helix) / double($len) * 100}]&#xA;    puts $&lt;/span&gt;outfile &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$i\t$&lt;/span&gt;percent&amp;quot;&#xA;}&#xA;&lt;span class=&quot;math-container&quot;&gt;$full delete&#xA;close $&lt;/span&gt;outfile&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the output i am the same percentage value at each timestep. I have figured that the reason behind that is the command &lt;code&gt;mol reanalyze top&lt;/code&gt; is not changing the secondary structure values at each frame. What should I correct in my script?&lt;/p&gt;&#xA;" OwnerUserId="1605" LastEditorUserId="5" LastEditDate="2021-06-18T14:25:06.487" LastActivityDate="2021-06-19T03:01:54.783" Title="Secondary structure information at each frame in a VMD trajectory" Tags="|molecular-dynamics|proteins|vmd|protein-folding|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6183" PostTypeId="1" AcceptedAnswerId="6242" CreationDate="2021-06-18T14:30:25.497" Score="13" ViewCount="527" Body="&lt;p&gt;Quantifying the similarity of crystal structures is important to understand and predict the properties of less-studied crystals. For example, the inorganic crystal structure database (ICSD) contains over 200,000 crystal structures and most crystal structures are labelled with a &amp;quot;structure type&amp;quot; in addition to other symmetry information and experimental details. &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe2O3}$&lt;/span&gt;, for instance belongs to Corundum &lt;span class=&quot;math-container&quot;&gt;$\ce{Al2O3}$&lt;/span&gt; structure indicating high similarity between these two crystals. I wonder whether they find &amp;quot;structure type&amp;quot; by manual inspection.&lt;/p&gt;&#xA;&lt;p&gt;My question is, are there any high-throughput tools to compare crystal structures and obtain a similarity measure between them? Ideally, I should be able to load crystal structures from a standard file format such as cif and quantify their similarity using a python/bash program. Is this feature available in tools such as pymatgen, ase, etc.?&lt;/p&gt;&#xA;&lt;p&gt;I understand that I can try to represent crystal structures with conventional methods such as coulomb matrix or more recent methods such as crystal graph neural network and then, capture cosine similarity between latent representations. But are there any out-of-the-box tools to do this?&lt;/p&gt;&#xA;" OwnerUserId="857" LastActivityDate="2021-06-24T21:59:17.937" Title="High throughput tool to quantify the similarity of crystal structures?" Tags="|crystal-structure|crystallography|materials-design|pymatgen|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6184" PostTypeId="1" AcceptedAnswerId="6198" CreationDate="2021-06-18T15:38:52.857" Score="9" ViewCount="1611" Body="&lt;p&gt;I'm trying to do a redundant PES scan of a hydrogen abstraction in a Gaussian job while maintaining the rest of the system fixed. I need to scan the coordinate where H5 approaches to H6, maintaining the rest of the methane in place (that is, increasing the C1 H5 bond length). When I do a scan, the H6 just approaches H5. Is there a way so I can freeze everything except the coordinates of H5? So the distance between C1 and H5 increases and the distance between H5 and H6 decreases.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nz25C.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nz25C.png&quot; alt=&quot;Methane and Hydrogen abstraction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3797" LastEditorUserId="1380" LastEditDate="2021-06-19T09:55:13.410" LastActivityDate="2021-06-20T12:14:51.307" Title="Is it possible to do a Gaussian redundant scan with some fixed bonds?" Tags="|gaussian|geometry-optimization|potential-energy-surface|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6185" PostTypeId="1" CreationDate="2021-06-18T16:12:55.610" Score="11" ViewCount="117" Body="&lt;p&gt;I'm calculating condensed Fukui functions to explain the reactivity of my molecules.&lt;/p&gt;&#xA;&lt;p&gt;The manual for Multiwfn suggests using atomic dipole moment corrected Hirshfeld charges for it. However I get strange results, on some atoms in which &lt;span class=&quot;math-container&quot;&gt;$f^+$&lt;/span&gt; is negative.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I'm using def2-TZVPD basis set, and I'm wondering if diffuse functions can make Hirshfeld charges meaningless as they do for Mulliken charges?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-12-15T07:25:20.263" LastActivityDate="2021-12-15T07:25:20.263" Title="Should augmented basis be used for Hirshfeld charges?" Tags="|basis-sets|charge-density|conceptual-dft|multiwfn|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-07T03:08:16.970" ContentLicense="CC BY-SA 4.0" />
  <row Id="6186" PostTypeId="2" ParentId="6184" CreationDate="2021-06-18T16:22:12.207" Score="7" Body="&lt;p&gt;It can be done using &lt;code&gt;ModRedundant&lt;/code&gt; option in Gaussian (more on that &lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;). You just freeze everything in space except for the 5th and 6th hydrogen.&lt;/p&gt;&#xA;&lt;p&gt;However, in my opinion it would be better to perform a so called relaxed scan (a series of optimizations with the scanned coordinate fixed to certain values) as it yields better geometries for system states during the reaction.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-06-18T17:28:47.037" LastActivityDate="2021-06-18T17:28:47.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6187" PostTypeId="2" ParentId="1695" CreationDate="2021-06-18T18:07:21.643" Score="3" Body="&lt;h3&gt;NECI (N-electron configuration interaction solver)&lt;/h3&gt;&#xA;&lt;p&gt;This is a free and open-source software written mainly in FORTRAN but with components in C/C++ and Python. &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0005754&quot; rel=&quot;nofollow noreferrer&quot;&gt;It has been shown on a FeMoco calculation to have a parallelization efficiency of 99.7% up to at least 24800 cores&lt;/a&gt;. It does FCIQMC and has been used on Hubbard models in several papers, perhaps the most recent being this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.075119&quot; rel=&quot;nofollow noreferrer&quot;&gt;2019 paper where they treated a Hubbard model with up to 50 sites, and compared the FCIQMC result with AF-QMC&lt;/a&gt;. This &lt;a href=&quot;https://www.cond-mat.de/events/correl16/talks/alavi.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDF presentation&lt;/a&gt; also indicates that calculations have been done on the 3-band Hubbard model.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free, open-source, available on &lt;a href=&quot;https://github.com/ghb24/NECI_STABLE&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Very well tested on 24000+ cores (high parallel efficiency)&lt;/li&gt;&#xA;&lt;li&gt;Fairly big list of very active developers&lt;/li&gt;&#xA;&lt;li&gt;Relatively easy to contribute/add your own features or make tweaks (I speak from experience)&lt;/li&gt;&#xA;&lt;li&gt;Has a lot of state-of-the-art FCIQMC methods incorporated&lt;/li&gt;&#xA;&lt;li&gt;Works on a rather large range of problems, not just Hubbard Hamiltonians but also molecular Hamiltonians and can easily be adapted to work on other Hamiltonians&lt;/li&gt;&#xA;&lt;li&gt;There's a &lt;a href=&quot;https://molcas.gitlab.io/OpenMolcas/sphinx/installation.guide/stochcas.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;NECI interface with OpenMOLCAS&lt;/a&gt; and a &lt;a href=&quot;https://www.molpro.net/info/2015.1/doc/manual/node379.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;NECI interface with MOLPRO&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-18T18:07:21.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6188" PostTypeId="1" AcceptedAnswerId="6191" CreationDate="2021-06-19T00:20:00.093" Score="11" ViewCount="1144" Body="&lt;p&gt;I was very interested in the following question and answer about the Slater- and Gaussian-type orbitals (STO and GTO) used in quantum chemistry and a practical calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4383/gaussian-type-orbitals-vs-slater-type-orbitals-in-terms-of-computational-efficie&quot;&gt;Gaussian-type orbitals vs Slater-type orbitals in terms of computational efficiency&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;After reading this discussion, I am further interested in the critical difference and roles of these STO and GTO orbitals, because I have considered (or misunderstood!) that the STO is actually hard to calculate but always outperforms the GTO in computational accuracy.&lt;/p&gt;&#xA;&lt;p&gt;My question is that, does the GTO simply represent the STO by using many Gaussians, or not? &lt;/p&gt;&#xA;&lt;p&gt;Intuitively, it would be better to use many GTOs to represent the molecular orbitals in a many electron system in a flexible way, because it is not bound by the form of the hydrogen atom wavefunction. However, the GTO does not have a cusp and so... I'm very wondering how to understand this problem.&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-06-19T01:45:28.940" LastActivityDate="2021-06-20T23:27:28.757" Title="Critical difference and roles of Slater- and Gaussian-type orbitals" Tags="|quantum-chemistry|basis-sets|orbitals|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6189" PostTypeId="1" CreationDate="2021-06-19T00:57:13.220" Score="8" ViewCount="231" Body="&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/a/16634/16035&quot;&gt;@JohnCuster's answer to &lt;em&gt;Why is gold golden?&lt;/em&gt;&lt;/a&gt; is based on the band structure of the delocalized conduction electrons in gold, whereas other answers there tend to support the &amp;quot;Gold is gold due to relativistic shifts in atomic orbitals&amp;quot; &lt;a href=&quot;https://chemistry.stackexchange.com/a/16636/16035&quot;&gt;comparing silver to gold for example&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The absorption you see is a &lt;span class=&quot;math-container&quot;&gt;$\mathrm{5d \rightarrow 6s}$&lt;/span&gt; transition. For the silver &lt;span class=&quot;math-container&quot;&gt;$\mathrm{4d \rightarrow 5s}$&lt;/span&gt; transition, &lt;strong&gt;the absorption is in the UV region&lt;/strong&gt;, but the contraction gives gold a blue absorption (&lt;em&gt;i.e.&lt;/em&gt; less blue is reflected). Our eyes thus see a yellow color reflected.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;as does &lt;a href=&quot;https://physics.stackexchange.com/a/646118/83380&quot;&gt;this answer to &lt;em&gt;Why do “relativistic effects” come into play, when dealing with superheavy atoms?&lt;/em&gt;&lt;/a&gt;, and &lt;a href=&quot;https://space.stackexchange.com/a/32989/12102&quot;&gt;my answer to &lt;em&gt;How does the thin gold film in the glass of spacesuit helmets block thermal IR but transmit visible? What's the property?&lt;/em&gt;&lt;/a&gt; also parrots the absorption line theory (citing an ACS &amp;quot;communities post&amp;quot;) and lists specific gold atomic lines in the blue.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question(s):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Can the color of gold metal be reproduced by modeling only the conduction electron band structure, or is it necessary to invoke atomic absorption lines?&lt;/li&gt;&#xA;&lt;li&gt;Since the conduction bands depend on the details of the localized atomic structure, does it turn out that a relativistic effect affects those, and so indirectly affects the conduction bands and their optical properties?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ImgRM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ImgRM.png&quot; alt=&quot;metal reflectivities from near IR to visible to near UV; gold, silver and aluminum&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Image-Metal-reflectance.png&quot; rel=&quot;noreferrer&quot;&gt;Source&lt;/a&gt;, found in Wikipedia's &lt;a href=&quot;https://en.wikipedia.org/wiki/Relativistic_quantum_chemistry&quot; rel=&quot;noreferrer&quot;&gt;Relativistic quantum chemistry&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2021-06-19T04:34:21.933" LastActivityDate="2021-06-21T13:19:37.490" Title="Can the color of gold metal be reproduced by modeling only the conduction electron band structure, or do atomic absorption lines contribute?" Tags="|electronic-structure|transition-metals|optical-properties|metals|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6190" PostTypeId="1" AcceptedAnswerId="6193" CreationDate="2021-06-19T02:12:42.290" Score="8" ViewCount="2111" Body="&lt;p&gt;I'm now studying the quantum chemistry calculation and Gaussian basis set.&lt;/p&gt;&#xA;&lt;p&gt;For example, when using the 6-31G basis set,&#xA;the C atom has 6 basis functions in 1s orbital:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;whereas the O atom also has 6 basis functions in 1s orbital:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;3+1=4 in &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;That is, the number of basis functions is the same in these two atoms, is it correct?&lt;/p&gt;&#xA;&lt;p&gt;I think that the O atom has more electrons than the C atom, so the number of basis functions should be different and the O atom should have more basis functions than the C atom, but is this my misunderstanding?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-06-19T03:45:12.523" LastActivityDate="2021-06-19T09:07:48.313" Title="Is the number of basis functions same in the different atoms in the 6-31G basis set?" Tags="|gaussian|basis-sets|orbitals|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6191" PostTypeId="2" ParentId="6188" CreationDate="2021-06-19T02:18:20.117" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My question is that, does the GTO simply represent the STO by using many Gaussians, or not?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There does exist the &lt;a href=&quot;https://en.wikipedia.org/wiki/STO-nG_basis_sets&quot; rel=&quot;noreferrer&quot;&gt;STO-nG basis set family&lt;/a&gt; in which &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; Gaussian orbitals are fitting to represent a single STO. These are never used for serious applications to predict spectroscopic, thermodynamical, or kinetic properties of molecules (or atoms) though. They can be seen for testing new software, and recently they've started to get used for testing quantum computing hardware, but they are simply not accurate enough for serious applications.&lt;/p&gt;&#xA;&lt;p&gt;For more commonly used basis sets like the cc-pVXZ series, I don't like to think of GTOs the above way. The parameters of the GTOs are not optimized to reproduce a single STO, but instead for something else such as minimizing the energy given some constraints.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps for the sole case of a hydrogen atom, where the wavefunction obtained from solving the Schroedinger equation (with a non-relativistic Hamiltonian, not containing any fine, hyperfine, or other terms which would make it more accurate) would have the STO shape, you can think of a large number of GTOs &amp;quot;modeling&amp;quot; the STO shape. &lt;em&gt;&lt;strong&gt;But&lt;/strong&gt;&lt;/em&gt; for many-electron systems, the true wavefunction is not necessarily going to have a shape descried by STOs, so I would just say the GTOs are modeling the shape of the wavefunction, not the shape of the STO.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-19T03:42:57.807" LastActivityDate="2021-06-19T03:42:57.807" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6192" PostTypeId="2" ParentId="6182" CreationDate="2021-06-19T03:01:54.783" Score="6" Body="&lt;p&gt;I have found the solution to the problem. One needs to use the &lt;code&gt;animate&lt;/code&gt; command to change the frame in the top molecule in VMD. The corrected script which produces the desired output is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set outfile [open ./percent_helix.dat w]&#xA;set lookup {H G I}&#xA;set frame_num [molinfo top get numframes]&#xA;set full [atomselect top &amp;quot;name CA&amp;quot;]&#xA;set len [llength [&lt;span class=&quot;math-container&quot;&gt;$full get resid]]&#xA;$&lt;/span&gt;full delete&#xA;&#xA;for {set i 0} {&lt;span class=&quot;math-container&quot;&gt;$i &amp;lt; $&lt;/span&gt;frame_num} {incr i} {&#xA;    animate goto &lt;span class=&quot;math-container&quot;&gt;$i&#xA;    set sel [atomselect top &quot;name CA&quot;]&#xA;    mol ssrecalc top&#xA;    set struc_string [$&lt;/span&gt;sel get structure]&#xA;    set helix 0&#xA;    foreach letter &lt;span class=&quot;math-container&quot;&gt;$lookup {&#xA;        set temp [expr {[llength [split $struc_string $letter]] - 1}]&#xA;        incr helix $temp&#xA;    }&#xA;    set percent [expr {double($helix) / double($len) * 100}]&#xA;    puts $&lt;/span&gt;outfile &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$i\t$&lt;/span&gt;percent&amp;quot;&#xA;    &lt;span class=&quot;math-container&quot;&gt;$sel delete&#xA;}&#xA;close $&lt;/span&gt;outfile&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1605" LastActivityDate="2021-06-19T03:01:54.783" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6193" PostTypeId="2" ParentId="6190" CreationDate="2021-06-19T03:57:26.590" Score="8" Body="&lt;p&gt;Yes you're absolutely correct that the basis sets for O and C will typically have the same number of orbitals (not just for the 6-31G basis set but also for the famous cc-pVXZ family, and other basis sets).&lt;/p&gt;&#xA;&lt;p&gt;It's true that O has more electrons than C, but in both cases, the electrons are primarily occupied in the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$2p$&lt;/span&gt; orbitals. If you're considering to trim down the carbon basis set to have only &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt; (i.e. to remove &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt;) things can get imbalanced.&lt;/p&gt;&#xA;&lt;p&gt;B, C, N, O, F, and Ne will typically all have the same number of basis functions for a given basis set label (such as cc-pVDZ), whereas the corresponding atoms in the next row: Al, Si, P, S, Cl, and Ar will have a slightly bigger basis set than the previous atoms, but they will all have the same number of basis functions as each other.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-19T03:57:26.590" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6194" PostTypeId="1" AcceptedAnswerId="6249" CreationDate="2021-06-19T04:10:48.973" Score="7" ViewCount="226" Body="&lt;p&gt;Scanning tunneling microscopy comes in several flavors; vanilla (traditional STM) is &lt;a href=&quot;https://en.wikipedia.org/wiki/Scanning_tunneling_microscope#Procedure&quot; rel=&quot;noreferrer&quot;&gt;constant current&lt;/a&gt; where the tip height is varied to maintain a constant current at a set constant bias&lt;sup&gt;1&lt;/sup&gt; and the signal controlling the tip height is reported, and &lt;a href=&quot;https://en.wikipedia.org/wiki/Neapolitan_ice_cream&quot; rel=&quot;noreferrer&quot;&gt;neapolitan&lt;/a&gt; is &lt;a href=&quot;https://en.wikipedia.org/wiki/Scanning_tunneling_spectroscopy#Experimental_methods&quot; rel=&quot;noreferrer&quot;&gt;Scanning tunneling spectroscopy&lt;/a&gt; or dI/dV which can be implemented in various ways but usually uses a high frequency AC component to the bias above the frequency response of the feedback loop to &amp;quot;dither&amp;quot; and sense the differential conductivity at some average bias.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3502&quot;&gt;This answer to &lt;em&gt;Quantifying electronic overlap?&lt;/em&gt;&lt;/a&gt; briefly mentions in passing quantum ESPRESSO and CP2K in the context of STM, and &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4117&quot;&gt;this answer to &lt;em&gt;About the surface Greens function method for calculating the surface state&lt;/em&gt;&lt;/a&gt; briefly mentions in passing the open-source package WannierTools in the context of STM as well, but as far as I can tell this issue hasn't really been addressed in this site yet.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question(s):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How can scanning tunneling microscopy images (constant current and dI/dV conductivity) be simulated? I see that the linked Wikipedia articles contain some integrals, but in practice this is a complicate problem involving DOS of both the tip material and sample material, tunneling geometry and matrix elements for coupling into/out of (or simply between) those states. Has this ever actually been worked out in detail? (Assume DOS has previously been calculated, I'm only asking about simulation of the tunneling data.)&lt;/li&gt;&#xA;&lt;li&gt;What's under the hood in software packages that do this (well)? How far do they go down the rabbit hole of modeling this complex process?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt;Tip bias can be positive to sample (tunnel electrons from) filled states, or negative to sample (tunnel electrons into) empty states.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2021-06-19T04:16:47.577" LastActivityDate="2021-06-26T12:20:30.903" Title="How can scanning tunneling microscopy images (constant current and dI/dV conductivity) be simulated? What's under the hood in software packages?" Tags="|reference-request|surfaces|density-of-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6195" PostTypeId="1" CreationDate="2021-06-19T06:13:26.153" Score="9" ViewCount="107" Body="&lt;p&gt;The method I found, which seems to be the most commonly used for simulating surfaces, involves constructing a slab and doing a structural optimization by freezing a few of its lowermost layers.&lt;/p&gt;&#xA;&lt;p&gt;What confuses me is, how thick should such layers be? Also how many layers should be frozen?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2021-12-15T07:30:46.513" LastActivityDate="2021-12-15T07:30:46.513" Title="How to calculate the thickness of the slab when simulating a bulk surface?" Tags="|surfaces|physical-properties-of-materials|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-13T02:06:30.557" ContentLicense="CC BY-SA 4.0" />
  <row Id="6196" PostTypeId="2" ParentId="6190" CreationDate="2021-06-19T09:07:48.313" Score="7" Body="&lt;p&gt;I think that it is a feature of how the basis set is defined. 6-31G is a valence double-zeta basis set of the Pople family. Here, 6 means that the core orbitals are represented with 6 Gaussian functions (GTO) while 31 means the valence orbitals are split into two orbitals with the scheme 3 GTO + 1 GTO. So, I looked at the basis set data for 6-31G, and it seems to be clear how the orbitals are assigned.&lt;/p&gt;&#xA;&lt;p&gt;For example, look at the basis sets of N, P and As (group 15):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NITROGEN&#xA;S   6&#xA;1         0.4173511460E+04       0.1834772160E-02&#xA;2         0.6274579110E+03       0.1399462700E-01&#xA;3         0.1429020930E+03       0.6858655181E-01&#xA;4         0.4023432930E+02       0.2322408730E+00&#xA;5         0.1282021290E+02       0.4690699481E+00&#xA;6         0.4390437010E+01       0.3604551991E+00&#xA;L   3&#xA;1         0.1162636186E+02      -0.1149611817E+00       0.6757974388E-01&#xA;2         0.2716279807E+01      -0.1691174786E+00       0.3239072959E+00&#xA;3         0.7722183966E+00       0.1145851947E+01       0.7408951398E+00&#xA;L   1&#xA;1         0.2120314975E+00       0.1000000000E+01       0.1000000000E+01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For nitrogen &lt;span class=&quot;math-container&quot;&gt;$\ce{1s-&amp;gt;6 GTO; 2s,2p-&amp;gt;3GTO + 1GTO}$&lt;/span&gt;. A feature of the Pople style basis sets is that the s and p orbitals are fused when possible into an SP orbital (also called &amp;quot;L&amp;quot; orbital). This means that the s and p GTO's from the same orbital have the same exponent, but different coefficients. This was done to reduce the cost of calculations.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PHOSPHORUS&#xA;S   6&#xA;1         0.1941330000E+05       0.1851598923E-02&#xA;2         0.2909420000E+04       0.1420619174E-01&#xA;3         0.6613640000E+03       0.6999945928E-01&#xA;4         0.1857590000E+03       0.2400788603E+00&#xA;5         0.5919430000E+02       0.4847617180E+00&#xA;6         0.2003100000E+02       0.3351998050E+00&#xA;L   6&#xA;1         0.3394780000E+03      -0.2782170105E-02       0.4564616191E-02&#xA;2         0.8101010000E+02      -0.3604990135E-01       0.3369357188E-01&#xA;3         0.2587800000E+02      -0.1166310044E+00       0.1397548834E+00&#xA;4         0.9452210000E+01       0.9683280364E-01       0.3393617168E+00&#xA;5         0.3665660000E+01       0.6144180231E+00       0.4509206237E+00&#xA;6         0.1467460000E+01       0.4037980152E+00       0.2385858009E+00&#xA;L   3&#xA;1         0.2156230000E+01      -0.2529241139E+00      -0.1776531273E-01&#xA;2         0.7489970000E+00       0.3285184468E-01       0.2740581964E+00&#xA;3         0.2831450000E+00       0.1081254762E+01       0.7854215630E+00&#xA;L   1&#xA;1         0.9983170000E-01       0.1000000000E+01       0.1000000000E+01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For phosphorus, &lt;span class=&quot;math-container&quot;&gt;$\ce{1s-&amp;gt;6 GTO; 2s,2p-&amp;gt;6 GTO; 3s,3p-&amp;gt;3 GTO + 1 GTO}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;S   6&#xA;1         0.1005955000E+06       0.1726750000E-02&#xA;2         0.1510482000E+05       0.1323462000E-01&#xA;3         0.3440884000E+04       0.6535848000E-01&#xA;4         0.9703961000E+03       0.2278042000E+00&#xA;5         0.3112852000E+03       0.4774525000E+00&#xA;6         0.1066284000E+03       0.3567619000E+00&#xA;L   6&#xA;1         0.2166679000E+04       0.2271761000E-02       0.3832156000E-02&#xA;2         0.5165414000E+03       0.3033475000E-01       0.3023558000E-01&#xA;3         0.1678674000E+03       0.1259057000E+00       0.1328632000E+00&#xA;4         0.6364638000E+02      -0.6687172000E-02       0.3447648000E+00&#xA;5         0.2613673000E+02      -0.6065306000E+00       0.4640368000E+00&#xA;6         0.1085439000E+02      -0.4823144000E+00       0.2064824000E+00&#xA;L   6&#xA;1         0.9506989000E+02      -0.5587423000E-02      -0.6816583000E-02&#xA;2         0.3318087000E+02       0.5632506000E-01      -0.2970303000E-01&#xA;3         0.1406773000E+02       0.2625835000E+00       0.4704335000E-01&#xA;4         0.6153288000E+01      -0.1718349000E+00       0.3645042000E+00&#xA;5         0.2721712000E+01      -0.7175645000E+00       0.4945157000E+00&#xA;6         0.1185334000E+01      -0.3184598000E+00       0.2149830000E+00&#xA;L   3&#xA;1         0.1615315000E+01       0.2645372000E+00      -0.2574061000E-01&#xA;2         0.5513300000E+00      -0.1952737000E+00       0.3072764000E+00&#xA;3         0.2227620000E+00      -0.9595400000E+00       0.7537368000E+00&#xA;L   1&#xA;1         0.8292300000E-01       0.1000000000E+01       0.1000000000E+01&#xA;D   3&#xA;1         0.5030227000E+02       0.8144711000E-01&#xA;2         0.1384166000E+02       0.3792908000E+00&#xA;3         0.4393458000E+01       0.7040401000E+00&#xA;D   1&#xA;1         0.1310755000E+01       1.0000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For arsenic, I believe the assignment is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$\ce{1s-&amp;gt;6 GTO; 2s,2p-&amp;gt;6 GTO; 3s,3p-&amp;gt;6 GTO; 4s,4p-&amp;gt; 3 GTO +1 GTO; 3d-&amp;gt; 3 GTO + 1 GTO}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The same number of orbitals and GTOs are used in the same row. For example, if you look at the 6-31G basis set for &lt;a href=&quot;https://www.basissetexchange.org/basis/6-31g/format/gamess_us/?version=1&amp;amp;elements=14&quot; rel=&quot;noreferrer&quot;&gt;silicon&lt;/a&gt;, you would see the same type of assignment as in phosphorus. This type of scheme seems to be consistent in other basis set families too, as mentioned in @NikeDattani's answer.&lt;/p&gt;&#xA;&lt;p&gt;[All basis sets are from Basis Set Exchange: https://www.basissetexchange.org/, and in GAMESS(US) format]&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-06-19T09:07:48.313" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6197" PostTypeId="2" ParentId="6189" CreationDate="2021-06-19T09:26:26.197" Score="5" Body="&lt;p&gt;A band can either be expressed as a linear combination of plane waves, or as a linear combination of atomic orbitals. By asserting that the color of gold can be explained by relativistic shifts of atomic orbitals, one have implicitly expanded the conduction band wavefunctions into a linear combination of atomic orbitals. Then it follows easily that if an atomic orbital contributes significantly to a band, and the energy of the atomic orbital changes, then the energy of the band will tend to change in the same direction. One can as well explain the changes of the band structure starting from a plane wave expansion, only that the wordings will become clumsier. For example, the usual conclusion that relativistic effects usually lower the energy of s orbitals and raise the energy of d orbitals, will have to be rephrased as: &amp;quot;relativistic effects tend to lower the energy of those linear combinations of plane waves that have no angular node near a nucleus, but raise the energy of those linear combinations that have two angular nodes near a nucleus.&amp;quot; The latter phrasing is much less intuitive, but is valid.&lt;/p&gt;&#xA;&lt;p&gt;If you are interested in a reproduction of the color of gold without recourse to atomic energy levels, just imagine that you perform an all-electron, relativistic band structure calculation of gold metal, with bare, &amp;quot;non-pseudized&amp;quot; nuclear attraction potentials, and using a huge plane-wave basis set that is capable of expanding even the 1s orbitals of gold. This reproduces the color of gold as long as the density functional, quasiparticle theory, or whatever theory you are using to calculate the band structure, is accurate enough. Of course this is probably not doable in practice since you need an insanely high cutoff energy to describe the 1s orbital of gold. You can circumvent this by using a pseudopotential, but then your calculation will involve atomic energy levels implicitly, since pseudopotentials are usually parameterized by atomic energy levels and/or atomic wavefunctions.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-06-19T09:26:26.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6198" PostTypeId="2" ParentId="6184" CreationDate="2021-06-19T09:52:48.180" Score="5" Body="&lt;p&gt;I think @romaichenko's answer covers everything. But for a full answer I believe a sample input file is necessary.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# B3LYP/6-31G(d) Opt=ModRedundant&#xA;&#xA; methane with H&#xA;&#xA;0 2&#xA;C         -1.41531        0.37839        0.00000&#xA;H         -0.34531        0.37839        0.00000&#xA;H         -1.77197        0.64640       -0.97255&#xA;H         -1.77198        1.08664        0.71838&#xA;H         -1.77198       -0.59787        0.25418&#xA;H         -2.67803       -3.10703        0.79353&#xA;&#xA;B 1 6 F&#xA;B 5 6 S 20 -0.1&#xA;&#xA;! there has to be a newline at the end of input file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, replace the coordinates and the charge/multiplicity with your own coordinates. If you want atom 5 to move while keeping atom 1 and atom 6 fixed, then you would have to fix the distance between 1 and 6. &lt;code&gt;B&lt;/code&gt; indicates bond and &lt;code&gt;F&lt;/code&gt; requests Gaussian to freeze that coordinate.&lt;/p&gt;&#xA;&lt;p&gt;The last line indicates that the bond (&lt;code&gt;B&lt;/code&gt;) between atoms 5 and 6 are scanned (&lt;code&gt;S&lt;/code&gt;) with &lt;code&gt;20&lt;/code&gt; steps of size &lt;code&gt;-0.1&lt;/code&gt; Angstrom. In the image you posted in the question, the bond between 5 and 6 is long, so during the scan, the bond length would have to decrease which is why the step size is negative. Make sure that the number of the scan steps and the step size are consistent with the bond lengths of your system, because I cannot say what is the distance between 5 and 6 from an image. 20 steps of step size -0.1 Angstrom will reduce the bond length by 2 Angstrom.&lt;/p&gt;&#xA;&lt;p&gt;Note that the coordinates of the other three H atoms on methyl group (2,3,4) are not frozen, so they can move during the optimization, i.e. this is a relaxed scan to some extent.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-20T12:14:51.307" LastActivityDate="2021-06-20T12:14:51.307" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6199" PostTypeId="1" CreationDate="2021-06-19T10:18:30.983" Score="5" ViewCount="178" Body="&lt;p&gt;Yesterday &lt;a href=&quot;https://chemistry.stackexchange.com/q/153099/27342&quot;&gt;I made this query on Chemistry Stack Exchange&lt;/a&gt;, and a user has felt that perhaps here I will get a quicker answer.&lt;/p&gt;&#xA;&lt;p&gt;The structure of rhenium(VI) oxide, &lt;span class=&quot;math-container&quot;&gt;$\ce{ReO3}$&lt;/span&gt;, is similar to that of perovskite. Each rhenium atom is surrounded by six oxygen atoms (octahedral environment):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HkMqC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HkMqC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Experimentally, the density of states diagram is found to be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PEqfM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PEqfM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The diagram of molecular orbitals would have the following form. But, I don't know how many electrons I should place. Since the oxidation state of rhenium is 6+, its electronic configuration is [Xe] 4f14 5d1 and, consequently, the metal atom would contribute one electron. &lt;em&gt;&lt;strong&gt;But, I don't know how many are contributed by the oxygen (I think it would be 12, but I'm not sure). Can you help me with this?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;The idea is that once the molecular orbital diagram is drawn, it predicts the shape of the density of states by means of the type of orbital interaction (sigma, pi, delta):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mrlF2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mrlF2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The theory on which the problem is based is shown &lt;a href=&quot;https://slideplayer.com/slide/6278309/&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this slide&lt;/a&gt;, in case I have not explained it well.&lt;/p&gt;&#xA;" OwnerUserId="1744" LastEditorUserId="5" LastEditDate="2021-07-12T06:54:25.050" LastActivityDate="2021-07-12T06:54:25.050" Title="Predict the density of states (DOS) diagram for rhenium oxide (ReO3) from the molecular orbital diagram" Tags="|band-structure|from-chem-se|orbitals|perovskites|" AnswerCount="0" CommentCount="6" ClosedDate="2021-12-02T17:27:20.000" ContentLicense="CC BY-SA 4.0" />
  <row Id="6200" PostTypeId="1" AcceptedAnswerId="6203" CreationDate="2021-06-19T14:08:43.940" Score="8" ViewCount="187" Body="&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://www.reddit.com/r/comp_chem/comments/o3h2od/benchmark_test_cases_for_dft_program_or_vasp/?utm_source=share&amp;amp;utm_medium=web2x&amp;amp;context=3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cross-posted on reddit/comp-chem&lt;/a&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am trying to build my workflow of using DFT to predict properties of some materials, but I am not sure if I do it all right,  so I think there might be some benchmark test cases for the DFT program,  but it seems there are only some test cases for testing if the installation is right. I am not looking for a database of material properties, but a complete test case that includes every step of how to build the model.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;Where should I find a benchmark test case of my workflow?&lt;/strong&gt;&lt;Br&gt;&lt;/p&gt;&#xA;&lt;p&gt;And if it is not possible to get a benchmark test case for all DFT programs, a test case just for VASP would be also helpful.&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-06-22T17:59:51.207" LastActivityDate="2021-06-22T17:59:51.207" Title="Benchmark test cases for DFT program or VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6201" PostTypeId="2" ParentId="392" CreationDate="2021-06-19T18:26:55.160" Score="4" Body="&lt;h1&gt;2016: Reproducibility of DFT calculations (Lejaeghere &lt;em&gt;et al&lt;/em&gt;)&lt;/h1&gt;&#xA;&lt;p&gt;Lejaeghere et al.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; compared the calculated values for the equation of states for 71 elemental crystals from 15 different widely used DFT codes employing 40 different potentials. They defined a single parameter, Δ, which allowed the comparison of EOS calculated with different codes, giving a simple route to evaluating the reproducibility of DFT. Δ was defined as the root-mean-square energy difference between the equations of state of the two codes, averaged over all crystals in a purely elemental benchmark set.&lt;/p&gt;&#xA;&lt;p&gt;The key result from this paper is that modern DFT codes now achieve a precision which is comparable to  high-precision experiments; a delta value which is better than 1 meV/atom. This precision applies across various basis sets: plane waves, augmented plane waves, and numerical orbitals. It also applies to all-electron, PAW, and both ultra-soft and norm-conserving pseudopotential calculations.&#xA;The work demonstrates that the precision of DFT implementations can be determined and also shows that the pseudopotential approach using recent libraries are precise in comparison with all-electron results.&lt;/p&gt;&#xA;&lt;p&gt;The summary table from the paper is shown below; the numbers given are the RMS value for Δ across all 71 elements and colour indicates overall reliability.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1bL0z.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1bL0z.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://science.sciencemag.org/content/351/6280/aad3000&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lejaeghere, Kurt, et al. &amp;quot;Reproducibility in density functional theory calculations of solids.&amp;quot; Science 351.6280 (2016&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://molmod.ugent.be/deltacodesdft&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://molmod.ugent.be/deltacodesdft&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://davidbowler.github.io/AtomisticSimulations/blog/dft-reliability&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://davidbowler.github.io/AtomisticSimulations/blog/dft-reliability&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="88" LastActivityDate="2021-06-19T18:26:55.160" CommentCount="0" CommunityOwnedDate="2021-06-21T06:59:55.320" ContentLicense="CC BY-SA 4.0" />
  <row Id="6202" PostTypeId="2" ParentId="6183" CreationDate="2021-06-20T02:39:04.890" Score="8" Body="&lt;p&gt;Not sure what your input files are, but there's a technique based on spherical harmonics that is relevant described here: High Throughput Profiling of Molecular Shapes in Crystals &lt;a href=&quot;https://doi.org/10.1038/srep22204&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1038/srep22204&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The spherical harmonics approximate the shape of the electron distribution. They are then made rotationally invariant, and result in a descriptor that can be compared very quickly by calculating Euclidean distance between descriptors.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;chmpy&lt;/code&gt; (&lt;a href=&quot;https://github.com/peterspackman/chmpy&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/peterspackman/chmpy&lt;/a&gt;) library implements something similar. The library itself may not be complete, but it looks like it has molecule descriptors for crystals (from &lt;code&gt;chmpy/docs/shape_descriptors.md&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from chmpy import Crystal&#xA;c = Crystal.load(&amp;quot;tests/test_files/acetic_acid.cif&amp;quot;)&#xA;&#xA;# calculate shape descriptors for each molecule in the asymmetric unit&#xA;desc = c.molecular_shape_descriptors()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS you'll need to install the library SHTns manually to use the descriptors. Also note that the author of chnpy looks to be the lead author of that publication.&lt;/p&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="2225" LastEditDate="2021-06-20T04:12:07.330" LastActivityDate="2021-06-20T04:12:07.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6203" PostTypeId="2" ParentId="6200" CreationDate="2021-06-20T02:56:19.793" Score="4" Body="&lt;p&gt;The perfect resource for this is &lt;a href=&quot;http://kitchingroup.cheme.cmu.edu/dft-book/dft.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;John Kitchin's &amp;quot;Modeling Materials Using Density Functional Theory&amp;quot; ebook&lt;/a&gt;. There are numerous real examples using VASP (and the Atomic Simulation Environment) that you can use to confirm you are setting up your workflow correctly.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-06-20T02:56:19.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6204" PostTypeId="2" ParentId="1695" CreationDate="2021-06-20T08:39:21.243" Score="2" Body="&lt;h3&gt;&lt;strong&gt;ALF&lt;/strong&gt; (Algorithms for Lattice Fermions)&lt;/h3&gt;&#xA;&lt;p&gt;This is an auxiliary-field quantum Monte Carlo package. It's free, open-source, actively maintained (current version: &lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/ALF/-/tree/ALF-2.0&quot; rel=&quot;nofollow noreferrer&quot;&gt;2.0&lt;/a&gt;, with 2.1 on the works — news are posted on its &lt;a href=&quot;https://alf.physik.uni-wuerzburg.de&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;) and has been cited in dozens of &lt;a href=&quot;https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/page/publications/publications/&quot; rel=&quot;nofollow noreferrer&quot;&gt;publications&lt;/a&gt; since its release in 2017.&lt;/p&gt;&#xA;&lt;p&gt;The package is very flexible, as it can simulate any Hamiltonian that can be written in terms of sums of i) single-body operators, ii) squares of single-body operators, and iii) single-body operators coupled to an Ising field with given dynamics. Besides, you can also specify a Bravais lattice and observables, in addition to the package's predefined ones.&lt;/p&gt;&#xA;&lt;p&gt;For newcomers, the extensive &lt;a href=&quot;https://arxiv.org/abs/2012.11914&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; should be of help, as well as its &lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/ALF_Tutorial/-/tree/master/&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;, which aims to bring the absolute beginner to the point of coding their own models and observables — of course a steep learning curve, but the collaboration is &lt;a href=&quot;https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/page/contact/&quot; rel=&quot;nofollow noreferrer&quot;&gt;glad to help&lt;/a&gt;. The introductory part of the tutorial is based on a collection of Jupyter notebooks in Python, which relies on &lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/pyALF/-/tree/master&quot; rel=&quot;nofollow noreferrer&quot;&gt;pyALF&lt;/a&gt;, a Python interface to the Fortran core of ALF. Also available are the &lt;a href=&quot;https://alfworkshop2020.sciencesconf.org/resource/page/id/8&quot; rel=&quot;nofollow noreferrer&quot;&gt;slides and recorded talks&lt;/a&gt; from the ALF 2020 User Workshop.&lt;/p&gt;&#xA;&lt;p&gt;The code is also very efficient: offering parallelization via MPI and OpenMP, its single-core performance is near-optimal, and its restart facilities can be very useful in supercomputer facilities.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free and open-source code (&lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/ALF&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitLab&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;High performance (MPI &amp;amp; OpenMP implementation, with near-optimal scaling)&lt;/li&gt;&#xA;&lt;li&gt;General Hamiltonian, lattice and observables&lt;/li&gt;&#xA;&lt;li&gt;Ease of use (&lt;a href=&quot;https://arxiv.org/abs/2012.11914&quot; rel=&quot;nofollow noreferrer&quot;&gt;docs&lt;/a&gt;, &lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/ALF_Tutorial/-/tree/master/&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt; and &lt;a href=&quot;https://git.physik.uni-wuerzburg.de/ALF/pyALF/-/tree/master&quot; rel=&quot;nofollow noreferrer&quot;&gt;pyALF&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Advanced features, including:&lt;br /&gt;&#xA;parallel tempering, ground state projective QMC, global Monte Carlo updates, continuous fields, Langevin dynamics updates, stochastic Maximum Entropy method, symmetric Trotter decomposition, Dimer-Dimer correlations, Cotunneling for Kondo models, and Rényi Entropy.&lt;/li&gt;&#xA;&lt;li&gt;Support (&lt;a href=&quot;https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/page/contact/&quot; rel=&quot;nofollow noreferrer&quot;&gt;contact&lt;/a&gt; via email, chat or call)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disclaimer&lt;/strong&gt;: I've contributed to the package.&lt;/p&gt;&#xA;" OwnerUserId="625" LastActivityDate="2021-06-20T08:39:21.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6205" PostTypeId="1" AcceptedAnswerId="6275" CreationDate="2021-06-20T10:01:40.657" Score="7" ViewCount="680" Body="&lt;p&gt;I would like to reproduce the data of adsorption energies published in &lt;a href=&quot;https://doi.org/10.1016/j.apsusc.2017.12.046&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For example, they say the adsorption energy for Li atom on graphene is -1.19 eV (estimated by GGA-PBE). I used vasp (5.4) code using parameters indicated in the paper and estimated total energy for&lt;/p&gt;&#xA;&lt;p&gt;Supercell 4x4x1 of graphene: &lt;code&gt;-0.29529545E+03 eV&lt;/code&gt;;&lt;br&gt;&#xA;Graphene with one Li atom on its surface: &lt;code&gt;-0.29635605E+03 eV&lt;/code&gt;;&lt;br&gt;&#xA;One Li atom (estimated from bcc structures): &lt;code&gt;-1.909 eV&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, the adsorption energy should be &lt;code&gt;-296.35605 eV -[(-295.29545 eV) + (-1.909 eV)] = +0.848 eV&lt;/code&gt;. It is inconsistent with the previous calculation.&lt;/p&gt;&#xA;&lt;p&gt;If I use total energy for the isolated Li atom of &lt;code&gt;-0.29471258 eV&lt;/code&gt;, the obtained adsorption energy is &lt;code&gt;-0.767 eV&lt;/code&gt;. Both have a big gap with the published data. I wonder if there is a trick to accurately estimate the adsorption energy?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2021-06-21T19:24:50.340" LastActivityDate="2021-06-29T13:15:58.770" Title="How to estimate adsorption energy of Li atom on graphene?" Tags="|vasp|adsorption|" AnswerCount="1" CommentCount="6" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6206" PostTypeId="2" ParentId="6188" CreationDate="2021-06-20T23:27:28.757" Score="7" Body="&lt;p&gt;It's important to also note that the STO-nG family is a Gaussian fit to an old, minimal STO basis. Larger STO basis sets ranging up to quadruple-zeta quality are included in e.g. the ADF program that is based on Slater-type orbital basis sets.&lt;/p&gt;&#xA;&lt;p&gt;As Nike already said, more reasonable GTO basis sets don't even try to imitate STO basis sets, but rather just aim for the best possible energies and transferability across systems. Once the basis set is big enough, the form of the individual functions matters less than the span of the set of basis functions. A good example of this are fully numerical basis sets, where the basis functions may not look anything like atomic orbitals; however, you are able to describe the exact solution to arbitrary accuracy using such functions.&lt;/p&gt;&#xA;&lt;p&gt;STOs are also not exact solutions to anything except the hydrogen atom. Numerical atomic orbitals (NAOs) form a much better basis in this respect; they are almost immune to basis set superposition error because already the minimal NAO basis is exact for non-interacting atoms.&lt;/p&gt;&#xA;&lt;p&gt;You can read my review article in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25968&lt;/a&gt; for more discussion on GTO vs STO vs NAO and discussion on various fully numerical methods.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-06-20T23:27:28.757" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6207" PostTypeId="1" CreationDate="2021-06-21T05:42:59.263" Score="4" ViewCount="120" Body="&lt;p&gt;I am planning for the calculation of emission spectra of organic compounds showing the phenomenon of aggregation-induced emission (AIE). Can someone help me get started?&lt;/p&gt;&#xA;" OwnerUserId="3805" LastEditorUserId="5" LastEditDate="2021-06-21T19:22:07.517" LastActivityDate="2021-06-21T19:22:07.517" Title="Calculating emission spectrum of organic compounds by DFT. Can someone elaborate in terms of calculating it for aggregatrion induced emission?" Tags="|density-functional-theory|software|computational-chemistry|spectroscopy|" AnswerCount="0" CommentCount="3" ClosedDate="2021-07-12T14:47:37.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="6208" PostTypeId="1" CreationDate="2021-06-21T11:18:35.783" Score="12" ViewCount="337" Body="&lt;p&gt;Do van der Waals corrected DFT functionals include Keesom and Deby corrections too or just London dispersion? Because when I look at these methods in detail, I see that there is just an attempt to correct London dispersion correction and no mention to the remaining two (Deby and Keesom) van der Waals correction. What is the reason? If there is just London dispersion correction, then why are they called van der Waals corrections?&lt;/p&gt;&#xA;&lt;p&gt;Another question that I could not find an answer to is: Are Keesom and Deby forces already included in semilocal and local density functionals compared to long-range London dispersion interactions?&lt;/p&gt;&#xA;" OwnerUserId="3807" LastActivityDate="2022-04-03T12:33:52.220" Title="Keesom and Debye forces in DFT" Tags="|density-functional-theory|dispersion-correction|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6209" PostTypeId="1" AcceptedAnswerId="6258" CreationDate="2021-06-21T12:18:49.080" Score="7" ViewCount="2637" Body="&lt;p&gt;I have been trying to do geometrical optimization for ZnSe Quantum Dots using Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;The convergence is very slow, so slow that even after 200 iterations I could not get convergence. I tried reducing &lt;code&gt;mixing_beta&lt;/code&gt; to 0.3 like it says in the manual for QE(things got worse) and then I tried raising it to 0.8, this actually gave better results. Raising the cutoff energy also did not have much effect.&lt;/p&gt;&#xA;&lt;p&gt;The weird thing is that once one decimal place is obtained it just keeps going a bit up and down not being able to converge the next digits easily. I think &lt;em&gt;this could be solved by reducing the step size in the algorithm&lt;/em&gt;, is that somehow possible?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Convergence graph(energy)&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/f9oIS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/f9oIS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;    calculation   = &amp;quot;relax&amp;quot;&#xA;    forc_conv_thr =  1.00000e-03&#xA;    max_seconds   =  1.72800e+05&#xA;    nstep         = 100&#xA;    outdir        = &amp;quot;.\outdir&amp;quot;&#xA;    prefix        = &amp;quot;me&amp;quot;&#xA;    pseudo_dir    = &amp;quot;C:\Users\aman\.burai\.pseudopot&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;    a           =  2.50000e+01&#xA;    b           =  2.50000e+01&#xA;    c           =  2.50000e+01&#xA;    degauss     =  1.00000e-02&#xA;    ecutrho     =  2.49895e+02&#xA;    ecutwfc     =  2.75032e+01&#xA;    ibrav       = 8&#xA;    nat         = 44&#xA;    ntyp        = 2&#xA;    occupations = &amp;quot;fixed&amp;quot;&#xA;    smearing    = &amp;quot;gaussian&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  8.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;    ion_dynamics = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;CELL&#xA;/&#xA;&#xA;K_POINTS {gamma}&#xA;&#xA;ATOMIC_SPECIES&#xA;Zn     65.39000  Zn.pbe-van.UPF&#xA;Se     78.96000  Se.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Zn      7.349204   5.983991  13.367822&#xA;Zn     11.402731  13.004906  13.367822&#xA;Zn      7.349204   5.983991   6.705404&#xA;Zn     11.402731  13.004906   6.705404&#xA;Zn     13.429495  11.834754  10.036613&#xA;Zn      9.375968   4.813839  10.036613&#xA;Zn      5.322440   9.494449  13.367822&#xA;Zn      9.375967   9.494448  13.367822&#xA;Zn      7.349204  13.004906  13.367822&#xA;Zn      5.322440   9.494449   6.705404&#xA;Zn      9.375967   9.494448   6.705404&#xA;Zn      7.349204  13.004906   6.705404&#xA;Zn     15.456259   8.324296  10.036613&#xA;Zn     11.402731   8.324296  10.036613&#xA;Zn     13.429494   4.813839  10.036613&#xA;Zn     13.429495   9.494449  13.367822&#xA;Zn     11.402731   5.983991  13.367822&#xA;Zn     13.429495   9.494449   6.705404&#xA;Zn     11.402731   5.983991   6.705404&#xA;Zn      5.322440  11.834754  10.036613&#xA;Zn      7.349204   8.324296  10.036613&#xA;Zn      9.375968  11.834754  10.036613&#xA;Se     13.429495  11.834754   5.868711&#xA;Se      9.375968   4.813839   5.868711&#xA;Se      7.349204   5.983991   9.199920&#xA;Se     11.402731  13.004906   9.199920&#xA;Se     13.429495  11.834754  12.531128&#xA;Se      9.375968   4.813839  12.531128&#xA;Se     11.402731   8.324296   5.868711&#xA;Se      9.375967   9.494448  15.862337&#xA;Se      5.322440   9.494449   9.199920&#xA;Se      9.375967   9.494448   9.199920&#xA;Se      7.349204  13.004906   9.199920&#xA;Se     15.456259   8.324296  12.531128&#xA;Se     11.402731   8.324296  12.531128&#xA;Se     13.429494   4.813839  12.531128&#xA;Se      7.349204   8.324296   5.868711&#xA;Se      9.375968  11.834754   5.868711&#xA;Se     15.456259   5.983991   9.199920&#xA;Se     13.429495   9.494449   9.199920&#xA;Se     11.402731   5.983991   9.199920&#xA;Se      5.322440  11.834754  12.531128&#xA;Se      7.349204   8.324296  12.531128&#xA;Se      9.375968  11.834754  12.531128&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any other advice on convergence is also very much optimized, Thanks!&#xA;P.S the structure is neutral and I don't think there is anything wrong with the structure.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-06-22T01:30:18.413" LastActivityDate="2021-06-27T22:46:26.517" Title="SCF Calculation not converging after two decimal places in Quantum ESPRESSO" Tags="|quantum-espresso|numerical-convergence|quantum-dots|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6210" PostTypeId="2" ParentId="6189" CreationDate="2021-06-21T13:19:37.490" Score="3" Body="&lt;p&gt;Lets start with some data from &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S1875389212009273&quot; rel=&quot;nofollow noreferrer&quot;&gt;Optical Transmission in Thin Metal Films&lt;/a&gt; where they deposited a range of metals on glass and measured their transmission. Sticking with their data on the noble metals, they see pretty much what one would expect - some changes in shape as the film thickness goes from 0.5 to 4nm of gold, coupled with the clear emergence of the plasmon absorption feature. There are absolutely no atomic absorption lines in the spectrum (completely expected since any intra-gold transitions are at much much higher energies than the visible range of a few eV. (Also note the comparison of Cu, Ag, and Au, clearly seeing the plasmon absorption features in each of them that are close together, but close in the visible range and thus we are highly sensitive to small differences).&lt;/p&gt;&#xA;&lt;p&gt;Recall that plasmons are a feature of bulk (not atomic) systems with free carriers. In the noble metals the conduction bands are made up of the outer electrons that are donated to the cause of crystal binding. The plasmon frequency depends on the density of free carriers and their effective mass - that is pretty much all. All of the noble metals have highly similar band structure and Fermi surfaces (both bulk, not atomic, features). A peek at a table of electron binding energies (such as &lt;a href=&quot;https://xdb.lbl.gov/Section1/Table_1-1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;at LBL)&lt;/a&gt; shows you that the outermost electron of Au has a binding energy of 57.2eV. The next one is 74.2eV. For comparison, Ag has 58.3 and 63.7 eV, and Cu 75.1 and 73.3 eV, respectively. So, really, the outer electrons of Au are not particularly different from the outer electrons of the other noble metals as one would expect from their band structures noted in your first link.&lt;/p&gt;&#xA;&lt;p&gt;But, remember that the nice picture we keep in our heads of hydrogen-like atomic orbitals is, well, wrong (except for one-electron atoms, sort of). Bethe and Salpeter wrote an entire book (&lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/B00C59C6K6&quot; rel=&quot;nofollow noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum Mechanics of One- and Two-Electron Atoms&lt;/a&gt;, and I count myself extremely lucky to have taken graduate quantum mechanics from Ed Salpeter) on the difficulties of adding that second electron. With more and more electrons being added, the difficulties mount rapidly because of screening and other factors. Sometimes I sit in awe and contemplate just how well the hydrogen-like orbitals survive all of that.&lt;/p&gt;&#xA;&lt;p&gt;So, where do 'relativistic effects' come in to play? Looking back at the electron binding energy tables, one sees that the Au 1s electron has a binding energy of 80.725keV, about 15% of the rest energy of an electron. What this means is that, should you want to do a full-up multi-electron calculation of all 79 electron states, you are going to have to deal with the relativistic effects of those core orbitals which will have an influence on the outer states because they have a screening effect different from the simple hydrogen levels. All that means, is that the last few outer electrons of Au see a slightly different potential than they would have if there were no relativity. In the end, given the binding energies for Au compared with Cu and Ag there really is not much difference. The color differences of them are all done to the plasmon absorption in the visible, a bulk feature, with slight different plasmon energies for Cu, Ag, and Au. So, look to electron density and effective mass for your answer.&lt;/p&gt;&#xA;" OwnerUserId="716" LastActivityDate="2021-06-21T13:19:37.490" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="6211" PostTypeId="2" ParentId="6208" CreationDate="2021-06-21T13:46:08.943" Score="15" Body="&lt;p&gt;In computational chemistry, the term &amp;quot;van der Waals interaction&amp;quot; tend to refer to the London term only; the Keesom term (electrostatic interactions between two freely-rotating permanent dipoles) is generally included in the electrostatic interaction, while the Debye term (interaction between a permanent dipole and an induced dipole) is usually considered as a type of induction interaction and is treated on the same footing as the ion-induced dipole force. Both the Keesom and the Debye terms are described excellently by most density functionals, with caveats that are detailed below.&lt;/p&gt;&#xA;&lt;p&gt;To compute the Keesom term, the most rigorous way is to perform a rotational average over the interacting molecules, which may require either a molecular dynamics simulation or a Monte-Carlo sampling; the simple &amp;quot;geometry optimization + frequency + single point (+ counterpoise correction)&amp;quot; workflow cannot be guaranteed to capture the Keesom term correctly when the molecules can rotate quite freely, but if the molecules have a relatively fixed orientation with respect to each other (as is often the case for molecules that are not very small), then the rotational average is not necessary, and the usual quasi-RRHO scheme (as implemented in, e.g., ORCA) usually suffices to give accurate results.&lt;/p&gt;&#xA;&lt;p&gt;In more layman terms, if you don't do rotational averaging, the electronic energy does not accurately capture the Keesom term (and usually overestimates its magnitude), but the thermal correction U(T)-U(0), which you obtain from your frequency calculation, largely corrects the error of the Keesom term, so that if you add the U(T)-U(0) and ZPE terms to the electronic energy to give the energy at finite temperature U(T), you actually have the Keesom term at hand already. Note however that some programs (e.g., Gaussian) uses the RRHO scheme, instead of the quasi-RRHO scheme, in calculating the partition functions; in this cases the Keesom contribution may be poorly reproduced, and the way out is to use third-party tools like &lt;a href=&quot;https://github.com/bobbypaton/GoodVibes&quot; rel=&quot;nofollow noreferrer&quot;&gt;GoodVibes&lt;/a&gt; or &lt;a href=&quot;http://sobereva.com/soft/shermo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Shermo&lt;/a&gt; to recalculate the partition functions using quasi-RRHO. In any case, even if you do fail to compute the Keesom term accurately, it is not a failure of the functional, but a failure of (quasi-)RRHO.&lt;/p&gt;&#xA;&lt;p&gt;The Debye term depends on the permanent dipole of the polarizer molecule and the polarizability of the polarized molecule. Both are accurately reproduced by most functionals if and only if the basis set is sufficiently diffuse. So again, even if the Debye term is calculated wrong, it's not the functional to blame.&lt;/p&gt;&#xA;&lt;p&gt;For the London dispersion term, things are wholly different. The London interaction is a long-range correlation interaction that decays like &lt;span class=&quot;math-container&quot;&gt;$1/R^6$&lt;/span&gt;. By contrast, all local and semilocal functionals, as their name suggests, have a correlation contribution that decays at least exponentially. (EDIT: it is actually &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8863/how-to-explain-to-a-five-year-old-why-dft-with-local-exchange-correlation-funct&quot;&gt;possible&lt;/a&gt; to describe a &lt;span class=&quot;math-container&quot;&gt;$1/R^6$&lt;/span&gt;-decaying interaction with semilocal functionals, but this approach puts high demand on the basis functions and does not capture the required physics, so apparently no one has ever developed such a semilocal functional.) It is because of this reason that they cannot describe the London dispersion term adequately.&lt;/p&gt;&#xA;&lt;p&gt;Within the semilocal framework, one can parameterize the functional such that it describes the London interaction when the molecules are not very far apart (e.g. the M06 and M06-2X functionals), but as the molecules become progressively far from each other, any parameterization must eventually fail and underestimate the London interaction, because the exponential decay is bound to kick in. Thus, the simplest physically correct way to restore the London interaction is to introduce diatomic attraction potentials with built-in &lt;span class=&quot;math-container&quot;&gt;$1/R^6$&lt;/span&gt; behavior, which is exactly the approach used by DFT-D. More robust but costly alternatives (such as the VV10 correction) also exist.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="7" LastEditDate="2022-04-03T12:33:52.220" LastActivityDate="2022-04-03T12:33:52.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6212" PostTypeId="2" ParentId="6151" CreationDate="2021-06-21T22:00:04.690" Score="12" Body="&lt;p&gt;The following are three important aspects of any force-field fitting workflow,&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Training Data:&lt;/strong&gt; There should be DFT/experimental values that define structure, energetics, elastics or any other properties of the desired system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Optimizer:&lt;/strong&gt; This is the heart of any force-field fitting tool/software. The parameters of force-field can be optimized against the training data using any of the available techniques like &lt;em&gt;evolutionary search algorithms&lt;/em&gt;, &lt;em&gt;reinforcement learning&lt;/em&gt; etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Atomistic Simulator:&lt;/strong&gt; In order to guide the optimizer based on the calculated/heuristic guesses, the same properties which are a part of training data can be computed through a simple atomistic simulation via LAMMPS or any other similar tool. The errors act as a feedback for the optimizer's next step.&lt;/p&gt;&#xA;&lt;p&gt;For much more details, you could refer to the following work,&lt;/p&gt;&#xA;&lt;p&gt;Chan, H., Sasikumar, K., Srinivasan, S., Cherukara, M., Narayanan, B. and Sankaranarayanan, S.K., 2019. Machine learning a bond order potential model to study thermal transport in WSe 2 nanostructures. Nanoscale, 11(21), pp.10381-10392.&lt;/p&gt;&#xA;&lt;p&gt;Also, I am aware of one latest tool called BLAST which is capable of fitting force-fields across different interatomic models,&lt;/p&gt;&#xA;&lt;p&gt;Chan, H., Narayanan, B., Cherukara, M., Loeffler, T.D., Sternberg, M.G., Avarca, A. and Sankaranarayanan, S.K., 2021. BLAST: bridging length/timescales via atomistic simulation toolkit. MRS Advances, 6(2), pp.21-31.&lt;/p&gt;&#xA;" OwnerUserId="3810" LastActivityDate="2021-06-21T22:00:04.690" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6213" PostTypeId="2" ParentId="6126" CreationDate="2021-06-22T00:55:56.183" Score="5" Body="&lt;p&gt;I'm not a Quantum Espresso expert, but I'll try to answer this as best I can. There are two aspects to this answer: 1) whether you have a GPU-enabled version of Quantum Espresso; and 2) whether you should use your GPUs anyway.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;GPU port of Quantum Espresso&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Using GPUs effectively requires substantial changes to the source code (e.g. OpenACC, OpenMP5, CUDA-Fortran), and so you need to make sure you are using a version of Quantum Espresso which has those changes. You will also need a compiler which understands the GPU additions, which probably means the NVIDIA compiler.&lt;/p&gt;&#xA;&lt;p&gt;The previous GPU project was led by Filippo Spiga and was very quick, but made heavy use of CUDA-Fortran (only supported by NVIDIA) and I think it evolved into a separate branch, and it and the &amp;quot;main&amp;quot; Quantum Espresso diverged significantly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/fspiga/qe-gpu&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/fspiga/qe-gpu&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is a new GPU port of Quantum Espresso which is intended to stay &amp;quot;in sync&amp;quot; with the main developments. This has been released, but I'm not sure what state it's in -- it may still be a test release.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://gitlab.com/QEF/q-e-gpu/releases&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e-gpu/releases&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Regardless, you will need the NVIDIA Fortran compiler and the CUDA toolkit (both are free). You will not be able to use Intel's compilers and I doubt that you can use GNU's either.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;GPUs for DFT simulations&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The GPUs which people usually use for DFT simulations are not graphics cards, they are dedicated compute-platforms (GPGPUs) which use technology based on graphics cards.&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;built-in&amp;quot; Intel GPU is unlikely to be useful; it has relatively low performance, it probably has no fast, dedicated RAM, and it is unlikely to be supported by your compiler. It is also very difficult to program for two different kinds of GPUs in the same system, and I doubt either QE or the compiler would cope.&lt;/p&gt;&#xA;&lt;p&gt;The NVIDIA GPU probably has a good headline performance, and some fast, dedicated RAM, but I'm confident that it will only support up to single-precision arithmetic in hardware. Accurate DFT simulations rely on double-precision, and whilst the cards can emulate this in software it is extremely slow.&lt;/p&gt;&#xA;&lt;p&gt;Much of the speed of a GPGPU is only attainable at all because they also have dedicated, high bandwidth memory (e.g. HBM2), which may not be true of a laptop model. You typically want a lot of dedicated RAM as well, which most consumer cards do not have.&lt;/p&gt;&#xA;&lt;p&gt;If we look at the NVIDIA GPU-based offerings, you end up looking at a Titan or Tesla card before you have enough fast RAM and any significant double-precision performance for DFT simulations. Both of these have error-corrected (ECC) RAM, which I also consider important to getting reliable, publishable results (this goes for CPU calculations too, of course).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-06-22T00:55:56.183" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6214" PostTypeId="1" AcceptedAnswerId="6217" CreationDate="2021-06-22T03:33:03.673" Score="11" ViewCount="348" Body="&lt;p&gt;I have a large matrix for a 1D zigzag edge model of an otherwise &lt;span class=&quot;math-container&quot;&gt;$3\times 3$&lt;/span&gt; tight-binding Hamiltonian (3 basis functions, each corresponding to an atomic orbital), involving the variable &lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt;. The large matrix contains blocks of this &lt;span class=&quot;math-container&quot;&gt;$3\times 3$&lt;/span&gt; Hamiltonian for each unit cell involved (I chose 100 unit cells).&#xA;For different values of &lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt;, I numerically calculate eigenvalues and eigenvectors, and use the eigenvalues to plot the band structure shown below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OHwHr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OHwHr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do I identify which of the three orbitals the edge states are coming from, by using the numerical wavefunctions or otherwise?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I've done so far: I used the following (HIGHLY INEFFICIENT) Python code to identify the indices of eigenvalues where the bands approximately cross. I was hoping to use this to find the eigenvectors corresponding to the point, and then identify which orbitals the edge states are coming from. My rationale is that the probability will suddenly jump to something else (or switch between bands) when the bands cross. I guess my biggest confusion is that I do not know which eigenvectors to choose, nor what they mean. That is, if my original matrix is tridiagonal, with &lt;span class=&quot;math-container&quot;&gt;$3\times 3$&lt;/span&gt; blocks making up the system, what bases do the resulting eigenvectors have? In the case of energy eigenstates in just momentum space, I understand that each eigenvector corresponds to an energy wavefunction. But now I have the added complication of several unit cells.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;find_evec_with_energy = 1; # crossing occurs around here&#xA;tol = 0.02&#xA;rows,cols = np.asarray(energies).shape # for each iteration of kx, I append the eigenvalues into the list called 'energies'&#xA;&#xA;indices = []&#xA;for j in range(rows):&#xA;    for k in range(cols):&#xA;        if np.abs(np.asarray(energies)[j,k]-find_evec_with_energy)&amp;lt;tol:&#xA;            indices.append(f&amp;quot;{j},{k}&amp;quot;)&#xA;print(&amp;quot;row,column of eigenvalue with desired energy&amp;quot;)&#xA;print(indices)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, I guess I take choose the eigenvector corresponding to one of these indices, and then plot each triplet of rows, squared? I'm not sure.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;n = 75 # index of unit cell where band crossing occurs??&#xA;wavefunction = evecs[:,n]&#xA;up,middle,down = wavefunction[::3],wavefunction[1::3],wavefunction[2::3]&#xA;&#xA;plt.plot(np.abs(up)**2) &#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Sorry if this is a basic question, but I am only now starting to learn real-space material systems. Thanks.&#xA;P.S. I'm not sure what tags to use.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;EDIT: updated code:&lt;/p&gt;&#xA;&lt;p&gt;First, loop over various momenta and get eigenvectors and eigenvalues:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;energies = []&#xA;evecs = []&#xA;W = 100&#xA;for i in range(v_segs):&#xA;    ham = H(vary_range[i],W)&#xA;    ev,evc = np.linalg.eigh(ham)&#xA;    energies.append(ev)&#xA;    evecs.append(evc)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, find indices of energies near band crossing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;find_evec_with_energy = 1; # crossing occurs around here&#xA;tol = 0.02&#xA;rows,cols = np.array(energies).shape&#xA;print(rows)&#xA;print(cols)&#xA;&#xA;indices = []&#xA;for j in range(rows):&#xA;    for k in range(cols):&#xA;        if np.abs(np.array(energies)[j,k]-find_evec_with_energy)&amp;lt;tol:&#xA;            indices.append([j,k])&#xA;print(&amp;quot;row,column of eigenvalue with desired energy&amp;quot;)&#xA;print(indices) # outputs [[12, 100], [87, 100]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Finally, try to find orbitals involved in band crossing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def find_orbitals(index): #n is the row we want&#xA;    ik,iband = index&#xA;    wavefunction = np.array(evecs)[ik,:,iband]&#xA;    w = wavefunction.conj() * wavefunction&#xA;    up,middle,down = w[::3],w[1::3],w[2::3]&#xA;    print(f&amp;quot;up,middle,down at index {index}&amp;quot;)&#xA;    tol = 0.01&#xA;        if np.allclose(middle, 0, atol=tol):&#xA;    print(&amp;quot;edge states from up,down&amp;quot;)&#xA;else:&#xA;    print(&amp;quot;not middle&amp;quot;)&#xA;    &#xA;if np.allclose(up, 0, atol=tol):&#xA;    print(&amp;quot;edge states from middle,down&amp;quot;)&#xA;else:&#xA;    print(&amp;quot;not up&amp;quot;)&#xA;&#xA;if np.allclose(down, 0, atol=tol):&#xA;    print(&amp;quot;edge states from up,middle&amp;quot;)&#xA;else:&#xA;    print(&amp;quot;not down&amp;quot;)&#xA;        &#xA;    plt.plot(np.abs(up)**2) &#xA;    plt.show()&#xA;&#xA;    plt.plot(np.abs(mid)**2) &#xA;    plt.show()&#xA;&#xA;    plt.plot(np.abs(down)**2) &#xA;    plt.show()&#xA;&#xA;#list_of_indices = indices#[[12,100],[87,100]]&#xA;list_of_indices = [[12,100],[87,100]]&#xA;&#xA;for q in range(len(list_of_indices)):&#xA;    find_orbitals(list_of_indices[q])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-06-22T18:54:34.897" LastActivityDate="2021-06-28T07:43:28.467" Title="How to use wavefunctions/density to determine which orbitals lead to edge states?" Tags="|condensed-matter|python|model-hamiltonians|tight-binding|wavefunctions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6215" PostTypeId="2" ParentId="3664" CreationDate="2021-06-22T08:52:25.573" Score="5" Body="&lt;p&gt;This is a complicated question for which I do not have a full answer. However, here are some thoughts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Excited state relaxation.&lt;/strong&gt; In solids, the calculation of excited states typically requires the many-body &lt;em&gt;GW&lt;/em&gt; approximation for quasi-particle energies and the solution of the Bethe-Salpeter equation for excitonic properties. The calculation of forces, a prerequisite to perform geometry optimizations, is not standard in these approaches. This &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.90.076401&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; by Ismail-Beigi and Louie discusses an approach to calculate forces in the excited state, but despite being almost 20 years old, there is not much in terms of follow-up. My best guess as to why there is not much work in this direction is because excitations are typically screened rather effectively in solids, so geometry changes in the excited state tend to be smaller than in molecules.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Out-of-equilibrium BSE.&lt;/strong&gt; If one ignores geometry changes in the excited state, then it is possible to study recombination using the out-of-equilibrium Bethe-Salpeter equation. In this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.99.081109&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; [disclaimer: I am a co-author] this is used to calculate phonon-assisted luminescence in an indirect band gap semiconductor.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-06-22T08:52:25.573" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6216" PostTypeId="2" ParentId="6169" CreationDate="2021-06-22T09:32:48.067" Score="5" Body="&lt;p&gt;Properties that seem experimentally relevant and computationally accessible would include, naïvely:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Density of States at the Fermi level, relation with conductivity&lt;/li&gt;&#xA;&lt;li&gt;Density of States above and below the Fermi level, relation with how much negative/positive charge the system will accept, and at what voltage&lt;/li&gt;&#xA;&lt;li&gt;Density (in g/cm&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt; trivially obtained from unit cell mass/volume)&lt;/li&gt;&#xA;&lt;li&gt;Kinetics of the desired electrochemical reactions, related with charging time&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Phenomena that would also be interesting experimentally but which would require more detailed theoretical studies could be those related to materials fatigue, e.g.:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Formation and propagation of defects&lt;/li&gt;&#xA;&lt;li&gt;Irreversible redox reactions&lt;/li&gt;&#xA;&lt;li&gt;Structure and chemical reactions at the grain boundaries&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="198" LastActivityDate="2021-06-22T09:32:48.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6217" PostTypeId="2" ParentId="6214" CreationDate="2021-06-22T10:50:21.773" Score="10" Body="&lt;p&gt;One way of determining this is using the projected density of states (P-DOS)&lt;/p&gt;&#xA;&lt;p&gt;This resolves the DOS into specific orbitals thereby allowing you to discretize each orbitals weight for a specific energy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$&#xA;\mathrm{PDOS}_\nu(E) = \sum_i \psi^*_{i,\nu} [\mathbf S | \psi_{i}\rangle]_\nu D(E-\epsilon_i)&#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note here that &lt;span class=&quot;math-container&quot;&gt;$|\psi_i\rangle$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th eigenvector and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; is the orbital index. The overlap matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf S$&lt;/span&gt; is here for generality but for orthogonal basis it is the identity matrix, and finally &lt;span class=&quot;math-container&quot;&gt;$D(E)$&lt;/span&gt; is the distribution function, Gaussian, Lorentzian etc.&lt;/p&gt;&#xA;&lt;p&gt;The following analysis depends on what you want to figure out. If you are only interested in the &lt;em&gt;weight&lt;/em&gt; of a given orbital for a given eigenstate, then doing &lt;span class=&quot;math-container&quot;&gt;$\psi^*_{i,\nu}|\mathbf S|\psi_i\rangle$&lt;/span&gt; would give you the vector that gives you the weight for each orbital.&lt;br /&gt;&#xA;If you want this across the entire Brillouin zone you have to integrate over that, &lt;span class=&quot;math-container&quot;&gt;$\sum_k w_k \mathrm{PDOS}_\nu(E)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So here it seems your Python code is almost complete. You'll just want to sum the contribution for each block orbitals to get the full picture. Generally one may then plot the &lt;em&gt;so-called&lt;/em&gt; fatbands which is basically the PDOS on top of the band-structure.&lt;/p&gt;&#xA;&lt;p&gt;Note that the energy dependence on the P-DOS is not necessary if you are not interested in energy-resolved quantities.&lt;/p&gt;&#xA;&lt;p&gt;If you want to &lt;em&gt;track&lt;/em&gt; the eigenvectors in the Brillouin zone I would suggest you to sort according to the eigenvectors that resemble each other the most (besides a common phase-factor).&#xA;I.e. something like &lt;span class=&quot;math-container&quot;&gt;$\langle \psi_j|\mathbf S|\psi_i\rangle e^{i\theta}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; should be optimized to maximize the overlap between the states.&lt;/p&gt;&#xA;&lt;p&gt;PS. It isn't totally clear to me what exactly you want to describe. Whether the PDOS is enough or whether you want some band-unfolding procedure isn't totally clear to me.&#xA;Also, are you using the same small 3-orbital Hamiltonian repeated 100 times along one direction? This wouldn't be the best method.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I have understood your question like this, you want to figure out how the edge states are dispersed across the orbitals in the system. And possibly which of the 3 orbitals (from the primary cell) have the largest contribution to the edge states.&lt;br /&gt;&#xA;I would suggest you start with a smaller system, say a width = 8 or less system such that the bands are easier to distinguish. Using a width of 100 only makes the spaghetti band-structure more difficult.&lt;br /&gt;&#xA;Since you already know which state is the &lt;em&gt;edge-state&lt;/em&gt; I suggest you do as you first suggested. Have a specific index for the edge-state, then at some band-crossing (happening at a specific &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;) and do your PDOS like this. No need to complicate things if not necessary. :)&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-06-28T07:43:28.467" LastActivityDate="2021-06-28T07:43:28.467" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6218" PostTypeId="2" ParentId="6169" CreationDate="2021-06-22T15:19:25.743" Score="5" Body="&lt;p&gt;I have personally worked on many of these projects, and &lt;strong&gt;I consider the following paper as the most simplistic benchmark (as well as the Holy Grail)&lt;/strong&gt; to better understand the properties of interest that need to be computed for energy storage materials, with necessary proof on why each of such properties are significant: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0360319920340106&quot; rel=&quot;nofollow noreferrer&quot;&gt;High capacity reversible hydrogen storage in titanium doped 2D carbon allotrope Ψ-graphene: Density Functional Theory investigations&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the computational point of view, involving methodologies like DFT (Density Functional Theory), the following properties would be of prime interest:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Density of States at the Fermi level, relation with magnetic nature and conductivity&lt;/li&gt;&#xA;&lt;li&gt;Density of States above and below the Fermi level, relation with details on the charge transfer occurring within the constituent atoms&lt;/li&gt;&#xA;&lt;li&gt;Density (in g/cm3 trivially obtained from unit cell mass/volume)&lt;/li&gt;&#xA;&lt;li&gt;Kinetics of the desired electrochemical reactions, related with charging time&lt;/li&gt;&#xA;&lt;li&gt;MD Simulations are to be run to check for stability at higher operating temperatures.&lt;/li&gt;&#xA;&lt;li&gt;Diffusion Energy Barrier Calculations need to be performed and illustrated&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2021-06-23T21:38:05.847" LastActivityDate="2021-06-23T21:38:05.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6219" PostTypeId="1" AcceptedAnswerId="6222" CreationDate="2021-06-22T15:34:04.230" Score="9" ViewCount="1488" Body="&lt;p&gt;Rephrasing the above, what is the pattern in which the electron-density data is stored in the CHGCAR file?&lt;/p&gt;&#xA;&lt;p&gt;I understand that the electron density data in a CHGCAR file is in the form of a 3D Fortran array, but I believe that such electron density data should be stored in 3 columns (NX,NY,NZ). Instead we see the presence of 5 columns.&#xA;&lt;em&gt;&lt;strong&gt;What I am requesting, is a comprehensive description of the 5-column electron density data present in every CHGCAR file, and the significance of every column present to represent the electron-density data.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have shown the part of the CHGCAR data that I am referring to, is shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  64   64   64&#xA; 0.27296628474E+03 0.27129538645E+03 0.26632236747E+03 0.25816527382E+03 0.24701868651E+03&#xA; 0.23315320780E+03 0.21691723332E+03 0.19873896341E+03 0.17912393717E+03 0.15864307047E+03&#xA; 0.13790873569E+03 0.11754046377E+03 0.98125176377E+02 0.80177959210E+02 0.64108387081E+02&#xA; 0.50195641939E+02 0.38574367354E+02 0.29232778335E+02 0.22024079253E+02 0.16690923309E+02&#xA; 0.12900228129E+02 0.10283187627E+02 0.84752878195E+01 0.72047216409E+01 0.63226226628E+01&#xA; 0.57166613639E+01 0.53025284991E+01 0.50199593897E+01 0.48277275324E+01 0.46988015018E+01&#xA; 0.46162530737E+01 0.45701256193E+01 0.45552760083E+01 0.45701256193E+01 0.46162530737E+01&#xA; 0.46988015018E+01 0.48277275324E+01 0.50199593897E+01 0.53025284991E+01 0.57166613639E+01&#xA; 0.63226226628E+01 0.72047216409E+01 0.84752878195E+01 0.10283187627E+02 0.12900228129E+02&#xA; 0.16690923309E+02 0.22024079253E+02 0.29232778335E+02 0.38574367354E+02 0.50195641939E+02&#xA; 0.64108387081E+02 0.80177959210E+02 0.98125176377E+02 0.11754046377E+03 0.13790873569E+03&#xA; 0.15864307047E+03 0.17912393717E+03 0.19873896341E+03 0.21691723332E+03 0.23315320780E+03&#xA; 0.24701868651E+03 0.25816527382E+03 0.26632236747E+03 0.27129538645E+03 0.27129538645E+03&#xA;..................... over a hundred thousand lines of data&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2021-06-22T20:13:01.100" LastActivityDate="2022-11-13T21:01:11.647" Title="What is the format of the electron-density data in a CHGCAR file?" Tags="|density-functional-theory|vasp|electron-density|fortran|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6220" PostTypeId="1" CreationDate="2021-06-22T15:58:50.300" Score="7" ViewCount="45" Body="&lt;p&gt;I used first principle calculations to study the thin film model. An obvious crossing was shown to appear at the gamma point when the edge state was calculated, which was originally predicted to be the evidence of quantum spin hall phases. The edge state occur at the Gamma point but it is not the location of of VBM. Therefore when I use the recursive green function method to calculate the edge state, the crossing appear inside the bulk band region.  &lt;strong&gt;If we use the non-Abelian Berry connection method to calculate the &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt;, is it possible to get a &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; = 0 result in this situation?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="621" LastEditDate="2021-06-24T14:05:49.543" LastActivityDate="2021-06-24T14:05:49.543" Title="The quantum spin Hall phase with Z2 = 0?" Tags="|density-functional-theory|condensed-matter|topological-insulators|tight-binding|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-26T00:04:18.300" ContentLicense="CC BY-SA 4.0" />
  <row Id="6222" PostTypeId="2" ParentId="6219" CreationDate="2021-06-22T17:16:21.227" Score="8" Body="&lt;p&gt;From the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/CHGCAR&quot; rel=&quot;noreferrer&quot;&gt;Vaspwiki&lt;/a&gt;, the CHGCAR file writes out the density using this Fortran snippet:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;WRITE(IU,FORM) (((C(NX,NY,NZ),NX=1,NGXF),NY=1,NGYF),NZ=1,NGZF)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Basically, this will iterate through the coordinates in the order X, then Y, then Z. For your case, this would look something like with &lt;span class=&quot;math-container&quot;&gt;$(N_x,N_y,N_z)$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$(1,1,1),(2,1,1),...,(64,1,1),(1,2,1),(2,2,1),...$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The five columns don't have any particular meaning, the screen would just become too cluttered if you tried to include more values per line, so they just print five at a time. This is what the &lt;code&gt;FORM&lt;/code&gt; option in the code above is doing; they don't include the code for the format on the Vaspwiki, but if the code were just &lt;code&gt;write(iu,*)&lt;/code&gt;, it would try to print all these values on one line until it ran out of buffer space.&lt;/p&gt;&#xA;&lt;p&gt;To find the actual coordinate values of a grid point from its index, you can convert using &lt;span class=&quot;math-container&quot;&gt;$$(N_x,N_y,N_z)=\frac{N_x-1}{N_{GXF}}\vec{a}+\frac{N_y-1}{N_{GYF}}\vec{b}+\frac{N_z-1}{N_{GZF}}\vec{c}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\vec{a},\vec{b},\vec{c}$&lt;/span&gt; are the lattice vectors.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-22T19:28:23.860" LastActivityDate="2021-06-22T19:28:23.860" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6223" PostTypeId="1" CreationDate="2021-06-22T19:03:39.507" Score="6" ViewCount="1541" Body="&lt;p&gt;I would like to understand how to calculate the band structure of the Graphene monolayer system using DFT. I am using VASP for material simulation. My question is how to write the crystal structure information file (POSCAR) for a 2D system such as Graphene. I think I can write the POSCAR file for many 3D systems, but I would like to understand how to write the POSCAR file if I am dealing with a 2D material system.&lt;/p&gt;&#xA;" OwnerUserId="3815" LastActivityDate="2021-06-23T08:39:37.670" Title="POSCAR data file for a 2D system" Tags="|density-functional-theory|vasp|condensed-matter|2d-lattice|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6224" PostTypeId="2" ParentId="6223" CreationDate="2021-06-22T19:36:39.647" Score="6" Body="&lt;p&gt;You generally cannot calculate a 2D system per se with a plane-wave program, but rather you should do a vacuum slab calculation. As for graphene, you would essentially do a calculation on graphite, but with the interlayer distance set at a large value, say 20 Angstrom (and the lattice constant c enlarged accordingly), so that the different layers of graphene virtually do not interact with each other. Make sure to freeze the lattice constant c, and use only one k-point along the c direction, although you still need an appropriate number of k-points along the a and b directions.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-06-23T08:22:26.560" LastActivityDate="2021-06-23T08:22:26.560" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6225" PostTypeId="1" AcceptedAnswerId="8522" CreationDate="2021-06-22T19:43:34.633" Score="9" ViewCount="1173" Body="&lt;p&gt;We all know that Vesta helps us visualize the electron clouds present in the CHGCAR data, but I am looking for a better way to process the electron-density data we get in a CHGCAR file for compact handling and eventually better understanding.&lt;/p&gt;&#xA;&lt;p&gt;For example, I have a CHGCAR file on a 64x64x64 grid. But it is a 5 column dataset as shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     64   64   64&#xA; 0.27296628474E+03 0.27129538645E+03 0.26632236747E+03 0.25816527382E+03 0.24701868651E+03&#xA; 0.23315320780E+03 0.21691723332E+03 0.19873896341E+03 0.17912393717E+03 0.15864307047E+03&#xA; 0.13790873569E+03 0.11754046377E+03 0.98125176377E+02 0.80177959210E+02 0.64108387081E+02&#xA; 0.50195641939E+02 0.38574367354E+02 0.29232778335E+02 0.22024079253E+02 0.16690923309E+02&#xA; 0.12900228129E+02 0.10283187627E+02 0.84752878195E+01 0.72047216409E+01 0.63226226628E+01&#xA; 0.57166613639E+01 0.53025284991E+01 0.50199593897E+01 0.48277275324E+01 0.46988015018E+01&#xA; 0.46162530737E+01 0.45701256193E+01 0.45552760083E+01 0.45701256193E+01 0.46162530737E+01&#xA; 0.46988015018E+01 0.48277275324E+01 0.50199593897E+01 0.53025284991E+01 0.57166613639E+01&#xA; 0.63226226628E+01 0.72047216409E+01 0.84752878195E+01 0.10283187627E+02 0.12900228129E+02&#xA; 0.16690923309E+02 0.22024079253E+02 0.29232778335E+02 0.38574367354E+02 0.50195641939E+02&#xA; 0.64108387081E+02 0.80177959210E+02 0.98125176377E+02 0.11754046377E+03 0.13790873569E+03&#xA; 0.15864307047E+03 0.17912393717E+03 0.19873896341E+03 0.21691723332E+03 0.23315320780E+03&#xA; 0.24701868651E+03 0.25816527382E+03 0.26632236747E+03 0.27129538645E+03 0.27129538645E+03&#xA;..................... over a hundred thousand lines of data&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I understand that this data is written serially, and as a result there are 5 data per line. If there is a way to parse and convert this data into a 3D Matrix of shape (64,64,64), it could be better handled.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Note&lt;/em&gt;: This is related to my prior post &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6219/what-is-the-format-of-the-electron-density-data-in-a-chgcar-file&quot;&gt;What is the format of the electron-density data in a CHGCAR file?&lt;/a&gt;, but they are distinct questions. While the initial question was about what format was used for CHGCAR data, this particular question aims to find a post-processing method for this data.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-06-25T21:36:38.177" LastActivityDate="2022-01-10T19:41:27.090" Title="How to process electron-density data from a CHGCAR for better handling?" Tags="|density-functional-theory|vasp|python|electron-density|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6226" PostTypeId="1" CreationDate="2021-06-22T20:52:38.890" Score="5" ViewCount="158" Body="&lt;p&gt;A &lt;code&gt;.cif&lt;/code&gt; file can be used for multiple purposes and is a more generic format to store atomic data.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-06-22T21:52:12.377" LastActivityDate="2021-06-23T15:22:17.400" Title="Can a CHGCAR file be converted into a CIF file?" Tags="|density-functional-theory|vasp|cif|electron-density|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6227" PostTypeId="2" ParentId="5011" CreationDate="2021-06-23T03:42:18.493" Score="8" Body="&lt;p&gt;I recently made charge densities available for the MOFs and coordination polymers of the Quantum MOF (QMOF) Database. Please read &lt;a href=&quot;https://github.com/arosen93/QMOF&quot; rel=&quot;noreferrer&quot;&gt;the GitHub page&lt;/a&gt; for details on how to access the charge densities. That being said, given the large size of the files, I wish you luck downloading it in bulk.&lt;/p&gt;&#xA;" OwnerUserId="206" LastEditorUserId="3566" LastEditDate="2021-06-23T13:33:51.857" LastActivityDate="2021-06-23T13:33:51.857" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6228" PostTypeId="2" ParentId="6223" CreationDate="2021-06-23T08:39:37.670" Score="4" Body="&lt;p&gt;The VASP package solving the KS-equation with periodic boundary conditions (PBC). For two-dimensional materials such as graphene, you only have two periodic directions along &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{b}$&lt;/span&gt; but the VASP assumes you still have three directions. To avoid this, you need to add enough vacuum (in general large than 15 angstroms) along the &lt;span class=&quot;math-container&quot;&gt;$\vec{c}$&lt;/span&gt; dirction.&lt;/p&gt;&#xA;&lt;p&gt;Here is a &lt;code&gt;POSCAR&lt;/code&gt; template:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C&#xA;1.0&#xA;    2.4600000381         0.0000000000         0.0000000000&#xA;   -1.2300000191         2.1304225263         0.0000000000&#xA;    0.0000000000         0.0000000000        15.0000000000  ! add vacuum along the assumed PBC direction.&#xA;C&#xA;2&#xA;Direct&#xA;    0.000000000         0.000000000         0.500000000&#xA;    0.333333359         0.666666706         0.500000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-06-23T08:39:37.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6229" PostTypeId="2" ParentId="6219" CreationDate="2021-06-23T08:45:38.503" Score="2" Body="&lt;p&gt;&lt;code&gt;VESTA&lt;/code&gt; can understand the data format of &lt;code&gt;CHGCAR&lt;/code&gt; outputted by &lt;code&gt;VASP&lt;/code&gt;. You just need to move &lt;code&gt;CHGCAR&lt;/code&gt; to &lt;code&gt;CHGCAR.vasp&lt;/code&gt; and then open with &lt;code&gt;VESTA&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="3566" LastEditDate="2022-11-13T21:01:11.647" LastActivityDate="2022-11-13T21:01:11.647" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6230" PostTypeId="2" ParentId="4003" CreationDate="2021-06-23T13:35:07.727" Score="7" Body="&lt;p&gt;Judging by your initial energies, it looks like you're starting a calculation from scratch. I've had good luck so far converging spin-polarized calculations by first doing a non-spin-polarized calculation, writing the &lt;code&gt;CHG&lt;/code&gt;, &lt;code&gt;CHGCAR&lt;/code&gt;, and &lt;code&gt;WAVECAR&lt;/code&gt; files, and using those to start a spin-polarized calculation. This is the recommended method if such calculations aren't converging reliably &lt;a href=&quot;https://www.vasp.at/wiki/index.php/MAGMOM&quot; rel=&quot;nofollow noreferrer&quot;&gt;according to the wiki&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In addition, I've found &lt;code&gt;ALGO=All&lt;/code&gt; to converge sometimes when the default doesn't.&lt;/p&gt;&#xA;" OwnerUserId="3817" LastEditorUserId="5" LastEditDate="2021-06-23T18:31:05.967" LastActivityDate="2021-06-23T18:31:05.967" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6231" PostTypeId="1" CreationDate="2021-06-23T14:12:18.490" Score="7" ViewCount="82" Body="&lt;p&gt;I am separately learning about DFT modelling of materials using Quantum ESPRESSO (QE), and the theory of plasma-material interactions (PMI). This made me wonder: Is there any way to model PMI using DFT even if it's a crude model?&lt;/p&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2021-12-18T16:39:07.173" LastActivityDate="2021-12-18T18:07:53.500" Title="Simulate plasma-material interactions (PMI) using Density Functional Theory (DFT)?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="1" ClosedDate="2022-01-13T02:08:13.723" ContentLicense="CC BY-SA 4.0" />
  <row Id="6232" PostTypeId="2" ParentId="6159" CreationDate="2021-06-23T14:17:00.850" Score="3" Body="&lt;h2&gt;Hückel method can be related to Graph theory&lt;/h2&gt;&#xA;&lt;p&gt;Graph theory is not part of the average Chemistry undergraduate curriculum, so I have just cursory knowledge about it. But from what I read about, it shows everywhere in Chemistry. Regarding Matter Modeling, &lt;a href=&quot;https://en.wikipedia.org/wiki/H%C3%BCckel_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hückel molecular orbital theory&lt;/a&gt; is one of the early wins of quantitative theoretical chemistry, developed by &lt;a href=&quot;https://en.wikipedia.org/wiki/Erich_H%C3%BCckel&quot; rel=&quot;nofollow noreferrer&quot;&gt;Erich Hückel&lt;/a&gt; in the 1930s, to explain systems containing conjugated double bonds that show up a lot in organic chemistry. For a bit of history on it, see (1). &lt;a href=&quot;https://en.wikipedia.org/wiki/Benzene&quot; rel=&quot;nofollow noreferrer&quot;&gt;Benzene&lt;/a&gt; is the poster child of these systems.&lt;/p&gt;&#xA;&lt;p&gt;Hückel proposed the energy levels in these systems can be obtained by solving a secular determinant with this form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$det([H_{ij} - ES_{ij}]) = 0$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$H_{ij}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; are known as the overlap and Hamiltonian matrices. To solve it, he adopted the following approximations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S_{ij} = 1,\text{ if } i = j$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{ij} = 0,\text{ if } i \neq j$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H_{ij} = \alpha,\text{ if } i = j$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H_{ij} = \beta,\text{ if } i \text{ adjacent to } j$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H_{ij} = 0,\text{ otherwise}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is approximately the energy of a electron in a &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt; isolated carbon orbital, and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; approximately the interaction energy of parallel &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt; orbitals in adjacent carbons.&lt;/p&gt;&#xA;&lt;p&gt;Taking the example of benzene, we obtain this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/spPm8.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/spPm8.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then we can use a computer algebra system (CAS) like &lt;a href=&quot;https://www.sympy.org/en/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SymPy&lt;/a&gt; to solve this secular determinant:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from sympy import symbols, Matrix, roots&#xA;&#xA;E, α, β = symbols('E α β')&#xA;M = Matrix([[α-E,β,0,0,0,β],&#xA;            [β,α-E,β,0,0,0],&#xA;            [0,β,α-E,β,0,0],&#xA;            [0,0,β,α-E,β,0],&#xA;            [0,0,0,β,α-E,β],&#xA;            [β,0,0,0,β,α-E]])&#xA;benzene_polynomial = M.det()&#xA;benzene_roots = roots(benzene_polynomial, E)&#xA;print('Solutions:', benzene_roots)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Getting the following result:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Solutions: {α + 2*β: 1, α - 2*β: 1, α + β: 2, α - β: 2}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Filling the pi electrons contributed by each of the six carbons according to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Aufbau_principle&quot; rel=&quot;nofollow noreferrer&quot;&gt;Aufbau principle&lt;/a&gt;, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lnMv3.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lnMv3.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That explains the stability of benzene, as every pi electron ends in a orbital at a energy level bellow the reference energy &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (note &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; is a negative number), and they're all paired up, thus avoiding a reactive radical form with unpaired electrons. So we find benzene and benzene-like molecules everywhere in organic chemistry. The &lt;a href=&quot;https://en.wikipedia.org/wiki/Nucleobase&quot; rel=&quot;nofollow noreferrer&quot;&gt;nucleobases&lt;/a&gt; in DNA, for example, have benzene-like rings in their structures.&lt;/p&gt;&#xA;&lt;p&gt;As explained in (2), the Huckel secular determinant can be related to the adjacency matrix of the molecular graph:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Theorem 4. If λ is an eigenvalue and z an eigenvector of the matrix&#xA;A, then α + βλ is an eigenvalue and z is an eigenvector of the matrix&#xA;H.&lt;/p&gt;&#xA;&lt;p&gt;From this theorem it follows that the Hückel molecular orbitals&#xA;coincide with the eigenvectors zj of eigenvalues λj, j=1,2,...,n, of&#xA;the adjacency matrix of the Hückel graph. The eigenvalues λj of the&#xA;matrix A and the energies Ej of the corresponding electrons are&#xA;related simply as&lt;/p&gt;&#xA;&lt;p&gt;Ej = α + βλj.&lt;/p&gt;&#xA;&lt;p&gt;There are exactly n different molecular orbitals, namely the zj for&#xA;j=1,2,...,n. This important conclusion shows that there is a deep and&#xA;far-reaching relation between the Hückel molecular orbital theory and&#xA;graph spectral theory. The Hückel theory provides an important field&#xA;of application of the graph spectra. The main contribution of [9] was&#xA;to establish that the Hückel theory and theory of graph spectra are&#xA;essentially the same.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;(1). &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20470&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kutzelnigg, Werner. “What I like about Hückel theory”. Journal of Computational Chemistry, vol. 28, no 1, 2007, p. 25–34. Wiley Online Library, doi:https://doi.org/10.1002/jcc.20470.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(2). &lt;a href=&quot;https://match.pmf.kg.ac.rs/electronic_versions/Match72/n2/match72n2_565-572.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cvetkovic, Dragoš. “Two mathematical papers relevant for the Hückel molecular orbital theory”. MATCH Commun. Math. Comput. Chem, vol. 72, 2014, p. 565–72.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2021-06-23T14:17:00.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6233" PostTypeId="2" ParentId="6226" CreationDate="2021-06-23T15:22:17.400" Score="3" Body="&lt;p&gt;While a CIF is not a suitable file format for handling volumetric charge density data, you may find Henkelman's chg2cube.pl &lt;a href=&quot;https://theory.cm.utexas.edu/vtsttools/scripts.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;script&lt;/a&gt; to achieve what you're looking for. It will convert a VASP CHGCAR file into a &lt;a href=&quot;http://paulbourke.net/dataformats/cube/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cube&lt;/a&gt; format, the latter of which many programs can also read and is fairly easy to understand.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-06-23T15:22:17.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6234" PostTypeId="2" ParentId="6225" CreationDate="2021-06-23T15:42:46.267" Score="6" Body="&lt;p&gt;While its technically more of a direct programming question at this point (since you don't necessarily need to know the source of this data to parse the format), this can be done fairly easily with numpy and pandas.&lt;/p&gt;&#xA;&lt;p&gt;As a test case, I used a toy version of your data in a file called &lt;code&gt;data.txt&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     11   2   3&#xA; 0.27296628474E+03 0.27129538645E+03 0.26632236747E+03 0.25816527382E+03 0.24701868651E+03&#xA; 0.23315320780E+03 0.21691723332E+03 0.19873896341E+03 0.17912393717E+03 0.15864307047E+03&#xA; 0.13790873569E+03 0.11754046377E+03 0.98125176377E+02 0.80177959210E+02 0.64108387081E+02&#xA; 0.50195641939E+02 0.38574367354E+02 0.29232778335E+02 0.22024079253E+02 0.16690923309E+02&#xA; 0.12900228129E+02 0.10283187627E+02 0.84752878195E+01 0.72047216409E+01 0.63226226628E+01&#xA; 0.57166613639E+01 0.53025284991E+01 0.50199593897E+01 0.48277275324E+01 0.46988015018E+01&#xA; 0.46162530737E+01 0.45701256193E+01 0.45552760083E+01 0.45701256193E+01 0.46162530737E+01&#xA; 0.46988015018E+01 0.48277275324E+01 0.50199593897E+01 0.53025284991E+01 0.57166613639E+01&#xA; 0.63226226628E+01 0.72047216409E+01 0.84752878195E+01 0.10283187627E+02 0.12900228129E+02&#xA; 0.16690923309E+02 0.22024079253E+02 0.29232778335E+02 0.38574367354E+02 0.50195641939E+02&#xA; 0.64108387081E+02 0.80177959210E+02 0.98125176377E+02 0.11754046377E+03 0.13790873569E+03&#xA; 0.15864307047E+03 0.17912393717E+03 0.19873896341E+03 0.21691723332E+03 0.23315320780E+03&#xA; 0.24701868651E+03 0.25816527382E+03 0.26632236747E+03 0.27129538645E+03 0.27129538645E+03&#xA; 0.1000000000e+10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I added one extra value to give it a consistent grid dimension and to show how incomplete rows are handled.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pandas as pd&#xA;import numpy as np&#xA;&#xA;#Make a table, elements separated by whitespace,&#xA;#Always five columns&#xA;df = pd.read_table('data.txt', sep='\s+', names=range(5))&#xA;&#xA;#Grab the dimensions, first three elements of the first row&#xA;dims=tuple(int(d) for d in in df.iloc[0][:3])&#xA;&#xA;#Find number of missing values, displayed as nan&#xA;#remove two for &amp;quot;missing values&amp;quot; in dimension row&#xA;nan_count=df.isna().sum().sum()-2&#xA;&#xA;#Convert to 1D numpy array, removing excess nans/dimensions&#xA;if nan_count==0:&#xA;    D=df.to_numpy().flatten()[5:]&#xA;else:&#xA;    D=df.to_numpy().flatten()[5:-nan_count]&#xA;&#xA;#Reshape to 3D array&#xA;D=D.reshape(dims)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will give an &lt;span class=&quot;math-container&quot;&gt;$(11,2,3)$&lt;/span&gt; numpy array where the dimensions are ordered &lt;span class=&quot;math-container&quot;&gt;$(X,Y,Z)$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-06-23T15:42:46.267" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6235" PostTypeId="1" CreationDate="2021-06-23T17:17:19.673" Score="6" ViewCount="542" Body="&lt;p&gt;My aim is to voxelize a CHGCAR file. I am trying to build up a workflow to do the same. With the aid of the Matter Modeling community members, I have figured out a way to convert a CHGCAR file into the CUBE format. Now I want to further process the CUBE file, in an attempt to voxelize it.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-06-23T18:23:16.067" LastActivityDate="2021-06-24T03:10:46.347" Title="Can a file in the Gaussian CUBE format be voxelized?" Tags="|vasp|gaussian|visualization-software|charge-density|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6236" PostTypeId="2" ParentId="6235" CreationDate="2021-06-23T19:14:59.520" Score="8" Body="&lt;p&gt;I'm not sure precisely what you mean, but if you want to convert a Cube file to an (&lt;span class=&quot;math-container&quot;&gt;$N\times4$&lt;/span&gt;) matrix where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of points and the 4 columns are (x,y,z,value), you can try the following code snippet taken from my GitHub repository &lt;a href=&quot;https://github.com/arosen93/mof-adsorbate-initializer/blob/master/mai/grid_handler.py#L6&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, which I reproduce below:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;&#xA;cube_filepath = '/path/to/mycube.cube' # Path to Cube File&#xA;&#xA;def cube_to_xyzval(cube_file):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Converts cube to pandas DataFrame&#xA;&#xA;    Args:&#xA;        cube_file (string): path to cube file&#xA;    &#xA;    Returns:&#xA;        pd_data (Pandas dataframe): dataframe of (x,y,z,val) grid&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    at_coord=[]&#xA;    spacing_vec=[]&#xA;    nline = 0&#xA;    values=[]&#xA;    data = []&#xA;    with open(cube_file,'r') as f:&#xA;        for line in f:&#xA;            nline += 1&#xA;            if nline == 3:&#xA;                nat=int(line.split()[0])&#xA;            elif nline &amp;gt;3 and nline &amp;lt;= 6:&#xA;                spacing_vec.append(line.split())&#xA;            elif nline &amp;gt; 6 and nline &amp;lt;= 6+nat:&#xA;                at_coord.append(line.split())&#xA;            elif nline &amp;gt; 5 and nline &amp;gt; 6+nat:&#xA;                for i in line.split():&#xA;                    values.append(float(i))&#xA;    idx = -1&#xA;    for i in range(0,int(spacing_vec[0][0])):&#xA;        for j in range(0,int(spacing_vec[1][0])):&#xA;            for k in range(0,int(spacing_vec[2][0])):&#xA;                idx += 1&#xA;                x,y,z = i*float(spacing_vec[0][1]),j*float(spacing_vec[1][2]),k*float(spacing_vec[2][3])&#xA;                data.append([x,y,z,values[idx]])&#xA;    pd_data = pd.DataFrame(data)&#xA;    return pd_data&#xA;&#xA;df = cube_to_xyzval(cube_filepath)&#xA;df.columns = ['x','y','z','val']&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="206" LastEditorUserId="206" LastEditDate="2021-06-24T03:10:46.347" LastActivityDate="2021-06-24T03:10:46.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6237" PostTypeId="1" CreationDate="2021-06-23T21:37:18.293" Score="2" ViewCount="79" Body="&lt;p&gt;I can convert a &lt;code&gt;CHGCAR&lt;/code&gt; file on the NxNxN grid into a 3D array of shape (N,N,N) for better handling, if that helps. At the end of the day, I want plot/visualize the charge density with Python.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-06-23T21:55:35.800" LastActivityDate="2021-06-23T21:55:35.800" Title="How to plot a charge density from a CHGCAR file in Python?" Tags="|vasp|python|visualization-software|charge-density|" AnswerCount="0" CommentCount="6" ClosedDate="2021-11-29T18:59:14.203" ContentLicense="CC BY-SA 4.0" />
  <row Id="6238" PostTypeId="2" ParentId="6181" CreationDate="2021-06-23T22:06:06.830" Score="6" Body="&lt;p&gt;You likely need to ensure the correct anaconda environment is loaded.  Use the following to get a 2.7 environment.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;conda create --name py2 python=2.7&#xA;conda activate 2.7&#xA;pip install ase==3.12.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Your problems probably stem from issues with pip or the location of the installation.  Use this method to ensure you have your 2.7 environment and you have ase in it.  Then whenever you need the 2.7 version, simply run the activate command (you wont have to remake the environment).&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-06-23T22:06:06.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6239" PostTypeId="2" ParentId="1643" CreationDate="2021-06-23T22:27:46.303" Score="3" Body="&lt;h1&gt;Psi4&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://psicode.org/psi4manual/master/introduction.html#&quot; rel=&quot;nofollow noreferrer&quot;&gt;Psi4&lt;/a&gt; provides functions for &lt;a href=&quot;https://psicode.org/psi4manual/master/api/psi4.driver.fcidump.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;reading&lt;/a&gt; and &lt;a href=&quot;https://psicode.org/psi4manual/master/api/psi4.driver.fcidump_from_file.html#psi4.driver.fcidump_from_file&quot; rel=&quot;nofollow noreferrer&quot;&gt;writing&lt;/a&gt; FCIDUMP files from wavefunction objects. Using Psi4 as a Python module, these look something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import psi4&#xA;&#xA;#Writing (default fname is &amp;quot;INTDUMP&amp;quot;)&#xA;E, wfn = psi4.energy('scf', return_wfn=True)&#xA;psi4.fcidump(wfn)&#xA;&#xA;#Reading&#xA;##Returns dict of numerous properties including 1e (&amp;quot;hcore&amp;quot;) and 2e (&amp;quot;eri&amp;quot;) integrals&#xA;values=psi4.fcidump_from_file(&amp;quot;INTDUMP&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-06-23T22:27:46.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6240" PostTypeId="2" ParentId="4979" CreationDate="2021-06-24T14:34:53.757" Score="3" Body="&lt;p&gt;As specified in the &lt;a href=&quot;http://myweb.liu.edu/%7Enmatsuna/gamess/input/ORMAS.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GAMESS Documentation&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;nspace=n&lt;/code&gt; means the active space will be split into &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; groups.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;mstart&lt;/code&gt; sets the starting orbital for each of the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; groups. In your case, the first group extends from orbital 3 to orbital 9, while the second is from orbital 10 to &lt;code&gt;NCORE+NACT&lt;/code&gt; (the number of core and active space orbitals). They mention that in this only makes sense if you have used &lt;code&gt;NORDER&lt;/code&gt; in the guess section (I suppose otherwise there is no guarantee the active space is contiguous or that it is right after the core).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;mine&lt;/code&gt; sets the minimum number of electrons for each group.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;maxe&lt;/code&gt; sets the maxium number of electrons for each group.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-06-24T14:34:53.757" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6241" PostTypeId="2" ParentId="388" CreationDate="2021-06-24T17:46:11.310" Score="5" Body="&lt;p&gt;This question is a bit old now, but hopefully my answer can complement Thomas's for anyone who comes across it.&lt;/p&gt;&#xA;&lt;p&gt;While &amp;quot;materials&amp;quot; is not in the name of the book, I think great (though more advanced) introductions to these topics can be found in Thijssen's &lt;em&gt;Computational Physics&lt;/em&gt;. What's nice about it is that it covers the theory, provides coding (as well as theoretical) exercises, and has sample programs for each chapter on the author's website (albeit in Fortran77, which is a language I abhor). You should definitely know how to program and at least the basics of numerical methods to start this book. [1]&lt;/p&gt;&#xA;&lt;p&gt;For &lt;strong&gt;DFT&lt;/strong&gt;, as mentioned &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1056/how-to-write-my-own-density-functional-theory-dft-code-in-python/2108#2108&quot;&gt;in another post&lt;/a&gt;, the book starts you off with the Hartree problem, then you do the Hartree-Fock problem, and eventually planewave DFT.&lt;/p&gt;&#xA;&lt;p&gt;For &lt;strong&gt;Quantum Monte Carlo&lt;/strong&gt;, you start off with classical Monte Carlo integration and the Metropolis algorithm, before discussing a variety of modern QMC methods (VMC, DMC, PIMC).&lt;/p&gt;&#xA;&lt;p&gt;For &lt;strong&gt;Molecular Dynamics&lt;/strong&gt;, you start with a relatively simple symplectic integrator for a classical monatomic simulation, then move on to molecular systems, quantum systems, and eventually the Car-Parinello method (disclaimer: I didn't finish this section as it's not related to my own work).&lt;/p&gt;&#xA;&lt;p&gt;It also covers a range of other useful (or at least interesting) topics, though mostly focused on matter modelling, from the Duffing oscillator to lattice field theory. Thijssen covers a broad range of topics and hence doesn't go into such gruesome detail, however, so this should really be treated as an introduction, after which you can read more specialised books and review articles in the areas that interest you. In addition to getting the satisfaction of writing some of these programs from scratch, I have found it to be helpful in understanding what the software suites (e.g. Molpro, CASINO) I use for these calculations actually do and how to use them more effectively.&lt;/p&gt;&#xA;&lt;p&gt;[1]: For an introduction to numerics, I personally used Ascher and Greif's &lt;em&gt;Introduction to Numerical Methods&lt;/em&gt;, but this is not a matter modelling book. I have heard good things about Newman's and Koonin's books which are both more introductory as well and probably more interesting to people interested in matter modelling.&lt;/p&gt;&#xA;" OwnerUserId="1522" LastActivityDate="2021-06-24T17:46:11.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6242" PostTypeId="2" ParentId="6183" CreationDate="2021-06-24T20:02:44.180" Score="11" Body="&lt;p&gt;As Thomas mentioned, there are tools from Materials Project that we use for structure similarity. See for example &lt;a href=&quot;https://doi.org/10.1039/C9RA07755C&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, with code available in &lt;a href=&quot;https://pymatgen.org&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt;. This works by creating local environment &amp;quot;fingerprints&amp;quot; (e.g. octahedral, tetrahedral sites, etc.) and creating a distance between structures based on this.&lt;/p&gt;&#xA;&lt;p&gt;Other that this, one method I'm very fond of is the one described in &lt;a href=&quot;https://doi.org/10.1039/C6CP00415F&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; using the SOAP descriptor. I can highly recommend the implementation of this in &lt;a href=&quot;https://singroup.github.io/dscribe/latest/&quot; rel=&quot;noreferrer&quot;&gt;DScribe&lt;/a&gt;. This is actually quite performant and mathematically elegant. The disadvantage of this approach is that it doesn’t give as much human insight, since the SOAP vectors are more difficult to interpret than the local environment vectors (which can give values like “the degree of octahedral-ness”).&lt;/p&gt;&#xA;&lt;p&gt;I've implemented several of these for interactive use in &lt;a href=&quot;https://crystaltoolkit.org&quot; rel=&quot;noreferrer&quot;&gt;crystal toolkit&lt;/a&gt; if you want to try them out -- take a look at the &amp;quot;local environment&amp;quot; panel.&lt;/p&gt;&#xA;&lt;p&gt;I wouldn’t necessarily advise the neural network / cosine similarity approach. While this would likely work well, it’s also over-complicating the problem.&lt;/p&gt;&#xA;&lt;p&gt;Apologies, I would offer a longer response if I had the time, but I hope this is a good place to get started! If you have any questions about the Materials Project methods specifically, feel free to ask us about them at &lt;a href=&quot;https://matsci.org&quot; rel=&quot;noreferrer&quot;&gt;matsci.org&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastEditorUserId="1333" LastEditDate="2021-06-24T21:59:17.937" LastActivityDate="2021-06-24T21:59:17.937" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6243" PostTypeId="2" ParentId="6106" CreationDate="2021-06-24T22:14:57.897" Score="6" Body="&lt;h1&gt;ORBKIT&lt;/h1&gt;&#xA;&lt;p&gt;This uses the &lt;a href=&quot;http://orbkit.github.io&quot; rel=&quot;noreferrer&quot;&gt;ORBKIT&lt;/a&gt; package.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Gunter Hermann, Vincent Pohl, Jean Christophe Tremblay, Beate Paulus, Hans-Christian Hege, and Axel Schild, &lt;a href=&quot;https://doi.org/10.1002/jcc.24358&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;ORBKIT: A Modular Python Toolbox for Cross-Platform Postprocessing of Quantum Chemical Wavefunction Data&amp;quot;, J. Comput. Chem. 2016, 37, 1511-1520.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;import orbkit as ok&#xA;&#xA;ok.options.filename = '/path/to/86.molden' # also directly reads file.molden.gz if needed&#xA;ok.options.itype = 'molden'&#xA;ok.options.no_output = True # we'll directly get a Numpy array without generating a file&#xA;ok.options.adjust_grid = [5, 0.1] # 5 bohr padding on all sides, 0.1 bohr resolution&#xA;ok.options.numproc = 4 # or whatever you want - uses Python subprocess&#xA;&#xA;data = ok.run_orbkit() # prints useful log bits in Jupyter&#xA;&#xA;data.shape # returns (186, 179, 282) for my example file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you want to do this in a loop, you'll need to set the &lt;code&gt;ok.options&lt;/code&gt; every time:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ok.init()&#xA;# Set some options (again)&#xA;ok.options.filename = '/path/to/new/file.molden'&#xA;ok.options.itype = 'molden'&#xA;ok.options.no_output = True&#xA;ok.options.adjust_grid = [5, 0.1] # 5 bohr padding on all sides, 0.1 bohr resolution&#xA;ok.options.numproc = 4 # or whatever you want - uses Python subprocess&#xA;# run orbkit again&#xA;data_2 = ok.run_orbkit()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Orbkit easily handles the following formats:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Molden&lt;/li&gt;&#xA;&lt;li&gt;wfn/wfx&lt;/li&gt;&#xA;&lt;li&gt;fchk&lt;/li&gt;&#xA;&lt;li&gt;Interface to &lt;a href=&quot;https://cclib.gitub.io&quot; rel=&quot;noreferrer&quot;&gt;cclib&lt;/a&gt; parser (for other formats)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Beyond electron density it's pretty easy to generate:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;orbitals&lt;/li&gt;&#xA;&lt;li&gt;spin density&lt;/li&gt;&#xA;&lt;li&gt;derivatives (analytical first and second order)&lt;/li&gt;&#xA;&lt;li&gt;Laplacian&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;More can be found on the &lt;a href=&quot;https://orbkit.github.io/&quot; rel=&quot;noreferrer&quot;&gt;ORBKIT website&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I had to patch ORBKIT to read the Molden files I had (&lt;a href=&quot;https://github.com/orbkit/orbkit/pull/39&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/orbkit/orbkit/pull/39&lt;/a&gt;) but you can install via &lt;code&gt;pip install orbkit&lt;/code&gt; or &lt;code&gt;python setup.py install&lt;/code&gt; once you download.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-06-24T22:14:57.897" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6244" PostTypeId="5" CreationDate="2021-06-25T21:35:23.477" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-25T21:35:23.477" LastActivityDate="2021-06-25T21:35:23.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6245" PostTypeId="4" CreationDate="2021-06-25T21:35:23.477" Score="0" Body="For questions related to interpreting/debugging FORTRAN modeling code. Note, this tag need not be used for every question about FORTRAN software (like MOLPRO). It is only need for questions directly concerned with the code of such programs." OwnerUserId="5" LastEditorUserId="7" LastEditDate="2021-07-30T18:28:40.803" LastActivityDate="2021-07-30T18:28:40.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6246" PostTypeId="2" ParentId="4635" CreationDate="2021-06-26T03:14:57.767" Score="5" Body="&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/&quot; rel=&quot;noreferrer&quot;&gt;Amazon Elastic Compute Cloud (Amazon EC2)&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;AWS Free Tier (one year free trial) includes 750 hours per month for 12 months of t2.micro (1 vCPU, 1GB Memory) or t3.micro (2 vCPU, 1GB Memory) instance depending on region.&lt;/p&gt;&#xA;&lt;p&gt;You can choose from various &lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/instance-types/&quot; rel=&quot;noreferrer&quot;&gt;instance types&lt;/a&gt;&lt;/strong&gt; that is best suitable for your use case.&lt;/p&gt;&#xA;&lt;p&gt;There are a few pricing models:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/pricing/on-demand/&quot; rel=&quot;noreferrer&quot;&gt;On-Demand&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You pay for only what you use (by the hour or the second depending on which instances you run).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;E.g. Hourly on-demand rates for general purpose instances with 8 vCPU are ranged from 0.2 to 0.7 USD per hour.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0GpcI.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0GpcI.png&quot; alt=&quot;on-demand general purpose instances w 8 vCPU&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/dedicated-hosts/pricing/&quot; rel=&quot;noreferrer&quot;&gt;Spot instances&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Spot instance prices are adjusted gradually based on supply and demand trends, one can use spot instances and save up to 90% off the on-demand price.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/pricing/reserved-instances/pricing/&quot; rel=&quot;noreferrer&quot;&gt;Reserved Instances&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Commit to using EC2 for a 1 or 3 year term and save up to 75% comparing to on-demand price&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://aws.amazon.com/ec2/dedicated-hosts/pricing/&quot; rel=&quot;noreferrer&quot;&gt;Dedicated Hosts&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-06-26T03:14:57.767" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6247" PostTypeId="2" ParentId="4054" CreationDate="2021-06-26T09:11:44.580" Score="4" Body="&lt;p&gt;I think this is a valid question.&lt;/p&gt;&#xA;&lt;p&gt;As the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PROJWFC.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation of &lt;code&gt;projwfc.x&lt;/code&gt; explains&lt;/a&gt;, it computes the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1439/what-are-the-types-of-charge-analysis/1465#1465&quot;&gt;Löwdin charges&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation of &lt;code&gt;pw.x&lt;/code&gt;&lt;/a&gt; seems to be silent on the scheme used to compute the charges reported by the SCF calculation.&lt;/p&gt;&#xA;&lt;p&gt;Luckily, Quantum ESPRESSO is open-source, so you can look at &lt;a href=&quot;https://gitlab.com/QEF/q-e&quot; rel=&quot;nofollow noreferrer&quot;&gt;the source&lt;/a&gt; and work back from the &lt;code&gt;Magnetic moment per site&lt;/code&gt; string =&amp;gt; &lt;code&gt;PP/src/report_mag.f90&lt;/code&gt; =&amp;gt; &lt;code&gt;get_locals.f90&lt;/code&gt; =&amp;gt; &lt;code&gt;make_pointslist.f90&lt;/code&gt;.&#xA;You find what you've been looking for in the documentation of the &lt;code&gt;make_pointslist&lt;/code&gt; subroutine:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This initialization is needed in order to integrate charge (or magnetic moment) in a sphere around the atomic positions.&#xA;This can be used to simply monitor these quantities during the scf&#xA;cycles or in order to calculate constraints on these quantities.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If the integration radius r_m is not provided in input, it is&#xA;calculated here. The integration is a sum over all points in real&#xA;space with&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the weight 1, if they are closer than &lt;span class=&quot;math-container&quot;&gt;$r_m$&lt;/span&gt; to an atom&#xA;and&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$(1 - (\text{distance}-r_m)/(0.2*r_m) )$&lt;/span&gt; if &lt;span class=&quot;math-container&quot;&gt;$( r_m &amp;lt; \text{distance}&amp;lt;1.2*r_m )$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The radius &lt;span class=&quot;math-container&quot;&gt;$r_m$&lt;/span&gt; is determined as&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... set the radius r_m to a value a little smaller than the&#xA;minimum&#xA;distance divided by 2*1.2 (so no point in space can belong to more than one atom)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I.e. the charge reported by the SCF calculation is a weighted integration of the electronic charge in a sphere around the nucleus.&#xA;The formula looks empirical, and the result is probably not comparable to quantities computed by other DFT codes.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-06-26T09:11:44.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6248" PostTypeId="2" ParentId="116" CreationDate="2021-06-26T11:02:07.927" Score="3" Body="&lt;p&gt;I would just like to point out that the question explicitly mentions adsorbing &lt;em&gt;atomic&lt;/em&gt; oxygen rather than &lt;span class=&quot;math-container&quot;&gt;$\mathrm{O_{2}}$&lt;/span&gt; (without mentioning the oxygen source or the surface).&lt;/p&gt;&#xA;&lt;p&gt;One can therefore somewhat simplify the question to: what is the strongest bond the oxygen atom can form?&lt;/p&gt;&#xA;&lt;p&gt;In molecules, &lt;a href=&quot;https://en.wikipedia.org/wiki/Bond-dissociation_energy&quot; rel=&quot;nofollow noreferrer&quot;&gt;the strongest bond is the C≡O triple bond in carbon monoxide&lt;/a&gt; at 11.16 eV (experimental value at room temperature).&lt;/p&gt;&#xA;&lt;p&gt;I.e. adsorbing atomic oxygen on a hypothetical &amp;quot;atomic carbon substrate&amp;quot; would indeed give an energy in the 10 eV range.&#xA;For realistic substrates like amorphous carbon, however, where surface carbons are bound to other carbons, the energy of the oxygen double bond should be significantly lower (I guess &lt;a href=&quot;http://cp.cm.kyushu-u.ac.jp/tools/IELSFOC/contents/virtual%20textbook/bond%20energy/bond%20energy.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;more in the 7-8 eV range&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-06-29T18:50:13.593" LastActivityDate="2021-06-29T18:50:13.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6249" PostTypeId="2" ParentId="6194" CreationDate="2021-06-26T11:59:39.157" Score="5" Body="&lt;p&gt;To answer your first question: the theory has certainly been worked out in some detail.&lt;/p&gt;&#xA;&lt;p&gt;The most accurate approach (a) would involve a quantum transport calculation in the non-equilibrium Green function formalism, describing the tip (L) and the sample (R) as semi-infinite leads, connected by a central region (C), and using the Meir-Wingreen formula to compute the I-V curve.&#xA;There are codes like &lt;a href=&quot;http://www.physics.lancs.ac.uk/gollum/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gollum&lt;/a&gt; that can do this (I haven't tried it myself).&lt;/p&gt;&#xA;&lt;p&gt;In the limit of the tip and the sample being well separated (b), you can start by computing the electronic structure of the tip and the sample independently, and then obtain the current from the overlap between the quasiparticle states of the two systems (Bardeen's theory of tunneling).&lt;/p&gt;&#xA;&lt;p&gt;Experimentally, however, the exact shape of the tip is often unknown (and also not the focus of interest of STM: you typically want to study the sample rather than the tip).&#xA;In the Tersoff-Hamann approximation (c), the tip is replaced by a single s-orbital and constant density of states (extensions exist for p-orbitals as found in CO-tips etc.).&#xA;This makes the tip wave function analytic and enables straightforward  simulation of STM images directly from the electronic states of the sample.&lt;/p&gt;&#xA;&lt;p&gt;While there are cases where the Tersoff-Hamann approximation will fail, its simplicity (both in terms of interpretation and computational complexity) often makes it the method of choice in practice; going to higher levels of theory only when required.&lt;/p&gt;&#xA;&lt;p&gt;For references and more details, including the formulae + numerical aspects like extrapolation of wave functions, see section 2.5 of &lt;a href=&quot;https://doi.org/10.5167/uzh-116635&quot; rel=&quot;nofollow noreferrer&quot;&gt;my Ph.D. thesis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EoIFF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EoIFF.png&quot; alt=&quot;Different ways of STM simulations&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-06-26T12:20:30.903" LastActivityDate="2021-06-26T12:20:30.903" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6250" PostTypeId="2" ParentId="4984" CreationDate="2021-06-26T23:18:20.307" Score="8" Body="&lt;p&gt;As mentioned by Phil Hasnip in the comments, placing a &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Na_2S_2}$&lt;/span&gt; molecule under periodic boundary conditions is akin to simulating a 3d array of these molecules.&#xA;If the molecule has a nonzero dipole moment, this give rise to an electric (dipole) field between adjacent 2d &amp;quot;planes&amp;quot; of molecules.&#xA;Unless you take care to orient the dipole of your molecule along a specific cartesian axis, it can point in &lt;em&gt;any&lt;/em&gt; direction of the cell. I.e. the effect you are seeing along the z direction may as well exist along x and y with different magnitudes proportional to the component of the molecular dipole in that direction.&lt;/p&gt;&#xA;&lt;p&gt;As with a parallel plate capacitor, at sufficient distance from the 2d &amp;quot;planes&amp;quot; of molecules the electric field is roughly constant, giving rise to the linear region of the potential in your plot.&#xA;The purpose of the dipole correction is to place a counter-dipole of opposite magnitude at a position sufficiently far away from the molecule in order to &amp;quot;flatten&amp;quot; the potential curve.&#xA;I'm not quite sure what you mean by &amp;quot;when I add dipole correction gave me two vacuum potentials&amp;quot;. When done right (see e.g. &lt;a href=&quot;https://christoph-wolf.at/2018/05/02/dipole-correction-in-quantum-espresso/&quot; rel=&quot;noreferrer&quot;&gt;this example&lt;/a&gt; by Christoph Wolf), you should simply obtain a flat potential.&lt;/p&gt;&#xA;&lt;p&gt;By the way, if you are just interested in the value of the vacuum potential, you could place the molecule in the center of the cell and simply take the value of the potential in a corner of the simulation box.&#xA;This neglects the polarizing effect of the electric field on the electron cloud in the molecule but should converge to the vacuum potential with increasing cell size.&lt;/p&gt;&#xA;&lt;p&gt;Finally, you don't state the purpose of this calculation (and there may be valid reasons for you to use Quantum ESPRESSO) but if it is to compute quantities like the ionization potential or the electron affinity of a molecule, don't use a code with periodic boundary conditions.&#xA;This is what quantum chemistry codes are for, and there are both &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4538/what-is-a-good-replacement-for-gaussian&quot;&gt;great commercial and free implementations&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-06-27T02:25:19.000" LastActivityDate="2021-06-27T02:25:19.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6251" PostTypeId="2" ParentId="5027" CreationDate="2021-06-26T23:41:06.677" Score="8" Body="&lt;p&gt;Please read the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm200&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;pw.x&lt;/code&gt; documentation on the Bravais lattice index (&lt;code&gt;ibrav&lt;/code&gt;)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The cell vectors for the primitive cell corresponding to the cubic face-centered Bravais lattice (&lt;code&gt;ibrav=2&lt;/code&gt;) are&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;v1 = (a/2)(-1,0,1),  v2 = (a/2)(0,1,1), v3 = (a/2)(-1,1,0)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The cell volume is &lt;span class=&quot;math-container&quot;&gt;$V=|v_1 \times v_2 \cdot v_3| = (a/2)^32=328.85\ \mathrm{a.u.}^3$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-06-26T23:41:06.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6252" PostTypeId="1" AcceptedAnswerId="6253" CreationDate="2021-06-27T00:10:08.023" Score="22" ViewCount="8904" Body="&lt;p&gt;Fortran language is used in many first-principles matter modeling codes, such as &lt;code&gt;VASP&lt;/code&gt; and &lt;code&gt;QE&lt;/code&gt;. These codes usually include many files and thousand of lines and are not readable for a newbie. Are there good strategies and resources to master the Fortran language with minimal effort if I have some experience with the &lt;code&gt;PYTHON&lt;/code&gt; language? The final purpose is to read and modify the existing Fortran codes such as &lt;code&gt;QE&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="269" LastEditDate="2021-06-27T17:06:33.370" LastActivityDate="2021-07-08T19:37:52.460" Title="How to master Fortran with minimal effort?" Tags="|vasp|quantum-espresso|programming|fortran|" AnswerCount="9" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6253" PostTypeId="2" ParentId="6252" CreationDate="2021-06-27T05:16:19.757" Score="28" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;How to master Fortran programing with minimal effort?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The concept of &amp;quot;mastering&amp;quot; a programming language is a bit subjective, and people typically don't &amp;quot;master&amp;quot; a language with &amp;quot;minimal effort&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;However as a Fortran programmer myself, there's two strategies I can recommend:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(1) Tutorials:&lt;/strong&gt; As with any programming language, there's plenty of books and tutorials for Fortran, and some of these come with exercises you can do to help you learn the language. Here's some of them:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ourcodingclub.github.io/tutorials/fortran-intro/&quot; rel=&quot;noreferrer&quot;&gt;Our coding club Fortran intro&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://fortran-lang.org/learn/&quot; rel=&quot;noreferrer&quot;&gt;Fortran-lang.org&lt;/a&gt; (there's a multitude of links to other tutorials and books there!)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.fortrantutorial.com/&quot; rel=&quot;noreferrer&quot;&gt;FORTRANtutorial.com&lt;/a&gt; (a 7 lesson course)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=__2UgFNYgf8&quot; rel=&quot;noreferrer&quot;&gt;Fortran tutorial youtube video&lt;/a&gt; (for those that like to listen rather than read)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;(2) Practicing:&lt;/strong&gt; As the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6252/how-to-master-fortran-programing-with-minimal-effort#comment12552_6252&quot;&gt;comment by user tmph says&lt;/a&gt; the best way is often just to practice. When I began Fortran as an undergrad summer student, I was told ahead of time that I'd be coding in Fortran, and I dreaded it.  I went to the library and picked up a bunch of books (online tutorials and youtube videos were unheard of at the time), thinking that I'd learn based on strategy #1 above. It turns out though that I learned much faster &amp;quot;by doing&amp;quot; rather than by reading.&lt;/p&gt;&#xA;&lt;p&gt;I recommend playing around with existing Fortran code, and adding simple features with gradually increasing complexity. Changing the number of digits for a numerical output in QE is an easy thing that I think you can try doing right now! Next you can add more output (more words, more numbers, etc.) You could also try to add new input flags for the feature you want to implement, and at every step of the way, see if it compiles, and &lt;em&gt;follow the error messages at compile time: I learned so much Fortran that way!&lt;/em&gt; &lt;strong&gt;Very soon&lt;/strong&gt; you'll find yourself feeling quite comfortable and you'll gain your confidence this way!&lt;/p&gt;&#xA;&lt;p&gt;I find Fortran to actually be in many respects, simpler and easier to master than Python, especially since &lt;em&gt;most&lt;/em&gt; Fortran code is not object-oriented, and you'll see that it's really &lt;em&gt;designed&lt;/em&gt; for scientific computing (the way you can output numerical values for example, will probably convince you of this). Python was not originally designed for number crunching, and neither was C or C++ or Java: these languages were designed to be more general, and are used for writing everything from operating systems, to GUIs, to web applications, to computer games, etc., whereas Fortran was literally designed for number crunching (a bit like MATLAB and Julia, the latter which was discussed &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/501/5&quot;&gt;here at MMSE&lt;/a&gt;) so once you spend some time familiarizing yourself with it, I'm confident that you'll find it much more natural for scientific computing than other languages you've used in the past.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="1206" LastEditDate="2021-06-27T19:21:52.693" LastActivityDate="2021-06-27T19:21:52.693" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6254" PostTypeId="2" ParentId="6252" CreationDate="2021-06-27T15:06:10.547" Score="20" Body="&lt;p&gt;Fortran is a language that evolved strongly and a programmer just maintain very old legacy codes will have very different needs from a programmer maintaining codes written in Fortran 95 and different needs will have a programmer who wants to employ modern techniques and develop new program that use Fortran 2003, 2008 and 2018 (and future revisions).&lt;/p&gt;&#xA;&lt;p&gt;The amount of features that appear in the successive revisions increases strongly, the biggest steps being Fortran 90 and Fortran 2003.&lt;/p&gt;&#xA;&lt;p&gt;Fortran 90 was completely superseded by Fortran 95 which fixed several defects or inconsistencies.&lt;/p&gt;&#xA;&lt;p&gt;Fortran 77 and earlier are very old and the programs often use techniques that are strongly discouraged today (and even deleted from the standard or marked obsolescent).&lt;/p&gt;&#xA;&lt;p&gt;Fortran 2003 brought object orientation, portable interfacing to C and much more. Fortran 2008 added smaller enhancement and parallel programming using coarrays.&lt;/p&gt;&#xA;&lt;p&gt;Fortran can be learnt from book and there is a choice different styles of introductory books. I always preferred the Fortran Explained (Fortran 90 explained, &lt;a href=&quot;https://global.oup.com/academic/product/fortran-952003-explained-9780198526926?lang=en&amp;amp;cc=in&quot; rel=&quot;noreferrer&quot;&gt;Fortran 2003 explained&lt;/a&gt;, &lt;a href=&quot;https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198811893.001.0001/oso-9780198811893&quot; rel=&quot;noreferrer&quot;&gt;Modern Fortran Explained&lt;/a&gt;) by Metcalf, Reid and Cohen. However, it is rather terse and can also be used as a reference book. It is written in a university textbook style and I prefer to use it as the recommended reference for my course.&lt;/p&gt;&#xA;&lt;p&gt;Some other books are oriented more practically, like the &lt;a href=&quot;https://www.mheducation.com/highered/product/fortran-scientists-engineers-chapman/M9780073385891.html&quot; rel=&quot;noreferrer&quot;&gt;Fortran for Scientists and Engineers&lt;/a&gt; series by Chapman or &lt;a href=&quot;https://www.cambridge.org/core/books/modern-fortran-in-practice/BC5BD23B2E478B4D457C5D6265BA9363&quot; rel=&quot;noreferrer&quot;&gt;Modern Fortran in Practice&lt;/a&gt; by Markus.&lt;/p&gt;&#xA;&lt;p&gt;There are several other books that I did not have in my hand. &lt;a href=&quot;https://www.cambridge.org/de/academic/subjects/computer-science/scientific-computing-scientific-software/modern-fortran-style-and-usage?format=PB&quot; rel=&quot;noreferrer&quot;&gt;Modern Fortran: Style and Usage&lt;/a&gt; by Norman and Spector is for more advanced programmers who want to use good style but know the basic language.&lt;/p&gt;&#xA;&lt;p&gt;You can get a lot of help at Stack Overflow in the Fortran tag &lt;a href=&quot;https://stackoverflow.com/questions/tagged/fortran&quot;&gt;https://stackoverflow.com/questions/tagged/fortran&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;When it comes to online tutorials, be aware that there are many obsolete ones. &lt;a href=&quot;https://www.fortran90.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.fortran90.org/&lt;/a&gt; is not that old, even if missing more advanced modern stuff, and the author Ondřej Čertík is active in the standard committee developing future Fortran standards.&lt;/p&gt;&#xA;&lt;p&gt;The community dealing with modern Fortran, developing a community software ecosystem, libraries and so on meets at &lt;a href=&quot;https://fortran-lang.discourse.group/&quot; rel=&quot;noreferrer&quot;&gt;https://fortran-lang.discourse.group/&lt;/a&gt; and will be happy to discuss any interesting Fortran topic. The usenet channel &lt;code&gt;comp.lang.fortran&lt;/code&gt; can also be used for discussion with experts and contains a lot of useful information in its history.&lt;/p&gt;&#xA;&lt;p&gt;An interesting option to try Fortran is the &lt;a href=&quot;https://lfortran.org/&quot; rel=&quot;noreferrer&quot;&gt;https://lfortran.org/&lt;/a&gt;. A compiler that is still in development, but enables you to try Fortran interactively in notebooks you might know from Python or Julia (Jupyter).&lt;/p&gt;&#xA;" OwnerUserId="3473" LastEditorUserId="7" LastEditDate="2021-06-27T21:24:19.613" LastActivityDate="2021-06-27T21:24:19.613" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6255" PostTypeId="2" ParentId="1541" CreationDate="2021-06-27T16:55:13.140" Score="7" Body="&lt;p&gt;I disagree with the statement by Tyberius that: &amp;quot;Bond order isn't terribly useful to a computationalist directly; however, it can be invaluable for translating Quantum Mechanical results into a framework thats readily understood by experimentalists.&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Bond order quantifies the number of electrons that are shared (technically, 'dressed exchanged') between two atoms in a material. Bond order is the quantification of the number of bonds formed between two atoms in material. It's not possible to understand the chemistry of a material without understanding how many chemical bonds are involved.  For example, you can't understand the chemistry of an oxygen molecule if you think it has a single bond instead of a double bond. Similarly, you can't understand the chemistry of acetylene if you think it has a double bond instead of a triple bond between the carbon atoms.&lt;/p&gt;&#xA;" OwnerUserId="1342" LastEditorUserId="5" LastEditDate="2021-06-27T18:20:23.087" LastActivityDate="2021-06-27T18:20:23.087" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6256" PostTypeId="2" ParentId="6252" CreationDate="2021-06-27T17:59:44.710" Score="14" Body="&lt;p&gt;The answers provided by others are excellent and rather comprehensive. I would only introduce a few other resources that could help you down the road to find answers to problems more efficiently. Several Fortran communities can be extremely helpful in learning optimization and performance tips or simply to seek help from experts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://community.intel.com/t5/Intel-Fortran-Compiler/bd-p/fortran-compiler&quot; rel=&quot;noreferrer&quot;&gt;The Intel Fortran forum&lt;/a&gt; has over 130,000 Fortran-related questions and posts, as far I as remember from a few years ago that I checked. There are also many industries and academia experts, as well as Fortran Standard Committee members there ready to take challenging questions and to guide and educate people (I have no connection to the Intel HPC team, just a user).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://forums.developer.nvidia.com/c/accelerated-computing/hpc-compilers/nvc-nvc-and-nvfortran/313&quot; rel=&quot;noreferrer&quot;&gt;The NVIDIA Fortran forum&lt;/a&gt; is another place to seek help, although NVIDIA is more focused on CUDA and GPU-enabled Fortran.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.reddit.com/r/fortran/&quot; rel=&quot;noreferrer&quot;&gt;The Reddit Fortran community&lt;/a&gt; has close to 6,000 Fortran programmers and enthusiasts already who can help with a diverse range of Fortran-related questions or direct you to relevant people or communities for further help.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are likely many more resources that I am simply missing in the above list. There are also online Fortran compilers like the following that can aid rapid limited testing of ideas:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tutorialspoint.com/compile_fortran_online.php&quot; rel=&quot;noreferrer&quot;&gt;tutorialspoint&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://rextester.com/l/fortran_online_compiler&quot; rel=&quot;noreferrer&quot;&gt;rextester&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.onlinegdb.com/&quot; rel=&quot;noreferrer&quot;&gt;onlinegdb&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.jdoodle.com/execute-fortran-online/&quot; rel=&quot;noreferrer&quot;&gt;jdoodle&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://godbolt.org/&quot; rel=&quot;noreferrer&quot;&gt;godbolt&lt;/a&gt; (for inspecting the generated assembly code)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;and Fortran Jupyter bindings for serial and parallel Fortran programming like &lt;a href=&quot;https://github.com/sourceryinstitute/jupyter-CAF-kernel#quick-start&quot; rel=&quot;noreferrer&quot;&gt;OpenCoarrays Jupyter Binder&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3850" LastEditorUserId="3850" LastEditDate="2021-06-27T21:15:48.437" LastActivityDate="2021-06-27T21:15:48.437" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6257" PostTypeId="2" ParentId="6252" CreationDate="2021-06-27T19:15:40.147" Score="11" Body="&lt;p&gt;Extending the answer by Nike Dattani separately rather than an addition in the text:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(2) Practicing, bis:&lt;/strong&gt; After gaining &lt;em&gt;some&lt;/em&gt; familiarity with the language, join a &amp;quot;drill site&amp;quot; like &lt;a href=&quot;https://www.codewars.com/&quot; rel=&quot;noreferrer&quot;&gt;codewars.com&lt;/a&gt; where you may train yourself (dojo-like) according to difficulty, or subject.  In addition to &amp;quot;you passed the test&amp;quot;, there is a community-based rating for solutions by others to the same problem (and if you know an other language than Fortran, you may tackle the problem again there).&lt;/p&gt;&#xA;&lt;p&gt;Open an account on a platform like &lt;a href=&quot;https://github.com/&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;.  Aside from learning version control, you may draw inspiration and spur collaboration from projects you identified by a search with &lt;code&gt;Fortran&lt;/code&gt; as a keyword.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(3) user groups / conferences:&lt;/strong&gt;  Get in touch with others already using the language.  In the best case, this will be an exchange of mutual benefit.  You might like the idea to have a sparring partner, especially if you are not sure if a concept was understood by you.  It may show you applications of Fortran you did not anticipate yet.  An example was the eventually virtual &lt;a href=&quot;https://www.hpc-ch.org/fortrancon-2020/&quot; rel=&quot;noreferrer&quot;&gt;FortanCon2020&lt;/a&gt;, with video &lt;a href=&quot;https://www.youtube.com/playlist?list=PLeKbr7eYHjt77h90hDVC-vGzrWmvDhCAf&quot; rel=&quot;noreferrer&quot;&gt;recordings available&lt;/a&gt;, yet the monthly video calls on fortran-lang.org (e.g., &lt;a href=&quot;https://www.youtube.com/watch?v=D107yFcuZoE&quot; rel=&quot;noreferrer&quot;&gt;April 2021&lt;/a&gt;, code-curation of rocket programs) equally may contain such insights.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-06-27T19:15:40.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6258" PostTypeId="2" ParentId="6209" CreationDate="2021-06-27T22:46:26.517" Score="5" Body="&lt;p&gt;My suggestion is that you first get an SCF calculation to converge for this structure before you try relaxing, especially if you aren't sure what you're going to get. Then you can proceed to converging the numerical settings like the cutoff energies for your properties of interest.&lt;/p&gt;&#xA;&lt;p&gt;I was able to get an SCF calculation to converge using your input file by switching the &lt;code&gt;occupations = &amp;quot;smearing&amp;quot;&lt;/code&gt; instead of &lt;code&gt;&amp;quot;fixed&amp;quot;&lt;/code&gt;. It seems like this may have been what you intended based on your choices for &lt;code&gt;&amp;quot;smearing&amp;quot;&lt;/code&gt; and &lt;code&gt;&amp;quot;degauss&amp;quot;&lt;/code&gt;, which seem to be ignored if you have &lt;code&gt;occupations = &amp;quot;fixed&amp;quot;&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-06-27T22:46:26.517" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6259" PostTypeId="2" ParentId="6252" CreationDate="2021-06-28T08:29:09.270" Score="9" Body="&lt;p&gt;I have not had the pleasure of programming Fortran, but have learned and used many other languages over decades, both privately and commercially.&lt;/p&gt;&#xA;&lt;p&gt;My preferred way of diving into a new language may be a bit old-fashioned. I normally stay &lt;em&gt;very much&lt;/em&gt; clear of &amp;quot;tutorials&amp;quot; and the like. First thing I do is I grab the official reference documentation - or, if you are lucky, a more informal long-form text (in the old days, a book; but today, plenty of languages have this kind of description as well, next to a more dry reference) - but only if it comes from the same source as the language itself, whatever that may be.&lt;/p&gt;&#xA;&lt;p&gt;For example, to learn Ruby, I first read a seminal book on it (&lt;a href=&quot;http://ruby-doc.com/docs/ProgrammingRuby/&quot; rel=&quot;noreferrer&quot;&gt;Programming Ruby&lt;/a&gt;), then I actually read quite a few of the dry reference pages from top to bottom (e.g. &lt;a href=&quot;https://ruby-doc.org/core-3.0.1/Array.html&quot; rel=&quot;noreferrer&quot;&gt;Array&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;For C, I did (back in the day) indeed buy &lt;a href=&quot;http://hikage.freeshell.org/books/theCprogrammingLanguage.pdf&quot; rel=&quot;noreferrer&quot;&gt;The C Programming Language&lt;/a&gt; and read it completely (obviously speed-reading/glossing over some bits).&lt;/p&gt;&#xA;&lt;p&gt;For Fortran, start at &lt;a href=&quot;https://fortran-lang.org/learn/&quot; rel=&quot;noreferrer&quot;&gt;fortran-lang.org&lt;/a&gt; and pick those documentations they suggest for you; maybe do one of the quick tutorials they link, but take everything written in a tutorial with a grain of salt. Not because it's necessarily wrong, but because they are by nature very much condensed, and by taking them as gospel might hurt you very much in the long term.&lt;/p&gt;&#xA;&lt;p&gt;As soon as you have a general feel of the language (which you, for your current background, probably already have), get the most technical, most complete documentation you can find and stomach, and go through it front to back. You do not need to read, much less understand every single word, but you should know all the major &lt;em&gt;concepts&lt;/em&gt; - at least know that they exist, and where you have to look when you need actual hard facts during development.&lt;/p&gt;&#xA;" OwnerUserId="3854" LastEditorUserId="269" LastEditDate="2021-06-28T12:35:19.003" LastActivityDate="2021-06-28T12:35:19.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6260" PostTypeId="1" AcceptedAnswerId="6264" CreationDate="2021-06-28T13:45:03.100" Score="8" ViewCount="317" Body="&lt;p&gt;Consider the following atoms object.&#xA;&lt;code&gt;atoms_al = ase.build.fcc111('Al', size=(1,2,2), vacuum=16.0, orthogonal=True)&lt;/code&gt;&#xA;To set the periodic boundary conditions along the x-direction I use:&#xA;&lt;code&gt;atoms_al.pbc=np.array([1,0,0],dtype=bool)&lt;/code&gt;&#xA;I am trying to understand what exactly changes, mathematically, in the atoms_al object once the periodic boundary conditions are applied? Will some attributes of the atoms_al object change once the pbc are applied?&#xA;If so, what can they be for example?&lt;/p&gt;&#xA;&lt;p&gt;I have looked up the source code to find what atoms.pbc does to the atoms object but I did not have any luck. If you could please point me to where I can see the implementation, that would be very helpful.&lt;/p&gt;&#xA;" OwnerUserId="2196" LastActivityDate="2021-07-01T17:54:37.067" Title="Periodic Boundary Conditions in Atomistic Simulation Environment" Tags="|atomic-simulation-environment|periodic-boundary-conditions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6261" PostTypeId="2" ParentId="6252" CreationDate="2021-06-28T14:49:46.987" Score="14" Body="&lt;p&gt;I've done that professionally.&lt;/p&gt;&#xA;&lt;p&gt;In the early '90's, I worked at IBM and spent some time porting FORTRAN &amp;quot;codes&amp;quot; to work on the new RISC SYSTEM / 6000.&lt;/p&gt;&#xA;&lt;p&gt;I found that FORTRAN was such a simple language that it could be worked with without &amp;quot;knowing&amp;quot; it, per se.  I obtained a FORTRAN 77 text book, which was rather small and slim, about the same volume as a paperback novel though the pages were larger and the the number of pages smaller.  With the text book, I easily looked up the meaning of any non-obvious construct and precise details like the exact order of precedence, when needed.&lt;/p&gt;&#xA;&lt;p&gt;The real problem with these &amp;quot;codes&amp;quot; isn't the nuances of the FORTRAN language, but the code itself.  They are typically written by people who are not software engineers, and cobbled together over time.  Worse, are complex programs that go to great lengths to exceed the natural bounds of the language:  I recall MODFLOW implementing its own memory management in order to do dynamic data structures as subscripts in static arrays; and more generally the lack of structures, so related data is spread out over separate named variables or parallel arrays.  Of course, we only had current source code, &lt;em&gt;zero&lt;/em&gt; design documents or anything explaining the code organization.&lt;/p&gt;&#xA;&lt;p&gt;Point is, your &amp;quot;thousands of lines&amp;quot; might not be readable even when you are fluent in exactly what the FORTRAN statements mean.  Now, with the World Wide Web, you can easily find some reference material for the language itself, and since you already know how to program it will be no problem understanding it all.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&amp;quot;Modern&amp;quot; Fortran is a more complex language, but I expect it's just a matter of learning the specific syntax as the concepts are no different than what is found in other languages; e.g. structures (use &lt;code&gt;%&lt;/code&gt; instead of &lt;code&gt;.&lt;/code&gt;), modules (like Modula-2), generics (like Ada), block-structured statements (any modern procedural language), etc.&lt;/p&gt;&#xA;" OwnerUserId="3858" LastEditorUserId="3858" LastEditDate="2021-06-28T16:05:29.047" LastActivityDate="2021-06-28T16:05:29.047" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6262" PostTypeId="2" ParentId="4322" CreationDate="2021-06-28T14:50:53.623" Score="7" Body="&lt;p&gt;As I had previously written in the comments, the warning given by gromacs seems to indicate that the GROMOS force fields should not be used due to wrong parameterization:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  The GROMOS force fields have been parametrized with a physically&#xA;  incorrect multiple-time-stepping scheme for a twin-range cut-off. When&#xA;  used with a single-range cut-off (or a correct Trotter&#xA;  multiple-time-stepping scheme), physical properties, such as the density,&#xA;  might differ from the intended values. Since there are researchers&#xA;  actively working on validating GROMOS with modern integrators we have not&#xA;  yet removed the GROMOS force fields, but you should be aware of these&#xA;  issues and check if molecules in your system are affected before&#xA;  proceeding. Further information is available at&#xA;  https://redmine.gromacs.org/issues/2884 , and a longer explanation of our&#xA;  decision to remove physically incorrect algorithms can be found at&#xA;  https://doi.org/10.26434/chemrxiv.11474583.v1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(copied from the question)&lt;/p&gt;&#xA;&lt;p&gt;The redmine link returns a 404 error, but the chemrxiv paper is accessible. From a quick read of the paper, it seems that the GROMACS code inherited its algorithms from the GROMOS87  code. The old algorithm used a &amp;quot;twin range cut-off&amp;quot; scheme, where the short-range forces were calculated in every step, but the long range forces were calculated every N number of steps (N is a certain integer number, probably set by the software). The long-range forces were added to the short-range values every step to approximate a longer cut-off value. This algorithm was written at a time when computational power was not cheap so not calculating long range forces in every step saved a lot of cpu time. This algorithm has been found to cause artifacts especially for lipid bilayers with zwitterionic molecules. Another problem with the algorithm was that it was not time-reversible.&lt;sup&gt;[1]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;A better algorithm is the Trotter multiple time stepping scheme which was adopted by GROMACS since version 4.5 (2013). However, the old GROMOS force fields were parameterized using the legacy GROMOS algorithm, which means that with the new Trotter algorithm, the GROMOS parameters would give different (and possibly wrong) results. There also seems to be some other issues with the constraints (SHAKE) for the GROMOS parameters.&lt;sup&gt;[1]&lt;/sup&gt; This is why from version &lt;a href=&quot;https://manual.gromacs.org/documentation/2019.2/release-notes/2019/2019.2.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;2019.2&lt;/a&gt;, GROMACS (the &lt;code&gt;grompp&lt;/code&gt; module) prints out a warning whenver the GROMOS force-fields are used, and stops execution.&lt;/p&gt;&#xA;&lt;p&gt;The only utility of the warning is to ask the user to check whether the system they are using gives correct results with the GROMOS parameters when using the newer algorithm. So, if you get the error, you should check your system before proceeding. Once you are happy with the choice of force-field and system, then just add the argument &lt;code&gt;-maxwarn 1&lt;/code&gt; to the end of the &lt;code&gt;gmx grompp&lt;/code&gt; command that you are attempting to run. The command will now run as normal, and ignore the warning. It's as simple as that.&lt;/p&gt;&#xA;&lt;p&gt;In 2020, Diem and Oostenbrink studied the differences in solvation energy of various amino acid side chains in water and the physical properties of six pure liquids, when using the twin-range algorithm vs the Trotter algorithm. They found that the error in using the old algorithm is mostly minor and within the range of uncertainty in the experimental data used to validate the results. Another important finding was that the error is smaller when using group-based cut-off schemes than for an atom-based cut-off.&lt;sup&gt;[2]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;B. Hess, D. van der Spoel, M. J. Abraham, E. Lindahl, &amp;quot;On The Importance of Accurate Algorithms for Reliable Molecular Dynamics Simulations&amp;quot;, &lt;a href=&quot;https://doi.org/10.26434/chemrxiv.11474583.v1&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.26434/chemrxiv.11474583.v1&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;M. Diem, C. Oostenbrink, &amp;quot;The Effect of Using a Twin-Range Cutoff Scheme for Nonbonded Interactions: Implications for Force-Field Parametrization?&amp;quot;, &lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt;, 2020, &lt;strong&gt;16&lt;/strong&gt;, 10, 5985–5990, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c00509&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jctc.0c00509&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-06-30T04:00:55.643" LastActivityDate="2021-06-30T04:00:55.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6263" PostTypeId="1" AcceptedAnswerId="6265" CreationDate="2021-06-28T14:53:15.837" Score="5" ViewCount="83" Body="&lt;p&gt;(&lt;a href=&quot;https://physics.stackexchange.com/q/647756/134583&quot;&gt;Crossposted on physics SE&lt;/a&gt;)&#xA;I am reading Introduction to Polymer Physics by Doi, and in his proof for the probability distribution for ideal polymers of length &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; and end-to-end vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;, he does the following:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;P(\mathbf{R}-\mathbf{b}_i,N-1)=P(\mathbf{R},N)-\frac{\partial P}{\partial N}-\frac{\partial P}{\partial R_{\alpha}}b_{i\alpha}+\frac{1}{2}\cdot \frac{\partial ^2 P}{\partial R_{\alpha}\partial R_{\beta}}b_{i\alpha}b_{i\beta}\label{1}\tag{1}&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$b_{i\alpha}$&lt;/span&gt; is the component of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}_i$&lt;/span&gt; in the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; direction, &lt;span class=&quot;math-container&quot;&gt;$R_{\alpha}$&lt;/span&gt; is a component of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;,for the lattice the polymer lies in. We are using the Einstein convention for summation in the above equation.&lt;/p&gt;&#xA;&lt;p&gt;He makes the statement,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{z}\sum _{i=1}^z b_{i\alpha}b_{i\beta} = \frac{\delta _{\alpha\beta}b^2}{3}\label{2}\tag{2}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; is the coordination number, &lt;span class=&quot;math-container&quot;&gt;$\delta _{ij}$&lt;/span&gt; is the Kronecker delta, &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; is the length of the lattice edge, so &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{b}_i| = b$&lt;/span&gt;. I don't understand where this comes from.&lt;/p&gt;&#xA;&lt;p&gt;What is the proof of this statement?&lt;/p&gt;&#xA;&lt;p&gt;Since I have a problem with the Taylor expansion, I am going to write down what I am not understanding.&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;P(\mathbf{R}-\mathbf{b}) = P([R_x-b_x, R_y-b_y]^T)\approx P([R_x,R_y]^T)-\frac{\partial P}{\partial R_x} b_x-\frac{\partial P}{\partial R_y}b_y+\frac{1}{2}\cdot \left(\frac{\partial ^2 P}{\partial R_x^2}b_x^2+\frac{\partial ^2 P}{\partial R_y^2}b_y^2 + 2\frac{\partial ^2 P}{\partial R_xR_y}b_xb_y \right)&#xA;\end{align}&lt;/span&gt;&#xA;This was derived using the standard higher-dimensional Taylor expansion formula for &lt;span class=&quot;math-container&quot;&gt;$f(\mathbf{x})$&lt;/span&gt; where&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;f(\mathbf{x}) = f(\mathbf{a}) + Df(\mathbf{x})(\mathbf{x}-\mathbf{a})^T+\frac{1}{2}(\mathbf{x}-\mathbf{a}) Hf(\mathbf{x})(\mathbf{x}-\mathbf{a})^T&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is the Hessian of &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2021-06-29T15:43:51.527" LastActivityDate="2021-06-29T15:43:51.527" Title="Derivation of probability density of isolated polymers" Tags="|mathematical-modeling|statistical-thermodynamics|polymers|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6264" PostTypeId="2" ParentId="6260" CreationDate="2021-06-28T18:08:58.117" Score="8" Body="&lt;p&gt;The PBC attribute in ASE is used for:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;finding nearest neighbours&lt;/li&gt;&#xA;&lt;li&gt;input for calculators that may use that information (dftd3, dmol, etc.)&lt;/li&gt;&#xA;&lt;li&gt;creation of surfaces&lt;/li&gt;&#xA;&lt;li&gt;finding the Bravais lattice&lt;/li&gt;&#xA;&lt;li&gt;certain constraints&lt;/li&gt;&#xA;&lt;li&gt;certain optimization strategies&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Nothing is &lt;em&gt;per se&lt;/em&gt; changed in the object. But much of the functionality of ASE depends on that attribute.&lt;/p&gt;&#xA;&lt;p&gt;If you are interested then you could grep for the pbc uses &lt;code&gt;grep '\.pbc' **/*.py&lt;/code&gt;&#xA;which will list where it is used.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="7" LastEditDate="2021-07-01T17:54:37.067" LastActivityDate="2021-07-01T17:54:37.067" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6265" PostTypeId="2" ParentId="6263" CreationDate="2021-06-28T20:14:52.657" Score="5" Body="&lt;p&gt;For context to future readers, Doi starts with a model of an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; unit polymer formed by a random walk along a uniform grid of lattice length &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xaQvQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xaQvQ.png&quot; alt=&quot;2D Random walk on integer grid to describe polymer formation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It seems to be implicitly assumed in the described derivation that the lattice used is &lt;span class=&quot;math-container&quot;&gt;$b\mathbb{Z}^3$&lt;/span&gt;, that is the uniform 3D grid. Note there are other types of lattices for which Eq.&lt;span class=&quot;math-container&quot;&gt;$\,(\ref{2})$&lt;/span&gt; is not true. Also note the factor of &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{3}$&lt;/span&gt; comes from the dimension, so this expression is also not true for the 2D grid they show as an example.&lt;/p&gt;&#xA;&lt;p&gt;For the 3D uniform grid, the result arises fairly simply. We have &lt;span class=&quot;math-container&quot;&gt;$z=6$&lt;/span&gt;&#xA;corresponding to the vectors &lt;span class=&quot;math-container&quot;&gt;$(\pm \mathbf{b}_1,\pm \mathbf{b}_2,\pm \mathbf{b}_3)$&lt;/span&gt;. For simplicity, we can say these just align with the usual Cartesian axes &lt;span class=&quot;math-container&quot;&gt;$(\pm x,\pm y,\pm z)$&lt;/span&gt;, since Eq.&lt;span class=&quot;math-container&quot;&gt;$\,(\ref{2})$&lt;/span&gt; should not be dependent on the orientation of the grid. Clearly if &lt;span class=&quot;math-container&quot;&gt;$\alpha\neq\beta$&lt;/span&gt;, the sum equals zero, as all of the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}_i$&lt;/span&gt; vectors only point along one Cartesian direction. For &lt;span class=&quot;math-container&quot;&gt;$\alpha=\beta$&lt;/span&gt;, only &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; of the &lt;span class=&quot;math-container&quot;&gt;$6$&lt;/span&gt; vectors (i.e. &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{3}$&lt;/span&gt;) will have this component be nonzero and for these vectors the product is just &lt;span class=&quot;math-container&quot;&gt;$b^2$&lt;/span&gt;. So for any Cartesian, the sum will result in &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{3}zb^2$&lt;/span&gt;, which when divided by &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; gives the expression from Eq.&lt;span class=&quot;math-container&quot;&gt;$\,(\ref{2})$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-29T15:33:23.157" LastActivityDate="2021-06-29T15:33:23.157" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6266" PostTypeId="1" CreationDate="2021-06-28T22:19:09.613" Score="10" ViewCount="110" Body="&lt;p&gt;I'm looking for a fairly large (&amp;gt;100k) dataset of chemical compounds (and materials) that has conductivities. I've looked at PubMed, but couldn't find conductivities.&lt;/p&gt;&#xA;&lt;p&gt;I would ideally like to avoid APIs as they have limits, and scraping is too slow. I would like to just download a file containing a compound and it's physical/chemical properties (ie. like a JSON or something).&lt;/p&gt;&#xA;&lt;p&gt;I've looked through The Materials Project's datasets and they don't have the properties I listed above.&lt;/p&gt;&#xA;" OwnerUserId="3860" LastEditorUserId="5" LastEditDate="2021-12-15T19:41:30.783" LastActivityDate="2021-12-15T19:41:30.783" Title="Large dataset with conductivities of materials and chemical compounds?" Tags="|reference-request|physical-properties-of-materials|databases|materials-project|" AnswerCount="0" CommentCount="11" ClosedDate="2023-02-07T03:08:37.637" ContentLicense="CC BY-SA 4.0" />
  <row Id="6267" PostTypeId="2" ParentId="6163" CreationDate="2021-06-28T22:37:53.603" Score="5" Body="&lt;p&gt;PySCF and Psi4 both implement analytical geometric Hessians for Hartree-Fock calculations. The computation of the geometric Hessian indeed requires solving the coupled perturbed Hartree-Fock equations: while one can evaluate the force acting on the nuclei just with the SCF wave function and the integral derivatives, the second derivative also contains a response term for the relaxation of the orbitals upon the perturbation.&lt;/p&gt;&#xA;&lt;p&gt;You also stated interest in getting the derivative integrals. These are naturally also available in both PySCF and Psi4; the former computes integrals with the libcint library by Qiming Sun (original author of PySCF), the latter uses the libint library by Ed Valeev.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-06-28T22:37:53.603" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6268" PostTypeId="2" ParentId="4953" CreationDate="2021-06-28T22:44:18.437" Score="5" Body="&lt;h1&gt;LEVEL&lt;/h1&gt;&#xA;&lt;p&gt;For a &lt;em&gt;diatomic&lt;/em&gt; molecule, LEVEL can calculate all Franck-Condon factors (FKF):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\langle \psi_{v,J} | \psi_{v^\prime,J^\prime}\rangle|^2\tag{1},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;between rovibrational levels &lt;span class=&quot;math-container&quot;&gt;$(v,J)$&lt;/span&gt; of one potential energy curve, and &lt;span class=&quot;math-container&quot;&gt;$(v^\prime,J^\prime)$&lt;/span&gt; of another potential energy curve (or the same potential energy curve).&lt;/p&gt;&#xA;&lt;p&gt;To calculate FKF, the variable &lt;code&gt;LXPCT&lt;/code&gt; must be larger than 2 or smaller than -2, and the following can be treated as dummy variables &lt;code&gt;MORDR&lt;/code&gt;, &lt;code&gt;IRFN&lt;/code&gt; and &lt;code&gt;DREF&lt;/code&gt;. If you set &lt;code&gt;MORDR&lt;/code&gt; to be negative, you may experience faster computations.&lt;/p&gt;&#xA;&lt;p&gt;This program was a project that Bob Le Roy worked on since the 1960s, and had contributions from several others over the decades, including myself. The latest version available online was from 2016, and since &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6177/5&quot;&gt;someone else needed a program like this for something else&lt;/a&gt;, I pushed the most recent version I could find into Github &lt;a href=&quot;https://github.com/HPQC-LABS/LEVEL&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; (let me know if you have any trouble compiling it).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free and open-source.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Extremely accurate&lt;/em&gt;, and &lt;em&gt;extremely fast&lt;/em&gt; (orders of magnitude faster and more black-box than other radial Schroedinger solvers I know some others have used).&lt;/li&gt;&#xA;&lt;li&gt;Widely used and with a rich history spanning several decades.&lt;/li&gt;&#xA;&lt;li&gt;There's not a lot of other programs available with this type of functionality.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Only works for diatomics.&lt;/li&gt;&#xA;&lt;li&gt;You do need to get your accurate potential energy curve(s) from somewhere else (for example, you mentioned NWChem).&lt;/li&gt;&#xA;&lt;li&gt;It's an &amp;quot;old school&amp;quot; program mainly with FORTRAN 77 style input and output, though it was probably originally written in FORTRAN 66, and we did modernize it over the years to use a lot of FORTRAN 90 (and beyond!) syntax.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-29T03:04:07.857" LastActivityDate="2021-06-29T03:04:07.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6269" PostTypeId="1" CreationDate="2021-06-29T00:35:35.717" Score="8" ViewCount="83" Body="&lt;p&gt;In the &lt;a href=&quot;https://github.com/mompiou/pycotem&quot; rel=&quot;nofollow noreferrer&quot;&gt;pycotem code&lt;/a&gt;, this error comes up when using the Diffraction GUI.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pycotem\diffraction_main_.py&amp;quot;, line 186, in angle_check&#xA;inc = ui.ListBox_d_2.currentItem().text().split(',')&#xA;AttributeError: 'NoneType' object has no attribute 'text'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Has anyone tried to resolve this?&lt;/p&gt;&#xA;" OwnerUserId="3679" LastEditorUserId="7" LastEditDate="2021-06-29T17:29:16.507" LastActivityDate="2021-11-29T19:16:11.393" Title="Error when using pycotem to index an electron diffraction pattern?" Tags="|python|software-assistance|diffraction|graphical-user-interface|pycotem|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6270" PostTypeId="5" CreationDate="2021-06-29T02:56:54.983" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/mompiou/pycotem&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/mompiou/pycotem&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-29T02:56:54.983" LastActivityDate="2021-06-29T02:56:54.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6271" PostTypeId="4" CreationDate="2021-06-29T02:56:54.983" Score="0" Body="Questions about or related to the pycotem software, for working with crystal orientations in transmission electron microscopy." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-29T02:56:54.983" LastActivityDate="2021-06-29T02:56:54.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6272" PostTypeId="2" ParentId="6252" CreationDate="2021-06-29T08:10:04.007" Score="10" Body="&lt;p&gt;If you already know Python, perhaps you could try to convert Python code to Fortran code.  That is probably the fastest way to get to know the language.  Unless you go from one paradigm to another programming principals are mostly the same and it is syntax that differentiates one language from another.  If you go through books and tutorials then you will probably be &amp;quot;reinventing the wheel&amp;quot; to some extent by going over familiar ground.&lt;/p&gt;&#xA;" OwnerUserId="3863" LastActivityDate="2021-06-29T08:10:04.007" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6273" PostTypeId="2" ParentId="5034" CreationDate="2021-06-29T08:40:00.620" Score="7" Body="&lt;p&gt;The paradox discovered by @HansWurst comes by the assumption that it is possible to treat both minima on the 1D PES separately and define a separate set of normal coordinates for them. 3N normal coordinates are functions of 3N Cartesian coordinates of the bodies in our system. It turns out that for a double-well potential in 1D, which you describe here, the normal-mode approximation is a very bad one. We only have one dynamical dimension, hence we can only define one normal coordinate for this system. Splitting into two independent coordinates is the 'mistake' here. To treat this problem we can define a variational basis composed of sums of 1D Harmonic Oscillator basis functions centred at the two local minima. Such a basis is likely to serve well.&lt;/p&gt;&#xA;&lt;p&gt;In general, when more dimensions are involved it is rather customary to perform rotations on full sets of normal coordinates (so called &lt;em&gt;Duschinsky&lt;/em&gt; rotation), such that, for instance, a set of normal coordinates for the electronic ground state can be expressed with normal coordinates of a displaced and deformed electronically excited state.&lt;/p&gt;&#xA;" OwnerUserId="99" LastActivityDate="2021-06-29T08:40:00.620" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6274" PostTypeId="1" AcceptedAnswerId="6276" CreationDate="2021-06-29T11:50:21.980" Score="10" ViewCount="571" Body="&lt;p&gt;I have read the following paper, &amp;quot;Bypassing the Kohn-Sham equations with machine learning&amp;quot;, published from Nature Communications in 2017.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41467-017-00839-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/s41467-017-00839-3&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Hohenberg-Kohn theorem states that there is one-to-one correspondence between the external potential &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt; and the electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;. I believe that the form of &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt; is the Coulomb as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{ext}(r) = \sum_{i=1}^M \frac{Z_i}{||r-R_i||}$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the electron position, &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is the atomic position, and &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; is the nuclear charge. Instead of the Coulomb, however, this paper uses the &lt;strong&gt;Gaussian external potential&lt;/strong&gt; as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{ext}(r) = \sum_{i=1}^M Z_i e^{-||r-R_i||^2}$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;because &amp;quot;The external (Coulomb) potential diverges for 3D molecules and is, therefore, not a good feature to measure the distance in machine learning (ML). Instead, we use an artificial Gaussian potential...&amp;quot;, and here I have a question about the selection of &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the Hohenberg-Kohn map between the input &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt; and the output &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, &lt;strong&gt;can &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt; be anything form&lt;/strong&gt; such as the Gaussian, not the Coulomb? For example, the following figure shows the electron density values (calculated by Gaussian09 software) on the C=C bond in the benzene molecule, and the Coulomb potential has a very extreme form; in contrast, the Gaussian potential seems to be closer to the calculated density.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/r3Uup.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/r3Uup.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When considering the map from &lt;span class=&quot;math-container&quot;&gt;$V_{ext}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, the Gaussian seems to be more reasonable in a molecule (also may be reasonable for other molecules) than the Coulomb from a practical point of view. Nevertheless, &lt;strong&gt;is the actual external potential Coulomb?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-06-29T20:10:40.140" LastActivityDate="2021-06-29T20:10:40.140" Title="External potential in the Hohenberg-Kohn map" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6275" PostTypeId="2" ParentId="6205" CreationDate="2021-06-29T13:15:58.770" Score="6" Body="&lt;p&gt;Following @NikeDattani's advice, now I rewrite my comments into an answer.&lt;/p&gt;&#xA;&lt;p&gt;First of all, you should try to reproduce the geometry given in the paper. You mentioned in the comment that you got an adsorption energy of -1.104 eV at the hollow site, which is already quite close to the literature value of -1.19 eV. Does the adsorption geometry at the hollow site match the literature perfectly (not only qualitatively but also quantitatively, if you can assess their optimized atomic coordinates)? If the geometry still differs a little bit, then this may be the reason for the remaining discrepancy, for example whether you allowed your lattice constants to relax, whether you used the same slab width with the literature, etc.&lt;/p&gt;&#xA;&lt;p&gt;As for whether you should use a single Li atom or bulk Li in calculating the adsorption energy, the answer is that unless otherwise specified, you should always use the energy of the single atom. That's how adsorption energy is defined.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-06-29T13:15:58.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6276" PostTypeId="2" ParentId="6274" CreationDate="2021-06-29T14:29:05.347" Score="9" Body="&lt;p&gt;The actual external potential of molecules is indeed a sum of the Coulomb potentials of the nuclei (except when one uses a pseudopotential, where the potential will be Gaussian-like near the nuclei; but pseudopotentials are approximations). The point is that, there is also a one-to-one correspondence between the sum of nuclear-centered Gaussians and the sum of nuclear-centered Coulomb potentials (you can easily verify this). Thus, the fact that there is a one-to-one correspondence between the external potential and the density (when the ground state is not degenerate), means that there is also a one-to-one correspondence between the artificial sum-of-Gaussian potential and the density.&lt;/p&gt;&#xA;&lt;p&gt;However, there are some potentially misleading points that I'd like to clarify:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;It seems that the ML algorithm proposed in the paper only used the fact that &lt;span class=&quot;math-container&quot;&gt;$v(r)$&lt;/span&gt; uniquely determines &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; (which is only true if the ground state is non-degenerate). This is a much weaker, in fact trivial, statement than the Hohenberg-Kohn theorem, which also states that &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; uniquely determines &lt;span class=&quot;math-container&quot;&gt;$v(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The Hohenberg-Kohn theorem does not only apply to nuclear Coulomb potentials, but also to non-nuclear and/or non-Coulomb potentials. For example, if you have a molecule in a possibly non-uniform external electric field, then one can reveal the exact distribution of the electric field simply by examining the ground state density of the molecule. Or if the sizes of the nuclei are taken into account, so that the nuclear potentials do not have a cusp. Or if we used pseudopotentials. Or if we lived in a weird universe where the nuclear Coulomb interaction is &lt;span class=&quot;math-container&quot;&gt;$V(r) = -Z \exp(-\alpha r)/r$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$V(r)=-Z/r$&lt;/span&gt;. This is what makes the Hohenberg-Kohn theorem a very deep result. In fact if we already know that the potential is the sum of the Coulomb potentials of a finite number of nuclei, we can find the potential simply by looking at the positions and strengths of the cusps of the density (owing to Kato's conditions), which would make the one-to-one correspondence between &lt;span class=&quot;math-container&quot;&gt;$v(r)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; a trivial result.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The similarity between the Gaussian potential and the density does not guarantee a better mapping. Besides, sufficiently near the nuclei, the Gaussian potential does not look like the density. If you draw your A and B points at the centers of the respective carbon atoms, and if you properly include the contributions of the core electrons, you will find very localized and very strong cusps in the density, but the Gaussian potential will be much more slow-varying and rather featureless.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;One can view the Gaussian potentials as yet another method to convert the nuclear coordinated into ML descriptors (besides the Coulomb matrix, rotationally symmetric functions, etc.). In this sense, this work represents simply a ML method that predicts the electronic density and energy from nuclear coordinates.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It's much harder to predict the energy than the density, at least when the required accuracy of the density is not very high. For example, you can get a not-too-bad density by simply superimposing the neutral atomic densities, which is already sufficient for some applications, e.g. solving XRD structures. What is difficult is to calculate the energy given the density. Traditional non-ML approaches typically given atomization energies that are in error of &amp;gt; 200 kcal/mol, which is useless for &lt;em&gt;any&lt;/em&gt; application. Thus, what should be really highlighted in this paper is the good energies.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-06-29T14:29:05.347" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6277" PostTypeId="1" CreationDate="2021-06-29T17:34:46.533" Score="5" ViewCount="266" Body="&lt;p&gt;My input file for the (221) &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; monolayer was created through Cif2QE (QEtoolkit):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation='relax',&#xA;  restart_mode = 'from_scratch',&#xA;  prefix       = 'MoS2', &#xA;  pseudo_dir='./',&#xA;  outdir       = './out', &#xA;  verbosity='high',&#xA;  tprnfor=.true., &#xA;  forc_conv_thr=1.0d-4,&#xA;  etot_conv_thr = 1d-6 &#xA;  nstep=50,&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0, &#xA;  nat= 12, &#xA;  ntyp= 2, &#xA;  input_dft = 'pbe' &#xA;  occupations = 'smearing', &#xA;  smearing = 'gauss', &#xA;  degauss = 1.0d-2,&#xA;  ecutwfc = 60, &#xA;  ecutrho = 240,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-6&#xA;  mixing_beta = 0.5d0&#xA;  diagonalization  ='cg'&#xA;/&#xA;&amp;amp;IONS&#xA;  ion_dynamics = 'bfgs',&#xA;/&#xA;ATOMIC_SPECIES&#xA;  Mo 95.94 Mo.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;  S 32.066 S.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;CELL_PARAMETERS (angstrom)&#xA;    6.2800000000  0.0000000000  0.0000000000&#xA;  -3.1400000000  5.4386395358  0.0000000000&#xA;   0.0000000000  0.0000000000 27.5300010000&#xA;ATOMIC_POSITIONS (crystal)&#xA;   S  0.3333330000  0.1666670000  0.1250000000&#xA;   S  0.8333330000  0.1666670000  0.1250000000&#xA;   S  0.3333330000  0.6666670000  0.1250000000&#xA;   S  0.8333330000  0.6666670000  0.1250000000&#xA;  Mo  0.1666670000  0.3333330000  0.2500000000&#xA;  Mo  0.6666670000  0.3333330000  0.2500000000&#xA;  Mo  0.1666670000  0.8333330000  0.2500000000&#xA;  Mo  0.6666670000  0.8333330000  0.2500000000&#xA;   S  0.3333330000  0.1666670000  0.3750000000&#xA;   S  0.8333330000  0.1666670000  0.3750000000&#xA;   S  0.3333330000  0.6666670000  0.3750000000&#xA;   S  0.8333330000  0.6666670000  0.3750000000&#xA;K_POINTS {automatic}&#xA;  4 4 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the output file, I got a warning:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;WARNING: bfgs curvature condition failed, but it get relaxed.&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why am I getting this warning message? Is there any other tag I have to add to my input file (supercell)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/NigilNithya/NigilNithya/blob/main/relax.out&quot; rel=&quot;nofollow noreferrer&quot;&gt;Output file&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="7" LastEditDate="2021-06-30T14:36:14.870" LastActivityDate="2021-06-30T14:36:14.870" Title="Cif2QE (QEtoolkit): Error when using this input file for (221) MoS2 monolayer" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="13" ClosedDate="2021-10-29T20:15:24.410" ContentLicense="CC BY-SA 4.0" />
  <row Id="6278" PostTypeId="1" AcceptedAnswerId="6279" CreationDate="2021-06-29T19:32:26.420" Score="9" ViewCount="1281" Body="&lt;p&gt;I would like to be able to parse a molecule into its functional groups, and, also, know the number of occurrences of each.&lt;/p&gt;&#xA;&lt;p&gt;A &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4736/181&quot;&gt;similar question&lt;/a&gt; was asked on matter modelling specifically for xyz files. I am going to assume at this point most large databases will have molecules either a SMILES or SMARTS tag, or, have a tag that can be converted into a SMILES or SMARTS.&lt;/p&gt;&#xA;&lt;p&gt;There is a &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acsomega.7b01464&quot; rel=&quot;noreferrer&quot;&gt;published&lt;/a&gt; python code for the Joback method which uses RDKit with &lt;a href=&quot;https://github.com/curieshicy/JRgui&quot; rel=&quot;noreferrer&quot;&gt;github repo&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Looking over the code, which frankly captures the spirit of what I want, there seems to be alot of hardcoding. Is it possible to simply query a program(command line driven) with a molecules SMILE ID and get all of its functionals back?&lt;/p&gt;&#xA;&lt;p&gt;I know you can ask rdkit if a molecule has a specific functional, but I don't really want that since I don't want to make a list of all possible functionals and then figure out how to count them in rdkit, as well as remove duplicates i.e, a parse for COOH would count as an carboxylic acid, but a separate parse for OH would return true for that same group, and a separate parse for =O would also return true, so I would have to correct for this. Also, I would want that to return as a carboxylic acid, not as an =O, OH and some kind of C. That affects a group contribution method in an undesired way.&lt;/p&gt;&#xA;&lt;p&gt;Finally, I need every atom to be accounted for.&lt;/p&gt;&#xA;&lt;p&gt;Python would be much preferred.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2021-06-29T20:54:39.523" LastActivityDate="2021-06-30T18:48:36.357" Title="Functional group detection for group contribution methods" Tags="|one-topic-per-answer|software-recommendations|python|databases|cheminformatics|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6279" PostTypeId="2" ParentId="6278" CreationDate="2021-06-29T20:46:24.660" Score="9" Body="&lt;h1&gt;ErtlFunctionalGroupsFinder&lt;/h1&gt;&#xA;&lt;p&gt;A Java library for automated functional group implemented with the &lt;a href=&quot;https://cdk.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemical Development Kit&lt;/a&gt; (CDK) program. It should run on Windows/Mac/Linux operating systems.&lt;/p&gt;&#xA;&lt;p&gt;It relies on the Ertl algorithm, which is also used by the RDKit for functional group detection. A key difference between the two implementations seems to be in their ability to account for the surrounding environment. For example, EFGF distinguishes a carboxyl group, an ester group and a formic acid ester group using pseudo SMILES strings, while RDKit would produce a single SMILES string for each of these.&lt;/p&gt;&#xA;&lt;p&gt;The implementation is very fast, allowing them to process 1.8 million molecules from the &lt;a href=&quot;https://www.ebi.ac.uk/chembl/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChEMBL database&lt;/a&gt; in 74s (50 million/hour) on a single core, with the option to parallelize if needed.&lt;/p&gt;&#xA;&lt;p&gt;A somewhat more detailed description of the code is available in [1] and the code itself can be viewed/downloaded from its &lt;a href=&quot;https://github.com/zielesny/ErtlFunctionalGroupsFinder&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub repo&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Fritsch, S., Neumann, S., Schaub, J. et al. ErtlFunctionalGroupsFinder: automated rule-based functional group detection with the Chemistry Development Kit (CDK). J Cheminform 11, 37 (2019). &lt;a href=&quot;https://doi.org/10.1186/s13321-019-0361-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1186/s13321-019-0361-8&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-06-30T18:48:36.357" LastActivityDate="2021-06-30T18:48:36.357" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6280" PostTypeId="5" CreationDate="2021-06-30T00:26:11.623" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-06-30T00:26:11.623" LastActivityDate="2021-06-30T00:26:11.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6281" PostTypeId="4" CreationDate="2021-06-30T00:26:11.623" Score="0" Body="Synonym for chemoinformatics. For questions about applying informatics techniques to study chemical systems.  " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-25T20:47:53.053" LastActivityDate="2021-12-25T20:47:53.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6282" PostTypeId="1" AcceptedAnswerId="6283" CreationDate="2021-06-30T15:22:40.200" Score="9" ViewCount="179" Body="&lt;p&gt;I am reading Introduction to Polymer Physics by Doi and I am having trouble understanding a derivation by him on the concentration fluctuations in polymer solutions. I have outlined his method and have mentioned where I am having trouble following it:&lt;/p&gt;&#xA;&lt;p&gt;Consider a mixture of two polymers A and B, having degrees of polymerization &lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N_B$&lt;/span&gt;, respectively. Let &lt;span class=&quot;math-container&quot;&gt;$\phi_A, \phi_B$&lt;/span&gt; be their respective volume fractions. So we can say that &lt;span class=&quot;math-container&quot;&gt;$\phi_A+\phi_B = 1$&lt;/span&gt;.&#xA;Define a function based on the spatial coordinate &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; such that &lt;span class=&quot;math-container&quot;&gt;$\phi_x(r)=1$&lt;/span&gt; if polymer X is at point &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\phi _x (r) =0$&lt;/span&gt; if polymer X is not a point &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. Let &lt;span class=&quot;math-container&quot;&gt;$\langle...\rangle$&lt;/span&gt; denote equilibrium ensemble average. Then, define&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\langle \phi _A(r) \rangle = \phi _A \quad(1)&#xA;\end{align}&lt;/span&gt;&#xA;Define &lt;span class=&quot;math-container&quot;&gt;$$\delta \phi _A(r)=\phi_A (r) - \phi _A\quad(2)$$&lt;/span&gt;&#xA;The fluctuation in concentration is defined by the correlation function&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{ab}(r-r')=\langle \delta \phi _a (r) \delta \phi _b (r')\rangle \quad(3)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$a,b$&lt;/span&gt; can be any of A and B. This can be proven by seeing that &lt;span class=&quot;math-container&quot;&gt;$\delta \phi _A (r)= - \delta \phi _B (r)$&lt;/span&gt;, so&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{AA}(r) = S_{BB}(r) = -S_{AB}(r) = -S_{BA}(r)$$&lt;/span&gt;&#xA;Therefore, the concentration fluctuations of an incompressible system are characterized by the single correlation function &lt;span class=&quot;math-container&quot;&gt;$S(r)=S_{AA}(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In order to evaluate &lt;span class=&quot;math-container&quot;&gt;$S_{ab}(r)$&lt;/span&gt;, we use the following relationship from linear response theory. Consider weak external potentials &lt;span class=&quot;math-container&quot;&gt;$u_A(r),u_B(r)$&lt;/span&gt; which act respectively on A and B. The change in the system's potential energy is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$U_{\rm ext}=\int dr[u_A(r)\phi _A(r)+u_B(r)\phi_B(r)] \quad (4)$$&lt;/span&gt;&#xA;If the external field is small. the deviation &lt;span class=&quot;math-container&quot;&gt;$\overline{\delta \phi _a(r)}=\langle \phi _a(r) \rangle _{ext}-\phi _a$&lt;/span&gt; can be written as a linear function of the external potential:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\overline{\delta \phi_a(r)}=-\sum _{b}\int dr' \Gamma_{ab}(r-r')u_b(r')\quad (5)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Gamma _{ab}(r)$&lt;/span&gt; is called the response function. It is related to the correlation function S_{ab} is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Gamma _{ab}(r) =\beta S_{ab}(r)\quad (6)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The tricky bit starts here. I want to now prove the above statement (6).&#xA;I am going to reproduce exactly what Doi has:&lt;/p&gt;&#xA;&lt;p&gt;To prove the above statement, let us write the intrinsic energy of the system as &lt;span class=&quot;math-container&quot;&gt;$U_0$&lt;/span&gt;, so that the equilibrium average &lt;span class=&quot;math-container&quot;&gt;$\overline{\delta \phi_a}$&lt;/span&gt; in the presence of the external field can be expressed as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\overline{\delta \phi _a} &amp;amp;=\frac{T_r\delta \phi _a \exp [-\beta(U_0+U_{ext})]}{T_r \exp [-\beta(U_0 +U_{ext})] } \\&#xA;&amp;amp;= \frac{T_r\delta \phi _a \exp [-\beta(U_0+U_{ext})]}{T_r \exp [-\beta(U_0)] }\cdot \frac{T_r \exp [-\beta U_0]}{T_r \exp [-\beta(U_0 +U_{ext})] } \\&#xA;&amp;amp;= \frac{\langle \delta \phi _a \exp (-\beta U_{ext})\rangle}{\langle \exp (-\beta U_{ext}\rangle} \quad (7)&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\langle ... \rangle = \frac{T_r...  \exp [-\beta(U_0)]}{T_r \exp [-\beta(U_0)] }$&lt;/span&gt; denotes the equilibrium average when the external field is not applied. For weak external fields, &lt;span class=&quot;math-container&quot;&gt;$\exp(-\beta U_{ext})$&lt;/span&gt; can be approximated as &lt;span class=&quot;math-container&quot;&gt;$1-\beta U_{ext}$&lt;/span&gt;. So from &lt;span class=&quot;math-container&quot;&gt;$(4),(7)$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\overline{\delta \phi_a (r)} = \langle \delta \phi _a (r) \rangle (1+\langle \beta U_{ext} \rangle )-\langle \delta \phi _a (r) \beta U_{ext}\rangle = -\beta \sum _b \int dr' \langle \delta \phi _a (r) \delta \phi _b (r') \rangle u_b (r')\quad (8)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I do not understand how they came up with the above equation. I apologize if I am not following some basic math, but I am really confused as to how Doi got the above equation &lt;span class=&quot;math-container&quot;&gt;$(8)$&lt;/span&gt;. If I approximate &lt;span class=&quot;math-container&quot;&gt;$$\exp(-\beta U_{ext})=1-\beta U_{ext}$$&lt;/span&gt;&#xA;If I plug it into &lt;span class=&quot;math-container&quot;&gt;$(7)$&lt;/span&gt;, I simply do not get the middle term in equation &lt;span class=&quot;math-container&quot;&gt;$(8)$&lt;/span&gt;. I get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\overline{\delta \phi _a} = \frac{\langle \delta \phi_a (1-\beta U_{ext})\rangle }{\langle 1-\beta U_{ext} \rangle} = \frac{\langle\delta \phi_a \rangle -\langle \delta \phi _a \beta U_{ext}\rangle}{\langle 1-\beta U_{ext}\rangle} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How does he get to &lt;span class=&quot;math-container&quot;&gt;$(8)$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$(1)-(7)$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-06-30T17:29:58.523" LastActivityDate="2021-06-30T18:16:23.220" Title="Derivation on correlation function and response functions in polymer physics" Tags="|mathematical-modeling|statistical-thermodynamics|polymers|correlation-functions|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6283" PostTypeId="2" ParentId="6282" CreationDate="2021-06-30T17:42:17.447" Score="8" Body="&lt;p&gt;It looks Doi makes some extra simplifications (beyond expanding the exponential) that are valid when the external field is weak.&lt;/p&gt;&#xA;&lt;p&gt;Let's start with what you wrote and make one simplification,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{eqnarray}&#xA;\overline{\delta \phi _a}&#xA;&amp;amp;= \frac{\langle\delta \phi_a \rangle -\langle \delta \phi _a \beta U_{ext}\rangle}{\langle 1-\beta U_{ext}\rangle} \tag{1}\\&#xA;&amp;amp;= \frac{\langle\delta \phi_a \rangle -\langle \delta \phi _a \beta U_{ext}\rangle}{1 - \langle \beta U_{ext}\rangle}.\tag{2} \\&#xA;\end{eqnarray}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, since we want the &lt;em&gt;linear&lt;/em&gt; response, we continue approximating on the basis that &lt;span class=&quot;math-container&quot;&gt;$U_{ext}$&lt;/span&gt; is small. To expand the denominator, we use&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{1}{1-x} \approx 1 + x,\tag{3}&#xA;$$&lt;/span&gt;&#xA;which is valid for small &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. After dropping any terms with two or more factors of &lt;span class=&quot;math-container&quot;&gt;$U_{ext}$&lt;/span&gt;, we get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\overline{\delta \phi _a}&#xA;= \langle\delta \phi_a \rangle \left[1 + \langle \beta U_{ext}\rangle\right] -\langle \delta \phi _a \beta U_{ext}\rangle ,&#xA;\tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is Doi's expression.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="5" LastEditDate="2021-06-30T18:16:23.220" LastActivityDate="2021-06-30T18:16:23.220" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6284" PostTypeId="1" CreationDate="2021-06-30T21:20:36.453" Score="8" ViewCount="123" Body="&lt;p&gt;I'm looking for classic references that describe the usual electrostatic contributions which have to be calculated in molecular dynamics simulations. I find it very hard to apprehend what different interaction potentials actually do to calculate electrostatic interactions.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;strong&gt;Why do electrostatics for most potentials seem to stop at charge and dipole interactions? Shouldn't we really consider interactions involving higher-order mutipoles as well?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, I have a lot of basic holes in my knowledge of the way these calculations are carried out even though I have personally implemented some of these methods before. If someone could provide me with references that discuss the different types of approximations (and how they relate to one another) to the electrostatic part of the interactions needed for MD simulations, that would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-12-25T21:04:10.250" LastActivityDate="2023-11-15T10:13:50.197" Title="References for Electrostatics Calculations Used in Molecular Dynamics" Tags="|molecular-dynamics|reference-request|molecular-interactions|intermolecular-forces|electrostatic|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6285" PostTypeId="2" ParentId="4953" CreationDate="2021-06-30T22:16:14.987" Score="5" Body="&lt;h1&gt;FCBand&lt;/h1&gt;&#xA;&lt;p&gt;FCBand is a Python package for simulating vibronic bands of electronic absorption spectroscopy using the Franck-Condon displaced harmonic oscillator (FC-DHO) models. These models are suitable for simulating the unresolved vibronic band shapes of electronic spectra that involve many electronic transitions and vibrational modes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://comp.chem.umn.edu/fcband/&quot; rel=&quot;noreferrer&quot;&gt;https://comp.chem.umn.edu/fcband/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="878" LastActivityDate="2021-06-30T22:16:14.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6286" PostTypeId="1" AcceptedAnswerId="6289" CreationDate="2021-07-01T02:14:32.153" Score="5" ViewCount="118" Body="&lt;p&gt;I am trying to write eq. 2 in &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/1701/1701.02880.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this PDF&lt;/a&gt; into matrix form (reproduced below) for numerical purposes. There are some definitions that I am not too familiar with, and don't seem to be given in the paper.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_0=\alpha k^2+\begin{pmatrix} 0 &amp;amp; \beta k_+^2 &amp;amp; 0 &amp;amp; 0 \\&#xA;                                 \beta^* k_-^2 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \\&#xA;                                 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; \beta k_+^2 \\&#xA;                                 0 &amp;amp; 0 &amp;amp; \beta^* k_-^2 &amp;amp; 0  &#xA;\end{pmatrix}$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$k_\pm=k_x\pm k_y$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For the atomic SOC effect, &lt;span class=&quot;math-container&quot;&gt;$H_{so}=\lambda_{so}L\cdot S$&lt;/span&gt; is diagonal in the selected basis. The ferromagnetic exchange term is added as &lt;span class=&quot;math-container&quot;&gt;$H_M=M_{\sigma z}\otimes1$&lt;/span&gt;. So the the total Hamiltonian can be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H=H_0+H_{so}+H_M$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I figured that &lt;span class=&quot;math-container&quot;&gt;$\alpha k^2$&lt;/span&gt; is added to the diagonal of eq. 1, that &lt;span class=&quot;math-container&quot;&gt;$k^2 = k_x^2 + k_y^2$&lt;/span&gt;, and that &lt;span class=&quot;math-container&quot;&gt;$H_M = M_{\sigma z} \otimes 1 = \sigma_z \otimes 1$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$\sigma_z$&lt;/span&gt; is the Pauli z matrix, and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; identity matrix).&lt;/p&gt;&#xA;&lt;p&gt;However, I am stumped on the definition of &lt;span class=&quot;math-container&quot;&gt;$H_{SO}=\lambda_{SO} L\cdot S$&lt;/span&gt;. What is &lt;span class=&quot;math-container&quot;&gt;$L\cdot S$&lt;/span&gt;? They mention that it is diagonal in the selected basis. Does this mean that it is simply &lt;span class=&quot;math-container&quot;&gt;$\lambda_{SO} 1$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; is now the &lt;span class=&quot;math-container&quot;&gt;$4\times 4$&lt;/span&gt; identity matrix? But then, how would the spin-up &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; block be differentiated from the spin-down &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; block? Am I missing some eigenvalue spin index that changes sign (perhaps &lt;span class=&quot;math-container&quot;&gt;$H_{SO}$&lt;/span&gt; is just the constant &lt;span class=&quot;math-container&quot;&gt;$\pm \lambda_{SO}$&lt;/span&gt; added to the diagonal?)? Any corrections to my assumptions would help. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-07-01T22:25:32.207" LastActivityDate="2021-07-01T22:55:20.600" Title="Help with definitions of SOC and ferromagnetic exchange terms in MoS2 Hamiltonian" Tags="|model-hamiltonians|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6287" PostTypeId="2" ParentId="1697" CreationDate="2021-07-01T05:45:02.437" Score="2" Body="&lt;p&gt;Since you are interested in quantum simulation, I would actually suggest reading Feynman and Hibbs &lt;em&gt;Quantum Mechanics and Path Integrals&lt;/em&gt;. It is very cheap which is a big plus and also remarkably readable as everything Feynman wrote is. Even though the book would be considered advanced because path integrals are considered advanced, much of what the book does is frame fairly basic statistical mechanics in terms of path integrals.&lt;/p&gt;&#xA;&lt;p&gt;There are other very good reasons to read this book based on your question. One is that Feynman did some of the earliest work on very low temperature Helium which is about as quantum of a fluid as one can get. Helium turns into a super-fluid at very low temperatures, and one can understand and model this using path integrals quite naturally. This is actually discussed a bit in the book. Feynman also provides a nice introduction to some of the problems which are still major problems in quantum statistical mechanics today. Those being things like the &amp;quot;sign problem&amp;quot; (of which there are actually a few different ones).&lt;/p&gt;&#xA;&lt;p&gt;As far as academic literature goes, this isn't molecular dynamics, but I would suggest reading the review on the theory of condensed helium, Rev. Mod. Phys. 67, 279, as he gives a very nice introduction to path integral monte carlo and actually closes the loop on a lot of the things Feynman discusses in the book I mentioned before. Also, there are a lot more conceptual similarities between path integral monte carlo and path integral molecular dynamics than between ordinary monte carlo and ordinary molecular dynamics.&lt;/p&gt;&#xA;&lt;p&gt;Finally, you should absolutely read the following paper: Chandler, D., &amp;amp; Wolynes, P. G. (1981). Exploiting the isomorphism between quantum theory and classical statistical mechanics of polyatomic fluids. The Journal of Chemical Physics, 74(7), 4078-4095.&lt;/p&gt;&#xA;&lt;p&gt;This paper uses the fact that the propagator of path integrals in imaginary time has the same form as the classical partition function of a classical system in an extended phase space.&lt;/p&gt;&#xA;&lt;p&gt;Finally, for more modern work in PIMD, I would suggest looking at the work of Michele Ceriotti, who is one of the primarily developers of i-PI, which is a good package for doing PIMD simulations.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-07-01T05:45:02.437" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6288" PostTypeId="1" CreationDate="2021-07-01T05:57:33.157" Score="3" ViewCount="741" Body="&lt;p&gt;I am running a test setup in LAMMPS. I am using &lt;span class=&quot;math-container&quot;&gt;$4000$&lt;/span&gt; atom hcp system with &lt;a href=&quot;https://atomicrex.org/potentials/meam.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;MEAM&lt;/a&gt; potential.&#xA;The system need to be at equilibrium at &lt;span class=&quot;math-container&quot;&gt;$\pu{10K}$&lt;/span&gt; and for this I am giving initial velocity at &lt;span class=&quot;math-container&quot;&gt;$\pu{10K}$&lt;/span&gt; and running NVE for short duration of &lt;span class=&quot;math-container&quot;&gt;$\pu{2ps}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\pu{1fs}$&lt;/span&gt; timestep) followed by NPT at &lt;span class=&quot;math-container&quot;&gt;$\pu{10K}$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$\pu{20ps}$&lt;/span&gt;. I want a configuration where system is at &lt;span class=&quot;math-container&quot;&gt;$\pu{10K}$&lt;/span&gt; with low pressure.&lt;/p&gt;&#xA;&lt;h2&gt;Step 1: NVE for short time&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;velocity all create 10 4928459&#xA;fix 1 all nve&#xA;run 20000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Output&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Step      Temp         TotEng       Press&#xA;   18500    4.9325929   -6191.5587    135.54744&#xA;   19000    5.0476045   -6191.5587    134.10653&#xA;   19500    5.0523007   -6191.5588    133.15733&#xA;   20000    5.1187478   -6191.5588    132.81736&#xA;   20010    5.0694554   -6191.5587    133.90782&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Final output is as expected and system equlibrated at &lt;span class=&quot;math-container&quot;&gt;$\pu{5K}$&lt;/span&gt; as we started with initial velocity of &lt;span class=&quot;math-container&quot;&gt;$\pu{10K}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\pu{133bar}$&lt;/span&gt; of pressure.&lt;/p&gt;&#xA;&lt;h2&gt;Step 2: NPT&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix 1 all npt temp 10 10 0.1 iso 0.0 0.0 1&#xA;run 200000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Output&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Step      Temp         TotEng       Press&#xA;  217000     10.04384   -6186.4403    157.98486&#xA;  217500    9.7292229   -6186.5088   -11.700501&#xA;  218000    9.7728786   -6186.3937   -92.777014&#xA;  218500    10.165017   -6186.3155   -69.765655&#xA;  219000     9.875577   -6186.5188   -10.970014&#xA;  219500    9.9095766   -6186.5424    74.030269&#xA;  220000    10.251927   -6186.3377    182.70663&#xA;  220010    10.259622   -6186.3333     76.85412&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here I used &lt;code&gt;Tdamp&lt;/code&gt; of &lt;span class=&quot;math-container&quot;&gt;$100\times \text{timestep}$&lt;/span&gt; and &lt;code&gt;Pdamp&lt;/code&gt; of &lt;span class=&quot;math-container&quot;&gt;$1000\times \text{timestep}$&lt;/span&gt;. I have changed different Pdamp value also and found that pressure varies from &lt;span class=&quot;math-container&quot;&gt;$\pu{-200 bar}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\pu{+200 bar}$&lt;/span&gt;. (Note for Non-LAMMPS users, the damp parameters give the amount of time for that property to relax).&lt;/p&gt;&#xA;&lt;p&gt;I can suppress this fluctuation by introducing drag term to Nose-Hoover equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix 1 all npt temp 10 10 0.1 iso 0.0 0.0 1 drag 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Output&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Step      Temp         TotEng       Press&#xA;   39000    10.074096   -6186.3848   0.88364453&#xA;   39500    10.001291   -6186.3747   0.29228989&#xA;   40000    9.9810361   -6186.3857  -0.12452421&#xA;   40010    9.7588549    -6186.392  -0.91715159&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I want to suppress these fluctuation in pressure only using real ensemble (with no drag). I tried to increase further run to &lt;span class=&quot;math-container&quot;&gt;$\pu{100 ps}$&lt;/span&gt;, but I can still see fluctuations. &lt;strong&gt;How much fluctuation in pressure is acceptable, as these fluctuations increase with temperature also?&lt;/strong&gt; Any further insight is highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2021-07-02T13:10:35.903" LastActivityDate="2021-07-02T13:10:35.903" Title="Practical way to reduce pressure fluctuations in molecular dynamics?" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="7" ClosedDate="2021-08-24T15:43:01.053" ContentLicense="CC BY-SA 4.0" />
  <row Id="6289" PostTypeId="2" ParentId="6286" CreationDate="2021-07-01T07:47:51.670" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;However, I am stumped on the definition of &lt;span class=&quot;math-container&quot;&gt;$H_{SO}=\lambda_{SO} L\cdot S$&lt;/span&gt;. &lt;strong&gt;What is &lt;span class=&quot;math-container&quot;&gt;$L\cdot S$&lt;/span&gt;&lt;/strong&gt;?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Spin-orbit coupling is typically written as a scalar coupling constant (in this case &lt;span class=&quot;math-container&quot;&gt;$\lambda_{\textrm{SO}}$&lt;/span&gt;) multiplied with &lt;span class=&quot;math-container&quot;&gt;$\hat{L}\cdot \hat{S}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\hat{L}$&lt;/span&gt; is an orbital angular momentum operator and &lt;span class=&quot;math-container&quot;&gt;$\hat{S}$&lt;/span&gt; is a spin angular momentum operator (hence ther term &amp;quot;spin-orbit&amp;quot; coupling). This can be further turned into:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;\hat{L} \cdot \hat{S} = \frac{1}{2}\left(\hat{J}^2 - \hat{L}^2 - \hat{S}^2 \right),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\hat{J} \equiv \hat{L} + \hat{S}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is the origin of one of the most popular approximations for the &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin%E2%80%93orbit_interaction#Final_energy_shift&quot; rel=&quot;nofollow noreferrer&quot;&gt;SO energy shift &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{\textrm{SO}}$&lt;/span&gt; in hydrogenic atoms&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \hat{L} \cdot \hat{S} \rangle = \frac{\hbar^2}{2}\left( j(j+1)  - l(l+1) - s(s+1) \right),\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;\Delta E_{\textrm{SO}}  = \frac{\beta}{2}\left( j(j+1)  - l(l+1) - s(s+1) \right),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;\beta \equiv Z^4 \frac{\mu_0}{4\pi} g_{\textrm{s}} \mu_{\textrm{B}}^2 \frac{1}{n^3 a_0^3\;l(l+1/2)(l+1)}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;They mention that it is diagonal in the selected basis. Does this mean that it is simply &lt;span class=&quot;math-container&quot;&gt;$\lambda_{SO} 1$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; is now the &lt;span class=&quot;math-container&quot;&gt;$4\times 4$&lt;/span&gt; identity matrix?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It seems that the overall Hamiltonian (in your case, it's labelled as &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;) is being written in the basis of eigenstates of the &lt;span class=&quot;math-container&quot;&gt;$\hat{L}\cdot \hat{S}$&lt;/span&gt;  operator, which would indeed make &lt;span class=&quot;math-container&quot;&gt;$H_{\textrm{SO}}$&lt;/span&gt; diagonal, &lt;em&gt;&lt;strong&gt;but&lt;/strong&gt;&lt;/em&gt; diagonal does not necessarily mean proportional to the identity matrix. If the eigenvalues of &lt;span class=&quot;math-container&quot;&gt;$\hat{L}\cdot \hat{S}$&lt;/span&gt; are, for example: &lt;span class=&quot;math-container&quot;&gt;$\left(0,\frac{1}{2},2,3\right)$&lt;/span&gt; then &lt;span class=&quot;math-container&quot;&gt;$H_{\textrm{SO}}$&lt;/span&gt; could be &lt;span class=&quot;math-container&quot;&gt;$\textrm{diag}\left(0,\frac{\lambda_{\textrm{SO}}}{2},2\lambda_{\textrm{SO}},3\lambda_{\textrm{SO}}\right)$&lt;/span&gt;. This would happen if the second excited state under the &lt;span class=&quot;math-container&quot;&gt;$H_{\textrm{SO}}$&lt;/span&gt; Hamiltonian was higher in energy than the ground state by 4x more than the first excited state is.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;But then, how would the spin-up &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; block be differentiated from the spin-down &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; block?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The spin-up and spin-down blocks will be identifiable if you keep track of how the states are ordered in your basis. They don't even have to be &amp;quot;spin-up block&amp;quot; and &amp;quot;spin-down block&amp;quot;. you could order the states with spin-up and spin-down alternating. &lt;/p&gt;&#xA;&lt;p&gt;In thi case of this paper, they do seem to have ordered the basis with spin-up followed by spin-down, as you can see earlier in the paragraph that they have labeled the basis vectors in the following way:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{6} |d_{+2} \uparrow\rangle ,|d_{-2} \uparrow\rangle ,|d_{+2} \downarrow\rangle   ,|d_{-2} \downarrow\rangle , |d_{\pm2}\rangle \equiv |d_{x^2 - y^2}\rangle \pm 2\textrm{i}|d_{xy}\rangle. &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-01T22:55:20.600" LastActivityDate="2021-07-01T22:55:20.600" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6290" PostTypeId="1" CreationDate="2021-07-01T07:58:56.483" Score="6" ViewCount="138" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lcBjk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lcBjk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/YRwKc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YRwKc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;In the band structure of (221) &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; supercell, all the curvature are looking like straight lines. I cannot calculate band gap.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uZe0U.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uZe0U.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;high-symmetry point:  0.0000 0.0000 0.0000   x coordinate   0.0000&#xA;high-symmetry point:  0.0000 0.3849 0.0000   x coordinate   0.3849&#xA;high-symmetry point:  0.0000-0.5774 0.0000   x coordinate   0.3849&#xA;high-symmetry point:  0.1667 0.2887 0.0000   x coordinate   1.2668&#xA;high-symmetry point:  0.1667 0.4811 0.0000   x coordinate   1.4593&#xA;high-symmetry point:  0.3333 0.5774 0.0000   x coordinate   1.6517&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;point group &lt;span class=&quot;math-container&quot;&gt;$C_{3v}$&lt;/span&gt; (3m), there are  3 classes. The character table:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;       E     2C3   3s_v &#xA;A_1    1.00  1.00  1.00&#xA;A_2    1.00  1.00 -1.00&#xA;E      2.00 -1.00  0.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="5" LastEditDate="2021-07-05T22:36:51.657" LastActivityDate="2021-07-05T22:36:51.657" Title="Band Curvature looks like straight lines for (221) MoS2 Monolayer in Quantum ESPRESSO" Tags="|quantum-espresso|band-structure|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-04T15:26:53.707" ContentLicense="CC BY-SA 4.0" />
  <row Id="6291" PostTypeId="1" AcceptedAnswerId="6294" CreationDate="2021-07-01T08:49:11.143" Score="11" ViewCount="2142" Body="&lt;p&gt;I am attempting to analyse the radial distribution function (oxygen to oxygen) for a ~400ps simulation on a droplet of water (MD done with NAMD). I am using the python library &lt;a href=&quot;https://www.mdanalysis.org/&quot; rel=&quot;noreferrer&quot;&gt;MDAnalysis&lt;/a&gt; to do this. However, the problem is that the default RDF function (&lt;code&gt;MDAnalysis.analysis.rdf.InterRDF&lt;/code&gt;) from MDAnalysis uses periodic boundary conditions. The water droplet simulation I am doing is in vacuum i.e. with no boundary conditions.&lt;/p&gt;&#xA;&lt;p&gt;The calculation of the RDF seems to have a step where the total number is divided by the box volume to get the density. So, when I am using the function on my system, python is giving me a &lt;code&gt;divide by zero&lt;/code&gt; error, as the box volume is zero. The RDF I got is zero throughout because of this. How should I fix this?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wSWXK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wSWXK.png&quot; alt=&quot;RDF of O-O&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have considered writing my python code to get the RDF, because MDAnalysis provides the coordinates of each atoms for each frame. I was sort of able to do this when there was only one reference atom (i.e. RDF from one atom) (in the jupyter notebook), but I don't know how to get the RDF when there are multiple reference atoms. There are a lot of formulas for RDF that I could find, but I am not sure which one to use, or how to implement them in python. If anyone could help me with this, that would also be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;I cannot share my raw data as it is an ongoing research project, but I can share the Jupyter Notebook I used for the analysis: &lt;a href=&quot;https://github.com/ShoubhikRaj/molecular-modelling/blob/main/matter-modelling/rdf-mdanalysis/RDF_analysis-Copy1.ipynb&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/ShoubhikRaj/molecular-modelling/blob/main/matter-modelling/rdf-mdanalysis/RDF_analysis-Copy1.ipynb&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-07-02T12:54:56.800" Title="How should I generate a radial distribution function (RDF) for an MD trajectory with python?" Tags="|molecular-dynamics|python|radial-distribution-function|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6292" PostTypeId="2" ParentId="5034" CreationDate="2021-07-01T11:56:38.983" Score="7" Body="&lt;p&gt;I agree with Emil Zak's answer that normal mode coordinates from different minima should, in general, be put together with special care.  However, relating the two different sets of normal mode origin from different minima (or transition states) is not of nonsense, see SVP model of Hua Guo and Bin Jiang and related theories.&lt;/p&gt;&#xA;&lt;p&gt;To make things short, I will use the same symbols as in the question.  The relation between the normal mode coordinates and Cartesian coordinates, are&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{R}=\mathfrak{R}_{\alpha}\cdot\left(\mathbf{R}_{\alpha}+\sum_{i=7}^{3N}{{Q}_{\alpha}}_i\cdot {\mathbf{K}_{\alpha}}_i\right)+\mathbf{t},\tag{1}&#xA;$$&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\mathbf{R}=\mathfrak{R}_{\beta}\cdot\left(\mathbf{R}_{\beta}+\sum_{i=7}^{3N}{{Q}_{\beta}}_i\cdot {\mathbf{K}_{\beta}}_i\right)+\mathbf{t}.&#xA;$$&lt;/span&gt;&#xA;Here, we assume that the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_{\alpha}$&lt;/span&gt; are originated from the COM of molecule. &lt;span class=&quot;math-container&quot;&gt;$\mathfrak{R}_{\alpha}$&lt;/span&gt; mean a rotation matrix and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{t}$&lt;/span&gt; is the translation.  And the mass-weighted part are omitted for simplicity.&lt;/p&gt;&#xA;&lt;p&gt;Note that I separate rotation, translation, and vibration on purpose.  Although in practice you can keep them together and compute the all &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; DOF based on normal modes fashion, like in Gaussian software you get 6 &amp;quot;low frequencies&amp;quot; for translations and rotations, which should be exact zeros in principle, when you use the normal modes vectors to represent the coordinate, it is &lt;em&gt;not&lt;/em&gt; a good idea to use the rotation normal modes, more importantly, the molecular orientation must be the same as of the reference geometry, because the vibration normal modes are attached to the reference geometry, and that is why the rotation matrix is outside the big parentheses.&lt;/p&gt;&#xA;&lt;p&gt;Using the formulae above, it is easy to convert the normal mode coordinate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}_{\alpha}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt;, and if we have an algorithm to get &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}_{\beta}$&lt;/span&gt;, the problem will be solved.&lt;/p&gt;&#xA;&lt;p&gt;The main idea is&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Translate the molecule so that the COM located at &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Rotate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_{\beta}$&lt;/span&gt; to align with &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; with some algorithm (Wahba's problem).  In my implement, Kabsch's algorithm is used. So the rotation matrix &lt;span class=&quot;math-container&quot;&gt;$\mathfrak{R}_{\beta}$&lt;/span&gt; is get. (Edit: Here, one may minimize the mass-weighted RMSD&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta=\sqrt{\frac{1}{N}\sum_{i=1}^{N}m_i|\mathfrak{R}_{\beta}\mathbf{R}_{\beta i}-\mathbf{R}_{\alpha i}|^2}, \tag{3}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt; is the mass of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th atom.&#xA;&lt;a href=&quot;https://doi.org/10.1063/1.1929739&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kudin and Dymarsky&lt;/a&gt; has shown that minimization of mass-weighted RMSD is equivalent with the Eckart condition. I thank @Hans Wurst provided the information.)&lt;/li&gt;&#xA;&lt;li&gt;Utilizing the orthogonality of mass-weighted normal mode vectors, get the coordinates &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}_{\beta}$&lt;/span&gt;. Note that in this step you only need the vibration ones, and exclude the rotation and translations&lt;/li&gt;&#xA;&lt;li&gt;&lt;del&gt;Now rotate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_{\beta}$&lt;/span&gt; to align with &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}+{{Q}_{\beta}}_i\cdot {\mathbf{K}_{\beta}}_i$&lt;/span&gt;, update &lt;span class=&quot;math-container&quot;&gt;$\mathfrak{R}_{\beta}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}_{\beta}$&lt;/span&gt;.&lt;/del&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;del&gt;Do it iteratively until the two molecules are perfectly aligned.&lt;/del&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;del&gt;The algorithm above is implemented with Julia programming language by me as shown in &lt;a href=&quot;https://gist.github.com/zhaiyusci/985d01edfda4bea990a7682917b333f4&quot; rel=&quot;nofollow noreferrer&quot;&gt;gist&lt;/a&gt;.&lt;/del&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then you can do&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;\mathbf{Q}_{\alpha} \leftrightarrow \mathbf{R} \leftrightarrow \mathbf{Q}_{\beta}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Problem solved.&lt;/p&gt;&#xA;&lt;p&gt;I would suggest that the reader refer to some published work, thanks to the anonymous reviewers.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Gábor Czakó, &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;116&lt;/strong&gt;, 116, 7467–7473 (2012)&lt;/li&gt;&#xA;&lt;li&gt;Philip R. Bunker, &lt;em&gt;Molecular Symmetry and Spectroscopy&lt;/em&gt; (1979), Academic Press, New York (see Ch. 7 therein)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are some methods that use intramolecular curvilinear coordinates as the &amp;quot;bridge&amp;quot;, although I think use Cartesian coordinates is easier to be understood.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="339" LastEditDate="2021-08-20T03:05:01.913" LastActivityDate="2021-08-20T03:05:01.913" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6293" PostTypeId="1" CreationDate="2021-07-01T12:57:27.567" Score="6" ViewCount="156" Body="&lt;p&gt;As I am exploring material simulations one really hard truth that I have realized is that my gaming laptop is not at all going to cut it for my research work. Currently I am trying to find the absorption spectra of a quantum dot which has 45 atoms in total and I am using the PBE functional (so not that much accuracy). The geometrical optimization converged after 10-12 hours by running the executable for absorption spectra (&lt;code&gt;turbo_lanczos.x&lt;/code&gt;) did not go that well. The computation ran for 23 hours after which my laptop gave out.&lt;/p&gt;&#xA;&lt;p&gt;So I am looking for clusters which do not burn a big hole in my pocket. AWS and GCS came first to my mind. Although &lt;a href=&quot;http://star.mit.edu/hpc/documentation/ec2scripts/&quot; rel=&quot;nofollow noreferrer&quot;&gt;I found a tutorial&lt;/a&gt; for running on AWS &lt;strong&gt;I am not sure how to know how many cores, nodes, RAM or instances I need&lt;/strong&gt;. I was also not able to find any such documentation for Google Cloud.&lt;/p&gt;&#xA;&lt;p&gt;Could you guys help me with some guidance?&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-07-01T15:24:18.847" LastActivityDate="2021-07-01T15:24:18.847" Title="How to run Quantum ESPRESSO on Google Cloud Services or Amazon Web Services" Tags="|quantum-espresso|high-performance-computing|quantum-dots|cloud-computing|" AnswerCount="0" CommentCount="11" ClosedDate="2022-01-26T15:04:07.033" ContentLicense="CC BY-SA 4.0" />
  <row Id="6294" PostTypeId="2" ParentId="6291" CreationDate="2021-07-01T15:26:56.247" Score="9" Body="&lt;p&gt;You could fool the MDAnalysis RDF function &lt;code&gt;InterRDF&lt;/code&gt; by setting an artificial cell of a size large enough so that the periodic boundary conditions don't cause any atom to be counted twice.&lt;/p&gt;&#xA;&lt;p&gt;This can be done by adding the following lines before computing the rdf.&#xA;It basically creates a cell twice as large as the largest distance in the selected frame of the universe.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;d = np.max(u.atoms.positions) - np.min(u.atoms.positions)&#xA;u.dimensions = [2*d, 2*d, 2*d, 90, 90, 90]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If your system size fluctuates a lot you can be on the safe size by taking the largest possible distance accross the entire trajectory.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;d = np.max([np.max(u.atoms.positions) - np.min(u.atoms.positions) for ts in u.trajectory])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You should only pay attention to the fact that this rdf isn't normalised as you take an arbitrary density when defining the cell. However it shouldn't be too hard to use a prefactor to normalise it if you have a particular definition of the density for your system.&#xA;The density of the MDAnalysis arbitrary cell can be obtained with&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    density = u.atoms.n_atoms / MDAnalysis.lib.mdamath.box_volume(u.dimensions)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The quantity &lt;code&gt;rdf * density&lt;/code&gt; is invariant from the size of the arbitrary cell (if it's large enough).&lt;/p&gt;&#xA;&lt;p&gt;A minimal working example inspired by your notebook could be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import MDAnalysis as mda&#xA;from MDAnalysis.analysis import rdf&#xA;import matplotlib.pyplot as plt&#xA;import numpy as np&#xA;u = mda.Universe(&amp;quot;15_ws.psf&amp;quot;,&amp;quot;100H2O_prelim.dcd&amp;quot;) #load files&#xA;&#xA;# New two lines to create a large cell&#xA;d = np.max(u.atoms.positions) - np.min(u.atoms.positions)&#xA;u.dimensions = [2*d, 2*d, 2*d, 90, 90, 90]&#xA;&#xA;oxy = u.select_atoms('name OH2') # get oxygens&#xA;hyd = u.select_atoms('type HT') # get hydrogens&#xA;O_O = rdf.InterRDF(oxy,oxy,verbose=True)&#xA;O_O.run()&#xA;plt.plot(O_O.bins, O_O.rdf)&#xA;# or if you're interested in the density invariant quantity&#xA;density = u.atoms.n_atoms / MDAnalysis.lib.mdamath.box_volume(u.dimensions)&#xA;plt.plot(O_O.bins, density * O_O.rdf)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="1609" LastEditDate="2021-07-02T12:54:56.800" LastActivityDate="2021-07-02T12:54:56.800" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6295" PostTypeId="1" CreationDate="2021-07-02T00:15:20.717" Score="7" ViewCount="77" Body="&lt;p&gt;As I understand the anomalous Hall effect, in materials with a strong spin-orbit coupling, the intrinsic deflection effect is dominant over the side jump and skew scattering effects. In the intrinsic deflection effect, the electrons acquire an anomalous velocity due to the Berry curvature (which is not null because there is a break in the spatial inversion symmetry). The anomalous Hall effect is present in ferromagnetic materials, since the DOS is separated into two (one higher than the other), so there are more spin up electrons than spin down electrons, which travel in curved paths to different sides depending on the spin. As there is more spin up than spin down, this will generate a non-zero Hall potential difference. In the spin Hall effect, a non-magnetic material that has the same number of spin up and down electrons is used. Thus, the Hall potential is zero, but there is a current that flows due to the spins. I have a question:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can the anomalous Hall effect only be applied to magnetic materials? Can't be applied to non-magnetic materials?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thank you for your help.&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2021-12-25T21:06:26.200" LastActivityDate="2021-12-25T21:06:26.200" Title="Can the anomalous Hall effect only be applied to magnetic materials?" Tags="|density-of-states|spin-orbit-coupling|berry-phase|transition-metals|spin|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T22:41:36.403" ContentLicense="CC BY-SA 4.0" />
  <row Id="6296" PostTypeId="1" CreationDate="2021-07-02T16:30:49.060" Score="7" ViewCount="132" Body="&lt;p&gt;&lt;strong&gt;EDIT: Please see my first comment on this question first.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://journals.jps.jp/doi/pdf/10.1143/JPSJ.76.053702&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, Fukui and Hatsugai present a numerical scheme for the calculation of the &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; index that uses the following definition:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\mathbb{Z}_2 = \frac{1}{2\pi}\left[ \oint_{\partial HBZ} A dk - \int_{HBZ} \Omega_z d^2k \right] (\text{mod } 2).&#xA;$$&lt;/span&gt;&#xA;In Figure 1 of the paper (screenshot below), they identify three types of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points in a discretized Brillouin zone lattice. These three sets are denoted by &lt;span class=&quot;math-container&quot;&gt;$\mathcal{B}_s^\pm$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{B}_s^0$&lt;/span&gt;. They define what each of these points are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{B}_s^0$&lt;/span&gt; are time-reversal &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-invariant sites: &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}H(k_l)\mathcal{T}^{-1}=H(k_l)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;As a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; constraint, states at &lt;span class=&quot;math-container&quot;&gt;$-k_l\in\mathcal{B}_s^+$&lt;/span&gt; are Kramers doublets of states at &lt;span class=&quot;math-container&quot;&gt;$k_l \in \mathcal{B}_s^-$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If the spectrum at each &lt;span class=&quot;math-container&quot;&gt;$k_l$&lt;/span&gt; is arranged as &lt;span class=&quot;math-container&quot;&gt;$\epsilon_n (k_l)\leq\epsilon_{n+1}(k_l)$&lt;/span&gt;, the states at &lt;span class=&quot;math-container&quot;&gt;$-k_l$&lt;/span&gt; can be constrained as: &lt;span class=&quot;math-container&quot;&gt;$|n(-k_l)\rangle=\mathcal{T}|n(k_l)\rangle,$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$k_l\in\mathcal{B}_s^-$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Both Kramers doublets are included in &lt;span class=&quot;math-container&quot;&gt;$\mathcal{B}_s^0$&lt;/span&gt;. Arranging the spectrum here as &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{2n-1}(k)= \epsilon_{2n}(k)\leq \epsilon_{2n+1}(k)$&lt;/span&gt;, they impose a final constraint: &lt;span class=&quot;math-container&quot;&gt;$|2n(k_l)\rangle=\mathcal{T}|n(k_l)\rangle$&lt;/span&gt;, for &lt;span class=&quot;math-container&quot;&gt;$k_l\in\mathcal{B}_s^-$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;They use these constrained states to define a link variable per the usual &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0503172&quot; rel=&quot;noreferrer&quot;&gt;Fukui-Hatsugai-Susuki scheme&lt;/a&gt; (I think). I have implemented this common scheme in Python and MATLAB with no issue, &lt;strong&gt;but I am having trouble imposing the required constraints and properly choosing one half-Brillouin-zone for eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; above&lt;/strong&gt;. I can see it being easy to do with some hard-coding in a low-resolution lattice, but I was wondering whether someone give me insight on translating the above constraints to code, and properly choosing the three different types of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{B}_s^i$&lt;/span&gt;) automatically without hard-coding. Thanks.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NIHCK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NIHCK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="7" LastEditDate="2021-07-19T15:20:48.627" LastActivityDate="2023-12-18T20:35:54.637" Title="How to choose half-Brillouin-zone (HBZ) in Fukui &amp; Hatsugai's numerical scheme for the Z2 invariant?" Tags="|berry-phase|brillouin-zone|spin-models|topological-matter|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6298" PostTypeId="1" CreationDate="2021-07-02T20:42:38.780" Score="9" ViewCount="69" Body="&lt;p&gt;I have been thinking about so-called valley Chern numbers &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt; and associated topological phenomena. To my knowledge, they are usually applicable when inter-valley scattering is suppressed, leaving the Berry curvature peaked at a high symmetry point (&lt;span class=&quot;math-container&quot;&gt;$K,K',\Gamma,M,...$&lt;/span&gt;). Following are few of several examples involving such Hamiltonians:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.pnas.org/content/110/26/10546&quot; rel=&quot;noreferrer&quot;&gt;Zhang, Fan, Allan H. MacDonald, and Eugene J. Mele. &amp;quot;Valley Chern numbers and boundary modes in gapped bilayer graphene.&amp;quot; Proceedings of the National Academy of Sciences 110.26 (2013): 10546-10551&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.125405&quot; rel=&quot;noreferrer&quot;&gt;Qiao, Zhenhua, et al. &amp;quot;Topological phases in gated bilayer graphene: Effects of Rashba spin-orbit coupling and exchange field.&amp;quot; Physical Review B 87.12 (2013): 125405&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In theoretical models, people usually use Hamiltonians (sometimes starting from lattice Hamiltonians), to derive a &lt;span class=&quot;math-container&quot;&gt;$k\cdot p$&lt;/span&gt; Hamiltonian that is centered at the &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; point. Then, they sum the Berry curvature of filled bands in the limit &lt;span class=&quot;math-container&quot;&gt;$k\rightarrow \infty$&lt;/span&gt; (usually a very large &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space numerically) to get the Chern number at each valley &lt;span class=&quot;math-container&quot;&gt;$C_K,C_{K'}$&lt;/span&gt;. This is then used to calculate &lt;span class=&quot;math-container&quot;&gt;$C_v=C_K - C_{K'}$&lt;/span&gt;. Numerically, &lt;span class=&quot;math-container&quot;&gt;$C_K$&lt;/span&gt; are oftentimes not perfectly quantized, but are very close (ex: &lt;span class=&quot;math-container&quot;&gt;$0.999 \rightarrow 1$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;On top of models like these, there are lattice models (&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.61.2015&quot; rel=&quot;noreferrer&quot;&gt;such as Haldane's model for the QAHE&lt;/a&gt;), that can yield similar quantized results. In these cases, one could do a low-energy expansion at the &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; point to potentially &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.85.165456&quot; rel=&quot;noreferrer&quot;&gt;see something similar&lt;/a&gt; (idea of 'topological charge').&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My confusion is:&lt;/strong&gt; What makes these valley-type Hamiltonians special enough to give quantized Chern numbers in these limits? I am used to thinking of topological quantities as properties of the entire Bruillouin zone (ex: Chern number of QAHE), half-Brillouin zone (ex: &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; index), or just a loop around gapless points (ex: &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-phase in graphene). So, what makes these valley-type Hamiltonians correctly give the same/accurate information about topological phenomena even though they are simpler and localized to special points? I think that &lt;span class=&quot;math-container&quot;&gt;$k\cdot p$&lt;/span&gt; models are diagonal at the &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; point, and off-diagonals kick in as we move farther away from the chosen point. While I think that some information is lost (not sure what exactly), perhaps there might be some special symmetry that isn't lost? I am not convinced that all this is due to &lt;em&gt;&lt;strong&gt;potential&lt;/strong&gt;&lt;/em&gt; linear Dirac dispersions...&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am asking because I messed around with some &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space effective Hamiltonians derived from DFT calculations, and they don't seem to behave as nicely/quantizedly compared to aforementioned theoretical/lattice/&lt;span class=&quot;math-container&quot;&gt;$k\cdot p$&lt;/span&gt; models.&lt;/strong&gt; Perhaps, this question might also be related to the question of how a &lt;span class=&quot;math-container&quot;&gt;$k\cdot p$&lt;/span&gt; Hamiltonian about a high-symmetry/&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; point might reflect valley topology accurately whereas a fictitious &lt;span class=&quot;math-container&quot;&gt;$k\cdot p$&lt;/span&gt; Hamiltonian about a faraway, non-special, &amp;quot;low-symmetry point&amp;quot; might not.&lt;/p&gt;&#xA;&lt;p&gt;I apologize this question might not have been phrased properly, but I appreciate your patience.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-12-25T21:07:49.973" LastActivityDate="2021-12-25T21:07:49.973" Title="What is special about valley-focused Hamiltonians that make them give quantized/rational (valley) Chern numbers?" Tags="|mathematical-modeling|model-hamiltonians|berry-phase|valleytronics|topological-matter|" AnswerCount="0" CommentCount="4" ClosedDate="2022-08-23T22:16:44.307" ContentLicense="CC BY-SA 4.0" />
  <row Id="6299" PostTypeId="1" CreationDate="2021-07-03T14:11:58.410" Score="7" ViewCount="84" Body="&lt;p&gt;I'm trying to simulate the behavior of chromophore molecules incorporated into a polymer under an external electric field.&lt;/p&gt;&#xA;&lt;p&gt;I've tried to use classical molecular dynamics (GROMACS) but it's unable to reproduce some phenomena such as molecule aggregation due to its dispersion nature.&lt;/p&gt;&#xA;&lt;p&gt;So I'm looking for a dynamic method/software that is able to reproduce dispersion interactions on the scale of thousands of atoms. I'm personally thinking about CP2K or CPMD but I'm not sure.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-07-03T16:04:46.613" LastActivityDate="2021-07-03T16:04:46.613" Title="Molecular dynamics to reproduce dispersion interactions" Tags="|molecular-dynamics|software-recommendations|cp2k|intermolecular-forces|cpmd|" AnswerCount="0" CommentCount="10" ClosedDate="2022-01-26T14:58:55.507" ContentLicense="CC BY-SA 4.0" />
  <row Id="6300" PostTypeId="5" CreationDate="2021-07-03T16:06:30.477" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://bioexcel.eu/software/cpmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://bioexcel.eu/software/cpmd/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Car%E2%80%93Parrinello_molecular_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Car%E2%80%93Parrinello_molecular_dynamics&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-03T16:06:30.477" LastActivityDate="2021-07-03T16:06:30.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6301" PostTypeId="4" CreationDate="2021-07-03T16:06:30.477" Score="0" Body="Questions related to the software CPMD, or the Car-Parinello Molecular Dynamics method that it's named after." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-03T16:06:30.477" LastActivityDate="2021-07-03T16:06:30.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6302" PostTypeId="5" CreationDate="2021-07-03T16:50:57.053" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://atb.uq.edu.au/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://atb.uq.edu.au/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Malde AK, Zuo L, Breeze M, Stroet M, Poger D, Nair PC, Oostenbrink C, Mark AE.&#xA;An Automated force field Topology Builder (ATB) and repository: version 1.0.&#xA;J. Chem. Theory Comput., 2011, 7, 4026-4037. DOI:10.1021/ct200196m&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-03T16:50:57.053" LastActivityDate="2021-07-03T16:50:57.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6303" PostTypeId="4" CreationDate="2021-07-03T16:50:57.053" Score="0" Body="Questions about the ATB software and repository for providing classical molecular force fields for compounds" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-03T16:50:57.053" LastActivityDate="2021-07-03T16:50:57.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6304" PostTypeId="1" CreationDate="2021-07-04T06:31:31.920" Score="7" ViewCount="1018" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vFWCy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vFWCy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which is my ecutwfc converged value in this calculation result.&lt;/p&gt;&#xA;&lt;p&gt;How to choose ecutrho in quantum espresso calculation.&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="3687" LastEditDate="2021-07-04T06:40:29.170" LastActivityDate="2022-12-08T08:34:05.617" Title="Converged value of ecutwfc in Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6305" PostTypeId="1" AcceptedAnswerId="6321" CreationDate="2021-07-04T08:55:57.743" Score="6" ViewCount="512" Body="&lt;p&gt;I am currently doing a simulation of the behaviour of various sizes of water droplets (~100-1000 water molecules) in vacuum. I am using NAMD with the spherical boundary conditions to keep the droplet in place, and using the CHARMM parameters for simulation.&lt;/p&gt;&#xA;&lt;p&gt;The CHARMM parameter stream files contain a list of options which contain the recommended non-bonded cut offs for vdW forces and electrostatics:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NONBONDED nbxmod  5 atom cdiel shift vatom vdistance vswitch -&#xA;cutnb 14.0 ctofnb 12.0 ctonnb 10.0 eps 1.0 e14fac 1.0 wmin 1.5&#xA;                !adm jr., 5/08/91, suggested cutoff scheme&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(Explanation—pair-list distance= 14 Å, cut-off distance= 12 Å, dielectric const.= 1, 1,4-interaction scaling= 1)&lt;/p&gt;&#xA;&lt;p&gt;However, these values are only read by the CHARMM software, NAMD manual &lt;a href=&quot;https://www.ks.uiuc.edu/Training/Tutorials/namd/namd-tutorial-unix-html/node25.html&quot; rel=&quot;noreferrer&quot;&gt;mentions&lt;/a&gt; that NAMD will ignore them, and set the values according to what is set inside the NAMD configuration file.&lt;/p&gt;&#xA;&lt;p&gt;If I understand correctly, force fields are usually parameterised considering a liquid system (i.e. with 3D periodic boundary conditions) therefore, these cut offs are also likely optimised for a liquid simulation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What cut-offs should be used if a system in vacuum has to be simulated with CHARMM parameters? (and why?)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;My guess here is that because the CHARMM non-bonded parameters were developed with that cut-off, the cut-off should be kept the same, even if the simulation is done in vacuum. However, a more-experienced colleague has told me that I should use a very large cut-off distance (much larger than the droplet, say ~500Å).&lt;/p&gt;&#xA;&lt;p&gt;So I am confused about what cut-off I should use, and how much it would affect the system if I use a very large cut-off.&lt;/p&gt;&#xA;&lt;p&gt;(Note that in the simulation I am &lt;em&gt;not&lt;/em&gt; trying to measure any dynamic property of the system like diffusion or timescales etc. I am only interested in overall positions of the water molecules, their distributions, effect of a different molecule in the droplet etc.)&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-07-12T08:26:13.330" LastActivityDate="2021-07-12T08:26:13.330" Title="Should I use a different cut-off scheme for non-bonded interactions when simulating a system with MD in vacuum?" Tags="|molecular-dynamics|forcefields|intermolecular-forces|namd|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6306" PostTypeId="2" ParentId="6304" CreationDate="2021-07-04T09:15:46.393" Score="7" Body="&lt;p&gt;Convergence is always defined in term of tolerance what user choose and based on your data, I will take &lt;code&gt;ecutwfc&lt;/code&gt; as 70 Ryd. You should also report run time along with these data.&#xA;For considering &lt;code&gt;ecutrho&lt;/code&gt; I will suggest you to stick with default value, if you are dealing with metallic system.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Kinetic energy cutoff (Ry) for charge density and potential:&#xA;For norm-conserving pseudopotential you should stick to the&#xA;default value, you can reduce it by a little but it will&#xA;introduce noise especially on forces and stress.&#xA;If there are ultrasoft PP, a larger value than the default is&#xA;often desirable (ecutrho = 8 to 12 times ecutwfc, typically).&#xA;PAW datasets can often be used at 4*ecutwfc, but it depends&#xA;on the shape of augmentation charge: testing is mandatory.&#xA;The use of gradient-corrected functional, especially in cells&#xA;with vacuum, or for pseudopotential without non-linear core&#xA;correction, usually requires an higher values of ecutrho&#xA;to be accurately converged.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm274&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm274&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2021-07-04T13:13:20.560" LastActivityDate="2021-07-04T13:13:20.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6307" PostTypeId="1" AcceptedAnswerId="6308" CreationDate="2021-07-04T11:24:51.980" Score="6" ViewCount="466" Body="&lt;p&gt;I am using &lt;code&gt;VMD&lt;/code&gt; to visualise the secondary structure of protein &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The trajectories are from my Gromacs simulation. Firstly I use &lt;code&gt;File - New Molecule...&lt;/code&gt; to load the &lt;code&gt;protein.gro&lt;/code&gt; file. Secondly I use &lt;code&gt;File - Load Data into Molecule...&lt;/code&gt; to load my &lt;code&gt;protein.xtc&lt;/code&gt; trajectories.&lt;/p&gt;&#xA;&lt;p&gt;Then I use &lt;code&gt;Cartoon&lt;/code&gt; to visulise the structure. As I drag the time frames, all the secondary structures (e.g. alpha-helix, beta-sheet) stay the same. But I am pretty sure some of them are changing, as I look into the &lt;code&gt;Timeline&lt;/code&gt; analysis for secondary structure.&lt;/p&gt;&#xA;&lt;p&gt;So how do I use &lt;code&gt;VMD&lt;/code&gt; to see the secondary structures at different time frames?&lt;/p&gt;&#xA;" OwnerUserId="1667" LastActivityDate="2021-07-04T13:25:57.937" Title="Can VMD change its cartoon representation for secondary structure according to trajectories?" Tags="|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6308" PostTypeId="2" ParentId="6307" CreationDate="2021-07-04T12:34:57.900" Score="9" Body="&lt;p&gt;Yes, It can. Just run this script in &lt;code&gt;Extensions --&amp;gt; TK console&lt;/code&gt; of vmd before visualizing&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;proc structure_trace {name index op} {&#xA;      vmd_calculate_structure $index&#xA;}&#xA;&#xA;trace variable vmd_frame w structure_trace&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="3593" LastEditDate="2021-07-04T13:25:57.937" LastActivityDate="2021-07-04T13:25:57.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6309" PostTypeId="1" CreationDate="2021-07-04T14:39:43.593" Score="4" ViewCount="91" Body="&lt;p&gt;I am trying to predict the magnetic order transformations in Mn doped SmFeO3 using the MagneticStructureEnumerator class of pymatgen.&#xA;Attached is the error message:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;OSError                                   Traceback (most recent call last)&#xA;&amp;lt;ipython-input-1-4d89c9b376bb&amp;gt; in &amp;lt;module&amp;gt;&#xA;     37 from pymatgen.transformations.advanced_transformations import MagOrderingTransformation     &#xA;38 mag_par = MagOrderingTransformation({&amp;quot;Sm3+&amp;quot;:5,&amp;quot;Fe3+&amp;quot;:5,&amp;quot;O2-&amp;quot;:0,&amp;quot;Mn3+&amp;quot;:4}, order_parameter=0.5)&#xA;---&amp;gt; 39 SmFeO3_Mn_Mag_new = mag_par.apply_transformation(SmFeO3_Mn_prop)    &#xA;40 print(SmFeO3_Mn_Mag_new)&#xA;&#xA;~\anaconda3\lib\site-packages\pymatgen\transformations\advanced_transformations.py in apply_transformation(self, structure, return_ranked_list)   &#xA;940         t = EnumerateStructureTransformation(**enum_kwargs)   &#xA;941     &#xA;--&amp;gt; 942         alls = t.apply_transformation(structure, return_ranked_list=return_ranked_list)&#xA;    943 &#xA;    944         # handle the fact that EnumerateStructureTransformation can either&#xA;&#xA;~\anaconda3\lib\site-packages\pymatgen\transformations\advanced_transformations.py in apply_transformation(self, structure, return_ranked_list)&#xA;    445             )   &#xA;446             try:&#xA;--&amp;gt; 447                 adaptor.run()   &#xA; 448             except EnumError:   &#xA; 449                 warn(&amp;quot;Unable to enumerate for max_cell_size = {}&amp;quot;.format(max_cell_size))&#xA;&#xA;~\anaconda3\lib\site-packages\pymatgen\command_line\enumlib_caller.py in run(self)    &#xA;140             self._gen_input_file()    &#xA;141             # Perform the actual enumeration&#xA;--&amp;gt; 142             num_structs = self._run_multienum()&#xA;143             # Read in the enumeration output as structures.    &#xA;144             if num_structs &amp;gt; 0:&#xA;&#xA;~\anaconda3\lib\site-packages\pymatgen\command_line\enumlib_caller.py in _run_multienum(self)    &#xA;292     def _run_multienum(self):    &#xA;293 &#xA;--&amp;gt; 294         p = subprocess.Popen([enum_cmd],    &#xA;295                              stdout=subprocess.PIPE,    &#xA;296                              stdin=subprocess.PIPE, close_fds=True)&#xA;&#xA;~\anaconda3\lib\subprocess.py in __init__(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, encoding, errors, text)    &#xA;852                             encoding=encoding, errors=errors    &#xA;853&#xA;--&amp;gt; 854             self._execute_child(args, executable, preexec_fn, close_fds,   &#xA;855                                 pass_fds, cwd, env,   &#xA;856                                 startupinfo, creationflags, shell,&#xA;&#xA;~\anaconda3\lib\subprocess.py in _execute_child(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_start_new_session)  &#xA;1305             # Start the process  &#xA;1306             try:&#xA;-&amp;gt; 1307                 hp, ht, pid, tid = _winapi.CreateProcess(executable, args,  &#xA;1308                                          # no special security &#xA;1309                                          None, None,&#xA;OSError: [WinError 193] %1 is not a valid Win32 application&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How do I resolve this error?&lt;/p&gt;&#xA;" OwnerUserId="3878" LastEditorUserId="7" LastEditDate="2021-07-05T02:16:09.677" LastActivityDate="2021-07-05T02:16:09.677" Title="Predicting the magnetic behaviour of Mn doped SmFeO3" Tags="|anti-ferromagnetic|pymatgen|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-13T19:14:32.150" ContentLicense="CC BY-SA 4.0" />
  <row Id="6310" PostTypeId="1" CreationDate="2021-07-04T16:41:50.723" Score="10" ViewCount="1660" Body="&lt;p&gt;I found the following example of code which uses density functional theory to compute the electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;    #!/usr/bin/env python&#xA;    #&#xA;    # Author: Qiming Sun &amp;lt;osirpt.sun@gmail.com&amp;gt;&#xA;    #&#xA;&#xA;    import numpy&#xA;    from pyscf import lib&#xA;    from pyscf.dft import numint, gen_grid&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Gaussian cube file format&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;&#xA;    def density(mol, outfile, dm, nx=80, ny=80, nz=80):&#xA;    coord = mol.atom_coords()&#xA;    box = numpy.max(coord, axis=0) - numpy.min(coord, axis=0) + 4&#xA;    boxorig = numpy.min(coord, axis=0) - 2&#xA;    xs = numpy.arange(nx) * (box[0] / nx)&#xA;    ys = numpy.arange(ny) * (box[1] / ny)&#xA;    zs = numpy.arange(nz) * (box[2] / nz)&#xA;    coords = lib.cartesian_prod([xs, ys, zs])&#xA;    coords = numpy.asarray(coords, order=&amp;quot;C&amp;quot;) - (-boxorig)&#xA;&#xA;    nao = mol.nao_nr()&#xA;    ngrids = nx * ny * nz&#xA;    blksize = min(200, ngrids)&#xA;    rho = numpy.empty(ngrids)&#xA;    for ip0, ip1 in gen_grid.prange(0, ngrids, blksize):&#xA;        ao = numint.eval_ao(mol, coords[ip0:ip1])&#xA;        rho[ip0:ip1] = numint.eval_rho(mol, ao, dm)&#xA;    rho = rho.reshape(nx, ny, nz)&#xA;&#xA;    with open(outfile, &amp;quot;w&amp;quot;) as f:&#xA;        f.write(&amp;quot;Density in real space\n&amp;quot;)&#xA;        f.write(&amp;quot;Comment line\n&amp;quot;)&#xA;        f.write(&amp;quot;]&amp;quot; % mol.natm)&#xA;        f.write(&amp;quot; .8f .8f .8f\n&amp;quot; % tuple(boxorig.tolist()))&#xA;        f.write(&amp;quot;] .8f .8f .8f\n&amp;quot; % (nx, xs[1], 0, 0))&#xA;        f.write(&amp;quot;] .8f .8f .8f\n&amp;quot; % (ny, 0, ys[1], 0))&#xA;        f.write(&amp;quot;] .8f .8f .8f\n&amp;quot; % (nz, 0, 0, zs[1]))&#xA;        for ia in range(mol.natm):&#xA;            chg = mol.atom_charge(ia)&#xA;            f.write(&amp;quot;%5d %f&amp;quot; % (chg, chg))&#xA;            f.write(&amp;quot; .8f .8f .8f\n&amp;quot; % tuple(coord[ia]))&#xA;        fmt = &amp;quot; .8e&amp;quot; * nz + &amp;quot;\n&amp;quot;&#xA;        for ix in range(nx):&#xA;            for iy in range(ny):&#xA;                f.write(fmt % tuple(rho[ix, iy].tolist()))&#xA;&#xA;&#xA;if __name__ == &amp;quot;__main__&amp;quot;:&#xA;    from pyscf import gto, scf&#xA;    from pyscf.tools import cubegen&#xA;&#xA;    mol = gto.M(atom=&amp;quot;H 0 0 0; H 0 0 1&amp;quot;)&#xA;    mf = scf.RHF(mol)&#xA;    mf.scf()&#xA;    cubegen.density(mol, &amp;quot;h2.cube&amp;quot;, mf.make_rdm1())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wonder however about the nature of this output rho. So if I was to visualize this electron density how would I plot it? Is anyone familiar with this package? It seems to be an array with three columns &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, each of length 80. But what does one point then correspond to?&lt;/p&gt;&#xA;" OwnerUserId="3879" LastEditorUserId="5" LastEditDate="2021-07-05T03:18:35.370" LastActivityDate="2022-03-10T19:48:00.450" Title="Visualize electron density using pyscf" Tags="|density-functional-theory|quantum-chemistry|electronic-structure|hartree-fock|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6311" PostTypeId="1" CreationDate="2021-07-04T18:34:18.203" Score="8" ViewCount="631" Body="&lt;p&gt;I am using ORCA version 4.2.1 to calculate on the RI-BP86/def2-SVP level of theory the molecule &lt;span class=&quot;math-container&quot;&gt;$\ce{NI3}$&lt;/span&gt;. I would assume this to be a rather trivial matter, but I am running into an error. I've only been using ORCA casually, so I'm not that experienced. I also know that version 5.0 was just released, but I did not have the time to update.&lt;br /&gt;&#xA;My guess is I'm doing something wrong, or missing something important. Here is the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! RI BP86 def2-SVP def2/J D3BJ TIGHTSCF Opt TIGHTOPT Grid5 FinalGrid5 Freq&#xA;! LargePrint PrintBasis&#xA;%geom&#xA;Calc_Hess true # Calculate Hessian in the beginning&#xA;Recalc_Hess 5  # Recalculate the Hessian every 5 steps&#xA;end&#xA;%maxcore 1200&#xA;&#xA;*xyz 0 1&#xA;N        -0.00447226283705   -0.00447228533261   -0.00447218389615&#xA;I         1.96253257409287   -0.47903013984302   -0.47903017483099&#xA;I        -0.47903014119403    1.96253259549055   -0.47903017643514&#xA;I        -0.47903017006179   -0.47903017031492    1.96253253516228&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The molecular structure was preoptimised with GFN2-xTB, so it should be a decent guess.&lt;/p&gt;&#xA;&lt;p&gt;At the tail of things, within the initial SCF cycle, I'll get the error:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;                         ----------------------------&#xA;                         !        ITERATION    27   !&#xA;                         ----------------------------&#xA;   Total Energy        :    -947.817767792740 Eh&#xA;   Energy Change       :      -0.082996473216 Eh&#xA;   MAX-DP              :       0.392236224899&#xA;   RMS-DP              :       0.018540257659&#xA;   Orbital gradient    :       0.093887611787&#xA;   Orbital Rotation    :       0.570102706559&#xA;   Actual Damping      :       0.0000&#xA;   Int. Num. El.       :    82.00000308 (UP=   41.00000154 DN=   41.00000154)&#xA;   Exchange            :   -70.09754201&#xA;   Correlation         :    -3.88915080&#xA;&#xA;&#xA;          ************************************************************&#xA;          *                     SERIOUS PROBLEM IN SOSCF             *&#xA;          *                     ------------------------             *&#xA;          *            HUGE, UNRELIABLE STEP WAS ABOUT TO BE TAKEN   *&#xA;          *                         ABORTING THE RUN                 *&#xA;          ************************************************************&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is the reason for this and how can I get it to converge?&lt;/p&gt;&#xA;" OwnerUserId="49" LastActivityDate="2021-07-04T19:31:15.100" Title="Why is my ORCA calculation of nitrogen iodide failing?" Tags="|density-functional-theory|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6312" PostTypeId="2" ParentId="6311" CreationDate="2021-07-04T19:31:15.100" Score="14" Body="&lt;p&gt;There was a bug with the PModel guess of iodine, which leads to a very poor initial guess for molecules containing iodine, and consequently divergent SCF calculation. This bug has been fixed in ORCA 5.0. ORCA 5.0 can be downloaded at &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/?cat=13&quot; rel=&quot;noreferrer&quot;&gt;https://orcaforum.kofo.mpg.de/app.php/dlext/?cat=13&lt;/a&gt;. Note that ORCA 5.0 does not support the keywords Grid5 and FinalGrid5 anymore (because we now use a new set of grids, and the new default grid is much more accurate than the old one, with about the same cost), you have to remove them before you run the input file with ORCA 5.0.&lt;/p&gt;&#xA;&lt;p&gt;If updating to ORCA 5.0 isn't an option, you can use the PAtom guess instead. By the way, in case you encounter a similar error message in the future that is not due to a bug of the initial guess, you can probably get rid of the error by adding !NoSOSCF.&lt;/p&gt;&#xA;&lt;p&gt;Finally, I'd say that the ORCA forum (&lt;a href=&quot;https://orcaforum.kofo.mpg.de/index.php&quot; rel=&quot;noreferrer&quot;&gt;https://orcaforum.kofo.mpg.de/index.php&lt;/a&gt;) is probably a better place to ask questions about ORCA.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-04T19:31:15.100" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6314" PostTypeId="1" CreationDate="2021-07-05T01:25:31.227" Score="7" ViewCount="617" Body="&lt;p&gt;I am a beginner of Quantum Espresso. I have taken 221 MoS2 Monolayer and done a relax calculation.&#xA;In case of bulk system, or any doping in supercell, which is preferred: &lt;code&gt;vc-relax&lt;/code&gt; or &lt;code&gt;relax&lt;/code&gt;?&#xA;It's not clear to me under what conditions I need to use one vs the other.&lt;/p&gt;&#xA;&lt;p&gt;Before the relax calculation, I converged ecutwfc, k-points and ecutrho (using ultrasoft pseudopotential). Do any other parameters have to converge before starting this type of calculation?&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="7" LastEditDate="2021-07-05T02:04:31.220" LastActivityDate="2021-07-05T16:51:21.973" Title="What parameters have to converge before doing a relax calculation?" Tags="|quantum-espresso|cell-optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6315" PostTypeId="2" ParentId="6310" CreationDate="2021-07-05T06:07:59.687" Score="9" Body="&lt;p&gt;This is just the Gaussian cube format. It's essentially a voxel dump of the wave function evaluated on a grid. You can find some documentation at &lt;a href=&quot;http://paulbourke.net/dataformats/cube/&quot; rel=&quot;noreferrer&quot;&gt;http://paulbourke.net/dataformats/cube/&lt;/a&gt; and &lt;a href=&quot;https://h5cube-spec.readthedocs.io/en/latest/cubeformat.html&quot; rel=&quot;noreferrer&quot;&gt;https://h5cube-spec.readthedocs.io/en/latest/cubeformat.html&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;Most electronic structure programs are able to generate Gaussian cube files. Several molecular viewers can also do so. For instance, I think Avogadro, Jmol and IQmol all support visualizing from Gaussian cube format.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-07-05T06:07:59.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6316" PostTypeId="1" CreationDate="2021-07-05T09:46:33.910" Score="6" ViewCount="265" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aSTNM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aSTNM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For my 221MoS2 supercell, I fixed ecutwfc (60Ry) and k-points (441),&lt;/p&gt;&#xA;&lt;p&gt;I used ultrasoft pseudopotential for my calculation. Which ecutrho value is correct because all are nearly similar.&lt;/p&gt;&#xA;" OwnerUserId="3687" LastActivityDate="2021-07-05T16:43:15.030" Title="Which is my correct ecutrho convergence?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6317" PostTypeId="2" ParentId="6316" CreationDate="2021-07-05T16:43:15.030" Score="5" Body="&lt;p&gt;It all depends on the precision you need for your calculations.&lt;/p&gt;&#xA;&lt;p&gt;One way...&#xA;From your data, if you are concerning only with energies with only one/two decimal places, your calculation are ok since the first value of ecutoff, 240 (as the first two decimal places remains the same for all other calculations). But if you are interested in energies with four decimal places, for example, the cutoff converged energy will be 420, as all the other results with greater ecutoff values remains with the same four decimal places.&lt;/p&gt;&#xA;&lt;p&gt;Another way...&#xA;You can calculate a property you can measure and them, choose the corresponding value of ecutoff such the theoretical value has the same error as the experimental measurement.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-07-05T16:43:15.030" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6318" PostTypeId="2" ParentId="6314" CreationDate="2021-07-05T16:51:21.973" Score="3" Body="&lt;p&gt;Prior to any production calculation, the convergence study with &lt;code&gt;ecutwfc&lt;/code&gt;, &lt;code&gt;k-points&lt;/code&gt; and &lt;code&gt;ecutrho&lt;/code&gt; should be enough. But, the better should be to do a convergence study using the property you are interested in.&lt;/p&gt;&#xA;&lt;p&gt;Please, take a look in previous discussion &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/500/24&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/316/24&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/317/24&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-07-05T16:51:21.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6319" PostTypeId="1" AcceptedAnswerId="6320" CreationDate="2021-07-05T19:21:39.137" Score="9" ViewCount="489" Body="&lt;p&gt;TMDs (transition metal dichalcogenides) are materials that can have a layered structure. When moving from bulk to monolayers, the bandgap changes from indirect to direct according to the image (DFT to MoSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;). From what I understand, this may be due to the effect of quantum confinement, but I didn't understand what this phenomenon consists of for the specific case of TMDs. What is quantum confinement for TMDs?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AeUw5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AeUw5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Kumar, A. e Ahluwalia, P., Electronic structure of transition metal dichalcogenides monolayers 1H-­MX&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; (M = Mo, W; X = S, Se, Te) from ab-­initio theory: New direct band gap semiconductors. European Physical Journal B, 85:1–7, 2012.)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2021-07-05T22:04:23.497" LastActivityDate="2021-07-06T09:10:02.430" Title="Quantum confinement of transition metal dichalcogenides (TMDs)" Tags="|density-functional-theory|band-structure|transition-metals|dichalcogenides|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6320" PostTypeId="2" ParentId="6319" CreationDate="2021-07-06T09:10:02.430" Score="6" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Quantum confinement is a kind of physical effect, which describes the change of electronic and optical properties when the material sampled is of sufficiently small size----typically 10 nanometers or less.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For layered TMDC materials, when the materials are downsized to the 2D limit, the dielectric screening environment will be reduced significantly, and hence the interaction between electron and hole will be greatly increased (forming exciton with large binding energy), as illustrated by the following figure.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/y225f.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y225f.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In addition, the bandgap of semiconducting materials will be promoted due to quantum confinement and also increase the exciton binding energy, as shown below.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IU2DF.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IU2DF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In summary, quantum confinement in 2D TMDC materials will lead to a strong excitonic effect.&lt;/p&gt;&#xA;&lt;p&gt;Ref: &lt;a href=&quot;https://journals.aps.org/prl/pdf/10.1103/PhysRevLett.113.076802&quot; rel=&quot;noreferrer&quot;&gt;PRL 113, 076802 (2014)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-07-06T09:10:02.430" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6321" PostTypeId="2" ParentId="6305" CreationDate="2021-07-06T10:27:56.200" Score="6" Body="&lt;p&gt;I think the effect of larger cutoffs will not affect your simulation. Shorter cutoffs will be more problematic and can see artifacts than the larger cutoffs. Even if you have larger cutoffs, the interaction strength will be very very weak as you go outward and eventually die. This will just increase your computational cost (neighbour list calculation) and will not affect observable properties in the simulation.&lt;/p&gt;&#xA;&lt;p&gt;In biomolecules, with shorter cutoffs, the conformations of the proteins deviated far away from the initial structure and were significantly distorted, but for longer cutoffs the structure was quite stable. [1]&lt;/p&gt;&#xA;&lt;p&gt;If you use WCA potential instead of LJ-potential, there can be issues with varying cutoff distances.[2]&lt;/p&gt;&#xA;&lt;p&gt;Earlier works have shown that with WCA potential, there is little effect of cutoffs in determining the equilibrium structure of fluid in NVT ensemble. Whereas in NPT ensemble, cutoff distances play a key role in fluid equilibrium structure, density and self diffusion coefficient.&lt;/p&gt;&#xA;&lt;p&gt;I will be looking for more brainstorming on this topic. Feel free to comment.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;[1] Norberg, Jan, and Lennart Nilsson. &amp;quot;On the truncation of long-range electrostatic interactions in DNA.&amp;quot; Biophysical journal 79.3 (2000): 1537-1553.&lt;/p&gt;&#xA;&lt;p&gt;[2] Huang, Cunkui, et al. &amp;quot;Effect of cut-off distance used in molecular dynamics simulations on fluid properties.&amp;quot; Molecular Simulation 36.11 (2010): 856-864.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2021-07-06T10:27:56.200" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6322" PostTypeId="1" AcceptedAnswerId="6327" CreationDate="2021-07-06T18:33:02.133" Score="8" ViewCount="118" Body="&lt;p&gt;We've had several questions regarding calculation and plotting of electron density.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://chemistry.stackexchange.com/a/66532/5017&quot;&gt;electrostatic potential&lt;/a&gt; represents the interaction between a point charge at a given point &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; in a system of atoms, given by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$V(\mathbf{r})=\sum_{A=1}^{N_{\text {atoms }}} \frac{Z_{A}}{\left|\mathbf{R}_{A}-\mathbf{r}\right|}-\int \frac{\rho\left(\mathbf{r}^{\prime}\right)}{\left|\mathbf{r}-\mathbf{r}^{\prime}\right|} d \mathbf{r}^{\prime}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first part of this is easy - it's the classical Coulomb formula between the atomic nuclear charges &lt;span class=&quot;math-container&quot;&gt;$Z_A$&lt;/span&gt; at positions &lt;span class=&quot;math-container&quot;&gt;$R_A$&lt;/span&gt; and the point &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The second piece involves an integral over the electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'd like to evaluate the electrostatic potential at a set of points, either over a grid or vertices of a surface mesh. Ideally, I'd like to see the algorithm as well as an open source implementation.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-07-07T07:21:49.817" Title="Are there efficient open source implementations of electrostatic potential integrals?" Tags="|quantum-chemistry|electronic-structure|electrostatic|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6323" PostTypeId="1" AcceptedAnswerId="6330" CreationDate="2021-07-07T02:47:25.063" Score="6" ViewCount="579" Body="&lt;p&gt;This is a follow-up question to my previous question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6163/computing-analytic-derivatives-of-molecular-hamiltonians-obtained-from-solving-h&quot;&gt;Computing analytic derivatives of molecular Hamiltonians obtained from solving Hartree-Fock equations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;After looking at various quantum chemistry packages, such as PySCF, Psi4, and GAMESS, it is now clear that one can compute analytic molecular Hessians. However, it seems as though Hessians can only be computed analytically within the Hartree-Fock approximation, with more precise treatments using a finite-difference approach.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering: is it possible to use any of the above (or other) quantum chemistry libraries to compute Hessians &lt;strong&gt;analytically&lt;/strong&gt; at the level of Full CI?&lt;/p&gt;&#xA;" OwnerUserId="3693" LastEditorUserId="5" LastEditDate="2021-07-07T18:32:11.457" LastActivityDate="2021-07-07T18:32:11.457" Title="Analytic Hessian at the level of full CI?" Tags="|software-recommendations|geometry-optimization|full-configuration-interaction|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6324" PostTypeId="1" AcceptedAnswerId="7210" CreationDate="2021-07-07T03:50:19.280" Score="10" ViewCount="169" Body="&lt;h2&gt;Background&lt;/h2&gt;&#xA;&lt;p&gt;Let's say I have the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;'th gas molecule with velocity &lt;span class=&quot;math-container&quot;&gt;$\vec v_i(t)$&lt;/span&gt; at time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. To find the net displacement &lt;span class=&quot;math-container&quot;&gt;$s_i$&lt;/span&gt; we integrate with respect to &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \vec s_i = \int_{0}^{t} \vec v_i(t') dt' $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since, the gas molecule under goes collisions. Initially  the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;'th gas molecule has velocity &lt;span class=&quot;math-container&quot;&gt;$v_{i,1}$&lt;/span&gt; for time interval &lt;span class=&quot;math-container&quot;&gt;$t_1$&lt;/span&gt; and then velocity &lt;span class=&quot;math-container&quot;&gt;$v_{i,2}$&lt;/span&gt; for time interval &lt;span class=&quot;math-container&quot;&gt;$t_2$&lt;/span&gt; and so on ...&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \vec v_i(t') dt'  = \vec v_{i,1} t_1 + \vec v_{i,2} t_2 + \dots + \vec v_{i,n} t_n $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, we can write the velocity as the infinitesimal ratio of displacement and time:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \vec v_i(t') dt'  =  t_1 \frac{d \vec x_{i,1}}{dt}  + t_2 \frac{d \vec x_{i,1}}{dt}  + \dots + t_n \frac{dx_{i,n}}{dt}    $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Multiplying both sides by &lt;span class=&quot;math-container&quot;&gt;$dt$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \Big( \int_{0}^{t''} \vec v_i(t') dt' \Big) dt'' =  \int^{ \vec x_i(t)}_{\vec x_i(0)} t_1 d \vec x_{i,1} + t_2 d \vec x_{i,2}  + \dots + t_n dx_{i,n} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Using some &lt;a href=&quot;https://math.stackexchange.com/questions/2888976/the-definite-integral-problem-with-a-twist&quot;&gt;number theory and analysis&lt;/a&gt; and assuming the &lt;span class=&quot;math-container&quot;&gt;$\vec v_i$&lt;/span&gt; which appear follow a particular distribution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \Big( \int_{0}^{t''} \vec v_i(t') dt' \Big) dt''  = \langle t_c \rangle  \int^{ \vec x_i(t)}_{\vec x_i(0)}   d  \vec x_i  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\langle t_c \rangle$&lt;/span&gt; is the average time interval for a collision. Since we have only done this for one particle we now proceed to do this over all the particles in a volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; (and assume the collision rate in the block of volume is the same/the temperature is the same in the volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \Big( \int_{0}^{t''} \sum_{i=\text{all particle in $V$}}m_i \vec v_i(t') dt' \Big) dt'' /M = \langle t_c  \rangle \sum_{i=\text{all particle in $V$}}  \int_{ \vec x_i(0)}^{\vec x_i(t)}  m_i d   \vec x_i /M $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is the total mass &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt; is the mass of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;'th particle. Since the center of mass is immune to collisions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_{0}^{t} \Big( \int_{0}^{t''} \vec v_{CM}(t') dt' \Big) dt'' = \langle t_c  \rangle      \int_{0}^t \vec v_{CM} (t'') dt'' $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\vec v_{CM}$&lt;/span&gt; is the velocity of the center of mass and we used:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \sum_{i=\text{all particle in $V$}} m_i \int_{ \vec x_i(0)}^{\vec x_i(t)}   d   \vec x_i /M = \sum_i m_i \int_0^t ( \vec v_{i,1} + \vec v_{i,2} + \vec v_{i,3} + \dots ) dt /M  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Question&lt;/h2&gt;&#xA;&lt;p&gt;Is the derivation correct? Is there some clever computational experiment way to verify this?&lt;/p&gt;&#xA;" OwnerUserId="1810" LastEditorUserId="1810" LastEditDate="2021-07-10T12:16:13.703" LastActivityDate="2021-12-06T19:43:38.477" Title="Is it possible to experimentally verify this collision rate formula?" Tags="|molecular-dynamics|statistical-thermodynamics|thermodynamics|experimental|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6325" PostTypeId="1" CreationDate="2021-07-07T04:55:37.690" Score="4" ViewCount="157" Body="&lt;p&gt;I want to simulate a graphene based metasurface using COMSOL. Can anyone tell me the steps of defining Graphene in COMSOL or provide any tutorial for the same?&lt;/p&gt;&#xA;" OwnerUserId="3897" LastActivityDate="2021-07-07T04:55:37.690" Title="How to design Graphene metasurface using COMSOL?" Tags="|graphene|metamaterials|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-06T18:46:48.353" ContentLicense="CC BY-SA 4.0" />
  <row Id="6326" PostTypeId="2" ParentId="6323" CreationDate="2021-07-07T05:12:46.480" Score="6" Body="&lt;p&gt;Analytical Hessians have been derived for pretty much everything; they just aren't available in most programs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.cfour.de/&quot; rel=&quot;noreferrer&quot;&gt;CFOUR&lt;/a&gt; has analytical vibrational frequencies i.e. nuclear Hessians for HF and the following post-HF methods: MP2, MP3, MP4, CC2, CCD, QCISD, CCSD, QCISD(T), CCSD(T), CCSDT-n (n=1-4), CC3,&#xA;CCSDT.&lt;/p&gt;&#xA;&lt;p&gt;Kállay's &lt;a href=&quot;https://mrcc.hu/&quot; rel=&quot;noreferrer&quot;&gt;MRCC&lt;/a&gt; program has analytical Hessians for arbitrary single- or multireference configuration interaction or coupled-cluster approach (note that this includes full CI by definition!) in &lt;a href=&quot;https://doi.org/10.1063/1.1668632&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 120, 6841 (2004)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Analytical Hessians are available for at least the simpler methods in many other codes, as well. For instance, analytic MP2 hessians can probably be found in any older quantum chemistry program since MP2 was very popular in the 1990s before DFT came along.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-07-07T05:12:46.480" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6327" PostTypeId="2" ParentId="6322" CreationDate="2021-07-07T05:34:23.557" Score="5" Body="&lt;p&gt;If you know the Gaussian basis set and the density matrix, the task simplifies to the calculation of nuclear attraction integrals.&lt;/p&gt;&#xA;&lt;p&gt;The electron density is expanded in the basis set as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n({\bf r}) = \sum_{\mu \nu} P_{\mu \nu} \chi_\mu({\bf r}) \chi_\nu({\bf r}).$$&lt;/span&gt;&#xA;When you substitute this into your equation, you get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V({\bf r}) = \sum_{A=1}^{N_{\rm atoms}} \frac {Z_A}  {|{\bf r}-{\bf R}_A|} -  \sum_{\mu \nu} P_{\mu \nu} \int \frac {\chi_\mu({\bf r}') \chi_\nu({\bf r}')} {{|{\bf r}-{\bf r}'|}} {\rm d}^3r'. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The nuclear attraction integral for atom &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V^A_{\mu \nu}  = \int \frac {\chi_\mu({\bf r}) \chi_\nu({\bf r})} {|{\bf r}-{\bf R}_A|} {\rm d}^3r $$&lt;/span&gt;&#xA;so you can see that you just need to compute these integrals for every point on your grid; one-electron integrals are pretty cheap even though the nuclear-attraction integrals are the most expensive to compute.&lt;/p&gt;&#xA;&lt;p&gt;Nuclear attraction integrals are available e.g. in Sun's &lt;a href=&quot;https://github.com/sunqm/libcint/&quot; rel=&quot;noreferrer&quot;&gt;libcint library&lt;/a&gt; described in &lt;a href=&quot;https://doi.org/10.1002/jcc.23981&quot; rel=&quot;noreferrer&quot;&gt;J. Comput. Chem. 36, 1664 (2015)&lt;/a&gt; or Bin Gao's &lt;a href=&quot;https://gitlab.com/bingao/gen1int/tree/master&quot; rel=&quot;noreferrer&quot;&gt;GEN1INT library&lt;/a&gt; described in &lt;a href=&quot;https://doi.org/10.1002/qua.22886&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 111, 858 (2010)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-07-07T05:34:23.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6328" PostTypeId="2" ParentId="6322" CreationDate="2021-07-07T07:21:49.817" Score="6" Body="&lt;p&gt;The open-source program Multiwfn (&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;) contains a module that calculates the electrostatic potentials. According to Tian Lu, it has been quite thoroughly optimized for speed. Depending on your workflow, you may even be able to obtain the electrostatic potentials by calling Multiwfn in a black-box manner through command line, without having to dig into its source code.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-07T07:21:49.817" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6329" PostTypeId="1" AcceptedAnswerId="6331" CreationDate="2021-07-07T08:56:16.547" Score="10" ViewCount="199" Body="&lt;p&gt;In the famous 1996 &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.77.3865&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; of Burke, Perdew and Ernzerhof in the very first paragraph it is stated that &lt;span class=&quot;math-container&quot;&gt;$E_{XC} = E_X + E_C$&lt;/span&gt;. Then, a GGA functional is derived starting from the energy density of uniform electron gas with an attenuation function. In the final step a formula for the XC-energy is abruptly given but the correlation energy is seemingly left out with no explanation.&lt;/p&gt;&#xA;&lt;p&gt;The starting point for the correlation energy is &lt;span class=&quot;math-container&quot;&gt;$E_C = \int \text{d}^3 r\, n \cdot (\epsilon_C^{\text{unif}} + H)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is dependent on &lt;span class=&quot;math-container&quot;&gt;$\nabla n/n$&lt;/span&gt; and is chosen such that &lt;span class=&quot;math-container&quot;&gt;$E_C$&lt;/span&gt; is sensible for certain conditions of the particle density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, the exchange energy is given by &lt;span class=&quot;math-container&quot;&gt;$E_X = \int \text{d}^3r\, n \epsilon_X^{\text{unif}} F_X$&lt;/span&gt;, where in almost the same way &lt;span class=&quot;math-container&quot;&gt;$F_X$&lt;/span&gt; is dependent on &lt;span class=&quot;math-container&quot;&gt;$\nabla n / n$&lt;/span&gt; and is constructed to satisfy certain conditions of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Thinking back to the definition of &lt;span class=&quot;math-container&quot;&gt;$E_{XC}$&lt;/span&gt;, one would expect that these two energies are taken as a sum to give the final result. However, to my surprise a new coefficient is given&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{XC} = \int \text{d}^3 r\, n \epsilon_X^{\text{unif}}F_{XC}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Moreover, the actual functional form of &lt;span class=&quot;math-container&quot;&gt;$F_{XC}$&lt;/span&gt; is omitted, which leaves me in confusion.&lt;/p&gt;&#xA;&lt;p&gt;Where are any of the parts of &lt;span class=&quot;math-container&quot;&gt;$E_C$&lt;/span&gt; in the final XC-energy? Are they contained in &lt;span class=&quot;math-container&quot;&gt;$F_{XC}$&lt;/span&gt;? Why did they not write the form of &lt;span class=&quot;math-container&quot;&gt;$F_{XC}$&lt;/span&gt; into the paper? What am I missing here?&lt;/p&gt;&#xA;" OwnerUserId="3901" LastActivityDate="2021-07-07T09:56:05.823" Title="Why does the PBE XC functional not appear to be a sum of exchange and correlation energy?" Tags="|density-functional-theory|exchange-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6330" PostTypeId="2" ParentId="6323" CreationDate="2021-07-07T08:57:56.930" Score="6" Body="&lt;p&gt;GAMESS also should be able to calculate analytic hessian for the full CI case. From the GAMESS manual:&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;$FORCE group&#xA;&#xA;(optional, relevant for RUNTYP=HESSIAN,OPTIMIZE,SADPOINT)&#xA;&#xA;This group controls the computation of the hessian&#xA;matrix (the energy second derivative tensor, also known&#xA;as the force constant matrix), and an optional harmonic&#xA;vibrational analysis.  This can be a very time consuming&#xA;calculation.  ...&#xA;&#xA;METHOD = chooses the computational method:&#xA;       = ANALYTIC is a fully analytic calculation.  This&#xA;                  is implemented for SCFTYP=RHF, UHF, ROHF,&#xA;                  GVB (for NPAIR=0 or 1, only), &lt;b&gt;and&#xA;                  MCSCF (for CISTEP=ALDET or ORMAS, only)&lt;/b&gt;.&#xA;                  R-DFT and U-DFT are also analytic.&#xA;                  This is the default for these cases.&#xA;       = SEMINUM  does numerical differentiation of&#xA;                  analytically computed first derivatives. ...&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;(I have removed some extra text, emphasis mine)&lt;/p&gt;&#xA;&lt;p&gt;So GAMESS can do analytic hessians with MCSCF (which means CASSCF, which means full CI can be done). The CISTEP keyword just indicates which scheme is used to generate the excited configurations. (ALDET is Ames Lab determinant full CI, and ORMAS is Occupation Restricted Multiple Active Space determinant CI.)&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-07-07T10:05:24.150" LastActivityDate="2021-07-07T10:05:24.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6331" PostTypeId="2" ParentId="6329" CreationDate="2021-07-07T09:56:05.823" Score="6" Body="&lt;p&gt;The final equation you quoted merely serves to define &lt;span class=&quot;math-container&quot;&gt;$F_{XC}$&lt;/span&gt;, which is plotted in Fig. 1 of the article to succinctly illustrate the behavior of the PBE functional as a function of density and density gradient. Without removing the &lt;span class=&quot;math-container&quot;&gt;$\epsilon_X^{unif}(n)$&lt;/span&gt; factor from &lt;span class=&quot;math-container&quot;&gt;$E_{XC}$&lt;/span&gt;, one cannot plot the &lt;span class=&quot;math-container&quot;&gt;$r_s=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_s=\infty$&lt;/span&gt; curves anymore, that's why the authors have to define &lt;span class=&quot;math-container&quot;&gt;$F_{XC}$&lt;/span&gt; and plot it, rather than plotting &lt;span class=&quot;math-container&quot;&gt;$E_{XC}$&lt;/span&gt; itself. The equation is not meant to be an alternative definition of &lt;span class=&quot;math-container&quot;&gt;$E_{XC}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-07T09:56:05.823" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6332" PostTypeId="1" AcceptedAnswerId="6335" CreationDate="2021-07-07T11:50:47.440" Score="10" ViewCount="107" Body="&lt;p&gt;The projector augmented-wave (PAW) method as introduced by &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.50.17953&quot; rel=&quot;noreferrer&quot;&gt;Blöchl&lt;/a&gt; gives an expression for the most general form for the projector functions&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\langle \tilde{p}_i \vert = \sum_j \left( \lbrace \langle f_k \vert  \tilde{\phi}_l \rangle \rbrace \right)_{ij}^{-1} \langle f_j \vert,&#xA;$$&lt;/span&gt;&#xA;&amp;quot;where &lt;span class=&quot;math-container&quot;&gt;$\vert f_j \rangle $&lt;/span&gt; form an arbitrary, linearly independent set of functions&amp;quot;. This statement is given without any further detail.&lt;/p&gt;&#xA;&lt;p&gt;My assumption so far is that this satisfies the condition &lt;span class=&quot;math-container&quot;&gt;$\langle \tilde{p}_i \vert \tilde{\phi}_j \rangle = \delta_{ij}$&lt;/span&gt;. Thus I have tried to plug it in but I can't show the relation. I am confused about several things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Is the summation index &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; the same one as the one of &lt;span class=&quot;math-container&quot;&gt;$\tilde{\phi}_j$&lt;/span&gt; in the orthonormality relation?&lt;/li&gt;&#xA;&lt;li&gt;I take it that the indices &lt;span class=&quot;math-container&quot;&gt;$ij$&lt;/span&gt; denote a matrix element and the power of &lt;span class=&quot;math-container&quot;&gt;$-1$&lt;/span&gt; denotes the inverse. Then where does the condition of linear independence for &lt;span class=&quot;math-container&quot;&gt;$f_j$&lt;/span&gt;  come into play?&lt;/li&gt;&#xA;&lt;li&gt;Is this even the right track?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3901" LastEditorUserId="5" LastEditDate="2021-07-07T17:43:19.663" LastActivityDate="2021-07-07T19:15:57.830" Title="In the PAW-method how does one come up with the most general form for the projector functions?" Tags="|projector-augmented-wave|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6333" PostTypeId="2" ParentId="6252" CreationDate="2021-07-07T15:40:51.393" Score="2" Body="&lt;p&gt;The best start for learning Fortran it to try to ignore the newer languages you have learned.  Fortran is an early language that was very powerful at the time.  It is not &amp;quot;Object Oriented&amp;quot; and is not geared for dealing with bits, bytes, addresses.&#xA;I have taught Assembler, Visual Basic, RPG, PL1, Pascal, Fortran, C, &amp;amp; C++ in colleges. But I will admit that Fortran (IV, 77) was one of my favorites.  Many of these were on the on mainframes.&lt;/p&gt;&#xA;" OwnerUserId="3912" LastEditorUserId="7" LastEditDate="2021-07-07T15:48:19.373" LastActivityDate="2021-07-07T15:48:19.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6335" PostTypeId="2" ParentId="6332" CreationDate="2021-07-07T16:50:54.093" Score="8" Body="&lt;p&gt;You're right that this part is key:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;My assumption so far is that this satisfies the condition &lt;span class=&quot;math-container&quot;&gt;$\langle \tilde{p}_i \vert \tilde{\phi}_j \rangle = \delta_{ij}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To make the notation a bit simpler, let's define &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; as the matrix with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S_{ij} = \langle f_i \vert  \tilde{\phi}_j \rangle\tag{1}.&#xA;$$&lt;/span&gt;&#xA;Its inverse matrix is &lt;span class=&quot;math-container&quot;&gt;$S^{-1}$&lt;/span&gt;. The expression for the projectors is then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \tilde{p}_i \vert = \sum_j (S^{-1})_{ij} \langle f_j \vert,\tag{2}&#xA;$$&lt;/span&gt;&#xA;such that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\langle \tilde{p}_i \vert \tilde{\phi}_j \rangle &#xA;&amp;amp;=\sum_k (S^{-1})_{ik} S_{kj} \tag{3}\\&#xA;&amp;amp;= (S^{-1} S)_{ij} \tag{4}\\&#xA;&amp;amp;= \delta_{ij}.\tag{5}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="1021" LastEditDate="2021-07-07T19:15:57.830" LastActivityDate="2021-07-07T19:15:57.830" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6336" PostTypeId="2" ParentId="4926" CreationDate="2021-07-07T19:37:04.127" Score="5" Body="&lt;p&gt;Your protocol is right and rigorous in the sense as if you don't have the crystal structure of your protein and want to do some predictions, them the only way is using homology modeling.&lt;/p&gt;&#xA;&lt;p&gt;I am not a big fan of homology modeling, so I always recommend to avoid it as possible.&lt;/p&gt;&#xA;&lt;p&gt;My addition will be that, instead using only one resource to model the 3D structure, to use several services combined with different techniques. Then, submit all the structures to services that check the quality of the structures (also using different approaches). Finally, organize the structures using as criteria the one with more successful tests.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-07-07T19:37:04.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6337" PostTypeId="2" ParentId="4850" CreationDate="2021-07-07T20:14:06.590" Score="5" Body="&lt;p&gt;Generally not. The pH difference between the two sides of a membrane can be very noticeable, for example when the membrane is that of a mitochondrion. Actually mitochondria works by actively transporting protons from one side of the membrane to the other side, using the chemical energy released by reducing O2 to H2O, and then use the proton gradient to generate ATP. If you have the same pH on both sides of your mitochondria membranes, you'll die instantly because of a lack of ATP, as will happen if you are poisoned by cyanide.&lt;/p&gt;&#xA;&lt;p&gt;Note that only neutral, relatively hydrophobic small molecules can readily cross the lipid bilayer. H3O+ and OH- are both charged and extremely hydrophilic, so they don't pass through the lipid bilayer at all, that's why the pH of the two sides of a lipid bilayer don't spontaneously equilibrate. To let the pH equilibration to actually happen, you need a &amp;quot;shuttle&amp;quot; molecule, such that both the molecule itself and its conjugate acid/base are hydrophobic (for example, &lt;a href=&quot;https://en.wikipedia.org/wiki/2,4-Dinitrophenol&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/2,4-Dinitrophenol&lt;/a&gt;). The molecule can then carry protons through the membrane and do the equilibration.&lt;/p&gt;&#xA;&lt;p&gt;If you are referring to the protonation states of the part of protein that is within the lipid bilayer (that is the transmembrane structural domains; they are of course dominated by hydrophobic residues, but a stray acidic/basic residue isn't entirely impossible), that's an even more difficult question, as that part of protein cannot readily equilibrate with either side of the membrane. I'm afraid that the protonation states of these residues are dependent on the history of the synthesis of the protein, and cannot be deduced from the protein structure itself. Perhaps someone else may be an expert on this topic and can give a better answer on this.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-07-08T06:54:47.987" LastActivityDate="2021-07-08T06:54:47.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6338" PostTypeId="1" CreationDate="2021-07-08T07:28:07.157" Score="9" ViewCount="3254" Body="&lt;p&gt;I have just started studying DFT. I did some basic calculations using a Windows system. How will Ubuntu help me if I install it on my system? How much space should I allocate on drive for the Ubuntu system as to run it in parallel with Windows?&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2021-07-09T16:35:13.443" LastActivityDate="2021-07-10T13:34:44.463" Title="Is Ubuntu the best option for DFT calculations?" Tags="|density-functional-theory|high-performance-computing|" AnswerCount="5" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6339" PostTypeId="1" CreationDate="2021-07-08T08:12:42.507" Score="6" ViewCount="40" Body="&lt;p&gt;I have been mainly exposed to 2D momentum-space condensed matter models in the context of Berry-related topology. I now want to study models where, if I take a closed loop in momentum space, I will have the possibility of an interband transition governed by selection rules.&#xA;So far, all I have seen are charge-pumping-like effects with the Rice-Mele model (quantized flux pumping after one closed loop trajectory; &lt;a href=&quot;https://arxiv.org/abs/0907.2021&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt;). I have seen some 2D models for excitons as well (&lt;a href=&quot;https://arxiv.org/abs/1709.08310&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt;), but these don't consider a loop explicitly. Additionally, I understand that there is a perspective of &lt;em&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2515-7639/abf0b5/pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;potential virtual transitions&lt;/a&gt;&lt;/em&gt; associated with Berry curvature (due to its inherent interband character). However, I am looking for something more concrete than that.&lt;/p&gt;&#xA;&lt;p&gt;I have read a bit about &lt;a href=&quot;http://www.princeton.edu/%7Emlittman/landau_zener.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Landau-Zener transitions&lt;/a&gt;, but most works I have seen involve the time variable explicitly (&lt;a href=&quot;https://arxiv.org/pdf/1305.0977.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;example of selection rules&lt;/a&gt;). &lt;strong&gt;However, I am looking for an example of a model that studies interband transitions and selections rules in the context of a closed loop in k-space&lt;/strong&gt; (very likely parameterized by parameter &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$(k_x(t),k_y(t))$&lt;/span&gt;. Since I have a ways to go in familiarizing myself with the field, I was hoping someone could suggest a resource that features such a model.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-07-08T14:31:05.387" LastActivityDate="2021-07-08T14:31:05.387" Title="Example of 2D k-space models allowing interband transitions after a closed-loop trajectory?" Tags="|condensed-matter|model-hamiltonians|quantum-mechanics|berry-phase|" AnswerCount="0" CommentCount="4" ClosedDate="2022-08-23T22:16:23.840" ContentLicense="CC BY-SA 4.0" />
  <row Id="6340" PostTypeId="1" AcceptedAnswerId="6348" CreationDate="2021-07-08T09:21:53.450" Score="5" ViewCount="186" Body="&lt;p&gt;I wish to calculate the values of the orbital angular momentum of excited electronic states, using Molpro. So &lt;span class=&quot;math-container&quot;&gt;$\langle L_x \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\langle L_y \rangle$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\langle L_z \rangle$&lt;/span&gt;. (Specifically for my case, I'm looking for the projection on the z-axis in a diatomic molecule. But I guess the answer should apply generally for all projections.) This should ideally be done at the &lt;code&gt;CASSCF&lt;/code&gt; or &lt;code&gt;MRCI&lt;/code&gt; level. But feel free to share procedures if they exist in other programs too.&lt;/p&gt;&#xA;&lt;p&gt;I can find one mention of &lt;a href=&quot;https://www.molpro.com/manual/doku.php?id=program_control&amp;amp;s%5B%5D=gexpec#one-electron_operators_and_expectation_values_gexpec&quot; rel=&quot;nofollow noreferrer&quot;&gt;these operators in the documentation&lt;/a&gt;, called &lt;code&gt;LOP&lt;/code&gt; taken together, or &lt;code&gt;LX&lt;/code&gt;, &lt;code&gt;LY&lt;/code&gt;, &lt;code&gt;LZ&lt;/code&gt;, individually. However they are listed with parity &lt;code&gt;-1&lt;/code&gt;, and: &amp;quot;Expectation values are only nonzero for symmetric operators (&lt;code&gt;parity=1&lt;/code&gt;)&amp;quot;. Still, the electronic state must have some angular momentum. For instance, in &lt;code&gt;CASSCF&lt;/code&gt; I can calculate the &lt;span class=&quot;math-container&quot;&gt;$\langle L_x^2 \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\langle L_y^2 \rangle$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\langle L_z^2 \rangle$&lt;/span&gt; with the card &lt;code&gt;EXPEC2,LXX,LYY,LZZ&lt;/code&gt;. But then the sign of the projected angular momentum is lost, and I wish to compare signs for the different excited states.&lt;/p&gt;&#xA;" OwnerUserId="3536" LastEditorUserId="5" LastEditDate="2021-07-09T10:09:51.427" LastActivityDate="2021-07-09T10:09:51.427" Title="In Molpro, how to calculate the orbital angular momentum?" Tags="|molpro|casscf|mrci|expectation-values|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6341" PostTypeId="2" ParentId="6338" CreationDate="2021-07-08T12:51:10.053" Score="9" Body="&lt;p&gt;As previously commented, any Linux distro will be much better than Windows to run simulations.&lt;/p&gt;&#xA;&lt;p&gt;About your first question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is Ubuntu a better option for DFT calculations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;No, it is not. But there is nothing special about Ubuntu, any Linux distribution would be a better choice than Windows. You can use Ubuntu or other distros like Mint or the father of them, Debian. Also, you can use Fedora, a daughter of RedHat or OpenSUSE. There are many other variants (in this &lt;a href=&quot;https://haydenjames.io/best-linux-distro/&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; you will find 12.)&lt;/p&gt;&#xA;&lt;p&gt;About your second question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How will Ubuntu help me if I install it on my system?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, it will. Normally, Ubuntu will recognize your Windows installation and will suggest you how to partition the hard disk space in order to install it together with Windows. Also, it will setup the boot loader with the two options so you can select at boot.&lt;/p&gt;&#xA;&lt;p&gt;About your third question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How much space should I allocate on drive for the Ubuntu system as to&#xA;run it parallel with Windows.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can have a Linux installation with only the main developer packages (C, C++, and fortran compilers and also Python, etc.) in 5GB-10GB (less than a 16GB memory stick). For that, avoid to use the install recommendation packages and select yourself. Then you can mount your Windows partition and use it to put your working files.&lt;/p&gt;&#xA;&lt;p&gt;My recommendation is to look for the software requirements of your simulation package. You will be free of headache trying to compile/install if the requirements are not fulfilled. Even if you can put your code to work, it is possible that after a system update (that is very common in distros like (or based on) Ubuntu), your software stop working.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-07-10T13:34:44.463" LastActivityDate="2021-07-10T13:34:44.463" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6342" PostTypeId="1" CreationDate="2021-07-08T15:51:11.987" Score="3" ViewCount="303" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/15YPY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/15YPY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/eFyci.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eFyci.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My System is 2H MoS2 unit cell with vacuum. Energy is varied in zig zag form. How can predict the k points from this convergence.&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="3687" LastEditDate="2021-07-10T02:59:09.897" LastActivityDate="2021-07-10T02:59:09.897" Title="How to choose K point from this convergence value" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="9" ClosedDate="2021-12-01T19:32:26.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="6343" PostTypeId="2" ParentId="6252" CreationDate="2021-07-08T19:37:52.460" Score="5" Body="&lt;p&gt;Mastery and minimal effort create a large conflict. It takes significant effort to master a computer language, beyond just learning the syntax. So, I'd first set my expectations that I need to work hard.&lt;/p&gt;&#xA;&lt;p&gt;Next, yes, the previous authors have very sound suggestions and I'll respectfully not repeat them here.&lt;/p&gt;&#xA;&lt;p&gt;One technique I've used in my many decade career (and yes, I did Fortran programming back in 1971), is to take a task for which I already have a sound algorithm and implementation in another language, and implement in the new language. It helps understand syntax and semantics of the new language, in more detail, as it is applied to fundamental constructs - data types, memory management, logic, looping, arrays, structures, functions, I/O, string formatting (and reading and writing and parsing), etc. Running the same program in different languages and then comparing (CPU time, memory usage, I/O, the actual results) between the two, which should be very similar in almost all cases, will illuminate important items for deeper learning when results are vastly different. My favorite piece of code is a raytracer, which I've implemented in Fortran, C, C++, .NET, JAVA, and most recently in GPU coding.&lt;/p&gt;&#xA;&lt;p&gt;My final thought is that much more effort &amp;quot;mastering&amp;quot; the various libraries supplied or available in the langauge (ie, GUI, numerical algorithms, I/O, tasking, memory management, communicating with other running tasks, etc.) takes much more effort than learning the language syntax, and is a worthwhile expenditure of your time and energy. After all, then you are building on the shoulders of those who built the libraries for you.&lt;/p&gt;&#xA;" OwnerUserId="3930" LastActivityDate="2021-07-08T19:37:52.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6344" PostTypeId="2" ParentId="4926" CreationDate="2021-07-09T06:39:26.187" Score="5" Body="&lt;p&gt;In the past I had the same question and after a long search I found that every two year there is a worldwide competition to assess the quality of 3D structure prediction of proteins. In the past the winner was an online services called I-tasser that you can find &lt;a href=&quot;https://zhanglab.dcmb.med.umich.edu/I-TASSER/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I tested it also in the past year with the covid spike protein and after the publication of the experimental 3D structure I compared the 2 structure, finding a very good agreement between the two. I guess it is a nice starting point. You only need the AA sequence and paste it into the online for and let I-tasser do the rest. Hope this help.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2021-07-09T06:39:26.187" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6345" PostTypeId="1" CreationDate="2021-07-09T07:30:26.760" Score="9" ViewCount="669" Body="&lt;p&gt;I want to do some molecular dynamics simulations for silicene with hydrogen and halogen atoms deposited at the surface. Where can I find Stillinger-Weber potentials to use for this? There doesn't seem to be any available in the list of potentials in the LAMMPS installation.&lt;/p&gt;&#xA;" OwnerUserId="347" LastEditorUserId="5" LastEditDate="2021-07-09T16:38:46.520" LastActivityDate="2022-03-19T13:28:05.373" Title="Where to get Tersoff and SW potentials for LAMMPS" Tags="|molecular-dynamics|lammps|surfaces|forcefields|interatomic-potentials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6346" PostTypeId="2" ParentId="6338" CreationDate="2021-07-09T09:16:17.923" Score="6" Body="&lt;p&gt;Well, my advice is to always check benchmarks before doing any consideration. I suggest you to follow the phoronix website because here you can read a lot about Linux benchmark in terms of different distributions, different hardware and also some comparison with windows OS. For example &lt;a href=&quot;https://www.phoronix.com/scan.php?page=article&amp;amp;item=windows11-wsl2-preview&amp;amp;num=1&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; you can find performance benchmarks comparing Ubuntu and Ubuntu on Windows wsl. &lt;a href=&quot;https://www.phoronix.com/scan.php?page=article&amp;amp;item=amd-epyc7543-11way&amp;amp;num=1&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; you can find for example some recent benchmark between different Linux distributions. DFT software are not usually tested, but these tests are good starting point.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2021-07-09T09:16:17.923" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6347" PostTypeId="2" ParentId="6338" CreationDate="2021-07-09T09:39:04.990" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is Ubuntu a better option than Windows for DFT calculations?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;The vast majority of quantum chemistry and solid-state physics software&lt;/a&gt; were designed/developed for Linux. Your &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6338/is-ubuntu-a-better-option-for-dft-calculations#comment12807_6338&quot;&gt;comment&lt;/a&gt; says you're specifically interested in Quantum ESPRESSO, and we recently had someone else complain that Quantum ESPRESSO was not performing the way they expected when using Windows: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6126/5&quot;&gt;Running Quantum ESPRESSO on a GPU in Windows&lt;/a&gt;. The same will be the case for most of the programs listed in the link I provided in the beginning of this paragraph.&lt;/p&gt;&#xA;&lt;p&gt;The most highly upvoted comment on this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1215/5&quot;&gt;What software is available to do molecular dynamics on Windows?&lt;/a&gt; said this very accurately:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Although it's possible to run molecular dynamics on Windows, if you are serious about computational science it's best to get comfortable with Linux. It costs nothing monetarily. Most high-performance computing platforms (clusters and supercomputers) are Linux-based. Most molecular simulation software and ancillary codes (system building and analysis tools) are developed on Linux. Even where Windows compatibility exists, it is often incomplete (some features are missing) or poorly supported.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Another similar question to yours was asked before (and my answer was similar to my answer to you here): &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5010/5&quot;&gt;GUI for DFT calculations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally (since Camps already answered the part in your question about how much space you'll need to allocate for Linux), I'll say that Ubuntu isn't the only option, and that there's some Linux distributions that are specifically designed for matter modeling, and other more general distributions like Fedora which already have a lot of matter modeling software packaged: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1224/5&quot;&gt;Which Linux distribution is best for Matter Modeling?&lt;/a&gt;. Ubuntu does likely have more than 40 million users though (&lt;a href=&quot;https://skeptics.stackexchange.com/a/32413/38337&quot;&gt;Does Ubuntu have 40 million users?&lt;/a&gt;) and by far has the largest number of users out of all Linux distributions, and there's an entire Stack Exchange site called &lt;a href=&quot;https://askubuntu.com/&quot;&gt;Ask Ubuntu&lt;/a&gt; just for Ubuntu, so there's advantages in terms of getting help if you run into any problems. However, if you're considering to build a compute server (see &amp;quot;https://mattermodeling.stackexchange.com/q/5018/5&amp;quot; and &amp;quot;https://mattermodeling.stackexchange.com/q/6165/5&amp;quot; first), the most popular Linux distribution for that purpose would no longer be Ubuntu: Red Hat (not free), CentOS  (basically a free version of Red Hat that was unfortunately discontinued a few months ago) and OpenSUSE (mainly used in Germany) are more popular for that.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-09T09:39:04.990" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6348" PostTypeId="2" ParentId="6340" CreationDate="2021-07-09T10:08:33.963" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;However they are listed with parity &lt;code&gt;-1&lt;/code&gt;, and: &amp;quot;Expectation values are&#xA;only nonzero for symmetric operators (parity=1)&amp;quot;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This matches the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6340/in-molpro-how-to-calculate-the-orbital-angular-momentum#comment12794_6340&quot;&gt;comment by wzkchem5&lt;/a&gt; which suggests that those expectation values, like &lt;span class=&quot;math-container&quot;&gt;$\left\langle \hat{L}_x \right\rangle$&lt;/span&gt; which you correctly found to be listed as &lt;code&gt;-1&lt;/code&gt; in the parity column of the table in the link you provided, will be zero. It may be true that &lt;span class=&quot;math-container&quot;&gt;$\left\langle \hat{L}^2_x \right\rangle$&lt;/span&gt; is not zero, because there's no longer cancellation of positive and negative parts.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-09T10:08:33.963" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6349" PostTypeId="2" ParentId="6338" CreationDate="2021-07-09T10:46:18.490" Score="5" Body="&lt;p&gt;Another advantage of using Linux is that it's more portable if you later end up switching to supercomputing facilities.&lt;/p&gt;&#xA;&lt;p&gt;Most jobs I've been involved with have had just enough shell scripting etc. in there for things to go wrong if not tested on a sufficiently similar system.  Running a long job is no fun if your script copied the wrong input file over, or (if you're queued on a busy supercomputer) if the job script fails on the 2nd line when your turn arrives.  I tend to check basic operation on a desktop, with very coarse parameters, then refine the parameters and launch the job on the cluster.&lt;/p&gt;&#xA;" OwnerUserId="1921" LastActivityDate="2021-07-09T10:46:18.490" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6350" PostTypeId="2" ParentId="4926" CreationDate="2021-07-09T11:26:24.507" Score="6" Body="&lt;p&gt;Here's what I did. Assuming that you have a part of the protein crystal structure.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I have an incomplete structure of the protein. Lets say if I have an amino acid (AA) sequence of 520 (full length), I have the pdb for certain domains which are functionally important. So, I went for homology modelling. I used two predictors &lt;strong&gt;Robetta&lt;/strong&gt; and &lt;strong&gt;tr-Rosetta&lt;/strong&gt;. Each predictor will give 5 models, and score accordingly. Normally the first model of robetta or tr-Rosetta is always the best. But in my experience it is not always the case.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here's what I did to select the best out of 10 models.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As I know the crystal structure of the part of the protein. I compare the &lt;code&gt;radius of gyration&lt;/code&gt;, &lt;code&gt;secondary structure&lt;/code&gt; and &lt;code&gt;root mean square deviations&lt;/code&gt; between the crystal structure (PDB) and the part of the model (Rosetta and tr-Rosetta) whose crystal structure is already known. Then I select the model based on the errors of the measured quantities. I used the priority as follows &lt;code&gt;secondary structure &amp;gt; radius of gyration &amp;gt; RMSD&lt;/code&gt;.  I did this for at least 20 proteins and found that it is not necessarily the first model given by a predictor is always the best. I sometimes find the 5th model is the best. And coming to comparison between &lt;code&gt;Robetta&lt;/code&gt; and &lt;code&gt;tr-Rosetta&lt;/code&gt;, I would say it depends on the protein you are modelling. For example, I modelled a &lt;code&gt;HSP70&lt;/code&gt; chaperone, the Radius of gyration (Rg) given by &lt;code&gt;tr-rosetta&lt;/code&gt; is almost double the Rg given by &lt;code&gt;Robetta&lt;/code&gt;.  In this case, it is very clear that &lt;code&gt;Robetta&lt;/code&gt; did a good job. (Because the models given by tr-Rosetta are like spaghetti, you can clearly know once you see).&lt;/p&gt;&#xA;&lt;p&gt;One more technique you can use to know a good model is from cross linking mass spectrometry. This technique gives a good structural information of which residues are crosslinked by a specific organic molecule. For instance, the commonly used lysine specific reactive organic molecules are &lt;code&gt;disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS(3) )&lt;/code&gt; , By using this chemical, researchers can exactly pinpoint to which lysine residues this DSS has crosslinked. If two lysine residues are crosslinked by a DSS, then it is for sure, they need to be at a certain distance between each other.  The distance normally is 26-30 angstroms. Now you look at your models from &lt;code&gt;Robetta&lt;/code&gt; and &lt;code&gt;tr-Rosetta&lt;/code&gt; and see if this distance criteria is maintained or not. If not, discard the model.&lt;/p&gt;&#xA;&lt;p&gt;As for docking, I used High Ambiguity Driven Docking (HADDOCK), which is a free docking server, which can dock protein-protein, protein-ligand etc..&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="3593" LastEditDate="2021-07-09T11:50:42.557" LastActivityDate="2021-07-09T11:50:42.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6351" PostTypeId="2" ParentId="6338" CreationDate="2021-07-09T14:07:13.770" Score="5" Body="&lt;p&gt;If you want to use quantum chemical programs as packaged for &lt;em&gt;and&lt;/em&gt; distributed by your Linux distribution of choice, the long term support (LTS) releases of the Ubuntu familiy are typically good to familiarize with the program in question, and to perform many types of computation.  If you opt for a light-weight desktop environment (e.g., Xfce as in Xubuntu) instead of GNOME (as in default Ubuntu), a less performant computer may dedicate some resources not used for graphics for the scientific computations ahead.&lt;/p&gt;&#xA;&lt;p&gt;Still assuming you use the program as distributed by the LTS distribution you may become interested in more recent versions of the program in question for that they adjust present / introduce new features, or correct errors.  Then, the lag until a new release of the LTS distribution hopefully including version (&lt;span class=&quot;math-container&quot;&gt;$n + 1$&lt;/span&gt;) of your program of interest may be noticeable.  E.g., still supported Linux Xubuntu 18.04 LTS includes &lt;a href=&quot;https://en.wikipedia.org/wiki/NWChem&quot; rel=&quot;noreferrer&quot;&gt;NWChem&lt;/a&gt; in version 6.6, current Xubuntu 20.04 LTS in version 7.0.0 (&lt;a href=&quot;https://packages.ubuntu.com/search?keywords=nwchem&amp;amp;searchon=names&amp;amp;suite=all&amp;amp;section=all&quot; rel=&quot;noreferrer&quot;&gt;tracker&lt;/a&gt;), while the program (by October 2020) was released as version 7.0.2.  If you report a bug in the corresponding user forums, you may receive an answer in lines of «the issue reported by you (already) was resolved in the past with version X.  Since version X no longer is supported, please update and use version Y instead».&lt;/p&gt;&#xA;&lt;p&gt;This may be an incentive to either a) learn how to compile / install the program from what the developers distribute.  Or b), to use a distribution with a more continious integration and upgrade of the packaged programs, e.g., Linux Debian branch &lt;em&gt;testing&lt;/em&gt;, where you may track which (new) relases are available for you (&lt;a href=&quot;https://tracker.debian.org/pkg/nwchem&quot; rel=&quot;noreferrer&quot;&gt;example&lt;/a&gt; from the &lt;a href=&quot;https://blends.debian.org/debichem/tasks/&quot; rel=&quot;noreferrer&quot;&gt;DebiChem&lt;/a&gt; collection).  You may chose a), b), as well as a) &lt;em&gt;and&lt;/em&gt; b).&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-07-09T14:07:13.770" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6352" PostTypeId="2" ParentId="6345" CreationDate="2021-07-09T14:26:29.330" Score="9" Body="&lt;p&gt;Generally, if you want to perform simulations with some force field, you will have to &lt;strong&gt;search the literature&lt;/strong&gt; for published FFs tailored for your problem. The Stillinger-Weber (SW) model is very popular to describe bulk (diamond) silicon, for which it was designed in the first place. But several reparametrizations have also been published. &lt;strong&gt;If&lt;/strong&gt; you happen to find the publication that matches your interest, you'll have to see if the authors provide a suitable parameter file themselves, or if you can make one yourself based on the published parameters. If you closely follow the &lt;a href=&quot;https://docs.lammps.org/pair_sw.html&quot; rel=&quot;noreferrer&quot;&gt;descriptions in the LAMMPS manual&lt;/a&gt;, this is not too hard for SW. But you will have to run some benchmark calculations before you use it for production simulations.&lt;/p&gt;&#xA;&lt;p&gt;You may also take a look at the &lt;a href=&quot;https://www.ctcms.nist.gov/potentials/&quot; rel=&quot;noreferrer&quot;&gt;NIST potentials database&lt;/a&gt;, which collects many FFs for various systems, most of which are provided in LAMMPS-readable format. If you click on Si, you will find many FFs, some of which are in fact parametrized for silicene in particular (references are also provided for all FFs). I do not see multi-component systems, though, which are generally much harder to parametrize.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2021-07-09T14:26:29.330" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6354" PostTypeId="1" AcceptedAnswerId="6361" CreationDate="2021-07-10T10:00:25.793" Score="9" ViewCount="172" Body="&lt;p&gt;Suppose we want to compute the exact standard molar electronic entropy of helium at a finite but not very high temperature, say &lt;span class=&quot;math-container&quot;&gt;$T = 298.15 \textrm{ K}$&lt;/span&gt;. By &amp;quot;standard&amp;quot; I mean the &lt;a href=&quot;https://en.wikipedia.org/wiki/Standard_state&quot; rel=&quot;nofollow noreferrer&quot;&gt;standard state&lt;/a&gt;, i.e. the helium is an ideal gas at 1 bar, where all interactions between different helium atoms are neglected, or equivalently speaking, the helium is at an infinitesimal pressure and the resulting entropy is converted to 1 bar by applying the ideal gas formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}S_1 - S_0 = R \ln \frac{p_0}{p_1}$$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The molar electronic entropy is given as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{2}&#xA;S_e = -R \sum_i p_i \ln p_i \\&#xA;= -R \sum_i \frac{1}{Q} e^{-\frac{E_i-E_0}{kT}} \ln \frac{1}{Q} e^{-\frac{E_i-E_0}{kT}} \tag{3}\\&#xA;= R \sum_i \frac{1}{Q} e^{-\frac{E_i-E_0}{kT}} (\frac{E_i-E_0}{kT} + \ln Q),\tag{4}&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt; is energy of the electronic state &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; is the partition function:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;Q = \sum_i e^{-\frac{E_i-E_0}{kT}}&#xA;$$&lt;/span&gt;&#xA;Now, for the helium atom, there are an infinite number of electronic states below the first ionization potential of helium, &lt;span class=&quot;math-container&quot;&gt;$I_1$&lt;/span&gt;. Thus,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Q &amp;gt; \sum_i^{+\infty} e^{-\frac{I_1-E_0}{kT}} = +\infty\tag{6}&#xA;$$&lt;/span&gt;&#xA;Consequently, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;S_e &amp;gt; R \sum_i \frac{1}{Q} e^{-\frac{E_i-E_0}{kT}} (\frac{E_0-E_0}{kT} + \ln Q) \tag{7}\\&#xA;= R \sum_i \frac{1}{Q} e^{-\frac{E_i-E_0}{kT}} \ln Q \tag{8}\\ &#xA;= R \ln Q  = +\infty&#xA;\end{align}&lt;/span&gt;&#xA;However, this would mean that the total standard molar entropy of helium is also infinite. Actually we may substitute helium by practically any gaseous molecule, and conclude that the standard molar entropies of all molecular gasses are infinite! Of course the entropy diverges very slowly, because &lt;span class=&quot;math-container&quot;&gt;$e^{-\frac{I_1-E_0}{kT}}$&lt;/span&gt; is extremely small at room temperature and the entropy is the logarithm of the sum, but since I apparently didn't make any approximation, this infinity does pose a theoretic problem.&lt;/p&gt;&#xA;&lt;p&gt;My intuition is that as long as the interactions between the helium atoms are taken into account, the summation becomes finite, however small the interactions are (but I cannot prove this at the moment). But an ideal gas reference state is, by definition, a hypothetical state where the atoms cannot see each other at all, as if the gas is infinitely thin.&lt;/p&gt;&#xA;&lt;p&gt;My questions are thus:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Are the above derivations correct?&lt;/li&gt;&#xA;&lt;li&gt;If yes, does this imply that it is inherently flawed to define the standard molar entropy of a gas using an ideal gas reference state?&lt;/li&gt;&#xA;&lt;li&gt;Are there any alternative definitions of the standard molar entropy of a gas, that can get rid of this divergence? One may think of choosing the reference state as a state with very small but non-zero pressure, small enough so that the effect of intermolecular interaction on translational entropy can be neglected but large enough so that the divergence of the electronic partition function is effectively suppressed. But then, how should one choose the value of the pressure, without introducing arbitrariness into the definition of the standard molar entropy?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastEditorUserId="5" LastEditDate="2021-07-12T06:23:17.267" LastActivityDate="2021-07-12T12:08:29.900" Title="Rigorous definition of electronic entropy" Tags="|statistical-thermodynamics|entropy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6356" PostTypeId="1" CreationDate="2021-07-11T00:32:59.997" Score="18" ViewCount="4022" Body="&lt;p&gt;Suppose I want to calculate the band structure of a material system along a specific high symmetry path in the Brillouin Zone. If the point group of the system is given, how can I easily compute the fractional coordinates of the high symmetry points U, G, W, etc.? Can Pymatgen compute these points? I guess this should be automated. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="3941" LastEditorUserId="5" LastEditDate="2021-07-12T16:40:00.537" LastActivityDate="2022-12-04T13:39:11.573" Title="How to generate the high symmetry paths for band structure calculations?" Tags="|band-structure|python|k-points|brillouin-zone|pymatgen|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6357" PostTypeId="1" AcceptedAnswerId="6471" CreationDate="2021-07-11T01:31:24.227" Score="9" ViewCount="282" Body="&lt;p&gt;I want to simulate the attached model for a Cu NP in Ar using my GPU, but I got erratic results. All looks well when I simulate it in my CPU with the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun --use-hwthread-cpus lmp -in in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and, in my understanding, it should be the same input card for a GPU but executed with the command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lmp -sf gpu -pk gpu 1 -in in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the results look very different between both. What do you think about this?&lt;/p&gt;&#xA;&lt;p&gt;Thanks a lot!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://drive.google.com/file/d/1ozgBJKeGdV7sORw_MYhkGrGVl9C0B534/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/file/d/1ozgBJKeGdV7sORw_MYhkGrGVl9C0B534/view?usp=sharing&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/r79ik.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/r79ik.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="562" LastEditorUserId="5" LastEditDate="2021-07-11T02:51:42.907" LastActivityDate="2021-07-29T19:48:48.527" Title="LAMMPS input card in an NVIDIA GPU" Tags="|molecular-dynamics|lammps|graphical-processing-unit|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6358" PostTypeId="2" ParentId="6356" CreationDate="2021-07-11T05:54:47.633" Score="14" Body="&lt;p&gt;If the crystal unit cell is in a format readable by &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;, then you can use code that looks approximately like so:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase.io import read&#xA;&#xA;&#xA;atoms = read(&amp;quot;myfilename.xyz&amp;quot;)&#xA;bandpath = atoms.cell.bandpath()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This &lt;code&gt;bandpath&lt;/code&gt; object will have the relevant attributes to play with (kpoint coordinates, special point labels, special point coordinates, etc). &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/gettingstarted/tut04_bulk/bulk.html#band-structure&quot; rel=&quot;noreferrer&quot;&gt;This&lt;/a&gt; is a nice intro tutorial on the above process in a bit more detail than my rather minimal code block.&lt;/p&gt;&#xA;" OwnerUserId="512" LastActivityDate="2021-07-11T05:54:47.633" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6360" PostTypeId="2" ParentId="6356" CreationDate="2021-07-11T16:37:50.397" Score="15" Body="&lt;p&gt;If you are really interested in learning how to generate the path, I strongly advice you to avoid using any automatic tool like suggested in previous answers.&lt;/p&gt;&#xA;&lt;p&gt;In the Wiki page entitle &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;noreferrer&quot;&gt;Brillouin zone&lt;/a&gt; you can find the first Brillouin zone for each one of the Bravais lattice. This Wiki is based on the following paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Setyawan, Wahyu; Curtarolo, Stefano (2010). &amp;quot;High-throughput electronic band structure calculations: Challenges and tools&amp;quot;. Computational Materials Science. 49 (2): 299–312 (DOI: &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2010.05.010&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.commatsci.2010.05.010&lt;/a&gt;). &lt;a href=&quot;https://arxiv.org/abs/1004.2974&quot; rel=&quot;noreferrer&quot;&gt;arXiv:1004.2974&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Of course that you also need to go through solid state books like:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Kittel, Charles (1996). Introduction to Solid State Physics. New York: Wiley. ISBN 978-0-471-14286-7.&lt;/li&gt;&#xA;&lt;li&gt;Ashcroft, Neil W.; Mermin, N. David (1976). Solid State Physics. Orlando: Harcourt. ISBN 978-0-03-049346-1.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;After you know the Bravais lattice of your system, you look for the Brillouin zone, then look for the corresponding table with the high symmetry points and then you create your own path. Normally we start from the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point that is the center of the Brillouin zone. The subsequent points are selected maintaining the continuity of the path.&lt;/p&gt;&#xA;&lt;p&gt;For example, if your system has tetragonal symmetry (lets said, it is primitive tetragonal), then the first Brillouin zone will be:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/DkN47.png&quot; width=&quot;300&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;In the caption of the figure, there is a suggestion for the path. If you look carefully, there are three branch: the first one between &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; and Z, a second one between X and R; and finally, a third one between M and A. As you can see, there is a discontinuity between Z and X and between R and M as you have to jump to reach them.&lt;/p&gt;&#xA;&lt;p&gt;Now, that you know the high symmetry points and created the path, you need to know how to generate it. The table bellow has the values of each point (in the reciprocal space) according the cell parameters.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EV7Dc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EV7Dc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, you go to your program and add the path in accordance with its own format.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-07-11T16:37:50.397" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6361" PostTypeId="2" ParentId="6354" CreationDate="2021-07-11T17:58:27.070" Score="5" Body="&lt;p&gt;I'll try to summarize the argument mentioned in the comments from Daniel Schroeder's &lt;em&gt;Introduction to Thermal Physics&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Your derivation is correct within a certain approximation commonly made when dealing with atomic sized systems. Consider an isolated system of an hydrogen atom in thermal equilibrium with a reservoir (which could in principle be the rest of the universe). The Boltzmann factor for an electronic state &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; of the atom arises from the Boltzmann entropy equation for the reservoir:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_R(i)=k\ln(\Omega_R(i))\to\Omega_R(i)=\exp(kS_R(i))\tag{1}$$&lt;/span&gt;&#xA;Where &lt;span class=&quot;math-container&quot;&gt;$S_R(i)$&lt;/span&gt; is the entropy of the reservoir when the atom is in the state &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Omega_R(i)$&lt;/span&gt; is the number of microstates.  The partition function is just the sum of the microstates for each macrostate, &lt;span class=&quot;math-container&quot;&gt;$Q=\sum_i\Omega_R(i)=\exp(kS_R(i))$&lt;/span&gt;. Going forward, I will actually use entropy &lt;em&gt;differences&lt;/em&gt; relative to some reference state in these expressions. This simply corresponds to multiplying the Boltzmann factors (and thus the partition function) by a fixed constant, so it won't affect any of the derived results.&lt;/p&gt;&#xA;&lt;p&gt;To get the expression for the partition function in terms of the electronic energy of the atom, we can use the general relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathrm{d} S_R=T\mathrm{d} U_R+P\mathrm{d} V_R-\mu\mathrm{d} N_R=-T\mathrm{d} E-P\mathrm{d} V_r+\mu\mathrm{d} N_r\tag{2}$$&lt;/span&gt;&#xA;The second equality arises from the fact that any of the changes to the reservoir &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; must be coming at the expense of the single atom subsystem &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. In this case, &lt;span class=&quot;math-container&quot;&gt;$\mu\mathrm{d}N_r=0$&lt;/span&gt; as we are not exchanging this single atom.&lt;/p&gt;&#xA;&lt;p&gt;Here is where we get to the approximation at the root of the divergence you found. Typically, the &lt;span class=&quot;math-container&quot;&gt;$P\mathrm{d} V$&lt;/span&gt; is also neglected because the volume change of an atom becoming excited, and thus the PV work, is typically miniscule in comparison to the electronic energy change. However, this is not always true. Schroeder gives &lt;span class=&quot;math-container&quot;&gt;$a_0n^2$&lt;/span&gt; as a rough approximation of hydrogens radius for an excited state &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, which will lead to significant volume change for very large &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;. By including this term, the contribution of the higher lying Rydberg states to the partition function will rapidly go to zero, allowing the sum to converge.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-12T12:08:29.900" LastActivityDate="2021-07-12T12:08:29.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6362" PostTypeId="2" ParentId="6356" CreationDate="2021-07-12T03:46:08.033" Score="10" Body="&lt;p&gt;Pymatgen can definitely do what you are asking for. You can find several algorithms under the &lt;code&gt;pymatgen.symmetry.kpath&lt;/code&gt; module &lt;a href=&quot;https://pymatgen.org/pymatgen.symmetry.kpath.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I include a minimal example below using the new method from &lt;a href=&quot;https://www.nature.com/articles/s41524-020-00383-7&quot; rel=&quot;noreferrer&quot;&gt;Munro &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; implemented in Pymatgen:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymatgen.core import Structure&#xA;from pymatgen.symmetry.kpath import KPathLatimerMunro&#xA;struc = Structure.from_file('myfilename.cif')&#xA;kpath = KPathLatimerMunro(struc)&#xA;kpts = kpath.get_kpoints()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2021-07-12T06:15:19.857" LastActivityDate="2021-07-12T06:15:19.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6364" PostTypeId="1" CreationDate="2021-07-12T13:58:11.343" Score="7" ViewCount="343" Body="&lt;p&gt;I am simulating &lt;a href=&quot;https://en.wikipedia.org/wiki/Low-energy_electron_diffraction&quot; rel=&quot;nofollow noreferrer&quot;&gt;low energy electron diffraction&lt;/a&gt; (LEED) from a polyfaceted sample. Usually it's a single, well-defined flat crystalline surface.&lt;/p&gt;&#xA;&lt;p&gt;Since low energy electrons (below a few hundred eV) only penetrate a few monolayers, the allowed diffraction spots are governed by the 2D lattice of the surface rather than the 3D bulk.&lt;/p&gt;&#xA;&lt;p&gt;For example, &lt;strong&gt;I needed to generate&lt;/strong&gt; the hexagonal lattice vectors for the four distinct (111) planes of a fcc crystal structure. I've done it brute force by doing 3D rotations while imagining the geometry, but I would like to know if there is a formalism that I can use to do it the &amp;quot;right way&amp;quot; such that can be sure the results are correct and can cite the method in a publication.&lt;/p&gt;&#xA;&lt;p&gt;I'd also like to extend it to the surfaces of (110) and (100) facets.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;From the original question post about (111) only:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we slice the corners off of an fcc cube, the exposed (111) surfaces have hexagonal symmetry and can be described by two lattice vectors (with 3 components each) with &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;=60°.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UuFcU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UuFcU.png&quot; alt=&quot;fcc with corners cut off&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://www.semanticscholar.org/paper/O2-Activation-by-Metal-Surfaces%3A-Implications-for-Montemore-Spronsen/314fb4e96ca02e587cbcd47749b471a122d38fc6&quot; rel=&quot;nofollow noreferrer&quot;&gt;Source&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Opposite corners present identical surfaces, so there will be four unique planes, and if we start with one plane, call it &amp;quot;top&amp;quot; (cube sitting on one corner) then each of the other three will share one hexagonal lattice vector with the first plane.&lt;/p&gt;&#xA;&lt;p&gt;I've drawn them below five atoms long for better visibility.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; Is there a straightforward formalism I can both use to get these four sets of two hexagonal lattice vectors, and also &lt;em&gt;cite&lt;/em&gt;  as a reliable source for it?&lt;/p&gt;&#xA;&lt;p&gt;Of course if it's &amp;quot;trivially obvious&amp;quot; to everyone else besides me, then perhaps a straightforward explanation or short derivation is all I need.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;I think&lt;/em&gt; that all eight of the resulting vectors will be in directions with index triplets that contain (-1, 0, 1) in various arrangements with a factor of &lt;span class=&quot;math-container&quot;&gt;$a/\sqrt{2}$&lt;/span&gt; in front.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/arL8B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/arL8B.png&quot; alt=&quot;image&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://www.researchgate.net/figure/a-A-typical-equilibrated-truncated-octahedron-nanoparticle-Top-view-showing-the-local_fig1_323754335&quot; rel=&quot;nofollow noreferrer&quot;&gt;Generalized nano-thermodynamic model for capturing size-dependent surface segregation in multi-metal alloy nanoparticles&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I've made some &lt;em&gt;ad hoc&lt;/em&gt; progress, four sets of red/green unit vectors (positioned arbitrarily), the black lines are surface normals. But I am sure there's a simpler, straightforward mathematical way that I've missed.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/L7Kdn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/L7Kdn.png&quot; alt=&quot;example&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2023-03-26T03:29:33.803" LastActivityDate="2023-03-26T03:29:33.803" Title="Straightforward formalism to get sets of lattice vectors of fcc (111), (110) and (100) facet surfaces that I can also cite?" Tags="|crystallography|2d-lattice|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6366" PostTypeId="1" AcceptedAnswerId="6368" CreationDate="2021-07-12T17:19:48.547" Score="13" ViewCount="1819" Body="&lt;p&gt;I am trying to understand Quantum ESPRESSO input file, line by line. So far everything seems pretty easy to understand. However, I do not know what &lt;code&gt;occupations='tetrahedra'&lt;/code&gt; means?&lt;/p&gt;&#xA;&lt;p&gt;I saw that it should be used when calculating the density of states, but I do not know why.&lt;/p&gt;&#xA;" OwnerUserId="3945" LastEditorUserId="5" LastEditDate="2021-07-12T17:32:29.083" LastActivityDate="2021-07-13T01:13:12.457" Title="What does occupations='tetrahedra' mean in Quantum ESPRESSO?" Tags="|quantum-espresso|k-points|kohn-sham|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6367" PostTypeId="1" CreationDate="2021-07-12T17:50:42.133" Score="8" ViewCount="353" Body="&lt;p&gt;Right now I'm focused on transition metal dichalcogenides. These compounds in the Brillouin zone have valleys in the valence band and in the conduction band at points K and -K. From what I've seen of the Zeeman effect, as you apply a magnetic field, you break the time reversal symmetry. But in this &lt;a href=&quot;https://www.youtube.com/watch?v=5Sq5dyWdCgs&quot; rel=&quot;noreferrer&quot;&gt;Youtube video&lt;/a&gt; close to the 11:15 minute, they mention that as the K and -K valleys are connected by the time reversal symmetry, so the g-factors are going to be 2 and -2, respectively. I don't quite understand why they say that applying a magnetic field in this case breaks the time reverse symmetry, but at the same time they say that the valleys in K and -K are joined by time reversal symmetry. &lt;strong&gt;It seems a bit contradictory. Could you explain to me why it is not a contradiction?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1AZFr.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1AZFr.png&quot; alt=&quot;Diagram depicting Zeeman effect in K and -K valley excitations&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Zeeman effect contributions image taken from Srivastava, Ajit, Sidler, Meinrad, Allain, Adrien, Lembke, Dominik, Kis, Andras, Imamoğlu, A., &lt;em&gt;Valley Zeeman effect in elementary optical excitations of monolayer WSe&lt;span class=&quot;math-container&quot;&gt;$_\mathit{2}$&lt;/span&gt;&lt;/em&gt;. Nature Physics, 11:141-147, 2015.)&lt;/p&gt;&#xA;" OwnerUserId="1065" LastEditorUserId="5" LastEditDate="2021-07-12T19:33:59.067" LastActivityDate="2021-07-24T18:06:41.753" Title="Valleys and time reversal symmetry (Zeeman effect)" Tags="|quantum-mechanics|k-points|dichalcogenides|magnetic-field|valleytronics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6368" PostTypeId="2" ParentId="6366" CreationDate="2021-07-12T20:45:50.907" Score="12" Body="&lt;p&gt;For the &amp;quot;why&amp;quot; you should use the tetrahedron method when computing the density of states, check out &lt;a href=&quot;https://arxiv.org/abs/2103.03469&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; on exactly that topic! In short, other approaches (e.g. Gaussian smearing) will occasionally obscure (and artificially introduce) some features of the density of states.&lt;/p&gt;&#xA;&lt;p&gt;As for how the method works, quoting from the paper directly about the tetrahedron method:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The tetrahedron method... divides the Brillouin zone into tetrahedra, calculates the eigenenergies at the corners of each tetrahedron, and linearly interpolates the eigenenergies inside of each tetrahedron to perform the integration. The tetrahedron method is reminiscent of the trapezoidal rule for approximating the integral of single-variable functions.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="206" LastEditorUserId="5" LastEditDate="2021-07-13T01:13:12.457" LastActivityDate="2021-07-13T01:13:12.457" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6369" PostTypeId="1" AcceptedAnswerId="6370" CreationDate="2021-07-13T06:49:00.033" Score="11" ViewCount="1237" Body="&lt;p&gt;In German there is the name &amp;quot;Buntmetalle&amp;quot; which means &amp;quot;colorful metals&amp;quot; for &lt;a href=&quot;https://en.wikipedia.org/wiki/Non-ferrous_metal&quot; rel=&quot;nofollow noreferrer&quot;&gt;non-ferrous metals&lt;/a&gt; which are also not &lt;a href=&quot;https://en.wikipedia.org/wiki/Noble_metal&quot; rel=&quot;nofollow noreferrer&quot;&gt;noble metals&lt;/a&gt;:  Cadmium (Cd), Cobalt (Co), Copper (Cu), Nickel (Ni), Lead (Pb), Tin (Sn) and Zinc (Zn)&#xA;I didn't find any equivalent for this in English. Is there such a labeling/categorizing in English at all?&lt;/p&gt;&#xA;" OwnerUserId="3950" LastEditorUserId="5" LastEditDate="2021-07-13T16:04:34.567" LastActivityDate="2021-07-13T17:33:40.830" Title="Is there any specific name for non-ferrous metals which are not noble metals?" Tags="|terminology|alloys|metals|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6370" PostTypeId="2" ParentId="6369" CreationDate="2021-07-13T13:33:21.980" Score="11" Body="&lt;p&gt;I don't think it's ideal, but there is the term &lt;a href=&quot;https://en.wikipedia.org/wiki/Base_metal&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;base metal&amp;quot;&lt;/a&gt;. There are various definitions for what is considered a base metal, but the main noble (or precious) metals are always excluded. Some definitions also exclude ferrous metals. Unfortunately, this variation in meaning means it might be better to just say &amp;quot;non-ferrous, non-noble&amp;quot;, as TheSimpliFire suggested in a comment. If you want to use &amp;quot;base metal&amp;quot; as a term for this specific set of metals, it's probably best to define it yourself, or at least refer to a definition.&lt;/p&gt;&#xA;&lt;p&gt;Wikipedia states (emphasis mine):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In contrast to noble metals, base metals may be distinguished by oxidizing or corroding relatively easily and reacting variably with diluted hydrochloric acid (HCl) to form hydrogen. Examples include iron, nickel, lead and zinc. Copper is also considered a base metal because it oxidizes relatively easily, although it does not react with HCl.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;In mining and economics, the term base metals refers to industrial non-ferrous metals excluding precious metals.&lt;/strong&gt; These include copper, lead, nickel and zinc.[2]&lt;/p&gt;&#xA;&lt;p&gt;The U.S. Customs and Border Protection agency is more inclusive in its definition of commercial base metals. Its list includes—in addition to copper, lead, nickel, and zinc—the following metals: iron and steel, aluminium, tin, tungsten, molybdenum, tantalum, cobalt, bismuth, cadmium, titanium, zirconium, antimony, manganese, beryllium, chromium, germanium, vanadium, gallium, hafnium, indium, niobium, rhenium, and thallium, and their alloys.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Some googling led me to a summary from &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/B0080437516091374&quot; rel=&quot;nofollow noreferrer&quot;&gt;this book chapter&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Base metal is a wide-ranging term that refers either to metals inferior in value to those of gold and silver, or alternatively, to metals that are more chemically active than gold, silver, and the platinum metals (AGI, 1957). Accordingly, a review of base-metal mineralogy would encompass much of the world's metal production and geology. Usage of the term “base metal” in the minerals industry is rather loose, but a common application is to the nonferrous ore metals that include copper, lead, and zinc. Thus, e.g., Kesler (1994) grouped manganese, nickel, chromium, silicon, cobalt, molybdenum, vanadium, tungsten, niobium, and tellurium as ferroalloy metals, and copper, lead, zinc, and tin as base metals.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2021-07-13T17:30:58.210" LastActivityDate="2021-07-13T17:30:58.210" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6371" PostTypeId="2" ParentId="1746" CreationDate="2021-07-13T15:17:49.157" Score="3" Body="&lt;p&gt;The TD-Schrodinger equation is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H(\lambda)|\psi(t)\rangle=i\hbar\frac{\partial}{\partial t}|\psi(t)\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, we just need to plug in \eqref{4} and remove all terms that aren't first-order in &lt;span class=&quot;math-container&quot;&gt;$\dot\lambda$&lt;/span&gt;. Let's start with the left-hand side, since its a little simpler.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}H(\lambda)|\psi(t)\rangle&amp;amp;=e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\bigg[H(\lambda)|n(t)\rangle+\dot\lambda H(\lambda)|\delta n(t)\rangle\bigg]\\ &amp;amp;\overset{\text{First order}}{\to}e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\bigg[\dot\lambda H(\lambda)|\delta n(t)\rangle\bigg]\end{align}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now for the right side, which is a bit more involved:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align} &#xA;i\hbar\frac{\partial}{\partial t}|\psi(t)\rangle&amp;amp;=i\hbar\frac{\partial}{\partial t}e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\bigg[|n(t)\rangle+\dot\lambda|\delta n(t)\rangle\bigg]\\&amp;amp; =i\hbar \Bigg[iA_n(t)|\psi(t)\rangle-iE_n|\psi(t)\rangle+e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\bigg[\frac{\partial}{\partial t}|n(t)\rangle+\ddot\lambda|\delta n(t)\rangle+\dot\lambda\frac{\partial}{\partial t}|\delta n(t)\rangle\bigg]\Bigg]\\&#xA;&amp;amp;\overset{\text{First order}}{\to}i\hbar e^{i\phi(\lambda(t))}e^{-i\gamma(t)}\dot\lambda \Bigg[iA_n(\lambda)|n(t)\rangle-iE_n|\delta n(t)\rangle\rangle+\frac{\partial}{\partial \lambda}|n(\lambda)\rangle\Bigg]&#xA;\end{align}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;As mentioned in the text just before Eqn 3.53, we can make the substitution &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial}{\partial t}|n(t)\rangle=\dot\lambda\frac{\partial}{\partial \lambda}|n(\lambda)\rangle$&lt;/span&gt; using the chain rule to express the derivative in terms of &lt;span class=&quot;math-container&quot;&gt;$\dot\lambda$&lt;/span&gt;. The inconsistent switching between &lt;span class=&quot;math-container&quot;&gt;$|n(t)\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|n(\lambda(t))\rangle$&lt;/span&gt; can make the derivation a bit confusing, but these expression are defined to be equivalent and you can verify that the equations are consistent with either expression for the functional form of &lt;span class=&quot;math-container&quot;&gt;$|n\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Combining these expressions, removing the common factor of &lt;span class=&quot;math-container&quot;&gt;$\dot\lambda e^{i\phi(\lambda(t))}e^{-i\gamma(t)}$&lt;/span&gt;, and separating &lt;span class=&quot;math-container&quot;&gt;$|n\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\delta n\rangle$&lt;/span&gt; terms, we obtain:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(H(\lambda)-E_n)|\delta n\rangle=i\hbar\bigg(\frac{\partial}{\partial \lambda}+iA_n\bigg)|n\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which is just \eqref{5} with the sign of both sides flipped. To get \eqref{6} just requires using the definition &lt;span class=&quot;math-container&quot;&gt;$A_n(\lambda)=\langle n(\lambda)|i\frac{\partial}{\partial \lambda}|n(\lambda)\rangle$&lt;/span&gt;. We can then rearrange the right hand side to be in terms of &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial}{\partial \lambda}|n\rangle$&lt;/span&gt;, which you can succinctly express by introducing &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Q}_n=1-|n\rangle\langle n|$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(H(\lambda)-E_n)|\delta n\rangle=i\hbar\mathcal{Q}_n\frac{\partial}{\partial \lambda}|n\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-13T15:32:35.110" LastActivityDate="2021-07-13T15:32:35.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6372" PostTypeId="2" ParentId="6369" CreationDate="2021-07-13T17:33:40.830" Score="4" Body="&lt;p&gt;Not only do I agree with the comments by TheSimpliFire, S R Maiti, and wzkchem5, that there is likely no word for this in English; I'll also go as far as to say that even the German word you suggested does not &lt;em&gt;precisely&lt;/em&gt; fit your description of being &amp;quot;non-ferrous and non-noble&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&amp;quot;Buntmetalle&amp;quot; just means &amp;quot;colorful metals&amp;quot;.&lt;/strong&gt; &lt;/p&gt;&#xA;&lt;p&gt;The term is applied to non-ferrous metals &lt;em&gt;excluding precious metals&lt;/em&gt;. It so happens that most metals that are usually considered &amp;quot;noble metals&amp;quot; are also usually considered &amp;quot;precious metals&amp;quot;, but the latter two terms are not &amp;quot;rigorously defined&amp;quot;. For example, &lt;a href=&quot;https://www.elsevier.com/books/principles-of-corrosion-engineering-and-corrosion-control/ahmad/978-0-7506-5924-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;page 40 of this 2006 book&lt;/a&gt; includes copper as a &amp;quot;noble metal&amp;quot;, but copper is never considered a &amp;quot;precious metal&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Note that copper (sometimes considered a noble metal) is one of the metals in your list of buntmetalle!&lt;/p&gt;&#xA;&lt;p&gt;Anyon's answer suggesting the term &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6370/5&quot;&gt;&amp;quot;base metals&amp;quot;&lt;/a&gt; is probably the closest you can get, but that term is &lt;em&gt;also&lt;/em&gt; not &amp;quot;rigorously defined&amp;quot; (just like &amp;quot;noble metals&amp;quot;, &amp;quot;precious metals&amp;quot;, and even &amp;quot;buntmetalle&amp;quot;), so it often includes metals like rhenium which is &lt;a href=&quot;https://en.wikipedia.org/wiki/Precious_metal&quot; rel=&quot;nofollow noreferrer&quot;&gt;one of the &lt;em&gt;&lt;strong&gt;most precious&lt;/strong&gt;&lt;/em&gt; metals out of all the precious metals&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-13T17:33:40.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6373" PostTypeId="1" CreationDate="2021-07-13T17:35:12.327" Score="10" ViewCount="1073" Body="&lt;p&gt;I want to know which particular calculations are suitable for each of them.&#xA;Is SIESTA free, as in can you work on it without license. (question is based on the fact for now that all these will be done locally at home and not at institute where such software’s are available)&#xA;If there is some other options available, please let me know.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2021-07-14T12:08:37.550" Title="Quantum espresso vs SIESTA" Tags="|density-functional-theory|quantum-espresso|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6374" PostTypeId="1" AcceptedAnswerId="6388" CreationDate="2021-07-13T20:07:46.957" Score="6" ViewCount="173" Body="&lt;p&gt;I am trying to numerically do calculations using Eq. 8 of &lt;a href=&quot;https://www.pnas.org/content/pnas/108/30/12233.full.pdf#page100&quot; rel=&quot;nofollow noreferrer&quot;&gt;MacDonald's simple model for twisted Bilayer graphene&lt;/a&gt;. I only want to calculate the Berry phase. However, I don't think I have my definitions right (as my band diagram looks very off). Would someone mind clarifying where I went wrong with my definitions and code below? Thanks.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_k=\begin{bmatrix}&#xA;h_k(\theta/2) &amp;amp; T_b &amp;amp; T_{tr} &amp;amp; T_{tl}\\&#xA;T_b^\dagger &amp;amp; h_{k_{b}}(-\theta/2) &amp;amp; 0 &amp;amp; 0 \\&#xA;T_{tr}^\dagger &amp;amp; 0 &amp;amp; h_{k_{tr}}(-\theta/2) &amp;amp; 0 \\&#xA;T_{tl}^\dagger &amp;amp; 0 &amp;amp; 0 &amp;amp; h_{k_{tl}}(-\theta/2)&#xA;\end{bmatrix},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_j = k + q_j$&lt;/span&gt;. Additionally:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;T_1=\begin{bmatrix}&#xA;1 &amp;amp; 1 \\&#xA;1 &amp;amp; 1&#xA;\end{bmatrix},  \text{ } &#xA;T_2=e^{-i G^{(2)'}\cdot d}\begin{bmatrix}&#xA;e^{-i \phi} &amp;amp; 1 \\&#xA;e^{i \phi} &amp;amp; e^{-i \phi}&#xA;\end{bmatrix}, \text{ and } &#xA;T_3=e^{-i G^{(3)'}\cdot d}\begin{bmatrix}&#xA;e^{i \phi} &amp;amp; 1 \\&#xA;e^{-i \phi} &amp;amp; e^{i \phi}&#xA;\end{bmatrix} \text{ (for } \phi = 2\pi/3\text{)}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;h_k(\theta)=-v k \begin{bmatrix}&#xA;0 &amp;amp; e^{i(\theta_k - \theta)} \\&#xA;e^{-i(\theta_k - \theta)}  &amp;amp; e^{-i \phi}&#xA;\end{bmatrix}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In Figure 1, they give the hopping directions of the other Dirac points as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;j &amp;amp;= 1 (\equiv b?) \rightarrow (0,-1) \equiv (q_{x_1},q_{y_1}) \\&#xA;j &amp;amp;= 2 (\equiv tr?) \rightarrow (\sqrt{3}/2,1/2) \equiv (q_{x_2},q_{y_2}) \\&#xA;j &amp;amp;= 3 (\equiv tl?) \rightarrow (-\sqrt{3}/2,1/2) \equiv (q_{x_3},q_{y_3}).&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Below eq. 7, they state that the spectrum is independent of the vector &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$\theta \neq 0$&lt;/span&gt;, and &lt;strong&gt;so I set &lt;span class=&quot;math-container&quot;&gt;$d = (0,0)$&lt;/span&gt;. Is this valid?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore, I set the exponential factor involving &lt;span class=&quot;math-container&quot;&gt;$G\cdot d$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$=1$&lt;/span&gt;. With this interpretation, &lt;span class=&quot;math-container&quot;&gt;$T_1\equiv T_b,T_2\equiv T_{tr}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_3\equiv T_{tl}$&lt;/span&gt; seem pretty clear. &lt;strong&gt;However, is this correct?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Next, I set &lt;span class=&quot;math-container&quot;&gt;$v=1$&lt;/span&gt; (the Dirac velocity). However, I am not sure whether this is justifiable because the authors involve some 'renormalized velocity' in eq. 11, involving a parameter &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. &lt;strong&gt;If I don't care about the analysis in Fig. 4, am I okay with setting &lt;span class=&quot;math-container&quot;&gt;$v=1$&lt;/span&gt;?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, my biggest confusion is with the definition of &lt;span class=&quot;math-container&quot;&gt;$h_i(\theta)$&lt;/span&gt;. Since I have my parameter space as &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt;, am I right in setting &lt;span class=&quot;math-container&quot;&gt;$k=\sqrt{k_x^2+k_y^2}$&lt;/span&gt;? &lt;strong&gt;Since I am taking &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; = twist angle, I leave that as a constant - correct?&lt;/strong&gt;&#xA;&lt;strong&gt;But, how do I define &lt;span class=&quot;math-container&quot;&gt;$\theta_k$&lt;/span&gt;?&lt;/strong&gt; It is defined as the 'momentum orientation relative to the x axis'. My guess was that:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;h_k(\theta/2) &amp;amp;\leftarrow \arctan2(ky+q_{y_0},kx+q_{x_0}) - \theta/2 \\&#xA;h_{k_b}(-\theta/2) &amp;amp;\leftarrow \arctan2(ky+q_{y_1},kx+q_{x_1}) + \theta/2 \\&#xA;h_{k_{t_r}}(-\theta/2) &amp;amp;\leftarrow \arctan2(ky+q_{y_2},kx+q_{x_2}) + \theta/2 \\&#xA;h_{k_{t_l}}(-\theta/2) &amp;amp;\leftarrow \arctan2(ky+q_{y_3},kx+q_{x_3}) + \theta/2,&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where above, I indicated only the argument fed into the function; and &lt;strong&gt;used &lt;span class=&quot;math-container&quot;&gt;$(q_{x_0},q_{y_0}) = (0,0)$&lt;/span&gt;. I assumed this because the authors did not seem to mention this&lt;/strong&gt;. Also, I assumed the 'orientation' meant 'angle', and that it should be calculated with respect to the directional vectors above the horizontal line in this post.&lt;/p&gt;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$-1\leq k_x \leq 1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_y=0$&lt;/span&gt;, I get the following 'band diagram' that is clearly incorrect:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/B52AF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B52AF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My Python code for defining the Hamiltonian is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;t = params[0] # twist angle&#xA;v = 1 # dirac velocity&#xA;k = np.sqrt(kx**2+ky**2)&#xA;&#xA;q1x = 0; q1y = 0&#xA;q2x = 0; q2y = -1&#xA;q3x = np.sqrt(3)/2; q3y = 1/2&#xA;q4x = -np.sqrt(3)/2; q4y = 1/2&#xA;&#xA;tk1 = np.arctan2(ky+q1y,kx+q1x)-t/2&#xA;tk2 = np.arctan2(ky+q2y,kx+q2x)+t/2&#xA;tk3 = np.arctan2(ky+q3y,kx+q3x)+t/2&#xA;tk4 = np.arctan2(ky+q4y,kx+q4x)+t/2&#xA;&#xA;hk = -v*k*np.matrix([[0,np.exp(1j*tk1)],[np.exp(-1j*tk1),0]])&#xA;hkb = -v*k*np.matrix([[0,np.exp(1j*tk2)],[np.exp(-1j*tk2),0]])&#xA;hktr = -v*k*np.matrix([[0,np.exp(1j*tk3)],[np.exp(-1j*tk3),0]])&#xA;hktl = -v*k*np.matrix([[0,np.exp(1j*tk4)],[np.exp(-1j*tk4),0]])&#xA;&#xA;phi = 2*np.pi/3&#xA;G2 = 0  # below eq 7 say G.d = 0&#xA;G3 = 0  # below eq 7 say G.d = 0&#xA;Tb = np.matrix([[1,1],[1,1]])&#xA;Ttr = np.exp(-1j*G2)*np.matrix([[np.exp(-1j*phi),1],[np.exp(1j*phi),np.exp(-1j*phi)]])&#xA;Ttl = np.exp(-1j*G3)*np.matrix([[np.exp(1j*phi),1],[np.exp(-1j*phi),np.exp(1j*phi)]])&#xA;&#xA;zer = np.zeros((2,2))&#xA;H = np.block([[hk,Tb,Ttr,Ttl],&#xA;[Tb.H,hkb,zer,zer],&#xA;[Ttr.H,zer,hktr,zer],&#xA;[Ttl.H,zer,zer,hktl]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any advice? I have indicated my confusion-points in &lt;strong&gt;bold&lt;/strong&gt;. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-07-14T18:31:31.940" LastActivityDate="2021-07-16T00:55:44.077" Title="Help with definitions in k-space twisted bilayer graphene model" Tags="|condensed-matter|quantum-mechanics|model-hamiltonians|berry-phase|graphene|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6375" PostTypeId="1" AcceptedAnswerId="6376" CreationDate="2021-07-13T20:17:43.940" Score="6" ViewCount="59" Body="&lt;p&gt;I am reading through Introduction to Polymer Physics by Doi, and I am studying the concentration fluctuation in polymer solutions, specifically the random phase approximation. For the most part, I understand the logic, until they try to solve for the volume fractions from the following three equations:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\overline{\delta \phi _A (r)} &amp;amp;= -\beta \int dr' S_{AA}^0 (r-r')[u_A(r')+w_A(r')+V(r')]\label{1}\tag{1}\\&#xA;\overline{\delta \phi _B (r)} &amp;amp;= -\beta \int dr' S_{BB}^0 (r-r')[u_B(r')+w_B(r')+V(r')]\label{2}\tag{2}\\&#xA;\end{align}&lt;/span&gt;&#xA;Using the constraint relation &lt;span class=&quot;math-container&quot;&gt;$\phi _A(r) + \phi_B(r) = 1$&lt;/span&gt;, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\overline{\delta \phi _A (r)} + \overline{\delta \phi_B (r)}=0\label{3}\tag{3}$$&lt;/span&gt;&#xA;The objective is to solve the above 3 equations.&#xA;We also have the following definitions:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;w_A(r) &amp;amp;= -z[\epsilon_{AA}\overline{\phi _A(r)}+\epsilon _{AB} \overline{\phi _B (r)}] \label{4}\tag{4}\\&#xA;w_B(r) &amp;amp;= -z[\epsilon _{BA}\overline{\phi_A(r)}+\epsilon _{BB}\overline{\phi_B (r)}]\label{5}\tag{5}&#xA;\end{align}&lt;/span&gt;&#xA;They use Fourier transform to solve these equations and I don't quite understand the process. This is how Doi puts it forward:&#xA;To solve the above equations, we will use the Fourier transform defined as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\overline{\phi _{Aq}}=\int dr e^{iq\cdot r}\overline{\delta \phi _A (r)}=\int dr e^{iq\cdot r}\overline{\phi _A (r)}\label{6}\tag{6}&#xA;\end{align}&lt;/span&gt;&#xA;(And then suddenly) the above equations take the form&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\overline{\phi_{A}} = -\beta S_{AA}^0[u_A-z(\epsilon _{AA}\overline{\phi_A}+\epsilon_{AB} \overline{\phi _B}) +V)]\label{7}\tag{7} \\&#xA;\overline{\phi_{B}} = -\beta S_{BB}^0[u_B-z(\epsilon _{BA}\overline{\phi_A}+\epsilon_{BB} \overline{\phi _B}) +V)]\label{8}\tag{8}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, how did he get to the above equations from the Fourier transforms? I am confused about the math here, if anything.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="7" LastEditDate="2021-07-13T21:04:08.760" LastActivityDate="2021-07-14T19:12:17.903" Title="Solving for the deviation in the polymer volume fraction under the random phase approximation" Tags="|statistical-thermodynamics|polymers|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6376" PostTypeId="2" ParentId="6375" CreationDate="2021-07-13T21:45:17.877" Score="6" Body="&lt;p&gt;Doi makes this slightly more confusing because just after these equations, he writes:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Here for simplicity we have dropped the subscript q.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So all of the pieces of your Eqs \eqref{7} and \eqref{8} are actually the Fourier transforms of the pieces of your \eqref{1} and \eqref{2}, so they should all have q subscripts. Its also common to write Fourier transformed functions as &lt;span class=&quot;math-container&quot;&gt;$\tilde{f}(q)$&lt;/span&gt; to emphasize that it is not the same functional form as &lt;span class=&quot;math-container&quot;&gt;$f(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The reason the integral disappears is actually due to a general result called the &lt;a href=&quot;https://en.wikipedia.org/wiki/Convolution_theorem&quot; rel=&quot;nofollow noreferrer&quot;&gt;Convolution Theorem&lt;/a&gt;. A convolution of two functions &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is defined as &lt;span class=&quot;math-container&quot;&gt;$$f(r)*g(r)\equiv\int f(r-r')g(r')dr'=\int f(r')g(r-r')dr'\tag{1}$$&lt;/span&gt;&#xA;The Convolution theorem states that &lt;span class=&quot;math-container&quot;&gt;$$\mathcal{F}[f(r)*g(r)]=\tilde{f}(q)\cdot \tilde{g}(q)\tag{2}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathcal{F}$&lt;/span&gt; is the Fourier transform. This means convolutions in real space become products in the reciprocal space (and vice versa).&lt;/p&gt;&#xA;&lt;p&gt;Because your \eqref{1} and \eqref{2} have the form of a convolution, their Fourier transforms are just the products of the Fourier transform of &lt;span class=&quot;math-container&quot;&gt;$S_{AA/BB}$&lt;/span&gt; with the Fourier transform of each potential term.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-07-14T19:12:17.903" LastActivityDate="2021-07-14T19:12:17.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6377" PostTypeId="2" ParentId="6373" CreationDate="2021-07-13T22:07:23.973" Score="10" Body="&lt;p&gt;Comparing what each software is capable off, is relative easy: open both webpages and look for feature pages.&lt;/p&gt;&#xA;&lt;p&gt;From SIESTA project &lt;a href=&quot;https://siesta-project.org/siesta/About/overview.html&quot; rel=&quot;noreferrer&quot;&gt;page&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Total and partial energies.&lt;/li&gt;&#xA;&lt;li&gt;Atomic forces.&lt;/li&gt;&#xA;&lt;li&gt;Stress tensor.&lt;/li&gt;&#xA;&lt;li&gt;Electric dipole moment.&lt;/li&gt;&#xA;&lt;li&gt;Atomic, orbital and bond populations (Mulliken).&lt;/li&gt;&#xA;&lt;li&gt;Electron density.&lt;/li&gt;&#xA;&lt;li&gt;Geometry relaxation, fixed or variable cell.&lt;/li&gt;&#xA;&lt;li&gt;Constant-temperature molecular dynamics (Nose thermostat).&lt;/li&gt;&#xA;&lt;li&gt;Variable cell dynamics (Parrinello-Rahman).&lt;/li&gt;&#xA;&lt;li&gt;Spin polarized calculations (collinear or not).&lt;/li&gt;&#xA;&lt;li&gt;k-sampling of the Brillouin zone.&lt;/li&gt;&#xA;&lt;li&gt;Local and orbital-projected density of states.&lt;/li&gt;&#xA;&lt;li&gt;COOP and COHP curves for chemical bonding analysis.&lt;/li&gt;&#xA;&lt;li&gt;Dielectric polarization.&lt;/li&gt;&#xA;&lt;li&gt;Vibrations (phonons).&lt;/li&gt;&#xA;&lt;li&gt;Band structure.&lt;/li&gt;&#xA;&lt;li&gt;Quantum Transport.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;From Quantum-ESPRESSO (QE) &lt;a href=&quot;https://www.quantum-espresso.org/project/what-can-qe-do&quot; rel=&quot;noreferrer&quot;&gt;page&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ground-state calculations.&lt;/li&gt;&#xA;&lt;li&gt;Structural Optimization, molecular dynamics, potential energy surfaces.&lt;/li&gt;&#xA;&lt;li&gt;Electrochemistry and special boundary conditions.&lt;/li&gt;&#xA;&lt;li&gt;Response properties (DFPT).&lt;/li&gt;&#xA;&lt;li&gt;Spectroscopic properties.&lt;/li&gt;&#xA;&lt;li&gt;Quantum Transport.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;em&gt;Personal opinion.&lt;/em&gt; I tested several DFT software for periodical systems. Today, I only use SIESTA and can run simulations in regular desktop (8 cores, 16GB RAM) and even in my notebook (12 cores, 8GB RAM). Recently we run a calculation in QE that failed after one week (in a workstation with 64GB RAM and 32 cores). The same calculation run smoothly in my PC in 30 minutes (8 cores, 16GB RAM).&lt;/p&gt;&#xA;&lt;p&gt;One of the main complain about QE is that it needs huge computational resources: too much RAM and if you don't have enough RAM, too much hard disk space.&lt;/p&gt;&#xA;&lt;p&gt;Taking a careful read about what each software can do, you will find that SIESTA is a little limited compare to QE.&lt;/p&gt;&#xA;&lt;p&gt;About the license type:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;SIESTA: &lt;a href=&quot;https://gitlab.com/siesta-project/siesta/-/blob/master/COPYING&quot; rel=&quot;noreferrer&quot;&gt;GPL open-source&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;QE: &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node6.html&quot; rel=&quot;noreferrer&quot;&gt;GNU General Public License&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-07-14T12:08:37.550" LastActivityDate="2021-07-14T12:08:37.550" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6379" PostTypeId="1" CreationDate="2021-07-14T23:02:57.817" Score="8" ViewCount="104" Body="&lt;p&gt;I am trying to create an &lt;span class=&quot;math-container&quot;&gt;$\ce{LiFePO4}$&lt;/span&gt; crystal in WulffPack. I have the surface energies of seven different surfaces from the paper [1]. When I input the same to WulffPack, it creates a structure comprising of just the lowest energy surface, as shown:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from wulffpack import SingleCrystal&#xA;from ase.io import write&#xA;from ase.build import bulk&#xA; &#xA;surface_energies = {(1, 0, 0): 0.66, (0, 1, 0): 0.64,(0, 0, 1): 0.97, &#xA;                    (1, 0, 1): 0.62, (0, 1, 1): 0.76,(1, 1, 0): 1.30,&#xA;                    (1, 1, 1): 0.85, (2, 0, 1): 0.52, (3, 0, 1): 0.62}&#xA; &#xA;prim = bulk('Li', 'orthorhombic', a=10.4363, b=6.0491, c=4.7546)&#xA;particle = SingleCrystal(surface_energies, prim) &#xA;&#xA;particle.view() &#xA;particle.write('LFP.obj')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ySGEC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ySGEC.png&quot; alt=&quot;LiFePO4_MyStructure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But the structure given in the paper has five surfaces as shown:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/hjuo9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hjuo9.png&quot; alt=&quot;LiFePO4_Wang et.al.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not able to understand why there is a difference, or where I am making a mistake. I would appreciate any kind of help related to this. Thanks!&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;First-principles study of surface properties of LiFePO4: Surface energy, structure, Wulff shape, and surface redox potential&#xA;October 2007 Physical Review B 76(16):165435 DOI: 10.1103/PhysRevB.76.165435&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3960" LastEditorUserId="5" LastEditDate="2021-12-27T04:19:54.800" LastActivityDate="2021-12-27T04:19:54.800" Title="Constructing an anisotropic crystal in WulffPack" Tags="|solid-state-physics|atomic-simulation-environment|wulffpack|" AnswerCount="0" CommentCount="9" ClosedDate="2022-01-14T01:25:35.073" ContentLicense="CC BY-SA 4.0" />
  <row Id="6380" PostTypeId="1" CreationDate="2021-07-15T01:49:02.937" Score="7" ViewCount="48" Body="&lt;p&gt;I've been reading articles about Zeeman's effect on TMDs specifically on WSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. In the article: &lt;a href=&quot;https://www.nature.com/articles/nphys3203.pdf&quot; rel=&quot;noreferrer&quot;&gt;Srivastava, Ajit, Sidler, Meinrad, Allain, Adrien, Lembke, Dominik, Kis, Andras, Imamoğlu, A., Valley Zeeman effect in elementary optical excitations of monolayer WSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. Nature Physics, 11:141-147, 2015&lt;/a&gt; in the first two curves, the blue curve representing the K valley is shifted to the higher energy region while the red curve representing the K' valley is shifted to the lower energy region.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sO7kS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sO7kS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PgY9q.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PgY9q.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, in an article on the same topic: &lt;a href=&quot;https://www.nature.com/articles/nphys3201.pdf&quot; rel=&quot;noreferrer&quot;&gt;Aivazian, G., Zhirui, Gong, Jones, Aaron, Chu, Rui-Lin, Yan, J., Mandrus, D., Zhang, Chuanwei, Cobden, David, Yao, Wang, Xu, X., Magnetic control of valley pseudospin in monolayer WSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. Nature Physics, 11:148-152, 2015&lt;/a&gt; the red line is in the region of higher energy while the blue line is in the region of lower energy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Kxl7q.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Kxl7q.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are the two articles not contradicting each other as it is the same material (WSe&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;) and the applied magnetic field is positive? Which of the two representations is right?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1065" LastActivityDate="2021-07-15T01:49:02.937" Title="Difference between graphics in the Zeeman effect" Tags="|dichalcogenides|magnetic-field|valleytronics|photoluminescence|" AnswerCount="0" CommentCount="2" ClosedDate="2021-11-19T01:38:59.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="6381" PostTypeId="1" AcceptedAnswerId="6410" CreationDate="2021-07-15T10:29:20.107" Score="7" ViewCount="463" Body="&lt;p&gt;I am a newbie to material studio. I have a membrane, coordinates are in pdb format. I am trying to visualize the pores of this membrane. I tried Atoms and Volume surfaces, but the result was that the VdW surfaces were also shown. I also unchecked the VdW surfaces in analysis window, but it still shows. My probe radius is 1 angstrom. Is there anyway that I can just visualize the pores. I am attaching a picture of the settings and my output.&#xA;This is what I am looking for. Figure 1d in &lt;a href=&quot;https://www.nature.com/articles/nmat4638&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/nmat4638&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Rj1hh.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Rj1hh.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tQ9t8.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tQ9t8.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="3593" LastEditDate="2021-07-20T21:42:19.170" LastActivityDate="2021-07-20T21:42:19.170" Title="How to visualize pores using material studio?" Tags="|visualization-software|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6382" PostTypeId="2" ParentId="5012" CreationDate="2021-07-15T13:25:33.167" Score="7" Body="&lt;p&gt;So I have been researching Quantum Dots but I will give you some advice on how could you go about creating your structure using VESTA and add ligands using IQ mol. You should watch this video first - &lt;a href=&quot;https://www.youtube.com/watch?v=KxO5uLsvkRE.%5C&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=KxO5uLsvkRE.\&lt;/a&gt;&#xA;Moreover at the point where the instructor changes the central atom and uses that to create the bonds what you could do is to change atoms in a row and then use some minimum bond length(this you could get from the desired width). &lt;a href=&quot;https://i.stack.imgur.com/sTHZu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sTHZu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I got the above image and I think it looks like a nano rod. Further once you have a long cylindrical shape you could adjust the length, the only idea I have for this is to check the distance between the end points and eliminate the atoms on either side.&lt;br /&gt;&#xA;Totally not an expert but hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2021-07-15T13:25:33.167" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6383" PostTypeId="1" CreationDate="2021-07-15T13:53:21.093" Score="8" ViewCount="1883" Body="&lt;p&gt;I have a query on HSE06 + SOC method in VASP.&lt;/p&gt;&#xA;&lt;p&gt;This is a follow-up question to the comment given for a similar question at:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4269/how-to-carry-out-hse06soc-band-structure-calculation-using-vasp/6378?noredirect=1#comment12890_6378&quot;&gt;How to carry out HSE06+SOC band structure calculation using VASP?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I haven't done HSE+SOC before. I presume the other &lt;code&gt;INCAR&lt;/code&gt; tags, shall be intact while adding the SOC @PBE and SOC @HSE level. Is that right?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Regards&lt;/p&gt;&#xA;" OwnerUserId="1657" LastEditorUserId="5" LastEditDate="2021-08-01T04:01:47.287" LastActivityDate="2021-09-05T02:17:37.100" Title="HSE06+SOC method using VASP" Tags="|density-functional-theory|vasp|spin-orbit-coupling|hse06|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6384" PostTypeId="1" CreationDate="2021-07-15T16:25:33.277" Score="8" ViewCount="215" Body="&lt;p&gt;I am trying to simulate the change in magnetic moments during a ferromagnetic to antiferromagnetic transition.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;MagneticStructureEnumerator(SmFeO3_Mn_prop,&#xA;           default_magmoms={&amp;quot;Sm3+&amp;quot;:0.009 ,&amp;quot;Fe3+&amp;quot;:4.36 ,&amp;quot;Mn3+&amp;quot;:5.0 ,&amp;quot;O2-&amp;quot;:0.173},&#xA;           strategies=('ferromagnetic', 'antiferromagnetic'))       &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;SmFeO3_Mn_prop&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\ce{SmFeO3}$&lt;/span&gt; (&lt;a href=&quot;https://materialsproject.org/materials/mp-24989/&quot; rel=&quot;nofollow noreferrer&quot;&gt;mp-20243&lt;/a&gt; in the Materials Project database) doped with &lt;span class=&quot;math-container&quot;&gt;$\ce{Mn}$&lt;/span&gt; replacing &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt; atoms.&lt;/p&gt;&#xA;&lt;p&gt;However when I apply the &lt;code&gt;MagneticStructureEnumerator&lt;/code&gt; class it returns the message: &lt;code&gt;&amp;lt;pymatgen.analysis.magnetism.analyzer.MagneticStructureEnumerator object at 0x7ff411d6da10&amp;gt;&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;How may I print the generated enumerator?&lt;/p&gt;&#xA;" OwnerUserId="3878" LastEditorUserId="5" LastEditDate="2021-07-16T02:28:54.930" LastActivityDate="2021-07-16T02:28:54.930" Title="Magnetic Transition Pymatgen Error" Tags="|magnetism|pymatgen|anti-ferromagnetic|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6385" PostTypeId="2" ParentId="6384" CreationDate="2021-07-15T17:15:38.960" Score="5" Body="&lt;p&gt;I suspect this is not an error, but just an issue with how you are trying to print it.  The enumerator object is an object, so when you print it attempts to give you information about the enumerator and not the actually enumeration.  You can try to convert it to a list first, then print the enumeration.&lt;/p&gt;&#xA;&lt;p&gt;This still might be difficult however to read, so you might try printing each magnetic structure independently and not all at once.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(list(EnumeratorOfSomeData))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-07-15T17:15:38.960" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6386" PostTypeId="1" CreationDate="2021-07-15T18:33:20.440" Score="10" ViewCount="219" Body="&lt;p&gt;While studying polymer dynamics, one comes across a wide range of correlation functions. A lot of times, we are interested in the Fourier transforms of these functions, as the FT allows us to solve equations which come out of using these correlation functions.&lt;/p&gt;&#xA;&lt;p&gt;Let's take the example of the RDF of a generic bead-spring polymer, where the location of monomer segment &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is denoted by &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_i$&lt;/span&gt;.&#xA;The RDF of the monomer beads is given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$g(\mathbf{r})=\frac{1}{N}\sum_{n=1}^N \sum_{m=1}^N \langle \delta(\mathbf{r}-(\mathbf{R}_m - \mathbf{R}_n)) \rangle \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The FT of &lt;span class=&quot;math-container&quot;&gt;$g(\mathbf{r})$&lt;/span&gt; is given by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$g(\mathbf{q}) = \int d\mathbf{r} e^{i\mathbf{q}\cdot\mathbf{r}}g(\mathbf{r})=\frac{1}{N}\sum _{n=1}^N \sum _{m=1}^N\langle \exp[i\mathbf{q}\cdot(\mathbf{R}_m-\mathbf{R}_n)] \rangle \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The quantity &lt;span class=&quot;math-container&quot;&gt;$g(\mathbf{q})$&lt;/span&gt; can be measured experimentally by SAXS.&lt;/p&gt;&#xA;&lt;p&gt;One application they have in polymer physics of the above quantity is that they calculate the radius of gyration of a polymer, &lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt;, by using the above definition of &lt;span class=&quot;math-container&quot;&gt;$g(\mathbf{q})$&lt;/span&gt;, and Taylor expanding it at small &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;. I don't understand the physical interpretation of what it means to be in the regime of &lt;em&gt;small&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My question is, what exactly is &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; over here? The only time I have seen FT's being used is during functional analysis, or analysis of PDEs/ODEs.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-07-16T02:31:53.560" LastActivityDate="2021-11-12T20:46:11.017" Title="What is the physical meaning of the q in Fourier transforms of correlation functions?" Tags="|statistical-thermodynamics|polymers|fourier-transform|" AnswerCount="1" CommentCount="3" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6387" PostTypeId="2" ParentId="6384" CreationDate="2021-07-15T20:00:22.307" Score="6" Body="&lt;p&gt;Oddly, despite the name, the class doesn't specifically implement any methods to do iteration directly on the object to access the structures. You can see in the &lt;a href=&quot;https://github.com/materialsproject/pymatgen/blob/v2022.0.9/pymatgen/analysis/magnetism/analyzer.py#L625-L1103&quot; rel=&quot;nofollow noreferrer&quot;&gt;source code&lt;/a&gt;, you can see the class doesn't have an &lt;code&gt;__iter__&lt;/code&gt; or &lt;code&gt;__getitem__&lt;/code&gt; method.&lt;/p&gt;&#xA;&lt;p&gt;However, it does have attributes &lt;code&gt;ordered_structures&lt;/code&gt; and &lt;code&gt;ordered_structures_origin&lt;/code&gt;, which are lists of structures and the transformations used to create them respectively.&lt;/p&gt;&#xA;&lt;p&gt;So with your enumerator, you should be able to print them with:&#xA;&lt;code&gt;print(your_enum.ordered_structures)&lt;/code&gt; or&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for struct in your_enum.ordered_structures:&#xA;    print(struct)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wasn't able to find the attributes of the &lt;code&gt;MagneticStructureEnumerator&lt;/code&gt; object in the pymatgen documentation, so figuring out certain features may require looking at the source code until the documentation for some of these objects is more fleshed out (or I may have just missed where these attributes were described).&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-15T20:10:18.567" LastActivityDate="2021-07-15T20:10:18.567" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6388" PostTypeId="2" ParentId="6374" CreationDate="2021-07-16T00:55:44.077" Score="3" Body="&lt;p&gt;I don't think I can use this Hamiltonian to recover the band structure. The band structure should use a tight-binding Hamiltonian with several unit cells. A colleague told me that this Hamiltonian is just for their discussion in Figure 4.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-07-16T00:55:44.077" CommentCount="1" CommunityOwnedDate="2021-07-16T00:55:44.077" ContentLicense="CC BY-SA 4.0" />
  <row Id="6389" PostTypeId="1" CreationDate="2021-07-16T12:21:19.973" Score="14" ViewCount="600" Body="&lt;p&gt;If I want to equilibrate a NPT system until a property reaches its equilibrium value (let’s say the volume V), what is the common practice to have a rough estimate of the total simulation time required?&#xA; &lt;/p&gt;&#xA;&lt;p&gt;Of course you could just do a simulation and check if the value is equilibrated. But I would like to know if there is another method to estimate the number of timesteps needed &lt;em&gt;prior&lt;/em&gt; to the calculation. That would also allow to double check and be able to assert that there is something wrong if a property takes much too long to converge.&#xA; &lt;/p&gt;&#xA;&lt;p&gt;I was thinking the fluctuation dissipation theorem might come in handy in estimating the rate at which my volume is going to relax to its equilibrium value, but I struggle to find a proper formulation.&lt;/p&gt;&#xA;" OwnerUserId="3967" LastActivityDate="2021-07-18T02:17:29.747" Title="MD: How to estimate number of timesteps to converge a property" Tags="|molecular-dynamics|convergence-test|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6390" PostTypeId="1" CreationDate="2021-07-16T16:55:45.217" Score="6" ViewCount="67" Body="&lt;p&gt;I had a question about Haldane's wormhole interpretation (&lt;a href=&quot;https://arxiv.org/pdf/1112.3311.pdf&quot; rel=&quot;noreferrer&quot;&gt;picture below&lt;/a&gt;). I believe he first proposed it in his paper &lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0408417.pdf&quot; rel=&quot;noreferrer&quot;&gt;Berry Curvature on the Fermi Surface: Anomalous Hall Effect as a Topological Fermi-Liquid Property&lt;/a&gt;. To my understanding, this is for 3D band structures, where a gapless point initially gives one Dirac string, which then immediately splits to two Dirac points and creates a Berry flux loop.&lt;/p&gt;&#xA;&lt;p&gt;My question is, let's say we have a 2D model (instead of 3D) - such as gapped graphene or &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.61.2015&quot; rel=&quot;noreferrer&quot;&gt;the Haldane model&lt;/a&gt; with a K and K' point - with a band touching ONLY at K'. Am I correct in saying that:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the Hilbert spaces of the two tori (one torus per band) have a&#xA;wormhole/string there as well (since the gapless point is a source of Berry flux, where the Berry curvature is a dirac delta function)? i.e. this isn't exclusively a 3D&#xA;interpretation?&lt;/li&gt;&#xA;&lt;li&gt;that instead of having a pair of wormholes (Dirac&#xA;point splitting), we have only one source of Berry curvature flux&#xA;(i.e. only one Dirac string connecting points of each torus&#xA;corresponding to the K' point)?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Or, does this picture fail in 2D?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/07p6q.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/07p6q.png&quot; alt=&quot;https://arxiv.org/pdf/1112.3311.pdf&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-07-20T06:10:56.563" Title="Confusions in interpreting Dirac strings (wormholes) in Haldane's Hilbert space picture ft. two tori joined by strings at gapless points" Tags="|condensed-matter|quantum-mechanics|berry-phase|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6391" PostTypeId="1" CreationDate="2021-07-16T18:29:01.157" Score="11" ViewCount="350" Body="&lt;p&gt;While carrying out constant volume simulations, I've observed that sometimes when the gaseous molecules come closer from their initial spacing, an empty space is created in the box. As I should imagine the system in PBC:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;does that mean that there are pockets of material and gaps of vacuum throughout my system in a zoomed out bigger picture?&lt;/li&gt;&#xA;&lt;li&gt;How does this affect the calculation of results on averaging for a continuous system?&lt;/li&gt;&#xA;&lt;li&gt;Should anything be done to prevent such occurrences?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2021-08-24T00:52:13.600" LastActivityDate="2021-08-30T14:19:01.353" Title="What does vacuum signify in the simulation box after the simulation?" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6392" PostTypeId="2" ParentId="6389" CreationDate="2021-07-16T18:30:54.797" Score="10" Body="&lt;p&gt;&lt;strong&gt;tl;dr: simulate for greater than N*period of oscillation&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;To understand how I arrived at this answer consider that properties can be written as a function of the partition function Q.&lt;/p&gt;&#xA;&lt;p&gt;For example, the average value of the volume will be&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\displaystyle \langle V\rangle =\pm {\frac {\partial \ln Q}{\partial \beta P}}.}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The partition function for N identical classical particles can be evaluated as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$Q = \frac{1}{N! \, h^{3N}} \int d^N \textbf{q} \int d^N \textbf{p} \ \exp \Big[ {-\beta \sum \limits_{i=1}^N H(\textbf{q}, \textbf{p})} \Big]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; is Planck's constant, the bolded &lt;span class=&quot;math-container&quot;&gt;$\textbf{q}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\textbf{p}$&lt;/span&gt; are the 3-D position and momentum vectors, respectively, and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{k_B T}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt; is the Boltzmann constant and &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the temperature.&lt;/p&gt;&#xA;&lt;p&gt;This is a 6N dimensional function, which is basically impossible to evaluate for any meaningful system.&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless, we can still learn a bit by considering a model system.&lt;/p&gt;&#xA;&lt;p&gt;Consider a classical simple 1-D harmonic oscillator (HO) with mass &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; and spring constant &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;.&#xA;The hamiltonian for this system is &lt;span class=&quot;math-container&quot;&gt;$H(x, p) = \frac{p^2}{2m} + \frac12 k x^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We an analytically solve this for this :&#xA;&lt;span class=&quot;math-container&quot;&gt;$$Q = \frac{1}{N!}\frac{kT}{\hbar \omega}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But we can also numerically solve for this, which would require that we at least need to sample over the period of the oscillation in &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/k1xjX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k1xjX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Bfypj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Bfypj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Phase space can get pretty tricky, tho. In some cases you can get stuck in a region of phase space which might skew your results. So my formula above isn't a guarantee, more like a lower bound.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-07-16T18:30:54.797" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6393" PostTypeId="2" ParentId="6389" CreationDate="2021-07-16T21:12:15.440" Score="10" Body="&lt;p&gt;On the mathematical side, there exists no algorithm that estimates the time required to converge a property within any predefined accuracy, however low the accuracy is. The reason is simple. Suppose you perform a series of simulations of a liquid, with successively low temperature. When you are above the freezing point of the liquid, your simulation probably well equilibrates within the nanosecond timescale. But as soon as you reach below the freezing point, since the thermodynamically stable phase is now the solid, your property can only be considered converged when the now supercooled liquid freezes - and this may easily take days, even if you are as much as 10 K below the freezing point! So in order to have a time estimate that is always reliable, you have to be able to predict the freezing point of the liquid to arbitrary precision - this holds even if the estimate is only required to be accurate to &lt;span class=&quot;math-container&quot;&gt;$\pm7$&lt;/span&gt; orders of magnitude (from nanoseconds to days)! No matter how accurate your estimate of the freezing point is, your estimate of the equilibration time will fail by tens of orders of magnitude, if your simulation temperature happens to be between your estimate of the freezing point and the true freezing point.&lt;/p&gt;&#xA;&lt;p&gt;The take home message is, any technique that can possibly work, will only work if you are far from a phase transition, and if your initial condition is not in a metastable state. These two conditions should preferably be verified by experimental data of this system and/or related systems.&lt;/p&gt;&#xA;&lt;p&gt;If these two conditions are already shown to hold, the time required to converge the volume can probably be estimated by comparing to literature values of materials that have similar compressibility as your system. Compressibility describes the sensitivity of volume as a function of pressure, and should correlate well with the time required for the volume to equilibrate, since the primary reason for the volume to fluctuate is the local fluctuations of the pressure.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-16T21:12:15.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6394" PostTypeId="1" AcceptedAnswerId="6396" CreationDate="2021-07-17T16:58:12.807" Score="10" ViewCount="945" Body="&lt;p&gt;I am trying to run some coarse-grained simulations of an Intrinsically Disordered Protein (IDP) using the &lt;a href=&quot;http://cgmartini.nl/index.php/tutorials&quot; rel=&quot;nofollow noreferrer&quot;&gt;Martini force field&lt;/a&gt;, and I want to increase the strength of interaction between water and protein. Specifically I want to alter the &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; value to change the Lennard-Jones potential calculation at each update:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V_{\text{LJ}}(r_{ij})=4\epsilon_{ij}\Bigg[\bigg(\frac{\sigma_{ij}}{r_{ij}}\bigg)^{12}-\bigg(\frac{\sigma_{ij}}{r_{ij}}\bigg)^{6}\Bigg]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From my understanding, the potential parameters are stored in this .itp file in the form of an interaction matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;martini_v3.0.b.3.2.itp:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ nonbond_params ]&#xA;    P5    P5  1 4.700000e-01    5.000000e+00&#xA;    P4    P4  1 4.700000e-01    4.750000e+00&#xA;    P2    P2  1 4.700000e-01    4.300000e+00&#xA;    P1    P1  1 4.700000e-01    4.100000e+00&#xA;    N3    N3  1 4.700000e-01    4.100000e+00&#xA;    ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;martini_v2.2.itp&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ nonbond_params ]&#xA;  P5    P5      1   0.24145E-00     0.26027E-02 ; supra attractive&#xA;  SP5   SP5     1   0.10620E-00     0.67132E-03 ; 75supra attractive, s=0.43&#xA;  P4    P4      1   0.21558E-00     0.23238E-02 ; attractive &#xA;  BP4   BP4     1   0.21558E-00     0.23238E-02 ; attractive&#xA;  SP4   SP4     1   0.94820E-01     0.59939E-03 ; 75attractive, s=0.43&#xA;  ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are no headers so I don't know which value is which, but I imagine the first is &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and the second is &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; ? I also can't find what each of the letters represents except for some definitions in the 2008 Martini paper.&lt;/p&gt;&#xA;&lt;p&gt;Do I need to write a parser in python that modifies these column values for the relevant interaction pairs? Or is there an easier way to do this?:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VG8aj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VG8aj.png&quot; alt=&quot;Table of amino acid CG representation s&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3970" LastEditorUserId="7" LastEditDate="2021-07-19T15:13:16.953" LastActivityDate="2021-07-19T15:13:16.953" Title="How can I modify the Martini v2 or v3 force field to increase the Lennard Jones potential well depth (epsilon)?" Tags="|molecular-dynamics|gromacs|forcefields|coarse-grained|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6395" PostTypeId="2" ParentId="6394" CreationDate="2021-07-17T21:10:15.350" Score="7" Body="&lt;p&gt;I believe I have figured it out.&lt;/p&gt;&#xA;&lt;p&gt;For those trying to martinize their all-atom files into coarse grain representations for martini 3, use the following package:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/marrink-lab/vermouth-martinize&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/marrink-lab/vermouth-martinize&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;With respect to modifying the water for IDP simulations, I pulled out the W, SW and TW interactions from the martini v3.0.0 forcefield, like so:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; W    P6  1 4.650000e-01    4.750000e+00&#xA;SW    P6  1 4.350000e-01    3.880000e+00&#xA;TW    P6  1 3.950000e-01    3.410000e+00&#xA; W   SP6  1 4.250000e-01    4.530000e+00&#xA;SW   SP6  1 4.050000e-01    3.730000e+00&#xA;TW   SP6  1 3.780000e-01    3.290000e+00&#xA; W   TP6  1 3.850000e-01    4.630000e+00&#xA;SW   TP6  1 3.750000e-01    3.650000e+00&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The last column is the epsilon value. I saved all these values into a separate file called &lt;code&gt;default-water-ff-params.txt&lt;/code&gt;, and wrote a short script in python:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pandas as pd&#xA;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;#How much to increase the strength? (Between 1 and 1.5 typically)&#xA;scalar = 1.06 #6% increase in strength between water and protein&#xA;&#xA;df = pd.read_csv(&amp;quot;/home/nick/GROMACS/martini3/default-water-ff-params.txt&amp;quot;, delim_whitespace=True, names=['bead-1', 'bead-2', 'x', 'sigma', 'epsilon'])&#xA;&#xA;for index, row in df.iterrows():&#xA;    &#xA;    if 'W' not in row['bead-2']:&#xA;        &#xA;        df.loc[index, 'epsilon'] = row['epsilon'] * scalar&#xA;&#xA;print(df.to_string(index=False))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output from this script is like so:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;bead-1 bead-2  x  sigma    epsilon&#xA;     W     P6  1  0.465   5.996766&#xA;    SW     P6  1  0.435   4.898411&#xA;    TW     P6  1  0.395   4.305046&#xA;     W    SP6  1  0.425   5.719021&#xA;    SW    SP6  1  0.405   4.709039&#xA;    TW    SP6  1  0.378   4.153549&#xA;     W    TP6  1  0.385   5.845268&#xA;    SW    TP6  1  0.375   4.608041&#xA;    ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Make a new copy of the martini_v3.0.0.itp forcefield file and name it something like martini_v3.0.0_WATER-PROTEIN-1.06.itp to specify the increased strength of interaction. Copy the values from the script to replace the originals, and run your MD simulation.&lt;/p&gt;&#xA;&lt;p&gt;It would be good if someone can confirm that this is the right approach. My protein (which in previous sims was very compact) quickly unfolded into a noodle, consistent with experimental data, and the &lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt; fluctuated around the measured value. So, I am pretty sure this changed the forcefield parameters, but would like confirmation that I didn't modify an interaction I shouldn't have.&lt;/p&gt;&#xA;" OwnerUserId="3970" LastEditorUserId="3970" LastEditDate="2021-07-17T21:17:55.560" LastActivityDate="2021-07-17T21:17:55.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6396" PostTypeId="2" ParentId="6394" CreationDate="2021-07-18T00:32:25.697" Score="10" Body="&lt;p&gt;Since you seem to have at least a start on automating the process of modifying the file, I will just address the other two parts of your question: the format of the &lt;code&gt;nonbond_params&lt;/code&gt; section of a GROMACS &lt;code&gt;.itp&lt;/code&gt; file and the meaning of the symbols used in the Martini force field.&lt;/p&gt;&#xA;&lt;h2 id=&quot;gromacs-format-ad5s&quot;&gt;GROMACS format&lt;/h2&gt;&#xA;&lt;p&gt;This is given in the &lt;a href=&quot;https://manual.gromacs.org/documentation/current/reference-manual/topologies/parameter-files.html#non-bonded-parameters&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS manual&lt;/a&gt;. To summarize:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Atom1 Atom2    Func (1)     C6/sigma  C12/epsilon&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first two columns give the types of particles interacting, the third column being 1 means it is a Lennard-Jones interaction. The last columns are the one of two different parameterizations. The interpretation of these values depends on the combination rule specified in the earlier &lt;code&gt;[defaults]&lt;/code&gt; section of the &lt;code&gt;.itp&lt;/code&gt; file. It determines the meaning of the values stored in the these two columns and how to generate missing cross-interactions. If this combination rule equals 1, the next two columns are&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}&#xA;C_{ij}^{(6)}&amp;amp;=4\epsilon_{ij}\sigma_{ij}^6\\&#xA;C_{ij}^{(12)}&amp;amp;=4\epsilon_{ij}\sigma_{ij}^{12}&#xA;\end{align}$$&lt;/span&gt;&#xA;And missing interactions between atoms of different types are formed by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}&#xA;C_{ij}^{(n)}&amp;amp;=\sqrt{C_{ii}^{(n)}C_{jj}^{(n)}}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;A value of 2 or 3 will make the next columns &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, with different rules for creating missing interactions. Combination rule 3 will use the formula above, forming C6/C12 from &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; while combination rule 2 uses the following formulas.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}&#xA;\sigma_{ij}&amp;amp;=\frac{1}{2}(\sigma_{ii}\sigma_{jj})\\&#xA;\epsilon_{ij}&amp;amp;=\sqrt{\epsilon_{ii}\epsilon_{jj}}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe the Martini values are specified as &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and all pairs of interactions are specified, so you should be able to use either 2 or 3 for the combination rule. This may is probably the default setting in these files, so you ideally shouldn't need to change anything.&lt;/p&gt;&#xA;&lt;h2 id=&quot;martini-oer4&quot;&gt;Martini&lt;/h2&gt;&#xA;&lt;p&gt;The atom types are described in [1][2]. The first reference is the original paper, while the 2nd is about new additions in Martini 3.&lt;/p&gt;&#xA;&lt;p&gt;Martini 3 defines five main types of coarse grained sites: Q (charged), P (polar), N (nonpolar), C (apolar), and W (water). Each of these has further subtypes depending on what particular atoms are included in the site and their relative interaction energy. They generally map 4 atoms to a site, but the S (small) and T (tiny) prefixes denote 3:1 and 2:1 mappings for a slightly less coarse depiction. The LJ &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; values among all these CG sites were reparameterized in Martini 3 for each possible interaction. Note, if you wind up working with Martini 2, there was no W site and instead water was included in the P group (P4 specifically).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Siewert J. Marrink, H. Jelger Risselada, Serge Yefimov, D. Peter Tieleman, and Alex H. de Vries &lt;em&gt;The MARTINI Force Field:  Coarse Grained Model for Biomolecular Simulations&lt;/em&gt;&#xA;The Journal of Physical Chemistry B 2007 111 (27), 7812-7824&#xA;DOI: 10.1021/jp071097f&lt;/li&gt;&#xA;&lt;li&gt;Souza, P.C.T., Alessandri, R., Barnoud, J. et al. &lt;em&gt;Martini 3: a general purpose force field for coarse-grained molecular dynamics&lt;/em&gt;. Nat Methods 18, 382–388 (2021). &lt;a href=&quot;https://doi.org/10.1038/s41592-021-01098-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/s41592-021-01098-3&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-18T15:34:05.990" LastActivityDate="2021-07-18T15:34:05.990" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6397" PostTypeId="2" ParentId="6389" CreationDate="2021-07-18T02:17:29.747" Score="6" Body="&lt;p&gt;I wasn't going to answer, because there is no answer, but, anyways...&lt;/p&gt;&#xA;&lt;h2 id=&quot;first-common-practice-is&quot;&gt;First: common practice is...&lt;/h2&gt;&#xA;&lt;p&gt;Common practice is to frequently measure the property you are after, as well as others, such as internal energy, density and make a plot. The property will fluctuate but eventually reach an equilibrium that is easy for the eye to spot on a plot. Or, use the maths as Chodera has done &lt;a href=&quot;https://www.biorxiv.org/content/10.1101/021659v5&quot; rel=&quot;noreferrer&quot;&gt;paper here, open access, thanks BioRxiv&lt;/a&gt;, and let the computer tell you when you have reached equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;This is what is done. either manually or algorithmically check that the property is fluctuating about some mean value with a standard deviation you would consider indicative of equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;This, however, doesn't tell you how long it will take, it only tells you how long it took.&lt;/p&gt;&#xA;&lt;h2 id=&quot;second&quot;&gt;Second:...&lt;/h2&gt;&#xA;&lt;p&gt;The idea I propose, which is crude, possibly too crude, is a rather simple one...&lt;/p&gt;&#xA;&lt;p&gt;If you know what something value is, and you know its rate of change, and you know where you want it to be, you can figure out how long it will take. The problem is really knowing the rate of change. If we take a first order expansion of pressure as a (made up) function of time we could say we have&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;P_{\rm equilibrium}(t) = P_{\rm current}(t_{curr}) + \left(\frac{\partial P}{\partial t}\right)_{t_{curr}} \Delta t&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It would be simple in theory to estimate the rate of change of pressure by measuring the pressure at two different time steps&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\left(\frac{\partial P}{\partial t}\right)_{t_{curr}} \approx \frac{P_2 - P_1}{t_2 -t_1}&#xA;\end{equation}&lt;/span&gt;&#xA;So you could rearrange for the time&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \Delta t = \frac{P_{equil} - P_{curr}}{\frac{P_2 - P_1}{t_2 -t_1}}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You could probably replace P for pressure with P for property.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately this probably won't work, particularly in the case of pressure, since instantaneous pressure can jump wildly. You would need to calculate the rate of change many times and take the average.&lt;/p&gt;&#xA;&lt;p&gt;Another reason it likely wouldn't be that accurate would be that the rate of change would probably not be constant. It would be like when a download says 5 minutes remaining, and then in 1 minute it says 10 minutes remaining, and then in another minute, 30 minutes remaining, and then in another minute Download Complete.&lt;/p&gt;&#xA;&lt;p&gt;Anyways, that is a thought I had.&lt;/p&gt;&#xA;&lt;p&gt;In the event you were doing an NPT and wanted to guess what the volume would be at equilibrium, you could probably apply chain rule, and come up with a scheme, where there would be a partial derivative that is essentially the compressibility factor.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2021-07-18T02:17:29.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6398" PostTypeId="1" AcceptedAnswerId="7041" CreationDate="2021-07-18T13:59:59.027" Score="9" ViewCount="730" Body="&lt;p&gt;I am studying an IDP with a lot of helical secondary structure, and trying to find a trajectory that I can use as an ensemble that fits my SAXS data. My starting models are the output from the &lt;a href=&quot;https://robetta.bakerlab.org/&quot; rel=&quot;noreferrer&quot;&gt;Robetta prediction server&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am converting the IDP to a coarse-grained model so I can let the simulation run for ~&lt;span class=&quot;math-container&quot;&gt;$10\mu s$&lt;/span&gt;. In the process of converting it, I use &lt;a href=&quot;https://github.com/marrink-lab/vermouth-martinize&quot; rel=&quot;noreferrer&quot;&gt;martinize2&lt;/a&gt;. The python script takes the .pdb file, an output file name, and a pointer to the dssp binary (which I have looked everywhere for and haven't been able to find an 'official' source...).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;martinize2 -f ../data/pdb/Robetta2.pdb -x cg.gro -o topol.top -dssp /usr/local/bin/dssp&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I run martinize2.py without specifying the -dssp parameter, the script runs fine and outputs my coarse grained model. If I specify the binary (I have probably tried 3 different versions of dssp), or &lt;a href=&quot;https://www3.cmbi.umcn.nl/xssp/output/pdb_file/dssp/d6a806e6-d0bc-4c1c-b7cc-ec59f723ca61&quot; rel=&quot;noreferrer&quot;&gt;specify -ss using the output from a dssp webserver&lt;/a&gt;, I will get different errors.&lt;/p&gt;&#xA;&lt;p&gt;Am I okay to exclude the dssp parameter? Will my coarse grain model have the appropriate constraints for helical secondary structure from the PDB file? What is dssp even for in this context?&lt;/p&gt;&#xA;&lt;p&gt;EXAMPLES OF ERRORS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WARNING - unknown-input - Could not identify the modifications for residues ['ALA190'], involving atoms ['3059-3HB']&#xA;    File &amp;quot;/home/nick/.local/lib/python3.8/site-packages/vermouth/dssp/dssp.py&amp;quot;, line 214, in run_dssp&#xA;        raise DSSPError(message.format(err=process.stderr, file=tmpfile_name))&#xA;    vermouth.dssp.dssp.DSSPError: DSSP encountered an error. The message was DSSP could not be created due to an error:&#xA;    empty protein, or no valid complete residues&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;File &amp;quot;/home/nick/.local/lib/python3.8/site-packages/vermouth/dssp/dssp.py&amp;quot;, line 214, in run_dssp&#xA;    raise DSSPError(message.format(err=process.stderr, file=tmpfile_name))&#xA;vermouth.dssp.dssp.DSSPError: DSSP encountered an error. The message was Error parsing PDB at line 1&#xA;Error trying to load file &amp;quot;/home/nick/GROMACS/projects/CG-4/dssp_in_i6lpkoe1.pdb&amp;quot;&#xA;Expected record CRYST1 but found ATOM&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;File &amp;quot;/home/nick/.local/lib/python3.8/site-packages/vermouth/dssp/dssp.py&amp;quot;, line 557, in run_system&#xA;    raise ValueError(&#xA;ValueError: The length of the sequence (13) does not match the number of residues in the selection (227).&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3970" LastEditorUserId="5" LastEditDate="2021-08-24T00:49:02.390" LastActivityDate="2021-11-10T19:21:21.130" Title="What is the purpose of DSSP when using martinize2?" Tags="|gromacs|biomaterials|structural-biology|coarse-grained|martini|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6399" PostTypeId="1" AcceptedAnswerId="6400" CreationDate="2021-07-19T04:55:18.177" Score="11" ViewCount="663" Body="&lt;p&gt;Recently, I have got to learn that if time-reversal symmetry and inversion symmetry are present simultaneously in the system we have the following conditions on energy of Bloch's states:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{n,\chi }(\overrightarrow{k})=E_{n,-\chi }(\overrightarrow{-k})\:\:\:\:\:\:(time\: reversal)$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_{n,\chi }(\overrightarrow{k})=E_{n,\chi }(\overrightarrow{-k})\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:(inversion)$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Rightarrow E_{n,-\chi }(\overrightarrow{k})=E_{n,\chi }(\overrightarrow{k})\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where, &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; represents the spin-up, and &lt;span class=&quot;math-container&quot;&gt;$-\chi$&lt;/span&gt; represents the spin-down electronic states. The third equation is the consequence of the first two equations. This implies that for each band-index(&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;), the energy of spin-up and spin-down electronic states are degenerate at a particular &lt;span class=&quot;math-container&quot;&gt;$\overrightarrow{k}$&lt;/span&gt; in momentum space.&lt;/p&gt;&#xA;&lt;p&gt;Does, this mean if we perform the spin polarised DFT calculation on any system, in which we account for up and down electronics states differently, it breaks the time-reversal symmetry of the system?&lt;/p&gt;&#xA;&lt;p&gt;If the system is non-magnetic, do we get the same band structure for spin-up and spin down electrons if spin polarised DFT calculation is performed? Hence the TRS is not broken?&lt;/p&gt;&#xA;&lt;p&gt;Please clarify my doubts!&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1361" LastEditDate="2021-07-19T05:17:22.637" LastActivityDate="2021-07-19T08:40:11.340" Title="Does the spin polarised DFT calculation mean broken time reversal symmetry?" Tags="|density-functional-theory|band-structure|symmetry|spin-polarization|topological-matter|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6400" PostTypeId="2" ParentId="6399" CreationDate="2021-07-19T08:40:11.340" Score="10" Body="&lt;p&gt;Yes, broken symmetry solutions do break time-reversal symmetry, and that's one of the reasons why they are unphysical when the total magnetic moment of the system is 0 (although they are physical when the total magnetic moment is not 0, due to spin polarization). The reason is that, suppose you have a spin polarized &lt;span class=&quot;math-container&quot;&gt;$M_S=0$&lt;/span&gt; state, then if you flip the spin of every electron, you get another spin polarized solution with the same energy. But the new state has the same symmetry as the original state, so the two states will generally mix, and since they have the same energy, they will mix in a 1:1 ratio, giving an in-phase combination and an out-of-phase combination. In both linear combinations, the spin densities of the two states cancel out, and you obtain two spin-unpolarized, yet multiconfigurational states.&lt;/p&gt;&#xA;&lt;p&gt;The very reason that one uses spin-polarized DFT is to get correct energetics, e.g. correct &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; parameters. This is related to the size inconsistency of spin-unpolarized DFT. E.g. consider an infinitely stretched &lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt; molecule. If you do a spin-unpolarized DFT calculation, you retain time-reversal symmetry but get an energy that is higher than the sum of two &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; atoms; yet if you do a spin-polarized DFT calculation, you get the same energy as the sum of two &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; atoms, but you break time-reversal symmetry. Usually energies are more important than time-reversal symmetry, so people usually prefer to do spin-polarized calculations (whenever the system is so large that beyond-DFT approaches are not feasible), and if necessary, qualitatively or semiquantitatively discuss the changes of the result if we could restore the time-reversal symmetry. There is a nice &lt;a href=&quot;http://dx.doi.org/10.1021/cr200107z&quot; rel=&quot;noreferrer&quot;&gt;review&lt;/a&gt; by Weitao Yang et al. on this topic.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-19T08:40:11.340" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6401" PostTypeId="1" AcceptedAnswerId="6402" CreationDate="2021-07-19T09:05:17.280" Score="10" ViewCount="1930" Body="&lt;p&gt;I am interested in converting the one-particle reduced matrix (rdm1) from the molecular orbital (M.O.) basis to the atomic orbital (A.O.) basis. Is the following method correct (in an identical fashion to how one converts the Fock matrix basis: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1540/how-to-calculate-the-fock-matrix-in-the-molecular-orbital-basis-pyscf&quot;&gt;How to calculate the Fock matrix in the molecular orbital basis PySCF?&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;rdm1_ao = C @ rdm1_mo @ C.T&#xA;rdm1_mo = C.T @ rdm1_ao @ C&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="786" LastActivityDate="2021-07-20T23:41:14.377" Title="Convert reduced density matrix from M.O. to A.O. basis" Tags="|quantum-chemistry|hartree-fock|pyscf|reduced-density-matrix|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6402" PostTypeId="2" ParentId="6401" CreationDate="2021-07-19T10:29:43.113" Score="13" Body="&lt;p&gt;Only the first line is correct, as long as the AO basis is not orthogonal.&lt;/p&gt;&#xA;&lt;p&gt;The point is: the AO &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; MO transformations of density matrices and Fock matrices require different formulas. For the Fock matrix the formulas are&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;F_{MO} &amp;amp;= C^T F_{AO} C \tag{1}\\&#xA;F_{AO} &amp;amp;= SC F_{MO} C^TS \tag{2}&#xA;\end{align}&lt;/span&gt;&#xA;While for the density matrix, they are&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;D_{MO} &amp;amp;= C^TS D_{AO} SC \tag{3}\\&#xA;D_{AO} &amp;amp;= C D_{MO} C^T \tag{4}&#xA;\end{align}&lt;/span&gt;&#xA;Herein &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the AO overlap matrix, and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is the MO coefficient matrix. The condition that MOs are orthonormal is utilized, otherwise one has to include the MO overlap matrix as well.&lt;/p&gt;&#xA;&lt;p&gt;The reason for this difference is that, when we talk about the Fock matrix under some basis and the density matrix under some basis, we are talking about different things. The Fock matrix elements under a basis, no matter whether the basis is AO or MO, are the matrix elements of an operator, namely the Fock operator. Thus we can say, e.g. the diagonal elements of the AO Fock matrix are the energy expectation values of AOs. By contrast, for the density matrix, only the MO basis matrix elements are the matrix elements of an operator (the occupation number operator), but the AO basis matrix elements do not admit the same interpretation. We cannot say that the diagonal elements of the AO density matrix are the expectation values of the occupation numbers of AOs, because they can be larger than 2. Conceptually that explains the difference between the transformation rules of the density matrix and the Fock matrix. Actually proving the formulas is easier, by applying &lt;span class=&quot;math-container&quot;&gt;$FC=SC\epsilon$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C^TSC=I$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$D=CnC^T$&lt;/span&gt; etc.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="142" LastEditDate="2021-07-20T23:41:14.377" LastActivityDate="2021-07-20T23:41:14.377" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6403" PostTypeId="1" CreationDate="2021-07-19T11:38:47.930" Score="9" ViewCount="1052" Body="&lt;p&gt;How should I calculate lattice thermal conductivity in Quantum ESPRESSO? I have installed phonopy. My Linux distribution is Ubuntu.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2021-07-31T00:34:30.000" LastActivityDate="2023-01-19T09:51:33.383" Title="Calculating lattice thermal conductivity using Quantum ESPRESSO and phonopy" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|phonopy|thermal|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6404" PostTypeId="5" CreationDate="2021-07-19T15:17:20.443" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-19T15:17:20.443" LastActivityDate="2021-07-19T15:17:20.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6405" PostTypeId="4" CreationDate="2021-07-19T15:17:20.443" Score="0" Body="For models of molecular/biomolecular systems that reduce complexity by using a simplified representation of groups of atoms. One common example is the Martini force field" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-19T15:17:20.443" LastActivityDate="2021-07-19T15:17:20.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6406" PostTypeId="1" AcceptedAnswerId="6414" CreationDate="2021-07-19T17:23:17.937" Score="7" ViewCount="465" Body="&lt;p&gt;I am attempting to calculate the driving force of nucleation for several different precipitate phases using TC-Python. To this I want to suspend all phases, except for the matrix phase (e.g. FCC_L12). Then I want to set the precipitate phase of interest to be dormant (so the driving force can still be calculated).&lt;/p&gt;&#xA;&lt;p&gt;Below is an example of what my current approach looks like. The issue is that Thermo-Calc will automatically generate several FCC composition sets (e.g. &amp;quot;FCC_L12#2&amp;quot;, &amp;quot;FCC_L12#3&amp;quot;, etc.), but I only want one of these composition sets to be active (as the matrix). I don't know how to suspend certain composition sets and allow others. Is this possible to do in TC-Python?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with TCPython() as session:&#xA;    system=(session.disable_caching()&#xA;           .select_database_and_elements(database_name, elements)&#xA;           .get_system())&#xA;           &#xA;    calc=(system.with_single_equilibrium_calculation()&#xA;         .with_options(SingleEquilibriumOptions()&#xA;         .enable_approximate_driving_force_for_metastable_phases())&#xA;         .enable_global_minimization())&#xA;    calc.set_condition(ThermodynamicQuantity.temperature(), temp)&#xA;    for el_indx in range(len(elements)):&#xA;        calc.set_condition(ThermodynamicQuantity&#xA;             .mole_fraction_of_a_component(elements[el_indx]), comps[el_indx])&#xA;&#xA;    calc.set_phase_to_suspended(&amp;quot;*&amp;quot;)&#xA;    calc.set_phase_to_entered(&amp;quot;FCC_L12&amp;quot;, 0)&#xA;    calc.set_phase_to_dormant(precip_phaseName)&#xA;&#xA;    calc_result=calc.calculate()&#xA;    drivingForce = calc_result.get_value_of('DGM(' + precip_phaseName + ')')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="7" LastEditDate="2021-07-19T19:05:39.757" LastActivityDate="2023-08-22T16:08:02.127" Title="Thermo-Calc: how to suspend specific composition sets?" Tags="|python|gibbs-free-energy|calphad|thermo-calc|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6407" PostTypeId="2" ParentId="6296" CreationDate="2021-07-20T06:03:28.870" Score="4" Body="&lt;p&gt;I think I figured this out. For most practical purposes, I think it is fine to just choose &lt;span class=&quot;math-container&quot;&gt;$-\pi\leq k_x\leq \pi$&lt;/span&gt; and  &lt;span class=&quot;math-container&quot;&gt;$0\leq k_y\leq \pi$&lt;/span&gt; (half-BZ, with exact ranges depending on the model). I think I over-complicated the authors' work. It is unlikely that the vortices/singularities will occur near the boundary of the chosen region. So, I can just take the difference between the Berry connection and curvature integrals. If the singularities do occur near the boundary, I think it is okay to offset the region of integration in a consistent manner to avoid having to choose the region of integration so carefully as in Figure 1. Someone please correct me if I am wrong. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-07-20T06:03:28.870" CommentCount="0" CommunityOwnedDate="2021-07-20T06:03:28.870" ContentLicense="CC BY-SA 4.0" />
  <row Id="6408" PostTypeId="2" ParentId="6390" CreationDate="2021-07-20T06:10:56.563" Score="2" Body="&lt;p&gt;I found the following slides helpful: &lt;a href=&quot;https://physics.princeton.edu//%7Ehaldane/talks/dirac.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://physics.princeton.edu//~haldane/talks/dirac.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are my answers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Yes. From what I understood, the above is not necessarily a 3D effect. The wormholes appear only at gapless points, so we can expect only one Dirac string in my example.&lt;/li&gt;&#xA;&lt;li&gt;Partly correct. We have only one wormhole from the gapless point. However, there may be other non-singular sources of Berry curvature flux, where the curvature may be peaked at the other valley. I do not know the extent to which one may consider a non-singular region a source of flux vs not.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Someone please feel free to correct me if anything above is off. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-07-20T06:10:56.563" CommentCount="0" CommunityOwnedDate="2021-07-20T06:10:56.563" ContentLicense="CC BY-SA 4.0" />
  <row Id="6409" PostTypeId="2" ParentId="4926" CreationDate="2021-07-20T08:07:03.697" Score="6" Body="&lt;p&gt;I'm adding another answer because I recently find these news. The machine learning-based methods alphafold and rosettafold were recently released on github. Someone has just implemented it in Google colab as Jupiter notebook that you can simply reuse with your colab account. The only thing that you need to do is change the AA sequence. It seems that in the recent CASP edition alphafold was able to gain the first place as the best structure prediction method. You can find all these informations and code in this &lt;a href=&quot;https://twitter.com/sokrypton/status/1415998861789831175?s=19&quot; rel=&quot;noreferrer&quot;&gt;tweet&lt;/a&gt;. You can run different prediction software  with different methods and the compare the results. I think this is the best way to understand if the structures you obtained are completely wrong or meaningful.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2021-07-20T08:07:03.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6410" PostTypeId="2" ParentId="6381" CreationDate="2021-07-20T09:57:02.277" Score="4" Body="&lt;p&gt;Finally got the solution to visualize pores of a membrane.&lt;/p&gt;&#xA;&lt;p&gt;The first thing you need to do is to check your lattice parameters. I had a membrane of &lt;code&gt;110*110*70&lt;/code&gt; angstroms, but the pdb file contains the dimensions as &lt;code&gt;120*120*100&lt;/code&gt;. This is the main issue for me.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 1&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Change the lattice parameters here, &lt;code&gt;build -&amp;gt; build crystal -&amp;gt; options -&amp;gt; lattice parameters&lt;/code&gt; (check your lattice parameters) and click &lt;code&gt;apply&lt;/code&gt; and finally &lt;code&gt;build crystal&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 2&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Go to &lt;code&gt;Tools -&amp;gt; Atom Volume and Surfaces -&amp;gt; Task-Solvent Surfaces&lt;/code&gt; and change the settings according to your need and &lt;code&gt;create the isosurface&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 3&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Right click on the image you have generated go to &lt;code&gt;display style -&amp;gt; isosurfaces&lt;/code&gt; and increase the &lt;code&gt;Transparency&lt;/code&gt; slider.&lt;/p&gt;&#xA;&lt;p&gt;The resulting image will show the pores of your membrane.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2021-07-20T09:57:02.277" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6412" PostTypeId="1" CreationDate="2021-07-20T14:44:25.247" Score="7" ViewCount="557" Body="&lt;p&gt;I am trying to install the thirdorder script that is mean to work in tandem with &lt;a href=&quot;https://www.shengbte.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ShengBTE&lt;/a&gt; on an Ubuntu OS, but I'm getting the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;npy_1_7_deprecated_api.h:17:2: warning: #warning &amp;quot;Using deprecated NumPy API, disable it with &amp;quot; &amp;quot;#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION&amp;quot; [-Wcpp]&#xA;   17 | #warning &amp;quot;Using deprecated NumPy API, disable it with &amp;quot; \&#xA;      |  ^~~~~~~&#xA;thirdorder_core.c:559:10: fatal error: spglib/spglib.h: No such file or directory&#xA;  559 | #include &amp;quot;spglib/spglib.h&amp;quot;&#xA;      |          ^~~~~~~~~~~~~~~~~&#xA;compilation terminated.&#xA;error: command 'gcc' failed with exit status 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Please direct me how to solve this.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2022-03-16T00:33:43.310" LastActivityDate="2022-10-04T00:25:44.653" Title="Error while installing ShengBTE" Tags="|python|software-assistance|phonons|thermal|shengbte|" AnswerCount="1" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="6413" PostTypeId="1" CreationDate="2021-07-20T18:37:47.437" Score="10" ViewCount="76" Body="&lt;p&gt;I'm trying to analyse doping in a certain material in low concentrations. I'm approaching the problem by taking crystallographic unit cell of that material, then expanding that to a 2x2x2 supercell and then substituting one or more atoms with other element. Changing amount of atoms substituted I can control the doping level.&lt;/p&gt;&#xA;&lt;p&gt;If I choose to substitute one atom in a 32 atom supercell, I obtain 3.125 % doping. If I substitute two atoms, I get 6.25% doping and so on. But I cannot know beforehand which lattice points will be preferable, so I have to calculate all possible configurations. For 2 atoms, it means 240 possible structures, but most of them are repeated. For a simple example, although these two configurations presented below are the same, in P1 supercell they are different. For two atoms, I'm able to generate close to full set of configurations, but for higher number of heteroatoms it gets tedious.&lt;/p&gt;&#xA;&lt;p&gt;My question is mostly practical. I suppose &lt;strong&gt;I should use symmetry operations to reduce the number of configurations, but how may I do  it practically?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/N0BAu.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/N0BAu.png&quot; alt=&quot;Two corresponding configurations&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3981" LastEditorUserId="5" LastEditDate="2021-07-31T00:39:44.167" LastActivityDate="2021-07-31T00:39:44.167" Title="How to generate a complete set of doped (substituted) structures?" Tags="|software-recommendations|crystallography|symmetry|from-phys-se|" AnswerCount="0" CommentCount="6" ClosedDate="2021-12-22T13:04:13.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="6414" PostTypeId="2" ParentId="6406" CreationDate="2021-07-21T15:38:06.760" Score="6" Body="&lt;p&gt;Thermo-Calc creates new composition sets from the global minimization process and you cannot, to my knowledge, have direct control of preventing certain composition sets from being created. Disabling global minimization (removing &lt;code&gt;.enable_global_minimization()&lt;/code&gt;) may get you what you need, but you should be careful to ensure that the composition set of FCC_L12 that you get as your matrix corresponds to the composition set that you intend to be the matrix.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with TCPython() as session:&#xA;    system=(session.disable_caching()&#xA;           .select_database_and_elements(database_name, elements)&#xA;           .get_system())&#xA;           &#xA;    calc=(system.with_single_equilibrium_calculation()&#xA;         .with_options(SingleEquilibriumOptions()&#xA;         .enable_approximate_driving_force_for_metastable_phases()))&#xA;    calc.set_condition(ThermodynamicQuantity.temperature(), temp)&#xA;    for el_indx in range(len(elements)):&#xA;        calc.set_condition(ThermodynamicQuantity&#xA;             .mole_fraction_of_a_component(elements[el_indx]), comps[el_indx])&#xA;&#xA;    calc.set_phase_to_suspended(&amp;quot;*&amp;quot;)&#xA;    calc.set_phase_to_entered(&amp;quot;FCC_L12&amp;quot;, 0)&#xA;    calc.set_phase_to_dormant(precip_phaseName)&#xA;&#xA;    calc_result=calc.calculate()&#xA;    drivingForce = calc_result.get_value_of('DGM(' + precip_phaseName + ')')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-07-21T15:38:06.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6416" PostTypeId="1" CreationDate="2021-07-21T22:19:55.637" Score="4" ViewCount="561" Body="&lt;p&gt;I'm trying to do spin-orbit coupling calculations with VASP but when I started to run them, I got this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ERROR: non collinear calculations require that VASP is compiled&#xA;  without the flag -DNGXhalf and -DNGZhalf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So how may I compile VASP without those flags?&lt;/p&gt;&#xA;" OwnerUserId="3984" LastEditorUserId="5" LastEditDate="2021-07-31T00:42:40.843" LastActivityDate="2021-07-31T00:42:40.843" Title="How to compile VASP without the flags -DNGXhalf and -DNGZhalf?" Tags="|vasp|software-assistance|spin-orbit-coupling|" AnswerCount="0" CommentCount="6" ClosedDate="2021-08-09T16:55:26.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="6417" PostTypeId="1" AcceptedAnswerId="6418" CreationDate="2021-07-22T06:44:53.860" Score="7" ViewCount="269" Body="&lt;p&gt;I am studying the dehydrogenation of a cyclohexane ring containing &lt;span class=&quot;math-container&quot;&gt;$\ce{B-N}$&lt;/span&gt; on the adjacent position.&#xA;or simply we can think about &lt;span class=&quot;math-container&quot;&gt;$\ce{H3N-BH3}$&lt;/span&gt;.&#xA;If we release one &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecule from it then the  Gibbs free energy and the enthalpy of dehydrogenation are negative (See Scheme 1 under Fig. 1 here: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ja9106622&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/ja9106622&lt;/a&gt; ). If we calculate simple dehydrogenation energy for &lt;span class=&quot;math-container&quot;&gt;$\ce{H3N-BH3}$&lt;/span&gt; then it is also negative.&lt;/p&gt;&#xA;&lt;p&gt;Negative dehydrogenation energy means it's a spontaneous reaction and we do not need anything to release the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecule from the system. My concern is &amp;quot;How the system is stable in its pristine condition if its dehydrogenation enthalpy/energy is negative&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;Under the scheme 3rd of Fig. 1 in the above-mentioned paper. If we release &lt;span class=&quot;math-container&quot;&gt;$\ce{1H2}$&lt;/span&gt; from the ring then the dehydrogenation energy is negative. I do not understand how I can explain this negative value of dehydrogenation energy.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="1380" LastEditDate="2021-07-22T07:06:23.090" LastActivityDate="2021-07-22T07:27:41.197" Title="Can the dehydrogenation energy be negative?" Tags="|thermodynamics|reaction-mechanism|organic-chemistry|dehydrogenation|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6418" PostTypeId="2" ParentId="6417" CreationDate="2021-07-22T07:27:41.197" Score="10" Body="&lt;p&gt;Because the hydrogenation release has a barrier (activation energy) that is not too low. The fact that the dehydrogenation energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{H3N-BH3}$&lt;/span&gt; is negative does prove that it will eventually decompose if left at room temperature, but it does so extremely slowly so that you don't notice, and it's more useful to treat it as stable. It's like, your oxidation energy is negative too, yet you haven't disappeared into &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt; yet.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-22T07:27:41.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6420" PostTypeId="1" AcceptedAnswerId="6421" CreationDate="2021-07-20T09:44:49.203" Score="6" ViewCount="92" Body="&lt;p&gt;What data structure is used in representing protein structures in computers so that we can apply algorithms?&lt;/p&gt;&#xA;&lt;p&gt;Matrix or Graph or tree?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;P.S.&lt;/strong&gt; I am absolutely new to Bioinformatics.&lt;/p&gt;&#xA;" OwnerUserId="3990" OwnerDisplayName="user366312" LastActivityDate="2021-07-23T03:09:15.453" Title="How are tertiary protein structures represented in computers?" Tags="|proteins|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6421" PostTypeId="2" ParentId="6420" CreationDate="2021-07-20T10:05:25.807" Score="5" Body="&lt;p&gt;You don't specify what the algorithms shall do.  If &lt;em&gt;represented&lt;/em&gt; does not equal to &lt;em&gt;visualization&lt;/em&gt;, then a the structures may be stored, transferred and processed &lt;em&gt;via&lt;/em&gt; the atomic coordinates of the protein.  For proteins, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Protein_Data_Bank_(file_format)&quot; rel=&quot;noreferrer&quot;&gt;.pdb&lt;/a&gt; format is quite common.  After a header, the (x,y,z) are described in a block like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOM      1  N   PRO A   1       8.316  21.206  21.530  1.00 17.44           N&#xA;ATOM      2  CA  PRO A   1       7.608  20.729  20.336  1.00 17.44           C&#xA;ATOM      3  C   PRO A   1       8.487  20.707  19.092  1.00 17.44           C&#xA;ATOM      4  O   PRO A   1       9.466  21.457  19.005  1.00 17.44           O&#xA;ATOM      5  CB  PRO A   1       6.460  21.723  20.211  1.00 22.26           C&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(&lt;em&gt;loc. cit.&lt;/em&gt;)&lt;/p&gt;&#xA;&lt;p&gt;in the first three columns with entries of type &lt;em&gt;real&lt;/em&gt; (not &lt;em&gt;integer&lt;/em&gt;, nor &lt;em&gt;character&lt;/em&gt;) with the implicit unit of Angstrom (i.e., &lt;span class=&quot;math-container&quot;&gt;$\pu{10^{-10} m}$&lt;/span&gt;).  Note that the format equally supports &lt;code&gt;D&lt;/code&gt; instead of &lt;code&gt;H&lt;/code&gt; to describe the deuterium isotope (&lt;a href=&quot;http://wiki.jmol.org/index.php/File_formats/Coordinates#PDB&quot; rel=&quot;noreferrer&quot;&gt;reference&lt;/a&gt;).  If you need to familiarize yourself with this file fomat, visit e.g., Jmol's public set of reference files &lt;a href=&quot;https://sourceforge.net/p/jmol/code/HEAD/tree/trunk/Jmol-datafiles/pdb/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If the algorithms are about determining &lt;em&gt;similarity&lt;/em&gt; between molecules stored in a database, then likely &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/Fingerprints/intro.html&quot; rel=&quot;noreferrer&quot;&gt;fingerprints&lt;/a&gt; are more suitable for you.&lt;/p&gt;&#xA;" OwnerUserId="1206" OwnerDisplayName="Buttonwood" LastActivityDate="2021-07-20T10:05:25.807" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6422" PostTypeId="1" CreationDate="2021-07-22T17:43:09.893" Score="8" ViewCount="282" Body="&lt;p&gt;I would like to use QE to obtain u_&lt;strong&gt;K&lt;/strong&gt;(&lt;strong&gt;r&lt;/strong&gt;), which is the Bloch wave function of spin-up maximum valance band at &lt;strong&gt;K&lt;/strong&gt; point. If I define the &lt;strong&gt;K&lt;/strong&gt; point in the input file and do an SCF calculation by QE including spin-orbit coupling, &lt;strong&gt;I was wondering how I can extract the mentioned Bloch wave function?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have followed the below link:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4201/what-is-the-best-program-to-manipulate-numerical-dft-wavefunctions-to-calculate&quot;&gt;What is the best program to manipulate numerical DFT wavefunctions to calculate custom matrix elements?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;to get &lt;code&gt;.hdf5&lt;/code&gt; files. &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/snippets/1869219&quot; rel=&quot;nofollow noreferrer&quot;&gt;This link&lt;/a&gt;, presents how to collect wavefunctions.&lt;/p&gt;&#xA;&lt;p&gt;I am not sure how to use the script together with python to obtain the desired wave function. I would appreciate your help and advice on this.&lt;/p&gt;&#xA;" OwnerUserId="3993" LastEditorUserId="5" LastEditDate="2021-08-09T16:58:10.297" LastActivityDate="2021-08-09T16:58:10.297" Title="Bloch wave function extraction for the specific k-points and specific band from QE calculation" Tags="|density-functional-theory|quantum-espresso|python|spin-orbit-coupling|" AnswerCount="0" CommentCount="2" ClosedDate="2021-08-24T15:46:54.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="6423" PostTypeId="2" ParentId="3611" CreationDate="2021-07-22T21:24:13.203" Score="8" Body="&lt;h2 id=&quot;replica-exchange-q9dc&quot;&gt;Replica Exchange&lt;/h2&gt;&#xA;&lt;p&gt;Methods like &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0009261499011239&quot; rel=&quot;nofollow noreferrer&quot;&gt;temperature replica exchange&lt;/a&gt; and Hamiltonian replica exchange can help to sample phase space more uniformly. For temperature replica exchange, we have the base temperature that we are interested in (often room temperature or body temperature) and a number of other replicas with higher temperatures. For instance, we could have 10 replicas with temperatures of 300, 350, 400, 450, 500, 550, 600, 650, 700, and 750 K. We run simulations at these temperatures simultaneously. At the higher temperatures, enthalpic barriers easier to cross (they are smaller relative to thermal energy, &lt;span class=&quot;math-container&quot;&gt;$k_\mathrm{B}T$&lt;/span&gt;) and the kinetics are faster. For example, while the &lt;em&gt;cis&lt;/em&gt; and &lt;em&gt;trans&lt;/em&gt; amide conformations of proline have similar energy, there is a &lt;a href=&quot;https://doi.org/10.1021/jp9046962&quot; rel=&quot;nofollow noreferrer&quot;&gt;large barrier&lt;/a&gt; between (&amp;gt;10 kcal/mol) them. At 300 K, the transitions between the &lt;em&gt;cis&lt;/em&gt; and &lt;em&gt;trans&lt;/em&gt; will never occur on the simulation timescale (microseconds). You could probably run continuously for a year and never see such a transition. However, transitions can be observed within a few nanoseconds at 750 K. So, our high temperature simulations will explore more of conformational space. We can take advantage of this by applying a &lt;a href=&quot;https://en.wikipedia.org/wiki/Parallel_tempering&quot; rel=&quot;nofollow noreferrer&quot;&gt;Monte Carlo procedure&lt;/a&gt; that improves sampling at the base temperature (300 K), while maintaining correct &lt;span class=&quot;math-container&quot;&gt;$NVT$&lt;/span&gt; ensemble at this temperature.&lt;/p&gt;&#xA;&lt;p&gt;For example, we can let the simulations run for each replica and every 1000 steps attempt exchanges of atomic coordinates between the replicas. We calculate the probability of the exchange by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ p_\mathrm{exchange} = \min \left\{ 1,\frac{\exp(- \beta_i V_j - \beta_j V_i)}{\exp(-\beta_i V_i - \beta_j V_j)} \right\},\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; are the indices of two replicas, &lt;span class=&quot;math-container&quot;&gt;$V_i$&lt;/span&gt; is the potential energy of replica &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; before the exchange attempt, and &lt;span class=&quot;math-container&quot;&gt;$\beta_i = 1/(k_\mathrm{B} T_i)$&lt;/span&gt; is the inverse temperature of the ensemble for replica &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. We can see &lt;span class=&quot;math-container&quot;&gt;$\frac{\exp(- \beta_i V_j - \beta_j V_i)}{\exp(-\beta_i V_i - \beta_j V_j)}$&lt;/span&gt;, as the ratio of the probability of observing the states of the two replicas after exchange to the probability of observing the states of the two replicas before exchange. If this ratio is larger than one, then we accept the exchange immediately. If this ratio is less than one, we generate a random number on [0,1] and accept the exchange if that number is less than the probability ratio. If the atomic configurations are exchanged, we reset the velocities from a Maxwell-Boltzmann distribution at the destination temperature (alternatively, we can include the kinetic energy in the probability calculation and exchange velocities too).&lt;/p&gt;&#xA;&lt;p&gt;Hence, barriers can be crossed at high temperature and the resulting atomic configurations can be passed down to lower temperatures. The reason that we often need many temperatures is that, if the temperatures are too far apart, the energies distributions will not overlap, &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; will be very small, and the exchanges will rarely, if ever, be accepted. We need exchanges to be accepted to get the enhanced sampling we desire. So the temperature range and number of replicas must be chosen carefully to both obtain better exploration of phase space (usually promoted by a higher maximum temperature) and a reasonably high acceptance rate (promoted by having a small difference in temperature between adjacent replicas).&lt;/p&gt;&#xA;&lt;p&gt;A major problem with the temperature replica exchange scheme is that it does not scale well as the number of degrees of freedom in the system is increased. The energy fluctuation (standard deviation of the energy distribution) of a system in the &lt;span class=&quot;math-container&quot;&gt;$NVT$&lt;/span&gt; ensemble is &lt;span class=&quot;math-container&quot;&gt;$\sigma_E = \sqrt{k_\mathrm{B} T^2 C_V}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$C_V$&lt;/span&gt; is the heat capacity at constant volume. The heat capacity is typically proportional to the number of particles &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, so the width of the energy distribution grows like &lt;span class=&quot;math-container&quot;&gt;$\sqrt{N}$&lt;/span&gt;. However, the mean energy typically grows like &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, so if we double the size of the system, the energy distributions between simulations at 300 and 350 K will overlap less.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Hamiltonian replica exchange&lt;/strong&gt; can be more targeted and is thus better suited for systems with large numbers of degrees of freedom. In this case, we have a base Hamiltonian, which is our unmodified and presumably realistic force field. The other replicas have an increasingly more biased potential energy. The biasing potential is chosen to help us to sample the transitions we want (for example, &lt;a href=&quot;https://doi.org/10.1002/jcc.23476&quot; rel=&quot;nofollow noreferrer&quot;&gt;conformational transitions in a peptide&lt;/a&gt;), while not changing interactions for other degrees of freedom (for example, water–water interactions). Again, we expect faster exploration of phase space for the most biased replicas and the resulting conformations can be exchanged down to the base (unbiased) replica. We attempt exchanges every so many steps and accept them with the probability&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ p_\mathrm{exchange} = \min \left\{ 1,\frac{\exp(-\beta V_i(\mathbf{X}_j) - \beta V_j(\mathbf{X}_i)}{\exp(-\beta V_i(\mathbf{X}_i) - \beta V_j(\mathbf{X}_j)} \right\},\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; is the constant temperature for all replicas, &lt;span class=&quot;math-container&quot;&gt;$V_i$&lt;/span&gt; is the potential energy function for replica &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{X}_i$&lt;/span&gt; is the set of all atomic coordinates for replica &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; before the exchange attempt.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-07-23T17:32:24.253" LastActivityDate="2021-07-23T17:32:24.253" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6424" PostTypeId="1" CreationDate="2021-07-22T23:58:11.217" Score="6" ViewCount="91" Body="&lt;p&gt;I installed &lt;code&gt;Fullprof_Suite_March2021_Linux64.tgz&lt;/code&gt; in Ubuntu 18.04. I also installed &amp;quot;libmotif-common&amp;quot; libraries. But all the GUIs are not opening. Why is this?&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="7" LastEditDate="2021-07-30T18:30:03.567" LastActivityDate="2021-07-30T18:30:03.567" Title="Why does the GUI not run after the installation of FullProf Suite?" Tags="|software-assistance|graphical-user-interface|fullprof-suite|" AnswerCount="0" CommentCount="5" ClosedDate="2021-08-24T15:48:37.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="6425" PostTypeId="5" CreationDate="2021-07-23T01:12:45.207" Score="0" Body="&lt;p&gt;Mainly developed for Rietveld analysis (structure profile refinement) of neutron (constant wavelength, time of flight, nuclear and magnetic scattering) or X-ray powder diffraction data collected at constant or variable step in scattering angle 2theta.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ill.eu/sites/fullprof/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ill.eu/sites/fullprof/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-23T01:12:45.207" LastActivityDate="2021-07-23T01:12:45.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6426" PostTypeId="4" CreationDate="2021-07-23T01:12:45.207" Score="0" Body="Questions about or related to FullProf Suite for Windows, Linux and macOS, which is includes the following crystallographic programs: FullProf, WinPLOTR, EdPCR, GFourier, etc.). " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-07-23T01:12:45.207" LastActivityDate="2021-07-23T01:12:45.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6427" PostTypeId="1" AcceptedAnswerId="6428" CreationDate="2021-07-23T18:55:43.003" Score="11" ViewCount="481" Body="&lt;p&gt;I have heard people talk about DFT functionals built starting from MP2 corrections. Do you happen to have a reference I read about that from?&lt;/p&gt;&#xA;" OwnerUserId="381" LastEditorUserId="5" LastEditDate="2021-07-23T19:58:11.470" LastActivityDate="2021-07-23T22:32:40.187" Title="DFT functionals from MP2 methods" Tags="|density-functional-theory|quantum-chemistry|functional|many-body-perturbation-theory|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6428" PostTypeId="2" ParentId="6427" CreationDate="2021-07-23T19:07:54.203" Score="12" Body="&lt;p&gt;These are called double hybrid functionals. You add a fraction of MP2 correlation on top of the DFT energy.&lt;/p&gt;&#xA;&lt;p&gt;A good reference is e.g. the review by Goerigk and Grimme from 2014 published in &lt;a href=&quot;https://doi.org/10.1002/wcms.1193&quot; rel=&quot;noreferrer&quot;&gt;WIREs 4, 576 (2014)&lt;/a&gt;. Note that this is already 7 years old; many double hybrids have appeared since then. However, it should give you a good overview.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-07-23T19:07:54.203" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6429" PostTypeId="2" ParentId="6427" CreationDate="2021-07-23T22:32:40.187" Score="11" Body="&lt;p&gt;Susi is right that these are called &lt;em&gt;&lt;strong&gt;double hybrids&lt;/strong&gt;&lt;/em&gt;, I'll just add a bit more to complement that correct answer. My answer to &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;&amp;quot; was about double hybrids, and it looks like the community here considered that to be one of the most important &amp;quot;recent&amp;quot; developments in DFT.&lt;/p&gt;&#xA;&lt;p&gt;About the MP2 contributions, single contributions are ignored (this is already the case when starting from Hartree-Fock because Brillouin's theorem says they don't exist, but when starting from a DFT calculation single excitations can contribute, and early developers of double hybrid functionals decided not to include them), see this: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1665/5&quot;&gt;Why are single excitations ignored in the MP2 component of double hybrid functional calculations?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Another interesting discussion about double hybrids can be found here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/690/5&quot;&gt;Physically motivated double hybrid DFT?&lt;/a&gt;, and here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4160/5&quot;&gt;Using double-hybrid functional instead of MP2 to avoid basis set dependence&lt;/a&gt;, and if you're interested in going even further than MP2, there's been some papers that used QCISD or RPA: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/688/5&quot;&gt;Extended Hybrid Methods&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, double hybrids have been recommended or their accuracy has been discussed, in a lot of answers on this site, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4875/5&quot;&gt;What does B3LYP do well? What does it do badly?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1430/5&quot;&gt;Create a new DFT functional from experimental data&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4939/5&quot;&gt;Which DFT functional should I use to simulate spectra of pesticides?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1257/5&quot;&gt;Is there an example where TD-DFT fails to provide sufficient accuracy for a small system, where RI-CC2 is sufficient?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-23T22:32:40.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6430" PostTypeId="2" ParentId="6367" CreationDate="2021-07-24T14:51:27.067" Score="3" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;First of all, H-phase TMDC monolayers like &lt;span class=&quot;math-container&quot;&gt;$\ce{WSe_2}$&lt;/span&gt; are non-magnetic semiconducting materials, which means the time-reversal symmetry (TRS) is preserved. Therefore, you can say the energy states at &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-K$&lt;/span&gt; are connected by TRS, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1728/separation-of-valence-bands-in-transition-metal-dichalcogenides-tmds&quot;&gt;seeing this post&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For H-phase TMDC monolayers, the inversion symmetry (IS) is broken. In addition, the spin-orbit coupling (SOC) in these materials is strong. The combination of broken IS and strong SOC leads to the spin splittings at valleys &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;/&lt;span class=&quot;math-container&quot;&gt;$-K$&lt;/span&gt;. In fact, the splitting at valleys &lt;span class=&quot;math-container&quot;&gt;$K/-K$&lt;/span&gt; likes Zeeman-type splitting.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2021-07-24T18:06:41.753" LastActivityDate="2021-07-24T18:06:41.753" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6431" PostTypeId="1" CreationDate="2021-07-24T19:13:04.937" Score="18" ViewCount="1198" Body="&lt;p&gt;I am trying to understand what exactly the flying ice cube effect is, and how it manifests itself in MD simulation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Flying_ice_cube#:%7E:text=In%20molecular%20dynamics%20(MD)%20simulations,and%20rotation%20of%20the%20system.&quot; rel=&quot;noreferrer&quot;&gt;From what I have read about it&lt;/a&gt;, I see that as we run certain forms of velocity-rescaling without scrutiny, they system &amp;quot;freezes&amp;quot; into certain fixed states with a net momentum (like an ice-cube flying in space), instead of jostling around with zero net momentum. The article says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the energy of high-frequency fundamental modes is drained into low-frequency modes, particularly into zero-frequency motions such as overall translation and rotation of the system.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What exactly is a high-frequency energy mode for point particles in space? Why does energy get drained out of them, and go into translation and rotation?&lt;/p&gt;&#xA;&lt;p&gt;I am thinking of point particles moving in space with some kinetic energy, and with some interaction potential energy &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;. So the Hamiltonian is pretty much:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{1}&#xA;\mathcal{H} &amp;amp;= \mathcal{K}(\mathbf{p})+\mathcal{U}(\mathbf{r}), \\\tag{2}&#xA;\mathcal{H} &amp;amp;= \frac{1}{2}\sum _i \frac{\mathbf{p}_i^2}{m_i} + \mathcal{U}(\mathbf{r}).&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I consistently rescale velocity to reach a certain temperature, why does it lead to a fixed state and the energy of high-frequency modes being drained into low-frequency modes like translation and rotation?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-07-26T15:53:05.050" LastActivityDate="2021-07-26T15:53:05.050" Title="Flying ice cube effect in molecular dynamics?" Tags="|molecular-dynamics|statistical-thermodynamics|thermodynamics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6432" PostTypeId="2" ParentId="6431" CreationDate="2021-07-25T01:38:07.443" Score="10" Body="&lt;p&gt;High frequency in this case is 'particles move all independently, with different directions and speed', and low frequency means 'particles can be represented as gradually changing field of speed and direction of particles in the region'. Something like 'frequency in space', how often to change speed and direction as you observe more and more particles.&lt;/p&gt;&#xA;&lt;p&gt;If your particles are not centered, so that movement of center of mass is not zero, then large movement may take up most of the mantissa of your variables.&lt;/p&gt;&#xA;&lt;p&gt;For example, big movement is 1000 units, and thermal movement is 1.001 units. Non-centered particle speed is 1001.001. This requires a lot of digits to store, and last digit may be lost in rounding.&lt;/p&gt;&#xA;" OwnerUserId="1690" LastActivityDate="2021-07-25T01:38:07.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6433" PostTypeId="1" CreationDate="2021-07-25T05:52:59.107" Score="4" ViewCount="301" Body="&lt;p&gt;I am trying to calculate the electronic structure of Monolayer Molybdenum Disulfide (&lt;span class=&quot;math-container&quot;&gt;$\ce{MoS_2}$&lt;/span&gt;) using Vasp. However, I encounter problems with convergence. It does not seem that my calculations converge at all. I am using a Monkhorst Pack grid 15 * 15 * 1 (although I tried different densities to understand if this would influence convergence).&lt;/p&gt;&#xA;&lt;p&gt;In the POSCAR file, I start with the bulk POSCAR file available on &lt;a href=&quot;http://materialsproject.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;materialsproject.org&lt;/a&gt; and I increase the length of the vector &amp;quot;c&amp;quot; pointing from one layer to its neighbor. Regarding the INCAR parameters, I just use ISMEAR = 0 , SIGMA = 0.2 , ENCUT = 500 , PREC = Accurate. I'm still learning Vasp and more generally matter simulation and CMT, so I do not fully understand what many of the INCAR parameters do. Therefore, my INCAR file is quite simple.&lt;/p&gt;&#xA;&lt;p&gt;My question is: what is the underlying reason for this non-convergence when modeling a monolayer &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; system and how to avoid it?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="4000" LastEditorUserId="1380" LastEditDate="2021-07-25T09:14:33.580" LastActivityDate="2021-07-25T09:14:33.580" Title="DFT Vasp calculation not converging when doing a SCF calculation for monolayer MoS2" Tags="|vasp|electronic-structure|numerical-convergence|monolayer|" AnswerCount="0" CommentCount="2" ClosedDate="2021-08-24T15:49:12.810" ContentLicense="CC BY-SA 4.0" />
  <row Id="6434" PostTypeId="1" CreationDate="2021-07-25T09:30:39.320" Score="6" ViewCount="559" Body="&lt;p&gt;I have to do simulations of some inorganic anions, specifically &lt;span class=&quot;math-container&quot;&gt;$\ce{PO4^3-}$&lt;/span&gt; (ortho-phosphate), &lt;span class=&quot;math-container&quot;&gt;$\ce{CO3^2-}$&lt;/span&gt; (carbonate), &lt;span class=&quot;math-container&quot;&gt;$\ce{SO4^2-}$&lt;/span&gt; (sulfate), in an aqueous enviornment. However, I am having a lot of difficulties in getting hold of parameters for such ions. I am looking for mainly OPLS-AA parameters. (but I am willing to use other force-fields if I have to)&lt;/p&gt;&#xA;&lt;p&gt;The official site for OPLS-AA parameters is the &lt;a href=&quot;http://zarbi.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;LigParGen&lt;/a&gt; server, however, it fails with any ionic species that I put in. The github issue-tracker for LigParGen seems to have been abandoned.&lt;/p&gt;&#xA;&lt;p&gt;There are some papers which seem to have developed parameters for phosphate or other ions, but they all developed the parameters for solid state calculations (e.g. on apatite etc.). So, I am not sure if those parameters are transferable to liquid phase aqueous simulations.&lt;/p&gt;&#xA;&lt;p&gt;There are also some parameters for ionic liquids, but the same problem of transferability is present.&lt;/p&gt;&#xA;&lt;p&gt;I could find carbonate parameters in CgenFF, but it does not mention whether it is usable in water (or which model of water was used to parameterize it). The other two ions are not in CgenFF however.&lt;/p&gt;&#xA;&lt;p&gt;My questions are—&lt;strong&gt;Are there any parameters for those ions to be used for aqueous simulations? Alternatively, is there any software/server which can generate the parameters for it?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-07-26T03:00:29.243" LastActivityDate="2021-07-26T11:22:54.357" Title="Where can I find/generate force-field parameters for common inorganic anions in water?" Tags="|molecular-dynamics|reference-request|forcefields|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6435" PostTypeId="1" CreationDate="2021-07-25T12:57:16.400" Score="5" ViewCount="266" Body="&lt;p&gt;I'm looking for a list of tools similar to ATAT which are available for creating random multi-component alloy inputs for DFT/MD.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2021-07-26T00:46:36.720" LastActivityDate="2021-07-27T07:22:00.567" Title="List of software for creating random multi-component alloy inputs for DFT or MD" Tags="|density-functional-theory|molecular-dynamics|one-topic-per-answer|software-recommendations|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6436" PostTypeId="2" ParentId="6431" CreationDate="2021-07-25T19:52:00.653" Score="9" Body="&lt;p&gt;The flying ice cube effect is when the kinetic energy leaks into the translations and rotations.&lt;/p&gt;&#xA;&lt;p&gt;In a constant energy simulation (NVE) this must come at the expense of vibrations, which has the effect of &amp;quot;freezing&amp;quot; the bonds, angles and torsions. Obviously, this is a purely classical effect because even at 0 K a bond will vibrate at the zero-point energy (ZPE).&lt;/p&gt;&#xA;&lt;p&gt;Here is a breakdown of the types of vibrations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Bond stretches: Highest in energy&lt;/li&gt;&#xA;&lt;li&gt;Bends: Somewhat lower in energy&lt;/li&gt;&#xA;&lt;li&gt;Torsional motions: Lower still&lt;/li&gt;&#xA;&lt;li&gt;“Breathing” modes (very large molecules): Lowest energy&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To prevent energy from being leaked into translations and rotations one must be careful in how they prepare initial conditions and remove translation and rotations every so often.&lt;/p&gt;&#xA;&lt;p&gt;For example, Amber will remove COM translations (and rotations if a non-periodic simulation) every &lt;code&gt;nscm steps&lt;/code&gt;. The default is 1000. The manual also says something interesting about Langevin Dynamics which are NVT simulations&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For Langevin dynamics, the position of the center-of-mass of the&#xA;molecule is re- set to zero every NSCM steps, but the velocities are&#xA;not affected Hence there is no change to either the translation or&#xA;rotational components of the momenta. (Doing anything else would&#xA;destroy the way in which temperature is regulated in a Langevin&#xA;dynamics system.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can also ensure you don't have translations and rotations by operating in internal coordinates. But that is very non-standard practice. Boltzamann sampled initial conditions from normal modes can be a good way to generate initial conditions as well, but that is restricted to things you can actually calculate normal modes for, which is typically less than a few hundred atoms and probably not worth your time.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2021-07-25T20:09:33.370" LastActivityDate="2021-07-25T20:09:33.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6437" PostTypeId="2" ParentId="6434" CreationDate="2021-07-26T01:37:09.443" Score="7" Body="&lt;p&gt;Any parameters are better than no parameters. Part of using a FF is checking that results make sense, so if you can find &lt;em&gt;something&lt;/em&gt; in this bare market for anions, try it. Proof will be in the pudding.&lt;/p&gt;&#xA;&lt;p&gt;LigParGen can only generate ions between -2 and +2 charge, so &lt;span class=&quot;math-container&quot;&gt;$\ce{PO4^3-}$&lt;/span&gt; is out. When I tried with &lt;span class=&quot;math-container&quot;&gt;$\ce{SO4^2-}$&lt;/span&gt;, it did not work. &lt;span class=&quot;math-container&quot;&gt;$\ce{H2SO4}$&lt;/span&gt; also did not work. I then tried &lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt; (via SMILES) and it(LigParGen) did not work. I then tried &lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt; via pdb file, it worked. I tried &lt;span class=&quot;math-container&quot;&gt;$\ce{CO3^2-}$&lt;/span&gt;, it did not work, but &lt;span class=&quot;math-container&quot;&gt;$\ce{H2CO3}$&lt;/span&gt; did work. I have attached the &lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{H2CO3}$&lt;/span&gt; pdbs so you can remake them if you wish, but also attach the GROMACS topology files (actually I have pasted them at the bottom... I don't know how to attach them...).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I did a quick and dirty geometry optimization in Avogadro using GAFF&lt;/strong&gt;, so, we know that GAFF at least can do the anions(Avogadro says the molecular formula includes the hydrogens, so I am not sure if it is really doing the anion? I removed hydrogens anyways. Atomic properties does not list hydrogens...), so I would suggest looking into GAFF along with OPLS/AA.&lt;/p&gt;&#xA;&lt;p&gt;My suggestion is to try using GAFF to get the bond/angle parameters (maybe GAFF[Antechamber] will even do the charges too, but I wouldn't want to use them). I would suggest generating MBIS partial charges. If GAFF will do the anions, then use the LJ parameters it generates. If it does not, generate the neutral molecules, for instance, &lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{H2SO4}$&lt;/span&gt; and &amp;quot;borrow&amp;quot; the LJ parameters as well as bond/angle parameters. You can tweak the bond/angle parameters using QM if you wish. Then get partial charges...I would use a partitioning method over a random number generator like RESP, but regardless, you can generate the partial charges using QM programs. Gaussian will do ESP/Hirshfeld/CM5 and many others. HORTON will do MBIS for you.&lt;/p&gt;&#xA;&lt;p&gt;It is hopefully worth making the forcefield in this somewhat Frankenstein manner if you can't find one. The anions are small so you should be able to &amp;quot;tweak&amp;quot; parameters to make it work for the property you are interested in. Only trial and error will tell :S&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt; PDB file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COMPND    UNNAMED&#xA;AUTHOR    GENERATED BY OPEN BABEL 2.3.90&#xA;HETATM    1  P   UNL     1      -1.464   0.745  -2.751  1.00  0.00           P  &#xA;HETATM    2  O   UNL     1      -2.421   1.312  -3.725  1.00  0.00           O  &#xA;HETATM    3  O   UNL     1      -1.527  -0.862  -2.535  1.00  0.00           O  &#xA;HETATM    4  H   UNL     1      -0.784  -1.161  -1.978  1.00  0.00           H  &#xA;HETATM    5  O   UNL     1      -1.530   1.339  -1.276  1.00  0.00           O  &#xA;HETATM    6  O   UNL     1       0.076   0.988  -3.056  1.00  0.00           O  &#xA;HETATM    7  H   UNL     1      -2.453   1.221  -1.091  1.00  0.00           H  &#xA;HETATM    8  H   UNL     1       0.145   0.489  -3.857  1.00  0.00           H  &#xA;CONECT    1    2    3    5    6                                       &#xA;CONECT    2    1                                                      &#xA;CONECT    3    1    4                                                 &#xA;CONECT    4    3                                                      &#xA;CONECT    5    1    7                                                 &#xA;CONECT    6    1    8                                                 &#xA;CONECT    7    5                                                      &#xA;CONECT    8    6                                                      &#xA;MASTER        0    0    0    0    0    0    0    0    8    0    8    0&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;OPLS/AA FF for &lt;span class=&quot;math-container&quot;&gt;$\ce{H3PO4}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;;&#xA;; GENERATED BY LigParGen Server&#xA;; Jorgensen Lab @ Yale University &#xA;;&#xA;[ atomtypes ]&#xA;  opls_806  H806     1.0080     0.000    A    0.00000E+00   0.00000E+00&#xA;  opls_801  O801    15.9990     0.000    A    2.96000E-01   8.78640E-01&#xA;  opls_800  P800    30.9738     0.000    A    3.74000E-01   8.36800E-01&#xA;  opls_807  H807     1.0080     0.000    A    0.00000E+00   0.00000E+00&#xA;  opls_805  O805    15.9990     0.000    A    3.12000E-01   7.11280E-01&#xA;  opls_802  O802    15.9990     0.000    A    3.12000E-01   7.11280E-01&#xA;  opls_804  O804    15.9990     0.000    A    3.12000E-01   7.11280E-01&#xA;  opls_803  H803     1.0080     0.000    A    0.00000E+00   0.00000E+00&#xA;[ moleculetype ]&#xA;; Name               nrexcl&#xA;UNL                   3&#xA;[ atoms ]&#xA;;   nr       type  resnr residue  atom   cgnr     charge       mass  &#xA;     1   opls_800      1    UNL   P00      1     2.8980    30.9738 &#xA;     2   opls_801      1    UNL   O01      1    -1.2051    15.9990 &#xA;     3   opls_802      1    UNL   O02      1    -1.0619    15.9990 &#xA;     4   opls_803      1    UNL   H03      1     0.4728     1.0080 &#xA;     5   opls_804      1    UNL   O04      1    -1.0008    15.9990 &#xA;     6   opls_805      1    UNL   O05      1    -0.9984    15.9990 &#xA;     7   opls_806      1    UNL   H06      1     0.4508     1.0080 &#xA;     8   opls_807      1    UNL   H07      1     0.4445     1.0080 &#xA;[ bonds ]&#xA;    2     1     1      0.1480 439320.000&#xA;    3     1     1      0.1610 192464.000&#xA;    4     3     1      0.0945 462750.400&#xA;    5     1     1      0.1610 192464.000&#xA;    6     1     1      0.1610 192464.000&#xA;    7     5     1      0.0945 462750.400&#xA;    8     6     1      0.0945 462750.400&#xA;&#xA;[ angles ]&#xA;;  ai    aj    ak funct            c0            c1            c2            c3 &#xA;    2     1     3     1    108.230    836.800&#xA;    1     3     4     1    108.500    460.240&#xA;    2     1     5     1    108.230    836.800&#xA;    2     1     6     1    108.230    836.800&#xA;    1     5     7     1    108.500    460.240&#xA;    1     6     8     1    108.500    460.240&#xA;    3     1     5     1    102.600    376.560&#xA;    5     1     6     1    102.600    376.560&#xA;    3     1     6     1    102.600    376.560&#xA;&#xA;[ dihedrals ]&#xA;; IMPROPER DIHEDRAL ANGLES &#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;&#xA;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    4    3    1    2        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    7    5    1    2        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    8    6    1    2        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    7    5    1    3        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    8    6    1    5        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    8    6    1    3        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    7    5    1    6        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    5    1    3    4        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;    6    1    3    4        3       0.000   0.000   0.000  -0.000  -0.000   0.000&#xA;&#xA;[ pairs ]&#xA;     2     4    1&#xA;     4     5    1&#xA;     2     7    1&#xA;     4     6    1&#xA;     3     7    1&#xA;     2     8    1&#xA;     3     8    1&#xA;     6     7    1&#xA;     5     8    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H2CO3}$&lt;/span&gt; PDB file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COMPND    UNNAMED&#xA;AUTHOR    GENERATED BY OPEN BABEL 2.3.90&#xA;HETATM    1  C   UNL     1       0.943   0.994  -1.701  1.00  0.00           C  &#xA;HETATM    2  O   UNL     1       1.658   0.127  -2.342  1.00  0.00           O  &#xA;HETATM    3  O   UNL     1       1.315   2.096  -2.237  1.00  0.00           O  &#xA;HETATM    4  H   UNL     1       1.969  -0.472  -1.669  1.00  0.00           H  &#xA;HETATM    5  H   UNL     1       1.933   1.686  -2.870  1.00  0.00           H  &#xA;HETATM    6  O   UNL     1       0.632   0.886  -0.535  1.00  0.00           O  &#xA;CONECT    1    2    3    6                                            &#xA;CONECT    2    1    4                                                 &#xA;CONECT    3    1    5                                                 &#xA;CONECT    4    2                                                      &#xA;CONECT    5    3                                                      &#xA;CONECT    6    1                                                      &#xA;MASTER        0    0    0    0    0    0    0    0    6    0    6    0&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H2CO3}$&lt;/span&gt; Topology file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;;&#xA;; GENERATED BY LigParGen Server&#xA;; Jorgensen Lab @ Yale University &#xA;;&#xA;[ atomtypes ]&#xA;  opls_804  H804     1.0080     0.000    A    0.00000E+00   0.00000E+00&#xA;  opls_801  O801    15.9990     0.000    A    3.12000E-01   7.11280E-01&#xA;  opls_805  O805    15.9990     0.000    A    2.96000E-01   8.78640E-01&#xA;  opls_802  O802    15.9990     0.000    A    3.12000E-01   7.11280E-01&#xA;  opls_803  H803     1.0080     0.000    A    0.00000E+00   0.00000E+00&#xA;  opls_800  C800    12.0110     0.000    A    3.55000E-01   2.92880E-01&#xA;[ moleculetype ]&#xA;; Name               nrexcl&#xA;UNL                   3&#xA;[ atoms ]&#xA;;   nr       type  resnr residue  atom   cgnr     charge       mass  &#xA;     1   opls_800      1    UNL   C00      1     0.6339    12.0110 &#xA;     2   opls_801      1    UNL   O01      1    -0.6044    15.9990 &#xA;     3   opls_802      1    UNL   O02      1    -0.4751    15.9990 &#xA;     4   opls_803      1    UNL   H03      1     0.4774     1.0080 &#xA;     5   opls_804      1    UNL   H04      1      0.475     1.0080 &#xA;     6   opls_805      1    UNL   O05      1    -0.5067    15.9990 &#xA;[ bonds ]&#xA;    2     1     1      0.1364 376560.000&#xA;    3     1     1      0.1364 376560.000&#xA;    4     2     1      0.0945 462750.400&#xA;    5     3     1      0.0945 462750.400&#xA;    6     1     1      0.1229 476976.000&#xA;&#xA;[ angles ]&#xA;;  ai    aj    ak funct            c0            c1            c2            c3 &#xA;    2     1     3     1    118.180    584.923&#xA;    1     2     4     1    113.000    292.880&#xA;    1     3     5     1    113.000    292.880&#xA;    2     1     6     1    121.000    669.440&#xA;    3     1     6     1    121.000    669.440&#xA;&#xA;[ dihedrals ]&#xA;; IMPROPER DIHEDRAL ANGLES &#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;     6     1     2     3    4        180.000     43.932     2  &#xA;&#xA;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;;  ai    aj    ak    al funct            c0            c1            c2            c3            c4            c5&#xA;    4    2    1    3        3      23.012   0.000  -23.012  -0.000  -0.000   0.000&#xA;    5    3    1    2        3      23.012   0.000  -23.012  -0.000  -0.000   0.000&#xA;    6    1    2    4        3      23.012   0.000  -23.012  -0.000  -0.000   0.000&#xA;    6    1    3    5        3      23.012   0.000  -23.012  -0.000  -0.000   0.000&#xA;&#xA;[ pairs ]&#xA;     3     4    1&#xA;     2     5    1&#xA;     4     6    1&#xA;     5     6    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-07-26T11:22:54.357" LastActivityDate="2021-07-26T11:22:54.357" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6438" PostTypeId="1" CreationDate="2021-07-26T07:35:17.670" Score="11" ViewCount="1093" Body="&lt;p&gt;My current procedure is to create a .xyz file out of my MD run for a crystal structure. I can read the energy and also each atomic position. But I want to add forces. If I add forces as the additional three columns for each atom, ASE seems to ignore this. ASE considers only the first three columns per atom which are the positions.&lt;/p&gt;&#xA;&lt;p&gt;What's the best way to read positions and forces into ASE?&lt;/p&gt;&#xA;&lt;p&gt;I'm working with FHI aims and I've just done an MD run. I don't think this is as important because the object to read FHI aims with ASE seems to be deprecated.&lt;/p&gt;&#xA;" OwnerUserId="3864" LastEditorUserId="3864" LastEditDate="2021-07-27T06:15:41.223" LastActivityDate="2021-07-29T19:00:13.180" Title="Best way to read forces and positions and energies into Atomic Simulation Environment (ASE)?" Tags="|databases|forcefields|atomic-simulation-environment|fhi-aims|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6439" PostTypeId="1" CreationDate="2021-07-26T20:42:00.270" Score="8" ViewCount="538" Body="&lt;p&gt;I would like to simulate &lt;span class=&quot;math-container&quot;&gt;$\ce{Bi_2Se_3}$&lt;/span&gt; using a DFT calculation on VASP. However, it seems I am not able to get a result; the electronic steps take &lt;span class=&quot;math-container&quot;&gt;$\sim \infty$&lt;/span&gt; of time to complete. Here are the details of my input.&lt;/p&gt;&#xA;&lt;p&gt;INCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System = bi2se3 soc calculation -- SCF&#xA;&#xA;ISMEAR = 0&#xA;SIGMA = 0.2&#xA;&#xA;&#xA;EDIFF = 0.00000001&#xA;&#xA;PREC = Accurate&#xA;&#xA;LSORBIT = .TRUE.&#xA;&#xA;&#xA;&#xA;NCORE = 16&#xA;&#xA;ICHARG = 2&#xA;&#xA;&#xA;ENCUT = 500&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Automatic Mesh generation &#xA;0&#xA;M&#xA;15 15 15&#xA;0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am pretty sure the structure file is correct. However, I did not relax the bulk structures. I suspect the problem could be due to the density of the Brillouin zone grid mesh / the &lt;code&gt;ENCUT&lt;/code&gt; parameter value, but I am not sure. How can I approach this problem? Currently, the calculation seems to be frozen even before the output shows the table of the electronic steps.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4000" LastEditorUserId="5" LastEditDate="2021-07-31T00:48:32.660" LastActivityDate="2021-08-04T14:24:13.923" Title="Calculating the band structure of Bi2Se3 with spin-orbit coupling" Tags="|vasp|band-structure|self-consistent-field|spin-orbit-coupling|brillouin-zone|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6440" PostTypeId="2" ParentId="6435" CreationDate="2021-07-27T07:22:00.567" Score="4" Body="&lt;p&gt;There are a number of open-source and commercial software that can do a completely random substitution alloy.&lt;/p&gt;&#xA;&lt;p&gt;In the open-source segment, you can try the python software: Pymatgen (&lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pymatgen.org/&lt;/a&gt;). Atomsk (&lt;a href=&quot;https://atomsk.univ-lille.fr/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://atomsk.univ-lille.fr/&lt;/a&gt;) is another great software to do this. I have tried to do this using Atomsk and it works perfectly.&lt;/p&gt;&#xA;&lt;p&gt;In the commercial software segment, you can try the model builder routine of QuantumATK (&lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.synopsys.com/silicon/quantumatk.html&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2021-07-27T07:22:00.567" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6441" PostTypeId="1" CreationDate="2021-07-27T07:52:20.923" Score="8" ViewCount="86" Body="&lt;p&gt;I'm working with a binary alloy system (call it 'AB'), and I'd like to generate a few unique configurations for DFT purposes.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My primitive cubic unit cell consists of 4 atoms; i.e. 4 positions. Thus, if I want 25% A, 75% B, I'll assign 1 atom of type A and 3 atoms of type B to my 4 positions. For instance, in fractional coordinates, this looks like:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A:  0    0    0&lt;/li&gt;&#xA;&lt;li&gt;B:  0.5  0.5  0&lt;/li&gt;&#xA;&lt;li&gt;B:  0.5  0    0.5&lt;/li&gt;&#xA;&lt;li&gt;B:  0    0.5  0.5&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In this example, there is only 1 unique configuration. For instance, say I swap the positions of the first two atoms. This resulting coordinate list looks different, but it would still describe the exact same configuration because it is equivalent via symmetry operations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A:  0.5  0.5  0&lt;/li&gt;&#xA;&lt;li&gt;B:  0    0    0&lt;/li&gt;&#xA;&lt;li&gt;B:  0.5  0    0.5&lt;/li&gt;&#xA;&lt;li&gt;B:  0    0.5  0.5&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This isn't really an issue for the 4-atom system, because the number of possible combinations is so small (only 4) that it's easy to check them. However, the problem scales rapidly. Assuming I stick with 25% A and 75% B percentage, if I generate a:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;8-atom supercell: I have (8 choose 2) = 28 possible combinations.&lt;/li&gt;&#xA;&lt;li&gt;16-atom supercell: I have (16 choose 4) = 1820 possible combinations.&lt;/li&gt;&#xA;&lt;li&gt;32-atom supercell: I have (32 choose 8) = 10518300 possible combinations.&lt;/li&gt;&#xA;&lt;li&gt;64 atom supercell: I have (64 choose 16) = 4.885e+14 possible combinations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;...and so forth.&#xA;Considering that the system I would like to work with has a size of 128 atoms, proper sampling needs to be done intelligently.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;How can I determine the number of UNIQUE combinations?&lt;/strong&gt; I would like to sample from the set of &lt;em&gt;unique&lt;/em&gt; combinations, instead of from the set of &lt;em&gt;possible&lt;/em&gt; combinations. Given the large configuration space, this needs to be done in a computationally efficient manner.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;This problem seems so fundamental that I would have expected someone to have found some sort of solution to it, but I haven't been able to find one yet.&lt;/p&gt;&#xA;&lt;p&gt;(... I suspect the answer has something to do with utilizing space groups and symmetry operations. However, I'm relatively new to group theory / crystallographic concepts, so advice from someone more well-versed in these topics would be greatly appreciated.)&lt;/p&gt;&#xA;" OwnerUserId="3973" LastEditorUserId="5" LastEditDate="2021-08-24T00:36:58.577" LastActivityDate="2021-08-24T00:36:58.577" Title="Crystallography: How to sample *unique* structures from configuration space? (binary alloy supercell)" Tags="|density-functional-theory|crystallography|symmetry|space-groups|supercell|" AnswerCount="0" CommentCount="7" ClosedDate="2022-01-14T01:24:27.107" ContentLicense="CC BY-SA 4.0" />
  <row Id="6442" PostTypeId="1" AcceptedAnswerId="6684" CreationDate="2021-07-27T10:31:53.017" Score="10" ViewCount="490" Body="&lt;p&gt;I wanted to calculate the normal modes of some particular material using the Quantum ESPRESSO. Everything went fairly well, but there is a couple of lines in the output that I do not understand. In particular, one of the lines that came out in the ph.out file reads as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;freq ( 4 - 5) = 62.3 [cm-1] --&amp;gt; E_u X_5' M_5' I&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From here we can read off the phonon frequency &lt;span class=&quot;math-container&quot;&gt;$\left(62.3 \,\textrm{cm}^{-1}\right)$&lt;/span&gt; and we can also see that this particular vibration belongs to &lt;span class=&quot;math-container&quot;&gt;$E_u$&lt;/span&gt; irreducible representations. It is also possible to see that this mode is IR active. However, I do not understand this piece of information:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;X_5' M_5'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What does this tell us?&lt;/p&gt;&#xA;&lt;p&gt;PS: We are working with point group  &lt;span class=&quot;math-container&quot;&gt;$D_{4h}$&lt;/span&gt; (&lt;a href=&quot;https://en.wikipedia.org/wiki/Tetragonal_crystal_system&quot; rel=&quot;nofollow noreferrer&quot;&gt;4/mmm&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="3945" LastEditorUserId="5" LastEditDate="2021-08-24T00:36:07.673" LastActivityDate="2021-09-05T18:54:38.823" Title="Quantum ESPRESSO ph.x output" Tags="|quantum-espresso|phonons|symmetry|kohn-sham|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6444" PostTypeId="1" CreationDate="2021-07-27T13:21:13.587" Score="5" ViewCount="264" Body="&lt;p&gt;I am trying to learn how RDF is working. To learn how RDF is working in practice I am testing the script (below) by printing all of the variables using this .xyz file example:&lt;/p&gt;&#xA;&lt;p&gt;I passed cartesian coordination data correctly, and the boundary condition and the printed variables are correct which I checked with manual calculations.&lt;/p&gt;&#xA;&lt;p&gt;However, the resulting plot only shows a flat line at &lt;strong&gt;y = 0&lt;/strong&gt;.&#xA;Probably I missed something small thing but I cannot catch it.&#xA;Have I missed something here?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      16&#xA;Energy           -200.0&#xA;A            1.977502779         1.825612486        -1.078815994&#xA;A            0.073484389        -2.915354734        -1.169129839&#xA;A           -1.682844787        -1.543503043        -2.245494959&#xA;A            0.226989000         0.103121000        -0.417822000&#xA;B            -0.693058883         0.156772052         1.151824239&#xA;B            -1.448474661        -3.517890885        -2.298992143&#xA;B            -1.458396055        -1.997135497        -0.344566446&#xA;B             0.985126104        -4.427396897        -0.775735938&#xA;B            -3.121800014        -1.219516661        -3.292662828&#xA;B             2.017385825         0.679529254         0.430803534&#xA;B             0.212637914        -1.726148783        -2.725852021&#xA;B             3.217540502         3.061671270        -1.526834132&#xA;B             1.456477430         0.338098844        -2.124519369&#xA;B            -1.187423538         0.191670365        -1.675742064&#xA;B             0.143729055         2.143022931        -0.717464213&#xA;B             1.083320805        -1.581985916        -0.284118283&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the printed variables are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;edges: [-12.    -11.999 -11.998 ...   1.199   1.2     1.201]&#xA;num_increments: 13201&#xA;x is [ 0.648635 -0.712093  1.175089  2.536351  0.431639  0.68227   1.776624&#xA;2.48202  -2.049614  2.48957  -1.061626  0.443473  0.890669 -0.407062&#xA;1.391732  3.873991]&#xA;len(x) is 16&#xA;S is 12&#xA;numberDensity is 0.009259259259259259&#xA;d is [4.16134966 5.64980835 4.16167321 1.64793118 5.16051574 4.84601737&#xA;2.79507052 3.09205521 7.29774691 2.7948553  5.45595986 5.45590615&#xA;3.0918364  4.84603638 5.16043525 2.4       ]&#xA;g[p, :]: [0. 0. 0. ... 0. 0. 0.]&#xA;result is [0 0 0 ... 0 0 0]&#xA;numberDensity is 0.009259259259259259&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RK9B2.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RK9B2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def pairCorrelationFunction_3D(x, y, z, S, rMax, dr):&#xA;&amp;quot;&amp;quot;&amp;quot;Compute the three-dimensional pair correlation function for a set of&#xA;spherical particles contained in a cube with side length S.  This simple&#xA;function finds reference particles such that a sphere of radius rMax drawn&#xA;around the particle will fit entirely within the cube, eliminating the need&#xA;to compensate for edge effects.  If no such particles exist, an error is&#xA;returned.  Try a smaller rMax...or write some code to handle edge effects! ;)&#xA;Arguments:&#xA;    x               an array of x positions of centers of particles&#xA;    y               an array of y positions of centers of particles&#xA;    z               an array of z positions of centers of particles&#xA;    S               length of each side of the cube in space&#xA;    rMax            outer diameter of largest spherical shell&#xA;    dr              increment for increasing radius of spherical shell&#xA;Returns a tuple: (g, radii, interior_indices)&#xA;    g(r)            a numpy array containing the correlation function g(r)&#xA;    radii           a numpy array containing the radii of the&#xA;                    spherical shells used to compute g(r)&#xA;    reference_indices   indices of reference particles&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;from numpy import zeros, sqrt, where, pi, mean, arange, histogram&#xA;&#xA;# Find particles which are close enough to the cube center that a sphere of radius&#xA;# rMax will not cross any face of the cube&#xA;bools1 = x &amp;gt; rMax&#xA;bools2 = x &amp;lt; (S - rMax)&#xA;bools3 = y &amp;gt; rMax&#xA;bools4 = y &amp;lt; (S - rMax)&#xA;bools5 = z &amp;gt; rMax&#xA;bools6 = z &amp;lt; (S - rMax)&#xA;&#xA;interior_indices, = where(bools1 * bools2 * bools3 * bools4 * bools5 * bools6)&#xA;num_interior_particles = len(interior_indices)&#xA;&#xA;if num_interior_particles &amp;lt; 1:&#xA;    raise  RuntimeError (&amp;quot;No particles found for which a sphere of radius rMax\&#xA;            will lie entirely within a cube of side length S.  Decrease rMax\&#xA;            or increase the size of the cube.&amp;quot;)&#xA;&#xA;edges = arange(-S, rMax + 1.1 * dr, dr)&#xA;num_increments = len(edges) - 1&#xA;g = zeros([num_interior_particles, num_increments])&#xA;radii = zeros(num_increments)&#xA;numberDensity = len(x) / S**3&#xA;&#xA;# Compute pairwise correlation for each interior particle&#xA;for p in range(num_interior_particles):&#xA;    index = interior_indices[p]&#xA;    d = sqrt((x[index] - x)**2 + (y[index] - y)**2 + (z[index] - z)**2)&#xA;    d[index] = 2 * rMax&#xA;&#xA;    (result, bins) = histogram(d, bins=edges, normed=False)&#xA;    g[p,:] = result / numberDensity&#xA;&#xA;# Average g(r) for all interior particles and compute radii&#xA;g_average = zeros(num_increments)&#xA;for i in range(num_increments):&#xA;    radii[i] = (edges[i] + edges[i+1]) / 2.&#xA;    rOuter = edges[i + 1]&#xA;    rInner = edges[i]&#xA;    g_average[i] = mean(g[:, i]) / (4.0 / 3.0 * pi * (rOuter**3 - rInner**3))&#xA;&#xA;return (g_average, radii, interior_indices)&#xA;# Number of particles in shell/total number of particles/volume of shell/number density&#xA;# shell volume = 4/3*pi(r_outer**3-r_inner**3)&#xA;&#xA;&#xA;&#xA;# preprocess the structure file (struc)&#xA;a_file = open(struc)&#xA;lines = a_file.readlines()&#xA;a_file.close()&#xA;&#xA;# del first two lines&#xA;del lines[0]&#xA;del lines[0]&#xA;&#xA;df = pd.read_fwf(struc)&#xA;df.to_csv('struc_file.csv')&#xA;&#xA;df.dropna(inplace = True)&#xA;&#xA;column_label = [&amp;quot;ID&amp;quot;, &amp;quot;type&amp;quot;, &amp;quot;b&amp;quot;, &amp;quot;c&amp;quot;]&#xA;df = pd.read_csv('struc_file.csv', names=column_label)&#xA;&#xA;df = df.drop([0, 1])    # first and second row&#xA;df = df.drop(columns = [&amp;quot;ID&amp;quot;])&#xA;new = df[&amp;quot;b&amp;quot;].str.split(&amp;quot; &amp;quot;, n = 1, expand = True)&#xA;&#xA;df[&amp;quot;x&amp;quot;] = new[0]&#xA;df[&amp;quot;y&amp;quot;] = new[1]&#xA;df[&amp;quot;z&amp;quot;] = df[&amp;quot;c&amp;quot;]&#xA;df = df.drop(columns = [&amp;quot;b&amp;quot;, &amp;quot;c&amp;quot;])&#xA;df = df.reset_index(drop=True)&#xA;&#xA;&#xA;# Calculation setup&#xA;domain_size = 12&#xA;num_particles = 10&#xA;&#xA;dr = 0.001&#xA;particle_radius = 0.1&#xA;rMax = domain_size / 10&#xA;&#xA;g_r, r, reference_indeces = pairCorrelationFunction_3D(x_particle, y_particle, z_particle, domain_size, rMax, dr)&#xA;&#xA;plt.figure()&#xA;plt.plot(r, g_r, color='black')&#xA;plt.xlabel('r')&#xA;plt.ylabel('g(r)')&#xA;plt.xlim( (-rMax, rMax) )&#xA;plt.ylim( (0, 1.05 * g_r.max()) )&#xA;plt.show()&#xA;#The script is from https://github.com/cfinch/Shocksolution_Examples/blob/master/PairCorrelation/example_3D.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="748" LastActivityDate="2021-07-28T14:09:31.040" Title="Have I missed something? RDF (radial distribution) script cannot capture the correct .xyz" Tags="|python|radial-distribution-function|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6445" PostTypeId="2" ParentId="1094" CreationDate="2021-07-27T14:08:38.607" Score="3" Body="&lt;p&gt;I am not too experienced on this topic, so take my answer with a grain of salt.&lt;/p&gt;&#xA;&lt;p&gt;PCM (Polarizable Continuum Model) deals with solvation effects by assuming that the effect of solvent molecules surrounding the solute cavity can be treated by adding point charges on the cavity surface (generally determined by considering some kind of scaled van der Waals radii). Then the solute can be polarized by the solvent field, which can in turn be polarized by the solute—and this can be solved by an iterative procedure to get the final polarized wavefunction of the solute.&lt;/p&gt;&#xA;&lt;p&gt;However, the assumption in this method is that the solute charge is entirely constrained inside the cavity (Because there is only one layer of point charges outside of the solute, which is supposed to represent all of the solvent surrounding it). But when the calculations are allowed to run without any constraint, the wavefunction of the solute always penetrates outside the solvation cavity. This is usually referred to as &amp;quot;escaped charges&amp;quot;. This leads to extra polarization of the solute, as you mention in the question.&lt;/p&gt;&#xA;&lt;p&gt;A way to model the actual solute-solvent interaction is to add more layers of point charges on the solute, to model the layers of solvent around the solute. (until most of the wavefunction of the solute is inside the layers of solvent.) This method is called the surface and volume polarization for electrostatic interaction(SVPE).&lt;/p&gt;&#xA;&lt;p&gt;The good thing about this method is that it is possible to add more and more solvent layers, until the problem of escaped charges becomes negligible, at which point, SVPE solvation gives the exact surface and volume polarization which would be obtained if the Poisson's equations were analytically solved.&lt;/p&gt;&#xA;&lt;p&gt;There is also SS(V)PE, which attempts to simulate the SVPE solvation at low cost by putting some extra point charges instead of modelling each layer explicitly.&lt;/p&gt;&#xA;&lt;p&gt;SVPE or SS(V)PE gives the electrostatic part of the solvent effect, and the non-electrostatic part can be added to it to get more accurate solvation free energies. (Just like in PCM, adding CDS terms gives the SMD model). There are two models—one where parameter-fitted non-electrostatic corrections were taken directly from SMD (called &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct100025j&quot; rel=&quot;nofollow noreferrer&quot;&gt;SMVLE&lt;/a&gt;), and other is where parameter-fitted dispersion, exchange and short-range extremum(DEFESR) correction is added(called &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct400894j&quot; rel=&quot;nofollow noreferrer&quot;&gt;CMIRS&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;These methods give very good results, especially with ions. For example, CMIRS v1.0 gives a mean unsigned error in hydration energy of 2.4 kcal/mol against experimental data for ions, whereas SMD gives 4 kcal/mol error with ions. The data is not reported separately for anions and cations, but anions in general show higher errors in solvation energies (&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.9b02340&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A 2019, 123, 44, 9498–9504&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;CMIRS v1.1 (newer parameterization) is implemented in GAMESS and Q-Chem. SMVLE is implemented only in GAMESS afaik.&lt;/p&gt;&#xA;&lt;p&gt;Reference-&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;M. J. Vilkas, C. G. Zhan, &amp;quot;An efficient implementation for determining volume polarization in self-consistent reaction field theory&amp;quot;, &lt;em&gt;J. Chem. Phys.&lt;/em&gt;, 2008, &lt;strong&gt;129&lt;/strong&gt;(19), 194109.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-07-27T16:52:52.120" LastActivityDate="2021-07-27T16:52:52.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6446" PostTypeId="1" CreationDate="2021-07-27T19:35:05.267" Score="7" ViewCount="192" Body="&lt;p&gt;I am trying to generate exchange energy separately in pyscf but didn't see a way to do that. For correlation energy, it's fairly simple but do you have any idea how to calculate exchange energy?&lt;/p&gt;&#xA;" OwnerUserId="4028" LastEditorUserId="5" LastEditDate="2021-07-27T19:39:09.850" LastActivityDate="2021-08-04T17:39:38.953" Title="How can I calculate the exchange energy for a molecule in PySCF?" Tags="|density-functional-theory|software|quantum-chemistry|pyscf|exchange-correlation|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-29T18:01:47.117" ContentLicense="CC BY-SA 4.0" />
  <row Id="6447" PostTypeId="1" AcceptedAnswerId="6534" CreationDate="2021-07-27T21:01:02.873" Score="12" ViewCount="597" Body="&lt;p&gt;After reading &lt;a href=&quot;https://chemistry.stackexchange.com/q/103387/&quot;&gt;What exactly is meant by 'multi-configurational' and 'multireference'?&lt;/a&gt;&#xA;I still don't understand what the multiple &amp;quot;references&amp;quot; are. I understand that you can for example use a HF ansatz and exited states for multi-configurational methods. And that multi reference methods use more than one configuration to build exited states. But what are these configurations? There is only one HF Slater determinant, how do the other references look?&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate if you could answer the questions with some additional formulas instead of just describing it by words :)&lt;/p&gt;&#xA;&lt;p&gt;In a comment on the question I previously asked in Chemistry Stack Exchange, I was told that these other determinants have just different occupied orbitals. But then they are excited states and should already be included in the normal multi-configurational ansatz (CISD for example).&lt;/p&gt;&#xA;&lt;p&gt;So how does CISD and multi-reference CISD differ?&lt;/p&gt;&#xA;" OwnerUserId="4029" LastEditorUserId="49" LastEditDate="2021-08-06T22:46:45.813" LastActivityDate="2021-08-09T15:44:08.067" Title="What are the references in multi-reference methods?" Tags="|quantum-chemistry|ab-initio-calculations|from-chem-se|multi-reference|mrci|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6448" PostTypeId="1" CreationDate="2021-07-27T21:19:50.150" Score="6" ViewCount="691" Body="&lt;p&gt;I have a &lt;span class=&quot;math-container&quot;&gt;$10\mu s$&lt;/span&gt; trajectory with 10,000 frames that I would like to backmap to atomistic representations so that I can compare my ensemble to experimental measurements.&lt;/p&gt;&#xA;&lt;p&gt;I am using &lt;a href=&quot;https://github.com/Tsjerk/MartiniTools&quot; rel=&quot;nofollow noreferrer&quot;&gt;MartiniTools&lt;/a&gt; for this, specifically the scripts &lt;a href=&quot;https://github.com/Tsjerk/MartiniTools/blob/master/initram.sh&quot; rel=&quot;nofollow noreferrer&quot;&gt;initram.sh&lt;/a&gt; and &lt;a href=&quot;https://github.com/Tsjerk/MartiniTools/blob/master/backward.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;backward.py&lt;/a&gt; to one-by-one generate atomic coordinate files from CG frames. I made a shell script to back-map:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;&#xA;for i in {0..10000}&#xA;    do&#xA;        ../../martini3/MartiniTools/initram.sh -f &amp;quot;trjg/_state&lt;span class=&quot;math-container&quot;&gt;$i.gro&quot; -o &quot;atomistic/charmm_state$&lt;/span&gt;i.gro&amp;quot; -to charmm27 -p atomistic_topology2.top&#xA;    done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This works fine until the script reaches frame 55, at which point the shell stops, no PDB file is output, and I get the following warnings in console:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Step 0, time 0 (ps)  LINCS WARNING&#xA;relative constraint deviation after LINCS:&#xA;rms 0.285972, max 5.254007 (between atoms 341 and 343)&#xA;bonds that rotated more than 90 degrees:&#xA; atom 1 atom 2  angle  previous, current, constraint length&#xA;    263    265   93.2    0.1580   0.2883      0.1538&#xA;    285    287   98.4    0.1638   0.2961      0.1538&#xA;    302    304  101.1    0.1703   0.4000      0.1538&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I press &lt;code&gt;CTRL+C&lt;/code&gt;, that iteration of the script is killed and it moves onto the next one but no output &lt;code&gt;.gro&lt;/code&gt; file is written. I am hoping desperately someone can help me modify the md parameters so that the energy minimization warnings/constraint warnings are ignored and I can obtain my ensemble!&lt;/p&gt;&#xA;&lt;p&gt;I tried modifying the MD parameters within &lt;code&gt;initram.sh&lt;/code&gt; to the following to see if it would flow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;integrator=steep&#xA;nsteps=$EMSTEPS (changed to 2500 instead of default 500)&#xA;emtol=9999999999 (from default 10)&#xA;emstep=0.05 (from default 0.1)&#xA;pbc=xyz&#xA;lincs-warnangle=90 (from default 30)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any help is greatly appreciated!&lt;/p&gt;&#xA;&lt;p&gt;Description of &lt;code&gt;initram.sh&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1. Projection&#xA;2. Energy minimization ( steps), excluding non-bonded interactions&#xA;   between atoms in selected groups, e.g. membrane and protein.&#xA;3. Energy minimization (500 steps)&#xA;4. Position restrained NVT simulation (300K), with time step 0.2 fs&#xA;5. Position restrained NVT simulation (300K), with time step 0.5 fs&#xA;6. Position restrained NVT simulation (300K), with time step 1.0 fs&#xA;7. Position restrained NVT simulation (300K), with time step 2.0 fs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3970" LastEditorUserId="5" LastEditDate="2021-08-24T00:49:33.363" LastActivityDate="2021-08-24T00:49:33.363" Title="Back-mapping Martini 3 coarse-grain to all-atom representations" Tags="|molecular-dynamics|gromacs|coarse-grained|martini|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-04T15:28:48.577" ContentLicense="CC BY-SA 4.0" />
  <row Id="6449" PostTypeId="2" ParentId="6447" CreationDate="2021-07-27T23:04:25.277" Score="8" Body="&lt;p&gt;Rather than starting with a single-determinant (single-reference) such as the Hartree-Fock determinant which is obtained by an HF-SCF calculation, multi-reference methods such as MRCI, MR-ACPF, MR-AQCC, and even MR-CC will start with a multi-configurational SCF (MCSCF) calcualtion. There's many types of these, and many can be found here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;What are the types of MCSCF?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Perhaps the most common starting point for an MRCI calculation is to do a CASSCF calculation. For example you might choose 3 spatial orbitals and 3 electrons and form a CAS(3,3) calculation which can result in a wavefunction that is the sum of &lt;em&gt;&lt;strong&gt;many&lt;/strong&gt;&lt;/em&gt; determinants. Now rather than doing the post-SCF (i.e. CI, CC, etc.) calculation on top of only one reference determinant, you can have many of them.&lt;/p&gt;&#xA;&lt;p&gt;Finally, based on what you wrote in your question, I want to emphasize strongly that multi-reference methods are not just for excited states, but also for &lt;em&gt;ground states&lt;/em&gt; in cases where the most dominant determinant does not have a much stronger weight in the overall wavefunction compared to some other determinants, and this happens in many molecules such as &lt;span class=&quot;math-container&quot;&gt;$\ce{Cr2}$&lt;/span&gt;, in which the ground electronic state requires a multi-reference treatment.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-09T15:44:08.067" LastActivityDate="2021-08-09T15:44:08.067" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6450" PostTypeId="1" CreationDate="2021-07-28T03:03:46.323" Score="7" ViewCount="138" Body="&lt;p&gt;I am looking for tools for symbolic calculation of quantum transport or quantum mechanics that involves Keldysh NEGF (non-equilibrium Green's function) formalism.  The closest tool I heard/seen is &lt;code&gt;symGF.m&lt;/code&gt; for Mathematica but I could not find the library/file for it.   Have anyone seen this file or equivalent tools?&lt;/p&gt;&#xA;" OwnerUserId="4030" LastEditorUserId="5" LastEditDate="2021-07-29T21:43:01.647" LastActivityDate="2021-07-29T21:43:01.647" Title="Tools for symbolic calculations of quantum transport using the Keldysh NEGF formalism" Tags="|software-recommendations|mathematical-modeling|quantum-mechanics|greens-functions|" AnswerCount="0" CommentCount="4" ClosedDate="2021-11-29T19:30:44.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="6451" PostTypeId="1" AcceptedAnswerId="6474" CreationDate="2021-07-28T04:24:02.950" Score="8" ViewCount="443" Body="&lt;p&gt;I am testing an example of the 'cut' function in ASE &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html&quot; rel=&quot;noreferrer&quot;&gt;cut&lt;/a&gt;. In this example, the surface Al(111) is created using vectors (1, -1, 0) and (0, 1, -1) included in the &amp;quot;cut&amp;quot; function. But I am not clear how to define those vectors (1, -1, 0) and (0, 1, -1). Can you help me to explain?&#xA;If I have to create the surface Al(112), which vectors should I include in the 'cut' function?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase.spacegroup import crystal&#xA;a = 4.0&#xA;aluminium = crystal('Al', [(0,0,0)], spacegroup=225,cellpar=[a, a, a, 90, 90, 90])&#xA;al111 = cut(aluminium, (1,-1,0), (0,1,-1), nlayers=3) #vectors input here&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2021-07-28T04:26:55.453" LastActivityDate="2021-07-29T22:16:09.643" Title="How to define the a, b, c vectors in the cut function in ASE" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6452" PostTypeId="1" AcceptedAnswerId="8411" CreationDate="2021-07-28T08:07:05.833" Score="6" ViewCount="105" Body="&lt;p&gt;I'm studying the nature of electronic excitation in conjugated organic dyes.&lt;/p&gt;&#xA;&lt;p&gt;To define the donor and acceptor part I've run TDDFT and CIS calculation, they both gave similar set of configurations for the transition, but the resulting electron-hole localization is not that I expected.&lt;/p&gt;&#xA;&lt;p&gt;I've got &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;-diagnostics value around 0.5 so it's not very well described by TDDFT.&lt;/p&gt;&#xA;&lt;p&gt;So I'm looking for advice for method to get accurate electron-hole localization.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastEditorUserId="5" LastEditDate="2021-12-28T00:24:34.910" LastActivityDate="2021-12-28T02:09:36.367" Title="Accurate electron-hole localization for charge-transfer transitions" Tags="|electronic-structure|td-dft|excited-states|configuration-interaction|organic-chemistry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6453" PostTypeId="2" ParentId="6444" CreationDate="2021-07-28T14:09:31.040" Score="3" Body="&lt;p&gt;Ok, I think I figured out why your code is giving a straight line. This is too big to write as a comment, so I am putting this as answer.&lt;/p&gt;&#xA;&lt;p&gt;At the start of the function, you are determining the edges of the bins of histograms:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;edges = arange(-S, rMax + 1.1 * dr, dr)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, your edges range between &lt;code&gt;-S&lt;/code&gt; and &lt;code&gt;rMax+1.1*dr&lt;/code&gt;. From the data you fed to the function, the &lt;code&gt;edges&lt;/code&gt; range from -12 to  1.2 (&lt;code&gt;edges: [-12.    -11.999 -11.998 ...   1.199   1.2     1.201]&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Your edges are mainly in the negative region, with only a small part at the end of the range extending into the positive region.&lt;/p&gt;&#xA;&lt;p&gt;Now, the array &lt;code&gt;d&lt;/code&gt; holds the distances between atom pairs, all of which are obviously positive numbers. And the values of &lt;code&gt;d&lt;/code&gt; you show:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;d is [4.16134966 5.64980835 4.16167321 1.64793118 5.16051574 4.84601737&#xA;2.79507052 3.09205521 7.29774691 2.7948553  5.45595986 5.45590615&#xA;3.0918364  4.84603638 5.16043525 2.4       ]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;all seem to be above 1.201. The function is calculating histogram in the range you gave, and since there are no values in that range, your histogram is &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; all over.&lt;/p&gt;&#xA;&lt;p&gt;It seems that there is some error in the formula that you used to calculate &lt;code&gt;edges&lt;/code&gt;. I can't say what the correct formula should be without studying the code in more detail. As it's your code, you would be able to fix it much faster.&lt;/p&gt;&#xA;&lt;p&gt;Personally, I would suggest not calculating edges explicitly, but rather using the &lt;code&gt;range=()&lt;/code&gt; argument and just specifying the number of bins in &lt;code&gt;numpy.histogram&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-07-28T14:09:31.040" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6454" PostTypeId="1" CreationDate="2021-07-28T16:04:57.073" Score="4" ViewCount="78" Body="&lt;p&gt;I'm a computer scientist, helping with a chemistry project in python.&lt;/p&gt;&#xA;&lt;p&gt;I have been working with the library &lt;code&gt;pysmiles&lt;/code&gt; in order to parse &lt;code&gt;SMILES&lt;/code&gt; into a molecule graph, and that worked fine until now. Recently, I started changing code so it will work with &lt;code&gt;RDkit&lt;/code&gt; as well, since the &lt;code&gt;RDkit&lt;/code&gt; library is much larger and has many other useful features.&lt;/p&gt;&#xA;&lt;p&gt;However, I noticed that &lt;code&gt;RDkit&lt;/code&gt; doesn't create a bond for a molecule that has a &amp;quot;zero-order bond&amp;quot;, unlike &lt;code&gt;pysmiles&lt;/code&gt; which just puts the &amp;quot;zero-order-bond&amp;quot; as a data on that edge.&lt;/p&gt;&#xA;&lt;p&gt;For technical reasons, I would like &lt;code&gt;RDkit&lt;/code&gt; to do the same as &lt;code&gt;pysmiles&lt;/code&gt;, and &lt;em&gt;do&lt;/em&gt; create a bond, writing in it that it is a &amp;quot;zero-order bond&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;As an example, the following molecule was generated by &lt;code&gt;RDkit&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6qJ0c.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6qJ0c.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want the &lt;span class=&quot;math-container&quot;&gt;$\ce{Cl-}$&lt;/span&gt; to have an edge to the &lt;span class=&quot;math-container&quot;&gt;$\ce{N}$&lt;/span&gt;, that will have the data written on it that it is a zero order bond (any other node besides &lt;span class=&quot;math-container&quot;&gt;$\ce{N}$&lt;/span&gt; would work as well, for as long as the process of choosing that node is deterministic and depends only on the molecule).&lt;/p&gt;&#xA;&lt;p&gt;How can I do this? I didn't manage to find an answer in their documentation. Thanks!&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As a side note, any technical way of making the molecule graph connected (in a way that doesn't depend on the particular &lt;code&gt;SMILES&lt;/code&gt; string for a certain molecule) will suffice for me.&lt;/p&gt;&#xA;" OwnerUserId="4042" OwnerDisplayName="nir shahar" LastEditorUserId="4042" LastEditDate="2021-07-28T20:00:08.980" LastActivityDate="2021-07-28T20:00:08.980" Title="RDkit parse zero-order bonds (python)" Tags="|python|rdkit|smiles|" AnswerCount="0" CommentCount="8" ClosedDate="2021-11-18T21:45:12.093" ContentLicense="CC BY-SA 4.0" />
  <row Id="6455" PostTypeId="1" CreationDate="2021-07-28T17:08:17.360" Score="9" ViewCount="2110" Body="&lt;p&gt;I am trying to calculate the Gibbs free energy for a bulk material. Since DFT ground state calculations give the energy at 0K, a temperature dependent part has to be added in this to obtain correct result.&lt;/p&gt;&#xA;&lt;p&gt;Can someone refer me to the correct procedure to calculate this quantity, &lt;em&gt;for example&lt;/em&gt; using VASP?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="5" LastEditDate="2021-07-28T18:53:21.160" LastActivityDate="2021-07-29T04:44:55.383" Title="How can we calculate the Gibbs free energy from first principles?" Tags="|vasp|reference-request|one-topic-per-answer|software-recommendations|gibbs-free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6456" PostTypeId="1" AcceptedAnswerId="6457" CreationDate="2021-07-28T17:41:44.353" Score="12" ViewCount="850" Body="&lt;p&gt;In a geometry optimisation, one can check if they have reached a minimum by checking the phonons. And to a certain extent, the global minimum can be confirmed by relaxing from different starting geometries (sometimes with a bit of initiation).&lt;/p&gt;&#xA;&lt;p&gt;In SCF calculations (such as Hartree-Fock), is there a way of confirming if one has obtained the global minimum? I assume one could change the initial guess and analyse the converge behaviour, but I was hoping for something a bit more analytical.&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2021-07-29T06:25:25.680" LastActivityDate="2021-07-29T06:36:48.897" Title="For DFT and Hartree-Fock, how can we know that we have a true minimum? Is there an equivalent to the &quot;frequency analysis&quot; for geometry optimization?" Tags="|quantum-chemistry|ab-initio-calculations|electronic-structure|self-consistent-field|hartree-fock|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6457" PostTypeId="2" ParentId="6456" CreationDate="2021-07-28T18:48:44.457" Score="11" Body="&lt;p&gt;You're right about the ability to change the initial guess repeatedly until you get the lowest energy, and this is how it's done in software like MOLPRO which don't offer &amp;quot;stability analysis&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;However in software like GAUSSIAN and CFOUR, you can do something called stability analysis, which is described for example in the &lt;a href=&quot;https://gaussian.com/stable/&quot; rel=&quot;noreferrer&quot;&gt;GAUSSIAN documentation under the command &lt;code&gt;Stable&lt;/code&gt;&lt;/a&gt; (make sure to click on &lt;code&gt;Options&lt;/code&gt; and see all the various different options for using the stability analysis):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;This calculation type method requests that the stability of the Hartree-Fock or DFT wavefunction be tested. Gaussian has the ability to test the stability of a single-determinant wavefunction with respect to relaxing various constraints [Seeger77, Bauernschmitt96](see also [Schlegel91a]). These include:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Allowing an RHF determinant to become UHF.&lt;/li&gt;&#xA;&lt;li&gt;Allowing orbitals to become complex.&lt;/li&gt;&#xA;&lt;li&gt;Reducing the symmetry of the orbitals.&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In CFOUR  you can use the keyword &lt;code&gt;HFSTABILITY=ON&lt;/code&gt; to tell CFOUR to do the stability analysis calculation (this basically just prints out the lowest eigenvalues and eigenvectors of the relevant orbital Hessian, but does not &amp;quot;follow&amp;quot; them to try to get a better HF solution), or &lt;code&gt;HFSTABILITY=FOLLOW&lt;/code&gt; can be used to actually try to get a lower HF solution &lt;em&gt;&lt;strong&gt;if&lt;/strong&gt;&lt;/em&gt; an instability is found during the stability analysis. More about this can be found at the &lt;a href=&quot;http://slater.chemie.uni-mainz.de/cfour/index.php?n=Main.Hartree-FockStabilityAnalysis&quot; rel=&quot;noreferrer&quot;&gt;CFOUR documentation for HF stability analysis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you properly use the &lt;code&gt;Stable&lt;/code&gt; keyword and its relevant options in GAUSSIAN, or the &lt;code&gt;HFSTABILITY=FOLLOW&lt;/code&gt; keyword in CFOUR, if lower HF solutions do exist after the first HF calculation is done, then more HF calculations will be done, and the final one should (ideally) give you an energy that can't be beat (within the basis set chosen, as well as the symmetry constraints, although I know CFOUR forces you to use &lt;code&gt;REF=UHF&lt;/code&gt; and &lt;code&gt;SYM=OFF&lt;/code&gt; so symmetry constraints may not even be possible when doing this).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-28T18:48:44.457" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6458" PostTypeId="1" CreationDate="2021-07-28T19:30:00.620" Score="6" ViewCount="1197" Body="&lt;p&gt;I heard about the polarization catastrophe in a talk about polarizable force fields.&lt;/p&gt;&#xA;&lt;p&gt;The speaker talked about how the dipole induction is damped at short range to avoid the “polarization catastrophe&amp;quot;. For example, as in &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3196664/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Apparently if two induced dipoles get two close together this leads to a singularity in the &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; matrix, which is the polarization matrix, because two rows of the matrix are degenerate.&lt;/p&gt;&#xA;&lt;p&gt;But what is the polarization catastrophe?&lt;/p&gt;&#xA;&lt;p&gt;Apparently this is also important in other contexts as well so any details would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-07-29T04:53:26.590" LastActivityDate="2021-07-31T00:15:36.310" Title="What is the polarization catastrophe?" Tags="|molecular-modeling|terminology|intermolecular-forces|electrostatic|dipole|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6459" PostTypeId="2" ParentId="6455" CreationDate="2021-07-28T20:46:12.910" Score="14" Body="&lt;p&gt;To extend your 0K energies to finite temperature, you essentially need to add up the different sources of entropy. Some examples as reviewed by Hickel &lt;em&gt;et al.&lt;/em&gt; [1]:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Vibrational entropy (usually split into harmonic and anharmonic contributions)&lt;/li&gt;&#xA;&lt;li&gt;Electronic entropy&lt;/li&gt;&#xA;&lt;li&gt;Magnetic entropy&lt;/li&gt;&#xA;&lt;li&gt;Configurational entropy&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Each of these contributions has some underlying theory or competing theories. For example, electronic entropy is quite straightfoward and is effectively a post-processing step on the electronic density of states from a typical DFT calculation. Harmonic vibrational contributions could be approximated by one of the flavors of the Debye model or treated explictly via phonons.  Magnetic entropy is relatively difficult to compute and there are multiple approaches with different performance/accuracy tradeoffs.&lt;/p&gt;&#xA;&lt;p&gt;Most of the formulations involve computing the individual contributions as a Helmoltz energy on a grid of volumes:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ F(T,V) = E_0(V) + F_\textrm{vib}(T,V) + F_\textrm{el}(T,V) + F_\textrm{mag}(T,V) + \dots \tag{1}$$&lt;/span&gt;&#xA;and computing the Gibbs energy by a Legendre transform&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ G = F + PV \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The exact procedures depend on what physics is energetically relevant for your application and how much compute you can afford to capture that physics.&lt;/p&gt;&#xA;&lt;p&gt;[1] T. Hickel, B. Grabowski, F. Körmann, J. Neugebauer, &lt;a href=&quot;https://doi.org/10.1088/0953-8984/24/5/053202&quot; rel=&quot;noreferrer&quot;&gt;Advancing density functional theory to finite temperatures: Methods and applications in steel design&lt;/a&gt;, J. Phys. Condens. Matter. 24 (2012). doi:10.1088/0953-8984/24/5/053202.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="5" LastEditDate="2021-07-29T04:44:55.383" LastActivityDate="2021-07-29T04:44:55.383" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6460" PostTypeId="1" AcceptedAnswerId="6485" CreationDate="2021-07-28T23:09:58.027" Score="8" ViewCount="1399" Body="&lt;p&gt;I recently started using both &lt;code&gt;pysmiles&lt;/code&gt; and &lt;code&gt;RDkit&lt;/code&gt; to parse &lt;code&gt;SMILES&lt;/code&gt; strings into molecules. However, I sometimes got different results between the two libraries.&lt;/p&gt;&#xA;&lt;p&gt;For example, on the molecule described by the string &lt;code&gt;OCCn2c(=N)n(CCOc1ccc(Cl)cc1Cl)c3ccccc23&lt;/code&gt;, which is parsed using &lt;code&gt;RDkit&lt;/code&gt; into the following molecule:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xQGdG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xQGdG.png&quot; alt=&quot;SMILES string converted to molecule by RDkit&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This molecule has some atom such that &lt;code&gt;RDkit&lt;/code&gt;'s &lt;code&gt;atom.GetNumImplicitHs()&lt;/code&gt; gives a value of &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;, while &lt;code&gt;pysmiles&lt;/code&gt;  &lt;code&gt;hcount&lt;/code&gt; attribute for these atoms is &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This also happens for other molecules, and also with the formal charge value I have seen a similar problem.&lt;/p&gt;&#xA;&lt;p&gt;Why does this happen? How can I know which library is &amp;quot;right&amp;quot;? Or maybe I didn't understand correctly those features (I'm no chemist, so excuse me for that)? Thanks!&lt;/p&gt;&#xA;&lt;p&gt;For completeness, the code I used to process the SMILES string with each library is shown below:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;RDkit: &lt;code&gt;molecule = RDkit.Chem.MolFromSmiles(smiles)&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;pysmiles: &lt;code&gt;molecule = pysmiles.read_smiles(smiles)&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4042" LastEditorUserId="7" LastEditDate="2021-07-29T15:26:42.877" LastActivityDate="2021-07-31T16:30:42.733" Title="RDkit and PySmiles results differ on some SMILES strings" Tags="|python|rdkit|smiles|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6461" PostTypeId="1" AcceptedAnswerId="6463" CreationDate="2021-07-29T05:53:36.047" Score="5" ViewCount="85" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\require{mediawiki-texvc}$&lt;/span&gt;&#xA;Many authors in their research papers involving VASP, report for the k-mesh sampling with a statement like this:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Gamma-Centered mesh with a resolution of &lt;span class=&quot;math-container&quot;&gt;$2\pi \times 0.02 ~~ \pu{\AA}^{-1}$&lt;/span&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Could you please tell me what its Quantum ESPRESSO equivalent is?&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-07-29T06:13:40.030" LastActivityDate="2021-07-29T06:46:04.350" Title="What is the Quantum ESPRESSO equivalent for VASP's k-mesh sampling resolution?" Tags="|vasp|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6462" PostTypeId="2" ParentId="6456" CreationDate="2021-07-29T06:36:48.897" Score="11" Body="&lt;p&gt;Just like geometry optimization, there is no practical way to be &lt;strong&gt;100%&lt;/strong&gt; sure that you have the global minimum of SCF solutions.&lt;/p&gt;&#xA;&lt;p&gt;But there are checks you can do to make sure that the SCF solution you got is a reasonable minimum. One of them is checking the electronic hessian at the SCF solution and determining the lowest eigenvalues. If one or more negative eigenvalues are found then the solution is a saddle point in the wavefunction space. Read Nike's &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6457/1380&quot;&gt;answer&lt;/a&gt; on how to do this with Gaussian and CFOUR.&lt;/p&gt;&#xA;&lt;p&gt;There are options to do this in other softwares as well, however, not all features might be available.&lt;/p&gt;&#xA;&lt;h3 id=&quot;orca-96ca&quot;&gt;Orca&lt;/h3&gt;&#xA;&lt;p&gt;In Orca, you can request a stability analysis from &lt;code&gt;%scf&lt;/code&gt; block—&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP def2-SVP NoRI SP &#xA;# only single point calculations supported&#xA;%scf&#xA;  STABPerform true  # turns on SCF stability analysis&#xA;  STABRestartUHFUnstable true # restart the UHF-SCF calculation if unstable&#xA;  STABNRoots 3  # (default 3) number of lowest eigenvalues sought&#xA;  STABlambda +0.5 # (default +0.5) mixing parameter for new UHF-SCF calculation&#xA;end &#xA;&#xA;*xyz 0 1&#xA;H 0.0 0.0 0.0&#xA;H 0.0 0.0 1.4&#xA;* &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;STABlambda&lt;/code&gt; parameter determines how much the old SCF and new orbitals for the new guess. Note that the stability calculation can be done for both RHF/RKS and UHF/UKS references, but restarting the calculation if the solution is unstable (&lt;code&gt;STABRestartUHFUnstable&lt;/code&gt;) is only allowed for UHF/UKS references.&lt;/p&gt;&#xA;&lt;p&gt;Refer to the Orca manual for other available options.&lt;/p&gt;&#xA;&lt;h3 id=&quot;gamess-0mvl&quot;&gt;GAMESS&lt;/h3&gt;&#xA;&lt;p&gt;GAMESS can also do stability analysis, but only for RHF references. The keyword &lt;code&gt;UHFCHK=.TRUE.&lt;/code&gt; has to be added to &lt;code&gt;$CONTRL&lt;/code&gt; section.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP/aug-cc-PVDZ on H2&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=ACCD $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=ENERGY ISPHER=1&#xA; DFTTYP=B3LYP UHFCHK=.TRUE. $&lt;/span&gt;END&#xA;&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;H     1.0    -7.56825     2.73003     0.00000&#xA;H     1.0    -6.86039     2.74400     0.00000&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This checks pairs of orbitals for RHF-&amp;gt;UHF instabilities. By default, it only checks HOMO-1, HOMO, LUMO, LUMO+1 and LUMO+2; but more orbitals can be checked by using the &lt;code&gt;NHOMO&lt;/code&gt; and &lt;code&gt;NLUMO&lt;/code&gt; keywords in the same section.&lt;/p&gt;&#xA;&lt;p&gt;You can also turn off any type of symmetry usage by adding the keyword &lt;code&gt;NOSYM=1&lt;/code&gt; in &lt;code&gt;$CONTRL&lt;/code&gt;, and see if that changes the SCF solution.&lt;/p&gt;&#xA;&lt;p&gt;Keep in mind though, that none of these methods are fool-proof and they should not be used as black-boxes. It is always good to check the orbital populations, energies, spin densities etc. to see if that makes chemical sense.&lt;/p&gt;&#xA;&lt;p&gt;Also note that these codes generally perform calculations with Gaussian type basis sets, and mainly for small molecules. In your question, you used the word &amp;quot;phonon&amp;quot; which makes me think that you might be considering periodic systems with plane wave basis sets. I do not have any experience with those but I believe that the same principles should apply.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-07-29T06:36:48.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6463" PostTypeId="2" ParentId="6461" CreationDate="2021-07-29T06:46:04.350" Score="5" Body="&lt;p&gt;This can be understood from solid-state physics.&lt;/p&gt;&#xA;&lt;p&gt;First of all, for the investigated system with lattice constants &lt;span class=&quot;math-container&quot;&gt;$\vec{a}_1,\vec{a}_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{a}_3$&lt;/span&gt; (length), the reciprocal lattice vectors (1/length) can be calculated as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\vec{b}_1 &amp;amp; = 2\pi \dfrac{\vec{a}_2\times\vec{a}_3}{\Omega} \\&#xA;\vec{b}_2 &amp;amp; = 2\pi \dfrac{\vec{a}_3\times\vec{a}_1}{\Omega} \\&#xA;\vec{b}_3 &amp;amp; = 2\pi \dfrac{\vec{a}_1\times\vec{a}_2}{\Omega} \\&#xA;\end{align}&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\Omega=\vec{a}_1\cdot[\vec{a_2}\times\vec{a}_3]$&lt;/span&gt; is the volume of the investigated system.&lt;/p&gt;&#xA;&lt;p&gt;Then, back to the Kohn-Sham equation solvers like QE and VASP, they will do many integrals in reciprocal space with numerical techniques, which means that you should sample the reciprocal space along &lt;span class=&quot;math-container&quot;&gt;$\vec{b}_1, \vec{b}_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{b}_3$&lt;/span&gt;. For example, if you adopt a &lt;span class=&quot;math-container&quot;&gt;$N_1 \times N_2 \times N_3$&lt;/span&gt; k-mesh, you can calculated the resolution as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\dfrac{\vec{b}_1}{N_1}, \qquad \dfrac{\vec{b}_2}{N_2}, \qquad \dfrac{\vec{b}_3}{N_3},&#xA;\end{align}&lt;/span&gt;&#xA;respectively. Basically, this just tell you how they are sampling the simulated cell in reciprocal space.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-07-29T06:46:04.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6464" PostTypeId="1" AcceptedAnswerId="6465" CreationDate="2021-07-29T12:40:22.973" Score="4" ViewCount="211" Body="&lt;p&gt;I calculated the electron density of a molecule by a DFT software (Gaussian 16) with a standard setting in terms of the basis set and hybrid functional. After that calculation, I viewed the plot about the correspondence between the obtained electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and the external potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; by Coulomb (i.e., &lt;span class=&quot;math-container&quot;&gt;$V(r) = -\sum_{i=1}^{M} \frac{Z_i}{||r-R_i||}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; is the atomic number and &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is the atomic position) on some grid points &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; in the molecule.&lt;/p&gt;&#xA;&lt;p&gt;The Hohenberg-Kohn theorem shows the one-to-one correspondence between &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;; however, my calculation result did not show it. The following figure shows that the same density values provided different potential values or the same potential values provided different density values.&lt;/p&gt;&#xA;&lt;p&gt;My calculation might be wrong, but I have tried to calculate many times, and the result seems to be correct. Why did I get such a result that seems to contradict the Hohenberg-Kohn theorem?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wWtoR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wWtoR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-07-29T13:20:58.707" LastActivityDate="2021-07-29T13:33:09.497" Title="One-to-one correspondence between electron density and external (Coulomb) potential" Tags="|density-functional-theory|electron-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6465" PostTypeId="2" ParentId="6464" CreationDate="2021-07-29T13:33:09.497" Score="5" Body="&lt;p&gt;This situation does not contradict the Hohenberg-Kohn theorems:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the same density values provided different potential values or the same potential values provided different density values.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The first Hohenberg-Kohn theorem refers &lt;em&gt;not&lt;/em&gt; to pointwise correspondence, but rather to correspondence between entire functions. It tells us that if I give you the full density—the entire function, not just values at a few points—you can (in principle) determine the shape of the full potential. However, the relationship is complex: the density at a single point will likely depend on the potential at all nearby points, and vice versa.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastActivityDate="2021-07-29T13:33:09.497" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6466" PostTypeId="1" AcceptedAnswerId="6468" CreationDate="2021-07-29T15:15:49.533" Score="7" ViewCount="2350" Body="&lt;p&gt;I came across this &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acsomega.7b00278&quot; rel=&quot;noreferrer&quot;&gt;publication&lt;/a&gt; that calculates the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; - &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; energy gap using TDDFT as implemented in Gaussian. I would like to do the same using ORCA. Im extremely new to ORCA and local orbital codes in general and would like to know how to do the same with an example of an input file.&lt;/p&gt;&#xA;" OwnerUserId="4048" LastActivityDate="2021-07-29T17:06:24.590" Title="How can I calculate the energy gap between the singlet and triplet state using ORCA?" Tags="|orca|excited-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6467" PostTypeId="2" ParentId="6460" CreationDate="2021-07-29T16:40:00.437" Score="8" Body="&lt;p&gt;Speculating a comparison of the outputs by both programs may help, I let &lt;code&gt;RDKit&lt;/code&gt; process to SMILES to yield a representation including the atom indices.  Derived from the &lt;a href=&quot;https://www.rdkit.org/docs/Cookbook.html#include-an-atom-index&quot; rel=&quot;nofollow noreferrer&quot;&gt;cookbook&lt;/a&gt;, the MWE for the Jupyter notebook was&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;from rdkit.Chem import Draw&#xA;from rdkit.Chem import rdDepictor&#xA;from rdkit.Chem.Draw import rdMolDraw2D&#xA;&#xA;from IPython.display import SVG&#xA;IPythonConsole.ipython_useSVG=True  &#xA;&#xA;&#xA;def mol_with_atom_index(mol):&#xA;    for atom in mol.GetAtoms():&#xA;        atom.SetAtomMapNum(atom.GetIdx())&#xA;    return mol&#xA;&#xA;&#xA;mol = Chem.MolFromSmiles(&amp;quot;OCCn2c(=N)n(CCOc1ccc(Cl)cc1Cl)c3ccccc23&amp;quot;)&#xA;mol = mol_with_atom_index(mol)&#xA;mc = Chem.Mol(mol.ToBinary())&#xA;&#xA;&#xA;drawer = rdMolDraw2D.MolDraw2DSVG(450, 200) &#xA;drawer.DrawMolecule(mc)&#xA;drawer.FinishDrawing()&#xA;&#xA;svg = drawer.GetDrawingText()&#xA;display(SVG(svg.replace('svg:','')))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In a second step, I requested &lt;code&gt;pysmiles&lt;/code&gt; to list for non-H atoms atom index, atom symbol (first two columns) and number of hydrogen bound (trailing column).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pysmiles import read_smiles&#xA;&#xA;smiles = &amp;quot;OCCn2c(=N)n(CCOc1ccc(Cl)cc1Cl)c3ccccc23&amp;quot;&#xA;molecule = read_smiles(smiles)&#xA;&#xA;pysmiles_list = zip(molecule.nodes(data=&amp;quot;element&amp;quot;), molecule.nodes(data=&amp;quot;hcount&amp;quot;))&#xA;for element in pysmiles_list:&#xA;    print(element)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By visual inspection, RDKit's annotated formula and pysmiles' listing agree with each other &lt;em&gt;except&lt;/em&gt; for the endocyclic nitrogens (&lt;code&gt;N:3&lt;/code&gt; and &lt;code&gt;N:6&lt;/code&gt;):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/6H5QM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6H5QM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;((0, 'O'), (0, 1))&#xA;((1, 'C'), (1, 2))&#xA;((2, 'C'), (2, 2))&#xA;((3, 'N'), (3, 1))&#xA;((4, 'C'), (4, 0))&#xA;((5, 'N'), (5, 1))&#xA;((6, 'N'), (6, 1))&#xA;((7, 'C'), (7, 2))&#xA;((8, 'C'), (8, 2))&#xA;((9, 'O'), (9, 0))&#xA;((10, 'C'), (10, 0))&#xA;((11, 'C'), (11, 1))&#xA;((12, 'C'), (12, 1))&#xA;((13, 'C'), (13, 0))&#xA;((14, 'Cl'), (14, 0))&#xA;((15, 'C'), (15, 1))&#xA;((16, 'C'), (16, 0))&#xA;((17, 'Cl'), (17, 0))&#xA;((18, 'C'), (18, 0))&#xA;((19, 'C'), (19, 1))&#xA;((20, 'C'), (20, 1))&#xA;((21, 'C'), (21, 1))&#xA;((22, 'C'), (22, 1))&#xA;((23, 'C'), (23, 0))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A similar listing of atom index, atom type, and number of hydrogens bond to the non-H may be achieved iterating with RDKit over the non-H atoms&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for atom in mol.GetAtoms():&#xA;    print(&amp;quot;{:2} {:2} {}&amp;quot;.format(atom.GetIdx(), atom.GetSymbol(),&#xA;                                atom.GetTotalNumHs()))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to yield&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 0 O  1&#xA; 1 C  2&#xA; 2 C  2&#xA; 3 N  0&#xA; 4 C  0&#xA; 5 N  1&#xA; 6 N  0&#xA; 7 C  2&#xA; 8 C  2&#xA; 9 O  0&#xA;10 C  0&#xA;11 C  1&#xA;12 C  1&#xA;13 C  0&#xA;14 Cl 0&#xA;15 C  1&#xA;16 C  0&#xA;17 Cl 0&#xA;18 C  0&#xA;19 C  1&#xA;20 C  1&#xA;21 C  1&#xA;22 C  1&#xA;23 C  0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As outlined in the answer by &lt;code&gt;@rapelpy&lt;/code&gt;, there is a problem with pysmiles which the maintainer(s) might rectify in future. The computations in this answer were performed with &lt;a href=&quot;https://pypi.org/project/pysmiles/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pysmiles&lt;/a&gt; (version 1.0.1, Jun 25, 2020), and &lt;a href=&quot;https://rdkit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDKit&lt;/a&gt; as packaged for &lt;a href=&quot;https://tracker.debian.org/pkg/rdkit&quot; rel=&quot;nofollow noreferrer&quot;&gt;Debian 11 (testing)&lt;/a&gt; (version 2020.09.4).&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="1206" LastEditDate="2021-07-31T15:43:44.327" LastActivityDate="2021-07-31T15:43:44.327" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6468" PostTypeId="2" ParentId="6466" CreationDate="2021-07-29T17:06:24.590" Score="7" Body="&lt;p&gt;First of all, if you are only interested in molecules with about the same size as the ones in the article you cited, then TDDFT is probably not the best method for this purpose. ORCA supports many methods that are much more reliable than TDDFT for singlet-triplet gaps, yet are still affordable for molecules of this size, for example DLPNO-STEOM-CCSD, NEVPT2, ICE etc. (For details please refer to the ORCA manual.) They give singlet-triplet gaps that are usually accurate to 0.1~0.2 eV, while for TDDFT, errors around ~0.5 eV are quite common. But that being said, it's still a good idea to start with TDDFT calculations, to get familiar with ORCA and the problem at hand.&lt;/p&gt;&#xA;&lt;p&gt;If you want to reproduce the Gaussian result in this paper as closely as possible, you can write the input file as follows:&lt;/p&gt;&#xA;&lt;p&gt;(1) Optimize the structure&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP/G 6-311++G(d,p) Opt Freq&#xA;%pal nprocs 8 end # this parallelizes the calculation over 8 processes&#xA;* xyz 0 1 # change 0 and 1 to the actual charge and multiplicity&#xA;# atomic coordinates here, in Angstrom&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After the job finishes, check if the geometry optimization converges and there is no imaginary frequency. If yes, prepare and run a second input file:&lt;/p&gt;&#xA;&lt;p&gt;(2) TDDFT calculation&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP/G 6-311++G(d,p)&#xA;%pal nprocs 8 end&#xA;%tddft&#xA;tda false&#xA;nroots 5 # calculate 5 singlet excited states&#xA;triplets true # calculate an equal number of triplet excited states&#xA;end&#xA;* xyzfile 0 1 xxx.xyz # xxx.xyz is the xyz file generated by the optimization job&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that the calculation will not exactly reproduce the Gaussian result, because Gaussian uses Cartesian d functions in the 6-311++G(d,p) basis set, while ORCA uses spherical d functions. The difference is expected to be within about 0.05 eV.&lt;/p&gt;&#xA;&lt;p&gt;If reproducing the literature result isn't a primary concern, it is probably better to optimize the structure at the wB97X-D3/def2-SVP level of theory, and do the TDDFT calculation at the wB97X-D3/def2-TZVP level of theory. This is because (1) B3LYP sometimes predict wrong bond length alternation patterns in large conjugated molecules; (2) B3LYP tends to underestimate the energies of triplet excited states; (3) ORCA is more optimized for the def2 basis sets, and less optimized for the Pople basis sets (6-31G(d), 6-311G(d,p) and the like). For serious research, it is advised to survey benchmark papers to decide on which DFT functional to use.&lt;/p&gt;&#xA;&lt;p&gt;Finally, there is a great resource for new ORCA users: the &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/&quot; rel=&quot;noreferrer&quot;&gt;ORCA input library&lt;/a&gt;. You can easily find example input files for the most common types of ORCA jobs.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-29T17:06:24.590" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6469" PostTypeId="2" ParentId="6438" CreationDate="2021-07-29T19:00:13.180" Score="4" Body="&lt;p&gt;ASE should be able to read forces from the additional columns. Here is an example of an .xyz file which contains forces.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2&#xA;Lattice=&amp;quot;6.0 0.0 0.0 0.0 6.0 0.0 0.0 0.0 6.0&amp;quot; Properties=species:S:1:pos:R:3:forces:R:3:magmoms:R:1 energy=-6.801137982077364 dipole=&amp;quot;-1.3543798178593251e-15 -1.5609399349163789e-15 6.566746345129899e-16&amp;quot; magmom=0.0 pbc=&amp;quot;F F F&amp;quot;&#xA;H        3.00000000       3.00000000       2.62674398      -0.00000000      -0.00000000      -0.00053835       0.00000000&#xA;H        3.00000000       3.00000000       3.37325602      -0.00000000      -0.00000000       0.00053835       0.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For ASE to read it with forces, you can do&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; import ase.io&#xA;&amp;gt;&amp;gt;&amp;gt; atoms = ase.io.read('h2.xyz')&#xA;&amp;gt;&amp;gt;&amp;gt; atoms.get_forces()&#xA;array([[-0.        , -0.        , -0.00053835],&#xA;       [-0.        , -0.        ,  0.00053835]])&#xA;&amp;gt;&amp;gt;&amp;gt; from ase import __version__&#xA;&amp;gt;&amp;gt;&amp;gt; __version__&#xA;'3.22.0b1'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I hope it helps. If not, then I suggest to post a sample of your xyz file to see if there is a way to make it compatible.&lt;/p&gt;&#xA;" OwnerUserId="1109" LastActivityDate="2021-07-29T19:00:13.180" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6470" PostTypeId="1" AcceptedAnswerId="6472" CreationDate="2021-07-29T19:27:56.880" Score="6" ViewCount="670" Body="&lt;p&gt;I know that the U atom has four unpaired electrons. Therefore it has a total spin S of 2. This means its multiplicity is 2S+1 = 5.&#xA;Now consider a complicated molecule such as &lt;span class=&quot;math-container&quot;&gt;$UF_6$&lt;/span&gt;. In theory all I need to do is calculate how many unpaired electrons exist and then for each un paired electron assign a value of 0.5 in order to get the toal spin S and then use the fact that the multiplicity is 2S +1.&#xA;However when dealing with d and f block elements things get much trickier and I am unable to work the multiplicity out.&#xA;Is there a straighforward way to determine the multiplicity of &lt;span class=&quot;math-container&quot;&gt;$UF_6$&lt;/span&gt;, or better still an online database that contains this information for many different molecules (as I would also like to eventually determine the multiplicities of Uranium and Tungsten oxides) .&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-07-29T19:49:18.980" LastActivityDate="2021-08-19T17:49:12.457" Title="How to find out the multiplicities of molecules containing d and f block species?" Tags="|molecular-modeling|electronic-structure|transition-metals|spin|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6471" PostTypeId="2" ParentId="6357" CreationDate="2021-07-29T19:30:35.007" Score="3" Body="&lt;p&gt;This was answered on the &lt;a href=&quot;https://matsci.org/t/lammps-input-card-in-a-nvidia-gpu/37400/5&quot; rel=&quot;nofollow noreferrer&quot;&gt;matsci LAMMPS forum&lt;/a&gt; by Axel Kohlmeyer.&lt;/p&gt;&#xA;&lt;p&gt;To summarize, there is a &lt;a href=&quot;https://github.com/lammps/lammps/issues/2621&quot; rel=&quot;nofollow noreferrer&quot;&gt;known bug&lt;/a&gt; (still unresolved as of 7/28/2021) that leads to a corrupted neighbor list when using GPUs in combination with a hybrid pair style. Axel suggests using the command &lt;code&gt;lmp -sf gpu -pk gpu 1 neigh no -in in&lt;/code&gt; as a workaround.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-29T19:48:48.527" LastActivityDate="2021-07-29T19:48:48.527" CommentCount="0" CommunityOwnedDate="2021-07-29T19:30:35.007" ContentLicense="CC BY-SA 4.0" />
  <row Id="6472" PostTypeId="2" ParentId="6470" CreationDate="2021-07-29T19:44:14.910" Score="8" Body="&lt;p&gt;With metals, they can often exist as different multiplicities depending on the compound they are in and it is not always simple to predict the correct multiplicity. More often than not, determining the multiplicity of the ground state is either done experimentally or by comparing the energies of likely multiplicities computationally.&lt;/p&gt;&#xA;&lt;p&gt;In your case, it seems be to well established [1-3] that &lt;span class=&quot;math-container&quot;&gt;$\ce{UF6}$&lt;/span&gt; has a closed shell (and thus singlet) ground state. For other metal compounds, you should generally seek out an experimental value first and if you can't find one, you will  essentially need to brute force the problem, calculating all possible multiplicities to determine which is the global minimum.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;P. Jeffrey Hay , &amp;quot;Ab initio studies of excited states of polyatomic molecules including spin‐orbit and multiplet effects: The electronic states of UF6&amp;quot;, The Journal of Chemical Physics 79, 5469-5482 (1983) &lt;a href=&quot;https://doi.org/10.1063/1.445665&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.445665&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Fan Wei, Guo-Shi Wu, W. H. Eugen Schwarz, and Jun Li &amp;quot;Excited States and Absorption Spectra of UF6: A RASPT2 Theoretical Study with Spin–Orbit Coupling&amp;quot;&#xA;Journal of Chemical Theory and Computation 2011 7 (10), 3223-3231&#xA;&lt;a href=&quot;https://doi.org/10.1021/ct2000233&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/ct2000233&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Shao-Wen Hu, Xiang-Yun Wang, Tai-Wei Chu, and Xin-Qi Liu&#xA;The Journal of Physical Chemistry A 2008 112 (37), 8877-8883&#xA;&lt;a href=&quot;https://doi.org/10.1021/jp804797a&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jp804797a&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-08-19T17:49:12.457" LastActivityDate="2021-08-19T17:49:12.457" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6473" PostTypeId="1" CreationDate="2021-07-29T20:14:27.907" Score="5" ViewCount="440" Body="&lt;p&gt;Is there a way to convert psp8 pseudopotential files (used for abinit) to UPF format (used for Quantum ESPRESSO)? I noticed there is the &lt;code&gt;upfconv.x&lt;/code&gt; utility in Quantum ESPRESSO but it does not support psp8 files.&lt;/p&gt;&#xA;" OwnerUserId="4050" LastEditorUserId="5" LastEditDate="2021-07-29T20:28:42.483" LastActivityDate="2021-12-27T13:36:02.697" Title="Convert PSP8 pseudopotential files to UPF format" Tags="|software|quantum-espresso|pseudopotentials|abinit|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6474" PostTypeId="2" ParentId="6451" CreationDate="2021-07-29T21:23:16.863" Score="5" Body="&lt;p&gt;As described in the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/tools.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;, the &lt;code&gt;a&lt;/code&gt;, &lt;code&gt;b&lt;/code&gt;, and &lt;code&gt;c&lt;/code&gt; vectors passed into &lt;code&gt;ase.build.cut&lt;/code&gt; define lines that make up your cell. To see that the vectors you passed in give a (111) surface, consider the third vector &lt;code&gt;c&lt;/code&gt;, which when it is not explicitly passed in, is formed using &lt;span class=&quot;math-container&quot;&gt;$\vec{c}=\vec{a} \times \vec{b}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\vec{c}$&lt;/span&gt; is then the normal vector to plane formed by &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{b}$&lt;/span&gt;, which is exactly the Miller index for the plane.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(1,-1,0)\times(0,1,-1)=(1,1,1)\to (111)$$&lt;/span&gt;&#xA;So we can see that this will give a (111) surface. But how would we select these vectors to begin with? We can use another way that Miller indices are defined in terms of intersections with lattice vectors. For example, a (111) surface should have its intercept one unit along each axis, i.e. at the points (1,0,0),(0,1,0), and (0,0,1). These 3 noncollinear points determine a plane, but we can also express this plane using two intersecting lines, which we can generate by forming vectors between pairs of these points.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(1,0,0)-(0,1,0)=(1,-1,0)=\vec{a}\\&#xA;  (0,1,0)-(0,0,1)=(0,1,-1)=\vec{b}$$&lt;/span&gt;&#xA;The particular choice of pairs is arbitrary and you could just as well have used e.g (1,0,-1) for &lt;span class=&quot;math-container&quot;&gt;$\vec{b}$&lt;/span&gt; and still produced the same plane.&lt;/p&gt;&#xA;&lt;p&gt;So how would you make a (112) surface? We want to change the surface normal to be (1,1,2), or equivalently to intersect with the first two lattice vectors as 1 and the third at 1/2. So we can substitute &lt;span class=&quot;math-container&quot;&gt;$\vec{b}=(0,1,-1/2)$&lt;/span&gt;, which will give a surface normal of &lt;span class=&quot;math-container&quot;&gt;$\vec{c}=(1/2,1/2,1)$&lt;/span&gt;, which after multiplying by the least common denominator we can see leads to a (112) surface.&lt;/p&gt;&#xA;&lt;p&gt;When generating a surface of a single compound, any scaling factor applied to each vector is irrelevant, as it will still result in a surface from the same family. However, if you are considering multiple types of surfaces forming an interface or multiple layers, you will need to consider these factors, as these will affect the relative positioning of the surfaces. An example of this given in the documentation for &lt;code&gt;ase.build.stack&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase.spacegroup import crystal&#xA;&#xA;# Create an Ag(110)-Si(110) interface with three atomic layers&#xA;# on each side.&#xA;a_ag = 4.09&#xA;ag = crystal(['Ag'], basis=[(0,0,0)], spacegroup=225,&#xA;             cellpar=[a_ag, a_ag, a_ag, 90., 90., 90.])&#xA;ag110 = cut(ag, (0, 0, 3), (-1.5, 1.5, 0), nlayers=3)&#xA;&#xA;a_si = 5.43&#xA;si = crystal(['Si'], basis=[(0,0,0)], spacegroup=227,&#xA;             cellpar=[a_si, a_si, a_si, 90., 90., 90.])&#xA;si110 = cut(si, (0, 0, 2), (-1, 1, 0), nlayers=3)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, you can work out that these should be (110) surface, but you can also see that the vectors passed for each are different to avoid placing them right on top of each other.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-07-29T22:16:09.643" LastActivityDate="2021-07-29T22:16:09.643" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6475" PostTypeId="2" ParentId="6470" CreationDate="2021-07-29T21:25:09.803" Score="5" Body="&lt;p&gt;To obtain the spin multiplicity of the ground electronic state of a molecule, can be extremely hard.&lt;/p&gt;&#xA;&lt;p&gt;In your question you mentioned &lt;span class=&quot;math-container&quot;&gt;$\ce{UF6}$&lt;/span&gt; which has 7 atoms, and not all of them being of the same element. But even for a very simple homonuclear (all atoms being of the same element) diatomic molecule  like &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe2}$&lt;/span&gt;, my answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1247/5&quot;&gt;&amp;quot;Total spin and/or multiplicity for transition metal ions?&amp;quot;&lt;/a&gt; shows that several papers from 1975-2015 were dedicated to trying to figure out the ground state spin configuration &lt;em&gt;&lt;strong&gt;and still there was no consensus&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A table that I presented in my answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4495/5&quot;&gt;&amp;quot;How to determine occupied and closed orbitals for a Molpro CASSCF calculation?&amp;quot;&lt;/a&gt; shows that &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe2}$&lt;/span&gt; is not the only homonuclear diatomic molecule for which the spin state remained unknown even after more than a century of modern spectroscopy and quantum mechanics.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately to determine the ground state spin multiplicity of a complicated molecule, one needs to either:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;calculate many energies of the molecule, each time assuming a different spin multiplicity, until you have considered all of the possible candidates, and pick the one that has the lowest energy; or&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;do spectroscopy experiments and find the ground state (most stable version of the molecule) that way.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-29T21:25:09.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6476" PostTypeId="1" CreationDate="2021-07-29T22:40:05.840" Score="12" ViewCount="446" Body="&lt;p&gt;What are some of the limitations on the use of a pairwise additive forcefields in classical molecular dynamics simulations?&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorUserId="5" LastEditDate="2021-08-02T01:18:48.860" LastActivityDate="2021-08-02T04:08:04.850" Title="Limitations of pairwise additive forcefields" Tags="|molecular-dynamics|forcefields|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6477" PostTypeId="2" ParentId="6476" CreationDate="2021-07-29T23:00:08.357" Score="8" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Axilrod%E2%80%93Teller_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;Axilrod-Teller force&lt;/a&gt; is not a &amp;quot;pairwise&amp;quot; force but a &amp;quot;3-body&amp;quot; force whose potential has the formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;V_{ijk}= E_{0} \left(&#xA;\frac{1 + 3 \cos\gamma_{i} \cos\gamma_{j} \cos\gamma_{k}}{\left( r_{ij} r_{jk} r_{ik} \right)^3}&#xA;\right),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;as opposed to a pairwise force like the Van der Waals force which is commonly used in molecular dynamics because of its presence in the Lennard-Jones potential:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{ij}= E_{0} \left(&#xA;\frac{1}{r_{ij}^6}&#xA;\right).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;A pairwise additive forcefield would probably not do well in cases where 3-body interactions like the Axilrod-Teller force are important (e.g. at very low temperatures and when very high accuracy is needed).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-02T01:19:17.667" LastActivityDate="2021-08-02T01:19:17.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6478" PostTypeId="1" AcceptedAnswerId="6481" CreationDate="2021-07-30T00:28:56.710" Score="17" ViewCount="1379" Body="&lt;p&gt;The molecular Hamiltonian (or, for simplicity, the Fock operator) contains coulomb potentials as well as momentum operators. To evaluate the coulomb potential, we need to know where the electrons are. So basically we are messing with the position and momentum of the electron at the same time. Therefore, there should be problems with uncertainty, but somehow this does not seem to be a big issue. Why?&lt;/p&gt;&#xA;" OwnerUserId="4029" LastActivityDate="2021-10-13T16:51:27.327" Title="Why is uncertainty not a big problem in computational chemistry?" Tags="|computational-chemistry|model-hamiltonians|hartree-fock|uncertainty-analysis|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6479" PostTypeId="2" ParentId="6478" CreationDate="2021-07-30T08:49:11.720" Score="12" Body="&lt;p&gt;Indeed, due to the uncertainty relation, the electrons in a molecule do not have a definite potential energy, nor do they have a definite kinetic energy (yet they have well-defined expectation values of potential energy and kinetic energy). But, assuming that the molecule is in an energy eigenstate, the two uncertainties exactly cancel out, and gives an unambiguous and definite total energy. So conceptually, the uncertainty relation does not make the total energy uncertain.&lt;/p&gt;&#xA;&lt;p&gt;In practice, the uncertainty relation does make computational chemistry much more difficult than it would otherwise be. If a particle could have simultaneously a certain momentum and a certain position, then the ground state of the system will have all electrons absorbed into the nuclei, and there is no longer concepts like bonding, or electronic structure in general, so computational chemistry will become completely trivial. Thus, we generally do not view the uncertainly relation as a problematic issue, because without the uncertainly relation there is essentially no computational chemistry: not only the problems are gone, but the whole discipline will disappear too. (In fact, as the electrons collapse into the nuclei, we will all disappear too...)&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-07-30T08:49:11.720" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6480" PostTypeId="1" CreationDate="2021-07-30T14:30:38.197" Score="13" ViewCount="793" Body="&lt;p&gt;I have been running MD simulations on water droplets with an ion in them. I am trying to implement a program that could calculate the radial distribution function from &lt;strong&gt;ion&lt;/strong&gt; to &lt;strong&gt;oxygen&lt;/strong&gt; (or ion to hydrogen)&lt;/p&gt;&#xA;&lt;p&gt;I use the MDAnalysis Python program to read the trajectory file and provide coordinates of atoms, frame by frame. Following the example given here, I have written a Python code (comments are added to explain each line):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import MDAnalysis as mda&#xA;import matplotlib.pyplot as plt&#xA;import numpy as np&#xA;&#xA;trj300 = mda.Universe(&amp;quot;file.psf&amp;quot;,&amp;quot;trajectory.dcd&amp;quot;) #load files&#xA;oxy = trj300.select_atoms('name OH2')&#xA;cal = trj300.select_atoms('name CAL') # ion is calcium here&#xA;&#xA;mybinsize = 80 # set up the bins for the histogram&#xA;counts300 = np.zeros(mybinsize,dtype=np.int_) #numpy histogram generates same no. of counts as binsize argument&#xA;for frame1 in trj300.trajectory[5000:]: # discard initial 100 ns&#xA;    dist_vec = oxy.positions - cal.position # from each oxygen coordinate, subtract ion coodinate&#xA;    dist_scal = np.linalg.norm(dist_vec,axis=1) # get list of ion-oxygen distances&#xA;    tmp_hist, lengths300 = np.histogram(dist_scal,bins=mybinsize,range=(0,18)) # calculate histogram&#xA;    counts300 += tmp_hist # collect the histogram counts of each frame into one array&#xA;&#xA;# normalize the count by dividing by number of frames&#xA;counts300_mod = counts300/len(trj300.trajectory[5000:])&#xA;# calculate the volume of each shell (determined by bin width)&#xA;shell_volumes300 = (4/3) * np.pi * (lengths300[1:]**3 - lengths300[:-1]**3)&#xA;# normalize the count by dividing each by shell volume (because the shell volume changes with radius)&#xA;counts300_mod = counts300_mod/shell_volumes300&#xA;# normalize by dividing by the number of selected oxygen atoms&#xA;counts300_mod = counts300_mod/len(oxy) # -&amp;gt; should this be done??&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I plot with pyplot:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;plt.plot((lengths300[:-1]+lengths300[1:])/2,counts300_mod,color='red')&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and get (click for larger image):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xJFwKl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xJFwKm.png&quot; alt=&quot;calcium-oxygen radial distribution function&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first peak has an intensity of ~ 0.0004.&lt;/p&gt;&#xA;&lt;p&gt;However, when I compare it to the one I generated from VMD, the shape matches, but the y-axis does not match (click for larger images):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/grAXL.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/grAXLm.png&quot; alt=&quot;VMD g(r) plugin&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/73nnG.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/73nnGm.jpg&quot; alt=&quot;calculated calcium-oxygen rdf from VMD&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the first peak appears at the same location on x-axis (~2.5 Angstrom) but it's intensity on y-axis is 0.015, it does not match.&lt;/p&gt;&#xA;&lt;p&gt;This makes me believe that I have gotten the formulas for normalization of RDF wrong. Clearly the same pattern is visible, which means histogramming and shell-volume normalization was done correctly. &lt;strong&gt;Which formulas should I use to calculate the RDF?&lt;/strong&gt; &lt;strong&gt;Have I missed a nomralization procedure in my algorithm?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note: I have tried removing the normalization for frame number, or the normalization by the number of oxygen atoms, but &lt;strong&gt;neither&lt;/strong&gt; gives the same value as VMD.&lt;/p&gt;&#xA;&lt;p&gt;If someone knows how to accomplish this with or without Python, I'd be interested in their answers. &lt;strong&gt;The programming language or scripting language is not the most important aspect of this question.&lt;/strong&gt; I want to know the correct algorithm (i.e. formula) for RDF calculation when there is no PBC.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-12-31T10:15:35.793" LastActivityDate="2022-12-30T15:45:21.060" Title="How to calculate RDFs for MD trajectories without PBC, directly from coordinates?" Tags="|molecular-dynamics|python|vmd|radial-distribution-function|" AnswerCount="1" CommentCount="17" ClosedDate="2023-01-04T00:15:46.127" ContentLicense="CC BY-SA 4.0" />
  <row Id="6481" PostTypeId="2" ParentId="6478" CreationDate="2021-07-30T19:49:14.397" Score="17" Body="&lt;p&gt;Following your arguments, we would see also a 'violation' of the Heisenberg uncertainty principle (HUP) in single-particle quantum mechanics, e.g. in a Hamiltonian of a particle in an external potential:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H = \hat{p}^2/2m  + V(\hat x) \quad .\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But writing down such a Hamiltonian does not mean that we know the position or momentum (or both) of this particle. The HUP does not state that you can't write a Hamiltonian like this (or more generally a many-body Hamiltonian).&lt;/p&gt;&#xA;&lt;p&gt;Similarly, writing the wave function as &lt;span class=&quot;math-container&quot;&gt;$\psi(x) \equiv \langle x|\psi\rangle$&lt;/span&gt; does not mean that we know the particle is at position &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, but instead the wave function gives the corresponding probability amplitude.&lt;/p&gt;&#xA;&lt;p&gt;In fact, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Uncertainty_principle#Robertson%E2%80%93Schr%C3%B6dinger_uncertainty_relations&quot; rel=&quot;noreferrer&quot;&gt;Robertson uncertainty relations&lt;/a&gt; for the position and the momentum operators &lt;span class=&quot;math-container&quot;&gt;$ \hat x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat p$&lt;/span&gt; say that (under certain assumptions) their corresponding variances in a physical (normalized) state &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; fulfill&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_\psi(\hat x) \, \sigma_\psi(\hat{p}) \geq \hbar/2  . \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It tells you that if you prepare an ensemble of identical states &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; and measure the position and momentum (separately) many times, then the respective variances of these measurements fulfill the above inequality.&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2021-10-13T16:51:27.327" LastActivityDate="2021-10-13T16:51:27.327" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6482" PostTypeId="2" ParentId="6458" CreationDate="2021-07-30T20:29:01.893" Score="3" Body="&lt;p&gt;In short, the polarization catastrophe is the fact that the classical description of polarization applied to point dipoles contains a singularity which occurs at a distance which should regularly be sampled in the course of ordinary classical dynamics.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;More specifically, the polarization catastrophe is the failure that happens when one tries to describe the interactions of molecules with polarizable atoms without any kind of short-range damping. There is a very popular solution to this problem called Thole-damping[1]. Thole explains the basics of the problem in Ref. [1], so I will just paraphrase some portions of what is explained there, but the whole paper is quite a good read.&lt;/p&gt;&#xA;&lt;p&gt;The polarizability is the dipole response of a molecule to an applied field,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu_{mol}=\alpha_{mol}E \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Getting &lt;span class=&quot;math-container&quot;&gt;$\alpha_{mol}$&lt;/span&gt; is actually somewhat non-trivial as it requires contracting a tensor of all the atomic polarizabilities into a single tensor describing the molecular response. Thole provides the analytic solution to this for the case of a diatomic both parallel and perpendicular to the bond axis:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{\mathbin{\|}}=\frac{\alpha_A+\alpha_B+4\alpha_A\alpha_B/r^3}{1-4\alpha_A\alpha_B/r^6}\tag{2}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{\perp}=\frac{\alpha_A+\alpha_B-2\alpha_A\alpha_B/r^3}{1-\alpha_A\alpha_B/r^6}\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This has a singularity in &lt;span class=&quot;math-container&quot;&gt;$\alpha_{\mathbin{\|}}$&lt;/span&gt; when &lt;span class=&quot;math-container&quot;&gt;$r=(4\alpha_A\alpha_B)^{1/6}$&lt;/span&gt;. So, in other words, the polarizability blows up at certain atom-atom distances, which tends to be catastrophic for the results of your simulation. Hence, polarization catastrophe.&lt;/p&gt;&#xA;&lt;p&gt;This is somewhat interesting because clearly this doesn't happen in nature, so some kind of damping is required. Thole damping is, in my opinion, a very elegant way of solving the problem. The paper explains it better than I will.  Essentially, the method changes the length scale associated with the dipole interactions that nonetheless follow the appropriate limits and makes infinite polarizabilities much less likely. In the last paragraph of section 3, some approximate bounds on the stability of the polarization are given.&lt;/p&gt;&#xA;&lt;p&gt;Note that there are other methods of calculating polarization that also avoid the polarization catastrophe. Drude oscillators tend to be good at avoiding this problem I think. Don't take my word for that though.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1] Thole, B. T. (1981). Molecular polarizabilities calculated with a modified dipole interaction. Chemical Physics, 59(3), 341-350.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-07-31T00:15:36.310" LastActivityDate="2021-07-31T00:15:36.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6483" PostTypeId="2" ParentId="6478" CreationDate="2021-07-30T23:29:46.417" Score="9" Body="&lt;p&gt;A common textbook statement of the uncertainty principle is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA; \Delta x \Delta p \ge \frac{\hbar}{2},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Delta p$&lt;/span&gt; are the uncertainties in measurements of the position &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and momentum &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; respectively. What mathematically is an &amp;quot;uncertainty&amp;quot;? In this case it's the standard deviation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{2}&#xA;\Delta x &amp;amp;\equiv \sqrt{\left\langle \hat{x}^2  \right\rangle - \Big\langle \hat{x}  \Big\rangle^2} \\&#xA;\Delta p &amp;amp;\equiv \sqrt{\left\langle \hat{p}^2  \right\rangle - \Big\langle \hat{p}  \Big\rangle^2},\tag{3}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and from our quantum mechanics courses we know the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Big\langle \hat{x}  \Big\rangle &amp;amp;\equiv \int_{-\infty}^{\infty} \psi(x)^* x \psi(x)\textrm{d}x \tag{4}\\&#xA;\left\langle \hat{x}^2  \right\rangle &amp;amp;\equiv \int_{-\infty}^{\infty} \psi(x)^* x^2 \psi(x)\textrm{d}x \tag{5}\\&#xA;\Big\langle \hat{p} \Big\rangle &amp;amp;\equiv \int_{-\infty}^{\infty} \psi^*(x)\left( \frac{\hbar}{\textrm{i}} \right)\frac{\partial}{\partial x} \psi(x)\textrm{d}x \tag{6}\\&#xA;\left\langle \hat{p}^2 \right\rangle &amp;amp;\equiv \int_{-\infty}^{\infty} \psi^*(x)\left( \frac{\hbar}{\textrm{i}} \right)^2\frac{\partial^2}{\partial x^2} \psi(x)\textrm{d}x. \tag{7}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now in computational chemistry, when we're calculating energies for whatever reason (geometry optimization, singlet-triplet-gap, excitation energies, ionization energies, electron affinities, potential energy surfaces, reaction energies, etc.) we are calculating the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Big\langle H \Big\rangle \equiv  \int_{-\infty}^{\infty} \psi(x)^* H\psi(x)\textrm{d}x. \tag{8}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now you seem to be concerned about the fact that the &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; in Eq. 8 involves both &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; and we can never have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Big\langle \hat{x}^2 \Big\rangle - \Big\langle \hat{x} \Big\rangle^2 &amp;amp;= 0, ~~\textrm{or} \tag{9} \\&#xA;\Big\langle \hat{p}^2 \Big\rangle - \Big\langle \hat{p} \Big\rangle^2 &amp;amp;= 0.\tag{10}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In fact, you could also have asked, how can we ever get the quantity in Eq. 6? Because the right-hand-side involves both &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, just like Eq. 8 does.&lt;/p&gt;&#xA;&lt;p&gt;The answer to your concern is that just because we cannot have Eqs. 9 or 10, does not mean that we can't calculate Eq. 8.&lt;/p&gt;&#xA;&lt;p&gt;We do not need to &amp;quot;know&amp;quot; with some great accuracy, the position of the system to calculate Eq. 8: &lt;strong&gt;We are actually &lt;em&gt;integrating&lt;/em&gt; over all possible values of position!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-07-30T23:29:46.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6484" PostTypeId="2" ParentId="1786" CreationDate="2021-07-31T10:22:29.447" Score="7" Body="&lt;h1&gt;Rosetta@home&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Research area&lt;/strong&gt;: Protein structure prediction and disease related research (Alzheimer, HIV, COVID-19, etc.), but also a testing framework for new methods in structural bioinformatics&lt;br&gt;&#xA;&lt;strong&gt;Initiated by&lt;/strong&gt;: &lt;a href=&quot;https://cruizbran.medium.com/rosetta-home-the-origin-786e8c1171c4&quot; rel=&quot;noreferrer&quot;&gt;University of Washington&lt;/a&gt;&lt;br&gt;&#xA;&lt;strong&gt;Present leader&lt;/strong&gt;: Baker laboratory (University of Washington)&lt;br&gt;&#xA;&lt;strong&gt;Active&lt;/strong&gt;: October 2005 to Present &lt;br&gt;&#xA;&lt;strong&gt;Supported OS&lt;/strong&gt;: Windows, Mac, Linux, Android&lt;br&gt;&#xA;&lt;strong&gt;Supported hardware types&lt;/strong&gt;: Anything supported by &lt;a href=&quot;https://boinc.berkeley.edu/&quot; rel=&quot;noreferrer&quot;&gt;BOINC&lt;/a&gt;&lt;br&gt;&#xA;&lt;strong&gt;Peak FLOPS&lt;/strong&gt;: 1.7 petaFLOPS on 28 March 2020 &lt;br&gt;&#xA;&lt;strong&gt;Resulted in&lt;/strong&gt;: Multiple publications, played a role in the development of &lt;a href=&quot;https://en.wikipedia.org/wiki/NL-201&quot; rel=&quot;noreferrer&quot;&gt;NL-201&lt;/a&gt;. Some of the results are used as the basis for Folding@home projects by providing the most likely structure, where Folding@home will verify the results and add details on molecule shape. &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Uses the same Berkeley Open Infrastructure for Network Computing (BOINC) system as SETI@home (extraterrestrial), LHC@home (fundamental physics) and Einstein@home (astrophysics, pulsars), making it run on almost any CPU and GPU (some run it on a  Raspberry Pi). With a mobile user-interface, you can keep track of your progress from a mobile device as well.&lt;/p&gt;&#xA;" OwnerUserId="653" LastEditorUserId="5" LastEditDate="2021-07-31T15:14:41.993" LastActivityDate="2021-07-31T15:14:41.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6485" PostTypeId="2" ParentId="6460" CreationDate="2021-07-31T10:53:47.260" Score="6" Body="&lt;p&gt;It is a bug in pysmiles.&lt;/p&gt;&#xA;&lt;p&gt;pysmiles has problems with aromatic nitrogen if the SMILES is in aromatic form (lower case) but not if it is kekulized (upper case and double bonds)&lt;/p&gt;&#xA;&lt;p&gt;If we add the hydrogens to the molecule, the nitrogens on index 3 and 6 have none, because they have already three bonds.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;from rdkit.Chem import Draw&#xA;import pysmiles&#xA;&#xA;s1 = 'OCCn2c(=N)n(CCOc1ccc(Cl)cc1Cl)c3ccccc23'  # aromatic&#xA;s2 = 'OCCN2C(=N)N(CCOC1=CC=C(Cl)C=C1Cl)C3=CC=CC=C23'  # kekulized&#xA;&#xA;&#xA;def show_implicit_h(smiles):&#xA;    m = Chem.MolFromSmiles(smiles)&#xA;    for atom in m.GetAtoms():&#xA;        atom.SetProp('atomLabel', str(atom.GetIdx()))&#xA;    m = Chem.AddHs(m)&#xA;    return Draw.MolToImage(m, size=(300, 300))&#xA;&#xA;&#xA;show_implicit_h(s1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/p0pE5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/p0pE5.png&quot; alt=&quot;aromatic&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;show_implicit_h(s2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/p0pE5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/p0pE5.png&quot; alt=&quot;kekulized&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Counting the hydrogen on both smiles shows that pysmiles finds hydrogen in the aromatic, but not in the kekulized SMILES.&#xA;RDKit finds none in both.&lt;/p&gt;&#xA;&lt;p&gt;Columns: Index, Symbol, hcount pysmiles, hcount RDKit&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def count_implicit_h(s):&#xA;    m = Chem.MolFromSmiles(s)&#xA;&#xA;    mol = pysmiles.read_smiles(s)&#xA;    hc = mol.nodes(data='hcount')&#xA;&#xA;    for n in hc:&#xA;        print(n[0],&#xA;              m.GetAtomWithIdx(n[0]).GetSymbol(), n[1],&#xA;              m.GetAtomWithIdx(n[0]).GetNumImplicitHs())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;aromatic form (&lt;code&gt;count_implicit_h(s1)&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 O 1 1&#xA;1 C 2 2&#xA;2 C 2 2&#xA;3 N 1 0&#xA;4 C 0 0&#xA;5 N 1 1&#xA;6 N 1 0&#xA;7 C 2 2&#xA;8 C 2 2&#xA;9 O 0 0&#xA;10 C 0 0&#xA;11 C 1 1&#xA;12 C 1 1&#xA;13 C 0 0&#xA;14 Cl 0 0&#xA;15 C 1 1&#xA;16 C 0 0&#xA;17 Cl 0 0&#xA;18 C 0 0&#xA;19 C 1 1&#xA;20 C 1 1&#xA;21 C 1 1&#xA;22 C 1 1&#xA;23 C 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;kekulized form (&lt;code&gt;count_implicit_h(s2)&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 O 1 1&#xA;1 C 2 2&#xA;2 C 2 2&#xA;3 N 0 0&#xA;4 C 0 0&#xA;5 N 1 1&#xA;6 N 0 0&#xA;7 C 2 2&#xA;8 C 2 2&#xA;9 O 0 0&#xA;10 C 0 0&#xA;11 C 1 1&#xA;12 C 1 1&#xA;13 C 0 0&#xA;14 Cl 0 0&#xA;15 C 1 1&#xA;16 C 0 0&#xA;17 Cl 0 0&#xA;18 C 0 0&#xA;19 C 1 1&#xA;20 C 1 1&#xA;21 C 1 1&#xA;22 C 1 1&#xA;23 C 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3494" LastEditorUserId="1206" LastEditDate="2021-07-31T16:30:42.733" LastActivityDate="2021-07-31T16:30:42.733" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6486" PostTypeId="1" AcceptedAnswerId="6513" CreationDate="2021-08-01T00:56:53.463" Score="10" ViewCount="1808" Body="&lt;p&gt;I often see supercells and slabs explained like this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$2\sqrt{2} \times 6$&lt;/span&gt; slab of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; (001)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sqrt{2} \times \sqrt{2} \times 2$&lt;/span&gt; supercell of &lt;span class=&quot;math-container&quot;&gt;$\ce{Y Ba(1−x)Sr(x)CuFeO5}$&lt;/span&gt; (&lt;a href=&quot;https://www.researchgate.net/figure/a-2-2-2-Supercell-of-YBa1-xSrxCuFeO5-showing-FeO5-and-CuO5-square-pyramids-in_fig1_315494032&quot; rel=&quot;noreferrer&quot;&gt;see here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Take &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt;, for example. Can someone please help me understand how we can have &lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}$&lt;/span&gt; of a unit cell for this case? Thank you.&lt;/p&gt;&#xA;" OwnerUserId="4059" LastEditorUserId="5" LastEditDate="2021-08-01T03:03:29.457" LastActivityDate="2022-06-24T18:14:57.637" Title="Help understanding square root notation of supercell" Tags="|vesta|2d-lattice|supercell|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6490" PostTypeId="5" CreationDate="2021-08-02T00:15:56.987" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.physics.rutgers.edu/pythtb/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.physics.rutgers.edu/pythtb/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-02T00:15:56.987" LastActivityDate="2021-08-02T00:15:56.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6491" PostTypeId="4" CreationDate="2021-08-02T00:15:56.987" Score="0" Body="Questions about or related to the Python Tight Binding (PythTB) software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-02T00:15:56.987" LastActivityDate="2021-08-02T00:15:56.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6492" PostTypeId="2" ParentId="6476" CreationDate="2021-08-02T01:06:42.847" Score="5" Body="&lt;p&gt;Pairwise force-fields neglects 3 body and higher interactions (many body). As Nike pointed out, there are force-fields that can take into account higher order interactions and still be somewhat pairwise, but parameterizing them is hard(er). It is easier to parameterize a simple model, and often, more accurate. We have put alot of work into simple pairwise FF's. and are pretty good at fudging them, I mean, parameterizing them.&lt;/p&gt;&#xA;&lt;p&gt;An important piece of the many body problem is polarization. Classical pairwise FF's are fixed charge. They are impervious to their environment which is an obvious weakness, since the electrons in a molecule would shift around depending on distance, orientation and type of molecules surrounding them.&lt;/p&gt;&#xA;&lt;p&gt;Generally pairwise FF's use quadratic potentials (Hooke's law) for describing intramolecular bonding. This means it is impossible to break or form a bond. This is a classic example of a weakness, but this is only really a weakness if you are interested in kinetics. If you are after thermodynamic properties, for instance, chemical reaction equilibria, you do not need to bother with manually breaking and forming bonds. You can calculate the chemical potentials of the molecules of interest(alchemical free energy calculations are one way) and use thermodynamics to figure out what and how far the reactions will progress. You could also use Reaction Ensemble Monte Carlo, which is again calculates chemical equilibria without actually breaking or forming bonds. The take-home from this paragraph is that when people tell you you can't do something, just be clever and figure out a way.&lt;/p&gt;&#xA;&lt;p&gt;There are two strengths to pairwise FF's, one of which is also their downfall. Pairwise FF's are very fast to use, so time or ensembles can be thoroughly sampled. However, this speed is due to their reliance on parameters which essentially fudge the fact that they ignore quite a bit of physics, such as many body interactions. Parameters are fit so that the  FF will replicate some kind of experimental(or computational) data. The FF is constrained to systems generally similar to that of the data to which it was fit. Some typical examples of this being an issue is using a FF for the same molecule in different phases. Of this, the solid phase is the most troubling. Most FF's are fit for gas or condensed phase simulations, and are poor at solid phases, which is a problem considering how important the solid phase is to the booming biotech/pharma industry.&lt;/p&gt;&#xA;&lt;p&gt;The nice thing though about pairwise FF is that it is not all that hard to fit them to specific systems. This is happening alot, particularly in the crystal structure prediction community (they often use multipole FF's as well though). Hundreds of thousands or even millions of possible crystal structures for pure or multi-component crystals are generated, pairwise or multipole Force-Fields are fit to many of the crystals structures and then the crystals are evaluated using the custom FF, and the majority is thrown out. More sophisticated methods, like plane-wave DFT are then used to figure out the best structure. This is because, even when custom fit, a pairwise (or even multipole expansion) FF is missing essential physics and not quite accurate enough.&lt;/p&gt;&#xA;&lt;p&gt;That said, &lt;a href=&quot;https://www.eyesopen.com/crystal-structure-prediction&quot; rel=&quot;noreferrer&quot;&gt;OpenEye&lt;/a&gt; is doing some interesting things with their multipole FF that is performing as well as plane-wave DFT for crystal structure prediction, but is an order of magnitude faster, which just goes to show, people give up on simple models way too fast a.k.a. it is easier to publish research if you claim something new is needed, but alas, here we are still using pairwise FF's. I have a feeling one could probably perform as well as the multipole models by simply adding off-center charges and doing a good parameterization ;)&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-08-02T01:13:06.360" LastActivityDate="2021-08-02T01:13:06.360" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6493" PostTypeId="2" ParentId="6476" CreationDate="2021-08-02T04:08:04.850" Score="4" Body="&lt;p&gt;There are many deficiencies in pairwise force fields that are balancing to perform well at some specific task. Pairwise interactive force fields are almost always parameterized to reproduce some kind of experimental data. That experimental data is gathered at some finite temperature and pressure and most likely does not appear in the actual potential. That is, many potentials strive to reproduce some radial distribution function, but the RDF is not actually part of the interaction potential, so the connection between parameters and experiment is somewhat fabricated. This means that most pairwise potentials are not even representations of the Born-Oppenheimer potential energy surface. Hence, the dynamics generated with them are occurring on some kind of pseudo free-energy surface. This is a drawback if you are interested in phenomena happening over a large range of temperatures, particularly in the low temperature limit. When going to low temperature, nuclear quantum effects will probably become relevant, but doing a path integral simulation with pairwise potentials would not be physically reliable since quantum effects are already parameterized in to some extent.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, pairwise potentials totally fail to simultaneously capture both energetic and structural components of systems that have large many-body effects. Water is the most important example in this case. Nearly all pairwise additive water models exhibit the wrong trend in structures going from the gas-phase to the condensed phase. This is because in the condensed phase, the average dipole moment on each water increases due to polarization from the surrounding environment. Without polarization (i.e. with fixed charges), all you can do to increase the dipole is narrow the bond angle (bring charges more in line), when experimentally the bond angle increases going from the gas phase to clusters to liquid to ice.&lt;/p&gt;&#xA;&lt;p&gt;The most accurate water models either explicitly fit electronic energies for the short-range part of the potential (MB-Pol, HBB2, etc.) or use induced dipoles to add in many-body effects. These potentials actually live on the Born-Oppenheimer surface, so it is actually more appropriate to carry out nuclear quantum simulations with them than ordinary molecular dynamics. Even though these potentials tend to be much slower to evaluate, they give the right answers for the right reasons, and hence are transferable across the entire phase diagram. They also manage to simultaneously describe molecular structure and energetics correctly while capturing appropriate dynamics.&lt;/p&gt;&#xA;&lt;p&gt;There is a certainly a place for both types of potentials, but whenever pairwise potentials give you the right answer, it's because they've been manufactured to do so for the system you're interested in. You shouldn't expect it to happen again in a different situation. Many-body models are much more reliable. They are, however, much harder to make and can't access the same timescales as pairwise additive models.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-08-02T04:08:04.850" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6494" PostTypeId="1" CreationDate="2021-08-02T08:57:48.217" Score="7" ViewCount="279" Body="&lt;p&gt;Suppose you are given the atomic number of an element, e.g. Technetium, which is 43. Is it possible to return an array which shows the distribution of electrons across different shells of an atom using vanilla JavaScript?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example Input/Output:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Atomic number&lt;/th&gt;&#xA;&lt;th&gt;Electronic configuration&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;20&lt;/code&gt; (Calcium)&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;[2, 8, 8, 2]&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;43&lt;/code&gt; (Technetium)&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;[2, 8, 18, 13, 2]&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;50&lt;/code&gt; (Tin)&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;[2, 8, 18, 18, 4]&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;" OwnerUserId="4067" LastEditorUserId="7" LastEditDate="2021-08-02T14:37:10.957" LastActivityDate="2021-08-02T14:37:10.957" Title="Calculate number of electrons per shell for an atom" Tags="|computational-chemistry|nanoparticles|programming|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6495" PostTypeId="2" ParentId="6383" CreationDate="2021-08-02T09:45:06.710" Score="5" Body="&lt;p&gt;A complete input card is given for the previous post about HSE06+SOC band structure calculation.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Step-I: DFT SCF calculation with SOC (&lt;code&gt;INCAR&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; System=XXX&#xA; ISTART=0&#xA; ICHARG=2                      &#xA; ENCUT=400                     &#xA; EDIFF=1E-6                     &#xA; NELM=300                       &#xA; ISMEAR=-5                      &#xA; #SIGMA=0.05                     &#xA; IALGO=38                       &#xA; #LREAL=Auto                    &#xA;&#xA; #SOC-related:&#xA; LSORBIT=.TRUE.                &#xA; SAXIS= 0 0 1  &#xA; ISYM=0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Step-II: DFT band calculation with SOC (&lt;code&gt;INCAR&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; System=XXX&#xA; ISTART=0                      &#xA; ICHARG=11                     &#xA; ENCUT=400                      &#xA; EDIFF=1E-6                     &#xA; NELM=300                     &#xA; ISMEAR=0                      &#xA; SIGMA=0.05                     &#xA; IALGO=38                       &#xA; LREAL=False&#xA;&#xA; #SOC-related:&#xA; LSORBIT=.TRUE.                &#xA; SAXIS= 0 0 1  &#xA; ISYM=0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Step-III: HSE06 SCF calculation with SOC (&lt;code&gt;INCAR&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System=XXX&#xA;#ISTART=0  &#xA;#ICHARG=2&#xA;ENCUT=400 &#xA;EDIFF=1E-6 &#xA;NELM=120                    &#xA;ISMEAR=0                      &#xA;SIGMA=0.05                     &#xA;#IALGO=38                      &#xA;#LREAL=False &#xA;&#xA;#SOC-related:&#xA;LSORBIT=.TRUE.                &#xA;SAXIS= 0 0 1  &#xA;ISYM=0                   &#xA;&#xA;#HSE06-related:&#xA;LHFCALC = .TRUE.&#xA;HFSCREEN = 0.2&#xA;ALGO = Damped         #Damped/Normal/All&#xA;TIME = 0.4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Step-IV: HSE06 NSCF calculation with SOC:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System=XXX&#xA;#ISTART=0                      &#xA;#ICHARG=2                       &#xA;ENCUT=400                     &#xA;EDIFF=1E-6                     &#xA;NELM=300                      &#xA;ISMEAR=0                &#xA;SIGMA=0.05                     &#xA;#IALGO=38                      &#xA;#LREAL=False &#xA;&#xA;#SOC-related:&#xA;LSORBIT=.TRUE.                &#xA;SAXIS= 0 0 1  &#xA;ISYM=0                  &#xA;&#xA;#HSE06 related:&#xA;LHFCALC = .TRUE.               &#xA;HFSCREEN = 0.2&#xA;ALGO = Normal                  !use Normal&#xA;TIME = 0.4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can check the meaning of each tag from &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspwiki&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-09-05T02:17:37.100" LastActivityDate="2021-09-05T02:17:37.100" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6496" PostTypeId="2" ParentId="6494" CreationDate="2021-08-02T09:56:38.917" Score="9" Body="&lt;p&gt;Yes - you can just pre-calculate them and hard-code them into your code, so that the script is simply a conditional switch that returns the required array when given the atomic number, without any actual calculation. Although this gives a script that is much longer than it needs to be, it's less susceptible to unexpected errors, since the shell occupation numbers of many metal atoms are irregular and must be treated separately anyway. You only need to watch out for copy-paste errors. Most (if not all) computational chemistry codes I know of, that implement this functionality, indeed hard-code the numbers, rather than relying on a generic formula and accounting for its exceptions separately.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-08-02T09:56:38.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6497" PostTypeId="1" CreationDate="2021-08-02T16:54:25.960" Score="12" ViewCount="1819" Body="&lt;p&gt;It is my first time trying to use an HPC system and I am a bit overwhelmed. I have gone through a course on using HPC systems on Coursera and have a basic idea about using Linux. Could you guys tell me what the general procedure is for running &lt;em&gt;ab initio&lt;/em&gt; packages such as Quantum ESPRESSO?&lt;/p&gt;&#xA;&lt;p&gt;For the information about my particular HPC system you can have a look &lt;a href=&quot;https://www.iuac.res.in/high-performance-computing-lab&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. It says that we use a system called SGE, but I don't know how this works.&lt;/p&gt;&#xA;&lt;p&gt;You can find the coursera course &lt;a href=&quot;https://www.coursera.org/learn/introduction-high-performance-computing/home/welcome&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2021-08-07T21:16:58.667" LastActivityDate="2021-08-07T21:16:58.667" Title="How can I submit jobs to an HPC scheduler?" Tags="|quantum-espresso|one-topic-per-answer|high-performance-computing|job-scheduler|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6498" PostTypeId="2" ParentId="6497" CreationDate="2021-08-02T18:32:07.427" Score="13" Body="&lt;h1&gt;SLURM&lt;/h1&gt;&#xA;&lt;p&gt;I'll provide you with a general script to run QE on your HPC. This is with the assumption that the HPC facility is using &lt;a href=&quot;https://slurm.schedmd.com/documentation.html&quot; rel=&quot;noreferrer&quot;&gt;SLURM&lt;/a&gt; as your workload manager and also with the assumption that you have the essential modules installed like openmpi (for parallel execution of the QE code) and intel compiler (in the example given below):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH --partition=cpu&#xA;#SBATCH --job-name=scf&#xA;#SBATCH --nodes=2 &#xA;#SBATCH --ntasks-per-node=1&#xA;#SBATCH --cpus-per-task=28&#xA;#SBATCH --time=5-00:00:00&#xA;&#xA;module load qe/6.5&#xA;module load intel&#xA;&#xA;mpirun -np 56 ~/path to bin folder of QE/pw.x -inp QE_input_file.in &amp;gt; QE_output_file.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here the  &lt;code&gt;--nodes=2&lt;/code&gt; indicates the number of nodes allocate to QE to parallelize over and the number &lt;code&gt;56&lt;/code&gt; after &lt;code&gt;-np&lt;/code&gt; is the number of processors the QE is allowed to parallelize over. In my case each node in the HPC facility i used has 28 cores and thats why I'm able to parallelize QE over 56 CPU cores. Usually there would be a restriction on the number of nodes a person can use, for me it was 8 (hence I could parallelize QE over 224 CPU cores at the most). The &lt;code&gt;module load &amp;lt;package&amp;gt;&lt;/code&gt; line loads in the required packages for your task at hand. The &lt;code&gt;~/path to bin folder of QE/pw.x&lt;/code&gt; indicates that if you have compiled QE by yourself on the HPC provided to you just add the path to the required QE routine there and your good to go!!.&lt;/p&gt;&#xA;&lt;p&gt;If QE is installed in the HPC (and if its added as an environment variable) you could just specify &lt;code&gt;pw.x&lt;/code&gt; (assuming that you are running a SCF calculation) in place of &lt;code&gt;~/path to bin folder of QE/pw.x&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;In order to run the job, copy the code into a shell script (say &lt;code&gt;submit.sh&lt;/code&gt;) and submit it using the command :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sbatch submit.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You could read more about SLURM in the documentation link I've attached above. I hope it helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastEditorUserId="1355" LastEditDate="2021-08-02T19:12:01.177" LastActivityDate="2021-08-02T19:12:01.177" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6499" PostTypeId="2" ParentId="6497" CreationDate="2021-08-02T19:05:38.593" Score="11" Body="&lt;h1&gt;LoadLeveler&lt;/h1&gt;&#xA;&lt;p&gt;I would recommend to save the following &lt;code&gt;shell script&lt;/code&gt; file with a name like &lt;code&gt;submission.sh&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#! /bin/ksh&#xA;# @ job_name   = Calculation_for_Parmeet &#xA;# @ job_type=MPICH&#xA;# @ error = job.err.$(jobid)&#xA;# @ node = 2&#xA;# @ tasks_per_node = 20&#xA;# @ wall_clock_limit = 23:58:00&#xA;# @ notification = complete&#xA;# @ notify_user = nike@hpqc.org&#xA;# @ queue&#xA;&#xA;module load qe/6.5&#xA;module load intel&#xA;&#xA;mpirun -np 40 ~/path_to_bin_folder_of_QE/pw.x -inp QE_input_file.in &amp;gt; QE_output_file.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now running &lt;code&gt;./submission.sh&lt;/code&gt; in the folder where &lt;code&gt;submission.sh&lt;/code&gt; was saved, will run a job:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;named &lt;code&gt;Calculation_for_Parmeet&lt;/code&gt;,&lt;/li&gt;&#xA;&lt;li&gt;with 2 nodes and 20 cores/node (40 cores in total),&lt;/li&gt;&#xA;&lt;li&gt;a time limit of just under 24 hours (since making it exactly 24 hours might send your job to a queue for longer jobs, which might make it take longer for your job to run, depending on the HPC system's configurations),&lt;/li&gt;&#xA;&lt;li&gt;with an email notification to &lt;code&gt;nike@hpqc.org&lt;/code&gt;,&lt;/li&gt;&#xA;&lt;li&gt;with error messages printed to &lt;code&gt;job.err.$(jobid)&lt;/code&gt; where &lt;code&gt;jobid&lt;/code&gt; is the ID number for the job, assigned by the scheduler,&lt;/li&gt;&#xA;&lt;li&gt;with an input file called &lt;code&gt;QE_input_file.in&lt;/code&gt; and output file &lt;code&gt;QE_output_file.out&lt;/code&gt;,&lt;/li&gt;&#xA;&lt;li&gt;with &lt;code&gt;qe/6.5&lt;/code&gt; installed as a module and compiled with the HPC system's &lt;code&gt;intel&lt;/code&gt; module, and the QE program &lt;code&gt;pw.x&lt;/code&gt; located in &lt;code&gt;~/path_to_bin_folder_of_QE/&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-02T19:05:38.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6500" PostTypeId="1" CreationDate="2021-08-02T22:44:12.080" Score="10" ViewCount="448" Body="&lt;p&gt;I tried to search online if there are examples or suggestions on how to set up a 4-point flexible water model, such as &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3663219&quot; rel=&quot;nofollow noreferrer&quot;&gt;TIP4P/2005f&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3167790&quot; rel=&quot;nofollow noreferrer&quot;&gt;qTIP4P/f&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/2012.04769&quot; rel=&quot;nofollow noreferrer&quot;&gt;TIP4P/&lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; FLEX&lt;/a&gt;, etc., but there's no clear example on how to set up intermolecular constraints, particularly for dummy atom distances and angles, with respect to the &lt;span class=&quot;math-container&quot;&gt;$\ce{O}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; atoms.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am looking for input examples for CP2K and GROMACS, but an input setup for any major classical MD software with an explanation would be really helpful.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2021-12-31T01:34:55.160" LastActivityDate="2021-12-31T01:34:55.160" Title="Setup for 4-point flexible water model" Tags="|molecular-dynamics|gromacs|cp2k|software-input-file-request|water|" AnswerCount="0" CommentCount="7" ClosedDate="2022-01-14T01:33:11.927" ContentLicense="CC BY-SA 4.0" />
  <row Id="6501" PostTypeId="1" CreationDate="2021-08-02T23:01:00.527" Score="7" ViewCount="66" Body="&lt;p&gt;My main aim is to extract the SWAXS spectra for the hydration shell surrounding a solvated molecule and I am unfamiliar with the idea of excluded solvent volume. I tried looking online but many articles did not elaborate on the process of setting up such a calculation, or directly used an online server for those results.&lt;/p&gt;&#xA;&lt;p&gt;In my case I have a single large solute molecule fixed and frozen at the center of the simulation box and I can calculate the SWAXS spectra of the entire simulation system using the xyz coordinates. Using this a stepping point, how can I go about calculating the SWAXS spectra for the hydration shell defined by distance cutoff criteria?&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2021-08-02T23:06:17.160" LastActivityDate="2021-08-06T12:19:59.067" Title="How to calculate small and wide-angle X-ray scattering spectra for the hydration shell restricted by a distance radius criteria" Tags="|molecular-dynamics|spectroscopy|x-ray-diffraction|water|solvation|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6502" PostTypeId="1" AcceptedAnswerId="6507" CreationDate="2021-08-03T00:39:44.350" Score="5" ViewCount="273" Body="&lt;p&gt;I was trying to define regions using a 'for' loop.&lt;/p&gt;&#xA;&lt;p&gt;Please find the regions:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;defregion(0, xrange(-1024e-9, -964e-9))&#xA;defregion(1, xrange(-964e-9, -844e-9))&#xA;defregion(2, xrange(-844e-9, -784e-9))&#xA;defregion(3, xrange(-784e-9, -664e-9))&#xA;defregion(4, xrange(-664e-9, -604e-9))&#xA;defregion(5, xrange(-604e-9, -484e-9))&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, the periodicity is &lt;code&gt;w1=60e-9&lt;/code&gt;, and &lt;code&gt;w2=120e-9&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So I was trying to define the regions using a loop like in the following way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    l=1024e-9&#xA;    w1=60e-9&#xA;    w2=120e-9&#xA;&#xA;    for i := 0; i &amp;lt;= 5; i+=2 {&#xA;        defregion(i, xrange(-l+i*w2, -l+(i+1)*w1));&#xA;        for j:=i+1; j&amp;lt;= 5; j+=1{&#xA;            defregion(j, xrange(-l+j*w1, -l+(j+1)*w2))&#xA;            }&#xA;    }&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this case, the software forms the geometry only with the &lt;code&gt;w1&lt;/code&gt; value. The &lt;code&gt;w2&lt;/code&gt; value is not taken.&#xA;However, the required geometry has not been formed.&lt;/p&gt;&#xA;&lt;p&gt;Could anyone please let me know where I am wrong and how to solve this problem?&lt;/p&gt;&#xA;&lt;p&gt;I have tried with the following solution (got it from the first answer!)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;l=1024e-9&#xA;w1=60e-9&#xA;w2=120e-9&#xA;&#xA;for i := 0; i &amp;lt;= 5; i+=2 {&#xA;    defregion(i, xrange(-l+i*w2, -l+(i+1)*w1));&#xA;    for j:=i+1; j&amp;lt;= 5; j+=1{&#xA;        defregion(j, xrange(-l+j*w1, -l+(j+1)*w2))&#xA;        }&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And, the error looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/M7jbM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/M7jbM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1505" LastEditorUserId="1505" LastEditDate="2021-08-04T15:35:32.040" LastActivityDate="2021-08-04T16:04:31.390" Title="Define a geometry region using 'for' loop in MuMax3" Tags="|geometry-optimization|algorithms|mumax3|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6503" PostTypeId="5" CreationDate="2021-08-03T01:34:51.953" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://mumax.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Main website&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-03T01:34:51.953" LastActivityDate="2021-08-03T01:34:51.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6504" PostTypeId="4" CreationDate="2021-08-03T01:34:51.953" Score="0" Body="Questions about or related to the mumax^3 software for GPU accelerated magnetism calculations." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-03T01:34:51.953" LastActivityDate="2021-08-03T01:34:51.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6505" PostTypeId="2" ParentId="4757" CreationDate="2021-08-03T11:53:48.780" Score="6" Body="&lt;p&gt;This is not a xyz file. If you have xyz file then you can use&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;numpy.genfromtxt() module to read from the data.&lt;/li&gt;&#xA;&lt;li&gt;create an numpy array having each component as an element of the array.&lt;/li&gt;&#xA;&lt;li&gt;Using eular's method to find the distance&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2021-08-03T11:53:48.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6506" PostTypeId="1" CreationDate="2021-08-03T11:49:27.510" Score="8" ViewCount="563" Body="&lt;p&gt;I have been trying to extract the transition density cube of a simple molecule, &lt;span class=&quot;math-container&quot;&gt;$\ce{H_2O}$&lt;/span&gt;. I did a regular geometry optimization and then TD-DFT calculation with a keyword &lt;code&gt;Density=Transition=1&lt;/code&gt;, which is supposed to write the transition density between the ground and the first excited state in the output, while using Gaussian software. However, if I try to generate the electron density cube in Gaussview from &lt;code&gt;.chk&lt;/code&gt; or &lt;code&gt;.fch&lt;/code&gt; file in Gaussian &lt;code&gt;Cubegen&lt;/code&gt;, the only option available is the SCF density, despite the fact that there is a section &amp;quot;&lt;code&gt;Total CI Rho(1) Density&lt;/code&gt;&amp;quot; in the output file. How is it possible to get transition density cube? Should I use additional software like MultiWfn or change my approach to transition density calculation?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for your help!&lt;/p&gt;&#xA;" OwnerUserId="4571" OwnerDisplayName="aerospace" LastEditorUserId="5" LastEditDate="2021-08-09T16:47:37.550" LastActivityDate="2021-08-14T15:43:05.777" Title="How to extract transition density cube from .fch file in Gaussian?" Tags="|density-functional-theory|quantum-chemistry|computational-chemistry|td-dft|multiwfn|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6507" PostTypeId="2" ParentId="6502" CreationDate="2021-08-03T13:52:55.250" Score="2" Body="&lt;p&gt;I have not used MuMax3 before, so I may be missing something, but I think you are overcomplicating things by trying to use a nested loop. It looks like you define a region in one loop and then redefine in another iteration, so its tough to reason out what values you will get.&lt;/p&gt;&#xA;&lt;p&gt;Running the equivalent of your loops in Python, I get&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 (-1.024e-06, -9.64e-07)&#xA;1 (-9.64e-07, -7.84e-07)&#xA;2 (-7.84e-07, -8.440000000000001e-07)&#xA;3 (-8.440000000000001e-07, -5.440000000000001e-07)&#xA;4 (-5.440000000000001e-07, -7.240000000000001e-07)&#xA;5 (-7.240000000000001e-07, -3.040000000000002e-07)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I believe you could instead use a single loop to get the result you want.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;l:=1024e-9&#xA;w1:=60e-9&#xA;w2:=120e-9&#xA;&#xA;start:=0&#xA;stop:=0&#xA;swap:=0&#xA;for i := 0; i &amp;lt;= 5; i+=1 {&#xA;    stop=stop+w1&#xA;    defregion(i, xrange(-l+start, -l+stop));&#xA;    swap=w1&#xA;    w1=w2&#xA;    w2=swap&#xA;    start=start+w2&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;start&lt;/code&gt; and &lt;code&gt;stop&lt;/code&gt; store how much you should add to the initial value to get the next interval. At each iteration, &lt;code&gt;w1&lt;/code&gt; and &lt;code&gt;w2&lt;/code&gt; are swapped so that the beginning and end of each region increase by the correct amount, which alternates.&lt;/p&gt;&#xA;&lt;p&gt;Initially, my answer used &lt;code&gt;=&lt;/code&gt; everywhere rather than &lt;code&gt;:=&lt;/code&gt;. It seems, based on the examples I could find on the MuMax3 page, that &lt;code&gt;=&lt;/code&gt; is used to set options for the program or redefine existing variables while &lt;code&gt;:=&lt;/code&gt; is used for user created variable assignment.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-08-04T16:04:31.390" LastActivityDate="2021-08-04T16:04:31.390" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6509" PostTypeId="2" ParentId="6497" CreationDate="2021-08-03T20:55:47.080" Score="6" Body="&lt;h2&gt;SGE&lt;/h2&gt;&#xA;&lt;p&gt;&lt;em&gt;Disclaimer&lt;/em&gt;: I haven't ever used SGE before, so there may be some inaccuracies that other users can correct. However, it seems similar to other systems and the &lt;a href=&quot;https://www.iuac.res.in/themes/iuac/images/pdf/k2-instructions-2.pdf&quot; rel=&quot;noreferrer&quot;&gt;instructions&lt;/a&gt; from your university page seem sufficient.&lt;/p&gt;&#xA;&lt;p&gt;The example input is very similar to those already given:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#&lt;span class=&quot;math-container&quot;&gt;$ -S /bin/bash   #specifies shell&#xA;#$&lt;/span&gt; -cwd          #where to find input/place output&#xA;#&lt;span class=&quot;math-container&quot;&gt;$ -N JobName &#xA;#$&lt;/span&gt; -pe mpich 32   #-pe=Parallel environment, 32 is number of CPU &#xA;#&lt;span class=&quot;math-container&quot;&gt;$ -e $&lt;/span&gt;JOB_ID.err  #Error file, named with variable &lt;span class=&quot;math-container&quot;&gt;$JOB_ID&#xA;#$&lt;/span&gt; -o &lt;span class=&quot;math-container&quot;&gt;$JOB_ID.out  #Output file, should contain prints to console&#xA;#$&lt;/span&gt; -q all.q     #submission queue&#xA;#$ -V      #Says to load your environment variables for the job&#xA;&#xA;module load qe/6.5&#xA;module load intel&#xA;&#xA;mpirun -np 40 ~/path_to_bin_folder_of_QE/pw.x -inp QE_input_file.in &amp;gt; QE_output_file.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are a couple things you will need to look out for with your university's system.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For the number of CPUs, your administrators say all nodes have 16, so you should mainly specify jobs in increments of 16.&lt;/li&gt;&#xA;&lt;li&gt;They seem to have several queue: all.q, largejob.q, and test.q. These have different uses, permissions, and restrictions associated with them. As the name suggests, you should probably test your job with test.q first to see if it at least starts. Then you can run it with all.q, which will give access to more time/CPUs.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can then submit using &lt;code&gt;qsub ScriptName&lt;/code&gt; where &lt;code&gt;ScriptName&lt;/code&gt; can be whatever you want (I tend to just use &lt;code&gt;job&lt;/code&gt;) if its something I can use generally that isn't terribly specific to one type of job.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-08-03T20:55:47.080" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6510" PostTypeId="2" ParentId="6439" CreationDate="2021-08-04T03:17:59.073" Score="4" Body="&lt;p&gt;Here are some possible changes to your input that may resolve the problem:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Your &lt;code&gt;EDIFF&lt;/code&gt; is very small; use the default and then increase precision from there.&lt;/li&gt;&#xA;&lt;li&gt;Use a smaller &lt;code&gt;SIGMA&lt;/code&gt;, start with 0.15 or 0.1.&lt;/li&gt;&#xA;&lt;li&gt;Decrease the number of k-points, start with 5x5x5, then increase to reach the desired precision.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;" OwnerUserId="4089" LastEditorUserId="5" LastEditDate="2021-08-04T14:24:13.923" LastActivityDate="2021-08-04T14:24:13.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6511" PostTypeId="1" CreationDate="2021-08-04T09:44:08.900" Score="4" ViewCount="209" Body="&lt;p&gt;Could someone explain, is it possible to make Hubbard Hamiltonian manifestly SU(2) invariant? I know about the interaction term, but how would kinetic (hopping effect) term have to look like?&lt;/p&gt;&#xA;&lt;p&gt;Here I'm talking about the simplified Fermi-Hubbard Hamiltonian that only has those two terms (hopping effect term which includes the nearest cites and interaction term, where the interaction exists only between the electrons on the same lattice cite).&lt;/p&gt;&#xA;&lt;p&gt;How could creation and annihilation Fermi operator look like when expressed in terms of spin operators?&lt;/p&gt;&#xA;&lt;p&gt;I'm looking forward to hearing from someone here.&lt;/p&gt;&#xA;" OwnerUserId="4092" LastEditorUserId="5" LastEditDate="2021-08-09T16:24:32.237" LastActivityDate="2021-08-09T16:28:06.877" Title="Hubbard model SU(2) symmetry: manifest invariance" Tags="|condensed-matter|mathematical-modeling|model-hamiltonians|symmetry|hubbard-model|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6512" PostTypeId="1" AcceptedAnswerId="8448" CreationDate="2021-08-04T09:46:27.373" Score="6" ViewCount="387" Body="&lt;p&gt;The Dzyaloshinskii-Moriya interaction (DMI) existing in the interface of the ferromagnetic insulator and the metal with strong spin-orbit coupling (SOC) &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.89.025006&quot; rel=&quot;nofollow noreferrer&quot;&gt;is shown below&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cqPsy.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cqPsy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Mathematically, it can be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\vec{D}_{12}\cdot(\vec{S}_1\times\vec{S}_2)\tag{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.71.165310&quot; rel=&quot;nofollow noreferrer&quot;&gt;In this paper&lt;/a&gt;, the Rashba SOC has been second quantized. So my question is how can we second quantize the DMI-type SOC?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-12-31T21:10:59.857" LastActivityDate="2021-12-31T21:10:59.857" Title="How to formulate the second quantization of Dzyaloshinskii-Moriya interaction?" Tags="|condensed-matter|quantum-mechanics|model-hamiltonians|spin-orbit-coupling|derivations|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6513" PostTypeId="2" ParentId="6486" CreationDate="2021-08-04T10:31:48.253" Score="9" Body="&lt;p&gt;The main idea here is to preserve the periodic boundary conditions when creating a fractional supercell. Therefore, not all combinations are possible, such as &lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}\times\sqrt{2}$&lt;/span&gt; or&lt;span class=&quot;math-container&quot;&gt;$\sqrt{5}\times\sqrt{5}$&lt;/span&gt; for the case of MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Basically, you need to define a rotation matrix for creating such supercells.&#xA;e.g.,&#xA;B=RA (in matrix form), where A is the original lattice vectors (in matrix form), R is the rotation matrix and B is the result.&lt;/p&gt;&#xA;&lt;p&gt;For example, one can define a rotation matrix R to create &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}\times\sqrt{3}R30^{0}$&lt;/span&gt; supercell as following:&lt;span class=&quot;math-container&quot;&gt;\begin{bmatrix}2 &amp;amp; 1 &amp;amp; 0\\-1 &amp;amp; 1&amp;amp; 0 \\0 &amp;amp; 0&amp;amp; 1\end{bmatrix}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I showed here three pictures for comparison of a fractional supercell of Sqrt3xSqrt3R30 to normal cells, see how the supercell looks like and how you define matrix.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ff4EU.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ff4EU.png&quot; alt=&quot;sqrt3 supercell diagrams&quot; /&gt;&lt;/a&gt;&#xA;So, to make a cell of size Sqrt3xSqrt3R30, you traverse 2 time x and then 1 time y, making [2 1 0] the first line of matrix, similarly, 1 times in -x and 1 time y makes [-1 1 0] the second line of matrix. You can't have any combination giving Sqrt2xSqrt2 with periodic boundary conditions.&#xA;Hope it will be clear now.&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="7" LastEditDate="2021-09-06T14:41:59.717" LastActivityDate="2021-09-06T14:41:59.717" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6514" PostTypeId="1" CreationDate="2021-08-04T19:54:25.893" Score="2" ViewCount="53" Body="&lt;p&gt;Hope you're doing well. Actually I am working on a project related to DNA regulated Nanozyme and I have a nanozyme of mesoporous silica &amp;quot;Iron Manganese Silicate nanoparticle (IMSN) nanozyme&amp;quot;. I have to do MD simulation of this inorganic particle with LAMMPS but for that I need its structure in PDB format for input files. I only know its chemical formula &lt;span class=&quot;math-container&quot;&gt;$\ce{FeMn(SiO4)}$&lt;/span&gt; as I am new to inorganic nanoparticles simulations so I have to make this molecule in Avogadro. But I don't know how to generate this molecule like how this  nanoparticle attaches in structure.&#xA;Can anyone help me to build this molecule? or can anyone please guide me about its structure? Is this Silica act as a ligand or a core shell here?&#xA;Your Answers are really appreciated.&#xA;Thanks&lt;/p&gt;&#xA;" OwnerUserId="4100" LastEditorUserId="5" LastEditDate="2021-08-25T02:58:31.823" LastActivityDate="2021-08-25T02:58:31.823" Title="Chemical Structure of Iron Manganese Silicate Nanoparticle (IMSN) Nanozyme?" Tags="|molecular-dynamics|lammps|proteins|biomaterials|avogadro|" AnswerCount="0" CommentCount="2" ClosedDate="2021-11-29T19:00:49.000" ContentLicense="CC BY-SA 4.0" />
  <row Id="6515" PostTypeId="1" CreationDate="2021-08-05T08:27:23.277" Score="4" ViewCount="111" Body="&lt;p&gt;Is it possible to somehow calculate the inner product (or overlap) between the electronic wave-functions of excited states in Molpro? What I want to do is to compare the electronic wave-functions that I get from two different (although only slightly different) nuclear geometries, by calculating all inner products between pairs of excited states. In other words, what I'm looking for is a command that takes two different records—each storing &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; wave-functions—and calculates the &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; inner products. I'm using CASSCF and MRCI, but please share if there are any such functions in other programs too.&lt;/p&gt;&#xA;" OwnerUserId="3536" LastActivityDate="2021-08-05T08:27:23.277" Title="Calculating wave-function overlap in MOLPRO" Tags="|molpro|casscf|mrci|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6516" PostTypeId="1" CreationDate="2021-08-05T10:45:53.353" Score="7" ViewCount="259" Body="&lt;p&gt;A CIF file of Monoclinic &lt;span class=&quot;math-container&quot;&gt;$\ce{MoO2}$&lt;/span&gt; is not available in the  &lt;a href=&quot;http://www.crystallography.net/cod/&quot; rel=&quot;noreferrer&quot;&gt;Crystallography Open Database&lt;/a&gt; website. How can I make it myself or find it elsewhere?&lt;/p&gt;&#xA;" OwnerUserId="4106" LastEditorUserId="7" LastEditDate="2021-08-05T14:35:07.483" LastActivityDate="2021-08-05T23:40:18.500" Title="How can I make a CIF file for Monoclinic MoO2?" Tags="|crystallography|cif|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6517" PostTypeId="1" CreationDate="2021-08-05T11:21:11.533" Score="6" ViewCount="51" Body="&lt;p&gt;I was reading a paper online that can be found &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/5.0039465&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the paper they claim that BEB (binary encounter bethe) AE and ECP (all-electrons and effective core potential) will typically underestimate the ionisation cross section when compared with experimental data. They justify this as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It should be noted that a disadvantage of using an ECP is that all&#xA;the inner shell orbitals are removed. These orbitals may contribute&#xA;little to the BEB cross section at low energies; however, the high&#xA;energy tail of an ECP calculated BEB cross section can be expected to&#xA;be underestimated as a result of the missing core ionization.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However I have done some calculations for SF6 and some other flourinated hydrocarbons and in these handful of examples we see that actually the theoretical BEB model overestimates the ionisation cross section when compared with experimentel data.&lt;/p&gt;&#xA;&lt;p&gt;My question is whether anybody can think of a reason/explanation as to why the BEB model will overestimate the ionisation cross sections for &lt;span class=&quot;math-container&quot;&gt;$SF_6$&lt;/span&gt; and some florinated carbons.&lt;/p&gt;&#xA;&lt;p&gt;If anyone has any ideas I would really appreciate it because currently it is confusing me.&lt;/p&gt;&#xA;&lt;p&gt;I have attached the following data from NIST to illustrate my point of how BEB overestimates the ionisation cross section for &lt;span class=&quot;math-container&quot;&gt;$SF_6$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/b1Pag.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/b1Pag.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-12-31T01:29:52.907" LastActivityDate="2021-12-31T01:29:52.907" Title="Binary Encounter Bethe model: Why does it overestimate ionisation cross-sections SF6, even though generally it underestimates them for other species" Tags="|scattering|" AnswerCount="0" CommentCount="2" ClosedDate="2022-01-14T01:34:42.603" ContentLicense="CC BY-SA 4.0" />
  <row Id="6518" PostTypeId="2" ParentId="6516" CreationDate="2021-08-05T14:47:31.307" Score="5" Body="&lt;p&gt;I was able to find a CIF for this compound through the &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt;. You can download the CIF, along with viewing other properties of this structure, here: &lt;a href=&quot;https://materialsproject.org/materials/mp-559140/&quot; rel=&quot;noreferrer&quot;&gt;Monoclinic MoO2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In general, the Materials Project is a good place to look for CIFs, along with any of the databases listed by the &lt;a href=&quot;https://www.iucr.org/resources/data/databases&quot; rel=&quot;noreferrer&quot;&gt;IUCR&lt;/a&gt; (International Union of Crystallography).&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-08-05T14:47:31.307" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6519" PostTypeId="2" ParentId="6516" CreationDate="2021-08-05T14:52:04.873" Score="3" Body="&lt;p&gt;You can download structures freely from the database of &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For example, the monoclinic MoO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; can be found from this link:&#xA;&lt;a href=&quot;https://materialsproject.org/materials/mp-559140/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialsproject.org/materials/mp-559140/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-08-05T23:40:18.500" LastActivityDate="2021-08-05T23:40:18.500" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6520" PostTypeId="1" CreationDate="2021-08-05T23:36:49.297" Score="5" ViewCount="125" Body="&lt;p&gt;Currently, I am trying to figure out the &lt;a href=&quot;https://github.com/lucydot/effmass&quot; rel=&quot;nofollow noreferrer&quot;&gt;effmass&lt;/a&gt; module. I'm newly into effective mass stuff and I'm able to run it and generate effective masses. However, I'm facing some trouble understanding it. Is there anyone in this community who could help me?&lt;/p&gt;&#xA;&lt;p&gt;For example, I want to find the effective mass of &lt;span class=&quot;math-container&quot;&gt;$\ce{WS2}$&lt;/span&gt; bulk system at VBM and CBM but this module generates so-called segments and I could not figure the logic behind that. What are these segments and what do these numbers in the square bracket mean?&lt;/p&gt;&#xA;&lt;p&gt;In the following plot, it shows generated effmass plot for the &lt;span class=&quot;math-container&quot;&gt;$\ce{WS2}$&lt;/span&gt; bulk system. &lt;a href=&quot;https://i.stack.imgur.com/DnEfA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DnEfA.png&quot; alt=&quot;Effective mass plot for WS2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, effective mass values for segments 0 and 1 are:&lt;/p&gt;&#xA;&lt;p&gt;0: &lt;span class=&quot;math-container&quot;&gt;$-0.49$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;1: &lt;span class=&quot;math-container&quot;&gt;$-0.37$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which one is the K point effective mass? It really confuses me.&lt;/p&gt;&#xA;" OwnerUserId="984" LastEditorUserId="7" LastEditDate="2021-08-07T00:21:06.977" LastActivityDate="2021-08-07T00:26:34.487" Title="Interpretation of effmass module" Tags="|density-functional-theory|band-structure|effective-mass|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6521" PostTypeId="2" ParentId="6520" CreationDate="2021-08-06T00:14:09.723" Score="2" Body="&lt;p&gt;I will give a quick answer, someone more experienced in this field may be able to elaborate better.  You have two different effective masses because you have a different effective mass in the K-&amp;gt;M and K-&amp;gt;G directions in the valence band.  I suspect the numbers in brackets represent the direction.  M likely corresponds to &lt;code&gt;[1 -2 0]&lt;/code&gt; for example.&lt;/p&gt;&#xA;&lt;p&gt;You may find the tool &lt;a href=&quot;https://smtg-ucl.github.io/sumo/sumo-bandstats.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;sumo-bandstats&lt;/a&gt; to give you easier access to this information directly, I have never used effmass so I cannot advise if a similar tool exists within it.  I have taken an example output from that page and included here so you can see how the output compares to what you see.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Direct band gap: 0.712 eV&#xA;  k-point: [0.00, 0.00, 0.00]&#xA;  k-point indexes: 0, 113&#xA;  Band indexes: 34, 37&#xA;&#xA;Valence band maximum:&#xA;  Energy: 1.444 eV&#xA;  k-point: [0.00, 0.00, 0.00]&#xA;  k-point location: \Gamma&#xA;  k-point indexes: 0, 113&#xA;  Band indexes: 34, 35, 36&#xA;&#xA;Conduction band minimum:&#xA;  Energy: 2.155 eV&#xA;  k-point: [0.00, 0.00, 0.00]&#xA;  k-point location: \Gamma&#xA;  k-point indexes: 0, 113&#xA;  Band indexes: 37&#xA;&#xA;Using parabolic fitting of the band edges&#xA;&#xA;Hole effective masses:&#xA;  m_h: -0.641 | band 34 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.50, 0.50] (L)&#xA;  m_h: -0.516 | band 34 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.00, 0.50] (X)&#xA;  m_h: -0.641 | band 35 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.50, 0.50] (L)&#xA;  m_h: -0.516 | band 35 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.00, 0.50] (X)&#xA;  m_h: -1.234 | band 36 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.50, 0.50] (L)&#xA;  m_h: -15.158 | band 36 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.00, 0.50] (X)&#xA;&#xA;Electron effective masses:&#xA;  m_e: 0.207 | band 37 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.50, 0.50] (L)&#xA;  m_e: 0.211 | band 37 | [0.00, 0.00, 0.00] (\Gamma) -&amp;gt; [0.50, 0.00, 0.50] (X)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-08-06T00:14:09.723" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6522" PostTypeId="1" CreationDate="2021-08-06T01:22:17.587" Score="5" ViewCount="2166" Body="&lt;p&gt;On the &lt;a href=&quot;http://www.crystallography.net/cod/&quot; rel=&quot;nofollow noreferrer&quot;&gt;COD&lt;/a&gt; website, only 2-layer hexagonal (2H) and 3-layer orthorhombic (3R) &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; are available. I can't find the 1-layer tetragonal (1T) and 1H CIF for &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt;. Where can I find them, or how can I make them myself?&lt;/p&gt;&#xA;" OwnerUserId="4106" LastEditorUserId="7" LastEditDate="2021-08-06T15:36:19.787" LastActivityDate="2021-08-06T15:36:19.787" Title="1T and 1H CIF file for MoS2" Tags="|crystallography|cif|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6523" PostTypeId="1" CreationDate="2021-08-06T02:54:18.117" Score="5" ViewCount="44" Body="&lt;p&gt;I have been redirected to this forum from &lt;a href=&quot;https://chemistry.stackexchange.com/questions/155607/how-do-i-model-drug-diffusion-from-polymeric-matrix&quot;&gt;Chemistry SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My problem consists of a structure (say a cylinder) made from a homogenous distribution of a drug from a polymeric matrix. These compounds are mixed homogeneously in different concentrations (10% drug and 90% polymer, or, 20% drug and 80% polymer) and extruded to form the structure. This structure is immersed in a media.&lt;/p&gt;&#xA;&lt;p&gt;As the structure interacts with the media, the drug and the polymer degrades into the media and the media is able to diffuse into the structure and the drug in the interior breaks down. This continues till the entire structure is degraded (however, I am interested in only till all drug has been released).&lt;/p&gt;&#xA;&lt;p&gt;I want to find out how the structure will physically and chemically degrade. I also want to find out what the rate of drug dissolution in the media will look like, and how the structure would look in 3D over time.&lt;/p&gt;&#xA;&lt;p&gt;Is there any computational tool that can model this problem and provide a solution.&lt;/p&gt;&#xA;&lt;p&gt;Any help will be appreciated!!&lt;/p&gt;&#xA;" OwnerUserId="4110" LastEditorUserId="7" LastEditDate="2021-08-09T18:36:11.840" LastActivityDate="2021-08-09T18:36:11.840" Title="How do I model drug diffusion from polymeric matrix?" Tags="|molecular-dynamics|from-chem-se|polymers|biomaterials|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-10T22:19:52.790" ContentLicense="CC BY-SA 4.0" />
  <row Id="6524" PostTypeId="1" AcceptedAnswerId="6545" CreationDate="2021-08-06T06:37:21.010" Score="8" ViewCount="202" Body="&lt;p&gt;This question is related to nonlinear Hall effect proposed in &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.216806&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. The Boltzmann equation in the electric field under relaxation time approximation is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$-e E_a \partial_a f+\partial_t f=\dfrac{f_0-f}{\tau} \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$\partial_a=\dfrac{\partial}{\partial_{k_a}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_0$&lt;/span&gt; is the equilibrium distribution in the absence of external fields. Note that we have adopted the Einstein convention for vector analysis. To solve Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; we take the following two assumpations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The electric field is given as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_a(t)=Re\{\mathcal{E}_ae^{i\omega t}\} \qquad \mathcal{E}_a \in C \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The distribution is expanded up to second order:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$f=Re\{f_0+f_1+f_2\} \tag{3}$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$f_n\propto |\mathcal{E}|^n \tag{4} $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Under these conditions, the authors obtain the following analytic solutions:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$f_1=f_1^\omega e^{i\omega t} \quad f_1^\omega=\dfrac{e\tau\mathcal{E}_a\partial_a f_0}{1+i\omega\tau} \tag{5}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$f_2=f_2^0+f_2^{2\omega}e^{2i\omega t} \quad f_2^0=\dfrac{(e\tau)^2\mathcal{E}_a^* \mathcal{E}_b\partial_{ab}f_0}{2(1+i\omega \tau)} \quad f_2^{2\omega}=\dfrac{(e\tau)^2\mathcal{E}_a\mathcal{E}_b\partial_{ab}f_0}{2(1+i\omega\tau)(1+2i\omega\tau)} \tag{6} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is how to obtain Eqs. &lt;span class=&quot;math-container&quot;&gt;$(5)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(6)$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-08-10T04:45:34.427" LastActivityDate="2021-08-10T04:45:34.427" Title="Analytic solution of Boltzmann equation" Tags="|mathematical-modeling|derivations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6525" PostTypeId="2" ParentId="6522" CreationDate="2021-08-06T06:56:53.520" Score="3" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;1H MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; without inversion symmetry (I assume you want to MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; monolayer) can be built from 2H bulk MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;. The following is a raw model (saved as MoS2.vasp and open with VESTA software).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MoS2&#xA; 1.00000000000000&#xA; 3.1828219313310346    0.0002029835391965    0.0000002023172743&#xA;-1.5914442249239205    2.7566628171638539    0.0000005369011847&#xA; 0.0000012654406512    0.0000046797187921   20.2699679926205256&#xA;   Mo   S&#xA;   1     2&#xA; Direct&#xA;0.6666693217032124  0.3333217596688635  0.1678141091468308&#xA;0.3333188567802812  0.6666460846006057  0.0906781102229205&#xA;0.3333188035165100  0.6666461137305300  0.2449511886302513&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;1T MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; with inversion symmetry can be downloaded from Materials Project: &lt;a href=&quot;https://materialsproject.org/materials/mp-1238797/#&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialsproject.org/materials/mp-1238797/#&lt;/a&gt;. If you want to monolayer, just add vacuum along &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; direction.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-08-06T06:56:53.520" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6526" PostTypeId="1" AcceptedAnswerId="6527" CreationDate="2021-08-06T07:14:53.107" Score="5" ViewCount="743" Body="&lt;p&gt;I am adding a new collective variable (CV) that I will use to calculate a path density with OpenPathSampling. I played around a bit with the CVs and I have one error that I'm not sure how to fix. I'm hoping you can help me with it.&#xA;I am trying to select the atoms directly with residue number and atom name from the topology to calculate the CV.&#xA;To do this, I have a function to calculate the CV and then I've written a function to wrap this in the CollectiveVariable object.&#xA;The &lt;code&gt;topology.select&lt;/code&gt; seems to be the issue and that means I'm not calling the data properly. How do I make this selection?&lt;/p&gt;&#xA;&lt;p&gt;The function to calculate the CV:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def rolling_angle(traj, backbone, rollingbase):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Parameters&#xA;    ----------&#xA;    traj : mdtraj.Trajectory&#xA;        trajectory to analyze&#xA;    rolling_atoms : RollingAtoms&#xA;        info on which atoms to use; returned from get_baserolling_atoms&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    def normalize(vector):&#xA;        norms = np.linalg.norm(vector, axis=1)&#xA;        return vector / norms.reshape(len(norms), 1)&#xA;    def arccos_based_angle(v1, v2):&#xA;        return np.arccos(np.clip(np.dot(v1, v2), -1, 1))&#xA;    def atan2_based_angle(v1, v2):&#xA;        return np.arctan2(np.cross(v1, v2), np.dot(v1, v2))&#xA;&#xA;    # get the vector associated with the rolling base&#xA;    bp_v21 = traj.xyz[:,rollingbase[0]] - traj.xyz[:,rollingbase[1]]&#xA;    bp_v23 = traj.xyz[:,rollingbase[2]] - traj.xyz[:,rollingbase[1]]&#xA;    bp_vector = normalize(np.cross(bp_v21, bp_v23))&#xA;&#xA;    # get the vector associated with the backbone&#xA;    bb_vector = traj.xyz[:,backbone[1]] - traj.xyz[:,backbone[0]]&#xA;    bb_vector = normalize(bb_vector)&#xA;    # calculate angle&#xA;    return np.degrees([&#xA;        atan2_based_angle(bb, bp)&#xA;        for (bb, bp) in zip(bb_vector, bp_vector)&#xA;    ])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The function to wrap in object:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def rolling_base(snapshot):&#xA;    topology = snapshot.topology&#xA;    backbone = topology.select(&amp;quot;resid 5 10 and name P&amp;quot;)&#xA;    rollingbase = topology.select(&amp;quot;resid 3 and name N7 N3 N1&amp;quot;)&#xA;    return rolling_angle(traj, backbone, rollingbase)&#xA;&#xA;new_cv = paths.CoordinateFunctionCV('rolling_base',rolling_base)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Plotting the CV:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;path_density = paths.PathDensityHistogram(cvs=[d_WC, new_cv],&#xA;                                          left_bin_edges=(0.2,0.2),&#xA;                                          bin_widths=(0.01,0.01))&#xA;path_dens_counter = path_density.histogram(trajs[:5])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4111" LastEditorUserId="2004" LastEditDate="2021-08-06T15:19:03.923" LastActivityDate="2021-08-06T15:19:03.923" Title="How do I select atoms using mdtraj_topology when creating a CV?" Tags="|python|openpathsampling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6527" PostTypeId="2" ParentId="6526" CreationDate="2021-08-06T12:23:00.543" Score="4" Body="&lt;p&gt;For the error you're seeing right now, the problem is that your function requires an &lt;code&gt;mdtraj.Trajectory&lt;/code&gt; as input, but you're wrapping it with a &lt;code&gt;paths.CoordinateFunctionCV&lt;/code&gt;, which provides the wrapped function with OpenPathSampling trajectory. Wrapping with a &lt;code&gt;paths.MDTrajFunctionCV&lt;/code&gt; should fix that error: it converts to MDTraj.&lt;/p&gt;&#xA;&lt;p&gt;However, there's also a more straightforward way to achieve the same result, &lt;em&gt;without&lt;/em&gt; creating the extra function.&lt;/p&gt;&#xA;&lt;h2&gt;The current error&lt;/h2&gt;&#xA;&lt;p&gt;It looks like the function &lt;code&gt;rolling_base&lt;/code&gt; is designed to take an MDTraj trajectory as input, not an OPS snapshot. MDTraj provides the &lt;code&gt;select&lt;/code&gt; functionality; OPS does not. In that case, you should wrap it with &lt;code&gt;MDTrajCVFunction&lt;/code&gt; instead of &lt;code&gt;CoordinateCVFunction&lt;/code&gt; when you create &lt;code&gt;new_cv&lt;/code&gt;. This automatically handles the process of translating between OPS and MDTraj, so the input your function sees is an MDTraj trajectory. Note that &lt;code&gt;MDTrajFunctionCV&lt;/code&gt; also requires a topology object as input (where the topology is the OPS-wrapped version of the MDTraj topology, which you may have already created for your engine.)&lt;/p&gt;&#xA;&lt;h2&gt;Another (probably easier) approach&lt;/h2&gt;&#xA;&lt;p&gt;You've added an extra function, &lt;code&gt;rolling_base&lt;/code&gt;, that exists to &amp;quot;freeze&amp;quot; some of the parameters to the &lt;code&gt;rolling_angle&lt;/code&gt; function. This isn't necessary -- CVs in OPS can do this for you. You just need to pass the extra arguments as keywords (i.e., with an explicit &lt;code&gt;=&lt;/code&gt;) when you make the CV.&lt;/p&gt;&#xA;&lt;p&gt;Wrapping with an &lt;code&gt;MDTrajFunctionCV&lt;/code&gt; (and assuming an OPS-wrapped MDTraj topology in &lt;code&gt;topology&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;topology = ...  # OPS wrapper for an MDTraj topology; probably have this in engine&#xA;mdtraj_topology = topology.mdtraj&#xA;new_cv = paths.MDTrajFunctionCV(&#xA;   'rolling_base'&#xA;   rolling_angle,&#xA;   topology=topology,&#xA;   backbone=mdtraj_topology.select(&amp;quot;resid 5 10 and name P&amp;quot;),&#xA;   rollingbase=mdtraj_topology.select(&amp;quot;resid 3 and name N7 N3 N1&amp;quot;)&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will &amp;quot;freeze&amp;quot; the parameters &lt;code&gt;backbone&lt;/code&gt; and &lt;code&gt;rollingbase&lt;/code&gt; when the function &lt;code&gt;rolling_angle&lt;/code&gt; is called. You can find some simplified examples of this in the &lt;a href=&quot;http://openpathsampling.org/latest/topics/creating_collective_variables.html#generalizing-your-cv-function&quot; rel=&quot;nofollow noreferrer&quot;&gt;OPS documentation on creating CVs&lt;/a&gt;. The idea is similar to &lt;a href=&quot;https://docs.python.org/3/library/functools.html#functools.partial&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;functools.partial&lt;/code&gt;&lt;/a&gt; from the Python standard library (discussed with examples &lt;a href=&quot;https://siddharth1.medium.com/partial-functions-in-python-functools-partial-with-applications-and-examples-b65114ba82fb&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). Note that, unlike &lt;code&gt;functools.partial&lt;/code&gt;, with OPS CVs, you must always specify the keyword name (i.e., you need to include &lt;code&gt;backbone=&lt;/code&gt; and &lt;code&gt;rollingbase=&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;h2&gt;Checking that your new CV works&lt;/h2&gt;&#xA;&lt;p&gt;After you've made your new CV, it's best to check that it works on some simple example data. It looks like &lt;code&gt;trajs&lt;/code&gt; is a list of OPS trajectories; what I would do is (assuming (1) you're in a Jupyter notebook; (2) have imported matplotlib as &lt;code&gt;plt&lt;/code&gt;, and (3) &lt;code&gt;trajs&lt;/code&gt; is a list of trajectories):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;plt.plot(new_cv(trajs[0]))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;That should give you &lt;code&gt;new_cv&lt;/code&gt; on the y axis, frame number on the x axis, for trajectory 0. Is it reasonable? If not:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Double-check the &amp;quot;frozen&amp;quot; variables in your CV. In this case, check that your selections have the number of atoms you expect, and that your have the right topology. It looks like the function expects 2 integers for &lt;code&gt;backbone&lt;/code&gt; (atom indices to create a vector) and 3 integers for &lt;code&gt;rollingbase&lt;/code&gt; (atom indices to create a vector normal to the plane defined by the atoms). Is that what your selections return? You can get the &lt;code&gt;topology&lt;/code&gt; for a snapshot from &lt;code&gt;snapshot.engine.topology&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Double-check that the function itself gives reasonable result. This looks like a function that has already been tested against an MDTraj CV, but you can create an MDTraj trajectory from an OPS trajectory with &lt;code&gt;trajectory.to_mdtraj()&lt;/code&gt;. Then directly check whether you get reasonable results from the &lt;code&gt;rolling_angle&lt;/code&gt; function.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-08-06T12:23:00.543" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6528" PostTypeId="1" AcceptedAnswerId="6529" CreationDate="2021-08-06T17:16:43.360" Score="4" ViewCount="291" Body="&lt;p&gt;I'm &lt;strong&gt;looking to build a surface slab in Atomic Simulation Environment&lt;/strong&gt; (ASE) for CeO2 (fluorite structure). Using ase.build.surface( ) allowed modelling the surface. I would now like to run a relaxation on the slab w/ the bottom layer frozen, but &lt;strong&gt;all atom tags are '0'&lt;/strong&gt; (according to get_tags() method): &lt;strong&gt;does ase.build.surface() not assign layer tags?&lt;/strong&gt; or have a made a formatting error causing the slab to be tagged as an adsorbate?&#xA;&lt;strong&gt;Thanks!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase import Atoms,Atom&#xA;from ase.build import surface&#xA;&#xA;a = 5.467&#xA;bulk_ceo2 = Atoms([&#xA;             Atom('Ce', (0.000000,  0.000000,  0.000000)),&#xA;             Atom('Ce', (0.000000,  0.500000,  0.500000)),&#xA;             Atom('Ce', (0.500000,  0.000000,  0.500000)),&#xA;             Atom('Ce', (0.500000,  0.500000,  0.000000)),&#xA;             Atom('O',  (0.750000,  0.250000,  0.250000)),&#xA;             Atom('O',  (0.250000,  0.750000,  0.750000)),&#xA;             Atom('O',  (0.750000,  0.750000,  0.750000)),&#xA;             Atom('O',  (0.250000,  0.250000,  0.250000)),&#xA;             Atom('O',  (0.250000,  0.250000,  0.750000)),&#xA;             Atom('O',  (0.750000,  0.750000,  0.250000)),&#xA;             Atom('O',  (0.250000,  0.750000,  0.250000)),&#xA;             Atom('O',  (0.750000,  0.250000,  0.750000))&#xA;                                                          ])&#xA;&#xA;cell = [(a, 0.0, 0.0),&#xA;        (0.0, a, 0.0),&#xA;        (0.0, 0.0, a)]&#xA;&#xA;bulk_ceo2.set_cell(cell, scale_atoms=True)&#xA;&#xA;#(1,1,1) slab; 4 unit cells along Z direction&#xA;slab = surface(bulk_ceo2, (1,1,1), 4)&#xA;&#xA;#Repeat slab 2 unit cells in X and 1 in Y directions&#xA;slab = slab.repeat((2,1,1))&#xA;slab.center(vacuum=8, axis=2)&#xA;&#xA;slab_tags = slab.get_tags()&#xA;&#xA;print(slab_tags)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="910" LastActivityDate="2021-08-06T19:30:55.040" Title="Are all the atom tags equal to 0 for ase.build.surface() objects?" Tags="|surfaces|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6529" PostTypeId="2" ParentId="6528" CreationDate="2021-08-06T19:30:55.040" Score="3" Body="&lt;p&gt;ASE is not aware of which layer things are on when you use the surface function to build an arbitrary surface.  However, the indices should be in order of z height I believe.&lt;/p&gt;&#xA;&lt;p&gt;You can use the following to assign the tags, just be aware that this will not work for more complex surfaces very well (which is why it is not done by default I believe).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;slab = surface(bulk_ceo2, (1,1,1), 4)&#xA;slab.set_tags(range(len(slab)))&#xA;slab *= (2,2,1)&#xA;slab.center(vacuum=8, axis=2)&#xA;&#xA;slab_tags = slab.get_tags()&#xA;print(slab_tags)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-08-06T19:30:55.040" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6530" PostTypeId="2" ParentId="6520" CreationDate="2021-08-06T19:58:51.057" Score="2" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;nofollow noreferrer&quot;&gt;effective mass&lt;/a&gt; (&lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;) is one of the properties used in Solid State Physics, and specially in Semiconductor Physics. It is defined from the energy dispersion relationship as follow:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(\frac{1}{m^*})_{ij}=\frac{1}{\hbar^2}\frac{\partial^2E_n(\vec{k})}{\partial k_i \partial k_j},\;\;i,j=x,y,z$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In case of parabolic bands, it can be calculated under the approximation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E(\vec{k}) = E_0 + \frac{\hbar^2\vec{k}^2}{2m^*}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, in order to calculate it, you need to specify all the &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt;. As the k-path depends on the crystal symmetry, you can also &amp;quot;map&amp;quot; the k points with the crystal directions.&lt;/p&gt;&#xA;&lt;p&gt;How &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt; is calculated, depend on how the program implements the first formula. In a full implementation, you will get one value for each pair &lt;span class=&quot;math-container&quot;&gt;$(k_i,k_j)$&lt;/span&gt;. From your question, looks like the software you are using do a linearization around the maxima/minimum, instead going through all the real k points.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="7" LastEditDate="2021-08-07T00:26:34.487" LastActivityDate="2021-08-07T00:26:34.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6532" PostTypeId="1" CreationDate="2021-08-07T02:28:36.697" Score="16" ViewCount="924" Body="&lt;p&gt;This question is about tools like Open Babel. Are there any good command-line parsers for quantum chemistry program outputs? A good Python library could come in as a close second.&lt;/p&gt;&#xA;&lt;p&gt;I am interested e.g. in support for the Psi4 output format.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2021-08-07T03:53:11.650" LastActivityDate="2021-08-14T05:44:15.160" Title="What's the best quantum chemistry output parser for the command line?" Tags="|one-topic-per-answer|quantum-chemistry|software-recommendations|geometry-optimization|openbabel|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6533" PostTypeId="2" ParentId="6532" CreationDate="2021-08-07T12:18:01.830" Score="11" Body="&lt;h2&gt;CCLIB&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://cclib.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cclib&lt;/a&gt; is an &lt;a href=&quot;https://github.com/cclib/cclib&quot; rel=&quot;nofollow noreferrer&quot;&gt;open source&lt;/a&gt; python library that can parse and interpret output files of common computational chemistry programs. As of now, it supports Psi4 version 1.0 and 1.2.1.&lt;/p&gt;&#xA;&lt;p&gt;It can be called from both command line and from python shell (or a python script).&lt;/p&gt;&#xA;&lt;p&gt;From command line, you can use the &lt;code&gt;ccget&lt;/code&gt; utility to parse the log file, and get a certain attribute.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C:\Users\Public&amp;gt; ccget atomcharges acetate.log&#xA;Attempting to read acetate.log&#xA;atomcharges&#xA;{'lowdin': array([-0.681752,  0.120888,  0.226508,  0.23122 ,  0.232586, -0.561103, -0.568346]),&#xA; 'mulliken': array([-0.912454,  0.268637,  0.250721,  0.25877 ,  0.257854, -0.568736, -0.554792])}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this example, I used a GAMESS log file for a single point calculation on acetate, but the output format is the same regardless of the program used.&lt;/p&gt;&#xA;&lt;p&gt;There are also three other utilites—&lt;code&gt;ccwrite&lt;/code&gt;(which writes parsed data into json, cjson, cml and xyz formats), &lt;code&gt;cda&lt;/code&gt; (which does chemical decomposition analysis), &lt;code&gt;ccframe&lt;/code&gt; (which gives additional data writing capabilities, but requires the pandas library).&lt;/p&gt;&#xA;&lt;p&gt;You can also call it from python:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; import cclib&#xA;&amp;gt;&amp;gt;&amp;gt; data = cclib.io.ccread(&amp;quot;acetate.log&amp;quot;)&#xA;&amp;gt;&amp;gt;&amp;gt; print(&amp;quot;Number of molecular orbitals: &amp;quot;, data.nmo)&#xA;Number of molecular orbitals: 82&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Further guide on data parsing can be found &lt;a href=&quot;https://cclib.github.io/how_to_parse.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, and &lt;a href=&quot;https://cclib.github.io/data.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. Apart from Psi4, it can also read the outputs of GAMESS, Gaussian, Orca, NWChem, Turbomole, Molcas, ADF, Q-chem, Turbomole, Molpro etc.&lt;/p&gt;&#xA;&lt;p&gt;The program works on Linux, Windows and Mac OS. It can be installed without Python as well (in which case only the command line utilities work).&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-08-14T05:44:15.160" LastActivityDate="2021-08-14T05:44:15.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6534" PostTypeId="2" ParentId="6447" CreationDate="2021-08-07T15:33:46.750" Score="9" Body="&lt;p&gt;I hope this basic example helps you to see the difference. I'll denote configurations by simple tuples where each number indicates the occupation of a spatial orbital, with increasing energy from left to right.&lt;/p&gt;&#xA;&lt;p&gt;Let's take only the ground state determinant as reference and do CIS within a space of 4 spatial orbitals (yielding 8 spin orbitals in total)  and two electrons. The additional configurations that we obtain when we look at all single excitations are the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(2 0 0 0) -&amp;gt; (1 1 0 0) | (1 0 1 0) | (1 0 0 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now let's add a second configuration and do CIS on this new configuration. I'll omit configurations that have already been generated in the former step.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(0 1 1 0) -&amp;gt; (0 2 0 0) | (0 0 2 0) | (0 0 1 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You see that you get new determinants based on single excitations starting from this reference. This set of configurations differs from the set that you would have obtained by doing all single and double excitations based on the groundstate configuration. If we had done CISD we would have gotten one more determinant,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(0 0 0 2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this basic example the difference is small but as the active space and the number of electrons grows, the number of possible configurations &amp;quot;explodes&amp;quot; in size.&lt;/p&gt;&#xA;&lt;p&gt;The same transfers to multireference CISD. By adding a reference and doing single and double excitations you will get additional configurations that aren't generated based on a single reference. It is also different from simply doing the next higher excitation scheme, as you can see in my CIS example.&lt;/p&gt;&#xA;&lt;p&gt;You can also include determinants that correspond to higher excitations by starting from a doubly excited determinant and doing single excitations on top of it, if we had more electrons and a larger active space.&lt;/p&gt;&#xA;&lt;p&gt;The multireference ansatz allows us thus to include some higher excited configurations without including the whole set of all higher excited determinants, which is often unfeasible due to the large number of possible combinations that are available given a larger active space. It also allows us to add higher excited configurations without the cost of doing the full higher excited scheme.&lt;/p&gt;&#xA;&lt;p&gt;The diagonalization of the CI matrix based on the generated configurations yields&#xA;your electronic states and eigenvalues. The electronic states are mathematically linear combinations of the determinants although many states often have a dominant contribution. This allows us to approximately identify a state with the determinant,  that has the highest coefficient in the linear combination.&lt;/p&gt;&#xA;" OwnerUserId="2289" LastEditorUserId="5" LastEditDate="2021-08-09T15:11:37.960" LastActivityDate="2021-08-09T15:11:37.960" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6535" PostTypeId="1" AcceptedAnswerId="6539" CreationDate="2021-08-07T18:58:54.277" Score="6" ViewCount="84" Body="&lt;p&gt;If I know trivial (anti)commutation relation for some operators (let's say Fermi operators), I can only use it if they are in the same moment of time. If I have their time dependence and they don't have to be observed in the same moment of time, then those (anti)commutation relations are not that trivial and so I can't use them that way.&lt;/p&gt;&#xA;&lt;p&gt;But what about imaginary time dependence (via the exponential factor)? For example, let's consider Fermi operators in Heisenberg picture, or Dirac (interaction) picture. Do they have some trivial (anti)commutation relations that can be used or not?&lt;/p&gt;&#xA;" OwnerUserId="4092" LastEditorUserId="5" LastEditDate="2021-08-09T16:09:43.563" LastActivityDate="2021-08-09T16:09:43.563" Title="Imaginary time dependent operators: (anti)commutation relations" Tags="|condensed-matter|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6536" PostTypeId="2" ParentId="6511" CreationDate="2021-08-08T11:52:09.467" Score="3" Body="&lt;p&gt;The Hubbard Model is already manifestly SU(2) spin-rotation invariant because there are no terms that connect the &lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt; sectors (here by &lt;em&gt;connect,&lt;/em&gt; I mean change a &lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt; to a &lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt; or &lt;em&gt;vice versa&lt;/em&gt;. The full Hamiltonian in terms of fermion annihilation/creation operators is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H = - t \sum \limits_{t,\sigma} \left( c^\dagger_{i,\sigma} c_{i+1,\sigma} + c^\dagger_{i+1,\sigma} c_{i,\sigma} \right) + U\sum_i n_{i,\uparrow} n_{i,\downarrow}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that the hopping term &lt;em&gt;only&lt;/em&gt; acts on either the &lt;span class=&quot;math-container&quot;&gt;$\uparrow$&lt;/span&gt; &lt;strong&gt;or&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$\downarrow$&lt;/span&gt; sectors, it never changes the **number$$ of $\uparrow$ or $\downarrow$ electrons. The potential ($U$) term &lt;em&gt;does&lt;/em&gt; allow interaction between $\uparrow$ and $\downarrow$ electrons, but it is &lt;em&gt;diagonal,&lt;/em&gt; so it never changes the total spin of the system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;In terms of spin ladder operators:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The most common way of thinking about the Hubbard model in terms of spin ladder operators is to consider the case of large &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; at half filling. Half filling means there are &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; sites, and large-&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; means that the energy cost of double-occupying a site is high.&lt;/p&gt;&#xA;&lt;p&gt;From this setup, we can do time-independent degenerate perturbation theory, treating the &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; term as &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; and the hopping as a perturbation. Let's consider ju From this standpoint, we have a set of degenerate ground states with one electron on each site. The energy of this ground state is zero (&lt;span class=&quot;math-container&quot;&gt;$E_0 =0$&lt;/span&gt;) and all possible combinations of up and down spins are degenerate.&lt;/p&gt;&#xA;&lt;p&gt;As a rough example, let's consider an isolated pair of Hubbard sites with hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; and hopping perturbation &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;H_0 &amp;amp;= &amp;amp; U ( n_{+,1} n_{-,1} +  n_{+,2} n_{-,2} ) \tag{2}\\&#xA;V &amp;amp;= &amp;amp; -t ( c^\dagger_{\pm,1} c_{\pm,2} + c^\dagger_{\pm,2} c_{\pm,1} )\tag{3}&#xA;\end{eqnarray}&lt;/span&gt;&#xA;The eigenstates of &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; in the subspace of half filling are&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;H_0 | 1 \rangle = &amp;amp; H_0 | \pm, \pm \rangle  = 0 \tag{4}\\&#xA;H_0 |2 \rangle = &amp;amp; H_0  |\pm, \mp \rangle  = 0 \tag{5}\\&#xA;H_0 |3 \rangle = &amp;amp; H_0 |0,2\rangle = U \tag{6}\\&#xA;H_0 |4 \rangle = &amp;amp; H_0 |2,0\rangle= U\tag{7}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This hamiltonian has two degenerate ground states: &lt;span class=&quot;math-container&quot;&gt;$|1\rangle,|2\rangle$&lt;/span&gt; with eigenvalues of 0. Here, first order degenerate perturbation theory fails because there the matrix elements &lt;span class=&quot;math-container&quot;&gt;$\langle 1|V|2 \rangle = 0$&lt;/span&gt;, so we must advance to second-order perturbation theory:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E^{(2)}_i = \sum \limits_{i \ne j} \frac{ \langle i | H_0 | j \rangle \langle j | H_0 | i \rangle }{E^{(0)}_i - E^{(0)}_j}\tag{8}&#xA;$$&lt;/span&gt;&#xA;In second order, a pair of antiparallel spins can make a virtual transition to a double occupied state and back. This effectively lowers the energy of antiparallel neighbors, while parallel neighbors don't benefit from this virtual transition (also called super exchange). For example, consider state 2:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E^{(2)}_2 &amp;amp;=  \frac{ \langle \pm \mp | H_0 |  0 2 \rangle \langle 0 2 | H_0 | \pm \mp \rangle }{0 - U}  +  \frac{ \langle \pm \mp | H_0 |  2 0 \rangle \langle 2 0 | H_0 | \pm \mp \rangle }{0 - U} \tag{9}\\ \nonumber&#xA;E^{(2)}_2 &amp;amp;= -\frac{t_0^2  }{U} -  \frac{ t_0^2 }{ U}  \tag{10}\\&#xA;&amp;amp;= - \frac{ 2 t_0^2}{U} \tag{11}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This means that &lt;span class=&quot;math-container&quot;&gt;$H |2 \rangle = -\frac{2t_0^2}{U} | 2\rangle $&lt;/span&gt; therefore &lt;span class=&quot;math-container&quot;&gt;$J = \frac{2t_0^2}{U}$&lt;/span&gt;. This is not a rigorous derivation, but it gets the basic idea across.&lt;/p&gt;&#xA;&lt;p&gt;The equivalent spin-ladder operator Hamiltonian to the large-U half-filling Hubbard model is there for just the Heisenberg model with &lt;span class=&quot;math-container&quot;&gt;$J = 2\frac{t^2}{U}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2021-08-09T16:28:06.877" LastActivityDate="2021-08-09T16:28:06.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6537" PostTypeId="1" CreationDate="2021-08-08T14:26:09.363" Score="4" ViewCount="200" Body="&lt;p&gt;I see from the phonopy web page &lt;a href=&quot;https://phonopy.github.io/phonopy/interfaces.html#frequency-default-value-interfaces&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt; that the physical unit systems used for the calculators are different for different codes &lt;a href=&quot;https://phonopy.github.io/phonopy/interfaces.html#frequency-default-value-interfaces&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;.  On the same page, it is mentioned that &amp;quot;For these sets of physical properties, phonon frequency is calculated in THz.&amp;quot; Does it mean that the final unit for frequency and group velocity in &lt;code&gt;band.yaml&lt;/code&gt; and &lt;code&gt;gruneisen.yaml&lt;/code&gt; for VASP and QE codes are the same?&lt;/p&gt;&#xA;&lt;p&gt;I was told by Prof. Togo, the developer of phonopy, that the unit of frequency is considered the same in VASP and QE, but that of group velocity is not.&lt;/p&gt;&#xA;&lt;p&gt;Could someone please help me: how can I convert the unit of velocity in the QE &lt;code&gt;band.yaml&lt;/code&gt; file to the units of the VASP &lt;code&gt;band.yaml&lt;/code&gt; format (THz/Angstrom).&lt;/p&gt;&#xA;&lt;p&gt;The unit in the VASP &lt;code&gt;band.yaml&lt;/code&gt; file is THz/Angstrom while in the &lt;code&gt;band.yaml&lt;/code&gt; file of QE it may be in THz/Bohr (not sure). To make the QE format of &lt;code&gt;band.yaml&lt;/code&gt; into &lt;code&gt;VASP band.ymal&lt;/code&gt;, can we do the conversion like below?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1bohr = 0.529177249 Angstrom&#xA;1/bohr = 1/0.529177249 = 1.88972598857&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I need to multiply the velocity in &lt;code&gt;band.yaml&lt;/code&gt; of QE by 1.88972598857?&lt;/p&gt;&#xA;&lt;p&gt;My half-finished conversation on the phonopy mailing list can be found here &lt;a href=&quot;https://sourceforge.net/p/phonopy/mailman/phonopy-users/thread/CAJYci%2BT_NRa0uDqzh-NVyKPq%2BAhy2OdU5oenwARacMspR1SZFA%40mail.gmail.com/#msg37332350&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;An example of the VASP &lt;code&gt;band.yaml&lt;/code&gt; and QE &lt;code&gt;band.yaml&lt;/code&gt; can be found here &lt;a href=&quot;https://we.tl/t-aIfkaoJIO3&quot; rel=&quot;nofollow noreferrer&quot;&gt;3&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1713" LastEditorUserId="5" LastEditDate="2021-08-09T16:14:35.263" LastActivityDate="2021-08-09T16:14:35.263" Title="How to correct units in the band.yaml file of QE, to band.yaml of VASP" Tags="|vasp|quantum-espresso|phonopy|" AnswerCount="0" CommentCount="7" ClosedDate="2021-12-31T18:09:50.267" ContentLicense="CC BY-SA 4.0" />
  <row Id="6538" PostTypeId="1" AcceptedAnswerId="6542" CreationDate="2021-08-08T14:56:55.407" Score="10" ViewCount="774" Body="&lt;p&gt;During the same minute as asking this question, I also asked &lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/20782/2293&quot;&gt;this&lt;/a&gt; at Quantum Computing SE.&lt;/p&gt;&#xA;&lt;p&gt;In Qiskit, each qubit corresponds to one spin orbital. For example, the &lt;span class=&quot;math-container&quot;&gt;$\ce{N2}$&lt;/span&gt; molecule would have 10 molecular orbitals, which correspond to 20 spin orbitals for alpha and beta spins for the &lt;code&gt;sto-3g&lt;/code&gt; basis set. In my opinion, this is the case because the for each atom contained in the molecule, we need to account for the orbitals included, which are &lt;code&gt;1s&lt;/code&gt;, &lt;code&gt;2s&lt;/code&gt;, &lt;code&gt;2p&lt;/code&gt; for the nitrogen atom. However, in this case, how could one deal with the molecular orbitals when in the situation like choosing the active space for the molecule?&lt;/p&gt;&#xA;" OwnerUserId="2043" LastEditorUserId="5" LastEditDate="2021-08-21T21:21:09.587" LastActivityDate="2022-07-13T11:54:54.097" Title="Molecular orbitals and active space" Tags="|quantum-chemistry|basis-sets|orbitals|casscf|quantum-computing|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6539" PostTypeId="2" ParentId="6535" CreationDate="2021-08-08T23:45:49.860" Score="4" Body="&lt;p&gt;I assume that you are talking about something related to many-body Green's function method. Usually, we learn the (anti)commutation from basic quantum mechanics, which are formulated in the Schrodinger picture, and hence the operator is time independence. However, when you want to perform many-body perturbation expansion, you need Dirac and Heisenberg pictures, in which all the operators are time-dependent. Now, what are the corresponding commutation relations between creation and annihilation operators? This is what you want to know? Simply, it will be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\{c_{k_1}(t_1),c^\dagger_{k_2}(t_2)\}=\delta_{k_1k_2}\delta(t_1-t_2)\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\{c_{k_1}(\tau_1),c^\dagger_{k_2}(\tau_2)\}=\delta_{k_1k_2}\delta(\tau_1-\tau_2)\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The imaginary time technique doesn't change the commutation relation and is just used to unify the relation between the time-evolution operator and the Boltzmann factor. You can find more from the famous book: Quantum Statistical Mechanics (Leo P. Kadanoff and Gordon Baym).&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-08-09T16:09:18.490" LastActivityDate="2021-08-09T16:09:18.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6540" PostTypeId="1" AcceptedAnswerId="6550" CreationDate="2021-08-09T04:21:08.947" Score="10" ViewCount="600" Body="&lt;p&gt;I would like to know what is the difference between a &lt;strong&gt;Half metal (HM)&lt;/strong&gt; and a &lt;strong&gt;Spin Gapless Semiconductor (SGS)&lt;/strong&gt; in terms of &lt;em&gt;definition&lt;/em&gt; and &lt;em&gt;DOS/Bandstructure appearance&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="1218" LastEditDate="2021-08-12T08:54:00.657" LastActivityDate="2021-08-12T08:54:00.657" Title="What is the difference between a half metal (HM) and a spin gapless semiconductor (SGS)?" Tags="|band-structure|density-of-states|spintronics|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6541" PostTypeId="2" ParentId="6532" CreationDate="2021-08-09T11:31:54.290" Score="7" Body="&lt;h2&gt;IOData&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/theochem/iodata&quot; rel=&quot;nofollow noreferrer&quot;&gt;iodata&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Python based i/o module meant to go with &lt;a href=&quot;https://github.com/theochem/horton&quot; rel=&quot;nofollow noreferrer&quot;&gt;HORTON&lt;/a&gt;, but also operates entirely on its own.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://iodata.readthedocs.io/en/latest/getting_started.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Docs&lt;/a&gt; go over many of the things it can do, but it can read in, and output many file types. It also can create input files for you i.e., give it &lt;code&gt;xyz&lt;/code&gt; or &lt;code&gt;pdb&lt;/code&gt; or other and get a Gaussian input file. It is easy to customize the input file as well&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from iodata import load_one&#xA;&#xA;mol = load_one('water.xyz')  # XYZ files contain atomic coordinates in Angstrom&#xA;print(mol.atcoords)  # print coordinates in Bohr.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Currently when I use &lt;code&gt;psi4&lt;/code&gt;, I get it to output a &lt;code&gt;fchk&lt;/code&gt; file and then just read in the &lt;code&gt;fchk&lt;/code&gt; with &lt;code&gt;iodata&lt;/code&gt;. There are other options though, that is just the one I have used.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from iodata import load_one&#xA;&#xA;mol = load_one('water.fchk')  &#xA;print(mol.atcoords)  # print coordinates in Bohr.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-08-11T12:01:58.123" LastActivityDate="2021-08-11T12:01:58.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6542" PostTypeId="2" ParentId="6538" CreationDate="2021-08-09T14:23:19.120" Score="10" Body="&lt;p&gt;As you said above, nitrogen has 2 s orbitals and one p orbital. However, one would typically freeze the chemically inactive 1s orbital, leaving you 5 electrons in 4 orbitals per atom, or 10 electrons in 8 orbitals for N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;; this is denoted &lt;span class=&quot;math-container&quot;&gt;$(10e,8o)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Going beyond the minimal STO-3G basis, in addition to the occupied molecular orbitals (which are poorly described by STO-3G), you will have a large number of unoccupied molecular orbitals that are necessary to describe electron correlation.&lt;/p&gt;&#xA;&lt;p&gt;Choosing the active space for complete-active space (CAS) self-consistent field (SCF) calculations is traditionally quite difficult, see e.g. &lt;a href=&quot;https://doi.org/10.1002/qua.23068&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 111, 3329 (2011)&lt;/a&gt;. The traditional CAS-SCF approach is equivalent to exact diagonalization of the real two-electron Hamiltonian in the space of electron configurations, i.e. the full configuration interaction (FCI) method. Since the challenge of the FCI solution scales exponentially, in practice the problem size is limited in practice to &lt;span class=&quot;math-container&quot;&gt;$\lesssim(20e,20o)$&lt;/span&gt;. Because of this limitation, it is not possible to include all valence orbitals in the CASSCF calculation already for diatomic molecules; however, the results one gets with various choices for the active orbitals may differ.&lt;/p&gt;&#xA;&lt;p&gt;There are a number of alternative approaches to the FCI problem, such as the density matrix renormalization group (DMRG) method or various selected CI methods, which are able to push back the scaling wall and which have been found to be immensely useful for chemical applications. As a rule of thumb, these methods can handle strongly correlated electrons in three dimensions up to problem sizes of roughly (50e,50o). Future large-scale quantum computers are hailed as a panacea for chemistry, because they might be able to push back the problem size limit further to hundreds of electrons in hundreds of orbitals, at which point full valence orbital active spaces become feasible.&lt;/p&gt;&#xA;&lt;p&gt;Because of the importance of the choice of the active orbitals in traditional CAS-SCF calculations, a multitude of ways in which to choose the active orbitals has been suggested. For general 3D molecular systems, a variety of strategies can be chosen. Using the canonical orbitals is not advised, because the unoccupied orbitals are not good estimates of excited states. Instead, common ways to pick the natural orbitals include employing natural orbitals from a lower level of theory; for instance, unrestricted Hartree-Fock natural orbitals (UNO) have been found to yield good orbitals for CAS calculations; MP2 and CISD are other commonly-used alternatives. Another established alternative are the so-called improved virtual orbitals, which are a way to improve the choice for the unoccupied orbitals to include in the active space. It is also possible to define the active space directly in terms of a reference set of gas-phase atomic orbitals, see &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.7b00128&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 2017, 13, 9, 4063–4078&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In diatomic molecules like N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, the choice can be done simply by symmetry: as the Hamiltonian does not depend on the angle measured around the bond, the orbitals are periodic with respect to this angle, &lt;span class=&quot;math-container&quot;&gt;$\exp(i m \phi)$&lt;/span&gt;  (see e.g. &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int J. Quantum Chem. 119, e25968 (2019)&lt;/a&gt;), and the orbitals can be classified into &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$m=0$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$m=\pm 1$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$m=\pm 2$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$\varphi$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$m=\pm 3$&lt;/span&gt;), etc orbitals. In N&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, the two s orbitals both yield a &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; orbital and the two p orbitals yield 2 &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; and 2 &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; orbitals, yielding an active space of 2 &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; and 4 &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; orbitals (a  &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; orbital fits 2 electrons, while the &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; and higher orbitals each fit 4 electrons).&lt;/p&gt;&#xA;&lt;p&gt;However, the choice of the initial orbitals should matter less and less when the size of the active space is increased. If all the valence orbitals fit into the active space, the orbital optimization in CASSCF should converge quite rapidly even when begun from the canonical orbitals.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2022-07-13T11:54:54.097" LastActivityDate="2022-07-13T11:54:54.097" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6543" PostTypeId="1" CreationDate="2021-08-09T18:51:21.247" Score="10" ViewCount="504" Body="&lt;p&gt;I found in an article [1] the following definition of FNV (Freysoldt, Neugebauer and Van de Walle) energy correction term for a charged defect in a cubic supercell:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{\text{corr}}=\frac{\alpha_Mq^2}{2\epsilon L}-q\Delta V^{\text{DFT/pc}}_{q/0}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then it says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt; is the macroscopic dielectric constant of the medium. For systems which do not undergo significant relaxation, the use of the high-frequency dielectric constant &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_\infty$&lt;/span&gt; is appropriate to describe the screening. Otherwise, one needs to use the static dielectric constant &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the physical difference between &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_\infty$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_0$&lt;/span&gt;?&lt;/strong&gt; Is &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_\infty$&lt;/span&gt; the real part of the dielectric constant at infinite wavelength from an optical calculation to get &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Re}(\varepsilon)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{Im}(\varepsilon)$&lt;/span&gt;? Would &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_0$&lt;/span&gt; be what can be accessed experimentally forming a capacitor?&lt;/p&gt;&#xA;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Wei Chen and Alfredo Pasquarello 2015 J. Phys.: Condens. Matter 27 133202 DOI: 10.1088/0953-8984/27/13/133202&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4118" LastEditorUserId="5" LastEditDate="2021-08-21T18:09:37.120" LastActivityDate="2021-08-21T18:09:37.120" Title="Difference of high-frequency and static dielectric constants?" Tags="|ab-initio-calculations|supercell|defects|formation-energy|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-02T20:29:11.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="6544" PostTypeId="1" AcceptedAnswerId="6548" CreationDate="2021-08-10T03:39:49.510" Score="7" ViewCount="439" Body="&lt;p&gt;The potential terms of the Hamiltonian in the Kohn-Sham equation are the external, Hartree, and exchange-correlation terms, which can be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{ext}(r) = - \sum_{i=1}^{M} \frac{Z_i} {||r - R_i||} \\&#xA;V_{H}(r) = \int \frac {\rho(r')} {||r - r'||} dr' \\&#xA;V_{xc}(r) = \int f(\rho(r)) dr$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The external potential is always negative because it contains the atomic number but has minus sign; the Hartree is always positive because the density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is always positive.&lt;/p&gt;&#xA;&lt;p&gt;Here, &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; can be written using a function &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; by various approximation approaches (e.g., LDA), but is this &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; term always positive? Or can this &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; be negative depending on the type of approximation?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-08-10T03:49:48.047" LastActivityDate="2021-08-11T06:15:13.330" Title="Is the exchange-correlation term in Kohn-Sham equation always positive or negative?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6545" PostTypeId="2" ParentId="6524" CreationDate="2021-08-10T04:29:46.137" Score="6" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally, I figure out this question on my own. Put Eq.&lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(3)$&lt;/span&gt; into Eq.&lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;-e \Re\{\mathcal{E}_a e^{i\omega t}\} (\partial_a f_0+\partial_a f_1)+(\partial_tf_1+\partial_tf_2)=\dfrac{-f_1-f_2}{\tau} \tag{7}&#xA;\end{equation}&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\Re\{\mathcal{E}_a e^{i\omega t}\}f_2\propto |\mathcal{E}|^3$&lt;/span&gt; is droped and &lt;span class=&quot;math-container&quot;&gt;$\partial_t f_0=0$&lt;/span&gt;. Furthermore, we can investigate Eq&lt;span class=&quot;math-container&quot;&gt;$(7)$&lt;/span&gt; by the order of &lt;span class=&quot;math-container&quot;&gt;$|\mathcal{E}|$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$|\mathcal{E}|^1$&lt;/span&gt; term:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;-e \mathcal{E}_a e^{i\omega t} \partial_a f_0+\partial_t f_1=-\dfrac{f_1}{\tau} \tag{8}&#xA;\end{equation}&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\partial_t f_0$&lt;/span&gt; is real.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$|\mathcal{E}|^2$&lt;/span&gt; term:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;-e \Re\{ \mathcal{E}_a e^{i\omega t} \}\partial_af_1+\partial_t f_2=-\dfrac{f_2}{\tau} \tag{9}&#xA;\end{equation}&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\Re\{ \mathcal{E}_a e^{i\omega t} \}$&lt;/span&gt; is real.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Eqs.&lt;span class=&quot;math-container&quot;&gt;$(8)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(9)$&lt;/span&gt; are linear inhomogenious  differential equation of order one, which can be solved easily.&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\dfrac{dx(t)}{dt}+p(t)x(t)=q(t) \Rightarrow x(t)=e^{-\int p(t) dt}[c+\int q(t) e^{\int p(t) dt}dt]\tag{10}&#xA;\end{equation}&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2021-08-10T04:42:06.337" LastActivityDate="2021-08-10T04:42:06.337" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6546" PostTypeId="1" CreationDate="2021-08-10T12:57:40.310" Score="5" ViewCount="90" Body="&lt;p&gt;I would like to obtain the Cartesian gradient from a Gaussian formatted checkpoint file with more digits than 8 (specified in scientific notation). Is there any way to do this?&lt;/p&gt;&#xA;" OwnerUserId="4119" OwnerDisplayName="TobiR" LastEditorUserId="5" LastEditDate="2021-08-10T17:41:13.900" LastActivityDate="2021-08-10T17:41:13.900" Title="How to extract Cartesian gradient with more digits than 8 using Gaussian?" Tags="|software|gaussian|" AnswerCount="0" CommentCount="9" ClosedDate="2021-10-29T17:20:21.617" ContentLicense="CC BY-SA 4.0" />
  <row Id="6547" PostTypeId="1" CreationDate="2021-08-10T21:43:32.923" Score="6" ViewCount="262" Body="&lt;p&gt;I would like to form the (numerical) gradient and the Hessian of the total electronic energy with respect only to a few internal coordinates (namely, the six intermolecular coordinates of a weakly bound dimer). In those cases I saw, when second derivatives were calculated, Gaussian always determined the full Hessian. &lt;strong&gt;Do you know an option capable of controlling the set of active variables used to calculate the gradient and the Hessian of reduced size?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4119" LastEditorUserId="5" LastEditDate="2021-08-10T23:56:54.903" LastActivityDate="2021-08-10T23:56:54.903" Title="How to calculate energy gradient and Hessian with respect to only a few internal coordinates using Gaussian?" Tags="|quantum-chemistry|ab-initio-calculations|electronic-structure|gaussian|geometry-optimization|" AnswerCount="0" CommentCount="10" ClosedDate="2022-01-07T09:37:23.933" ContentLicense="CC BY-SA 4.0" />
  <row Id="6548" PostTypeId="2" ParentId="6544" CreationDate="2021-08-11T06:15:13.330" Score="6" Body="&lt;p&gt;I think this is true at least for the exchange energy &lt;span class=&quot;math-container&quot;&gt;$$&#xA;E = \int \epsilon_{x}({\bf r}) {\rm d}^3r&#xA;$$&lt;/span&gt;&#xA;which is usually written in terms of an enhancement function &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; times the local density approximation's exchange energy (which is always negative)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA; \epsilon_{x}({\bf r}) = - C n^{4/3}({\bf r}) F(\gamma, \tau) {\rm d}^3r&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; is the reduced gradient and &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the local kinetic energy density. If the enhancement function is nonnegative, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_x$&lt;/span&gt; will also be nonnegative.&lt;/p&gt;&#xA;&lt;p&gt;The correlation energy is a correction to the mean field, and it is much smaller than the exchange energy, thus on this argument alone it should be always negative. However, I would expect the correlation energy to also be always negative, because that is basically the definition of correlation energy: it's the energy gain you get by switching from Hartree-Fock to a many-electron description like MP2, CCSD or FCI.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-08-11T06:15:13.330" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6549" PostTypeId="1" CreationDate="2021-08-12T08:18:12.797" Score="6" ViewCount="64" Body="&lt;p&gt;I am interested in how the orbital space of a system can be partitioned into clusters.&lt;/p&gt;&#xA;&lt;p&gt;I read reading 'Cluster many-body expansion: A many-body expansion of the electron correlation energy about a cluster mean field reference': &lt;a href=&quot;https://doi.org/10.1063/5.0057752&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 155, 054101 (2021)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A couple of examples used in the paper are the &lt;span class=&quot;math-container&quot;&gt;$\ce{C_{2}}$&lt;/span&gt; dimer and different polyacene Kekulé structures. Given a list of natural orbitals, how can one form sensible clusters?&lt;/p&gt;&#xA;&lt;p&gt;For instance: consider a molecule with 5 occupied orbitals and 6 virtual orbitals:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol.orbital_list = [0,1,2,3,4,5,6,7,8,9,10]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Would one partition the orbital space into different frozen clusters:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol.cluster_1 = [0,2,4,6,8,10]&#xA;mol.cluster_2 = [1,3,5,7,9]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If so, how are the orbital clusters determined?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2021-08-21T17:50:42.417" LastActivityDate="2021-08-21T17:50:42.417" Title="Orbital space clustering" Tags="|quantum-chemistry|ab-initio-calculations|electronic-structure|orbitals|" AnswerCount="0" CommentCount="2" ClosedDate="2021-11-29T19:28:13.990" ContentLicense="CC BY-SA 4.0" />
  <row Id="6550" PostTypeId="2" ParentId="6540" CreationDate="2021-08-12T08:53:13.020" Score="7" Body="&lt;p&gt;The concept of spin gapless semiconductors (SGS) was proposed in this paper: &lt;a href=&quot;https://journals.aps.org/prl/pdf/10.1103/PhysRevLett.100.156404&quot; rel=&quot;noreferrer&quot;&gt;PRL 100, 156404 (2008)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In quantum solid-state band theory, materials in nature are generally classified as insulators, semiconductors, metals, semimetals, and half-metals based on the electronic band structures (density of states or band structure), as shown below.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fwCbo.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fwCbo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;(a): Metal&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(b): Semiconductor or Insulator by the gap value&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(c): Semimetal (The valence band and conduction band are touching slightly.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;(d): Half-metal&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Energy band diagrams for spin gapless semiconductors with linear dispersion between energy and momentum.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EKYNy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EKYNy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Energy band diagrams for spin gapless semiconductors with parabolic dispersion between energy and momentum.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/95mwr.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/95mwr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Compared to the band structure of half metal, one spin channel of SGS is touching slightly (gapless).&lt;/p&gt;&#xA;&lt;p&gt;Take a careful look at the cited paper and then you will figure out the difference!&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-08-12T08:53:13.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6551" PostTypeId="1" AcceptedAnswerId="6554" CreationDate="2021-08-12T12:21:36.717" Score="20" ViewCount="1592" Body="&lt;p&gt;I have been looking at using Goedecker-Teter-Hutter (GTH) pseudo-potentials and I came across the abbreviation PADE.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering what this abbreviation actually stood for and how it is related to LDA?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2021-08-12T18:31:58.313" LastActivityDate="2022-01-03T03:52:15.677" Title="What is a Padé approximant?" Tags="|density-functional-theory|mathematical-modeling|pseudopotentials|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6552" PostTypeId="2" ParentId="6551" CreationDate="2021-08-12T12:37:12.240" Score="20" Body="&lt;p&gt;PADE refers to the mathematician &lt;a href=&quot;https://en.wikipedia.org/wiki/Henri_Pad%C3%A9&quot; rel=&quot;noreferrer&quot;&gt;Henri Padé&lt;/a&gt;, who developed the Padé approximation, which can approximate a function using rational polynomial functions.&lt;/p&gt;&#xA;&lt;p&gt;For ex:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sin(x)\approx {\frac {(12671/4363920)x^{5}-(2363/18183)x^{3}+x}{1+(445/12122)x^{2}+(601/872784)x^{4}+(121/16662240)x^{6}}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This feature is used to approximate the total correlational functional and Kinetic Energy functional for the Local Density Approximation (LDA) methods.&lt;/p&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0009261497001759&quot; rel=&quot;noreferrer&quot;&gt;Padé approximants in density functional theory&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2021-08-12T12:37:12.240" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6553" PostTypeId="2" ParentId="6506" CreationDate="2021-08-12T14:20:09.323" Score="5" Body="&lt;p&gt;In the past I used &lt;a href=&quot;https://sourceforge.net/projects/nancyex/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tool&lt;/a&gt; called Nancy_ex developed by my friend to extract transition density cube directly from the .fchk file.&#xA;Taken from the description:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;An open source code for the analysis of electronic excited states:&#xA;Natural Transition Orbitals;&#xA;Detachment and Attachment Density Matrices;&#xA;Quantum Chemical Charge-Transfer Descriptors.&#xA;The code is intended to postprocess Gaussian 03 and 09 outputs.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;At the link you can find all the information you need. Please let me know if this is what you needed.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="7" LastEditDate="2021-08-14T15:43:05.777" LastActivityDate="2021-08-14T15:43:05.777" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6554" PostTypeId="2" ParentId="6551" CreationDate="2021-08-12T18:31:39.477" Score="27" Body="&lt;p&gt;To complement &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6552/5&quot;&gt;mykd's already excellent answer&lt;/a&gt;, I will just add that the approximant we all learn in school (the Taylor approximant) is nice to teach and easy to help students learn the concept of approximations, but in practice it's one of the worst options in terms of it's accuracy-to-complexity ratio.&lt;/p&gt;&#xA;&lt;p&gt;The Taylor approximant matches the &lt;span class=&quot;math-container&quot;&gt;$n^{\textrm{th}}$&lt;/span&gt; derivative at a single point. It is &lt;em&gt;&lt;strong&gt;extremely rare&lt;/strong&gt;&lt;/em&gt; that you would actually care about the &lt;em&gt;&lt;strong&gt;8th derivative&lt;/strong&gt;&lt;/em&gt; (for example) matching at a &lt;em&gt;&lt;strong&gt;single point&lt;/strong&gt;&lt;/em&gt;. More likely, you would want the first, second and maybe third derviatives to match &lt;em&gt;&lt;strong&gt;at several points&lt;/strong&gt;&lt;/em&gt; (i.e. you want the whole function to be well approximated). But in the example below, even the 7th order Taylor approximant is not enough for the approximant to match the original function at &lt;span class=&quot;math-container&quot;&gt;$x=7$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5esgKm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5esgKm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;That is very unfortunate since a 7th degree polynomial will shoot off to &lt;span class=&quot;math-container&quot;&gt;$\pm \infty$&lt;/span&gt; extremely rapidly (as high-order polynomials always do), so even if such an approximant was excellent at describing the original function in some small region, it would extrapolate horrendously.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, imagine trying to approximate a very simple function like &lt;span class=&quot;math-container&quot;&gt;$1/x$&lt;/span&gt; with a (Taylor) polynomial near &lt;span class=&quot;math-container&quot;&gt;$x=0$&lt;/span&gt;. This would be quite impossible, but imagine if instead of trying to come up with the best polynomial approximation, we instead tried to come up with the best &lt;em&gt;&lt;strong&gt;rational&lt;/strong&gt;&lt;/em&gt; function approximation. Now we have the flexibility of adjusting the coefficients in &lt;em&gt;&lt;strong&gt;two&lt;/strong&gt;&lt;/em&gt; polynomials (the one in the numerator and the one in the denominator) instead of just one of them like in the Taylor series, and the &lt;em&gt;&lt;strong&gt;singularities&lt;/strong&gt;&lt;/em&gt; where the denominator of the original function is zero, can now be treated very naturally.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;That is precisely the reason for Padé functions: Trying to give the best rational approximation to a function, rather than just the best polynomial approximation to a function.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are just some of the many different types of approximants which are often superior to the Taylor series, for various practical applications, but are unfortunately not given much attention, even in advanced-level calculus courses:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Pad%C3%A9_approximant&quot; rel=&quot;noreferrer&quot;&gt;Padé approximants&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/B%C3%A9zier_curve&quot; rel=&quot;noreferrer&quot;&gt;Bézier curves&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Spline_(mathematics)&quot; rel=&quot;noreferrer&quot;&gt;Splines&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Chebyshev_polynomials&quot; rel=&quot;noreferrer&quot;&gt;Chebyshev approximants&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;For discussion about generalizations of Padé approximants to functions of more than one variable, you can see &lt;a href=&quot;https://mathoverflow.net/a/413017/66334&quot;&gt;my answer on the topic at MathOverflow&lt;/a&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-03T03:52:15.677" LastActivityDate="2022-01-03T03:52:15.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6555" PostTypeId="1" CreationDate="2021-08-12T20:31:53.463" Score="8" ViewCount="957" Body="&lt;p&gt;I am trying to optimize some 4 atom Ni clusters. There are 4 types: one linear, one zigzag, one 2D and one 3D.&lt;/p&gt;&#xA;&lt;p&gt;Using the setup below, I don't get the calculations to converge even after 1000 SCF steps (which is huge!).&lt;/p&gt;&#xA;&lt;p&gt;I already play with &lt;code&gt;DM.MixingWeight&lt;/code&gt;, &lt;code&gt;SCF.Mixer.History&lt;/code&gt;, &lt;code&gt;SCF.Mixer.Variant&lt;/code&gt;, &lt;code&gt;SCF.Mixer.Kick&lt;/code&gt;, and nothing works.&lt;/p&gt;&#xA;&lt;p&gt;The tolerance is not even high, it is only 1E-3.&lt;/p&gt;&#xA;&lt;p&gt;The input is below.&lt;/p&gt;&#xA;&lt;p&gt;Any ideas, suggestions?&lt;/p&gt;&#xA;&lt;p&gt;Regards,&lt;/p&gt;&#xA;&lt;p&gt;Camps&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SystemName          NiM4-1Dlinear&#xA;SystemLabel         NiM4-1Dlinear&#xA;&#xA;LatticeConstant             12.787740 Ang&#xA;%block LatticeVectors&#xA;     1.394587   0.000000 0.000000&#xA;     0.000000   1.394587 0.000000&#xA;     0.000000   0.000000 1.000000&#xA;%endblock LatticeVectors&#xA;&#xA;NumberOfSpecies        1&#xA;NumberOfAtoms          4&#xA;&#xA;%block ChemicalSpeciesLabel&#xA;  1  28  Ni&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;AtomicCoordinatesFormat Ang&#xA;&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;      8.9168000      8.7888600      9.6866000     1&#xA;      8.9168000      8.7888600      7.5067061     1&#xA;      8.9168000      8.7888600      3.1011000     1&#xA;      8.9168000      8.7888600      5.2809939     1&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA; -- SELF-CONSISTENT FIELD --&#xA;PAO.BasisSize     DZP&#xA;MD.TypeOfRun  CG&#xA;MD.NumCGsteps     1000&#xA;MinSCFIterations  3&#xA;MaxSCFIterations  1000&#xA;SpinPolarized     T&#xA;MeshCutoff        500 Ry&#xA;DM.MixingWeight   0.25&#xA;SCF.Mixer.History  6   # replace DM.NumberPulay&#xA;#SCF.Mixer.Variant  GR&#xA;SCF.Mixer.Kick 3&#xA;DM.Tolerance  0.001&#xA;XC.functional     GGA&#xA;XC.authors        PBE&#xA;SolutionMethod diagon&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="887" LastEditDate="2021-10-05T07:50:40.667" LastActivityDate="2022-08-30T04:47:00.177" Title="How to make SCF converge in SIESTA?" Tags="|numerical-convergence|siesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6556" PostTypeId="2" ParentId="6555" CreationDate="2021-08-13T06:44:00.727" Score="7" Body="&lt;p&gt;A mixing weight of 0.25 is pretty high, if not excessively high in this case.&lt;/p&gt;&#xA;&lt;p&gt;Did you try, say 0.02, or something like that?&lt;/p&gt;&#xA;&lt;p&gt;Also, kicks are &lt;em&gt;only&lt;/em&gt; necessary when you have problems with stalls in convergence. If you stall after 50 SCF, you should have a kick at that point, but definitely not at every 3rd SCF, that may worsen your convergence.&lt;/p&gt;&#xA;&lt;p&gt;Generally one should try first without kicks, or at least a rather high kick value (50-100). As mentioned above kicks are for stalls in the SCF cycle.&lt;/p&gt;&#xA;&lt;p&gt;The mixing weight is more flexible, a too low value will make it converge slower but is more likely to converge in the end. A higher value can make it converge faster but will be more likely to diverge in the SCF cycle.&lt;/p&gt;&#xA;&lt;p&gt;The variant &lt;code&gt;GR&lt;/code&gt; (guaranteed reduction) should in principle be better, but this has some of the downsides that also applies to &amp;quot;kicks&amp;quot;. It may be good for the system or not, again, this is very dependent on the mixing weight.&lt;/p&gt;&#xA;&lt;p&gt;Generally it is very difficult to provide good defaults for all systems as &lt;em&gt;it depends&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-08-13T08:36:53.050" LastActivityDate="2021-08-13T08:36:53.050" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6557" PostTypeId="1" CreationDate="2021-08-13T10:35:07.143" Score="5" ViewCount="93" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AelWv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AelWv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this SSSP pseudopotential file for Quantum ESPRESSO, what does the &amp;quot;pn&amp;quot; column mean?&lt;/p&gt;&#xA;" OwnerUserId="4143" LastEditorUserId="5" LastEditDate="2021-08-13T17:54:35.713" LastActivityDate="2021-08-13T17:55:05.857" Title="What does the &quot;pn&quot; column mean in this pseudopotential file?" Tags="|quantum-espresso|pseudopotentials|terminology|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6558" PostTypeId="2" ParentId="6557" CreationDate="2021-08-13T12:58:52.107" Score="5" Body="&lt;p&gt;The &amp;quot;pn&amp;quot; column here gives the principal quantum number (&amp;quot;n&amp;quot;) for the states of the pseudoatom, which is the &amp;quot;atom&amp;quot; that remains after the core electrons are removed and the original Coulomb potential is replaced with the pseudopotential.&lt;/p&gt;&#xA;&lt;p&gt;For example, in the file you show, the &lt;span class=&quot;math-container&quot;&gt;$n=1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$l=0$&lt;/span&gt; state of the pseudo-atom corresponds to the &lt;span class=&quot;math-container&quot;&gt;$4S$&lt;/span&gt; state (&lt;span class=&quot;math-container&quot;&gt;$n=4$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$l=0$&lt;/span&gt;) of the original all-electron atom.&lt;/p&gt;&#xA;" OwnerUserId="1021" LastEditorUserId="5" LastEditDate="2021-08-13T17:55:05.857" LastActivityDate="2021-08-13T17:55:05.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6559" PostTypeId="1" AcceptedAnswerId="6562" CreationDate="2021-08-13T13:26:39.580" Score="8" ViewCount="264" Body="&lt;p&gt;I am trying to work with the STO-3G basis set, but I noticed that the STO-3G in Basis set exchange is different from the STO-3G originally published, and not only that, the BSE version seem to be significantly worse. I am sure I am doing something wrong, can anyone please point out? (original references are provided in the python script)&lt;/p&gt;&#xA;&lt;p&gt;Here are the plotted STO-3G functions and python script for plotting the analytical H1S and STO-3G functions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LptDk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LptDk.png&quot; alt=&quot;Pople vs BSE&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;#-------------------------------------------------------------------&#xA;# BASIS SET EXCHANGE STO3G H&#xA;# https://www.basissetexchange.org/basis/sto-3g/format/nwchem/?version=1&amp;amp;elements=1&#xA;# BASIS &amp;quot;ao basis&amp;quot; PRINT&#xA;# #BASIS SET: (3s) -&amp;gt; [1s]&#xA;# H    S&#xA;#       0.3425250914E+01       0.1543289673E+00&#xA;#       0.6239137298E+00       0.5353281423E+00&#xA;#       0.1688554040E+00       0.4446345422E+00&#xA;# END&#xA;# ------------------------------------------------------------------&#xA;def STO3G_BSE(x0,x):&#xA;    return \&#xA;        0.1543289673E+00 * (2 * 0.3425250914E+01/ np.pi)**(3/4) * \&#xA;        np.exp(-0.3425250914E+01*(x0 - x)**2) + \&#xA;        0.5353281423E+00 * (2 * 0.6239137298E+00/ np.pi)**(3/4) * \&#xA;        np.exp(-0.6239137298E+00*(x0 - x)**2) + \&#xA;        0.4446345422E+00 * (2 * 0.1688554040E+00/ np.pi)**(3/4) * \&#xA;        np.exp(-0.1688554040E+00*(x0 - x)**2) &#xA;&#xA;&#xA;#------------------------------------------------------------------&#xA;# Pople, Hehre and Stewart STO-3G 1S&#xA;# Hehre, W. J., Stewart, R. F., &amp;amp; Pople, J. A. (1969). &#xA;# Self‐Consistent Molecular‐Orbital Methods. I. Use of Gaussian Expansions of Slater‐Type Atomic Orbitals. &#xA;# The Journal of Chemical Physics, 51(6), 2657–2664. doi:10.1063/1.1672392 &#xA;# Table 1&#xA;#------------------------------------------------------------------&#xA;&#xA;def STO3G_PHS(x0,x):&#xA;    return \&#xA;        0.1543289673E+00 * (2 * 2.227660/ np.pi)**(3/4) * \&#xA;        np.exp(-2.227660*(x0 - x)**2) + \&#xA;        0.5353281423E+00 * (2 * 0.405771/ np.pi)**(3/4) * \&#xA;        np.exp(-0.405771*(x0 - x)**2) + \&#xA;        0.4446345422E+00 * (2 * 0.109818/ np.pi)**(3/4) * \&#xA;        np.exp(-0.109818*(x0 - x)**2) &#xA;&#xA;&#xA;&#xA;# 1H 1S&#xA;plt.plot(np.linspace(0,10),1/np.sqrt(np.pi) * np.exp(- np.linspace(0,10)), label=&amp;quot;1S&amp;quot;)&#xA;&#xA;# STO3G from BSE&#xA;plt.plot(np.linspace(0,10),STO3G_BSE(0., np.linspace(0,10)), label=&amp;quot;BSE&amp;quot;)&#xA;&#xA;# STO3G from the Pople paper&#xA;plt.plot(np.linspace(0,10),STO3G_PHS(0., np.linspace(0,10)), label=&amp;quot;Pople et al.&amp;quot;)&#xA;&#xA;plt.xlabel(&amp;quot;r [a.u.]&amp;quot;)&#xA;plt.legend()&#xA;&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="785" LastActivityDate="2021-08-13T14:44:41.977" Title="Difference between original STO-3G and BSE STO-3G" Tags="|computational-chemistry|basis-sets|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6560" PostTypeId="1" AcceptedAnswerId="6561" CreationDate="2021-08-13T13:36:47.127" Score="6" ViewCount="54" Body="&lt;p&gt;The total wave function of &lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt; can be written as a linear combination of configurations built from bonding and anti-bonding orbitals:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle \Psi _{\text{MC}}=C_{1}\Phi _{1}+C_{2}\Phi _{2},}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Phi_2$&lt;/span&gt; is the electronic configuration &lt;span class=&quot;math-container&quot;&gt;$(φ_2)^2$&lt;/span&gt;. In this multiconfigurational description of the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; chemical bond, &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt;  = 1 and &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt; = 0 close to equilibrium, and &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; will be comparable to &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt; for large separations.&lt;/p&gt;&#xA;&lt;p&gt;How are the coefficients calculated?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="7" LastEditDate="2021-08-13T14:46:35.483" LastActivityDate="2021-08-13T14:46:35.483" Title="Multi-configurational self-consistent field coefficients" Tags="|self-consistent-field|multi-reference|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6561" PostTypeId="2" ParentId="6560" CreationDate="2021-08-13T14:24:45.553" Score="6" Body="&lt;p&gt;In a MCSCF approach, the coefficients &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; are calculated by minimizing the energy &lt;span class=&quot;math-container&quot;&gt;$\langle \Psi_{\mathrm{MC}}|H|\Psi_{\mathrm{MC}} \rangle$&lt;/span&gt; with respect to (1) the MOs contributing to the configurations &lt;span class=&quot;math-container&quot;&gt;$\Phi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Phi_2$&lt;/span&gt; (herein we have only two active orbitals, &lt;span class=&quot;math-container&quot;&gt;$\varphi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varphi_2$&lt;/span&gt;), and also (2) the coefficients &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt;, subject to (1) orthonormality conditions of the MOs and (2) orthonormality conditions of the configurations.&lt;/p&gt;&#xA;&lt;p&gt;Although this uniquely determines the mathematical problem to be solved, the actual algorithm of solving this minimization problem is another matter. For example, the following techniques are all quite popular:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Optimize &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; holding &lt;span class=&quot;math-container&quot;&gt;$\varphi_i$&lt;/span&gt; fixed (which is equivalent to full CI within the active space), then optimize &lt;span class=&quot;math-container&quot;&gt;$\varphi_i$&lt;/span&gt; holding &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; fixed, and so on, until both converge. The latter optimization can proceed by using the gradient only, or using both the gradient and the Hessian.&lt;/li&gt;&#xA;&lt;li&gt;Optimize both &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varphi_i$&lt;/span&gt; at the same time, using only the gradient of the energy &lt;span class=&quot;math-container&quot;&gt;$\langle \Psi_{\mathrm{MC}}|H|\Psi_{\mathrm{MC}} \rangle$&lt;/span&gt; with respect to  &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varphi_i$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Optimize both &lt;span class=&quot;math-container&quot;&gt;$C_I$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\varphi_i$&lt;/span&gt; at the same time, using both gradient and Hessian information.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Implementing any such algorithm, especially when fast convergence is desired, is highly non-trivial. Anyway I hope the above answer already gives you a rough idea about how this works.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-08-13T14:24:45.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6562" PostTypeId="2" ParentId="6559" CreationDate="2021-08-13T14:44:41.977" Score="9" Body="&lt;p&gt;Your formula for the analytical &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; 1S orbital is incorrect. A 1S orbital has the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\phi_{1s}(\zeta_1,r)=\sqrt{\frac{\zeta_1^3}{\pi}}\exp(-\zeta_1 r)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; the optimal value for &lt;span class=&quot;math-container&quot;&gt;$\zeta_1$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$1.24$&lt;/span&gt;. If you update your plot in this way, you will see that the BSE plot is the correct one for &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So what is wrong with the coefficients from the Pople paper? Nothing, except that these are all determined for &lt;span class=&quot;math-container&quot;&gt;$\zeta_1=1$&lt;/span&gt; and the Gaussians need to be rescaled if &lt;span class=&quot;math-container&quot;&gt;$\zeta_1$&lt;/span&gt; is changed. This can be done using&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_{1s}(\zeta_1,r)=\zeta_1^{3/2}\phi_{1s}(1,\zeta r)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So to get your PHS graph to match the others, you need to multiply each Gaussian by &lt;span class=&quot;math-container&quot;&gt;$1.24^{3/2}=1.380805$&lt;/span&gt; and multiply the exponent by a factor of &lt;span class=&quot;math-container&quot;&gt;$1.24^2=1.5376$&lt;/span&gt;. If you compare the BSE and PHS specifications of the basis set, you can see that the exponents are different by a factor of &lt;span class=&quot;math-container&quot;&gt;$1.5376$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To sum up, the issue is that the Pople values aren't specifically for &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; 1s STO-3g; rather they are for any element's 1s STO-3g, provided that they are appropriately rescaled by the optimal &lt;span class=&quot;math-container&quot;&gt;$\zeta_1$&lt;/span&gt; value for that element.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-08-13T14:44:41.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6563" PostTypeId="1" AcceptedAnswerId="6567" CreationDate="2021-08-13T15:28:13.823" Score="9" ViewCount="1305" Body="&lt;p&gt;I am interested to understand the advantages of the Davidson diagonalization method over other sparse matrix diagonalization routines. For instance, Intel MKL.&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2021-08-13T17:57:12.727" LastActivityDate="2021-08-16T23:17:40.313" Title="What are the advantages of the Davidson diagonalization method over other sparse matrix diagonalization methods?" Tags="|high-performance-computing|mathematical-modeling|numerical-convergence|full-configuration-interaction|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6564" PostTypeId="1" CreationDate="2021-08-14T01:48:55.290" Score="11" ViewCount="139" Body="&lt;p&gt;I am not entirely sure if this is better suited to Chemistry.SE or Matter modelling, but hey, you guys are nicer.&lt;/p&gt;&#xA;&lt;p&gt;I am fascinated by just how complicated combustion processes are.&lt;/p&gt;&#xA;&lt;p&gt;I was watching an old SpaceX video on how they model the combustion processes in their Raptor engines. (&lt;a href=&quot;https://www.youtube.com/watch?v=txk-VO1hzBY&amp;amp;t=39m40s&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here is a really relevant video with timestamp, which I recommend people watch in full&lt;/a&gt;.)&lt;/p&gt;&#xA;&lt;p&gt;They give the example of hydrogen burning with oxygen, which requires 23 separate chemical equations to model, and that is with the &lt;em&gt;reduced mechanism.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/F780g.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/F780g.png&quot; alt=&quot;The myriad of intermediate chemical reactions involved in combusting hydrogen with oxygen&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Incidentally, I would like to know what column 'b' refers to in the table above.)&lt;/p&gt;&#xA;&lt;p&gt;The situation with methane combustion is even worse. 53 species and 325 reactions are involved.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If one were to attempt to model simplified versions of these processes, how would they go about it?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there an &lt;em&gt;a-priori&lt;/em&gt; way of telling which individual reactions contribute little to the overall combustion, just by the identity of the species involved and the other entries in the table? Intuitively, one expects the interactions of two different rare high-energy intermediates to not contribute greatly to the overall combustion, but what if it does?&lt;/p&gt;&#xA;&lt;p&gt;While highly nonlinear, I don't believe these equations are chaotic, at least in a situation with perfect mixing. Even so, I suspect changes in the proportion of trace intermediates could very easily have large effects on subsequent reactions.&lt;/p&gt;&#xA;&lt;p&gt;Does it come down to running the full simulation, then successively removing reactions until the accuracy drops below an acceptable threshold? Or are there tricks one can use to simplify these equations?&lt;/p&gt;&#xA;" OwnerUserId="4153" LastEditorUserId="4153" LastEditDate="2022-01-16T23:08:17.643" LastActivityDate="2022-04-07T22:58:13.700" Title="Combustion models. How does one determine the most relevant reactions?" Tags="|reaction-mechanism|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6565" PostTypeId="5" CreationDate="2021-08-14T16:59:06.620" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://xtb-docs.readthedocs.io/en/latest/contents.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-14T16:59:06.620" LastActivityDate="2021-08-14T16:59:06.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6566" PostTypeId="4" CreationDate="2021-08-14T16:59:06.620" Score="0" Body="Questions about or related to XTB, the semi-empirical (extended) tight-binding software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-14T16:59:06.620" LastActivityDate="2021-08-14T16:59:06.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6567" PostTypeId="2" ParentId="6563" CreationDate="2021-08-15T06:27:47.300" Score="9" Body="&lt;p&gt;The Davidson-Method is the best algorithm when you want a comparatively small number of eigenvectors/eigenvalues from a sparse, diagonally dominant matrix.&lt;/p&gt;&#xA;&lt;p&gt;MKL doesn’t have a sparse matrix diagonalization method, but it’s a good idea to use it for the Linear Algebra operations used when implementing Davidson. If you want ALL the eigenvectors then you definitely want a dense eigensolver like what MKL offers.&lt;/p&gt;&#xA;&lt;p&gt;Previous to the Davidson Algorithm the methods used to calculate a few eigenvectors were the Power method, and the Raleigh-Ritz Method. The power method is still widely used today in applications but &lt;strong&gt;IIRC&lt;/strong&gt; the advantage of Davidson is that it's faster than these methods because If you have many roots you need to solve for, you don't need to update them all if some have converged, which saves a lot of time.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-08-15T06:27:47.300" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6568" PostTypeId="2" ParentId="3628" CreationDate="2021-08-15T06:37:34.827" Score="8" Body="&lt;p&gt;The error of a MD simulation can be roughly partitioned into four contributions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Error due to short-period statistical fluctuations;&lt;/li&gt;&#xA;&lt;li&gt;Error due to poor- or non-ergodicity (in other words, extremely long-period statistical fluctuations);&lt;/li&gt;&#xA;&lt;li&gt;Error due to numerical round-off and the use of a finite time step;&lt;/li&gt;&#xA;&lt;li&gt;Error due to the force field itself.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Quantification of 1 is trivial, for example you can compute your desired property using a series of short MD trajectories, and compute the standard deviation of their mean. 2 is very hard and basically impossible to reliably estimate, because it requires one to sample all low-barrier paths that leads the simulation to a basin with low free energy, which should be NP-hard. 3 is probably predominantly reflected in the conservation of energy, and if in doubt, you can always estimate it by using higher numerical precision (double precision instead of single precision) and a smaller time step.&lt;/p&gt;&#xA;&lt;p&gt;4 is the most interesting (and arguably the most underrated) contribution. There are some methods for estimating it, for example &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3545069&quot; rel=&quot;noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.3545069&lt;/a&gt;. However this requires that you go into the training set of the force field, and also have knowledge of the experimental uncertainties of the training data, which can be a non-trivial amount of work. You may search for articles that cite this paper for more examples of error quantification of the force field itself.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-08-15T06:37:34.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6569" PostTypeId="2" ParentId="4323" CreationDate="2021-08-15T07:04:05.517" Score="8" Body="&lt;p&gt;In general, you should use the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state by default, unless you have reasons to suspect that your molecule is anti-Kasha.&lt;/p&gt;&#xA;&lt;p&gt;IMHO satisfying one of the following criteria guarantees that your molecule obeys the Kasha rule (supposing that your calculation is accurate), and you basically need not suspect otherwise:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The experimental fluorescence spectrum mirrors the longest wavelength absorption peak, and the calculated &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state is a bright state. (This reasonably shows that the experimental fluorescence is from the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state. Note that the latter criterion is important and is frequently overlooked by experimentalists, because if the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state is dark, the longest wavelength absorption peak does not correspond to &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; anymore.)&lt;/li&gt;&#xA;&lt;li&gt;The chromophore of the molecule closely resembles a system that is known to obey the Kasha rule.&lt;/li&gt;&#xA;&lt;li&gt;Optimizing the geometry of the &lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; state ends up at a &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; conical intersection. (This means the &lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; internal conversion is extremely fast, within ~ 1 ps, which prevents the &lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; state from fluorescing.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Satisfying one of the following criteria, however, means that you must closely check if the fluorescence is anti-Kasha, for example by a full set of calculations of relevant internal conversion rates and fluorescence rates. Note the criteria alone are not sufficient for guaranteeing that the molecules does not obey the Kasha rule:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The experimental fluorescence spectrum does not mirror the longest wavelength absorption peak, and instead mirrors a shorter wavelength absorption peak.&lt;/li&gt;&#xA;&lt;li&gt;Computations suggest that the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state is dark (f &amp;lt; 0.0001) at the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; equilibrium.&lt;/li&gt;&#xA;&lt;li&gt;Optimizing the geometry of the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state ends up at a &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; conical intersection, however optimizing the &lt;span class=&quot;math-container&quot;&gt;$S_2$&lt;/span&gt; state does not end up at a conical intersection.&lt;/li&gt;&#xA;&lt;li&gt;The computed &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; emission wavelength is much longer than the experimental emission wavelength.&lt;/li&gt;&#xA;&lt;li&gt;The chromophore closely resembles a known anti-Kasha molecule, for example azulene.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-08-15T07:04:05.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6571" PostTypeId="1" AcceptedAnswerId="6577" CreationDate="2021-08-16T15:00:27.183" Score="6" ViewCount="340" Body="&lt;p&gt;Is it possible to direct VASP to read a &lt;code&gt;POSCAR-xyz&lt;/code&gt; file instead of reading the default POSCAR?&lt;/p&gt;&#xA;&lt;p&gt;For example, I want to run VASP in the Quantum ESPRESSO format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$/PW.x &amp;lt; QE.in &amp;gt; QE.out . &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here &lt;code&gt;pw.x&lt;/code&gt; can read any filename that we give with a file extension of &lt;code&gt;.in&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the same way, I want to direct VASP to read POSCAR-xyz file instead of POSCAR.&lt;/p&gt;&#xA;" OwnerUserId="1713" LastEditorUserId="1713" LastEditDate="2021-08-16T16:51:31.710" LastActivityDate="2021-08-17T02:09:15.630" Title="How to run multiples VASP files named as POSCAR-XYZ" Tags="|vasp|software|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6572" PostTypeId="2" ParentId="6563" CreationDate="2021-08-16T17:45:27.217" Score="8" Body="&lt;p&gt;To supplement Cody's excellent answer, Davidson diagonalization originates from quantum chemistry, where solving configuration interaction problems requires diagonalizing the Hamiltonian in the space of electron configurations. The Davidson algorithm and refinements thereof enabled full configuration interaction calculations with matrix sizes of &lt;span class=&quot;math-container&quot;&gt;$10^9 \times 10^9$&lt;/span&gt; already in the early 1990s. The key in the algorithm is that the matrix is extremely sparse, since matrix elements are nonzero only in the case where two configurations differ by a double excitation, at most; moreover, the diagonal elements are energies of individual configurations which increase monotonically, and are larger than the off-diagonal values.&lt;/p&gt;&#xA;&lt;p&gt;An alternative to Davidson, which appears to be popular among physicists, is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lanczos_algorithm&quot; rel=&quot;noreferrer&quot;&gt;Lanczos algorithm&lt;/a&gt;. Davidson and Lanczos are somewhat similar algorithms, in that both operate on a vector subspace which is used to estimate the eigenvalues and eigenvectors of the full matrix.&lt;/p&gt;&#xA;&lt;p&gt;However, according to an older colleague who worked on large configuration interaction calculations in the 1990s, the Davidson algorithm has much better and more reliable convergence properties, because the vectors added at each step lead to an optimal decrease of the energy; this is especially true for the reformulations due to e.g. Jeppe Olsen that employ better preconditioning and eliminate potential numerical instabilities that appear for gigantic matrices. At variance, the Lanczos method may stagnate for a long time (for tens to hundreds of iterations), and then change suddenly as the algorithm lands on a new, more important basis vector. This makes it hard to trust the results of Lanczos calculations, as seemingly converged values may turn out to be not converged. In contrast, you can always trust Davidson if it has been converged to a suitably small threshold.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-08-16T17:45:27.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6573" PostTypeId="1" CreationDate="2021-08-16T19:37:52.253" Score="8" ViewCount="115" Body="&lt;p&gt;I have recently started working on Double Perovskites Quantum Dots and one of the main issue with them is that they are not much stable. Some papers did talk about how much stable there compounds are but there is not much quantitative comparison I could find. So before going into the depth of optical and electronic properties I thought I should do a comparison between stability for different types of Quantum Dots (the ones I think which show a lot of promise: &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs2AgMX6}$&lt;/span&gt;, M = Sb,In,Bi). However I am a bit confused how do I approach this.&lt;/p&gt;&#xA;&lt;p&gt;Some literature I found online uses convex hull method to find possible stable structures, but how do I implement this. And I think doing a comparison of Goldschmidt's tolerance factor along with cation/anion radius ratio might also help.&lt;/p&gt;&#xA;&lt;p&gt;Please guide me what possible approach would be suitable for this type of comparison.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2021-08-25T11:13:27.183" LastActivityDate="2021-08-25T11:13:27.183" Title="How to compare the stability of two nano-structures using ab-inito calculations?" Tags="|quantum-espresso|gaussian|nanostructures|quantum-dots|perovskites|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-31T18:08:40.513" ContentLicense="CC BY-SA 4.0" />
  <row Id="6574" PostTypeId="1" CreationDate="2021-08-16T20:34:33.343" Score="7" ViewCount="159" Body="&lt;p&gt;I am looking for a way to computationally analyse the interactions between two molecular species (as solute and solvent) in an isotropic mixture using X-ray scattering. &lt;strong&gt;Is there a guideline as to how an obtained &lt;a href=&quot;https://en.wikipedia.org/wiki/Structure_factor&quot; rel=&quot;nofollow noreferrer&quot;&gt;structure factor, &lt;span class=&quot;math-container&quot;&gt;$S(q)$&lt;/span&gt;,&lt;/a&gt; can be analysed?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;As an example, Figure 2 (below) from &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5111643&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structural analysis of ionic liquids with symmetric and asymmetric fluorinated anions&lt;/a&gt; shows the &lt;span class=&quot;math-container&quot;&gt;$S(q)$&lt;/span&gt; for various ionic liquids and suggests that the dashed vertical line at 2 &lt;span class=&quot;math-container&quot;&gt;$Å^{−1}$&lt;/span&gt; is the approximate boundary between intermolecular (&lt;span class=&quot;math-container&quot;&gt;$q &amp;lt; 2 Å^{−1}$&lt;/span&gt;) and intramolecular (&lt;span class=&quot;math-container&quot;&gt;$q &amp;gt; 2 Å^{−1}$&lt;/span&gt;) interactions, which is not clearly evident from the article itself.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pNnyh.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pNnyh.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A radial distribution function (RDF) for a solid-liquid or liquid mixture can be analysed in terms of solvation shells, coordination numbers, etc, so I was hoping there might be a similar way we can analyse structure factors.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2021-12-31T01:18:26.617" LastActivityDate="2021-12-31T01:18:26.617" Title="How to analyse structure factors calculated from a mixture of isotropic amorphous substrates" Tags="|molecular-dynamics|spectroscopy|molecular-interactions|x-ray-diffraction|radial-distribution-function|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6575" PostTypeId="2" ParentId="6563" CreationDate="2021-08-16T22:16:47.797" Score="11" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6563/what-are-the-advantages-of-the-davidson-diagonalization-method-over-other-sparse#comment14304_6563&quot;&gt;Following Nike Dattani's suggestion&lt;/a&gt;, I now add some comparisons of the Davidson method with methods that are more &amp;quot;modern&amp;quot; than it, to supplement the existing answers which compared the Davidson method with methods that predates it. However my answer will be more or less off-topic because I will mainly talk about &lt;em&gt;dis&lt;/em&gt;advantages of the Davidson method compared to these methods. (It would sound strange if I introduce some new methods just to reveal their disadvantages!)&lt;/p&gt;&#xA;&lt;p&gt;The Davidson method was developed in the 1970s (E. R. Davidson, J. Comput. Phys. 1975, 17, 87), and basically consists of:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Projecting the matrix to be diagonalized, &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, onto a basis &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; whose dimension is much smaller than &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; itself.&lt;/li&gt;&#xA;&lt;li&gt;Perform exact diagonalization on the projected matrix, giving eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\{E\}$&lt;/span&gt; and eigenvectors &lt;span class=&quot;math-container&quot;&gt;$\{V\}$&lt;/span&gt;. If the desired eigenvectors of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; can be exactly spanned by the basis &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$\{E\}$&lt;/span&gt; are exact eigenvalues of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, and exact eigenvectors of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; can be obtained from &lt;span class=&quot;math-container&quot;&gt;$\{V\}$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;C_k = \sum_i X_i V_{ik} \tag{1}&#xA;\end{align}&lt;/span&gt;&#xA;However as &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; has a much lower dimension than &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; does, this condition is normally not exactly fulfilled, and we must expand &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; until the desired eigenvectors are entirely contained in that space.&lt;/li&gt;&#xA;&lt;li&gt;Compute approximate eigenvectors &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; according to Eq. (1), and check if they have converged. The latter is done by verifying if &lt;span class=&quot;math-container&quot;&gt;$HC - EC$&lt;/span&gt; is (approximately) the zero vector.&lt;/li&gt;&#xA;&lt;li&gt;If the eigenvectors have not converged yet, expand the basis &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; in the hope that we can expand the exact eigenvectors better with the enlarged basis. To expand the basis in the most efficient way, we resort to the residual vector &lt;span class=&quot;math-container&quot;&gt;$HC - EC$&lt;/span&gt;, which roughly tells us in which direction &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is wrong. We then selectively include some basis vectors that point to roughly the same direction as &lt;span class=&quot;math-container&quot;&gt;$HC - EC$&lt;/span&gt; does (but not quite, since even better results are given by first scaling the residual vector by a matrix called the preconditioner - this is the essence of the Davidson method).&lt;/li&gt;&#xA;&lt;li&gt;Go to step 1, using the enlarged basis instead.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;(Note that the very fact that the Davidson method is faster than dense matrix diagonalization routines, such as DSYEV in LAPACK, is because we only want a small subset of the matrix's eigenvalues and eigenvectors. Otherwise, the Davidson method, at least in its original form, cannot be faster than DSYEV even if the matrix is sparse. Conversely, if we want only a few eigenvalues and eigenvectors, then Davidson is faster than DSYEV even if the matrix is dense.)&lt;/p&gt;&#xA;&lt;p&gt;Despite the great success of the Davidson method, it has two drawbacks:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The memory cost increases during the iterations. For large scale calculations, the basis &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; thus must be periodically reduced by discarding some of the basis vectors, in order to avoid memory bottlenecks, but this frequently throws important basis vectors away, leading to poor convergence.&lt;/li&gt;&#xA;&lt;li&gt;It's hard, or even impossible, to converge some eigenvalues in the middle of the spectrum of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, without calculating either all eigenvalues that are smaller than them, or all eigenvalues that are larger than them. For example, suppose you want to calculate the carbon K-edge X-ray absorption spectrum of an organic molecule with TDDFT. With the Davidson method, you have to either (1) calculate all the eigenvalues from the visible region to UV to X-ray, until you reach the carbon K-edge; or (2) calculate all the eigenvalues from the highest energy X-ray absorption downward, until you reach the carbon K-edge. Neither is affordable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;One remedy of the first problem is to throw away certain linear combinations of the basis vectors in &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; that are known to be relatively unimportant. If this is done at each iteration, rather than only when the memory bottleneck is reached, then it is found that the second problem can also be solved. To see this, suppose that the user wants to calculate all eigenvalues within an interval &lt;span class=&quot;math-container&quot;&gt;$[ E_1, E_2 ]$&lt;/span&gt;. At one point the expansion space &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; may contain a basis vector that is a linear combination of two eigenvectors, the eigenvalue of one of them being smaller than &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt;, the other larger than &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt;. When diagonalizing the projected matrix, this basis vector will give a spurious eigenvalue that may fall within the window &lt;span class=&quot;math-container&quot;&gt;$[ E_1, E_2 ]$&lt;/span&gt;. If &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; approaches a fixed size, then as the basis &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; becomes better and better, such spurious eigenvectors will eventually disappear, as the basis will eventually be good enough for the algorithm to discover that the eigenvalue is spurious. However, if &lt;span class=&quot;math-container&quot;&gt;$\{X\}$&lt;/span&gt; keeps enlarging, then more spurious eigenvalues keep appearing in the energy window while we remove the existing spurious eigenvalues, which easily makes the program resemble Sisyphus.&lt;/p&gt;&#xA;&lt;p&gt;Based on this idea (remove certain linear combination of basis vectors at every iteration), several successors of the Davidson method emerged in recent decades, e.g. GPLHR, LOBPCG and iVI. Of these, iVI is the most general, and includes LOBPCG and a variant of GPLHR as special cases. The details of the algorithm (&lt;a href=&quot;http://doi.org/10.1002/jcc.24907&quot; rel=&quot;noreferrer&quot;&gt;http://doi.org/10.1002/jcc.24907&lt;/a&gt;) are rather technical so I'll not reproduce them here. Instead I only mention some practical benefits of iVI:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;iVI can be used to calculate core excitation spectra (X-ray absorption spectra), which the Davidson method struggles to converge;&lt;/li&gt;&#xA;&lt;li&gt;When doing a SCF calculation of a material that has many energy bands, one can parallelize the calculation with respect to the energy bands, so that each computer node solves a few bands, and during the calculation there is no internode communication; this is in contrast to most programs where the calculation can only be parallelized on the level of atoms, basis functions and/or grid points, thereby involving a lot of communication overhead.&lt;/li&gt;&#xA;&lt;li&gt;Likewise, a TDDFT calculation can be parallelized based on wavelength ranges. Suppose you have a large molecule that has hundreds of excited states in the visible region. You can compute the &lt;span class=&quot;math-container&quot;&gt;$&amp;gt; 600 \textrm{ nm}$&lt;/span&gt; part of the spectrum on one node, the &lt;span class=&quot;math-container&quot;&gt;$500 \sim 600 \textrm{ nm}$&lt;/span&gt; part on a second node, the &lt;span class=&quot;math-container&quot;&gt;$420 \sim 500 \textrm{ nm}$&lt;/span&gt; part on a third one, and the &lt;span class=&quot;math-container&quot;&gt;$380 \sim 420 \textrm{ nm}$&lt;/span&gt; part on a fourth one. Finally you combine the four spectra to yield the whole visible absorption spectrum.&lt;/li&gt;&#xA;&lt;li&gt;You can compute the absorption spectrum within a wavelength range by directly specifying the wavelength range itself, and you do not need to guess the number of roots that you need to calculate - the program will automatically find this out.&lt;/li&gt;&#xA;&lt;li&gt;iVI requires less memory than the Davidson method, typically by 2x or more.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, back to topic. What are the &lt;em&gt;advantages&lt;/em&gt; of the Davidson method compared to iVI etc.? One can name a few:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The Davidson method is easier to implement than iVI, and open-source implementations of the former are easier to find;&lt;/li&gt;&#xA;&lt;li&gt;For TDDFT calculations, iVI sometimes suffer from the accumulation of numerical errors that affect the orthogonality of the basis vectors, and require additional matrix-vector product calculations to remove, although this problem is specific to full TDDFT, and is absent when the matrix to be diagonalized is Hermitian, for example in SCF or the Tamm-Dancoff approximation of TDDFT. Note that the Davidson method also suffer from similar orthogonality errors, but they are very cheap to remove.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastEditorUserId="5" LastEditDate="2021-08-16T23:17:40.313" LastActivityDate="2021-08-16T23:17:40.313" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6576" PostTypeId="1" CreationDate="2021-08-16T23:19:42.057" Score="4" ViewCount="41" Body="&lt;p&gt;I am interested in creating an enterocyte intestinal basal membrane.&lt;/p&gt;&#xA;&lt;p&gt;So, I wonder if there is a database or site where the membrane could be downloaded or created.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-08-17T17:13:03.237" LastActivityDate="2021-08-17T17:13:03.237" Title="Is there a site to obtain or create membranes?" Tags="|one-topic-per-answer|databases|biomaterials|membranes|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6577" PostTypeId="2" ParentId="6571" CreationDate="2021-08-17T02:09:15.630" Score="9" Body="&lt;p&gt;Vasp package will not read any other name instead of &lt;code&gt;POSCAR&lt;/code&gt;, The best trick is to write a small script , Here is bash script&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for xyz in `seq  1 1 5` # change the range needed&#xA;do&#xA;mkdir $xyz&#xA;cp INCAR $xyz/&#xA;cp POTCAR $xyz/&#xA;cp POSCAR.$xyz $xyz/POSCAR&#xA;cp KPOINTS $xyz/&#xA;cd $xyz&#xA;vasp-5.4.4  # This is vasp run command add mpi if needed&#xA;cd ..&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Save this as &lt;code&gt;script.sh&lt;/code&gt; and run as &lt;code&gt;bash script.sh&lt;/code&gt;&#xA;You can also combined &lt;code&gt;POSCAR&lt;/code&gt;, &lt;code&gt;KPOINTS&lt;/code&gt; and &lt;code&gt;INCAR&lt;/code&gt; as single script VASP.sh same as quantum espresso.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-08-17T02:09:15.630" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6579" PostTypeId="2" ParentId="6576" CreationDate="2021-08-17T07:15:42.790" Score="4" Body="&lt;h1&gt;CHARMM-GUI&lt;/h1&gt;&#xA;&lt;p&gt;It is possible to create molecular systems with a membrane using &lt;a href=&quot;https://www.charmm-gui.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CHARMM-GUI&lt;/a&gt;. There is also a &lt;a href=&quot;https://charmm-gui.org/?doc=tutorial&amp;amp;project=membrane&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt; available. The current version requires a registered user account but it is free for academic use. If you need the system for molecular dynamics simulations, one can easily create input files, e.g. for &lt;a href=&quot;https://www.ks.uiuc.edu/Research/namd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NAMD&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4163" LastEditorUserId="5" LastEditDate="2021-08-17T17:12:25.510" LastActivityDate="2021-08-17T17:12:25.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6580" PostTypeId="1" CreationDate="2021-08-17T08:40:51.030" Score="4" ViewCount="350" Body="&lt;p&gt;I would like to perform single-point/geometry-optimization/NEB calculations on systems involving both molecular oxygens and adsorbed oxygens. Reductions by hydrogens are also involved.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am still struggling to find an approach to deal with the spin. Molecular oxygen is a triplet, but this is not the case after/during a reaction/adsorption.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The DFT calculation should be able to find a triplet electronic state for molecular oxygens (gas phase) without me enforcing it.&lt;/p&gt;&#xA;&lt;p&gt;I am using Quantum ESPRESSO currently and I am still unsure about spin calculations in general.&lt;/p&gt;&#xA;&lt;p&gt;I am pretty sure about using &lt;code&gt;nspin=2&lt;/code&gt; (spin-polarized calculation) and not setting any &lt;code&gt;tot_magnetization&lt;/code&gt;. For a simple isolated molecular oxygen molecule the final magnetization is around 0.7 per atom, &lt;strong&gt;so should I put this value as &amp;quot;&lt;code&gt;starting_magnetization&lt;/code&gt;&amp;quot; for the oxygen element?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2021-08-17T17:50:22.223" LastActivityDate="2021-08-18T03:37:18.333" Title="Density functional theory and oxygen spin" Tags="|density-functional-theory|quantum-espresso|molecular-modeling|spin|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6581" PostTypeId="2" ParentId="6580" CreationDate="2021-08-18T03:37:18.333" Score="2" Body="&lt;p&gt;I don't have much experience with QE, but in VASP, which I imagine is pretty similar, oftentimes not setting an initial magnetization on each ion results in zero magnetic moments on those ions. This is probably because, numerically, it finds a local minima that results in zero spin despite doing a spin polarized calculation. I would highly suggest initializing the spin of the unit cell or, better yet, of individual ions to roughly what you think they should be. In the case of O2, that would be 1.0 per oxygen (ie 1 spin up electron per O).&lt;/p&gt;&#xA;&lt;p&gt;Side note: The &lt;a href=&quot;https://www.vasp.at/wiki/index.php/MAGMOM&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP wiki&lt;/a&gt; also states that it's sometimes a good idea to set the initial magnetic moments 1.2-1.5 times what you think it ought to be, though I'll defer to someone more experienced with QE to tell you whether that's a good idea or not.&lt;/p&gt;&#xA;" OwnerUserId="3817" LastActivityDate="2021-08-18T03:37:18.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6582" PostTypeId="2" ParentId="4196" CreationDate="2021-08-18T08:30:40.780" Score="4" Body="&lt;p&gt;LDA only includes local density effects.&lt;/p&gt;&#xA;&lt;p&gt;GGA also includes dependence on the gradient of the density.&lt;/p&gt;&#xA;&lt;p&gt;Meta-GGAs include dependence on the Laplacian of the density and/or the local kinetic energy density.&lt;/p&gt;&#xA;&lt;p&gt;Double hybrids include a mixture of post-Hartree-Fock correlation; typically either according to MP2 or RPA.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-08-18T08:30:40.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6583" PostTypeId="1" AcceptedAnswerId="6585" CreationDate="2021-08-18T12:38:19.223" Score="6" ViewCount="100" Body="&lt;p&gt;I'm trying to create a CV for angle theta. To make this calculation, the right atom selections need to be made. The function is given below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def theta_(traj):&#xA;    angI = mdtraj_topology.select('resid ' + residA + dicACGT['A'])&#xA;    angII = mdtraj_topology.select('resid ' + residA + ' and name P OP1 OP2 or resid ' + str(int(residA) - 1) + ' and name P OP1 OP2')&#xA;                              &#xA;    subIIIa = mdtraj_topology.select('resid ' + str(int(residA) - 1) + dicACGT[neighbors[0]])&#xA;    subIIIb = mdtraj_topology.select('resid ' + str(int(residA) + 1) + dicACGT[neighbors[1]])&#xA;    subIIIc = mdtraj_topology.select('resid ' + str(int(residT) - 1) + dicACGT[neighbors[2]])&#xA;    subIIId = mdtraj_topology.select('resid ' + str(int(residT) + 1) + dicACGT[neighbors[3]])&#xA;                             &#xA;    angIII = np.concatenate((subIIIa, subIIIb, subIIIc, subIIId))&#xA;    outputI = get_center_of_mass(traj, angI)&#xA;    outputII = get_center_of_mass(traj, angII)&#xA;    outputIII = get_center_of_mass(traj, angIII)&#xA;    return(angIII)&#xA;&#xA;    thta=[]&#xA;    for f in range(traj.n_frames):&#xA;        vec1 = np.subtract(outputI[f], outputII[f])&#xA;        vec2 = np.subtract(outputIII[f], outputII[f])&#xA;        thta.append(angle_between_vectors(vec1,vec2))&#xA;    #return(thta)&#xA;&#xA;coms = paths.MDTrajFunctionCV('theta_',&#xA;                              theta_,&#xA;                              topology = engine.topology)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The atom selection (for variables angI, andII, subIIIa, subIIIb, subIIIc, subIIId), however, varies when I check with MDTraj trajectory which gives the right selection.&lt;/p&gt;&#xA;&lt;p&gt;Selection with MDTraj trajectory&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;n = trajs[0].to_mdtraj()&#xA;theta_(n)&#xA;&#xA;array([ 43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,&#xA;        56, 107, 108, 109, 110, 111, 112, 114, 116, 120, 121, 202, 203,&#xA;       204, 205, 207, 211, 212, 213, 264, 265, 266, 267, 268, 269, 270,&#xA;       271, 272, 273, 274, 275, 276, 277])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Selection from OPS wrapper:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;coms(trajs[0])&#xA;&#xA;array([43, 44, 45, 46, 47, 48, 49, 50])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The angle calculation as a consequence fails as well when creating the CV. I think I might be missing an argument to the wrapper. How do I make the right selection?&lt;/p&gt;&#xA;" OwnerUserId="4111" LastActivityDate="2021-08-18T16:44:10.940" Title="How is the atom selection going wrong when creating the collective variable?" Tags="|python|openpathsampling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6584" PostTypeId="2" ParentId="3630" CreationDate="2021-08-18T12:50:05.120" Score="4" Body="&lt;p&gt;Unlike other properties of matter such as electrical conductivity and heat capacity, which can be defined quite precisely, flammability is more like &amp;quot;hardness&amp;quot; which is more vaguely defined (for example using &lt;a href=&quot;https://geology.com/minerals/mohs-hardness-scale.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mohs hardness scale&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The flammability of a substance may seem to be categorized rather arbitrarily, for example the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hazardous_Materials_Identification_System&quot; rel=&quot;nofollow noreferrer&quot;&gt;HMIS (Hazardous Materials Identification System)&lt;/a&gt; classifies flammability as follows:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Rating&lt;/th&gt;&#xA;&lt;th&gt;Description&lt;/th&gt;&#xA;&lt;th&gt;Examples&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;td&gt;Liquids or non-aerosols that don't burn under &amp;quot;normal&amp;quot; conditions.&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CCl4}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;Liquids or non-aerosols that will only burn above 94°C.&lt;/td&gt;&#xA;&lt;td&gt;Canola oil&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;Liquids or non-aerosols that will only burn between 38-94°C &lt;em&gt;&lt;strong&gt;*OR*&lt;/strong&gt;&lt;/em&gt; aerosols with a heat of combustion &lt;span class=&quot;math-container&quot;&gt;$\le 20$&lt;/span&gt; kJ/g.&lt;/td&gt;&#xA;&lt;td&gt;Diesel fuel&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;Liquids or non-aerosols that will only burn between 23-38°C &lt;em&gt;&lt;strong&gt;*OR*&lt;/strong&gt;&lt;/em&gt;  with a boiling point at or above 38°C and flash point below    23°C &lt;em&gt;&lt;strong&gt;*OR*&lt;/strong&gt;&lt;/em&gt; aerosols with a heat of combustion &lt;span class=&quot;math-container&quot;&gt;$\le 30$&lt;/span&gt; kJ/g but &lt;span class=&quot;math-container&quot;&gt;$\gt 20$&lt;/span&gt; kJ/g.&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C3H6O}$&lt;/span&gt; (acetone)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;Liquids or non-aerosols with a boiling point below 38°C and flash point below  23°C &lt;em&gt;&lt;strong&gt;*OR*&lt;/strong&gt;&lt;/em&gt; aerosols with a heat of combustion &lt;span class=&quot;math-container&quot;&gt;$\gt 30$&lt;/span&gt; kJ/g.&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C4H10}$&lt;/span&gt; (butane)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;So the answer depends not only on the classification system you're using to define flammability, but can also depend on other things such as &lt;em&gt;&lt;strong&gt;whether the substance is an aerosol, or a non-aerosol / liquid.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's start with aerosols since the HMIS classification of flammability is more precise in this case, since it's based on the heat of combustion (energy released during combustion, divided by the amount of it). We do need to define &amp;quot;combustion&amp;quot; though, and contrary to the aspect described in your question, which is the &amp;quot;ability to ignite fire&amp;quot;: combustion does not always result in fire. It is just a high-temperature exothermic redox reaction involving fuel and an oxidant. In fact &lt;a href=&quot;https://cameochemicals.noaa.gov/react/21&quot; rel=&quot;nofollow noreferrer&quot;&gt;alkali metals are sometimes considered to be nonflammable&lt;/a&gt; (again contrary to what you wrote in your question, but also contrary to the HMIS flammability classification, so this is a good example of the lack of standardization in these definitions) but they are combustible.&lt;/p&gt;&#xA;&lt;p&gt;You are correct though, that the oxidant &lt;em&gt;&lt;strong&gt;does not have to be oxygen,&lt;/strong&gt;&lt;/em&gt;  for example it could be chlorine (hydrogen burns in chlorine), fluorine, chlorine trifluoride, nitrous oxide, nitric acid, etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Now we've learned that determining flammability of an aerosol may be practically impossible, because there is no way to check every single possible candidate for the oxidant.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;However if we make the question more specific, for example &amp;quot;how can we computationally determine combustibility of an aerosol with in the presence of an oxygen, chlorine, nitrogen or fluorine oxidant?&amp;quot; then it becomes easier (but still difficult).&lt;/p&gt;&#xA;&lt;p&gt;You would computationally study the reaction:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\ce{Fuel + Oxidant → Products}\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for example in the case of alkali metals, which you mentioned in your question, we could have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\ce{6Li + N2 → 2Li3N}\tag{2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now all you would have to do would be to computationally calculate how much energy is released in that reaction, for which you can get a decent estimate with the help of an &lt;a href=&quot;/questions/tagged/electronic-structure&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;electronic-structure&amp;#39;&quot; rel=&quot;tag&quot;&gt;electronic-structure&lt;/a&gt; software, which will help you get estimates on the energies of each substance in the equation.&lt;/p&gt;&#xA;&lt;p&gt;For liquids or non-aerosols, the situation is more complicated and your best route might be to follow a procedure for doing a &lt;a href=&quot;/questions/tagged/molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;molecular-dynamics&lt;/a&gt; simulation such as what I described in my answers to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4772/5&quot;&gt;How to calculate the volumetric energy density of a molecule?&lt;/a&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4817/5&quot;&gt;How do I simulate the interaction between two atoms?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-18T14:41:46.100" LastActivityDate="2021-08-18T14:41:46.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6585" PostTypeId="2" ParentId="6583" CreationDate="2021-08-18T16:44:10.940" Score="6" Body="&lt;p&gt;I can't tell why you're getting that specific difference, but most likely it's related to the fact that the CV is using global variables. It's possible that something changed in those globals. OPS CVs shouldn't use global variables, and in fact, you'll get an error if you try to save a CV that uses global variables.&lt;/p&gt;&#xA;&lt;h2&gt;CVs shouldn't use globals&lt;/h2&gt;&#xA;&lt;p&gt;The &lt;code&gt;theta_&lt;/code&gt; function you give uses the global variables &lt;code&gt;mdtraj_topology&lt;/code&gt;, &lt;code&gt;residA&lt;/code&gt;, &lt;code&gt;residT&lt;/code&gt;, &lt;code&gt;dicACGT&lt;/code&gt;, and &lt;code&gt;neighbors&lt;/code&gt;. It also uses the function &lt;code&gt;get_center_of_mass&lt;/code&gt; (and, if the early return is removed, &lt;code&gt;angle_between_vectors&lt;/code&gt; ). There are all defined in global scope, and the OPS CVs don't save their global scope. If you somehow changed the values in the globals, that would explain the error. You would also get an error warning you about this if you tried to save your CV.&lt;/p&gt;&#xA;&lt;p&gt;For more background, &lt;a href=&quot;https://www.datacamp.com/community/tutorials/scope-of-variables-python&quot; rel=&quot;noreferrer&quot;&gt;here's an article on scope in Python&lt;/a&gt;. The function wrapped by an OPS CV will not know about anything defined in global scope.&lt;/p&gt;&#xA;&lt;p&gt;In general, the way to handle this is to pass these as additional variables to your &lt;code&gt;theta_&lt;/code&gt; function, and freeze them with keyword arguments when creating your CV:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def theta_(traj, mdtraj_topology, residA, residT, dicACGT, &#xA;           neighbors, get_center_of_mass, angle_between_vectors):&#xA;    ...  # fill in your stuff here&#xA;&#xA;coms = paths.MDTrajFunctionCV(&#xA;    'theta_',&#xA;    theta_,&#xA;    topology=engine.topology,&#xA;    mdtraj_topology=mdtraj_topology,&#xA;    residA=residA,&#xA;    residT=residT,&#xA;    dicACGT=dicACGT,&#xA;    neighbors=neighbors,&#xA;    get_center_of_mass=get_center_of_mass,&#xA;    angle_between_vectors=angle_between_vectors&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the specific case of atom index selection, however, it's probably better to do that outside the CV (although we'll use the same idea of passing additional parameters as keywords).&lt;/p&gt;&#xA;&lt;h2&gt;Recommended approach: Do the selection outside the CV&lt;/h2&gt;&#xA;&lt;p&gt;Right now, you're doing the selection inside the CV. In most cases, that's not what you would want. Keep in mind that a given CV instance is already tied to a specific topology, so the atom indices you select will always be the same. To handle selections from different topologies, you can create multiple CV instances that wrap the same function.&lt;/p&gt;&#xA;&lt;p&gt;So I'd recommend doing the selection &lt;em&gt;outside&lt;/em&gt; the function, before creating your CV. This avoids problems with the different globals affecting your selections, because you provide a constant selection to your CV.&lt;/p&gt;&#xA;&lt;p&gt;You could define your &lt;code&gt;theta_&lt;/code&gt; function as:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def theta_(traj, angI, angII, angIII, get_center_of_mass, angle_between_vectors):&#xA;    ...  # start after the selection&#xA;&#xA;&#xA;# fill these in, or create functions to extract them&#xA;angI = ...&#xA;angII = ...&#xA;angIII = ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This also allows you to validate the indices you selected, so you're sure you have the right selection before you start your simulation.&lt;/p&gt;&#xA;&lt;p&gt;Next you'll give &lt;code&gt;angI&lt;/code&gt;, &lt;code&gt;angII&lt;/code&gt;, and &lt;code&gt;angIII&lt;/code&gt; as parameters that you freeze when you create the CV. Note that (just as above) you'll also need to pass functions that you'll use (such as &lt;code&gt;get_center_of_mass&lt;/code&gt;) as parameters.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;coms = paths.MDTrajFunctionCV(&#xA;    'theta_',&#xA;    theta_,&#xA;    topology=engine.topology,&#xA;    angI=angI,&#xA;    angII=angII,&#xA;    angIII=angIII,&#xA;    get_center_of_mass=get_center_of_mass,&#xA;    angle_between_vectors=angle_between_vectors&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-08-18T16:44:10.940" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6587" PostTypeId="1" CreationDate="2021-08-19T11:24:52.120" Score="2" ViewCount="49" Body="&lt;p&gt;Is there a way to work out the geometries for the  &lt;span class=&quot;math-container&quot;&gt;$\ce{UO_x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{WO_x}$&lt;/span&gt; species for (&lt;span class=&quot;math-container&quot;&gt;$x=1-3$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I know that deducing the multiplicity (the number of unpaired electrons) in d and f block containing molecules &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6470/how-to-find-out-the-multiplicities-of-molecules-containing-d-and-f-block-species&quot;&gt;is difficult&lt;/a&gt; however I believe that the multiplicity can directly affect the geometry of molecules. So I was wondering how can one deduce the geometry of such molecules if they can't determine the multiplicity.&lt;/p&gt;&#xA;&lt;p&gt;Also, if anyone has any sources concerning the multiplicities/ geometries (or ideally both) for &lt;span class=&quot;math-container&quot;&gt;$\ce{UO_x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{WO_x}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$x=1-3$&lt;/span&gt;),&#xA;I would greatly appreciate it if they could provide me with them.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-08-19T19:35:46.783" LastActivityDate="2021-08-19T19:53:44.630" Title="Determining the geometry of UOx and WOx for (x=1-3)" Tags="|molecular-modeling|geometry-optimization|transition-metals|geometry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6588" PostTypeId="1" CreationDate="2021-08-19T14:07:03.713" Score="4" ViewCount="264" Body="&lt;p&gt;I have a beta Ti (Space Group 229) structure with 16 atoms, I prepared 15 disordered TiNb structures with 5 atoms of Nb. I did it using &lt;code&gt;VASPKIT&lt;/code&gt;. However, before the geometry optimization, I found out that the symmetry of all multicomponent structures was decreased to monoclinic. Is it ok?&lt;/p&gt;&#xA;&lt;p&gt;Moreover, what is better to do the relaxation in &lt;code&gt;VASP&lt;/code&gt;, using &lt;code&gt;ISIF=2&lt;/code&gt;? If the symmetry was decreased how may I calculate the correct elastic constants for my cubic TiNb structure? I am a bit confused.&lt;/p&gt;&#xA;&lt;p&gt;This is my &lt;code&gt;POSCAR&lt;/code&gt; file for pure Ti&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   1.00000000000000     &#xA;     6.6399998665000002    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    6.6399998665000002    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    6.6399998665000002&#xA;   Ti&#xA;    16&#xA;Direct&#xA;  0.0000000000000000  0.0000000000000000  0.0000000000000000&#xA;  0.0000000000000000  0.0000000000000000  0.5000000000000000&#xA;  0.0000000000000000  0.5000000000000000  0.0000000000000000&#xA;  0.0000000000000000  0.5000000000000000  0.5000000000000000&#xA;  0.5000000000000000  0.0000000000000000  0.0000000000000000&#xA;  0.5000000000000000  0.0000000000000000  0.5000000000000000&#xA;  0.5000000000000000  0.5000000000000000  0.0000000000000000&#xA;  0.5000000000000000  0.5000000000000000  0.5000000000000000&#xA;  0.2500000000000000  0.2500000000000000  0.2500000000000000&#xA;  0.2500000000000000  0.2500000000000000  0.7500000000000000&#xA;  0.2500000000000000  0.7500000000000000  0.2500000000000000&#xA;  0.2500000000000000  0.7500000000000000  0.7500000000000000&#xA;  0.7500000000000000  0.2500000000000000  0.2500000000000000&#xA;  0.7500000000000000  0.2500000000000000  0.7500000000000000&#xA;  0.7500000000000000  0.7500000000000000  0.2500000000000000&#xA;  0.7500000000000000  0.7500000000000000  0.7500000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is one of the substituted Ti with Nb &lt;code&gt;POSCAR&lt;/code&gt; prepared by VASPKIT&#xA;This file is generated by &lt;code&gt;VASPKIT&lt;/code&gt; code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   6.6399998665000002    0.0000000000000000    0.0000000000000000&#xA;   0.0000000000000000    6.6399998665000002    0.0000000000000000&#xA;   0.0000000000000000    0.0000000000000000    6.6399998665000002&#xA;  Nb   Ti&#xA;    5    11&#xA;Direct&#xA;   0.0000000000000000    0.5000000000000000    0.0000000000000000&#xA;   0.5000000000000000    0.5000000000000000    0.0000000000000000&#xA;   0.2500000000000000    0.2500000000000000    0.2500000000000000&#xA;   0.2500000000000000    0.2500000000000000    0.7500000000000000&#xA;   0.7500000000000000    0.2500000000000000    0.7500000000000000&#xA;   0.0000000000000000    0.0000000000000000    0.0000000000000000&#xA;   0.0000000000000000    0.0000000000000000    0.5000000000000000&#xA;   0.0000000000000000    0.5000000000000000    0.5000000000000000&#xA;   0.5000000000000000    0.0000000000000000    0.0000000000000000&#xA;   0.5000000000000000    0.0000000000000000    0.5000000000000000&#xA;   0.5000000000000000    0.5000000000000000    0.5000000000000000&#xA;   0.2500000000000000    0.7500000000000000    0.2500000000000000&#xA;   0.2500000000000000    0.7500000000000000    0.7500000000000000&#xA;   0.7500000000000000    0.2500000000000000    0.2500000000000000&#xA;   0.7500000000000000    0.7500000000000000    0.2500000000000000&#xA;   0.7500000000000000    0.7500000000000000    0.7500000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3486" LastEditorUserId="1179" LastEditDate="2021-08-20T18:08:31.350" LastActivityDate="2021-08-21T13:46:15.663" Title="How to do a proper relaxation of the multicomponent structure?" Tags="|vasp|geometry-optimization|symmetry|alloys|elasticity|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6589" PostTypeId="1" AcceptedAnswerId="6591" CreationDate="2021-08-19T15:54:28.673" Score="11" ViewCount="859" Body="&lt;p&gt;Based on some of my previous reading and questions that I have asked I am aware that determining the ground state electronic configuration for molecules containing d-block elements theoretically is difficult. The method that is usually suggested is to calculate many energies of the molecule, each time assuming a different spin multiplicity, until all possible candidates have been considered before picking the one that has the lowest energy.&lt;/p&gt;&#xA;&lt;p&gt;I was just wondering what are some of the theoretical difficulties encountered when trying to deduce the ground state electronic configuration using this method specifically when dealing with&#xA;d block element containing molecules and what extra difficulties are encountered when trying to deal with the f block elements.&lt;/p&gt;&#xA;" OwnerUserId="2106" LastEditorUserId="5" LastEditDate="2021-08-19T20:29:25.963" LastActivityDate="2021-08-19T20:29:25.963" Title="Why is it so hard to find the ground state of molecules with d-block or f-block elements?" Tags="|electronic-structure|transition-metals|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6590" PostTypeId="2" ParentId="6589" CreationDate="2021-08-19T16:42:00.200" Score="5" Body="&lt;p&gt;Very briefly, in many cases d- and f- orbitals are (quasi)degenerate. So to accurately calculate energies we need to take into account all permutations of electrons over those orbitals (multireference calculations).&lt;/p&gt;&#xA;&lt;p&gt;If you want to know more there is a nice &lt;a href=&quot;https://www.researchgate.net/publication/317106028_CASSCF_and_Firefly_A_tutorial&quot; rel=&quot;noreferrer&quot;&gt;tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1432" LastActivityDate="2021-08-19T16:42:00.200" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6591" PostTypeId="2" ParentId="6589" CreationDate="2021-08-19T19:34:38.760" Score="9" Body="&lt;p&gt;&lt;em&gt;&lt;strong&gt;Difficulty in capturing enough electron correlation:&lt;/strong&gt;&lt;/em&gt; The difference between the lowest states belonging to different electronic configurations can be small (for example, on the order of 1 kcal/mol). Traditional methods for full configuration interaction (FCI) calculations such as the &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6563/5&quot;&gt;Davidson method&lt;/a&gt; are unable to be used in any remotely accurate basis set for a molecule beyond a handful of electrons, but d-block elements have far more than a handful of electrons.&lt;/p&gt;&#xA;&lt;p&gt;Take scandium for example, which is the first d-block element. Even if you freeze the neon core, there's 11 electrons. You are asking about molecules, so we must at least have a hydrogen attached to the scandium, so now we have 12 electrons to correlate. Even if we use the cc-pVDZ basis set (which is often not enough to get 1 kcal/mol accuracy in the difference between two electronic ground state energies), we would have 48 spatial orbitals. How many ways can you put 6 spin-up electrons and 6 spin-down electrons into 48 spatial orbitals without imposing any spatial symmetry restrictions? The answer is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;{48\choose6}^2 \approx 1.5  \times 10^{14}. \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If each FCI coefficient were to be represented using double-precision arithmetic (8 bytes), you would need more than 1 petabyte to store all coefficients, and even taking advantage of sparsity won't help you get to size where traditional FCI methods will be convenient. More recently developed methods such as &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0005754&quot; rel=&quot;noreferrer&quot;&gt;FCIQMC&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5063376&quot; rel=&quot;noreferrer&quot;&gt;SHCI and DMRG&lt;/a&gt; would be able to treat systems with &lt;span class=&quot;math-container&quot;&gt;$10^{14}$&lt;/span&gt; FCI coefficients fairly well, but these methods are less black-box and have a bit more of a learning curve in order to understand how to determine that the calculations are properly converged. Furthermore, if you switch scandium with an element that has only 3 more electrons (chromium), and you switch hydrogen with an element that has only 2 more electrons (lithium, whose cc-pVDZ basis set is bigger than it is for hydrogen) the calculation in Eq. 1 becomes:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;{63\choose9}{63\choose8} \approx 2  \times 10^{18}. \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;The calculation just became more then 10000 times bigger simply by switching scandium to an element 3 electrons larger and hydrogen to an element 2 electrons larger!&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, molecules containing d-block elements tend to have several FCI determinants which are nearly equal in importance, meaning that either FCI or multi-reference methods are required, as opposed to the highly efficient single-reference methods like those based on a coupled cluster model (this is what &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6590/5&quot;&gt;Roma's answer says&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h3&gt;Extra difficulties when involving f-block elements&lt;/h3&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Relativistic effects:&lt;/strong&gt;&lt;/em&gt; The heavier the elements involved, the more that relativistic effects become important, which means that you need to know a bit more in order to know how to do the calculations properly. Furthermore, spin-orbit coupling starts to become more and more important, and this will make calculations more expensive, and will reduce the number of computer programs available for you to do the calculations (since not all electronic structure software packages have all methods implemented for the highly relativistic cases).&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Even more electrons:&lt;/strong&gt;&lt;/em&gt; If you thought that the examples in Eqs. 1 and 2 were hard, then just imagine &lt;span class=&quot;math-container&quot;&gt;$\ce{LaH}$&lt;/span&gt; which involves the first f-block element and the lightest element in the periodic table. The cc-pVDZ-X2C basis set has 84 spatial orbitals and even with the krypton core frozen, you would have 21 electrons from the lanthaninum  and 1 from the hydrogen, which means Eq 1 becomes 100000000 (10 million) times larger:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;{89\choose11}{89\choose10} \approx 2  \times 10^{26}. \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Lack of basis set choices available:&lt;/strong&gt;&lt;/em&gt; Basis set choices are far more limited for the f-block elements compared to the smaller elements in the periodic table. This has improved a bit in recent years, but there is still some more progress to be made in this direction. You may need to optimize your own basis sets, or to resort to using pseudopotentials (which can be considered under the list of extra things you'd have to learn in order to do relativistic calculations).&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Lack of programs that can treat basis sets with k-type orbitals:&lt;/strong&gt;&lt;/em&gt; Most electronic structure software does not allow you to do post-HF calculations with k-type orbitals in the basis set, so you wouldn't be able to use a 5Z basis set on uranium, for example, in &lt;a href=&quot;/questions/tagged/molpro&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molpro&amp;#39;&quot; rel=&quot;tag&quot;&gt;molpro&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/orca&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;orca&amp;#39;&quot; rel=&quot;tag&quot;&gt;orca&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/gamess&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gamess&amp;#39;&quot; rel=&quot;tag&quot;&gt;gamess&lt;/a&gt;, the public release of &lt;a href=&quot;/questions/tagged/cfour&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; rel=&quot;tag&quot;&gt;cfour&lt;/a&gt;, or the publicly purchasable version of &lt;a href=&quot;/questions/tagged/gaussian&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gaussian&amp;#39;&quot; rel=&quot;tag&quot;&gt;gaussian&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-19T19:34:38.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6592" PostTypeId="2" ParentId="6587" CreationDate="2021-08-19T19:53:44.630" Score="1" Body="&lt;p&gt;You are correct that the optimum geometry for one spin multiplicity will in general be different for another spin multiplicity. Therefore if you want to know the geometry of the lowest-energy state of a molecule, a pre-requisite is to first know the electronic configuration (spin multiplicity and spatial configuration) of the lowest-energy state of the molecule, then optimize the geometry of the molecule in that specific electronic state. &lt;em&gt;&lt;strong&gt;Since you don't know what the lowest-energy state of the molecule is, you might want to do a geometry optimization for all states.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Perhaps you were hoping that you could optimize the geometry at any multiplicity and deduce the geometry of the lowest-energy state based on that, but this is not correct at all. Even for a diatomic molecule (in this case &lt;span class=&quot;math-container&quot;&gt;$\ce{Na2}$&lt;/span&gt;, with the figure being from &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.78.483&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;), the lowest &lt;span class=&quot;math-container&quot;&gt;$^3 \Sigma_g$&lt;/span&gt; state has a potential energy minimum at least 1 Bohr larger than the potential energy minimum for the lowest &lt;span class=&quot;math-container&quot;&gt;$^1 \Sigma_g$&lt;/span&gt; state.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KYUhF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KYUhF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This type of difference is even worse in some cases, though much milder in other cases, but in any case, even a 0.5 Bohr difference in an equilibrium bond length of a diatomic can be considered enormous.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-19T19:53:44.630" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6593" PostTypeId="2" ParentId="6589" CreationDate="2021-08-19T20:10:46.880" Score="6" Body="&lt;h2&gt;d-block&lt;/h2&gt;&#xA;&lt;p&gt;The extra difficulty of studying a d-block element/transition metal complex is that the &amp;quot;breaking of degeneracies of electron orbital states&amp;quot; can result in different stable configurations depending on the geometry and symmetry of the molecule. This is the simple linear combination of atomic orbitals (LCAO) picture, or if you want more details see &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;noreferrer&quot;&gt;Crystal Field Theory&lt;/a&gt;. Furthermore, because of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Aufbau_principle&quot; rel=&quot;noreferrer&quot;&gt;Aufbau Principle&lt;/a&gt; we fill these orbitals one electron at a time, we can end up with different electronic spin multiplicity.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, as you said in your question, for d-block complexes you need to check different spins (and geometries).&lt;/p&gt;&#xA;&lt;p&gt;The question is why? Why do similar complexes in the same column of the periodic table adopt different spins and geometries? For example, the molecule  &lt;span class=&quot;math-container&quot;&gt;$\ce{[PdCl4]2−}$&lt;/span&gt; is diamagnetic, which indicates a square planar geometry as all eight d-electrons are paired in the lower-energy orbitals. However,  &lt;span class=&quot;math-container&quot;&gt;$\ce{[NiCl4]2−}$&lt;/span&gt; is also d8 but has two unpaired electrons, indicating a tetrahedral geometry. The answer to this question is the subject of &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystal_field_theory&quot; rel=&quot;noreferrer&quot;&gt;Crystal Field Theory&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Any theory that does not properly allow for an open-shell solution is no good (e.g. RHF). You must at the minimum allow for unrestricted calculations. Furthermore, you should allow for a multi-reference solution (for more details see Nike's answer in this thread) since these electronic states can be quite close together and can actually interconvert in what is known as a Jahn-Teller distortion.&lt;/p&gt;&#xA;&lt;h2&gt;f-block&lt;/h2&gt;&#xA;&lt;p&gt;Finally, f-block elements are much different and pose a far greater challenge. Unlike in d-block where the molecular orbitals are split first and then those orbitals can be further split by a magnetic field into different levels, for f-block elements the levels are first split by spin-orbit coupling and then by crystal field splitting. It's very different.&lt;/p&gt;&#xA;&lt;p&gt;For these you need a theory that correctly describes spin-orbit coupling. The exact solution requires relativistic treatment.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="52" LastEditDate="2021-08-19T20:17:34.843" LastActivityDate="2021-08-19T20:17:34.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6594" PostTypeId="1" CreationDate="2021-08-19T19:17:18.197" Score="6" ViewCount="571" Body="&lt;p&gt;I'm new in the field of QM methods and I've run into a problem for which I can't find a solution online.&lt;/p&gt;&#xA;&lt;p&gt;I have tried with different basis sets, I've raised the maximum number of iterations and number of steps, changed the gradient convergence criteria, mixed up coordinates of atoms, tried different optimization methods, etc. Nothing worked.&lt;/p&gt;&#xA;&lt;p&gt;I've previously minimized the structure using UFF and MMFF94s in Avogadro.&lt;/p&gt;&#xA;&lt;p&gt;I'll paste the input text. Any help would be appreciated!&lt;/p&gt;&#xA;&lt;p&gt;File created by the GAMESS Input Deck Generator Plugin for Avogadro:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=STO NGAUSS=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE MULT=1 ICHARG=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT OPTTOL=0.0005 NSTEP=200 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM TIMLIM=525600 MEMORY=30000000 PARALL=.TRUE. $&lt;/span&gt;END&#xA; &#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;C     6.0     0.44525    -3.16984     0.69612&#xA;C     6.0     1.01573    -4.03321     1.61274&#xA;C     6.0     2.41072    -3.80725     1.61097&#xA;C     6.0     2.67608    -2.82362     0.67533&#xA;N     7.0     1.45795    -2.36971     0.21750&#xA;C     6.0     3.90546    -2.34686     0.10991&#xA;C     6.0     4.05712    -1.04579    -0.23679&#xA;C     6.0     5.21540    -0.44191    -0.85574&#xA;C     6.0     5.05403     0.87344    -0.99275&#xA;C     6.0     3.70858     1.06810    -0.43356&#xA;N     7.0     3.13224    -0.03282    -0.03960&#xA;C     6.0     3.16875     2.46275    -0.34431&#xA;C     6.0     1.83356     2.65144    -0.33629&#xA;C     6.0     1.15168     3.94223    -0.27795&#xA;C     6.0    -0.17973     3.74202    -0.29816&#xA;C     6.0    -0.44459     2.30513    -0.36740&#xA;N     7.0     0.80858     1.73703    -0.38199&#xA;C     6.0    -1.66025     1.72152    -0.50118&#xA;C     6.0    -1.74252     0.22603    -0.45510&#xA;C     6.0    -2.99115    -0.38252    -0.93654&#xA;C     6.0    -2.74372    -1.67799    -0.75080&#xA;C     6.0    -1.41952    -1.88040    -0.19917&#xA;N     7.0    -0.83234    -0.62964    -0.07998&#xA;C     6.0    -0.88336    -3.06808     0.16991&#xA;H     1.0     0.48692    -4.78481     2.18676&#xA;H     1.0     3.14281    -4.35524     2.19072&#xA;H     1.0     1.32408    -1.59926    -0.42603&#xA;H     1.0     6.09460    -0.97630    -1.18243&#xA;H     1.0     5.71915     1.59050    -1.43500&#xA;H     1.0     1.62190     4.91198    -0.23985&#xA;H     1.0    -0.91995     4.52597    -0.27506&#xA;H     1.0     0.95387     0.73081    -0.31926&#xA;H     1.0    -3.86702     0.07728    -1.35203&#xA;H     1.0    -3.43575    -2.47239    -0.99291&#xA;C     6.0     5.01165    -3.32684    -0.09860&#xA;C     6.0     4.80323    -4.43424    -0.92915&#xA;C     6.0     6.92926    -5.30155    -0.40954&#xA;C     6.0     6.21677    -3.24050     0.60124&#xA;C     6.0     7.18305    -4.22849     0.43747&#xA;C     6.0     5.48783    -6.55588    -1.93242&#xA;N     7.0     5.75586    -5.38564    -1.07564&#xA;H     1.0     6.43367    -6.93986    -2.32293&#xA;H     1.0     4.85110    -6.24747    -2.76568&#xA;H     1.0     4.98761    -7.30560    -1.31455&#xA;C     6.0     4.09828     3.60885    -0.24634&#xA;C     6.0     4.66088     3.95246     0.98833&#xA;C     6.0     4.41857     4.37817    -1.36593&#xA;C     6.0     5.28427     5.45895    -1.23237&#xA;N     7.0     5.50715     5.00575     1.09501&#xA;C     6.0     5.81916     5.75962     0.01557&#xA;C     6.0    -2.90380     2.52166    -0.34897&#xA;C     6.0    -3.66129     2.56849     0.82733&#xA;N     7.0    -4.81632     3.27544     0.88045&#xA;C     6.0    -5.27208     3.94587    -0.20273&#xA;C     6.0    -3.36321     3.21702    -1.46861&#xA;C     6.0    -4.55383     3.93261    -1.39330&#xA;C     6.0    -5.60984     3.29056     2.12518&#xA;H     1.0    -6.11974     4.25361     2.21048&#xA;H     1.0    -4.94027     3.15848     2.97883&#xA;H     1.0    -6.32923     2.47041     2.06314&#xA;C     6.0    -1.71894    -4.29132     0.03909&#xA;C     6.0    -1.71807    -5.02753    -1.14744&#xA;C     6.0    -2.51092    -6.17434    -1.26052&#xA;C     6.0    -3.31052    -6.61750    -0.19482&#xA;C     6.0    -3.30480    -5.87783     0.98628&#xA;C     6.0    -2.51580    -4.72439     1.10405&#xA;N     7.0    -4.05948    -7.78149    -0.43353&#xA;C     6.0    -4.89310    -8.55874     0.31080&#xA;C     6.0    -5.16776    -8.28274     1.75727&#xA;H     1.0    -4.23558    -8.26628     2.32654&#xA;H     1.0    -5.79022    -9.08611     2.16452&#xA;H     1.0    -5.71925    -7.34591     1.86399&#xA;O     8.0    -5.42168    -9.52251    -0.25008&#xA;C     6.0     6.07588     5.36035     2.41047&#xA;H     1.0     5.41546     6.10513     2.86119&#xA;H     1.0     7.08124     5.76404     2.26527&#xA;H     1.0     6.13218     4.46273     3.03142&#xA;H     1.0    -3.99409    -8.17283    -1.36812&#xA;H     1.0     3.86903    -4.58358    -1.46487&#xA;H     1.0     8.12201    -4.17578     0.98576&#xA;H     1.0     7.65002    -6.10332    -0.54924&#xA;H     1.0     6.39871    -2.42357     1.29876&#xA;H     1.0     4.43770     3.40075     1.89831&#xA;H     1.0     5.53797     6.07004    -2.09755&#xA;H     1.0     6.49265     6.60082     0.16210&#xA;H     1.0     3.99352     4.14840    -2.34365&#xA;H     1.0    -3.36137     2.04034     1.72923&#xA;H     1.0    -6.21197     4.48444    -0.10738&#xA;H     1.0    -4.92606     4.47294    -2.26256&#xA;H     1.0    -2.80635     3.19914    -2.40612&#xA;H     1.0    -2.52664    -4.17043     2.04095&#xA;H     1.0    -1.10653    -4.71768    -1.99108&#xA;H     1.0    -2.49054    -6.72496    -2.19955&#xA;H     1.0    -3.89964    -6.14606     1.84813&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here's the part of my output file that is SCF-related:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;          --------------------------&#xA;                 RHF SCF CALCULATION&#xA;          --------------------------&#xA;&#xA;     NUCLEAR ENERGY =      6789.1338849966&#xA;     MAXIT =   30     NPUNCH=    2&#xA;     EXTRAP=T  DAMP=F  SHIFT=F  RSTRCT=F  DIIS=F  DEM=F  SOSCF=T&#xA;     DENSITY MATRIX CONV=  1.00E-05&#xA;     SOSCF WILL OPTIMIZE   23688 ORBITAL ROTATIONS, SOGTOL=   0.250&#xA;     MEMORY REQUIRED FOR RHF ITERS=    819320 WORDS.&#xA;&#xA; ITER EX DEM     TOTAL ENERGY        E CHANGE  DENSITY CHANGE     ORB. GRAD&#xA;   1  0  0    -2243.0902254864 -2243.0902254864   0.641974797   0.000000000&#xA;          ---------------START SECOND ORDER SCF---------------&#xA;   2  1  0    -2246.0402678439    -2.9500423574   0.296673768   0.098393134&#xA;   3  2  0    -2246.1780346977    -0.1377668539   0.918798210   0.089555764&#xA;   4  3  0    -2241.9109382429     4.2670964549   0.915303672   0.282318567&#xA;   5  4  0    -2246.1174690545    -4.2065308116   0.604249079   0.121159545&#xA;   6  5  0    -2246.0432278272     0.0742412273   0.579402296   0.238306637&#xA;   7  6  0    -2246.2092437253    -0.1660158981   0.609110594   0.117220258&#xA;   8  7  0    -2245.4738991800     0.7353445453   0.785785223   0.390438537&#xA;   9  8  0    -2245.8285426085    -0.3546434285   0.475649688   0.134490303&#xA;  10  9  0    -2246.1021152737    -0.2735726652   0.587216948   0.144268895&#xA;  11 10  0    -2245.0340885624     1.0680267113   0.657495276   0.408934150&#xA;  12 11  0    -2246.1749635724    -1.1408750100   0.231319789   0.081220026&#xA;  13 12  0    -2246.2480160025    -0.0730524302   0.204610410   0.066506475&#xA;  14 13  0    -2246.2658401926    -0.0178241901   0.172142881   0.079471677&#xA;  15 14  0    -2246.2873580939    -0.0215179013   0.161126202   0.059525949&#xA;  16 15  0    -2246.3210293981    -0.0336713042   0.056114250   0.022848617&#xA;  17 16  0    -2246.3305780028    -0.0095486047   0.041231998   0.012283754&#xA;  18 17  0    -2246.3305121964     0.0000658064   0.021626233   0.014104884&#xA;  19 18  0    -2246.3330591814    -0.0025469850   0.015124765   0.004783815&#xA;  20 19  0    -2246.3332910450    -0.0002318636   0.010371230   0.003217253&#xA;  21 20  0    -2246.3334251468    -0.0001341018   0.007962098   0.002766804&#xA;  22 21  0    -2246.3335199835    -0.0000948366   0.005375285   0.001779536&#xA;  23 22  0    -2246.3335639378    -0.0000439543   0.003552000   0.000853716&#xA;  24 23  0    -2246.3335616981     0.0000022397   0.002276108   0.001140585&#xA;  25 24  0    -2246.3335762709    -0.0000145729   0.000648266   0.000186249&#xA;  26 25  0    -2246.3335762326     0.0000000384   0.000442354   0.000284347&#xA;  27 26  0    -2246.3335769845    -0.0000007519   0.000249739   0.000058733&#xA;  28 27  0    -2246.3335769710     0.0000000135   0.000146064   0.000083809&#xA;  29 28  0    -2246.3335770730    -0.0000001019   0.000094133   0.000024011&#xA;  30 29  0    -2246.3335770721     0.0000000008   0.000046691   0.000031845&#xA;&#xA; SCF IS UNCONVERGED, TOO MANY ITERATIONS&#xA;     TIME TO FORM FOCK OPERATORS=       1.4 SECONDS (       0.0 SEC/ITER)&#xA;     TIME TO SOLVE SCF EQUATIONS=       0.4 SECONDS (       0.0 SEC/ITER)&#xA;&#xA; FINAL RHF ENERGY IS        0.0000000000 AFTER  30 ITERATIONS&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user115080" LastEditorUserId="7" LastEditDate="2021-08-20T13:42:36.160" LastActivityDate="2021-08-27T15:10:36.613" Title="SCF not converging during RHF/STO-3G geometry optimisation" Tags="|quantum-chemistry|geometry-optimization|self-consistent-field|gamess|semi-empirical-method|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6595" PostTypeId="1" CreationDate="2021-08-20T11:41:29.103" Score="5" ViewCount="246" Body="&lt;p&gt;I followed the steps mentioned in the answer of question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4269/how-to-carry-out-hse06soc-band-structure-calculation-using-vasp&quot;&gt;How to carry out HSE06+SOC band structure calculation using VASP&lt;/a&gt;&#xA;but I found a zigzag band structure. Any idea how to remove false k-points in VASP files directly, because I need projected band structure to plot?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4WV3i.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4WV3i.png&quot; alt=&quot;HSE DOS and Band structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4169" LastEditorUserId="7" LastEditDate="2021-08-24T15:44:50.527" LastActivityDate="2021-08-24T15:44:50.527" Title="HSE06+SOC calculation in VASP: How to remove false k-points?" Tags="|density-functional-theory|vasp|band-structure|spin-orbit-coupling|hse06|" AnswerCount="0" CommentCount="8" ClosedDate="2021-12-02T17:20:36.137" ContentLicense="CC BY-SA 4.0" />
  <row Id="6597" PostTypeId="2" ParentId="6588" CreationDate="2021-08-20T15:00:10.440" Score="4" Body="&lt;p&gt;A few things:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;If you start with your supercell of pure bcc Ti, the spacegroup symmetry will be Im-3m, as expected. As soon as you replace one or a few atoms of Ti with Nb, or any different species, you are breaking symmetries and the symmetry will be lowered. &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2017.10.016&quot; rel=&quot;nofollow noreferrer&quot;&gt;Marker &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; computed elastic properties for bcc Ti-X (X=Mo,&lt;strong&gt;Nb&lt;/strong&gt;,Ta,Zr,Sn) and handled the lower symmetry of the special quasirandom structures (SQS) that they used by a Voigt-Reuss-Hill approach.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;bcc Ti is not stable at 0K (it has imaginary phonon modes). I would expect the symmetry of bcc will break if you relax it. Whether that's okay for you depends on what you are trying to study, but you may not be studying the bcc structure that you intend.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This is not typically the way you model a random alloy, if that is your goal. Some recent work from &lt;a href=&quot;https://doi.org/10.1016/j.actamat.2020.01.056&quot; rel=&quot;nofollow noreferrer&quot;&gt;Skripnyak &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; has some nice calculations for bcc Ti-V alloys. Ti-V should be similar to your Ti-Nb and you can see both the effect of bcc Ti instability and a few different methods for calculating energies for random alloys.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="1179" LastEditDate="2021-08-21T13:46:15.663" LastActivityDate="2021-08-21T13:46:15.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6598" PostTypeId="1" CreationDate="2021-08-20T16:01:46.003" Score="6" ViewCount="253" Body="&lt;p&gt;I'm trying to run lammps for a system subject to a custom short-range potential, that I have in a table, as well as the lammps lj/cut/dipole/long interaction (with LJ epsilon set to 0 because I do not want its contribution) with ewald summation. I need to provide a kspace_style for this in the input script, but I always get the error:&lt;/p&gt;&#xA;&lt;p&gt;ERROR: KSpace style is incompatible with Pair style (src/kspace.cpp:201)&lt;/p&gt;&#xA;&lt;p&gt;I tried ewald, ewald/dipole and ewald/disp, same error. I am using lammps-29Oct20.&lt;/p&gt;&#xA;&lt;p&gt;I want to know if I need to add some tags or something to the hybrid/overlay command. I tried just the dipole interaction with the ewald/dipole kspace style, and it did not produce this error, so I figure it's to do with either the table or the hybrid/overlay pair styles.&lt;/p&gt;&#xA;&lt;p&gt;Here is my input script. Any input would be appreciated.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;variable t index 50&#xA;units    lj&#xA;atom_style      hybrid dipole sphere&#xA;&#xA;region          box1 block 0 5 0 5 0 5&#xA;create_box      2 box1&#xA;lattice         fcc 1.0&#xA;create_atoms    1 box&#xA;&#xA;&#xA;timestep         0.001000&#xA;&#xA;set     group all charge 0.0&#xA;set     group all dipole 0.0 0.0 1.0&#xA;&#xA;&#xA;mass     1 1.0&#xA;pair_style       hybrid/overlay table spline 11000 ewald lj/long/dipole/long cut long 0 5&#xA;&#xA;pair_coeff       * * lj/long/dipole/long 0.0 1.0&#xA;&#xA;pair_coeff       * * table colloid.table colloid 2.5&#xA;&#xA;kspace_style     ewald/dipole 1.0E-5&#xA;&#xA;neighbor         0.3 bin&#xA;neigh_modify     delay 0 every 100 check no&#xA;&#xA;&#xA;#OUTPUT&#xA;dump     lmptest.xyz all xyz 50 lmptest.xyz&#xA;fix      1 all nvt temp 1.000000 1.000000 10&#xA;thermo   1&#xA;thermo_style     custom elapsed pe ke etotal press temp&#xA;run      $t&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4173" LastActivityDate="2021-08-20T18:43:21.987" Title="KSpace style for hybrid/overlay table and dipole?" Tags="|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6599" PostTypeId="2" ParentId="6598" CreationDate="2021-08-20T18:43:21.987" Score="4" Body="&lt;p&gt;Answer here from Axel Kohlmeyer of LAMMPS&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://matsci.org/t/kspace-style-for-hybrid-overlay-table-and-dipole/37966/3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://matsci.org/t/kspace-style-for-hybrid-overlay-table-and-dipole/37966/3&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4173" LastActivityDate="2021-08-20T18:43:21.987" CommentCount="0" CommunityOwnedDate="2021-08-20T19:18:42.923" ContentLicense="CC BY-SA 4.0" />
  <row Id="6600" PostTypeId="2" ParentId="6594" CreationDate="2021-08-21T17:00:22.517" Score="5" Body="&lt;p&gt;If you look at your last five iterations, you will see that the &lt;em&gt;&lt;strong&gt;density change&lt;/strong&gt;&lt;/em&gt; (which is what matters most for SCF convergence) is getting smaller in each iteration, meaning that the calculation is still converging, and will converge if you give it more iterations:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Iteration&lt;/th&gt;&#xA;&lt;th&gt;SCF Energy&lt;/th&gt;&#xA;&lt;th&gt;Energy change&lt;/th&gt;&#xA;&lt;th&gt;Density Change&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;26&lt;/td&gt;&#xA;&lt;td&gt;-2246.3335762326&lt;/td&gt;&#xA;&lt;td&gt;0.0000000384&lt;/td&gt;&#xA;&lt;td&gt;0.000&lt;em&gt;&lt;strong&gt;442354&lt;/strong&gt;&lt;/em&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;27&lt;/td&gt;&#xA;&lt;td&gt;-2246.3335769845&lt;/td&gt;&#xA;&lt;td&gt;-0.0000007519&lt;/td&gt;&#xA;&lt;td&gt;0.000&lt;em&gt;&lt;strong&gt;249739&lt;/strong&gt;&lt;/em&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;28&lt;/td&gt;&#xA;&lt;td&gt;-2246.3335769710&lt;/td&gt;&#xA;&lt;td&gt;0.0000000135&lt;/td&gt;&#xA;&lt;td&gt;0.000&lt;em&gt;&lt;strong&gt;146064&lt;/strong&gt;&lt;/em&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;29&lt;/td&gt;&#xA;&lt;td&gt;-2246.3335770730&lt;/td&gt;&#xA;&lt;td&gt;-0.0000001019&lt;/td&gt;&#xA;&lt;td&gt;0.000&lt;em&gt;&lt;strong&gt;094133&lt;/strong&gt;&lt;/em&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;30&lt;/td&gt;&#xA;&lt;td&gt;-2246.3335770721&lt;/td&gt;&#xA;&lt;td&gt;0.0000000008&lt;/td&gt;&#xA;&lt;td&gt;0.000&lt;em&gt;&lt;strong&gt;046691&lt;/strong&gt;&lt;/em&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;You just have to increase the maximum number of iterations beyond the &lt;a href=&quot;http://classic.chem.msu.su/cgi-bin/ceilidh.exe/gran/gamess/forum/?C35ed6a13fby4-8924-1129+00.htm&quot; rel=&quot;noreferrer&quot;&gt;default value of 30&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-21T17:00:22.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6601" PostTypeId="1" AcceptedAnswerId="6602" CreationDate="2021-08-22T06:31:12.720" Score="6" ViewCount="252" Body="&lt;p&gt;I did an optimization for a monolayer with GGA (550 eV ecut, 12 12 1 k-mesh) with ISIF=3 and IBRION=2.&lt;/p&gt;&#xA;&lt;p&gt;My original POSCAR was:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;5.2916193008         0.0000000000         0.0000000000&#xA;0.0000000000         5.2916193008         0.0000000000&#xA;0.0000000000         0.0000000000        20.0097122192&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After optimization, my CONTACR is this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 5.2753749526661906    0.0000000006352637    0.0000000700426255&#xA;-0.0000000006164817    5.2753749536648096   -0.0000000640637957&#xA; 0.0000002625200859   -0.0000002421078825   19.9912853387061134&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can see my lattice vectors (off-diagonal) has some non-zero values now and vacuum size is reduced a bit.&lt;/p&gt;&#xA;&lt;p&gt;Do you think my CONTCAR is okay for further calculations, or should I worry about that?&lt;/p&gt;&#xA;&lt;p&gt;NOTE: I did not fix any axis for the optimization.&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="697" LastEditDate="2021-08-23T01:28:55.557" LastActivityDate="2021-08-23T01:28:55.557" Title="Lattice vectors are misaligned and vacuum size is reduced, was my calculation successful" Tags="|vasp|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6602" PostTypeId="2" ParentId="6601" CreationDate="2021-08-22T06:36:00.143" Score="6" Body="&lt;p&gt;You used &lt;code&gt;ISIF = 3&lt;/code&gt;, which tells VASP you want to relax the atomic positions and the cell shape/volume. It looks like the cell shape/volume has changed slightly during the relaxation process, as you noted. Based on this information, the input lattice constants yield a structure with higher energy than those in the converged CONTCAR. It seems like VASP is doing precisely what you asked it to do.&lt;/p&gt;&#xA;&lt;p&gt;On a related note, if you have a monolayer with lots of vacuum in the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;-dimension, it does not seem wise to relax all three lattice constants. You probably want to keep the vacuum dimension fixed.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2021-08-22T06:36:00.143" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6603" PostTypeId="1" AcceptedAnswerId="6625" CreationDate="2021-08-23T11:10:27.770" Score="4" ViewCount="423" Body="&lt;p&gt;Using VASP, I have conducted DOS and BS calculations of a Ti-doped &lt;span class=&quot;math-container&quot;&gt;$\ce{MoI3}$&lt;/span&gt; monolayer using the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;POSCAR&lt;/strong&gt;&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MoI3                                    &#xA;   1.00000000000000     &#xA;    14.4854649408170939   -0.0007532821817704    0.0005796963007335&#xA;    -7.2434972127101211   12.5459583006560749   -0.0041326374435996&#xA;     0.0032311730240303   -0.0104455455087482   18.1668086991713693&#xA;   Mo   I    Ti&#xA;     7    24     1&#xA;Direct&#xA;  0.3330971891338734  0.1665736841755603  0.5001910329994956&#xA;  0.8338455665356221  0.1665137499446203  0.5000335513376868&#xA;  0.8337203761162328  0.6672255720968678  0.4997592499121311&#xA;  0.1668628879574570  0.3324368411586676  0.4996237331998330&#xA;  0.1666184313766692  0.8342365889988201  0.5005685048525947&#xA;  0.6670249562338242  0.3334898971870714  0.4998774696965782&#xA;  0.6677440326294573  0.8338841744313470  0.4999147964603026&#xA;  0.3185958390353250  0.4990001196708960  0.4083710595595704&#xA;  0.3224440807443472  0.0000730839056828  0.4107381054445298&#xA;  0.8230113583266387  0.5002725798922327  0.4102414939751000&#xA;  0.8236284250252481  0.0001794556197936  0.4101278084079425&#xA;  0.1768491044609064  0.1760019495846450  0.4100411439620828&#xA;  0.1791796302185205  0.6795166206652183  0.4106424776233766&#xA;  0.6779141980430552  0.1774485021457863  0.4105289952472475&#xA;  0.6775027972865217  0.6773950436894296  0.4105178207308171&#xA;  0.0001120659225933  0.3223358259823073  0.4106311815782249&#xA;  0.0001845604753541  0.8236045013874786  0.4101885057831041&#xA;  0.4998608569263183  0.3222287852645920  0.4106355330682092&#xA;  0.5000851739820860  0.8214457178196923  0.4109122177341433&#xA;  0.1768409869017873  0.0007345664211797  0.5903431383554363&#xA;  0.1791385851876157  0.4996356126462445  0.5893403090229796&#xA;  0.6778624449165420  0.0001609976698589  0.5893797531545246&#xA;  0.6779724716073687  0.5003694678926749  0.5893281968251074&#xA;  0.3231945670457677  0.3230001036273578  0.5895971617382969&#xA;  0.3183718014933135  0.8193577758142965  0.5918113350629071&#xA;  0.8228303391782177  0.3225522091477657  0.5895183779090090&#xA;  0.8235858965414664  0.8233930983732023  0.5897716811696228&#xA;  0.0002009070245350  0.1765762143626333  0.5897595904439115&#xA;  0.9997867292834854  0.6776268821436702  0.5893750036233527&#xA;  0.5002106990392505  0.1777406882794708  0.5893809980283820&#xA;  0.5001248011394424  0.6786600597049599  0.5890115938959326&#xA;  0.3319993862111303  0.6658919222959270  0.5000070991975392&#xA; &#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;SCF INCAR&lt;/strong&gt;&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE = 2&#xA;#KPAR = 5&#xA;# Self Consistent Calculation step:&#xA;ISTART = 0&#xA;ICHARG = 2&#xA;IBRION = -1&#xA;NSW = 0&#xA;LORBIT = 11&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 600 eV&#xA;EDIFF = 1.0E-6&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;ALGO = Normal&#xA;ADDGRID=.TRUE.&#xA;&#xA;#Relaxation:&#xA;ISMEAR = -5&#xA;SIGMA = 0.1&#xA;EDIFFG = -0.01&#xA;GGA COMPAT = .FALSE.&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 7*5.0 24*0.6 1*0.6&#xA;LASPH = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;#AMIX     = 0.2&#xA;#BMIX     = 0.00001&#xA;#AMIX_MAG = 0.8&#xA;#BMIX_MAG = 0.00001&#xA;&#xA;GGA+U&#xA;  LDAU      = .TRUE.&#xA;  LDAUTYPE  = 2&#xA;  LDAUL     = 2 -1 2&#xA;  LDAUU     = 3.00 0.00 2.50&#xA;  LDAUJ     = 0.00 0.00 0.00&#xA;  LDAUPRINT = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;DOS INCAR :&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE = 6&#xA;#KPAR = 5&#xA;# DOS&#xA;ICHARG = 11&#xA;IBRION = -1&#xA;NSW = 0&#xA;LORBIT = 11&#xA;NEDOS = 2001&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 600 eV&#xA;EDIFF = 1.0E-6&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;ALGO = Normal&#xA;ADDGRID=.TRUE.&#xA;&#xA;#Relaxation:&#xA;ISMEAR = -5&#xA;#SIGMA = 0.1&#xA;EDIFFG = -0.01&#xA;GGA COMPAT = .FALSE.&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 7*5.0 24*0.6 1*0.6&#xA;LASPH = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;#AMIX     = 0.2&#xA;#BMIX     = 0.00001&#xA;#AMIX_MAG = 0.8&#xA;#BMIX_MAG = 0.00001&#xA;&#xA;GGA+U&#xA;  LDAU      = .TRUE.&#xA;  LDAUTYPE  = 2&#xA;  LDAUL     = 2 -1 2&#xA;  LDAUU     = 3.00 0.00 2.50&#xA;  LDAUJ     = 0.00 0.00 0.00&#xA;  LDAUPRINT = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;DOS statistics :&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     +-------------------------- Summary ----------------------------+&#xA;            Spin Channel:     &amp;lt;UP&amp;gt;       &amp;lt;DOWN&amp;gt;      &amp;lt;TOTAL&amp;gt;&#xA;           Band Gap (eV):    1.3920      2.4001      1.3920&#xA;  Eigenvalue of VBM (eV):   -2.4897     -3.0363     -2.4897&#xA;  Eigenvalue of CBM (eV):   -1.0977     -0.6362     -1.0977&#xA;       Fermi Energy (eV):   -2.4852     -2.4852     -2.4852&#xA;               HOMO Band:       150       128         150&#xA;               LUMO Band:       151       129         151&#xA;    Location of VBM (UP):    0.0000      0.4615     -0.0000&#xA;    Location of CBM (UP):    0.0000      0.0000      0.0000&#xA;    Location of VBM (DW):    0.0000      0.0000      0.0000&#xA;    Location of CBM (DW):    0.0000      0.0000      0.0000&#xA;    Location of VBM (TO):    0.0000      0.4615     -0.0000&#xA;    Location of CBM (TO):    0.0000      0.0000      0.0000&#xA; +---------------------------------------------------------------+&#xA;E-fermi = -2.485212&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;BS INCAR :&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE = 2&#xA;#KPAR = 5&#xA;# Self Consistent Calculation step:&#xA;ISTART = 0&#xA;ICHARG = 2&#xA;IBRION = -1&#xA;NSW = 0&#xA;LORBIT = 11&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 600 eV&#xA;EDIFF = 1.0E-6&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;ALGO = Normal&#xA;ADDGRID=.TRUE.&#xA;&#xA;#Relaxation:&#xA;ISMEAR = 0&#xA;SIGMA = 0.1&#xA;EDIFFG = -0.01&#xA;GGA COMPAT = .FALSE.&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 7*5.0 24*0.6 1*0.6&#xA;LASPH = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;#AMIX     = 0.2&#xA;#BMIX     = 0.00001&#xA;#AMIX_MAG = 0.8&#xA;#BMIX_MAG = 0.00001&#xA;&#xA;GGA+U&#xA;  LDAU      = .TRUE.&#xA;  LDAUTYPE  = 2&#xA;  LDAUL     = 2 -1 2&#xA;  LDAUU     = 3.00 0.00 2.50&#xA;  LDAUJ     = 0.00 0.00 0.00&#xA;  LDAUPRINT = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;BS statistics :&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; +-------------------------- Summary ----------------------------+&#xA;            Spin Channel:     &amp;lt;UP&amp;gt;       &amp;lt;DOWN&amp;gt;      &amp;lt;TOTAL&amp;gt;&#xA;           Band Gap (eV):    1.5015      2.4738      1.5015&#xA;  Eigenvalue of VBM (eV):   -2.5966     -3.0388     -2.5966&#xA;  Eigenvalue of CBM (eV):   -1.0951     -0.5650     -1.0951&#xA;       Fermi Energy (eV):   -2.0467     -2.0467     -2.0467&#xA;               HOMO Band:       150       128         150&#xA;               LUMO Band:       151       129         151&#xA;    Location of VBM (UP):   -0.2222      0.4444      0.0000&#xA;    Location of CBM (UP):    0.0000      0.0000      0.0000&#xA;    Location of VBM (DW):    0.0000      0.0000      0.0000&#xA;    Location of CBM (DW):    0.0000      0.0000      0.0000&#xA;    Location of VBM (TO):   -0.2222      0.4444      0.0000&#xA;    Location of CBM (TO):    0.0000      0.0000      0.0000&#xA; +---------------------------------------------------------------+&#xA;    E-fermi = -2.046733&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also, when I draw BS and DOS I noticed that they are shifted from each other. I have also got this problem with some other materials. What might be my mistake?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-08-23T23:52:43.603" LastActivityDate="2022-08-30T01:46:37.710" Title="What is the source of this band structure and DOS inconsistency?" Tags="|vasp|band-structure|density-of-states|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6605" PostTypeId="1" AcceptedAnswerId="6611" CreationDate="2021-08-23T15:08:05.120" Score="6" ViewCount="190" Body="&lt;p&gt;I am an outsider to this field, so I am not sure about the validity of my work below.&lt;/p&gt;&#xA;&lt;p&gt;Let us define the following Hamiltonian from &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory#Derivation_and_formalism&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{1}H_{ij} \psi_{ij} \equiv (-\frac{\hbar^2 \nabla_i^2}{2m}  -\frac{\hbar^2 \nabla_j^2}{2m}  + \frac{1}{4 \pi \epsilon_0}\frac{k_2}{\vec r_i ^2}  + \frac{1}{4 \pi \epsilon_0}\frac{k_2}{\vec r_j ^2} + \frac{\lambda}{4 \pi \epsilon_0} \frac{k_1}{(\vec r_i - \vec r_j)^2} ) \psi_{ij}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_2$&lt;/span&gt; are constants. Let &lt;span class=&quot;math-container&quot;&gt;$\psi_{12}$&lt;/span&gt; be the lowest energy state of the system:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2} \min_\psi H_{12} \psi = E_0(\lambda) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We add a constant energy to the system such that the minimum eigenvalue obeys:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3} \min (H_{12} + c)\psi_{12} = (E_0(\lambda) + c)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Lets say I want to solve the minimum energy of a &lt;span class=&quot;math-container&quot;&gt;$3$&lt;/span&gt; electron material. I play the following trick&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4} \min ((H_{12}+ c) \psi_{12})^3 = (E_0(\lambda) + c )^3 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let us use:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5} \!\!\!\!\!\!\!\!\!\!\!\!\! \min ((H_{12}+ c) \psi_{12})^3 = \min ((H_{12}+ c)  \psi_{12}) \min ((H_{12}+ c) \psi_{12}) \min ((H_{12}+ c) \psi_{12})  \!\!\!\!\!\!\!$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{6}\min ((H_{12}+ c) \psi_{12})^3 =\min ((H_{12}+ c) \psi_{12}) ((H_{23}+ c) \psi_{23})((H_{31}+ c) \psi_{31})  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Focusing on the constant &lt;span class=&quot;math-container&quot;&gt;$c^2$&lt;/span&gt; term:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{7} \min c^2(H_{12} + H_{23} + H_{31})\psi_{12} \psi_{23} \psi_{31} = 3c^2 E_0 (\lambda) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However there will be &lt;span class=&quot;math-container&quot;&gt;$n-2$&lt;/span&gt; excess kinetic energy terms and static external potential terms. Thus we choose &lt;span class=&quot;math-container&quot;&gt;$\lambda =n-1 $&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$n=3$&lt;/span&gt; over here)&lt;/p&gt;&#xA;&lt;p&gt;And get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{8} \min \frac{c^{2}}{2}((H_{12} + H_{23} + H_{31})\psi_{12} \psi_{23} \psi_{31} ) =\frac{3}{2}c^2 E_0( 2) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In general for &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; electrons:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{9} H \equiv \min \frac{c^{N-1}}{n-1}(\sum_{i\neq j}^n H_{ij}  ) =c^{N-1} \frac{N}{n-1}E_0( n-1) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N = n(n-1)/2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Question&lt;/h2&gt;&#xA;&lt;p&gt;Is this trick correct?&#xA;Can someone cross check if this yields correct answers?&lt;/p&gt;&#xA;" OwnerUserId="1810" LastEditorUserId="1810" LastEditDate="2021-08-24T04:08:43.243" LastActivityDate="2021-08-24T04:08:43.243" Title="Ground State energy trick for many-body electronic structure calculations?" Tags="|density-functional-theory|electronic-structure|mathematical-modeling|quantum-mechanics|derivations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6606" PostTypeId="1" AcceptedAnswerId="6608" CreationDate="2021-08-23T16:22:31.800" Score="5" ViewCount="1599" Body="&lt;p&gt;If I have &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; can I calculate equilibrium distance &lt;span class=&quot;math-container&quot;&gt;$r_e$&lt;/span&gt; in one run? What I have tried is to put &lt;span class=&quot;math-container&quot;&gt;$V = \epsilon$&lt;/span&gt; and bring out the &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; from the formula, but it seems not solvable. So I am clueless. I need to calculate the equilibrium distance for some project of mine (game-like) with atom interactions.&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2021-08-23T17:06:08.107" LastActivityDate="2021-08-23T17:06:08.107" Title="What is the equilibrium bond length for a Lennard-Jones potential?" Tags="|molecular-dynamics|mathematical-modeling|spectroscopy|interatomic-potentials|potential-energy-surface|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6607" PostTypeId="1" AcceptedAnswerId="6609" CreationDate="2021-08-23T16:26:34.947" Score="7" ViewCount="275" Body="&lt;p&gt;I've been studying MD and more specifically about Car-Parrinello Molecular Dynamics and I'm not entirely sure if I understood the meaning behind the minimization.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;This is the way I understand it:&lt;/strong&gt; The wave function optimization/minimization of the system at the beginning of a CPMD simulation is to make sure there won't be energy transfer between the nuclei and the electrons. Since the electrons will be on the Born-Oppenheimer surface after the minimization, they will be considered &amp;quot;cold&amp;quot; and then in a different temperature from the ions. And then the dynamics might proceed adiabatically, and a result being that the wavefunction doesn't need to be optimized after each time step in the CP method.&lt;/p&gt;&#xA;&lt;p&gt;Is this way of thinking correct or am I missing something? I've also thought about it being related to the Kohn-Sham energy functional.&lt;/p&gt;&#xA;" OwnerUserId="4184" LastEditorUserId="49" LastEditDate="2021-08-25T22:29:48.950" LastActivityDate="2021-08-25T22:29:48.950" Title="What is the real reason behind the minimization of the system at the beginning of a Car-Parrinello MD calculation?" Tags="|molecular-dynamics|from-chem-se|kohn-sham|aimd|cpmd|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6608" PostTypeId="2" ParentId="6606" CreationDate="2021-08-23T17:05:38.387" Score="5" Body="&lt;p&gt;I searched for the word &amp;quot;minimum&amp;quot; on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia page for Lennard-Jones potential&lt;/a&gt;, and the 2nd paragraph says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The potential minimum is at &lt;span class=&quot;math-container&quot;&gt;$r=r_m = 2^{1/6}\sigma$&lt;/span&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can obtain this by calculating the derivative of the Lennard-Jones potential with respect to &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and finding which &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; value makes that derivative equal to 0.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-23T17:05:38.387" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6609" PostTypeId="2" ParentId="6607" CreationDate="2021-08-23T17:52:05.507" Score="6" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1525/5&quot;&gt;I explained Car-Parrinello MD here&lt;/a&gt;, and a key point is that it approximates BOMD (Born-Oppenheimer Molecular Dynamics) where the electronic state is minimized (i.e. the ground electronic state is found and used) at each step. The reason for the minimization in CPMD at the first step, is the same as the reason in the earlier BOMD method that it approximates. Also, the reason why the electronic state's wavefunction doesn't need to be re-minimized at each step in CPMD, is explained in my answer linked at the beginning of this paragraph: a fictitious force is used to keep the electronic state close to the ground state.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;As for why BOMD and CPMD aim to involve the ground electronic state instead of an excited one:&lt;/strong&gt; First of all, why would you not want to minimize the electronic state when doing molecular dynamics? I can only think of two reasons:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(1) it's computationally expensive&lt;/li&gt;&#xA;&lt;li&gt;(2) you might be trying to simulate some system which is not in the ground state for some reason.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you are not in category (2), then I see no reason not to minimize the electronic state if you have a computer that's capable of doing it accurately enough for it to be worth it, and since DFT is typically used to approximate the minimization of the ground state, quite accurate results can be obtained at quite a low cost. Is the &amp;quot;quite good&amp;quot; accuracy of DFT electronic state minimization worth the &amp;quot;quite low&amp;quot; cost? Well CPMD is an extremely popular method, with the &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.55.2471&quot; rel=&quot;noreferrer&quot;&gt;original paper&lt;/a&gt; currently having  &lt;a href=&quot;https://scholar.google.com/citations?view_op=view_citation&amp;amp;hl=en&amp;amp;user=lnkt9rgAAAAJ&amp;amp;citation_for_view=lnkt9rgAAAAJ:u5HHmVD_uO8C&quot; rel=&quot;noreferrer&quot;&gt;12704 citations on Google Scholar&lt;/a&gt;, so I would hope so! &lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2021-08-23T17:52:05.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6610" PostTypeId="2" ParentId="6607" CreationDate="2021-08-23T20:24:19.793" Score="5" Body="&lt;p&gt;Yes your understanding is correct.&lt;/p&gt;&#xA;&lt;p&gt;It helps to think about BOMD as classical dynamics. The electrons are the springs that hold the masses together and the nuclei are the masses.The two key terms are the internal energy (U) and the kinetic energy of the masses (K).&lt;/p&gt;&#xA;&lt;p&gt;We seek to calculate the positions of the system as a function of time, which we can do numerically by integrating the equation of motion.&lt;/p&gt;&#xA;&lt;p&gt;Force-field molecular dynamics is exactly this, where the potential energy is just written as harmonic oscillators with the parameters obtained by fitting. We can also calculate the internal energy from first principles using quantum mechanics/the Schrodinger equation.&lt;/p&gt;&#xA;&lt;p&gt;In either case, the nuclei are following the potential formed by the electrons. As Nike explained above, CPMD just seeks to get the internal energy faster by taking advantage of numerical tricks.&lt;/p&gt;&#xA;&lt;p&gt;It is &lt;strong&gt;critical&lt;/strong&gt; that we can solve the motion of the nuclei on a potential that is parametrically dependent on the positions of the nuclei &lt;span class=&quot;math-container&quot;&gt;$\psi(r;R)$&lt;/span&gt;. This is known as the Born-Oppenheimer approximation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;If the motion of electrons is coupled to the motion of the nuclei this is known as non-adiabatic effects and causes a breakdown of the BOMD.&lt;/strong&gt;&lt;/em&gt; This can happen at places known as conical intersections where two or more potential energy surfaces intersect and the electronic state changes rapidly as a function of nuclear position.&lt;/p&gt;&#xA;" OwnerUserId="52" LastEditorUserId="5" LastEditDate="2021-08-23T21:03:16.933" LastActivityDate="2021-08-23T21:03:16.933" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6611" PostTypeId="2" ParentId="6605" CreationDate="2021-08-23T21:11:49.353" Score="8" Body="&lt;p&gt;There are a few issues with the derivation:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;(not necessarily a mistake, but) please note that if you mean the Coulomb Hamiltonian, the RHS of (1) should involve the reciprocals of &lt;span class=&quot;math-container&quot;&gt;$|r_i|$&lt;/span&gt; etc., not &lt;span class=&quot;math-container&quot;&gt;$r_i^2$&lt;/span&gt; etc. The Coulomb interaction enters the Hamiltonian in the form of potential energy, rather than in the form of force. Please ignore this comment if you are deliberately using the inverse square potential as an example.&lt;/li&gt;&#xA;&lt;li&gt;In (2), note that the quantity to be minimized is &lt;span class=&quot;math-container&quot;&gt;$\langle \psi|H|\psi \rangle$&lt;/span&gt; (in other words, &lt;span class=&quot;math-container&quot;&gt;$\int \psi^*(\vec{r})H\psi(\vec{r}) d\vec{r}$&lt;/span&gt;), not &lt;span class=&quot;math-container&quot;&gt;$H|\psi\rangle$&lt;/span&gt;. The latter is not even a number; rather, it's a function, and you cannot minimize a function - you can only minimize a number.&lt;/li&gt;&#xA;&lt;li&gt;By using &lt;span class=&quot;math-container&quot;&gt;$\langle \psi|H|\psi \rangle$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$H|\psi\rangle$&lt;/span&gt;, you will be able to correct some of the equations that follow, but you won't arrive at anything that resembles your conclusion. You'll end up at something like &lt;span class=&quot;math-container&quot;&gt;$\langle \psi_{12}|H_{12}+c|\psi_{12} \rangle\langle \psi_{23}|H_{23}+c|\psi_{23} \rangle\langle \psi_{31}|H_{31}+c|\psi_{31} \rangle$&lt;/span&gt;, but you can't proceed further because the multiplications of bras, kets and operators are in general not commutative. You can't rearrange this into a form that resembles (7). Whenever in doubt, write all bras and kets into the equivalent integral form, write out the differential operators in H, and apply basic calculus rules to see which operations you can do and which you can't.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;And finally, a general advice: there is almost certainly no free lunch with the Coulombic many-body problem. It's worthwhile to consider how to numerically approximate it in the best way, but attempts to simplify it analytically would almost certainly be fruitless. I remember that in my first year as a graduate student I expanded the &lt;span class=&quot;math-container&quot;&gt;$e^{-iHt/\hbar}$&lt;/span&gt; operator using the BCH approximation, and attempted to simplify and resum the series by using the fact &lt;span class=&quot;math-container&quot;&gt;$\nabla^2 V = 0$&lt;/span&gt;. This took quite a lot of my spare time and I got nothing, except for the precious lesson that any efforts to analytically simplify the Coulombic many-body problem are likely bound to make little sense. Indeed if you can analytically simplify the problem to a significant degree, you will prove P=NP.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-08-23T21:24:38.613" LastActivityDate="2021-08-23T21:24:38.613" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6612" PostTypeId="2" ParentId="6603" CreationDate="2021-08-23T23:20:41.047" Score="3" Body="&lt;p&gt;Neither the valence band maximum (VBM) nor the conduction band minimum (CBM) have to be at a k-point from the k-point set that you use for an SCF, DOS, or band structure calculation. I don't know what VASP reports as the Fermi level for insulators, but I guess that it is the energy of the highest occupied state within the used k-point set. Since it is not guaranteed that this is the real VBM you have to see this as an approximation. If you use a k-point mesh you can actually systematically converge this quantity by using finer and finer meshes. If you use a high-symmetry k-point path you cannot do that. The VBM is not guaranteed to be on that path. The same argument applies to the size of the band gap.&lt;/p&gt;&#xA;&lt;p&gt;As a consequence these quantities differ when using different k-point sets.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="5" LastEditDate="2021-08-23T23:35:45.047" LastActivityDate="2021-08-23T23:35:45.047" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6613" PostTypeId="5" CreationDate="2021-08-24T00:24:00.100" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/Tsjerk/MartiniTools&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Tsjerk/MartiniTools&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-24T00:24:00.100" LastActivityDate="2021-08-24T00:24:00.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6614" PostTypeId="4" CreationDate="2021-08-24T00:24:00.100" Score="0" Body="Questions about or related to the MartiniTools software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-24T00:24:00.100" LastActivityDate="2021-08-24T00:24:00.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6615" PostTypeId="5" CreationDate="2021-08-24T00:50:28.543" Score="0" Body="&lt;p&gt;A related website: &lt;a href=&quot;http://cgmartini.nl/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://cgmartini.nl/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-24T00:50:28.543" LastActivityDate="2021-08-24T00:50:28.543" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6616" PostTypeId="4" CreationDate="2021-08-24T00:50:28.543" Score="0" Body="Questions about the Martini forcefield and related programs such as MartiniTools, Martinize, Martinize2, etc." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-08-24T00:50:28.543" LastActivityDate="2021-08-24T00:50:28.543" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6617" PostTypeId="2" ParentId="4940" CreationDate="2021-08-24T01:41:53.027" Score="4" Body="&lt;p&gt;Resetting the atom IDs with the &lt;code&gt;reset_atom_ids&lt;/code&gt; command can help with that. You can read more about it &lt;a href=&quot;https://docs.lammps.org/reset_atom_ids.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the older version of LAMMPS, you may try &lt;code&gt;reset_ids&lt;/code&gt; instead.&lt;/p&gt;&#xA;" OwnerUserId="4187" LastEditorUserId="5" LastEditDate="2021-08-24T02:18:23.940" LastActivityDate="2021-08-24T02:18:23.940" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6618" PostTypeId="1" CreationDate="2021-08-24T07:14:40.050" Score="4" ViewCount="152" Body="&lt;p&gt;So I was given &lt;a href=&quot;https://openkim.org/files/MO_959249795837_003/LennardJones612_UniversalShifted.params&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt;, and was happy that I have now the epsilons and sigmas that I can use in Lennard-Jones potential calculations, but found out that the information in other sources is very different.&lt;/p&gt;&#xA;&lt;p&gt;It says &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Supplemental_Modules_(Physical_and_Theoretical_Chemistry)/Physical_Properties_of_Matter/Atomic_and_Molecular_Properties/Intermolecular_Forces/Specific_Interactions/Lennard-Jones_Potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The  ϵ  and  σ  values for Xenon (Xe) are found to be 1.77 kJ/mol and 4.10 angstroms, respectively.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Which is different from the table in first link which says epsilon = 0.0238880 eV (2.304881456 kJ/mol) and sigma = 2.4945200 angstroms.&lt;/p&gt;&#xA;&lt;p&gt;I understand that there could be some insignificant differences, but these are rather big ones. Maybe I am not correctly reading the table (ignoring cutoff) or something else?&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2021-08-24T18:57:18.443" LastActivityDate="2021-08-24T18:57:18.443" Title="Problems with Lennard Jones potential parameters reading" Tags="|interatomic-potentials|reproducing-data-from-papers|" AnswerCount="0" CommentCount="5" ClosedDate="2021-10-29T18:53:05.320" ContentLicense="CC BY-SA 4.0" />
  <row Id="6622" PostTypeId="1" AcceptedAnswerId="6635" CreationDate="2021-08-24T09:23:18.983" Score="4" ViewCount="558" Body="&lt;p&gt;I have performed some calculations for a 2D-monolayer using &lt;code&gt;VASP&lt;/code&gt;.&#xA;I run DOS calculations without &lt;code&gt;LOPTICS = .TRUE.&lt;/code&gt;&#xA;I found that when I run the &lt;code&gt;vaspkit&lt;/code&gt;, I got the files for optical properties.&#xA;Could someone please explain to me, if we are getting the files for optical properties, then how reliable are these files?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;INCAR&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART   = 1&#xA;# ICHARG   = 11&#xA;# ISYM = 0&#xA; PREC     = Accurate&#xA; ENCUT    = 550&#xA; ISMEAR   = 0&#xA; SIGMA    = 0.1&#xA; LREAL    = .FALSE.&#xA; LWAVE    = .TRUE.  &#xA; LCHARG   = .TRUE.   &#xA; ADDGRID  = .TRUE.  &#xA; EDIFF   = 1e-6&#xA; EDIFFG  = -0.02&#xA; NSW     = 0&#xA;  LORBIT  = 12&#xA;  NEDOS   = 5000&#xA;  LHFCALC= T&#xA;  AEXX   =  0.25 HFSCREEN= 0.2  &#xA;  ALGO   =  ALL&#xA;  TIME   =  0.4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="789" LastEditorUserId="7" LastEditDate="2021-08-27T13:50:43.020" LastActivityDate="2021-08-27T13:50:43.020" Title="Optical properties without LOPTICS tag" Tags="|vasp|2d-lattice|optical-properties|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6624" PostTypeId="1" CreationDate="2021-08-24T18:50:31.450" Score="5" ViewCount="33" Body="&lt;p&gt;My research is on the structural optimization of fibre-reinforced composite material (transversely isotropic material). I am currently working on a homogenization method for attaining the effective properties of fibre-reinforced composite materials. A lot of literature is available on how to compute the effective properties of composite material using homogenization.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However, I would like to understand if the attained effective properties of composite material is a convex function or not?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Considering only the linear (elastic) regime, how can one prove that composite's effective properties using the homogenization method are convex function or not?&lt;/p&gt;&#xA;&lt;p&gt;I would be grateful if someone can help me to understand how I can approach the above problem or direct me to the relevant paper (if it exists).&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your time and attention.&lt;/p&gt;&#xA;" OwnerUserId="4189" LastEditorUserId="5" LastEditDate="2021-08-25T19:52:11.720" LastActivityDate="2021-08-25T19:52:11.720" Title="Linear combination of homogenized composite material" Tags="|physical-properties-of-materials|materials-design|materials-engineering|microstructure|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-02T17:23:52.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="6625" PostTypeId="2" ParentId="6603" CreationDate="2021-08-24T20:10:45.417" Score="2" Body="&lt;p&gt;Thanks to all who contributed to answer to this post.&lt;/p&gt;&#xA;&lt;p&gt;I have found that the problem is that I have used &lt;code&gt;ICHARG=11&lt;/code&gt; in DOS to read the charge density from &lt;code&gt;SCF&lt;/code&gt; calcualtion, but for BS I have used &lt;code&gt;ICHARG=2&lt;/code&gt; which doesn't allow the reading of charge density from &lt;code&gt;SCF&lt;/code&gt; calcualtion. So DOS and BS doesn't start from the same charge density.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-08-24T20:10:45.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6626" PostTypeId="1" CreationDate="2021-08-25T01:05:32.497" Score="8" ViewCount="314" Body="&lt;p&gt;We are all aware of the fact that negative charge densities in the atomic cores are an artefact of Density Functional theory Calculations using Projector Augmented Wave (PAW) method. But what is the justification for these negative charges? They certainly did not appear out of nowhere. I request an explanation and a convincing proof if available.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2021-08-25T15:30:54.617" LastActivityDate="2021-08-25T15:30:54.617" Title="Why do I get negative charge density values in the core of atoms when I perform DFT calculations with PAW?" Tags="|density-functional-theory|vasp|quantum-espresso|charge-density|projector-augmented-wave|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-14T01:36:23.200" ContentLicense="CC BY-SA 4.0" />
  <row Id="6627" PostTypeId="1" AcceptedAnswerId="6628" CreationDate="2021-08-25T09:27:38.280" Score="8" ViewCount="369" Body="&lt;p&gt;From &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6464/one-to-one-correspondence-between-electron-density-and-external-coulomb-potent&quot;&gt;this question and answer&lt;/a&gt;, I understood the Hohenberg-Kohn theorem and found that there is a one-to-one correspondence between the external potential &lt;span class=&quot;math-container&quot;&gt;$V_\text{ext}$&lt;/span&gt; and the electron density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; as entire functions, not pointwise.&lt;/p&gt;&#xA;&lt;p&gt;Now I would like to know the relationship between &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and the effective potential &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt; (= &lt;span class=&quot;math-container&quot;&gt;$V_\text{ext}$&lt;/span&gt; + &lt;span class=&quot;math-container&quot;&gt;$V_{H}$&lt;/span&gt; + &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$V_{H}$&lt;/span&gt; is the Hatree term and &lt;span class=&quot;math-container&quot;&gt;$V_{xc}$&lt;/span&gt; is the exchange-correlation term). Is there any kind of pointwise correspondence between &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; in systems? I understand that the DFT can be described as the &lt;strong&gt;electron cloud moving in &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt;&lt;/strong&gt;, that is, the &lt;strong&gt;electrons do not interact with each other and are spread on &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt;&lt;/strong&gt; like the following figure of Schrödinger's and DFT's views (&lt;a href=&quot;https://www.semanticscholar.org/paper/TOPICAL-REVIEW%3A-Designing-meaningful-density-theory-Mattsson-Schultz/9e57d4b4d5eec0f1b65fe774638b6d97a99f5f53/figure/0&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.semanticscholar.org/paper/TOPICAL-REVIEW%3A-Designing-meaningful-density-theory-Mattsson-Schultz/9e57d4b4d5eec0f1b65fe774638b6d97a99f5f53/figure/0&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rpU8S.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rpU8S.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, is there any pointwise correspondence between &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;? The reason for thinking this way is that, I was wondering if there is such a mapping between the effective potential and the non-interacting electron cloud, I believe that we may be able to learn the mapping by machine learning method described in the following paper.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.nature.com/articles/s41467-017-00839-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/s41467-017-00839-3&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Postscript&lt;/strong&gt;: the word of 'point-wise' mapping means the mapping between the value of &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}(r)$&lt;/span&gt; on a point &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and the value of &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; on &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, not the the mapping between their entire functions, &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; in the system. The (non-interacting) electrons are &lt;strong&gt;moving on&lt;/strong&gt; the effective potential, so if we have or can consider a mapping between the scalars, &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}(r)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt;, such situation is easy for machine learning to learn the mapping from data.&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="1179" LastEditDate="2021-08-25T12:01:18.130" LastActivityDate="2021-08-25T12:01:18.130" Title="A mapping between effective potential and non-interacting electrons moving on the potential" Tags="|density-functional-theory|kohn-sham|" AnswerCount="1" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6628" PostTypeId="2" ParentId="6627" CreationDate="2021-08-25T10:05:08.617" Score="8" Body="&lt;p&gt;Roughly speaking and provided that the Hohenberg-Kohn theorem applies, if the &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representable ground state density of an interacting system &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is additionally non-interacting &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representable, then by definition there exists a non-interacting system with potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; as its ground state density. By the virtue of the Hohenberg-Kohn theorem, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; uniquely determines &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and vice versa. In the Kohn-Sham approach, then an explicit form of &lt;span class=&quot;math-container&quot;&gt;$V=V_\mathrm{eff}=V_\mathrm{eff}[\rho]$&lt;/span&gt; is constructed, such that solving the Kohn-Sham equations self-consistently yields &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I don't know what exactly you mean with 'point-wise'; the mapping between &lt;span class=&quot;math-container&quot;&gt;$V_\mathrm{eff}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is similar to the mapping between the external potential in the interacting system &lt;span class=&quot;math-container&quot;&gt;$V_\mathrm{int}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, i.e. is a mapping between the 'complete' functions, since it is also governed by the Hohenberg-Kohn theorem.&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2021-08-25T11:51:30.883" LastActivityDate="2021-08-25T11:51:30.883" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6629" PostTypeId="1" CreationDate="2021-08-25T12:15:02.280" Score="6" ViewCount="147" Body="&lt;p&gt;I am doing &lt;code&gt;DFPT&lt;/code&gt; calculations using &lt;code&gt;VASP+Phonopy&lt;/code&gt;.&#xA;To plot phonon band structure, I need a band.conf file in which we need to provide  &lt;code&gt;primitive axis&lt;/code&gt;.&#xA;There is an option to use &lt;code&gt;--pa=auto&lt;/code&gt; but in my case, it is not working, or maybe for &lt;code&gt;DFPT&lt;/code&gt;, we need to supply a proper &lt;code&gt;primitive axis&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is there any way or code using which we can know the primitive axis of any system?&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;POSCAR&lt;/code&gt; for my system is mentioned below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System                                  &#xA;   1.00000000000000     &#xA;     5.2830000000000004    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    5.2830000000000004    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   20.0000000000000000&#xA;   Ta   N &#xA;     2     4&#xA;Direct&#xA;  0.0000000038778781 -0.0000000040248837  0.4999999999997483&#xA;  0.5000000098083184  0.4999999954548999  0.4999999998722517&#xA;  0.1428654795841584  0.6428651637231821  0.5338481609868386&#xA;  0.8571345120369003  0.3571348472078131  0.5338481661924134&#xA;  0.6428651606314468  0.8571345203839439  0.4661518370931707&#xA;  0.3571348450612953  0.1428654882550420  0.4661518358555774&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="789" LastActivityDate="2021-08-25T12:15:02.280" Title="How can I find primitive axis for any bulk or 2D (monolayer) material" Tags="|vasp|phonopy|dfpt|" AnswerCount="0" CommentCount="8" ClosedDate="2022-01-14T03:16:44.417" ContentLicense="CC BY-SA 4.0" />
  <row Id="6630" PostTypeId="1" AcceptedAnswerId="9196" CreationDate="2021-08-25T13:28:27.093" Score="8" ViewCount="786" Body="&lt;p&gt;I noticed that a lot of articles use DFT+U methods to calculate different formation energies when using regular DFT and DFT+U methods. For example, in the attached paper[1] on &lt;span class=&quot;math-container&quot;&gt;$\ce{In2O3}$&lt;/span&gt;, the enthalpy of formation was found to be &lt;span class=&quot;math-container&quot;&gt;$\pu{-9.86 eV}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\pu{-10.41 eV}$&lt;/span&gt; using LDA and LDA+U, respectively.&lt;/p&gt;&#xA;&lt;p&gt;When calculating the formation energies using DFT+U, I am wondering if the energies of the elemental reference states (&lt;span class=&quot;math-container&quot;&gt;$\ce{In}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt; in the above case) also need to be calculated using DFT+U, or just from regular DFT, since they often do not have band gaps that DFT+U seeks to correct.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pakpoom Reunchan, Xin Zhou, Sukit Limpijumnong, Anderson Janotti, Chris G. Van de Walle, Vacancy defects in indium oxide: An ab-initio study, Current Applied Physics, Volume 11, Issue 3, Supplement, 2011, Pages S296-S300,DOI: &lt;a href=&quot;https://doi.org/10.1016/j.cap.2011.03.051&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1016/j.cap.2011.03.051&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4192" LastEditorUserId="6055" LastEditDate="2023-10-13T14:59:41.603" LastActivityDate="2023-10-13T14:59:41.603" Title="How to calculate formation energy using DFT+U?" Tags="|ab-initio-calculations|dft-u|formation-energy|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6631" PostTypeId="1" AcceptedAnswerId="6633" CreationDate="2021-08-25T13:47:30.167" Score="7" ViewCount="93" Body="&lt;p&gt;When I consider the grid positions &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; in a molecular system,&#xA;I have a matrix, where each row can be regarded as an &lt;strong&gt;N-dimensional vector&lt;/strong&gt;&#xA;and each column can be regarded as a &lt;strong&gt;G-dimensional vector&lt;/strong&gt;.&#xA;In the following figure,&#xA;N is the number of orbitals and G is the number of grid positions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/U0uv1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/U0uv1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this case, the elements of &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th N-dimensional vector is the values of orbital functions on the position &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt;; the elements of &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;th G-dimensional vector is the values of &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;th orbital function.&lt;/p&gt;&#xA;&lt;p&gt;In this matrix, I believe that there are two kinds of interactions.&#xA;(1) The interactions between different distances (red arrow).&#xA;(2) The interactions between different orbitals (blue arrow) .&lt;/p&gt;&#xA;&lt;p&gt;The DFT concept is based on the &lt;strong&gt;non-interacting electrons&lt;/strong&gt; moving in the effective potential. Here, is the meaning of non-interacting electrons (1) or (2) or both?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-08-25T13:56:15.683" LastActivityDate="2021-08-28T19:38:50.923" Title="Electron interactions between different positions or different orbitals" Tags="|density-functional-theory|electronic-structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6632" PostTypeId="2" ParentId="6630" CreationDate="2021-08-25T16:31:00.610" Score="5" Body="&lt;p&gt;To calculate formation energies from DFT+U, you must use a self consistent set of parameters.  This is easy to visualize since you can imagine the reaction of InO&lt;sub&gt;DFT&lt;/sub&gt; -&amp;gt; InO&lt;sub&gt;DFT+U&lt;/sub&gt;, which will end up having some non-zero reaction energy.  While this example is obviously incorrect, mixing energy differences with DFT+U corrections and non-corrected differences results in a similar picture, but is often less obvious.&lt;/p&gt;&#xA;&lt;p&gt;There have been some attempts to mix these however and &lt;a href=&quot;https://docs.materialsproject.org/methodology/total-energies/#accuracy-of-total-energies&quot; rel=&quot;noreferrer&quot;&gt;materials project&lt;/a&gt; has a small section on a mixing correction they have applied, however I do not know personally if this has been successful or not.  Someone more familiar with materials project might know more.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-08-25T16:31:00.610" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6633" PostTypeId="2" ParentId="6631" CreationDate="2021-08-25T16:50:07.373" Score="8" Body="&lt;p&gt;The non-interacting orbitals in exact KS-DFT still interact between different distances and different orbitals, so the answer is (1) and (2).&lt;/p&gt;&#xA;&lt;p&gt;Your spatial representation is basically a projection into position eigenstates, while the real orbital has contributions from all over the system. To evaluate the one-orbital contributions correctly, you need to integrate over the system, giving you (1).&lt;/p&gt;&#xA;&lt;p&gt;Next, already the Coulomb contribution, which is included in the exact Kohn-Sham functional, includes interactions between orbitals (between orbital contributions to the total density) which gives (2).&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;non-interacting&amp;quot; just means that the Kohn-Sham wave function is a single Slater determinant, while the true wave function consists of exponentially many determinants.&lt;/p&gt;&#xA;&lt;p&gt;Addendum: what you attempted to do with the grid, i.e. a real-space solution of the wave function can actually be achieved with e.g. finite differences or finite elements, see my open access review in &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/qua.25968&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int J Quantum Chem 119, e25968 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-08-28T19:38:50.923" LastActivityDate="2021-08-28T19:38:50.923" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6634" PostTypeId="2" ParentId="6630" CreationDate="2021-08-26T08:52:58.727" Score="6" Body="&lt;p&gt;As far as my knowledge, they must be calculated using DFT+U. When you calculate the energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{In}$&lt;/span&gt; in its bulk state using DFT, it won't lead to the same value using DFT+U.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-08-26T08:52:58.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6635" PostTypeId="2" ParentId="6622" CreationDate="2021-08-26T14:37:11.810" Score="5" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When you open the &lt;code&gt;LHFCALC&lt;/code&gt; tag, the DFT hybrid functional type dielectric function is calculated. All the output files you obtain are calculated by &lt;code&gt;VASPKIT&lt;/code&gt; using this dielectric function.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://vaspkit.com/tutorials.html#optic-properties&quot; rel=&quot;noreferrer&quot;&gt;https://vaspkit.com/tutorials.html#optic-properties&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Could someone please explain to me, if we are getting the files for optical properties, then how reliable are these files?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For 2D materials, these results cannot be believed. You should use the GW+BSE method to obtain reliable results. See this post for more information: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3674/how-to-start-with-the-optical-properties-of-2d-materials-with-the-vasp-code&quot;&gt;How to start with the optical properties of 2D materials with the VASP code?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-08-26T14:37:11.810" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6636" PostTypeId="1" AcceptedAnswerId="8449" CreationDate="2021-08-26T15:44:30.750" Score="11" ViewCount="318" Body="&lt;p&gt;When doing DFT calculations of periodic solids, from either &lt;a href=&quot;https://en.wikipedia.org/wiki/K%C2%B7p_perturbation_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{k \cdot p}$&lt;/span&gt; perturbation theory&lt;/a&gt; or simply using the trick &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r} \rightarrow i\partial_{\mathbf{k}}$&lt;/span&gt;, one can obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \psi_{c\mathbf{k}}|\partial_\mathbf{k} \psi_{v\mathbf{k}}\rangle = -i \langle \psi_{c\mathbf{k}}| \mathbf{r} | \psi_{v\mathbf{k}}\rangle = -i \langle u_{c\mathbf{k}}|\mathbf{r}| u_{v\mathbf{k}}\rangle \tag{1}\label{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; is the position operator, &lt;span class=&quot;math-container&quot;&gt;$\psi_{c\mathbf{k}}=u_{c\mathbf{k}}e^{i\mathbf{k \cdot r}}$&lt;/span&gt; is the Bloch wave function, &lt;span class=&quot;math-container&quot;&gt;$c,v$&lt;/span&gt; for conduction and valence bands, respectively. If we insert the Bloch function in the l.h.s of Eq. (1), we alternatively have:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\begin{align}&#xA;\langle \psi_{c\mathbf{k}}|\partial_\mathbf{k} \psi_{v\mathbf{k}}\rangle &amp;amp;=&#xA;\langle u_{c\mathbf{k}}|e^{-i\mathbf{k \cdot r}}\partial_\mathbf{k} (u_{v\mathbf{k}}e^{i\mathbf{k \cdot r}}) \rangle \\ \tag{3}&amp;amp;= \langle u_{c\mathbf{k}}|e^{-i\mathbf{k \cdot r}}(\partial_\mathbf{k} u_{v\mathbf{k}}e^{i\mathbf{k \cdot r}}+i\mathbf{r}e^{i\mathbf{k \cdot r}}u_{v\mathbf{k}}) \rangle \\&amp;amp;= \langle u_{c\mathbf{k}}|\partial_\mathbf{k} u_{v\mathbf{k}}\rangle + i \langle u_{c\mathbf{k}}|\mathbf{r}| u_{v\mathbf{k}}\rangle = 0 \tag{4}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;So we get a different answer for the same initial braket. I believe there is something wrong with the second equation. Any idea?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="5" LastEditDate="2022-01-01T03:33:25.540" LastActivityDate="2022-01-01T03:35:33.163" Title="Transition dipole matrix element" Tags="|density-functional-theory|band-structure|solid-state-physics|periodic-system|" AnswerCount="1" CommentCount="7" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6639" PostTypeId="2" ParentId="1478" CreationDate="2021-08-27T09:31:01.660" Score="5" Body="&lt;p&gt;Unfortunately, due to my reputation, I cannot comment yet. However, to the surprise of &lt;a href=&quot;https://mattermodeling.stackexchange.com/posts/1506/revisions&quot;&gt;Tyberius&lt;/a&gt;, I would like to note that the function young_modulus does not return the Young's modulus, but the compliance.&lt;/p&gt;&#xA;&lt;p&gt;The code looks as follows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; return (lin_elastic_region[-1,1],lin_elastic_region[0,1])/(lin_elastic_region[-1,0]-lin_elastic_region[0,0])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;with lin_elastic_region being of type [stress,strain]. If you interchange the columns to&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;return (lin_elastic_region[-1,0],lin_elastic_region[0,0])/(lin_elastic_region[-1,1]-lin_elastic_region[0,1])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the value of &lt;span class=&quot;math-container&quot;&gt;$2.08236\times10^{-5}$&lt;/span&gt; actually turns out as &lt;span class=&quot;math-container&quot;&gt;$48022.43$&lt;/span&gt;, which may be interpreted as MPa or equivalently about &lt;span class=&quot;math-container&quot;&gt;$48$&lt;/span&gt; GPa. This value is still somewhat small for the stiffness of aluminium, but is quite close to an average value of about &lt;span class=&quot;math-container&quot;&gt;$70$&lt;/span&gt; GPa.&lt;/p&gt;&#xA;&lt;p&gt;Also I would like to add, that the program calls the adjust function, which aims on making all strain values positive, but actually sets non-positive values to &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;. I changed this value to a very small positive number, such as &lt;span class=&quot;math-container&quot;&gt;$1\times10^{-5}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4197" LastEditorUserId="4197" LastEditDate="2022-05-25T07:03:27.897" LastActivityDate="2022-05-25T07:03:27.897" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6640" PostTypeId="2" ParentId="6594" CreationDate="2021-08-27T15:10:36.613" Score="6" Body="&lt;p&gt;Based on your input file, I tried to run the calculation in my machine. As you didn't specified how did you obtain the original structure (assembled by hand or downloaded from structure database), I first generated a SDF file of your structure with &lt;a href=&quot;https://en.wikipedia.org/wiki/Avogadro_(software)&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt;, and did a conformer search with obconformer from &lt;a href=&quot;https://en.wikipedia.org/wiki/Open_Babel&quot; rel=&quot;noreferrer&quot;&gt;Open Babel&lt;/a&gt;, just to be sure to pick a initial conformation close to a global minimum:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obconformer 2000 100 C46H39N8O.sdf &amp;gt; C46H39N8O_best_conformer.sdf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I created a input file similar to yours, but replacing the atomic coordinates with those of the best conformer I could find, and adding the line &amp;quot; \$SCF DIRSCF=.TRUE. \$END&amp;quot;, just to avoid heavy disk load as discussed in &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3672/243&quot;&gt;another question here&lt;/a&gt;. So my first modified input file was as shown bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=STO NGAUSS=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE MULT=1 ICHARG=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT OPTTOL=0.0005 NSTEP=200 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM TIMLIM=525600 MEMORY=30000000 PARALL=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;C     6.0   0.41860  -3.30490   0.31600&#xA;C     6.0   1.10200  -4.52370   0.73380&#xA;C     6.0   2.42450  -4.28410   0.78380&#xA;C     6.0   2.67500  -2.89250   0.39540&#xA;N     7.0   1.41990  -2.36510   0.23560&#xA;C     6.0   3.89300  -2.34610   0.20370&#xA;C     6.0   4.00810  -0.89640  -0.17300&#xA;C     6.0   5.30160  -0.40640  -0.68190&#xA;C     6.0   5.05870   0.89400  -0.83740&#xA;C     6.0   3.70420   1.21910  -0.44440&#xA;N     7.0   3.08680   0.02710  -0.09330&#xA;C     6.0   3.16320   2.46290  -0.38800&#xA;C     6.0   1.78790   2.65610  -0.01270&#xA;C     6.0   1.14300   3.71600   0.59850&#xA;C     6.0  -0.24560   3.46160   0.55600&#xA;C     6.0  -0.44080   2.24970  -0.08490&#xA;N     7.0   0.81320   1.72900  -0.32930&#xA;C     6.0  -1.63850   1.60250  -0.55470&#xA;C     6.0  -1.72630   0.25390  -0.68420&#xA;C     6.0  -2.86790  -0.47210  -1.20130&#xA;C     6.0  -2.73200  -1.78180  -1.01290&#xA;C     6.0  -1.40480  -1.84960  -0.38790&#xA;N     7.0  -0.80540  -0.69210  -0.27150&#xA;C     6.0  -0.89590  -3.18980   0.04360&#xA;H     1.0   0.62760  -5.46160   0.97420&#xA;H     1.0   3.17890  -4.99650   1.07840&#xA;H     1.0   1.24780  -1.39800  -0.02880&#xA;H     1.0   6.20030  -0.95600  -0.88630&#xA;H     1.0   5.77840   1.60660  -1.21090&#xA;H     1.0   1.62360   4.60840   0.97960&#xA;H     1.0  -1.03010   4.12500   0.89730&#xA;H     1.0   0.99550   0.81810  -0.73260&#xA;H     1.0  -3.72340  -0.01020  -1.67100&#xA;H     1.0  -3.39930  -2.57860  -1.27710&#xA;C     6.0   5.09930  -3.17940   0.24060&#xA;C     6.0   5.33760  -4.21240  -0.76950&#xA;C     6.0   7.34990  -4.84480   0.33370&#xA;C     6.0   6.01250  -3.04610   1.22980&#xA;C     6.0   7.19050  -3.89900   1.27580&#xA;C     6.0   6.57730  -6.17400  -1.61860&#xA;N     7.0   6.45010  -5.03620  -0.71060&#xA;H     1.0   7.62650  -6.36620  -1.86580&#xA;H     1.0   6.04580  -5.99540  -2.56060&#xA;H     1.0   6.15630  -7.07230  -1.15420&#xA;C     6.0   4.00990   3.64960  -0.68460&#xA;C     6.0   5.15900   4.03920   0.13990&#xA;C     6.0   3.70200   4.45190  -1.73110&#xA;C     6.0   4.48900   5.63560  -2.03240&#xA;N     7.0   5.93110   5.15330  -0.17120&#xA;C     6.0   5.54380   5.93410  -1.25720&#xA;C     6.0  -2.82270   2.44170  -0.86750&#xA;C     6.0  -2.82510   3.44000  -1.93690&#xA;N     7.0  -3.95940   4.19450  -2.21580&#xA;C     6.0  -5.08590   4.00550  -1.41900&#xA;C     6.0  -3.94570   2.33460  -0.11600&#xA;C     6.0  -5.12750   3.12490  -0.40690&#xA;C     6.0  -3.91230   5.27840  -3.19350&#xA;H     1.0  -4.88250   5.40460  -3.68690&#xA;H     1.0  -3.17110   5.08010  -3.97540&#xA;H     1.0  -3.65020   6.21960  -2.69830&#xA;C     6.0  -1.80030  -4.35770   0.16170&#xA;C     6.0  -2.46430  -4.61430   1.36570&#xA;C     6.0  -3.29040  -5.73860   1.50590&#xA;C     6.0  -3.47450  -6.62770   0.44370&#xA;C     6.0  -2.81370  -6.36800  -0.76480&#xA;C     6.0  -1.98080  -5.24840  -0.90450&#xA;N     7.0  -4.28310  -7.78400   0.51290&#xA;C     6.0  -5.00990  -8.24260   1.59660&#xA;C     6.0  -5.75030  -9.52020   1.29710&#xA;H     1.0  -6.48430  -9.35060   0.50470&#xA;H     1.0  -6.27980  -9.85850   2.19530&#xA;H     1.0  -5.04800 -10.30200   0.99580&#xA;O     8.0  -5.08920  -7.71850   2.70470&#xA;C     6.0   6.99280   5.59990   0.72850&#xA;H     1.0   6.58200   6.27190   1.48970&#xA;H     1.0   7.77730   6.13550   0.18170&#xA;H     1.0   7.46870   4.75240   1.23410&#xA;H     1.0  -4.33120  -8.34650  -0.32950&#xA;H     1.0   4.61530  -4.40300  -1.55610&#xA;H     1.0   7.90580  -3.76690   2.07770&#xA;H     1.0   8.20090  -5.51870   0.34110&#xA;H     1.0   5.89450  -2.31560   2.02460&#xA;H     1.0   5.42530   3.48250   1.03100&#xA;H     1.0   4.19970   6.26210  -2.86720&#xA;H     1.0   6.15030   6.81630  -1.43690&#xA;H     1.0   2.84840   4.24770  -2.36970&#xA;H     1.0  -1.92590   3.65640  -2.50250&#xA;H     1.0  -5.94130   4.62570  -1.66740&#xA;H     1.0  -6.01410   2.98860   0.19980&#xA;H     1.0  -4.00490   1.64550   0.72110&#xA;H     1.0  -1.46770  -5.08290  -1.85000&#xA;H     1.0  -2.33390  -3.94840   2.21780&#xA;H     1.0  -3.77150  -5.89310   2.46710&#xA;H     1.0  -2.92930  -7.03750  -1.61360&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But then I ran into the same error you encountered, failure to converge SCF:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;...... END OF PROPERTY EVALUATION ......&#xA; CPU     0: STEP CPU TIME=     0.12 TOTAL CPU TIME=         79.1 (      1.3 MIN)&#xA; TOTAL WALL CLOCK TIME=         80.3 SECONDS, CPU UTILIZATION IS    98.56%&#xA;&#xA;           ***** FAILURE TO LOCATE STATIONARY POINT, SCF HAS NOT CONVERGED&#xA;     UPDATED HESSIAN, GEOMETRY, AND VECTORS WILL BE PUNCHED FOR RESTART&#xA; EXECUTION OF GAMESS TERMINATED -ABNORMALLY- AT 10:44:44 27-AUG-2021    &#xA;              1154292  WORDS OF DYNAMIC MEMORY USED&#xA; CPU     0: STEP CPU TIME=     0.00 TOTAL CPU TIME=         79.1 (      1.3 MIN)&#xA; TOTAL WALL CLOCK TIME=         80.3 SECONDS, CPU UTILIZATION IS    98.54%&#xA; DDI Process 0: error code 911&#xA; ddikick.x: application process 0 quit unexpectedly.&#xA; ddikick.x: Fatal error detected.&#xA; The error is most likely to be in the application, so check for&#xA; input errors, disk space, memory needs, application bugs, etc.&#xA; ddikick.x will now clean up all processes, and exit...&#xA; DDI Process 2: terminated upon request.&#xA; DDI Process 1: terminated upon request.&#xA; ddikick.x: Sending kill signal to DDI processes.&#xA; ddikick.x: Execution terminated due to error(s).&#xA;unset echo&#xA;----- accounting info -----&#xA;Files used on the master node user-PC were:&#xA;-rw-rw-r-- 1 user user     3996 ago 27 10:43 /tmp/C46H39N8O_best_conformer.F05&#xA;-rw-rw-r-- 1 user user 10143200 ago 27 10:44 /tmp/C46H39N8O_best_conformer.F10&#xA;ls: No match.&#xA;ls: No match.&#xA;ls: No match.&#xA;sex 27 ago 2021 10:44:46 -03&#xA;0.112u 0.032s 1:22.91 0.1%  0+0k 2768+24io 13pf+0w&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In my second attempt I followed the advice given by @NikeDattani in his answer, increasing the maximum number of SCF cycles by adding MAXIT=60 to the  \$CONTRL group, what doubles the limit, from the default (30):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=STO NGAUSS=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE MULT=1 ICHARG=3 MAXIT=60 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT OPTTOL=0.0005 NSTEP=200 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM TIMLIM=525600 MEMORY=30000000 PARALL=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;C     6.0   0.41860  -3.30490   0.31600&#xA;C     6.0   1.10200  -4.52370   0.73380&#xA;C     6.0   2.42450  -4.28410   0.78380&#xA;C     6.0   2.67500  -2.89250   0.39540&#xA;N     7.0   1.41990  -2.36510   0.23560&#xA;C     6.0   3.89300  -2.34610   0.20370&#xA;C     6.0   4.00810  -0.89640  -0.17300&#xA;C     6.0   5.30160  -0.40640  -0.68190&#xA;C     6.0   5.05870   0.89400  -0.83740&#xA;C     6.0   3.70420   1.21910  -0.44440&#xA;N     7.0   3.08680   0.02710  -0.09330&#xA;C     6.0   3.16320   2.46290  -0.38800&#xA;C     6.0   1.78790   2.65610  -0.01270&#xA;C     6.0   1.14300   3.71600   0.59850&#xA;C     6.0  -0.24560   3.46160   0.55600&#xA;C     6.0  -0.44080   2.24970  -0.08490&#xA;N     7.0   0.81320   1.72900  -0.32930&#xA;C     6.0  -1.63850   1.60250  -0.55470&#xA;C     6.0  -1.72630   0.25390  -0.68420&#xA;C     6.0  -2.86790  -0.47210  -1.20130&#xA;C     6.0  -2.73200  -1.78180  -1.01290&#xA;C     6.0  -1.40480  -1.84960  -0.38790&#xA;N     7.0  -0.80540  -0.69210  -0.27150&#xA;C     6.0  -0.89590  -3.18980   0.04360&#xA;H     1.0   0.62760  -5.46160   0.97420&#xA;H     1.0   3.17890  -4.99650   1.07840&#xA;H     1.0   1.24780  -1.39800  -0.02880&#xA;H     1.0   6.20030  -0.95600  -0.88630&#xA;H     1.0   5.77840   1.60660  -1.21090&#xA;H     1.0   1.62360   4.60840   0.97960&#xA;H     1.0  -1.03010   4.12500   0.89730&#xA;H     1.0   0.99550   0.81810  -0.73260&#xA;H     1.0  -3.72340  -0.01020  -1.67100&#xA;H     1.0  -3.39930  -2.57860  -1.27710&#xA;C     6.0   5.09930  -3.17940   0.24060&#xA;C     6.0   5.33760  -4.21240  -0.76950&#xA;C     6.0   7.34990  -4.84480   0.33370&#xA;C     6.0   6.01250  -3.04610   1.22980&#xA;C     6.0   7.19050  -3.89900   1.27580&#xA;C     6.0   6.57730  -6.17400  -1.61860&#xA;N     7.0   6.45010  -5.03620  -0.71060&#xA;H     1.0   7.62650  -6.36620  -1.86580&#xA;H     1.0   6.04580  -5.99540  -2.56060&#xA;H     1.0   6.15630  -7.07230  -1.15420&#xA;C     6.0   4.00990   3.64960  -0.68460&#xA;C     6.0   5.15900   4.03920   0.13990&#xA;C     6.0   3.70200   4.45190  -1.73110&#xA;C     6.0   4.48900   5.63560  -2.03240&#xA;N     7.0   5.93110   5.15330  -0.17120&#xA;C     6.0   5.54380   5.93410  -1.25720&#xA;C     6.0  -2.82270   2.44170  -0.86750&#xA;C     6.0  -2.82510   3.44000  -1.93690&#xA;N     7.0  -3.95940   4.19450  -2.21580&#xA;C     6.0  -5.08590   4.00550  -1.41900&#xA;C     6.0  -3.94570   2.33460  -0.11600&#xA;C     6.0  -5.12750   3.12490  -0.40690&#xA;C     6.0  -3.91230   5.27840  -3.19350&#xA;H     1.0  -4.88250   5.40460  -3.68690&#xA;H     1.0  -3.17110   5.08010  -3.97540&#xA;H     1.0  -3.65020   6.21960  -2.69830&#xA;C     6.0  -1.80030  -4.35770   0.16170&#xA;C     6.0  -2.46430  -4.61430   1.36570&#xA;C     6.0  -3.29040  -5.73860   1.50590&#xA;C     6.0  -3.47450  -6.62770   0.44370&#xA;C     6.0  -2.81370  -6.36800  -0.76480&#xA;C     6.0  -1.98080  -5.24840  -0.90450&#xA;N     7.0  -4.28310  -7.78400   0.51290&#xA;C     6.0  -5.00990  -8.24260   1.59660&#xA;C     6.0  -5.75030  -9.52020   1.29710&#xA;H     1.0  -6.48430  -9.35060   0.50470&#xA;H     1.0  -6.27980  -9.85850   2.19530&#xA;H     1.0  -5.04800 -10.30200   0.99580&#xA;O     8.0  -5.08920  -7.71850   2.70470&#xA;C     6.0   6.99280   5.59990   0.72850&#xA;H     1.0   6.58200   6.27190   1.48970&#xA;H     1.0   7.77730   6.13550   0.18170&#xA;H     1.0   7.46870   4.75240   1.23410&#xA;H     1.0  -4.33120  -8.34650  -0.32950&#xA;H     1.0   4.61530  -4.40300  -1.55610&#xA;H     1.0   7.90580  -3.76690   2.07770&#xA;H     1.0   8.20090  -5.51870   0.34110&#xA;H     1.0   5.89450  -2.31560   2.02460&#xA;H     1.0   5.42530   3.48250   1.03100&#xA;H     1.0   4.19970   6.26210  -2.86720&#xA;H     1.0   6.15030   6.81630  -1.43690&#xA;H     1.0   2.84840   4.24770  -2.36970&#xA;H     1.0  -1.92590   3.65640  -2.50250&#xA;H     1.0  -5.94130   4.62570  -1.66740&#xA;H     1.0  -6.01410   2.98860   0.19980&#xA;H     1.0  -4.00490   1.64550   0.72110&#xA;H     1.0  -1.46770  -5.08290  -1.85000&#xA;H     1.0  -2.33390  -3.94840   2.21780&#xA;H     1.0  -3.77150  -5.89310   2.46710&#xA;H     1.0  -2.92930  -7.03750  -1.61360&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With this I was able to finish the calculation successfully. The first SCF cycle took 35 iterations to converge, a bit over the default limit:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;......END OF GEOMETRY SEARCH......&#xA; CPU     0: STEP CPU TIME=     0.08 TOTAL CPU TIME=       2025.0 (     33.8 MIN)&#xA; TOTAL WALL CLOCK TIME=       2046.8 SECONDS, CPU UTILIZATION IS    98.94%&#xA;              1154292  WORDS OF DYNAMIC MEMORY USED&#xA; EXECUTION OF GAMESS TERMINATED NORMALLY 11:36:53 27-AUG-2021    &#xA; DDI: 263640 bytes (0.3 MB / 0 MWords) used by master data server.&#xA;&#xA; ----------------------------------------&#xA; CPU timing information for all processes&#xA; ========================================&#xA; 0: 2016.668 + 8.342 = 2025.10&#xA; 1: 2009.392 + 8.384 = 2017.776&#xA; 2: 2010.217 + 6.687 = 2016.905&#xA; ----------------------------------------&#xA; ddikick.x: exited gracefully.&#xA;unset echo&#xA;----- accounting info -----&#xA;Files used on the master node user-PC were:&#xA;-rw-rw-r-- 1 user user     4005 ago 27 11:02 /tmp/C46H39N8O_best_conformer_scf60.F05&#xA;-rw-rw-r-- 1 user user 10241360 ago 27 11:36 /tmp/C46H39N8O_best_conformer_scf60.F10&#xA;ls: No match.&#xA;ls: No match.&#xA;ls: No match.&#xA;sex 27 ago 2021 11:36:56 -03&#xA;0.123u 0.010s 34:09.93 0.0%     0+0k 0+32io 0pf+0w&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The optimized geometry I found is shown bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      ***** EQUILIBRIUM GEOMETRY LOCATED *****&#xA; COORDINATES OF ALL ATOMS ARE (ANGS)&#xA;   ATOM   CHARGE       X              Y              Z&#xA; ------------------------------------------------------------&#xA; C           6.0   0.4670707680  -3.3552994825   0.1507280614&#xA; C           6.0   1.1588544563  -4.6338783718   0.4445871557&#xA; C           6.0   2.4689515383  -4.4395943535   0.4541873257&#xA; C           6.0   2.7562370062  -3.0091345193   0.1743635960&#xA; N           7.0   1.5156307238  -2.4081016375   0.0266144568&#xA; C           6.0   3.9719116669  -2.4023232928   0.0699346952&#xA; C           6.0   4.1405832586  -0.9644046019  -0.1600003936&#xA; C           6.0   5.4756194557  -0.3454977898  -0.4364880003&#xA; C           6.0   5.2790151208   0.9487939050  -0.5948465975&#xA; C           6.0   3.8224457041   1.1994350671  -0.4111569799&#xA; N           7.0   3.1653624898  -0.0733429468  -0.1746656501&#xA; C           6.0   3.2131860874   2.4010969967  -0.4378266471&#xA; C           6.0   1.7672389380   2.6554884179  -0.3133471273&#xA; C           6.0   1.1332781145   3.8551546052  -0.0713582931&#xA; C           6.0  -0.2507525509   3.6384497899  -0.1139104189&#xA; C           6.0  -0.4682879581   2.3055153479  -0.3838216106&#xA; N           7.0   0.7750275545   1.7027871421  -0.4979505168&#xA; C           6.0  -1.7468027986   1.5998399162  -0.5865430539&#xA; C           6.0  -1.9116339609   0.2647953389  -0.5994588091&#xA; C           6.0  -3.1821261231  -0.4763219558  -0.8388994600&#xA; C           6.0  -2.9257325274  -1.7565880622  -0.6544317854&#xA; C           6.0  -1.4716213631  -1.8669966678  -0.3121022621&#xA; N           7.0  -0.8590506810  -0.7022080072  -0.3165959982&#xA; C           6.0  -0.8541201662  -3.1777547335  -0.0061204650&#xA; H           1.0   0.6291084008  -5.5607129561   0.6224905515&#xA; H           1.0   3.2311470499  -5.1734400558   0.6576256324&#xA; H           1.0   1.3887951614  -1.4034432947  -0.0961927507&#xA; H           1.0   6.4056173353  -0.8859732005  -0.5168353875&#xA; H           1.0   6.0133099933   1.7000523593  -0.8377011545&#xA; H           1.0   1.6154633754   4.7976054509   0.1285275782&#xA; H           1.0  -1.0098946530   4.3833914876   0.0530459525&#xA; H           1.0   0.9215494399   0.6929455612  -0.5952873091&#xA; H           1.0  -4.1176741983  -0.0238319094  -1.1255705275&#xA; H           1.0  -3.5951921601  -2.6001830701  -0.7402330786&#xA; C           6.0   5.2062931648  -3.2539791268   0.1968439888&#xA; C           6.0   5.4345540416  -4.2996656313  -0.6881651055&#xA; C           6.0   7.4564151939  -4.9104627605   0.3962751372&#xA; C           6.0   6.1715756891  -3.0573006214   1.2012524545&#xA; C           6.0   7.2900117884  -3.8794176402   1.2991235245&#xA; C           6.0   6.7075649458  -6.2571245757  -1.5522415989&#xA; N           7.0   6.5324185192  -5.1115755044  -0.5894160954&#xA; H           1.0   7.7716647339  -6.3907547483  -1.7452654634&#xA; H           1.0   6.1855611903  -6.0173075948  -2.4773936225&#xA; H           1.0   6.2885912437  -7.1618015633  -1.1048650881&#xA; C           6.0   4.0351172403   3.6556082505  -0.6671988984&#xA; C           6.0   5.0705942148   4.0202936679   0.1769952752&#xA; C           6.0   3.7622782712   4.5050886825  -1.7549623535&#xA; C           6.0   4.5118858743   5.6548011229  -1.9746306092&#xA; N           7.0   5.8148660896   5.1507795630  -0.0456114931&#xA; C           6.0   5.5410466764   5.9655184978  -1.1067795480&#xA; C           6.0  -2.9513482825   2.4931116417  -0.8040307568&#xA; C           6.0  -2.9560562783   3.4260904715  -1.8297332327&#xA; N           7.0  -4.0348848243   4.2347357727  -2.0632659425&#xA; C           6.0  -5.1515451254   4.1458524398  -1.2778204428&#xA; C           6.0  -4.0992511240   2.4185675772   0.0024204078&#xA; C           6.0  -5.1984888766   3.2399670026  -0.2384935236&#xA; C           6.0  -3.9872304236   5.2568474916  -3.1689140647&#xA; H           1.0  -4.9688732350   5.3074177934  -3.6405070772&#xA; H           1.0  -3.2373700226   4.9493588835  -3.8957744772&#xA; H           1.0  -3.7250311799   6.2272056385  -2.7404039003&#xA; C           6.0  -1.7796374651  -4.3696310302   0.1289365796&#xA; C           6.0  -2.4851314791  -4.5928304737   1.3084203425&#xA; C           6.0  -3.3227346391  -5.6822895359   1.4495100316&#xA; C           6.0  -3.4807749020  -6.5863546324   0.3923217964&#xA; C           6.0  -2.7794390275  -6.3593149327  -0.7984059247&#xA; C           6.0  -1.9420651035  -5.2692015437  -0.9215120564&#xA; N           7.0  -4.3303193356  -7.7167938506   0.4780566884&#xA; C           6.0  -5.0441563383  -8.1844319953   1.6296607490&#xA; C           6.0  -5.7966048821  -9.5013881185   1.3551089539&#xA; H           1.0  -6.5125343745  -9.3647235413   0.5491391298&#xA; H           1.0  -6.3232601112  -9.8056646733   2.2533226070&#xA; H           1.0  -5.0965328402 -10.2824153924   1.0714207460&#xA; O           8.0  -5.0495580137  -7.5930429013   2.6938406681&#xA; C           6.0   6.9223323747   5.5243219559   0.9064200048&#xA; H           1.0   6.5230737524   6.1983745084   1.6677805024&#xA; H           1.0   7.7118231089   6.0198094112   0.3411000509&#xA; H           1.0   7.3056035494   4.6157354939   1.3685263928&#xA; H           1.0  -4.3588141998  -8.3149668203  -0.3458960881&#xA; H           1.0   4.7524718717  -4.5278223370  -1.5042538440&#xA; H           1.0   8.0295458045  -3.7349956645   2.0782600222&#xA; H           1.0   8.3030442874  -5.5955645782   0.4190807020&#xA; H           1.0   6.0369991829  -2.2532588197   1.9211273287&#xA; H           1.0   5.3458015582   3.4378444187   1.0540054726&#xA; H           1.0   4.3086212165   6.3105131733  -2.8136498157&#xA; H           1.0   6.1691685170   6.8493372179  -1.2191039501&#xA; H           1.0   2.9523433434   4.2538428125  -2.4358062564&#xA; H           1.0  -2.1092162398   3.5600091100  -2.4988273991&#xA; H           1.0  -5.9725452929   4.8204810613  -1.5208509855&#xA; H           1.0  -6.0895834320   3.1828816102   0.3768112030&#xA; H           1.0  -4.1294840212   1.7114112541   0.8288813738&#xA; H           1.0  -1.4078347920  -5.1149991579  -1.8511763110&#xA; H           1.0  -2.3732586854  -3.9059428186   2.1390277103&#xA; H           1.0  -3.8595693161  -5.8529255892   2.3709361837&#xA; H           1.0  -2.8980480782  -7.0470788280  -1.6247108319&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As your molecule has a charge of +3, I also tested starting a run including solvation effects, instead of increasing MAXIT, by including the line &amp;quot; \$PCM SOLVNT=H2O \$END&amp;quot; in your original input file, as shown bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$BASIS GBASIS=STO NGAUSS=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF RUNTYP=OPTIMIZE MULT=1 ICHARG=3 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$STATPT OPTTOL=0.0005 NSTEP=200 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM TIMLIM=525600 MEMORY=30000000 PARALL=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIRSCF=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$PCM SOLVNT=H2O $&lt;/span&gt;END&#xA; &#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA &#xA;Title&#xA;C1&#xA;C     6.0     0.44525    -3.16984     0.69612&#xA;C     6.0     1.01573    -4.03321     1.61274&#xA;C     6.0     2.41072    -3.80725     1.61097&#xA;C     6.0     2.67608    -2.82362     0.67533&#xA;N     7.0     1.45795    -2.36971     0.21750&#xA;C     6.0     3.90546    -2.34686     0.10991&#xA;C     6.0     4.05712    -1.04579    -0.23679&#xA;C     6.0     5.21540    -0.44191    -0.85574&#xA;C     6.0     5.05403     0.87344    -0.99275&#xA;C     6.0     3.70858     1.06810    -0.43356&#xA;N     7.0     3.13224    -0.03282    -0.03960&#xA;C     6.0     3.16875     2.46275    -0.34431&#xA;C     6.0     1.83356     2.65144    -0.33629&#xA;C     6.0     1.15168     3.94223    -0.27795&#xA;C     6.0    -0.17973     3.74202    -0.29816&#xA;C     6.0    -0.44459     2.30513    -0.36740&#xA;N     7.0     0.80858     1.73703    -0.38199&#xA;C     6.0    -1.66025     1.72152    -0.50118&#xA;C     6.0    -1.74252     0.22603    -0.45510&#xA;C     6.0    -2.99115    -0.38252    -0.93654&#xA;C     6.0    -2.74372    -1.67799    -0.75080&#xA;C     6.0    -1.41952    -1.88040    -0.19917&#xA;N     7.0    -0.83234    -0.62964    -0.07998&#xA;C     6.0    -0.88336    -3.06808     0.16991&#xA;H     1.0     0.48692    -4.78481     2.18676&#xA;H     1.0     3.14281    -4.35524     2.19072&#xA;H     1.0     1.32408    -1.59926    -0.42603&#xA;H     1.0     6.09460    -0.97630    -1.18243&#xA;H     1.0     5.71915     1.59050    -1.43500&#xA;H     1.0     1.62190     4.91198    -0.23985&#xA;H     1.0    -0.91995     4.52597    -0.27506&#xA;H     1.0     0.95387     0.73081    -0.31926&#xA;H     1.0    -3.86702     0.07728    -1.35203&#xA;H     1.0    -3.43575    -2.47239    -0.99291&#xA;C     6.0     5.01165    -3.32684    -0.09860&#xA;C     6.0     4.80323    -4.43424    -0.92915&#xA;C     6.0     6.92926    -5.30155    -0.40954&#xA;C     6.0     6.21677    -3.24050     0.60124&#xA;C     6.0     7.18305    -4.22849     0.43747&#xA;C     6.0     5.48783    -6.55588    -1.93242&#xA;N     7.0     5.75586    -5.38564    -1.07564&#xA;H     1.0     6.43367    -6.93986    -2.32293&#xA;H     1.0     4.85110    -6.24747    -2.76568&#xA;H     1.0     4.98761    -7.30560    -1.31455&#xA;C     6.0     4.09828     3.60885    -0.24634&#xA;C     6.0     4.66088     3.95246     0.98833&#xA;C     6.0     4.41857     4.37817    -1.36593&#xA;C     6.0     5.28427     5.45895    -1.23237&#xA;N     7.0     5.50715     5.00575     1.09501&#xA;C     6.0     5.81916     5.75962     0.01557&#xA;C     6.0    -2.90380     2.52166    -0.34897&#xA;C     6.0    -3.66129     2.56849     0.82733&#xA;N     7.0    -4.81632     3.27544     0.88045&#xA;C     6.0    -5.27208     3.94587    -0.20273&#xA;C     6.0    -3.36321     3.21702    -1.46861&#xA;C     6.0    -4.55383     3.93261    -1.39330&#xA;C     6.0    -5.60984     3.29056     2.12518&#xA;H     1.0    -6.11974     4.25361     2.21048&#xA;H     1.0    -4.94027     3.15848     2.97883&#xA;H     1.0    -6.32923     2.47041     2.06314&#xA;C     6.0    -1.71894    -4.29132     0.03909&#xA;C     6.0    -1.71807    -5.02753    -1.14744&#xA;C     6.0    -2.51092    -6.17434    -1.26052&#xA;C     6.0    -3.31052    -6.61750    -0.19482&#xA;C     6.0    -3.30480    -5.87783     0.98628&#xA;C     6.0    -2.51580    -4.72439     1.10405&#xA;N     7.0    -4.05948    -7.78149    -0.43353&#xA;C     6.0    -4.89310    -8.55874     0.31080&#xA;C     6.0    -5.16776    -8.28274     1.75727&#xA;H     1.0    -4.23558    -8.26628     2.32654&#xA;H     1.0    -5.79022    -9.08611     2.16452&#xA;H     1.0    -5.71925    -7.34591     1.86399&#xA;O     8.0    -5.42168    -9.52251    -0.25008&#xA;C     6.0     6.07588     5.36035     2.41047&#xA;H     1.0     5.41546     6.10513     2.86119&#xA;H     1.0     7.08124     5.76404     2.26527&#xA;H     1.0     6.13218     4.46273     3.03142&#xA;H     1.0    -3.99409    -8.17283    -1.36812&#xA;H     1.0     3.86903    -4.58358    -1.46487&#xA;H     1.0     8.12201    -4.17578     0.98576&#xA;H     1.0     7.65002    -6.10332    -0.54924&#xA;H     1.0     6.39871    -2.42357     1.29876&#xA;H     1.0     4.43770     3.40075     1.89831&#xA;H     1.0     5.53797     6.07004    -2.09755&#xA;H     1.0     6.49265     6.60082     0.16210&#xA;H     1.0     3.99352     4.14840    -2.34365&#xA;H     1.0    -3.36137     2.04034     1.72923&#xA;H     1.0    -6.21197     4.48444    -0.10738&#xA;H     1.0    -4.92606     4.47294    -2.26256&#xA;H     1.0    -2.80635     3.19914    -2.40612&#xA;H     1.0    -2.52664    -4.17043     2.04095&#xA;H     1.0    -1.10653    -4.71768    -1.99108&#xA;H     1.0    -2.49054    -6.72496    -2.19955&#xA;H     1.0    -3.89964    -6.14606     1.84813&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I did this because solvation help stabilize charged species, so perhaps it could converge more easily under solvation, rather than in a vacuum. Under those conditions it didn't get stuck in the first SCF cycle with the default maximum 30 iterations. But I didn't finish this run, as it would probably take far more time.&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2021-08-27T15:10:36.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6641" PostTypeId="1" AcceptedAnswerId="6652" CreationDate="2021-08-28T09:47:56.683" Score="8" ViewCount="601" Body="&lt;p&gt;In addition to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6603/what-is-the-source-of-this-band-structure-and-dos-inconsistency&quot;&gt;post&lt;/a&gt;, The used settings were :&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;DOS:&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISMEAR = -5&#xA;SIGMA = 0.2 (default value)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;BS:&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISMEAR = 0&#xA;SIGMA = 0.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, This settings have lead to the same exact Band-gap stats, but the Fermi energy isn't the same. I am wondering which one of them leads to the correct &lt;span class=&quot;math-container&quot;&gt;$E_{Fermi}$&lt;/span&gt; value.&lt;/p&gt;&#xA;&lt;p&gt;Could I adopt the &lt;span class=&quot;math-container&quot;&gt;$E_{Fermi}$&lt;/span&gt; value of one calculation for the other when plotting the results as suggested &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=3750&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; in the last answer.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-08-28T10:57:15.500" LastActivityDate="2021-09-01T03:18:37.797" Title="If Gaussian and Tetrahedron smearing method lead to different Fermi energies, which one is the correct?" Tags="|vasp|band-structure|density-of-states|fermi-energy|smearing|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6642" PostTypeId="1" AcceptedAnswerId="6651" CreationDate="2021-08-29T11:55:11.977" Score="9" ViewCount="94" Body="&lt;p&gt;A &lt;em&gt;&lt;strong&gt;Half-Semiconductor&lt;/strong&gt;&lt;/em&gt; is a material with a &lt;em&gt;&lt;code&gt;narrow&lt;/code&gt;&lt;/em&gt; band-gap for one spin channel and a &lt;em&gt;&lt;code&gt;wide&lt;/code&gt;&lt;/em&gt; band-gap for the other channel.&#xA;Knowing that for this material :&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{gap}(up)$&lt;/span&gt; = 0.9609 eV&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{gap}(down)$&lt;/span&gt; = 2.4974 eV&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Can I consider the spin-up gap as narrow, and the spin-down as wide and call it  a Half-Semiconductor material ?&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-09-01T03:16:39.457" Title="Can these Band-gap specifications be attributed to a Half-Semiconductor material?" Tags="|vasp|band-structure|spintronics|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6643" PostTypeId="2" ParentId="6642" CreationDate="2021-08-30T02:27:18.920" Score="5" Body="&lt;p&gt;I think you will be hard pressed to find a definitive answer, however I would say you are within reason to call it a half semiconductor.  Just be aware that this doesn't seem to be a well defined term and you may need to give the audience / reader a prompting on what you mean by half semiconductor.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-08-30T02:27:18.920" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6644" PostTypeId="1" CreationDate="2021-08-30T08:41:35.510" Score="8" ViewCount="825" Body="&lt;p&gt;I have been using Quantum ESPRESSO for my calculations and I do most of my processing in Linux. Recently I bought a new laptop and it came with Windows and I need to keep it like that for several reasons. I realized that there aren't many options to visualize structures from Quantum ESPRESSO input in Windows!&lt;/p&gt;&#xA;&lt;p&gt;I know of VESTA but that one doesn't read QE input or output files. I found atomsk which I installed in the WSL (Windows subsystem for Linux) and used it to convert a QE input file to a VESTA format but it didn't do it correctly and the structure was not showing correctly in VESTA.&lt;/p&gt;&#xA;&lt;p&gt;Xcrysden doesn't work in Windows and only works with errors when run from WSL (with a display server).&lt;/p&gt;&#xA;&lt;p&gt;The question is: are there any good visualization software for QE input/output files for Windows? And why not, for Linux? (xcrysden is good-ish but it could do with an update).&lt;/p&gt;&#xA;&lt;p&gt;Cheers.&lt;/p&gt;&#xA;" OwnerUserId="843" LastEditorUserId="5" LastEditDate="2021-08-30T10:30:30.330" LastActivityDate="2021-08-31T00:15:07.527" Title="Structure visualization software for Windows" Tags="|quantum-espresso|software-recommendations|visualization-software|windows-operating-system|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6645" PostTypeId="2" ParentId="6391" CreationDate="2021-08-30T14:19:01.353" Score="6" Body="&lt;p&gt;Following Nike and Tyberius's suggestions, I rewrite my comment into an answer.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, it is obvious that when the volume of the simulation box is sufficiently large, then a significant fraction of the box must be gaseous. Secondly, note that the simulation box has a finite size, so that when the equilibrium pressure of the gas is sufficiently low, it may well be that there is not even a single gaseous molecule during the whole simulation, and all molecules cluster together as a solid, a liquid, or a mixture of solid and liquid.&lt;/p&gt;&#xA;&lt;p&gt;But even if this happens, it does not mean that the real material is a very porous, uniform mixture of small particles/droplets and vacuum. The reason why in your simulation the material behaves as such, is that you have employed the PBC. When the PBC is active, any particle that is much smaller than the size of the box cannot meet and merge with its periodic image (otherwise the PBC is violated), so that once all molecules in a box forms a single cluster, the condensing process stops there. While in reality, there is no such thing as the PBC, and the particles/droplets are free to find each other and merge, until you end up with macroscopic rain drops or snowflakes. Unfortunately, in calculations you must either only consider a microscopic number of molecules, or use the PBC, due to computational cost considerations, which means that you have to live with such artifacts of the simulation.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-08-30T14:19:01.353" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6646" PostTypeId="2" ParentId="6644" CreationDate="2021-08-31T00:15:07.527" Score="9" Body="&lt;p&gt;You can install xcrysden using Xming and Cygwin without resorting to WSL and it worked well for me.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Install &lt;a href=&quot;https://sourceforge.net/projects/xming/&quot; rel=&quot;noreferrer&quot;&gt;XMing&lt;/a&gt; and RUN&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Install &lt;a href=&quot;https://cygwin.com/&quot; rel=&quot;noreferrer&quot;&gt;CYGWIN&lt;/a&gt; with the following packages:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;    tcl-tk, tcl-togl, fftw3, libGL1, xorg-server, bash, bc,coreutils, grep, gzip&#xA;    &#xA;    less, util-linux, ImageMagick, tcl-tk8.6, tcl-togl, ImageMagick, xinit, mesa&#xA;    &#xA;    libfftw3_3, libgfortran4, libGLU1, gawk&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;In user folder of Cygwin, copy and untar the XCrySDen package:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;untar: tar xvzf {name package}.tar.gz&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Copy the file &lt;strong&gt;libTogl2.0.dll&lt;/strong&gt; to &lt;strong&gt;&amp;quot;.\cygwin64\bin&amp;quot;&lt;/strong&gt; directory&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Edit the ~/.bashrc file and include the following:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;export DISPLAY=:0&#xA;&#xA;export PATH=$PATH:/usr/lib&#xA;&#xA;cd {folder of XCrySDen}&#xA;&#xA;./xcrysden&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;NOTE:&lt;/strong&gt; Everytime Xcrysden is used, the Xming should be live. Otherwise Xcrysden wont work.&lt;/p&gt;&#xA;&lt;p&gt;Heres the &lt;a href=&quot;https://www.youtube.com/watch?v=fUXVXPMSBMw&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt; to the youtube video I've refered to.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps :)&lt;/p&gt;&#xA;" OwnerUserId="1355" LastActivityDate="2021-08-31T00:15:07.527" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6647" PostTypeId="1" AcceptedAnswerId="6656" CreationDate="2021-08-31T07:42:04.623" Score="10" ViewCount="441" Body="&lt;p&gt;Let's say I want to find the electronic energy bands from DFT calculations in VASP along a chosen path in the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;Now, I want to make sure I choose a path that captures the conduction band minimum (and valence band maximum.) How can I find such a path?&lt;/p&gt;&#xA;&lt;p&gt;In principle, I could calculate the band structure very densely over the full Brillouin zone. This, however, sounds computationally demanding, and I still don't know how dense my grid must be.&lt;/p&gt;&#xA;" OwnerUserId="1490" LastActivityDate="2021-09-09T15:19:08.817" Title="How can I be sure that I have found the conduction band minimum in DFT?" Tags="|density-functional-theory|vasp|electronic-structure|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6648" PostTypeId="1" AcceptedAnswerId="6650" CreationDate="2021-08-31T16:12:44.313" Score="12" ViewCount="879" Body="&lt;p&gt;Over the years many open-source &lt;em&gt;ab initio&lt;/em&gt; packages have been developed and the diversity in subroutines, methods and portability (ability to interface with other software) is quite varied for different packages. While a main distinction can be drawn between packages that focus on materials and molecular systems, within these subcategories there is still a lot of variance. &lt;/p&gt;&#xA;&lt;p&gt;I have made a few notes about GAMESS, OpenMOLCAS, and Psi4 below, and I wonder about their validity:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;GAMESS&lt;/strong&gt; seems to have an old academic user base and a stable code for most traditional calculations, post-HF methods (and DFT methods), solvent continuum models etc. Another good thing seems to be its ability to be interfaced MD packages like GROMACS with PLUMED(though I haven't used it).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;OpenMOLCAS&lt;/strong&gt; has a wide range of methods implemented but, I think its not as openly available as the other packages I have mentioned here. They also have a python module pyMolcas that can be used to create workflows.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Psi4&lt;/strong&gt; seems to be attractive as the source-code openly available to the community over Github and is actively being developed by a growing user-base. It has a user-friendly python module and can be easily integrated into any code/workflows. Many parts of the code seem to be written in C/C++ and features shared memory parallelization for multi-core machines.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="5" LastEditDate="2021-09-01T00:49:49.397" LastActivityDate="2021-09-08T03:34:15.263" Title="Comparing GAMESS, OpenMOLCAS and Psi4" Tags="|software|quantum-chemistry|ab-initio-calculations|electronic-structure|open-source|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6650" PostTypeId="2" ParentId="6648" CreationDate="2021-09-01T00:46:41.630" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;GAMESS seems to have an old academic user base and a stable code for most traditional calculations&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;GAMESS has been in development since the 1970s and split into GAMESS(US) and GAMESS(UK) in 1981, whereas MOLCAS has been in development since the 1980s and Psi4 is much newer. However, I would not focus too much on the age of the software. The first commits to the GitHub repository for PySCF &lt;a href=&quot;https://github.com/pyscf/pyscf/graphs/contributors&quot; rel=&quot;noreferrer&quot;&gt;were in 2014&lt;/a&gt; but still it will be your first choice for certain things. The extra decades of history don't give GAMESS very much of a leg up &lt;em&gt;overall&lt;/em&gt; against the other software packages mentioned.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;[GAMESS is good at] post-HF methods (and DFT methods),&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;MOLCAS &lt;a href=&quot;https://www.molcas.org/documentation/manual/node110.html#SECTION052434210000000000000&quot; rel=&quot;noreferrer&quot;&gt;can do DFT&lt;/a&gt; as &lt;a href=&quot;https://psicode.org/psi4manual/master/dft.html&quot; rel=&quot;noreferrer&quot;&gt;can Psi4&lt;/a&gt;. All of them can do post-HF calculations, with MOLCAS being more geared towards multi-reference methods such as CASSCF, RASSCF, GASSCF, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1614/5&quot;&gt;LASSCF&lt;/a&gt;, CASOT2, RASPT2, etc., but still able to do coupled cluster and other things. MOLCAS also interfaces with NECI (to do FCIQMC) and QCMaquis, BLOCK, and CheMPS2 (to give 3 different options for DMRG), while Psi4 interfaces with CheMPS2 (to do DMRG) and MRCC (for arbitrary-order coupled cluster), so these programs can do a lot more of the more recently developed and closer to state-of-the-art post-SCF correlation methods.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;[GAMESS is good at] solvent continuum models etc.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;MOLCAS can &lt;a href=&quot;https://www.molcas.org/documentation/manual/node126.html&quot; rel=&quot;noreferrer&quot;&gt;be used directly for solvent continuum models&lt;/a&gt; and Psi4 &lt;a href=&quot;https://psicode.org/psi4manual/master/pcmsolver.html&quot; rel=&quot;noreferrer&quot;&gt;has an interface to PCMSolver&lt;/a&gt; for PCM (polarizable continuum model) calculations.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Another good thing [about GAMESS] seems to be its ability to be interfaced MD packages like GROMACS with PLUMED (though I haven't used it).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you want something that can interface to GROMACS and PLUMED, then maybe this is the only place that you mentioned so far where GAMESS really has the other two beat, though the MOLCAS package has the &lt;code&gt;DYNAMIX&lt;/code&gt; program &lt;a href=&quot;https://www.molcas.org/documentation/manual/node77.html&quot; rel=&quot;noreferrer&quot;&gt;which can do MD&lt;/a&gt; and it can bring you closer to quantum mechanical accuracy than GROMACS, via the &lt;a href=&quot;https://www.molcas.org/documentation/manual/node114.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;surfacehop&lt;/code&gt; program&lt;/a&gt; and the interface to  &lt;a href=&quot;https://sharc-md.org/&quot; rel=&quot;noreferrer&quot;&gt;SHARC&lt;/a&gt;. As far as I know, Psi4 does not offer MD capabilities.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;OpenMOLCAS has a wide range of methods implemented but, I think its not as openly available as the other packages I have mentioned here. [...] Psi4 seems to be attractive as the source-code openly available to the community over Github and is actively being developed by a growing user-base.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The OpenMOLCAS source is openly available at GitLab &lt;a href=&quot;https://gitlab.com/Molcas/OpenMolcas&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;: I can't see why it should be considered any less &amp;quot;openly available&amp;quot; compared to the other two. GAMESS is &lt;a href=&quot;https://en.wikipedia.org/wiki/GAMESS_(US)&quot; rel=&quot;noreferrer&quot;&gt;apparently&lt;/a&gt; not considered &amp;quot;open source&amp;quot; and is just considered &amp;quot;source-available freeware&amp;quot; due to the way it's licensed.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;[OpenMOLCAS also has] a python module pyMolcas that can be used to create workflows. [... Psi4 also] has a user-friendly python module and can be easily integrated into any code/workflows.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;While these things may be true, and you may consider them to indicate an advantage over GAMESS, I have yet to see any benefit to Python modules when doing serious quantum chemistry calculations, and I have done &lt;em&gt;&lt;strong&gt;a lot of them&lt;/strong&gt;&lt;/em&gt;. For GAMESS and MOLCAS, I would prepare an input file in VI and then run the software with scheduler via a submissions script. I can imagine a Python interface providing me with some benefits, and also some problems (in addition to those problems, I actually never managed to run a calculation in Psi4 because of its relationship to Python and the difficulties I had with installing it using the documentation's recommended process involving Anaconda and components which required Python versions higher than what I had available at the time).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Many parts of the [Psi4] code seem to be written in C/C++ and features shared memory parallelization for multi-core machines.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Any quantum chemistry software worth discussing, has parallelization implemented for multi-core machines. GAMESS and MOLCAS are written in FORTRAN, which is specifically designed for scientific computing and number crunching, whereas C/C++ were designed for more general purposes, such as for operating systems, computer games, etc. FORTRAN is arguably much easier to learn, and large FORTRAN software packages like GAMESS and OpenMOLCAS tend to be easier to install because they don't have dependencies like BOOST and Eigen which are needed for C/C++ programs to do high-performance calculations (I mentioned that I've never been able to install Psi4 because of some Python issues, but I've also struggled with installing other C/C++ software due to the delicacies associated with BOOST and Eigen versions). See this: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/365/5&quot;&gt;What is a good programming language for matter modeling?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-01T12:32:04.737" LastActivityDate="2021-09-01T12:32:04.737" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6651" PostTypeId="2" ParentId="6642" CreationDate="2021-09-01T03:03:12.527" Score="4" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;For the up-spin channel, you can absolutely consider it as a semiconductor; for the down-spin channel, you can consider it as an insulator (may someone also consider it as a semiconductor, just different conventions). Thus, you can say your material is a half-semiconductor (HSC). (HSC is a semiconductor in one spin channel but an insulator in the other spin channel.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;One more thing you should check is the band alignment (don't mix the HSG and bipolar magnetic semiconductors (BMS)), seeing (d) and (f) below:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5tLF7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5tLF7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Ref: &lt;a href=&quot;https://academic.oup.com/nsr/article/3/3/365/2236578?login=true&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://academic.oup.com/nsr/article/3/3/365/2236578?login=true&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;PS: As @Tristan Maxson said, it's hard to identify insulators (with a large bandgap) and semiconductors (with a moderate or small bandgap) with a definitive gap value.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally how you obtained these gaps listed above? DFT, HSE06, or GW? I suggest that you calculate them with HSE06 or GW. DFT usually underestimates the bandgap of the semiconductors. If the GW gap of the up-spin channel is below 1.5eV and the GW gap of the down-spin channel is above 3eV, then it must be classified into HSCs.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2021-09-01T03:16:39.457" LastActivityDate="2021-09-01T03:16:39.457" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6652" PostTypeId="2" ParentId="6641" CreationDate="2021-09-01T03:18:37.797" Score="8" Body="&lt;ul&gt;&#xA;&lt;li&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;ISMEAR=-5 gives you the correct Fermi energy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Usually, the Fermi level is set to the VBM.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;If you shift the BS by the Fermi energy from the DOS calculation with ISMEAR=-5, you will find your Fermi level is set to VBM.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2021-09-01T03:18:37.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6653" PostTypeId="1" AcceptedAnswerId="6733" CreationDate="2021-09-01T05:06:51.880" Score="7" ViewCount="177" Body="&lt;p&gt;When dealing with 2D materials and monolayer families like : transition metal trihalides, TMDCs,...etc. In which cases SOC should be included in our calculations ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-09-07T13:06:01.647" LastActivityDate="2021-09-11T21:42:08.833" Title="In which cases should SOC be included?" Tags="|spin-orbit-coupling|relativistic|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6654" PostTypeId="1" CreationDate="2021-09-01T07:31:59.217" Score="3" ViewCount="114" Body="&lt;p&gt;Starting from a &lt;span class=&quot;math-container&quot;&gt;$\ce{BaTiO3}$&lt;/span&gt; structure, I want to dope this with Strontium to obtain &lt;span class=&quot;math-container&quot;&gt;$\ce{Ba_{0.67}Sr_{0.33}TiO3}$&lt;/span&gt;. Is there a way to do this using LAMMPS?&lt;/p&gt;&#xA;&lt;p&gt;I began a discussion about this in Chinese on the &lt;a href=&quot;http://bbs.keinsci.com/thread-24926-1-1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Chemistry Commune&lt;/a&gt;. I know this can be done using a scripting language (e.g. Bash/Python) to edit my input file, but I was curious if LAMMPS or some other existing tool can already automate this process.&lt;/p&gt;&#xA;" OwnerUserId="4211" LastEditorUserId="7" LastEditDate="2021-09-01T14:26:49.753" LastActivityDate="2021-09-01T14:26:49.753" Title="Generate doped solid using LAMMPS?" Tags="|lammps|doping|" AnswerCount="0" CommentCount="7" ClosedDate="2021-12-01T19:31:23.590" ContentLicense="CC BY-SA 4.0" />
  <row Id="6656" PostTypeId="2" ParentId="6647" CreationDate="2021-09-02T07:59:48.670" Score="7" Body="&lt;p&gt;The band extrema may be at an arbitrary point in the Brillouin zone, so determining their position can become computationally demanding. The following strategy is something that is sometimes used to locate Weyl points (band crossings) in a band structure, which I think should also be useful for locating band extrema. The strategy would be:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Sample the full Brillouin zone with a uniform &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid.&lt;/li&gt;&#xA;&lt;li&gt;Locate the band extrema in your &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid.&lt;/li&gt;&#xA;&lt;li&gt;Sample a patch of the Brillouin zone around the band extrema of your previous grid.&lt;/li&gt;&#xA;&lt;li&gt;Iterate until convergence of the location of the band extrema.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are still some choices to be made (density of sampling grids, size of patches), and I imagine this will require some trial-and-error as ideal values will depend on the specific band structure (effective masses, bandwidth).&lt;/p&gt;&#xA;&lt;p&gt;The approach does sound computationally demanding, but you should be able to diagonalize the Hamiltonian over the required &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grids in a non-self-consistent manner, which should accelerate the calculations.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-09-02T07:59:48.670" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6657" PostTypeId="1" AcceptedAnswerId="6659" CreationDate="2021-09-02T08:58:11.480" Score="8" ViewCount="1052" Body="&lt;p&gt;I have read the paper of &amp;quot;&lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0211443.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;A bird's-eye view of density-functional theory [PDF]&lt;/a&gt;&amp;quot; and I have a question about the &lt;strong&gt;functional derivative&lt;/strong&gt; of the energy by the density.&lt;/p&gt;&#xA;&lt;p&gt;I have found the following equation in the paper and attached the screenshot as follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/D73yv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/D73yv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is the derivative of the energy functional with respect to the density, and the right side of this equation contains the external potential and Hartree potential terms. Each term is a scalar value at a position &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, I think this equation means that this derivative is &lt;strong&gt;zero at each position (all positions)&lt;/strong&gt;. For example, if I make a finite grid points and get &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; points (e.g., &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt;, ... &lt;span class=&quot;math-container&quot;&gt;$r_G$&lt;/span&gt;), I believe that the grid points have the derivatives and they are zero as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;δE/δn(r_1) = δE/δn(r_2) = ... = δE/δn(r_G) = 0.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is it right?&lt;/p&gt;&#xA;&lt;p&gt;If so, I can not have &lt;strong&gt;an intuitive understanding&lt;/strong&gt; and the physical meaning of this. If the functional derivative results in its derivative being zero at each positions (all positions), does this mean that the energy does not change with the density, i.e., is this a constant function and does this mean the ground-state?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-09-02T14:45:49.243" LastActivityDate="2021-09-02T14:56:32.667" Title="Functional derivative of energy with respect to density" Tags="|density-functional-theory|mathematical-modeling|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6658" PostTypeId="2" ParentId="6657" CreationDate="2021-09-02T14:17:10.107" Score="8" Body="&lt;p&gt;By asking about the discretization of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;, I think you may be trying to visualize/intuitively understand the spatial variation of the energy and density, &lt;span class=&quot;math-container&quot;&gt;$\mathrm{d}E/\mathrm{d}\mathbf{r}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathrm{d}n(\mathbf{r})/\mathrm{d}\mathbf{r}$&lt;/span&gt;, and you are conflating that with the meaning of the functional derivative &lt;span class=&quot;math-container&quot;&gt;$δE[n]/δn(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you have a density, &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt;, such that &lt;span class=&quot;math-container&quot;&gt;$$\tag{1} \frac{δE[n]}{δn(\mathbf{r})} = 0,$$&lt;/span&gt; you have found a stationary point. This derivative should be interpreted as how the &lt;em&gt;energy changes with respect to the density&lt;/em&gt; (at all &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;). That is, assuming that the stationary point corresponds to a minimum (which is the goal here), the density that satifies my Eq. (1) minimizes the energy at all &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;. Any change to the density (anywhere in space) will no longer minimize the energy. By definition, the ground state is the minimum energy state.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="5" LastEditDate="2021-09-02T14:28:37.077" LastActivityDate="2021-09-02T14:28:37.077" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6659" PostTypeId="2" ParentId="6657" CreationDate="2021-09-02T14:17:34.577" Score="8" Body="&lt;p&gt;You are developing the right idea, but your Eq. 1 is a bit awkward. To understand why, let me say a bit about functionals and functional derivatives.&lt;/p&gt;&#xA;&lt;p&gt;A functional acts on a &lt;em&gt;function&lt;/em&gt; in its entirety, for example we need to know the full input function &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; in order to obtain the corresponding value for the functional:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;E[n(r)] = \int_0^1n(r)\textrm dr.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The output is different for &lt;span class=&quot;math-container&quot;&gt;$n(r) = n^2$&lt;/span&gt; versus for &lt;span class=&quot;math-container&quot;&gt;$n(r) = \sqrt{n},$&lt;/span&gt; and each &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; function will give a different value for the functional &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is &lt;em&gt;&lt;strong&gt;different&lt;/strong&gt;&lt;/em&gt; from an ordinary &lt;em&gt;composite&lt;/em&gt; function like &lt;span class=&quot;math-container&quot;&gt;$f(g(r))$&lt;/span&gt; with &lt;em&gt;&lt;strong&gt;round&lt;/strong&gt;&lt;/em&gt; parentheses, because &lt;em&gt;&lt;strong&gt;you do not need to take into account all of &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt;&lt;/strong&gt;&lt;/em&gt; in order to get &lt;span class=&quot;math-container&quot;&gt;$f(g(r))$&lt;/span&gt;, since &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is only acting on &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; at a specific point like &lt;span class=&quot;math-container&quot;&gt;$r=2$&lt;/span&gt;, which means that &lt;span class=&quot;math-container&quot;&gt;$f(g(2))$&lt;/span&gt; makes sense but &lt;span class=&quot;math-container&quot;&gt;$E[n(2)]$&lt;/span&gt; is a bit awkward. Technically speaking, &lt;span class=&quot;math-container&quot;&gt;$n(2)$&lt;/span&gt; &lt;em&gt;can be&lt;/em&gt; considered a constant &lt;em&gt;function&lt;/em&gt;, but a constant function of what? The integral in my Eq. 1 can still be evaluated (with respect to the variable that was already set to 2?), but the &lt;em&gt;&lt;strong&gt;square&lt;/strong&gt;&lt;/em&gt; brackets tell us that &lt;span class=&quot;math-container&quot;&gt;$E[n(r)]$&lt;/span&gt; is &lt;em&gt;&lt;strong&gt;meant&lt;/strong&gt;&lt;/em&gt; to be evaluated &lt;em&gt;&lt;strong&gt;based on&lt;/strong&gt;&lt;/em&gt; all values of &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, not just one of them.&lt;/p&gt;&#xA;&lt;p&gt;Technically functionals are also functions, in which the &lt;a href=&quot;https://en.wikipedia.org/wiki/Domain_of_a_function&quot; rel=&quot;noreferrer&quot;&gt;domain&lt;/a&gt; contains functions (i.e. it maps functions to &lt;em&gt;outputs&lt;/em&gt;, which can be scalars, vectors, functions, or even functionals; an example of the latter being a functional that turns polynomials into operators, like &lt;span class=&quot;math-container&quot;&gt;$r^2 \rightarrow \frac{\textrm{d}^2}{\textrm{d}r^2}$&lt;/span&gt;), but we use square brackets and round brackets to tell us how the author &lt;em&gt;intends&lt;/em&gt; for us to use the two different types of operators.&lt;/p&gt;&#xA;&lt;p&gt;Consider the difference between the following two derivatives:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\frac{\textrm{d}f(g(r))}{\textrm{d}r}~~~~~~~~~~~,~~~~~~~~~~~ \frac{\delta f[g(r)]}{\delta g(r)}~~.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It would be awkward to put &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; in the denominator of the first one, because the ordinary derviative &lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}}{\textrm{d}r}$&lt;/span&gt; acts on functions whose domains are points (not functions), and likewise it would be awkward to put just a point like &lt;span class=&quot;math-container&quot;&gt;$g(r_1)$&lt;/span&gt; in the denominator of the second one (otherwise why are you using the &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta}{\delta\left(\cdot\right)}$&lt;/span&gt; notation rather than the &lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}}{\textrm{d}\left( \cdot \right)}$&lt;/span&gt; notation?).&lt;/p&gt;&#xA;&lt;p&gt;Therefore, your Eq. 1 is written awkwardly.&lt;/p&gt;&#xA;&lt;p&gt;Now consider what it really means for the functional derivative of the energy with respect to the density, to be 0. It means that changing the &lt;em&gt;function&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; will not change the energy. For example if you &lt;em&gt;shift&lt;/em&gt; the Gaussian &lt;span class=&quot;math-container&quot;&gt;$n(r) = e^{-r^2}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$n(r) = e^{-(r-0.1)^2}$&lt;/span&gt;, the energy does not change (if the functional derivative of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; with respect to &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; is 0). Contrarily, if the derivative of the energy with respect to a grid point &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt; is 0, it would mean:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;\left. \frac{\textrm{d}E(n(r))}{\textrm{d}r_1} = \frac{\textrm{d}E}{\textrm{d}n}\frac{\textrm{d}n}{\textrm{d}r} \right|_{r=r_1}= 0,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which can happen if &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; is &lt;em&gt;flat&lt;/em&gt;, meaning that it doesn't change if you move the grid point &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;It is not true that the density &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; has to be flat (constant with respect to &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;) in order for &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta E}{\delta n(r)}$&lt;/span&gt; to be 0. The density can take the shape of a roller coaster, and still we can have that the energy does not change when we change the shape of the roller coaster (i.e. the functional derivative of the energy with respect to the shape of the roller coaster is 0).&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-02T14:56:32.667" LastActivityDate="2021-09-02T14:56:32.667" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6661" PostTypeId="1" CreationDate="2021-09-02T18:09:03.387" Score="8" ViewCount="326" Body="&lt;p&gt;In &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/aenm.202001305&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, they have plotted the band structure of orthorhombic  &lt;span class=&quot;math-container&quot;&gt;$\ce{CsPbI3}$&lt;/span&gt; using Wein2k. The k-path given here is Γ—X—R—Z—Γ—X—R—A—M—X, but I cannot find the M point in the orthorhombic crystal structure &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;noreferrer&quot;&gt;online&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the M point of an orthorhombic crystal structure? What are the coordinates?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This question has reference to my  &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6660/how-to-implement-discontinuous-k-points-in-quantum-espresso&quot;&gt;previous post&lt;/a&gt; on the Brilloiun zone k-path.&lt;/p&gt;&#xA;" OwnerUserId="4206" LastEditorUserId="5" LastEditDate="2021-09-02T18:13:17.920" LastActivityDate="2021-09-03T09:57:17.873" Title="What is the M-point of an orthorhombic crystal structure?" Tags="|quantum-espresso|k-points|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6662" PostTypeId="1" AcceptedAnswerId="6663" CreationDate="2021-09-03T06:20:26.227" Score="5" ViewCount="314" Body="&lt;p&gt;Thanks to very helpful and detailed answers for &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6657/functional-derivative-of-energy-with-respect-to-density&quot;&gt;my previous question&lt;/a&gt;,&#xA;I understand the functional derivative of the energy with respect to the density.&#xA;In addition, this functional derivative is equal to zero as follows (this screenshot is a page of the paper: &amp;quot;&lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0211443.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;A bird's-eye view of density-functional theory [PDF]&lt;/a&gt;&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hqPgM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hqPgM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, this equation means that&#xA;the sum of the potential terms (external &lt;span class=&quot;math-container&quot;&gt;$v_\text{ext}$&lt;/span&gt;, Hartree &lt;span class=&quot;math-container&quot;&gt;$v_\text{H}$&lt;/span&gt;,&#xA;and exchange-correlation &lt;span class=&quot;math-container&quot;&gt;$v_\text{xc}$&lt;/span&gt; (e.g., LDA))&#xA;and the functional derivative of the kinetic energy with respect to the density,&#xA;&lt;span class=&quot;math-container&quot;&gt;$δT_s[n]/δn(r)$&lt;/span&gt;, is zero.&#xA;In other words, does this mean that&#xA;we have &lt;strong&gt;zero at all positions&lt;/strong&gt; as shown in the following figure? Is it right?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/i35Wo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/i35Wo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the &lt;span class=&quot;math-container&quot;&gt;$δT_s[n]/δn(r)$&lt;/span&gt; term remains in the equation. Is it possible to write this term with &lt;strong&gt;a clear expression&lt;/strong&gt; like these potential terms? More precisely, the kinetic energy is a functional of &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; in the Kohn-Sham DFT (i.e., &lt;span class=&quot;math-container&quot;&gt;$T_s[\{\psi_i(r)\}_{i=1}^N]$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; is the Kohn-Sham orbital), but can't we write down this derivative using another equation without &lt;span class=&quot;math-container&quot;&gt;$δ$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-09-03T15:00:01.460" LastActivityDate="2021-09-03T15:29:13.573" Title="Relationship between functional derivative and potential value at a position" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6663" PostTypeId="2" ParentId="6662" CreationDate="2021-09-03T09:07:35.077" Score="5" Body="&lt;p&gt;Yes, the sum of these potentials is zero everywhere with the true ground-state density. But the true ground-state density is generally only expressible when the basis set is complete (if you know the true ground-state density in advance, you can of course construct a finite basis set that reproduces it exactly, but if you don't know the exact density, you normally have to use a complete basis set). So in an actual calculation, the sum of the potentials will in general not be everywhere zero, especially far away from the molecule and/or near the nuclei, where the quality of the basis set is generally poor.&lt;/p&gt;&#xA;&lt;p&gt;As for the functional derivative of the kinetic energy - of course you may write it as something like &lt;span class=&quot;math-container&quot;&gt;$v_{T_s}(\mathbf{r})$&lt;/span&gt; (I'm not sure about what the most common notation in the literature is, though). The literature you cited spelled out the functional derivative explicitly, because in the Kohn-Sham approach the real-space representation of this functional derivative never appears in the actual calculations - it is transformed away after introducing the Kohn-Sham orbitals. In orbital-free DFT, however, one may be more willing to write this term in a form similar to &lt;span class=&quot;math-container&quot;&gt;$v_{T_s}(\mathbf{r})$&lt;/span&gt;, because in this case the latter form is indeed involved directly in the calculations.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-03T09:07:35.077" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6664" PostTypeId="2" ParentId="6661" CreationDate="2021-09-03T09:57:17.873" Score="5" Body="&lt;p&gt;This is not a direct answer to your question, but instead the description of a resource that you can use to learn about high symmetry points and paths of &lt;em&gt;any&lt;/em&gt; structure (including your orthorhombic lead halide perovskite).&lt;/p&gt;&#xA;&lt;p&gt;Website: &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;noreferrer&quot;&gt;SeeK-path&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Short description: it allows you to upload a crystal structure (in many formats, including QE, VASP, CASTEP, cif), and it depicts the Brillouin zone, high symmetry coordinates and labels, and provides a suggested high symmetry path along the Brillouin zone on which to evaluate the band structure.&lt;/p&gt;&#xA;&lt;p&gt;For you: if you upload your structure file (I understand you have it in QE format?), then it should provide the coordinates of the M point.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-09-03T09:57:17.873" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6665" PostTypeId="1" CreationDate="2021-09-03T14:07:42.497" Score="6" ViewCount="206" Body="&lt;p&gt;I was examining a system with a problematic equilibration (more details given at the end, but probably unnecessary to answer the question), and came upon what is presumably a pretty basic conceptual question that I unfortunately didn’t find an answer to on my own.&lt;/p&gt;&#xA;&lt;p&gt;I am using LAMMPS to simulate a NPT ensemble for an ionic crystal with some small organic molecules, using a force field made up of two different pairwise potentials (lj and Buckingham), and some molecular terms (bonds, angles, tetrahedrals). When plotting the pairwise energy, the molecular energy, and the total potential energy (pair+molec+long range interactions), I noticed a trend that I don’t understand well:&#xA; &lt;a href=&quot;https://i.stack.imgur.com/uuRku.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uuRku.png&quot; alt=&quot;graph of the different energies&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here is what I observe:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The system reaches the target temperature (300K) almost instantly at the scale of the graph, and then the geometry take a (very) long time to relax. While doing so, the pairwise energy goes down, but the molecular energy compensates it pretty much exactly to keep the potential energy constant.&lt;/p&gt;&#xA;&lt;p&gt;I do not understand this well. In particular, why is the molecular energy going up? Upon a quick examination of the system, it seems like the bond lengths are simply vibrating but not drifting higher or lower. What is the source of this energy change? And why does it have to compensate the change in pairwise energy? I don’t see a good reason why the potential energy would be conserved in a NPT. On a side note, kinetic energy and total system energy are also conserved throughout&#xA; &lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here is what I would have qualitatively expected to observe:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Pairwise energy does go down as the relaxation/equilibrations happens: this would be because the atoms are adjusting and getting into their “optimal average positions” energy wise under the action of the interactions, minimizing this pairwise “binding energy” (similar to how a dft simulation looks for an energy minimum. Of course, in a statistical ensemble, there is no such thing, but I would still reasonably expect the pairwise energy to decrease as the equilibration proceeds)&lt;/li&gt;&#xA;&lt;li&gt;Molecular energy remains pretty much the same, granted that no significant change is going on in the average molecule geometry&lt;/li&gt;&#xA;&lt;li&gt;Potential energy decreases with the pairwise one&lt;/li&gt;&#xA;&lt;li&gt;Kinetic energy remains more or less the same once the target temperature is reached, implying a decrease of the total energy of the system (which is alright since it’s not NVE, we are not expecting energy to be a conserved quantity)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Basically, I just don’t understand why the molecular energy is increasing, and why it’s precisely compensating the pairwise energy. Could anyone point me in the right direction? Many thanks!&lt;/p&gt;&#xA;&lt;p&gt; &#xA;In case it helps, my system is &lt;span class=&quot;math-container&quot;&gt;$\ce{MAPbI3}$&lt;/span&gt;, an ionic crystal of &lt;span class=&quot;math-container&quot;&gt;$\ce{Pb2+}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{I-}$&lt;/span&gt;, and methyllamonium cation. The dynamics of the cation (notably rotations) are relevant to the overall relaxation to a ~ cubic system. The force field used is taken from the literature and has been used by several authors. I am observing a slow relaxation of the crystal lattice over ~1.5e6 timesteps of 0.5fs.&#xA; &lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT&lt;/strong&gt;: I am using a harmonic model for the bond which has the form &lt;span class=&quot;math-container&quot;&gt;$E_{bond}=K(r-r_0)^2$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$r_0$&lt;/span&gt; the parametrized bond length, and &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; the actual bond length. If &lt;span class=&quot;math-container&quot;&gt;$r_0 \approx \langle r\rangle$&lt;/span&gt; (which should be the case since it is the point of parameterizing the bond after all), then we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle E_{bond} \rangle \approx K\langle(r-\langle r \rangle)^2\rangle \approx K\textrm{var}(r),\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the increasing bond energy can be explained by an increasing variance in bond length during equilibration, even if the average bond length remains the same. I still do not understand how this is related to the decrease in pairwise energy and why the potential energy ends up being conserved&lt;/p&gt;&#xA;" OwnerUserId="3967" LastEditorUserId="5" LastEditDate="2022-01-14T01:38:03.613" LastActivityDate="2022-01-14T01:38:03.613" Title="Apparent conservation of potential energy in NPT simulation?" Tags="|molecular-dynamics|lammps|binding-energy|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6666" PostTypeId="1" CreationDate="2021-09-03T14:53:25.883" Score="7" ViewCount="406" Body="&lt;p&gt;This question is related to this &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Standard_MD&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP tutorial&lt;/a&gt;, in which the pair correlation function (or radial distribution function: RDF) is utilized to justify whether the solid silicon is melt by AIMD (ab-initio molecular dynamics) or not.&lt;/p&gt;&#xA;&lt;p&gt;How is the RDF defined and what information can we obtain from it?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/U76BN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/U76BN.png&quot; alt=&quot;Pair correlation function of melting silicon&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pWeHY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pWeHY.png&quot; alt=&quot;Radial distribution function for Copper-zinc system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2021-12-02T17:30:18.437" LastActivityDate="2021-12-02T17:30:18.437" Title="What's the pair correlation function? What information does it contain?" Tags="|molecular-dynamics|radial-distribution-function|correlation-functions|" AnswerCount="0" CommentCount="6" FavoriteCount="0" ClosedDate="2022-01-18T15:27:48.733" ContentLicense="CC BY-SA 4.0" />
  <row Id="6667" PostTypeId="2" ParentId="6662" CreationDate="2021-09-03T15:29:13.573" Score="3" Body="&lt;p&gt;Since we are considering the left side of your Eq. 69 as a function of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;, it must be the constant function of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; that is 0 everywhere: &lt;span class=&quot;math-container&quot;&gt;$0(\mathbf{r})$&lt;/span&gt;. If it were any other function, such that the left side of the equation were to be non-zero anywhere, we would not write a 0 there. So it's true that your Eq. 69 is saying that the RHS is zero at all of the points in your diagram.&lt;/p&gt;&#xA;&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6663/5&quot;&gt;wzkchem5 said&lt;/a&gt;, Eq. 69 will not in practice be true in your real-world computer calculations, and is likely to be further away from 0 at places where the basis set is not as good of an approximation of the true function its aiming to represent.&lt;/p&gt;&#xA;&lt;p&gt;About the definition of &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta T}{\delta n(\mathbf{r})}$&lt;/span&gt;: Continuing from my answer to your question &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6659/5&quot;&gt;Functional derivative of energy with respect to density&lt;/a&gt;&amp;quot;, this is how &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; changes when &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; changes. If the change in &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; with respect to &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; stays the same no matter what your position &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; is, then your functional derivative is a constant with respect to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;; let's call it &lt;span class=&quot;math-container&quot;&gt;$v_T$&lt;/span&gt;. Let's say that at each position &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;, the way that &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; changes with respect to &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; is slightly different, then the functional derivative will have some &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; dependence, so we can call it &lt;span class=&quot;math-container&quot;&gt;$v_T(\mathbf{r})$&lt;/span&gt;. As wzkchem5 said, this may make sense in &lt;a href=&quot;https://mattermodeling.stackexchange.com/search?q=orbital+free+dft&quot;&gt;orbital-free DFT&lt;/a&gt;, but in Kohn-Sham DFT the introduction of the KS orbitals replaces the need for dealing directly with any such &lt;span class=&quot;math-container&quot;&gt;$v_T(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-09-03T15:29:13.573" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6668" PostTypeId="1" CreationDate="2021-09-03T15:39:46.110" Score="6" ViewCount="258" Body="&lt;p&gt;It seems there is a general agreement among the practitioners of Molecular Dynamics that 1fs is a fairly reasonable time step, with shorter time steps being required for materials with higher vibrational frequencies. But I haven't seen much information on how one might derive the highest vibrational frequency of a material.&lt;/p&gt;&#xA;&lt;p&gt;The following question from this site is related: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/498/how-should-one-choose-the-time-step-in-a-molecular-dynamics-integration/514?newreg=8271db8e38504b1593c741a5a4dfcdd3&quot;&gt;How should one choose the time step in a molecular dynamics integration?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The question has two great answers referencing Nyquist's Theorem and explaining the reasoning behind choosing a timestep frequency below the highest vibrational frequency, but when it comes to establishing if the timestep you've chosen is appropriate it suggests empirically checking various timesteps for energy drift.&lt;/p&gt;&#xA;&lt;p&gt;Having read around further it seems there are a few other methods for establishing the correct time step, and they are below along with the empirical method:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Empirically check the time-step is correct by performing NVE simulations and checking for energy drift.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the first crossing point of the &amp;quot;Velocity Auto-Correlation Function&amp;quot; to establish an appropriate time step. Seen here on the LAMMPS source forge mailing list: &lt;a href=&quot;https://sourceforge.net/p/lammps/mailman/message/26183023/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://sourceforge.net/p/lammps/mailman/message/26183023/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Analyse your Interatomic Pair Potentials to establish what the highest frequency is likely to be and use that as a base for you timestep.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Which method would you recommend as the most mathematically/ physically rigorous, and does anyone know or have a link to the specifics of the latter two methods?&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2021-09-03T16:18:24.633" LastActivityDate="2021-09-03T16:18:24.633" Title="How do you Select a Time Step for Molecular Dynamics Simulations?" Tags="|molecular-dynamics|mathematical-modeling|lammps|vibrations|interatomic-potentials|" AnswerCount="0" CommentCount="12" ClosedDate="2023-12-09T23:03:52.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="6669" PostTypeId="2" ParentId="498" CreationDate="2021-09-03T16:03:11.937" Score="8" Body="&lt;p&gt;Having read the above answers I think it's important to point out why you generally use a time step below the upper limit provided by &lt;strong&gt;Nyquist's Theorem.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The theorem itself describes the maximum number of signals it's possible to send through a telegraph cable and still have them be discernable from one another. That makes the limiting case a &lt;strong&gt;sampling frequency&lt;/strong&gt; that gives you &lt;strong&gt;two points&lt;/strong&gt; along a wave period, one in the positive section and one in the negative section. This is fine for a signal being processed as Ones and Zeroes, but for &lt;strong&gt;atoms&lt;/strong&gt; in &lt;strong&gt;molecular dynamics&lt;/strong&gt; whose interactions are governed by a continuous pair potential this is &lt;strong&gt;extremely low resolution.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore, a &lt;strong&gt;smaller time step&lt;/strong&gt; is &lt;strong&gt;often chosen&lt;/strong&gt; than the limiting frequency indicated by Nyquist's theorem, because such a low resolution can still produce &lt;strong&gt;unphysical results&lt;/strong&gt; that cause a &lt;strong&gt;loss of energy conservation.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2021-09-03T16:37:04.490" LastActivityDate="2021-09-03T16:37:04.490" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6670" PostTypeId="1" AcceptedAnswerId="6673" CreationDate="2021-09-03T17:22:17.173" Score="7" ViewCount="3101" Body="&lt;p&gt;Here is my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase.io import read, write&#xA;bec = ase.io.read(&amp;quot;bec_replaced.vasp&amp;quot;)&#xA;bec_new = ase.io.write(&amp;quot;bec_replaced.xyz&amp;quot;, format=&amp;quot;xyz&amp;quot;)&#xA;TypeError: write() missing 1 required positional argument: 'images'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What am I supposed to put for &lt;code&gt;images&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="5" LastEditDate="2021-09-03T18:12:00.047" LastActivityDate="2021-09-03T18:22:08.537" Title="Converting input file into XYZ format using ASE" Tags="|atomic-simulation-environment|geometry|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6671" PostTypeId="1" CreationDate="2021-09-02T11:22:32.557" Score="5" ViewCount="183" Body="&lt;p&gt;The double bonds are initially present at the sdf file but disappear or are misplaced after &lt;code&gt;.pdbqt&lt;/code&gt; conversion. I tried all kinds of combinations using renumbering atoms, manually including connect bonds or connect bonds, changing A atoms to Cs, NA atoms to N, small case lettering, &lt;code&gt;.sdf&lt;/code&gt;, &lt;code&gt;.pdb&lt;/code&gt; or &lt;code&gt;.mol&lt;/code&gt; inputs. Nothing worked!!!.&lt;/p&gt;&#xA;&lt;p&gt;When any of those alternative solutions were converted by OpenBabel to their corresponding &lt;code&gt;.pdbqt&lt;/code&gt;, none of them interpret the double bonds of triazine (&lt;code&gt;c1ncncn1&lt;/code&gt;) correctly. Furthermore, sometimes  they introduced double bonds in other parts of the molecules, misplaced them or broke them.&lt;/p&gt;&#xA;&lt;p&gt;I enclose two of my Triazine derivatives in the &lt;code&gt;.sdf&lt;/code&gt; format.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;136627870N3+2.2&#xA;  MOLSOFT 09022111472D&#xA;&#xA; 29 30  0  0  0  0  0  0  0  0999 V2000&#xA;    0.0000   -0.0000   -0.0000 O   0  0  0&#xA;    1.2534    0.7910   -0.0000 C   0  0  0&#xA;   -1.3507    0.7910   -0.0000 C   0  0  0&#xA;    2.5067    0.0608   -0.0000 N   0  0  0&#xA;   -2.7014    0.0608   -0.0000 C   0  0  0&#xA;    2.4581   -1.3994   -0.0000 C   0  0  0&#xA;    3.7601    0.8518   -0.0000 C   0  0  0&#xA;    3.7114   -2.1295   -0.0000 N   0  0  0&#xA;    1.1073   -2.1295   -0.0000 N   0  0  0&#xA;    3.7114    2.4094   -0.0000 C   0  0  0&#xA;    3.6628   -3.5898   -0.0000 C   0  0  0&#xA;    1.0587   -3.5898   -0.0000 C   0  0  0&#xA;    2.4337    3.1639   -0.0000 C   0  0  0&#xA;    2.3120   -4.3199   -0.0000 N   0  0  0&#xA;    4.9161   -4.3199    0.0000 N   0  0  0&#xA;   -0.2920   -4.3199   -0.0000 N   0  0  0&#xA;    2.3851    4.7214   -0.0000 C   0  0  0&#xA;    4.8675   -5.7801    0.0000 C   0  0  3&#xA;    6.1695   -3.5289   -0.0000 C   0  0  0&#xA;   -1.6428   -3.5289   -0.0000 C   0  0  0&#xA;   -0.3407   -5.7801   -0.0000 C   0  0  0&#xA;    3.5167   -6.5102    0.0000 O   0  0  0&#xA;    6.1208   -6.5102    0.0000 C   0  0  0&#xA;    7.4229   -4.2590   -0.0000 C   0  0  0&#xA;   -1.6914   -1.9713   -0.0000 O   0  0  0&#xA;   -1.6914   -6.5102   -0.0000 C   0  0  0&#xA;    7.3742   -5.7314   -0.0000 C   0  0  0&#xA;   -3.0422   -5.7314   -0.0000 C   0  0  0&#xA;   -4.3929   -6.4616   -0.0000 C   0  0  0&#xA;  1  2  1&#xA;  1  3  1&#xA;  2  4  1&#xA;  3  5  1&#xA;  4  6  1&#xA;  4  7  1&#xA;  6  8  2&#xA;  6  9  1&#xA;  7 10  1&#xA;  8 11  1&#xA;  9 12  2&#xA; 10 13  1&#xA; 11 14  2&#xA; 11 15  1&#xA; 12 16  1&#xA; 12 14  1&#xA; 13 17  1&#xA; 15 19  1&#xA; 16 20  1&#xA; 16 21  1&#xA; 18 15  1&#xA; 18 22  1&#xA; 18 23  1&#xA; 19 24  1&#xA; 20 25  1&#xA; 21 26  1&#xA; 23 27  1&#xA; 24 27  1&#xA; 26 28  1&#xA; 28 29  1&#xA;M  END&#xA;&amp;gt; &amp;lt;molFormula&amp;gt;&#xA;C20H38N6O3&#xA;&#xA;&amp;gt; &amp;lt;smiles&amp;gt;&#xA;CCCCN(CO)c1nc(nc(n1)N1CCCCC1O)N(CCCC)COCC&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;135839733N3+1.3&#xA;  MOLSOFT 09022111472D&#xA;&#xA; 25 27  0  0  0  0  0  0  0  0999 V2000&#xA;    0.0000   -0.0000    0.0000 O   0  0  0&#xA;    0.0250    1.4637    0.0000 C   0  0  3&#xA;   -1.2260    2.2018    0.0000 N   0  0  0&#xA;    1.2260    2.1768    0.0000 C   0  0  0&#xA;   -2.4771    1.4387   -0.0000 C   0  0  0&#xA;   -1.2761    3.7281   -0.0000 C   0  0  0&#xA;    1.2135    3.7782   -0.0000 C   0  0  0&#xA;   -3.8032    2.2269   -0.0000 N   0  0  0&#xA;   -2.4521   -0.0626   -0.0000 N   0  0  0&#xA;   -0.0500    4.5163   -0.0000 C   0  0  0&#xA;   -5.0542    1.4637   -0.0000 C   0  0  0&#xA;   -3.7031   -0.8257   -0.0000 C   0  0  0&#xA;   -5.0292   -0.0375   -0.0000 N   0  0  0&#xA;   -6.3803    2.2519   -0.0000 N   0  0  0&#xA;   -3.6781   -2.3269   -0.0000 N   0  0  0&#xA;   -6.4304    3.7782   -0.0000 C   0  0  0&#xA;   -7.7065    1.5388   -0.0000 C   0  0  0&#xA;   -2.3770   -3.0901   -0.0000 C   0  0  0&#xA;   -5.0042   -3.0400   -0.0000 C   0  0  0&#xA;   -7.7565    4.5663   -0.0000 C   0  0  0&#xA;   -9.0326    2.3269   -0.0000 C   0  0  0&#xA;   -1.0759   -2.3520   -0.0000 O   0  0  0&#xA;   -5.0542   -4.4787   -0.0000 C   0  0  0&#xA;   -9.0826    3.8532   -0.0000 C   0  0  0&#xA;   -3.7531   -5.2419   -0.0000 C   0  0  0&#xA;  2  1  1&#xA;  2  3  1&#xA;  2  4  1&#xA;  3  5  1&#xA;  3  6  1&#xA;  4  7  1&#xA;  5  8  2&#xA;  5  9  1&#xA;  6 10  1&#xA;  7 10  1&#xA;  8 11  1&#xA;  9 12  2&#xA; 11 13  2&#xA; 11 14  1&#xA; 12 15  1&#xA; 12 13  1&#xA; 14 16  1&#xA; 14 17  1&#xA; 15 18  1&#xA; 15 19  1&#xA; 16 20  1&#xA; 17 21  1&#xA; 18 22  1&#xA; 19 23  1&#xA; 20 24  1&#xA; 21 24  1&#xA; 23 25  1&#xA;M  END&#xA;&amp;gt; &amp;lt;molFormula&amp;gt;&#xA;C17H30N6O2&#xA;&#xA;&amp;gt; &amp;lt;smiles&amp;gt;&#xA;CCCN(CO)c1nc(nc(n1)N1CCCCC1O)N1CCCCC1&#xA;&#xA;$$$&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4222" OwnerDisplayName="Julio Coll" LastEditorUserId="5" LastEditDate="2021-09-03T19:03:50.787" LastActivityDate="2021-09-03T19:03:50.787" Title="How can I add double bonds to Triazine-derivatives for OpenBabel generation of pdbqt files?" Tags="|software|computational-chemistry|molecular-modeling|openbabel|" AnswerCount="0" CommentCount="4" ClosedDate="2021-12-13T19:30:36.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="6672" PostTypeId="2" ParentId="6670" CreationDate="2021-09-03T17:54:48.727" Score="5" Body="&lt;p&gt;You should do something like this instead:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import ase&#xA;from ase.io import read, write&#xA;bec = ase.io.read(&amp;quot;bec_replaced.vasp&amp;quot;)&#xA;bec_new = ase.io.write(&amp;quot;bec_replaced.xyz&amp;quot;, bec, format=&amp;quot;xyz&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;according to the documentation page.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2021-09-03T17:54:48.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6673" PostTypeId="2" ParentId="6670" CreationDate="2021-09-03T18:22:08.537" Score="7" Body="&lt;p&gt;Here is a more concise way of doing the same thing.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase.io import read&#xA;bec = read(&amp;quot;bec_replaced.vasp&amp;quot;).write(&amp;quot;bec_replaced.xyz&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is not needed to import ase and import the functions, you want to do one or the other (This is a python thing not ASE).  read also returns an atoms object with a write function built in, so there is no need to import a write function.  ASE will also assume the file format from the file extension, however you might need to use the format argument when it detects things incorrectly.&lt;/p&gt;&#xA;&lt;p&gt;Optionally, use the command line instead&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;ase convert bec_replaced.vasp bec_replaced.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-09-03T18:22:08.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6674" PostTypeId="5" CreationDate="2021-09-03T19:04:22.950" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://openbabel.org/wiki/Main_Page&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-03T19:04:22.950" LastActivityDate="2021-09-03T19:04:22.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6675" PostTypeId="4" CreationDate="2021-09-03T19:04:22.950" Score="0" Body="Questions about or related to Open Babel." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-03T19:04:22.950" LastActivityDate="2021-09-03T19:04:22.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6676" PostTypeId="2" ParentId="498" CreationDate="2021-09-04T08:00:13.773" Score="9" Body="&lt;p&gt;Other answers explaining Nyquist's Sampling Theorem are completely correct. Read those before mine. I'd like to add some information about how details of how you run your simulation can affect the  Nyquist frequency, and therefore, in practice, affect the fundamental question of how to choose your time step.&lt;/p&gt;&#xA;&lt;p&gt;As one can easily imagine, tricks that let you simulate a longer time for the same computational effort have been a major area of research. Here are a few relevant points I know of (no effort to be comprehensive -- just the articles that spring to my mind!):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Integration algorithms can affect reasonable step size.&lt;/strong&gt; Some integrators (a.k.a. propagators) can exhibit fortuitous cancellation of errors that allows a larger step size. The main example of this that I know is the Langevin &amp;quot;BAOAB&amp;quot; splitting. For details, see this paper: &lt;a href=&quot;https://doi.org/10.1093/amrx/abs010&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1093/amrx/abs010&lt;/a&gt; (arXiv: &lt;a href=&quot;https://arxiv.org/abs/1203.5428&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1203.5428&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;You can add constraints to increase step size (and an integrator to exploit that).&lt;/strong&gt; The purpose of constraints is usually to allow larger step sizes -- by removing faster vibrational motions, you change the Nyquist frequency. This can be further exploited by integration algorithms to allow even larger time step. For example, the article introducing the geodesic BAOAB Langevin integrator suggests that it should allow step sizes of up to 8 fs for biomolecular system! Here's the reference for g-BAOAB: &lt;a href=&quot;https://royalsocietypublishing.org/doi/full/10.1098/rspa.2016.0138&quot; rel=&quot;noreferrer&quot;&gt;https://royalsocietypublishing.org/doi/full/10.1098/rspa.2016.0138&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;There is good evidence that you can redistribute mass to increase step size.&lt;/strong&gt; In general, the highest frequency vibrations are those involving a hydrogen atom. For this reason, it is common to constrain bonds to hydrogen atoms. However, another approach is &amp;quot;hydrogen mass repartitioning&amp;quot; (HMR), where mass from the heavy atom is transferred to the hydrogen, keeping the same total mass without requiring constraints, and resulting in a slower Nyquist frequency. Here's a reference for that: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct5010406&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/ct5010406&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-09-04T08:00:13.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6677" PostTypeId="1" AcceptedAnswerId="6681" CreationDate="2021-09-04T19:05:04.930" Score="4" ViewCount="268" Body="&lt;p&gt;Searching about the microstructure of Cu-Ni-Zn alloys I came across this article (published 2017) which in its conclusion section says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It was observed that the starting and finishing transformation&#xA;temperatures from austenite to martensite (&lt;span class=&quot;math-container&quot;&gt;$A_s$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$A_f$&lt;/span&gt;) affected by Zn&#xA;percent.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As far as know, the starting and finishing temperatures from austenite to martensite must be &lt;span class=&quot;math-container&quot;&gt;$M_s$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M_f$&lt;/span&gt;, so I'm confused now. Any ideas if it's a mistake in the article or everything is okay and I'm getting this wrong?&lt;/p&gt;&#xA;&lt;p&gt;P.S.:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$A_s$&lt;/span&gt; - Austenite start temperature&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$A_f$&lt;/span&gt; - Austenite finish temperature&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$M_s$&lt;/span&gt; - martensite start temperature&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$M_f$&lt;/span&gt; - martensite finish temperature&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3950" LastEditorUserId="5" LastEditDate="2021-09-05T22:18:59.373" LastActivityDate="2021-09-05T22:18:59.373" Title="Martensitic transformation, start and finish temperatures" Tags="|materials-engineering|alloys|phase-transitions|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6678" PostTypeId="1" AcceptedAnswerId="6705" CreationDate="2021-09-05T03:31:45.083" Score="7" ViewCount="478" Body="&lt;p&gt;In many scripts I came across, I saw for the calculation of the RDF, both the&#xA;trajectory and the individual timeframe also have been used.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can anybody help me with understanding how they are different or&#xA;similar?&lt;/strong&gt; Also, if possible, please make any comment on how you read&#xA;the partial RDF plots?&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="5" LastEditDate="2021-09-05T23:38:55.010" LastActivityDate="2021-09-07T19:35:46.817" Title="Radial distribution function for trajectories or time frame?" Tags="|molecular-dynamics|radial-distribution-function|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6679" PostTypeId="1" CreationDate="2021-09-05T04:48:27.953" Score="3" ViewCount="119" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/664217/simplifying-double-integrals-of-isotropic-functions&quot;&gt;Cross-posted from physics SE&lt;/a&gt;.&#xA;I am studying statistical mechanics, and I am studying ideas surrounding potential of mean force and n-body density functions.&lt;/p&gt;&#xA;&lt;p&gt;In a derivation, they mention that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$-\left\langle \frac{\partial U}{\partial r_1} \right\rangle=k_BT\frac{d}{dr_1}\ln g(|r_1,r_2|)$$&lt;/span&gt;&#xA;and then they say, &amp;quot;since integrating over the average force yields work, we get&amp;quot;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$w(r)= -k_BT\ln g(r)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I feel like I don't understand how the integration works here.&#xA;I understand &lt;span class=&quot;math-container&quot;&gt;$\langle F\rangle = -k_BT\frac{d}{dr_1}\ln g(r_1,r_2)$&lt;/span&gt;&#xA;But now what I am doing is I am dragging particle 2 from &lt;span class=&quot;math-container&quot;&gt;$\infty$&lt;/span&gt; to some distance &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; from particle 1.&#xA;So, the integration should look like:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$w(r) = \int_{\infty} ^{r_1+r} \int_{0}^R \langle F \rangle \cdot r dr_1dr_2 = -\int_{\infty}^{r_1+r} \int_{0}^{\infty} k_BT\frac{d}{dr_1}\ln g(|r_1-r_2|) dr_1 dr_2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not sure how to safely reduce these integrals into the nice statement&#xA;&lt;span class=&quot;math-container&quot;&gt;$$w(r) = -k_BT\ln g(r)$$&lt;/span&gt;&#xA;How does one go about reducing such an integral? Or if there is an error in the way I have set this up, I would appreciate knowing that too.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-09-05T15:16:28.893" LastActivityDate="2021-09-05T15:16:28.893" Title="Simplifying double integrals of isotropic functions" Tags="|statistical-thermodynamics|from-phys-se|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6680" PostTypeId="2" ParentId="6679" CreationDate="2021-09-05T08:33:22.470" Score="4" Body="&lt;p&gt;The work is a single integral over &lt;span class=&quot;math-container&quot;&gt;$|r_1-r_2|$&lt;/span&gt;, not a double integral over &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt;. As you are fixing particle 1, you shouldn't integrate over particle 1. Moreover, the work is &lt;span class=&quot;math-container&quot;&gt;$w(r) = \int Fdr$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$w(r) = \int Frdr$&lt;/span&gt;, as you can see from dimensional analysis (&lt;span class=&quot;math-container&quot;&gt;$dr$&lt;/span&gt; has the dimension of length, too). Therefore, you treat &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt; as constant, integrate over &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt; and define &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$|r_1-r_2|$&lt;/span&gt;, and you get the result trivially.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-09-05T14:49:36.170" LastActivityDate="2021-09-05T14:49:36.170" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6681" PostTypeId="2" ParentId="6677" CreationDate="2021-09-05T16:08:21.747" Score="3" Body="&lt;p&gt;This seems to be a typo in the paper. As they mention in the introduction, austenite is the &amp;quot;hot&amp;quot; phase of this compound, so it should form on heating martensite. In their experiments, they heat  samples with varying compositions to determine at what temperature the austensitic transformation starts/finishes.&lt;/p&gt;&#xA;&lt;p&gt;The martensite temperatures should refer to the transformation from austenite to martensite on cooling. So their experiment does give them the austenite temperatures, but they erroneously refer to the austenite to martensite transformation in their Experimental and Conclusion sections.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-09-05T16:08:21.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6682" PostTypeId="2" ParentId="3707" CreationDate="2021-09-05T17:33:30.450" Score="3" Body="&lt;p&gt;&lt;strong&gt;AiiDA plugin for Quantum ESPRESSO&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://github.com/aiidateam/aiida-quantumespresso&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;aiida-quantumespresso&lt;/code&gt;&lt;/a&gt; plugin contains fairly advanced parsing capabilities of the output of various QE executables, all written in Python.&#xA;See the &lt;a href=&quot;https://github.com/aiidateam/aiida-quantumespresso/tree/develop/aiida_quantumespresso/parsers&quot; rel=&quot;nofollow noreferrer&quot;&gt;parsers subdirectory&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Part of the parsing is interleaved with AiiDA-specific data structures but you should be able to reuse much in other contexts as well.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2021-09-06T12:33:20.187" LastActivityDate="2021-09-06T12:33:20.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6683" PostTypeId="2" ParentId="95" CreationDate="2021-09-05T17:51:43.950" Score="4" Body="&lt;p&gt;I also remember finding it difficult to navigate the landscape of atomistic simulation engines as a Ph.D. student.&#xA;While there are very &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;extensive&lt;/a&gt; &lt;a href=&quot;https://en.wikipedia.org/wiki/Comparison_of_software_for_molecular_mechanics_modeling&quot; rel=&quot;nofollow noreferrer&quot;&gt;lists&lt;/a&gt; on Wikipedia, I often found it difficult to understand which of these codes actually are in broad use and for what purpose.&lt;/p&gt;&#xA;&lt;p&gt;This was one of the motivations for me creating the &lt;a href=&quot;https://atomistic.software&quot; rel=&quot;nofollow noreferrer&quot;&gt;atomistic.software&lt;/a&gt; collection, which strives to combine metadata on all major atomistic simulation engines with annual citation data from Google Scholar from 2010 until today.&#xA;You can filter by license type (and more), and you can click on each citation count to see the query that was used to obtain it and browse through the articles that are citing the code.&lt;/p&gt;&#xA;&lt;p&gt;More information in the &lt;a href=&quot;https://arxiv.org/abs/2108.12350&quot; rel=&quot;nofollow noreferrer&quot;&gt;associated preprint&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-09-05T17:51:43.950" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6684" PostTypeId="2" ParentId="6442" CreationDate="2021-09-05T18:54:38.823" Score="4" Body="&lt;p&gt;For questions like these where the answer is not provided by the Quantum ESPRESSO user guide, it usually pays off to search the source code on the &lt;a href=&quot;https://gitlab.com/QEF/q-e&quot; rel=&quot;nofollow noreferrer&quot;&gt;QE gitlab repository&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Searching for &amp;quot;freq&amp;quot; turns up &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/PHonon/PH/find_mode_sym.f90#L360&quot; rel=&quot;nofollow noreferrer&quot;&gt;find_mode_sym.f90&lt;/a&gt;, which shows that this information is stored in the &lt;code&gt;name_rap&lt;/code&gt; variable.&#xA;Searching for &amp;quot;name_rap(1)&amp;quot; turns up &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/PW/src/divide_class.f90#L2104-2115&quot; rel=&quot;nofollow noreferrer&quot;&gt;PW/src/divide_class.f90&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The comment documenting the &lt;code&gt;set_irr_rap&lt;/code&gt; subroutine mentions&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Various names have been used in the litterature to identify&#xA;the irreducible representations. Several equivalent names are&#xA;collected in this routine. The first name is taken&#xA;from the book of P.W. Atkins, M.S. Child, and C.S.G. Phillips,&#xA;&amp;quot;Tables for group theory&amp;quot;.&#xA;D, G, L, S are used for Delta, Gamma, Lambda and Sigma.&#xA;Representations which correspond to infrared or raman active modes&#xA;are identified with the string in ir_ram: I (infrared active),&#xA;R (Raman active), I+R (Infrared and Raman active).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I.e. &lt;code&gt;X_5'&lt;/code&gt; and &lt;code&gt;M_5'&lt;/code&gt; are just labels for the &lt;code&gt;E_u&lt;/code&gt; representation in alternative labelling schemes [1].&lt;/p&gt;&#xA;&lt;p&gt;[1] Which labelling schemes I don't know but I'm also not an expert in point groups.&#xA;Clicking on &lt;code&gt;blame&lt;/code&gt; will tell you that the last person who touched this code is Andrea dal Corso in 2006.&#xA;If you would like to contribute to improving the documentation, I suggest you &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/issues&quot; rel=&quot;nofollow noreferrer&quot;&gt;open an issue&lt;/a&gt; and ping @dalcorso for a reference concerning these symbols.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-09-05T18:54:38.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6685" PostTypeId="5" CreationDate="2021-09-05T22:46:41.120" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://aoterodelaroza.github.io/critic2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aoterodelaroza.github.io/critic2/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-05T22:46:41.120" LastActivityDate="2021-09-05T22:46:41.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6686" PostTypeId="4" CreationDate="2021-09-05T22:46:41.120" Score="0" Body="Questions about or related to the Critic2 software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-05T22:46:41.120" LastActivityDate="2021-09-05T22:46:41.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6687" PostTypeId="1" CreationDate="2021-09-06T01:45:40.043" Score="3" ViewCount="31" Body="&lt;p&gt;(Cross-posting from Chemistry.SE due to recommendation that this be posted here; &lt;a href=&quot;https://chemistry.stackexchange.com/questions/154064/question-regarding-conflicting-results-of-checking-the-electron-preciseness-of-i?noredirect=1#comment317320_154064&quot;&gt;see comment section&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;It is well known that the tert-butyl cation's empty 2p orbital on the central carbon is stabilised by hyperconjugation from neighboring C-H bonds. This would mean that the central 2p &amp;quot;lone pair&amp;quot; is antibonding in character in the tert-butyl cation; the same would go for the empty boron 2p orbital of trimethylborane and filled nitrogen 2p orbital of trimethylamine.&lt;/p&gt;&#xA;&lt;p&gt;However, when I did NBO calculations using the minimal STO-3G basis set on the aforementioned three species (note that the lattermost species is &amp;quot;two electrons too rich&amp;quot; of being isoelectronic with the first two) on Gaussian, I got a surprising answer- the empty &amp;quot;lone pair&amp;quot;s of both the tert-butyl cation and the trimethylborane molecule did turn out to be antibonding in character, but the filled &amp;quot;lone pair&amp;quot; of the trimethylamine molecule was not antibonding in character.&lt;/p&gt;&#xA;&lt;p&gt;Defining electron-preciseness of a molecule being the statement, if true, that &amp;quot;all molecular orbitals of molecule in question, up to (and including) the highest lying orbital(s) that are not antibonding, are doubly filled and all other orbitals are empty&amp;quot;, this would mean that both the trimethylborane molecule and the tert-butyl cation are electron-precise, while the trimethylnitrenium cation, being two electrons poor of the electron-precise trimethylamine molecule, would actually be electron-decifient. Since two isoelectronic species must be either both electron-precise, both electron-rich or both electron-deficient, this means that the NBO calculation method I used (Gaussian, STO-3G) does not accurately predict whether a &amp;quot;lone pair&amp;quot; is of antibonding character or not.&lt;/p&gt;&#xA;&lt;p&gt;My question now proceeds; which is electron-precise (via the above EHM-based definition) of the following species, trimethylborane or trimethylamine?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="5" LastEditDate="2021-09-06T04:26:21.160" LastActivityDate="2021-09-06T08:16:37.213" Title="Question regarding conflicting results of checking the electron-preciseness of isoelectronic species via NBO and EHM calculations" Tags="|molecular-modeling|electronic-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6688" PostTypeId="1" CreationDate="2021-09-06T02:01:14.617" Score="6" ViewCount="257" Body="&lt;p&gt;I'm working with the Siesta DFT software, and managed to reproduce the band structure of bulk Si without any issues. However, when trying the same with a Si nanowire, the band structure looks nowhere near those &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1386947705005345?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;published in literature&lt;/a&gt;, and there doesn't seem to be any bandgap either. Has anyone had previous experience with a similar situation?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/y9g5O.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y9g5O.png&quot; alt=&quot;Relevant figure from the article&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/n3W8U.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/n3W8U.png&quot; alt=&quot;Results from current calculations&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SystemName      Si&#xA;SystemLabel     Si&#xA;&#xA;NumberOfSpecies         1&#xA;NumberOfAtoms           85&#xA;&#xA;%block ChemicalSpeciesLabel&#xA;  1  14  Si&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;LatticeConstant 5.41 Ang&#xA;%block LatticeVectors&#xA;  16.00  0.00   0.00&#xA;   0.00  1.00   0.00&#xA;   0.00  0.00  16.00&#xA;%endblock LatticeVectors&#xA;&#xA;AtomCoorFormatOut  Ang&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;35.1650000000 0.0000000000 35.1650000000 1&#xA;36.5175000000 1.3525000000 36.5175000000 1&#xA;...&#xA;51.3950000000 2.7050000000 48.6900000000 1&#xA;50.0425000000 1.3525000000 50.0425000000 1&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA;   1  0   0  0.5&#xA;   0  16  0  0.5&#xA;   0  0   1  0.5&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;PAO.BasisSize           DZP&#xA;XC.functional           LDA      &#xA;XC.authors              CA       &#xA;SpinPolarized           .false.  &#xA;MeshCutoff              300 Ry   &#xA;kgrid_cutoff            100.0 Ang&#xA;&#xA;MD.TypeOfRun       CG               &#xA;MD.VariableCell    true             &#xA;MD.NumCGsteps      50               &#xA;MD.MaxCGDispl      0.1 Bohr         &#xA;MD.MaxForceTol     0.01 eV/Ang      &#xA;MD.MaxStressTol    0.0001 eV/Ang**3 &#xA;%block GeometryConstraints          &#xA;&#xA;%endblock GeometryConstraints&#xA;&#xA;MD.UseSaveXV  true&#xA;MaxSCFIterations   100&#xA;DM.MixingWeight    0.01&#xA;DM.NumberPulay     3&#xA;DM.Tolerance       1.d-3&#xA;ElectronicTemperature  25 meV&#xA;SolutionMethod    diagon&#xA;&#xA;BandLinesScale        pi/a&#xA;%block BandLines&#xA;1  0.0000000000 0.0000000000 0.0000000000 \Gamma&#xA;50 0.0000000000 1.0000000000 0.0000000000 Y&#xA;%endblock BandLines&#xA;&#xA;%block WaveFuncKPoints&#xA;0.000 0.000 0.000 from 1 to 20&#xA;%endblock WaveFuncKPoints&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2022-01-14T01:41:38.953" LastActivityDate="2022-09-14T04:21:27.627" Title="Nanowire Band Structure using Siesta DFT" Tags="|density-functional-theory|band-structure|siesta|nanostructures|" AnswerCount="1" CommentCount="17" ContentLicense="CC BY-SA 4.0" />
  <row Id="6689" PostTypeId="1" AcceptedAnswerId="6690" CreationDate="2021-09-06T02:54:44.907" Score="5" ViewCount="838" Body="&lt;pre&gt;&lt;code&gt;114&#xA;&#xA;Ge 11.184091389011632 8.1000459052469 7.912778504608498 0.7601333333333333&#xA;Ge 8.15544869153235 6.003103511684641 4.013838014930662 0.7568333333333334&#xA;Ge 9.485968612508206 8.750636482182767 3.89712476883384 0.5934333333333334&#xA;....&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want to change the number of atoms, preferably using Python where it will automatically find the number atom. Such as here, we have 8 atoms but it shows 114. Any lead how to do this edit automatically for different input files.&lt;/p&gt;&#xA;" OwnerUserId="4219" LastActivityDate="2021-09-09T09:46:40.260" Title="How to edit the first line of XYZ file?" Tags="|molecular-modeling|python|software-input-file-request|" AnswerCount="4" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6690" PostTypeId="2" ParentId="6689" CreationDate="2021-09-06T05:08:03.087" Score="5" Body="&lt;p&gt;You could do this by just modifying the first line of the file.&lt;/p&gt;&#xA;&lt;p&gt;But here are some more general purpose utilities you could use (note it requires the &lt;code&gt;re&lt;/code&gt; module)&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def read_xyz(&#xA;    filename, &#xA;    scale=1.):&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot; Read xyz file&#xA;&#xA;    Params:&#xA;        filename (str) - name of xyz file to read&#xA;&#xA;    Returns:&#xA;        geom ((natoms,4) np.ndarray) - system geometry (atom symbol, x,y,z)&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    &#xA;    lines = open(filename).readlines()&#xA;    lines = lines[2:]&#xA;    geom = []&#xA;    for line in lines:&#xA;        mobj = re.match(r'^\s*(\S+)\s+(\S+)\s+(\S+)\s+(\S+)\s*$', line)&#xA;        geom.append((&#xA;            mobj.group(1),&#xA;            scale*float(mobj.group(2)),&#xA;            scale*float(mobj.group(3)),&#xA;            scale*float(mobj.group(4)),&#xA;            ))&#xA;    return geom&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def write_xyz(&#xA;    filename, &#xA;    geom, &#xA;    comment=0,&#xA;    scale=1.0 #(1.0/units.ANGSTROM_TO_AU),&#xA;    ):&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot; Writes xyz file with single frame&#xA;&#xA;    Params:&#xA;        filename (str) - name of xyz file to write&#xA;        geom ((natoms,4) np.ndarray) - system geometry (atom symbol, x,y,z)&#xA;&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    fh = open(filename,'w')&#xA;    fh.write('%d\n' % len(geom))&#xA;    fh.write('{}\n'.format(comment))&#xA;    for atom in geom:&#xA;        fh.write('%-2s %14.6f %14.6f %14.6f\n' % (&#xA;            atom[0],&#xA;            scale*atom[1],&#xA;            scale*atom[2],&#xA;            scale*atom[3],&#xA;            ))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you read the file and then write the file it will automatically save it with the correct number of atoms.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-09-06T05:08:03.087" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6691" PostTypeId="2" ParentId="4412" CreationDate="2021-09-06T05:55:00.313" Score="4" Body="&lt;p&gt;I've put some code online &lt;a href=&quot;https://gist.github.com/craldaz/b38e1c951d515c807c67aac303406343&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gist.github.com/craldaz/b38e1c951d515c807c67aac303406343&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;that demonstrates how one removes translations and rotations from the Hessian using the description you linked &lt;a href=&quot;https://web.archive.org/web/20191229092611/https://gaussian.com/vib/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://web.archive.org/web/20191229092611/https://gaussian.com/vib/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;First you have to form the axes of inertia which is done in the function &lt;code&gt;eckart_frame&lt;/code&gt;, then the basis of vibrations is formed in the function &lt;code&gt;vibrational_basis&lt;/code&gt; and finally the hessian is projected into this vibrational basis in &lt;code&gt;normal_modes&lt;/code&gt; to remove all the translations and rotations.&lt;/p&gt;&#xA;&lt;p&gt;The axes of inertia are used in the &lt;code&gt;vibrational_basis&lt;/code&gt; function to form the matrix TR (or D in the web archive) which contains all translations and rotation. The null space of TR is the vibrational basis, B, in the Eckart frame. The final projection to get the Hessian in internal coordinates is done using B&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_{int} = BHB$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;*Note that I am using the SVD and not the Gram-Schmidt algorithm the Gaussian archive uses. It's much easier to do.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-09-06T05:55:00.313" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6692" PostTypeId="2" ParentId="6687" CreationDate="2021-09-06T08:16:37.213" Score="3" Body="&lt;p&gt;Note that there is no absolute distinction between non-bonding orbitals and bonding (or antibonding) orbitals, especially in multiatomic molecules, because the orbitals that are generally considered as non-bonding still more or less mix with the orbitals of neighboring atoms. For example, the oxygen lone pairs of water are usually regarded as perfectly non-bonding orbitals, but they are not, since they mix with the hydrogen 2s and 2p orbitals.&lt;/p&gt;&#xA;&lt;p&gt;As NBO is designed for arbitrary basis sets (not just minimal ones), to meaningfully allow for non-bonding orbitals, one must define non-bonding orbitals as orbitals whose bonding and antibonding characters are below a certain non-zero threshold. Thus the lone pair of trimethylamine is classified as non-bonding, because its antibonding character is below the default threshold.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-06T08:16:37.213" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6693" PostTypeId="2" ParentId="4388" CreationDate="2021-09-06T11:19:16.873" Score="2" Body="&lt;p&gt;&lt;strong&gt;Your interpretation of the results.&lt;/strong&gt; I agree with you that if you find no imaginary frequencies in the cubic phase it means it is at a local minimum of the potential energy landscape, and that if you do find imaginary frequencies for the tetragonal phase, then that one is at a saddle point. I also agree that a phase exhibiting imaginary frequencies may be stabilized by entropic contributions (see more below). Just a small caveat at this point: entropic contributions typically favor higher symmetry phases, so I am a little surprised that you find a stable cubic phase but an unstable tetragonal phase. This suggests that the cubic phase is the low temperature phase, while the tetragonal phase is the high temperature phase. In many compounds (e.g. perovskites) this is usually the other way around. Either way, the comments below apply to any unstable phase.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Finite temperature stabilization.&lt;/strong&gt; While you are correct that a phase exhibiting imaginary phonons may be stabilized by entropic finite temperature contributions, your approach to evaluate these looks incorrect. If I understand what you are doing, then you are evaluating the Helmholtz free energy as a function of temperature using the harmonic approximation. While this is fine for a phase without imaginary phonons, this is incorrect for a phase with imaginary phonons. How would you include the contribution of the imaginary modes to the free energy? Instead, what you need to do is to include &lt;em&gt;anharmonic&lt;/em&gt; terms in the expansion of the potential energy landscape. This is the only way in which you may be able to accurately evaluate the Helmholtz free energy of a phase that exhibits imaginary phonons at the harmonic level.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Anharmonic calculations.&lt;/strong&gt; There are a variety of strategies to include anharmonic terms in the calculations to evaluate the Helmholtz free energy. Methods range from molecular dynamics to the self-consistent harmonic approximation, and which one is more appropriate will depend on the details of your system. However, their computational expense is significantly larger than that of harmonic calculations.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-09-06T11:19:16.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6694" PostTypeId="1" CreationDate="2021-09-06T18:08:46.380" Score="11" ViewCount="131" Body="&lt;p&gt;In Quantum ESPRESSO turning &lt;strong&gt;lraman&lt;/strong&gt; to &lt;em&gt;true&lt;/em&gt; in the &lt;strong&gt;ph.x&lt;/strong&gt; input is not possible if the material is made to converge using &lt;strong&gt;smearing&lt;/strong&gt;. Is there any way to circumvent this, as my material isn't a metallic a system, and increasing the &lt;strong&gt;ecutwfc&lt;/strong&gt; , &lt;strong&gt;ecutrho&lt;/strong&gt; or &lt;strong&gt;k-pioints&lt;/strong&gt; doesnt help ?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2022-01-14T01:42:17.323" LastActivityDate="2022-01-14T01:42:17.323" Title="Is it possible to calculate non-resonant Raman coefficient in Quantum ESPRESSO for systems that require smearing to converge?" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6695" PostTypeId="1" CreationDate="2021-09-06T19:23:35.017" Score="4" ViewCount="53" Body="&lt;p&gt;I've modeled a QDFET transistor of sorts at an atomic scale, as it's not a standard MOSFET, and was wondering how to do a drain current/gate voltage simulation. I don't really have any idea how to begin with this, and was wondering anyone had any guidance. Thank you!&lt;/p&gt;&#xA;&lt;p&gt;More specifically, I was trying to simulate the results of &lt;a href=&quot;https://www.nature.com/articles/s41467-020-18932-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper, however simulation of transistors beyond the standard FET model is fairly limited from what my google searches tell me.&lt;/p&gt;&#xA;&lt;p&gt;In addition, I asked the authors of above paper, and they listed to read &lt;a href=&quot;https://www.nature.com/articles/s41598-021-86790-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper of theirs.&lt;/p&gt;&#xA;" OwnerUserId="4236" LastEditorUserId="4236" LastEditDate="2021-09-09T03:17:42.270" LastActivityDate="2021-09-09T03:17:42.270" Title="Simulate drain current gate voltage for QDFET" Tags="|software|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-28T02:59:10.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="6696" PostTypeId="1" AcceptedAnswerId="6702" CreationDate="2021-09-07T05:37:17.023" Score="8" ViewCount="257" Body="&lt;p&gt;I'm trying to simulate a ZnO nanoribbon structure using TranSIESTA in the siesta package. When I performed the transport calculations, for a few bias points within the bias window, the transmission spectrum value exceeded 1.&lt;br /&gt;&#xA;The transmission spectrum gives the probability of transmission of electrons. Since it is a probability function, its value shouldn't exceed 1.&lt;/p&gt;&#xA;&lt;p&gt;Are my simulation results correct?&lt;/p&gt;&#xA;" OwnerUserId="4239" LastEditorUserId="887" LastEditDate="2021-09-07T13:02:19.217" LastActivityDate="2021-09-08T17:39:25.337" Title="Can transmission spectrum value exceed 1 within bias window?" Tags="|density-functional-theory|siesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6699" PostTypeId="1" CreationDate="2021-09-07T06:19:00.410" Score="5" ViewCount="187" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/brYVx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/brYVx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;I have below &lt;code&gt;&amp;amp;SYSTME&lt;/code&gt; information from my input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      &amp;amp;CONTROL&#xA;      calculation = 'scf'&#xA;      etot_conv_thr =   1.0000000000d-04&#xA;      forc_conv_thr =   1.0000000000d-04&#xA;      outdir = './tmp/'&#xA;      prefix = 'pwscf'&#xA;      pseudo_dir = './'&#xA;      tprnfor = .true.&#xA;      tstress = .true.&#xA;      verbosity = 'high'&#xA;    /&#xA;    &amp;amp;SYSTEM&#xA;      degauss =   1.4699723600d-02&#xA;      ecutrho =   3.6000000000d+02&#xA;      ecutwfc =   4.5000000000d+01&#xA;      ibrav = 0&#xA;      nat = 12&#xA;      nosym = .false.&#xA;      ntyp = 2&#xA;      occupations = 'smearing'&#xA;      smearing = 'cold'&#xA;    /&#xA;    &amp;amp;ELECTRONS&#xA;      conv_thr =   1.0000000000d-09&#xA;      electron_maxstep = 100&#xA;      mixing_beta =   3.0000000000d-01&#xA;    /&#xA;    ATOMIC_SPECIES&#xA;    Ta       ta_pbe_v1.4.uspp.F.UPF&#xA;    Ni       ni_pbe_v1.4.uspp.F.UPF&#xA;    ATOMIC_POSITIONS crystal&#xA;   Ta            0.0000000000       0.0000000000       0.2500000000 &#xA;   Ta            0.0000000000       0.0000000000       0.7500000000 &#xA;   Ta            0.5000000000       0.5000000000       0.7500000000 &#xA;   Ta            0.5000000000       0.5000000000       0.2500000000 &#xA;    Ni           0.1677000000       0.6677000000       0.0000000000 &#xA;    Ni           0.3323000000       0.1677000000       0.0000000000 &#xA;    Ni           0.8323000000       0.3323000000       0.0000000000 &#xA;    Ni           0.6677000000       0.8323000000       0.0000000000 &#xA;    Ni           0.1677000000       0.3323000000       0.5000000000 &#xA;    Ni           0.6677000000       0.1677000000       0.5000000000 &#xA;    Ni           0.8323000000       0.6677000000       0.5000000000 &#xA;    Ni           0.3323000000       0.8323000000       0.5000000000 &#xA;    K_POINTS automatic&#xA;    7 7 8 0 0 0&#xA;    CELL_PARAMETERS angstrom&#xA;          4.9910000000       0.0000000000       0.0000000000&#xA;          0.0000000000       4.9910000000       0.0000000000&#xA;          0.0000000000       0.0000000000       4.2470000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I make ferromagnetic, anti-ferromagnetic, and ferrimagnetic structures from it?&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="789" LastEditDate="2021-09-14T10:07:15.597" LastActivityDate="2021-09-14T10:07:15.597" Title="How to make ferro, feri and antiferro magnetic structure for QE" Tags="|density-functional-theory|quantum-espresso|magnetism|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6701" PostTypeId="2" ParentId="6689" CreationDate="2021-09-07T06:47:32.580" Score="2" Body="&lt;p&gt;This is a strange type question. First, there is something wrong with the xyz file having total 5 columns.&#xA;For you answer,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Find total row number (let it be r)&lt;/li&gt;&#xA;&lt;li&gt;calculate r-2 (since the format of the xyz is that after the total number of atoms, there is a gap followed by atomic coordinates. The end of atomic coordinate specifications ends the file)&lt;/li&gt;&#xA;&lt;li&gt;replace first line(row) with r-2 value.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You either do it with bash or python you like.&lt;/p&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2021-09-07T06:47:32.580" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6702" PostTypeId="2" ParentId="6696" CreationDate="2021-09-07T08:35:35.323" Score="5" Body="&lt;p&gt;Each &lt;em&gt;electron&lt;/em&gt; has an associated transmission probability, put in another common nomenclature is that for every &lt;em&gt;channel&lt;/em&gt; you'll have a transmission probability between 0 and 1. So if you have 2 channels you can get between 0 and 2 and so forth.&lt;/p&gt;&#xA;&lt;p&gt;So your simulations seems perfectly fine.&lt;/p&gt;&#xA;&lt;p&gt;For bulk systems you can see the number of &lt;em&gt;channels&lt;/em&gt; in the bandstructure. Basically each energy crosses a set number of bands, for bulk systems the transmission equals the number of bands crossed at that energy.&lt;br /&gt;&#xA;Only when introducing defects will you see fractional transmissions that can still maximally be the number of bands for the electrodes at the given energy (remember the electrons originate from the electrodes).&lt;/p&gt;&#xA;&lt;p&gt;When applying a bias the electrodes are still in equilibrium since one only shifts the electronic structure. This is the basis for NEGF calculations in TranSiesta, OpenMX, ATK etc.. I.e. the eigenspectrum of an electrode at &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; gets all eigenvalues shifted according to &lt;span class=&quot;math-container&quot;&gt;$\epsilon(\mu) = \epsilon(0) + \mu$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So the same procedure about examining the bandstructures from the electrodes applies, simply examine energies while taking into account the chemical potentials.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-09-08T17:39:25.337" LastActivityDate="2021-09-08T17:39:25.337" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6703" PostTypeId="2" ParentId="6689" CreationDate="2021-09-07T14:40:30.743" Score="3" Body="&lt;p&gt;More a comment than an answer, note that e.g., for methane&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;5&#xA;&#xA;C          0.92745       -0.05402        0.04264&#xA;H          2.01965       -0.05402        0.04264&#xA;H          0.56338        0.81142        0.60065&#xA;H          0.56338       -0.96998        0.51313&#xA;H          0.56338       -0.00348       -0.98585&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the first line including &lt;code&gt;5&lt;/code&gt; (in this example) announces how many atoms will follow &lt;em&gt;past&lt;/em&gt; the second line which may be used for comments (like the name of structure/molecular weight as a label-like e.g., &lt;a href=&quot;https://github.com/openbabel/openbabel&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenBabel&lt;/a&gt; does).  Thus keep this integer consistent with the content.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-09-07T14:40:30.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6704" PostTypeId="1" CreationDate="2021-09-07T15:39:06.777" Score="6" ViewCount="116" Body="&lt;p&gt;I have a question regarding to how to construct an operator from k.p Hamiltonian. Maybe there are some problems in my understanding, I hope you can point me out and correct my description if I made something wrong below.&lt;/p&gt;&#xA;&lt;p&gt;We know that the k.p Hamiltonian can be obtained by taking the inner product of the basis function that belongs to the same irreducible representation for a given point group. Another way is to write down the tight binding model explicitly and do the expansion. For example, the Dirac Hamiltonian obtained by expanding the tight binding element in the high symmetry point in graphene. But for the former, I don't how to construct an operator explicitly. As I understand, for a tight binding Hamiltonian, we can monitor how the basis was transformed so that we can write down the explicit matrix representation of a certain symmetry operation. I want to split this into 2 sub-questions.&lt;/p&gt;&#xA;&lt;p&gt;Like I said above, if the effective k.p Hamiltonian can be obtained by doing an expansion around the high symmetry point in the tight binding element, does it mean that the basis of the k.p Hamiltonian matrix obtained from the point group approach must correspond to some basis in my tight binding matrix?&#xA;If yes, that means I can use the symmetry operator in my tight binding form to act on the effective k.p form. If no, how can we construct it explicitly?&lt;/p&gt;&#xA;" OwnerUserId="621" LastEditorUserId="1179" LastEditDate="2021-09-07T17:39:59.633" LastActivityDate="2021-09-07T17:39:59.633" Title="Constructing the symmetry operator from k.p Hamiltonian" Tags="|band-structure|condensed-matter|symmetry|solid-state-physics|tight-binding|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-14T02:32:54.270" ContentLicense="CC BY-SA 4.0" />
  <row Id="6705" PostTypeId="2" ParentId="6678" CreationDate="2021-09-07T19:35:46.817" Score="8" Body="&lt;p&gt;If I understand your question correctly, you are saying that you have seen cases where time is included in the calculation of the radial distribution function (RDF).&lt;/p&gt;&#xA;&lt;p&gt;The RDF itself does not depend on time (and its calculation does not depend on any timestep). That is, the RDF is calculated as an ensemble average, so that either molecular dynamics or monte carlo could be used and it would make no difference.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, if you have a system which is undergoing large structural changes over time, one could calculate an RDF over a sliding window of a trajectory to get a better view of what transformation is taking place. So, in this case, the RDF you are calculating for each window is not necessarily the equilibrium RDF, but is more like a semi-local (in time) RDF.&lt;/p&gt;&#xA;&lt;p&gt;For instance, if one were heating up a system throughout the course of an MD simulation, then taking various slices of the total trajectory and calculating some RDFs would give you a picture of how the structure is changing with temperature. None of these RDFs, however, are necessarily the equilibrium RDFs you would get if you ran a full simulation at that particular temperature.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-09-07T19:35:46.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6706" PostTypeId="1" CreationDate="2021-09-07T21:44:58.880" Score="8" ViewCount="68" Body="&lt;p&gt;I would like to generate wavefunctions as functions of spatial coordinates (X, Y, Z) using Gaussian G09 and then visualize them. How might I go about doing this? I am using Linux and my preferred visualization software is Gmolden.&lt;/p&gt;&#xA;" OwnerDisplayName="C M" LastEditorUserId="7" LastEditDate="2021-09-08T01:59:05.713" LastActivityDate="2021-09-08T01:59:05.713" Title="Visualizing wavefunctions in real space" Tags="|computational-chemistry|gaussian|visualization-software|wavefunctions|" AnswerCount="0" CommentCount="1" ClosedDate="2021-10-29T17:17:25.347" ContentLicense="CC BY-SA 4.0" />
  <row Id="6707" PostTypeId="1" CreationDate="2021-09-08T06:38:19.980" Score="3" ViewCount="813" Body="&lt;p&gt;What is the procedure to do lattice optimization, encut optimization and kpoint optimization in VASP?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4238" LastActivityDate="2021-09-08T13:37:27.433" Title="How to do lattice optimization, encut optimization and Kpoint optimization in VASP?" Tags="|density-functional-theory|vasp|k-points|cell-optimization|optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6708" PostTypeId="1" AcceptedAnswerId="6712" CreationDate="2021-09-08T09:27:02.977" Score="9" ViewCount="656" Body="&lt;p&gt;I am trying to calculate isothermal compressibility from an NPT molecular dynamics simulation, but am not that experienced and don't know how to use an expression from a paper to do it.&lt;/p&gt;&#xA;&lt;p&gt;The part that confuses me is the &lt;span class=&quot;math-container&quot;&gt;$\Delta V^2$&lt;/span&gt; term in the numerator.  I know that to calculate &lt;span class=&quot;math-container&quot;&gt;$\langle V\rangle$&lt;/span&gt; in the denominator, I should take the average of the volume over a simulation. Does anyone know what the &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt; term in the numerator means and how to apply it to volume data like this example, where each value represents a different time step?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;34.5&#xA;35.4&#xA;33.2&#xA;30.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I read in a forum that it is the &amp;quot;fluctuation&amp;quot; volume.  The only thing I can come up with is that it means the change in volume from one timestep to another (so &lt;span class=&quot;math-container&quot;&gt;$\Delta V^2$&lt;/span&gt; at timestep &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; would be &lt;span class=&quot;math-container&quot;&gt;$\Delta V_{i-1} - \Delta V_{i}$&lt;/span&gt;) but that seems strange because I'm pretty sure there should be no path dependence.  Maybe I'm wrong?&lt;/p&gt;&#xA;&lt;p&gt;The equation I'm referencing is from [1] and I have reproduced it below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\beta_T=\frac{1}{k_BT}\frac{\langle\Delta V^2\rangle_{NTP}}{\langle V\rangle_{NTP}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Voichita M. Dadarlat and Carol Beth Post J. Phys. Chem. B 2001, 105, 715-724 DOI: 10.1021/jp0024118 (Also available &lt;a href=&quot;https://www.purdue.edu/postlab/wp-content/uploads/Publications/2001JPCDadarlat-wSI.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1035" LastEditorUserId="7" LastEditDate="2021-09-08T13:57:00.633" LastActivityDate="2021-09-08T16:58:48.870" Title="Calculating compressibility from a molecular dynamics simulation: what is meant by &quot;volume fluctuation&quot;?" Tags="|molecular-dynamics|molecular-modeling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6710" PostTypeId="2" ParentId="6707" CreationDate="2021-09-08T13:29:20.753" Score="7" Body="&lt;p&gt;You can start with this bash script for Aluminum to begin&lt;/p&gt;&#xA;&lt;p&gt;Note: Make sure to fix two quantities while changing third one among &lt;code&gt;INCAR&lt;/code&gt;,&lt;code&gt;KPOINTS&lt;/code&gt;,&lt;code&gt;POSCAR&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Lattice optimization&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in `seq -w 4.01 0.01 4.05` # change the range needed&#xA;do&#xA;cat &amp;lt;&amp;lt;EOF &amp;gt;POSCAR&#xA;Al bulk FCC&#xA;&lt;span class=&quot;math-container&quot;&gt;$i&#xA;0 0.5 0.5&#xA;0.5 0 0.5&#xA;0.5 0.5 0&#xA;1&#xA;direct&#xA;0.0    0.0     0.0&#xA;EOF&#xA;mkdir $&lt;/span&gt;i&#xA;cp INCAR &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cp POSCAR $&lt;/span&gt;i/&#xA;cp POTCAR &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cp KPOINTS $&lt;/span&gt;i/&#xA;cd &lt;span class=&quot;math-container&quot;&gt;$i&#xA;/apps/VASP/vasp.6.2.0/original/bin/vasp_std  # This is vasp run command add mpi if needed&#xA;# post process &#xA;E=`grep 'F' OSZICAR|tail -n 1 | awk '{ print $5}'`;&#xA;echo $&lt;/span&gt;i $E &amp;gt;&amp;gt;../pos-conv.txt&#xA;cd ..&#xA;done&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Encut optimization&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in `seq -w 300 50 500` # change the range needed&#xA;do&#xA;cat &amp;lt;&amp;lt;EOF &amp;gt;INCAR&#xA;SYSTEM = Al :fcc&#xA;ISTART=0         # start new job&#xA;ICHARG=2         # 2 for atom&#xA;INIWAV=1         # initial wave function&#xA;ENCUT= $i eV # Energy cut-off for calculation&#xA;PREC = Normal    # Normal Precision&#xA;LREAL= .FALSE    # real space projection .FALSE.&#xA;LCHARGE= .FALSE  # no charge file output&#xA;LWAVE= .FALSE    # no wavefile output&#xA;NCORE=4          # NCORE specifies how many cores store one orbital&#xA;ISMEAR = 1;     # smearing&#xA;SIGMA = 0.2      # smearing value&#xA;ISIF = 2;        # 2- scf CALCULATION/IONIC MOVEMENT # 3 for volume relax&#xA;IBRION=2         # cg&#xA;NELM=30         # Maximum number of iteration&#xA;NELMIN=3         # Minimum number of iteration&#xA;NSW=30           # number of step for ionic update&#xA;EDIFF=1E-5       # stopping criteria for electronic update&#xA;EDIFFG=-0.01     # force convergence&#xA;EOF&#xA;&#xA;mkdir &lt;span class=&quot;math-container&quot;&gt;$i&#xA;cp INCAR $&lt;/span&gt;i/&#xA;cp POSCAR &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cp POTCAR $&lt;/span&gt;i/&#xA;cp KPOINTS &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cd $&lt;/span&gt;i&#xA;/apps/VASP/vasp.6.2.0/original/bin/vasp_std  # This is vasp run command add mpi if needed&#xA;# post process &#xA;E=`grep 'F' OSZICAR|tail -n 1 | awk '{ print $5}'`;&#xA;echo &lt;span class=&quot;math-container&quot;&gt;$i $&lt;/span&gt;E &amp;gt;&amp;gt;../incar-conv.txt&#xA;cd ..&#xA;done&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;KPOINTS optimization&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in `seq  1 1 5` # change the range needed&#xA;do&#xA;cat &amp;lt;&amp;lt;EOF &amp;gt;KPOINTS&#xA;MONK #header file&#xA;0&#xA;M&#xA;&lt;span class=&quot;math-container&quot;&gt;$i $&lt;/span&gt;i &lt;span class=&quot;math-container&quot;&gt;$i&#xA;0 0 0&#xA;EOF&#xA;mkdir $&lt;/span&gt;i&#xA;cp INCAR &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cp POSCAR $&lt;/span&gt;i/&#xA;cp POTCAR &lt;span class=&quot;math-container&quot;&gt;$i/&#xA;cp KPOINTS $&lt;/span&gt;i/&#xA;cd &lt;span class=&quot;math-container&quot;&gt;$i&#xA;/apps/VASP/vasp.6.2.0/original/bin/vasp_std  # This is vasp run command add mpi if needed&#xA;# post process &#xA;E=`grep 'F' OSZICAR|tail -n 1 | awk '{ print $5}'`;&#xA;echo $&lt;/span&gt;i $E &amp;gt;&amp;gt;../kconv.txt&#xA;cd ..&#xA;done&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2021-09-08T13:37:27.433" LastActivityDate="2021-09-08T13:37:27.433" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6712" PostTypeId="2" ParentId="6708" CreationDate="2021-09-08T16:58:48.870" Score="8" Body="&lt;p&gt;The fluctuation volume &lt;span class=&quot;math-container&quot;&gt;$\langle\Delta V^2\rangle$&lt;/span&gt; is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Variance&quot; rel=&quot;noreferrer&quot;&gt;variance&lt;/a&gt; of the volume V, defined as the squared distance between V and the average volume &lt;span class=&quot;math-container&quot;&gt;$\langle V \rangle$&lt;/span&gt;, averaged over the trajectory:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle\Delta V^2\rangle = \langle(V - \langle V \rangle)^2\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It can easily be computed with the following equivalent formula, where &lt;span class=&quot;math-container&quot;&gt;$\langle V^2 \rangle$&lt;/span&gt;  is the average over the trajectory of the squared volume:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle\Delta V^2\rangle = \langle V^2 \rangle - \langle V \rangle^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This method to compute the compressibility assumes that equilibrium is reached and that the system volume fluctuates around the mean volume long enough so that the result is independent of the precise path at equilibrium.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-09-08T16:58:48.870" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6713" PostTypeId="1" CreationDate="2021-09-07T17:05:21.147" Score="7" ViewCount="293" Body="&lt;p&gt;I'm working on this project where I have to simulate a gold nanoparticle impact in a gold plate, my script is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;units           metal&#xA;boundary        p p p&#xA;&#xA;atom_style      atomic&#xA;atom_modify map array sort 0 0.0&#xA;read_data       system.lammps&#xA;mass             1  196.97&#xA;&#xA;&#xA;pair_style      eam/alloy &#xA;pair_coeff      * * Au.lammps.eam Au&#xA;&#xA;&#xA;region          1 block   35.00 65.00 35.00 65.00 26.509 100.00  &#xA;group           A region 1&#xA;region          2 block   0.0 101.9575 0.0 101.9575 4.078 26.509    &#xA;group           B region 2 &#xA;region          3 block   0.0 101.9575 0.0 101.9575 0.0 4.078&#xA;group           C region 3&#xA;&#xA;fix             4 C setforce 0.0 0.0 0.0&#xA;&#xA;&#xA;timestep        0.001&#xA;neighbor    0.3 bin&#xA;neigh_modify    delay 0 every 1 check yes&#xA;thermo_style    custom step temp pe ke &#xA;&#xA;&#xA;thermo          100&#xA;fix         5 all box/relax dilate all &#xA;minimize        1.0e-6 1.06e-6 10000 10000&#xA;run             1&#xA;unfix           5&#xA;&#xA;&#xA;&#xA;velocity        A set 0.0 0.0 -5.00 rot yes mom yes dist gaussian &#xA;run             0&#xA;compute         7 A com &#xA;variable        com equal c_7[1]&#xA;variable        com equal c_7[2]&#xA;variable        com equal c_7[3]&#xA;fix             11 A print v_com &amp;quot;coords of center of mass&amp;quot; file cdm.dat&#xA;run             100&#xA;---------------------------------------&#xA;uncompute       7&#xA;fix             8 all nvt temp 300.00 300.00 0.1&#xA;compute         10 all ke/atom&#xA;variable        E atom c_10&#xA;dump            12 all custom 10 energy.dat c_10&#xA;&#xA;&#xA;&#xA;dump            9 all custom 10 dump_system.lammpstrj id element x y z c_10&#xA;dump_modify     9 element Au &#xA;run             20500&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The error I get is:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Fix print timestep variable returned a bad timestep.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have read the LAMMPS documentation but I could not come up with a solution, perhaps I can get some help?&lt;/p&gt;&#xA;" OwnerDisplayName="Rodolfo Damián Chapa González" LastEditorUserId="7" LastEditDate="2021-09-13T19:22:54.400" LastActivityDate="2021-09-13T19:22:54.400" Title="How to fix &quot;bad timestep&quot; error in LAMMPS?" Tags="|molecular-dynamics|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6714" PostTypeId="1" AcceptedAnswerId="6763" CreationDate="2021-09-08T23:22:13.520" Score="12" ViewCount="556" Body="&lt;p&gt;Which quantum chemistry methods can be used in an external electrostatic field?  Also which software supports that?   I'm interested in anything from semiempirical (eg XTB) to DFT (eg ωB97, B3LYP-D3) to coupled cluster (eg DLPNO-CCSD(T)).  The only starting point I have is a few mentions of &lt;a href=&quot;http://gaussian.com/field/&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;Field=&lt;/code&gt; keyword&lt;/a&gt; in Gaussian and a mention of an undocumented &lt;code&gt;efield&lt;/code&gt; keyword in the ORCA forums.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to add a field to (eg) a calculator in ASE?  Do any of the open source codes like psi4, xtb, libxc etc support this?&lt;/p&gt;&#xA;&lt;p&gt;Also, more generally: when doing electrostatic embedding between QM and MM, certainly an electric field has to be passed from the MM to the QM system - how is this usually handled?  It is probably not a single planar field or dipole, I'm guessing it must involve passing either a multipole (for the nearest MM atoms with their partial charges), or an approximation of that as a multipole with fewer virtual charge sites.  In open source software that supports QM/MM with electrostatic embedding, where/how exactly is the field passed along?&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2021-09-09T04:22:12.573" LastActivityDate="2022-01-11T13:00:40.370" Title="Quantum chemistry in external electrostatic field?" Tags="|molecular-dynamics|quantum-chemistry|gaussian|orca|electric-field|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6715" PostTypeId="2" ParentId="6713" CreationDate="2021-09-09T05:38:03.987" Score="7" Body="&lt;p&gt;Your problem comes from the line:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;fix             11 A print v_com &amp;quot;coords of center of mass&amp;quot; file cdm.dat&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;As per the &lt;a href=&quot;https://docs.lammps.org/fix_print.html&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;, the correct syntax is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;fix ID group-ID print N string keyword value ...&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where it will print every &lt;code&gt;N&lt;/code&gt; timesteps. So you are asking LAMMPS to print the same message every &lt;code&gt;v_com&lt;/code&gt; timesteps. And LAMMPS is respectfully telling you that it finds that confusing since &lt;code&gt;v_com&lt;/code&gt; is not an integer. You might wanna check this doc page in more details.&lt;/p&gt;&#xA;&lt;p&gt;Also, as an aside, although I can't be certain what you really intended to get from the way you defined the same com variable 3 times in a row, I'm  pretty confident it's not what you're going to get&lt;/p&gt;&#xA;" OwnerUserId="3967" LastEditorUserId="85" LastEditDate="2021-09-09T09:20:01.733" LastActivityDate="2021-09-09T09:20:01.733" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6716" PostTypeId="2" ParentId="6689" CreationDate="2021-09-09T09:46:40.260" Score="3" Body="&lt;p&gt;It should be easy to achieve what you want with a bash script. For a file named &lt;code&gt;test.xyz&lt;/code&gt;, it can be achieved with:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;fname=test.xyz&#xA;nlines=`wc -l $fname | awk '{print $1}'`&#xA;natoms=$((nlines-2))&#xA;sed -i &amp;quot;1s/.*/$natoms/&amp;quot; $fname&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This follows the logic given in the answer by @Prasanta. It should be easy to change this to a script taking the filename as input so that you can do the same with many input files.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2021-09-09T09:46:40.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6717" PostTypeId="2" ParentId="6647" CreationDate="2021-09-09T15:19:08.817" Score="6" Body="&lt;p&gt;In addition to ProfM's answer, for many materials it's typical for the band extrema to be on high symmetry points or lines. Sampling these lines can often help you find the extrema or a point close to it.&lt;/p&gt;&#xA;&lt;p&gt;However, there are several schemes for determining what lines in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-space to sample, including:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The scheme from Setyawan and Curtarolo &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2010.05.010&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.commatsci.2010.05.010&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The scheme from Hinuma et al. &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2016.10.015&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.commatsci.2016.10.015&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The newer scheme from Latimer and Munro &lt;a href=&quot;https://www.nature.com/articles/s41524-020-00383-7&quot; rel=&quot;noreferrer&quot;&gt;https://www.nature.com/articles/s41524-020-00383-7&lt;/a&gt; (disclaimer, I am also on this paper) which adds some lines missing in previous schemes&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These schemes are accessible via the Python code &lt;em&gt;pymatgen&lt;/em&gt; and the &lt;a href=&quot;https://pymatgen.org/pymatgen.symmetry.bandstructure.html#pymatgen.symmetry.bandstructure.HighSymmKpath&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;HighSymmKpath&lt;/code&gt; class&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note that this method will not be robust for all materials! Sometimes very fine uniform sampling of the Brillouin zone is required as ProfM notes. In this case, tools which help to interpolate between &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points like &lt;a href=&quot;https://www.imc.tuwien.ac.at/index.php?id=21094&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;BoltTraP2&lt;/code&gt;&lt;/a&gt; may help you refine your search.&lt;/p&gt;&#xA;" OwnerUserId="1333" LastActivityDate="2021-09-09T15:19:08.817" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6718" PostTypeId="1" CreationDate="2021-09-09T19:32:28.013" Score="6" ViewCount="1154" Body="&lt;p&gt;Hope you're all doing well. I am a student of Doctorate in Beijing Institute of Technology. We are working on a project &amp;quot;DNA Regulated Nanozyme&amp;quot;. and we intend to build an interaction between DNA and Nanozyme and for this we need to do the MD simulation of our nanoparticle &amp;quot;Iron Manganese Silicone Nanoparticle&amp;quot; (IMSN). It is actually a silicon nanoparticle. And I am using LAMMPS for its simulation. But, I am new to LAMMPS so I can't understand how to build its input script file? Like what are the basic things I need to have for LAMMPS input script? Like I tried Avogadro to build its structure but couldn't able to make its structure. is there any way that how can I build my nanoparticle structure in Avogadro and then convert it into LAMMPS format for input script file?&#xA;I shall be very thankful to you for this help&#xA;Regards and Thanks&#xA;Misbah Naseem&lt;/p&gt;&#xA;" OwnerUserId="4100" LastActivityDate="2021-11-19T10:40:36.477" Title="How to make input script file for nanoparticle using LAMMPS?" Tags="|molecular-dynamics|lammps|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6719" PostTypeId="1" AcceptedAnswerId="6720" CreationDate="2021-09-09T22:18:49.887" Score="9" ViewCount="460" Body="&lt;p&gt;Regarding the branch of matter modeling that deals with electronic structure methods, I think we can divide it in two camps: Those who work mostly with planewave-based software, geared towards periodic systems, typical of solid-state physics research; and those working mostly with software based on atom-centered Gaussian type orbitals, geared toward molecular systems, typical of quantum chemistry research. There's a lot of overlap between both camps, but I think people tend to stick mostly with one kind of system, in their research.&lt;/p&gt;&#xA;&lt;p&gt;Said that, as someone more familiar with systems typical of quantum chemistry, even before having the hard numbers to back it up, I always had the impression my peers at the solid-state physics community were better served in terms of free software / open source tools (and even just &amp;quot;free as in beer&amp;quot; tools), while we were mostly stuck to expensive proprietary tools, the alternatives being much less well known and used. I even felt a bit envious because of this.&lt;/p&gt;&#xA;&lt;p&gt;Now I noticed &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6683/243&quot;&gt;this answer&lt;/a&gt; to one previous question here: &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/95/243&quot;&gt;More matter modeling codes or better codes?&lt;/a&gt;&amp;quot;, where user @leopold.talirz pointed to a study preprint(1) where they systematically reviewed available matter modeling packages, their citation counts, source availability (either closed, available, copyleft or permissive) and cost (either commercial, free, or free only for academics). Then I actually downloaded the data in &lt;a href=&quot;https://atomistic.software/#/&quot; rel=&quot;noreferrer&quot;&gt;their site&lt;/a&gt;, to check if my impression about this was right or not. I think it is mostly correct. If we filter by the &amp;quot;PW&amp;quot; tag, for planewave, we get this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aeR9W.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aeR9W.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;While filtering by &amp;quot;GTO&amp;quot; tag, we get this scenario:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SKuYa.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SKuYa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As we see, while both graphs show commercial software with high counts, the one for software with PW tags shows a sizeable fraction of total citation counts associated to noncommercial free / open source codes, specially to the gold standard copyleft licenses. Note the absence of opaque closed source codes. So the software ecosystem here looks healthier. For software with GTO tags, the share of free / open source is much lower.&lt;/p&gt;&#xA;&lt;p&gt;So I ask, what are the causes for this matter modeling software freedom gap between PW-based codes and GTO-based codes?&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;(1). Talirz, Leopold, et al. “Trends in atomistic simulation software usage”. arXiv:2108.12350 [cond-mat, physics:physics], agosto de 2021. arXiv.org, &lt;a href=&quot;http://arxiv.org/abs/2108.12350&quot; rel=&quot;noreferrer&quot;&gt;http://arxiv.org/abs/2108.12350&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2021-09-10T14:16:20.330" LastActivityDate="2021-09-10T14:16:20.330" Title="Why is the planewave codes ecosystem healthier on free/opensource software adoption, when compared to codes supporting atom-centered orbitals?" Tags="|quantum-chemistry|solid-state-physics|open-source|history|free-software|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6720" PostTypeId="2" ParentId="6719" CreationDate="2021-09-09T23:26:24.653" Score="8" Body="&lt;p&gt;Disclaimer: These are just some observations; I don't claim to know the answer to this question.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There's a lot of overlap between both camps, but I think people tend to stick mostly with one kind of system, in their research.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You may be largely correct - I'd just like to point out that if we are looking at the simulation engines (rather than what people do) there now are some that marry both worlds, such as CP2K or NWChem.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;what are the causes for this matter modeling software freedom gap between PW-based codes and GTO-based codes?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Some possible factors to consider:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The citations to commercial codes in this dataset are strongly dominated by Gaussian on the GTO side and VASP on the PW side (together they account for &amp;gt;50% of citations to commercial codes). Findings may therefore be difficult to generalize.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Quantum chemistry programs have had a substantial head start on solid state. The first version of Gaussian was released 1970; for VASP I don't know the date of the first public release but &lt;a href=&quot;https://github.com/ltalirz/atomistic-software/issues/8&quot; rel=&quot;noreferrer&quot;&gt;I guess at some point in the late 1990s depending on the definition of the term&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;On this time scale, open-source in scientific software is a relatively recent development - the GPL licenses were published in the 1990s [1].&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;[1] While the MIT license was created earlier (in the 1980s), the popularity of permissive licenses like MIT has only very recently (late 2000s) gained more prominence, at least as far as the codes in this dataset are concerned.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-09-09T23:26:24.653" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6721" PostTypeId="1" AcceptedAnswerId="6722" CreationDate="2021-09-10T10:32:43.823" Score="11" ViewCount="5772" Body="&lt;p&gt;When submitting a scientific paper written using LaTeX, to a journal, which high-quality image format do you usually use?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-09-10T23:54:14.970" LastActivityDate="2021-09-10T23:54:14.970" Title="Which image format is best to use in a scientific paper?" Tags="|software-recommendations|publishing|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6722" PostTypeId="2" ParentId="6721" CreationDate="2021-09-10T13:22:27.200" Score="19" Body="&lt;p&gt;For scientific papers in matter modeling, I always use &lt;a href=&quot;https://en.wikipedia.org/wiki/Vector_graphics&quot; rel=&quot;noreferrer&quot;&gt;vector graphics&lt;/a&gt; (e.g. &lt;code&gt;.eps&lt;/code&gt;, &lt;code&gt;.pdf,&lt;/code&gt; or &lt;code&gt;.svg&lt;/code&gt;, though the journals will not typically accept &lt;code&gt;.svg&lt;/code&gt; format).&lt;/p&gt;&#xA;&lt;p&gt;I stopped publishing in ACS journals (e.g. JCTC and JACS) after they turned one of my vector graphics into a pixelated &lt;a href=&quot;https://en.wikipedia.org/wiki/Raster_graphics&quot; rel=&quot;noreferrer&quot;&gt;raster&lt;/a&gt;, before publishing it. Even though it was 2015, and I'd been publishing papers with vector graphics in journals like JCP for many years already, they said they don't accept EPS or PDF files, when I was publishing &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ct501066k&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; in JCTC. In Figure 2, you can see the difference between the published version (top) zoomed in as much as possible (and yet still pixelated) and the &lt;a href=&quot;https://arxiv.org/abs/1411.3654&quot; rel=&quot;noreferrer&quot;&gt;version on arXiv&lt;/a&gt; (bottom) which can be zoomed in much more, and still doesn't get pixelated (&lt;strong&gt;click the image to see it larger&lt;/strong&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Jw8I2.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Jw8I2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6721/which-image-format-to-use-in-scientific-paper/6722#comment14652_6721&quot;&gt;Camps explained in his comment&lt;/a&gt;, they only accepted TIFF files at the time:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Date: Tue, 9 Jun 2015 at 10:01 &lt;br&gt;&#xA;Subject: RE: FW: ct-2014-01066k Why&#xA;Quantum Coherence Is Not Important in the FennaMatthewsOlsen Complex&lt;/p&gt;&#xA;&lt;p&gt;Dr. Dattani,&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your message concerning this manuscript. We are&#xA;currently exploring the use of vector graphics, but at this time we&#xA;are unable to grant your request. If you wish to see if tif files&#xA;submitted as explained below would improve the resolution of your&#xA;figures,  you may send new files directly to me by e-mail.  Please&#xA;advise.&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&lt;/p&gt;&#xA;&lt;p&gt;Production Assistant &lt;br&gt;&#xA;American Chemical Society&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That was in response to an email in which I'd complained that the label for picoseconds in my original vector graphic (bottom of image below) had been pixelated by the journal when they converted it to a raster (top of image below), here is a screenshot of that email I sent:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5SLJ7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5SLJ7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;Buttonwood made some very good points &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6721/which-image-format-to-use-in-scientific-paper/6722#comment14653_6722&quot;&gt;this comment&lt;/a&gt;, with which I completely agree. Vector images have searchable text whereas raster images typically do not. &lt;strong&gt;Furthermore the size of the image will be much smaller if you use a vector graphic instead of a raster:&lt;/strong&gt; arXiv has a limit on the size of the files submitted, and I once had a submission that was at least 10x too big in file size to get through arXiv's submission portal, but when I converted the figures to PDF format, the entire paper's size was about 53kB.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-10T13:43:30.630" LastActivityDate="2021-09-10T13:43:30.630" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6723" PostTypeId="1" CreationDate="2021-09-10T13:54:39.297" Score="5" ViewCount="747" Body="&lt;p&gt;Using RDKit (2020.09.5) I would like to assign InChi to molecules expressed as SMILES and fail to replicate this &lt;a href=&quot;https://gist.github.com/vfscalfani/f10c4718e8d2e48586c48674a654aa20&quot; rel=&quot;noreferrer&quot;&gt;GitHub gist&lt;/a&gt; for initial training written about 2 years ago (RDKit 2019.03.2). I would like to know if the required instruction changed, or if I miss importing/adjusting a relevant function/parameter then causing the errors.&lt;/p&gt;&#xA;&lt;p&gt;To quote the relevant code there:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# Load RDKit modules&#xA;from rdkit import Chem&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;from rdkit.Chem import Draw&#xA;&#xA;# Construct a molecular object from a SMILES string&#xA;m1 = Chem.MolFromSmiles('COC(=O)C1CN1C(=O)OCC2=CC=CC=C2')&#xA;&#xA;# Calculate InChI&#xA;Chem.MolToInchi(m1)&#xA;&#xA;# Calculate InChIKey&#xA;Chem.MolToInchiKey(m1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, neither the anticipated InChi (&lt;code&gt;'InChI=1S/C12H13NO4/c1-16-11(14)10-7-13(10)12(15)17-8-9-5-3-2-4-6-9/h2-6,10H,7-8H2,1H3'&lt;/code&gt;) nor the hash, i.e. InChiKey &lt;code&gt;'GTZJUBQWCWZING-UHFFFAOYSA-N'&lt;/code&gt; are accessible for me.&lt;/p&gt;&#xA;&lt;p&gt;Instead, the Jupyter notebook mentions the following errors:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;AttributeError                            Traceback (most recent call last)&#xA;&amp;lt;ipython-input-9-71f9b591b71d&amp;gt; in &amp;lt;module&amp;gt;&#xA;      8 &#xA;      9 # Calculate InChI&#xA;---&amp;gt; 10 Chem.MolToInchi(m1)&#xA;     11 &#xA;     12 # Calculate InChIKey&#xA;&#xA;AttributeError: module 'rdkit.Chem' has no attribute 'MolToInchi'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Following the recommendation in RDKit's manual here, I thought the substitution of &lt;code&gt;Chem.MolToInchi(m1)&lt;/code&gt; by &lt;code&gt;Chem.inchi.MolToInchi(m1)&lt;/code&gt; would remove the road block.  Contrary to anticipation, however, this doesn't work either:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;AttributeError                            Traceback (most recent call last)&#xA;&amp;lt;ipython-input-10-cddee16a293d&amp;gt; in &amp;lt;module&amp;gt;&#xA;      9 # Calculate InChI&#xA;     10 # Chem.MolToInchi(m1)&#xA;---&amp;gt; 11 Chem.inchi.MolToInchi(m1)&#xA;     12 &#xA;     13 # Calculate InChIKey&#xA;&#xA;AttributeError: module 'rdkit.Chem.inchi' has no attribute 'MolToInchi'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-09-12T16:53:44.877" Title="Change in RDKit's encoding of InChi?" Tags="|computational-chemistry|rdkit|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6724" PostTypeId="1" AcceptedAnswerId="6727" CreationDate="2021-09-10T14:51:18.247" Score="10" ViewCount="874" Body="&lt;p&gt;I have no experience in using Latex, but I am planning to use it for publishing purposes. Could you please recommend any resources that help me to learn in less time (at least the basics on how to publish an article using it)?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-09-11T12:46:18.243" LastActivityDate="2021-09-17T10:28:35.833" Title="How can I learn LaTeX?" Tags="|software-recommendations|publishing|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6725" PostTypeId="2" ParentId="6724" CreationDate="2021-09-10T16:07:46.870" Score="13" Body="&lt;p&gt;I personally started with &amp;quot;The Not So Short Introduction to LaTeX&amp;quot;, a PDF file that should come with most LaTeX distributions under the name &amp;quot;lshort.pdf&amp;quot;. The document claims that it can be read in 139 minutes (the precise number depends on the version). I remember I didn't finish it in such a short time (perhaps the given time estimate was for native English speakers, which I'm not) but in the worse case it won't take you more than half a day to read. While you read it, it's beneficial to create a tex file, actually type some commands (including inserting equations, tables, graphics, etc.) into it and compile the file.&lt;/p&gt;&#xA;&lt;p&gt;lshort.pdf does not contain all information you need, but the remaining intricacies are usually sufficiently few that you won't have much trouble googling them every time you encounter them. Another great resource for LaTeX-related problems is the &lt;a href=&quot;https://tex.stackexchange.com/&quot;&gt;LaTeX stack exchange&lt;/a&gt;, although googling LaTeX-related questions will usually lead you there anyway.&lt;/p&gt;&#xA;&lt;p&gt;If you are already relatively certain about the journal that your next paper will be submitted to, it's also beneficial to download the LaTeX template of that journal, once you learned the basics of LaTeX. It may save you some time if you type your article directly into that template, and frequently compile the document before you finish, to detect and correct the errors as soon as possible, so that you don't repeat any given error when you write the subsequent sections of the paper.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-10T16:07:46.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6726" PostTypeId="2" ParentId="6721" CreationDate="2021-09-10T16:23:15.147" Score="13" Body="&lt;p&gt;&lt;em&gt;Complementary&lt;/em&gt; to the answer given by Nike Dattani with focus on file format, I would like to draw your attention to how you present &lt;em&gt;the content&lt;/em&gt;  visually in photos, schemes and diagrams known as &lt;em&gt;artwork&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Regardless of the file format eventually elected (where suitable, vector based like .(e)ps or .pdf), determine in advance the dimension of the illustration: Are you invited to design the outer/inner title of the issue of the journal, may you use color(s), will the illustration span over two columns, or are you constrained to the width of a single narrow column.   This may be a guide to balance the content and detail it contains.&lt;/p&gt;&#xA;&lt;p&gt;The blueprints by architects, datavisualizations in the newspapers, or work e.g., by &lt;a href=&quot;https://www.edwardtufte.com/tufte/&quot; rel=&quot;noreferrer&quot;&gt;Edward Tufte&lt;/a&gt; may be &lt;em&gt;an inspiration&lt;/em&gt; to remove clutter and reorganization e.g., if the illustration is a photography.  Beside inspiration by illustrations by your colleagues, well maintained scientific journals provide advice, too (&lt;a href=&quot;https://journals.iucr.org/c/services/help/artwork/guide.html&quot; rel=&quot;noreferrer&quot;&gt;example IUCr&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If the illustration isn't a photography, design it like a flag -- easy recognizable from distance (e.g., Chicago):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Keep It Simple.&lt;/li&gt;&#xA;&lt;li&gt;Use Meaningful Symbolism.&lt;/li&gt;&#xA;&lt;li&gt;Use 2 or 3 Basic Colors.&lt;/li&gt;&#xA;&lt;li&gt;(...)&lt;/li&gt;&#xA;&lt;li&gt;Be Distinctive or Be Related.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;(Credit to &lt;a href=&quot;https://nava.org/content.aspx?page_id=22&amp;amp;club_id=622278&amp;amp;module_id=475721&quot; rel=&quot;noreferrer&quot;&gt;Good Flag, Bad Flag&lt;/a&gt; compiled by &lt;a href=&quot;https://nava.org/&quot; rel=&quot;noreferrer&quot;&gt;NAVA&lt;/a&gt;.  I do not think their point 4 is relevant here.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So if you plot data in a diagram, consider markers clearly distinctive by color, yet &lt;em&gt;still&lt;/em&gt; distinctive &lt;em&gt;by shape&lt;/em&gt; if the publication isn't transmitted in color passing a Xerox:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kWv5X.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kWv5X.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;https://journals.iucr.org/c/services/help/artwork/guide.html&quot; rel=&quot;noreferrer&quot;&gt;image credit&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Note: If you start with a too large dimensions, the journal's request to scale the illustration to fit into a single column may render these markers difficult/impossible to discern (especially if a publisher converts them into pixel bitmaps).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The more discrete colors in the illustration, the more the &lt;em&gt;potential&lt;/em&gt; lost of information when this is reproduced in grey scale:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dco36.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dco36.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;https://journals.iucr.org/c/services/help/artwork/guide.html&quot; rel=&quot;noreferrer&quot;&gt;image credit&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Use freely accessible tools like &lt;a href=&quot;https://colorbrewer2.org&quot; rel=&quot;noreferrer&quot;&gt;ColorBrewer2&lt;/a&gt; to probe color schemes &lt;em&gt;safe enough&lt;/em&gt; to convey sequential/diverging, or qualitative data.  You may toggle on/off options for greyscale, photocopy, color blindness.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Consider color blindness.  There are much more men (and to lesser extent, women) prone to this, than you might think (&lt;a href=&quot;https://jfly.uni-koeln.de/html/color_blind/&quot; rel=&quot;noreferrer&quot;&gt;see examples&lt;/a&gt;).  Check your illustration in advance with tools like &lt;a href=&quot;https://www.vischeck.com/vischeck/vischeckImage.php&quot; rel=&quot;noreferrer&quot;&gt;visicheck&lt;/a&gt;, or your image editor (&lt;a href=&quot;https://docs.gimp.org/en/gimp-display-filter-dialog.html#gimp-deficient-vision&quot; rel=&quot;noreferrer&quot;&gt;example GIMP&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If your illustration is a 2D projection of 3D map where e.g., intensity of a property is color encoded, substitute default color schemes like «jet» by one like «viridis» (continous data):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XhyF4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XhyF4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;http://www.kennethmoreland.com/color-advice/&quot; rel=&quot;noreferrer&quot;&gt;credit&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;or «blue-white-red» about divergent data by «bent-cool-warm»:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0fCwj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0fCwj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;http://www.kennethmoreland.com/color-advice/&quot; rel=&quot;noreferrer&quot;&gt;credit&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;It is worth to invest some time and effort into this topic. The work by &lt;a href=&quot;http://www.kennethmoreland.com/color-advice/&quot; rel=&quot;noreferrer&quot;&gt;Kenneth Moreland&lt;/a&gt; (&lt;a href=&quot;https://www.youtube.com/watch?v=xAoljeRJ3lU&quot; rel=&quot;noreferrer&quot;&gt;a presentation&lt;/a&gt;), or &lt;a href=&quot;https://www.youtube.com/watch?v=XjHzLUnHeM0&quot; rel=&quot;noreferrer&quot;&gt;Kristen Thyng&lt;/a&gt; may guide you further. Often, such palettes are freely available for e.g., Python's &lt;a href=&quot;https://matplotlib.org/stable/tutorials/colors/colormaps.html&quot; rel=&quot;noreferrer&quot;&gt;mathplotlib&lt;/a&gt;, or &lt;a href=&quot;http://www.gnuplotting.org/tag/palette/&quot; rel=&quot;noreferrer&quot;&gt;gnuplot&lt;/a&gt;; so, once set up well, it will work in the background for you.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It isn't easy to follow all these points at once equally well.  Like any profession, it asks for training, curiosity, and testing.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-09-10T16:23:15.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6727" PostTypeId="2" ParentId="6724" CreationDate="2021-09-10T17:44:52.483" Score="15" Body="&lt;p&gt;As a gentle, free (as in free beer and as in &lt;a href=&quot;https://www.learnlatex.org/en/licenses&quot; rel=&quot;noreferrer&quot;&gt;free speech&lt;/a&gt;) on-line introduction, I would recommend &lt;a href=&quot;https://www.learnlatex.org/&quot; rel=&quot;noreferrer&quot;&gt;learnlatex.org&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;At the start, you choose one of currently eight languages (Catalan, German, English, Spanish, French, Marathi, Portuguese, Vietnamese).  Subsequently, all teaching is going to be provided in this language only.&lt;/p&gt;&#xA;&lt;p&gt;Later, you enter 16 core lessons; all at your pace, without hassle of installation.  These cover elementary concepts like document classes for articles, books, slides; how to interact with graphics, how to embed mathematics, the use of cross-references and citations.  Contrasting to other starter kits, the organization of larger projects with LaTeX2e or debugging errors equally is part of the game.  You train from your browser:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8UKyv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8UKyv.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;https://www.learnlatex.org/en/lesson-03&quot; rel=&quot;noreferrer&quot;&gt;credit&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;For work and generation of the .pdf in &lt;a href=&quot;https://www.overleaf.com/&quot; rel=&quot;noreferrer&quot;&gt;Overleaf&lt;/a&gt; (left hand button), a platform equally set up for collaborative edit, you need a log-in.  Your school may be among the subscribers.  To run the small examples, the work with TeXLive/LaTeX online (right hand button) does not require a subscription.&lt;/p&gt;&#xA;&lt;p&gt;Then, according to the language selected, there are special lectures.  For example, by TeX's age and origin in the States, the input of characters not covered by ASCII 7-bit (like in matériaux, polymères, École, garçon, Nöel from the Latin script) or use of a dedicated hyphenation pattern requires some information.&lt;/p&gt;&#xA;&lt;p&gt;The project doesn't aim to be an encyclopedia.  Joseph Wright, the moderator of the project, equally is maintainer of extensions for LaTeX2e (e.g., &lt;a href=&quot;https://ctan.org/pkg/siunitx&quot; rel=&quot;noreferrer&quot;&gt;siuntix&lt;/a&gt;) and moderator on &lt;a href=&quot;https://tex.stackexchange.com/&quot;&gt;https://tex.stackexchange.com/&lt;/a&gt;.  If your native language is not yet among the eight, you may contribute to the project's extension &lt;em&gt;via&lt;/em&gt; &lt;a href=&quot;https://github.com/learnlatex/learnlatex.github.io&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;, too.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="4266" LastEditDate="2021-09-15T13:28:17.063" LastActivityDate="2021-09-15T13:28:17.063" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6728" PostTypeId="1" CreationDate="2021-09-10T13:45:55.753" Score="8" ViewCount="247" Body="&lt;p&gt;While I have seen many papers in which Gaussian is used in calculations, I have not seen any paper in recent times where new methods are implemented in Gaussian. The latest paper I could find concerned the EDIIS method which was published nearly twenty years ago. Development of methods seems to happen in Q-Chem, Psi4 and TURBOMOLE.&lt;/p&gt;&#xA;&lt;p&gt;Is Gaussian too old, the code too deprecated or are there copyright issues?&lt;/p&gt;&#xA;" OwnerUserId="4334" OwnerDisplayName="BoringBoron" LastEditorUserId="5" LastEditDate="2021-09-11T00:40:32.413" LastActivityDate="2021-09-14T02:27:02.380" Title="Why are method developments and new implementations not done much in Gaussian?" Tags="|quantum-chemistry|computational-chemistry|density-functional-theory|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6729" PostTypeId="2" ParentId="6728" CreationDate="2021-09-11T01:59:04.977" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is Gaussian too old, the code too deprecated or are there copyright issues?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You mentioned &amp;quot;&lt;strong&gt;copyright issues&lt;/strong&gt;&amp;quot; but papers that are publicly available in academic journals are not subject to the type of copyright laws that would prevent Gaussian from being allowed to implement them.&lt;/p&gt;&#xA;&lt;p&gt;You suggested that the code is &lt;strong&gt;too deprecated&lt;/strong&gt; but if you look &lt;a href=&quot;https://gaussian.com/people/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; then click on &amp;quot;Collaborators&amp;quot;, you'll see a lot of academic researchers who appear as co-authors of at least one version of Gaussian, and still actively develop new methods, often using a developer version of Gaussian as a starting sandbox. &lt;/p&gt;&#xA;&lt;p&gt;The other suggestion you made was that GAUSSIAN is &lt;strong&gt;too old,&lt;/strong&gt; which is also not the case. &lt;a href=&quot;https://en.wikipedia.org/wiki/MOLPRO&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOLPRO development started in the 1960s&lt;/a&gt;, yet several &lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=recent_changes&quot; rel=&quot;nofollow noreferrer&quot;&gt;new features were implemented in the following new versions:&lt;/a&gt; 2021.2, 2021.1, 2020.2, 2020.1, 2019.2, 2018.1, etc.  These include, the &lt;a href=&quot;https://arxiv.org/abs/1701.07862&quot; rel=&quot;nofollow noreferrer&quot;&gt;AVAS method&lt;/a&gt; which was first in 2017, and PNO-LCCSD(T) and PNO-LCCSD(T)-F12 and  PNO-CASSCF and PNO-CASPT2 (which likely weren't available anywhere before 2015, though they are similar in spirit to the DLPNO methods in ORCA, which were also implemented for the first time much more recently than the nearly 20-years ago you mentioned for the development of EDIIS).&lt;/p&gt;&#xA;&lt;p&gt;So &lt;em&gt;&lt;strong&gt;if it's true&lt;/strong&gt;&lt;/em&gt; that MOLPRO, Q-Chem, Psi4, and TURBOMOLE are still implementing newly developed methods, substantially more than Gaussian, and you want to know why this might be, then read on:&lt;/p&gt;&#xA;&lt;p&gt;Psi4 is open-source, so I'm not surprised that it's still being actively developed and contains implementations of newly developed methods.&lt;/p&gt;&#xA;&lt;p&gt;None of the other software packages that you mentioned are open-source, so we can talk about those now. The newly developed methods that keep getting implemented in MOLPRO, Q-Chem, and TURBOMOLE are largely the developments of active researchers who are developers of those same software packages. It was asked here whether any non-free software packages have implemented any methods which are not available in any free software and also have been &lt;em&gt;used&lt;/em&gt; in publications &lt;em&gt;that are not by&lt;/em&gt; the developers of that method: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/584/5&quot;&gt;What significant matter modelling methods are implemented in commercial software, for which there is no freeware alternative?&lt;/a&gt;  No answers have been given to that question yet!  Specifically, I mentioned AVAS in MOLPRO, for which the original paper that I cited there had Gerald Knizia as the last-listed author, and Gerald happens to have also been one of the major contributors to MOLPRO (notice he is the [first author of the 2012 version, apart from the Werner an Knowles who happen to be the two main authors of the package). I also mentioned the PNO methods in MOLPRO, which according to the bibliography section of &lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=local_correlation_methods_with_pair_natural_orbitals_pnos&quot; rel=&quot;nofollow noreferrer&quot;&gt;this page&lt;/a&gt; were implemented based on 13 papers, all with Werner a co-author.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, the current &lt;a href=&quot;https://manual.q-chem.com/5.4/sect_features-5.4.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Q-Chem manual&lt;/a&gt; says that version 5.4 is the most recent, and the new features in 5.4 include methods like &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4977727&quot; rel=&quot;nofollow noreferrer&quot;&gt;incremental FCI&lt;/a&gt; based on Paul Zimmerman's papers, and Paul happens to be a co-author on the &lt;a href=&quot;https://scholar.google.com/citations?view_op=view_citation&amp;amp;hl=en&amp;amp;user=UsBTxRkAAAAJ&amp;amp;citation_for_view=UsBTxRkAAAAJ:qjMakFHDy7sC&quot; rel=&quot;nofollow noreferrer&quot;&gt;2015 Q-Chem paper&lt;/a&gt;. All members of the &lt;a href=&quot;https://www.q-chem.com/about/team/board/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Q-Chem Board of Directors&lt;/a&gt; except for Hilary Pople, are highly active &lt;em&gt;&lt;strong&gt;researchers&lt;/strong&gt;&lt;/em&gt; at universities.&lt;/p&gt;&#xA;&lt;p&gt;TURBOMOLE is similar, with the company being run by Wim Klopper (Karlsruhe Institute of Technology), David Tew (Oxford University), Christof Hättig  (Ruhr-Universität Bochum), etc.&lt;/p&gt;&#xA;&lt;p&gt;The last three paragraphs are in contrast to Gaussian, where if you go &lt;a href=&quot;https://gaussian.com/people/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; again but this time don't click anything, you'll see that Gaussian is run by employees who are full-time staff members of the company, and researchers who are running larger research groups of their own tend to be listed as &amp;quot;Collaborators&amp;quot;. This is in sharp contrast to what I described for MOLRPO, Q-Chem and TURBOMOLE, and if more academic research development is getting implemented into the latter three software packages than in Gaussian, it may be largely due to this difference in the &lt;em&gt;extent&lt;/em&gt; to which they've become &amp;quot;commercialized&amp;quot; (they're &lt;em&gt;&lt;strong&gt;all&lt;/strong&gt;&lt;/em&gt; commercial software packages, but &lt;strong&gt;they all began with researchers from &lt;em&gt;educational&lt;/em&gt; institutions&lt;/strong&gt; and the extent to which Gaussian's culture and main employees transitioned from educational-type environments to their newer corporate-type environment, seems to differ greatly considering that MOLPRO, Q-Chem and TURBOMOLE are all run by people still at universities whereas Gaussian is run by their own &lt;em&gt;full-time&lt;/em&gt; employees while researchers at educational institutions are relegated to the label of &amp;quot;collaborators&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Also: Gaussian has historically probably been the most popular of all of these software packages, in terms of the sheer number of users that have used it. When a user-base is as big as theirs, it's not always as easy to make changes to the code with consequences as mild as if the user-base is smaller.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-14T02:27:02.380" LastActivityDate="2021-09-14T02:27:02.380" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6730" PostTypeId="1" AcceptedAnswerId="6971" CreationDate="2021-09-11T08:39:25.037" Score="5" ViewCount="177" Body="&lt;p&gt;When using gnuplot scripts to generate graphs in PDF format, there is the &lt;code&gt;size&lt;/code&gt; option. I would like to know how one can estimate the right size of the output graph to place in a scientific paper.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-09-12T17:57:51.313" LastActivityDate="2021-10-29T22:02:19.523" Title="How to determine the right size of gnuplot terminal output?" Tags="|visualization-software|publishing|gnuplot|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6731" PostTypeId="2" ParentId="467" CreationDate="2021-09-11T08:56:00.023" Score="11" Body="&lt;h1&gt;MoleView&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Super lightweight&lt;/li&gt;&#xA;&lt;li&gt;Developed based on standard plotting library (Matplotlib)&lt;/li&gt;&#xA;&lt;li&gt;Very easy to install &lt;code&gt;pip install moleview&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;All-in-one command &lt;code&gt;moleview your_file.xyz&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;More info: &lt;a href=&quot;https://github.com/moleview/moleview&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/moleview/moleview&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NOI61.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NOI61.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="579" LastActivityDate="2021-09-11T08:56:00.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6732" PostTypeId="2" ParentId="6699" CreationDate="2021-09-11T16:44:09.947" Score="5" Body="&lt;p&gt;Since the question concerns only magnetic order, I am going to address only that, leaving out details about smearing and other parameters.&lt;/p&gt;&#xA;&lt;p&gt;Let's take a simple A-type magnetic system from this illustration.&lt;a href=&quot;https://i.stack.imgur.com/nIMcn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nIMcn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that there are primarily two types of magnetism: Intra-layer and inter-layer. I would advise the following procedure for creating your input file:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Determine what atoms in your system are magnetic - Is it the Ni, Ta etc..&lt;/li&gt;&#xA;&lt;li&gt;Determine what kind of spin arrangement you require - pay attention to both intra-layer and inter-layer channels.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As an example, let me work with the system in your question. Let's assume the nickel atoms are magnetic. You can clearly notice that 4 nickel atoms are in the same plane, and they are separated by half a lattice constant along 'z'. I can outline some ideas so that you get the general gist.&lt;/p&gt;&#xA;&lt;p&gt;a) A type antiferromagnet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Ni1           0.1677000000       0.6677000000       0.0000000000 &#xA;Ni1           0.3323000000       0.1677000000       0.0000000000 &#xA;Ni1           0.8323000000       0.3323000000       0.0000000000 &#xA;Ni1          0.6677000000       0.8323000000       0.0000000000 &#xA;Ni2           0.1677000000       0.3323000000       0.5000000000 &#xA;Ni2           0.6677000000       0.1677000000       0.5000000000 &#xA;Ni2           0.8323000000       0.6677000000       0.5000000000 &#xA;Ni2           0.3323000000       0.8323000000       0.5000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You would set starting_magnetization of Ni1 as 1 and starting_magnetization of Ni2 as -1.&lt;/p&gt;&#xA;&lt;p&gt;b) C-type antiferromagnet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Ni1           0.1677000000       0.6677000000       0.0000000000 &#xA;Ni2           0.3323000000       0.1677000000       0.0000000000 &#xA;Ni1           0.8323000000       0.3323000000       0.0000000000 &#xA;Ni2          0.6677000000       0.8323000000       0.0000000000 &#xA;Ni1           0.1677000000       0.3323000000       0.5000000000 &#xA;Ni2           0.6677000000       0.1677000000       0.5000000000 &#xA;Ni1           0.8323000000       0.6677000000       0.5000000000 &#xA;Ni2           0.3323000000       0.8323000000       0.5000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You would set starting_magnetization of Ni1 as 1 and starting_magnetization of Ni2 as -1.&lt;/p&gt;&#xA;&lt;p&gt;I hope you get the idea. For ferrimagnets, you would set the magnetization values so that the net value (whether intra or inter, depending on your system) is non-zero. Also keep in mind that for some systems the magnetic ordering of spins is in a specific direction - for example NiO. In these cases, I would advise you to thoroughly research the arrangement of spins before formulating your input file.&lt;/p&gt;&#xA;" OwnerUserId="683" LastActivityDate="2021-09-11T16:44:09.947" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6733" PostTypeId="2" ParentId="6653" CreationDate="2021-09-11T16:57:20.270" Score="5" Body="&lt;p&gt;Spin-orbit coupling scales as &lt;span class=&quot;math-container&quot;&gt;$Z^4/n^3$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; is the atomic number and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the principal quantum number. When you move down the periodic table and the nucleus becomes heavier and heavier, relativistic effects become more important.&lt;/p&gt;&#xA;&lt;p&gt;From a practical approach, when should you start incorporating SOC in your DFT calculations? From my experience, that cut-off has been Sulphur (Z=16). It's a good idea to perform a calculation with SOC turned on and investigate the results - if the difference is minimal, you can safely exclude SOC in your calculations. For me, this threshold is similar to the one I adopt for self-consistent calculations when testing different plane-wave cutoffs - Does the total energy of the system change by less than 10 meV/cell between non-SOC and SOC included cases? If so, I would safely ignore SOC. But I must provide a disclaimer here: I'm talking strictly in the context of electronic structure calculations - there could be other properties you could be interested in or exotic behavior such as in the case of Topological insulators.&lt;/p&gt;&#xA;" OwnerUserId="683" LastEditorUserId="52" LastEditDate="2021-09-11T21:42:08.833" LastActivityDate="2021-09-11T21:42:08.833" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6734" PostTypeId="2" ParentId="1888" CreationDate="2021-09-11T21:47:15.353" Score="3" Body="&lt;p&gt;You can enter an input file stream in gaussian cubman to add/subtract cube files. Eg. here is an input file named test.txt which has all answers to add two cube files (a.cube and b.cube) and gives an output sum.cube,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Add&#xA;a.cube&#xA;yes&#xA;b.cube&#xA;yes&#xA;sum.cube&#xA;yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can run this simply by entering,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cubman &amp;lt; test.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to get the required output.&lt;/p&gt;&#xA;&lt;p&gt;You can write a batch script to run multiple operations.&lt;/p&gt;&#xA;" OwnerUserId="4263" LastActivityDate="2021-09-11T21:47:15.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6735" PostTypeId="1" AcceptedAnswerId="6736" CreationDate="2021-09-11T22:20:28.073" Score="6" ViewCount="208" Body="&lt;p&gt;In computational material science, we need workflows for optimization surrogate models which requires high computation resources. I am actually concerned with why material science community is using &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1586/tools-for-high-throughput-dft-studies?newreg=67da6f06aa9144af97fa84a6c857f6d1&quot;&gt;FireWorks&lt;/a&gt; compared to highly supported workflow management package such as TensorFlow?&lt;/p&gt;&#xA;" OwnerUserId="1251" LastEditorUserId="5" LastEditDate="2021-09-12T17:13:15.757" LastActivityDate="2021-09-12T17:13:15.757" Title="FireWorks for Workflow management or TensorFlow" Tags="|high-performance-computing|materials-design|machine-learning|materials-informatics|computational-frameworks|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6736" PostTypeId="2" ParentId="6735" CreationDate="2021-09-11T23:23:20.820" Score="7" Body="&lt;p&gt;Tensorflow and FireWorks are different kinds of software. The &amp;quot;workflow management&amp;quot; features of Tensorflow are primarily designed to manage running Tensorflow itself, while FireWorks and related tools are designed to manage running other software.&lt;/p&gt;&#xA;&lt;p&gt;Tensorflow is a library for machine learning. It can be used to develop, train and evaluate machine learning models and provides some tooling to build model and data pipelines. Some comparable software to Tensorflow are &lt;a href=&quot;https://pytorch.org/&quot; rel=&quot;noreferrer&quot;&gt;PyTorch&lt;/a&gt;, &lt;a href=&quot;https://github.com/FluxML/Flux.jl&quot; rel=&quot;noreferrer&quot;&gt;Flux.jl&lt;/a&gt;, and &lt;a href=&quot;https://aesara.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;Aesara&lt;/a&gt; (formerly Theano). Environments like &lt;a href=&quot;https://reference.wolfram.com/language/guide/MachineLearning.html&quot; rel=&quot;noreferrer&quot;&gt;Wolfram Mathematica&lt;/a&gt; and &lt;a href=&quot;https://www.mathworks.com/solutions/machine-learning.html&quot; rel=&quot;noreferrer&quot;&gt;MATLAB&lt;/a&gt; also have comparable machine learning tools.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, FireWorks is a workflow management software. Some comparable software tools that are also general, not domain-specific are &lt;a href=&quot;https://luigi.readthedocs.io/en/stable/&quot; rel=&quot;noreferrer&quot;&gt;Luigi&lt;/a&gt; and &lt;a href=&quot;https://airflow.apache.org/&quot; rel=&quot;noreferrer&quot;&gt;Apache Airflow&lt;/a&gt;. These workflow management tools typically allow you to define and execute a directed graph of tasks with dependencies. The tasks can be anything from running code, shell scripts, running tasks that modify the workflow graph, and more. Workflow management tools are not used to build mathematical models, like the surrogate models you mentioned in your question.&lt;/p&gt;&#xA;&lt;p&gt;In matter modeling, workflow management tools are used to orchestrate running a series of calculations in a specific order,  enable passing relevant information between jobs, and to provide a high-level interface for managing job state. Some more matter modeling-specific examples are discussed &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1586/tools-for-high-throughput-dft-studies&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastEditorUserId="1179" LastEditDate="2021-09-11T23:28:37.417" LastActivityDate="2021-09-11T23:28:37.417" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6738" PostTypeId="1" AcceptedAnswerId="6739" CreationDate="2021-09-12T11:03:36.227" Score="7" ViewCount="284" Body="&lt;p&gt;I run some calculations using xTB. From one of the outputs I got:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;*** convergence criteria satisfied after 182 iterations ***&#xA;&#xA;         #    Occupation            Energy/Eh            Energy/eV&#xA;      -------------------------------------------------------------&#xA;         1        2.0000           -0.6285969             -17.1050&#xA;       ...           ...                  ...                  ...&#xA;       254        1.7813           -0.3250849              -8.8460&#xA;       255        1.7322           -0.3248659              -8.8401&#xA;       256        1.4992           -0.3241340              -8.8201&#xA;       257        1.3002           -0.3236807              -8.8078&#xA;       258        1.1554           -0.3233899              -8.7999&#xA;       259        1.1298           -0.3233404              -8.7985&#xA;       260        0.9584           -0.3230132              -8.7896 (HOMO)&#xA;       261        0.9131           -0.3229267              -8.7873 (LUMO)&#xA;       262        0.8611           -0.3228267              -8.7846&#xA;       263        0.7655           -0.3226383              -8.7794&#xA;       264        0.6860           -0.3224747              -8.7750&#xA;       265        0.6470           -0.3223914              -8.7727&#xA;       ...           ...                  ...                  ...&#xA;       516                         17.7730979             483.6306&#xA;      -------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: how can be the occupancy of molecular orbitals equal/above the LUMO greater than zero?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-09-13T13:09:25.547" Title="How is LUMO occupancy different from zero in XTB calculation?" Tags="|xtb|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6739" PostTypeId="2" ParentId="6738" CreationDate="2021-09-12T13:31:08.400" Score="8" Body="&lt;p&gt;XTB uses &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/sp.html#fermi-smearing&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fermi Smearing&lt;/a&gt; by default&#xA;at 300K. If you disable it, you should find that the virtual orbitals once again have zero occupancy.&lt;/p&gt;&#xA;" OwnerUserId="800" LastEditorUserId="800" LastEditDate="2021-09-13T13:09:25.547" LastActivityDate="2021-09-13T13:09:25.547" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6740" PostTypeId="2" ParentId="6723" CreationDate="2021-09-12T16:53:44.877" Score="3" Body="&lt;p&gt;Following &lt;code&gt;@Tyberius&lt;/code&gt; suggest, I departed from using Jupyter notebook in favor of the CLI.  In contrast of the GitHub gist,* the following script is to report InChi and InChiKey about pyridine:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;#!/bin/usr/env python3&#xA;&#xA;import rdkit&#xA;from rdkit import Chem&#xA;&#xA;molecule = Chem.MolFromSmiles('n1ccccc1')&#xA;&#xA;inchi = str(Chem.MolToInchi(molecule))&#xA;inchikey = str(Chem.MolToInchiKey(molecule))&#xA;&#xA;print(inchi)&#xA;print(inchikey)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to yield the strings&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;InChI=1S/C5H5N/c1-2-4-6-5-3-1/h1-5H&#xA;JUJWROOIHBZHMG-UHFFFAOYSA-N&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These match the output provided e.g., by the &lt;a href=&quot;https://chemdrawdirect.perkinelmer.cloud/js/sample/index.html#&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemDraw JS Sample Page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Notes taken &lt;em&gt;en route&lt;/em&gt; to this result:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Following the instructions by &lt;a href=&quot;https://www.rdkit.org/docs/Install.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDKit&lt;/a&gt;, a separate second Python interpreter was set up based on &lt;a href=&quot;https://docs.conda.io/en/latest/miniconda.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Miniconda&lt;/a&gt;.  While substantially smaller than a full Anaconda ecosystem, past the creation of a virtual environment by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;conda create -c conda-forge -n my-rdkit-env rdkit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the installation requires about &lt;span class=&quot;math-container&quot;&gt;$\pu{1.5 GB}$&lt;/span&gt; free space to include larger dependencies like &lt;code&gt;matplotlib&lt;/code&gt;, or &lt;code&gt;pandas&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;As of writing, this offers Python 3.9.7 and rdkit 2021.03.5 when working from the terminal.  The version of the later may be checked by either &lt;code&gt;print(rdkit.__version__)&lt;/code&gt;, or &lt;code&gt;import rdkit; help(rdkit); G&lt;/code&gt;.  For a reason beyond the scope of this question, Jupyter still was loading the elder version of rdkit provided by the hosting OS, 2020.09.5.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;*) RDKit 2019.03.2 the GitHub gist mentioned seems to be fine with the aziridine defined by the SMILES string &lt;code&gt;COC(=O)C1CN1C(=O)OCC2=CC=CC=C2&lt;/code&gt;. The present version of RDKit however recognizes the ambiguity present and prepends a note in the pattern of:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[hh:mm:ss] WARNING: Omitted undefined stereo&#xA;InChI=1S/C12H13NO4/c1-16-11(14)10-7-13(10)12(15)17-8-9-5-3-2-4-6-9/h2-6,10H,7-8H2,1H3&#xA;GTZJUBQWCWZING-UHFFFAOYSA-N&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In line with this, the Inchi -&amp;gt; structure conversion provided by the &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/edit3/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PubChem Sketcher&lt;/a&gt; draws a structure formula lacking wedges as if there were no (&lt;em&gt;R&lt;/em&gt;)/(&lt;em&gt;S&lt;/em&gt;) configuration.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-09-12T16:53:44.877" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6741" PostTypeId="5" CreationDate="2021-09-12T17:56:32.390" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Gnuplot&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Gnuplot&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-12T17:56:32.390" LastActivityDate="2021-09-12T17:56:32.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6742" PostTypeId="4" CreationDate="2021-09-12T17:56:32.390" Score="0" Body="Questions about or related to gnuplot." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-12T17:56:32.390" LastActivityDate="2021-09-12T17:56:32.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6743" PostTypeId="5" CreationDate="2021-09-12T18:50:51.647" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-12T18:50:51.647" LastActivityDate="2021-09-12T18:50:51.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6744" PostTypeId="4" CreationDate="2021-09-12T18:50:51.647" Score="0" Body="Questions about or related to disorder." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-12T18:50:51.647" LastActivityDate="2021-09-12T18:50:51.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6745" PostTypeId="1" CreationDate="2021-09-13T02:51:49.853" Score="6" ViewCount="84" Body="&lt;p&gt;I have written papers where code snippets are used much as one often uses equations: that is, a few lines of code are treated as a &amp;quot;display&amp;quot; block that should be part of the flow of the document, but separate from the paragraphs surrounding them. They are then followed by an explanation of the terms in that snippet. This is particularly useful when writing papers about software libraries, either to explain functionality or to illustrate how mathematical ideas map to the usage of library functions.&lt;/p&gt;&#xA;&lt;p&gt;I'm trying to do this in LaTeX, and would like the code snippets to have syntax highlighting. My question is: &lt;strong&gt;What tools to accomplish this are supported by various journals relevant to computational chemistry/chemical physics/matter modeling?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;To illustrate the problems I hope to avoid, this question comes from an experience I had in publishing a &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.8b00626&quot; rel=&quot;noreferrer&quot;&gt;pair&lt;/a&gt; of &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.8b00627&quot; rel=&quot;noreferrer&quot;&gt;papers&lt;/a&gt; that were very code-focused. We had used &lt;a href=&quot;https://ctan.org/pkg/minted&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;minted&lt;/code&gt;&lt;/a&gt; for nice, syntax-highlighted code. When we got to proofs, our code snippets had been treated as floating images that were then grouped together. Imagine grouping all the display equations in a paper -- the text where the display block was supposed to be becomes unintelligible. Additionally, because they were images, code snippets were also of all different sizes, and any change in proofs was like changing an image (i.e., we couldn't just say, &amp;quot;add a comma there,&amp;quot; because they couldn't edit the text). It took months of iterating on the proofs before the PDF/print versions looked okay. Even after that, the HTML rendering of the article is pretty bad. So I would say that &lt;code&gt;minted&lt;/code&gt; is &lt;em&gt;not&lt;/em&gt; well-supported by JCTC (at least, as of 2018/2019 when that paper was published).&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-09-13T02:51:49.853" Title="What LaTeX tools for code snippets are best-supported by matter modeling journals?" Tags="|publishing|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6746" PostTypeId="1" CreationDate="2021-09-13T12:32:19.307" Score="3" ViewCount="304" Body="&lt;p&gt;How can I determine the minimum of the conduction band of a semiconductor using DFT/VASP, or any other option?&lt;/p&gt;&#xA;" OwnerUserId="4272" LastActivityDate="2021-09-21T03:20:20.443" Title="Determining conduction band minimum of a semiconductor" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6747" PostTypeId="1" CreationDate="2021-09-13T13:48:25.033" Score="6" ViewCount="159" Body="&lt;p&gt;I was performing DFTB3 calculation with DFTB+ on water monomer. This is my input.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Geometry = xyzformat{&#xA;&amp;lt;&amp;lt;&amp;lt; &amp;quot;water.xyz&amp;quot;&#xA;}&#xA;&#xA;Driver{}&#xA;&#xA;Hamiltonian = DFTB {&#xA; SCC = Yes&#xA; SCCTolerance = 1.0e-08&#xA; SpinPolarisation = {}&#xA; SlaterKosterFiles {&#xA;  O-O = O-O.skf&#xA;  H-H = H-H.skf&#xA;  H-O = H-O.skf&#xA;  O-H = O-H.skf&#xA;  }&#xA; MaxAngularMomentum{&#xA;  O = p&#xA;  H = s&#xA; }&#xA; Filling = Fermi {&#xA;  Temperature [Kelvin] = 0.0&#xA; }&#xA; ThirdOrderFull = Yes&#xA; HubbardDerivs {&#xA;  O = -0.1575&#xA;  H = -0.1857&#xA; }&#xA;}&#xA;Options={}&#xA;ParserOptions {&#xA; ParserVersion = 5&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output it shows (I am attaching full output.)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;|===============================================================================&#xA;|&#xA;|  DFTB+ release 21.1&#xA;|&#xA;|  Copyright (C) 2006 - 2021  DFTB+ developers group&#xA;|&#xA;|===============================================================================&#xA;|&#xA;|  When publishing results obtained with DFTB+, please cite the following&#xA;|  reference:&#xA;|&#xA;|  * DFTB+, a software package for efficient approximate density functional&#xA;|    theory based atomistic simulations, J. Chem. Phys. 152, 124101 (2020).&#xA;|    [doi: 10.1063/1.5143190]&#xA;|&#xA;|  You should also cite additional publications crediting the parametrization&#xA;|  data you use. Please consult the documentation of the SK-files for the&#xA;|  references.&#xA;|&#xA;|===============================================================================&#xA;&#xA;Reading input file 'dftb_in.hsd'&#xA;Parser version: 9&#xA;&#xA;--------------------------------------------------------------------------------&#xA;***  Converting input from parser version  5 to parser version  9 ...&#xA;***  Done.&#xA;&#xA;Reading SK-files:&#xA;Done.&#xA;&#xA;&#xA;Processed input in HSD format written to 'dftb_pin.hsd'&#xA;&#xA;Starting initialization...&#xA;--------------------------------------------------------------------------------&#xA;OpenMP threads:              8&#xA;Chosen random seed:          44487222&#xA;Mode:                        Static calculation&#xA;Self consistent charges:     Yes&#xA;SCC-tolerance:                 0.100000E-07&#xA;Max. scc iterations:                    100&#xA;Shell resolved Hubbard:      No&#xA;Spin polarisation:           No&#xA;Nr. of up electrons:             4.000000&#xA;Nr. of down electrons:           4.000000&#xA;Periodic boundaries:         No&#xA;Electronic solver:           Relatively robust&#xA;Mixer:                       Broyden mixer&#xA;Mixing parameter:                  0.200000&#xA;Maximal SCC-cycles:                     100&#xA;Nr. of chrg. vec. in memory:              0&#xA;Electronic temperature:        0.100000E-07 H      0.272114E-06 eV&#xA;Initial charges:             Set automatically (system chrg:   0.000E+00)&#xA;Included shells:             O:  s, p&#xA;                             H:  s&#xA;Full 3rd order correction    Yes&#xA;Extra options:&#xA;                             Mulliken analysis&#xA;&#xA;--------------------------------------------------------------------------------&#xA;&#xA;***  Geometry step: 0&#xA;&#xA; iSCC Total electronic   Diff electronic      SCC error    &#xA;    1    0.00000000E+00    0.00000000E+00    0.78671399E+00&#xA;    2   -0.41164337E+01   -0.41164337E+01    0.58636504E+00&#xA;    3   -0.41186098E+01   -0.21761050E-02    0.27136865E-01&#xA;    4   -0.41207453E+01   -0.21354711E-02    0.16271916E-02&#xA;    5   -0.41207483E+01   -0.29932945E-05    0.22850510E-02&#xA;    6   -0.41207483E+01    0.57787499E-08    0.43132836E-04&#xA;    7   -0.41207483E+01   -0.21815850E-07    0.90476243E-07&#xA;    8   -0.41207483E+01   -0.74171780E-11    0.13073986E-11&#xA;&amp;gt;&amp;gt; Charges saved for restart in charges.bin&#xA;&#xA;Total Energy:                       -4.0618820527 H         -110.5294 eV&#xA;Extrapolated to 0K:                 -4.0618820527 H         -110.5294 eV&#xA;Total Mermin free energy:           -4.0618820527 H         -110.5294 eV&#xA;Force related energy:               -4.0618820527 H         -110.5294 eV&#xA;&#xA;&#xA;--------------------------------------------------------------------------------&#xA;DFTB+ running times                          cpu [s]             wall clock [s]&#xA;--------------------------------------------------------------------------------&#xA;SCC                                    +     0.07  ( 98.6%)      0.01  (100.0%)&#xA;--------------------------------------------------------------------------------&#xA;Missing                                +     0.00  (  1.4%)      0.00  (  0.0%)&#xA;Total                                  =     0.07  (100.0%)      0.01  (100.0%)&#xA;--------------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Previously I have calculated the same using HF/def2-QZVPPD having energy of ~-76 Hartree. My question is that, How can it be so different from -76 (HF) to -4 (DFTB3)?&#xA;Am I missing something?&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="2194" LastEditDate="2021-09-13T17:41:30.043" LastActivityDate="2021-09-13T17:41:30.043" Title="Differences between DFTB3 energy and HF energy" Tags="|hartree-fock|density-functional-tight-binding|dftb-plus|" AnswerCount="0" CommentCount="13" ClosedDate="2023-02-07T03:09:05.510" ContentLicense="CC BY-SA 4.0" />
  <row Id="6748" PostTypeId="2" ParentId="6728" CreationDate="2021-09-13T19:59:36.840" Score="4" Body="&lt;p&gt;Just to add 2 little cents regarding new methods in Gaussian - the extract from the Gaussian site (&lt;a href=&quot;http://www.gaussian.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;www.gaussian.com&lt;/a&gt;) about new methods in Gaussian 16:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;New Methods&#xA;Many DFT functionals have been added to Gaussian since the initial release of G09, including APFD [Austin12], functionals from the Truhlar group (most recently MN15 and MN15L [Yu16]) and PW6B95 &amp;amp; PW6B95D3 [Zhao05a].&#xA;Additional double-hybrid methods: DSDPBEP86 [Kozuch11], PBE0DH, PBEQIDH [Bremond11,Bremond14].&#xA;Empirical dispersion for a variety of functionals, using the schemes of Grimme (GD2, GD3, GD3BJ) [Grimme06, Grimme10, Grimme11] and others.&#xA;The PM7 semi-empirical method, both in the original formulation [Stewart13], and with modifications for continuous potential energy surfaces [Throssel17p].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1395" LastActivityDate="2021-09-13T19:59:36.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6749" PostTypeId="1" CreationDate="2021-09-14T10:36:19.333" Score="6" ViewCount="235" Body="&lt;p&gt;I would like to pick this problem from my previous post &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6699/how-to-make-ferro-feri-and-antiferro-magnetic-structure-for-qe/6732#6732&quot;&gt;See link&lt;/a&gt;.&#xA;I am clear about how to define &lt;code&gt;antiferromagnetism&lt;/code&gt; in QE.&#xA;Here I am with another issue.&lt;/p&gt;&#xA;&lt;p&gt;I am confused with &lt;code&gt;ferrimagnetism&lt;/code&gt; with Quantum ESPRESSO (QE).&#xA;Considering the same input file (mentioned below as well) from link [&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6699/how-to-make-ferro-feri-and-antiferro-magnetic-structure-for-qe/6732#6732&quot;&gt;1&lt;/a&gt;], I would like to know the difference between ferrimagnetism and antiferromagnetism in the QE input file.&lt;/p&gt;&#xA;&lt;p&gt;From the QE input file &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2019-March/042302.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;See link&lt;/a&gt;, I see this is the same as &lt;code&gt;antiferromagnetic&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      &amp;amp;CONTROL&#xA;      calculation = 'scf'&#xA;      etot_conv_thr =   1.0000000000d-04&#xA;      forc_conv_thr =   1.0000000000d-04&#xA;      outdir = './tmp/'&#xA;      prefix = 'pwscf'&#xA;      pseudo_dir = './'&#xA;      tprnfor = .true.&#xA;      tstress = .true.&#xA;      verbosity = 'high'&#xA;    /&#xA;    &amp;amp;SYSTEM&#xA;      degauss =   1.4699723600d-02&#xA;      ecutrho =   3.6000000000d+02&#xA;      ecutwfc =   4.5000000000d+01&#xA;      ibrav = 0&#xA;      nat = 12&#xA;      nosym = .false.&#xA;      ntyp = 2&#xA;      occupations = 'smearing'&#xA;      smearing = 'cold'&#xA;    /&#xA;    &amp;amp;ELECTRONS&#xA;      conv_thr =   1.0000000000d-09&#xA;      electron_maxstep = 100&#xA;      mixing_beta =   3.0000000000d-01&#xA;    /&#xA;    ATOMIC_SPECIES&#xA;    Ta       ta_pbe_v1.4.uspp.F.UPF&#xA;    Ni       ni_pbe_v1.4.uspp.F.UPF&#xA;    ATOMIC_POSITIONS crystal&#xA;   Ta            0.0000000000       0.0000000000       0.2500000000 &#xA;   Ta            0.0000000000       0.0000000000       0.7500000000 &#xA;   Ta            0.5000000000       0.5000000000       0.7500000000 &#xA;   Ta            0.5000000000       0.5000000000       0.2500000000 &#xA;    Ni           0.1677000000       0.6677000000       0.0000000000 &#xA;    Ni           0.3323000000       0.1677000000       0.0000000000 &#xA;    Ni           0.8323000000       0.3323000000       0.0000000000 &#xA;    Ni           0.6677000000       0.8323000000       0.0000000000 &#xA;    Ni           0.1677000000       0.3323000000       0.5000000000 &#xA;    Ni           0.6677000000       0.1677000000       0.5000000000 &#xA;    Ni           0.8323000000       0.6677000000       0.5000000000 &#xA;    Ni           0.3323000000       0.8323000000       0.5000000000 &#xA;    K_POINTS automatic&#xA;    7 7 8 0 0 0&#xA;    CELL_PARAMETERS angstrom&#xA;          4.9910000000       0.0000000000       0.0000000000&#xA;          0.0000000000       4.9910000000       0.0000000000&#xA;          0.0000000000       0.0000000000       4.2470000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="789" LastEditorUserId="5" LastEditDate="2021-12-27T23:48:43.540" LastActivityDate="2021-12-27T23:48:43.540" Title="How to define ferrimagnetism in Quantum ESPRESSO" Tags="|quantum-espresso|magnetism|solid-state-physics|software-input-file-request|anti-ferromagnetic|" AnswerCount="0" CommentCount="6" ClosedDate="2022-09-12T17:06:26.233" ContentLicense="CC BY-SA 4.0" />
  <row Id="6750" PostTypeId="1" CreationDate="2021-09-14T11:37:47.850" Score="8" ViewCount="47" Body="&lt;p&gt;I am running Multi Reference Configuration Interaction calculations for Aluminium Flouride molecule in its &lt;span class=&quot;math-container&quot;&gt;$A^1\Pi$&lt;/span&gt; state interacting with Helium. For a complete Potential energy surface, I am doing the same for multiple geometries which permit interpolation to fully account for the symmetries of the interaction. My question is when I run the MRCI calculation for the linear configuration (when He approached AlF from either the side of F or Al), the MRCI energy (C2v symmetry is assumed) significantly increases (5-8 cm^-1) which makes the potential energy surface discontinous. When i force a lower symmetry in this calculations(Cs), the result are continuous with the rest of them. What I dont understand is why is there a drastic change in the interaction energy when I change the implemented symmetry from Cs to C2v (for the same configuration) i.e are MRCI basis set not invariant under symmetry change and why? I have also attached a graph that shows the difference.&lt;a href=&quot;https://i.stack.imgur.com/KPc7d.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KPc7d.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4279" LastEditorUserId="5" LastEditDate="2021-09-14T15:29:53.950" LastActivityDate="2021-09-14T15:29:53.950" Title="Implementing symmetry in MRCI calculation" Tags="|quantum-chemistry|" AnswerCount="0" CommentCount="2" ClosedDate="2021-11-19T01:34:34.237" ContentLicense="CC BY-SA 4.0" />
  <row Id="6751" PostTypeId="2" ParentId="6718" CreationDate="2021-09-14T17:02:05.557" Score="8" Body="&lt;p&gt;I don't think you can build a nanoparticle using Avogadro, I personally use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/cluster/cluster.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; which is a python package that can output a lot of different formats (&lt;code&gt;xyz&lt;/code&gt;, &lt;code&gt;cif&lt;/code&gt;, &lt;code&gt;vasp&lt;/code&gt;, ...)&lt;/p&gt;&#xA;&lt;p&gt;You can directly output LAMMPS format using ASE or you can use &lt;a href=&quot;https://atomsk.univ-lille.fr&quot; rel=&quot;noreferrer&quot;&gt;Atomsk&lt;/a&gt; to convert whatever format to LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;By doing that you will obtain a &amp;quot;lammps-data&amp;quot; file, which needs to be read by a LAMMPS input using the &lt;a href=&quot;https://docs.lammps.org/read_data.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;read_data&lt;/code&gt; command&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to use LAMMPS for your project, it is a really powerful program but there is no way around it: you need to read the documentation.&lt;/p&gt;&#xA;&lt;p&gt;If you are a new computational chemist I would advise you to use ASE, it is not only useful for nanoparticles, I'm using it nearly every day.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2021-09-14T18:14:23.903" LastActivityDate="2021-09-14T18:14:23.903" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6752" PostTypeId="2" ParentId="6714" CreationDate="2021-09-14T22:56:27.860" Score="11" Body="&lt;p&gt;Electrostaic embedding is usually on the QM-side as simple point charges which add to the total hamiltonian of the nuceli+electrons. It should be just a simple coulumb interaction.&lt;/p&gt;&#xA;&lt;p&gt;Any modern electronic structure calculation software should support aleast electrostatic embedding. Openmolcas, Orca, Dalton/LSDalton, Bagel  all support electrostatic embedding, with some of them also supporting advanced embedding like polarizable density embedding.&lt;/p&gt;&#xA;&lt;p&gt;Regarding an example implementation, &lt;a href=&quot;https://gitlab.com/cobrammgroup/cobramm&quot; rel=&quot;noreferrer&quot;&gt;COBRAMM&lt;/a&gt; developed at the University of Bologna in the group of Dr. Marco Garavelli allows one to conduct quite sophisticated QMMM computations like optimizations, reaction paths and non-adiabatic dynamics in comdensed phase or protein environment. The program allows a great freedom to use any QM program (Openmolcas for wavefucntion based CASSCF/CASPT2 or Gaussian or DFT/TD-DFT) and uses Amber package for the MM part.&lt;/p&gt;&#xA;" OwnerUserId="4281" LastActivityDate="2021-09-14T22:56:27.860" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6755" PostTypeId="1" AcceptedAnswerId="6758" CreationDate="2021-09-16T06:26:37.060" Score="6" ViewCount="1184" Body="&lt;p&gt;I am really confused about why whenever I add one molecule into vesta, around 6 show up randomly not at that position? What's the correct procedure for working unit cells?&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mup5D.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mup5D.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4287" LastActivityDate="2021-11-08T02:45:47.343" Title="How to work with unit cells in Vesta" Tags="|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6756" PostTypeId="1" AcceptedAnswerId="6757" CreationDate="2021-09-16T21:42:22.247" Score="8" ViewCount="738" Body="&lt;p&gt;In &lt;a href=&quot;https://en.wikipedia.org/wiki/H%C3%BCckel_method&quot; rel=&quot;noreferrer&quot;&gt;Huckel Method&lt;/a&gt;, by numbering the sp2 carbons in a molecule with conjugated double bonds, we can assemble its secular determinant in a form similar to the adjacency matrix of a graph. Taking &lt;a href=&quot;https://en.wikipedia.org/wiki/(E)-Stilbene&quot; rel=&quot;noreferrer&quot;&gt;trans-stilbene&lt;/a&gt; as a example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/POO6e.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/POO6e.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Its secular determinant takes this simplified form:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[x,1,0,0,0,1,0,0,0,0,0,0,0,0],&#xA; [1,x,1,0,0,0,0,0,0,0,0,0,0,0],&#xA; [0,1,x,1,0,0,0,0,0,0,0,0,0,0],&#xA; [0,0,1,x,1,0,0,0,0,0,0,0,0,0],&#xA; [0,0,0,1,x,1,0,0,0,0,0,0,0,0],&#xA; [1,0,0,0,1,x,1,0,0,0,0,0,0,0],&#xA; [0,0,0,0,0,1,x,1,0,0,0,0,0,0],&#xA; [0,0,0,0,0,0,1,x,1,0,0,0,0,0],&#xA; [0,0,0,0,0,0,0,1,x,1,0,0,0,1],&#xA; [0,0,0,0,0,0,0,0,1,x,1,0,0,0],&#xA; [0,0,0,0,0,0,0,0,0,1,x,1,0,0],&#xA; [0,0,0,0,0,0,0,0,0,0,1,x,1,0],&#xA; [0,0,0,0,0,0,0,0,0,0,0,1,x,1],&#xA; [0,0,0,0,0,0,0,0,1,0,0,0,1,x]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To convert it to a adjacency matrix, it's necessary just to replace the x variables in the main diagonal with zeroes.&lt;/p&gt;&#xA;&lt;p&gt;Now the problem is: if we start with the adjacency matrix, not knowing the structure beforehand, one needs to grab pen and paper and do a bit of scribbling to see the shape it represents, as that information is not apparent just by glancing at the matrix. This procedure is a bit slow and error-prone when the molecule is large.&lt;/p&gt;&#xA;&lt;p&gt;I noticed WolframAlpha allows us to get a graph representation from the adjacency matrix, as shown &lt;a href=&quot;https://www.wolframalpha.com/input/?i=AdjacencyGraph%5B%7B%7B0%2C1%2C0%2C0%2C0%2C1%7D%2C+%7B1%2C0%2C1%2C0%2C0%2C0%7D%2C+%7B0%2C1%2C0%2C1%2C0%2C0%7D%2C+%7B0%2C0%2C1%2C0%2C1%2C0%7D%2C+%7B0%2C0%2C0%2C1%2C0%2C1%7D%2C+%7B1%2C0%2C0%2C0%2C1%2C0%7D%7D%5D&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for Benzene, but as the site uses proprietary software, we soon run into artificial limitations. My stilbene matrix exceeds maximum character limit, for example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RJRc7.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RJRc7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And it also can't be automated for larger number of structures.&lt;/p&gt;&#xA;&lt;p&gt;So I'd like to ask some recommendations on how to do the same, but using Free / Open Source Software. Python libraries would be great, to ease automation.&lt;/p&gt;&#xA;" OwnerUserId="243" LastEditorUserId="243" LastEditDate="2021-09-16T21:52:07.263" LastActivityDate="2021-09-17T02:28:54.343" Title="Given the adjacency matrix of a molecule, how can I get a graphical representation using only open source software?" Tags="|molecular-modeling|software-recommendations|mathematical-modeling|open-source|cheminformatics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6757" PostTypeId="2" ParentId="6756" CreationDate="2021-09-17T02:18:38.757" Score="9" Body="&lt;h2&gt;&lt;a href=&quot;https://networkx.org/&quot; rel=&quot;noreferrer&quot;&gt;NetworkX&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;This is a widely-used Python library for graph theory stuff. Open source (&lt;a href=&quot;https://github.com/networkx/networkx&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/networkx/networkx&lt;/a&gt;) under a 3-clause BSD license.&lt;/p&gt;&#xA;&lt;p&gt;Caveat: since this is a tool that knows nothing about chemistry, the &amp;quot;chemical&amp;quot; nature of the structure might get lost in the projection of the network (e.g., some bond lengths might not look reasonable). However, OP's question suggested an interest in a rough structure. For sufficiently complicated things, especially with significant 3D structure, this will probably run into trouble. It does an okay job on trans-stilbene, though. Play with different &lt;a href=&quot;https://networkx.org/documentation/stable/reference/drawing.html#module-networkx.drawing.layout&quot; rel=&quot;noreferrer&quot;&gt;layouts&lt;/a&gt; to see which are perform best with your molecules.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import networkx as nx&#xA;import numpy as np&#xA;&#xA;x = 0  # so this is a proper adjacency matrix&#xA;&#xA;adj = [[x,1,0,0,0,1,0,0,0,0,0,0,0,0],&#xA; [1,x,1,0,0,0,0,0,0,0,0,0,0,0],&#xA; [0,1,x,1,0,0,0,0,0,0,0,0,0,0],&#xA; [0,0,1,x,1,0,0,0,0,0,0,0,0,0],&#xA; [0,0,0,1,x,1,0,0,0,0,0,0,0,0],&#xA; [1,0,0,0,1,x,1,0,0,0,0,0,0,0],&#xA; [0,0,0,0,0,1,x,1,0,0,0,0,0,0],&#xA; [0,0,0,0,0,0,1,x,1,0,0,0,0,0],&#xA; [0,0,0,0,0,0,0,1,x,1,0,0,0,1],&#xA; [0,0,0,0,0,0,0,0,1,x,1,0,0,0],&#xA; [0,0,0,0,0,0,0,0,0,1,x,1,0,0],&#xA; [0,0,0,0,0,0,0,0,0,0,1,x,1,0],&#xA; [0,0,0,0,0,0,0,0,0,0,0,1,x,1],&#xA; [0,0,0,0,0,0,0,0,1,0,0,0,1,x]]&#xA;&#xA;# note that NetworkX requires that you wrap in a numpy array&#xA;graph = nx.Graph(np.array(adj))&#xA;&#xA;nx.draw(graph)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OqqxH.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OqqxH.png&quot; alt=&quot;network visualization of bondgraph&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've used this approach to debug problems with structures before (IIRC, I used &lt;a href=&quot;https://www.mdtraj.org/1.9.5/index.html&quot; rel=&quot;noreferrer&quot;&gt;MDTraj&lt;/a&gt;'s &lt;code&gt;Topology.to_bondgraph&lt;/code&gt; method, which produces an NetworkX graph, in my case). You can easily label nodes with atom names -- see &lt;a href=&quot;https://networkx.org/documentation/stable/tutorial.html&quot; rel=&quot;noreferrer&quot;&gt;NetworkX tutorial&lt;/a&gt; for more.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-09-17T02:28:54.343" LastActivityDate="2021-09-17T02:28:54.343" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6758" PostTypeId="2" ParentId="6755" CreationDate="2021-09-17T03:05:50.580" Score="4" Body="&lt;p&gt;Nevermind, it turned out I was using a CIF file, transforming and then using structural parameters to add atoms, converting to .vasp fixed all the issues!&lt;/p&gt;&#xA;&lt;p&gt;More detailed answer, I was using a CIF unit cell file, which is fairly normal, and then transformed it to a supercell, and was trying to add molecules using &amp;quot;Edit Data &amp;gt; Structural Parameters&amp;quot;, however the issue with this was that by editing a CIF file, there was some issue, so exporting the supercell into .vasp, and then re-opening it and using edit data, it worked much better.&lt;/p&gt;&#xA;" OwnerUserId="4287" LastEditorUserId="4287" LastEditDate="2021-11-08T02:45:47.343" LastActivityDate="2021-11-08T02:45:47.343" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6759" PostTypeId="1" CreationDate="2021-09-17T08:32:10.010" Score="16" ViewCount="177" Body="&lt;p&gt;I was wondering if anybody can recommend an easy-to-use library/program to solve the 3D Poisson equation &lt;span class=&quot;math-container&quot;&gt;$\nabla^2 V(r,\theta,\phi) = \rho(r,\theta,\phi)$&lt;/span&gt; with vanishing solutions at infinity:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V(r,\theta,\phi) = \int d^3\mathbf{r}'\frac{\rho(\mathbf{r}')}{|\mathbf{r}-\mathbf{r}'|},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r} \rightarrow (r,\theta,\phi)$&lt;/span&gt;. Here &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is a discrete + continuous charge density. The intended application is to calculate the electrostatic potential of a model polyatomic molecule composed of static, point-like nuclear charges and an arbitrary continuous electron density.&lt;/p&gt;&#xA;&lt;p&gt;This question is a follow up to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1366/3d-poisson-equation-solver-for-arbitrary-charge-distribution&quot;&gt;3D Poisson equation solver for arbitrary charge distribution?&lt;/a&gt; ,&#xA;which remains unanswered.&lt;/p&gt;&#xA;&lt;p&gt;I am looking for a library, which is straightforward to use and which does not invoke the multipole expansion. There are plenty of solvers available on the market. I am familiar with three:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://fenicsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Fenics project&lt;/a&gt; (finite element methods)&lt;/li&gt;&#xA;&lt;li&gt;The '&lt;a href=&quot;https://github.com/maroba/multipoles&quot; rel=&quot;nofollow noreferrer&quot;&gt;multipoles&lt;/a&gt;' python library (solutions in the form of the multipole expansion)&lt;/li&gt;&#xA;&lt;li&gt;COMSOL Multiphysics (not a freeware, finite elements),&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;but if anybody has a good experience with some other library (ideally in python or Fortran), sharing this experience here would be appreciated. The widely used &lt;a href=&quot;https://people.sc.fsu.edu/%7Ejburkardt&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Burkardt's libraries &lt;/a&gt; do not seem to contain such a solver routine.&lt;/p&gt;&#xA;&lt;p&gt;Ideally, I wish to define the charge distribution &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; (on a grid or analytically) and receive the value of the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; at any point &lt;span class=&quot;math-container&quot;&gt;$(r,\theta,\phi)$&lt;/span&gt;, without too much hustle.&lt;/p&gt;&#xA;" OwnerUserId="99" LastEditorUserId="181" LastEditDate="2022-02-07T11:20:37.270" LastActivityDate="2022-02-07T11:20:37.270" Title="Calculating the electrostatic potential of a molecule: what is a good 3D Poisson equation solver?" Tags="|charge-density|electrostatic|electron-density|finite-element-analysis|partial-differential-equations|" AnswerCount="0" CommentCount="5" ClosedDate="2022-02-24T14:27:39.387" ContentLicense="CC BY-SA 4.0" />
  <row Id="6760" PostTypeId="2" ParentId="6724" CreationDate="2021-09-17T10:28:35.833" Score="6" Body="&lt;p&gt;Learning Latex to create documents is like becoming a mechanic to learn how to drive a car. &lt;a href=&quot;https://www.lyx.org&quot; rel=&quot;noreferrer&quot;&gt;Lyx&lt;/a&gt; is based on the Latex typesetting system, but provides a content-focused &amp;quot;live preview&amp;quot; editor that doesn't expose the inner workings to the user. Advanced formatting is still possible, with lots of it made accessible to the user through meaningful GUI interaction.&lt;/p&gt;&#xA;&lt;p&gt;If you've ever had to write complicated equations (or, god forbid, tables!) in pure Tex, you'll very quickly understand why this program is so useful.&lt;/p&gt;&#xA;" OwnerUserId="1440" LastActivityDate="2021-09-17T10:28:35.833" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6761" PostTypeId="1" AcceptedAnswerId="6785" CreationDate="2021-09-18T05:13:11.750" Score="8" ViewCount="248" Body="&lt;p&gt;Crossposted from &lt;a href=&quot;https://physics.stackexchange.com/questions/666674/functional-derivatives-in-density-functional-theory&quot;&gt;Physics SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am studying density functional theory and I am currently dealing with manipulating the intrinsic free energy, &lt;span class=&quot;math-container&quot;&gt;$\mathcal{F}$&lt;/span&gt;, which is defined as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{F} = F - \int  dr \rho ^{(1)}(r)\phi (r) $$&lt;/span&gt;&#xA;which can be expressed in it's differential form as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\delta \mathcal{F} = -S\delta T+ \int dr \delta \rho ^{(1)}(r) \psi (r)$$&lt;/span&gt;&#xA;In the above equations, &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is the Helmholtz free energy, &lt;span class=&quot;math-container&quot;&gt;$\phi (r)$&lt;/span&gt; is some external field, &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; is the intrinsic chemical potential defined as &lt;span class=&quot;math-container&quot;&gt;$\psi (r) = \mu - \phi (r)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the chemical potential, and &lt;span class=&quot;math-container&quot;&gt;$\rho ^{(1)}$&lt;/span&gt; is the single-particle density given in terms of the local activity as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\rho ^{(1)} (r_1)=\Xi ^{-1} \sum _{N=1}^{\infty} \frac{1}{(N-1)!} \int dr^{(N-1)} \exp [-\beta U(r^N)] \prod _{i=1}^N \left\{ z^{*}(r_i) \right\}$$&lt;/span&gt;&#xA;which can be generalized to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\rho ^{(n)} (r_1)=\Xi ^{-1} \sum _{N=n}^{\infty} \frac{1}{(N-n)!} \int dr^{(N-n)} \exp [-\beta U(r^N)] \prod _{i=1}^N \left\{ z^{*}(r_i) \right\} $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$z^{*}(r) = z\exp [-\beta \phi (r)]$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; is the fugacity.&lt;/p&gt;&#xA;&lt;p&gt;Defining the grand potential &lt;span class=&quot;math-container&quot;&gt;$$\Omega = \mathcal{F} - N\mu + \int dr \rho ^{(1)}(r) \phi (r)$$&lt;/span&gt;&#xA;we obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\delta \Omega = -S\delta T - \int dr \rho ^{(1)}(r) \delta \psi (r)$$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is all fine so far.&#xA;Now, in the notes I have been provided, they calculate the second derivative of &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt;, we take the &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; derivative of &lt;span class=&quot;math-container&quot;&gt;$\rho ^{(1)}$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta ^2 \Omega}{\delta \psi (r_1) \delta \psi (r_2)} = -\frac{\delta \rho ^{(1)}(r_1)}{\delta \psi (r_2)}$$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The first derivative makes sense, but now, they claim that&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align*}&#xA;-\frac{\delta \rho ^{(1)}(r_1)}{\delta \psi (r_2)} &amp;amp;= \beta [\rho^{(1)}(r_1)\rho ^{(1)}(r_2) - \rho ^{(1)}(r_1) \delta (r_1-r_2) -\rho ^{(2)}(r_1,r_2)] \\&#xA;&amp;amp;= -\beta[\rho ^{(1)}(r_1) \rho ^{(1)}(r_2) h^{(2)}(r_1,r_2)+\rho ^{(1)}(r_1) \delta (r_1-r_2)]&#xA;\end{align*}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$h(r_1,r_2)$&lt;/span&gt; is the total correlation function.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I have no idea how they performed these derivatives and used the correlations. How did they simplify &lt;span class=&quot;math-container&quot;&gt;$d\rho ^{(1)}(r_1)/d\psi (r_2)$&lt;/span&gt;? I do not understand how the chain rule leads to the terms on the RHS. Nor how they managed to get &lt;span class=&quot;math-container&quot;&gt;$\rho ^{(2)}$&lt;/span&gt; in the mix.&#xA;Any help with these functional derivatives would be appreciated!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-09-23T14:14:51.983" Title="Functional derivatives in DFT" Tags="|density-functional-theory|statistical-thermodynamics|thermodynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6762" PostTypeId="1" AcceptedAnswerId="6972" CreationDate="2021-09-19T04:50:35.950" Score="8" ViewCount="156" Body="&lt;p&gt;I am running a methanol simulation with a topology I obtained from Tinker for OPLS-AA, at 298 K and 1 bar. This is my .itp file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ atomtypes ]&#xA;; atm_kind   symbol      mass    charge      ptype   sigma   epsilon &#xA;         MTH0      C01    12.0110     0.000       A   0.35000   0.27614&#xA;         MTH1      O02    15.9990     0.000       A   0.31200   0.71128&#xA;         MTH2      H03     1.0080     0.000       A   0.25000   0.12552&#xA;         MTH3      H04     1.0080     0.000       A   0.25000   0.12552&#xA;         MTH4      H05     1.0080     0.000       A   0.25000   0.12552&#xA;         MTH5      H06     1.0080     0.000       A   0.00000   0.00000&#xA;&#xA;[ moleculetype ]&#xA;; residue    nrexcl&#xA;MTH      3   &#xA;&#xA;[ atoms ]&#xA;; srno   atm_kind    resnr   res     sym     cgnr    charge      mass &#xA;     1         MTH0      1    MTH      C01      1     0.145    12.0110&#xA;     2         MTH1      1    MTH      O02      1    -0.683    15.9990&#xA;     3         MTH2      1    MTH      H03      1     0.040     1.0080&#xA;     4         MTH3      1    MTH      H04      1     0.040     1.0080&#xA;     5         MTH4      1    MTH      H05      1     0.040     1.0080&#xA;     6         MTH5      1    MTH      H06      1     0.418     1.0080&#xA;&#xA;[ bonds ]&#xA;; p1     p2      funct   r0      ks  &#xA;    1     2     1      0.1410 267776.000&#xA;    1     3     1      0.1090 284512.000&#xA;    1     4     1      0.1090 284512.000&#xA;    1     5     1      0.1090 284512.000&#xA;    2     6     1      0.0945 462750.400&#xA;&#xA;[ angles ]&#xA;; p1     p2      p3      funct   theta0      kb  &#xA;    2     1     3     1    109.500    292.880&#xA;    2     1     4     1    109.500    292.880&#xA;    2     1     5     1    109.500    292.880&#xA;    3     1     4     1    107.800    276.144&#xA;    3     1     5     1    107.800    276.144&#xA;    4     1     5     1    107.800    276.144&#xA;    1     2     6     1    108.500    460.240&#xA;&#xA;[ dihedrals ]&#xA;; PROPER DIHEDRAL ANGLES&#xA;; p1     p2      p3      p4      funct   c0      c1      c2      c3      c4      c5  &#xA;    3    1    2    6      3       0.736    2.209    0.000   -2.946    0.000    0.000&#xA;    4    1    2    6      3       0.736    2.209    0.000   -2.946    0.000    0.000&#xA;    5    1    2    6      3       0.736    2.209    0.000   -2.946    0.000    0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I run the npt equilibration step before my production run, I get the following note:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NOTE 1 [file unknown]:&#xA;  You are using constraints on all bonds, whereas the forcefield has been&#xA;  parametrized only with constraints involving hydrogen atoms. We suggest&#xA;  using constraints = h-bonds instead, this will also improve performance.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These are my constraints in my .mdp file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;continuation            = yes       ; Restarting after NPT &#xA;constraint_algorithm    = lincs     ; holonomic constraints &#xA;constraints             = all-bonds   ; bonds involving H are constrained&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Furthermore, my performance is pretty slow. I have 3000 methanol molecules, so 18000 atoms, and I am taking upwards of 24 hours to get 50 ns. What could be the cause of such a slow down? Methanol is a small, well-studied molecule and I want to benchmark TINKER before I move forward.&lt;/p&gt;&#xA;&lt;p&gt;Any advice you have would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-10-29T19:13:35.287" Title="Very slow performance for an OPLS-AA methanol simulation" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6763" PostTypeId="2" ParentId="6714" CreationDate="2021-09-19T18:51:36.913" Score="8" Body="&lt;p&gt;vkj's answer addressed the third part of the question. I'll answer the first part.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Which quantum chemistry methods can be used in an external electrostatic field? Also which software supports that? I'm interested in anything from semiempirical (eg XTB) to DFT (eg ωB97, B3LYP-D3) to coupled cluster (eg DLPNO-CCSD(T)). The only starting point I have is a few mentions of Field= keyword in Gaussian and a mention of an undocumented efield keyword in the ORCA forums.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;An external electrostatic field can be implemented in &lt;strong&gt;any method&lt;/strong&gt;, since it's just a trivial modification of the one-electron Hamiltonian as &lt;span class=&quot;math-container&quot;&gt;$\hat{H} \to \hat{H} - e\phi({\bf r})$&lt;/span&gt;. Most programs, such as GAUSSIAN and ORCA that were already mentioned as well as others like Psi4, only implement static fields, &lt;span class=&quot;math-container&quot;&gt;${\bf E}={\bf E}_0$&lt;/span&gt;; you give the cartesian components with the necessary keyword. The electric field is the negative gradient of the potential, &lt;span class=&quot;math-container&quot;&gt;${\bf E} = -\nabla \phi$&lt;/span&gt;, so for a static field &lt;span class=&quot;math-container&quot;&gt;$\phi({\bf r}) = \phi_0 -{\bf E}_0 \cdot {\bf r} $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now, the big conceptual problem arises: the potential diverges to &lt;span class=&quot;math-container&quot;&gt;$-\infty$&lt;/span&gt;, meaning that no state can be really bound in such a potential. If your basis set is extended enough, there will always be artificial states far away from the system because of the divergent potential. Often, this is not a problem in practice, if the basis set does not reach far enough. Another route is given by perturbation theory, that is, you can build a Taylor series at zero field: &lt;span class=&quot;math-container&quot;&gt;$E({\bf E}) = E_0 + \nabla_{\bf E} E \cdot {\bf E} + \frac 1 2 {\bf E} \cdot \nabla_{\bf E} \nabla_{\bf E} E \cdot {\bf E} + \dots $&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\nabla_{\bf E}$&lt;/span&gt; is just the dipole moment, &lt;span class=&quot;math-container&quot;&gt;$\nabla_{\bf E} \nabla_{\bf E} E$&lt;/span&gt; is the polarizability tensor, then you have the first hyperpolarizability (rank-3 tensor), and so on.&lt;/p&gt;&#xA;&lt;p&gt;The most important thing to note, however, is that in order to correctly describe behavior in an external field, you need to have a flexible basis set. Already reproducing the dipole moment correctly requires diffuse functions; it is a textbook example for their necessity. For instance, if I remember correctly, an augmented double-zeta basis set gives you the dipole moment of the water molecule as accurately as a non-augmented quadruple-zeta basis set, at the Hartree-Fock level. I think polarizabilities may be even more demanding to get accurately.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-09-19T18:51:36.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6764" PostTypeId="1" AcceptedAnswerId="6766" CreationDate="2021-09-20T02:30:31.077" Score="8" ViewCount="366" Body="&lt;p&gt;I am now reading the paper (or review for beginners), &lt;a href=&quot;https://arxiv.org/pdf/cond-mat/0211443.pdf&quot; rel=&quot;noreferrer&quot;&gt;A bird's-eye view of density-functional theory&lt;/a&gt;, but I could not understand that the energy minimization problem, in which the derivative of the kinetic energy functional can not be written, can be replaced by solving the Kohn-Sham equation (page 33).&lt;/p&gt;&#xA;&lt;p&gt;First, the energy minimization problem is written as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;0 = \frac{\delta E}{\delta \rho(\mathbf r)} =&#xA;v_\text{ext}(\mathbf r) +&#xA;v_\text{H}(\mathbf r) +&#xA;\frac{\delta T_\text{s}[\{\psi_n\}]}{\delta \rho(\mathbf r)} +&#xA;v_\text{xc}(\mathbf r),&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the external and Hartree terms, &lt;span class=&quot;math-container&quot;&gt;$v_\text{ext}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$v_\text{H}(\mathbf r)$&lt;/span&gt; are written exactly, and &lt;span class=&quot;math-container&quot;&gt;$v_\text{xc}$&lt;/span&gt; can be calculated explicitly once an approximation, such as the local density approximation (LDA) and generalized gradient approximation (GGA), is determined.&lt;/p&gt;&#xA;&lt;p&gt;Here, because the single-particle exact kinetic energy, &lt;span class=&quot;math-container&quot;&gt;$T_\text{s}[\{\psi_n\}]$&lt;/span&gt;, is written as an orbital functional (not a density functional &lt;span class=&quot;math-container&quot;&gt;$T_\text{s}[\rho]$&lt;/span&gt;), we can not write the derivative form.&lt;/p&gt;&#xA;&lt;p&gt;Subsequently, the paper describes that Kohn and Sham replace this problem by solving an equation (of course, this is the Kohn-Sham equation).&lt;/p&gt;&#xA;&lt;p&gt;However, there is a gap in my understanding here. I understand the form of the energy minimization problem, and I also understand that the functional derivative of &lt;span class=&quot;math-container&quot;&gt;$T_\text{s}[\{\psi_n\}]$&lt;/span&gt; with respect to &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; cannot be written exactly. However, why are these two problems equivalent to solving the KS equation, that is, the eigenvalue problem?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-09-20T03:19:34.303" LastActivityDate="2021-09-20T07:39:06.947" Title="Replacement from minimizing the energy to solving the KS equation (or eigenvalue problem)" Tags="|density-functional-theory|kohn-sham|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6765" PostTypeId="2" ParentId="6718" CreationDate="2021-09-20T05:29:32.520" Score="8" Body="&lt;p&gt;You can either use python or MATLAB to generate the coordinates, or even use the built in tools in LAMMPS. To do this in LAMMPS, you only need to follow three steps.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the lattice command to define the &lt;a href=&quot;https://docs.lammps.org/lattice.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;lattice&lt;/a&gt; type (diamond for Silicon).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the region command to &lt;a href=&quot;https://docs.lammps.org/region.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;define a region&lt;/a&gt; with the desired dimensions. (Note that you may use boolean operations to obtain the exact shape).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Populate that region using atoms which can be achieved using the &lt;a href=&quot;https://docs.lammps.org/create_atoms.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Create_atoms command&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;However, an &lt;a href=&quot;https://docs.lammps.org/minimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;energy minimization&lt;/a&gt; step followed by relaxation in the NPT and/or NVE ensembles should be recommended to ensure that the structure is stable at the particular conditions.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="4232" LastEditDate="2021-11-19T10:40:36.477" LastActivityDate="2021-11-19T10:40:36.477" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6766" PostTypeId="2" ParentId="6764" CreationDate="2021-09-20T07:39:06.947" Score="9" Body="&lt;p&gt;The trick is that, instead of solving &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta E}{\delta \rho}=0$&lt;/span&gt;, we solve the equivalent set of equations &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta E}{\delta \psi^*_n}=0, \forall n$&lt;/span&gt; (plus the Lagrange multipliers required to enforce the orthonormalization constraints of the molecular orbitals).&lt;/p&gt;&#xA;&lt;p&gt;Any energy term &lt;span class=&quot;math-container&quot;&gt;$\tilde{E}$&lt;/span&gt; whose functional derivative w.r.t. the density is known explicitly as &lt;span class=&quot;math-container&quot;&gt;$\tilde{v}(\mathbf{r})$&lt;/span&gt;, gives a contribution of &lt;span class=&quot;math-container&quot;&gt;$\tilde{v}(\mathbf{r})\psi_n(\mathbf{r})$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\frac{\delta E}{\delta \psi^*_n}$&lt;/span&gt;, owing to the chain rule. &lt;span class=&quot;math-container&quot;&gt;$T_s = \sum_n\langle \psi_n|-\frac{1}{2}\nabla^2|\psi_n\rangle$&lt;/span&gt; gives a contribution of &lt;span class=&quot;math-container&quot;&gt;$-\frac{1}{2}\nabla^2\psi_n(\mathbf{r})$&lt;/span&gt;. These explain the LHS of the Kohn-Sham equation, &lt;span class=&quot;math-container&quot;&gt;$(-\frac{1}{2}\nabla^2 + v_{\mathrm{ext}}(\mathbf{r}) + v_{\mathrm{H}}(\mathbf{r}) + v_{\mathrm{xc}}(\mathbf{r}))\psi_n(\mathbf{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The RHS, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_n\psi_n(\mathbf{r})$&lt;/span&gt;, is due to the Lagrange multipliers which result from the orthonormality of the orbitals. I'll omit the details here because this part of the derivation is exactly the same as the derivation of the Hartree-Fock equation.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-20T07:39:06.947" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6767" PostTypeId="1" AcceptedAnswerId="6770" CreationDate="2021-09-20T08:28:30.870" Score="6" ViewCount="215" Body="&lt;p&gt;I'm trying to perform NBO calculations on a bimetallic complex to evaluate bond orders. However, while I've previously done NBO calculations to obtain partial charges which worked without problems, the NBO calculations for this complex just outright fail.&lt;/p&gt;&#xA;&lt;p&gt;I get the error message on top of the NBO output claiming:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WORTH: ATDIAG and DISCRD failed to remove linear dependence in the PNAOs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Unfortunately, I can't find anything regarding those abbreviations in the official NBO manual or elsewhere online. Maybe someone of you has an idea how this problem could be solved.&lt;/p&gt;&#xA;&lt;p&gt;I am using NBO 7.0 for all my calculations, in case this changes anything.&lt;/p&gt;&#xA;" OwnerUserId="4303" OwnerDisplayName="O2_AC" LastActivityDate="2021-09-21T12:22:34.527" Title="NBO Calculation failing (ATDIAG DISCRD)" Tags="|computational-chemistry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6768" PostTypeId="1" CreationDate="2021-09-20T14:48:43.247" Score="12" ViewCount="221" Body="&lt;p&gt;I would like to calculate the following four quantities in a free electronic structure program:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{alignat}{2}\tag{1}&#xA;e_1&amp;amp;=\langle\phi_1|H^{KS}|\phi_1\rangle,\\&#xA;e_2&amp;amp;=\langle\phi_2|H^{KS}|\phi_2\rangle,\tag{2}\\&#xA;J&amp;amp;=\langle\phi_1|H^{KS}|\phi_2\rangle ~~~~~~~&amp;amp;\textrm{(charge transfer integral),}\tag{3}\\&#xA;S&amp;amp;=\langle\phi_1|\phi_2\rangle &amp;amp;\textrm{(overlap integral),}\tag{4}&#xA;\end{alignat}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, if thee's a program that can &lt;em&gt;directly&lt;/em&gt; calculate the effective transfer integrals &lt;span class=&quot;math-container&quot;&gt;$J_{\text{eff}}$&lt;/span&gt; from monomer &lt;strong&gt;A&lt;/strong&gt; to monomer &lt;strong&gt;B&lt;/strong&gt; within dimer &lt;strong&gt;AB&lt;/strong&gt; by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$J_{\text{eff}}=\frac{J-S\cdot (e_1+e_2)/2}{1-S^2},\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;then that would be even better!&lt;/p&gt;&#xA;&lt;p&gt;In the above equations, &lt;span class=&quot;math-container&quot;&gt;$\phi_1$&lt;/span&gt; is the LUMO or HOMO of monomer &lt;strong&gt;A&lt;/strong&gt;, &lt;span class=&quot;math-container&quot;&gt;$\phi_2$&lt;/span&gt; is the LUMO or HOMO of monomer &lt;strong&gt;B&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Can someone give me a step-by-step tutorial to obtain the quantity &lt;span class=&quot;math-container&quot;&gt;$J_{\textrm{eff}}$&lt;/span&gt; or the four quantities needed in order to calculate it manually? I would like to do this in free software, preferably GAMMES(US), but being able to do it in any free software would be helpful.&lt;/p&gt;&#xA;" OwnerUserId="4307" OwnerDisplayName="Alexey" LastEditorUserId="5" LastEditDate="2021-12-28T22:50:58.777" LastActivityDate="2021-12-28T22:50:58.777" Title="How may I calculate the &quot;effective transfer integral&quot; in free electronic-structure software?" Tags="|quantum-chemistry|computational-chemistry|ab-initio-calculations|electronic-structure|gamess|" AnswerCount="0" CommentCount="9" ClosedDate="2023-02-07T04:12:49.683" ContentLicense="CC BY-SA 4.0" />
  <row Id="6769" PostTypeId="2" ParentId="6746" CreationDate="2021-09-21T03:20:20.443" Score="2" Body="&lt;p&gt;Firstly due to the bandgap problem in density functional theory, the bandgap is underestimated (difference between valence band maximum and conduction band minimum). However, for semi-conductors, hybrid functionals such as HSE06 do a good job of predicting the bandgap. However, such calculations would be computationally expensive. To find the conduction band minimum you can run an HSE06 calculation with reasonable Brillion zone sampling. You have to run some convergence tests to determine the sampling since it is the system and supercell size-dependent. Once you run the calculation you can find the density of states (DOSCAR in case you are using VASP). From here you can plot the density of states and find both the valence band maxima and conduction band minima.&lt;/p&gt;&#xA;&lt;p&gt;Bonus tip: If you are using VASP. You can use python toolkits like Pymatgen to help you with a lot of analysis techniques.&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2021-09-21T03:20:20.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6770" PostTypeId="2" ParentId="6767" CreationDate="2021-09-21T12:22:34.527" Score="5" Body="&lt;p&gt;The &lt;a href=&quot;http://nboinc.chem.wisc.edu/phpBB3/viewtopic.php?f=3&amp;amp;t=213&quot; rel=&quot;noreferrer&quot;&gt;only thread&lt;/a&gt; I could find that had some discussion of this on the NBO forum was related to using the NBO interface in Gaussian and was likely about an earlier version of NBO based on the discussion being from 2016.&lt;/p&gt;&#xA;&lt;p&gt;However, the answerer there seems to be an NBO developer and he mentions that these linear dependency failures can often be resolved by shrinking the basis. Hopefully this should not affect the overall results much, as they suggest that NBO properties converge very quickly with basis set size:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NBO descriptors converge nicely as the basis set is extended. Double-zeta is usually really good, triple-zeta is better, and you'll likely not learn much more by going to quadruple-zeta or beyond.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-09-21T12:22:34.527" CommentCount="0" CommunityOwnedDate="2021-09-21T12:22:34.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="6771" PostTypeId="2" ParentId="6718" CreationDate="2021-09-21T13:03:44.593" Score="6" Body="&lt;h1&gt;Atomsk&lt;/h1&gt;&#xA;&lt;p&gt;You can use this software to play with the structure and then, generate de coordinate file for you program.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Atomsk is a free, Open Source command-line program dedicated to the&#xA;creation, manipulation, and conversion of data files for atomic-scale&#xA;simulations. It supports the file formats used by many programs,&#xA;including:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Visualization and analysis softwares: Atomeye, ddplot, OVITO, VESTA, XCrySDen;&lt;/li&gt;&#xA;&lt;li&gt;Ab initio calculation softwares: ABINIT, Quantum Espresso, VASP, SIESTA;&lt;/li&gt;&#xA;&lt;li&gt;Classical force-field simulation softwares: DL_POLY, GULP, IMD, LAMMPS, XMD;&lt;/li&gt;&#xA;&lt;li&gt;TEM image simulation softwares: Dr Probe, JEMS, QSTEM.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The reference paper is: Atomsk: A tool for manipulating and converting atomic data files&amp;quot; Pierre Hirel, Comput. Phys. Comm. 197 (2015) 212-219&#xA;doi:&lt;a href=&quot;https://dx.doi.org/10.1016/j.cpc.2015.07.012&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.cpc.2015.07.012&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The program documentation is &lt;a href=&quot;https://atomsk.univ-lille.fr/doc.php&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There are some tutorials than can help/guide you &lt;a href=&quot;https://atomsk.univ-lille.fr/tutorials.php&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-09-21T13:03:44.593" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6772" PostTypeId="1" CreationDate="2021-09-21T14:06:38.833" Score="7" ViewCount="302" Body="&lt;p&gt;How to calculate ionization energy for an alloy system (for eg. &lt;span class=&quot;math-container&quot;&gt;$\ce{Mg17Al12}$&lt;/span&gt;) using DFT?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-09-24T02:08:30.477" Title="Calculation of ionization energy for an alloy" Tags="|density-functional-theory|vasp|quantum-espresso|alloys|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6773" PostTypeId="1" CreationDate="2021-09-21T19:17:41.907" Score="5" ViewCount="85" Body="&lt;p&gt;When compiled with the HDF5 flag on, Quantum ESPRESSO (QE) saves wavefunctions in the .save folder. At each k-point, we have an &lt;span class=&quot;math-container&quot;&gt;$m\times n$&lt;/span&gt; matrix, where &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; are the complex number entries of eigenvectors in the plane wave basis, and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; are the bands.&lt;/p&gt;&#xA;&lt;p&gt;However, I now desire an &lt;span class=&quot;math-container&quot;&gt;$n\times n$&lt;/span&gt; matrix of eigenvectors in the energy eigenstate basis. Is there a way I can do this? I cannot think of ways to achieve this.&lt;/p&gt;&#xA;&lt;p&gt;I asked a similar question a while ago: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4266/how-to-understand-the-wavefunction-outputed-by-qe-with-hdf5-format&quot;&gt;How to understand the wavefunction outputed by QE with HDF5 format?&lt;/a&gt;, but I cannot seem to go further from there.&lt;/p&gt;&#xA;&lt;p&gt;What I naively tried: I summed each row of each column to get a complex number for each band, but this can at most give me probability amplitudes one way or another, to my understanding. Not eigenvectors.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-09-21T19:17:41.907" Title="How to get energy eigenstates using plane wave basis wavefunction .hdf5 output from Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|quantum-mechanics|basis-sets|wavefunctions|" AnswerCount="0" CommentCount="4" ClosedDate="2022-08-23T22:15:58.800" ContentLicense="CC BY-SA 4.0" />
  <row Id="6774" PostTypeId="5" CreationDate="2021-09-21T22:30:58.863" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Doping_(semiconductor)&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Doping_(semiconductor)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Dopant&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Dopant&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-21T22:30:58.863" LastActivityDate="2021-09-21T22:30:58.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6775" PostTypeId="4" CreationDate="2021-09-21T22:30:58.863" Score="0" Body="Questions related to calculations involving doping or dopants or materials with dopants in them. " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-21T22:30:58.863" LastActivityDate="2021-09-21T22:30:58.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6776" PostTypeId="5" CreationDate="2021-09-21T22:48:57.370" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/pyxem/diffsims&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/pyxem/diffsims&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-21T22:48:57.370" LastActivityDate="2021-09-21T22:48:57.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6777" PostTypeId="4" CreationDate="2021-09-21T22:48:57.370" Score="0" Body="Questions about or related to diffsims, the package for simulating diffraction." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-09-21T22:48:57.370" LastActivityDate="2021-09-21T22:48:57.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6778" PostTypeId="2" ParentId="6096" CreationDate="2021-09-21T23:33:58.037" Score="2" Body="&lt;p&gt;I tried to answer the question in the github issue  github.com/pyxem/diffsims/issues/176&lt;/p&gt;&#xA;&lt;p&gt;Answer:&lt;/p&gt;&#xA;&lt;p&gt;The reason it doesn't work is that the calibration parameter of the diffraction pattern is not set. A diffraction pattern in diffsims is represented by a list of &lt;code&gt;(x, y)&lt;/code&gt; coordinates in projected reciprocal space, and an associated intensities &lt;code&gt;I&lt;/code&gt;. Together they represent diffraction spots, and the main purpose of diffsims is to calculate &lt;code&gt;I&lt;/code&gt; in these patterns depending on the microscope conditions (like sample orientation, acceleration voltage, ...) and create libraries of these simulated patterns for template matching (comparing to experimental data). A diffraction pattern can exist &amp;quot;etherially&amp;quot; in reciprocal space coordinates, but to convert them to an image one needs to know the size of a pixel in reciprocal space units. By default, this value is 1 (see &lt;a href=&quot;https://github.com/pyxem/diffsims/blob/3c2540e520f7c8a6a60d24ec9b88844c4d2c8f83/diffsims/sims/diffraction_simulation.py#L50&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/pyxem/diffsims/blob/3c2540e520f7c8a6a60d24ec9b88844c4d2c8f83/diffsims/sims/diffraction_simulation.py#L50&lt;/a&gt;), meaning that 1 pixel will correspond to 1 angstrom^-1. You are thus creating a diffraction pattern image where all the diffraction spots are all blurred together in the center. In a sense, you just needs to &amp;quot;magnify&amp;quot; the diffraction pattern by setting a different calibration. Before the line&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dp= diffraction_pattern.get_diffraction_pattern(size=512, sigma=2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;you should add a line&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;diffraction_pattern.calibration = #some other value representing the number of angstrom^-1 / pixel&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope this helps.&lt;/p&gt;&#xA;&lt;p&gt;Also an important note: since diffraction patterns in diffsims are essentially a structured point cloud, an unprocessed pattern is basically a zero image with some bright pixels. When we collect real diffraction patterns in the microscope, spots have a finite size due to imperfect optics, thermal vibrations, finite sample and beam size, dynamic diffraction,... All these effects are not considered in diffsims, it only uses the kinematical approximation. To make the pattern appear more like experimental patterns, the bright pixels are simply blurred with a 2D gaussian. This is not representative of a physical process and just serves as a sanity check when judging the patterns.&lt;/p&gt;&#xA;" OwnerUserId="4312" LastEditorUserId="4312" LastEditDate="2021-09-22T07:54:14.460" LastActivityDate="2021-09-22T07:54:14.460" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6779" PostTypeId="1" CreationDate="2021-09-22T04:47:46.387" Score="11" ViewCount="600" Body="&lt;p&gt;If I'm interested in getting an answer that is minimally correct what is the minimum basis set level I should use? (i.e. anything less would be much less reliable)&lt;/p&gt;&#xA;&lt;p&gt;Obviously this depends on the methods, property of interest and opinion.&lt;/p&gt;&#xA;&lt;p&gt;Let's say I'm just interested in relative energies (but feel free to chime in with information about properties if you are inclined).  I am interested to hear how this depends on the different methods and the various arguments there are for &lt;em&gt;minimum&lt;/em&gt; basis sets one should use.&lt;/p&gt;&#xA;" OwnerUserId="52" LastActivityDate="2021-09-22T08:09:14.133" Title="What is the minimum basis set one should use?" Tags="|density-functional-theory|basis-sets|wavefunctions|soft-question|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6780" PostTypeId="1" AcceptedAnswerId="6783" CreationDate="2021-09-22T07:49:54.233" Score="4" ViewCount="247" Body="&lt;p&gt;am looking to draw wurtzite unit cell of ZnO, and i find two of them&#xA;&lt;a href=&quot;https://i.stack.imgur.com/qNz7U.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qNz7U.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the second one&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CzQK6.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CzQK6.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;how can I draw the first one in software like vesta?&lt;/p&gt;&#xA;" OwnerUserId="4317" LastEditorUserId="5" LastEditDate="2021-09-22T14:14:00.697" LastActivityDate="2021-09-23T05:48:54.780" Title="wurtzite unit cell of ZnO" Tags="|crystallography|vesta|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6781" PostTypeId="2" ParentId="6779" CreationDate="2021-09-22T08:09:14.133" Score="14" Body="&lt;p&gt;Different people will have slightly different opinions, so take my answer with a grain of salt. I'll try to give the &lt;em&gt;minimum publishable&lt;/em&gt; basis sets, i.e. if you use worse basis sets than these, you'll have a strong reason why you do so, written in the article, otherwise you'll probably face suspicion from the reviewers.&lt;/p&gt;&#xA;&lt;p&gt;DFT (excluding double hybrid) geometry optimizations: def2-SV(P) or 6-31G(d)&lt;/p&gt;&#xA;&lt;p&gt;DFT (excluding double hybrid) single point: 6-311G(d,p) (some may argue it's not large enough) or def2-TZVP&lt;/p&gt;&#xA;&lt;p&gt;Double hybrid functional: def2-TZVP (with geometry optimization one may get down to def2-TZVP(-f)? But definitely not down to double-zeta basis sets)&lt;/p&gt;&#xA;&lt;p&gt;CCSD(T): def2-TZVP or cc-pVTZ&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-22T08:09:14.133" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6782" PostTypeId="1" CreationDate="2021-09-22T10:51:25.550" Score="7" ViewCount="135" Body="&lt;p&gt;Using Quantum ESPRESSO I want to perform a slab calculation with a charged ligand (&lt;span class=&quot;math-container&quot;&gt;$\ce{H3O+}$&lt;/span&gt;), in order to avoid dipole effects across the cell I am using the &amp;quot;Effective Screening Medium&amp;quot;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;assume_isolated = &amp;quot;esm&amp;quot;&#xA;esm_bc          = &amp;quot;bc1&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I find the documentation a little bit confusing about the &lt;code&gt;esm_w&lt;/code&gt; keyword, it is said that the screening will start at &lt;span class=&quot;math-container&quot;&gt;$z = \pm[L_z/2 + \mathrm{esm}_w]$&lt;/span&gt; and that my slab should be centered around &lt;span class=&quot;math-container&quot;&gt;$z = 0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;After some research, it seems that when esm is activated the cell is shifted so that &lt;span class=&quot;math-container&quot;&gt;$L_z/2$&lt;/span&gt; is the top edge and &lt;span class=&quot;math-container&quot;&gt;$-L_z/2$&lt;/span&gt; is bottom edge, is that right?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2022-02-24T03:39:12.360" LastActivityDate="2022-09-22T16:05:43.473" Title="Confused about Effective Screening Medium for surfaces" Tags="|quantum-espresso|surfaces|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6783" PostTypeId="2" ParentId="6780" CreationDate="2021-09-23T05:48:54.780" Score="1" Body="&lt;p&gt;Step1 : find the coordinate of a &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn}$&lt;/span&gt; atom, for example,&lt;a href=&quot;https://i.stack.imgur.com/nxOBC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nxOBC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Atom: 1 Zn1 Zn 0.33333 0.66667 0.00055&lt;/p&gt;&#xA;&lt;p&gt;step 2 : go to edit&amp;gt; unit cell and click on transform&#xA;&lt;a href=&quot;https://i.stack.imgur.com/17e4G.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/17e4G.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fill origin shift as 0.33333 0.6667 0.0055 and click ok and again ok&#xA;&lt;a href=&quot;https://i.stack.imgur.com/HTSwe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HTSwe.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;strong&gt;BAZINGAA&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ngK5n.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ngK5n.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-09-23T05:48:54.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6784" PostTypeId="1" AcceptedAnswerId="6791" CreationDate="2021-09-23T12:34:54.267" Score="10" ViewCount="190" Body="&lt;p&gt;I was wondering if Kohn-Sham orbitals corresponding to a different Bloch wavevector should be orthogonal? I know that we should have &lt;span class=&quot;math-container&quot;&gt;$$\int d \boldsymbol{r}\phi_i(\boldsymbol{r}) \phi_j^*(\boldsymbol{r}) = \delta_{ij}\tag{1}$$&lt;/span&gt; but I was wondering whether, if we also considered the &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{k}$&lt;/span&gt; dependence, we should also have &lt;span class=&quot;math-container&quot;&gt;$$\int d \boldsymbol{r}\phi_i(\boldsymbol{r}, \boldsymbol{k}) \phi_j^*(\boldsymbol{r},\boldsymbol{k}' ) = \delta_{ij} \delta(\boldsymbol{k} - \boldsymbol{k}')\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My feeling is that this should be the case and so the appropriate Lagrange multipliers used in the solution of the KS equations would have to be sought for each &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{k}$&lt;/span&gt; point?&lt;/p&gt;&#xA;" OwnerUserId="3985" LastEditorUserId="5" LastEditDate="2021-09-25T22:42:45.557" LastActivityDate="2021-09-25T22:42:45.557" Title="Orthonormality of Kohn-Sham orbitals" Tags="|density-functional-theory|kohn-sham|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6785" PostTypeId="2" ParentId="6761" CreationDate="2021-09-23T14:14:51.983" Score="3" Body="&lt;p&gt;This is not a complete answer, since I can't seem to work out the &lt;span class=&quot;math-container&quot;&gt;$r_1=r_2$&lt;/span&gt; case, but I think this should get you most of the way to an answer.&lt;/p&gt;&#xA;&lt;p&gt;To start, its useful to give another definition for the grand potential in terms of the grand partition function and write the derivatives implicitly using this definition:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Omega=\frac{1}{\beta}\ln(\Xi)\tag{1}\label{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta\Omega}{\delta\psi(r_1)}=\frac{1}{\beta}\frac{\frac{\delta\Xi}{\delta\psi(r_1)}}{\Xi}\tag{2}\label{2}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta^2\Omega}{\delta\psi(r_1)\delta\psi(r_2)}=\frac{1}{\beta}\bigg[\frac{\frac{\delta^2\Xi}{\delta\psi(r_1)\delta\psi(r_2)}}{\Xi}-\frac{\frac{\delta\Xi}{\delta\psi(r_1)}}{\Xi}\frac{\frac{\delta\Xi}{\delta\psi(r_2)}}{\Xi}\bigg]\tag{3}\label{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\Xi$&lt;/span&gt; is the grand partition function. We can also re-express &lt;span class=&quot;math-container&quot;&gt;$\rho^{(n)}$&lt;/span&gt; using &lt;span class=&quot;math-container&quot;&gt;$\Xi$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\rho^{(n)}=\frac{1}{\beta\Xi}\frac{\delta^n\Xi}{\delta\psi(r_1)\delta\psi(r_2)...\delta\psi(r_n)}\label{4}\tag{4}$$&lt;/span&gt;&#xA;which we can see would lead to the result in equation \eqref{3} having the same form as in your question (at least for the &lt;span class=&quot;math-container&quot;&gt;$r_1\neq r_2$&lt;/span&gt; case).&lt;/p&gt;&#xA;&lt;p&gt;To see why this definition for &lt;span class=&quot;math-container&quot;&gt;$\rho^{(n)}$&lt;/span&gt; works, we just need to remember how the functional derivative behaves for this sort of expression. In general, for a functional of the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$F[\psi(r)]=\int dr f(r,\psi(r))$$&lt;/span&gt;&#xA;the functional derivative can be expressed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\delta F}{\delta\psi}=\frac{\partial f}{\partial\psi}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, the functional derivative has the effect of removing an integral over &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and taking the partial derivative of the integrand. This is exactly what we see in your explicit expression for &lt;span class=&quot;math-container&quot;&gt;$\rho^{(n)}$&lt;/span&gt;: every time &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; increase, the lowest index term in the sum is removed, the next lowest has its integral over &lt;span class=&quot;math-container&quot;&gt;$r_n$&lt;/span&gt; removed, and each term gets a factor of &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; due to the partial derivative.&lt;/p&gt;&#xA;&lt;p&gt;I based most of this answer off my interpretation of what is described in &lt;a href=&quot;https://ftp.rush.edu/users/molebio/Dirk/papers/Fundamentals%20of%20Inhomogeneous%20Fluids.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fundamentals of Inhomogeneous Fluids&lt;/a&gt;, mainly parts of chapters 2-3.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-09-23T14:14:51.983" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6786" PostTypeId="1" CreationDate="2021-09-23T16:54:37.473" Score="6" ViewCount="71" Body="&lt;p&gt;I'm about to do an NBO analysis to evaluate bond characteristics in a novel transition-metal complex.&lt;/p&gt;&#xA;&lt;p&gt;As I have never done anything like that, I tried to understand the basic output for an octahedral ruthenium complex with three phosphines, two hydrides and a carbonyl ligand &lt;span class=&quot;math-container&quot;&gt;$[\ce{RuP_3(H)_2(CO)}]$&lt;/span&gt; beforehand.&#xA;I'm expecting to find bonding orbitals for all three &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-P}$&lt;/span&gt; bonds, the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-C}$&lt;/span&gt; and the two &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-H}$&lt;/span&gt; bonds. However, the output only shows bonding orbitals for two &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-P}$&lt;/span&gt;  bonds and the &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-C}$&lt;/span&gt;  bond. The two hydrides appear as separate molecular units.&lt;/p&gt;&#xA;&lt;p&gt;The missing &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-P}$&lt;/span&gt; bond in the NBO analysis regards the phosphine in &lt;em&gt;trans&lt;/em&gt; position to the carbonyl ligand.&#xA;I assume that due to the &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-acceptor nature of the carbonyl ligand, &amp;quot;problems&amp;quot; in the NBO calculation occur leading to the absence of the &lt;em&gt;trans&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-P}$&lt;/span&gt; bond in the NBO analysis.&lt;/p&gt;&#xA;&lt;p&gt;Can someone point me into the right direction to get my head wrapped around that? (Bonus: Why is NBO treating the hydrides as separate units and thus not finding bonding orbitals &lt;span class=&quot;math-container&quot;&gt;$\ce{Ru-H}$&lt;/span&gt;?)&lt;/p&gt;&#xA;" OwnerUserId="4303" LastEditorUserId="7" LastEditDate="2021-09-23T18:55:46.807" LastActivityDate="2021-09-23T18:55:46.807" Title="Confused by NBO output, due to missing bonds" Tags="|computational-chemistry|transition-metals|orbitals|" AnswerCount="0" CommentCount="3" ClosedDate="2021-11-19T02:05:42.950" ContentLicense="CC BY-SA 4.0" />
  <row Id="6787" PostTypeId="1" CreationDate="2021-09-24T01:44:56.103" Score="5" ViewCount="53" Body="&lt;p&gt;I am studying doping in 0D and 2D perovskites which present tilted octahedra. It is important for me to analyze the contributions in the PDOS in terms of &lt;span class=&quot;math-container&quot;&gt;$e_g$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$t_{2g}$&lt;/span&gt; levels for d orbital in the transition metal. However, since the octahedra is tilted, Quantum Espresso doesn't give me the appropriate projections, except if I rotate the Bravais lattice so that the axis match and rerun everything as suggested in this &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2015-January/031368.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;QE list-serv discussion&lt;/a&gt; from 2015:&lt;/p&gt;&#xA;&lt;p&gt;You can see the PDOS figures attached:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DLv2j.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DLv2j.png&quot; alt=&quot;PDOS (top) original lattice (bottom) rotated lattice to match octahedra orientation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This works, but it is awful to redo all scf, nscf and postprocessing for my calculations with the tilted axis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does anybody know of a code that I can use to obtain the appropriate projections for this atom in my structure?&lt;/strong&gt; I couldn't find anything up to now, I even tried to obtain a rule to map the projections with spherical harmonics rotation but it was far from trivial.&lt;/p&gt;&#xA;" OwnerUserId="4118" LastEditorUserId="5" LastEditDate="2022-01-14T01:47:59.853" LastActivityDate="2022-01-14T01:47:59.853" Title="DOS projection in alternate axis for eg and t2g contributions" Tags="|density-functional-theory|quantum-espresso|crystallography|density-of-states|crystal-field|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-01T03:43:03.053" ContentLicense="CC BY-SA 4.0" />
  <row Id="6788" PostTypeId="2" ParentId="6772" CreationDate="2021-09-24T02:08:30.477" Score="5" Body="&lt;p&gt;Ionization energy is more appropriate for isolated atoms, you want the workfunction or ionization potential of your alloy surface. You calculate this usually from slab calculations because there is explicit vacuum.&#xA;Work function is defined as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Phi=E(vacuum)-E(Fermi)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you use vasp this can be useful &lt;a href=&quot;https://github.com/WMD-group/workfunction&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/WMD-group/workfunction&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And a very precise example in quantum espresso is available here: &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/tree/master/PP/examples/WorkFct_example&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/tree/master/PP/examples/WorkFct_example&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4118" LastActivityDate="2021-09-24T02:08:30.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6789" PostTypeId="1" CreationDate="2021-09-24T07:21:35.420" Score="9" ViewCount="130" Body="&lt;p&gt;I am looking for a summary of your favorite methods to estimate a reaction rate constant for a “complex” polyatomic reaction (requiring a cell of ~100 atoms) from ab initio methods (the one I have in mind currently is degradation of a surface layer of perovskite by superoxide, following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\small \ce{4CH_3NH_3PbI_3^* + O_2^- \rightarrow 4PbI_2 + 2I2 + 2H_2O + 4CH_3NH_2}}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt; &#xA;The most basic approach I know of would be to perform a DFT based NEB (nudged elastic band) calculation to identify the saddle point, compute the energy barrier &lt;span class=&quot;math-container&quot;&gt;$E_a$&lt;/span&gt; in the ground state, and use a Boltzmann-like relationship &lt;span class=&quot;math-container&quot;&gt;$\nu(T)=\nu_0.e^{-\beta E_a}$&lt;/span&gt; to speculate a characteristic reaction time at finite temperature. This approach has several weaknesses, in order of importance for me:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For a “complex” reaction, finding the actual saddle point with a simple NEB seems like wishful thinking to me: there could be many reaction pathways, steps, etc… which makes it challenging to set up the NEB properly. The cost of testing many potential paths would also quickly become prohibitive  since a single NEB on a relatively large system is already pretty expensive (at least at my scale)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The term &lt;span class=&quot;math-container&quot;&gt;$\nu_0$&lt;/span&gt; is quite a big unknown. I’ve seen people use “educated guesses” to plug a reasonable value into it (like the frequency of oscillations in the crystal as an attempt frequency), but it seems quite hand-wavy and could easily be way off, which begs the question of knowing whether such a guess-based result has much significance&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;It seems like a fairly harsh approximation to encapsulate all effects of thermalization in a Boltzmann law.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt; &#xA;I have seen more sophisticated methods that build upon this and bring more accuracy, like the semiclassical transition state theory (SCTST), and basically alleviate the 2 last points, but still requires to find the saddle point, and leaves me with my issue #1, which is that it might be unpractical for more complex reactions (correct me if I'm wrong and if there are reliable methods to find this saddle point)&#xA; &lt;/p&gt;&#xA;&lt;p&gt;In summary:&lt;/p&gt;&#xA;&lt;p&gt; &#xA;&lt;strong&gt;What are the schemes available to compute reaction rates at finite temperatures for relatively big systems and multi-molecular reactions? I am particularly interested in accuracy vs complexity trade-off&lt;/strong&gt; (i.e. I am interested in having a “not-so-precise-but-kinda-reasonable” result if it makes the calculations more affordable)&lt;/p&gt;&#xA;" OwnerUserId="3967" LastEditorUserId="7" LastEditDate="2022-02-12T13:43:33.827" LastActivityDate="2022-02-27T18:40:55.493" Title="Reaction rate estimation for relatively complex reactions" Tags="|density-functional-theory|transition-state|reaction-mechanism|temperature|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6791" PostTypeId="2" ParentId="6784" CreationDate="2021-09-24T14:50:13.043" Score="8" Body="&lt;p&gt;You are correct that orbitals from different &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points should be orthogonal. &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points are irreps of the translation group and, similar to the irreps of point groups for molecules, integrals of two functions with different irreps will always result in &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;More generally, we can actually separately solve the SCF equations for each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point, since the Fock matrix can be split into blocks for each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$F^kC^k=S^kC^k\epsilon^k$$&lt;/span&gt;&#xA;Some details about efficiently solving for the energy and forces of periodic systems using Gaussian type orbitals and transformations back-and-forth from real space to &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space are given in &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.16440&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Konstantin N. Kudin and Gustavo E. Scuseria Phys. Rev. B 61, 16440 DOI: &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.16440&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1103/PhysRevB.61.16440&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="887" LastEditDate="2021-09-25T20:48:24.307" LastActivityDate="2021-09-25T20:48:24.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6792" PostTypeId="1" CreationDate="2021-09-24T17:29:54.323" Score="5" ViewCount="94" Body="&lt;p&gt;An example of a solid state reaction: sintering of an initial powder of reactants leading to a product. Densification of the sintered powder giving a highly pure product powder.&lt;/p&gt;&#xA;&lt;p&gt;What methods (&lt;em&gt;ab initio&lt;/em&gt; or otherwise) would one use to study the reaction mechanism involved, possible reaction pathways, and identify intermediates? &lt;/p&gt;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-12-25T22:01:19.087" LastActivityDate="2021-12-25T22:01:19.087" Title="Methods to study reaction mechanisms in solid state reactions and identifying intermediates" Tags="|computational-chemistry|ab-initio-calculations|reaction-mechanism|" AnswerCount="0" CommentCount="6" ClosedDate="2022-02-28T14:40:54.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="6793" PostTypeId="1" CreationDate="2021-09-24T21:11:32.987" Score="10" ViewCount="867" Body="&lt;p&gt;&lt;strong&gt;I need help with:&lt;/strong&gt; I would like to know what is the most common approach to treat valence 4f electrons of lanthanides (3+ charge) in VASP that circumvents the calculation problems shown below. (or more recommendations)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;System&lt;/strong&gt;: I am having trouble with SCF calculations of a system that contains &lt;span class=&quot;math-container&quot;&gt;$\ce{2Yb^{3+}}$&lt;/span&gt; as dopants when including 4f electrons of Yb.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Setup&lt;/strong&gt;: I am using the parameters below in the &lt;code&gt;INCAR&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NWRITE = 2          &#xA;ISTART = 0  &#xA;ICHARG = 2    &#xA;LORBIT = 11&#xA;LPLANE = .FALSE. &#xA;NPAR = 4   &#xA;PREC  = Accurate  (Precision level)  &#xA;LREAL = AUTO  (Projection operators: automatic) &#xA;ALGO  = N         (Elect. algorithm: 38/48)  &#xA;ENCUT = 500 eV&#xA;&#xA;!GGA + U correction for Yb ion &#xA;LDAU = .TRUE. &#xA;LDAUTYPE = 2  &#xA;LDAUL = -1 -1 -1 3 &#xA;LDAUU = 0 0 0 7 &#xA;EDIFF  = 1.0e-05  &#xA;EDIFFG = -1.0e-01      &#xA;NBLOCK = 1       &#xA;IBRION = -1 &#xA;NSW    = 0  &#xA;ISYM   = 0    &#xA;ISMEAR = 0   &#xA;SIGMA  = 0.01  &#xA;POTIM  = 0.90 &#xA;LWAVE = .TRUE. &#xA;LCHARG = .TRUE.&#xA;!Magnetisation   &#xA;ISPIN  = 2  &#xA;LMAXMIX = 6 ! FM ORDER &#xA;MAGMOM = 27*0 24*0 81*0 1.0 1.0 &#xA;NUPDOWN = 2&#xA;&#xA;!Mixer  &#xA;AMIX     = 0.2 &#xA;BMIX     = 0.00001 &#xA;AMIX_MAG = 0.8 &#xA;BMIX_MAG = 0.00001&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also, I have varied several of them &lt;code&gt;ENCUT&lt;/code&gt;, &lt;code&gt;AMIX&lt;/code&gt; and &lt;code&gt;BMIX&lt;/code&gt; as well as the U correction from 3 to 7. Have also tried different electronic algorithms to no avail.&lt;/p&gt;&#xA;&lt;p&gt;This is a 3x3x3 supercell so I am testing runs only on the Gamma point and also with automatic Gamma 2 2 2 grid.&#xA;I have tried HSE0 functional as well and the same problem persists.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Errors&lt;/strong&gt;: Using &lt;code&gt;ALGO=N&lt;/code&gt; I can get this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error EDDDAV: Call to ZHEGV failed. Returncode =   7 1   8&#xA;and some other trials the energies keep decreasing indefinitely to really big negative numbers: &#xA;free energy    TOTEN  =      -131.40843111 eV &#xA;free energy    TOTEN  =      -120.45157042 eV  &#xA;free energy    TOTEN  =      -103.28925863 eV  &#xA;free energy    TOTEN  =    -12481.39444222 eV &#xA;free energy    TOTEN  = -67096650.34128196 eV &#xA;free energy    TOTEN  = ****************** eV &#xA;free energy    TOTEN  = ****************** eV &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Workarounds?&lt;/strong&gt;: I have found papers where a &amp;quot;\Delta SCF&amp;quot; approach is used to move one 4f electron to 5d orbital and reach desired orbital occupancy (&lt;span class=&quot;math-container&quot;&gt;$\ce{Yb^{3+}}$&lt;/span&gt;) but to know which band's occupation one needs to modify, a previously converged solution (probably without spin polarization: ISPIN=1) is needed which is not possible in my case due to charge unbalance.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Other resources:&lt;/strong&gt; Similar issues have been found in other systems with lanthanides and specifically with &lt;span class=&quot;math-container&quot;&gt;$\ce{Yb^{3+}}$&lt;/span&gt;: See post &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=18253&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;and also &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=3&amp;amp;t=14808&amp;amp;p=14808&amp;amp;hilit=4f+electrons#p14808&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; When turning off spin polarization and using Yb_3 (valence : 5p6 6s2 5d1) PAW pseudopotential with frozen f electrons the calculations converge just fine.&lt;/p&gt;&#xA;" OwnerUserId="449" LastEditorUserId="449" LastEditDate="2021-09-27T18:15:51.970" LastActivityDate="2021-10-26T06:42:51.237" Title="Recommendations to treat 4f electrons (valence) of Yb3+ in magnetic systems in VASP" Tags="|vasp|pseudopotentials|lanthanide|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6794" PostTypeId="2" ParentId="6793" CreationDate="2021-09-25T11:20:55.923" Score="6" Body="&lt;p&gt;There is a &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Available_PAW_potentials#f_elements&quot; rel=&quot;noreferrer&quot;&gt;discussion&lt;/a&gt; on this limitation on VASP page. Maybe the approach of a frozen f valence PAW pseudopotential could help you. Although magnetic properties might not be as well represented.&#xA;I'm quantum espresso user and when their PAW potentials show problems (not so rare) I go to a norm-conserving solution like &lt;code&gt;pseudodojo&lt;/code&gt; library, if you can do this in VASP i think it may help.&#xA;Also about the charge treatment, in QuantumESPRESSO in many cases I just implement a total charge on the supercell instead of specific atom as I think you're doing. If you have a dopant scf will usually bring charge localization towards the dopant in the end without need to explicitly set it in the atom, it may help convergence too.&lt;/p&gt;&#xA;" OwnerUserId="4118" LastEditorUserId="5" LastEditDate="2021-09-26T01:12:43.527" LastActivityDate="2021-09-26T01:12:43.527" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6795" PostTypeId="1" CreationDate="2021-09-25T19:15:01.130" Score="6" ViewCount="464" Body="&lt;p&gt;I am looking into double perovskite materials. One of the possible materials is &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs4CuSb2Cl12}$&lt;/span&gt;. Now, although there are a few papers which have done ab intio calculations but none of the common open databases have a CIF for this structure(COD and materials project). The &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.0c04919&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; which I am currently looking into has submitted their data to ICSD, but I do not have access.&lt;/p&gt;&#xA;&lt;p&gt;Due to which I have decided to start working on my own cif file. An older &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/407/how-can-i-create-a-cif-file-from-x-ray-diffraction-data-in-a-paper-for-compoun&quot;&gt;answer&lt;/a&gt; gave a brief description on how to do this using VESTA (and I am also comfortable with the software), but I still have some doubts. Mainly how does one calculate the spatial coordinates of each atoms and how do we add the term U (which I suppose is the energy of some sort)?&lt;/p&gt;&#xA;&lt;p&gt;If anyone has any idea how I can obtain a CIF or how to go about finding the coordinates and finally making a CIF (please also mention what other information is needed apart from the space group and lattice parameters)&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="7" LastEditDate="2021-12-07T01:22:09.800" LastActivityDate="2021-12-07T01:22:09.800" Title="How to create a CIF using VESTA?" Tags="|crystallography|vesta|cif|dft-u|perovskites|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-14T03:12:13.780" ContentLicense="CC BY-SA 4.0" />
  <row Id="6796" PostTypeId="1" CreationDate="2021-09-25T19:28:16.560" Score="11" ViewCount="260" Body="&lt;p&gt;Let's take an example of a simple FCC material, a binary alloy. Above absolute zero K, the alloy will start to disorder and become an FCC solid solution. The alloy would develop defects as it disorders. What would the best strategy (workflow) to find this alloy's equilibrium structure at &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; K be?&lt;/p&gt;&#xA;&lt;p&gt;One workflow that I can think of:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Geometry optimization at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; K using DFT.&lt;/li&gt;&#xA;&lt;li&gt;Lattice dynamics study of the alloy to get its volume (V) vs temperature (T) data, i.e. V = f(T).&lt;/li&gt;&#xA;&lt;li&gt;Find V at &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; K, &lt;span class=&quot;math-container&quot;&gt;$V_x$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Create a DFT supercell of the alloy with &lt;span class=&quot;math-container&quot;&gt;$V_x$&lt;/span&gt;. Use this cell to find formation energies (thermal stability) and phonon bandstructures (dynamic stability) of various possible disordered structures.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;When I think of MD calculations, I think of the time evolution of the system. What, then, does it mean to simulate temperature-based evolution of the system in MD or &lt;em&gt;ab initio&lt;/em&gt; MD?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="116" LastEditorUserId="5" LastEditDate="2021-10-10T22:59:54.280" LastActivityDate="2021-10-10T22:59:54.280" Title="How would one find a material's equilibrium structure at any specific temperature?" Tags="|density-functional-theory|molecular-dynamics|geometry-optimization|geometry|aimd|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6797" PostTypeId="1" CreationDate="2021-09-26T02:59:37.567" Score="10" ViewCount="1421" Body="&lt;p&gt;I was using SIESTA, and just learning the program in general, however, was having trouble finding a suitable way to automatically generate FDF files, I understand this can be done manually, and have been doing that, but I wanted an automatic solution.&lt;/p&gt;&#xA;&lt;p&gt;I heard about wxDragon, however the website is offline (If anyone has macOS Binaries that would be amazing) but are there any other tools?&lt;/p&gt;&#xA;" OwnerUserId="4287" LastEditorUserId="5" LastEditDate="2021-09-26T03:01:57.443" LastActivityDate="2021-12-31T04:34:15.813" Title="Generating SIESTA FDF File from xyz or vasp?" Tags="|siesta|apple-operating-system|" AnswerCount="4" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6798" PostTypeId="1" CreationDate="2021-09-26T08:59:49.733" Score="5" ViewCount="1589" Body="&lt;p&gt;I am using HSE06 hybrid functional to calculate the band structure. I copied IBZKPT file as the KPOINTS file and pasted the k point path for the band structure after this file. The k point path for the band structure was obtained by another band structure calculation with PBE functional for the same system before. The new KPOINTS files is shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Automatically generated mesh&#xA;61&#xA;Reciprocal lattice&#xA;0.00000000000000 0.00000000000000 0.00000000000000 1&#xA;0.09090909090909 0.00000000000000 0.00000000000000 2&#xA;...&#xA;-0.09090909090909 0.45454545454546 0.00000000000000 2&#xA;0.00000000 0.00000000 0.00000000 0.000&#xA;...&#xA;0.50000000 0.50000000 0.00000000 0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The INCAR file is shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 1&#xA;LWAVE = .FALSE.&#xA;LCHARGE = .TRUE.&#xA;ICHARG = 11&#xA;IVDW = 12&#xA;ISPIN = 2&#xA;MAGMOM = 0.156 -0.155 -0.096 0.096 -0.156 0.155 -0.156 0.155 0.096\&#xA;-0.096 0.156 -0.155 -0.156 0.155 0.096 -0.096 0.156 -0.155\&#xA;0.156 -0.155 -0.096 0.096 -0.156 0.155&#xA;LORBIT = 11&#xA;ENCUT = 500&#xA;ISMEAR = 0&#xA;SIGMA = 0.03&#xA;PREC = Accurate&#xA;LHFCALC = .TRUE.&#xA;AEXX = 0.25&#xA;HFSCREEN = 0.2&#xA;ALGO = Damped&#xA;TIME = 0.4&#xA;PRECFOCK = Fast&#xA;ISYM = 3&#xA;LREAL = Auto&#xA;NELMIN = 5&#xA;NELM = 700&#xA;NELMDL = -10&#xA;EDIFF = 1e-5&#xA;NPAR = 32&#xA;KPAR= 16&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After the NSCF calculation done, the band structure is completely wrong. I upload the band structure below, which I obtained through using p4v software to read vasprun.xml file from the non-self consistent calculation with the HSE06 hybrid functional.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ygRwR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ygRwR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The output file shows the warning information below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;| |&#xA;| W W AA RRRRR N N II N N GGGG !!! |&#xA;| W W A A R R NN N II NN N G G !!! |&#xA;| W W A A R R N N N II N N N G !!! |&#xA;| W WW W AAAAAA RRRRR N N N II N N N G GGG ! |&#xA;| WW WW A A R R N NN II N NN G G |&#xA;| W W A A R R N N II N N GGGG !!! |&#xA;| |&#xA;| Your generating k-point grid is not commensurate to the symmetry |&#xA;| of the lattice. This can cause slow convergence with respect |&#xA;| to k-points for HF type calculations |&#xA;| suggested SOLUTIONS: |&#xA;| ) if not already the case, use automatic k-point generation |&#xA;| ) shift your grid to Gamma (G) (e.g. required for hex or fcc lattice) |&#xA;| |&#xA;-----------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am doing the band structure calculation and I have to set up the k point path manually. I cannot use automatic k-point generation, which is used in single point calculation so I do not understand what VASP means by use automatic k-point generation in this band structure calculation step.&lt;/p&gt;&#xA;&lt;p&gt;Would anyone please give me some suggestions on the solution?&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much.&lt;/p&gt;&#xA;&lt;p&gt;Kieran&lt;/p&gt;&#xA;" OwnerUserId="4342" LastEditorUserId="4343" LastEditDate="2021-09-27T03:00:26.167" LastActivityDate="2022-10-31T14:01:09.747" Title="Band Structure Calculation with HSE06 Hybrid Functional in VASP" Tags="|vasp|band-structure|hse06|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6800" PostTypeId="1" CreationDate="2021-09-26T17:54:16.403" Score="5" ViewCount="350" Body="&lt;p&gt;&lt;strong&gt;Context:&lt;/strong&gt; We perform a lot of CFD (Computational Fluid Dynamics) modelling for our clients (geothermal, construction, general underground engineering, etc) where we have to model temperature flows and changes in a soil medium. In this type of modelling small changes in the thermal conductivity value of the soil medium have dramatic effects on the results of the model.&lt;/p&gt;&#xA;&lt;p&gt;We've identified inaccuracies in our model's soil thermal conductivity value (when compared to the actual thermal conductivity of the real-world soil we are trying to model) as one of the primary sources of error in our models.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What is the most accurate method for estimating the thermal conductivity of a target real-world soil, besides costly direct physical measurement? We can generally get estimates of many soil properties for our target soil from geo-tech studies, such as texture, carbon, rock content, etc. so these can potentially be used as inputs.&lt;/p&gt;&#xA;" OwnerUserId="4344" LastEditorUserId="5" LastEditDate="2021-09-26T20:04:57.767" LastActivityDate="2021-09-26T20:04:57.767" Title="Soil Modelling: Getting accurate Thermal Conductivity values" Tags="|software|software-recommendations|thermal|computational-frameworks|fluid-dynamics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6801" PostTypeId="2" ParentId="6800" CreationDate="2021-09-26T18:07:40.173" Score="9" Body="&lt;p&gt;I don't think this is something that you can model accurately in an ab initio manner, as there is no good method for predicting the thermal conductivity of amorphous materials yet, let alone materials that are both amorphous and have macroscopic inhomogeneities. IMHO the way to go is to collect experimental thermal conductivity data on soil samples with different properties, and train a Bayesian model against the data (for example a simple kriging may suffice).&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-09-26T18:07:40.173" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6802" PostTypeId="2" ParentId="6800" CreationDate="2021-09-26T18:12:15.530" Score="6" Body="&lt;h1&gt;Our Method&lt;/h1&gt;&#xA;&lt;p&gt;We have created a machine learning model for estimating the thermal conductivity of any soil, which we have made publicly available at &lt;a href=&quot;https://soilconductivity.com&quot; rel=&quot;noreferrer&quot;&gt;soilconductivity.com&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Our model is significantly more accurate than any other existing method that we are aware of (MAE of around 0.08 W/mK), besides direct physical measurement of the soil, of course. (&lt;a href=&quot;https://soilconductivity.com/accuracy&quot; rel=&quot;noreferrer&quot;&gt;here is a link&lt;/a&gt; to a detailed comparison of our model's accuracy to the best available models described in &lt;a href=&quot;https://www.researchgate.net/publication/276133549_Evaluation_of_soil_thermal_conductivity_models&quot; rel=&quot;noreferrer&quot;&gt;Evaluation of Soil Thermal Conductivity Models&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Our model DOES require information about the soil. Specifically you need to know the soil texture, carbon content, coarse-particle/gravel content, rough temperature (is it frozen or thawed), and moisture. However these properties are much easier and cheaper to find than a direct measurement of Soil Thermal Conductivity. Additionally, for an even cheaper and quicker option, our website actually includes prediction tools to estimate all of these soil properties from a given geographic location and depth.&lt;/p&gt;&#xA;" OwnerUserId="4344" LastActivityDate="2021-09-26T18:12:15.530" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6803" PostTypeId="2" ParentId="6797" CreationDate="2021-09-26T18:53:12.620" Score="7" Body="&lt;p&gt;You can use the &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;sisl&lt;/a&gt; code to convert and manage fdf files.&lt;/p&gt;&#xA;&lt;p&gt;Say reading the &lt;code&gt;xyz&lt;/code&gt; file and converting this to the appropriate &lt;code&gt;fdf&lt;/code&gt; file can be done with this command-line utility:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;sgeom input.xyz output.fdf&#xA;sgeom POSCAR output.fdf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;input.xyz&lt;/code&gt; contains the lattice information in case it has been generated by &lt;code&gt;sisl&lt;/code&gt; or &lt;code&gt;ASE&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note, I am the author of sisl.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-09-27T08:13:48.007" LastActivityDate="2021-09-27T08:13:48.007" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6804" PostTypeId="1" CreationDate="2021-09-26T19:42:03.163" Score="8" ViewCount="86" Body="&lt;p&gt;I am reading Hansen and MacDonald's &lt;a href=&quot;https://www.elsevier.com/books/theory-of-simple-liquids/hansen/978-0-12-387032-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;Theory of Simple Liquids&lt;/a&gt;, and I am going through Integral Equation theories.&lt;/p&gt;&#xA;&lt;p&gt;In section 4.3, they put forward the equation (4.3.14),&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\small \Omega _{\phi} = \Omega _0 + \int \rho ^{(1)}(r) \phi (r) dr + kT\int \rho ^{(1)}(r) \ln \frac{\rho ^{(1)}(r)}{\rho _0} - \Delta \rho ^{(1)}(r) dr - \frac{1}{2}k_BT \int \int \Delta \rho ^{(1)}(r) c^{(2)}_0 (|r-r'|)\Delta \rho ^{(1)}(r')drdr'}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then using the mass constraint, where &lt;span class=&quot;math-container&quot;&gt;$$\int \Delta \rho ^{(1)} (r)dr =0$$&lt;/span&gt;&#xA;Using the idea that particle &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; provides an external field on all the other particles, he goes on to use &lt;span class=&quot;math-container&quot;&gt;$\phi(r) = u(0,r)$&lt;/span&gt;, and then uses the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Hypernetted-chain_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;HyperNetted Chain&lt;/a&gt; (HNC) approximation to state that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$g(r) = \exp [-\beta u(r)]\exp [h(r)-c(r)]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, the authors make the jump and say that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Omega = \Omega _0 + \frac{1}{2}\rho k_BT\int h(r)[h(r)-c(r)]dr - \rho k_BT\int c(r) dr$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The quantity &lt;span class=&quot;math-container&quot;&gt;$\Delta \Omega = \Omega - \Omega _0$&lt;/span&gt; is the change in grand potential arising from the additional particle at &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt;, and using the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Ornstein%E2%80%93Zernike_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ornstein-Zernike&lt;/a&gt; relation, which states that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$h(r) = c(r) + \rho \int c(|r-r'|)h(r')dr'$$&lt;/span&gt;&#xA;for the homogeneous isotropic case.&lt;/p&gt;&#xA;&lt;p&gt;I am using &lt;span class=&quot;math-container&quot;&gt;$\ln g(0,r) = -\beta u(0,r) + (h(r)-c(r))$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\rho^{(1)}= \rho g(0,r)$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\Delta \rho^{(1)}= \rho h(0,r)$&lt;/span&gt;. However, I am not getting the result as they predict.&lt;/p&gt;&#xA;&lt;p&gt;I think I am struggling with reducing the third term with the double integral, because I see that the first term with &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; gets eliminated after I use &lt;span class=&quot;math-container&quot;&gt;$\ln g = -\beta u + h-c$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\phi(r) = u(0,r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Any advice on how to go about this jump would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="7" LastEditDate="2022-03-27T20:24:16.850" LastActivityDate="2022-03-27T20:24:16.850" Title="How to use the HNC approximation to find the change in grand potential" Tags="|density-functional-theory|statistical-thermodynamics|correlation-functions|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6805" PostTypeId="1" CreationDate="2021-09-27T06:58:21.560" Score="10" ViewCount="169" Body="&lt;p&gt;When considering the band structure of two materials or two structures along a specific k path, what exactly is meant by the gradient and the distance between band lines?&#xA;Does this show any information other than the difference in the band gap of the materials?&#xA;Is there a good reference book from where I can learn this?&lt;/p&gt;&#xA;" OwnerUserId="4346" LastActivityDate="2021-09-27T18:16:26.860" Title="What is signified by the properties of the electronic band structure?" Tags="|density-functional-theory|band-structure|electronic-structure|condensed-matter|electronic-transport|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6806" PostTypeId="2" ParentId="6797" CreationDate="2021-09-27T11:50:39.460" Score="6" Body="&lt;p&gt;You can use &lt;strong&gt;OpenBabel&lt;/strong&gt; to convert between several formats:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;abinit -- ABINIT Output Format [Read-only]&#xA;acesin -- ACES input format [Write-only]&#xA;acesout -- ACES output format [Read-only]&#xA;acr -- ACR format [Read-only]&#xA;adf -- ADF cartesian input format [Write-only]&#xA;adfband -- ADF Band output format [Read-only]&#xA;adfdftb -- ADF DFTB output format [Read-only]&#xA;adfout -- ADF output format [Read-only]&#xA;alc -- Alchemy format&#xA;aoforce -- Turbomole AOFORCE output format [Read-only]&#xA;arc -- Accelrys/MSI Biosym/Insight II CAR format [Read-only]&#xA;ascii -- ASCII format [Write-only]&#xA;axsf -- XCrySDen Structure Format [Read-only]&#xA;bgf -- MSI BGF format&#xA;box -- Dock 3.5 Box format&#xA;bs -- Ball and Stick format&#xA;c09out -- Crystal 09 output format [Read-only]&#xA;c3d1 -- Chem3D Cartesian 1 format&#xA;c3d2 -- Chem3D Cartesian 2 format&#xA;cac -- CAChe MolStruct format [Write-only]&#xA;caccrt -- Cacao Cartesian format&#xA;cache -- CAChe MolStruct format [Write-only]&#xA;cacint -- Cacao Internal format [Write-only]&#xA;can -- Canonical SMILES format&#xA;car -- Accelrys/MSI Biosym/Insight II CAR format [Read-only]&#xA;castep -- CASTEP format [Read-only]&#xA;ccc -- CCC format [Read-only]&#xA;cdjson -- ChemDoodle JSON&#xA;cdx -- ChemDraw binary format [Read-only]&#xA;cdxml -- ChemDraw CDXML format&#xA;cht -- Chemtool format [Write-only]&#xA;cif -- Crystallographic Information File&#xA;ck -- ChemKin format&#xA;cml -- Chemical Markup Language&#xA;cmlr -- CML Reaction format&#xA;cof -- Culgi object file format&#xA;com -- Gaussian Input [Write-only]&#xA;confabreport -- Confab report format [Write-only]&#xA;CONFIG -- DL-POLY CONFIG&#xA;CONTCAR -- VASP format&#xA;CONTFF -- MDFF format&#xA;copy -- Copy raw text [Write-only]&#xA;crk2d -- Chemical Resource Kit diagram(2D)&#xA;crk3d -- Chemical Resource Kit 3D format&#xA;csr -- Accelrys/MSI Quanta CSR format [Write-only]&#xA;cssr -- CSD CSSR format [Write-only]&#xA;ct -- ChemDraw Connection Table format&#xA;cub -- Gaussian cube format&#xA;cube -- Gaussian cube format&#xA;dallog -- DALTON output format [Read-only]&#xA;dalmol -- DALTON input format&#xA;dat -- Generic Output file format [Read-only]&#xA;dmol -- DMol3 coordinates format&#xA;dx -- OpenDX cube format for APBS&#xA;ent -- Protein Data Bank format&#xA;exyz -- Extended XYZ cartesian coordinates format&#xA;fa -- FASTA format&#xA;fasta -- FASTA format&#xA;fch -- Gaussian formatted checkpoint file format [Read-only]&#xA;fchk -- Gaussian formatted checkpoint file format [Read-only]&#xA;fck -- Gaussian formatted checkpoint file format [Read-only]&#xA;feat -- Feature format&#xA;fh -- Fenske-Hall Z-Matrix format [Write-only]&#xA;fhiaims -- FHIaims XYZ format&#xA;fix -- SMILES FIX format [Write-only]&#xA;fps -- FPS text fingerprint format (Dalke) [Write-only]&#xA;fpt -- Fingerprint format [Write-only]&#xA;fract -- Free Form Fractional format&#xA;fs -- Fastsearch format&#xA;fsa -- FASTA format&#xA;g03 -- Gaussian Output [Read-only]&#xA;g09 -- Gaussian Output [Read-only]&#xA;g16 -- Gaussian Output [Read-only]&#xA;g92 -- Gaussian Output [Read-only]&#xA;g94 -- Gaussian Output [Read-only]&#xA;g98 -- Gaussian Output [Read-only]&#xA;gal -- Gaussian Output [Read-only]&#xA;gam -- GAMESS Output [Read-only]&#xA;gamess -- GAMESS Output [Read-only]&#xA;gamin -- GAMESS Input&#xA;gamout -- GAMESS Output [Read-only]&#xA;gau -- Gaussian Input [Write-only]&#xA;gjc -- Gaussian Input [Write-only]&#xA;gjf -- Gaussian Input [Write-only]&#xA;got -- GULP format [Read-only]&#xA;gpr -- Ghemical format&#xA;gr96 -- GROMOS96 format [Write-only]&#xA;gro -- GRO format&#xA;gukin -- GAMESS-UK Input&#xA;gukout -- GAMESS-UK Output&#xA;gzmat -- Gaussian Z-Matrix Input&#xA;hin -- HyperChem HIN format&#xA;HISTORY -- DL-POLY HISTORY [Read-only]&#xA;inchi -- InChI format&#xA;inchikey -- InChIKey [Write-only]&#xA;inp -- GAMESS Input&#xA;ins -- ShelX format [Read-only]&#xA;jin -- Jaguar input format&#xA;jout -- Jaguar output format [Read-only]&#xA;k -- Compare molecules using InChI [Write-only]&#xA;lmpdat -- The LAMMPS data format [Write-only]&#xA;log -- Generic Output file format [Read-only]&#xA;lpmd -- LPMD format&#xA;mcdl -- MCDL format&#xA;mcif -- Macromolecular Crystallographic Info&#xA;MDFF -- MDFF format&#xA;mdl -- MDL MOL format&#xA;ml2 -- Sybyl Mol2 format&#xA;mmcif -- Macromolecular Crystallographic Info&#xA;mmd -- MacroModel format&#xA;mmod -- MacroModel format&#xA;mna -- Multilevel Neighborhoods of Atoms (MNA) [Write-only]&#xA;mol -- MDL MOL format&#xA;mol2 -- Sybyl Mol2 format&#xA;mold -- Molden format&#xA;molden -- Molden format&#xA;molf -- Molden format&#xA;molreport -- Open Babel molecule report [Write-only]&#xA;moo -- MOPAC Output format [Read-only]&#xA;mop -- MOPAC Cartesian format&#xA;mopcrt -- MOPAC Cartesian format&#xA;mopin -- MOPAC Internal&#xA;mopout -- MOPAC Output format [Read-only]&#xA;mp -- Molpro input format [Write-only]&#xA;mpc -- MOPAC Cartesian format&#xA;mpd -- MolPrint2D format [Write-only]&#xA;mpo -- Molpro output format [Read-only]&#xA;mpqc -- MPQC output format [Read-only]&#xA;mpqcin -- MPQC simplified input format [Write-only]&#xA;mrv -- Chemical Markup Language&#xA;msi -- Accelrys/MSI Cerius II MSI format [Read-only]&#xA;msms -- M.F. Sanner's MSMS input format [Write-only]&#xA;nul -- Outputs nothing [Write-only]&#xA;nw -- NWChem input format [Write-only]&#xA;nwo -- NWChem output format [Read-only]&#xA;orca -- ORCA output format [Read-only]&#xA;orcainp -- ORCA input format [Write-only]&#xA;out -- Generic Output file format [Read-only]&#xA;outmol -- DMol3 coordinates format&#xA;output -- Generic Output file format [Read-only]&#xA;paint -- Painter format [Write-only]&#xA;pc -- PubChem format [Read-only]&#xA;pcjson -- PubChem JSON&#xA;pcm -- PCModel Format&#xA;pdb -- Protein Data Bank format&#xA;pdbqt -- AutoDock PDBQT format&#xA;png -- PNG 2D depiction&#xA;pointcloud -- Point cloud on VDW surface [Write-only]&#xA;pos -- POS cartesian coordinates format [Read-only]&#xA;POSCAR -- VASP format&#xA;POSFF -- MDFF format&#xA;pov -- POV-Ray input format [Write-only]&#xA;pqr -- PQR format&#xA;pqs -- Parallel Quantum Solutions format&#xA;prep -- Amber Prep format [Read-only]&#xA;pwscf -- PWscf format [Read-only]&#xA;qcin -- Q-Chem input format [Write-only]&#xA;qcout -- Q-Chem output format [Read-only]&#xA;report -- Open Babel report format [Write-only]&#xA;res -- ShelX format [Read-only]&#xA;rinchi -- RInChI [Write-only]&#xA;rsmi -- Reaction SMILES format&#xA;rxn -- MDL RXN format&#xA;sd -- MDL MOL format&#xA;sdf -- MDL MOL format&#xA;siesta -- SIESTA format [Read-only]&#xA;smi -- SMILES format&#xA;smiles -- SMILES format&#xA;smy -- SMILES format using Smiley parser [Read-only]&#xA;stl -- STL 3D-printing format [Write-only]&#xA;svg -- SVG 2D depiction [Write-only]&#xA;sy2 -- Sybyl Mol2 format&#xA;t41 -- ADF TAPE41 format [Read-only]&#xA;tdd -- Thermo format&#xA;text -- Read and write raw text&#xA;therm -- Thermo format&#xA;tmol -- TurboMole Coordinate format&#xA;txt -- Title format&#xA;txyz -- Tinker XYZ format&#xA;unixyz -- UniChem XYZ format&#xA;VASP -- VASP format&#xA;vmol -- ViewMol format&#xA;wln -- Wiswesser Line Notation [Read-only]&#xA;xed -- XED format [Write-only]&#xA;xml -- General XML format [Read-only]&#xA;xsf -- XCrySDen Structure Format [Read-only]&#xA;xyz -- XYZ cartesian coordinates format&#xA;yob -- YASARA.org YOB format&#xA;zin -- ZINDO input format [Write-only]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Many software use it in the background to make their &amp;quot;own&amp;quot; conversions.&#xA;You can download it from &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; or just installed from your Linux repository.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-09-27T11:50:39.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6807" PostTypeId="2" ParentId="6798" CreationDate="2021-09-27T12:06:41.673" Score="5" Body="&lt;p&gt;As the error indicate:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;| Your generating k-point grid is not commensurate to the symmetry |&#xA;| of the lattice. This can cause slow convergence with respect |&#xA;| to k-points for HF type calculations |&#xA;| suggested SOLUTIONS: |&#xA;| ) if not already the case, use automatic k-point generation |&#xA;| ) shift your grid to Gamma (G) (e.g. required for hex or fcc lattice) |&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You need to define/use a correct k-point path.&lt;/p&gt;&#xA;&lt;p&gt;As you already state that you can not use automatic k-point generation, the solution is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Identify the crystal symmetry you are working on.&lt;/li&gt;&#xA;&lt;li&gt;Look for the Brillouin zones of that symmetry.&lt;/li&gt;&#xA;&lt;li&gt;Select the high symmetry points for the path.&lt;/li&gt;&#xA;&lt;li&gt;Generate the k-point between each symmetry points.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Take o look &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6360/24&quot;&gt;here&lt;/a&gt; about how to accomplish these tasks.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-09-27T12:06:41.673" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6809" PostTypeId="1" CreationDate="2021-09-27T15:06:02.823" Score="8" ViewCount="830" Body="&lt;p&gt;Reference: Density Functional Theory: A Practical Introduction, David Sholl, Janice A. Steckel, Chapter 2, Page No. 48&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Section 2.2 The fcc Cu calculations in Fig. 2.3 used a cubic supercell&#xA;with 4 Cu atoms, a cutoff energy of 292 eV, and 12 x 12 x 12 k points.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I approached this problem like this,&lt;br /&gt;&#xA;&lt;strong&gt;[cu_fcc.vcr.in]&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'vc-relax' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '../outdir' ,&#xA;                  pseudo_dir = '../pseudo' ,&#xA;                      prefix = 'cu' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 4.91,&#xA;                         nat = 4,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 21 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'gaussian' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Cu   63.55000  Cu.pbe-kjpaw.UPF &#xA;ATOMIC_POSITIONS {alat} &#xA;   Cu      0.000000000    0.000000000    0.000000000    &#xA;   Cu      0.500000000    0.000000000    0.500000000    &#xA;   Cu      0.000000000    0.500000000    0.500000000    &#xA;   Cu      0.500000000    0.500000000    0.000000000    &#xA;K_POINTS automatic &#xA;  12 12 12   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;[cu_fcc.vcr.out]&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program PWSCF v.6.8 starts on 27Sep2021 at 20:15:59 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI), running on     1 processors&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     2319 MiB available memory on the printing compute node when the environment starts&#xA;&#xA;     Reading input from cu_fcc.vcr.in&#xA;&#xA;     Current dimensions of program PWSCF are:&#xA;     Max number of different atomic species (ntypx) = 10&#xA;     Max number of k-points (npk) =  40000&#xA;     Max angular momentum in pseudopotentials (lmaxx) =  4&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine check_atoms (1):&#xA;     atoms #   1 and #   2 differ by lattice vector ( 0,-1, 1) in crystal axis&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Unfortunately, Am getting an error, which is posted above. Where is the problem in my input file?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit 1:&lt;/strong&gt;&lt;br /&gt;&#xA;As suggested by @tyberius, I changed the values from 0.5 to 0.25 and re-run the calculations. Now am getting a different error.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;[cu_fcc.vcr.out]&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program PWSCF v.6.8 starts on 27Sep2021 at 22:43:53 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI), running on     1 processors&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     934 MiB available memory on the printing compute node when the environment starts&#xA;&#xA;     Reading input from cu_fcc.vcr.in&#xA;&#xA;     Current dimensions of program PWSCF are:&#xA;     Max number of different atomic species (ntypx) = 10&#xA;     Max number of k-points (npk) =  40000&#xA;     Max angular momentum in pseudopotentials (lmaxx) =  4&#xA;&#xA;     Subspace diagonalization in iterative solution of the eigenvalue problem:&#xA;     a serial algorithm will be used&#xA;&#xA;&#xA;     G-vector sticks info&#xA;     --------------------&#xA;     sticks:   dense  smooth     PW     G-vecs:    dense   smooth      PW&#xA;     Sum          73      73     31                  387      387     113&#xA;&#xA;     Using Slab Decomposition&#xA;&#xA;&#xA;&#xA;     bravais-lattice index     =            2&#xA;     lattice parameter (alat)  =       4.9100  a.u.&#xA;     unit-cell volume          =      29.5927 (a.u.)^3&#xA;     number of atoms/cell      =            4&#xA;     number of atomic types    =            1&#xA;     number of electrons       =        44.00&#xA;     number of Kohn-Sham states=           26&#xA;     kinetic-energy cutoff     =      21.0000  Ry&#xA;     charge density cutoff     =      84.0000  Ry&#xA;     scf convergence threshold =      1.0E-06&#xA;     mixing beta               =       0.7000&#xA;     number of iterations used =            8  plain     mixing&#xA;     energy convergence thresh.=      1.0E-04&#xA;     force convergence thresh. =      1.0E-03&#xA;     press convergence thresh. =      5.0E-01&#xA;     Exchange-correlation= SLA  PW   PBX  PBC&#xA;                           (   1   4   3   4   0   0   0)&#xA;     nstep                     =           50&#xA;&#xA;&#xA;     celldm(1)=   4.910000  celldm(2)=   0.000000  celldm(3)=   0.000000&#xA;     celldm(4)=   0.000000  celldm(5)=   0.000000  celldm(6)=   0.000000&#xA;&#xA;     crystal axes: (cart. coord. in units of alat)&#xA;               a(1) = (  -0.500000   0.000000   0.500000 )  &#xA;               a(2) = (   0.000000   0.500000   0.500000 )  &#xA;               a(3) = (  -0.500000   0.500000   0.000000 )  &#xA;&#xA;     reciprocal axes: (cart. coord. in units 2 pi/alat)&#xA;               b(1) = ( -1.000000 -1.000000  1.000000 )  &#xA;               b(2) = (  1.000000  1.000000  1.000000 )  &#xA;               b(3) = ( -1.000000  1.000000 -1.000000 )  &#xA;&#xA;&#xA;     PseudoPot. # 1 for Cu read from file:&#xA;     ../pseudo/Cu.pbe-kjpaw.UPF&#xA;     MD5 check sum: fe769b0ab65dca5f3352e2411ad4c6f8&#xA;     Pseudo is Projector augmented-wave + core cor, Zval = 11.0&#xA;     Generated using &amp;quot;atomic&amp;quot; code by A. Dal Corso (espresso distribution)&#xA;     Shape of augmentation charge: BESSEL&#xA;     Using radial grid of 1199 points,  6 beta functions with: &#xA;                l(1) =   2&#xA;                l(2) =   2&#xA;                l(3) =   0&#xA;                l(4) =   0&#xA;                l(5) =   1&#xA;                l(6) =   1&#xA;     Q(r) pseudized with 0 coefficients &#xA;&#xA;&#xA;     atomic species   valence    mass     pseudopotential&#xA;        Cu            11.00    63.55000     Cu( 1.00)&#xA;&#xA;     48 Sym. Ops., with inversion, found (36 have fractional translation)&#xA;&#xA;&#xA;&#xA;   Cartesian axes&#xA;&#xA;     site n.     atom                  positions (alat units)&#xA;         1           Cu  tau(   1) = (   0.0000000   0.0000000   0.0000000  )&#xA;         2           Cu  tau(   2) = (   0.2500000   0.0000000   0.2500000  )&#xA;         3           Cu  tau(   3) = (   0.0000000   0.2500000   0.2500000  )&#xA;         4           Cu  tau(   4) = (   0.2500000   0.2500000   0.0000000  )&#xA;&#xA;     number of k points=    72  Gaussian smearing, width (Ry)=  0.0200&#xA;                       cart. coord. in units 2pi/alat&#xA;        k(    1) = (   0.0000000   0.0000000   0.0000000), wk =   0.0011574&#xA;        k(    2) = (  -0.0833333   0.0833333  -0.0833333), wk =   0.0092593&#xA;        k(    3) = (  -0.1666667   0.1666667  -0.1666667), wk =   0.0092593&#xA;        k(    4) = (  -0.2500000   0.2500000  -0.2500000), wk =   0.0092593&#xA;        k(    5) = (  -0.3333333   0.3333333  -0.3333333), wk =   0.0092593&#xA;        k(    6) = (  -0.4166667   0.4166667  -0.4166667), wk =   0.0092593&#xA;        k(    7) = (   0.5000000  -0.5000000   0.5000000), wk =   0.0046296&#xA;        k(    8) = (   0.0000000   0.1666667   0.0000000), wk =   0.0069444&#xA;        k(    9) = (  -0.0833333   0.2500000  -0.0833333), wk =   0.0277778&#xA;        k(   10) = (  -0.1666667   0.3333333  -0.1666667), wk =   0.0277778&#xA;        k(   11) = (  -0.2500000   0.4166667  -0.2500000), wk =   0.0277778&#xA;        k(   12) = (  -0.3333333   0.5000000  -0.3333333), wk =   0.0277778&#xA;        k(   13) = (   0.5833333  -0.4166667   0.5833333), wk =   0.0277778&#xA;        k(   14) = (   0.5000000  -0.3333333   0.5000000), wk =   0.0277778&#xA;        k(   15) = (   0.4166667  -0.2500000   0.4166667), wk =   0.0277778&#xA;        k(   16) = (   0.3333333  -0.1666667   0.3333333), wk =   0.0277778&#xA;        k(   17) = (   0.2500000  -0.0833333   0.2500000), wk =   0.0277778&#xA;        k(   18) = (   0.1666667  -0.0000000   0.1666667), wk =   0.0138889&#xA;        k(   19) = (   0.0000000   0.3333333   0.0000000), wk =   0.0069444&#xA;        k(   20) = (  -0.0833333   0.4166667  -0.0833333), wk =   0.0277778&#xA;        k(   21) = (  -0.1666667   0.5000000  -0.1666667), wk =   0.0277778&#xA;        k(   22) = (  -0.2500000   0.5833333  -0.2500000), wk =   0.0277778&#xA;        k(   23) = (   0.6666667  -0.3333333   0.6666667), wk =   0.0277778&#xA;        k(   24) = (   0.5833333  -0.2500000   0.5833333), wk =   0.0277778&#xA;        k(   25) = (   0.5000000  -0.1666667   0.5000000), wk =   0.0277778&#xA;        k(   26) = (   0.4166667  -0.0833333   0.4166667), wk =   0.0277778&#xA;        k(   27) = (   0.3333333   0.0000000   0.3333333), wk =   0.0138889&#xA;        k(   28) = (   0.0000000   0.5000000   0.0000000), wk =   0.0069444&#xA;        k(   29) = (  -0.0833333   0.5833333  -0.0833333), wk =   0.0277778&#xA;        k(   30) = (  -0.1666667   0.6666667  -0.1666667), wk =   0.0277778&#xA;        k(   31) = (   0.7500000  -0.2500000   0.7500000), wk =   0.0277778&#xA;        k(   32) = (   0.6666667  -0.1666667   0.6666667), wk =   0.0277778&#xA;        k(   33) = (   0.5833333  -0.0833333   0.5833333), wk =   0.0277778&#xA;        k(   34) = (   0.5000000   0.0000000   0.5000000), wk =   0.0138889&#xA;        k(   35) = (   0.0000000   0.6666667   0.0000000), wk =   0.0069444&#xA;        k(   36) = (  -0.0833333   0.7500000  -0.0833333), wk =   0.0277778&#xA;        k(   37) = (   0.8333333  -0.1666667   0.8333333), wk =   0.0277778&#xA;        k(   38) = (   0.7500000  -0.0833333   0.7500000), wk =   0.0277778&#xA;        k(   39) = (   0.6666667  -0.0000000   0.6666667), wk =   0.0138889&#xA;        k(   40) = (   0.0000000   0.8333333   0.0000000), wk =   0.0069444&#xA;        k(   41) = (   0.9166667  -0.0833333   0.9166667), wk =   0.0277778&#xA;        k(   42) = (   0.8333333   0.0000000   0.8333333), wk =   0.0138889&#xA;        k(   43) = (   0.0000000  -1.0000000   0.0000000), wk =   0.0034722&#xA;        k(   44) = (  -0.1666667   0.3333333   0.0000000), wk =   0.0277778&#xA;        k(   45) = (  -0.2500000   0.4166667  -0.0833333), wk =   0.0555556&#xA;        k(   46) = (  -0.3333333   0.5000000  -0.1666667), wk =   0.0555556&#xA;        k(   47) = (   0.5833333  -0.4166667   0.7500000), wk =   0.0555556&#xA;        k(   48) = (   0.5000000  -0.3333333   0.6666667), wk =   0.0277778&#xA;        k(   49) = (  -0.1666667   0.5000000   0.0000000), wk =   0.0277778&#xA;        k(   50) = (  -0.2500000   0.5833333  -0.0833333), wk =   0.0555556&#xA;        k(   51) = (   0.6666667  -0.3333333   0.8333333), wk =   0.0555556&#xA;        k(   52) = (   0.5833333  -0.2500000   0.7500000), wk =   0.0555556&#xA;        k(   53) = (   0.5000000  -0.1666667   0.6666667), wk =   0.0555556&#xA;        k(   54) = (   0.4166667  -0.0833333   0.5833333), wk =   0.0555556&#xA;        k(   55) = (   0.3333333   0.0000000   0.5000000), wk =   0.0277778&#xA;        k(   56) = (  -0.1666667   0.6666667  -0.0000000), wk =   0.0277778&#xA;        k(   57) = (   0.7500000  -0.2500000   0.9166667), wk =   0.0555556&#xA;        k(   58) = (   0.6666667  -0.1666667   0.8333333), wk =   0.0555556&#xA;        k(   59) = (   0.5833333  -0.0833333   0.7500000), wk =   0.0555556&#xA;        k(   60) = (   0.5000000   0.0000000   0.6666667), wk =   0.0277778&#xA;        k(   61) = (   0.8333333  -0.1666667   1.0000000), wk =   0.0277778&#xA;        k(   62) = (   0.7500000  -0.0833333   0.9166667), wk =   0.0555556&#xA;        k(   63) = (   0.6666667   0.0000000   0.8333333), wk =   0.0277778&#xA;        k(   64) = (  -0.1666667  -1.0000000  -0.0000000), wk =   0.0138889&#xA;        k(   65) = (   0.6666667  -0.3333333   1.0000000), wk =   0.0277778&#xA;        k(   66) = (   0.5833333  -0.2500000   0.9166667), wk =   0.0555556&#xA;        k(   67) = (   0.5000000  -0.1666667   0.8333333), wk =   0.0277778&#xA;        k(   68) = (   0.6666667  -0.1666667   1.0000000), wk =   0.0277778&#xA;        k(   69) = (   0.5833333  -0.0833333   0.9166667), wk =   0.0555556&#xA;        k(   70) = (   0.5000000   0.0000000   0.8333333), wk =   0.0277778&#xA;        k(   71) = (  -0.3333333  -1.0000000   0.0000000), wk =   0.0138889&#xA;        k(   72) = (  -0.5000000  -1.0000000   0.0000000), wk =   0.0069444&#xA;&#xA;     Dense  grid:      387 G-vectors     FFT dimensions: (  12,  12,  12)&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;       4.38 MB&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine memory_report (1):&#xA;     more bands than PWs!&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4352" LastEditorUserId="4352" LastEditDate="2021-09-27T17:23:39.637" LastActivityDate="2021-10-02T10:19:18.290" Title="Cu FCC vc-relax method error" Tags="|density-functional-theory|quantum-espresso|crystallography|cell-optimization|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6810" PostTypeId="2" ParentId="6809" CreationDate="2021-09-27T16:42:15.390" Score="5" Body="&lt;p&gt;As the error message states, your atoms 1 and 2 are related by translation vectors, so you can't specify both of them.&lt;/p&gt;&#xA;&lt;p&gt;Note the lattice vectors used for an &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm199&quot; rel=&quot;noreferrer&quot;&gt;FCC system&lt;/a&gt; in QE:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;2          cubic F (fcc)&lt;/p&gt;&#xA;&lt;p&gt;v1 = (a/2)(-1,0,1),  v2 = (a/2)(0,1,1), v3 = (a/2)(-1,1,0)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As you can see, &lt;code&gt;-v2+v3= (-.5,0,-.5)&lt;/code&gt;, which is the distance between atoms 1 and 2.&lt;/p&gt;&#xA;&lt;p&gt;I haven't done much with Quantum Espresso, but I believe you just need to set the coordinates in your input to 0.25 rather than 0.50.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-09-27T16:42:15.390" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6811" PostTypeId="2" ParentId="6805" CreationDate="2021-09-27T18:16:26.860" Score="8" Body="&lt;p&gt;The band structure determines the dispersion relation for the electrons within the material, the E(k) relation. Its gradient (the inverse of it, to be more precise) is related to the effective mass of the carriers. The occupation of the bands, according to the Fermi level, determines if the material is a metal or an insulator, depending on if the Fermi level crosses or not a band. More information about the electronic and optical properties can be obtained using the band structure together with the density of states. Also, the band structure can be resolved in spin, to elucidate magnetic properties. Therefore, apart from determining the bandgap, lots of information can be retrieved about the material's properties using the band structure.&lt;/p&gt;&#xA;&lt;p&gt;Good references are Solid State books such as Ashcroft and Mermin - Solid State Physics; Gerald Bastard - Wave Mechanics Applied to Semiconductor Heterostructures; Charles Kittel - Introduction to Solid State Physics.&lt;/p&gt;&#xA;&lt;p&gt;Hope it helps!&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2021-09-27T18:16:26.860" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6813" PostTypeId="1" CreationDate="2021-09-27T22:30:03.417" Score="13" ViewCount="1020" Body="&lt;p&gt;During the convergence test of k points, I observed my energy start increasing instead of decreasing. I am doubtful is this correct or I am doing something wrong. can I take the appropriate K point in this type of converged graph in which energy is inceasing.&#xA;I am doing this convergence test for bulk material (spin polarised calculation) and K points I took like 2X2X2 then 3X3X3 and so on and observed the corresponding energy.&lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/xTwyx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xTwyx.png&quot; alt=&quot;energy convergence with different K points mesh&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are my input file settings:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM = GRPH Electronic Relaxation 1 ISTART = 0 ICHARG = 2 ISPIN = 2 LWAVE = .F. LELF = .F. MAGMOM = 128*1.0 PREC = Accurate ENCUT = 500 LREAL = A NELM = 100 NELMIN = 4 EDIFF = 1E-5 EDIFFG = -1E-2 NSW = 500 IBRION = 2 ISIF = 3 LORBIT = 10 #DOS related values ISMEAR = 0; SIGMA = 0.05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4354" LastEditorUserId="5" LastEditDate="2021-09-30T21:07:08.190" LastActivityDate="2021-09-30T21:07:08.190" Title="Doubt about energy convergence with different k points" Tags="|density-functional-theory|vasp|k-points|convergence-test|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6814" PostTypeId="1" AcceptedAnswerId="6815" CreationDate="2021-09-28T07:19:40.440" Score="7" ViewCount="533" Body="&lt;p&gt;Reference: Density Functional Theory: A Practical Introduction, David Sholl, Janice A. Steckel, Chapter 3, Page No. 59&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A useful rule of thumb is that calculations that have similar&#xA;densities of k points in reciprocal space will have similar levels of&#xA;convergence. This rule of thumb suggests that using 8x8x2k points&#xA;would give reasonable convergence, where the three numbers  refer to&#xA;the number of k points along the reciprocal lattice vectors &lt;span class=&quot;math-container&quot;&gt;$b_1$&lt;/span&gt; ,&#xA;&lt;span class=&quot;math-container&quot;&gt;$b_2$&lt;/span&gt; , and &lt;span class=&quot;math-container&quot;&gt;$b_3$&lt;/span&gt; , respectively. You should check from the definition&#xA;of the reciprocal lattice vectors that this choice for the k points&#xA;will define a set of k points with equal density in each direction in&#xA;reciprocal space.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I didn't understand what the author wants to convey. Prior to this paragraph, he talks about how many k-points one should take (&lt;strong&gt;Monkhorst – Pack sampling&lt;/strong&gt;) during calculation. Gives an example of bulk Cu which contains 16 atoms in its supercell with lattice vectors given by,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{a}_1 = a(1, 0, 0), \quad \vec{a}_2 = a(0, 1, 0), \quad \vec{a}_3 = a(0, 0, 4) &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How does the author figure the optimal number of k-points and how does he justify his findings?&lt;/p&gt;&#xA;" OwnerUserId="4352" LastEditorUserId="4352" LastEditDate="2021-09-28T07:27:28.173" LastActivityDate="2021-09-28T20:31:56.297" Title="Monkhorst – Pack sampling: How many k points one should take" Tags="|density-functional-theory|k-points|convergence-test|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6815" PostTypeId="2" ParentId="6814" CreationDate="2021-09-28T08:12:27.297" Score="4" Body="&lt;p&gt;The author does this by saying that we need 8 k-points along each lattice direction with unit length. And since one of the lattice vectors is 4 times longer it needs &lt;span class=&quot;math-container&quot;&gt;$1/4$&lt;/span&gt; of the k-points. Remember that in reciprocal space the length of the &lt;span class=&quot;math-container&quot;&gt;$b_i$&lt;/span&gt; vectors are (in orthogonal lattices) &lt;span class=&quot;math-container&quot;&gt;$b_i=1/a_i$&lt;/span&gt;. And to sample with reciprocal vectors with the same density you can infer the number of k-points.&lt;/p&gt;&#xA;&lt;p&gt;In this case &lt;span class=&quot;math-container&quot;&gt;$|a_1|=|a_2|=|a_3|/4$&lt;/span&gt;, and in reciprocal space we have &lt;span class=&quot;math-container&quot;&gt;$|b_1| =|b_2|=4|b_3|$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As an example, consider a 1D chain with lattice constant &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;. You sample this with &lt;span class=&quot;math-container&quot;&gt;$N_k$&lt;/span&gt; k-points. Now take the same 1D chain and double it to &lt;span class=&quot;math-container&quot;&gt;$a'=2a$&lt;/span&gt;. To sample exactly the same k-points in reciprocal space you need only &lt;span class=&quot;math-container&quot;&gt;$N_k/2$&lt;/span&gt; k-points in the &lt;span class=&quot;math-container&quot;&gt;$a'$&lt;/span&gt; system.&lt;/p&gt;&#xA;&lt;p&gt;So say the lattice is made twice as big along the &lt;span class=&quot;math-container&quot;&gt;$a_1$&lt;/span&gt;, then you would halve the number of k-points&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-09-28T20:31:56.297" LastActivityDate="2021-09-28T20:31:56.297" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6816" PostTypeId="2" ParentId="6813" CreationDate="2021-09-28T09:45:10.007" Score="15" Body="&lt;p&gt;Let's just remind ourselves what k point sampling is. It is used to approximate the integral of a function over the Brillouin zone by replacing the integral with a sum over a finite number of points:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\int_{BZ} F({\bf k})d{\bf k} \approx \sum_j w_j F({\bf k_j})&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now this is an approximation, and for any relatively sane function the error in this approximation will decrease with the number of sampling points, and eventually converge to the correct value. But note there is absolutely &lt;em&gt;nothing&lt;/em&gt; which says what the sign of the error is. It could be positive. It could be negative. And whether it is positive or negative could vary with the number of sampling points. Thus it is far from uncommon to see the total Energy increase when you initially increase the number of k points, and then show damped oscillations about the converged value, which is what you seem to be observing.&lt;/p&gt;&#xA;&lt;p&gt;Compare this with how the total energy changes with respect to variations in the wavefunction. Here the variational principle applies, so any approximate wavefunction will result in a total energy higher than the ground state energy, unless the wavefunction is exactly the ground state wavefunction. Thus we can solve for the ground state wavefunction (and energy) by a minimization procedure. However for k point sampling this principle does &lt;em&gt;not&lt;/em&gt; apply, and thus we can see errors of either sign - k point sampling is &lt;em&gt;not&lt;/em&gt; variational, but enough k points will converge to the true value (or more strictly to within a desired error from the true value)&lt;/p&gt;&#xA;" OwnerUserId="269" LastActivityDate="2021-09-28T09:45:10.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6817" PostTypeId="1" AcceptedAnswerId="6833" CreationDate="2021-09-28T12:31:39.600" Score="5" ViewCount="90" Body="&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;: Density Functional Theory: A Practical Introduction, David Sholl, Janice A. Steckel, Chapter 2, Page No. 46&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Hf is experimentally observed to be an hcp metal with c/a 1.58. Perform calculations&#xA;to predict the lattice parameters for Hf and compare them with experimental observations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;[hf.vc-rlx.in]&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'vc-relax' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '../tmp' ,&#xA;                  pseudo_dir = '../pseudo' ,&#xA;                      prefix = 'hf' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 4,&#xA;                   celldm(1) = 6.5,&#xA;                   celldm(3) = 1.58,&#xA;                         nat = 1,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 36 ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'methfessel-paxton' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA;                    conv_thr = 1d-8 ,&#xA;                 mixing_mode = 'plain' ,&#xA;                 mixing_beta = 0.7 ,&#xA; /&#xA; &amp;amp;IONS&#xA;                ion_dynamics = 'bfgs' ,&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA;                       press = 0 ,&#xA;              press_conv_thr = 0.5 ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Hf  178.49000  Hf.pbe-spdfn-rrkjus_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Hf      0.000000000    0.000000000    0.000000000    &#xA;K_POINTS automatic &#xA;  4 4 4   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;[hf.vc-rlx.out]&lt;/strong&gt;(limited)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Final enthalpy           =   -1516.8783325778 Ry&#xA;&#xA;     File ../tmp/hf.bfgs deleted, as requested&#xA;Begin final coordinates&#xA;     new unit-cell volume =     76.72443 a.u.^3 (    11.36939 Ang^3 )&#xA;     density =     26.06909 g/cm^3&#xA;&#xA;CELL_PARAMETERS (alat=  6.50000000)&#xA;   0.631871376  -0.000000000  -0.000000000&#xA;  -0.315935688   0.547216664  -0.000000000&#xA;  -0.000000000  -0.000000000   0.807989338&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA;Hf            0.0000000000        0.0000000000        0.0000000000&#xA;End final coordinates&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;[Results]&lt;/strong&gt;&lt;br /&gt;&#xA;Lattice paramter of Hafnium is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;a = 2.248600941 \, \mathrm{A}^\circ \tag{Without shape preserving}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;a = 3.818654808 \, \mathrm{A}^\circ \tag{with shape preserving}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But these values are &lt;a href=&quot;https://sites.psu.edu/dftap/2018/01/25/determining-the-lattice-parameters-of-hf/&quot; rel=&quot;noreferrer&quot;&gt;incorrect&lt;/a&gt;, the &lt;a href=&quot;https://www.webelements.com/hafnium/crystal_structure.html&quot; rel=&quot;noreferrer&quot;&gt;experimental&lt;/a&gt; value is &lt;span class=&quot;math-container&quot;&gt;$3.19 \mathrm{A}^\circ$&lt;/span&gt;. I could not figure out where am I doing wrong.&lt;/p&gt;&#xA;" OwnerUserId="4352" LastActivityDate="2021-10-02T10:33:21.587" Title="Variable Cell Optimization of Halfnium Crystal" Tags="|density-functional-theory|quantum-espresso|crystallography|geometry-optimization|virtual-crystal-approximation|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6818" PostTypeId="2" ParentId="6809" CreationDate="2021-09-28T15:30:55.060" Score="5" Body="&lt;p&gt;&lt;code&gt;ibrav = 2&lt;/code&gt; in Quantum Espresso gives an fcc Bravis lattice, as mentioned in the answer by Tyberius, with the lattice vectors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a(1) = (  -0.500000   0.000000   0.500000 )&#xA;a(2) = (   0.000000   0.500000   0.500000 )&#xA;a(3) = (  -0.500000   0.500000   0.000000 )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using an fcc Bravis lattice, which the primitive cell for fcc structures contains one atom. The cubic, conventional fcc cell contains four atoms, which is the source of confusion.&lt;/p&gt;&#xA;&lt;p&gt;I set up a relaxation file based on the one you had for fcc Cu like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'vc-relax' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '../outdir' ,&#xA;                  pseudo_dir = '../pseudo' ,&#xA;                      prefix = 'cu' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 7.2,&#xA;                         nat = 1,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 21 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'gaussian' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Cu   63.55000  Cu.pbe-kjpaw.UPF &#xA;ATOMIC_POSITIONS {alat} &#xA;   Cu      0.000000000    0.000000000    0.000000000    &#xA;K_POINTS automatic &#xA;  12 12 12   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The differences are in the choice of &lt;code&gt;celldm(1) = 7.2&lt;/code&gt; for the initial guess, &lt;code&gt;nat = 1&lt;/code&gt; and the single Cu atom in the &lt;code&gt;ATOMIC_POSITIONS&lt;/code&gt; card.&lt;/p&gt;&#xA;&lt;p&gt;I'm not sure what &lt;code&gt;celldm(1)&lt;/code&gt; you were using once you tried only one atom. The way I determined 7.2 as a guess was to perform several SCF calculations at different values of &lt;code&gt;celldm(1)&lt;/code&gt; and add those cell dimensions and energies to a file called &lt;code&gt;alat-e.dat&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;6.0 -212.99886753&#xA;6.5 -213.12777832&#xA;6.8 -213.15585359&#xA;7.0 -213.16375461&#xA;7.2 -213.16506950&#xA;7.5 -213.16053932&#xA;8.0 -213.13825503&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I ran Quantum Espresso's &lt;code&gt;ev.x&lt;/code&gt; with the input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ ev.x&#xA;     Lattice parameter or Volume are in (au, Ang) &amp;gt; au&#xA;     Enter type of bravais lattice (fcc, bcc, sc, noncubic) &amp;gt; fcc&#xA;     Enter type of equation of state :&#xA;     1=birch1, 2=birch2, 3=keane, 4=murnaghan &amp;gt; 4&#xA;     Input file &amp;gt; alat-e.dat&#xA;     Output file &amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which gives the output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# equation of state: murnaghan.        chisq =   0.2682D-07&#xA;# a0 =  7.1754 a.u., k0 = 1018 kbar, dk0 =  4.51 d2k0 =  0.000 emin = -213.16545&#xA;# a0 =  3.79708 Ang, k0 = 101.9 GPa,  V0 =    92.36 (a.u.)^3,  V0 =   13.69 A^3&#xA;&#xA;#########################################################################&#xA;# Lat.Par       E_calc        E_fit       E_diff    Pressure      Enthalpy&#xA;# a.u.            Ry           Ry            Ry        GPa           Ry&#xA;#########################################################################&#xA;  6.00000    -212.99887    -212.99887    -0.00000     231.74     -212.14819&#xA;  6.50000    -213.12778    -213.12781     0.00004      63.49     -212.83147&#xA;  6.80000    -213.15585    -213.15581    -0.00004      24.15     -213.02679&#xA;  7.00000    -213.16375    -213.16357    -0.00019       8.99     -213.11137&#xA;  7.20000    -213.16507    -213.16541     0.00034      -1.02     -213.17154&#xA;  7.50000    -213.16054    -213.16037    -0.00017     -10.17     -213.23347&#xA;  8.00000    -213.13826    -213.13828     0.00003     -17.40     -213.28964&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;celldm(1) = 7.2&lt;/code&gt; I rounded from the &lt;code&gt;a0 =  7.1754 a.u.&lt;/code&gt; value in the output. The value of &lt;code&gt;a0&lt;/code&gt; in Å, &lt;code&gt;a0 =  3.79708 Ang&lt;/code&gt;, seems reasonable, but I haven't checked it.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-09-28T15:30:55.060" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6819" PostTypeId="1" CreationDate="2021-09-29T06:52:54.433" Score="9" ViewCount="281" Body="&lt;p&gt;I am working with semiconductor materials using the SIESTA DFT package. I have tried the BoltzTraP2 software interface with SIESTA, however the results (Seebeck coefficient of MgO and Si) did not match with those published in literature. Are there any other options available to do this with reduced computational cost?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="887" LastEditDate="2021-09-29T12:37:30.157" LastActivityDate="2021-10-14T15:34:14.020" Title="Evaluating Seebeck coefficient using DFT" Tags="|density-functional-theory|condensed-matter|tight-binding|siesta|electronic-transport|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6820" PostTypeId="1" CreationDate="2021-09-29T12:58:02.100" Score="5" ViewCount="58" Body="&lt;p&gt;My question is, how do I calculate the carrier concentration from a DFT study? I am using MedeA VASP for the DFT simulation.&lt;/p&gt;&#xA;" OwnerUserId="4364" LastEditorUserId="5" LastEditDate="2021-09-30T20:59:19.630" LastActivityDate="2021-09-30T20:59:19.630" Title="MedeA VASP: Determination of carrier concentration" Tags="|density-functional-theory|vasp|ab-initio-calculations|" AnswerCount="0" CommentCount="3" ClosedDate="2021-12-02T17:09:16.560" ContentLicense="CC BY-SA 4.0" />
  <row Id="6821" PostTypeId="1" CreationDate="2021-09-29T15:00:00.567" Score="4" ViewCount="207" Body="&lt;p&gt;I understand that my question is similar to what Mythreyi asked here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/90/generating-special-quasirandom-structures-sqs-for-surface-calculations&quot;&gt;Generating special quasirandom structures (SQS) for surface calculations?&lt;/a&gt;, but based on the rules this website specifies, I thought it was better to start a new question.&lt;/p&gt;&#xA;&lt;p&gt;My research is on gas-surface reactions. I generated SQS using ATAT mcsqs, and optimized the structure using VASP. I then built the surface using VASP optimized bulk structure, added the vacuum space so that I can study gas-surface reaction, and tried to optimize the structure again with VASP, but it failed. It seems this failure supports Mythreyi's concern.&lt;/p&gt;&#xA;&lt;p&gt;I wonder if anyone had ever successfully developed the surface for SQS.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;&lt;p&gt;Edit:&#xA;Hello Nike, thank you for your comments.&#xA;I have some updates. When I tried to optimize the geometry the first time, I allowed the atom position, Cell shape, and Cell volume to change, and VASP failed to converge. I, then, performed the following three restricted calculations, and all three calculations were converged.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Allow atom position and cell volume to change.&#xA;E0 = -436.77914 eV after 18 calculation cycles&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Allow only atom position to change.&#xA;E0 = -436.77971 eV  after 18 calculation cycles&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Allow atom position and cell shape to change.&#xA;E0 = -436.82406 eV after 22 calculation cycles&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The total energies for #1 and #2 were similar. #3 was different from the other two, but it had a lower energy.&lt;/p&gt;&#xA;&lt;p&gt;I greatly appreciate it if anyone can comment on these results, such as which one is the most reasonable choice.&lt;/p&gt;&#xA;&lt;p&gt;I'll post my inputs and possibly outputs later.&lt;/p&gt;&#xA;" OwnerUserId="4360" LastEditorUserId="7" LastEditDate="2021-10-02T01:02:37.767" LastActivityDate="2021-10-02T01:02:37.767" Title="Building the surface for Special Quasi-random Structure (SQS)" Tags="|surfaces|special-quasirandom-structures|" AnswerCount="0" CommentCount="2" ClosedDate="2021-12-02T15:25:41.897" ContentLicense="CC BY-SA 4.0" />
  <row Id="6822" PostTypeId="1" CreationDate="2021-09-29T17:21:05.117" Score="5" ViewCount="93" Body="&lt;p&gt;The Nosé thermostat is explained in Chapter 6 of &lt;a href=&quot;https://www.elsevier.com/books/understanding-molecular-simulation/frenkel/978-0-12-267351-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;Understanding Molecular Simulation&lt;/a&gt;. Perhaps it's because I find it difficult to follow the derivation, but the physical meaning behind the &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; parameter being added to the system isn't obvious to me.&lt;/p&gt;&#xA;&lt;p&gt;The Langrangian of the system is extended and becomes:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{L} = \sum^N_{i=1}\frac{m_i}{2}s^2\dot{\vec{r}}_i^2 - \mathcal{U}\left(\vec{r}^N\right) +\frac{Q}{2}\dot{s}^2 - \frac{L}{\beta}\ln(s)\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; is an additional coordinate, &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; is an effective mass associated with &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is a parameter to be fixed later, and presumably &lt;span class=&quot;math-container&quot;&gt;$\beta = \frac{1}{k_B T}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I understand that &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; is supposed to represent the system being attached to a heat bath, but what is the physical explanation for this? How would you describe what the Nosé thermostat does qualitatively?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Frenkel, D., &amp;amp; Smit, B. (2002). Understanding molecular simulation: From algorithms to applications. Academic Press. ISBN: 9780122673511&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="5" LastEditDate="2022-01-14T01:51:49.770" LastActivityDate="2022-01-14T01:51:49.770" Title="What is the qualitative meaning of the Nosé thermostat?" Tags="|molecular-dynamics|statistical-thermodynamics|thermodynamics|" AnswerCount="0" CommentCount="7" ClosedDate="2023-02-07T03:05:44.233" ContentLicense="CC BY-SA 4.0" />
  <row Id="6823" PostTypeId="1" AcceptedAnswerId="6865" CreationDate="2021-09-30T11:37:50.617" Score="11" ViewCount="199" Body="&lt;p&gt;To calculate the excited state properties and processes of semiconductors (e.g. during the photocatalysis process), can be important. Non-Adiabatic Molecular Dynamics (NAMD) is one of the popular methods. I think NAMD still works within the DFT framework according to the introduction of the &lt;a href=&quot;https://dornsife.usc.edu/assets/sites/1066/docs/ar198.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;PYXAID Program&lt;/a&gt; and &lt;a href=&quot;http://home.ustc.edu.cn/%7Ezqj/code/namd.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hefei-NAMD&lt;/a&gt;. &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;But since the DFT works not so well when dealing with semiconductors and excited-state calculations, wouldn't NAMD be too erroneous considering the nuclei vibrations?&lt;br&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-10-10T05:16:10.553" LastActivityDate="2021-10-10T05:16:10.553" Title="Deviation caused by using DFT in Non-Adiabatic Molecular Dynamics" Tags="|density-functional-theory|molecular-dynamics|td-dft|photochemistry|non-adiabatic|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6824" PostTypeId="1" AcceptedAnswerId="6881" CreationDate="2021-09-30T21:48:44.163" Score="8" ViewCount="1118" Body="&lt;p&gt;What is the difference between the GW and non-GW potentials in VASP.  While it is clear that the GW potentials should be used with GW calculations, the documentation also states that these potentials should be okay for standard DFT.&lt;/p&gt;&#xA;&lt;p&gt;What time cost / accuracy difference is expected with using GW potentials rather than standard potentials and what is the fundamental difference between these potentials?&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="7" LastEditDate="2021-11-01T16:55:24.383" LastActivityDate="2022-11-09T00:14:53.707" Title="VASP GW PAW Pseudopotentials" Tags="|vasp|reference-request|pseudopotentials|gw-bse|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6825" PostTypeId="1" AcceptedAnswerId="9197" CreationDate="2021-09-30T22:43:29.080" Score="4" ViewCount="63" Body="&lt;p&gt;I am trying to develop phase coexistence curves for generic polymers. Of course, I can use standard Flory theory free energy functionals to do this, but I want to define my nearest neighbor polymer-polymer and polymer-solvent interaction energies explicitly, and run numerical experiments.&lt;/p&gt;&#xA;&lt;p&gt;I am thinking about running Monte Carlo simulations of polymers on a discrete lattice. My question is, does such software exist? I want to plant a polymer on a lattice along with solvent molecules and examine the behavior of the system after &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; moves.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2022-01-14T01:52:18.667" LastActivityDate="2022-06-04T02:41:11.603" Title="Discrete lattice polymer simulations" Tags="|software|software-recommendations|monte-carlo|polymers|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6826" PostTypeId="1" CreationDate="2021-10-01T07:07:18.660" Score="6" ViewCount="84" Body="&lt;p&gt;I am trying to learn the characterization of Weyl nodes computationally. For this, I am using &lt;strong&gt;Wannier90&lt;/strong&gt; and &lt;strong&gt;Z2pack&lt;/strong&gt; codes in interface with &lt;strong&gt;Quantum ESPRESSO&lt;/strong&gt;. I have done scf, nscf, bands structure, DOS, etc calculations in Quantum ESPRESSO, earlier. I want to learn how I can characterize the presence of Weyl nodes using these codes. I think for this I have to calculate the Chern number for a surface (spherical) which enclosed the Weyl points in k-space. For Weyl nodes, it should be +1 and -1 (opposite chirality).&lt;/p&gt;&#xA;&lt;p&gt;I want to know, what steps do I have to follow to get the result, eg. in band structure calculation we perform SCF, bands calculation with pw.x executable and then use the bands.x to get the .dat files. What do I have to do in this case?  I have already installed all the codes and interfaces.&lt;/p&gt;&#xA;&lt;p&gt;I have surfed on the internet a lot but didn't get any clarified tutorial for this. Please share your experience if you have done it. It will be helpful.&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2022-01-14T01:53:04.117" LastActivityDate="2022-01-14T01:53:04.117" Title="What computational steps needed to characterize the Weyl points?" Tags="|density-functional-theory|quantum-espresso|topological-insulators|wannier90|weyl-semimetal|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-01T03:42:04.597" ContentLicense="CC BY-SA 4.0" />
  <row Id="6827" PostTypeId="1" CreationDate="2021-10-01T11:14:46.520" Score="3" ViewCount="347" Body="&lt;p&gt;I would like to perform a &amp;quot;vc-relax&amp;quot; calculation on a simple 3x4x5 &lt;span class=&quot;math-container&quot;&gt;$\ce{Pt}111$&lt;/span&gt; slab, this calculation is running well but as soon as I add the &lt;code&gt;ESM&lt;/code&gt; keyword it crashes at the first SCF iteration of the second BFGS step.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'vc-relax'&#xA;  etot_conv_thr = 1.0000000000d-05&#xA;  forc_conv_thr = 5.0000000000d-04&#xA;  pseudo_dir = 'XXXXXXXXXXXX/PseudoPotentials'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss = 0.015&#xA;  ecutrho = 440&#xA;  ecutwfc = 55&#xA;  ibrav = 8&#xA;  A = 8.3155757468&#xA;  B = 9.6019997917&#xA;  C = 29&#xA;  nat = 60&#xA;  nosym = .true.&#xA;  ntyp = 1&#xA;  occupations = 'smearing'&#xA;  smearing = 'cold'&#xA;  input_dft = &amp;quot;rpbe&amp;quot;&#xA;  assume_isolated = &amp;quot;esm&amp;quot;&#xA;  esm_bc = &amp;quot;bc1&amp;quot;&#xA;  esm_w = 0.0&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 5D-8&#xA;  mixing_mode = &amp;quot;local-TF&amp;quot;&#xA;  mixing_beta = 0.3&#xA;/&#xA;&amp;amp;IONS&#xA;  ion_dynamics = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&amp;amp;CELL&#xA;  cell_dynamics = &amp;quot;bfgs&amp;quot;&#xA;  press_conv_thr = 0.5&#xA;  cell_dofree = &amp;quot;xy&amp;quot;&#xA;/&#xA;ATOMIC_SPECIES&#xA;Pt 195.084 Pt.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS angstrom&#xA;Pt       0.00000000       1.60034000      -4.52643000&#xA;Pt       2.77186000       1.60034000      -4.52643000&#xA;Pt       5.54371000       1.60034000      -4.52643000&#xA;Pt       1.38593000       4.00084000      -4.52643000&#xA;Pt       4.15778000       4.00084000      -4.52643000&#xA;Pt       6.92964000       4.00084000      -4.52643000&#xA;Pt       0.00000000       6.40134000      -4.52643000&#xA;Pt       2.77186000       6.40134000      -4.52643000&#xA;Pt       5.54371000       6.40134000      -4.52643000&#xA;Pt       1.38593000       8.80184000      -4.52643000&#xA;Pt       4.15778000       8.80184000      -4.52643000&#xA;Pt       6.92964000       8.80184000      -4.52643000&#xA;Pt       0.00000000       0.00000000      -2.26321000&#xA;Pt       2.77186000       0.00000000      -2.26321000&#xA;Pt       5.54371000       0.00000000      -2.26321000&#xA;Pt       1.38593000       2.40050000      -2.26321000&#xA;Pt       4.15778000       2.40050000      -2.26321000&#xA;Pt       6.92964000       2.40050000      -2.26321000&#xA;Pt       0.00000000       4.80100000      -2.26321000&#xA;Pt       2.77186000       4.80100000      -2.26321000&#xA;Pt       5.54371000       4.80100000      -2.26321000&#xA;Pt       1.38593000       7.20150000      -2.26321000&#xA;Pt       4.15778000       7.20150000      -2.26321000&#xA;Pt       6.92964000       7.20150000      -2.26321000&#xA;Pt       1.38593000       0.80017000       0.00000000&#xA;Pt       4.15778000       0.80017000       0.00000000&#xA;Pt       6.92964000       0.80017000       0.00000000&#xA;Pt       0.00000000       3.20067000       0.00000000&#xA;Pt       2.77186000       3.20067000       0.00000000&#xA;Pt       5.54371000       3.20067000       0.00000000&#xA;Pt       1.38593000       5.60117000       0.00000000&#xA;Pt       4.15778000       5.60117000       0.00000000&#xA;Pt       6.92964000       5.60117000       0.00000000&#xA;Pt       0.00000000       8.00167000       0.00000000&#xA;Pt       2.77186000       8.00167000       0.00000000&#xA;Pt       5.54371000       8.00167000       0.00000000&#xA;Pt       0.00000000       1.60034000       2.26321000&#xA;Pt       2.77186000       1.60034000       2.26321000&#xA;Pt       5.54371000       1.60034000       2.26321000&#xA;Pt       1.38593000       4.00084000       2.26321000&#xA;Pt       4.15778000       4.00084000       2.26321000&#xA;Pt       6.92964000       4.00084000       2.26321000&#xA;Pt       0.00000000       6.40134000       2.26321000&#xA;Pt       2.77186000       6.40134000       2.26321000&#xA;Pt       5.54371000       6.40134000       2.26321000&#xA;Pt       1.38593000       8.80184000       2.26321000&#xA;Pt       4.15778000       8.80184000       2.26321000&#xA;Pt       6.92964000       8.80184000       2.26321000&#xA;Pt       0.00000000       0.00000000       4.52643000&#xA;Pt       2.77186000       0.00000000       4.52643000&#xA;Pt       5.54371000       0.00000000       4.52643000&#xA;Pt       1.38593000       2.40050000       4.52643000&#xA;Pt       4.15778000       2.40050000       4.52643000&#xA;Pt       6.92964000       2.40050000       4.52643000&#xA;Pt       0.00000000       4.80100000       4.52643000&#xA;Pt       2.77186000       4.80100000       4.52643000&#xA;Pt       5.54371000       4.80100000       4.52643000&#xA;Pt       1.38593000       7.20150000       4.52643000&#xA;Pt       4.15778000       7.20150000       4.52643000&#xA;Pt       6.92964000       7.20150000       4.52643000&#xA;K_POINTS automatic&#xA;4 3 1 1 1 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I looked on the Quantum Espresso mailing list and tried a few other options: increase vacuum, increase ecut, increase nbnd... nothing is working so far.&lt;/p&gt;&#xA;&lt;p&gt;Could someone help here?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="7" LastEditDate="2021-10-01T16:44:07.193" LastActivityDate="2021-10-01T16:44:07.193" Title="Simple Pt111 slab not converging using Quantum Espresso" Tags="|quantum-espresso|geometry-optimization|surfaces|" AnswerCount="0" CommentCount="4" ClosedDate="2021-11-29T18:55:02.830" ContentLicense="CC BY-SA 4.0" />
  <row Id="6829" PostTypeId="1" AcceptedAnswerId="6899" CreationDate="2021-10-02T03:55:32.977" Score="10" ViewCount="1251" Body="&lt;p&gt;I have installed quantum espresso with GPU support on a system.&lt;/p&gt;&#xA;&lt;p&gt;Ubuntu 18.04.5 LTS (GNU/Linux 4.15.0-135-generic x86_64)&lt;/p&gt;&#xA;&lt;p&gt;System Configuration:&#xA;Processor: Intel Xeon Gold 5120 CPU 2.20 GHz (2 Processor)&#xA;RAM: 96 GB&#xA;HDD: 6 TB&#xA;Graphics Card: NVIDIA Quadro P5000 (16 GB)&lt;/p&gt;&#xA;&lt;p&gt;Usually, without GPU support, I submit jobs simply using: mpirun pw.x -inp input.in &amp;gt; output.out. The output file in such cases includes these lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;  Parallel version (MPI), running on    28 processors&#xA;      MPI processes distributed on     1 nodes&#xA;      K-points division:     npool     =       2&#xA;      R &amp;amp; G space division:  proc/nbgrp/npool/nimage =      14&#xA;      wavefunctions fft division:  Y-proc x Z-proc =       2      7&#xA;      wavefunctions fft division:  task group distribution&#xA;                                   #TG    x Z-proc =       2      7&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I do not understand what additional parameters are to be included while running with GPU support to use it. I read about -ndiag, ntg, npool and other options on the internet but could not understand how to use them for my configuration.&#xA;I am totally new to parallelization and would be really grateful if someone could give more insight into using these options to use GPU in my calculations fully.&#xA;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2021-10-16T04:46:33.837" LastActivityDate="2021-10-16T15:54:38.250" Title="Command to run QE-GPU" Tags="|quantum-espresso|graphical-processing-unit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6830" PostTypeId="1" AcceptedAnswerId="6856" CreationDate="2021-10-02T10:00:46.810" Score="6" ViewCount="1072" Body="&lt;p&gt;As my question indicated, I would like to perform carrier (electron-hole) doping. Could you please guide to the right method using VASP ?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-10-08T08:19:10.703" Title="How to perform carrier-doping in VASP" Tags="|vasp|doping|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6831" PostTypeId="1" CreationDate="2021-10-02T10:04:31.983" Score="12" ViewCount="696" Body="&lt;p&gt;Why is that increasing the number of cores (openMP) in a computation does not decrease the duration of the process? Is it due to consecutive approximation?&lt;/p&gt;&#xA;&lt;p&gt;I took a very simple system of Cu in FCC lattice and did the self consistent field (SCF) calculations with increasing number of cores. If you see the plot, the duration of task (Wall Clock) is nearly same or increases slightly. I am using an ordinary laptop with Intel Core i5 8th Generation, which has 4 cores (8 logical). Compiler: gfortran with openMP.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wAcc6.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wAcc6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;No of Cores&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;CPU Clock (s)&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Wall Clock (s)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;010.17&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;10.34&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;2&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;019.01&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;09.80&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;3&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;028.17&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;09.72&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;4&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;035.59&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;09.20&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;5&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;047.85&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;09.97&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;6&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;055.19&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;09.51&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;7&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;085.91&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;12.65&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;8&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;109.32&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;14.34&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;" OwnerUserId="4352" LastActivityDate="2021-10-02T18:59:56.293" Title="Computational Speed vs multicores" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6832" PostTypeId="2" ParentId="6809" CreationDate="2021-10-02T10:19:18.290" Score="1" Body="&lt;p&gt;With the help of @Tyberius and @BrandonBocklund, I did the calculation of Cu in FCC lattice. Calculated lattice constant &lt;span class=&quot;math-container&quot;&gt;$a = 3.62613952 \, A^\circ$&lt;/span&gt;, where as experimental value is &lt;span class=&quot;math-container&quot;&gt;$a = 3.6149 \, A^\circ$&lt;/span&gt;. The major source of confusion is, I interpreted the question as FCC primitive cell has 4 Atoms.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'vc-relax' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '../../tmp' ,&#xA;                  pseudo_dir = '../../pseudo' ,&#xA;                      prefix = 'cu_fcc' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 7.1754,&#xA;                         nat = 1,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 40 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'methfessel-paxton' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA;                    conv_thr = 1d-8 ,&#xA;                 mixing_mode = 'plain' ,&#xA;                 mixing_beta = 0.7 ,&#xA; /&#xA; &amp;amp;IONS&#xA;                ion_dynamics = 'bfgs' ,&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA;                       press = 0 ,&#xA;              press_conv_thr = 0.5 ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Cu   63.55000  Cu.pbe-dn-rrkjus_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS alat &#xA;   Cu      0.000000000    0.000000000    0.000000000    &#xA;K_POINTS automatic &#xA;  8 8 8   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4352" LastActivityDate="2021-10-02T10:19:18.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6833" PostTypeId="2" ParentId="6817" CreationDate="2021-10-02T10:33:21.587" Score="4" Body="&lt;p&gt;The source of mistake is assuming one atom in the primitive cell of the hexagonal system. Actually there are two atoms, the atomic positions are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS {alat}&#xA;   Hf    0.000000000    0.000000000    0.000000000&#xA;   Hf    0.666666667    0.333333333    0.790000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4352" LastActivityDate="2021-10-02T10:33:21.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6834" PostTypeId="1" CreationDate="2021-10-02T10:45:53.857" Score="6" ViewCount="488" Body="&lt;p&gt;Why is my plot of 'Total Energy vs Energy cut off' is jagged. Previously ecutwfc was kept at 40, 60 and now 80. But still I am unable to figure why isn't it converging. Where as 'Total Energy vs K points' show convergent behavior.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'scf' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '../../tmp' ,&#xA;                  pseudo_dir = '../../pseudo' ,&#xA;                      prefix = 'Pt' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 7.5828,&#xA;                         nat = 1,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 80 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'mp' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Pt  195.07800  Pt.pbe-nd-rrkjus.UPF&#xA;ATOMIC_POSITIONS alat&#xA;   Pt    0.000000000    0.000000000    0.000000000&#xA;K_POINTS automatic&#xA;  8 8 8  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EPvGD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EPvGD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WVa6M.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WVa6M.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit 1:&lt;/strong&gt;&lt;br /&gt;&#xA;Changing 'ecutwfc' ranging between 6-40 in the intervals of 2 gives very good convergence.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why doesn't this happen in other plot where it ranges from 20-80 in the intervals of 1?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mC51Z.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mC51Z.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4352" LastEditorUserId="4352" LastEditDate="2021-10-02T12:44:29.763" LastActivityDate="2021-10-02T19:16:55.640" Title="Total Energy vs Energy Cut Off convergence" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|convergence-test|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6835" PostTypeId="1" CreationDate="2021-10-02T12:04:41.030" Score="8" ViewCount="785" Body="&lt;p&gt;I use the GROMACS software for MD simulations and I am trying to understand the calculation of viscosity using combinations of different ensembles and different methods.&lt;/p&gt;&#xA;&lt;p&gt;For a non-equilibrium MD calculation using periodic perturbation of external shear, which is the best ensemble that can be used? My values appear similar for NVT and NPT but vary by a large amount with NVE ensemble. I am assuming that NVE gives the best results because of no influence of thermostat and barostat and all of the change in energy is captured in calculation of viscosity. Is my reasoning appropriate?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2021-12-27T23:52:15.623" LastActivityDate="2021-12-29T13:05:32.627" Title="Viscosity calculation using molecular dynamics simulations" Tags="|molecular-dynamics|gromacs|physical-properties-of-materials|nonequilibrium|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6836" PostTypeId="2" ParentId="6831" CreationDate="2021-10-02T12:57:36.413" Score="8" Body="&lt;p&gt;I think that there should be three considerations (and of course I could be wrong).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;If you have not compiled the software to work in parallel, specifying multiple (N number of) threads sometimes is said to cause the same job to run in serial mode but N times.&lt;/li&gt;&#xA;&lt;li&gt;Even though you have a multi-core calculation, the actual work being done may not really need more than a single core. To check this, you can monitor the utilization of individual cores to ensure that they are being fully utilize during each calculation.&lt;/li&gt;&#xA;&lt;li&gt;No matter how fast your processor completes a calculation, if your memory is slow, that could be the bottleneck (although this is highly unlikely for a small number of atoms judging by the wall time for each calculation).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-02T12:57:36.413" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6837" PostTypeId="1" AcceptedAnswerId="6839" CreationDate="2021-10-02T17:25:48.777" Score="7" ViewCount="183" Body="&lt;p&gt;I am a rookie in the DFT calculation area, I found that I could often make mistakes when writing a new input file, so I'd like to ask if there is a tool for checking the syntax and consistency of these input files before I running the calculation on HPC? Or maybe some tools help me to generate these input files of INCAR, POSCAT, KPOINTS?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2021-10-06T04:34:51.553" Title="Check the syntax of the VASP input file before running" Tags="|density-functional-theory|vasp|high-performance-computing|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6838" PostTypeId="2" ParentId="6831" CreationDate="2021-10-02T18:59:56.293" Score="10" Body="&lt;p&gt;You don't give any real details on the system, but I can make a guess from your scaling that either the code doesn't properly support openmp (which is unlikely) or your system is way too small to see a benefit.  I suspect if you use a bigger system (that can't finish in about 10 seconds on a single core) you will see an improvement.&lt;/p&gt;&#xA;&lt;p&gt;Also keep in mind a practical consideration for using a laptop, you likely have other programs running in the background. This means using 100% of cores will always force some cores to be inactive for the calculation doing other things, slowing  things down.  An intel i5 8th gen will also probably have hyperthreading, so make sure you are using all of the cores not all of the threads.  Hyperthreading tends to be bad for these sorts of workloads and its normally disabled or not available on high end software.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-02T18:59:56.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6839" PostTypeId="2" ParentId="6837" CreationDate="2021-10-02T19:05:15.820" Score="6" Body="&lt;p&gt;To make Andrew Rosen's comment a full answer, &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/calculators/vasp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;you can use ASE to do this&lt;/a&gt;.  ASE will still let you do some stupid things if you ask it to, but it can make selecting paw potentials easier (setup=&amp;quot;materialsproject&amp;quot; for example will select potentials according to materials project, assuming you have the correct potentials available).  It also helps significantly for doing DFT+U since you can define a single dictionary to lookup element specific parameters.&lt;/p&gt;&#xA;&lt;p&gt;You can also use the GUI to setup your calculation and for spin polarized systems this can be very helpful.  You can define magnetic moments in the GUI visually, save as a &lt;code&gt;.traj&lt;/code&gt; file, load into ASE, and the spin polarization will be done automatically for you.  This is particularly helpful since the VASP syntax for it is easy to make mistakes with.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2021-10-03T06:17:15.540" LastActivityDate="2021-10-03T06:17:15.540" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6840" PostTypeId="2" ParentId="6834" CreationDate="2021-10-02T19:16:55.640" Score="2" Body="&lt;p&gt;The energy should be variational with regard to encut, but this is not something to expect for kpoints.  However, normally this results in the opposite of what you are observing with the kpoints showing some sort of oscillation.&lt;/p&gt;&#xA;&lt;p&gt;The result you see is due to numerical noise in the encut convergence calculations.  Try to tighten &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#etot_conv_thr&quot; rel=&quot;nofollow noreferrer&quot;&gt;the electronic cutoff&lt;/a&gt; and you will see less oscillation, however also keep in mind the scale of the graph.  You have an oscillation of about 0.005 Ry from 40 Ry - 60 Ry.  This is about 0.06 eV in terms I am more used to seeing. This seems like more than it should be.  This says to me that there might still be a problem, but this can be solved by raising the convergence.  However, you should never expect this behavior to totally go away.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-02T19:16:55.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6841" PostTypeId="1" CreationDate="2021-10-03T03:36:13.470" Score="9" ViewCount="383" Body="&lt;p&gt;A specific HESSIAN calculation carried out with GAMESS software presents this result:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* * * WARNING, MODE 7 HAS BEEN CHOSEN AS A VIBRATION&#xA;          WHILE MODE 1 IS ASSUMED TO BE A TRANSLATION/ROTATION.&#xA; PLEASE VERIFY THE PROGRAM'S DECISION MANUALLY!&#xA;&#xA;&#xA; MODES 1 TO 6 ARE TAKEN AS ROTATIONS AND TRANSLATIONS.&#xA;&#xA;     FREQUENCIES IN CM**-1, IR INTENSITIES IN DEBYE**2/AMU-ANGSTROM**2&#xA;&#xA;                        1          2         3         4         5         6         7           &#xA;       FREQUENCY:       0.04       0.02      0.05      2.43      2.74      4.22     14.57       &#xA;    REDUCED MASS:    7.89669    7.90996   7.90399   5.75740   5.67992   5.13823   4.53741&#xA;    IR INTENSITY:    0.00002    0.00000   0.00000   0.03626   0.01094   0.09661   0.22220&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;All frequencies have values greater than zero. However, 1, 2, and 3 frequencies are close to zero. Going the GAMESS recommendation, the frequencies were visualized with Chemcraft.&lt;/p&gt;&#xA;&lt;p&gt;In this verification:&#xA;MODES 1, 2, and 3 are TRANSLATIONS&#xA;MODES 4, 5, AND 6 are ROTATIONS&#xA;MODE 7 is a VIBRATION&lt;/p&gt;&#xA;&lt;p&gt;My questions are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is it an equilibrium geometry?&lt;/li&gt;&#xA;&lt;li&gt;Must it once again be optimized?&lt;/li&gt;&#xA;&lt;li&gt;Is it reliable the calculation?&lt;/li&gt;&#xA;&lt;li&gt;If this calculation is not realiable, how can this be corrected?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I will appreciate the answer.&lt;/p&gt;&#xA;" OwnerUserId="4382" OwnerDisplayName="rm_hdz" LastEditorUserId="1380" LastEditDate="2021-10-03T21:00:44.447" LastActivityDate="2021-10-09T14:34:01.197" Title="Vibrational frequencies results with GAMESS. Is it an equilibrium geometry?" Tags="|quantum-chemistry|computational-chemistry|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6842" PostTypeId="2" ParentId="6841" CreationDate="2021-10-03T14:21:32.420" Score="2" Body="&lt;p&gt;Your question is quite clear and on point, however it is a bit difficult to reply with the information you provided.&#xA;I have never used GAMESS myself, so I cannot help you with the specific commands.&#xA;I do not know on which molecules you are working, but it would be useful to know in order to reply.&lt;/p&gt;&#xA;&lt;p&gt;If the output is the eigenvalues of the Hessian matrix then either the structure is not optimized or there is some problem with the input.&lt;/p&gt;&#xA;&lt;p&gt;Since a molecule has 6 (5) degrees of freedom, in an minimum you expect 3N-6(5) non-zero values.&#xA;I assume you have a diatomic molecule, you would then expect 1 vibrational mode.&#xA;Since you have 7 positive eigenvalues your structure is clearly not in a minimum; not even in a saddle really.&lt;/p&gt;&#xA;&lt;p&gt;While the first three &lt;em&gt;could&lt;/em&gt; be related to floating point errors, the other three are clearly not zero.&#xA;This is not an equilibrium geometry and you should optimize it.&lt;/p&gt;&#xA;" OwnerUserId="4376" OwnerDisplayName="stanton63" LastEditorUserId="4376" LastEditDate="2021-10-03T16:02:33.117" LastActivityDate="2021-10-03T16:02:33.117" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6843" PostTypeId="2" ParentId="6841" CreationDate="2021-10-04T20:44:05.070" Score="7" Body="&lt;p&gt;You don't mention your molecule, which would help a lot. I'm trying to figure out how one gets 7 vibrational modes including translations and rotations... 3N will never equal 7, and 3N-5 = 7 would imply 3N = 12, so 4 atoms? If there was only one vibration, then it's a diatomic, but we'd only see 6 modes from 2 atoms.&lt;/p&gt;&#xA;&lt;p&gt;If you can mention what the molecule is, it will be much easier to answer the question.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;While it's a good sign that all the frequencies are positive, usually a geometry optimization shows that forces (gradients) are close to zero before calculating frequencies. So I'd rather see the &lt;em&gt;combination&lt;/em&gt; of:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;negligible forces&lt;/strong&gt; (GAMESS geometry optimization finished successfully)&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;positive frequencies&lt;/strong&gt; (Hessian doesn't show negative eigenvalues)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Did the first optimization complete successfully? GAMESS is usually conservative about declaring a completed optimization.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You could mean several things by &amp;quot;reliable.&amp;quot; For example, you don't indicate the method / functional / basis set you used to calculate the Hessian. I'd normally suggest something like this for a small molecule:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;RI-MP2&lt;/strong&gt; or modern DFT functional&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;def2-TZVPP&lt;/strong&gt; or larger basis set (or equivalent, e.g., jun-cc-pVTZ)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Moreover, for frequencies to be accurate, a full geometry optimization is needed first.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2021-10-09T14:34:01.197" LastActivityDate="2021-10-09T14:34:01.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6844" PostTypeId="1" AcceptedAnswerId="6845" CreationDate="2021-10-05T05:51:44.783" Score="8" ViewCount="293" Body="&lt;p&gt;The SIESTA DFT software provides to incorporate a &lt;a href=&quot;https://siesta-project.org/SIESTA_MATERIAL/Docs/Manuals/siesta-4.1.5.pdf#siesta-pos-78-kgrid.MonkhorstPack&quot; rel=&quot;noreferrer&quot;&gt;Monkhorst-Pack k grid&lt;/a&gt; in DFT calculations. However to use the results with the BoltzTraP2 software, a Gamma centered k-grid with uniform distribution is required. Has anyone had any experience with this kind of a problem for 1D and 2D systems?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-05T10:23:56.297" Title="Generating a Gamma centered uniform k mesh in SIESTA DFT" Tags="|density-functional-theory|k-points|siesta|brillouin-zone|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6845" PostTypeId="2" ParentId="6844" CreationDate="2021-10-05T06:44:27.690" Score="5" Body="&lt;p&gt;The siesta kgrid specification looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block kgrid.MonkhorstPack&#xA;  &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;offset&amp;gt;&#xA;  &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;offset&amp;gt;&#xA;  &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;int&amp;gt; &amp;lt;offset&amp;gt;&#xA;%endblock kgrid.MonkhorstPack&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; centered means is that the offsets are all &lt;span class=&quot;math-container&quot;&gt;$0.$&lt;/span&gt;.&lt;br /&gt;&#xA;For some systems it may be beneficial to use non-centered grids to reduce the total number of k-points due to symmetries. However, if BoltzTraP2 requires the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; centered variant, simply do as above and set &lt;code&gt;&amp;lt;offset&amp;gt;&lt;/code&gt; to &lt;span class=&quot;math-container&quot;&gt;$0.$&lt;/span&gt; for each direction.&lt;/p&gt;&#xA;&lt;p&gt;Here an example with &lt;code&gt;NA, NB, NC&lt;/code&gt; being the number of k-points along each reciprocal lattice vector:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block kgrid.MonkhorstPack&#xA;  NA 0 0 0.&#xA;  0 NB 0 0.&#xA;  0 0 NC 0.&#xA;%endblock kgrid.MonkhorstPack&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For details related to their meaning see &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2238/887&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-10-05T07:53:10.400" LastActivityDate="2021-10-05T07:53:10.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6847" PostTypeId="2" ParentId="6797" CreationDate="2021-10-05T18:20:29.873" Score="5" Body="&lt;p&gt;Another option is &lt;a href=&quot;https://www.c2x.org.uk&quot; rel=&quot;nofollow noreferrer&quot;&gt;c2x&lt;/a&gt; which supports both Siesta and Vasp, amongst others, and has Mac binaries for download. [Declaration of interest: I wrote c2x.]&lt;/p&gt;&#xA;&lt;p&gt;c2x --fdf POSCAR out.fdf&lt;/p&gt;&#xA;&lt;p&gt;etc. Converting from xyz is trickier, due to different conventions about if/where to put the unit cell parameter, required by Siesta, in an xyz file. C2x attempts to support the common conventions.&lt;/p&gt;&#xA;" OwnerUserId="4384" LastEditorUserId="4384" LastEditDate="2021-10-06T19:52:29.563" LastActivityDate="2021-10-06T19:52:29.563" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6848" PostTypeId="2" ParentId="6837" CreationDate="2021-10-06T04:34:51.553" Score="4" Body="&lt;p&gt;Just putting another software that can be used to develop all the input files such as INCAR, POSCAR, KPOINTS and POTCAR from a CIF file, is pymatgen. &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pymatgen.org/&lt;/a&gt;. It is a python based software toolkit that can help you not only with the input files but also analyzing the output files from vasp. This software is being used in the development of the materials project. They have a lot of tutorials online to output the vasp input files. &lt;a href=&quot;https://pymatgen.org/pymatgen.io.vasp.inputs.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pymatgen.org/pymatgen.io.vasp.inputs.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2021-10-06T04:34:51.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6849" PostTypeId="1" CreationDate="2021-10-06T07:40:08.457" Score="8" ViewCount="928" Body="&lt;p&gt;I made auto optimization working by installing openbabel using &lt;code&gt;sudo apt install openbabel&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is there any way to make Gaussian extension working by doing something?&lt;/p&gt;&#xA;&lt;p&gt;I've the &lt;code&gt;avogenerators&lt;/code&gt; scripts in &lt;code&gt;/home/jupiter/.local/share/OpenChemistry/Avogadro/inputGenerators/OpenChemistry-avogenerators-eddfee4&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Please help me to generate input file for gaussian, ASAP.&#xA;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="4387" LastEditorUserId="24" LastEditDate="2021-10-06T12:31:56.963" LastActivityDate="2021-10-06T12:31:56.963" Title="How to generate a input file for gaussian in Avogadro 2?" Tags="|density-functional-theory|computational-chemistry|gaussian|avogadro|" AnswerCount="1" CommentCount="2" ClosedDate="2021-11-05T22:38:04.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="6850" PostTypeId="1" CreationDate="2021-10-06T09:44:10.990" Score="6" ViewCount="498" Body="&lt;p&gt;I have a multi model pdb file and would like to extract the last frame or any other frame from it.&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2021-10-18T15:07:16.327" Title="How to extract specific frames/model from a multi model pdb file?" Tags="|proteins|pdb|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6851" PostTypeId="2" ParentId="6850" CreationDate="2021-10-06T12:10:16.207" Score="3" Body="&lt;p&gt;You can use the Python script &lt;em&gt;multiple_model_PDB_file_splitter&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# multiple_model_PDB_file_splitter.py by Wayne Decatur&#xA;# ver 0.2&#xA;#&#xA;#*******************************************************************************&#xA;## PURPOSE: Takes a formatted pdb file with multiple models and splits each model&#xA;# into individual files. Requires the PDB file include both MODEL and ENDMDL&#xA;&#xA;&#xA;# records for each of the models.&#xA;&#xA;# Originally developed in Python 2.7, but confirmed to work in Python 3.6.&#xA;#&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can download it from &lt;a href=&quot;https://github.com/fomightez/structurework/blob/master/python_scripts/multiple_model_PDB_file_splitter.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Other useful script from the same author can be download &lt;a href=&quot;https://proteopedia.org/wiki/index.php/User:Wayne_Decatur/Code_for_Molecular_Structure_and_Visualization_Work&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-10-06T12:51:24.977" LastActivityDate="2021-10-06T12:51:24.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6852" PostTypeId="2" ParentId="6849" CreationDate="2021-10-06T12:21:39.447" Score="5" Body="&lt;p&gt;You can use OpenBabel directly to obtain the Gaussian input from command line.&lt;/p&gt;&#xA;&lt;p&gt;OpenBabel supports two types of Gaussian input generation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Gaussian 98/03 Cartesian Input&lt;/li&gt;&#xA;&lt;li&gt;Gaussian Z-matrix Input&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To run OpenBabel:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel [-i&amp;lt;input-type&amp;gt;] &amp;lt;infilename&amp;gt; [-o&amp;lt;output-type&amp;gt;] -O&amp;lt;outfilename&amp;gt; [Options]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Take a look at &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4738/24&quot;&gt;this&lt;/a&gt; answer for information about all the formats OpenBabel work with.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-06T12:21:39.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6853" PostTypeId="1" AcceptedAnswerId="7172" CreationDate="2021-10-06T15:21:56.330" Score="7" ViewCount="219" Body="&lt;p&gt;I have come across the &lt;a href=&quot;https://icme.hpc.msstate.edu/mediawiki/index.php/MPC.html&quot; rel=&quot;noreferrer&quot;&gt;MEAM Parameter Calibration toolkit&lt;/a&gt; (link leads to Wiki, video tutorials, and download link for the package) for fitting your own MEAM potentials [1].&lt;/p&gt;&#xA;&lt;p&gt;Is this the best software out there for the job? Or is there another way of creating/ fitting your own MEAM potentials?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Barrett, C.D., Carino, R.L. The MEAM parameter calibration tool: an explicit methodology for hierarchical bridging between ab initio and atomistic scales. Integr Mater Manuf Innov 5, 177–191 (2016). &lt;a href=&quot;https://doi.org/10.1186/s40192-016-0051-6&quot; rel=&quot;noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="7" LastEditDate="2021-10-06T17:37:22.103" LastActivityDate="2021-11-29T19:09:47.203" Title="How Do you Produce your own MEAM Potentials?" Tags="|molecular-dynamics|ab-initio-calculations|interatomic-potentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6854" PostTypeId="2" ParentId="6850" CreationDate="2021-10-06T22:32:14.417" Score="6" Body="&lt;p&gt;Do you have access to &lt;a href=&quot;https://github.com/openbabel/openbabel&quot; rel=&quot;noreferrer&quot;&gt;OpenBabel&lt;/a&gt; to run from the terminal?&lt;/p&gt;&#xA;&lt;p&gt;For the purpose of demonstration, the example following is demonstrated on a file listing SMILES strings.  However, &lt;em&gt;the concept&lt;/em&gt; may be applied on a &lt;code&gt;.pdb&lt;/code&gt; with multiple models (and equally works well enough on multi-model &lt;code&gt;.sdf&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The input file &lt;code&gt;input.smi&lt;/code&gt; is a small set of aromatics.  SMILES strings and labels are tabulator separated:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;c1ccccc1    Compound 1&#xA;c1(cc(cc(c1)C)C)C   Compound 2&#xA;c1(ccc(cc1)C)C  Compound 3&#xA;c1(ccccc1)C Compound 4&#xA;n1ccccc1    Compound 5&#xA;n1cnccc1    Compound 6&#xA;n1cncnc1    Compound 7&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My interest is on the &lt;em&gt;p&lt;/em&gt;-xylene only (i.e., &lt;code&gt;Compound 3&lt;/code&gt;).  With the instruction&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;obabel -ismi input.smi -f 3 -l 3 -osmi -O interest.smi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;OpenBabel anticipates the input file to contain SMILES (&lt;code&gt;-ismi&lt;/code&gt;), starts processing with the third model entry onward (&lt;code&gt;-f 3&lt;/code&gt;, line/model counting index in the file starts by &lt;code&gt;1&lt;/code&gt;), accessing all entries up &lt;em&gt;and including&lt;/em&gt; the third one (&lt;code&gt;-l 3&lt;/code&gt;) in this file.  The output, to contain SMILES and their labels (if present) is formatted (&lt;code&gt;-osmi&lt;/code&gt;) and written permanently (&lt;code&gt;-O&lt;/code&gt;) into file &lt;code&gt;interest.smi&lt;/code&gt; which eventually contains&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt; c1(ccc(cc1)C)C  Compound 3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since OpenBabel &lt;em&gt;run from CLI&lt;/em&gt; is agnostic about file extensions, your processing of &lt;code&gt;.pdb&lt;/code&gt; to be read, and to be written requires an adjustment of the input/output parameters e.g., in the pattern of&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;obabel -ipdb input.pdb -f 3 -l 3 -opdb -O interest.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;This approach equally allows to extract &lt;em&gt;a contiguous set&lt;/em&gt; of entries, e.g.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;obabel -ismi input.smi -f3 -l5 -osmi -O interest.smi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to process 3 molecules at once.  The toggles &lt;code&gt;-f&lt;/code&gt; and &lt;code&gt;-l&lt;/code&gt; may be used independently of each other, and spaces between them and their then mandatory integer parameters may be omitted.  The approach however is unable to pick a set molecules in the mixed pattern like &lt;code&gt;(1, 3-5, 7)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Said selection may be achieve from &lt;code&gt;obgui&lt;/code&gt;, too:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/koBri.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/koBri.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="1206" LastEditDate="2021-10-07T07:14:26.890" LastActivityDate="2021-10-07T07:14:26.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6855" PostTypeId="1" CreationDate="2021-10-06T22:33:21.023" Score="6" ViewCount="158" Body="&lt;p&gt;For Bloch electrons, the Berry connection is defined as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathcal{A}_n(\mathbf{k}) = i\langle u_{n\mathbf{k}}|\partial_\mathbf{k}|u_{n\mathbf{k}}\rangle \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$u_{n\mathbf{k}}$&lt;/span&gt; is the cell-periodic part of the Bloch function with band index &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and crystal momentum &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;. Now, I'd like to evaluate the difference &lt;span class=&quot;math-container&quot;&gt;$\mathcal{A}_n(\mathbf{k})-\mathcal{A}_m(\mathbf{k})$&lt;/span&gt;, where the empty bands are also included. Although the Berry connection itself is Gauge dependent, the difference should be Gauge invariant due to the arbitrary phase term cancellation. As far as I know, Wannier90 could evaluate it. However, the wannierization for empty entangled bands is less efficient. Apart from Wannier90, is there any other DFT (say, VASP, QE) post processing scripts or codes that have the ability?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2021-10-13T13:30:22.337" LastActivityDate="2021-10-13T13:30:22.337" Title="How to calculate the Berry connection difference?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6856" PostTypeId="2" ParentId="6830" CreationDate="2021-10-07T07:10:54.677" Score="7" Body="&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/NELECT&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;NELECT&lt;/code&gt; tag&lt;/a&gt; should do the trick. A number that's larger than the default value (which is automatically calculated by VASP to be the number of valence electrons in the system) gives you charge doping and a real number that's lower than the default value gives you hole doping.&lt;/p&gt;&#xA;&lt;p&gt;Note that one doesn't necessarily needs to do a normal calculation to know the default &lt;code&gt;NELECT&lt;/code&gt; value. It can be calculated manually by checking the number of valence electrons for each element in the &lt;code&gt;POTCAR&lt;/code&gt; file and multiply that number of electrons with the number of corresponding atoms in the &lt;code&gt;POSCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Carrier concentration can be calculated by calculate the number of carrier you added/substracted (call it &lt;span class=&quot;math-container&quot;&gt;$\Delta N_\text{elect}$&lt;/span&gt;) divided by the volume of the unit cell (&lt;span class=&quot;math-container&quot;&gt;$V_\text{cell}$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="1804" LastEditorUserId="1804" LastEditDate="2021-10-08T08:19:10.703" LastActivityDate="2021-10-08T08:19:10.703" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6857" PostTypeId="1" CreationDate="2021-10-07T20:09:25.320" Score="8" ViewCount="79" Body="&lt;p&gt;What's the point of using extremely denser k-grid for extracting curvature effective masses? I saw in some publications that they use extremely dense k-grid for band structure calculations for reliable effective masses. However, in some publications they just extract effective masses from a band structure that determined with relatively coarse k-grid. I could not find so many information about effective mass convergence. Is it something really reliable? Thanks for your comments&lt;/p&gt;&#xA;" OwnerUserId="4389" LastEditorUserId="5" LastEditDate="2021-10-07T20:21:06.843" LastActivityDate="2021-10-10T13:55:54.227" Title="Effective mass convergence" Tags="|density-functional-theory|band-structure|effective-mass|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6858" PostTypeId="1" AcceptedAnswerId="6861" CreationDate="2021-10-08T02:16:25.233" Score="14" ViewCount="768" Body="&lt;p&gt;How do computer simulations of liquid hydrogen-bonding systems incorporate hydrogen bonding? Since I think hydrogen bonding has mixed covalent and electrostatic character, wouldn't you need something beyond a classical force field? Yet, for example, simulations of water using a simple classical model like spc/e reproduce the structure, including the tetrahedral coordination.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastActivityDate="2021-10-28T14:33:34.200" Title="How do you incorporate hydrogen bonding into molecular simulations?" Tags="|molecular-dynamics|monte-carlo|intermolecular-forces|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6859" PostTypeId="1" AcceptedAnswerId="9656" CreationDate="2021-10-08T05:29:05.587" Score="9" ViewCount="881" Body="&lt;p&gt;I am trying to run GPU enabled QE (QE 6.8 running on Ubuntu 18.04.5 LTS (GNU/Linux 4.15.0-135-generic x86_64) System Configuration: Processor: Intel Xeon Gold 5120 CPU 2.20 GHz (2 Processor) RAM: 96 GB HDD: 6 TB Graphics Card: NVIDIA Quadro P5000 (16 GB))&lt;/p&gt;&#xA;&lt;p&gt;I am successfully able to run small jobs (with dynamical ram ~1GB). However, when going to even larger systems (less than 16GB), the output abruptly stops during the first iteration(attached below)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program PWSCF v.6.8 starts on  8Oct2021 at 10:33: 9 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI &amp;amp; OpenMP), running on     784 processor cores&#xA;     Number of MPI processes:                28&#xA;     Threads/MPI process:                    28&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     R &amp;amp; G space division:  proc/nbgrp/npool/nimage =      28&#xA;     43440 MiB available memory on the printing compute node when the environment starts&#xA; &#xA;     Reading input from 001.in&#xA;Warning: card &amp;amp;CELL ignored&#xA;Warning: card / ignored&#xA;&#xA;     Current dimensions of program PWSCF are:&#xA;     Max number of different atomic species (ntypx) = 10&#xA;     Max number of k-points (npk) =  40000&#xA;     Max angular momentum in pseudopotentials (lmaxx) =  4&#xA;     file Ti.pbe-spn-rrkjus_psl.1.0.0.upf: wavefunction(s)  3S 3D renormalized&#xA;&#xA;     gamma-point specific algorithms are used&#xA;     Found symmetry operation: I + ( -0.0000 -0.5000  0.0000)&#xA;     This is a supercell, fractional translations are disabled&#xA;&#xA;     Subspace diagonalization in iterative solution of the eigenvalue problem:&#xA;     a serial algorithm will be used&#xA;&#xA; &#xA;     Parallelization info&#xA;     --------------------&#xA;     sticks:   dense  smooth     PW     G-vecs:    dense   smooth      PW&#xA;     Min         637     232     57                81572    18102    2258&#xA;     Max         640     234     60                81588    18118    2266&#xA;     Sum       17865    6549   1633              2284245   507201   63345&#xA; &#xA;     Using Slab Decomposition&#xA; &#xA;&#xA;&#xA;     bravais-lattice index     =           14&#xA;     lattice parameter (alat)  =      21.0379  a.u.&#xA;     unit-cell volume          =    9204.2807 (a.u.)^3&#xA;     number of atoms/cell      =           36&#xA;     number of atomic types    =            2&#xA;     number of electrons       =       288.00&#xA;     number of Kohn-Sham states=          173&#xA;     kinetic-energy cutoff     =      55.0000  Ry&#xA;     charge density cutoff     =     600.0000  Ry&#xA;     scf convergence threshold =      1.0E-06&#xA;     mixing beta               =       0.4000&#xA;     number of iterations used =            8  local-TF  mixing&#xA;     energy convergence thresh.=      1.0E-04&#xA;     force convergence thresh. =      1.0E-03&#xA;     Exchange-correlation= PBE&#xA;                           (   1   4   3   4   0   0   0)&#xA;     nstep                     =          500&#xA;&#xA;&#xA;     GPU acceleration is ACTIVE.&#xA;&#xA;     Message from routine print_cuda_info:&#xA;     High GPU oversubscription detected. Are you sure this is what you want?&#xA;&#xA;     GPU used by master process:&#xA;&#xA;        Device Number: 0&#xA;        Device name: Quadro P5000&#xA;        Compute capability : 61&#xA;        Ratio of single to double precision performance  : 32&#xA;        Memory Clock Rate (KHz): 4513000&#xA;        Memory Bus Width (bits): 256&#xA;        Peak Memory Bandwidth (GB/s): 288.83&#xA;&#xA;     celldm(1)=  21.037943  celldm(2)=   1.000000  celldm(3)=   2.419041&#xA;     celldm(4)=  -0.766650  celldm(5)=  -0.766650  celldm(6)=   0.533303&#xA;&#xA;     crystal axes: (cart. coord. in units of alat)&#xA;               a(1) = (   1.000000   0.000000   0.000000 )  &#xA;               a(2) = (   0.533303   0.845924   0.000000 )  &#xA;               a(3) = (  -1.854558  -1.023161   1.168553 )  &#xA;&#xA;     reciprocal axes: (cart. coord. in units 2 pi/alat)&#xA;               b(1) = (  1.000000 -0.630438  1.035056 )  &#xA;               b(2) = ( -0.000000  1.182139  1.035056 )  &#xA;               b(3) = (  0.000000  0.000000  0.855759 )  &#xA;&#xA;&#xA;     PseudoPot. # 1 for Ti read from file:&#xA;     ../Ti.pbe-spn-rrkjus_psl.1.0.0.upf&#xA;     MD5 check sum: e281089c08e14b8efcf92e44a67ada65&#xA;     Pseudo is Ultrasoft + core correction, Zval = 12.0&#xA;     Generated using &amp;amp;quot;atomic&amp;amp;quot; code by A. Dal Corso  v.6.2.2&#xA;     Using radial grid of 1177 points,  6 beta functions with: &#xA;                l(1) =   0&#xA;                l(2) =   0&#xA;                l(3) =   1&#xA;                l(4) =   1&#xA;                l(5) =   2&#xA;                l(6) =   2&#xA;     Q(r) pseudized with 0 coefficients &#xA;&#xA;&#xA;     PseudoPot. # 2 for O  read from file:&#xA;     ../O.pbe-n-rrkjus_psl.1.0.0.upf&#xA;     MD5 check sum: 91400c9766925bcf19f520983a725ff0&#xA;     Pseudo is Ultrasoft + core correction, Zval =  6.0&#xA;     Generated using &amp;amp;quot;atomic&amp;amp;quot; code by A. Dal Corso  v.6.3MaX&#xA;     Using radial grid of 1095 points,  4 beta functions with: &#xA;                l(1) =   0&#xA;                l(2) =   0&#xA;                l(3) =   1&#xA;                l(4) =   1&#xA;     Q(r) pseudized with 0 coefficients &#xA;&#xA;&#xA;     atomic species   valence    mass     pseudopotential&#xA;        Ti            12.00    47.86700     Ti( 1.00)&#xA;        O              6.00    15.99940     O ( 1.00)&#xA;&#xA;     Starting magnetic structure &#xA;     atomic species   magnetization&#xA;        Ti           0.200&#xA;        O            0.000&#xA;&#xA;     No symmetry found&#xA;&#xA;&#xA;                                    s                        frac. trans.&#xA;&#xA;      isym =  1     identity                                     &#xA;&#xA; cryst.   s( 1) = (     1          0          0      )&#xA;                  (     0          1          0      )&#xA;                  (     0          0          1      )&#xA;&#xA; cart.    s( 1) = (  1.0000000  0.0000000  0.0000000 )&#xA;                  (  0.0000000  1.0000000  0.0000000 )&#xA;                  (  0.0000000  0.0000000  1.0000000 )&#xA;&#xA;&#xA;     point group C_1 (1)    &#xA;     there are  1 classes&#xA;     the character table:&#xA;&#xA;       E    &#xA;A      1.00&#xA;&#xA;     the symmetry operations in each class and the name of the first element:&#xA;&#xA;     E        1&#xA;          identity                                               &#xA;&#xA;   Cartesian axes&#xA;&#xA;     site n.     atom                  positions (alat units)&#xA;         1           O   tau(   1) = (  -0.8353365  -0.5987815   0.7050395  )&#xA;         2           Ti  tau(   2) = (  -0.6772809  -0.5115821   0.7050395  )&#xA;         3           O   tau(   3) = (  -0.5192254  -0.4243827   0.7050395  )&#xA;         4           Ti  tau(   4) = (  -0.9272815  -0.5115821   0.5842738  )&#xA;         5           O   tau(   5) = (  -0.7692260  -0.4243827   0.5842738  )&#xA;         6           O   tau(   6) = (  -0.3186838  -0.1758181   0.5842738  )&#xA;         7           O   tau(   7) = (  -0.4520098  -0.3872999   0.4635080  )&#xA;         8           Ti  tau(   8) = (  -0.2939543  -0.3001004   0.4635080  )&#xA;         9           O   tau(   9) = (  -0.1358987  -0.2129011   0.4635080  )&#xA;        10           O   tau(  10) = (  -0.5686844  -0.1758181   0.7050395  )&#xA;        11           Ti  tau(  11) = (  -0.4106289  -0.0886188   0.7050395  )&#xA;        12           O   tau(  12) = (  -0.2525734  -0.0014194   0.7050395  )&#xA;        13           Ti  tau(  13) = (  -0.6606296  -0.0886188   0.5842738  )&#xA;        14           O   tau(  14) = (  -0.5025740  -0.0014194   0.5842738  )&#xA;        15           O   tau(  15) = (  -0.0520318   0.2471452   0.5842738  )&#xA;        16           O   tau(  16) = (  -0.1853578   0.0356635   0.4635080  )&#xA;        17           Ti  tau(  17) = (  -0.0273023   0.1228629   0.4635080  )&#xA;        18           O   tau(  18) = (   0.1307533   0.2100623   0.4635080  )&#xA;        19           O   tau(  19) = (  -0.3353351  -0.5987815   0.7050395  )&#xA;        20           Ti  tau(  20) = (  -0.1772797  -0.5115821   0.7050395  )&#xA;        21           O   tau(  21) = (  -0.0192241  -0.4243827   0.7050395  )&#xA;        22           Ti  tau(  22) = (  -0.4272803  -0.5115821   0.5842738  )&#xA;        23           O   tau(  23) = (  -0.2692247  -0.4243827   0.5842738  )&#xA;        24           O   tau(  24) = (   0.1813175  -0.1758181   0.5842738  )&#xA;        25           O   tau(  25) = (   0.0479915  -0.3872999   0.4635080  )&#xA;        26           Ti  tau(  26) = (   0.2060470  -0.3001004   0.4635080  )&#xA;        27           O   tau(  27) = (   0.3641026  -0.2129011   0.4635080  )&#xA;        28           O   tau(  28) = (  -0.0686832  -0.1758181   0.7050395  )&#xA;        29           Ti  tau(  29) = (   0.0893724  -0.0886188   0.7050395  )&#xA;        30           O   tau(  30) = (   0.2474280  -0.0014194   0.7050395  )&#xA;        31           Ti  tau(  31) = (  -0.1606282  -0.0886188   0.5842738  )&#xA;        32           O   tau(  32) = (  -0.0025728  -0.0014194   0.5842738  )&#xA;        33           O   tau(  33) = (   0.4479695   0.2471452   0.5842738  )&#xA;        34           O   tau(  34) = (   0.3146435   0.0356635   0.4635080  )&#xA;        35           Ti  tau(  35) = (   0.4726991   0.1228629   0.4635080  )&#xA;        36           O   tau(  36) = (   0.6307546   0.2100623   0.4635080  )&#xA;&#xA;   Crystallographic axes&#xA;&#xA;     site n.     atom                  positions (cryst. coord.)&#xA;         1           O   tau(   1) = (  0.2719137  0.0219125  0.6033439  )&#xA;         2           Ti  tau(   2) = (  0.3749954  0.1249943  0.6033439  )&#xA;         3           O   tau(   3) = (  0.4780771  0.2280761  0.6033439  )&#xA;         4           Ti  tau(   4) = ( -0.0000046 -0.0000050  0.4999975  )&#xA;         5           O   tau(   5) = (  0.1030772  0.1030768  0.4999975  )&#xA;         6           O   tau(   6) = (  0.3969147  0.3969146  0.4999975  )&#xA;         7           O   tau(   7) = (  0.2719156  0.0219145  0.3966511  )&#xA;         8           Ti  tau(   8) = (  0.3749973  0.1249964  0.3966511  )&#xA;         9           O   tau(   9) = (  0.4780790  0.2280781  0.3966511  )&#xA;        10           O   tau(  10) = (  0.2719134  0.5219140  0.6033439  )&#xA;        11           Ti  tau(  11) = (  0.3749952  0.6249957  0.6033439  )&#xA;        12           O   tau(  12) = (  0.4780769  0.7280775  0.6033439  )&#xA;        13           Ti  tau(  13) = ( -0.0000048  0.4999964  0.4999975  )&#xA;        14           O   tau(  14) = (  0.1030769  0.6030781  0.4999975  )&#xA;        15           O   tau(  15) = (  0.3969145  0.8969160  0.4999975  )&#xA;        16           O   tau(  16) = (  0.2719153  0.5219160  0.3966511  )&#xA;        17           Ti  tau(  17) = (  0.3749970  0.6249978  0.3966511  )&#xA;        18           O   tau(  18) = (  0.4780787  0.7280796  0.3966511  )&#xA;        19           O   tau(  19) = (  0.7719150  0.0219125  0.6033439  )&#xA;        20           Ti  tau(  20) = (  0.8749966  0.1249943  0.6033439  )&#xA;        21           O   tau(  21) = (  0.9780784  0.2280761  0.6033439  )&#xA;        22           Ti  tau(  22) = (  0.4999967 -0.0000050  0.4999975  )&#xA;        23           O   tau(  23) = (  0.6030784  0.1030768  0.4999975  )&#xA;        24           O   tau(  24) = (  0.8969160  0.3969146  0.4999975  )&#xA;        25           O   tau(  25) = (  0.7719169  0.0219145  0.3966511  )&#xA;        26           Ti  tau(  26) = (  0.8749985  0.1249964  0.3966511  )&#xA;        27           O   tau(  27) = (  0.9780803  0.2280781  0.3966511  )&#xA;        28           O   tau(  28) = (  0.7719147  0.5219140  0.6033439  )&#xA;        29           Ti  tau(  29) = (  0.8749965  0.6249957  0.6033439  )&#xA;        30           O   tau(  30) = (  0.9780782  0.7280775  0.6033439  )&#xA;        31           Ti  tau(  31) = (  0.4999965  0.4999964  0.4999975  )&#xA;        32           O   tau(  32) = (  0.6030782  0.6030781  0.4999975  )&#xA;        33           O   tau(  33) = (  0.8969158  0.8969160  0.4999975  )&#xA;        34           O   tau(  34) = (  0.7719166  0.5219160  0.3966511  )&#xA;        35           Ti  tau(  35) = (  0.8749983  0.6249978  0.3966511  )&#xA;        36           O   tau(  36) = (  0.9780801  0.7280796  0.3966511  )&#xA;&#xA;     number of k points=     1  Gaussian smearing, width (Ry)=  0.0100&#xA;                       cart. coord. in units 2pi/alat&#xA;        k(    1) = (   0.0000000   0.0000000   0.0000000), wk =   1.0000000&#xA;&#xA;                       cryst. coord.&#xA;        k(    1) = (   0.0000000   0.0000000   0.0000000), wk =   1.0000000&#xA;&#xA;     Dense  grid:  1142123 G-vectors     FFT dimensions: ( 180, 180, 400)&#xA;&#xA;     Smooth grid:   253601 G-vectors     FFT dimensions: ( 100, 100, 243)&#xA;&#xA;     Dynamical RAM for                 wfc:       2.99 MB&#xA;&#xA;     Dynamical RAM for     wfc (w. buffer):       2.99 MB&#xA;&#xA;     Dynamical RAM for           str. fact:       1.24 MB&#xA;&#xA;     Dynamical RAM for           local pot:       0.00 MB&#xA;&#xA;     Dynamical RAM for          nlocal pot:       7.05 MB&#xA;&#xA;     Dynamical RAM for                qrad:       3.93 MB&#xA;&#xA;     Dynamical RAM for          rho,v,vnew:      25.98 MB&#xA;&#xA;     Dynamical RAM for               rhoin:       8.66 MB&#xA;&#xA;     Dynamical RAM for           G-vectors:       2.40 MB&#xA;&#xA;     Dynamical RAM for          h,s,v(r/c):       2.74 MB&#xA;&#xA;     Dynamical RAM for          &amp;lt;psi|beta&amp;gt;:       0.54 MB&#xA;&#xA;     Dynamical RAM for                 psi:       5.98 MB&#xA;&#xA;     Dynamical RAM for                hpsi:       5.98 MB&#xA;&#xA;     Dynamical RAM for                spsi:       5.98 MB&#xA;&#xA;     Dynamical RAM for      wfcinit/wfcrot:       8.53 MB&#xA;&#xA;     Dynamical RAM for           addusdens:     131.34 MB&#xA;&#xA;     Dynamical RAM for          addusforce:     160.16 MB&#xA;&#xA;     Estimated static dynamical RAM per process &amp;gt;      76.37 MB&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;     236.53 MB&#xA;&#xA;     Estimated total dynamical RAM &amp;gt;       6.47 GB&#xA;&#xA;     Check: negative core charge=   -0.000001&#xA;     Generating pointlists ...&#xA;     new r_m :   0.0722 (alat units)  1.5191 (a.u.) for type    1&#xA;     new r_m :   0.0722 (alat units)  1.5191 (a.u.) for type    2&#xA;&#xA;     Initial potential from superposition of free atoms&#xA;&#xA;     starting charge  287.98222, renormalised to  288.00000&#xA;&#xA;     negative rho (up, down):  9.119E-05 6.477E-05&#xA;     Starting wfcs are  216 randomized atomic wfcs&#xA;&#xA;     total cpu time spent up to now is       14.0 secs&#xA;&#xA;     Self-consistent Calculation&#xA;[tb_dev] Currently allocated     2.23E+01 Mbytes, locked:    0 /   9&#xA;[tb_pin] Currently allocated     0.00E+00 Mbytes, locked:    0 /   0&#xA;&#xA;     iteration #  1     ecut=    55.00 Ry     beta= 0.40&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;           980 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         32000 MiB available memory on the node where the printing process lives&#xA;     GPU memory used/free/total (MiB): 11117 / 5152 / 16270&#xA;------------------&#xA;     ethr =  1.00E-02,  avg # of iterations =  1.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The CRASH file generated says&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        24&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        14&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         5&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         7&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        15&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        17&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        10&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         9&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        12&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         4&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        13&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #        19&#xA;     from  addusdens_gpu  : error #         1&#xA;      cannot allocate aux2_d &#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using -ndiag 1 and -ntg1 with pw.x also gave a similar output with the following additional lines&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     negative rho (up, down):  9.119E-05 6.477E-05&#xA;     Starting wfcs are  216 randomized atomic wfcs&#xA;&#xA;     total cpu time spent up to now is       11.9 secs&#xA;&#xA;     Self-consistent Calculation&#xA;[tb_dev] Currently allocated     3.21E+01 Mbytes, locked:    0 /   9&#xA;[tb_pin] Currently allocated     0.00E+00 Mbytes, locked:    0 /   0&#xA;&#xA;     iteration #  1     ecut=    55.00 Ry     beta= 0.40&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;          1036 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         36041 MiB available memory on the node where the printing process lives&#xA;     GPU memory used/free/total (MiB): 8915 / 7354 / 16270&#xA;------------------&#xA;     ethr =  1.00E-02,  avg # of iterations =  1.5&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156244752 bytes requested; status = 2(out of memory)&#xA;0: ALLOCATE: 156239280 bytes requested; status = 2(out of memory)&#xA;--------------------------------------------------------------------------&#xA;Primary job  terminated normally, but 1 process returned&#xA;a non-zero exit code. Per user-direction, the job has been aborted.&#xA;--------------------------------------------------------------------------&#xA;--------------------------------------------------------------------------&#xA;mpirun detected that one or more processes exited with non-zero status, thus causing&#xA;the job to be terminated. The first process to do so was:&#xA;&#xA;  Process name: [[58344,1],12]&#xA;  Exit code:    127&#xA;--------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I believe I am not &amp;quot;filling the CPUs with OpenMP threads&amp;quot;, or running 1 MPI on 1 GPU, as suggested in this &lt;a href=&quot;https://gitlab.com/QEF/material-for-ljubljana-qe-summer-school/-/blob/master/Day-5/slides/Hands-on.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;document.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can someone please give some suggestions? Sorry for the long post. I am totally new to this field. Any help would be appreciated. Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2022-01-14T01:53:53.503" LastActivityDate="2022-09-14T01:02:26.617" Title="How to &quot;Fill the CPU with OpenMP threads&quot; to run QE-GPU" Tags="|quantum-espresso|high-performance-computing|graphical-processing-unit|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6860" PostTypeId="2" ParentId="6858" CreationDate="2021-10-08T07:49:01.980" Score="14" Body="&lt;p&gt;The short answer is that, while hydrogen bonds do have some covalent character, you can mimic that covalent character by increasing the electrostatic term. For example you can specify point charges to the oxygen and hydrogen atoms that are larger than they would otherwise be, and the overestimated electrostatic attraction will compensate for the neglect of covalent character. Water models are usually fitted against experimentally observable quantities, such as heat of vaporization, radial correlation function, dimerization energy, and so on, rather than against the ab initio electrostatic, polarization, Pauli repulsion, dispersion and covalent contributions to the energy, so if the model neglects a term, the other terms must be absorbing the resulting error.&lt;/p&gt;&#xA;&lt;p&gt;Besides, the tetrahedral coordination structure of water (or more accurately speaking, ice) does not require the description of the covalent part of the hydrogen bond. Even with a purely electrostatic description of water molecules, the oxygen atoms will still be tetrahedral (just with somewhat inaccurate hydrogen bond lengths), due to angular repulsion effects.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-10-08T07:49:01.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6861" PostTypeId="2" ParentId="6858" CreationDate="2021-10-08T21:52:35.107" Score="10" Body="&lt;p&gt;The current biomolecular force fields that I'm familiar with &lt;strong&gt;don't include any special energy terms for hydrogen bonds&lt;/strong&gt;. Typically, hydrogen atoms that are capable of hydrogen bonding have very small Lennard-Jones radii and significant positive charges, which allow for very strong electrostatic interactions. For example, in the CHARMM force field, the alcohol hydrogen of serine has a 12-6 potential Rmin of 0.449 Å and a charge of 0.43, while a terminal methyl hydrogen of leucine has an Rmin of 2.68 Å and a charge of 0.09. So, the alcohol hydrogen can donate strong hydrogen bonds, while the methyl hydrogen does not. In the Amber force field, the situation is similar, although less pronounced: the alcohol hydrogen of serine has an Rmin of 1.2 Å and a charge of 0.4275, while the leucine methyl has an Rmin of 2.974 Å and a charge 0.1.&lt;/p&gt;&#xA;&lt;p&gt;Very old versions of the CHARMM force field used to have &lt;a href=&quot;https://www.charmm.org/ubbthreads/ubbthreads.php?ubb=showflat&amp;amp;Number=1683&quot; rel=&quot;noreferrer&quot;&gt;a special 12-10 potential term for hydrogen bonds&lt;/a&gt;, but that has been long deprecated.&lt;/p&gt;&#xA;&lt;p&gt;Now, maybe, in principle, the bonded terms involving the hydrogen should change upon formation of the hydrogen bond. I would imagine that an alcohol hydrogen interacts differently with its parent oxygen depending on whether it participates in a hydrogen bond with something else. But force fields such as CHARMM and Amber ignore any such effects: the bond, angle, and dihedral terms don't change depending on whether a hydrogen bond has formed or not. These force fields have been very successful in reproducing many experimental results with proteins, lipids, DNA and carbohydrates in water, so, at least for some purposes, the approximation is valid.&lt;/p&gt;&#xA;&lt;p&gt;Covalent character does not necessarily mean you can't represent a interaction by a classical force field. With a sufficiently &lt;a href=&quot;https://authors.library.caltech.edu/17896/11/jp9035056_si_002.pdf&quot; rel=&quot;noreferrer&quot;&gt;complex force field&lt;/a&gt;, you can represent a lot of chemistry (for example, &lt;a href=&quot;https://en.wikipedia.org/wiki/ReaxFF&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF&lt;/a&gt;). I should also mention that ReaxFF has a special term for hydrogen bonds: &lt;span class=&quot;math-container&quot;&gt;$$E_\mathrm{Hbond} = p_\mathrm{hb1} \left[ 1 - \exp(p_\mathrm{hb2} \mathsf{BO}_\mathrm{XH}) \right] \exp \left[ p_\mathrm{hb3} \left( \frac{r^\circ_\mathrm{hb}}{r_\mathrm{HZ}} + \frac{r_\mathrm{HZ}}{r^\circ_\mathrm{hb}} - 2 \right) \right] \sin^8 \left( \frac{\Theta_\mathrm{XHZ}}{2} \right),$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathsf{BO}_\mathrm{XH}$&lt;/span&gt; is the bond order between the donor atom and the hydrogen atom (calculated as detailed in the &lt;a href=&quot;https://doi.org/10.1021/jp709896w&quot; rel=&quot;noreferrer&quot;&gt;supporting information of the paper&lt;/a&gt;), &lt;span class=&quot;math-container&quot;&gt;$r_\mathrm{HZ}$&lt;/span&gt; is the distance between hydrogen atom and the acceptor atom, &lt;span class=&quot;math-container&quot;&gt;$\Theta_\mathrm{XHZ}$&lt;/span&gt; is the donor-hydrogen-acceptor angle, and all other variables are free parameters defined in the force field.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2021-10-28T14:33:34.200" LastActivityDate="2021-10-28T14:33:34.200" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6862" PostTypeId="1" AcceptedAnswerId="6891" CreationDate="2021-10-09T07:07:56.187" Score="10" ViewCount="819" Body="&lt;p&gt;I am trying to do the band structure calculation considering the Spin Orbit Coupling but getting the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Computing kpt #:    92&#xA; total cpu time spent up to now is     3908.6 secs&#xA;&#xA; Computing kpt #:    93&#xA; total cpu time spent up to now is     3955.6 secs&#xA;&#xA; Computing kpt #:    94&#xA;&#xA;&#xA;&#xA;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%     &#xA;     Error in routine cdiaghg (463):    &#xA;     S matrix not positive definite     &#xA;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have tried doing this calculation with both PAW and Ultrasoft fully relativistic pseudopotential and getting the same error in both the cases. Before it I have already done the scf calculation without any error with both the pseudopotential. I have tried increasing the plane wave cutoff too, but still getting the same error.&lt;/p&gt;&#xA;&lt;p&gt;The link for the scf, nscf input out file is &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/6862&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am wondering why this is happening. I have already checked for the overlap of atoms in xcrysden but I don't think that is the problem cause then scf calculation would not have been done successfully. Please suggest me how can I remove this errors as I am dealing with it for last three days.&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2021-10-14T17:44:38.683" Title="Error in nscf calculation while considering Spin Orbit Coupling in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|band-structure|pseudopotentials|spin-orbit-coupling|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6863" PostTypeId="1" AcceptedAnswerId="6866" CreationDate="2021-10-09T10:27:13.740" Score="9" ViewCount="80" Body="&lt;p&gt;Is there any standard file format (.txt, .dat etc) for storing one and two electron integrals (generated from &lt;em&gt;ab initio&lt;/em&gt; packages) which doesn't compromise on precision and is convenient for reading into HPC routines in Fortran for calculations (and also, maybe, Python for some trivial calculations).&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="5" LastEditDate="2021-10-09T21:06:02.533" LastActivityDate="2021-10-09T21:11:51.560" Title="Is there a standard file format for storing one and two electron integrals?" Tags="|computational-chemistry|high-performance-computing|high-precision|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6864" PostTypeId="1" AcceptedAnswerId="6868" CreationDate="2021-10-09T13:17:59.663" Score="9" ViewCount="272" Body="&lt;p&gt;In DFT calculations using vasp, symmetry analysis are performed to determine space group symmetries at first, if symmetrization is turned on, such as ISYM = 2. When magmoms are set in INCAR, symmetries broken by local magnetic moments are removed and magnetic symmetries are obtained. To test whether a symmetry &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is compatible with local magnetic moments, given a site &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt;, an equivalent site, &lt;span class=&quot;math-container&quot;&gt;$r_j = gr_i+R$&lt;/span&gt;, related by the symmetry is found at first. &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is a Bravais lattice. After applying the symmetry to the magnetic moment on the site &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt;, if resulting magnetic moments is equal to the magnetic moment on the equivalent site,&lt;span class=&quot;math-container&quot;&gt;$m_j=gm_i$&lt;/span&gt;, the symmetry is preserved. The equality must be hold within some tolerance, that is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|m_j-gm_i|&amp;lt;\delta.&#xA;$$&lt;/span&gt;&#xA;My question is what is value of the tolerance give a value of SYMPREC?&lt;/p&gt;&#xA;" OwnerUserId="3456" LastEditorUserId="5" LastEditDate="2021-10-09T21:03:10.477" LastActivityDate="2021-10-10T12:46:35.157" Title="How is SYMPREC used to determine symmetries compatible with local magnetic moments in VASP?" Tags="|vasp|magnetism|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6865" PostTypeId="2" ParentId="6823" CreationDate="2021-10-09T21:01:22.163" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;But since the DFT works not so well when dealing with semiconductors and excited-state calculations, wouldn't NAMD be too erroneous considering the nuclei vibrations?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;First of all, DFT in this context might not be as bad as you think. For example, my answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt; shows that even 10 years ago in 2011, some functionals were on average within 1.8 kcal/mol of CCSD(T) for a study across 30 test sets involving 1218 total energies overall. The double-hybrids described there, were extended for application to excited states within the TDDFT framework as early as in 2007 with &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.2772854&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Still, in many applications 1 kcal/mol is not accurate enough, but in such applications, the entire NAMD framework might not be either. In the &lt;a href=&quot;http://home.ustc.edu.cn/%7Ezqj/code/namd.pdf&quot; rel=&quot;noreferrer&quot;&gt;PDF presentation about Hefei-NAMD&lt;/a&gt; which you showed us in your question body, search for the word &amp;quot;assumptions&amp;quot; and you will see that Hefei-NAMD is far from an &amp;quot;exact&amp;quot; method for dynamics predictions in general. Likewise in the &lt;a href=&quot;https://dornsife.usc.edu/assets/sites/1066/docs/ar198.pdf&quot; rel=&quot;noreferrer&quot;&gt;PDF paper about the PYXAID program&lt;/a&gt; which again you showed us in your question body, just search for the word &amp;quot;neglected&amp;quot; and &amp;quot;approximate&amp;quot; and you'll find corners that are being cut in that program, which will prevent you from getting a numerically exact prediction of the true dynamics.&lt;/p&gt;&#xA;&lt;p&gt;But whatever errors you are getting due to using DFT or NAMD, may be perfectly okay for what you are wishing to calculate, or if not, the resulting calculation may at least be the best we can do for such a large system at present, with the amount of resources available in the group that has enough interest in the specific problem right now. Better accuracy might be possible for the electronic structure, by using the coupled-cluster method, or &lt;a href=&quot;https://www.frontiersin.org/articles/10.3389/fchem.2021.749779/abstract&quot; rel=&quot;noreferrer&quot;&gt;GW&lt;/a&gt;, or any of a number of other higher-accuracy methods, but they will all have some limitations, and if your system is large enough you might be forced to only use vanilla DFT. Likewise, you can avoid some of the approximations made in Hefei-NAMD and in PYXAID by doing numerically exact quantum dynamics which would be possible with methods like MCTDH or my own program &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465513002294?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;FeynDyn&lt;/a&gt; which calculates the &lt;em&gt;dyn&lt;/em&gt;amics using &lt;em&gt;Feyn&lt;/em&gt;man integrals, or the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct501066k&quot; rel=&quot;noreferrer&quot;&gt;HEOM&lt;/a&gt; method which converts the same Feynman integrals into systems of differential equations to be numerically solved. But all of these mechanisms that offer a numerically exact quantum dynamics result, again have limitations which cause it to often be worthwhile to just use MD (or maybe NAMD) methods.&lt;/p&gt;&#xA;&lt;p&gt;It's also possible that for your application, combining DFT and NAMD is &lt;em&gt;not&lt;/em&gt; worthwhile, but to be more sure certain of this it would help if we knew &lt;em&gt;precisely&lt;/em&gt; what you wanted to calculate, and probably a lot of other information such as how these methods have performed on similar systems or in similar settings.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-09T21:01:22.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6866" PostTypeId="2" ParentId="6863" CreationDate="2021-10-09T21:11:51.560" Score="5" Body="&lt;p&gt;The &lt;code&gt;FCIDUMP&lt;/code&gt; format is probably the closest thing to what you are seeking. More than a dozen different quantum chemistry programs already have a built-in mechanism to read or write one- and two-electron integrals in &lt;code&gt;FCIDUMP&lt;/code&gt; format, as described here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1643/5&quot;&gt;How do the various programs read or write integrals in FCIDUMP format?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;which doesn't compromise on precision&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I've also never seen an &lt;code&gt;FCIDUMP&lt;/code&gt; file in which the integrals were not stored with double-precision.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;and is convenient for reading into HPC routines in Fortran for calculations (and also, maybe, Python for some trivial calculations).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Many of those programs listed in the body of the question linked above, already have some FORTRAN or Python code written for reading (and/or writing) &lt;code&gt;FCIDUMP&lt;/code&gt; files.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-09T21:11:51.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6867" PostTypeId="2" ParentId="4111" CreationDate="2021-10-10T00:50:44.590" Score="7" Body="&lt;p&gt;The general answer to your question is that it depends on what scientific question you are wanting to answer. However, since you're interested in thermoelectric properties, the material you're studying is probably a semiconductor and has a band-gap. This means that the conductivity is essentially zero unless you dope it, so using the undoped Fermi energy from the SCF will not give you anything interesting.&lt;/p&gt;&#xA;&lt;p&gt;If you want to compare to an experiment, you will probably want to look at the temperature variation at the experimental doping concentration; however, be aware that in practice the material may have intrinsic defects or other impurities which may act as additional dopants or compensate the doping, and you may need to account for these when you set the dopant concentration in BoltzTraP.&lt;/p&gt;&#xA;&lt;p&gt;It may be more instructive to look at S vs T &lt;em&gt;and&lt;/em&gt; doping concentration. I suggest you plot S vs doping concentration and overlay the curves for a series of temperatures, e.g. T = 300 K, 400 K, 500 K etc.&lt;/p&gt;&#xA;&lt;p&gt;Be aware that BoltzTraP assumes that the material's underlying electronic structure is unchanged by doping. In other words, it assumes that, when you dope the material, all that happens is conduction states are occupied (n-dopants) or valence states are unoccupied (p-dopants). This is perfectly reasonable for small doping concentrations, but in thermoelectric applications it is common to dope the material very heavily, sometimes almost to the solubility limit, and BoltzTraP's assumptions could break down. I recommend you benchmark the results against a separate calculation with some explicit dopants in the model (i.e. actually make the substitution in your DFT program, or whatever you're using to compute the electronic structure).&lt;/p&gt;&#xA;&lt;p&gt;Finally, I recommend BoltzTraP2 in general, as a superior tool. Not only does it have all the functionality of BoltzTraP, but it has some additional functionality such as being able to plot the interpolated bands, which is extremely useful for checking that the interpolation is sensible.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-10-10T00:50:44.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6868" PostTypeId="2" ParentId="6864" CreationDate="2021-10-10T12:46:35.157" Score="3" Body="&lt;p&gt;Without any testing, I think the value of &lt;code&gt;SYMPREC&lt;/code&gt; is also used for the tolerance &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; in your expression.&lt;/p&gt;&#xA;&lt;p&gt;The subroutine related to the magnetic sites is called &lt;code&gt;MAGSYM&lt;/code&gt; that can be found in &lt;code&gt;symlib.F&lt;/code&gt;. In the subroutine, the magnetic moment of sites are compared with that of their corresponding sites after symmetry operation and the tolerance is set to a variable called &lt;code&gt;TINY&lt;/code&gt; with a default value of 1E-5. The default value of &lt;code&gt;TINY&lt;/code&gt; can be found in module &lt;code&gt;sim_prec&lt;/code&gt; at the beginning of &lt;code&gt;symlib.F&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;And this &lt;code&gt;TINY&lt;/code&gt; variable is also read in by &lt;code&gt;READER&lt;/code&gt; subroutine inside &lt;code&gt;reader.F&lt;/code&gt; from &lt;code&gt;SYMPREC&lt;/code&gt; tag in your &lt;code&gt;INCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, I would suppose that changing the value of &lt;code&gt;SYMPREC&lt;/code&gt; also changes the magnetic tolerance.&lt;/p&gt;&#xA;" OwnerUserId="1804" LastActivityDate="2021-10-10T12:46:35.157" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6869" PostTypeId="2" ParentId="6857" CreationDate="2021-10-10T13:55:54.227" Score="5" Body="&lt;p&gt;The effective mass is related to the second derivative of the E-k curve as&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tn4Rs.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tn4Rs.gif&quot; alt=&quot;eff mass&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So an accurate value of effective mass requires an accurate dispersion curve at all k points. If enough k values are not taken to plot the curve, plotting tools will interpolate the values to have a smooth curve, and the values may vary significantly from the actual values. This may lead to an inaccurate value of effective mass in those regions of brillouin zone.&lt;/p&gt;&#xA;" OwnerUserId="3611" LastActivityDate="2021-10-10T13:55:54.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6870" PostTypeId="1" AcceptedAnswerId="6884" CreationDate="2021-10-10T14:01:56.643" Score="10" ViewCount="1295" Body="&lt;p&gt;When conducting a minimization on Gaussian software, What are the procedures used to eliminate imaginary frequencies if we have already found a stationary point? Are there any keywords that would help to find the minimum?&lt;/p&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="5" LastEditDate="2021-10-11T17:41:10.170" LastActivityDate="2021-10-13T05:46:21.040" Title="How to eliminate imaginary frequencies during a Gaussian geometry optimization?" Tags="|gaussian|geometry-optimization|vibrations|geometry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6871" PostTypeId="2" ParentId="6796" CreationDate="2021-10-10T22:53:33.473" Score="7" Body="&lt;p&gt;You mentioned DFT, which is typically used to calculate the &lt;em&gt;&lt;strong&gt;electronic&lt;/strong&gt;&lt;/em&gt; energy at zero temperature. You can adjust the geometry until this electronic energy is lowest, but then you might ask why for a given pressure, if you increase the temperature, a substance's geometry changes, perhaps from an ordered lattice, to a disordered liquid, to a bunch of molecules that are effectively unbound from each other:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/51eF1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/51eF1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Does the geometry of the substance stay exactly the same if you stay in the &amp;quot;solid&amp;quot; region of the above diagram, and move parallel to the horizontal axis, toward the &amp;quot;liquid&amp;quot; region? If so, does the geometry just spontaneously change drastically when you cross the line between &amp;quot;solid&amp;quot; and &amp;quot;liquid&amp;quot;? Or does the geometry (bond lengths and angles) of the solid lattice change a bit as we move away from the vertical axis along a perpendicular line?&lt;/p&gt;&#xA;&lt;p&gt;One way you can study this is to do a molecular dynamics simulation, as I described in my answers to the following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4772/5&quot;&gt;How to calculate the volumetric energy density of a molecule?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4817/5&quot;&gt;How do I simulate the interaction between two atoms?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'll give a simpler summary here. Instead of using PACKMOL, as I described in the above two answers, you have already suggested in step 1 of your proposed procedure, to do a DFT optimization at 0K, so this may be how you want to  set the equilibrium geometry of your system of atoms. Then, you can simply use &lt;a href=&quot;/questions/tagged/lammps&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; rel=&quot;tag&quot;&gt;lammps&lt;/a&gt;, or &lt;a href=&quot;/questions/tagged/gromacs&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gromacs&amp;#39;&quot; rel=&quot;tag&quot;&gt;gromacs&lt;/a&gt;, or &lt;a href=&quot;/questions/tagged/cp2k&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cp2k&amp;#39;&quot; rel=&quot;tag&quot;&gt;cp2k&lt;/a&gt; or any molecular dynamics software to propagate the system for a chosen pressure and temperature (the initial volume is already known, thanks to your input geometry, and the volume may change as the MD simulation progresses, but you expect this anyway, since you're wondering what the new geometry, including the new volume, will be). You can choose a &lt;a href=&quot;/questions/tagged/forcefield&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;forcefield&amp;#39;&quot; rel=&quot;tag&quot;&gt;forcefield&lt;/a&gt; based on the atoms you have in your system, and let the MD program find how Newton's 2nd law (F = ma) says the atoms should move. They will keep moving until hopefully an equilibrium is reached, &lt;em&gt;&lt;strong&gt;which is now your geometry&lt;/strong&gt;&lt;/em&gt; at the given temperature and pressure.&lt;/p&gt;&#xA;&lt;p&gt;This can be made more accurate by not just choosing some predetermined forcefield, but by actually using an electronic structure method (like DFT) to calculate the forces between your atoms for their respective geometry at each step of the MD simulation. This is called &lt;a href=&quot;/questions/tagged/aimd&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;aimd&amp;#39;&quot; rel=&quot;tag&quot;&gt;aimd&lt;/a&gt; or &lt;em&gt;ab initio&lt;/em&gt; MD, and it can be very slow, so you may want to use CPMD as described in the answers by myself and Tyberius here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1525/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;. To explain &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6796/how-would-one-find-a-materials-equilibrium-structure-at-any-specific-temperatur#comment14809_6796&quot;&gt;dwhswenson's comment&lt;/a&gt;, I'll say that you can even take this further and do full quantum dynamics if you want even more accuracy, meaning that instead of using Newton's classical equation F = ma, you could literally solve the time-dependent Schroedinger equation &lt;span class=&quot;math-container&quot;&gt;$\frac{d|\psi(t)\rangle}{dt} = -\frac{i }{\hbar}\hat{H}(t) |\psi(t)\rangle$&lt;/span&gt;, but as I very recently explained in my answer to this: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6865/5&quot;&gt;Deviation caused by using DFT in Non-Adiabatic Molecular Dynamics&lt;/a&gt;, that you would be limited to a very small system and considering that your &amp;quot;force&amp;quot; calculations from DFT (or even coupled-cluster or more more sophisticated methods) will be limited in accuracy for the types of problems for which this calculation would even be relevant.&lt;/p&gt;&#xA;&lt;p&gt;Your best bet is therefore likely to do something quick in (for example) LAMMPS or GROMACS  (using a predetermined forcefield) or to try for something a bit more accurate using CPMD (the method) with CP2K or CPMD (the software), for example.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-10T22:53:33.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6872" PostTypeId="1" CreationDate="2021-10-11T06:02:28.023" Score="13" ViewCount="2316" Body="&lt;p&gt;I know there are programs that can automatically visualize .cube files (like VMD), but I'm trying to do it myself in python/matplotlib (or equivalent) to better understand what the numbers mean.&lt;/p&gt;&#xA;&lt;p&gt;I understand that there are nx*ny*nz grid points in the file (and can be saved in an array fo dimensions [nx,ny,nz]), but I can't quite figure out how to visualize them or what kind of plot they correspond to (with respect to the modules available on matplotlib).&lt;/p&gt;&#xA;&lt;p&gt;Part of a script that extracts info from cube file :&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;filename1 = 'density.cube'&#xA;with open(filename1, 'r') as f:&#xA;    lines = f.read().splitlines()&#xA;no_of_atoms, _, _, _ = lines[2].split()&#xA;no_of_atoms = int(no_of_atoms)&#xA;xdim, _, _, _ = lines[3].split()&#xA;xdim = int(xdim)&#xA;ydim, _, _, _ = lines[4].split()&#xA;ydim = int(ydim)&#xA;zdim, _, _, _ = lines[5].split()&#xA;zdim = int(zdim)&#xA;&#xA;elements = [None] * no_of_atoms&#xA;atoms_x_coords_in_density = [None] * no_of_atoms&#xA;atoms_y_coords_in_density = [None] * no_of_atoms&#xA;atoms_z_coords_in_density = [None] * no_of_atoms&#xA;&#xA;for _ in range(no_of_atoms):&#xA;    (elements[_], __,&#xA;     atoms_x_coords_in_density[_],&#xA;     atoms_y_coords_in_density[_],&#xA;     atoms_z_coords_in_density[_]) = lines[6 + _].split()&#xA;    elements[_] = int(elements[_])&#xA;    atoms_x_coords_in_density[_] = float(atoms_x_coords_in_density[_])&#xA;    atoms_y_coords_in_density[_] = float(atoms_y_coords_in_density[_])&#xA;    atoms_z_coords_in_density[_] = float(atoms_z_coords_in_density[_])&#xA;&#xA;# Load the data, we need to remove the first 8 lines and the space after&#xA;str = ' '.join(file(filename1).readlines()[(6 + no_of_atoms):])&#xA;data = np.fromstring(str, sep=' ')&#xA;data.shape = (xdim, ydim, zdim)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, the grid points are in the &lt;code&gt;data&lt;/code&gt; array, but I'm not sure how to plot them. I've seen an example using the &lt;code&gt;mayavi&lt;/code&gt; package, but that's also a black box solution (plus I couldn't get it installed for some reason -- the conda version seems broken). I'm trying to understand about what's happening under the hood.&lt;/p&gt;&#xA;&lt;p&gt;Any help is appreciated.&lt;/p&gt;&#xA;" OwnerUserId="4403" LastEditorUserId="5" LastEditDate="2021-10-19T20:57:38.950" LastActivityDate="2022-05-07T00:58:54.940" Title="How to plot a Gaussian cube file with python/matplotlib?" Tags="|python|gaussian|visualization-software|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6873" PostTypeId="1" CreationDate="2021-10-11T09:41:21.433" Score="6" ViewCount="715" Body="&lt;p&gt;Can we optimize a molecular structure using Moller-Plesset MP4 method on GAUSSIAN software? If yes what keyword do we have to add?&lt;/p&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="5" LastEditDate="2021-10-11T17:52:41.770" LastActivityDate="2021-10-11T18:28:03.937" Title="Geometry optimization with Moller-Plesset MP4" Tags="|gaussian|geometry-optimization|geometry|structure|many-body-perturbation-theory|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6874" PostTypeId="2" ParentId="6855" CreationDate="2021-10-11T14:08:53.183" Score="3" Body="&lt;p&gt;Perhaps not the most detailed answer, since I'm not hugely familiar with the precise functionality/details that would be involved, but GPAW does seem to &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorialsexercises/electronic/berry/berry_tutorial.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;have the functionality&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Caveat: The GPAW docs are currently undergoing a fairly complete overhaul, so the link may be dead in the medium/long-term future, but as of the writing of this answer, it works.&lt;/p&gt;&#xA;" OwnerUserId="512" LastActivityDate="2021-10-11T14:08:53.183" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6875" PostTypeId="2" ParentId="6873" CreationDate="2021-10-11T17:36:31.417" Score="9" Body="&lt;p&gt;Gaussian &lt;a href=&quot;https://gaussian.com/mp/&quot; rel=&quot;noreferrer&quot;&gt;can do all the way up to MP5&lt;/a&gt; for single-point energies, but analytic gradients are only available for MP2, MP3, MP4(DQ) and MP4(SDQ), the latter including only single, double and quadruple substitutions.&lt;/p&gt;&#xA;&lt;p&gt;MP4(SDTQ) which is like MP4(SDQ) but also with triple substitutions, and MP5, are listed in the manual as being able to do numerical gradients. Keep in mind that the Gaussian documentation already linked above says &amp;quot;MP4: Fourth-order MP theory correction [Raghavachari78], which defaults to full MP4 with single, double, triple and quadruple substitutions [Raghavachari78, Raghavachari80] (MP4(SDTQ))&amp;quot;, meaning that MP4(SDTQ) and MP4 mean the same thing in Gaussian's terminology.&lt;/p&gt;&#xA;&lt;p&gt;All of what I wrote above applies only to RHF and/or UHF reference states, since Gaussian only provides single-point energies for MP methods with an ROHF reference (you can see some discussion about that at the Chemistry SE here: &lt;a href=&quot;https://chemistry.stackexchange.com/q/76064/27342&quot;&gt;Is it possible to perform ROMP2 numerical optimizations in Gaussian09?&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Beware that MP4 calculations are quite a lot slower than MP2 ones, which can make geometry optimization quite prohibitive depending on the size of your system, so you would probably want to use analytic gradients with RHF or UHF (instead of ROHF) and with MP4(DQ) or MP4(SDQ) rather than trying to do numericaly gradients in Gaussian with MP4 or numerical gradients manually on your own using ROMP4.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, the MP series (MP2, MP3, MP4, MP5, etc.) is rarely used beyond MP2, largely because methods like CCSD can be far more accurate, and many DFT functionals may be more accurate while also being less computationally expensive (especially double-hybrid functionals which combine DFT with MP2-style calculations and can be astonishingly close to CCSD(T) in accuracy while being only a bit more expensive than MP2, see my answer to this:  &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;). So if you're about to launch 100s of geometry optimization calculations at the MP3 or MP4 level, I would encourage you to consider carefully the purpose of the project.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-10-11T17:59:43.253" LastActivityDate="2021-10-11T17:59:43.253" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6876" PostTypeId="1" AcceptedAnswerId="6877" CreationDate="2021-10-11T17:48:53.690" Score="14" ViewCount="2296" Body="&lt;p&gt;I am trying to make plots based to &lt;a href=&quot;https://www.vasp.at/&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt; simulation results, but I am struggling with how to download so much data from the server. A lot of examples on the internet are taught using the local desktop environment, which has a GUI like &lt;a href=&quot;https://www.gnome.org/&quot; rel=&quot;noreferrer&quot;&gt;GNOME&lt;/a&gt;. They could use Python to make plots easily, but when I need to run some serious simulation, I would like to do it on an HPC cluster, which doesn't have a GUI.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do I have to download all the data to my laptop, or are there some other solutions?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2021-10-13T14:17:52.103" LastActivityDate="2021-11-17T07:52:39.787" Title="How can I use a GUI on a supercomputer?" Tags="|vasp|high-performance-computing|python|visualization-software|graphical-user-interface|" AnswerCount="3" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6877" PostTypeId="2" ParentId="6876" CreationDate="2021-10-11T18:11:26.817" Score="15" Body="&lt;p&gt;I prefer to just download the data from the remote disks and then do the plots on my own local machine, which has all of my favorite tools for post-processing my data.&lt;/p&gt;&#xA;&lt;p&gt;I understand that this can be inconvenient though. It is indeed possible to run a GUI on a remote supercomputer though, if you first use &lt;code&gt;ssh -X&lt;/code&gt; or &lt;code&gt;ssh -Y&lt;/code&gt; when signing into the remote machine (The  &lt;a href=&quot;//askubuntu.com/a/35518/676348&quot;&gt;difference between the &lt;code&gt;-X&lt;/code&gt; and &lt;code&gt;-Y&lt;/code&gt; options&lt;/a&gt; is the degree of trust you give the X11 clients). The reason I don't usually do this, is because viewing on my local computer, a GUI that's running on a remote machine, can sometimes be painfully slow, but this will depend on many factors (speeds of the internet connections involved, age of the hardware involved, etc.), so you might at least like to try it once. From a Windows computer, you can run an X11 server such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Xming&quot; rel=&quot;noreferrer&quot;&gt;Xming&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Personally though, I watch my data as it's being calculated, using the &lt;code&gt;awk&lt;/code&gt; command; and if I want to make a publication-quality plot, I download the data to my local machine and do all post-processing and/or plotting offline. If you post the exact output from VASP and what precise numbers you want in your plot/visualization (with a question title like &amp;quot;how can I visualize the following data from the command line?&amp;quot;), I can try to give you an &lt;code&gt;awk&lt;/code&gt; command that would work for your case.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="-1" LastEditDate="2021-10-13T13:35:41.940" LastActivityDate="2021-10-13T13:35:41.940" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6878" PostTypeId="2" ParentId="6873" CreationDate="2021-10-11T18:28:03.937" Score="7" Body="&lt;p&gt;Complementing the @Nike answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Can we optimize a molecular structure using Moller-Plesset MP4 method&#xA;on GAUSSIAN software?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If yes what keyword do we have to add?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You need to add the corresponding keywords like below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt mp4(sdtq)/6-31++g(d,p) geom=connectivity&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From Gaussian &lt;a href=&quot;https://gaussian.com/&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt;:&lt;br /&gt;&#xA;&lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;noreferrer&quot;&gt;opt&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This keyword requests that a geometry optimization be performed. The geometry will be adjusted until a stationary point on the potential surface is found. Analytic gradients will be used if available. For the Hartree-Fock, CIS, MP2, MP3, MP4(SDQ), CID, CISD, CCD, CCSD, QCISD, BD, CASSCF, and all DFT and semi-empirical methods, the default algorithm for both minimizations (optimizations to a local minimum) and optimizations to transition states and higher-order saddle points is the Berny algorithm using GEDIIS [Li06] in redundant internal coordinates [Pulay79, Fogarasi92, Pulay92, Baker93, Peng93, Peng96] (corresponding to the Redundant option).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://gaussian.com/mp/&quot; rel=&quot;noreferrer&quot;&gt;mp4&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The MPn method keywords request a Hartree-Fock calculation (by default, RHF for singlets, UHF for higher multiplicities) followed by a Møller-Plesset correlation energy correction (...) MP4: Fourth-order MP theory correction, which defaults to full MP4 with single, double, triple and quadruple substitutions (MP4(SDTQ)).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;6-31++g(d,p): Is the chosen &lt;a href=&quot;https://gaussian.com/basissets/&quot; rel=&quot;noreferrer&quot;&gt;basis set&lt;/a&gt;. You need to select the basis set that better represent your system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://gaussian.com/geom/&quot; rel=&quot;noreferrer&quot;&gt;geom&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Geom keyword specifies the source of the molecule specification&#xA;input, options related to coordinate definitions, and geometry-related&#xA;output. By default, it is read from the input stream, as described&#xA;previously. Geom may be used to specify an alternate input source. It&#xA;also controls what geometry-related information is printed and use of&#xA;internal consistency checks on the Z-matrix. The Geom keyword is not&#xA;meaningful without at least one item selection option.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-11T18:28:03.937" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6879" PostTypeId="1" AcceptedAnswerId="6880" CreationDate="2021-10-11T21:10:43.113" Score="6" ViewCount="79" Body="&lt;p&gt;Specifically, in the General Utility Lattice Program (GULP) &lt;a href=&quot;https://doi.org/10.1080/0892702031000104887&quot; rel=&quot;nofollow noreferrer&quot;&gt;2003 paper&lt;/a&gt;, in the methods section on Two-body Short-range Interactions we have the following:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For covalently bonded atoms, it is often preferable to Coulomb subtract the interaction and to describe it with either a harmonic or Morse potential.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What exactly does that mean? Does that mean the Coulomb interaction has no effect at all when using a pair potential? That seems to be what it's implying to me, but I can't find an explanation of the terminology anywhere.&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="5" LastEditDate="2021-10-12T00:14:44.633" LastActivityDate="2021-10-12T00:14:44.633" Title="What is the meaning of Coulomb Subtraction?" Tags="|software|terminology|interatomic-potentials|lattice-dynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6880" PostTypeId="2" ParentId="6879" CreationDate="2021-10-11T21:44:14.097" Score="4" Body="&lt;p&gt;Got a bit too long for a comment, so I'll leave it as a semi-complete answer for now. In case the paper is inaccessible to other readers, much of the same information is in the &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/help/gulp5.2_manual.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;gulp5.2 manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In regards to the question, it does seem to elaborate a little in the sentences following your quote. From earlier in the document:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Here the Coulomb interaction, and usually the dispersion one too, is subtracted for interactions which are between neighbours (i.e. bonded or 1-2) and next nearest neighbours (i.e. which have a common bonded atom, 1-3) according to the connectivity. This is done so that the parameters in the two- and three-body potentials can be directly equated with experimentally observable quantities, such as force constants from spectroscopy.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think it essentially just amounts to a shift of the equations in order to make the parameters of the potential corresponding to physically meaningful/experimentally measurable quantities.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-10-11T21:44:14.097" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6881" PostTypeId="2" ParentId="6824" CreationDate="2021-10-12T00:07:16.763" Score="9" Body="&lt;p&gt;A lot of it will be in the difference in cost. But as a rule of thumb, GW potentials are typically harder, and include more states (semicores).&lt;/p&gt;&#xA;&lt;p&gt;This need not &lt;em&gt;always&lt;/em&gt; be the case, since if you look at the Ag POTCARS, there isn't any difference at all in the recommended ENMIN/ENMAX, partial core radius, or even the states that are considered valence.&lt;/p&gt;&#xA;&lt;p&gt;In contrast, the Ti POTCARs for plain Ti vs the GW Ti are quite different. The GW POTCAR has a higher cutoff, lower partial core radius, a &lt;em&gt;much&lt;/em&gt; higher cutoff requirement for the augmentation charge, etc.&lt;/p&gt;&#xA;&lt;p&gt;A counter example to the whole 'is probably harder, probably has more states' are the Li/Li_GW or Na/Na_GW potentials, where the GW variant appears to be softer. I do not know why this is. There is presumably a reason, but I am not aware of it.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps a more relevant difference is the pseudo-wavefunction norm, which in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.90.075125&quot; rel=&quot;nofollow noreferrer&quot;&gt;this work here&lt;/a&gt;, it is derived that you need (at least in the formalism used) an approximately norm-conserving PAW core. This can be seen in the C/C_nc_GW pair, with the nc GW potential having ~3x higher of a recommended cutoff (as well as augmentation cutoff).&lt;/p&gt;&#xA;&lt;p&gt;From looking at this fairly minimal set of comparisons, the most obvious indicator of the difference in calculation costs from using the _GW potentials will be in the increased cutoff required to converge the core-region charge density/wavefunctions. However, whether those &lt;em&gt;need&lt;/em&gt; to be converged when doing a ground state DFT calculation (as opposed to a GW calculation), I do not know.&lt;/p&gt;&#xA;" OwnerUserId="512" LastEditorUserId="512" LastEditDate="2022-11-09T00:14:53.707" LastActivityDate="2022-11-09T00:14:53.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6882" PostTypeId="1" AcceptedAnswerId="7066" CreationDate="2021-10-12T07:48:23.007" Score="9" ViewCount="282" Body="&lt;p&gt;I have been attempting to optimize the structure of a Si nanowire using SIESTA. The original structure fed into the optimization is as follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TL6cjm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TL6cjm.png&quot; alt=&quot;Original structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once it is optimized, the structure would change to being as given below.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Eeuf2m.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Eeuf2m.png&quot; alt=&quot;Optimized structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this, there appears to be several atoms moving away from cubic diamond lattice structure (white atoms) as the structure gets optimized (which is something that I expected). However, if I deleted these (white) atoms, the overall structure appears to be much cleaner and nicer as below.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/WLn6Tm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WLn6Tm.png&quot; alt=&quot;New structure: with atoms deleted manually&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/TREkNm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TREkNm.png&quot; alt=&quot;Legend&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now with all these changes in the structure, I am seeing several band lines pass through the Fermi level in the optimized structure (shown in image 2).&#xA;&lt;a href=&quot;https://i.stack.imgur.com/I3VFom.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/I3VFom.png&quot; alt=&quot;Band Structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Does this (lack of band-gap) occur because of the atoms deviating from the cubic diamond crystal arrangement? Is this acceptable to occur in a structure (since the original cross section was manually set by carving out a cylindrical region from a bulk block of Si)?&#xA;Or could it be some error caused by me during the calculation?&lt;/p&gt;&#xA;&lt;p&gt;My fdf script is attached as well&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SystemName       Si&#xA;SystemLabel      Si&#xA;&#xA;NumberOfSpecies    1&#xA;NumberOfAtoms      185&#xA;&#xA;%block ChemicalSpeciesLabel&#xA; 1 14 Si&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;LatticeConstant 5.41 Ang&#xA;%block LatticeVectors &#xA; 10.00  0.00   0.00&#xA;  0.00  1.00   0.00&#xA;  0.00  0.00  10.00&#xA;%endblock LatticeVectors&#xA;&#xA;AtomCoorFormatOut           Ang&#xA;AtomicCoordinatesFormat     Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;20.2875000000000000 1.3525000000000000  14.8775000000000000 1&#xA;21.6400000000000000 2.7050000000000000  13.5250000000000000 1&#xA;24.3450000000000000 0.0000000000000000  13.5250000000000000 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1&#xA;35.1650000000000000 2.7050000000000000  37.8700000000000000 1&#xA;33.8125000000000000 1.3525000000000000  39.2225000000000000 1&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA;  1  0  0  0.0&#xA;  0  6  0  0.0&#xA;  0  0  1  0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;PAO.BasisSize           DZP&#xA;XC.functional           LDA &#xA;XC.authors              CA &#xA;SpinPolarized           .false. &#xA;MeshCutoff              150 Ry  &#xA;kgrid_cutoff            100.0 Ang&#xA;&#xA;MD.TypeOfRun            CG &#xA;MD.VariableCell         true &#xA;MD.NumCGsteps           500 &#xA;MD.MaxCGDispl           0.1 Bohr &#xA;MD.MaxForceTol          0.04 eV/Ang  &#xA;MD.MaxStressTol         0.0001 eV/Ang**3 &#xA;&#xA;MD.UseSaveCG            true&#xA;MD.UseSaveXV            true&#xA;MaxSCFIterations        500&#xA;DM.MixingWeight         0.01&#xA;DM.NumberPulay          3&#xA;DM.Tolerance            1.d-3&#xA;#ElectronicTemperature   25 meV&#xA;SolutionMethod          diagon&#xA;&#xA;BandLinesScale ReciprocalLatticeVectors&#xA;%block BandLines&#xA;1   0.0000000000 0.0000000000 0.0000000000 \Gamma&#xA;100 0.0000000000 0.5000000000 0.0000000000 y&#xA;%endblock BandLines&#xA;&#xA;%block WaveFuncKPoints&#xA;0.000 0.000 0.000 from 1 to 100&#xA;%endblock WaveFuncKPoints&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2021-11-16T17:15:19.577" LastActivityDate="2021-11-16T17:15:19.577" Title="Geometry optimization using DFT" Tags="|density-functional-theory|band-structure|geometry-optimization|siesta|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6883" PostTypeId="2" ParentId="6876" CreationDate="2021-10-12T10:53:01.603" Score="13" Body="&lt;p&gt;It would probably be easier to use some software such as &lt;a href=&quot;https://winscp.net/eng/download.php&quot; rel=&quot;noreferrer&quot;&gt;WinSCP&lt;/a&gt;. It allows you to select the location on your remote system and synchronise with the local system by matching either the time stamp or size (and probably other properties). Also if you are using Linux, read the answers on this &lt;a href=&quot;https://stackoverflow.com/questions/299412/is-there-any-winscp-equivalent-for-linux&quot;&gt;Stack Overflow question&lt;/a&gt; to get an idea of alternatives. This way you can visually manipulate the required files in a manner much similar to what is done in a tutorial.&lt;/p&gt;&#xA;&lt;p&gt;Note: If possible, ask the system administrator to install &lt;a href=&quot;http://xrdp.org/&quot; rel=&quot;noreferrer&quot;&gt;xrdp&lt;/a&gt; (and other required packages which I am sure he would know) which is similar to Windows &lt;a href=&quot;https://en.wikipedia.org/wiki/Remote_Desktop_Protocol&quot; rel=&quot;noreferrer&quot;&gt;RDP&lt;/a&gt; and allows you to connect to a GUI instance of the server.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="1118" LastEditDate="2021-10-12T19:53:49.677" LastActivityDate="2021-10-12T19:53:49.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6884" PostTypeId="2" ParentId="6870" CreationDate="2021-10-13T05:46:21.040" Score="9" Body="&lt;p&gt;Use tighter convergence criteria.&lt;/p&gt;&#xA;&lt;p&gt;If the geometry is already converged with default convergence criteria, then just using tighter convergence thresholds should work. Look at the &lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;noreferrer&quot;&gt;tight option in the gaussian manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Sometimes one will just almost always have one small imaginary frequency (like a few wavenumbers) and it can be very hard to eliminate these, especially when any finite differences are used in calculating the gradient or hessian. This is because there is inherent noise/uncertainty associated with the iterative processes involved in both geometry optimizations and solving the relevant electronic structure equations (both have somewhat arbitrary convergence criteria).&lt;/p&gt;&#xA;&lt;p&gt;In rare cases where you are optimizing a very floppy molecule, you might need to increase the step size used in the optimization as the potential surface can be too flat along some coordinate leading the optimization to erroneously stop because the geometry changes so little that the convergence criteria seem to be met when not at a minimum. I've only seen this happen once though, so that's unlikely to be the problem.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2021-10-13T05:46:21.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6885" PostTypeId="1" CreationDate="2021-10-13T07:17:29.233" Score="30" ViewCount="4422" Body="&lt;p&gt;&lt;strong&gt;Related cross-network post:&lt;/strong&gt; &lt;a href=&quot;https://hsm.stackexchange.com/q/14051/8052&quot;&gt;Have there been instances in physics where different scientists have interpreted the same data differently?&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Here is my problem: I have been testing a force field published in a peer-reviewed paper, and later used by quite a few other authors (I am not sure if I should cite said paper, as I don't want to seem &amp;quot;incriminating&amp;quot;)&lt;/p&gt;&#xA;&lt;p&gt;I was initially able to reproduce quite closely the published results in the original paper while testing it, but they seemed rather unstable (with respect to initial geometry, equilibration time, etc…). To me, this seemed to indicate that the system was not properly equilibrated, and indeed, when equilibrating for a much longer time, I observed the following a behavior (below is the average lattice constant vs number of timesteps for a NPT run at 300K, timestep being 0.5 fs):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kgdcs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kgdcs.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Basically, the system relaxes in 2 steps: there’s a first initial “relaxation” to a value that matches well with the paper and experiments (~6.29A), happening over just a few thousand timesteps. But then the system seems to re-adjust on a much slower timescale, and eventually reaches an equilibrium at a lower value (~6.24A).&lt;/p&gt;&#xA;&lt;p&gt;It is either one fo two things: either I’m doing something wrong, or the original paper published results based on a not properly equilibrated system (which basically makes their force field faulty, and also impacts the credibility of subsequent papers using it)&lt;/p&gt;&#xA;&lt;p&gt;In favor of the first possibility, I have less experience than the authors, and it seems like something that would be hard to miss for them. However, I am using input files that they were kind enough to provide me themselves, with almost no modification at all. Those files are pretty simple, making the possibility of mistakes rather low, and I’ve been trying to double check again and again.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;How likely is it that a force field that has been published in a respectable paper by serious authors and has then been used by many others is faulty and based on non-equilibrated results?&lt;/strong&gt;&lt;/em&gt; It seems like that problem is too basic to go unnoticed. I have tried to contact the author about that issue, providing them a much more detailed account of the problems I found, but they have not reached back.&lt;/p&gt;&#xA;&lt;p&gt;I can provide more details and explanations if needed. I am currently pretty stuck because of this problem&lt;/p&gt;&#xA;" OwnerUserId="3967" LastEditorUserId="5" LastEditDate="2022-01-11T21:48:32.377" LastActivityDate="2022-01-11T21:48:32.377" Title="Can a highly-cited published paper have this type of error?" Tags="|molecular-dynamics|crystallography|lammps|publishing|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6886" PostTypeId="2" ParentId="6885" CreationDate="2021-10-13T07:45:17.567" Score="15" Body="&lt;p&gt;I was actually going to provide this as a comment as this in itself is not a proper answer. But since this got a bit too lengthy for a comment, I am providing this as an answer.&lt;/p&gt;&#xA;&lt;p&gt;It is possible for a highly cited paper to have non-equilibrated results. However, you should consider the fact that you may be using a different precision for your calculations. Also, if the paper was published a long time back, that could mean that they had significantly slower computing power. Therefore they may never have known that equilibrating the system even further results in a smaller lattice constant (not much guilt on their part then).&lt;/p&gt;&#xA;&lt;p&gt;Since you are facing doubts, I recommend that you start with an energy minimization, and move to a good NPT equilibration followed by an NVE run. During the NVE run, you can check the system pressure, KE and PE (which should all be constant) to check if the system has actually reached equilibrium.&#xA;In any case your system (when confirmed to be in equilibrium) has a different lattice constant, you can simply cite the original paper and mention the difference so that the same error does not affect others.&lt;/p&gt;&#xA;&lt;p&gt;Note: I have seen that LAMMPS installations on different systems had minor differences in results which I think could have been caused by round off errors etc.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-13T07:45:17.567" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6887" PostTypeId="1" CreationDate="2021-10-13T13:27:52.997" Score="5" ViewCount="773" Body="&lt;p&gt;I am using Quantum Espresso along with a different code, I am performing calculations on Platinum bulk.&lt;/p&gt;&#xA;&lt;p&gt;After choosing the &amp;quot;cold&amp;quot; smearing (which I read is a good choice for metals) with a value of &lt;code&gt;~ 0.009 Ry (~ 0.1292 eV, ~ 1500 K&lt;/code&gt;). I have been told: &amp;quot;The natural way is Fermi-Dirac and 1500 K is way too big. Please use Fermi-Dirac and a lower value so that we can compare it with the other code&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;So now I use Fermi-Dirac with &lt;code&gt;0.0038 Ry (0.0517 eV, 600 K)&lt;/code&gt;, but I see some &lt;code&gt;c_bands: X eigenvalues not converged&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I read here and there that Fermi-Dirac with metals should be used with high values, typically between &lt;code&gt;0.2 eV&lt;/code&gt; and &lt;code&gt;0.5 eV&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible that a code would need a bigger smearing value than another one? That would explain why this person told me this?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2021-12-13T13:55:46.160" Title="Smearing values for different codes" Tags="|density-functional-theory|metals|smearing|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6888" PostTypeId="2" ParentId="6885" CreationDate="2021-10-13T16:58:59.703" Score="26" Body="&lt;p&gt;Many published papers, even extremely highly cited ones by what you call &amp;quot;serious&amp;quot; authors, have issues like these.&lt;/p&gt;&#xA;&lt;p&gt;Consider for example &lt;a href=&quot;https://www.pnas.org/content/106/41/17255&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; which currently has 862 Google Scholar citations, and has been used as a benchmark for the quantum dynamics of the seven density matrix diagonals in a 7-site model of the FMO complex. The authors were (and still are) two of the most respected scientists in their field, and I personally know the author that did the calculations and think extremely highly of him. But in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct501066k&quot; rel=&quot;noreferrer&quot;&gt;my paper&lt;/a&gt; years later, we showed that the several dozen papers that used their supposedly &lt;em&gt;exact&lt;/em&gt; dynamics plot as a &lt;em&gt;benchmark&lt;/em&gt; to compare the dynamics of a new method, were not actually comparing to exact dynamics after all:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3cSsI.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3cSsI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Likewise, &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.130501&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; currently has 163 Google Scholar citations and they claimed to have factored the number 143 by finding the ground state of a 4-qubit Hamiltonian  with an NMR quantum computer. Two years later, with an undergrad-level student, I discovered that the Hamiltonian not only factored 143 but also larger numbers such as 56153.  Dozens of articles were published by journalists, about my discovery, and I particularly find amusing the title of this one: &lt;a href=&quot;https://www.theregister.com/2014/12/04/boffins_we_factored_143_no_you_factored_56153/&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Quantum computing is so powerful it takes two years to understand what happened&amp;quot;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In a &lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.84.041926&quot; rel=&quot;noreferrer&quot;&gt;different paper&lt;/a&gt; currently with 145 Google Scholar citations, I was unable to reproduce a plot in one of the figures when using their parameter values. I kept insisting this, and the author I emailed kept insisting that there was no mistake, and after seven (very long, because there was a lot of detail involved to figure this out) back-and-forth emails, I got this eighth email:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Hi Nike,&lt;/p&gt;&#xA;&lt;p&gt;sorry for the late response.&lt;/p&gt;&#xA;&lt;p&gt;I at least could check for your first question and I have to apologize&#xA;here. You are right and I simply misprinted the values. We actually&#xA;used  wc = (50 fs)^(-1) as was the values Ishizaki used in their PNAS&#xA;for  figure 2 and 3. They used the other value for figure 4, a&#xA;calculation  which we did not actually repeat.&lt;/p&gt;&#xA;&lt;p&gt;Sorry for that but thanks for being insitant and pointing my nose to&#xA;my  mistake.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This email from 14 September 2011 came several months after my initial email on 12 April 2011. The paper unfortunately remains with this error and no published Erratum or Comment. I don't know why they didn't publish an Erratum, but I can say that I didn't publish a Comment because I've in general been reluctant to do so (I feel that it's better to talk to the authors, and decide together what the best course of action is, and if they don't suggest publishing an Erratum together, then they probably don't want me publishing a Comment either; but now that I'm more senior I wouldn't be as hesitant to publish a Comment if I'm confident that I'm right).&lt;/p&gt;&#xA;&lt;p&gt;In another highly-cited paper in PRL, the authors went into great depths to prove that a problem was in the complexity class &lt;a href=&quot;https://en.wikipedia.org/wiki/QMA&quot; rel=&quot;noreferrer&quot;&gt;QMA&lt;/a&gt; but a (different) undergrad student of mine found that the solution can actually be found in constant time, meaning that it's not only trivially in QMA but also in NP, P and even smaller complexity classes.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, there has been a highly-cited and published &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1367-2630/13/11/113034/meta&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; in which the authors used 50 terms to represent a function as a sum of a particular type of basis function, when in fact I was able to get the same quality of fit with only two of the same type of basis function.&lt;/p&gt;&#xA;&lt;p&gt;I can also provide several examples of errors or impactful typos in spectroscopy papers or quantum chemistry papers related to spectroscopic properties of molecules.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;em&gt;&lt;strong&gt;one&lt;/strong&gt;&lt;/em&gt; example I can think of, where I turned out to be wrong after contacting an author due to not being able to reproduce her result (in this case a mathematical derivation), my first email was an extremely carefully written report authored by myself (PhD student at the time), a post-doc, and our supervisor, and we didn't get any response back at all. It took me approximately two years to figure out (on my own!) why we were wrong and the original paper was right, but I had still never heard from the author of that paper. Several years later I met up with her, and then started having meals with her annually, and while I originally thought that not receiving a response from her was a sign of coldness and not wanting to talk to us, she turned out to be an extremely warm person who just might have had too much going on in her life to reply to the first email, or wasn't able to figure out the reason why &lt;em&gt;&lt;strong&gt;my&lt;/strong&gt;&lt;/em&gt; result didn't match hers.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;When things like these happen, it's best to compose a careful email to the authors (which you've already done!) and continue to investigate whether or not it's you that's wrong (which you are doing here). So you are going about this in the correct way! Keep in mind the timeline in my above examples (several months before the author in the first example finally agreed that the paper had an error; two years for me to find my mistake in the last example), which is there to show you that figuring out these things can take a very long time.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-13T16:58:59.703" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6889" PostTypeId="1" CreationDate="2021-10-13T23:46:31.763" Score="14" ViewCount="171" Body="&lt;p&gt;I am looking for a C or a C++ library that can do crystal generation, that is, multiply unit cells in one or more directions with symmetry information. (in other words, generate supercells).&#xA;I have been using OpenBabel (also C++) but it doesn't have this function (it is more oriented to molecules).&lt;/p&gt;&#xA;&lt;p&gt;If the library can read or write CIF or other similar formats that would be even better.&lt;/p&gt;&#xA;&lt;p&gt;Can you recommend one?&lt;/p&gt;&#xA;&lt;p&gt;I know that libraries like this exist in Python, e.g. ASE, but I need to generate them on the fly (e.g from CIF files.)&lt;/p&gt;&#xA;&lt;p&gt;I am not looking in particular to generate random periodic structures, but it is fine as long as the simpler case I mention above can be performed as well.&lt;/p&gt;&#xA;" OwnerUserId="4417" LastEditorUserId="1609" LastEditDate="2021-11-30T09:43:52.590" LastActivityDate="2021-11-30T09:43:52.590" Title="Looking for crystal generator library" Tags="|software-recommendations|crystallography|programming|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6890" PostTypeId="1" CreationDate="2021-10-14T07:52:10.370" Score="8" ViewCount="509" Body="&lt;p&gt;I have a magnetic crystal system. I want to calculate the total energy of the system if the magnetization direction is aligned in different directions such as [110], [010]. By default Quantum ESPRESSO measures the magnetization along [001] direction and I am not getting any parameter to change the direction in the input file. Actually, I want to produce the band structures for different magnetic directions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is it possible to change the direction of magnetization in Quantum ESPRESSO?&lt;/strong&gt; How can I do that?&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2022-01-14T01:55:03.337" LastActivityDate="2022-09-23T14:55:10.940" Title="How to change the magnetization direction in Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|magnetism|spin-orbit-coupling|spin-polarization|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6891" PostTypeId="2" ParentId="6862" CreationDate="2021-10-14T08:24:44.627" Score="9" Body="&lt;p&gt;This error has been resolved now. Though I am not an expert but here are few thoughts. There may be several reasons for this error:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This error might appear due to numerical instability from overlapping atoms.&lt;/li&gt;&#xA;&lt;li&gt;As mentioned by @Phil Hasnip, if the S-matrix eigenvalues are really small.&lt;/li&gt;&#xA;&lt;li&gt;Some pseudopotential may not fit with calculation, USPP giving non-positive charge density, leading to a violation of positiveness of the S matrix appearing in the USPP formalism or maybe the presence of the ghost states (I am not aware of these states)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These steps may help in resolving the issue:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Changing the pseudopotential file, it may be corrupted.&lt;/li&gt;&#xA;&lt;li&gt;Set the higher &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm279&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ecutwfc&lt;/code&gt;&lt;/a&gt; and &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm282&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ecutrho&lt;/code&gt;&lt;/a&gt; values.&lt;/li&gt;&#xA;&lt;li&gt;Changing the parameter &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm858&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;diago_david_ndim&lt;/code&gt;&lt;/a&gt; to 2(or maybe increase to 8). Currently, the default value is 4.&lt;/li&gt;&#xA;&lt;li&gt;Run the calculation with the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm845&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;diagonalization&lt;/code&gt;&lt;/a&gt; = &lt;code&gt;'cg'&lt;/code&gt; instead of default value &lt;code&gt;davidson&lt;/code&gt;. &lt;code&gt;cg&lt;/code&gt; diagonalization is more robust.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In my case, changing the value of &lt;code&gt;diago_david_ndim&lt;/code&gt; to '2' has resolved the issue for 'davidson' diagonalization.&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="1361" LastEditDate="2021-10-14T17:44:38.683" LastActivityDate="2021-10-14T17:44:38.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6892" PostTypeId="1" AcceptedAnswerId="6893" CreationDate="2021-10-14T10:48:53.833" Score="5" ViewCount="409" Body="&lt;p&gt;Hexagonal unit cells can be converted to rhombohedral unit cells, and the latter unit cells have fewer atoms. But how can I convert them? Is there any software or codes that are able to do this transformation? For example, Cr2O3 has 30 atoms in the hexagonal unit cell, but can also be represented by 10 atoms in a rhombohedral unit cell.&lt;/p&gt;&#xA;" OwnerUserId="3924" LastActivityDate="2021-10-14T12:50:05.123" Title="How to convert a hexagonal unit cell to rhombohedral unit cell?" Tags="|structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6893" PostTypeId="2" ParentId="6892" CreationDate="2021-10-14T12:50:05.123" Score="4" Body="&lt;p&gt;The &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt; package should be able to do it. But I'm not sure if it had rhombohedral or not. I recommend that you download and try &lt;code&gt;Edit data -&amp;gt; Unit cell&lt;/code&gt; option. You should be able to find enough tutorials doing this.&#xA;Alternatively, the &lt;a href=&quot;https://docs.quantumatk.com/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum ATK&lt;/a&gt; package can handle the job. Refer to the &lt;a href=&quot;https://docs.quantumatk.com/tutorials/rhombo_hex_trigonal/rhombo_hex_trigonal.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-14T12:50:05.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6894" PostTypeId="1" CreationDate="2021-10-14T12:55:34.880" Score="7" ViewCount="265" Body="&lt;p&gt;I generated the following SQS cell using ATAT (the sructure is converted to POSCAR format)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR&#xA;3.5169&#xA;  1.000000 -1.000000 0.000000&#xA;-2.000000 -1.500000 0.500000&#xA;-0.500000 0.000000 -3.500000&#xA;  A  B&#xA;  45   5&#xA;Cartesian&#xA;  -2    -1.5    -0.5&#xA;-1.5    -2  -0.5&#xA;-1.5    -1.5    0&#xA;-1  -2  0&#xA;-1.5    -2  -1.5&#xA;-1.5    -1.5    -1&#xA;-1  -2  -1&#xA;-1  -1.5    -0.5&#xA;-1  -1  0&#xA;-0.5    -2  -0.5&#xA;-0.5    -1.5    0&#xA;-1.5    -2  -2.5&#xA;-1.5    -1.5    -2&#xA;-1.5    -1  -1.5&#xA;-1  -2  -2&#xA;-1  -1.5    -1.5&#xA;-1  -1  -1&#xA;-0.5    -1.5    -1&#xA;-0.5    -1  -0.5&#xA;0   -1.5    -0.5&#xA;0   -1  0&#xA;-1.5    -1.5    -3&#xA;-1  -1.5    -2.5&#xA;-1  -1  -2&#xA;-0.5    -1.5    -2&#xA;-0.5    -1  -1.5&#xA;-0.5    -0.5    -1&#xA;0   -1.5    -1.5&#xA;0   -1  -1&#xA;0   -0.5    -0.5&#xA;-1.5    -2.5    -3&#xA;0.5 -1  -0.5&#xA;-2  -2  -3&#xA;-1  -1  -3&#xA;-1  -0.5    -2.5&#xA;-0.5    -1.5    -3&#xA;-0.5    -1  -2.5&#xA;-0.5    -0.5    -2&#xA;0   -1  -2&#xA;0   -0.5    -1.5&#xA;0.5 -1  -1.5&#xA;-0.5    -0.5    -3&#xA;0   -1  -3&#xA;0   -0.5    -2.5&#xA;0.5 -1  -2.5&#xA;-2  -1.5    -1.5&#xA;-2  -1.5    -2.5&#xA;-0.5    -0.5    0&#xA;-1.5    -1  -2.5&#xA;-1  -2  -3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wanted to create slabs such that:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a = [3-3 0]&#xA;b = [1 1 -2]&#xA;c= [1 1 1]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but whenever I try to transform the cell the structure ends up in an incorrect form.&lt;/p&gt;&#xA;&lt;p&gt;I have tried transforming (in VESTA) using the inverse of the initial lattice matrix to get to &lt;code&gt;a = [100] b=[0 1 0]&lt;/code&gt; and &lt;code&gt;c = [0 0 1]&lt;/code&gt; but I end up changing the composition of the structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do you know the correct way to create a slab from SQS files?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4422" LastEditorUserId="5" LastEditDate="2021-12-25T21:25:17.117" LastActivityDate="2021-12-28T19:07:46.937" Title="Changing orientation of SQS structure generated from ATAT" Tags="|ab-initio-calculations|surfaces|vesta|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6895" PostTypeId="1" AcceptedAnswerId="6923" CreationDate="2021-10-14T14:44:05.610" Score="8" ViewCount="427" Body="&lt;p&gt;In my bachelor thesis, I am trying to use the VEDA program to analyze the vibrational energy distribution to associate different vibrations to the calculated modes from gaussian. I am stuck now because the VEDA program seems to provide unrealistic output. I calculated methane as a simple way to show my problems.&lt;/p&gt;&#xA;&lt;p&gt;The input file to gaussian:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=methan.chk&#xA;#p opt freq=SaveNormalmodes B3LYP/6-311G(d,p) nosymm&#xA;&#xA; methan&#xA;&#xA;0 1&#xA;6         -2.69391        0.67007        0.00000&#xA;1         -1.62391        0.67007        0.00000&#xA;1         -3.05057       -0.15258       -0.58389&#xA;1         -3.05058        1.58706       -0.42049&#xA;1         -3.05058        0.57573        1.00438&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I use the log and fchk file from this calculation as input for VEDA. VEDA creates the .fmv file from this input.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt freq=SaveNormalmodes B3LYP/6-311G(d,p) nosymm        &#xA;&#xA;Atomic orientation and masses&#xA;  1   6   -2.69391033    0.67006991    0.00000005     12.00000000&#xA;  2   1   -1.60343431    0.67007262    0.00000174      1.00782504&#xA;  3   1   -3.05739820   -0.16832644   -0.59506760      1.00782504&#xA;  4   1   -3.05740398    1.60460983   -0.42853870      1.00782504&#xA;  5   1   -3.05740406    0.57392428    1.02360451      1.00782504&#xA;&#xA;Force constants in Cartesian coordinates&#xA; 5.33572579E+00  3.66810060E-02  3.66778578E-02  3.66800417E-02  3.04938267E-02&#xA; 4.78002374E-02  9.34030448E-02 -1.23337201E-02 -7.49599366E-02 -8.44033441E-02&#xA; 5.90658770E-02 -4.86412743E-02  6.40541790E-02  1.12695453E-01  0.00000000E+00&#xA; 3.66810060E-02  5.33567095E+00  3.66758568E-02  3.66792176E-02  3.05027864E-02&#xA;-1.23355319E-02 -7.49650905E-02  4.77820938E-02  9.34122780E-02 -8.43965515E-02&#xA; 5.90646100E-02 -4.86546903E-02 -1.12696475E-01 -6.40417842E-02  0.00000000E+00&#xA; 3.66778578E-02  3.66758568E-02  5.33575627E+00  3.66785235E-02 -1.91501878E-02&#xA; 5.31942717E-02 -8.29810618E-02  5.32006592E-02 -8.29790123E-02  7.87153470E-02&#xA; 4.16992065E-02  1.25083636E-01  6.25372507E-02 -6.25463857E-02  0.00000000E+00&#xA; 3.66800417E-02  3.66792176E-02  3.66785235E-02  5.33573582E+00 -4.18424802E-02&#xA;-8.86563336E-02  6.45291179E-02 -8.86563832E-02  6.45448771E-02  9.00810935E-02&#xA;-1.59827744E-01 -2.77950854E-02 -1.39023999E-02  1.38926855E-02  0.00000000E+00&#xA; 3.04938267E-02  3.05027864E-02 -1.91501878E-02 -4.18424802E-02  3.03668368E-01&#xA;-1.34786428E-01 -2.01270285E-01 -1.34786926E-01 -2.01266979E-01  3.68441953E-01&#xA; 2.06837032E-01 -1.25413382E-01 -6.27074976E-02  6.27058841E-02  7.78459520E+01&#xA; 4.78002374E-02 -1.23355319E-02  5.31942717E-02 -8.86563336E-02 -1.34786428E-01&#xA; 5.72465784E-01 -3.47913849E-01 -3.19509681E-02  3.82124777E-01 -4.39938925E-01&#xA; 1.65917376E-01  1.44129337E-01  2.18665399E-01  7.45360625E-02 -6.80511800E+00&#xA; 9.34030448E-02 -7.49650905E-02 -8.29810618E-02  6.45291179E-02 -2.01270285E-01&#xA;-3.47913849E-01  1.11839029E+00  3.82124891E-01 -5.42349371E-01 -4.08981216E-01&#xA;-2.25554975E-01 -1.06247502E-01  8.31603827E-03  1.14563541E-01  1.70127922E+00&#xA;-1.23337201E-02  4.77820938E-02  5.32006592E-02 -8.86563832E-02 -1.34786926E-01&#xA;-3.19509681E-02  3.82124891E-01  5.72467245E-01 -3.47916055E-01 -4.39937727E-01&#xA; 1.65917460E-01  1.44130988E-01 -7.45350363E-02 -2.18666024E-01  1.70128008E+00&#xA;-7.49599366E-02  9.34122780E-02 -8.29790123E-02  6.45448771E-02 -2.01266979E-01&#xA; 3.82124777E-01 -5.42349371E-01 -3.47916055E-01  1.11839152E+00 -4.08983943E-01&#xA;-2.25552099E-01 -1.06251760E-01 -1.14564521E-01 -8.31276143E-03  1.70127939E+00&#xA;-8.44033441E-02 -8.43965515E-02  7.87153470E-02  9.00810935E-02  3.68441953E-01&#xA;-4.39938925E-01 -4.08981216E-01 -4.39937727E-01 -4.08983943E-01  1.32939890E+00&#xA;-8.75646378E-02  4.96524369E-02  2.48257890E-02 -2.48266478E-02  1.70127933E+00&#xA; 5.90658770E-02  5.90646100E-02  4.16992065E-02 -1.59827744E-01  2.06837032E-01&#xA; 1.65917376E-01 -2.25554975E-01  1.65917460E-01 -2.25552099E-01 -8.75646378E-02&#xA; 4.56529024E-01  2.29232226E-02  1.14607952E-02 -1.14624275E-02  0.00000000E+00&#xA;-4.86412743E-02 -4.86546903E-02  1.25083636E-01 -2.77950854E-02 -1.25413382E-01&#xA; 1.44129337E-01 -1.06247502E-01  1.44130988E-01 -1.06251760E-01  4.96524369E-02&#xA; 2.29232226E-02  2.83728369E-01  1.41864449E-01 -1.41863920E-01  0.00000000E+00&#xA; 6.40541790E-02 -1.12696475E-01  6.25372507E-02 -1.39023999E-02 -6.27074976E-02&#xA; 2.18665399E-01  8.31603827E-03 -7.45350363E-02 -1.14564521E-01  2.48257890E-02&#xA; 1.14607952E-02  1.41864449E-01  2.88104389E-01  1.46239939E-01  0.00000000E+00&#xA; 1.12695453E-01 -6.40417842E-02 -6.25463857E-02  1.38926855E-02  6.27058841E-02&#xA; 7.45360625E-02  1.14563541E-01 -2.18666024E-01 -8.31276143E-03 -2.48266478E-02&#xA;-1.14624275E-02 -1.41863920E-01  1.46239939E-01  2.88103859E-01  3.11383808E+01&#xA; 0.00000000E+00  0.00000000E+00  0.00000000E+00  0.00000000E+00  7.78459520E+01&#xA;-6.80511800E+00  1.70127922E+00  1.70128008E+00  1.70127939E+00  1.70127933E+00&#xA; 0.00000000E+00  0.00000000E+00  0.00000000E+00  3.11383808E+01  0.00000000E+00&#xA;&#xA;Harmonic frequencies&#xA;F =3134.24   IR =  27.91   S = A&#xA;   3  -7   5    -31  -1   1      4   6   7    -28  72 -32     15   2 -40   &#xA;F =3134.23   IR =  27.91   S = A   &#xA;  -7   1   5     69   0   1     -5  -8  -4      1  -7   5     22   6 -66   &#xA;F =3134.22   IR =  27.91   S = A   &#xA;  -4  -6  -5     41  -1  -1     28  66  46     -7  15  -9    -10  -4  24   &#xA;F =3028.36   IR =   0.00   S = A&#xA;   0   0   0     50   0   0    -17 -38 -27    -17  43 -20    -17  -4  47   &#xA;F =1560.38   IR =   0.00   S = A   &#xA;   0   0   0      0 -33 -38     46 -20   0    -14  16  46    -32  37  -8   &#xA;F =1560.38   IR =   0.00   S = A   &#xA;   0   0   0      0  38 -33    -11 -25  42     45  21   6    -34 -33 -15   &#xA;F =1341.02   IR =  16.94   S = A&#xA;   0 -12  -4      0  57  19    -22   9 -15     15  16  38      4  59   5   &#xA;F =1341.02   IR =  16.94   S = A   &#xA;  -7   3 -10     -5 -15  47     24 -38  31     18  27  28     47 -12  10   &#xA;F =1341.02   IR =  16.94   S = A   &#xA; -10  -3   7     -8  12 -32     47   5 -37     52   6 -29     31   7  20   &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To receive the potential energy distribution I create the .dd2 file with VEDA and use the standard optimization options in Veda. I optimize the file until there is no more improvement in the Emp value calculated by VEDA.&lt;/p&gt;&#xA;&lt;p&gt;methan.vdf&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;abbreviation of: e:\bachelorarbeit\veda\methan\methan.ved&#xA;IR spectrum from file: e:\bachelorarbeit\veda\methan\methan.log&#xA;diagonality factor = 51.86   &amp;lt;EPm&amp;gt; = 53.85&#xA;    IR      CM-1&#xA;  27.91  3134.24  *8201.25   s2 48   s5 10   s9 29&#xA;  27.91  3134.23  *2652.43   s3 92&#xA;  27.91  3134.22  *1441.36   s2 -10   s5 -16   s9 57&#xA;   0.00  3028.36  *1434.71   s1 27   s7 -27   s8 37&#xA;   0.00  1560.38  *1382.52   s4 -15   s5 14   s7 31   s8 22&#xA;   0.00  1560.38  *1081.74   s4 55   s7 17   s8 16&#xA;  16.94  1341.02  * 885.94   s1 51   s5 22&#xA;  16.94  1341.02  * 447.29   s4 17   s6 76&#xA;  16.94  1341.02  *-8129.88   s2 -40   s5 39   s8 12&#xA;with (*) frequencies calculated by Veda&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;methan.dd2&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Average max. Potential Energy &amp;lt;EPm&amp;gt; = 53.852&#xA;TED Above 100 Factor TAF=0.000&#xA;Average coordinate population 1.333&#xA;Most complex coordinate No. 4 , population = 2 &#xA;s 1     1.00   STRE    1    4   CH    1.090476  f1435 27  f886 51&#xA;s 2     1.00   STRE    1    5   CH    1.090476  f8201 48  f1441 10  f8130 40&#xA;s 3     1.00   STRE    1    2   CH    1.090476  f2652 92&#xA;s 4     1.00   STRE    1    4   CH    1.090476  f1383 15  f1082 55  f447 17&#xA;        1.00           1    3   CH    1.090476&#xA;s 5     1.00   BEND    2    1    3   HCH   109.47  f8201 10  f1441 16  f1383 14  f886 22  f8130 39&#xA;        1.00           3    1    4   HCH   109.47&#xA;s 6     1.00   BEND    3    1    4   HCH   109.47  f447 76&#xA;s 7     1.00   BEND    4    1    5   HCH   109.47  f1435 27  f1383 31  f1082 17&#xA;        1.00           3    1    4   HCH   109.47&#xA;s 8     1.00   OUT     1    4    2    5   CHHH    19.47  f1435 37  f1383 22  f1082 16  f8130 12&#xA;s 9     1.00   OUT     1    3    2    4   CHHH    19.47  f8201 29  f1441 57&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why differ the calculated modes from methan.vdf file to this extent in comparison to the calculated modes from gaussian? Is there an error in my input, which results in that difference?&#xA;The calculations of methane should result in CH-stretching vibrations at 3000 1/cm. The assignment by VEDA for the mode at 3134.23 1/cm from the gaussian log file or 2652.43 1/cm calculated by VEDA seems right. The other modes over 3000 1/cm are partly assigned to the bending-vibrations s5 and out-of-plane-vibrations s9 which are described in the dd2 file. I do not understand why the VEDA program assigns these vibrations to a mode at 3000 1/cm. In a vibration visualization by VEDA and other programs, the modes calculated over 3000 1/cm are clearly identified as CH-stretching vibrations.&lt;/p&gt;&#xA;" OwnerUserId="1682" LastEditorUserId="1682" LastEditDate="2021-10-18T07:22:21.797" LastActivityDate="2021-10-20T22:55:50.470" Title="How to use VEDA to analyze vibrational energy distribution?" Tags="|software|software-assistance|software-input-file-request|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6896" PostTypeId="2" ParentId="6819" CreationDate="2021-10-14T15:34:14.020" Score="6" Body="&lt;p&gt;I'm posting this here as an answer so that if anyone else runs into the same problem, they can get it clarified.&lt;/p&gt;&#xA;&lt;p&gt;After searching endlessly (because the &lt;a href=&quot;https://siesta-project.org/siesta/&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt; to &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/tutorial&quot; rel=&quot;noreferrer&quot;&gt;BoltzTraP2&lt;/a&gt; interface provided by the developers failed), I figured it out by myself. What happened was a problem of the k-point output file from SIESTA not being what BoltzTraP2 expects.&lt;/p&gt;&#xA;&lt;p&gt;If you are working to link the two packages, follow the &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/siesta&quot; rel=&quot;noreferrer&quot;&gt;instructions&lt;/a&gt; provided in their wiki with one exception. At the place where the SYSTEM_NAME.KP file is read by BoltzTraP2, make sure to multiply the array of k-points by 2 before being used by BoltzTraP2.&lt;/p&gt;&#xA;&lt;p&gt;Also, the BoltzTraP2 package works with a gamma centered, uniform k-grid. To achieve this, the best way would be to use odd number of k-points (to have equal numbers of k-points on each side of the gamma point) and to set &lt;code&gt;0.&lt;/code&gt; to the &lt;code&gt;dk&lt;/code&gt; value (to obtain a gamma centered grid). However, I cannot verify this statement for every unit cell implementation. So in such a case, plot the k-points generated by the Monkhorst-Pack scheme and see if the resultant grid is uniform or not.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, the current version of BoltzTraP2 does not support non-periodic boundary conditions. To analyze non-periodic systems, I currently set 3 k-points in the non-periodic direction (which includes a vacuum and so no interactions would be present between adjacent unit cell images) and ignore the BoltzTraP2 results for that direction. I am also working on a modification to the code to enable support for 2D and 1D systems, and shall update this thread if I succeed.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-14T15:34:14.020" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6897" PostTypeId="1" AcceptedAnswerId="6903" CreationDate="2021-10-16T04:39:06.580" Score="5" ViewCount="159" Body="&lt;p&gt;When it comes to studying 2D, 1D or 0D nanomaterials, saturating the dangling bonds in the surface helps remove unwanted localized surface states from the band structure &lt;a href=&quot;https://www.nature.com/articles/s41598-021-92936-z&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;. However, so far I have not found an ideal way to conduct this saturation process.&lt;/p&gt;&#xA;&lt;p&gt;My current procedure includes using the &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; software to add H to the surface (of Si and Ge nanostructures). However this package treats any structure as a molecule, and adds H to the periodic directions as well (and I later delete the extra atoms and edit the structure manually). Are there any other &lt;code&gt;free alternatives&lt;/code&gt; which can be used?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-16T22:25:37.753" Title="Tool to saturate the dangling bonds at the surface of nanostructures" Tags="|density-functional-theory|band-structure|siesta|avogadro|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="6898" PostTypeId="1" CreationDate="2021-10-16T14:12:34.363" Score="4" ViewCount="907" Body="&lt;p&gt;I found the only parameter related to pressure is Pstress tag in VASP. But the pressure of Pstress tag is Hydrostatic pressure, while I only want to put stress along z-axis. Could you please help me with this problem?&#xA;Any advice will be highly appreciated! Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4428" LastActivityDate="2021-10-16T22:20:15.973" Title="In VASP, how to perform putting normal stress , with the parameter -PSTRESS?" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6899" PostTypeId="2" ParentId="6829" CreationDate="2021-10-16T15:54:38.250" Score="9" Body="&lt;p&gt;Have you already tried the &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2008-September/010153.html&quot; rel=&quot;noreferrer&quot;&gt;Pw_forum&lt;/a&gt;?&lt;/p&gt;&#xA;&lt;p&gt;I do not use QE and so cannot directly answer your question. However, I'd say that this is one of those things where you are better off finding either a tutorial (in places such as &lt;a href=&quot;https://www.youtube.com/&quot; rel=&quot;noreferrer&quot;&gt;YouTube&lt;/a&gt;) or someone you know with experience in compiling software for linux (just to make sure that your compilation is successful).&lt;/p&gt;&#xA;&lt;p&gt;That said, the basic idea is that you should already have the &lt;a href=&quot;https://gitlab.com/QEF/q-e-gpu/-/wikis/home&quot; rel=&quot;noreferrer&quot;&gt;GPU enabled version of QE&lt;/a&gt; installed (which you say you have already done). So read through the QE user guide sections 2.3 and 2.4 as mentioned in the comments by user @147875 and you might find a clue to the required flags when running the &lt;code&gt;pw.x&lt;/code&gt; command.&lt;/p&gt;&#xA;&lt;p&gt;A. If you check and find that the GPU enabled version is already installed. It should simply be a matter of either adding an additional line such as &lt;code&gt;package gpu 1&lt;/code&gt; to your input script, or even a command line flag which should be added to the command that you currently use to run QE. You can contact the &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2008-September/010153.html&quot; rel=&quot;noreferrer&quot;&gt;Pw_forum&lt;/a&gt; regarding this.&lt;/p&gt;&#xA;&lt;p&gt;B. In any case if you haven't got the GPU enabled version installed properly, the basic steps should be as follows. So try to figure out where you went wrong.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Install matching &lt;a href=&quot;https://www.nvidia.com/Download/index.aspx&quot; rel=&quot;noreferrer&quot;&gt;NVIDIA drivers&lt;/a&gt; and the &lt;a href=&quot;https://developer.nvidia.com/cuda-downloads&quot; rel=&quot;noreferrer&quot;&gt;CUDA toolkit&lt;/a&gt;: Typing &lt;code&gt;nvidia-smi&lt;/code&gt; in a terminal will spit out details of the current CUDA version and NVIDIA driver version if they are both installed. If not, follow the &lt;a href=&quot;https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html&quot; rel=&quot;noreferrer&quot;&gt;guidelines&lt;/a&gt; given by NVIDIA.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Get the CUDA enabled version of QE and compile it with the appropriate flags: You should be able to find information regarding these in either the &lt;a href=&quot;http://www.quantum-espresso.org/Doc/user_guide.pdf&quot; rel=&quot;noreferrer&quot;&gt;user manual&lt;/a&gt;, or this &lt;a href=&quot;https://forums.developer.nvidia.com/t/problems-installing-quantum-epsresso-with-gpu-acceleration/189908&quot; rel=&quot;noreferrer&quot;&gt;question on the NVIDIA forum&lt;/a&gt;, or this &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2016-August/036172.html&quot; rel=&quot;noreferrer&quot;&gt;Tutorial&lt;/a&gt; posted in the QE forums.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Once that is done, you should have a CUDA enabled version of QE installed in your system. In this case, you are now back to what I mentioned in the step &lt;code&gt;A&lt;/code&gt; earlier.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;C. Alternatively, read through this &lt;a href=&quot;https://github.com/anmolpanda/QE-GPU&quot; rel=&quot;noreferrer&quot;&gt;GitHub link&lt;/a&gt; they seem to have a way to patch an existing version of QE to work with CUDA. However, I cannot confirm if it is successful or not.&lt;/p&gt;&#xA;&lt;p&gt;Note: I provided this answer since nobody had answered your question and understand what it is like to be stuck in a situation like this. Keep in mind that even the most detailed tutorials and guidelines may not directly work for your system (which means that your compiled version of QE may not have GPU enabled). It all depends on the linux distribution and version you are running, the available compilers, the places where the compilers and the libraries are installed etc. So in that way, every computer can be considered as unique. But the &lt;a href=&quot;https://askubuntu.com/&quot;&gt;Ask Ubuntu&lt;/a&gt; and &lt;a href=&quot;https://stackoverflow.com/&quot;&gt;Stack Overflow&lt;/a&gt; communities along with the forums of the software that you are compiling could prove to be really helpful.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-16T15:54:38.250" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6900" PostTypeId="1" AcceptedAnswerId="6901" CreationDate="2021-10-16T21:56:36.160" Score="5" ViewCount="130" Body="&lt;p&gt;For example, in something like the General Utility Lattice Program, you perform structural optimisation and then use phonons to calculate properties like elastic constants etc.&lt;/p&gt;&#xA;&lt;p&gt;The latter part seems to me to be quit obviously Lattice Dynamics, but would structural optimisation be Lattice Statics or Dynamics?&lt;/p&gt;&#xA;" OwnerUserId="4220" LastActivityDate="2021-10-16T22:15:40.010" Title="What's the Difference between Lattice Statics and Lattice Dynamics?" Tags="|cell-optimization|lattice-dynamics|optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6901" PostTypeId="2" ParentId="6900" CreationDate="2021-10-16T22:15:40.010" Score="8" Body="&lt;p&gt;Lattice statics refer more to the minimum energy lattice structure such as spacegroup, lattice constant, bond distances, or any other property you can derive from a geometric standpoint on that optimized structure.  I don't think I would consider the actual optimization to be lattice statics, more of a way to get to the lattice statics.&lt;/p&gt;&#xA;&lt;p&gt;Lattice dynamics such as phonon calculations help look at the excited states of the lattice to determine things such as thermal conductivity, infrared spectra, Raman spectra, or thermodynamic properties that depend on temperature.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-16T22:15:40.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6902" PostTypeId="2" ParentId="6898" CreationDate="2021-10-16T22:20:15.973" Score="1" Body="&lt;p&gt;If the stress tensor is calculated by setting ISIF appropriately, then you can read the stress from the OUTCAR.  There is no way to apply an axial stress from tags, however you can do a geometry optimization to 0 stress, then manually stress the cell in the Z direction by modifying the cell.  You will need to do this for multiple volumes then fit a relationship between volume to stress and determine the volume needed for your desired stress.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-16T22:20:15.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6903" PostTypeId="2" ParentId="6897" CreationDate="2021-10-16T22:25:37.753" Score="4" Body="&lt;p&gt;Atomic simulation environment can do this with the following line of logic.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculate the number of nearest neighbors for all atoms&lt;/li&gt;&#xA;&lt;li&gt;Select the undercoordinated atoms&lt;/li&gt;&#xA;&lt;li&gt;Calculate the direction away from the neighbors (sum vectors from&#xA;neighbor-&amp;gt;atom and normalize)&lt;/li&gt;&#xA;&lt;li&gt;Add your atom to cover the dangling bonds, such as H, in direction&#xA;of calculated vector&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A working example of this might be difficult without a concrete system to work with and explore, however this will probably be somewhat fiddly work where you need to tune everything for your specific system.  I also suspect that is why not many tools exist to do this out of the box.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-16T22:25:37.753" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6904" PostTypeId="1" AcceptedAnswerId="6907" CreationDate="2021-10-17T01:57:21.493" Score="10" ViewCount="363" Body="&lt;p&gt;Consider the following situation that&#xA;the exchange-correlation term (e.g., B3LYP) overestimates the energy in a system&#xA;(i.e., a simpler one (e.g., LDA) is sufficient in the system).&#xA;In this case, my question is that,&#xA;will the obtained density be incorrect,&#xA;that is, will the parameters in LCAO (i.e., orbital superposition) be incorrect&#xA;even if the energy accuracy calculated by B3LYP is very good?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/E40bd.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/E40bd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In other words, does good accurate energy calculated&#xA;using a complex energy functional always guarantee the correct density?&#xA;I am wondering that an overestimated energy functional can output the accurate energy even if the LCAO parameters (i.e., coefficient in orbital superposition) are incorrect and this will lead to the incorrect density.&lt;/p&gt;&#xA;&lt;p&gt;I also found the discussion and in the Science paper&#xA;(&amp;quot;&lt;a href=&quot;https://www.science.org/doi/full/10.1126/science.aah5975&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Density functional theory is straying from&#xA;the path toward the exact functional&lt;/em&gt;&lt;/a&gt;&amp;quot; and its &lt;a href=&quot;https://www.science.org/doi/10.1126/science.aam9364&quot; rel=&quot;noreferrer&quot;&gt;comment&lt;/a&gt;).&#xA;Especially in recent years in machine learning research,&#xA;very complicated deep learning models with over ten million parameters&#xA;have been developed and successfully predicted the energy of various molecules&#xA;(e.g., &lt;a href=&quot;https://arxiv.org/pdf/2003.03123.pdf&quot; rel=&quot;noreferrer&quot;&gt;molecular graph message passing model&lt;/a&gt; and &lt;a href=&quot;https://arxiv.org/pdf/2106.14583.pdf&quot; rel=&quot;noreferrer&quot;&gt;neural network potential&lt;/a&gt;)&#xA;However, such deep models seem to completely ignore the density.&#xA;I am wondering that such overparameterized models are good or not&#xA;for both energy and density.&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-10-17T04:08:04.453" LastActivityDate="2021-10-17T11:24:03.093" Title="Accuracy trade-off between energy and density in DFT calculations" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6905" PostTypeId="1" CreationDate="2021-10-17T05:36:06.290" Score="9" ViewCount="709" Body="&lt;p&gt;I'm trying to calculate the magnetic anisotropy energy of  Cr&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt; by comparing the total energy difference of the system in different spin configurations (in-plane and out-of-plane). However, when doing VASP scf calculations with Hubbard U settings, the calculation did not converge for 400+ electronic steps.&lt;/p&gt;&#xA;&lt;p&gt;I read from the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/BMIX&quot; rel=&quot;nofollow noreferrer&quot;&gt;vasp wiki&lt;/a&gt; that you can set the optimal &lt;code&gt;AMIX&lt;/code&gt; by looking at the &lt;code&gt;GAMMA&lt;/code&gt; value in OUTCAR:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In VASP the eigenvalue spectrum of the charge dielectric matrix is calculated and written to the OUTCAR file at each electronic step. This allows a rather easy optimization of the mixing parameters, if required. Search in the OUTCAR file for&#xA;eigenvalues of (default mixing * dielectric matrix)&#xA;The parameters for the mixing are optimal if the mean eigenvalue Γmean=1, and if the width of the eigenvalue spectrum is minimal. For an initial linear mixing (BMIX≈0) an optimal setting for AMIX can be found easily by setting AMIXoptimal=AMIXcurrent*Γmean.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But my question is, &lt;strong&gt;how to adjust the &lt;code&gt;AMIX_MAG&lt;/code&gt; and &lt;code&gt;BMIX_MAG&lt;/code&gt; parameters for magnetic system calculations?&lt;/strong&gt; Are there some guidelines on how to efficiently adjust them for optimal calculation speed?&lt;/p&gt;&#xA;" OwnerUserId="3924" LastEditorUserId="5" LastEditDate="2022-01-14T01:57:17.130" LastActivityDate="2022-01-14T01:57:17.130" Title="How to efficiently adjust the AMIX_MAG and BMIX_MAG parameter in VASP calculations?" Tags="|vasp|software|" AnswerCount="0" CommentCount="3" ClosedDate="2022-08-05T01:57:41.443" ContentLicense="CC BY-SA 4.0" />
  <row Id="6906" PostTypeId="2" ParentId="6850" CreationDate="2021-10-17T08:33:59.770" Score="4" Body="&lt;pre&gt;&lt;code&gt;file=test.pdb #pdb file &#xA;frame=10 # frame number to extract &#xA;x_frame=&lt;span class=&quot;math-container&quot;&gt;$(egrep &quot;MODEL.* $&lt;/span&gt;frame&lt;span class=&quot;math-container&quot;&gt;$&quot; $&lt;/span&gt;file)&#xA;sed -n &amp;quot;/&lt;span class=&quot;math-container&quot;&gt;$x_frame/,/ENDMDL/p&quot; $&lt;/span&gt;file &amp;gt; &lt;span class=&quot;math-container&quot;&gt;${file::-4}_frame_$&lt;/span&gt;frame.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;output file will be written as filename_frame_10.pdb&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The bash script below provides easier (repeated) access to the functionality described:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;#!/bin/bash&#xA;&#xA;# Extract a specific .pdb from a multi model .pdb file&#xA;&#xA;# Save this bash script as pick_pdb.sh and run&#xA;#&#xA;# bash pick_pdb.sh test.pdb 3&#xA;#&#xA;# to write test_frame_3.pdb as new file.  Relies on bash and sed.&#xA;&#xA;if [[ -z &amp;quot;$1&amp;quot; ]] ; then&#xA;    printf &amp;quot;Check how to use this bash script with&#xA;        bash pick_pdb.sh -h  \n&amp;quot;&#xA;&#xA;elif [[ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$1&quot; == &quot;-h&quot; || &quot;$&lt;/span&gt;1&amp;quot; == &amp;quot;--help&amp;quot; ]] ; then&#xA;    printf &amp;quot;Export a specific model from multi model .pdb file.&#xA;&#xA;E.g., to extract the third model from intput.pdb,&#xA;&#xA;    bash pick_pdb.sh input.pdb 3&#xA;&#xA;writes file input_frame_2.pdb.  \n&amp;quot;&#xA;&#xA;&#xA;else&#xA;    file=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$1&quot;&#xA;frame=&quot;$&lt;/span&gt;2&amp;quot;&#xA;&#xA;    filebase=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$(basename &quot;$&lt;/span&gt;file&amp;quot; .pdb)&amp;quot;&#xA;    output=&lt;span class=&quot;math-container&quot;&gt;${filebase}_frame_$&lt;/span&gt;frame.pdb&#xA;&#xA;    x_frame=&lt;span class=&quot;math-container&quot;&gt;$(egrep &quot;MODEL.* $&lt;/span&gt;frame&lt;span class=&quot;math-container&quot;&gt;$&quot; &quot;$&lt;/span&gt;file&amp;quot;)&#xA;    sed -n &amp;quot;/&lt;span class=&quot;math-container&quot;&gt;$x_frame/,/ENDMDL/p&quot; &quot;$&lt;/span&gt;file&amp;quot; &amp;gt; &amp;quot;$output&amp;quot;&#xA;fi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="125" LastEditorUserId="1206" LastEditDate="2021-10-18T15:07:16.327" LastActivityDate="2021-10-18T15:07:16.327" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6907" PostTypeId="2" ParentId="6904" CreationDate="2021-10-17T08:58:31.740" Score="9" Body="&lt;p&gt;If a functional always gives the exact energy for arbitrary external potentials, then it is easy to see that the functional must always give the exact density. Consider two DFT calculations, one with an external potential &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})$&lt;/span&gt;, and another with the potential &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r}) + \epsilon\delta(\mathbf{r}_0)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is infinitesimal. By perturbation theory, the energy difference between the two systems is &lt;span class=&quot;math-container&quot;&gt;$-\epsilon\rho(\mathbf{r}_0) + O(\epsilon^2)$&lt;/span&gt;. So if the functional gives exact energies, it must give exact &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r}_0)$&lt;/span&gt; at an arbitrary point &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;That being said, there may well exist functionals that give good (but not exact) energies but bad densities, e.g. as mentioned in the Science paper you cited. Or there may even exist functionals that give exact energies for systems composed of integer-charge atomic nuclei, but bad densities; since the functionals are not required to be exact for external potentials that cannot be expressed as a sum of integer-charge Coulomb attraction potentials, my proof doesn't work. It is especially the possible presence of the latter class of functionals that suggests that fitting a functional against only energies does not necessarily improve the density, even if the training set approaches completeness. Including properties that directly reflect the density distribution, e.g. dipole moments, in the parameterization, may ease this problem to some extent, although the best remedy is to explicitly include densities in the fitting. Another possible way is to fit the functional against non-Coulomb external potentials, but I doubt if this has ever been done, except for the trivial cases where the external potential is a sum of atomic pseudopotentials, or where the external potential is a jellium etc.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-10-17T11:24:03.093" LastActivityDate="2021-10-17T11:24:03.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6908" PostTypeId="1" AcceptedAnswerId="7019" CreationDate="2021-10-17T14:18:35.190" Score="11" ViewCount="499" Body="&lt;p&gt;I read a &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/cm203303y&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; and the authors wrote they use AIMD to estimate the ionic diffusivity of materials. I wonder steps to obtain the value at different temperatures. What are the input and output of calculations in VASP?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2021-10-17T17:17:10.763" LastActivityDate="2021-11-08T01:36:39.330" Title="Steps to obtain ionic diffusivity using AIMD" Tags="|vasp|software-input-file-request|aimd|" AnswerCount="1" CommentCount="1" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6910" PostTypeId="1" CreationDate="2021-10-17T16:28:30.997" Score="7" ViewCount="74" Body="&lt;p&gt;Electronic circular dichroism (ECD) spectra is commonly used in organic chemistry to characterize chiral molecules. Here the question is how to simulate ECD spectra using MCTDH (Multi-configurational time-dependent Hartree)? It would be nice if the answers could provide explicit formulas.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2022-01-14T01:58:00.550" LastActivityDate="2022-01-14T01:58:00.550" Title="How to calculate electronic circular dichroism (ECD) spectra from MCTDH?" Tags="|spectroscopy|quantum-dynamics|" AnswerCount="0" CommentCount="6" ClosedDate="2023-02-16T01:20:06.863" ContentLicense="CC BY-SA 4.0" />
  <row Id="6912" PostTypeId="1" CreationDate="2021-10-17T19:16:34.030" Score="6" ViewCount="259" Body="&lt;p&gt;I am going to simulate the electronic structure of the &lt;strong&gt;Au 111 surface including Fe-centered porphyrin&lt;/strong&gt; on top. Since the molecule includes Fe, I first did spin-polarized calculations. Using converged parameters, I found a value of ~2 for the spin moment along S_z (&lt;code&gt;spin moment: S , {S} =    2.11024       0.0       0.0   2.11024&lt;/code&gt;). The freestanding molecule also results in a quite similar spin moment.&lt;/p&gt;&#xA;&lt;p&gt;To study spin anisotropy, then, I started SOC. Considering stringent MeshCutoff, tolerance in Hamiltonian, and density with a fine kgrid, I found an odd value of S=4.7 for Au surface + Fe_porphyrin&#xA;&lt;code&gt;spin moment: S , {S} =    4.67450  -3.29554  -3.31518  -0.00096&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I had defined the initial DM as below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block DM.InitSpin&#xA;Fe_index  2.0    0.0     0.0&#xA;%endblock DM.InitSpin&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which means that the Fe atom starts with 2 unpaired when the S vector is along Z axes.&lt;/p&gt;&#xA;&lt;p&gt;A Mulliken charge analysis says the extra spin moment stems from the Au surface. I am struggling with this and therefore, any advice will be highly appreciated! Thanks!&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Both &lt;strong&gt;SIESTA/4.1-b4&lt;/strong&gt; and &lt;strong&gt;Siesta/4.1.5&lt;/strong&gt; result in the same S value with a slight difference of hundredth.&lt;/li&gt;&#xA;&lt;li&gt;PPs are blyp and consist of required relativistic effects.&lt;/li&gt;&#xA;&lt;li&gt;Atomic positions were highly optimized.&lt;/li&gt;&#xA;&lt;li&gt;DZP was used for all elements.&#xA;A Gamma-centered &lt;code&gt;kgrid_Monkhorst_Pack&lt;/code&gt; of 5x5x1 is used while a coarser grid is sufficient for converging the &lt;code&gt;E_tot&lt;/code&gt; in spin-polarized calculations.&lt;/li&gt;&#xA;&lt;li&gt;VDW-KBM is also applied&lt;/li&gt;&#xA;&lt;li&gt;Tolerance of DM, H, and EDM is ten to the power of -6, -5, and -3, respectively.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4435" LastEditorUserId="7" LastEditDate="2022-01-14T03:14:31.790" LastActivityDate="2022-01-14T03:14:31.790" Title="Spin-orbit coupling in Siesta" Tags="|surfaces|spin-orbit-coupling|siesta|" AnswerCount="0" CommentCount="8" ClosedDate="2022-02-24T20:53:07.097" ContentLicense="CC BY-SA 4.0" />
  <row Id="6913" PostTypeId="1" CreationDate="2021-10-18T09:46:05.560" Score="13" ViewCount="258" Body="&lt;p&gt;In computational chemistry, I have come across many test sets which are used to benchmark a new method. For example, the G2 test set for thermochemical calculations (heats of formation). There is the SAMPL-1 set for hydration free energies. These sets usually have a diverse range of molecules/species of interest so that it is possible to check if the new method has a problem in modelling a particular class of molecules.&lt;/p&gt;&#xA;&lt;p&gt;I am currently working on predicting UV-vis absoprtion band of organic molecules (i.e. the &lt;span class=&quot;math-container&quot;&gt;$\lambda_{max}$&lt;/span&gt;) with statistical learning. So I was wondering if there is a robust benchmark test set with UV-vis data (with experimental results) which I can use for my purpose. I haven't found much with google searches so far.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="7" LastEditDate="2021-11-10T18:06:48.480" LastActivityDate="2021-11-10T18:06:48.480" Title="Are there any benchmark test sets for UV-vis absorption maxima?" Tags="|reference-request|one-topic-per-answer|spectroscopy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6914" PostTypeId="2" ParentId="6913" CreationDate="2021-10-18T17:17:26.723" Score="12" Body="&lt;p&gt;There is a program called PhotochemCAD by Tanuchi and Lindsey which contains a database of experimental absorption and emission spectra of more than 300 organic and organometallic compounds. The spectra are available in plain text form. While the maximum absorption wavelengths of the most intense peaks of each compound have already been tabulated in the main text of the linked article, if you are also interested in the absorption maxima of weaker peaks too, you may need to extract this information from the spectra by yourself.&lt;/p&gt;&#xA;&lt;p&gt;By the way, given that the database contains complete spectra information, it may actually be a good idea to train your model to reproduce the overall line shape instead of just the absorption maxima, giving an even more useful model :)&lt;/p&gt;&#xA;&lt;p&gt;Taniguchi, M.; Lindsey J. S. &lt;em&gt;Database of Absorption and Fluorescence Spectra of &amp;gt;300 Common Compounds for use in PhotochemCAD&lt;/em&gt; in &lt;em&gt;Photochem. Photobiol.&lt;/em&gt; &lt;strong&gt;2018&lt;/strong&gt;, &lt;em&gt;94&lt;/em&gt;, 90-327; &lt;a href=&quot;https://doi.org/10.1111/php.12860&quot; rel=&quot;noreferrer&quot;&gt;doi 10.1111/php.12860&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Project page: &lt;a href=&quot;https://www.photochemcad.com/&quot; rel=&quot;noreferrer&quot;&gt;https://www.photochemcad.com/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="1206" LastEditDate="2021-10-18T17:29:30.017" LastActivityDate="2021-10-18T17:29:30.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6915" PostTypeId="1" CreationDate="2021-10-18T18:20:48.720" Score="8" ViewCount="132" Body="&lt;p&gt;I have a set of molecular dimers (~25 atoms) for which DFT-D3 interaction energies are calculated by Psi4 and Turbomole program. Now I want to compare these values against Force-Field methods like UFF/Amber/OPLS. I have known that in Gromacs or Amber suite of programs can do that but for these small systems, I think those will be overkill.&#xA;Any suggestion of programs which can calculate single point energies of the small dimers?&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="5" LastEditDate="2021-11-18T06:10:00.790" LastActivityDate="2021-11-18T06:10:00.790" Title="Calculate FF interaction energy of small molecular dimers" Tags="|density-functional-theory|gromacs|forcefields|turbomole|amber|" AnswerCount="0" CommentCount="15" ClosedDate="2022-01-27T04:29:49.737" ContentLicense="CC BY-SA 4.0" />
  <row Id="6917" PostTypeId="2" ParentId="1606" CreationDate="2021-10-18T21:25:53.257" Score="5" Body="&lt;p&gt;If the content of the &lt;code&gt;.cif&lt;/code&gt; in question is &lt;em&gt;fairly&lt;/em&gt; molecule-like, my recommendation are the &lt;a href=&quot;https://wiki.crystallography.net/cod-tools/&quot; rel=&quot;noreferrer&quot;&gt;cod-tools&lt;/a&gt; collection by the &lt;a href=&quot;http://www.crystallography.net/cod/index.php&quot; rel=&quot;noreferrer&quot;&gt;Crystallography Open Database&lt;/a&gt;.  These may be obtained directly from their web site; if you use Debian 10/buster or Ubuntu 18.10LTS and higher, you equally find them in the the repositories (&lt;a href=&quot;https://tracker.debian.org/pkg/cod-tools&quot; rel=&quot;noreferrer&quot;&gt;DebiChem tracker&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;A typical extraction follows the pattern of&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;codcif2sdf input.cif &amp;gt; output.sdf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to write a new record (v2000 style). This works quite well, &lt;em&gt;not only&lt;/em&gt; for &lt;code&gt;.cif&lt;/code&gt; by the COD, but equally from other databases (including &lt;code&gt;.cif&lt;/code&gt; the CSD file by CCDC if you forgot the direct export of &lt;code&gt;.mol2&lt;/code&gt; from the database), too.  The &lt;code&gt;cod-tools&lt;/code&gt; collection shines especially with unit cells of higher space group symmetries where a small number of unique atoms suffice to put the molecule together.&lt;/p&gt;&#xA;&lt;p&gt;On occasion, an adjustment of bond orders may be necessary; e.g. in triazines like &lt;a href=&quot;http://www.crystallography.net/cod/2102215.html&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; by COD where all six aromatic bonds between carbon and nitrogen are as double, instead as an aromatic bond.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-10-18T21:25:53.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6918" PostTypeId="1" AcceptedAnswerId="6919" CreationDate="2021-10-19T09:47:42.643" Score="7" ViewCount="956" Body="&lt;p&gt;I was facing convergence problems in my 2D system, but after I have used the &lt;code&gt;ALGO = All&lt;/code&gt; tag the convergence problems have gone.&#xA;I would like to know how accurate is this option comparing to &lt;code&gt;ALGO = Normal&lt;/code&gt; and &lt;code&gt;ALGO = Fast&lt;/code&gt; options.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-10-19T18:32:39.023" Title="How accurate is ALGO= All in VASP?" Tags="|vasp|convergence-test|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6919" PostTypeId="2" ParentId="6918" CreationDate="2021-10-19T18:32:39.023" Score="5" Body="&lt;p&gt;&lt;code&gt;ALGO&lt;/code&gt; only refers to the method used to reach convergence, as a result there is no difference in accuracy.  &lt;code&gt;ALGO = Normal / Fast&lt;/code&gt; tends to be faster than &lt;code&gt;ALGO = All&lt;/code&gt;, however this can be system / level of theory dependent.&lt;/p&gt;&#xA;&lt;p&gt;It should be noted, this isn't strictly true since you can optimize to a different ground state minimum.  This can result in a different magnetic structure in some cases, but I have never seen this problem in practice.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-19T18:32:39.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6920" PostTypeId="1" AcceptedAnswerId="6946" CreationDate="2021-10-20T01:35:06.153" Score="8" ViewCount="82" Body="&lt;h3&gt;Background&lt;/h3&gt;&#xA;&lt;p&gt;Quasiparticle interference (QPI) is a technique that can be used to study 2D surface state band structure; carrier reflections at boundaries or impurity sites will interfere producing standing waves which can be imaged by STM. Plotting the periods of the standing waves vary with STM tip bias (by Fourier transform analysis of the dI/dV STM images) produces &lt;span class=&quot;math-container&quot;&gt;$E(\mathbf{k})$&lt;/span&gt;-like plots that can be directly compared to band structures measured via photoelectron emission spectroscopy (&lt;a href=&quot;https://en.wikipedia.org/wiki/Angle-resolved_photoemission_spectroscopy&quot; rel=&quot;nofollow noreferrer&quot;&gt;ARPES&lt;/a&gt;) and predicted via DFT.&lt;/p&gt;&#xA;&lt;p&gt;We have a system where grain boundaries are not showing QPI in a situation where one would expect to see it. There can be (more than) several explanations for this.&lt;/p&gt;&#xA;&lt;p&gt;One I'd like to explore is that there's something about this interface that is &lt;em&gt;non-reflective&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Question&lt;/h3&gt;&#xA;&lt;p&gt;In optics it's easy to make antireflection coatings. The simplest and most well known is the quarter-wave index-matching layer with &lt;span class=&quot;math-container&quot;&gt;$n_{\lambda / 4} = \sqrt{n_1 n_2}$&lt;/span&gt; but this has a limited range of wavelengths for which it is effective. Another transmissive technique is a slow gradient in index, and if absorption (complex &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) is allowed one can impedance match to free space. Broadband AR coatings are optimized designs with multiple layers of different indices and thicknesses.&lt;/p&gt;&#xA;&lt;p&gt;I have some history/background/familiarity with optics but not in QM. Nevertheless I must give this a try.&lt;/p&gt;&#xA;&lt;p&gt;If I'm solving the 1D Schrodinger's equation for a wave incident on a surface defined by a change in potential, what quantity is most analogous to index of refraction from the perspective of antireflection optimization?&lt;/p&gt;&#xA;&lt;p&gt;Is it energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\sqrt{E}$&lt;/span&gt; or does it turn out to be something I shouldn't actually vary like effective mass? Or something else? Or none-of-the-above?&lt;/p&gt;&#xA;&lt;p&gt;Potentially helpful but I'm not really sure as it focuses on enhanced tunneling rather than reflection of a freely propagating wave: &lt;a href=&quot;https://www.nature.com/articles/s41598-017-13028-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;Antireflection coating of barriers to enhance electron tunnelling: exploring the matter wave analogy of superluminal optical phase velocity&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Famous IBM image of QPI standing waves for background only&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lGHhs.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lGHhs.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://www.nisenet.org/catalog/scientific-image-quantum-corral-top-view&quot; rel=&quot;nofollow noreferrer&quot;&gt;Scientific Image - Quantum Corral (top view)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The corral is an artificial structure created from 48 iron atoms (the sharp peaks) on a copper surface. The wave patterns in this scanning tunneling microscope image are formed by copper electrons confined by the iron atoms. Don Eigler and colleagues created this structure in 1993 by using the tip of a low-temperature scanning tunneling microscope (STM) to position iron atoms on a copper surface, creating an electron-trapping barrier. This was the first successful attempt at manipulating individual atoms and led to the development of new techniques for nanoscale construction.&lt;/p&gt;&#xA;&lt;p&gt;SIZE: The radius of the corral is about 7 nm.&lt;/p&gt;&#xA;&lt;p&gt;IMAGING TOOL: Scanning tunneling microscope&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2021-10-21T19:02:23.140" LastActivityDate="2021-10-26T17:51:41.940" Title="Quantum mechanical antireflection coating; what quantity would be analogous to index of refraction?" Tags="|quantum-mechanics|surfaces|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6922" PostTypeId="1" CreationDate="2021-10-20T21:36:54.270" Score="10" ViewCount="215" Body="&lt;p&gt;When it comes to improving the accuracy of DFT calculations, there is a well known hierarchy:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;starting from LDA using &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;proceeding with GGA and its &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[ n, \nabla n]$&lt;/span&gt; dependency&lt;/li&gt;&#xA;&lt;li&gt;and finally meta-GGAs with  &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[ n, \nabla n, \nabla^2n~\text{or}~\nabla^2\phi_i]$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I always wondered why higher order derivatives are not used but  never really looked into it. Recently I heard from an expert in the field  that it can be shown that &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt; can not converge in the sense of a Taylor series.&lt;/p&gt;&#xA;&lt;p&gt;How? Why?&lt;/p&gt;&#xA;&lt;p&gt;I just couldn't find more on this matter.&lt;/p&gt;&#xA;" OwnerUserId="3901" LastEditorUserId="3901" LastEditDate="2021-10-20T21:57:50.697" LastActivityDate="2021-10-21T16:38:50.847" Title="Non-Convergence of the XC functional in the sense of a Taylor series" Tags="|density-functional-theory|exchange-correlation|" AnswerCount="2" CommentCount="1" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6923" PostTypeId="2" ParentId="6895" CreationDate="2021-10-20T22:55:50.470" Score="5" Body="&lt;p&gt;After some experimentation, I was able to track down the problem.&lt;/p&gt;&#xA;&lt;p&gt;Your output files tell me that you are using Gaussian 16. Upon inspection, the formchk utility in that version seems to put an &amp;quot;Internal Force Constants&amp;quot; section into the formatted checkpoint file in addition to the &amp;quot;Cartesian Force Constants&amp;quot; that VEDA is expecting. Thus, VEDA gets tripped up and reads junk from the file. You can confirm this by deleting that &amp;quot;Internal&amp;quot; section from the formchk file, or even just mangling the word &amp;quot;Force&amp;quot; in the title line so that VEDA doesn't pick it up anymore. Then the results are reasonable again.&lt;/p&gt;&#xA;&lt;p&gt;I did my tests with Gaussian 09, where the formchk utility doesn't print those problematic internal forces. Thus I was not able to reproduce it at first. However, if I use the formchk utility from Gaussian 16 on your chk file, then I get the same issue.&lt;/p&gt;&#xA;&lt;p&gt;VEDA seems to work fine if you just rename the Gaussian 16 output file to fmt and read it in. That would probably be the easier way to go than messing with your fchk files.&lt;/p&gt;&#xA;" OwnerUserId="1440" LastActivityDate="2021-10-20T22:55:50.470" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6924" PostTypeId="2" ParentId="6922" CreationDate="2021-10-21T01:19:11.763" Score="9" Body="&lt;p&gt;I agree with the comment by @jheindel. One issue is that the derivatives in GGA and meta-GGA functionals are not used like a Taylor series. The derivatives are used to obey more known constraints and to provide hooks to parameterize on.&lt;/p&gt;&#xA;&lt;p&gt;I'll now try to address the spirit of your question, supposing that the derivatives &lt;em&gt;were&lt;/em&gt; used to construct a Taylor series. The Taylor series is used to approximate a function, the energy functional, in this case. As you know, the approximation improves with higher orders of terms in the series (assuming the Taylor series converges). However, that does not mean that the function that is being approximated is actually correct.&lt;/p&gt;&#xA;&lt;p&gt;Concretely: constructing a Taylor expansion for the exchange-correlation functional of a homogenous electron gas would simply yield better and better approximations of the energy functional for a homogeneous electron gas, which is still incorrect. That is, &lt;span class=&quot;math-container&quot;&gt;$E_{xc}^{\mathrm{HEG}}[n^\mathrm{exact}] \neq E_{xc}^\mathrm{exact}$&lt;/span&gt; except for the case of the homogenous electron gas.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-10-21T01:19:11.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6925" PostTypeId="1" CreationDate="2021-10-21T13:29:57.413" Score="10" ViewCount="611" Body="&lt;p&gt;I am using Quantum Espresso to simulate a platinum surface with ligands, so far everything is working ok. I now need to introduce a solvated hydronium &lt;span class=&quot;math-container&quot;&gt;$\ce{H_3O^+(H_2O)_2}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is there something I should be careful about when introducing charged species? I will add the keyword &lt;code&gt;tot_charge = +1&lt;/code&gt; but I see that I could also use &lt;code&gt;starting_charge(i), i=1,ntyp&lt;/code&gt;. Which one is preferred?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="7" LastEditDate="2021-10-29T19:21:41.837" LastActivityDate="2021-10-29T19:21:41.837" Title="Simulation of charged species with plane-waves in Quantum Espresso" Tags="|quantum-espresso|surfaces|plane-waves|charged-molecules|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6926" PostTypeId="2" ParentId="6922" CreationDate="2021-10-21T16:38:50.847" Score="6" Body="&lt;p&gt;It's somewhat ambiguous to talk about approximating the XC energy as a Taylor expansion. A Taylor expansion is a series involving a fixed number of variables, and contains successively higher (non-negative integer) powers of the variables. But the hierarchy that you mentioned involves an increasing number of variables, where each variable is a successively higher order derivative of the density, and the density derivatives can enter the expression in arbitrary forms (fractional powers, exponentials, logarithms, trigonometric functions, ...). The latter is obviously quite different from a Taylor expansion.&lt;/p&gt;&#xA;&lt;p&gt;In fact, if the XC energy is not restricted to a single spatial integral, but is allowed to take the following double integral form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;E_{xc} = \int f\left(\int g(\mathbf{r},\mathbf{r'},n(\mathbf{r})) d\mathbf{r}\right)d\mathbf{r'} \tag{1}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;then the exact XC energy is recovered already at the LDA level (!). The reason is simple: express both integrals as infinite sums, so that the formula resembles a single-layer neural network with an infinite number of neurons, where &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the activation function. Then invoke the &lt;a href=&quot;https://en.wikipedia.org/wiki/Universal_approximation_theorem&quot; rel=&quot;noreferrer&quot;&gt;Universal Approximation Theorem&lt;/a&gt;. QED.&lt;/p&gt;&#xA;&lt;p&gt;Of course, most of the time we are talking about the single integral form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;E_{xc} = \int \epsilon(n(\mathbf{r}),\nabla n(\mathbf{r}),\ldots) d\mathbf{r} \tag{2}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(give or take a factor &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; in front of &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, depending on the convention). While I'm not sure if the result will not converge at all when the maximum order of gradient approaches infinity, it's easy to construct examples where the result converges to a wrong value. Consider two infinite potential wells, each containing a helium atom. Now we place these two wells at a non-zero but finite distance with each other, and ask what will be the interaction energy of the two helium atoms, before the electronic densities have time to change due to the interaction. A semilocal functional, which only involves the density and its (arbitrary order) derivatives, will yield a zero interaction energy, since the density and its derivatives at an arbitrary point in one of the wells are not altered by the mere act of placing the two wells together. However, the real interaction energy is negative, due to the dispersion interaction between the helium atoms. This proves that semilocal functionals can never be exact, and when we push the accuracy sufficiently far, non-local terms like VV10 correlation must be included.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-10-21T16:38:50.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6927" PostTypeId="1" AcceptedAnswerId="7025" CreationDate="2021-10-22T09:51:06.590" Score="9" ViewCount="100" Body="&lt;p&gt;I adapted an example first-principles water simulation to do simulations of liquid SiO2, but did not know what I was doing and did not remove a Grimme dispersion correction term.&lt;/p&gt;&#xA;&lt;p&gt;It would be great to get some guidance on whether there is likely to be much difference between including and not including a dispersion correction in a non-water system.&lt;/p&gt;&#xA;&lt;p&gt;It seems like dispersion forces are likely to be minimal in a dense liquid like SiO2 (compared to water) but this is not my forte.  Maybe Grimme correction terms act regardless of the system.  I have not been able to find any newbie-level guidance online.  Could anyone please help me think through this?&lt;/p&gt;&#xA;" OwnerUserId="1035" LastActivityDate="2021-11-09T18:51:53.697" Title="How might inclusion of a Grimme dispersion correction influence a simulation of a dense liquid that is not water?" Tags="|molecular-dynamics|intermolecular-forces|dispersion-correction|atomistic-simulation|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="6928" PostTypeId="2" ParentId="3944" CreationDate="2021-10-23T04:18:58.670" Score="6" Body="&lt;p&gt;&lt;strong&gt;Software to do molecular dynamics on windows&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.lammps.org/&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt; molecular dynamics package has a windows version.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, have you considered the &lt;a href=&quot;https://docs.microsoft.com/en-us/windows/wsl/&quot; rel=&quot;noreferrer&quot;&gt;Windows Subsystem for Linux&lt;/a&gt; (WSL) using which you can easily install linux based applications? I use the WSL daily for most of my work and can confirm that the performance degradation when compared to a native installation of linux is minimal (at least for my use cases of LAMMPS and SIESTA dft).&lt;/p&gt;&#xA;&lt;p&gt;Also, is there any specific reason why you would want to use python for DFT? If you are willing to try a package such as &lt;a href=&quot;https://siesta-project.org/siesta/Documentation/index.html&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt;,  there are &lt;a href=&quot;https://personales.unican.es/junqueraj/JavierJunquera_files/Metodos/Hands-on-session.html&quot; rel=&quot;noreferrer&quot;&gt;tutorials&lt;/a&gt; that sufficiently describe the process of simulating a water molecule. Also the SIESTA package is capable to working with large systems due to the use of localized basis sets. However, there would be a reduction in accuracy when compared to other Plane Wave packages such as &lt;a href=&quot;https://www.quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;Quantum Espresso&lt;/a&gt; and &lt;a href=&quot;https://www.abinit.org/&quot; rel=&quot;noreferrer&quot;&gt;ABINIT&lt;/a&gt;, but the increased system size usually justifies the error introduced.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-23T04:18:58.670" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6929" PostTypeId="1" AcceptedAnswerId="6932" CreationDate="2021-10-23T07:21:30.610" Score="7" ViewCount="404" Body="&lt;p&gt;Following to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3557/determine-dftu-values-by-linear-response&quot;&gt;post&lt;/a&gt;, I would like to know how to perform linear response theory for calculation of U Hubbard parameter in VASP?&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-10-23T10:01:33.967" LastActivityDate="2021-10-23T18:47:53.613" Title="How to perform linear response theory calculation of U Hubbard parameter in VASP?" Tags="|density-functional-theory|vasp|dft-u|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6930" PostTypeId="1" CreationDate="2021-10-23T10:31:10.320" Score="4" ViewCount="254" Body="&lt;p&gt;How to run &lt;code&gt;hp.x&lt;/code&gt; command in QuantumEspresso v6.8? It is saying &lt;code&gt;command not found&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;After doing &lt;code&gt;make hp&lt;/code&gt;, it is saying &lt;code&gt;command not found&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4421" LastEditorUserId="5" LastEditDate="2021-10-24T06:17:50.290" LastActivityDate="2021-10-25T18:58:52.320" Title="How to run hp.x command in Quantum ESPRESSO 6.8?" Tags="|quantum-espresso|hubbard-model|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6931" PostTypeId="1" CreationDate="2021-10-23T10:33:38.187" Score="4" ViewCount="69" Body="&lt;p&gt;I am running an ONIOM optimization calculation on GAUSSIAN software and when I open the LOG file I get a warnig saying:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ConnectionGlob::Parse_BINK0 failure reading archive entry&lt;/code&gt;&#xA;and on other systems using the same method I get the following warning:&#xA;&lt;code&gt;unable to find dipole derivative&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;What does it mean? Are there any problems with my calculations? Do I have to redo them?&lt;/p&gt;&#xA;" OwnerUserId="4401" LastActivityDate="2021-10-23T10:33:38.187" Title="Gaussian warning" Tags="|gaussian|" AnswerCount="0" CommentCount="1" ClosedDate="2021-11-17T04:17:48.203" ContentLicense="CC BY-SA 4.0" />
  <row Id="6932" PostTypeId="2" ParentId="6929" CreationDate="2021-10-23T18:47:53.613" Score="7" Body="&lt;p&gt;&lt;a href=&quot;http://grandcentral.apam.columbia.edu:5555/tutorials/dft_procedures/linear_response_u/index.html&quot; rel=&quot;noreferrer&quot;&gt;This page&lt;/a&gt; is a really good resource for doing linear response in VASP.&lt;/p&gt;&#xA;&lt;p&gt;The general idea is you do a ground state calculation, apply linear response non-self-consistently, then apply it self-consistently.  As far as I can tell, there is no good package that will do this for you and its a bit tricky to get working.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-10-23T18:47:53.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6933" PostTypeId="1" AcceptedAnswerId="6934" CreationDate="2021-10-24T03:10:03.920" Score="12" ViewCount="587" Body="&lt;p&gt;We are all aware of the fact that MD Simulations using force fields can treat very big systems. But they cannot handle &amp;quot;exotic&amp;quot; materials. Why?&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2021-10-24T05:57:19.717" LastActivityDate="2021-12-10T12:23:12.753" Title="Why can MD simulations not handle &quot;exotic&quot; materials?" Tags="|molecular-dynamics|molecular-modeling|molecular-mechanics|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6934" PostTypeId="2" ParentId="6933" CreationDate="2021-10-24T06:17:03.060" Score="14" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;But they cannot handle &amp;quot;exotic&amp;quot; materials. Why?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You have claimed this without a reference! MD in principle can be done for any group of interacting particles, especially if you have an accurate forcefield. The issue is that &lt;em&gt;&lt;strong&gt;classical&lt;/strong&gt;&lt;/em&gt; MD with a &lt;em&gt;&lt;strong&gt;classical&lt;/strong&gt;&lt;/em&gt; forcefield will probably not do as well for an &lt;a href=&quot;https://en.wikipedia.org/wiki/Exotic_material&quot; rel=&quot;noreferrer&quot;&gt;exotic material&lt;/a&gt; like a superconductor, semiconductor, or even just a superalloy containing a transition-metal (e.g. chromium), as it would do for simulating, for example some atmospheric molecules like oxygen, nitrogen and carbon dioxide. So the calculations can be done, but their accuracy will be questionable.&lt;/p&gt;&#xA;&lt;p&gt;All of the examples of exotic materials that I've mentioned, are either intrinsically quantum mechanical (can you successfully describe superconductors without quantum mechanics?), or contain significant quantum mechanical effects, so the forcefield would have to have quantum mechanical effects included (which is not always easy, or is not very accurate in cases where a forcefield was made easily). Furthermore, all the exotic materials mentioned, have relatively heavy elements, meaning relativistic effects are needed too. Basically, exotic materials quite often involve elements that are not even easy to describe for &lt;em&gt;&lt;strong&gt;static&lt;/strong&gt;&lt;/em&gt; electronic structure properties using DFT, so treating their &lt;em&gt;&lt;strong&gt;dynamical&lt;/strong&gt;&lt;/em&gt; motion using classical MD (or AIMD involving DFT calculations that are already difficult or inaccurate), will not be so easy either.&lt;/p&gt;&#xA;&lt;p&gt;Basically, it might be hard to get great accuracy in an MD simulation of an exotic material compared to a system involving just atmospheric molecules (for example), but it's not easy to get great accuracy for exotic materials' static properties like their electronic structure, either.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-10-27T03:11:26.317" LastActivityDate="2021-10-27T03:11:26.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6935" PostTypeId="1" CreationDate="2021-10-24T21:05:15.290" Score="7" ViewCount="287" Body="&lt;p&gt;What does the following notation mean?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$A_{20}\left&amp;lt;r^2\right&amp;gt; = -100 \mathrm{K}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$A_{20}$&lt;/span&gt; is termed a &lt;strong&gt;Crystal Electric Field Parameter&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I often see this notation when reading papers on the magnetic properties of materials from first principles. What is a Crystal Electric Field parameter and why is its value given in Kelvin?&lt;/p&gt;&#xA;&lt;p&gt;An example of this can be found in the following paper: &lt;a href=&quot;http://dx.doi.org/10.7566/JPSJ.83.043702&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dx.doi.org/10.7566/JPSJ.83.043702&lt;/a&gt;, which has the title:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;First-Principles Study of Magnetocrystalline Anisotropy and&#xA;Magnetization in NdFe12, NdFe11Ti, and NdFe11TiN&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In this paper they discuss the changes to the magnetic characteristics of the NdFe12 crystal structure with the addition of Titanium and Nitrogen. To do so they talk about the aforementioned &lt;span class=&quot;math-container&quot;&gt;$A_{20}$&lt;/span&gt; Crystal Electric Field Parameter, the Crystal Electric Field is first mentioned in the following paragraph:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The crystal electric field (CEF) combined with strong spin–orbit coupling causes the anisotropy as follows. The CEF breaks symmetry of the space for the f electrons. It determines stable direction of the orbital magnetization. Then, the spin moment, coupled to the orbital magnetization by strong spin–orbit interaction, is aligned in parallel (in the case of heavy rare-earth element) or anti-parallel (light rare-earth) to the orbital moment. The spin direction is mediated to transition metal sites via R-5d electrons, which fixes the direction of large magnetization of the whole compound. Therefore, the CEF parameters at the R sites are good measure for the strength of magnetocrystalline anisotropy.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;After this initial paragraph they define how they calculate the Crystal Electric Field Parameter:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The CEF parameters are defined by expanding the potential &lt;span class=&quot;math-container&quot;&gt;$v_{CEF}$&lt;/span&gt; at the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; site by the real spherical harmonics &lt;span class=&quot;math-container&quot;&gt;$Z_{lm}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$$v_{CEF} = \sum_{l=0}^{\infty}\sum_{m=-l}^lA_{lm}\frac{\left&amp;lt;r^l\right&amp;gt;}{F_{lm}}Z_{lm}(\hat{r})$$&lt;/span&gt;&#xA;where radial dependence is integrated out using the 4f atomic&#xA;orbital &lt;span class=&quot;math-container&quot;&gt;$\frac{\phi}{r}Y_{lm}(\Omega)$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$X \equiv \int X\phi^2(r)dr$&lt;/span&gt;.&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$A_{lm}$&lt;/span&gt; is the CEF parameter, and &lt;span class=&quot;math-container&quot;&gt;$F_{lm}$&lt;/span&gt;’s are numerical factors, whose explicit expressions can be found in, e.g., Ref. 8.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A_{20}$&lt;/span&gt; is one of these CEF parameters, and is the one of interest because it defines in plane or out of plane magnetisation in this particular crystal structure.&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2023-01-31T23:55:54.957" LastActivityDate="2023-02-01T14:48:56.523" Title="What are Crystal Electric Field Parameters?" Tags="|ab-initio-calculations|electronic-structure|magnetism|magnetic-field|crystal-field|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="6936" PostTypeId="1" CreationDate="2021-10-25T01:47:12.667" Score="6" ViewCount="2025" Body="&lt;p&gt;I am running a simple example of &lt;code&gt;vc-relax&lt;/code&gt;/&lt;code&gt;scf&lt;/code&gt; for aluminum using PBE pseudo-potential.Setting are given below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;control                                                            &#xA;    calculation='vc-relax'                                           &#xA;    restart_mode='from_scratch',                                     &#xA;    pseudo_dir =.                                                    &#xA;    outdir=./tmp/,                                                   &#xA;    prefix='al'                                                      &#xA;    tprnfor = .true.                                                 &#xA;    tstress = .true.                                                 &#xA;    etot_conv_thr=1D-06                                              &#xA;    forc_conv_thr=1D-03                                              &#xA; /                                                                   &#xA; &amp;amp;system                                                             &#xA;    ibrav=  2,A=4.04,nat=  1, ntyp= 1, ecutwfc =30.0,                &#xA;    occupations='smearing', smearing='mp', degauss=0.05              &#xA; /                                                                   &#xA; &amp;amp;electrons                                                          &#xA;  conv_thr    = 1.D-6,                                               &#xA;  mixing_mode='plain',                                               &#xA;  startingwfc='atomic-random',                                              &#xA;  mixing_beta = 0.7D0,                                               &#xA;  diagonalization = &amp;quot;cg&amp;quot;                                             &#xA; /                                                                   &#xA;&amp;amp;ions                                                                &#xA;ion_dynamics='bfgs'                                                  &#xA;/                                                                    &#xA;&amp;amp;cell                                                                &#xA;cell_dynamics='bfgs'                                                 &#xA;/                                                                    &#xA;                                                                     &#xA;ATOMIC_SPECIES                                                       &#xA; Al  26.98 Al.pbe-n-kjpaw_psl.1.0.0.UPF                              &#xA;ATOMIC_POSITIONS alat                                                &#xA; Al 0.00 0.00 0.00                                                   &#xA;K_POINTS automatic&#xA;21 21 21 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am getting warning in some of the scf cycle as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;     iteration #  1     ecut=    30.00 Ry     beta= 0.70&#xA;     CG style diagonalization&#xA;     c_bands:  1 eigenvalues not converged&#xA;     c_bands:  5 eigenvalues not converged&#xA;     c_bands:  3 eigenvalues not converged&#xA;     c_bands:  2 eigenvalues not converged&#xA;     c_bands:  4 eigenvalues not converged&#xA;     c_bands:  3 eigenvalues not converged&#xA;     c_bands:  3 eigenvalues not converged&#xA;     c_bands:  4 eigenvalues not converged&#xA;     c_bands:  4 eigenvalues not converged&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have changed &lt;code&gt;mixing_mode&lt;/code&gt;,&lt;code&gt;mixing_beta&lt;/code&gt;,&lt;code&gt;Kpoints&lt;/code&gt;,&lt;code&gt;ecutwfc&lt;/code&gt;,&lt;code&gt;smearing&lt;/code&gt; &lt;code&gt;startingwfc&lt;/code&gt;,&lt;code&gt;diagonalization&lt;/code&gt; and convergence tolerances, to all extent but warning still exists.&#xA;What is perfect solution to this warning?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-10-25T16:46:58.863" Title="Eigen-values not converged, warning in Quantum espresso" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6937" PostTypeId="2" ParentId="6936" CreationDate="2021-10-25T16:46:58.863" Score="9" Body="&lt;p&gt;Please go through the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/pw_user_guide/node21.html&quot; rel=&quot;noreferrer&quot;&gt;userguide&lt;/a&gt;. At the bottom, it has some nice suggestions. Check this &lt;a href=&quot;https://www.mail-archive.com/users@lists.quantum-espresso.org/msg38442.html&quot; rel=&quot;noreferrer&quot;&gt;mail thread&lt;/a&gt; also.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Does the program stops because too many errors have not converged or,&#xA;the  calculation keeps going on ?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If the calculation did not stop and keeps going on, then you can ignore these warnings. Please do some convergence tests before you proceed for &lt;code&gt;vc-relax&lt;/code&gt;. I did calculations for Al, I even got convergence error in first iteration but subsequent calculations were fine.&lt;/p&gt;&#xA;&lt;p&gt;[Al.vc-relax.in]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;                 calculation = 'vc-relax' ,&#xA;                restart_mode = 'from_scratch' ,&#xA;                      outdir = '.' ,&#xA;                  pseudo_dir = '.' ,&#xA;                      prefix = 'Al' ,&#xA; /&#xA; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 7.6897,&#xA;                         nat = 1,&#xA;                        ntyp = 1,&#xA;                     ecutwfc = 80 ,&#xA;                 occupations = 'smearing' ,&#xA;                     degauss = 0.02 ,&#xA;                    smearing = 'mp' ,&#xA; /&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA; &amp;amp;CELL&#xA;               cell_dynamics = 'bfgs' ,&#xA; /&#xA;ATOMIC_SPECIES&#xA;   Al  26.98  Al.pbe-nl-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS alat&#xA;   Al    0.000000000    0.000000000    0.000000000&#xA;K_POINTS automatic&#xA;  20 20 20  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;[Al.vc-relax.out]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Begin final coordinates&#xA;     new unit-cell volume =    111.15446 a.u.^3 (    16.47139 Ang^3 )&#xA;     density =      2.71995 g/cm^3&#xA;&#xA;CELL_PARAMETERS (alat=  7.68970000)&#xA;  -0.496275584  -0.000000000   0.496275584&#xA;   0.000000000   0.496275584   0.496275584&#xA;  -0.496275584   0.496275584   0.000000000&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA;Al            0.0000000000        0.0000000000        0.0000000000&#xA;End final coordinates&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;[Al.eos]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# equation of state: birch 1st order.  chisq =   0.5139D-05&#xA;# a0 =  7.6897 a.u., k0 =  678 kbar, dk0 =  4.27 d2k0 =  0.000 emin =   -5.03767&#xA;# a0 =  4.06919 Ang, k0 =  67.8 GPa,  V0 =   113.67 (a.u.)^3,  V0 =   16.84 A^3 &#xA;&#xA;#########################################################################&#xA;# Lat.Par       E_calc        E_fit       E_diff    Pressure      Enthalpy&#xA;# a.u.            Ry           Ry            Ry        GPa           Ry&#xA;#########################################################################&#xA;  5.60000      -4.52379      -4.52017    -0.00362     518.54       -2.97618&#xA;  5.80000      -4.66251      -4.66460     0.00208     364.14       -3.45508&#xA;  6.00000      -4.76977      -4.77322     0.00346     255.35       -3.83242&#xA;  6.20000      -4.85181      -4.85448     0.00267     178.18       -4.13015&#xA;  6.40000      -4.91365      -4.91472     0.00107     123.13       -4.36511&#xA;  6.60000      -4.95932      -4.95872    -0.00060      83.70       -4.55036&#xA;  6.80000      -4.99207      -4.99014    -0.00193      55.39       -4.69607&#xA;  7.00000      -5.01447      -5.01177    -0.00270      35.05       -4.81018&#xA;  7.20000      -5.02866      -5.02579    -0.00287      20.44       -4.89899&#xA;  7.40000      -5.03643      -5.03388    -0.00255      10.00       -4.96759&#xA;  7.60000      -5.03924      -5.03734    -0.00191       2.57       -5.02006&#xA;  7.80000      -5.03820      -5.03721    -0.00100      -2.65       -5.05954&#xA;  8.00000      -5.03420      -5.03429     0.00009      -6.25       -5.08860&#xA;  8.20000      -5.02805      -5.02924     0.00119      -8.68       -5.10937&#xA;  8.40000      -5.02050      -5.02254     0.00205     -10.24       -5.12368&#xA;  8.60000      -5.01207      -5.01462     0.00254     -11.18       -5.13294&#xA;  8.80000      -5.00306      -5.00577     0.00271     -11.66       -5.13815&#xA;  9.00000      -4.99371      -4.99627     0.00256     -11.82       -5.14014&#xA;  9.20000      -4.98419      -4.98631     0.00212     -11.74       -5.13957&#xA;  9.40000      -4.97465      -4.97605     0.00140     -11.50       -5.13698&#xA;  9.60000      -4.96521      -4.96562     0.00042     -11.15       -5.13281&#xA;  9.80000      -4.95596      -4.95513    -0.00083     -10.72       -5.12745&#xA; 10.00000      -4.94697      -4.94465    -0.00232     -10.25       -5.12118&#xA; 10.20000      -4.93828      -4.93424    -0.00403      -9.76       -5.11423&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/GQkR9.png&quot; alt=&quot;etot_vs_alat&quot; /&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/J5sdD.png&quot; alt=&quot;etot_vs_ecut&quot; /&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/5jztV.png&quot; alt=&quot;etot_vs_k&quot; /&gt;&lt;/p&gt;&#xA;" OwnerUserId="4352" LastActivityDate="2021-10-25T16:46:58.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6938" PostTypeId="2" ParentId="6930" CreationDate="2021-10-25T17:07:47.637" Score="4" Body="&lt;p&gt;Executables are soft-linked in &lt;code&gt;./bin&lt;/code&gt; folder of the parent directory. If you did not compile, please follow these &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node13.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;steps&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;make hp&#xA;cd bin&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After that, run the command,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./hp.x&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you are accessing the executable from QE input file folder, then you have to specify the whole path of the executable&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/path-to-qe-folder/bin/hp.x&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The best practice is to &lt;code&gt;export&lt;/code&gt; the &lt;a href=&quot;https://linuxhint.com/export-a-path-in-bashrc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;path variables&lt;/a&gt; into the &lt;code&gt;~/.bashrc&lt;/code&gt; or similar file, so that it can be accessible anywhere.&lt;/p&gt;&#xA;&lt;p&gt;P.S. I presume you are using some flavor of linux OS or atleast compatible linux shell in windows.&lt;/p&gt;&#xA;" OwnerUserId="4352" LastEditorUserId="4352" LastEditDate="2021-10-25T18:58:52.320" LastActivityDate="2021-10-25T18:58:52.320" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6939" PostTypeId="1" CreationDate="2021-10-25T20:07:56.687" Score="9" ViewCount="556" Body="&lt;p&gt;I have one doubt about K points selection for a supercell. I construct one 2X2X1 supercell with 64 atoms having a=11.19, b=11.19, c=5.59. For checking K points convergence test with energy should I consider like 2x2x2, 3x3x3, this type of set or 1x1x2, 1x1x3, 1x1x4 or 2x2x1, 3x3x1, 4x4x1 Which set is more convenient for K points convergence and further calculations.&lt;/p&gt;&#xA;" OwnerUserId="4354" LastActivityDate="2021-10-29T17:11:49.573" Title="Doubt about K point selection for 2x2x1 supercell" Tags="|density-functional-theory|k-points|convergence-test|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6940" PostTypeId="1" AcceptedAnswerId="6945" CreationDate="2021-10-25T21:05:07.943" Score="12" ViewCount="124" Body="&lt;p&gt;When you submit a paper to be published, the journal will ask you to suggest at least three reviewers. My question is how to search for appropriate reviewers for your paper? &lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-10-26T11:06:22.193" LastActivityDate="2021-10-26T11:46:09.520" Title="How to find reviewers for your paper?" Tags="|publishing|" AnswerCount="1" CommentCount="4" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6941" PostTypeId="1" AcceptedAnswerId="7250" CreationDate="2021-10-26T05:43:18.660" Score="7" ViewCount="486" Body="&lt;p&gt;I am working on &lt;span class=&quot;math-container&quot;&gt;$\ce{GeHfTe}$&lt;/span&gt; and in the case of a non-collinear calculation, I am getting the DOS in the attached photo. I have already relaxed my structure with VC-relax and it is converged with respect to k-points, EOS parameter, and degauss value.&lt;/p&gt;&#xA;&lt;p&gt;If any one can guide me what is wrong in the DOS obtained it will be very helpful. I am not quite sure about the two sharp peaks around &lt;span class=&quot;math-container&quot;&gt;$\pu{-25eV}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xIHOJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xIHOJ.png&quot; alt=&quot;DOS of GeHfTe&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  restart_mode  = 'from_scratch'&#xA;  etot_conv_thr =   1.0000000000d-13&#xA;  forc_conv_thr =   1.0000000000d-09&#xA;  outdir = './'&#xA;  prefix = 'GeHfTe'&#xA;  pseudo_dir = '/home/yash/project/qe-6.7-ReleasePack/qe-6.7/pseudo'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss =   0.001&#xA;  ecutwfc =   150&#xA;  ibrav = 0&#xA;  nat = 6&#xA;  ntyp = 3&#xA;  occupations = 'smearing'&#xA;  smearing = 'cold'&#xA; noncolin=.true.&#xA;  lspinorb=.true.&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.2000000000d-15&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;/&#xA;ATOMIC_SPECIES&#xA;Ge     72.64  Ge.rel-pz-dn-rrkjus_psl.0.2.2.UPF&#xA;Hf     178.49 Hf.rel-pz-spn-rrkjus_psl.1.0.0.UPF&#xA;Te     127.6 Te.rel-pz-dn-rrkjus_psl.0.2.2.UPF&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   3.799849132   0.000000000   0.000000000&#xA;   0.000000000   3.799849132   0.000000000&#xA;   0.000000000   0.000000000   8.387787463&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Hf            0.0000000000        0.5000000000        0.7536986859&#xA;Hf            0.5000000000        0.0000000000        0.2463013141&#xA;Ge            0.0000000000        0.0000000000       -0.0000000000&#xA;Ge            0.5000000000        0.5000000000        0.0000000000&#xA;Te            0.5000000000        0.0000000000        0.6218959934&#xA;Te            0.0000000000        0.5000000000        0.3781040066&#xA;&#xA;K_POINTS (automatic)&#xA;10 10 10 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4468" LastEditorUserId="7" LastEditDate="2021-10-26T13:42:05.937" LastActivityDate="2021-12-13T16:27:58.857" Title="Why am I getting DOS like this in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|density-of-states|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6943" PostTypeId="1" AcceptedAnswerId="6944" CreationDate="2021-10-26T07:11:39.017" Score="5" ViewCount="795" Body="&lt;p&gt;I have run a HF calculation on naphthalene and I have checked the MOs that have been obtained. Now, I have to select my active and inactive orbitals for CASCF(10,10). As there are 34 occupied orbitals, ORCA by default would read 31, 32, 33, 34, 35, 36, 37, 38, 39 but I have inspected how they look and I should use 27, 32, 32, 33, 34, 35, 36, 37, 41 and 48.&lt;/p&gt;&#xA;&lt;p&gt;So the changes to be done are:&lt;/p&gt;&#xA;&lt;p&gt;30 to 27&#xA;38 to 41&#xA;39 to 48&lt;/p&gt;&#xA;&lt;p&gt;How do you tell ORCA to read the MOs from output file and to change the default selection of the orbitals to the ones I chose? Thank you&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2021-10-26T08:21:46.163" Title="Modify ORCA orbitals for CASSCF" Tags="|software|orbitals|orca|casscf|multi-reference|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6944" PostTypeId="2" ParentId="6943" CreationDate="2021-10-26T08:21:46.163" Score="7" Body="&lt;p&gt;You can use the &amp;quot;rotate&amp;quot; keyword in the SCF block, like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%scf rotate {30,27,90} (38,41,90} {39,48,90} end end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &amp;quot;90&amp;quot;s mean &amp;quot;90 degrees&amp;quot;, since swapping two orbitals is equivalent to applying a unitary rotation of 90 degrees. The &amp;quot;90&amp;quot;s can actually be omitted, but I'm writing them out to illustrate that you can plug in different numbers to achieve other effects (e.g. use 45 to mix two orbitals in equal portions, or 180 to flip the phase of one of the orbitals).&lt;/p&gt;&#xA;&lt;p&gt;More details on how to perform CASSCF calculations using ORCA can be found in &lt;a href=&quot;https://orcaforum.kofo.mpg.de/app.php/dlext/?cat=4&quot; rel=&quot;noreferrer&quot;&gt;https://orcaforum.kofo.mpg.de/app.php/dlext/?cat=4&lt;/a&gt; (only visible if you have an account on the ORCA forum and have logged in), as well as in the ORCA manual.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-10-26T08:21:46.163" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6945" PostTypeId="2" ParentId="6940" CreationDate="2021-10-26T11:46:09.520" Score="8" Body="&lt;p&gt;This is actually a good question, with not so obvious an answer as it might seem for some people. If what I've written is too much, you can just look out for the text in bold font.&lt;/p&gt;&#xA;&lt;p&gt;My first journal paper was published with senior professors who had been publishing in mainstream journals for decades, and had been going to mainstream conferences for decades, and who themselves had well-established mainstream supervisors when they were early in their careers, so they knew what they were doing. &lt;strong&gt;I was an undergraduate student and my more senior co-authors chose the referees for that paper.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The next submission I made to a journal was rather unfortunately done completely on my own, as a solo author. I was now a PhD student at a different university, and it never occurred to me that I could ask my supervisor from the aforementioned earlier project, for advice (I should have). As a PhD student, any supervision I got from professors, was far more &amp;quot;hands-off&amp;quot;, and people were not as approachable for advice as that undergrad supervisor was (this doesn't have anything to do with PhD vs undergrad, it's just something that varies from person to person). For this solo-author paper, I could try to see if I have a copy of the submission information, but I'm certain I just put something like &amp;quot;No preference, except &lt;strong&gt;it would be inappropriate to send it to Person A&lt;/strong&gt; for the following reason...&amp;quot; where Person A was someone who I didn't want refereeing the paper. &lt;strong&gt;I'm 99% sure that they &lt;em&gt;sent&lt;/em&gt; it to Person A.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The next paper I submitted to a journal was again with the first supervisor I mentioned, and this it was only two of us co-authoring the paper, and I was a first-author and far more senior than before, so I was much more involved in the process compared to the first time. He said &lt;strong&gt;&amp;quot;let's send it out to all our competitors!&amp;quot;&lt;/strong&gt;. Now I'm only starting to realize, while thinking about your question, how complicated referee selection can actually be. In that particular case, the work was of such high quality, that it was pretty much guaranteed to get accepted, and &lt;strong&gt;sending it to the leading competitors in the field meant we got excellent feedback while still getting the paper accepted.&lt;/strong&gt; When I say &amp;quot;competitors&amp;quot;, I mean: the very small number of  people in the world who were designing exactly the same type of models as we were, but who had extremely strong preferences for their own types of models versus our type. These &amp;quot;competitors&amp;quot; got into long-lasting heated debates with my senior co-author, at conferences, and stubbornly refused to use our model, or admit that it was better than there's. &lt;strong&gt;However, choosing &amp;quot;copmpetitors&amp;quot; like this, is not always a good idea.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Typically, for the average paper, &lt;strong&gt;people choose referees who they know &lt;em&gt;fairly&lt;/em&gt; well&lt;/strong&gt; (if you go to enough conferences regularly, you meet the same people each year and become familiar with each other, or you meet people through email interactions when discussing each others papers), but &lt;strong&gt;&lt;em&gt;not&lt;/em&gt; people they know &lt;em&gt;too&lt;/em&gt; well&lt;/strong&gt; such as co-authors, colleagues, former supervisors/students, family members, etc.&lt;/p&gt;&#xA;&lt;p&gt;To conclude: &lt;strong&gt;people typically learn the referee selection process by the experience of working with co-authors who know what they're doing.&lt;/strong&gt; If you don't have a co-author like this, then you may want to ask a more senior person near you (geographically or figuratively), who is familiar with the subject of the paper.&lt;/p&gt;&#xA;&lt;h3&gt;If you can't do that, then describing the paper and asking the MMSE community might be a good idea!&lt;/h3&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-26T11:46:09.520" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6946" PostTypeId="2" ParentId="6920" CreationDate="2021-10-26T17:51:41.940" Score="4" Body="&lt;p&gt;In terms of the 1D Schrodinger equation formalism, this question has a relatively straightforward answer. I'm not sure, however, that the answer we get from the theory has a clear correlation with the an easy-to-measure property of the coating.&lt;/p&gt;&#xA;&lt;p&gt;The simplest version of this would be a 1D particle scattering off a step potential.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ V(x&amp;lt;0) = 0$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V(0&amp;lt;x&amp;lt;a) = V_b $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V(a&amp;lt;x) = V_0$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$V=0$&lt;/span&gt; is free space, &lt;span class=&quot;math-container&quot;&gt;$V_b$&lt;/span&gt; represents your &amp;quot;barrier&amp;quot; or your antireflective coating) and &lt;span class=&quot;math-container&quot;&gt;$V_0$&lt;/span&gt; is the material you're putting the coating on.&lt;/p&gt;&#xA;&lt;p&gt;You now have a schodinger equation in three distinct regions, which you can solve by generalizing the step function solution. The algebra is difficult, but manageable. In the end, you will want to solve for the conditions that minimize &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; in terms of the thickness of the coating, &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can make some simplifying assumptions: &lt;span class=&quot;math-container&quot;&gt;$E&amp;gt;V_b, V_0$&lt;/span&gt; (since you want your particle to propagate. You will therefore have complex expotentials in all three sections.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-10-26T17:51:41.940" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6947" PostTypeId="1" AcceptedAnswerId="6948" CreationDate="2021-10-27T00:54:12.380" Score="7" ViewCount="147" Body="&lt;p&gt;Does PySCF support CAS-SCF calculations? If not, it is possible to implement it based on their GTO integral library?&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2021-10-27T01:21:56.013" Title="Does PySCF support CAS-SCF calculation?" Tags="|electronic-structure|multi-reference|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6948" PostTypeId="2" ParentId="6947" CreationDate="2021-10-27T01:21:56.013" Score="6" Body="&lt;p&gt;Yes, it does, and it is even quite efficient in it. Choosing the active space is also quite simple to do with the AVAS method if you know which atoms' valence orbitals you want to make active; alternatively, you can form UHF, MP2, or CISD etc natural orbitals and pick the active space based on them. I even believe that you can input your own integrals so that you can easily study also model systems.&lt;/p&gt;&#xA;&lt;p&gt;Please see the user guide's MCSCF* section at &lt;a href=&quot;https://pyscf.org/user/mcscf.html&quot; rel=&quot;noreferrer&quot;&gt;https://pyscf.org/user/mcscf.html&lt;/a&gt; for details how to run the calculations&lt;/p&gt;&#xA;&lt;p&gt;(*) CASSCF is a special type of MCSCF&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-10-27T01:21:56.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6949" PostTypeId="1" CreationDate="2021-10-27T06:58:18.010" Score="7" ViewCount="236" Body="&lt;p&gt;I am stuck in calculating the frequencies of one optimised geometry for naphthalene CASSCF(10,10) with Gaussian 16. I have optimised its geometry and checked the active space is the pi system of it, as I wanted. However, I have tried to run either &lt;em&gt;Opt Freq&lt;/em&gt; and &lt;em&gt;Freq&lt;/em&gt; alone and keeps giving me errors. Does anyone know if it is a problem of Gaussian or if it can be overcome with any Iop option.&lt;/p&gt;&#xA;&lt;p&gt;This is the error that I am getting:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Number              0&#xA; Base            40448&#xA; End             65536&#xA; End1            65536&#xA; Wr Pntr         40448&#xA; Rd Pntr         40448&#xA; Length          25088&#xA; Int.Num             1&#xA; Operation on file out of range.&#xA; FileIO: IOper= 1 IFilNo(1)=  2800 Len=       20502 IPos=           0 Q=  139934647205904&#xA; Error termination in NtrErr:&#xA; NtrErr Called from FileIO.&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And so it seems like it is a problem of writing. In the following drive link you have the .chk file that I am using to check, as well as my .com input file. I am also adding my output file, so the error can be traced more easily.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://drive.google.com/drive/folders/1_MExyaeyJknTn_VnIFhwzCbfToE0HqqD?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;Gaussian files&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="3382" LastEditDate="2021-10-27T08:24:02.707" LastActivityDate="2021-11-12T23:05:37.980" Title="Frequency error in Gaussian CASSCF(10,10)" Tags="|software|gaussian|casscf|multi-reference|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6950" PostTypeId="1" AcceptedAnswerId="6960" CreationDate="2021-10-27T13:47:49.337" Score="6" ViewCount="106" Body="&lt;p&gt;Is the following notation&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi^\mathrm{HF}_0  \equiv | \phi_1, \phi_2, \cdots, \phi_i, \phi_j, \cdots, \phi_N \rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia}    \equiv | \phi_1, \phi_2, \cdots, \phi_a, \phi_j, \cdots, \phi_N \rangle $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia,jb} \equiv | \phi_1, \phi_2, \cdots, \phi_a, \phi_b, \cdots, \phi_N \rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\cdots$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia}$&lt;/span&gt; refers to single excited Slater determinant (SD) and &lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia,jb}$&lt;/span&gt; refers to a double excited SD correct?&lt;/p&gt;&#xA;&lt;p&gt;I want to use this notation to define the operators&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat a^a \hat a_i \Phi^\mathrm{HF}_0  = \Phi_{ia}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat a^a \hat a^b \hat a_j \hat a_i \Phi^\mathrm{HF}_0  = \Phi_{ia,jb}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which I then want to use to define &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; (part of the cluster operator) as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat T_1 = \sum_i \sum_a t_a^i \hat{a}^a \hat{a}_i$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there something wrong with how I define &lt;span class=&quot;math-container&quot;&gt;$\Phi^\mathrm{HF}_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\Phi_{ia,jb}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="4029" LastEditorUserId="142" LastEditDate="2021-10-27T15:13:56.803" LastActivityDate="2021-11-07T04:07:36.487" Title="Is this notation for single and double excited Slater determinants correct?" Tags="|coupled-cluster|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6951" PostTypeId="1" CreationDate="2021-10-27T14:33:33.873" Score="6" ViewCount="50" Body="&lt;p&gt;Is there a way to search to search for specific structural motifs in proteins?&#xA;For example can a database where we can find structures with zing finger motif or an hairpin...&lt;/p&gt;&#xA;&lt;p&gt;PDBeMotif (ebi.ac.uk) has some motifs for example but no way to download them.&#xA;Small Three-Dimensional Protein Motifs (gla.ac.uk) also offers some.&lt;/p&gt;&#xA;" OwnerUserId="125" LastActivityDate="2021-10-27T14:33:33.873" Title="How to look for specific structural motifs in proteins?" Tags="|proteins|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-27T04:27:48.453" ContentLicense="CC BY-SA 4.0" />
  <row Id="6952" PostTypeId="1" CreationDate="2021-10-27T14:49:47.607" Score="6" ViewCount="700" Body="&lt;p&gt;While calculating the band structure using VASP, we usually take two steps: one is the self-consistent run to get the right CHGCAR file; and the other is a nonself-consistent calculation to generate the band structure. Two different Fermi energy occur in these two steps.&lt;/p&gt;&#xA;&lt;p&gt;Take single-layered-graphene for example: Fermi energy in step one is &lt;span class=&quot;math-container&quot;&gt;$\pu{-3.22eV}$&lt;/span&gt;, while another one in step two is &lt;span class=&quot;math-container&quot;&gt;$\pu{-3.01ev}$&lt;/span&gt;. The difference between them is very large, I want to know which one should we use?&#xA;If the latter fermi energy is not correct, will the band structure calculated with it also not correct?&lt;/p&gt;&#xA;" OwnerUserId="4428" LastEditorUserId="7" LastEditDate="2021-12-13T15:10:43.147" LastActivityDate="2021-12-13T15:10:43.147" Title="SC vs NSC Fermi energy in VASP, which is correct?" Tags="|vasp|band-structure|fermi-energy|" AnswerCount="1" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6953" PostTypeId="2" ParentId="6933" CreationDate="2021-10-27T20:41:49.623" Score="8" Body="&lt;p&gt;By molecular dynamics, I assume you mean molecular dynamics using force-fields (a.k.a. Classical Molecular Dynamics). Remember that there is also ab initio MD.&lt;/p&gt;&#xA;&lt;p&gt;Force fields are parameterised, i.e. they depend on the a set of constant parameters, which have been previously fitted to reproduce experimental data/high level ab initio results. These parameters are necessary to calculate all of the interaction terms between the particles in your system. So, the applicability of force-field based molecular dynamics depends on whether there are accurate parameters that are available for the system that you want to study.&lt;/p&gt;&#xA;&lt;p&gt;A system which is &amp;quot;exotic&amp;quot; would be unlikely to have accurate parameters developed for it, because so few researchers would have studied that system (otherwise it wouldn't be exotic, would it?). It is also likely that an &amp;quot;exotic&amp;quot; system would have unusual properties which would make it difficult to develop parameters for it (maybe the species is unstable, or its potential energy surface has an odd shape etc.).&lt;/p&gt;&#xA;&lt;p&gt;In the absence of parameters fitted for that particular system, you would be forced to use general force-field parameters (like UFF for instance). There you would run into the problem of poor transferability—parameters fitted to one system are rarely usable in other unrelated systems.&lt;/p&gt;&#xA;&lt;p&gt;So, the answer to your question is simple: MD cannot handle exotic systems well because there are no good parameters for those systems, precisely because the system is exotic. MD can be done on &lt;strong&gt;any&lt;/strong&gt; system, provided you can fit  parameters.&lt;/p&gt;&#xA;&lt;p&gt;[In the recent years, there has been a lot of investigation into force field development for exotic molecules using ab initio and machine learning. For example, a PhD researcher I know is working on developing parameters for some short-lived species like &lt;span class=&quot;math-container&quot;&gt;$\ce{NO3}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{SOF}$&lt;/span&gt; etc. So, a lot of things that were previously exotic are no longer exotic.]&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-12-10T12:23:12.753" LastActivityDate="2021-12-10T12:23:12.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6954" PostTypeId="1" AcceptedAnswerId="7012" CreationDate="2021-10-27T20:52:31.167" Score="13" ViewCount="157" Body="&lt;p&gt;I am currently working on prediction of UV-vis spectra from structure of molecules. I have read multiple papers where structure descriptors were used as inputs for machine learning to find various properties. I have also come across different types of structre descriptors such as the adjacency matrix.&lt;/p&gt;&#xA;&lt;p&gt;However, I haven't been able to find much information on how exactly these descriptors are fed into the statistical model. I want to understand how the descriptors are interpreted by the software algorithm. For example, if I have an adjacency matrix, how should I put it into a software like scikit-learn? I am looking for a beginner's level explanation of the descriptors and their interpretation by software (not just adjacency matrices, other types of descriptors too, like MOE, 3D descriptors, fingerprints etc.).&lt;/p&gt;&#xA;&lt;p&gt;I am using machine learning to some extent, but would like to know about applying regression based methods on descriptors because I want to understand what actually is happening under the hood.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-11-05T18:55:46.687" Title="How are structure descriptors used in regression or machine learning?" Tags="|reference-request|one-topic-per-answer|machine-learning|qsar|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6955" PostTypeId="1" AcceptedAnswerId="6959" CreationDate="2021-10-27T23:56:11.827" Score="7" ViewCount="578" Body="&lt;p&gt;I have the following molecule in SMILE format (saved as &lt;code&gt;my_molecule.smi&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I created an image using ChemAxon Marvin's &lt;a href=&quot;https://docs.chemaxon.com/display/docs/molconvert.md&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;molconvert&lt;/strong&gt;&lt;/a&gt; command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MarvinSuite/bin/molconvert &amp;quot;jpeg:w800:h800&amp;quot; my_molecule.smi -o mol.jpg&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It produces the following image:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Wy8Mz.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Wy8Mz.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then I use &lt;a href=&quot;https://www.rdkit.org&quot; rel=&quot;noreferrer&quot;&gt;RDKit&lt;/a&gt;, with the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;m = Chem.MolFromSmiles('[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O')&#xA;m&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get this image:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7goIX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7goIX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that it is circular, and missing an H3C.&#xA;With RDKit, how can I create the identical image with the one made by &lt;code&gt;molconvert&lt;/code&gt;?&#xA;i.e. straight format and H3C included.&lt;/p&gt;&#xA;&lt;p&gt;Python code can be tried in &lt;a href=&quot;https://colab.research.google.com/drive/1AJy1YcIpSvr2x5s-LFHisKU4LhI0cOEW?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;my Google Colab&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4475" OwnerDisplayName="scamander" LastActivityDate="2021-10-28T04:11:58.577" Title="How to create molecule image similar with molconvert using RDKit" Tags="|cheminformatics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6956" PostTypeId="2" ParentId="6939" CreationDate="2021-10-28T01:43:44.963" Score="7" Body="&lt;p&gt;The KPOINTS have an inverse relationship with the real space lattice vectors. In either way, you won't go wrong. I would prefer to test it using 1x1x2, 1x1x3, 1x1x4, etc. This is simply because your c axis is much smaller than the a and b axis. However, you might also want to explore the other alternatives such as 2x2x3, 2x2x4, etc. Since it is not guaranteed that in the reciprocal a and b directions (&lt;span class=&quot;math-container&quot;&gt;$a^{*}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b^{*}$&lt;/span&gt;)  one KPOINT sampling would be enough.&lt;/p&gt;&#xA;&lt;p&gt;To add furthermore, you can consider using a package like pymatgen(&lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;noreferrer&quot;&gt;https://pymatgen.org/&lt;/a&gt;) where they can give reliable initial guesses on the KPOINT sampling. From these guesses, you can actually run your convergence tests by having integral multiple of KPOINTS.&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2021-10-28T01:43:44.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6957" PostTypeId="1" AcceptedAnswerId="7132" CreationDate="2021-10-28T02:16:34.483" Score="9" ViewCount="233" Body="&lt;p&gt;After calculating the band diagram of a structure, is there a way to identify localized surface states?&lt;/p&gt;&#xA;&lt;p&gt;I am working with Si nanowires with different cross sections. I want to determine the band gap variation between them, and so saturated the surface bonds using H atoms. However I want to confirm that the resulting structures are free of any localized surface states. I have attached two sample band diagrams below.&lt;/p&gt;&#xA;&lt;p&gt;Note: the K-path varies from the Gamma point along the length of the structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kvHJh.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kvHJh.jpg&quot; alt=&quot;Structure 1&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7EoLq.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7EoLq.jpg&quot; alt=&quot;Structure 2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-11-24T13:03:30.060" Title="How to identify localized surface states in the band structure" Tags="|density-functional-theory|band-structure|condensed-matter|siesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6958" PostTypeId="1" CreationDate="2021-10-28T02:41:15.303" Score="10" ViewCount="257" Body=" Computationally, there are various ways to calculate the electron-phonon coupling constants as a function of phonon index and momentum. My question is about the reverse process. Let us say that an experimentalist is (miraculously?) able to measure the effective Coulomb interaction in a material &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{eff}} (\mathbf{k}-\mathbf{k}', \nu)$&lt;/span&gt; defined as: &#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V_{\textrm{eff}} (\mathbf{k}-\mathbf{k}', \nu) = \frac{V_0(\mathbf{k}-\mathbf{k}')}{\epsilon(\mathbf{k}-\mathbf{k}', \nu)}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$V_0(\mathbf{k}-\mathbf{k}') = \frac{4\pi e^2}{\vert \mathbf{k}-\mathbf{k}' \vert^2}$&lt;/span&gt; is the bare Coulomb interaction, and &lt;span class=&quot;math-container&quot;&gt;$\epsilon(\mathbf{k}-\mathbf{k}', \nu)$&lt;/span&gt; is the dielectric function.&lt;/p&gt;&#xA;&lt;p&gt;My question is the following: &lt;strong&gt;Is there a generic, model-independent way to extract out the electron-phonon coupling constants (or coupling &lt;em&gt;functions&lt;/em&gt;, rather) or the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-resolved Eliashberg function from such a measurement of &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{eff}} (\mathbf{k}-\mathbf{k}', \nu)$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$\epsilon(\mathbf{k}-\mathbf{k}', \nu)$&lt;/span&gt;)?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Presumably, phonons should appear as poles in &lt;span class=&quot;math-container&quot;&gt;$\epsilon^{-1}(\mathbf{k}-\mathbf{k}', \nu)$&lt;/span&gt;, so clearly some information about phonons is contained in the dielectric function, but it is unclear to me what role electron-phonon coupling plays in the appearance of phonons in the dielectric function.&lt;/p&gt;&#xA;&lt;p&gt;Edit: To be clear, I am not interested in comparing simulated dielectric functions (where coupling constants are inputs) to experiment dielectric functions. I am interested in whether the physics of electron-phonon coupling is fully contained and extractable from the dielectric function &lt;em&gt;in principle&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1113" LastEditorUserId="5" LastEditDate="2021-12-26T21:10:49.987" LastActivityDate="2021-12-27T00:31:20.520" Title="Can electron-phonon coupling be extracted from the dielectric function?" Tags="|computational-chemistry|ab-initio-calculations|electronic-structure|phonons|experimental|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6959" PostTypeId="2" ParentId="6955" CreationDate="2021-10-28T04:11:58.577" Score="9" Body="&lt;p&gt;You're not going to get something identical. Different toolkits use different code to do 2D molecule layout. Generally the current RDKit code (which uses the CoordGen library) tends to prefer geometries closer to square, which is useful when drawing a bunch of molecules in a grid.&lt;/p&gt;&#xA;&lt;p&gt;In short, I don't think there's anything you can do if you prefer an extended form and want RDKit to generate that.&lt;/p&gt;&#xA;&lt;p&gt;Adding explicit methyl groups is pretty easy with recent RDKit (2020.03 and later), which adds &lt;a href=&quot;http://rdkit.blogspot.com/2020/04/new-drawing-options-in-202003-release.html&quot; rel=&quot;noreferrer&quot;&gt;new drawing options&lt;/a&gt;, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import Draw&#xA;from rdkit.Chem.Draw import rdMolDraw2D&#xA;from rdkit.Chem import rdDepictor&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;from IPython.display import SVG&#xA;&#xA;m = Chem.MolFromSmiles('[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O')&#xA;&#xA;d2d = rdMolDraw2D.MolDraw2DSVG(350,300)&#xA;d2d.drawOptions().explicitMethyl =True&#xA;d2d.DrawMolecule(m)&#xA;d2d.FinishDrawing()&#xA;SVG(d2d.GetDrawingText())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The options are documented for the &lt;a href=&quot;https://www.rdkit.org/docs/source/rdkit.Chem.Draw.rdMolDraw2D.html&quot; rel=&quot;noreferrer&quot;&gt;rdMolDraw2D module&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-10-28T04:11:58.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6960" PostTypeId="2" ParentId="6950" CreationDate="2021-10-28T06:11:05.013" Score="6" Body="&lt;p&gt;In Configuration Interaction and Couple Cluster theory, the widely used convention for singles, doubles, triples Wave functions(Slater determinants, coefficients etc) is to denote occupied orbitals in subscripts and virtual orbitals in superscript.&lt;/p&gt;&#xA;&lt;p&gt;For example, &lt;span class=&quot;math-container&quot;&gt;$|\Phi_{i}^{a}\rangle$&lt;/span&gt; represents a singles Slater determinant where the electron is excited from &lt;em&gt;occupied orbital&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is excited to &lt;em&gt;virtual orbital&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;. Also, note that its a widely used convention to use indicies &lt;span class=&quot;math-container&quot;&gt;$i,j,k,l....$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$a,b,c,d...$&lt;/span&gt; for occupied and virtual molecular orbitals respectively.&lt;/p&gt;&#xA;&lt;p&gt;The ordering of the indices may not matter, i.e. &lt;span class=&quot;math-container&quot;&gt;$|\Phi_{ijk}^{abc}\rangle$&lt;/span&gt; is the same as &lt;span class=&quot;math-container&quot;&gt;$|\Phi_{kji}^{abc}\rangle$&lt;/span&gt; as by definition we consider anti-symmetrical wave functions. This can also be understood by playing around with the combinations of second quantized notation using commutation relations of your fermionic creation-annihilation operators.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\hat{a_{a}}^{\dagger} \hat{a^{}_{i}}\hat{a_{b}}^{\dagger}\hat{a^{}_{j}}\hat{a_{c}}^{\dagger}\hat{a^{}_{k}} | \Phi_{0}\rangle = |\Phi_{ijk}^{abc}\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can find more information on such issues in chapter two of Szabo and Ostlund.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Szabo, Attila, and Neil S. Ostlund. Modern quantum chemistry:&#xA;introduction to advanced electronic structure theory. Courier&#xA;Corporation, 2012.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Note: The convention for indices is different from the ones found in Szabo, which seems to follow a convention that's considered outdated now.&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="7" LastEditDate="2021-11-07T04:07:36.487" LastActivityDate="2021-11-07T04:07:36.487" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6961" PostTypeId="1" CreationDate="2021-10-28T08:31:36.883" Score="10" ViewCount="110" Body="&lt;p&gt;I want to learn DFT for research purposes and I need to implement a toy DFT for pedagogical reasons.&#xA;I would like some recommendations regarding resources like books, articles, or any other thing that will help in this matter.&lt;/p&gt;&#xA;" OwnerUserId="4476" LastActivityDate="2021-10-28T08:31:36.883" Title="How to implement a toy DFT" Tags="|density-functional-theory|crystallography|" AnswerCount="0" CommentCount="7" ClosedDate="2021-11-10T19:12:00.910" ContentLicense="CC BY-SA 4.0" />
  <row Id="6962" PostTypeId="1" CreationDate="2021-10-29T04:18:46.317" Score="6" ViewCount="130" Body="&lt;p&gt;Considering one component of the electric quadrupole operator &lt;span class=&quot;math-container&quot;&gt;$\hat{r}_x \hat{r}_y$&lt;/span&gt;, I'm wondering if the following equalities hold:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle u_{n\mathbf{k}} | \hat{r}_x \hat{r}_y |u_{m\mathbf{k}} \rangle = -i\langle \partial_{k_x} u_{n\mathbf{k}} | \hat{r}_y |u_{m\mathbf{k}} \rangle = \langle \partial_{k_x} u_{n\mathbf{k}}  |\partial_{k_y} u_{m\mathbf{k}} \rangle&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$u_{n\mathbf{k}}=e^{-i\mathbf{k \cdot r}}\psi_{n\mathbf{k}}$&lt;/span&gt; is the cell-periodic part of the Bloch function with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; the band index and crystal momentum.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2022-01-16T14:40:53.447" Title="Electric quadrupole operator for periodic systems" Tags="|quantum-mechanics|periodic-system|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6963" PostTypeId="1" CreationDate="2021-10-29T07:10:29.963" Score="6" ViewCount="180" Body="&lt;p&gt;Following the previous threads on this topic, I would like to know the minimum supercell size suitable for Phonon spectrum calculation using Phonopy (DFPT) for CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; monolayer system given by this unit cell POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; CrI3                                    &#xA;   1.00000000000000     &#xA;     7.2414772987377169   -0.0000334312315729   -0.0000273695524433&#xA;    -3.6207634204735277    6.2714102717088256    0.0000236446352383&#xA;    -0.0000690784193687    0.0000291507055479   18.1739997862014491&#xA;   Cr   I &#xA;     2     6&#xA;Direct&#xA;  0.6666642998354509  0.3332969407635646  0.4999838454239838&#xA;  0.3333680676615832  0.6666687700374014  0.5000267181089781&#xA;  0.6449405535702791  0.9999734919584491  0.4102132677332540&#xA;  0.3551208025009766  0.3550499098699756  0.4102112382804572&#xA;  0.0000237365755498  0.6448837571827296  0.4102090416058436&#xA;  0.3550928327367056 -0.0000708711957224  0.5897938401149568&#xA;  0.6449229383444248  0.6449027058686945  0.5897995792122650&#xA;  0.0000673177750284  0.3550765345149079  0.5898047365202591&#xA; &#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;  0.00000000E+00  0.00000000E+00  0.00000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2022-01-14T02:03:39.327" LastActivityDate="2022-01-14T02:03:39.327" Title="What is the minimum supercell size for phonon spectrum calculation for this monolayer system?" Tags="|vasp|phonons|phonopy|dfpt|" AnswerCount="0" CommentCount="9" ClosedDate="2023-02-07T03:04:36.863" ContentLicense="CC BY-SA 4.0" />
  <row Id="6964" PostTypeId="1" CreationDate="2021-10-29T08:12:51.577" Score="17" ViewCount="3285" Body="&lt;p&gt;In MD simulation &lt;a href=&quot;https://images.nvidia.com/content/tesla/pdf/Molecular-Dynamics-July-2017-MB-slides.pdf&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;benchmarking&lt;/strong&gt;&lt;/a&gt;, you often see performance expressed in terms of &lt;code&gt;ns/day&lt;/code&gt; and &lt;code&gt;hours/ns&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How do I translate these values to the amount of real-time a simulation takes? In other words, what would be a reasonable value of &lt;code&gt;ns/day&lt;/code&gt; in order to run standard MD simulations using GPUs?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-10-30T20:44:48.810" LastActivityDate="2021-10-30T20:44:48.810" Title="What does ns/day mean in high-performance computing?" Tags="|molecular-dynamics|molecular-modeling|high-performance-computing|graphical-processing-unit|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6965" PostTypeId="2" ParentId="6964" CreationDate="2021-10-29T09:06:40.410" Score="14" Body="&lt;p&gt;&lt;code&gt;ns/day&lt;/code&gt; refers to the number of &lt;a href=&quot;https://en.wikipedia.org/wiki/Nanosecond&quot; rel=&quot;noreferrer&quot;&gt;nanoseconds&lt;/a&gt; (&lt;code&gt;ns&lt;/code&gt;) of simulation (referring to the variable &lt;code&gt;time&lt;/code&gt; in the simulation) that you can do in a &lt;code&gt;day&lt;/code&gt; of computation (&lt;a href=&quot;https://en.wikipedia.org/wiki/Elapsed_real_time&quot; rel=&quot;noreferrer&quot;&gt;elapsed real time or wall time&lt;/a&gt;).&#xA;It is a useful quantity to schedule one's work or to get a sense of what is achievable in a given period of time.&lt;/p&gt;&#xA;&lt;p&gt;There's no standard &lt;code&gt;ns/day&lt;/code&gt; as it depends on the type of MD (ab initio, classical, ...), its parametrization, system size, the number of CPUs/GPUs you use, etc.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="1609" LastEditDate="2021-10-29T13:03:27.023" LastActivityDate="2021-10-29T13:03:27.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6966" PostTypeId="2" ParentId="6964" CreationDate="2021-10-29T11:48:31.663" Score="12" Body="&lt;p&gt;I am providing only a basic overview of this process and so to get a complete idea of what is happening, please refer to published literature.&lt;/p&gt;&#xA;&lt;p&gt;During MD simulations, one is generally interested in how the system evolves with time (for example, the random motion of atoms cause the system temperature). Therefore, one must have an idea of how time varies for the system being modeled.&lt;/p&gt;&#xA;&lt;p&gt;To achieve this, a static image of the system is taken, and the positions, force acting on each atom and the velocities are first evaluated. Once done, the system time is advanced (the forces and velocities are integrated to obtain new positions) by a small amount of time (timestep of the simulation) and the resulting system is once again evaluated. As you can see, the system always evolves with time, and at the end of each timestep, the new forces acting on the atoms are evaluated. However when doing this in the real world, the time taken to calculate the system properties from one timestep to another becomes important.&lt;/p&gt;&#xA;&lt;p&gt;Hence the terms &lt;code&gt;ns/day&lt;/code&gt; and &lt;code&gt;hours/ns&lt;/code&gt; indicates a measure of actual time taken to calculate a &lt;code&gt;ns&lt;/code&gt; of time history in the simulation. However, as you can see, setting the timestep to a value twice as high can change the &lt;code&gt;ns/day&lt;/code&gt; measurement significantly, as only half the amount of timesteps need to be calculated to reach the same simulation time. Similarly, changing the number of atoms or even the inter-atomic interaction model would change this parameter.&lt;/p&gt;&#xA;&lt;p&gt;But if you maintain the system size, species, inter-atomic interaction models and timestep, you can now compare the performance between different computer configurations (with and without GPU, varying the number of cores or even two different computers etc.) while you do the calculation.&lt;/p&gt;&#xA;&lt;p&gt;Also since it seems that you are starting to learn MD, I suggest that you start with a bulk model of a very well established material such as Lennard-Jones (LJ) Argon (its a solid at around 40K ;P). This enables you to use a smaller system size to reduce the computational time, and you can find a significant amount of literature if you search online. Additionally the LJ potential is one of the easiest potentials to work with. But if you find a straightforward tutorial using some other bulk material, go for it without any worries. Try to understand the fundamental concepts.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="4232" LastEditDate="2021-10-29T14:27:20.370" LastActivityDate="2021-10-29T14:27:20.370" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6967" PostTypeId="1" AcceptedAnswerId="6974" CreationDate="2021-10-29T12:21:02.373" Score="7" ViewCount="188" Body="&lt;p&gt;I'm trying to use openpathsampling to simulate the binding of a ligand to my enzyme. I'm using Gromacs for my normal simulation on the HPC system provided by my university. I created an initial trajectory using some pull code for Gromacs. I tried to load this trajectory (in trr format) as described &lt;a href=&quot;http://openpathsampling.org/latest/topics/simulation_setup.html#loading-from-a-file&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from openpathsampling.engines.openmm.tools import trajectory_from_mdtraj&#xA;&#xA;init_traj = md.load(&amp;quot;md_pull_conf2_1st.trr&amp;quot;, top=&amp;quot;npt_conf2.gro&amp;quot;)&#xA;&#xA;trr = md.formats.TRRTrajectoryFile(&amp;quot;md_pull_conf2_1st.trr&amp;quot;)&#xA;vel = trr._read(n_frames=len(init_traj), atom_indices=None, get_velocities=True)[5]&#xA;&#xA;OPS_init_traj = trajectory_from_mdtraj(init_traj, velocities=vel)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, then I get the following error for the last step:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/[...]/openpathsampling/engines/openmm/tools.py&amp;quot;, line 237, in trajectory_from_mdtraj&#xA;    &#xA;NameError: name 'MDTrajTopology' is not defined&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From what I understand, in the tools.py script &lt;code&gt;MDTrajTopology&lt;/code&gt; is only imported if OpenMM in installed. Since I can't install OpenMM on the HPC system, I tried to add the following import statement outside of &lt;code&gt;if HAS_OPENMM:&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from openpathsampling.engines import Topology, MDTrajTopology&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I run the import code like this, I get the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 2, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/[...]openpathsampling/engines/openmm/tools.py&amp;quot;, line 244, in trajectory_from_mdtraj&#xA;    unit.nanometers)&#xA;  File &amp;quot;/[...]/simtk/unit/quantity.py&amp;quot;, line 170, in __init__&#xA;    if value == None:&#xA;ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also tried to load &lt;code&gt;trajectory_from_mdtraj&lt;/code&gt; from &lt;code&gt;openpathsampling.engines.openmm&lt;/code&gt; instead of &lt;code&gt;openpathsampling.engines.openmm.tools&lt;/code&gt;. Then I get the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/[...]/openpathsampling/engines/openmm/__init__.py&amp;quot;, line 2, in missing_openmm&#xA;    raise RuntimeError(&amp;quot;Install OpenMM to use this feature&amp;quot;)&#xA;RuntimeError: Install OpenMM to use this feature&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is OpenMM required just to load the trajectory? Or is there a workaround which is not dependent on OpenMM?&lt;/p&gt;&#xA;" OwnerUserId="4480" LastActivityDate="2021-11-02T15:30:31.870" Title="Import an initial trajectory into OPS without OpenMM" Tags="|gromacs|openpathsampling|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6968" PostTypeId="2" ParentId="6939" CreationDate="2021-10-29T17:11:49.573" Score="5" Body="&lt;p&gt;I agree with the answer provided by Tara Mishra in that the longer directions in real space correspond to shorter directions in reciprocal space, and therefore comparatively fewer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points are required. However, I want to provide a complementary answer: rather than explicitly writing out a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid such as &lt;span class=&quot;math-container&quot;&gt;$n_1\times n_2\times n_3$&lt;/span&gt; where you have to converge the different &lt;span class=&quot;math-container&quot;&gt;$n_i$&lt;/span&gt; separately in the most general case, you can instead use a single-parameter &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point spacing or density. This latter approach would automatically take into account that you have doubled your primitive cell in two directions but not in the third, by reducing the number of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points in the two corresponding directions in reciprocal space. The resulting convergence exercise is much simpler because you have a single parameter rather than three.&lt;/p&gt;&#xA;&lt;p&gt;I know of several codes that support this functionality, including Castep with the keyword &lt;a href=&quot;https://www.tcm.phy.cam.ac.uk/castep/Parameters/node145.html&quot; rel=&quot;noreferrer&quot;&gt;KPOINT_MP_SPACING&lt;/a&gt;, and Vasp with the keyword &lt;a href=&quot;https://www.vasp.at/wiki/index.php/KSPACING&quot; rel=&quot;noreferrer&quot;&gt;KSPACING&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2021-10-29T17:11:49.573" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6969" PostTypeId="2" ParentId="6967" CreationDate="2021-10-29T17:36:31.377" Score="5" Body="&lt;p&gt;&lt;strong&gt;Note&lt;/strong&gt;: not surprisingly, this answer doesn't resolve the main issue. See dwhswenson's answer for a full fix.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;trajectory_from_mdtraj((mdtrajectory, simple_topology=False, velocities=None)&lt;/code&gt; is the &lt;a href=&quot;https://github.com/openpathsampling/openpathsampling/blob/7443c83d87322cc1593f8d91a07580cc1c6528d5/openpathsampling/engines/openmm/tools.py#L207&quot; rel=&quot;nofollow noreferrer&quot;&gt;full signature&lt;/a&gt; for the method you are calling. Within the method, there is this small segment, which controls whether &lt;code&gt;MDTrajTopology&lt;/code&gt; is used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;if simple_topology:&#xA;    topology = Topology(*mdtrajectory.xyz[0].shape)&#xA;else:&#xA;    topology = MDTrajTopology(mdtrajectory.topology)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So specifying &lt;code&gt;simple_topology=True&lt;/code&gt; should let you use OPS's native topology checker. I haven't tested this to ensure your example will work, but from looking at the code it seems like this would enough to skip around the OpenMM dependency.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-10-29T23:48:46.810" LastActivityDate="2021-10-29T23:48:46.810" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6970" PostTypeId="2" ParentId="6127" CreationDate="2021-10-29T17:45:55.913" Score="3" Body="&lt;p&gt;This may not be the issue, but the manual says the &lt;code&gt;max_seconds&lt;/code&gt; keyword under &lt;code&gt;&amp;amp;control&lt;/code&gt; is maximum CPU time, not wall time, the calculation will run. So if you ran the calculation on even two CPUs, it would likely die if it ran for roughly half the given time, so 43200 seconds or 12 hrs.&lt;/p&gt;&#xA;&lt;p&gt;So your calculation may have just timed out. In most programs, an abort in an error message means the job was cancelled by the user or ran out of time unexpectedly.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-10-29T17:45:55.913" CommentCount="0" CommunityOwnedDate="2021-10-29T17:45:55.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="6971" PostTypeId="2" ParentId="6730" CreationDate="2021-10-29T18:51:44.423" Score="4" Body="&lt;p&gt;I think Camps has the right idea here: Make the image with gnuplot as large as you need, then scale the size down in whatever program you are using to write your paper.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-10-29T18:51:44.423" CommentCount="0" CommunityOwnedDate="2021-10-29T18:51:44.423" ContentLicense="CC BY-SA 4.0" />
  <row Id="6972" PostTypeId="2" ParentId="6762" CreationDate="2021-10-29T19:13:35.287" Score="4" Body="&lt;p&gt;After running some tests, the best way to overcome the slow performance was to simply use the constraints no &lt;code&gt;h-bonds&lt;/code&gt;. There was no significant difference in densities and diffusion coefficient when constraint was changed to &lt;code&gt;all-bonds&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2021-10-29T19:13:35.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6973" PostTypeId="2" ParentId="6925" CreationDate="2021-10-29T19:14:42.863" Score="5" Body="&lt;p&gt;Personally, I prefer to use the second option.&lt;/p&gt;&#xA;&lt;p&gt;The full description of first option is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tot_charge  REAL&#xA;Default:    0.0&#xA;&#xA;    Total charge of the system. Useful for simulations with charged cells.&#xA;    By default the unit cell is assumed to be neutral (tot_charge=0).&#xA;    tot_charge=+1 means one electron missing from the system,&#xA;    tot_charge=-1 means one additional electron, and so on.&#xA;&#xA;    In a periodic calculation a compensating jellium background is&#xA;    inserted to remove divergences if the cell is not neutral.&#xA;             &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, with this option, you are indicating that your cell is not neutral but without specifying where the charge is located.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the full description of the second option is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;starting_charge(i), i=1,ntyp    REAL&#xA;Default:    0.0&#xA;&#xA;    starting charge on atomic type 'i',&#xA;    to create starting potential with startingpot = 'atomic'.&#xA;             &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this case, you are in control where the charge is initially located. Also, you can specify the potential (keyword &lt;code&gt;startingpot&lt;/code&gt;) being calculated from the charges of the system or from a file (previous calculation):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;startingpot     CHARACTER&#xA;&#xA;     Available options are:&#xA;                &#xA;&#xA;    'atomic' :&#xA;&#xA;        starting potential from atomic charge superposition&#xA;        (default for scf, *relax, *md)&#xA;                    &#xA;&#xA;    'file' :&#xA;&#xA;        start from existing &amp;quot;charge-density.xml&amp;quot; file in the&#xA;        directory specified by variables prefix and outdir&#xA;        For nscf and bands calculation this is the default&#xA;        and the only sensible possibility.&#xA;                    &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-29T19:14:42.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6974" PostTypeId="2" ParentId="6967" CreationDate="2021-10-29T19:18:32.753" Score="6" Body="&lt;p&gt;Snapshot types in OpenPathSampling depend on the type of engine you're using. To some extent, snapshot types can be interchanged (if you had OpenMM available, I think the approach you're trying would work), but the OPS Gromacs engine has some different internals.&lt;/p&gt;&#xA;&lt;p&gt;The Gromacs engine in OpenPathSampling mainly uses externally-defined trajectories (that is, trajectories that exist in external files, not in the internal format used by OPS). In this way, it is very different from the OpenMM engine, which stores everything in the internal format. Because the Gromacs engine only saves a reference to a file, if you need to recalculate something from an existing TRR file, it needs to be at the same relative path to the original when you use it later (example below).&lt;/p&gt;&#xA;&lt;p&gt;Here's the overall process I would recommend to load a TRR file for use with Gromacs (code follows):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Create the engine that you'll use for the dynamics.&lt;/li&gt;&#xA;&lt;li&gt;Use the engine's &lt;code&gt;read_frame_from_file&lt;/code&gt; method to load the snapshots and wrap them in an OPS &lt;code&gt;Trajectory&lt;/code&gt; object.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;(Side note: In the following, I'll use list comprehensions (things that look like&lt;code&gt;[f(x) for x in a_list]&lt;/code&gt;). If you (OP, or possibly a future reader) aren't familiar with list comprehensions, I recommend &lt;a href=&quot;https://treyhunner.com/2015/12/python-list-comprehensions-now-in-color/&quot; rel=&quot;noreferrer&quot;&gt;Trey Hunner's description&lt;/a&gt;.)&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import openpathsampling as paths&#xA;&#xA;# MDTraj only used in this script to get the number of frames&#xA;# (but OPS uses it internally, so you need it on your system)&#xA;import mdtraj as md&#xA;&#xA;# change these filenames and the engine definition to meet your needs&#xA;trr_file = &amp;quot;example.trr&amp;quot;&#xA;pdb_file = &amp;quot;example.pdb&amp;quot;&#xA;engine = paths.engines.gromacs.Engine(&#xA;    gro=pdb_file,  # using pdb gives better MDTraj integration than gro&#xA;    mdp=&amp;quot;md.mdp&amp;quot;,&#xA;    top=&amp;quot;topol.top&amp;quot;,&#xA;    options={&#xA;        'snapshot_timestep': 0.02,&#xA;        'n_frames_max': 10000,&#xA;        'grompp_args': &amp;quot;-maxwarn 1&amp;quot;,  # may be specific to my example.pdb&#xA;    }&#xA;).named(&amp;quot;engine&amp;quot;)&#xA;n_frames = len(md.load(trr_file, top=pdb_file))&#xA;&#xA;# external_traj uses externally-stored snapshots&#xA;external_traj = paths.Trajectory([engine.read_frame_from_file(trr_file, num)&#xA;                                  for num in range(n_frames)])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From here, you can even save that &lt;code&gt;external_traj&lt;/code&gt; and reuse it:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;st = paths.Storage(&amp;quot;setup.nc&amp;quot;, mode='w')&#xA;st.save(external_traj)&#xA;st.close()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;About keeping the original trajectory with the file: Now lets say I run the OPS command line from a subdirectory. From your shell (if you've installed the &lt;a href=&quot;https://github.com/openpathsampling/openpathsampling-cli&quot; rel=&quot;noreferrer&quot;&gt;OpenPathSampling CLI&lt;/a&gt;) what happens if you run:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;mkdir subdir &amp;amp;&amp;amp; cd subdir&#xA;openpathsampling md ../setup.nc -e engine --init-frame -1 --nsteps 10 -o output.nc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(where &lt;code&gt;--init-frame -1&lt;/code&gt; will use the file's last frame as the initial frame.) Well, right now, you'll get a mess of an error that includes &lt;code&gt;OSError: The file 'example.trr' doesn't exist&lt;/code&gt;. This is because OPS expects a file called &lt;code&gt;example.trr&lt;/code&gt; in your current working directory. Fix it with:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;cp ../example.trr ./&#xA;openpathsampling md ../setup.nc -e engine --init-frame -1 --nsteps 10 -o output.nc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And you'll see it runs Gromacs! Point of this digression: If you need the data from the TRR file, you'll need the TRR file. You'll also need to ensure it has the same path relative to your working directory. Be very careful not put a different file there with the same name, or you could get nonsense results!&lt;/p&gt;&#xA;&lt;p&gt;(This isn't a concern for other Gromacs files, such as the options for &lt;code&gt;mdp&lt;/code&gt;, &lt;code&gt;gro&lt;/code&gt;, and &lt;code&gt;top&lt;/code&gt;. Those files are actually stored with the OPS engine, and will be recreated if the directory is missing them.)&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-10-29T19:18:32.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6975" PostTypeId="2" ParentId="4076" CreationDate="2021-10-29T19:20:07.657" Score="2" Body="&lt;p&gt;I would make the argument that for a single, fixed configuration of some system, charge analysis doesn't tell you much. Since &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1439/what-are-the-types-of-charge-analysis&quot;&gt;different methods for computing charges&lt;/a&gt; can vary widely in the value they produce and atomic charge isn't an observable, the absolute value of charge/population on an atom isn't necessarily meaningful.&lt;/p&gt;&#xA;&lt;p&gt;However, like many properties in computational chemistry, useful information can be derived from differences in these populations between related structures. This could mean, for example, looking at the population for different conformers of a molecule, how the population varies over the course of a reaction, or a family of molecules with varying substitutions/dopants.&lt;/p&gt;&#xA;&lt;p&gt;Taking the reaction example, you might be interested in figuring out why, intuitively, a given reaction occurs, beyond just determining that the products are more stable than the reactants. By monitoring the charge of key atoms over the reaction pathway, you may be able to determine a reason why the reaction proceeds by that mechanism (e.g. the reaction may reduce the charge on a metal center).&lt;/p&gt;&#xA;&lt;p&gt;So I would say there is quite a lot you can do with charges, but it is very context dependent what information you can or want to derive from them.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-10-29T19:20:07.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6976" PostTypeId="2" ParentId="6403" CreationDate="2021-10-29T19:34:55.540" Score="3" Body="&lt;p&gt;Some years ago I found the following steps in &lt;a href=&quot;https://www.researchgate.net/post/How_could_we_find_thermal_conductivity_using_Phonon_band_structure_Particularly_step_by_step_using_Quantum_Espresso&quot; rel=&quot;nofollow noreferrer&quot;&gt;ResearchGate&lt;/a&gt;:&#xA;You need:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.quantum-espresso.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuantumEspresso&lt;/a&gt; (QE)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://phonopy.github.io/phono3py/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phono3py&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.shengbte.org/home&quot; rel=&quot;nofollow noreferrer&quot;&gt;ShengBTE &amp;amp; thirdorder.py&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;First, you need to create a QE input file (&lt;code&gt;pwscf&lt;/code&gt;), using &lt;code&gt;ibrav=0&lt;/code&gt;,&#xA;lattice vectors in bohr units, atomic coordinates in crystal units.&lt;/li&gt;&#xA;&lt;li&gt;Using the input file, run &lt;code&gt;phono3py/third_order.py&lt;/code&gt; to create supercell&#xA;within finite displacement method.&lt;/li&gt;&#xA;&lt;li&gt;Then you need to write a script&#xA;that will copy all header option, specially &lt;code&gt;&amp;amp;control&lt;/code&gt; and &lt;code&gt;&amp;amp;system&lt;/code&gt; to&#xA;each supercell file and rename to &lt;code&gt;scf.in&lt;/code&gt; and generate sequential&#xA;folder namely, &lt;code&gt;disp-00001&lt;/code&gt;..., ect.&lt;/li&gt;&#xA;&lt;li&gt;Now run &lt;code&gt;pwscf&lt;/code&gt; for each supercell and&#xA;please do not forget to select force calculation in &lt;code&gt;pwscf&lt;/code&gt; input file.&lt;/li&gt;&#xA;&lt;li&gt;After this step you need to run &lt;code&gt;phono3py&lt;/code&gt; to calculate second order&#xA;(harmonic) and third order (anharmonic) force constants.&lt;/li&gt;&#xA;&lt;li&gt;Finally, run &lt;code&gt;phono3py&lt;/code&gt; to calculate lattice thermal conductivity using dense q-point grid and primitive cell.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-29T19:34:55.540" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6977" PostTypeId="2" ParentId="6730" CreationDate="2021-10-29T22:02:19.523" Score="3" Body="&lt;p&gt;Output to a large size with a lot of whitespace (A4 is usually fine) and then trim the whitespace using &lt;code&gt;pdfcrop&lt;/code&gt;, a command line tool included in every latex distribution. &lt;a href=&quot;https://tex.stackexchange.com/a/25807/82370&quot;&gt;See this great answer&lt;/a&gt; Pdfcrop is really reliable, so I do this for all my PDF graphics before I put them in my papers so tex can handle them consistently and I don't end up with weird tiny figures surrounded by whitespace.&lt;/p&gt;&#xA;" OwnerUserId="97" LastActivityDate="2021-10-29T22:02:19.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6978" PostTypeId="1" AcceptedAnswerId="7055" CreationDate="2021-10-30T00:04:16.360" Score="8" ViewCount="106" Body="&lt;p&gt;I have a polymer and solvent on a lattice, and I am performing an NVT Monte Carlo simulation. I am performing the following moves on it:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3mJXb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3mJXb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, how should these moves be conducted to effectively sample phase space? I have 4 functions written up: &lt;code&gt;end_rotation(), kink_jump, crankshaft(), reptation()&lt;/code&gt;, which I can call sequentially in my code - but I want to understand what is the best way to call them to sample as much of this ensemble as I can to get meaningful statistics from this - something like the Flory exponent.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="625" LastEditDate="2021-11-03T15:43:52.907" LastActivityDate="2021-11-13T20:45:53.657" Title="How often does one have to run polymer Monte Carlo moves to effectively sample phase space?" Tags="|statistical-thermodynamics|monte-carlo|polymers|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="6979" PostTypeId="1" CreationDate="2021-10-30T00:32:48.817" Score="6" ViewCount="65" Body="&lt;p&gt;I would like to model magnetic field of a permanent magnet like this one &lt;a href=&quot;https://www.magnet4less.com/diametrically-magnetized-n50-neodymium-magnet-1-4-in-x-1-2-in-cylinder?gclid=Cj0KCQjwt-6LBhDlARIsAIPRQcLFxN6WzdzDA1_n9qiQGflnW0oRf_lLmS-oh1HBQgYHBysKOyR-sdQaAmMaEALw_wcB&quot; rel=&quot;nofollow noreferrer&quot;&gt;magnet&lt;/a&gt; . Ideally, I would like to do it python or any other language. I would like to start with some simple geometry and some properties of the material and end up with vector field. I am planning to move this vector field around and observe generated voltage. So far I found a couple of python libraries and &lt;a href=&quot;https://www.femm.info/wiki/HomePage&quot; rel=&quot;nofollow noreferrer&quot;&gt;FEMM&lt;/a&gt; with Python API. FEMM looks the most promising, but really hard to understand. Are there any tutorials for FEMM? Also what does the modelling process consists off? I see that finite element method is used, but I am not clear why are we trying to solve certain equations numerically? Do we represent permanent magnet as coil and the using Maxwell equation trying to figure out the vector field? What if our permanent magnet shape is far from simple coil geometry? I am willing to start with something simple like finite difference. Too many questions, not sure where to start.&lt;/p&gt;&#xA;" OwnerUserId="4063" LastEditorUserId="5" LastEditDate="2022-01-14T02:04:13.113" LastActivityDate="2022-01-14T02:04:13.113" Title="Modeling magnetic field of permanent magnet: Where to start?" Tags="|magnetism|finite-element-analysis|" AnswerCount="0" CommentCount="2" ClosedDate="2022-02-24T14:22:24.867" ContentLicense="CC BY-SA 4.0" />
  <row Id="6980" PostTypeId="1" CreationDate="2021-10-30T00:52:08.217" Score="6" ViewCount="1219" Body="&lt;p&gt;I have two PDB files (each corresponding to a ligand and a receptor).&#xA;Each downloaded separately from &lt;a href=&quot;https://www.rcsb.org&quot; rel=&quot;noreferrer&quot;&gt;PDB&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I'd like to perform ligand to protein docking process with MD with &lt;a href=&quot;https://www.gromacs.org&quot; rel=&quot;noreferrer&quot;&gt;GROMACS&lt;/a&gt; or &lt;a href=&quot;https://ambermd.org&quot; rel=&quot;noreferrer&quot;&gt;Amber&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Using those two files directly, does GROMACS/Amber automatically perform the docking for us?&#xA;Or should we give the pre-docked PDB files?&#xA;These pre-docked PDB files may come from rigid-body docking tools like &lt;a href=&quot;https://cluspro.bu.edu&quot; rel=&quot;noreferrer&quot;&gt;ClusPro&lt;/a&gt; or flexible docking like &lt;a href=&quot;http://flexpepdock.furmanlab.cs.huji.ac.il/index.php&quot; rel=&quot;noreferrer&quot;&gt;FlexPepDock&lt;/a&gt; .&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2021-10-30T03:20:45.927" LastActivityDate="2021-10-30T13:16:15.883" Title="How to initiate protein-ligand docking with MD simulation tools" Tags="|molecular-dynamics|gromacs|docking|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6981" PostTypeId="1" CreationDate="2021-10-30T00:59:55.103" Score="6" ViewCount="436" Body="&lt;p&gt;I would like to learn more about Charge density different and would like suggestion for how to get any information from the Charge Density Different plots. How accurate it is and if anyone have suggestion on book or articles talking about it.&#xA;I have been searching and most of the literatures i found only talk briefly about it.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your suggestion!&lt;/p&gt;&#xA;" OwnerUserId="4021" LastActivityDate="2021-10-30T12:58:21.523" Title="How to extract information from Charge Density Different?" Tags="|vasp|charge-density|charge-transfer|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6982" PostTypeId="1" AcceptedAnswerId="7007" CreationDate="2021-10-30T01:34:41.707" Score="10" ViewCount="1631" Body="&lt;p&gt;I have the following SMILES, wrapped in Python RDKit:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;m = Chem.MolFromSmiles('[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there away I can convert that into an Amino acid sequence, e.g, &lt;code&gt;KKAW&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;I'm open to other solution than RDKit.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem.rdmolfiles import MolFromMolFile, MolToFASTA&#xA;fa = MolToFASTA( Chem.MolFromSmiles('[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O')) &#xA;fa&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But &lt;code&gt;fa&lt;/code&gt; returns empty string.&lt;/p&gt;&#xA;&lt;p&gt;Documentation said this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;rdkit.Chem.rdmolfiles.MolToFASTA((Mol)mol) → str :&#xA;Returns the FASTA string for a molecule&#xA;ARGUMENTS:&#xA;&#xA;mol: the molecule&#xA;&#xA;NOTE: the molecule should contain monomer information in AtomMonomerInfo structures&#xA;&#xA;RETURNS:&#xA;&#xA;a string&#xA;&#xA;C++ signature :&#xA;std::__cxx11::basic_string&amp;lt;char, std::char_traits&amp;lt;char&amp;gt;, std::allocator&amp;lt;char&amp;gt; &amp;gt; MolToFASTA(RDKit::ROMol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't know how to check if my mol contains &lt;code&gt;monomer information in AtomMonomerInfo structures&lt;/code&gt;. And how to add it if it doesn't have those.&lt;/p&gt;&#xA;" OwnerUserId="4479" LastEditorUserId="4479" LastEditDate="2021-11-01T12:23:56.207" LastActivityDate="2021-11-04T01:27:43.743" Title="How to convert SMILES to Amino Acids sequence using RDKit" Tags="|computational-chemistry|rdkit|smiles|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6983" PostTypeId="2" ParentId="6980" CreationDate="2021-10-30T05:48:34.480" Score="7" Body="&lt;p&gt;You can do it either way.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You need to give predocked files to &lt;a href=&quot;https://www.gromacs.org/&quot; rel=&quot;noreferrer&quot;&gt;GROMACS&lt;/a&gt;/&lt;a href=&quot;https://ambermd.org/&quot; rel=&quot;noreferrer&quot;&gt;Amber&lt;/a&gt; for running protein-ligand complex molecular simulations. Also have a look at &lt;a href=&quot;https://wenmr.science.uu.nl/haddock2.4/&quot; rel=&quot;noreferrer&quot;&gt;HADDOCK&lt;/a&gt; web server for predocking.&lt;/li&gt;&#xA;&lt;li&gt;Place the receptor outside the interaction range of your protein (randomly) and run an MD simulation, to find the binding regions. But you need to do multiple MD runs to make sure that the binding region observed is not an local minima (event).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;And why outside the interaction range of the protein, This is to ensure that you results are not biased on the position of the ligand.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/cn300091a&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/full/10.1021/cn300091a&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="3593" LastEditDate="2021-10-30T08:56:08.407" LastActivityDate="2021-10-30T08:56:08.407" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="6984" PostTypeId="2" ParentId="6981" CreationDate="2021-10-30T12:58:21.523" Score="4" Body="&lt;h1&gt;Multiwfn&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiwfn&lt;/a&gt; is a package you can use to obtain a lot of electronic properties from the system wave function.&lt;/p&gt;&#xA;&lt;h3&gt;Major functions of Multiwfn&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Showing molecular structure and viewing orbitals (MO, NBO, natural orbital, NTO, LMO, etc.). Speed of generating orbital graph is extremely fast, and the use is very convenient.&lt;/li&gt;&#xA;&lt;li&gt;Calculating real space function in a plane and plot plane map. Supported graph types include filled-color map, contour map, relief map (with/without projection), gradient map and vector field map.&lt;/li&gt;&#xA;&lt;li&gt;Topology analysis for any real space function, such as electron density (AIM analysis), Laplacian, ELF, LOL, electrostatic potential and so on. Critical points (CPs) can be located, topology paths and interbasin surfaces can be generated, and then they can be directly visualized in a 3D GUI window or be plotted in plane map.&lt;/li&gt;&#xA;&lt;li&gt;Population analysis. Hirshfeld, Hirshfeld-I, VDD, Mulliken, Löwdin, Modified Mulliken (including three methods: SCPA, Stout &amp;amp; Politzer, Bickelhaupt), Becke, ADCH (Atomic dipole moment corrected Hirshfeld), CM5, 1.2*CM5, CHELPG, Merz-Kollmann, RESP (Restrained ElectroStatic Potential), RESP2, AIM (Atoms-In-Molecules), EEM (Electronegativity Equalization Method) and PEOE (Gasteiger) are supported. Electrostatic interaction energy of two given fragments can be calculated based on atomic charges.&#xA;-Charge decomposition analysis (CDA) and extended CDA analysis. Orbital interaction diagram can be plotted. Infinite number of fragments can be defined.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Real space functions supported by Multiwfn&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Electron density&lt;/li&gt;&#xA;&lt;li&gt;Gradient norm of electron density&lt;/li&gt;&#xA;&lt;li&gt;Laplacian of electron density&lt;/li&gt;&#xA;&lt;li&gt;Value of orbital wavefunction&lt;/li&gt;&#xA;&lt;li&gt;Electron spin density&lt;/li&gt;&#xA;&lt;li&gt;Hamiltonian kinetic energy density K(r)&lt;/li&gt;&#xA;&lt;li&gt;Lagrangian kinetic energy density G(r)&lt;/li&gt;&#xA;&lt;li&gt;Electrostatic potential from nuclear / atomic charges&lt;/li&gt;&#xA;&lt;li&gt;Electron localization function (ELF) defined by Becke and the one defined by Tsirelson&lt;/li&gt;&#xA;&lt;li&gt;Electron delocalization range function EDR(r;d) and orbital overlap distance function D(r).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can download it from here: &lt;a href=&quot;http://sobereva.com/multiwfn/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/download.html&lt;/a&gt;&lt;br /&gt;&#xA;The &lt;a href=&quot;http://sobereva.com/multiwfn/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; has all the information you need not only about how to use the program but also about the description of each method used (with their references).&#xA;It has a &lt;a href=&quot;http://sobereva.com/multiwfn/misc/Multiwfn%20quick%20start.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quick Start&lt;/a&gt; guide and a discussion &lt;a href=&quot;http://sobereva.com/wfnbbs/&quot; rel=&quot;nofollow noreferrer&quot;&gt;forum&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-30T12:58:21.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6985" PostTypeId="2" ParentId="6980" CreationDate="2021-10-30T13:16:15.883" Score="6" Body="&lt;p&gt;Docking and Molecular dynamics are two very different process.&lt;/p&gt;&#xA;&lt;p&gt;In docking, you will need the ligand (normally in a separate file), the protein (can be in a separate file too), and the information about the site where you want to dock the ligand. This information can be some residues or simple a (x,y,z) coordinate. Then the docking program will generate a library of initial ligand conformations, put in the site you specified and then score the interaction ligand/protein using a score function.&lt;br /&gt;&#xA;The docking software can do rigid/rigid docking (protein rigid/ligand rigid), rigid/flexible (protein rigid/ligand flexible) or flexible/flexible (protein flexible/ligand flexible). The last one is not always fully available.&lt;br /&gt;&#xA;This is a very fast technique where you can do virtual throughput screening with thousand of ligands even on a personal computer/notebook.&lt;/p&gt;&#xA;&lt;p&gt;Molecular dynamics (MD) will need a protein/ligand complex with the ligand already in the site where you want to study the interactions. For this step you can use a complex resulting from a docking simulation or just a complex that you create in a molecular drawing software (you can load both molecules and them move the ligand until it is in the regions you want). The MD software then will solve the Newton's equation of movement where the position, velocity, acceleration and force on each atom is calculated.&lt;br /&gt;&#xA;In this case, both protein and ligand will be treated as flexible. MD is a very time and computational resource demanding task. The best way to perform MD is using a GPU.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-10-30T13:16:15.883" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6986" PostTypeId="2" ParentId="6964" CreationDate="2021-10-30T20:44:16.487" Score="6" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;ns/day&lt;/strong&gt; measures the number of nanoseconds of the system's dynamics that can be simulated in 1 day of computing.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;hours/ns&lt;/strong&gt; measures the number of hours of computing required to simulate 1 nanosecond of the system's dynamics.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Both of these are extremely hardware-dependent and even more importantly, depend on the size of the system being simulated. In the link you gave us to NVIDIA's presentation which uses these terms, you can see that increasing the number of atoms in the system being simulated, slowed down the calculation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;470 ns/day on 1 GPU for L-Iduronic acid (1362 atoms) &lt;br&gt;&#xA;116 ns/day on 1 GPU for DHFR (23K atoms)&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-10-30T20:44:16.487" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6987" PostTypeId="1" AcceptedAnswerId="10483" CreationDate="2021-10-30T23:06:40.567" Score="6" ViewCount="3009" Body="&lt;p&gt;I have the following Pymol visual,&#xA;The green molecule is receptor and red/yellow is the ligand.&#xA;In the ligand I highlighted Lysine (K) residue as yellow.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GJy8Kl.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GJy8Kl.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I want to do is to highlight and draw the electro static contact of the ligand especially with Lysine residue. Like this in Pymol:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/M8lCum.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/M8lCum.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How can I achieve that?&lt;/p&gt;&#xA;&lt;p&gt;I'm open to other solution other than Pymol, e.g. VMD.&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2021-10-31T10:46:56.880" LastActivityDate="2023-02-25T11:18:48.867" Title="How to show electrostatic interactions in Pymol or other on the wanted residue" Tags="|proteins|vmd|pymol|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="6988" PostTypeId="1" CreationDate="2021-10-31T04:56:46.263" Score="10" ViewCount="3027" Body="&lt;p&gt;I have a ligand and receptor to simulate with MD. These are my specs:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Receptor has 4674 atoms,&lt;/li&gt;&#xA;&lt;li&gt;Ligand has 273 atoms&lt;/li&gt;&#xA;&lt;li&gt;CHARMM force field&lt;/li&gt;&#xA;&lt;li&gt;MD software GROMACS&lt;/li&gt;&#xA;&lt;li&gt;Computing machine: Amazon &lt;a href=&quot;https://aws.amazon.com/ec2/instance-types/g4/&quot; rel=&quot;noreferrer&quot;&gt;g4dn.xlarge&lt;/a&gt; (1 GPU 4vCPUs)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;10ns&lt;/code&gt; of dynamics&lt;span class=&quot;math-container&quot;&gt;$^*$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;What's the time needed to run the MD (i.e. in hr, days)?&#xA;How to calculate and is there a formula to calculate it?&#xA;I need to estimate the cost of using the Amazon machine.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^*$&lt;/span&gt; I'm not sure the reasonable value for the timing&#xA;required for the dynamics. Please advice too.&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4232" LastEditDate="2021-10-31T07:22:45.907" LastActivityDate="2021-10-31T09:02:34.760" Title="How to calculate the computational time required for a MD simulation" Tags="|molecular-dynamics|proteins|benchmark-timings|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6989" PostTypeId="2" ParentId="6988" CreationDate="2021-10-31T07:43:04.547" Score="14" Body="&lt;p&gt;The simulation speed and efficiency depends on the hardware and software that you use. Things that you should keep in mind are,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Every computer is unique in its ability. So only someone with access to the exact same hardware (processor, gpu etc.) can test this out and tell you.&lt;/li&gt;&#xA;&lt;li&gt;As far as I know, there is no established method of calculating the computational time required for a calculation. But you can test this for yourself and get a scaling graph of how the number of atoms and cpu cores change the computational efficiency (This is valid only for a similar use case and so do not expect someone else's work to give a proper prediction).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;That said, there actually are some things that you can try. First reduce the amount of dynamics that you simulate from &lt;code&gt;10ns&lt;/code&gt; to say a &lt;code&gt;several hundred pico seconds&lt;/code&gt; thereby reducing the computational time required. This way, you can achieve a very small calculation, at the end of which, you would see the computational speed prediction from the MD software (usually in the form of &lt;code&gt;hours/ns&lt;/code&gt; or &lt;code&gt;ns/day&lt;/code&gt;). Once you know this, you can get an idea of how long the calculation might take for a &lt;code&gt;10ns&lt;/code&gt; dynamics length. However, do keep note that this estimation could have a small error and so it would be best to have some extra time allocated.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;When doing this, remember that if the calculation writes files to the hard drive frequently, the time taken to write those files would slow the simulation down. This would be slightly difficult to account for in the initial short run. Also keep in mind that different ensembles have different computational speeds. For example, in my workstation, the NVE ensemble can be calculated around 50% faster than the NPT ensemble. However I do not know whether this is universal or not.&lt;/p&gt;&#xA;&lt;p&gt;Also do note that as you proceed with your work, you would gain experience regarding the time taken for each calculation. With that experience, you would be able to get a pretty good guess of how long it takes (as long as the computer remains the same).&lt;/p&gt;&#xA;&lt;p&gt;Since you seem to be just starting MD calculations, keep in mind that more cores is not always faster. Sometimes increasing the number of cores can reduce the computational efficiency by increasing communication time. So it would be best to try changing the number of cores allocated to see the configuration that gives the best performance.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-10-31T07:43:04.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="6990" PostTypeId="2" ParentId="6988" CreationDate="2021-10-31T09:02:34.760" Score="11" Body="&lt;p&gt;&lt;strong&gt;Short answer: Do a short test run for performance estimates.&lt;/strong&gt; Once you're familiar with a specific hardware/software combination, you may be able to estimate based on the size of the system, but the general advice (especially with hardware you're not familiar with) is to do a short benchmarking run.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Gromacs-specific practical advice:&lt;/strong&gt; Use the &lt;code&gt;-maxh&lt;/code&gt; option to &lt;code&gt;gmx mdrun&lt;/code&gt; (&lt;a href=&quot;https://manual.gromacs.org/documentation/current/onlinehelp/gmx-mdrun.html#gmx-mdrun&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;). This will allow you to run for a fixed amount of wall time, letting you benchmark for a fixed cost (say, 1 hour compute time). You can run for 1 hour, and get a good estimate of ns/day by multiplying the result number of ns by 24, and use that in production run cost estimates. (You probably can get a decent estimate from 10-15 minutes; much less than that may not give accurate results.) Note: performance can vary from run to run, even on the same hardware. This is especially true if you use some of Gromacs's tools to auto-optimize performance.&lt;/p&gt;&#xA;&lt;p&gt;Another option: since you'll typically want to equilibrate in NVT and/or NPT before starting a production run, you can use the equilibration run as your benchmark.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Side notes:&lt;/strong&gt; Not specific to the question here, but I see a couple red flags in the description. (1) You don't list waters. Are you intending to run with an implicit water model? If not, then keep in mind the majority of your atoms will be water. This is especially true if you're studying the ligand binding/unbinding process, where you typically need to pad with more water than just a globular protein with the same number of residues (you need a simulation box big enough for the fully unbound ligand-receptor system). (2) 10ns is a pretty short run. For biomolecular systems with molecular mechanics force fields, I would usually do multiple runs (minimum 4, typically 8-10) of at least 100ns each, and that's just to characterize a stable basin. If you're interested in transitions (binding/unbinding) the timescales are typically much longer, and in many cases aren't feasible by direct molecular dynamics -- enhanced sampling methods are required.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-10-31T09:02:34.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6991" PostTypeId="1" AcceptedAnswerId="6997" CreationDate="2021-10-31T17:16:17.387" Score="5" ViewCount="1696" Body="&lt;p&gt;I am trying to dock a ligand that features a boron (B) atom. AutoDock Vina throws an error with the following message:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ATOM syntax incorrect: &amp;quot;B&amp;quot; is not a valid AutoDock type. Note that AutoDock atom types are case-sensitive.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I assumed that the error meant that I had to add boron to my &lt;code&gt;Lib\site-packages\AutoDockTools\AD4_parameters.dat&lt;/code&gt; file. I found the following parameters for boron in a discussion on the topic:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atom_par B      4.08  0.180  12.052   -0.00110  0.0  0.0  0  -1  -1  4  # Non H-bonding&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Together with &lt;code&gt;AD4_parameters.dat&lt;/code&gt;, I also added that line to &lt;code&gt;AD4.1_bound.dat&lt;/code&gt;, which is in the same directory as &lt;code&gt;AD4_parameters.dat&lt;/code&gt;, and to &lt;code&gt;..\AMDock\programs\AD4Zn.dat&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;But I am still getting the same &lt;code&gt;ATOM syntax incorrect&lt;/code&gt; error. Most of the links returned by a web search are from a Scripps Research web site that is no longer available.&lt;/p&gt;&#xA;&lt;p&gt;Any help would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3719" LastEditorUserId="5" LastEditDate="2021-11-01T15:54:54.173" LastActivityDate="2024-02-02T09:14:20.073" Title="How can I get Vina to recognise boron atoms?" Tags="|docking|autodock|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6992" PostTypeId="2" ParentId="4757" CreationDate="2021-10-31T20:31:30.893" Score="6" Body="&lt;pre&gt;&lt;code&gt;import math&#xA;import csv&#xA;&#xA;filename = input('Nome?')&#xA;dic_atomo = {}&#xA;dic_atomo_neigh = {}&#xA;&#xA;with open(filename,'r') as f:&#xA;&#xA;    for line in f.readlines()[1:]:&#xA;&#xA;        line = line.split()&#xA;&#xA;        dic_atomo[line[0]] = (float(line[2]),float(line[3]),float(line[4]))&#xA;&#xA;        dic_atomo_neigh[line[0]] =(line[6],line[7],line[8])&#xA;&#xA;       &#xA;&#xA;lista_d = []&#xA;&#xA;print (dic_atomo)&#xA;&#xA;&#xA;&#xA;for i in list(dic_atomo):&#xA;&#xA;    x = dic_atomo[i][0]&#xA;&#xA;    y = dic_atomo[i][1]&#xA;&#xA;    z = dic_atomo[i][2]&#xA;&#xA;    for j in list(dic_atomo_neigh[i]):&#xA;&#xA;        if i != j:&#xA;&#xA;            x1 = dic_atomo[j][0]&#xA;&#xA;            y1 = dic_atomo[j][1]&#xA;&#xA;            z1 = dic_atomo[j][2]&#xA;&#xA;            print(&amp;quot;{} - ({},{},{}) - {} - ({},{},{}) &amp;quot;.format(i,x,y,z,j,x1,y1,z1))&#xA;&#xA;            d=math.sqrt((x1-x)**2+(y1-y)**2+(z1-z)**2)&#xA;&#xA;            a = (i,j,d)&#xA;&#xA;            lista_d.append(a)&#xA;&#xA;        &#xA;&#xA;print(lista_d)&#xA;&#xA;&#xA;&#xA;&#xA;&#xA;&#xA;&#xA;filename=input('Nome final? ')&#xA;&#xA;with open(filename, 'w') as csvfile:&#xA;&#xA;    csvwriter = csv.writer(csvfile)&#xA;&#xA;    csvwriter.writerows(lista_d)&#xA;&#xA;    &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3429" LastActivityDate="2021-10-31T20:31:30.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6993" PostTypeId="1" CreationDate="2021-11-01T02:04:24.610" Score="10" ViewCount="519" Body="&lt;p&gt;Quasicrystals show repeating motifs or patterns but are not periodic. And yet their &lt;em&gt;Fourier transforms&lt;/em&gt; invariably demonstrate a pattern of sharp peaks revealing that there is still an underlying... something.&lt;/p&gt;&#xA;&lt;p&gt;Generally if one works hard one can show that a quasicrystal proper of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; dimensions is actually a manifestation of periodic lattice of at least &lt;span class=&quot;math-container&quot;&gt;$n+1$&lt;/span&gt; dimensions. For example, some 3D quasicrystals with 10 and 12 fold symmetry have been shown to come from 5 dimensional lattices sliced at &amp;quot;funny&amp;quot; (irrational) angles.&lt;/p&gt;&#xA;&lt;p&gt;The actual atomic locations of the quasicrystal in our world will often slightly offset themselves to minimize energy (cf. &lt;a href=&quot;https://en.wikipedia.org/wiki/Phason&quot; rel=&quot;noreferrer&quot;&gt;phason&lt;/a&gt;) and so back-solving for the higher dimensional mathematical lattice from a given real-world quasicrystal atomic positions is a fun mathematical challenge.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; If one wants to propose that an observed structure&lt;sup&gt;1&lt;/sup&gt; could be a 2D quasicrystal these days, what would be considered as the necessary and sufficient conditions? Is &amp;quot;if it looks like a duck and quacks like a duck&amp;quot; sufficient (i.e. repeating motifs or patterns that are not periodic + strong, sharp peaks in a Fourier transform) or must one actually solve for the higher dimensional lattice to which it is associated first?&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt;In order to make this harder but more useful to me, let us stipulate that the Fourier transform has &lt;em&gt;sixfold symmetry&lt;/em&gt; and not ten- or twelve-fold. Thus we can't use the shortcut of &amp;quot;there aren't any 2D Bravais lattices with this rotational symmetry, therefore it's a quasicrystal Q.E.D.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;An example of a 2D quasicrystal with 6-fold symmetry would be &lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Moire_of_twisted_bilayer_graphene.svg&quot; rel=&quot;noreferrer&quot;&gt;twisted bilayer graphene&lt;/a&gt; at say several degrees but not 30° where it becomes 12-fold. (For more on the twelvefold 30° case &lt;a href=&quot;https://www.nature.com/articles/s41524-019-0258-0&quot; rel=&quot;noreferrer&quot;&gt;Dodecagonal bilayer graphene quasicrystal and its approximants&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;note:&lt;/strong&gt; There's a potentially quite helpful discussion in &lt;a href=&quot;https://www.mdpi.com/2073-4352/9/10/519/htm&quot; rel=&quot;noreferrer&quot;&gt;Twisted Graphene Bilayers and Quasicrystals: A Cut and Projection Approach&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;A simple but convenient illustration of how a 1D quasicrystal originates from a 2D regular lattice, from &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.054119&quot; rel=&quot;noreferrer&quot;&gt;Hyperuniformity of quasicrystals&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0eKSr.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0eKSrm.png&quot; alt=&quot;Projection of lattice points to create the 1D point set of interest. The red dots lie in the physical space X.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Projection of lattice points to create the 1D point set of interest. The red dots lie in the physical space X.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2021-11-01T04:12:57.097" LastActivityDate="2021-11-01T12:31:00.847" Title="Proposing a 2D quasicrystal; what are the necessary and sufficient conditions? (If it looks like a duck and quacks like a duck, or...?)" Tags="|crystallography|symmetry|terminology|quasicrystals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6994" PostTypeId="2" ParentId="4790" CreationDate="2021-11-01T05:31:55.043" Score="6" Body="&lt;p&gt;The theoretical formation energy is a little ambiguous here, depending on the way you calculate it. Is it a 0 K calculation (for example using DFT)? or have you already accounted for the entropic effects?&lt;/p&gt;&#xA;&lt;p&gt;If it is a 0 K calculation then it is indeed difficult to synthesize this particular compound. However, it is not impossible since you are still taking into account only the thermodynamics of the system rather than the kinetics. So you have to figure out some kinetic parameters to lock in your metastable configurations. This can be done by quick annealing or changing your precursors.&lt;/p&gt;&#xA;&lt;p&gt;However, if you are already accounting for entropy in your calculations. You can go check through lower temperatures if your formation energy becomes negative.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, formation energies are usually calculated with reference to a certain precursor. So do check if the formation energies are properly calculated or consider changing the precursors.&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2021-11-01T05:31:55.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6995" PostTypeId="2" ParentId="6993" CreationDate="2021-11-01T12:20:53.693" Score="6" Body="&lt;p&gt;Independent of facing a 3D sample, or one of 2D/2.5D, IUCr's definition applies to both of them when stating&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;«There are two definitions of the notion of quasicrystal.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;A quasicrystal is an aperiodic crystal that is not an incommensurate modulated structure, nor an aperiodic composite crystal. Often, quasicrystals have crystallographically 'forbidden' symmetries. These are rotations of order different from 1, 2, 3, 4 and 6. In three dimensions a lattice periodic structure may only have rotation symmetry of an order equal to one of these numbers. However, presence of such a forbidden symmetry is not required for a quasicrystal. A system with crystallographically allowed rotation symmetry that is locally similar to one with forbidden symmetries is also a quasicrystal.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The term quasicrystal stems from the property of quasiperiodicity observed for the first alloys found with forbidden symmetries. Therefore, the alternative definition is: a quasicrystal is an aperiodic crystal with diffraction peaks that may be indexed by n integral indices, where n is a finite number, larger than the dimension of the space (in general). This definition is similar to that of aperiodic crystal.»&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://dictionary.iucr.org/Quasicrystal&quot; rel=&quot;noreferrer&quot;&gt;IUCr's Online Dictionary of Crystallography&lt;/a&gt;, entry edited by 17 November 2017.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Perhaps the review by Steurer about the current state of affairs is helpful for your work, too (Fig. 6 bears similarity to the figure in your question):&lt;/p&gt;&#xA;&lt;p&gt;Steurer, W. &lt;em&gt;Quasicrystals: What do we know? What do we want to know? What can we know?&lt;/em&gt; in &lt;em&gt;Acta Cryst.&lt;/em&gt; &lt;strong&gt;2018&lt;/strong&gt;, &lt;em&gt;A74&lt;/em&gt;, 1-11; &lt;a href=&quot;https://doi.org/10.1107/S2053273317016540&quot; rel=&quot;noreferrer&quot;&gt;doi 10.1107/S2053273317016540&lt;/a&gt; (open access).&lt;/p&gt;&#xA;" OwnerUserId="1206" LastEditorUserId="1206" LastEditDate="2021-11-01T12:31:00.847" LastActivityDate="2021-11-01T12:31:00.847" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="6996" PostTypeId="2" ParentId="6982" CreationDate="2021-11-01T13:58:17.603" Score="8" Body="&lt;p&gt;Based on your recent comment to want to assemble a protein &lt;em&gt;from scratch&lt;/em&gt;, and assuming you want to stick to the naturally occurring &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-amino acids, I suggest to &lt;em&gt;type&lt;/em&gt; the amino acids by their three-letter code.  ChemDraw has a name2structure conversion routine understanding these codes.  If your institution doesn't have a campus license, the JavaScript &lt;a href=&quot;https://chemdrawdirect.perkinelmer.cloud/js/sample/index.html#&quot; rel=&quot;noreferrer&quot;&gt;sample page&lt;/a&gt; may be an alternative for you. (Get in touch with your supervisor if he/she is fine with this in advance.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YKunM.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YKunM.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Both SMILES and the sequence may be exported from the program for further processing.  Likely, a dictionary-based string substitution of the sequence string offers access to FASTA.&lt;/p&gt;&#xA;&lt;p&gt;By this, you stick to the amino acids known the program.  However, it is faster (and less prone to errors) than constructing the amino acids &lt;em&gt;atom by atom&lt;/em&gt;.  Other export formats (e.g., &lt;code&gt;.svg&lt;/code&gt; or &lt;code&gt;.mol&lt;/code&gt;) are at your disposition, too.  Possibly other programs offer a name2structure conversion of amino acid sequences, too; however, I don't know if the sample pages of e.g., Marvin or ChemDoodle are prepared for this operation.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-11-01T13:58:17.603" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="6997" PostTypeId="2" ParentId="6991" CreationDate="2021-11-01T14:04:04.560" Score="5" Body="&lt;p&gt;As Vina (and other docking software) uses Molecular Mechanics (force-fields) to optimize/score the ligand/protein, in order to use not predefined atoms, you need to generate, by yourself, the force-fields atom's parameters.&lt;/p&gt;&#xA;&lt;p&gt;You can do that as following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Determine the type of force-fields (equations) used by the Vina.&lt;/li&gt;&#xA;&lt;li&gt;Use a Quantum Mechanical based method (semiemprirical, density functional theory of &lt;em&gt;ab initio&lt;/em&gt;) to simulate the interaction of your atom with all other atoms present in the ligand and protein.&lt;/li&gt;&#xA;&lt;li&gt;Fit the force-field potential energy equations to calculations done with Quamtum Mechanics.&lt;/li&gt;&#xA;&lt;li&gt;Add the corresponding parameters to the Vina configuration files.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-11-01T14:04:04.560" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="6998" PostTypeId="2" ParentId="4670" CreationDate="2021-11-01T17:27:07.533" Score="3" Body="&lt;p&gt;I have not used CP2K, but based on the documentation, this should refer to the charge of the whole system. So if you don't have a reason to believe your system is charged, you should treat it as neutral.&lt;/p&gt;&#xA;&lt;p&gt;The reason for the &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/PRINT/MOMENTS.html#REFERENCE&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference keyword&lt;/a&gt; when computing the dipole/polarization (or any higher multipole of a molecule/solid) is that for charged systems, multipoles are dependent on your choice of coordinate origin. The dipole is still well-defined/calculable and you can compute derived properties from it like the polarizability, but you will need to report the reference point that you used for someone to be able to reproduce your specific value of the dipole. For consistency, the center of charge is often used as the origin in these cases.&lt;/p&gt;&#xA;&lt;p&gt;As a simple example of the origin dependence for charged systems, consider the dipole of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2+}$&lt;/span&gt;, which should have a bond length of roughly &lt;span class=&quot;math-container&quot;&gt;$\pu{2bohr}$&lt;/span&gt; and the charge split evenly among the two hydrogens. If we put the origin at one of the atoms:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$|\mu_\text{atom_origin}|=(\pu{0.5 e} \times \pu{0 bohr})+(\pu{0.5 e} \times \pu{2 bohr})=\pu{1 e*bohr}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, if we put the origin at the center of mass (COM) (which is also the center of charge):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$|\mu_\text{COM_origin}|=(\pu{0.5 e} \times \pu{-1 bohr})+(\pu{0.5 e} \times \pu{1 bohr})=\pu{0 e*bohr}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-01T17:32:40.023" LastActivityDate="2021-11-01T17:32:40.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="6999" PostTypeId="1" AcceptedAnswerId="8297" CreationDate="2021-11-01T22:29:49.733" Score="13" ViewCount="825" Body="&lt;p&gt;I am reading the book &lt;em&gt;Computer Simulation of Liquids&lt;/em&gt;&lt;sup&gt;[1]&lt;/sup&gt; where on multiple occasions it says MD is valid as long as the conditions simulated are away from phase transition. For example, at the beginning of section&#xA;2.3 (emphasis mine):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Since the ensembles are essentially artificial constructs, it would be reassuring to know that they produce average properties which are consistent with one another. In the thermodynamic limit (for an infinite system size) and &lt;strong&gt;as long as we avoid the neighbourhood of phase transitions&lt;/strong&gt;, this is believed to be true for the most commonly used statistic ensembles [Fisher 1964]&lt;sup&gt;[2]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the literature there are many MD studies of phase transitions. In fact there are some YouTube videos showing simulated MD system experiencing phase transition (for example &lt;a href=&quot;https://www.youtube.com/watch?v=6s0b_keOiOU&amp;amp;ab_channel=Jind%C5%99ichSoukup&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;My question is, what is the problem that makes simulating phase transition in MD non-trivial (if any)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Allen, M. P.; Tildesley, D. J. Computer Simulation of Liquids. &lt;em&gt;Oxford Scholarship Online&lt;/em&gt; &lt;strong&gt;2017&lt;/strong&gt;. &lt;a href=&quot;https://doi.org/10.1093/oso/9780198803195.001.0001&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1093/oso/9780198803195.001.0001&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Fisher, M. E. The free energy of a macroscopic system. &lt;em&gt;Arch. Ration. Mech. Anal.&lt;/em&gt; &lt;strong&gt;1964,&lt;/strong&gt; &lt;em&gt;17&lt;/em&gt; (5), 377–410. &lt;a href=&quot;https://doi.org/10.1007/BF00250473&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1007/BF00250473&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4496" LastEditorUserId="5" LastEditDate="2021-12-17T22:49:54.637" LastActivityDate="2021-12-19T15:25:32.843" Title="Phase transition in Molecular Dynamics simulations" Tags="|molecular-dynamics|computational-chemistry|phase-transitions|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7000" PostTypeId="1" CreationDate="2021-11-02T05:37:15.890" Score="7" ViewCount="75" Body="&lt;p&gt;I am studying Si nanowires with different cross sections. In my work, I plan to evaluate the thermoelectric performance variation between different configurations. To achieve this, my current approach is to evaluate the thermal conductivity of the nanowires using classical molecular dynamics simulations whereas the electrical properties are extracted through DFT calculations using SIESTA coupled with BoltzTraP2 (to solve the Boltzmann transport equation under the relaxation time approximation).&lt;/p&gt;&#xA;&lt;p&gt;The drawback of this methodology is that BoltzTraP2 gives the the electrical conductivity of the structure per unit relaxation time. However, since I am interested in determining the relative variation of these properties between individual structures, I can still compare the &lt;code&gt;Seebeck coefficient&lt;/code&gt; and &lt;code&gt;electrical conductivity/ relaxation time&lt;/code&gt; and determine which structure is more suited for thermoelectric applications.&lt;/p&gt;&#xA;&lt;p&gt;However, this whole comparison depends on whether the electron relaxation time remains constant between the individual configurations or not. Given that I use the same material (Si) and nanowires of similar diameters, would this assumption be reasonable?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="4232" LastEditorUserId="4232" LastEditDate="2021-11-03T00:03:55.297" LastActivityDate="2022-06-15T15:41:45.373" Title="Comments on the electronic relaxation time variation between nanowire configurations" Tags="|density-functional-theory|ab-initio-calculations|siesta|electronic-transport|boltztrap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7001" PostTypeId="1" AcceptedAnswerId="7117" CreationDate="2021-11-02T10:41:22.847" Score="8" ViewCount="629" Body="&lt;p&gt;I am working with Si nanowires using the SIESTA &lt;em&gt;ab initio&lt;/em&gt; code and the BoltzTraP2 Boltzmann transport equation solver. However, the output of the BoltzTraP2 code comes per relaxation time (&lt;code&gt;electrical conductivity/ relaxation time&lt;/code&gt;) since it works under the constant relaxation time approximation.&lt;/p&gt;&#xA;&lt;p&gt;Is there a method to use DFT to evaluate the relaxation time? Can this information be extracted from the band structure?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2021-11-18T05:59:27.633" LastActivityDate="2021-11-22T01:12:40.770" Title="How to evaluate the electron relaxation time of nanostructures computationally" Tags="|density-functional-theory|vasp|siesta|electronic-transport|boltztrap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7003" PostTypeId="1" AcceptedAnswerId="7005" CreationDate="2021-11-03T02:16:18.143" Score="13" ViewCount="4356" Body="&lt;p&gt;In MD simulations we often hear the term &lt;em&gt;force field&lt;/em&gt;.&#xA;What is it? &#xA;We know, for example that, &lt;a href=&quot;https://manual.gromacs.org/documentation/current/user-guide/force-fields.html&quot; rel=&quot;noreferrer&quot;&gt;Gromacs provides various types of forcefields&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="7" LastEditDate="2022-11-22T23:27:40.460" LastActivityDate="2023-03-09T12:01:11.557" Title="What does &quot;force field&quot; mean?" Tags="|molecular-dynamics|gromacs|forcefields|terminology|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7004" PostTypeId="2" ParentId="7003" CreationDate="2021-11-03T13:06:48.050" Score="8" Body="&lt;p&gt;Molecular dynamics is based in Molecular Mechanics. Molecular Mechanics do many approximations in order to treat the atomic/molecular system. A good definition can be seen &lt;a href=&quot;http://chem.winthrop.edu/molecular_modeling/molecular_mechanics.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Molecular Mechanics is a computational method that computes the&#xA;potential energy surface for a particular arrangement of atoms using&#xA;potential functions that are derived using classical physics. These&#xA;equations are known as a force-field.&lt;br /&gt;&#xA;Molecular Mechanics is based on&#xA;several assumptions:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;- It treats the electrons around a nucleus and a the nucleus itself as a perfect sphere.&#xA;- The bonds between molecules are treated as springs.&#xA;- Potential functions rely on experimental parameters such as force constants and equilibrium values.&#xA;- The potential energy function is the sum of individual functions for bond stretching, angle bending, torsional energies, and non-bonding interactions.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;About your second question: &lt;em&gt;how to choose which force field is appropriate for the use of our MD processes?&lt;/em&gt; the recommendation is to read the documentation (manual, scientific papers, etc.) about each available force field and look for its applications. As the fore filed used several experimental parameters, some of them are designed/optimized to very specific materials.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, you will find the so called universal force fields that have parameters for (almost) all the period table, but their precision is no as good as the specific force fields.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2023-03-09T12:01:11.557" LastActivityDate="2023-03-09T12:01:11.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7005" PostTypeId="2" ParentId="7003" CreationDate="2021-11-03T13:44:23.393" Score="20" Body="&lt;h2&gt;What is a force field?&lt;/h2&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Force_field_(chemistry)&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia entry on this&lt;/a&gt; is a good resource, but I'll give my own description below.&lt;/p&gt;&#xA;&lt;p&gt;In the context of molecular dynamics (MD), a &lt;strong&gt;force field&lt;/strong&gt; is one way of describing the interactions between atoms. In classical MD, the motion of atoms is determined by the instantaneous forces acting on the atoms (i.e., we need forces in order to calculate accelerations based Newton's famous &lt;span class=&quot;math-container&quot;&gt;$F=ma$&lt;/span&gt;). Force fields provide a way to calculate those forces.&lt;/p&gt;&#xA;&lt;p&gt;Force fields are usually contrasted with getting forces from quantum mechanics, e.g., via the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hellmann%E2%80%93Feynman_theorem&quot; rel=&quot;noreferrer&quot;&gt;Hellmann-Feynman theorem&lt;/a&gt;. In general, force fields should be thought of as an approximation to quantum mechanics. For large systems, such as proteins, quantum calculations are too computationally expensive to enable reasonable MD simulations.&lt;/p&gt;&#xA;&lt;p&gt;Atomistic force fields apply when you're performing simulations using &lt;strong&gt;molecular mechanics&lt;/strong&gt;, which expresses the total force as the sum of physically-motivated force terms. [Aside (pet peeve of mine): many people mix up the terms &amp;quot;classical MD&amp;quot; and &amp;quot;molecular mechanics&amp;quot; -- if you use forces from quantum calculations for Newtonian dynamics, that is still classical MD (not quantum MD), though it is not molecular mechanics.]&lt;/p&gt;&#xA;&lt;p&gt;Note that a lot of what you'll see described as force fields really applies to the subset of force fields that are widely used in biomolecular simulation. That is, you'll see the forces expressed as the sum of the following physically-motivated terms, divided into bonded and non-bonded terms, typically something like this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Bonded terms&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;bond between 2 atoms&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;angle between 3 atoms&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;dihedral angle formed by 4 atoms&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Nonbonded terms&lt;/strong&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;electrostatic interactions&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;van der Walls/dispersion terms&lt;/em&gt; (typically Lennard-Jones interactions)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This division of terms is useful as a good example for further discussion, but it's worth keeping in mind that there's no law a that force field must be exclusively expressed in these terms. Molecular mechanics force fields could have 5-atom bonded terms or 3-atom nonbonded terms or more detailed treatment of electronic interactions -- but the choices above represent most common force fields.&lt;/p&gt;&#xA;&lt;p&gt;In general, each of those terms has a specific functional form, with parameters that depend on the atom types in the system. For example, the potential energy describing a bond is frequently of the functional form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_\text{bond}(r) = k_{AB}(r - r^0_{AB})^2&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_{AB}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r^0_{AB}$&lt;/span&gt; are parameters that depend on the atom types (and the force itself is given by the gradient &lt;span class=&quot;math-container&quot;&gt;$F = -\nabla V$&lt;/span&gt; -- we frequently discuss force terms based on the functional form of the potential energy contribution instead of the functional form of the force itself).&lt;/p&gt;&#xA;&lt;p&gt;Note that the &amp;quot;atom type&amp;quot; here is usually more specific than just the &amp;quot;element type.&amp;quot; For example, it shouldn't be surprising that the angle between three carbons in an sp2 hybridized carbon (e.g., benzene) has different parameters than the angle in sp3 hybridized carbon (e.g., cyclohexane).&lt;/p&gt;&#xA;&lt;p&gt;Designing what &amp;quot;atom types&amp;quot; a force field recognizes is part of the challenge of making a force field &lt;strong&gt;transferable&lt;/strong&gt; to a wide range of molecules. Overly simple atom types (e.g., just the element) would not accurately account for different chemical environments; overly complex (e.g., having the each atom in each different molecule have a different type) would make it impossible to transfer the model to molecules that haven't been specifically parametrized.&lt;/p&gt;&#xA;&lt;p&gt;Most biomolecular force fields have limitations in the kind of chemistry they can represent (e.g., they can't capture bond making/breaking if the bonded term is described by a harmonic oscillator as above.) Specialized force fields, such as ReaxFF, are designed to get around those limitations.&lt;/p&gt;&#xA;&lt;h2&gt;How to choose which force field to use&lt;/h2&gt;&#xA;&lt;p&gt;I'd say there are three answers to this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Take the recommendation of people who know better.&lt;/strong&gt; For example, the developers of the Amber force field family &lt;a href=&quot;https://ambermd.org/AmberModels.php&quot; rel=&quot;noreferrer&quot;&gt;provide a page with their current recommendations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Keep up with the literature, especially for systems similar to yours.&lt;/strong&gt; People frequently publish papers comparing different force fields for a given system. Also dig into details of which force fields were used if looking at papers that compare existing computational results (authors &lt;em&gt;should&lt;/em&gt; always mention FF when comparing computational results, but don't always). This depends on your specific system -- there are different specialized force fields for lipids, nucleic acids, etc.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Use something recent and don't stress too much.&lt;/strong&gt; If you use a recently-published force field (say, last 5 years) from a group with a good track record of contributing to force field development, your results will probably be a meaningful contribution to science. Barring a major issue specific to your system and that force field, I doubt a paper would be rejected on the basis of a slightly old force field.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-11-04T19:13:01.693" LastActivityDate="2021-11-04T19:13:01.693" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7006" PostTypeId="2" ParentId="7003" CreationDate="2021-11-03T13:47:48.723" Score="12" Body="&lt;p&gt;The term's origin goes back to &lt;a href=&quot;https://en.wikipedia.org/wiki/Vector_field&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;&lt;strong&gt;vector field&lt;/strong&gt;&lt;/em&gt;&lt;/a&gt; which is a function that returns a vector for any given point in space (as in the image below on the left). We can almost &amp;quot;see&amp;quot; that such fields exist, by putting iron filings and a magnet on a sheet of paper (the &lt;em&gt;&lt;strong&gt;magnetic field&lt;/strong&gt;&lt;/em&gt; causes the iron filings to move accordingly):&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/oGBGU.png&quot; Width=&quot;151&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yjDu1.png&quot; Width=&quot;225&quot;&gt;&lt;/p&gt;&#xA;&lt;p&gt;In classical molecular dynamics, we want to calculate how particles (usually forming molecules) move, based on Newton's second law (F=ma). Therefore if you have the initial positions (and masses) of all the particles of interest, and the forces between them, you can use Newton's second law to see where they will go. As the particles in your simulation move), the forces will also change. If two particles in your simulation get further apart from each other, the forces between them may get weaker (for example). Therefore there's different force values depending on the relative positions of the particles, which is why we call it a &lt;em&gt;&lt;strong&gt;force field.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-03T15:27:23.990" LastActivityDate="2021-11-03T15:27:23.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7007" PostTypeId="2" ParentId="6982" CreationDate="2021-11-03T16:54:01.160" Score="8" Body="&lt;p&gt;&lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;nofollow noreferrer&quot;&gt;openbabel&lt;/a&gt; could also be used to tackle this problem.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Convert initial structure to &lt;a href=&quot;https://en.wikipedia.org/wiki/Protein_Data_Bank_(file_format)&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDB format&lt;/a&gt;. I suspect this can be done directly from whatever format you are using for the skeletal structure, but I would need to know your initial format to test this. However, if that doesn't seem to work, you can go from your SMILES to PDB with this snippet:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel -:'[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O' -O output.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Convert PDB to &lt;a href=&quot;https://en.wikipedia.org/wiki/FASTA_format&quot; rel=&quot;nofollow noreferrer&quot;&gt;FASTA&lt;/a&gt;. The command to run is very similar to the previous one:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel output.pdb -O new.fasta&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The FASTA file will have a header line, followed by the single letter amino acid sequence.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;output.pdb 4 bp; generated with OpenBabel 3.0.0&#xA;KKAW&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;RDKit should be able to perform a similar set of steps:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;import rdkit.Chem.rdmolfiles  as rdmol&#xA;&#xA;m = Chem.MolFromSmiles('[H]N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](C)C(=O)N[C@@H](CC1=CNC2=C1C=CC=C2)C(O)=O'&#xA;pdb= rdmol.MolToPDBBlock(m)&#xA;m2= rdmol.MolFromPDBBlock(pdb)&#xA;fa= rdmol.MolToFASTA(m2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The intermediate conversion to PDB should add in the monomer information that is left out when converting directly from SMILES.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-04T01:27:43.743" LastActivityDate="2021-11-04T01:27:43.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7008" PostTypeId="1" AcceptedAnswerId="7013" CreationDate="2021-11-03T22:50:23.817" Score="11" ViewCount="2203" Body="&lt;p&gt;I'm interested in doing some calculations to model the interstitial addition of nitrogen into a structure and I'm thinking of using Nudged Elastic Band to do it.&lt;/p&gt;&#xA;&lt;p&gt;From what I have read you start with two scenarios: an initial position, and the end result you hope to achieve, then the algorithm finds you a low energy path between the two.&lt;/p&gt;&#xA;&lt;p&gt;From this I expect I will be able to calculate the minimum energy required by the nitrogen to infiltrate the structure.&lt;/p&gt;&#xA;&lt;p&gt;Is this possible with nudged elastic band? What's the fundamental idea driving the method? Are there any good books or papers on the subject? What software would you recommend for this?&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="7" LastEditDate="2021-11-04T01:09:45.527" LastActivityDate="2021-11-05T19:43:25.117" Title="What's the Theory Behind Nudged Elastic Band?" Tags="|software|optimization|methodology|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7009" PostTypeId="1" CreationDate="2021-11-04T05:05:15.813" Score="7" ViewCount="341" Body="&lt;p&gt;I am doing simple scf calculation to find similarities in the output of &lt;code&gt;VASP&lt;/code&gt; and &lt;code&gt;QE&lt;/code&gt;.&#xA;Recently, I encounter an interesting case. I took face-centred orthorhombic cell of Aluminium. Here is my POSCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Al&#xA;   4.05000000000000&#xA;     1.0300000000000000    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    0.9700000000000000    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    1.0000000000000000&#xA;   Al&#xA;     4&#xA;Direct&#xA;  0.0000000000000000  0.0000000000000000  0.0000000000000000&#xA;  0.5000000000000000  0.5000000000000000  0.0000000000000000&#xA;  0.0000000000000000  0.5000000000000000  0.5000000000000000&#xA;  0.5000000000000000  0.0000000000000000  0.5000000000000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here vasp code detects symmetry of orthorhomic cell with following symmetry operation (in &lt;code&gt;OUTCAR&lt;/code&gt;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA; Subroutine INISYM returns: Found  8 space group operations&#xA; (whereof  8 operations are pure point group operations),&#xA; and found     4 'primitive' translations&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now using &lt;code&gt;QE&lt;/code&gt; with following input&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;control&#xA;    calculation='relax'&#xA;    restart_mode='from_scratch',&#xA;    pseudo_dir ='.'&#xA;    outdir='./tmp/',&#xA;    prefix='al'&#xA;    tprnfor = .true.&#xA;    tstress = .true.&#xA;    disk_io='none'&#xA; /&#xA; &amp;amp;system&#xA;    ibrav=  0,A =4.05, nat=  4, ntyp= 1, ecutwfc =60,&#xA;    occupations='smearing', smearing='mv', degauss=0.02&#xA;&#xA; /&#xA; &amp;amp;electrons&#xA;    diagonalization='cg'&#xA;    mixing_beta = 0.7&#xA; /&#xA;&amp;amp;ions&#xA;ion_dynamics='bfgs'&#xA;/&#xA;CELL_PARAMETERS alat&#xA;1.03 0 0&#xA;0 0.97 0&#xA;0 0 1&#xA;&#xA;ATOMIC_SPECIES&#xA; Al  26.98 Al.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS alat&#xA; Al 0.00 0.00 0.00&#xA; Al 0.50 0.50 0.00&#xA; Al 0.50 0.00 0.50&#xA; Al 0.00 0.50 0.50&#xA;K_POINTS automatic&#xA;15 15 15  0 0 0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and output have shown following symmetry operation&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      2 Sym. Ops. (no inversion) found&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have also test with &lt;code&gt;ibrav=8&lt;/code&gt;, results are still same&lt;/p&gt;&#xA;&lt;p&gt;Can somebody explain why &lt;code&gt;QE&lt;/code&gt; is resulting only 2 point group operation in reality, it must have 8.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-11-06T05:06:26.973" Title="Case study : Symmetry operation between VASP and Quantum espresso" Tags="|vasp|quantum-espresso|symmetry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7010" PostTypeId="1" AcceptedAnswerId="7011" CreationDate="2021-11-04T15:24:56.333" Score="6" ViewCount="667" Body="&lt;p&gt;I've been told that I should use the potentials from the Standard Solid-State Pseudopotential &lt;a href=&quot;https://www.materialscloud.org/discover/sssp/table/efficiency&quot; rel=&quot;nofollow noreferrer&quot;&gt;(SSSP)&lt;/a&gt; library in my simulations. I am interested in &lt;span class=&quot;math-container&quot;&gt;$\ce{Pt}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{O}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt;. Oxygen is Projector-Augmented Wave &lt;a href=&quot;https://en.wikipedia.org/wiki/Projector_augmented_wave_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;(PAW)&lt;/a&gt; while platinum and hydrogen are Ultra Soft Pseudopotentials &lt;a href=&quot;https://www.physics.rutgers.edu/%7Edhv/uspp/&quot; rel=&quot;nofollow noreferrer&quot;&gt;(USPP)&lt;/a&gt; (I am surprised that quantum espresso is able to run multiple PP descriptions at the same time).&lt;/p&gt;&#xA;&lt;p&gt;The advised energy cutoffs for platinum, hydrogen, and oxygen are &lt;span class=&quot;math-container&quot;&gt;$35$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$60$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\pu{50 Ry}$&lt;/span&gt; respectively. My system is made of &lt;span class=&quot;math-container&quot;&gt;$85\%$&lt;/span&gt; platinum and a few oxygen/hydrogen atoms, do I still need to use &lt;code&gt;ecutwfc = 60&lt;/code&gt;? It seems like a waste of time in this case?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="7" LastEditDate="2021-11-04T17:12:52.273" LastActivityDate="2021-11-04T17:12:52.273" Title="Quantum Espresso energy cutoff for different pseudopotential" Tags="|quantum-espresso|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7011" PostTypeId="2" ParentId="7010" CreationDate="2021-11-04T15:53:17.780" Score="5" Body="&lt;p&gt;You can do a convergence test and see if ecutwfc=60 is really needed.  Depending on your application, you also might find the treatment of hydrogen may result in energies shifting but no relative difference changes for example (All OH groups treated equally bad).  This is a form of error cancellation, so be careful about it, but if you never change the state of the hydrogen and it doesn't affect your answer, I do not see why you need to go all the way to ecutwfc=60.&lt;/p&gt;&#xA;&lt;p&gt;I would predict you are doing some sort of Pt surface with H2, OH, H2O adsorbates etc.  In this case, the H may play a significant role and you will likely need ecutwfc=60 or even higher (showing the importance of convergence tests!).  You could also consider trying to find a different pseudopotential with a lower cutoff, since you can mix types under some conditions as you have discovered.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-11-04T15:53:17.780" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7012" PostTypeId="2" ParentId="6954" CreationDate="2021-11-05T18:55:46.687" Score="5" Body="&lt;p&gt;One way that matrix information can be passed into a learning algorithm is by diagonalizing it and instead passing in the sorted eigenvalues. An example of this in a fairly recent paper[1] is the use of Coulomb Matrix Eigenvalues (CMEs) in a number of different regression models as a descriptor to distinguish isomers of a molecule (there are Mathematica notebooks in the SI showing how all these calculations were done). The original paper defining Coulomb Matrices[2] similarly used their eigenvalues to make an ML model for atomization energies.&lt;/p&gt;&#xA;&lt;p&gt;In principle, there is nothing stopping you from having a matrix as a descriptor, see for example &lt;a href=&quot;https://towardsdatascience.com/how-to-do-deep-learning-on-graphs-with-graph-convolutional-networks-7d2250723780&quot; rel=&quot;noreferrer&quot;&gt;this tutorial&lt;/a&gt; on creating a graph convolutional network using a matrix descriptor and an adjacency matrix. As shown in this &lt;a href=&quot;https://stackoverflow.com/questions/36900841/scikit-learn-linear-regression-on-square-matrix-seems-incorrect&quot;&gt;SO question&lt;/a&gt;, programs like scikit learn can handle matrix features. However, as was the case with the Coulomb matrix, we can often simplify a matrix feature  into several scalar features, reducing the number of features we need to deal with.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;J. Schrier, Can One Hear the Shape of a Molecule (from its Coulomb Matrix Eigenvalues)? J. Chem. Inf. Model. 2020, 60, 8, 3804–3811 &lt;a href=&quot;https://doi.org/10.1021/acs.jcim.0c00631&quot; rel=&quot;noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller, and O. Anatole von Lilienfeld Phys. Rev. Lett. 108, 058301 &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.108.058301&quot; rel=&quot;noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-05T18:55:46.687" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7013" PostTypeId="2" ParentId="7008" CreationDate="2021-11-05T19:43:25.117" Score="8" Body="&lt;p&gt;The &lt;a href=&quot;https://theory.cm.utexas.edu/henkelman/research/saddle/neb/&quot; rel=&quot;noreferrer&quot;&gt;Nudged Elastic Band&lt;/a&gt; (NEB) method is a way to find the Minimum Energy Path (MEP) between a set of reactants and products. Some variants, like the Climbing Image (CI-NEB),  also specifically find the transition state along this path. So if your goal is to determine the reaction pathway, and possibly activation energy, for nitrogen infiltration into a solid, this method could be able to help with that.&lt;/p&gt;&#xA;&lt;p&gt;The idea behind the method is to consider a set of &amp;quot;images&amp;quot; or interpolated structures between the reactants and products. Rather than treating these as individual structure, we instead think of creating a large band between reactants and products, where adjacent images are linked using harmonic spring potential. We then optimize the structure of the band, considering just these spring forces along the band and the actual structural forces along the directions perpendicular to the band. In equation form, the force on each image &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is given as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{F}_i=\mathbf{F}^S_{i}|_{\parallel}-\mathbf{\nabla}E(\mathbf{R}_i)|_{\perp}\tag{1}\label{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{F}^S_{i}|_{\parallel}=k(|\mathbf{R}_{i+1}-\mathbf{R}_i|-|\mathbf{R}_{i}-\mathbf{R}_{i-1}|)\boldsymbol{\tau}_i \tag{2}\label{2}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{\nabla}E(\mathbf{R}_i)|_{\perp}= \mathbf{\nabla}E(\mathbf{R}_i)-\mathbf{\nabla}E(\mathbf{R}_{i})|_{\parallel}=\mathbf{\nabla}E(\mathbf{R}_i)-\mathbf{\nabla}E(\mathbf{R}_i)\cdot\boldsymbol{\tau}_i\boldsymbol{\tau}_i \tag{3}\label{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; denotes the spring force and &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is the tangent along the band (the definition requires some extra details to avoid kinks in the band, see the papers in the linked Henkleman group page above). The spring forces keep each of the images apart while the perpendicular forces move the band closer to the MEP.&lt;/p&gt;&#xA;&lt;p&gt;The CI variant doesn't take too much additional effort: after a few regular iterations, find the highest energy image, and replace its forces with&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$F_{i,\text{max}}=-\mathbf{\nabla}E(\mathbf{R}_{i,\text{max}})|_{\perp}+\mathbf{\nabla}E(\mathbf{R}_{i,\text{max}})|_{\parallel}=-\mathbf{\nabla}E(\mathbf{R}_{i,\text{max}})+2\mathbf{\nabla}E(\mathbf{R}_{i,\text{max}})|_{\parallel}\tag{4}\label{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So we remove the spring force and invert the structural forces along the band, making this image climb up in energy along the band until it reaches a saddle point (maximum along the band, minimum for all other coordinates).&lt;/p&gt;&#xA;&lt;p&gt;If you are comfortable doing VASP calculations, &lt;a href=&quot;https://www.vasp.at/wiki/index.php/TS_search_using_the_NEB_Method&quot; rel=&quot;noreferrer&quot;&gt;NEB is implemented&lt;/a&gt; in this program and it would probably be well suited for this sort of computation on a solid. Alternatively, if you have a preferred electronic structure program, you can interface it with ASE, which can &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/neb.html&quot; rel=&quot;noreferrer&quot;&gt;externally run NEB&lt;/a&gt; by using the electronic structure program as a calculator.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-05T19:43:25.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7014" PostTypeId="2" ParentId="7009" CreationDate="2021-11-06T05:06:26.973" Score="4" Body="&lt;p&gt;VASP input file is based on relative coordinates(&lt;code&gt;direct&lt;/code&gt;) of the simulation box whereas in &lt;code&gt;QE&lt;/code&gt; &lt;code&gt;alat&lt;/code&gt; doesn't define relative coordinate, It only scale by lattice parameter. In &lt;code&gt;QE&lt;/code&gt; relative coordinate is defined by atomic position tag &lt;code&gt;crystal&lt;/code&gt;.&#xA;Correct input file for 8 different symmetry operations will be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;control&#xA;    calculation='relax'&#xA;    restart_mode='from_scratch',&#xA;    pseudo_dir ='.'&#xA;    outdir='./tmp/',&#xA;    prefix='al'&#xA;    tprnfor = .true.&#xA;    tstress = .true.&#xA;    disk_io='none'&#xA; /&#xA; &amp;amp;system&#xA;    ibrav=  0,A =4.05, nat=  4, ntyp= 1, ecutwfc =60,&#xA;    occupations='smearing', smearing='mv', degauss=0.02&#xA;&#xA; /&#xA; &amp;amp;electrons&#xA;    diagonalization='cg'&#xA;    mixing_beta = 0.7&#xA; /&#xA;&amp;amp;ions&#xA;ion_dynamics='bfgs'&#xA;/&#xA;CELL_PARAMETERS alat&#xA;1.03 0 0&#xA;0 0.97 0&#xA;0 0 1&#xA;&#xA;ATOMIC_SPECIES&#xA; Al  26.98 Al.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA; Al 0.00 0.00 0.00&#xA; Al 0.50 0.50 0.00&#xA; Al 0.50 0.00 0.50&#xA; Al 0.00 0.50 0.50&#xA;K_POINTS automatic&#xA;15 15 15  0 0 0&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-11-06T05:06:26.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7015" PostTypeId="1" CreationDate="2021-11-07T07:43:06.163" Score="7" ViewCount="210" Body="&lt;p&gt;I calculated the bandgap for one system in the unit cell and in the supercell of 2x2x1 and 3x1x1. Although 3x1x1 gives the same bandgap as I got from the unit cell (1.79 eV) but 2x2x1 is giving 1.75 eV. I kept all input file settings same in all the supercells as in-unit cell including K- POINTS. I observed this bandgap by plotting the dos. I think the bandgap should remain the same in the supercell.&#xA;Any suggestion will be very helpful.&lt;/p&gt;&#xA;" OwnerUserId="4354" LastActivityDate="2021-11-10T20:34:40.030" Title="Different band gap observed in unitcell and in the supercell" Tags="|density-functional-theory|vasp|supercell|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7016" PostTypeId="1" CreationDate="2021-11-07T13:19:50.813" Score="8" ViewCount="79" Body="&lt;p&gt;The motivation for this question is similar in nature to the series of questions on different methods :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1568/5&quot;&gt;What are the types of SCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/784&quot;&gt;What are the types of MCSCF?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;What are the types of Quantum Monte Carlo?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1513/5&quot;&gt;What are the types of DFT?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1781/784&quot;&gt;What are the types of DMRG?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The answers to these questions were really insightful, so I am looking for an answer that briefly describes the different variants of Perturbation Theory (PT), and the context in which they are applied on different electronic structure methods.&lt;/p&gt;&#xA;&lt;p&gt;Rayleigh-Schrodinger perturbation theory (RSPT) is the most common form that is used, but there's also the Lennard-Jones-Brillouin-Wigner perturbation theory (BWPT). In fact, RSPT could be derived from BWPT. Again, depending the type of partitioning of the Hamiltonian, there are two variants: Moller-Plesset and Epstein-Nesbet. Then there are also many-body and diagrammatic PT. These methods have also been applied with both multi and single reference schemes as well as multi-configurational methods.&lt;/p&gt;&#xA;&lt;p&gt;Here are a few examples of such methods:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Second order corrections to ground state energies(the standard MPn methods)&lt;/li&gt;&#xA;&lt;li&gt;Perturbative corrections to CI  (see for example &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0009261494000700&quot; rel=&quot;nofollow noreferrer&quot;&gt;CIS(D) by Martin Head-Gordon et al&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;CASPT2 (multireference second-order PT)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="7" LastEditDate="2021-11-10T18:13:12.470" LastActivityDate="2021-11-10T18:13:12.470" Title="What are the types of PT applied to electronic structure methods?" Tags="|reference-request|quantum-chemistry|many-body-perturbation-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7017" PostTypeId="2" ParentId="2225" CreationDate="2021-11-08T00:34:00.040" Score="7" Body="&lt;p&gt;To the best of my knowledge, there is no universal or even near-universal heuristic for what the time constant should be. The only &lt;em&gt;rule of thumb&lt;/em&gt; I have encountered is that the time constant should be around 10x-1000x larger than the timestep of the simulation. Beyond that point, I would treat the damping constant as a hyperparameter, do a sensitivity analysis, and pick a value where changing the damping by e.g. 10x in either direction does not affect the results. In other words, if the simulation outcome is robust to the chosen value of damping, there is little for a picky reviewer to pick. In my own simulations, thermostatting between 10fs-1ps for simulation runs with a 1-fs timestep has never made a difference, unless there was energy getting added to the simulation mid-way through (e.g. from an applied electric field). But for those cases, NVE was more appropriate in the first place.&lt;/p&gt;&#xA;&lt;p&gt;For the specific system in question, a gas molecule and a surface, heat exchange between the molecule and the surface physically happens via some density of vibrational states. For example, when the molecule sits on a surface, it could transfer energy back and forth with the surface’s phonon modes. As the surface has a lot of atoms, its density of vibrational states is large, and could very well be treated as continuous. In the simplest terms, this is how equipartitioning physically happens. If the phonon-phonon couplings or vibrational coherence times (dephrasing rates) for the molecule and the surface are known, those could offer physics-based starting points for the optimization of the damping hyperparameter. The molecular vibrations are typically more singular, but the molecule also has (typically low-energy and low-frequency, i.e. slow) rotations and translations.&lt;/p&gt;&#xA;&lt;p&gt;The interplay between these slow degrees of freedom and the effective potential that keeps the molecule on the surface determines binding and unbinding. This is the effective potential in which the molecule moves as a whole. The correspondence of the simulation velocity and the accuracy with which the simulation describes the molecule’s positions (and the “hopping” in the question) depends on accuracy of thermalization on this relatively slow timescale. With translations and rotations being on the timescale of a terahertz (≈1 ps), and phonon thermalization typically faster, this should be the slowest timescale in the system.&lt;/p&gt;&#xA;&lt;p&gt;Now, physically speaking, how would a hop (as described in the question) happen? The molecule could move far enough to unbind or switch position. Practically, this should not happen within one timestep of the simulation. Assuming that the timestep of the simulation is small enough that translation takes a large number of time steps, then the continued presence of extra energy in the translational degree of freedom is either physical, or will be taken out by the thermostat. Ultimately, judging whether a binding or unbinding event is physical or unphysical is going to be up to the human behind the simulation.&lt;/p&gt;&#xA;&lt;p&gt;A second practical piece of advice I could offer is to verify whether exempting the center-of-mass motions of the molecule and/or the surface makes any difference. Sometimes that is sufficient to prevent unphysical accumulation of energy in the translational degrees of freedom, and I would consider it for simulations where one part of the system is expected to meaningfully translate past another, such as the molecule translating past the surface in question. E.g. for LAMMPS+Nosé:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix molVibr molecule temp/com ${molTemp}  ${molTemp}  ${moleculeDampingFactor}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="7" LastEditDate="2021-11-08T01:28:23.573" LastActivityDate="2021-11-08T01:28:23.573" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7018" PostTypeId="2" ParentId="7016" CreationDate="2021-11-08T01:02:07.950" Score="4" Body="&lt;h2&gt;Moller-Plesset (MPn)&lt;/h2&gt;&#xA;&lt;p&gt;Moller-Plesset perturbation theory combines the Rayleigh-Schrodinger style of perturbation expansion with a particular partitioning of the molecular Hamiltonian in order to compute the correlation energy (and/or perturbed wavefunctions).&lt;/p&gt;&#xA;&lt;p&gt;We express the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; as an unperturbed part &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; and a perturbation &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;. For the unperturbed part, we choose a sum of Fock operators for each electron:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H_0=\sum_i^Nf(i) = \sum_i^N h(i)+v^\text{HF}(i)$$&lt;/span&gt;&#xA;This is a convenient choice because the HF wavefunction is an exact eigenfunction of this Hamiltonian, &lt;span class=&quot;math-container&quot;&gt;$E_0^{(0)}=\sum_i^N \epsilon_i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This would correspond to MP0, which is never used on its own because it's a very poor prediction for the energy that can be easily (at least conceptually) improved on. To do this, we express the wavefunction and energy as perturbative expansions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=H_0+\lambda V$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Psi_0=\Psi_0^{(0)}+\lambda \Psi_0^{(1)}+\lambda^2\Psi_0^{(2)}+...$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_0=E_0^{(0)}+\lambda E_0^{(1)}+\lambda^2E_0^{(2)}+...$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;By plugging these expressions into the Schrodinger equation and separating by order (i.e how many factors of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; are in each term), we get a series of energy/wavefunction contributions that ideally converge to the true values for an infinite order expansion (practically, we are hoping for very good convergence with just a few terms included).&lt;/p&gt;&#xA;&lt;p&gt;This leads to a general form for the correction terms to the energy: &lt;span class=&quot;math-container&quot;&gt;$$E_0^{(n)}=\langle\Psi_0^{(0)}|V|\Psi_0^{(n-1)}\rangle$$&lt;/span&gt;&#xA;The general form for the wavefunction corrections is more involved, but the form for a given order is not conceptually difficult to obtain.&lt;/p&gt;&#xA;&lt;p&gt;Now we introduce the particular perturbation for MP &lt;span class=&quot;math-container&quot;&gt;$$V=\sum_{i&amp;lt;j}r_{ij}^{-1}- \sum_iv^\text{HF}(i)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;With &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; we can explicitly compute a few orders of energy corrections and we call the resulting energy summing up to that order the MPn energy. MP1 is actually just the Hartree-Fock energy, so it takes until MP2 before we get a nontrivial result for our effort.&lt;/p&gt;&#xA;&lt;p&gt;MPn methods are potentially useful whenever you need to include correlation effects. On the other hand, MPn calculations scale as &lt;span class=&quot;math-container&quot;&gt;$O(N^{3+n})$&lt;/span&gt;, making higher order expansions impractical for most systems (and often worse accuracy than comparably scaling coupled cluster methods). MP2 sees the most widespread use due to having a good balance of cost and accuracy. While DFT has started to take some of the work formerly reserved, MP2 still sees use both as an individual method and as a correction to DFT in &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6427/7&quot;&gt;double hybrid functionals&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-08T01:02:07.950" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7019" PostTypeId="2" ParentId="6908" CreationDate="2021-11-08T01:36:39.330" Score="1" Body="&lt;p&gt;Here is an example from &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Freezing&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspwiki&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2021-11-08T01:36:39.330" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7020" PostTypeId="1" CreationDate="2021-11-07T22:53:59.010" Score="5" ViewCount="107" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LwJRE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LwJRE.png&quot; alt=&quot;Neuronal Membrane as Cable Theory, from Wikimedia&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wikipedia.org/wiki/Cable_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cable theory&lt;/a&gt; is a good simulation for the resting potential. It imagines patches of cell membrane lipid bilayer as capacitors and transmembrane ion channels as resistors.&lt;/p&gt;&#xA;&lt;p&gt;But it seems this model is not enough to simulate the action potential cycle (Depolarisation, Repolarisation etc and associated Na+ and K+ channel states), and the propagation cycle of action potential. The array will seemingly produce a bland gradient of voltage along the circuit (as seen in 'length constant' graph)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What would be a circuit diagram for a more working model of action potential cycle and its propagation?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So far I have proceeded:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Zener diodes and/or voltage dependent resistors may help as simulate Na+ or K+ channels.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I may need to put some batteries at a certain interval along the circuit (serves as source of action potential)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Where I'm stuck:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I simulate the &amp;quot;closing&amp;quot; or plugging off (inactivation) of the sodium channel?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerDisplayName="user1101" LastEditorUserId="5" LastEditDate="2021-11-18T00:27:57.187" LastActivityDate="2021-11-18T00:27:57.187" Title="Simulating a circuit diagram for action potential" Tags="|biomaterials|structural-biology|membranes|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-24T14:40:03.587" ContentLicense="CC BY-SA 4.0" />
  <row Id="7021" PostTypeId="1" CreationDate="2021-11-08T09:01:12.637" Score="3" ViewCount="116" Body="&lt;p&gt;I am trying to calculate the dos of one bulk system. My dos calculation job stops in between without showing any error. Here I am attaching the link of my input dos calculation files. CONTCAR file is also empty.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://drive.google.com/drive/folders/1NLr_2ZCLqhGk3raoDykEfsikK7k1Ub6p?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://drive.google.com/drive/folders/1NLr_2ZCLqhGk3raoDykEfsikK7k1Ub6p?usp=sharing&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4354" LastActivityDate="2021-12-15T13:53:24.643" Title="Job stops in between without showing any error" Tags="|density-functional-theory|vasp|density-of-states|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7022" PostTypeId="1" AcceptedAnswerId="7070" CreationDate="2021-11-08T18:15:58.833" Score="11" ViewCount="203" Body="&lt;p&gt;I have a &lt;code&gt;xyz&lt;/code&gt; file of a system that doesn't contain any cell information, but which has all its coordinates wrapped inside the same (triclinic) cell.&lt;/p&gt;&#xA;&lt;p&gt;I would like to have a rough guess of the cell that would fit the positions of the atoms.&#xA;Do you know of any software (ranging from a python library to the GUI interface of a visualisation software) that can suggest such a guess?&lt;/p&gt;&#xA;&lt;p&gt;This problem occurs rather frequently when I recover some coordinate files from the Supporting Information/reply to a data request of an older paper of another group I'm interested in.&#xA;I've attached an example coordinate file and inserted snapshots here (with an orthogonal cell displayed that doesn't fit the structure at all):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ULCb3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ULCb3.png&quot; alt=&quot;Snapshot of the system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  276&#xA;&#xA;C       6.676339    0.192796   12.145936&#xA;C      11.366235   16.834216   11.495125&#xA;H      12.019625   16.145506   12.044248&#xA;C       6.280053    1.639054   12.103951&#xA;N      11.303223   18.196153   11.753643&#xA;Zn      9.200748    0.750607   13.658523&#xA;C       3.578268   11.370255    5.453809&#xA;C      13.699914   14.021615    9.570215&#xA;H      12.622041   13.861431    9.425111&#xA;C       4.881148   10.804871    4.968113&#xA;N      14.651099   13.166309    9.051709&#xA;Zn      2.194846    9.249976    3.894082&#xA;C      13.573519   19.782104    9.372003&#xA;C       9.650302    3.129888   11.785367&#xA;H       9.451958    3.777791   12.648844&#xA;C      13.402220   18.347024    9.002673&#xA;H      12.345544   18.034597    9.157673&#xA;H      14.047492   17.692827    9.624574&#xA;H      13.635063   18.196773    7.929953&#xA;N       9.589721    1.748789   11.888965&#xA;C      15.251869    8.903745    9.292279&#xA;C       4.734553    7.487697    4.402852&#xA;H       5.345935    8.231599    3.879621&#xA;C      13.931488    8.795944    9.990504&#xA;H      14.017715    9.209606   11.023534&#xA;H      13.127887    9.358163    9.470857&#xA;H      13.626476    7.728751   10.050790&#xA;N       3.391155    7.702228    4.636291&#xA;C      11.492100   17.969934    5.910694&#xA;C       7.710219    1.633914    6.953133&#xA;H       7.897343    2.609658    6.500153&#xA;C      11.871790   16.533542    5.695331&#xA;N       8.178834    0.474885    6.374283&#xA;Zn      8.846073    0.518570    4.431922&#xA;C      18.018082   13.102289   12.089180&#xA;C       7.797038   10.609563    7.407416&#xA;H       8.784880   10.150691    7.245500&#xA;C      16.657250   12.770488   12.624026&#xA;N       6.763390    9.912517    8.004245&#xA;Zn      7.287796    8.218983    8.950470&#xA;C      10.959897    1.902131    5.766770&#xA;C      15.458254   18.472285    3.835431&#xA;H      15.619357   17.600477    3.184691&#xA;C      10.384827    3.289231    5.783887&#xA;H      10.357980    3.670437    6.828553&#xA;H       9.376720    3.355456    5.333419&#xA;H      11.038229    3.972835    5.192128&#xA;N      14.527956   19.452798    3.525318&#xA;C       6.342419    5.444221    7.934236&#xA;C      17.113192    9.230065   12.448452&#xA;H      16.684351   10.209479   12.678873&#xA;C       7.704913    4.889852    7.656142&#xA;H       7.822026    4.588041    6.590487&#xA;H       8.455953    5.684095    7.859673&#xA;H       7.945187    4.014297    8.299972&#xA;N      18.454457    9.068402   12.177065&#xA;C       9.150045    7.564927    3.845904&#xA;C      15.627362    7.011960   16.210630&#xA;H      16.393699    7.326585   15.489868&#xA;C       8.851551    7.546020    5.316240&#xA;N      15.743846    7.267011   17.568874&#xA;Zn     10.881452    9.948103    3.612691&#xA;C      11.145352    7.154075   14.519854&#xA;C       6.557603    8.929112    1.998930&#xA;H       7.052734    9.054566    2.971215&#xA;C      10.658971    6.077478   13.597495&#xA;H       9.856155    5.474559   14.070719&#xA;H      10.269273    6.513559   12.655227&#xA;H      11.484152    5.374205   13.345025&#xA;N       6.105426    7.713129    1.510008&#xA;Zn      6.441266    5.975540    2.582166&#xA;C       6.404807   13.131627   -0.068408&#xA;C      12.198581   11.819676   12.116357&#xA;H      12.054318   11.306461   11.154472&#xA;C       5.791880   13.267054    1.289376&#xA;N      11.396191   11.536675   13.207880&#xA;Zn      4.827434   10.628725   -1.166858&#xA;C      14.708173   11.008743   16.156150&#xA;C       8.760805   13.306559    3.389321&#xA;H       8.537568   14.287203    3.822534&#xA;C      14.989668   10.335533   14.851565&#xA;H      14.513397    9.329954   14.835542&#xA;H      14.588745   10.931067   14.001634&#xA;H      16.084894   10.186719   14.721887&#xA;N       8.943752   13.119624    2.028267&#xA;Zn      8.974391   14.689065    0.715995&#xA;C       8.957609   12.087290    4.020148&#xA;H       8.830571   11.799461    5.071521&#xA;N       9.302096   11.149530    3.064910&#xA;C      14.411036    6.387805   15.992968&#xA;H      13.932985    6.077246   15.052492&#xA;H       9.451037    8.301016    5.866746&#xA;H       7.773858    7.742585    5.519121&#xA;H       9.097844    6.543566    5.737511&#xA;N      13.778078    6.224194   17.210264&#xA;C       6.409791    9.870768    1.003454&#xA;H       6.694736   10.928033    1.004326&#xA;N       5.861515    9.257696   -0.106418&#xA;C      13.122867   12.785623   12.490837&#xA;H      13.884957   13.294078   11.889375&#xA;H       5.282716   12.338508    1.616533&#xA;H       6.568851   13.530815    2.037771&#xA;H       5.018093   14.065592    1.286679&#xA;N      12.902468   13.103341   13.817350&#xA;C      14.361578   15.019237   10.279061&#xA;H      13.953930   15.861465   10.855413&#xA;H       5.210771    9.921468    5.563887&#xA;H       5.696809   11.557275    5.019954&#xA;H       4.780339   10.493639    3.901870&#xA;N      15.720511   14.787374   10.186987&#xA;Zn      4.883603   13.676186    7.099788&#xA;C      16.518190    7.980776   12.372815&#xA;H      15.462931    7.717038   12.558776&#xA;N      17.470848    7.043292   11.993391&#xA;Zn      3.698399    3.885889    6.509382&#xA;C       7.021785    1.310142    8.110820&#xA;H       6.476066    1.966490    8.806051&#xA;H      12.964522   16.448503    5.492520&#xA;H      11.642687   15.930883    6.600439&#xA;H      11.351254   16.080459    4.818441&#xA;N       7.058305   -0.066374    8.248390&#xA;Zn      5.605027   -0.855441    9.405391&#xA;C       7.377646   11.913600    7.207342&#xA;H       7.933338   12.773177    6.814760&#xA;H      16.090698   12.101319   11.935914&#xA;H      16.063653   13.704578   12.715967&#xA;H      16.723050   12.279741   13.622794&#xA;N       6.069967   12.025230    7.647205&#xA;C      16.122306   18.847337    4.996570&#xA;H      16.931240   18.367845    5.561867&#xA;N      15.609299   20.060653    5.407419&#xA;Zn     11.831287    2.129986    8.598593&#xA;C       5.089420    6.240094    4.923489&#xA;H       6.085073    5.782511    5.048832&#xA;N       3.951057    5.671853    5.475388&#xA;C      10.495529   16.545199   10.461760&#xA;H      10.289254   15.598051    9.941104&#xA;H       5.639666    1.852151   11.222702&#xA;H       5.697997    1.925936   13.012591&#xA;H       7.177800    2.294591   12.045937&#xA;N       9.883230   17.725185   10.068031&#xA;C       9.981367    3.449550   10.474937&#xA;H      10.141440    4.433533   10.011337&#xA;N      10.142927    2.274214    9.757123&#xA;C      11.952749   10.995966    6.353089&#xA;C      12.924023    9.132919    6.976836&#xA;H      13.577486    8.444173    7.525805&#xA;C      11.556381   12.442200    6.309941&#xA;H      10.977568   12.730516    7.220191&#xA;H      10.912590   12.653326    5.430602&#xA;H      12.453734   13.097901    6.247413&#xA;N      12.861250   10.494961    7.235182&#xA;C      10.583560    2.867395   15.223300&#xA;C       8.422659    3.219908   15.361987&#xA;H       7.344928    3.061655   15.213243&#xA;C      11.887920    2.296486   14.748249&#xA;N       9.373705    2.361576   14.848012&#xA;C       2.849498    9.771594    0.879751&#xA;C       2.644522   11.625157    2.016552&#xA;H       2.445590   12.273815    2.879387&#xA;C       2.677488    8.336578    0.511679&#xA;H       1.621396    8.024033    0.669918&#xA;H       3.324797    7.683127    1.132015&#xA;H       2.907623    8.186361   -0.561608&#xA;N       2.583383   10.244325    2.121776&#xA;C      13.691144   16.605953   13.812624&#xA;C      15.455798   17.490102   12.888514&#xA;H      16.066028   18.231683   12.360407&#xA;C      12.371224   16.501461   14.512298&#xA;H      12.456320   16.922138   15.542526&#xA;H      11.567069   17.059744   13.989177&#xA;H      12.066300   15.434776   14.579607&#xA;N      14.113422   17.706478   13.125200&#xA;C      18.498397    9.470541   15.674439&#xA;C      18.432633   11.638650   15.441743&#xA;H      18.617730   12.614280   14.987584&#xA;C      18.878699    8.034254   15.459276&#xA;H      19.971301    7.949825   15.255754&#xA;H      18.357994    7.580634   14.582736&#xA;H      18.650537    7.431765   16.364690&#xA;N      18.902116   10.479782   14.863272&#xA;C       7.292364    3.098945    3.604161&#xA;C       9.351903    2.908406    2.886974&#xA;H      10.338837    2.448752    2.721417&#xA;C       5.931916    2.767843    4.140624&#xA;N       8.319390    2.211875    3.486264&#xA;C       9.403366    9.598629   10.286638&#xA;C      10.183092    7.665480    9.625597&#xA;H      10.343840    6.794842    8.973125&#xA;C       8.826690   10.984979   10.307664&#xA;N       9.251716    8.646213    9.318397&#xA;C      11.618348   16.249488    2.138670&#xA;C      10.107938   17.733136    2.682860&#xA;H       9.679497   18.712967    2.912353&#xA;C      12.979846   15.693885    1.859437&#xA;N      11.448761   17.570307    2.410926&#xA;C       7.591857   15.265255    8.364377&#xA;C       8.620988   15.511532    6.446866&#xA;H       9.387277   15.826260    5.726124&#xA;C       7.293663   15.246474    9.834714&#xA;N       8.737671   15.766467    7.805192&#xA;C      16.420287   17.959168    8.726646&#xA;C      17.282844   18.933153   10.487683&#xA;H      17.778615   19.057765   11.459793&#xA;C      15.932109   16.883716    7.803773&#xA;H      15.132099   16.278529    8.278923&#xA;H      15.538136   17.321515    6.864105&#xA;H      16.757532   16.182705    7.546097&#xA;N      16.830091   17.717610    9.998126&#xA;C      13.409549    4.631698    9.700958&#xA;C      13.751948    4.124945    7.601212&#xA;H      13.606555    3.613167    6.638576&#xA;C      12.799797    4.762886   11.060487&#xA;N      12.952290    3.837898    8.693737&#xA;C       3.983815    1.003710    7.666170&#xA;C       3.486453    2.502152    9.182446&#xA;H       3.265221    3.482883    9.616429&#xA;C       4.262643    0.330836    6.360686&#xA;H       3.857125    0.925200    5.512164&#xA;H       5.357721    0.184763    6.225916&#xA;H       3.788984   -0.675966    6.346499&#xA;N       3.668735    2.315695    7.821205&#xA;C       3.682358    1.282530    9.812661&#xA;H       3.555263    0.994473   10.863971&#xA;N       4.025498    0.344799    8.856823&#xA;C       7.404745   14.887350    6.229280&#xA;H       6.926596   14.576855    5.288762&#xA;H       7.893022   16.001456   10.385187&#xA;H       6.216105   15.442423   10.037940&#xA;H       7.540673   14.244188   10.256112&#xA;N       6.771946   14.723560    7.446784&#xA;C      17.133827   19.875679    9.493507&#xA;H      17.418293   20.933009    9.494627&#xA;N      16.584285   19.263818    8.383598&#xA;C      14.675333    5.091639    7.976442&#xA;H      15.435798    5.603354    7.375640&#xA;H      12.287128    3.835318   11.384690&#xA;H      13.579083    5.020359   11.808656&#xA;H      12.029410    5.564680   11.062451&#xA;N      14.457176    5.405465    9.304289&#xA;C       9.084182    4.217835   16.070651&#xA;H       8.676372    5.061912   16.644301&#xA;H      12.200391    1.403125   15.338224&#xA;H      12.709503    3.040405   14.821799&#xA;H      11.801647    1.997339   13.677582&#xA;N      10.442824    3.983175   15.982713&#xA;C       9.511779   16.484270    2.607088&#xA;H       8.456197   16.221770    2.792915&#xA;H      13.098038   15.394683    0.793158&#xA;H      13.218182   14.816382    2.501108&#xA;H      13.732070   16.486198    2.065473&#xA;N      10.463176   15.546256    2.227365&#xA;C      17.745363   11.314796   16.600117&#xA;H      17.199739   11.971024   17.295520&#xA;N      17.782875    9.938371   16.738177&#xA;C       8.933336    4.213156    2.689531&#xA;H       9.488643    5.072535    2.295944&#xA;H       5.340738    3.702882    4.236765&#xA;H       5.997850    2.274170    5.137781&#xA;H       5.362367    2.102016    3.451829&#xA;N       7.626978    4.325471    3.133351&#xA;C      10.849316    8.039228   10.785877&#xA;H      11.660254    7.560108   11.348636&#xA;H       8.795260   11.361674   11.353896&#xA;H       9.482138   11.671424    9.721257&#xA;H       7.820973   11.051876    9.853019&#xA;N      10.336688    9.252251   11.199172&#xA;C      15.810234   16.242616   13.410065&#xA;H      16.805472   15.783387   13.532764&#xA;N      14.672437   15.676581   13.965184&#xA;C      12.053319    8.843934    5.943410&#xA;H      11.846943    7.896801    5.422855&#xA;N      11.441470   10.023948    5.549504&#xA;C       2.975958   11.942980    0.705818&#xA;H       3.135644   12.926508    0.240909&#xA;N       3.137256   10.766848   -0.010427&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-11-17T08:48:50.980" Title="Guess cell parameters from atomic coordinates" Tags="|software-recommendations|periodic-system|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="7023" PostTypeId="1" AcceptedAnswerId="7109" CreationDate="2021-11-08T18:46:58.203" Score="7" ViewCount="417" Body="&lt;p&gt;I have seen an increase in the use of the coupled-cluster doubles (CCD) method recently. CCD uses the exponential ansatz of the coupled cluster equations, but only includes amplitudes to double excitations. I know that it is possible to derive MP2 from the coupled cluster equations, and essentially show that MP2 is capturing some portion of the double excitations.&lt;/p&gt;&#xA;&lt;p&gt;I am curious, however, how MP2 and CCD compare in this respect? That is, should they be expected to be essentially comparable? Does MP2 implicitly include any excitations that CCD does not (perhaps some single excitations)? Or should CCD be strictly better than MP2 in terms of the amount of correlation included, presumably due to the presence of some approximate quadruple excitations (from the product of &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt; terms)? Also, is how does the computational cost of CCD compare to MP2?&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-11-18T06:12:12.257" LastActivityDate="2021-11-19T00:49:43.240" Title="How does coupled cluster doubles (CCD) compare to MP2?" Tags="|electronic-structure|coupled-cluster|many-body-perturbation-theory|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="7025" PostTypeId="2" ParentId="6927" CreationDate="2021-11-09T18:51:53.697" Score="6" Body="&lt;p&gt;Following Tyberius's suggestion, I now turn my comment into an answer.&lt;/p&gt;&#xA;&lt;p&gt;As always, the most reliable way of estimating the effect of the dispersion correction is to actually do two simulations, one with the correction and one without it. But since a liquid simulation is expensive, it's better to test the effect of the correction on a simpler system that is sufficiently similar to your system. The simplest choice is crystalline SiO2, whose density is not far from that of liquid SiO2, but whose structure optimization is very cheap due to the high symmetry. A more accurate choice may be glassy SiO2, with which you lose the advantage of a high symmetry and a small periodic cell, but which is still much cheaper than a liquid simulation, since with a glass you can do structure optimization (quenching) instead of MD.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-11-09T18:51:53.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7026" PostTypeId="1" CreationDate="2021-11-10T00:17:58.370" Score="5" ViewCount="88" Body="&lt;p&gt;I've heard so many times that spacetime translation invariance is assumed when we speak about Noether's current density. Could someone explain to me, why is that so? What if we don't assume it?&lt;/p&gt;&#xA;&lt;p&gt;To be precise, where did we get an idea for assuming something like that?&lt;/p&gt;&#xA;&lt;p&gt;I am, of course, familiar with conservation law and continuity equation that Noether's charges and current satisfy, but I still don't see why is spacetime translation always being assumed...&lt;/p&gt;&#xA;&lt;p&gt;I'm looking forward to hearing from somebody here.&lt;/p&gt;&#xA;" OwnerUserId="4092" LastEditorUserId="5" LastEditDate="2021-11-18T00:36:19.413" LastActivityDate="2021-11-18T00:36:19.413" Title="Spacetime translation of Noether's current density" Tags="|mathematical-modeling|symmetry|" AnswerCount="0" CommentCount="7" ClosedDate="2022-01-18T15:15:51.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="7028" PostTypeId="1" CreationDate="2021-11-10T14:45:49.977" Score="8" ViewCount="302" Body="&lt;p&gt;When creating a Graphene layer in VMD using the Nanotube Builder it only generates hexagons with single bonds because of this errors occur when creating the topology for gromacs software using,&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gaxGB.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gaxGB.png&quot; alt=&quot;graphene with double bonds&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx x2top -f graphene.pdb -o system.top&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here are the errors observed in gromacs output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Can not find forcefield for atom C-4 with 3 bonds&#xA;Can not find forcefield for atom C-6 with 3 bonds&#xA;Can not find forcefield for atom C-7 with 3 bonds&#xA;Can not find forcefield for atom C-8 with 3 bonds&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Please not that the border line C atoms will assign H atoms this can be done with another software which is not the major issue its missing double bonds thus carbon is missing its full 4 bonds.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone help me with this issue or please suggest any other software that can do this.&lt;/p&gt;&#xA;" OwnerUserId="4536" LastEditorUserId="5" LastEditDate="2021-11-18T06:14:50.870" LastActivityDate="2021-11-18T06:14:50.870" Title="How to add double bonds to hexagons when creating a graphene layer in VMD?" Tags="|gromacs|vmd|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-14T02:27:21.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="7029" PostTypeId="5" CreationDate="2021-11-10T18:02:48.187" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:02:48.187" LastActivityDate="2021-11-10T18:02:48.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7030" PostTypeId="4" CreationDate="2021-11-10T18:02:48.187" Score="0" Body="For questions related to the Protein Data Bank file format, e.g. information included, converting to/from this format. " OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:02:48.187" LastActivityDate="2021-11-10T18:02:48.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7031" PostTypeId="5" CreationDate="2021-11-10T18:05:50.523" Score="0" Body="&lt;p&gt;Most of PyMOL's source code is open source, though Schrodinger distributes compiled binaries with additional features to users with a license.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:05:50.523" LastActivityDate="2021-11-10T18:05:50.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7032" PostTypeId="4" CreationDate="2021-11-10T18:05:50.523" Score="0" Body="For questions about using the PyMOL molecular visualization program distributed by Schrodinger." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:05:50.523" LastActivityDate="2021-11-10T18:05:50.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7033" PostTypeId="5" CreationDate="2021-11-10T18:11:14.610" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:11:14.610" LastActivityDate="2021-11-10T18:11:14.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7034" PostTypeId="4" CreationDate="2021-11-10T18:11:14.610" Score="0" Body="For questions about the FCIDUMP file format used for saving one and two electron integral." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:11:14.610" LastActivityDate="2021-11-10T18:11:14.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7035" PostTypeId="5" CreationDate="2021-11-10T18:21:07.053" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:21:07.053" LastActivityDate="2021-11-10T18:21:07.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7036" PostTypeId="4" CreationDate="2021-11-10T18:21:07.053" Score="0" Body="For questions about the self-interaction error introduced in many approximate DFT functionals." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:21:07.053" LastActivityDate="2021-11-10T18:21:07.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7037" PostTypeId="5" CreationDate="2021-11-10T18:24:23.633" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:24:23.633" LastActivityDate="2021-11-10T18:24:23.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7038" PostTypeId="4" CreationDate="2021-11-10T18:24:23.633" Score="0" Body="For questions about employing multiple Schrödinger programs through Maestro. The individual programs (e.g. Jaguar, Quantum Espresso) should be tagged separately." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:24:23.633" LastActivityDate="2021-11-10T18:24:23.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7039" PostTypeId="5" CreationDate="2021-11-10T18:29:35.093" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:29:35.093" LastActivityDate="2021-11-10T18:29:35.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7040" PostTypeId="4" CreationDate="2021-11-10T18:29:35.093" Score="0" Body="For questions about materials designed to have properties that don't occur naturally." OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-10T18:29:35.093" LastActivityDate="2021-11-10T18:29:35.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7041" PostTypeId="2" ParentId="6398" CreationDate="2021-11-10T19:21:21.130" Score="1" Body="&lt;p&gt;Just basically collecting the comments here. The &lt;a href=&quot;http://cgmartini.nl/index.php/tutorials-general-introduction-gmx5/proteins-gmx5#soluble-protein&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials page&lt;/a&gt; for Martini states:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The secondary structure of the protein influences both the selected bead types and bond/angle/dihedral parameters of each residue.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So depending on the secondary structure, they may just alter how coarse the mapping is depending on how much detail is needed to emulate this structure.&lt;/p&gt;&#xA;&lt;p&gt;As Vasista notes, the parameters for beads can likely differ if its known to be part of a &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;-sheet or &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-helix.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-10T19:21:21.130" CommentCount="0" CommunityOwnedDate="2021-11-10T19:21:21.130" ContentLicense="CC BY-SA 4.0" />
  <row Id="7042" PostTypeId="2" ParentId="7015" CreationDate="2021-11-10T20:34:40.030" Score="7" Body="&lt;p&gt;First off, those values are pretty close, probably within the accuracy of your method (I assume DFT).&#xA;Notice that you state all input parameters stay the same except that cell size. However, some parameters are changing. In this case, it's the k-point density. Simulations with different cell sizes, but same k-point mesh, will have different k-point densities. So I'm guessing that's what's causing the slight difference.&lt;/p&gt;&#xA;" OwnerUserId="38" LastActivityDate="2021-11-10T20:34:40.030" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7043" PostTypeId="1" CreationDate="2021-11-10T23:55:02.800" Score="2" ViewCount="94" Body="&lt;p&gt;I would like to know if there are any free alternatives to VESTA for visualizing crystal structures.&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerDisplayName="Vikram Kumar" LastActivityDate="2021-11-10T23:59:31.137" Title="Visualizing Crystal Structures" Tags="|crystallography|" AnswerCount="0" CommentCount="3" ClosedDate="2021-11-11T13:03:56.240" ContentLicense="CC BY-SA 4.0" />
  <row Id="7044" PostTypeId="1" AcceptedAnswerId="7131" CreationDate="2021-11-11T11:30:56.997" Score="6" ViewCount="447" Body="&lt;p&gt;Using SIESTA, I want to plot the wavefunctions around the Fermi level (similar to HOMO/LUMO). Also, I want to do COOP analysis.&lt;/p&gt;&#xA;&lt;p&gt;From the SIESTA manual, I can setup to write the wavefunctions associated to a set of bands or selecting them by energy:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The user can optionally request that the wavefunctions corresponding&#xA;to the computed bands be written to file. They are written to the&#xA;SystemLabel.bands.WFSX file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The user can optionally request that specific wavefunctions are&#xA;written to file. These wavefunctions are re-computed after the&#xA;geometry loop (if any) finishes, using the last (presumably converged)&#xA;density matrix produced during the last self-consistent field loop&#xA;(after a final mixing). They are written to the&#xA;&lt;code&gt;SystemLabel.selected.WFSX&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;Note that the complete set of wavefunctions obtained during the last&#xA;iteration of the SCF loop will be written to &lt;code&gt;SystemLabel.fullBZ.WFSX&lt;/code&gt;&#xA;if the &lt;code&gt;COOP.Write&lt;/code&gt; option is in effect.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am using the following keywords:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WFS.Write.For.Bands     T&#xA;COOP.Write              T&#xA;WriteEigenvalues        T&#xA;WriteKbands             T&#xA;WriteBands              T&#xA;WriteWaveFunctions      T&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The results are two files a &lt;code&gt;SystemLabel.fullBZ.WFSX&lt;/code&gt; with ~800MB and a &lt;code&gt;SystemLabel.bands.WFSX&lt;/code&gt; with 14GB.&lt;/p&gt;&#xA;&lt;p&gt;A doubt:&lt;br /&gt;&#xA;&lt;strong&gt;Which one should I use to plot the wavefunctions corresponding to eigenvalues around the Fermi energy?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-11-11T20:47:10.710" LastActivityDate="2022-10-16T23:15:11.827" Title="SIESTA output wavefunctions: all vs selected?" Tags="|density-functional-theory|siesta|wavefunctions|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7045" PostTypeId="2" ParentId="1535" CreationDate="2021-11-11T13:48:33.830" Score="5" Body="&lt;h2&gt;FLEUR&lt;/h2&gt;&#xA;&lt;p&gt;&lt;em&gt;Disclaimer: I'm a developer of the Fleur code.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.flapw.de&quot; rel=&quot;noreferrer&quot;&gt;Fleur&lt;/a&gt; is a Fortran-based open source (MIT license) FLAPW(+LO) code under rapid development. A detailed user guide for the code is available on it's website and there also is a user forum. Fleur connects to numerous other software packages and frameworks. Among these are &lt;a href=&quot;https://www.flapw.de/MaX-5.1/spex/&quot; rel=&quot;noreferrer&quot;&gt;Spex&lt;/a&gt; (A GW code), Wannier90, AiiDA (for workflow automatization and provenance tracking), and LibXC.&lt;/p&gt;&#xA;&lt;p&gt;Work on Fleur is mainly performed by the &lt;a href=&quot;https://www.flapw.de/MaX-5.1/team/&quot; rel=&quot;noreferrer&quot;&gt;development group in Jülich&lt;/a&gt;. External development is appreciated, please register on the &lt;a href=&quot;https://iffgit.fz-juelich.de/fleur/fleur&quot; rel=&quot;noreferrer&quot;&gt;gitlab page&lt;/a&gt; to be able to contribute. I suggest that people interested in contributing to the code or basing their developments on the code get in contact with the group to find out how this is best done.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2021-11-11T13:48:33.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7046" PostTypeId="1" AcceptedAnswerId="7052" CreationDate="2021-11-11T18:45:45.090" Score="6" ViewCount="318" Body="&lt;p&gt;I know that &lt;code&gt;&amp;amp;CONTROL='vc-relax'&lt;/code&gt; option calculation performs a unit cell relaxation, and that the &lt;code&gt;ATOMIC_POSITIONS&lt;/code&gt; can be fixed as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS crystal&#xA;  Fe    0.000 0.000  0.00  0  0  0&#xA;  Fe    0.500 0.500  0.00  0  0  0&#xA;  Se    0.500 0.000  1.33  0  0  1&#xA;  Se    0.000 0.500 -1.33  0  0  1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which I believe tells me that only the z-component of the Se atoms &lt;em&gt;within&lt;/em&gt; the unit cell are adjusted. (This I learned from a nice tutorial by RadeMaker [1]. The pw.x documentation itself is not clear about this.)&lt;/p&gt;&#xA;&lt;p&gt;Can I do something similarly for the unit cell parameters themselves? For example...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS angstrom&#xA;  3.77 0.00 0.00  1  0  0&#xA;  0.00 3.77 0.00  0  1  0&#xA;  0.00 0.00 5.52  0  0  1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I can't find documentation detailing this, or anything clarifying on StackExchange or ResearchGate. I would very much like to prevent the boundary conditions from tilting out of the plane of the Fe atoms. Thanks!&lt;/p&gt;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://arxiv.org/abs/2011.09888&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/2011.09888&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="7" LastEditDate="2021-11-11T19:09:55.343" LastActivityDate="2021-11-13T01:52:05.240" Title="How do I relax only the in-plane component of the unit cell?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7047" PostTypeId="1" CreationDate="2021-11-12T00:05:18.010" Score="6" ViewCount="127" Body="&lt;p&gt;Are there any codes available? What is the easiest way?&lt;/p&gt;&#xA;" OwnerUserId="3613" LastEditorUserId="5" LastEditDate="2021-11-18T06:04:40.933" LastActivityDate="2021-11-19T10:32:11.283" Title="How can I build an MoS2 nanoribbon?" Tags="|density-functional-theory|software-recommendations|materials-design|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7048" PostTypeId="5" CreationDate="2021-11-12T19:48:44.343" Score="0" Body="" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-12T19:48:44.343" LastActivityDate="2021-11-12T19:48:44.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7049" PostTypeId="4" CreationDate="2021-11-12T19:48:44.343" Score="0" Body="For questions about modeling/predicting the structural of biomolecular entities (e.g. proteins, DNA/RNA, organelles, etc)" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-12T19:48:44.343" LastActivityDate="2021-11-12T19:48:44.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7050" PostTypeId="2" ParentId="6386" CreationDate="2021-11-12T20:46:11.017" Score="4" Body="&lt;p&gt;Based on your &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6375/solving-for-the-deviation-in-the-polymer-volume-fraction-under-the-random-phase&quot;&gt;previous questions&lt;/a&gt;, I assume this equation was from Section 1.2.1 of Doi's &lt;a href=&quot;https://www.eng.uc.edu/%7Ebeaucag/Classes/Properties/Books/M.%20Doi,%20H.%20See%20-%20Introduction%20to%20polymer%20physics-Oxford%20University%20Press,%20USA%20(1996).pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Polymer Physics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;While Doi doesn't explicitly state this anywhere that I can find, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; is the label he uses for the momentum/wavevector. I'm more accustomed to seeing this denoted as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;, but as Anyon noted in the comments, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; may be the more common notation when working with scattering. You should also watch out that &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q} $&lt;/span&gt; is also used in other places to denote the &lt;a href=&quot;https://en.wikipedia.org/wiki/Canonical_coordinates&quot; rel=&quot;nofollow noreferrer&quot;&gt;canonical &lt;em&gt;position&lt;/em&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As for what it means to work in the small &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; limit, it helps to think of it as a wavevector, which is related proportional in magnitude to &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{\lambda}$&lt;/span&gt;. So zero &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt; corresponds to an infinite wavelength, which means we are essentially taking the limit where &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is changing very slowly over space.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-12T20:46:11.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7051" PostTypeId="2" ParentId="6949" CreationDate="2021-11-12T23:05:37.980" Score="3" Body="&lt;p&gt;This is not quite an answer yet, but I wanted to collect some things I found.&lt;/p&gt;&#xA;&lt;p&gt;Since it looked like this was some kind of overflow error, I tried to see if shrinking the calculation or increasing the memory would eliminate the error. The error remained if I increased the memory, explicitly included an RWF file, and if removed the polarization functions (6-31g or STO-3G). However, if I dropped to doing an (8,8) CAS instead of a (10,10), the calculation finished without issue, even if I bump the basis up to cc-pvtz. Interestingly, a (8,10) CAS also gets past this point, despite print out the same &lt;code&gt;MEIJ SPACE OFLO&lt;/code&gt; message.&lt;/p&gt;&#xA;&lt;p&gt;To me it, it still seems like you are running into a limit on the configurations Gaussian can handle. The (8,8) has ~1,700 configs, the (8,10) ~13,000, and the (10,10) ~20,000. Somewhere in between those it seems to hit a limit and it's not clear to me if there is an IOP to change this or if it's hard coded.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-12T23:05:37.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7052" PostTypeId="2" ParentId="7046" CreationDate="2021-11-13T01:52:05.240" Score="4" Body="&lt;p&gt;To play with parameters or vectors of unit cell, you can use following tag inside &lt;code&gt;&amp;amp;CELL&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cell_dofree CHARACTER&#xA;Default:    'all'&#xA;Select which of the cell parameters should be moved:&#xA;            &#xA;'all' :&#xA; all axis and angles are moved&#xA;            &#xA;'ibrav' :&#xA; all axis and angles are moved, but the lattice remains consistent&#xA;with the initial ibrav choice. You can use this option in combination&#xA;with any other one by specifying &amp;quot;ibrav+option&amp;quot;. Please note that some&#xA;combinations do not make sense for some crystals and will guarantee that&#xA;the relax will never converge. E.g. 'ibrav+2Dxy' is not a problem for&#xA;hexagonal cells, but will never converge for cubic ones.&#xA;            &#xA;'x' :&#xA; only the x component of axis 1 (v1_x) is moved&#xA;            &#xA;'y' :&#xA; only the y component of axis 2 (v2_y) is moved&#xA;            &#xA;'z' :&#xA; only the z component of axis 3 (v3_z) is moved&#xA;            &#xA;'xy' :&#xA; only v1_x and v2_y are moved&#xA;            &#xA;'xz' :&#xA; only v1_x and v3_z are moved&#xA;            &#xA;'yz' :&#xA; only v2_y and v3_z are moved&#xA;            &#xA;'xyz' :&#xA; only v1_x, v2_y, v3_z are moved&#xA;            &#xA;'shape' :&#xA; all axis and angles, keeping the volume fixed&#xA;            &#xA;'volume' :&#xA; the volume changes, keeping all angles fixed (i.e. only celldm(1) changes)&#xA;            &#xA;'2Dxy' :&#xA; only x and y components are allowed to change&#xA;            &#xA;'2Dshape' :&#xA; as above, keeping the area in xy plane fixed&#xA;            &#xA;'epitaxial_ab' :&#xA; fix axis 1 and 2 while allowing axis 3 to move&#xA;            &#xA;'epitaxial_ac' :&#xA; fix axis 1 and 3 while allowing axis 2 to move&#xA;            &#xA;'epitaxial_bc' :&#xA; fix axis 2 and 3 while allowing axis 1 to move&#xA;Above tag may not work perfectly if cell is not orthogonal&#xA;            &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;If you don't want forces and stress to relax along certain direction, you have to&#xA;edit subroutine init_dofree in file Modules/cell_base.f90 and recompile your &lt;code&gt;QE&lt;/code&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-11-13T01:52:05.240" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7053" PostTypeId="2" ParentId="3899" CreationDate="2021-11-13T13:58:58.127" Score="6" Body="&lt;p&gt;Using the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Lubachevsky%E2%80%93Stillinger_algorithm&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lubachevsky-Stillinger algorithm&lt;/a&gt; is the best choice. You get up to 64% space filling for a random monodisperse sphere packing. Another classical study is the algorithm by Jodrey and Tory (&lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.32.2347&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;W. S. Jodrey and E. M. Tory&#xA;Computer simulation of close random packing of equal spheres, Phys. Rev. A 32, 2347 (1985)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4551" LastEditorUserId="7" LastEditDate="2021-11-14T16:36:00.697" LastActivityDate="2021-11-14T16:36:00.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7054" PostTypeId="2" ParentId="4741" CreationDate="2021-11-13T19:14:32.037" Score="3" Body="&lt;p&gt;I'm going to reproduce the part of my answer from the &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4737/5&quot;&gt;linked question&lt;/a&gt; that relates to the spin-splitting.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I don't believe the spin-splitting or field splitting can be read from the DOS. The way they are mentioned in the paper seems to suggest they are giving a qualitative explanation for seeing all the compounds in high spin configurations. The spectrochemical series gives an ordering of ligands based on how much field splitting they should cause. Since S is known to be a weak-field ligand, it makes sense that the spin splitting energy would be larger than the field splitting, leading to high spin configurations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As for the crystal-field splitting, perhaps not from the DOS on its own, but the &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4867/7&quot;&gt;PDOS&lt;/a&gt; could help you identify the gap in energy between states formed from different types of d-orbitals.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-13T19:20:02.797" LastActivityDate="2021-11-13T19:20:02.797" CommentCount="0" CommunityOwnedDate="2021-11-13T19:16:11.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="7055" PostTypeId="2" ParentId="6978" CreationDate="2021-11-13T20:45:53.657" Score="7" Body="&lt;p&gt;This is a very good and tricky question, which I don't think has a clear and definite answer. I think I should also preface by saying that I can't answer it from the point of view of polymer physics, but instead from my experience in biomolecular simulations. However, this particular problem is basically a version of the sampling exploration-exploitation trade-off and as such is equivalent in many different fields.&lt;/p&gt;&#xA;&lt;p&gt;You can think about two types of sampling problems: one with a small discrete number of states where your aim is to explore all of them during the course of your simulation, or alternatively (and much more commonly) a setting where you have too many states to explore and you just want to explore as many as possible.&lt;/p&gt;&#xA;&lt;p&gt;In the former case, it is conceptually (although not practically) straightforward to define a clear-cut &amp;quot;best&amp;quot; way to sample based on transition matrices: in this case, you can assign an effective averaged transition matrix (with dimensions equal to the number of discrete states) to each of the different moves. One such example is a simulated tempering simulation with a small number of discrete temperatures, where your aim is to have maximum mobility between the lowest and the highest temperature. This defines an optimisable quantity which is a function of these transition matrices and you can in this way determine the best type of move (if all moves are ergodic), or the best combination of moves otherwise. It is not obvious to me how you can actually do the latter in practice, but I imagine it is possible to do adaptively using some sort of reinforcement learning technique, since you have a countable action space and a well-defined reward function. Definitely not trivial, but well-defined and possible. This would make for a nice PhD project!&lt;/p&gt;&#xA;&lt;p&gt;The second setting (i.e. the one in question) is &lt;em&gt;much&lt;/em&gt; harder, because the objective is not even well-defined. On one hand you want to explore as many states as possible, but on the other hand you want to explore all of them &amp;quot;evenly&amp;quot;. What I mean by this is that even if one of the moves was guaranteed to provide you with strictly new configurations for the duration of your whole simulation, you would still want to attempt the other moves, since they provide configurations that cannot be explored by the first one (e.g. if you only did successful end rotations, the sampling would still be pretty useless). Therefore, you need to ask yourself how much you care about each of these moves and assign each one a &amp;quot;target&amp;quot; weight, which is purely arbitrary and based on your goals. The simplest and most obvious way to do this is to give an equal importance to each of these moves.&lt;/p&gt;&#xA;&lt;p&gt;But that's not the end of it, because in practice each of these moves will have different average acceptance probabilities, making some of them more efficient than the others. Again, if you were simply interested in new configurations regardless of the type of move, you should be simply able to adaptively determine the one giving you the best acceptance and choose it randomly proportional to its acceptance (how you define this proportionality is also of course arbitrary, because the only way to be completely sure certain moves are bad is to evaluate them and you don't want to do that!). However, if you care about all the moves to an extent, then you need to define how much performance loss you are willing to tolerate for each one of them. This is also completely arbitrary and it is not even clear to me if you can have a objectively good way of defining that.&lt;/p&gt;&#xA;&lt;p&gt;So what should you do? One way is to simply attempt all the moves with equal probability and accept that this is not the most efficient way, but is also the easiest way to define. Another (probably better) way is to continuously estimate the &amp;quot;usefulness&amp;quot; of each move and attempt it with a probability directly proportional to its currently estimated average acceptance: e.g. if one move has a 100 times better average acceptance than another one, it will be attempted 100 times as frequently. I have seen a variant of this idea be utilised in the case of &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726918/&quot; rel=&quot;noreferrer&quot;&gt;constant-pH simulations&lt;/a&gt;, where you want to change as many protonation states as possible, but you only want to do that if you are reasonably sure that the protonation state is likely at the pH of interest.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR: It is completely arbitrary how you do that, but it might make sense to start with equal probabilities and at some point switch to probabilities that are proportional to the average estimated acceptance of each of the moves.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2021-11-13T20:45:53.657" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7056" PostTypeId="1" CreationDate="2021-11-15T11:57:28.640" Score="10" ViewCount="699" Body="&lt;p&gt;How can one understand the concept of &lt;a href=&quot;https://en.wikipedia.org/wiki/Kramers_theorem&quot; rel=&quot;noreferrer&quot;&gt;Kramer's Degeneracy&lt;/a&gt; for an antiferromagnetic system where spin-up and spin-down bands overlap due to net zero magnetic moment?&lt;/p&gt;&#xA;" OwnerUserId="879" LastActivityDate="2021-11-15T13:18:11.493" Title="Kramer's Degeneracy and Antiferromagnetism" Tags="|density-functional-theory|condensed-matter|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7057" PostTypeId="2" ParentId="7056" CreationDate="2021-11-15T13:18:11.493" Score="8" Body="&lt;p&gt;You may want to have a look at my answer to a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6399/does-the-spin-polarised-dft-calculation-mean-broken-time-reversal-symmetry?rq=1&quot;&gt;related question&lt;/a&gt;. Basically, in the usual single-particle-model picture of an antiferromagnetic system, the total wavefunction is like &lt;span class=&quot;math-container&quot;&gt;$\Psi=|\uparrow\downarrow\uparrow\downarrow\uparrow\downarrow\cdots\rangle$&lt;/span&gt;. Its time-reversed version, &lt;span class=&quot;math-container&quot;&gt;$\tilde{\Psi}=|\downarrow\uparrow\downarrow\uparrow\downarrow\uparrow\cdots\rangle$&lt;/span&gt;, amounts to the system where every spin of the antiferromagnetic system is flipped, which certainly has the same energy as &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;. Therefore the Kramers degeneracy is present, but only on a global level.&lt;/p&gt;&#xA;&lt;p&gt;Note that the energy band model is an approximation, and is basically a single particle model. So while the Kramers theorem always holds when you flip all the spins of the system at once, it may or may not hold when you flip only one of them.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-11-15T13:18:11.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7058" PostTypeId="1" AcceptedAnswerId="7133" CreationDate="2021-11-15T15:43:39.287" Score="9" ViewCount="502" Body="&lt;p&gt;We are from a new research group working on matter modelling. Currently our work has focused mainly on classical Molecular Dynamics (MD), Lattice Dynamics (LD) and ab-initio methods. For  these, we have been using &lt;a href=&quot;https://www.lammps.org/&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt;, &lt;a href=&quot;http://gulp.curtin.edu.au/gulp/&quot; rel=&quot;noreferrer&quot;&gt;Gulp&lt;/a&gt;, &lt;a href=&quot;https://departments.icmab.es/leem/siesta/Documentation/index.html&quot; rel=&quot;noreferrer&quot;&gt;SIESTA&lt;/a&gt;, &lt;a href=&quot;https://www.quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;Quantum Espresso&lt;/a&gt; and &lt;a href=&quot;https://www.cp2k.org/&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Although we are currently studying the thermoelectric properties of semiconductor materials, we would like to expand our research focus to other areas &lt;strong&gt;such as gas adsorption as well&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;What software can we use for gas adsorption?&lt;/strong&gt;&lt;/em&gt; I am particularly interested in the ability to simulate larger system sizes, acceleration methods, interoperability with other third party tools, ease of use, etc. We are looking at both commercial as well as free packages.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2021-11-23T21:17:42.140" LastActivityDate="2021-12-06T14:47:11.803" Title="What software can I use for gas adsorption calculations?" Tags="|software|software-recommendations|condensed-matter|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="7059" PostTypeId="1" CreationDate="2021-11-16T03:37:32.867" Score="12" ViewCount="179" Body="&lt;p&gt;I have written a simulation engine in C++ to run a Monte Carlo simulation of polymers on a lattice. My code basically plants a polymer on a lattice, and performs certain Monte Carlo moves, including but not limited to the following:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/CStfs.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CStfs.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I ensure that excluded volume effects are maintained in this system as it evolves (if two monomers overlap, energy diverges, and move is rejected). Now that my software is running, I would like to run some benchmarks on it.&lt;/p&gt;&#xA;&lt;p&gt;My first thought is calculating Flory exponents. If I run my simulation with excluded volume and a certain monomer-solvent interaction, I should get a Flory exponent &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; such that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle R_g ^2 \rangle \propto N^\nu $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I have excluded volume interactions on a 3D lattice with no monomer-solvent interaction &lt;span class=&quot;math-container&quot;&gt;$\epsilon _{ms} = 0$&lt;/span&gt;, I should expect to see a &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; of 0.6. My question is, is there a scaling behavior to be seen when I have a &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{ms} &amp;gt;0$&lt;/span&gt; (bad solvent) and a &lt;span class=&quot;math-container&quot;&gt;$\epsilon _{ms} &amp;lt; 0$&lt;/span&gt; (good solvent)?&lt;/p&gt;&#xA;&lt;p&gt;Are there any other benchmarks I should run to check my simulation engine is functioning up to the mark?&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-11-18T05:59:58.453" LastActivityDate="2022-01-27T15:01:45.350" Title="Benchmarking Monte Carlo simulations of polymers" Tags="|software|high-performance-computing|monte-carlo|polymers|benchmark-timings|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7060" PostTypeId="2" ParentId="4447" CreationDate="2021-11-16T04:33:14.150" Score="5" Body="&lt;p&gt;If you are adamant on adding forces during geometry optimization, you could borrow formalisms from mechanochemistry. We have implemented such formalism using Python (see &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2352711021001436&quot; rel=&quot;noreferrer&quot;&gt;OpenMechanochem&lt;/a&gt;) and it is designed to work with &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;. This would allow you to patch quantum chemical software (molecular mechanics code too), including Gaussian and ORCA. But personally, I think fixing some important coordinates in your cluster can do the trick.&lt;/p&gt;&#xA;" OwnerUserId="4558" LastActivityDate="2021-11-16T04:33:14.150" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7061" PostTypeId="1" CreationDate="2021-11-16T10:42:20.090" Score="9" ViewCount="892" Body="&lt;p&gt;I'm writing this code of molecular dynamics about a pseudo-ideal gas in a box. The task is integrating the EOM for every atoms for a time-step dt fixed with the leapfrog method and measure the total energy, kinetic energy, potential energy (Lenard-Jones) plus the temperature and pressure. For the latters I should measure the &lt;strong&gt;autocorrelation function&lt;/strong&gt;, given as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Gamma(t)=\frac{1}{N-t}\sum_{i=1}^{N-t}(X_i-\bar{X})(X_{i+t}-\bar{X})\tag{1}&#xA;$$&lt;/span&gt;&#xA;Where &lt;span class=&quot;math-container&quot;&gt;$X_i$&lt;/span&gt; is the measure at the step &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\bar{X}$&lt;/span&gt; is the mean value.&#xA;Once did that, I should measure the &lt;strong&gt;autocorrelation time&lt;/strong&gt; which was given to us as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tau_{int}=\frac{1}{2}(1+2\sum_{t=1}^{N}\Gamma(t)) \tag{2}&#xA;$$&lt;/span&gt;&#xA;This &lt;span class=&quot;math-container&quot;&gt;$\tau_{int}$&lt;/span&gt; should give us an estimation of the true autocorrelation time, that would be, if the autocorrelation function was not discrete:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tau=\int_0^{+\infty} e^{-\frac{t}{\tau}}dt\tag{3}&#xA;$$&lt;/span&gt;&#xA;In my simuation I get &lt;span class=&quot;math-container&quot;&gt;$\tau_{int}\approx0.5$&lt;/span&gt;, which may tell me measures aren't correlated, the problem is I get that value whatever interval step I choose between a measure and the next one. In my case I get &lt;span class=&quot;math-container&quot;&gt;$\tau_{int}\approx0.5$&lt;/span&gt; for an interval of number of step &lt;span class=&quot;math-container&quot;&gt;$k=100$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k= 10$&lt;/span&gt;. To be honest I don't know how to explain it, mainly because I can't give meaning to the definition of &lt;span class=&quot;math-container&quot;&gt;$\tau_{int}$&lt;/span&gt;, if someone could explain me the reason behind that definition I woud be glad.&lt;/p&gt;&#xA;" OwnerUserId="4560" LastEditorUserId="5" LastEditDate="2021-11-16T20:57:20.880" LastActivityDate="2021-11-17T00:44:14.483" Title="What is autocorrelation time?" Tags="|molecular-dynamics|correlation-functions|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7062" PostTypeId="2" ParentId="467" CreationDate="2021-11-16T13:52:33.377" Score="10" Body="&lt;h1&gt;UnityMol&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Conceived with biological systems in mind, but relevant for any molecular system&lt;/li&gt;&#xA;&lt;li&gt;Modern interface: recent and still under active development&lt;/li&gt;&#xA;&lt;li&gt;Supported formats: &lt;code&gt;PDB&lt;/code&gt;, &lt;code&gt;mmCIF&lt;/code&gt;, &lt;code&gt;GRO&lt;/code&gt;, &lt;code&gt;Mol2&lt;/code&gt;, &lt;code&gt;XYZ&lt;/code&gt; and &lt;code&gt;SDF&lt;/code&gt; files, &lt;code&gt;OpenDX&lt;/code&gt; potential maps, &lt;code&gt;XTC&lt;/code&gt; trajectory files&lt;/li&gt;&#xA;&lt;li&gt;Important number of representation formats and coloring/rendering options&lt;/li&gt;&#xA;&lt;li&gt;VR (Virtual Reality) support (interactive mode), and presented as a &lt;a href=&quot;https://academic.oup.com/glycob/article/25/5/483/1988554&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;video game-based computer graphic software&amp;quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Open-source with a free-to-use licence for academics&lt;/li&gt;&#xA;&lt;li&gt;Available on Windows, MAC and Linux&lt;/li&gt;&#xA;&lt;li&gt;Official website: &lt;a href=&quot;http://www.baaden.ibpc.fr/umol/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.baaden.ibpc.fr/umol/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/87ABB.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/87ABB.jpg&quot; alt=&quot;Screenshot taken from the official website front page&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="1609" LastEditDate="2021-12-06T13:14:30.000" LastActivityDate="2021-12-06T13:14:30.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7063" PostTypeId="2" ParentId="467" CreationDate="2021-11-16T15:37:02.503" Score="13" Body="&lt;h1&gt;&lt;a href=&quot;https://beautiful-atoms.readthedocs.io/en/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;Beautiful Atoms&lt;/a&gt;&lt;/h1&gt;&#xA;&lt;p&gt;Beautiful Atoms is a Python package for editing and rendering atoms and molecules objects using Blender. A Python interface that allows for automating workflows.&lt;/p&gt;&#xA;&lt;p&gt;Features:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Model: space-filling, ball-stick, polyhedral, cavity and so on.&lt;/li&gt;&#xA;&lt;li&gt;Support file: cif, xyz, cube, pdb, json, VASP-out and so on.&lt;/li&gt;&#xA;&lt;li&gt;Support structure from ASE and Pymatgen&lt;/li&gt;&#xA;&lt;li&gt;Volumetric data (Isosurface and 2D slicing)&lt;/li&gt;&#xA;&lt;li&gt;Animation&lt;/li&gt;&#xA;&lt;li&gt;GUI&lt;/li&gt;&#xA;&lt;li&gt;Flexible: Python script, run interactively or in background.&lt;/li&gt;&#xA;&lt;li&gt;High quality rendering: 3D models&lt;/li&gt;&#xA;&lt;li&gt;Free, Open Source: Easy to download and install.&lt;/li&gt;&#xA;&lt;li&gt;Cross-platform: (Linux, Windows, macOS)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here are some nice pictures:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://beautiful-atoms.readthedocs.io/en/latest/gallery.html&quot; rel=&quot;noreferrer&quot;&gt;https://beautiful-atoms.readthedocs.io/en/latest/gallery.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/chXI4.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/chXI4.jpg&quot; alt=&quot;Crystal structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4562" LastActivityDate="2021-11-16T15:37:02.503" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7064" PostTypeId="1" CreationDate="2021-11-16T15:47:12.937" Score="11" ViewCount="372" Body="&lt;p&gt;I &lt;a href=&quot;https://physics.stackexchange.com/q/666029/134583&quot;&gt;asked this on Physics.SE&lt;/a&gt; and got recommended here.&lt;/p&gt;&#xA;&lt;p&gt;More precisely, as a condensed matter theory PhD student, I am often overwhelmed by the wide variety of chemical formulas that experimentalists trot out for their results. I'm thinking about the cuprates, transition metal dichalcogenides, iron pnictides, SrRu with O&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;, O&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;, O&lt;span class=&quot;math-container&quot;&gt;$_7$&lt;/span&gt;, and many more.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="4563" LastEditorUserId="5" LastEditDate="2021-11-18T16:30:54.437" LastActivityDate="2021-11-18T20:01:03.760" Title="How does a beginner condensed matter theorist working on real materials, get up to speed?" Tags="|reference-request|condensed-matter|from-phys-se|dichalcogenides|cuprates|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7065" PostTypeId="1" AcceptedAnswerId="7072" CreationDate="2021-11-16T16:17:22.950" Score="20" ViewCount="4976" Body="&lt;p&gt;I have a general and maybe a little silly / funny question.&lt;/p&gt;&#xA;&lt;p&gt;Why don't most CompChem or QuantumChem software have a GUI? SIESTA is trying with Simune as far as I know, but even proprietary software like GAUSSIAN or VASP is not doing any good.&lt;/p&gt;&#xA;&lt;p&gt;It seems that the development of a GUI for such software is somewhat obvious and would cause an explosion of interest. Essentially, with a good GUI all you would need to do DFT calculations, say as an experimentalist then, would be an understanding of DFT and even a marginal understanding of the parameters. You can then create an * input * file from a series of lists and choices, then run the calculation with a button (a bit like the optimization function in AVOGADRO but with DFT and many more parameters). You can then add a graphical interface for your spectra and a visualization program. You can maybe interface this with the multiple software that are available (sort of like what ASE is doing ?).&lt;/p&gt;&#xA;&lt;p&gt;I'm a bit lost with what I am trying to say. Maybe a sort of MATLAB for matter modelling would be the more appropriate way of defining what I feel is lacking in this space.&lt;/p&gt;&#xA;&lt;p&gt;EDIT on 18/11/2021 : Thank you everyone for these very clear answers !&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="4274" LastEditDate="2021-11-18T20:38:48.100" LastActivityDate="2021-12-03T12:54:31.370" Title="GUIs for Quantum Chemistry... Where are they?" Tags="|software|computational-chemistry|high-performance-computing|graphical-user-interface|matlab|" AnswerCount="10" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="7066" PostTypeId="2" ParentId="6882" CreationDate="2021-11-16T16:33:53.380" Score="4" Body="&lt;p&gt;I believe that after taking into consideration what the comments have pointed out you should also look into the fact that as your geometry has changed somewhat considerably after the optimization. This change in geometry would cause a breaking in the symmetry and thus when the BS is being calculated, as you go through your Brillouin zone you are not going to &amp;quot;see&amp;quot; the same states you saw before. Have you looked into this ? Hope this makes sense.&lt;/p&gt;&#xA;&lt;p&gt;Here is reference on what I am trying to convey:&lt;/p&gt;&#xA;&lt;p&gt;G. Vasseur, et al. Effect of Symmetry Breaking on Electronic Band Structure: Gap Opening at the High Symmetry Points &lt;em&gt;Symmetry&lt;/em&gt; &lt;strong&gt;2013&lt;/strong&gt;, 5(4), 344-354; &lt;a href=&quot;https://doi.org/10.3390/sym5040344&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.3390/sym5040344&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="7" LastEditDate="2021-11-16T17:01:29.447" LastActivityDate="2021-11-16T17:01:29.447" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7068" PostTypeId="2" ParentId="7044" CreationDate="2021-11-16T16:50:39.157" Score="5" Body="&lt;p&gt;I believe both can technically be used. Let me first point out that your calculation must have been long and heavy ! Good luck with those.&#xA;Your fullBZ.WFSX files are used for the COOP bonding analysis you want to do and .bands.WFSX will give you your fat bands which you can use for your wave-functions around the Fermi.&lt;/p&gt;&#xA;&lt;p&gt;Here's a tutorial from SIESTA that might help.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://personales.unican.es/junqueraj/JavierJunquera_files/Metodos/Structuralproperties/Fatbands-SrTiO3/Exercise-Fatbands-SrTiO3.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Exercise Fatbands SrTiO3&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://docs.siesta-project.org/projects/siesta/tutorials/advanced-analysis/coop-cohp/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;COOP-COHP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="24" LastEditDate="2021-11-16T17:48:31.567" LastActivityDate="2021-11-16T17:48:31.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7069" PostTypeId="1" CreationDate="2021-11-16T17:00:06.410" Score="5" ViewCount="684" Body="&lt;p&gt;Basically, I am trying to get the running coordination number (CN), but the result isn't correct? I am multiplying the Radial Distribution Function (RDF) with &lt;code&gt;4*np.pi*x*x*Number_of_Atoms/(A*B*C)&lt;/code&gt; .&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ovito.io import import_file&#xA;from ovito.modifiers import CoordinationAnalysisModifier&#xA;&#xA;cutoff=12.0 &#xA;number_of_bins=200&#xA;&#xA;# Load input data.&#xA;pipeline = import_file(&amp;quot;./traj/BEC/ge7/run10/local_minima.xyz&amp;quot;)&#xA;&#xA;# Print the list of input particle types.&#xA;# They are represented by ParticleType objects attached to the 'Particle Type' particle property.&#xA;for t in pipeline.compute().particles.particle_types.types:&#xA;    print(&amp;quot;Type %i: %s&amp;quot; % (t.id, t.name))&#xA;&#xA;# Calculate partial RDFs:&#xA;pipeline.modifiers.append(CoordinationAnalysisModifier(cutoff=12.0, number_of_bins=200, partial=True))&#xA;&#xA;# Access the output DataTable:&#xA;rdf_table = pipeline.compute().tables['coordination-rdf']&#xA;&#xA;# The y-property of the data points of the DataTable is now a vectorial property.&#xA;# Each vector component represents one partial RDF.&#xA;rdf_names = rdf_table.y.component_names&#xA;&#xA;# The DataTable.xy() method yields everthing as one combined NumPy table.&#xA;# This includes the 'r' values in the first array column, followed by the&#xA;# tabulated g(r) partial functions in the remaining columns. &#xA;&#xA;dr = cutoff/number_of_bins&#xA;x = [x for x in np.arange(0, int(cutoff), dr)]&#xA;&#xA;A = 12.6&#xA;B = 12.6&#xA;C = 13.3&#xA;&#xA;rdf_gege_lst = []&#xA;&#xA;for i in rdf_table.y[:,4]:&#xA;    rdf_gege_lst.append(i)  &#xA;&#xA;cn_GeGe_final = []&#xA;&#xA;cn_GeGe = (np.array(rdf_gege_lst) * 4 * np.pi * x * x * 10) / (A * B * C) &#xA;&#xA;for i in range(len(x)):&#xA;    result_GeGe = integrate.simps(cn_GeGe[:i + 1],x[:i+ 1])&#xA;    cn_GeGe_final.append(result_GeGe)&#xA;&#xA;plt.plot(x, rdf_gege_lst, 'g', label = &amp;quot;Ge-Ge&amp;quot;)&#xA;plt.plot(x, cn_GeGe_final, 'b', label = &amp;quot;Ge-Ge&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="7" LastEditDate="2021-12-07T01:17:45.970" LastActivityDate="2021-12-07T01:17:45.970" Title="How to get the coordination number from RDF in python ovito?" Tags="|molecular-dynamics|python|radial-distribution-function|coordination|ovito|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-20T23:46:21.513" ContentLicense="CC BY-SA 4.0" />
  <row Id="7070" PostTypeId="2" ParentId="7022" CreationDate="2021-11-16T17:17:19.643" Score="8" Body="&lt;p&gt;It is possible to approximate the cell parameters by determining the convex hull of the molecule and then computing the smallest parallelepiped that encloses it. This will automatically give the dimensions together with the vertices of the parallelepiped from which the angles can be computed.&lt;/p&gt;&#xA;&lt;p&gt;This problem was first investigated by &lt;a href=&quot;https://hal.inria.fr/inria-00071901/document&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vivien and Wicker (2002)&lt;/a&gt;&lt;sup&gt;1&lt;/sup&gt;, and their quickest algorithm runs in &lt;span class=&quot;math-container&quot;&gt;$\mathcal O(n\log n+v^2)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the number of atoms and &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; is the number of vertices of the convex hull. The pseudocode on page 13 revolves around the idea of building faces from normal vectors and iteratively minimising the volume.&lt;/p&gt;&#xA;&lt;p&gt;The C++ code is available to download as a tar file &lt;a href=&quot;http://perso.ens-lyon.fr/frederic.vivien/Logiciels/parallelepiped.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (click on the &lt;code&gt;parallelepiped&lt;/code&gt; link instead of &lt;code&gt;Download&lt;/code&gt; as the latter doesn't work).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sub&gt; Reference &lt;/sub&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sub&gt; [1a] Vivien, F., Wicker, N. (2002). Minimal enclosing parallelepiped in 3D. [Research Report] RR-4685, LIP RR-2002-49, INRIA, LIP. inria-00071901. &lt;/sub&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sub&gt; [1b] Vivien, F., Wicker, N. &lt;em&gt;Minimal enclosing parallelepiped in 3D&lt;/em&gt; in &lt;em&gt;Comput. Geom.&lt;/em&gt; &lt;strong&gt;2004&lt;/strong&gt;, &lt;em&gt;29&lt;/em&gt;, 177–190; &lt;a href=&quot;https://doi.org/10.1016/j.comgeo.2004.01.009&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi 10.1016/j.comgeo.2004.01.009&lt;/a&gt;, the &lt;a href=&quot;http://perso.ens-lyon.fr/frederic.vivien/Publications/ComGeo-Parallelepiped.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;author's copy&lt;/a&gt;.&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="35" LastEditorUserId="1206" LastEditDate="2021-11-17T08:48:50.980" LastActivityDate="2021-11-17T08:48:50.980" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7071" PostTypeId="1" CreationDate="2021-11-16T17:24:14.113" Score="7" ViewCount="88" Body="&lt;p&gt;I'm trying to setup a Multi State Transition Interface Sampling (MSTIS) simulation to study the ligand binding of my enzyme using OPS and GROMACS. My enzyme acts on small sugar chains and I would like to simulate which sugar unit it bound most often (roughly depicted in the picture below). I tried to run a Transition Path Sampling (TPS) simulation, but so far I was not able to obtain a decorrelated path:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9y2Xa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9y2Xa.png&quot; alt=&quot;Path tree for my TPS simulation from bound to unbound&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;According to my understanding so far, TIS might work better here since I think that this transition has a quite small probability. And if I include the other bound states as well, I'm hoping to get a good correlation between the transition frequencies here and those I observe in the lab.&lt;/p&gt;&#xA;&lt;p&gt;I docked my substrate in two ways, once with the second (AaAA) and once with the third (AAaA) sugar unit (short A) bound to the active site (the sugar at the active site is indicated by a lower case a). Using gromacs, I created an initial trajectory for both pulling them away from the active site.&lt;/p&gt;&#xA;&lt;p&gt;I load these trajectories as described by dwhswenson &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6967/import-an-initial-trajectory-into-ops-without-openmm&quot;&gt;here&lt;/a&gt;. As the collective variables (CVs), I chose the distance of one atom in the corresponding sugar unit to the metal ion in my active center (dist_AAaA &amp;amp; dist_AaAA).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HXc9R.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HXc9R.png&quot; alt=&quot;Overview of my system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Below a distance of 0.25, I consider the ligand to be bound, while with a distance greater than 1.5 (for both distances), I consider the ligand to be unbound. Since the distance is almost never smaller than 0.2 and the two distances influence each other, the two states (bound_AAaA &amp;amp; bound_AaAA) are quite small in the plot shown above. The dotted lines should indicate the interfaces.&lt;/p&gt;&#xA;&lt;p&gt;So far, my code looks like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import openpathsampling as paths&#xA;from openpathsampling.engines import gromacs as ops_gmx&#xA;&#xA;import mdtraj as md&#xA;import numpy as np&#xA;&#xA;# define the options for the MD simulation&#xA;options = {&#xA;    'gmx_executable': 'gmx -nobackup ',&#xA;    'snapshot_timestep': 0.02,&#xA;    'n_frames_max': 200,&#xA;    'grompp_args': '-n index.ndx',&#xA;    'mdrun_args': '-nb gpu -nt 6'&#xA;}&#xA;&#xA;# define the file names&#xA;trr_file_AAaA = &amp;quot;md_pull_AAaA_1st.trr&amp;quot;&#xA;trr_file_AaAA = &amp;quot;md_pull_AaAA_1st.trr&amp;quot;&#xA;pdb_file = &amp;quot;npt_AAaA_conf2.pdb&amp;quot;&#xA;top_file = &amp;quot;topol_AAaA+AaAA.top&amp;quot;&#xA;&#xA;# setup the engine&#xA;TIS_engine = ops_gmx.Engine(gro=pdb_file,&#xA;                             mdp=&amp;quot;TPS.mdp&amp;quot;,&#xA;                             top=top_file,&#xA;                             options=options,&#xA;                             base_dir=&amp;quot;.&amp;quot;,&#xA;                             prefix=&amp;quot;TIS&amp;quot;).named(&amp;quot;TIS_engine&amp;quot;)&#xA;&#xA;engine_setup = TIS_engine.current_snapshot&#xA;&#xA;# define the CVs for all 3 states&#xA;dist_AAaA = paths.MDTrajFunctionCV(&#xA;    &amp;quot;dist_AAaA&amp;quot;, md.compute_distances, engine_setup.topology, &#xA;    atom_pairs=[[3136,3180]], periodic=False)&#xA;&#xA;dist_AaAA = paths.MDTrajFunctionCV(&#xA;    &amp;quot;dist_AaAA&amp;quot;, md.compute_distances, engine_setup.topology, &#xA;    atom_pairs=[[3136,3207]], periodic=False)&#xA;&#xA;dist_unbound = paths.MDTrajFunctionCV(&#xA;    &amp;quot;dist_unbound&amp;quot;, md.compute_distances, engine_setup.topology, &#xA;    atom_pairs=[[3136,3192]], periodic=False)&#xA;&#xA;# define the states&#xA;bound_AAaA = (paths.CVDefinedVolume(&#xA;    dist_AAaA, 0, 0.25)).named(&amp;quot;bound_AAaA&amp;quot;)&#xA;bound_AaAA = (paths.CVDefinedVolume(&#xA;    dist_AaAA, 0, 0.25)).named(&amp;quot;bound_AaAA&amp;quot;)&#xA;unbound = (paths.CVDefinedVolume(&#xA;    dist_unbound, 1.5, 2)).named(&amp;quot;unbound&amp;quot;)&#xA;&#xA;# define the interfaces&#xA;bound_AAaA_interface = paths.VolumeInterfaceSet(&#xA;    dist_AAaA, 0, [0.25, 0.35, 0.45, 0.55])&#xA;bound_AaAA_interface = paths.VolumeInterfaceSet(&#xA;    dist_AaAA, 0, [0.25, 0.35, 0.45, 0.55])&#xA;unbound_interface = paths.VolumeInterfaceSet(&#xA;    dist_unbound, 2, [1.5, 1.3, 1.1, 0.9, 0.8, 0.7, 0.6])&#xA;&#xA;# import the two inital trajectories&#xA;# calculate the number of frames in both input trajectories&#xA;n_frames_AAaA = len(md.load(trr_file_AAaA, top=pdb_file))&#xA;n_frames_AaAA = len(md.load(trr_file_AaAA, top=pdb_file))&#xA;# external_traj uses externally-stored snapshots&#xA;init_traj_AAaA = paths.Trajectory(&#xA;    [TIS_engine.read_frame_from_file(trr_file_AAaA, num)&#xA;     for num in range(n_frames_AAaA)])&#xA;init_traj_AaAA = paths.Trajectory(&#xA;    [TIS_engine.read_frame_from_file(trr_file_AaAA, num)&#xA;     for num in range(n_frames_AaAA)])&#xA;&#xA;# create two networks to obtain the initial trajectories&#xA;tps_network_for_init_traj_AAaA = paths.TPSNetwork.from_states_all_to_all(&#xA;    [bound_AAaA, unbound])&#xA;tps_network_for_init_traj_AaAA = paths.TPSNetwork.from_states_all_to_all(&#xA;    [bound_AaAA, unbound])&#xA;&#xA;# take the subtrajectories matching the ensemble &#xA;subtrajectories = []&#xA;for ens in tps_network_for_init_traj_AAaA.analysis_ensembles:&#xA;    subtrajectories += ens.split(init_traj_AAaA)&#xA;&#xA;for ens in tps_network_for_init_traj_AaAA.analysis_ensembles:&#xA;    subtrajectories += ens.split(init_traj_AaAA)&#xA;&#xA;# create a TIS network for the sampling itself&#xA;mstis_network = paths.MSTISNetwork(&#xA;    [(bound_AAaA, bound_AAaA_interface),&#xA;     (bound_AaAA, bound_AaAA_interface),&#xA;     (unbound, unbound_interface)])&#xA;&#xA;# define a move scheme for the TIS simulation&#xA;scheme = paths.OneWayShootingMoveScheme(mstis_network, &#xA;                                        selector=paths.UniformSelector(),&#xA;                                        engine=TIS_engine)&#xA;&#xA;# make subtrajectories into initial conditions (trajectories become a sampleset)&#xA;initial_conditions = scheme.initial_conditions_from_trajectories(subtrajectories)&#xA;&#xA;# check that initial conditions are valid and complete&#xA;# (raise AssertionError otherwise)&#xA;scheme.assert_initial_conditions(initial_conditions)&#xA;&#xA;# setup the sampler&#xA;sampler = paths.PathSampling(&#xA;    storage=paths.Storage(&amp;quot;AAaA_AaAA_TIS.nc&amp;quot;, &amp;quot;w&amp;quot;, engine_setup),&#xA;    move_scheme=scheme, sample_set=initial_conditions)&#xA;&#xA;# sampler.run_until_decorrelated()&#xA;# run only 100 simulations for testing purposes&#xA;sampler.run(100)&#xA;&#xA;sampler.storage.close()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The code runs without any error, but I'm not sure if the setup is correct since my resulting path tree looks like this:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/1kA1b.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1kA1b.png&quot; alt=&quot;TIS tree from my first TIS simulation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you may have noticed, I didn't setup the unbound state as described above since a certain CV is needed for the interface setup (&lt;code&gt;unbound_interface = paths.VolumeInterfaceSet(CV,...)&lt;/code&gt;). Here I used the distance to another atom in the center of my ligand.&#xA;I get how you would setup the unbound state depending on the two distances with&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;unbound = (paths.CVDefinedVolume(dist_AAaA, 1.5, 2) &amp;amp;&#xA;           paths.CVDefinedVolume(dist_AaAA, 1.5, 2)).named(&amp;quot;unbound&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but I don't know how to incorporate that into the interface setup.&#xA;Preferably I would like to not use an unbound state at all since (at least from my understanding) it's not a stable state and I'm mainly interested in the transition towards to two bound states crossing the outer interface first and finally ending in the stable bound state. But I'm not sure if you could set it up like this. Maybe someone could comment on this.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, I'm not sure if the rest of the setup is correct. I did not define an &lt;code&gt;ms_outers&lt;/code&gt; for the &lt;code&gt;paths.MSTISNetwork&lt;/code&gt; as I'm not sure what this would be in my case or how to correctly define it. Maybe this could be used to remove the unbound state?&lt;/p&gt;&#xA;&lt;p&gt;And I would like to specify that I'm only interested in the transitions from the unbound to either of the bound states but not in the transition from one bound state to another bound state. So something similar to this:&#xA;&lt;code&gt;tps_network = paths.TPSNetwork([unbound, bound_AAaA],[unbound, bound_AaAA])&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I hope to get some help on these main issues, but if you have any comment regarding this setup or a link to a related paper this would be highly appreciated as well.&lt;/p&gt;&#xA;" OwnerUserId="4480" LastEditorUserId="7" LastEditDate="2021-11-16T19:06:28.600" LastActivityDate="2021-11-17T17:21:51.577" Title="How do I setup my MSTIS simulation correctly?" Tags="|molecular-dynamics|gromacs|openpathsampling|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7072" PostTypeId="2" ParentId="7065" CreationDate="2021-11-16T19:58:58.850" Score="16" Body="&lt;p&gt;Gaussian has &lt;a href=&quot;https://gaussian.com/gaussview6/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussview&lt;/a&gt;, QChem has &lt;a href=&quot;http://iqmol.org/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;IQMol&lt;/a&gt;, Schrodinger has &lt;a href=&quot;https://www.schrodinger.com/products/maestro&quot; rel=&quot;nofollow noreferrer&quot;&gt;Maestro&lt;/a&gt;, &lt;a href=&quot;https://www.synopsys.com/silicon/quantumatk/atomistic-simulation-products.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum ATK&lt;/a&gt; and &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BIOVIA Material Studio&lt;/a&gt; each have their own GUI. Notice, that both the program and GUI in these cases are paid products (except IQMol). There are also paid GUIs that work for several different programs, such as the &lt;a href=&quot;https://www.scm.com/amsterdam-modeling-suite/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Amsterdam Modeling Suite&lt;/a&gt; and &lt;a href=&quot;https://www.chemcraftprog.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemcraft&lt;/a&gt;. This hints at part of the problem: for developers in academia/industry, time spent on a GUI is time spent not doing other research or developing their core software. This leads to developers charging for their GUIs, only incrementally developing them, or just not making one at all.&lt;/p&gt;&#xA;&lt;p&gt;However there are also a number of free GUI, both for setting up and actually running calculations. To give just a few examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.21600&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gabedit&lt;/a&gt;- allows you build molecules, make/run input files for several different electronic structure programs, and view results from output.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro&lt;/a&gt; and &lt;a href=&quot;https://github.com/OpenChemistry/avogadroapp&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro2&lt;/a&gt;- builds molecules, makes input files, and views results.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://sourceforge.net/projects/mocalc2012/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MoCalc2012&lt;/a&gt;- interface to Avogadro/JSmol to make molecules, can make/run input files for several different electronic structure programs.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.webmo.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;WebMO&lt;/a&gt;- build molecules, make/run input, view results.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Some of these are supported by donations, some have tiers where only the basic program is free, and some have ceased development altogether. While there are a number of programs that can build/visualize molecules, it can challenging to make a program that goes from build-&amp;gt;input-&amp;gt;results because of the variety of programs that one could potentially have to support for the latter two steps, not to mention possible licensing issues with interfacing to these external programs.&lt;/p&gt;&#xA;&lt;p&gt;The takeaways from all this are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;There &lt;em&gt;are&lt;/em&gt; a wide variety of GUI programs, both free and proprietary, available for various stages of setting-up/post-processing a calculation. Some even work end to end.&lt;/li&gt;&#xA;&lt;li&gt;It might be more challenging than you would think to make a general purpose GUI for even just Quantum Chemistry simulations, let alone the various other types of Computational Matter Modeling (Molecular Dynamics, Docking, Cheminformatics, Material Design, etc).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-11-19T00:40:18.527" LastActivityDate="2021-11-19T00:40:18.527" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7073" PostTypeId="2" ParentId="7065" CreationDate="2021-11-16T20:18:19.437" Score="17" Body="&lt;p&gt;My answer to &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/5010/5&quot;&gt;GUI for DFT calculations&lt;/a&gt;&amp;quot; is a good introduction to my stance on this issue, but I will address your more specific questions here. First for some preliminaries:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Software development is expensive (whether monetarily, to hire developers, or temporally, in terms of the time and energy that goes into it). Almost all of computational chemistry and quantum chemistry is developed and used in academia, where money and time are scarce. There's companies that are in the business, but I imagine that it's hard for them to make a profit when the field is already &lt;em&gt;dominated&lt;/em&gt; by people in academia who make open-source and free software involving lots of hard work and labor for very little financial return.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In both the question and the first (and only) comment so far, Gaussian and VASP are the two poster cases mentioned. Both of them are expensive and have &amp;quot;unusual&amp;quot; business practices which suggest that they're not doing extremely well financially, or need to resort to extreme tactics in order to do so: (1) Gaussian bans anyone who compares its performance to other programs, often along with their institutions, and kicked out its founder, Nobel Prize winner John Pople; (2) VASP doesn't allow anyone to use their online forum unless they have paid for the expensive license. I don't know as much about VASP, but Gaussian is &lt;em&gt;&lt;strong&gt;far&lt;/strong&gt;&lt;/em&gt; from state-of-the-art for what it does. It is &lt;em&gt;&lt;strong&gt;one of the slowest&lt;/strong&gt;&lt;/em&gt; electronic structure programs, and can't do things like CCSDT which is available in free software like CFOUR, MRCC, NWChem, etc., cannot do (in the publicly purchasable version) the 1- and 2-electron integrals for basis sets containing L-type orbitals and beyond, whereas OpenMolcas, MRCC, Psi4, etc. can treat L-type, and often even more types of orbitals. Gaussian also can't do more modern electronic structure techniques like FCIQMC, DMRG, SCHI, etc., which are all things that have been incorporated into open-source packages like OpenMOLCAS and/or PySCF. As with almost everything in academia, quantum chemistry is constantly evolving, which makes it very hard to develop and maintain GUIs.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It seems that the development of a GUI for such software is somewhat obvious and would cause an explosion of interest.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I am not convinced that there would be an &amp;quot;explosion of interest&amp;quot;. Enrollment in chemistry and physics has decreased in recent years, while interest in computer science, economics and even psychology has increased. I don't think any of us have thousands of students knocking on our doors asking to work on computational chemistry projects, and I'm certain that introducing GUIs will not change that. Maybe some experimentalists would like to see a GUI, but evidently there hasn't been a big enough demand for anything beyond things like GaussView, otherwise like most things in academia, where there is a demand there is a supply (from people who wouldn't mind having their citation count &amp;quot;explode&amp;quot;).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;You can then add a graphical interface for your spectra and a visualization program.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The word &amp;quot;spectra&amp;quot; can mean a &lt;em&gt;&lt;strong&gt;lot&lt;/strong&gt;&lt;/em&gt; of different things, but the spectroscopy software PGOPHER does have a GUI that allows you to visualize spectra, and while it does have a lot of users in the small-molecule spectroscopy community, that community is relatively small compared to some other areas which interest computational chemists. Honestly, despite going to a PGOPHER workshop, I never quite figured out how to use PGOPHER the way I did the command-line electronic structure theory programs (maybe because I had someone show me one-on-one how to use MOLPRO at the beginning, which I didn't have for PGOPHER, or maybe because I never read the PGOPHER manual as thoroughly as I did the manuals for other small-molecular spectroscopy programs like DParFit, DPotFIT, BetaFit, LEVEL, RKR, etc., but largely because I found all the buttons on the GUI quite overwhelming!).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot; Maybe a sort of MATLAB for matter modelling would be the more appropriate way of defining what I feel is lacking in this space.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I absolutely &lt;em&gt;&lt;strong&gt;love&lt;/strong&gt;&lt;/em&gt; that you said that, for so many reasons! MATLAB is my favorite software for general numerical computing, and &lt;a href=&quot;https://mattermodeling.stackexchange.com/search?q=matlab&quot;&gt;I've mentioned it a lot here&lt;/a&gt;. The first electronic structure software that I used heavily was MOLPRO, and I often called it the &amp;quot;MATLAB of quantum chemistry&amp;quot;, although it doesn't have a GUI. The GUI is not the main feature of MATLAB either (the comparison was more for it's speed, convenience, and of course, price, among other things). There's a couple things for me to say regarding MATLAB, GUIs, and computational chemistry:&lt;/p&gt;&#xA;&lt;p&gt;MATLAB's &lt;em&gt;primary&lt;/em&gt; strength is in doing fast calculations from the command line, &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; in its GUIs. I can't talk about every single GUI that MATLAB has, but I'll mention the three main ones I've used (which I do like, don't get me wrong about that!):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The curve fitting toolbox GUI. This is so convenient for fitting data, especially compared to only using the command line, because it's so important to see how well the fit actually matches the shape of the curve (a single RMSD value without any visual information is not enough!) but when you use it, I'm sure you often find yourself frustrated with its lack of options to grab the &amp;quot;hidden&amp;quot; data, and you might find yourself needing to &lt;em&gt;combine&lt;/em&gt; the use of this GUI with the actual command window.&lt;/li&gt;&#xA;&lt;li&gt;The command window and editor. These are extremely slow, which you can see by opening MATLAB as a GUI vs opening the command-line version. Especially on a compute server (which is pretty much ubiquitous in computational chemistry), you don't want to be using a GUI (see my answer to &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6876/5&quot;&gt;How can I use a GUI on a supercomputer?&lt;/a&gt;&amp;quot;). The editor is just an editor, like VIM or emacs, but I do admit that it's extremely useful for debugging MATLAB code. Unfortunately even MATLAB's debugger is nothing compared to an EDI like Dr. Java or Eclipse, and you probably don't need me to explain why making a full-fledged GUI debugger for GAUSSIAN, VASP, or any other matter modeling software is not high on the priority list.&lt;/li&gt;&#xA;&lt;li&gt;MATLAB's GUI for making figures. This is where I think MATLAB really wins against its competitors like numpy, Mathematica, Sage, etc. However, it does have its flaws and glitches, and on top of that, I always use it &lt;em&gt;in combination&lt;/em&gt; with the command window. Based on the quality of MATLAB's GUI for making figures, despite its decades of development and multiple billions of dollars of total revenue, you can imagine that it won't be easy for a matter modeling researcher (or company) to make a great GUI for making publication-quality figures. It's inconvenient, but I just copy my data from the matter modeling software, into MATLAB to make my figures, as I explained in my answer to this question which I already mentioned here: &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6876/5&quot;&gt;How can I use a GUI on a supercomputer?&lt;/a&gt;&amp;quot;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-16T23:46:40.190" LastActivityDate="2021-11-16T23:46:40.190" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="7074" PostTypeId="5" CreationDate="2021-11-16T20:23:08.003" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-16T20:23:08.003" LastActivityDate="2021-11-16T20:23:08.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7075" PostTypeId="4" CreationDate="2021-11-16T20:23:08.003" Score="0" Body="Questions about or involving MATLAB (will be populated when bumping up questions becomes less of an issue, i.e. when our unanswered queue is smaller)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-16T20:23:08.003" LastActivityDate="2021-11-16T20:23:08.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7076" PostTypeId="2" ParentId="7061" CreationDate="2021-11-17T00:17:55.840" Score="9" Body="&lt;p&gt;The autocorrelation time comes from the statistical analysis of ergodic systems, where one is interested in obtaining statistical averages of an observable &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; by drawing samples from a distribution in a time-dependent manner, i.e.:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left&amp;lt;{A}\right&amp;gt;\approx \bar{A}\equiv \frac{1}{N}\sum_{i=1}^N A_i \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the total number of samples, &lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt;{A}\right&amp;gt;$&lt;/span&gt; is the &lt;em&gt;true&lt;/em&gt; expectation value/ensemble average and &lt;span class=&quot;math-container&quot;&gt;$\bar{A}$&lt;/span&gt; is the &lt;em&gt;estimated&lt;/em&gt; ensemble average.&lt;/p&gt;&#xA;&lt;p&gt;Usually, one is interested in the convergence of this calculation, or more specifically, the variance of the estimate &lt;span class=&quot;math-container&quot;&gt;$\bar{A}$&lt;/span&gt;. This is well-known to be (e.g. Eq. 15 &lt;a href=&quot;https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.459.56&amp;amp;rep=rep1&amp;amp;type=pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; or &lt;a href=&quot;https://dfm.io/posts/autocorr/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{aligned}&#xA;Var[\bar{A}] &amp;amp;= \left&amp;lt;\bar{A}^2\right&amp;gt; - \left&amp;lt;\bar{A}\right&amp;gt;^2 \\&#xA;&amp;amp;= \left&amp;lt;\Bigg(\frac{1}{N}\sum_{i=1}^N A_i\Bigg)^2\right&amp;gt; - \left&amp;lt;\frac{1}{N}\sum_{i=1}^N A_i\right&amp;gt;^2\\&#xA;&amp;amp;=\frac{1}{N^2}\sum_{i=1}^{N}\sum_{j=1}^{N}A_iA_j - \Bigg(\frac{1}{N}\sum_{i=1}^{N}A_i\Bigg)\Bigg(\frac{1}{N}\sum_{j=1}^{N}A_j\Bigg) \\&#xA;&amp;amp;= \frac{1}{N}Var[A_i] + \frac{2}{N}\sum_{t=1}^N Cov[A_i,A_{i+t}]&#xA;\end{aligned}\tag{2} &#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we define the quantity &lt;span class=&quot;math-container&quot;&gt;$\frac{Cov[A_i,A_{i+t}]}{Var[A_i]}$&lt;/span&gt; to be the discrete time-normalised autocorrelation function &lt;span class=&quot;math-container&quot;&gt;$\Gamma(t)$&lt;/span&gt;, we obtain:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$Var[\bar{A}]=\frac{1}{N}Var[A_i]\Bigg(1 + 2\sum_{t=1}^N \Gamma(t)\Bigg) \tag{3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Defining the relative autocorrelation time to be &lt;span class=&quot;math-container&quot;&gt;$\tau = 1 + 2\sum_{t=1}^N \Gamma(t)$&lt;/span&gt;, we see that when &lt;span class=&quot;math-container&quot;&gt;$\tau=1$&lt;/span&gt;, the variance of the estimator reduces to the variance of the mean, as expected. Note that &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is dimensionless and is relative to the sampling time, so there is no contradiction if you obtain &lt;span class=&quot;math-container&quot;&gt;$\tau \approx 1$&lt;/span&gt; at different time intervals. This just means that your samples are effectively decorrelated at both timescales. On the other hand, larger &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; means that &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{N}Var[A_i]$&lt;/span&gt; underestimates &lt;span class=&quot;math-container&quot;&gt;$Var[\bar{A}]$&lt;/span&gt;, so if you ignore this correlation, you will systematically be underestimating the true variance of the mean.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Another way to look at this is by defining an effective sample size &lt;span class=&quot;math-container&quot;&gt;$N_{eff}=N/\tau$&lt;/span&gt;. This is basically the &amp;quot;real&amp;quot; number of samples you have which you can use to estimate the variance of the mean using the usual approach. And if you have &lt;span class=&quot;math-container&quot;&gt;$N_{eff}$&lt;/span&gt; real samples after &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; steps, that means that you only create a new effective sample every &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; steps on average.&lt;/p&gt;&#xA;" OwnerUserId="710" LastEditorUserId="710" LastEditDate="2021-11-17T00:44:14.483" LastActivityDate="2021-11-17T00:44:14.483" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7077" PostTypeId="2" ParentId="7064" CreationDate="2021-11-17T00:25:55.647" Score="9" Body="&lt;p&gt;Welcome to the club of academic migrants! I didn't take any university-level chemistry courses during my undergrad years (except a special topics course for graduate students called &amp;quot;bioelectronics&amp;quot; which one might say was more physics and biology than chemistry). I was much more interested in physics and biology (and math) than chemistry, so I pursued a double major and double minor with my majors being &amp;quot;BMath in Applied Math&amp;quot; and &amp;quot;BSc in Honours Science&amp;quot;, with the minors being in Physics and Biology.&lt;/p&gt;&#xA;&lt;p&gt;However, my PhD ended up being granted from a chemistry department, and in recent years I probably worked more in quantum chemistry than in any other field. I know exactly how it feels.&lt;/p&gt;&#xA;&lt;p&gt;It might seem hypocritical for me to say this, because I personally didn't do this, but hindsight is 2020 (or in my case,&#xA;maybe even 1970 since my early lack of interest in chemistry might even trace back to my family always talking about physics, math and biology but rarely chemistry). It sounds like you're a relatively new PhD student and will have to take graduate-level courses anyway, so I hope my advice (based on what I'd probably do if I could turn back time) will be useful for your academic career: I'd recommend &lt;strong&gt;taking the following chemistry courses&lt;/strong&gt; if available: inorganic chemistry, transition metal chemistry, heavy-metal chemistry (involving lanthanides and actinides), solid-state chemistry. The following topics might also be of interest: quantum chemistry, computational chemistry (lab), main group chemistry.&lt;/p&gt;&#xA;&lt;p&gt;For quite some time, I've wanted to audit some of those courses, but I can't do it during COVID and during an extremely busy teaching term. If you were to ask for my advice (considering that my background is similar to yours, as well as my career trajectory, except that I was in your shoes many years ago), I would say to take those courses as early as possible! A lot of (or almost all of?) applied materials physics is chemistry.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-18T19:59:42.130" LastActivityDate="2021-11-18T19:59:42.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7079" PostTypeId="1" CreationDate="2021-11-17T03:44:00.397" Score="6" ViewCount="549" Body="&lt;p&gt;I am testing Quantum ESPRESSO with different values for &lt;code&gt;Npool&lt;/code&gt; and &lt;code&gt;bands&lt;/code&gt; in order to calculate run time.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pools: each image can be subpartitioned into &amp;quot;pools&amp;quot;, each taking care of a group of k-points.&#xA;bands: each pool is subpartitioned into &amp;quot;band groups&amp;quot;, each taking care of a group of Kohn-Sham orbitals (also called bands, or wavefunctions). Especially useful for calculations with hybrid functionals.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I took a simple 32-atom supercell of aluminum. Here is the input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation='scf'&#xA;    restart_mode='from_scratch',&#xA;    pseudo_dir = '.'&#xA;    outdir=./tmp/,&#xA;    prefix='al'&#xA;    tprnfor = .true.&#xA;    tstress = .true.&#xA;    disk_io='none'&#xA; /&#xA; &amp;amp;system&#xA;    ibrav=  0, A=4.05, nat=  32, ntyp= 1, ecutwfc =60.0,&#xA;    occupations='smearing', smearing='marzari-vanderbilt', degauss=0.05&#xA; /&#xA; &amp;amp;electrons&#xA;    diagonalization='david'&#xA;    mixing_beta = 0.7&#xA; /&#xA;CELL_PARAMETERS alat&#xA;2 0 0&#xA;0 2 0&#xA;0 0 2&#xA;&#xA;ATOMIC_SPECIES&#xA; Al  26.98 Al.pbe-n-kjpaw_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS crystal&#xA;      Al 0.00000000        0.00000000        0.00000000&#xA;      Al 0.25000000        0.25000000        0.00000000&#xA;      Al 0.25000000        0.00000000        0.25000000&#xA;      Al 0.00000000        0.25000000        0.25000000&#xA;      Al 0.50000000        0.00000000        0.00000000&#xA;      Al 0.75000000        0.25000000        0.00000000&#xA;      Al 0.75000000        0.00000000        0.25000000&#xA;      Al 0.50000000        0.25000000        0.25000000&#xA;      Al 0.00000000        0.50000000        0.00000000&#xA;      Al 0.25000000        0.75000000        0.00000000&#xA;      Al 0.25000000        0.50000000        0.25000000&#xA;      Al 0.00000000        0.75000000        0.25000000&#xA;      Al 0.50000000        0.50000000        0.00000000&#xA;      Al 0.75000000        0.75000000        0.00000000&#xA;      Al 0.75000000        0.50000000        0.25000000&#xA;      Al 0.50000000        0.75000000        0.25000000&#xA;      Al 0.00000000        0.00000000        0.50000000&#xA;      Al 0.25000000        0.25000000        0.50000000&#xA;      Al 0.25000000        0.00000000        0.75000000&#xA;      Al 0.00000000        0.25000000        0.75000000&#xA;      Al 0.50000000        0.00000000        0.50000000&#xA;      Al 0.75000000        0.25000000        0.50000000&#xA;      Al 0.75000000        0.00000000        0.75000000&#xA;      Al 0.50000000        0.25000000        0.75000000&#xA;      Al 0.00000000        0.50000000        0.50000000&#xA;      Al 0.25000000        0.75000000        0.50000000&#xA;      Al 0.25000000        0.50000000        0.75000000&#xA;      Al 0.00000000        0.75000000        0.75000000&#xA;      Al 0.50000000        0.50000000        0.50000000&#xA;      Al 0.75000000        0.75000000        0.50000000&#xA;      Al 0.75000000        0.50000000        0.75000000&#xA;      Al 0.50000000        0.75000000        0.75000000&#xA;K_POINTS automatic&#xA;11 11 11  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, I am running on single node with 48 processor with different number of &lt;code&gt;nk&lt;/code&gt;and &lt;code&gt;nb&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example :&lt;br /&gt;&#xA;&lt;code&gt;mpiexec.hydra -np 48 /USERS/pranav/compilation/q-e-qe-6.8/bin/pw.x -in al.scf.david.in -nk 3 -nb 4&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;In First study, I varied &lt;code&gt;nk&lt;/code&gt; while fixed &lt;code&gt;nb&lt;/code&gt;=1. Here is the result&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nk nb time(sec) &#xA;1 1 206&#xA;2 1 163&#xA;3 1 144&#xA;4 1 138&#xA;6 1 138&#xA;8 1 131&#xA;12 1 141&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In second run, I fixed &lt;code&gt;nk&lt;/code&gt; at 3 and varied &lt;code&gt;nb&lt;/code&gt; and&#xA;Here is the result&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nk nb time(sec) &#xA;3  1 144&#xA;3  2 181&#xA;3  4 255&#xA;3  8 426&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why is run-time increasing with increase in &lt;code&gt;nb&lt;/code&gt; in second run? I was hoping for decreasing in trend.&lt;/p&gt;&#xA;&lt;p&gt;&lt;br /&gt;&#xA;&lt;strong&gt;Note: QE v6. 8 is compiled with intel-oneapi and internal FFT library&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2021-11-18T00:25:55.627" LastActivityDate="2021-12-13T12:46:14.463" Title="Case study: KPOINT and band parallelization in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|benchmark-timings|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7080" PostTypeId="2" ParentId="7065" CreationDate="2021-11-17T04:04:13.593" Score="8" Body="&lt;p&gt;There are quite a few graphical programs for quantum chemistry programs. The problem is that, as a rule, you need several of them at once. Each small subtask has its own program. There are programs that allow you to visualize structure, 3D data, etc. All kinds of charts are built in specialized programs. Users of not the most common programs have problems. They have to write small scripts or programs on their own to convert their data to formats supported in existing programs.&lt;/p&gt;&#xA;&lt;p&gt;The idea of writing a program that almost automatically creates input files, runs the calculation and displays the results seems to me almost impossible for scientific calculations. In addition to the rapid development of quantum-chemical programs, which will require constant refinement of the function of generating input files, there is also a more serious problem. Quantum chemistry programs are very computationally intensive. They are run on remote clusters. These clusters use task queues. It may so happen that the task will be launched only after a few days. There is no need to talk about any real-time visualization here.&#xA;In addition, the choice of simulation parameters is a scientific task. It cannot be automated.&lt;/p&gt;&#xA;&lt;p&gt;I have been using the SIESTA program for many years. Despite the abundance of scripts (console) for processing the calculation results, I was constantly missing something and I was writing my programs. At some point, a program appeared that I was not ashamed to show to the scientific community, and I posted it on the github (GUI4dft, &lt;a href=&quot;https://github.com/sozykinsa/GUI4dft&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/sozykinsa/GUI4dft&lt;/a&gt;). The program is my attempt to help SIESTA users get rid of the need to combine multiple programs and get away from the console. I really hope this will lower the barriers to entry for new users.&lt;/p&gt;&#xA;" OwnerUserId="4566" LastActivityDate="2021-11-17T04:04:13.593" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7081" PostTypeId="2" ParentId="7065" CreationDate="2021-11-17T05:40:13.323" Score="8" Body="&lt;p&gt;As mentioned by other answers, there are multiple programs already.&lt;/p&gt;&#xA;&lt;p&gt;Certainly what you describe, is why I created Avogadro in the first place. A program that makes it easy to build molecules, materials .. systems, allows you to run multiple programs (which we do for research), read the output, and perform analysis, etc.&lt;/p&gt;&#xA;&lt;p&gt;Avogadro has perhaps been &lt;em&gt;too&lt;/em&gt; successful - it's hard to get momentum to finish v2 because people are still using v1.&lt;/p&gt;&#xA;&lt;p&gt;What we've tried to do with Avogadro 2, is make it easier to edit / update interfaces to computational programs. They're all Python scripts, and available on GitHub: &lt;a href=&quot;https://github.com/openchemistry/avogenerators&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/openchemistry/avogenerators&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There's also code for plotting, generating surfaces.. etc.&lt;/p&gt;&#xA;&lt;p&gt;ASE has done quite a bit towards a &amp;quot;MATLAB for computational chemistry.&amp;quot; It's maybe not ideal for molecular transformations, but I think that's largely because Open Babel and RDKit handle many of those tasks.&lt;/p&gt;&#xA;&lt;p&gt;I agree a lot with &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7072/30&quot;&gt;Tyberius' answer&lt;/a&gt; in that many commercial packages funnel license fees into graphical interfaces. (GaussView isn't actually developed by Gaussian, but that's a different story.)&lt;/p&gt;&#xA;&lt;p&gt;Otherwise, it's a matter of people with time / interest in contributing to open source efforts like Avogadro.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-11-17T05:40:13.323" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7082" PostTypeId="1" AcceptedAnswerId="7092" CreationDate="2021-11-17T05:59:31.913" Score="8" ViewCount="217" Body="&lt;p&gt;The usual verlet integration scheme for propagating molecular dynamics according to Newton's equations of motion looks like the following:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;x(t+\Delta t)=2x(t)-x(t-\Delta t)+a(t)\Delta t^2&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is accurate up to &lt;span class=&quot;math-container&quot;&gt;$O(\Delta t^2)$&lt;/span&gt;. There are, however, higher-order integrators which make a smaller discretization error and depend upon the third time-derivative of &lt;span class=&quot;math-container&quot;&gt;$x(t)$&lt;/span&gt;, the so-called jerk. I am wondering if the use of these higher-order integrators have been used at all, especially for relatively simple potentials where one could presumably calculate the  jerk term easily?&lt;/p&gt;&#xA;&lt;p&gt;Also, how would one actually go about calculating the third derivative of position with respect to time? For instance, in practice we actually calculate &lt;span class=&quot;math-container&quot;&gt;$a(t)=-\nabla V(x(t))/m$&lt;/span&gt;. That is, we calculate the gradient of the potential, taking advantage of Newton's second law. Is there any analogous relationship for the third-derivative of &lt;span class=&quot;math-container&quot;&gt;$x(t)$&lt;/span&gt;? Is it possibly related to the Hessian? Or would we be stuck using some kind of finite-difference scheme to get the third-derivative, which would presumably be very slow and thus invalidate of using a more accurate integrator, hence allowing us to take larger time steps.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="5" LastEditDate="2021-11-17T06:02:51.977" LastActivityDate="2021-11-19T23:15:00.543" Title="Use of higher-order integrators in molecular dynamics?" Tags="|molecular-dynamics|mathematical-modeling|numerical-convergence|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7083" PostTypeId="2" ParentId="7065" CreationDate="2021-11-17T07:44:24.977" Score="5" Body="&lt;p&gt;Another software that comes with a GUI is WIEN2k with its W2web web-interface. This interface is convenient for beginners, which I know because I had a course about wien2k when I had no idea about quantum chemistry.&lt;/p&gt;&#xA;&lt;p&gt;But the professor told me that somewhat experienced users only work from the command line because it is actually much faster once you are accustomed to it. Anyone dabbling in quantum chemistry would hit this bar pretty soon. I imagine it would be the same for all other codes.&lt;/p&gt;&#xA;" OwnerUserId="2084" LastEditorUserId="2084" LastEditDate="2021-12-02T08:53:01.400" LastActivityDate="2021-12-02T08:53:01.400" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7084" PostTypeId="2" ParentId="6876" CreationDate="2021-11-17T07:52:39.787" Score="5" Body="&lt;p&gt;To address your specific question: &lt;strong&gt;No&lt;/strong&gt;, you don't always have to download everything locally. VASP creates a lot of different output files and sometimes (most of the times?) you only need some of those. So you can &lt;strong&gt;delete&lt;/strong&gt; large output files you don't need in your study right after the calculation on the cluster and then download only the necessary files.&lt;/p&gt;&#xA;" OwnerUserId="2084" LastActivityDate="2021-11-17T07:52:39.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7085" PostTypeId="1" AcceptedAnswerId="7086" CreationDate="2021-11-17T08:51:10.340" Score="7" ViewCount="1774" Body="&lt;p&gt;I have been using Gaussian16 por metal complexes SCF single-point calculations involving triplets to investigate phosphorescence. I have actually run into trouble (very long computational time, even with 36 processors and quite a lot of memory) when using the regular SCF convergence criterion as default in the code.&lt;/p&gt;&#xA;&lt;p&gt;As a result from that, I thought of using the QC keyword, which made the calculations much faster and successfully converged. However, I am not sure if there is evidence on the effect of such an approximation or the lack of accuracy that might be obtained.&lt;/p&gt;&#xA;&lt;p&gt;I have also thought of using XQC keyword, which would make me able to run regular SCF procedure up to a number of cycles and then switch to QC.&lt;/p&gt;&#xA;&lt;p&gt;How safe am I when using QC? Am I losing a lot of accuracy, in general, when compared to the regular SCF procedure?&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2021-11-18T00:17:33.310" Title="Does QC convergence mode in Gaussian make a difference?" Tags="|gaussian|convergence-test|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7086" PostTypeId="2" ParentId="7085" CreationDate="2021-11-17T13:18:15.097" Score="5" Body="&lt;p&gt;The &lt;strong&gt;SCF=QC&lt;/strong&gt; keyword in Gaussian actually pertains to the choice of algorithm on how find the solution in the SCF procedure while &lt;strong&gt;SCF=Tight&lt;/strong&gt; is an option related to SCF cycle convergence. Gaussian SCF criterion depends on density matrix changes, consequently in energy.&lt;/p&gt;&#xA;&lt;p&gt;So using QC algorithm should not cost accuracy if the convergence criterion is the same.&lt;/p&gt;&#xA;&lt;p&gt;If you refer to Gaussian website, you will see &lt;strong&gt;SCF=TightLinEq&lt;/strong&gt;. They described this option as having 'tight' convergence throughout QC algorithm which I think makes this a safe choice.&lt;/p&gt;&#xA;&lt;p&gt;I am also sharing the link to &lt;a href=&quot;https://gaussian.com/scf/&quot; rel=&quot;noreferrer&quot;&gt;Gaussian SCF&lt;/a&gt; page for future reference.&lt;/p&gt;&#xA;" OwnerUserId="4558" LastEditorUserId="4558" LastEditDate="2021-11-17T13:24:05.957" LastActivityDate="2021-11-17T13:24:05.957" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7087" PostTypeId="1" AcceptedAnswerId="7095" CreationDate="2021-11-17T14:54:08.223" Score="9" ViewCount="955" Body="&lt;p&gt;I am trying to calculate the dipole moment of an excited state, using &amp;quot;Gaussian&amp;quot; software. My input commands were:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;opt freq td=(singlets,nstates=5,root=1) cam-b3lyp/6-31g(d) geom=connectivity&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;as I wanted to optimize the geometry of &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; state (starting from optimized &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; structure) and calculate the &lt;span class=&quot;math-container&quot;&gt;$S_1$&lt;/span&gt; dipole moment of the optimized structure. I am wondering, is this is the correct way to do the excited state dipole moment calculation? Moreover, is the Dipole moment in an output after the last &amp;quot;Population analysis using the SCF Density&amp;quot; the correct dipole moment of the excited state? I have looked for the answers over the Internet, however, information regarding this issue is very limited.&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much in advance for your help!&lt;/p&gt;&#xA;" OwnerUserId="4571" LastActivityDate="2021-11-17T23:11:59.473" Title="Calculating the excited state dipole moment" Tags="|quantum-chemistry|gaussian|quantum-mechanics|excited-states|dipole|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7088" PostTypeId="2" ParentId="7064" CreationDate="2021-11-17T16:58:02.993" Score="3" Body="&lt;p&gt;Answering &lt;em&gt;&amp;quot;How does a beginner condensed matter theorist working on real materials, get up to speed?&amp;quot;&lt;/em&gt; is not as easy as it could appear.&lt;/p&gt;&#xA;&lt;p&gt;From my own experience, if you are a condensed matter theory PhD student and only focus on condensed matter, you will (should?) grow faster.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I am a physicist and also made my PhD in theoretical condensed matter physics (developing a phonon laser called SASER). But then, I moved to make a post-doc in an experimental semiconductor group (coming back to my undergrad / master main subject). After the first year, I come back to applying theory to the semiconductor devices studied in the group.&lt;/p&gt;&#xA;&lt;p&gt;Then, I began to work as professor in my actual university. At the time (2006), the older researchers (all chemist and pharmacist) worked in inorganic chemistry developing materials and in organic chemistry in drug development for different diseases. In order to be inserted in that (new) research lines, I did a lot of individual studies and an organic chemistry course with one of the colleagues I was collaborating with. Certainly the latter &amp;quot;delayed&amp;quot; me a bit.&lt;/p&gt;&#xA;&lt;p&gt;Now, I can move between condensed matter, structural biology and drug development. So, for me, it was a win-win path.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-11-18T20:00:15.550" LastActivityDate="2021-11-18T20:00:15.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7089" PostTypeId="2" ParentId="7065" CreationDate="2021-11-17T17:12:11.390" Score="8" Body="&lt;p&gt;I come from an entirely different academic field and my answer is based on what I've seen across a variety of disciplines and my experience with software development.&lt;/p&gt;&#xA;&lt;p&gt;You can essentially break down any scientific GUI program into two parts: the part with the core functionality that can work perfectly fine as a console application, and the part that is the UI.&lt;/p&gt;&#xA;&lt;p&gt;The first part is essentially mandatory; you can't run an analysis without the core functionality. That means someone has to spend time and resources creating it. Writing a console application is relatively simple, especially if you want it to be cross platform. There could be some platform specific features you need that complicates this, but many of the core things you need are platform agnostic (like adding two numbers) and the language you're using will handle the platform specific details in the background.&lt;/p&gt;&#xA;&lt;p&gt;UI development is very different. Every platform has it's own libraries for creating UI components. There are libraries that abstract this away and allow you to write cross-platform UI code, but they can be very complex and time consuming to learn. Time that could be spent on other tasks, like developing more functionality in the core program, developing different programs for different tasks, or even doing other things like lab research that has clearer advantages for one's career.&lt;/p&gt;&#xA;&lt;p&gt;On top of learning how to code UI's, you also have to learn to how to design good and effective UI's. That is very difficult to do and takes time to get right. You have to learn to balance usability and intuitiveness for the user with how to provide full functionality. And you may end up in a situation where adding or changing something major in your core program forces you to spend a lot of time redesigning your UI when with command-line parameters all you might have to do is add a new flag.&lt;/p&gt;&#xA;&lt;p&gt;But then, after the GUI has been designed and created, it's a new source of maintenance burden. That means a program with a GUI will have to have time dedicated to fixing GUI issues for users, especially if an OS (or other system library) update breaks it. That's time that could be spent on other things more productive to one's career or research aspirations.&lt;/p&gt;&#xA;&lt;p&gt;A final thing is documentation. Creating good documentation for GUI software is more difficult and time-consuming than for command-line parameters (including lots of screenshots involved). And changing the design of the UI potentially means significant documentation updates.&lt;/p&gt;&#xA;&lt;p&gt;Now, there certainly are benefits to a GUI. In my field, researchers tend to be less technically proficient with computers and have very little experience with the command-line. That means they tend to avoid console applications and are drawn to software with a GUI. In that case, taking the time to develop a GUI for a piece of software may make sense for growing a large user base. Personally, I have the background in software development where I'm hoping to make a career of writing software with good UIs for researchers in my field (which is why the question title caught my interest on the homepage). But for other fields where people might be more proficient with things like the command-line, it may not make sense as a time investment.&lt;/p&gt;&#xA;" OwnerUserId="4572" LastActivityDate="2021-11-17T17:12:11.390" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7090" PostTypeId="2" ParentId="7071" CreationDate="2021-11-17T17:21:51.577" Score="3" Body="&lt;p&gt;This is a great question, with a lot to unpack in it. (In other words, strap in for a long answer.) There's a bit of an &lt;a href=&quot;https://meta.stackexchange.com/a/66378&quot;&gt;XY problem&lt;/a&gt; here: the specific question asked is a good one, but I think the more fundamental issue needs a different solution. I'll start with the fundamental issue, then move on to the specific question.&lt;/p&gt;&#xA;&lt;h2&gt;When to use TPS and when to use TIS&lt;/h2&gt;&#xA;&lt;p&gt;In general, the choice of standard transition path sampling (TPS) vs. transition interface sampling (TIS) doesn't depend on the physical system you're modeling. Instead, it's about what information you want to calculate about the system. TPS mainly gives you mechanisms. TIS gives you mechanisms and reaction rates. The downside is that TIS is a lot more expensive than TPS, so you only want to use TIS if you need that more detailed information.&lt;/p&gt;&#xA;&lt;h2&gt;What to do when you're not getting decorrelated trajectories&lt;/h2&gt;&#xA;&lt;p&gt;The OP's plot of the path tree is a perfect example of a common issue with getting decorrelated trajectories with one-way shooting TPS. (In two-way shooting, the same problem manifests as shooting moves always getting rejected.)&lt;/p&gt;&#xA;&lt;p&gt;Let me zoom in on part of the path tree. Under it, I'm going to sketch my guess of what the committor probability looks like as a function of this path.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VkseR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VkseR.png&quot; alt=&quot;the committor jumps from 0 to 1 in a region between accepted backward shots and accepted forward shots&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Reminder: the committor is the probability that, from that configuration with random velocities, you end up in the final state before hitting the initial state. A shot in one-way shooting isn't exactly a committor attempt, because the velocities aren't truly randomized, but for condensed phase systems the velocity memory is relatively short, so you can think of each shot as &amp;quot;almost&amp;quot; a committor attempt.&lt;/p&gt;&#xA;&lt;p&gt;The problem here is every trial from a shooting point left of the committor jump has near-0% probability of accepting a forward shot (you only accept backward shots), and every trial right of the committor jump has a near-0% probability accepting a backward shot. So you end up with this gap between blue (backward) and red (forward), and that gap means no decorrelated trajectories.&lt;/p&gt;&#xA;&lt;p&gt;Now that we know the problem, the answer (in principle) is easy: select shooting points from closer to the transition state (where the committor is 0.5 and you have equal chance of accepting forward or backward shots). Unfortunately, easy in principle doesn't always mean easy in practice.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;If you know where the transition state is&lt;/strong&gt;, then instead of using uniform shooting point selection, you can select from points more likely to be near the transition state. In OPS, you do this by changing the &lt;code&gt;selector&lt;/code&gt; parameter, in, e.g., the &lt;code&gt;OneWayShootingMoveScheme&lt;/code&gt;. There are two main options here that are relevant: &lt;a href=&quot;http://openpathsampling.org/latest/api/generated/openpathsampling.shooting.BiasedSelector.html#openpathsampling.shooting.BiasedSelector&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;BiasedSelector&lt;/code&gt;&lt;/a&gt;, which allows you to use any function you want to for the shooting point bias, and &lt;a href=&quot;http://openpathsampling.org/latest/api/generated/openpathsampling.shooting.GaussianBiasSelector.html#openpathsampling.shooting.GaussianBiasSelector&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;GaussianBiasSelector&lt;/code&gt;&lt;/a&gt;, which specifically uses a Gaussian form (since that's the most common choice).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;If you don't know where the transition state is&lt;/strong&gt;, &lt;a href=&quot;http://dx.doi.org/10.1063/1.4965882&quot; rel=&quot;nofollow noreferrer&quot;&gt;spring shooting&lt;/a&gt; will find its way to the transition state. In OPS, you use a different move scheme to do spring shooting. So instead of the standard TPS &lt;code&gt;OneWayShootingMoveScheme&lt;/code&gt;, you use &lt;code&gt;SpringShootingMoveScheme&lt;/code&gt;. &lt;a href=&quot;https://github.com/openpathsampling/openpathsampling/blob/master/examples/misc/spring_shooting_example.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here's an example&lt;/a&gt; of spring shooting used on a toy model.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Caveat: Multiple states make this harder.&lt;/strong&gt; This specific system has a transition that, at some point, splits into two different channels (depending on which type of bound state). The risk is that if the transition state comes after the split into two channels, then you have different transition states for each channel. Path sampling might get stuck sampling only one channel. Approaches to enhance switching between channels is still an active area of research. (If your transition state is before the channel split, then will shoot from the part of the path that is common to both channels and you should see channel switching.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Conceptually, a similar analysis was done in &lt;a href=&quot;https://doi.org/10.1073/pnas.1906502116&quot; rel=&quot;nofollow noreferrer&quot;&gt;Arjun et al.&lt;/a&gt;, although in that case the different states (two kinds of solids) were only identified &lt;em&gt;after&lt;/em&gt; the sampling was done. However, that can give some ideas of how path density analysis can be useful here.&lt;/p&gt;&#xA;&lt;h2&gt;Selecting only certain state pairs in TPS&lt;/h2&gt;&#xA;&lt;p&gt;You have two bound states and one unbound state, and you're interested in unbound -&amp;gt; bound transitions. The standard constructor for &lt;code&gt;TPSNetwork&lt;/code&gt; takes parameters &lt;code&gt;initial_states&lt;/code&gt; and &lt;code&gt;final_states&lt;/code&gt;, so you can get the network you want with:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;network = paths.TPSNetwork(initial_states=[unbound],&#xA;                           final_states=[bound_AaAA, bound_AAaA])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;from_states_all_to_all&lt;/code&gt; constructor is &lt;a href=&quot;https://github.com/openpathsampling/openpathsampling/blob/b619a07994aab24d8ea33288999196a3c19d0ba8/openpathsampling/high_level/network.py#L274-L278&quot; rel=&quot;nofollow noreferrer&quot;&gt;literally just a shortcut&lt;/a&gt; so that, if the initial states are the same as the final states, you don't have to type the list of states twice.&lt;/p&gt;&#xA;&lt;p&gt;Not immediately relevant to OP, but for a more complicated set of transitions where you only wanted some transition pairs selected, you could use the &lt;code&gt;from_state_pairs&lt;/code&gt; constructor. For example, imagine you have states &lt;code&gt;A&lt;/code&gt;, &lt;code&gt;B&lt;/code&gt;, &lt;code&gt;C&lt;/code&gt;, and &lt;code&gt;D&lt;/code&gt;, and you want transitions &lt;code&gt;A-&amp;gt;C&lt;/code&gt;, &lt;code&gt;B-&amp;gt;C&lt;/code&gt; &lt;code&gt;A-&amp;gt;D&lt;/code&gt;, but not &lt;code&gt;B-&amp;gt;D&lt;/code&gt;. &lt;code&gt;from_states_all_to_all&lt;/code&gt; gives all possible 2-state pairs from those 4 states, (except self-transitions, like &lt;code&gt;A-&amp;gt;A&lt;/code&gt;). The normal constructor &lt;code&gt;TPSNetwork(initial_states=[A, B], final_states=[C, D])&lt;/code&gt; would allow the &lt;code&gt;B-&amp;gt;D&lt;/code&gt; transitions. But you could get exactly the desired transitions with:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;network = paths.TPSNetwork.from_state_pairs([(A, C), (B, C), (A, D)])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Where MSTIS isn't doing what you might want&lt;/h2&gt;&#xA;&lt;p&gt;There are a couple of points to make about your MSTIS setup -- first, as I mentioned earlier, unless you want something that you can calculate efficiently with TIS (e.g., rates), there's no reason to do the more expensive setup. Also, I don't think the setup/results here are really doing what you want:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;TIS allows A-&amp;gt;A trajectories.&lt;/strong&gt; This is necessary for the way it calculates rates, but if you're mainly interested in the mechanism, that's pointless. The short trajectories you see are A-&amp;gt;A trajectories.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;MSTIS links all states to all other states&lt;/strong&gt;: This means that with MSTIS, you are allowing the &lt;code&gt;AaAA&lt;/code&gt; to &lt;code&gt;AAaA&lt;/code&gt; transition (and vice versa). Multiple interface set TIS (MISTIS) is an approach (disclaimer: I developed) to avoid that problem. Here's an &lt;a href=&quot;http://openpathsampling.org/latest/examples/mistis.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;OPS example of MISTIS&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;The path tree follows a single replica&lt;/strong&gt;: The path tree shown doesn't tell us much because it is probably only following the innermost replica. In MSTIS, you'll be sampling one replica for each interface (and if that path tree is for the replica 0, it's probably an innermost interface anyway, so unlikely to see transitions).&lt;/p&gt;&#xA;&lt;p&gt;That said, it looks to me like this is an example of what I call the 3-frame problem in TIS -- after step 45, these trajectories are all 3 frames long, which means only one frame is not in the state (only one valid shooting point). These can be very hard to decorrelate.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;On setting up the interface set/state definitions for the unbound state&lt;/h2&gt;&#xA;&lt;p&gt;First, your unbound state &lt;em&gt;is&lt;/em&gt; a stable state -- it is stable due to entropy. There are a lot of ways for your ligand to be unbound, not so many for it to be bound. And if you just run MD in the unbound state, presumably it takes a long time before you reach the target bound states.&lt;/p&gt;&#xA;&lt;p&gt;More generally, as discussed above, you probably don't actually want to do TIS here. But a couple points if you did:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Interface sets should be in terms of increasing CV values.&lt;/strong&gt; The unbound interface set uses decreasing values of the CV. Although OPS allows you to set up interface sets where the interface values decrease, the analysis tools can't handle that (yet). The easy trick here is to wrap your distance CV in another CV that just returns the negative of it:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def neg_cv(snapshot, cv):&#xA;    return -cv(snapshot)&#xA;&#xA;neg_dist_unbound = paths.CoordinateFunctionCV(&#xA;    'neg_dist_unbound',&#xA;    neg_cv,&#xA;    cv=dist_unbound&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;The state is treated separately from the interface set.&lt;/strong&gt; States do not have to be defined only in terms of the CV used in the interface set. If your state definition is more strict than your innermost interface, then you have an &amp;quot;interstitial&amp;quot; region between the state and the innermost interface. On the other hand, if your state definition is less strict that your innermost interface, then the edge of your innermost interface is effectively defined by your state. All of this is fine mathematically, although it can make it harder to think about what's going on (especially if the effective interface is defined by the state definition in some degrees of freedom and the interface CV in another.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;You can use a custom CV that combines your existing CVs.&lt;/strong&gt; The CV associated with the unbound interface set should be seen as &amp;quot;pushing you away from&amp;quot; the unbound state. One way to do that (independent of which final state it goes to) is to create a CV that uses both of the individual distances. For example:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def neg_min_dist(snapshot, cv1, cv2):&#xA;    # using negative here for reason listed above&#xA;    return -min(cv1(snapshot), cv2(snapshot))&#xA;&#xA;unbound_cv = paths.CoordinateFunctionCV(&#xA;    &amp;quot;unbound_cv&amp;quot;,&#xA;    neg_min_dist,&#xA;    cv1=dist_AaAA,&#xA;    cv2=dist_AAaA&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Additional notes&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I notice that you're passing the &lt;a href=&quot;https://www.mdtraj.org/1.9.5/api/generated/mdtraj.compute_distances.html#mdtraj.compute_distances&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;periodic=False&lt;/code&gt;&lt;/a&gt; argument to MDTraj in your CVs. Since you're explicitly doing that, I assume you mean to, but I'm not sure why. It looks to me like a potential source of errors.&lt;/li&gt;&#xA;&lt;li&gt;Python supports &lt;code&gt;float('infinity')&lt;/code&gt; -- for unbound states I usually use that for the maximum, because that way I can reuse the same state definition regardless of things like box size.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-11-17T17:21:51.577" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7091" PostTypeId="2" ParentId="7065" CreationDate="2021-11-17T20:06:06.937" Score="9" Body="&lt;p&gt;As two people asked me to convert a comment to an answer, voilà:&lt;/p&gt;&#xA;&lt;p&gt;The notion of an &amp;quot;easy to use, spits out the result GUI&amp;quot; is an &amp;quot;industry approach&amp;quot; where obtaining a result matters more than the minutiae of how said result is obtained.&#xA;For this group there exists at least one commercial quantum chemistry product from the Netherlands. I used a trial version and the automation actually irritated me... - There you built a molecule and the software would go as far as to suggest a functional and method.&#xA;&amp;quot;Input in, output out.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;If we move to the quantum chemistry research field which is significantly bigger than industry use (at present), the users are either learning how to use quantum chemistry or are already experienced in it.&#xA;In this case you want to be able to explicitly control your inputs - maybe compare functionals, basis sets: a GUI can even be a hindrance if you like using scripts. (Its easy to run a benchmark when scripts do a lot of work ;).&#xA;Keep in mind that most calculations in quantum chemistry are relative and not absolute. You want to compare the difference between A and B, you need to be sure that A and B are calculated using the same methods.&lt;/p&gt;&#xA;&lt;p&gt;Now an interface could accommodate all possible combinations, however once you attempt to cover all options, you arrive at an unnecessarily complex GUI. As a result, a GUI will often propose only a subset of options. The most frequently or well known functionals, commonly used basis set. If you use the GUI as a text editor, then its use is limited - especially if you need to know your inputs anyway. A light text editor is much faster.&#xA;(Look up the GMTKN benchmark - there is one from 2017 which evaluated functionals. How do you want to support all in a GUI in an easily usable manner? You cannot. Given the number of functionals that exist, documentation with a long list and a text editor is actually the best solution for experienced users. And then you need to update it every time a new functional comes out...)&lt;/p&gt;&#xA;&lt;p&gt;The main interest in/reasons for using a GUI in quantum chemistry are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;building the initial molecule (though you might even be running calculation son an existing benchmark set of xyz co-ordinates)&lt;/li&gt;&#xA;&lt;li&gt;visualizing frequencies (I do not think you can really understand the frequencies without a GUI, BUT you can easily calculated with the resulting values without seeing them.)&lt;/li&gt;&#xA;&lt;li&gt;visualizing for example an IRC calculation to verify that you have obtained the correct transition state.)&#xA;The vast majority of information that you obtain from quantum chemistry calculations are available in plain text in the output file, you do not need a GUI to read the value.&#xA;In some cases, you can even be unsure as to what the actual value in the GUI is... (There is a certain US product where I believe the GUI and text file provided different E0 energies, possibly shifted by the Zero Point vibrational Energy...)&#xA;So once again, if you are doing research, it is much faster to run a script to pull the values from the text file than clicking around a GUI to do the same thing. - Plus you know exactly what value you are getting from where and how.&#xA;Now it can be said that the output of some quantum chemistry code is atrocious in its formatting - mainly a result of the age of the underlying code and there GUIs invariably provide some benefit, but they aren't the perfect solution either. (See my E0/ZPE comment...)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Nowadays my favourite quantum chemistry code is ORCA, which, due to having a much younger code base compared to other codes, provides very clear and structured output that you are much better off accessing &amp;quot;as is&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;This brings along another important question:&#xA;Should software retain the same file format when the limitations become more and more obvious? - If your output file is not easily usable, it makes more sense to update the output in a future release to be more legible, rather than creating software that attempts to interpret data displayed in an overly complex manner. (Typically a concise manner relate to limitation in Fortran several decades ago.)&lt;/p&gt;&#xA;&lt;p&gt;The utility of a user interface further directly depends on the complexity of the input.&#xA;Standard &amp;quot;Gaussian type functional&amp;quot; quantum chemistry has today become (in many forms of its application) trivial and standardized with xyz input and ouputs for geometries.&#xA;(Yes, I know that metals and heavy atoms require a careful choice of method from functionals to basis sets.)&lt;/p&gt;&#xA;&lt;p&gt;In contrast, setting up a quantum chemistry simulation for periodic systems using plane waves benefit a lot more from user interfaces. While it is easy to specify a &amp;quot;trivial&amp;quot; structure such as for example solid diamond based on literature parameters, the investigation of real life crystal structures (maybe with adsorbents) benefits tremendously from assistive software. I looked at plane waves briefly a good 10 years ago - and defining a good input is already a non-trivial subject. (Also the fact that neighbouring cells interact, etc. etc.)&#xA;Back then I was shown a specialized GUI in another department - which helped them define their systems. - And these softwares are not cheap as far as I am aware. On the free side I am aware of only ECCE (for NWChem) and VESTA.&lt;/p&gt;&#xA;&lt;p&gt;Another field that benefits a lot more from user interfaces is Molecular Dynamics. While I'm sure experts can configure these easily from text files once the initial configuration is done, developing the initial understanding is not trivial. However as far as I am aware, in the case of GROMACS, the input has changed multiple times in incompatible ways between versions...&#xA;(Again, about 5 years ago I looked at Molecular Dynamics and failed and stuck to my Gaussian type functionals/calculations that I know how to do.)&#xA;As far as I am aware there is maybe one major Molecular Dynamics interface that can be had for free (for academic use) which is VMD. After that, the interfaces that exist are often commercial: Potentially because we return to the previous point. Industry wants results (and Molecular Dynamics if of interest in the pharmaceutical filed) while scientists want to understand the system and thus often want to modify minutiae in the configuration.&lt;/p&gt;&#xA;" OwnerUserId="540" LastEditorUserId="7" LastEditDate="2021-11-18T18:56:58.997" LastActivityDate="2021-11-18T18:56:58.997" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7092" PostTypeId="2" ParentId="7082" CreationDate="2021-11-17T20:17:28.660" Score="8" Body="&lt;p&gt;Higher-order integrators are used, but usually the way they perform the calculation is not through directly calculating higher order derivatives, but essentially through multiple force calculations. The Wikipedia page on &lt;a href=&quot;https://en.wikipedia.org/wiki/Symplectic_integrator&quot; rel=&quot;nofollow noreferrer&quot;&gt;symplectic integrators&lt;/a&gt; gives some information on this, including 3rd order and 4th order examples. I've personally used the 4th order integrator in semiclassical simulations, where we were concerned about high accuracy to preserve quantum phase interference effects (although I'm not sure it was actually necessary).&lt;/p&gt;&#xA;&lt;p&gt;In condensed phase systems, we're often simulating at a constant temperature, frequently with a stochastic thermostat, so the error in question should be how well we preserve the ensemble, not the energy itself. The &lt;a href=&quot;https://doi.org/10.1093/amrx/abs010&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;BAOAB&amp;quot; Langevin splitting&lt;/a&gt; has been shown to have a coincidental cancellation of errors that makes it a higher order integrator at the cost of a lower order scheme.&lt;/p&gt;&#xA;&lt;p&gt;Non-symplectic predictor-corrector schemes used to be used more frequently, but it's generally agreed that symplectic methods are superior (thanks to some guaranteed properties coming from them being &lt;a href=&quot;https://en.wikipedia.org/wiki/Canonical_transformation&quot; rel=&quot;nofollow noreferrer&quot;&gt;canonical transformations&lt;/a&gt;). I've used 4th-order &lt;a href=&quot;https://en.wikiversity.org/wiki/Adams-Bashforth_and_Adams-Moulton_methods&quot; rel=&quot;nofollow noreferrer&quot;&gt;Adam-Bashforth-Moulton predictor-correctors&lt;/a&gt;, as well as a 6th order Gear predictor corrector (modified to use adaptive time steps; needed when I hit a system where fixed time steps didn't work). The Gear predictor-corrector is presented in an appendix of [EDIT: the first edition of] Allen and Tildesley's &amp;quot;Computer Simulation of Liquids,&amp;quot; which for a long time was one of the best books to learn MD (it's a little out of date now, being as it was published in 1987, [EDIT: and it looks like the new edition quite reasonably removed this appendix]). The Gear PC tries to actually estimate the values of the derivatives (whereas ABM uses a higher discretization in time). Some of my own old notes on ABM integrator and 4th order symplectic integrators can be found under the heading &amp;quot;Qual Prep&amp;quot; &lt;a href=&quot;http://hyperblazer.net/teaching/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (warning -- you'll have to decipher my handwriting).&lt;/p&gt;&#xA;&lt;p&gt;Overall, although higher-order integrators have certainly been used, I think the overall sense in the community is that the cost-benefit ratio just isn't worth it.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Also, how would one actually go about calculating the third derivative of position with respect to time?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This should be feasible just by applying the chain rule. However, I think this would indeed require the whole Hessian matrix, which rules it out for large-scale MD.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-11-19T23:15:00.543" LastActivityDate="2021-11-19T23:15:00.543" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7093" PostTypeId="2" ParentId="7087" CreationDate="2021-11-17T21:21:47.603" Score="7" Body="&lt;p&gt;There's actually more than one way to calculate the dipole moment, and you can check whether or not the numbers you're obtaining from &lt;code&gt;td=(singlets,nstates=5,root=1)&lt;/code&gt; are making sense by comparing your result to what you'd get with a more &amp;quot;manual&amp;quot; approach in which you can see exactly what's going on.&lt;/p&gt;&#xA;&lt;p&gt;The simplest formula is simply the expectation value of the dipole moment operator:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\langle \psi | \mathbf{\hat{\mu} }| \psi\rangle. &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, it can be much harder to get wavefunctions than energies, and a first-order error in the wavefunction can lead to a second-order error in the energy, so it would be convenient if we could calculate the dipole moment via only energy calculations (also, some electronic structure methods or implementations in software may be easily able to give energies but not wavefunctions). In fact we &lt;em&gt;&lt;strong&gt;can&lt;/strong&gt;&lt;/em&gt; calculate the dipole moment with only simple energy calculations.&lt;/p&gt;&#xA;&lt;p&gt;It can be shown that for an electric field &lt;span class=&quot;math-container&quot;&gt;$\mathcal{E}$&lt;/span&gt; we have (see &lt;a href=&quot;https://www.southampton.ac.uk/assets/centresresearch/documents/compchem/perturbation_theory.pdf&quot; rel=&quot;noreferrer&quot;&gt;section 4 of this PDF&lt;/a&gt;, for example):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle \psi | \mathbf{\hat{\mu} }| \psi\rangle = -\frac{\textrm{d}E}{\textrm{d}\mathcal{E}}\tag{2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is related to perturbation theory and/or linear response theory, and it allows us to calculate Eq. 1 without ever needing the wavefunction, simply by calculating the energy multiple times and doing finite differences to approximate the derivative (if you want &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; components of the dipole moment, you'll need to do &lt;span class=&quot;math-container&quot;&gt;$n+1$&lt;/span&gt; extra energy calculations in addition to the zero-field energy calculation, but even for 3-components of the dipole moment, I often wouldn't mind doing 5 energy calculations if it could help me avoid requiring use of the wavefunction).&lt;/p&gt;&#xA;&lt;p&gt;Whenever I hear &amp;quot;finite differences&amp;quot; I cringe a bit since I almost always prefer to do things analytically if possible, but &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/epdf/10.1002/qua.560430505&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; by Ernzerhof (the 'E' in PBE)  &lt;em&gt;et al.&lt;/em&gt; actually explains that using finite differences can be better than trying to calculate the dipole moment more directly. The same is said in &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-4075/43/13/133001&quot; rel=&quot;noreferrer&quot;&gt;section 3.1 of this paper&lt;/a&gt; by Lodi &amp;amp; Tennyson, along with more references that recommend the finite differences approach over the more &amp;quot;direct&amp;quot; approach. You can see the differences between numerical values obtained via finite differences versus DFPT &lt;a href=&quot;http://cmt.dur.ac.uk/sjc/thesis_prt/node110.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and the difference between finite differences and using the linear response &lt;a href=&quot;https://juliamolsim.github.io/DFTK.jl/stable/examples/polarizability/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So if you're not sure if the direct approach is giving you sensible answers, you can just do a simple energy calculation &lt;span class=&quot;math-container&quot;&gt;$2 + n$&lt;/span&gt; times if you want &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; components of the dipole moment&lt;/strong&gt;, and it might not be a bad idea to do this second method anyway, to see whether or not the more &amp;quot;direct&amp;quot; approach is giving sensible results!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-17T21:33:26.540" LastActivityDate="2021-11-17T21:33:26.540" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7094" PostTypeId="2" ParentId="689" CreationDate="2021-11-17T22:45:58.160" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Single particle spectrum can be easily deduced from the above Hamiltonian&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This statement is a bit misleading. Your equation &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is a many-body Hamiltonian involving interactions (operators quartic in &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;'s, or likewise quadratic in &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;'s) and single-particle hopping (first part that is quadratic in &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;'s). It is only the single-particle hopping that defines the single-particle spectrum in question.&lt;/p&gt;&#xA;&lt;p&gt;Let's consider a general (single-particle) tight-binding Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$h=\sum_{ij}a_i^{\dagger}t_{ij}a_j$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The index &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; spans over all the single-particle degrees of freedom. For example, &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; may simply label the sites of a lattice; or if there is more than one orbital &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; per unit cell &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; should be understood to represent a combined index, i.e &lt;span class=&quot;math-container&quot;&gt;$i=(x,a)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; is translationally invariant -- either an infinite lattice or wrapped on a torus -- then the eigenenergies are functions of the crystal momentum &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. As a practical matter, we can determine this single-particle spectrum by diagonalizing the matrix &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt;, which provides a unitary transformation &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$a_{i}^{\dagger} = \sum_{k,\mu}b_{\mu}(k)^{\dagger}\Omega_{\mu i}(k) ,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which takes &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; into the band basis. (I've written the band basis creation/annihilation operators as &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;'s.) I want to stress here that &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; is a &lt;em&gt;rotation of the single-particle basis&lt;/em&gt;, into one which diagonalizes &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt;, i.e&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$h = \sum_{k,\mu}b_\mu(k)^{\dagger}\epsilon_{\mu}(k)b_{\mu}(k) .$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The index &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; labels the bands, of which there are &lt;span class=&quot;math-container&quot;&gt;$N=\text{dimension}(\mu)$&lt;/span&gt; states at every &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. If there is only one orbital per unit cell, then the tight-binding model will have only 1 band, i.e &lt;span class=&quot;math-container&quot;&gt;$N=1$&lt;/span&gt;. More generally however, if we remember &lt;span class=&quot;math-container&quot;&gt;$i=(x,a)$&lt;/span&gt;, then there are &lt;span class=&quot;math-container&quot;&gt;$N=\text{dimension}(a)$&lt;/span&gt; bands. So that the number of bands depends on the number of orbitals in the unit cell. At this point, we have only rotated our basis, and not projected.&lt;/p&gt;&#xA;&lt;p&gt;Since we are interested in a many-body problem let's introduce some general interactions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V=\sum_{ijkl}a_i^{\dagger}a_j^{\dagger}V_{ijkl}a_ka_l$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;such that our total Hamiltonian is &lt;span class=&quot;math-container&quot;&gt;$H=h+V$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=\sum_{ij}a_i^{\dagger}t_{ij}a_j+\sum_{ijkl}a_i^{\dagger}a_j^{\dagger}V_{ijkl}a_ka_l .$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To quote from the paper you referenced (just before their Eqn 2),&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The projection onto the lowest band realizes a new effective problem [...] which derives from the density-density interactions of the microscopic Hamiltonian.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This statement might come off as confusing, since &amp;quot;lowest band&amp;quot; refers to a single-particle state, while &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is a many-body Hamiltonian involving interactions. More technically, we are constraining ourselves to that section of Fock space where the number operator for any band &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is zero except for the band of interest. Practically, this can be achieved by defining a new &amp;quot;projected-a&amp;quot; operator&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{a}_i^{\dagger}\equiv\mathcal{P}_{\mu_o}a_i^{\dagger}\mathcal{P}_{\mu_o}=\sum_{k}b_{\mu_o}(k)^{\dagger}\Omega_{i,\mu_o}(k),$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mu_o$&lt;/span&gt; here references the band of interest. (We can also project onto a subset of bands similarly.) We can then project our Hamiltonian by replacing all &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; operators with &lt;span class=&quot;math-container&quot;&gt;$\hat{a}$&lt;/span&gt; operators. The effective Hamiltonian for the system projected onto &lt;span class=&quot;math-container&quot;&gt;$\mu_o$&lt;/span&gt; is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_{\text{effective}(\mu_o)}=\sum_{k}b_{\mu_o}^{\dagger}(k)\epsilon_{\mu_o}(k)b_{\mu_o}(k)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$+\sum_{k_1k_2k_3k_4}b_{\mu_o}(k_1)^{\dagger}b_{\mu_o}(k_2)^{\dagger}\Big(\sum_{ijkl}\Omega^*_{i\mu_o}(k_1)\Omega^*_{j\mu_o}(k_2)V_{ijkl}\Omega_{k\mu_o}(k_3)\Omega_{l\mu_o}(k_4)\Big)b_{\mu_o}(k_3)b_{\mu_o}(k_4)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the band is &lt;strong&gt;truly&lt;/strong&gt; flat, i.e if &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{\mu_o}(k)=\text{constant}$&lt;/span&gt;, then the projected kinetic energy is simply a constant shift in the energy, and can be gauged out, leaving only the interacting part. If it has some dispersion, then one needs to ask if the interactions are much larger than its bandwidth, in which case we could solve the interacting problem (without the kinetic energy), then consider kinetic energy as a perturbation -- the strong coupling approach. I believe this is the paradigm behind the paper you shared.&lt;/p&gt;&#xA;&lt;p&gt;This expression I've given here for projected &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is pretty general, so you'll have to put in some effort in order to get its projected matrix elements into the form in the paper. Not to shamelessly advertise my own work, but a colleague and I wrote a pedagogical section in our paper in which we detail how this is done in the context of the quantum Hall &lt;a href=&quot;https://www.scipost.org/SciPostPhysCore.3.2.015&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt; (see Section 3 up through Eqn 8 for spin-half particles in continuum). This technique is common for studying quantum Hall physics, including fractional quantum Hall, and is a pretty quintessential use of projected potentials for flat bands. Since the gap between Landau levels (i.e bands) can be made much larger than the interactions, mixing between the lowest Landau level (i.e band) and the next Landau level is suppressed to the point where corrections due to inter-band mixing can be ignored. This justifies the projection.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;WARNING&lt;/strong&gt;: One should be careful and justify the projection, seeing that it involves throwing out information about other bands in the system. There is a pretty typical hierarchy in what people refer to as &amp;quot;flat/narrow band&amp;quot; system: (1) interactions and thermal energy &amp;lt;&amp;lt; band gap, for the projection to be justified; and (2) interactions &amp;gt;&amp;gt; bandwidth, for kinetic energy to be considered as a perturbation in the strong coupling problem.&lt;/p&gt;&#xA;&lt;p&gt;If (1) is not satisfied, then interactions may substantially mix the bands, and thus the error coming from projecting out those bands will be high. This is why the Renormalization Group (RG) is so popular (&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.257602&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;). Ultimately, at the end of the day, RG and projection have the same goal -- create an effective Hamiltonian. The difference being that RG does &lt;em&gt;not&lt;/em&gt; throw out information about the system, as in the case of the projection. Instead, undesired modes are averaged over, which in turn leads to an effective Hamiltonian which accounts for the presence of those modes. No thermodynamic information is lost in the sense that the partition function is unchanged. This is not true for a straight projection.&lt;/p&gt;&#xA;&lt;p&gt;Sorry for the lengthy explanation! I thought it would make sense to cover some important facts regarding the practicalities of projection, at the very least for the sake of a future googler who might come here looking for related answers. I hope this explanation kicks you in the right direction!&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="4543" LastEditDate="2021-11-17T23:31:54.793" LastActivityDate="2021-11-17T23:31:54.793" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7095" PostTypeId="2" ParentId="7087" CreationDate="2021-11-17T23:11:59.473" Score="7" Body="&lt;p&gt;This looks like it has been addressed on the &lt;a href=&quot;http://www.ccl.net/chemistry/resources/messages/2010/01/25.008-dir/index.html&quot; rel=&quot;noreferrer&quot;&gt;CCL&lt;/a&gt; previously.&lt;/p&gt;&#xA;&lt;p&gt;To summarize and add details for your case, Gaussian can directly calculate the excited state dipole, but you need to add the keyword &lt;code&gt;Density=current&lt;/code&gt; to get it to use the density from the excited rather than the ground state. The excited dipole should then be under a header like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**********************************************************************&#xA;Population analysis using the CI density.&#xA;**********************************************************************&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will print twice during an optimization: once for the initial geometry and once for the final geometry.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-17T23:11:59.473" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7096" PostTypeId="2" ParentId="7085" CreationDate="2021-11-18T00:17:33.310" Score="4" Body="&lt;p&gt;As @danjodc already pointed out, SCF=QC is not an approximation but rather a way of solving the SCF equations. The SCF equations arise from the extremality condition for the orbitals that minimize energy (see e.g. our open access review &lt;a href=&quot;https://www.mdpi.com/1420-3049/25/5/1218&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.mdpi.com/1420-3049/25/5/1218&lt;/a&gt;). Instead of solving the SCF equations by iterative re-diagonalization, you can just optimize the orbitals directly. This is essentially what SCF=QC does in Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;The diagonalization based approach tends to be very fast for &amp;quot;easy&amp;quot; systems, because of Pulay's DIIS procedure that is often able to find the ground state solution quickly. However, in cases where DIIS fails to lead to reliable convergence, energy minimization may be a better alternative.&lt;/p&gt;&#xA;&lt;p&gt;I don't remember by heart what kind of algorithm Gaussian uses in SCF=QC, but the most famous quadratic convergence algorithm i.e. Newton-Raphson algorithm is also infamous for converging to saddle-point solutions. Moreover, direct energy minimization may only lead you to the &lt;em&gt;closest&lt;/em&gt; minimum, not the &lt;strong&gt;global&lt;/strong&gt; minimum.&lt;/p&gt;&#xA;&lt;p&gt;If you are experiencing convergence problems, I recommend the XQC algorithm which is sort of the best of both worlds: it uses DIIS for starters, and only when DIIS does not converge it switches over to quadratic convergence. If you're dealing with metals, you might also try toying around with &lt;code&gt;SCF=Fermi&lt;/code&gt; which might help in locating the best orbitals. Moreover, running the calculation in a smaller basis first and reading it in as guess for the &amp;quot;production calculation&amp;quot; may also help in finding the converged solution.&lt;/p&gt;&#xA;&lt;p&gt;On a final note, metal complexes may prefer higher spin states. It might be good to check how the energy behaves with respect to the spin state: does it go down when you do e.g. singlet -&amp;gt; triplet -&amp;gt; quintet -&amp;gt; septet -&amp;gt; nonet -&amp;gt; etc?&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-11-18T00:17:33.310" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7097" PostTypeId="2" ParentId="7064" CreationDate="2021-11-18T03:47:52.027" Score="7" Body="&lt;p&gt;I'm grad student about to finish their PhD, so you may find my perspective valuable.&lt;/p&gt;&#xA;&lt;p&gt;For reference, my undergrad degree was in physics and math, where I did big data analysis on high energy data gathered at CERN. I had some much earlier experience working in a condensed matter lab, yet gained very little (to no) chemistry experience. To date, I have never actually taken a condensed matter course -- and don't intend to. I likewise don't have any specialized training in chemistry, and never took a chemistry class.&lt;/p&gt;&#xA;&lt;p&gt;Despite this, I feel that I've developed a strong enough understanding of the field to curate my own interest and pursue my own problems. This is in part due to a research mindset that I inherited from my supervisor, and in part due to my own personal preferences toward learning.&lt;/p&gt;&#xA;&lt;p&gt;The mindset is as follows: Find &lt;em&gt;some&lt;/em&gt; problem that interests you enough that you'll throw everything you got at it. Maybe you know nothing about the field -- no general knowledge, no specialized techniques, absolutely nothing. It's like staring out at an ocean -- and condensed matter is a vast ocean -- and not knowing how to pass the beach. Don't fret. Pursue your problem with as much zeal as your interest can muster. Learning everything related to this problem; and with time, effort, and some help, you'll find before you a tiny island of knowledge, deep in the scientific ocean.&lt;/p&gt;&#xA;&lt;p&gt;Some people might say (and you might feel) that it is necessary to take a class about X, Y, and Z in order to even &lt;em&gt;start&lt;/em&gt; doing proper research. But homework -- simple problems that have a clear answer in a book -- will only have you playing in the shallows. Yes, you should calculate and do problems, perhaps even from a book (or paper) if it helps, but always in pursuit of your problem.&lt;/p&gt;&#xA;&lt;p&gt;These smaller problems orbiting your goal will form the beaches of this tiny island of knowledge. And it is that island which will define your unique perspective as a researcher, and allow you to see farther in the scientific ocean than you could if you stayed in the shallows. And with time, and more island forming research in the deep, you'll have an archipelago to call your own.&lt;/p&gt;&#xA;&lt;p&gt;Essentially, what I mean by this bit of philosophical mumbo jumbo is: dive deep into an interesting problem. Your own efforts in solving the problem will provide you the ground-level knowledge needed to do other things in your field. And perhaps most importantly, it is the &lt;em&gt;only&lt;/em&gt; way to actually learn how to research -- doing research.&lt;/p&gt;&#xA;&lt;p&gt;This is definitely just my perspective, one which is informed by my experiences. No doubt I am on the extreme end of being class anti-oriented.&lt;/p&gt;&#xA;&lt;p&gt;As a personal example, I started my theory career studying the Fe-based superconductors (pnictides and chalcogenides). In particular, I chose one material in that broader family -- FeSe -- and studied the hell out of it. Not only are many of the Fe-based superconductors electronically similar, in part owing to the similarities in their symmetries, but I find that the tools I learned translate to other unrelated materials as well.&lt;/p&gt;&#xA;&lt;p&gt;In real materials, there are also many different types of measurement techniques and experiments: conductance, photoemission, scanning tunneling microscopy, to name a few. I find it can be overwhelming at times, especially when some critical new research in the field depends on a set of techniques which are entirely new to me. But it's in these novel moments that I find the chance to develop my best physics intuition. And a lot of the time, these many different measurements can be related to a few key concepts -- e.g density of states (DOS) shows up everywhere.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, as a new theory researcher you may consider exposing yourself to cutting-edge numerical methods, such as the Density Matrix Renormalization Group (DMRG), machine learning (ML), or Density Functional Theory (DFT). It's a bit of a myth that you need to invest your entire graduate career in order to learn these things, or that you won't have the opportunity to learn them if your supervisor isn't an expert. There are actually a number of readily accessible tools and codebases from which one can start: QuantumEspresso=DFT, ITensor=DMRG, and Keras/TensorFlow=ML are just a few that I've used.&lt;/p&gt;&#xA;&lt;p&gt;These toolsets aren't just useful blackboxes either, but a fully functioning code that has the potential to teach you the method. It can be challenging to build up a codebase from scratch, as there a lot of new things to learn, and all the pieces have to fit just right in order for it to properly compute. But a fully functioning codebase can have pieces rewritten piece by piece, with the understanding that if it doesn't compute, then it's your piece that's bad. There are also tons of related workshops where you can learn from the pros.&lt;/p&gt;&#xA;&lt;p&gt;This top-down approach to novel numerical methods is how industry teaches machine learning, since it's pedagogically faster, and allows one to get results while they learn. If you're supervisor talks about one of these techniques, but they themselves don't have experience coding them, then they'll likely be super impressed if you did. You might suddenly find yourself becoming extremely valuable to your research group.&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="5" LastEditDate="2021-11-18T20:01:03.760" LastActivityDate="2021-11-18T20:01:03.760" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7098" PostTypeId="1" AcceptedAnswerId="7099" CreationDate="2021-11-18T03:53:46.067" Score="12" ViewCount="452" Body="&lt;p&gt;When I go to talks, I hear the statement &amp;quot;coarse-graining is required to access spatio-temporal scales to observe important dynamical behavior for stimuli-responsive systems&amp;quot; before they go on about coarse-graining methods and so on. &lt;strong&gt;My question is, what are these stimuli-responsive systems?&lt;/strong&gt; I have run simulations of PNIPAM and have seen its thermoresponsive behavior (coil-to-globule) collapse around 305 K, but all it took was a 100 ns simulation for about 35k particles, tops. I assume we need to perform CG on more complicated systems, but specific to stimuli-response, what are these systems?&lt;/p&gt;&#xA;&lt;p&gt;Unless it is truly rigorous bottom-up CG, I am sometimes skeptical of the forcefields some people use, because the force-field is clearly biased to the problem they are trying to solve. You can coarse-grain frankly any macromolecule, but there has to be a phenomenon some experimentalist is observing that we can't seem to see by plain all-atom MD.&lt;/p&gt;&#xA;&lt;p&gt;I apologize if this sounds condescending, or rude. I am just genuinely confused and it is hard to ask questions on Zoom conferences...&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2021-11-18T05:52:32.767" LastActivityDate="2021-11-18T22:08:24.553" Title="What kind of systems do we need to coarse-grain to observe interesting phenomena?" Tags="|molecular-dynamics|molecular-modeling|high-performance-computing|polymers|coarse-grained|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7099" PostTypeId="2" ParentId="7098" CreationDate="2021-11-18T05:33:33.233" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What kind of systems do we need to coarse-grain to observe interesting phenomena?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Systems that would otherwise be too large and/or complicated to simulate in a reasonable amount of time and/or with a reasonable amount of computational resources.&lt;/p&gt;&#xA;&lt;p&gt;Basically if you want to see &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; seconds of dynamics for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms, and your computational-resources/time is only enough to do &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; atoms where &lt;span class=&quot;math-container&quot;&gt;$M \lll N$&lt;/span&gt;, then you could groups many atoms together into what are called &amp;quot;pseudo-atoms&amp;quot; and then you can do the simulation on the &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; resulting pseudo-atoms (with a slight or not-so-slight loss of accuracy). For example when simulating a long DNA molecule, you might group each nucleotide as a single pseudo-atom, which seems quite reasonable since each nucleotide on its own will likely stick together as a unit and it's only the nucleotide's relative position with respect to other nucleotides that might change, the the DNA molecule comes into contact with DNA helicase, for example. This grouping of multiple atoms into a pseudo-atom, is all coarse-graining is.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;When I go to talks, I hear the statement &amp;quot;coarse-graining is required to access spatio-temporal scales to observe important dynamical behavior for stimuli-responsive systems&amp;quot; before they go on about coarse-graining methods and so on.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I guess for those &amp;quot;stimuli-responsive systems&amp;quot; the combination of the spatial scale (&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;) and temporal scale (&lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;) is large enough that coarse-graining is necessary to observe whatever those people think is &amp;quot;important&amp;quot; behavior.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My question is, what are these stimuli-responsive systems?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That term is independent of the term coarse-graining. You can coarse-grain any system, whether or not it's stimuli-responsive, and you can simulate a stimuli-responsive system with regular non-coarse-grained MD if you have enough time and computational resources.&lt;/p&gt;&#xA;&lt;p&gt;If you're interested in what stimuli-responsive systems are, perhaps you could ask a question specifically about that (since the title of this question is, &amp;quot;what kind of systems require coarse-graining&amp;quot;). The review paper published only 4 years ago, with title &amp;quot;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2017/py/c6py01585a&quot; rel=&quot;noreferrer&quot;&gt;Stimuli-responsive systems and their applications&lt;/a&gt;&amp;quot; may be a good start!&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Coarse-grained_modeling&quot; rel=&quot;noreferrer&quot;&gt;The Wikipedia article on Coarse-graining&lt;/a&gt; never even once uses the word stimuli or stimulus or response or responsive.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I have run simulations of PNIPAM and have seen its thermoresponsive behavior (coil-to-globule) collapse around 305 K, but all it took was a 100 ns simulation for about 35k particles, tops.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It sounds like you don't need to be coarse-graining at all to see that behavior in that system! 35k particles is still well within the limits of what we can do with non-coarse-grained MD!&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I assume we need to perform CG on more complicated systems, but specific to stimuli-response, what are these systems?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Exactly, we need to perform CG on larger and more complicated systems, or when we need to watch the dynamics for longer periods of time, and &amp;quot;stimuli-responive systems&amp;quot; would only be one type of system for which we would want to do coarse-graining, and I can imagine some &amp;quot;stimuli-responsive systems&amp;quot; don't require it at all, if you have enough computational resources.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Unless it is truly rigorous bottom-up CG, I am sometimes skeptical of the forcefields some people use, because the force-field is clearly biased to the problem they are trying to solve. You can coarse-grain frankly any macromolecule, but there has to be a phenomenon some experimentalist is observing that we can't seem to see by plain all-atom MD.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's fair for you to be skeptical, because some pretty coarse approximations are being made when coarse-graining (hence why it's called &amp;quot;coarse&amp;quot;-graining). I would agree with you that &lt;em&gt;&lt;strong&gt;when accuracy is important&lt;/strong&gt;&lt;/em&gt;, it should only be done when necessary (i.e. when doing plain all-atom MD is not worth it). But if accuracy is not important at all, it might even be the case that all-atom MD is like cracking a nut with a sledgehammer.&lt;/p&gt;&#xA;&lt;p&gt;If you need to know what specific systems/phenomena require simulations that are currently out of reach for all-atom MD and do require coarse-graining, this may be a good question to ask with a title like &amp;quot;what are some interesting examples where coarse-graining was necessary and all-atom MD was infeasible?&amp;quot; with the &lt;a href=&quot;/questions/tagged/reference-request&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;reference-request&amp;#39;&quot; rel=&quot;tag&quot;&gt;reference-request&lt;/a&gt;&#xA;tag (rather than &amp;quot;What &lt;em&gt;&lt;strong&gt;kind&lt;/strong&gt;&lt;/em&gt; of systems...&amp;quot;). If you're specifically interested in &amp;quot;stimuli-responsive&amp;quot; systems, you could ask a question with that in the title.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-18T05:39:03.560" LastActivityDate="2021-11-18T05:39:03.560" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7100" PostTypeId="5" CreationDate="2021-11-18T06:00:47.657" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.ovito.org/manual/introduction.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;OVITO&lt;/a&gt;&#xA;&lt;a href=&quot;https://ovito.org/manual/python/introduction/running.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;OVITO's Python interface&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="1609" LastEditDate="2022-01-03T16:29:34.567" LastActivityDate="2022-01-03T16:29:34.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7101" PostTypeId="4" CreationDate="2021-11-18T06:00:47.657" Score="0" Body="Questions about or related to the OVITO software or its Python interface." OwnerUserId="5" LastEditorUserId="1609" LastEditDate="2022-01-03T16:29:20.263" LastActivityDate="2022-01-03T16:29:20.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7102" PostTypeId="5" CreationDate="2021-11-18T06:10:34.580" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/AMBER&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/AMBER&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-18T06:10:34.580" LastActivityDate="2021-11-18T06:10:34.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7103" PostTypeId="4" CreationDate="2021-11-18T06:10:34.580" Score="0" Body="Questions about or related to the AMBER software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-18T06:10:34.580" LastActivityDate="2021-11-18T06:10:34.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7104" PostTypeId="1" AcceptedAnswerId="7115" CreationDate="2021-11-18T11:21:27.550" Score="9" ViewCount="248" Body="&lt;p&gt;I have seen that &lt;a href=&quot;https://doi.org/10.1039/C6TC00409A&quot; rel=&quot;nofollow noreferrer&quot;&gt;some articles&lt;/a&gt; calculate Hubbard &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; value self-consistently using &lt;strong&gt;Quantum Espresso&lt;/strong&gt; code. Then, they use it in &lt;strong&gt;VASP&lt;/strong&gt; calculations. My question is: &lt;em&gt;In which conditions can this value be transferred from a code to another?&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-11-20T12:18:25.287" LastActivityDate="2021-11-21T20:58:21.547" Title="In which conditions can the self-consistent Hubbard U value calculated using Quantum Espresso be used for other VASP calculations?" Tags="|vasp|quantum-espresso|dft-u|hubbard-model|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7105" PostTypeId="2" ParentId="7065" CreationDate="2021-11-18T14:21:12.747" Score="8" Body="&lt;p&gt;&lt;strong&gt;The commandline scales, a GUI doesn't&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There have been some excellent answers so far, but I'd like to add a general one. I'm a computational biology researcher, so different field, but we spend considerable effort teaching Phd and Msc students how to use commandline tools. Why? Because they let you do bigger computation.&lt;/p&gt;&#xA;&lt;p&gt;A GUI is great, until you've outstripped the available compute power of the computer or server you're working on. Then, suddenly, you're into an High Performance Compute Environment. Even a university one is unlikely to have a way of handling a GUI. If it does, it will be clunky, and not let you get the most out of the jobs you're writing.&lt;/p&gt;&#xA;&lt;p&gt;If you have to go up another step, to something like a national tier cluster, there is no chance of a GUI. Jobs you submit are tightly controlled, and extremely automated. Lessons you learnt while getting the previous steps to work are vital here.&lt;/p&gt;&#xA;&lt;p&gt;Commercial companies often supply GUIs. This generally is because their next computing tier is a cloud based thing, normally accessed through a website. There's also a certain amount of value for them in obfuscating a little what their software is doing in the background, either because it's commercially sensitive, or because the tools they are using are freely available elsewhere.&lt;/p&gt;&#xA;&lt;p&gt;The other point to note is on reproducibility. A script or a series of commands is great here. When you come to publish your paper, the exact script you used can be included in the appendix or methods. Along with the (versioned) list of software you used, and the original data files, a person reading the paper should have no problem recreating precisely what you did. This isn't possible with a GUI. Do you remember which buttons you clicked three months ago when you've come to publish?&lt;/p&gt;&#xA;&lt;p&gt;So, I think, at least for research environments, we prefer commandline. It keeps a consistent experience through the whole project, and hopefully means you can take a script from start, to bigger compute environments, to publication.&lt;/p&gt;&#xA;" OwnerUserId="3789" LastEditorUserId="7" LastEditDate="2021-11-18T18:56:13.210" LastActivityDate="2021-11-18T18:56:13.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7106" PostTypeId="2" ParentId="7098" CreationDate="2021-11-18T22:08:24.553" Score="6" Body="&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7099/24&quot;&gt;answer&lt;/a&gt; given by @NikeDattani is very complete.&lt;/p&gt;&#xA;&lt;p&gt;My two cents...&lt;/p&gt;&#xA;&lt;p&gt;As the systems get bigger and bigger and the computational resources, even with the GPU development, doesn't grow in the same speed, we need to use some approximations if we want to get some knowledge of the system behavior.&lt;/p&gt;&#xA;&lt;p&gt;It is very common to think that molecular dynamics is only used in biological system but every day we found application to Condensed Matter problems. An example is the work of &lt;a href=&quot;https://doi.org/10.1038/s41467-017-00017-5&quot; rel=&quot;noreferrer&quot;&gt;Shibuta &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; where they simulate the nucleation of billion iron atoms. Another example is the workflow developed by &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.104.035120&quot; rel=&quot;noreferrer&quot;&gt;Ellis &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; to compute DFT electronic structure at finite temperatures (a mix of molecular dynamics, DFT calculations and neural networks).&lt;/p&gt;&#xA;&lt;p&gt;Whether the force-fields are a &amp;quot;bottle neck&amp;quot; for all atom molecular dynamic, in case of coarse-grained it is more delicate. You need not only parameters for the atoms but also for how the atoms are grouped. The image below is an example of how the &lt;a href=&quot;http://cgmartini.nl/index.php&quot; rel=&quot;noreferrer&quot;&gt;Martini General Purpose Coarse-Grained Force Field&lt;/a&gt; do some mapping. Due to that, the experimental validation is heavy and the number of available parametrized system is limited (even when you can parametrize your own structure).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aEDCg.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aEDCg.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;br /&gt;&#xA;Here: (A) Standard water particle representing four water molecules, (B) Polarizable water molecule with embedded charges, (C) DMPC lipid, (D) Polysaccharide fragment, (E) Peptide, (F) DNA fragment, (G) Polystyrene fragment, (H) Fullerene molecule. In all cases Martini CG beads are shown as cyan transparent beads overlaying the atomistic structure.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-11-18T22:08:24.553" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7107" PostTypeId="2" ParentId="7047" CreationDate="2021-11-18T22:33:21.647" Score="4" Body="&lt;h2&gt;NANOCUT&lt;/h2&gt;&#xA;&lt;p&gt;What is Nanocut?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Nanocut is a program designed to cut out various objects from three&#xA;dimensional crystal structures. It is aimed to be helpful when&#xA;creating geometry input for atomistic simulations. Currently it can&#xA;create following objects:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Spherical cluster&lt;/li&gt;&#xA;&lt;li&gt;Polyhedral cluster&lt;/li&gt;&#xA;&lt;li&gt;Cylindrical cluster&lt;/li&gt;&#xA;&lt;li&gt;Spherical wire (1D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Polyhedral wire (1D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Plain slab (2D periodic)&lt;/li&gt;&#xA;&lt;li&gt;Supercells (3D periodic)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The manual of NANOCUT can be seeing &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/downloads/manual-12.12.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;br /&gt;&#xA;The repository is &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/src/master/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;br /&gt;&#xA;The program can be downloaded &lt;a href=&quot;https://bitbucket.org/aradi/nanocut/downloads/nanocut-12.12.tar.gz&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-11-19T10:32:11.283" LastActivityDate="2021-11-19T10:32:11.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7108" PostTypeId="2" ParentId="7065" CreationDate="2021-11-18T23:41:10.477" Score="3" Body="&lt;p&gt;When I was a grad student, I mostly used used &lt;a href=&quot;https://en.wikipedia.org/wiki/Molden&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molden&lt;/a&gt; for interactive visualization. I used &lt;a href=&quot;https://en.wikipedia.org/wiki/Wolfram_Mathematica&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mathematica&lt;/a&gt; code I wrote myself for generating input files for VASP and Gaussian, and used Mathematica for producing figures.&lt;/p&gt;&#xA;" OwnerUserId="4581" LastActivityDate="2021-11-18T23:41:10.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7109" PostTypeId="2" ParentId="7023" CreationDate="2021-11-19T00:49:43.240" Score="6" Body="&lt;p&gt;Part of your question was:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Does MP2 implicitly include any excitations that CCD does not (perhaps some single excitations)?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;From the expansion of the exponential form of the cluster operator, we achieve powers of the each excitation operator (see &lt;a href=&quot;http://staff.ulsu.ru/moliver/ref/qc/bart07.pdf&quot; rel=&quot;noreferrer&quot;&gt;this reference&lt;/a&gt;, pp.297). So it's in fact the other way around: CCD includes excitations that MP2 does not.&lt;/p&gt;&#xA;&lt;p&gt;Excitations alone don't make the final energies, though. Both MP and CC calculate a series of amplitudes to weigh their excitation terms to calculate an energy, and they go about it in different ways. Quantum chemistry programs do typically report both CC and MP energies when conducting CC calculations, however as user @wzkchem5 pointed out in response to my previous comments, those amplitudes are in fact actual MP results that are then used as starting guesses for the CC amplitudes; they are not calculated using the final CC amplitudes. (I guess it would be interesting to see what would happen if one were to use CC amplitudes to calculate MP2 energies, although that idea seem somewhat like &amp;quot;throwing pearls before pigs&amp;quot;.)&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As to a direct comparison of MP2 and CCD results, I found this reference:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/0301010486870914?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;Förner et al.: Coupled cluster studies. III. Comparison of the numerical behaviour of coupled cluster doubles with configuration interaction and perturbation theory. Basis set and geometry optimizations&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the conclusions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The results suggest that in most cases (besides pathological ones, e.g. related to large nuclear seperations), even when MP2 gives a larger correlation energy than CCD, the CCD results are of similar quality as those of MP4(DQ).&lt;br /&gt;&#xA;The equilibrium properties of the investigated molecules computed with CCD are as reliable as those obtained with CID (which is variational but not size consistent) and very similar to those computed with MP4(DQ) (...)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For the small test molecules used in this paper, CCD seems to perform somewhat comparably to MP4(DQ), which I suppose shouldn't come as too big of a surprise seeing as they include some of the same excitations. For that matter, it would be interesting to see a systematic comparison with even higher MP orders such as MP6(DQH) etc.&lt;/p&gt;&#xA;" OwnerUserId="1440" LastActivityDate="2021-11-19T00:49:43.240" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7111" PostTypeId="1" AcceptedAnswerId="7112" CreationDate="2021-11-20T06:46:30.667" Score="7" ViewCount="697" Body="&lt;p&gt;In orca it is possible to use NumFreq and AnFreq to get the numerical and analytical frequencies, but the analytical frequencies take a large amount of memory and computing time compared to numerical frequencies at large system sizes.&lt;/p&gt;&#xA;&lt;p&gt;Since NumFreq must perform 6N (N=# of atoms) displacements, is there any way to parallelize this?  Instead of using 48 cores to do 1 displacement, I would like to use 8 cores to 6 displacements all at once and combine the results.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-11-22T08:39:38.867" Title="Numerical Frequency Parallelization in ORCA" Tags="|vibrations|orca|high-throughput|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7112" PostTypeId="2" ParentId="7111" CreationDate="2021-11-20T09:20:08.600" Score="8" Body="&lt;p&gt;This is exactly what ORCA actually does. For example if you have 48 cores, then ORCA does 48 displacements at once, each using only a single core. This is trivial to implement and is one of the major advantages of a numerical frequency calculation as compared to analytical ones, so basically every program that supports numerical frequencies will support this feature. (EDIT: according to the OP, this feature appears to be less universally supported in periodic codes than in molecular codes.)&lt;/p&gt;&#xA;&lt;p&gt;By the way, at least for DFT, analytical frequencies should almost always be faster than numerical frequencies (see the benchmark results in &lt;a href=&quot;https://www.tandfonline.com/doi/full/10.1080/00268976.2015.1025114&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;). If you ever encountered the opposite case, it's likely that your coupled-perturbed SCF calculation encountered some convergence difficulties, or that you specified a too small %maxcore, or that the calculation is so memory-intensive that it starts to use your virtual memory.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2021-11-22T08:39:38.867" LastActivityDate="2021-11-22T08:39:38.867" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7113" PostTypeId="1" AcceptedAnswerId="7252" CreationDate="2021-11-20T12:10:49.147" Score="8" ViewCount="1072" Body="&lt;p&gt;In this &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2020.109820&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;, they have rotated the unit cell using a rotation matrix, so the axes are aligned with the atomic bonds. I would like to know how they calculated that rotation matrix, and which software to use to apply that rotation on a unit cell.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-12-13T21:12:39.873" Title="How to choose a proper rotation matrix and apply it to rotate unit cell about Cartesian axis" Tags="|vasp|crystallography|density-of-states|vesta|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="7114" PostTypeId="2" ParentId="4757" CreationDate="2021-11-20T17:51:01.690" Score="9" Body="&lt;p&gt;Maybe this comes a bit late. There are some tools which can do this. But I was also interested in doing such a calculation using python. I first started with an iterative process which was terribly slow. Calculating the distance matrix in scipy is much faster.&lt;/p&gt;&#xA;&lt;p&gt;The distance matrix alone is not very helpful. You have to check every distance with the sum of the covalent radii. Please check my solution for the bond lengths. Finding angles and dihedral angles is more difficult, since you have to check every connection from atom A to atom B and C (and D). This information is in the distance matrix, but more difficult to obtain.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python3&#xA;# -*- coding: utf-8 -*-&#xA;&#xA;import pandas as pd                                       &#xA;from scipy.spatial.distance import pdist, squareform     &#xA;import numpy as np                                      &#xA;import io      &#xA;&#xA;pd.set_option(&amp;quot;display.max_rows&amp;quot;, None, &amp;quot;display.max_columns&amp;quot;, None)&#xA;&#xA;cov_radii = {&#xA;      &amp;quot;C&amp;quot; : 0.78,&#xA;      &amp;quot;H&amp;quot; : 0.41,&#xA;      &amp;quot;O&amp;quot; : 0.66,&#xA;}&#xA;&#xA;xyz_file = &amp;quot;&amp;quot;&amp;quot;60&#xA;            Buckminsterfullerene  (C60 Bucky Ball)&#xA;            C      0.56182991    1.03720708   -3.34153745   &#xA;            C     -0.02867841   -0.20922332   -3.53733326   &#xA;            C      0.68868170   -1.41687735   -3.17419275   &#xA;            C      1.96798784   -1.33001731   -2.62971513   &#xA;            C      2.58298268   -0.03190141   -2.42580025   &#xA;            C      1.89418484    1.12766893   -2.77448204   &#xA;            C     -0.26911535   -2.36054907   -2.62920302   &#xA;            C      2.34254586   -2.18322716   -1.51766993   &#xA;            C      0.09052931   -3.17978756   -1.56143494   &#xA;            C      1.42288437   -3.08932569   -0.99437947   &#xA;            C      1.93147043    2.28439304   -1.89955106   &#xA;            C      3.33762840   -0.08283139   -1.18772874   &#xA;            C      3.37342937    1.02783673   -0.34763393   &#xA;            C      2.65606922    2.23549084   -0.71077448   &#xA;            C     -1.42982841   -0.40652370   -3.21677674   &#xA;            C     -0.22432522    2.13802273   -2.81706602   &#xA;            C     -2.18468203    0.65046195   -2.71318765   &#xA;            C     -1.56968716    1.94857800   -2.50927274   &#xA;            C      3.18903027   -1.41242386   -0.62647337   &#xA;            C      0.62215914    2.90882602   -1.92586946   &#xA;            C     -1.57842655   -1.73611615   -2.65552140   &#xA;            C     -2.12435266    2.52208091   -1.29751971   &#xA;            C      0.08957811    3.45949446   -0.76236333   &#xA;            C     -1.31157175    3.26219407   -0.44180686   &#xA;            C      0.84422386    3.40856444    0.47570821   &#xA;            C      2.10140370    2.80899380    0.50097868   &#xA;            C     -3.11943529    0.42168510   -1.62746090   &#xA;            C     -3.08214969    1.57840920   -0.75252997   &#xA;            C     -2.47596183   -1.95578408   -1.61302381   &#xA;            C     -3.26211692   -0.85496848   -1.08855240   &#xA;            C      2.47596171    1.95578403    1.61302382   &#xA;            C      3.26211681    0.85496841    1.08855240   &#xA;            C      3.11943527   -0.42168513    1.62746090   &#xA;            C      3.08214970   -1.57840928    0.75252996   &#xA;            C      2.12435273   -2.52208091    1.29751964   &#xA;            C      1.31157182   -3.26219401    0.44180679   &#xA;            C     -1.42288432    3.08932572    0.99437953   &#xA;            C     -2.34254574    2.18322716    1.51766996   &#xA;            C     -3.18903022    1.41242378    0.62647331   &#xA;            C     -3.37342947   -1.02783679    0.34763388   &#xA;            C     -3.33762837    0.08283136    1.18772868   &#xA;            C     -0.09052935    3.17978761    1.56143497   &#xA;            C     -0.84422391   -3.40856443   -0.47570819   &#xA;            C     -2.10140382   -2.80899386   -0.50097868   &#xA;            C      0.26911532    2.36054910    2.62920311   &#xA;            C      1.57842653    1.73611617    2.65552148   &#xA;            C     -0.08957818   -3.45949441    0.76236329   &#xA;            C     -2.65606930   -2.23549092    0.71077442   &#xA;            C     -2.58298263    0.03190137    2.42580019   &#xA;            C     -1.93147042   -2.28439306    1.89955101   &#xA;            C     -1.89418482   -1.12766893    2.77448197   &#xA;            C     -1.96798776    1.33001737    2.62971509   &#xA;            C     -0.62215921   -2.90882598    1.92586939   &#xA;            C     -0.68868164    1.41687744    3.17419279   &#xA;            C      0.22432525   -2.13802261    2.81706605   &#xA;            C      1.56968719   -1.94857793    2.50927279   &#xA;            C      2.18468202   -0.65046198    2.71318771   &#xA;            C     -0.56182981   -1.03720706    3.34153744   &#xA;            C      0.02867849    0.20922332    3.53733334   &#xA;            C      1.42982839    0.40652370    3.21677684  &#xA;            &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;#read xyz file&#xA;xyz_df = pd.read_csv(io.StringIO(xyz_file), &#xA;      delim_whitespace=True, &#xA;      skiprows=2, &#xA;      names=[&amp;quot;element&amp;quot;, &amp;quot;x&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;z&amp;quot;])&#xA;&#xA;#append a column with the covalent radii of the atoms&#xA;xyz_df['cov_rad'] = xyz_df.apply(lambda x: cov_radii[x.element], axis=1)&#xA;&#xA;#calculate the distance matrix&#xA;dist_mat=pd.DataFrame(squareform(pdist(xyz_df.iloc[:,1:4],'euclid')))&#xA;&#xA;#calculate the radii matrix&#xA;radii_sum_mat = pd.DataFrame([[x + y for x in xyz_df['cov_rad']] for y in xyz_df['cov_rad']])&#xA;&#xA;#fill diagonals with zero&#xA;#distance of atom 0 to atom 0 is zero&#xA;np.fill_diagonal(radii_sum_mat.values, 0)&#xA;&#xA;#print('\nDistance matrix:\n', dist_mat,'\n')&#xA;#print('Sum of the covalent radii:\n',radii_sum_mat,'\n')&#xA;&#xA;#becomes 'True' if the calculated disctance is lower than the sum of atomic radii&#xA;bond_mat_true = dist_mat &amp;lt; radii_sum_mat&#xA;#print('Is this atom bonded to the other atom:\n',bond_mat_true,'\n')&#xA;&#xA;#combine the distance matrix with the 'True' or 'False' bond table&#xA;bond_mat = dist_mat.combine(bond_mat_true,np.multiply)&#xA;&#xA;#only one pair is needed, since bond length A-B = bond length B-A are equal&#xA;bond_mat.values[np.triu_indices_from(bond_mat, k=1)] = np.nan&#xA;&#xA;#replace zeros with nan&#xA;bond_mat = bond_mat.replace(0, np.nan)&#xA;&#xA;#drop all nan&#xA;bond_mat = bond_mat.unstack().dropna()&#xA;&#xA;print('Atom_x is bonded to Atom_y &amp;amp; bond length:\n', bond_mat)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4585" LastActivityDate="2021-11-20T17:51:01.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7115" PostTypeId="2" ParentId="7104" CreationDate="2021-11-21T20:58:21.547" Score="8" Body="&lt;p&gt;I have looked into this a bit, I think in general it is ill-advised to mix codes like this unless it is needed, but VASP does not support self-consistent hubbard U (no perturbations at non-zero U).  As long as you can prove the two codes produce the same results, it is probably okay.  Specifically, if you can prove the property of interest is the same at U=0 and U=U&lt;sub&gt;scf&lt;/sub&gt;, then I would not be too skeptical though.&lt;/p&gt;&#xA;&lt;p&gt;The main issue here is the U parameter is dependent on everything about the system.  Energy cutoff, grids, psuedopotentials, etc. could all make a difference so it should probably not be directly used without checking that band gap is the same for example.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-11-21T20:58:21.547" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7116" PostTypeId="1" CreationDate="2021-11-21T22:30:42.807" Score="5" ViewCount="330" Body="&lt;p&gt;How well can DFT, as implemented in VASP, describe surface reactions?&lt;/p&gt;&#xA;&lt;p&gt;For example, I want to study the hydrogen evolution reaction (HER) on the &lt;span class=&quot;math-container&quot;&gt;$(111), (110), (100) \text{ and } (011)$&lt;/span&gt; surface planes of Cobalt (III) Phosphide &lt;span class=&quot;math-container&quot;&gt;$\ce{CoP}$&lt;/span&gt;. Assuming I have optimized bare surface geometries, can I expect reasonable energetics for hydrogen production using DFT calculations of the energy and surface bound geometries?&lt;/p&gt;&#xA;" OwnerUserId="4270" LastEditorUserId="7" LastEditDate="2022-01-24T18:00:22.263" LastActivityDate="2022-02-07T13:39:58.183" Title="Using DFT to study Hydrogen Evolution Reaction on a surface?" Tags="|density-functional-theory|vasp|computational-chemistry|surfaces|hydrogen-bonds|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="7117" PostTypeId="2" ParentId="7001" CreationDate="2021-11-22T01:12:40.770" Score="5" Body="&lt;p&gt;The electronic relaxation time cannot be predicted from the band-structure alone, because it depends on additional physics. The dominant mechanism for electron relaxation in materials is usually the interaction with phonons (atomic vibrations). In order to compute the relaxation time, therefore, you need to compute the electron-phonon coupling.&lt;/p&gt;&#xA;&lt;p&gt;In density functional theory-based software, the electron-phonon matrix elements are usually approximated by the Kohn-Sham particle-phonon interactions, and are computed either semi-analytically (from density functional perturbation theory (DFPT)) or fully numerically (from a finite-displacement calculation). In either case, it is often quite computationally intensive to compute the electron-phonon coupling, since you need to sample the Brillouin zone well for both Kohn-Sham states and phonons. The relaxation time you get also depends on both the energy, E, and momentum, k, of the state.&lt;/p&gt;&#xA;&lt;p&gt;In many practical cases, the relaxation rate is dominated by phonons with small wavevectors (long wavelengths) and low energies, and a reasonable approximation is to restrict the calculation to those phonons. This is the basis of the deformation potential method, and in particular acoustic deformation potential theory, where we further restrict the calculation to the acoustic phonons (lowest energy phonons).&lt;/p&gt;&#xA;&lt;p&gt;The key concept in deformation potential theory is to note that if the phonon's wavelength is long enough, the corresponding displacement in any particular unit cell is almost exactly the same as that in adjacent unit cells, and we can model it with a perfectly periodic displacement. For the acoustic modes, all the atoms are moving together and the corresponding displacements may be modelled by straining the unit cell. The calculation itself is almost identical to a calculation of the elastic constants of the material, except that it is the valence and conduction band edges which are important, and how they change under the different acoustic phonons (i.e. the strains).&lt;/p&gt;&#xA;&lt;p&gt;In addition to the deformation potential itself, you also need to know the effective mass of the electrons which, again, is usually approximated by the effective mass of the Kohn-Sham states, computed from the band-curvature around the valence and conduction band edges.&lt;/p&gt;&#xA;&lt;p&gt;Computing relaxation times from deformation potential theory is an approximation, but it is often fairly accurate and only requires the strain-response of the N-atom unit cell, not all 3N phonon modes, meaning that it is much quicker to compute and scales as a ground state calculation with the number of atoms.&lt;/p&gt;&#xA;&lt;p&gt;Review paper for electron-phonon calculations in DFT:&lt;/p&gt;&#xA;&lt;p&gt;F. Giustino, ``Electron-phonon interactions from first principles'',&#xA;Rev. Mod. Phys. 89, 015003&lt;/p&gt;&#xA;&lt;p&gt;Original deformation potential theory papers:&lt;/p&gt;&#xA;&lt;p&gt;J. Bardeen and W. Shockley, ``Deformation Potentials and Mobilities in Non-Polar Crystals,'' Physical Review, vol. 80, no. 1, pp. 72-80, Oct 1950.&lt;/p&gt;&#xA;&lt;p&gt;C. Herring and E. Vogt, &lt;span class=&quot;math-container&quot;&gt;``&lt;/span&gt;Transport and Deformation-Potential Theory for Many-Valley Semiconductors with Anisotropic Scattering,'' Physical Review, vol. 101, no. 3, pp. 944-961, 1956.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-11-22T01:12:40.770" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7118" PostTypeId="1" CreationDate="2021-11-22T12:32:13.337" Score="5" ViewCount="1468" Body="&lt;p&gt;In spin-polarized calculation,total magnetic moment can be fixed to a specific value using &lt;code&gt;NUPDOWN&lt;/code&gt; tag. In non-colinear spin calculation, tag &lt;code&gt;I_CONSTRAINED_M = 1 or 2&lt;/code&gt; and can be used to contained direction and magnitude of magnetic moment. Neither of above two tag can fix local magnetic moment to fixed value. Is there any way to fix local magnetic moment to specific value? or Kindly suggest some changes in  &lt;code&gt;INCAR&lt;/code&gt; given below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;POSCAR&#xA;3.50&#xA;1 0 0&#xA;0 1 0&#xA;0 0 1&#xA;  Fe&#xA;  4&#xA;Direct&#xA;0 0 0&#xA;0.5 0.5 0&#xA;0.5 0 0.5&#xA;0 0.5 0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM = FCC&#xA;ISTART=0         # start new job&#xA;ICHARG=2         # 2 for atom&#xA;INIWAV=1         # initial wave function&#xA;ENCUT= 400.00 eV # Energy cut-off for calculation&#xA;LREAL= Auto   # real space projection .FALSE.&#xA;LCHARG= .FALSE  # no charge file output&#xA;ALGO=F&#xA;PREC=A&#xA;NCORE=8&#xA;KPAR=4&#xA;MAGMOM=0 0 1 0 0 -1 0 0 1 0 0 -1&#xA;ISYM=-1&#xA;LWAVE= .FALSE    # no wavefile output&#xA;ISMEAR = 1;     # tetrahedron method with Bloech 1 correction&#xA;SIGMA = 0.1      # smearing value&#xA;ISPIN=2         # Spin Polarisation&#xA;NELM=200         # Maximum number of iteration&#xA;NELMIN=3         # Minimum number of iteration&#xA;NSW=300          # number of step for ionic update&#xA;EDIFF=1E-4       # stopping criteria for electronic update&#xA;EDIFFG=-0.02&#xA;ISIF=3&#xA;IBRION=2&#xA;LORBMOM = .TRUE.&#xA;#NUPDOWN=0&#xA;I_CONSTRAINED_M=2&#xA;LNONCOLLINEAR = .TRUE.&#xA;M_CONSTR= 0 0 1 0 0 -1 0 0 1 0 0 -1&#xA;#ADDGRID=T&#xA;LORBIT=11&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;OUTPUT&lt;/em&gt; &lt;code&gt;OSZICAR&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   2 F= 0.65080119E+03 E0= 0.65080992E+03  d E =0.678114E+03  mag=     0.8391    -0.2230    -1.7841&#xA;   3 F= -.31196102E+02 E0= -.31191802E+02  d E =-.388330E+01  mag=    -5.0040    10.2547     2.8772&#xA;   4 F= -.31256210E+02 E0= -.31248490E+02  d E =-.394341E+01  mag=    -5.0955    10.5249     2.6127&#xA;   5 F= -.31250190E+02 E0= -.31243811E+02  d E =-.393739E+01  mag=    -5.0849    10.5771     2.5370&#xA;   6 F= -.31248427E+02 E0= -.31241528E+02  d E =-.393563E+01  mag=    -5.0749    10.5611     2.5074&#xA;   7 F= -.31256719E+02 E0= -.31250763E+02  d E =-.394392E+01  mag=    -5.1238    10.5592     2.4966&#xA;   8 F= -.31241928E+02 E0= -.31235361E+02  d E =-.392913E+01  mag=    -5.1036    10.5743     2.4683&#xA;   9 F= -.31250870E+02 E0= -.31243907E+02  d E =-.393807E+01  mag=    -5.1712    10.5782     2.3745&#xA;  10 F= -.31230308E+02 E0= -.31233397E+02  d E =-.391751E+01  mag=    -4.8791    10.5239     2.3687&#xA;  11 F= -.31234520E+02 E0= -.31229874E+02  d E =-.392172E+01  mag=    -4.8841    10.4645     2.4477&#xA;  12 F= -.30748687E+02 E0= -.30743533E+02  d E =-.343589E+01  mag=    -4.8649    10.4377     2.2561&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2021-11-22T12:40:29.820" LastActivityDate="2021-11-22T16:12:30.817" Title="How to fix local magnetic moment of each ions in VASP?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7120" PostTypeId="1" AcceptedAnswerId="7168" CreationDate="2021-11-22T15:47:09.647" Score="11" ViewCount="268" Body="&lt;p&gt;I have frequently come across MEAM potentials in my work, but I lack an intuitive understanding of what they do.&lt;/p&gt;&#xA;&lt;p&gt;What's a good qualitative description of a MEAM potential function?&lt;/p&gt;&#xA;" OwnerUserId="4220" LastActivityDate="2023-01-27T12:08:41.800" Title="Qualitatively, How do MEAM Potentials Work?" Tags="|interatomic-potentials|soft-question|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7121" PostTypeId="2" ParentId="7118" CreationDate="2021-11-22T16:12:30.817" Score="2" Body="&lt;p&gt;As far as I am aware, this is simply not implemented in VASP. This is a tricky thing for codes to do correctly, so you will need to just converge to the correct state.  You may overestimate some magnetic moments so they relax to their correct state.  You can also try a range of NUPDOWN.&lt;/p&gt;&#xA;&lt;p&gt;Its possible that you should be using a different approach though.  Fixing all magnetic moments is something you really shouldn't be doing outside of debugging calculations.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-11-22T16:12:30.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7123" PostTypeId="2" ParentId="7120" CreationDate="2021-11-22T16:59:03.793" Score="10" Body="&lt;p&gt;In short, it is a semi-empirical approach to atom/atom interaction for periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;It is based on the embedded atom method (EAM) idea where &amp;quot;the energy of a given atom is taken as one half the energy in two-body bonds with its neighboring atoms plus the energy to embed the atom in the electron density at its site arising from all the other atoms&amp;quot; [1,2].&lt;/p&gt;&#xA;&lt;p&gt;The MEAM is a modification of EAM [3]. The main modifications were the &lt;em&gt;ad hoc&lt;/em&gt; inclusion of the differences between metallic and covalent bonding [3].&lt;/p&gt;&#xA;&lt;p&gt;It had been applied to FCC, BCC, diamond cubic, and gaseous materials [4] and to HPC metals [5].&lt;/p&gt;&#xA;&lt;p&gt;[1] M.S. Daw and M.I. Baskes, &lt;em&gt;Semiempirical, Quantum Mechanical Calculation of Hydrogen Embrittlement in Metals&lt;/em&gt;, Phys. Rev. Lett. 50 1285 (1983). &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.50.1285&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevLett.50.1285&lt;/a&gt;&lt;br /&gt;&#xA;[2] M.S. Daw and M.I. Baskes, &lt;em&gt;Embedded-atom method: Derivation and application to impurities, surfaces, and other defects in metals&lt;/em&gt;, Phys. Rev. B. 29 644 (1984). &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.29.6443&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.29.6443&lt;/a&gt;&lt;br /&gt;&#xA;[3] M.I. Baskes, J.S. Nelson, and A.F. Wright, Semiempirical modified embedded-atom potentials for silicon and germanium, Phys. Rev. B. 40, 6085 (1989). &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.40.6085&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.40.6085&lt;/a&gt;&lt;br /&gt;&#xA;[4] M.I. Baskes, Modified embedded-atom potentials for cubic materials and impurities, Phys. Rev. B. 46, 2727 (1992). &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.46.2727&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.46.2727&lt;/a&gt;&lt;br /&gt;&#xA;[5] M.I. Baskes and R.A. Johnson, Modified embedded atom potentials for HCP metals, Modelling Simul. Mater. Sci. Eng. 2 147 (1994). &lt;a href=&quot;https://doi.org/10.1088/0965-0393/2/1/011&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1088/0965-0393/2/1/011&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-11-22T16:59:03.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7124" PostTypeId="1" CreationDate="2021-11-23T06:10:19.573" Score="6" ViewCount="284" Body="&lt;p&gt;I have been trying to calculate Lattice Thermal Conductivity on my system using QuantumEspresso. I used phonopy and phono3py.&lt;/p&gt;&#xA;&lt;p&gt;I was successful to run these codes on Si system for practice. Now when I am trying to solve this on my material it is showing error.&lt;/p&gt;&#xA;&lt;p&gt;Since I am doing it on my own and new to it, I think I don't know how to change parameters for calculations.&lt;/p&gt;&#xA;&lt;p&gt;Please let me know which parameters I can change here (eg: conv_thr, mesh size, cutoff energy) and if I can take these parameters in non converged values since we are taking supercell in initial displacement calculation.&lt;/p&gt;&#xA;&lt;p&gt;If there is any paper or written material on this, I would like to read it.&lt;/p&gt;&#xA;&lt;p&gt;These are the errors I am getting in the step where I have to get output of the input of displacement positions. I have taken 2 2 2 supercell which is giving me 255 values and 4 4 4 supercell which is giving values as high as 1875. please let me know upto which supercell I can get my further correct calculations.&lt;/p&gt;&#xA;&lt;p&gt;Following are the errors I am getting in the output file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine cdiaghg (211):&#xA;     S matrix not positive definite&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&#xA;job aborted:&#xA;[ranks] message&#xA;&#xA;[0] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 0&#xA;&#xA;[1-3] terminated&#xA;&#xA;---- error analysis -----&#xA;&#xA;[0] on DESKTOP-683NPIM&#xA;pw aborted the job. abort code 1&#xA;&#xA;---- error analysis -----&#xA;&#xA;&#xA;&#xA;&#xA;error 2&#xA;&#xA;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine c_bands (1):&#xA;     too many bands are not converged&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&#xA;job aborted:&#xA;[ranks] message&#xA;&#xA;[0] terminated&#xA;&#xA;[1] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 1&#xA;&#xA;[2] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 2&#xA;&#xA;[3] application aborted&#xA;aborting MPI_COMM_WORLD (comm=0x44000000), error 1, comm rank 3&#xA;&#xA;---- error analysis -----&#xA;&#xA;[1-3] on DESKTOP-683NPIM&#xA;pw aborted the job. abort code 1&#xA;&#xA;---- error analysis -----&#xA;&#xA;The command prompt errors-&#xA;&#xA;MPI_ABORT was invoked on rank 3 in communicator MPI_COMM_WORLD&#xA;with errorcode 1.&#xA;&#xA;NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.&#xA;You may or may not see output from other processes, depending on&#xA;exactly when Open MPI kills them.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note: I also think this is also because of low RAM. What system requirements should be kept in mind?&lt;/p&gt;&#xA;&lt;p&gt;For the geometry in header file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation='scf'&#xA;    tprnfor = .true.&#xA;    pseudo_dir = '.'&#xA;    outdir='outt'&#xA;/&#xA;&amp;amp;system&#xA;    ibrav = 0,&#xA;    nat = 24,&#xA;    ntyp = 3,&#xA;    occupations = 'smearing'&#xA;    smearing = 'gaussian'&#xA;    degauss = 0.01&#xA;    ecutwfc = 100&#xA;/&#xA;&amp;amp;electrons&#xA;    diagonalization = 'cg'  &#xA;    conv_thr = 1.0d-10,&#xA;    mixing_beta = 0.7d0,&#xA;/&#xA;K_POINTS {automatic}&#xA;2 2 2 1 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My geometry optimization converged values for this material was at &lt;code&gt;ecutoff=40&lt;/code&gt;, &lt;code&gt;K_points=16*16*16&lt;/code&gt;. I also need to confirm if I can take here 2 2 2 1 1 1, at 16&lt;em&gt;16&lt;/em&gt;16 is the converged value and the computation will increase.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="7" LastEditDate="2021-11-25T14:12:12.967" LastActivityDate="2021-12-05T13:33:24.333" Title="Lattice Thermal conductivity calculation error" Tags="|density-functional-theory|ab-initio-calculations|phonopy|phono3py|lattice-thermal-conductivity|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7125" PostTypeId="1" AcceptedAnswerId="7175" CreationDate="2021-11-23T08:53:01.793" Score="8" ViewCount="928" Body="&lt;p&gt;I used to build some small molecules using Avogadro. Now, I want to build a large molecule, Graphene oxide which unfortunately doesn't have a definite structure with different levels of oxidation. Can someone please suggest me how can we build such single sheet/layer of Graphene Oxide (GO) on Avogadro or any other tools? I will be extremely grateful for any inputs/suggestions.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2021-11-30T01:16:25.687" Title="Building model of Graphene Oxide" Tags="|software-recommendations|molecular-modeling|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7126" PostTypeId="2" ParentId="7125" CreationDate="2021-11-23T09:26:56.423" Score="5" Body="&lt;p&gt;I think that drawing the molecular form should not be so hard, accordingly to the structure bellow.&lt;/p&gt;&#xA;&lt;p&gt;But, you can use the supplementary data from the reference below and download, the structures they use in their calculations, the modify it as your needs.&lt;/p&gt;&#xA;&lt;p&gt;Reference: F. Mouhat, F-X. Coudert, and M-L. Bocquetc, Structure and chemistry of graphene oxide in liquid water from first principles, Nature Communications volume 11, Article number: 1566 (2020). &lt;a href=&quot;https://dx.doi.org/10.1038/s41467-020-15381-y&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1038/s41467-020-15381-y&lt;/a&gt;.&lt;br /&gt;&#xA;Github data repository can be downloaded &lt;a href=&quot;https://github.com/fxcoudert/citable-data/tree/master/122-Mouhat_NatureCommun_2020&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;br /&gt;&#xA;Full trajectory data can be donwloaded from &lt;a href=&quot;https://doi.org/10.5281/zenodo.3736713&quot; rel=&quot;noreferrer&quot;&gt;Zenodo&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/46Fjb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/46Fjb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-11-23T09:26:56.423" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7127" PostTypeId="1" AcceptedAnswerId="7128" CreationDate="2021-11-23T15:52:26.143" Score="5" ViewCount="172" Body="&lt;p&gt;For two organic molecules of essentially unlimited size (up to and including, and sometimes exceeding MW = 1000 g/mol), I would like to generate all possible dimer pairs in vacuum. The pairs may be heterogeneous, so there could be one molecule of MW=1000 g/mol paired with something that is only MW=50 g/mol.&lt;/p&gt;&#xA;&lt;p&gt;The objective is to find the lowest energy (preferably lowest free energy) dimer pair, in vacuum. The energy minimization I would count as an additional step. Given a set of dimer pairs I can take care of screening energies on my own, but if it will do it, so much the better.&lt;/p&gt;&#xA;&lt;p&gt;This sort of thing is routinely done for crystal structure prediction, where one generates unit cells, and then crystals. Is it perhaps best to retrofit the more complex operation of crystal structure prediction in something like PyXtal.py, COMPACK, GLEE etc, as examples, to request only dimers rather than all possible crystal structures?&lt;/p&gt;&#xA;&lt;p&gt;Bonus if the software is open source and MIT licence.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="3606" LastEditDate="2021-11-24T19:30:10.537" LastActivityDate="2021-11-24T19:30:10.537" Title="Software for generating ensembles of dimer pairs of organic molecules" Tags="|software-recommendations|geometry-optimization|open-source|potential-energy-surface|free-energy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7128" PostTypeId="2" ParentId="7127" CreationDate="2021-11-23T19:48:13.733" Score="8" Body="&lt;p&gt;Generating &lt;em&gt;all&lt;/em&gt; possible structures systematically might be difficult. When it comes to the generation and refinement of chemically useful structure guesses, I'd recommend looking into &lt;a href=&quot;https://github.com/grimme-lab/crest&quot; rel=&quot;noreferrer&quot;&gt;CREST&lt;/a&gt; by Stefan Grimme. It will sample your entire structure space, i.e, not only intermolecular docking motifs, but also intramolecular conformations. It uses an MM approach with some additional biasing and crossover techniques to sample the total conformational search space. Beware though that with large enough problems, it will still be difficult to judge how complete your coverage of that search space is.&lt;/p&gt;&#xA;" OwnerUserId="1440" LastActivityDate="2021-11-23T19:48:13.733" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7129" PostTypeId="2" ParentId="4983" CreationDate="2021-11-23T22:31:40.810" Score="5" Body="&lt;p&gt;I think my understanding on this problem has improved somewhat. Let me try to clarify my confusions. If anyone sees issues with this reasoning, please let me know.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The idea of phases in this context is related to the Chern number &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;, in the context of topological/Chern insulators. The answer to this question would require computing the Chern number and associating with it some physical meaning (ex: &lt;span class=&quot;math-container&quot;&gt;$c=0$&lt;/span&gt; trivial, &lt;span class=&quot;math-container&quot;&gt;$c=\pm 1$&lt;/span&gt; non-trivial).&lt;/li&gt;&#xA;&lt;li&gt;The confusion here is that I am considering two different contexts. A regular gap closing may be thought of in the context of a band diagram in a Brillouin zone, whereas edge states are associated with the interface between two different kinds of materials (or phases, using the language in 1. above). In this case, we may consider a domain wall, associated with gap closings (such as when &lt;span class=&quot;math-container&quot;&gt;$M(x)=0$&lt;/span&gt; at the point where &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;lt;0$&lt;/span&gt; transitions to &lt;span class=&quot;math-container&quot;&gt;$M(x)&amp;gt;0$&lt;/span&gt;, in this model). If the Chern number of each region in 1. above is different in these two regions, we may see topologically protected edge states.&lt;/li&gt;&#xA;&lt;li&gt;The last line in 2. above relates to this question. The answer lies in the bulk-boundary correspondence, which relates the difference in Chern numbers (bulk topological indices) to the number of edge states (usually follows from analytic computations).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;My main confusion was that, in my simulations, I plotted the band diagrams using &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; matrices for varying values of &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt;: I calculated the eigenvalues for each iteration of &lt;span class=&quot;math-container&quot;&gt;$M(x)$&lt;/span&gt; and plotted them all together at the end. Instead, for this domain wall problem, I should have chosen some real-space geometry, and used the tight-binding formalism to construct a huge Hamiltonian which then yields the band structure once diagonalized.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-11-23T22:31:40.810" CommentCount="0" CommunityOwnedDate="2021-11-23T22:31:40.810" ContentLicense="CC BY-SA 4.0" />
  <row Id="7130" PostTypeId="1" CreationDate="2021-11-24T10:53:32.743" Score="9" ViewCount="252" Body="&lt;p&gt;I am using Quantum-Espresso and I need to study mott-insulator.&#xA;Being a beginner, I am not sure, how do I confirm whether my system is a mott-insulator or not?&lt;/p&gt;&#xA;" OwnerUserId="789" LastActivityDate="2021-11-25T19:15:17.660" Title="How to confirm whether a system is mott-insulator or not from DFT calculations?" Tags="|density-functional-theory|quantum-espresso|mott-insulator|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7131" PostTypeId="2" ParentId="7044" CreationDate="2021-11-24T12:51:41.773" Score="5" Body="&lt;p&gt;The two different files contain different things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;*.fullBZ.WFSX&lt;/code&gt; contains all wavefunctions for the SCF sampled Brillouin zone, i.e. for all k-points defined in the &lt;code&gt;kgrid.MonkhorstPack&lt;/code&gt; block.&#xA;The k-point order can manually be inferred from the &lt;code&gt;KP&lt;/code&gt; file.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*bands.WFSX&lt;/code&gt; contains the wavefunctions for the bandstructure sampled Brillouin zone, i.e. from the blocks &lt;code&gt;BandLines&lt;/code&gt; or &lt;code&gt;BandPoints&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Since you are interested in the Fermi-level and that the band-structure contains the Fermi-level this would be easier to deal with, but both contains the relevant information in this case.&lt;/p&gt;&#xA;&lt;p&gt;I would however suggest you used &lt;a href=&quot;https://www.github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt; (disclaimer, I am the author) for reading wavefunction coefficients and coop analysis.&lt;/p&gt;&#xA;&lt;p&gt;Something like this would suffice:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import sisl&#xA;H = sisl.get_sile(&amp;quot;RUN.fdf&amp;quot;).read_hamiltonian()&#xA;wfsx = sisl.get_sile(&amp;quot;*.fullBZ.WFSX&amp;quot;, parent=H)&#xA;&#xA;E = np.linspace(-2, 2, 201)&#xA;for es in wfsx.yield_eigenstate():&#xA;    print(es.info[&amp;quot;k&amp;quot;])&#xA;    print(es.COOP(E))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which will print COOP curves for &lt;em&gt;every&lt;/em&gt; eigenstate contained in the WFSX file. Then you can selectively decide which ones you want.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2021-11-24T12:51:41.773" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7132" PostTypeId="2" ParentId="6957" CreationDate="2021-11-24T13:03:30.060" Score="4" Body="&lt;p&gt;Identification of bands belonging to specific atoms is generally easiest done by using the so-called fatbands.&lt;/p&gt;&#xA;&lt;p&gt;Basically the fatbands is a projected DOS analysis for each individual band.&#xA;The projected DOS can then be summed over specific orbitals to see the weight on each atom. Generally states are wide-spread and so determining whether a state has a &lt;em&gt;large&lt;/em&gt; weight on specific sites may be difficult to quantify due to the relative nature of the states.&lt;br /&gt;&#xA;In some cases the weight is very clearly localized in which case the projected weight on the atoms should be 1 (fully localized).&lt;/p&gt;&#xA;&lt;p&gt;Something to consider when comparing projected weights for sites is that a system of &lt;code&gt;N&lt;/code&gt; sites (orbitals) will have a weight of &lt;code&gt;1/N&lt;/code&gt; for a fully delocalized state.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2021-11-24T13:03:30.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7133" PostTypeId="2" ParentId="7058" CreationDate="2021-11-24T13:04:38.960" Score="9" Body="&lt;p&gt;You can look at &lt;a href=&quot;https://iraspa.org/raspa/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RASPA&lt;/a&gt; by Snurr et al. (Dubbledam, Calero, Vlugt). It is made for gas adsorption and other simulations. They used to have a Fortran version called Music, but this is a revamped edition written in C.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/GOMC-WSU/GOMC&quot; rel=&quot;nofollow noreferrer&quot;&gt;GOMC&lt;/a&gt; is a GPU optimized Monte Carlo code for many things, adsorption is one of them. Likely a good starting place.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://sites.nd.edu/maginn-group/cassandra/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cassandra&lt;/a&gt; by Maginn et al. is also used for gas adsorption in crystalline materials. It is Monte Carlo. This also has interface to the &lt;a href=&quot;https://mosdef.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MoSDeF&lt;/a&gt; consortium.&lt;/p&gt;&#xA;&lt;p&gt;You can also look at &lt;a href=&quot;http://towhee.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Towhee&lt;/a&gt;. You can do gas adsorption via grand canonical simulations, and probably others. This used to be Monte Carlo, and I think still is. It may also do Molecular Dynamics.&lt;/p&gt;&#xA;&lt;p&gt;You can also use &lt;a href=&quot;https://www.ccp5.ac.uk/DL_MONTE&quot; rel=&quot;nofollow noreferrer&quot;&gt;DL Monte&lt;/a&gt;, another Monte Carlo software, for gas adsorption.&lt;/p&gt;&#xA;&lt;p&gt;Cory Simon's group also has software written in Julia for gas adsorption &lt;a href=&quot;https://github.com/SimonEnsemble&quot; rel=&quot;nofollow noreferrer&quot;&gt;Simon Ensemble Git Repo&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you are after a program that can interface, I would lean towards Cassandra or RASPA since Cassandra has an interface to MoSDeF. There is a Monte Carlo code called &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jcim.0c00334&quot; rel=&quot;nofollow noreferrer&quot;&gt;BRiCK&lt;/a&gt; written by several authors involved in RASPA, and as such, there is a high probability of interfacing the two. Unfortunately for RASPA, while I have not used it myself, I know people who have, and they almost went insane :S&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately adsorption is largely done via Monte Carlo folks, and Monte Carlo software has not garnered the attention that Molecular Dynamics software has, so you won't find really high end software comparable to Gromacs/OpenMM/LAMMPS/AMBER/NAMD etc.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="3606" LastEditDate="2021-12-06T14:47:11.803" LastActivityDate="2021-12-06T14:47:11.803" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7134" PostTypeId="1" AcceptedAnswerId="7262" CreationDate="2021-11-24T18:34:30.853" Score="8" ViewCount="273" Body="&lt;p&gt;I'd like to use the tight-binding model with a linear combination of atomic orbitals.&lt;/p&gt;&#xA;&lt;p&gt;It should show the full energy bands, as well as the spatial probability distribution for each eigenfunction of the Hamiltonian. Ideally it would be easy to use with many tunable parameters.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone recommend a software for this?&lt;/p&gt;&#xA;" OwnerUserId="4613" LastEditorUserId="5" LastEditDate="2021-11-24T20:20:08.333" LastActivityDate="2021-12-14T21:25:04.937" Title="Which software is suitable for visualizing the electron wavefunctions in a crystal?" Tags="|band-structure|software-recommendations|solid-state-physics|tight-binding|electron-density|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7135" PostTypeId="1" CreationDate="2021-11-24T18:39:43.857" Score="7" ViewCount="525" Body="&lt;p&gt;What open source solvers (according to the generally accepted &lt;a href=&quot;https://opensource.org/osd&quot; rel=&quot;nofollow noreferrer&quot;&gt;Open Source Definition&lt;/a&gt; i.e. licensed under a valid open source license) are available for full configuration interaction calculations? Ideally, I am looking for a package with a modular interface which could be easily included in quantum chemistry programs.&lt;/p&gt;&#xA;&lt;p&gt;The solver should be able to return density matrices, for instance, since those are needed for complete-active-space self-consistent-field (CASSCF) calculations. Ideally, the code should also scale up to billion-determinant calculations.&lt;/p&gt;&#xA;&lt;p&gt;Note again that this question is about open source packages, not proprietary programs.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2021-12-15T06:47:49.073" LastActivityDate="2021-12-15T06:47:49.073" Title="Open source FCI solvers for exact diagonalization of the many-electron Hamiltonian" Tags="|one-topic-per-answer|open-source|casscf|full-configuration-interaction|exact-diagonalization|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7136" PostTypeId="2" ParentId="7135" CreationDate="2021-11-24T18:39:43.857" Score="5" Body="&lt;h1&gt;FCI&lt;/h1&gt;&#xA;&lt;p&gt;Peter Knowles' FCI program, published in &lt;a href=&quot;http://doi.org/10.1016/0010-4655(89)90033-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computer Physics Communications, 54, 75 (1989)&lt;/a&gt;, is available at  &lt;a href=&quot;https://bitbucket.org/pjknowles/fci/src/master/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://bitbucket.org/pjknowles/fci/src/master/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code is Fortran 77 and can handle at least tens of millions of determinants. It uses FCIDUMP files as input.&lt;/p&gt;&#xA;&lt;p&gt;It appears that some other implementations of the algorithm are available, such as one by Knizia at &lt;a href=&quot;https://sites.psu.edu/knizia/software/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://sites.psu.edu/knizia/software/&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-11-25T03:06:12.677" LastActivityDate="2021-11-25T03:06:12.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7137" PostTypeId="2" ParentId="7135" CreationDate="2021-11-24T18:43:29.633" Score="5" Body="&lt;h1&gt;LUCIA / LUCITA&lt;/h1&gt;&#xA;&lt;p&gt;Jeppe Olsen's LUCIA / LUCITA code has been included in e.g. Dalton, which is nowadays open source. The code has been successfully used in calculations including over one billion determinants, &lt;a href=&quot;https://doi.org/10.1016/0009-2614(90)85633-N&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Phys. Lett. 169, 463 (1990)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A massively parallel version of thecode is in NWChem, and it has been used to solve (20e,20o) problems &lt;a href=&quot;https://doi.org/10.1063/1.4989858&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 147, 184111 (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, it doesn't look like the code is available as a separate module at the moment.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-11-25T03:04:54.937" LastActivityDate="2021-11-25T03:04:54.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7138" PostTypeId="2" ParentId="7135" CreationDate="2021-11-24T20:03:24.743" Score="6" Body="&lt;h1&gt;MRCC&lt;/h1&gt;&#xA;&lt;p&gt;One of my favorite FCI programs is the one in &lt;a href=&quot;https://www.mrcc.hu/MRCC/manual/html/single/manual_sp.xhtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;MRCC&lt;/a&gt;, because it has a few advantages over the MOLPRO FCI program (which uses the program you described &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7136/5&quot;&gt;in your answer&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;When the entire calculation fits in memory and can be done reasonably quickly, MOLPRO's FCI program probably offers the best combination of speed and convenience (selected CI programs like &lt;a href=&quot;https://sanshar.github.io/Dice/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dice&lt;/a&gt; and &lt;a href=&quot;https://github.com/QMC-Cornell/shci&quot; rel=&quot;nofollow noreferrer&quot;&gt;Arrow&lt;/a&gt; can get you the same numerical energy faster, but among other issues, require you to know what you're doing in terms of checking that the selected CI convergence parameters were selected appropriately).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However&lt;/strong&gt;, when the calculation does not fit in memory, MOLPRO doesn't offer much (or anything at all). The FCI program in MRCC will likely be a lot slower for small systems, but for large systems it will try various things to make the RAM requirements smaller, and surprisingly it can even be &lt;em&gt;&lt;strong&gt;faster&lt;/strong&gt;&lt;/em&gt; in some cases despite requiring less RAM. The reason it can be faster while still requiring less RAM, is because unlike MOLPRO which only offers CISD and FCI but nothing in between (except if you use the MRCC plug-in), MRCC calculates CISD, CISCDT, CISDTQ, CISDTQP, CISDTQPH, CISDTQPHS, CISDTQPHSO, etc. and &lt;em&gt;&lt;strong&gt;can use the previous CI calculation to give an initial guess for the next one.&lt;/strong&gt;&lt;/em&gt; Therefore CISD can be extremely fast, and then the result can be used as a starting guess for CISDT, and so on, meaning that fewer iterations are required (sometime close to zero of them, I mean, I'm sure I've seen the FCI step converge after 1 or 2 iterations because CISDTQPH was so close to being FCI, but I often worked with a small number of electrons in a big basis set rather than the other way around).&lt;/p&gt;&#xA;&lt;p&gt;So &lt;em&gt;&lt;strong&gt;not only&lt;/strong&gt;&lt;/em&gt; can MRCC's FCI program can make adjustments for large FCI calculations so that they don't require as much memory, &lt;em&gt;&lt;strong&gt;but the calculations can converge more quickly&lt;/strong&gt;&lt;/em&gt; if they start from (for example) a CISDTQ result, and &lt;em&gt;&lt;strong&gt;as a bonus&lt;/strong&gt;&lt;/em&gt;, you also get the CI(n) energies for all values of n (which can be helpful despite those energies not being size-consistent, for example if you can't get the FCI energy but you find that CISDTQ, CISDTQP, and CISDTQPH all agree to within 1 nano-hartree, then you can be confident that you have the FCI energy despite not having enough computing power to calculate it). &lt;em&gt;&lt;strong&gt;Additionally&lt;/strong&gt;&lt;/em&gt;, I've found MRCC's FCI program to be a lot better in terms of parallelization (the MOLPRO versions I used, required a factor of N more RAM in order to run on N cores, whereas this is far from the case for MRCC). &lt;em&gt;&lt;strong&gt;Finally,&lt;/strong&gt;&lt;/em&gt; when MOLPRO's FCI calculation crashes after several iterations, I found myself simply restarting the calculation from scratch because restarts never worked as smoothly for me as they do in MRCC. In MRCC, I found restarts to be the smoothest out of all electronic structure programs I've used.&lt;/p&gt;&#xA;&lt;p&gt;There's still disadvantages of MRCC over other programs, and one is the huge amount of disk space that it can use for temporary files. Also, the &lt;code&gt;FCIDUMP&lt;/code&gt; format isn't precisely followed, but I regularly convert between &lt;code&gt;FCIDUMP&lt;/code&gt; and MRCC's &lt;code&gt;fort.55&lt;/code&gt; format, and the other way around, using the method I described in my answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1648/5&quot;&gt;For software that does not support FCIDUMP format, what format is used and how can we get the software to interact with FCIDUMP integrals?&lt;/a&gt;. MRCC isn't available on GitHub, but you can get an academic license fairly easily, which means you'll get a password which allows you to download the entire source code.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/HPQC-LABS/FeMoco/blob/master/Reiher1/MRCC_out.1660024.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;I have done a CCSDTQ calculation in MRCC involving 28,466,110,261 &amp;gt; 28 billion configurations&lt;/strong&gt;&lt;/a&gt; (and coupled cluster calculations are far more expensive than CI ones, so you can probably imagine having close to 1 trillion FCI determinants). This calculation used 747.255 GB of RAM and 23 CPU cores (seemingly not the smartest number of cores to use, I know).&lt;/p&gt;&#xA;&lt;p&gt;Update: For butadiene &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/C4H10/summary.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;I found in 2019&lt;/a&gt; that CCSDTQP for butadiene (C4H6) requires 2.4T (when using 4 cores) to treat the 781605786195 (781 billion) excitaitons, which was well within the 3TB  available on some of the nodes on Cedar and Graham at &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1516/5&quot;&gt;Compute Canada&lt;/a&gt;, so I do believe 1 trillion CI determinants would not be out of the question. Unfortunately, as the comments say, MRCC is not open source though (just free and with the source available to users, but not re-distributable without permission from the Mihaly Kallay).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-15T06:33:03.980" LastActivityDate="2021-12-15T06:33:03.980" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="7139" PostTypeId="1" CreationDate="2021-11-24T20:36:43.057" Score="7" ViewCount="113" Body="&lt;p&gt;In classical MD simulations of lattice structures, whenever we are trying to incorporate vdW corrections to the atomic force calculation, we need to set up cutoff length beyond which the vdW correction is not considered to keep the computational cost manageable. As a result, &lt;strong&gt;the classical simulation requires reasonably large supercell(usually with its dimensions twice as long as the cutoff length) to capture vdW interactions&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;When it comes to DFT calculations, however, the cutoff lengths for nonlocal vdW corrections, such as the rVV10 functional, are not explicitly set in DFT software like Quantum ESPRESSO. It is also common practice to use &lt;strong&gt;primitive cells in DFT calculations along with nonlocal vdW functionals&lt;/strong&gt;. By looking at the formalism of the rVV10 vdW correction, the integration of the functional is clearly performed within a volume,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{c}^{n l}=\frac{\hbar}{2} \iint n(\mathbf{r}) \Phi\left(n, n^{\prime},|\nabla n|,\left|\nabla n^{\prime}\right|,\left|\mathbf{r}-\mathbf{r}^{\prime}\right|\right) n\left(\mathbf{r}^{\prime}\right) d \mathbf{r} d \mathbf{r}^{\prime},\tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; is the charge density at location of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;. So my question is &lt;strong&gt;what are the lower and upper limits for Eq. (1), and how do we derive them?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;To attack this question, I tried to understand Eq.(1) in terms of its Fourier transform,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{c}^{n l}=\frac{\hbar}{2} \Omega \sum_{i j} \sum_{\mathbf{G}} \tilde{\theta}_{i}^{*}(\mathbf{G}) \tilde{\Phi}^{\mathrm{rVV} 10}\left(q_{i}, q_{j},|\mathbf{G}|\right) \tilde{\theta}_{j}(\mathbf{G}),\tag{2}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\tilde{\Phi}^{\mathrm{rVV} 10}\left(q_{i}, q_{j},|\mathbf{G}|\right)$&lt;/span&gt; are the Fourier transforms of the rVV10 kernel evaluated on a bidimensional grid of &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; values, and &lt;span class=&quot;math-container&quot;&gt;$\tilde{\theta}_{i}$&lt;/span&gt; are the Fourier transforms of &lt;span class=&quot;math-container&quot;&gt;$\theta_{i}$&lt;/span&gt; introduced in the rVV10 paper &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.041108&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. But this left me with more questions than answers. I have a feeling that I might be pursuing the answer in a wrong line of thinking, so any hint will be appreciated!&lt;/p&gt;&#xA;&#xA;" OwnerUserId="2290" LastEditorUserId="5" LastEditDate="2022-01-20T22:25:41.807" LastActivityDate="2022-01-20T22:25:41.807" Title="Cutoff length for vdW correction in DFT calculation" Tags="|density-functional-theory|mathematical-modeling|dispersion-correction|derivations|" AnswerCount="0" CommentCount="15" ClosedDate="2023-02-07T03:06:03.660" ContentLicense="CC BY-SA 4.0" />
  <row Id="7140" PostTypeId="2" ParentId="7130" CreationDate="2021-11-25T08:24:15.267" Score="7" Body="&lt;p&gt;I am by no means a DFT expert, so another may be able to provide a better/more complete answer. Nevertheless...&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;short answer:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The local density approximation (or its leading gradient extension) do not hold in the limit of a Mott insulator. This being because the Mott insulator is constructed from occupying maximally-localized electron orbitals, and therefore the gradients of density are not guaranteed to be small. The density does not slowly vary like an electron fluid. So you will never observe a Mott insulator using QEspresso.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;perhaps way too long answer:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Density Functional Theory (DFT) works within what I would refer to as the &amp;quot;weak coupling&amp;quot; paradigm. By this, I mean that the interactions are considered to be small relative to the kinetic energy, such that the interactions can be introduced as a perturbation of the non-interacting problem (i.e the electron gas). Spin isn't important to make this point, so let's consider a general (normal-ordered) Hamiltonian of the kind&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \int d{\bf r}\; c^{\dagger}_{\bf r}\big(\frac{-\nabla^2}{2}\big)c_{\bf r} + \int d{\bf r}\; c^{\dagger}_{\bf r}U({\bf r})c_{\bf r} + \int d{\bf r}d{\bf r'} c^{\dagger}_{\bf r}c^{\dagger}_{\bf r'}\frac{1}{2}V({\bf r}-{\bf r'})c_{\bf r'}c_{\bf r} , &#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is the (one-body) static lattice potential and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the (two-body) electron-electron interaction. Now &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is an operator whose eigenstates we would like to solve. But because of the interactions, the full &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is a challenging problem to solve outright. However we know the solution in the case that we turn off the interactions (i.e &lt;span class=&quot;math-container&quot;&gt;$V=0$&lt;/span&gt;), which is just a 1-body problem of an electron in a lattice potential. It's solution being to fill up the available (non-occupied) single-particle states of the system until we run out of electrons -- the Fermi sea. This can either be a metal or insulator, depending on whether the valence electrons occupy a partially filled band or complete the occupation of a band.&lt;/p&gt;&#xA;&lt;p&gt;Thus without interactions, the electron density is governed entirely by the crystal potential. If we can treat the effect of the interactions perturbatively, say by slowly turning up the size of &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, then we could re-solve for the density perturbatively in terms of the original Fermi sea. Physically, we can imagine the electron density slightly readjusts from the original density into an energetically better state -- but not so much, and it remains a &amp;quot;Fermi sea&amp;quot; of electrons filling the lowest available states. But this Fermi sea is slightly modified from the one the crystal potential determined without interactions. In other words, the largest effect of the perturbation is to modify the &lt;em&gt;single-particle&lt;/em&gt; states which the electrons occupy to form the sea -- but it is still a sea!&lt;/p&gt;&#xA;&lt;p&gt;Let us imagine a new state &lt;span class=&quot;math-container&quot;&gt;$|\Omega\rangle$&lt;/span&gt;, which is just a Slater determinant whose single-particle wavefunctions are yet to be determined, and which has electron density &lt;span class=&quot;math-container&quot;&gt;$n({\bf r})$&lt;/span&gt;. Thus we should think of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; as being variational, such that the energy expectation value &lt;span class=&quot;math-container&quot;&gt;$E[n]=\langle\Omega[n]|H|\Omega[n]\rangle$&lt;/span&gt; is a functional of the different possible &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;. The &lt;span class=&quot;math-container&quot;&gt;$n=n^*$&lt;/span&gt; which minimizes &lt;span class=&quot;math-container&quot;&gt;$E[n]$&lt;/span&gt; corresponds to the state &lt;span class=&quot;math-container&quot;&gt;$|\Omega[n^*]\rangle$&lt;/span&gt; with the lowest energy -- our new solution. This energy functional has the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E[n] = \int d{\bf r}\; v({\bf r})n({\bf r}) + \frac{1}{2}\int d{\bf r}d{\bf r}'n({\bf r})V({\bf r}-{\bf r}')n({\bf r}') + T[n] + E_{xc}[n] ,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$T[n]$&lt;/span&gt;  is the kinetic energy of a system of non-interacting electrons with density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt; is the exchange-correlation energy due to the two-body interaction.&lt;/p&gt;&#xA;&lt;p&gt;The form of &lt;span class=&quot;math-container&quot;&gt;$E[n]$&lt;/span&gt; above is general enough for any Slater determinant with total electron density &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;. For an arbitrary density, &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt; may depend on not only the density at any point in space &lt;span class=&quot;math-container&quot;&gt;$n[r]$&lt;/span&gt; but also its gradients &lt;span class=&quot;math-container&quot;&gt;$\nabla n[r]$&lt;/span&gt;. However, DFT makes a few simplifying assumptions about the nature of &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt;, in particular, that it can be expanded to leading order in the density (local density approximation) or to leading order in powers of the gradient [1].&lt;/p&gt;&#xA;&lt;p&gt;Now the rest of this explanation is to make a point about why this approximation is bad for interaction-driven insulators. We will not consider the local density approximation (or gradient extension) in what follows. Let &lt;span class=&quot;math-container&quot;&gt;$E[n]$&lt;/span&gt; be exact for a given &lt;span class=&quot;math-container&quot;&gt;$|\Omega[n]\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let us start with a system whose ground state &lt;span class=&quot;math-container&quot;&gt;$|\Omega[n^*]\rangle$&lt;/span&gt; is a Fermi sea. For this to be true, the interaction effects must be small. This is only justified depending on the density of the electron fluid, which can be understood using some unit analysis. For our fluid, the kinetic energy &lt;span class=&quot;math-container&quot;&gt;$\nabla^2$&lt;/span&gt; goes like units of &lt;span class=&quot;math-container&quot;&gt;$1/x^2 \sim n^{2/3}$&lt;/span&gt;. Considering the Coulomb interaction&#xA;&lt;span class=&quot;math-container&quot;&gt;$$V({\bf r}-{\bf r'})=\frac{1}{|{\bf r}-{\bf r}'|} ,$$&lt;/span&gt;&#xA;scales like units of &lt;span class=&quot;math-container&quot;&gt;$1/x \sim n^{1/3}$&lt;/span&gt;, then the kinetic energy dominates at large densities.&lt;/p&gt;&#xA;&lt;p&gt;In other words, we could say that our system is an electron gas, so long as the average separation of the electrons in the fluid is small. But as the density shrinks, we get pushed closer and closer into a regime in which the interactions dominate. At the extreme low-density end of this spectrum, the system is entirely dominated by interactions, and thus the ground state is one which minimizes the energy by separating the particles as far apart as possible. Rather than a smooth homogenous fluid, we have a sharp arrangement of localized particles with marginal-to-no density in between.&lt;/p&gt;&#xA;&lt;p&gt;A cartoon of such a state would be delta-function-like orbitals arranged in a crystal. The density of this state varies sharply like the derivative of a delta-function. More physically, this may be either a Wigner crystal or a Mott insulator depending on the relative density of the electrons to that of the static background crystal lattice.&lt;/p&gt;&#xA;&lt;p&gt;There is another way to think of a Mott insulator. In addition to the Fermi sea, there are other (effectively) single-particle problems hidden in &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; as well. For example, let us consider that &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; describes a metal when &lt;span class=&quot;math-container&quot;&gt;$V=0$&lt;/span&gt;, then turn on small repulsive &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;. While we turn up a repulsive interaction from zero, it is possible that the bandwidth of the partially occupied band becomes smaller than the interaction energy. In such a circumstance, it may be more energetically favorable for valence electrons to occupy localized orbitals. In other words, if the Hubbard model for the partially occupied band can minimize its energy by placing one particle per orbital, thus separating the particles as far apart as possible, it will do so. This particular example can only happen at special integer fillings of the band, and is what one would call a correlated (Mott-like) insulator. Why again is this a single-particle problem? Because it has a single-particle solution -- electrons occupying single-particle states, just not in the same way as the Fermi sea. This what I would refer to as a &amp;quot;strong coupling&amp;quot; paradigm, where kinetic energy is then taken as a perturbation.&lt;/p&gt;&#xA;&lt;p&gt;Again, unlike the run-of-the-mill DFT based on slowly varying electron fluids, the gradients of the density are not small, owing to the localization of the electron orbitals needed to minimize the interaction energy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;you may be interested in:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There may be a way for you to study Mott-like (i.e interaction-driven) insulators starting from your DFT results. Essentially, one could use the bands outputted from QEspresso in order to construct maximally-localized Wannier functions for the valence bands of your interesting material [2]. This later step involves a program known as Wannier-90, which can be interfaced with QEspresso. These Wannier functions can be used to construct a Hubbard-like tight-binding model, which will permit a Mott insulator at special fillings, and for strong enough interactions.&lt;/p&gt;&#xA;&lt;p&gt;There are a lot of details to Wanner construction which I'm glazing over, so check out Ref [2].&lt;/p&gt;&#xA;&lt;p&gt;Ref [1]: &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.140.A1133&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/pr/abstract/10.1103/PhysRev.140.A1133&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Ref [2]: &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.56.12847&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.56.12847&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="4543" LastEditDate="2021-11-25T19:15:17.660" LastActivityDate="2021-11-25T19:15:17.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7141" PostTypeId="1" CreationDate="2021-11-25T10:56:57.823" Score="4" ViewCount="67" Body="&lt;p&gt;What are some of the structural (protein) transformation packages available, which can change a bond length, angle or dihedral?&lt;/p&gt;&#xA;" OwnerUserId="125" LastEditorUserId="5" LastEditDate="2021-11-25T17:04:03.603" LastActivityDate="2021-12-14T21:13:23.197" Title="A structural transformation package?" Tags="|software-recommendations|proteins|structure|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-18T15:11:01.930" ContentLicense="CC BY-SA 4.0" />
  <row Id="7142" PostTypeId="1" CreationDate="2021-11-25T21:56:27.503" Score="7" ViewCount="4431" Body="&lt;p&gt;The &lt;code&gt;%maxcore&lt;/code&gt; parameter in ORCA gives the memory per core needed for a calculation, however it is unclear to me if this should be the entire memory available to the job or if it should be some percentage of the max memory.&lt;/p&gt;&#xA;&lt;p&gt;How would I define &lt;code&gt;%maxcore&lt;/code&gt; if I have a node with 64GB of memory, slurm allocates 32GB of the memory to me, and I have 4 cores.  Presumably it would be set to 8000 to assign 8GB to each core, but I have seen calculations fail with out of memory errors when doing this that I would not predict would have this problem.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-11-25T23:42:09.927" Title="How to properly define %maxcore in ORCA" Tags="|high-performance-computing|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7143" PostTypeId="2" ParentId="7142" CreationDate="2021-11-25T23:42:09.927" Score="5" Body="&lt;p&gt;The ORCA Input Library website has a list of &lt;a href=&quot;https://m.sites.google.com/site/orcainputlibrary/orca-common-errors-and-problems&quot; rel=&quot;noreferrer&quot;&gt;commonly encountered errors&lt;/a&gt; that discusses using the &lt;code&gt;maxcore&lt;/code&gt; option.&lt;/p&gt;&#xA;&lt;p&gt;As you described, this option does set the &amp;quot;max&amp;quot; memory per core. I put max in quotations because it seems this is the upper limit under ideal conditions and ORCA can (and apparently often does) overshoot this limit. They recommend requesting no more than 75% of the physical memory you have available, so in your case that would be 6GB per core.&lt;/p&gt;&#xA;&lt;p&gt;I have not extensively used ORCA, so I don't know if this is a conservative recommendation or if you really will often encounter issues if you request, say, 90% of physical memory.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-25T23:42:09.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7146" PostTypeId="1" CreationDate="2021-11-26T17:00:48.890" Score="10" ViewCount="3538" Body="&lt;p&gt;I'm attempting to make QEspresso's pw program on a new 2021 MacBook Air, which has an M1 processor. While ./configure does not throw any errors, running 'make pw' fails with the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;checking build system type... Invalid configuration `aarch64-apple-darwin20.6.0': machine `aarch64-apple' not recognized&#xA;configure: error: /bin/sh ./config/config.sub aarch64-apple-darwin20.6.0 failed&#xA;if test -d src/ ; then \&#xA;    ( cd src/ ; make ) ; fi&#xA;make[3]: *** No rule to make target `device_auxfunc_mod.o', needed by `deviceXlib_mod.o'.  Stop.&#xA;make[2]: *** [libsrc] Error 2&#xA;make[1]: *** [libcuda_devxlib] Error 2&#xA;make: *** [libcuda] Error 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I included what I believe are the relevant lines of the make output. The output prior to this seemed normal. I believe CUDA is related to parallelization, which I don't need right now, so I tried disabling parallelization as a make option -- yet this does not work. I've also tried&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo ./configure --disable-parallel --with-internal-FFTW --with-internal-blas --with-internal-lapack ARCH=&amp;quot;mac686&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;following the instructions of Ref [1] for Macs, however, I don't know if I need to manual set ARCH=&amp;quot;mac686&amp;quot;, or something different for the newer M1. Or maybe this is entirely the wrong direction.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone tried installing QEspresso on an M1 Mac yet? Or have any sense if this is currently even possible? My web search only dug up one reference to installing QEspresso on the new M1 (see Ref [2]), which was totally unhelpful, so I'm afraid I'm running into a dead end and major time sink.&lt;/p&gt;&#xA;&lt;p&gt;Ref [1]: &lt;a href=&quot;https://sites.google.com/a/ncsu.edu/cjobrien/tutorials-and-guides/pwscf&quot; rel=&quot;noreferrer&quot;&gt;https://sites.google.com/a/ncsu.edu/cjobrien/tutorials-and-guides/pwscf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Ref [2]: &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/developers/2021-July/002430.html&quot; rel=&quot;noreferrer&quot;&gt;https://lists.quantum-espresso.org/pipermail/developers/2021-July/002430.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="5" LastEditDate="2023-01-27T21:34:14.667" LastActivityDate="2023-01-27T21:34:14.667" Title="Installing Quantum ESPRESSO on an Apple M1 processor possible?" Tags="|quantum-espresso|software-assistance|apple-operating-system|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7147" PostTypeId="1" AcceptedAnswerId="7148" CreationDate="2021-11-26T23:53:16.317" Score="7" ViewCount="353" Body="&lt;p&gt;Let's say I have a &lt;span class=&quot;math-container&quot;&gt;$2 \times 2$&lt;/span&gt; Hamiltonian that I am solving using the time-dependent Schrodinger equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;i \frac{d}{dt} |{\Phi}\rangle=H|{\Phi}\rangle.\tag{1}&#xA;$$&lt;/span&gt;&#xA;Consider a generic Hamiltonian&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \begin{bmatrix}&#xA;h_1 &amp;amp; h_2\tag{2} \\&#xA;h_3 &amp;amp; h_4\&#xA;\end{bmatrix}.&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$|{\Phi}\rangle$&lt;/span&gt; takes the general form with complex coefficients &lt;span class=&quot;math-container&quot;&gt;$(a,b)^T$&lt;/span&gt; (a column vector). Then, given some initial conditions (such as &lt;span class=&quot;math-container&quot;&gt;$a(0)=0,b(0)=1$&lt;/span&gt;), I can solve the following system of equations resulting from the Schrodinger equation above:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}\tag{3}&#xA;i \dot{a}&amp;amp;=a h_1 + b h_2\\&#xA;i\dot{b}&amp;amp;=a h_3 + b h_4,\tag{4}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;where the overhead dot denotes a time-derivative.&lt;/p&gt;&#xA;&lt;p&gt;This can give me the coefficients &lt;span class=&quot;math-container&quot;&gt;$a,b$&lt;/span&gt; at each time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. However, I now want to plot this trajectory on the &lt;a href=&quot;https://medium.com/quantum-untangled/quantum-states-and-the-bloch-sphere-9f3c0c445ea3&quot; rel=&quot;noreferrer&quot;&gt;Bloch sphere&lt;/a&gt;, a convenient tool for visualizing 2-state systems. All 2-state Hermitian systems may be mapped to this tool, which in its simplest form corresponds to a spin-&lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}$&lt;/span&gt; particle in an effective magnetic field.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$|{\Phi}\rangle$&lt;/span&gt; can be written in the following basis:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|{\Phi}\rangle=a |0\rangle + b|1\rangle,\tag{5}&#xA;$$&lt;/span&gt;&#xA;(corresponding to the same coefficients &lt;span class=&quot;math-container&quot;&gt;$a,b$&lt;/span&gt; found earlier), we can equivalently write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|{\Phi}\rangle=\cos\left({\frac{\theta}{2}}\right) |0\rangle + \sin\left(\frac{\theta}{2}\right) e^{i\phi}|1\rangle,\tag{6}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; are the polar and azimuthal angles in spherical coordinates.&lt;/p&gt;&#xA;&lt;p&gt;How do I plot the trajectory of the state, say, from &lt;span class=&quot;math-container&quot;&gt;$t=0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$t=1$&lt;/span&gt;?&#xA;If I solve &lt;span class=&quot;math-container&quot;&gt;$a=\cos\left({\frac{\theta}{2}}\right) $&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b=\sin\left(\frac{\theta}{2}\right) e^{i\phi}$&lt;/span&gt;, the resulting &lt;span class=&quot;math-container&quot;&gt;$\theta,\phi$&lt;/span&gt; are going to be complex angles in general. These cannot be plotted on a sphere as they are not real values. Where did I go wrong in my understanding?&lt;/p&gt;&#xA;&lt;p&gt;What I want to achieve is similar to the animation in &lt;a href=&quot;https://mathoverflow.net/questions/243625/schr%C3%B6dinger-equation-on-the-bloch-sphere&quot;&gt;this post&lt;/a&gt;. Even in their case, you end up with complex &lt;span class=&quot;math-container&quot;&gt;$|\Phi\rangle$&lt;/span&gt;. I do not get how we can plot such complex angles.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2021-11-27T02:44:32.663" LastActivityDate="2021-11-27T02:51:07.733" Title="How to solve time-dependent Schrodinger equation and plot trajectory on Bloch sphere?" Tags="|mathematical-modeling|quantum-mechanics|quantum-computing|nuclear-magnetic-resonance|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7148" PostTypeId="2" ParentId="7147" CreationDate="2021-11-27T02:00:35.007" Score="5" Body="&lt;p&gt;The angles &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; &lt;em&gt;&lt;strong&gt;never&lt;/strong&gt;&lt;/em&gt; contain a non-zero imaginary part (they are always purely real numbers). The general solution to Eq. 1 is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;|\Phi(t)\rangle = e^{-\textrm{i}H t} | \Phi(0)\rangle.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This can be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;\begin{bmatrix}&#xA;a(t) \\&#xA;b(t)&#xA;\end{bmatrix} = U&#xA;\begin{bmatrix}&#xA;a(0) \\&#xA;b(0)&#xA;\end{bmatrix} &#xA;.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the unitary matrix &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is just the matrix exponential in Eq. 1. The general expression for a 2x2 unitary matrix is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;U = \begin{bmatrix}&#xA; c &amp;amp; d \\&#xA; -e^{i\varphi} d^* &amp;amp; e^{i\varphi} c^* \\&#xA;\end{bmatrix},&#xA;\qquad&#xA;\left| c \right|^2 + \left| d \right|^2 = 1.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You now have the solution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{4}&#xA;\begin{bmatrix}&#xA;a(t) \\&#xA;b(t)&#xA;\end{bmatrix} = &#xA;\begin{bmatrix}&#xA;c\cdot a(0) + d\cdot b(0)\\&#xA; -e^{i\varphi} d^*\cdot a(0) + e^{i\varphi} c^* \cdot b(0)&#xA;\end{bmatrix} &#xA;.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In your case, &lt;span class=&quot;math-container&quot;&gt;$a(0) = 0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b(0) = 1$&lt;/span&gt;, so its even simpler:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{5}&#xA;\begin{bmatrix}&#xA;a(t) \\&#xA;b(t)&#xA;\end{bmatrix} &amp;amp;= &#xA;\begin{bmatrix}&#xA; d\\&#xA;  e^{i\varphi} c^* &#xA;\end{bmatrix} &#xA;\\&#xA;&amp;amp;=d(t)|0\rangle +   e^{i\varphi} c^*(t)|1\rangle.\tag{6}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you recall the &lt;a href=&quot;https://en.wikipedia.org/wiki/Complex_number#Modulus_and_argument&quot; rel=&quot;noreferrer&quot;&gt;polar form&lt;/a&gt; of a complex number, the angle (or &amp;quot;phase&amp;quot;) is always a real number, and the same is true here.&lt;/p&gt;&#xA;&lt;p&gt;Often Eq. 3 is expressed as in Eq. 2.31 of &lt;a href=&quot;http://theory.caltech.edu/%7Epreskill/ph219/chap2_15.pdf&quot; rel=&quot;noreferrer&quot;&gt;this set of PDF lecture notes&lt;/a&gt; by John Preskill (but the same formula will be found in almost every first year course on quantum information theory and many advanced NMR courses):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nMIsf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nMIsf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\hat{n}$&lt;/span&gt; is a unit vector with three components and &lt;span class=&quot;math-container&quot;&gt;$\vec{\mathbf{\sigma}}$&lt;/span&gt; is a vector containing three elements: &lt;span class=&quot;math-container&quot;&gt;$\sigma_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\sigma_y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma_z$&lt;/span&gt;. Note also that any Hermitian 2x2 matrix can be decomposed in terms of the identity &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; and the three elements of &lt;span class=&quot;math-container&quot;&gt;$\vec{\sigma}$&lt;/span&gt;. Since &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\sigma_y$&lt;/span&gt; will be real, the only imaginary numbers will appear from &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\sigma_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\sigma_z$&lt;/span&gt;, for which in both cases you can factor out &lt;span class=&quot;math-container&quot;&gt;$e^{\textrm{i}\phi}$&lt;/span&gt;, especially since when &lt;span class=&quot;math-container&quot;&gt;$\phi=\frac{\pi}{2}$&lt;/span&gt; we have &lt;span class=&quot;math-container&quot;&gt;$e^{\textrm{i}\phi} = \textrm{i}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-27T02:51:07.733" LastActivityDate="2021-11-27T02:51:07.733" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="7149" PostTypeId="1" CreationDate="2021-11-27T12:42:34.157" Score="6" ViewCount="310" Body="&lt;p&gt;I want to plot the berry curvature flux by considering &lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_y$&lt;/span&gt; plane in momentum space. I have experience running DFT calculations in Quantum ESPRESSO. I have tried reading the user manual of Wannier90 tool but didn't find any way to do this. The below image can be referred for more understanding of what I am trying to do:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ptZjG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ptZjG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not asking for actual code but just the steps which I have to follow in Wannier90 to achieve this results. Any help will be appreciable regarding this!&lt;br /&gt;&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2022-01-20T22:28:32.980" LastActivityDate="2022-01-20T22:28:32.980" Title="How to plot Berry curvature flux by considering plane in momentum space?" Tags="|quantum-espresso|topological-insulators|berry-phase|wannier90|weyl-semimetal|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-10T03:07:59.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="7150" PostTypeId="1" CreationDate="2021-11-27T14:37:44.993" Score="11" ViewCount="1484" Body="&lt;p&gt;I am studying the dehydrogenation of an organic molecule. I see the HUMO-LUMO gap remains nearly the same for many dehydrogenated steps (for some steps, it is exactly the same) while the position of HOMO and LUMO has shifted slightly.&#xA;So, for the steps, I have a gap between, HOMO and LUMO same,  I need to consider the position of the HOMO and LUMO to explain my dehydrogenation steps.&lt;/p&gt;&#xA;&lt;p&gt;Here are my data.&lt;/p&gt;&#xA;&lt;p&gt;Could you please suggest how HOMO and LUMO affect the reactivity of the molecule?&#xA;Also, which edge (HOMO or LUMO) is more responsible for the reactivity of the molecule?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Cmdx5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cmdx5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="789" LastEditDate="2021-11-27T15:28:51.470" LastActivityDate="2023-11-22T20:57:17.103" Title="How reactivity of a organic molecule depends upon HOMO and LUMO" Tags="|thermodynamics|organic-chemistry|reactivity|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7151" PostTypeId="1" AcceptedAnswerId="7157" CreationDate="2021-11-27T17:12:36.440" Score="8" ViewCount="1900" Body="&lt;p&gt;While there's a lot of good information available out there about choosing laptops, I still find it hard to pick a personal machine for my scientific computing needs. Though most matter modelling researchers, run the bulk of their calculations on computing clusters, the need for a powerful personal computing machine still seems unavoidable. For a few reasons like:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Run some back-of-the-envelope-style quick numerics/computations&lt;/li&gt;&#xA;&lt;li&gt;Post-simulation analysis with scripting tools&lt;/li&gt;&#xA;&lt;li&gt;Plotting, Creating illustrations (for example with Blender or something similar) etc.&lt;/li&gt;&#xA;&lt;li&gt;Code Development (especially for people contributing to various packages across the board)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A few parameters to consider in this context:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Processors&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Intel (usually seemed to be the preferred ones due to Intel MKl and oneAPI)&lt;/li&gt;&#xA;&lt;li&gt;AMD (though not the default choice, they seem to be getting better)&lt;/li&gt;&#xA;&lt;li&gt;Apple silicon (They seem promising, but I am not sure if people in the community are already adopting these new architectures)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Other relevant Hardware specs&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;RAM&lt;/li&gt;&#xA;&lt;li&gt;SSDs&lt;/li&gt;&#xA;&lt;li&gt;integrated GPUs&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;p&gt;What kind of laptops would you recommend for scientific computing keeping the above parameters in mind?&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="5" LastEditDate="2023-06-07T15:50:01.663" LastActivityDate="2023-06-07T15:50:01.663" Title="Suggestions on personal computers for matter modeling" Tags="|high-performance-computing|matter-modeling-specific-technology|hardware|" AnswerCount="5" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7152" PostTypeId="2" ParentId="7151" CreationDate="2021-11-27T19:05:04.903" Score="7" Body="&lt;p&gt;From your lines &lt;em&gt;I assume&lt;/em&gt; you start studying chemistry/physics/materials science, and you want to select a computer for performing such computations as well as writing lab reports.  Please correct me if this assumption is wrong.&lt;/p&gt;&#xA;&lt;p&gt;Get in touch with your school because indeed it always will be a question of detail and level of theory about the computation ahead if these are tasks are suitable for your own computer, or are delegated (similar to cloud computing) to a cluster at your university.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Gaussian_(software)&quot; rel=&quot;noreferrer&quot;&gt;Gaussian&lt;/a&gt; may be an illustration for this.  It isn't only a about obtaining a license, or training how to prepare/how to interpret a computation.  But to be productive (as in &lt;em&gt;performing many demanding computations within a suitable delay&lt;/em&gt;) these often are sent anyway via protocols like &lt;a href=&quot;https://en.wikipedia.org/wiki/Secure_Shell&quot; rel=&quot;noreferrer&quot;&gt;ssh&lt;/a&gt; to a computing centre/cluster.&lt;/p&gt;&#xA;&lt;p&gt;Since these &lt;em&gt;typically&lt;/em&gt; run one form of Unix or Linux, &lt;em&gt;regardless&lt;/em&gt; of the operating system of your personal computer, I recommend to get familiar how to issue some of the elementary commands (e.g., &lt;a href=&quot;https://en.wikipedia.org/wiki/GNU_Core_Utilities&quot; rel=&quot;noreferrer&quot;&gt;GNU core utils&lt;/a&gt;) by you from the CLI/terminal (e.g., copy/move files; &lt;a href=&quot;https://swcarpentry.github.io/shell-novice/&quot; rel=&quot;noreferrer&quot;&gt;example&lt;/a&gt; of a course providing some familiarity). With the heavy number crunching delegated, post processing (visualization of structures, plotting diagrams) indeed is what you do outside the (remote) cluster, facing your computer.&lt;/p&gt;&#xA;&lt;p&gt;Independent from this, browse through publications, e.g., in &lt;em&gt;The Journal of Chemical Education&lt;/em&gt; for comparison.  &lt;em&gt;Molecular Modelling&lt;/em&gt; is one of the keywords indexed, and a search about «Gaussian» and «Blender» you mention yields e.g., to «Gaussian-2-Blender: An Open-Source Program for Conversion of Computational Chemistry Structure Files to 3D Rendering and Printing File Format».&lt;/p&gt;&#xA;&lt;p&gt;Reference:&lt;/p&gt;&#xA;&lt;p&gt;Echeverri-Jimenez, E.; Oliver-Hoyo, M. &lt;em&gt;J. Chem. Educ.&lt;/em&gt; &lt;strong&gt;2021&lt;/strong&gt;, &lt;em&gt;98&lt;/em&gt;, 3348-3355 (&lt;a href=&quot;https://doi.org/10.1021/acs.jchemed.1c00460&quot; rel=&quot;noreferrer&quot;&gt;doi 10.1021/acs.jchemed.1c00460&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-11-27T19:05:04.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7153" PostTypeId="1" CreationDate="2021-11-27T19:35:31.707" Score="6" ViewCount="432" Body="&lt;p&gt;Is there any way to get a memory estimate for VASP calculations either directly or indirectly (based on some example calculation)?  For example, I would like to be able to predict based on my settings how much memory is needed within about a GB per core.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-12-13T12:07:30.553" Title="VASP Memory Estimate" Tags="|vasp|high-performance-computing|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7154" PostTypeId="2" ParentId="7150" CreationDate="2021-11-27T19:37:17.330" Score="16" Body="&lt;p&gt;The HOMO-LUMO gap is only weakly correlated with the reactivity of the molecule. Many sources, however, only point out the correlation between the HOMO-LUMO gap and reactivity, but fail to point out that the correlation only holds in the statistical sense, and is by no means universal. In addition, among those people who ever attempted to compare the HOMO-LUMO gap against the reactivity, usually only those people who do find a correlation will publish their results, leading to considerable survivorship bias. As a result, more and more people try to use the HOMO-LUMO gap to rationalize their reactivity patterns, while not realizing that this does not work nearly as well as they thought.&lt;/p&gt;&#xA;&lt;p&gt;The correlation between the HOMO-LUMO gap and reactivity stems from second-order perturbation theory. A molecule is said to be reactive, if either (1) it reacts exothermically and quickly with many kinds of molecules, or (2) it decomposes exothermically and quickly by itself. These two cases can be unified as: &lt;strong&gt;a reactive molecule is one that tends to significantly lower its energy in the presence of a perturbation&lt;/strong&gt;, where the perturbation can be either external (from other molecules) or internal (from the structural change of the molecule itself).&lt;/p&gt;&#xA;&lt;p&gt;Suppose that the ground state wavefunction of the molecule is &lt;span class=&quot;math-container&quot;&gt;$|\Psi_0\rangle$&lt;/span&gt;, the Hamiltonian of the molecules is &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, and the perturbation is expressed as an operator &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;. Then from second-order perturbation theory, the (ground state) energy change caused by the perturbation is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Delta E &amp;amp; = \langle \Psi_0 | V | \Psi_0 \rangle - \sum_{I&amp;gt;0} \frac{|\langle \Psi_0 | V | \Psi_I \rangle|^2}{\omega_I} + O(V^3) \tag{1}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$|\Psi_I\rangle, I=1,2,\ldots$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;-th excited state of the molecule, and &lt;span class=&quot;math-container&quot;&gt;$\omega_I$&lt;/span&gt; is the excitation energy of the state &lt;span class=&quot;math-container&quot;&gt;$|\Psi_I\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now, the usual assertion &amp;quot;smaller HOMO-LUMO gap means higher reactivity&amp;quot; amounts to making the following 4 approximations to Eq. (1):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle \Psi_0 | V | \Psi_0 \rangle$&lt;/span&gt; is negligible. This means that &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; cannot be too small, since the second term on the right hand side of Eq. (1) scales quadratically with respect to &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, while the first term scales only linearly. But ironically, perturbation theory itself requires that &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; cannot be too large, otherwise the theory does not hold. Therefore the assertion can only possibly hold for those reactivities where the molecule undergoes a not-too-large, but also not-too-small change.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In the sum &lt;span class=&quot;math-container&quot;&gt;$\sum_{I&amp;gt;0} \frac{|\langle \Psi_0 | V | \Psi_I \rangle|^2}{\omega_I}$&lt;/span&gt;, the &lt;span class=&quot;math-container&quot;&gt;$I=1$&lt;/span&gt; term dominates. This can be partly justified by the fact that &lt;span class=&quot;math-container&quot;&gt;$\omega_1 &amp;lt; \omega_2 &amp;lt; \omega_3 &amp;lt; \ldots$&lt;/span&gt;, which means that the &lt;span class=&quot;math-container&quot;&gt;$I=1$&lt;/span&gt; term has the smallest denominator. But there is no guarantee that it has the largest numerator! The numerator, &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|^2$&lt;/span&gt;, can even be zero, for example when &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is a totally symmetric operator but &lt;span class=&quot;math-container&quot;&gt;$|\Psi_0 \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\Psi_1 \rangle$&lt;/span&gt; belong to different irreducible representations. Only when the numerator &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|^2$&lt;/span&gt; is not too small, can the &lt;span class=&quot;math-container&quot;&gt;$I=1$&lt;/span&gt; term possibly dominate over the remaining terms of the series.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\omega_1 \approx \epsilon_{LUMO} - \epsilon_{HOMO}$&lt;/span&gt;. In other words the first excitation energy is approximated as the HOMO-LUMO gap. This approximation is not a good one, with errors on the order of 1 eV or so, because the approximation neglects the exciton binding energy. But this may be the best approximation among all the four approximations, as the other approximations are even poorer.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|^2$&lt;/span&gt; is approximately constant across the molecules that you want to compare. This can only be justified if your molecules are very similar (i.e. have similar &lt;span class=&quot;math-container&quot;&gt;$|\Psi_0 \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\Psi_1 \rangle$&lt;/span&gt;), and possess similar reactivities (i.e. have similar &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;). However, similar molecules also tend to possess similar &lt;span class=&quot;math-container&quot;&gt;$\omega_1$&lt;/span&gt;, so the differences of &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|^2$&lt;/span&gt; among the molecules may still overshadow the differences of &lt;span class=&quot;math-container&quot;&gt;$\omega_1$&lt;/span&gt;. You have to make sure that the molecules differ considerably in the HOMO-LUMO gap, but do not differ much in other aspects, including the shapes of HOMO and LUMO (which affect the wavefunctions &lt;span class=&quot;math-container&quot;&gt;$|\Psi_0 \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\Psi_1 \rangle$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Only with these four drastic approximations can we arrive at our result&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Delta E &amp;amp; \propto \frac{1}{\epsilon_{LUMO} - \epsilon_{HOMO}} \tag{2}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;i.e. the reactivity is inversely proportional to the HOMO-LUMO gap.&lt;/p&gt;&#xA;&lt;p&gt;The obvious conclusion at this point is that, while the reactivity may have a negative statistical correlation with the HOMO-LUMO gap, the correlation can only be relied upon under heavily controlled conditions. The reactivity must not be too low, nor can it be too high; the matrix element &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|$&lt;/span&gt; must be relatively large, at least it must not be zero; the exciton binding energy of the first excited state is either small or systematic, so that the trend of &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{LUMO} - \epsilon_{HOMO}$&lt;/span&gt; reflects the trend of &lt;span class=&quot;math-container&quot;&gt;$\omega_1$&lt;/span&gt;; and finally &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_1 \rangle|$&lt;/span&gt; must be roughly constant among the molecules to be studied. If any of the conditions are violated, then you can never explain your reactivity based on the HOMO-LUMO gap. I said never, because even if the HOMO-LUMO gap does correlate perfectly with the reactivity, you are achieving this correlation largely by luck, i.e. by exploiting an accidental cancellation of the contributions of &lt;span class=&quot;math-container&quot;&gt;$\langle \Psi_0 | V | \Psi_0 \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$|\langle \Psi_0 | V | \Psi_I \rangle|$&lt;/span&gt;, the &lt;span class=&quot;math-container&quot;&gt;$O(V^3)$&lt;/span&gt; term, and the exciton binding energy.&lt;/p&gt;&#xA;&lt;p&gt;Thus my suggestion is: observe if your HOMO-LUMO gap data do correlate with your reactivities. If yes, you can comment that the correlation exists, or that the trend of the HOMO-LUMO gaps contributes to the trend of the reactivities, but unless you provide evidence that the aforementioned four approximations hold, you should not say that you &amp;quot;explained&amp;quot; the reactivities by the HOMO-LUMO gaps. If no, then simply move on, and try other descriptors (atomic charges/spin populations/bond orders at transition states, for example) instead - there wasn't a strong reason for you to expect a good correlation in the first place.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-11-22T20:57:17.103" LastActivityDate="2023-11-22T20:57:17.103" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7155" PostTypeId="1" AcceptedAnswerId="7159" CreationDate="2021-11-27T23:20:56.583" Score="8" ViewCount="362" Body="&lt;p&gt;I'm a little confused how to make a VASP input file to calculate the energy for the isolated atom:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Do I need to change the lattice parameter of my unit cell or can keep the value for the whole system?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If I have 4 atoms of one type in my unit cell, can I consider the position of any of them or must it be in the middle of the unit cell?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I observed that some people use K point set &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt; for calculating a single atom. Is it necessary to use this set or can I use the normal K points set that is used at the time of convergence?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;To boil it down to one question, &lt;strong&gt;what do I need to change about typical VASP input file to calculate the energy of a single atom?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4354" LastEditorUserId="4354" LastEditDate="2021-11-28T14:49:37.137" LastActivityDate="2021-11-28T14:49:37.137" Title="what do I need to change about typical VASP input file to calculate the energy of a single atom?" Tags="|density-functional-theory|vasp|software-input-file-request|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7156" PostTypeId="1" CreationDate="2021-11-28T05:42:12.770" Score="6" ViewCount="271" Body="&lt;p&gt;We have been wanting to do relaxation of lattice parameters as a function of the energy. I want to know the mathematical expression for this, and also the theoretical background related to this method.&#xA;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="5" LastEditDate="2021-11-28T05:51:27.047" LastActivityDate="2021-11-30T15:24:32.767" Title="Relation between lattice parameter and energy for relaxations" Tags="|density-functional-theory|vasp|quantum-espresso|ab-initio-calculations|optimization|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7157" PostTypeId="2" ParentId="7151" CreationDate="2021-11-28T07:20:56.893" Score="11" Body="&lt;p&gt;If you have the ability to setup a way through which you can access university resources remotely such as &lt;a href=&quot;https://docs.microsoft.com/en-us/troubleshoot/windows-server/remote/understanding-remote-desktop-protocol&quot; rel=&quot;noreferrer&quot;&gt;RDP&lt;/a&gt;, &lt;a href=&quot;https://www.teamviewer.com/en/&quot; rel=&quot;noreferrer&quot;&gt;Teamviewer&lt;/a&gt; or &lt;a href=&quot;https://anydesk.com/en&quot; rel=&quot;noreferrer&quot;&gt;Anydesk&lt;/a&gt;, that would probably be the best option. You can buy whatever the laptop based on the cost effectiveness, easy of carrying or battery endurance and use it to connect to the university resources remotely.&lt;/p&gt;&#xA;&lt;p&gt;In my opinion, the price to performance of a laptop is way less attractive than a modern PC (where assembling your own would generally result in the lowest cost but may be unattractive to some). However, this option is not portable.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, newer laptops are impressively fast and reliable. Both AMD and Intel offerings are sufficiently neck to neck and so there really wouldn't be too much of a difference. Also, there are many cloud servers that use AMD EPYC CPUs. So there could be alternatives to Intel MKL and OneAPI but I am not too familiar with this. Considering Apple, the newer M1 silicon appears to be great in terms of performance. However you should check whether it would be compatible with the specific use case. Take &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/7146/installing-quantum-espresso-on-an-apple-m1-processor-possible&quot;&gt;this question&lt;/a&gt; as an example.&lt;/p&gt;&#xA;&lt;p&gt;If you still insist on buying a laptop to potentially install either windows or linux, choosing each component based on what you need would be the best way to go. Consider the following scenarios,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;If you have computationally heavy workloads which use multiple cores, then AMD Zen3 &lt;a href=&quot;https://www.amd.com/en/processors/ryzen-mobile-for-gamers&quot; rel=&quot;noreferrer&quot;&gt;H series&lt;/a&gt; processors would probably be a good option. However the best performance if the task does not spread through multiple cores is something that you would have to find through something like gaming benchmarks (since they usually utilize a fewer number of cores)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If what you do consumes a lot of memory, the memory capacity is important. However, keep note that the memory speed plays a significant role too. There may be situations where the memory bandwidth causes bottlenecks which reduce the overall performance. To escape this, try to find a laptop with high memory frequency and low memory latency. However as I remember, the memory speed of laptops are significantly lower than desktop PCs. So I would recommend that you look into that separately. Take a previous &lt;a href=&quot;https://serverfault.com/questions/1081675/synchronizing-threads-in-multithreaded-applications&quot;&gt;question&lt;/a&gt; of mine for example. In this case, I had only two memory channels installed on my XEON processor (due to financial limitations and since I did not expect to conduct DFT calculations back then). As it turns out, increasing the memory channels (thereby the speed) gives a significant boost in performance.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Storage is something that you can always add on the go by changing the SSD or by using an external drive. However if you need to constantly read and write files to the storage, looking for a laptop with a faster SSD could show significant performance improvements.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If what you work with has support for CUDA or OPENCL, then GPU acceleration should be considered. If not, the integrated GPUs of both Intel and AMD processors are good enough. That said, some visualization software could perform smoother with a discreet GPU.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;All in all, most gaming laptops such as &lt;a href=&quot;https://www.lenovo.com/us/en/legion/&quot; rel=&quot;noreferrer&quot;&gt;Lenovo Legion&lt;/a&gt; and &lt;a href=&quot;https://www.asus.com/Laptops/For-Gaming/ROG-Republic-of-Gamers/&quot; rel=&quot;noreferrer&quot;&gt;ASUS ROG&lt;/a&gt; would perform significantly well in these situations. Also there are some workstation class laptops such as &lt;a href=&quot;https://www.lenovo.com/us/en/c/laptops/thinkpad/thinkpadp&quot; rel=&quot;noreferrer&quot;&gt;these&lt;/a&gt;. However I am not sure if the performance is significantly different from gaming laptops or not.&lt;/p&gt;&#xA;&lt;p&gt;Note: I use an MSI &lt;a href=&quot;https://www.msi.com/Business-Productivity/Modern-15-A11X/Specification&quot; rel=&quot;noreferrer&quot;&gt;Modern-15-A11M&lt;/a&gt; laptop with an Intel i5-1135G7 processor for similar applications. For me, the decisive factor was the weight and market availability of the device. I do some SIESTA DFT calculations on this laptop and use it to remotely connect to the university servers. So far, I have not been let down by either the processor or the integrated GPU.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-11-28T07:20:56.893" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7158" PostTypeId="2" ParentId="7151" CreationDate="2021-11-28T07:31:43.310" Score="6" Body="&lt;p&gt;I totally agree that having a decent personal machine is of utmost importance for a matter modeling researcher, but this doesn't mean you have to buy a very expensive and/or powerful laptop, especially for (most of) the reasons you provided after this part of your question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Though most matter modelling researchers, run the bulk of their calculations on computing clusters, the need for a powerful personal computing machine still seems unavoidable. For a few reasons like...&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'll go through &lt;em&gt;your&lt;/em&gt; reasons one by one:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;Run some back-of-the-envelope-style quick numerics/computations&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;By definition, a &amp;quot;back-of-the-envelope-style calculation&amp;quot; does not need a very expensive computer. I guess you mean &lt;em&gt;medium-scale calculations&lt;/em&gt;. I agree that it's nice to be able to run some fairly serious calculations in MATLAB on a laptop (even with a laptop GPU) but laptops are not meant for doing heavy calculations or even medium-scale calculations (except for laptops like TensorBook, which is extremely overpriced). The vast majority of laptops and laptop users do web browsing and word processing. A server-grade compute node in a proper cluster can run at 100% CPU capacity for days and not get dangerously overheated, but laptops were never meant to be safe for that type of usage, nor resilient to doing it without burning out.&lt;/p&gt;&#xA;&lt;p&gt;I'm also assuming that you're paying for this yourself rather than getting it for free, or on a budget that can only be spent on a single laptop (since most people reading this answer will be in the former situation). Laptops are overpriced (spec-for-spec) compared to bigger computers (meaning a laptop with 16GB of RAM will typically cost far more than a desktop with 16GB of RAM or putting a 16GB compute node into an existing cluster), and the only reason for getting a laptop rather than a desktop is portability/travel, which causes wear and tear and risk of dropping/losing it, which is just another reason why getting a very expensive one with 32GB of RAM is not the best idea.&lt;/p&gt;&#xA;&lt;p&gt;A laptop with 16GB of RAM is quite ideal: not too expensive (especially if you buy it with 8GB and an extra DIMM slot where you can add the other 8GB yourself, but unfortunately a lot of them these days don't allow that because they come with all slots filled with RAM that's soldered into the MOBO), and would rarely go over RAM capacity (especially with a good operating system and smart usage, such as browser tab suspenders). However, I say this more because researchers often like to have lots of tabs open in their web browser (lots of research papers that they &amp;quot;must read later but don't yet have time&amp;quot;!), &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; because it's great for doing back-of-the-envelope or medium-scale calculations. If you want to do calculations involving 16GB of RAM or more, seriously consider doing it on a server meant for calculations, even if your laptop has (for some reason) 128GB of RAM: such calculations will almost always be heavy in CPU usage too, and do you really want to burn out your expensive laptop CPU rather than the comparatively much cheaper server-grade CPU that's &lt;em&gt;designed&lt;/em&gt; for calculations?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;Post-simulation analysis with scripting tools&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Except for high-performance graphics (HPG?) which is addressed in your next point, I'm not sure what post-simulation analysis using scripting tools, you could be doing which needs more than 16GB of RAM and yet can't be done relatively easily on a compute cluster that's meant for doing such &amp;quot;heavier&amp;quot; calculations.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;Plotting, Creating illustrations (for example with Blender or something similar) etc.&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Most &amp;quot;plotting&amp;quot; is on a 2D grid (x-axis and y-axis) and doesn't need much computing power, but creating illustrations (or nowadays, also videos!) can be very demanding on computer resources. Is there a reason why you need a laptop to do these? If you're doing a lot of video editing, I'd recommend a desktop since one with 32GB of RAM could easily cost the same as an equally powerful laptop with 16GB of RAM (for example). I'm assuming that you're not doing a lot of serious video rendering while on a train anyways, but I appreciate that everyone has their own way of doing things.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;Code Development (especially for people contributing to various packages across the board)&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I totally agree that this requires a lot of debugging and testing, for which decent computing power is often needed, but it's again unlikely that you need something with more than 16GB of RAM.&lt;/p&gt;&#xA;&lt;p&gt;So now I'll answer the rest of your questions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;&amp;quot;Processors&lt;/strong&gt;&lt;br&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Intel (usually seemed to be the preferred ones due to Intel MKl and oneAPI)&lt;/li&gt;&#xA;&lt;li&gt;AMD (though not the default choice, they seem to be getting better)&lt;/li&gt;&#xA;&lt;li&gt;Apple silicon (They seem promising, but I am not sure if people in the community are already adopting these new architectures)&#xA;Other relevant Hardware specs&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Intel. It's true that AMD is getting better, but it's much easier and safer to just stick with Intel for now. You'll already have &lt;em&gt;millions&lt;/em&gt; of options available to you, so filtering your search results for only Intel will also help save you time, among many other advantages (some which you seem to already know!).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;&amp;quot;Other relevant Hardware specs&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;RAM&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I mentioned my recommendations earlier :)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;SSDs&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They are very helpful indeed, but unfortunately it's also easy to get this &amp;quot;wrong&amp;quot;. Having an SSD can certainly make a noticeable speed difference in your experience with booting the computer and opening software, but almost everybody has fewer than 128GB of software while the rest are personal files/data for which it's usually actually better to have an HDD drive since for the same price you can get &lt;em&gt;far, far, far&lt;/em&gt; more storage space with not much less functionality. I'd recommend 128-256GB of SSD and 1-2TB of HDD (I personally like to have a lot of storage space, but you might not need that much, so it's your call, but 512GB of SSD space is a bit overkill in my opinion since it's extremely unlikely that you're actually using all that data often).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;integrated GPUs&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's very convenient to have one if you're developing code that is meant to run on GPUs, or if you're testing or doing some simple calculations that use GPUs, but GPUs are expensive and you won't be able to compete with what supercomputing clusters have, so I wouldn't spend &lt;em&gt;too&lt;/em&gt; much money on this part (1-2GB of RAM at the most, for example). If you do get a GPU, for many things, it absolutely needs to be an NVIDIA GPU (many things in scientific computing only work with NVIDIA GPUs).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Final recommendation:&lt;/strong&gt; If you get a laptop with an Intel CPU and 16GB of RAM , a 128-256GB SDD, a 1-2TB HDD and a 1-2GB NVIDIA GPU (only if you really do need it, because otherwise it can actually be harmful, which I can explain in another answer if you want to ask!), then you'll be getting something very decent for your work as a matter modeling researcher with access to larger supercomputing facilities, without entering the realm of the &amp;quot;overpriced&amp;quot; and without risking walking around with something ultra-expensive (which can be stressful).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-11-28T07:42:59.810" LastActivityDate="2021-11-28T07:42:59.810" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7159" PostTypeId="2" ParentId="7155" CreationDate="2021-11-28T12:33:14.033" Score="7" Body="&lt;p&gt;Isolated atom itself mean that there is no interaction from other nuclei , Hence box needs to be large enough so that atom doesn't interact with periodic image. In general 10-15 Angstrom size of box is enough. Once box is defined large (cubic) enough, placing atom anywhere inside box will not result any interaction from periodic image. If real space is large enough, reciprocal image will shrink to a point and number of kpoints will boil down to single point, Hence 1x1x1 is used for energy calculations. Better to look at &lt;code&gt;OUTCAR&lt;/code&gt; to check reciprocal space lattice parameter and volume&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-11-28T12:33:14.033" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="7160" PostTypeId="2" ParentId="7151" CreationDate="2021-11-28T14:24:02.670" Score="5" Body="&lt;p&gt;You want as much computing power and the fastest RAM you can get and afford. Of course power grows only logarithmically with price; focus on your needs &lt;em&gt;right now&lt;/em&gt; and not in three years when you are close to buying a new machine anyway. My experience is that the &lt;em&gt;&amp;quot;second best&amp;quot;&lt;/em&gt; (metaphorically speaking) often hits the sweet spot with computer components (as well as with most other things).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Processors: For desktop/workstation CPU Intel has screwed up badly and AMD wins the performance competition hands down because their CPUs have many more cores, see e.g. &lt;a href=&quot;https://opendata.blender.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://opendata.blender.org/&lt;/a&gt; for Blender performance measurements. Not so sure with mobile processors, except that AMD may be cheaper. Before you buy a specific processor go to a comparison website like &lt;a href=&quot;https://www.cpubenchmark.net&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.cpubenchmark.net&lt;/a&gt; and compare it against the alternatives.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;GPU: Both &lt;a href=&quot;https://docs.blender.org/manual/en/latest/render/cycles/gpu_rendering.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Blender renderings&lt;/a&gt; as well as &lt;a href=&quot;https://developer.nvidia.com/blog/drop-in-acceleration-gnu-octave/&quot; rel=&quot;nofollow noreferrer&quot;&gt;numerical calculations&lt;/a&gt; can be sped up with GPUs. Ask colleagues or even the support (forums) of your specific tools for advice. For example, if CUDA support is better than OpenCL support you may want to buy an NVIDIA GPU. In any case, you want to have the fastest one with the most memory you can afford.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;RAM: As fast as possible and as much as possible for data intensive calculations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The performance demands come with a couple downsides.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Size, and weight.&lt;/strong&gt; A couple months ago I bought a small-ish, slim  laptop at the lower end of the performance range I can accept, and I'm positively in love with it. I put it in my take-on and I hardly notice it. I can carry it everywhere (in your cases: conferences etc.) without it being a pain to lug around. A much bigger advantage than I anticipated. A laptop that is supposed to come close to desktop performance will be huge and heavy and clunky. It may also look inelegant.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Heat&lt;/strong&gt; produced by the powerful processors, and the &lt;strong&gt;noise&lt;/strong&gt; produced by the fan(s) to get rid of it. Be prepared for constant fan noise. How much it matters largely depends on personal sensitivities. The settings  where it will be used may play a role as well (small conference room?).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;The battery life&lt;/strong&gt; will be much shorter for high-end laptops because the components have been optimized for performance, not frugality. Essentially, you'll need a power source nearby for anything more than a quick glance.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Price.&lt;/strong&gt; The powerful components are expensive. Additionally minimizing weight and size — an attempt to square the circle — will come at a severe financial penalty.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Summing up: If your prime focus is performance while noise and portability are secondary, go for as much power and RAM as you can afford.&lt;/p&gt;&#xA;&lt;p&gt;P.S. Oh, one more thing: Take a close look at your use cases. If you need a mobile solution mostly because you present results elsewhere or want to do office work on the weekends at home, but not because you'll do serious number crunching on it, then a much more mainstream laptop would do. A combination of that and a capable desktop may not be much more expensive than a high-end laptop, and serve both needs better.&lt;/p&gt;&#xA;" OwnerUserId="1617" LastEditorUserId="1617" LastEditDate="2021-11-29T11:57:37.207" LastActivityDate="2021-11-29T11:57:37.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7161" PostTypeId="1" CreationDate="2021-11-28T17:48:43.897" Score="8" ViewCount="389" Body="&lt;p&gt;For studying a bulk supercell, after creating some vacuum in it, I'm confused about how to relax it.&lt;/p&gt;&#xA;&lt;p&gt;With VASP, I can do relaxation using &lt;code&gt;NSW = 0&lt;/code&gt; and &lt;code&gt;ISIF&lt;/code&gt; tag 2 or 3.&#xA;Alternatively, I could set &lt;code&gt;NSW=100&lt;/code&gt; and with some value for &lt;code&gt;ISIF&lt;/code&gt; (not sure what would be best).&lt;/p&gt;&#xA;&lt;p&gt;A third option is to first relax the supercell, then after creating a vacuum, it is should be fine to select &lt;code&gt;ISIF=0&lt;/code&gt; for relaxation.&lt;/p&gt;&#xA;&lt;p&gt;I am not sure which one of these is the best option or whether there is a better alternative.&lt;/p&gt;&#xA;" OwnerUserId="4354" LastEditorUserId="118" LastEditDate="2021-11-29T15:25:09.707" LastActivityDate="2021-11-29T15:25:09.707" Title="Study of supercell after creating vacuum" Tags="|density-functional-theory|vasp|software-input-file-request|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7162" PostTypeId="1" AcceptedAnswerId="7189" CreationDate="2021-11-28T23:06:49.827" Score="8" ViewCount="287" Body="&lt;p&gt;In &lt;a href=&quot;https://arxiv.org/abs/1012.1337&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ran Cheng's review of the quantum geometric tensor&lt;/a&gt;, eq. (11) gives the tensor as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Q_{\mu\nu}=\sum_{n\neq 0}\frac{\langle\phi_0|\partial_\mu H|\phi_n\rangle\langle\phi_n|\partial_\nu H|\phi_0\rangle}{(E_0-E_n)^2}.&#xA;$$&lt;/span&gt;&#xA;Per eq. (6), we see that the quantum metric may be defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;g_{\mu\nu}=\text{Re }Q_{\mu\nu}.&#xA;$$&lt;/span&gt;&#xA;I now want to calculate the distance between two arbitrary quantum states of a two-level system parameterized by two variables &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt; using eq. (9):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\langle\phi(\lambda_F)|\phi(\lambda_I)\rangle|=1-\frac{1}{2}\int_{\lambda_I}^{\lambda_F} g_{\mu\nu}(\lambda)d\lambda^\mu d\lambda^\nu.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could someone verify that the steps I'm taking are correct? The results of my numerical simulations seem suspicious.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Find the two eigenvectors of the 2-level Hamiltonian (not resulting in the nice standard eigenvectors discussed in Cheng's work).&lt;/li&gt;&#xA;&lt;li&gt;Use these to calculate &lt;span class=&quot;math-container&quot;&gt;$g_{k_x k_x},g_{k_x k_y},g_{k_y k_x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g_{k_y k_y}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;To perform the path integral, I first parameterize some path in &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-space (for example using &lt;span class=&quot;math-container&quot;&gt;$k_x (t) = \sin(t), k_y(t) = \cos(t)$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Plug these &lt;span class=&quot;math-container&quot;&gt;$k_x(t),k_y(t)$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$g_{\mu\nu}$&lt;/span&gt; found in step 2.&lt;/li&gt;&#xA;&lt;li&gt;Using motivation from eq. (21) of the review, numerically integrate the following, for absolute value of some &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; indicated by &lt;span class=&quot;math-container&quot;&gt;$|x|$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\langle\phi(\lambda_F)|\phi(\lambda_I)\rangle|=1-\frac{1}{2}\int_{\lambda_I}^{\lambda_F} &#xA;\sqrt{&#xA;\left|g_{k_x k_x} \left(\frac{dk_x}{dt}\right)^2\right|+&#xA;\left|g_{k_x k_y}\left(\frac{dk_x}{dt}\right)\left(\frac{dk_y}{dt}\right)\right|+&#xA;\left|g_{k_y k_x}\left(\frac{dk_y}{dt}\right)\left(\frac{dk_x}{dt}\right)\right|+&#xA;\left|g_{k_y k_y}\left(\frac{dk_y}{dt}\right)^2\right|&#xA;}&#xA;dt.&#xA;$$&lt;/span&gt;&#xA;I am supposed to get an answer between &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;, but I am not sure I incorporated/defined the metric correctly. Any advice?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;UPDATE: As requested, here is (Mathematica) code that I used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(* Some Hamiltonian H[kx,ky] with eigenvectors |n[kx,ky]&amp;gt;,|p[kx,ky]&amp;gt; \&#xA;and eigenvalues Energy[kx,ky]*)&#xA;m = 0.1;&#xA;sx = {{0, 1}, {1, 0}}; sy = {{0, -I}, {I, 0}}; sz = {{1, 0}, {0, -1}};&#xA;H[kx_, ky_] = m sz + kx sz + ky sy;&#xA;p[kx_, ky_] = &#xA;  Eigenvectors[H[kx, ky]][[1]]/Norm[Eigenvectors[H[kx, ky]][[1]]];&#xA;n[kx_, ky_] = &#xA;  Eigenvectors[H[kx, ky]][[2]]/Norm[Eigenvectors[H[kx, ky]][[2]]];&#xA;Energy[kx_, ky_] = Eigenvalues[H[kx, ky]];&#xA;(* Components of Quantum geometric tensor *)&#xA;Qxx[kx_, ky_] = ((Conjugate[n[kx, ky]] . D[H[kx, ky], kx] . &#xA;       p[kx, ky]) (Conjugate[p[kx, ky]] . D[H[kx, ky], kx] . &#xA;       n[kx, ky]))/(Energy[kx, ky][[2]] - Energy[kx, ky][[1]])^2;&#xA;Qxy[kx_, ky_] = ((Conjugate[n[kx, ky]] . D[H[kx, ky], kx] . &#xA;       p[kx, ky]) (Conjugate[p[kx, ky]] . D[H[kx, ky], ky] . &#xA;       n[kx, ky]))/(Energy[kx, ky][[2]] - Energy[kx, ky][[1]])^2;&#xA;Qyx[kx_, ky_] = ((Conjugate[n[kx, ky]] . D[H[kx, ky], ky] . &#xA;       p[kx, ky]) (Conjugate[p[kx, ky]] . D[H[kx, ky], kx] . &#xA;       n[kx, ky]))/(Energy[kx, ky][[2]] - Energy[kx, ky][[1]])^2;&#xA;Qyy[kx_, ky_] = ((Conjugate[n[kx, ky]] . D[H[kx, ky], ky] . &#xA;       p[kx, ky]) (Conjugate[p[kx, ky]] . D[H[kx, ky], ky] . &#xA;       n[kx, ky]))/(Energy[kx, ky][[2]] - Energy[kx, ky][[1]])^2;&#xA;(* For integral, parameterize by g the k-space path (qx[g],qy[g]) of \&#xA;radius r, center (kx0,ky0). *)&#xA;r = 1; kx0 = 0; ky0 = 0;&#xA;qx[g_] = kx0 + r Cos[g];&#xA;qy[g_] = ky0 + r Sin[g];&#xA;(* Derivatives of qx[g],qy[g] for integral metric*)&#xA;dqx[g_] = D[qx[g], g]; dqy[g_] = D[qy[g], g];&#xA;(* Components of metric tensor*)&#xA;gxx[kx_, ky_] = Re[Qxx[kx, ky]];&#xA;gxy[kx_, ky_] = Re[Qxy[kx, ky]];&#xA;gyx[kx_, ky_] = Re[Qyx[kx, ky]];&#xA;gyy[kx_, ky_] = Re[Qyy[kx, ky]];&#xA;(* Starting and ending points of g, for integration limits. If \&#xA;gend=2Pi, I expect the distance to = 0, since they are the same point \&#xA;as the parameterized path is then that of a closed circle. *)&#xA;gstart = 0;&#xA;gend = 3/4 Pi;&#xA;(* Quantum distance: I am not sure whether my definition of the \&#xA;metric is correct. *)&#xA;distance = &#xA; 1 - (1/2) NIntegrate[&#xA;Sqrt[Abs[gxx[qx[g], qy[g]] dqx[g] dqx[g]] + &#xA;  Abs[gxy[qx[g], qy[g]] dqx[g] dqy[g]] + &#xA;  Abs[gyx[qx[g], qy[g]] dqy[g] dqx[g]] + &#xA;  Abs[gyy[qx[g], qy[g]] dqy[g] dqy[g]]], {g, gstart, gend}]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2021-11-29T05:18:41.230" LastActivityDate="2021-12-02T21:19:56.340" Title="How to numerically calculate quantum state distance using quantum metric?" Tags="|condensed-matter|quantum-mechanics|solid-state-physics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7163" PostTypeId="1" CreationDate="2021-11-29T00:23:35.630" Score="6" ViewCount="78" Body="&lt;p&gt;I am interested in writing my own molecular dynamics code that uses a polarizable force-field. I am wondering if there are relatively simple &amp;quot;toy repositories&amp;quot; for these models such as is very common for pairwise FF's. The &lt;a href=&quot;https://github.com/Allen-Tildesley/examples/tree/master/python_examples&quot; rel=&quot;noreferrer&quot;&gt;Allen-Tildesly&lt;/a&gt; python/fortran GIT repo is an excellent example for pair-wise additive models.&lt;/p&gt;&#xA;&lt;p&gt;There are three types of polarizable force-fields that meet the criteria that I am after:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;atomic multipoles&lt;/li&gt;&#xA;&lt;li&gt;drude oscillators&lt;/li&gt;&#xA;&lt;li&gt;fluctuating charge models.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;What these have in common is an underlying pairwise additive force-field that in addition accounts for the many body contribution from polarizability.&lt;/p&gt;&#xA;&lt;p&gt;This is all under the molecular mechanics umbrella, not ab-initio or more rigorous. A well written code should be able to sample in the nano-seconds per day for thousands of molecules, on 12 or less cpus, with the type of polarizable model I am after.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="5" LastEditDate="2022-01-20T22:31:16.490" LastActivityDate="2022-01-20T22:31:16.490" Title="Simple code for polarizable force-field molecular dynamics?" Tags="|molecular-dynamics|software-recommendations|databases|forcefields|polarizability|" AnswerCount="0" CommentCount="0" ClosedDate="2023-02-01T03:41:48.847" ContentLicense="CC BY-SA 4.0" />
  <row Id="7164" PostTypeId="2" ParentId="7161" CreationDate="2021-11-29T02:33:33.963" Score="7" Body="&lt;p&gt;The common feature of a surface is that interlayer distance changes near the surface. For relaxation of atom and calculating surface energy in vasp &lt;code&gt;ISIF=2&lt;/code&gt; and &lt;code&gt;NSW=100 &lt;/code&gt; is correct option.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-11-29T02:33:33.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7165" PostTypeId="1" CreationDate="2021-11-29T08:26:32.610" Score="6" ViewCount="603" Body="&lt;p&gt;I have tried running a NEB-TS calculation in orca with &lt;code&gt;%pal nprocs 32&lt;/code&gt;, but I get an error saying &lt;code&gt;Parallel child processes not implemented yet&lt;/code&gt;. However, when I use &lt;code&gt;nprocs 15&lt;/code&gt;, the calculation runs smoothly.&lt;/p&gt;&#xA;&lt;p&gt;I use ORCA 4.2.1 on Windows 10 and I use the input code below. Does anyone know how I can use all 32? Thank you!&lt;/p&gt;&#xA;&lt;p&gt;INPUT:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP 6-311++G** tightSCF NEB-TS FREQ&#xA;&#xA;%scf&#xA;   MaxIter 300000&#xA;end&#xA;&#xA;%pal&#xA;  nprocs 32&#xA;end&#xA;&#xA;%base &amp;quot;set1&amp;quot;&#xA;&#xA;%NEB &#xA;  NEB_END_XYZFILE &amp;quot;set1_end.xyz&amp;quot;&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4634" LastEditorUserId="5" LastEditDate="2021-12-25T21:12:07.813" LastActivityDate="2021-12-25T21:12:07.813" Title="How do you perform parallelization of NEB-TS in ORCA?" Tags="|quantum-chemistry|computational-chemistry|software-assistance|orca|transition-state|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-18T15:25:55.593" ContentLicense="CC BY-SA 4.0" />
  <row Id="7166" PostTypeId="1" AcceptedAnswerId="7174" CreationDate="2021-11-29T08:53:46.130" Score="8" ViewCount="993" Body="&lt;p&gt;The only basic definition of improper torsion/improper dihedral I have is - improper dihedral is formed when we have a central atom bonded to the three atoms. Can anyone help me visualize/help to understand how these improper dihedrals help to maintain the planar structure of let's say - benzene?&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-06-13T03:24:36.337" Title="Confused about the application/definition of improper torsions" Tags="|molecular-modeling|gromacs|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7168" PostTypeId="2" ParentId="7120" CreationDate="2021-11-29T13:09:58.927" Score="5" Body="&lt;p&gt;To add on to the answer given by Camps above, I will explain a bit more about the Semi-Empirical nature of the potentials.&lt;/p&gt;&#xA;&lt;p&gt;The idea is based on density functional theory, and approximates the electron density of orbitals around the nucleus using some functional form. In the Baskes paper the form chosen is a decaying exponential.&lt;/p&gt;&#xA;&lt;p&gt;In the original EAM there are four of these functions, which are known as partial electron densities, representing the four orbital shells: s, p, d, f. Each of these is approximated as a sphere originating at the nucleus. This proved to be too simplistic a model, and so in MEAM the partial electron densities are altered to give them directionality depending on the atom's local environment. In a sense, the partial densities become perturbations of the originals from the EAM formalism. Each partial electron density can be considered a correction to the basic approximation of the EAM partial electron densities.&lt;/p&gt;&#xA;&lt;p&gt;The total electron density at any point is the combination of these partial electron densities. The embedding function describes the change in energy that occurs when placing an atom into a position surrounded by the electron density given by its neighbours. The potential function &lt;span class=&quot;math-container&quot;&gt;$\Phi_{ij}$&lt;/span&gt; is chosen to match physical constants and so far as I'm aware could be any kind of formalism so long as it gets you the right values.&lt;/p&gt;&#xA;&lt;p&gt;This is the first time I've really looked at this, so corrections are welcome!&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2023-01-27T12:08:41.800" LastActivityDate="2023-01-27T12:08:41.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7169" PostTypeId="1" AcceptedAnswerId="7202" CreationDate="2021-11-29T16:20:59.413" Score="10" ViewCount="178" Body="&lt;p&gt;The Gibbs free energy of a molecule is generally expressed as a sum of translational, rotational, vibrational, electronic and nuclear contributions. The electronic contribution &lt;span class=&quot;math-container&quot;&gt;$G_{elec}$&lt;/span&gt; is formally a sum of Boltzmann factors of all possible electronic states of the system, but since the first electronic excitation energy is usually much larger than &lt;span class=&quot;math-container&quot;&gt;$kT$&lt;/span&gt;, many programs make the approximation &lt;span class=&quot;math-container&quot;&gt;$G_{elec} = -RT \ln g_0$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; is the degree of degeneracy of the ground state. For non-relativistic calculations of spatially non-degenerate states, &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; is simply the spin multiplicity &lt;span class=&quot;math-container&quot;&gt;$2S+1$&lt;/span&gt;. In this case the program can easily choose the correct &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; automatically, without intervention by the user.&lt;/p&gt;&#xA;&lt;p&gt;However, during our recent development of the BDF software (&lt;a href=&quot;http://182.92.69.169:7226/Introduction&quot; rel=&quot;noreferrer&quot;&gt;http://182.92.69.169:7226/Introduction&lt;/a&gt;), I realized that the determination of &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; in BDF is much more complicated than simply equating it to &lt;span class=&quot;math-container&quot;&gt;$2S+1$&lt;/span&gt;. The reason is that BDF is known for its accurate relativistic methods and full consideration of spatial symmetry, including double-group symmetry. Consequently, compared to other programs, a disproportionately high number of BDF users routinely perform calculations that take into account spin-orbit coupling, where the degree of degeneracy is &lt;span class=&quot;math-container&quot;&gt;$2J+1$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$2S+1$&lt;/span&gt;, and a considerable number of users also calculate spatially degenerate electronic states.&lt;/p&gt;&#xA;&lt;p&gt;My question is about the latter case. If the electronic state is spatially degenerate, say we are calculating the Gibbs free energy of the triply degenerate &lt;span class=&quot;math-container&quot;&gt;$1^3P$&lt;/span&gt; state of the carbon atom, should we also take the spatial degeneracy of the state into account (i.e. in this case we have &lt;span class=&quot;math-container&quot;&gt;$g_0=9$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$g_0=3$&lt;/span&gt;)?&lt;/p&gt;&#xA;&lt;p&gt;Theoretically it seems that the answer is yes, but if the electronic structure method used in calculating the electronic energy of the system breaks the spatial symmetry, then the consideration of spatial symmetry may lead to inconsistencies. For example, if the aforementioned carbon atom is computed at the DFT level, then the spherical rotational symmetry of the atom is broken, so that if we compute the excited states of the carbon atom at the same level using TDDFT, we will find that the other two components of the triply degenerate &lt;span class=&quot;math-container&quot;&gt;$1^3P$&lt;/span&gt; state lie quite a bit above the ground state, and a sum of Boltzmann factors will yield a nearly zero spatial contribution to the electronic Gibbs free energy, instead of the expected &lt;span class=&quot;math-container&quot;&gt;$-RT \ln 3$&lt;/span&gt;. Therefore, choosing &lt;span class=&quot;math-container&quot;&gt;$g_0=9$&lt;/span&gt; in this case amounts to taking into account a degeneracy that exists in reality but does not exist in the approximate computational method that we are using, which does not sound entirely satisfactory. Moreover, the consideration of spatial symmetry in this case makes the automatic determination of &lt;span class=&quot;math-container&quot;&gt;$g_0$&lt;/span&gt; very difficult, as the program has to deduce that the true spectral term of the carbon atom is &lt;span class=&quot;math-container&quot;&gt;$1^3P$&lt;/span&gt;, even though the DFT wavefunction has only &lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt; symmetry.&lt;/p&gt;&#xA;&lt;p&gt;On the practical side, the latter problem means that in all quantum chemistry programs that I know of, a &lt;span class=&quot;math-container&quot;&gt;$1^3P$&lt;/span&gt; carbon atom computed at the DFT level is treated as if it is spatially non-degenerate (at least the degeneracy does not enter the partition function). But I don't know if the user is supposed to manually correct for this. If no, then what about the calculations where the atom is treated by a method that does respect the spatial symmetry, like state-averaged CASSCF? To the best of my knowledge, many (if not all) quantum chemistry programs do not take into account the spatial degree of degeneracy even in this case, but again I don't know if the user has the responsibility to manually add the spatial contribution to the electronic Gibbs free energy.&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much in advance.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2021-12-06T18:12:45.893" Title="Should one consider the spatial degeneracies of the electronic state while calculating the Gibbs free energy?" Tags="|symmetry|statistical-thermodynamics|free-energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7170" PostTypeId="2" ParentId="7156" CreationDate="2021-11-29T18:13:40.047" Score="4" Body="&lt;p&gt;I don't have a chance to give a complete answer and this may not be as fitting since you are intending to use a planewave based code, but &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.61.16440&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; [1]  gives a good description of computing the forces on a solid for an AO basis calculation.&lt;/p&gt;&#xA;&lt;p&gt;In general, relaxing lattice parameters isn't all that different from a general geometry optimization. Assuming (for simplicity, not necessity) that your unit cell is rigid and won't change with different lattice parameters, relaxing the lattice parameters is as simple as adjusting them until you reach a minimum of the energy. This can be done a number of different ways, from a general optimization procedure to a grid search over different values of the parameters . A grid search could be promising if you are working with a 1D system and already have a good sense of what the value should be. Otherwise, applying some optimization procedure for the energy will be the better approach, especially if the unit cell is not rigid and you need to consider changes in its geometry as well.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Konstantin N. Kudin and Gustavo E. Scuseria Phys. Rev. B 61, 16440 &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.16440&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-29T18:13:40.047" CommentCount="0" CommunityOwnedDate="2021-11-29T18:24:17.317" ContentLicense="CC BY-SA 4.0" />
  <row Id="7171" PostTypeId="2" ParentId="7151" CreationDate="2021-11-29T18:47:32.733" Score="7" Body="&lt;p&gt;There are already some good answers, but I thought it might be nice to a have a brief answer:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;It depends on what you're doing.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;But you probably just want a very cheap, light laptop.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I have a $400 12.5&amp;quot; laptop running Ubuntu for writing papers, reading papers, scripting, and system preparation. Once I get all my simulation configuration files tested and ready for the production run, I upload them to another computer through ssh (using rsync). After the simulations have been running for a few minutes, I download them to my laptop for visualization and to check that they are running properly. I then move on to something else and check on them again in a few days.&lt;/p&gt;&#xA;&lt;p&gt;With the money you save on buying a laptop, you can buy a desktop with a top-of-the-line consumer graphics card (which is now &amp;gt;$1000). For most of the calculations (classical MD) that I'm doing these days, very little matters except the graphics card.&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2021-11-29T18:47:32.733" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7172" PostTypeId="2" ParentId="6853" CreationDate="2021-11-29T19:09:47.203" Score="2" Body="&lt;p&gt;I can't make any statement as to the quality of this program, but &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2015.05.016&quot; rel=&quot;nofollow noreferrer&quot;&gt;MEAMfit&lt;/a&gt; seems to be another package that can do what you are looking for.&lt;/p&gt;&#xA;&lt;p&gt;The code isn't directly available online, but the article suggests emailing the authors for instructions on how to obtain the code.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-29T19:09:47.203" CommentCount="0" CommunityOwnedDate="2021-11-29T19:09:47.203" ContentLicense="CC BY-SA 4.0" />
  <row Id="7173" PostTypeId="2" ParentId="6269" CreationDate="2021-11-29T19:16:11.393" Score="1" Body="&lt;p&gt;The &lt;a href=&quot;https://github.com/mompiou/pycotem/issues/4&quot; rel=&quot;nofollow noreferrer&quot;&gt;corresponding issue&lt;/a&gt; for this was closed on Github. According to the package author, mompiou:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It seems to me that the error comes from the fact that you forgot to select a measurement in the &lt;code&gt;Dist, Incl&lt;/code&gt; box before adding the data. Please refer to the &lt;a href=&quot;https://mompiou.github.io/pycotem/diffraction/#workflow&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-11-29T19:16:11.393" CommentCount="0" CommunityOwnedDate="2021-11-29T19:16:17.007" ContentLicense="CC BY-SA 4.0" />
  <row Id="7174" PostTypeId="2" ParentId="7166" CreationDate="2021-11-30T01:13:29.773" Score="8" Body="&lt;p&gt;The key thing to remember is that while a &amp;quot;proper&amp;quot; torsion includes atoms 1-2-3-4 with bonds between 1-2, then 2-3, and then 3-4, an improper torsion is just defined by any set of 4 atoms.&lt;/p&gt;&#xA;&lt;p&gt;So here's a proper torsion C-C-C-H in benzene:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Cxv1sm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cxv1sm.png&quot; alt=&quot;proper torsion 1-2-3-4 in benzene&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I want the ring to be flat, I'd define this torsion to be, e.g. ±180°&lt;/p&gt;&#xA;&lt;p&gt;But I don't need to have four atoms bonded in row. I can define an improper torsion like this - notice atoms 1-2 and 2-3 aren't even bonded. I just picked the three atoms around number 4.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Zk6SMm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Zk6SMm.png&quot; alt=&quot;improper torsion in benzene&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here if I wanted the ring to be flat, I'd set the torsion to be 0° as depicted. (It's going to be the angle between vector 1-2 and 3-4, which should naturally be zero for a planar structure.)&lt;/p&gt;&#xA;&lt;p&gt;The nice thing about improper torsions, opposed to other kinds of out-of-plane potential functions, is that they can take the same form as a proper torsion, and use the same type of angle calculation. No need to define a plane, etc.&lt;/p&gt;&#xA;&lt;p&gt;Bezene isn't a great example, because I can keep it planar with many proper torsions. Something like formaldehyde is a classic case because there's no way to define a 1-2-3-4 bonded set, but it should be planar:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mJFF8m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mJFF8m.png&quot; alt=&quot;formadehyde&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Naturally, adding an improper torsion to a force field will help ensure planarity of formaldehyde and similar compounds. It's also commonly used to define inversion potentials for N and P pyramidal geometries.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-11-30T01:13:29.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7175" PostTypeId="2" ParentId="7125" CreationDate="2021-11-30T01:16:25.687" Score="3" Body="&lt;p&gt;You asked as well on the &lt;a href=&quot;https://discuss.avogadro.cc/t/building-graphene-oxide/3665/4?u=ghutchis&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro forum&lt;/a&gt;, but I'll include my answer here for others:&lt;/p&gt;&#xA;&lt;p&gt;For GO, there are two fairly commonly used Python packages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;GOPY &lt;a href=&quot;https://github.com/Iourarum/GOPY/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Iourarum/GOPY/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;MakeGraphitics &lt;a href=&quot;https://github.com/velocirobbie/make-graphitics&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/velocirobbie/make-graphitics&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I admit I haven't used either of them, but from what I can tell, GOPY is maybe a bit more flexible, but only generates PDB files, and MakeGraphitics will generate parameters to use in LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;Both could be integrated into Avogadro v2 as plugins.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-11-30T01:16:25.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7176" PostTypeId="2" ParentId="6889" CreationDate="2021-11-30T01:30:14.777" Score="7" Body="&lt;p&gt;Please feel free to contribute to Open Babel. I'm sure people would use it! Probably the easiest C++ code to adapt would be from Avogadro 1, which directly used the Open Babel API.&lt;/p&gt;&#xA;&lt;p&gt;For example the &lt;a href=&quot;https://github.com/cryos/avogadro/blob/master/libavogadro/src/extensions/supercellextension.cpp&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;supercell extension&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      // For each atom, we loop through:&#xA;      // * convert the coords back to inverse space&#xA;      // * apply the transformations&#xA;      // * create new atoms&#xA;      // * check for atoms in the same spot due to symmetry&#xA;…&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are methods to put all the atoms into the unit cell (not strictly required), and duplicate the unit cell -- which is &lt;a href=&quot;https://github.com/cryos/avogadro/blob/master/libavogadro/src/extensions/supercellextension.cpp#L295&quot; rel=&quot;noreferrer&quot;&gt;just a big triple loop over a, b, and c repeats&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want more specific pointers, ping me on the Open Babel GitHub or mailing list.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-11-30T01:30:14.777" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7177" PostTypeId="2" ParentId="7146" CreationDate="2021-11-30T01:44:00.357" Score="5" Body="&lt;p&gt;It looks like Quantum Espresso is available through &lt;a href=&quot;https://anaconda.org/conda-forge/qe&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;conda-forge&lt;/code&gt;&lt;/a&gt; which will be helpful.&lt;/p&gt;&#xA;&lt;p&gt;Conda Forge has worked to migrate many packages to &lt;code&gt;osx-arm64&lt;/code&gt; and &lt;a href=&quot;https://conda-forge.org/blog/posts/2020-10-29-macos-arm64/&quot; rel=&quot;noreferrer&quot;&gt;will rebuild packages for you&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The easy way is to update the &lt;a href=&quot;https://github.com/conda-forge/conda-forge-pinning-feedstock/blob/master/recipe/migrations/osx_arm64.txt&quot; rel=&quot;noreferrer&quot;&gt;list of packages to migrate&lt;/a&gt; as a pull-request. Assuming that goes through, various scripts will update the &lt;code&gt;qe&lt;/code&gt; package on conda-forge and you'll get an &lt;code&gt;osx-arm64&lt;/code&gt; build in a day or so.&lt;/p&gt;&#xA;&lt;p&gt;If you want to build yourself, you can grab the &lt;a href=&quot;https://github.com/conda-forge/qe-feedstock&quot; rel=&quot;noreferrer&quot;&gt;feedstock&lt;/a&gt; and add changes to conda-forge.yml:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;build_platform:&#xA;  osx_arm64: osx_64&#xA;test_on_native_only: true&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Follow the instructions on the &lt;a href=&quot;https://conda-forge.org/blog/posts/2020-10-29-macos-arm64/&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;conda-forge&lt;/code&gt; blog page&lt;/a&gt; to finish a local build.&lt;/p&gt;&#xA;&lt;p&gt;I can't promise it'll all work, since Quantum Espresso is trying to guess CUDA, etc. based on the configure script. If you're just building for the M1, you shouldn't need to set ARCH but it's either &lt;code&gt;aarch64-apple-darwin&lt;/code&gt; or &lt;code&gt;osx-arm&lt;/code&gt; for most scripts.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-11-30T01:44:00.357" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7178" PostTypeId="1" CreationDate="2021-11-30T03:37:58.183" Score="8" ViewCount="1286" Body="&lt;p&gt;For background, I have never used VASP before and have limited knowledge of how the software works. I am working on a program for the automation of structural creation for 2D materials. I am more of a computer scientist then a computational chemist and someone else is employing all my programs for their VASP optimizations and band width calculations.&lt;/p&gt;&#xA;&lt;p&gt;Currently, my program takes in coordinates for metal centers, organic linkers, etc... and, along with some other user defined parameters, writes a .xyz file for the desired periodic structure. The coordinates from my program are extracted and another program (that I did not write) uses them to write a POSCAR file. However, when the periodic structure is visualized in VESTA with the unit cell vertices, the structure is not centered in the unit cell. At this point, I was asked to make a series of geometrical transformations to the original file in order to get the structure to the desired location.&lt;/p&gt;&#xA;&lt;p&gt;I proposed that we adjust the lattice vectors/parameters to center it based off of the periodic structure coordinates as opposed to using the same lattice parameters and transforming each structure individually, as the former might be more efficient. However, I was told that this is not possible.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Here is my question&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to define the vertices of the unit cell around the structural coordinates?&lt;/p&gt;&#xA;&lt;p&gt;If the situation or question is unclear, I can try and explain it better with diagrams or pictures, however, I apologize in advance as my knowledge in this subject is very limited.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I did not make these in VASP or VESTA but just made some pictures in Microsoft word to represent the situation as I don't have access to my lab computer right now. Hopefully this makes the question more clear.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/a454o.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a454o.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It initially looks like this when the structure and unit cell vertices are rendered in VESTA. Then, after essentially doing guess and check transformations with the original .xyz file, the structure is transformed to look like this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IXxv4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IXxv4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So instead of transforming the initial structure, is it possible to change the origin of the basis set for the unit cell vertices (i.e. move the box down and center it based off of the initial molecular coordinates provide.&lt;/p&gt;&#xA;" OwnerDisplayName="user1441" LastEditorDisplayName="user1441" LastEditDate="2021-11-30T13:05:19.473" LastActivityDate="2021-11-30T13:05:19.473" Title="Unit Cell Parameters for VASP Calculations" Tags="|vasp|vesta|periodic-system|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7179" PostTypeId="2" ParentId="7156" CreationDate="2021-11-30T11:29:17.153" Score="8" Body="&lt;p&gt;For system with small strain condition, energy of strained system can be written in Taylor series as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E(\epsilon)=E(0)+\frac{V_0}{2}\sum_{ijk}C_{ijkl}\epsilon_{ij}\epsilon_{kl}+...$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In Voigt notation, It can be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E(\epsilon)=E(0)+\frac{V_0}{2}C_{ij}\epsilon_{i}\epsilon_{j}+...$$&lt;/span&gt;&#xA;or&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E(\epsilon)=E(0)+\boldsymbol{\epsilon}^T\mathbf{C}\boldsymbol{\epsilon}+...$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Considering hydro-static pressure mode in cubic crystal&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\boldsymbol{\epsilon}=&#xA;\begin{bmatrix}&#xA;\delta &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp;\delta &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp;\delta \\&#xA;\end{bmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\boldsymbol{C}=&#xA;\begin{bmatrix}&#xA;C_{11} &amp;amp; C_{12} &amp;amp; C_{12} &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \\&#xA;C_{12} &amp;amp; C_{11} &amp;amp; C_{12} &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \\&#xA;C_{12} &amp;amp; C_{12} &amp;amp; C_{11} &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; C_{44} &amp;amp; 0 &amp;amp; 0  \\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; C_{44} &amp;amp; 0  \\&#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; C_{44}  \\&#xA;\end{bmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;After doing some mathematical jugglery, we can get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E(\epsilon)=E(V_0)+\frac{3V_0}{2}(C_{11}+C_{22})\delta^2+O(\delta^3)$$&lt;/span&gt;&#xA;which can be fit to a second order polynomial&#xA;&lt;span class=&quot;math-container&quot;&gt;$$Y=A+BX^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here coefficient &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; the is bulk modulus of the system. This can be further generalized to increasing degrees of freedom. Further relations of energy with strained volume can be incorporated with pressure and derivatives of pressure with volume. These are modified equation of states and there are several of them available.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Murnaghan_equation_of_state&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Murnaghan_equation_of_state&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mcbrennan.github.io/BMderivation.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://mcbrennan.github.io/BMderivation.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Birch%E2%80%93Murnaghan_equation_of_state&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Birch%E2%80%93Murnaghan_equation_of_state&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Rose%E2%80%93Vinet_equation_of_state&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Rose%E2%80%93Vinet_equation_of_state&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="364" LastEditorUserId="7" LastEditDate="2021-11-30T15:24:32.767" LastActivityDate="2021-11-30T15:24:32.767" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7180" PostTypeId="2" ParentId="7178" CreationDate="2021-11-30T12:38:27.310" Score="6" Body="&lt;p&gt;There some very important points to address here.&lt;/p&gt;&#xA;&lt;p&gt;In a periodical structure, the atom coordinates and the cell parameters are not &lt;em&gt;randomly&lt;/em&gt; selected. The crystal structure (atom positions, cell parameters, spacial group) are determined by &lt;a href=&quot;https://en.wikipedia.org/wiki/X-ray_crystallography&quot; rel=&quot;noreferrer&quot;&gt;X ray/neutron crystallographic&lt;/a&gt; using single crystal or powders. The atoms are placed in the so called &lt;a href=&quot;https://en.wikipedia.org/wiki/Wyckoff_positions&quot; rel=&quot;noreferrer&quot;&gt;Wyckoff positions&lt;/a&gt;. These are &lt;em&gt;special&lt;/em&gt; position that, after applying &lt;a href=&quot;https://en.wikipedia.org/wiki/Symmetry_operation&quot; rel=&quot;noreferrer&quot;&gt;symmetry operations&lt;/a&gt;, you reproduce the crystal periodicity.&lt;/p&gt;&#xA;&lt;p&gt;A second point here is that the &lt;a href=&quot;https://en.wikipedia.org/wiki/XYZ_file_format&quot; rel=&quot;noreferrer&quot;&gt;XYZ&lt;/a&gt; file format doesn't have information about crystal periodicity. This imply that if you start with a file with this information (like &lt;a href=&quot;https://en.wikipedia.org/wiki/Crystallographic_Information_File&quot; rel=&quot;noreferrer&quot;&gt;CIF file&lt;/a&gt;, for example), when you convert it, the periodic information is lost.&lt;/p&gt;&#xA;&lt;p&gt;The only justification to put the atom coordinates centered in the cell is if you are using non-periodic system (like molecules) and wants/needs to use periodic design software (like VASP) to run the calculations. In this case, you can just do something like this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculate the minimum/maximum for each coordinate, for example &lt;span class=&quot;math-container&quot;&gt;$X_{min}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$X_{max}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Calculate the distance between this two extremes &lt;span class=&quot;math-container&quot;&gt;$d_X = X_{max} - X_{min}$&lt;/span&gt;. This will give you an idea of the size of the cell in the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; direction.&lt;/li&gt;&#xA;&lt;li&gt;For molecular systems (non periodical by nature), you will need to add some vacuum space in each direction in order to avoid image interaction (a molecule from one cell interacting with the molecule of all other neighbor cells). Now you have full length for &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; direction, &lt;span class=&quot;math-container&quot;&gt;$d_a$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Change the &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; coordinates of atoms, moving them to the center of the cell (you already know the lower/higher &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; values, so, you can add/subtract the vacuum layer size).&lt;/li&gt;&#xA;&lt;li&gt;When creating the POSCAR, use the modified XYZ and the &lt;span class=&quot;math-container&quot;&gt;$d_a$&lt;/span&gt; calculated before.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-11-30T12:38:27.310" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7181" PostTypeId="1" AcceptedAnswerId="7184" CreationDate="2021-11-30T20:34:30.553" Score="5" ViewCount="200" Body="&lt;p&gt;The problem is my box is not orthorhombic (base angles different than 90 degrees). So, I am getting wrong results with the formula,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def distance(a, b):&#xA;    dx = abs(a[0] - b[0])&#xA;    x = min(dx, abs(A - dx))&#xA;     &#xA;    dy = abs(a[1] - b[1])&#xA;    y = min(dy, abs(B - dy))&#xA;     &#xA;    dz = abs(a[2] - b[2])&#xA;    z = min(dz, abs(C - dz))&#xA;     &#xA;    return sp.sqrt(x**2 + y**2 + z**2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any suggestion on how to get the proper distance between any atom and its neighbours, including the periodic images of the neighbours.&#xA;Basically, it makes the results of RDF and CN unphysical.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jO0ow.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jO0ow.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="1609" LastEditDate="2021-12-01T10:57:56.903" LastActivityDate="2021-12-02T00:56:09.753" Title="How to calculate displacement in each coordinate and wrap w.r.t. lattice parameter?" Tags="|atomic-simulation-environment|radial-distribution-function|coordination|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7182" PostTypeId="1" CreationDate="2021-12-01T04:20:57.163" Score="6" ViewCount="900" Body="&lt;p&gt;I am a beginner using VASP to do material modeling, and I'm confused about the following questions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How does the electronic iteration work in VASP relaxation calculation?&lt;/li&gt;&#xA;&lt;li&gt;Is the electronic iteration during structure optimization and the same as that done in a single static self-consistent calculation?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If they are the same, it seems that there is no need to perform a static self-consistent calculation after structure optimization. In the last ion step of structure optimization, the calculation converges and atom position will not change further, electronic iteration at this point should be equivalent to electronic iteration in the subsequent self-consistent calculation.&lt;/p&gt;&#xA;" OwnerUserId="4642" LastEditorUserId="7" LastEditDate="2021-12-01T15:59:30.770" LastActivityDate="2021-12-01T15:59:30.770" Title="How does electronic iteration work in a VASP relaxation calculation?" Tags="|density-functional-theory|vasp|geometry-optimization|density-of-states|self-consistent-field|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7183" PostTypeId="1" CreationDate="2021-12-01T04:39:32.413" Score="17" ViewCount="1043" Body="&lt;p&gt;What is the Physical interpretation of the k-points used in ab initio calculations? Why must the number of k-points be optimized rather than just using some large fixed number of them?&lt;/p&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="7" LastEditDate="2021-12-03T00:35:46.333" LastActivityDate="2021-12-13T14:16:23.420" Title="Physical interpretation of k-points" Tags="|density-functional-theory|vasp|quantum-espresso|ab-initio-calculations|k-points|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7184" PostTypeId="2" ParentId="7181" CreationDate="2021-12-01T10:55:41.343" Score="4" Body="&lt;p&gt;Sticking with &lt;code&gt;ase&lt;/code&gt; you can use the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html?highlight=distances#ase.Atoms.get_distance&quot; rel=&quot;nofollow noreferrer&quot;&gt;built-in get_distance function&lt;/a&gt;. It supports non-orthogonal unit cells.&lt;/p&gt;&#xA;&lt;p&gt;An example to get the distance between atom number &lt;code&gt;a&lt;/code&gt; and atom number &lt;code&gt;b&lt;/code&gt; is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;atom = ase.io.read('your_file.xyz')&#xA;distance_a_to_b = atom.get_distance(a, b)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Additionally if you want to compute the Radial Distribution Function (RDF) and Coordination Number (CN), &lt;a href=&quot;https://wiki.fysik.dtu.dk/asap/Radial%20Distribution%20Functions#rdfs-and-the-coordination-number&quot; rel=&quot;nofollow noreferrer&quot;&gt;asap3&lt;/a&gt; is a python package building on top of &lt;code&gt;ase&lt;/code&gt; that natively does it.&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-12-01T10:55:41.343" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7185" PostTypeId="2" ParentId="7182" CreationDate="2021-12-01T12:20:36.833" Score="6" Body="&lt;p&gt;The figure below represents very well the self-consistent field (SCF) procedure used to solve the Kohn-Sham (KS) equations under the Density Functional Theory (DFT) approach:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/XeXbm.png&quot; height=&quot;550&quot;&gt;&#xA;&lt;p&gt;I think that this diagram answer your questions.&lt;br /&gt;&#xA;In the convergence test, if the electronic density isn't converged, the calculations return to second step, using that density as input to calculate the effective potential.&lt;br /&gt;&#xA;If the electronic density is already converged, then all the desired properties are calculated using the converged electron density.&lt;/p&gt;&#xA;&lt;p&gt;Yet, we have two type of calculations: single-point and relaxation.&lt;br /&gt;&#xA;In single-point calculations, there is no structure relaxation so the system geometry is static, but the electron relaxation is done.&#xA;In relaxation calculations, the system structure is also relaxed/optimized (can be only the atoms positions or the atoms positions and the cell parameters).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-01T12:20:36.833" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7186" PostTypeId="2" ParentId="7181" CreationDate="2021-12-02T00:56:09.753" Score="3" Body="&lt;p&gt;Have you tried using the &lt;a href=&quot;https://www.ovito.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ovito&lt;/a&gt; where there are built in functions to evaluate both RDF and CN of a system?&lt;/p&gt;&#xA;&lt;p&gt;Additionally, it might be possible to use &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vesta&lt;/a&gt; to convert the unit cell to a rectangular one (see this &lt;a href=&quot;https://www.youtube.com/watch?v=Aw7goppiUHk&quot; rel=&quot;nofollow noreferrer&quot;&gt;video&lt;/a&gt;). That way you can use your code to do the analysis.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2021-12-02T00:56:09.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7188" PostTypeId="1" CreationDate="2021-12-02T21:11:15.957" Score="4" ViewCount="148" Body="&lt;p&gt;The 4th desirable property of a norm-conserving pseudopotential given by &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hamann et al&lt;/a&gt; is for the 'logarithmic derivatives of the real and pseudo wave function and their first energy derivatives agree for &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_c$&lt;/span&gt;'. However I do not understand how the energy derivative of the log derivative&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{d}{d\epsilon}r\frac{d}{dr}\ln\psi(\epsilon;r)&#xA;$$&lt;/span&gt;&#xA;can be defined. In the all-electron case, my understanding is that the valence states are discretised (traditionally labelled with &lt;span class=&quot;math-container&quot;&gt;$(n,l,m)$&lt;/span&gt;). So what are the states &lt;span class=&quot;math-container&quot;&gt;$\psi(\epsilon;r)$&lt;/span&gt; with continuous &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; that are presumably required to allow us to define the energy derivative of the log derivative above?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/7198/4650&quot;&gt;Link&lt;/a&gt; to follow-up question&lt;/p&gt;&#xA;" OwnerUserId="4650" LastEditorUserId="4650" LastEditDate="2021-12-04T10:21:34.193" LastActivityDate="2021-12-04T10:21:34.193" Title="How to understand the energy derivative of the logarithmic derivative of a wavefunction when deriving norm-conserving pseudopotentials" Tags="|density-functional-theory|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7189" PostTypeId="2" ParentId="7162" CreationDate="2021-12-02T21:19:56.340" Score="4" Body="&lt;p&gt;The issue was the absolute values, and misunderstanding the notation. Per eq. (2) of &lt;a href=&quot;https://arxiv.org/pdf/1906.01462.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, we have:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;ds^2&#xA;=1-|\langle\phi(\lambda_F)|\phi(\lambda_I)\rangle|&#xA;=\sum_{\mu\nu}g_{\mu\nu}(\lambda)d\lambda^\mu d\lambda^\nu&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, to get the quantum distance, all I needed to do was get &lt;span class=&quot;math-container&quot;&gt;$\int ds$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NIntegrate[Sqrt[gxx[g] + gxy[g] + gyx[g] + gyy[g]], {g, gstart, gend}],&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where I re-defined the functions &lt;code&gt;gxx&lt;/code&gt;, etc for convenience:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gxx[g_] = gxx[qx[g], qy[g]] dqx[g] dqx[g];&#xA;gxy[g_] = gxy[qx[g], qy[g]] dqx[g] dqy[g];&#xA;gyx[g_] = gyx[qx[g], qy[g]] dqy[g] dqx[g];&#xA;gyy[g_] = gyy[qx[g], qy[g]] dqy[g] dqy[g];&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;after re-defining each component in terms of parameter &lt;code&gt;g&lt;/code&gt; alone:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gxx[g_]=gxx[qx[g],qy[g]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2021-12-02T21:19:56.340" CommentCount="0" CommunityOwnedDate="2021-12-02T21:19:56.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="7190" PostTypeId="2" ParentId="7188" CreationDate="2021-12-02T22:13:59.123" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4387/why-are-norm-conserving-pseudopotentials-considered-so-important&quot;&gt;Related&lt;/a&gt; prior question about norm-conserving potentials. Hopefully someone more informed on pseudopotenials can give a more descriptive answer. However if I'm understanding the question correctly, I think the issue is what you are considering discretized.&lt;/p&gt;&#xA;&lt;p&gt;While the states for an atom/molecule are discretized, the energy of any given state can still vary continuously as you perturb the atom or molecule. Taking the example of an atom, while it has discrete set of orbitals, the energies of these individual orbitals can continuously vary if an electric field was applied to the atom or you embedded it within some larger molecule or structure.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-12-02T22:13:59.123" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7191" PostTypeId="2" ParentId="7124" CreationDate="2021-12-03T05:51:59.303" Score="4" Body="&lt;p&gt;Partial Answers&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;To remove this error&#xA;Error in routine cdiaghg (211):&#xA;S matrix not positive definite&#xA;Use PAW pseudopotential files instead of USPP. Make sure the exchange correlational functional are same for all elements&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Increase Energy cut off value. (I am still facing problems in completing the calculations, it's taking too long to complete one calculation. Need a solution for this.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The system requirement for the processors I used on a different system which did not give errors was - mpiexec -n -32. If there are some other changes which can optimize this, I want to know about them.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Lastly, i am still not sure if i can take the mesh size 2 2 2 1 1 1  here, but above are the things which might help you solve some errors. I still need to complete these calculations to get Lattice thermal conductivity.&lt;/p&gt;&#xA;&lt;p&gt;Edit 1&#xA;Adding some useful papers for reference (I found)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Esfarjani K, Stokes HT. Method to extract anharmonic force constants from first principles calculations. Phys Rev B 2008;77:144112.&lt;/li&gt;&#xA;&lt;li&gt;Parlinski K, Li ZQ, Kawazoe Y. First-principles determination of the soft mode in cubic ZrO2. Phys Rev Lett 1997;78:4063.&lt;/li&gt;&#xA;&lt;li&gt;Togo A, Chaput L, Tanaka I. Distributions of phonon lifetimes in Brillouin zones. Phys Rev B 2015;91:94306. &lt;a href=&quot;http://dx.doi.org/10.1103/PhysRevB.91.094306&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dx.doi.org/10.1103/PhysRevB.91.094306&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="2077" LastEditDate="2021-12-05T13:33:24.333" LastActivityDate="2021-12-05T13:33:24.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7192" PostTypeId="1" CreationDate="2021-12-03T08:14:15.260" Score="5" ViewCount="251" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/q/680587/134583&quot;&gt;&lt;strong&gt;Cross-posted and answered at Physics.SE&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The quantized versions of the Hall effect include (ignoring fractional quantum Hall effect):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Quantum Hall effect;&lt;/li&gt;&#xA;&lt;li&gt;Quantum anomalous Hall effect;&lt;/li&gt;&#xA;&lt;li&gt;Quantum spin Hall effect.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;All these effects are transport phenomena but driven by different mechanisms, &lt;a href=&quot;https://arxiv.org/abs/1508.07106&quot; rel=&quot;nofollow noreferrer&quot;&gt;illustrated below&lt;/a&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/0LafP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0LafP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the quantized Hall conductivity is closely related to Berry curvature, which can be viewed as the magnetic field in reciprocal space, as justified by the semiclassical equation (&lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.82.1959&quot; rel=&quot;nofollow noreferrer&quot;&gt;Eqs.(5.8-a,b) in this paper&lt;/a&gt;) of motions for Bloch electrons:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\hbar \dot{\vec{k}} &amp;amp; = -e \vec{E}-e\dot{\vec{r}} \times \vec{B} \\&#xA;\dot{\vec{r}} &amp;amp;=\dfrac{\partial \varepsilon_M(\vec{k})}{\hbar\partial\vec{k}}-\dot{\vec{k}} \times \vec{\Omega}&#xA;\end{align}&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\vec{\Omega}$&lt;/span&gt; is the Berry curvature. Because the &lt;span class=&quot;math-container&quot;&gt;$\vec{\Omega}$&lt;/span&gt; is explicitly incorporated into the equations of motion for Bloch electrons, so it must be playing some role like the magnetic field &lt;span class=&quot;math-container&quot;&gt;$\vec{B}$&lt;/span&gt; in the Hall effect. So what's the role of Berry curvature in various quantized Hall effects?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-01-03T07:10:07.733" LastActivityDate="2022-01-03T07:10:07.733" Title="What's the role of Berry curvature in quantized Hall effects?" Tags="|berry-phase|from-phys-se|quantum-dynamics|semiclassical|" AnswerCount="0" CommentCount="1" ClosedDate="2022-01-03T13:22:21.520" ContentLicense="CC BY-SA 4.0" />
  <row Id="7193" PostTypeId="1" AcceptedAnswerId="7204" CreationDate="2021-12-03T10:46:43.423" Score="7" ViewCount="86" Body="&lt;p&gt;I would like to investigate the stability of &lt;span class=&quot;math-container&quot;&gt;$\ce{VI_3}$&lt;/span&gt; monolayer, but I am confused about whether I start directly by performing Phonon spectrum calculation, or I should first investigate the magnetic stability (I mean is it FM or AFM?). Then, I perform phonons calculations.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="5" LastEditDate="2021-12-03T13:41:13.313" LastActivityDate="2021-12-05T17:48:34.780" Title="Which one should be investigated first? dynamic stability or magnetic stability?" Tags="|vasp|magnetism|phonons|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7194" PostTypeId="1" AcceptedAnswerId="8618" CreationDate="2021-12-03T12:10:03.817" Score="9" ViewCount="257" Body="&lt;p&gt;For a structure such benzene, the pi bonds between the carbon atoms are said to be de-localized. Therefore the electrons are expected to be exchanged in between individual C-C bonds.&lt;/p&gt;&#xA;&lt;p&gt;When dealing with DFT calculations of such a structure, should there be any additional considerations to ensure the accuracy of the results?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2022-01-21T23:56:50.960" LastActivityDate="2022-02-02T12:46:58.220" Title="How to treat delocalized pi bonds in DFT" Tags="|density-functional-theory|siesta|atoms-in-molecules|" AnswerCount="1" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="7195" PostTypeId="2" ParentId="7065" CreationDate="2021-12-03T12:54:31.370" Score="4" Body="&lt;p&gt;The solution to this problem is actually significantly easier (but tedious) than expected. All quantum chemistry codes use specific identifiers in the input script to notify the code about the settings applied by the user. For example, the ibrav flag in QuantumEspresso notifies the code of the Bravis lattice specification.&lt;/p&gt;&#xA;&lt;p&gt;To build a GUI, a web based tool such as javascript can be used where the user can select the individual settings from drop down menus thereby giving the GUI. At the end of configuration through the GUI, it is easy to take into account all the provided information and create a text file where the text is formatted according to the input specifications of the DFT code.&lt;/p&gt;&#xA;&lt;p&gt;However, to do this, someone will have to comb through the user manual of the DFT code and include each and every required input command while setting default values to be printed in the text file if the user does not specify any information regarding a specific setting.&lt;/p&gt;&#xA;&lt;p&gt;Adding to the fact that developers sometimes (although rarely) opt to change the names of individual settings, provide new options and so on, updating the code will require some communication with the developers as well.&lt;/p&gt;&#xA;&lt;p&gt;Also, this can be extended to multiple DFT packages as well. However, the commands for each individual DFT code will have to be included, which is a tremendously tedious task.&lt;/p&gt;&#xA;" OwnerDisplayName="user4582" LastActivityDate="2021-12-03T12:54:31.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7196" PostTypeId="1" AcceptedAnswerId="8534" CreationDate="2021-12-03T14:12:44.083" Score="7" ViewCount="235" Body="&lt;p&gt;I have been unable to find software for making surface calculations, so I currently perform surface calculations in LAMMPS by creating crystal structures in python, before rotating and cutting them into slabs then simulating. However, whilst trying to perform surface calculations on FePt L1&lt;span class=&quot;math-container&quot;&gt;$_0$&lt;/span&gt; my python code wasn't rotating the crystal structure correctly. Trying to solve this issue is significantly slowing down my work, and I'm sure there is a better way of doing it.&lt;/p&gt;&#xA;&lt;p&gt;What software is generally the best to use, what software or methods do you use?&lt;/p&gt;&#xA;&lt;p&gt;For reference, I am using MEAM potentials for my calculations (it's a comparative study, doesn't have to be completely accurate), and all I really need is something which can make slabs and setup simulations in LAMMPS. Even just making the slabs is good enough, I'm happy porting it over to LAMMPS. To clarify, I am happy for any suggestion that covers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A program that can generate structures for input to LAMMPS only.&lt;/li&gt;&#xA;&lt;li&gt;A program that can generate structures and interface with LAMMPS itself.&lt;/li&gt;&#xA;&lt;li&gt;A program that can generate structures and performs calculations with its own code. For the above problem said program must be able to use MEAM potentials.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Although I have given my own problem in detail, I think it could be worthwhile listing almost anything that you personally use, or have used, so the community can use this post as a reference. When I have solved my own code's problems I will come back and list it as a github repo/ python package.&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="5" LastEditDate="2022-01-12T06:22:22.020" LastActivityDate="2022-01-12T17:57:41.190" Title="What software can be used for Crystal Surface Calculations?" Tags="|software|software-recommendations|one-topic-per-answer|surfaces|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="7197" PostTypeId="1" CreationDate="2021-12-02T10:21:20.327" Score="4" ViewCount="303" Body="&lt;p&gt;I'm new to VMD and I'm having some problems with displaying my polymer chain. Instead of just one bond, VMD draws multiple bonds. Why does this happen?&lt;/p&gt;&#xA;&lt;p&gt;I'm creating the data with Lammps, below you can find the configuration file. The positions of each atom are generetad by a random walk.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Specify number of atoms, bonds etc.&#xA;101 atoms&#xA;1 atom types&#xA;100 bonds&#xA;1 bond types&#xA;&#xA;# Specify the dimensions of the simulation box&#xA;-500.0 500.0 xlo xhi&#xA;-500.0 500.0 ylo yhi&#xA;-500.0 500.0 zlo zhi&#xA;&#xA;# No comments after this line!&#xA;&#xA;Atoms&#xA;&#xA;1 1 1 0.0 1.0 0.0&#xA;2 1 1 -0.7434993336043932 1.1973737373610782 0.6389462800032122&#xA;3 1 1 -0.4411948976553678 1.137570596339683 1.5902798767659445&#xA;4 1 1 -0.6329859116374574 1.143394721643678 2.571698384091013&#xA;5 1 1 -0.7016274442277435 1.5021302926345295 3.5026103724709694&#xA;6 1 1 -0.5443514760156292 1.5702089669785606 2.517405031477275&#xA;7 1 1 -0.5699191941809161 1.7003885169393316 1.5262443096163696&#xA;8 1 1 -1.3177350755405703 2.278804471390844 1.2003510890329563&#xA;9 1 1 -1.9977740218975115 1.8881888342630524 0.5798944382756367&#xA;10 1 1 -1.9319374150896353 2.08627847024584 -0.3980759280035424&#xA;11 1 1 -2.040305568769746 2.2015106556365667 -1.3854856133510385&#xA;12 1 1 -1.5958175497595544 2.1530871983399344 -0.49101058869141345&#xA;13 1 1 -1.6192876558657934 2.76194631148644 0.3019205145311884&#xA;14 1 1 -1.3422312299743706 3.2765219531221295 1.113370849368441&#xA;15 1 1 -2.181024985309463 3.8015202975945197 1.2575990515762703&#xA;16 1 1 -2.324236992177467 4.0230406461086625 0.2930167293854623&#xA;17 1 1 -2.730805712527504 4.3686486995612945 -0.5527119203726122&#xA;18 1 1 -1.8597726738426696 3.884999560889903 -0.6386476881406687&#xA;19 1 1 -2.255892784762997 3.037544231209013 -0.28522397371289987&#xA;20 1 1 -2.645888322818996 2.426064305276162 0.4032495410119348&#xA;21 1 1 -2.8111412810230143 3.277083105698413 0.9017056184477448&#xA;22 1 1 -2.1832603711837275 3.2535843704402443 1.6796602266998304&#xA;23 1 1 -2.1759625810777194 3.2884641985946117 0.6802953584722693&#xA;24 1 1 -2.685192387009965 2.700495667863554 0.05182259723263627&#xA;25 1 1 -2.937904635957768 2.8634421461362494 1.0055442361033655&#xA;26 1 1 -3.054065629991879 3.8538354706453704 0.9305263300223641&#xA;27 1 1 -2.554837947349212 3.9855623981159605 1.7869256162565308&#xA;28 1 1 -1.6415758191968515 3.7290099444914597 1.470487433001302&#xA;29 1 1 -1.8900749817872389 3.8052189230819775 2.436116946724897&#xA;30 1 1 -2.470739903718883 3.7661227632376364 1.6229135658148421&#xA;31 1 1 -2.6825374467370144 3.5115429556262314 2.5664870512032474&#xA;32 1 1 -1.780045547641019 3.296498831281347 2.9396685039187407&#xA;33 1 1 -1.0993076906782537 3.6770461834785997 2.313745439290665&#xA;34 1 1 -0.46195880715527926 3.7096758875111138 3.0836296533688397&#xA;35 1 1 -0.23841501293801096 3.672672252244473 2.1096384300798405&#xA;36 1 1 0.22877811484089797 3.6560029605085447 1.225640287508725&#xA;37 1 1 0.0682198250699318 3.734301163350403 2.2095561512986923&#xA;38 1 1 0.7230805203838258 3.926048293734055 1.4785359684564963&#xA;39 1 1 0.7684881429903485 4.252876337322301 2.4225283295132494&#xA;40 1 1 1.6113196542703498 4.49210929302465 1.9404467632826092&#xA;41 1 1 1.6398315199916553 4.657581062920609 2.926249059324056&#xA;42 1 1 1.2992558899263837 5.402093576553395 3.5004522962095983&#xA;43 1 1 1.8976509831206507 4.872438608347428 2.8992959712027324&#xA;44 1 1 1.971560715445052 5.2288808395108175 3.830685410326346&#xA;45 1 1 2.2016332012055035 5.24869273979793 4.803657218706744&#xA;46 1 1 1.89269657465061 6.199055974672456 4.840642115241796&#xA;47 1 1 1.8867800232249257 5.975229856368981 5.815253249584323&#xA;48 1 1 0.9802959416118275 5.939989229426677 5.394486440062979&#xA;49 1 1 1.047924037924727 5.669647029351694 4.434100301341833&#xA;50 1 1 1.065681202100049 4.672344116872239 4.505315355090657&#xA;51 1 1 1.9890223906338584 4.855672815127894 4.842704800617423&#xA;52 1 1 1.6981323684620444 4.380604923138391 4.012226930351436&#xA;53 1 1 1.5841075231538293 5.37359111660389 4.043479998030235&#xA;54 1 1 1.4194089647068764 4.616586260426731 3.4111683402461224&#xA;55 1 1 1.448631461286475 4.7192110548939015 4.405459141397489&#xA;56 1 1 1.0602825297012965 3.967251325525684 4.938133218807988&#xA;57 1 1 1.1665353695251628 3.9032366704083077 5.9304096208047135&#xA;58 1 1 0.6147436849584818 3.088703537358636 5.751351775382207&#xA;59 1 1 0.3894975765175991 3.43048570224102 6.6637382847084625&#xA;60 1 1 0.07289811630462367 3.452170914517765 7.612049696303496&#xA;61 1 1 0.20597075094139916 2.538021347220522 7.994962535630007&#xA;62 1 1 0.22023706250016878 1.7841668009752478 7.3380760953225215&#xA;63 1 1 0.30848510038867083 1.8413405224543755 8.33253245403368&#xA;64 1 1 0.40652915584533633 2.078520457537169 9.299038036833766&#xA;65 1 1 0.3418049476997458 2.814650573041588 8.625299786526291&#xA;66 1 1 1.174165755942365 2.8613112521175283 8.073033305622493&#xA;67 1 1 1.442960329852769 3.074362975392315 7.133693941896066&#xA;68 1 1 1.6864169820447585 3.466978437241009 8.020588500240407&#xA;69 1 1 2.2434929878955114 4.249342708614907 7.7420701515038095&#xA;70 1 1 2.067430021991088 4.02157894285066 8.699736846675897&#xA;71 1 1 1.943445379529309 4.050699677692111 7.707880107405593&#xA;72 1 1 1.6624284693755162 3.794748444773335 6.78293769699564&#xA;73 1 1 2.088879815897793 3.805001652998303 7.687390084228065&#xA;74 1 1 2.275671871180298 3.7529818076023047 8.668411319354153&#xA;75 1 1 2.356579533891821 3.2927396662140116 9.552510364373926&#xA;76 1 1 1.7742705290786691 2.7560175183894886 8.94189955629062&#xA;77 1 1 0.9444528173236891 2.2406800487846494 9.155978648401481&#xA;78 1 1 1.576588748426326 2.761354773732321 8.582130240361806&#xA;79 1 1 0.9428470651966604 2.6153768933219466 9.34177616931037&#xA;80 1 1 0.9257234064979147 2.32681969593226 8.384466645620472&#xA;81 1 1 0.7066303623606289 2.9396471968940485 9.143703559946683&#xA;82 1 1 1.0081424534717858 2.7935316251905995 8.201503634973458&#xA;83 1 1 0.215091367278472 2.3745267415388094 7.759344294731102&#xA;84 1 1 0.8363081855105148 2.914149076941315 8.327584912674244&#xA;85 1 1 0.344025941389587 3.7523816381838344 8.562157642112407&#xA;86 1 1 0.748192744185691 3.872513874138282 9.468919706494326&#xA;87 1 1 0.07077650273719471 3.7309390412545818 10.190767199054731&#xA;88 1 1 0.09958038174286468 3.7064596929845313 11.190052492683382&#xA;89 1 1 0.14518080386775778 3.391684978503032 10.241982094123696&#xA;90 1 1 0.40296951577248574 4.084394216445771 10.915553836169998&#xA;91 1 1 -0.001759231744961065 4.854355021503993 11.4088640829793&#xA;92 1 1 -0.36521564443071763 3.9227878338502715 11.399808092446126&#xA;93 1 1 -0.44182564884993936 3.049235462804667 10.91914483998814&#xA;94 1 1 0.42809855383893103 2.733950887333662 10.53989885379158&#xA;95 1 1 1.0255155357668442 2.9120441783129927 9.75799366170478&#xA;96 1 1 0.8925334926302557 2.908971670619831 10.749107346354375&#xA;97 1 1 1.5688207561101777 2.5114790617426905 11.369296965054078&#xA;98 1 1 0.6114222053258117 2.226292114441501 11.414644732860493&#xA;99 1 1 0.2194072585912204 2.206191188157631 10.494905512048852&#xA;100 1 1 -0.6863081538403157 1.7963549441711444 10.60313602899773&#xA;101 1 1 -0.9577783952771719 0.9208842115233563 11.002954618224594&#xA;&#xA;&#xA;Bonds&#xA;&#xA;1 1 1 2&#xA;2 1 2 3&#xA;3 1 3 4&#xA;4 1 4 5&#xA;5 1 5 6&#xA;6 1 6 7&#xA;7 1 7 8&#xA;8 1 8 9&#xA;9 1 9 10&#xA;10 1 10 11&#xA;11 1 11 12&#xA;12 1 12 13&#xA;13 1 13 14&#xA;14 1 14 15&#xA;15 1 15 16&#xA;16 1 16 17&#xA;17 1 17 18&#xA;18 1 18 19&#xA;19 1 19 20&#xA;20 1 20 21&#xA;21 1 21 22&#xA;22 1 22 23&#xA;23 1 23 24&#xA;24 1 24 25&#xA;25 1 25 26&#xA;26 1 26 27&#xA;27 1 27 28&#xA;28 1 28 29&#xA;29 1 29 30&#xA;30 1 30 31&#xA;31 1 31 32&#xA;32 1 32 33&#xA;33 1 33 34&#xA;34 1 34 35&#xA;35 1 35 36&#xA;36 1 36 37&#xA;37 1 37 38&#xA;38 1 38 39&#xA;39 1 39 40&#xA;40 1 40 41&#xA;41 1 41 42&#xA;42 1 42 43&#xA;43 1 43 44&#xA;44 1 44 45&#xA;45 1 45 46&#xA;46 1 46 47&#xA;47 1 47 48&#xA;48 1 48 49&#xA;49 1 49 50&#xA;50 1 50 51&#xA;51 1 51 52&#xA;52 1 52 53&#xA;53 1 53 54&#xA;54 1 54 55&#xA;55 1 55 56&#xA;56 1 56 57&#xA;57 1 57 58&#xA;58 1 58 59&#xA;59 1 59 60&#xA;60 1 60 61&#xA;61 1 61 62&#xA;62 1 62 63&#xA;63 1 63 64&#xA;64 1 64 65&#xA;65 1 65 66&#xA;66 1 66 67&#xA;67 1 67 68&#xA;68 1 68 69&#xA;69 1 69 70&#xA;70 1 70 71&#xA;71 1 71 72&#xA;72 1 72 73&#xA;73 1 73 74&#xA;74 1 74 75&#xA;75 1 75 76&#xA;76 1 76 77&#xA;77 1 77 78&#xA;78 1 78 79&#xA;79 1 79 80&#xA;80 1 80 81&#xA;81 1 81 82&#xA;82 1 82 83&#xA;83 1 83 84&#xA;84 1 84 85&#xA;85 1 85 86&#xA;86 1 86 87&#xA;87 1 87 88&#xA;88 1 88 89&#xA;89 1 89 90&#xA;90 1 90 91&#xA;91 1 91 92&#xA;92 1 92 93&#xA;93 1 93 94&#xA;94 1 94 95&#xA;95 1 95 96&#xA;96 1 96 97&#xA;97 1 97 98&#xA;98 1 98 99&#xA;99 1 99 100&#xA;100 1 100 101&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ofjbm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ofjbm.png&quot; alt=&quot;My polymer with multiple bonds from a single atom&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4660" OwnerDisplayName="Jakob Boonen" LastEditorUserId="5" LastEditDate="2021-12-13T19:23:13.073" LastActivityDate="2021-12-13T19:23:13.073" Title="VMD polymer draws multiple bonds" Tags="|lammps|vmd|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="7198" PostTypeId="1" CreationDate="2021-12-04T10:19:49.497" Score="9" ViewCount="127" Body="&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;Norm-conserving pseudopotentials&lt;/a&gt; are defined such that the energy derivative of the log derivative of the real and pseudo wavefunctions agree at &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_c$&lt;/span&gt;. I understand that although valence eigenenergies are discretised, they (and their associated valence wavefunctions) can be varied continuously by applying a perturbation to the potential, which allows us to define the energy derivative of the log derivative. &lt;strong&gt;However, I do not understand which perturbation we apply in this definition.&lt;/strong&gt; I asked a related question &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/7188/4650&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4650" LastEditorUserId="142" LastEditDate="2023-02-04T10:49:10.040" LastActivityDate="2023-02-06T10:02:36.223" Title="Which specific perturbation do we consider applying to the potential when defining the energy derivative of the log derivative?" Tags="|density-functional-theory|mathematical-modeling|pseudopotentials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7199" PostTypeId="1" CreationDate="2021-12-04T18:56:16.420" Score="8" ViewCount="1161" Body="&lt;p&gt;I've previously installed the Quantum Espresso (QEsp) binaries using &amp;quot;apt install&amp;quot; on an Ubuntu 16.04.7 LTS distro. This has worked fine, except that calculations don't produce .hdf5 output, which I need to transfer the data to Mathematica/Python/etc. So now I'm compiling from source.&lt;/p&gt;&#xA;&lt;p&gt;According to [1], QEsp needs a special flag at compile time in order for it to have HDF5 support. In other words, someone could run the command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./configure -with-hdf5=yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However for me, this produces the output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;The following libraries have been found:&#xA;  BLAS_LIBS=-L/opt/intel/mkl/lib/intel64 -lmkl_gf_lp64  -lmkl_sequential -lmkl_core&#xA;  LAPACK_LIBS=&#xA;  FFT_LIBS=&#xA;  HDF5_LIBS=&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which I'm pretty sure means that HDF5_LIBS were not found. According to [1], if this happens, I need only specify the include and lib locations using the commands&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./configure -with-hdf5-libs=&amp;lt;options&amp;gt; -with-hdf5-include=&amp;lt;path&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &amp;quot;&amp;lt;options&amp;gt;&amp;quot; and &amp;quot;&amp;lt;path&amp;gt;&amp;quot; are placeholders for the necessary directories. If I run the command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;h5fc -show&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;as per the instructions of [1], I get the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;x86_64-conda_cos6-linux-gnu-gfortran -I/home/eugenio/miniconda3/include -L/home/eugenio/miniconda3/lib /home/eugenio/miniconda3/lib/libhdf5hl_fortran.a /home/eugenio/miniconda3/lib/libhdf5_hl.a /home/eugenio/miniconda3/lib/libhdf5_fortran.a /home/eugenio/miniconda3/lib/libhdf5.a -L/home/eugenio/miniconda3/lib -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,-rpath,/home/eugenio/miniconda3/lib -L/home/eugenio/miniconda3/lib -lrt -lpthread -lz -ldl -lm -Wl,-rpath -Wl,/home/eugenio/miniconda3/lib&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How do I properly specify the include and lib directories, given the above output? How will I know that I have done this correctly, and that it will compile with HDF5 support?&lt;/p&gt;&#xA;&lt;p&gt;I've unsuccessfully tried a number of different rearrangements, and have heeded the warning in [1] that &amp;quot;directories in the list must be separated by spaces&amp;quot;... I'm pretty sure I'm doing this part incorrectly.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;&lt;p&gt;Ref [1]: &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node11.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/user_guide/node11.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="5" LastEditDate="2021-12-05T05:56:05.417" LastActivityDate="2022-01-10T23:15:34.397" Title="How do I compile Quantum Espresso with HDF5 support? (Linux)" Tags="|quantum-espresso|software-assistance|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7200" PostTypeId="1" AcceptedAnswerId="7203" CreationDate="2021-12-05T04:20:45.390" Score="11" ViewCount="556" Body="&lt;p&gt;I need a code/app/website that can receive a DNA sequence, for instance AATCT, and output a file with the atomic coordinates.&lt;/p&gt;&#xA;&lt;p&gt;I used to do this on this &lt;a href=&quot;http://www.scfbio-iitd.res.in/software/drugdesign/bdna.jsp#1&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt; but the service is no longer working and I haven't mange to find a substitute.&lt;/p&gt;&#xA;&lt;p&gt;I found a &lt;a href=&quot;https://casegroup.rutgers.edu/fd_helix.c&quot; rel=&quot;nofollow noreferrer&quot;&gt;code&lt;/a&gt; that does this but doesn't include de H atoms .&lt;/p&gt;&#xA;&lt;p&gt;I have also visited some data banks but they don't have what I'm looking for, I want to have control over the DNA sequence I want.&lt;/p&gt;&#xA;" OwnerUserId="4659" OwnerDisplayName="Carlos Andrés del Valle" LastEditorUserId="24" LastEditDate="2021-12-21T17:46:51.773" LastActivityDate="2021-12-21T17:46:51.773" Title="Where to find DNA structural atomic coordinates?" Tags="|computational-chemistry|structural-biology|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7201" PostTypeId="1" AcceptedAnswerId="7208" CreationDate="2021-12-05T11:58:28.707" Score="8" ViewCount="149" Body="&lt;p&gt;I am doing a code that can calculate the hartree-fock energy. I want to form the two-electrons integral by reading the data from the input like this one below.  The first four number are the indices of array(Matrix) and not all the indices are written because some of them are the same such as 2 1 1 1 == 1 2 1 1&#xA;and the float number is the value of index and value of my two-electrons that I want to form an array using these float number&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1    1    1    1      0.7746059439198979&#xA;2    1    1    1      0.4441350695399573&#xA;2    1    2    1      0.2970603935859659&#xA;2    2    1    1      0.5696940113278337&#xA;2    2    2    1      0.4441350695399575&#xA;2    2    2    2      0.7746059439198979&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I use my code and I didn't get what I want.&lt;/p&gt;&#xA;&lt;p&gt;My code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;electron2 = []&#xA;for line in open('Two_Electron.txt'):&#xA;    r,c,d,e,v = line.split()&#xA;    r = int(r)-1&#xA;    c = int(c)-1&#xA;    d = int(d)-1&#xA;    e = int(e)-1    &#xA;    v = float(v)&#xA;    if c == 0: &#xA;        electron2.append( [v] )&#xA;    else:&#xA;        electron2[-1].append(v)&#xA;&#xA;for i in range(len(electron2)-1):&#xA;    for j in range(i+1,len(electron2)):&#xA;        for k in range(len(electron2)-1):&#xA;            for l in range(k+2,len(electron2)):&#xA;                electron2[i].append( electron2[j][i] )&#xA;                electron2[k].append( electron2[l][k] )              &#xA;                &#xA;V_ee = np.array(electron2)&#xA;&#xA;print(V_ee)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output I got is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[list([0.7746059439198979, 0.4441350695399573, 0.2970603935859659, 0.2970603935859659, 0.2970603935859659, 0.2970603935859659])&#xA; list([0.4441350695399573, 0.5696940113278337])&#xA; list([0.2970603935859659, 0.5696940113278337, 0.4441350695399575, 0.7746059439198979])]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output I want to get&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[[[0.77460594 0.4441351 ]&#xA;   [0.4441351  0.56969403]]&#xA;&#xA;  [[0.4441351  0.29706043]&#xA;   [0.29706043 0.4441351 ]]]&#xA;&#xA;&#xA; [[[0.4441351  0.29706043]&#xA;   [0.29706043 0.4441351 ]]&#xA;&#xA;  [[0.56969403 0.4441351 ]&#xA;   [0.4441351  0.77460594]]]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What did I do wrong?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="7" LastEditDate="2021-12-06T15:59:49.603" LastActivityDate="2021-12-06T15:59:49.603" Title="How to read data from an input and form two-electrons integral?" Tags="|python|hartree-fock|pyscf|integrals|fcidump|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7202" PostTypeId="2" ParentId="7169" CreationDate="2021-12-05T12:24:35.050" Score="7" Body="&lt;p&gt;First, let's look from the most fundamental point of view. For this part of the answer I'll be referencing McQuarrie's Statistical Mechanics [1].&#xA;As the Gibbs free energy, &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;, can be calculated from the molecular partition function, &lt;span class=&quot;math-container&quot;&gt;$q_{\text {molecule }}$&lt;/span&gt;, we will start with &lt;span class=&quot;math-container&quot;&gt;$q_{\text {molecule }}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$q_{\text {molecule }}=q_{\text {translational }} q_{\text {rotational }} q_{\text {vibrational }} q_{\text {electronic }} \cdots$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, we assume that molecular Hamiltonian can be approximated by a sum of Hamiltonians for the various degrees of freedom of the molecule (which is not always true).&lt;/p&gt;&#xA;&lt;p&gt;Now, focusing on the electronic partition function, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$q_{\mathrm{elect}}=\sum \omega_{e i} e^{-\beta \varepsilon_{i}} \quad\quad(1)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\omega_{e i}$&lt;/span&gt; is the degeneracy, and &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_i$&lt;/span&gt; the energy of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th electronic level. &lt;span class=&quot;math-container&quot;&gt;$\beta = 1/k_\mathrm{B}T$&lt;/span&gt;.&#xA;Setting the arbitrary zero of energy such that &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_1 = 0$&lt;/span&gt;, the electronic contribution to &lt;span class=&quot;math-container&quot;&gt;$q_{\text {molecule }}$&lt;/span&gt; can then be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$q_{\mathrm{elect}}=\omega_{e 1}+\omega_{e 2} e^{-\beta \Delta \varepsilon_{12}}+\cdots$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Delta \varepsilon_{1 j}$&lt;/span&gt; is the energy of the &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;th electronic level relative to the ground state. These are typically of the order of electron volts, so &lt;span class=&quot;math-container&quot;&gt;$\beta\Delta\varepsilon$&lt;/span&gt; is typically large at ordinary temperature and only the first term in the summation for &lt;span class=&quot;math-container&quot;&gt;$q_{\mathrm{elect}}$&lt;/span&gt; is significantly different from zero.&lt;/p&gt;&#xA;&lt;p&gt;As your question mentions the carbon atom and as electronic energies of atoms are well tabulated [2], let's take a closer look at that.&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;atom&lt;/th&gt;&#xA;&lt;th&gt;electronic configuration&lt;/th&gt;&#xA;&lt;th&gt;term symbol&lt;/th&gt;&#xA;&lt;th&gt;degeneracy &lt;span class=&quot;math-container&quot;&gt;$g = 2J + 1$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;th&gt;energy (cm&lt;span class=&quot;math-container&quot;&gt;$^{-1})$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;C&lt;/td&gt;&#xA;&lt;td&gt;2s&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;2p&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$^3P_0$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;0.0000000&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt; &lt;/td&gt;&#xA;&lt;td&gt; &lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$^3P_1$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;16.4167130&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt; &lt;/td&gt;&#xA;&lt;td&gt; &lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$^3P_2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;td&gt;43.4134567&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;Using eq. 1, we can calculate &lt;span class=&quot;math-container&quot;&gt;$q_{\mathrm{elect}}$&lt;/span&gt; at different temperatures:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;&lt;span class=&quot;math-container&quot;&gt;$T(\mathrm{K})$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;th&gt;&lt;span class=&quot;math-container&quot;&gt;$q_{\mathrm{elect}}(T)$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;298.15&lt;/td&gt;&#xA;&lt;td&gt;7.8264551&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2000&lt;/td&gt;&#xA;&lt;td&gt;8.811036&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;20000&lt;/td&gt;&#xA;&lt;td&gt;8.9808679&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;We can see that at absolute zero the partition function is the degeneracy of the ground state and that it increases as the temperature increases, going to the limit of 9 at infinite temperature as all available states would be accessible and the spin-orbit coupling would be negligible (note that we would have to include more states in eq. 1 at high temperatures). If one neglected spin-orbit coupling from the beginning, the result would be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ q_{\mathrm{elect}}(T) = 9 = (2S+1)(2L+1) = \sum_J (2J+1)$$&lt;/span&gt; for any temperature.&lt;/p&gt;&#xA;&lt;p&gt;Now, one has to think how to make a general implementation of something like this in an electronic structure code. And here is my opinion: you don't.&lt;/p&gt;&#xA;&lt;p&gt;If one does a non relativistic calculation for the ground state of the carbon atom, assuming that one has to work with an Abelian point group, one can use the &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; point group where a &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; state would have components in the &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt; irreducible representations. Individually, each single one of them is non-degenerate, so I don't think that there is a way for the code to know that it must account for other components that it is not computing. Therefore, it seems reasonable to consider only the spin part as other codes do, for example Gaussian [3].&lt;/p&gt;&#xA;&lt;p&gt;If the user wants to include excited states or consider the full degeneracy of the electronic ground state in a thermochemical calculation, it must be dealt case by case, manually. If one has near degenerate electronic states, including a few terms in the electronic partition function is the least of their problems.&lt;/p&gt;&#xA;&lt;p&gt;One thing that you can to in your code to facilite for the user is to allow them to override the standard &lt;span class=&quot;math-container&quot;&gt;$g_0 = (2S+1)$&lt;/span&gt; in an input option. For example, if I want to use &lt;span class=&quot;math-container&quot;&gt;$g_0 = 7.8264551$&lt;/span&gt; in my thermochemical calculation for the carbon atom, I could provide that in my input.&lt;/p&gt;&#xA;&lt;p&gt;And of course, everything could be well documented in the manual and, even, in the output file.&lt;/p&gt;&#xA;&lt;p&gt;Here are some examples of rate constant calculations that make use of experimental data to include the spin-orbit coupling in the calculation of the electronic partition function of some reactants.&lt;/p&gt;&#xA;&lt;p&gt;In the study of the O(&lt;span class=&quot;math-container&quot;&gt;$^3P$&lt;/span&gt;) + HBr reaction [4], the potential energy surface was calculated at the MRCI/CBS+SO level of theory and the electronic partition function of the oxygen atom, in its ground state was calculated as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ q_\mathrm{el} = 5+3 \mathrm{e}^{-227.8 / \mathrm{T}}+\mathrm{e}^{-326.6 / T}$$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the study of the OH(&lt;span class=&quot;math-container&quot;&gt;$^2\Pi$&lt;/span&gt;) + HBr [5], the potential energy surface was determined at the UCCSD(T)/cc-pVDZ-F12a level of theory and the electronic partition function of the hydroxyl radical, in its ground state was calculated as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$g_{\mathrm{el}}(T)=2\left(1+\mathrm{e}^{-|A| h c / k_{\mathrm{B}} T}\right)$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is the experimental spin-orbit coupling constant.&lt;/p&gt;&#xA;&lt;p&gt;In the context of chemical kinetics, this procedure is related to the fact that multiple potential energy surfaces arise from the reaction of species in degenerate electronic states and only a fraction of the collisions will follow the ground state surface, which is the most relevant for low energy reactive scattering [6].&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;McQuarrie, Donald A. Statistical mechanics. New York: Harper &amp;amp; Row, 1975.&lt;/li&gt;&#xA;&lt;li&gt;Kramida, A., Ralchenko, Yu., Reader, J., and NIST ASD Team (2021). NIST Atomic Spectra Database (ver. 5.9), [Online]. Available: &lt;a href=&quot;https://physics.nist.gov/asd&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://physics.nist.gov/asd&lt;/a&gt; [2021, December 5]. National Institute of Standards and Technology, Gaithersburg, MD. DOI: &lt;a href=&quot;https://doi.org/10.18434/T4W30F&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.18434/T4W30F&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gaussian.com/thermo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gaussian.com/thermo/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;A. G. S. de Oliveira-Filho, F. R. Ornellas, K. A. Peterson, S. L. Mielke, Thermal Rate Constants for the O(3P) + HBr and O(3P) + DBr Reactions: Transition-State Theory and Quantum Mechanical Calculations. &lt;a href=&quot;http://pubs.acs.org/doi/abs/10.1021/jp4090684&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A. 117, 12703–12710 (2013)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;A. G. S. de Oliveira-Filho, F. R. Ornellas, J. M. Bowman, Energy Disposal and Thermal Rate Constants for the OH + HBr and OH + DBr Reactions: Quasiclassical Trajectory Calculations on an Accurate Potential Energy Surface. &lt;a href=&quot;http://dx.doi.org/10.1021/jp509430p&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. A. 118, 12080–12088 (2014)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;D. G. Truhlar, Multiple Potential Energy Surfaces for Reactions of Species in Degenerate Electronic States, &lt;a href=&quot;http://dx.doi.org/10.1063/1.1677674&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 56, 3189–3190 (1972)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastEditorUserId="878" LastEditDate="2021-12-06T18:12:45.893" LastActivityDate="2021-12-06T18:12:45.893" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7203" PostTypeId="2" ParentId="7200" CreationDate="2021-12-05T12:53:30.843" Score="10" Body="&lt;p&gt;If you know the program AMBER, There is an option where you write an input with the sequence that you want, automatically the program will build the two strands, and your output will be pdb format. Or You can use Avogadro program direct and you will write the sequence and the output will be XYZ format.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eQwLT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eQwLT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The output&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vNQcV.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vNQcV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2021-12-05T12:53:30.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7204" PostTypeId="2" ParentId="7193" CreationDate="2021-12-05T17:48:34.780" Score="6" Body="&lt;p&gt;I have found that the &lt;strong&gt;stable magnetic phase should be investigated first&lt;/strong&gt; before considering dynamic stability (Phonons). Because &lt;strong&gt;phonons are dependant on the magnetic phase&lt;/strong&gt; of the system especially if it is magnetic. Also, spin-polarized tags should be included in calculation inputs, like in VASP: &lt;code&gt;ISPIN=2&lt;/code&gt; and &lt;code&gt;MAGMOM&lt;/code&gt; tags should be included.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-12-05T17:48:34.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7205" PostTypeId="2" ParentId="7197" CreationDate="2021-12-06T06:46:29.177" Score="5" Body="&lt;p&gt;You have provided a LAMMPS data file as input to VMD and AFAIU, the default &lt;code&gt;New Molecule&lt;/code&gt; option from VMD can't read this format. I am not sure how you are reading the given file, but I think the issue you are facing is due to the way you are reading the file in VMD.&lt;/p&gt;&#xA;&lt;p&gt;You can use the &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/plugins/topotools/&quot; rel=&quot;noreferrer&quot;&gt;TopoTools plugin&lt;/a&gt; (which is available by default in VMD) to read this file. As the file you provided is a LAMMPS data file with &lt;code&gt;atom_style&lt;/code&gt; as &lt;code&gt;charge&lt;/code&gt;, the command to read it would be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;topo readlammpsdata data.lammps charge&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;data.lammps&lt;/code&gt; is the input LAMMPS data file given in the question. By changing the &amp;quot;Drawing Method&amp;quot; to &lt;code&gt;CPK&lt;/code&gt; and &amp;quot;Coloring Method&amp;quot; to &lt;code&gt;Index&lt;/code&gt;, you get the following:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/JUR7l.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JUR7l.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;br /&gt;&#xA;and you can see that there is no multiple bonds per atom here.&lt;/p&gt;&#xA;" OwnerUserId="85" LastActivityDate="2021-12-06T06:46:29.177" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7206" PostTypeId="1" CreationDate="2021-12-06T09:07:19.053" Score="7" ViewCount="423" Body="&lt;p&gt;I am dealing with a magnetic system.&lt;/p&gt;&#xA;&lt;p&gt;With Quantum Espresso I am getting the result as a half-metal but while using VASP we are getting it as a semiconductor.&lt;/p&gt;&#xA;&lt;p&gt;I would be glad if someone can provide me an INCAR equivalent tags of the quantum espresso input file&lt;/p&gt;&#xA;&lt;p&gt;Here is our INCAR file,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM = AxBy-bulk&#xA;PREC = Accurate&#xA;ISTART = 0 &#xA;ICHARG = 2&#xA;ENCUT = 850&#xA;NELM = 200; NELMIN= 6; NELMDL= -5&#xA;EDIFF = 1E-5&#xA;#LREAL = Auto&#xA;ISPIN = 2&#xA;MAGMOM = 4*-5 2*5 8*0&#xA;ALGO = Normal&#xA;EDIFFG = -1E-2&#xA;NSW = 0   &#xA;IBRION = -1&#xA;#ISIF = 3&#xA;ISYM = 0&#xA;POTIM = 0.2&#xA;ISMEAR = -5&#xA;SIGMA = 0.05&#xA;LWAVE = F&#xA;LCHARG = T&#xA;LORBIT = 11&#xA;LDAU      = .TRUE.&#xA;LDAUTYPE  = 2&#xA;LDAUL     = 2    2    -1 &#xA;LDAUU     = 5.00 5.00 0.00&#xA;LDAUJ     = 0.00 0.00 0.00&#xA;LDAUPRINT = 2&#xA;LMAXMIX   = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;my QE input file is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  etot_conv_thr =   0.0001&#xA;  forc_conv_thr =   0.001&#xA;  outdir = './tmp/'&#xA;  prefix = 'pwscf'&#xA;  pseudo_dir = './'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;!  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss =   0.022&#xA;  ecutrho =   840&#xA;  ecutwfc =   70&#xA;  ibrav = 0&#xA;  nat = 56&#xA;  nosym = .True.&#xA;  nspin = 2&#xA;  ntyp = 3&#xA;nbnd=350&#xA;  occupations = 'smearing'&#xA;  smearing = 'gauss'&#xA;  starting_magnetization(1) =   1&#xA;  starting_magnetization(2) =   -1&#xA;  starting_magnetization(3) =   0&#xA;  nspin = 2&#xA;  lda_plus_u=.true.&#xA;  Hubbard_U(1)=3&#xA;  Hubbard_U(2)=3&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.00000000d-06&#xA;  electron_maxstep = 300&#xA;  mixing_beta =   1.500000000d-01&#xA;!mixing_mode='local-TF'&#xA;&#xA;/&#xA;&amp;amp;IONS&#xA;                ion_dynamics = 'bfgs'&#xA; /&#xA;&amp;amp;CELL&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;A1      A.pbe-nd-rrkjus.UPF&#xA;A2     A.pbe-nd-rrkjus.UPF&#xA;B       B.pbe-rrkjus.UPF&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="789" LastEditorUserId="85" LastEditDate="2021-12-06T13:10:52.447" LastActivityDate="2021-12-06T18:21:59.487" Title="Need INCAR equivalent Quantum Espresso input file" Tags="|vasp|quantum-espresso|software-input-file-request|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7207" PostTypeId="2" ParentId="467" CreationDate="2021-12-06T13:12:52.643" Score="6" Body="&lt;h1&gt;PyMOL&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Molecular visualization system built on top of a python backend that can be used for scripting&lt;/li&gt;&#xA;&lt;li&gt;Powerful and flexible interface with GUI and command line options&lt;/li&gt;&#xA;&lt;li&gt;Conceived with biological systems in mind, but relevant for any molecular system&lt;/li&gt;&#xA;&lt;li&gt;Commercial product, but built on an open-source foundation and available for free for &lt;a href=&quot;https://pymol.org/edu/index.php&quot; rel=&quot;noreferrer&quot;&gt;Educational-Use-Only&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Available on Windows, MAC and Linux. Can be installed with conda&lt;/li&gt;&#xA;&lt;li&gt;Official website: &lt;a href=&quot;https://pymol.org/&quot; rel=&quot;noreferrer&quot;&gt;https://pymol.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pymol.org/2/img/screenshot1_rhodopsin.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://pymol.org/2/img/screenshot1_rhodopsin.png&quot; alt=&quot;Screenshot taken from the official website front page&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-12-06T13:12:52.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7208" PostTypeId="2" ParentId="7201" CreationDate="2021-12-06T15:03:37.313" Score="3" Body="&lt;p&gt;I'm not sure how your current code is supposed to work. Focusing just on the first half:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;electron2 = []&#xA;for line in open('Two_Electron.txt'):&#xA;    r,c,d,e,v = line.split()&#xA;    r = int(r)-1&#xA;    c = int(c)-1&#xA;    d = int(d)-1&#xA;    e = int(e)-1    &#xA;    v = float(v)&#xA;    if c == 0: &#xA;        electron2.append( [v] )&#xA;    else:&#xA;        electron2[-1].append(v)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It creates three nested lists:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[list([0.7746059439198979, 0.4441350695399573])&#xA; list([0.4441350695399573, 0.5696940113278337])&#xA; list([0.2970603935859659, 0.5696940113278337, 0.4441350695399575, 0.7746059439198979])]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since the remaining part of the code just appends to these list (and, at least in this case, just the first one), its difficult to see how you intend to convert these three lists to a 4D array.&lt;/p&gt;&#xA;&lt;p&gt;To me, the conceptually simplest way to do this would be to just take these values and fill them into the symmetry equivalent elements of an already initialized 4D array.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NBasis=2 #Could be determined with earlier code or just pre-entered&#xA;electron2 = np.zeros((NBasis,NBasis,NBasis,NBasis))&#xA;for line in open('Two_Electron.txt'):&#xA;    r,c,d,e,v = line.split()&#xA;    r = int(r)-1&#xA;    c = int(c)-1&#xA;    d = int(d)-1&#xA;    e = int(e)-1    &#xA;    val = float(v)&#xA;&#xA;    #Fill in all symmetry equivalent elements&#xA;    electron2[r,c,d,e]=val                             &#xA;    electron2[c,r,d,e]=val                                    &#xA;    electron2[r,c,e,d]=val    &#xA;    electron2[c,r,e,d]=val    &#xA;    &#xA;    #Need to take complex conjugate if not all real integrals&#xA;    #Assume integrals are indexed with chemist notation&#xA;    electron2[d,e,r,c]=val    &#xA;    electron2[e,d,r,c]=val    &#xA;    electron2[d,e,c,r]=val    &#xA;    electron2[e,d,c,r]=val    &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you have control over the input you are reading in, I would just put &lt;code&gt;NBasis&lt;/code&gt; at the beginning of it to avoid having to set it manually or having to go through a more complicated process to determine it automatically.&lt;/p&gt;&#xA;&lt;p&gt;There are definitely other things that could be done to make this cleaner/faster/etc, but this is probably the most direct way to do this.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-12-06T15:46:24.667" LastActivityDate="2021-12-06T15:46:24.667" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7209" PostTypeId="2" ParentId="7206" CreationDate="2021-12-06T18:21:59.487" Score="4" Body="&lt;p&gt;I notice you are using Hubbard U in your input file and you are not using the same Hubbard U in both, which is probably good.  However, you might consider if using a larger U value does give you the same result in VASP.  These results could be sensitive to this parameter.&lt;/p&gt;&#xA;&lt;p&gt;You may also want to actually show the spin resolved PDOS for both codes, that might reveal something if it turns out this suggestion does not work.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-12-06T18:21:59.487" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7210" PostTypeId="2" ParentId="6324" CreationDate="2021-12-06T19:43:38.477" Score="3" Body="&lt;p&gt;If I'm interpreting your last equation correctly, this is more or less true by definition. My interpretation of the equation (rearranging and subbing in variables):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{A_\text{CM}}{\Delta x_\text{CM}}=\langle t_\text{c} \rangle$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Delta x_\text{CM}$&lt;/span&gt; is the net displacement of the center of mass traveled in some time interval and &lt;span class=&quot;math-container&quot;&gt;$A_\text{CM}$&lt;/span&gt; is the mean &lt;a href=&quot;https://en.wikipedia.org/wiki/Absement&quot; rel=&quot;nofollow noreferrer&quot;&gt;absement&lt;/a&gt; or time integral of the displacement over that interval. Absement isn't a commonly used metric (I hadn't heard of it before researching this question), but you could think of it as a time-weighted displacement (or a displacement-weighted time). So in words, I think your equation would say &amp;quot;the average collision time is equal to the displacement-weighted time divided by the net displacement&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;While I think you could verify this by running an MD simulation and computing these quantities individually, I think this relationship basically just contains the same information as the typical expression for collision time (mean free time), which is just the mean free path divided by the average speed.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-12-06T19:43:38.477" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7211" PostTypeId="1" CreationDate="2021-12-07T02:39:57.553" Score="8" ViewCount="98" Body="&lt;p&gt;A Dyson orbital is defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\textrm{Dy}(x) = \int dx_1 \ldots dx_{N-1} \, (\Psi^+(x_1,\ldots,x_{N-1}))^* \, \Psi^0(x_1,\ldots,x_{N-1}, x),\tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\Psi^0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Psi^+$&lt;/span&gt; are the total wavefunctions of the neutral and cation, respectively.&#xA;For &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron molecule within Hartree-Fock picture, it's known that in most cases the Dyson orbital is similar to the HOMO of the neutral species and this is due to the fact that the MO's of the cation often look similar to the first &lt;span class=&quot;math-container&quot;&gt;$N-1$&lt;/span&gt; MO's of the neutral. Let's take an example of the &lt;span class=&quot;math-container&quot;&gt;$\ce{CO_2}$&lt;/span&gt; molecular orbital obtained by Hartree-Fock method where the HOMO has &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; symmetry and is thus doubly degenerate. One may identify these HOMO as &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;. Now the HOMO of &lt;span class=&quot;math-container&quot;&gt;$\ce{CO_2^+}$&lt;/span&gt; obtained with the same method also has &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; symmetry but is not degenerate, and I guess depending on the initial guess, it may collapse to having either &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;. If say, it has &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt; symmetry and then you calculate the Dyson orbital, it will have &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; symmetry.&lt;/p&gt;&#xA;&lt;p&gt;What looks strange to me is that the Dyson orbital does not seem to respect the degeneracy of the neutral. &lt;strong&gt;Or is it that there is a special treatment for degeneracy in calculating Dyson orbital?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1121" LastEditorUserId="5" LastEditDate="2022-01-20T22:36:40.270" LastActivityDate="2022-01-20T22:36:40.270" Title="Is the formula of a Dyson orbital independent of whether there is degeneracy or not in the HOMO of the neutral?" Tags="|symmetry|hartree-fock|orbitals|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="7212" PostTypeId="5" CreationDate="2021-12-07T20:53:48.453" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-07T20:53:48.453" LastActivityDate="2021-12-07T20:53:48.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7213" PostTypeId="4" CreationDate="2021-12-07T20:53:48.453" Score="0" Body="Questions about or related to supercells." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-07T20:53:48.453" LastActivityDate="2021-12-07T20:53:48.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7214" PostTypeId="5" CreationDate="2021-12-07T21:00:26.987" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-07T21:00:26.987" LastActivityDate="2021-12-07T21:00:26.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7215" PostTypeId="4" CreationDate="2021-12-07T21:00:26.987" Score="0" Body="Questions about or related to quantum dots." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-07T21:00:26.987" LastActivityDate="2021-12-07T21:00:26.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7216" PostTypeId="1" AcceptedAnswerId="7220" CreationDate="2021-12-08T07:46:26.077" Score="7" ViewCount="679" Body="&lt;p&gt;In this paper &amp;quot;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.98.245203&quot; rel=&quot;noreferrer&quot;&gt;Unified theory of direct or indirect band-gap nature of conventional semiconductors&lt;/a&gt;&amp;quot;, the authors calculated the irreducible representations of atomic orbitals at three K points, as shown in Table 1&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/g73Nml.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/g73Nml.png&quot; alt=&quot;test&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How such irreducible representations are determined? For example, I calculate electronic band structures using VASP, is there any software that can calculate the irreducible representations, particularly, the irreducible representations of atomic orbitals from the WAVECAR file?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastActivityDate="2021-12-08T18:36:26.890" Title="How to determine the irreducible representation of an atomic orbital at a K point?" Tags="|vasp|space-groups|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7217" PostTypeId="1" AcceptedAnswerId="7224" CreationDate="2021-12-08T15:58:00.840" Score="10" ViewCount="1429" Body="&lt;p&gt;The issue here is while converting a TRAJ file to POSCAR, it works. But, for TRAJ to XDATCAR, it shows &lt;code&gt;TypeError: images should be a sequence of Atoms objects&lt;/code&gt;. (Check below to see the error report)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase &#xA;from ase.io import read, write&#xA;from ase.io.vasp import write_vasp_xdatcar&#xA;&#xA;bec = ase.io.read(&amp;quot;./run10/local_minima.traj&amp;quot;)&#xA;bec_new_pos = ase.io.vasp.write_vasp(&amp;quot;local_minima_new.poscar&amp;quot;, bec, vasp5=True)&#xA;bec_new_xdat = ase.io.vasp.write_vasp_xdatcar(&amp;quot;local_minima_new.xdatcar&amp;quot;, bec, label=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;TypeError                                 Traceback (most recent call last)&#xA;/tmp/ipykernel_143176/175431421.py in &amp;lt;module&amp;gt;&#xA;      5 bec = ase.io.read(&amp;quot;./run10/local_minima.traj&amp;quot;)&#xA;      6 bec_new_pos = ase.io.vasp.write_vasp(&amp;quot;local_minima_new.poscar&amp;quot;, bec, vasp5=True)&#xA;----&amp;gt; 7 bec_new_xdat = ase.io.vasp.write_vasp_xdatcar(&amp;quot;local_minima_new.xdatcar&amp;quot;, bec, label=None)&#xA;&#xA;/usr/lib/python3/dist-packages/ase/utils/__init__.py in iofunc(file, *args, **kwargs)&#xA;    453                 else:&#xA;    454                     fd = file&#xA;--&amp;gt; 455                 obj = func(fd, *args, **kwargs)&#xA;    456                 return obj &#xA;    457             finally:&#xA;&#xA;/usr/lib/python3/dist-packages/ase/io/vasp.py in write_vasp_xdatcar(fd, images, label)&#xA;    596 &#xA;    597     if not isinstance(image, Atoms):&#xA;--&amp;gt; 598         raise TypeError(&amp;quot;images should be a sequence of Atoms objects.&amp;quot;)&#xA;    599 &#xA;    600     symbol_count = _symbol_count_from_symbols(image.get_chemical_symbols())&#xA;&#xA;TypeError: images should be a sequence of Atoms objects.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="7" LastEditDate="2021-12-08T16:34:34.673" LastActivityDate="2021-12-09T10:20:14.310" Title="ASE convesion of Trajectory file to XDATCAR" Tags="|molecular-dynamics|molecular-modeling|databases|atomic-simulation-environment|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7218" PostTypeId="1" CreationDate="2021-12-08T17:29:29.160" Score="9" ViewCount="768" Body="&lt;p&gt;I found plenty of packages that open &lt;code&gt;.nc&lt;/code&gt; files but all specifically catered to climate (meteorological) and geo-maps data. &lt;strong&gt;I would like to get suggestions of software that can open &lt;code&gt;.nc&lt;/code&gt; (NetCDF), which are either &lt;em&gt;generic&lt;/em&gt;, or cater to matter modeling.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have files related to condensed matter results such as electrostatic potential surfaces (with the structure information too).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-12-11T01:54:42.913" LastActivityDate="2022-07-16T17:08:44.040" Title="Recommended software to open NetCDF files?" Tags="|software-recommendations|one-topic-per-answer|high-performance-computing|visualization-software|" AnswerCount="5" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7219" PostTypeId="2" ParentId="7216" CreationDate="2021-12-08T18:24:56.117" Score="4" Body="&lt;p&gt;For VASP, you may try &lt;a href=&quot;https://github.com/zjwang11/irvsp&quot; rel=&quot;nofollow noreferrer&quot;&gt;irvasp&lt;/a&gt; or &lt;a href=&quot;https://github.com/stepan-tsirkin/irrep&quot; rel=&quot;nofollow noreferrer&quot;&gt;irRep&lt;/a&gt;. Or for Quantum espresso, you can directly read the group representations from the output of &lt;code&gt;bands.x&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2021-12-08T18:36:26.890" LastActivityDate="2021-12-08T18:36:26.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7220" PostTypeId="2" ParentId="7216" CreationDate="2021-12-08T18:31:54.680" Score="3" Body="&lt;p&gt;I don't know off-hand about software that can do this (though I expect it exists). You can find these irreducible in a character table for that type of k-point and symmetry of the wavevector.&lt;/p&gt;&#xA;&lt;p&gt;For example &lt;a href=&quot;https://link.springer.com/content/pdf/bbm%3A978-3-540-32899-5%2F1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Table C10&lt;/a&gt;, which I reproduce here with slight edits for notation  I'm more accustom to using for molecular point groups, gives the character table for &lt;span class=&quot;math-container&quot;&gt;$C_{3v}$&lt;/span&gt; at the point &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt;/&lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{array}{c|ccc|c} \hline&#xA;C_\mathrm{3v}(\Lambda) &amp;amp; E &amp;amp; 2C_3 &amp;amp; 3\sigma_\mathrm{v} &amp;amp; \text{Basis} \\ \hline&#xA;\mathrm{\Lambda_1} &amp;amp; 1 &amp;amp; 1 &amp;amp; 1 &amp;amp; 1, z, x^2+y^2, z^2 \\ &#xA;\mathrm{\Lambda_2} &amp;amp; 1 &amp;amp; 1 &amp;amp; -1     \\ &#xA;\mathrm{\Lambda_3} &amp;amp; 2 &amp;amp; -1 &amp;amp; 0 &amp;amp; (x,y), (x^2-y^2,xy), (xz,yz) \\ \hline&#xA;\end{array}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can then determine the irrep of an orbital based on the symmetry of the basis elements needed to represent it. For example, an &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; orbital is formed from a totally symmetric function, so it has the totally symmetry irrep &lt;span class=&quot;math-container&quot;&gt;$\Lambda_1$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; have a similar totally symmetric component, but also include factors of &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; respectively, so the  &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; orbitals are &lt;span class=&quot;math-container&quot;&gt;$\Lambda_1\oplus\Lambda_3$&lt;/span&gt;, with the &lt;span class=&quot;math-container&quot;&gt;$\Lambda_1$&lt;/span&gt; due to &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; and the &lt;span class=&quot;math-container&quot;&gt;$\Lambda_3$&lt;/span&gt; from the combination of &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2021-12-08T18:31:54.680" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7221" PostTypeId="2" ParentId="1125" CreationDate="2021-12-08T19:47:16.743" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I would like to be able to run my own &amp;quot;hobby&amp;quot; simulations at home, so a low energy, low capital investment is what I seek.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Disclaimer. I have not made a Raspberry Pi cluster.&lt;/p&gt;&#xA;&lt;p&gt;A few months ago (10/24/2021) the &lt;a href=&quot;https://turingpi.com/turing-pi-v2-is-here/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Turing Pi 2&lt;/a&gt; board was released.&lt;/p&gt;&#xA;&lt;p&gt;For a YouTube video (12/01/2021) on how to build a computer with 4 &lt;a href=&quot;https://www.raspberrypi.com/products/compute-module-4/?variant=raspberry-pi-cm4001000&quot; rel=&quot;nofollow noreferrer&quot;&gt;Raspberry Pi compute modules&lt;/a&gt; see this Jeff Geerling video.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=IUPYpZBfsMU&quot; rel=&quot;nofollow noreferrer&quot;&gt;4 Pis on a mini ITX board! The Turing Pi 2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;If anyone is wondering if Raspberry Pi is considered a valid way to go then consider this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.zdnet.com/article/raspberry-pi-supercomputer-los-alamos-to-use-10000-tiny-boards-to-test-software/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Raspberry Pi supercomputer: Los Alamos to use 10,000 tiny boards to test software&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Something to keep an eye on are these:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.jeffgeerling.com/blog/2021/uptime-labs-cm4-blade-adds-nvme-tpm-20-raspberry-pi&quot; rel=&quot;nofollow noreferrer&quot;&gt;Uptime Lab's CM4 Blade adds NVMe, TPM 2.0 to Raspberry Pi&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As noted on the web site&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A 1U rackmount enclosure is in the works, and 16 of these boards would deliver:&lt;/p&gt;&#xA;&lt;p&gt;64 ARM CPU cores&lt;br /&gt;&#xA;up to 128 GB of RAM&lt;br /&gt;&#xA;16 TB+ of NVMe SSD storage&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Jeff has a video on these&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://youtu.be/zH9GwYZu_aE&quot; rel=&quot;nofollow noreferrer&quot;&gt;Uptime Lab's CM4 Blade adds NVMe, TPM 2.0 to Raspberry Pi&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;but AFAIK these blades are not yet for sale. (12/09/2021) :-(&lt;/p&gt;&#xA;" OwnerUserId="4610" LastEditorUserId="4610" LastEditDate="2021-12-09T06:45:03.943" LastActivityDate="2021-12-09T06:45:03.943" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7222" PostTypeId="2" ParentId="7217" CreationDate="2021-12-08T21:05:12.660" Score="6" Body="&lt;p&gt;This should work, basically, one needs to put iterable of atoms as images.&#xA;So, using the trajectory reader should do the trick.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase&#xA;from ase.io import read, write&#xA;from ase.io.vasp import write_vasp_xdatcar&#xA;from ase.io.trajectory import Trajectory&#xA;&#xA;bec = Trajectory(&amp;quot;./run10/local_minima.traj&amp;quot;)&#xA;bec_new_xdat = ase.io.vasp.write_vasp_xdatcar(&amp;quot;local_minima_new.xdatcar&amp;quot;, bec, label=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastActivityDate="2021-12-08T21:05:12.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7223" PostTypeId="2" ParentId="2384" CreationDate="2021-12-09T02:44:26.880" Score="5" Body="&lt;p&gt;After a few months working with Aluminum-based structures, I'm confident to respond to my own question. And the answer is &lt;strong&gt;NO&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Keeping in mind that I'm using the IPA (independent particle approximation) to evaluate the optical properties since I'm dealing with metals (and the approximation is good enough), Quantum ESPRESSO presents two main packages: epsilon.x and simple.x, both written at IPA level.&lt;/p&gt;&#xA;&lt;p&gt;The major difference is that simple.x employs the optimal basis method to evaluate a reduced set of basis functions followed by a band interpolation and non-local commutator to speed up the calculations. It allows for an interpolated k-grid with twice as many points per direction.&lt;/p&gt;&#xA;&lt;p&gt;Even though simple.x enables a denser mesh with respect to epsilon.x, it comes at a cost of lots and lots of ram memory. Even for relatively small supercells with around 50 atoms, it swallows more than 300Gb of ram to perform the calculation for an interpolated mesh of 70x70x70 k-points. Talking to the developers, they said the amount of memory to be the bottleneck of the code, and that lighter algorithms are welcome.&lt;/p&gt;&#xA;&lt;p&gt;Both epsilon and simples responses are very dependent on the mesh density as well as on the number of unoccupied bands and on the threshold for the self-consistent calculation. For Aluminium, the threshold needed to be as low as 10^-12 Ry. The results agreed very well with the experiments.&lt;/p&gt;&#xA;" OwnerUserId="389" LastActivityDate="2021-12-09T02:44:26.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7224" PostTypeId="2" ParentId="7217" CreationDate="2021-12-09T10:20:14.310" Score="6" Body="&lt;p&gt;By default &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/io.html#ase.io.read&quot; rel=&quot;noreferrer&quot;&gt;ase.io.read&lt;/a&gt; only reads the last frame of the trajectory (an &lt;code&gt;Atoms&lt;/code&gt; object), you need to specify the &lt;code&gt;index&lt;/code&gt; argument to read several frames. &lt;code&gt;index=':'&lt;/code&gt; will read the entire trajectory.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase &#xA;from ase.io import read, write&#xA;from ase.io.vasp import write_vasp_xdatcar&#xA;&#xA;bec = ase.io.read(&amp;quot;./run10/local_minima.traj&amp;quot;, index=':')&#xA;bec_new_pos = ase.io.vasp.write_vasp(&amp;quot;local_minima_new.poscar&amp;quot;, bec, vasp5=True)&#xA;bec_new_xdat = ase.io.vasp.write_vasp_xdatcar(&amp;quot;local_minima_new.xdatcar&amp;quot;, bec, label=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2021-12-09T10:20:14.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7225" PostTypeId="1" AcceptedAnswerId="8280" CreationDate="2021-12-09T14:14:18.703" Score="7" ViewCount="117" Body="&lt;p&gt;I have a very simple technical question with regards to the SIESTA software. When defining an anion/cation for a given species, is it sufficient to add an electron when defining a given species? For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block ChemicalSpecieslabel&#xA;    1 17 S&#xA;%endblock ChemicalSpecieslabel&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or would this just be a Cl atom but with an S symbol. If I am incorrect, can anyone share how they would define an anion/cation in SIESTA ?&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="7" LastEditDate="2021-12-09T14:30:13.830" LastActivityDate="2021-12-17T10:31:34.037" Title="Defining an Anion/Cation in SIESTA" Tags="|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7226" PostTypeId="1" AcceptedAnswerId="7259" CreationDate="2021-12-09T14:30:37.820" Score="4" ViewCount="442" Body="&lt;p&gt;I have been using the ASE-SIESTA-PyNAO module to attempt some RAMAN/IR mode calculations on graphene (if anyone has any experience with this please send me a message maybe we can chat about it). At no point during these calculations do I define mass of carbon (neither in the PyNAO arguments nor in SIESTA species definition arguments which is very strange of course !) to get the RAMAN/IR spectra and I get shifted results (both blue and red shifts, which seem somewhat random) with respect to what a typical RAMAN spectrum of graphene would look like.&lt;/p&gt;&#xA;&lt;p&gt;I have also used the SIESTA/VIBRA module to extract all modes at the Gamma point, those do require mass, which makes sense, but I can't seem to find a method to extract the modes that are RAMAN or IR active from the total modes I obtain from VIBRA.&lt;/p&gt;&#xA;&lt;p&gt;My question here is thus in three parts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Can anyone explain how ASE calculates IR or RAMAN modes without implicating mass of the atoms ? (and if it does where can I toggle it to get better results).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Does anyone have a method for extracting RAMAM or IR active modes from the total modes we can obtain with the VIBRA module from SIESTA ?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Since the method from ASE-PyNAO-SIESTA differs completely from the SIESTA/VIBRA method to calculate vibrational modes, it seems impossible to parse VIBRA results through the ASE calculator to get RAMAN/IR activity. Is this assumption correct ?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="7" LastEditDate="2021-12-14T18:24:03.483" LastActivityDate="2021-12-14T18:24:03.483" Title="RAMAN calculation with SIESTA and ASE-SIESTA" Tags="|spectroscopy|vibrations|siesta|atomic-simulation-environment|pynao|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7227" PostTypeId="1" CreationDate="2021-12-09T15:03:03.067" Score="9" ViewCount="133" Body="&lt;p&gt;I'm using WebMO to construct molecules that have high multireference character, but I cannot seem to find any, or perhaps I'm not building them correctly on WebMO; I know singlet biradicals generally have high MR character, but when I carry out a CI calculation on them, the weight of the Hartree-Fock configuration is extremely high (1/Norm(A) value). I've carried out CI calculations on TMM, TME, p-quinodimethane, but these do not exhibit high MR character using my diagnostic of looking at the weight of the HF configuration in a CI calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can anyone suggest any medium-sized molecules that exhibit high MR character?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#N CI/6-31G(d) SP &#xA;&#xA;C4H6&#xA;&#xA;0 1&#xA;C &#xA;C 1 B1&#xA;C 2 B2 1 A1&#xA;H 3 B3 2 A2 1 D1&#xA;H 3 B4 2 A3 1 D2&#xA;C 2 B5 1 A4 3 D3&#xA;H 6 B6 2 A5 1 D4&#xA;H 6 B7 2 A6 1 D5&#xA;H 1 B8 2 A7 3 D6&#xA;H 1 B9 2 A8 3 D7&#xA;&#xA;B1 1.322324000&#xA;B2 1.469933386&#xA;B3 1.089341949&#xA;B4 1.089341949&#xA;B5 1.469933386&#xA;B6 1.089341949&#xA;B7 1.089341949&#xA;B8 1.087824972&#xA;B9 1.087824972&#xA;A1 148.4186871&#xA;A2 118.9917788&#xA;A3 118.9917788&#xA;A4 148.4186871&#xA;A5 118.9917788&#xA;A6 118.9917788&#xA;A7 121.5429429&#xA;A8 121.5429429&#xA;D1 73.31395214&#xA;D2 -73.31395214&#xA;D3 -180.0000000&#xA;D4 -73.31395214&#xA;D5 73.31395214&#xA;D6 180.0000000&#xA;D7 -0.000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4672" LastEditorUserId="5" LastEditDate="2021-12-15T06:47:00.763" LastActivityDate="2021-12-15T06:52:30.947" Title="Which molecules have multi-reference character?" Tags="|reference-request|computational-chemistry|casscf|multi-reference|configuration-interaction|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="7228" PostTypeId="2" ParentId="7218" CreationDate="2021-12-09T16:15:34.637" Score="4" Body="&lt;p&gt;I don't know if you used VMD.&#xA;In general, if you didn't use VMD. It is one of the best to visualize and there are a lot of options that you can use to analysis if you need. It is available to win and Linux, and I recommend you to use Linux Version.&lt;/p&gt;&#xA;&lt;p&gt;All you need to upload the parameter of your structure or the format you have, depend on your calculation and then load the NetCDF file over the parameter.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zwOOq.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zwOOq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/k0uxs.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k0uxs.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2021-12-09T16:15:34.637" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="7229" PostTypeId="2" ParentId="7218" CreationDate="2021-12-09T16:48:43.077" Score="9" Body="&lt;h2&gt;Python libraries: xarray and hvplot&lt;/h2&gt;&#xA;&lt;p&gt;This is a rather generic answer for opening and quickly visualizing a &lt;code&gt;netCFD&lt;/code&gt; file with python. It is not specific to condensed matter, but can be used for it (I personally use it to explore properties computed during MD simulations).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://docs.xarray.dev/en/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;xarray&lt;/a&gt; is a python library for handling labelled multi-dimensional arrays, &lt;a href=&quot;https://docs.xarray.dev/en/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;primarily stored as netCFD files&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import xarray as xr&#xA;ds = xr.open_dataset(&amp;quot;saved_on_disk.nc&amp;quot;) # read&#xA;ds.to_netcdf(&amp;quot;saved_on_disk.nc&amp;quot;) # write&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It comes with its own &lt;a href=&quot;https://xarray.pydata.org/en/stable/user-guide/plotting.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;built-in plotting methods&lt;/a&gt;, but an easier way to explore the data is to use the &lt;a href=&quot;https://hvplot.holoviz.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;hvPlot&lt;/a&gt; library. It creates customizable and interactive graphs that fit nicely in jupyter notebooks. &lt;a href=&quot;https://hvplot.holoviz.org/user_guide/Gridded_Data.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here's an overview of how it can be used to explore an xarray file&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import hvplot.xarray  # noqa&#xA;ds.hvplot()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h5&gt;Example with Siesta ElectrostaticPotential grid&lt;/h5&gt;&#xA;&lt;p&gt;Using one of the &lt;a href=&quot;https://lamodel.unifal-mg.edu.br/downloads/nc_files.zip&quot; rel=&quot;nofollow noreferrer&quot;&gt;example files provided by Camps&lt;/a&gt;, this plot was obtained with the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ds = xr.open_dataset('ElectrostaticPotential.grid.nc')&#xA;ds.gridfunc.isel(n3=0).hvplot.contour() # plot gridfunc dataarray for first n3 coordinate&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NeDvi.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NeDvi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Exploring all the &lt;code&gt;n3&lt;/code&gt; coordinates  can be done using an &lt;a href=&quot;https://hvplot.holoviz.org/user_guide/Interactive.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;interactive widget&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import panel.widgets as pnw&#xA;ds.gridfunc.interactive().sel(spin=0, n3=pnw.DiscreteSlider).hvplot(x='n1', y ='n2', kind='contour')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1609" LastEditorUserId="118" LastEditDate="2022-07-16T17:08:44.040" LastActivityDate="2022-07-16T17:08:44.040" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7230" PostTypeId="1" CreationDate="2021-12-09T19:44:17.223" Score="4" ViewCount="75" Body="&lt;p&gt;I would like to use a program to automate sorting drug molecules into structurally similar groups. What protocols, or better yet, software, is available to aid this endeavour?&lt;/p&gt;&#xA;&lt;p&gt;For instance, I know one measure of similarity is the &lt;code&gt;Tanimoto similarity coefficient&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Are there better or even just other methods?&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="3606" LastEditDate="2021-12-09T20:58:56.180" LastActivityDate="2021-12-10T19:11:17.987" Title="What ways are there to sort drug molecules into structurally similar groups?" Tags="|structure|fingerprint|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7231" PostTypeId="1" CreationDate="2021-12-10T04:52:11.490" Score="6" ViewCount="576" Body="&lt;p&gt;I am new on the VASP platform, and have learned how to calculate any material's DOS and Band structure.&lt;/p&gt;&#xA;&lt;p&gt;However, I don't know how to interpret these properties. Can you recommend resources that explain the basics of DOS and band structure interpretation?&lt;/p&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="5" LastEditDate="2021-12-25T21:24:05.330" LastActivityDate="2021-12-25T21:24:05.330" Title="How to interpret density of states and band structure of a material?" Tags="|vasp|band-structure|reference-request|ab-initio-calculations|density-of-states|" AnswerCount="0" CommentCount="5" ClosedDate="2022-01-20T18:34:32.453" ContentLicense="CC BY-SA 4.0" />
  <row Id="7232" PostTypeId="2" ParentId="7218" CreationDate="2021-12-10T07:39:08.997" Score="7" Body="&lt;p&gt;This problem is generically problematic for different software packages since there is no standardized format for storing grid values.&lt;/p&gt;&#xA;&lt;p&gt;In my software package &lt;a href=&quot;https://www.github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt; the interaction with Siesta grid output files is seamless and converts between the most common formats, cube and xsf files.&lt;/p&gt;&#xA;&lt;p&gt;For instance to convert the &lt;code&gt;Rho.grid.nc&lt;/code&gt; to a cube or xsf file, simply do:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sgrid Rho.grid.nc Rho.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Generally a cube file also needs to know the geometry to see it in visualization, so one needs to attach the geometry as well. Additionally one can compute differences (say spin), here is an example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sgrid Rho.grid.nc{0} --geometry RUN.fdf --diff Rho.grid.nc{1} diff_up-down.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which takes the difference between the 1st and 2nd spin-components and stores them in &lt;code&gt;diff_up_down.cube&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;All of the above commands also works for the binary &lt;code&gt;.VT&lt;/code&gt; etc. files that siesta outputs.&lt;/p&gt;&#xA;&lt;p&gt;They can also be used for VASP, although there are probably some corner case files that I haven't thought about.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2021-12-10T12:28:57.150" LastActivityDate="2021-12-10T12:28:57.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7233" PostTypeId="2" ParentId="7218" CreationDate="2021-12-10T10:25:06.180" Score="6" Body="&lt;p&gt;Adding to @nickpapior answer, the &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt; python package also includes intrinsic visualization tools that can help you visualize grids (in this case, stored in &lt;code&gt;.nc&lt;/code&gt; files). It is as easy as, in python:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;import sisl.viz&#xA;&#xA;grid_plot = sisl.get_sile(&amp;quot;myfile.nc&amp;quot;).plot()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are lots of things you can tweak on a grid plot directly from python, starting from visualizing things in 3D, 2D and 1D and hiding/showing the structure. Here's a page where the options are displayed in an illustrative way: &lt;a href=&quot;https://zerothi.github.io/sisl/visualization/viz_module/showcase/GridPlot.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://zerothi.github.io/sisl/visualization/viz_module/showcase/GridPlot.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A cool thing is that the &lt;code&gt;sisl&lt;/code&gt; visualization framework is agnostic on the particular plotting framework that renders the plots, so using the same settings you can see the display in any of the supported backends (currently &lt;code&gt;plotly&lt;/code&gt;, &lt;code&gt;matplotlib&lt;/code&gt; and &lt;code&gt;blender&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Here's some brief introduction to the framework: &lt;a href=&quot;https://zerothi.github.io/sisl/visualization/viz_module/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://zerothi.github.io/sisl/visualization/viz_module/index.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And here's a quick tutorial to get started plotting your things in blender:&#xA;&lt;a href=&quot;https://zerothi.github.io/sisl/visualization/viz_module/blender/Getting%20started.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://zerothi.github.io/sisl/visualization/viz_module/blender/Getting%20started.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There is no problem with the size of the grids, I use grid sizes like this or more all the time, so I doubt it will kill the kernel, unless your computer has a very small memory.&lt;/p&gt;&#xA;&lt;p&gt;If you have specific doubts about the usage or suggestions you can use &lt;a href=&quot;https://discord.com/channels/742636379871379577/845235607461691402&quot; rel=&quot;nofollow noreferrer&quot;&gt;the discord channels&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4675" LastEditorUserId="4675" LastEditDate="2021-12-11T09:13:00.830" LastActivityDate="2021-12-11T09:13:00.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7234" PostTypeId="1" AcceptedAnswerId="8314" CreationDate="2021-12-10T12:41:26.150" Score="11" ViewCount="5290" Body="&lt;p&gt;I am working on a QSAR project where the 3D structural descriptors are an input to a machine learning model. I am generating the descriptors using the python Mordred API (which uses rdkit).&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit import Chem&#xA;from mordred import Calculator,descriptors&#xA;import pandas as pd&#xA;&#xA;data = pd.read_csv('output_data.csv') # contains SMILES string of all molecules&#xA;&#xA;calc = Calculator(descriptors,ignore_3D=False)&#xA;&#xA;for index,row in data.iterrows():&#xA;    mol = Chem.MolFromSmiles(row['SMILES']) # get the SMILES string from each row&#xA;    # I need to put in the 3D coordinates from an xyz into 'mol' object here&#xA;    descs = list(calc(mol))&#xA;    # &#xA;    # ... processing descriptors...&#xA;    #&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The problem is that if I use rdkit to generate 3D coordinates from the SMILES, it will generate slightly different structures every time. However, I have optimized structure for each of those molecules as xyz files from the calculation that I ran on Orca. I wish to use the optimized structures for the 3D descriptors generation.&lt;/p&gt;&#xA;&lt;p&gt;How do I do this? The SMILES has the connectivity data, but the xyz has the coordinate data.&lt;/p&gt;&#xA;&lt;p&gt;I am open to using OpenBabel or any other tool that can be used from Python or the command line, but the main point is to combine connectivity of SMILES with the coordinates of xyz.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-12-10T23:26:38.870" LastActivityDate="2021-12-21T15:34:09.840" Title="How to input 3D coordinates from xyz file and connectivity from SMILES in rdkit?" Tags="|python|machine-learning|rdkit|smiles|qsar|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7235" PostTypeId="1" AcceptedAnswerId="7242" CreationDate="2021-12-10T14:58:34.450" Score="7" ViewCount="541" Body="&lt;p&gt;I am planning to use the finite displacement method for calculating phonon spectrum, and I have prepared the INCAR file below to try it on a transition metal trihalide monolayer (e.g., VI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;). I would be very grateful if you could please check it and tell me what I should add/omit, and if you recommend following this Phonopy &lt;a href=&quot;http://phonopy.github.io/phonopy/vasp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    NPAR = 6&#xA;# Self Consistent Calculation step:&#xA;ISTART = 0&#xA;ICHARG = 2&#xA;&#xA;#Electronic Relaxation:&#xA;ENCUT = 550 eV&#xA;EDIFF = 1.0E-8&#xA;PREC = Accurate&#xA;LREAL = .FALSE.&#xA;IALGO = 38&#xA;ADDGRID=.TRUE.&#xA;LCHARG = .FALSE.&#xA;LWAVE = .FALSE.&#xA;&#xA;#Phonons&#xA;IBRION = -1&#xA;&#xA;#Relaxation:&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;NSW = 1&#xA;GGA_COMPAT = .FALSE.&#xA;&#xA;# Magnetism:&#xA;ISPIN= 2&#xA;MAGMOM = 4*-5.0 4*5.0 24*0.6&#xA;LASPH = .TRUE.&#xA;LMAXMIX = 4&#xA;VOSKOWN = 1&#xA;&#xA;#Mixer&#xA;AMIX     = 0.2&#xA;BMIX     = 0.00001&#xA;AMIX_MAG = 0.8&#xA;BMIX_MAG = 0.00001&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am a little bit confused about which IBRION tag to use (IBRION=-1 or IBRION=6)&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-12-12T11:08:57.820" LastActivityDate="2021-12-13T10:52:25.790" Title="Which IBRION tag should be used for finite displacement method in calculating Phonons spectrum?" Tags="|vasp|phonons|phonopy|monolayer|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7236" PostTypeId="1" AcceptedAnswerId="7244" CreationDate="2021-12-10T18:14:29.497" Score="8" ViewCount="67" Body="&lt;p&gt;I am trying to figure out how to set the initial wavefunction in VASP, on the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/INIWAV&quot; rel=&quot;noreferrer&quot;&gt;VASP wiki page of INIWAV&lt;/a&gt;, it is said that VASP would fill wavefunction arrays with random numbers.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INIWAV=1&#xA;Fill wavefunction arrays with random numbers. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does &lt;code&gt;INIWAV=1&lt;/code&gt; mean the occupation number of each wavefunction orbital is random?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2021-12-10T18:56:54.810" LastActivityDate="2021-12-13T02:54:12.847" Title="Does the INIWAV tag in VASP assume that the wavefunctions are plane waves?" Tags="|density-functional-theory|vasp|orbitals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7237" PostTypeId="1" AcceptedAnswerId="7243" CreationDate="2021-12-10T18:51:23.033" Score="7" ViewCount="92" Body="&lt;p&gt;When initializing the charge density in VASP, I set the parameters as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Startparameter for this run:&#xA;ISTART =0         #job   :0-new  1-continue 2-samecut   charge:0-initial&#xA;ICHARG =2         #charge:0-initial orbitals 1-from CHGCAR 2-ISTART=0&#xA;INIWAV =1         #0-lowe 1-random: only ISTART=0 use! default-1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As shown on the wiki page of &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ICHARG&quot; rel=&quot;noreferrer&quot;&gt;ICHARG&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/INIWAV&quot; rel=&quot;noreferrer&quot;&gt;INIWAV&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ICHARG=2    #Take superposition of atomic charge densities&#xA;INIWAV=1    #Fill wavefunction arrays with random numbers.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;ICHARG=2&lt;/code&gt; looks like it tells VASP to store the atomic charge density from POTCAR files, and add them together to form the initial charge density.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;INIWAV=1&lt;/code&gt; seems to assume the wavefunctions in the unit cell are plane waves, and sets random occupation number for each wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Aren't these two options contradictory?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2021-12-10T19:00:10.333" LastActivityDate="2021-12-13T02:47:22.323" Title="Are CHARGE=2 and INIWAV=1 contradictory in the VASP setting?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7238" PostTypeId="2" ParentId="7230" CreationDate="2021-12-10T18:51:25.560" Score="1" Body="&lt;p&gt;According to the highly cited &lt;a href=&quot;https://jcheminf.biomedcentral.com/articles/10.1186/s13321-015-0069-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Tanimoto index, Dice index, Cosine coefficient and Soergel distance were identified to be the best (and in some sense equivalent) metrics for similarity calculations, i.e. these metrics could produce the rankings closest to the composite (average) ranking of the eight metrics. The similarity metrics derived from Euclidean and Manhattan distances are not recommended on their own, although their variability and diversity from other similarity metrics might be advantageous in certain cases (e.g. for data fusion).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.rdkit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;rdkit&lt;/a&gt; can do the Tanimoto index, Dice index, and Cosine coefficient. It is unclear at the moment if it can do the Soergel distance.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/openbabel/openbabel&quot; rel=&quot;nofollow noreferrer&quot;&gt;Openbabel&lt;/a&gt; can do the Tanimoto index.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://jcheminf.biomedcentral.com/articles/10.1186/s13321-015-0109-z&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemDes&lt;/a&gt; looks like it makes use of rdkit, openbabel(pybel) and other software, as an umbrella for doing a vast amount of fingerprinting.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="3606" LastEditDate="2021-12-10T19:11:17.987" LastActivityDate="2021-12-10T19:11:17.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7240" PostTypeId="2" ParentId="7234" CreationDate="2021-12-12T03:44:14.373" Score="4" Body="&lt;p&gt;The representation of a molecular structure as SMILES string is a (very) &lt;em&gt;reduced one&lt;/em&gt;, often with only implicit hydrogen atoms. Recreating &lt;em&gt;a&lt;/em&gt; 3D molecular structure with either OpenBabel or RDKit not only adds the atoms together, it will perform a quick/computational affordable force field optimization with some seed, too.  (The seed may be randomized, e.g., &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#writing-molecules&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDKit manual&lt;/a&gt;.) Thus the variation in the atomic coordinates you observe.  OpenBabel and RDKit are not written to substitute optimizing an organic structure with high-level theory (like DFT). They may suggest a different conformer than the one your computations with ORCA suggest/experimental findings from docking experiments and structure elucidation (X-ray diffraction, NMR, etc.).&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;.xyz&lt;/code&gt; file only stores information about atom coordinates.  If you want to retain information both about the spatial arrangement as well as connectivity of the atoms in a molecule, a &lt;code&gt;.mol&lt;/code&gt; file is better (or, if you want to store multiple models in one container, each about one molecule, a &lt;code&gt;.sdf&lt;/code&gt;) with a dedicated &lt;em&gt;connectivity table&lt;/em&gt; (see., e.g., &lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_table_file&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia's entry&lt;/a&gt;, and the current &lt;a href=&quot;https://web.archive.org/web/20210219065450/https://discover.3ds.com/sites/default/files/2020-08/biovia_ctfileformats_2020.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; if you want/need to go into detail).  RDKit is capable to work with them, too (see e.g., &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#reading-sets-of-molecules&quot; rel=&quot;nofollow noreferrer&quot;&gt;entry&lt;/a&gt; from RDKit's documentation), both with the elder v2000 as well as the more recent v3000 format (referring to RDKit version 2021.09.2) in reading and writing.&lt;/p&gt;&#xA;&lt;p&gt;Check if ORCA can provide the optimized geometry as &lt;code&gt;.mol&lt;/code&gt;, or &lt;code&gt;.sdf&lt;/code&gt; for your construction of a QSAR.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2021-12-12T03:44:14.373" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7241" PostTypeId="1" CreationDate="2021-12-12T19:02:12.330" Score="4" ViewCount="92" Body="&lt;p&gt;My decanters are washed in hot water. The outside is then dried with a clean cloth, as is the top of the inside of the neck — typically one can’t reach further. The still-warm decanter is then left standing, without stopper, so that the hot ‘wet’ air can rise out of it. So far, so good.&lt;/p&gt;&#xA;&lt;p&gt;For some decanters, the inside dries very fast, within a few minutes appearing to be crisply dry. For others, there is a mist of fine droplets on the inside surface that can take a week of dry weather to evaporate. It seems to be binary: some dry fast; some dry slowly; none in between.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a known property of types of glass which makes the drying quick or slow? If yes, what is that property? Can that property be identified in a decanter before purchase, such as in a shop or online?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It might help to reject some hypotheses.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Glass thickness?&lt;/em&gt; There is a continuum of glass thicknesses. But I do not observe a continuum of behaviour: two speeds: very fast, and very slow.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Water temperature?&lt;/em&gt; All my decanters are washed in my almost ritualistic way, with hot water from the same kitchen tap. And, always, drying starts with the decanter very hot and consistently so. Yet the reliably-quick are reliably quick, and the reliably-slow are reliably slow. It is a property of the decanter. Indeed, this is so reliable that a few years ago I gave away all of my slow decanters (except one, much liked for its shape — but it is still slow). The speed is a reliably repeatable quality of the decanter.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Air humidity?&lt;/em&gt; No, for the same reason as water temperature.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Water hardness?&lt;/em&gt; No, for the same reason as water temperature. Speed is a reliably repeatable quality of the decanter.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4680" LastActivityDate="2021-12-14T18:20:59.183" Title="Why do some decanters dry quickly, and others dry slowly?" Tags="|physical-properties-of-materials|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="7242" PostTypeId="2" ParentId="7235" CreationDate="2021-12-13T01:28:18.947" Score="6" Body="&lt;p&gt;&lt;code&gt;Phonopy&lt;/code&gt; creates different &lt;code&gt;POSCAR&lt;/code&gt; file in which atoms are perturbed, as you are running each &lt;code&gt;POSCAR&lt;/code&gt; for NSW=1 or 0, &lt;code&gt;IBRION=-1&lt;/code&gt; will be correct choice.&#xA;For &lt;code&gt;NSW=1 or 0&lt;/code&gt; , only one self consistency loop will run with no update in ion position , all &lt;code&gt;IBRION&lt;/code&gt; tags are equivalent.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;code&gt;IBRION=-1&lt;/code&gt;: no update.&lt;/p&gt;&#xA;&lt;p&gt;The ions are not moved, but NSW outer loops are performed. In each outer loop the electronic degrees of freedom are re-optimized (for NSW&amp;gt;0 this obviously does not make much sense, except for test purposes). If no ionic update is required use &lt;code&gt;NSW=0&lt;/code&gt; instead.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2021-12-13T01:32:08.907" LastActivityDate="2021-12-13T01:32:08.907" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7243" PostTypeId="2" ParentId="7237" CreationDate="2021-12-13T02:47:22.323" Score="7" Body="&lt;p&gt;If you solve the Kohn-Sham equations using density mixing (or any non-self-consistent method) then the density and wavefunctions are treated independently. This means that you are free to initialise the density and wavefunctions independently, and in this case it appears that the density is initialised from a sum of (pseudo-)atomic charge densities, and the wavefunctions are initialised randomly. This is quite a common initialisation.&lt;/p&gt;&#xA;&lt;p&gt;You might wonder how the wavefunctions and densities can be treated independently and still optimised to give the ground state. The usual approach is the &amp;quot;self-consistent field&amp;quot; method (SCF) where the wavefunctions are optimised by solving the Kohn-Sham equations (iteratively, in the case of a plane-wave-based code like VASP) for a &lt;em&gt;fixed&lt;/em&gt; input density,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathrm{H}_{k}[\rho_{in}]\psi_{bk}(r)=\epsilon_{bk}\psi_{bk}(r).$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once the optimised wavefunctions have been calculated, an &amp;quot;output density&amp;quot; is computed from them,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho_{out}(r) = \sum_{bk} f_{bk}|\psi_{bk}(r)|^2$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; are band and k-point indices, respectively, and &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt; are the band occupancies.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$\rho_{out}=\rho_{in}$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$\{\psi_{bk}\}$&lt;/span&gt; are the correct ground state Kohn-Sham states; however, this is not the case in general, and a new trial input density is contructed from &lt;span class=&quot;math-container&quot;&gt;$\rho_{out}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho_{in}$&lt;/span&gt; according to a different optimisation method (for example, a Kerker-Pulay mixing method). This constitutes one &amp;quot;SCF cycle&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The updated density is then used as the input density for the next SCF cycle, and the wavefunctions optimised for this new density. As the SCF cycles progress, the goal is for the input and output densities to converge towards each other to within some specified precision, at which point it is assumed that &lt;span class=&quot;math-container&quot;&gt;$\{\psi_{bk}\}$&lt;/span&gt; are sufficiently accurate to be treated as the ground state Kohn-Sham states. At this point &lt;span class=&quot;math-container&quot;&gt;$\rho_{out}\approx \rho_{in}$&lt;/span&gt; and the solution is said to be (approximately) &amp;quot;self-consistent&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T02:47:22.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7244" PostTypeId="2" ParentId="7236" CreationDate="2021-12-13T02:54:12.847" Score="6" Body="&lt;p&gt;No, it randomly chooses the different plane-wave coefficients &lt;span class=&quot;math-container&quot;&gt;$c_{Gbk}$&lt;/span&gt; for wavevector &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;, of each trial Kohn-Sham state at each band &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; and k-point &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}(r)=\sum_G c_{gbk}e^{iG.r}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The occupation of those states, &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt;, will be chosen differently. In fact, in a non-self-consistent method, the initial occupations are not important, since they are only used in constructing the output density,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho_{out}(r)=\sum_{bk}f_{bk}|\psi_{bk}(r)|^2,$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;at which point the trial eigenvalues are known and the occupations may be assigned following the Fermi-level search and pseudo-thermal occupation.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T02:54:12.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7245" PostTypeId="2" ParentId="7183" CreationDate="2021-12-13T12:00:16.237" Score="11" Body="&lt;p&gt;In order to answer this, I will introduce k-points in two different ways.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;1. Bloch's theorem&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The usual approach to introducing k-points is to start with Bloch's theorem. In a periodic potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, such that,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$V(r+L)=V(r),$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is any lattice vector, the Kohn-Sham density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; should share that periodicity, i.e.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho(r+L)=\rho(r).$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho(r)=\sum_{bk}f_{bk}|\psi_{bk}(r)|^2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(where &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; are band and k-point indices, respectively, and &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt; is the band occupation), this may be satisfied if the magnitude of the wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt; also has the requisite periodicity.&lt;/p&gt;&#xA;&lt;p&gt;Wavefunctions are complex-valued, and although we have determined that the magnitude should be periodic, their phase is undetermined; in fact, there will be solutions to the Kohn-Sham equations for &lt;em&gt;any&lt;/em&gt; choice of their phase. We express a particular solution as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}(r)=u_{bk}(r)e^{ik\cdot r},$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$u_{bk}(r)$&lt;/span&gt; is completely periodic in both its phase and magnitude,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$u_{bk}(r+L)=u_{bk}(r),$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and is usually called a Bloch function. &lt;span class=&quot;math-container&quot;&gt;$e^{ik\cdot r}$&lt;/span&gt; is called the phase factor, because it has unit magnitude for any choice of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, and so only affects the phase of &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is chosen such that &lt;span class=&quot;math-container&quot;&gt;$e^{ik\cdot r}$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt; periodic, except for the special choice &lt;span class=&quot;math-container&quot;&gt;$k=(0,0,0)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Thus, &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}(r)$&lt;/span&gt; is periodic in its magnitude, but not its phase:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}(r+L)=u_{bk}(r+L)e^{ik\cdot(r+L)}=u_{bk}(r)e^{ik\cdot r}e^{ik\cdot L}= \psi_{bk}(r)e^{ik\cdot L}.$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What should &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; be? There are solutions to the Kohn-Sham equations for any choice of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, so the most general solution would be to include a linear combination of all possible choices. Since &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is continuous, this means an integral over all the possible choices of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, i.e. those for which &lt;span class=&quot;math-container&quot;&gt;$k\cdot L \neq 2m\pi$&lt;/span&gt; for any integer &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;; this is an integral over the first Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;We don't know how the Kohn-Sham states vary with &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, so we can't perform this integral analytically. We choose to evaluate the integral numerically, sampling the Brillouin zone at various points and using it to estimate the integral; these sampling points are the &amp;quot;k-points&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Note that a k-point component of the form &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{n}$&lt;/span&gt;, for any integer &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, means that the wavefunction phase will be periodic with a period of &lt;span class=&quot;math-container&quot;&gt;$nL$&lt;/span&gt;. In other words, each rational k-point may be interpreted as an assumption that the wavefunction &lt;em&gt;is&lt;/em&gt; periodic, but with period &lt;span class=&quot;math-container&quot;&gt;$nL$&lt;/span&gt; rather than &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;2. Finite-sized systems&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For simplicity, let's consider an infinite 2D slab, where it is periodic in Cartesian &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and has a finite thickness in &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;. Let's assume we can separate the variables and write&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}(x,y,z)=\phi_{bk}(x,y)\chi_{bk}(z).$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What form does &lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(z)$&lt;/span&gt; take? In other words, what do the states look like with respect to &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;We could consider our 2D slab to be a potential well, let's say it has thickness &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; and let's suppose it is a deep enough well that we can treat it as infinitely deep (this is not required, but it simplifies our description). What are the lowest energy states of this infinite potential well in &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;The states of an infinitely deep potential well are well-known to anyone who has studied quantum mechanics. The particles are essentially &amp;quot;free&amp;quot; inside the well, since we're approximating the potential as a constant in this region, and they go to zero at the edges (since the potential is infinite; this is why we made that simplifying approximation). If we choose our origin (&lt;span class=&quot;math-container&quot;&gt;$z=0$&lt;/span&gt;) to be in the middle of the well, then the allowed states have the form,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi^{k_z}_{bk}(z)=A\sin{(k_z z)}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_z=\frac{m\pi}{C}$&lt;/span&gt; for any integer &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; (this choice of &lt;span class=&quot;math-container&quot;&gt;$k_z$&lt;/span&gt; is required for &lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(z)$&lt;/span&gt; to go to zero at the edges of the slab). Thus, we see that the allowed wavevectors in &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; are &lt;span class=&quot;math-container&quot;&gt;$k_z = \frac{\pi}{C}, \frac{2\pi}{C}, \frac{3\pi}{C}\ldots$&lt;/span&gt;. We can solve the Kohn-Sham equations for any particular choice of &lt;span class=&quot;math-container&quot;&gt;$k_z$&lt;/span&gt;, and we would write a general solution as a sum over all these possible choices,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(r)=\sum_{m=0}^\infty A_m\sin\left(\frac{m\pi z}{C}\right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's now write this in terms of complex exponentials,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(r) = \sum_{m=-\infty}^\infty A_m e^{i\frac{m\pi z}{C}},$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or, in terms of &lt;span class=&quot;math-container&quot;&gt;$k_z$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(r) = \sum_{k_z}A_{k_z}e^{ik_z z}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What happens as we make our slab thicker, i.e. increase &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;? A larger value of &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; means that &lt;span class=&quot;math-container&quot;&gt;$\frac{\pi}{C}$&lt;/span&gt; is smaller, so the allowed wavevectors are closer together. As &lt;span class=&quot;math-container&quot;&gt;$C\longrightarrow\infty$&lt;/span&gt; the allowed wavevectors form a continuum,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$A_{k_z}\longrightarrow A(k_z)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\chi_{bk}(r) = \int_{k_z}A(k_z)e^{ik_z z}dk_z$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So our k-points started as the allowed wavevectors for a slab of finite thickness, and as the thickness tended to infinity we recovered the familiar 3D result that they form a continuum.&lt;/p&gt;&#xA;&lt;p&gt;A particular choice of k-point is, therefore, equivalent to assuming that the wavefunction has the same form as for a slab of a particular thickness.  If we use 10 &amp;quot;k-points&amp;quot; in the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; direction, it's equivalent to assuming the wavefunction has the same form as a wavefunction for a slab of thickness 5 times the lattice vector (half, because in the finite slab &lt;span class=&quot;math-container&quot;&gt;$k_z=\frac{m\pi}{C}=\frac{2m\pi}{2C}$&lt;/span&gt;, i.e. periodic with &lt;span class=&quot;math-container&quot;&gt;$2C$&lt;/span&gt;, rather than  just &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2021-12-13T14:16:23.420" LastActivityDate="2021-12-13T14:16:23.420" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7246" PostTypeId="2" ParentId="7153" CreationDate="2021-12-13T12:07:30.553" Score="3" Body="&lt;p&gt;This is difficult to calculate in detail, but the largest memory objects are probably the Kohn-Sham wavefunctions and the pseudopotential projectors (if you're representing them in reciprocal-space). In order to calculate their memory requirements, you need to know the number of:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Plane-waves, &lt;span class=&quot;math-container&quot;&gt;$N_p$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Bands, &lt;span class=&quot;math-container&quot;&gt;$N_b$&lt;/span&gt; (all the bands you're calculating, i.e. including conduction bands)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;k-points, &lt;span class=&quot;math-container&quot;&gt;$N_k$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Spins, &lt;span class=&quot;math-container&quot;&gt;$N_s$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Total pseudopotential projectors, &lt;span class=&quot;math-container&quot;&gt;$N_{proj}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The wavefunction coefficients will be stored as double-precision complex values, meaning 16 bytes each. The total storage for the wavefunction is thus,&lt;/p&gt;&#xA;&lt;p&gt;RAM for &lt;span class=&quot;math-container&quot;&gt;$\psi = 16\times N_p\times N_b\times N_k\times N_s$&lt;/span&gt; bytes;&lt;/p&gt;&#xA;&lt;p&gt;RAM for projectors &lt;span class=&quot;math-container&quot;&gt;$= 16\times N_p\times N_{proj}\times N_k\times$&lt;/span&gt; bytes.&lt;/p&gt;&#xA;&lt;p&gt;(Assuming that the pseudopotentials are not spin-dependent.)&lt;/p&gt;&#xA;&lt;p&gt;This is the total storage for each object; as a rough guide, you could divide them by the number of processes to get the memory requirements per process.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T12:07:30.553" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7247" PostTypeId="2" ParentId="7079" CreationDate="2021-12-13T12:46:14.463" Score="5" Body="&lt;p&gt;I don't know for certain, but a fairly general model of the time taken &lt;span class=&quot;math-container&quot;&gt;$T(N)$&lt;/span&gt; for a parallel calculation on &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; processes is,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$T(N) = S + \frac{P}{N} + C(N-1)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$S\geq 0$&lt;/span&gt; is the serial part of the work (the part which can't be parallelised), &lt;span class=&quot;math-container&quot;&gt;$P\geq 0$&lt;/span&gt; is the parallelisable work, and &lt;span class=&quot;math-container&quot;&gt;$C\geq 0$&lt;/span&gt; represents the cost of doing parallel communications.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is large and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; are small, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$T(N)\approx \frac{P}{N}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and your calculation will scale perfectly. If, on the other hand, &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is large compared to &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$T(N)\approx S$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and your calculation will take the same amount of time, regardless of how many processes you use! Even worse, if &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is not negligible then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$T(N)\approx S + C(N-1)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the time will actually &lt;em&gt;increase&lt;/em&gt; with more processes.&lt;/p&gt;&#xA;&lt;p&gt;The final ingredient is to note that the communication cost actually comes as two parts, a latency cost and a bandwidth cost. The latency cost is the time it takes to establish a communication -- even a zero-length message takes this amount of time. The bandwidth cost is the time it takes to send data, once the communication has been established. The time it takes to send long messages depends mostly on the bandwidth, but short messages are dominated by the latency. As you increase &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, most algorithms will end up sending more messages, and each message will be shorter. Shorter messages take less time to send when you're limited by bandwidth, but at some point they are so short that latency becomes more important -- after this point, the message time becomes approximately constant.&lt;/p&gt;&#xA;&lt;p&gt;In your case, we have two different parallelisation schemes. The k-point parallelism is scaling well, which is generally found to be the case since only a few one-to-all communications are required per SCF cycle and almost all the work distributes well over k-point.&lt;/p&gt;&#xA;&lt;p&gt;When we look at band-parallelism, your times are &lt;em&gt;increasing&lt;/em&gt;. Band-parallelism requires more communications inside the SCF cycle, for example when performing orthonormalisation or subspace rotations; these actually require all-to-all communications. This communication cost will be small if there is a lot of work to do, but your calculation is not actually very large.&lt;/p&gt;&#xA;&lt;p&gt;Assuming that your pseudopotential has 3 valence electrons per aluminium atom, your 32-atom cell has 96 electrons, meaning 48 valence bands. I don't know how many conduction bands you're using, but let's suppose you have 16 to give us 64 bands in total. It looks like you've instructed QE to use a block-Davidson optimisation method, in which case these bands will be split into subgroups; I don't know how large these subgroups will be, but perhaps 4 groups of 16 bands each.&lt;/p&gt;&#xA;&lt;p&gt;16 bands is not very many to distribute, so it's likely that there won't be much work in between communications, and the communications will be fairly short, i.e. dominated by latency. These two factors mean that the cost of parallelising the calculation is quite high, and it is unlikely to scale well.&lt;/p&gt;&#xA;&lt;p&gt;This situation could be improved by increasing the number of bands in the subgroups, which would mean fewer subgroups. I don't know whether Quantum Espresso allows you to control that, but if it does then I suggest you try it. It would increase the work in between communications and also lead to fewer, longer messages; both of these should improve the scaling, though not necessarily the calculation time.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T12:46:14.463" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7248" PostTypeId="2" ParentId="6952" CreationDate="2021-12-13T13:03:46.083" Score="5" Body="&lt;p&gt;When you do the ground state calculation, you choose a k-point mesh to numerically integrate the states over the Brillouin zone. This is an approximation, but a controllable one; if you increase the number of k-points in the ground state calculation, the Fermi energy will eventually converge.&lt;/p&gt;&#xA;&lt;p&gt;A band-structure calculation involves calculating the Kohn-Sham states at special high-symmetry points and lines, which are specifically chosen to capture the maxima and minima of the states. These are &lt;em&gt;atypical&lt;/em&gt; points and terrible as sampling points, so any properties calculated from them are unlikely to be accurate -- this includes the Fermi energy.&lt;/p&gt;&#xA;&lt;p&gt;There is a very similar, related case where the second calculation is not a band-structure but a density-of-states (DOS). In this case, the DOS &lt;em&gt;is&lt;/em&gt; performed at a good set of sampling points, in fact they are usually a much better sampling mesh than the original ground state calculation. This will usually give a different Fermi energy as well, but in this case the difference is due to finite k-point sampling error. The value from the DOS is probably more accurate, but if you care about the difference then you should probably refine the original ground state calculation with more k-points.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T13:03:46.083" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7249" PostTypeId="2" ParentId="6887" CreationDate="2021-12-13T13:55:46.160" Score="5" Body="&lt;p&gt;The Fermi-Dirac function has a very long tail, so will tend to occupy states a long way above the Fermi level. This can mean that you need to include more conduction states in your calculation, in order to capture all of the occupied states, and have a well-behaved optimisation method. This is probably why your calculation is not converging in this case.&lt;/p&gt;&#xA;&lt;p&gt;Different codes should not need bigger smearing widths, if all other parameters remain the same. The only slight issue is the definition of smearing width; most codes use the standard deviation of the distribution, but occasionally you will see the full-width half-maximum used instead (and similar alternatives). It is straightforward to calculate (or just look up) the relationship between the two, if you do need to convert the numbers.&lt;/p&gt;&#xA;&lt;p&gt;I disagree with the statement &amp;quot;The natural way is Fermi-Dirac and 1500 K is way too big&amp;quot;. This appears to stem from a misunderstanding of what you are trying to accomplish with smearing. The goal of smearing is &lt;em&gt;not&lt;/em&gt; (usually) to compute the thermal occupation of the Kohn-Sham states, but to: (a) improve the numerical approximation of the integral of the band-energies and occupancies over the Brillouin zone; and (b) improve the conditioning of the Fermi-level search. This is why you can use smaller smearing widths if you increase the k-point sampling density.&lt;/p&gt;&#xA;&lt;p&gt;In the case of (a), the &amp;quot;natural&amp;quot; smearing is actually Gaussian, in the sense that it is related to both an uncertainty estimate and using Gaussian quadrature to compute the integral, rather than the raw numbers. For both (a) and (b) you want the width of the smearing function to be large enough to provide a smooth variation of the energies across the Brillouin zone; for typical k-point sampling densities, this means 0.1-0.2 eV.&lt;/p&gt;&#xA;&lt;p&gt;Using a smearing function does change the calculated ground state properties. For the ground state energy, the first-order error can be removed for all the usual smearing schemes, but in the case of Methfessel-Paxton and &amp;quot;cold smearing&amp;quot; you can do better than that, and remove the 2nd order error and even higher (depending on the order of the scheme). The smearing does cause a stress on the cell, essentially thermal expansion, and I am not aware of anyone having calculated a correction for this.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-13T13:55:46.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7250" PostTypeId="2" ParentId="6941" CreationDate="2021-12-13T15:34:52.867" Score="8" Body="&lt;p&gt;I suspect that these are the &lt;span class=&quot;math-container&quot;&gt;$5s$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$5p$&lt;/span&gt; states of &lt;span class=&quot;math-container&quot;&gt;$\ce{Hf}$&lt;/span&gt;, which are treated as valence in the pseudopotential you're using. These states will be fairly tightly bound to the nucleus, which always show up as sharp peaks in the DOS.&lt;/p&gt;&#xA;&lt;p&gt;The reason why tightly-bound states show up like this can be understood by noting that if the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is large compared to the kinetic term &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, then the Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; can be approximated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H\approx V$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; of a wavefunction &lt;span class=&quot;math-container&quot;&gt;$\psi_{k}$&lt;/span&gt; at k-point &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E &amp;amp; \approx \int d^3 r \psi^\ast_k(r)V(r)\psi_k(r)\\&#xA;&amp;amp;= \int d^3 r V(r)\psi^\ast_k(r)\psi_k(r)\\&#xA;&amp;amp;= \int d^3 r V(r)\left\vert \psi_k(r)\right\vert^2\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, recall that k-points are introduced when we apply Bloch's theorem, and write,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\psi_k(r)=u_k(r)e^{ik\cdot r}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$u_k$&lt;/span&gt; is the Bloch function, which does not explicitly depend on &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. Substituting into the energy expression, we have&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E &amp;amp; \approx \int d^3 r V(r)\left\vert u_k(r)\right\vert^2\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In other words, the phase factor is irrelevant and the dependence on the phase &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; has disappeared! The energy does not depend on &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; at all, and the state has the same energy regardless of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. This means that the density of states for this state is a delta-function at &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; -- which is essentially what you're seeing in your DOS plots.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="7" LastEditDate="2021-12-13T16:27:58.857" LastActivityDate="2021-12-13T16:27:58.857" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7251" PostTypeId="1" AcceptedAnswerId="7254" CreationDate="2021-12-13T18:34:07.030" Score="8" ViewCount="808" Body="&lt;p&gt;I have found many organic molecule databases, such as PubChem or chEMBL. But they don't provide the atomic coordinates of each atom on the structure. I'm especially interested in organic molecules that contain silicon. Where can I find these atomic coordinates?&lt;/p&gt;&#xA;" OwnerUserId="4659" LastActivityDate="2021-12-13T21:32:37.007" Title="Where to find organic molecules atomic coordinates" Tags="|quantum-chemistry|computational-chemistry|structure|organic-chemistry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7252" PostTypeId="2" ParentId="7113" CreationDate="2021-12-13T20:00:22.333" Score="2" Body="&lt;p&gt;Collecting my comments and clarifying them, in the paper they mention that they used VESTA and Atomsk to do this:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For this we first find the proper rotation matrix using the VESTA program [43]. Then we calculated the corresponding rotation angles and rotated the CrI3 unit cell using Atomsk&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I don't know much about either of these programs, but I can at least point you to the mathematical procedure for &lt;a href=&quot;https://math.stackexchange.com/questions/180418/calculate-rotation-matrix-to-align-vector-a-to-vector-b-in-3d&quot;&gt;rotating a vector onto another vector&lt;/a&gt;. Using Vesta, you should be able to determine the vector for a bond &lt;span class=&quot;math-container&quot;&gt;$\ce{A-B}$&lt;/span&gt; (call the vector &lt;span class=&quot;math-container&quot;&gt;$\vec{u}$&lt;/span&gt;) from the coordinates of &lt;span class=&quot;math-container&quot;&gt;$\ce{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{B}$&lt;/span&gt;. You could then align this bond with &lt;span class=&quot;math-container&quot;&gt;$\vec{x}=(1,0,0)$&lt;/span&gt; (for example), using the rotation matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$R=I+[U]_\times+[U]_\times^2\frac{1-\cos(\theta)}{\sin(\theta)^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; the angle between the &lt;span class=&quot;math-container&quot;&gt;$\vec{u}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{x}$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$[U]_\times=[\vec{u}\times \vec{x}]=&#xA;\begin{bmatrix}&#xA;0 &amp;amp; -u_3 &amp;amp; u_2\\&#xA;u_3 &amp;amp; 0 &amp;amp; -u_1\\&#xA;u_2 &amp;amp; u_1 &amp;amp; 0\\                            &#xA;\end{bmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once you have this rotation matrix, you can enter the &lt;code&gt;Transform&lt;/code&gt; tab in VESTA which should allow you enter and apply this rotation matrix. As Anyon mentioned, some languages like Mathematica have built in functions to form this rotation matrix. VESTA itself may have such a function, but I haven't found one thus far.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="142" LastEditDate="2021-12-13T21:12:39.873" LastActivityDate="2021-12-13T21:12:39.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7253" PostTypeId="1" CreationDate="2021-12-13T20:49:03.120" Score="9" ViewCount="444" Body="&lt;p&gt;In the presence of a 2D crystal and spin-orbit coupling, the SU(2) spin axial vector (Sx,Sy,Sz) decouples into an in-plane (Sx,Sy) and out-of-plane part Sz. For Quantum ESPRESSO, is there a way to turn on only the out-of-plane component of spin-orbit coupling?&lt;/p&gt;&#xA;&lt;p&gt;I happen to know that the effect of the in-plane spin-orbit is marginal for the bands near the Fermi level (as observed by photo-emission experiments). Therefore, I imagine turning off the in-plane part would not only be computationally easier, but also more accurate to my material.&lt;/p&gt;&#xA;&lt;p&gt;I don't see why this shouldn't be possible, seeing that it amounts to a constraint that the up/down spin should be conserved (i.e not mixed at the level of the Hamiltonian). I believe we would say the spins should remain &amp;quot;collinear&amp;quot;. However, I can't seem to find anything on this; and when I choose the following parameters&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  lspinorb = .true.&#xA;  noncolin = .false.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;then Quantum ESPRESSO (pw.x) immediately crashes with the following complaint (written in CRASH file):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;spin orbit requires a non collinear calculation&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;/p&gt;&#xA;&lt;p&gt;Compared to a non-spin-orbit scf calculation, the only other thing I'm doing differently is use fully relativistic pseudopotentials:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Fe.rel-pbesol-spn-kjpaw_psl.1.0.0.UPF&#xA;Se.rel-pbesol-dn-rrkjus_psl.1.0.0.UPF&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any insight would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="4543" LastEditorUserId="5" LastEditDate="2022-02-24T04:00:02.133" LastActivityDate="2022-02-24T08:34:36.603" Title="Is it possible to do a collinear spin-orbit calculation in Quantum ESPRESSO?" Tags="|quantum-espresso|crystallography|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7254" PostTypeId="2" ParentId="7251" CreationDate="2021-12-13T21:32:37.007" Score="6" Body="&lt;p&gt;There are a few sites where you can find geometries, for example&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PubChem &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/&quot; rel=&quot;noreferrer&quot;&gt;https://pubchem.ncbi.nlm.nih.gov/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;CCCBDB: Computational Chemistry Comparison and Benchmark Database &lt;a href=&quot;https://cccbdb.nist.gov/geom1x.asp&quot; rel=&quot;noreferrer&quot;&gt;https://cccbdb.nist.gov/geom1x.asp&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;ChemSpider &lt;a href=&quot;http://www.chemspider.com/&quot; rel=&quot;noreferrer&quot;&gt;http://www.chemspider.com/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;NIST Chemistry WebBook &lt;a href=&quot;https://webbook.nist.gov/chemistry/&quot; rel=&quot;noreferrer&quot;&gt;https://webbook.nist.gov/chemistry/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Public Computational Chemistry Database &lt;a href=&quot;http://pccdb.org/&quot; rel=&quot;noreferrer&quot;&gt;http://pccdb.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The problem with the database structures is that they are often of poor quality: the coordinates are typically optimized at B3LYP/6-31G* level of theory, and I'm not sure whether they correspond to the lowest-lying conformation.&lt;/p&gt;&#xA;&lt;p&gt;You didn't say what purpose you have in mind for the geometries, and how large molecules you are interested in. My general advice is to try to find a general database, and extract the kinds of molecules you are interested in. For instance, the tmQM transition metal dataset &lt;a href=&quot;https://doi.org/10.1021/acs.jcim.0c01041&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Inf. Model. 2020, 60, 12, 6135&lt;/a&gt; appears to have also molecules with silicon atoms in it.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-12-13T21:32:37.007" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="7255" PostTypeId="2" ParentId="7218" CreationDate="2021-12-13T21:54:48.763" Score="3" Body="&lt;h1&gt;NetCDF&lt;/h1&gt;&#xA;&lt;p&gt;According to the &lt;a href=&quot;https://www.unidata.ucar.edu/software/netcdf/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NetCDF homepage&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;NetCDF (Network Common Data Form) is a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. It is also a community standard for sharing scientific data. The Unidata Program Center supports and maintains netCDF programming interfaces for C, C++, Java, and Fortran. Programming interfaces are also available for Python, IDL, MATLAB, R, Ruby, and Perl.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Since this is a general format which can be used for any kind of data, and you did not specify what files you are actually interested in, I would recommend using the NetCDF library to open and handle NetCDF files that you encounter anywhere.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-12-13T21:54:48.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7256" PostTypeId="1" CreationDate="2021-12-14T07:48:51.180" Score="5" ViewCount="510" Body="&lt;p&gt;&lt;a href=&quot;https://drive.google.com/file/d/1TwkQQADbhKsS59wxgVte3Hcz_3KugSpK/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;The link to the trajectory is here.&lt;/a&gt;I am using the module and similar code of the &lt;a href=&quot;https://wiki.fysik.dtu.dk/asap/Radial%20Distribution%20Functions#id12&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASAP calculator from ASE&lt;/a&gt;. The problem is as follows, the running Coordination Number doesn't match the number of atoms in the cell.&#xA;Upon checking, I found that the ASE is reading the trajectory atoms boundary condition and cell correctly. But the results are this with 16 Ge-atoms in the cell. &lt;a href=&quot;https://i.stack.imgur.com/szXq8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/szXq8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/cMtde.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cMtde.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/7tnDF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7tnDF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, I am curious if someone can get the simple code below working,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from scipy import integrate&#xA;from asap3 import *&#xA;from asap3.analysis.rdf import RadialDistributionFunction&#xA;from ase.lattice.compounds import *&#xA;import matplotlib.pyplot as plt&#xA;import numpy as np&#xA;from ase.data import atomic_numbers, atomic_names, atomic_masses, covalent_radii&#xA;&#xA;def rdf(file_traj, ge_ratio):&#xA;    print(file_traj)&#xA;    rMax = 12.41&#xA;    nBins = 200&#xA;    traj = Trajectory(file_traj)&#xA;    RDFobj = None&#xA;    for atoms in traj:&#xA;        #print(atoms.get_cell())&#xA;        if RDFobj is None:&#xA;            RDFobj = RadialDistributionFunction(atoms, rMax, nBins)&#xA;        else:&#xA;            RDFobj.atoms = atoms  # Fool RDFobj to use the new atoms&#xA;        RDFobj.update()           # Collect data&#xA;&#xA;    x = (np.arange(nBins) + 0.5) * rMax / nBins      &#xA;    rdf = RDFobj.get_rdf()       &#xA;    plt.title('Total RDF-Ge Count%s'%ge_ratio, fontsize=15)&#xA;    plt.plot(x, rdf)&#xA;    plt.show()&#xA;&#xA;   # Get the partial RDFs and plot them&#xA;    Si = atomic_numbers['Si']&#xA;    Ge = atomic_numbers['Ge']&#xA;&#xA;    rdfGeGe = RDFobj.get_rdf(elements=(Ge, Ge))&#xA;    plt.title('Partial RDF-Ge Count%s'%ge_ratio, fontsize=15)&#xA;    plt.plot(x, rdfGeGe, 'r', label = &amp;quot;Ge-Ge&amp;quot;)&#xA;    plt.show()&#xA;   &#xA;    y = rdfGeGe * 4 * np.pi * x * x * (ge_ratio/rMax**3)   &#xA;    result_lst = []   &#xA;    for i in range(len(x)):&#xA;        result = integrate.simps(y[:i + 1],x[: i+ 1])&#xA;        result_lst.append(result)&#xA;    result_lst = np.array(result_lst)&#xA;&#xA;    plt.plot(x, result_lst, 'r', label = &amp;quot;Ge-Ge&amp;quot;)&#xA;    plt.title('CN-Ge Count%s'%ge_ratio, fontsize=15)&#xA;    plt.legend()&#xA;    plt.show()&#xA;    return  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="4219" LastEditDate="2021-12-15T22:17:59.450" LastActivityDate="2021-12-15T22:17:59.450" Title="Why calculation of coordination numbers from Element-specific RDFs (ASE) doesn't make sense?" Tags="|atomic-simulation-environment|materials-engineering|radial-distribution-function|coordination|" AnswerCount="0" CommentCount="8" FavoriteCount="0" ClosedDate="2022-01-20T23:55:57.017" ContentLicense="CC BY-SA 4.0" />
  <row Id="7258" PostTypeId="2" ParentId="7241" CreationDate="2021-12-14T16:21:32.090" Score="2" Body="&lt;p&gt;Lead in &lt;a href=&quot;https://en.wikipedia.org/wiki/Lead_glass&quot; rel=&quot;nofollow noreferrer&quot;&gt;lead crystal&lt;/a&gt; has the effect of making the glass glossy in finish. A lead crystal decanter could have a smoother surface than lead-free glass, which is more resistant to liquid and so the liquid flows away more readily.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The addition of lead also provides an improved look to the finished&#xA;product through increasing the refractive index and density of the glass, making it a clearer, less flawed substance.&amp;quot; [1]&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It could be that some antique lead crystal decanters no longer possesses this smooth surface quality, since the lead content is known to &amp;quot;leach lead into the food and beverages contained&amp;quot; if liquid is stored inside for long periods of time [2].&lt;/p&gt;&#xA;&lt;p&gt;So, a crystal decanter that has leached lead could possess a less smooth surface that doesn't repel liquid as readily, while a lead crystal decanter that has not contained liquid for long periods may maintain its smooth and slippy surface. You may be able to test this hypothesis by examining the microscopic surface in some way.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.assayoffice.co.uk/assets/uploads/Crystal%20Glass%20Factsheet.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.assayoffice.co.uk/assets/uploads/Crystal%20Glass%20Factsheet.pdf&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.canada.ca/en/health-canada/services/healthy-living/your-health/products/lead-crystalware-your-health.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.canada.ca/en/health-canada/services/healthy-living/your-health/products/lead-crystalware-your-health.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4684" LastEditorUserId="7" LastEditDate="2021-12-14T18:20:59.183" LastActivityDate="2021-12-14T18:20:59.183" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7259" PostTypeId="2" ParentId="7226" CreationDate="2021-12-14T17:28:11.613" Score="5" Body="&lt;p&gt;I've been using Pynao and Siesta recently. I made it work just a couple of days ago.&lt;/p&gt;&#xA;&lt;p&gt;Regarding your questions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;I am not sure, but I think ASE has a database for elements. You said about graphene, and I am pretty sure the mass is already defined. Maybe you could try &lt;code&gt;yoursystem.get_masses()&lt;/code&gt;. I am pretty sure it is there. Make sure you understand ASE, this is a simple question (pls, don't get me wrong).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I don't think VIBRA will get you Raman. It needs the vibrational and electronic properties for that. VIBRA will only get you the first one, if I am not mistaken.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I don't think it is impossible, but it is better not to mix the codes, since you should master both.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;According to your info, it is possible that you may be running a poor quality calculation. Also, bear in mind that the supercell must be large enough. I did not get the Raman yet, but with a 7x7 graphene supercell, you get a correct phonon dispersion using ASE's vibration module.&lt;/p&gt;&#xA;&lt;p&gt;Also, it is not in Pynao's documentation that you can select only the unitcell to move. You can create a simple number list (for graphene it would be &lt;code&gt;g = [0, 1]&lt;/code&gt;) and calculate everything only with these atoms. This saves time.&lt;/p&gt;&#xA;&lt;p&gt;It is an option in &lt;a href=&quot;https://mbarbrywebsite.ddns.net/pynao/doc/html/examples/ASERaman/tutorial_raman.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;StaticRamanCalculator&lt;/a&gt; called  &lt;code&gt;indices=&lt;/code&gt;. Look for Barbry PhD thesis.&lt;/p&gt;&#xA;" OwnerUserId="4685" LastEditorUserId="7" LastEditDate="2021-12-14T18:16:22.637" LastActivityDate="2021-12-14T18:16:22.637" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7260" PostTypeId="1" AcceptedAnswerId="7261" CreationDate="2021-12-14T19:38:58.437" Score="5" ViewCount="1017" Body="&lt;p&gt;I wanted to run ORCA 5.0.2 with the following input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; # Monomer A neutral&#xA; ! RKS B3LYP aug-cc-pVTZ Grid4 bohr&#xA; %output&#xA;   Print[ P_Mulliken ] 1&#xA;   Print[ P_AtCharges_M ] 1&#xA; end&#xA;* xyz   0 1&#xA;  O       0.0000000000000000      0.0000000000000000      0.1255133173000000&#xA;  H      -1.4536519622999999      0.0000000000000000     -0.9961739827000000&#xA;  H       1.4536519622999999      0.0000000000000000     -0.9961739827000000&#xA; *&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I obtained the error message &lt;code&gt;UNRECOGNIZED OR DUPLICATED KEYWORD(S) IN SIMPLE INPUT LINE GRID4 BOHR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My input is a valid input for ORCA 3.0.1. What has changed since then?&lt;/p&gt;&#xA;" OwnerUserId="4119" LastActivityDate="2021-12-14T20:49:57.570" Title="Unrecognized or duplicated keyword error using ORCA" Tags="|software|quantum-chemistry|computational-chemistry|electronic-structure|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7261" PostTypeId="2" ParentId="7260" CreationDate="2021-12-14T20:49:57.570" Score="6" Body="&lt;p&gt;Grid4 has been removed in Orca 5, you must use defgridX instead, where X=1,2,3.&lt;/p&gt;&#xA;&lt;p&gt;In general the defaults should be much better and Grid4 is probably at least met by the default grid in Orca 5.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2021-12-14T20:49:57.570" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7262" PostTypeId="2" ParentId="7134" CreationDate="2021-12-14T21:25:04.937" Score="9" Body="&lt;p&gt;The &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt; python package might be useful to you. It has:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Tools to build hamiltonians&lt;/strong&gt; with user-defined basis orbitals.&lt;/li&gt;&#xA;&lt;li&gt;A very &lt;strong&gt;high level API to visualize&lt;/strong&gt; the most common analysis from your hamiltonian (bands, PDOS, wavefunctions, etc...).&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Lower level APIs to customize&lt;/strong&gt; your analysis as you wish.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here's an example of how you might define a tight binding Hamiltonian for graphene:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;import sisl.viz&#xA;import numpy as np&#xA;&#xA;# Define a basis orbital, with a radial function that is defined by us&#xA;r = np.linspace(0, 3.5, 50)&#xA;f = np.exp(-r)&#xA;orb = sisl.AtomicOrbital('2pzZ', (r, f))&#xA;&#xA;# Build a graphene structure using our orbital as basis for the C atoms.&#xA;geom = sisl.geom.graphene(atoms=sisl.Atom(6, orb))&#xA;&#xA;# Initialize a hamiltonian matrix for the geometry&#xA;H = sisl.Hamiltonian(geom)&#xA;# And set the non zero values.&#xA;# In this case, matrix elements of atoms that are closer than 0.1 Ang&#xA;# (i.e. the same atom) are assigned 0 eV and connections of less than&#xA;# 1.44 Ang (first neighbours) are assigned -2.7 eV. &#xA;H.construct([(0.1, 1.44), (0, -2.7)], )&#xA;# To make it more interesting, we will change the on-site energies of&#xA;# the two atoms&#xA;H[0,0] = -1&#xA;H[1,1] = 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, you can go on and use any of the methods of the Hamiltonian (see &lt;a href=&quot;https://zerothi.github.io/sisl/api/generated/sisl.physics.Hamiltonian.html?highlight=hamiltonian#sisl.physics.Hamiltonian&quot; rel=&quot;noreferrer&quot;&gt;docs&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;However, if you want a quick analysis you can use the high level API of the visualization module (&lt;a href=&quot;https://zerothi.github.io/sisl/visualization/viz_module/index.html&quot; rel=&quot;noreferrer&quot;&gt;docs&lt;/a&gt;). Following I show you some of the quick analysis you can do. I tweak some parameters of each analysis, but there are more parameters for which I'm using the defaults.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PDOS:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;pdos_plot = H.plot.pdos(&#xA;    kgrid=[90,90,1], nE=500, Erange=[-4, 4],&#xA;    distribution={&amp;quot;method&amp;quot;: &amp;quot;gaussian&amp;quot;, &amp;quot;smearing&amp;quot;: 0.1}&#xA;)&#xA;&#xA;pdos_plot.split_DOS(on=&amp;quot;atoms&amp;quot;, name=&amp;quot;Atom $atoms&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ctUoy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ctUoy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Wavefunctions (given your defined basis):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;H.plot.wavefunction(&#xA;    i=1, grid_prec=0.05, axes=&amp;quot;xy&amp;quot;, &#xA;    represent=&amp;quot;mod&amp;quot;, nsc=[2,2,1], zsmooth=&amp;quot;best&amp;quot;&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pXkxa.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pXkxa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Bands:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# We need to define a path for the band structure&#xA;bz = sisl.BandStructure(&#xA;    H, points=[[0, 0, 0], [2/3, 1/3, 0], [1/2, 0, 0]],&#xA;    divisions=30, names=[&amp;quot;Gamma&amp;quot;, &amp;quot;M&amp;quot;, &amp;quot;K&amp;quot;]&#xA;)&#xA;&#xA;# Then just plot it&#xA;bz.plot()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9Vgsf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9Vgsf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Fatbands:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;fatbands = bz.plot.fatbands()&#xA;&#xA;fatbands.split_groups(on=&amp;quot;atoms&amp;quot;, name=&amp;quot;Atom $atoms&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ofb8W.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ofb8W.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you have doubts you can go through the &lt;a href=&quot;https://zerothi.github.io/sisl/&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt; or ask specific questions on the &lt;a href=&quot;https://discord.gg/5XnFXFdkv2&quot; rel=&quot;noreferrer&quot;&gt;discord server&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2021-12-14T21:25:04.937" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="7263" PostTypeId="1" AcceptedAnswerId="8276" CreationDate="2021-12-15T05:06:51.170" Score="7" ViewCount="3494" Body="&lt;p&gt;Can anyone please help me transform &lt;span class=&quot;math-container&quot;&gt;$\ce{LiCoO2}$&lt;/span&gt; hexagonal cell (&lt;span class=&quot;math-container&quot;&gt;$a \times a \times c$&lt;/span&gt;) to orthorhombic cell (&lt;span class=&quot;math-container&quot;&gt;$a \times a \sqrt{3} \times 1$&lt;/span&gt;) and hexagonal cell (&lt;span class=&quot;math-container&quot;&gt;$a \sqrt{3} \times a \sqrt{3}\times 1$&lt;/span&gt;)?&lt;a href=&quot;https://i.stack.imgur.com/g8yLv.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/g8yLv.jpg&quot; alt=&quot;Image of cell transformations from a hexagonal a x a x c cell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="7" LastEditDate="2021-12-15T14:08:58.650" LastActivityDate="2023-01-02T17:37:08.477" Title="How to transform lattice in VESTA" Tags="|crystallography|vesta|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="7264" PostTypeId="2" ParentId="7227" CreationDate="2021-12-15T06:04:59.077" Score="4" Body="&lt;p&gt;The following small- to medium-sized molecular have multi-reference character,  meaning that your CISD calculation will likely show the reference wavefunction to have a weight that is quite a fair bit smaller than 1 (this is not a complete list, but it contains molecules that I've either worked on recently or ones that others in the multi-reference community have studied a lot recently):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{FeMoco}$&lt;/span&gt; (I've published a couple papers on it [&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5063376&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;], [&lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0005754&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;]).&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{O3}$&lt;/span&gt; (away from equilibrium, as in &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4990673&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper of mine&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{Cr2}$&lt;/span&gt; (recent calculations have compared to my empirical potential &lt;a href=&quot;https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.2.012015&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{N2}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C2}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{CH2}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C2H4}$&lt;/span&gt; (ethylene)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C4H6}$&lt;/span&gt; (butadiene)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C6H8}$&lt;/span&gt; (hexatriene}&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;I notice that one of the molecules in my list (butadiene), happens to have the same chemical formula as the molecule you studied in your input file.&lt;/strong&gt; Butadiene is a very popular benchmark molecule for multi-reference calculations and you could cite my &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/C4H10/summary.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub database of energies on the molecule&lt;/a&gt;. If you want the geometry of butadiene used by myself and many others, you can look in &lt;a href=&quot;https://arxiv.org/abs/1804.09610&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; and follow the references forwards and backwards if necessary.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-15T06:52:30.947" LastActivityDate="2021-12-15T06:52:30.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7266" PostTypeId="1" CreationDate="2021-12-15T10:26:41.853" Score="6" ViewCount="744" Body="&lt;p&gt;I am trying to figure out the difference between ENCUT and ENAUG in VASP settings, I found the following description on the wiki of VASP.&lt;br&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/ENAUG&quot; rel=&quot;nofollow noreferrer&quot;&gt;ENAUG&lt;/a&gt; specifies the cut-off energy of the plane wave representation of the augmentation charges in eV.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/ENCUT&quot; rel=&quot;nofollow noreferrer&quot;&gt;ENCUT&lt;/a&gt; specifies the cutoff energy for the plane-wave-basis set in eV.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I also found the &lt;code&gt;ENMAX&lt;/code&gt; and &lt;code&gt;EAUG&lt;/code&gt; values from the pseudopotential file of the oxygen element&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   ENMAX  =  400.000; ENMIN  =  300.000 eV&#xA;   ICORE  =        2    local potential&#xA;   LCOR   =        T    correct aug charges&#xA;   LPAW   =        T    paw PP&#xA;   EAUG   =  605.392&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Apparently, they are different. I understand the &lt;code&gt;ENCUT&lt;/code&gt; and &lt;code&gt;ENMAX&lt;/code&gt; are used to determine how many plane-wave-basis will be included in the basis set. My question is:&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Regarding the &lt;code&gt;ENAUG&lt;/code&gt;, what does it mean by the &lt;code&gt;augmentation charges&lt;/code&gt;?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-12-15T18:44:00.097" LastActivityDate="2021-12-16T00:20:43.987" Title="Different between ENCUT and ENAUG in the VASP setting?" Tags="|density-functional-theory|vasp|projector-augmented-wave|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7267" PostTypeId="1" CreationDate="2021-12-15T11:05:37.663" Score="7" ViewCount="415" Body="&lt;p&gt;I am trying to figure out the initialization process of VASP, and I found an INCAR tag &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NELMDL&quot; rel=&quot;noreferrer&quot;&gt;NELMDL&lt;/a&gt;, on the wiki page of NELMDL, it is said that VASP requires 5-10 steps to obtain the reasonable orbitals. This seems strange, when setting ISTART=0 and INIWAV=1, the initial charge density is calculated by taking the superposition of atomic charge densities. So I could get reasonable charge density directly, and use it to calculate the reasonable orbitals by just one step.&lt;br&gt;&#xA;My question is:&#xA;Why does it take 5-10 steps to obtain reasonable orbitals?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Default: NELMDL&lt;br /&gt;&#xA;= -5    if ISTART=0, INIWAV=1, and IALGO=8&lt;br&gt;&#xA;= -12   if ISTART=0, INIWAV=1, and IALGO=48 &lt;br&gt;&#xA;Description: NELMDL specifies the number of non-selfconsistent steps at the beginning.&lt;br&gt;&#xA;If the orbitals are initialized using a random number generator (the&#xA;default in VASP), the initial orbitals are usually unreasonable and&#xA;the iterative matrix diagonalization will &lt;strong&gt;require 5-10 steps&lt;/strong&gt; to obtain&#xA;reasonable orbitals. &lt;strong&gt;The charge density corresponding to the initial&#xA;orbitals is also, at best, erratic.&lt;/strong&gt; It is hence advisable to perform a&#xA;few electronic steps while keeping the initial Hamiltonian fixed. This&#xA;initial Hamiltonian is usually determined from a superposition of&#xA;atomic charge densities.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Here is the Schematic representation of the self-consistent loop for the solution of Kohn–Sham equations. I think it would only take just once loop to get reasonable orbitals.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/89Mvd.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/89Mvd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2021-12-15T13:04:28.983" LastActivityDate="2021-12-24T20:29:31.713" Title="Why does it take 5-10 steps to obtain reasonable orbitals during initialization in VASP?" Tags="|density-functional-theory|vasp|ab-initio-calculations|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="7268" PostTypeId="2" ParentId="7021" CreationDate="2021-12-15T13:53:24.643" Score="3" Body="&lt;p&gt;The most common problem in vasp for any job to stop is out of memory. Before going through debugging whole process, first check your structure in &lt;code&gt;VESTA/OVITO&lt;/code&gt;, if you structure seems correct then run one SCF calculation with &lt;code&gt;ALGO=N&lt;/code&gt; or &lt;code&gt;IALGO=38&lt;/code&gt;, with &lt;code&gt;KPOINTS&lt;/code&gt; to single gamma point. Once everything is fine, increase your kpoints.  For surface calculation vacuum of 10-15 Angstrom is enough and Kpoints to be 1.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-12-15T13:53:24.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7269" PostTypeId="2" ParentId="3874" CreationDate="2021-12-15T15:22:12.993" Score="4" Body="&lt;p&gt;I'd start from&#xA;&lt;strong&gt;&lt;a href=&quot;https://biologicalmodeling.org/coronavirus/structure_intro&quot; rel=&quot;nofollow noreferrer&quot;&gt;An Introduction to Protein Structure Prediction&lt;/a&gt;&lt;/strong&gt; which is part of a just published course &lt;a href=&quot;https://biologicalmodeling.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Biological Modeling: A Free Online Course&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The author of this course is also a mathematician by training. He co-authored a bioinformatics MOOC on Coursera, one of the best online lectures I listened to (in the meantime this MOOC became a series of smaller courses and is not free anymore). I haven't had chance to go through the whole Biological Modeling course yet, but from what I see, it's also well prepared and geared towards mathematically inclined people.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2021-12-15T15:22:12.993" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="7270" PostTypeId="2" ParentId="7267" CreationDate="2021-12-15T17:29:56.710" Score="5" Body="&lt;p&gt;Most quantum chemistry codes that employ a linear combination of atomic orbitals approach employ dense matrix diagonalization, meaning that once you have the Fock matrix i.e. potential, you get the orbitals it generates in a single step.&lt;/p&gt;&#xA;&lt;p&gt;However, VASP, like every other plane wave code, employs an iterative diagonalizer / relaxation scheme to update the orbitals. Thus, even if you have a good guess for the electron density &amp;lt;=&amp;gt; the potential the electrons move in, you still have to perform several iterations to determine the orbitals that are eigenstates in this potential.&lt;/p&gt;&#xA;&lt;p&gt;However, since the potential from the superposition of atomic densities (SAD) guess differs from the potential generated by the true ground state electron density, it is often more efficient to omit full optimization of the initial guess orbitals, since the orbitals are wrong anyway. So, instead of converging the guess orbitals (which may require 20-30 iterations), 5-10 is sufficient to get the orbitals &amp;quot;close enough&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Some codes employ an alternative approach in which the guess orbitals are obtained from a small to minimal-basis LCAO calculation, which is then projected onto the plane wave basis. However, this requires more code than the initialization with random numbers + iterative diagonalization with the SAD potential.&lt;/p&gt;&#xA;&lt;p&gt;addendum: you've added the flowchart in the question. The steps that the manual talks about happen in the &amp;quot;solve KS equation&amp;quot; phase. Once you have updated values for the occupied orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi_i^\sigma$&lt;/span&gt;, you calculate the new electron density and the new potential, and solve again the KS equation with the new potential. Once the orbitals don't change any more, they have become self-consistent.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-12-24T20:29:31.713" LastActivityDate="2021-12-24T20:29:31.713" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="7271" PostTypeId="1" AcceptedAnswerId="7272" CreationDate="2021-12-15T18:08:27.470" Score="6" ViewCount="591" Body="&lt;p&gt;When calculating the band structure of a material, I have been told that at first, I need to do structure optimization to get a stationary structure(&lt;strong&gt;1st step&lt;/strong&gt;), and then keep the atoms' position fixed, do a self-consistent calculation to get the band structure(&lt;strong&gt;2nd step&lt;/strong&gt;). But if I am doing this job with VASP, self-consistent field calculation of the electrons is included in the loop when optimizing the structure. The only difference is at the first step of optimizing structures, the atoms' position is variant, but when getting to convergence, I am guessing the atoms' positions don't vary too much actually &lt;BR&gt;&#xA;My question is:&lt;br&gt;&#xA;Is there a difference between the charge density of the 1st step and 2nd step?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2021-12-15T18:33:45.460" LastActivityDate="2023-06-09T23:26:00.110" Title="Is it necessary to do self-consistent calculation after structure optimization?" Tags="|density-functional-theory|vasp|band-structure|materials-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="7272" PostTypeId="2" ParentId="7271" CreationDate="2021-12-15T18:22:52.733" Score="4" Body="&lt;p&gt;The procedure that takes more time to finish is the geometry optimization (in each step there are self-consistence field calculations).&lt;/p&gt;&#xA;&lt;p&gt;There are properties that can not be calculated at the same time (all in one step) or you need to know more information about how to calculate it. For example, to calculate the DOS, you need to know the band structure to then, select the energy interval.&lt;/p&gt;&#xA;&lt;p&gt;Answering your question: &lt;em&gt;Is there a significant difference between the charge density of the 1st step and 2nd step?&lt;/em&gt; No.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-15T18:22:52.733" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="7273" PostTypeId="2" ParentId="7266" CreationDate="2021-12-15T23:42:25.473" Score="5" Body="&lt;p&gt;When you're using a norm-conserving pseudopotential, the charge density &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{NC}(r)$&lt;/span&gt; is calculated directly from the modulus-squared of the wavefunction:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{1}&#xA;\rho^\mathrm{NC}(r) = \sum_{bk}\left\vert\psi_{bk}(r)\right\vert^2,&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; are band and k-point indices, respectively, and I've restricted the summation to over occupied bands, for simplicity (in general, we'd also need to include the band occupation). By convention, we also omit the fundamental charge of an electron, &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt;, since it has unit value in atomic units.&lt;/p&gt;&#xA;&lt;p&gt;In order to fully represent this charge density, we need to have a Fourier grid which is twice as big as the wavefunction cut-off wavevector in each direction. This factor of two comes directly from the fact that the density is the wavefunction &lt;em&gt;squared&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In an ultrasoft (or PAW) method, the charge density is no longer simply the modulus-squared of the Bloch functions, but gains an &amp;quot;augmentation&amp;quot; charge term,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{2}&#xA;\rho^\mathrm{USP}(r) = \sum_{bk}\left(\left\vert\psi_{bk}(r)\right\vert^2 + \sum_{nmI}Q^I_{nm}(r)\langle\psi_{bk}\vert\beta_{n}^I\rangle\langle\beta_{m}^I\vert\psi_{bk}\rangle\right),&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; is an atom index, and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; are projector indices. &lt;span class=&quot;math-container&quot;&gt;$Q^I_{nm}(r)$&lt;/span&gt; are the &lt;em&gt;augmentation charges&lt;/em&gt; themselves.&lt;/p&gt;&#xA;&lt;p&gt;If we have a Fourier grid twice as large as the cut-off wavevector, then we can represent the first term exactly; however, the second term depends on &lt;span class=&quot;math-container&quot;&gt;$Q^I_{nm}(r)$&lt;/span&gt;, which is not related to &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;. Can &lt;span class=&quot;math-container&quot;&gt;$Q^I_{nm}(r)$&lt;/span&gt; be represented exactly on this Fourier grid, or does it need a larger grid?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Q(r)$&lt;/span&gt; is actually &lt;em&gt;designed&lt;/em&gt; to have larger Fourier components, this is in fact why the ultrasoft/PAW method can give lower cut-off energies for &lt;span class=&quot;math-container&quot;&gt;$d-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f-$&lt;/span&gt;block elements. This means that it cannot usually be represented well on the same Fourier grid we used for the soft charge density, and we need a larger grid for the full &lt;em&gt;augmented&lt;/em&gt; charge density. It is the size of this &amp;quot;augmentation charge grid&amp;quot; which is controlled by &lt;code&gt;EAUG&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="5" LastEditDate="2021-12-16T00:20:43.987" LastActivityDate="2021-12-16T00:20:43.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8273" PostTypeId="1" CreationDate="2021-12-16T05:16:44.923" Score="9" ViewCount="132" Body="&lt;p&gt;I have a lattice system with two types of sites, namely A and B. Both A and B have a possible up or down spin orientation. There exists  &lt;span class=&quot;math-container&quot;&gt;$J_\textrm{aa,align}/J_\textrm{aa,mis}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J_\textrm{bb,align}/J_\textrm{bb,mis}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$J_\textrm{ab,align}/J_\textrm{ab,mis}$&lt;/span&gt; interactions in my system between nearest neighbors. There is no external field.&lt;/p&gt;&#xA;&lt;p&gt;I am following the notes given &lt;a href=&quot;https://csml.northwestern.edu/resources/Reprints/lnp_color.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; [1].&lt;/p&gt;&#xA;&lt;p&gt;I want to employ Swendsen-Wang evolution for this problem, and &lt;strong&gt;I wanted to know if I can form &amp;quot;bonds&amp;quot; between A and B sites? Is that rigorously possible? Or is do sites of type A only bond with sites of type A, and likewise for B?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Computer Simulations in Condensed Matter Systems: From Materials to Chemical Biology Volume 1. &lt;em&gt;Lect. Notes Phys.&lt;/em&gt; &lt;strong&gt;2006&lt;/strong&gt;. &lt;a href=&quot;https://doi.org/10.1007/3-540-35273-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1007/3-540-35273-2&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2022-09-28T22:39:05.293" LastActivityDate="2022-09-30T10:05:04.863" Title="Some questions about implementing Swendsen-Wang algorithm" Tags="|statistical-thermodynamics|monte-carlo|ising-model|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8274" PostTypeId="1" AcceptedAnswerId="8277" CreationDate="2021-12-17T01:03:44.893" Score="10" ViewCount="1467" Body="&lt;p&gt;I have a question about the basis functions of Gaussian. When the basis function is set (e.g., 6-31G), I would like to know the specific value of Gaussian's parameters for each atom.&lt;/p&gt;&#xA;&lt;p&gt;In particular, I would like to know the value of &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; (i.e., the orbital exponent) in &lt;span class=&quot;math-container&quot;&gt;$\exp(-\zeta r^2)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the distance.  Is this fixed or optimized in the energy minimization process?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2021-12-20T09:26:33.257" LastActivityDate="2021-12-23T00:48:25.760" Title="How can I find the parameters in a basis set?" Tags="|quantum-chemistry|electronic-structure|gaussian|basis-sets|databases|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8275" PostTypeId="1" AcceptedAnswerId="8282" CreationDate="2021-12-17T06:31:17.713" Score="7" ViewCount="755" Body="&lt;p&gt;I am building a model in the Materials Studio which includes many atoms, so I'd like to count the number of different atoms, is there any way to do that?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-12-17T06:52:42.643" LastActivityDate="2021-12-17T12:52:28.363" Title="How could I know the numbers of different atoms in Materials Studio?" Tags="|materials-design|materials-engineering|materials-studio|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8276" PostTypeId="2" ParentId="7263" CreationDate="2021-12-17T06:34:36.603" Score="5" Body="&lt;p&gt;&lt;strong&gt;structure 1&lt;/strong&gt;&lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/AvkRc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AvkRc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;br /&gt;&#xA;&lt;strong&gt;Method affine transformation of simulation box after replicating in X and Y in ovito&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/zMUEK.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zMUEK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;OUTPUT: POSCAR&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR file written by OVITO&#xA;1.0&#xA;        2.8428978920         0.0000000000         0.0000000000&#xA;        0.0000000000         4.9240398407         0.0000000000&#xA;        0.0000000000         0.0000000000        14.1456146240&#xA;   Li   Co    O&#xA;    6    6   12&#xA;Direct&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.500000461         0.166666663         0.333332985&#xA;     0.000000000         0.333333809         0.666666981&#xA;    -0.000000000         0.666667086         0.333332985&#xA;     0.499999958         0.500000436         0.000000000&#xA;     0.499999455         0.833334173         0.666666981&#xA;     0.000000000         0.333333809         0.166666998&#xA;    -0.000000000        -0.000000000         0.500000000&#xA;     0.500000461         0.166666663         0.833333019&#xA;     0.000000000         0.666667086         0.833333019&#xA;     0.499999455         0.833334173         0.166666998&#xA;     0.499999958         0.500000436         0.500000000&#xA;    -0.000000000        -0.000000000         0.239586996&#xA;     0.500000461         0.166666663         0.093745997&#xA;     0.500000461         0.166666663         0.572920049&#xA;    -0.000000000         0.333333809         0.427080019&#xA;    -0.000000000         0.333333809         0.906254011&#xA;    -0.000000000        -0.000000000         0.760412970&#xA;     0.000000000         0.666667086         0.093745997&#xA;    -0.000000000         0.666667086         0.572920049&#xA;     0.499999958         0.500000436         0.239586996&#xA;     0.499999455         0.833334173         0.427080019&#xA;     0.499999455         0.833334173         0.906254011&#xA;     0.499999958         0.500000436         0.760412970&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;structure2&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/S7rgO.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S7rgO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;br /&gt;&#xA;&lt;strong&gt;Method affine transformation of simulation box after replicating in X and Y in ovito&lt;/strong&gt;&lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/99oBP.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/99oBP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;OUTPUT: POSCAR&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POSCAR file written by OVITO&#xA;1.0&#xA;        4.9240450859         0.0000000000         0.0000000000&#xA;        2.4620173651         4.2643450666         0.0000000000&#xA;        0.0000000000         0.0000000000        14.1456146240&#xA;   Li   Co    O&#xA;    9    9   18&#xA;Direct&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.333333430        -0.000000000         0.333332985&#xA;    -0.000000007         0.333333975         0.666666981&#xA;    -0.000000018         0.666666944         0.333332985&#xA;     0.666665892        -0.000000000         0.666666981&#xA;     0.333333114         0.333333891         0.000000000&#xA;     0.666666524         0.333333835         0.333332985&#xA;     0.333332722         0.666667838         0.666666981&#xA;     0.666666229         0.666667782         0.000000000&#xA;    -0.000000007         0.333333975         0.166666998&#xA;    -0.000000000        -0.000000000         0.500000000&#xA;     0.333333430        -0.000000000         0.833333019&#xA;    -0.000000018         0.666666944         0.833333019&#xA;     0.666665892        -0.000000000         0.166666998&#xA;     0.333332722         0.666667838         0.166666998&#xA;     0.333333114         0.333333891         0.500000000&#xA;     0.666666524         0.333333835         0.833333019&#xA;     0.666666229         0.666667782         0.500000000&#xA;     0.000000000        -0.000000000         0.239586996&#xA;     0.333333430        -0.000000000         0.093745997&#xA;     0.333333430        -0.000000000         0.572920049&#xA;    -0.000000007         0.333333975         0.427080019&#xA;    -0.000000007         0.333333975         0.906254011&#xA;    -0.000000000         0.000000000         0.760412970&#xA;    -0.000000018         0.666666944         0.093745997&#xA;    -0.000000018         0.666666944         0.572920049&#xA;     0.666665892        -0.000000000         0.427080019&#xA;     0.666665892        -0.000000000         0.906254011&#xA;     0.333333114         0.333333891         0.239586996&#xA;     0.666666524         0.333333835         0.093745997&#xA;     0.666666524         0.333333835         0.572920049&#xA;     0.333332722         0.666667838         0.427080019&#xA;     0.333332722         0.666667838         0.906254011&#xA;     0.333333114         0.333333891         0.760412970&#xA;     0.666666229         0.666667782         0.239586996&#xA;     0.666666229         0.666667782         0.760412970&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Load POSCAR &amp;gt; show periodic image &amp;gt; affine transformation &amp;gt; manual selection &amp;gt; delete selected atoms &amp;gt;export as POSCAR&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;NOTE: During delete of extra atom outside simulation box don't include periodically equivalent atoms in boundaries&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-12-17T06:34:36.603" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8277" PostTypeId="2" ParentId="8274" CreationDate="2021-12-17T06:46:23.697" Score="10" Body="&lt;p&gt;Go to &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;noreferrer&quot;&gt;Basis Set Exchange&lt;/a&gt; and click on the elements in which you're interested, then click the basis set in which you're interested (in your question, you mentioned 6-31G) and then for &amp;quot;Format&amp;quot; you can choose &amp;quot;Gaussian&amp;quot; or any of various other programs. After all that, when you click &amp;quot;Get Basis Set&amp;quot; you will get the basis set &lt;strong&gt;parameters&lt;/strong&gt; for those elements, for the specific basis set you chose, and in the format you chose.&lt;/p&gt;&#xA;&lt;p&gt;Here's the basis set parameters for H, He, and Li for 6-31G in Gaussian format (which I obtained by following my above instructions):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H     0&#xA;S    3   1.00&#xA;      0.1873113696D+02       0.3349460434D-01&#xA;      0.2825394365D+01       0.2347269535D+00&#xA;      0.6401216923D+00       0.8137573261D+00&#xA;S    1   1.00&#xA;      0.1612777588D+00       1.0000000&#xA;****&#xA;He     0&#xA;S    3   1.00&#xA;      0.3842163400D+02       0.4013973935D-01&#xA;      0.5778030000D+01       0.2612460970D+00&#xA;      0.1241774000D+01       0.7931846246D+00&#xA;S    1   1.00&#xA;      0.2979640000D+00       1.0000000&#xA;****&#xA;Li     0&#xA;S    6   1.00&#xA;      0.6424189150D+03       0.2142607810D-02&#xA;      0.9679851530D+02       0.1620887150D-01&#xA;      0.2209112120D+02       0.7731557250D-01&#xA;      0.6201070250D+01       0.2457860520D+00&#xA;      0.1935117680D+01       0.4701890040D+00&#xA;      0.6367357890D+00       0.3454708450D+00&#xA;SP   3   1.00&#xA;      0.2324918408D+01      -0.3509174574D-01       0.8941508043D-02&#xA;      0.6324303556D+00      -0.1912328431D+00       0.1410094640D+00&#xA;      0.7905343475D-01       0.1083987795D+01       0.9453636953D+00&#xA;SP   1   1.00&#xA;      0.3596197175D-01       0.1000000000D+01       0.1000000000D+01&#xA;****&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the above data, for each row, the first number is the exponent, and the rest of the numbers in that row are the contraction coefficients.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://raw.githubusercontent.com/HPQC-LABS/AI_ENERGIES/master/GENBAS&quot; rel=&quot;noreferrer&quot;&gt;I also host an open-source basis set repository&lt;/a&gt; which is easy for any member of the public to edit, though the exponents and contraction coefficients are in &lt;code&gt;GENBAS&lt;/code&gt; format (the format used by at least ACES, CFOUR, and MRCC) instead of Gaussian format; but in this format it might be clearer to see what's going on (and you can see all basis sets at the same time without clicking anything or worrying about new windows popping up). For the H atom, the same basis set as above, is displayed this way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H:6-31G-EMSL&#xA;EMSL 30_08_2019&#xA;&#xA;  1&#xA;    0&#xA;    2&#xA;    4&#xA;&#xA;0.1873113696D+02  0.2825394365D+01  0.6401216923D+00  0.1612777588D+00&#xA;&#xA;0.3349460434D-01  0.00000000&#xA;0.2347269535D+00  0.00000000&#xA;0.8137573261D+00  0.00000000&#xA;0.00000000        1.0000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The first line is the name of the basis set which the electronic structure software will use in order to know where in the file to look&lt;/li&gt;&#xA;&lt;li&gt;The next line is a comment, to give you more information about the basis set without affecting calculations in any way (in this case I put &amp;quot;EMSL 30_08_2019&amp;quot; to indicate that I got the basis set from EMSL on that date).&lt;/li&gt;&#xA;&lt;li&gt;Next we have an integer telling us how many types of basis functions we'll use (s-type, p-type, etc.).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The following three integers in this example are &lt;code&gt;0 2 4&lt;/code&gt;, to indicate the number of exponents and contractions for s-type (hence the &lt;code&gt;0&lt;/code&gt;) basis functions.&lt;/li&gt;&#xA;&lt;li&gt;Next we get the &lt;code&gt;4&lt;/code&gt; exponents: &lt;code&gt;0.1873113696D+02  0.2825394365D+01  0.6401216923D+00  0.1612777588D+00&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;The rest of the numbers tell us about the contraction coefficients.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you find the Gaussian format confusing, you can always check the corresponding numbers in the &lt;code&gt;GENBAS&lt;/code&gt; format, which organizes it differently (and &lt;em&gt;vice versa&lt;/em&gt; if you're confused about the GENBAS format). You can see that the exponents and contraction coefficients in the Gaussian-formatted basis set from Basis Set Exchange are the same as in my &lt;code&gt;GENBAS&lt;/code&gt; file, for which I've given what I hope to be clear and thorough explanations for what each part represents.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-12-17T06:46:23.697" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8278" PostTypeId="5" CreationDate="2021-12-17T06:52:23.897" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Materials_Studio&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Materials_Studio&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-17T06:52:23.897" LastActivityDate="2021-12-17T06:52:23.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8279" PostTypeId="4" CreationDate="2021-12-17T06:52:23.897" Score="0" Body="Questions about or related to Materials Studio (the software distributed by BIOBIA)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-17T06:52:23.897" LastActivityDate="2021-12-17T06:52:23.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8280" PostTypeId="2" ParentId="7225" CreationDate="2021-12-17T10:31:34.037" Score="4" Body="&lt;p&gt;You are correct in saying that&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block ChemicalSpecieslabel&#xA;    1 17 S&#xA;%endblock ChemicalSpecieslabel&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;would just indicate that you have a &lt;code&gt;Cl&lt;/code&gt; atom but with an &lt;code&gt;S&lt;/code&gt; symbol.&lt;/p&gt;&#xA;&lt;p&gt;There's the &lt;code&gt;NetCharge&lt;/code&gt; flag. If you look at SIESTA's user guide it explains what it does. However, then you'd probably be defining a periodically charged system. Does this make sense? You should read carefully the indications in the manual to know if your system fits the very specific requirements for it to work.&lt;/p&gt;&#xA;&lt;p&gt;A more natural thing is usually to have a neutral system where your atoms get naturally charged because of the positions of their energy levels. Say if you think there's a &lt;span class=&quot;math-container&quot;&gt;$S^-$&lt;/span&gt; in your system, there probably is a positive ion as well that is donating the charge.&lt;/p&gt;&#xA;&lt;p&gt;You can then check Hirshfeld, Voronoi or Mulliken charges to understand if the atom is really getting charged. SIESTA will give you these outputs with the flags &lt;code&gt;WriteHirshfeldPop&lt;/code&gt;, &lt;code&gt;WriteVoronoiPop&lt;/code&gt; and &lt;code&gt;WriteMullikenPop&lt;/code&gt;, respectively. You can then check your output file manually or color your structure with charge values using &lt;a href=&quot;https://zerothi.github.io/sisl/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt;, for example (in python):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;import sisl.viz&#xA;&#xA;# Get your structure&#xA;geom = sisl.get_sile(&amp;quot;myfile.fdf&amp;quot;).read_geometry(output=True)&#xA;# Get the last charges from the output file&#xA;net_charges = sisl.get_sile(&amp;quot;myfile.out&amp;quot;).read_charge(&#xA;    &amp;quot;hirshfeld&amp;quot;, iscf=None, imd=None, as_dataframe=True&#xA;)['dq'].values&#xA;&#xA;# And plot the structure using the net charges as the color for the atoms&#xA;geom.plot(atoms_style={&amp;quot;color&amp;quot;: net_charges})&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2021-12-17T10:31:34.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8281" PostTypeId="1" AcceptedAnswerId="8606" CreationDate="2021-12-17T10:47:22.860" Score="10" ViewCount="1972" Body="&lt;p&gt;I am getting confused about what the electronic step and ionic step are in VASP.&#xA;I used to think that finishing the following loop one time is called an electronic step. but I am not sure how to express the ionic step on the following diagram.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/wE33V.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wE33V.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;According to some calculation experience and communication with others, now I tend to think that maybe each iteration during the iterative diagonalization procedure is called an electronic step, and finish &amp;quot;the solving Kohn-Sham equation Loop&amp;quot; is called ionic step, because when the program finishes this loop, it could adjust the atoms' position based on the Hellmann-Feynman theorem.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/GK00Y.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GK00Y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;My question is:&#xA;Which of these two thoughts is the right one?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-12-25T21:43:51.933" LastActivityDate="2022-01-26T18:22:13.887" Title="What are the electronic steps and ionic steps in VASP?" Tags="|density-functional-theory|vasp|quantum-chemistry|ab-initio-calculations|electronic-structure|" AnswerCount="1" CommentCount="8" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8282" PostTypeId="2" ParentId="8275" CreationDate="2021-12-17T12:52:28.363" Score="8" Body="&lt;p&gt;You have to set your interface to show the &lt;em&gt;Properties Explorer&lt;/em&gt;, then select all the atoms of your system and look at the &lt;em&gt;Properties Explorer&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the examples below, there are a periodic system and a molecular one.&lt;/p&gt;&#xA;&lt;p&gt;For the periodic system you will find the information in the &lt;em&gt;Symmetry System&lt;/em&gt; filter under the &lt;em&gt;Property Explorer&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In case of the molecular system, the information is under the &lt;em&gt;Physical System&lt;/em&gt; filter.&lt;/p&gt;&#xA;&lt;p&gt;Setting up &lt;em&gt;Property Explorer&lt;/em&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/M2j8Z.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/M2j8Z.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a periodic system, the info is under &lt;em&gt;Symmetry System&lt;/em&gt; filter:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/QGsKr.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QGsKr.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a molecular system, the info is under &lt;em&gt;Physical System&lt;/em&gt; filter:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gxm9u.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gxm9u.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-17T12:52:28.363" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8283" PostTypeId="1" CreationDate="2021-12-17T13:30:21.850" Score="6" ViewCount="49" Body="&lt;p&gt;If I have single-crystal measurements of electrical conductivity along 3D axes (considering for example anisotropic materials), is there any straightforward way to compute the bulk (global) electrical conductivity, to have a &lt;em&gt;compact&lt;/em&gt; measurement?&lt;/p&gt;&#xA;" OwnerUserId="2017" LastEditorUserId="5" LastEditDate="2021-12-25T22:09:32.467" LastActivityDate="2021-12-25T22:09:32.467" Title="Compute bulk electrical conducitivity from single-crystal measurements" Tags="|electronic-structure|crystallography|physical-properties-of-materials|experimental|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-21T00:47:03.253" ContentLicense="CC BY-SA 4.0" />
  <row Id="8284" PostTypeId="2" ParentId="8274" CreationDate="2021-12-17T14:22:28.663" Score="6" Body="&lt;p&gt;As Nike noted in his answer, Gaussian (and most gaussian orbital based electronic structure programs) does use fixed orbital exponents throughout a calculation. These are either from previously designed basis sets that Gaussian stores (like the Pople or Dunning basis sets) or could be entered in manually using the &lt;a href=&quot;https://gaussian.com/gen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gen&lt;/a&gt; keyword.&lt;/p&gt;&#xA;&lt;p&gt;These exponents are often obtained from an optimization using a single atom computation. This is often good enough to make a reasonable basis for a molecule composed of these atoms, but it could still be improved. It's possible to perform calculations where you do optimize these orbital exponents for the particular molecule they are in.&lt;/p&gt;&#xA;&lt;p&gt;Gaussian provides a utility for this called &lt;a href=&quot;https://gaussian.com/gauopt/&quot; rel=&quot;nofollow noreferrer&quot;&gt;gauopt&lt;/a&gt; which triggers multiple calculations starting from a template input file defining properties to be optimized. Depending on your programming savvy, you could also make a Python function that creates/runs Gaussian jobs given orbital exponents and you could pass this function to an optimization procedure like &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;scipy's minimize&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This paper&lt;sup&gt;[1]&lt;/sup&gt; describes the DiffiQult program, which can compute gradients of various parameters of an HF calculation using automatic differentiation. They demonstrated this with fully variational calculations on &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, where in addition to the MO coefficients, they also optimized the contraction coefficients and orbital exponents.&lt;/p&gt;&#xA;&lt;p&gt;This idea of a fully optimized basis was looked at more extensively (and specifically for solid state systems) in &lt;sup&gt;[2]&lt;/sup&gt;, where they use a DIIS-like procedure to optimize all the basis parameters. They point out how optimizing the basis can lead to greater accuracy than would be expected for a fixed basis of the same (or even larger) size.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Tamayo-Mendoza, T.; Kreisbeck, C.; Lindh, R.; Aspuru-Guzik, A. Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree–Fock. &lt;em&gt;ACS Cent. Sci.&lt;/em&gt; &lt;strong&gt;2018,&lt;/strong&gt; &lt;em&gt;4&lt;/em&gt; (5), 559–566. &lt;a href=&quot;https://doi.org/10.1021/acscentsci.7b00586&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1021/acscentsci.7b00586&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Daga, L. E.; Civalleri, B.; Maschio, L. Gaussian Basis Sets for Crystalline Solids: All-Purpose Basis Set Libraries vs System-Specific Optimizations. &lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;16&lt;/em&gt; (4), 2192–2201. &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.9b01004&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1021/acs.jctc.9b01004&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-12-17T16:22:32.403" LastActivityDate="2021-12-17T16:22:32.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8286" PostTypeId="1" CreationDate="2021-12-17T22:51:21.260" Score="9" ViewCount="218" Body="&lt;p&gt;I would like to use &lt;code&gt;libcint&lt;/code&gt;, the integral library in &lt;code&gt;pyscf&lt;/code&gt; from Fortran. Its webpage has a Fortran API and developer manual, but looks like I still need a tutorial. I posted &lt;a href=&quot;https://github.com/sunqm/libcint/issues/69&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, would like to cross post here, since more people are here.&lt;/p&gt;&#xA;&lt;p&gt;Namely from &lt;a href=&quot;https://github.com/sunqm/libcint/blob/master/examples/fortran_call_cartesian.F90&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;,&#xA;what kind of modifications would be needed to print out results as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto&#xA;mol = gto.Mole()&#xA;mol.atom = '''O 0 0 0; H  0 1 0; H 0 0 1'''&#xA;mol.basis = 'sto-3g'&#xA;mol.build()&#xA;&#xA;kin = mol.intor('int1e_kin')&#xA;vnuc = mol.intor('int1e_nuc')&#xA;overlap = mol.intor('int1e_ovlp')&#xA;eri = mol.intor('int2e')&#xA;&#xA;print('kin', kin.shape, kin)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;via Fortran?&#xA;Thanks a lot.&lt;/p&gt;&#xA;" OwnerUserId="4694" LastEditorUserId="5" LastEditDate="2022-01-20T22:46:04.997" LastActivityDate="2022-01-20T22:46:04.997" Title="Interacting with pyscf integral library from Fortran" Tags="|pyscf|integrals|fcidump|fortran|" AnswerCount="0" CommentCount="14" ClosedDate="2022-01-26T14:43:03.210" ContentLicense="CC BY-SA 4.0" />
  <row Id="8287" PostTypeId="2" ParentId="8274" CreationDate="2021-12-18T04:40:49.543" Score="5" Body="&lt;p&gt;A few points to add to Nike and Tyberius' answers.&lt;/p&gt;&#xA;&lt;p&gt;Literature basis sets &lt;span class=&quot;math-container&quot;&gt;$R_{nl}(r) =\sum_i {d_i^{nl}} \exp (-\alpha_{il} r^2) $&lt;/span&gt; indeed have fixed exponents &lt;span class=&quot;math-container&quot;&gt;$\alpha_i$&lt;/span&gt; and contraction coefficients &lt;span class=&quot;math-container&quot;&gt;$d_i$&lt;/span&gt;. A great paper I just started reading is, for instance, the first paper on the development of the earlier Karlsruhe basis set series, &lt;a href=&quot;https://doi.org/10.1063/1.463096&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 97, 2571 (1992)&lt;/a&gt;. You can find over 600 Gaussian basis sets on the &lt;a href=&quot;http://www.basissetexchange.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;Basis Set Exchange&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Although work on system-optimized basis sets have been recently published in the articles cited by Tyberius but also by some of my collaborators and myself in &lt;a href=&quot;https://arxiv.org/abs/2110.11678&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:2110.11678&lt;/a&gt; (and I think a few more recent works), the idea is quite old. I think its selling point is just as a &amp;quot;cool&amp;quot; demo for automatic differentiation. You don't really want to optimize the basis set for your system, since you don't know how it will affect the quality of your results. Even if your energy improves, your dipole moment may suffer since they are famously sensitive to diffuse functions that energy optimization doesn't favor. Also, it was shown already several decades ago that the optimization takes more time than just using a bigger basis set in the first place! [I am trying to remember the reference but I have to dig it up.]&lt;/p&gt;&#xA;&lt;p&gt;addendum: the early days of quantum chemistry even used floating orbitals, so the idea of system adapted basis sets was obvious already in the 1960s.&lt;/p&gt;&#xA;&lt;p&gt;addendum II: I finally found the reference for system-optimized basis sets I wrote about above. It took non-trivial effort to find, and this was not the first time I tried to dig it out again... I hope next time I'll be able to find it on here ;) The work by Tachikawa, Taneda, and Mori published in &lt;a href=&quot;https://doi.org/10.1002/(SICI)1097-461X(1999)75:4/5%3C497::AID-QUA15%3E3.0.CO;2-C&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 75, 497 (1999)&lt;/a&gt; discusses the &amp;quot;fully variational molecular orbital&amp;quot; (FVMO) method, in which the exponents and centers of the Gaussian basis functions are optimized.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2021-12-23T00:48:25.760" LastActivityDate="2021-12-23T00:48:25.760" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8288" PostTypeId="2" ParentId="8274" CreationDate="2021-12-18T06:13:55.863" Score="4" Body="&lt;p&gt;If you are using the software Gaussian, &lt;code&gt;gfinput&lt;/code&gt; can print out the basis set coefficients/exponents. For more information,&#xA;&lt;a href=&quot;https://gaussian.com/gfinput/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gaussian.com/gfinput/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;One example is at &lt;a href=&quot;http://www.ccl.net/cca/documents/dyoung/topics-orig/gaussian.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.ccl.net/cca/documents/dyoung/topics-orig/gaussian.html&lt;/a&gt;&#xA;with a sample input&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#n test rohf/sto-3g pop=full GFINPUT&#xA;&#xA;&#xA;O sto-3g triplet&#xA;&#xA;&#xA;0 3&#xA;O&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4694" LastEditorUserId="4694" LastEditDate="2021-12-18T17:09:12.583" LastActivityDate="2021-12-18T17:09:12.583" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8289" PostTypeId="1" AcceptedAnswerId="8334" CreationDate="2021-12-18T12:25:08.807" Score="7" ViewCount="2453" Body="&lt;p&gt;I am trying to test how to choose the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/SIGMA&quot; rel=&quot;noreferrer&quot;&gt;SIGMA&lt;/a&gt; value in VASP, so I did a little bit of test.&#xA;Here is the input file:&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;INCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM=FCC Si&#xA;#Start parameter for this run:&#xA;ISTART=0&#xA;ICHARG=2&#xA;&#xA;#Electronic Relaxation 1&#xA;ENCUT=240&#xA;&#xA;#Ionic relaxation&#xA;&#xA;#SMEARING&#xA;ISMEAR=0&#xA;SIGMA=0.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fcc Si:&#xA;3.9&#xA;0.5 0.5 0.0&#xA;0.0 0.5 0.5&#xA;0.5 0.0 0.5&#xA;1&#xA;cartesian&#xA;0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-POINTS SETUP&#xA;0&#xA;GAMMA&#xA;11 11 11&#xA;0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With different SIGMA values, here is the Total energy VS Sigma Value:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dPipf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dPipf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;It seems the total energy won't converge to a fixed limit as the sigma decreases, since the sigma value is used to generate orbital occupation numbers, I am guessing it doesn't mean the sigma value should be as small as possible. Is there any standard procedure to optimize the sigma value or is there a range of sigma values I could choose?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-10T00:27:46.817" Title="How to choose the best SIGMA value in VASP?" Tags="|density-functional-theory|vasp|electronic-structure|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8290" PostTypeId="1" CreationDate="2021-12-18T12:57:49.380" Score="7" ViewCount="152" Body="&lt;p&gt;I am working on protein-ligand complex MD simulation using GROMACS.&#xA;Now I'm running the &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/08_MD.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx grompp -f md.mdp -c npt.gro -t npt.cpt -p topol.top -n index.ndx -o md_0_10.tpr&#xA;&#xA;gmx mdrun -deffnm md_0_10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It use 10ns for md runs. The parameter is defined in it's &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/Files/md.mdp&quot; rel=&quot;nofollow noreferrer&quot;&gt;md.mdp&lt;/a&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;nsteps                  = 5000000   ; 2 * 5000000 = 10000 ps (10 ns)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;It tooks 5 days to run with 16 cores CPU.&#xA;Is it normal?&lt;/p&gt;&#xA;&lt;p&gt;Thus I seek a shorter time to execute.&#xA;What is the minimum reasonable time we can use? Is 1ns enough?&lt;/p&gt;&#xA;&lt;p&gt;-Sca&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-12-18T18:06:22.710" LastActivityDate="2021-12-18T18:06:22.710" Title="How to determine minimum reasonable MD timing for ligand-protein complex" Tags="|molecular-dynamics|high-performance-computing|gromacs|proteins|" AnswerCount="0" CommentCount="4" ClosedDate="2022-01-21T00:54:07.697" ContentLicense="CC BY-SA 4.0" />
  <row Id="8291" PostTypeId="1" AcceptedAnswerId="8302" CreationDate="2021-12-18T15:14:40.090" Score="6" ViewCount="1083" Body="&lt;p&gt;I want to calculate the overlap integral (S), I made the code, but it is only worked when I use a basis function that describe 1s and when I include 2s orbital, I start to get error.&#xA;The First Problem is solved as Tyberius said in the comments, But I still got wrong overlap integral. I noticed that the error is because that part of my equation is not like what I should get.&#xA;In details, Here what I have for example in zeta.txt.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#it is the zeta from the basis function description&#xA;    18.7311370000&#xA;    2.8253937000&#xA;    0.6401217000&#xA;    0.1612778000&#xA;    18.7311370000&#xA;    2.8253937000&#xA;    0.6401217000&#xA;    0.1612778000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My code below when I print(float(zetas[k])), I got most of the number correct but some of them are wrong, so what should be the error ?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   nb = 4&#xA;    S = np.zeros([nb,nb]) # nb is the number of basis set and I have it in the code &#xA;    print(distancess) # where distancess is an array that contains the coordinate &#xA;    # here is the shape of distancess =  [[0.0, 0.0, 0.0], [0.0, 0.0, 1.3999091131307069]]&#xA;    print(nprim) #is an array that contains the number of primitive for each basis function &#xA;    # nprim = [3, 1, 3, 1]&#xA;    with open(&amp;quot;zeta.txt&amp;quot;,&amp;quot;r&amp;quot;) as z_inp:&#xA;        with open(&amp;quot;cijk.txt&amp;quot;,&amp;quot;r&amp;quot;) as cijk_inp:&#xA;            zetas = z_inp.readlines()&#xA;            cijk = cijk_inp.readlines()&#xA;            for i in range(nb):&#xA;                for j in range(nb):&#xA;    &#xA;                    n_prim_i = nprim[i]&#xA;                    n_prim_j = nprim[j]&#xA;    &#xA;                    for k in range(n_prim_i):&#xA;                        for l in range(n_prim_j):&#xA;                           Q = distancess[atom_for_basis[i]] - &#xA;                              distancess[atom_for_basis[j]]&#xA;                           Q2 = np.dot(Q,Q)&#xA;&#xA;                           zetazeta = float(zetas[k]) + float(zetas[l])&#xA;                           print(float(zetas[k]))&#xA;                &#xA;                           zi = float(zetas[k]) * &#xA;                                float(zetas[l]) / zetazeta&#xA;                           c1c2 = float(cijk[k]) * &#xA;                           float(cijk[l])&#xA;                           gaussint = ((math.pi/zetazeta))**(3/2)&#xA;&#xA;                           prefac = math.exp(-zi*Q2)&#xA;                           S[i,j] +=  c1c2 * prefac * gaussint&#xA;    &#xA;    print(S)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output from my code for print(float(zetas[k])) is,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output that should I get for print(float(zetas[k])).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;18.731137&#xA;18.731137&#xA;18.731137&#xA;2.8253937&#xA;2.8253937&#xA;2.8253937&#xA;0.6401217&#xA;0.6401217&#xA;0.6401217&#xA;18.731137&#xA;2.8253937&#xA;0.6401217&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;0.1612778&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="142" LastEditDate="2021-12-20T03:42:30.807" LastActivityDate="2021-12-20T06:32:04.907" Title="How to compute the overlap matrix in Python" Tags="|python|hartree-fock|pyscf|integrals|fcidump|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8292" PostTypeId="2" ParentId="6999" CreationDate="2021-12-19T01:53:43.297" Score="4" Body="&lt;h2&gt;Thermodynamics&lt;/h2&gt;&#xA;&lt;p&gt;There is no problem with simulating a phase transition. There is only a problem with calculating thermodynamic averages during a phase transition.&lt;/p&gt;&#xA;&lt;p&gt;Short simple answer: I don't know anyone who has ever had a use for a property that corresponds to part one phase, part another phase. There are plenty of needs for the properties of mixed phase systems, but you need to know the pure phase properties, and mix these together, with a lever rule, essentially. One does not calculate the heat capacity of a fluid that is half liquid, half vapor. one calculates the heat capacity of a pure liquid and pure liquid, and then finds what a mixture that is 50/50 or X/(100-X) is. This is just thermodynamics, and stat mech is just microscopic thermodynamics, and simulations are just stat mech i.e., thermodynamics.&lt;/p&gt;&#xA;&lt;p&gt;If it isn't useful thermodynamically, then an ensemble average of something won't be useful(or relevant) computationally.&lt;/p&gt;&#xA;&lt;p&gt;If your simulation is at a phase boundary, your results will be strange. You will lose sleep, nothing will make sense, until you realize you aren't simulating a single phase. I know, I have done this, more than once, unfortunately.&lt;/p&gt;&#xA;&lt;p&gt;Another thing to realize (or perhaps just a different way of looking at the same problem) is you must manage your Degrees of Freedom(the following depends on a pure fluid. Refer to Gibbs phase rule for general case of multiple components) in a simulation. When you start a simulation, you must set what is constant i.e., T and P is common, but also, T and V. However, at a phase transition, you can only choose one degree of freedom. So you can't be simulating at a chosen T and P and a phase transition. That is purely unphysical.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2021-12-19T15:25:32.843" LastActivityDate="2021-12-19T15:25:32.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8293" PostTypeId="1" AcceptedAnswerId="8422" CreationDate="2021-12-19T06:09:57.497" Score="9" ViewCount="3186" Body="&lt;p&gt;I am trying to figure out the difference between vasp_std, vasp_gam, and vasp_ncl. I find some related details on the &lt;a href=&quot;https://blog.vasp.at/forum/viewtopic.php?f=2&amp;amp;t=17018&amp;amp;p=17490#p17490&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vasp forum&lt;/a&gt;, I think vasp_gam makes some customized optimization for the gamma-point only calculation. But I am not sure what the difference is between the vasp_std and vasp_ncl. It is said that vasp_ncl is for non-collinear calculations for instance to perform fully non-collinear magnetic structure calculations or to include spin-orbit interactions in the calculations.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;Is there a more detailed explanation about the difference between different versions, especially how different versions deal with the basic equations of DFT?&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I want to calculate the effect of spin-orbit interaction, do I have to use vasp_ncl instead of vaps_std?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-12-29T02:07:32.100" LastActivityDate="2021-12-30T00:22:41.187" Title="What is the detailed difference between Vasp_std and Vasp_ncl?" Tags="|density-functional-theory|vasp|software-assistance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8294" PostTypeId="1" AcceptedAnswerId="8295" CreationDate="2021-12-19T06:11:12.400" Score="5" ViewCount="627" Body="&lt;p&gt;In &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8274/the-orbital-exponent-in-gaussian&quot;&gt;this question and answers&lt;/a&gt;, I found that &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Basis Set Exchange&lt;/a&gt; provides information about the orbitals (e.g., the orbital exponents and contraction coefficients). For example, the following example is orbital data of the oxygen:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bsNnn.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bsNnn.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, I cannot understand the details about these values and meanings; specifically I have three questions as follows.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;I understood that first 6 lines show 6 orbital exponent values and 6 contraction coefficient values in 6-31; however, each line of next 3 and 1 parts has &amp;quot;one&amp;quot; orbital exponent value and &amp;quot;two&amp;quot; contraction coefficient values. Why does one orbital have two coefficients?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I believe that the oxygen orbital has 4 kinds of orbitals (i.e., 2s, 2px, 2py, and 2pz), but I cannot understand which value corresponds to 2s and which value corresponds to 2px.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Postscript using a concrete example.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;1. They are Pople-type basis set. Namely, s and p have the same exponents but different contraction coefficients. Hence, one set of exponents, two sets of coefficients. (Maybe format Gaussian somehow looks clearer) 2. Px/Py/Pz have the same coef and exp.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you for this comment from Lancashire3000. I add the following example for describing my confusing. I believe that &amp;quot;31&amp;quot; of 2px in the 6-31G basis set can be written (but omit the spherical harmonics) as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\phi_{2px} = \sum_{i=1}^3 d_i \exp(-\zeta_i r^2) + d_4 \exp(-\zeta_4 r^2)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, if px, py, pz have the same exp and coef, totally we have four exponents, &lt;span class=&quot;math-container&quot;&gt;$\zeta_1, \zeta_2, \zeta_3, \zeta_4$&lt;/span&gt;, and four coefficients, &lt;span class=&quot;math-container&quot;&gt;$d_1, d_2, d_3, d_4$&lt;/span&gt;. But the Basis Set Exchange file provides two contraction coefficients in each one; **that is, we seem to have &lt;span class=&quot;math-container&quot;&gt;$d_1, d'_1, d_2, d'_2, d_3, d'_3, d_4, d'_4$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; is for the s orbital and &lt;span class=&quot;math-container&quot;&gt;$d'$&lt;/span&gt; is for the px, py, pz orbitals?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2021-12-20T07:52:12.843" LastActivityDate="2021-12-21T02:38:57.380" Title="The format and values provided by Basis Set Exchange" Tags="|quantum-chemistry|electronic-structure|gaussian|basis-sets|databases|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8295" PostTypeId="2" ParentId="8294" CreationDate="2021-12-19T07:23:19.907" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I understood that first 6 lines show 6 orbital exponent values and 6 contraction coefficient values in 6-31; however, each line of next 3 and 1 parts has &amp;quot;one&amp;quot; orbital exponent value and &amp;quot;two&amp;quot; contraction coefficient values. Why does one orbital have two coefficients?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When it becomes confusing to figure out what's going on in a basis set, I find it useful to look at the same basis set in other formats.&lt;/p&gt;&#xA;&lt;p&gt;The CFOUR / ACESII / MRCC format for that same basis set looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O:6-31G(d,p)&#xA;6-31G + polarization on all atoms&#xA;&#xA;  3&#xA;    0    1    2&#xA;    3    2    1&#xA;   10    4    1&#xA;&#xA;0.5484671660D+04 0.8252349460D+03 0.1880469580D+03 0.5296450000D+02 0.1689757040D+02 &#xA;0.1553961625D+02 0.5799635340D+01 0.3599933586D+01 0.1013761750D+01 0.2700058226D+00 &#xA;&#xA;0.1831074430D-02  0.0000000000D+00 0.00000000 &#xA;0.1395017220D-01  0.0000000000D+00 0.00000000 &#xA;0.6844507810D-01  0.0000000000D+00 0.00000000 &#xA;0.2327143360D+00  0.0000000000D+00 0.00000000 &#xA;0.4701928980D+00  0.0000000000D+00 0.00000000 &#xA;0.0000000000D+00 -0.1107775495D+00 0.00000000 &#xA;0.3585208530D+00  0.0000000000D+00 0.00000000 &#xA;0.0000000000D+00 -0.1480262627D+00 0.00000000 &#xA;0.0000000000D+00  0.1130767015D+01 0.00000000 &#xA;0.0000000000D+00  0.0000000000D+00 0.1000000000D+01 &#xA;&#xA;0.1553961625D+02 0.3599933586D+01 0.1013761750D+01 0.2700058226D+00 &#xA;&#xA;0.7087426823D-01 0.00000000 &#xA;0.3397528391D+00 0.00000000 &#xA;0.7271585773D+00 0.00000000 &#xA;0.0000000000D+00 0.1000000000D+01 &#xA;&#xA;0.8000000000D+00 &#xA;&#xA;1.0000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can see here that all four of the P-type functions have the same exponents as the L-type functions in your version, and both versions show &lt;em&gt;&lt;strong&gt;two&lt;/strong&gt;&lt;/em&gt; &amp;quot;contraction coefficients&amp;quot; for each of these exponents, but in my version one contraction coefficient for each of these exponents is always zero, meaning that there's only ever one non-zero contraction coefficient for each exponent here.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I believe that the oxygen orbital has 4 kinds of orbitals (i.e., 2s, 2px, 2py, and 2pz), but I cannot understand which value corresponds to 2s and which value corresponds to 2px.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Notice that the &lt;em&gt;&lt;strong&gt;first&lt;/strong&gt;&lt;/em&gt; column says &amp;quot;S&amp;quot;, &amp;quot;L&amp;quot;, and &amp;quot;D&amp;quot;. The &amp;quot;L&amp;quot; in your case represents &amp;quot;SP&amp;quot; which just means that there's an S-type function with the given parameters, &lt;em&gt;&lt;strong&gt;and&lt;/strong&gt;&lt;/em&gt; a P-type function with the same parameters. In my version of the basis set, I've explained how to find the S-type and P-type functions in my answer to your recent post here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8274/5&quot;&gt;The orbital exponent in Gaussian&lt;/a&gt;. Examine the following part:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0    1    2&#xA;    3    2    1&#xA;   10    4    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This means that:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For S-type functions (L=0), we have 10 exponents and 3 contractions.&lt;/li&gt;&#xA;&lt;li&gt;For P-type functions (L=1), we have 4 exponents and 2 contractions, and&lt;/li&gt;&#xA;&lt;li&gt;For D-type functions (L=2), we have 1 exponent and 1 contraction.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You are then given the S-type exponents followed by the S-type contraction coefficients then the P-type exponents (&lt;code&gt;0.1553961625D+02 0.3599933586D+01 0.1013761750D+01 0.2700058226D+00&lt;/code&gt;) followed by their contraction coefficients, etc. You can then match these four P-type exponents and their corresponding contraction coefficients with the ones in your version of the basis set.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-20T09:19:17.690" LastActivityDate="2021-12-20T09:19:17.690" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8296" PostTypeId="1" AcceptedAnswerId="8323" CreationDate="2021-12-19T08:09:10.113" Score="6" ViewCount="258" Body="&lt;p&gt;I am trying to figure out why the DOSCAR file during structure relation is useless, for the last step of structure, the atoms' positions are almost fixed, is that the same as a static calculation?&#xA;But according to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/DOSCAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP wiki&lt;/a&gt;, after structure relaxation, I have to do the static calculation one more time. Why is that?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For relaxations, the DOSCAR is usually useless. If you want to get an accurate DOS for the final configuration, first copy CONTCAR to POSCAR and continue with one static (ISTART=1; NSW=0) calculation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="671" LastEditDate="2021-12-19T17:03:24.630" LastActivityDate="2021-12-22T13:09:35.257" Title="DOSCAR file during structure relaxation is useless?" Tags="|density-functional-theory|vasp|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8297" PostTypeId="2" ParentId="6999" CreationDate="2021-12-19T09:34:57.823" Score="6" Body="&lt;p&gt;Off the top of my head, I can think of two reasons to be concerned about simulations near a phase transition, although I'm only really well-qualified to talk about one of them in detail.&lt;/p&gt;&#xA;&lt;p&gt;The one I know less about is &lt;strong&gt;finite size effects&lt;/strong&gt;. There are many cases where the limited size of the system prevents it from behaving as it would at the thermodynamic limit. My recollection is that phase transitions are one of these, but better to hear from someone who remembers the details. I expect this is actually what A&amp;amp;T were thinking about in this context.&lt;/p&gt;&#xA;&lt;p&gt;The one I know more about is &lt;strong&gt;time scale limitations&lt;/strong&gt;. Quite simply, a phase change is frequently an example of a &lt;em&gt;rare event&lt;/em&gt; -- that is to say, it takes a long time for it to spontaneously occur. So ergodic sampling is impossible because there is a kinetic barrier large enough that kinetic trapping keeps you stuck on the &amp;quot;wrong&amp;quot; side for longer than simulations can explore.&lt;/p&gt;&#xA;&lt;p&gt;This may seem surprising, but in many cases, a &amp;quot;long time&amp;quot; here can even be long on human timescales. Some standard examples are superheating, supercooling, and supersaturation. (Search YouTube for &amp;quot;sodium acetate supersaturation&amp;quot; for some nice videos; &lt;a href=&quot;https://www.youtube.com/watch?v=nrmQBdYp5tU&quot; rel=&quot;noreferrer&quot;&gt;here's one&lt;/a&gt;). We can experimentally create metastable states on a multi-mole size scale and multi-second (or hour!) time scale, where the more thermodynamically stable state is only found upon perturbation. The experimental physics shows that these transitions don't spontaneously occur on human-relevant time scales, so what chance would MD have to sample ergodically?&lt;/p&gt;&#xA;&lt;p&gt;Note that many simulations you'll find of &amp;quot;melting&amp;quot; or whatnot are done at temperatures far from the equilibrium conditions. It's one thing to study the phase equilibrium of ice and water at 0°C, it's another to say, &amp;quot;look, my ice melts if I simulate it at 75°C!&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-12-19T09:34:57.823" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8298" PostTypeId="1" AcceptedAnswerId="8335" CreationDate="2021-12-19T18:03:18.997" Score="6" ViewCount="326" Body="&lt;p&gt;I am trying to compare the band structure of a slab and the bulk phase, just like the example on the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Ni_100_surface_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP wiki&lt;/a&gt;. In the example of VASP, it calculates the band structure of the slab of Ni metal.&lt;br&gt;&#xA;A slab is basically a crystal that has a new kind of symmetry, but the example doesn't generate K-points from the slab, it uses the K points extracted from the Brillouin zone of the bulk primitive cell. I am not sure if this is appropriate.&lt;BR&gt;&#xA;And I should follow the way in the example, why should I choose K points from the one facet of the Brillouin Zone of bulk phase?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Pvxza.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Pvxza.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2021-12-19T21:00:11.227" LastActivityDate="2021-12-24T11:43:45.007" Title="How to determine the right k-points for the band structure of a slab?" Tags="|density-functional-theory|vasp|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8299" PostTypeId="1" CreationDate="2021-12-19T18:25:10.273" Score="8" ViewCount="1494" Body="&lt;p&gt;I searched in the &lt;a href=&quot;http://www.wannier.org/support/&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials in WANNIER90&lt;/a&gt; and example 18 says that the calculation of the Berry curvature requires the &amp;quot;recent version of the &lt;code&gt;pw2wannier90&lt;/code&gt; interface&amp;quot;. In other words, it requires the interface between Quantum ESPRESSO and WANNIER90.&lt;/p&gt;&#xA;&lt;p&gt;Would anyone please tell me whether the interface between VASP and WANNIER90 can also calculate the Berry curvature or not? I mean plotting the Berry curvature along the high-symmetry k-points, same as those in the band structure.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="7" LastEditDate="2022-01-24T14:46:16.053" LastActivityDate="2022-02-06T00:01:45.867" Title="Berry Curvature with VASP+WANNIER90" Tags="|vasp|berry-phase|wannier90|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8300" PostTypeId="1" CreationDate="2021-12-19T21:31:15.080" Score="5" ViewCount="325" Body="&lt;p&gt;Let suppose the we have a &amp;quot;big&amp;quot; system. By &amp;quot;big&amp;quot; I mean a system that have a certain number of atoms that the software is not capable to treat with the default initial parameters.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: Is there a recommended way to proceed in order to get the geometry optimized (or the self-consistence field calculation completed) with production parameters?&lt;/strong&gt;&lt;br /&gt;&#xA;(By &lt;em&gt;production parameters&lt;/em&gt; I mean good for scientific conclusions)&lt;/p&gt;&#xA;&lt;p&gt;Some possible examples of actions that came to my mind:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;increase the geometry steps number (straightforward but not always optimal);&lt;/li&gt;&#xA;&lt;li&gt;increase the number of self-consistence field steps (straightforward but not always optimal);&lt;/li&gt;&#xA;&lt;li&gt;decrease the accuracy and after getting and optimized geometry, increase the accuracy;&lt;/li&gt;&#xA;&lt;li&gt;start with a low level basis set, use the optimized geometry as input with a higher basis set;&lt;/li&gt;&#xA;&lt;li&gt;use a simple method (like molecular mechanics) to optimize the geometry, then move to the desired method;&lt;/li&gt;&#xA;&lt;li&gt;etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-20T18:09:51.610" Title="Which is the recommended way to optimize &quot;big&quot; systems?" Tags="|geometry-optimization|self-consistent-field|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8301" PostTypeId="2" ParentId="1719" CreationDate="2021-12-20T00:47:01.163" Score="5" Body="&lt;p&gt;If this is happening, I think there's a few reasons: &lt;/p&gt;&#xA;&lt;p&gt;Quantum physics in general is the science subject where the most precise agreement between theory and experiment exists. For example, the experimental work: &lt;a href=&quot;https://www.nature.com/articles/s41586-020-2964-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;&lt;strong&gt;Nature&lt;/strong&gt;&lt;/em&gt; 588, pg 61–65 (2020) &amp;quot;Determination of the fine-structure constant with an &lt;strong&gt;accuracy of 81 parts per trillion&lt;/strong&gt;&amp;quot;&lt;/a&gt;, and a QED calculation involving 12672 10th order Feynman diagrams agree in the &amp;quot;part per 10 billion&amp;quot; digit for the reciprocal of the fine structure constant :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1/137.0359992 [experiment, up to 10 significant digits]&#xA;1/137.0359992 [QED, up to 10 significant digits]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Even for actual matter modeling, we have had similar success, see: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/554/5&quot;&gt;How accurate are the most accurate calculations?&lt;/a&gt;. Solid-state condensed matter is more complicated since more atoms and molecules are involved, but we are still able to quite precisely predict phase transitions, conductivity, and with BCS theory, even &lt;em&gt;&lt;strong&gt;super&lt;/strong&gt;&lt;/em&gt;conductivity properties, often within the limits of what experimentalists can do, or to what practically matters. The editors of physics journals, and the people from the physics community that will be asked to referee papers, will largely come from physics departments, which at least until very recently had far more people from the &amp;quot;old-school&amp;quot; physics tradition (&amp;quot;biophysics&amp;quot; is a relatively new term) and &lt;em&gt;&lt;strong&gt;will be used to trusting calculations&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Biology is on average much less quantitative. Some areas can be extremely quantitative, but the vast majority of a biology department will be wet lab experimentalists who did not learn math or computer programming beyond their first year calculus class, rather than bioinformatics (another relatively new term) researchers. &lt;em&gt;Most biologists are used to being around people who don't have the same level of appreciation for the fact that things like&lt;/em&gt; &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\hat{H} | \psi_n(t) \rangle = i \hbar \frac{\partial}{\partial t} | \psi_n(t) \rangle$&lt;/span&gt;&amp;quot; &lt;em&gt;can sometimes actually predict physical quantities with more accuracy than the best experiments (something that is often proven to be correct many years or decades later).&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Biology by definition is about living things, and life is a complicated thing (even the &lt;em&gt;&lt;strong&gt;components&lt;/strong&gt;&lt;/em&gt; of life, which you're studying in a structural biology simulation). It's far easier thermodynamically, for atoms and molecules to randomly come together and form a solid-state material that can be studied by typical condensed matter physicists, than for randomness to result in a non-living protein that can be studied by typical structural biologists. In that sense, &lt;strong&gt;biologists are a lot less lucky,&lt;/strong&gt; in that they are not dealing with quantities for which we can calculate the values &lt;em&gt;ab initio&lt;/em&gt; with such exquisite accuracy: I often say &amp;quot;climate change (like biology) is complicated because we don't have the Schroedinger equation for tomorrow's weather&amp;quot; and I also happened to see this quote at the end of a &lt;a href=&quot;https://youtu.be/Mg-hst8igEo?t=329&quot; rel=&quot;nofollow noreferrer&quot;&gt;youtube video&lt;/a&gt; this morning:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I can calculate the motion of heavenly bodies but not the madness of&#xA;people.&amp;quot; ~ Isaac Newton&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I can also calculate the conductivity of a material, but not how a protein folds.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-21T19:34:47.407" LastActivityDate="2021-12-21T19:34:47.407" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8302" PostTypeId="2" ParentId="8291" CreationDate="2021-12-20T05:29:08.773" Score="3" Body="&lt;p&gt;Here is an updated version of your code that I believe now works. I had to add in a few of the values that were computed elsewhere in your code, but otherwise it is mostly the same.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;nb = 4&#xA;S = np.zeros([nb,nb]) # nb is the number of basis set and I have it in the code&#xA;distancess=np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 1.4]])&#xA;#is an array that contains the number of primitive for each basis function&#xA;nprim = [3, 1, 3, 1]&#xA;atom_for_basis=[0,0,1,1]&#xA;&#xA;zetas = 2*[18.7311370000,2.8253937000,0.6401217000,0.1612778000]&#xA;cijk = 2*[0.0334946434,.2347269535,0.8137573261,1.00000000]&#xA;norms= 2*[6.4170171 , 1.55317145, 0.51004325,0.18138065]&#xA;&#xA;current_i=0&#xA;for i in range(nb):&#xA;    n_prim_i = nprim[i]&#xA;    current_j=0&#xA;    for j in range(nb):&#xA;        n_prim_j = nprim[j]&#xA;&#xA;        for k in range(current_i,current_i+n_prim_i):&#xA;            for l in range(current_j,current_j+n_prim_j):&#xA;               Q = distancess[atom_for_basis[i]] - distancess[atom_for_basis[j]]&#xA;               Q2 = np.dot(Q,Q)&#xA;&#xA;               zetazeta = float(zetas[k]) + float(zetas[l])&#xA;&#xA;               zi = float(zetas[k]) * float(zetas[l]) / zetazeta&#xA;               c1c2 = float(cijk[k]) * float(cijk[l])&#xA;               gaussint = ((np.pi/zetazeta))**(3/2)&#xA;&#xA;&#xA;               prefac = np.exp(-zi*Q2)&#xA;               S[i,j] +=  c1c2 * prefac * gaussint*norms[k]*norms[l]&#xA;        current_j+=n_prim_j&#xA;    current_i+=n_prim_i&#xA;print(S)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So what still needed fixing?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Your loops over &lt;code&gt;k&lt;/code&gt; and &lt;code&gt;l&lt;/code&gt; always started at zero for every iteration, meaning you never got past the first three basis functions when accessing &lt;code&gt;zeta&lt;/code&gt; and &lt;code&gt;cijk&lt;/code&gt;. I added &lt;code&gt;current_i&lt;/code&gt; and &lt;code&gt;current_j&lt;/code&gt; to keep track of how far you had already travelled through these arrays. Having the loops include these variables and incrementing at the end of each &lt;code&gt;i&lt;/code&gt; and &lt;code&gt;j&lt;/code&gt; loop, it will now go through all of &lt;code&gt;zeta&lt;/code&gt; and &lt;code&gt;cijk&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You need to normalize the integrals or each of the individual basis functions (I discuss this for a &lt;a href=&quot;https://chemistry.stackexchange.com/questions/108223/overlap-matrix-h2-molecule-sto-3g/108254#108254&quot;&gt;similar question&lt;/a&gt; on Chem SE). Here, I explicitly included values to normalize each function, but you will need to add code to do this in general. For an s-type function, the normalization formula is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}N=\bigg(\frac{2\zeta}{\pi}\bigg)^{3/4}$$&lt;/span&gt;&#xA;The normalization will be different for higher angular momentum functions (p, d, f, etc).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2021-12-20T06:32:04.907" LastActivityDate="2021-12-20T06:32:04.907" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8303" PostTypeId="1" AcceptedAnswerId="8304" CreationDate="2021-12-20T08:52:19.860" Score="6" ViewCount="1528" Body="&lt;p&gt;GROMACS version: gmx, version 2021.4&#xA;GROMACS modification: No&lt;/p&gt;&#xA;&lt;p&gt;I'm following the &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/index.html&quot; rel=&quot;noreferrer&quot;&gt;Protein-Ligand Complex tutorial&lt;/a&gt;.&#xA;I'd like to visualize the binding using &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;noreferrer&quot;&gt;VMD&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I use the output from &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/08_MD.html&quot; rel=&quot;noreferrer&quot;&gt;these commands&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx grompp -f md.mdp -c npt.gro -t npt.cpt -p topol.top -n index.ndx -o md_0_10.tpr&#xA;&#xA;gmx mdrun -deffnm md_0_10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Especially these two files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;md_0_10.gro&#xA;md_0_10.xtc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And with this VMD setting:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/35DwYl.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/35DwYl.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;At best I can get is only the receptor (protein) but not the ligand bound to it.&#xA;This is done by assigning &amp;quot;protein&amp;quot; to Selected Atoms form in Graphical Representation dialog box.&#xA;I can't see anything where I can include ligand.&lt;/p&gt;&#xA;&lt;p&gt;How can I also show ligand in the binding?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/244jll.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/244jll.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-12-20T09:14:53.817" LastActivityDate="2021-12-20T12:30:19.253" Title="How to visualize protein-ligand complex MD run using VMD" Tags="|molecular-dynamics|gromacs|visualization-software|vmd|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8304" PostTypeId="2" ParentId="8303" CreationDate="2021-12-20T12:30:19.253" Score="7" Body="&lt;p&gt;First, You need to click on &lt;strong&gt;Create Rep&lt;/strong&gt; and you will get a new line in the box below as the picture attached (with the same name &amp;quot;protein&amp;quot; in your case).&lt;/p&gt;&#xA;&lt;p&gt;To show the ligand, you should know the name of your ligand, to ensure about your ligand name, you can choose in the keyword &amp;quot;resname&amp;quot; and all the resname will appear in the value box. Or you can see the number of residue of your ligand , if you have the pdb file, you can know the number of the residue easily&lt;/p&gt;&#xA;&lt;p&gt;Then select one of the two line in the box under Create Rep and start to write the name of your ligand in selected atom section Like this  &lt;strong&gt;resname LIG&lt;/strong&gt; or this &lt;strong&gt;resid 41&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Last thing, you can change the draw style of your ligand, so you can see clearly and observe if there is binding or reaction etc&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QqkPF.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QqkPF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KCtYb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KCtYb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2021-12-20T12:30:19.253" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8305" PostTypeId="2" ParentId="8294" CreationDate="2021-12-20T15:32:35.683" Score="5" Body="&lt;p&gt;&lt;code&gt;L&lt;/code&gt; is the name Pople used for this type of shell, but I like how the Gaussian format labels these functions (&lt;code&gt;SP&lt;/code&gt;) as it makes it more explicit what is being described. Your overall description of the (GAMESS?) basis format is correct, but this use of two contraction coefficients is almost exclusively seen in the older Pople (x-yzG) and STO-nG basis sets.&lt;/p&gt;&#xA;&lt;p&gt;In the original STO-nG paper&lt;sup&gt;[1]&lt;/sup&gt;, they decided that rather than using a separate set of exponents for the 2s and 2p orbitals, they would use a single exponent for each of them. Even more so than today, calculation speed was highly valued at the time this basis set was made. By creating this &lt;code&gt;L&lt;/code&gt; shell, integral (particularly two-electron integral) evaluations could done more quickly with more reuse of intermediates. As an example that they give in the paper, if you have a two electron integral involving four &lt;code&gt;P&lt;/code&gt; functions, you can reuse the same exponential and error function intermediates to compute &lt;span class=&quot;math-container&quot;&gt;$3^4=81$&lt;/span&gt; different integrals (same intermediates for &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt;). If you have integrals involving 4 &lt;code&gt;L&lt;/code&gt; functions, these intermediates can be reused for &lt;span class=&quot;math-container&quot;&gt;$4^4=256$&lt;/span&gt; different integrals.&lt;/p&gt;&#xA;&lt;p&gt;Overall they found that the time per integral for small molecules was roughly half when using these &lt;code&gt;L&lt;/code&gt; functions compared to having separate &lt;code&gt;S&lt;/code&gt; and &lt;code&gt;P&lt;/code&gt; exponents. The downside to using the same exponents for &lt;code&gt;S&lt;/code&gt; and &lt;code&gt;P&lt;/code&gt; functions is that it makes the basis less flexible. Combine this with the relatively minor speedup by today's standards and you can see why this practice fell out of favor.&lt;/p&gt;&#xA;&lt;p&gt;So this specification for &lt;code&gt;L&lt;/code&gt; tells you the exponents used for 2s &lt;em&gt;and&lt;/em&gt; 2p (x/y/z) in the first column and then the next two columns give the separate contraction coefficients for the 2s and 2p respectively. You likely won't see this three column format outside of the Pople and STO-nG basis sets because more modern basis sets have found different ways to speed up integral evaluation without combining primitive exponents.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Hehre, W. J.; Stewart, R. F.; Pople, J. A. Self‐Consistent Molecular‐Orbital Methods. I. Use of Gaussian Expansions of Slater‐Type Atomic Orbitals. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;1969,&lt;/strong&gt; &lt;em&gt;51&lt;/em&gt; (6), 2657–2664. &lt;a href=&quot;https://doi.org/10.1063/1.1672392&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1063/1.1672392&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2021-12-21T02:38:57.380" LastActivityDate="2021-12-21T02:38:57.380" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8306" PostTypeId="2" ParentId="8300" CreationDate="2021-12-20T18:09:51.610" Score="9" Body="&lt;h2&gt;Suggestions for Molecular-Like Systems (not periodic unit cells)&lt;/h2&gt;&#xA;&lt;p&gt;I'll make some general suggestions for molecular / isolated systems, not crystals. (In the case of periodic systems, some methods aren't available or are different.)&lt;/p&gt;&#xA;&lt;p&gt;You mentioned increasing the number of self-consistent steps. If your SCF calculation doesn't converge, there are a variety of separate questions / methods to try.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The main problem is that getting to a final equilibrium geometry with a DFT or high-level wavefunction method can be slow. For larger systems, there are many degrees of freedom and often the potential energy surface is fairly flat, especially with dihedral angles.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So the goal is to get &lt;em&gt;close&lt;/em&gt; to a converged geometry with a faster method, then to switch eventually to your method of choice.&lt;/p&gt;&#xA;&lt;p&gt;Years ago, the advice would be to use a force field to &amp;quot;pre-optimize&amp;quot; a system, since these are intended to get quality geometries. I no longer advise this unless you have a specialized force field (e.g., biomolecule force fields work well for biomolecules).&lt;/p&gt;&#xA;&lt;p&gt;In particular in two benchmark papers, we found that force field methods weren't very good:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;A sobering assessment of small-molecule force field methods for low energy conformer predictions&amp;quot; &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.25512&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Int. J. Quantum Chem.&lt;/em&gt; &lt;strong&gt;2018&lt;/strong&gt; 118 e25512&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;Assessing conformer energies using electronic structure and machine learning methods&amp;quot; &lt;a href=&quot;https://doi.org/10.1002/qua.26381&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;Int. J. Quantum Chem.&lt;/em&gt; &lt;strong&gt;2021&lt;/strong&gt; 121 e26381&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;We found that the MMFF94-optimized geometries had large forces when you switched to semiempirical or DFT methods. We also found that when ranking different conformer poses by energy, the force field had poor correlation with &lt;em&gt;ab initio&lt;/em&gt; methods.&lt;/p&gt;&#xA;&lt;p&gt;Instead, we find much better results with the approximate GFN2 / xtb method, or if possible with methods like ANI-2x, with the caveat that GFN2 works for all elements.&lt;/p&gt;&#xA;&lt;p&gt;Our most recent workflow is something like this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Generate an initial geometry (e.g. in Avogadro, RDKit, etc.)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimize the geometry using &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;noreferrer&quot;&gt;xtb&lt;/a&gt; which is fast and often &amp;quot;forgiving&amp;quot; (e.g., easier to converge SCF).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimize the geometry using B97-3c or similar GGA method (e.g. r&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;SCAN-3c looks good too)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimize the geometry in your favorite method with dispersion correction (e.g., &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D4 or &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97M-V for example, triple-zeta basis set).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If step 4 still takes a long time or fails to converge, we'll often optimize with def2-SVP first (often with looser convergence criteria) and then switch to the larger basis set.&lt;/p&gt;&#xA;&lt;p&gt;It's a process - in part because getting the electrostatic and non-covalent interactions right is hard. Some ML-based methods may help with this in the future, but beyond ANI, they are not widely available.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-20T18:09:51.610" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8307" PostTypeId="1" AcceptedAnswerId="8442" CreationDate="2021-12-20T22:55:51.540" Score="6" ViewCount="439" Body="&lt;p&gt;This question is simply:&#xA;How can we use DFT in the field of electrochemistry?&lt;/p&gt;&#xA;&lt;p&gt;What are the best resources (Books, reviews, papers, software ...) to learn about using DFT in electrochemistry? Specifically the electrochemistry of molecules.&lt;/p&gt;&#xA;&lt;p&gt;I want to ask this open ended and broad question so that we can use this question as a space to express our thoughts on the field. I will have to start looking next year into DFT techniques to simulate electrochemical properties and I might post an answer myself when I'm ready.&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="5" LastEditDate="2021-12-28T00:21:57.747" LastActivityDate="2021-12-30T18:25:50.020" Title="How can I get started on DFT?" Tags="|density-functional-theory|reference-request|quantum-chemistry|ab-initio-calculations|electronic-structure|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8308" PostTypeId="1" AcceptedAnswerId="8437" CreationDate="2021-12-21T03:13:44.383" Score="10" ViewCount="1204" Body="&lt;p&gt;I am running a VMD renderer to view my &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8303/how-to-visualize-protein-ligand-complex-md-run-using-vmd&quot;&gt;GROMACS molecular dynamics output&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;At one frame, the geometry looks fairly normal like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/E95LWl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/E95LWl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;At another frame, it displays a distorted geometry, with the receptor stretched out&#xA;like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9twbal.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9twbal.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is this common? Is it a biophysical effect of the MD system?&#xA;Or is it a bug during my MD simulation steps?&lt;/p&gt;&#xA;&lt;p&gt;If this is a problem in my processing, how can I resolve that?&#xA;Or is there any setting in VMD where I can fix that?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="7" LastEditDate="2021-12-21T18:09:09.417" LastActivityDate="2021-12-30T05:49:10.943" Title="Molecular dynamics frame distorted by VMD?" Tags="|molecular-dynamics|gromacs|vmd|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8309" PostTypeId="1" AcceptedAnswerId="8313" CreationDate="2021-12-21T04:06:21.753" Score="7" ViewCount="510" Body="&lt;p&gt;I keep getting this error with Siesta every time I do a calculation,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Program aborted. Backtrace:&#xA;Semicore shell(s) with -1 electrons included in the valence for&#xA;Al&#xA;Semicore shell(s) with  1 electrons included in the valence for&#xA;As&#xA;Al                   must be in PAO.Basis (it has semicore states)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm pretty sure I'm including them properly, I have a structure with Al As and C, the C works fine, but I'm unsure why the others aren't working well.&lt;/p&gt;&#xA;&lt;p&gt;I've tried using B instead of Al and I get the same error.&lt;/p&gt;&#xA;&lt;p&gt;Pseudopotentials are the ones from here&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/periodictable-gga-abinit.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/periodictable-gga-abinit.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4287" LastEditorUserId="671" LastEditDate="2021-12-21T15:01:54.197" LastActivityDate="2022-09-07T13:15:04.710" Title="SIESTA error: must be in PAO.Basis, (it has semicore states)" Tags="|density-functional-theory|siesta|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8310" PostTypeId="1" CreationDate="2021-12-21T07:52:47.013" Score="8" ViewCount="580" Body="&lt;p&gt;I am now preparing a ligand topology following &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/02_topology.html&quot; rel=&quot;noreferrer&quot;&gt;GROMACS protein-ligand tutorial&lt;/a&gt;.&#xA;However, I have a large ligand (446 atoms).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ wc -l my_ligand.pdb&#xA;446 my_ligand.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I tried to upload &lt;code&gt;my_ligand_fix.mol2&lt;/code&gt; to &lt;a href=&quot;https://cgenff.umaryland.edu&quot; rel=&quot;noreferrer&quot;&gt;CGenFF server&lt;/a&gt;, I noticed it the maximum number of atoms allowable is 384.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8VEGe.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8VEGe.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that &lt;code&gt;my_ligand_fix.mol2&lt;/code&gt; has gone through processing right up to &lt;code&gt;sort_mol2_bonds.pl&lt;/code&gt; output.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to get around this?&#xA;Or what other alternative to CGenFF that I can use instead?&lt;/p&gt;&#xA;&lt;p&gt;-Sca&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-12-28T00:22:57.860" LastActivityDate="2021-12-28T00:22:57.860" Title="Alternative to CGenFF for generating large ligand topology" Tags="|molecular-dynamics|gromacs|proteins|forcefields|charmm|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8311" PostTypeId="2" ParentId="8308" CreationDate="2021-12-21T10:18:56.877" Score="10" Body="&lt;p&gt;Don't Worry, it is not a problem, This happened because you used PBC (Periodic boundary condition) and VMD sometimes has bugs during the visualization in this case. The most important to you to see that the protein wasn't broken through all frames.&lt;/p&gt;&#xA;&lt;p&gt;You can solve this problem by using this command &lt;strong&gt;pbc unwrap -sel &amp;quot;protein&amp;quot;&lt;/strong&gt; inside the Tk console as in the picture attached.&#xA;Due to the PBC, the protein may have moved out of your box, so this command just ensure that the protein is in the box (by removing the frame). This will be usefull for you if you are going to do RMSD or center of mass etc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5FO16.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5FO16.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="5" LastEditDate="2021-12-21T23:57:41.570" LastActivityDate="2021-12-21T23:57:41.570" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8312" PostTypeId="1" AcceptedAnswerId="8587" CreationDate="2021-12-21T11:13:20.550" Score="7" ViewCount="985" Body="&lt;p&gt;I have used the finite displacements method for phonon spectrum calculation, and when I typed the command to create force sets:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy -f disp-{001..024}/vasprun.xml&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I have got this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        _&#xA;  _ __ | |__   ___  _ __   ___   _ __  _   _&#xA; | '_ \| '_ \ / _ \| '_ \ / _ \ | '_ \| | | |&#xA; | |_) | | | | (_) | | | | (_) || |_) | |_| |&#xA; | .__/|_| |_|\___/|_| |_|\___(_) .__/ \__, |&#xA; |_|                            |_|    |___/&#xA;                                       2.7.1&#xA;&#xA;Python version 3.8.3&#xA;Spglib version 1.16.0&#xA;&#xA;Displacements were read from &amp;quot;phonopy_disp.yaml&amp;quot;.&#xA;counter (file index): 1 2 3 4 5 6 7 Traceback (most recent call last):&#xA;  File &amp;quot;/home/ouettar/.local/bin/phonopy&amp;quot;, line 43, in &amp;lt;module&amp;gt;&#xA;    main(**argparse_control)&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/cui/phonopy_script.py&amp;quot;, line 1553, in main&#xA;    create_FORCE_SETS_from_settings(settings, symprec, log_level)&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/cui/phonopy_script.py&amp;quot;, line 438, in create_FORCE_SETS_from_settings&#xA;    create_FORCE_SETS(&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/cui/create_force_sets.py&amp;quot;, line 115, in create_FORCE_SETS&#xA;    force_sets = get_force_sets(interface_mode,&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/calculator.py&amp;quot;, line 586, in get_force_sets&#xA;    force_sets = parse_set_of_forces(num_atoms,&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/vasp.py&amp;quot;, line 69, in parse_set_of_forces&#xA;    forces = vasprun.read_forces()&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/vasp.py&amp;quot;, line 501, in read_forces&#xA;    return self._parse_expat_vasprun_xml()&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/vasp.py&amp;quot;, line 597, in _parse_expat_vasprun_xml&#xA;    return self._parse_by_expat(self._fileptr)&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/vasp.py&amp;quot;, line 602, in _parse_by_expat&#xA;    vasprun.parse()&#xA;  File &amp;quot;/home/ouettar/.local/lib/python3.8/site-packages/phonopy/interface/vasp.py&amp;quot;, line 712, in parse&#xA;    self._p.ParseFile(self._fileptr)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you have any idea how to fix this error?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-01-21T02:29:20.757" Title="How to solve this Phonopy-related problem?" Tags="|vasp|python|phonons|phonopy|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8313" PostTypeId="2" ParentId="8309" CreationDate="2021-12-21T14:56:22.690" Score="4" Body="&lt;p&gt;Before I try and answer your specific query, the first thing I would do is to get my Pseudopotentials from :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://nninc.cnf.cornell.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://nninc.cnf.cornell.edu/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Pseudos here are utilized a bit more and better tested. It is also what SIESTA developers recommend here :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://departments.icmab.es/leem/siesta/Pseudopotentials/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://departments.icmab.es/leem/siesta/Pseudopotentials/index.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Testing out your Pseudos should be an important step. Of course let's try and make the calculations work first !&lt;/p&gt;&#xA;&lt;p&gt;Now, for your specific question, it would help if you could share your input (.fdf) file if possible since I think what is happening is that a Pseudo is either not well defined or that there is contradictory information in the basis set versus the Pseudos. Here is a thread of a similar issue in the SIESTA mail archive :&#xA;&lt;a href=&quot;https://www.mail-archive.com/siesta-l@uam.es/msg03437.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.mail-archive.com/siesta-l@uam.es/msg03437.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I could elaborate the answer with a bit more information on your part.&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2021-12-21T14:56:22.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8314" PostTypeId="2" ParentId="7234" CreationDate="2021-12-21T15:34:09.840" Score="7" Body="&lt;p&gt;Your best bet is to keep the molecule (e.g., as a &lt;code&gt;.mol&lt;/code&gt; or &lt;code&gt;.sdf&lt;/code&gt; file) around and then simply update the coordinates from the &lt;code&gt;.xyz&lt;/code&gt; file as you wish.&lt;/p&gt;&#xA;&lt;p&gt;As you mention, reading bond orders from XYZ is imperfect - the file simply doesn't contain them and you have to guess. There is no perfect way to do that. Even a highly accurate algorithm for bond order perception .. maybe 97% is still going to make 3% errors.&lt;/p&gt;&#xA;&lt;p&gt;So rather than attempting to reconstruct the topology, keep it and update the coordinates from the geometry optimization. No loss of information.&lt;/p&gt;&#xA;&lt;p&gt;You can do this either in Open Babel or RDKit (or other toolkits). Since you mentioned RDKit, here's some rough code that should do that.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;m = Chem.MolFromMolFile(sdf_file)&#xA;&#xA;# this assumes whatever program you use doesn't re-order atoms&#xA;#  .. which is usually a safe assumption&#xA;#  .. so we don't bother tracking atoms&#xA;atomic_symbols = []&#xA;xyz_coordinates = []&#xA;&#xA;with open(xyz_file, &amp;quot;r&amp;quot;) as file:&#xA;    for line_number,line in enumerate(file):&#xA;        if line_number == 0:&#xA;            num_atoms = int(line)&#xA;        elif line_number == 1:&#xA;            comment = line # might have useful information&#xA;        else:&#xA;            atomic_symbol, x, y, z = line.split()&#xA;            atomic_symbols.append(atomic_symbol)&#xA;            xyz_coordinates.append([float(x),float(y),float(z)])&#xA;&#xA;# from https://github.com/rdkit/rdkit/issues/2413&#xA;from rdkit.Geometry import Point3D&#xA;conf = m.GetConformer()&#xA;&#xA;# in principal, you should check that the atoms match&#xA;for i in range(m.GetNumAtoms()):&#xA;   x,y,z = xyz_coordinates[i]&#xA;   conf.SetAtomPosition(i,Point3D(x,y,z))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-21T15:34:09.840" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8315" PostTypeId="2" ParentId="7200" CreationDate="2021-12-21T15:56:32.077" Score="3" Body="&lt;p&gt;For batch use, I recommend &lt;a href=&quot;https://openbabel.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;Open Babel&lt;/a&gt; which can translate &lt;code&gt;fasta&lt;/code&gt; format DNA sequences into single or double-stranded DNA coordinates. (Indeed, it's used in Avogadro.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/FASTA_format&quot; rel=&quot;nofollow noreferrer&quot;&gt;FASTA format&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt; DNA&#xA;AATCT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you can use something like this (&lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/FileFormats/FASTA_format.html?highlight=fasta&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel file.fasta -O file.pdb # output double-stranded&#xA;obabel file.fasta -O file.pdb -a1 # output single-stranded&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And of course &lt;code&gt;file.pdb&lt;/code&gt; could be &lt;code&gt;file.sdf&lt;/code&gt; or &lt;code&gt;file.mol2&lt;/code&gt; for other formats supported by Open Babel.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-21T15:56:32.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8316" PostTypeId="1" CreationDate="2021-12-21T15:59:56.930" Score="4" ViewCount="31" Body="&lt;p&gt;I am trying to generate the band structure of a slab, a lot of tutorials tell me that I need to generate the high symmetry K point path, but I am wondering that if the VBM and CBM have to be on the high symmetry point?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2021-12-21T15:59:56.930" Title="Do the VBM and CBM have to be on the high symmetry point?" Tags="|condensed-matter|symmetry|k-points|solid-state-physics|" AnswerCount="0" CommentCount="5" ClosedDate="2021-12-22T05:51:55.673" ContentLicense="CC BY-SA 4.0" />
  <row Id="8317" PostTypeId="2" ParentId="8310" CreationDate="2021-12-21T18:51:51.560" Score="7" Body="&lt;p&gt;I'd use OpenMM's &lt;code&gt;openmmforcefields&lt;/code&gt; package, which is available on &lt;a href=&quot;https://github.com/openmm/openmmforcefields&quot; rel=&quot;noreferrer&quot;&gt;GitHub&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I haven't used it extensively, but I recommended to a student in a colleague's lab and they've found it useful.&lt;/p&gt;&#xA;&lt;p&gt;Small molecule force fields:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;GAFF 1.x and 2.x parameters&lt;/li&gt;&#xA;&lt;li&gt;OpenFF parameters&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Biomolecule force fields:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Amber-type (albeit not &lt;code&gt;Amber ff19SB&lt;/code&gt; yet)&lt;/li&gt;&#xA;&lt;li&gt;CHARMM-type&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;And it will, if needed, generate AM1-BCC partial charges using OpenEye or &lt;code&gt;antechamber&lt;/code&gt; tools.&lt;/p&gt;&#xA;&lt;p&gt;The README gives some example Python code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Create an OpenFF Molecule object for benzene from SMILES&#xA;from openff.toolkit.topology import Molecule&#xA;molecule = Molecule.from_smiles('c1ccccc1')&#xA;# Create the GAFF template generator&#xA;from openmmforcefields.generators import GAFFTemplateGenerator&#xA;gaff = GAFFTemplateGenerator(molecules=molecule)&#xA;# Create an OpenMM ForceField object with AMBER ff14SB and TIP3P with compatible ions&#xA;from simtk.openmm.app import ForceField&#xA;forcefield = ForceField('amber/protein.ff14SB.xml', 'amber/tip3p_standard.xml', 'amber/tip3p_HFE_multivalent.xml')&#xA;# Register the GAFF template generator&#xA;forcefield.registerTemplateGenerator(gaff.generator)&#xA;# You can now parameterize an OpenMM Topology object that contains the specified molecule.&#xA;# forcefield will load the appropriate GAFF parameters when needed, and antechamber&#xA;# will be used to generate small molecule parameters on the fly.&#xA;from simtk.openmm.app import PDBFile&#xA;pdbfile = PDBFile('t4-lysozyme-L99A-with-benzene.pdb')&#xA;system = forcefield.createSystem(pdbfile.topology)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For example you could load your molecules like this from an &lt;code&gt;.sdf&lt;/code&gt; file (again from the README):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecules = Molecule.from_file('molecules.sdf')&#xA;gaff = GAFFTemplateGenerator(molecules=molecules, forcefield='gaff-2.11')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-21T18:51:51.560" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8318" PostTypeId="2" ParentId="8296" CreationDate="2021-12-22T09:25:44.613" Score="2" Body="&lt;p&gt;As far as my knowledge, you need to run SCF with &lt;code&gt;ISMEAR = -5&lt;/code&gt; to just get very accurate energies, while for relaxations you need to use &lt;code&gt;ISMEAR = 0&lt;/code&gt; (for semiconductors and insulators). Also, the DOSCAR file is used for the density of states calculations, and &lt;strong&gt;the tetrahedron smearing (&lt;code&gt;ISMEAR = -5&lt;/code&gt;) must be toggled on to get the correct Fermi energy&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2021-12-22T09:25:44.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8319" PostTypeId="1" CreationDate="2021-12-22T10:56:05.657" Score="7" ViewCount="482" Body="&lt;p&gt;I installed open-source pymol software using miniconda4 which have been installed successfully. I worked with the software, but whenever I am shutting down my PC and again restarted, the &amp;gt;pymol command on miniconda4 to open Pymol is not working. It is neither showing error nor opening. When I am trying to reinstall it, it is showing pymol is installed in my computer, and suggesting to reinstalled. It happened more than once. Now I am in a situation, whenever I am needing this software, I am installing it afresh or cannot shut down my PC. Can anyone shed some light on this problem and how to work on it?&lt;/p&gt;&#xA;" OwnerUserId="4704" LastEditorUserId="5" LastEditDate="2021-12-22T15:05:40.047" LastActivityDate="2021-12-22T15:05:40.047" Title="Pymol is not opening after startup" Tags="|python|software-assistance|pymol|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-18T15:30:45.570" ContentLicense="CC BY-SA 4.0" />
  <row Id="8320" PostTypeId="1" AcceptedAnswerId="8324" CreationDate="2021-12-22T11:14:16.070" Score="9" ViewCount="703" Body="&lt;p&gt;I am working on a project where I have to calculate the TDDFT excitation energies of organic molecules (to compare to the experimental UV/visible i.e. optical absorption spectrum). Now, if I understand correctly, most of the time, the absorption peaks in the UV/vis spectrum correspond to a vertical excitation i.e., the geometry of the molecule stays the same while the electron density shifts quickly (Frank-Condon).&lt;/p&gt;&#xA;&lt;p&gt;Now I have seen the pictures for excitation from the ground state, like the following [from Wikipedia]:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/k6V2mm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k6V2mm.png&quot; alt=&quot;Frank-Condon excitation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The vertical excitation (blue line in picture) happens from the lowest point of the PES of the ground electronic state(&lt;span class=&quot;math-container&quot;&gt;$E_0$&lt;/span&gt;), i.e. from the minimum energy geometry. This seems to suggest that excitation energies (with TDDFT or any other method) should be calculated only using the method/basis set combination in which the geometry is a minimum. So, I should &lt;strong&gt;optimise the geometry using the same method that I am using for excitation energies&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, I have seen research papers where EOM-CCSD excitation energies were calculated on geometries obtained with B3LYP/6-31G* for example. Is this correct? Is there any error in the calculated values if I use different functionals or basis sets for the geometry optimisation and the excited state calculation?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2021-12-22T15:54:38.193" Title="Is it reasonable to calculate TDDFT excitation energies at a geometry optimized with a different method?" Tags="|geometry-optimization|td-dft|excited-states|potential-energy-surface|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8321" PostTypeId="1" AcceptedAnswerId="8329" CreationDate="2021-12-22T12:10:35.910" Score="9" ViewCount="238" Body="&lt;p&gt;I am a VASP user, and I would like to know what are the things to keep in mind to obtain a good phonons spectrum curve without imaginary frequencies in terms of:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Which method is better for monolayers? DFPT or finite displacements?&lt;/li&gt;&#xA;&lt;li&gt;The supercell size?&lt;/li&gt;&#xA;&lt;li&gt;The use of normal pseudopotentials or ultrasoft pseudopotials?&lt;/li&gt;&#xA;&lt;li&gt;INCAR settings?&lt;/li&gt;&#xA;&lt;li&gt;Accuracy? etc...&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A detailed answer would be very appreciated, and thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="272" LastEditorUserId="272" LastEditDate="2021-12-22T19:41:25.073" LastActivityDate="2021-12-30T20:23:36.280" Title="How to improve a phonon spectrum calculation for a monolayer material?" Tags="|vasp|phonons|dfpt|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8322" PostTypeId="2" ParentId="8320" CreationDate="2021-12-22T12:29:49.187" Score="9" Body="&lt;p&gt;From my point of view, it will not affect so much on the excitation energy, but it is preferred to use the same level of functional and basis set unless you will increase the level of theory to get more accurate result.&lt;/p&gt;&#xA;&lt;p&gt;I did before a B3LYP/6-31G* optimization, and then I did the vertical excitation(CASPT2 with different basis set) using the optimized geometry(B3LYP) and the result is published at an excellent journal with IF=15,34.&lt;/p&gt;&#xA;&lt;p&gt;In general, You will use TD-DFT just to save time and understand your system, but the result from TD-DFT is not accurate compared to other methods.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2021-12-22T12:29:49.187" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8323" PostTypeId="2" ParentId="8296" CreationDate="2021-12-22T13:09:35.257" Score="4" Body="&lt;p&gt;The DOSCAR requires another run after a relaxation to be useful because the DOSCAR gives an average of the DOS across the ionic steps.&lt;/p&gt;&#xA;&lt;p&gt;In the first paragraph of the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/DOSCAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOSCAR VASP wiki page&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For dynamic simulations and relaxations, an averaged DOS and an averaged integrated DOS is written to the file. For a description of how the averaging is done see the tags NBLOCK, KBLOCK, EMIN, EMAX and NEDOS&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The average is contributed to every NBLOCK steps and written every NBLOCK*KBLOCK steps. By default, the average is contributed to by each step (NBLOCK=1) and written at the last ionic step (KBLOCK=NSW).&lt;/p&gt;&#xA;&lt;p&gt;Maybe the DOS could be useful if NBLOCK=KBLOCK=1, where the average would be written and reset after each ionic step, assuming your Brillouin zone integration method gave an acceptable DOS and acceptable forces, as mentioned in the answer by Chi Kou.&lt;/p&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2021-12-22T13:09:35.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8324" PostTypeId="2" ParentId="8320" CreationDate="2021-12-22T15:54:38.193" Score="7" Body="&lt;p&gt;The question, in some sense, is &amp;quot;how accurate is the geometry?&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;Yes, in principal, you should do TD-DFT on a true minimum geometry. However, the diagram also indicates that if you displace the geometry a small amount, the excitation energy won't change &amp;quot;much&amp;quot; (depending on your definition of &amp;quot;small amount&amp;quot; for the displacement and &amp;quot;much&amp;quot; for the &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; of the excitation).&lt;/p&gt;&#xA;&lt;p&gt;In my experience, if you're using a &amp;quot;good&amp;quot; method for the geometry optimization of a molecule (e.g., dispersion-corrected hybrid density functional) the differences in the excitation energies are smaller than the errors in TD-DFT for low-energy excitations like you're describing.&lt;/p&gt;&#xA;&lt;p&gt;You mention cases with EOM-CCSD excitation energies on B3LYP geometries. There are two reasons for this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Performing geometry optimizations with CCSD for anything but small molecules is extremely computationally-intensive.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimization with B3LYP is fairly standard for organic molecules - it produces fairly good geometries.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Taken together, people usually optimize with RI-MP2 or a good density functional for TD-DFT or an EOM method. These days, I'd probably recommend RI-MP2 or &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97X-D4 or &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;B97M-V.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-22T15:54:38.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8325" PostTypeId="1" AcceptedAnswerId="8331" CreationDate="2021-12-23T05:58:11.770" Score="11" ViewCount="1079" Body="&lt;p&gt;I am trying to calculate the band structure of a TiO2-Rutile slab, but the result I got is not very smooth, and the result shows it is an indirect gap material, but the bulk phase of TiO2-Rutile is a direct gap material.&#xA;My question is:&lt;br&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is it possible that the energy gap of the material is direct in the bulk but indirect in the slab?&lt;/li&gt;&#xA;&lt;li&gt;Is it normal that the band structure of a slab is not smooth? I can see the result of &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Ni_100_surface_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ni 100 surface bandstructure&lt;/a&gt; on the vasp tutorial, it seems also not very smooth.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here are the INCAR,POSCAR and KPOINTS files I use:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System=TiO2 surface DOS&#xA;#Startparameter for this run:&#xA;    ISTART =1         #job   :0-new  1-continue 2-samecut   charge:0-initial&#xA;    ICHARG =11         #charge:0-initial orbitals 1-from CHGCAR 2-ISTART=0 superposition of atoms&#xA;&#xA;#Electronic Properties&#xA;   ISMEAR =1         #part.occupancies -5-Blochl -4-tetra -1-fermi 0-guas;when calculate band,don't use ISMEAR=-5  conductor-1  semiconductor and insulator-0&#xA;   SIGMA  =0.05      #broadening in eV, when calculate Band structure, ISMEAR, SIGMA use default values   &#xA;   ISPIN  =2         #spin polarized calculation? 1-no 2-yes default-2&#xA;   LORBIT = 11&#xA;#Electronic Relaxation&#xA;    PREC   =Accurate&#xA;    ENCUT  =520       #energy cutoff in eV: Default-largest ENMAX from POTCAR-file&#xA;    EDIFF  =0.1E-04   #stopping-criterion for ELM&#xA;    NELM   =100       #the maximum number of electronic SC steps,default=60&#xA;    NELMIN =3         #the minimum number of electronic SC steps,default=2&#xA;#    NELMDL =3        #number of non-selfconsistent steps at the begining，default=5-10&#xA;&#xA;#DOS&#xA;    NEDOS  =2000&#xA;    EMIN   =-10&#xA;    EMAX   =10&#xA;&#xA;#Write file or not?&#xA;#    LWAVE  =.FALSE.   #write WAVECAR,default= .TRUE. &#xA;#    LCHARG =.FALSE.   #write CHG/CHGCAR,default= .TRUE. &#xA;&#xA;#Ionic relaxation&#xA;#    EDIFFG =0.1E-03   #stopping-criterion for IOM, default: EDIFFG = EDIFF×10 &#xA;#    NSW    =200        #number of steps for IOM.  0-default&#xA;#    IBRION =2         #ionic relax: ionic relaxation: 0-MD 1-quasi-New 2-CG&#xA;#    ISIF   =2         #stress and relaxation, when IBRION=0, ISIF=0,other default values is 2.&#xA;#   POTIM  =0.10      #time-step for inoic-motion&#xA;#   LREAL  =.FALSE.   #.TRUE.=true space  .FALSE.=reciprocal space = default.&#xA;&#xA;#Parallelization flags&#xA;    NCORE=8&#xA;    #KPAR=6&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;TiO2_mp-2657_computed\(1\1\0)&#xA;1.0&#xA;        2.9691998959         0.0000000000         0.0000000000&#xA;        0.0000000000         6.5806999207         0.0000000000&#xA;        0.0000000000         0.0000000000        40.7333984375&#xA;   Ti    O&#xA;   10   20&#xA;Direct&#xA;     0.500000000         0.000000000         0.129769996&#xA;     0.500000000         0.500000000         0.210549995&#xA;     0.500000000         0.000000000         0.291330010&#xA;     0.500000000         0.500000000         0.372099996&#xA;     0.500000000         0.000000000         0.452879995&#xA;     0.000000000         0.500000000         0.129769996&#xA;     0.000000000         0.000000000         0.210549995&#xA;     0.000000000         0.500000000         0.291330010&#xA;     0.000000000         0.000000000         0.372099996&#xA;     0.000000000         0.500000000         0.452879995&#xA;     0.500000000         0.304580003         0.129769996&#xA;     0.500000000         0.804579973         0.210549995&#xA;     0.500000000         0.304580003         0.291330010&#xA;     0.500000000         0.804579973         0.372099996&#xA;     0.500000000         0.304580003         0.452879995&#xA;     0.500000000         0.695420027         0.129769996&#xA;     0.500000000         0.195419997         0.210549995&#xA;     0.500000000         0.695420027         0.291330010&#xA;     0.500000000         0.195419997         0.372099996&#xA;     0.500000000         0.695420027         0.452879995&#xA;     0.000000000         0.000000000         0.098200001&#xA;     0.000000000         0.500000000         0.178979993&#xA;     0.000000000         0.000000000         0.259759992&#xA;     0.000000000         0.500000000         0.340530008&#xA;     0.000000000         0.000000000         0.421310008&#xA;     0.000000000         0.000000000         0.161339998&#xA;     0.000000000         0.500000000         0.242119998&#xA;     0.000000000         0.000000000         0.322899997&#xA;     0.000000000         0.500000000         0.403679997&#xA;     0.000000000         0.000000000         0.484450012&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;Special k-points for band structure&#xA;10  ! intersections &#xA;line-mode&#xA;reciprocal&#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;    0.5000000000     0.0000000000     0.0000000000 1    X &#xA;&#xA;&#xA;    0.5000000000     0.0000000000     0.0000000000 1    X &#xA;    0.5000000000     0.5000000000     0.0000000000 1    S &#xA;&#xA;&#xA;    0.5000000000     0.5000000000     0.0000000000 1    S &#xA;    0.0000000000     0.5000000000     0.0000000000 1    Y &#xA;&#xA;&#xA;    0.0000000000     0.5000000000     0.0000000000 1    Y &#xA;    0.0000000000     0.0000000000     0.0000000000 1    GAMMA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the result I got:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OUTCAR -&amp;gt;&#xA;NSPIN  =    2; NKPTS  =   40;&#xA;NBANDS =  150; Efermi =  -2.8040&#xA;------------------------------------------------------&#xA;                 SPIN_UP               SPIN_DN&#xA;------------------------------------------------------&#xA;      IND          111                   111&#xA; CBM  ENG        -1.63250              -1.63220&#xA;      KPT  0.5000 0.5000 0.0000  0.5000 0.5000 0.0000&#xA;          ____________________________________________&#xA;      IND          110                   110&#xA; VBM  ENG        -2.81420              -2.83650&#xA;      KPT  0.1667 0.5000 0.0000  0.1111 0.0000 0.0000&#xA;          ____________________________________________&#xA;   GAP           1.18170               1.20430&#xA;               inDirect_Gap          inDirect_Gap&#xA;                            1.18170&#xA;                          inDirect_Gap&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q5Ekc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q5Ekc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;An update after a new test, if I use 40 intersections between two special points. The band structure looks better obviously.&lt;br&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/QqEAG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QqEAG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2021-12-24T19:13:47.197" LastActivityDate="2021-12-24T19:13:47.197" Title="Why the band structure of a slab is not smooth?" Tags="|density-functional-theory|vasp|band-structure|condensed-matter|solid-state-physics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8326" PostTypeId="1" AcceptedAnswerId="8328" CreationDate="2021-12-23T08:40:52.807" Score="9" ViewCount="1180" Body="&lt;p&gt;I'm running and MD run with this command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx mdrun -v -deffnm md&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It also produces trajectory file with &lt;code&gt;.xtc&lt;/code&gt; extension.&#xA;Typically this file is extremely large, e.g. 143Gb for 1ns simulation and 143Tb for 10ns simulation.&lt;/p&gt;&#xA;&lt;p&gt;My questions is the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there an option in &lt;code&gt;gmx mdrun&lt;/code&gt; to specify where to write the &lt;code&gt;.xtc&lt;/code&gt; file?     For example I want to specify specific directory path with large disk space. Is there away to shrink the size of &lt;code&gt;.xtc&lt;/code&gt; file?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-12-24T17:29:44.703" LastActivityDate="2021-12-24T17:29:44.703" Title="How to manage disk space for Gromacs XTC (trajectory) file output" Tags="|molecular-dynamics|high-performance-computing|gromacs|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8327" PostTypeId="2" ParentId="8325" CreationDate="2021-12-23T12:52:16.333" Score="10" Body="&lt;p&gt;&lt;em&gt;1. Is it possible that the energy gap of the material is direct in the bulk but indirect in the slab?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Yes, this is possible (as is the reverse). The 2D slab does not have the same symmetry as the full 3D slab, and there is no requirement for the conduction band minima and valence band minima to be at the same points in reciprocal-space. As you make the slab thicker and thicker, you would usually expect to recover the properties of the 3D bulk materials, although strictly speaking the symmetry is not fully recovered whilst it is only 2D-periodic.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;2. Is it normal that the band structure of a slab is not smooth?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;No, this is not physically sensible. The curvature of the band in reciprocal-space is related to the particle's effective mass, &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;, by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\left[m^{-1}\right]_{ij} = \frac{1}{\hbar^2} \frac{\partial^2 E}{\partial k_i \partial k_j}.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Except for a fully localised band, the effective mass should be finite. The jagged, non-differentiable parts of your band-structure are artefacts of the calculation or plotting. This is probably due to the finite sampling of k-points (10 is not very many for such a small real-space cell), and I expect they would disappear if you used more intermediate points or a larger real-space cell. Note that your cell has an in-plane aspect ratio of approximately 1:2 so the k-points are spaced twice as far apart in one direction, and this is where the bands appear most jagged.&lt;/p&gt;&#xA;&lt;p&gt;Jagged band-structures can also be artefacts of the plotting software, which usually joins bands together based simply on their energy, rather than the corresponding physical state. Using additional information, such as band-gradients or projections, can allow a more physical matching of states across the Brillouin zone, and improve the quality of the plot.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2021-12-23T21:10:05.887" LastActivityDate="2021-12-23T21:10:05.887" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8328" PostTypeId="2" ParentId="8326" CreationDate="2021-12-23T14:56:04.667" Score="9" Body="&lt;blockquote&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is there an option in &lt;code&gt;gmx mdrun&lt;/code&gt; to specify where to write the &lt;code&gt;.xtc&lt;/code&gt; file? For example I want to specify specific directory path with large disk space.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When you use the &lt;code&gt;-deffnm md&lt;/code&gt; argument to &lt;code&gt;gmx mdrun&lt;/code&gt;, it is assumed that all of the files will have the base name of &lt;code&gt;md&lt;/code&gt;, so gromacs looks for &lt;code&gt;md.tpr&lt;/code&gt; as input, and it writes &lt;code&gt;md.xtc&lt;/code&gt;, &lt;code&gt;md.edr&lt;/code&gt; etc. as output files in the current directory. This is not made clear in the documentation unfortunately.&lt;/p&gt;&#xA;&lt;p&gt;To write the output files to other directories, you need to mention them explicitly. So, you need to run:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx mdrun -s md_01.tpr [-x /path/md_01.xtc] [-o md_01.trr] -c mdout.gro -g md_01.log -e md_01.edr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;-s&lt;/code&gt; argument supplies the binary topology input file (&lt;code&gt;.tpr&lt;/code&gt;), the &lt;code&gt;-x&lt;/code&gt; argument is for the compressed output, and &lt;code&gt;-o&lt;/code&gt; for uncompressed output, so use whichever you selected in the &lt;code&gt;.mdp&lt;/code&gt; file. The &lt;code&gt;-c&lt;/code&gt;, &lt;code&gt;-g&lt;/code&gt; and &lt;code&gt;-e&lt;/code&gt; arguments provide the files for output coordinates, logfile and energy output file respectively. You can supply a file path for each of these arguments.&lt;/p&gt;&#xA;&lt;p&gt;If you do not provide any of these arguments the default names would be used and the files would be written to the current working directory. The default names can be found &lt;a href=&quot;https://manual.gromacs.org/documentation/2021/onlinehelp/gmx-mdrun.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Is there away to shrink the size of &lt;code&gt;.xtc&lt;/code&gt; file?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is difficult, there are three ways you can reduce the size of the file, and you have to change the MD settings by modifying the &lt;code&gt;.mdp&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;One way is to change the frequency of writing the coordinates to the file i.e. increase the number of steps between writing to &lt;code&gt;.xtc&lt;/code&gt; file by changing the value of the parameter &lt;code&gt;nstxout-compressed&lt;/code&gt; in the &lt;code&gt;.mdp&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;Another way is to decrease the precision of the coordinates written, using the parameter &lt;code&gt;compressed-x-precision&lt;/code&gt; in the &lt;code&gt;.mdp&lt;/code&gt; file. The default value is &lt;code&gt;1000&lt;/code&gt;, which signifies 3-decimal point precision, so you can decrease that to &lt;code&gt;100&lt;/code&gt; i.e. 2-decimal points.&lt;/p&gt;&#xA;&lt;p&gt;There is also the setting &lt;code&gt;compressed-x-grps&lt;/code&gt; which allow you to only write coordinates of a specific group into the trajectory file. This might be useful if you have for instance, a protein in solvent, and you only need information about the protein. &lt;a href=&quot;https://manual.gromacs.org/archive/5.0.4/online/mdp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here&lt;/a&gt; you can find an example where only the protein coordinates are being written to the &lt;code&gt;.xtc&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;A detailed documentation of all of the &lt;code&gt;.mdp&lt;/code&gt; options can be found &lt;a href=&quot;https://manual.gromacs.org/documentation/2021/user-guide/mdp-options.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As an aside, an 143 GB output file for an 1 ns simulation seems unusually large. Your system likely has a large number of atoms, and you are storing coordinates every step. Usually, it is not necessary to do this. Consider the kind of analysis you need, and then adjust the saving frequency accordingly. For example, if you save coordinates each 2 ps (&lt;span class=&quot;math-container&quot;&gt;$\equiv2000$&lt;/span&gt; steps if each timestep = 1 fs), then already you have 500 frames saved in your trajectory, which is sufficient for most common properties that can be analysed from a trajectory.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2021-12-24T16:54:06.280" LastActivityDate="2021-12-24T16:54:06.280" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8329" PostTypeId="2" ParentId="8321" CreationDate="2021-12-23T19:15:08.080" Score="8" Body="&lt;p&gt;This is actually an important question regardless of the code you're using (I use SIESTA and NWChem).&#xA;To obtain a good phonon spectrum, the first thing you need is a truly relaxed/optimized structure. This requirement entails several parameter optimizations (mesh cutoff, force tolerance, basis set ..). Afterwards, other requirements are also important. I will address them while answering your specific queries.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;For the DFPT or finite displacements question, it has actually been answered before here :&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/89/are-there-differences-in-accuracy-and-reliability-between-the-frozen-phonon-meth&quot;&gt;Are there differences in accuracy and reliability between the frozen phonon method and Density Functional Perturbation Theory?&lt;/a&gt;&#xA;Here is a quote from that answer that might be all you need :&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In summary, these two methods lead to comparable accuracies. If DFPT is available, then the calculations will be cheaper and DFPT should be the method of choice&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;For the supercell size, the general rule is of course the larger the better, of course time and computational costs will play a role here (just as they would in choosing your optimization/relaxation parameters in the first step). Here is a &lt;a href=&quot;https://www.researchgate.net/post/How_large_supercell_should_I_build_in_order_to_calculate_phonon&quot; rel=&quot;nofollow noreferrer&quot;&gt;short post&lt;/a&gt; on ResearchGate that tackles this same question.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The Pseudopotential question has also already been answered. Here is the link for that answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1956/what-is-the-difference-between-ultrasoft-oncv-and-paw-pseudopotentials-which-i&quot;&gt;What is the difference between Ultrasoft, ONCV and PAW Pseudopotentials? Which is better for a spin-orbit coupled calculation?&lt;/a&gt;&#xA;Let me add also a quote from that answer :&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There is no systematic manner for deciding which pseudopotential is &amp;quot;better&amp;quot; as a pseudopotential that works well for obtaining one property may not work well for another property&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;For the VASP specific enquiries, it would probably be better for you to look into those in the VASP documentation and actually edit this answer to add them so that we could have a complete account of all the parameters.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here is some advice when doing phonon calculations where you obtain several negative (or imaginary, depending on the code you are using) modes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Take the lowest of these modes and displace the atoms along their respective eigenvectors. As this should reduce the total energy of your system and since you don’t know in which sense to displace, try both. From whichever displacement gives you lower energy, you can restart a new structure relaxation run followed by phonon spectrum.&lt;/li&gt;&#xA;&lt;li&gt;Check the accuracy of your atomic masses.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Finally here is an article, which covers your issue specifically but in a 3D structure instead of a monolayer&lt;sup&gt;[1]&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Evarestov, R. A.; Losev, M. V. All-electron LCAO calculations of the LiF crystal phonon spectrum: Influence of the basis set, the exchange-correlation functional, and the supercell size. &lt;em&gt;J. Comput. Chem.&lt;/em&gt; &lt;strong&gt;2009,&lt;/strong&gt; &lt;em&gt;30&lt;/em&gt; (16), 2645–2655. &lt;a href=&quot;https://doi.org/10.1002/jcc.21259&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1002/jcc.21259&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="7" LastEditDate="2021-12-30T20:23:36.280" LastActivityDate="2021-12-30T20:23:36.280" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8330" PostTypeId="2" ParentId="6356" CreationDate="2021-12-23T19:25:38.417" Score="2" Body="&lt;p&gt;Here are a couple of extra links that might be helpful in your (now 5months old) quest: [&lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;], [&lt;a href=&quot;https://www.cryst.ehu.es/cryst/get_kvec.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;p&gt;It would be helpful for all of us if you could put up that green chekmarck on the answers you found helpful and maybe tell us how you ended up resolving your issue, if you already have that is ...&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="5" LastEditDate="2021-12-23T21:56:25.883" LastActivityDate="2021-12-23T21:56:25.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8331" PostTypeId="2" ParentId="8325" CreationDate="2021-12-23T19:29:59.713" Score="7" Body="&lt;p&gt;You should take &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8325/why-the-band-structure-of-a-slab-is-not-smooth#comment17074_8325&quot;&gt;Binh Tien's advice&lt;/a&gt; for the continuity part of your problem. It has also been answered somewhat here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/771/how-to-ensure-a-smooth-band-structure?rq=1&quot;&gt;How to ensure a smooth band structure?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As for the gap issue, adding to Phil Hasnip's answer, a similar question has also had several proposals for answers here :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6356/how-to-generate-the-high-symmetry-paths-for-band-structure-calculations/8330#8330&quot;&gt;How to generate the high symmetry paths for band structure calculations?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;These might be enough for you to fix your issue.&lt;/p&gt;&#xA;&lt;p&gt;Allow me to stress again on the fact that, &lt;em&gt;&amp;quot;The 2D slab does not have the same symmetry as the full 3D slab, and there is no requirement for the conduction band minima and valence band minima to be at the same points in reciprocal-space&amp;quot;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Don't forget to give that green checkmark for the answers that help you resolve your issue and to comeback and tell us how you did it yourself so that we can close out this issue !&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="5" LastEditDate="2021-12-23T21:58:33.753" LastActivityDate="2021-12-23T21:58:33.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8332" PostTypeId="1" AcceptedAnswerId="8662" CreationDate="2021-12-24T04:45:27.450" Score="7" ViewCount="321" Body="&lt;p&gt;My question is somewhat related to molecular rotation. I have calculated the polarizability tensor of &lt;span class=&quot;math-container&quot;&gt;$\ce{HCHO}$&lt;/span&gt; molecule in PSI4. The output tensor is this,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0     20.834919148327081     1.691888747924788    -0.000000000000510&#xA;1      1.691888747924788    10.794718480348456    -0.000000000000070&#xA;2     -0.000000000000510    -0.000000000000070    15.501236458190954&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, keeping the bond parameters same, if I rotate the molecule and again calculate the same, the output is as follows,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;               0                     1                     2        &#xA;&#xA;0     20.899104179948107    -0.873319044510326    -0.000000000000008&#xA;1     -0.873319044510326    15.698712047619225     0.000000000000006&#xA;2     -0.000000000000008     0.000000000000006    10.526399871832178&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Looking at the diagonal elements, it is clear that depending upon the rotation, the matrix elements changes.&lt;/p&gt;&#xA;&lt;p&gt;The problem is, this calculation takes very long with larger basis (Q-Zeta). So, I was wondering if there is any mechanism (probably using euler rotation) where I need only to calculate the tensor once and rotate the tensor as the molecule is rotated in the real system.&lt;/p&gt;&#xA;&lt;p&gt;I would be grateful for any suggestion/help. If more clarity is/are needed, please comment/edit.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Following @Tyberius and @Susi's suggestion. I have gathered a small code.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def kabsch_umeyama(A, B):&#xA;    assert A.shape == B.shape&#xA;    n, m = A.shape&#xA;&#xA;    EA = np.mean(A, axis=0)&#xA;    EB = np.mean(B, axis=0)&#xA;    VarA = np.mean(np.linalg.norm(A - EA, axis=1) ** 2) #Variation of reference CoM and points&#xA;&#xA;    H = ((A - EA).T @ (B - EB)) / n                     #Calculation of covariance matrix&#xA;    U, D, VT = np.linalg.svd(H)                         #Singular value decomposition&#xA;    d = np.sign(np.linalg.det(U) * np.linalg.det(VT))&#xA;    S = np.diag([1] * (m - 1) + [d])&#xA;&#xA;    R = U @ S @ VT                                      #R= optimal rotation matrix&#xA;    &#xA;    c = VarA / np.trace(np.diag(D) @ S)                 #c=Scale factor&#xA;    t = EA - c * R @ EB&#xA;&#xA;    return R, c, t&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A and B refers to P and Q, two set of points (coordinates of formaldehyde), as P=&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[ 0.          0.6012398  -1.35383976]&#xA; [ 0.         -0.59301814 -1.55209021]&#xA; [ 0.9354225   1.17427624 -1.26515132]&#xA; [-0.9354225   1.17427624 -1.26515132]]&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and Q=&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      [[ 0.        , -0.60200476,  1.55228866],&#xA;       [ 0.        ,  0.59238638,  1.35511328],&#xA;       [ 0.        , -1.00937982,  2.57524635],&#xA;       [ 0.        , -1.32002906,  0.71694997]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The rotation matrix R=&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      [[ 0.00000112,  0.16405875,  0.98645057],&#xA;       [-0.16029666, -0.97369463,  0.16193746],&#xA;       [ 0.98706888, -0.15812491,  0.02629698]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;applying scaling and Rotation on Q, as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(np.array([t + c * R @ q for q in Q]))&#xA;&#xA;[[-0.0004728   0.6063693  -1.35626887]&#xA; [ 0.0009733  -0.58816112 -1.55025658]&#xA; [ 0.94149768  1.16850837 -1.26498045]&#xA; [-0.94199817  1.17005758 -1.26472672]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which suggest the rotation has been performed very well since, rotation on Q produces P very nearly.&lt;/p&gt;&#xA;&lt;p&gt;Now I have calculated polarizability tensor of P and Q. Which are as follows,&#xA;P=&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      [[22.1081711 ,  1.51237211,  0.        ],&#xA;       [ 1.51237211, 13.15927185,  0.        ],&#xA;       [ 0.        ,  0.        , 17.44240983]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and Q =&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      [[22.17406111, -0.76701797, -0.        ],&#xA;       [-0.76701797, 17.61697616, -0.        ],&#xA;       [-0.        , -0.        , 12.91504335]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My thinking is that, application of Rotation on Polarizability tensor of Q (Q_pol) should give Polarizability tensor of P (P_pol).&#xA;So, &lt;span class=&quot;math-container&quot;&gt;$P_{pol}=RQ_{pol}$&lt;/span&gt; or &lt;code&gt;P_pol=R@Q_pol&lt;/code&gt; (in python3)&#xA;However, I am getting R@Q_pol as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[ -0.12581111   2.89021823  12.74005187]&#xA; [ -2.80758665 -17.03060472   2.09142938]&#xA; [ 22.00861039  -3.5427824    0.33962659]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, as the problem was, main diagonal elements are on the other direction and it doesn't conserve the trace.&lt;/p&gt;&#xA;&lt;p&gt;However, &lt;span class=&quot;math-container&quot;&gt;$RR^\dagger=I$&lt;/span&gt; (or &lt;code&gt;R@np.transpose(R)=I&lt;/code&gt;)&#xA;as, I =&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[1. 0. 0.]&#xA; [0. 1. 0.]&#xA; [0. 0. 1.]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any help?&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="7" LastEditDate="2022-02-08T14:05:44.677" LastActivityDate="2022-02-08T15:13:52.883" Title="How to rotate polarizability tensor depending upon the molecular coordinates?" Tags="|electronic-structure|molecular-modeling|mathematical-modeling|polarizability|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8333" PostTypeId="2" ParentId="8332" CreationDate="2021-12-24T05:06:55.403" Score="7" Body="&lt;p&gt;Tensors are extremely useful in physics, since they allow writing down the laws of physics in a manner that doesn't depend on the used coordinate system. The definition of a tensor is in fact &amp;quot;that it transforms like a tensor&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume your original coordinate system is defined by the vectors &lt;span class=&quot;math-container&quot;&gt;$\hat{e}_i$&lt;/span&gt;, and you want to find the tensor &lt;span class=&quot;math-container&quot;&gt;${\bf T}$&lt;/span&gt; in the axis system defined by &lt;span class=&quot;math-container&quot;&gt;$\hat{e}'_i = Q_{ji} \hat{e}_j$&lt;/span&gt;  (Einstein summation assumed). How do we do this?&lt;/p&gt;&#xA;&lt;p&gt;A rank-1 tensor is a vector. Let's assume our vector &lt;span class=&quot;math-container&quot;&gt;${\bf v}$&lt;/span&gt; has components &lt;span class=&quot;math-container&quot;&gt;$v_i$&lt;/span&gt; in the original coordinate system, that is, &lt;span class=&quot;math-container&quot;&gt;${\bf v} = v_i \hat{e}_i$&lt;/span&gt;. The vector has to be the same in the two coordinate systems, &lt;span class=&quot;math-container&quot;&gt;${\bf v}=v_i \hat{e}_i = v_i' \hat{e}'_i$&lt;/span&gt;. The components thus transform as &lt;span class=&quot;math-container&quot;&gt;$v_i' = {\bf v} \cdot \hat{e}_i' = v_k\hat{e}_k \cdot Q_{ji} \hat{e}_j = v_k Q_{ji} \delta_{kj} = v_j Q_{ji} = Q_{ij}^\text{T} v_j = Q_{ij}^{-1} v_j$&lt;/span&gt;; that is, the components transform in the inverse direction of the coordinate system.&lt;/p&gt;&#xA;&lt;p&gt;A rank-2 tensor is given by &lt;span class=&quot;math-container&quot;&gt;${\bf T} = T_{ij} \hat{e}_i \otimes \hat{e}_j$&lt;/span&gt;; its tensor elements form a matrix &lt;span class=&quot;math-container&quot;&gt;$T_{ij}$&lt;/span&gt;. Repeating the same analysis, one finds that the tensor components transform as &lt;span class=&quot;math-container&quot;&gt;$T_{ij}' = Q_{ik}^{-1} Q_{jl}^{-1} T_{kl}$&lt;/span&gt;. You didn't specify the rotation matrix for the molecule, but you should be able to reproduce the tensor transform with this equation.&lt;/p&gt;&#xA;&lt;p&gt;Note that if you employ DFT in your calculations, the quadrature grid may result in breaking of rotational invariance; if that is the case then you need to increase the size of the grid.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-12-24T05:06:55.403" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8334" PostTypeId="2" ParentId="8289" CreationDate="2021-12-24T11:30:35.737" Score="6" Body="&lt;p&gt;Following the suggestion by Ian, let's first translate SIGMA into electronic structure language: VASP's SIGMA parameter defines the smearing width of the Fermi-Dirac [1] occupation function &lt;code&gt;f(E)&lt;/code&gt; in electron volts.&lt;/p&gt;&#xA;&lt;p&gt;There are at least two different reasons for choosing a finite smearing:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You want to simulate a finite electronic temperature.&lt;/li&gt;&#xA;&lt;li&gt;You are dealing with a metal (or material with a very small Kohn-Sham gap), and you would like to speed up convergence with respect to the density of the k-point grid.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;From your post, it seems neither is the case - you don't mention electronic temperature, and you are simulating silicon, i.e. a semiconductor (while semi-local density functionals will underestimate its band gap, the resulting gap is not close to 0, see e.g. &lt;a href=&quot;https://materialsproject.org/materials/mp-149&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Further points:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Electronic smearing is not a convergence parameter. Physically speaking, at T=0K, electronic smearing is 0.&lt;/li&gt;&#xA;&lt;li&gt;If the energy gap of your material is much larger than the chosen smearing value, its effect on the electronic occupation (and thus on the total energy) is negligible. This is why VASP gets away with using a default smearing width of 0.2eV (which would correspond to a temperature of roughly 2300K) - for semiconductors and insulators it should not have an effect, while for metals it helps with convergence as a function of the k-point density.&lt;/li&gt;&#xA;&lt;li&gt;Your plot does not show the magnitude of the effect you are seeing. I would expect it to be negligible - if not, one may need to investigate (or a VASP user may comment).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;[1] &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISMEAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;By default, VASP uses Methfessel-Paxton smearing&lt;/a&gt;, but this detail is not required for the discussion here.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2022-01-10T00:27:46.817" LastActivityDate="2022-01-10T00:27:46.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8335" PostTypeId="2" ParentId="8298" CreationDate="2021-12-24T11:43:45.007" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;the example doesn't generate K-points from the slab, it uses the K points extracted from the Brillouin zone of the bulk primitive cell.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Not sure you're reading the figure correctly.&lt;/p&gt;&#xA;&lt;p&gt;The bottom of the figure shows the three-dimensional Brillouin zone of the primitive cell, but the top of the figure (which the G-M-X-G path refers to) shows the two-dimensional Brillouin zone of the slab.&lt;/p&gt;&#xA;&lt;p&gt;You are right that the relation between the Brillouin zone of the primitive cell and a slab may not be straightforward and certainly depends on how the slab is constructed.&#xA;In this particular instance, the authors indicate a relation between the W point of the lower BZ and the G-M midpoint in the upper BZ.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2021-12-24T11:43:45.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8336" PostTypeId="1" CreationDate="2021-12-24T14:35:24.970" Score="5" ViewCount="562" Body="&lt;p&gt;Currently I'm doing an MD simulation of a protein-ligand complex using GROMACS.&lt;/p&gt;&#xA;&lt;p&gt;In the tutorial it mentioned the process of &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/06_equil.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Restraining the Ligand&lt;/em&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Why do we do it? Is it absolutely necessary?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2021-12-24T15:42:19.530" LastActivityDate="2021-12-29T23:44:25.333" Title="Why are ligands restrained when simulating a protein-ligand complex with MD?" Tags="|molecular-dynamics|gromacs|proteins|docking|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8337" PostTypeId="1" AcceptedAnswerId="8338" CreationDate="2021-12-24T15:26:04.637" Score="8" ViewCount="208" Body="&lt;p&gt;I conduct my DFT calculations using the SIESTA DFT package. For this, I obtained the pseudopotentials from this &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/periodictable-lda-abinit.html&quot; rel=&quot;noreferrer&quot;&gt;site&lt;/a&gt; which says that they have obtained the data from the Abinit database. However I do not see any details on a specific article or pseudopotential version to be cited.&lt;/p&gt;&#xA;&lt;p&gt;When writing a research article where these pseudopotentials have been used, how do I cite the origin of this data?&lt;/p&gt;&#xA;&lt;p&gt;With previous work in classical molecular dynamics, I am used to specifying the author of the interatomic interaction method as well as the version of the potential used if it has been modified at a later stage. Does this not happen with DFT calculations? I have seen published research where no reference is made to the origin of the Pseudopotential data.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2021-12-24T17:28:17.757" LastActivityDate="2021-12-24T17:28:17.757" Title="Citing a pseudopotential" Tags="|density-functional-theory|pseudopotentials|siesta|databases|abinit|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8338" PostTypeId="2" ParentId="8337" CreationDate="2021-12-24T16:20:33.277" Score="6" Body="&lt;p&gt;Other answers are most welcome, but here I will outline the process through which I went to find a reference that you can cite for a hydrogen pseudopotential. Hopefully this will help you find references for other other elements, and to dig deeper on your own in cases where references for these types of things seem harder to find.&lt;/p&gt;&#xA;&lt;p&gt;I followed the URL in your question, and as you said, it lead to a link to the ABINIT database. From there I clicked the link that said &amp;quot;Atomic data / pseudopotentials&amp;quot;, then the link that said &amp;quot;Recommended norm-conserving pseudo potentials&amp;quot; which got me to &lt;a href=&quot;https://www.abinit.org/psps_abinit&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt;. By clicking the H in the first periodic table shown, I obtained a file called &lt;code&gt;H.psp8&lt;/code&gt; which says in a comment:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#While it is not required under the terms of the GNU GPL, it is&#xA;#suggested that you cite D. R. Hamann, Phys. Rev. B 88, 085117 (2013)&#xA;#in any publication utilizing these pseudopotentials.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Therefore, for that specific norm-conserving pseudo-potential, you can cite &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.88.085117&quot; rel=&quot;noreferrer&quot;&gt;D. R. Hamann, Phys. Rev. B 88, 085117 (2013)&lt;/a&gt;.&lt;/p&gt;&#xA; &#xA;&lt;p&gt;The numbers in there, such as &lt;code&gt;-5.26468&lt;/code&gt; don't show up in, for example, the &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/Pseudos_LDA_Abinit/H_html/H.psf&quot; rel=&quot;noreferrer&quot;&gt;PSF file&lt;/a&gt; that we get by clicking the &lt;code&gt;H&lt;/code&gt; button directly on the site whose link you provided.&lt;/p&gt;&#xA;&lt;p&gt;So if you want, you may have to apply similar techniques of digging into things in order to find a reference for the data in that PSF file. Also note though, that one of the ABINIT pages that I previously mentioned but for which I didn't yet provide a link (&lt;a href=&quot;https://www.abinit.org/atomic-data-files&quot; rel=&quot;noreferrer&quot;&gt;here it is&lt;/a&gt;) says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;To use ABINIT in specific conditions it is recommended to produce&#xA;your own atomic data sets.&lt;/p&gt;&#xA;&lt;p&gt;This is the case, for example, if one wants to make simulations in&#xA;specific thermodynamic conditions, or use specific&#xA;exchange-correlation functionals, etc...&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Norm-conserving pseudo potential generators&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.mat-simresearch.com/&quot; rel=&quot;noreferrer&quot;&gt;ONCVPSP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.tddft.org/programs/APE/&quot; rel=&quot;noreferrer&quot;&gt;APE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://opium.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;OPIUM&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://cpc.cs.qub.ac.uk/summaries/ADKA_v1_0.html&quot; rel=&quot;noreferrer&quot;&gt;FHI98PP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;PAW atomic data file generators&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.abinit.org/downloads/PAW2/guideatompaw&quot; rel=&quot;noreferrer&quot;&gt;AtomPAW atomic dataset generator&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.abinit.org/downloads/PAW2/guideuspp&quot; rel=&quot;noreferrer&quot;&gt;USPP atomic dataset generator&lt;/a&gt;&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you follow that advice, you can generate your own data, and cite the program (from any one of the links in the quote directly above). Citing these programs seems a lot more straightforward than finding the citations for data given in databases that don't make it clear where they got the data (though generating one's own data is not the most convenient way to get a pseudopotential). While looking through all this, I've found some pesudopotential files in which there's no citation provided and not even anything close to a clue: this, along with the &lt;code&gt;comment&lt;/code&gt; above by Hamann that says &amp;quot;While it is not required under the terms of the GNU GPL, it is suggested that you cite [...]&amp;quot;  suggests that the authors of these pseudopotentials are not so fussed about getting citations for use of their pseudopotentials, and the lack of easily-accessible citation information given by SIESTA and ABINIT suggests that the &amp;quot;common practice&amp;quot; of citing this type of pseudopotential data is quite different from the common practice for citing basis sets, as you can see MOLPRO's equivalent online database for basis sets gives references, for example the cc-pVDZ basis set for hydrogen is &lt;a href=&quot;https://www.molpro.net/info/basis.php?describe=1&amp;amp;element=H&amp;amp;basis=cc-pVDZ&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; along with the literature citation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;H      : T.H. Dunning, Jr. J. Chem. Phys. 90, 1007 (1989).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Note though, that even when using basis sets, a lot of people don't give citations for the original papers from which the basis set came, such as the Dunning paper mentioned directly above, but this is usually because they don't know any better. You are doing the right thing by trying to find citations for the pseudopotentials you're using.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-24T17:26:47.353" LastActivityDate="2021-12-24T17:26:47.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8339" PostTypeId="1" CreationDate="2021-12-24T22:06:11.003" Score="6" ViewCount="137" Body="&lt;p&gt;I found two space groups of &lt;span class=&quot;math-container&quot;&gt;$\ce{LaCrO3}$&lt;/span&gt; material Pnma and Pm-3m. If someone is familiar with this material, please help to understand which phase is more stable. what are the factors that determine which phase is more stable?&lt;/p&gt;&#xA;" OwnerUserId="4354" LastEditorUserId="5" LastEditDate="2021-12-24T22:34:32.330" LastActivityDate="2021-12-25T04:41:11.330" Title="About LaCrO3 space group stability" Tags="|quantum-chemistry|condensed-matter|symmetry|physical-properties-of-materials|space-groups|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8340" PostTypeId="2" ParentId="8339" CreationDate="2021-12-25T03:52:06.207" Score="7" Body="&lt;p&gt;First of all make sure both phases are stable or not, to check stability of any phase, find mechanical stability and dynamical stability. From mechanical stability, I am referring to stiffness matrix should be positive definite, and dynamical stability means no imaginary vibration frequency exists. &lt;br /&gt;&#xA;&lt;strong&gt;Compare stability of two phases&lt;/strong&gt;&lt;br /&gt;&#xA;Basically you need to find Gibbs energy of both phases at particular temperature and at zero kelvin, Gibbs energy will come down to E0 with zero point energy correction (assuming pv term to be small) .In short, phase with lower Gibbs energy is more stable.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2021-12-25T04:41:11.330" LastActivityDate="2021-12-25T04:41:11.330" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8341" PostTypeId="1" AcceptedAnswerId="8342" CreationDate="2021-12-25T11:53:49.283" Score="11" ViewCount="1357" Body="&lt;p&gt;I was performing MD simulation for protein-ligand complex&#xA;following &lt;a href=&quot;http://www.mdtutorials.com/gmx/complex/09_analysis.html&quot; rel=&quot;noreferrer&quot;&gt;GROMACS tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I compared the  energy of two ligands (S1 and S2) to a protein,&#xA;using GROMACS &lt;strong&gt;LJ-SR&lt;/strong&gt; (Lennard-Jones Short Range) and &lt;strong&gt;Coul-SR&lt;/strong&gt; (Coulombic Short Range) option.&lt;/p&gt;&#xA;&lt;p&gt;Below is the plot.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fTY3N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fTY3N.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see the LJ-SR is complete opposite of Coul-SR.&#xA;Are they expected to be the opposite?&#xA;Which is more appropriate choice to represent real binding energy?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2021-12-25T12:07:11.823" LastActivityDate="2021-12-27T14:18:31.533" Title="How to choose appropriate energy term in GROMACS MD simulation (Lennard-Jones or Coulomb)?" Tags="|molecular-dynamics|gromacs|binding-energy|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8342" PostTypeId="2" ParentId="8341" CreationDate="2021-12-25T13:37:16.147" Score="12" Body="&lt;h2&gt;Which is more appropriate for the binding energy? Neither.&lt;/h2&gt;&#xA;&lt;p&gt;Obi-Wan voice: &lt;em&gt;&amp;quot;These are not the energies you're looking for.&amp;quot;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I understand your goal, you're trying to compare two ligands and determine which is better at binding to a given protein (and, ideally, quantify &amp;quot;how much better&amp;quot; one is compared to the other). If that is the case, then the quantity you're interested in is the &lt;strong&gt;relative free energy of binding&lt;/strong&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Delta\Delta G_\text{bind}$&lt;/span&gt;. The tutorial you're using explicitly states (regarding the energies you plot above):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It is important to note that this quantity is &lt;strong&gt;NOT&lt;/strong&gt; a free energy or a binding energy. In fact, most force fields are not parametrized in such a way that this quantity is actually physically meaningful.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The energies you're looking at here only provide a small part of the total picture for the free energy. Among other things, entropic concerns can dwarf the pure energetics. The quantities you're looking at here &lt;em&gt;may&lt;/em&gt; be useful for other things: for example, you might be able to characterize different binding poses based on these energies, and certainly bound vs. unbound would give significantly different values for these.&lt;/p&gt;&#xA;&lt;p&gt;The simplest way to get binding free energies from MD simulations is probably to use MM-PBSA (or a related method). &lt;a href=&quot;https://doi.org/10.1517/17460441.2015.1032936&quot; rel=&quot;noreferrer&quot;&gt;Here is a review article from a few years ago on those methods&lt;/a&gt;. These require some additional calculations, but a tool for doing MM-PBSA with Gromacs exists: &lt;a href=&quot;https://rashmikumari.github.io/g_mmpbsa/&quot; rel=&quot;noreferrer&quot;&gt;https://rashmikumari.github.io/g_mmpbsa/&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A more exact way to calculate the relative free energy of binding would be alchemical free energy simulations, which combine MD simulations from non-physical ensembles to estimate the difference in free energy between different states. &lt;a href=&quot;https://www.livecomsjournal.org/index.php/livecoms/article/view/v2i1e18378&quot; rel=&quot;noreferrer&quot;&gt;Here is a &amp;quot;living review&amp;quot; (intended to be regularly updated) of best practices for that kind of simulation&lt;/a&gt;; I recommend that as a starting point.&lt;/p&gt;&#xA;&lt;p&gt;Another approach is to calculate the dissociation rate (&lt;span class=&quot;math-container&quot;&gt;$k_\text{off}$&lt;/span&gt;), using rare events methods, and use the assumption that &lt;span class=&quot;math-container&quot;&gt;$k_\text{on}$&lt;/span&gt; is typically &lt;a href=&quot;https://www.nature.com/articles/nrd.2015.18&quot; rel=&quot;noreferrer&quot;&gt;near-constant for reversible binders&lt;/a&gt;. In my experience, this tends to be a more challenging calculation than the alchemical approach, but it may be more forgiving if your initial binding pose is not perfect (depending on specifics of the algorithm used).&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-12-25T13:37:16.147" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8343" PostTypeId="1" CreationDate="2021-12-25T14:51:29.343" Score="7" ViewCount="482" Body="&lt;p&gt;I read the basis set from book&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A d-type GTO written in terms of the spherical functions has five&#xA;components (Y2,2, Y2,1, Y2,0, Y2,1, Y2,2),but there appear to be six&#xA;components in the Cartesian coordinates (x2, y2, z2, xy, xz, yz). The&#xA;latter six functions, however, may be transformed to the five&#xA;spherical d-functions and one additional s-function (x^2 +y^2 +z^2).&#xA;Similarly, there are 10 Cartesian &amp;quot;f-functions&amp;quot; which may be&#xA;transformed into seven spherical f-functions and one set of spherical&#xA;p-functions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I try to solve this question in other books or lectures. However, they just told me what it is, how to fit GTO to STO (only s). I didn't know the detail how to transfrom 6 Cartesian d-functions to 5 spherical d-functions and one additional s-funcition?&lt;/p&gt;&#xA;" OwnerUserId="4716" LastActivityDate="2021-12-25T19:03:48.000" Title="Transforming basis functions from Cartesian to speherical" Tags="|quantum-chemistry|ab-initio-calculations|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8344" PostTypeId="1" AcceptedAnswerId="8349" CreationDate="2021-12-25T15:45:10.733" Score="8" ViewCount="615" Body="&lt;p&gt;I have been studying the Boltztrap2 software to calculate the thermoelectric properties of materials. However when following the tutorial given, the Seebeck coefficient is plotted against &lt;code&gt;mu&lt;/code&gt; as seen &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/tutorial&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; under section 5 towards the bottom of the page.&lt;/p&gt;&#xA;&lt;p&gt;However as far as I have seen (being a newbie), the symbol &lt;code&gt;mu&lt;/code&gt; is used for both &lt;code&gt;mobility&lt;/code&gt; as well as &lt;code&gt;chemical potential&lt;/code&gt;. Is there a way to distinguish between the two?&lt;/p&gt;&#xA;&lt;p&gt;Also, why is the graph plotted with &lt;code&gt;mu-fermi energy&lt;/code&gt;? Does this give some advantage when visualizing the data? If I am working with an non-doped semiconductor, should I consider the Seebeck coefficient value at &lt;code&gt;mu-fermi energy = 0&lt;/code&gt;? Should I be considering this &lt;code&gt;mu-fermi energy&lt;/code&gt; axis as an indication of the doping level in the first place?&lt;/p&gt;&#xA;" OwnerUserId="4346" LastEditorUserId="24" LastEditDate="2021-12-25T22:36:38.143" LastActivityDate="2021-12-25T23:01:53.233" Title="Mobility and chemical potential" Tags="|electronic-structure|solid-state-physics|electronic-transport|fermi-energy|boltztrap|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8345" PostTypeId="2" ParentId="8343" CreationDate="2021-12-25T19:03:48.000" Score="3" Body="&lt;p&gt;The difference between cartesian and spherical basis functions is that the latter use &lt;a href=&quot;https://en.wikipedia.org/wiki/Table_of_spherical_harmonics#Real_spherical_harmonics&quot; rel=&quot;nofollow noreferrer&quot;&gt;real spherical harmonics&lt;/a&gt;; for instance, &lt;span class=&quot;math-container&quot;&gt;$Y_{20} \propto \frac {-x^2 -y^2 +2z^2} {r^2}$&lt;/span&gt;. Quantum chemistry codes evaluate the basis functions or their integrals in the cartesian basis, and then use the connection between the cartesian functions and spherical functions to obtain the basis functions or the integrals in the spherical basis.&lt;/p&gt;&#xA;&lt;p&gt;This transformation has been discussed by Schlegel and Frisch in &lt;a href=&quot;https://doi.org/10.1002/qua.560540202&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 54, 83 (1995)&lt;/a&gt;. You may also want to have a look at the purple bible, i.e. the book &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9781119019572&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Electronic-Structure Theory&lt;/a&gt; by Helgaker, Jørgensen and Olsen.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2021-12-25T19:03:48.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8346" PostTypeId="2" ParentId="8344" CreationDate="2021-12-25T22:10:23.920" Score="7" Body="&lt;p&gt;In this case, &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; refers to the chemical potential. The reason it is given as &lt;span class=&quot;math-container&quot;&gt;$\mu-E_f$&lt;/span&gt; is simply to highlight that the &amp;quot;zero&amp;quot; has been set to the Fermi-level of the reference calculation (usually, undoped bulk). In a pseudopotential calculation, there is an arbitrary, pseudopotential-dependent offset to the energies, so their absolute values are meaningless, and only differences are important.&lt;/p&gt;&#xA;&lt;p&gt;You are correct that &lt;span class=&quot;math-container&quot;&gt;$\mu-E_f$&lt;/span&gt; is essentially a measure of doping. BoltzTraP(2) uses the rigid-band approximation, i.e. it assumes that the electronic states (usually approximated by the Kohn-Sham states) do not change appreciably under doping, and so all that changes is the electronic chemical potential (and, hence, the band occupancies).&lt;/p&gt;&#xA;&lt;p&gt;If you are interested in thermoelectric properties, you will never be working with an undoped semiconductor - apart from anything else, the electrical conductivity would be zero for most sensible temperature ranges, meaning that ZT would also be zero. In real materials, there are often intrinsic defects (e.g. vacancies or impurities) which act as dopants, so if you're comparing to experiment you'll need to estimate these effects and calibrate your calculations accordingly.&lt;/p&gt;&#xA;&lt;p&gt;Having said all that, remember that the &amp;quot;zero&amp;quot; of doping is the actual simulation you did; usually, this would be the undoped semiconductor, but there's nothing stopping you putting a dopant or two in there. In that case, what BoltzTraP considers &amp;quot;undoped&amp;quot; would actually be your doped semiconductor!&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2021-12-25T22:10:23.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8347" PostTypeId="5" CreationDate="2021-12-25T22:11:29.593" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-25T22:11:29.593" LastActivityDate="2021-12-25T22:11:29.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8348" PostTypeId="4" CreationDate="2021-12-25T22:11:29.593" Score="0" Body="Questions about or related to the Fermi energy." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-25T22:11:29.593" LastActivityDate="2021-12-25T22:11:29.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8349" PostTypeId="2" ParentId="8344" CreationDate="2021-12-25T22:35:01.497" Score="6" Body="&lt;p&gt;If you go to the definition of the Seebeck coefficient (&lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;) you will find:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S = \frac{{e{k_B}}}{\sigma }\int {d\varepsilon \left( { - \frac{{\partial {f_0}}}{{\partial \varepsilon }}} \right)} \Xi \left( \varepsilon  \right)\frac{{\varepsilon  - \mu }}{{{k_B}T}}\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here: &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt; is the electronic elementary charge, &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$f_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; are the Boltzmann constant, the Fermi-Dirac function and the chemical potential, and &lt;span class=&quot;math-container&quot;&gt;$\Xi$&lt;/span&gt; is the transport distribution (TD) function.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So, &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the chemical potential with units of energy.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Answering your questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;Is there a way to distinguish between the two?&lt;/em&gt; Just by the symbol, no. But you can go through the used equations and check the physics behind or just check the units, for example.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Also, why is the graph plotted with &lt;code&gt;mu-fermi energy&lt;/code&gt;?&lt;/em&gt; I think that it will depend on what are you studying. If you are interested in knowing the behavior of the Seebeck coefficient with the electron concentrations, plotting against &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is a good idea, as it depend directly on the electron concentrations.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Does this give some advantage when visualizing the data?&lt;/em&gt; Against, it is a choice. You can also plot it against the temperature, for example.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Should I consider the Seebeck coefficient value at &lt;code&gt;mu-fermi energy = 0&lt;/code&gt;?&lt;/em&gt; I don't thing so as &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; depends on it directly. There are properties, like electronic bands, that you can &amp;quot;shift&amp;quot; without any problem because they don't depend on &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; directly.&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Should I be considering this &lt;code&gt;mu-fermi energy&lt;/code&gt; axis as an indication of the doping level in the first place?&lt;/em&gt; As &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; directly depends on the electron concentration and the electron concentration can be modified by the doping level, yes, in principle, you can use &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; as a parameter very related to doping level.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2021-12-25T23:01:53.233" LastActivityDate="2021-12-25T23:01:53.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8350" PostTypeId="2" ParentId="8341" CreationDate="2021-12-25T22:46:28.290" Score="5" Body="&lt;p&gt;Just complementing the @dwhswenson &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8342/24&quot;&gt;answer&lt;/a&gt;, when studying ligand/protein binding process, there is no &lt;em&gt;best&lt;/em&gt; energy to look for.&lt;/p&gt;&#xA;&lt;p&gt;In the binding process there are several mechanism that will influence it. Knowing the influence of such and each mechanism, you can design your ligand accordingly to increase the binding.&lt;/p&gt;&#xA;&lt;p&gt;One of the advantage of using force fields is that the energy can be &amp;quot;partitioned&amp;quot; in several terms each one representing one interaction mechanism.&lt;/p&gt;&#xA;&lt;p&gt;For example, the &lt;a href=&quot;https://www.schrodinger.com/products/glide&quot; rel=&quot;nofollow noreferrer&quot;&gt;GLIDE&lt;/a&gt; score function (a roughly free binding energy) is partitioned in the following terms:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;vDW: van der Waals energy;&lt;/li&gt;&#xA;&lt;li&gt;Coul: Coulomb energy;&lt;/li&gt;&#xA;&lt;li&gt;Lipo: Energy contribution due to lipophilic interactions;&lt;/li&gt;&#xA;&lt;li&gt;HBond: Energy due to the hydrogen bond interactions;&lt;/li&gt;&#xA;&lt;li&gt;Metal: term associated to interaction of the ligand with metals;&lt;/li&gt;&#xA;&lt;li&gt;Site: energy due to polar interactions in the active site.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note: GLIDE is a docking software.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://github.com/HuiLiuCode/CaFE_Plugin&quot; rel=&quot;nofollow noreferrer&quot;&gt;CaFE plugin&lt;/a&gt; calculates the binding energy for a  ligand/protein complex using the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct300418h&quot; rel=&quot;nofollow noreferrer&quot;&gt;MM/PBSA&lt;/a&gt; method and returns the contribution of several terms (Elec, Vdw, PB, SA, Gas, Sol, Pol, Npol).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-12-27T14:18:31.533" LastActivityDate="2021-12-27T14:18:31.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8351" PostTypeId="2" ParentId="6958" CreationDate="2021-12-27T00:25:05.033" Score="2" Body="&lt;p&gt;Your equation for the effective Coulomb interaction is given as Eq. 7.203 &lt;a href=&quot;https://www.uio.no/studier/emner/matnat/fys/nedlagte-emner/FYS-KJM4480/h09/undervisningsmateriale/Lecture%20notes/mahan.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this PDF of Mahan's &amp;quot;Many-Particle Physics&amp;quot; book&lt;/a&gt;, but he &lt;em&gt;&lt;strong&gt;also&lt;/strong&gt;&lt;/em&gt; writes the same quantity in terms of the screened (&amp;quot;screening&amp;quot; it discussed in, e.g. Section 5.4 of the same book) electron-phonon interaction (in his notation):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;V_\textrm{eff} = \frac{V_q}{\varepsilon_\textrm{total}} = \frac{V_q^{(\infty)}}{\varepsilon(q,\omega)} + V_{\textrm{sc-ph}}(q,\omega),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;V_q^{(\infty)} = \frac{V_q}{\varepsilon_\infty}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Therefore if you obtain &lt;span class=&quot;math-container&quot;&gt;$V_\textrm{eff}$&lt;/span&gt; &lt;em&gt;&lt;strong&gt;and&lt;/strong&gt;&lt;/em&gt; the &lt;span class=&quot;math-container&quot;&gt;$\varepsilon (q,\omega)$&lt;/span&gt; empirically, then the screened electron-phonon coupling &lt;em&gt;function&lt;/em&gt; (or perhaps, the Fourier transform of it)  could be obtained by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;V_{\textrm{sc-ph}}(q,\omega) = V_\textrm{eff} - \frac{V_q}{\varepsilon_\infty \varepsilon(q,\omega)}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If empirically we have &lt;em&gt;&lt;strong&gt;only&lt;/strong&gt;&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$\varepsilon (q,\omega)$&lt;/span&gt;, then we can get the &lt;em&gt;&lt;strong&gt;difference&lt;/strong&gt;&lt;/em&gt;  between &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{sc-ph}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_\textrm{eff}$&lt;/span&gt;, but not &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{sc-ph}}$&lt;/span&gt; alone unless we're able to express &lt;span class=&quot;math-container&quot;&gt;$V_\textrm{eff}$&lt;/span&gt; in terms of known/obtainable quantities in another way (a bit like the &amp;quot;two equations for two unknowns&amp;quot; concept).&lt;/p&gt;&#xA;&lt;p&gt;If empirically we have &lt;em&gt;&lt;strong&gt;only&lt;/strong&gt;&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$V_\textrm{eff}$&lt;/span&gt;, then to get &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{sc-ph}}$&lt;/span&gt; alone we would need to express &lt;span class=&quot;math-container&quot;&gt;$\varepsilon (q,\omega)$&lt;/span&gt; in terms of known/obtainable quantities, which is discussed a bit in Section 5.5 of the same book by Mahan. An &amp;quot;exact&amp;quot; expression is given as:&lt;/p&gt;&#xA;&lt;p&gt;        &lt;a href=&quot;https://i.stack.imgur.com/CtTuP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CtTuP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and a definition in terms of other objects (the impurity charge density &lt;span class=&quot;math-container&quot;&gt;$\rho_i(\mathbf{q})$&lt;/span&gt; and screening charge density &lt;span class=&quot;math-container&quot;&gt;$\rho_s(\mathbf{q})$&lt;/span&gt;) is here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JKQ3c.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JKQ3c.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and linear screening models simply assume:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fMVkb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fMVkb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The opening sentence of Section 5.5 of the same book by Mahan, says that even for the uniform electron gas, no one had derived an exact solution to Eq. 5.110 for the dielectric function. He presented four different approximate solutions: Thomas-Fermi (Section 5.5.1), Lindhard/RPA (Section 5.5.2), Hubbard (Section 5.5.3), Singwi-Sjoelander (Section 5.5.4) and that this is &amp;quot;only a small subset of the vast number which are available&amp;quot; (and that was decades ago).&lt;/p&gt;&#xA;&lt;p&gt;The RPA is discussed again in Chapter 7, so I'll give the expression for &lt;span class=&quot;math-container&quot;&gt;$\varepsilon(q,\omega)$&lt;/span&gt; from there:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/drMEc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/drMEc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For some cases the expressions can be spelled out more directly, for example if you have a polar solid insulator with conduction electrons, you would simply get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Mx9PN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Mx9PN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;which makes it easier to get your &lt;span class=&quot;math-container&quot;&gt;$V_{\textrm{sc-ph}}(q,\omega)$&lt;/span&gt; function in terms from your empirical &lt;span class=&quot;math-container&quot;&gt;$V_\textrm{eff}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T00:31:20.520" LastActivityDate="2021-12-27T00:31:20.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8352" PostTypeId="2" ParentId="1642" CreationDate="2021-12-27T03:29:54.377" Score="5" Body="&lt;p&gt;&amp;quot;Inversion&amp;quot; is common in wavefunction-based quantum mechanics, for example the &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.444673&quot; rel=&quot;noreferrer&quot;&gt;RKR inversion method&lt;/a&gt; which constructs a potential energy function based on information that can be obtained from spectroscopic experiments, such that a Hamiltonian using this potential, when fed through the Schroedinger equation, will give eigenvalue differences that match the experimentally observed spectra. Likewise similar things can be done if the experimental data doesn't only contain energies (eigenvalues) but contains wavefunction information (such as Franck-Condon factors or spectroscopic intensities). The RKR method has a lot of historical significance, and it still sometimes used today, including (sometimes) as a stepping stone towards &amp;quot;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;Direct Potential Fitting&lt;/a&gt;&amp;quot; which is the state-of-the-art method for obtaining an empirical potential function for a small molecule from experimental spectroscopic data.&lt;/p&gt;&#xA;&lt;p&gt;A similar thing could be done if we had an &amp;quot;experimental&amp;quot; ground-state electron density, because:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;HK Theorem 1:&lt;/strong&gt; The external potential, is a unique functional of the electron density&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;which means &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r}_i) = V[n(\mathbf{r})]$&lt;/span&gt;, which can then be plugged into the canonical expression for the many-electron time-dependent Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4Tv3c.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4Tv3c.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then since the kinetic energy (the first sum) and the electron-electron interaction energy (third sum) are &amp;quot;universal operators&amp;quot;, meaning that they're the same for any &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron system, plugging in our obtained &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r}_i)$&lt;/span&gt; gives us a completely characterized Hamiltonian, which means &lt;em&gt;&lt;strong&gt;all&lt;/strong&gt;&lt;/em&gt; properties of the system, including the many-body wavefunction follow, though if we had the density we could have just got those properties properties from:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left\langle \hat{O} \right\rangle = \textrm{Tr} \left(\hat{\rho}\hat{O} \right), ~ \hat{\rho} = n(\mathbf{r}).&#xA;\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;There's some caveats:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Just as in the &amp;quot;Direct Potential Fitting (DPF)&amp;quot; using wavefunction-based quantum mechanics where you need a &amp;quot;model&amp;quot; for the potential energy function, if you don't know the functional &lt;span class=&quot;math-container&quot;&gt;$V[n(\mathbf{r})]$&lt;/span&gt; you would need to use a model functional and the accuracy of the &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})$&lt;/span&gt; that you get, will depend on how good your model functional is.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Obtaining the Hamiltonian can be considered obtaining the &amp;quot;material's properties&amp;quot; (to use your words), but by &amp;quot;material properties&amp;quot; you might mean things like &amp;quot;conductivity&amp;quot;. In the DPF case we do obtain things like bond lengths from the fitting procedure, but only because bond length is a property defined based on an easily accessible property of the potential energy function which was obtained in the DPF process: likewise any properties of the material which are defined based on easily accessible properties of &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})$&lt;/span&gt;, will be obtained, but other properties which are defined differently, could be better obtained from Eq. 2.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Finally to answer your follow-up question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;As a followup, what experimental accuracy for ρ(r) is needed to accurately determine those material properties?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can use &lt;a href=&quot;https://en.wikipedia.org/wiki/Propagation_of_uncertainty&quot; rel=&quot;noreferrer&quot;&gt;error propagation&lt;/a&gt; techniques to determine what an error in &lt;span class=&quot;math-container&quot;&gt;$n(\mathbf{r})$&lt;/span&gt; will imply for the errors of &lt;span class=&quot;math-container&quot;&gt;$\left\langle \hat{O} \right\rangle$&lt;/span&gt; from Eq. 2, but for obtaining properties based on &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})$&lt;/span&gt; &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285298976469&quot; rel=&quot;noreferrer&quot;&gt;this paper by Bob Le Roy&lt;/a&gt; would be a good place to start, but beware of the fact that there will be a contribution to the final uncertainty in the material property coming from the choice of the model (functional in your case, potential energy functioni n the Schroedinger-based DPF case) you use, which can be extremely difficult even to define, and is unfortunately ignored usually in research papers even by experts.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2021-12-27T03:29:54.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8353" PostTypeId="5" CreationDate="2021-12-27T04:21:26.013" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://wulffpack.materialsmodeling.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wulffpack.materialsmodeling.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T04:21:26.013" LastActivityDate="2021-12-27T04:21:26.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8354" PostTypeId="4" CreationDate="2021-12-27T04:21:26.013" Score="0" Body="Questions about or related to WulffPack, the Python software for Wulff constructions." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T04:21:26.013" LastActivityDate="2021-12-27T04:21:26.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8355" PostTypeId="1" CreationDate="2021-12-27T05:16:41.493" Score="5" ViewCount="44" Body="&lt;p&gt;We synthesis a lot of ceramic catalysts. For a long time now, we are facing problems in accurately and efficiently characterising the synthesized powders. We have identified the main problems as follows -&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;We have a doubt whether we are doing the sample treatment correctly or not. A lot of vendors tell us that, “providing a dry, fine powder is sufficient”. But is there any comprehensive guide or something that can help me help in deciding the appropriate sample treatment for a particular characterisation method?&lt;/li&gt;&#xA;&lt;li&gt;For a lot of techniques/methods, depending on the instruments the operator has to choose between a lot of parameters depending on the inherent characterisation properties of the powders. We feel the operators that we are dealing with nonchalantly input the default settings and this makes the output coming out not so accurate. Again, how do I navigate efficiently through this space?&#xA;Anyone who has experience in operating various machines and analysing the output, any help will be appreciated.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;PS – We are doing the following techniques –&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Powder XRD&lt;/li&gt;&#xA;&lt;li&gt;ICP-AES&lt;/li&gt;&#xA;&lt;li&gt;TEM/SEM&lt;/li&gt;&#xA;&lt;li&gt;XRF&lt;/li&gt;&#xA;&lt;li&gt;Chemisorption&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4725" LastActivityDate="2022-01-04T21:55:54.827" Title="Navigating through the various ceramic characterisation techniques?" Tags="|x-ray-diffraction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8356" PostTypeId="1" CreationDate="2021-12-27T12:20:16.577" Score="9" ViewCount="509" Body="&lt;p&gt;I was trying to optimize Vanadium doped 4x4 MoS2 using SIESTA. Plotting the band structure I was able to see the symmetry breaking at K and K'.&#xA;But when I tried to do the same calculation in Quantum ESPRESSO, the first trouble I can across is that I needed to set a starting magnetization value which wasn't needed for SIESTA. Does SIESTA have a default value for it?&#xA;Secondly, I tried using different values of starting magnetization for Vanadium but all of them converged to zero. SIESTA had output that Vanadium had an extra up spin.&lt;/p&gt;&#xA;&lt;p&gt;Edit 1 : As suggested by Camps, I tried optimizing the structure using starting_magnetization value of 1 for all three atoms. Still, the system converged to a state without magnetization.&lt;/p&gt;&#xA;&lt;p&gt;Edit 2 : I have finally got similar spin splitting i.e. up and down for Quantum espresso by adding Hubbard Potentials for the atoms. I believe this has got to do with difference in the basis sets used for SIESTA and QE. (I tried the following on smaller system where neither QE nor SIESTA showed any symmetry breaking at K and K')&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="1195" LastEditDate="2021-12-31T04:58:24.460" LastActivityDate="2021-12-31T04:58:24.460" Title="Spin polarized calculation gives different solution in SIESTA and Quantum ESPRESSO" Tags="|quantum-espresso|siesta|spin-polarization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8357" PostTypeId="2" ParentId="6473" CreationDate="2021-12-27T13:36:02.697" Score="1" Body="&lt;p&gt;You can take a look &lt;a href=&quot;http://publish.illinois.edu/yubo-paul-yang/tutorials/quantum-espresso/pseudopotential-generation/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; about how to generate UPF pseudos using the software &lt;code&gt;ld1.x&lt;/code&gt; that is part of QuantumEspresso.&lt;/p&gt;&#xA;&lt;p&gt;In principle, you will need an input file with the information about the atom you want to generate the pseudopotential. Here is an example of an input file (&lt;code&gt;infile&lt;/code&gt;) to generate the UPF pseudopotential for Si:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;input&#xA;title = 'all-electron Si'&#xA;zed = 14.0 ! or equivalently atom = 'Si'&#xA;iswitch = 3 ! 1 for all electron, 2 for PP test, 3 for PP generation&#xA;dft = 'lda'&#xA;prefix = 'si'&#xA;config = '[Ne] 3s2 3p2' ! neutral atom&#xA;rmax = 20 ! (bohr) the extent of the most delocalized orbital&#xA;! take logarithmic derivative at Rcut=2.20 over the energy&#xA;! range -2.0 to 1.0 with dE=0.01&#xA;rlderiv = 2.20, eminld = -2.0, emaxld = 1.0, deld = 0.01&#xA;&#xA;&amp;amp;inputp&#xA;pseudotype = 1 ! old-format norm-conserving&#xA;lloc = 1 ! angular momentum of the local channel ?&#xA;file_pseudopw = 'Si.UPF'&#xA;tm = .true. ! Troullier-Martins&#xA;author = 'me!'&#xA;/&#xA;2&#xA;3S 1 0 2.00 0.00 2.20 2.20&#xA;! S=1 l occ. energy Rcut Rcut_us&#xA;3P 2 1 2.00 0.00 2.20 2.20&#xA;! P=2 l occ. eigen. Rcut Rcut_us&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, run: &lt;code&gt;ld1.x &amp;lt; infile &amp;gt; outfile&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the &lt;code&gt;outfile&lt;/code&gt;, you can use the name you want, but I recommend to use something informative, like &lt;code&gt;Si_LDA.UPF&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In this &lt;a href=&quot;http://publish.illinois.edu/yubo-paul-yang/files/2015/12/exercise1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; you can get the tutorial &lt;em&gt;Construction of norm-conserving semi-local pseudopotentials for Si&lt;/em&gt; with all the details and information.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-27T13:36:02.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8358" PostTypeId="2" ParentId="8356" CreationDate="2021-12-27T14:17:40.543" Score="9" Body="&lt;p&gt;When running spin polarized calculations with SIESTA, the logical keyword &lt;code&gt;DM.InitSpin.AF&lt;/code&gt; will define the initial magnetization. From the SIESTA manual (v4.1.5):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;DM.InitSpin.AF &lt;strong&gt;false&lt;/strong&gt; (logical)&lt;br /&gt;&#xA;It defines the initial spin density for&#xA;a spin polarized calculation. The spin density is initially&#xA;constructed with the maximum possible spin polarization for each atom&#xA;in its atomic configuration. This variable defines the relative&#xA;orientation of the atomic spins: If &lt;strong&gt;false&lt;/strong&gt; the initial&#xA;spin-configuration is a ferromagnetic order (all spins up). If &lt;strong&gt;true&lt;/strong&gt;&#xA;all odd atoms are initialized to spin-up, all even atoms are&#xA;initialized to spin-down.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can also use the block &lt;code&gt;DM.InitSpin&lt;/code&gt; and define your own spin configuration for each atom. Example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block DM.InitSpin&#xA;5 -1. 90. 0. # Atom index, spin, theta, phi (deg)&#xA;3 +45. -90.&#xA;7 -&#xA;%endblock DM.InitSpin&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This block has precedence over &lt;code&gt;DM.InitSpin.AF&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-27T14:17:40.543" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8359" PostTypeId="1" AcceptedAnswerId="8440" CreationDate="2021-12-27T19:40:46.437" Score="10" ViewCount="1003" Body="&lt;p&gt;There are many programs out there where you pass an XYZ coordinate file and the program will give you a visualization of the molecule. I want to make a plot like the one in the picture, with bond lengths on top and a second one with bond angles. Again, plotting the molecule, calculating the bond angles and lengths is easy. The problem is to put them on the same image in the right place. I have tried many molecular visualization programs such as gdis, xcrysden, and Python libraries such as RDKit and sisl. None of these allow me to do what I want. I guess I could photoshop them on top but that will be very tedious. My molecule has around 70 angles and 45 bonds. Does someone know a good way to do this?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QHuZV.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QHuZV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4659" LastActivityDate="2021-12-30T16:50:08.430" Title="How to plot molecules with angles and bond lengths" Tags="|quantum-chemistry|computational-chemistry|software-recommendations|molecular-modeling|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8360" PostTypeId="2" ParentId="8359" CreationDate="2021-12-27T21:00:39.617" Score="10" Body="&lt;p&gt;Using Jmol you can label all the bonds, angle, etc. but in &lt;strong&gt;3D&lt;/strong&gt; using the command &lt;a href=&quot;https://chemapps.stolaf.edu/jmol/docs/index.htm?ver=14.31#measure&quot; rel=&quot;noreferrer&quot;&gt;measure&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Renders a measurement between the specified atoms. See also set&#xA;(measure). Two general syntaxes are available. In the older syntax, a&#xA;series of two to four atom numbers are given, and the appropriate&#xA;measure (distance, angle, or dihedral angle) is then displayed. The&#xA;newer, more general syntax is as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;measure RANGE &amp;lt;minValue&amp;gt; &amp;lt;maxValue&amp;gt; ALL|ALLCONNECTED|DELETE (\&amp;lt;atom expression&amp;gt;) (\&amp;lt;atom expression&amp;gt;)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Using this syntax one can specify a set of measurements to define all at once. Note that these sets are embedded atom expressions that must be enclosed in parentheses. If neither &lt;code&gt;ALL&lt;/code&gt; nor &lt;code&gt;ALLCONNECTED&lt;/code&gt; is present, only the first matching atom in the entire model set (all frames, so probably the first frame) is matched in each atom expression. When &lt;code&gt;ALL&lt;/code&gt; or &lt;code&gt;ALLCONNECTED&lt;/code&gt; is specified, all matching criteria in all frames are generated, thus allowing for &amp;quot;animated&amp;quot; measures.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The image below is an example:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/YejO7.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YejO7.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2021-12-27T21:05:52.567" LastActivityDate="2021-12-27T21:05:52.567" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8361" PostTypeId="2" ParentId="8355" CreationDate="2021-12-27T22:00:44.423" Score="4" Body="&lt;p&gt;Each of the technique you mention is specialized in one characterization type. So, using all those techniques will give you several properties of your materials.&lt;/p&gt;&#xA;&lt;p&gt;There are techniques like powder XRD and TEM/SEM from which you can obtain the grain size from both, for example. From the powder XRD in an indirect way whereas from TEM/SEM in a direct way. In this case, you can use both techniques in complementary way.&lt;/p&gt;&#xA;&lt;p&gt;For some of those techniques, only the operator experience is needed as the properties are obtained directly from the measurement. But there are other techniques, like powder XRD, that needs an iteration process between the operator and who will treat your data and get the properties you want (e.g. the grain size, cell size, symmetry group, etc.).&lt;/p&gt;&#xA;&lt;p&gt;My advice is to go through the &lt;em&gt;chemistry/physics&lt;/em&gt; of each techniques, &lt;em&gt;what&lt;/em&gt; can be determine from each one and &lt;em&gt;how&lt;/em&gt; can be determined. Also, read papers where they use them to characterize similar materials. Also, trying to correlate each property is a good path.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-27T22:00:44.423" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8362" PostTypeId="5" CreationDate="2021-12-27T23:04:21.447" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:04:21.447" LastActivityDate="2021-12-27T23:04:21.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8363" PostTypeId="4" CreationDate="2021-12-27T23:04:21.447" Score="0" Body="Questions about or related to reactivity and/or reactions." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:04:21.447" LastActivityDate="2021-12-27T23:04:21.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8364" PostTypeId="5" CreationDate="2021-12-27T23:05:07.323" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:07.323" LastActivityDate="2021-12-27T23:05:07.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8365" PostTypeId="4" CreationDate="2021-12-27T23:05:07.323" Score="0" Body="Questions about or related to exact or numerically exact methods for finding eigenvalues/eigenvectors/eigenfunctions." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:07.323" LastActivityDate="2021-12-27T23:05:07.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8366" PostTypeId="5" CreationDate="2021-12-27T23:05:21.503" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:21.503" LastActivityDate="2021-12-27T23:05:21.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8367" PostTypeId="4" CreationDate="2021-12-27T23:05:21.503" Score="0" Body="Questions about or related to Mott insulators." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:21.503" LastActivityDate="2021-12-27T23:05:21.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8368" PostTypeId="5" CreationDate="2021-12-27T23:05:40.513" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:40.513" LastActivityDate="2021-12-27T23:05:40.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8369" PostTypeId="4" CreationDate="2021-12-27T23:05:40.513" Score="0" Body="Questions about or related to lattice thermal conductivity." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:05:40.513" LastActivityDate="2021-12-27T23:05:40.513" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8370" PostTypeId="5" CreationDate="2021-12-27T23:08:06.927" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://phonopy.github.io/phono3py/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://phonopy.github.io/phono3py/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://phonopy.github.io/phonopy/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:08:06.927" LastActivityDate="2021-12-27T23:08:06.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8371" PostTypeId="4" CreationDate="2021-12-27T23:08:06.927" Score="0" Body="Questions about or related to phono3py: &quot;Phonopy is an open source package for phonon calculations at harmonic and quasi-harmonic levels. Phono3py is another open source package for phonon-phonon interaction and lattice thermal conductivity calculations.&quot;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:08:06.927" LastActivityDate="2021-12-27T23:08:06.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8372" PostTypeId="5" CreationDate="2021-12-27T23:08:58.993" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:08:58.993" LastActivityDate="2021-12-27T23:08:58.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8373" PostTypeId="4" CreationDate="2021-12-27T23:08:58.993" Score="0" Body="Questions about or related to redox (oxidation and/or reduction)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:08:58.993" LastActivityDate="2021-12-27T23:08:58.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8374" PostTypeId="5" CreationDate="2021-12-27T23:09:15.357" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:09:15.357" LastActivityDate="2021-12-27T23:09:15.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8375" PostTypeId="4" CreationDate="2021-12-27T23:09:15.357" Score="0" Body="Questions about or related to ferroelectricity." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:09:15.357" LastActivityDate="2021-12-27T23:09:15.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8376" PostTypeId="5" CreationDate="2021-12-27T23:10:06.130" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:10:06.130" LastActivityDate="2021-12-27T23:10:06.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8377" PostTypeId="4" CreationDate="2021-12-27T23:10:06.130" Score="0" Body="&quot;The minimum-image convention is a common form of PBC particle bookkeeping in which each individual particle in the simulation interacts with the closest image of the remaining particles in the system.&quot;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:10:06.130" LastActivityDate="2021-12-27T23:10:06.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8378" PostTypeId="5" CreationDate="2021-12-27T23:10:23.893" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:10:23.893" LastActivityDate="2021-12-27T23:10:23.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8379" PostTypeId="4" CreationDate="2021-12-27T23:10:23.893" Score="0" Body="Questions about or related to curve fitting." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:10:23.893" LastActivityDate="2021-12-27T23:10:23.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8380" PostTypeId="5" CreationDate="2021-12-27T23:12:15.797" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://uspex-team.org/en&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://uspex-team.org/en/uspex/overview&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://uspex-team.org/en/uspex/overview&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:15.797" LastActivityDate="2021-12-27T23:12:15.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8381" PostTypeId="4" CreationDate="2021-12-27T23:12:15.797" Score="0" Body="Questions about or related to USPEX (Universal Structure Predictor: Evolutionary Xtallography)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:15.797" LastActivityDate="2021-12-27T23:12:15.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8382" PostTypeId="5" CreationDate="2021-12-27T23:12:34.253" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:34.253" LastActivityDate="2021-12-27T23:12:34.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8383" PostTypeId="4" CreationDate="2021-12-27T23:12:34.253" Score="0" Body="Questions about or related to Curie temperature." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:34.253" LastActivityDate="2021-12-27T23:12:34.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8384" PostTypeId="5" CreationDate="2021-12-27T23:12:50.127" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:50.127" LastActivityDate="2021-12-27T23:12:50.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8385" PostTypeId="4" CreationDate="2021-12-27T23:12:50.127" Score="0" Body="Questions about or related to crystal plasticity." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:12:50.127" LastActivityDate="2021-12-27T23:12:50.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8386" PostTypeId="5" CreationDate="2021-12-27T23:13:06.023" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:13:06.023" LastActivityDate="2021-12-27T23:13:06.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8387" PostTypeId="4" CreationDate="2021-12-27T23:13:06.023" Score="0" Body="Questions about or related to smearing." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:13:06.023" LastActivityDate="2021-12-27T23:13:06.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8388" PostTypeId="5" CreationDate="2021-12-27T23:13:16.947" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:13:16.947" LastActivityDate="2021-12-27T23:13:16.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8389" PostTypeId="4" CreationDate="2021-12-27T23:13:16.947" Score="0" Body="Questions about or related to membranes." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:13:16.947" LastActivityDate="2021-12-27T23:13:16.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8390" PostTypeId="5" CreationDate="2021-12-27T23:43:39.317" Score="0" Body="&lt;p&gt;Did not yet delete this tag because for at least one of the questions that use it, I couldn't easily think of two other tags to saturate the question's tags, so removing this one wouldn't help much in that regard.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:43:39.317" LastActivityDate="2021-12-27T23:43:39.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8391" PostTypeId="4" CreationDate="2021-12-27T23:43:39.317" Score="0" Body="Questions about or related to vacuum potentials." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:43:39.317" LastActivityDate="2021-12-27T23:43:39.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8392" PostTypeId="5" CreationDate="2021-12-27T23:44:16.737" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:44:16.737" LastActivityDate="2021-12-27T23:44:16.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8393" PostTypeId="4" CreationDate="2021-12-27T23:44:16.737" Score="0" Body="Questions about or related to computer hardware." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:44:16.737" LastActivityDate="2021-12-27T23:44:16.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8394" PostTypeId="5" CreationDate="2021-12-27T23:44:32.110" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:44:32.110" LastActivityDate="2021-12-27T23:44:32.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8395" PostTypeId="4" CreationDate="2021-12-27T23:44:32.110" Score="0" Body="Questions about or related to organic chemistry." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:44:32.110" LastActivityDate="2021-12-27T23:44:32.110" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8396" PostTypeId="5" CreationDate="2021-12-27T23:45:11.063" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:11.063" LastActivityDate="2021-12-27T23:45:11.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8397" PostTypeId="4" CreationDate="2021-12-27T23:45:11.063" Score="0" Body="Questions about or related to enhanced sampling.&#xD;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:11.063" LastActivityDate="2021-12-27T23:45:11.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8398" PostTypeId="5" CreationDate="2021-12-27T23:45:26.243" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:26.243" LastActivityDate="2021-12-27T23:45:26.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8399" PostTypeId="4" CreationDate="2021-12-27T23:45:26.243" Score="0" Body="Questions about or related to DMFT." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:26.243" LastActivityDate="2021-12-27T23:45:26.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8400" PostTypeId="5" CreationDate="2021-12-27T23:45:46.410" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:46.410" LastActivityDate="2021-12-27T23:45:46.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8401" PostTypeId="4" CreationDate="2021-12-27T23:45:46.410" Score="0" Body="Questions about or related to fractals." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:45:46.410" LastActivityDate="2021-12-27T23:45:46.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8402" PostTypeId="5" CreationDate="2021-12-27T23:56:11.830" Score="0" Body="&lt;p&gt;This one: &lt;a href=&quot;https://gitlab.com/mbarbry/pynao&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/mbarbry/pynao&lt;/a&gt;, not this &lt;a href=&quot;https://github.com/BrutusTT/pyNAO&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/BrutusTT/pyNAO&lt;/a&gt; or this: &lt;a href=&quot;https://github.com/x1angli/pynao&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/x1angli/pynao&lt;/a&gt; (the latter two both being about robotics). The website: &lt;a href=&quot;https://mbarbrywebsite.ddns.net/pynao/doc/html/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://mbarbrywebsite.ddns.net/pynao/doc/html/&lt;/a&gt; was not working on 27 December 2021.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:56:11.830" LastActivityDate="2021-12-27T23:56:11.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8403" PostTypeId="4" CreationDate="2021-12-27T23:56:11.830" Score="0" Body="Questions about or related to PyNAO the Python numerical orbital code." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:56:11.830" LastActivityDate="2021-12-27T23:56:11.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8404" PostTypeId="5" CreationDate="2021-12-27T23:56:52.567" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:56:52.567" LastActivityDate="2021-12-27T23:56:52.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8405" PostTypeId="4" CreationDate="2021-12-27T23:56:52.567" Score="0" Body="Questions about or related to fingerprints." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-27T23:56:52.567" LastActivityDate="2021-12-27T23:56:52.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8406" PostTypeId="2" ParentId="8307" CreationDate="2021-12-28T00:15:30.440" Score="8" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I will have to start looking next year into DFT techniques [...]&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;We have had some questions about how to get started on learning DFT here on this site before, and have received plenty of answers:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1046/5&quot;&gt;I am a beginner in DFT. What are some resources that could help me to learn the basics?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/388/5&quot;&gt;What are good resources to learn Materials Modeling?&lt;/a&gt; (this is about materials modeling, but the answers recommend some books useful for learning DFT).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1056/5&quot;&gt;How to write my own density functional theory (DFT) code in Python?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1053/5&quot;&gt;How to &amp;quot;get my feet wet&amp;quot; in Density Functional Theory by simulating a water molecule using Python&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Once you learn DFT, and electrochemistry, you can put the two together to &lt;em&gt;apply&lt;/em&gt; DFT to electrochemistry.&lt;/p&gt;&#xA;&lt;p&gt;Much of my quantum chemistry knowledge came from working on specific projects which involved &lt;em&gt;doing&lt;/em&gt; calculations. If you want to get a head start on the project that you're starting next year, I'd recommend to find the name of the electrochemical system that you want to simulate, and do a literature review of what DFT calculations have been done on the system in the past. Ideally you would have someone with experience in DFT working in your lab. If not, you can build your confidence by reproducing some of the DFT calculations in the papers you found during your literature review. For this you may want to first choose a software to use for your DFT calculations (perhaps Quantum ESPRESSO for free solid-state/periodic calculations or MRCC for calculations on separated molecules). When you get to more specific questions, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;how do I install this software?&amp;quot; or&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;why does this software not compile?&amp;quot; or&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;why is my input file in this software resulting in an error?&amp;quot; or&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;why do they use this functional instead of that one?&amp;quot; or&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;why are my calculated numbers not matching the ones in this paper?&amp;quot;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;you can ask them here (after first searching the site thoroughly for similar questions, so that the question doesn't get deleted as a duplicate).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-12-28T00:15:30.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8407" PostTypeId="5" CreationDate="2021-12-28T00:23:35.083" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-28T00:23:35.083" LastActivityDate="2021-12-28T00:23:35.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8408" PostTypeId="4" CreationDate="2021-12-28T00:23:35.083" Score="0" Body="Check other tags first! This tag isn't popular." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-28T00:23:35.083" LastActivityDate="2021-12-28T00:23:35.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8409" PostTypeId="5" CreationDate="2021-12-28T00:23:48.440" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-28T00:23:48.440" LastActivityDate="2021-12-28T00:23:48.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8410" PostTypeId="4" CreationDate="2021-12-28T00:23:48.440" Score="0" Body="Check other tags first! This one isn't popular." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-28T00:23:48.440" LastActivityDate="2021-12-28T00:23:48.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8411" PostTypeId="2" ParentId="6452" CreationDate="2021-12-28T02:09:36.367" Score="3" Body="&lt;p&gt;The &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiwfn&lt;/a&gt; software is capable to run hole-electron analysis to fully characterize electron excitations.&lt;/p&gt;&#xA;&lt;p&gt;From its manual:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The hole-electron analysis module of Multiwfn is quite powerful, it is&#xA;able to present very comprehensive characterization for all kinds of&#xA;electron excitations.&lt;br /&gt;&#xA;...&lt;br /&gt;&#xA;This very powerful module is used to analyze and visualize hole-electron distribution, transition density and transition electric/magnetic dipole moment density. Moreover, hole and electron can be decomposed to orbital pair contributions as well as atom and fragment contributions; furthermore, the atom/fragment contributions can be directly plotted as heat map for visual&#xA;inspection.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It uses different indices like local excitation (LE), single direction and centrosymmetric charge-transfer excitation (CT) and Rydberg.&lt;/p&gt;&#xA;&lt;p&gt;The Multiwfn is free to download and use.&lt;/p&gt;&#xA;&lt;p&gt;Here are some links:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Web site: &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Download (including manual): &lt;a href=&quot;http://sobereva.com/multiwfn/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/download.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;User forum: &lt;a href=&quot;http://sobereva.com/wfnbbs/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/wfnbbs/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-28T02:09:36.367" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8412" PostTypeId="1" AcceptedAnswerId="8413" CreationDate="2021-12-28T06:14:47.287" Score="10" ViewCount="2695" Body="&lt;p&gt;Upon creating the index file with &lt;code&gt;gmx make_ndx&lt;/code&gt;, we are usually&#xA;prompted with interactive shell.&lt;/p&gt;&#xA;&lt;p&gt;For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ gmx make_ndx -f em.gro -o index.ndx&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Will give:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  0 System              : 120070 atoms&#xA;  1 Protein             :  7132 atoms&#xA;  2 Protein-H           :  3818 atoms&#xA;  3 C-alpha             :   500 atoms&#xA;  4 Backbone            :  1500 atoms&#xA;  5 MainChain           :  2001 atoms&#xA;  6 MainChain+Cb        :  2463 atoms&#xA;  7 MainChain+H         :  2472 atoms&#xA;  8 SideChain           :  4660 atoms&#xA;  9 SideChain-H         :  1817 atoms&#xA; 10 Prot-Masses         :  7132 atoms&#xA; 11 non-Protein         : 112938 atoms&#xA; 12 Other               :   446 atoms&#xA; 13 PEP                 :   446 atoms&#xA; 14 NA                  :   156 atoms&#xA; 15 CL                  :   112 atoms&#xA; 16 Water               : 112224 atoms&#xA; 17 SOL                 : 112224 atoms&#xA; 18 non-Water           :  7846 atoms&#xA; 19 Ion                 :   268 atoms&#xA; 20 PEP                 :   446 atoms&#xA; 21 NA                  :   156 atoms&#xA; 22 CL                  :   112 atoms&#xA; 23 Water_and_ions      : 112492 atoms&#xA;&#xA; nr : group      '!': not  'name' nr name   'splitch' nr    Enter: list groups&#xA; 'a': atom       '&amp;amp;': and  'del' nr         'splitres' nr   'l': list residues&#xA; 't': atom type  '|': or   'keep' nr        'splitat' nr    'h': help&#xA; 'r': residue              'res' nr         'chain' char&#xA; &amp;quot;name&amp;quot;: group             'case': case sensitive           'q': save and quit&#xA; 'ri': residue index&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then manually I have to do this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Choosing &amp;quot;1 Protein&amp;quot; and &amp;quot;13 PEP&amp;quot; when prompted&#xA;&amp;gt; 1 | 13&#xA;&amp;gt; q&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I by-pass that by issuing &lt;em&gt;just one&lt;/em&gt; command line?&#xA;I tried this but failed:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ echo &amp;quot;1 | 13&amp;quot; | gmx make_ndx -f em.gro -o index.ndx&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2021-12-28T06:21:32.380" LastActivityDate="2022-03-22T18:16:07.283" Title="How to perform &quot;gmx make_ndx&quot; with single command line bypassing the interactive shell?" Tags="|molecular-dynamics|gromacs|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8413" PostTypeId="2" ParentId="8412" CreationDate="2021-12-28T08:05:21.497" Score="7" Body="&lt;p&gt;Note: there's nothing specific to Gromacs in the answer below. These are just shell scripting techniques that are relevant to any program that takes input from &lt;code&gt;stdin&lt;/code&gt;. For cases where I know that colleagues have needed this with Gromacs, we've used the first option listed below (heredoc). FWIW, I didn't test either of these with Gromacs, but they should work.&lt;/p&gt;&#xA;&lt;h2&gt;1. Heredoc&lt;/h2&gt;&#xA;&lt;p&gt;A very common way to make an interactive program into a script is by using &lt;a href=&quot;https://en.wikipedia.org/wiki/Here_document&quot; rel=&quot;noreferrer&quot;&gt;heredoc&lt;/a&gt; format. This allows you to write a shell script that acts as if it was receiving the input within the heredoc. In particular, people use heredoc for exactly this purpose with Gromacs. This is particularly useful if you're using this as one step among several in a workflow, and you'd like the whole workflow to be in a script.&lt;/p&gt;&#xA;&lt;p&gt;You use heredoc within another scripting language. Most shell scripting languages support it. With &lt;code&gt;sh&lt;/code&gt;, you should be able to write a script that looks something like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;#!/bin/sh&#xA;&#xA;# This is in the file heredoc.sh&#xA;&#xA;gmx make_ndx -f em.gro -o index.ndx &amp;lt;&amp;lt; EOF&#xA;1 | 13&#xA;q&#xA;EOF&#xA;&#xA;# don't forget the line with q to quit and save!&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you run that script as &lt;code&gt;sh heredoc.sh&lt;/code&gt;. Here I chose the text &lt;code&gt;EOF&lt;/code&gt; as a marker, but that is up to you -- any text is allowed, but it must bracket the start and end of the input section. &lt;a href=&quot;https://tldp.org/LDP/abs/html/here-docs.html&quot; rel=&quot;noreferrer&quot;&gt;Here's some more documentation&lt;/a&gt; on heredocs.&lt;/p&gt;&#xA;&lt;p&gt;This is a generic shell scripting technique; not at all specific to Gromacs. I can write a little Python program that takes the same inputs as a sort of &amp;quot;pretend&amp;quot; &lt;code&gt;gmx make_ndx&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# myscript.py&#xA;indices = input()&#xA;quit = input()&#xA;assert quit == &amp;quot;q&amp;quot;&#xA;print('indices = ', indices)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and a heredoc based shell script:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;python myscript.py &amp;lt;&amp;lt; EOF&#xA;1 | 13&#xA;q&#xA;EOF&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And then:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;$ sh heredoc.sh&#xA;indices =  1 | 13&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;2. Keep the inputs in a separate file (&lt;a href=&quot;https://fsl.fmrib.ox.ac.uk/fslcourse/unix_intro/io.html&quot; rel=&quot;noreferrer&quot;&gt;input redirection&lt;/a&gt;)&lt;/h2&gt;&#xA;&lt;p&gt;You can also keep a separate file with the inputs. In the file &lt;code&gt;inputs.txt&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1 | 13&#xA;q&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then &lt;code&gt;gmx make_ndx -f em.gro -o index.ndx &amp;lt; inputs.txt&lt;/code&gt; should work. Using my python script above:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-none prettyprint-override&quot;&gt;&lt;code&gt;$ python myscript.py &amp;lt; inputs.txt&#xA;indices =  1 | 13&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h2&gt;When to use each&lt;/h2&gt;&#xA;&lt;p&gt;Use heredoc if this is part of a bigger script, or if the input data is closely associated with the program (only to be used once). Use input redirection if the input is distinct from the program or likely to be reused. In your use case, I would usually use heredoc.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2021-12-28T08:22:39.027" LastActivityDate="2021-12-28T08:22:39.027" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8414" PostTypeId="2" ParentId="8412" CreationDate="2021-12-28T08:33:54.230" Score="7" Body="&lt;p&gt;How about this, also writes to a log file. This selects both group 1 and group 13 and write the indices to a index file (index.ndx)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo -e &amp;quot;1|13\nq&amp;quot;| gmx make_ndx -f em.gro -o index.ndx|&amp;amp; tee -a youlogfile.log&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="4475" LastEditDate="2021-12-29T13:21:34.123" LastActivityDate="2021-12-29T13:21:34.123" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="8415" PostTypeId="1" CreationDate="2021-12-28T09:01:53.807" Score="8" ViewCount="53" Body="&lt;p&gt;I want to study the effect of different mediums, gas and various solvents, on the energy of the 10th highest molecular orbital of multiple quinones, which I obtained by a Gaussian software calculation. I already have these energies in each case, but I do not know how to compare them. I was thinking about using a python program to sort them for every molecular orbital. But even if I will do so, I do not know how to analyze the result afterward.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can you suggest a way to study the effect of solvation on the molecular orbital energies of these systems? Can you recommend a book or an article about this?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="5" LastEditDate="2022-01-20T22:54:49.000" LastActivityDate="2022-01-20T22:54:49.000" Title="The effect of different mediums on the molecular orbital energies" Tags="|reference-request|molecular-interactions|solvation|energy|" AnswerCount="0" CommentCount="6" ClosedDate="2023-02-01T03:48:34.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="8416" PostTypeId="1" CreationDate="2021-12-28T15:12:32.830" Score="6" ViewCount="318" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{TiCoSb}$&lt;/span&gt; has Wyckoff position as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Ti  Ti          0.25000    0.25000    0.25000    1.000    0.050    4c      -43m&#xA; Co  Co          0.00000    0.00000    0.00000    1.000    0.050    4a      -43m&#xA; Sb  Sb          0.75000    0.75000    0.75000    1.000    0.050    4d      -43m&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want to know the position of 4 Ti atoms, as I want to try to do basic calculation substituting each position of Ti for alloying.&lt;/p&gt;&#xA;&lt;p&gt;I don't want to use supercell as that would increase time of calculations and I don't have that much capacity in my PC.&#xA;&lt;strong&gt;Please help me to identify these positions.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want to keep the number of atoms to no more than 6.&#xA;My current understanding is that I have to remove symmetry to get to know these positions.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="7" LastEditDate="2021-12-28T15:31:28.673" LastActivityDate="2021-12-28T16:14:38.727" Title="What Wyckoff position to put in Input file of Unit Cell of TiCoSb?" Tags="|quantum-espresso|solid-state-physics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8417" PostTypeId="2" ParentId="8416" CreationDate="2021-12-28T16:14:38.727" Score="4" Body="&lt;p&gt;You can use the &lt;a href=&quot;https://www.cryst.ehu.es/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Bilbao Crystallographic Server&lt;/strong&gt;&lt;/a&gt;. Then open (click) on the first menu &lt;strong&gt;Space-group symmetry&lt;/strong&gt; and click on the &lt;a href=&quot;https://www.cryst.ehu.es/cryst/get_wp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;WYCKPOS&lt;/strong&gt;&lt;/a&gt; menu to go to the Wyckoff Positions of Space Groups.&lt;/p&gt;&#xA;&lt;p&gt;There you put the space group number and the server will return the corresponding Wyckoff positions.&lt;/p&gt;&#xA;&lt;p&gt;Just in between...  Working with alloy demands supercell in order to obtain physically manful results. Only 6 atoms will return meaningless results.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.cryst.ehu.es/cryst/get_wp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.cryst.ehu.es/cryst/get_wp.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-28T16:14:38.727" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8419" PostTypeId="2" ParentId="6894" CreationDate="2021-12-28T19:07:46.937" Score="3" Body="&lt;p&gt;In general ,&lt;code&gt;SQS&lt;/code&gt; changes shape of cell to find best quasi random structure, here you are trying for an orthogonal cell, but as output you are getting non-orthogonal cell. In order to get SQS structure with constrained cell, use following method&lt;/p&gt;&#xA;&lt;p&gt;Run mcsqs -n xx. Stop the mcsqs process as soon as it&#xA;generates the sqscell.out file.&#xA;Trim the sqscell.out file, and leave only cell shapes which have equal lattice vector lengths. If many cells have equal lengths, only use those with the shortest lengths, because it means they are the closest to a cubic shape.&#xA;Restart mcsqs -rc&#xA;For example, if we want to build a 2-2-2 fcc supercell with 32 atoms, we can define the &lt;code&gt;sqscell.out &lt;/code&gt;as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1&#xA;&#xA;2 0 0&#xA;0 2 0&#xA;0 0 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://cniu.me/2017/08/05/SQS.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://cniu.me/2017/08/05/SQS.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2021-12-28T19:07:46.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8420" PostTypeId="1" AcceptedAnswerId="8450" CreationDate="2021-12-28T21:37:07.490" Score="9" ViewCount="225" Body="&lt;p&gt;I want to find the Cauchy stress tensor in certain materials with &lt;em&gt;ab initio&lt;/em&gt; methods. I already have the analytical form of my own definition of &amp;quot;energy&amp;quot; and &amp;quot;forces&amp;quot; (not from DFT), and I now wonder how to derive the stress tensor from them? I've checked &lt;em&gt;Kittel's Intro to Solid State Physics&lt;/em&gt; and &lt;em&gt;Lautrup's Physics of Continuous Matter&lt;/em&gt;, but it's not discussed there.&lt;/p&gt;&#xA;&lt;p&gt;Any recommendation for the right reference to this specific problem? It can be a DFT textbook if it has some detailed discussion in it about how to obtain the Cauchy stress tensor from a DFT energy and forces.&lt;/p&gt;&#xA;&lt;p&gt;Dr. Clark's &lt;a href=&quot;http://cmt.dur.ac.uk/sjc/Castep_Lectures2/lecture14.PDF&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASTEP workshop lecture 14&lt;/a&gt; seems to have the answer to my question on page 7. But I'm still a little bit confused on how to implement Hellman-Feynman Theorem to get the stress tensor.&lt;/p&gt;&#xA;" OwnerUserId="3848" LastEditorUserId="7" LastEditDate="2021-12-29T15:41:06.247" LastActivityDate="2022-01-01T03:38:17.863" Title="How to find the Cauchy stress tensor in solids using ab-initio methods?" Tags="|ab-initio-calculations|solid-state-physics|physical-properties-of-materials|materials-engineering|stress-strain|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8421" PostTypeId="2" ParentId="8359" CreationDate="2021-12-28T21:42:35.197" Score="11" Body="&lt;p&gt;Only a half answer (bond lengths), but maybe interesting for people working with the RDKit.&lt;/p&gt;&#xA;&lt;p&gt;The code was written in a Jupyter Noteboook.&lt;/p&gt;&#xA;&lt;p&gt;Calculate the 3D shape of a molecule for the bond lengths and the 2D shape for the depiction.&lt;/p&gt;&#xA;&lt;p&gt;Get the bond lengths and add them to the 2D structure.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import AllChem as Chem&#xA;from rdkit.Chem import rdMolTransforms&#xA;from rdkit.Chem.Draw import rdMolDraw2D, rdDepictor, IPythonConsole&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from IPython.display import Image&#xA;&#xA;smiles = 'Nc1cc2[nH]cc(C(=O)O)c(=O)c2cc1F'&#xA;&#xA;# 3D for lengths&#xA;mol3d = Chem.AddHs(Chem.MolFromSmiles(smiles))&#xA;Chem.EmbedMolecule(mol3d, randomSeed=42)&#xA;Chem.MMFFOptimizeMolecule(mol3d)&#xA;&#xA;# 2D for depiction&#xA;mol2d = Chem.AddHs(Chem.MolFromSmiles(smiles))&#xA;rdDepictor. Compute2DCoords(mol2d)&#xA;&#xA;bonds = [(x.GetBeginAtomIdx(), x.GetEndAtomIdx()) for x in mol3d.GetBonds()]&#xA;&#xA;conf = mol3d.GetConformer()&#xA;&#xA;b_lengths = []&#xA;&#xA;for b in bonds:&#xA;    bl = rdMolTransforms.GetBondLength(conf,b[0],b[1])&#xA;    b_lengths.append(str(round(bl,2)))&#xA;&#xA;d = rdMolDraw2D.MolDraw2DCairo(600, 400)&#xA;&#xA;for n in range(len(b_lengths)):&#xA;    mol2d.GetBondWithIdx(n).SetProp('bondNote', b_lengths[n])&#xA;&#xA;d.DrawMolecule(mol2d)&#xA;d.FinishDrawing()&#xA;d.WriteDrawingText('bonds.png')&#xA;Image('bonds.png')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WZXUb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WZXUb.png&quot; alt=&quot;bondlenhths&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2021-12-28T21:42:35.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8422" PostTypeId="2" ParentId="8293" CreationDate="2021-12-29T01:43:54.173" Score="6" Body="&lt;p&gt;I don't know any VASP-specific details, but the basic answer is that the three versions are almost identical, and solve the same equations in the same way. If we take vasp_std as the reference, then the differences are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;vasp_gam&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If your system has time-reversal symmetry (true for most simulations), then &lt;span class=&quot;math-container&quot;&gt;$+k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-k$&lt;/span&gt; are symmetry-related and we can restrict our calculation to just one half of the Brillouin Zone. At the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point, &lt;span class=&quot;math-container&quot;&gt;$k=(0,0,0)$&lt;/span&gt; and so &lt;span class=&quot;math-container&quot;&gt;$+k=-k$&lt;/span&gt;; in this case, time-reversal symmetry relates &lt;span class=&quot;math-container&quot;&gt;$+G$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$-G$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; is a reciprocal lattice vector. This means that the plane-wave coefficients &lt;span class=&quot;math-container&quot;&gt;$c(G)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c(-G)$&lt;/span&gt; are related by symmetry (in fact, they are the complex conjugate of each other). Thus, if we're using the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point we only need to consider half of the plane-waves explicitly, and we can generate the rest by symmetry. This halves the memory requirements of the calculation, and makes the calculation go twice as quickly.&lt;/p&gt;&#xA;&lt;p&gt;One consequence of this symmetry between &lt;span class=&quot;math-container&quot;&gt;$+G$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$-G$&lt;/span&gt; is that the wavefunctions in real-space can be made to have zero imaginary components -- i.e. entirely real. This means that any inner product or Hermitian matrix element must also be real, since we could calculate them in real-space if we wanted and now everything is real there. Thus, whenever we calculate a matrix element we only need to bother computing the real part, since we already know that the imaginary part will be zero; this reduces the time to compute matrix elements by an &lt;em&gt;additional&lt;/em&gt; factor of two.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps the best part, is that the cubically scaling parts of the calculation, such as orthogonalisation of the Kohn-Sham wavefunction, now involves cubically scaling steps on a real matrix, whereas before they were complex. These operations are now &lt;span class=&quot;math-container&quot;&gt;$2^3=8$&lt;/span&gt; times faster, meaning that the asymptotic speed-up when using the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point version is x8.&lt;/p&gt;&#xA;&lt;p&gt;NB A slightly more subtle, but very similar symmetry argument can be made for points at the boundary of the Brillouin Zone (&lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt;-points etc) and some DFT software can also exploit that, e.g. ABINIT.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;vasp_ncl&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Spin-orbit coupling is a relativistic effect which is included in the external potential in the (electronic) Kohn-Sham equations, and hence enters via the pseudopotential term in VASP and similar programs (e.g. ABINIT, CASTEP or Quantum Espresso). The pseudopotential generator has to solve an atomic Dirac-like equation now, not a Schroedinger-like one, and this means that the solutions are spinors. A full solution needs 4-component spinors, but in fact for ground state calculations the major components are so large compared to the minor ones, that 2-component spinors suffice for the valence states. The Kohn-Sham wavefunctions thus have twice the plane-wave coefficients as in a &amp;quot;normal&amp;quot; calculation, and require twice the memory storage.&lt;/p&gt;&#xA;&lt;p&gt;The usual approach to handling the spin-orbit interaction is from &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.71.115106&quot; rel=&quot;nofollow noreferrer&quot;&gt;dal Corso and Conte&lt;/a&gt;, and moves all the spin-orbit terms into the non-local pseudopotential projectors; this has the consequence that the local pseudopotential term must &lt;em&gt;not&lt;/em&gt; be for a chemically-relevant angular-momentum channel. The pseudopotential projectors now depend not on the orbital angular momentum &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; directly, but on the total angular momentum &lt;span class=&quot;math-container&quot;&gt;$j=l+s$&lt;/span&gt;. This requires there to be at least twice as many pseudopotential projectors for a spin-orbit pseudopotential, as for a &amp;quot;normal&amp;quot; pseudopotential.&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham valence wavefunctions are 2-component spinors, so they gain a spinor index in addition to the plane-wave, band and k-point indices (NB there is no &lt;span class=&quot;math-container&quot;&gt;$s_z$&lt;/span&gt; index, since &lt;span class=&quot;math-container&quot;&gt;$s_z$&lt;/span&gt; is no longer a good quantum number and spin is entirely described by the spinors). Inner products now have to be calculated by summing over spinor indices as well, e.g.,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{1}&#xA;\langle \psi_{bk}\vert\phi_{b^\prime k}\rangle =&amp;amp; \sum_{\sigma} \int \psi_{b\sigma k}^\ast(r)\phi_{b^\prime\sigma k}(r)d^3 r. &#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that we only needed one spinor index here, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, because the spinor basis is orthogonal and we only wanted the inner product.&lt;/p&gt;&#xA;&lt;p&gt;For matrix elements the situation is more complicated, because some interactions do couple different spinor components, and so they gain &lt;em&gt;two&lt;/em&gt; spinor indices, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma^\prime$&lt;/span&gt;. Perhaps the simplest example is actually not a matrix element exactly, but the spin-density-matrix &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;, which becomes,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{2}&#xA;\rho_{\sigma \sigma^\prime}(r)=\sum_{bk} \psi_{b\sigma k}^\ast(r)\psi_{b\sigma^\prime k}(r).&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The trace of this matrix over the spinor components is the usual charge density, but the other elements describe the spin, which may now point in any direction in real-space -- i.e. it is a vector. (You can calculate the components of spin in any particular direction using the &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; Pauli spin matrices acting on this density matrix.)&lt;/p&gt;&#xA;&lt;p&gt;The addition of two spinor indices to several key objects in the Kohn-Sham scheme means that for large calculations the computational cost is 8 times that of a &amp;quot;normal&amp;quot; calculation (4 times compared to a collinear-spin calculation).&lt;/p&gt;&#xA;&lt;p&gt;(Note that in the presence of spin-orbit coupling, the Kohn-Sham states are complex in real-space even at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point, unless the spin is aligned along &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; everywhere.)&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2021-12-30T00:22:41.187" LastActivityDate="2021-12-30T00:22:41.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8423" PostTypeId="1" CreationDate="2021-12-29T02:51:46.303" Score="7" ViewCount="106" Body="&lt;p&gt;I need to generate the XANES region spectra of the Pt L3 edge of a theoretical Pt6 crystal with adsorbed atoms/molecules, such as &lt;span class=&quot;math-container&quot;&gt;$\ce{Pt(H^*), Pt(O^*), Pt(OH^*),Pt(CO^*)}$&lt;/span&gt;. It is for generating theoretical reference XANES spectra as described in &lt;a href=&quot;https://doi.org/10.1039/b927120c&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, based on what I have read, I would need the FEFF8 code but I only have access to FEFF8-lite (free version, limited to EXAFS analysis) and the Demeter package which is for analysis of experimental data, if I'm not mistaken. Is there an alternative software (free) or method to generate or calculate a theoretical XANES spectra?&lt;/p&gt;&#xA;" OwnerUserId="4734" LastEditorUserId="142" LastEditDate="2021-12-29T16:52:15.443" LastActivityDate="2022-06-02T15:36:17.003" Title="XANES simulation software/code besides FEFF for Pt L3 edge?" Tags="|crystallography|spectroscopy|adsorption|feff|heavy-elements|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8424" PostTypeId="5" CreationDate="2021-12-29T03:08:43.993" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://monalisa.phys.washington.edu/feffproject-feff.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://monalisa.phys.washington.edu/feffproject-feff.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-29T03:08:43.993" LastActivityDate="2021-12-29T03:08:43.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8425" PostTypeId="4" CreationDate="2021-12-29T03:08:43.993" Score="0" Body="Questions about or related to The FEFF (Standing for &quot;f_effective&quot;) Code." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-29T03:08:43.993" LastActivityDate="2021-12-29T03:08:43.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8426" PostTypeId="1" CreationDate="2021-12-29T05:39:29.850" Score="10" ViewCount="89" Body="&lt;p&gt;I'm wondering what are the typical examples (experiments) for magnetic dipole transitions and electric quadrupole transitions in crystals?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2021-12-31T01:32:59.727" Title="Optical spectra beyond electric dipole approximation" Tags="|optical-properties|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8427" PostTypeId="2" ParentId="6835" CreationDate="2021-12-29T13:05:32.627" Score="3" Body="&lt;p&gt;I got the answer to this question on the GROMACS forum which can be found &lt;a href=&quot;https://gromacs.bioexcel.eu/t/ensemble-for-viscosity-calculation-in-non-equilibrium-md/2948/3&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the thermostat influence in the non-equilibrium cosine perturbation approach is automatically taken care by GROMACS, which biases termperature rescaling based on the velocity profile of fluid particles.&#xA;However, some thermostats will introduce additional ‘artificial’ viscosity, so your reasoning is correct, I believe. However, from a practical standpoint I don’t see the reason why one would want to compute a nominal value of viscosity from a NVE simulation, mainly because of two reasons:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;production runs are rarely NVE, so you would want to use a consistent value for viscosity (and the one from NVE would be incorrect).&lt;/li&gt;&#xA;&lt;li&gt;viscosity itself is a function of temperature, so I’m not sure if it makes sense from a purely physical standpoint to estimate if by fixing the total energy, rather than temperature.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;When it comes to pressure, as far as I know it may be problematic to estimate viscosity from equilibrium NPT simulations (you want the cell volume not to fluctuate in order for the Green-Kubo formula to converge). I am not sure about non-equilibrium though; probably volume fluctuations are not a problem in NE.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="148" LastActivityDate="2021-12-29T13:05:32.627" CommentCount="1" CommunityOwnedDate="2021-12-29T15:12:08.293" ContentLicense="CC BY-SA 4.0" />
  <row Id="8428" PostTypeId="1" CreationDate="2021-12-29T13:34:11.257" Score="9" ViewCount="615" Body="&lt;p&gt;What's the suggested best practice to simulate peptide solubility?&#xA;I'm considering to use Gromacs &lt;a href=&quot;http://www.mdtutorials.com/gmx/lysozyme/index.html&quot; rel=&quot;noreferrer&quot;&gt;Tutorial Lysozyme in Water&lt;/a&gt; as the model.&lt;/p&gt;&#xA;&lt;p&gt;Later, I'm considering to use &lt;a href=&quot;http://www.mdtutorials.com/gmx/lysozyme/10_analysis2.html&quot; rel=&quot;noreferrer&quot;&gt;Radius of Gyration&lt;/a&gt; as measure of solubility?&lt;/p&gt;&#xA;&lt;p&gt;Is it a reasonable approach? Or is there a better way?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastActivityDate="2022-01-12T03:53:57.817" Title="How to simulate peptide solubility using molecular dynamics (GROMACS)?" Tags="|molecular-dynamics|gromacs|solubility|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8429" PostTypeId="1" AcceptedAnswerId="8430" CreationDate="2021-12-29T13:44:36.637" Score="8" ViewCount="212" Body="&lt;p&gt;I am trying to calculate the UV-visible spectrum of p-benzoquinone. In the literature, the point group of p-benzoquinone is &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;, but when I optimize this molecule in the ground state with Gaussian software, I obtain the &lt;span class=&quot;math-container&quot;&gt;$C_s$&lt;/span&gt; group symmetry.&lt;/p&gt;&#xA;&lt;p&gt;I used a semi-empirical method &lt;code&gt;# opt freq am1 geom=connectivity&lt;/code&gt;, than used this geometry as starting point for a DFT calculation &lt;code&gt;# opt freq rb3lyp geom=connectivity&lt;/code&gt; and than &lt;code&gt;# opt freq rb3lyp/6-31g(d) geom=connectivity&lt;/code&gt;. I tried changing the z-matrix, but I still have a &lt;span class=&quot;math-container&quot;&gt;$C_s$&lt;/span&gt; group.&lt;/p&gt;&#xA;&lt;p&gt;Is there any fault with my calculation? What can I do to have a &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; symmetry? If I use the &lt;span class=&quot;math-container&quot;&gt;$C_s$&lt;/span&gt; geometry I obtained, will the UV-visible absorption spectrum be false?&lt;/p&gt;&#xA;&lt;p&gt;Here are the links to the out-log files of my calculations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://drive.google.com/file/d/1oE6Gj0P7NawOCBdhweul_XokvbEiSsIP/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/file/d/1oE6Gj0P7NawOCBdhweul_XokvbEiSsIP/view?usp=sharing&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://drive.google.com/file/d/1y3XzXK44mrWA1MwwMwHvH_cRLiCUJhG3/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/file/d/1y3XzXK44mrWA1MwwMwHvH_cRLiCUJhG3/view?usp=sharing&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://drive.google.com/file/d/1vvwnsNQE7mvehOLkiZbNaSk56rfgTjrM/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/file/d/1vvwnsNQE7mvehOLkiZbNaSk56rfgTjrM/view?usp=sharing&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://drive.google.com/file/d/1KPQEN01VQk1ObaOjhwLNndbbLQdM-ZRJ/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;https://drive.google.com/file/d/1KPQEN01VQk1ObaOjhwLNndbbLQdM-ZRJ/view?usp=sharing&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="7" LastEditDate="2021-12-29T14:12:51.337" LastActivityDate="2021-12-29T15:25:49.897" Title="Symmetry group of p-benzoquinone" Tags="|molecular-modeling|gaussian|geometry-optimization|symmetry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8430" PostTypeId="2" ParentId="8429" CreationDate="2021-12-29T15:25:49.897" Score="9" Body="&lt;p&gt;&lt;strong&gt;tldr: For a UV/Vis spectra, it shouldn't matter much.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've found that Gaussian's AM1 / PM3 implementation often breaks symmetry during optimization. So I'm not surprised at your finding.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, in many cases, it's good to start with the expected symmetry geometry. For example, if I open the output in Avogadro, I can use Properties =&amp;gt; Symmetry =&amp;gt; Symmetrize to correct to &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; .. it seems very, very close. GaussView has a similar feature, as do many other interfaces (WebMO, etc.)&lt;/p&gt;&#xA;&lt;p&gt;As mentioned in the comment, optimizations can break symmetry. &lt;a href=&quot;https://gaussian.com/symmetry/&quot; rel=&quot;noreferrer&quot;&gt;In Gaussian&lt;/a&gt;, you can use, e.g.:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Symm=(Loose,Follow)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This loosens the symmetry perception in the initial step and requests that the point group (hopefully &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;) is retained during optimization.&lt;/p&gt;&#xA;&lt;p&gt;When you convert to a z-matrix, you can also force a symmetry by using symbolic notation to ensure corresponding bonds and angles are kept equivalent. The &lt;a href=&quot;https://gaussian.com/zmat/&quot; rel=&quot;noreferrer&quot;&gt;documentation gives the example of hydrogen peroxide&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H&#xA;O 1 R1&#xA;O 2 R2 1 A&#xA;H 3 R1 2 A 1 D&#xA;  Variables:&#xA;R1 0.9&#xA;R2 1.4&#xA;A 105.0&#xA;D 120.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice that the two H-O-O angles are defined as the same variable (A), and the H-O bond lengths are defined as identical (R1), ensuring symmetry no matter the optimized values.&lt;/p&gt;&#xA;&lt;p&gt;It's a bit tedious, but you could do this for your benzoquinone. It looks like some of the bond angles are a tiny bit off, which is why Gaussian has optimized it into the &lt;span class=&quot;math-container&quot;&gt;$C_s$&lt;/span&gt; point group.&lt;/p&gt;&#xA;&lt;p&gt;Your question, though, is whether it will matter for UV/Vis spectra. In my experience, due to orbital symmetry, you might see some issues with excitation intensities (i.e., transitions that might be &amp;quot;forbidden&amp;quot; in the higher symmetry, but weak in the low-symmetry group). But in real life, molecules are dynamic, leading to such symmetry breaking anyway. So a symmetry-forbidden UV/Vis transition is usually just a weak excitation in an experimental spectra.&lt;/p&gt;&#xA;&lt;p&gt;I'd worry much more about getting an accurate geometry and potential errors in your choice of methods. I don't remember G09 that well, but you should try to use a larger basis set (e.g., def2-TZVP) and ideally a dispersion-corrected functional (B3LYP-D3BJ if you want B3LYP) for the geometry. I'd also look at different methods for your TD-DFT calculations. This will matter more than a geometry in a symmetric subgroup.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2021-12-29T15:25:49.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8432" PostTypeId="2" ParentId="8428" CreationDate="2021-12-29T17:06:05.600" Score="11" Body="&lt;p&gt;I'm not sure why you would use radius for gyration as a measure of solubility. Radius of gyration roughly measures how &amp;quot;unfolded&amp;quot; (or more accurately, how &amp;quot;stretched out&amp;quot;) a polymer is. Although this may correspond to a higher &lt;a href=&quot;https://en.wikipedia.org/wiki/Accessible_surface_area&quot; rel=&quot;noreferrer&quot;&gt;solvent accessible surface area&lt;/a&gt; (which can itself be calculated and is useful in some cases), it has nothing to do with solubility.&lt;/p&gt;&#xA;&lt;p&gt;If you want solubility, you'll likely want the &lt;strong&gt;free energy of solvation&lt;/strong&gt;, or, as it is called when water is the solvent, the &lt;strong&gt;free energy of hydration&lt;/strong&gt;. Alchemical free energy methods are one family of tools that have been useful for calculating these quantities.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jced.7b00104&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt; (full text &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648357/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) compares experimental and simulated hydration free energies for several hundred small molecules. It describes the protocol used, and files to reproduce the simulations are available in the SI and &lt;a href=&quot;https://github.com/mobleylab/FreeSolv&quot; rel=&quot;noreferrer&quot;&gt;on GitHub&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;References within that paper, in particular in the section titled &amp;quot;Hydration and solvation free energies have a range of applications&amp;quot;, may be useful to point you situations more analogous to the specific experimental comparison you have in mind.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2021-12-29T17:06:05.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8433" PostTypeId="2" ParentId="8336" CreationDate="2021-12-29T23:44:25.333" Score="4" Body="&lt;p&gt;The cause to use restrains is due to a previous knowledge (i.e. experimental) of system behavior/characteristics that you want to include/retain/reproduce in your simulations.&lt;/p&gt;&#xA;&lt;p&gt;In the case of protein-ligand complex simulations, they encode specifically prior knowledge about the macromolecular system to be simulated and is built of several components. These include the following&lt;sup&gt;1,2&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(i) Stereochemical information (e.g. bond distances, angles) about the constituent blocks (e.g. amino acids, nucleic acids) of macromolecules and the covalent links between them.&lt;/p&gt;&#xA;&lt;p&gt;(ii) The internal consistency of macromolecules (e.g. non-crystallographic symmetry, if present).&lt;/p&gt;&#xA;&lt;p&gt;(iii) Additional structural knowledge (similarity to known structures, current interatomic distances or secondary-structure elements etc.).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Another use of restrains is when refining the structure of macromolecule–ligand complexes using X-Ray crystallographic&lt;sup&gt;1&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The process of generating a set of restraints, or ‘dictionary’, for a&#xA;small molecule involves (i) taking a description of the molecule as an&#xA;input, (ii) processing its description to derive atom energy types and&#xA;connectivities, and finally (iii) using this information to generate&#xA;an idealized set of coordinates to allow fitting of the ligand to&#xA;electron density and a list of geometric restraints with associated&#xA;weights to allow the fitted ligand to be refined.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This can be think as similar when you run a molecular docking inside the active site region only instead of running a blind docking. Here, the active site is the most important region of the enzyme as it directly catalyzes the chemical reaction&lt;sup&gt;3&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The effect of restrains in simulations should be studied comparing its effects in the system free energy and entropy&lt;sup&gt;4&lt;/sup&gt;.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;br /&gt;&#xA;(1) R.A. Steinera, and J.A. Tucker. &lt;em&gt;Keep it together: restraints in crystallographic refinement of macromolecule–ligand complexes&lt;/em&gt;. Acta Crystallogr. D Struct. Biol. 73(Pt 2): 93–102 (2017). (DOI: &lt;a href=&quot;https://dx.doi.org/10.1107%2FS2059798316017964&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1107/S2059798316017964&lt;/a&gt;)&lt;br /&gt;&#xA;(2) A. Sali, T.L. Blundell. &lt;em&gt;Comparative protein modelling by satisfaction of spatial restraints&lt;/em&gt;.  J. Mol. Biol. 234, 779-815 (1993). (DOI: &lt;a href=&quot;https://dx.doi.org/10.1006/jmbi.1993.1626&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1006/jmbi.1993.1626&lt;/a&gt;)&lt;br /&gt;&#xA;(3) &lt;a href=&quot;https://en.wikipedia.org/wiki/Active_site&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Active_site&lt;/a&gt;&lt;br /&gt;&#xA;(4) G. Heinzelmann, PhD Thesis. Computational Studies of Glutamate Transporters and Receptors, 2014. (&lt;a href=&quot;https://ses.library.usyd.edu.au/bitstream/handle/2123/12299/2014_Germano_Heinzelmann_Thesis.pdf?sequence=2&amp;amp;isAllowed=yA&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2021-12-29T23:44:25.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8434" PostTypeId="1" CreationDate="2021-12-30T03:22:18.933" Score="5" ViewCount="583" Body="&lt;p&gt;I'm getting an error when trying to perform a relax calculation for &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; on &lt;span class=&quot;math-container&quot;&gt;$221$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt;.&#xA;I have tried changing &lt;code&gt;conv_thr&lt;/code&gt; and &lt;code&gt;etot_conv_thr&lt;/code&gt; but again the output shows &lt;code&gt;SCF correction compared to forces is large: reduce conv_thr to get better values&lt;/code&gt;. I have included the input and the relevent section of the output below.&lt;/p&gt;&#xA;&lt;h2&gt;Input&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation='relax', &#xA;  restart_mode = 'from_scratch',&#xA;  prefix       = 'MoS2', &#xA;  pseudo_dir='./',&#xA;  outdir       = './perHSout',  &#xA;  verbosity='high',&#xA;  tprnfor=.true., &#xA;  forc_conv_thr=1.0d-4,&#xA;  etot_conv_thr = 1d-8, &#xA;  nstep=100,  &#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0,&#xA;  nat= 14,&#xA;  ntyp= 3,&#xA;  nbnd = 100,&#xA;  input_dft = 'pbe'   &#xA;  occupations = 'smearing', &#xA;  smearing = 'gauss', &#xA;  degauss = 1.0d-2,&#xA;  ecutwfc = 80, &#xA;  ecutrho = 640,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-8&#xA;  mixing_beta = 0.5d0&#xA;  diagonalization  ='cg',&#xA;/&#xA;&amp;amp;IONS&#xA;  ion_dynamics = 'damp',&#xA;/&#xA;ATOMIC_SPECIES&#xA;  Mo 95.94 Mo.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;  S 32.066 S.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;  H 1.00794 H.pbe-rrkjus_psl.1.0.0.UPF &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;OUTPUT&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt; Forces acting on atoms (cartesian axes, Ry/au):&#xA;&#xA; atom    1 type  2   force =    -0.00000000   -0.00006340    0.00008063&#xA; atom    2 type  2   force =     0.00000000    0.00000000    0.00002999&#xA; atom    3 type  2   force =    -0.00005490    0.00003170    0.00008063&#xA; atom    4 type  2   force =     0.00005490    0.00003170    0.00008063&#xA; atom    5 type  1   force =    -0.00002689   -0.00001553    0.00003083&#xA; atom    6 type  1   force =     0.00002689   -0.00001553    0.00003083&#xA; atom    7 type  1   force =     0.00000000    0.00000000   -0.00001622&#xA; atom    8 type  1   force =     0.00000000    0.00003105    0.00003083&#xA; atom    9 type  2   force =    -0.00000000   -0.00003835   -0.00009142&#xA; atom   10 type  2   force =     0.00000000    0.00000000   -0.00005669&#xA; atom   11 type  2   force =    -0.00003321    0.00001917   -0.00009142&#xA; atom   12 type  2   force =     0.00003321    0.00001917   -0.00009142&#xA; atom   13 type  3   force =     0.00000000    0.00000000   -0.00000904&#xA; atom   14 type  3   force =     0.00000000    0.00000000   -0.00000815&#xA; The non-local contrib.  to forces&#xA; atom    1 type  2   force =     0.00000000   -0.00001332    0.26962422&#xA; atom    2 type  2   force =     0.00000000    0.00000000    0.26955768&#xA; atom    3 type  2   force =    -0.00001153    0.00000666    0.26962422&#xA; atom    4 type  2   force =     0.00001153    0.00000666    0.26962422&#xA; atom    5 type  1   force =    -0.00005393   -0.00003114   -0.00012327&#xA; atom    6 type  1   force =     0.00005393   -0.00003114   -0.00012327&#xA; atom    7 type  1   force =     0.00000000    0.00000000   -0.00007839&#xA; atom    8 type  1   force =     0.00000000    0.00006228   -0.00012327&#xA; atom    9 type  2   force =     0.00000000   -0.00000150   -0.26973639&#xA; atom   10 type  2   force =     0.00000000    0.00000000   -0.26948830&#xA; atom   11 type  2   force =    -0.00000130    0.00000075   -0.26973639&#xA; atom   12 type  2   force =     0.00000130    0.00000075   -0.26973639&#xA; atom   13 type  3   force =     0.00000000    0.00000000    0.06820805&#xA; atom   14 type  3   force =     0.00000000    0.00000000   -0.06820782&#xA; The ionic contribution  to forces&#xA; atom    1 type  2   force =     0.00001610    0.00009996  -41.41131874&#xA; atom    2 type  2   force =     0.00001609   -0.00000929  -41.41309517&#xA; atom    3 type  2   force =     0.00011070   -0.00006391  -41.41131875&#xA; atom    4 type  2   force =    -0.00007852   -0.00006392  -41.41131874&#xA; atom    5 type  1   force =     0.00486030    0.00284324   -1.55715733&#xA; atom    6 type  1   force =    -0.00492467    0.00284326   -1.55715735&#xA; atom    7 type  1   force =    -0.00003219    0.00001858   -1.55517833&#xA; atom    8 type  1   force =    -0.00003216   -0.00563076   -1.55715733&#xA; atom    9 type  2   force =     0.00001609    0.00066602   40.08007053&#xA; atom   10 type  2   force =     0.00001608   -0.00000929   40.07032538&#xA; atom   11 type  2   force =     0.00060093   -0.00034694   40.08007053&#xA; atom   12 type  2   force =    -0.00056875   -0.00034695   40.08007053&#xA; atom   13 type  3   force =     0.00000000   -0.00000000    5.02030759&#xA; atom   14 type  3   force =     0.00000000   -0.00000000    6.54285719&#xA; The local contribution  to forces&#xA; atom    1 type  2   force =     0.00000000   -0.00034700   41.14397702&#xA; atom    2 type  2   force =     0.00000000    0.00000000   41.14580130&#xA; atom    3 type  2   force =    -0.00030051    0.00017350   41.14397702&#xA; atom    4 type  2   force =     0.00030051    0.00017350   41.14397702&#xA; atom    5 type  1   force =    -0.00633118   -0.00271056    1.55618948&#xA; atom    6 type  1   force =     0.00469486   -0.00271058    1.55618950&#xA; atom    7 type  1   force =    -0.00081818    0.00047238    1.55415502&#xA; atom    8 type  1   force =    -0.00081818    0.00683824    1.55618948&#xA; atom    9 type  2   force =     0.00000000   -0.00090627  -39.81313135&#xA; atom   10 type  2   force =     0.00000000    0.00000000  -39.80363553&#xA; atom   11 type  2   force =    -0.00078486    0.00045314  -39.81313135&#xA; atom   12 type  2   force =     0.00078486    0.00045314  -39.81313135&#xA; atom   13 type  3   force =     0.00000000   -0.00000000   -5.08852831&#xA; atom   14 type  3   force =     0.00000000   -0.00000000   -6.47466195&#xA; The core correction contribution to forces&#xA; atom    1 type  2   force =    -0.00000000   -0.00000087   -0.00222779&#xA; atom    2 type  2   force =    -0.00000000    0.00000000   -0.00222378&#xA; atom    3 type  2   force =    -0.00000075    0.00000044   -0.00222779&#xA; atom    4 type  2   force =     0.00000075    0.00000044   -0.00222779&#xA; atom    5 type  1   force =     0.00000511   -0.00000530    0.00000128&#xA; atom    6 type  1   force =     0.00000918   -0.00000530    0.00000128&#xA; atom    7 type  1   force =     0.00000715   -0.00000413   -0.00000128&#xA; atom    8 type  1   force =     0.00000715   -0.00000177    0.00000128&#xA; atom    9 type  2   force =    -0.00000000   -0.00000155    0.00222923&#xA; atom   10 type  2   force =    -0.00000000    0.00000000    0.00222224&#xA; atom   11 type  2   force =    -0.00000134    0.00000077    0.00222923&#xA; atom   12 type  2   force =     0.00000134    0.00000077    0.00222923&#xA; atom   13 type  3   force =     0.00000000    0.00000000    0.00000000&#xA; atom   14 type  3   force =     0.00000000    0.00000000    0.00000000&#xA; The Hubbard contrib.    to forces&#xA; atom    1 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom    2 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom    3 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom    4 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom    5 type  1   force =     0.00000000    0.00000000    0.00000000&#xA; atom    6 type  1   force =     0.00000000    0.00000000    0.00000000&#xA; atom    7 type  1   force =     0.00000000    0.00000000    0.00000000&#xA; atom    8 type  1   force =     0.00000000    0.00000000    0.00000000&#xA; atom    9 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom   10 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom   11 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom   12 type  2   force =     0.00000000    0.00000000    0.00000000&#xA; atom   13 type  3   force =     0.00000000    0.00000000    0.00000000&#xA; atom   14 type  3   force =     0.00000000    0.00000000    0.00000000&#xA; The SCF correction term to forces&#xA; atom    1 type  2   force =    -0.00000000    0.00018854    0.00001249&#xA; atom    2 type  2   force =    -0.00000000    0.00000000   -0.00002345&#xA; atom    3 type  2   force =     0.00016328   -0.00009427    0.00001249&#xA; atom    4 type  2   force =    -0.00016328   -0.00009427    0.00001249&#xA; atom    5 type  1   force =     0.00064962    0.00037505    0.00110724&#xA; atom    6 type  1   force =    -0.00064961    0.00037505    0.00110724&#xA; atom    7 type  1   force =     0.00000002   -0.00000001    0.00107334&#xA; atom    8 type  1   force =     0.00000000   -0.00075011    0.00110724&#xA; atom    9 type  2   force =     0.00000000    0.00019566    0.00046313&#xA; atom   10 type  2   force =     0.00000000   -0.00000000    0.00050610&#xA; atom   11 type  2   force =     0.00016945   -0.00009783    0.00046313&#xA; atom   12 type  2   force =    -0.00016945   -0.00009783    0.00046313&#xA; atom   13 type  3   force =    -0.00000000    0.00000000   -0.00000980&#xA; atom   14 type  3   force =     0.00000000   -0.00000000   -0.00000900&#xA;&#xA;     Total force =     0.000267     Total SCF correction =     0.002764&#xA;     SCF correction compared to forces is large: reduce conv_thr to get better values&#xA;&#xA;     Damped Dynamics: convergence achieved in  60 steps&#xA;&#xA;     End of damped dynamics calculation&#xA;&#xA;     Final energy =    -728.6511735210 Ry&#xA;&#xA;Begin final coordinates&#xA;     new unit-cell volume =   7497.74335 a.u.^3 (  1111.05093 Ang^3 )&#xA;     density =      0.95997 g/cm^3&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   6.280000000   0.000000000   0.000000000&#xA;  -3.140000000   5.438639536   0.000000000&#xA;   0.000000000   0.000000000  32.529999000&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;S             0.3333367259        0.1666744517        0.1924559453&#xA;S             0.8333330000        0.1666670000        0.1924565082&#xA;S             0.3333367259        0.6666632741        0.1924559453&#xA;S             0.8333255483        0.6666632741        0.1924559453&#xA;Mo            0.1666505307        0.3333247654        0.2410118615&#xA;Mo            0.6666752346        0.3333247654        0.2410118615&#xA;Mo            0.1666670000        0.8333330000        0.2410123522&#xA;Mo            0.6666752346        0.8333494693        0.2410118615&#xA;S             0.3333324803        0.1666659607        0.2895684512&#xA;S             0.8333330000        0.1666670000        0.2895698989&#xA;S             0.3333324803        0.6666675197        0.2895684512&#xA;S             0.8333340393        0.6666675197        0.2895684512&#xA;H             0.8333330000        0.1666670000        0.4596930029&#xA;H             0.8333330000        0.1666670000        0.4827594636&#xA;End final coordinates&#xA;&#xA;&#xA;&#xA;     Writing output data file ./perHSout/MoS2.save/&#xA; &#xA;     init_run     :      5.65s CPU      5.85s WALL (       1 calls)&#xA;     electrons    :  21330.56s CPU  21607.08s WALL (      61 calls)&#xA;     update_pot   :     80.37s CPU     80.87s WALL (      60 calls)&#xA;     forces       :    215.34s CPU    219.34s WALL (      61 calls)&#xA;&#xA;     Called by init_run:&#xA;     wfcinit      :      3.48s CPU      3.54s WALL (       1 calls)&#xA;     wfcinit:atom :      0.02s CPU      0.02s WALL (      12 calls)&#xA;     wfcinit:wfcr :      3.38s CPU      3.44s WALL (      12 calls)&#xA;     potinit      :      0.54s CPU      0.55s WALL (       1 calls)&#xA;     hinit0       :      0.68s CPU      0.71s WALL (       1 calls)&#xA;&#xA;     Called by electrons:&#xA;     c_bands      :  20265.86s CPU  20453.28s WALL (     552 calls)&#xA;     sum_band     :    861.57s CPU    918.81s WALL (     552 calls)&#xA;     v_of_rho     :     47.56s CPU     49.40s WALL (     591 calls)&#xA;     v_h          :      3.54s CPU      3.60s WALL (     591 calls)&#xA;     v_xc         :     48.54s CPU     50.48s WALL (     652 calls)&#xA;     newd         :    162.54s CPU    191.05s WALL (     591 calls)&#xA;     mix_rho      :      7.58s CPU      7.73s WALL (     552 calls)&#xA;&#xA;     Called by c_bands:&#xA;     init_us_2    :     37.76s CPU     37.87s WALL (   13992 calls)&#xA;     ccgdiagg     :  18467.53s CPU  18639.51s WALL (    7185 calls)&#xA;     wfcrot       :   1759.11s CPU   1773.76s WALL (    6201 calls)&#xA;&#xA;     Called by sum_band:&#xA;     sum_band:wei :      0.28s CPU      0.32s WALL (     552 calls)&#xA;     sum_band:loo :    653.37s CPU    661.20s WALL (     552 calls)&#xA;     sum_band:buf :     12.37s CPU     12.47s WALL (    6624 calls)&#xA;     sum_band:ini :     16.86s CPU     16.91s WALL (    6624 calls)&#xA;     sum_band:cal :    269.04s CPU    270.56s WALL (    6624 calls)&#xA;     sum_band:bec :      1.69s CPU      1.71s WALL (    6624 calls)&#xA;     addusdens    :    193.95s CPU    242.58s WALL (     552 calls)&#xA;     addusd:skk   :      1.53s CPU      1.74s WALL (    1656 calls)&#xA;     addusd:dgemm :     84.81s CPU    132.82s WALL (    1656 calls)&#xA;     addusd:qvan2 :    102.12s CPU    102.15s WALL (    1656 calls)&#xA;&#xA;     Called by *cgdiagg:&#xA;     h_psi        :  10320.92s CPU  10414.63s WALL ( 2285498 calls)&#xA;     s_psi        :   5370.12s CPU   5401.52s WALL ( 4564795 calls)&#xA;&#xA;     Called by h_psi:&#xA;     h_psi:calbec :   3799.89s CPU   3847.07s WALL ( 2285498 calls)&#xA;     vloc_psi     :   3645.37s CPU   3681.81s WALL ( 2285498 calls)&#xA;     add_vuspsi   :   2831.81s CPU   2846.22s WALL ( 2285498 calls)&#xA;     hs_1psi      :  11741.60s CPU  11834.99s WALL ( 2279297 calls)&#xA;     s_1psi       :   5351.28s CPU   5410.80s WALL ( 2279297 calls)&#xA;&#xA;     General routines&#xA;     calbec       :   6888.49s CPU   6997.44s WALL ( 4574347 calls)&#xA;     fft          :     47.60s CPU     49.94s WALL (    8314 calls)&#xA;     ffts         :      1.56s CPU      1.62s WALL (    1143 calls)&#xA;     fftw         :   3576.05s CPU   3612.46s WALL ( 6461194 calls)&#xA;     interpolate  :      3.73s CPU      3.83s WALL (     591 calls)&#xA; &#xA;     Parallel routines&#xA;     fft_scatt_xy :    318.28s CPU    321.75s WALL ( 6470651 calls)&#xA;     fft_scatt_yz :   1418.14s CPU   1436.92s WALL ( 6470651 calls)&#xA; &#xA;     PWSCF        :      6h 0m CPU      6h 5m WALL&#xA;&#xA; &#xA;   This run was terminated on:  21:34:47  26Dec2021            &#xA;&#xA;=------------------------------------------------------------------------------=&#xA;   JOB DONE.&#xA;=------------------------------------------------------------------------------=&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4740" LastEditorUserId="7" LastEditDate="2021-12-30T16:37:36.107" LastActivityDate="2021-12-30T16:37:36.107" Title="Quantum Espresso error: &quot;SCF correction compared to forces is large: reduce conv_thr to get better values&quot;. How to solve?" Tags="|quantum-espresso|geometry-optimization|" AnswerCount="0" CommentCount="3" ClosedDate="2022-01-21T16:39:46.113" ContentLicense="CC BY-SA 4.0" />
  <row Id="8435" PostTypeId="1" CreationDate="2021-12-30T03:44:52.823" Score="7" ViewCount="98" Body="&lt;p&gt;In &lt;a href=&quot;http://susi.theochem.tuwien.ac.at/&quot; rel=&quot;noreferrer&quot;&gt;WIEN2k&lt;/a&gt;, the subprogram &lt;code&gt;lapwso&lt;/code&gt; will generate both &lt;code&gt;case.energy&lt;/code&gt; and &lt;code&gt;case.energyso&lt;/code&gt; files. What puzzle me is that  &lt;code&gt;case.energyso&lt;/code&gt; has different total number of energy points compared with &lt;code&gt;case.energy&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What is the format of these files? Which one is the true energy with SOC modified?&lt;/p&gt;&#xA;" OwnerUserId="4741" LastEditorUserId="7" LastEditDate="2021-12-30T16:47:24.120" LastActivityDate="2023-07-12T02:30:54.980" Title="Some questions on case.energy and case.energyso in WIEN2k" Tags="|density-functional-theory|spin-orbit-coupling|wien2k|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8436" PostTypeId="1" AcceptedAnswerId="8438" CreationDate="2021-12-30T05:32:03.097" Score="8" ViewCount="256" Body="&lt;p&gt;Currently in my VMD display, I define the &lt;em&gt;Trajectory Smoothing Window Size&lt;/em&gt;&#xA;in the dialog box as below.&lt;/p&gt;&#xA;&lt;p&gt;Figure below is for &lt;code&gt;protein&lt;/code&gt; selection, the &lt;em&gt;Trajectory Smoothing Window Size&lt;/em&gt; as 5.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rpJS0l.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rpJS0l.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How can I encode that to Tcl script?&lt;/p&gt;&#xA;&lt;p&gt;The current Tcl script I have is this (&lt;code&gt;vmd.tcl&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;display projection Orthographic&#xA;display rendermode GLSL&#xA;mol modselect 0 0 protein&#xA;mol modstyle 0 0 NewCartoon 0.300000 10.000000 4.100000 0&#xA;mol modcolor 0 0 Structure&#xA;mol addrep 0&#xA;mol modselect 1 0 resname PEP&#xA;mol modstyle 1 0 Licorice 0.300000 12.000000 12.000000&#xA;mol modcolor 1 0 Name&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And I'd like to incorporate the &lt;em&gt;Trajectory Smoothing Window Size&lt;/em&gt; into it,&#xA;for both &lt;code&gt;protein&lt;/code&gt; and &lt;code&gt;resname PEP&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Later I execute it as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ vmd md.gro md_noPBC.xtc -e vmd.tcl&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4475" LastActivityDate="2021-12-30T06:06:42.780" Title="How to assign &quot;Trajectory Smoothing Window Size&quot; inside VMD Tcl script" Tags="|molecular-dynamics|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8437" PostTypeId="2" ParentId="8308" CreationDate="2021-12-30T05:49:10.943" Score="4" Body="&lt;p&gt;Its neither a biophysical effect nor a bug in your MD simulation steps. It's just an visualisation issue. You could use the &lt;code&gt;gmx trjconv&lt;/code&gt; command to make your protein and ligand to the center of the box and fit all atoms to a reference structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;gmx trjconv -s yourTpr.tpr -f yourTrr.trr -pbc mol -center -o yourTrr_centered.trr&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Clear details of individual subcommands are shown &lt;a href=&quot;https://manual.gromacs.org/documentation/5.1/onlinehelp/gmx-trjconv.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2021-12-30T05:49:10.943" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8438" PostTypeId="2" ParentId="8436" CreationDate="2021-12-30T06:06:42.780" Score="8" Body="&lt;p&gt;You could use &lt;code&gt;mol smoothrep x y z&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;where&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;x&lt;/code&gt; is the &lt;code&gt;molid&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;y&lt;/code&gt; is the representation number (starts from 0)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;z&lt;/code&gt; is the &lt;code&gt;trajectory smoothining window size&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In your case, for &lt;code&gt;molid 0&lt;/code&gt; and for &lt;code&gt;protein&lt;/code&gt; representation and &lt;code&gt;trajectory smoothing window size&lt;/code&gt; of 5, the command will be&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mol smoothrep 0 0 5&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;and for representation of &lt;code&gt;resname PEP&lt;/code&gt;, the command will be&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mol smoothrep 0 1 5&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2021-12-30T06:06:42.780" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8439" PostTypeId="2" ParentId="8428" CreationDate="2021-12-30T15:03:25.333" Score="7" Body="&lt;h2&gt;You need the chemical potential to do solubility&lt;/h2&gt;&#xA;&lt;p&gt;The problem with solubility of large molecules, is that you need to know the chemical potential in the liquid and the solid. You can use Free Energy calculations to get the residual contribution to the chemical potential in the liquid, but, the residual contribution to the chemical potential of the solid is really hard. It can be done, but, not accurately. &lt;a href=&quot;https://mobleylab.org/2018/06/06/challenges-in-the-use-of-atomistic-simulations-to-predict-solubilities-of-drug-like-molecules/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MD attempt at solubility&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Macroscopic modelers do solubility calculations routinely by using an activity coefficient model to calculate the excess contribution to the chemical potential. here the excess is the total contribution to the chemical potential, minus the reference state (pure liquid) - similar, but not quite the same as a residual contribution. They also run into problems with the solid chemical potential, so they fall back on experiment.&lt;/p&gt;&#xA;&lt;p&gt;I will save the derivation, but in the end what you need is the activity coefficient of of the solute in the solution and the experimental (or predicted) enthalpy of fusion of the solute.&lt;/p&gt;&#xA;&lt;p&gt;Thus you solve:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ln (x_i) = \frac{\Delta H_m}{R} \left(\frac{1}{T_m} - \frac{1}{T} \right) + RT \ln \gamma_i(x_i)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(note I need to verify this, my memory is hazy and Wikipedia is bad at this stuff. I will look up my own code later, it works, so... I trust it more than Wikipedia. I may have plus and/or minus signs wrong here).&lt;/p&gt;&#xA;&lt;p&gt;Here we have the experimental enthalpy of melting (fusion) and some models activity coefficient(macroscopic equation of state, free energy calculation, divine intervention ...). note that the activity coefficient depends on the composition, so the composition (solubility) is on the left and right hand side. Thus, we have to solve this iteratively, which is why it is nice for macroscopic models, which takes fractions of seconds, and, not so nice for molecular models which take hours(have not actually done this yet using MD, it is on my list of things to do). I find that a simple secant method is fine when doing it using macroscopic equations of state. Simply updating will unfortunately lead to divergence sometimes.&lt;/p&gt;&#xA;&lt;p&gt;It is possible to calculate the activity coefficient of the solute using molecular simulation (molecular dynamics or Monte Carlo) free energy of solvation calculations if you understand how to relate that output value to the activity coefficient, but is far from trivial... it is much easier to do wrong than right.&lt;/p&gt;&#xA;&lt;p&gt;If using molecular simulations, you must understand that you are calculating a free energy with a different reference state than the typical activity coefficient models use (they are based on the Lewis-Randall chemical potential reference state (pure liquid)). COSMO models have to deal with the derivation for solubility using a chemical potential model that is not Lewis-Randall, so check that out to see how to use your models excess or residual chemical potential properly, or if using, for instance, a Henry law model, derive it carefully from scratch, and have many colleagues look it over.&lt;/p&gt;&#xA;&lt;h2&gt;Option 2:&lt;/h2&gt;&#xA;&lt;p&gt;Another option is to set up slabs of the solid in the solution, and then simply run MD or MC. the solids will slowly dissolve into the solution, and at some appropriate spot in the bulk, you measure the concentration of the solute. This is also not so trivial as it seems, but look to literature for guidance. A good question is &amp;quot;what is the solid (crystal) form of my drug molecule?&amp;quot;. The answer is frequently unknown... Also, does the FF model the crystal solid well? probably not.&lt;/p&gt;&#xA;&lt;h2&gt;Option 3:&lt;/h2&gt;&#xA;&lt;p&gt;Try to correlate something to experimental results and use this fit to predict solubility. This type of rational design strategy makes me a bit queasy, but, sometimes science doesn't have a quantitative strategy that is computationally feasible, and we have to fall back on parameter fitting. Who knows, maybe there is a good correlation between radius of gyration and free energy, or solubility. You could throw in hydrogen bonding sites into the regression as well, the list of features never ends...&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-01-12T03:53:57.817" LastActivityDate="2022-01-12T03:53:57.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8440" PostTypeId="2" ParentId="8359" CreationDate="2021-12-30T16:37:08.520" Score="7" Body="&lt;p&gt;I also manage to do the bond lengths in a slightly different way. I also used RDKit and my code is based on this &lt;a href=&quot;https://github.com/rdkit/rdkit/discussions/4832#discussioncomment-1882386&quot; rel=&quot;noreferrer&quot;&gt;discussion&lt;/a&gt;. I wanted to upload my answer earlier but the holidays are busy days.&lt;/p&gt;&#xA;&lt;p&gt;First of all, as I was working with .mol files instead of the smiles I noticed that &lt;code&gt;GetBondLength&lt;/code&gt; was giving me the wrong values. Then, I calculated the distances directly from the coordinates of the .mol file. To load the data I used&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;coords = []&#xA;new_coords = []&#xA;with open(file) as f:&#xA;    for _ in range(3):&#xA;        next(f)&#xA;    for line in f:&#xA;        coords.append(line.split())&#xA;&#xA;N = int(coords[0][0])&#xA;&#xA;for i in range(1,int(N)+1):&#xA;    new_coords.append([float(coords[i][0]),float(coords[i][1]),float(coords[i][2])])&#xA;&#xA;c = np.asarray(new_coords)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, to add the lengths I used&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for bnd in molecule.GetBonds():&#xA;        bl = np.linalg.norm(c[bnd.GetBeginAtomIdx()]- c[bnd.GetEndAtomIdx()])&#xA;        molecule.GetBondWithIdx(bnd.GetIdx()).SetProp('bondNote',f'{bl:.2f}')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After that, I used the style proposed in the discussion to draw the molecule. Also, because I had some Hydrogen bonds That weren't showing I created a &lt;code&gt;Chem.RWMol&lt;/code&gt; molecule, added manually the bonds as bonds of type zero, and then applied the bond lengths to draw&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule = Chem.MolFromMolFile(File, removeHs=False)&#xA;new_mol = Chem.RWMol(molecule)&#xA;new_mol.AddBond(8,25,Chem.rdchem.BondType('21'))&#xA;new_mol.AddBond(10,27,Chem.rdchem.BondType('21'))&#xA;molecule2 = Chem.Mol(new_mol)&#xA;&#xA;Draw_with_bond_lengths(molecule2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The final result is&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yiteD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yiteD.png&quot; alt=&quot;2D molecule image, overlaid with bond lengths&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4659" LastEditorUserId="7" LastEditDate="2021-12-30T16:50:08.430" LastActivityDate="2021-12-30T16:50:08.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8441" PostTypeId="2" ParentId="8426" CreationDate="2021-12-30T17:57:21.063" Score="7" Body="&lt;p&gt;&lt;strong&gt;Observation of a pure electric quadrupole mechanism for a solid-state electronic transition&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A pure electric quadrupole electronic transition was observed for single crystals of &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs2UO3Cl4}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the conclusion, the authors wrote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Finally we wish to comment on the possible occurrence of other examples of this mechanism. The relative magnitude of the electric-quadrupole intensity compared to magnetic-dipole intensity will increase with increasing atomic radius and most examples will therefore be found in the lanthanide or actinide series.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1080/00268977500103311&quot; rel=&quot;noreferrer&quot;&gt;R. G. Denning, T. R. Snellgrove, D. R. Woodwark, Observation of a pure electric quadrupole mechanism for a solid-state electronic transition, Mol. Phys. 30, 1819–1828 (1975)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Other example in the literature is &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs2NaSmCl6}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/0009-2614(81)85279-7&quot; rel=&quot;noreferrer&quot;&gt;R. W. Schwartz, A. K. Banerjee, Observation of a possible pure electric quadrupole transition in solid Cs2NaSmCl6, Chem. Phys. Lett. 79, 19–21 (1981).&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1080/00268979200100181&quot; rel=&quot;noreferrer&quot;&gt;P. A. Tanner, G. G. Siu, Electric quadrupole allowed transitions of lanthanide ions in octahedral symmetry, Mol. Phys. 75, 233–242 (1992).&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastEditorUserId="5" LastEditDate="2021-12-30T18:42:07.077" LastActivityDate="2021-12-30T18:42:07.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8442" PostTypeId="2" ParentId="8307" CreationDate="2021-12-30T18:25:50.020" Score="6" Body="&lt;p&gt;DFT can be used in the field of electrochemistry to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;predict reduction potentials of electron transfer and other electrochemical reactions and half-reactions in both aqueous and nonaqueous solutions [1].&lt;/li&gt;&#xA;&lt;li&gt;investigate electrocatalytic mechanisms [2].&lt;/li&gt;&#xA;&lt;li&gt;model electron transfer across metal electrode/electrolyte solution interfaces [3].&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These are a few examples that, hopefully, can get you started.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://xlink.rsc.org/?DOI=c4cp01572j&quot; rel=&quot;noreferrer&quot;&gt;A. V. Marenich, J. Ho, M. L. Coote, C. J. Cramer, D. G. Truhlar, Computational electrochemistry: prediction of liquid-phase reduction potentials, Phys. Chem. Chem. Phys. 16, 15068–15106 (2014).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcc.0c08120&quot; rel=&quot;noreferrer&quot;&gt;A. Govind Rajan, E. A. Carter, Discovering Competing Electrocatalytic Mechanisms and Their Overpotentials: Automated Enumeration of Oxygen Evolution Pathways. J. Phys. Chem. C. 124, 24883–24898 (2020).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/qua.25035&quot; rel=&quot;noreferrer&quot;&gt;R. R. Nazmutdinov, M. D. Bronshtein, T. T. Zinkicheva, D. V. Glukhov, Modeling of electron transfer across electrochemical interfaces: State-of-the art and challenges for quantum and computational chemistry. Int. J. Quantum Chem. 116, 189–201 (2016).&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2021-12-30T18:25:50.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8443" PostTypeId="2" ParentId="8426" CreationDate="2021-12-30T23:36:48.693" Score="5" Body="&lt;p&gt;For magnetic dipole transitions, it seems well-known examples are Eu3+ doped phosphors, for example, &lt;a href=&quot;https://www.nature.com/articles/ncomms1984&quot; rel=&quot;nofollow noreferrer&quot;&gt;Eu3+:Y2O3&lt;/a&gt; and &lt;a href=&quot;https://link.springer.com/referenceworkentry/10.1007%2F978-90-481-9751-4_30&quot; rel=&quot;nofollow noreferrer&quot;&gt;Eu3+ chelates&lt;/a&gt;. The &lt;span class=&quot;math-container&quot;&gt;$^5D_0 \rightarrow  ^7F_1$&lt;/span&gt; transition is magnetic dipole allowed, which is competitive to the &lt;span class=&quot;math-container&quot;&gt;$^5D_0 \rightarrow  ^7F_2$&lt;/span&gt; electric dipole transition, as shown in the following figure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9yEbR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9yEbR.png&quot; alt=&quot;MD transition&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is a kind of examples that almost resembles atomic nature, although embeded in a crystal environment. Anyway, could be a reference.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastEditorUserId="1318" LastEditDate="2021-12-31T01:32:59.727" LastActivityDate="2021-12-31T01:32:59.727" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8444" PostTypeId="1" CreationDate="2021-12-31T04:31:48.280" Score="6" ViewCount="83" Body="&lt;p&gt;I am studying nano-scale constrictions in semiconductor materials. Imagine two nano-particles joined together by a single point of crystalline contact to look like an hour-glass filled with sand. Since this structure consists of around 3000-4000 atoms for a unit cell, running DFT based calculations is not feasible with the computational resources available at hand.&lt;/p&gt;&#xA;&lt;p&gt;The study requires the comparison of electron scattering between several of such structures, all with similar shape but with different cross sectional area at the constriction. Also the variation of surface area and volume between the individual structure configurations is relatively insignificant compared to the cross section of the constriction.&lt;/p&gt;&#xA;&lt;p&gt;In this case, &lt;strong&gt;would it be acceptable to simply take the cross section of the constriction (modeled as an infinitely long section), and evaluate the electron relaxation time while neglecting the larger sections?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am aware that looking at the complete structure would be the best way to go, but it is not feasible for the study. &lt;strong&gt;If there is an alternative feasible approach, I'd be happy to try it out.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2022-02-24T04:04:39.993" LastActivityDate="2022-02-24T04:04:39.993" Title="Validity of estimating electron relaxation time using the smallest cross section of a structure" Tags="|density-functional-theory|electronic-structure|nanostructures|electronic-transport|semiconductor|" AnswerCount="0" CommentCount="5" ClosedDate="2023-02-11T01:39:47.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="8445" PostTypeId="2" ParentId="6797" CreationDate="2021-12-31T04:34:15.813" Score="2" Body="&lt;p&gt;I use SIESTA regularly so I'll tell you the way I do it. You can use &lt;code&gt;sisl&lt;/code&gt; as @nickpapior proposed, so I will give you a different alternative. Using the program &lt;code&gt;gdis&lt;/code&gt;, with it can open multiple molecular coordinate formats, including xyz, mol, pdb, etc. Then, in the top left corner, you have the option of saving the molecule in SIESTA format. This is nice when you have a molecule with many atoms. Then what I do is to delete all the presets gdis puts in the fdf file except for &lt;code&gt;SystemLabel&lt;/code&gt;, &lt;code&gt;NumberOfAtoms&lt;/code&gt;, &lt;code&gt;NumberOfSpecies&lt;/code&gt;, &lt;code&gt;block ChemicalSpeciesLabel&lt;/code&gt;, &lt;code&gt;block AtomicCoordinatesAndAtomicSpecies&lt;/code&gt;. Then at the end I add the line &lt;code&gt;include defaults.fdf&lt;/code&gt;. &lt;code&gt;defaults.fdf&lt;/code&gt; is a file with all the parameters I use. Usually, within the same project that file doesn't change much from simulation to simulation. That's not a 100 % automatic solution but is pretty close. If you are in Ubuntu or Debian-based system you can install it easily from the command line with &lt;code&gt;apt&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One little warning, if you are creating a &lt;code&gt;.fdf&lt;/code&gt; file from a &lt;code&gt;.pdb&lt;/code&gt; in that format molecules are enumerated, for example, C1, C2, C3, ... Then, before creating the &lt;code&gt;fdf&lt;/code&gt; you have to select all atoms of the same species and relabel them. That's easy to do inside the program in editor mode.&lt;/p&gt;&#xA;&lt;p&gt;Inside the program, you can select and configure some settings for the &lt;code&gt;fdf&lt;/code&gt; but I still recommend you have your own defaults.&lt;/p&gt;&#xA;" OwnerUserId="4659" LastActivityDate="2021-12-31T04:34:15.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8446" PostTypeId="5" CreationDate="2021-12-31T20:29:16.080" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-31T20:29:16.080" LastActivityDate="2021-12-31T20:29:16.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8447" PostTypeId="4" CreationDate="2021-12-31T20:29:16.080" Score="0" Body="Questions about or related to topology in matter modeling." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2021-12-31T20:29:16.080" LastActivityDate="2021-12-31T20:29:16.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8448" PostTypeId="2" ParentId="6512" CreationDate="2021-12-31T21:08:12.280" Score="4" Body="&lt;p&gt;Let's first break down the symbols we know in that expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\mathbf{\vec{S}} &amp;amp;= \frac{\hbar}{2}\boldsymbol{\vec{\sigma}}\tag{1}\\&#xA;&amp;amp;=\frac{\hbar}{2}\left(\sigma_x \boldsymbol{\hat{x}} + \sigma_y \boldsymbol{\hat{y}} + \sigma_z\boldsymbol{\hat{z}}\right)\tag{2}\\&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\small&#xA;\mathbf{\vec{S}}_1\times \mathbf{\vec{S}}_2 = \left(\sigma_{y,1}\sigma_{z,2} -  \sigma_{z,1}\sigma_{y,2}\right)\boldsymbol{\hat{x}} - \left(\sigma_{x,1}\sigma_{z,2} -  \sigma_{z,2}\sigma_{x,1}\right)\boldsymbol{\hat{y}} + \left(\sigma_{x,1}\sigma_{y,2} -  \sigma_{y,2}\sigma_{x,1}\right)\boldsymbol{\hat{z}} \!\!\!\!\tag{3}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We now want to second-quantize all Pauli operators, and as &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6512/how-to-formulate-the-second-quantization-of-dmi-interaction#comment14191_6512&quot;&gt;Anyon said in this comment&lt;/a&gt; there's plenty of ways to do that. I mentioned two of those ways (the Jordan-Wigner transform and the Bravyi-Kitaev transform) in &lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/16465/2293&quot;&gt;this answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The final part of the Hamiltonian which I haven't yet mentioned is &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\vec{D}}_{12}$&lt;/span&gt;. In the 79-page paper you gave us, and in my brief look of it, I was only able to find this sentence about that symbol:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{\vec{D}}_{12} (= - \mathbf{\vec{D}}_{21})$&lt;/span&gt; depends on&#xA;details of electron wave functions and the symmetry of the crystal&#xA;structure (Moriya, 1960a; Bogdanov and Hubert, 1994).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To second-quantize &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\vec{D}}_{12}$&lt;/span&gt; you would have to first decide what it is (depending on the details of the electron wave functions and the symmetry of the crystal structure, which suggests that it will depend on your material).&lt;/p&gt;&#xA;&lt;p&gt;The procedure for how to second-quantize the Rashba spin-orbit coupling Hamiltonian was given in the second paper you gave us &lt;strong&gt;in sections IIIA and IIIB&lt;/strong&gt;, and a similar procedure would be followed once you have enough detail about &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\vec{D}}_{12}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2021-12-31T21:08:12.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8449" PostTypeId="2" ParentId="6636" CreationDate="2022-01-01T03:15:48.483" Score="5" Body="&lt;p&gt;Expanding my comment to an answer, I believe the &amp;quot;trick&amp;quot; is incorrect.&lt;/p&gt;&#xA;&lt;p&gt;As far as I'm aware, the relationship between &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{r}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{\nabla_k}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$$\boldsymbol{r}\to-i\exp(i\boldsymbol{k}\cdot \boldsymbol{r})\boldsymbol{\nabla_k}\exp(-i\boldsymbol{k}\cdot \boldsymbol{r})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This would mean at least the middle equality of equation [\ref{1}] is incorrect.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2022-01-01T03:35:33.163" LastActivityDate="2022-01-01T03:35:33.163" CommentCount="0" CommunityOwnedDate="2022-01-01T03:15:48.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="8450" PostTypeId="2" ParentId="8420" CreationDate="2022-01-01T03:33:36.057" Score="6" Body="&lt;p&gt;A useful reference for this is [1], which describes how to compute the energy, forces, and stress tensor efficiently when performing PBC calculations using Gaussian atomic orbitals.&lt;/p&gt;&#xA;&lt;p&gt;Assuming you can calculate forces, the stress isn't too much more challenging to calculate. For a uniform lattice deformation due to strain &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{ab}$&lt;/span&gt;, the stress is computed as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\frac{\delta E}{\delta\epsilon_{ab}}=\sum_c^{\text{cells}}\sum_{I\in c}^\text{atoms}r^a_{I_c}\frac{dE}{dr^b_{I_c}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$I_c$&lt;/span&gt; indexes atoms in cell &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the energy per unit cell, and &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the Cartesian coordinates of all the atoms in all cells.&lt;/p&gt;&#xA;&lt;p&gt;The referenced paper provides detailed expressions for the various terms that contribute to this equation. It mostly boils down to two types of terms&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Forces on atoms times their position in the central cell (changes in the system energy due to changing the atomic positions)&lt;/li&gt;&#xA;&lt;li&gt;Forces on atoms in each cell times the corresponding lattice vectors/cell indicies (changes in the system energy due to changing lattice vector length).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Kudin, K. N.; Scuseria, G. E. Linear-scaling density-functional theory with Gaussian orbitals and periodic boundary conditions: Efficient evaluation of energy and forces via the fast multipole method. &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2000,&lt;/strong&gt; &lt;em&gt;61&lt;/em&gt; (24), 16440–16453. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.61.16440&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.61.16440&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2022-01-01T03:38:17.863" LastActivityDate="2022-01-01T03:38:17.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8451" PostTypeId="1" CreationDate="2022-01-01T06:24:17.577" Score="10" ViewCount="1473" Body="&lt;p&gt;Software such as ChemCraft or GaussView is easy to find for vibrational calculations in gas phase, but I am finding it much more difficult to find good visualization software for phonons.  I have attempted to use Phonopy, but found it difficult to actually get to work and I am not certain I am viewing the correct mode.&lt;/p&gt;&#xA;&lt;p&gt;Using the Quantum Espresso ph.x output, force constants, or phonopy output, what is the best visualization tool for viewing phonons in solids?  A GUI or CLI solution meshed with ASE could work well, I don't have a strong preference.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T10:08:42.700" Title="Tools to Visualize Phonons" Tags="|quantum-espresso|software-recommendations|phonons|visualization-software|phonopy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8452" PostTypeId="1" CreationDate="2022-01-01T09:01:32.380" Score="7" ViewCount="1563" Body="&lt;p&gt;I am performing &lt;code&gt;vc relax&lt;/code&gt; calculations to find the effect of pressure on the cell. Both tensile and compression pressure. But I am confused about the lattice parameters it is giving me. Its a cubic FCC structure with ibrav = 2&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS (alat= 11.14000000)&#xA;  -0.499839154   0.000000000   0.499839154&#xA;   0.000000000   0.499839154   0.499839154&#xA;  -0.499839154   0.499839154   0.000000000&#xA;these are at 0 pressure&#xA;CELL_PARAMETERS (alat= 11.14000000)&#xA;  -0.498989421   0.000000000   0.498989421&#xA;   0.000000000   0.498989421   0.498989421&#xA;  -0.498989421   0.498989421   0.000000000&#xA;these are at 10 Kbar pressure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wanted to clarify, does the 0 pressure give the actual cell parameters? Or are they different than what you get from volume optimization?&lt;/p&gt;&#xA;&lt;p&gt;Are the parameters &lt;code&gt;= 11.14*(0.499839154)&lt;/code&gt;? I have to do further calculations after this to see their effects on properties.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="7" LastEditDate="2022-01-01T23:52:45.077" LastActivityDate="2022-01-01T23:52:45.077" Title="Meaning of lattice parameters in vc relax calculations" Tags="|quantum-espresso|cell-optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8453" PostTypeId="2" ParentId="8452" CreationDate="2022-01-01T14:41:53.610" Score="5" Body="&lt;p&gt;From documentation&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ibrav      structure                   celldm(2)-celldm(6)&#xA;                                     or: b,c,cosbc,cosac,cosab&#xA;  0          free&#xA;      crystal axis provided in input: see card CELL_PARAMETERS&#xA;&#xA;  1          cubic P (sc)&#xA;      v1 = a(1,0,0),  v2 = a(0,1,0),  v3 = a(0,0,1)&#xA;&#xA;  2          cubic F (fcc)&#xA;      v1 = (a/2)(-1,0,1),  v2 = (a/2)(0,1,1), v3 = (a/2)(-1,1,0)&#xA;&#xA;  3          cubic I (bcc)&#xA;      v1 = (a/2)(1,1,1),  v2 = (a/2)(-1,1,1),  v3 = (a/2)(-1,-1,1)&#xA; -3          cubic I (bcc), more symmetric axis:&#xA;      v1 = (a/2)(-1,1,1), v2 = (a/2)(1,-1,1),  v3 = (a/2)(1,1,-1)&#xA;&#xA;  4          Hexagonal and Trigonal P        celldm(3)=c/a&#xA;      v1 = a(1,0,0),  v2 = a(-1/2,sqrt(3)/2,0),  v3 = a(0,0,c/a)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When &lt;code&gt;ibrav=2&lt;/code&gt; and &lt;code&gt;celldm(1)=11.44&lt;/code&gt; is chosen&lt;/p&gt;&#xA;&lt;p&gt;Following size of simulation box&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-0.5 0.0 0.5&#xA; 0.0 0.5 0.5&#xA;-0.5 0.5 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here &lt;code&gt;celldm(1)&lt;/code&gt; act as scaling factor which changes simulation box.&#xA;After relaxation scaling parameter remain same where as simulation cell changed to&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS (alat= 11.14000000)&#xA;  -0.499839154   0.000000000   0.499839154&#xA;   0.000000000   0.499839154   0.499839154&#xA;  -0.499839154   0.499839154   0.000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hence you have to find cell change that happen relative to 0.5 of original cell vector&lt;br /&gt;&#xA;Hence output &lt;strong&gt;11.14x0.499839154/0.5=11.1364163511&#xA;bohr&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can redo whole exercise instead of &lt;code&gt;ibrav=2&lt;/code&gt;, use &lt;code&gt;ibrav=0&lt;/code&gt; and define &lt;code&gt;CELL_PARAMETERS&lt;/code&gt; along with &lt;code&gt;ATOMIC_POSITIONS&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-01-01T14:41:53.610" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8454" PostTypeId="1" CreationDate="2022-01-02T08:28:20.057" Score="8" ViewCount="257" Body="&lt;p&gt;NSCF (non-self-consistent field) calculations are done on a dense mesh. I did it on a unit cell. Then since I have to try using a supercell for alloying, I am doing calculations to see the results of band gaps, and band structures.&lt;/p&gt;&#xA;&lt;p&gt;But I got an increased band gap when using a supercell. Please help me in this, and also let me know if it's because of something wrong I am doing here.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2022-01-07T00:30:45.503" LastActivityDate="2022-01-07T16:55:31.783" Title="Do NSCF calculations on Supercell gives different band gap than the Unit Cell?" Tags="|quantum-espresso|band-structure|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8455" PostTypeId="2" ParentId="8435" CreationDate="2022-01-02T12:09:53.357" Score="4" Body="&lt;p&gt;From the WIEN2k manual:&lt;br /&gt;&#xA;&lt;code&gt;LAPWSO&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;code&gt;lapwso&lt;/code&gt; includes spin-orbit (SO) coupling in a 2nd variational&#xA;procedure and computes eigenvalues and eigenvectors (stored in&#xA;&lt;code&gt;case.vectorso&lt;/code&gt;) using the scalar-relativistic wavefunctions from&#xA;&lt;code&gt;lapw1&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So, after running the inputs with &lt;code&gt;-so&lt;/code&gt;, the output files will be named with &lt;code&gt;so&lt;/code&gt; added to the end. The next number of energies output depends upon the values in case.inso, so is different from lapw1. Note that these are just levels, not those which are filled.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For instructions about plotting the bands with SPAGHETTI module: This&#xA;program generates an energy bandstructure plot (postscript file&#xA;&lt;code&gt;case.spaghetti.ps&lt;/code&gt; and xmgrace file &lt;code&gt;case.bands.agr&lt;/code&gt;) using the&#xA;eigenvalues printed in &lt;code&gt;case.output1&lt;/code&gt; or &lt;code&gt;case.outputso&lt;/code&gt; (with switch &lt;code&gt;-so&lt;/code&gt;) or &lt;code&gt;case.energy&lt;/code&gt; (with switch &lt;code&gt;-enefile&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2023-07-12T02:30:54.980" LastActivityDate="2023-07-12T02:30:54.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8456" PostTypeId="1" CreationDate="2022-01-02T21:10:50.147" Score="6" ViewCount="555" Body="&lt;p&gt;First of all, I'm very new to LAMMPS so I'm sorry if my question is trivial.&lt;/p&gt;&#xA;&lt;p&gt;I'm trying to model a gas of atoms that float in a square box, they obey an NVE integration and only feel a shifted Lennard-Jones potential, no other interaction is introduced. What I'm trying to do is to fill a file with energy values (alongside times) in order to plot them and see if energy is conserved. To do so, I use the fix print function, where previously I defined a variable Etot which should contain the energy I need, the full fix print line I'm using is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix print_energy all print 1000 &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$t $&lt;/span&gt;{Etot}&amp;quot; file data_13_5_a.txt screen no&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which should create the file &lt;code&gt;data_13_5_a.txt&lt;/code&gt; with times alongside energies. The problem is that I receive an error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ERROR on proc 0: Substitution for illegal variable Etot (../input.cpp:617&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I think the simulation itself is working because the dump file (see code below) .lammpstrj gives a result in Ovito.&#xA;In the end I also tried with another fix print (see below) but it gives me a similar error (&lt;code&gt;Substitution for illegal variable K&lt;/code&gt;).&#xA;I don't know what I'm doing wrong, for reference and errors, here is the full code I wrote:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;####################################################################################################&#xA;#                                      Lennard-Jones fluid                                         #&#xA;####################################################################################################&#xA;&#xA;&#xA;#--------------------------------------Dordoni Luca 0880068----------------------------------------#&#xA;#----------------------------------------------13.5a-----------------------------------------------#&#xA;&#xA;&#xA;#-------------------------------------------Parameters---------------------------------------------#&#xA;&#xA;# Number of integration timesteps&#xA;variable steps equal 1e5&#xA;&#xA;# Integration timestep &#xA;variable dt equal 5e-3&#xA;&#xA;# Truncation radius and LJ parameters&#xA;variable epsilon equal 1&#xA;variable sigma equal 1&#xA;variable Rc equal 2.5&#xA;&#xA;# Length of cubic simulation box&#xA;variable L equal 10.&#xA;&#xA;# Number of particles&#xA;variable rho equal 0.3&#xA;variable V equal &lt;span class=&quot;math-container&quot;&gt;$L*$&lt;/span&gt;L*&lt;span class=&quot;math-container&quot;&gt;$L&#xA;variable N equal $&lt;/span&gt;{rho}*$V&#xA;&#xA;# Temperature&#xA;variable T equal 2.&#xA;&#xA;# Particles' mass&#xA;variable m equal 1.&#xA;&#xA;# Seed for the RNG&#xA;variable seed equal 123&#xA;&#xA;&#xA;#-----------------------------------------Define Styles--------------------------------------------#&#xA;&#xA;&#xA;# Atom style used &#xA;atom_style atomic&#xA;&#xA;&#xA;#---------------------------------------Create cubic box-------------------------------------------#&#xA;&#xA;&#xA;# Define cubic region &#xA;region sim_box block -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L) -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L) -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L)&#xA;&#xA;# Create simulation box based on region&#xA;create_box 1 sim_box &#xA;&#xA;&#xA;#-----------------------------------------Create Atoms---------------------------------------------#&#xA;&#xA;&#xA;# Place particles in box randomly&#xA;create_atoms 1 random &lt;span class=&quot;math-container&quot;&gt;$N $&lt;/span&gt;{seed} NULL&#xA;&#xA;&#xA;#---------------------------------------------Masses-----------------------------------------------#&#xA;&#xA;&#xA;mass 1 $m&#xA;&#xA;&#xA;#----------------------------------------Pair Coefficients-----------------------------------------#&#xA;&#xA;&#xA;# Truncated LJ interactions for repulsion among particles&#xA;pair_style lj/cut ${Rc}&#xA;&#xA;# Shift the LJ potential to 0.0 at the cutoff (thus no discontinuities). The coefficients should&#xA;# be the ones of the LJ interaction formula: epsilon and sigma, also another for the shift.&#xA;pair_modify shift yes&#xA;&#xA;# Coefficients of the pair interactions &#xA;pair_coeff 1 1 &lt;span class=&quot;math-container&quot;&gt;${epsilon} $&lt;/span&gt;{sigma} ${Rc}&#xA;&#xA;# neighbor $(2.*v_Rc) bin        # not needed but may be useful&#xA;&#xA;&#xA;#-------------------------------------------Minimize-----------------------------------------------#&#xA;&#xA;&#xA;# minimize to improve the random distance at which atoms are placed and avoid errors.&#xA;minimize 1e-4 1e-7 10000 10000&#xA;&#xA;reset_timestep 0&#xA;&#xA;&#xA;#---------------------------------------------Fixes------------------------------------------------#&#xA;&#xA;&#xA;# Initialize velocities to MB distribution and zero total momentum&#xA;velocity all create &lt;span class=&quot;math-container&quot;&gt;$T $&lt;/span&gt;{seed} mom yes&#xA;&#xA;# Microcanonical ensemble (total energy constant)&#xA;fix 1 all nve&#xA;&#xA;&#xA;#------------------------------------------Measurements--------------------------------------------#&#xA;&#xA;&#xA;# Include this if for visualisation with vmd.&#xA;dump movie all atom 10 ./movie_13_5_a.lammpstrj&#xA;&#xA;# Current timestep&#xA;variable t equal step*${dt}&#xA;&#xA;&#xA;#--------------------------------------------Energies----------------------------------------------#&#xA;&#xA;&#xA;# group particles type 1      # test&#xA;&#xA;# calculate total kinetic energy of the system, store it in the compute variable c_Kenergy&#xA;compute Kenergy all ke&#xA;&#xA;# calculate total potential energy of the system, store it in the compute variable c_Venergy&#xA;compute Venergy all pe&#xA;&#xA;# Store the energies (kinetic, potential and total) in three variables which can be accessed &#xA;# by the print command. Don't set Etot equal &lt;span class=&quot;math-container&quot;&gt;$K+$&lt;/span&gt;V, because LAMMPS will complain...&#xA;variable K equal c_Kenergy&#xA;variable V equal c_Venergy&#xA;variable Etot equal c_Kenergy+c_Venergy&#xA;&#xA;# thermo_style custom time etotal&#xA;# thermo 200&#xA; &#xA;&#xA;#-----------------------------------------------Run------------------------------------------------#&#xA;&#xA;&#xA;# set timestep for integration&#xA;timestep ${dt}&#xA;&#xA;# Write to a file&#xA;fix print_energy all print 1000 &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$t $&lt;/span&gt;{Etot}&amp;quot; file &amp;quot;./data_13_5_a.txt&amp;quot; screen no&#xA;# fix energy_print all print 10 &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$t $&lt;/span&gt;K &lt;span class=&quot;math-container&quot;&gt;$V $&lt;/span&gt;E&amp;quot; file energy.dat screen no title &amp;quot;#Timestep Kinetic Potential Total&amp;quot;&#xA;&#xA;run ${steps}&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Furthermore, I'm using Mac, and to run the simulation I wrote in the terminal &lt;code&gt;lmp_serial -in input_13_5_a&lt;/code&gt; where &lt;em&gt;input_13_5_a&lt;/em&gt; is the file containing my script.&lt;/p&gt;&#xA;&lt;p&gt;Edit. Here is the log file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LAMMPS (29 Sep 2021 - Update 1)&#xA;####################################################################################################&#xA;#                                      Lennard-Jones fluid                                         #&#xA;####################################################################################################&#xA;&#xA;&#xA;#--------------------------------------Dordoni Luca 0880068----------------------------------------#&#xA;#----------------------------------------------13.5a-----------------------------------------------#&#xA;&#xA;&#xA;#-------------------------------------------Parameters---------------------------------------------#&#xA;&#xA;# Number of integration timesteps&#xA;variable steps equal 1e5&#xA;&#xA;# Integration timestep&#xA;variable dt equal 5e-3&#xA;&#xA;# Truncation radius and LJ parameters&#xA;variable epsilon equal 1&#xA;variable sigma equal 1&#xA;variable Rc equal 2.5&#xA;&#xA;# Length of cubic simulation box&#xA;variable L equal 10.&#xA;&#xA;# Number of particles&#xA;variable rho equal 0.3&#xA;variable V equal &lt;span class=&quot;math-container&quot;&gt;$L*$&lt;/span&gt;L*&lt;span class=&quot;math-container&quot;&gt;$L&#xA;variable V equal 10*$&lt;/span&gt;L*&lt;span class=&quot;math-container&quot;&gt;$L&#xA;variable V equal 10*10*$&lt;/span&gt;L&#xA;variable V equal 10*10*10&#xA;variable N equal &lt;span class=&quot;math-container&quot;&gt;${rho}*$&lt;/span&gt;V&#xA;variable N equal 0.3*$V&#xA;variable N equal 0.3*1000&#xA;&#xA;# Temperature&#xA;variable T equal 2.&#xA;&#xA;# Particles' mass&#xA;variable m equal 1.&#xA;&#xA;# Seed for the RNG&#xA;variable seed equal 123&#xA;&#xA;&#xA;#-----------------------------------------Define Styles--------------------------------------------#&#xA;&#xA;&#xA;# Atom style used&#xA;atom_style atomic&#xA;&#xA;&#xA;#---------------------------------------Create cubic box-------------------------------------------#&#xA;&#xA;&#xA;# Define cubic region&#xA;region sim_box block -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L) -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L) -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L)&#xA;region sim_box block -5 &lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) -$&lt;/span&gt;(0.5 * v_L) &lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) -$&lt;/span&gt;(0.5 * v_L) &lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L)&#xA;region sim_box block -5 5 -$&lt;/span&gt;(0.5 * v_L) &lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) -$&lt;/span&gt;(0.5 * v_L) &lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L)&#xA;region sim_box block -5 5 -5 $&lt;/span&gt;(0.5 * v_L) -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L)&#xA;region sim_box block -5 5 -5 5 -&lt;span class=&quot;math-container&quot;&gt;$(0.5 * v_L) $&lt;/span&gt;(0.5 * v_L)&#xA;region sim_box block -5 5 -5 5 -5 $(0.5 * v_L)&#xA;region sim_box block -5 5 -5 5 -5 5&#xA;&#xA;# Create simulation box based on region&#xA;create_box 1 sim_box&#xA;Created orthogonal box = (-5.0000000 -5.0000000 -5.0000000) to (5.0000000 5.0000000 5.0000000)&#xA;  1 by 1 by 1 MPI processor grid&#xA;&#xA;&#xA;#-----------------------------------------Create Atoms---------------------------------------------#&#xA;&#xA;&#xA;# Place particles in box randomly&#xA;create_atoms 1 random &lt;span class=&quot;math-container&quot;&gt;$N $&lt;/span&gt;{seed} NULL&#xA;create_atoms 1 random 300 ${seed} NULL&#xA;create_atoms 1 random 300 123 NULL&#xA;Created 300 atoms&#xA;  using lattice units in orthogonal box = (-5.0000000 -5.0000000 -5.0000000) to (5.0000000 5.0000000 5.0000000)&#xA;  create_atoms CPU = 0.000 seconds&#xA;&#xA;&#xA;#---------------------------------------------Masses-----------------------------------------------#&#xA;&#xA;&#xA;mass 1 $m&#xA;mass 1 1&#xA;&#xA;&#xA;#----------------------------------------Pair Coefficients-----------------------------------------#&#xA;&#xA;&#xA;# Truncated LJ interactions for repulsion among particles&#xA;pair_style lj/cut ${Rc}&#xA;pair_style lj/cut 2.5&#xA;&#xA;# Shift the LJ potential to 0.0 at the cutoff (thus no discontinuities). The coefficients should&#xA;# be the ones of the LJ interaction formula: epsilon and sigma, also another for the shift.&#xA;pair_modify shift yes&#xA;&#xA;# Coefficients of the pair interactions&#xA;pair_coeff 1 1 &lt;span class=&quot;math-container&quot;&gt;${epsilon} $&lt;/span&gt;{sigma} &lt;span class=&quot;math-container&quot;&gt;${Rc}&#xA;pair_coeff 1 1 1 $&lt;/span&gt;{sigma} &lt;span class=&quot;math-container&quot;&gt;${Rc}&#xA;pair_coeff 1 1 1 1 $&lt;/span&gt;{Rc}&#xA;pair_coeff 1 1 1 1 2.5&#xA;&#xA;# neighbor $(2.*v_Rc) bin        # not needed but may be useful&#xA;&#xA;&#xA;#-------------------------------------------Minimize-----------------------------------------------#&#xA;&#xA;&#xA;# minimize to improve the random distance at which atoms are placed and avoid errors.&#xA;minimize 1e-4 1e-7 10000 10000&#xA;WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (../min.cpp:188)&#xA;Neighbor list info ...&#xA;  update every 1 steps, delay 0 steps, check yes&#xA;  max neighbors/atom: 2000, page size: 100000&#xA;  master list distance cutoff = 2.8&#xA;  ghost atom cutoff = 2.8&#xA;  binsize = 1.4, bins = 8 8 8&#xA;  1 neighbor lists, perpetual/occasional/extra = 1 0 0&#xA;  (1) pair lj/cut, perpetual&#xA;      attributes: half, newton on&#xA;      pair build: half/bin/atomonly/newton&#xA;      stencil: half/bin/3d&#xA;      bin: standard&#xA;Per MPI rank memory allocation (min/avg/max) = 4.214 | 4.214 | 4.214 Mbytes&#xA;Step Temp E_pair E_mol TotEng Press &#xA;       0            0     31424599            0     31424599     37710155 &#xA;     503            0   -5.2799826            0   -5.2799826  -0.12954156 &#xA;Loop time of 0.106709 on 1 procs for 503 steps with 300 atoms&#xA;&#xA;99.8% CPU use with 1 MPI tasks x no OpenMP threads&#xA;&#xA;Minimization stats:&#xA;  Stopping criterion = energy tolerance&#xA;  Energy initial, next-to-last, final = &#xA;      31424598.7313598  -5.27947676473381  -5.27998264715565&#xA;  Force two-norm initial, final = 7.6269644e+11 7.3211830&#xA;  Force max component initial, final = 4.5240368e+11 1.1862632&#xA;  Final line search alpha, max atom move = 0.017969632 0.021316714&#xA;  Iterations, force evaluations = 503 1005&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 0.065804   | 0.065804   | 0.065804   |   0.0 | 61.67&#xA;Neigh   | 0.030718   | 0.030718   | 0.030718   |   0.0 | 28.79&#xA;Comm    | 0.0043468  | 0.0043468  | 0.0043468  |   0.0 |  4.07&#xA;Output  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Modify  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Other   |            | 0.005841   |            |       |  5.47&#xA;&#xA;Nlocal:        300.000 ave         300 max         300 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Nghost:        840.000 ave         840 max         840 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Neighs:        7939.00 ave        7939 max        7939 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 7939&#xA;Ave neighs/atom = 26.463333&#xA;Neighbor list builds = 146&#xA;Dangerous builds = 1&#xA;&#xA;reset_timestep 0&#xA;&#xA;&#xA;#---------------------------------------------Fixes------------------------------------------------#&#xA;&#xA;&#xA;# Initialize velocities to MB distribution and zero total momentum&#xA;velocity all create &lt;span class=&quot;math-container&quot;&gt;$T $&lt;/span&gt;{seed} mom yes&#xA;velocity all create 2 ${seed} mom yes&#xA;velocity all create 2 123 mom yes&#xA;&#xA;# Microcanonical ensemble (total energy constant)&#xA;fix 1 all nve&#xA;&#xA;&#xA;#------------------------------------------Measurements--------------------------------------------#&#xA;&#xA;&#xA;# Include this if for visualisation with vmd.&#xA;dump movie all atom 10 ./movie_13_5_a.lammpstrj&#xA;&#xA;# Current timestep&#xA;variable t equal step*${dt}&#xA;variable t equal step*0.005&#xA;&#xA;&#xA;#--------------------------------------------Energies----------------------------------------------#&#xA;&#xA;&#xA;# group particles type 1      # test&#xA;&#xA;# calculate total kinetic energy of the system, store it in the compute variable c_Kenergy&#xA;compute Kenergy all ke&#xA;&#xA;# calculate total potential energy of the system, store it in the compute variable c_Venergy&#xA;compute Venergy all pe&#xA;&#xA;# Store the energies (kinetic, potential and total) in three variables which can be accessed&#xA;# by the print command. Don't set Etot equal &lt;span class=&quot;math-container&quot;&gt;$K+$&lt;/span&gt;V, because LAMMPS will complain...&#xA;variable K equal c_Kenergy&#xA;variable V equal c_Venergy&#xA;variable Etot equal c_Kenergy+c_Venergy&#xA;&#xA;# thermo_style custom time etotal&#xA;# thermo 200&#xA;&#xA;&#xA;#-----------------------------------------------Run------------------------------------------------#&#xA;&#xA;&#xA;# set timestep for integration&#xA;timestep ${dt}&#xA;timestep 0.005&#xA;&#xA;# Write to a file&#xA;fix print_energy all print 1000 &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$t $&lt;/span&gt;{Etot}&amp;quot; file &amp;quot;./data_13_5_a.txt&amp;quot; screen no&#xA;# fix energy_print all print 10 &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$t $&lt;/span&gt;K &lt;span class=&quot;math-container&quot;&gt;$V $&lt;/span&gt;E&amp;quot; file energy.dat screen no title &amp;quot;#Timestep Kinetic Potential Total&amp;quot;&#xA;&#xA;run ${steps}&#xA;run 100000&#xA;ERROR on proc 0: Substitution for illegal variable Etot (../input.cpp:617)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4756" LastEditorUserId="4756" LastEditDate="2022-01-03T13:04:14.193" LastActivityDate="2022-01-03T13:04:14.193" Title="LAMMPS fix print function" Tags="|molecular-dynamics|lammps|apple-operating-system|ovito|" AnswerCount="0" CommentCount="11" FavoriteCount="0" ClosedDate="2022-02-24T14:26:18.730" ContentLicense="CC BY-SA 4.0" />
  <row Id="8457" PostTypeId="1" CreationDate="2022-01-03T11:09:24.690" Score="9" ViewCount="965" Body="&lt;p&gt;Spin-orbit coupling&lt;sup&gt;[1]&lt;/sup&gt; means the system has a non-collinear spin. Therefore, spin exists as a spinor, hence there is no meaning to 'up' and 'down' spin. Still, is there any way to get fat-band plot separating 'up' and 'down' spin for a system with SOC?&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Xu, X.; Ma, Y.; Zhang, T.; Lei, C.; Huang, B.; Dai, Y. Nonmetal-Atom-Doping-Induced Valley Polarization in Single-Layer Tl2O. &lt;em&gt;J. Phys. Chem. Lett.&lt;/em&gt; &lt;strong&gt;2019,&lt;/strong&gt; &lt;em&gt;10&lt;/em&gt; (16), 4535–4541. &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.9b01602&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1021/acs.jpclett.9b01602&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="7" LastEditDate="2022-01-03T18:40:56.403" LastActivityDate="2022-01-08T09:02:42.087" Title="How to obtain spin projected band structure for system with Spin Orbit Coupling?" Tags="|quantum-espresso|spin-orbit-coupling|spin-polarization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8458" PostTypeId="1" AcceptedAnswerId="9700" CreationDate="2022-01-03T11:30:29.117" Score="6" ViewCount="216" Body="&lt;p&gt;Are there any free to use tools which can be used to calculate the electrical conductivity of nanostructured materials. The systems that I am interested in consist of several thousand atoms, and running DFT calculations is not an option due to the lack of computational resources.&lt;/p&gt;&#xA;&lt;p&gt;Are there any &lt;strong&gt;tools or theoretical methods&lt;/strong&gt; which I can use to calculate the &lt;strong&gt;electrical conductivity&lt;/strong&gt; of these 2D and 1D materials?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="7" LastEditDate="2022-09-22T20:27:18.923" LastActivityDate="2022-09-23T00:37:15.083" Title="Are there tools to calculate the electrical conductivity of large (&gt;1000 atom) nanostructures?" Tags="|software-recommendations|physical-properties-of-materials|nanostructures|electronic-transport|" AnswerCount="2" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="8459" PostTypeId="1" AcceptedAnswerId="8508" CreationDate="2022-01-03T16:59:21.633" Score="10" ViewCount="579" Body="&lt;p&gt;I am looking for open-source software that could help me to build Heterostructure models visually, I've been working with BIOVIA Materials Studio before, but I got no valid license now, so I'd like to find some open-source alternative that works like BIOVIA Materials Studio. I tried the VESTA program, but it needs a lot of manual work to build a valid model for DFT calculation.&lt;br&gt;&#xA;Any recommendation is welcome.&lt;/p&gt;&#xA;&lt;p&gt;For example, in Materials studio, when creating a slab, I could set the parameter of HKL and thickness, then I could get the result, but in VESTA, I need to set some kind of transformation matrix and delete some atoms manually.&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mxez3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mxez3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-01-07T17:13:12.840" LastActivityDate="2022-01-07T17:28:01.460" Title="Recommendation of open source software that could build Heterostructure models visually?" Tags="|software|software-recommendations|molecular-modeling|crystallography|heterostructures|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8460" PostTypeId="1" AcceptedAnswerId="8476" CreationDate="2022-01-03T17:15:11.187" Score="5" ViewCount="77" Body="&lt;p&gt;Usually when passivating the slab's bottom side with pseudohydrogen, I would optimize the structure of the bulk, cut the bulk and get the slab model, then I would add the  pseudohydrogen at the midpoint of the bond between the bottom atom and the atom from the neighbor unit cell. Do I have to put the pseudohydrogen at the midpoint?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-01-03T18:21:10.330" LastActivityDate="2022-01-05T01:50:59.687" Title="Where should I put the pseudohydrogen?" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8461" PostTypeId="1" CreationDate="2022-01-03T22:46:17.680" Score="8" ViewCount="908" Body="&lt;p&gt;I have heard both terms in various lectures and books on quantum chemistry, however, I have not found a proper explanation of them. As I understand now, size consistency of a method means for example, that the energy of two molecules separated by an infinite distance is the same as the sum of the energies individually calculated on each. Size extensivity seems to be about whether the method scales linearly (?) with the number of electrons.&lt;/p&gt;&#xA;&lt;p&gt;What is confusing is that sometimes these terms are used to mean the same thing, in lectures or presentations. I am really unsure about which methods are size consistent and which are size extensive and which are not.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2022-01-04T23:08:30.290" LastActivityDate="2022-01-04T23:08:30.290" Title="What do size-extensivity and size-consistency mean?" Tags="|hartree-fock|coupled-cluster|binding-energy|configuration-interaction|many-body-perturbation-theory|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8462" PostTypeId="2" ParentId="8457" CreationDate="2022-01-03T23:28:18.667" Score="7" Body="&lt;p&gt;Non-collinear spin doesn't mean there's no &amp;quot;up&amp;quot; and &amp;quot;down&amp;quot;, it means that the natural quantisation axis (which defines &amp;quot;up&amp;quot; and &amp;quot;down&amp;quot;) can vary in space. In other words, at each point in space there's a local &amp;quot;up&amp;quot; direction, but that direction may change throughout space so we no longer have a global spin direction.&lt;/p&gt;&#xA;&lt;p&gt;In order to plot the spin of each band, you need to decide what you are actually interested in. You could choose a global direction and project the spin onto that, for example project onto the Cartesian &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;-axis and plot the bands coloured (or fattened) according to &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt;, as you probably would for a collinear spin calculation.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps a more natural method would be to use colour to map out the actual expectation value of the spin vector, &lt;span class=&quot;math-container&quot;&gt;$(S_x,S_y,S_z)$&lt;/span&gt;, e.g. as the three components of an RGB colour.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-01-03T23:28:18.667" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8463" PostTypeId="2" ParentId="8461" CreationDate="2022-01-03T23:42:52.027" Score="7" Body="&lt;p&gt;&lt;strong&gt;Size-consistency&lt;/strong&gt;: Your description is correct. &lt;span class=&quot;math-container&quot;&gt;$E_{AB}(r=\infty) = E_A + E_B$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Size-extensivity:&lt;/strong&gt; I explained this in my answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1329/5&quot;&gt;&amp;quot;Constraint #13: Size-Extensivity&amp;quot;&lt;/a&gt; to the question asking for the 17 different constraints for the  SCAN functional.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What is confusing is that sometimes these terms are used to mean the same thing.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That's true. Based on my experience, what you have observed happens because the vast majority of quantum chemists do not really know what these terms mean. Size-consistency is largely known, but I've seen some of the best experts in the field (people who did their PhD exclusively on developing coupled cluster methods) who don't quite know what size-extensivity means, or frequently confuse the two, or would frequently need to look up the definitions to remind themselves of the meanings.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-04T02:11:36.757" LastActivityDate="2022-01-04T02:11:36.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8464" PostTypeId="1" CreationDate="2022-01-04T09:44:13.457" Score="5" ViewCount="1333" Body="&lt;p&gt;I am trying to perform heating and quenching simulations of iron from various temperatures. I took 2000 atom simulation box and performed following methodology&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#=====starting from random velocity at 500K  final temp will be 250K ========&#xA;velocity all create 500.0 4928459 rot yes dist gaussian&#xA;fix 1 all nve&#xA;run 10000&#xA;unfix 1&#xA;# ==== re-relax with npt =========&#xA;fix 2 all npt temp 250.0 250.0 0.1 iso 0.0 0.0 1&#xA;run 10000&#xA;unfix 2&#xA;#=========== constant heating=============&#xA;fix 2 all npt temp 250.0 600.0 0.1 iso 0.0 0.0 1&#xA;run 500000&#xA;unfix 2&#xA;#==========re-relax at Tmax =============&#xA;fix 2 all nvt temp 600.0 600.0 0.1&#xA;run 100000&#xA;unfix 2&#xA;write_restart restart.heat&#xA;#================ Quench to 100K ===========&#xA;fix 3 all nvt temp 100 100 0.1&#xA;run 100000&#xA;unfix 3&#xA;write_restart restart.quench&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not sure about the quenching methodology is correct or not. Kindly comment on both heating and quenching process. Timestep :1fs&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Uz4ZD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Uz4ZD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-01-04T11:48:53.283" LastActivityDate="2022-01-04T11:48:53.283" Title="Heating and Quenching simulation in lammps" Tags="|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8465" PostTypeId="1" CreationDate="2022-01-04T10:41:14.230" Score="3" ViewCount="110" Body="&lt;p&gt;If there was a deviation between the experimentally calculated values and theoretical determination done by DFT calculation, then what is the reason?&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="671" LastEditDate="2022-01-05T00:47:30.717" LastActivityDate="2022-01-06T04:34:29.690" Title="Why is there a deviation between the experimentally calculated values and theoretical done by DFT calculation?" Tags="|density-functional-theory|condensed-matter|physical-properties-of-materials|" AnswerCount="0" CommentCount="8" ClosedDate="2022-01-05T05:10:17.157" ContentLicense="CC BY-SA 4.0" />
  <row Id="8466" PostTypeId="2" ParentId="8464" CreationDate="2022-01-04T11:27:26.063" Score="3" Body="&lt;p&gt;In my calculations, what I opt to do is somewhat different. However, I can't comment on whether you method is correct or not. But based on the results which I have obtained, I think that your method could be questionable. My procedure is as follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Generate initial temperature and relax sufficiently in the NPT ensemble followed by NVE to make sure that the effects of the random distribution of velocities prescribed initially are lost.&lt;/li&gt;&#xA;&lt;li&gt;Heat the system in the NPT ensemble at the desired rate by around 50-100K.&lt;/li&gt;&#xA;&lt;li&gt;Relax the system at constant temperature in the NPT ensemble followed by NVE to ensure the stability of the system (add NVT as well if necessary).&lt;/li&gt;&#xA;&lt;li&gt;Repeat steps 2 and 3 until the desired final temperature is achieved.&lt;/li&gt;&#xA;&lt;li&gt;Cool the system from the current (maximum) temperature to the initial temperature using the NPT ensemble in a single run at a desired rate.&lt;/li&gt;&#xA;&lt;li&gt;The rate of cooling is best determined from literature. However if no published data is available, try several rates and validate with data for amorphous phase (assuming that this is what you are after) from experiments.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2022-01-04T11:27:26.063" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8468" PostTypeId="1" CreationDate="2022-01-04T16:04:58.220" Score="10" ViewCount="1531" Body="&lt;p&gt;This is a follow up question from &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8461/what-is-size-extensivity-and-size-consistency&quot;&gt;another question&lt;/a&gt; I posted here. I am looking for an explanation (or a mathematical proof, if possible) of the size extensivity and size consistency of the following commonly used quantum chemistry methods:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Hartree-Fock (i.e. RHF, ROHF, UHF)&lt;/li&gt;&#xA;&lt;li&gt;Density Functional Theory (do all functionals have the same property?)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8469/5&quot;&gt;Configuration interaction&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Complete Active Space SCF (CASSCF)&lt;/li&gt;&#xA;&lt;li&gt;Quadratic CISD, with perturbative triples i.e. QCISD(T)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8472/5&quot;&gt;MBPT and coupled cluster methods&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Local correlation methods (i.e. DLPNO-CCSD, DLPNO-MP2 etc.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;What is the size consistency and size extensivity of each of these methods, and why?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2022-01-04T23:06:21.237" LastActivityDate="2022-01-04T23:06:21.237" Title="Which methods are size-consistent / size-extensive, and why?" Tags="|computational-chemistry|one-topic-per-answer|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8469" PostTypeId="2" ParentId="8468" CreationDate="2022-01-04T17:36:07.863" Score="9" Body="&lt;h2&gt;Configuration Interaction (CI)&lt;/h2&gt;&#xA;&lt;p&gt;A good explanation of size consistency/extensivity for CI is given in Chapter 4, section 6 [1], though note that they describe both properties as forms of size consistency. This answer mostly focuses on truncated CI, but its helpful to contrast its behavior with Full CI.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Full&lt;/em&gt; CI is size consistent and size extensive; this makes sense as it should exactly solve the Schrodinger equation (for the finite basis used) and real systems are size consistent/extensive. &lt;em&gt;Truncated&lt;/em&gt; CI, however, is neither size consistent nor size extensive.&lt;/p&gt;&#xA;&lt;p&gt;This is very easy to show for size consistency: consider the example of infinitely separated &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecules in a minimal basis. For a single &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, CISD is equivalent to Full CI (each molecule only has two electrons and a single unoccupied spatial orbital), so the energy we get from calculations on the separated molecules individually is just two times the Full CI energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;. For the combined system, CISD is no longer equivalent to full CI: without quadruple excitations, we aren't including the case where both &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecules are doubly excited. So the energy is not consistent when calculated as a supersystem vs separate monomer calculations. This same argument can be extended to any truncated CI in any basis.&lt;/p&gt;&#xA;&lt;p&gt;The argument for truncated CI failing to be size extensive can be made very similarly. Instead of two &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; monomers, we can consider a chain of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; of them. We still consider them all infinitely separated, though this is just so we can compare with the exact energy per monomer. [1] shows that CID energy of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; minimal basis &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; scales as &lt;span class=&quot;math-container&quot;&gt;$O(N^{1/2})$&lt;/span&gt;, while size extensivity implies that the energy should scale as &lt;span class=&quot;math-container&quot;&gt;$O(N)$&lt;/span&gt;. In the limit as &lt;span class=&quot;math-container&quot;&gt;$N\to\infty$&lt;/span&gt;, this means that the energy per monomer in DCI will actually vanish, which is clearly unphysical.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Szabo, Attila, and Neil S. Ostlund. Modern quantum chemistry : introduction to advanced electronic structure theory. Mineola, N.Y: Dover Publications, 1996. Print.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="5" LastEditDate="2022-01-04T20:19:18.917" LastActivityDate="2022-01-04T20:19:18.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8470" PostTypeId="1" AcceptedAnswerId="8474" CreationDate="2022-01-04T19:25:30.337" Score="4" ViewCount="2279" Body="&lt;p&gt;I would like to optimize the following code. In real applications, the number of snapshots can be 10000, and for each of them, the lengths can be &lt;code&gt;length_list = np.arange(0, 13, 0.01)&lt;/code&gt;. So, it takes ages for it to calculate the properties of matter that I want.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;list_shot = list(np.arange(0, 100, 50)) &#xA;list_lens = list(np.arange(10))&#xA;list_total = []&#xA;&#xA;for shot in list_shot:&#xA;    print(&amp;quot;-&amp;quot;, shot)&#xA;    list_out = []&#xA;&#xA;    for lens in list_lens:&#xA;        val = shot * lens&#xA;        list_out.append(val)&#xA;    print(list_out)&#xA;&#xA;    list_total.append(list_out) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Basically, the above code is just a simple representation of a code that I need running much faster than it's presently running.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="4219" LastEditorUserId="5" LastEditDate="2022-01-06T14:28:00.713" LastActivityDate="2022-01-06T15:08:57.883" Title="Is there a way to do array broadcasting faster, or without using loops?" Tags="|high-performance-computing|python|" AnswerCount="4" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="8471" PostTypeId="1" CreationDate="2022-01-04T20:09:09.083" Score="7" ViewCount="353" Body="&lt;p&gt;I'm trying to write a restricted Hartree Fock code in Fortran that reads in a file of zeroth-iteration 1 and 2 electron integrals (FCIDUMP format) and uses them to do the SCF procedure from an initial guess of a density matrix. The thing I'm struggling with is the 8-fold symmetry of the 2-electron integrals and how I can leverage it to construct my Coulomb and Exchange matrices efficiently.&lt;/p&gt;&#xA;&lt;p&gt;FCIDUMP files use the symmetries of 1 and 2 electron integrals to save space, i.e. since &lt;span class=&quot;math-container&quot;&gt;$H_{\text{core},p,q}$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$H_{\text{core},q,p}$&lt;/span&gt;, it will only print matrix elements of &lt;span class=&quot;math-container&quot;&gt;$H_{core}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$p \geq q$&lt;/span&gt;. Thus, reading in the matrix elements from FCIDUMP makes a lower triangular matrix which must be symmetrized along the diagonal to get the &lt;span class=&quot;math-container&quot;&gt;$H_{core}$&lt;/span&gt; matrix. Easy enough:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;h_core = e1ints&#xA;do q =1,norb&#xA;    do p =1,q&#xA;        h_core(p,q) = h_core(q,p) !lower triangular to symmetric&#xA;    end do&#xA;end do&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where &lt;code&gt;norb&lt;/code&gt; is the number of spatial orbitals (i.e. the dimension of the Fock matrix is &lt;code&gt;norb*norb&lt;/code&gt;) and &lt;code&gt;e1ints&lt;/code&gt; is the lower triangular matrix I've constructed from FCIDUMP. Of course, it's more memory-efficient to keep the matrix lower-diagonal, but since &lt;span class=&quot;math-container&quot;&gt;$H_{core}$&lt;/span&gt; must be added to the Fock matrix eventually, I don't think there's any way around this.&lt;/p&gt;&#xA;&lt;p&gt;The same printing methodology holds true for the 2 electron integrals, where the symmetry is&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\small (pq|rs) = (pq|sr) = (qp|sr) = (qp|rs) = (rs|pq) = (rs|qp) = (sr|qp) = (sr|pq)\tag{1}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where I'm getting tripped up is&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;how much more time and memory symmetrizing a &amp;quot;lower triangular&amp;quot; 4-dimensional electron repulsion integral (ERI) tensor will take&lt;/li&gt;&#xA;&lt;li&gt;generally thinking about how to code the following across eight-fold symmetry instead of two-fold.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The general formula for the elements of the Coulomb and Exchange matrices, respectively, are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$J_{pq} = \sum_{r,s=1}^{\text{norb}} (pr|qs)P_{rs}\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$K_{pq} = \sum_{r,s=1}^{\text{norb}} (pr|sq)P_{rs}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the density matrix. Since of the &lt;span class=&quot;math-container&quot;&gt;$\text{norb}^4$&lt;/span&gt; elements of the full ERI tensor, I only have &lt;span class=&quot;math-container&quot;&gt;$$\frac{\frac{\text{norb}(\text{norb}+1)}{2}\cdot(\frac{\text{norb}(\text{norb}+1)}{2}+1)}{2}\tag{4}$$&lt;/span&gt; of them (for a &lt;span class=&quot;math-container&quot;&gt;$n\times n$&lt;/span&gt; triangular matrix, there are &lt;span class=&quot;math-container&quot;&gt;$\frac{n(n+1)}{2}$&lt;/span&gt; nonzero matrix elements).&lt;/p&gt;&#xA;&lt;p&gt;How can I efficiently use this symmetry to construct the &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; matrices without making the ERI tensor huge by symmetrizing it? Since the tensor is not used explicitly in the construction of the Fock matrix, I don't think it makes sense to symmetrize it - I'm just at a loss for how to get around this. There are codes on GitHub that deal with FCIDUMP files, but after many hours of searching, I unfortunately haven't been able to find one that uses these files in the way I need to. With a fully symmetrized ERI tensor, I could do something like this, but there must be a more efficient way that avoids symmetrizing, right?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;do i =1,norb&#xA;    do j =1,norb&#xA;        mat2int(i,j) = 0.0 !Coulomb + Exchange together&#xA;        do k =1,norb&#xA;            do l =1,norb&#xA;                mat2int(i,j) = mat2int(i,j) + density_mat(k,l)*(2*e2ints_sym(i,j,k,l) - e2ints_sym(i,l,k,j))&#xA;            end do&#xA;        end do&#xA;    end do&#xA;end do&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerDisplayName="user4763" LastEditorDisplayName="user4763" LastEditDate="2022-01-06T20:09:51.807" LastActivityDate="2022-01-06T20:09:51.807" Title="Exploiting 8-fold symmetry of ERI tensor for building Coulomb and Exchange matrices" Tags="|hartree-fock|from-chem-se|integrals|fcidump|fortran|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8472" PostTypeId="2" ParentId="8468" CreationDate="2022-01-04T20:18:58.877" Score="7" Body="&lt;h2&gt;Coupled Cluster and MBPT methods&lt;/h2&gt;&#xA;&lt;p&gt;The basis for this answer is the Brueckner-Goldstone linked-diagram theorem which applies to many-body perturbation theory (MBPT) and coupled-cluster methods. The original papers by Bruckner (1955) and Goldstrone (1957) are given in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1329/5&quot;&gt;my answer explaining what about size-extensivity means&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The most important part to remember is that when using only linked diagrams, a method based on this diagramatic approach will be size-consistent. Size-&lt;em&gt;inconsistency&lt;/em&gt; is also sometimes associated with the presence of &amp;quot;unlinked diagrams&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;For closed-shell systems, RHF is size-consistent, and therefore size-extensivity of a method to treat correlation beyond RHF is sufficient for guaranteeing size-consistency of the post-RHF method. For systems that dissociate into open-shell fragments, a UHF reference might have spin contamination, so one must be careful when using UHF, but it's still possible to generate a linked-diagram expansion from a UHF reference.&lt;/p&gt;&#xA;&lt;p&gt;MBPT and coupled cluster methods happen to both be linked-diagram expansions which can be made on top of either an RHF or UHF reference wavefunction, and therefore MBPT and coupled cluster methods derived in this way (e.g. CCSD and CCSD(T)) are size-extensive and therefore in this case, also size-consistent.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-01-04T20:18:58.877" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8473" PostTypeId="2" ParentId="8471" CreationDate="2022-01-04T21:54:10.897" Score="6" Body="&lt;p&gt;AFAIK the standard way is to obtain the memory efficiency at the expense of some code repetition in the innermost loop. A preliminary example goes like:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Construct a nested loop that only loops over the non-redundant &lt;code&gt;(i,j,k,l)&lt;/code&gt; quartets. Say by&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;do i =1,norb&#xA;    do j =1,i&#xA;        do k =1,i&#xA;            do l =1,k&#xA;                if(k==i .and. l&amp;gt;j) cycle&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;In the innermost loop, you can use the non-symmetrized integral &lt;code&gt;e2ints(i,j,k,l)&lt;/code&gt;, either by reading it from disk on-the-fly or by fetching it from an array in the memory. Enumerate all possible ways that &lt;code&gt;e2ints(i,j,k,l)&lt;/code&gt; (and its symmetry-equivalent analogues, e.g. &lt;code&gt;e2ints(i,j,l,k)&lt;/code&gt;, &lt;code&gt;e2ints(k,l,i,j)&lt;/code&gt; etc.) participates in the Fock building. You should come up with a maximum of 8 occurrences of this integral in the Coulomb term, and another 8 occurrences in the exchange term. When i==j or k==l or (i==k .and. j==l) etc., the number of terms are even fewer. You can either write a select case clause to deal with all the possible cases, or write a general case code that assumes &lt;code&gt;(i,j,k,l)&lt;/code&gt; are mutually different, and scale the &lt;code&gt;density_mat(*,*)*e2ints(i,j,k,l)&lt;/code&gt; contributions by a symmetrization factor (e.g. &lt;code&gt;density_mat(k,l)*e2ints(i,j,k,l)&lt;/code&gt; should be scaled by 0.5 when &lt;code&gt;k&lt;/code&gt; and &lt;code&gt;l&lt;/code&gt; are equal) to avoid over-counting. The former approach has fewer FLOPs but requires 100~200 lines of additional code, while the latter approach has more FLOPs but gives a more elegant code.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The above approach is already essentially optimal in terms of memory. It can then be optimized for computational time, as follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Some additions can be saved by taking advantage of the transpose symmetry of &lt;code&gt;density_mat&lt;/code&gt;. For example &lt;code&gt;mat2int(i,j) = mat2int(i,j) + density_mat(k,l)*e2ints(i,j,k,l); mat2int(i,j) = mat2int(i,j) + density_mat(l,k)*e2ints(i,j,k,l)&lt;/code&gt; can be reduced to &lt;code&gt;mat2int(i,j) = mat2int(i,j) + 2.d0*density_mat(k,l)*e2ints(i,j,k,l)&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Similarly, some computation can be saved by taking advantage of the transpose symmetry of &lt;code&gt;mat2int&lt;/code&gt;, but this is a more subtle issue. The trick is to: (1) whenever a term is being added to &lt;code&gt;mat2int(i,j)&lt;/code&gt; and an equivalent term is being added to &lt;code&gt;mat2int(j,i)&lt;/code&gt; (where &lt;code&gt;i&lt;/code&gt; is not equal to &lt;code&gt;j&lt;/code&gt;), only perform the former calculation; (2) whenever a term is being added to &lt;code&gt;mat2int(i,i)&lt;/code&gt;, scale the term by 0.5; (3) after all &lt;code&gt;(i,j,k,l)&lt;/code&gt; quartets have been processed, add one line &lt;code&gt;mat2int = mat2int + transpose(mat2int)&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Skip the quartet &lt;code&gt;(i,j,k,l)&lt;/code&gt; if the absolute value of &lt;code&gt;e2ints(i,j,k,l)&lt;/code&gt; is sufficiently small.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The above tricks (plus OpenMP parallelization) should already give you a code that rivals the best codes in terms of efficiency (but note that the contraction of integrals with density matrix elements is usually not the rate-determining step; rather, the bottleneck is usually the calculation of the integrals and/or the I/O of the FCIDUMP file), at least for molecules that are small enough such that the size of the FCIDUMP file is still reasonable. However, expect that your code expands to ~100 lines, and expect that most of the lines are copy-pasted from a previous line and then edited (thus error-prone). There are also some other optimizations that I did not mention, because they only make a difference when the molecule is so large that the FCIDUMP file cannot be stored on a typical disk.&lt;/p&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-01-04T21:54:10.897" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8474" PostTypeId="2" ParentId="8470" CreationDate="2022-01-04T22:30:41.727" Score="10" Body="&lt;p&gt;What you're trying to do can actually be done &lt;em&gt;&lt;strong&gt;very&lt;/strong&gt;&lt;/em&gt; quickly, &lt;em&gt;&lt;strong&gt;without&lt;/strong&gt;&lt;/em&gt; any loops, and can even be ported to make valuable use of a GPU.&lt;/p&gt;&#xA;&lt;p&gt;Here's a quick example that you can test yourself in &lt;a href=&quot;https://octave-online.net/&quot; rel=&quot;noreferrer&quot;&gt;octave-online&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;shots=0:50:250&#xA;lens = 0:10&#xA;bsxfun(@times,shots',lens)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The outputs are as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;shots=[0    50   100   150   200   250]&#xA;lens =[0    1    2    3    4    5    6    7    8    9   10]&#xA;bsxfun(@times,shots',lens)&#xA;ans =&#xA;&#xA;      0      0      0      0      0      0      0      0      0      0      0&#xA;      0     50    100    150    200    250    300    350    400    450    500&#xA;      0    100    200    300    400    500    600    700    800    900   1000&#xA;      0    150    300    450    600    750    900   1050   1200   1350   1500&#xA;      0    200    400    600    800   1000   1200   1400   1600   1800   2000&#xA;      0    250    500    750   1000   1250   1500   1750   2000   2250   2500&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For shots up to 10,000 in steps of 50, the calculation takes &lt;code&gt;5.6e-5&lt;/code&gt; seconds on a CPU:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tic;shots=0:50:10000;lens=0:10;bsxfun(@times,shots',lens);toc;&#xA;Elapsed time is 5.79357e-05 seconds.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With an extremely un-optimized &lt;code&gt;FOR LOOP&lt;/code&gt; in octave-online, I repeated the calculation 100,000 times and the total CPU time was 1.97 seconds:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tic;for i=1:1e5;shots=0:50:10000;lens=0:10;bsxfun(@times,shots',lens);end;toc;&#xA;Elapsed time is 1.96675 seconds.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Believe it or not, this single function called &lt;code&gt;bsxfun&lt;/code&gt; which stands for &amp;quot;binary singleton expansion function&amp;quot;  was the basis for porting &lt;a href=&quot;https://github.com/HPQC-LABS/FeynDyn&quot; rel=&quot;noreferrer&quot;&gt;my code for calculating Feynman integrals for open quantum systems numerically&lt;/a&gt; from CPUs onto GPUs (though I used &lt;code&gt;bsxfun&lt;/code&gt; for the CPU version too since this saves enormous time compared to using loops or other functions), which lead to huge speed-ups (more and more as the arrays got bigger). A paper about this: &amp;quot;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465513002294?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;Dattani (2013) FeynDyn: A MATLAB program for fast numerical Feynman integral calculations for open quantum system dynamics on GPUs&lt;/a&gt;&amp;quot; explains the story.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If you need to run this on a GPU you can ask a separate question about that and I'll answer that&lt;/strong&gt; (it's been a while since I've done development for GPUs).&lt;/p&gt;&#xA;&lt;h1&gt;In Python&lt;/h1&gt;&#xA;&lt;p&gt;In Python the task accomplished by &lt;code&gt;bsxfun&lt;/code&gt; is known as &amp;quot;broadcasting&amp;quot; and is implemented in &lt;code&gt;numpy.broadcast&lt;/code&gt; so that when you multiply two arrays, you &lt;strong&gt;automatically&lt;/strong&gt; get nearly exactly the result that you desire here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;shots = np.array([1.0, 2.0, 3.0])&#xA;lens = np.array([2.0, 2.0, 2.0])&#xA;shots * lens&#xA;array([ 2.,  4.,  6.])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;numpy.broadcast&lt;/code&gt; documentation will then tell you how to generalize to work with more elements in the way that &lt;code&gt;bsxfun&lt;/code&gt; does in MATLAB/Octave.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-05T01:18:04.007" LastActivityDate="2022-01-05T01:18:04.007" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8475" PostTypeId="2" ParentId="8457" CreationDate="2022-01-04T22:47:05.793" Score="8" Body="&lt;p&gt;Phil's answer is absolutely correct. In non-collinear spinor calculation The spin for each state (at a specific k-point and specific band) can points towards different direction. However, since spin is still a good quantum number, we still have pairs of states in which one electron's spin points toward one direction and the other toward the opposite direction, the only difference is that for different pairs, the axis of which spins lie on can differ.&lt;/p&gt;&#xA;&lt;p&gt;What Phil said in his answer is probably the most direct way of calculating this. Here, on a technical note, I can think of two ways of actually doing this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Using the &lt;a href=&quot;http://www.wannier.org&quot; rel=&quot;noreferrer&quot;&gt;Wannier90&lt;/a&gt;'s spin projection option (see example 17 in Wannier90's tutorial).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Using the weights obtained from spinor projections onto atomic orbitals. This can be achieved for VASP using &lt;a href=&quot;https://github.com/QijingZheng/pyband&quot; rel=&quot;noreferrer&quot;&gt;pyband package&lt;/a&gt;. You can use the following command line option to enable this feature:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;pyband --occ 1 --lsorbit --spin z --occL --occLC_cbar_vmin -1 --occLC_cbar_vmax 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the meaning of each command line option can be checked using:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pyband -h&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm not familiar with quantum espresso but presumably the same thing can also be done. &lt;/p&gt;&#xA;" OwnerUserId="1804" LastActivityDate="2022-01-04T22:47:05.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8476" PostTypeId="2" ParentId="8460" CreationDate="2022-01-04T23:48:11.053" Score="4" Body="&lt;p&gt;No, you don't have to put the pseudohydrogen at the mid-point of the bond. Putting it at the mid-point is an attempt to put it close to its optimal location, on the assumption that any X-H bond will be short (for a generic element X), and half of the X-X bond length is a good approximation. A simple alternative is to estimate how long the X-H bond would be, convert that to a fraction of the X-X bond, and place the pseudohydrogen that far along.&lt;/p&gt;&#xA;&lt;p&gt;There is a significant potential problem with placing the pseudohydrogen exactly along the X-X bond: it preserves the symmetry of the bulk X-X. Most simulation programs will preserve input symmetry, either by explicitly enforcing it, or simply because the computed force will be symmetric, and hence have zero component in any symmetry-breaking direction. If you are not interested at all in the passivated face, then this may be acceptable; however, be aware that if the actual ground state of the X-H face does &lt;em&gt;not&lt;/em&gt; have the same symmetry, then the symmetric face may be mechanically unstable. This means that if you compute phonon properties, for example, there would be large negative phonon frequencies arising from these unstable pseudohydrogen faces.&lt;/p&gt;&#xA;&lt;p&gt;A simple method to avoiding any such symmetry issues is to add a small amount of random noise to the pseudohydrogens after you have placed them. The noise needn't be large, perhaps up to 0.05 Angstroms; just enough to break the symmetry. If the system's ground state &lt;em&gt;does&lt;/em&gt; have the symmetry, then the forces will act to restore the symmetric geometry; if, however, the symmetric position is unstable, then the forces should be large enough to push the atoms further away and, eventually, to the correct locations.&lt;/p&gt;&#xA;&lt;p&gt;Whatever your choice of initial positions, it is usually wise to constrain all but the surface X and H for the initial geometry optimisation, at least if the optimisation is in absolute coordinates. If you don't do this, the optimisation will create a phonon-like displacement wave which travels through the slab at a rate of one atomic layer per geometry iteration, meaning that thick slabs can take an extremely large number of iterations to converge. (This problem should not be present in optimisers using delocalised internal coordinates, or similar relational coordinates.)&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-01-05T01:50:59.687" LastActivityDate="2022-01-05T01:50:59.687" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8477" PostTypeId="1" CreationDate="2022-01-04T23:49:07.980" Score="3" ViewCount="52" Body="&lt;p&gt;What is cutoff energy in solid state calculations? I would just like a detailed explanation and the applicable formulas!&lt;/p&gt;&#xA; &#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2022-01-05T03:14:14.053" LastActivityDate="2022-01-05T03:14:14.053" Title="Cutoff energy in Quantum ESPRESSO calculation" Tags="|quantum-espresso|solid-state-physics|terminology|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-06T19:45:08.247" ContentLicense="CC BY-SA 4.0" />
  <row Id="8478" PostTypeId="2" ParentId="8470" CreationDate="2022-01-04T23:53:01.737" Score="7" Body="&lt;p&gt;You can use dot multiplication to achieve this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;shot = np.array([np.arange(0, 100, 50)]).T&#xA;lens = np.array([np.arange(10)])&#xA;&#xA;total = np.dot(shot,lens)&#xA;print(total)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives you the below results:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[  0   0   0   0   0   0   0   0   0   0]&#xA; [  0  50 100 150 200 250 300 350 400 450]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-05T01:19:30.107" LastActivityDate="2022-01-05T01:19:30.107" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8479" PostTypeId="2" ParentId="8470" CreationDate="2022-01-05T01:44:42.533" Score="9" Body="&lt;p&gt;Assuming that your sample code is really what you are looking for (which I doubt judging by the full code example you had posted originally), the answer by @vtan707 would work, but is very awkward because of its requirement for specifically shaped 2D arrays. Having to do nested calls of &lt;code&gt;np.array&lt;/code&gt; on a single-element list of a function output kinda gives it away.&lt;/p&gt;&#xA;&lt;p&gt;In fact, your example code is essentially a verbose version of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Outer_product&quot; rel=&quot;nofollow noreferrer&quot;&gt;outer vector product&lt;/a&gt; where you multiply each element of one vector with each element of another one. You could simplify it to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;shot = np.arange(...)&#xA;lens = np.arange(...)&#xA;&#xA;total = np.outer(shot, lens)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As per @NikeDattani's request in the comments, here are some ipython timings with their larger arrays. The first one is using &lt;code&gt;np.outer&lt;/code&gt;, the second one reshapes the arrays into row and column vectors and lets numpy broadcast the result when using the &lt;code&gt;*&lt;/code&gt; operator:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;shots = np.arange(0,11) # 0 to 10 including&#xA;lens = np.arange(0,10001,50) # 0 to 10000 including&#xA;&#xA;%timeit -n 100000 np.outer(shots, lens)&#xA;4.33 µs ± 17.7 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)&#xA;&#xA;%timeit -n 100000 shots[:,None] * lens[None,:]&#xA;3.38 µs ± 19.1 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;sup&gt;(I've used the slightly obscure indexing using &lt;code&gt;None&lt;/code&gt; to create new dimensions here. For more info, see &lt;a href=&quot;https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dimensional Indexing Tools&lt;/a&gt; in the numpy docs.)&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;Because numpy is heavily optimized behind the scenes, there is no big performance difference between &lt;code&gt;np.outer&lt;/code&gt; and the reshaped example -- presumably because it falls back to the exact same operations anyway. The slight overhead we see might come from function calls.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Interesting side note:&lt;/em&gt; The processing times increase slightly for both strategies (to about 5 to 6 µs) if I reverse the two arrays.&lt;/p&gt;&#xA;&lt;p&gt;(Thanks also to @wflynny for doing some more timings &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8481&quot;&gt;in their answer&lt;/a&gt;.)&lt;/p&gt;&#xA;" OwnerUserId="1440" LastEditorUserId="1440" LastEditDate="2022-01-05T19:41:29.827" LastActivityDate="2022-01-05T19:41:29.827" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8480" PostTypeId="1" AcceptedAnswerId="8523" CreationDate="2022-01-05T08:24:05.923" Score="8" ViewCount="571" Body="&lt;p&gt;I often see some papers that don't use pseudohydrogen passivating the slab's bottom side when doing DFT simulation on the metal oxide's surface, for example, the following description is from &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacsau.1c00004&quot; rel=&quot;nofollow noreferrer&quot;&gt;a paper about TiO2&lt;/a&gt;. It doesn't use pseudohydrogen.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The calculated anatase TiO2 bulk lattice parameters of a = b = 3.89 Å&#xA;and c = 9.65 Å agree well with the experiment values of a = b = 3.79 Å&#xA;and c = 9.52 Å. (54) The anatase TiO2 (101) surface containing 72&#xA;atoms was constructed as a slab model with the addition of a 15 Å&#xA;vacuum layer. The atoms of the bottom three layers were fixed to&#xA;maintain the bulk properties. Replacing the highlighted&#xA;five-coordinated surface Ti atom with a Cu atom gave the Cu-doped TiO2&#xA;system, marked as Cu_TiO2.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But according to some other papers, for example, &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.79.115410&quot; rel=&quot;nofollow noreferrer&quot;&gt;Composition, structure, and stability of the rutile TiO2(110) surface: Oxygen depletion, hydroxylation, hydrogen migration, and water adsorption&lt;/a&gt;, whether using pseudohydrogen is influential on the electronic structure, just like shown in the following screenshot:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mIBJj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mIBJj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is: When do I need to passivate a slab's bottom side with pseudohydrogen?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-01-06T15:52:08.850" LastActivityDate="2022-01-11T13:07:12.613" Title="When to use pseudohydrogens to passivate a slab?" Tags="|density-functional-theory|vasp|2d-lattice|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="8481" PostTypeId="2" ParentId="8470" CreationDate="2022-01-05T18:02:39.070" Score="7" Body="&lt;p&gt;Just adding some timings for @Antimon's answer.  Using &lt;code&gt;numpy.outer&lt;/code&gt; is definitely the way to go IMO.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def list_version(shots, lens):&#xA;    list_total = []&#xA;    for shot in list_shot:&#xA;        list_out = []&#xA;&#xA;        for lens in list_lens:&#xA;            val = shot * lens&#xA;            list_out.append(val)&#xA;&#xA;        list_total.append(list_out) &#xA;    return list_total&#xA;&#xA;def numpy_version1(shots, lens):&#xA;    _shots = np.array(shots)&#xA;    _lens = np.array(lens)&#xA;    return np.outer(_shots, _lens)&#xA;&#xA;def numpy_version2(shots, lens):&#xA;    return np.outer(shots, lens)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Depending on the input type (meaning the original arrays are numpy arrays and don't need to be converted to lists), &lt;code&gt;numpy.outer&lt;/code&gt; can give a substantial (300 fold) increase in performance:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;arr_shot = np.arange(0, 10000)&#xA;arr_lens = np.linspace(0, 13, 0.01)&#xA;list_shot = list(arr_shot)&#xA;list_lens = list(arr_lens)&#xA;&#xA;%timeit list_version(list_shot, list_lens)&#xA;21.5 s ± 24.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)&#xA;&#xA;%timeit numpy_version1(list_shot, list_lens)&#xA;73 ms ± 75.2 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)&#xA;&#xA;%timeit numpy_version2(arr_shot, arr_lens)&#xA;72.2 ms ± 46.6 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Method&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: right;&quot;&gt;Time (ms)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Original&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: right;&quot;&gt;21500&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Native Numpy&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: right;&quot;&gt;72.2&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Numpy convert from list&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: right;&quot;&gt;73&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&lt;hr /&gt;&#xA;&lt;p&gt;In response to @Nike's comment below, I timed the numpy version over several scales of input array sizes:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;results = []&#xA;for m in np.logspace(1, 4, 10, base=10, dtype=int):&#xA;    for n in np.logspace(1, 4, 10, base=10, dtype=int):&#xA;        x = np.random.rand(m)&#xA;        y = np.random.rand(n)&#xA;        t = timeit.timeit(&amp;quot;numpy_version2(x, y)&amp;quot;, number=10, globals=globals())&#xA;        results.append((m, n, t))&#xA;data = pd.DataFrame(results, columns=[&amp;quot;size_shots&amp;quot;, &amp;quot;size_lens&amp;quot;, &amp;quot;time_numpy&amp;quot;])&#xA;data[&amp;quot;size_total&amp;quot;] = data.size_shots * data.size_lens&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This should produce 2 measurements of 10 iterations at every combination of array sizes (whose log10s are equally spaced) from 10 to 10,000.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eCnbL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eCnbL.png&quot; alt=&quot;Timings visualized&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;TLDR: OP's arrays are of the order of 10^5 and 10^3 elements which should take &amp;lt;10s (10^8 output elements takes &amp;lt;10s above).&lt;/p&gt;&#xA;" OwnerUserId="4765" LastEditorUserId="4765" LastEditDate="2022-01-06T15:08:57.883" LastActivityDate="2022-01-06T15:08:57.883" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8482" PostTypeId="5" CreationDate="2022-01-05T19:40:07.017" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-05T19:40:07.017" LastActivityDate="2022-01-05T19:40:07.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8483" PostTypeId="4" CreationDate="2022-01-05T19:40:07.017" Score="0" Body="Questions in which answers are in the style of &quot;code golfing&quot; in which users attempt to make more and more efficient code (whether in terms of the speed,.size, elegance, or anything else)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-01-05T19:40:07.017" LastActivityDate="2022-01-05T19:40:07.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8484" PostTypeId="1" CreationDate="2022-01-05T19:40:51.537" Score="4" ViewCount="119" Body="&lt;p&gt;A type of electrical amplifier is proposed in which only magnetism and it’s analogous current exists for the most part. There is no voltage and no wattage (to speak of) in which electricity has to noticeably exhibit Ohms Law. Once connections are made to an outside appliance, voltage appears, because none of the junctions in and around the load are shorted with each other nor with ground. But all of the nodes of the power supply section of the circuit are shorted with each other. So there are only two nodes in the power supply, the ground node on one terminal of the sine wave generator and the common node among all of the inductors on the other terminal of the sine wave generator.&lt;/p&gt;&#xA;&lt;p&gt;Self shorting all of the nodes (in common with each other) eliminates the effectiveness of utilizing any diodes, capacitors, or spark gaps. Only inductors have any relevance in this type of circuit.&lt;/p&gt;&#xA;&lt;p&gt;Since there is no electrical throughput except through the sine wave generator, mutual inductance has to be precisely tuned. And self inductance also has to be structured a certain way as shown below…&lt;/p&gt;&#xA;&lt;p&gt;Given a pair of coils (#1), and another pair of coils (#2), and a single coil (#3), and the following magnetic couplings among them:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #1 is between coils #1 and coils #2.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #2 is between coils #1 and coil #3.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #3 is between coils #2 and coil #3.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #1 is greater than or equal to the golden ratio of 0.618…&#xA;(e.g. 0.99).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #2 is precisely the square root of the difference between unity and coupling #1: &lt;span class=&quot;math-container&quot;&gt;$\sqrt{(1 - 0.99)} = \sqrt{(0.01)} = 0.1$&lt;/span&gt;, or 10%&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Coupling #3 is precisely the cube of the difference between unity and coupling #1...&#xA;ie, (1 - 0.99)^3 = (0.01)^3 = 0.000001, or 0.0001%.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the chances of effectively replicating super conductance (without altering temperature) by shorting out all of the nodes among all of these five coils and connect this common node to the output of a sine wave generator operating at 1 µV and a frequency of 1 MHz?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am assuming that the simulator environment (of a &lt;a href=&quot;https://ufile.io/ybwqggmj&quot; rel=&quot;nofollow noreferrer&quot;&gt;Micro-Cap circuit&lt;/a&gt; from Spectrum-Soft) is both theoretical and logical to assume that anything is possible within that environment and limited to that environment with no guarantees outside of that environment making it highly theoretical - not necessarily probable, nor possible - in the concrete world, but only guaranteed in the world of the abstract mathematics involved.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;In the physical world, it’s conjectural to assume it’s probability if coils #1 are made of iron, coils #2 are made of copper, and coil #3 is made of aluminum?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/YYsX7.png&quot; alt=&quot;drawing of circuit diagram&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/L76Jh.png&quot; alt=&quot;screenshot of Micro-Cap circuit&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/LlpCc.png&quot; alt=&quot;nodal voltages&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/dDS9e.png&quot; alt=&quot;first 20 µs of output&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/ruUQ5.png&quot; alt=&quot;first 10 ms of output&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://i.stack.imgur.com/PeqE3.png&quot; alt=&quot;First 120 ms of output&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since resistance merely governs voltage drop, any impedance of high resistance will foster our habitual tendency to solve a problem by increasing the voltage. This is known as the Ferranti Effect. On the other hand, a purely reactant impedance can, actually, overcome resistance and begin to exhibit characteristics analogous to superconductivity if the frequency of reactance is high enough to overcome resistance per unit time. Raising the frequency of a sine wave generator does not “cost” more energy. Nor does it defy physics’ conservation of energy. Yet, in this case, amplification of current occurs while voltage retains a zero status within the body of each inductor.&lt;/p&gt;&#xA;&lt;p&gt;It is not the conservation of energy which is being defied, here. Instead, it is Michael Faraday’s Law of Induction which is given a restraint, a limitation, of jurisdiction. For, it is not always necessary to move a coil through a magnetic field in order to manifest current inside of that coil. Purely reactive impedance, devoid of resistive impedance, is a satisfactory replacement.&lt;/p&gt;&#xA;&lt;p&gt;Frequency over time is equivalent to motion through space. Magnetic flux, or it’s analog, is rotating in both examples.&lt;/p&gt;&#xA;&lt;p&gt;The amplitude of a voltage source is not the only option available for supplying an energy input. The frequency of a low voltage source is another, because frequency is a potential form of energy. This is why the conservation of energy has not been defied, because conservation includes both kinetic and potential forms of energy. And Michael Faraday’s Law of Induction has simply been expanded to include a more pervasive definition.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Energy lost to resistance&amp;quot; merely accounts for the physical contribution of self-inductance. Mutual inductance is not taken into account probably because it is not a physical contribution; it is a non-physical mathematical contribution without any physical counterpart to justify its existence apart from the ephemeral relationship among lumped inductors (in the case of this circuit) and their mutual inductances.&lt;/p&gt;&#xA;&lt;p&gt;Energy conservation is a simple and straightforward affair whenever impedance is purely resistive as in a flashlight circuit. But whenever reactive impedance dominates resistive impedance, conservation of energy and the logical progression of energy production exceeding its consumption (due to resistive losses) does an about-face. Energy will remain mathematically accountable, but will lose any of its familiarity with our conditioned way of life... Energy will be consumed at a rate which is faster than it is being produced, because of stationary inductors generating negative watts in a negatively resistive environment.&lt;/p&gt;&#xA;&lt;p&gt;As an example, coils should theoretically become cool (endothermic) rather than warm or hot (exothermic) due to these coils absorbing heat rather than dissipating it under conventional expectations of their being positively resistive. But, due to resistive impedance shrinking its role into becoming submissive to reactive impedance, resistive impedance gets rescripted into an inversion of its resistive losses becoming resistive gains. And, unlike heat absorption from a coil's environment, electrically reactive power has no physical source for its energy. Instead, its energy arises from the mathematical behavior of: frequency, capacitance and inductance modifying a scant input of (so-called) normal energy into becoming almost entirely reactive.&lt;/p&gt;&#xA;&lt;p&gt;This transcendence of reactive power is always dependent upon real power for initiating its existence. But normalcy stops right there as the rate of amplification (of this conversion) escalates at an ever-increasing rate.&lt;/p&gt;&#xA;&lt;p&gt;A &amp;quot;load&amp;quot; would, normally, halt this escalation preventing it from surprising us. And loads come in several formats. A voltage source is one of them when substantial enough to do the job. A sufficiently low frequency of input is another.&lt;/p&gt;&#xA;&lt;p&gt;But the load of an appliance is not sufficient to suppress this escalation whenever its location carefully places it in the circuit where it won't suppress this escalation. Normally, this location is adjacent to its paltry source rather than somewhere else...&lt;/p&gt;&#xA;&lt;p&gt;Micro-Cap schematic...&#xA;&lt;img src=&quot;https://i.stack.imgur.com/JL5Vq.png&quot; alt=&quot;Micro-Cap schematic...&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;Nodal voltages...&#xA;&lt;img src=&quot;https://i.stack.imgur.com/xOOL8.png&quot; alt=&quot;Nodal voltages...&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;First set of virtual oscilloscope tracings...&#xA;&lt;img src=&quot;https://i.stack.imgur.com/lkxjD.png&quot; alt=&quot;First set of virtual oscilloscope tracings...&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;Second set of tracings...&#xA;&lt;img src=&quot;https://i.stack.imgur.com/niRdt.png&quot; alt=&quot;Second set of tracings...&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;I discovered this when I wrote a provisional patent proposal &lt;a href=&quot;http://vinyasi.info/mhoslaw/Provisional%20Patent%20Application%20-%2063221840.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this past summer&lt;/a&gt; by studying the behavior of a neon bulb spark gap. I calculated the total negative watts against the total positive watts to see if the generation of power versus its consumption would zero out. This would account for all energy expenditures. It didn't work except in the case of circuits which were regulated by a voltage source, such as: a simple simulation of a flashlight involving a resistor and a battery. It did not work for circuits with a precharged micro-voltage stored within a capacitor and if this precharged capacitor was inline with a neon bulb spark gap. The precharged condition would quickly dissipate and was superseded by a rising voltage which escalated at an exponential rate.&lt;/p&gt;&#xA;&lt;p&gt;This is why I hold this latest development to be so unique. Instead of a circuit dominated by explosive electromotive force, it is dominated by explosive magnetomotive force. Thus, current excels and voltage is suppressed. High voltage is so pervasive in our culture in which Tesla Coils abound. It is refreshing to see its alternative of high current without voltage!&lt;/p&gt;&#xA;&lt;p&gt;I caution against expecting a satisfactory accountability. Not when reactive impedance dominates resistive impedance will a physically-oriented accountability yield satisfaction. Instead, it may unhinge our sensibilities by producing unexpected results.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://vinyasi.info/patent/pri-vate/Burying%20our%20Overunity%20Circuits%20to%20Eliminate%20their%20Electrostatic%20Buildup.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Source for the images, above&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4766" LastEditorUserId="4766" LastEditDate="2022-01-07T16:52:34.970" LastActivityDate="2022-01-07T16:52:34.970" Title="Can superconductivity be faked by using precise mathematics in a simulated circuit &amp; specific materials in an actual circuit?" Tags="|mathematical-modeling|superconductivity|" AnswerCount="0" CommentCount="9" ClosedDate="2022-01-09T00:28:44.803" ContentLicense="CC BY-SA 4.0" />
  <row Id="8486" PostTypeId="1" AcceptedAnswerId="8487" CreationDate="2022-01-05T21:28:34.430" Score="8" ViewCount="222" Body="&lt;p&gt;I am wondering if there is a detailed explanation about how ASE chooses the INCAR tags, since VASP already provides default values for a lot of tags, does ASE choose the default values?&#xA;There are a few parameters that might be tricky, for example, ISMEAR should be different for different systems, it depends on whether the system is metal or semiconductor.&#xA;My question is: How does ASE choose the INCAR tags smartly or does ASE just choose the default values?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-06T07:52:20.310" Title="What is the principle of generating INCAR tags in ASE?" Tags="|density-functional-theory|vasp|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8487" PostTypeId="2" ParentId="8486" CreationDate="2022-01-05T22:40:03.953" Score="6" Body="&lt;p&gt;ASE in general picks the VASP default, by simply not including the tag if not directly asked for.  This is done by setting the tag to &amp;quot;None&amp;quot; which has no meaning in VASP.  Then when the INCAR is generated, the tag is simply not output, leaving VASP to fall back on its default behavior.&lt;/p&gt;&#xA;&lt;p&gt;For things such as the functional, ASE does attempt to set up things as properly as possible with regards to the VASP manual.  The &amp;quot;recommended&amp;quot; setup dataset also corresponds to the VASP wiki recommended pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;ASE does not set any defaults based on metal vs semiconductor, I vaguely think Pymatgen might have some functionality for this though.&lt;/p&gt;&#xA;&lt;p&gt;If you do not set kpoints, the gamma point will be used, however you must request the vasp_gam executable for the speedup associated with gamma point only calculations manually.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="697" LastEditDate="2022-01-06T07:52:20.310" LastActivityDate="2022-01-06T07:52:20.310" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8488" PostTypeId="1" CreationDate="2022-01-05T23:43:18.797" Score="8" ViewCount="266" Body="&lt;p&gt;I'm trying to model a 2D TMD (transition metal dichalcogenide) nanocrystal on a graphene substrate. I know how to generate 2D TMDs through the MX2 module, and I certainly know how to make graphene on ASE, but I am unsure how to stack the two together. Is there a specific module that could get the job done? The ASE documentation has not been too helpful.&lt;/p&gt;&#xA;&lt;p&gt;Any help would be appreciated!&lt;/p&gt;&#xA;" OwnerUserId="4768" LastEditorUserId="3770" LastEditDate="2023-07-14T17:19:31.607" LastActivityDate="2023-07-15T03:37:32.000" Title="How to stack a nanocrystal on top of a graphene slab in ASE?" Tags="|python|atomic-simulation-environment|graphene|" AnswerCount="1" CommentCount="3" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8489" PostTypeId="1" CreationDate="2022-01-05T23:56:39.213" Score="6" ViewCount="165" Body="&lt;p&gt;There are programs out there which calculate the binding affinity between a ligand and a target protein (Autodock 4, Autodock Vina, Chimera... etc). Is there any analogous program that can be used to calculate the binding affinities between two molecules?&lt;/p&gt;&#xA;&lt;p&gt;For my purposes, I'd like to computationally determine the binding affinity between crystalline hydroxyapatite and an analogue of a bisphosphonate molecule.&lt;/p&gt;&#xA;" OwnerUserId="4761" LastActivityDate="2022-01-05T23:56:39.213" Title="Any Open-Source, Free Software That Can Be Used to Computationally Calculate Binding Affinity Between Two Molecules?" Tags="|software|reference-request|software-recommendations|molecular-modeling|crystallography|" AnswerCount="0" CommentCount="5" ClosedDate="2022-09-07T03:11:03.047" ContentLicense="CC BY-SA 4.0" />
  <row Id="8490" PostTypeId="1" CreationDate="2022-01-04T21:58:59.273" Score="5" ViewCount="421" Body="&lt;p&gt;I was confronted with an error, upon trying to dock a minimized ligand to a target protein, that the &amp;quot;&lt;code&gt;service 'local' [is] unavailable&lt;/code&gt;&amp;quot;. I then realized that one must have an executable file to perform a local docking. &lt;strong&gt;What steps must I take to do this? Is there a file I must download somewhere?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4761" OwnerDisplayName="Thunderbolt114" LastEditorUserId="5" LastEditDate="2022-02-24T04:06:31.597" LastActivityDate="2022-02-24T04:06:31.597" Title="Autodock Vina Error on Chimera: Service &quot;local&quot; unavailable" Tags="|software|computational-chemistry|docking|" AnswerCount="0" CommentCount="2" ClosedDate="2022-09-07T03:09:25.277" ContentLicense="CC BY-SA 4.0" />
  <row Id="8491" PostTypeId="2" ParentId="2437" CreationDate="2022-01-06T05:33:13.767" Score="6" Body="&lt;p&gt;Your assumption that neutron-nucleus scattering is primarily via magnetic interaction is not correct.  Neutron-nucleus scattering is primarily from the strong interaction, which is (as its imaginative name suggests) stronger than electromagnetism.  While neutrons &lt;em&gt;can&lt;/em&gt; interact by scattering magnetically from electrons, as currently suggested by another answer, the neutron-electron interaction is much smaller than the neutron-nuclear interaction.&lt;/p&gt;&#xA;&lt;p&gt;Most nuclei have a “neutron separation energy” of order &lt;span class=&quot;math-container&quot;&gt;$\sim 8\rm\,MeV$&lt;/span&gt;: if a free neutron were to settle down and be trapped inside of a nucleus, that’s the amount of energy it would have to release.  Nuclei are smaller than atoms, and the nuclear interaction is short-range.  So to a free neutron, a crystal lattice looks more or less like empty space with a network of delta-function-like attractive potentials at the locations of the nuclei.&lt;/p&gt;&#xA;&lt;p&gt;When you solve the Schrödinger equation for a square well,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(\frac{\hat p^2}{2m} + V(\vec r)\right)\psi = E\psi&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;you find that a free particle has more momentum (and therefore shorter wavelength) inside of the well than outside.  For thermal-or-cold neutrons the difference is enormous: the free particle has milli-eV kinetic energy and angstrom-scale wavelength, while the piece of the wavefunction within the nucleus is mega-eV above the bottom of the well and has femtometer-scale wavelength.&lt;/p&gt;&#xA;&lt;p&gt;If you go through the freshman-quantum exercise of matching the wavefunction at the boundary of the square well, so that it is continuous and smooth, with spherical symmetry, you find something interesting. For nearly all widths and depths of the square well, the free part of the wavefunction will have a zero-crossing somewhere near the nuclear radius.  (I remember a good illustration of this in Golub’s textbook.) You can produce the same &lt;em&gt;external&lt;/em&gt; wavefunction if, instead of a finely-tuned attractive well, you imagine an infinite, repulsive barrier whose radius is the location of this zero in the wavefunction.  The radius of this made-up repulsive potential is called the “scattering length,” and the whole model is called the &lt;a href=&quot;https://en.wikipedia.org/wiki/Pseudopotential&quot; rel=&quot;noreferrer&quot;&gt;Fermi pseudopotential&lt;/a&gt;.  The scattering length is directly related to the scattering cross section.&lt;/p&gt;&#xA;&lt;p&gt;If you look at a table of scattering lengths and cross sections (like &lt;a href=&quot;https://www.ill.eu/fileadmin/user_upload/ILL/1_About_ILL/Documentation/NeutronDataBooklet.pdf&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt;, which used to be available as a little booklet that fit in your pocket), you’ll see that all of the even-even nuclei (like &lt;span class=&quot;math-container&quot;&gt;$\rm{}^{12}C_6$&lt;/span&gt;) have zero &lt;em&gt;incoherent&lt;/em&gt; scattering cross section, because even-even nuclei have no spin to exchange with the neutron.  But all of the coherent scattering cross sections are a a few barns, because all of the coherent scattering lengths are a few femtometers.  (There are a couple of low-mass nuclei where the scattering length is negative, because the zero in the wavefunction shows up on the wrong side of the origin, but even then the length scale is femtometers.)&lt;/p&gt;&#xA;&lt;p&gt;Contrast this with the &lt;a href=&quot;https://journals.aps.org/prc/abstract/10.1103/PhysRevC.51.3363&quot; rel=&quot;noreferrer&quot;&gt;neutron-electron scattering length&lt;/a&gt; of &lt;span class=&quot;math-container&quot;&gt;$10^{-3}$&lt;/span&gt; femtometers: the electrons are basically invisible, compared to the nuclei.&lt;/p&gt;&#xA;&lt;p&gt;Even for spin-incoherent scattering, it’s not right to think of the neutron-nucleus interaction as magnetic. The energy scales are wrong. The nuclear magneton &lt;span class=&quot;math-container&quot;&gt;$e\hbar/2m_N$&lt;/span&gt; is much smaller than the Bohr magneton &lt;span class=&quot;math-container&quot;&gt;$e\hbar/2m_e$&lt;/span&gt;, but incoherent neutron-nucleus scattering lengths are still mostly femtometer-ish.  Incoherent neutron scattering comes from spin exchange mediated by the strong force.&lt;/p&gt;&#xA;&lt;p&gt;So, that’s the answer to your title question.  Neutron scattering from carbon-12 isn’t about magnetism at all.  Neutron scattering from carbon-12 is about the neutron looking down into the abyss, wondering what its life would be like as part of a carbon-13, deciding that there is no place for it there, but having its long-distance behavior changed by the experience.&lt;/p&gt;&#xA;" OwnerUserId="1438" LastActivityDate="2022-01-06T05:33:13.767" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8492" PostTypeId="1" AcceptedAnswerId="8506" CreationDate="2022-01-06T17:17:29.180" Score="5" ViewCount="122" Body="&lt;p&gt;There is job.sh script in a lot of official VASP examples, for example: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Graphite_MBD_binding_energy&quot; rel=&quot;noreferrer&quot;&gt;Graphite MBD binding energy&lt;/a&gt;. it is used to help submit job on supercomputer&lt;br&gt;&#xA;But in the script, it usually uses &lt;code&gt;vaspcmd&lt;/code&gt;, which I am not sure what it is, I checked the vasp wiki and vasp help document, there is not explanation about it.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;What is vaspcmd?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;#&#xA;# To run VASP this script calls &lt;span class=&quot;math-container&quot;&gt;$vasp_std&#xA;# (or posibly $&lt;/span&gt;vasp_gam and/or $vasp_ncl).&#xA;# These variables can be defined by sourcing vaspcmd&#xA;. vaspcmd 2&amp;gt; /dev/null&#xA;&#xA;#&#xA;# When vaspcmd is not available and &lt;span class=&quot;math-container&quot;&gt;$vasp_std,&#xA;# $&lt;/span&gt;vasp_gam, and/or &lt;span class=&quot;math-container&quot;&gt;$vasp_ncl are not set as environment&#xA;# variables, you can specify them here&#xA;[ -z &quot;`echo $&lt;/span&gt;vasp_std`&amp;quot; ] &amp;amp;&amp;amp; vasp_std=&amp;quot;mpirun -np 8 /path-to-your-vasp/vasp_std&amp;quot;&#xA;[ -z &amp;quot;`echo &lt;span class=&quot;math-container&quot;&gt;$vasp_gam`&quot; ] &amp;amp;&amp;amp; vasp_gam=&quot;mpirun -np 8 /path-to-your-vasp/vasp_gam&quot;&#xA;[ -z &quot;`echo $&lt;/span&gt;vasp_ncl`&amp;quot; ] &amp;amp;&amp;amp; vasp_ncl=&amp;quot;mpirun -np 8 /path-to-your-vasp/vasp_ncl&amp;quot;&#xA;&#xA;#&#xA;# The real work starts here&#xA;#&#xA;&#xA;# Here the work starts&#xA;rm results.dat&#xA;&#xA;drct=$(pwd)&#xA;&#xA;for i in graphene graphite&#xA;do&#xA;  cd &lt;span class=&quot;math-container&quot;&gt;$drct/$&lt;/span&gt;i&#xA;  $vasp_std&#xA;done&#xA;&#xA;cd $drct&#xA;&#xA;# obtain total energy for graphite &#xA;en2=&lt;span class=&quot;math-container&quot;&gt;$(grep &quot;free  ene&quot; graphite/OUTCAR |tail -1|awk '{print $&lt;/span&gt;5}') &#xA;&#xA;# obtain total energy for graphene&#xA;en1=&lt;span class=&quot;math-container&quot;&gt;$(grep &quot;free  ene&quot; graphene/OUTCAR |tail -1|awk '{print $&lt;/span&gt;5}')&#xA;&#xA;# compute interlayer binding energy (eV/atom)&#xA;deltaE=&lt;span class=&quot;math-container&quot;&gt;$(echo print $&lt;/span&gt;en2/4 - $en1/2 |python)&#xA;&#xA;echo &amp;quot;Binding energy (eV/atom): &amp;quot; $deltaE &amp;gt;results.dat&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-07T17:05:31.057" Title="What is vaspcmd in job.sh of the official VASP examples?" Tags="|density-functional-theory|vasp|software-assistance|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8493" PostTypeId="1" CreationDate="2022-01-06T18:58:43.797" Score="2" ViewCount="42" Body="&lt;p&gt;Since the major problem with DFT is that the exact functional for exchange and correlation is not known, except for the free-electron gas (LDA from Thomas-Fermi model). The discovery of &amp;quot;the&amp;quot; exact exchange-correlation functional would be (in my opinion):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A Nobel prize winning discovery.&lt;/li&gt;&#xA;&lt;li&gt;Would transform the matter modelling world.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I wanted to ask what are the advancements on this front? How do physicists/mathematicians/SSP's and even chemists even go about solving this issue?&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="5" LastEditDate="2022-01-07T04:58:09.510" LastActivityDate="2022-01-07T04:58:09.510" Title="What are the most advanced or best methods we know so far to try and find the exact exchange-correlation energy functionals for all matter?" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="6" ClosedDate="2022-01-06T19:44:01.627" ContentLicense="CC BY-SA 4.0" />
  <row Id="8494" PostTypeId="2" ParentId="8451" CreationDate="2022-01-07T10:08:42.700" Score="5" Body="&lt;h1&gt;1. Interactive Phonon visualizer by Materials Cloud&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://interactivephonon.materialscloud.io/&quot; rel=&quot;noreferrer&quot;&gt;https://interactivephonon.materialscloud.io/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This tool allows to visualize the phonon dispersion calculated with an external software and display graphically the eigenstates, i.e., the normal modes of the lattice vibrations.&lt;/p&gt;&#xA;&lt;p&gt;With this tool, you can i) visualize the phonon dispersion along a path in the Brillouin Zone ii) visualize interactively a supercell of the crystal structure, where atoms oscillate according to the phonon normal modes of a point selected on the phonon dispersion plot and iii)show the vectors of oscillation, and change the oscillation speed and amplitude&#xA;&lt;a href=&quot;https://i.stack.imgur.com/WX0oe.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WX0oe.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;2 Phonon Visualizer by Henrique Miranda&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://henriquemiranda.github.io/phononwebsite/phonon.html&quot; rel=&quot;noreferrer&quot;&gt;https://henriquemiranda.github.io/phononwebsite/phonon.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This project aims to provide a simple way to visualize the lattice vibrations of different materials. The tool displays an animation of how the atoms vibrate according to any particular mode. By default you can visualize the phonon dispersion of a few selected materials . If you want to see your own calculations, the tool currently support phonon calculations from Abinit, Quantum Espresso and phononpy.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/hX6bv.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hX6bv.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2022-01-07T10:08:42.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8495" PostTypeId="1" AcceptedAnswerId="8501" CreationDate="2022-01-07T10:49:40.697" Score="3" ViewCount="133" Body="&lt;p&gt;I am trying to relax my model's structure by letting some atoms could move freely along some specific direction, in VASP, I could set selective dynamics, but it seems I could only adjust the freedom along with three different lattice directions, so what should I do if I wanna choose a special direction?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Autosave\of\TiO2_mp-2657_compute\(1\1\0)\(2)&#xA;1.0&#xA;+11.8767995834  +0.0000000000  +0.0000000000 &#xA; +0.0000000000 +13.1613998413  +0.0000000000 &#xA; +0.0000000000  +0.0000000000 +33.4453010559 &#xA;Ti O H C&#xA; 64 128 8 8&#xA;Selective&#xA;Direct&#xA; +0.1250000000  +0.2500000000  +0.1880100070  F F F&#xA; +0.1250000000  +0.0000000000  +0.2863900070  F F F&#xA; +0.1250000000  +0.2500000000  +0.3847799900  T T T&#xA; +0.1250000000  +0.0000000000  +0.4831599890  T T T&#xA; +0.0000000000  +0.0000000000  +0.1880100070  F F F&#xA; +0.0000000000  +0.2500000000  +0.2863900070  F F F&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-07T16:47:28.757" Title="How to keep the freedom of an atom along a specific direction in VASP?" Tags="|density-functional-theory|vasp|software-assistance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8496" PostTypeId="1" AcceptedAnswerId="8500" CreationDate="2022-01-07T10:57:05.367" Score="3" ViewCount="699" Body="&lt;p&gt;I often use selective dynamics to do structure optimization in VASP, but I am not sure how to do it when using ASE, it seems I could use the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;constraint&lt;/a&gt; class to tell ASE what I want to do.&#xA;My question is:&lt;br&gt;&#xA;When I use the &lt;code&gt;constraint&lt;/code&gt; class, does ASE generate the POSCAR that includes the &lt;code&gt;selective dynamics&lt;/code&gt; parameter? Or it is like the case of &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/gettingstarted/tut02_h2o_structure/h2o.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;optimizer&lt;/a&gt;, ASE could just use VASP as a calculator, and set the constraint outside the loop of VASP calculation?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1380" LastEditDate="2022-01-07T15:16:00.033" LastActivityDate="2022-01-07T16:44:08.047" Title="How could I generate the parameter of 'selective dynamics' in POSCAR with ASE?" Tags="|vasp|software-assistance|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8497" PostTypeId="1" AcceptedAnswerId="8502" CreationDate="2022-01-07T11:56:38.403" Score="5" ViewCount="1599" Body="&lt;p&gt;I am trying to understand the function of dipole correction in DFT. I find that there are two examples related to this topic on the VASP wiki.&lt;br&gt;&#xA;The first case is about &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Partial_DOS_of_CO_on_Ni_111_surface#Work_function&quot; rel=&quot;noreferrer&quot;&gt;CO on Ni 111 surface&lt;/a&gt;&lt;br&gt;&#xA;The input INCAR file is :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; general:&#xA;   ENMAX = 400&#xA;   SYSTEM = CO adsorption on Ni(111)&#xA;   ISMEAR = -5&#xA;   ALGO= Fast&#xA;&#xA; LDOS:&#xA;   LORBIT = 11&#xA;&#xA; workfunction:&#xA;   IDIPOL=3&#xA;   LDIPOL= .TRUE.&#xA;   LVHAR = .TRUE.&#xA;#  LVTOT = .TRUE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ptikf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ptikf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The second case is about &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Adsorption_of_H2O_on_TiO2&quot; rel=&quot;noreferrer&quot;&gt;Adsorption of H2O on TiO2&lt;/a&gt;&lt;br&gt;&#xA;The input INCAR file is :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM   = H2O_TiO2&#xA;ENMAX    = 400&#xA;ISMEAR   =  2&#xA;SIGMA = 0.05&#xA;EDIFF = 1e-6&#xA;EDIFFG = -0.05&#xA;IBRION = 2&#xA;POTIM = 0.5&#xA;NSW = 200&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4Zzvc.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4Zzvc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Apparently, the slabs of these two cases are both asymmetric, but it seems that the second case doesn't set dipole correction.&lt;br&gt; As far as I understand, when the slab model is asymmetric, I should always use dipole correction.&#xA;My question is:&lt;br&gt;&#xA;When should I use dipole correction?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-07T16:50:19.017" Title="When should I use dipole correction?" Tags="|density-functional-theory|vasp|dipole|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8498" PostTypeId="1" CreationDate="2022-01-07T15:08:23.963" Score="8" ViewCount="255" Body="&lt;p&gt;So if I write the &lt;a href=&quot;https://en.wikipedia.org/wiki/Action_(physics)&quot; rel=&quot;nofollow noreferrer&quot;&gt;action&lt;/a&gt; for a gas:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ S = \int (T -U) dt \tag{1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the kinetic energy and &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is potential energy.&lt;/p&gt;&#xA;&lt;p&gt;I suspect there is a constant term (which does not affect the equations of motion) for the gas (in classical mechanics). I was hoping to verify my &lt;s&gt; &lt;a href=&quot;https://drive.google.com/file/d/1deuIYhorbMBnIRoblhe_0q1P4CkIx3DD/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper's&lt;/a&gt;  idea &lt;/s&gt; (There is now an updated version see &lt;a href=&quot;https://drive.google.com/file/d/1K95v8crlBWsf2_3kFiEbRDMNa5xVBdOV/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;) up to equation &lt;span class=&quot;math-container&quot;&gt;$(19)$&lt;/span&gt;.The summary of ideas section wise are as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.1)$&lt;/span&gt; We consider an arbitrary potential which &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; everywhere until both the gas molecules collide.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.2)$&lt;/span&gt; Assuming a non-ideal collision (finite collision time) I get a non-zero action&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.3)$&lt;/span&gt; We use Newton's second law to find the finite collision time and the average force is considered as pressure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.4)$&lt;/span&gt; The deformed face of the molecule has an area which is also considered.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.5)$&lt;/span&gt; Since we are considering &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; spheres colliding which is a function of their relative velocity we can find the average momentum change assuming the collision is not a special event.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$(1.6)$&lt;/span&gt; The collision per unit 4-volume is mentioned as derived by Einstein.&lt;/p&gt;&#xA;&lt;p&gt;Combining all the above subsections we derive a constant action term:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S_c = \int \frac{N R \tilde V'(2R)}{\pi}  \frac{ \langle \mu \rangle \lambda }{k_B  } dt \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of particles, &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is the radius of the particle, &lt;span class=&quot;math-container&quot;&gt;$ \tilde V'(x)$&lt;/span&gt; is the spatial derivative potential and &lt;span class=&quot;math-container&quot;&gt;$ \frac{ \langle \mu \rangle \lambda }{k_B  } $&lt;/span&gt; are constants.&lt;/p&gt;&#xA;&lt;p&gt;Is this expression correct?&lt;/p&gt;&#xA;" OwnerUserId="1810" LastEditorUserId="5" LastEditDate="2022-01-26T03:14:23.317" LastActivityDate="2022-01-26T03:14:23.317" Title="Contribution in action from collisions for a gas?" Tags="|molecular-dynamics|thermodynamics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8499" PostTypeId="1" AcceptedAnswerId="8505" CreationDate="2022-01-07T16:30:43.740" Score="7" ViewCount="767" Body="&lt;p&gt;The standard procedure to calculate DOS or band structure is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Structure optimization,&lt;/li&gt;&#xA;&lt;li&gt;SCF calculation,&lt;/li&gt;&#xA;&lt;li&gt;non-SCF calculation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;According to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/CHGCAR&quot; rel=&quot;noreferrer&quot;&gt;vasp wiki&lt;/a&gt;, it is because:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Mind&lt;/strong&gt;: Since the charge density written to the file CHGCAR is not the self-consistent charge density for the positions on the CONTCAR file, do not perform a bandstructure calculation (ICHARG=11) directly after a dynamic simulation (IBRION=0).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But according to the result I got from the structure optimization:&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;CHGCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;unknown system                          &#xA;   1.00000000000000     &#xA;    13.950000    0.000000    0.000000&#xA;     0.000000   13.950000    0.000000&#xA;     0.000000    0.000000    8.928000&#xA;   O    Ti&#xA;   108    54&#xA;Direct&#xA;  0.268106  0.065717  0.167082&#xA;  0.065369  0.268163  0.166767&#xA;  0.101149  0.101162  0.000275&#xA;  0.231588  0.232049  0.000228&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;CONTCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O Ti                                   &#xA;   1.00000000000000     &#xA;    13.9500000000000011    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000   13.9500000000000011    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    8.9280000000000008&#xA;   O    Ti&#xA;   108    54&#xA;Direct&#xA;  0.2681055481518182  0.0657169184815687  0.1670824834593189&#xA;  0.0653691262260372  0.2681632907730134  0.1667673218695771&#xA;  0.1011490079420389  0.1011622291646118  0.0002747383173194&#xA;  0.2315880276338604  0.2320489480787421  0.0002283670824430&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;O Ti &#xA; 1.0000000000000000&#xA;    13.9500000000000011    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000   13.9500000000000011    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    8.9280000000000008&#xA; O   Ti &#xA; 108  54&#xA;Cartesian&#xA;  3.7365895255885855  0.9134104744114493  1.4879999999999789&#xA;  0.9134104744114493  3.7365895255885855  1.4879999999999789&#xA;  1.4115895255885178  1.4115895255885178  0.0000000000000000&#xA;  3.2384104744114151  3.2384104744114151  0.0000000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Apparently, the &lt;code&gt;CHGCAR&lt;/code&gt; file uses the same atom coordinate as &lt;code&gt;CONTCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does this mean that the VASP wiki is wrong and I don't have to do SCF calculation before calculating DOS or do I understand it wrong?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-01-07T16:47:10.980" LastActivityDate="2023-06-09T23:12:14.487" Title="Does SCF calculation have to be done before calculating DOS?" Tags="|density-functional-theory|vasp|software-assistance|density-of-states|self-consistent-field|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8500" PostTypeId="2" ParentId="8496" CreationDate="2022-01-07T16:44:08.047" Score="0" Body="&lt;p&gt;The &lt;code&gt;FixAtoms&lt;/code&gt; constraint will be turned into the selective dynamics tags as &amp;quot;F F F&amp;quot;.  ASE will also convert selective dynamics to this constraint when reading.&lt;/p&gt;&#xA;&lt;p&gt;I think the &lt;code&gt;FixedPlane&lt;/code&gt; and &lt;code&gt;FixedLine&lt;/code&gt; could in theory also work, but I am not sure they do since they support directions not aligned with the X, Y, and Z axis. If you need this and it doesn't work (just give it a try), you might ask on the ASE Matrix chat to see if someone is willing to add it for you or tell you how to change it yourself.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T16:44:08.047" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8501" PostTypeId="2" ParentId="8495" CreationDate="2022-01-07T16:47:28.757" Score="1" Body="&lt;p&gt;This is related to your other question, you are correct VASP only supports fixing atoms along the X, Y, and Z axis.  You can use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/optimize.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE optimizers&lt;/a&gt; with the &lt;code&gt;FixLine&lt;/code&gt; or &lt;code&gt;FixPlane&lt;/code&gt; &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;constraints&lt;/a&gt; to do this.  You just specify which atoms are constrained and which direction they are constrained to move in.&lt;/p&gt;&#xA;&lt;p&gt;Just be aware, ASE running VASP is slower than VASP running its own optimizer.  You can offset this by outputting the CHGCAR/WAVECAR or by using the &lt;code&gt;VaspInteractive&lt;/code&gt; calculator in ASE if the cell is not changing.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T16:47:28.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8502" PostTypeId="2" ParentId="8497" CreationDate="2022-01-07T16:50:19.017" Score="3" Body="&lt;p&gt;With a large enough vacuum, you don't need a dipole correction as badly to get good results.  Sometimes the correction can cause convergence issues or problems with single steps giving incorrect energies.&lt;/p&gt;&#xA;&lt;p&gt;The second calculation looks like a geometry optimization, so maybe this was done to improve stability; a dipole correction should be applied after converging the structure, but its not critical beforehand.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T16:50:19.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8503" PostTypeId="2" ParentId="8499" CreationDate="2022-01-07T16:54:26.507" Score="5" Body="&lt;p&gt;In the passage just above what you quoted, it says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For dynamic simulation (IBRION=0), the charge density on the file is the predicted charge density for the next step: i.e. it is compatible with the CONTCAR file, but incompatible with the last positions in the OUTCAR file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This means while the density in the CHGCAR file is a density for the position given in the CONTCAR, it is only a &lt;em&gt;predicted&lt;/em&gt; charge density, essentially the initial guess for the SCF at that position. This means you would still have to get the self-consistent density for that position.&lt;/p&gt;&#xA;&lt;p&gt;Note the quote you mentioned only applies to &lt;code&gt;IBRION=0&lt;/code&gt;, i.e. a molecular dynamics simulation. For your geometry optimization, the remainder of the previous paragraph confirms that the CHGCAR should be fine for determining a band structure:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For static calculations and relaxations (IBRION=-1,1,2) the written charge density is the self-consistent charge density for the last step and might be used e.g. for accurate band-structure calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-01-07T17:08:01.390" LastActivityDate="2022-01-07T17:08:01.390" CommentCount="4" CommunityOwnedDate="2022-01-07T16:54:26.507" ContentLicense="CC BY-SA 4.0" />
  <row Id="8504" PostTypeId="2" ParentId="8454" CreationDate="2022-01-07T16:55:31.783" Score="3" Body="&lt;p&gt;If the band gap increased when you moved to the supercell, its likely that your kpoint grid doesn't hit the ideal valence max/conduction minima.  This problem could occur in the SCF step, even if you use the same exact path for the primitive and supercell for the NSCF step.  This is especially likely if the primitive is gamma centered and the supercell is not, or vice versa.&lt;/p&gt;&#xA;&lt;p&gt;You should also check if you get a distortion in the supercell, this could also change the valence band position or conductance band position and increase or decrease the bandgap.  If you did not do a geometry optimization after making the supercell, this is unlikely to be the case though.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T16:55:31.783" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8505" PostTypeId="2" ParentId="8499" CreationDate="2022-01-07T17:01:54.753" Score="7" Body="&lt;p&gt;The community wiki by Tyberius is a bit misleading here, you are not doing molecular dynamics calculations (IBRION=0) but likely a geometry optimization (IBRION=1,2,3).  In the case of geometry optimization, the CHGCAR is not the predicted charge density, but is instead the charge density of the last completed step.&lt;/p&gt;&#xA;&lt;p&gt;For this reason, you should find no difference between doing an SCF calculation and just using the geometry optimization calculation.  However, I do advise still doing the SCF calculation since this is a good opportunity to refine the kpoint grid further (and check the forces at this stage to ensure they are still low).  You might do something like the following (numbers picked arbitrarily).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(3, 3, 3) for Geometry&lt;/li&gt;&#xA;&lt;li&gt;(6, 6, 6) for Single Point&lt;/li&gt;&#xA;&lt;li&gt;(24, 24, 24) for NSCF DOS&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T17:01:54.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8506" PostTypeId="2" ParentId="8492" CreationDate="2022-01-07T17:05:31.057" Score="4" Body="&lt;pre&gt;&lt;code&gt;#&#xA;# To run VASP this script calls &lt;span class=&quot;math-container&quot;&gt;$vasp_std&#xA;# (or posibly $&lt;/span&gt;vasp_gam and/or $vasp_ncl).&#xA;# These variables can be defined by sourcing vaspcmd&#xA;. vaspcmd 2&amp;gt; /dev/null&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As mentioned in the comments, the answer is actually in your question.  vaspcmd is just any script you provide that defines the &lt;code&gt;$vasp_std&lt;/code&gt;, &lt;code&gt;$vasp_gam&lt;/code&gt; and &lt;code&gt;$vasp_ncl&lt;/code&gt; variables which give the full path to the executables.  You must write this script, it is not provided since it depends on the installation location.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T17:05:31.057" CommentCount="0" CommunityOwnedDate="2022-01-07T17:05:31.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="8508" PostTypeId="2" ParentId="8459" CreationDate="2022-01-07T17:28:01.460" Score="4" Body="&lt;p&gt;Not a fully GUI solution but if we can assume you get a primitive cell to work with, Atomic Simulation Environment can generate your surface.&lt;/p&gt;&#xA;&lt;p&gt;For some extra spice, its common to want to make root surfaces such as &lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}$&lt;/span&gt;x&lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}$&lt;/span&gt;, so I included a final step which will do this assuming there is a valid &lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}$&lt;/span&gt;x&lt;span class=&quot;math-container&quot;&gt;$\sqrt{2}$&lt;/span&gt; to make.  There is also a &lt;code&gt;root_surface_analysis&lt;/code&gt; function if you are working with an unknown cell.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import surface, root_surface&#xA;from ase.io import read&#xA;from ase.visualize import view&#xA;&#xA;filename = &amp;quot;primitive.POSCAR&amp;quot;&#xA;layers = 4&#xA;miller = (1, 0, 0)&#xA;root = 2&#xA;&#xA;atoms = read(filename)&#xA;surf = surface(atoms, miller, layers)&#xA;&#xA;view(surf)&#xA;&#xA;root_surf = root_surface(surf, root)&#xA;&#xA;view(root_surf)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-07T17:28:01.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8509" PostTypeId="1" CreationDate="2022-01-07T20:02:04.083" Score="3" ViewCount="758" Body="&lt;p&gt;I understand that it's possible to calculate the Gibbs free energy of a system &lt;em&gt;ab initio&lt;/em&gt;, see for example: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6455/5&quot;&gt;How can we calculate the Gibbs free energy from first principles?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm wondering how I can do it for a simple solid in Quantum ESPRESSO?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2022-01-07T21:33:59.650" LastActivityDate="2022-01-07T21:33:59.650" Title="What input setting in Quantum ESPRESSO will allow me to calculate the free energy of a solid?" Tags="|quantum-espresso|electronic-structure|thermodynamics|software-input-file-request|free-energy|" AnswerCount="0" CommentCount="13" ClosedDate="2022-09-07T03:12:21.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="8510" PostTypeId="1" CreationDate="2022-01-07T21:21:44.963" Score="5" ViewCount="95" Body="&lt;p&gt;The figure below illustrates a 2x2x1 supercell of transition metal-doped CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; monolayer. The red, green, and black atoms represent Cr, I, and transition metal atoms, respectively. I want to calculate the energy of this doped monolayer in the AFM configuration, but I don't know how to set it. Please I need your urgent help on how to set the spins of the atoms for the AFM configuration for this doped monolayer. I mean which ones to set up, and which ones to set down? should I increase the supercell size?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/upEzi.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/upEzi.jpg&quot; alt=&quot; set&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-01-10T07:32:25.053" Title="How to set the AFM configuration in this doped monolayer system?" Tags="|density-functional-theory|vasp|magnetism|" AnswerCount="0" CommentCount="8" ClosedDate="2022-09-07T03:12:53.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="8511" PostTypeId="1" AcceptedAnswerId="8515" CreationDate="2022-01-08T11:36:16.507" Score="7" ViewCount="490" Body="&lt;p&gt;Question is based on further learning about the previously asked question - &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8454/does-nscf-calculations-on-supercell-gives-different-band-gap-than-the-unit-cell&quot;&gt;Do NSCF calculations on Supercell gives different band gap than the Unit Cell?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How should I compare SCF and NSCF calculations on both? How are Band structures compared?&#xA;The nbnd (that is number of electrons) increases when we increase number of atoms, that i have observed. What else can be checked here?&#xA;How do I make sure the super cell created is correct or not?&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="2077" LastEditDate="2022-01-09T07:11:09.143" LastActivityDate="2022-01-09T14:46:14.793" Title="What parameters should be checked on both unit cell and super cell to make sure the calculations are going fine?" Tags="|quantum-espresso|band-structure|bandgap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8513" PostTypeId="1" CreationDate="2022-01-09T01:29:19.733" Score="4" ViewCount="153" Body="&lt;p&gt;Input file for 221 MoS2&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;projwfc        &#xA;&#xA;prefix       = 'MoS2', &#xA;outdir       = './out',&#xA;deltae       = 0.1,&#xA;filproj      = 'MoS2-pdos.dat',&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Another file run is plot-pdos.gnu&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set autoscale         # scale axes automatically&#xA;unset log             # remove any log-scaling&#xA;unset label           # remove any previous labels&#xA;set xtic auto         # set xtics automatically&#xA;set ytic auto         # set ytics automatically&#xA;set title &amp;quot;Density of states (DOS) of MoS2 crystal&amp;quot;&#xA;set xlabel &amp;quot;Energy (ev)&amp;quot;&#xA;set ylabel &amp;quot;PDOS&amp;quot;&#xA;set arrow 1 from -1.1888,0 to -1.1888,2 nohead ls 10 dt 2      #Fermienegy&#xA;plot &amp;quot;atom_Mo_s.dat&amp;quot; using 1:2 title 'Mo s orbital' with linespoints,\&#xA;     &amp;quot;atom_Mo_p.dat&amp;quot; using 1:2 title 'Mo p orbital' with linespoints,\&#xA;     &amp;quot;atom_Mo_d.dat&amp;quot; using 1:2 title 'Mo d orbital' with linespoints,\&#xA;     &amp;quot;atom_S_s.dat&amp;quot; using 1:2 title 'S s orbital' with linespoints,\&#xA;     &amp;quot;atom_S_p.dat&amp;quot; using 1:2 title 'S p orbital' with linespoints,\&#xA;     &amp;quot;atom_Mo_tot.dat&amp;quot; using 1:2 title 'Mo total' with linespoints,\&#xA;     &amp;quot;atom_S_tot.dat&amp;quot; using 1:2 title 'S total' with linespoints&#xA;pause -1 &amp;quot;Hit any key to continue\n&amp;quot;   #so that the code doesn't exit automatically&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The correct PDOS should look like this&#xA;&lt;a href=&quot;https://i.stack.imgur.com/39c0d.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/39c0d.jpg&quot; alt=&quot;Correct PDOS&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;While ploting pdos output using xmgrace, I am getting additional slanting lines my plot. How do resolve this?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ct3Vi.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ct3Vi.jpg&quot; alt=&quot;Incorrect PDOS&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4777" LastEditorUserId="7" LastEditDate="2022-01-09T03:30:09.440" LastActivityDate="2022-01-09T03:30:09.440" Title="Why extra lines in PDOS plot using xmgrace" Tags="|quantum-espresso|visualization-software|density-of-states|" AnswerCount="0" CommentCount="8" ClosedDate="2022-09-07T03:13:32.620" ContentLicense="CC BY-SA 4.0" />
  <row Id="8514" PostTypeId="2" ParentId="2" CreationDate="2022-01-09T10:09:42.887" Score="6" Body="&lt;p&gt;Probably this recent paper by James Kirkpatrick, Aron Cohen and co-workers is getting closest to it: &amp;quot;Pushing the frontiers of density functionals by solving the fractional electron problem&amp;quot;, &lt;a href=&quot;https://dx.doi.org/10.1126/science.abj6511&quot; rel=&quot;noreferrer&quot;&gt;Science 2021, 374, 1385&lt;/a&gt;. In it, they used Deep Learning to describe charge delocalization and strong correlation, resulting in the DM21 functional.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2022-01-09T10:09:42.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8515" PostTypeId="2" ParentId="8511" CreationDate="2022-01-09T14:46:14.793" Score="7" Body="&lt;p&gt;Here are some thoughts about calculations involving primitive cells and supercells:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The energy cutoff used should be the same between a primitive cell and a supercell.&lt;/li&gt;&#xA;&lt;li&gt;The density of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points should be the same between a primitive cell and a supercell. This may not be possible in practice if the grid sizes are not commensurate with the supercell sizes, and if this is the case, you want to build the corresponding grid that gives the closest possible density between the two sizes. In general, if the primitive cell calculations are well-converged with respect to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid size, this should be fine.&lt;/li&gt;&#xA;&lt;li&gt;There are several programs that allow you to automate the construction of a supercell from a given primitive cell, and one I like is &lt;a href=&quot;http://www.c2x.org.uk&quot; rel=&quot;noreferrer&quot;&gt;c2x&lt;/a&gt;. If the forces and stresses for the primitive cell vanish, then they should also vanish for the supercell. There may be slight differences due to the possible &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point grid inconsistency described above. If you perform a geometry relaxation and the supercell changes, then this means that your primitive cell was not a true primitive cell of the system. In what follows, I will assume that the primitive cell of the system was a true primitive cell.&lt;/li&gt;&#xA;&lt;li&gt;The density of states of the primitive and supercell should be the same, so this is a good quantity to check that you are calculating electronic quantities correctly.&lt;/li&gt;&#xA;&lt;li&gt;The band structures will look different superficially due to band folding (when you increase the cell size the Brillouin zone becomes correspondingly smaller). However, there should still be a one-to-one correspondence between the band structures of the primitive cell and the supercell. A good overview of band folding can be found in this other &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/700/why-is-the-band-structure-of-a-supercell-more-dense-than-for-simple-cell&quot;&gt;question/answer&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If the supercell is &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; times larger than the primitive cell, then the number of electrons in the supercell should be &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; times larger. However, due to band folding, the number of bands at a given &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point will also be &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; times larger, so the Fermi energy and density of states will not change.&lt;/li&gt;&#xA;&lt;li&gt;For a band structure calculation for the same reciprocal space path, you need to convert the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-points used in the primitive cell to those corresponding to the supercell, taking into account that the supercell Brillouin zone is smaller. This will still exhibit band folding, but you should be able to identify the primitive cell bands within the band folded supercell bands as the paths are now identical.&lt;/li&gt;&#xA;&lt;li&gt;You can use band unfolding to have a more direct comparison between the primitive and supercell band structures.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-01-09T14:46:14.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8516" PostTypeId="1" CreationDate="2022-01-09T16:45:44.317" Score="8" ViewCount="725" Body="&lt;p&gt;There are many benchmark sets in different branches of computational chemistry and physics, that are frequently used to assess the &amp;quot;average error&amp;quot; of a method for a certain property, on a certain set of systems. For example, &lt;a href=&quot;https://www.chemie.uni-bonn.de/pctc/mulliken-center/software/GMTKN/gmtkn&quot; rel=&quot;nofollow noreferrer&quot;&gt;the GMTKN benchmark sets of the Grimme group&lt;/a&gt;, &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.4952647&quot; rel=&quot;nofollow noreferrer&quot;&gt;the benchmark set compiled by the Head-Gordon group&lt;/a&gt;, as well as numerous other benchmark sets, are used for the benchmarking of reaction energies and barriers of molecular reactions, non-covalent interaction energies of molecules, and relative conformational energies etc. Other benchmark sets may deal with excitation energies, geometries, etc., just to name a few, and some may be more focused on periodic systems and surfaces. Usually, one computes the data entries of a benchmark set using several methods (with different functionals, basis sets, etc.), compares them against the reference values, and calculates the mean absolute error and/or RMS error of the methods. The results are then used to assess the relative accuracy of the methods, and can also be used as an estimate of the typical error magnitudes of the methods.&lt;/p&gt;&#xA;&lt;p&gt;Now, observe that what one really obtains from the benchmarking process, is the average error of a method when the user randomly picks a system from the benchmark set and calculates that system. However, in the real world the user is instead choosing a system based on their research project, and calculating that system. This raises a question: the error estimate from the benchmark study can only make sense, if the benchmark set is a statistically representative sample from all the systems that will be calculated after the benchmark paper is published. But none of the benchmark sets that I'm aware of seem to have taken this into account. Specifically, consider two systems A and B in a benchmark set. I've never seen any benchmark set that assigns appropriate weights to these two systems based on how likely a user will compute a system that is similar to A, compared to computing a system that is similar to B. Most benchmark sets do try to include a sufficiently diverse set of molecules, but even if a benchmark set has exhausted all important classes of systems, this still does not guarantee that it is a statistically representative sample from all the systems that will be studied in the future, unless they are explicitly weighted to account for this. A few benchmark sets (like GMTKN) do assign weights to the different entries of the benchmark set, but the weights only depend on the difficulty of the corresponding calculations; data entries that are hard to compute accurately often receive a smaller weight so that they do not unnecessarily dominate the error function. In particular, a commonly studied type of molecule is not weighted more than a rarely studied, but equally difficult type of molecule.&lt;/p&gt;&#xA;&lt;p&gt;So my question is: &lt;strong&gt;are there any benchmark sets, regardless of what property or what kind of systems they focus on, that explicitly take into account the number of researchers in different subfields, and use this to weight its entries?&lt;/strong&gt; For example, if a benchmark set contains the SARS-CoV and SARS-CoV-2 spike proteins, and there are 10x more publications on the latter than the former, then the latter receives a weight factor that is 10 times that of the former, even though the two molecules are very similar in terms of prediction difficulty. Only by this way can we point to the benchmark result and say, e.g. &amp;quot;this is the expected error of a random computational prediction of the binding Gibbs free energy of a spike protein with an acceptor/antibody&amp;quot;. Of course, what we really want is the expected error of a future research result, not a research result randomly drawn from published data, so an even more rigorous approach is to include a time series prediction that predicts how many publications related to a certain class of molecules will come out in the next few years. But maybe this is too far of a stretch from what has actually been done in existing benchmark sets, so I'm already more than pleased to know if any existing benchmark set has its entries weighted by publication counts, or other metrics that can be used to measure the popularity of different classes of molecules (or materials in general) based on existing publications.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="5" LastEditDate="2022-01-10T03:12:02.140" LastActivityDate="2022-01-10T03:12:02.140" Title="Is there a benchmark paper that takes into account how often each molecule is studied?" Tags="|computational-chemistry|ab-initio-calculations|electronic-structure|molecular-modeling|databases|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="8517" PostTypeId="2" ParentId="8516" CreationDate="2022-01-09T23:40:33.853" Score="9" Body="&lt;p&gt;I don't think any studies such as this are currently available, however I think they violate a general feeling I have about &amp;quot;benchmarking&amp;quot;.  Studies which do general benchmarks are designed more to highlight &lt;strong&gt;when&lt;/strong&gt; a method is good, not &lt;strong&gt;which&lt;/strong&gt; method is good.&lt;/p&gt;&#xA;&lt;p&gt;If I benchmark pbesol vs pbe and I find that pbesol works well for solids for example, this is useful information that can be used to pre-screen methods.  However, if I instead say that 80% of catalysis models do not work with pbesol, this does nobody any good because they do not know which group they are in.&lt;/p&gt;&#xA;&lt;p&gt;These benchmarking sets are designed to intentionally find corner cases representative of real world research, if you expect a method to have issues with halogen bonding then you include some halogen bonding benchmarks in your dataset.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-09T23:40:33.853" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8518" PostTypeId="2" ParentId="8516" CreationDate="2022-01-10T03:08:24.943" Score="6" Body="&lt;p&gt;I certainly see the value in having such a benchmark dataset.&lt;/p&gt;&#xA;&lt;p&gt;If asked why such a dataset doesn't yet exist, I would say that it already takes an enormous amount of work to create things like the GMTKN dataset which you mentioned. Often this is an  &lt;em&gt;&lt;strong&gt;underappreciated&lt;/strong&gt;&lt;/em&gt; amount of work, such that only the people that made the dataset really have an appreciation for how much work goes into it, and more often than not, people underestimate how much work goes into it. Also, often people simply use the dataset and cite it by name without citing the papers that lead to it, a bit like how people very often name the basis set they use without citing the paper in which its parameters were initially optimized and presented to the world.&lt;/p&gt;&#xA;&lt;p&gt;What you are proposing, has some enormous advantages over the the databases that currently exist, but would take an extraordinarily larger amount of effort to complete compared to the already enormous work that goes into making datasets like the GMTKN. For example, &lt;strong&gt;how exactly are you going to find out how many papers pertain to O3, and how many pertain to CO2?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://scholar.google.ca/citations?user=qjKZRHUAAAAJ&amp;amp;hl=en&quot; rel=&quot;noreferrer&quot;&gt;Peter Bernath&lt;/a&gt; hosts the &lt;a href=&quot;http://diref.uwaterloo.ca/admin_login.html&quot; rel=&quot;noreferrer&quot;&gt;DiRef&lt;/a&gt; database, in which you can type the formula for any diatomic molecule and get what was attempted to be every single paper ever published about that diatomic molecule, but this took a huge amount of &lt;em&gt;&lt;strong&gt;manual&lt;/strong&gt;&lt;/em&gt; effort from his full-time employee Sean Macleod (not a student, but a senior IT staff who would have likely been paid more than double the average post-doc at the time). The database was probably quite complete in its earlier days, but it went out-of-date extremely quickly. I remember another one of his full-time employees (again not a student) having been tasked with updating it &lt;em&gt;circa&lt;/em&gt; 2018 and he was given a &lt;em&gt;&lt;strong&gt;long&lt;/strong&gt;&lt;/em&gt; list of journals and was searching in attempt to find every single paper mentioning a molecule in the title and/or abstract, in each of the journals in that list. I don't think this project of updating the database was very successful, and if it was, the database would still only be accurate up to 2018. Now, imagine doing that for triatomics and larger (knowing the vast diversity of molecules that appear in datasets like the GMTKN one)!&lt;/p&gt;&#xA;&lt;p&gt;For diatomics, I think we could at least come up with a rough estimate of the number of times a paper has been published about that molecule, by counting the query results you get in DiRef for that molecule, and we could scale a functional's error according to the number of times that molecule has been mentioned in the title or abstract of a publication. This would still require a lot of manual work even for diatomics, where DiRef exists, and would require far more work for triatomics and larger moelcules, and even after all this effort, the whole concept will still have its flaws, such as the fact that (for example) H2 and Li2 will appear in that database far more times than many of the other molecules, simply because there's so many &amp;quot;fundamental&amp;quot; studies on these extremely simple benchmark systems, which doesn't necessarily reflect how often you are likely to be using the tested functional on those molecules in a real-world application.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-01-10T03:08:24.943" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8520" PostTypeId="1" CreationDate="2022-01-10T18:55:59.263" Score="5" ViewCount="638" Body="&lt;p&gt;I am trying to calculate the band gap type(Direct or Indirect) of TiO2-Rutile, according to the &lt;a href=&quot;https://materialsproject.org/materials/mp-2657/#electronic-structure&quot; rel=&quot;noreferrer&quot;&gt;Material Project&lt;/a&gt;, rutile is a direct bandgap type semiconductor. The VBM and CBM are both at the Gamma point.&lt;BR&gt;&#xA;I try to use VASP to calculate the electronic structure of a TiO2-Rutile unit cell. But my result shows that it is an indirect bandgap material. As shown below, there is a small energy difference of two valence bands at Gamma and M points.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;If my calculation is wrong, how should I improve my calculation settings? I have already tried to increase the number of k-points, set &lt;code&gt;PREC = Accurate&lt;/code&gt;, but still got the same result.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/B49bz.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B49bz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I follow the standard procedure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Structure optimization&lt;/li&gt;&#xA;&lt;li&gt;Self-consistent field calculation&lt;/li&gt;&#xA;&lt;li&gt;Band structure calculation&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here are the input files used for 1st step:&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;DFT+U Calculation&#xA;LDAU   = .TRUE.        (Activate DFT+U)&#xA;LDATYPE=  2            (Dudarev; only U-J matters)&#xA;LDAUL  =  2 -1         (Orbitals for each species)&#xA;LDAUU  =  4.5  0         (U for each species)&#xA;LDAUJ  =  0  0         (J for each species)&#xA;LMAXMIX=  4            (Mixing cut-off; 4-d, 6-f)&#xA; &#xA;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;# ICHARG =  11         (Non-self-consistent: GGA/LDA band structures)&#xA;LREAL  = .FALSE.       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Accurate       (Precision level)&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;# NPAR   = 4           (Max is no. nodes; don't set for hybrids)&#xA;# Nwrite = 2           (Medium-level output)&#xA;# KPAR   = 2           (Divides k-grid into separate groups)&#xA;# NGX    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGY    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGZ    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA; &#xA;Electronic Relaxation&#xA;ISMEAR =  0            (Gaussian smearing; metals:1)&#xA;SIGMA  =  0.05         (Smearing value in eV; metals:0.2)&#xA;NELM   =  90           (Max electronic SCF steps)&#xA;NELMIN =  6            (Min electronic SCF steps)&#xA;EDIFF  =  1E-08        (SCF energy convergence; in eV)&#xA;# GGA  =  PS           (PBEsol exchange-correlation)&#xA; &#xA;Ionic Relaxation&#xA;NSW    =  100          (Max ionic steps)&#xA;IBRION =  2            (Algorithm: 0-MD; 1-Quasi-New; 2-CG)&#xA;ISIF   =  2            (Stress/relaxation: 2-Ions, 3-Shape/Ions/V, 4-Shape/Ions)&#xA;EDIFFG = -2E-03        (Ionic convergence; eV/AA)&#xA;# ISYM =  2            (Symmetry: 0=none; 2=GGA; 3=hybrids)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Spacing Value to Generate K-Mesh: 0.040&#xA;0&#xA;Gamma&#xA;   5   5   8&#xA;0.0  0.0  0.0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Ti2 O4&#xA;1.0&#xA;        4.6532721519         0.0000000000         0.0000000000&#xA;        0.0000000000         4.6532721519         0.0000000000&#xA;        0.0000000000         0.0000000000         2.9692029953&#xA;   Ti    O&#xA;    2    4&#xA;Cartesian&#xA;     2.326636076         2.326636076         1.484601498&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.909342430         3.743929583         1.484601498&#xA;     3.743929583         0.909342430         1.484601498&#xA;     1.417293646         1.417293646         0.000000000&#xA;     3.235978645         3.235978645         0.000000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here are the input files used for 2nd step:&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DFT+U Calculation&#xA;LDAU   = .TRUE.        (Activate DFT+U)&#xA;LDATYPE=  2            (Dudarev; only U-J matters)&#xA;LDAUL  =  2 -1         (Orbitals for each species)&#xA;LDAUU  =  4.5  0         (U for each species)&#xA;LDAUJ  =  0  0         (J for each species)&#xA;LMAXMIX=  4            (Mixing cut-off; 4-d, 6-f)&#xA; &#xA;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;# ICHARG =  11         (Non-self-consistent: GGA/LDA band structures)&#xA;LREAL  = .FALSE.       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Accurate       (Precision level)&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;# NPAR   = 4           (Max is no. nodes; don't set for hybrids)&#xA;# Nwrite = 2           (Medium-level output)&#xA;# KPAR   = 2           (Divides k-grid into separate groups)&#xA;# NGX    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGY    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGZ    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA; &#xA;Electronic Relaxation&#xA;ISMEAR =  0            (Gaussian smearing; metals:1)&#xA;SIGMA  =  0.05         (Smearing value in eV; metals:0.2)&#xA;NELM   =  90           (Max electronic SCF steps)&#xA;NELMIN =  6            (Min electronic SCF steps)&#xA;EDIFF  =  1E-08        (SCF energy convergence; in eV)&#xA;LORBIT =  11&#xA;# GGA  =  PS           (PBEsol exchange-correlation)&#xA; &#xA;Ionic Relaxation&#xA;#NSW    =  100          (Max ionic steps)&#xA;#IBRION =  2            (Algorithm: 0-MD; 1-Quasi-New; 2-CG)&#xA;#ISIF   =  2            (Stress/relaxation: 2-Ions, 3-Shape/Ions/V, 4-Shape/Ions)&#xA;EDIFFG = -2E-03        (Ionic convergence; eV/AA)&#xA;# ISYM =  2            (Symmetry: 0=none; 2=GGA; 3=hybrids)&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Spacing Value to Generate K-Mesh: 0.020&#xA;0&#xA;Gamma&#xA;  11  11  17&#xA;0.0  0.0  0.0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here are the input files used for 3rd step:&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DFT+U Calculation&#xA;LDAU   = .TRUE.        (Activate DFT+U)&#xA;LDATYPE=  2            (Dudarev; only U-J matters)&#xA;LDAUL  =  2 -1         (Orbitals for each species)&#xA;LDAUU  =  4.5  0         (U for each species)&#xA;LDAUJ  =  0  0         (J for each species)&#xA;LMAXMIX=  4            (Mixing cut-off; 4-d, 6-f)&#xA; &#xA;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;ICHARG =  11         (Non-self-consistent: GGA/LDA band structures)&#xA;LREAL  = .FALSE.       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Accurate       (Precision level)&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;# NPAR   = 4           (Max is no. nodes; don't set for hybrids)&#xA;# Nwrite = 2           (Medium-level output)&#xA;# KPAR   = 2           (Divides k-grid into separate groups)&#xA;# NGX    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGY    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGZ    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA; &#xA;Electronic Relaxation&#xA;ISMEAR =  0            (Gaussian smearing; metals:1)&#xA;SIGMA  =  0.05         (Smearing value in eV; metals:0.2)&#xA;NELM   =  90           (Max electronic SCF steps)&#xA;NELMIN =  6            (Min electronic SCF steps)&#xA;EDIFF  =  1E-08        (SCF energy convergence; in eV)&#xA;LORBIT =  11&#xA;# GGA  =  PS           (PBEsol exchange-correlation)&#xA; &#xA;Ionic Relaxation&#xA;#NSW    =  100          (Max ionic steps)&#xA;#IBRION =  2            (Algorithm: 0-MD; 1-Quasi-New; 2-CG)&#xA;#ISIF   =  2            (Stress/relaxation: 2-Ions, 3-Shape/Ions/V, 4-Shape/Ions)&#xA;EDIFFG = -2E-03        (Ionic convergence; eV/AA)&#xA;# ISYM =  2            (Symmetry: 0=none; 2=GGA; 3=hybrids)&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Path Generated by VASPKIT.&#xA;   20&#xA;Line-Mode&#xA;Reciprocal&#xA;   0.0000000000   0.0000000000   0.0000000000     GAMMA          &#xA;   0.0000000000   0.5000000000   0.0000000000     X              &#xA; &#xA;   0.0000000000   0.5000000000   0.0000000000     X              &#xA;   0.5000000000   0.5000000000   0.0000000000     M              &#xA; &#xA;   0.5000000000   0.5000000000   0.0000000000     M              &#xA;   0.0000000000   0.0000000000   0.0000000000     GAMMA          &#xA; &#xA;   0.0000000000   0.0000000000   0.0000000000     GAMMA          &#xA;   0.0000000000   0.0000000000   0.5000000000     Z              &#xA; &#xA;   0.0000000000   0.0000000000   0.5000000000     Z              &#xA;   0.0000000000   0.5000000000   0.5000000000     R              &#xA; &#xA;   0.0000000000   0.5000000000   0.5000000000     R              &#xA;   0.5000000000   0.5000000000   0.5000000000     A              &#xA; &#xA;   0.5000000000   0.5000000000   0.5000000000     A              &#xA;   0.0000000000   0.0000000000   0.5000000000     Z              &#xA; &#xA;   0.0000000000   0.5000000000   0.0000000000     X              &#xA;   0.0000000000   0.5000000000   0.5000000000     R              &#xA; &#xA;   0.5000000000   0.5000000000   0.0000000000     M              &#xA;   0.5000000000   0.5000000000   0.5000000000     A              &#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-10T18:55:59.263" Title="How to get the right type of bandgap(indirect/direct) in VASP?" Tags="|vasp|electronic-structure|bandgap|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:51:22.197" ContentLicense="CC BY-SA 4.0" />
  <row Id="8521" PostTypeId="1" CreationDate="2022-01-10T19:04:56.183" Score="6" ViewCount="328" Body="&lt;p&gt;I am trying to understand the workflow of VASP, so I make a simple diagram to show how VASP updates the related file during iteration. Did I make it right?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/V28Nr.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/V28Nr.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-10T19:04:56.183" Title="The workflow of VASP" Tags="|density-functional-theory|vasp|software-assistance|" AnswerCount="0" CommentCount="3" ClosedDate="2022-02-24T14:24:52.727" ContentLicense="CC BY-SA 4.0" />
  <row Id="8522" PostTypeId="2" ParentId="6225" CreationDate="2022-01-10T19:41:27.090" Score="9" Body="&lt;p&gt;I know this was long ago, but for those that find the same problem in the future, the &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;sisl&lt;/code&gt;&lt;/a&gt; python package might be useful. It has a generic &lt;code&gt;Grid&lt;/code&gt; object and it knows how to read the grids from VASP:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;grid = sisl.get_sile(&amp;quot;path/to/your/CHGCAR&amp;quot;).read_grid()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then &lt;code&gt;grid&lt;/code&gt; is a sisl &lt;code&gt;Grid&lt;/code&gt; object, so:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;grid.grid&lt;/code&gt; contains the &lt;code&gt;numpy&lt;/code&gt; array of values if that's all you need.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;grid.geometry&lt;/code&gt; contains the structure to which the grid corresponds (as a sisl &lt;code&gt;Geometry&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;grid&lt;/code&gt; has plenty of methods to help you in common manipulations (see &lt;a href=&quot;https://zerothi.github.io/sisl/api/generated/sisl.Grid.html?highlight=grid#sisl.Grid&quot; rel=&quot;noreferrer&quot;&gt;docs&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;grid.plot()&lt;/code&gt; will allow you to visualize it quickly in python in 1D, 2D and 3D (see &lt;a href=&quot;https://zerothi.github.io/sisl/visualization/viz_module/showcase/GridPlot.html&quot; rel=&quot;noreferrer&quot;&gt;docs&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here's &lt;a href=&quot;https://zerothi.github.io/sisl/index.html&quot; rel=&quot;noreferrer&quot;&gt;the package documentation&lt;/a&gt; and if you have doubts you can ask them on &lt;a href=&quot;https://discord.gg/5XnFXFdkv2&quot; rel=&quot;noreferrer&quot;&gt;discord&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2022-01-10T19:41:27.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8523" PostTypeId="2" ParentId="8480" CreationDate="2022-01-10T21:12:57.060" Score="8" Body="&lt;p&gt;TL;DR If bonds are broken in creating the lower surface of the slab, then passivation is probably a good idea.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Let's start with a little bit of context:&lt;/p&gt;&#xA;&lt;p&gt;Slab calculations in computational materials science are often (but not always) designed to study the properties of a surface of a macroscopic crystal.&#xA;In these cases, an accurate model of physical reality would involve a slab of macroscopic thickness.&lt;/p&gt;&#xA;&lt;p&gt;Unless you are open to using Green-function techniques for modeling a semi-infinite slab (which may not be readily available in standard codes), this is not going to be computationally tractable.&#xA;It is also not necessary: you just need your slab to be thick enough to converge the surface property of interest to the accuracy you desire.&lt;/p&gt;&#xA;&lt;p&gt;While the number of layers of the slab is your most straightforward convergence parameter, increasing the number of layers can substantially increase the number of atoms in your calculation, i.e. be very expensive.&#xA;This opens the door for computational tricks to achieve convergence of surface properties at lower numbers of layers - e.g. making the bottom of the slab more &amp;quot;bulk-like&amp;quot; by fixing the lattice constants of some bottom layers to their known bulk value(s) and/or by passivating unwanted surface states at the bottom of the slab through the addition of (pseudo-)hydrogens (which only adds 1 electron per atom =&amp;gt; cheap).&lt;/p&gt;&#xA;&lt;p&gt;This brings us to your question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When do I need to passivate a slab's bottom side with pseudohydrogen?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;One obvious answer is that you don't really &lt;em&gt;need&lt;/em&gt; to - you can always&lt;sup&gt;1&lt;/sup&gt; achieve convergence by increasing the thickness of your slab.&lt;/p&gt;&#xA;&lt;p&gt;So, when would passivation be &lt;em&gt;useful&lt;/em&gt; to improve the accuracy of the calculation?&#xA;I'm sorry to say that I don't have a rigorous answer to this question&lt;sup&gt;2&lt;/sup&gt; but it seems reasonable to think that passivation will be useful, if bonds are broken in the process of creating the lower surface of the slab.&lt;/p&gt;&#xA;&lt;p&gt;Of course this rule depends on the notion of a bond.&#xA;It certainly applies not only to the breaking of covalent bonds (which would result in the &amp;quot;dangling bonds&amp;quot; you mention): the Au(111) surface is an example of a metal surface with a Shockley surface state, which decays exponentially towards the bulk.&lt;/p&gt;&#xA;&lt;p&gt;The figure below from the &lt;a href=&quot;http://hdl.handle.net/10810/52178&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ph.D. thesis of Nora Gonzalez Lakunza&lt;/a&gt; shows the difference between a bare slab (left) and a hydrogen-passivated slab (right).&#xA;In the bare slab, the surface states from the top and bottom of the slab overlap, forming bonding and antibonding linear combinations, which give rise to an artificial band splitting in the surface band structure that can affect how the surface interacts with adsorbed molecules (details in Appendix I.b).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/N8Ikv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/N8Ikv.png&quot; alt=&quot;Au(111) surface state&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As shown in this thesis, by passivating the lower side of the slab you can converge the electronic structure at the surface with ~4 rather than with 9 Au layers - not bad!&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, however, that's not where complications end: a perfect Au(111) surface does not exist in nature.&#xA;Instead, the breaking of bonds at the surface causes the Au(111) surface to reconstruct, which increases the size of the surface unit cell from &lt;span class=&quot;math-container&quot;&gt;$1\times 1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$22\times\sqrt{3}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, if you're creating your surface by polishing a crystal, you're going to have (reconstructed) Au(111) terraces of finite width as shown in the figure below (Figure 3.13 from &lt;a href=&quot;https://doi.org/10.3929/ethz-a-7358981&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ph.D. thesis of Roberto Gaspari&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1vJnr.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1vJnr.jpg&quot; alt=&quot;Stepped Au(111) surface&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Of course, the steps in between terraces have their own peculiar electronic structure - at some point, the question always becomes: how accurately do you need to represent reality?&lt;/p&gt;&#xA;&lt;p&gt;I'm not really familiar with the TiO2(110) surface but I read in chapter 3.5 of &lt;a href=&quot;https://phys.au.dk/fileadmin/site_files/publikationer/phd/Anders_Ronnau.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this thesis by Anders Rønnau&lt;/a&gt; that this termination involves substantial atomic relaxation of the subsurface layers, so it seems reasonable that a suitable passivation will help.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; One aspect we don't discuss here are polar surfaces (surfaces that contain a net charge). For such cases, a dipole correction will be necessary for the correct description of the electric field at the slab's surface.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt; For a more rigorous analysis of when surface states arise in the tight binding picture, see e.g. &lt;a href=&quot;https://doi.org/10.1016/0079-6816(93)90055-Z&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. Amongst other conclusions, Forstmann mentions &amp;quot;On surfaces of threedimensional crystals, one expects as many surface states as there are surface atoms&amp;quot; - but it is important to understand the assumptions that go into this statement (it is certainly not true in general).&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2022-01-11T13:07:12.613" LastActivityDate="2022-01-11T13:07:12.613" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8524" PostTypeId="2" ParentId="7199" CreationDate="2022-01-10T23:10:43.420" Score="9" Body="&lt;p&gt;Here are a few things you could try:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;./configure --with-hdf5-libs=&amp;lt;options&amp;gt; --with-hdf5-include=&amp;lt;path&amp;gt;&lt;/code&gt; (note the double dashes)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;export HDF5_LIBS='-L/path/to/your/lib -lhdf5 -lhdf5fortran'&lt;/code&gt; before you &lt;code&gt;./configure&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Use the new cmake route to install QE (see example instructions &lt;a href=&quot;https://github.com/conda-forge/qe-feedstock/blob/3129a9c3b64a82169293dccca0a4a3cc4a2ebfaf/recipe/build.sh#L11-L24&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) which should be more robust and will likely replace the &lt;code&gt;configure&lt;/code&gt; route at some point in the future&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For the cherry on top, I &lt;a href=&quot;https://github.com/conda-forge/qe-feedstock/pull/27&quot; rel=&quot;noreferrer&quot;&gt;just added&lt;/a&gt; HDF5 support to the &lt;code&gt;qe&lt;/code&gt; conda-forge feedstock, i.e. you can now (in 1-2h)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;conda install -c conda-forge qe&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;on Linux on MacOS to get a HDF5-enabled, pre-compiled Quantum ESPRESSO 7.0.&lt;/p&gt;&#xA;&lt;p&gt;Cheers!&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="5" LastEditDate="2022-01-10T23:15:34.397" LastActivityDate="2022-01-10T23:15:34.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8525" PostTypeId="2" ParentId="6714" CreationDate="2022-01-11T13:00:40.370" Score="3" Body="&lt;p&gt;Check DFTB+ with its xtb implementation.&#xA;Among DFT codes working with ASE, take a look on GPAW, where you also have an external field option.&lt;/p&gt;&#xA;" OwnerUserId="4786" LastActivityDate="2022-01-11T13:00:40.370" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8526" PostTypeId="1" AcceptedAnswerId="8535" CreationDate="2022-01-11T16:54:46.300" Score="5" ViewCount="640" Body="&lt;p&gt;I see a lot of post-processing tools for VASP, including ASE, VASPKIT,Pymagten and some other customized codes. They all read the VASP output files like a normal text file. Sometimes I would meet incompatibility issues between the parsers of some tools and VASP output files. I am wondering if there is a standard format or parser of the VASP output files?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-12T04:09:59.703" Title="The standard format and parser of VASP output files" Tags="|vasp|software-assistance|atomic-simulation-environment|pymatgen|vaspkit|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8527" PostTypeId="2" ParentId="7196" CreationDate="2022-01-11T17:08:21.217" Score="3" Body="&lt;p&gt;The &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt; can &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;generate surfaces&lt;/a&gt; and &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/calculators/lammps.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;run &lt;code&gt;LAMMPS&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2022-01-11T17:08:21.217" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8528" PostTypeId="1" AcceptedAnswerId="8529" CreationDate="2022-01-11T17:24:51.847" Score="8" ViewCount="479" Body="&lt;p&gt;How could I get the Brillouin Zone of 2*2 supercell? I tried to use &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;noreferrer&quot;&gt;see k-path&lt;/a&gt; website, but when I upload a supercell, it still generates the Brillouin Zone of the unit cell.&lt;/p&gt;&#xA;&lt;p&gt;What I want to do is to know when building a supercell, how could I fold a specific high symmetry point to the Gamma point.&lt;br&gt;&#xA;As shown below, how could I fold M point back to Gamma point?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bj7Av.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bj7Av.png&quot; alt=&quot;Band structure of the MoS2/WS2 heterostructure.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-11T21:43:46.170" Title="How could I fold a specific high symmetry point to the Gamma point?" Tags="|k-points|brillouin-zone|supercell|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8529" PostTypeId="2" ParentId="8528" CreationDate="2022-01-11T20:44:14.460" Score="6" Body="&lt;p&gt;&lt;strong&gt;Setup.&lt;/strong&gt; Consider a primitive cell with lattice vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{p_1}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{p_2}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{p_3}$&lt;/span&gt;. You can construct a supercell with lattice vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{s_1}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{s_2}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}_{s_3}$&lt;/span&gt; by making linear combinations of the primitive cell lattice vectors:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{s_1} \\&#xA;\mathbf{a}_{s_2} \\&#xA;\mathbf{a}_{s_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33} &#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{p_1} \\&#xA;\mathbf{a}_{p_2} \\&#xA;\mathbf{a}_{p_3}&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$S_{ij}\in\mathbb{Z}$&lt;/span&gt; are the elements of the so-called supercell matrix.&lt;/p&gt;&#xA;&lt;p&gt;The corresponding reciprocal space lattice vectors between the primitive cell and the supercell are related by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{s_1} \\&#xA;\mathbf{b}_{s_2} \\&#xA;\mathbf{b}_{s_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;\overline{S}_{11} &amp;amp; \overline{S}_{12} &amp;amp; \overline{S}_{13} \\&#xA;\overline{S}_{21} &amp;amp; \overline{S}_{22} &amp;amp; \overline{S}_{23} \\&#xA;\overline{S}_{31} &amp;amp; \overline{S}_{32} &amp;amp; \overline{S}_{33} &#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{p_1} \\&#xA;\mathbf{b}_{p_2} \\&#xA;\mathbf{b}_{p_3}&#xA;\end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\overline{S}_{ij}=(S^{-1})_{ji}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reciprocal space points.&lt;/strong&gt; A &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point in reciprocal space can be written in terms of the reciprocal space primitive lattice basis vectors or in terms of the reciprocal space superlattice basis vectors. The corresponding fractional coordinates are related by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;\begin{pmatrix}&#xA;k_{s_1} \\&#xA;k_{s_2} \\&#xA;k_{s_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11} &amp;amp; S_{12} &amp;amp; S_{13} \\&#xA;S_{21} &amp;amp; S_{22} &amp;amp; S_{23} \\&#xA;S_{31} &amp;amp; S_{32} &amp;amp; S_{33} &#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;k_{p_1} \\&#xA;k_{p_2} \\&#xA;k_{p_3}&#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&#xA;If the reciprocal space superlattice fractional coordinates &lt;span class=&quot;math-container&quot;&gt;$(k_{s_1},k_{s_2},k_{s_3})$&lt;/span&gt; are all integers, then this &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point is mapped to the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point in the corresponding supercell.&lt;/p&gt;&#xA;&lt;p&gt;There are an infinite number of supercells that map a given &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point to the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point, and one is usually interested in the smallest possible supercell. A general discussion of how to find this smallest possible supercell is presented in this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.184301&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; [disclaimer: I am a co-author].&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Your question.&lt;/strong&gt; As an example, let's consider your question, where the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point of interest is the M point with reciprocal space primitive lattice fractional coordinates &lt;span class=&quot;math-container&quot;&gt;$(k_{p_1},k_{p_2},k_{p_3})=(\frac{1}{2},0,0)$&lt;/span&gt;. We need to find a supercell matrix &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; such that this &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point written in terms of the reciprocal space supercell lattice gives integer fractional coordinates &lt;span class=&quot;math-container&quot;&gt;$(k_{s_1},k_{s_2},k_{s_3})$&lt;/span&gt;. By inspection, we see that picking this supercell matrix will do the trick:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;\begin{pmatrix}&#xA;2 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; 1 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 1 &#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&#xA;This also happens to be the smallest such supercell. Other supercells that will also map M to the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point (but that are not the smallest possible) include:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;\begin{pmatrix}&#xA;4 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; 1 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 1 &#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;or&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{6}&#xA;\begin{pmatrix}&#xA;2 &amp;amp; 0 &amp;amp; 0 \\&#xA;0 &amp;amp; 2 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 2 &#xA;\end{pmatrix}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2022-01-11T21:43:46.170" LastActivityDate="2022-01-11T21:43:46.170" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8530" PostTypeId="2" ParentId="1322" CreationDate="2022-01-11T22:23:13.787" Score="2" Body="&lt;h2&gt;Constraint #16: Static linear response of the uniform electron gas&lt;/h2&gt;&#xA;&lt;p&gt;This constraint is actually one of the 11 exact constraints that are also satisfied by the PBE GGA functional, as well as the TPSS Meta-GGA. If I'm understanding [1] correctly, the form of this constraint is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\lim_{k\to0}\gamma_x(y)=1+\frac{5}{9}y^2+\frac{73}{225}y^4-\frac{146}{3375}y^6+\mathcal{O}(y^8)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\gamma_x(y)$&lt;/span&gt; is the response function of jellium/uniform electron gas and &lt;span class=&quot;math-container&quot;&gt;$y=\frac{k}{2k_F}$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; the perturbation wavevector and &lt;span class=&quot;math-container&quot;&gt;$k_F$&lt;/span&gt; the Fermi energy per electron.&lt;/p&gt;&#xA;&lt;p&gt;Clearly this is a desirable trait for our any given density functional approximation to have: if we can't even correctly predict how the density of an electrons cloud responds to a vanishingly small perturbation, we will likely have a challenging time predicting the effect on a molecular system or solid where we have to deal with the potential coming from discrete positive charges (i.e. nuclei).&lt;/p&gt;&#xA;&lt;p&gt;This is not to say that functional that fail to satisfy this constraint can't be accurate for a great many cases. However, failing to meet this constraint (or any of these exact constraints) does suggest that a functional could be less generalizable and less accurately describing the true underlying physics.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Tao, J.; Perdew, J. P.; Almeida, L. M.; Fiolhais, C.; Kümmel, S. Nonempirical density functionals investigated for jellium: Spin-polarized surfaces, spherical clusters, and bulk linear response. &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2008,&lt;/strong&gt; &lt;em&gt;77&lt;/em&gt; (24), No. 245107. &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.77.245107&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.77.245107&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-11T22:23:13.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8531" PostTypeId="1" AcceptedAnswerId="8611" CreationDate="2022-01-11T23:37:55.457" Score="6" ViewCount="149" Body="&lt;p&gt;A question about the &lt;a href=&quot;https://chemistry.stackexchange.com/questions/162136/why-are-there-two-infrared-vibrational-frequencies-for-the-terminal-co-ligands-o&quot;&gt;IR absorption modi of diiron nonacarbonyl&lt;/a&gt; on chemistry.se found two answers.  One of them provided an illustration with animated vibrations.&lt;/p&gt;&#xA;&lt;p&gt;In the 1990s, the Gasteiger group offered with TeleSpek the interested the possibility to submit organic structures, e.g., as a SMILES string for a simulation/prediction of likely IR spectra.  At present, this service appears as no longer active:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Na1MG.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Na1MG.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(a couple of screen photos taken from the &lt;a href=&quot;https://www2.chemie.uni-erlangen.de/services/telespec/&quot; rel=&quot;noreferrer&quot;&gt;project's page&lt;/a&gt;, tab «how to use»).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The question&lt;/strong&gt; to the readers of mattermodelling.se:  Do you know about a similar, yet ongoing service which is able to provide such a (I guess, by today's standards much more affordable) quick, installation free prediction of IR modi (incl. animation), which would be instructive, e.g. for teaching/self study?  With this purpose in mind, the implementation searched needn't be at high level of theory.&lt;/p&gt;&#xA;&lt;p&gt;A first idea I had was &lt;a href=&quot;https://molcalc.org/&quot; rel=&quot;noreferrer&quot;&gt;MolCalc&lt;/a&gt; by Jensen and Kromann.  Likely to preserve resources, the submission of the SMILES string &lt;code&gt;O=C1[Fe]2(=C=O)(=C=O)(=C=O)C(=O)[Fe]1(=C=O)(=C=O)(=C=O)C2=O&lt;/code&gt; &lt;a href=&quot;https://en.wikipedia.org/wiki/Diiron_nonacarbonyl&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt; uses to describe the complex is deflected with «Stop Casper. Max ten heavy atoms.» when aiming to enter the calculation of properties.  (&lt;em&gt;As far as I recall&lt;/em&gt;, the service by Gasteiger &lt;em&gt;et al&lt;/em&gt; sent an e-mail about a successful computation, even if this meant multiple hours of work.)&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2022-01-27T23:15:22.770" Title="Similar (and still ongoing) services like TeleSpek IR simulator on the web?" Tags="|software-recommendations|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8532" PostTypeId="1" CreationDate="2022-01-12T00:44:04.570" Score="6" ViewCount="117" Body="&lt;p&gt;Suppose I am running a molecular dynamics simulation of a polymer solution that exhibits upper critical solution temperature. From standard solution thermodynamics, we expect to see a polymer-rich zone and a polymer-lean zone. &lt;strong&gt;How do we spot these in a simulation cell?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is it a visual check, or is there analysis one can perform to see this? What are some key methods one employs to check solution phase behavior?&lt;/p&gt;&#xA;&lt;p&gt;For example, I am told that &lt;a href=&quot;https://en.wikipedia.org/wiki/Poly(N-isopropylacrylamide)&quot; rel=&quot;nofollow noreferrer&quot;&gt;PNIPAm&lt;/a&gt; exhibits lower critical solution temperature (LCST) above 305 K. I expect the PNIPAm chains to congregate and so on. But my question is, what thermodynamic quantity or correlation should I be on the look out for after I have run this simulation to prove that I am seeing LCST-type phase separation?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="7" LastEditDate="2022-02-24T14:34:17.933" LastActivityDate="2022-09-12T17:25:32.950" Title="How to check for phase separation in polymer simulations?" Tags="|molecular-dynamics|polymers|phase-diagram|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8533" PostTypeId="2" ParentId="8531" CreationDate="2022-01-12T01:22:15.193" Score="7" Body="&lt;p&gt;For most organic molecules, you can use &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;noreferrer&quot;&gt;xtb&lt;/a&gt; as a low level of theory to generate an optimized structure with a full frequency analysis.  While xtb is semi-emperical, you might find that for a qualitative or even semi-quantitative analysis it can be quite good.  You will also find calculations can be performed in at most a couple minutes for even fairly large molecules on a standard desktop or laptop.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-12T01:22:15.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8534" PostTypeId="2" ParentId="7196" CreationDate="2022-01-12T03:40:05.123" Score="7" Body="&lt;h2&gt;Atomsk&lt;/h2&gt;&#xA;&lt;p&gt;Creating surface based on Miller indices is tough work if it is not cubic lattice. for example &lt;span class=&quot;math-container&quot;&gt;$\langle011\rangle$&lt;/span&gt; direction and &lt;span class=&quot;math-container&quot;&gt;$(011)$&lt;/span&gt; plane normal in case of &lt;span class=&quot;math-container&quot;&gt;$c&amp;gt;a$&lt;/span&gt; is not same. So, in case you are trying to create orthogonal simulation box, you may end up in a situation where orthogonal box is quite large or periodicity is not found. Dependency of software is another challenge, whether it is correctly finding the surface or not. I normally do these thing manually in OVITO by slicing and cutting.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Create a cubic lattice with a specific crystal orientation&lt;/strong&gt;&#xA;Another software solution you can check is &lt;code&gt;atomsk&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;atomsk --create bcc 2.85 Fe orient [121] [-101] [1-11] lmp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or you can rotate using specific angle such as&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;atomsk --create bcc 2.85 Fe -rotate z 45 -rotate y 35 -orthogonal-cell lmp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or you can feed LAMMPS data file and rotate it by Euler angle,&#xA;Even though I prefer to do things manually in OVITO.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-01-12T17:57:41.190" LastActivityDate="2022-01-12T17:57:41.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8535" PostTypeId="2" ParentId="8526" CreationDate="2022-01-12T04:09:59.703" Score="4" Body="&lt;p&gt;If by &amp;quot;standard&amp;quot;, you mean an &amp;quot;official&amp;quot; VASP-supported program, then the answer is no. VASP gives you the raw text output for you to deal with on your own. That being said, the &lt;code&gt;vasprun.xml&lt;/code&gt; file produced at the end of a run contains many of the important calculation results, so any parser than can read an XML file can also parse this data in a trivial fashion.&lt;/p&gt;&#xA;&lt;p&gt;It sounds like you're already aware of it, but I highly recommend Pymatgen's VASP output parsers. They are thorough and battle-tested. I don't think you'll run into many &amp;quot;incompatibility issues&amp;quot;. If you do, please open an issue on GitHub, and I can try and address it personally.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymatgen.io.vasp.outputs import Outcar, Vasprun&#xA;vr = Vasprun('vasprun.xml')&#xA;outcar = Outcar('OUTCAR')&#xA;print(vr.as_dict())&#xA;print(outcar.as_dict())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Disclaimer: I work with the Materials Project team, which develops and maintains pymatgen.&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2022-01-12T04:09:59.703" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8536" PostTypeId="1" AcceptedAnswerId="8538" CreationDate="2022-01-12T07:16:33.010" Score="5" ViewCount="713" Body="&lt;p&gt;I want to perform redox potential calculations using the Gaussian. To check if I'm setting things up correctly, I want to compare it to a benchmark database published by Grimme et al.&lt;sup&gt;[1]&lt;/sup&gt; I performed all calculations with my functional/basis set combination for the gas phase molecule.&lt;/p&gt;&#xA;&lt;p&gt;Now I need to perform the calculations for the species with charge &lt;span class=&quot;math-container&quot;&gt;$+1$&lt;/span&gt;. I choose molecule number 45 from the OROP Set (Supplemental Information), it is &lt;a href=&quot;https://en.wikipedia.org/wiki/Hydroquinone&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hydroquinone&lt;/a&gt;. The paper said it should have multiplicity 1 and charge +1. But I think I have to remove an atom to get the combination of M=1 and Ch=+1.&lt;/p&gt;&#xA;&lt;p&gt;Can somebody help me out, which atom do I have to remove? Thanks in advance!&lt;/p&gt;&#xA;&lt;p&gt;I also looked up the zip-dataset, which should include (according to the README) the geometries (these can I see), but also the charge and multiplicity data, which I can not find in the zip file! Are they missing or can my Mac not show them?&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Neugebauer, H.; Bohle, F.; Bursch, M.; Hansen, A.; Grimme, S. Benchmark Study of Electrochemical Redox Potentials Calculated with Semiempirical and DFT Methods. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;124&lt;/em&gt; (35), 7166–7176. &lt;a href=&quot;https://doi.org/10.1021/acs.jpca.0c05052&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1021/acs.jpca.0c05052&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here are my calculated Energies. (II) is the normal Molecule, (III) is with charge +1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCFE (g) (II) =     -382.81331295&#xA;SCFE (solv) (II) =  -382.82970187&#xA;GibbsCorr (II) =    0.077174&#xA;SCFE (g) (III) =     -382.53186782&#xA;SCFE (solv) (III) = -382.63171676&#xA;GibbsCorr (III) =   0.078470&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1680" OwnerDisplayName="Andrea" LastEditorUserId="1680" LastEditDate="2022-01-12T21:48:22.117" LastActivityDate="2022-01-12T21:48:22.117" Title="How to alter the charge and multiplicity of a molecule in Gaussian?" Tags="|gaussian|databases|redox|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8537" PostTypeId="1" AcceptedAnswerId="8590" CreationDate="2022-01-12T15:00:50.003" Score="8" ViewCount="531" Body="&lt;p&gt;I am using VASP to calculate the projected DOS, but I am not sure why we aren't using the principal quantum number when doing the projection.&lt;/p&gt;&#xA;&lt;p&gt;According to the VASP wiki, &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LORBIT&quot; rel=&quot;nofollow noreferrer&quot;&gt;LORBIT&lt;/a&gt; would control VASP to generate &lt;a href=&quot;https://www.vasp.at/wiki/index.php/PROCAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;PROCAR&lt;/a&gt; file, which contains the spd- and site projected wave function character of each orbital. It is called &lt;code&gt;lm-decomposed&lt;/code&gt;, where l,m are the angular moment and magnetic quantum numbers.&lt;/p&gt;&#xA;&lt;p&gt;Since the electronic band structure is composed of atom orbitals, &lt;strong&gt;shouldn't we use the principal quantum number for projection as well?&lt;/strong&gt;&#xA;Taking Titanium as an example, its electron configuration is 1s² 2s² 2p⁶ 3s² 3p⁶ 4s² 3d². If we only do lm-decomposition, how should we distinguish the contribution from 3s and 4s?&lt;/p&gt;&#xA;&lt;p&gt;There are three types of pseudopotentials in VASP for Titanium:&lt;br&gt;&#xA;Ti_sv:   VRHFIN =Ti: 3s3p4s3d ZVAL   =   12.000&lt;br&gt;&#xA;Ti_pv:   VRHFIN =Ti: d3 s1    ZVAL   =   10.000&lt;br&gt;&#xA;Ti:      VRHFIN =Ti: d3 s1    ZVAL   =    4.000&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8JuAv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8JuAv.png&quot; alt=&quot;Titanium periodic table data&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-01-14T08:11:50.093" LastActivityDate="2022-01-21T12:36:22.703" Title="Why don't we use the principal quantum number when building the projected density of state?" Tags="|density-functional-theory|vasp|density-of-states|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8538" PostTypeId="2" ParentId="8536" CreationDate="2022-01-12T15:36:05.200" Score="5" Body="&lt;p&gt;In the dataset files for a given molecule, the charge and number of unpaired electrons for each species are stored in files &lt;code&gt;.CHG1&lt;/code&gt;/&lt;code&gt;.CHG2&lt;/code&gt; and &lt;code&gt;.UHF1&lt;/code&gt;/&lt;code&gt;.UHF2&lt;/code&gt; respectively. On some computers, files starting with &lt;code&gt;.&lt;/code&gt; are hidden by default. On Mac, you can display these in Finder by pressing &lt;code&gt;&amp;lt;COMMAND&amp;gt;&amp;lt;SHIFT&amp;gt;.&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Looking at these for molecule 45 of the OROP set, it says that the charged species should have a &lt;span class=&quot;math-container&quot;&gt;$+1$&lt;/span&gt; charge and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; unpaired electron (i.e. a multiplicity of &lt;span class=&quot;math-container&quot;&gt;$2=2\cdot\frac{1}{2}+1$&lt;/span&gt;). So you shouldn't need to remove any atoms to make this a valid charge/multiplicity, but you will need to perform an unrestricted calculation. You shouldn't need to do anything special for that, as Gaussian will run an unrestricted calculation whenever the multiplicity is greater than 1. From the paper, they didn't seem to run unrestricted calculations for the closed shell molecules (and in the vast majority of cases it would just give the same result as a restricted calculation any way).&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-01-12T21:36:34.893" LastActivityDate="2022-01-12T21:36:34.893" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8540" PostTypeId="2" ParentId="4258" CreationDate="2022-01-12T16:25:17.497" Score="1" Body="&lt;p&gt;I don't see the value you quote in your question anywhere in the tutorial. In any event, Gibb's Free energies in Gaussian will always be reported in Hartree, while the redox potential (which you would need to calculate using these Gibb's Free energies) is typically given in Volts.&lt;/p&gt;&#xA;&lt;p&gt;To show how this works, I'll explicitly convert their example from the last section of the tutorial. Reproducing the values here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCF(g)(II) : SCF Done: E(UB3LYP) = -510.439067386&#xA;SCF(solv)(II): SCF Done: E(UB3LYP) = -510.444248948&#xA;GibbsCorr (II): Thermal correction to Gibbs Free Energy= 0.134232&#xA;&#xA;SCF(g)(III) : SCF Done: E(UB3LYP) = -510.170289413&#xA;SCF(solv)(III): SCF Done: E(UB3LYP) = -510.239713457&#xA;GibbsCorr (III): Thermal correction to Gibbs Free Energy= 0.132483&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8ZGUH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8ZGUH.png&quot; alt=&quot;Thermocycle for oxidation in gas and solution phase&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;We want to solve for &lt;span class=&quot;math-container&quot;&gt;$\Delta G_{ox (sol)}$&lt;/span&gt; (we will later convert this to &lt;span class=&quot;math-container&quot;&gt;$\Delta E_{ox (sol)}$&lt;/span&gt;). Using Hess's law and the thermodynamic cycle above, we can write this as &lt;span class=&quot;math-container&quot;&gt;$$\Delta G_{\text{ox (sol)}}=\Delta G_{\text{solv}}(\text{III})+\Delta G_{\text{ox (g)}}-\Delta G_{\text{solv}}(\text{II})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Evaluating this in Python and converting to volts at the end:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; hartree_to_Volt=-2625000.5/96500 #Numerator converts hartree to J/mol&#xA;&amp;gt;&amp;gt;&amp;gt; dG_g=(-510.170289413+0.132483)-(-510.439067386+0.134232)&#xA;&amp;gt;&amp;gt;&amp;gt; dG_II=(-510.444248948--510.439067386)&#xA;&amp;gt;&amp;gt;&amp;gt; dG_III=(-510.239713457--510.170289413)&#xA;&amp;gt;&amp;gt;&amp;gt; dG_III+dG_g-dG_II&#xA;0.20278649099998347&#xA;&amp;gt;&amp;gt;&amp;gt; (dG_III+dG_g-dG_II)*hartree_to_Volt&#xA;-5.516213888789659&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which gives a us a value of &lt;span class=&quot;math-container&quot;&gt;$E_\text{red}=5.52$&lt;/span&gt; (we have to flip the sign again to give a reduction potential rather than an oxidation potential). I could have simplified the math slightly here, but note that just directly computing &lt;span class=&quot;math-container&quot;&gt;$\Delta G_{ox (sol)}$&lt;/span&gt; from the two solvated calculations would have produced a different result, as these calculations used the gas-phase geometry and did not compute thermal corrections at the optimal geometry for the solvated species.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-12T16:25:17.497" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8541" PostTypeId="1" CreationDate="2022-01-01T08:42:16.370" Score="9" ViewCount="3408" Body="&lt;p&gt;I come from a mainly computer science background, but have become involved in a project related to artificial intelligence-based drug discovery. I made a model that generates novel molecules, for which I want to compute their synthetic accessibility score&lt;sup&gt;[1]&lt;/sup&gt;. I am aware of the RDKIT library which is very helpful in computer-aided chemistry, however, I can't find any method/function for this purpose. If anyone knows a way, it would be much appreciated.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ertl, P.; Schuffenhauer, A. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. &lt;em&gt;J. Cheminf.&lt;/em&gt; &lt;strong&gt;2009,&lt;/strong&gt; &lt;em&gt;1&lt;/em&gt; (1), No. 8. &lt;a href=&quot;https://doi.org/10.1186/1758-2946-1-8&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1186/1758-2946-1-8&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerDisplayName="Amine Chadi" LastEditorUserId="7" LastEditDate="2022-01-12T20:58:14.860" LastActivityDate="2022-01-12T21:04:02.950" Title="How to compute the synthetic accessibility score in Python?" Tags="|python|rdkit|cheminformatics|drug-design|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8542" PostTypeId="2" ParentId="8537" CreationDate="2022-01-12T20:07:10.350" Score="7" Body="&lt;p&gt;I think this issue is avoided in practical sense.  I am not sure any of the psuedopotentials provided with VASP actually include valence electrons of the same angular momentum (so you never have 3s and 4s as valence), since these states are normally part of the core.  I don't think there is any reason you cannot do this in theory, but in practice the core is always remaining the same so this doesn't need to be available in VASP.&lt;/p&gt;&#xA;&lt;p&gt;This is probably not true if you are doing all-electron calculations in a different code.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-12T20:07:10.350" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8544" PostTypeId="2" ParentId="8541" CreationDate="2022-01-12T21:04:02.950" Score="7" Body="&lt;p&gt;Ertl and Schuffenhauer, who developed the synthetic accessibility score, provide an implementation packaged with RDKit called &lt;a href=&quot;https://github.com/rdkit/rdkit/blob/master/Contrib/SA_Score/sascorer.py&quot; rel=&quot;noreferrer&quot;&gt;sascorer.py&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is provided in the Contrib folder of the RDKit repo; what this means is it isn't formally part of RDKit, but with a little work can be accessed from RDKit. An example of how to do this is given in an &lt;a href=&quot;https://github.com/rdkit/rdkit/issues/2279&quot; rel=&quot;noreferrer&quot;&gt;issue&lt;/a&gt; on the RDKit Github. I'll reproduce the code from &lt;a href=&quot;https://github.com/iwatobipen&quot; rel=&quot;noreferrer&quot;&gt;iwatobipen&lt;/a&gt; here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import RDConfig&#xA;import os&#xA;import sys&#xA;sys.path.append(os.path.join(RDConfig.RDContribDir, 'SA_Score'))&#xA;# now you can import sascore!&#xA;import sascorer&#xA;mol = Chem.MolFromSmiles('NC(=O)c1ccccc1')&#xA;s = sascorer.calculateScore(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first section temporarily adds the Config directory to your path so you can import &lt;code&gt;sascorer&lt;/code&gt;. If you don't want to include this every time you want to run this program, you will need to add this directory to your system path. The commands to do so vary by operating system.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-12T21:04:02.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8546" PostTypeId="1" AcceptedAnswerId="8565" CreationDate="2022-01-12T21:43:11.227" Score="6" ViewCount="312" Body="&lt;p&gt;I'm interested in predicting the protonation and tautomer state of organic molecules (typically CHNOS) at near pH 7 in water.  I've used tools like Schrodinger's Epik / LigPrep before, but they definitely make wrong predictions sometimes, and I don't know exactly how they work under the hood.  I'd like to try to do something based on running QM calculations myself but I'm really not familiar enough with this particular subfield to know what is considered the best approach.&lt;/p&gt;&#xA;&lt;p&gt;What is the current state of the art method for predicting protonation and tautomer state?&lt;/p&gt;&#xA;&lt;p&gt;P.S. Related: what is the standard benchmark for this?&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2022-01-13T20:16:03.457" LastActivityDate="2022-01-14T19:10:05.247" Title="How to predict protonation state of molecules in water?" Tags="|software|quantum-chemistry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8547" PostTypeId="1" AcceptedAnswerId="8548" CreationDate="2022-01-12T21:54:13.183" Score="5" ViewCount="227" Body="&lt;p&gt;I calculated the redox potential with Gaussian for hydroquinone with different combinations of functional/basis sets always values like 5.4V (B3LYP/6-311G+(2d,p) and SMD model). The experimental value is about 1.1V according to [1], so I'm missing by a decent amount.&lt;/p&gt;&#xA;&lt;p&gt;Has somebody an idea what I did wrong?&lt;/p&gt;&#xA;&lt;p&gt;These are the energies I calculated:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCFE (g) (molecule) =   -382.81331295&#xA;SCFE (solv) (molecule) =  -382.82970187&#xA;GibbsCorr (molecule) =    0.077174&#xA;SCFE (g) (species) =     -382.53186782&#xA;SCFE (solv) (species) = -382.63171676&#xA;GibbsCorr (species) =   0.078470&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and an example job file for the optimization of the charged species:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%rwf=bench_40_spec_b3lyp_tight.rwf&#xA;%NoSave&#xA;%chk=bench_40_spec_b3lyp_tight.chk&#xA;#p opt=(calcfc,tight,recalcfc=3) b3lyp/6-311+g(2d,p) nosymm scf=qc&#xA;&#xA;040 Tight Opt Gas&#xA;&#xA;1 2&#xA; C                 -0.68613672   -1.20444633   -0.00000200&#xA; C                  0.69506215   -1.19541581   -0.00000235&#xA; C                  1.39161904    0.00718044    0.00000031&#xA; C                  0.68613843    1.20444943   -0.00000167&#xA; C                 -0.69505913    1.19541474   -0.00000053&#xA; C                 -1.39161802   -0.00718091    0.00000159&#xA; O                 -2.75490670   -0.05822072   -0.00000096&#xA; H                 -3.11159203    0.83776787    0.00004645&#xA; H                 -1.23719750    2.13172433   -0.00000924&#xA; H                  1.23422725    2.13274296   -0.00001200&#xA; O                  2.75490286    0.05821954    0.00000081&#xA; H                  3.11158561   -0.83777105    0.00003365&#xA; H                  1.23719782   -2.13172346   -0.00000066&#xA; H                 -1.23422866   -2.13274050   -0.00000041&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I used the method linked in here:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4258/units-of-energy-in-gaussian&quot;&gt;Redox Method&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Neugebauer, H.; Bohle, F.; Bursch, M.; Hansen, A.; Grimme, S. Benchmark Study of Electrochemical Redox Potentials Calculated with Semiempirical and DFT Methods. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;2020,&lt;/strong&gt; &lt;em&gt;124&lt;/em&gt; (35), 7166–7176. &lt;a href=&quot;https://doi.org/10.1021/acs.jpca.0c05052&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1021/acs.jpca.0c05052&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="1680" LastEditDate="2022-01-12T22:32:05.910" LastActivityDate="2022-01-12T22:39:56.173" Title="Calculated Redoxpotential is too far away from experimental value" Tags="|density-functional-theory|gaussian|redox|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8548" PostTypeId="2" ParentId="8547" CreationDate="2022-01-12T22:39:56.173" Score="7" Body="&lt;p&gt;Your reference paper says that it subtracts the &amp;quot;absolute potential of the reference electrode&amp;quot; from the calculated values. I can't get to the citation that explains what reference electrode they are referring to, but the most common is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Standard_hydrogen_electrode&quot; rel=&quot;noreferrer&quot;&gt;Standard hydrogen electrode&lt;/a&gt;, which is estimated to have an absolute potential of &lt;span class=&quot;math-container&quot;&gt;$\pu{4.44V}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Subtracting this from the potential of &lt;span class=&quot;math-container&quot;&gt;$\pu{5.4V}$&lt;/span&gt; that you calculated gives &lt;span class=&quot;math-container&quot;&gt;$\pu{0.96V}$&lt;/span&gt;. This is only off by ~&lt;span class=&quot;math-container&quot;&gt;$\pu{0.1V}$&lt;/span&gt;, which is well in line with the errors reported in the paper for DFT and semiempirical methods.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-12T22:39:56.173" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8549" PostTypeId="2" ParentId="4154" CreationDate="2022-01-13T10:02:20.190" Score="6" Body="&lt;p&gt;The computational chemistry software &lt;a href=&quot;https://orcaforum.kofo.mpg.de/index.php&quot; rel=&quot;noreferrer&quot;&gt;ORCA&lt;/a&gt; (requires the registration of an account, although both registration and the software itself is free for academic users; for a tutorial that is viewable without registration, see &lt;a href=&quot;https://www.orcasoftware.de/tutorials_orca/index.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.orcasoftware.de/tutorials_orca/index.html&lt;/a&gt;). In ORCA one can compute XAS/XES/RIXS at the TDDFT, DFT/ROCIS (a spin-adapted, empirically scaled TDDFT/TDA method, suitable for Mott insulators) and CASCI/NEVPT2 (a multireference method with perturbative second-order dynamical correlation) levels. Some additional highlights are the inclusion of scalar relativistic (ZORA or DKH2) and spin-orbit coupling effects, the inclusion of transition quadrupole moment contributions to the oscillator strengths (thus dipole-forbidden but quadrupole-allowed transitions are correctly predicted as bright), and the possibility of computing circular dichroism and even magnetic circular dichroism spectra.&lt;/p&gt;&#xA;&lt;p&gt;Note that ORCA is a molecular code, not a periodic code. This means that you have to use a cluster model in the computations, although as X-ray spectra are rather local properties, you can usually get away with clusters of modest size (well within 100 atoms, for example). The immediate environment of the cluster is treated by an embedding potential, while the distant part of the environment is treated by point charges. The non-periodicity of the system also means that some functionalities that are difficult to access with periodic codes become very easy to do, for example a full treatment of long-range HF exchange is well possible, and multireference treatments of the metal center are also completely doable.&lt;/p&gt;&#xA;&lt;p&gt;Another possible option is the &lt;a href=&quot;http://182.92.69.169:7226/Introduction&quot; rel=&quot;noreferrer&quot;&gt;BDF&lt;/a&gt; (Beijing Density Functional) software package. BDF supports the calculation of XAS/XES spectra at the X-TDDFT level of theory, although it does not support RIXS yet. Advantages of BDF in this aspect include: (1) while X-TDDFT is also a spin-adapted TDDFT method, it is cheaper than DFT/ROCIS; (2) the scalar relativistic effects are treated at the sf-X2C level; (3) the core-valence excitations are allowed to mix with the valence-valence excitations; (4) thanks to the use of the iVI method (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6563/what-are-the-advantages-of-the-davidson-diagonalization-method-over-other-sparse/6575#6575&quot;&gt;my another answer on this site&lt;/a&gt;), the user can request the program to calculate all excited states within a given excitation energy range, and only those states that are within that range, without knowing how many excited states there are in that range; and (5) the boundary of the cluster and the environment is treated using the projected hybrid orbital (PHO) method, which is usually more accurate than the embedding potential method used by ORCA when the cluster-environment interaction is mostly covalent (conversely ORCA's treatment is more accurate when the interaction is mostly ionic). Therefore, BDF may be useful when you cannot afford DFT/ROCIS, when ZORA and DKH2 are not accurate enough for your system, or when your material has a high covalent character.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-01-13T10:02:20.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8550" PostTypeId="1" CreationDate="2022-01-13T14:44:59.443" Score="4" ViewCount="135" Body="&lt;p&gt;I want to study electronic and thermal transport properties of a Weyl semimetal. Until now, I have used only the continuum model hamiltonian (&lt;span class=&quot;math-container&quot;&gt;$H=k⋅σ$&lt;/span&gt;). As the continuum model has several limitations, a lattice model would potentially be an improvement. But, more realistic studies could be done with tight binding analysis. However, as a beginner, I don't know how to implement a Weyl semimetal in a tight binding model.&lt;/p&gt;&#xA;&lt;p&gt;I have seen several example of tight binding codes to implement Graphene and other 2D topological materials using &lt;a href=&quot;https://kwant-project.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;kwant&lt;/a&gt;, but didn't find any example for a Weyl semimetal.&lt;/p&gt;&#xA;&lt;p&gt;Is there any example codes written by others (ideally in Python)? Are there any dedicated Python packages (other than kwant) to handle it?&lt;/p&gt;&#xA;" OwnerUserId="4790" LastEditorUserId="7" LastEditDate="2022-01-14T16:30:29.637" LastActivityDate="2022-01-14T16:30:29.637" Title="How to implement a Weyl semimetal in tight binding?" Tags="|python|tight-binding|electronic-transport|weyl-semimetal|topological-matter|" AnswerCount="0" CommentCount="2" ClosedDate="2022-03-01T17:46:20.017" ContentLicense="CC BY-SA 4.0" />
  <row Id="8551" PostTypeId="1" AcceptedAnswerId="8552" CreationDate="2022-01-13T14:45:09.250" Score="4" ViewCount="191" Body="&lt;p&gt;I am using VASP to do the simulation of a slab, I used some pseudohydrogen to passivate the bottom side of the slab. After the structure optimization calculation, the &lt;code&gt;CONTCAR&lt;/code&gt; I get looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; TiO2_mp-2657_slab_unitcell             &#xA;   1.0000000000000000     &#xA;     2.9691998959000001    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    6.5806999206999999    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   38.4453010559000035&#xA;   Ti   O    H.   H1&#xA;     8    16     1     1&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The original &lt;code&gt;POSCAR&lt;/code&gt; is:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; TiO2_mp-2657_slab_unitcell             &#xA;   1.0000000000000000     &#xA;     2.9691998959000001    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    6.5806999206999999    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   38.4453010559000035&#xA;   Ti   O    H.66   H1.33&#xA;     8    16     1     1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As shown above, the &lt;code&gt;H.66&lt;/code&gt; and &lt;code&gt;H1.33&lt;/code&gt; turn into &lt;code&gt;H.&lt;/code&gt; and &lt;code&gt;H1&lt;/code&gt;. Is this just a small bug of the input/output, or is it gonna affect the calculation results?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-13T15:18:20.480" Title="Using pseudo-hydrogen in VASP results in the wrong format in CONTCAR" Tags="|density-functional-theory|vasp|software-assistance|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8552" PostTypeId="2" ParentId="8551" CreationDate="2022-01-13T15:18:20.480" Score="4" Body="&lt;p&gt;I could be wrong, but I am fairly certain that line of the CONTCAR technically doesn't matter. If you put a O instead of H, but put the potentials in the right order, you will get the right result even though the element is wrong. For visualization, it will definitely be wrong but I don't think the calculated result is wrong.&lt;/p&gt;&#xA;&lt;p&gt;In tools such as ASE the potentials are derived from this line of the POSCAR though, so be careful.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-01-13T15:18:20.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8553" PostTypeId="1" CreationDate="2022-01-13T17:01:44.703" Score="5" ViewCount="92" Body="&lt;p&gt;I want to simulate a MWCNT bundle in which the central MWCNT is pulled out of the bundle.&#xA;How to define the stress/strain curve of such system?&lt;/p&gt;&#xA;&lt;p&gt;I am building my system with scikit-nano and using LAMMPS with Airebo-M force field for simulation.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;create the geometry file:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;from sknano.generators import MWNTBundleGenerator&#xA;from ase.io import read, write&#xA;from ase.visualize import view&#xA;&#xA;mwntbundle = MWNTBundleGenerator(Nwalls=3, min_wall_diameter=5, Lz=5, bundle_geometry='hexagon')&#xA;mwntbundle.save('mwcnt_boundle.xyz')&#xA;mwcnt_ase = read('mwcnt_boundle.xyz')&#xA;view(mwcnt_ase)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Transform the so-produced xyz file into a lammps geometry file:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;def read_xyz(xyz_file):&#xA;    with open(xyz_file, 'r') as f:&#xA;        xyz_lines = f.readlines()&#xA;    n_atoms = int(xyz_lines[0])&#xA;    coords_str = np.array([ ll.split()[1:] for ll in xyz_lines[2:] ])&#xA;    coords_float = coords_str.astype(np.float)&#xA;    return n_atoms, coords_float&#xA;&#xA;def write_lammps(coords):&#xA;    nat_per_mwcnt = len(coords)/7&#xA;    with open('mwcnt_boundle.lammps', &amp;quot;w+&amp;quot;) as f:&#xA;        f.write('# LAMMPS data file \n\n')&#xA;        f.write(str(len(coords))+' atoms\n\n')&#xA;        f.write('1 atom types\n\n')&#xA;        f.write('-100 100 xlo xhi\n')&#xA;        f.write('-100 100 ylo yhi\n')&#xA;        f.write('-100 100 zlo zhi\n\n')&#xA;        f.write('Masses\n')&#xA;        f.write(' 1 12.010700 # C\n')&#xA;        f.write('Atoms\n')&#xA;        for cc in range(len(coords)):&#xA;            crd = coords[cc]&#xA;            ## creating 7 different molecules, each one corresponding to a MWCNT&#xA;            if cc%nat_per_mwcnt == 0:&#xA;                nmol = int(cc//nat_per_mwcnt)&#xA;            f.write( '{:4d} {:2d} 1 0 {:6f} {:6f} {:6f}\n'.format(cc+1, nmol, crd[0], crd[1], crd[2]) )&#xA;        f.write('\n')&#xA;&#xA;n_atoms, coords = read_xyz(&amp;quot;mwcnt_boundle.xyz&amp;quot;)&#xA;write_lammps(coords)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;At this point I can use LAMMPS to simulate the central mwcnt being pulled out of the bundle. The mwcnt correspond to residue 1. Please find below my input file. In a nutshell: I define a cilynder enclosing molecule G1 and pull it out with the displace_atoms command from LAMMPS. This will go into an external loop making it more effective.&#xA;I have taken inspiration from &lt;a href=&quot;https://lammpstutorials.github.io/tutorial04.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ref1&lt;/a&gt; and &lt;a href=&quot;https://www.linkedin.com/pulse/how-perform-uniaxial-tensile-tests-graphene-sample-lammps-dewapriya/?trackingId=grfCMA6NR5aKzINRl0my7g%3D%3D&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ref2&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am defining the strain as the &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;Z between the top layer of the shifted mwcnt and its initial position, while the stress is defined with &amp;quot;compute stress/atom&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Unsurprisingly, even with a larger system than the one produced here, I get a not very clear result, with strain/stress oscillating between -1e10 and 1e10.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone suggest a way to improve this simulation?&#xA;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Initialisation&#xA;&#xA;units           metal&#xA;dimension           3&#xA;boundary        p p p&#xA;atom_style      full &#xA;newton          on&#xA;&#xA;read_data       mwcnt_boundle.lammps &#xA;pair_style      airebo/morse 3.0 1 1&#xA;pair_coeff      * * /data/mdi0316/WORK/MWCNT/src/Inputfiles/CH.airebo-m C&#xA;&#xA;# time settings&#xA;variable        dt      equal   0.001&#xA;variable        tprod   equal   5&#xA;variable        Nruns    equal floor(&lt;span class=&quot;math-container&quot;&gt;${tprod}/$&lt;/span&gt;{dt})&#xA;variable        Nevery   equal 10&#xA;variable        Nrepeat  equal 10&#xA;variable        Nfreq    equal 100&#xA;timestep        &lt;span class=&quot;math-container&quot;&gt;${dt} #ps&#xA;print           &quot;--- Time settings ---&quot;&#xA;print           &quot;    dt       = $&lt;/span&gt;{dt}&amp;quot;&#xA;print           &amp;quot;    tprod    = &lt;span class=&quot;math-container&quot;&gt;${tprod}&quot;&#xA;print           &quot;    Nruns    = $&lt;/span&gt;{Nruns}&amp;quot;&#xA;print           &amp;quot;    Nevery   = &lt;span class=&quot;math-container&quot;&gt;${Nevery}&quot;&#xA;print           &quot;    Nrepeat  = $&lt;/span&gt;{Nrepeat}&amp;quot;&#xA;print           &amp;quot;    Nfreq    = ${Nfreq}&amp;quot;&#xA;&#xA;# computes and output variables settings&#xA;compute         cKe all ke&#xA;compute         cPe all pe&#xA;variable        totE equal c_cKe+c_cPe&#xA;compute         Tall all temp&#xA;compute         cP all pressure Tall&#xA;thermo          100&#xA;thermo_style    custom time temp pe v_totE press vol density&#xA;&#xA;# ----------------------------------------------&#xA;# groups settings&#xA;group           G1 molecule 1&#xA;variable        xmax equal bound(G5,xmax)+0.5&#xA;variable        xmin equal bound(G5,xmin)-0.5&#xA;variable        zmax equal bound(G5,zmax)+0.5&#xA;variable        zmin equal bound(G5,zmin)-0.5&#xA;variable        Cdiam equal &lt;span class=&quot;math-container&quot;&gt;${xmax}-$&lt;/span&gt;{xmin}&#xA;variable        Cradi equal &lt;span class=&quot;math-container&quot;&gt;${Cdiam}/2&#xA;variable        Cleng equal $&lt;/span&gt;{zmax}-${zmin}&#xA;&#xA;variable        x_com_inner equal xcm(G1,x)&#xA;variable        y_com_inner equal xcm(G1,y)&#xA;&#xA;region          innreg cylinder z &lt;span class=&quot;math-container&quot;&gt;${x_com_inner} $&lt;/span&gt;{y_com_inner} &lt;span class=&quot;math-container&quot;&gt;${Cradi} $&lt;/span&gt;{zmin} &lt;span class=&quot;math-container&quot;&gt;${zmax}&#xA;variable        innvol equal $&lt;/span&gt;{Cleng}*3.14*&lt;span class=&quot;math-container&quot;&gt;${Cradi}*$&lt;/span&gt;{Cradi}&#xA;&#xA;#---------------STRESS-------------------------------------&#xA;compute         1 all stress/atom NULL&#xA;compute         2 all reduce sum c_1[3]&#xA;fix             1 all ave/time 1 1 100 c_2&#xA;variable        sigmazz equal f_1&#xA;&#xA;## -------------- OUTPUTS ----------------------&#xA;fix             3 all ave/time 1 1 100 v_zmin v_zmax v_sigmazz file displace.dat&#xA;&#xA;# ----------------------------------------------&#xA;# NPT&#xA;&#xA;fix             bar all temp/berendsen 300 300 0.1 #Tstart Tstop Tdamp = 0.1ps&#xA;fix             mynpt all npt temp 300 300 0.1 aniso 1 1 1&#xA;dump            Dnpt all atom 100 dump_npt.lammpstrj&#xA;fix             fnpt all ave/time &lt;span class=&quot;math-container&quot;&gt;${Nevery} $&lt;/span&gt;{Nrepeat} &lt;span class=&quot;math-container&quot;&gt;${Nfreq} c_Tall v_totE c_cP v_innvol file npt.dat&#xA;print           &quot;--- Beginning of NPT run ($&lt;/span&gt;{Nruns} steps) ---&amp;quot;&#xA;#displace_atoms&#xA;displace_atoms  G1 move 0 0 10&#xA;run             ${Nruns}&#xA;write_data      restart.npt&#xA;undump          Dnpt&#xA;unfix           mynpt&#xA;unfix           fnpt&#xA;&#xA;print           '---- DONE ----'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="5" LastEditDate="2022-02-24T04:21:52.203" LastActivityDate="2022-02-24T04:21:52.203" Title="Define stress-strain for a multi-wall carbon nanotubes bundle" Tags="|molecular-dynamics|lammps|nanostructures|stress-strain|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:49:49.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="8555" PostTypeId="1" CreationDate="2022-01-12T23:07:18.737" Score="5" ViewCount="144" Body="&lt;p&gt;I am running some simulations on a metal organic framework and I need to set different 1-4 &lt;code&gt;coul&lt;/code&gt; and &lt;code&gt;lj&lt;/code&gt; parameters for different components on my MOF. I need to set it to be &lt;code&gt;0 1&lt;/code&gt; for the inorganic part and &lt;code&gt;0.833 0.5&lt;/code&gt; for the organic part.&lt;/p&gt;&#xA;&lt;p&gt;The line I want in LAMMPS is &lt;code&gt;special bonds&lt;/code&gt; but I'm not sure how to avoid applying to to all the atoms. There is the &amp;quot;group&amp;quot; function, but I don't think this is what I want as it doesn't allow me to specify 1-4 interactions. Would &lt;code&gt;molecule&lt;/code&gt; be helpful?&lt;/p&gt;&#xA;&lt;p&gt;Any advice appreciated! Unfortunately, it's not possible for me to use another software.&lt;/p&gt;&#xA;" OwnerUserId="4655" OwnerDisplayName="Pineapple" LastEditorUserId="7" LastEditDate="2022-01-13T19:08:05.700" LastActivityDate="2022-01-13T19:08:05.700" Title="Is there a way to set different special bonds for different atom groups in the same structure in LAMMPS?" Tags="|molecular-dynamics|computational-chemistry|lammps|" AnswerCount="0" CommentCount="2" ClosedDate="2022-02-24T14:29:55.097" ContentLicense="CC BY-SA 4.0" />
  <row Id="8556" PostTypeId="1" CreationDate="2022-01-12T22:16:55.177" Score="7" ViewCount="227" Body="&lt;p&gt;I need to displace atoms along a complicated normal mode involving many atoms. I have the normal mode eigenvector, I just don't know how to turn the eigenvector into an algorithm to translate the actual points &amp;quot;along&amp;quot; the normal mode by a given distance for the normal coordinate. I can't find the answer anywhere. Even just a mathematical description of this task would be helpful. I can code from that. Basically, I need to know how programs like GaussView and WebMO show you the normal modes in motion given the eigenvectors - that algorithm.&lt;/p&gt;&#xA;" OwnerDisplayName="Daniel Konstantinovsky" LastEditorUserId="7" LastEditDate="2022-01-13T19:09:49.963" LastActivityDate="2022-01-14T23:42:04.903" Title="How to move atom coordinates along a normal mode given the eigenvector?" Tags="|visualization-software|vibrations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8557" PostTypeId="1" AcceptedAnswerId="8579" CreationDate="2022-01-13T22:02:51.247" Score="7" ViewCount="680" Body="&lt;p&gt;I am considering using ASE to translate my old work into a Python script. I already have the INCAR and POSCAR KPOINTS files. Is it possible to let ASE read these files and generate Python scripts that include the key information?&lt;/p&gt;&#xA;&lt;p&gt;For example, I have an INCAR file like:&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;# ICHARG =  11         (Non-self-consistent: GGA/LDA band structures)&#xA;LREAL  = .FALSE.       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Normal       (Precision level)&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;# NPAR   = 4           (Max is no. nodes; don't set for hybrids)&#xA;# Nwrite = 2           (Medium-level output)&#xA;# KPAR   = 2           (Divides k-grid into separate groups)&#xA;# NGX    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGY    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGZ    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA; &#xA;Static Calculation&#xA;ISMEAR =  0            (gaussian smearing method)&#xA;SIGMA  =  0.05         (please check the width of the smearing)&#xA;LORBIT =  11           (PAW radii for projected DOS)&#xA;NEDOS  =  2001         (DOSCAR points)&#xA;NELM   =  60           (Max electronic SCF steps)&#xA;EDIFF  =  1E-04        (SCF energy convergence; in eV)&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'd like to translate this INCAR into something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import bulk&#xA;from ase.calculators.vasp import Vasp&#xA;&#xA;si = bulk('Si')&#xA;&#xA;mydir = 'bandstructure'    # Directory where we will do the calculations&#xA;&#xA;# Make self-consistent ground state&#xA;calc = Vasp(kpts=(4, 4, 4), directory=mydir)&#xA;&#xA;si.calc = calc&#xA;si.get_potential_energy()  # Run the calculation&#xA;&#xA;# Non-SC calculation along band path&#xA;kpts = {'path': 'WGX',     # The BS path&#xA;        'npoints': 30}     # Number of points along the path&#xA;&#xA;calc.set(isym=0,           # Turn off kpoint symmetry reduction&#xA;         icharg=11,        # Non-SC calculation&#xA;         kpts=kpts)&#xA;&#xA;# Run the calculation&#xA;si.get_potential_energy()&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-01-18T09:41:54.443" LastActivityDate="2022-01-18T11:51:09.827" Title="Translate INCAR to Python script using ASE" Tags="|vasp|software|atomic-simulation-environment|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8558" PostTypeId="2" ParentId="8556" CreationDate="2022-01-14T00:46:36.560" Score="5" Body="&lt;p&gt;&lt;strong&gt;This answer is primarily applicable to gas-phase molecules. I've never done this for periodic systems, so maybe someone can supplement with an answer for that context.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Presumably you have eigenvector of length &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of atoms. Call this eigenvector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}$&lt;/span&gt;. Typically we think of xyz cartesian coordinates as an &lt;span class=&quot;math-container&quot;&gt;$N\times3$&lt;/span&gt; matrix, but if you just flatten this matrix into a vector, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;, where the elements are ordered as &lt;span class=&quot;math-container&quot;&gt;$[x_1,y_1,z_1,x_2,y_2,z_2,\cdots]$&lt;/span&gt;, then you just need to scale the eigenvector and add it to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; to displace along that normal mode.&lt;/p&gt;&#xA;&lt;p&gt;That is,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\mathbf{r}_{disp}=\mathbf{r}+\lambda\mathbf{v}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is a constant you can choose. The actual values of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; are generally chosen just to make the displacements easy to visualize. As noted in the comments, one could associate the maximum displacement with temperature and hence give some physical meaning to &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;. Since thermal fluctuations are likely to be fairly small compared to zero-point fluctuations, this isn't that common (at least I haven't seen it). So, you should pick a range of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; values which give a nice visualization of how the atoms move.&lt;/p&gt;&#xA;&lt;p&gt;In python code (which probably won't run) this would look something like,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lam = np.linspace(-0.1,0.1,21)&#xA;r_disp = [r.flatten() + lam[i] * v for i in range(len(lam))]&#xA;r_disp = [r_disp[i].reshape(-1,3) for i in range(len(r_disp))]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You then want to write out each of the 21 geometries the above code generates and they should give a nice animation of what happens when moving along a particular mode.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="1170" LastEditDate="2022-01-14T23:42:04.903" LastActivityDate="2022-01-14T23:42:04.903" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8561" PostTypeId="2" ParentId="4356" CreationDate="2022-01-14T08:08:07.990" Score="4" Body="&lt;p&gt;When dealing with monolayers, I have found that using the &lt;code&gt;ISIF=4&lt;/code&gt; tag is better and is less time-consuming. As mentioned in &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISIF&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vaspwiki&lt;/a&gt;, it allows the relaxation of both lattice constants and atomic coordinates with a fixed volume. However, what is important here is uncommenting the &lt;code&gt;FCELL(3,3)=SAVE&lt;/code&gt; line in &lt;code&gt;constr_cell_relax.F&lt;/code&gt; file and recompiling VASP. This trick prevents the relaxation along the z-direction, which is negligible in monolayers.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-01-14T08:08:07.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8562" PostTypeId="2" ParentId="4965" CreationDate="2022-01-14T08:38:21.493" Score="5" Body="&lt;h5&gt;Short version&lt;/h5&gt;&#xA;&lt;p&gt;If the &lt;span class=&quot;math-container&quot;&gt;$\text{LiCoO}_2$&lt;/span&gt; is computed with van der Waals included, so should everything else.&lt;/p&gt;&#xA;&lt;h5&gt;Long version&lt;/h5&gt;&#xA;&lt;p&gt;This seems more of a thermodynamics question than a simulations question given the comment from May 12 '21. What is set to zero by definition is the Gibbs free energy of formation at standard temperature and pressure (1 atm, 298.15 K) for pure elements in their natural state. This explains the difference between the cited values for the solid and the liquid (comment from May 12 '21): the difference is the enthalpy of melting. More generally, the chemical potential of the various species must be taken into account appropriately to compute voltages (which are, strictly speaking, temperature-dependent) and for example defect formation energies. See for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Chemical potential of oxygen gas for surface equilibria: &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevB.65.035406&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://link.aps.org/doi/10.1103/PhysRevB.65.035406&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Chemical potentials for electronic defect energies in semiconductors: &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevLett.67.2339&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://link.aps.org/doi/10.1103/PhysRevLett.67.2339&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Chemical potentials for defect energies during synthesis: &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1361-648X/aacb05&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://iopscience.iop.org/article/10.1088/1361-648X/aacb05&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;What is computed in VASP energy minimization is the electronic potential energy of the atoms, relative to the same atoms being infinitely far apart as elemental gas. This is equal to the Gibbs free energy only at effectively zero temperature, plus the vaporization. They are different by the entropy term times the finite temperature. The DFT code does not know about us humans setting a reference state for Gibbs free energies, so everything has to be built up from the energies at 0K plus chemical potentials.&lt;/p&gt;&#xA;&lt;p&gt;[Someone correct me if I'm wrong:] The zero-point energy of vibrations is not included, and sometimes that is non-negligible, see for example: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemmater.0c03442&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.chemmater.0c03442&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Because of this, the energies computed for pure elements (e.g. the Na and the Co) do not have to be zero. All energies will change with the functional that is used. For consistency purposes, it is necessary to compute all parts of the reaction with the same level of theory and functional. If the &lt;span class=&quot;math-container&quot;&gt;$\text{LiCoO}_2$&lt;/span&gt; is computed with van der Waals included, so should everything else.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-07-30T14:05:17.900" LastActivityDate="2022-07-30T14:05:17.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8563" PostTypeId="2" ParentId="6962" CreationDate="2022-01-14T17:10:15.130" Score="3" Body="&lt;p&gt;To my understanding, the (approximate) substitution to transform the dipole from real to k-space is:&lt;sup&gt;[1]&lt;/sup&gt; &lt;span class=&quot;math-container&quot;&gt;$$\mathbf{r}\to i\exp(i\mathbf{k}\cdot \mathbf{r})\nabla_k\exp(-i\mathbf{k}\cdot \mathbf{r})\tag{1}\label{1}$$&lt;/span&gt; Applying this same identity for the quadrupole operator, you should get something like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle\psi_{n\mathbf{k}}|\mathbf{r}\mathbf{r}|\psi_{m\mathbf{k}}\rangle=-\langle u_{n\mathbf{k}}|\nabla_{\mathbf{k}}\nabla_{\mathbf{k}}|u_{m\mathbf{k}}\rangle\tag{2}\label{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the main differences between our formulas are the sign of the right hand expression and the use of &lt;span class=&quot;math-container&quot;&gt;$\psi_{n\mathbf{k}}$&lt;/span&gt; in the integrals on the lefthand side.&lt;/p&gt;&#xA;&lt;p&gt;As discussed in [1], this substitution is only valid for insulating systems in weak electric fields, as there should be an additional term in Eq \eqref{1} related to induced current within the bands of the material.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Kudin, K. N.; Scuseria, G. E. An efficient finite field approach for calculating static electric polarizabilities of periodic systems. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2000,&lt;/strong&gt; &lt;em&gt;113&lt;/em&gt; (18), 7779–7785. &lt;a href=&quot;https://doi.org/10.1063/1.1315999&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1063/1.1315999&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-01-16T14:40:53.447" LastActivityDate="2022-01-16T14:40:53.447" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8564" PostTypeId="1" AcceptedAnswerId="8567" CreationDate="2022-01-14T18:46:02.810" Score="6" ViewCount="2224" Body="&lt;p&gt;I want to add a bond between specific atoms.&#xA;I found on VMD page that one can use topotools (e.g. &lt;code&gt;topo addbond 1 2 &lt;/code&gt;), but I have a lot of residues so this method didn't work with me.&#xA;I need to select the two residues and then build a bond between the two atoms of the two different residues.&#xA;Does anyone have an idea how to do this?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="7" LastEditDate="2022-01-14T18:53:04.783" LastActivityDate="2022-01-15T07:33:21.417" Title="How to add a bond between two atoms in VMD?" Tags="|visualization-software|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8565" PostTypeId="2" ParentId="8546" CreationDate="2022-01-14T19:10:05.247" Score="6" Body="&lt;p&gt;While I don't know how particular protonation / tautomer tools work, most are trained with various ML models to predict pKa in water. Fortunately, we have a &lt;em&gt;lot&lt;/em&gt; of experimental data for that task, although sometimes of varying quality.&lt;/p&gt;&#xA;&lt;p&gt;For pKa prediction, there are a few public databases:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://openmolecules.org/datawarrior/download.html&quot; rel=&quot;noreferrer&quot;&gt;DataWarrior&lt;/a&gt; includes a set prepared by Thomas Sander&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ebi.ac.uk/chembl/&quot; rel=&quot;noreferrer&quot;&gt;ChEMBL 25&lt;/a&gt; includes many pKa records&lt;/li&gt;&#xA;&lt;li&gt;All of these are available from the &lt;a href=&quot;https://github.com/czodrowskilab/Machine-learning-meets-pKa&quot; rel=&quot;noreferrer&quot;&gt;Czodrowski lab&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'm aware of two major open source models:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/NIEHS/OPERA&quot; rel=&quot;noreferrer&quot;&gt;OPERA&lt;/a&gt; in Java from Mansouri, &lt;em&gt;et. al.&lt;/em&gt; (&lt;a href=&quot;https://doi.org/10.1186/s13321-019-0384-1&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1186/s13321-019-0384-1&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/czodrowskilab/Machine-learning-meets-pKa&quot; rel=&quot;noreferrer&quot;&gt;Machine Learning meets pKa&lt;/a&gt; from Baltruschat and Czodrowski (&lt;a href=&quot;https://f1000research.com/articles/9-113&quot; rel=&quot;noreferrer&quot;&gt;https://f1000research.com/articles/9-113&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You mentioned an interest in &lt;em&gt;quantum&lt;/em&gt; calculations for pKa. This would approach the proton affinity.&lt;/p&gt;&#xA;&lt;p&gt;To my knowledge, the current state of the art is from the Grimme group:&#xA;&lt;a href=&quot;https://link.springer.com/article/10.1007%2Fs10822-018-0145-7&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Their &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/crestxmpl.html#molecular-prototropy-screening&quot; rel=&quot;noreferrer&quot;&gt;CREST / xtb tool&lt;/a&gt; can do semi-automated protonation, deprotonation, and tautomer (deprotonation followed by protonation) screening using the GFN2 semiempirical DFTB method. Generally they recommend following the GFN2 energy calculations with higher-level DFT calculations.&lt;/p&gt;&#xA;&lt;p&gt;There are similar papers by other groups (i.e., fast semiempirical calculation, followed by DFT energy calculations of the different protonated or deprotonated forms).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-01-14T19:10:05.247" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8566" PostTypeId="1" AcceptedAnswerId="8568" CreationDate="2022-01-15T04:13:00.113" Score="9" ViewCount="280" Body="&lt;p&gt;I know that there are published interatomic potentials provided for most elements when using classical molecular dynamics tools such as LAMMPS. However, if someone were to use their own DFT calculations to develop classical potentials, what material properties should one validate to obtain an accurate description of the interactions? Or else, would it be wiser to stick to published and already available data?&lt;/p&gt;&#xA;&lt;p&gt;I am looking to study the thermal properties of Half-Heusler and Anti-florite materials.&lt;/p&gt;&#xA;&lt;p&gt;I know that a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6151/creating-interatomic-potential-for-lammps-using-dft&quot;&gt;similar question&lt;/a&gt; has been previously answered here. But I am looking for some additional details not discussed there.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="269" LastEditDate="2022-01-15T20:39:46.183" LastActivityDate="2022-06-30T21:10:31.523" Title="Considerations when developing ab initio based interatomic potentials for classical molecular dynamics" Tags="|density-functional-theory|lammps|interatomic-potentials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8567" PostTypeId="2" ParentId="8564" CreationDate="2022-01-15T07:33:21.417" Score="4" Body="&lt;p&gt;&lt;code&gt;topo addbond x y&lt;/code&gt; should do the trick. where x is the index of the atom of an residue in which you are interested.&lt;br /&gt;&#xA;if you want a more automated way, then you need to know the exact atom name and the residue number.&lt;/p&gt;&#xA;&lt;p&gt;Let's say, the residue number you are interested in is 250 and the atom name is HG1, and you want to add a bond to atom name OG1 of residue 267.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set a [atomselect top &amp;quot;residue 250 and name HG1&amp;quot;] &#xA;set aindex [$a get index]&#xA;&#xA;set a1 [atomselect top &amp;quot;residue 267 and name OG1&amp;quot;] &#xA;set a1index [$a1 get index]&#xA;&#xA;topo addbond &lt;span class=&quot;math-container&quot;&gt;$aindex $&lt;/span&gt;a1index&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;if you have a list of atom names and a list of residue numbers, you can just do a &lt;code&gt;foreach&lt;/code&gt; loop and keep the above code in the loop, in that way you can add bonds to all the desired atoms at once.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2022-01-15T07:33:21.417" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8568" PostTypeId="2" ParentId="8566" CreationDate="2022-01-15T12:35:05.743" Score="8" Body="&lt;p&gt;There is quite abit of work going on in this field right now. Take a look at what &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0035032&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rogers et al.&lt;/a&gt; are doing using MP2 to derive all aspects of a force-field. They are also working on a DFT implementation using &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acsphyschemau.1c00006&quot; rel=&quot;nofollow noreferrer&quot;&gt;B3LYP-D3(BJ)&lt;/a&gt;, since DFT is alot faster and computationally cheaper.&lt;/p&gt;&#xA;&lt;p&gt;I will assume that by &lt;em&gt;interatomic&lt;/em&gt;, we are concerned with distant atoms interacting, and not near neighbors in the same molecules, ie. bonds/angles/torsions which are generally classed as &lt;em&gt;intramolecular&lt;/em&gt; interactions. Interatomic interactions in classical molecular simulations are generally calculated as the interactions due to atom centered partial charges and Lennard-Jones (LJ) interactions, although sometimes LJ is replaced with a more expensive model such as the Buckingham (EXP-6) or other model.&lt;/p&gt;&#xA;&lt;p&gt;For inter-atomic force-field parameters, you would want to ensure that the energies and forces between atoms are accurately calculated. You can regress the Lennard-Jones(or Buckingham, or whatever model you are using) parameters to minimize the error between the model and the energy/forces calculated using quantum mechanics (QM). Perhaps start with dimers/trimers and work your way up to bigger systems if needs be.&lt;/p&gt;&#xA;&lt;p&gt;Part of the inter-atomic interactions is the partial charges, so you need to decide on a method for calculating the partial charges first( I prefer partitioning methods like MBIS or CM5, but you could use restrained-electrostatic potential (RESP) as well, or other). Once they are set in stone, you just optimize the LJ or exp-6 or other parameters.&lt;/p&gt;&#xA;&lt;p&gt;Traditionally this optimization was done by fitting to experimental data for densities, enthalpy of vaporization, and free energy (and other data). You could also add in experimental data, but, as the paper I linked shows, we are now at a stage where quite good results can be obtained purely ab-initio.&lt;/p&gt;&#xA;&lt;p&gt;Also look into the work being done by &lt;a href=&quot;https://openforcefield.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;openFF&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-06-30T21:10:31.523" LastActivityDate="2022-06-30T21:10:31.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8570" PostTypeId="1" CreationDate="2022-01-15T16:51:18.453" Score="5" ViewCount="101" Body="&lt;p&gt;I am trying to figure out how density functional theory(DFT) decides the Fermi energy. As I understand, DFT could get the result of every orbital in the periodic system, then it could fulfill the valence electrons into these orbitals. After this process of fulfilling electrons, for metal, the HOMO(Highest Occupied Molecular Orbital) should be the Fermi energy, but for semiconductors, the Fermi energy could be in the bandgap.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;For semiconductors, how does DFT decide where the Fermi energy is?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-01-15T18:26:02.580" LastActivityDate="2022-01-17T00:36:56.557" Title="How does DFT decide the Fermi energy?" Tags="|density-functional-theory|fermi-energy|" AnswerCount="0" CommentCount="2" FavoriteCount="0" ClosedDate="2022-01-17T15:16:38.457" ContentLicense="CC BY-SA 4.0" />
  <row Id="8571" PostTypeId="1" AcceptedAnswerId="8576" CreationDate="2022-01-15T18:11:00.713" Score="6" ViewCount="544" Body="&lt;p&gt;I am trying to analyze the density of electronic states of a &lt;span class=&quot;math-container&quot;&gt;$\ce{TiO2}$&lt;/span&gt; slab, but the result I got from VASP shows the fermi energy is lower than the valence band maximum (VBM) by a small energy difference (&lt;span class=&quot;math-container&quot;&gt;$\pu{0.05eV}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I am wondering if this is possible for semiconductors?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ge2TC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ge2TC.png&quot; alt=&quot;Band structure with Fermi energy below VBM&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-01-15T20:10:09.537" LastActivityDate="2022-01-17T09:15:41.767" Title="Fermi energy lower than valence band maximum?" Tags="|density-functional-theory|vasp|fermi-energy|semiconductor|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8572" PostTypeId="1" CreationDate="2022-01-16T08:26:10.857" Score="2" ViewCount="85" Body="&lt;p&gt;I'd like to compare my simulation result of a TiO2-110 surface's electronic structure, but all the literature shows too many different results, so I'd like to look for a database for surface electronic structure. Is there any database for this purpose?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-16T08:26:10.857" Title="Database of surface electronic structure" Tags="|density-functional-theory|electronic-structure|surfaces|databases|transition-metals|" AnswerCount="0" CommentCount="2" ClosedDate="2024-01-11T14:37:44.383" ContentLicense="CC BY-SA 4.0" />
  <row Id="8573" PostTypeId="1" CreationDate="2022-01-16T09:39:09.520" Score="2" ViewCount="122" Body="&lt;p&gt;I am struggling to figure out the relationship between bandgap value and surface states. To my understanding, when considering the material that includes surface, there would be some surface states in the bandgap or near the VBM/CBM, which often causes the bandgap to decrease. &lt;BR&gt;&#xA;According to my test and literature research, surface states could decrease the bandgap value by 20%-50%, for example, if the original bandgap value is 1.5eV, when there are surface states, the bandgap could be 1 or 1.2eV.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;How much would the surface state affect the band gap values, and how could I estimate it?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-01-16T09:39:09.520" Title="How would surface state affect the band gap value of semiconductors?" Tags="|density-functional-theory|band-structure|surfaces|bandgap|semiconductor|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:49:35.180" ContentLicense="CC BY-SA 4.0" />
  <row Id="8574" PostTypeId="1" CreationDate="2022-01-16T10:48:48.080" Score="4" ViewCount="185" Body="&lt;p&gt;I tried to calculate the bandgap of the TiO2-Rutile bulk phase, DFT(not +U) calculation shows the bandgap is about 1.8eV, which is roughly the same as the 1.78eV on the Material Project. When calculating the TiO2-Rutile -110 slab, whether +U or not +U, the bandgap is about 1.3eV, which is 0.5eV smaller than the bulk. After checking some literature, there are also many cases where the slab band gap is obviously smaller than bulk.&lt;/p&gt;&#xA;&lt;p&gt;But for TiO2, a lot of literature show the bandgap of the slab is 2eV-3eV with the DFT+U method, and the U value given is not very large, between 4-6, but I can’t reproduce similar results. When I increase U to 6, the bandgap of Rutile-110-slab is still around 1.3,eV which has not increased significantly, let alone reached the experimental level of 3eV.&lt;/p&gt;&#xA;&lt;p&gt;my question is:&#xA;Generally speaking, can the bandgap of slab be reduced by about 20%-40% compared to bulk?&#xA;Can +U make the bandgap change from 1.3eV to 3eV?&#xA;The slab calculation results given in the literature, using the DFT+U method to obtain a bandgap as large as 3eV, is it credible?&lt;/p&gt;&#xA;&lt;p&gt;As the following DOS diagram shows, pseudohydrogen does reduce the density of state near VBM and CBM, but it also causes the Fermi energy to fall below the VBM, which makes the material turn into a conductor.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dVgEA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dVgEA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I checked the charge density of my result, the charge from H.66 moves to H1.33.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/h2miY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/h2miY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are the VASP input files:&lt;br&gt;&#xA;KPOINTS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Spacing Value to Generate K-Mesh: 0.040&#xA;0&#xA;Gamma&#xA;   8   4   1&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;# ICHARG =  11         (Non-self-consistent: GGA/LDA band structures)&#xA;LREAL  = .FALSE.       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Normal       (Precision level)&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;# NPAR   = 4           (Max is no. nodes; don't set for hybrids)&#xA;# Nwrite = 2           (Medium-level output)&#xA;# KPAR   = 2           (Divides k-grid into separate groups)&#xA;# NGX    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGY    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA;# NGZ    = 500         (FFT grid mesh density for nice charge/potential plots)&#xA; &#xA;Static Calculation&#xA;ISMEAR =  0            (gaussian smearing method)&#xA;SIGMA  =  0.05         (please check the width of the smearing)&#xA;LORBIT =  11           (PAW radii for projected DOS)&#xA;NEDOS  =  2001         (DOSCAR points)&#xA;NELM   =  60           (Max electronic SCF steps)&#xA;EDIFF  =  1E-04        (SCF energy convergence; in eV)&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TiO2_mp-2657_slab_unitcell             &#xA;   1.0000000000000000     &#xA;     2.9691998959000001    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    6.5806999206999999    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   38.4453010559000035&#xA;   Ti   O    H1.33   H.66&#xA;     8    16     1     1&#xA;Selective dynamics&#xA;Direct&#xA;  0.5000000000168399  0.4999999999468159  0.1635600030510105   F   F   F&#xA;  0.5000000000168399  0.0000000000000000  0.2491499930530523   F   F   F&#xA;  0.5000000000168399  0.4999999999468159  0.3347299993122306   F   F   F&#xA;  0.5000000000168399  0.0000000000000000  0.4203200042185671   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.1635600030510105   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.2491499930530523   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.3347299993122306   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.4203200042185671   F   F   F&#xA;  0.5000000000168399  0.8045799732252163  0.1635600030510105   F   F   F&#xA;  0.5000000000168399  0.3045800030624690  0.2491499930530523   F   F   F&#xA;  0.5000000000168399  0.8045799732252163  0.3347299993122306   F   F   F&#xA;  0.5000000000168399  0.3045800030624690  0.4203200042185671   F   F   F&#xA;  0.5000000000168399  0.1954199970363035  0.1635600030510105   F   F   F&#xA;  0.5000000000168399  0.6954200267671808  0.2491499930530523   F   F   F&#xA;  0.5000000000168399  0.1954199970363035  0.3347299993122306   F   F   F&#xA;  0.5000000000168399  0.6954200267671808  0.4203200042185671   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.1301099955941751   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.2157000005265246   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.3012799918554023   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.3868699967877447   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.1970099955775382   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.2825999856055930   F   F   F&#xA;  0.0000000000000000  0.4999999999468159  0.3681800067430530   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.4537700116754024   F   F   F&#xA;  0.0000000000000000  0.0000000000000000  0.1179976847000919   T   T   T&#xA;  0.0000000000000000  0.4999999999468159  0.1034677544189809   T   T   T&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-01-17T14:40:55.730" LastActivityDate="2022-01-17T14:40:55.730" Title="The comparison of bandgap value of slab and bulk phase" Tags="|density-functional-theory|vasp|band-structure|hubbard-model|bandgap|" AnswerCount="0" CommentCount="8" ClosedDate="2022-01-25T21:16:48.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="8575" PostTypeId="2" ParentId="4611" CreationDate="2022-01-16T16:03:24.737" Score="7" Body="&lt;p&gt;The purpose of the dipole correction is to remove the spurious electric field that arises between the polarized 2d layer and its periodic replica (think of the correction as if it made your calculation non-periodic along z).&lt;/p&gt;&#xA;&lt;p&gt;However, there is still a physical, finite electric field &lt;em&gt;inside&lt;/em&gt; your layer, pointing from the positively charged side to the negatively charged one.&#xA;When moving a test charge through your layer, that electric field will do work on the test charge, and thus the vacuum potential [1] (=the potential &amp;quot;just outside the material&amp;quot;) is &lt;em&gt;different&lt;/em&gt; between the top and the bottom of the layer.&lt;/p&gt;&#xA;&lt;p&gt;Now, if I understand your plots and comments correctly, in this particular material the direction of the polarization is not static: at finite temperature, even the &lt;em&gt;orientation&lt;/em&gt; of the polarization swings back and forth over time.&#xA;There are two possibilities: (a) over time, the vacuum potential on the top and the bottom of the slab average out to the same value (polarization is washed out by thermal vibrations), or (b) a finite difference remains between the average vacuum potential at the top and the bottom.&lt;/p&gt;&#xA;&lt;p&gt;If (b) is the case, then, in principle, it matters whether you are interested in the vacuum potential at the top or the bottom of the layer.&lt;/p&gt;&#xA;&lt;p&gt;Note, however, that you are simulating a 2d material in vacuum, which does not exist in the real world.&#xA;In reality, your material will be supported by a substrate, which can screen the electric field, modify the vibrations, etc.&lt;/p&gt;&#xA;&lt;p&gt;[1] In case it gives you some comfort, I also struggled with the term &amp;quot;vacuum potential&amp;quot; (aka &amp;quot;vacuum level&amp;quot;) in the past, since I would intuitively associate it with the energy of an electron (or positron, whatever sign you prefer) at rest, infinitely far away from the material.&#xA;That energy (let's call it the &amp;quot;infinity level&amp;quot;) is of course always the same by definition.&lt;/p&gt;&#xA;&lt;p&gt;How does one reconcile this with the fact that, in your calculation, the potential at the top and the bottom of the layer will always be different, no matter how far away you go?&#xA;The issue here is that your layer's infinite size along x and y makes it impossible to get away from it.&#xA;Once you make your layer finite (non-periodic) in x,y it will give rise to weak, long-range electric fields (at the length scale of the dimensions of the layer), which will align the &amp;quot;infinity level&amp;quot; on both sides of the layer.&#xA;A difference in the &lt;em&gt;vacuum level&lt;/em&gt; on both sides of the slab, however, would remain.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2022-01-26T21:40:45.920" LastActivityDate="2022-01-26T21:40:45.920" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8576" PostTypeId="2" ParentId="8571" CreationDate="2022-01-16T21:58:47.103" Score="7" Body="&lt;p&gt;No, this isn't possible for an undoped semiconductor. The reason it's happening is because the Fermi level is not well defined for your semiconductor at finite temperature, and you're trying to read the valence band maximum (VBM) from the graph of your broadened DOS. I recommend taking the VBM directly from the band energies, instead.&lt;/p&gt;&#xA;&lt;p&gt;In a DFT program, the states are computed at a discrete set of k-points, and have well-defined eigenvalues (&amp;quot;band energies&amp;quot;) at those points. The DOS for this system is a set of spikes (delta-functions) at those energies, but this doesn't give you a smooth, meaningful DOS. The problem is that the DOS should be integrated over the whole Brillouin zone, but all you have are discrete sampling points.&lt;/p&gt;&#xA;&lt;p&gt;The common solution is to replace each spike with a narrow Gaussian, or similar &amp;quot;smearing function&amp;quot;, which has the effect of smoothing the states out in energy. The states are almost unchanged by any reasonable choice of the width of the Gaussian (the &amp;quot;smearing width&amp;quot;). If you increase the smearing width, the DOS gets smoother and the tail of the smearing distribution stretches to higher energies, which naturally pushes some densities-of-states higher in energy. The way you're reading the DOS, this would raise the VBM, even though the states are the same as they were before. Even worse, strictly-speaking the smearing function &lt;em&gt;never&lt;/em&gt; goes to zero, so if you &amp;quot;zoom in&amp;quot; on the DOS, you'll never find somewhere that it decays to zero, until you hit the limits of the calculations finite precision.&lt;/p&gt;&#xA;&lt;p&gt;The actual VBM is the band-energy of the topmost occupied band, so I recommend you just use that instead. If the precise value is important to you, you will need to ensure that you've sampled the Brillouin zone at the correct k-point (or as close to it as possible). You can check this visually by computing and plotting the band-structure (particularly along the high-symmetry directions).&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-01-17T09:15:41.767" LastActivityDate="2022-01-17T09:15:41.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8577" PostTypeId="2" ParentId="3505" CreationDate="2022-01-16T23:46:22.120" Score="12" Body="&lt;p&gt;The Fermi energy is defined implicitly, by requiring that the total of the band occupancies &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the number of electrons, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sum_{b=0}^{N_b}f_b=N\tag{1}\label{occ}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N_b$&lt;/span&gt; is the number of bands in the calculation. The occupancy is computed from&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$f_b = f\left(\frac{\epsilon_b-E_F}{\sigma}\right)\tag{2}\label{smearing}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the smearing function (e.g. Gaussian, Fermi-Dirac, Methfessel-Paxton), &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is the smearing width, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_b$&lt;/span&gt; is the band eigenvalue, and &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; is the Fermi energy. Only the latter of these is unknown.&lt;/p&gt;&#xA;&lt;p&gt;A simple approach is to use a bisection search. To start with, we need to bracket the true &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt;; as an example, you could try setting &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; to the minimum computed Kohn-Sham eigenvalue, and then to the maximum computed Kohn-Sham eigenvalue. There are much better choices of course, but this is a simple approach and it does work (it just takes more steps than a better choice). Once you've bracketed the real answer, you use a standard bisection search to narrow the bracket until you've determined &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; to your desired accuracy.&lt;/p&gt;&#xA;&lt;p&gt;Note that this method also demonstrates why &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; is not well-defined for semiconductors or insulators: any value in the band-gap gives the same occupancies (to within machine precision), apart from a small region where the smearing function has pushed some weight into the band-gap.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-01-18T14:24:37.567" LastActivityDate="2022-01-18T14:24:37.567" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8579" PostTypeId="2" ParentId="8557" CreationDate="2022-01-18T11:51:09.827" Score="8" Body="&lt;p&gt;There seems to be a function to read INCAR files in ASE however in the code it mentions that the functions &amp;quot;are under early constructions&amp;quot;. You can give it a try though and it might work well enough:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.calculators.vasp import Vasp&#xA;calc = Vasp()&#xA;calc.read_incar('INCAR')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Alternatively, you could move over to Pymatgen which has a more thorough pipeline to parse Vasp files: &lt;a href=&quot;https://pymatgen.org/pymatgen.io.vasp.inputs.html&quot; rel=&quot;noreferrer&quot;&gt;https://pymatgen.org/pymatgen.io.vasp.inputs.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;&lt;p&gt;-Peter&lt;/p&gt;&#xA;" OwnerUserId="4776" LastActivityDate="2022-01-18T11:51:09.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8580" PostTypeId="2" ParentId="3505" CreationDate="2022-01-18T16:07:58.243" Score="7" Body="&lt;p&gt;This has been answered very well already but just to add a practical note: For semiconductors, Vasp places the Fermi level at the valence band maximum (&lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt; smearing energy) whereas Quantum Espresso or GPAW place it at the center of the gap. If you use another code then it's advisable to double-check what convention/algorithm it uses.&lt;/p&gt;&#xA;" OwnerUserId="4776" LastActivityDate="2022-01-18T16:07:58.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8581" PostTypeId="1" AcceptedAnswerId="8582" CreationDate="2022-01-18T18:31:32.183" Score="8" ViewCount="580" Body="&lt;p&gt;I am trying to do structure optimization of TiO2, since titanium is a transition metal, I need to use DFT+U to simulate the right band structure, but the electronic band structure would also affect the force on atoms, so does this mean that I need to use DFT+U model during the structure optimization stage? How important would the inclusion of U values be?&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-01-18T19:25:10.677" LastActivityDate="2022-01-19T00:01:55.243" Title="Do the U values affect structure optimization with the DFT+U simulation to optimize crystal structure?" Tags="|density-functional-theory|electronic-structure|geometry-optimization|structure|dft-u|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8582" PostTypeId="2" ParentId="8581" CreationDate="2022-01-19T00:01:55.243" Score="10" Body="&lt;p&gt;This isn't possible to answer with any certainty without trying it. Strictly speaking, if you need a Hubbard U to correct for the spurious self-interaction, then you need it to model the material accurately - including modelling the forces, dynamical matrix etc.&lt;/p&gt;&#xA;&lt;p&gt;Having said that, it is usually found that the forces are very similar with and without U, at least as long as the ground state is qualitatively similar (e.g. it keeps the same non-metallic character, same kind of magnetisation etc). The Hubbard U only affects a few states, so the effect on the forces is often fairly small. There are no guarantees with this, this is little more than a plausibility argument and empirical observation.&lt;/p&gt;&#xA;&lt;p&gt;On a practical note, you don't have to do a full geometry optimisation to see what difference it makes. Why not do a single DFT and DFT+U calculation for the initial geometry and see how similar the forces are? If they are similar, then you could probably do the geometry optimisation without the Hubbard U. Once you've obtained the DFT ground state geometry, you can then do a DFT+U calculation at that optimised geometry and see whether the forces are within your force convergence tolerance or not.&lt;/p&gt;&#xA;&lt;p&gt;As a final remark, I'm assuming that the reason you want to do the geometry optimisation without a Hubbard U is because the DFT+U is slower or less robust. If it's slower, it might be worth seeing whether there are quicker ways of applying it (some DFT programs have several methods implemented); if it's less robust, then it may be worth investigating more sophisticated density/potential mixing methods, or alternative fully-self-consistent methods which don't use mixing schemes.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-01-19T00:01:55.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8584" PostTypeId="1" AcceptedAnswerId="8586" CreationDate="2022-01-20T05:44:46.283" Score="10" ViewCount="1893" Body="&lt;p&gt;I'm new to quantum chemistry software, so I'll try my best to explain my thought process. When running a DFT calculation, the software uses a linear combination of basis functions to approximate the electron density. The coefficients of the basis functions are optimized to minimize the energy. My question is: how do I get those coefficients out of PySCF?&lt;/p&gt;&#xA;&lt;p&gt;I've provided some code below in case it is helpful to build off of:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, dft&#xA;&#xA;# Create molecule and select basis set&#xA;mol = gto.Mole()&#xA;mol.atom = 'N 0 0 0; N 0 0 1.2'&#xA;mol.basis = 'STO-3G'&#xA;mol.build()&#xA;&#xA;# Create DFT solver and xc functional&#xA;mf = dft.RKS(mol)&#xA;mf.xc = 'b3lyp'&#xA;&#xA;# Run DFT calculation&#xA;mf.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this example, I'm using the STO-3G basis set which requires 5 orbitals per nitrogen atom: 1s, 2s, and three 2p orbitals.  Since there are 10 orbitals, I'm looking for the 10 values of the coefficients (several will be identical because of cylindrical symmetry).&lt;/p&gt;&#xA;" OwnerUserId="4819" LastActivityDate="2022-02-02T17:37:13.250" Title="How to get atomic orbital coefficients in PySCF" Tags="|density-functional-theory|pyscf|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8585" PostTypeId="1" CreationDate="2022-01-20T06:11:30.607" Score="10" ViewCount="161" Body="&lt;p&gt;It seems almost all the common implementations of Generalized Born (GB) implicit solvent models (in Amber, OpenMM etc) use the &amp;quot;pairwise descreening&amp;quot; approximation, which is described in Hawkins, Cramer &amp;amp; Truhlar 1995&lt;sup&gt;[1]&lt;/sup&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... &lt;span class=&quot;math-container&quot;&gt;$H_k$&lt;/span&gt; is eclipsed surface area of sphere of radius &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; centered at atom &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. Therefore&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\alpha_k^{-1}=\rho_k^{-1}-\int_{\rho_k}^{\infty}\frac{dr}{r^2}H_k(r,\{R_{kk'},\rho_{k'}\}_\text{all k'})\tag{9}$$&lt;/span&gt;&#xA;Using the pairwise descreening approximation, we can replace Eq. (9) with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\alpha_k^{-1}=\rho_k^{-1}-\sum_{k'}\int_{\rho_k}^{\infty}\frac{dr}{r^2}H_{kk'}(R_{kk'},\rho_{k'})\tag{10}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$H_{kk'}$&lt;/span&gt; is the fraction of the area of a sphere with radius &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; centered at atom &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; that is shielded by a sphere of radius &lt;span class=&quot;math-container&quot;&gt;$\rho_{k'}$&lt;/span&gt; at a distance &lt;span class=&quot;math-container&quot;&gt;$R_{kk'}$&lt;/span&gt;. Eq. (10) is exact provided there is no overlap between any atomic spheres &lt;span class=&quot;math-container&quot;&gt;$k',k''\neq k$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\alpha_k$&lt;/span&gt; is the Generalized Born radius of atom &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;.  Equation 9 is exact, where the integral is over the area eclipsed by all nearby atoms; equation 10 is the approximation, which is a sum of integrals over the area eclipsed by one atom at a time.&lt;/p&gt;&#xA;&lt;p&gt;I understand what the approximation does, but I don't understand how it is not a really inaccurate approximation, especially with bonded atoms. Consider a sphere of radius r (dashed line) around atom A, which intersects two atoms B and C bonded to each other (where &lt;span class=&quot;math-container&quot;&gt;$\text{bond length} \ll \text{sum of atom radiuses}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Bramn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Bramn.png&quot; alt=&quot;Overlapping spheres B and C within a radius r of sphere A&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Under the pairwise approximation, the area where the two atoms overlap would count as being eclipsed twice (instead of the correct method which is to count it once). In a typical biomolecular simulation (e.g. a protein), each atom is bonded to a few others and the Born radius (~&lt;span class=&quot;math-container&quot;&gt;$\pu{0.27nm}$&lt;/span&gt; for carbon) is much more than the bond length (~&lt;span class=&quot;math-container&quot;&gt;$\pu{0.15nm}$&lt;/span&gt; for C-C bond). Most bonded atoms would have a lot of overlap - back of the envelope, two carbons bonded to each other would have about 65% area overlap in a plane that passes through their nuclei, and similar percentage overlap in the integral in equation 10. In a crowded environment where a lot of the space is occupied (relatively little solvent volume) and most atoms each have a few bonds (and hence overlap the atoms they're bonded to), this would seem to result in a very large relative error in calculated GB radius.&lt;/p&gt;&#xA;&lt;h4&gt;How is this approximation okay? Are there any systematic studies of the degree of error this introduces?&lt;/h4&gt;&#xA;&lt;p&gt;P.S. I think pairwise descreening idea originally comes from Schaeffer and Froemmel 1995&lt;sup&gt;[2]&lt;/sup&gt;; the Hawkins paper above may be the first to derive the analytical expression for the GB radius.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Hawkins, G. D.; Cramer, C. J.; Truhlar, D. G. Pairwise solute descreening of solute charges from a dielectric medium. &lt;em&gt;Chem. Phys. Lett.&lt;/em&gt; &lt;strong&gt;1995,&lt;/strong&gt; &lt;em&gt;246&lt;/em&gt; (1-2), 122–129. &lt;a href=&quot;https://doi.org/10.1016/0009-2614(95)01082-K&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1016/0009-2614(95)01082-K&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Schaefer, M.; Froemmel, C. A precise analytical method for calculating the electrostatic energy of macromolecules in aqueous solution. &lt;em&gt;J. Mol. Biol.&lt;/em&gt; &lt;strong&gt;1990,&lt;/strong&gt; &lt;em&gt;216&lt;/em&gt; (4), 1045–1066. &lt;a href=&quot;https://doi.org/10.1016/S0022-2836(99)80019-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1016/S0022-2836(99)80019-9&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="40" LastEditorUserId="5" LastEditDate="2022-02-24T04:25:19.757" LastActivityDate="2023-02-03T16:37:37.087" Title="Generalized Born implicit solvent models and pairwise descreening" Tags="|molecular-dynamics|implicit-solvent|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8586" PostTypeId="2" ParentId="8584" CreationDate="2022-01-20T11:18:05.650" Score="10" Body="&lt;p&gt;Broadly, there are two flavors of Density Functional Theory (DFT): Orbital Free DFT and Kohn-Sham DFT (KS-DFT). In Orbital Free DFT, we do indeed directly optimize the density until we find the minimum energy. In KS-DFT, however, we instead optimize the coefficients of the KS orbitals, which are the solutions to the KS equations:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\left(-\frac{1}{2}\nabla^2 + v(r)\right) \psi_i(r) = \epsilon_i \psi_i(r),\tag{1}$$&lt;/span&gt;&#xA;and which can be used to construct the density:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\rho(r) = \sum_i^N |\psi_i(r)|^2.\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The coefficients of the KS orbitals are readily available as a 2D array through &lt;code&gt;mf.mo_coeff&lt;/code&gt;. If you read &lt;a href=&quot;https://pyscf.org/quickstart.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;the quickstart guide&lt;/a&gt;, you can see them being manipulated in the section “Spatially Localized Molecular Orbitals”.&lt;/p&gt;&#xA;&lt;p&gt;Now, as you mentioned we are using some finite basis for these calculations. In practice, these basis functions are used to represent the KS Orbitals, not the density:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi_i(r) = \sum_j^M c_{ij} \phi_j(r).\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You'll notice that if you try plugging this equation in to the equation for the density, you will end up squaring both the coefficients and the basis functions, so that it is not straightforward to compute the density in the original basis. Furthermore, just because the original basis can represent the KS orbitals well, there is no guarantee it can represent the density.&lt;/p&gt;&#xA;&lt;p&gt;Nonetheless, we have to construct the density in order to compute the KS potential. Inside PySCF, in fact the density is constructed on a set of atom centered, radial grids. In the &lt;a href=&quot;https://pyscf.org/user/dft.html#numerical-integration-grids&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF tutorial on DFT&lt;/a&gt;, you can see a snippet constructing the density on such a grid. You might also want to construct the density on a regularly spaced grid so that you can visualize it directly. This can be done using the &lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.tools.html#module-pyscf.tools.cubegen&quot; rel=&quot;nofollow noreferrer&quot;&gt;cubegen module&lt;/a&gt; of PySCF.&lt;/p&gt;&#xA;" OwnerUserId="800" LastEditorUserId="5" LastEditDate="2022-01-22T23:25:32.643" LastActivityDate="2022-01-22T23:25:32.643" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8587" PostTypeId="2" ParentId="8312" CreationDate="2022-01-21T02:23:50.073" Score="6" Body="&lt;p&gt;This is basic bash-script which will be quite useful, just start with scratch&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy -d --dim 2 2 2 --pa auto -c POSCAR                    &#xA;                                                                     &#xA;for m in `ls POSCAR-0*`                                              &#xA;do                                                                   &#xA;fol=`echo $m|cut -d &amp;quot;-&amp;quot; -f 2`                                        &#xA;mkdir dis_&lt;span class=&quot;math-container&quot;&gt;$fol                                                       &#xA;cp POSCAR-$&lt;/span&gt;fol dis_&lt;span class=&quot;math-container&quot;&gt;$fol/POSCAR                                       &#xA;cp INCAR.phon dis_$&lt;/span&gt;fol/INCAR                                         &#xA;cp POTCAR dis_&lt;span class=&quot;math-container&quot;&gt;$fol/                                                  &#xA;cp KPOINTS.phon dis_$&lt;/span&gt;fol/KPOINTS                                     &#xA;#cp run.pbs dis_&lt;span class=&quot;math-container&quot;&gt;$fol/                                                &#xA;cd dis_$&lt;/span&gt;fol/                                                         &#xA;#run vasp                                        &#xA;cd ..                                                                &#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;save this as file1.sh and run as bash -i file1.sh&#xA;For getting results in one shot&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;list=&lt;span class=&quot;math-container&quot;&gt;$(ls -d dis*)                                                   &#xA;echo $&lt;/span&gt;{list}                                                         &#xA;phonopy -f ${list}/vasprun.xml                   &#xA;cat &amp;lt;&amp;lt;END &amp;gt;mesh.conf                                                 &#xA;DIM = 2 2 2                                                          &#xA;ATOM_NAME = Al                                                       &#xA;MP = 31 31 31                                                        &#xA;EIGENVECTORS = .true.                                                &#xA;FORCE_CONSTANTS = Write                                              &#xA;END                                                                  &#xA;phonopy -t mesh.conf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;save this again in as bash script and run it&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-01-21T02:29:20.757" LastActivityDate="2022-01-21T02:29:20.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8588" PostTypeId="1" CreationDate="2022-01-21T08:08:29.890" Score="8" ViewCount="287" Body="&lt;p&gt;I am trying to optimize the geometry of a Cs4CuSb2Cl12 Stoichiometric Quantum dot and I have checked the input multiple times, but the opt+freq calculation is not converging. The quantum dot has about 80 atoms and is charge neutral furthermore I don't see any dangling bonds as such.&lt;/p&gt;&#xA;&lt;p&gt;Here is my input file -&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%NProcShared=16&#xA;%mem=24GB&#xA;%chk=Checkpoint_dbperovskite_geo_2.chk&#xA;#p opt freq cam-b3lyp/gen nosymm int=(grid=ultrafine,acc2e=12) pseudo=read&#xA;&#xA; geometry opetimization_cs4cusb2cl12_stochiometric&#xA;&#xA;0 1&#xA;Cs         3.89312        0.00000       10.49322&#xA;Cs         1.85782        3.66335        7.48003&#xA;Sb        -0.41300        0.00000        9.15427&#xA;Cu         4.07868        0.00000        6.03024&#xA;Cl         5.00209        1.62404        7.36968&#xA;Cl         1.78933        0.00000        7.65648&#xA;Cl         0.56747        1.74654       10.53435&#xA;Cl        -2.53224        0.00000       10.58850&#xA;Cs         4.26424        0.00000        1.56726&#xA;Cs        -2.61973        3.66335       10.49322&#xA;Cs        10.77709        3.66335        1.56726&#xA;Cs         6.29954        3.66335        4.58045&#xA;Cs         8.37067        0.00000        7.48003&#xA;Cs        -0.21331        0.00000        4.58045&#xA;Sb         8.57036        0.00000        2.90621&#xA;Sb         6.09985        3.66335        9.15427&#xA;Sb         2.05751        3.66335        2.90621&#xA;Cu        -2.43417        3.66335        6.03024&#xA;Cl         3.15527        1.62404        4.69080&#xA;Cl         3.15527        5.70266        4.69080&#xA;Cl         5.00209        5.70266        7.36968&#xA;Cl        -1.51076        5.28739        7.36968&#xA;Cl         9.66812        5.28739        4.69080&#xA;Cl         9.66812        2.03931        4.69080&#xA;Cl        -1.51076        2.03931        7.36968&#xA;Cl         6.36803        0.00000        4.40401&#xA;Cl         8.30218        3.66335        7.65648&#xA;Cl        -0.14482        3.66335        4.40401&#xA;Cl         7.58989        1.74654        1.52613&#xA;Cl         7.58989        5.58016        1.52613&#xA;Cl         0.56747        5.58016       10.53435&#xA;Cl         7.08032        5.40989       10.53435&#xA;Cl         1.07704        5.40989        1.52613&#xA;Cl         1.07704        1.91681        1.52613&#xA;Cl         7.08032        1.91681       10.53435&#xA;Cl        10.68959        0.00000        1.47198&#xA;Cl         3.98061        3.66335       10.58850&#xA;Cl         4.17674        3.66335        1.47198&#xA;Cs        -0.97523        0.00000       22.55371&#xA;Cs        -3.01053        3.66335       19.54052&#xA;Sb        -5.28135        0.00000       21.21475&#xA;Cu        -0.78967        0.00000       18.09072&#xA;Cl         0.13374        1.62404       19.43016&#xA;Cl        -3.07902        0.00000       19.71696&#xA;Cl        -4.30088        1.74654       22.59483&#xA;Cl        -7.40058        0.00000       22.64898&#xA;Cs        -0.60410        0.00000       13.62774&#xA;Cs        -7.48808        3.66335       22.55371&#xA;Cs         5.90875        3.66335       13.62774&#xA;Cs         1.43119        3.66335       16.64093&#xA;Cs         3.50232        0.00000       19.54052&#xA;Cs        -5.08166        0.00000       16.64093&#xA;Sb         3.70201        0.00000       14.96670&#xA;Sb         1.23150        3.66335       21.21475&#xA;Sb        -2.81084        3.66335       14.96670&#xA;Cu        -7.30252        3.66335       18.09072&#xA;Cl        -1.71308        1.62404       16.75129&#xA;Cl        -1.71308        5.70266       16.75129&#xA;Cl         0.13374        5.70266       19.43016&#xA;Cl        -6.37911        5.28739       19.43016&#xA;Cl         4.79977        5.28739       16.75129&#xA;Cl         4.79977        2.03931       16.75129&#xA;Cl        -6.37911        2.03931       19.43016&#xA;Cl         1.49968        0.00000       16.46449&#xA;Cl         3.43383        3.66335       19.71696&#xA;Cl        -5.01317        3.66335       16.46449&#xA;Cl         2.72155        1.74654       13.58662&#xA;Cl         2.72155        5.58016       13.58662&#xA;Cl        -4.30088        5.58016       22.59483&#xA;Cl         2.21197        5.40989       22.59483&#xA;Cl        -3.79130        5.40989       13.58662&#xA;Cl        -3.79130        1.91681       13.58662&#xA;Cl         2.21197        1.91681       22.59483&#xA;Cl         5.82125        0.00000       13.53247&#xA;Cl        -0.88773        3.66335       22.64898&#xA;Cl        -0.69160        3.66335       13.53247&#xA;&#xA;Cs Sb Cu 0&#xA;LANL2DZ&#xA;****&#xA;Cl 0&#xA;6-31+g(d)&#xA;****&#xA;&#xA;Cs Sb Cu 0&#xA;LANL2DZ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If there is anything that could be causing the convergence issues please let me know. And if the input is correct does that mean our quantum dot system is not stable. Because the PhD student who I am working under thinks that our input as well as system is correct but Gaussian's basis set are not compatible with this and all the literature regarding the substance actually uses VASP or some other plane wave based dft code.&lt;/p&gt;&#xA;&lt;p&gt;I think it is possible that it is possible that there is something wrong with the structure too, so here is a snipit.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GCEQA.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GCEQA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/l2O7X.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/l2O7X.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The log file gives the conversion error at the end&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt; Convergence criterion not met.&#xA; SCF Done:  E(RCAM-B3LYP) =  -23237.5859709     A.U. after  129 cycles&#xA;             Convg  =    0.1362D-02             -V/T =  2.0258&#xA; KE= 2.265279142009D+04 PE=-1.242564502738D+05 EE= 4.383249239695D+04&#xA; Convergence failure -- run terminated.&#xA; Error termination via Lnk1e in /scf-data/apps/gaussian/g09/l502.exe at Sun Dec 26 05:00:55 2021.&#xA; Job cpu time: 39 days  3 hours 26 minutes 55.5 seconds.&#xA; File lengths (MBytes):  RWF=   1493 Int=      0 D2E=      0 Chk=    442 Scr=      2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Although the same convergence error is not seen in the out.txt file but rather some weird error shows up,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error: segmentation violation&#xA;   rax 0000000000000000, rbx ffffffffffffffff, rcx ffffffffffffffff&#xA;   rdx 0000000000016888, rsp 00007ffc6e52a518, rbp 00007ffc6e52ab00&#xA;   rsi 000000000000000b, rdi 0000000000016888, r8  00007f90d2e81740&#xA;   r9  0000000000000000, r10 00007ffc6e529920, r11 0000000000000206&#xA;   r12 0000000000000000, r13 0000000000000000, r14 00007ffc6e52ab48&#xA;   r15 00000000000003e6&#xA;  --- traceback not available&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the link to the &lt;a href=&quot;https://drive.google.com/file/d/14ZknhkJoRS3ICAR7xHz4cTTSHU0RPDPG/view?usp=sharing&quot; rel=&quot;noreferrer&quot;&gt;log file&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-01-21T18:07:18.873" LastActivityDate="2022-01-23T18:07:39.713" Title="Geometrical Optimization not converging for a double perovskite quantum dot, using Gaussian" Tags="|gaussian|quantum-dots|perovskites|energy-conversion|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8589" PostTypeId="1" AcceptedAnswerId="8605" CreationDate="2022-01-21T10:33:56.303" Score="10" ViewCount="155" Body="&lt;p&gt;In finding out the viscosity of a system with non-equilibrium MD using GROMACS, an acceleration is given to the system due to which, the velocity profile changes. This change in energy is used to estimate viscosity as shown by the equations in this &lt;a href=&quot;https://manual.gromacs.org/documentation/2019-rc1/reference-manual/special/viscosity-calculation.html&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For different molecular systems at the same T&amp;amp;P conditions and similar densities but with different acceleration amplitudes, the viscosity decreases with a different slope, as acceleration amplitude increases. As the viscosity at steady state is obtained by extrapolating these values to 0 acceleration amplitude, this slope is important in changing the values significantly. Therefore, I would like to know the property that this slope signifies.&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="148" LastEditDate="2022-01-21T10:44:34.287" LastActivityDate="2022-01-25T15:19:15.657" Title="What does the slope in the viscosity vs shear acceleration graph from non-equilibrium MD signify?" Tags="|molecular-dynamics|gromacs|nonequilibrium|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8590" PostTypeId="2" ParentId="8537" CreationDate="2022-01-21T12:36:22.703" Score="7" Body="&lt;p&gt;I think the reason is many-fold. In addition to what Tristan mentioned, there are some other possible reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The principle quantum number is a relatively ill-defined concept for an atom in a molecule or material. The valence orbitals of an atom usually shrink somewhat upon bonding (or expand, if the atom becomes noticeably negatively charged during bonding). Do you view a shrunk 4s orbital as a pure 4s orbital, or a linear combination of 3s and 4s (and possibly other s) orbitals? There are some inherent ambiguities here. By contrast, an s orbital is always a pure s orbital, without any other angular momentum contributions, if it simply expands or contracts. Even if it is deformed and acquire p, d, ... components, it is always possible to rigorously separate out these components by harmonic analysis.&lt;/li&gt;&#xA;&lt;li&gt;If one defines a shrunk 4s orbital as still essentially a 4s orbital (and similarly for other principle quantum numbers), then one will find that orbitals with &amp;quot;core&amp;quot; principle quantum numbers are always almost full, and those with &amp;quot;Rydberg&amp;quot; ones always almost empty. Thus for every atom and every angular momentum, there is usually only one principle quantum number for which the orbital has a non-trivial occupation number. Decomposing the DOS using principle quantum numbers thus usually does not lead to any additional insights.&lt;/li&gt;&#xA;&lt;li&gt;With the exception of high-lying Rydberg orbitals (which are generally not interesting in bulk materials anyway, as it is usually more physically useful to describe them using plane waves instead, because any tight binding approximation will fail for these high-lying bands), the PDOSs of all principle quantum numbers of the same angular momentum are usually well-separated in energy. Thus, if you look at the s PDOS of a period 4 element, for example, you will find that the 1s, 2s, 3s and 4s components already stand out as very clearly separated bands, and you can identify their principle quantum numbers by simple counting; from 5s on, the s bands may start to overlap, but you are usually not interested in them anyway. This contrasts with the usual practice where you decompose a mixed band of 3d, 4s and 4p into s, p and d contributions using PDOS, in which case you cannot do the same job simply by looking at the total DOS.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-01-21T12:36:22.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8591" PostTypeId="1" CreationDate="2022-01-22T00:58:59.733" Score="7" ViewCount="332" Body="&lt;p&gt;Many software packages provide means to calculate the Coulomb and exchange integrals, for example, the exchange&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\int \phi^*(1) \, \psi^*(2) \frac{1}{|\mathbf{r_1} - \mathbf{r_2}|} \, \psi(1) \, \phi(2) \, d\mathbf{r_1} \, d\mathbf{r_2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;using gaussian type orbitals, either in cartesian or spherical coordinates.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know how this integral is evaluated in practice, since the Coulomb term &lt;span class=&quot;math-container&quot;&gt;$1/|\mathbf{r_1}-\mathbf{r_2}|$&lt;/span&gt; should diverge whenever two different electron densities' volume elements overlap. I understand that when you use spherical coordinates, you can get rid of &lt;span class=&quot;math-container&quot;&gt;$1/r_{12}$&lt;/span&gt; because the spherical volume element becomes something like &lt;span class=&quot;math-container&quot;&gt;$r^2 \cos{\theta} \, dr \, d\theta \, d\phi$&lt;/span&gt;, so you cancel &lt;span class=&quot;math-container&quot;&gt;$r^2$&lt;/span&gt; in the numerator with &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; in the denominator. But I'm having trouble to see how can this be done for cartesian GTO in cartesian coordinates.&lt;/p&gt;&#xA;" OwnerUserId="4794" LastActivityDate="2022-01-22T00:58:59.733" Title="Evaluating Coulomb and exchange integrals in practice using cartesian coordinates" Tags="|hartree-fock|integrals|exchange-correlation|" AnswerCount="0" CommentCount="7" ClosedDate="2022-11-03T15:48:12.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="8592" PostTypeId="1" AcceptedAnswerId="8604" CreationDate="2022-01-22T00:56:57.997" Score="10" ViewCount="400" Body="&lt;p&gt;I am trying to prepare turbostratic carbon structure from an initial random carbon sample with a density of 1.8gcm&lt;span class=&quot;math-container&quot;&gt;$^{-3}$&lt;/span&gt;. The initial sample image is attached here:  &lt;a href=&quot;https://i.stack.imgur.com/Xv8lc.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Xv8lc.jpg&quot; alt=&quot;Initial sample with randomly arranged carbon atoms placed with minimum distance (1.95 Angstrom) between them&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The problem is the high negative pressure (up to -100,000 bars) during the quenching process. You can see the pressure distribution as the blue curve of the following image: &lt;a href=&quot;https://i.stack.imgur.com/4pg39.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4pg39.png&quot; alt=&quot;macroscopic/average properties over time&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I understand pressure can be negative in MD simulations. However, this is a very high negative pressure in my opinion, and something is going wrong here I'm guessing. Moreover, it creates problems later on when a barostat is applied to equilibrate sample at room pressure (e.g. stress distribution in atoms changes completely after barostating, due to large adjustment of atom positions corresponding to large pressure adjustment). I'd really appreciate any advice on getting rid of such high negative pressure. I have used &amp;quot;&lt;a href=&quot;https://docs.lammps.org/fix_temp_csvr.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bussi1&lt;/a&gt;&amp;quot;  thermostat along with NVE integrator to control temperature and update atom positions and velocity respectively. below is my script&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# ------------------------------------------&#xA;# ----- Initialization----------------------&#xA;# ------------------------------------------&#xA;&#xA;units metal&#xA;atom_style atomic&#xA;boundary p p p&#xA;newton on&#xA;dimension 3&#xA;&#xA;# reading initial/restart sample -----------&#xA;read_data MDSample.dat&#xA;&#xA;&#xA;# ------------------------------------------&#xA;# -------- Simulation setting --------------&#xA;# ------------------------------------------&#xA;&#xA;# pair potential----------------------------&#xA;pair_style tersoff&#xA;pair_coeff * * SiCGe.tersoff C&#xA;&#xA;# time step---------------------------------&#xA;#reset_timestep 0&#xA;timestep 0.00005&#xA;&#xA;# minimization -----------------------------&#xA;min_style cg&#xA;minimize 1.0e-20 1.0e-20 1000 10000&#xA;&#xA;# set intial temperature -------------------&#xA;velocity all create 100 1201&#xA;&#xA;# compute virial stress of each atoms ------&#xA;compute atomstress all stress/atom NULL virial&#xA;&#xA;# compute ke of each atoms -----------------&#xA;compute atomke all ke/atom&#xA;&#xA;# compute pe of each atoms -----------------&#xA;compute atompe all pe/atom&#xA;&#xA;# compute global msd ----------------------- &#xA;compute mymsd all msd&#xA;&#xA;# macroscopic/ensemble average output variables --------------------------------&#xA;thermo_style custom step dt time atoms temp press pe ke etotal evdwl vol density c_mymsd[*]&#xA;thermo 1000&#xA;&#xA;&#xA;# -----------------------------------------&#xA;# ---- Melting simulation(8000K) (5ps)-----&#xA;# -----------------------------------------&#xA;&#xA;# set ensemble -----------------------------&#xA;fix 1 all nve&#xA;fix 2 all temp/csvr 8000.0 8000.0 0.1 54324&#xA;&#xA;# print restart file -----------------------&#xA;restart 100000 MeltSample.restart&#xA;&#xA;# print sample file for visualization -----&#xA;dump sample all custom 100000 MeltSample.txt id x y z c_atomstress[*] c_atomke c_atompe&#xA;&#xA;run 100000 #--------------------------------&#xA;unfix 1&#xA;unfix 2&#xA;&#xA;&#xA;# -----------------------------------------&#xA;# ---- Quenching simulation(300K) (5ps)----&#xA;# -----------------------------------------&#xA;&#xA;# set ensemble -----------------------------&#xA;fix 3 all nve&#xA;fix 4 all temp/csvr 300.0 300.0 0.1 54324&#xA;&#xA;# print restart file -----------------------&#xA;restart 200000 Quench300K.restart&#xA;&#xA;# print sample file for visualization -----&#xA;dump sample1 all custom 200000 Quench300K.txt id x y z c_atomstress[*] c_atomke c_atompe&#xA;&#xA;run 100000 #--------------------------------&#xA;unfix 3&#xA;unfix 4&#xA;&#xA;&#xA;# -----------------------------------------&#xA;# ---Annealing simulation (5000K)(50ps)---&#xA;# -----------------------------------------&#xA;&#xA;# set ensemble -----------------------------&#xA;fix 5 all nve&#xA;fix 6 all temp/csvr 5000.0 5000.0 0.1 54324&#xA;&#xA;# print restart file -----------------------&#xA;restart 1200000 Ann5000K.restart&#xA;&#xA;# print sample file for visualization -----&#xA;dump sample2 all custom 1200000 Ann5000K.txt id x y z c_atomstress[*] c_atomke c_atompe&#xA;&#xA;run 1000000 #--------------------------------&#xA;unfix 5&#xA;unfix 6&#xA;&#xA;&#xA;#############################################&#xA;print &amp;quot;All done&amp;quot;&#xA;#############################################&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4833" OwnerDisplayName="Abd" LastEditorUserId="5" LastEditDate="2022-01-26T03:14:48.787" LastActivityDate="2022-01-26T03:14:48.787" Title="Very high negative pressure in MD simulation of liquid quenching" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="8593" PostTypeId="1" AcceptedAnswerId="8594" CreationDate="2022-01-22T15:11:51.640" Score="8" ViewCount="331" Body="&lt;p&gt;I was pointed towards the use of the &lt;a href=&quot;https://www.iue.tuwien.ac.at/phd/windbacher/node31.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Deformation Potential&lt;/a&gt; (DP) theory to calculate the electron relaxation time in a &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7117/4232&quot;&gt;previous question&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, I still have a doubt regarding its applicability to 2D and 1D systems.&lt;/p&gt;&#xA;&lt;p&gt;Are there any special considerations which I should take before applying the DP theory to such low-dimensional systems?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2022-01-23T05:01:26.663" LastActivityDate="2022-01-23T05:01:26.663" Title="Can deformation potential theory be applied to 2D and 1D systems?" Tags="|vasp|condensed-matter|solid-state-physics|electronic-transport|quantum-dots|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8594" PostTypeId="2" ParentId="8593" CreationDate="2022-01-22T23:24:40.887" Score="9" Body="&lt;p&gt;Deformation potential theory is almost always used to study 2D materials. The first line of the abstract of the &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.80.72&quot; rel=&quot;noreferrer&quot;&gt;original Bardeen-Shockley paper&lt;/a&gt; mentions &amp;quot;deformations of the crystal lattice&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;So the considerations you should take when applying the DP theory to 2D systems are not &amp;quot;special&amp;quot;, they are the standard. If you need help getting started on applying the DP theory to your specific 2D system, then it would be wise to look at some examples of the DP theory being used on real systems. It is discussed in a plethora of a papers and even books, for example in Section 1.3.C of &lt;a href=&quot;https://books.google.ca/books?id=0PPjBwAAQBAJ&amp;amp;pg=PA39&amp;amp;lpg=PA39&amp;amp;dq=deformation+potential+mahan+many-particle+physics&amp;amp;source=bl&amp;amp;ots=KEvuKPSZsu&amp;amp;sig=ACfU3U3zhePvHBWTyFLOwd24RT7X094VUw&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=2ahUKEwjjp-rFvMb1AhXzlWoFHQjhA-sQ6AF6BAgfEAM#v=onepage&amp;amp;q=deformation%20potential%20mahan%20many-particle%20physics&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;this version of Mahan's Many-Particle Physics&lt;/a&gt; book (this book also contains references to some of the older papers on deformation potentials, and you can look at papers that have cited those papers recently in order to find more recent examples of related literature).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-01-22T23:24:40.887" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8595" PostTypeId="1" CreationDate="2022-01-23T10:00:02.550" Score="6" ViewCount="97" Body="&lt;p&gt;I am trying to calculate transition dipole moment derivatives using Turbomole 7.3. For some reason, and although I think I included the neccessary keywords to perform such a calculation, they are not found in the output, maybe beause an instruction is not properly written or is missing.&lt;/p&gt;&#xA;&lt;p&gt;This are the keywords I included in the control file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$denconv - flag&#xA;$excitations&#xA;  irrep=a  multiplicity=  1  nexc=  3  npre=  1  nstart=  1&#xA;  exprop  states=all relaxed  operators=xdiplen,ydiplen,zdiplen&#xA;  spectrum states=all  operators=xdiplen,ydiplen,zdiplen&#xA;  momdrv states=all operators=xdiplen,ydiplen,zdiplen&#xA;$response&#xA;  fop relaxed&#xA;$ricc2&#xA;  adc(2)&#xA;  maxiter = 100&#xA;$cbas file=auxbasis&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have checked the excited state file and also the output one, but only the transition dipole moments are written, not the derivatives.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know how to solve this problem? Thank you&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2022-01-23T10:00:02.550" Title="Transition dipole moment derivative TURBOMOLE" Tags="|excited-states|dipole|turbomole|" AnswerCount="0" CommentCount="2" ClosedDate="2022-11-03T15:47:53.233" ContentLicense="CC BY-SA 4.0" />
  <row Id="8596" PostTypeId="1" CreationDate="2022-01-23T11:17:03.393" Score="2" ViewCount="193" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zv3ni.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zv3ni.png&quot; alt=&quot;Iron carbon phase diagram&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've tried calculating the percent composition of the ferrite eutectoid solid using: &lt;span class=&quot;math-container&quot;&gt;$$\frac{(6.67-1.09)}{(6.67-0)}=83.7\%$$&lt;/span&gt; but the answer key says it should be &lt;span class=&quot;math-container&quot;&gt;$35.8\%$&lt;/span&gt;. What am I doing wrong?&lt;/p&gt;&#xA;" OwnerUserId="4835" LastEditorUserId="7" LastEditDate="2022-01-23T21:31:16.197" LastActivityDate="2022-01-23T21:31:16.197" Title="Determine eutectic composition from iron-carbon phase diagram" Tags="|alloys|phase-diagram|microstructure|" AnswerCount="0" CommentCount="2" ClosedDate="2022-01-29T18:31:06.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="8597" PostTypeId="2" ParentId="8588" CreationDate="2022-01-23T14:48:40.623" Score="5" Body="&lt;p&gt;I didn't deal with perovskite before, but I got this problem when I used metal atom in my complex.&lt;/p&gt;&#xA;&lt;p&gt;So, from my point of view, I think your calculation needs more cycles to get converged so what about increasing the number of cycles using keyword &lt;code&gt;SCF(MaxCycle=1000)&lt;/code&gt; and if it didn't work well, you can use keyword &lt;code&gt;SCF=XQC&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;XQC means you will use quadratically convergent SCF procedure in case the first-order SCF has not converged. It will need more time, so my advice, you can try with small basis set to see if it worked well, then you can use your basis set.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="4657" LastEditDate="2022-01-23T14:55:00.217" LastActivityDate="2022-01-23T14:55:00.217" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8598" PostTypeId="2" ParentId="8588" CreationDate="2022-01-23T18:07:39.713" Score="6" Body="&lt;p&gt;OK, I do not want to be that guy, but I will be that guy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Some general remarks&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You should plan better your calculation projects. You got 129 SCF cycle calculated in about 3 days. Even if this converges and everything goes right, it can easily take a month to complete a single “opt freq” calculation. That is way too much time to “just trying out something” or fiddling with parameters.&lt;/li&gt;&#xA;&lt;li&gt;Especially if you have a slower calculation like this, it worth to pre-optimize your structure with something similar but faster: eg with a pure functional.&lt;/li&gt;&#xA;&lt;li&gt;Whenever you have an SCF convergence problem, check: geometry, if you have a small HOMO-LUMO gap, how does the SCF energies look like. Sometimes you just need a few steps more, sometimes those are wildly oscillating. It is always a good idea to play a little bit with DIIS and dumping, it often cures smaller issues.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Remarks specific to nanoparticles&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Nanoparticles, oxides, halogenides etc are notoriously hard to calculate with local basis sets.&lt;/li&gt;&#xA;&lt;li&gt;Geometry of the nanoparticle does matter. Try to find the dominant faces and morphologies. Try to find out what are the typical coordinations on the surface (from experimental data). When you create models, do not just randomly cut out something from the bulk. Generally, models that has no huge dipole moment, somewhat symmetric, all metal ions are mostly coordinated and shapes not too elongated are the easiest to converge. Compared to that you have many Sb and Cu with low coordination numbers. I would also expect dipole moment, too, just from how asymmetric arrangement of positive and negative ions.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="91" LastActivityDate="2022-01-23T18:07:39.713" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8599" PostTypeId="1" CreationDate="2022-01-24T05:36:32.023" Score="10" ViewCount="1170" Body="&lt;p&gt;I'm trying to visualize the different methods of getting localized orbital (LO) given in the &lt;a href=&quot;https://pyscf.org/user/lo.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;User Guide&lt;/a&gt;.  I went through the example, saved the orbitals as cube files, then opened the files in Avogadro to visualize.  However, most of the occupied orbitals don't look localized at all so I think I'm doing something wrong.  The code I'm using is below.  I also tried to parallel the &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/local_orb/04-ibo_benzene_cubegen.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;example code for generating cube files&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from pyscf import gto, scf, lo&#xA;from pyscf.tools import cubegen&#xA;&#xA;x = .63&#xA;mol = gto.M(atom=[['C', (0, 0, 0)],&#xA;                  ['H', (x ,  x,  x)],&#xA;                  ['H', (-x, -x,  x)],&#xA;                  ['H', (-x,  x, -x)],&#xA;                  ['H', ( x, -x, -x)]],&#xA;            basis='ccpvtz')&#xA;mf = scf.RHF(mol).run()&#xA;&#xA;# C matrix stores the AO to localized orbital coefficients&#xA;C = lo.orth_ao(mf, 'nao')&#xA;orbs = C[:,mf.mo_occ&amp;gt;0] # Only get occupied orbitals&#xA;&#xA;for i in range(orbs.shape[1]):&#xA;    cubegen.orbital(mol, f'ch4_nao_mo{i+1}.cube', orbs[:,i])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Eauvis.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Eauvis.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/IRKqls.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IRKqls.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/xoWXns.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xoWXns.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/0LbSws.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0LbSws.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/MfqK2s.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MfqK2s.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4819" LastEditorUserId="5" LastEditDate="2022-01-24T22:18:31.440" LastActivityDate="2022-01-24T22:18:31.440" Title="How to visualize natural atomic orbitals from PySCF" Tags="|visualization-software|orbitals|pyscf|avogadro|" AnswerCount="0" CommentCount="5" ClosedDate="2022-09-07T03:17:47.160" ContentLicense="CC BY-SA 4.0" />
  <row Id="8600" PostTypeId="1" AcceptedAnswerId="8601" CreationDate="2022-01-24T07:12:46.980" Score="18" ViewCount="1351" Body="&lt;p&gt;Slater type orbitals (STO) are considered to be more accurate than gaussian type orbitals (GTO) for atomic and molecular QM calculations because - among other reasons - they decay with &lt;span class=&quot;math-container&quot;&gt;$e^{-\alpha r}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$r \to \infty$&lt;/span&gt;. But GTOs are more popular because they are easier to calculate with. GTOs decay with &lt;span class=&quot;math-container&quot;&gt;$e^{-\alpha r^2}$&lt;/span&gt;, so its adequate to sometimes add diffuse functions to the GTO basis set to compensate for gaussian decay behaviour.&lt;/p&gt;&#xA;&lt;p&gt;Also, exact hydrogen wavefunctions decay exponentially, so the motivation for STOs.&lt;/p&gt;&#xA;&lt;p&gt;I understand that the only boundary requirement for solving the Schrödinger equation for atoms and molecules in free space is that the wavefunction goes zero as &lt;span class=&quot;math-container&quot;&gt;$r \to \infty$&lt;/span&gt;, but there are no &lt;em&gt;a priori&lt;/em&gt; requirements for the way it decays as it does so.&lt;/p&gt;&#xA;&lt;p&gt;My question is: do we have theoretical (&lt;em&gt;ab initio&lt;/em&gt;) and/or experimental reasons to believe that all atomic and molecular wavefunctions decay like &lt;span class=&quot;math-container&quot;&gt;$e^{-\alpha r}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$r \to \infty$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4794" LastEditorUserId="5" LastEditDate="2022-01-24T17:48:00.110" LastActivityDate="2022-02-04T10:33:11.400" Title="Do we know for sure that all atomic and molecular wavefunctions decay exponentially as r goes to infinity?" Tags="|molecular-modeling|mathematical-modeling|quantum-mechanics|orbitals|atomistic-simulation|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8601" PostTypeId="2" ParentId="8600" CreationDate="2022-01-24T08:41:17.277" Score="25" Body="&lt;p&gt;I'll answer this question from the theoretical side. The exponential behavior follows simply from the Schrödinger equation. Consider the one-electron Schrödinger equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;(-\frac{1}{2}\nabla^2 + V(\mathbf{r}))\psi(\mathbf{r}) = \epsilon\psi(\mathbf{r}), \epsilon &amp;lt; 0&#xA;$$&lt;/span&gt;&#xA;At spatial points that are very far away from the nucleus, &lt;span class=&quot;math-container&quot;&gt;$V(\mathbf{r})\approx 0$&lt;/span&gt;, so that the asymptotic solution is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;-\frac{1}{2}\nabla^2\psi(\mathbf{r}) = \epsilon\psi(\mathbf{r}), \epsilon &amp;lt; 0&#xA;$$&lt;/span&gt;&#xA;This differential equation has basic solutions of the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi(\mathbf{r}) = Ce^{-\sqrt{-2\epsilon}\mathbf{k}\cdot\mathbf{r}}&#xA;$$&lt;/span&gt;&#xA;for some unit vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;. The real asymptotic behavior of &lt;span class=&quot;math-container&quot;&gt;$\psi(\mathbf{r})$&lt;/span&gt; is thus a linear combination of these basic solutions. The linear combination may bring a polynomial prefactor to the exponential, but will never alter the exponent. Thus we have not only proved the exponential behavior, but also derived the correct exponent &lt;span class=&quot;math-container&quot;&gt;$\alpha = \sqrt{-2\epsilon}$&lt;/span&gt;. For a multi-electronic, non-interacting system, the overall decay rate is governed by the slowest decaying orbital, i.e. the HOMO.&lt;/p&gt;&#xA;&lt;p&gt;Of course, the real wavefunction can only be described by a multi-electron Schrödinger equation. But we can work on the equivalent Kohn-Sham system and show that the Kohn-Sham wavefunction decays at a rate given by the Kohn-Sham HOMO energy. By Janak's theorem, the Kohn-Sham HOMO energy is just the negative of the ionization potential of the exact system. To see this, consider a huge ensemble of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; identical, non-interacting molecules. If we remove one electron from the ensemble and let the hole delocalize evenly between all the molecules, then as &lt;span class=&quot;math-container&quot;&gt;$N\to +\infty$&lt;/span&gt;, the electron removal has a negligible impact on the electron density of any molecule (and therefore the Kohn-Sham potential of each molecule). Therefore under the Kohn-Sham framework we see that removing such an electron costs an energy of &lt;span class=&quot;math-container&quot;&gt;$-\epsilon_{\mathrm{HOMO}}$&lt;/span&gt; (it does not matter whether the HOMO refers to that of the ensemble or that of a molecule, since their orbital energies are equal), since the electron is taken from an energy level whose energy is &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{\mathrm{HOMO}}$&lt;/span&gt; and the Hamiltonian is not changed in this process. On the other hand, from the perspective of the real system it is clear that the energy cost is equal to the first ionization energy of one of the molecules, &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;. Therefore we have &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{\mathrm{HOMO}} = -I$&lt;/span&gt;, which means that the Kohn-Sham wavefunction decays like (again up to a possible polynomial prefactor; the precise determination of this polynomial prefactor is a much more difficult question)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi(\mathbf{r}) = Ce^{-\sqrt{2I}\mathbf{k}\cdot\mathbf{r}}&#xA;$$&lt;/span&gt;&#xA;Although the Kohn-Sham wavefunction is fictional, its density is equal to the true multielectronic density, and in order for the true density to have the same asymptotic behavior as the Kohn-Sham density, the true wavefunction must have the same asymptotic behavior as the Kohn-Sham wavefunction. Q.E.D.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-02-04T10:33:11.400" LastActivityDate="2022-02-04T10:33:11.400" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8602" PostTypeId="1" CreationDate="2022-01-24T19:22:45.130" Score="6" ViewCount="193" Body="&lt;p&gt;Why is it recommended to set &lt;code&gt;GGA_COMPAT = .FALSE.&lt;/code&gt;  for non-colinear calculations?  Could someone explain what GGA_COMPAT does?&lt;/p&gt;&#xA;" OwnerUserId="4793" LastEditorUserId="5" LastEditDate="2022-01-24T22:19:37.183" LastActivityDate="2022-01-24T22:37:44.207" Title="What does GGA_COMPAT do in VASP and why is it recommended to set it to FALSE for non-colinear calculations?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8603" PostTypeId="2" ParentId="8602" CreationDate="2022-01-24T22:37:44.207" Score="6" Body="&lt;p&gt;&lt;code&gt;GGA_COMPAT&lt;/code&gt; is meant to restore symmetry for non-cubic cells when using gradient-corrected functionals. This is because gradient-corrected functionals might slightly break the Bravais lattice for non-cubic cells (e.g. primitive FCC and BCC latices).&lt;/p&gt;&#xA;&lt;p&gt;Setting &lt;code&gt;GGA_COMPAT = .FALSE.&lt;/code&gt; restores the full lattice symmetry for gradient-corrected functionals, by setting the gradient field and the charge density to 0  for all reciprocal lattice vectors that exceed an automatically determined (by VASP) cutoff length, before calculating the exchange correlation energy and potential.&lt;/p&gt;&#xA;&lt;p&gt;The VASP developers &lt;a href=&quot;https://www.vasp.at/wiki/index.php/GGA_COMPAT&quot; rel=&quot;noreferrer&quot;&gt;tried to explain this in the VASP Wiki&lt;/a&gt; but the article has grammatical errors which makes it difficult to follow, and the reason why they called it &lt;code&gt;GGA_COMPAT&lt;/code&gt; is not explained there, and they also didn't make it clear why the default setting for &lt;code&gt;GGA_COMPAT&lt;/code&gt; was &lt;code&gt;TRUE&lt;/code&gt; until VASP 5.2 and apparently also now, despite them strongly recommending to use &lt;code&gt;FALSE&lt;/code&gt; and prividing no reason why you would ever want to use &lt;code&gt;TRUE&lt;/code&gt;. I welcome other users to answer here if they would like to give some scenarios in which it would be preferred to use &lt;code&gt;TRUE&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One thing from that VASP Wiki page which is especially to note is that (emphasis added by me):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;setting the flag usually changes the energy only in the sub meV energy range (0.1 meV), and &lt;strong&gt;for most results it does matter little how &lt;code&gt;GGA_COMPAT&lt;/code&gt; is set&lt;/strong&gt;. The most important exception are magnetic anisotropies, for which we strongly recommend to set &lt;code&gt;GGA_COMPAT = .FALSE.&lt;/code&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-01-24T22:37:44.207" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8604" PostTypeId="2" ParentId="8592" CreationDate="2022-01-25T14:56:41.187" Score="12" Body="&lt;p&gt;&lt;strong&gt;That kind of pressure feels reasonable.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't think there's any cause for concern based on the data you have shown. Consider the following back-of-the-envelope calculation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The thermal expansion coefficient of carbon is (&lt;a href=&quot;https://www.webelements.com/carbon/physics.html&quot; rel=&quot;noreferrer&quot;&gt;according to WebElements&lt;/a&gt;) roughly 7.1 ppm/K. That's the linear (length) expansion coefficient, the volumetric expansion coefficient is approximately three times larger. Let's take &lt;span class=&quot;math-container&quot;&gt;$\alpha_V$&lt;/span&gt; = 20 ppm/K as a rough guess for your material.&lt;/li&gt;&#xA;&lt;li&gt;Assuming that the thermal expansion coefficient is constant across the entire temperature range (which is a really crude assumption), cooling your material down by 7700 K will make its volume &lt;strong&gt;shrink by 15.4%&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;li&gt;The bulk modulus of carbon is (again according to WebElements) K = 33 GPa. Since &lt;span class=&quot;math-container&quot;&gt;$K = - V \frac{dP}{dV}$&lt;/span&gt;, let's assume it's again constant during the whole quenching procedure and thus &lt;span class=&quot;math-container&quot;&gt;$\Delta P = - K \frac{\Delta V}{V}$&lt;/span&gt;. This gives us &lt;span class=&quot;math-container&quot;&gt;$\Delta P = -33 \cdot 0.154 = -5\,\mathrm{GPa}$&lt;/span&gt;, or &lt;strong&gt;-50000 bar&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Given the (in)accuracy of this estimate, it is fairly OK that your observed pressure change is just a factor of 2 off. You could make a better estimate using a real equation of state for carbon, but note also that the empirical force field will on its own likely have a limited accuracy in reproducing the true EOS.&lt;/p&gt;&#xA;" OwnerUserId="774" LastActivityDate="2022-01-25T14:56:41.187" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8605" PostTypeId="2" ParentId="8589" CreationDate="2022-01-25T15:19:15.657" Score="8" Body="&lt;p&gt;&lt;strong&gt;This is &lt;a href=&quot;https://en.wikipedia.org/wiki/Shear_thinning&quot; rel=&quot;noreferrer&quot;&gt;shear thinning&lt;/a&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This kind of non-Newtonian behaviour is not really important for simple fluids like water at macroscopic scales, but it is readily observable in simulations of small systems on short timescales.&lt;/p&gt;&#xA;&lt;p&gt;The physical reason for shear thinnning in water (at simulated timescales) is that water as a liquid has quite a complex structure where the molecules are interconnected in big hydrogen-bonded networks. These hydrogen bonds take a short while to develop (molecules have to reorient the right way to form a hydrogen bond), so the faster you shear, the less time the molecules have to grab onto their neighbors, the weaker the hydrogen bonding and thus the lower the viscosity.&lt;/p&gt;&#xA;&lt;p&gt;The same occurs in solutions of polymers and the like, because their long chains get entangled if given enough time to do so. You won't see much shear thinning in nice simple fluids made of isotropic spheres like the Lennard-Jones fluid.&lt;/p&gt;&#xA;&lt;p&gt;Apart from true shear thinning, you can also see artifacts due to inadequate thermostatting. Shearing the fluid injects a considerable amount of energy into the system. This can disturb energy equipartitioning between different degrees of freedom or make it difficult for the thermostat to hold the temperature constant. Viscosity depends a whole lot on temperature, so any temperature disturbance is going to affect the results. (This becomes a big problem when you go to excessively high shear rates.)&lt;/p&gt;&#xA;" OwnerUserId="774" LastActivityDate="2022-01-25T15:19:15.657" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8606" PostTypeId="2" ParentId="8281" CreationDate="2022-01-26T18:22:13.887" Score="5" Body="&lt;p&gt;Just to wrap up the discussion in the comments, your first image would depict an &lt;em&gt;electronic step&lt;/em&gt; or SCF iteration where a set of orbital coefficients (equivalently, the electronic density) is calculated. These steps change how electron density is distributed within the molecule. The results of an electronic step are used as guess for the next electronic step (assuming the density hasn't converged).&lt;/p&gt;&#xA;&lt;p&gt;An &lt;em&gt;ionic step&lt;/em&gt; would occur after a full cycle of SCF iterations has completed. This involves moving the nuclei/ions of the system based on the forces calculated from the converged electronic wavefunction/density. Once the nuclei/ions have been moved, you have to start a new electronic cycle to figure out where the electrons should go for the updated geometry.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-26T18:22:13.887" CommentCount="0" CommunityOwnedDate="2022-01-26T18:22:13.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="8607" PostTypeId="1" CreationDate="2022-01-27T08:30:09.343" Score="3" ViewCount="282" Body="&lt;p&gt;The peak shift for XRD of the 1T and 2H phases of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; differs by a few degrees (just below 10 degrees for 1T, 14 degrees for 2H).&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://en.wikipedia.org/wiki/Rietveld_refinement&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rietveld Refinement&lt;/a&gt;, a standard CIF file can be used for peak fitting. A CIF for the 2H phase of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; is available from the &lt;a href=&quot;http://www.crystallography.net/cod/&quot; rel=&quot;nofollow noreferrer&quot;&gt;COD database&lt;/a&gt;, but I can't seem to find the 1T phase CIF. Is this available from some other source (or am I just missing it on the COD website)?&lt;/p&gt;&#xA;" OwnerUserId="4740" LastEditorUserId="7" LastEditDate="2022-01-27T15:51:57.903" LastActivityDate="2022-01-27T22:03:56.237" Title="1T phase MoS2 CIF File" Tags="|crystallography|databases|x-ray-diffraction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8608" PostTypeId="2" ParentId="7059" CreationDate="2022-01-27T15:01:45.350" Score="6" Body="&lt;p&gt;Alot of the early pioneering in Monte Carlo (MC) moves were done initially using lattices. While I am not directly aware of places to look for benchmarks, the pioneers in the 90's for Monte Carlo moves I would say are Daan Frenkel, Thijs Vlugt, Berend Smidt, Edward Maginn and others.&lt;/p&gt;&#xA;&lt;p&gt;Professor Edward Maginn hosts the Monte Carlo code &lt;a href=&quot;https://cassandra.nd.edu/&quot; rel=&quot;noreferrer&quot;&gt;Cassandra&lt;/a&gt; from Notre Dame. Daan Frenkel and Berend Smidt wrote the textbook(Bible) &lt;a href=&quot;https://www.elsevier.com/books/understanding-molecular-simulation/frenkel/978-0-12-267351-1&quot; rel=&quot;noreferrer&quot;&gt;Understanding Molecular Simulation: From algorithms to applications&lt;/a&gt;, and they have accompanying code written in Fortran, with excerpts written by Vlugt.&lt;/p&gt;&#xA;&lt;p&gt;This would be where I would start: I would check out Prof. Maginn's software Cassandra for benchmarks, and try to find the Fortran code for Frenkel &amp;amp; Smit, or even just check Frenkel &amp;amp; Smit's textbook which is riddled with pseudocode.&lt;/p&gt;&#xA;&lt;p&gt;You can also check out &lt;a href=&quot;http://towhee.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;MCCCS Towhee&lt;/a&gt;, another well known MC simulation package, but it is notoriously difficult with its documentation.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastActivityDate="2022-01-27T15:01:45.350" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8609" PostTypeId="1" CreationDate="2022-01-27T15:34:32.600" Score="8" ViewCount="42" Body="&lt;p&gt;As I'm learning more about viscoelasticity and creep experiments, I'm trying to understand how to distinguish between the different deformation mechanisms.&#xA;In general, when a sample of viscoelastic material is being deformed - there are few regimes: elastic, anelastic, and steady-state creep.&#xA;The deformation in the anelastic and steady-state are mainly due to the motion of defects (point defects, dislocations and grain boundaries).&#xA;Hypothetically, what would be the way to know which of the defects is behind the deformation? Is there a way to distinguish between them (I know they can happen simultaneously, but one might be more dominant)&lt;/p&gt;&#xA;&lt;p&gt;(I wasn't sure if I should post this question here or in Physics)&lt;/p&gt;&#xA;" OwnerUserId="4852" LastActivityDate="2022-01-27T15:34:32.600" Title="How to distinguish between deformation mechanisms in creep experiment?" Tags="|defects|stress-strain|" AnswerCount="0" CommentCount="4" ClosedDate="2022-11-03T15:47:00.657" ContentLicense="CC BY-SA 4.0" />
  <row Id="8610" PostTypeId="2" ParentId="8607" CreationDate="2022-01-27T22:03:56.237" Score="5" Body="&lt;p&gt;(A shift of a peak by &lt;span class=&quot;math-container&quot;&gt;$\Delta2\theta \approx 4^\circ$&lt;/span&gt; in PXRD may be considered as quite a bit.)&lt;/p&gt;&#xA;&lt;p&gt;For multiple years, there is a &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/&quot; rel=&quot;noreferrer&quot;&gt;website in common&lt;/a&gt; by CCDC about the public entries in the CSD file (organic/organometallic small molecule .cif) &lt;em&gt;and&lt;/em&gt; ICSD database (inorganic .cif).  It is not as comfortable as searching  on their respective &lt;em&gt;own&lt;/em&gt; interfaces (like WebCSD/conquest for CSD) or ICSD directly, though.  It aims to help e.g., reviewing publications.  Thus, CCDC blocks you (temporarily) if they associate your IP address with «too many attempts to download .cif/unit of time».*  (&lt;em&gt;Public entries&lt;/em&gt; refers to entries where authors of these data permit their data to be retrieved.  There may be good reasons to deposit the data and e.g., await successful peer-review of the corresponding publication in a journal before such an «embargo» is lifted.)&lt;/p&gt;&#xA;&lt;p&gt;However, you may search by compound name like &lt;code&gt;molybdenum disulfide&lt;/code&gt; (&lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/Search?Compound=molybdenum%20disulfide&amp;amp;DatabaseToSearch=Published&quot; rel=&quot;noreferrer&quot;&gt;example&lt;/a&gt;) to yield .cif one may download and a bibliographic reference to the original publication.  Thus one finds models in &lt;span class=&quot;math-container&quot;&gt;$P 6_3/mmc$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$a = b \approx \pu{3.16 Å}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$c \approx \pu{12.3 Å}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha = \beta = 90^\circ$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma = 120^\circ$&lt;/span&gt; e.g., entry ICSD 49801) as well as two in &lt;span class=&quot;math-container&quot;&gt;$R3m$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$a = b \approx \pu{3.16 Å}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$c \approx \pu{18.4 Å}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha = \beta = 90^\circ$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma = 120^\circ{}$&lt;/span&gt; e.g., entry ICSD 196772).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;*) If your school isn't yet subscriber to these databases (ask e.g., groups active in crystallography/inorganic chemistry/materials science/physics/organic chemistry), get in touch with research libraries. A single FTE becomes quite affordable (compared to other databases) if you join a local «consortium» of multiple interested groups where the library manages remote access and updates for you.  Plus the benefit of the databases' infrastructure (e.g., tailored Python libraries for &lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/csd-python-api/&quot; rel=&quot;noreferrer&quot;&gt;the CSD&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2022-01-27T22:03:56.237" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8611" PostTypeId="2" ParentId="8531" CreationDate="2022-01-27T23:15:22.770" Score="5" Body="&lt;p&gt;There's now a web server that uses GFN2 and GFN-FF to calculate vibrations and visualize them, thanks to Berend Smit:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://ir.cheminfo.org&quot; rel=&quot;noreferrer&quot;&gt;https://ir.cheminfo.org&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can draw a structure or insert a SMILES, and the server will run the vibrational calculation (up to 60 atoms for GFN2 or 100 atoms for GFN-FF), and offer several visualizations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vq3LM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vq3LM.png&quot; alt=&quot;ir.cheminfo.org screenshot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;standard transmittance vs. wavenumber plot&lt;/li&gt;&#xA;&lt;li&gt;JSMol animation of the vibration&lt;/li&gt;&#xA;&lt;li&gt;table of modes, calculated intensity, and wavenumber&lt;/li&gt;&#xA;&lt;li&gt;bond depiction to connect between bonds and vibrations (e.g., the C=O bond is highly localized)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There's also a nice description of the resource and some educational discussion:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.jchemed.1c01101&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Making Molecules Vibrate: Interactive Web Environment for the Teaching of Infrared Spectroscopy&amp;quot; &lt;em&gt;J. Chem. Ed.&lt;/em&gt; &lt;strong&gt;2022&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The authors also provide the service as a Docker image to run yourself: &lt;a href=&quot;https://github.com/cheminfo-py/xtbservice&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/cheminfo-py/xtbservice&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-01-27T23:15:22.770" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8612" PostTypeId="1" AcceptedAnswerId="8614" CreationDate="2022-01-28T01:33:21.023" Score="9" ViewCount="402" Body="&lt;p&gt;After calculating the energy of a &lt;span class=&quot;math-container&quot;&gt;$\ce{CH4}$&lt;/span&gt; molecule with a 6-31G(d,p) basis set, I obtained the Gaussian/GAMESS log file and describe a part of the log file as follows.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    1  C  1  1S&#xA;    2  C  1  2S&#xA;    3  C  1  2X&#xA;    4  C  1  2Y&#xA;    5  C  1  2Z&#xA;    6  C  1  3S&#xA;    7  C  1  3X&#xA;    8  C  1  3Y&#xA;    9  C  1  3Z&#xA;   10  C  1  4XX&#xA;   11  C  1  4YY&#xA;   12  C  1  4ZZ&#xA;   13  C  1  4XY&#xA;   14  C  1  4XZ&#xA;   15  C  1  4YZ&#xA;   16  H  2  1S&#xA;   17  H  2  2S&#xA;   18  H  2  2X&#xA;   19  H  2  2Y&#xA;   20  H  2  2Z&#xA;   ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This shows the orbital types of each atom (i.e., C and H), but in 6-31G(d,p) I believe that C does not have 3S, 3X/Y/Z/etc orbitals and H does not have 2S orbital. In addition, I believe that the number of d orbitals (e.g., 4XX and 4YY) is five, but the above file has six d orbitals.&lt;/p&gt;&#xA;&lt;p&gt;It may be my lack of study, but does the 6-31G(d,p) calculation actually use more orbitals?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2022-01-28T11:17:02.850" LastActivityDate="2022-02-01T23:32:28.247" Title="The number of orbitals in Gaussian/GAMESS log file" Tags="|ab-initio-calculations|gaussian|basis-sets|orbitals|gamess|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8613" PostTypeId="2" ParentId="8612" CreationDate="2022-01-28T04:00:05.997" Score="7" Body="&lt;p&gt;Yes, a good basis set will contain virtual (unoccupied) orbitals, in addition to the orbitals that are occupied by electrons.&lt;/p&gt;&#xA;&lt;p&gt;Almost always: the larger the basis set, the more accurate the calculations (but the more computationally demanding they are).&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;When I calculated the carbon ionization energy with an aug-cc-pCV8Z basis set&lt;/a&gt;, we had 1182 spin orbitals for a single carbon atom, and not only D-type orbitals, but also F-type, G-type, H-type, I-type, K-type, and L-type orbitals.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-01-28T04:00:05.997" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8614" PostTypeId="2" ParentId="8612" CreationDate="2022-01-28T04:36:26.233" Score="8" Body="&lt;p&gt;As Nike mentioned, most basis sets produce more orbitals than the minimal set that you tend to think of for these elements. We can see how this works out for 6-31G(d,p) by looking at how the basis set is defined:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H     0&#xA;S    3   1.00&#xA;      0.1873113696D+02       0.3349460434D-01&#xA;      0.2825394365D+01       0.2347269535D+00&#xA;      0.6401216923D+00       0.8137573261D+00&#xA;S    1   1.00&#xA;      0.1612777588D+00       1.0000000&#xA;P    1   1.00&#xA;      0.1100000000D+01       1.0000000&#xA;****&#xA;C     0&#xA;S    6   1.00&#xA;      0.3047524880D+04       0.1834737132D-02&#xA;      0.4573695180D+03       0.1403732281D-01&#xA;      0.1039486850D+03       0.6884262226D-01&#xA;      0.2921015530D+02       0.2321844432D+00&#xA;      0.9286662960D+01       0.4679413484D+00&#xA;      0.3163926960D+01       0.3623119853D+00&#xA;SP   3   1.00&#xA;      0.7868272350D+01      -0.1193324198D+00       0.6899906659D-01&#xA;      0.1881288540D+01      -0.1608541517D+00       0.3164239610D+00&#xA;      0.5442492580D+00       0.1143456438D+01       0.7443082909D+00&#xA;SP   1   1.00&#xA;      0.1687144782D+00       0.1000000000D+01       0.1000000000D+01&#xA;D    1   1.00&#xA;      0.8000000000D+00       1.0000000&#xA;****&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So for &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt;, we get 3 different types of orbitals: an S orbital formed from 3 primitive Gaussians, an S orbital formed from 1 primitive, and 3 P orbitals formed from 1 primitive. For C, we have an S orbital formed from 6 primitives (meant to represent the core S orbital), 2 sets of SP orbitals (meant to represent the valence S and P orbitals), and 6 D orbitals formed from 1 primitive.&lt;/p&gt;&#xA;&lt;p&gt;The P orbital for &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; and D orbital for &lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt; (these are the (d,p) in 6-31g(d,p)) are referred to as polarization functions. These are higher angular functions added to the basis to allow for a more flexible description of the electron density, especially directional interactions like bonds.&lt;/p&gt;&#xA;&lt;p&gt;As for why there are 6 D orbitals rather than 5, this is because the Pople basis (the ones written X-YZ...G) use Cartesian functions rather than spherical ones. In the Cartesian representation, it takes 6 functions to represent the D orbitals. This discrepancy between the number of Cartesian and spherical functions continues for higher angular momentum functions as well (e.g. there are 10 Cartesian F functions, rather than the typically seen 7 spherical ones).&lt;/p&gt;&#xA;&lt;p&gt;However, as Susi noted in the comments, the Pople basis sets actually use spherical functions for F orbitals; this can be confusing to handle. Among many other reasons, this is why the Pople basis sets are mainly just of historical significance and that other, more modern basis sets should be used.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-02-01T23:32:28.247" LastActivityDate="2022-02-01T23:32:28.247" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8615" PostTypeId="1" CreationDate="2022-01-28T07:04:11.713" Score="5" ViewCount="425" Body="&lt;p&gt;I have to perform strain engineering in a material. The strain would be expansive strain and compressive strain. How do I perform those both?&lt;/p&gt;&#xA;&lt;p&gt;I am currently using the &lt;code&gt;press&lt;/code&gt; command for hydrostatic pressure which is giving me compression as it's reducing the cell parameters. How do I also include expansive strain?&#xA;Do I have to do it manually by increasing/decreasing cell parameters?&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Khandy, S. A.; Chai, J. &lt;a href=&quot;https://doi.org/10.1016/j.jallcom.2020.156615&quot; rel=&quot;nofollow noreferrer&quot;&gt;Strain engineering of electronic structure, phonon, and thermoelectric properties of p-type half-Heusler semiconductor&lt;/a&gt;. &lt;em&gt;J. Alloys Compd.&lt;/em&gt; &lt;strong&gt;2021,&lt;/strong&gt; &lt;em&gt;850,&lt;/em&gt; 156615. DOI: 10.1016/j.jallcom.2020.156615.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2022-01-29T21:15:55.080" LastActivityDate="2022-01-29T21:15:55.080" Title="How to perform Strain induced properties in Quantum ESPRESSO?" Tags="|quantum-espresso|stress-strain|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8616" PostTypeId="2" ParentId="8299" CreationDate="2022-01-28T10:23:36.467" Score="5" Body="&lt;p&gt;Yes, one can do the similar calculations with VASP.&lt;/p&gt;&#xA;&lt;p&gt;TL;DR. Check out my example &lt;a href=&quot;https://github.com/Chengcheng-Xiao/VASP2WAN90_v2_fix/tree/dev/example/example4&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There are two steps involved here, one is obtaining well localized Wannier functions and the other is using those wanner functions to calculate the stuff (here, Berry curvature).&lt;/p&gt;&#xA;&lt;p&gt;The first step is achieved by telling the DFT code to output projection coefficients (as a guiding point for constructing Wannier functions) and overlap matrices between Bloch functions at neighboring K-point.&lt;/p&gt;&#xA;&lt;p&gt;The original tutorial was written for Quantum ESPRESSO and for VASP, the same can can be achieved by writing a &lt;code&gt;wannier90.win&lt;/code&gt; file and setting the tag &lt;code&gt;LWANNIER90 = .T.&lt;/code&gt; in &lt;code&gt;INCAR&lt;/code&gt; file of a single point calculation.&lt;/p&gt;&#xA;&lt;p&gt;Then the procedure is the same as those described in the original tutorial.After obtained said objects, one need to run &lt;code&gt;wannier90.x&lt;/code&gt; to get the unitary matrices (+ other informations) stored in &lt;code&gt;.chk&lt;/code&gt; file. Finally, we can obtain the Berry curvature data using &lt;code&gt;postw90.x&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1804" LastEditorUserId="1804" LastEditDate="2022-02-06T00:01:45.867" LastActivityDate="2022-02-06T00:01:45.867" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8617" PostTypeId="1" AcceptedAnswerId="8620" CreationDate="2022-01-28T12:44:51.070" Score="7" ViewCount="377" Body="&lt;p&gt;I want to run multiple jobs on Gaussian using windows. I know it is possible to do so on Linux. But can we perform a loop in Gaussian with Windows?&lt;/p&gt;&#xA;&lt;p&gt;In my calculation, I need to use the optimized geometry of geom1.log as a starting point for geom2.gjf, but sometimes  I need to perform a second optimization on geom1.log and add keywords in the .gjf file to attend the convergence.&lt;/p&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="7" LastEditDate="2022-01-28T14:35:49.467" LastActivityDate="2022-01-28T23:08:15.933" Title="Loop calculation in Gaussian" Tags="|high-performance-computing|gaussian|windows-operating-system|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8618" PostTypeId="2" ParentId="7194" CreationDate="2022-01-28T21:42:16.910" Score="5" Body="&lt;p&gt;The most common form of the self-consistent field (SCF) calculations, which are used in DFT and Hartree-Fock, assumes that each molecular orbital is a linear combination of all the atomic orbitals (aka basis function), and that the molecular orbitals are orthogonal to each other.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi^\mathrm{MO}_\mathrm{i} = \sum_\mathrm{p} c_\mathrm{pi} \chi^\mathrm{AO}_\mathrm{p}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So you start with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; atomic orbitals, and by taking linear combinations, you get &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; orthogonal MO's. These molecular orbitals are called canonical orbitals. (Assuming there is no linear dependency in the AO basis set)&lt;/p&gt;&#xA;&lt;p&gt;As the SCF procedure assumes from the start that each MO can have contributions from all of the AO's, the concept of delocalization is built into the procedure by default.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, when you do a DFT calculation on a molecule like benzene, no other considerations are required. If there is any delocalization, it will be treated by the method.&lt;/p&gt;&#xA;&lt;p&gt;For example, have a look at the HOMO-1 orbital of butadiene (which is supposed to the lowest &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-orbital, which all of the 2p-orbitals of carbon overlapping constructively) from a B3LYP/6-31+G(2d,p) calculation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/50ed5m.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/50ed5m.png&quot; alt=&quot;butadiene lowest pi orbital&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is quite clear that the delocalization is accounted for.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As an aside, I want to add that even if you start with localized orbitals, the canonical wavefunction can be obtained by taking linear combination of the various different ways you can localize the orbitals. This is something I learnt in my quantum chemistry lectures, and the math works out, but it is difficult to have an intuitive sense of why this works. So for example you can write the structure of benzene in two Kekule forms, and it turns out that the canonical wavefunction of benzene is simply a linear combination of both - benzene exists as a superposition of the Kekule-type localized wavefunctions.&lt;/p&gt;&#xA;&lt;p&gt;There can only be one set of canonical MO's that satisfy the orthonormality condition, but there can be multiple way to localize the MO's. There are actually some exotic quantum chemistry methods (such as ALMO), which actually start with localized wavefunctions (determined for specified fragments of the system), and then builds up the total wavefunction from those fragmented localized MO's. This works quite efficiently for large systems such as water clusters, because there is no delocalization, so electron-electron interaction only happens locally.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2022-02-02T12:46:58.220" LastActivityDate="2022-02-02T12:46:58.220" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8619" PostTypeId="2" ParentId="1541" CreationDate="2022-01-28T23:06:34.127" Score="6" Body="&lt;p&gt;An interesting application of bond orders in reactive molecular dynamics simulations is the &lt;a href=&quot;https://en.wikipedia.org/wiki/ReaxFF&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF&lt;/a&gt; force field, where the MD force field parameters are optimized by &lt;em&gt;ab initio&lt;/em&gt; simulations.&lt;/p&gt;&#xA;&lt;p&gt;To quote one of the papers:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;To make practical the molecular dynamics simulation of large scale reactive chemical systems (1000s of atoms), we developed ReaxFF, a force field for reactive systems. ReaxFF uses a general relationship between bond distance and bond order on one hand and between bond order and bond energy on the other hand that leads to proper dissociation of bonds to separated atoms. Other valence terms present in the force field (angle and torsion) are defined in terms of the same bond orders so that all these terms go to zero smoothly as bonds break.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Some of the first publications are &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp004368u&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF:  A Reactive Force Field for Hydrocarbons&lt;/a&gt;, and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp709896w&quot; rel=&quot;noreferrer&quot;&gt;ReaxFF Reactive Force Field for Molecular Dynamics Simulations of Hydrocarbon Oxidation&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Since then many more applications have been developed, see &lt;a href=&quot;https://www.nature.com/articles/npjcompumats201511&quot; rel=&quot;noreferrer&quot;&gt;The ReaxFF reactive force-field: development, applications and future directions&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4794" LastActivityDate="2022-01-28T23:06:34.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8620" PostTypeId="2" ParentId="8617" CreationDate="2022-01-28T23:08:15.933" Score="5" Body="&lt;p&gt;If the geometry optimization is failing to converge fairly often, it is probably better to not try to run the calculations automatically in sequence and to instead check on the geometry before starting the excited state calculation.&lt;/p&gt;&#xA;&lt;p&gt;Having said that, there is a way to define a sequence of Gaussian jobs that I think could fit your use case. In a Gaussian input file, you can write multi jobs, separated by a &lt;code&gt;--Link1--&lt;/code&gt; &lt;a href=&quot;https://gaussian.com/input/&quot; rel=&quot;noreferrer&quot;&gt;header&lt;/a&gt;. These jobs can use information from previous steps through the check point file. So in your case, you could do something like (adding in your specific keywords and actual geometry).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=initial_geom.chk&#xA;#p opt&#xA;&#xA;Initial Geom Opt&#xA;&#xA;0 1&#xA;H 0.0 0.0 0.0&#xA;H 0.0 0.0 1.0&#xA;&#xA;--Link1--&#xA;%oldchk=initial_geom.chk&#xA;%chk=better_geom.chk&#xA;#p opt guess=read geom=check !additional keywords to improve convergence&#xA;                       !Should finish almost immediately if already converged &#xA;&#xA;Better Geometry &#xA;&#xA;0 1&#xA;&#xA;--Link1--&#xA;%oldchk=better_geom.chk&#xA;%chk=excited.chk&#xA;#p guess=read geom=check !Excited state keywords&#xA;&#xA;Excited calc&#xA;&#xA;0 1&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This should do the initial geometry optimization, then start another optimization with your keywords to ensure convergence (which should end very quickly if the calculation is already converged), and finally run an excited state calculation on this improved geometry.&lt;/p&gt;&#xA;&lt;p&gt;If you weren't actually sure that the 2nd step would converge, you could add an arbitrary number of intermediate steps in an effort to get a converged geometry. If you really wanted something that keeps trying the optimization until it is converged, I believe you would need an external shell/python/etc script to manage the Gaussian calculations, parse their output, and determine the need for additional calculations.&lt;/p&gt;&#xA;&lt;p&gt;However, as I mentioned, I think anything beyond the three step approach I described here would be a worse idea than just submitting all the geometry optimizations separately, manually addressing any issues for failed cases, and then submitting the excited state calculations.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-01-28T23:08:15.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8621" PostTypeId="2" ParentId="8615" CreationDate="2022-01-29T15:37:59.197" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Do I have to do it manually by increasing/decreasing cell parameters?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The answer is yes, you need to change the simulation box vector based on strain.&lt;/p&gt;&#xA;&lt;p&gt;You can use the following logic:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$a'=a(\epsilon+I),\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$a'$&lt;/span&gt; is the new simulation cell vector and &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is the current simulation vector. &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$6\times6$&lt;/span&gt; identity matrix and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$6\times6$&lt;/span&gt; strain matrix. In your case of expansion and compression:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon_{\text{exp}}=\begin{bmatrix}1+\delta &amp;amp; 0  &amp;amp; 0\\0 &amp;amp; 1+\delta&amp;amp;0\\0 &amp;amp; 0 &amp;amp;1+\delta \end{bmatrix},\tag{2}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon_{\text{com}}=\begin{bmatrix}1-\delta &amp;amp; 0  &amp;amp; 0\\0 &amp;amp; 1-\delta&amp;amp;0\\0 &amp;amp; 0 &amp;amp;1-\delta \end{bmatrix}.\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2022-01-29T21:14:44.723" LastActivityDate="2022-01-29T21:14:44.723" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8622" PostTypeId="1" AcceptedAnswerId="8625" CreationDate="2022-01-30T08:55:03.150" Score="6" ViewCount="310" Body="&lt;p&gt;I have seen many articles&lt;sup&gt;[1]&lt;/sup&gt; that write in the title &amp;quot;mechanical properties of ...&amp;quot;, but in the subsections of the paper, they write &amp;quot;elastic properties&amp;quot; and discuss elastic properties.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know if elastic and mechanical properties are the same, or is there any difference between them.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Yue, Q.; Kang, J.; Shao, Z.; Zhang, X.; Chang, S.; Wang, G.; Qin, S.; Li, J. Mechanical and electronic properties of monolayer MoS2 under elastic strain. &lt;em&gt;Phys. Lett. A&lt;/em&gt; &lt;strong&gt;2012,&lt;/strong&gt; &lt;em&gt;376&lt;/em&gt; (12-13), 1166–1170. &lt;a href=&quot;https://doi.org/10.1016/j.physleta.2012.02.029&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1016/j.physleta.2012.02.029&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="272" LastEditorUserId="7" LastEditDate="2022-01-31T15:53:22.040" LastActivityDate="2022-01-31T15:53:22.040" Title="What is the difference between elastic and mechanical properties of materials?" Tags="|density-functional-theory|physical-properties-of-materials|elasticity|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8623" PostTypeId="1" CreationDate="2022-01-30T23:32:35.970" Score="13" ViewCount="515" Body="&lt;p&gt;I am working on a project involving water clusters with ions in them. One of the problems that I ran into quite early on was that good forcefield parameters are not available for highly charged ions such as &lt;span class=&quot;math-container&quot;&gt;$\ce{Al^3+}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe^3+}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{La^3+}$&lt;/span&gt; (these are the three I am interested in currently).&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/gfnff.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GFN-FF&lt;/a&gt; force field claims to be a partially polarizable force field for materials, organometallics and biochemical systems. It claims to provide quantum-chemistry-level accuracy at the cost of a force field calculation. The original &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202004239&quot; rel=&quot;nofollow noreferrer&quot;&gt;publication&lt;/a&gt; seems to indicate that it can be applied to almost all types of systems. The xTB software also has semi-empirical GFN0, GFN1 and GFN2 methods, which perform QM calculation instead of being classical forcefields.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does anyone have any experience using GFN-FF or the other xTB methods for calculations on ion water interactions (or just biological systems containing ions in general)? Do they work well?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am worried that there could be problems related to treating the polarization of the water molecules by highly charged ions in GFN-FF (as it calculates the partial charges only once at the start of the calculation). I haven't found any papers that use GFN-FF for molecular dynamics as well. Obviously I could use one of the semi-empirical ones, but it would be very slow for the systems I am working on.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2022-11-03T11:10:01.403" LastActivityDate="2023-02-17T11:37:49.343" Title="Applicability of GFN-FF force field and other xTB methods for dynamics of ions in water" Tags="|molecular-dynamics|quantum-chemistry|forcefields|water|xtb|" AnswerCount="0" CommentCount="11" ClosedDate="2023-10-01T14:45:39.133" ContentLicense="CC BY-SA 4.0" />
  <row Id="8624" PostTypeId="1" AcceptedAnswerId="9628" CreationDate="2022-01-31T10:07:52.297" Score="3" ViewCount="499" Body="&lt;p&gt;I have some experience in dealing with structural, electronic, and magnetic properties of 2D materials, but I want to go further to study the elastic properties. Could you please guide me on this? which properties should be calculated and discussed?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-09-24T19:48:59.617" Title="How to start with the elastic properties of 2D materials using the VASP code?" Tags="|vasp|elasticity|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8625" PostTypeId="2" ParentId="8622" CreationDate="2022-01-31T14:00:41.623" Score="4" Body="&lt;p&gt;When we talk about mechanical properties, we generally refer to response of the material on application of external load. Apart from external load, responses can be of mixed nature, such as thermo-mechanical response. In the broader sense, mechanical properties have a very wide domain, and subsets of these domains often overlap. For example, the non-linear response of material that may be elastic or plastic in nature.&lt;/p&gt;&#xA;&lt;p&gt;Even if we focus only on elastic response, we encounter linear and non-linear behavior of material against deformation. It all depends on type of material, external stimuli, and its internal configuration. Talking about elastic properties, many research groups majorly deal with constitutive behaviour of small material domain at atomic scale. These small scale modelling results are used in higher length scale simulations to mimic the material response at the macroscopic level.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, depending upon the symmetry of the crystal, the number of independent elastic constants which defines this constitutive behavior also varies. Here in the above paper, the author is considering average elastic behaviour of two-dimensional structure on the application of small strain. The consideration of elastic constants are based on small deformation theory and material is taken as &lt;em&gt;homogeneous isotropic&lt;/em&gt; &lt;strong&gt;hookean&lt;/strong&gt; material where Young's modulus was derived from the second derivative of the strain energy. Again other properties such as in-plane stiffness and Poisson's ratio were also calculated using this same above assumption.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-01-31T14:46:41.050" LastActivityDate="2022-01-31T14:46:41.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8626" PostTypeId="1" CreationDate="2022-01-31T23:55:48.997" Score="6" ViewCount="93" Body="&lt;p&gt;I am running Monte Carlo simulations of polymers with nearest neighbor interactions only. For benchmarking purposes, I decided to run some excluded volume simulations (no overlaps) allowed on a 3D simple cubic lattice (coordination number of 6).&lt;/p&gt;&#xA;&lt;p&gt;These are the moves I implemented:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/h0qn5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/h0qn5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The problem I am seeing is that the end-to-end autocorrelation function for my single polymer is not dying down to zero. The reason I call this a problem because I am getting incorrect Flory Exponents:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle R_g^2\rangle \propto N^{2\nu}, \tag{1}$$&lt;/span&gt;&#xA;where I am getting &lt;span class=&quot;math-container&quot;&gt;$\nu = 0.8$&lt;/span&gt;, which is too high.&lt;/p&gt;&#xA;&lt;p&gt;I am running 10^7 steps with Rosenbluth sampling.&lt;/p&gt;&#xA;&lt;p&gt;E.g. If there are N possible kink jump spots, I will test each spot until there is a vacancy available. Same applies for the end rotations.&lt;/p&gt;&#xA;&lt;p&gt;What could be the cause of this? Is it simply that my moves are too local? How do I decorrelate my system faster, as N increases?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2022-02-01T00:45:25.293" LastActivityDate="2022-09-07T21:42:12.383" Title="End-to-end correlation of polymers not decorrelating" Tags="|statistical-thermodynamics|monte-carlo|polymers|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8627" PostTypeId="1" AcceptedAnswerId="8628" CreationDate="2022-02-01T15:18:12.857" Score="7" ViewCount="233" Body="&lt;p&gt;The question is pretty simple, is GGA better than LDA at predicting vibrational properties of molecules/materials ? What is the nuance and so forth.&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2022-02-01T20:29:46.883" Title="LDA vs GGA for vibrational properties?" Tags="|vibrations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8628" PostTypeId="2" ParentId="8627" CreationDate="2022-02-01T20:29:46.883" Score="7" Body="&lt;p&gt;This is a partial answer focusing on comparing phonons calculated with LDA or GGA in solids.&lt;/p&gt;&#xA;&lt;p&gt;LDA tends to overbind solids, which means that LDA equilibrium volumes tend to be smaller than experimental equilibrium volumes. By contrast, GGAs like PBE tend to underbind solids, which means that the corresponding volumes tend to be larger than experimental equilibrium volumes. As a result of these different volumes, LDA phonon frequencies tend to be higher than PBE phonon frequencies because the LDA potential is steeper. An intermediate result is typically obtained with PBEsol, a GGA tuned to accurately reproduce experimental volumes, which then leads to phonon frequencies in-between those of LDA and PBE.&lt;/p&gt;&#xA;&lt;p&gt;Overall, the volume difference is what tends to drive any differences in phonon frequencies when comparing LDA and GGAs. There is some work on using other types of functional (e.g. hybrids) and in that case effects other than volume differences can be observed to influence the predicted phonon frequencies. However, I would argue that the latter is still an open area of research, so I would recommend doing your own tests.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-02-01T20:29:46.883" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8629" PostTypeId="1" CreationDate="2022-02-01T21:33:33.233" Score="9" ViewCount="103" Body="&lt;p&gt;In order to pose the question, I reproduce an excerpt from this Physics.SE question, about the size of atoms in a Bose-Einstein condensate (BEC):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/691936/heisenbergs-uncertainty-principle-in-frames-of-reference-with-different-velocit&quot;&gt;Heisenberg's uncertainty principle in frames of reference with different velocities&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I heard this from Professor Claude Cohen-Tannoudji himself on a lecture about BECs: as the temperature of the gas decreases, the momentum of the atoms decrease, and thus the uncertainty in the momentum also decreases. Due to the uncertainty principle, the uncertainty  in the position has to increase. &lt;strong&gt;Atoms &lt;em&gt;grow bigger&lt;/em&gt; as they are cooled down&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So, in an atomic BECs the gas temperature is so low, and atoms get so large, that their atomic wavefunctions start to overlap, and begin oscillate in-phase. Thus the condensate behaves as if it was a huge single atom, their wavefunctions oscillating coherently, allowing for applications like &lt;a href=&quot;https://en.wikipedia.org/wiki/Atom_laser&quot; rel=&quot;noreferrer&quot;&gt;atom-lasers&lt;/a&gt; (see also &lt;a href=&quot;http://www.physics.otago.ac.nz/nx/jdc/bec-basics.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Now, my question here is: in which theoretical framework does the size of the wavefunction of an atom depend on temperature - or rather, on its momentum? Do we have any calculations that can reproduce the increase of the size of the atom with lowering the temperature of the gas? I had assumed, for example, that most QM calculations of atoms and molecules were effectively at zero temperature, so I'm confused how this effect is taken into account.&lt;/p&gt;&#xA;&lt;p&gt;In order to provide futher insight into the question, I quote an excerpt of &lt;a href=&quot;https://www.nature.com/articles/416211a&quot; rel=&quot;noreferrer&quot;&gt;this article&lt;/a&gt; on Nature by James Anglin and Wolfgang Ketterle:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As long as the atoms’ de Broglie wavelength &lt;span class=&quot;math-container&quot;&gt;$\lambda_{\textrm{dB}} = \hbar / (2 M k_{\textrm{B}} T)^{1/2}$&lt;/span&gt; is small compared to the spacing between atoms, one can describe their motion with classical trajectories. (&lt;span class=&quot;math-container&quot;&gt;$\lambda_{\textrm{dB}}$&lt;/span&gt; is the &lt;strong&gt;position uncertainty associated with the thermal momentum distribution&lt;/strong&gt;, and increases with decreasing temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; and atomic mass &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;.) Quantum degeneracy begins when &lt;span class=&quot;math-container&quot;&gt;$\lambda_{\textrm{dB}}$&lt;/span&gt; and the interatomic distance become comparable. The atomic wave packets overlap, and the gas starts to become a ‘quantum soup’ of indistinguishable particles. &lt;em&gt;(emphasis mine)&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="4794" LastEditorUserId="7" LastEditDate="2022-02-03T03:14:32.003" LastActivityDate="2022-02-03T04:11:22.987" Title="In which theoretical framework does the size of an atom depend on the temperature of the gas (Bose-Einstein condensates)" Tags="|wavefunctions|temperature|atomistic-simulation|atomic-physics|quantum-size-effects|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8630" PostTypeId="2" ParentId="8612" CreationDate="2022-02-01T22:47:13.250" Score="4" Body="&lt;p&gt;I should complement Nike and Tyberius' answers by the simple statement that e.g. hydrogen only consists of a single S function for the non-interacting atom. When the atomic symmetry is lifted, you get more contributions.&lt;/p&gt;&#xA;&lt;p&gt;For instance, even though the H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; ground state consists of a doubly occupied &lt;span class=&quot;math-container&quot;&gt;$1\sigma^2$&lt;/span&gt; orbital in Hartree-Fock and density functional theory, the expansion of this molecular orbital in terms of atomic orbitals on the two nuclei consists of not just the &lt;span class=&quot;math-container&quot;&gt;$Y_0^0$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-type spherical harmonic of the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt; ground state of hydrogen, but also&#xA;of the &lt;span class=&quot;math-container&quot;&gt;$Y_1^0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_2^0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_3^0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Y_4^0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\dots$&lt;/span&gt; spherical harmonics which are provided by &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\dots$&lt;/span&gt; functions.&lt;/p&gt;&#xA;&lt;p&gt;In addition, you need several radial functions per angular momentum. The additional &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; functions are known as &amp;quot;breathing&amp;quot; functions, since they enable the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt; function in the atom to expand or contract, while the higher-angular-momentum functions are indeed known as polarization functions.&lt;/p&gt;&#xA;&lt;p&gt;If you go to post-Hartree-Fock level of theory, you also need basis functions that are used to describe excited electronic configurations. These are called correlating functions.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-02-01T22:47:13.250" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8631" PostTypeId="2" ParentId="8584" CreationDate="2022-02-01T23:15:12.590" Score="4" Body="&lt;p&gt;Amending KobeGote's answer above, computing the density is in fact quite simple.&lt;/p&gt;&#xA;&lt;p&gt;The molecular orbitals (MOs) are expanded in the basis set as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \psi_i^\sigma({\bf r}) = \sum_\alpha C^\sigma_{\alpha i} \chi_\alpha({\bf r}), \tag{1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\chi_i$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$i^{\textrm{th}}$&lt;/span&gt; basis function and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}^\sigma$&lt;/span&gt; is the matrix of MO coefficients for spin &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;. (Note that the MOs are stored by columns, and the number of MOs can be different from the number of basis functions: &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}^\sigma$&lt;/span&gt; is typically not a square matrix.)&lt;/p&gt;&#xA;&lt;p&gt;The spin-&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; electron density is,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n^\sigma({\bf r}) = \sum_{i \text{ occupied}} |\psi_i^\sigma({\bf r})|^2,\tag{2}$$&lt;/span&gt;&#xA;and the total electron density is simply,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n({\bf r}) = \sum_\sigma n^\sigma({\bf r}).\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Evaluating the electron density can be done in two ways: either by expanding the square,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n^\sigma({\bf r}) = \sum_{i \alpha \beta} C^\sigma_{\alpha i} C^\sigma_{\beta i} \chi_\alpha({\bf r}) \chi_\beta({\bf r}) \equiv \sum_{\alpha \beta} P^\sigma_{\alpha \beta} \chi_\alpha({\bf r}) \chi_\beta({\bf r}) \tag{4}$$&lt;/span&gt;&#xA;where&#xA;&lt;span class=&quot;math-container&quot;&gt;$$P^\sigma_{\alpha \beta} = \sum_i C^\sigma_{\alpha i} C^\sigma_{\beta i},\tag{5} $$&lt;/span&gt; is the density matrix, or just by first computing the values of the occupied MOs and then squaring them and summing them together. If the basis set is large compared to the number of occupied orbitals (or one is interested in the density of only a single orbital), the latter approach is much more efficient.&lt;/p&gt;&#xA;&lt;p&gt;Note that the density expansion is in the product basis &lt;span class=&quot;math-container&quot;&gt;$\chi_\alpha \chi_\beta$&lt;/span&gt; which is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;1)&lt;/strong&gt; different from the orbital basis &lt;span class=&quot;math-container&quot;&gt;$\chi_\alpha$&lt;/span&gt; and,&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;2)&lt;/strong&gt;  pathologically linearly dependent. Due to the linear dependency, one can build a compact set of auxiliary basis functions &lt;span class=&quot;math-container&quot;&gt;$\chi_A$&lt;/span&gt; in which the density can be expanded accurately as&#xA;&lt;span class=&quot;math-container&quot;&gt;$n^\sigma({\bf r}) = \sum_A c^\sigma_A \chi_A({\bf r})$&lt;/span&gt;; this is the idea of the density-fitting (DF) approach which has been used to great success in quantum chemistry for several decades. I have recently proposed an approach for automatic formation of auxiliary basis sets for DF calculations in &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.1c00607&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 17, 6886 (2021)&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-02-02T17:37:13.250" LastActivityDate="2022-02-02T17:37:13.250" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8632" PostTypeId="1" AcceptedAnswerId="8646" CreationDate="2022-02-03T00:35:18.390" Score="5" ViewCount="829" Body="&lt;p&gt;How do I convert  a POSCAR-format-like file to a XSF file (visualized by &lt;a href=&quot;http://www.xcrysden.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;XCrySDen&lt;/a&gt;)?&lt;/p&gt;&#xA;&lt;p&gt;I'm looking for a step by step tutorial on the process and what tools/programs are needed.&lt;/p&gt;&#xA;" OwnerUserId="4793" LastEditorUserId="7" LastEditDate="2022-02-05T00:19:08.570" LastActivityDate="2022-02-05T16:28:07.353" Title="Convert a POSCAR-format-like file to a XSF file?" Tags="|density-functional-theory|vasp|computational-chemistry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8633" PostTypeId="2" ParentId="8629" CreationDate="2022-02-03T04:11:22.987" Score="4" Body="&lt;p&gt;In calculations of the electronic energy/wavefunction, temperature typically is not taken in to account (besides cases of orbital occupation smearing, though this is used more as a computational trick than a physical description of the system). So these calculations are effectively zero temperature and often more like no temperature, since temperature is a statistical quantity that isn't well defined when dealing with a single atom or molecule.&lt;/p&gt;&#xA;&lt;p&gt;So if these simulations are essentially zero temperature, why don't we see this change in atom size you describe? The key is that these are &lt;em&gt;electronic&lt;/em&gt; calculations. In principle, the nuclei should also be treated as quantum mechanically and the wavefunction of the atom/molecule should involve both nuclear and electronic degrees of freedom. In practice, these sorts of simulations are much more challenging and thus much less common (though not nonexistent, see usage of nuclear-electronic orbitals, NEOs). In typical electronic structure calculations, nuclei are treated as fixed point charges and under normal chemical conditions this is a very good approximation.&lt;/p&gt;&#xA;&lt;p&gt;However, as you saw in the Anglin/Ketterle paper, the wave like behavior of nuclei can become apparent at very low temperatures (milli or even micro kelvin), allowing the formation of phases like the Bose-Einstein condensate where the nuclear wavefunctions of neighboring atoms start to overlap.&lt;/p&gt;&#xA;&lt;p&gt;I'm not nearly experienced enough with this area to recommend software that could do this simulation, but whatever program would have to describe the nuclei in the system quantum mechanically and incorporate effects of temperature using something like the thermostats seen in classical MD simulations. I expect programs that can do this aren't available off the shelf and are specially built to simulate specific systems rather than being general purpose simulation platforms.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-02-03T04:11:22.987" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8634" PostTypeId="1" CreationDate="2022-02-03T16:54:27.847" Score="7" ViewCount="72" Body="&lt;p&gt;I am non-specialist who is new to the field of computational physics/biology. I have a few questions about the relevance and effectiveness of Markov State Models (MSM) in capturing the dynamics towards equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;It is my understanding that based upon recordings of the trajectories of some observed value of a system, it may be possible to fit a markov state model to it by discretising the trajectories into states and then estimating the transition matrix. However, these recorded trajectories are not necessarily of the equilibrium configuration, rather in my case consist of some transient change in the parameter followed by equilibration towards a time-independent mean value. If a markov state model is constructed from such data, will it also to some extend capture these relaxation characteristics?&lt;/p&gt;&#xA;&lt;p&gt;An example of such a recorded trajectory is shown below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KbnAa.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KbnAa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, the trajectory consists of some initial transient phenomena that slowly converges onto a mean. Furthermore, the step like changes at fixed time-interval suggests a MSM might be reasonable.  I would like the Markov state model to capture the characteristics of this transient phenomena. By this I mean, if the MSM is simulated with similar initial conditions to the data then the relaxation behaviour (eg time-scales) should be similar.&lt;/p&gt;&#xA;" OwnerUserId="4889" LastActivityDate="2022-02-03T16:54:27.847" Title="Can Markov State Models based on short-term non-equilibrium datasets also capture the dynamics towards equilibrium?" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|markovianity|" AnswerCount="0" CommentCount="3" ClosedDate="2022-11-03T15:47:37.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="8635" PostTypeId="1" AcceptedAnswerId="8641" CreationDate="2022-02-03T16:55:08.937" Score="19" ViewCount="1957" Body="&lt;p&gt;I've been mostly using ab initio methods as a routine calculation tool, so even though I know some things from the theoretical side, I still have mostly hands-on experience. One of the things that I know is if your molecular geometry does not make sense, then SCF crashes. One example would be if I use angstroms instead of bohrs in the geometry definition (who hasn't been there!). I assume that if my molecular geometry makes little chemical sense, SCF would also crash.&lt;/p&gt;&#xA;&lt;p&gt;What would be some physical/numerical reasons for these failures?&lt;/p&gt;&#xA;" OwnerDisplayName="user4626" LastEditorUserId="5" LastEditDate="2022-02-04T22:58:50.480" LastActivityDate="2022-02-15T06:27:06.033" Title="What are the physical reasons if the SCF doesn't converge?" Tags="|density-functional-theory|molecular-modeling|self-consistent-field|hartree-fock|numerical-convergence|" AnswerCount="4" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8636" PostTypeId="1" CreationDate="2022-02-04T00:54:44.453" Score="17" ViewCount="335" Body="&lt;p&gt;Often empirical electrostatic models or molecular force fields approximate the molecular polarizability using an additive model, e.g., for N atoms:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{mol} = \sum_i^N \alpha_{atom_i}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This assumes polarizability is additive — and for many molecules, that assumption works okay. It also assumes isotropic polarizabilities. For atoms, that's a reasonable assumption because they're roughly spherical.&lt;/p&gt;&#xA;&lt;p&gt;But molecules aren't spherical, so all the elements of the polarizability tensor matter (e.g., the anisotropy).&lt;/p&gt;&#xA;&lt;p&gt;For a given &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8332/30&quot;&gt;frame of reference / coordinate system&lt;/a&gt;, how do you calculate an approximate &lt;span class=&quot;math-container&quot;&gt;$3 \times 3$&lt;/span&gt; polarizability tensor from the additive &lt;span class=&quot;math-container&quot;&gt;$\alpha_{atom_i}$&lt;/span&gt; components?&lt;/p&gt;&#xA;&lt;p&gt;It seems like there should be an easy way (e.g., you calculate the rank-1 dipole moment from the charges and the atomic coordinates) but I haven't found a ready reference.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-01-05T18:39:07.877" Title="Constructing a molecular polarizability tensor from sets of atomic polarizabilities?" Tags="|forcefields|electrostatic|polarizability|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8637" PostTypeId="1" AcceptedAnswerId="8759" CreationDate="2022-02-04T01:10:50.577" Score="7" ViewCount="595" Body="&lt;p&gt;I am trying to find the d-band center of pdos data generated using quantum espresso 6.8.&#xA;I'm aware that this maybe calculated by the formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{\int_{-\infty}^\infty E \cdot \textrm{pdos}(E)dE}{\int_{-\infty}^\infty \textrm{pdos}(E)dE} \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried XMgrace as suggested &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2014-September/030667.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; but was not able to do it. Is there a way to use this formula using MatLab, or any other software to integrate the pdos curve (maybe a piece of code)? Any help would be appreciated :)&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2022-03-02T19:21:34.233" LastActivityDate="2022-03-03T04:24:26.530" Title="How to calculate the d-band from pdos data?" Tags="|quantum-espresso|density-of-states|matlab|d-band|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8638" PostTypeId="2" ParentId="8635" CreationDate="2022-02-04T07:01:17.557" Score="4" Body="&lt;p&gt;There are countless reasons why the SCF might be difficult to converge. Some physically interpretable scenarios include a system that is not appropriately charge-balanced, closely overlapping atoms, or charge sloshing. As noted &lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.033305&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, &amp;quot;charge sloshing generally refers to the long-wavelength oscillations of the output charge density due to some small changes in the input density during the iterations, and results in a slow convergence or even divergence.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="206" LastActivityDate="2022-02-04T07:01:17.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8639" PostTypeId="1" CreationDate="2022-02-04T08:38:25.557" Score="7" ViewCount="175" Body="&lt;p&gt;As from the title, I want to do NEB-TS for chemical reactions in the liquid phase, and use the information to calculate reaction rates/kinetic rates.&lt;/p&gt;&#xA;&lt;p&gt;I know that the NEB-TS is possible in the liquid phase using CPCM, for example. I'm not so clear on heterogeneous catalysis, for surface reactions. Logically, heterogeneous catalysis means I have components reacting, which adsorbs to the surface, and desorbs to form a product. Almost all microkinetic modelling I see mentions typically gas phase or solution phase, yet none of them mention the presence of a catalyst in the solution phase for the chemical reaction modelling. Do I have to physically model the surface in the quantum software?&lt;/p&gt;&#xA;" OwnerUserId="4892" LastEditorUserId="7" LastEditDate="2022-02-04T15:49:56.393" LastActivityDate="2022-02-04T15:49:56.393" Title="Is It possible to do microkinetic modelling for liquid phase reactions, in the presence of a catalyst?" Tags="|computational-chemistry|orca|reaction-mechanism|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8640" PostTypeId="2" ParentId="8639" CreationDate="2022-02-04T10:52:43.063" Score="9" Body="&lt;p&gt;Usually if you have a heterogeneous catalyst, the best way to model it is to use a periodic slab (a thin plate that is periodic in two dimensions). A cluster model (i.e. approximating the catalyst as a nanoparticle) may also work. For heterogeneous catalysis in solution, the free space surrounding the catalyst can be described by e.g. CPCM, as usual.&lt;/p&gt;&#xA;&lt;p&gt;I noticed that you have added the tag &amp;quot;orca&amp;quot; to your question. If you are specifically interested in studying surface catalysis with ORCA, then using a cluster model is the only choice. You may search for &amp;quot;CRYSTAL-QMMM&amp;quot; in the ORCA manual for details on how to perform such a calculation. Briefly, you take a suitably sized cluster from the surface of the catalyst (say ~100 atoms), and use this as the QM region. The catalyst atoms in immediate vicinity of the QM region are described by embedding potentials, and catalyst atoms further away are described by MM point charges. Then you can perform NEB-TS or essentially whatever calculation as usual. For example you can optimize the adsorbed structure by placing the adsorbent on the QM part of the surface (make sure that it does not get too near to any MM atom, otherwise the result may be inaccurate), and doing a geometry optimization where all MM atoms and the atoms described by embedding potentials are fixed.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-02-04T10:52:43.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8641" PostTypeId="2" ParentId="8635" CreationDate="2022-02-04T11:45:32.747" Score="15" Body="&lt;p&gt;I have written a section in the &lt;a href=&quot;https://bdf-manual.readthedocs.io/zh_CN/latest/User%20Guide.html#scfconvproblems&quot; rel=&quot;noreferrer&quot;&gt;BDF user manual&lt;/a&gt; on this issue. It is in Chinese but I'll roughly translate the key parts to English as below.&lt;/p&gt;&#xA;&lt;p&gt;Common reasons for the SCF procedure to fail to converge include:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A too small HOMO-LUMO gap, which causes repetitive changes of the frontier orbital occupation numbers. Imagine two orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt;, where the former is occupied and the latter is unoccupied at the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-th SCF iteration. If the orbital energies of &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt; do not differ much, then it may well be that at the &lt;span class=&quot;math-container&quot;&gt;$N+1$&lt;/span&gt;-th SCF iteration, the orbital energy of &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; becomes higher than that of &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt;, resulting in the electron(s) on &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; transferring to the orbital &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt;. However, this will inevitably cause a large change in the density matrix, and therefore the Fock matrix. Thus chances are that if one diagonalizes the new Fock matrix, one finds that &lt;span class=&quot;math-container&quot;&gt;$\psi_1$&lt;/span&gt; is again lower in energy than &lt;span class=&quot;math-container&quot;&gt;$\psi_2$&lt;/span&gt;. In this unfortunate scenario, the orbital occupation number oscillates between two patterns, which prevents convergence. Typical signatures of this scenario include an oscillating SCF energy (with an amplitude of &lt;span class=&quot;math-container&quot;&gt;$10^{-4} \sim 1$&lt;/span&gt; Hartree), and a clearly wrong occupation pattern printed at the end of the SCF calculation.&lt;/li&gt;&#xA;&lt;li&gt;The HOMO-LUMO gap is relatively small but not excessively small, so that the occupation numbers of the orbitals do not change, but the orbital shape oscillates (this is what the physicists call &amp;quot;charge sloshing&amp;quot;). (The polarizability of a system is inversely proportional to the HOMO-LUMO gap, and if the polarizability is high, a small error in the Kohn-Sham potential may result in a large distortion of the electronic density. When the HOMO-LUMO gap shrinks beyond a certain point, the distorted density may give a Kohn-Sham potential that is even more erroneous than the original one, which marks the onset of divergence.) Typical signatures include an oscillating SCF energy with a slightly smaller magnitude, and a qualitatively correct occupation pattern.&lt;/li&gt;&#xA;&lt;li&gt;Numerical noise caused by a too small grid or a too loose integral cutoff threshold. Typical signatures include an oscillating SCF energy with a very small magnitude (&lt;span class=&quot;math-container&quot;&gt;$&amp;lt;10^{-4}$&lt;/span&gt; Hartree), and a qualitatively correct occupation pattern.&lt;/li&gt;&#xA;&lt;li&gt;The basis set (orbital basis set, auxiliary basis sets, etc.) is close to linearly dependent, or the grid is so small that the projection of the basis set on the grid is close to linearly dependent (this problem does not exist for plane wave basis sets). Typical signatures include a wildly oscillating or unrealistically low SCF energy (error &amp;gt; 1 Hartree), and a qualitatively wrong occupation pattern.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Note that a wrong geometry or a wrong charge merely increase the likelihood that problems 1, 2 and 4 arise, and are themselves not separate reasons for SCF non-convergence. In particular, too long bonds make problems 1 and 2 more likely, while too short bonds tend to invoke problem 4. Many people tend to ignore or underestimate the importance of problems 3 and 4, such that they play around hopelessly with damp and level shift (or in the physicists' language, different mixing schemes), which actually only work for problems 1 and 2, when the true cause of the non-convergence is actually numerical noise or basis set linear dependence. (For the sake of this particular question, however, one may argue that only problems 1 and 2 are &amp;quot;physical reasons&amp;quot;, since problems 3 and 4 are purely numerical artifacts and are not due to any physical property of the system being studied.)&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-02-04T11:45:32.747" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8642" PostTypeId="1" CreationDate="2022-02-04T15:02:08.953" Score="3" ViewCount="65" Body="&lt;p&gt;I couldn’t find any software. Does anyone have any free software suggestions. I tried to do it with vesta but couldn’t figure out and for polytypes other than the 2H there are not any sources. Thanks a lot!&lt;/p&gt;&#xA;" OwnerUserId="4894" LastActivityDate="2022-02-04T15:02:08.953" Title="How to build [11-20] and [10-10] surfaces of hexagonal 2H, 1T and 1T’ monolayers?" Tags="|density-functional-theory|surfaces|" AnswerCount="0" CommentCount="4" ClosedDate="2022-03-02T20:05:37.737" ContentLicense="CC BY-SA 4.0" />
  <row Id="8643" PostTypeId="2" ParentId="7146" CreationDate="2022-02-04T15:12:51.463" Score="11" Body="&lt;p&gt;I was able to replicate your output on a Macbook Pro M1. Therefore, at the moment running &lt;code&gt;./configure&lt;/code&gt; followed by &lt;code&gt;make all&lt;/code&gt; is not an option because the script will try to compile using &lt;code&gt;clang&lt;/code&gt;. However, I was able to compile Quantum Espresso 7.0 using &lt;code&gt;cmake&lt;/code&gt;, &lt;code&gt;gcc-11&lt;/code&gt;, and &lt;code&gt;open-mpi&lt;/code&gt; with the &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/wikis/Developers/CMake-build-system&quot; rel=&quot;nofollow noreferrer&quot;&gt;instructions&lt;/a&gt; from the official QE GitLab.&lt;/p&gt;&#xA;&lt;p&gt;Since Google does not return any other discussion (besides this thread) on how to install QE with the new M1 Apple Silicon, here are the steps I followed. Hopefully this will avoid a headache to someone else.&lt;/p&gt;&#xA;&lt;h1&gt;Compile Quantum Espresso on M1&lt;/h1&gt;&#xA;&lt;p&gt;Install &lt;code&gt;gcc&lt;/code&gt;, &lt;code&gt;cmake&lt;/code&gt;, and &lt;code&gt;open-mpi&lt;/code&gt; via &lt;code&gt;brew&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ brew install gcc open-mpi cmake&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Download the QE release 7.0 &lt;a href=&quot;https://github.com/QEF/q-e/releases&quot; rel=&quot;nofollow noreferrer&quot;&gt;from here&lt;/a&gt; and unzip the source code. From terminal, &lt;code&gt;cd&lt;/code&gt; into the unzipped folder that contains the downloaded QE source code and create an empty folder (e.g. /build/). &lt;code&gt;cd&lt;/code&gt; into this folder, configure via &lt;code&gt;cmake&lt;/code&gt; with the options &lt;code&gt;mpicc&lt;/code&gt; and &lt;code&gt;mpif90&lt;/code&gt;, and compile. The commands are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ mkdir build&#xA;$ cd build&#xA;$ cmake -DCMAKE_C_COMPILER=mpicc -DCMAKE_Fortran_COMPILER=mpif90 ..&#xA;$ make -jN all&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;N&lt;/code&gt; is the number of processors to be used for compilation. Running &lt;code&gt;make all&lt;/code&gt; works just fine too. When compilation is over, the executables should be located in /build/bin/, and can be run with the usual&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ mpirun -np N path/to/build/bin -in input_file.in &amp;gt; output_file.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;N&lt;/code&gt; is again the number of processors to be used for the calculation.&lt;/p&gt;&#xA;" OwnerUserId="4864" LastEditorUserId="4864" LastEditDate="2022-02-07T11:04:02.630" LastActivityDate="2022-02-07T11:04:02.630" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8644" PostTypeId="2" ParentId="8635" CreationDate="2022-02-04T18:57:16.290" Score="8" Body="&lt;p&gt;There are several good answers. One concern that's not currently mentioned in the other answers is when the initial guess is poor.&lt;/p&gt;&#xA;&lt;p&gt;While most programs have several methods to perform an initial guess, and these are usually fairly good, they can also fail.&lt;/p&gt;&#xA;&lt;p&gt;As a simple example, let's consider the superposition of atomic potentials:&#xA;&lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Theory Comput.&lt;/em&gt; &lt;strong&gt;2019&lt;/strong&gt;, 15, 3, 1593–1604&lt;/a&gt;. It works well and it's conceptually easy to understand both why it should work and cases when it can fail.&lt;/p&gt;&#xA;&lt;p&gt;If I want to converge this calculation of benzene, I'd start with the atom potentials from six carbon atoms and six hydrogen atoms:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MPxxpm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MPxxpm.png&quot; alt=&quot;benzene molecule&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Not surprisingly, this is a fairly good initial guess and the SCF can converge.&lt;/p&gt;&#xA;&lt;p&gt;This one is harder to converge. I stretched all the bonds by &lt;span class=&quot;math-container&quot;&gt;$3\times$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0Ov5Jm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0Ov5Jm.png&quot; alt=&quot;stretched benzene&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this case, how do I treat the atoms? Are they individual non-interacting atoms? No, the bonds are stretched a lot, but there's still some shared electron density.&lt;/p&gt;&#xA;&lt;p&gt;I can probably still converge this &amp;quot;stretched benzene,&amp;quot; but it's harder because the initial guess is often tailored for covalently bonded carbon.&lt;/p&gt;&#xA;&lt;p&gt;Problems with poor initial guess can happen more for unusual charge or spin states, or with metal centers. For the latter, consider that small differences in geometry could lead to different spin states, etc.&lt;/p&gt;&#xA;&lt;p&gt;(Some programs I will not use for inorganic or organometallic calculations because the initial guess are routinely poor -- although most programs continue to improve.)&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-02-04T18:57:16.290" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8645" PostTypeId="1" AcceptedAnswerId="8827" CreationDate="2022-02-05T09:23:36.883" Score="6" ViewCount="2905" Body="&lt;p&gt;Does somebody know how to resolve the error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Inv3 failed in PCMMkU.&#xA; Error termination via Lnk1e in /g16/g16/l502.exe at Sat Jan 15 19:18:03 2022.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt=modredundant freq m062x/6-31g(d) scrf=(smd,solvent=n-Hexane)&#xA;geom=connectivity&#xA;&#xA;[...]&#xA;&#xA;surface=ses&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried all the surfaces present in Gaussian (WdV, SAS and SES) but all of them returns the same error&lt;/p&gt;&#xA;&lt;p&gt;This is the output of the log&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Atomic radii for non-electrostatic terms: SMD-CDS.&#xA; ------------------------------------------------------------------------------&#xA; Nuclear repulsion after PCM non-electrostatic terms =     3242.6649455991 Hartrees.&#xA; One-electron integrals computed using PRISM.&#xA; NBasis=   514 RedAO= T EigKep=  4.41D-04  NBF=   514&#xA; NBsUse=   514 1.00D-06 EigRej= -1.00D+00 NBFU=   514&#xA; Lowest energy guess from the checkpoint file:  &amp;quot;chkname.chk&amp;quot;&#xA; B after Tr=     0.000000    0.000000    0.000000&#xA;         Rot=    1.000000   -0.000006   -0.000001   -0.000002 Ang=  -0.00 deg.&#xA; B after Tr=     0.000000    0.000000    0.000000&#xA;         Rot=    1.000000    0.000015    0.000003    0.000005 Ang=   0.00 deg.&#xA; Requested convergence on RMS density matrix=1.00D-08 within 128 cycles.&#xA; Requested convergence on MAX density matrix=1.00D-06.&#xA; Requested convergence on             energy=1.00D-06.&#xA; No special actions if energy rises.&#xA; Inv3:  Mode=1 IEnd=    47664588.&#xA; Iteration    1 A*A^-1 deviation from unit magnitude is 1.82D-12 for   2700.&#xA; [...]&#xA; Iteration   10 A*A^-1 deviation from orthogonality  is 2.26D-09 for   2700   1612.&#xA; Iteration   10 A^-1*A deviation from unit magnitude is 2.39D-09 for   2700.&#xA; Iteration   10 A^-1*A deviation from orthogonality  is 3.47D-09 for   2700   1676.&#xA; Inv3 failed in PCMMkU.&#xA; Error termination via Lnk1e in /g16/g16/l502.exe at Sat Jan 15.&#xA; Job cpu time:       8 days  6 hours  4 minutes  3.1 seconds.&#xA; Elapsed time:       0 days  3 hours 25 minutes 24.9 seconds.&#xA; File lengths (MBytes):  RWF=    688 Int=      0 D2E=      0 Chk=     28 Scr=      1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Another important this is that &lt;strong&gt;only&lt;/strong&gt; with M06-2x functional throws this error.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="4895" LastEditDate="2022-02-06T10:11:09.357" LastActivityDate="2022-03-21T17:59:52.287" Title="Gaussian Inv3 Error" Tags="|gaussian|implicit-solvent|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8646" PostTypeId="2" ParentId="8632" CreationDate="2022-02-05T10:35:44.667" Score="5" Body="&lt;p&gt;There are couple of tools which can quickly convert POSCAR to xsf format.&lt;/p&gt;&#xA;&lt;h2&gt;Atomsk&lt;/h2&gt;&#xA;&lt;p&gt;The basic syntax to convert POSCAR to xsf:&#xA;&lt;code&gt;atomsk POSCAR xsf&lt;/code&gt;&lt;/p&gt;&#xA;&lt;h2&gt;VASPKIT&lt;/h2&gt;&#xA;&lt;p&gt;Inside the structure editor there is the option&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;406) Convert POSCAR/CONTCAR to Other Formats&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The xsf format is one of the available options.&lt;/p&gt;&#xA;&lt;h2&gt;ASE&lt;/h2&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase.io import vasp&#xA;from ase.io import xsf&#xA;a=vasp.read_vasp('POSCAR')&#xA;xsf.write_xsf('new.xsf',a)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above Python script should convert a POSCAR file to &lt;code&gt;new.xsf&lt;/code&gt;&#xA;You can also look at another &lt;a href=&quot;https://github.com/QijingZheng/VaspVib2XSF&quot; rel=&quot;nofollow noreferrer&quot;&gt;python script&lt;/a&gt; which can convert other types of VASP files.&lt;/p&gt;&#xA;&lt;h2&gt;Custom Bash script&lt;/h2&gt;&#xA;&lt;p&gt;This &lt;a href=&quot;https://github.com/houzf/poscar2xsf&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub repo&lt;/a&gt; made by user houzf has a bash script to do this conversion.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-02-05T16:28:07.353" LastActivityDate="2022-02-05T16:28:07.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8647" PostTypeId="1" AcceptedAnswerId="8658" CreationDate="2022-02-05T16:37:37.033" Score="6" ViewCount="198" Body="&lt;p&gt;BoltzTraP code is giving errors in Quantum espresso of indentation and then Typerror: 'Float' object can not be interpreted as an integer.&#xA;What should I do to run this properly? What should I update or change? Maybe environment of the system is not set, But how to do that?&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2022-02-06T05:27:02.247" LastActivityDate="2022-02-07T23:33:19.043" Title="BoltzTraP script works with which python version?" Tags="|quantum-espresso|python|boltztrap|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8648" PostTypeId="1" CreationDate="2022-02-05T18:07:54.637" Score="6" ViewCount="58" Body="&lt;p&gt;Is it possible to simulate the intercalation of hydrogen nanobubbles into 2D layered materials using first principles calculations such as Density Functional Theory? Would this require a multi-scale modeling approach?&lt;/p&gt;&#xA;" OwnerUserId="4270" LastActivityDate="2022-02-09T18:34:09.230" Title="Is it possible to simulate the intercalation of hydrogen nanobubbles?" Tags="|density-functional-theory|molecular-dynamics|molecular-modeling|nanostructures|dehydrogenation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8649" PostTypeId="1" AcceptedAnswerId="8653" CreationDate="2022-02-05T18:14:12.923" Score="6" ViewCount="1738" Body="&lt;p&gt;I tried to generate a density surface (the one from red to blue) for Clothianidin, but GaussView 6 gives me errors.&#xA;I am using GaussView 6.0 without Gaussian installed on the same machine. Gaussian16 is installed on a server, where I can optimize my structure or generate cubes.&lt;/p&gt;&#xA;&lt;p&gt;To make it short:&#xA;What files e.g. only optimization or frequency do I need to use for cubegen?&#xA;Do I need &lt;code&gt;cubegen Density=SCF&lt;/code&gt; and &lt;code&gt;cubegen Potential=SCF&lt;/code&gt;?&#xA;What else do I need?&lt;/p&gt;&#xA;&lt;h2&gt;My Attempt(s)&lt;/h2&gt;&#xA;&lt;p&gt;So what I did was to optimize my structure and generate a fchk file using formcheck e.g. &lt;code&gt;formchk -2 Clothianidin_opt2.chk&lt;/code&gt;. I also tried formcheck -3 which ended with the same results.&#xA;Then I generated a cubefile using &lt;code&gt;cubegen 1 Density=SCF Clothianidin_opt2.fchk Clothianidin_opt2.cube 80 h&lt;/code&gt; which resulted in this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;  Clothianidin_aug-cc-pvTZ Rotamer1 Density=SCF  Electron density from&#xA;&amp;gt; Total SCF Density    23  -14.508446   -9.185611   -8.060497    1   108&#xA;&amp;gt; 0.299772    0.000000    0.000000    70    0.000000    0.299772    0.000000    67    0.000000    0.000000    0.299772    17   17.000000    9.411010   -0.663572    0.080443&#xA;&amp;gt;     6    6.000000    6.208134   -0.939150    0.357091&#xA;&amp;gt;     7    7.000000    4.714953   -1.379204   -1.492821&#xA;&amp;gt;     6    6.000000    2.271291   -1.496183   -0.658306&#xA;&amp;gt;     6    6.000000    1.905644   -1.138093    1.850851    16   16.000000    4.789064   -0.613814    3.284518&#xA;&amp;gt;     6    6.000000   -0.527227   -1.167258    3.303661&#xA;&amp;gt;     7    7.000000   -2.715471   -1.279566    1.698451&#xA;&amp;gt;     6    6.000000   -3.701916    0.716798    0.488475&#xA;&amp;gt;     7    7.000000   -5.898175    0.857682   -0.699938&#xA;&amp;gt;     7    7.000000   -7.493805   -1.150643   -0.668691&#xA;&amp;gt;     8    8.000000   -6.873423   -3.221607    0.238729&#xA;&amp;gt;     8    8.000000   -9.537711   -0.789805   -1.617011&#xA;&amp;gt;     7    7.000000   -2.349769    2.873389    0.479663&#xA;&amp;gt;     1    1.000000   -0.490259    2.708699    0.792811&#xA;&amp;gt;     6    6.000000   -3.201984    5.101774   -0.861255&#xA;&amp;gt;     1    1.000000   -3.310255    4.779762   -2.885485&#xA;&amp;gt;     1    1.000000   -5.063000    5.637655   -0.204045&#xA;&amp;gt;     1    1.000000   -1.880202    6.615397   -0.473743&#xA;&amp;gt;     1    1.000000   -3.836257   -2.821282    1.639883&#xA;&amp;gt;     1    1.000000   -0.589188   -2.808413    4.534685&#xA;&amp;gt;     1    1.000000   -0.638050    0.488941    4.524813&#xA;&amp;gt;     1    1.000000    0.780564   -1.861533   -1.991145&#xA;&amp;gt;   6.19673E-11  8.83004E-11  1.23586E-10  1.69934E-10  2.29631E-10  3.05069E-10&#xA;&amp;gt;   3.98654E-10  5.12710E-10  6.49378E-10  8.10526E-10  9.97653E-10  1.21180E-09&#xA;&amp;gt;   1.45346E-09  1.72240E-09  2.01751E-09  2.33654E-09  2.67583E-09  3.03002E-09&#xA;&amp;gt;   3.39182E-09  3.75190E-09  4.09899E-09  4.42026E-09  4.70199E-09  4.93048E-09&#xA;&amp;gt;   5.09323E-09  5.18010E-09  5.18441E-09  5.10381E-09  4.94065E-09  4.70197E-09&#xA;&amp;gt;   4.39892E-09  4.04581E-09  3.65884E-09  3.25473E-09  2.84941E-09  2.45690E-09&#xA;&amp;gt;   2.08855E-09  1.75259E-09  1.45411E-09  1.19523E-09  9.75599E-10  7.92931E-10&#xA;&amp;gt;   6.43632E-10  5.23354E-10  4.27493E-10  3.51563E-10  2.91469E-10  2.43659E-10&#xA;&amp;gt;   2.05198E-10  1.73763E-10  1.47592E-10  1.25405E-10  1.06307E-10  8.96951E-11&#xA;&amp;gt;   7.51744E-11  6.24857E-11  5.14501E-11  4.19301E-11  3.38038E-11  2.69509E-11&#xA;&amp;gt;   2.12473E-11  1.65642E-11  1.27715E-11  9.74160E-12  7.35311E-12  5.49453E-12&#xA;&amp;gt;   4.06627E-12 ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does this makes sense having density that small e.g. E-11 ?&lt;/p&gt;&#xA;&lt;p&gt;Anyway back to GaussView I opened the fchk file, clicked on Results/Surfaces/Contours... loaded the cube file above via cube actions, clicked on surface actions and new mapped surface, used type ESP with density matrix SCF and gained the warning:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Surface map failed! Executing Gaussian cubegen job&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Giving me this:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/fpN7d.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fpN7d.png&quot; alt=&quot;density cube&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Maybe this makes sense, as I don´t have Gaussian installed on this machine. So I generated another cube using &lt;code&gt;cubegen 1 Potential=SCF Clothianidin_opt2.fchk Clothianidin_opt2b.cube 80 h&lt;/code&gt; which resulted in this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;  Clothianidin_aug-cc-pvTZ Rotamer1 Potential=SCF  Electrostatic&#xA;&amp;gt; potential from Total SCF Density    23  -14.508446   -9.185611  &#xA;&amp;gt; -8.060497    1   108    0.299772    0.000000    0.000000    70    0.000000    0.299772    0.000000    67    0.000000    0.000000    0.299772    17   17.000000    9.411010   -0.663572    0.080443&#xA;&amp;gt;     6    6.000000    6.208134   -0.939150    0.357091&#xA;&amp;gt;     7    7.000000    4.714953   -1.379204   -1.492821&#xA;&amp;gt;     6    6.000000    2.271291   -1.496183   -0.658306&#xA;&amp;gt;     6    6.000000    1.905644   -1.138093    1.850851    16   16.000000    4.789064   -0.613814    3.284518&#xA;&amp;gt;     6    6.000000   -0.527227   -1.167258    3.303661&#xA;&amp;gt;     7    7.000000   -2.715471   -1.279566    1.698451&#xA;&amp;gt;     6    6.000000   -3.701916    0.716798    0.488475&#xA;&amp;gt;     7    7.000000   -5.898175    0.857682   -0.699938&#xA;&amp;gt;     7    7.000000   -7.493805   -1.150643   -0.668691&#xA;&amp;gt;     8    8.000000   -6.873423   -3.221607    0.238729&#xA;&amp;gt;     8    8.000000   -9.537711   -0.789805   -1.617011&#xA;&amp;gt;     7    7.000000   -2.349769    2.873389    0.479663&#xA;&amp;gt;     1    1.000000   -0.490259    2.708699    0.792811&#xA;&amp;gt;     6    6.000000   -3.201984    5.101774   -0.861255&#xA;&amp;gt;     1    1.000000   -3.310255    4.779762   -2.885485&#xA;&amp;gt;     1    1.000000   -5.063000    5.637655   -0.204045&#xA;&amp;gt;     1    1.000000   -1.880202    6.615397   -0.473743&#xA;&amp;gt;     1    1.000000   -3.836257   -2.821282    1.639883&#xA;&amp;gt;     1    1.000000   -0.589188   -2.808413    4.534685&#xA;&amp;gt;     1    1.000000   -0.638050    0.488941    4.524813&#xA;&amp;gt;     1    1.000000    0.780564   -1.861533   -1.991145  -1.06018E-02 -1.08792E-02 -1.11586E-02 -1.14393E-02 -1.17201E-02 -1.19998E-02  -1.22773E-02 -1.25511E-02 -1.28196E-02 -1.30811E-02 -1.33340E-02 -1.35761E-02  -1.38057E-02 -1.40206E-02 -1.42187E-02 -1.43979E-02 -1.45561E-02 -1.46913E-02  -1.48016E-02 -1.48852E-02 -1.49406E-02 -1.49664E-02 -1.49615E-02 -1.49252E-02  -1.48570E-02 -1.47568E-02 -1.46249E-02 -1.44619E-02 -1.42688E-02 -1.40468E-02  -1.37975E-02 -1.35228E-02 -1.32247E-02 -1.29054E-02 -1.25673E-02 -1.22130E-02  -1.18448E-02 -1.14654E-02 -1.10770E-02 -1.06823E-02 -1.02833E-02 -9.88236E-03  -9.48137E-03 -9.08220E-03 -8.68652E-03 -8.29583E-03 -7.91145E-03 -7.53453E-03  -7.16607E-03 -6.80689E-03 -6.45767E-03 -6.11895E-03 -5.79116E-03 -5.47460E-03  -5.16946E-03 -4.87585E-03 -4.59380E-03 -4.32327E-03 -4.06415E-03 -3.81627E-03  -3.57945E-03 -3.35343E-03 -3.13795E-03 -2.93273E-03 -2.73743E-03 -2.55175E-03  -2.37535E-03 ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Loaded this cube to surfaces and was able to click on electrostatical potential / surface actions and new mapped surface / use an existing cube, select electron density, pressed ok and gained the warning:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Surface build failed!  Reading cube file Writing Grid Data Reading&#xA;Grid Point Line Number 10215 No data to plot. IsoValue may be out of range.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I played with the isovalues and always got the same message.&lt;/p&gt;&#xA;&lt;p&gt;Then I tried to use cubegen density=SCF with the freq=raman file of the optimized structure resulting in this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;  Clothianidin_aug-cc-pvTZ Rotamer1 Density=SCF  Electron density from&#xA;&amp;gt; Total SCF Density    23  -14.720430   -9.389071   -9.369187    1   107&#xA;&amp;gt; 0.302641    0.000000    0.000000    71    0.000000    0.302641    0.000000    67    0.000000    0.000000    0.302641    17   17.000000    9.246225    0.463788   -1.228247&#xA;&amp;gt;     6    6.000000    6.098476   -0.120440   -0.826692&#xA;&amp;gt;     7    7.000000    4.468003   -0.079914   -2.611440&#xA;&amp;gt;     6    6.000000    2.117989   -0.628869   -1.685338&#xA;&amp;gt;     6    6.000000    1.962729   -1.087829    0.829228    16   16.000000    4.934572   -0.817273    2.148065&#xA;&amp;gt;     6    6.000000   -0.325160   -1.742793    2.367719&#xA;&amp;gt;     7    7.000000   -2.640963   -1.518183    0.966174&#xA;&amp;gt;     6    6.000000   -3.828287    0.674504    0.513435&#xA;&amp;gt;     7    7.000000   -6.126859    1.010551   -0.413585&#xA;&amp;gt;     7    7.000000   -7.613589   -1.022699   -0.899286&#xA;&amp;gt;     8    8.000000   -6.814014   -3.220296   -0.730685&#xA;&amp;gt;     8    8.000000   -9.749694   -0.540506   -1.540856&#xA;&amp;gt;     7    7.000000   -2.588956    2.823436    1.083883&#xA;&amp;gt;     1    1.000000   -0.703004    2.708938    1.198058&#xA;&amp;gt;     6    6.000000   -3.665831    5.286456    0.570168&#xA;&amp;gt;     1    1.000000   -3.940101    5.595358   -1.440374&#xA;&amp;gt;     1    1.000000   -5.483984    5.454605    1.491321&#xA;&amp;gt;     1    1.000000   -2.389744    6.701318    1.317225&#xA;&amp;gt;     1    1.000000   -3.686129   -3.045921    0.507781&#xA;&amp;gt;     1    1.000000   -0.196125   -3.682799    3.025270&#xA;&amp;gt;     1    1.000000   -0.406044   -0.555342    4.049952&#xA;&amp;gt;     1    1.000000    0.532873   -0.676284   -2.957095&#xA;&amp;gt;   8.65666E-12  1.19103E-11  1.60910E-11  2.13384E-11  2.77799E-11  3.55358E-11&#xA;&amp;gt;   4.47422E-11  5.55998E-11  6.84525E-11  8.38973E-11  1.02912E-10  1.26981E-10&#xA;&amp;gt;   1.58181E-10  1.99184E-10  2.53147E-10  3.23428E-10  4.13162E-10  5.24687E-10&#xA;&amp;gt;   6.58923E-10  8.14781E-10  9.88751E-10  1.17477E-09  1.36449E-09  1.54787E-09&#xA;&amp;gt;   1.71421E-09  1.85331E-09  1.95667E-09  2.01854E-09  2.03656E-09  2.01193E-09&#xA;&amp;gt;   1.94910E-09  1.85500E-09  1.73801E-09  1.60684E-09  1.46951E-09  1.33263E-09&#xA;&amp;gt;   1.20097E-09  1.07742E-09  9.63253E-10  8.58505E-10  7.62493E-10  6.74248E-10&#xA;&amp;gt;   5.92858E-10  5.17660E-10  4.48295E-10  3.84672E-10  3.26856E-10  2.74956E-10&#xA;&amp;gt;   2.29016E-10  1.88955E-10  1.54538E-10  1.25389E-10  1.01018E-10  8.08750E-11&#xA;&amp;gt;   6.43859E-11  5.09952E-11  4.01908E-11  3.15191E-11  2.45908E-11  1.90788E-11&#xA;&amp;gt;   1.47128E-11  1.12713E-11  8.57358E-12  6.47230E-12  4.84729E-12  3.60048E-12&#xA;&amp;gt;   2.65197E-12 ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Loaded this cube to surfaces, which gave me a second but different electron density:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/41bzO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/41bzO.png&quot; alt=&quot;Surfaces 3 cubes loaded&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then I was able to click on (the Raman) electron density / surface actions and new mapped surface / use an existing cube, select (the first optimized) electron density, pressed ok and gained finally no errors resulting in this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ns9Oy.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ns9Oy.png&quot; alt=&quot;electron density of clo&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Well, I was expecting a bit more red, especially there are oxygens and nitrogens in that molecule. So I changed the values of minus and plus 1.981e-2 to e-5 and everything in between, changing the colors of the surface but still not as expected.&lt;/p&gt;&#xA;&lt;p&gt;Do you have a hint for me?&lt;/p&gt;&#xA;" OwnerUserId="3826" LastEditorUserId="7" LastEditDate="2022-02-06T18:28:04.743" LastActivityDate="2022-10-07T03:04:14.377" Title="How to generate a 3D electron density surface from fchk file using GaussView 6 without Gaussian" Tags="|gaussian|surfaces|electron-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8650" PostTypeId="2" ParentId="4974" CreationDate="2022-02-05T23:26:12.227" Score="4" Body="&lt;p&gt;This is a somewhat handwaving answer but I think it gets the main point across:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;We should start by pointing out that the two components of your eigenstates represent the wave function amplitudes on the A/B sublattices of graphene. If you would like to plot the eigenstates in real space, besides a dependency on &lt;span class=&quot;math-container&quot;&gt;$(k_x,k_y)$&lt;/span&gt; there will also be a dependence on the lattice vector &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; but let's forget about that for the moment as it is not required for the discussion.&lt;/li&gt;&#xA;&lt;li&gt;In perfect graphene, the two sublattices are symmetric. In the absence of spontaneous symmetry breaking, the electronic density corresponding to your eigenstates (=observable) will therefore be as well. This holds for all energies.&lt;/li&gt;&#xA;&lt;li&gt;As explained in equation (20) of &lt;a href=&quot;https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/3/67057/files/2018/09/graphene_tight-binding_model-1ny95f1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;your source&lt;/a&gt;, the onsite potential &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; you're introducing is applied with positive sign on sublattice A and with negative sign on sublattice B, breaking sublattice symmetry. For example, for &lt;span class=&quot;math-container&quot;&gt;$M&amp;gt;0$&lt;/span&gt;, the lowest-energy states in the spectrum will now have more weight on sublattice B than on sublattice A, while the highest-energy states in the spectrum will have more weight on sublattice A.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2022-02-05T23:33:12.070" LastActivityDate="2022-02-05T23:33:12.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8651" PostTypeId="1" AcceptedAnswerId="8657" CreationDate="2022-02-06T02:01:01.630" Score="9" ViewCount="102" Body="&lt;p&gt;After my previous question (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8274/how-can-i-find-the-parameters-in-a-basis-set&quot;&gt;here&lt;/a&gt;), I'm now studying the orbitals actually used in Gaussian through calculating them myself using Basis Set Exchange data. However, I found that some orbital exponents of s-orbital are too large and correspondingly their normalization terms become too large. As a result, the scale of s-orbital and other orbitals (e.g., p- and d-orbitals) is very different.&lt;/p&gt;&#xA;&lt;p&gt;For example, the following figure shows the orbital shapes on O-H bond of H2O molecule (note that the direction of spherical harmonic is along O-H bond, that is, O-H is the x-axis).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/S6sMI.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S6sMI.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Of course, each primitive Gaussian function is normalized (e.g., six primitives for O_1s) so that the integral is one. Actually, Basis Set Exchange provides the following orbital exponent and contraction coefficient values for the primitive functions as follows.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SHELL TYPE PRIMITIVE        EXPONENT          CONTRACTION COEFFICIENT(S)&#xA;O     0&#xA;S    6   1.00&#xA;      0.5484671660D+04       0.1831074430D-02&#xA;      0.8252349460D+03       0.1395017220D-01&#xA;      0.1880469580D+03       0.6844507810D-01&#xA;      0.5296450000D+02       0.2327143360D+00&#xA;      0.1689757040D+02       0.4701928980D+00&#xA;      0.5799635340D+01       0.3585208530D+00&#xA;SP   3   1.00&#xA;      0.1553961625D+02      -0.1107775495D+00       0.7087426823D-01&#xA;      0.3599933586D+01      -0.1480262627D+00       0.3397528391D+00&#xA;      0.1013761750D+01       0.1130767015D+01       0.7271585773D+00&#xA;SP   1   1.00&#xA;      0.2700058226D+00       0.1000000000D+01       0.1000000000D+01&#xA;D    1   1.00&#xA;      0.8000000000D+00       1.0000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Comparing p- and d-orbitals, the extreme value of s-orbital near O atom seems strange to me. Is this because the orbital exponent is too large (e.g., 0.5484671660D+04 and 0.8252349460D+03)? Or is this because multiple primitive Gaussian functions with large exponents actually represent a real Slater function? (Or this may be just a mistake of my implementation.)&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2022-02-06T02:16:23.203" LastActivityDate="2022-02-07T15:34:06.303" Title="Too large value of s-orbital in near nucleus" Tags="|gaussian|orbitals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8652" PostTypeId="2" ParentId="4361" CreationDate="2022-02-06T04:26:35.033" Score="3" Body="&lt;p&gt;As per request from some interested readers, I'm leaving a summary of what we ended up concluding and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.inorgchem.1c01890&quot; rel=&quot;nofollow noreferrer&quot;&gt;publishing&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In our study, &amp;quot;A0&amp;quot; is the cluster of Zr and O atoms in the metal-organic framework named PCN-224, and &amp;quot;B&amp;quot; is one of the two drug molecules (nalidixic acid &amp;quot;NDX&amp;quot; or ofloxacin &amp;quot;OFL&amp;quot;) that we're trying to bind to the Zr-cluster. The experiment is done with water as the solvent, though the solvent was acetic acid in earlier stages of the synthesis of PCN-224.&lt;/p&gt;&#xA;&lt;p&gt;The Zr atoms in the cluster has some &amp;quot;exposed&amp;quot; sites that allow coordinate bonding with other molecules. In water, these sites are usually occupied by H2O...OH (&amp;quot;A1&amp;quot;), together making &amp;quot;A&amp;quot;. When pitted against B, A1 is supposed to detach from A0 before allowing B to bind to A0, forming &amp;quot;C&amp;quot;. As stated in my original question, removing A1 requires energy, which is supplied thermally from the experimental setup and is observed to further proceed to the formation of C. So we expected the DFT calculation to show C having lower energy than A, but got the opposite result.&lt;/p&gt;&#xA;&lt;p&gt;We then asked ourselves whether the acetate molecules (conjugate base of acetic acid) from the earlier stages of the experiment still remain attached to the Zr-cluster. When the calculation was redone with A1 set to acetate, the energy to remove A1 from A turned out to be smaller and gave C an energy lower than A. So the whole process was energetically explained.&lt;/p&gt;&#xA;&lt;p&gt;PS. Though not stated in the paper, changing &lt;code&gt;PBE-D3(BJ)/Def2SVP&lt;/code&gt; to &lt;code&gt;M06L-D3/Def2TZVPP&lt;/code&gt; didn't change our result.&lt;/p&gt;&#xA;" OwnerUserId="1363" LastEditorUserId="1363" LastEditDate="2022-02-06T04:33:09.720" LastActivityDate="2022-02-06T04:33:09.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8653" PostTypeId="2" ParentId="8649" CreationDate="2022-02-06T13:43:36.443" Score="8" Body="&lt;p&gt;&lt;strong&gt;Finally found the solution:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;After optimizing the structure I needed to generate an electron density cube like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cubegen 1 Density=SCF Clothianidin_opt2.fchk Clothianidin_opt2_dens.cube 80 h&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I calculated the Electrostatic potential using the density of SCF like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cubegen 1 Potential=SCF Clothianidin_opt2.fchk Clothianidin_opt2_pot.cube 80 h&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After this was done I loaded the fchk file of the optimized structure (in my case Clothianidin_opt2.fchk) into GaussView, clicked on Results/Surfaces/Contours... loaded both cube files above via cube actions, selected &amp;quot;Electron density from Total SCF Density&amp;quot;, clicked on surface actions and Use an existing cube, selected the only cube available, which was the &amp;quot;Electrostatic potential from total SCF Density&amp;quot; and confirmed with ok.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/berIX.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/berIX.png&quot; alt=&quot;select surfaces&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now this gave me the right surface, where I only needed to adjust the neg and pos values for coloring:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hiXov.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hiXov.png&quot; alt=&quot;MEP of Clo&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finished!&lt;/p&gt;&#xA;" OwnerUserId="3826" LastActivityDate="2022-02-06T13:43:36.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8654" PostTypeId="1" CreationDate="2022-02-06T19:17:19.943" Score="1" ViewCount="48" Body="&lt;p&gt;From the perspective of physics, everything is made of atoms, ions, electrons, etc. Since we know the basic interaction between elementary particles, it might be possible to design customized materials or catalysts. But apparently, the real world is more complicated than just adding different interactions together, in condensed matter physics, it is well known that there are new patterns emerging as scaling up, for example, the quasiparticles and superconductor.&lt;br&gt;&#xA;My questions are:&lt;br&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;What is the current view of designing customized materials or catalysts based on elementary laws of physics?&lt;/li&gt;&#xA;&lt;li&gt;From the perspective of ab initio calculation, maybe if we have a powerful supercomputer, we could use Numerical analysis to simulate the real material from the elementary law of physics of each atom. Currently, there is some research about using multi-scale modeling, which introduces some approximation at each level, but I don't see any research of designing materials with multi-scale modeling, is it useful on the subject of material design?&lt;/li&gt;&#xA;&lt;li&gt;I see a lot of research focusing on building a database of materials and trying to use machine learning techniques to find new patterns. Is this a hopeful way to deal with our dilemma?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-02-06T19:17:19.943" Title="What prevents us from designing material or catalysts to meet the custom requirements?" Tags="|quantum-chemistry|condensed-matter|materials-design|catalysis|" AnswerCount="0" CommentCount="5" ClosedDate="2022-02-07T02:08:07.937" ContentLicense="CC BY-SA 4.0" />
  <row Id="8655" PostTypeId="1" CreationDate="2022-02-05T06:59:23.327" Score="9" ViewCount="75" Body="&lt;p&gt;I’m a medicinal chemistry undergraduate student who is preparing his dissertation. My idea would be to create a classifier that can distinguish anticancer drugs as active or inactive and distinguish those active in three classes, describing the molecules as a graph. My supervisor suggested me to use the &lt;a href=&quot;https://en.wikipedia.org/wiki/Random_forest&quot; rel=&quot;noreferrer&quot;&gt;random forest&lt;/a&gt; classifier, and to do this I need to convert my graph into a vector trying to keep as many characteristics as possible.&lt;/p&gt;&#xA;&lt;p&gt;I start from a molecular graph dataset like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-python prettyprint-override&quot;&gt;&lt;code&gt;Data(x=[9, 9], edge_index=[2, 18], edge_attr=[18, 2], y=[0], smiles='COC(=O)C=CN1CC1')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;x&lt;/code&gt;, &lt;code&gt;edge_index&lt;/code&gt; and &lt;code&gt;edge_attr&lt;/code&gt; are a &lt;a href=&quot;https://pytorch.org/docs/stable/tensors.html&quot; rel=&quot;noreferrer&quot;&gt;torch tensor&lt;/a&gt;, and &lt;code&gt;y&lt;/code&gt; is the label (&lt;code&gt;0&lt;/code&gt; is inactive, &lt;code&gt;1&lt;/code&gt; is activity of class one, &lt;code&gt;2&lt;/code&gt; is activity of class two, …). To run a random forest classifier I think I must convert them into a vector like a &lt;code&gt;np.array&lt;/code&gt;, but I have no idea how to do it. Has anyone had experience on this task?&lt;/p&gt;&#xA;" OwnerUserId="4898" OwnerDisplayName="Gianmarco Luchetti " LastActivityDate="2022-02-07T02:15:37.973" Title="Graph Classification via Random Forest" Tags="|cheminformatics|machine-learning|" AnswerCount="0" CommentCount="7" ClosedDate="2022-09-03T02:26:28.597" ContentLicense="CC BY-SA 4.0" />
  <row Id="8656" PostTypeId="2" ParentId="7116" CreationDate="2022-02-07T13:39:58.183" Score="3" Body="&lt;p&gt;Your initial question is quite broad, and there are many sub-questions that DFT calculations may or may not be able to answer. For example, DFT is useful for studying trends in reaction kinetics vs. reactivity of materials. There are many examples of this in literature.&lt;/p&gt;&#xA;&lt;p&gt;For example, trends in calculated surface reactivity across metal phosphides correlated with observed HER kinetics: &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2015/ee/c5ee02179k&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2015/ee/c5ee02179k&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is harder to be confident in getting &amp;quot;reasonable energetics&amp;quot;, as you put it, for a particular adsorption thermochemistry. Trends and differences in adsorption thermochemistry have often been found to be insightful, as in the linked study.&#xA;This is a bit of a broad answer to a broad question.&lt;/p&gt;&#xA;" OwnerUserId="1109" LastActivityDate="2022-02-07T13:39:58.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8657" PostTypeId="2" ParentId="8651" CreationDate="2022-02-07T15:34:06.303" Score="7" Body="&lt;p&gt;Individual basis functions do not have to be physical. Only the superposition of basis functions is used to represent atomic or molecular orbitals. Several kinds of atomic basis functions can be used, as I have discussed in a recent open access review paper: &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25968 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The only Gaussian basis functions that &lt;em&gt;do&lt;/em&gt; have physical content are natural orbital basis sets, which represent components of the correlated electron density. Such basis sets are always generally contracted, i.e. each primitive basis function contributes to all contractions.&lt;/p&gt;&#xA;&lt;p&gt;In contrast, segmented basis sets, such as the Pople sets, split the orbital description into pieces. They do not represent atomic orbitals any more.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-02-07T15:34:06.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8658" PostTypeId="2" ParentId="8647" CreationDate="2022-02-07T23:33:19.043" Score="5" Body="&lt;p&gt;To summarize the discussion from the comments/chat, the errors you are seeing are likely due trying to run BoltzTraP using Python3.9 when it is a Python2 program. I imagine some of these errors can be resolved simply by running this program with Python2.7.&lt;/p&gt;&#xA;&lt;p&gt;However, neither Python2 nor BoltzTraP are actively developed. &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2&quot; rel=&quot;noreferrer&quot;&gt;BoltzTraP2&lt;/a&gt; is a more up to date Python module that works with Python3.5+. If you want to take advantage of or request potential bug fixes and new features, it would probably be best to switch to the newer version of this program.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-02-07T23:33:19.043" CommentCount="0" CommunityOwnedDate="2022-02-07T23:33:19.043" ContentLicense="CC BY-SA 4.0" />
  <row Id="8661" PostTypeId="1" CreationDate="2022-02-08T10:03:07.547" Score="9" ViewCount="601" Body="&lt;p&gt;I have worked with the SIESTA code last 2 years. Recently, I faced some errors &lt;code&gt;Error in Cholesky factorisation in cdiag&lt;/code&gt; during graphene-BC3 heterostructure optimisation. I checked the SIESTA mailing list and tried to perform the calculation with a more accurate bond length and angle. Still, I am facing the same problem.&lt;/p&gt;&#xA;&lt;p&gt;It would be of great help if you could suggest where I am doing wrong and how I can overcome this problem.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JTBlD.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JTBlD.png&quot; alt=&quot;Output displaying cholesky error&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4917" LastEditorUserId="7" LastEditDate="2022-02-08T15:20:19.150" LastActivityDate="2023-12-13T13:41:25.737" Title="How to resolve &quot;Error in Cholesky factorisation in cdiag&quot; in SIESTA?" Tags="|molecular-modeling|siesta|heterostructures|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8662" PostTypeId="2" ParentId="8332" CreationDate="2022-02-08T15:13:52.883" Score="4" Body="&lt;p&gt;As Susi already mentioned, rotating a matrix is different from rotating a vector. While a vector can rotated using &lt;span class=&quot;math-container&quot;&gt;$Rv$&lt;/span&gt; , a matrix requires you to do &lt;span class=&quot;math-container&quot;&gt;$RMR^\dagger$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;With the Kabsch algorithm, its also important to consider which points you are passing in as &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, since it solves for the optimal rotation of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; and since it allows for scaling and translating the two transformations the &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; transformation will not necessarily be the reverse transformation.&lt;/p&gt;&#xA;&lt;p&gt;You also have a slight deviation from the typical notation in your code. You write &lt;code&gt;R = U @ S @ VT&lt;/code&gt;, but the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kabsch_algorithm&quot; rel=&quot;nofollow noreferrer&quot;&gt;optimal rotation&lt;/a&gt; is usually written &lt;code&gt;R = V @ S @ U.T&lt;/code&gt;, which is the transpose of what you have. This isn't an issue as long as you are consistent, but if you are using formulas related to this matrix from the literature, you will have to account for this transpose to make them agree.&lt;/p&gt;&#xA;&lt;h3&gt;Modified code&lt;/h3&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np    &#xA;    &#xA;def kabsch_umeyama(A, B):    &#xA;    assert A.shape == B.shape    &#xA;    n, m = A.shape    &#xA;    &#xA;    EA = np.mean(A, axis=0)    &#xA;    EB = np.mean(B, axis=0)    &#xA;    VarA = np.mean(np.linalg.norm(A - EA, axis=1) ** 2) #Variation of reference CoM and points    &#xA;    &#xA;    H = ((A - EA).T @ (B - EB))                      #Calculation of covariance matrix    &#xA;    U, D, VT = np.linalg.svd(H)                         #Singular value decomposition    &#xA;    d = np.sign(np.linalg.det(U.T) * np.linalg.det(VT.T))    &#xA;    S = np.diag([1] * (m - 1) + [d])    &#xA;        &#xA;    R = VT.T @ S @ U                                      #R= optimal rotation matrix    &#xA;    &#xA;    c = VarA / np.trace(np.diag(D) @ S)                 #c=Scale factor    &#xA;    t = EA - c * R @ EB    &#xA;    &#xA;    return R, c, t    &#xA;    &#xA;P=np.array([[ 0.     ,     0.6012398 , -1.35383976],    &#xA; [ 0.       ,  -0.59301814, -1.55209021],    &#xA; [ 0.9354225 ,  1.17427624 ,-1.26515132],    &#xA; [-0.9354225 ,  1.17427624 ,-1.26515132]])    &#xA;    &#xA;Q=np.array([[ 0.        , -0.60200476,  1.55228866],    &#xA;       [ 0.        ,  0.59238638,  1.35511328],    &#xA;       [ 0.        , -1.00937982,  2.57524635],    &#xA;       [ 0.        , -1.32002906,  0.71694997]])    &#xA;&#xA;R,c,t=kabsch_umeyama(Q,P)&#xA;print(R)&#xA;&#xA;Q_pol=np.array([[22.17406111, -0.76701797, -0.        ],&#xA;       [-0.76701797, 17.61697616, -0.        ],&#xA;       [-0.        , -0.        , 12.91504335]])&#xA;&#xA;print(R@Q_pol@R.T)&#xA;print(c,t)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Result&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;R=[[-0.98709715  0.16007156  0.00403816]&#xA; [ 0.02172461  0.15886771 -0.98706083]&#xA; [-0.1586419  -0.97423721 -0.16029536]]&#xA;R@Q_pol@R.T=[[ 2.22995315e+01  3.86328068e-02 -1.47789384e-03]&#xA; [ 3.86328068e-02  1.30327906e+01 -7.24086379e-01]&#xA; [-1.47789384e-03 -7.24086379e-01  1.73737585e+01]]&#xA;c=0.2500901704406381 &#xA;t=[-0.02221427 -0.94365544  1.63897257]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-02-08T15:13:52.883" CommentCount="3" CommunityOwnedDate="2022-02-08T15:13:52.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="8663" PostTypeId="1" CreationDate="2022-02-09T01:13:15.710" Score="11" ViewCount="159" Body="&lt;p&gt;Many BZ integrals of interest are related to the spectral function&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G(\omega) = \int_{BZ}\frac{F(\mathbf{k})d\mathbf{k}}{\omega - \omega(\mathbf{k}) + i\eta} \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\omega(\mathbf{k})$&lt;/span&gt; are the eigenvalues, &lt;span class=&quot;math-container&quot;&gt;$F(\mathbf{k})$&lt;/span&gt; some matrix elements. It is shown that the imaginary part of &lt;span class=&quot;math-container&quot;&gt;$G(\omega)$&lt;/span&gt; is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Im(G) = -\pi \int d\mathbf{k} F(\mathbf{k}) \delta(\omega - \omega(\mathbf{k})) \tag{2}&#xA;$$&lt;/span&gt;&#xA;In practice, the &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; function can be replaced by some broadening functions (gaussian, lorentzian) or using the  &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0022-3719/12/15/008&quot; rel=&quot;noreferrer&quot;&gt;tetrahedron method&lt;/a&gt;. The real part can then be obtained by Kramers-Kronig transformation of the imaginary part. Now, I would like to evaluate&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G^\prime(\omega) = \int_{BZ}\frac{F(\mathbf{k})d\mathbf{k}}{(\omega - \omega(\mathbf{k}) + i\eta)^2} \tag{3}&#xA;$$&lt;/span&gt;&#xA;I'm wondering if the imaginary part of &lt;span class=&quot;math-container&quot;&gt;$G^\prime$&lt;/span&gt; can be expressed as &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; function, then I can evaluate it with similar recipe?&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2022-02-15T05:29:15.283" Title="Brillouin zone integration and delta function" Tags="|density-functional-theory|brillouin-zone|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8664" PostTypeId="2" ParentId="8648" CreationDate="2022-02-09T09:23:07.880" Score="4" Body="&lt;p&gt;Tupical pressure that would affect intercalation is about 3 GPa. Nanobubbles are stable when their size is about 100 nm, and in water their pressure is about 3 MPa. Smaller nanobubbles would have higher pressure, but then this pressure just collapses them and they dissolve quickly. And intercalation is suitable for particles of a few nm in size. In water surface tension at this scale is so extreme for a bubble, that bubble will not be stable.&lt;/p&gt;&#xA;&lt;p&gt;I dont see it working. These effects in my opinion dont have an overlap where they both could be used at once.&lt;/p&gt;&#xA;&lt;p&gt;You would need a liquid with higher surface tension and lower hydrogen solubility than water for it to work.&lt;/p&gt;&#xA;&lt;p&gt;I dont agree that bubbles would join together naturally, their preferred way to dissapear is dissolving I think. Surface tension can keep them apart, as separate structures. Added charged particles from surfactants can help to make groups of bubbles, or keep bubbles apart.&lt;/p&gt;&#xA;" OwnerUserId="1690" LastEditorUserId="1690" LastEditDate="2022-02-09T18:34:09.230" LastActivityDate="2022-02-09T18:34:09.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8665" PostTypeId="1" CreationDate="2022-02-09T09:46:56.157" Score="10" ViewCount="576" Body="&lt;p&gt;I built a function to generate graphs from smiles strings using networkx, inserting various features on the nodes. This is the code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def mol_to_nx(mol):&#xA;    G = nx.Graph()&#xA;    &#xA;    for atom in mol.GetAtoms():&#xA;        G.add_node(atom.GetIdx(),&#xA;                   atomic_num=atom.GetAtomicNum(),&#xA;                   dg=atom.GetDegree(),&#xA;                   charge=atom.GetFormalCharge(),&#xA;                   hyb=atom.GetHybridization(),&#xA;                   is_aromatic=atom.GetIsAromatic(),&#xA;                   Hs=atom.GetTotalNumHs(),&#xA;                   rad=atom.GetNumRadicalElectrons,&#xA;                   ring=atom.IsInRing(),&#xA;                   chirality=atom.GetChiralTag())&#xA;        &#xA;    for bond in mol.GetBonds():&#xA;        G.add_edge(bond.GetBeginAtomIdx(),&#xA;                   bond.GetEndAtomIdx(),&#xA;                   bond_type=bond.GetBondType())&#xA;        &#xA;    return G&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now my question is: if I convert a smiles to graph G (e.g. &lt;code&gt;G=mol_to_nx('COC(=O)C=CN1CC1')&lt;/code&gt;), is there a way to compute the node features matrix, where the rows are the nodes and the columns are the attributes I entered with &lt;code&gt;G.add_node&lt;/code&gt;? Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4898" LastEditorUserId="1609" LastEditDate="2022-02-09T11:06:45.723" LastActivityDate="2022-02-10T22:50:02.090" Title="Node features matrix with Networkx" Tags="|python|machine-learning|smiles|drug-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8666" PostTypeId="1" AcceptedAnswerId="8667" CreationDate="2022-02-09T16:11:08.343" Score="7" ViewCount="642" Body="&lt;p&gt;I like to plot with GaussView 5 the ESP surface of a charged molecule. The charge is +2, the molecule is paraquat.&lt;/p&gt;&#xA;&lt;p&gt;The problem is when I generate a cube with GaussView with the total density and as surface the ESP I just got a deep blue surface. With the molecules without charge, this way works for me. I just request an optimization with the keyword opt. No other options. Do I have to perform other calculations to see the ESP surface of the molecule? Or is it not possible because the molecule has a charge. I think the charge is localized at the nitrogen atoms. But maybe Gaussian can not display this?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="1680" LastEditDate="2022-02-09T19:12:56.200" LastActivityDate="2022-02-09T19:12:56.200" Title="ESP of molecule with charge" Tags="|density-functional-theory|surfaces|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8667" PostTypeId="2" ParentId="8666" CreationDate="2022-02-09T17:09:12.230" Score="5" Body="&lt;p&gt;You need to have two cube files: one for the electronic density and one for the ESP. Then, in GaussView, you load both cube files and then generate what is called a mapped suface: you draw the electronic density surface but colored as the ESP values.&lt;/p&gt;&#xA;&lt;p&gt;other path is, using a file with the charge information on it (like mol2), load it on Jmol and then create the ESP surface directly (it will use the charges to do that).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2022-02-09T17:48:32.817" LastActivityDate="2022-02-09T17:48:32.817" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8668" PostTypeId="1" CreationDate="2022-02-09T23:10:54.243" Score="5" ViewCount="122" Body="&lt;p&gt;I apologize if this is off-topic and if so would be grateful for someone to point me to a relevant source of information.&lt;/p&gt;&#xA;&lt;p&gt;Dissipative Particle Dynamics (DPD) is a quick simulation technique that clumps molecules in a fluid into &amp;quot;beads&amp;quot; of similar size that interact only through short range repulsive forces.  I want to introduce a polymer chain into the fluid simulation so I need tell the DPD package in LAMMPS that there is a specific (simple) potential between the &amp;quot;beads&amp;quot; that chain together to form the polymer. (Eventually we may make membranes as well).&lt;/p&gt;&#xA;&lt;p&gt;The potentials that I can find on the LAMMPS site are for specific atoms, or contain too much physics for the simple  beads-in-a-chain model I am trying to construct.  Is there a package or way to enter simple potentials for DPD?&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-02-09T23:10:54.243" Title="How to define a simple potential in DPD for some type of beads?" Tags="|lammps|coarse-grained|mesoscopic-physics|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T03:20:11.403" ContentLicense="CC BY-SA 4.0" />
  <row Id="8669" PostTypeId="1" CreationDate="2022-02-10T02:50:12.793" Score="4" ViewCount="65" Body="&lt;p&gt;I am new to LAMMPS/DPD (Dissipative particle dynamics), but as i read through DPD model there are three main forces between beads (beads are the spheres consisting of a group of atoms). FC which is a repulsive force, Random and dissipative force.&lt;/p&gt;&#xA;&lt;p&gt;My question is, how a protein remains as a protein by maintaining its chain-like shape if there is no attractive forces defined between its beads?&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="3593" LastEditDate="2022-02-10T12:15:51.293" LastActivityDate="2022-02-10T12:15:51.293" Title="Using DPD/LAMMPS how does a protein remains a protein although there are no attractive forces in DPD?" Tags="|lammps|coarse-grained|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T03:20:32.790" ContentLicense="CC BY-SA 4.0" />
  <row Id="8670" PostTypeId="2" ParentId="8663" CreationDate="2022-02-10T12:24:42.877" Score="7" Body="&lt;p&gt;I think in this case one should realize what the &lt;em&gt;imaginary&lt;/em&gt; constant &lt;span class=&quot;math-container&quot;&gt;$i\eta$&lt;/span&gt; stands for.&lt;/p&gt;&#xA;&lt;p&gt;Ideally this is a non-physical constant that is used to remove the possibility of hitting the singular point &lt;span class=&quot;math-container&quot;&gt;$\omega = \omega(\mathbf k)$&lt;/span&gt;. As such it is a user-defined value that is used to ensure that the inverse is not infinite, i.e. can be calculated.&lt;/p&gt;&#xA;&lt;p&gt;In Green function methods the imaginary part of the Green function as given in your Eq. (1) is directly related to the Lorentzian function with broadening &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt;. So here there is a clear connection between the &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; value and a temperature.&lt;/p&gt;&#xA;&lt;p&gt;The same will apply when you are dealing with the squared &lt;span class=&quot;math-container&quot;&gt;$\delta \omega$&lt;/span&gt;. So the &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; will still be a non-physical constant used to remove infinities.&lt;/p&gt;&#xA;&lt;p&gt;In this case I would instead do:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;G^\prime(\omega) = \int_{BZ}\frac{F(\mathbf{k})d\mathbf{k}}{(\omega - \omega(\mathbf{k}))^2 + i\eta^2}&#xA;$$&lt;/span&gt;&#xA;The purpose here is to make the broadening &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; on the same order as your &lt;span class=&quot;math-container&quot;&gt;$\delta\omega$&lt;/span&gt; (and with same units).&lt;/p&gt;&#xA;&lt;p&gt;A good example is the Green function for electrons (denominator is &lt;span class=&quot;math-container&quot;&gt;$E-E'$&lt;/span&gt;) and phonons (denominator &lt;span class=&quot;math-container&quot;&gt;$(\omega - \omega')^2$&lt;/span&gt;). And to make the imaginary number a relatable physical quantity one will still use the same energy unit for &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; and just follow the power of the denominator.&lt;/p&gt;&#xA;&lt;p&gt;This will give you the same Lorentzian &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; function for &lt;em&gt;any&lt;/em&gt; power of the Green function as this, note that the broadening is changed by the same power:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\mathcal L(\omega) = \frac{\eta^p}{\delta\omega^{2p} + \eta^{2p}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Generally books and texts are not focusing too many details on where the parenthesis is placed for one obvious reason: &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; should &lt;em&gt;always&lt;/em&gt; be chosen to be so small that &lt;span class=&quot;math-container&quot;&gt;$\delta\omega\eta\sim 0$&lt;/span&gt;. If this is not the case then &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; is probably too large to gather any physical meaning of the calculation.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="5" LastEditDate="2022-02-15T04:50:19.073" LastActivityDate="2022-02-15T04:50:19.073" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8671" PostTypeId="2" ParentId="8665" CreationDate="2022-02-10T22:50:02.090" Score="5" Body="&lt;p&gt;You can get a list of lists of the node features like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;g = mol_to_nx(Chem.MolFromSmiles('CCC'))&#xA;[list(g.nodes[n].values()) for n in range(g.number_of_nodes())]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but you will note that the features aren't all of the same type - some are integers, some are objects from RDKit. That means it won't look like a numpy matrix.&lt;/p&gt;&#xA;" OwnerUserId="2225" LastActivityDate="2022-02-10T22:50:02.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8672" PostTypeId="1" AcceptedAnswerId="9654" CreationDate="2022-02-11T10:43:24.760" Score="8" ViewCount="295" Body="&lt;p&gt;Is there an option to calculate circular dichroism (CD spectra) and anisotropic Dissymmetry factor in VASP.&lt;/p&gt;&#xA;&lt;p&gt;I need to calculate the spectra for chiral system&lt;/p&gt;&#xA;" OwnerUserId="4793" LastActivityDate="2022-11-27T18:38:02.870" Title="How to calculate circular dichroism in VASP?" Tags="|density-functional-theory|vasp|computational-chemistry|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8674" PostTypeId="1" AcceptedAnswerId="8677" CreationDate="2022-02-11T18:10:07.290" Score="5" ViewCount="267" Body="&lt;p&gt;I have just started working with VMD, and I figured out how to generate a Carbon Nano Tube (CNT) in VMD and save it's atom positions to use as initial file in LAMMPS. My question is, if you know of any simple way in VMD so that I can get the bonding and angle data as well, to use in my LAMMPS initial file?&lt;/p&gt;&#xA;&lt;p&gt;in other words, after creating a CNT in VMD, How can I generate a data file containing not only the atom positions, but also bonding and angle information in the format of LAMMPS initial input file?&lt;/p&gt;&#xA;&lt;p&gt;Best Regards&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-03-29T07:01:45.560" Title="How to generate CNT bond-type information for LAMMPS intial file?" Tags="|lammps|vmd|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8675" PostTypeId="1" AcceptedAnswerId="8676" CreationDate="2022-02-11T18:48:34.283" Score="7" ViewCount="822" Body="&lt;p&gt;I just used Orca for the first time.&#xA;Can someone address me a valid guide to understand all the files in the directory?&lt;/p&gt;&#xA;&lt;p&gt;I'd like to perform a Nudged Elastic Band (NEB) calculation, but I'm stuck understanding the output file of the preliminary optimisation of the starting and ending structures.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="7" LastEditDate="2022-02-12T13:41:08.260" LastActivityDate="2022-02-12T13:41:08.260" Title="What are the output files generated by an NEB calculation?" Tags="|geometry-optimization|orca|transition-state|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8676" PostTypeId="2" ParentId="8675" CreationDate="2022-02-11T22:31:35.577" Score="8" Body="&lt;p&gt;This question is bit too broad for a specific answer. The most common types of files that are generated by Orca are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;*.gbw&lt;/code&gt; files are binary wavefunction files, they cannot be read by a text editor, only by Orca. They also may contain basis set information and geometry information&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*.engrad&lt;/code&gt; files contain energy and gradient, generated in an &lt;code&gt;!ENGRAD&lt;/code&gt; run or &lt;code&gt;!OPT&lt;/code&gt; run.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*_property.txt&lt;/code&gt; are text files containing various properties that has been calculated in the run&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*.hess&lt;/code&gt; files contain the Hessian (i.e. second derivative matrix) data&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*.cis&lt;/code&gt; files are generated during CIS or TD-DFT runs, and likely contains data about excited states&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;*.smd.out&lt;/code&gt; are text files, and they contain information about the solvation energy contributions and surface areas when SMD solvation is used&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There are also temporary files generated during the run, usually with extensions &lt;code&gt;*.tmp&lt;/code&gt;, &lt;code&gt;*.0&lt;/code&gt;, &lt;code&gt;*.1&lt;/code&gt;, &lt;code&gt;*.VAUXJ&lt;/code&gt; etc. which are deleted when the run ends.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Edit: The question is specifically about NEB calculation. These files are generated by a standard NEB-TS run with preliminary optimization of the end points:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;file.NEB.log&lt;/code&gt; - This is a plain text log file that contains the energies, forces, and various other quantities of each image in the NEB calculation, for each iteration.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_reactant.xyz&lt;/code&gt; - This contains the optimized structure of the reactant (after the optimization ends)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_reactant_trj.xyz&lt;/code&gt; - This is the optimization trajectory for the reactant.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_product.xyz&lt;/code&gt; - Optimized structure of product&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_produc_trj.xyz&lt;/code&gt; - Optimization trajectory of product&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;.gbw&lt;/code&gt;, &lt;code&gt;.opt&lt;/code&gt;, &lt;code&gt;.prop&lt;/code&gt;, &lt;code&gt;.densities&lt;/code&gt; files associated with the product and the reactant&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_im{n}.xyz&lt;/code&gt; - These contain the current structures of the images (&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;th image) and are updated as the NEB calculation progresses. (For some reason Orca seems to delete these files on my laptop after the calculation ends)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_im{n}.gbw&lt;/code&gt; - These contain the wavefunctions of each image&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file.interp&lt;/code&gt; - This file contains the energy profiles and interpolations during each iteration. The data for final iteration is stored in &lt;code&gt;file.final.interp&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_NEB-CI_converged.xyz&lt;/code&gt; - The final converged structure of the climbing image&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_NEB-TS_converged.xyz&lt;/code&gt; - The final converged structure of the TS&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;file_initial_path_trj.xyz&lt;/code&gt; - The first NEB path constructed&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A description of the files is also given inside the Orca output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Following output files will be written:&#xA;Energy profile during opt. written to    ....  NEB-test.interp&#xA;Optimization log-file                    ....  NEB-test.NEB.log&#xA;Current trajectory will be written to    ....  NEB-test_MEP_trj.xyz&#xA;       and to allxyz file                ....  NEB-test_MEP.allxyz&#xA;       and individual images to xyz file ....  NEB-test_im{NIm}.xyz&#xA;Trajectory history will be written to    ....  NEB-test_MEP_ALL_trj.xyz&#xA;Converged CI will be written to          ....  NEB-test_NEB-CI_converged.xyz&#xA;Converged TS will be written to          ....  NEB-test_NEB-TS_converged.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2022-02-12T12:01:50.383" LastActivityDate="2022-02-12T12:01:50.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8677" PostTypeId="2" ParentId="8674" CreationDate="2022-02-12T05:32:29.633" Score="5" Body="&lt;p&gt;Use &lt;strong&gt;Tkconsole&lt;/strong&gt; under extension and follow&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;topo retypebonds&#xA;topo guessdihedrals&#xA;topo writelammpsdata lmp.data full&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uZsej.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uZsej.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-02-12T10:58:33.007" LastActivityDate="2022-02-12T10:58:33.007" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8678" PostTypeId="2" ParentId="3942" CreationDate="2022-02-12T10:45:22.343" Score="18" Body="&lt;p&gt;Just want to add a small comment upon Geoff's excellent answer.&lt;/p&gt;&#xA;&lt;p&gt;One may be tempted to think that a &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;\pu{10 cm-1}$&lt;/span&gt; imaginary frequency introduces a negligible error to the energy or the property of interest, and this is usually true. But one frequently overlooks the fact that, even an infinitesimal imaginary frequency has a finite impact on the Gibbs free energy, and that finite impact is usually non-negligible.&lt;/p&gt;&#xA;&lt;p&gt;To see this, consider a molecule whose lowest frequency is only slightly above zero. In the RRHO approximation (as used by programs like Gaussian), this vibrational mode gives a very negative contribution to the Gibbs free energy, which diverges logarithmically to negative infinity as the frequency approaches zero:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;  G(\nu) &#xA;    &amp;amp;= \frac{1}{2}h\nu + kT\ln \left(&#xA;         1 - \exp\left\{-\frac{h\nu}{kT}\right\}&#xA;       \right)\\&#xA;    &amp;amp;= \frac{1}{2}h\nu + kT\ln \left(&#xA;         \frac{h\nu}{kT} + O(\nu^2)&#xA;       \right). \tag{1}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is a result of the logarithmic divergence of the entropy:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{gather}&#xA;  S(\nu) &#xA;    = k\left[&#xA;        \frac{h\nu}{kT\left(&#xA;          \exp\left\{\frac{h\nu}{kT}\right\} - 1&#xA;        \right)} - \ln\left(&#xA;          1 - \exp\left\{-\frac{h\nu}{kT}\right\}&#xA;        \right)&#xA;      \right]. \tag{2}&#xA;\end{gather}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But when &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; is imaginary, it contributes zero to the Gibbs free energy (and the entropy), because only real frequencies enter the partition function. Therefore, if a small positive frequency is erroneously calculated as imaginary, there is a positive error in the Gibbs free energy, and that error can be arbitrarily large even if the error in the frequency is infinitesimal! (The good news is, because the divergence of the RRHO Gibbs free energy is only logarithmic, the probability of having a certain magnitude of error decreases exponentially w.r.t. the error magnitude.)&lt;/p&gt;&#xA;&lt;p&gt;Things improve somewhat with programs like ORCA or Turbomole, which use the quasi-RRHO (or QRRHO) method&lt;sup&gt;[1]&lt;/sup&gt; instead. In the QRRHO method, the limit &lt;span class=&quot;math-container&quot;&gt;$G(\nu=0)$&lt;/span&gt; is regularized to a finite value, which numerically equals to &lt;span class=&quot;math-container&quot;&gt;$\pu{-2.68 kcal/mol}$&lt;/span&gt;. So with an infinitesimal error in the frequency you can make  an error of up to &lt;span class=&quot;math-container&quot;&gt;$\pu{+2.68 kcal/mol}$&lt;/span&gt; in the Gibbs free energy, which is still quite sizeable for most studies! Even worse you may have more than one false imaginary frequency per molecule, and as the errors are always positive, they add up.&lt;/p&gt;&#xA;&lt;p&gt;The lesson is that, numerical error-induced imaginary frequencies are much bigger problems for Gibbs free energies than for most other properties, and a small (even infinitesimal) imaginary frequency does not guarantee a small error in the Gibbs free energy. This is due to the fact that the Gibbs free energy is not a continuous function w.r.t. the frequency when the latter changes from real to imaginary.&lt;/p&gt;&#xA;&lt;h3&gt;References:&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Grimme, S. Supramolecular Binding Thermodynamics by Dispersion-Corrected Density Functional Theory. &lt;em&gt;Chem. Eur. J.&lt;/em&gt; &lt;strong&gt;2012,&lt;/strong&gt; &lt;em&gt;18&lt;/em&gt; (32), 9955–9964. &lt;a href=&quot;https://doi.org/10.1002/chem.201200497&quot; rel=&quot;noreferrer&quot;&gt;DOI: 10.1002/chem.201200497&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastEditorUserId="49" LastEditDate="2022-02-16T22:07:13.637" LastActivityDate="2022-02-16T22:07:13.637" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8679" PostTypeId="2" ParentId="87" CreationDate="2022-02-13T07:42:37.117" Score="2" Body="&lt;p&gt;If you're using Gaussian you can &lt;strong&gt;also&lt;/strong&gt; use the QST2 and QST3 methods: the first uses reagents and products as input and try to think of a reaction coordinate to find the MEP; the former uses reagent, product and a guess of the TS as inputs instead.&lt;/p&gt;&#xA;&lt;p&gt;If you want to change computational software, on the other hand, there is ORCA which allows you to compute an NEB simulation that takes as input the reagent and the product and some images (that will be computed by the software) and tries to fit this on the PES of the system finding the maximum in energy in quite a few iterations.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="4895" LastEditDate="2022-02-13T17:57:17.527" LastActivityDate="2022-02-13T17:57:17.527" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8680" PostTypeId="1" CreationDate="2022-02-13T08:04:06.673" Score="6" ViewCount="453" Body="&lt;p&gt;I am trying to calculate the surface energies of Ni fcc (111) and (311) surfaces, therefore I need to calculate the surface areas. I use periodic slabs to model these surfaces. For a flat fcc (111) surface as shown below&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O7PAu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O7PAu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;the surface area is simply given by the norm of the cross product of the two lattice vectors of the unit cell. In Python code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111&#xA;import numpy as np&#xA;        &#xA;slab = fcc111('Ni', (4, 4, 4), vacuum=5.)&#xA;A_surf = np.linalg.norm(np.cross(slab.cell[0], slab.cell[1]))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, for the stepped fcc (311) surface, the slab looks like below (top and side views):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KjCAO.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KjCAO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ivNJJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ivNJJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How should I calculate the surface area for a stepped surface (assuming I already know the Cartesian coordinates of all atoms and the lattice vectors of the unit cell)?&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2022-02-13T08:04:06.673" Title="How to calculate the surface area of a stepped surface slab in a unit cell?" Tags="|crystallography|surfaces|atomic-simulation-environment|periodic-system|atomistic-simulation|" AnswerCount="0" CommentCount="8" ClosedDate="2022-11-02T00:31:20.290" ContentLicense="CC BY-SA 4.0" />
  <row Id="8681" PostTypeId="1" AcceptedAnswerId="8683" CreationDate="2022-02-13T12:24:54.680" Score="7" ViewCount="2648" Body="&lt;p&gt;I have a &lt;code&gt;.pdb&lt;/code&gt; file for a single frame of water in a box. I need to calculate and analyse the electrostatic field for choosing a viable atom in this particular configuration.&lt;/p&gt;&#xA;&lt;p&gt;The software I am using - &lt;code&gt;g_elpot&lt;/code&gt; requires a &lt;code&gt;.tpr&lt;/code&gt; file to read the charges and such.&#xA;How can I generate a &lt;code&gt;.tpr&lt;/code&gt; file for my &lt;code&gt;.pdb&lt;/code&gt; file ?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastActivityDate="2022-02-13T22:14:10.240" Title="How to generate a .tpr file from a .pdb or .xyz file in gromacs" Tags="|molecular-dynamics|gromacs|electric-field|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8682" PostTypeId="1" CreationDate="2022-02-12T18:13:32.950" Score="10" ViewCount="112" Body="&lt;p&gt;I want to define occupied orbitals in terms of &lt;a href=&quot;https://www.molpro.net/info/2015.1/doc/manual/node571.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;IRREPs&lt;/code&gt;&lt;/a&gt; for tungsten which has f orbitals. The highest possible point group for &lt;span class=&quot;math-container&quot;&gt;$\ce{WF2}$&lt;/span&gt; in &lt;a href=&quot;https://www.molpro.net&quot; rel=&quot;noreferrer&quot;&gt;MOLPRO&lt;/a&gt; is &lt;span class=&quot;math-container&quot;&gt;$D_{2\mathrm h}$&lt;/span&gt;. Unfortunately, one can't write &lt;span class=&quot;math-container&quot;&gt;$\Phi_{u}$&lt;/span&gt; as a direct sum of IRREPS in &lt;span class=&quot;math-container&quot;&gt;$D_{2\mathrm h}$&lt;/span&gt;. How can I solve this?&lt;/p&gt;&#xA;" OwnerUserId="8151" OwnerDisplayName="Jung" LastEditorUserId="7" LastEditDate="2022-02-14T15:05:07.180" LastActivityDate="2022-04-04T02:54:30.280" Title="Correlation tables between irreps for f orbitals" Tags="|computational-chemistry|symmetry|transition-metals|molpro|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8683" PostTypeId="2" ParentId="8681" CreationDate="2022-02-13T14:44:47.450" Score="7" Body="&lt;p&gt;For generating a tpr file, you need a topology file (.top), a coordinate file (.gro/.pdb) and a input parameter file (.mdp).&lt;/p&gt;&#xA;&lt;p&gt;Assuming, you are working with amber forcefield (a99ffSBdisp), Here's how I do it.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx pdb2gmx -ff a99SBdisp -f yourpdbfile.pdb -o water_1.gro -ignh -p topol.top &#xA;gmx grompp -f water.mdp -c water_1.gro -p topol.top -o water.tpr -maxwarn 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Below I have pasted the &lt;code&gt;water.mdp&lt;/code&gt; file, which can also be found &lt;a href=&quot;http://www.mdtutorials.com/gmx/lysozyme/Files/ions.mdp&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; ions.mdp - used as input into grompp to generate ions.tpr&#xA;; Parameters describing what to do, when to stop and what to save&#xA;integrator  = steep         ; Algorithm (steep = steepest descent minimization)&#xA;emtol       = 1000.0        ; Stop minimization when the maximum force &amp;lt; 1000.0 kJ/mol/nm&#xA;emstep      = 0.01          ; Minimization step size&#xA;nsteps      = 50000         ; Maximum number of (minimization) steps to perform&#xA;&#xA;; Parameters describing how to find the neighbors of each atom and how to calculate the interactions&#xA;nstlist         = 1         ; Frequency to update the neighbor list and long range forces&#xA;cutoff-scheme   = Verlet    ; Buffered neighbor searching &#xA;ns_type         = grid      ; Method to determine neighbor list (simple, grid)&#xA;coulombtype     = cutoff    ; Treatment of long range electrostatic interactions&#xA;rcoulomb        = 1.0       ; Short-range electrostatic cut-off&#xA;rvdw            = 1.0       ; Short-range Van der Waals cut-off&#xA;pbc             = xyz       ; Periodic Boundary Conditions in all 3 dimensions&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;a99SBdisp is the forcefield file (.ff), Here I specified my forcefield exculsively, if not there will be a list of options given to you when you remove &lt;code&gt;-ff a99SBdisp&lt;/code&gt; and run the command. Choose from the list&lt;/p&gt;&#xA;&lt;p&gt;For more information, &lt;a href=&quot;http://www.mdtutorials.com/gmx/lysozyme/04_ions.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;follow this&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="5" LastEditDate="2022-02-13T22:14:10.240" LastActivityDate="2022-02-13T22:14:10.240" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8685" PostTypeId="1" CreationDate="2022-02-14T09:43:26.390" Score="5" ViewCount="152" Body="&lt;p&gt;I want to do a simple SCF calculation for an entropy stabilised oxide (a kind of high entropy alloy) using VASP (DFT code). The chemical formula is (CuCoMgNiZn)O (Rocksalt structure). I am considering 160 atoms from which 80 atoms will be of Oxygen and other 80 will be equally divided by the anions i.e., Cu=16, Co=16, Mg=16, Ni=16 and Zn=16. I am using the mcsqs code from ATAT (Alloy theoretic automated toolkit) as the structure needs to be random in nature. Then I am using the SQS generated structure (bestsqs.out) as an input in VASP. But the problem I am facing is even if I am using a very high number of cores, I am always getting the wall time error. I have tried to simplify the INCAR also. Still I am getting the same error. The INCAR file is attached here for your reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    ALGO = Fast&#xA;    EDIFF = 0.001&#xA;    EDIFFG = -0.05&#xA;    ENCUT = 400&#xA;    IBRION = 2&#xA;    ISIF = 2&#xA;    ICHARG = 2&#xA;    ISMEAR = -5&#xA;    ISPIN = 2&#xA;    MAGMOM = 80*0 16*0 16*0 8*3 8*-3 8*4 8*-4 16*0&#xA;    LREAL = A&#xA;    PREC = Accurate&#xA;    SIGMA = 0.01&#xA;    NELM = 60&#xA;    NSW = 0&#xA;    ISTART = 0&#xA;    LWAVE = .FALSE.&#xA;    LCHARG = .FALSE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there any way to solve this kind of issue? I am also attaching the rndstr.in file that I have used to generate the SQS structure.&lt;/p&gt;&#xA;&lt;p&gt;rndstr.in&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    4.23 4.23 4.23 90 90 90&#xA;    0 0.5 0.5&#xA;    0.5 0 0.5&#xA;    0.5 0.5 0&#xA;    0 0 0 Mg=0.1,Ni=0.1,Cu=0.1,Co=0.1,Zn=0.1,O=0.5&#xA;    0.5 0.5 0.5 Mg=0.1,Ni=0.1,Cu=0.1,Co=0.1,Zn=0.1,O=0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2022-02-14T09:43:26.390" Title="VASP calculation of entropy stabilised oxide (ESO)" Tags="|vasp|alloy-theoretic-automated-toolkit|" AnswerCount="0" CommentCount="4" ClosedDate="2022-11-02T12:50:02.827" ContentLicense="CC BY-SA 4.0" />
  <row Id="8686" PostTypeId="1" AcceptedAnswerId="8687" CreationDate="2022-02-14T13:49:26.927" Score="8" ViewCount="772" Body="&lt;p&gt;Suppose that I wanna make a program to predict possible forms of &lt;a href=&quot;https://en.wikipedia.org/wiki/Allotropy#List_of_allotropes&quot; rel=&quot;nofollow noreferrer&quot;&gt;carbon's Allotropy&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My idea is to use a structure search program to generate a lot of structures and calculate the Gibbs free energy to determine the stability.&lt;/p&gt;&#xA;&lt;p&gt;Is there some program available for this sort of job, and if so, is what I described computationally feasible?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-02-15T02:34:00.270" LastActivityDate="2022-02-15T02:51:14.923" Title="Could we predict all possible forms of carbon Allotropes?" Tags="|crystallography|materials-design|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8687" PostTypeId="2" ParentId="8686" CreationDate="2022-02-14T14:32:19.557" Score="8" Body="&lt;p&gt;One of the software I know is able to search/generate new structures is &lt;a href=&quot;https://uspex-team.org/en/uspex/overview&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From their site, USPEX means:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;USPEX (Universal Structure Predictor: Evolutionary Xtallography...and&#xA;in Russian &amp;quot;uspekh&amp;quot; means &amp;quot;success&amp;quot; - owing to the high success rate&#xA;and many useful results produced by this method) is a method developed&#xA;by the Oganov laboratory since 2004. The problem of crystal structure&#xA;prediction is very old and does, in fact, constitute the central&#xA;problem of theoretical crystal chemistry. In 1988 John Maddox wrote&#xA;that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;One of the continuing scandals in the physical sciences is that&#xA;it remains in general impossible to predict the structure of even&#xA;the simplest crystalline solids from a knowledge of their chemical&#xA;composition solids such as crystalline water (ice) are still&#xA;thought to lie beyond mortals' ken&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;USPEX code solves this problem and allows to predict crystal structure&#xA;with arbitrary P-T conditions by knowing only chemical composition of&#xA;the material. Nowdays, it is used by over 7600 researchers worldwide.&#xA;The First Blind Test of Inorganic Crystal Structure Prediction shows&#xA;that USPEX outperforms other methods in terms of efficiency and&#xA;reliability. The method continues to be rapidly developed.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It is developed in Python but needs other codes to optimize/characterize the generated structures. Works with VASP, GULP, LAMMPS, QuantumEspresso and ABINIT and run in any Linux based system.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="-1" LastEditDate="2022-02-15T02:51:14.923" LastActivityDate="2022-02-15T02:51:14.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8688" PostTypeId="1" AcceptedAnswerId="8692" CreationDate="2022-02-14T15:10:19.103" Score="10" ViewCount="460" Body="&lt;p&gt;VASPs POSCAR/CONTCAR file does not contain any direct information about the cell symmetry. If I run for example a calculation on simple TiN in space group 225, this symmetry is (should be) preserved. In other cases this is not so clear, so I would like to have a tool to extract the space group from a given structure file. A google search turned up a post on the VASP forum with the same question, but only unsatisfying answers - a commercial software package (Material Studio) and a now defunct link.&lt;/p&gt;&#xA;&lt;p&gt;VESTA can impose a certain symmetry on a structure, but that is for entering lattice parameters, not for detecting present symmetry.&lt;/p&gt;&#xA;&lt;p&gt;So I am asking now what simple, freely available tool can give me that information, preferably as a python package or similar.&lt;/p&gt;&#xA;" OwnerUserId="2084" LastActivityDate="2022-02-14T21:19:31.677" Title="How to extract the crystal symmetry from VASPs POSCAR/CONTCAR file?" Tags="|crystallography|symmetry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8689" PostTypeId="2" ParentId="8686" CreationDate="2022-02-14T15:31:20.853" Score="5" Body="&lt;p&gt;I will answer this from a &amp;quot;how much time does this cost&amp;quot; perspective.  In general, I would say no we cannot predict all possible allotropes because there is always a chance that at higher pressure or higher temperature we form a new crystal.  Even if we consider only a single finite temperature and pressure, there is no way to ensure that our unit cell in the calculation is large enough to show the true crystal structure for example.  We can always make the cell larger or the true crystal may not even be periodic.&lt;/p&gt;&#xA;&lt;p&gt;However, in general you should probably expect the simpler crystal structures to be the correct ones and this might not be a practical problem for practical research.  This does not mean that we can predict all forms of a given material, even presumably simple ones containing a single element. In general, a scientifically informed guess does tend to allow us to predict the correct structure which is why codes such as USPEX are seen as a success.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-02-14T15:31:20.853" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8690" PostTypeId="1" CreationDate="2022-02-14T17:52:14.740" Score="4" ViewCount="70" Body="&lt;p&gt;I know that generating a Carbon Nanotube (CNT) in VMD, I can get the required LAMMPS input file. Since VMD makes my life way easier, giving me the position, angle and bonding information in the format of a LAMMPS input file, I would love to be able generate my nanotube which has a different lattice structure than hexagonal using VMD. Is that possible with VMD or are there alternative that generate/upload a lattice structure?&lt;/p&gt;&#xA;&lt;p&gt;In general I am looking for a software to generate for example a nanotube from a triangular lattice or a cubic lattice and has the ability to produce the input file for LAMMPS.&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="7" LastEditDate="2022-02-15T02:30:52.727" LastActivityDate="2022-02-15T02:30:52.727" Title="Is it possible to generate a non-predefined nanotube in VMD?" Tags="|lammps|vmd|" AnswerCount="0" CommentCount="1" ClosedDate="2022-09-07T03:21:32.707" ContentLicense="CC BY-SA 4.0" />
  <row Id="8691" PostTypeId="1" CreationDate="2022-02-14T20:08:06.670" Score="9" ViewCount="472" Body="&lt;p&gt;I want to know why we need fake k-points in HSE band structure calculation? I mean why we can't take a simple high symmetric path like we do in PBE calculation?&lt;/p&gt;&#xA;" OwnerUserId="4946" LastEditorUserId="5" LastEditDate="2022-02-14T23:52:36.190" LastActivityDate="2022-02-15T09:24:39.153" Title="Why do we need to use fake k-points when doing HSE band structure in VASP?" Tags="|vasp|band-structure|symmetry|k-points|hse06|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8692" PostTypeId="2" ParentId="8688" CreationDate="2022-02-14T21:19:31.677" Score="10" Body="&lt;p&gt;There are multiple programs that can do this. As far as I know, all the open source codes use the excellent &lt;a href=&quot;https://spglib.github.io/spglib/&quot; rel=&quot;noreferrer&quot;&gt;spglib&lt;/a&gt; package by Atsushi Togo &amp;quot;under the hood&amp;quot; for space group perception, symmetrization, etc.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pymatgen.org/pymatgen.symmetry.analyzer.html&quot; rel=&quot;noreferrer&quot;&gt;pymatgen&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ajjackson.github.io/ase-tutorial-symmetry/&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'll outline using the Avogadro v2 interface. (Avogadro v1 is very similar).&lt;/p&gt;&#xA;&lt;p&gt;I loaded a rutile POSCAR:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NAhx7m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NAhx7m.png&quot; alt=&quot;rutile crystal structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now I go to perceive the space group:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/t1D36m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/t1D36m.png&quot; alt=&quot;Avogadro menu for space group perception&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm done. There is no step 3, unless you want to change the tolerances:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KWbqcm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KWbqcm.png&quot; alt=&quot;dialog of space group perception&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-02-14T21:19:31.677" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8693" PostTypeId="2" ParentId="8691" CreationDate="2022-02-15T03:51:01.010" Score="6" Body="&lt;p&gt;The reason is that the HSE method are obtaining the band structure with self-consistent calculation rather than non-self-consistent calculation like PBE band structure calculation. For self-consistent calculation, you will sample the k-space with a uniform k mesh. The fake k-points are just the high-symmetry path used in PBE calculations, which are added into the self-consistent calculations to calculate the eigenvalues or energy band you are wanted.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2022-02-15T03:51:01.010" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8694" PostTypeId="2" ParentId="8663" CreationDate="2022-02-15T04:11:32.190" Score="3" Body="&lt;p&gt;The short answer is No.&lt;/p&gt;&#xA;&lt;p&gt;From your Eq.(1) to Eq.(2), the following identity is used:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{1}&#xA;\dfrac{1}{x-i\eta}&#xA;=&#xA;\dfrac{x+i\eta}{x^2+\eta^2}=\dfrac{P}{x}+i\pi\delta(x)&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; represents the Cauchy principal value.&lt;/p&gt;&#xA;&lt;p&gt;You can't do the same thing for your Eq.(3).&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-02-15T05:29:15.283" LastActivityDate="2022-02-15T05:29:15.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8695" PostTypeId="1" CreationDate="2022-02-15T06:03:26.950" Score="8" ViewCount="161" Body="&lt;p&gt;I want to study the crystallographic phase transitions of crystals with increasing temperature. Which freely available MD package should I choose, which has easily available tutorials/example-input-files for this kind of work?&lt;/p&gt;&#xA;" OwnerUserId="4951" LastEditorUserId="5" LastEditDate="2022-11-01T19:39:34.927" LastActivityDate="2022-11-01T19:39:34.927" Title="What software should I use for an MD study of a temperature-dependent crystallographic phase transition?" Tags="|molecular-dynamics|software-recommendations|one-topic-per-answer|crystallography|phase-transitions|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8696" PostTypeId="2" ParentId="8635" CreationDate="2022-02-15T06:27:06.033" Score="4" Body="&lt;p&gt;Let me add one more: (incorrectly high)  symmetry, which can lead to zero HOMO-LUMO gap.&lt;/p&gt;&#xA;&lt;p&gt;One scenario is when one poses too high symmetry to a system, compared to the real symmetry of the electronic system. Another common scenario is that the method cannot describe properly the electronic structure of the systems, e.g. DFT calculations on low-spin Fe(II) in the octahedral field, therefore using high symmetry, while chemically correct, will lead to convergence problems.&lt;/p&gt;&#xA;&lt;p&gt;Neither of these is just SCF convergence error, but the error and the small HOMO-LUMO gap can be an indicator that something is wrong.&lt;/p&gt;&#xA;" OwnerUserId="91" LastActivityDate="2022-02-15T06:27:06.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8697" PostTypeId="2" ParentId="8691" CreationDate="2022-02-15T09:24:39.153" Score="6" Body="&lt;p&gt;This question has already been answered in the quantum espresso forum &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2018-April/040575.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. To reiterate the Fock operator at a certain k-point needs the wavefunction on a grid that is commensurate with it. Hence we cannot calculate the single k-point non-selfconsistently from the charge density. Therefore, in a hybrid functional we have to  use the entire self consistent calculations.&lt;/p&gt;&#xA;" OwnerUserId="3923" LastActivityDate="2022-02-15T09:24:39.153" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8698" PostTypeId="1" CreationDate="2022-02-15T15:25:19.357" Score="5" ViewCount="121" Body="&lt;p&gt;I am working with Fluoro-Graphene (let's assume a fully relaxed monolayer on the XY plane with 16C-1F cell where the F is &amp;quot;covalently&amp;quot; bound to the graphene on top of it with respect to the z axis). I am currently using the 4.0.1 version of SIESTA and doing the post-processing with the 4.1beta4.&lt;/p&gt;&#xA;&lt;p&gt;I am using (and comparing) both the VIBRA post processing module and the ASE extension to try and get IR active normal modes at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point and their respective intensities. With both the ASE module and the VIBRA extension, I can get the frequencies of all the normal modes (with high enough k-point sampling of course).&lt;/p&gt;&#xA;&lt;p&gt;However, the modes I get with ASE, and their respective IR intensities, correspond much better to the literature and can be much better utilized to extract IR activity than the results of the VIBRA module. In fact, the BC (Born effective charge matrix) used by VIBRA to get these intensities is a null matrix making all the intensities for all modes null. This seems to be a glitch in the VIBRA tool since I have tried changing all the parameters (&lt;code&gt;MESH PSEUDOS XC FORCE DISPLACEMENTS BASIS ...&lt;/code&gt;) and still get a null BC matrix.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone explain how VIBRA calculates the IR intensities in a more clear way than what is done in the SIESTA and VIBRA manuals? How does this differ from the way the ASE module calculates it?&lt;/p&gt;&#xA;&lt;p&gt;I understand the chemistry and physics of the phenomena but not the computational &amp;quot;translation&amp;quot; of the concepts. I believe a lot of us struggle with this same problem&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="7" LastEditDate="2022-02-15T17:38:25.897" LastActivityDate="2022-02-15T17:38:25.897" Title="How does the VIBRA module of SIESTA compute IR intensities?" Tags="|phonons|spectroscopy|vibrations|siesta|graphene|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-06T19:54:03.777" ContentLicense="CC BY-SA 4.0" />
  <row Id="8700" PostTypeId="1" CreationDate="2022-02-16T09:53:55.137" Score="14" ViewCount="1128" Body="&lt;p&gt;I know that is a very general question but I would like to start a ML project in Python to predict some chemical properties with a large set of experimental data.&#xA;The compounds I would like to study are transition metal complexes so I have difficult generating SMILES, for example.&#xA;I would like to know if there are any books (or other sources) on which to learn well what descriptors are, which ones to use, how to apply them, which databases to use, how to choose a regression model or how to faithfully convert coordination bonds of complexes.&lt;/p&gt;&#xA;" OwnerUserId="4955" LastActivityDate="2022-02-16T12:09:51.123" Title="How to start a Machine Learning project for chemical properties prediction?" Tags="|computational-chemistry|python|machine-learning|metal-complexes|cheminformatics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8701" PostTypeId="2" ParentId="8700" CreationDate="2022-02-16T12:09:51.123" Score="14" Body="&lt;p&gt;Admittedly, there are tons of materials on the chemistry + machine learning topics. Let me give one:&lt;/p&gt;&#xA;&lt;p&gt;An introductory text I find useful is &lt;a href=&quot;https://pubs.acs.org/doi/book/10.1021/acs.infocus.7e4001&quot; rel=&quot;noreferrer&quot;&gt;Machine Learning in Chemistry&lt;/a&gt; from Janet and Kulik in ACS in Focus series. If you check the papers of the &lt;a href=&quot;http://hjkgrp.mit.edu/&quot; rel=&quot;noreferrer&quot;&gt;Kulik group&lt;/a&gt; at MIT you will find much insightful information on which descriptors of coordination compounds work and ties up nicely with the above-mentioned tutorial by the same authors.&lt;/p&gt;&#xA;" OwnerUserId="91" LastActivityDate="2022-02-16T12:09:51.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8702" PostTypeId="2" ParentId="2346" CreationDate="2022-02-16T15:53:23.383" Score="3" Body="&lt;p&gt;While this is an old question, let me chip in: These cyanides are essentially a potassium salt of the metal cyanide complex, so you can focus on the &lt;span class=&quot;math-container&quot;&gt;$\ce{[Mn(III)(CN)_6]^{3-}}$&lt;/span&gt; complex. As for magnetism, coordination complexes can have a spin and orbital contribution to their moment. In octahedral field, simply from the placement of d electrons (low spin state, due to the strong ligand field), you can have an educated guess about the spin state and the expected orbital degeneracy. If there is no orbital degeneracy, spin only momentum is your best guess for magnetic moment, and no fancy calculation will give you any more accurate.&lt;/p&gt;&#xA;&lt;p&gt;If there is an orbital degeneracy, technically speaking you should calculate that contribution, however here is a catch: in reality, this orbital contribution is often quenched (i.e. very little or zero, due to deformation of the complex). So the educated guesses in these situation a close-to zero orbital contribution (with the exception of Co(II) complexes, which are often close to fully unquenched orbital contribution). If there is a partial quenching, you are in big trouble for several reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the actual quenching is most probably sensitive to the environment of the complex ion, what you can or cannot model,&lt;/li&gt;&#xA;&lt;li&gt;if your workhorse calculation method is DFT, the wavefunction can represent only &lt;span class=&quot;math-container&quot;&gt;$L=0 $&lt;/span&gt; states, so it will be hard to get accurate information about orbital multiplicity of the state.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If you have a good understanding of the geometry (eg you have X-ray) or you have a more rigid ligands around the metal, you can build a Ligand Field model to estimate &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt;, but in most cases it is not really accurate.&lt;/p&gt;&#xA;" OwnerUserId="91" LastEditorUserId="7" LastEditDate="2022-02-16T15:57:35.550" LastActivityDate="2022-02-16T15:57:35.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8705" PostTypeId="1" AcceptedAnswerId="8708" CreationDate="2022-02-17T05:53:15.873" Score="5" ViewCount="93" Body="&lt;p&gt;In many books, e.g., Szabo and Ostlund, Helgaker Jorgensen and Olsen, etc etc, the expansion of Hartree-Fock orbital by basis set is written as a kind of&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_i = \sum_{\mu} C_{\mu i} \chi_{\mu}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, why the expansion coefficient &lt;span class=&quot;math-container&quot;&gt;$ C_{\mu i} $&lt;/span&gt; is not written in &lt;span class=&quot;math-container&quot;&gt;$ C_{i \mu} $&lt;/span&gt;?  I thought &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is coefficient, &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; is a basis, if one wrote as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sum_{\mu} C_{ i \mu} \chi_{\mu}&#xA;$$&lt;/span&gt;&#xA;the contracted indices come closer. But in reality, it is the opposite. Is that because people more commonly coded in Fortran, which is column-major, thus &lt;span class=&quot;math-container&quot;&gt;$ C_{\mu i}$&lt;/span&gt; looks better (the first index changes first)?&lt;/p&gt;&#xA;" OwnerUserId="4694" LastEditorUserId="5" LastEditDate="2022-02-17T13:36:38.047" LastActivityDate="2022-02-17T16:41:58.847" Title="About the order of indices in basis set expansion" Tags="|basis-sets|hartree-fock|fortran|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8706" PostTypeId="1" AcceptedAnswerId="8707" CreationDate="2022-02-17T12:27:11.050" Score="8" ViewCount="243" Body="&lt;p&gt;It is a general question. I know, but I need some help.&lt;/p&gt;&#xA;&lt;p&gt;I am interested to parametrize a complex that contains transition metal like Ru and Pt etc.&#xA;Furthermore, I will use this Force Field to do Molecular Dynamics with DNA and maybe later QM/MM. I saw some Literature, but they don't tell me how can I do it. So I am trying to find a Tutorial.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2022-02-17T15:07:04.643" Title="Parameterize a complex that contains Transition metal (Build Force Field)?" Tags="|molecular-dynamics|forcefields|qmmm|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8707" PostTypeId="2" ParentId="8706" CreationDate="2022-02-17T15:07:04.643" Score="6" Body="&lt;p&gt;I think that the parametrization process is straightforward (but very hardworking!):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;select and use an &lt;em&gt;ab initio&lt;/em&gt;/DFT software that works well for your metal atoms,&lt;/li&gt;&#xA;&lt;li&gt;take a look at the force field equations that your selected molecular dynamic software uses,&lt;/li&gt;&#xA;&lt;li&gt;simulate the interactions between your metal with all the other atoms in your system using the &lt;em&gt;ab initio&lt;/em&gt;/DFT (for example, for bonds/angles, you will need to run some scan of energy versus coordinates),&lt;/li&gt;&#xA;&lt;li&gt;fit the results from &lt;em&gt;ab initio&lt;/em&gt;/DFT to the force field equations to get the corresponding parameters,&lt;/li&gt;&#xA;&lt;li&gt;add the parameters to the force field database files.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-02-17T15:07:04.643" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8708" PostTypeId="2" ParentId="8705" CreationDate="2022-02-17T15:11:57.327" Score="3" Body="&lt;p&gt;I think it has less to do with the language the equations were written in and more with where MO coefficients are used in the program.&lt;/p&gt;&#xA;&lt;p&gt;Let's start by writing the MO expansion in matrix form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Phi=C^\dagger\Psi$$&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; are column vectors of MO and AO basis functions respectively. So we have to use the adjoint/transpose of the MO coefficients to transform between the two, but it seems like we could just as easily have defined the MO coefficients as &lt;span class=&quot;math-container&quot;&gt;$B=C^\dagger$&lt;/span&gt; so that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Phi=B\Psi$$&lt;/span&gt;&#xA;and we wouldn't have to take a transpose. Let's continue on with this alternate definition and write out the Hartree-Fock Roothaan-Hall equations:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$FB^\dagger=SB^\dagger\epsilon$$&lt;/span&gt;&#xA;Now we have a transpose in these equations, so it seems like we are stuck with one either way and its just a matter of where we want to put it. Why might we prefer to have the transpose for the AO to MO transformation?&lt;/p&gt;&#xA;&lt;p&gt;For one, we generally don't have to explicitly use this equation in a HF calculation, since we can solve the HF equations in AO basis and generally only need to transform to MO basis if we are proceeding on to some correlated post-HF method. Another reason is &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; can be nicely thought of as a collection of column vectors that represent the MOs in AO basis. Notice the Roothaan-Hall equation doesn't directly use the MO functions, but instead passes around their coefficient representation.&lt;/p&gt;&#xA;&lt;p&gt;Nothing would necessarily stop us from writing row vectors representing the MOs, but its something of a &lt;a href=&quot;https://math.stackexchange.com/questions/1198729/row-vector-vs-column-vector&quot;&gt;mathematical convention&lt;/a&gt; to say that vectors correspond to column vectors while row vectors are formally &lt;a href=&quot;https://en.wikipedia.org/wiki/Linear_form&quot; rel=&quot;nofollow noreferrer&quot;&gt;covectors&lt;/a&gt;. Vectors vs covectors is well beyond the scope of this answer, but suffice it to say that column vector representations are generally preferred in mathematics (this is presumably the motivation Fortran had for using column major form).&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-02-17T16:41:58.847" LastActivityDate="2022-02-17T16:41:58.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8709" PostTypeId="1" CreationDate="2022-02-17T16:25:41.623" Score="5" ViewCount="55" Body="&lt;p&gt;I have done a simulation of a crystalline material using DFT and have extracted its normal modes and its phonon density of states.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have an algorithm/code or a detailed resource that can extract a crystalline material's specific heat or heat capacity form the phonon density of states ? What are other thermal properties that I can extract from the phonon-DOS ?&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2022-02-17T16:25:41.623" Title="How to derive specific heat of a crystalline material from phonon density of states?" Tags="|phonons|vibrations|thermodynamics|phonon-density-of-state|lattice-thermal-conductivity|" AnswerCount="0" CommentCount="5" FavoriteCount="0" ClosedDate="2022-09-07T03:22:16.010" ContentLicense="CC BY-SA 4.0" />
  <row Id="8710" PostTypeId="1" CreationDate="2022-02-17T16:58:57.007" Score="3" ViewCount="56" Body="&lt;p&gt;I was looking for a way or a software to construct a carbon nanotube from a triabgular lattice. I need to create triangular lattice CNT to use it in VMD (as VMD just has the regular hegzagonal CNT) and get the input data file for LAMMPS.&#xA;I saw online that some people use Material Studio to create their material to be used in VMD. I have not used material Studio before and would appreciate it if somebody kindly give me some hints about how to create a CNT from a triangular lattice using material studio.&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-02-17T16:58:57.007" Title="Is it possible to build a carbon nanotube from a triangular lattice using Material Studio?" Tags="|lammps|vmd|" AnswerCount="0" CommentCount="3" ClosedDate="2022-11-02T12:48:47.407" ContentLicense="CC BY-SA 4.0" />
  <row Id="8712" PostTypeId="1" AcceptedAnswerId="8714" CreationDate="2022-02-18T01:31:02.627" Score="9" ViewCount="1311" Body="&lt;p&gt;When generating the  kpoint by vaspkit for two compounds that have the same lattice system, I found the kpath is&#xA;G–X–S–Y–G–Z–U–R–T–Z|Y–T|U–X|S–R.&lt;/p&gt;&#xA;&lt;p&gt;But why in the article (as shown in the picture) was a different path used? How is the correct path determined?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7FvBt.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7FvBt.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Kmap0.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Kmap0.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4793" LastEditorUserId="7" LastEditDate="2023-12-16T02:38:39.060" LastActivityDate="2023-12-16T02:38:39.060" Title="How is the right k-path chosen for band structure?" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8713" PostTypeId="1" CreationDate="2022-02-18T03:29:58.420" Score="6" ViewCount="159" Body="&lt;p&gt;For RPA calculations in VASP, a &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ACFDT/RPA_calculations#General_recipe_to_calculate_ACFDT-RPA_total_energies&quot; rel=&quot;noreferrer&quot;&gt;four step process&lt;/a&gt; can be utilized where the first step is to compute the occupied orbitals at either the GGA or hybrid GGA level.&lt;/p&gt;&#xA;&lt;p&gt;I am curious with materials that are strongly correlated, such as NiO, if this ground state should be calculated using DFT+U or not.  Are there any caveats with applying DFT+U that should be expected as well when following it up with RPA calculations?&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-04-04T00:40:56.753" Title="DFT+U for RPA Ground State" Tags="|vasp|reference-request|dft-u|random-phase-approximation|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8714" PostTypeId="2" ParentId="8712" CreationDate="2022-02-18T10:36:02.510" Score="12" Body="&lt;p&gt;There is no such thing as &amp;quot;correct path&amp;quot;. The only condition you should use to select the path is that it has to be continuous, only that. After that, the selection will depend on what are you interesting in or what are you looking for. As the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point is the center of the Brillouin zone, it is almost always used in the path.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2022-02-18T12:24:07.633" LastActivityDate="2022-02-18T12:24:07.633" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8715" PostTypeId="1" CreationDate="2022-02-18T14:55:33.623" Score="4" ViewCount="335" Body="&lt;p&gt;I am facing an issue while converting &lt;code&gt;.cif&lt;/code&gt;/&lt;code&gt;.vesta&lt;/code&gt; files into &lt;code&gt;.xyz&lt;/code&gt; and &lt;code&gt;.vasp&lt;/code&gt; format in which the original space group of the unit cell/super cell crystal automatically gets converted to the &lt;span class=&quot;math-container&quot;&gt;$P1$&lt;/span&gt; space group. After converting to &lt;code&gt;.xyz&lt;/code&gt;, when I try to redefine space group through &lt;code&gt;edit --&amp;gt; edit data --&amp;gt; unit cell&lt;/code&gt;, the structure gets completely ruined.&lt;/p&gt;&#xA;&lt;p&gt;How can I redefine space group after converting to &lt;code&gt;.xyz&lt;/code&gt; without ruining the crystal structure? If this is not possible, can I label atoms without converting from &lt;code&gt;.vesta&lt;/code&gt; to `.xyz format? Vesta does                                                                                          not index/label atoms that are transformed from unit cell to supercell/bulk structure.&lt;/p&gt;&#xA;&lt;h2&gt;Vesta file&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ixbil.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ixbil.png&quot; alt=&quot;.vesta file with space group and lattice parameter&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;xyz, incorrect lattice parameters&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8W1IG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8W1IG.png&quot; alt=&quot;.xyz file with ruined space group and lattice parameters&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4979" LastEditorUserId="7" LastEditDate="2022-02-18T15:37:12.837" LastActivityDate="2022-02-18T15:37:12.837" Title="Space group issue with XYZ, VASP formats in VESTA" Tags="|atomic-simulation-environment|vesta|materials-design|" AnswerCount="0" CommentCount="5" ClosedDate="2022-09-24T19:36:29.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="8717" PostTypeId="1" AcceptedAnswerId="8718" CreationDate="2022-02-19T16:49:16.537" Score="8" ViewCount="1469" Body="&lt;p&gt;In the ORCA output for a TD-DFT calculation, there are two types of spectra printed. One is called &amp;quot;transition electric dipole moment&amp;quot; and &amp;quot;transition velocty dipole moment&amp;quot;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-----------------------------------------------------------------------------&#xA;         ABSORPTION SPECTRUM VIA TRANSITION ELECTRIC DIPOLE MOMENTS&#xA;-----------------------------------------------------------------------------&#xA;State   Energy    Wavelength  fosc         T2        TX        TY        TZ  &#xA;        (cm-1)      (nm)                 (au**2)    (au)      (au)      (au) &#xA;-----------------------------------------------------------------------------&#xA;   1   27648.0    361.7   0.719341268   8.56537  -2.87788   0.45802  -0.27090&#xA;   2   30253.3    330.5   0.184731134   2.01022  -1.38229   0.30293  -0.08792&#xA;   3   33113.8    302.0   0.000596722   0.00593  -0.06749  -0.02846   0.02383&#xA;   4   33958.2    294.5   0.016666067   0.16157  -0.23836  -0.26972   0.17890&#xA;   5   35481.0    281.8   0.001963234   0.01822   0.07587  -0.09746   0.05442&#xA;   6   36251.0    275.9   0.082087211   0.74547   0.30134   0.67418  -0.44737&#xA;   7   36892.9    271.1   0.007036359   0.06279  -0.18262  -0.04896   0.16444&#xA;   8   40296.4    248.2   0.163705579   1.33744  -1.15180   0.10363   0.00712&#xA;   9   40712.6    245.6   0.085961535   0.69511  -0.81462  -0.01219   0.17707&#xA;  10   41670.1    240.0   0.002721111   0.02150   0.08394  -0.09869  -0.06864&#xA;&#xA;-----------------------------------------------------------------------------&#xA;         ABSORPTION SPECTRUM VIA TRANSITION VELOCITY DIPOLE MOMENTS&#xA;-----------------------------------------------------------------------------&#xA;State   Energy    Wavelength   fosc        P2         PX        PY        PZ  &#xA;        (cm-1)      (nm)                 (au**2)     (au)      (au)      (au) &#xA;-----------------------------------------------------------------------------&#xA;   1   27648.0    361.7   0.179172895   0.03386   0.18109  -0.00384  -0.03240&#xA;   2   30253.3    330.5   0.036126643   0.00747   0.08535   0.01325  -0.00302&#xA;   3   33113.8    302.0   0.007496146   0.00170   0.03852   0.00888  -0.01156&#xA;   4   33958.2    294.5   0.001365959   0.00032   0.01150  -0.01299  -0.00401&#xA;   5   35481.0    281.8   0.002616796   0.00063  -0.00588   0.01407   0.02005&#xA;   6   36251.0    275.9   0.011772984   0.00292  -0.04163   0.03367  -0.00706&#xA;   7   36892.9    271.1   0.000265060   0.00007  -0.00315   0.00212   0.00724&#xA;   8   40296.4    248.2   0.075499769   0.02079   0.14370  -0.00400  -0.01129&#xA;   9   40712.6    245.6   0.028944201   0.00805   0.08950   0.00244  -0.00615&#xA;  10   41670.1    240.0   0.000916239   0.00026  -0.00984   0.01137   0.00590&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The oscillator strenghts are different in each, but the wavelengths are the same.&lt;/p&gt;&#xA;&lt;p&gt;I am working on predicting UV/visible spectra. I do not need the exact intensities (extinction coefficients), however, I need to be able to get the relative order of the intensities of the peaks right, so that I can match the TD-DFT result to the experimental result with a script. Notice that the order of the intensities between root 3 and 7 are not the same between the two spectra.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which of the oscillator strengths are better correlated with the experimental extinction coefficient (in the experimental absorption spectrum)? (And more generally, why are the two different?)&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2022-02-19T19:58:57.510" LastActivityDate="2022-02-20T01:47:26.713" Title="Different types of transition dipole moment in ORCA output" Tags="|spectroscopy|orca|terminology|td-dft|dipole|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8718" PostTypeId="2" ParentId="8717" CreationDate="2022-02-19T17:16:39.760" Score="10" Body="&lt;p&gt;You have stumbled across a problem that was described in 1983 in the following way (note that the &amp;quot;40 years&amp;quot; refers to 1943-1983):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Over the past 40 years, many authors have tried to answer the following question: For a given pair of approximate wavefunctions &lt;span class=&quot;math-container&quot;&gt;$|\phi_a\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\phi_b\rangle$&lt;/span&gt;, which form of the &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; value, &lt;span class=&quot;math-container&quot;&gt;$f_L$&lt;/span&gt; calculated with [&lt;em&gt;the dipole length transition moment&lt;/em&gt;] or &lt;span class=&quot;math-container&quot;&gt;$f_V$&lt;/span&gt; calculated with [&lt;em&gt;the dipole velocity transition moment&lt;/em&gt;] may be expected to be more accurate?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The phrase &amp;quot;transition velocity dipole moment&amp;quot; is sometimes used to refer to the &amp;quot;&lt;a href=&quot;http://astro1.panet.utoledo.edu/%7Eljc/fsum16.jpg&quot; rel=&quot;noreferrer&quot;&gt;velocity form&lt;/a&gt;&amp;quot; of the transition dipole moment.&lt;/p&gt;&#xA;&lt;p&gt;The above quote comes from the paper &amp;quot;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0009261483803571&quot; rel=&quot;noreferrer&quot;&gt;Electric dipole oscillator strengths: length &lt;em&gt;and&lt;/em&gt; velocity!&lt;/a&gt;&amp;quot; by  Roginsky, Klapisch and Cohen published in &amp;quot;&lt;em&gt;Chemical Physics Letters&lt;/em&gt; Volume &lt;strong&gt;95&lt;/strong&gt;, Issue 6, 18 March 1983, Pages 568-572&amp;quot; proposed that when &lt;span class=&quot;math-container&quot;&gt;$f_L$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_V$&lt;/span&gt; (the &amp;quot;length&amp;quot; and &amp;quot;velocity&amp;quot; forms of the electric dipole oscillator strength) values are different, then an appropriate &lt;strong&gt;linear combination of them&lt;/strong&gt; will often be &lt;em&gt;more accurate&lt;/em&gt; than the better of &lt;span class=&quot;math-container&quot;&gt;$f_L$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_V$&lt;/span&gt;.  They also define an &amp;quot;acceleration&amp;quot; version in Eq. 6 of that paper!&lt;/p&gt;&#xA;&lt;p&gt;None of this would be necessary if exact wavefunctions were used, but usually in quantum chemistry calculations, we only have approximate wavefunctions.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-02-19T17:51:33.820" LastActivityDate="2022-02-19T17:51:33.820" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8719" PostTypeId="2" ParentId="8717" CreationDate="2022-02-20T01:47:26.713" Score="6" Body="&lt;p&gt;To give a little background on where these different forms come from, it is related to &lt;a href=&quot;https://en.wikipedia.org/wiki/Gauge_theory#Classical_electromagnetism&quot; rel=&quot;noreferrer&quot;&gt;gauge theory&lt;/a&gt; in electromagnetism. We can represent an electromagnetic field through Maxwell's equations using a scalar potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; and a vector potential &lt;span class=&quot;math-container&quot;&gt;$\mathbf{A}$&lt;/span&gt;. It turns out these values are not unique: for any twice differentiable function &lt;span class=&quot;math-container&quot;&gt;$f(x,t)$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;V' = V-\frac{\partial f}{\partial t}\\&#xA;\mathbf{A}' = \mathbf{A} + \nabla f&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;are also valid solutions that describe the same field. This is referred to as a gauge symmetry. While different gauges (i.e. choices of &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;) are equivalent for exact calculations (more on this below), they lead to different forms of various matrix elements, most notably the electric dipole.&lt;/p&gt;&#xA;&lt;p&gt;The common form of dipole matrix elements &lt;span class=&quot;math-container&quot;&gt;$-\langle a|\boldsymbol{r}|b\rangle$&lt;/span&gt; (in atomic units) corresponds to using the so called length gauge (due to the dipole depending on the length operator). In the velocity gauge, these same matrix elements would be written &lt;span class=&quot;math-container&quot;&gt;$i\omega_{ab}^{-1}\langle a|\boldsymbol{p}|b\rangle$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$-\omega_{ab}^{-1}\langle a|\boldsymbol{\nabla}|b\rangle$&lt;/span&gt; showing the connection to velocity).&lt;/p&gt;&#xA;&lt;p&gt;For the exact eigenstates of the molecular Hamiltonian, these expressions are exactly equal due to the identity&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle a|\boldsymbol{X}|b\rangle=\omega_{ab}^{-1}\langle a|[\boldsymbol{X},H]|b\rangle$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol{X}$&lt;/span&gt; can be any operator and &lt;span class=&quot;math-container&quot;&gt;$[\boldsymbol{r},H]=-\boldsymbol{p}$&lt;/span&gt;.&#xA;Since this identity/commutator only holds exactly for an exact calculation, these different forms of the dipole are not equivalent in practical calculations.&lt;/p&gt;&#xA;&lt;p&gt;As to which form to use for your calculations, I don't think there is a great physical reason to choose one gauge over another in general; afterall in principle they are both equally valid. I'm most familiar with this gauge issue in the context of computing optical rotation (OR) and for that property the choice is usually made based on computational convenience.&lt;/p&gt;&#xA;&lt;p&gt;The length gauge leads to an origin dependent OR without corrections, such as using gauge-including/London atomic orbitals, so it is somewhat trickier to implement properly. The velocity gauge is origin independent, but gives a nonzero OR for a static perturbation, which is nonphysical, so this static limit is usually subtracted from the results for other frequencies, essentially making any given calculation twice as expensive. So for OR, it depends whether you want a cheaper calculation or a simpler implementation.&lt;/p&gt;&#xA;&lt;p&gt;For absorption, I expect any choice between the two will largely be an empirical and system dependent, though Nike's answer suggests some efforts have been made to mathematically motivate one choice or another.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-02-20T01:47:26.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8720" PostTypeId="1" AcceptedAnswerId="8756" CreationDate="2022-02-20T19:26:21.353" Score="10" ViewCount="262" Body="&lt;p&gt;For pedagogical reasons, I started adding &lt;a href=&quot;https://www.tddft.org/programs/libxc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;libxc&lt;/a&gt; to the atomic DFT &lt;a href=&quot;https://github.com/certik/dftatom&quot; rel=&quot;nofollow noreferrer&quot;&gt;dftatom&lt;/a&gt;. In this program only spherical symmetric charges. That means that the final potential is just radial.&lt;/p&gt;&#xA;&lt;p&gt;To my understanding, if the LDA xc energy is defined as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[n(r)] = \int n(\mathbf{r}) \varepsilon_{xc}[n(\mathbf{r})]\ d\mathbf{r},&#xA;$$&lt;/span&gt;&#xA;the radial xc potential contribution will be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{xc}[n(r)] = \varepsilon_{xc}(r) + n(r)\,\frac{d \varepsilon_{xc}(r)}{d n(r)}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;According to the manual of libxc from the function with the interface&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;void xc_lda_exc_vxc(const xc_lda_type *p, inp np, double *rho, &#xA;     double *exc, double *vrho);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{xc}$&lt;/span&gt; from &lt;code&gt;exc&lt;/code&gt; and &lt;span class=&quot;math-container&quot;&gt;$\frac{d \varepsilon_{xc}}{d n}$&lt;/span&gt; from &lt;code&gt;vrho&lt;/code&gt;. Judging from comparison to simple analytical expressions (e.g. Slater exchange), I would say the &lt;code&gt;vrho&lt;/code&gt; actually returns the whole radial expression &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{xc} + n\frac{d \varepsilon_{xc}}{d n}$&lt;/span&gt; already.&lt;/p&gt;&#xA;&lt;p&gt;I am starting to wonder is the gradient correction term for GGA returned from the interface. Generally, GGA potential is written as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{xc}[n] = \varepsilon_{xc} + n\frac{\partial \varepsilon_{xc}}{\partial n} - \nabla\cdot\left[n\frac{\partial \varepsilon_{xc}}{\partial \nabla n}\right].&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and with the contracted gradient &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{xc}[n] = \varepsilon_{xc} + n\frac{\partial \varepsilon_{xc}}{\partial n} - 2 \, \nabla\cdot\left[n\frac{\partial \varepsilon_{xc}}{\partial \sigma} \nabla n\right].&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The interface for GGA is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;void xc_gga_exc_vxc(const xc_func_type *p, int np, double *rho, double *sigma, &#xA;     double *exc, double *vrho, double *vsigma)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also here I would say that &lt;code&gt;vrho&lt;/code&gt; returns the sum of the first two terms and &lt;code&gt;vsigma&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$n\frac{\partial \varepsilon_{xc}}{\partial \sigma}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Can somebody verify the correct implementation for GGA and LDA from the libxc functions?&lt;/p&gt;&#xA;" OwnerUserId="717" LastEditorUserId="697" LastEditDate="2022-02-22T23:43:01.970" LastActivityDate="2022-03-02T23:32:11.667" Title="How can the GGA functionals in libxc be evaluated?" Tags="|density-functional-theory|software|exchange-correlation|libxc|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8721" PostTypeId="1" CreationDate="2022-02-21T01:51:01.890" Score="3" ViewCount="47" Body="&lt;p&gt;I am not asking which software to use to or how to remove atoms from a supercell. But rather how to decide which part should be removed. Like do I give preference to some surfaces or some particular molecules. Currently I am working with a layered material and that is why I am a bit confused. Like do I take the layer into the nano material or not and if I do take it then do I take one layer or two?&lt;/p&gt;&#xA;&lt;p&gt;I am pretty sure that there exists some logical pointers that must be considered while cutting a structure. And things like make the structure more symmetric are also helpful.  Any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2022-02-21T04:29:54.787" LastActivityDate="2022-02-21T04:29:54.787" Title="How to cut a Nano material from a cif file properly" Tags="|structure|nanostructures|quantum-dots|" AnswerCount="0" CommentCount="4" ClosedDate="2022-09-03T02:25:01.253" ContentLicense="CC BY-SA 4.0" />
  <row Id="8722" PostTypeId="1" CreationDate="2022-02-22T11:14:49.833" Score="6" ViewCount="273" Body="&lt;p&gt;I built a prediction model with fingerprints from 300 molecules and got an R2 of 0.9&#xA;However when I go to perform a cross-validation I get a very low R2.&#xA;How can I improve this result?&#xA;I'm using sklearn and PaDEL descriptors, maybe I'm doing something wrong though. Where can I learn how to do it correctly?&lt;/p&gt;&#xA;" OwnerUserId="4955" LastActivityDate="2022-02-22T19:48:53.073" Title="How to improve my cross-validation R2_score?" Tags="|machine-learning|drug-design|qsar|fingerprint|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8723" PostTypeId="2" ParentId="8661" CreationDate="2022-02-22T11:56:18.960" Score="5" Body="&lt;p&gt;Generally a failure in the Cholesky factorization happens when two orbitals are extremely similar and thus the overlap matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf S$&lt;/span&gt; becomes singular. If you get this error first check the coordinates of atoms and ensure they are not &lt;em&gt;on top of each other&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-02-22T11:56:18.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8724" PostTypeId="1" CreationDate="2022-02-22T17:40:21.413" Score="7" ViewCount="185" Body="&lt;p&gt;I am looking for an electronic structure method code (e.g. tight binding  DFTB) that supports cheap calculations of NMR shieldings and has support for periodical systems. I would be grateful for any help!&lt;/p&gt;&#xA;&lt;p&gt;There exist many codes using GIPAW and GIAO that use expensive DFT calculations.&lt;/p&gt;&#xA;&lt;p&gt;However, the only papers using DFTB I have found appear not to publish their code or they do not support periodic systems (see e.g. &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp9923062&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/abs/10.1021/jp9923062&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="5000" LastActivityDate="2022-02-22T17:40:21.413" Title="Cheap NMR shift calculations in periodic systems" Tags="|electronic-structure|tight-binding|nuclear-magnetic-resonance|" AnswerCount="0" CommentCount="17" ClosedDate="2023-10-20T01:34:38.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="8725" PostTypeId="1" CreationDate="2022-02-22T19:30:02.350" Score="4" ViewCount="511" Body="&lt;p&gt;I began with an imported a .cif file from materials project and have updated the structure to my specifications. I would like to change the global cartesian coordinate system so that I can project the bands and DOS onto d-orbitals of a particular orientation.&lt;/p&gt;&#xA;&lt;p&gt;To this end, I have determined the required 3D rotation matrix to transform from the original coordinate system to the new one. I have applied the transformation to the a, b, and c vectors given in the POSCAR file that define the unit cell. Specifically, I manually replace the coordinates that define the a, b, and c vectors by their transformed coordinates in the POSCAR file.&lt;/p&gt;&#xA;&lt;p&gt;To check that the transformation had the desired effect, I open the modified POSCAR file in VESTA. The structure appears unchanged, but I expected the x,y,z coordinates of each atom to have changed according to the transformation. Instead, I find them to be exactly the same. Furthermore, if I try to export data from this modified POSCAR file, VESTA outputs a POSCAR with the &lt;em&gt;original&lt;/em&gt; a,b, and c coordinates. It is as though VESTA has overwritten or ignored my modifications.&lt;/p&gt;&#xA;&lt;p&gt;What is going on here? Is there another approach to change coordinates?&lt;/p&gt;&#xA;" OwnerUserId="5001" LastActivityDate="2022-02-22T19:30:02.350" Title="Changing global cartesian coordinate system with VESTA" Tags="|vesta|" AnswerCount="0" CommentCount="5" ClosedDate="2022-11-02T12:48:16.927" ContentLicense="CC BY-SA 4.0" />
  <row Id="8726" PostTypeId="2" ParentId="8722" CreationDate="2022-02-22T19:48:53.073" Score="7" Body="&lt;p&gt;You don't give a lot of details (e.g., type of model, target property, etc.), but with only 300 molecules, it's very likely that your model is over-fit. Thus when you cross-validate, you get low &lt;span class=&quot;math-container&quot;&gt;$R^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Consider that each descriptor you add is at least one parameter. You'll want more data than you have parameters.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;You want to look for more data if possible&lt;/li&gt;&#xA;&lt;li&gt;You'll want to use LASSO or other method to remove descriptors that don't add much information&lt;/li&gt;&#xA;&lt;li&gt;You'll want to use cross-validation (e.g., 5-fold or 10-fold CV) from the start to minimize the chance of an over fit model&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But you also should think carefully about descriptors. Consider whether the descriptors you use would be meaningful for the model you want.&lt;/p&gt;&#xA;&lt;p&gt;Let's say I wanted a model for solubility prediction. I can think of a few properties / descriptors that might be important:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Molecular size (molecular weight or volume)&lt;/li&gt;&#xA;&lt;li&gt;Molecular shape (like dissolves like)&lt;/li&gt;&#xA;&lt;li&gt;Hydrogen bond donors and acceptors&lt;/li&gt;&#xA;&lt;li&gt;Dipole moment / electrostatics&lt;/li&gt;&#xA;&lt;li&gt;etc.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Yet for other properties (e.g., redox potential) most of these are probably less relevant.&lt;/p&gt;&#xA;&lt;p&gt;If you want a good model, you need to be careful with what descriptors you use.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-02-22T19:48:53.073" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8727" PostTypeId="1" CreationDate="2022-02-23T04:04:41.197" Score="10" ViewCount="455" Body="&lt;p&gt;This question about &lt;a href=&quot;https://en.wikipedia.org/wiki/Octaoxygen&quot; rel=&quot;noreferrer&quot;&gt;octaoxygen&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/questions/163209/why-is-octaoxygen-diamagnetic&quot;&gt;Why is octaoxygen diamagnetic?&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;p&gt;was asked in chemistry, but I really don't have an answer in terms of molecular orbitals. I &lt;em&gt;think&lt;/em&gt; it could be a mixing of the O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;'s &lt;span class=&quot;math-container&quot;&gt;$\pi^*$&lt;/span&gt; orbitals that have been bent inwards the monoclinic structure due to the high pressure of the &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt;-phase (about 10 GPa), thus greatly reducing sample volume, but I can't find a ressonant combination of 8 &lt;span class=&quot;math-container&quot;&gt;$\pi^*$&lt;/span&gt; mixed orbitals that works.&lt;/p&gt;&#xA;&lt;p&gt;I know that Gaussian can &lt;a href=&quot;https://www.youtube.com/watch?v=WT-196JH0f8&quot; rel=&quot;noreferrer&quot;&gt;calculate&lt;/a&gt; molecular orbitals, but I don't have access to it.&lt;/p&gt;&#xA;&lt;p&gt;My question is: is there any package out there, preferably free open-source software, which can calculate molecular orbitals of octaoxygen, which works for the gigapascal range (perhaps simulating cluster pressure with external electrostatic field)?&lt;/p&gt;&#xA;" OwnerUserId="4794" LastActivityDate="2022-02-23T16:49:30.223" Title="How to calculate molecular orbitals of octaoxygen under high pressure?" Tags="|software|ab-initio-calculations|orbitals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8728" PostTypeId="2" ParentId="8727" CreationDate="2022-02-23T09:58:31.093" Score="8" Body="&lt;h2&gt;TL;DR&lt;/h2&gt;&#xA;&lt;p&gt;Two recently published and easy-to-use methods come to mind:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;X-HCFF (1)&lt;/li&gt;&#xA;&lt;li&gt;GOSTSHYP (2)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Both are available in Q-Chem 5 (6). The user can simply input a desired pressure, and the algorithms take care of the rest. Note that X-HCFF does not let the electrons interact with the pressure, but GOSTSHYP does. X-HCFF only works for molecules (i.e. multi-nuclei systems), but GOSTSHYP can be used for both atoms and molecules.&lt;/p&gt;&#xA;&lt;h2&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;There are several methods available that can simulate the electronic structure of molecules under high pressure. How to include pressure in an electronic structure calculation is not necessarily obvious or straightforward; no terms in the Hamiltonian operator depend explicitly on the pressure. So we need to smuggle it in, somehow.&lt;/p&gt;&#xA;&lt;p&gt;As far as my understanding goes, there are essentially two main categories of ways to include pressure: 1) By confining the nuclei to a smaller volume, and 2) By confining the electron density to a smaller volume.&lt;/p&gt;&#xA;&lt;h2&gt;Confining the nuclei&lt;/h2&gt;&#xA;&lt;p&gt;This is the simplest method, and also the more &lt;em&gt;physically incorrect&lt;/em&gt; way. The general idea is to compute external mechanical forces on each nuclei, that point inward either toward the molecular centroid or inward perpendicular to the molecular surface. The methods differ in how these forces are defined and how they are computed. The external forces are then added to the nuclear gradient, and the effect of pressure is simulated due to the compression that takes place during a geometry optimization. Such methods belong to the class &amp;quot;quantum mechanochemistry&amp;quot;, and I refer you to the literature for more information about this topic (3-5). Note that the electron density is not directly affected; one only modifies the potential energy surface by adding external forces to the nuclear gradient, and then the wave function is relaxed to the new geometry during the SCF.&lt;/p&gt;&#xA;&lt;p&gt;A modern quantum mechanochemical method is the &lt;strong&gt;eXtended Hydrostatic Compression Force Field&lt;/strong&gt; (X-HCFF) (1). The idea is to build a van der Waal's surface of the molecule, which is tesselated by a Lebedev grid. The user inputs a pressure (e.g. 100 GPa), and the forces perpendicular to the surface are computed in such a way that the requested pressure is exerted on the molecule. This method is available in Q-Chem 5 (6) (free trial version). Note that this method cannot be used for single atoms, since one relies on being able to compute the nuclear gradient (one cannot geometry optimize a single atom).&lt;/p&gt;&#xA;&lt;h2&gt;Confining the electron density&lt;/h2&gt;&#xA;&lt;p&gt;A more physically correct strategy is to have the electrons directly interact with whatever is causing the pressure. This can be done by confining the electron density. Electron confinement is quite fundamental to quantum mechanics; recall that the quantized energy levels in a particle-in-a-box is a consequence of the electron being confined.&#xA;Electron confinement has a long history in quantum chemistry, and typically various confinement potentials have been used. However, a flexible and easy-to-use method was recently published: &lt;strong&gt;Gaussians On Surface Tesserae Simulate Hydrostatic Pressure&lt;/strong&gt; (GOSTSHYP) (2).&lt;/p&gt;&#xA;&lt;p&gt;The idea in GOSTSHYP is to build a van der Waal's surface of the molecule and tesselate it by a Levedev grid. The Gaussian potentials are added at each grid point. The width of each Gaussian is determined in a way to ensure that the Gaussian field is as uniform as possible. The user inputs a certain pressure, and the amplitudes of each Gaussian is determined in a way to ensure that the requested pressure is indeed applied. The pressure arises from the repulsive interactions due to the electrons and the Gaussian potentials. The GOSTSHYP method is also available in Q-Chem 5. Also note that the GOSTSHYP method can be used for both atoms and molecules, since one does not rely on the nuclear gradient.&lt;/p&gt;&#xA;&lt;p&gt;Another strategy for confining the electrons is the &lt;strong&gt;eXtreme Pressure Polarizable Continuum Model&lt;/strong&gt; (XP-PCM) (7). This is based on the PCM approach for simulating solvent effects. Here, pressure is simulated by the repulsive Pauli interactions between the molecule's electron density and the solvent's electron (uniform) electron density. However, the XP-PCM is not available in any release version of quantum chemistry programs, as far as I am aware.&lt;/p&gt;&#xA;&lt;h2&gt;References&lt;/h2&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;T. Stauch. &lt;em&gt;Int J Quantum Chem&lt;/em&gt;. &lt;strong&gt;2020&lt;/strong&gt;, 153, 134503. &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0024671&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1063/5.0024671&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;M. Scheurer et al. &lt;em&gt;Int J Quantum Chem&lt;/em&gt;. &lt;strong&gt;2021&lt;/strong&gt;, 17, 583–597. &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c01212&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1021/acs.jctc.0c01212&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;L. Takacs. &lt;em&gt;Chem Soc Rev&lt;/em&gt;. &lt;strong&gt;2013&lt;/strong&gt;, 42, 7649-7659. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/cs/c2cs35442j&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1039/C2CS35442J&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;T. Stauch and A. Dreuw. &lt;em&gt;Chem Rev&lt;/em&gt;. &lt;strong&gt;2016&lt;/strong&gt;, 116, 14137–14180. &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.chemrev.6b00458&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1021/acs.chemrev.6b00458&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;T. Stauch. &lt;em&gt;Int J Quantum Chem&lt;/em&gt;. &lt;strong&gt;2021&lt;/strong&gt;, 121, e26208. &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/qua.26208&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1002/qua.26208&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.q-chem.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.q-chem.com/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;R. Cammi et al. &lt;em&gt;Chem Phys&lt;/em&gt;. &lt;strong&gt;2008&lt;/strong&gt;, 344, 135-141. &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0301010407005691?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi: 10.1016/j.chemphys.2007.12.010&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1885" LastEditorUserId="7" LastEditDate="2022-02-23T16:49:30.223" LastActivityDate="2022-02-23T16:49:30.223" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8729" PostTypeId="1" CreationDate="2022-02-23T17:20:37.587" Score="6" ViewCount="550" Body="&lt;p&gt;I have a question about construction of a Wannier function for a tight-binding model. Let's say we consider the tight-binding model of a 1D chain with two atoms (site A and B in a unit cell). In k-space we can write the single-particle Hamiltonian in following way:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;H = \sum_{k} \Psi_{k}^\dagger h(k) \Psi_k~~,~~\tag{1}\\ &#xA;\Psi_k = ( c_{A,k} ~~ c_{B,k}) ~~,~~\tag{2}\\&#xA; h(k)=&#xA;\begin{pmatrix}&#xA;\epsilon(k) &amp;amp; \Delta(k)  \\&#xA;\Delta(k)^\dagger &amp;amp; \epsilon(k)&#xA;\end{pmatrix}.\tag{3}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;By diagonalizing the single-particle Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$h(k)$&lt;/span&gt;, we get the Bloch wavefunction &lt;span class=&quot;math-container&quot;&gt;$| \psi_{nk} \rangle$&lt;/span&gt; for each &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, where the Bloch wavefunctions are 2-dimensional. To construct the Wannier function, we can think of it as the inverse Fourier function of Bloch waves:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{4}&#xA;| R n \rangle = \frac{V}{(2 \pi)^D} \int d^{D}k ~~ e^{-i k\cdot R} |\psi_{nk} \rangle ,&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$|R n \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; are is the Wannier function, the band index, and the real space lattice vector respectively.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;My question is how to construct the Wannier function numerically.&lt;/strong&gt;&lt;/em&gt; The picture in my mind is that the resulting Wannier function should be centred at the home unit cell. However,  &lt;span class=&quot;math-container&quot;&gt;$| \psi_{nk} \rangle$&lt;/span&gt; is a 2D array, it means that the Wannier function that I compute should be a vector rather than a function. So, how can I interpret the elements of the resulting vector after Wannierization? After Wannierization, what things should I plot in order to see the localized function in real space? I appreciate all comments.&lt;/p&gt;&#xA;&lt;p&gt;This is my rough and trial code for the Wannierization process in python:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import scipy.linalg as la &#xA;&#xA;# Suppose I solved the Hamiltonian and get a set of states &#xA;psi_k = np.array([ la.eigh(H(k))[0] for k in k_list ]) #[0] means returns the eigvecs&#xA;&#xA;# Select the lower band ( 1D chain with 2 atoms &amp;gt; 2 bands in k-space) &#xA;low_band = psi_k[:,:,0]&#xA;&#xA;# Wannier function &#xA;def Wannier(psi_k,r_list, k_list):&#xA;    WF = 0&#xA;    for r in r_list:&#xA;        for i in range(len(k_list)):&#xA;            WF += np.exp(-j*k*R) * psi_k[i,:,0]&#xA;    return WF*len(k_list)**-1 &#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4341" LastEditorUserId="5" LastEditDate="2022-03-16T00:11:56.840" LastActivityDate="2022-03-16T00:11:56.840" Title="How to get a Wannier function for a tight-binding model numerically?" Tags="|python|condensed-matter|mathematical-modeling|solid-state-physics|" AnswerCount="0" CommentCount="4" ClosedDate="2022-09-03T02:30:22.040" ContentLicense="CC BY-SA 4.0" />
  <row Id="8730" PostTypeId="1" AcceptedAnswerId="8732" CreationDate="2022-02-23T19:07:07.873" Score="15" ViewCount="2587" Body="&lt;p&gt;I was wondering, can you simulate the chemical reaction between two or more molecules using DFT? If not, what numerical method is usually used for this?&lt;/p&gt;&#xA;" OwnerUserId="4659" LastEditorUserId="5" LastEditDate="2022-02-24T03:27:19.370" LastActivityDate="2022-02-27T21:30:40.010" Title="Can DFT simulate chemical reactions?" Tags="|density-functional-theory|molecular-dynamics|computational-chemistry|quantum-dynamics|reaction-mechanism|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8731" PostTypeId="2" ParentId="8730" CreationDate="2022-02-24T00:23:41.530" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Can you simulate the chemical reaction between two or more molecules using DFT?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The short answer is no. In essence, DFT is solving the Kohn-Sham equation, which is a time-independent Schrodinger equation and hence can't capture the dynamical processes in chemical reactions.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If not, what numerical method is usually used for this?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The time-dependent density functional theory (TDDFT) maybe can be used for that purpose.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-02-24T03:06:20.340" LastActivityDate="2022-02-24T03:06:20.340" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8732" PostTypeId="2" ParentId="8730" CreationDate="2022-02-24T03:23:09.290" Score="14" Body="&lt;p&gt;DFT can be used for many things. One of them is to calculate an approximation of the ground state energy of a molecule. By calculating the ground state energies of all reactants, and all products, you can gain valuable information about a chemical reaction between them, such as an estimate of how much energy would be released if the chemical reaction were to occur, or how much extra energy would need to be given to the system in order for the reaction to become likely. DFT can also be used to map out the potential energy surface for a chemical reaction.&lt;/p&gt;&#xA;&lt;p&gt;However, other aspects of a reaction such as, how must faster it will be at some temperature/pressure compared to another temperature/pressure, may be better modeled using &lt;a href=&quot;/questions/tagged/molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;molecular-dynamics&lt;/a&gt;. I have given some explanations about how molecular dynamics works in my answers to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4735/5&quot;&gt;How to calculate the volumetric energy density of a molecule?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4817/5&quot;&gt;How do I simulate the interaction between two atoms?&lt;/a&gt;, and again here,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6871/5&quot;&gt;How would one find a material's equilibrium structure at any specific temperature?&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My answer to the last of those questions also discusses how to do a more accurate chemical dynamics simulation by solving the time-&lt;em&gt;&lt;strong&gt;dependent&lt;/strong&gt;&lt;/em&gt; Schroedinger equation (which is in practice quite computationally demanding and often seen as overkill for most applications today).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-02-24T03:23:09.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8733" PostTypeId="2" ParentId="7253" CreationDate="2022-02-24T08:34:36.603" Score="4" Body="&lt;p&gt;I believe this is just a polarized calculation, see here for the input flags: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2350/how-to-do-spin-polarization-calculations-using-quantum-espresso&quot;&gt;How to do spin polarization calculations using Quantum ESPRESSO?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think in the case where they are separated, as you say, then spin-orbit does not play a role. Otherwise you are looking at spin-constrained calculations. I don't know if QE does this.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-02-24T08:34:36.603" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8735" PostTypeId="1" CreationDate="2022-02-25T07:07:45.713" Score="6" ViewCount="561" Body="&lt;p&gt;Using this input&lt;br /&gt;&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6809/cu-fcc-vc-relax-method-error&quot;&gt;Cu FCC vc-relax method error&lt;/a&gt;&#xA;to calculate Ebulk, I'm trying to calculate the cohesive energy of solid Cu (Ecoh = Eatom − Ebulk). For the Eatom I'm using a similar input but with '&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     calculation = &amp;quot;scf&amp;quot;, &#xA;&#xA;      ibrav = 1, &#xA;       &#xA;      celldm(1) = 30.0,&#xA;&#xA;      K_POINTS (automatic)&#xA;       1 1 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm getting Eatom=-212.83147680 Ry and Ebulk = -213.09295997 Ry. Which will give an Ecoh far from the 3.49 eV (the literature value &lt;a href=&quot;http://www.knowledgedoor.com/2/elements_handbook/cohesive_energy.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.knowledgedoor.com/2/elements_handbook/cohesive_energy.html&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Could this be related to the pseudo I'm using (Cu.pbe-dn-kjpaw_psl.1.0.0.UPF)? Or do I need to modify my input files?&lt;/p&gt;&#xA;" OwnerUserId="4450" LastEditorUserId="4450" LastEditDate="2022-02-25T15:06:51.220" LastActivityDate="2022-02-27T15:25:07.810" Title="Cohesive energy of Cu with Quantum Espresso" Tags="|quantum-espresso|physical-properties-of-materials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8736" PostTypeId="1" AcceptedAnswerId="8754" CreationDate="2022-02-25T09:23:52.643" Score="7" ViewCount="281" Body="&lt;p&gt;I am implementing a Hartree-Fock SCF program with an educational purpose. Although the code works fine using a Core Hamiltonian guess for the SCF iterative process, I want to implement a more accurate initial guess, so I have programmed a simple Extended Hückel guess using a minimal basis set (MINI) and the parameters used by the GAMESS-US software as the diagonal elements of the matrix. This guess works fine for Hartree-Fock SCF calculations using minimal basis sets, but I want to generalize it for any type of basis set (my code support some split-valence basis sets, such as 3-21G). The manuals of some popular quantum chemistry packages state that the density matrix guess obtained using the Extended Hückel Method can be projected onto the desired basis set, but not explaining explicitly how it's done. After some search, I've found that the pyscf package implements a function called &lt;code&gt;project_dm_nr2nr()&lt;/code&gt; which does exactly what I'm looking for. The guide of the program (&lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.scf.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pyscf.org/pyscf_api_docs/pyscf.scf.html&lt;/a&gt;) states that the projection is done using the equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{AO2}=PD_{AO1}P^T&#xA;$$&lt;/span&gt;&#xA;with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;P=S^{-1}_{AO2}\langle AO2|AO1\rangle&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$D_{AO2}$&lt;/span&gt; is the electronic density matrix expressed in the new atomic orbital basis,&lt;span class=&quot;math-container&quot;&gt;$D_{AO1}$&lt;/span&gt;  is the density matrix expressed in the minimal basis set (in which the extended Hückel calculation has been done), &lt;span class=&quot;math-container&quot;&gt;$S^{-1}_{AO2}$&lt;/span&gt; is the inverse of the overlap matrix of the new basis set and &lt;span class=&quot;math-container&quot;&gt;$\langle AO2|AO1\rangle$&lt;/span&gt; is the overlap matrix between the two basis sets.&lt;/p&gt;&#xA;&lt;p&gt;Although I've been searching information about the topic, I haven't found any information about where this formula(in textbooks about quantum chemistry nor the Internet) comes from and I wouldn't like to implement something that I don't understand in my program.I suspect that it is a basic question and I lack the mathematical knowledge for deriving the formula.Could you help me deriving this equation?&lt;/p&gt;&#xA;" OwnerUserId="5016" LastEditorUserId="7" LastEditDate="2022-02-25T16:51:13.857" LastActivityDate="2022-03-02T23:34:18.137" Title="Hartree-Fock Method: Projection of density matrix onto a larger basis set" Tags="|computational-chemistry|hartree-fock|pyscf|" AnswerCount="1" CommentCount="1" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8737" PostTypeId="1" AcceptedAnswerId="8751" CreationDate="2022-02-25T16:24:35.190" Score="17" ViewCount="344" Body="&lt;p&gt;I am currently working with ReaxFF, an empirical reactive force field that can describe chemical bond forming and breaking. The main advantage over &lt;em&gt;ab initio&lt;/em&gt; methods are of course the greatly increased system and time scales, with the drawback of inferior accuracy.&lt;/p&gt;&#xA;&lt;p&gt;Recently, machine learning potentials have introduced themselves as methods that are much cheaper to calculate than &lt;em&gt;ab initio&lt;/em&gt; methods, but with almost on-par accuracy.&lt;/p&gt;&#xA;&lt;p&gt;A few months back, one could argue that empirical force fields are still considerably faster than MLP's. Another typical argument was that much less training data was required to refit a force field than to train a MLP. However, the recent developments in MLP's (for example &lt;a href=&quot;https://arxiv.org/abs/2101.03164&quot; rel=&quot;noreferrer&quot;&gt;NequIP&lt;/a&gt;) are countering all those arguments, as the speed is currently very close, accuracy is much better and the required training set size is decreasing quickly.&lt;/p&gt;&#xA;&lt;p&gt;Is there still an objective argument to justify the use and further development of empirical force fields in a time of machine learning potentials?&lt;/p&gt;&#xA;" OwnerUserId="5019" LastEditorUserId="7" LastEditDate="2022-02-26T02:55:30.250" LastActivityDate="2022-03-02T06:08:05.037" Title="What are the advantages of (semi)-empirical force fields over Machine Learning Potentials?" Tags="|molecular-dynamics|forcefields|machine-learning|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8738" PostTypeId="1" CreationDate="2022-02-26T11:11:26.893" Score="6" ViewCount="128" Body="&lt;p&gt;Given a pdb file that looks like the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TITLE     Generated by gmx solvate&#xA;REMARK    THIS IS A SIMULATION BOX&#xA;CRYST1   12.500   12.500   12.500  90.00  90.00  90.00 P 1           1&#xA;MODEL        1&#xA;ATOM      1  OW  SOL     3       5.300  10.220   4.860  1.00  0.00&#xA;ATOM      2  HW1 SOL     3       6.200   9.970   4.700  1.00  0.00&#xA;ATOM      3  HW2 SOL     3       5.260  11.150   4.630  1.00  0.00&#xA;ATOM      5  OW  SOL     4       8.140   4.780   4.990  1.00  0.00&#xA;ATOM      6  HW1 SOL     4       7.890   5.660   5.270  1.00  0.00&#xA;ATOM      7  HW2 SOL     4       8.110   4.810   4.030  1.00  0.00&#xA;ATOM      9  OW  SOL     5       2.560   5.060   4.270  1.00  0.00&#xA;ATOM     10  HW1 SOL     5       2.880   5.940   4.090  1.00  0.00&#xA;ATOM     11  HW2 SOL     5       2.440   5.040   5.220  1.00  0.00&#xA;ATOM     13  OW  SOL     6       3.340   9.190  13.280  1.00  0.00&#xA;ATOM     14  HW1 SOL     6       3.970   8.660  12.790  1.00  0.00&#xA;ATOM     15  HW2 SOL     6       3.150   9.930  12.710  1.00  0.00&#xA;ATOM     17  OW  SOL     7       6.550   2.610   5.140  1.00  0.00&#xA;ATOM     18  HW1 SOL     7       7.130   3.370   5.160  1.00  0.00&#xA;ATOM     19  HW2 SOL     7       5.900   2.820   4.470  1.00  0.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want to calculate and plot the electric field/electrostatic forces of this configuration. I have tried a few things like &lt;code&gt;g_elpot&lt;/code&gt; but to no affect. Is there a tried and tested method anybody else has ?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastActivityDate="2022-02-26T11:11:26.893" Title="How to calculate and plot the electrostatic forces in a .pdb file" Tags="|molecular-dynamics|gromacs|electrostatic|electric-field|" AnswerCount="0" CommentCount="8" ClosedDate="2022-09-03T02:28:34.113" ContentLicense="CC BY-SA 4.0" />
  <row Id="8739" PostTypeId="1" CreationDate="2022-02-26T14:08:24.693" Score="7" ViewCount="593" Body="&lt;p&gt;I have a &lt;code&gt;.pdb&lt;/code&gt; file containing water molecules.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TITLE     Generated by gmx solvate&#xA;REMARK    THIS IS A SIMULATION BOX&#xA;CRYST1   12.500   12.500   12.500  90.00  90.00  90.00 P 1           1&#xA;MODEL        1&#xA;ATOM      1  OW  SOL     3       5.300  10.220   4.860  1.00  0.00&#xA;ATOM      2  HW1 SOL     3       6.200   9.970   4.700  1.00  0.00&#xA;ATOM      3  HW2 SOL     3       5.260  11.150   4.630  1.00  0.00&#xA;ATOM      5  OW  SOL     4       8.140   4.780   4.990  1.00  0.00&#xA;ATOM      6  HW1 SOL     4       7.890   5.660   5.270  1.00  0.00&#xA;ATOM      7  HW2 SOL     4       8.110   4.810   4.030  1.00  0.00&#xA;ATOM      9  OW  SOL     5       2.560   5.060   4.270  1.00  0.00&#xA;ATOM     10  HW1 SOL     5       2.880   5.940   4.090  1.00  0.00&#xA;ATOM     11  HW2 SOL     5       2.440   5.040   5.220  1.00  0.00&#xA;ATOM     13  OW  SOL     6       3.340   9.190  13.280  1.00  0.00&#xA;ATOM     14  HW1 SOL     6       3.970   8.660  12.790  1.00  0.00&#xA;ATOM     15  HW2 SOL     6       3.150   9.930  12.710  1.00  0.00&#xA;ATOM     17  OW  SOL     7       6.550   2.610   5.140  1.00  0.00&#xA;ATOM     18  HW1 SOL     7       7.130   3.370   5.160  1.00  0.00&#xA;ATOM     19  HW2 SOL     7       5.900   2.820   4.470  1.00  0.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want to generate the charges on these atoms using gromacs. What commands will i run with which force-field to do this ?&lt;/p&gt;&#xA;" OwnerUserId="1102" LastActivityDate="2022-02-28T13:04:56.837" Title="Gromacs generate charges for a .pdb file" Tags="|molecular-dynamics|gromacs|pdb|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8741" PostTypeId="2" ParentId="8735" CreationDate="2022-02-27T15:25:07.810" Score="3" Body="&lt;p&gt;1 Ry is roughly 13.6 eV, so actually you aren't that far off in that calculation.  You find a difference of roughly 0.26 Ry, which multiplied by 13.6 will give you 3.54 eV.  This is a pretty good match considering although you may get different numbers with different psuedopotentials.&lt;/p&gt;&#xA;&lt;p&gt;I will say though, your input file for both calculations differs by more than it should.  You will need to make sure everything you apply to the bulk, is applied to the gas phase atom, except for some things such as the cell relaxation and the kpts should be (1, 1, 1).  You should make sure that energy cutoffs, functional, etc match exactly or your calculations are not comparable.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-02-27T15:25:07.810" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8742" PostTypeId="2" ParentId="6789" CreationDate="2022-02-27T18:40:55.493" Score="5" Body="&lt;p&gt;Relatively big systems can be treated with fragmentation methods that allow one to reduce the cost of the overall computation by using the most accurate and/or expensive approach on the most relevant part of the system and leaving the rest with cheaper and/or less accurate approximations. This allows one to find for an optimal trade-off between cost and accuracy as the user can choose the way that the system will be fragmented and the level of theory used in each part of the system. If the resulting model is cheap enough for geometry optimizations and vibrational frequencies calculations (not all degrees of freedom have to be optimized to cut costs), rate constants can be calculated using convencional transition state theory, &lt;em&gt;i.e.&lt;/em&gt;, the Eyring equation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ k = \frac{k_\mathrm{B}T}{hc^\circ}e^{-\Delta^\ddagger G/RT}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is a couple of fragmentation methods and examples of their use (there are many others)&lt;/p&gt;&#xA;&lt;h2&gt;Fragment Molecular Orbital (FMO)&lt;/h2&gt;&#xA;&lt;p&gt;The fragment molecular orbital method (FMO) can be used to compute very large molecular systems by dividing them into fragments and performing ab initio or density functional calculations of fragments and their dimers, whereby the Coulomb field from the whole system is included. The FMO code is very efficiently parallelized utilizing the generalized distributed data interface.&lt;/p&gt;&#xA;&lt;p&gt;The FMO method was used, for example, to investigate the adsorption of toluene and phenol on a faujasite zeolite, with good accuracy, reproducing &lt;em&gt;ab initio&lt;/em&gt; results.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;K. Kitaura, E. Ikeo, T. Asada, T. Nakano, M. Uebayasi, Fragment molecular orbital method: an approximate computational method for large molecules. &lt;em&gt;Chem. Phys. Lett.&lt;/em&gt; &lt;strong&gt;313&lt;/strong&gt;, 701–706 (1999).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;S. Tanaka, Y. Mochizuki, Y. Komeiji, Y. Okiyama, K. Fukuzawa, Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems. &lt;em&gt;Phys. Chem. Chem. Phys.&lt;/em&gt; &lt;strong&gt;16&lt;/strong&gt;, 10310–10344 (2014).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;D. G. Fedorov, J. H. Jensen, R. C. Deka, K. Kitaura, Covalent bond fragmentation suitable to describe solids in the fragment molecular orbital method. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;112&lt;/strong&gt;, 11808–11816 (2008).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;Surface Integrated Molecular Orbital/Molecular Mechanics (SIMOMM)&lt;/h2&gt;&#xA;&lt;p&gt;Surface Integrated Molecular Orbital/Molecular Mechanics (SIMOMM) is a QM/MM (quantum mechanics/molecular mechanics) optimization scheme for modeling surfaces that is based on the IMOMM (Integrated Molecular Orbital/Molecular Mechanics) approach of Maseras and Morokuma.&lt;/p&gt;&#xA;&lt;p&gt;A combination of the surface integrated molecular orbital/molecular mechanics (SIMOMM) and fragment molecular orbital (FMO) methods was used to investigate the aldol reaction catalyzed by an amine-substituted mesoporous silica nanoparticle (amine-MSN) surface using a large molecular cluster model (&lt;span class=&quot;math-container&quot;&gt;$\ce{Si392O958C6NH361}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;J. R. Shoemaker, L. W. Burggraf, M. S. Gordon, SIMOMM: An integrated molecular orbital/molecular mechanics optimization scheme for surfaces. &lt;em&gt;J. Phys. Chem. A&lt;/em&gt; &lt;strong&gt;103&lt;/strong&gt;, 3245–3251 (1999).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;F. Maseras, K. Morokuma, IMOMM: A new integratedab initio + molecular mechanics geometry optimization scheme of equilibrium structures and transition states. &lt;em&gt;J. Comput. Chem.&lt;/em&gt; &lt;strong&gt;16&lt;/strong&gt;, 1170–1179 (1995).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A. P. de Lima Batista, F. Zahariev, I. I. Slowing, A. A. C. Braga, F. R. Ornellas, M. S. Gordon, Silanol-assisted carbinolamine formation in an Amine-functionalized mesoporous silica surface: Theoretical investigation by fragmentation methods. &lt;em&gt;J. Phys. Chem. B&lt;/em&gt; &lt;strong&gt;120&lt;/strong&gt;, 1660–1669 (2016).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h2&gt;WF-in-DFT Embedding&lt;/h2&gt;&#xA;&lt;p&gt;WF-in-DFT is a projection-based quantum embedding for electronic structure, which provides a formally exact method for density functional theory (DFT) embedding. The method also provides a rigorous and accurate approach for describing a small part of a chemical system at the level of a correlated wavefunction (WF) method while the remainder of the system is described at the level of DFT.&lt;/p&gt;&#xA;&lt;p&gt;This method was used to study the oxidation potentials of neat ethylene carbonate, neat dimethyl carbonate, and 1:1 mixtures of ethylene carbonate and  dimethyl carbonate in a embedding scheme with a CCSD(T) description of the oxidized molecule, a DFT description of the surrounding molecules, and a molecular mechanics (MM) description of more distant molecules.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;S. J. R. Lee, M. Welborn, F. R. Manby, T. F. Miller III, Projection-based wavefunction-in-DFT embedding. &lt;em&gt;Acc. Chem. Res.&lt;/em&gt; &lt;strong&gt;52&lt;/strong&gt;, 1359–1368 (2019).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;T. A. Barnes, J. W. Kaminski, O. Borodin, T. F. Miller III, Ab initio characterization of the electrochemical stability and solvation properties of condensed-phase ethylene carbonate and dimethyl carbonate mixtures. &lt;em&gt;J. Phys. Chem. C&lt;/em&gt; &lt;strong&gt;119&lt;/strong&gt;, 3865–3880 (2015).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2022-02-27T18:40:55.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8743" PostTypeId="2" ParentId="8730" CreationDate="2022-02-27T21:30:40.010" Score="12" Body="&lt;p&gt;In this answer I would like to supplement the existing, concise answers with some detailed contexts.&lt;/p&gt;&#xA;&lt;p&gt;I assume that you are interested in either the thermodynamics or kinetics, or both, of a molecular reaction, and want to derive this information from a computational study. There are a few ways to do this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The most straightforward idea is to put the reactant molecules together and simulate the dynamics of the system frame by frame (typically you would need a frame for every 0.5~2 femtoseconds), until the molecules react; then, from the average time needed for a reaction to occur, one can deduce the rate constant, and if you allow the reaction to go back and forth multiple times, and count how many frames the system is in the product state, you can read out the equilibrium constant. You can also get plenty information about &lt;em&gt;how&lt;/em&gt; the reaction occurs, for example which sequence of formation, distortion and breakage of bonds are involved in the reaction. This is called a &lt;strong&gt;molecular dynamics&lt;/strong&gt; (MD) simulation.&lt;/li&gt;&#xA;&lt;li&gt;When the reaction takes longer than maybe a microsecond, a direct MD simulation is not affordable, as the total number of frames needed to cover the desired time scale is too large. In this case you may speed up the simulation by encouraging the molecules to participate in a reaction, say by applying forces to them to bring them together; this will of course lead to a drastic overestimation of the rate constant, but this overestimation can be mathematically corrected after the simulation. Thus you can, for example, simulate a reaction that takes milliseconds by a simulation of merely a nanosecond. Depending on the exact technique used, this may be called a &lt;strong&gt;metadynamics&lt;/strong&gt; simulation, or it may have some other fancy names.&lt;/li&gt;&#xA;&lt;li&gt;Sometimes, even metadynamics is not affordable, either because the required simulation time is still too long, or because the reaction cannot be easily promoted by an artificial force. In this case one can optimize the transition state of the reaction, and calculate the rate constant from the activation Gibbs free energy using the Eyring equation, which is less accurate (maybe introducing an error of about an order of magnitude to the rate constant) but is considerably cheaper, with a computational cost usually comparable to no more than a picosecond of MD simulation. This is called a &lt;strong&gt;transition state theory&lt;/strong&gt; approach, and is probably much more popular than MD in DFT-based studies, but some may refuse to call it a simulation since it does not involve a frame-by-frame simulation of a real process.&lt;/li&gt;&#xA;&lt;li&gt;Of course, when only the equilibrium constant is desired, one does not even need to find the transition state; simply calculating the Gibbs free energies of the reactant(s) and the product(s) is enough. This can be done in two ways, either by a conformational sampling (e.g. using MD or Monte Carlo), or by Taylor expanding the potential energy surface (PES) at the equilibrium geometries (which encompasses the extremely commonplace approach of estimating the Gibbs free energy from a harmonic approximation, as well as approaches that incorporate anharmonic corrections, e.g. VPT2). Not everyone would call these simulations, although if a conformation sampling is involved and it is done by MD, it can usually be called a simulation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As you can see, the question may be further clarified by specifying whether the word &amp;quot;simulate&amp;quot; encompasses all computational chemistry studies (including transition state theory calculations, where essentially only three &amp;quot;checkpoints&amp;quot; of the reaction are calculated), or only those computational studies where the reaction is simulated frame by frame. Fortunately, the &lt;em&gt;answer&lt;/em&gt; to the question does not depend much on this.&lt;/p&gt;&#xA;&lt;p&gt;If one works under the &lt;strong&gt;Born-Oppenheimer approximation&lt;/strong&gt; and is studying a &lt;strong&gt;ground state reaction&lt;/strong&gt;, then the electrons in the molecules always minimize their energy instantly as soon as the atomic nuclei move to a new set of positions. This means that, in a MD simulation one only needs to simulate the dynamics of the nuclei, which (apart from the dependency on the initial condition and the environment) is completely determined by the adiabatic potential energy surface (PES) of the system. In a transition state theory approach, the activation Gibbs free energy is used instead, and this is also completely determined by the adiabatic PES. As DFT is an exact theory for the ground state electronic energy of a system under any given nuclear configuration, it follows that we can do an exact Born-Oppenheimer MD (BOMD) simulation of an arbitrary reaction, or an exact Gibbs free energy calculation of any species, if we have the exact functional at hand. In this sense the answer to your question is affirmative. Of course we only have access to approximate functionals, which make the simulation approximate as well, sometimes even qualitatively wrong, but you can blame the approximate functionals rather than the DFT theory itself for that.&lt;/p&gt;&#xA;&lt;p&gt;When the reaction &lt;strong&gt;is an excited state reaction&lt;/strong&gt;, DFT cannot be directly used because it only gives ground state energies. However you can calculate excitation energies using TDDFT (through the response functions of the ground state), which means that you can perform excited state MD simulations and Gibbs free energy calculations using TDDFT. Thus, if you consider a TDDFT simulation as a type of DFT simulation (as some people do), the answer in this case is also affirmative. Again, the simulation is only exact when you have access to the exact functional (&lt;em&gt;and&lt;/em&gt; the exact frequency-dependent XC kernel), which you don't have; and if you use approximate functionals and XC kernels, you may sometimes experience qualitative failures, for example the electronic energy may become a complex number at some time during a MD simulation or a geometry optimization, effectively forcing the simulation to abort. Again, you may blame the approximate functionals and XC kernels instead of blaming the DFT theory itself.&lt;/p&gt;&#xA;&lt;p&gt;When the reaction &lt;strong&gt;involves at least two electronic states&lt;/strong&gt; (e.g. when it involves a spin crossover, or an internal conversion from an excited state, or involves a spontaneous excitation to an excited state), the Born-Oppenheimer approximation fails, and one should perform a non-adiabatic MD (NAMD) simulation instead. A NAMD simulation requires not only the electronic energies of the electronic states, but also the non-adiabatic coupling matrix elements (NACMEs) between the electronic states. It was not until the last decade that it was shown that NACMEs can be calculated exactly by TDDFT (you may have a look at &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.accounts.1c00312&quot; rel=&quot;noreferrer&quot;&gt;a review on this topic by me and coworkers&lt;/a&gt;). Therefore, one can exactly simulate a reaction (at least under the assumption that the nuclei are non-relativistic particles) using TDDFT even if the Born-Oppenheimer approximation does not hold, and this is a non-trivial statement! Again, with approximate functionals you only get approximate results, and this time there is an additional kind of possible qualitative failure, namely the approximate NACMEs may become infinite even when the exact NACMEs are finite. In the review linked above, I mentioned a way of getting rid of this divergence at little loss of accuracy, but the resulting equation is probably no longer exact when one uses the exact functional and XC kernel.&lt;/p&gt;&#xA;&lt;p&gt;In summary, the conclusion is: (1) DFT can be used to simulate adiabatic, ground-state reactions; (2) DFT can only be used to simulate non-adiabatic and excited-state reactions if you think a TDDFT simulation can be called a DFT simulation; (3) if you ever find the opposite during an actual simulation, this is due to the additional approximations involved, and is not a problem of (TD)DFT itself - that being said, if the problem is universal among all approximate functionals available to you, this may still force you to abandon DFT and use, e.g. wavefunction methods instead.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-02-27T21:30:40.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8744" PostTypeId="2" ParentId="8739" CreationDate="2022-02-27T23:09:24.593" Score="4" Body="&lt;p&gt;GROMACS keeps internal topology files for common water models. You are clearly using a 3-point water model such as spc, spc/e, tip3p, OPC3 etc. You can also supply your own topology file. Here is a full topology file. Often, molecule parameters are stored in an &lt;code&gt;itp&lt;/code&gt; file, since the topology has other stuff not specific to molecules, such as &lt;code&gt;1-4&lt;/code&gt; interactions, simulation name, numbers of molecules etc. However, for an spc/e simulation, you could supply this topology&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ defaults ]&#xA;; nbfunc        comb-rule       gen-pairs       fudgeLJ fudgeQQ&#xA;  1             2               yes             0.5       0.8333&#xA;&#xA;[ atomtypes ]&#xA;;         name   mass      charge     ptype    sigma(nm)     epsilon(kJ/mol)  &#xA;; SPC/E atoms  &#xA;O1        O1    15.99940   -0.8476      A       0.3166       0.6500000 &#xA;H         H     1.008000   0.4238       A       0.0000       0.0000000 &#xA;&#xA;&#xA;[ moleculetype ]&#xA;SOL     2&#xA;&#xA;[ atoms ]&#xA; 1   O1   1  SD    OW    1    -0.8476   15.99940&#xA; 2   H    1  SD    HW1   1     0.4238   1.00800&#xA; 3   H    1  SD    HW2   1     0.4238   1.00800&#xA;&#xA;#ifndef FLEXIBLE&#xA;&#xA;[ settles ]&#xA;;OW  funct   doh   dhh&#xA;1      1     0.1    0.16330&#xA;&#xA;[ exclusions ]&#xA;1    2    3&#xA;2    1    3&#xA;3    1    2&#xA;&#xA;#else&#xA;&#xA;[ bonds ]&#xA;;   i    j    funct    length    force.c&#xA;1    2         1        0.1          345000&#xA;1    3         1        0.1          345000&#xA;&#xA;[ angles ]&#xA;&#xA;  i   j   k   funct   angle   force.c&#xA; 2    1    3     1    109.47   383&#xA;&#xA;#endif&#xA; &#xA;[ system ]&#xA;spce&#xA;&#xA;[ molecules ]&#xA;SOL 5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that all oxygens will have charge of &lt;code&gt;-0.8476&lt;/code&gt; and all hydrogens will have charge of &lt;code&gt;0.4238&lt;/code&gt;. Different water models will have different charges, but all oxygens and hydrogens in waters will have uniform charges.&lt;/p&gt;&#xA;" OwnerUserId="3606" LastEditorUserId="3606" LastEditDate="2022-02-28T13:04:56.837" LastActivityDate="2022-02-28T13:04:56.837" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8746" PostTypeId="1" CreationDate="2022-02-28T22:57:01.047" Score="6" ViewCount="113" Body="&lt;p&gt;I am trying to understand and implement the Gay-Berne potential, but I do not quite understand how one goes about constructing them.&#xA;I am following &lt;a href=&quot;https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.78.3137&amp;amp;rep=rep1&amp;amp;type=pdf&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; paper to parse through the idea.&lt;/p&gt;&#xA;&lt;p&gt;I understand how Lennard-Jones/Coulombic potentials work in MD engines: every particle has some &lt;span class=&quot;math-container&quot;&gt;$\epsilon, \sigma, q$&lt;/span&gt; associated with it, and these potentials are purely a function of the distance &lt;span class=&quot;math-container&quot;&gt;$r=|\mathbf{r}_{ij}|$&lt;/span&gt; between two particles. It does not depend upon the orientation of the two particles. &lt;span class=&quot;math-container&quot;&gt;$$U = U(r)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the above paper, a particle &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; at position &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt; and orientation &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; with respect to the laboratory frame is represented by a Gaussian function &lt;span class=&quot;math-container&quot;&gt;$G_i (\omega _i, \mathbf{r})$&lt;/span&gt; which is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ G_i(\omega _i, \mathbf{r}) = \exp [-\frac{1}{2}(\mathbf{r}-\mathbf{r}_i)^T M_i ^T S_i ^{-2} M_i (\mathbf{r}-\mathbf{r}_i)]$$&lt;/span&gt;&#xA;where S is a diagonal 'shape' matrix with elements &lt;span class=&quot;math-container&quot;&gt;$\sigma _x, \sigma _y, \sigma _z$&lt;/span&gt;, the axes of the ellipsoid representing the molecule measures with respect to a unit length &lt;span class=&quot;math-container&quot;&gt;$\sigma _0$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$M_i$&lt;/span&gt; is the rotation matrix transforming from laboratory to a molecular frame.&lt;/p&gt;&#xA;&lt;p&gt;What I don't understand is, why do we need a Gaussian function to denote a particle? A 3-dimensional ellipse can be represented with the shape matrix S, and its orientation which can be given by the matrix M. Where does &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; figure into the above definition? If anybody has any recommendations on how to go about understanding the implementation of this idea, I would greatly appreciate it.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-03-08T13:50:03.007" Title="How do biaxial potentials like the Gay-Berne potential work?" Tags="|molecular-dynamics|interatomic-potentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8747" PostTypeId="1" CreationDate="2022-03-01T01:33:39.087" Score="5" ViewCount="773" Body="&lt;p&gt;It seems that Xcrysden is the best software to visualize quantum espresso files.&#xA;I've followed the directions from &lt;a href=&quot;http://www.xcrysden.org/Download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Xcrysden&lt;/a&gt;&#xA;and was able to install it on macOS Monterey using &lt;a href=&quot;https://ports.macports.org/port/xcrysden/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MacPorts&lt;/a&gt;. However, I cannot open even the quantum espresso example files under Xcrysden examples.&lt;/p&gt;&#xA;&lt;p&gt;Was anyone successful in installing it on Macs?&lt;/p&gt;&#xA;&lt;p&gt;Follow some screenshots of the error messages I'm getting.&#xA;As soon as I open it:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/1Crng.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1Crng.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, when I try to open the example file&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Vnr7R.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Vnr7R.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I click on error info I get this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dyld[2342]: Library not loaded: &#xA;@rpath/libgfortran.5.dylib&#xA;  Referenced from: /opt/local/lib/xcrysden-&#xA;1.6.2/pwi2xsf&#xA;  Reason: tried: '/opt/local/lib/xcrysden-&#xA;1.6.2/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/gcc-devel/gcc/aarch64-apple-darwin21/12.0.0/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/gcc-devel/gcc/aarch64-apple-darwin21/12.0.0/../../../libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/xcrysden-1.6.2/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/gcc-devel/gcc/aarch64-apple-darwin21/12.0.0/libgfortran.5.dylib' (no such file), &#xA;'/opt/local/lib/gcc-devel/gcc/aarch64-apple-darwin21/12.0.0/../../../libgfortran.5.dylib' (no such file), &#xA;'/usr/local/lib/libgfortran.5.dylib' (no such file), &#xA;'/usr/lib/libgfortran.5.dylib' (no such file)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4450" LastEditorUserId="7" LastEditDate="2022-03-01T02:21:42.137" LastActivityDate="2022-03-01T02:21:42.137" Title="xcrysden on a macOS Monterey" Tags="|quantum-espresso|visualization-software|" AnswerCount="0" CommentCount="8" ClosedDate="2022-09-03T02:23:55.337" ContentLicense="CC BY-SA 4.0" />
  <row Id="8749" PostTypeId="1" AcceptedAnswerId="8750" CreationDate="2022-03-01T16:10:58.187" Score="10" ViewCount="1167" Body="&lt;p&gt;I have obtained cube files of charge density difference using Quantum Espresso. I am trying to plot these as a contour plot in an aesthetically pleasing manner with good quality. I'm aware that XCrsyDen could do this, but the resolution of the exported file isn't good. Also tried Vesta, but was not satisfied with the results.&#xA;I desire to plot something like figure 5 in this paper (&lt;a href=&quot;https://doi.org/10.1186/s11671-018-2605-3&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1186/s11671-018-2605-3&lt;/a&gt;). Is there some other software/piece of code that can help accomplish similar results?&lt;/p&gt;&#xA;&lt;p&gt;Any help would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2022-03-01T17:44:08.903" Title="Best software to plot Charge densities" Tags="|quantum-espresso|visualization-software|charge-density|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8750" PostTypeId="2" ParentId="8749" CreationDate="2022-03-01T17:44:08.903" Score="10" Body="&lt;p&gt;I am going to agree with Camps here, but I should add to this that you can do a composite approach to making a figure such as this one.  You should follow a procedure as such.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculate the charge density of the system&lt;/li&gt;&#xA;&lt;li&gt;Consider if you are showing the true charge density or if you want to subtract out some sort of reference and show a difference (sometimes useful for dopants / adsorbates etc&lt;/li&gt;&#xA;&lt;li&gt;Plot the atomic structure using your favorite tool and save it, ideally with transparency&lt;/li&gt;&#xA;&lt;li&gt;Plot your contour plot of charge density using MultiWfn and hide the default atomic rendering&lt;/li&gt;&#xA;&lt;li&gt;Overlay your structure ontop of the contour plot&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This means you do not have to use a single tool to do everything and you can keep your figures looking consistent throughout the paper.  This might be too much work for a quick figure to show someone, but this is the best sort of procedure for a published figure of this sort.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-03-01T17:44:08.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8751" PostTypeId="2" ParentId="8737" CreationDate="2022-03-02T06:08:05.037" Score="13" Body="&lt;p&gt;The answer to this question is inevitably going to be opinionated. My opinion is that there are still very good reasons to explore the development of force fields while also pursuing better ML potentials. Here is a list of reasons I think force fields are worth pursuing.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Points in Favor of Force Fields:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Interpretation of the fidelity of force fields is straightforward. Most importantly, it is fairly easy to understand the limitations of a model you fit with physically meaningful parameters&lt;/li&gt;&#xA;&lt;li&gt;Force fields, in principle, should be faster than ML potentials because they inevitably require less computation. In practice, I'm not sure this is going to be the case because it's hard to write efficient GPU code by hand and hence tons of parallelization is left on the table&lt;/li&gt;&#xA;&lt;li&gt;Force fields are easier to distribute and use than ML potentials (this might be a contentious point)&lt;/li&gt;&#xA;&lt;li&gt;Certain types of force fields can be made exceptionally accurate with minimal electronic structure calculations (e.g. see MB-UCB which is a very accurate water model using only calculations up to the water pentamer)&lt;/li&gt;&#xA;&lt;li&gt;This is a meta-reason that I still think is important: scientists learn things about phsyics/chemistry/materials from making a force field. Fitting an ML force field mostly teaches you about computer science.&lt;/li&gt;&#xA;&lt;li&gt;Expanding a force field to include new atoms is often quite straightforward and shouldn't make the existing potential worse. That is, adding an atom to ReaxFF only involves fitting a dozen-ish new paramaters. This is not at all the case for an ML potential because re-training with new data might actually make the existing potential worse, which effectively creates a &amp;quot;version control&amp;quot; problem for reproducing past science. It's not clear how much of a problem that really is though.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Points in Favor of ML Potentials:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The accuracy is almost certainly going to be better with ML potentials in general. Note that this is true somewhat trivially. ML potentials use many orders of magnitude more parameters than force fields, so they better be more accurate. Also, one could argue that ML potentials aren't necessarily always going to be more accurate. This is because they are often restricted to DFT-based methods and many existing force fields are more accurate than DFT for specific systems.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;You get a GPU-based potential &amp;quot;for free&amp;quot;. This, in my mind, is actually the biggest selling point for ML potentials. Scientists always want larger, better models to simulate, and ML force fields give you parallelism for free since all the infrastructure of ML already runs on GPUs.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;ML force fields can be bootstrapped to become more accurate. I'm thinking of recent &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;-ML models where a cheaper method is used to generate a full force field and then a smaller sample of configurations is used to correct this model to a higher-accuracy method. There's not an obvious parallel to this for force fields.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Here is the biggest problem restricting machine learning potentials from taking over. Fitting a generic machine learned potential is almost entirely a sampling problem, and there is an infinite amount of chemical space that needs to be sampled. Many-body expansion techniques avoid this problem by limiting the search to small sub-systems. This then introduces a problem of combinatorial complexity in how many atoms can be included in the model. MOB-ML circumvents the combinatorial explosion of atom-types by fitting to orbital information. The downside of this is that it requires orbitals and hence MOB-ML calculations are slow.&lt;/p&gt;&#xA;&lt;p&gt;Basically, ML is greedy for data. The mechanics of how to fit force fields is actually quite well understood at this point. So, people are going to need molecular configurations. A lot of these configurations are going to come from force fields, which then get labelled using electronic structure.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I'm sure there are tons of points on both sides I missed, as I wrote this somewhat stream of consciousness. The reality is that people will work on both sides of things (I personally am working on both sides of this). This is good. The two techniques can and will feed off of each other. For instance, doing &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;-ML off of relatively crude force fields seems like a possibly useful idea.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-03-02T06:08:05.037" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8752" PostTypeId="1" CreationDate="2022-03-02T07:23:43.043" Score="17" ViewCount="4229" Body="&lt;p&gt;I would like to know how to choose the best GPU on the basis of its FP32 or FP64 efficiency, depending on different types of simulations.&lt;/p&gt;&#xA;&lt;p&gt;In brief I would like to know what types of simulations work in single precision, versus the types that require double-precision.&lt;/p&gt;&#xA;" OwnerUserId="982" LastEditorUserId="5" LastEditDate="2022-03-02T18:52:23.567" LastActivityDate="2022-03-04T00:32:52.283" Title="I am considering to purchase a GPU. What calculations would need FP32, and what would need FP64?" Tags="|molecular-dynamics|quantum-chemistry|one-topic-per-answer|high-performance-computing|graphical-processing-unit|" AnswerCount="4" CommentCount="16" ContentLicense="CC BY-SA 4.0" />
  <row Id="8753" PostTypeId="2" ParentId="8752" CreationDate="2022-03-02T18:51:44.830" Score="16" Body="&lt;h2&gt;Numerical Feynman integrals&lt;/h2&gt;&#xA;&lt;p&gt;I wrote a software to &amp;quot;exact quantum dynamics&amp;quot; calculations, meaning that given a density matrix of a system under the influence of noise at one point in time, the program gives you the quantum mechanical time-evolution of the density matrix with no semi-classical, Markovian, weak-coupling, or other physical approximations, as long as you give the program the temperature and the Hamiltonian describing the system and the noise from its environment. The program accomplishes this by calculating the appropriate double Feynman integral numerically, and more details can be found in &lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/23384/2293&quot;&gt;this answer at Quantum Computing Stack Exchange&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As long as the GPU has enough RAM, the calculation is much faster on a GPU than a CPU, and this difference increases as you try to simulate the system dynamics for more and more picoseconds (all figures below come from &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465513002294?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;my 2013 paper about the software, which is called &amp;quot;FeynDyn&amp;quot; since is uses the &lt;em&gt;&lt;strong&gt;Feyn&lt;/strong&gt;&lt;/em&gt;man integral to calculate &lt;em&gt;&lt;strong&gt;dyn&lt;/strong&gt;&lt;/em&gt;amics&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/gyXAp.png&quot; Width=&quot;500&quot;&gt;&#xA;&lt;p&gt;You can see in the figure below that the speed-up gained by using the GPU also increased with the amount of RAM that the calculation required (the RAM required can increase depending on the size of the system, for example) up to about a 20x speed-up, but since the figure below was done &lt;a href=&quot;https://arxiv.org/abs/1205.6872&quot; rel=&quot;noreferrer&quot;&gt;prior to May 2012&lt;/a&gt; I couldn't go beyond 4GB on the GPU! I can only imagine what this would look like now in 2022:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VlDdy.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VlDdy.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The same paper showed that single-precision and double-precision gave almost the same result for every version of the problem except the ones in which the influence of the noise was very strong (rapid loss of quantum coherence in the system of interest):&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/jcaDy.png&quot; Width=&quot;500&quot;&gt;&#xA;&lt;p&gt;&lt;strong&gt;Therefore, if you want to calculate open quantum system dynamics by numerically calculating the appropriate Feynman integral, the last diagram&#xA;here shows that single-precision is almost always enough.&lt;/strong&gt; &lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-03-02T18:51:44.830" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8754" PostTypeId="2" ParentId="8736" CreationDate="2022-03-02T23:08:59.663" Score="4" Body="&lt;p&gt;The spin-&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; density matrix is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mathbf{P}^\sigma = \mathbf{C}_\text{occ}^\sigma (\mathbf{C}_\text{occ}^\sigma)^\text{T} $$&lt;/span&gt;&#xA;so if we know how the orbital coefficients &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}^\sigma$&lt;/span&gt; transform, then we know how &lt;span class=&quot;math-container&quot;&gt;$\mathbf{P}^\sigma$&lt;/span&gt; transforms.&lt;/p&gt;&#xA;&lt;p&gt;Now, the orbitals are given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ |\psi_{i \sigma} \rangle = \sum_\alpha C_{\alpha i}^\sigma |\chi_\alpha\rangle $$&lt;/span&gt;&#xA;Inserting the resolution of the identity&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mathbf{1} = \sum_{AB} |A\rangle \langle A | B \rangle^{-1} \langle B|  $$&lt;/span&gt;&#xA;from the left of the right-hand side we get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ |\psi_{i \sigma} \rangle = \sum_\alpha C^\sigma_{\alpha i} |A\rangle \langle A | B \rangle^{-1} \langle B|\chi_\alpha\rangle \equiv \sum_A C^\sigma_{Ai} |A\rangle  $$&lt;/span&gt;&#xA;from which we can read the transformed coefficients&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ C^\sigma_{Ai} = \sum_\alpha \langle A | B \rangle^{-1} \langle B|\chi_\alpha\rangle C^\sigma_{\alpha i}.  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I call the basis &lt;span class=&quot;math-container&quot;&gt;$|\chi_\alpha \rangle$&lt;/span&gt; basis 1, and the basis &lt;span class=&quot;math-container&quot;&gt;$|A\rangle$&lt;/span&gt; basis 2, this equation can be rewritten in compact matrix notation as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mathbf{C}^\sigma_{2} = \mathbf{S}_{22}^{-1} \mathbf{S}_{21} \mathbf{C}^\sigma_{1}.  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The equation for projecting the density matrix follows trivially:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mathbf{P}^\sigma_{2} = \mathbf{S}_{22}^{-1} \mathbf{S}_{21} \mathbf{C}^\sigma_{1\text{, occ}} \left(\mathbf{S}_{22}^{-1} \mathbf{S}_{21} \mathbf{C}^\sigma_{1\text{, occ}}\right)^\text{T} = \mathbf{S}_{22}^{-1} \mathbf{S}_{21} \mathbf{C}^\sigma_{1\text{, occ}} (\mathbf{C}^\sigma_{1\text{, occ}})^\text{T} \mathbf{S}_{12}^\text{T} = \mathbf{S}_{22}^{-1} \mathbf{S}_{21} \mathbf{P}^\sigma_{11}  \mathbf{S}_{12} \mathbf{S}_{22}^{-1}   $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that these equations don't make any assumptions of the size of the basis sets, or the level of theory used.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-03-02T23:34:18.137" LastActivityDate="2022-03-02T23:34:18.137" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8755" PostTypeId="1" CreationDate="2022-03-02T23:10:19.583" Score="9" ViewCount="107" Body="&lt;p&gt;The linked question(s) below describes a DIY project to simulate how Xenes (honeycomb nets of atoms like graphehe) behave on single crystal surfaces. Behaviors include rotation, strain, and heigh modulations (moires, bucklings, etc.) and will in the future include defects.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scicomp.stackexchange.com/q/40634/17869&quot;&gt;How amenable is this 2D Frenkel–Kontorova-like energy minimization problem in Python to the use of a modest PC + GPU? (Heavy reliance on indexing)&lt;/a&gt;  (SciComp SE)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scicomp.stackexchange.com/a/40614/17869&quot;&gt;Going to try to move some of my scipy/numpy calculation to a new GPU, how to avoid disappointing results?&lt;/a&gt;  (SciComp SE)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The simplest implementation could just use a &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lennard-Jones potential&lt;/a&gt; for Xene bond lengths, ignore bond angles and use a sinusoidal-like periodic potential for interaction with an unperturbed crystal surface as shown below.&lt;/p&gt;&#xA;&lt;p&gt;But now I am considering &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1053/201&quot;&gt;get my feet wet&lt;/a&gt; in classical molecular dynamics proper, and starting to incorporate some open source molecular dynamics &lt;a href=&quot;https://en.wikipedia.org/wiki/Force_field_(chemistry)&quot; rel=&quot;nofollow noreferrer&quot;&gt;force fields&lt;/a&gt; by using parameterizations in my script.&lt;/p&gt;&#xA;&lt;p&gt;My guess is that open source force fields are likely to be in a form that is easy to plug in to open source MD software, and someone might comment &amp;quot;Why don't you just run program X instead of writing something likely to be less powerful and slower?&amp;quot; and the answer to that is because that's just my &lt;em&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Modus_operandi&quot; rel=&quot;nofollow noreferrer&quot;&gt;modus operandi&lt;/a&gt;&lt;/em&gt;  I always try to calculate things first myself before running someone else's program for reasons of fun and insight.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; DIY molecular dynamics for Xenes on crystal surfaces; where can I get applicable open-source force field parameters that I can use in my scripts?&lt;/p&gt;&#xA;&lt;p&gt;Here are the types of atoms I'm interested in; I certainly don't need all of them, so any place to start will already be helpful.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Xenes of interest include honeycombs of C, Pb, Si, Ge, Sn, BN, SiC, (graphene, plumbene, silicene, germanene, stanene, 2D boron nitride and silicon carbide)...&lt;/li&gt;&#xA;&lt;li&gt;Crystal surfaces of interest include Pb, Au, Ag, hexagonal BN, hexagonal SiC, epitaxial graphene&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Related:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1412/201&quot;&gt;What is the cutting edge for open-source Force-Field generation?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://openforcefield.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://openforcefield.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/q/123524/16035&quot;&gt;Are all stable Xenes (graphene-like 2D honeycomb sheets) buckled?&lt;/a&gt; (Chemistry SE)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My nascent DIY model, from &lt;a href=&quot;https://scicomp.stackexchange.com/q/40634/17869&quot;&gt;here&lt;/a&gt; (click for larger)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QzZBk.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QzZBkm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2022-03-11T12:32:14.743" LastActivityDate="2022-03-11T12:32:14.743" Title="DIY molecular dynamics for Xenes on crystal surfaces; where can I get applicable open-source force field parameters that I can use in my scripts?" Tags="|molecular-dynamics|surfaces|forcefields|interatomic-potentials|graphene|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8756" PostTypeId="2" ParentId="8720" CreationDate="2022-03-02T23:32:11.667" Score="7" Body="&lt;p&gt;The xc energy is given by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_\text{xc} = \int n({\bf r}) \epsilon_\text{xc} ({\bf r}) {\rm d}^3r \equiv \int f_\text{xc} ({\bf r}) {\rm d}^3r $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\epsilon_\text{xc}$&lt;/span&gt; is the energy density &lt;em&gt;per particle&lt;/em&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_\text{xc}$&lt;/span&gt; is the energy density. What Libxc gives you is &lt;span class=&quot;math-container&quot;&gt;$\epsilon_\text{xc}$&lt;/span&gt; and derivatives of &lt;span class=&quot;math-container&quot;&gt;$f_\text{xc}$&lt;/span&gt;, such as &lt;span class=&quot;math-container&quot;&gt;$\partial f_\text{xc} / \partial n_\sigma$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\partial f_\text{xc} / \partial \gamma_{\sigma \sigma'}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\partial f_\text{xc} / \partial \nabla^2 n_\sigma$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\partial f_\text{xc} / \partial \tau_\sigma$&lt;/span&gt; that you need for e.g. self-consistent field calculations.&lt;/p&gt;&#xA;&lt;p&gt;How you actually use these variables depends on the numerical approach. The approach you have described above is the one based on a real-space potential &lt;span class=&quot;math-container&quot;&gt;$v({\bf r})$&lt;/span&gt;, which is simple for the LDA but gets a bit hairy already for GGAs since you need to evaluate the divergence of a term that contains both the density and the density functional.&lt;/p&gt;&#xA;&lt;p&gt;If you have a basis set, you can use integration by parts to get rid of the divergences and end up with a straightforward quadrature problem as discussed e.g. in our recent open access review article: &lt;a href=&quot;https://doi.org/10.3390/molecules25051218&quot; rel=&quot;noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;. This also works nicely with numerical basis sets, as I've demonstrated e.g. in &lt;a href=&quot;https://doi.org/10.1002/qua.25945&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25945 (2019)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you have a basis set, you can also evaluate the real-space potential &lt;span class=&quot;math-container&quot;&gt;$v({\bf r})$&lt;/span&gt; in an analytical fashion. This leads to higher-order derivatives of &lt;span class=&quot;math-container&quot;&gt;$f_\text{xc}$&lt;/span&gt; which are also provided by Libxc as well as derivatives of the density; I have demonstrated this for atoms in &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.101.012516&quot; rel=&quot;noreferrer&quot;&gt;Phys. Rev. A 101, 012516 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In contrast, as far as I know, programs employing the finite difference approach like dftatom evaluate the GGA contribution to the potential by finite differences.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-03-02T23:32:11.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8757" PostTypeId="2" ParentId="8752" CreationDate="2022-03-03T00:33:26.087" Score="11" Body="&lt;h1&gt;Forcefield-based Molecular Dynamics (Molecular Mechanics)&lt;/h1&gt;&#xA;&lt;p&gt;It is common for molecular dynamics programs have the option of using mixed precision approaches on GPUs. This means that the many individual interactions might be calculated in single precision, and then they get added up in (for example) double precision. The result is that these give great performance on less expensive (single-precision) GPU hardware, while still having almost as much accuracy as full double precision.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://ambermd.org/gpus16/benchmarks.htm&quot; rel=&quot;noreferrer&quot;&gt;An older set of benchmarks for Amber&lt;/a&gt; provides a metric of &amp;quot;dollars per nanoseconds per day&amp;quot; for a few GPUs (numbers now outdated). If you're shopping, this is the metric you want -- spend the least money to get the most performance.  Not surprisingly, gaming-class single precision GPUs are a much better deal for this kind of simulation than full double precision GPUs. Note that &lt;a href=&quot;http://ambermd.org/GPUSupport.php&quot; rel=&quot;noreferrer&quot;&gt;more recent information on running Amber on GPUs&lt;/a&gt; is available, but they no longer provide numbers in terms of dollar cost.&lt;/p&gt;&#xA;&lt;p&gt;I focus on Amber here because they have good documentation of these issues; the same principles would apply to other programs that use mixed precision techniques. A few relevant papers on mixed precision calculations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Mixed single/double precision in Amber: &lt;a href=&quot;https://doi.org/10.1021/ct200909j&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/ct200909j&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Mixed single/fixed precision in Amber: &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2012.09.022&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1016/j.cpc.2012.09.022&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2022-03-03T00:33:26.087" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8758" PostTypeId="2" ParentId="8752" CreationDate="2022-03-03T04:02:22.577" Score="11" Body="&lt;h2&gt;Classical Molecular Dynamics&lt;/h2&gt;&#xA;&lt;p&gt;I have been using the &lt;a href=&quot;https://www.lammps.org/&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt; classical molecular dynamics package and several GPU computational codes written by myself for my research activities. While working, I have seen that most calculations (over 95% of the time) have the same result in all precision settings single, mixed and double.&lt;/p&gt;&#xA;&lt;p&gt;However, in certain systems (mostly inhomogeneous ones), there have been variations between single and double precision results. This has happened to me independent of the pair-potentials being used, and so I would not recommend predicting whether the calculations you plan to do are best off when done with a specific precision setting (since a GPU can last for at least 5-6 years and the calculations being done can change during this time). Because of this, I usually test my calculations in both mixed and double precision modes to ensure the accuracy of the results.&lt;/p&gt;&#xA;&lt;p&gt;That said, you should consider the requirement of other features such as ECC and memory capacity as well. For example, compare this &lt;a href=&quot;https://www.techpowerup.com/gpu-specs/geforce-rtx-3080.c3621&quot; rel=&quot;noreferrer&quot;&gt;RTX3080&lt;/a&gt; with the &lt;a href=&quot;https://www.techpowerup.com/gpu-specs/rtx-a5000.c3748&quot; rel=&quot;noreferrer&quot;&gt;RTX A5000&lt;/a&gt;. They are both based on the GA102 die, but the FP64 performance and memory capacity are significantly different (not to mention the price). However, I would expect both to perform similar when using single or mixed precision modes.&lt;/p&gt;&#xA;&lt;p&gt;Also I should mention that &lt;a href=&quot;https://compubench.com/result.jsp&quot; rel=&quot;noreferrer&quot;&gt;CompuBench&lt;/a&gt; gives a pretty good overlook of how each GPU performs based on the kind of calculation being done. However I do not know about the accuracy of the results, but the overall scaling seems reasonable.&lt;/p&gt;&#xA;&lt;p&gt;Also if you are thinking about the reliability of the consumer GPUs, I have been using an RTX2070 Super ROG Strix for my calculations for well over two years. The card has been used at almost 100% capacity 24x7 in a particularly warm and dusty environment and has experienced multiple sudden shut downs due to power failure (the only time when the GPU stays unused). So far, I have not seen a single problem with the card and I can say for certain that it performs much better than a Quadro RTX A4000 which is twice as expensive.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="4232" LastEditDate="2022-03-03T07:50:34.497" LastActivityDate="2022-03-03T07:50:34.497" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8759" PostTypeId="2" ParentId="8637" CreationDate="2022-03-03T04:24:26.530" Score="2" Body="&lt;p&gt;Numerical integration for evenly-spaced data can be performed using &lt;code&gt;trapz&lt;/code&gt; function in &lt;code&gt;MATLAB&lt;/code&gt;. Here infinite integration can assumed to integrate between extrema of data.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;d_center=trapz(E,P)/trapz(E)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Trapezoidal rule of integration&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\int_{a}^{b}f(x)dx=\frac{b-a}{2N}( f(x_{1})+2f(x_{2})...+2f(x_{n})+f(x_{n+1}))$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-03-03T04:24:26.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8760" PostTypeId="1" AcceptedAnswerId="8762" CreationDate="2022-03-03T06:25:56.920" Score="10" ViewCount="313" Body="&lt;p&gt;The question below describes my plan to make a basic molecular dynamics calculation using a Python script rather than a canned, self-contained program.&lt;/p&gt;&#xA;&lt;p&gt;There seems to be three parts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;a model of the honeycomb net and substrate atoms&lt;/li&gt;&#xA;&lt;li&gt;an expression for energy based on atomic positions&lt;/li&gt;&#xA;&lt;li&gt;an energy minimization procedure (the topic of this question)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The two procedures I can imagine implementing are&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Monte_Carlo_method&quot; rel=&quot;noreferrer&quot;&gt;Monte-carlo method&lt;/a&gt; jiggle the positions randomly using some pseudo-temperature parameter, keep the new positions if energy goes down and flip a coin about keeping the new positions if higher based on *how much higher) it is.&lt;/li&gt;&#xA;&lt;li&gt;Kinematically using a damped differential equation and a standard ODE solver for all atomic positions.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;These are general tools that I'm aware of and know how to implement in general and I can start with these no problem. But are these the numerical techniques that proper classical molecular dynamical simulations use, or are there different and/or better ways?&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8755/201&quot;&gt;DIY molecular dynamics for Xenes on crystal surfaces; where can I get applicable open-source force field parameters that I can use in my scripts?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;My nascent DIY model, from &lt;a href=&quot;https://scicomp.stackexchange.com/q/40634/17869&quot;&gt;here&lt;/a&gt; (click for larger)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QzZBk.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QzZBkm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="201" LastActivityDate="2022-03-03T11:21:02.940" Title="Basics of numerical energy minimization techniques used in molecular dynamics?" Tags="|molecular-dynamics|mathematical-modeling|forcefields|finite-difference-time-domain|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8761" PostTypeId="1" CreationDate="2022-03-03T06:43:23.287" Score="5" ViewCount="150" Body="&lt;p&gt;I’m learning to use PyTorch Geometric, I tried to replicate the WL kernel written by the PyG developers on GitHub (&lt;a href=&quot;https://github.com/pyg-team/pytorch_geometric/blob/master/examples/wl_kernel.py&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/pyg-team/pytorch_geometric/blob/master/examples/wl_kernel.py&lt;/a&gt;), but when I run the program I get this error which I can’t solve:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sL1uC.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sL1uC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I use a custom dataset where the data looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Data(x=[9, 9], edge_index=[2, 18], edge_attr=[18, 2], y=[0])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Exactly like in the example. Which one had the same problem and was able to solve it? Thank you all!&lt;/p&gt;&#xA;" OwnerUserId="4898" LastActivityDate="2022-03-16T15:31:34.807" Title="PyTorch WL Kernel" Tags="|python|machine-learning|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8762" PostTypeId="2" ParentId="8760" CreationDate="2022-03-03T11:21:02.940" Score="6" Body="&lt;p&gt;AFAIK most MD codes do something like conjugate gradients or BFGS for energy minimization. Your option 1 is Metropolis Monte Carlo, while option 2 sounds like the FIRE algorithm.&lt;/p&gt;&#xA;&lt;p&gt;However, why implement something yourself, when there is a multitude of solvers already available in e.g. scipy? See &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html&quot; rel=&quot;noreferrer&quot;&gt;https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html&lt;/a&gt;, for example.&#xA;You could just interface to these routines and get a lot of functionality &amp;quot;for free&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-03-03T11:21:02.940" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8763" PostTypeId="1" CreationDate="2022-03-03T22:38:27.283" Score="6" ViewCount="58" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8762/201&quot;&gt;This answer to &lt;em&gt;Basics of numerical energy minimization techniques used in molecular dynamics?&lt;/em&gt;&lt;/a&gt; mentions&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;conjugate gradients, BFGS for energy minimization&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Metropolis Monte Carlo (and the) the FIRE algorithm&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;for dynamical simulations.&lt;/p&gt;&#xA;&lt;p&gt;While the metropolis method has the potential to discover many adjacent minima depending on how high of a temperature it starts with and how rapidly it cools (&lt;a href=&quot;https://en.wikipedia.org/wiki/Simulated_annealing#The_annealing_schedule&quot; rel=&quot;noreferrer&quot;&gt;annealing schedule&lt;/a&gt;) the others will tend to find minima near where they are initialized and not necessarily find the global minimum.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What are the basics of configuration initialization strategies used in molecular dynamics simulations? Is this an art based on intuition and a &amp;quot;feel&amp;quot; for the problem? Does one first start with a project budget (e.g. &amp;quot;I've got three months to get results and \$10,000 to spend on supercomputer time&amp;quot;) and sprinkle it randomly over initial configuration space?&lt;/p&gt;&#xA;&lt;p&gt;Of course different types of problems may require very different strategies and all answers are welcome. But for what I'm doing the questions below describes my plan to make a basic molecular dynamics calculation using a Python script rather than a canned, self-contained program.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scicomp.stackexchange.com/q/40634/17869&quot;&gt;How amenable is this 2D Frenkel–Kontorova-like energy minimization problem in Python to the use of a modest PC + GPU? (Heavy reliance on indexing)&lt;/a&gt;  (SciComp SE)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://scicomp.stackexchange.com/a/40614/17869&quot;&gt;Going to try to move some of my scipy/numpy calculation to a new GPU, how to avoid disappointing results?&lt;/a&gt;  (SciComp SE)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8755/201&quot;&gt;DIY molecular dynamics for Xenes on crystal surfaces; where can I get applicable open-source force field parameters that I can use in my scripts?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="201" LastActivityDate="2022-03-03T22:38:27.283" Title="Basics of configuration initialization strategies used in molecular dynamics?" Tags="|molecular-dynamics|mathematical-modeling|" AnswerCount="0" CommentCount="12" ClosedDate="2022-03-04T04:22:56.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="8764" PostTypeId="1" AcceptedAnswerId="8856" CreationDate="2022-03-04T00:01:47.260" Score="6" ViewCount="2735" Body="&lt;p&gt;I learned how to create an initial data file for LAMMPS using VMD, So I can get all the position and bonding information.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;/p&gt;&#xA;&lt;p&gt;I have a LAMMPS initial data file which only has the positions of CNT atoms in it. I want to load that same CNT file to VMD and create another initial input file in which the positions are the same as my own file but I also have the bond and angle information. Is that possible?&lt;/p&gt;&#xA;&lt;p&gt;How to load an initial LAMMPS data file into VMD? how to see the molecule?&lt;/p&gt;&#xA;&lt;p&gt;Thank you so much for your help&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-03-27T06:24:42.947" Title="How do I use a LAMMPS initial data file in VMD to see the material structure?" Tags="|lammps|vmd|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8765" PostTypeId="2" ParentId="8752" CreationDate="2022-03-04T00:32:52.283" Score="12" Body="&lt;h2&gt;First principles simulations&lt;/h2&gt;&#xA;&lt;p&gt;When simulating chemicals or materials with quantum mechanical methods, it is common to require &lt;em&gt;at least&lt;/em&gt; FP64 precision in order to get reliable results. One reason for this is the requirement that electronic states (or any fermionic states) are strictly orthonormal, which usually involves the calculation and inversion of matrices which can be ill-conditioned. Similarly, the diagonalisation of a Hamiltonian can also be an ill-conditioned problem, for example when states are nearly degenerate.&lt;/p&gt;&#xA;&lt;h4&gt;Ill-conditioning&lt;/h4&gt;&#xA;&lt;p&gt;The term &amp;quot;ill-conditioned&amp;quot; refers to problems where small errors in the input to an operation can give large errors in the output. For example, suppose that we wish to invert the matrix &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}$&lt;/span&gt;, where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{M}=\left(\begin{array}{cc}&#xA;1 &amp;amp; 2\\&#xA;\frac{9}{8} &amp;amp; 2&#xA;\end{array}\right)&#xA;$$&lt;/span&gt;&#xA;First, let's write the matrix in decimal form to four significant figures, so that our matrix is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{M}_\mathrm{4sf}=\left(\begin{array}{cc}&#xA;1.000 &amp;amp; 2.000\\&#xA;1.125 &amp;amp; 2.000&#xA;\end{array}\right).&#xA;$$&lt;/span&gt;&#xA;In this case, our decimal representation is exact. If we also assume that our inversion operation is perfect, i.e. that it works internally in infinite precision, we will obtain the inverse as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{M}_\mathrm{4sf}^{-1}=\left(\begin{array}{cc}&#xA;-8.000 &amp;amp; 8.000\\&#xA;4.500 &amp;amp; -4.000&#xA;\end{array}\right),&#xA;$$&lt;/span&gt;&#xA;which is easily shown to be the correct answer.&lt;/p&gt;&#xA;&lt;p&gt;Now let us try the same calculation with only two significant figures of accuracy for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}$&lt;/span&gt;. We have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{M}_\mathrm{2sf}=\left(\begin{array}{cc}&#xA;1.0 &amp;amp; 2.0\\&#xA;1.1 &amp;amp; 2.0&#xA;\end{array}\right),&#xA;$$&lt;/span&gt;&#xA;which is an exact representation of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}$&lt;/span&gt; except for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}_{21}$&lt;/span&gt;, which has an error of 0.025 (approximately 2.3%). Giving &lt;em&gt;this&lt;/em&gt; matrix to our infinitely-precise inversion algorithm, we obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{M}_\mathrm{2sf}^{-1}=\left(\begin{array}{cc}&#xA;-10 &amp;amp; 10\\&#xA;5.5 &amp;amp; 5.0&#xA;\end{array}\right).&#xA;$$&lt;/span&gt;&#xA;Comparing this to &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}_\mathrm{4sf}^{-1}$&lt;/span&gt; we see that our &lt;span class=&quot;math-container&quot;&gt;$\sim 2\%$&lt;/span&gt; error in a single element of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}$&lt;/span&gt; has led to errors of over 20% in &lt;em&gt;every&lt;/em&gt; element of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{M}_\mathrm{2sf}^{-1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Sloshing instabilities&lt;/h4&gt;&#xA;&lt;p&gt;One well-known example in materials modelling is the problem of &amp;quot;charge-sloshing&amp;quot; instabilities in self-consistent field (SCF) methods. In a simple SCF method for a density functional theory calculation, we might start with a guess for the electronic charge density &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt;, and then:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Compute the potential &lt;span class=&quot;math-container&quot;&gt;$V[\rho]$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Solve the Kohn-Sham equations with this &lt;span class=&quot;math-container&quot;&gt;$V[\rho]$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Use the Kohn-Sham states to construct a new density &lt;span class=&quot;math-container&quot;&gt;$\rho_\mathrm{new}(r)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;If &lt;span class=&quot;math-container&quot;&gt;$\vert\rho_\mathrm{new}-\rho|$&lt;/span&gt; is small, stop; else set &lt;span class=&quot;math-container&quot;&gt;$\rho = \rho_\mathrm{new}$&lt;/span&gt; and go to step 1.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This simple method fails (diverges) for all but the smallest materials simulations, because it is ill-conditioned. The ill-conditioning arises primarily from the Hartree contribution to the potential, &lt;span class=&quot;math-container&quot;&gt;$V_\mathrm{H}[\rho]$&lt;/span&gt;. In reciprocal-space, this has the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_\mathrm{H}(G) = \frac{\rho(G)}{\vert G \vert^2}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$G\neq 0$&lt;/span&gt; is a reciprocal lattice vector, and we've used Hartree atomic units.&lt;/p&gt;&#xA;&lt;p&gt;During the calculation, the density has some error &lt;span class=&quot;math-container&quot;&gt;$\delta\rho$&lt;/span&gt;, and so the calculated Hartree potential also has an error&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\delta V_\mathrm{H}(G) = \frac{\delta\rho(G)}{\vert G \vert^2}.&#xA;$$&lt;/span&gt;&#xA;The trouble is, as we increase the simulation size in real-space, we &lt;em&gt;decrease&lt;/em&gt; the size of the smallest reciprocal vectors, and so there are some wavevectors for which &lt;span class=&quot;math-container&quot;&gt;$|G|^2$&lt;/span&gt; is very small indeed. Any error in the density for these wavevectors will be amplified enormously in the Hartree potential. Thus, even a small error in the density can lead to a large error in the potential.&lt;/p&gt;&#xA;&lt;p&gt;Since the potential is used to construct the Kohn-Sham equations in the next iteration, the new Kohn-Sham states will also have a large error - and these states are used to construct the new density. In this way, a small error in the density in one iteration leads to a large error in the density for the next iteration - not a good idea for a stable algorithm!&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-03-04T00:32:52.283" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8766" PostTypeId="1" AcceptedAnswerId="8805" CreationDate="2022-03-05T22:53:32.063" Score="6" ViewCount="182" Body="&lt;h3&gt;Introduction/Preamble&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8762/201&quot;&gt;@SusiLehtola's answer to &lt;em&gt;Basics of numerical energy minimization techniques used in molecular dynamics?&lt;/em&gt;&lt;/a&gt; mentions conjugate gradients, BFGS for energy minimization, Metropolis Monte Carlo, and the FIRE algorithm for dynamical simulations.&lt;/p&gt;&#xA;&lt;p&gt;The FIRE algorithm was introduced in the 2006 Phys. Rev. Letter &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.170201&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structural Relaxation Made Simple&lt;/a&gt; (Bitzek, Koskinen, Gähler, Moseler and Gumbsch, PRL &lt;strong&gt;97&lt;/strong&gt;, 170201, also available &lt;a href=&quot;https://www.math.uni-bielefeld.de/%7Egaehler/papers/fire.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://www.researchgate.net/publication/6644744_Structural_Relaxation_Made_Simple&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;, &lt;a href=&quot;https://www.math.uni-bielefeld.de/%7Egaehler/papers/fire_old.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;3&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Consider a blind skier searching for the fastest way to the bottom of a valley in an unknown mountain range described by the potential energy landscape &lt;span class=&quot;math-container&quot;&gt;$E(x)$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$x = (x_1,x_2)$&lt;/span&gt;. Assuming that the skier is able to retard and steer we would recommend him to use the following equation of motion:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{\dot{v}}(t) = \mathbf{F}(t)/m - \gamma(t) |\mathbf{v}(t)| \left(\mathbf{\hat{v}}(t) - \mathbf{\hat{F}}(t) \right) \tag{1}\label{eq1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with the mass m, the velocity &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} = \mathbf{\dot{x}}$&lt;/span&gt;, the force &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F} =  \nabla E(\mathbf{x})$&lt;/span&gt;, and hat for a unit vector. We recommend as strategy that the skier introduces acceleration in a direction that is ‘steeper’ than the current direction of motion via the function &lt;span class=&quot;math-container&quot;&gt;$\gamma(t)$&lt;/span&gt;  if the power &lt;span class=&quot;math-container&quot;&gt;$P(t) = \mathbf{F}(t) \cdot \mathbf{v}(t)$&lt;/span&gt;is positive, and in order to avoid uphill motion he simply stops as soon as the power becomes negative. On the other hand, &lt;span class=&quot;math-container&quot;&gt;$\gamma(t)$&lt;/span&gt; should not be too large, because the current velocities carry information about the reasonable ‘average’ descent direction and energy scale.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and later:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The numerical treatment of the algorithm is simple. Any common MD integrator can be used as the basis for the propagation due to the conservative forces. The MD trajectory is continuously re-adjusted by two kinds of velocity modifications: a) the above mentioned immediate stop upon uphill motion and b) a simple mixing of the global (&lt;span class=&quot;math-container&quot;&gt;$3N_{atoms}$&lt;/span&gt; dimensional) velocity and force vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow (1-\alpha) \mathbf{v} + \alpha \mathbf{\hat{F}} |\mathbf{v}|$&lt;/span&gt; resulting from an &lt;strong&gt;Euler-discretization of the last term in eq. (1)&lt;/strong&gt; with time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha = \gamma \Delta t$&lt;/span&gt;. Both &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; are treated as dynamically adaptive quantities.&lt;/p&gt;&#xA;&lt;p&gt;Explicitly, the FIRE algorithm uses the following propagation rules (given initial values for &lt;span class=&quot;math-container&quot;&gt;$\Delta t, \alpha = \alpha_{start}$&lt;/span&gt; and for the global vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}=0$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MD: calculate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}, \mathbf{F} = -\nabla E(\mathbf{x})$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}$&lt;/span&gt; using any common MD integrator; check for convergence&lt;/li&gt;&#xA;&lt;li&gt;F1: calculate &lt;span class=&quot;math-container&quot;&gt;$P = \mathbf{F} \cdot \mathbf{v}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F2: set &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow (1-\alpha) \mathbf{v} + \alpha \mathbf{\hat{F}} |\mathbf{v}|$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F3: if &lt;span class=&quot;math-container&quot;&gt;$P &amp;gt; 0$&lt;/span&gt; and the number of steps since &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; was negative is larger than &lt;span class=&quot;math-container&quot;&gt;$N_{min}$&lt;/span&gt;, increase the time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t \rightarrow \min(\Delta t f_{inc}, \Delta t_{max})$&lt;/span&gt; and decrease &lt;span class=&quot;math-container&quot;&gt;$\alpha \rightarrow \alpha f_{\alpha}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F4: if &lt;span class=&quot;math-container&quot;&gt;$P \le 0$&lt;/span&gt;, decrease time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t \rightarrow \Delta t f_{dec}$&lt;/span&gt;, freeze the system &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow 0$&lt;/span&gt; and set &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; back to &lt;span class=&quot;math-container&quot;&gt;$\alpha_{start}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F5: return to MD&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;In relaxation an accurate calculation of the atomic trajectories is not necessary&lt;/strong&gt;, and the adaptive time step allows FIRE to increase &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; until either the largest stable time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t_{max}$&lt;/span&gt; is reached, or an energy minimum along the current direction of motion (&lt;span class=&quot;math-container&quot;&gt;$P &amp;lt; 0$&lt;/span&gt;) is encountered.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Actual Question&lt;/h3&gt;&#xA;&lt;p&gt;Despite the lengthy preamble, my question is fairly short.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; Understanding discretized FIRE; how did the authors get from Equation &lt;span class=&quot;math-container&quot;&gt;$\eqref{eq1}$&lt;/span&gt; to the recommended algorithm?&lt;/p&gt;&#xA;&lt;p&gt;I've bolded&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...Euler-discretization of the last term in eq. (1)...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and the &lt;a href=&quot;https://en.wikipedia.org/wiki/Euler_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;Euler method&lt;/a&gt; is an extremely simple if not particularly accurate ODE solver. The last bit of the quote points out that particularly high accuracy is not necessary in order to simply find our way to the bottom; we don't care if we take the &lt;em&gt;exact&lt;/em&gt; same path as a the skier to get there, but only that we do.&lt;/p&gt;&#xA;&lt;p&gt;Once could alternatively solve Equation &lt;span class=&quot;math-container&quot;&gt;$\eqref{eq1}$&lt;/span&gt; with a fancy ODE solver as well, but then one would have to construct an appropriate &lt;span class=&quot;math-container&quot;&gt;$\gamma(t)$&lt;/span&gt; and and manage step sizes accordingly and that would probably not end up being FIRE anymore.&lt;/p&gt;&#xA;&lt;p&gt;But here I'm only asking how the authors get from Equation &lt;span class=&quot;math-container&quot;&gt;$\eqref{eq1}$&lt;/span&gt; to the recommended algorithm.&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="7" LastEditDate="2022-03-16T14:09:07.890" LastActivityDate="2022-06-24T21:41:12.070" Title="Understanding derivation of discretized FIRE algorithm" Tags="|molecular-dynamics|mathematical-modeling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8768" PostTypeId="1" CreationDate="2022-03-08T01:28:08.383" Score="6" ViewCount="70" Body="&lt;p&gt;I am currently trying to use some modeling software for a project I have to do for school. I am currently using Python 3.8.10 on Ubuntu 20.04.4 and VSCode as my IDE.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to use a library called &lt;a href=&quot;https://github.com/fusion-energy/openmc-plasma-source&quot; rel=&quot;nofollow noreferrer&quot;&gt;openmc-plasma-source&lt;/a&gt; to model a plasma in a tokamak. For this I installed openmc as well, and followed the &lt;a href=&quot;https://docs.openmc.org/en/stable/quickinstall.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;install from source&lt;/a&gt; tutorials for Ubuntu. I copied the &lt;a href=&quot;https://github.com/fusion-energy/openmc-plasma-source/blob/main/examples/tokamak_source_example.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;sample code found for a tokamak&lt;/a&gt; from their repo into a file and hit run. When I try and run the script from either my IDE or straight from terminal, I am met with this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                                 %%%%%%%%%%%%%%%&#xA;                           %%%%%%%%%%%%%%%%%%%%%%%%&#xA;                        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;                      %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;                    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;                   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;                                    %%%%%%%%%%%%%%%%%%%%%%%%&#xA;                                     %%%%%%%%%%%%%%%%%%%%%%%%&#xA;                 ###############      %%%%%%%%%%%%%%%%%%%%%%%%&#xA;                ##################     %%%%%%%%%%%%%%%%%%%%%%%&#xA;                ###################     %%%%%%%%%%%%%%%%%%%%%%%&#xA;                ####################     %%%%%%%%%%%%%%%%%%%%%%&#xA;                #####################     %%%%%%%%%%%%%%%%%%%%%&#xA;                ######################     %%%%%%%%%%%%%%%%%%%%&#xA;                #######################     %%%%%%%%%%%%%%%%%%&#xA;                 #######################     %%%%%%%%%%%%%%%%%&#xA;                 ######################     %%%%%%%%%%%%%%%%%&#xA;                  ####################     %%%%%%%%%%%%%%%%%&#xA;                    #################     %%%%%%%%%%%%%%%%%&#xA;                     ###############     %%%%%%%%%%%%%%%%&#xA;                       ############     %%%%%%%%%%%%%%%&#xA;                          ########     %%%%%%%%%%%%%%&#xA;                                      %%%%%%%%%%%&#xA;&#xA;                 | The OpenMC Monte Carlo Code&#xA;       Copyright | 2011-2022 MIT, UChicago Argonne LLC, and contributors&#xA;         License | https://docs.openmc.org/en/latest/license.html&#xA;         Version | 0.13.0&#xA;        Git SHA1 | cff247e35785e7236d67ccf64a3401f0fc50a469&#xA;       Date/Time | 2022-03-06 19:33:51   OpenMP Threads | 8&#xA;&#xA;&#xA;Reading settings XML file...  ERROR: No cross_sections.xml file was &#xA;specified in materials.xml or in the OPENMC_CROSS_SECTIONS environment &#xA;variable. OpenMC needs such a file to identify where to find data &#xA;libraries. Please consult the user's guide at https://docs.openmc.org/ &#xA;for information on how to set up data libraries. &#xA;&#xA;Traceback (most recent call last): &#xA;File &amp;quot;plasma.py&amp;quot;, line 64, in &amp;lt;module&amp;gt;&#xA;    model.run()   &#xA;File &amp;quot;/home/agilan/.local/lib/python3.8/site-packages/openmc/model/model.py&amp;quot;, line 580, in run&#xA;    openmc.run(particles, threads, geometry_debug, restart_file,   &#xA;File &amp;quot;/home/agilan/.local/lib/python3.8/site-packages/openmc/executor.py&amp;quot;, line 276, in run&#xA;    _run(args, output, cwd)   &#xA;File &amp;quot;/home/agilan/.local/lib/python3.8/site-packages/openmc/executor.py&amp;quot;, line 116, in _run&#xA;    raise RuntimeError(error_msg) RuntimeError: &#xA;&#xA;No cross_sections.xml file was specified in materials.xml or in the &#xA;OPENMC_CROSS_SECTIONS environment variable. OpenMC needs such a file to&#xA;identify where to find data libraries. Please consult the user's guide &#xA;at https://docs.openmc.org/ for information on how to set up data &#xA;libraries.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Sorry if this is a dumb mistake, but I'm still a beginner. Could anybody help or tell me what I did wrong? Thank you.&lt;/p&gt;&#xA;" OwnerUserId="5056" LastEditorUserId="5" LastEditDate="2022-03-09T01:46:39.240" LastActivityDate="2022-03-09T01:46:39.240" Title="Issues with running plasma-modeling sample script" Tags="|python|openmc-plasma-source|" AnswerCount="0" CommentCount="2" ClosedDate="2022-03-15T19:17:48.177" ContentLicense="CC BY-SA 4.0" />
  <row Id="8769" PostTypeId="1" CreationDate="2022-03-08T09:01:21.987" Score="7" ViewCount="184" Body="&lt;p&gt;I am trying to understand if my idea for the computation of diffusion coefficient as a function of distance is right or not. So, the diffusion coefficient as a function of distance is given by,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$D(z) = \frac{\mathrm{var}(z)}{\tau}$$&lt;/span&gt;&#xA;Here, I am calculating the diffusion coefficient for the motion of a solute when the solute is restrained to some position along the transmembrane coordinate &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; by a harmonic potential (&lt;a href=&quot;https://en.wikipedia.org/wiki/Umbrella_sampling&quot; rel=&quot;noreferrer&quot;&gt;Umbrella Sampling&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;So, if I fit the position autocorrelation function with &lt;span class=&quot;math-container&quot;&gt;$e^\frac{-t}{\tau}$&lt;/span&gt;, it should give me autocorrelation time &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; which I can plug in the above equation to compute the diffusion coefficient for that particular restrained position. Am I following correctly? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="7" LastEditDate="2022-03-08T14:08:19.863" LastActivityDate="2022-03-08T14:08:19.863" Title="Diffusion coefficient as a function of distance from the position autocorrelation function" Tags="|molecular-dynamics|molecular-modeling|correlation-functions|" AnswerCount="0" CommentCount="5" ClosedDate="2023-02-01T03:44:07.363" ContentLicense="CC BY-SA 4.0" />
  <row Id="8770" PostTypeId="2" ParentId="8746" CreationDate="2022-03-08T13:50:03.007" Score="1" Body="&lt;p&gt;I don't have a ton of time to answer and this is somewhat outside my area, but I think I can at least address some parts of your question.&lt;/p&gt;&#xA;&lt;p&gt;To start, they mention just after equation 6 of your linked paper that &lt;span class=&quot;math-container&quot;&gt;$\omega=(\alpha, \beta,\gamma)$&lt;/span&gt;, the Euler angles that define the orientation. This set of Euler angles is used to &lt;a href=&quot;https://en.wikipedia.org/wiki/Euler_angles#Conversion_to_other_orientation_representations&quot; rel=&quot;nofollow noreferrer&quot;&gt;define the rotation matrix&lt;/a&gt; &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; in a succinct way.&lt;/p&gt;&#xA;&lt;p&gt;My understanding of why a Gaussian is used is to simply model the interaction between particles. Since the exponent measures distance from the ellipse, the Gaussian will be largest at the border of the ellipse and will slowly decay as you move further away from it. If you wanted to just model hard ellipses, you could just consider when the ellipses of each particle made contact to model collisions, but with a Gaussian you include interactions from when the particles are slightly further away.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-08T13:50:03.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8771" PostTypeId="1" CreationDate="2022-03-08T16:59:24.697" Score="3" ViewCount="616" Body="&lt;p&gt;I've only been able to export atomic coordinates for a crystal when looking down the c axis, but I need to do so along the a and b axis as well. I've tried changing the Projection Vector in the Orientation window, but this didn't change the exported data at all.&lt;/p&gt;&#xA;" OwnerUserId="5060" LastActivityDate="2022-03-11T01:01:35.557" Title="How to export .xyz files from VESTA of crystal viewed along different crystallographic axes" Tags="|software|vesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8772" PostTypeId="5" CreationDate="2022-03-09T01:47:26.233" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://pypi.org/project/openmc-plasma-source/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pypi.org/project/openmc-plasma-source/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-03-09T01:47:26.233" LastActivityDate="2022-03-09T01:47:26.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8773" PostTypeId="4" CreationDate="2022-03-09T01:47:26.233" Score="0" Body="Questions about openmc-plasma-source, the Python package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-03-09T01:47:26.233" LastActivityDate="2022-03-09T01:47:26.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8774" PostTypeId="1" CreationDate="2022-03-09T19:34:45.677" Score="8" ViewCount="1350" Body="&lt;p&gt;I am new to Wannier90 calculations. I am trying to obtain the Wannier functions and Wannier interpolated band structure.&lt;/p&gt;&#xA;&lt;p&gt;But I am having a problem in setting the parameters like &lt;code&gt;dist_win_min&lt;/code&gt;, &lt;code&gt;dist_win_max&lt;/code&gt;, &lt;code&gt;dist_froz_min&lt;/code&gt;, &lt;code&gt;dist_froz_max&lt;/code&gt; and orbital projections. What are the steps which I should follow for guessing the values of these parameters?&lt;/p&gt;&#xA;&lt;p&gt;I have gone through the examples of Wannier90 but that didn't clarify how to guess the initial values of these parameters if we want to perform calculations in new systems.&lt;/p&gt;&#xA;" OwnerUserId="1361" LastEditorUserId="5" LastEditDate="2022-09-03T23:36:56.883" LastActivityDate="2023-05-05T16:32:56.437" Title="How to select the projections and inner/outer window for Wannier90 calculations?" Tags="|density-functional-theory|quantum-espresso|orbitals|software-input-file-request|wannier90|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8776" PostTypeId="1" AcceptedAnswerId="8912" CreationDate="2022-03-10T06:12:31.623" Score="9" ViewCount="344" Body="&lt;p&gt;For the radial distribution function&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$g(r)=\frac{N(r)}{4\pi r^{2}dr \rho}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;how do you do the calculation of the volume of the spherical shell in the denominator, &lt;span class=&quot;math-container&quot;&gt;$4\pi r^{2} dr$&lt;/span&gt;, when the simulation is done on a lattice? Since only discrete values of &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; are possible, I imagine the calculation might be subtle.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorUserId="181" LastEditDate="2022-03-10T18:24:48.457" LastActivityDate="2022-04-08T10:10:09.027" Title="How do you calculate a radial distribution function on a lattice?" Tags="|statistical-thermodynamics|structure|radial-distribution-function|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8777" PostTypeId="1" CreationDate="2022-03-10T06:33:45.657" Score="1" ViewCount="263" Body="&lt;p&gt;Can anyone please explain, what is the physical meaning of band.conf, mesh.conf and pdos.conf in phonon calculation?&#xA;if it is possible please explain about tags used in it.&lt;/p&gt;&#xA;" OwnerUserId="4238" LastActivityDate="2022-03-10T06:33:45.657" Title="can anyone please explain what is meaning of band.conf , mesh.conf and pdos.conf in phonon calculation?" Tags="|density-functional-theory|vasp|phonopy|phonon-density-of-state|phonon-dispersion|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-03T02:22:10.050" ContentLicense="CC BY-SA 4.0" />
  <row Id="8778" PostTypeId="2" ParentId="8771" CreationDate="2022-03-10T16:45:41.163" Score="5" Body="&lt;p&gt;Orientation window will change only the view but it will not rotate the data as coordinate axis remain same even orientation window changes. If you want to swap axis for e.g z with y or any other custom vector. It will be necessary to rotate the unit cell using transformation matrix. Inside VESTA, kindly follow this step.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;edit&amp;gt;edit data&amp;gt;unit cell&amp;gt;Transform&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are other tools such as &lt;code&gt;vaspkit&lt;/code&gt;, &lt;code&gt;atomsk&lt;/code&gt;which can quick swap vectors of unit cell.&#xA;for example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;1. atomsk&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atomsk initial.cfg -swap X Y final.xsf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;2. VASPKIT&lt;/strong&gt;&lt;br /&gt;&#xA;VASPKIT (407) can do swap two axis of lattice vector.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-03-11T01:01:35.557" LastActivityDate="2022-03-11T01:01:35.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8779" PostTypeId="1" AcceptedAnswerId="8781" CreationDate="2022-03-10T18:01:55.137" Score="6" ViewCount="393" Body="&lt;p&gt;One common way of calculating a dipole polarizability from electronic structure is by calculating the following derivative by finite difference:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{\mu}=\left(\frac{\partial U}{\partial \mathbf{E}}\right)_{\mathbf{E}=0}&#xA;$$&lt;/span&gt;&#xA;where here &lt;span class=&quot;math-container&quot;&gt;$\mathbf{E}$&lt;/span&gt; is an external electric field and &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is the electronic energy. Therefore, we can calculate the three components of the dipole moment, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{\mu}$&lt;/span&gt;, via finite difference where we apply a finite field along the principle axes in both the positive and negative directions. Notice, however, that this calculation is typically done in the case that zero net field is applied.&lt;/p&gt;&#xA;&lt;p&gt;We can then calculate the dipole polarizability in the same manner as the change in dipole in response to an electric field or the second derivative of the energy with respect to a field,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{pq}=\left(\frac{\partial^2 U}{\partial \mathbf{E}_p\partial \mathbf{E}_q}\right)_{\mathbf{E}=0}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can then calculate each of the nine polarizability tensor components via second-order finite difference of the energy. &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; are the cartesian axes. Typically, again, this is done with zero net external field.&lt;/p&gt;&#xA;&lt;p&gt;My question is: Is there any physical reason and/or technical reason why I can't do the same thing in the case of a finite external field?&lt;/p&gt;&#xA;&lt;p&gt;If one considers a molecule in solution, for example, the dipole response should not be the same as the gas-phase zero-field dipole response because the molecule is in the presence of an electric field created by the surrounding environment. That's the motivation for the calculation.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Additionally, any references that do this or explain why not to do this would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-03-11T01:00:51.913" Title="Is it possible to calculate the dipole polarizability in the presence of a nonzero electric field?" Tags="|reference-request|quantum-chemistry|electronic-structure|polarizability|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8780" PostTypeId="2" ParentId="6310" CreationDate="2022-03-10T19:48:00.450" Score="7" Body="&lt;p&gt;Cube files can be parsed into a 3D scalar grid (i.e. a numpy array) directly. These can then by visualized by applying the marching cubes approach (&lt;code&gt;scikit-image&lt;/code&gt; has an implementation) to generate a mesh, and this mesh can be shown in interactive 3d using &lt;code&gt;meshplot&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For example, to parse cube files, in the past I've used:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def parse_cube(filename):&#xA;    #from: https://github.com/psi4/psi4numpy/blob/6ed03e715689ec82bf96fbb23c1855fbe7835b90/Tutorials/14_Visualization/vizualize.ipynb&#xA;    &amp;quot;&amp;quot;&amp;quot; Parses a cube file, returning a dict of the information contained.&#xA;        The cubefile itself is stored in a numpy array. &amp;quot;&amp;quot;&amp;quot;&#xA;    with open(filename) as fp:&#xA;        results = {}&#xA;&#xA;        # skip over the title&#xA;        fp.readline()&#xA;        fp.readline()&#xA;&#xA;        origin = fp.readline().split()&#xA;        natoms = int(origin[0])&#xA;        results['minx'] = minx = float(origin[1])&#xA;        results['miny'] = miny = float(origin[2])&#xA;        results['minz'] = minz = float(origin[3])&#xA;&#xA;        infox = fp.readline().split()&#xA;        numx = int(infox[0])&#xA;        incx = float(infox[1])&#xA;        results['incx'] = incx&#xA;        results['numx'] = numx&#xA;        results['maxx'] = minx + incx * numx&#xA;&#xA;        infoy = fp.readline().split()&#xA;        numy = int(infoy[0])&#xA;        incy = float(infoy[2])&#xA;        results['incy'] = incy&#xA;        results['numy'] = numy&#xA;        results['maxy'] = miny + incy * numy&#xA;&#xA;        infoz = fp.readline().split()&#xA;        numz = int(infoz[0])&#xA;        incz = float(infoz[3])&#xA;        results['incz'] = incz&#xA;        results['numz'] = numz&#xA;        results['maxz'] = minz + incz * numz&#xA;&#xA;        atnums = []&#xA;        coords = []&#xA;        for atom in range(natoms):&#xA;            coordinfo = fp.readline().split()&#xA;            atnums.append(int(coordinfo[0]))&#xA;            coords.append(list(map(float, coordinfo[2:])))&#xA;        results['atom_numbers'] = np.array(atnums)&#xA;        results['atom_coords'] = np.array(coords)&#xA;&#xA;        data = np.array([ float(entry) for line in fp for entry in line.split() ])&#xA;        if len(data) != numx*numy*numz:&#xA;            raise Exception(&amp;quot;Amount of parsed data is inconsistent with header in Cube file!&amp;quot;)&#xA;        results['data'] = data.reshape((numx,numy,numz))&#xA;&#xA;        return results&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now load up a cube file:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;cube = parse_cube('ESP.cube')&#xA;print(cube['data'].min(), cube['data'].max())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I print the min/max because I want to know some range within which to set the cutoff for marching cubes. Here the cutoff is 0.07, and the spacing (i.e. gridsize) is 0.3 angstroms. Note that the spacing is hardcoded into the cube file - one would normally set it when calculating the ESP.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from skimage import measure&#xA;vert, faces, norm, values= measure.marching_cubes(cube['data'], &#xA;                                                  0.07,&#xA;                                                  spacing=(0.3,0.3,0.3))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;finally, draw this mesh with &lt;code&gt;meshplot&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import meshplot as mp&#xA;vert = vert&#xA;mp.plot(vert, faces)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the final result looks a bit like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pIIqG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pIIqG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;meshplot: &lt;a href=&quot;https://skoch9.github.io/meshplot/tutorial/&quot; rel=&quot;noreferrer&quot;&gt;https://skoch9.github.io/meshplot/tutorial/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;scikitimage: &lt;a href=&quot;https://scikit-image.org/&quot; rel=&quot;noreferrer&quot;&gt;https://scikit-image.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2225" LastActivityDate="2022-03-10T19:48:00.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8781" PostTypeId="2" ParentId="8779" CreationDate="2022-03-10T19:49:02.407" Score="6" Body="&lt;p&gt;There is nothing wrong with taking electric field derivatives at nonzero field strengths. The zero field strength conditions come from taking a Taylor expansion of the internal energy about &lt;span class=&quot;math-container&quot;&gt;$\vec{E}=0$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;U=U_0+\mu_0\cdot\vec{E}+\frac{1}{2}\alpha_0:\vec{E}\vec{E}+...&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the static dipole/polarizability are defined at zero field strength. A similar expansion could be made for the energy at any field strength, yielding dipoles, polarizabilities, hyperpolarizabilities, etc. for those field strengths.&lt;/p&gt;&#xA;&lt;p&gt;Note the frequency &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; of the field also affects these properties, but as long as the you are including this frequency in however you represent the field in your calculation, your finite difference scheme should capture this frequency dependence as well.&lt;/p&gt;&#xA;&lt;p&gt;You should also be careful with taking double numerical derivatives, as it can often require very high precision (and/or a &lt;a href=&quot;https://en.wikipedia.org/wiki/Finite_difference_coefficient&quot; rel=&quot;nofollow noreferrer&quot;&gt;stencil&lt;/a&gt; with many points) to achieve reasonable accuracy.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-03-11T01:00:51.913" LastActivityDate="2022-03-11T01:00:51.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8782" PostTypeId="1" CreationDate="2022-03-10T20:04:01.190" Score="6" ViewCount="3202" Body="&lt;p&gt;I am currently learning how to use VASP and was looking at how to get the DOS plots. I have been recommended to use P4VASP but due to some reason I am not able to install it on my Ubuntu 20.04. When I try to use &lt;code&gt;sudo&lt;/code&gt; to install the said package it says no package p4vasp found. And I think that the older website has also been depreciated &lt;a href=&quot;http://p4vasp.at/&quot; rel=&quot;noreferrer&quot;&gt;http://p4vasp.at/&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Am I required to work with Ubuntu 18.04 only? Or is it somehow possible that p4vasp is no longer working or something. Thanks&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2022-11-15T03:12:50.240" Title="Unable to install P4Vasp" Tags="|vasp|software-assistance|visualization-software|" AnswerCount="4" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8783" PostTypeId="2" ParentId="8782" CreationDate="2022-03-10T20:30:52.540" Score="6" Body="&lt;p&gt;The &lt;a href=&quot;https://github.com/orest-d/p4vasp&quot; rel=&quot;noreferrer&quot;&gt;source code&lt;/a&gt; is still available on Github, though it hasn't been updated for nearly 4 years. While the project seems to be &lt;a href=&quot;https://github.com/orest-d/p4vasp/issues/22&quot; rel=&quot;noreferrer&quot;&gt;abandonded&lt;/a&gt;, you should be able to compile from source. I don't suspect the change from Ubuntu 18 to 20 would make it unable to compile, but there probably is not a readily installable version for Ubuntu 20.04.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-10T20:30:52.540" CommentCount="0" CommunityOwnedDate="2022-03-10T20:30:52.540" ContentLicense="CC BY-SA 4.0" />
  <row Id="8784" PostTypeId="2" ParentId="8782" CreationDate="2022-03-10T23:05:44.653" Score="6" Body="&lt;p&gt;The &lt;strong&gt;P4VASP&lt;/strong&gt; code is one of the easiest visualization tools for VASP outputs that I have been using. From your question, I understand that your system can't find the p4vasp executable file which can be solved by adding its path to the &lt;code&gt;.bashrc&lt;/code&gt; file in the home folder. However, there are a lot of visualization tools that offer higher quality and more control of VASP output plots. I recommend using &lt;a href=&quot;https://vaspkit.com/&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT&lt;/a&gt; to extract data from VASP outputs, and then you can use &lt;strong&gt;XMGRACE&lt;/strong&gt; or &lt;strong&gt;GNUPLOT&lt;/strong&gt; to plot the graphs. You can check this &lt;a href=&quot;http://molphys.org/gnuplot_tutorial/dos_plot.html&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt; that contains some &lt;strong&gt;GNUPLOT&lt;/strong&gt; scripts for high-quality DOS plots. I recommend also checking this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1988/what-are-some-good-band-structure-dos-plotting-tools-styles/2219#2219&quot;&gt;thread&lt;/a&gt; which I believe will be very useful for you.&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-03-10T23:05:44.653" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8787" PostTypeId="1" AcceptedAnswerId="8788" CreationDate="2022-03-11T08:11:07.890" Score="8" ViewCount="698" Body="&lt;p&gt;I have finished a scan of a bond length, but I need to continue the coordinate scan adding more points to the same scan.&lt;/p&gt;&#xA;&lt;p&gt;I thought of writing a second input file from the last geometry, relaunching the scan updating the redundant coordinates. Is there another way like something scan=(restart)?.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="5" LastEditDate="2022-03-11T13:55:07.813" LastActivityDate="2024-01-11T22:06:20.420" Title="Restart potential energy scan in Gaussian with additional scan points" Tags="|gaussian|geometry|potential-energy-surface|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8788" PostTypeId="2" ParentId="8787" CreationDate="2022-03-11T15:42:55.547" Score="7" Body="&lt;p&gt;If I'm understanding correctly, something like this should work.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%oldchk=short_scan.chk&#xA;%chk=new_scan.chk&#xA;#p opt=modredundant Geom=(Checkpoint,ModRedundant)&#xA;&#xA;0 1 !Or your particular charge/multiplicity&#xA;&#xA;!Your new scan coordinate&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This should read the last scan step from the prior checkpoint file and then you can start a new scan (or other modredundant coordinate modification) from there. This assumes you are doing a relaxed scan and not using the &lt;code&gt;scan&lt;/code&gt; keyword to do a rigid scan. I don't know how rigid scans interact with the checkpoint file.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-11T15:42:55.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8790" PostTypeId="1" AcceptedAnswerId="9409" CreationDate="2022-03-13T05:59:12.490" Score="7" ViewCount="231" Body="&lt;p&gt;I am getting some conflicting results on this topic while searching for literature online, so I am asking this question here with respect to a simplified experimental setup. If we are trying to theoretically model an experimental setup for excitation and relaxation of a molecule in solution due to external radiation, there should be a sink for the energy dissipation, which is observed in the experiment as the heat dissipation from the solution. So in my understanding there should be an external &amp;quot;sink&amp;quot; attached to the MD setup. On the other hand the energy dissipation in the solution then becomes dependent on the coupling strength between the MD system and the thermostat, which can bias the results. So how should I approach this issue?&lt;/p&gt;&#xA;&lt;p&gt;P.S.: It would be very helpful if there are some relevant literature pointed in the answers.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2022-03-13T13:39:31.513" LastActivityDate="2022-07-20T11:42:28.670" Title="Is it incorrect to use a NVT ensemble for Non-equilibrium MD simulation?" Tags="|molecular-dynamics|reference-request|statistical-thermodynamics|molecular-mechanics|" AnswerCount="1" CommentCount="4" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8791" PostTypeId="2" ParentId="8782" CreationDate="2022-03-13T14:35:32.287" Score="4" Body="&lt;p&gt;py4vasp is also used as an interface for VASP. You can install p4vasp by using pip &lt;code&gt;pip install py4vasp&lt;/code&gt;&#xA;Please check &lt;a href=&quot;https://vasp.at/py4vasp/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;p4vasp&lt;/a&gt; for more detail.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2022-03-13T15:00:54.210" LastActivityDate="2022-03-13T15:00:54.210" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8792" PostTypeId="1" AcceptedAnswerId="8831" CreationDate="2022-03-13T15:30:56.120" Score="7" ViewCount="219" Body="&lt;p&gt;I am trying to model the surface relaxation on the TiO2(Anatase-101) surface, but it confuses me that when I try to set some atoms as fixed, unlike the crystal that only contains one element, there is no clear boundary between each layer of atoms.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;For metal oxide, there is no boundary line between each layer, how should I choose the atoms that I want to fix?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wAMeC.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wAMeC.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-03-22T15:27:42.217" Title="Which atoms should be fixed when simulating metal oxides surface relaxation?" Tags="|vasp|crystallography|surfaces|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8793" PostTypeId="1" AcceptedAnswerId="8794" CreationDate="2022-03-13T16:36:28.067" Score="6" ViewCount="696" Body="&lt;p&gt;I want to rearrange the order of the atoms in the POSCAR file, is there any software able to do this? For example, in the below POSCAR file, I want to put Ti atoms before others.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TiO2_mp-390_primitive_geo_opt (1 0 1)-pseudoH_opt_supercell-fix-1 &#xA;1.0 &#xA;10.518000 -3.881298 0.000000 &#xA;0.000000 7.762594 0.000001 &#xA;0.000000 0.000000 25.587641 &#xA;H C O Ti Pt &#xA;4 4 48 24 1 &#xA;Selective Dynamics&#xA;Direct &#xA;0.368202 0.184099 0.117556 F F F &#xA;0.868201 0.184099 0.117556 F F F &#xA;0.368202 0.684099 0.117556 F F F &#xA;0.868201 0.684099 0.117556 F F F &#xA;0.108065 0.054035 0.118569 F F F &#xA;0.608065 0.054035 0.118569 F F F &#xA;0.108065 0.554036 0.118569 F F F &#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-03-13T17:32:25.397" LastActivityDate="2022-03-13T20:19:53.090" Title="Reorder the atoms in the POSCAR file" Tags="|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8794" PostTypeId="2" ParentId="8793" CreationDate="2022-03-13T20:19:53.090" Score="7" Body="&lt;p&gt;&lt;code&gt;atomsk&lt;/code&gt; can sort atoms based on &lt;strong&gt;atomic weight&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atomsk POSCAR -sort species down pos&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;short trick is whichever element you want to be at top, make sure its name in &lt;code&gt;POSCAR&lt;/code&gt; should have highest &lt;strong&gt;atomic weight&lt;/strong&gt;. In your case, you want &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; at the top which have lower atomic weight than &lt;span class=&quot;math-container&quot;&gt;$\ce{Pt}$&lt;/span&gt;, hence I will replace &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\ce{U}$&lt;/span&gt; in &lt;code&gt;POSCAR&lt;/code&gt; and run the above command.After generating &lt;code&gt;POSCAR&lt;/code&gt;, I will change &lt;span class=&quot;math-container&quot;&gt;$\ce{U}$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; again. This is not the best method but it works.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-03-13T20:19:53.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8795" PostTypeId="1" AcceptedAnswerId="8809" CreationDate="2022-03-14T05:32:29.517" Score="7" ViewCount="622" Body="&lt;p&gt;I meet some convergence problems when doing self-consistent field calculation in VASP, I find some parameters on &lt;a href=&quot;https://www.vasp.at/wiki/index.php/AMIX&quot; rel=&quot;noreferrer&quot;&gt;VASP wiki&lt;/a&gt; that might be able to tune the convergence performance. But I don't quite understand the relationship between convergence and average eigenvalue, as explained below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In VASP the eigenvalue spectrum of the charge dielectric matrix is&#xA;calculated and written to the OUTCAR file at each electronic step.&#xA;This allows a rather easy optimization of the mixing parameters, if&#xA;required. Search in the OUTCAR file for&lt;/p&gt;&#xA;&lt;p&gt;eigenvalues of (default mixing * dielectric matrix)&lt;/p&gt;&#xA;&lt;p&gt;The parameters for the mixing are optimal if the mean eigenvalue&#xA;Γmean=1, and if the width of the eigenvalue spectrum is minimal. For&#xA;an initial linear mixing (BMIX≈0) an optimal setting for AMIX can be&#xA;found easily by setting AMIXoptimal=AMIXcurrent*Γmean. For the Kerker&#xA;scheme (IMIX=1) either AMIX or BMIX can be optimized, but we recommend&#xA;to change only BMIX and keep AMIX fixed (you must decrease BMIX if the&#xA;mean eigenvalue is larger than one, and increase BMIX if the mean&#xA;eigenvalue Γmean&amp;lt;1). However, the optimal AMIX depends very much on&#xA;the system, for metals this parameter usually has to be rather small,&#xA;e.g. AMIX= 0.02.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I checked my result, the average eigenvalue at GAMMA is 0.2025.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA; eigenvalues of (default mixing * dielectric matrix)&#xA;  average eigenvalue GAMMA=   0.2025&#xA;  1.2461  0.6193  0.4021  0.4021  0.2087  0.2087  0.0809  0.0809  0.0725  0.0725&#xA;  0.0815  0.0815  0.1056  0.1056  0.1091  0.0921  0.0654  0.0654  0.0566  0.0566&#xA;  0.0386&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;Why is the model's convergence performance better when the average eigenvalue at GAMMA is 1?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-03-17T02:38:21.580" Title="The relationship between average eigenvalue and convergence performance in VASP?" Tags="|density-functional-theory|vasp|numerical-convergence|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8796" PostTypeId="1" AcceptedAnswerId="9728" CreationDate="2022-03-14T06:17:15.157" Score="7" ViewCount="556" Body="&lt;p&gt;I am a little confused about what should be the correct number of kpoints that I wanna use. I am currently working on a small cluster so picking a high value(even around 10) gives me a memory fault. My first question is how does choosing the k points vary for nanostructures and for bulk.&lt;/p&gt;&#xA;&lt;p&gt;For our geometry optimization we use a k-points&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Automatic generation     &#xA;0                                                                                                                       &#xA;Monkhorst-pack                                                                                                           &#xA;1 1 1                                                                                                                   &#xA;0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And for calcualtion of DOS we have been using &lt;code&gt;3 3 3&lt;/code&gt; which I think is less. I am currently exploring how the DOS vary for various values of K Points. And the values vary a lot when I take &lt;code&gt;4 4 4&lt;/code&gt; instead of &lt;code&gt;3 3 3 &lt;/code&gt;. Why is this happening!&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-03-15T11:00:43.527" LastActivityDate="2022-09-28T19:49:01.793" Title="Minimum number of kpoints for calculation of properties of nanoparticles in vasp" Tags="|vasp|k-points|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8797" PostTypeId="1" CreationDate="2022-03-14T06:31:41.373" Score="4" ViewCount="368" Body="&lt;p&gt;I was planning to use VASPKIT in order to determine the linear optical properties of my nanostructure. But upon running VASPKIT, I do not see an option for 0D materials but only for 2D and bulk.&lt;/p&gt;&#xA;&lt;p&gt;Is there any other way we can evaluate these properties or do I have to code this up myself?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/61FuE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/61FuE.png&quot; alt=&quot;VASPKIT command prompt inputs for bulk or 2d linear optical spectra&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2022-11-02T00:26:00.437" LastActivityDate="2022-11-02T00:26:00.437" Title="Evaluating absorption coefficient using VASPKIT for nanostructures (specifically quantum dots)" Tags="|vasp|optical-properties|vaspkit|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8800" PostTypeId="1" CreationDate="2022-03-15T08:00:45.530" Score="3" ViewCount="277" Body="&lt;p&gt;In real crystals, the atoms may not always sit at their ideal lattice sites. How to quantify this lattice distortion?&lt;/p&gt;&#xA;&lt;p&gt;Based on my understanding from X-ray diffraction books, the Radial Distribution Function/Pair Distribution Function can qualitatively give information about the lattice distortion. Is there a way to give a number to this lattice distortion?&lt;/p&gt;&#xA;&lt;p&gt;I want to know if there's a method/technique which can predict that the binary alloy &lt;span class=&quot;math-container&quot;&gt;$\ce{AB}$&lt;/span&gt; has lattice parameter of XÅ with lattice distortion of ±YÅ.&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="7" LastEditDate="2022-03-16T20:17:05.433" LastActivityDate="2022-04-12T19:41:36.297" Title="How to quantify the lattice distortion from XRD?" Tags="|molecular-dynamics|symmetry|radial-distribution-function|lattice-dynamics|x-ray-diffraction|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8801" PostTypeId="1" CreationDate="2022-03-15T16:21:05.603" Score="7" ViewCount="271" Body="&lt;p&gt;From my understanding, generally in the RDF plot for liquids, the value of &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; goes to a maximum near the first solvation shell and then goes to a minimum and then slowly tapers off to the value of 1. For solids, we observe a discontinuous RDF plot because the atoms are considered to be fixed in particular positions and there exists empty space where no atom exists.&lt;/p&gt;&#xA;&lt;p&gt;Now in a system of solution at a supercritical state, I am trying to understand the plot of RDF between the solute and the solvent molecular pairs. This RDF only keeps increasing and tapers off to 1.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is this a reasonable RDF plot for the supercritical phase and if so, how should I interpret it?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Its not clear to me how I could determine the first solvation shell since there is no minima or how to calculate the coordination number in such a case. The density of the molecules in the shells around the solute is always less than the bulk density, so I wonder if this implies repulsion between the solute and the solvent.&lt;/p&gt;&#xA;&lt;p&gt;Below is the figure for your reference.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/sV9Gs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sV9Gs.png&quot; alt=&quot;Supercritical fluid RDF plot. Steadily increases towards 1 before tapering off around 4 angstroms&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Snapshot of the system:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Okk9s.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Okk9s.png&quot; alt=&quot;Simulation cell of supercritical fluid&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="7" LastEditDate="2022-03-16T15:40:56.220" LastActivityDate="2022-03-16T15:40:56.220" Title="What does the shape of the radial distribution function(RDF) indicate?" Tags="|molecular-dynamics|intermolecular-forces|molecular-interactions|" AnswerCount="0" CommentCount="11" ClosedDate="2022-11-02T00:30:55.667" ContentLicense="CC BY-SA 4.0" />
  <row Id="8802" PostTypeId="1" AcceptedAnswerId="8806" CreationDate="2022-03-15T23:22:05.820" Score="7" ViewCount="537" Body="&lt;p&gt;I'm currently doing some research on perovskite structures and I'm curious about finding out the properties of the orthorhombic lattice. So the cubic structure was easy enough since all sides are the same, just calculate for the Goldschmidt Tolerance Factor and plug that value into equations to solve for a predicted stable lattice constant, to which I can set a range in which I can make energy calculations to determine the stable lattice constant. I'm just curious about how to approach modeling the orthorhombic structure in general. That is, how do I go about finding a, b, and c? Been looking around but as of yet I haven't found the answer I'm looking for.&lt;/p&gt;&#xA;" OwnerUserId="5108" LastActivityDate="2022-03-16T04:50:37.763" Title="How do you approach solving for lattice constants (a, b, and c) for orthorhombic structures using Quantum Espresso?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8803" PostTypeId="5" CreationDate="2022-03-16T00:34:26.007" Score="0" Body="&lt;p&gt;Website: &lt;a href=&quot;https://www.shengbte.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.shengbte.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-03-16T00:34:26.007" LastActivityDate="2022-03-16T00:34:26.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8804" PostTypeId="4" CreationDate="2022-03-16T00:34:26.007" Score="0" Body="Questions about the ShengBTE software package for solving the BTE (Boltzmann Transport Equation) for phonons." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-03-16T00:34:26.007" LastActivityDate="2022-03-16T00:34:26.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8805" PostTypeId="2" ParentId="8766" CreationDate="2022-03-16T03:45:48.340" Score="4" Body="&lt;p&gt;Using the &lt;a href=&quot;https://en.wikipedia.org/wiki/Backward_Euler_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;backward Euler method&lt;/a&gt; to generate velocities from Eq. \ref{eq1}, we would arrive at the expression&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{v}_{i+1}= \mathbf{v}_i+\bigg(\frac{\mathbf{F}_{i+1}}{m} - \gamma_{i+1} |\mathbf{v}_{i+1}| \left(\mathbf{\hat{v}}_{i+1} - \mathbf{\hat{F}}_{i+1} \right)\bigg)\Delta t&#xA;$$&lt;/span&gt;&#xA;where I replaced the time variable with an index. It is probably possible to solve this expression for &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_{i+1}$&lt;/span&gt;, but due to the dependence on &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_{i+1}$&lt;/span&gt; on the right-hand side, it's more complicated then we would like.&lt;/p&gt;&#xA;&lt;p&gt;A simple way around this that should get us to roughly the same result is to use a &lt;a href=&quot;https://en.wikipedia.org/wiki/Predictor%E2%80%93corrector_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;predictor-corrector&lt;/a&gt; like scheme. In the first step we generate a guess for the next velocity using an MD integrator&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tilde{\mathbf{v}}_{i+1}=\mathbf{v}_i+\bigg(\frac{\mathbf{F}_{i+1}}{m}\bigg)\Delta t&#xA;$$&lt;/span&gt;&#xA;where I'm writing the guess with a tilde. To correct this guess and move it closer to the desired FIRE velocity, we add in the remaining terms from Eq. \ref{eq1}, using &lt;span class=&quot;math-container&quot;&gt;$\tilde{\mathbf{v}}_{i+1}$&lt;/span&gt; in place of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}_{i+1}$&lt;/span&gt; on the right hand side.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{v}_{i+1}=\tilde{\mathbf{v}}_{i+1}-\bigg(\gamma_{i+1} |\tilde{\mathbf{v}}_{i+1}| \left(\tilde{\mathbf{\hat{v}}}_{i+1} - \mathbf{\hat{F}}_{i+1} \right)\bigg)\Delta t&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;After simplifying, this gives step F2 of their proposed algorithm. I don't know if this is how they derived their approach, but it seems to fit their analogy well, taking a trajectory and incrementally adjusting it to follow a steeper path.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-06-24T21:41:12.070" LastActivityDate="2022-06-24T21:41:12.070" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8806" PostTypeId="2" ParentId="8802" CreationDate="2022-03-16T04:50:37.763" Score="7" Body="&lt;p&gt;Posted this question mainly because I was trying to find empirical formulas that could help predict the values of a, b, and c for the orthorhombic perovskite structure, just as there are formulas for the prediction of lattice constants for cubic structures. And then I'd use these predicted values as a comparison for when I perform vc-relax optimizations on the crystal that I'm working with to see if the results are close.&lt;/p&gt;&#xA;&lt;p&gt;After posting this question, looked around and I found &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0925838809017265&quot; rel=&quot;noreferrer&quot;&gt;THIS&lt;/a&gt; paper by R. Ubic and G. Subodh where they managed to derive an empirical correlation between ionic radii and lattice constants and, thus, a set of formulas that could be used for the prediction of values of a, b, and c for orthorhombic perovskites. Thanks to Phil Hasnip for answering my query.&lt;/p&gt;&#xA;" OwnerUserId="5108" LastActivityDate="2022-03-16T04:50:37.763" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8808" PostTypeId="2" ParentId="8761" CreationDate="2022-03-16T15:31:34.807" Score="1" Body="&lt;p&gt;Just to aggregate information from the comments, this seems to be a bug in PyTorch Geometric, as typically &lt;a href=&quot;https://stackoverflow.com/a/41721518/7696914&quot;&gt;assertion errors in Python&lt;/a&gt; should only be seen on the development side, rather than for an end user.&lt;/p&gt;&#xA;&lt;p&gt;One possible option you have is to run the script with the &lt;code&gt;-O&lt;/code&gt; flag, which will (among other things) ignore assertions. This will likely not fix the problem, but the error message or faulty data you get from removing this check may provide a hint at what specifically is wrong with the code.&lt;/p&gt;&#xA;&lt;p&gt;You should &lt;a href=&quot;https://github.com/pyg-team/pytorch_geometric/issues&quot; rel=&quot;nofollow noreferrer&quot;&gt;submit an issue&lt;/a&gt; on this repository and/or check that this hasn't already been reported.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-16T15:31:34.807" CommentCount="0" CommunityOwnedDate="2022-03-16T15:31:34.807" ContentLicense="CC BY-SA 4.0" />
  <row Id="8809" PostTypeId="2" ParentId="8795" CreationDate="2022-03-17T01:58:29.523" Score="7" Body="&lt;p&gt;In general, the difficulty of an optimisation problem depends on how widely spread the eigenvalues of the Hessian are. To see why this is, consider a minimisation problem where we wish to find the minimum value of the function &lt;span class=&quot;math-container&quot;&gt;$f(\mathbf{r})$&lt;/span&gt;, given an initial &amp;quot;guess&amp;quot; set of inputs, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Gradient optimisation (steepest descent)&lt;/h3&gt;&#xA;&lt;p&gt;A common approach is to compute the gradient of the function at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_0$&lt;/span&gt;, i.e. &lt;span class=&quot;math-container&quot;&gt;$\nabla f(\mathbf{r}_0)$&lt;/span&gt;, and use it to determine an improved guess &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_1$&lt;/span&gt;. Since the gradient is the direction in which the function &lt;em&gt;increases&lt;/em&gt; quickest, and we wish to &lt;em&gt;minimise&lt;/em&gt; the function, we use &lt;span class=&quot;math-container&quot;&gt;$-\nabla f(\mathbf{r}_0)$&lt;/span&gt; as the direction in which to move. We then write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r}_1 = \mathbf{r}_0 - \alpha \nabla f(\mathbf{r}_0),\tag{1}\label{eq:step}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is the step we take in the search direction &lt;span class=&quot;math-container&quot;&gt;$-\nabla f(\mathbf{r}_0)$&lt;/span&gt;. This step could be a fixed guess, or we could try various different values and try to find the optimum (often called &amp;quot;line minimisation&amp;quot;). (NB In the context of machine learning, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is sometimes called the &amp;quot;learning rate&amp;quot;.)&lt;/p&gt;&#xA;&lt;h3&gt;Finding the optimal step length&lt;/h3&gt;&#xA;&lt;p&gt;What determines what &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; should be? Let's Taylor-expand the function around our trial inputs, and write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;f(\mathbf{r}) \approx f(\mathbf{r}_0) + (\mathbf{r}-\mathbf{r}_0)^\dagger\nabla f(\mathbf{r}_0)+\frac{1}{2}(\mathbf{r}-\mathbf{r}_0)^\dagger\mathrm{B}.(\mathbf{r}-\mathbf{r}_0),\tag{2}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}$&lt;/span&gt; is the Hessian matrix, which is the matrix of second derivatives,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{B}_{ij}=\left.\frac{\partial^2 f}{\partial r_i \partial r_j}\right\vert_{\mathbf{r}=\mathbf{r}_0}.\tag{3}&#xA;$$&lt;/span&gt;&#xA;At the minimum, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}=\mathbf{r}_\mathrm{opt}$&lt;/span&gt;, we know that the gradient should be zero - so let's differentiate the Taylor expansion to get the gradient expression:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\nabla f(\mathbf{r}) \approx \nabla f(\mathbf{r}_0)+\mathrm{B}.(\mathbf{r}-\mathbf{r}_0),\tag{4}&#xA;$$&lt;/span&gt;&#xA;Now we set this to zero, and rearrange&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{eqnarray}{}&#xA;&amp;amp; \nabla f(\mathbf{r}_0)+\mathrm{B}.(\mathbf{r}_\mathrm{opt}-\mathbf{r}_0) &amp;amp;= 0\tag{5}\\&#xA;\Rightarrow &amp;amp; \mathrm{B}.(\mathbf{r}_\mathrm{opt}-\mathbf{r}_0) &amp;amp;= -\nabla f(\mathbf{r}_0)\tag{6}\\&#xA;\Rightarrow &amp;amp; (\mathbf{r}_\mathrm{opt}-\mathbf{r}_0) &amp;amp;= -\mathrm{B}^{-1}\nabla f(\mathbf{r}_0)\tag{7}\\ &#xA;\Rightarrow &amp;amp; \mathbf{r}_\mathrm{opt} &amp;amp;= \mathbf{r}_0 -\mathrm{B}^{-1}\nabla f(\mathbf{r}_0)\tag{8}&#xA;\end{eqnarray}&#xA;$$&lt;/span&gt;&#xA;Comparing this with equation \eqref{eq:step}, we see that the basic form is the same, except that the scalar &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; has been replaced by the matrix &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; is a diagonal matrix, and all the eigenvalues are the same, then it has the form,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{9}&#xA;\mathrm{B}^{-1}=\left(\begin{array}{ccc}&#xA;\lambda &amp;amp;    0    &amp;amp;  0 &amp;amp; \ldots\\&#xA;0       &amp;amp; \lambda &amp;amp;  0 &amp;amp; \ldots\\&#xA;0       &amp;amp;     0   &amp;amp;\lambda &amp;amp;  \\&#xA;\vdots  &amp;amp; \vdots &amp;amp;   &amp;amp; \ddots &#xA;\end{array}\right) =\lambda\mathrm{I},&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathrm{I}$&lt;/span&gt; is the identity matrix. In this case, setting &lt;span class=&quot;math-container&quot;&gt;$\alpha=\lambda$&lt;/span&gt; will give the ideal step length and, in fact, will jump straight to the minimum of the function in a single step.&lt;/p&gt;&#xA;&lt;p&gt;If the eigenvalues of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; are different, then there is no single value of &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; which can mimic &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; perfectly. The best approximation is for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; to match &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; as closely as possible. Since we used &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; because of the relation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{B}^{-1}\mathrm{B}=I,\tag{10}&#xA;$$&lt;/span&gt;&#xA;this leads naturally to the conclusion that we want&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha\mathrm{B} \approx I.\tag{11}&#xA;$$&lt;/span&gt;&#xA;The identity matrix &lt;span class=&quot;math-container&quot;&gt;$\mathrm{I}$&lt;/span&gt; has eigenvalues of 1, and the best approximation for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is when the average eigenvalue of &lt;span class=&quot;math-container&quot;&gt;$\alpha\mathrm{B}$&lt;/span&gt; is one.&lt;/p&gt;&#xA;&lt;h3&gt;Density mixing&lt;/h3&gt;&#xA;&lt;p&gt;In the case of density mixing, the function we wish to minimise is the difference between the input and output densities in the self-consistent field cycle. The relevant Hessian is the static dielectric matrix for the system, which is why VASP is using that for its reporting -- although note that VASP is not actually computing the dielectric matrix, because that is computationally quite expensive. Instead, it builds up an approximate form for the dielectric matrix over the course of the calculation (see below).&lt;/p&gt;&#xA;&lt;p&gt;NB it is actually possible to use the dielectric matrix, either by computing it directly (perhaps only for the lowest wavevectors; ABINIT can do this), or using it implicitly by solving the perturbation theory equations iteratively for the dielectric response.&lt;/p&gt;&#xA;&lt;h3&gt;Beyond gradient optimisation&lt;/h3&gt;&#xA;&lt;p&gt;There are two additional methods which are commonly used: preconditioning; and quasi-Newton methods. I will not go into details here, but briefly preconditioning is a technique for transforming your problem into one where the eigenvalues are closer together (&amp;quot;compressing the eigenspectrum&amp;quot;), and quasi-Newton methods are a way to build up a model of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{B}^{-1}$&lt;/span&gt; in order to capture the change of search direction as well.&lt;/p&gt;&#xA;&lt;p&gt;In the case of density-mixing methods, preconditioning is commonly done using an approximate inverse dielectric matrix proposed by Manninen et al, although it is usually named after Kerker, who noted its wider applicability. It is based on the asymptotic limit of the dielectric matrix at long wavelengths, where the response of the material is dominated by the electron-electron interaction (the Hartree potential, in density functional theory).&lt;/p&gt;&#xA;&lt;p&gt;Quasi-Newton methods start with an initial approximation for the dielectric matrix (the Hessian), which is often the Kerker form, and successively improve it using the actual change in the density during the self-consistent field cycles. There are different ways to do this, and the most common are those of Broyden and Pulay (Anderson). In the case of VASP, it is actually this &lt;em&gt;approximate&lt;/em&gt; dielectric matrix which is used for the eigenvalue decomposition, since this is much faster to compute.&lt;/p&gt;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.12.4012&quot; rel=&quot;noreferrer&quot;&gt;Electrons and positrons in metal vacancies&lt;/a&gt;&amp;quot;, M. Manninen, R. Nieminen, P. Hautojärvi, and J. Arponen, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;12&lt;/strong&gt;, 4012 (1975).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.23.3082&quot; rel=&quot;noreferrer&quot;&gt;Efficient iteration scheme for self-consistent pseudopotential calculations&lt;/a&gt;&amp;quot;, G. P. Kerker, &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;23&lt;/strong&gt;, 3082 (1981).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://www.ams.org/journals/mcom/1965-19-092/S0025-5718-1965-0198670-6/&quot; rel=&quot;noreferrer&quot;&gt;A class of methods for solving nonlinear simultaneous equations&lt;/a&gt;&amp;quot;, C. G. Broyden, &lt;em&gt;Math. Comp.&lt;/em&gt; &lt;strong&gt;19&lt;/strong&gt;, 577-593 (1965).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1016/0009-2614(80)80396-4&quot; rel=&quot;noreferrer&quot;&gt;Convergence acceleration of iterative sequences. the case of scf iteration&lt;/a&gt;&amp;quot;, P. Pulay, &lt;em&gt;Chem. Phys. Lett.&lt;/em&gt; &lt;strong&gt;73&lt;/strong&gt;, 393 (1980).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1002/jcc.540030413&quot; rel=&quot;noreferrer&quot;&gt;Improved SCF convergence acceleration&lt;/a&gt;&amp;quot;, P. Pulay, &lt;em&gt;J. Comput. Chem.&lt;/em&gt; &lt;strong&gt;3&lt;/strong&gt;, 556(1982).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;&lt;a href=&quot;https://doi.org/10.1145/321296.321305&quot; rel=&quot;noreferrer&quot;&gt;Iterative Procedures for Nonlinear Integral Equations&lt;/a&gt;&amp;quot;, D. G. Anderson, &lt;em&gt;J. ACM&lt;/em&gt; &lt;strong&gt;12&lt;/strong&gt; 4 (1965).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="403" LastEditorUserId="5" LastEditDate="2022-03-17T02:38:21.580" LastActivityDate="2022-03-17T02:38:21.580" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8811" PostTypeId="1" AcceptedAnswerId="8814" CreationDate="2022-03-17T15:29:37.350" Score="9" ViewCount="129" Body="&lt;p&gt;The Fermi surface is something that separates unfilled orbitals from filled orbitals. I found in some documents that electrical properties are related to the shape of the Fermi surfaces. I am not clear about the significance of the Fermi surface shape. Can anyone explain and give examples or introduce more documents about Fermi surface? When we explore electrical properties, do we need to consider only the Fermi surface near the Fermi level?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2022-03-18T18:54:04.460" Title="What is the significance of Fermi surface shape?" Tags="|fermi-surface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8812" PostTypeId="1" CreationDate="2022-03-18T02:28:30.087" Score="8" ViewCount="91" Body="&lt;p&gt;During my undergraduate studies, I was introduced to oscillatory and nonlinear reactions, which are essentially chemical reactions oscillating far away from equilibrium conditions - A very visual example is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Belousov%E2%80%93Zhabotinsky_reaction&quot; rel=&quot;nofollow noreferrer&quot;&gt;BZ reaction&lt;/a&gt;. As I am not linked to this research area, I was wondering if there are new advancements or significant studies done that enhances our understanding in this field, possibly 2000-present.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cTQA8.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cTQA8.gif&quot; alt=&quot;BZ reaction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;P.S. It would be great if someone could point to atomistic simulation studies of these reactions, as I couldn't find one as compared to other fields in materials modeling.&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2022-06-01T18:42:33.250" LastActivityDate="2022-06-01T18:42:33.250" Title="What are some recent significant developments/studies in theoretical nonlinear chemical dynamics?" Tags="|reference-request|one-topic-per-answer|atomistic-simulation|nonequilibrium|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8813" PostTypeId="1" CreationDate="2022-03-18T06:57:59.233" Score="4" ViewCount="64" Body="&lt;p&gt;Given the start configuration (.pdb), topology file (topol.top) and run file(water.mdp).&#xA;I want to generate the forces on atoms. I tried, using:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx grompp -f water.mdp -c water_1.gro -p topol.top -o water.tpr -maxwarn 2&#xA;gmx traj -f water_1.gro -s water.tpr -of force.xvg -ox coords.xvg&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the forces.xvg file turned up empty. What are my other alternatives here?&lt;/p&gt;&#xA;&lt;p&gt;P.S. I used charmm force-field.&lt;/p&gt;&#xA;" OwnerUserId="1102" LastActivityDate="2022-03-18T06:57:59.233" Title="Gromacs generate forces using .pdb topol.top and .mdp file" Tags="|molecular-dynamics|gromacs|forcefields|intermolecular-forces|" AnswerCount="0" CommentCount="2" ClosedDate="2022-04-12T14:35:54.803" ContentLicense="CC BY-SA 4.0" />
  <row Id="8814" PostTypeId="2" ParentId="8811" CreationDate="2022-03-18T18:54:04.460" Score="7" Body="&lt;p&gt;Many electronic properties, particularly of metals, are directly related to the Fermi surface shape. Screening properties and conductivity are especially affected by the Fermi surface. For example, the explanation for why copper is a better conductor than iron involves the disconnected nature of iron's Fermi surface, see e.g. &lt;a href=&quot;https://chemistry.stackexchange.com/a/80673/98152&quot;&gt;this Chem.SE answer&lt;/a&gt;. Recall that the low-energy excitations dominate transport properties (at least in the linear response regime), and these are near the Fermi surface by definition. For more examples of the impact of Fermi surface shapes you may have a look at &lt;a href=&quot;https://doi.org/10.1088/0031-8949/91/5/053009&quot; rel=&quot;noreferrer&quot;&gt;S B Dugdale: Life on the edge: a beginner's guide to the Fermi surface. &lt;em&gt;Phys. Scr.&lt;/em&gt; &lt;strong&gt;91,&lt;/strong&gt; 053009 (2016).&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2022-03-18T18:54:04.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8816" PostTypeId="2" ParentId="8800" CreationDate="2022-03-19T09:19:21.020" Score="3" Body="&lt;p&gt;First of all it must be clarified that a lattice is a collection of geometrical point all characterized by a same surrounding (that is, each lattice point has the same number of nearest neighbour lattice points arranged with the same point distances and angles).&lt;/p&gt;&#xA;&lt;p&gt;Hence, widespread definitions such as “lattice distortion”, “lattice dynamics”, “lattice energy” and so on are misleading, but unfortunately commonly used; in this case the term “lattice” should be substituted by “structure”. A crystal structure is obtained by the convolution of a lattice with a basis (i.e. an atom of a group of atoms).&lt;/p&gt;&#xA;&lt;p&gt;Having clarified this, structural distortion can be evaluated by diffraction. Distortion can be dynamic or static. Pair distribution function analysis provides a better estimate of the Debye-Waller parameters, whereas the widths of the peaks give the bond distance distribution of the considered atomic pair. But this last information characterizes the local scale, not the structural parameters.&lt;/p&gt;&#xA;&lt;p&gt;Diffraction line (peak) broadening can be used for evaluating the structural strain, that is the fluctuation of the inter-planar distances along the different crystallographic directions. Simplifying, the components of the diffraction line profile have a &lt;span class=&quot;math-container&quot;&gt;$\tan(2\theta)$&lt;/span&gt; dependence on the scattering angle &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; by means of which strain along the different directions can be valuated.&lt;/p&gt;&#xA;&lt;p&gt;The qualitative analysis of the strain distribution is rather easy from high quality diffraction data, but an accurate quantitative evaluation is not. This is not a predictive method (neither is PDF analysis), but gives you qualitative information about the structural distortion.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastEditorUserId="7" LastEditDate="2022-03-19T12:31:17.173" LastActivityDate="2022-03-19T12:31:17.173" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8818" PostTypeId="1" CreationDate="2022-03-19T17:19:26.657" Score="9" ViewCount="480" Body="&lt;p&gt;I'm trying to write a 1D density functional theory code on Python to predict the electronic structure of certain ions using the local density approximation.&#xA;I'm trying to construct the hamiltonian for this system:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E \left[ n(r) \right] = -\frac 12  \frac{d^2}{dr^2} + V_H(r) + V_N(r) + V_x(r)\tag{1},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where: &lt;span class=&quot;math-container&quot;&gt;$$V_H(r)  = \int \frac{ n( r')}{| r - r'|} dr'\tag{2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've discretised my space and created matrix versions for each of the components of the energy functional but I'm not able to grasp how the &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; would look like as a matrix. To my understanding, it won't be diagonal but hermitian. I'm trying to use the trapezium method for numerical integration:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sum( n * delta_r_prime /np.sqrt(r - r_prime) )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but won't the denominator just be zero? I'm trying to understand what the matrix elements of &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; are and how to create this in Python but I'm getting really confused. I'd really appreciate it if someone could enlighten me on this!&lt;/p&gt;&#xA;" OwnerUserId="5105" LastEditorUserId="5" LastEditDate="2022-03-19T21:58:19.020" LastActivityDate="2022-03-20T22:01:50.873" Title="Numerically integrating the Hartree potential" Tags="|density-functional-theory|electronic-structure|python|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8819" PostTypeId="2" ParentId="8818" CreationDate="2022-03-19T22:32:30.103" Score="7" Body="&lt;p&gt;Based on your clarifications starting &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/60685584#60685584&quot;&gt;here&lt;/a&gt;, I see that you are starting with the simple case in which &lt;span class=&quot;math-container&quot;&gt;$n(r^\prime) = 1$&lt;/span&gt;. In this case we have the integral:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\int \frac{1}{|r-r^\prime|}\textrm{d}r^\prime,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for which can check to see whether or not our numerical integration procedure works by comparing with the &lt;a href=&quot;https://www.wolframalpha.com/input?i=Integrate+1%2F%7Cr-s%7C+with+respect+to+s&quot; rel=&quot;noreferrer&quot;&gt;analytic expression for the integral&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/p8xAp.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/p8xAp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To do the integral in Eq. 1 numerically, we need to know how to numerically integrate a function of two variables, &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r^\prime$&lt;/span&gt;, with respect to one of them &lt;span class=&quot;math-container&quot;&gt;$r^\prime$&lt;/span&gt;. This &lt;a href=&quot;https://www.google.com/search?q=numerical+integration+of+two+variable+function+with+repect+to+one+variable&amp;amp;oq=numerical+integration+of+two+variable+function+with+repect+to+one+variable&amp;amp;aqs=chrome..69i57.7755j0j7&amp;amp;sourceid=chrome&amp;amp;ie=UTF-8&quot; rel=&quot;noreferrer&quot;&gt;search for &amp;quot;numerical integration of two variable function with respect to one variable&amp;quot;&lt;/a&gt; results in &lt;a href=&quot;https://i.stack.imgur.com/QviP1.png&quot; rel=&quot;noreferrer&quot;&gt;many immediate results&lt;/a&gt;, including (in order) on the following high-quality Q/A venues:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.mathworks.com/matlabcentral/answers/110181-integration-of-function-with-two-variables-with-respect-to-one-of-them&quot; rel=&quot;noreferrer&quot;&gt;Matlab Answers&lt;/a&gt;: &amp;quot;&lt;strong&gt;Integration of function with two variables with respect to one of them&lt;/strong&gt;&amp;quot;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;How to implement the trapezoid rule in MATLAB is the same as what you would want to do in NumPy.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mathematica.stackexchange.com/q/47592/4295&quot;&gt;Mathematica StackExchange&lt;/a&gt;: &amp;quot;&lt;strong&gt;Numerical integration of two variable function&lt;/strong&gt;&amp;quot;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Although I admit that Mathematica's &lt;code&gt;NIntegrate&lt;/code&gt; function mentioned in the accepted answer, shelters you from getting to see the details, but the details for how to do it in MATLAB are indeed given in the question).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://stackoverflow.com/q/21285435/1271772&quot;&gt;StackOverflow&lt;/a&gt;: &amp;quot;&lt;strong&gt;numerical integration of two variable function over one variable only in C++ (using Numerical Recipes libraries)&lt;/strong&gt;&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.researchgate.net/post/what_are_the_methods_for_the_numerical_integration_of_a_function_of_more_than_one_variable&quot; rel=&quot;noreferrer&quot;&gt;ResearchGate&lt;/a&gt;: &amp;quot;&lt;strong&gt;What are the methods for the numerical integration of a function of more than one variable?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Basically what you are hoping to do is perfectly reasonable and has been implemented in many places, many times. You are on the right track, but as for your question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;but won't the denominator just be zero?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;you may just have allowed &lt;span class=&quot;math-container&quot;&gt;$r = r^\prime$&lt;/span&gt; at some point, which would have lead you to receive an error suggesting that your denominator is zero.&lt;/p&gt;&#xA;&lt;p&gt;If you look at the analytic expression for the integral, in my above screenshot, you'll see that even the analytic expression becomes ugly when &lt;span class=&quot;math-container&quot;&gt;$r=r^\prime$&lt;/span&gt;, particularly because you'd be evaluating &lt;span class=&quot;math-container&quot;&gt;$\log(0)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Notice also that the analytic expression (in the above screenshot) for the integral, looks remarkably similar to &lt;a href=&quot;https://www.wolframalpha.com/input?i=Integrate+1%2F%7Cu%7C+with+respect+to+u&quot; rel=&quot;noreferrer&quot;&gt;what you would get if you calculate the integral of a related 1-variable function&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\tag{2}&#xA;u &amp;amp;= r - r^\prime \\&#xA;\textrm{d}u &amp;amp;= -\textrm{d}r^\prime\\&#xA;-\int &amp;amp;\frac{1}{|u|}\textrm{d}u.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, while this last piece of information may be helpful in the early stages of your code development, in which you want to test your code for simple functions like &lt;span class=&quot;math-container&quot;&gt;$n(r^\prime)$&lt;/span&gt; = 1, the more general numerical techniques for calculating the integral of a 2-variable function with respect to one of the variables, may be the best way forward for the general case.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-03-19T22:32:30.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8821" PostTypeId="2" ParentId="8818" CreationDate="2022-03-20T22:01:50.873" Score="2" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$r^{-1}$&lt;/span&gt; operator is not bounded in 1D, as Nike's answer above illustrates: the integral diverges logarithmically. Indeed, it is well-known in the literature that even if you solve this by truncating &lt;code&gt;1/r&lt;/code&gt; to a constant beyind some small &lt;code&gt;r&lt;/code&gt; value, your answer depends pathologically on the truncation threshold and does not converge to an answer in the limit of no truncation i.e. the constant going to infinity.&lt;/p&gt;&#xA;&lt;p&gt;Thus, your physical model is wrong. You need to use a softened Coulomb operator:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac 1 r \to \frac 1 {\sqrt{r^2 + d^2}}$$&lt;/span&gt;&#xA;with &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; a parameter.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-03-20T22:01:50.873" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8822" PostTypeId="1" AcceptedAnswerId="8823" CreationDate="2022-03-21T02:33:47.780" Score="4" ViewCount="169" Body="&lt;p&gt;Some time ago, I conducted a discussion with &lt;a href=&quot;https://scholar.google.com/citations?user=qbI2lYgAAAAJ&amp;amp;hl=zh-CN&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dr. Gui-Bin Liu&lt;/a&gt; on topological materials &lt;a href=&quot;https://github.com/goodluck1982/SpaceGroupIrep/discussions/23#discussioncomment-2173638&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. One relevant thing he said was:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The format of trace.txt file is only a necessary condition to be used by getBandRep.&lt;br&gt;&#xA;Another issue is that the rotation matrices used, especially the SU(2) spin rotation matrix, have to be the same with vasp and vasp2trace.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;On the other hand, as for SU(2) representation, there are two popular gauges: Pauli and Cartan, as commented here. So, I want to know/confirm the precise forms of these matrices used by VASP. Any tips would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;I also asked on the VASP forum &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=18421&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Postscript:&lt;/p&gt;&#xA;&lt;p&gt;@&lt;a href=&quot;https://mattermodeling.stackexchange.com/users/5/nike-dattani&quot;&gt;nike-dattani&lt;/a&gt;, Thank you for your inspection. I also did a similar check in the &lt;code&gt;vasp.6.3.0&lt;/code&gt; source code and found these definitions that are exactly the same as your conclusion and a related variable called &lt;code&gt;PAULI_VECTOR&lt;/code&gt;, which I have listed below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ rg -A8 -i 'pauli-mat' |head -9&#xA;src/spinsym.F:    ! Define Pauli-matrices&#xA;src/spinsym.F-    sig=zero&#xA;src/spinsym.F-    sig(1,2,1)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;src/spinsym.F-    sig(2,1,1)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;src/spinsym.F-    sig(1,2,2)=cmplx( 0.0_q,-1.0_q,kind=q)&#xA;src/spinsym.F-    sig(2,1,2)=cmplx( 0.0_q, 1.0_q,kind=q)&#xA;src/spinsym.F-    sig(1,1,3)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;src/spinsym.F-    sig(2,2,3)=cmplx(-1.0_q, 0.0_q,kind=q)&#xA;src/spinsym.F-    !---&#xA;&#xA;$ rg -A45 -B3 -i 'The PAULI_VECTOR is ' | head -46&#xA;src/locproj.F-#if 0&#xA;src/locproj.F-      ! Diagonalize the Pauli vector times quantization axis vector dot(SPIN_QAXIS,PAULI_VECTOR)&#xA;src/locproj.F-      ! to obtain the eigenvectors and eigenvalues.&#xA;src/locproj.F:      ! The PAULI_VECTOR is (Sx,Sy,Sx) where Sx,Sy,Sz are the Pauli matrices&#xA;src/locproj.F-      SPIN_QAXIS = SPIN_QAXIS/SQRT(SUM(SPIN_QAXIS**2))&#xA;src/locproj.F-      PV_MATRIX = SIGMADOTN(SPIN_QAXIS)&#xA;src/locproj.F-      CALL ZGEEV( 'N', 'V', 2, PV_MATRIX, 2, ZW, ZVL, 1, &amp;amp;&#xA;src/locproj.F-           ZVR, 2, ZWORK, 4, RWORK, INFO)&#xA;src/locproj.F-      ! debug: Verify that these are eigenvectors&#xA;src/locproj.F-      !PV_MATRIX = SIGMADOTN(SPIN_QAXIS)&#xA;src/locproj.F-      !WRITE(*,*) DOT_PRODUCT(ZVR(:,1),MATMUL(PV_MATRIX,ZVR(:,1)))&#xA;src/locproj.F-      !WRITE(*,*) DOT_PRODUCT(ZVR(:,2),MATMUL(PV_MATRIX,ZVR(:,2)))&#xA;src/locproj.F-#else&#xA;src/locproj.F-      ! Use spin rotation matrix to rotate quantization axis.&#xA;src/locproj.F-      ! The rotation matrix is obtained from two spin rotations.&#xA;src/locproj.F-      ! A spin rotation is defined by an angle and an axis&#xA;src/locproj.F-      ! R_s(theta,axis) = exp(-I*theta/2*dot(axis,pauli_vector))&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! The two rotations are the same as the EULER routine:&#xA;src/locproj.F-      ! 1. rotation around y-axis of beta&#xA;src/locproj.F-      ! R_s(beta,y) = [ cos(beta/2)   -sin(beta/2) ]&#xA;src/locproj.F-      !               [ sin(beta/2     cos(beta/2) ]&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! 2. rotation around z-axis of alpha&#xA;src/locproj.F-      ! R_s(alpha,z) = [ exp(-I*alpha/2)              0 ]&#xA;src/locproj.F-      !                [               0 exp(I*alpha/2) ]&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! The spin rotation is given by&#xA;src/locproj.F-      ! R = R_s(alpha,z)*R_s(beta,y)&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! Rotating the spin up and down states of Sz yields:&#xA;src/locproj.F-      ! ZVR(:,1) = R [1,0]&#xA;src/locproj.F-      ! ZVR(:,2) = R [0,1]&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! This is equivalent to the case above because:&#xA;src/locproj.F-      ! R Sz Dagger(R) = dot(SPIN_QAXIS,PAULI_VECTOR)&#xA;src/locproj.F-      ! i.e. rotating the Sz operator we obtain the same operator that we diagonalize above&#xA;src/locproj.F-      ! This is equivalent to rotating the eigenvectors of the Sz operator (stored in ZVR)&#xA;src/locproj.F-      CALL EULER(SPIN_QAXIS,ALPHA,BETA)&#xA;src/locproj.F-      ZVR(:,1) = [ COS(BETA/2)*EXP(-CMPLX(0.0_q,ALPHA/2,q)),SIN(BETA/2)*EXP(CMPLX(0.0_q,ALPHA/2,q))]&#xA;src/locproj.F-      ZVR(:,2) = [-SIN(BETA/2)*EXP(-CMPLX(0.0_q,ALPHA/2,q)),COS(BETA/2)*EXP(CMPLX(0.0_q,ALPHA/2,q))]&#xA;src/locproj.F-      ! debug: Verify that these are eigenvectors&#xA;src/locproj.F-      !PV_MATRIX = SIGMADOTN(SPIN_QAXIS)&#xA;src/locproj.F-      !WRITE(*,*) DOT_PRODUCT(ZVR(:,1),MATMUL(PV_MATRIX,ZVR(:,1)))&#xA;src/locproj.F-      !WRITE(*,*) DOT_PRODUCT(ZVR(:,2),MATMUL(PV_MATRIX,ZVR(:,2)))&#xA;src/locproj.F-#endif&#xA;&#xA;$ rg -A11 -i 'two rotations' |head -11&#xA;src/locproj.F:      ! The two rotations are the same as the EULER routine:&#xA;src/locproj.F-      ! 1. rotation around y-axis of beta&#xA;src/locproj.F-      ! R_s(beta,y) = [ cos(beta/2)   -sin(beta/2) ]&#xA;src/locproj.F-      !               [ sin(beta/2     cos(beta/2) ]&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! 2. rotation around z-axis of alpha&#xA;src/locproj.F-      ! R_s(alpha,z) = [ exp(-I*alpha/2)              0 ]&#xA;src/locproj.F-      !                [               0 exp(I*alpha/2) ]&#xA;src/locproj.F-      !&#xA;src/locproj.F-      ! The spin rotation is given by&#xA;src/locproj.F-      ! R = R_s(alpha,z)*R_s(beta,y)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Regards,&#xA;Hongyi Zhao&lt;/p&gt;&#xA;" OwnerUserId="5128" LastEditorUserId="5128" LastEditDate="2022-03-22T01:21:06.740" LastActivityDate="2022-03-22T01:21:06.740" Title="What are the precise forms for the SU(2) and rotation matrices in VASP?" Tags="|vasp|mathematical-modeling|spin|topological-matter|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8823" PostTypeId="2" ParentId="8822" CreationDate="2022-03-21T04:00:30.007" Score="4" Body="&lt;p&gt;The answer you got on the VASP forum &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=18421&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (thank you for giving us that in your question!) said to look in &lt;code&gt;spinsym.F&lt;/code&gt; but was not clear at all, especially due to the typo in the formatting of that file name.&lt;/p&gt;&#xA;&lt;p&gt;I just looked in the file &lt;code&gt;vasp.5.4.4_2D/src/spinsym.F&lt;/code&gt; and did a case-insensitive search for &amp;quot;Pauli&amp;quot; and found this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! Define Pauli-matrices&#xA;sig=zero&#xA;sig(1,2,1)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;sig(2,1,1)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;sig(1,2,2)=cmplx( 0.0_q,-1.0_q,kind=q)&#xA;sig(2,1,2)=cmplx( 0.0_q, 1.0_q,kind=q)&#xA;sig(1,1,3)=cmplx( 1.0_q, 0.0_q,kind=q)&#xA;sig(2,2,3)=cmplx(-1.0_q, 0.0_q,kind=q)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I did the same for &amp;quot;Cartan&amp;quot; and found nothing (which did not surprise me &lt;em&gt;&lt;strong&gt;at all&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Therefore I can conclude the following: All Pauli matrices are given exactly as in the introduction of &lt;a href=&quot;https://en.wikipedia.org/wiki/Pauli_matrices&quot; rel=&quot;nofollow noreferrer&quot;&gt;this article&lt;/a&gt;, and they are labeled as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;sig(:,:,1)&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\sigma_x$&lt;/span&gt; &lt;br&gt;&#xA;&lt;code&gt;sig(:,:,2)&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\sigma_y$&lt;/span&gt; &lt;br&gt;&#xA;&lt;code&gt;sig(:,:,3)&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\sigma_z$&lt;/span&gt; &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I have never run a VASP calculation in my life, nor ever looked at any of its code, but I'm not at all surprised that they chose to define the SU(2) operators in this way!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Likwise for the rotation matrices, we have:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!The two rotations are the same as the EULER routine:&#xA;! 1. rotation around y-axis of beta&#xA;! R_s(beta,y) = [ cos(beta/2)   -sin(beta/2) ]&#xA;!               [ sin(beta/2     cos(beta/2) ]&#xA;!&#xA;! 2. rotation around z-axis of alpha&#xA;! R_s(alpha,z) = [ exp(-I*alpha/2)              0 ]&#xA;!                [               0 exp(I*alpha/2) ]&#xA;!&#xA;! The spin rotation is given by&#xA;! R = R_s(alpha,z)*R_s(beta,y)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-03-21T05:36:04.573" LastActivityDate="2022-03-21T05:36:04.573" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8826" PostTypeId="1" CreationDate="2022-03-21T08:41:17.977" Score="3" ViewCount="272" Body="&lt;p&gt;When doing RPA calculations &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ACFDT/RPA_calculations&quot; rel=&quot;nofollow noreferrer&quot;&gt;as explained here&lt;/a&gt;, if I want to calculate it with hybrid PBE0 should I put &lt;code&gt;LHFCALC = .TRUE.&lt;/code&gt; for just step 1 or step 1, step 3 and step 4?&lt;/p&gt;&#xA;" OwnerUserId="4894" LastEditorUserId="7" LastEditDate="2022-03-21T12:56:27.170" LastActivityDate="2022-03-21T12:56:27.170" Title="RPA calculations with Hybrid Functionals" Tags="|density-functional-theory|vasp|software|random-phase-approximation|" AnswerCount="0" CommentCount="9" ClosedDate="2022-09-07T22:40:51.410" ContentLicense="CC BY-SA 4.0" />
  <row Id="8827" PostTypeId="2" ParentId="8645" CreationDate="2022-03-21T17:59:52.287" Score="1" Body="&lt;p&gt;As suggested I changed the command line in&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt=modredundant freq m062x/6-31g(d) scrf=(smd,solvent=n-Hexane,iterative)&#xA;geom=connectivity&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And thanks to the iterative calculation of the SMD solvation, the geometry converged&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-03-21T17:59:52.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8828" PostTypeId="1" AcceptedAnswerId="10056" CreationDate="2022-03-21T18:26:24.210" Score="24" ViewCount="827" Body="&lt;p&gt;I'd like to introduce band structure to a class of undergraduate chemists, along the lines of Roald Hoffmann's &lt;em&gt;Solids and Surfaces&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;That is, I'd like to start with a s-band in 1D, which is easy because you can do it with hydrogen:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/P8OlZ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/P8OlZ.png&quot; alt=&quot;1D band structure of hydrogen 1s&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But then I'd like to look at different 2p-bands in 1D, 3d-bands in 1D, and build up a 2D and 3D band structure.&lt;/p&gt;&#xA;&lt;p&gt;For example, here's a 2p band in 1D which naturally introduces nodes (from &lt;em&gt;Solids and Surfaces&lt;/em&gt; by Roald Hoffmann):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MyUu0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MyUu0.png&quot; alt=&quot;1D band structure of p-orbitals&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And here's how this builds the 2D case with both s and p orbitals (also from &lt;em&gt;Solids and Surfaces&lt;/em&gt; by Hoffmann):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2c144l.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2c144l.png&quot; alt=&quot;2D band structure including s and p orbitals&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Ideally all of these would make it fairly easy to change the lattice parameters to show the effects, delocalization vs. localization, etc.&lt;/p&gt;&#xA;&lt;p&gt;There are plenty of codes and notes for &lt;em&gt;real&lt;/em&gt; materials. Are there already some tight-binding packages / notebooks for teaching purposes?&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2023-03-07T18:35:18.987" LastActivityDate="2023-03-13T07:22:28.257" Title="Easy ways to generate &quot;teaching&quot; band structures in Python?" Tags="|band-structure|python|tight-binding|education|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8829" PostTypeId="1" CreationDate="2022-03-21T19:06:47.857" Score="13" ViewCount="279" Body="&lt;p&gt;I'm pretty new to DFT calculations but I'm trying to learn how to do &lt;a href=&quot;https://en.wikipedia.org/wiki/X-ray_photoelectron_spectroscopy&quot; rel=&quot;nofollow noreferrer&quot;&gt;X-ray photoelectron spectroscopy&lt;/a&gt; (XPS) calculations, particularly for open-shell molecular systems in common non-periodic DFT codes.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5146" LastEditorUserId="5" LastEditDate="2022-11-01T18:23:50.500" LastActivityDate="2022-11-01T18:23:50.500" Title="Calculating Core-Level Binding Energies (XPS) using DFT" Tags="|density-functional-theory|software-recommendations|spectroscopy|excited-states|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8830" PostTypeId="1" CreationDate="2022-03-21T20:57:40.567" Score="4" ViewCount="65" Body="&lt;p&gt;Pretty much what the title states: what is a procedure to construct a binodal and spinodal curve (temperature against composition)?&lt;/p&gt;&#xA;&lt;p&gt;I am running an on-lattice polymer solution Monte Carlo simulation with a phase transition in an NVT ensemble and want to generate critical temperature curves (the UCST and LCST). I understand that the binodal is when &lt;span class=&quot;math-container&quot;&gt;$\frac{dF}{d\phi} =\mu=0$&lt;/span&gt;, but how does one go about doing that?&lt;/p&gt;&#xA;&lt;p&gt;One method I am considering is keeping track of heat capacity over a range of temperatures, given a concentration. In the event that there is a discontinuity, I will record that temperature and plot it against &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;. But is this a reasonable method? Does this work?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-03-21T20:57:40.567" Title="How to construct spinodal and binodal curves from a molecular simulation?" Tags="|monte-carlo|phase-transitions|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8831" PostTypeId="2" ParentId="8792" CreationDate="2022-03-22T15:27:42.217" Score="4" Body="&lt;p&gt;Worst option in terms of precision, but simplest one: make fixed atom every crystall cell. This way you will see familiar crystalline structure, but a lot of forces will remain between these fixed points. You will only see changes in extreme case, like change of a crystal cell. Example: research about high pressure change to a crystal structure, probably superconductors.&lt;/p&gt;&#xA;&lt;p&gt;Popular method with some precision: make atoms that are closer than a certain distance to a surface fixed. Idea is that in practice oxide is often attached to a substrate, and that substrate doesnt allow the oxide to move. You can study surface effects, catalytic activity for small molecules. Example: surface catalysts used in cars exchausts, hand warmers. Substrate plays an important role if oxide is a few nanometers, as it defines forces that keep the catalyst in a certain extended or contracted state. You can account for this by spacing atoms of the oxide's first layer accordingly. You will likely be able to see only a few layers, and then atoms' positions will become more chaotic, especially if spacing is far from what is found in a bulk crystal.&lt;/p&gt;&#xA;&lt;p&gt;Emerging field, nanotechnology: make only one or a few far away atoms fixed. This allows to study most complex topics like nucleation, nanoparticle growth and stabilization. You will likely not see any familiar patterns, small nucleation sites are full of defects, and structure looks chaotic. Example: some UV protection for plastics, window films.&lt;/p&gt;&#xA;&lt;p&gt;As usual, 'it depends'. What effects, what industry, do you want this study to be useful for? Select an appropriate complexity of a model based on that.&lt;/p&gt;&#xA;" OwnerUserId="1690" LastActivityDate="2022-03-22T15:27:42.217" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8832" PostTypeId="1" AcceptedAnswerId="8855" CreationDate="2022-03-22T18:06:59.450" Score="3" ViewCount="699" Body="&lt;p&gt;I'm wanting to use &lt;a href=&quot;https://manual.gromacs.org/documentation/5.1/onlinehelp/gmx-sasa.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;gmx sasa&lt;/a&gt;. I've done this on some residues I'm interested in analyzing. When I look at the output, I expect some value of &lt;span class=&quot;math-container&quot;&gt;$\pu{nm^2}$&lt;/span&gt; or maybe &lt;span class=&quot;math-container&quot;&gt;$\pu{\unicode[.8,0]{x212B}^2}$&lt;/span&gt;. Instead, the &lt;code&gt;.xvg&lt;/code&gt; file that is output has the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#   gmx_mpi sasa -f md_nojump.xtc -s md.tpr -n dyes.ndx -o gromacsSASA.xvg -odg gromacsSASADeltaG.xvg -or gromacsSASAAverage.xvg -tv gromacsSASAVolume.xvg -e 2010000 -pbc -rmpbc -probe 0.14 -ndots 24&#xA;# gmx sasa is part of G R O M A C S:&#xA;#&#xA;# Glycine aRginine prOline Methionine Alanine Cystine Serine&#xA;#&#xA;@    title &amp;quot;Solvent Accessible Surface&amp;quot;&#xA;@    xaxis  label &amp;quot;Time (ps)&amp;quot;&#xA;@    yaxis  label &amp;quot;Area (nm\S2\N)&amp;quot;&#xA;@TYPE xy&#xA;@ view 0.15, 0.15, 0.75, 0.85&#xA;@ legend on&#xA;@ legend box on&#xA;@ legend loctype view&#xA;@ legend 0.78, 0.8&#xA;@ legend length 2&#xA;@ s0 legend &amp;quot;Total&amp;quot;&#xA;      0.000   11.749&#xA;     10.000   11.430&#xA;     20.000   11.209&#xA;     30.000   11.114&#xA;     40.000   11.620&#xA;     50.000   11.810&#xA;     60.000   10.976&#xA;     70.000   11.592&#xA;     80.000   10.932&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is a sample of what the atoms I'm interested. They are a part of a DNA-ligand type system. They are about 120 atoms total I'm looking at.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/qXIGF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qXIGF.png&quot; alt=&quot;Molecules analyzed by gmx SASA&quot; /&gt;&lt;/a&gt;&#xA;Does anyone know what that area unit is? It looks something like (nm)(seconds^-2)(Newton^-1). This would not be an area unit if that's the case, so this doesn't make sense to me.&lt;/p&gt;&#xA;&lt;p&gt;Or maybe it is nm^2/(number of dots)?. I think that might make sense, but the GROMACS documentation doesn't say. The paper they reference that talks about the algorithm doesn't give any kind of hints for units either.&lt;/p&gt;&#xA;" OwnerUserId="3596" LastEditorUserId="3596" LastEditDate="2022-03-23T20:51:37.520" LastActivityDate="2022-03-26T01:54:46.913" Title="Units of SASA generated from GROMACS gmx_sasa?" Tags="|gromacs|surfaces|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8833" PostTypeId="2" ParentId="8412" CreationDate="2022-03-22T18:16:07.283" Score="2" Body="&lt;p&gt;Just to give you another option if you want to keep using pipe and echo. I have been doing it with the following syntax:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo &amp;quot;1 13&amp;quot; | gmx...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This had been working for me, but I like the answer currently.&lt;/p&gt;&#xA;" OwnerUserId="3596" LastActivityDate="2022-03-22T18:16:07.283" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8834" PostTypeId="1" CreationDate="2022-03-23T00:07:36.263" Score="2" ViewCount="303" Body="&lt;p&gt;I'm building multilayer structure. I build the heterostructure importing the the to phase of structure in VESTA&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;File -&amp;gt; New structure -&amp;gt; Phase -&amp;gt; Import&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now I want rotate second layer of the structure (e.g. 30∘). VESTA has a rotation matrix in &lt;code&gt;Unit -&amp;gt; Transform&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uJsaS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uJsaS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What is the form of this matrix? In case that I want make a matrix for an arbitrary angle (e.g. from 0∘ to 30∘)&#xA;`&lt;/p&gt;&#xA;&lt;p&gt;Last, and not less important. When I have the two structures and I export (e.g. VASP) only one of two is exported, the other is ignored.&lt;/p&gt;&#xA;&lt;p&gt;How can I export all atoms of the heterostructure to fractional coordinates file (VASP POSCAR)?&lt;/p&gt;&#xA;" OwnerUserId="5152" LastActivityDate="2022-03-23T00:07:36.263" Title="How to rotate layer of heterostructure and save it to fractional coordinate using VESTA?" Tags="|crystallography|vesta|materials-design|heterostructures|" AnswerCount="0" CommentCount="4" ClosedDate="2022-09-24T03:21:54.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="8835" PostTypeId="1" AcceptedAnswerId="9651" CreationDate="2022-03-23T12:06:32.583" Score="9" ViewCount="482" Body="&lt;p&gt;This is my first time asking a question - if I mess something up please let me know and I'll amend. I believe this goes beyond questions on how to use QE so here seems appropriate over the QE forums.&lt;/p&gt;&#xA;&lt;p&gt;I've been running a lot of DFT simulations with QuantumESPRESSO, and run into an interesting issue with supercells. To be clear, I am not talking about band folding (unless I'm very mistaken). I'm looking at surface relaxations and surface band structures, and have found that a supercell band structure comes out different &lt;strong&gt;even when the kpath does not include any components in the direction of the increase in size of the unit cell&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I've attached a quick example with Sodium, comparing the unit cell and 1x1x2 supercell. This is not using relaxed values in the name of convenience, but the error persists in my main investigations with fully relaxed/converged values. The supercell is 1x1x2 along z, and the k-path (slightly peculiarly, I know) does not include anything in the kz direction. As you can see, there are twice as many bands and they're all over the place.&lt;/p&gt;&#xA;&lt;p&gt;I know that supercells slightly break QE's symmetry detection algorithm, so it is presumably guessing the irrep content wrong. However, physically we should expect these extra bands to be 'accidentally' degenerate with the bulk bands of the conventional unit cell.&lt;/p&gt;&#xA;&lt;p&gt;Inputs:&lt;/p&gt;&#xA;&lt;p&gt;Unit cell scf&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation = 'scf'&#xA;        restart_mode = 'from_scratch'&#xA;        prefix = 'Na'&#xA;        outdir = './outdir/'&#xA;        pseudo_dir = '/pseudodir/'&#xA;        etot_conv_thr = 1e-8&#xA;/&#xA;&amp;amp;SYSTEM&#xA;        ibrav=1, celldm(1) = 8.111,&#xA;        nat = 2, ntyp = 1,&#xA;        nbnd = 25&#xA;        ecutrho = 325,&#xA;        ecutwfc = 80,&#xA;        occupations = 'smearing'&#xA;        smearing = 'gaussian'&#xA;        degauss = 0.01&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr=1e-8&#xA;        !mixing_beta = 0.5&#xA;/&#xA;ATOMIC_SPECIES&#xA; Na     22.99   Na.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA; Na 0.000000 0.000000 0.000000&#xA; Na 0.5 0.5 0.5&#xA;&#xA;K_POINTS (automatic)&#xA; 12 12 12 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Unit cell bands&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation = 'bands'&#xA;        restart_mode = 'from_scratch'&#xA;        prefix = 'Na'&#xA;        outdir = './outdir/'&#xA;        pseudo_dir = '/pseudodir/'&#xA;        etot_conv_thr = 1e-8&#xA;/&#xA;&amp;amp;SYSTEM&#xA;        ibrav=1, celldm(1) = 8.111,&#xA;        nat = 2, ntyp = 1,&#xA;        nbnd = 25,&#xA;        ecutrho = 325,&#xA;        ecutwfc = 80,&#xA;        occupations = 'smearing'&#xA;        smearing = 'gaussian'&#xA;        degauss = 0.01&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr=1e-8&#xA;        mixing_beta = 0.5&#xA;/&#xA;ATOMIC_SPECIES&#xA; Na     22.99   Na.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA; Na 0.000000 0.000000 0.000000&#xA; Na 0.5 0.5 0.5&#xA;&#xA;!weird k path with no z&#xA;K_POINTS {crystal_b}&#xA; 5&#xA;    0 0 0 20 !G&#xA;        0.5 -0.5 0 20 !H&#xA;        0 0.5 0 20 !N&#xA;        0.25 0.25 0 20 !P&#xA;        0 0 0 1 !G&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Supercell scf&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation = 'scf'&#xA;        restart_mode = 'from_scratch'&#xA;        prefix = 'NaSC'&#xA;        outdir = './outdir/'&#xA;        pseudo_dir = '/pseudodir/'&#xA;        etot_conv_thr = 1e-8&#xA;/&#xA;&amp;amp;SYSTEM&#xA;        ibrav=6, celldm(1) = 8.111, celldm(3) = 2,&#xA;        nat = 4, ntyp = 1,&#xA;        nbnd = 50&#xA;        ecutrho = 325,&#xA;        ecutwfc = 80,&#xA;        occupations = 'smearing'&#xA;        smearing = 'gaussian'&#xA;        degauss = 0.01&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr=1e-8&#xA;        !mixing_beta = 0.5&#xA;/&#xA;ATOMIC_SPECIES&#xA; Na     22.99   Na.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA; Na 0.000000 0.000000 0.000000&#xA; Na 0.5 0.5 0.5&#xA; Na 0 0 1&#xA; Na 0.5 0.5 1.5&#xA;K_POINTS (automatic)&#xA; 12 12 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Supercell bands&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation = 'bands'&#xA;        restart_mode = 'from_scratch'&#xA;        prefix = 'NaSC'&#xA;        outdir = './outdir/'&#xA;        pseudo_dir = '/pseudodir/'&#xA;        etot_conv_thr = 1e-8&#xA;/&#xA;&amp;amp;SYSTEM&#xA;        ibrav=6, celldm(1) = 8.111, celldm(3) = 2,&#xA;        nat = 4, ntyp = 1,&#xA;        nbnd = 50,&#xA;        ecutrho = 325,&#xA;        ecutwfc = 66,&#xA;        occupations = 'smearing'&#xA;        smearing = 'gaussian'&#xA;        degauss = 0.01&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr=1e-8&#xA;        mixing_beta = 0.5&#xA;/&#xA;ATOMIC_SPECIES&#xA; Na     22.99   Na.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA; Na 0.000000 0.000000 0.000000&#xA; Na 0.5 0.5 0.5&#xA; Na 0 0 1&#xA; Na 0.5 0.5 1.5&#xA;K_POINTS {crystal_b}&#xA; 5&#xA;    0 0 0 20 !G&#xA;        0.5 -0.5 0 20 !H&#xA;        0 0.5 0 20 !N&#xA;        0.25 0.25 0 20 !P&#xA;        0 0 0 1 !G&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the band structures:&lt;/p&gt;&#xA;&lt;p&gt;Unit cell:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/adm4S.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/adm4S.png&quot; alt=&quot;Unit cell&quot; /&gt;&lt;/a&gt;&#xA;Supercell:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/OID8L.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OID8L.png&quot; alt=&quot;Supercell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Has anyone seen this before? Can anyone help explain why this happens? Even better, can anyone fix this?&#xA;Thanks.&lt;/p&gt;&#xA;&lt;p&gt;Edit 1: Thank you to Camps for pointing out an error - I believe I've fixed this now.&lt;/p&gt;&#xA;" OwnerUserId="5154" LastEditorUserId="5154" LastEditDate="2022-03-23T14:05:57.220" LastActivityDate="2022-09-12T09:38:34.527" Title="Different band structure in supercell, but not due to band folding" Tags="|density-functional-theory|quantum-espresso|band-structure|supercell|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8836" PostTypeId="1" CreationDate="2022-03-23T14:02:45.590" Score="3" ViewCount="509" Body="&lt;p&gt;I have to calculate the S1 - T1 energy gap using coupled cluster (STEOM-DLPNO-CCSD) in ORCA. The output file contains only singlet energies.&#xA;IROOT=... (no notation singlet or triplet).&#xA;I tried adding &amp;quot;DoTriplet true&amp;quot;, but it didn't work.&#xA;I would like to know how to do it with an example of an input file.&lt;/p&gt;&#xA;" OwnerUserId="5156" LastEditorUserId="5" LastEditDate="2022-03-23T20:52:18.807" LastActivityDate="2022-03-25T04:11:48.523" Title="STEOM-DLPNO-CCSD" Tags="|orca|software-input-file-request|coupled-cluster|excited-states|" AnswerCount="0" CommentCount="8" ClosedDate="2022-12-11T13:49:40.417" ContentLicense="CC BY-SA 4.0" />
  <row Id="8837" PostTypeId="1" CreationDate="2022-03-23T15:13:17.390" Score="2" ViewCount="132" Body="&lt;p&gt;I am working on Pt(111) / nanoparticles with various ligands, I am mainly using two softwares:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;A well known general purpose plane-wave code (Quantum Espresso).&lt;/li&gt;&#xA;&lt;li&gt;A less known software that is also aiming general purpose with plane-wave accuracy, the theory is a little bit more complicated (Wannier functions). It has been actively developed for 20 years.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The second software has difficulties performing geometry optimisations to a force threshold that I would consider not really tight (0.25 eV/A). The force gradient has an oscillating behaviour, it is getting down but really slowly (50 geometry iterations to get to 0.4 eV/A) as a comparison Quantum Espresso get to 0.01 eV/A in 30 iterations.&lt;/p&gt;&#xA;&lt;p&gt;From what I have seen so far this problem seems to be a general problem and not only restricted to my system.&lt;/p&gt;&#xA;&lt;p&gt;I have different persons telling me two possible explanations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This problem is inherent to Wannier wavefunctions DFT, due to the truncation applied on the orbitals, forces will have some noise.&lt;/li&gt;&#xA;&lt;li&gt;This problem is due to a bad geometry optimiser which needs to be rewritten.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Is there anyone on this Stack Exchange with experience on this topic or any references that might help my case?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2022-03-23T15:13:17.390" Title="Force convergence in Wannier orbitals based DFT code" Tags="|density-functional-theory|geometry-optimization|plane-waves|" AnswerCount="0" CommentCount="14" ClosedDate="2022-11-02T00:31:30.003" ContentLicense="CC BY-SA 4.0" />
  <row Id="8838" PostTypeId="1" CreationDate="2022-03-23T20:41:20.297" Score="9" ViewCount="2503" Body="&lt;p&gt;I have been trying to take an FFT of the radial distribution function to calculate a structure factor. My understanding is this is the same as the regular FFT from the time to frequency domain. The calculation should be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S(k) = 1 + \rho \int \exp(-ikr)g(r)dr$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which often in physics is taken as a radial Fourier transform, i.e.,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S(k) = 1 + 4\pi \rho \int r^{2} g(r)\frac{\sin(kr)}{kr}dr$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the density of the fluid. This is what it should look like for the simplest such system, argon:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pOQDW.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pOQDW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I imagine I can just follow Eq. 1. I have the data &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; for  that model system, so I do the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nfft = 2^nextpow2(length(gr));&#xA;dt = r(2) - r(1);&#xA;df = 1/dt;&#xA;Freq = (df/2)*linspace(0,1,nfft/2+1);&#xA;sk = fft(gr,nfft)/length(gr);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And then I think I should take the one-sided FFT and the amplitude following Eq. 1, so I plot the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;plot(Freq,1+rho*2*abs(sk(1:numel(Freq))))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I get something radically different from the known case, and it doesn't oscillate about 1. Note that &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; is interchangeable with &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;. I'm doing something wrong, but any ideas what? In posting here, I feel that my question is equal parts Matlab and computational physics.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorUserId="7" LastEditDate="2022-03-23T23:59:15.943" LastActivityDate="2022-03-24T13:50:07.363" Title="How to calculate a structure factor from a radial distribution function?" Tags="|structure|radial-distribution-function|diffraction|fourier-transform|matlab|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8839" PostTypeId="1" AcceptedAnswerId="8879" CreationDate="2022-03-24T09:56:04.503" Score="6" ViewCount="1113" Body="&lt;p&gt;I want to calculate the magnetic anisotropy energy of the CrI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; monolayer which has 8 atoms per unit cell. I have understood from &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Determining_the_Magnetic_Anisotropy&quot; rel=&quot;noreferrer&quot;&gt;VASPWIKI&lt;/a&gt; that there are two steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;A standard SCF collinear calculation is used to generate the WAVECAR and CHGCAR files.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A non-collinear calculation by adding these tags: &lt;code&gt;LSORBIT = .TRUE.&lt;/code&gt; ,&lt;code&gt;ICHARG = 11&lt;/code&gt;, &lt;code&gt;LMAXMIX = 4&lt;/code&gt; and &lt;code&gt;SAXIS&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I also understand that step 2 must be run three times with: &lt;code&gt;SAXIS=0 0 1&lt;/code&gt;, &lt;code&gt;SAXIS=0 1 0&lt;/code&gt; and &lt;code&gt;SAXIS=1 0 0&lt;/code&gt;. But I didn't understand how to set the &lt;code&gt;MAGMOM&lt;/code&gt; tag in the second step. Knowing that in the first step I specified &lt;code&gt;MAGMOM = 2*5.0 6*0.6&lt;/code&gt; because I have 8 atoms (two are magnetic and six are non-magnetic).&lt;/p&gt;&#xA;&lt;p&gt;Could you please help me in choosing the right setting of the &lt;code&gt;MAGMOM&lt;/code&gt; tag?&lt;/p&gt;&#xA;" OwnerUserId="272" LastActivityDate="2022-03-31T14:40:47.620" Title="How to calculate the magnetic anisotropy energy using the VASP code?" Tags="|vasp|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8840" PostTypeId="1" CreationDate="2022-03-24T10:45:10.340" Score="6" ViewCount="154" Body="&lt;p&gt;Suppose, one knows the ground state wave function &lt;span class=&quot;math-container&quot;&gt;$|\Phi\rangle$&lt;/span&gt; in terms of a slater determinant(SD) basis say, from a Configuration interaction calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$|\Phi\rangle= c_{\text{HF}}\left|\Psi_{\text{HF}}\right\rangle+\sum_{r a} c_{a}^{r}\left|\Psi_{a}^{r}\right\rangle+\sum_{a&amp;lt;b, r&amp;lt;s} c_{a b}^{r s}\left|\Psi_{a b}^{r s}\right\rangle+\sum_{r&amp;lt;s&amp;lt;t, a&amp;lt;b&amp;lt;c} c_{a b c}^{r s t}\left|\Psi_{a b c}^{r s t}\right\rangle+\ldots&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How can one transform to the molecular orbital(MO) basis?  (it is implied that one knows the MOs used to build the SDs in the first place.)&lt;/p&gt;&#xA;&lt;p&gt;Do any of the ab initio packages already have the functionality where I can pass the eigen vectors of the CI Hamiltonian and the MO coefficients to get the density matrix or the wavefunction in terms of the MO basis?&lt;/p&gt;&#xA;&lt;p&gt;I am trying to calculate the density matrices from the CI wavefunction in terms of MO basis, so that I can visualize the states from my CI calculation.&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastActivityDate="2022-03-24T12:00:34.027" Title="Transforming from CI basis to MO basis" Tags="|computational-chemistry|molecular-modeling|configuration-interaction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8841" PostTypeId="1" CreationDate="2022-03-24T11:15:40.393" Score="5" ViewCount="326" Body="&lt;p&gt;I have calculated frequency-dependent dielectric constant in VASP using PBE exchange-correlation functional, within the framework of Independent particle approximation (with RPA). I want to perform the same calculation using HSE.&#xA;I have seen a lot of examples and tutorials for Band structure calculation with HSE but could not find a step-by-step procedure for the optical property with HSE.&#xA;If any expert can give a set of INCAR files for the same I will remain grateful.&lt;/p&gt;&#xA;" OwnerUserId="5161" LastActivityDate="2022-03-24T11:15:40.393" Title="Optical Property calculation in VASP using HSE" Tags="|vasp|optical-properties|hse06|" AnswerCount="0" CommentCount="3" ClosedDate="2022-04-12T14:25:53.550" ContentLicense="CC BY-SA 4.0" />
  <row Id="8842" PostTypeId="2" ParentId="8840" CreationDate="2022-03-24T12:00:34.027" Score="7" Body="&lt;p&gt;This is impossible (except in the trivial case where there is only one electron), because MOs span the space of single electron wavefunctions, while SDs span the space of multielectron wavefunctions. As MOs and SDs span different spaces, you cannot transform one to the other. You can transform a single electron wavefunction between MO, AO, orthogonal AO, plane wave, and Wannier function bases, etc., and you can transform a multielectron wavefunction between SD and CSF bases, but you cannot do any basis transformations between these two categories of bases because such transformations are not even defined.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-03-24T12:00:34.027" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8843" PostTypeId="2" ParentId="8838" CreationDate="2022-03-24T12:49:29.390" Score="7" Body="&lt;p&gt;Without data to test exactly what you are doing it's difficult to say for absolute certain, but it looks to me that your main problem is that your first equation, the equation you are using for your program, is wrong. It should be a 3D transform. Writing it out in full to make the point it should be&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S({\bf k}) = 1 + \rho \int \int \int \exp(-i{\bf k}\cdot{\bf r})g({\bf r })dr_x dr_y dr_z$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The second equation is correct for spherically symmetric &lt;span class=&quot;math-container&quot;&gt;$g({\bf r})$&lt;/span&gt;, which is often assumed to be the case. Thus for such functions the triple integral in equation one can be reduced to the single integral in equation two - possibly the simplest way to show this is to expand the plane wave in &lt;a href=&quot;https://en.wikipedia.org/wiki/Plane-wave_expansion&quot; rel=&quot;noreferrer&quot;&gt;spherical harmonics&lt;/a&gt; and then note as &lt;span class=&quot;math-container&quot;&gt;$g({\bf r})$&lt;/span&gt; is spherically symmetric only the &lt;span class=&quot;math-container&quot;&gt;$l=0$&lt;/span&gt; terms survive due to the orthogonality properties of spherical harmonics.&lt;/p&gt;&#xA;&lt;p&gt;To use equation 2 to evaluate your structure factor, see &lt;a href=&quot;https://math.stackexchange.com/questions/3527070/how-to-compute-the-dft-of-a-radially-symmetric-function-in-3d&quot;&gt;this answer&lt;/a&gt; on the sister maths site. You will need to perform a &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Sine_and_cosine_transforms&quot; rel=&quot;noreferrer&quot;&gt;Sine transform&lt;/a&gt; of &lt;span class=&quot;math-container&quot;&gt;$r g({\bf r})$&lt;/span&gt; and halve the result for this - I don't speak much python, but according to &lt;a href=&quot;https://realpython.com/python-scipy-fft/#the-discrete-cosine-and-sine-transforms&quot; rel=&quot;noreferrer&quot;&gt;this site&lt;/a&gt; it looks like &lt;code&gt;dst()&lt;/code&gt; is what you are looking for.&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="7" LastEditDate="2022-03-24T13:50:07.363" LastActivityDate="2022-03-24T13:50:07.363" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8844" PostTypeId="1" AcceptedAnswerId="8847" CreationDate="2022-03-24T15:44:27.620" Score="8" ViewCount="276" Body="&lt;p&gt;I have a pdb file of some solvent molecules in a box of 20 Angstroms I have built using Tinker. I have opened the file with Chimera, Molden, Pymol and Avogadro... but I would like to see, and maybe generate a figure with, the proper limits of the box if there is any tool for doing so.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone succeded before? I do not mind getting used to another visualization program or tool.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance&lt;/p&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="5" LastEditDate="2022-03-24T16:48:07.640" LastActivityDate="2022-03-25T05:10:20.770" Title="Limits of periodic box from pdb" Tags="|visualization-software|vmd|pdb|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8845" PostTypeId="1" CreationDate="2022-03-24T21:38:16.580" Score="7" ViewCount="54" Body="&lt;p&gt;I am interested in calculating the non-interacting non-local susceptibility for simple molecules.&lt;/p&gt;&#xA;&lt;p&gt;In principle, if you have a single Slater determinant, then you should just take a sum over the occupied orbitals &lt;span class=&quot;math-container&quot;&gt;$ \{\phi_i\} $&lt;/span&gt; as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \chi(r,r') = \sum_{occ} \frac{\phi_i(r) \phi_j(r') \phi_i(r') \phi_j(r)}{\varepsilon_i-\varepsilon_j} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe if you have the representation of the wavefunctions in Cartesian space, then you can &amp;quot;simply&amp;quot; sum over them. In practice, however, I am not sure I want to write a code that does this, so I'm asking: does anyone know about a package that does this?&lt;/p&gt;&#xA;&lt;p&gt;I think it should be possible, as &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; is an intermediate property for RPA calculations as well as an interesting object in conceptual DFT (&lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/jz1002132&quot; rel=&quot;noreferrer&quot;&gt;see this paper&lt;/a&gt; for example where they actually calculate this quantity, but they don't report their full function, neither do they provide their code...)&lt;/p&gt;&#xA;" OwnerDisplayName="user4626" LastEditorUserId="5" LastEditDate="2022-03-24T23:13:35.467" LastActivityDate="2022-03-29T17:11:48.673" Title="Any molecular codes to calculate non-local susceptibility?" Tags="|quantum-chemistry|molecular-modeling|software-recommendations|basis-sets|response-theory|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8846" PostTypeId="1" AcceptedAnswerId="8858" CreationDate="2022-03-25T00:12:32.437" Score="5" ViewCount="314" Body="&lt;p&gt;This is a variation of a question asked on &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6982/how-to-convert-smiles-to-amino-acids-sequence-using-rdkit&quot;&gt;October 30, 2021 here&lt;/a&gt;, but it is different enough that I think it warrants a new post. I'm also trying to use RDKit.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to convert a SMILES notation of a cyclopeptide into a list of masses, rather than a list of amino acid names? For example, &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/compound/45485348&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tyrocidine B1&lt;/a&gt; has the following isomeric SMILES format:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;CC(C)C[C@H]1C(=O)N[C@@H](C(=O)N2CCC[C@H]2C(=O)N[C@H](C(=O)N[C@@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N1)CCCCN)C(C)C)CC3=CC=C(C=C3)O)CCC(=O)N)CC(=O)N)CC4=CC=CC=C4)CC5=CNC6=CC=CC=C65)CC7=CC=CC=C7&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above question would try to write out the specific amino acids. Tyrocidine B1 would look something like the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;cyclo[Asn-Gln-Tyr-Val-Lys-Leu-D-Phe-Pro-Trp-D-Phe]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe the cyclic nature of the peptide invalidates the answers provided in the above question. Furthermore, rather than listing the amino acids by name, I was hoping to obtain a list of amino acid masses. For Tyrocidine B1 it would look something like the following in python:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;[114.04, 128.06, 163.06, 99.07, 128.09, 113.08, 147.07, 97.05, 186.08, 147.07]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm thinking that, because I'm focusing on the masses specifically and may deal with unknown amino acids in the future, it may be more straightforward to identify the peptide bonds and add up the mass of atoms in between them to achieve this goal. For example, if I found peptide bond 1 and peptide bond 2, I would add up all carbon, hydrogen, and nitrogen atoms (and possibly others) between those bonds to obtain the mass of that amino acid. I've been researching how best to do so, and feel like I've come close with the below code. However, I'm struggling with understanding the output of running a &lt;code&gt;Mol&lt;/code&gt; object through &lt;code&gt;GetSubstructMatches&lt;/code&gt;, and don't know how to use that to obtain amino acid masses.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;&#xA;tyroB1 = 'CC(C)C[C@H]1C(=O)N[C@@H](C(=O)N2CCC[C@H]2C(=O)N[C@H](C(=O)N[C@@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N1)CCCN)C(C)C)CC3=CC=C(C=C3)O)CCC(=O)N)CC(=O)N)CC4=CC=CC=C4)CC5=CNC6=CC=CC=C65)CC7=CC=CC=C7'&#xA;m = Chem.MolFromSmiles(tyroB1)&#xA;&#xA;# identify peptide bonds&#xA;substructure = Chem.MolFromSmarts('NCC(=O)N')&#xA;print(m.GetSubstructMatches(substructure))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;((7, 8, 9, 10, 11), (11, 15, 16, 17, 18), (18, 19, 20, 21, 22), (22, 23, 24, 25, 26), (26, 27, 28, 29, 30), (30, 31, 32, 33, 34), (34, 35, 36, 37, 38), (38, 39, 40, 41, 42), (42, 43, 44, 45, 46), (46, 4, 5, 6, 7))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm optimistic in that the above code clearly identifies the correct number of peptide bonds (and does so with the different cyclopeptides I've tried), but I've stuggled moving from there to assembling a list of amino acid masses.&lt;/p&gt;&#xA;&lt;p&gt;Would you have recommendations or ideas on how best to move forward, either in the direction I'm going or somewhere new? I would be obtaining information like SMILES formatting from PubChem, so anything that appears on cyclopeptide pages (like Tyrocidine B1 above) is fair game for use.&lt;/p&gt;&#xA;" OwnerUserId="5165" LastEditorUserId="5165" LastEditDate="2022-03-27T10:14:45.033" LastActivityDate="2022-03-27T10:55:49.480" Title="Convert SMILES format to Amino Acid masses using RDKit - Cyclopeptides" Tags="|python|proteins|rdkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8847" PostTypeId="2" ParentId="8844" CreationDate="2022-03-25T03:12:24.070" Score="5" Body="&lt;p&gt;In pymol the cell &lt;a href=&quot;https://pymolwiki.org/index.php/Cell&quot; rel=&quot;noreferrer&quot;&gt;can be displayed&lt;/a&gt; by typing &lt;code&gt;show cell&lt;/code&gt; into the command line.&lt;/p&gt;&#xA;" OwnerUserId="5167" LastActivityDate="2022-03-25T03:12:24.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8848" PostTypeId="1" CreationDate="2022-03-25T03:58:09.250" Score="3" ViewCount="102" Body="&lt;p&gt;What is the meaning of phonon calculation in 2D materials? And is it enough to predict the stability of materials based on positive phonon only?&lt;/p&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="7" LastEditDate="2022-03-25T04:27:59.953" LastActivityDate="2022-03-25T04:27:59.953" Title="Interpreting Phonon calculations for 2D materials" Tags="|vibrations|phonopy|terminology|phonon-density-of-state|phonon-dispersion|" AnswerCount="0" CommentCount="2" ClosedDate="2022-04-12T14:25:08.513" ContentLicense="CC BY-SA 4.0" />
  <row Id="8850" PostTypeId="2" ParentId="8844" CreationDate="2022-03-25T05:10:20.770" Score="6" Body="&lt;p&gt;Atomic simulation environment is useful for a lot of other manipulations you might want to do and it comes with a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/gui/gui.html&quot; rel=&quot;noreferrer&quot;&gt;GUI&lt;/a&gt; that is capable of doing this (given that you define the cell, it will also behave if you do not define a cell though since it works for periodic and non-periodic systems).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pip install --user ase&#xA;ase gui structure.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BuQnf.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BuQnf.png&quot; alt=&quot;Visual of the GUI in Atomic Simulation Environment&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-03-25T05:10:20.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8851" PostTypeId="1" CreationDate="2022-03-25T09:58:42.180" Score="2" ViewCount="58" Body="&lt;p&gt;I'm trying to build outer membrane of e. coli with small peptides above it, with CHARMM-GUI. Peptides should be positioned above the membrane, but CHARMM-GUI creates space for them between LPS (lipopolisacharides) pushing LPS-s to the edges of simulation box.&lt;/p&gt;&#xA;&lt;p&gt;If I use only one peptide, it is not problem, empty space is not big, and CHARMM-GUI successfully finishes job.&#xA;But when using more peptides, empty space created underneath them is large, so LPS-s are pushed to the edges, tightly packed, which obviously causes problem for CHARMM-GUI and gives error:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Charmm terminates abnormally. Please check the output or report this failure to the CHARMM-GUI developers. The bilayer generation is stopped to prevent an infinite loop. Please refresh the browser to restart the bilayer generation with different random seed.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I tried several times, with the same outcome. It looks like membrane builder thinks that peptides are &amp;quot;inserted&amp;quot; in LPS, so it leaves empty space for them in between LPS-s.&lt;/p&gt;&#xA;&lt;p&gt;I report error to CHARMM-GUI developers, and got short answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;View &lt;code&gt;step3_packing.pdb&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I looked, and see nothing strange, nothing to lead me to solve the problem.&lt;/p&gt;&#xA;&lt;p&gt;Any idea where to look, or how to solve problem?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sswxY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sswxY.png&quot; alt=&quot;hole_between_LPSs_picture1&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/CIuDb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CIuDb.png&quot; alt=&quot;hole_between_LPSs_picture2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;p.s. This question is appropriate for CHARMM forums, but I've not been able to register on CHARMM forums prior this question.&lt;/p&gt;&#xA;" OwnerUserId="5168" LastEditorUserId="7" LastEditDate="2022-03-25T12:47:53.993" LastActivityDate="2022-03-25T12:47:53.993" Title="CHARMM-gui creates empty space between LPS-s and terminates while building e. coli outer membrane with peptides above it" Tags="|molecular-modeling|graphical-user-interface|charmm|" AnswerCount="0" CommentCount="6" ClosedDate="2022-09-07T22:40:20.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="8852" PostTypeId="1" CreationDate="2022-03-25T10:37:03.380" Score="4" ViewCount="277" Body="&lt;p&gt;I want to use the 3D-RISM-SCF and ESM-RISM implementation in Quantum Espresso to compute solvated adsorption energies and absolute solvation energies.&lt;/p&gt;&#xA;&lt;p&gt;Before starting I read the main paper by  S. Nishihara and M. Otani and read (not completely) the code, at least to understand what was printed in the output file.&lt;/p&gt;&#xA;&lt;p&gt;In the code you can find the most important variable &amp;quot;esol&amp;quot; that is being printed as &amp;quot;solvation energy&amp;quot; in the energy detail. This variable is the sum of an array usol which are the chemical potentials of solvation for each site within the RISM formalism.&lt;/p&gt;&#xA;&lt;p&gt;It is explicitly stated in the code &amp;quot;only esol has physical meaning not usol&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Everything is perfect, I do my calculations and get my solvation energies. Until recently I have a discussion with one of the authors who tells me that &amp;quot;esol&amp;quot; has no physical meaning because it contains a divergent term that is cancelled by another DFT term.&lt;/p&gt;&#xA;&lt;p&gt;I read the theory again and I find the supplementary material where it is written that solvation energy (the esol term) diverge only when the unit cell is charged.&lt;/p&gt;&#xA;&lt;p&gt;I have a questions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can someone with RISM experience confirm what I just wrote?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2022-03-25T11:08:01.893" LastActivityDate="2022-08-31T22:59:59.037" Title="Compute solvation energies with (ESM) RISM-SCF" Tags="|density-functional-theory|plane-waves|solvation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8853" PostTypeId="1" CreationDate="2022-03-25T12:46:56.097" Score="3" ViewCount="508" Body="&lt;p&gt;I would like to use ORCA-3.0.1 under the following Linux version:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;5.10.0-10-amd64 #1 SMP Debian 5.10.84-1 (2021-12-08) x86_64 GNU/Linux&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and Intel version &lt;code&gt;2021.5.0&lt;/code&gt;. This old ORCA version is required by the &lt;a href=&quot;https://www.physics.udel.edu/%7Eszalewic/SAPT/documentation.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;autoPES2020.1&lt;/a&gt; program of Szalewicz and co-workers.&lt;/p&gt;&#xA;&lt;p&gt;Until the latest upgrade of our cluster, ORCA-3.0.1 worked properly, but now produces a segmentation fault without printing ANYTHING into the output file and just writing &amp;quot;Segmentation fault&amp;quot; into stderr. The last upgrade concerned the Intel compiler and the associated libraries.&lt;/p&gt;&#xA;&lt;p&gt;I try to execute the following command &lt;strong&gt;exactly&lt;/strong&gt; in the directory where the ORCA-3.0.1 executables are located:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./orca test.inp &amp;gt; test.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The content of the file &lt;code&gt;test.inp&lt;/code&gt; is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! HF def2-TZVP&#xA;%scf&#xA;convergence tight&#xA;end&#xA;* xyz 0 1&#xA;C 0.0 0.0 0.0&#xA;O 0.0 0.0 1.13&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The ORCA-5.0.1 version runs smoothly in this way in the analogous directory. Could you please help me find the origin of the problem?&lt;/p&gt;&#xA;&lt;p&gt;Note that there is no possibility to use ORCA-4.x or 5.x without modifying the autoPES code, which I would definitely like to avoid.&lt;/p&gt;&#xA;" OwnerUserId="4119" LastEditorUserId="7" LastEditDate="2022-03-26T02:42:09.630" LastActivityDate="2022-03-26T02:42:09.630" Title="Segmentation fault with ORCA-3.0.1" Tags="|quantum-chemistry|software-assistance|orca|" AnswerCount="0" CommentCount="8" ClosedDate="2022-09-07T22:39:57.893" ContentLicense="CC BY-SA 4.0" />
  <row Id="8854" PostTypeId="1" CreationDate="2022-03-25T13:44:59.707" Score="6" ViewCount="190" Body="&lt;p&gt;I am trying to get the Fermi contour lines of an FCC crystal system. For this, I am trying to use the wannier90 program. I have already done the wannierzation part successfully. Now I am trying to get the Fermi surface contour lines. But for this I need three parameters, &lt;code&gt;kslice_corner&lt;/code&gt;, &lt;code&gt;kslice_b1&lt;/code&gt;, &lt;code&gt;kslice_b2&lt;/code&gt;. &lt;code&gt;kslice_corner&lt;/code&gt; is the coordinates of the corner of kplane slice of our interest. &lt;code&gt;kslice_b1&lt;/code&gt; and &lt;code&gt;kslice_b2&lt;/code&gt; are the reduced coordinates of the reciprocal lattice vectors defining that plane. Say if I need fermi contour lines in &lt;code&gt;kz=0&lt;/code&gt; plane. What is the procedure to find the above three parameters for &lt;code&gt;kz=0&lt;/code&gt; plane for FCC? How can I achieve this? Is there any visualization tool for kslice planes and its coordinates? Below is the image of first Brillouin zone of FCC lattice:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O4Z4N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O4Z4N.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Please help with this.&lt;br /&gt;&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2022-03-25T13:44:59.707" Title="How to find the reduced coordinates of reciprocal lattice vector which defines the kslice plane in first brillouin zone?" Tags="|quantum-espresso|k-points|brillouin-zone|wannier90|fermi-surface|" AnswerCount="0" CommentCount="2" ClosedDate="2022-10-30T19:08:02.390" ContentLicense="CC BY-SA 4.0" />
  <row Id="8855" PostTypeId="2" ParentId="8832" CreationDate="2022-03-26T01:54:46.913" Score="5" Body="&lt;p&gt;The unit is actually &lt;span class=&quot;math-container&quot;&gt;$\pu{nm^2}$&lt;/span&gt;. What is written there is not is not specific to GROMACS, but to the plotting program it is using &lt;a href=&quot;https://plasma-gate.weizmann.ac.il/Xmgr/doc/fonts.html&quot; rel=&quot;noreferrer&quot;&gt;Xmgrace&lt;/a&gt;. &lt;code&gt;\S&lt;/code&gt; denotes the start of superscript font, which ends when it encounters a &lt;code&gt;\N&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you pass this file as an input to Xmgrace, it should produce a plot of surface area (&lt;span class=&quot;math-container&quot;&gt;$\pu{nm^2}$&lt;/span&gt;) vs time (&lt;span class=&quot;math-container&quot;&gt;$\pu{ps}$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-26T01:54:46.913" CommentCount="2" CommunityOwnedDate="2022-03-26T01:54:46.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="8856" PostTypeId="2" ParentId="8764" CreationDate="2022-03-26T10:16:50.773" Score="7" Body="&lt;p&gt;&lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/plugins/topotools/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Topotools&lt;/a&gt; plugins does provide you a method to read LAMMPS native data files. See the documentation for detailed usage.&lt;/p&gt;&#xA;&lt;p&gt;For instance, if the file &lt;code&gt;data.CNT&lt;/code&gt; contains information of atom positions, bonds, angles, dihedrals, etc, after running &lt;code&gt;vmd&lt;/code&gt;, run this command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;topo readlammpsdata data.CNT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is also great for debugging purposes: to make sure the fixed force field topology is compatible with the molecular/crystal graph.&lt;/p&gt;&#xA;" OwnerUserId="291" LastEditorUserId="291" LastEditDate="2022-03-27T06:24:42.947" LastActivityDate="2022-03-27T06:24:42.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8857" PostTypeId="2" ParentId="3865" CreationDate="2022-03-26T14:27:49.297" Score="5" Body="&lt;p&gt;Start by constructing 1×1 and 2×2 reciprocal space lattices; the latter case has the real space lattice constant twice as big, so its reciprocal lattice unit cell will be half the size, and square. The 1×2 structure is rectangular with a=1 and b=2, its reciprocal lattice has a* ~ 1 and b* ~ ½. LEED diffraction spots for 1×2 are at the vertices of (a*,b*) rectangles, and nothing in between. It has to be an incoherent sum of the two images from different domains of 1×2 and 2×1 superstructures (green and orange spots in the attached figure) that gives you the pattern in question.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/w6FMB.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w6FMB.png&quot; alt=&quot;Original 1×1 structure, 2x2 structure, and 1×2, 2x1 structures superimposed (incoherently)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5173" LastActivityDate="2022-03-26T14:27:49.297" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8858" PostTypeId="2" ParentId="8846" CreationDate="2022-03-27T10:47:56.070" Score="7" Body="&lt;p&gt;I'm not sure if it's improper to answer my own question, but I think I've cracked it.&lt;/p&gt;&#xA;&lt;p&gt;For each peptide bond match identified by &lt;code&gt;GetSubstructMatches&lt;/code&gt; the index [1] is the atom index of the alpha carbon. If you find all atoms connected to that carbon, excluding the nitrogens from the peptide bond, you get all of the atoms contained in the amino acid. Throw in one of the excluded nitrogens and you can calculate the mass using the &lt;code&gt;rdkit.Chem.Descriptors.ExactMolWt&lt;/code&gt; function. It accurately determined the sequences of Tyrocidine B1, Surugamide A and Surugamide B.&lt;/p&gt;&#xA;&lt;p&gt;The below code hasn't been optimized, and it does NOT account for the possibility of connected side chains. I can't think of a reliable method to account for connected side chains just by comparing atoms and bonds, a prior knowledge of the specific amino acids in question would likely be required. Fortunately, that is not required for my current project, though additional insights would be welcome.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.Descriptors import ExactMolWt&#xA;import numpy as np&#xA;from itertools import combinations&#xA;&#xA;tyroB1 = 'CC(C)C[C@H]1C(=O)N[C@@H](C(=O)N2CCC[C@H]2C(=O)N[C@H](C(=O)N[C@@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N1)CCCCN)C(C)C)CC3=CC=C(C=C3)O)CCC(=O)N)CC(=O)N)CC4=CC=CC=C4)CC5=CNC6=CC=CC=C65)CC7=CC=CC=C7'&#xA;&#xA;m = Chem.MolFromSmiles(tyroB1)&#xA;&#xA;peptide_bond_representation = Chem.MolFromSmarts('NCC(=O)N')&#xA;am = np.array(Chem.GetAdjacencyMatrix(m))&#xA;&#xA;masses = []&#xA;for peptide_bond in m.GetSubstructMatches(peptide_bond_representation):&#xA;&#xA;    alpha = peptide_bond[1]&#xA;    nitrogens = set([peptide_bond[0],peptide_bond[-1]])&#xA;&#xA;    aa_atom_idx = set([alpha])&#xA;    set2 = set()&#xA;    while aa_atom_idx != set2: # while loop repeats until all atoms in the amino acid are accounted for&#xA;        set2 = aa_atom_idx.copy()&#xA;        temp_am = am[:, list(aa_atom_idx)]&#xA;        aa_atom_idx = set(np.where(temp_am==1)[0]) | aa_atom_idx&#xA;        aa_atom_idx -= nitrogens # nitrogens from the peptide bond excluded to isolate atoms of this amino acid&#xA;    aa_atom_idx.add(peptide_bond[0]) #adding a single nitrogen back in&#xA;&#xA;    bonds = [] # Chem.PathToSubmol requires a list of bonds, not atoms&#xA;    for i,j in combinations(aa_atom_idx, 2):&#xA;        b = m.GetBondBetweenAtoms(int(i),int(j))&#xA;        if b: bonds.append(b.GetIdx())&#xA;&#xA;    tempMol = Chem.PathToSubmol(m, bonds)&#xA;    mass = ExactMolWt(tempMol)&#xA;    masses.append(mass)&#xA;print(masses)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&#xA;&lt;code&gt;[147.068413908, 97.052763844, 186.07931294, 147.068413908, 114.042927432, 128.058577496, 163.063328528, 99.068413908, 128.094963004, 113.084063972]&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="5165" LastEditorUserId="5165" LastEditDate="2022-03-27T10:55:49.480" LastActivityDate="2022-03-27T10:55:49.480" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8859" PostTypeId="1" CreationDate="2022-03-27T15:02:46.667" Score="3" ViewCount="717" Body="&lt;p&gt;A stainless steel is a ferritic alloy, in general, with a low carbon content and a Cr content equal to or greater than 10.5%. To study the phase transformations and heat treatments undergone by these steels, a phase diagram is used, as shown in the following figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MQI2k.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MQI2k.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this diagram, there is a sigma phase of tetragonal structure, whose occurrence I have read should be avoided. But, in the notes I am reading, the reason does not appear. Why should the sigma phase be avoided?&lt;/p&gt;&#xA;" OwnerUserId="1744" LastActivityDate="2022-03-27T15:02:46.667" Title="Phase diagrams for stainless steels" Tags="|materials-engineering|alloys|phase-diagram|" AnswerCount="0" CommentCount="3" ClosedDate="2022-10-26T13:16:21.273" ContentLicense="CC BY-SA 4.0" />
  <row Id="8860" PostTypeId="1" AcceptedAnswerId="8862" CreationDate="2022-03-28T08:29:49.463" Score="10" ViewCount="400" Body="&lt;p&gt;I have built a CG model of a surface on which I want to place a water droplet (some water molecules), and calculate the contact angle. Has anyone done similar work with gromacs (MD simulation)? First, I just want to place some water molecules in a sphere on the surface. Any suggestions?&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="1791" LastEditDate="2022-03-28T11:11:52.067" LastActivityDate="2023-09-05T15:14:06.760" Title="Contact Angle (water droplet on a surface)" Tags="|molecular-dynamics|molecular-modeling|gromacs|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8861" PostTypeId="1" CreationDate="2022-03-28T16:30:05.597" Score="11" ViewCount="402" Body="&lt;p&gt;Recently, I came across some &lt;a href=&quot;https://github.com/fevangelista/CHEM532-ElectronicStructure-Notes/blob/master/pdf/chem532-notes.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;lecture notes&lt;/a&gt; on electronic structure theory which had something peculiar about it. I noticed that FCI (configuration interaction) was introduced before Hartree-Fock theory, that got me thinking if its possible to think about FCI as an approach independent of HF theory as starting point (not particularly as post-HF method).&lt;/p&gt;&#xA;&lt;p&gt;Would such an approach be possible?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt; :&lt;/p&gt;&#xA;&lt;p&gt;In general can there be a generalized formalism for Full configuration interaction? (say in the form of a particle-hole construction, for example see the introduction section in &lt;a href=&quot;https://arxiv.org/pdf/1906.11361.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1906.11361&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastEditorDisplayName="user784" LastEditDate="2022-04-06T10:30:22.423" LastActivityDate="2022-04-06T10:30:22.423" Title="FCI without Hartree-Fock" Tags="|electronic-structure|configuration-interaction|full-configuration-interaction|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8862" PostTypeId="2" ParentId="8860" CreationDate="2022-03-28T18:42:19.123" Score="12" Body="&lt;p&gt;For generating the droplet, there are two ways. The 'dumb but it works' way is to just generate a box of water adjacent to the surface, and let it equilibrate in vacuum for a time. The box will naturally adhere to the surface and form a spherical droplet after a few 10's of nanoseconds. This has the advantage that you can keep the number of waters equivalent across simulations with different surfaces - just use the same waterbox while swapping out the surface.&lt;/p&gt;&#xA;&lt;p&gt;The slightly the more complex way is to first generate a regular box on top of the surface. Then, choose a point on the surface to act as the centre of a droplet, and delete any waters that are greater than some distance R (where R is the radius of a sphere). I suggest using VMD or mdanalysis for this task but I'm sure lots of programs can achieve it.&lt;/p&gt;&#xA;&lt;p&gt;Finally, a trick to improve correspondence with experiment: nano-scale waterdroplets may not accurately represent the contact angle observed in experiment. This is due to the ratio between the distance of the water/surface/vacuum contact line vs the surface area of the interface. To avoid this, one can make the surface periodic with a small cell distance in the x direction (or y), say 1-2nm, so that the droplet forms a cylinder. This makes the contact line linear and removes the effect of so-called 'line tension'. This is described in &amp;quot;On the Water-Carbon Interaction for Use in Molecular Dynamics Simulations of Graphite and Carbon Nanotubes&amp;quot;, DOI 10.1021/jp0268112&lt;/p&gt;&#xA;" OwnerUserId="2225" LastActivityDate="2022-03-28T18:42:19.123" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8863" PostTypeId="1" CreationDate="2022-03-28T19:20:13.477" Score="18" ViewCount="2484" Body="&lt;p&gt;From &lt;a href=&quot;https://politics.stackexchange.com/q/72003/16047&quot;&gt;How do you explain Canada's Trudeau's power-sharing agreement to a five-year-old (American)?&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The &amp;quot;explain to a five-year-old&amp;quot; question is a semi-standard format where the answer demonstrates their ability to understand both the subject matter, and the perspective and limitations of the answer's recipient.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Wikipedia's &lt;a href=&quot;https://en.wikipedia.org/wiki/Bilayer_graphene&quot; rel=&quot;noreferrer&quot;&gt;Bilayer graphene&lt;/a&gt; begins:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Bilayer graphene can exist in the AB, or Bernal-stacked form,&lt;sup&gt;2&lt;/sup&gt; where half of the atoms lie directly over the center of a hexagon in the lower graphene sheet, and half of the atoms lie over an atom, or, less commonly, in the AA form, in which the layers are exactly aligned.&lt;sup&gt;3&lt;/sup&gt; In Bernal stacked graphene, twin boundaries are common; transitioning from AB to BA stacking.&lt;sup&gt;4&lt;/sup&gt; Twisted layers, where one layer is rotated relative to the other, have also been extensively studied.&lt;/p&gt;&#xA;&lt;p&gt;Quantum Monte Carlo methods have been used to calculate the binding energies of AA- and AB-stacked bilayer graphene, which are 11.5(9) and 17.7(9) meV per atom, respectively.&lt;sup&gt;5&lt;/sup&gt; This is consistent with the observation that the AB-stacked structure is more stable than the AA-stacked structure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt;K Yan; H Peng; Y Zhou; H Li; Z Liu (2011). &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl104000b&quot; rel=&quot;noreferrer&quot;&gt;Formation of bilayer Bernal graphene: layer-by-layer epitaxy via chemical vapor deposition&lt;/a&gt;. Nano Lett. 11 (3): 1106–10&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;3&lt;/sup&gt;Z Liu; K Suenaga PJF Harris; S Iijima (2009). &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.015501&quot; rel=&quot;noreferrer&quot;&gt;Open and closed edges of graphene layers&lt;/a&gt;. Phys. Rev. Lett. 102 (1): 015501.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;4&lt;/sup&gt;Min, Lola; Hovden, Robert; Huang, Pinshane; Wojcik, Michal; Muller, David A.; Park, Jiwoong (2012). &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl204547v&quot; rel=&quot;noreferrer&quot;&gt;Twinning and Twisting of Tri- and Bilayer Graphene&lt;/a&gt;. Nano Letters. 12 (3): 1609–1615.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;5&lt;/sup&gt;E. Mostaani, N. D. Drummond and V. I. Fal'ko (2015). &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.115501&quot; rel=&quot;noreferrer&quot;&gt;Quantum Monte Carlo Calculation of the Binding Energy of Bilayer Graphene&lt;/a&gt;. Phys. Rev. Lett. 115 (11): 115501. also in &lt;a href=&quot;https://arxiv.org/abs/1506.08920&quot; rel=&quot;noreferrer&quot;&gt;arXiv&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The introduction to ref. 5 Mostaani, Drummond &amp;amp; Fal'ko (2015) states:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Standard first-principles approaches such as density functional theory (DFT) with local exchange–correlation functionals do not describe vdW interactions accurately&lt;/strong&gt;...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and goes on to discuss some enhancements or alternatives to better model van der Wall interactions for vdW materials like bilayar graphene:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;One technique for including vdW interactions in a first-principles framework is to add energies obtained using pairwise interatomic potentials to DFT total energies; this is the so-called DFT-D scheme [1–4]. The development of vdW density functionals (vdW-DFs) that can describe vdW interactions in a seamless fashion is another promising approach [5–8]. DFT-based random-phase approximation (RPA) calculations of the correlation energy [9, 10] provide a more sophisticated method for treating vdW interactions; however, RPA atomization energies are typically overestimated by up to 15% for solids [11, 12], and hence the accuracy of this approach is unclear. Symmetry-adapted perturbation theory based on DFT allows one to calculate the vdW interactions between molecules and hence, by extrapolation, between nanostructures [13]. Finally, empirical interatomic potentials with &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; tails may be used to calculate binding energies [14, 15], although such potentials give a qualitatively incorrect description of the interaction of metallic or πbonded two-dimensional (2D) materials at large separation [16].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But it does not say why &amp;quot;Standard first-principles approaches such as density functional theory (DFT) with local exchange–correlation functionals&amp;quot; fail.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; How do you explain to a &lt;em&gt;surface science equivalent&lt;/em&gt; five year old why &amp;quot;standard first-principles approaches such as... DFT with local exchange–correlation functionals do not describe van der Waals interactions accurately&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;And if possible within the constraints of a simplified explanation, can one hint at what it is about Quantum Monte Carlo that overcomes this particular limitation?&lt;/p&gt;&#xA;" OwnerUserId="201" LastActivityDate="2022-04-05T00:31:23.963" Title="How to explain to a five year old why &quot;DFT with local exchange–correlation functionals do(es) not describe van der Waals interactions accurately&quot;?" Tags="|density-functional-theory|graphene|quantum-monte-carlo|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8864" PostTypeId="2" ParentId="8863" CreationDate="2022-03-28T20:02:54.103" Score="18" Body="&lt;p&gt;Standard DFT functionals are based exclusively on local information, e.g. for a GGA functional&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_{xc} = \int n({\bf r}) \epsilon_{xc}(n({\bf r}), \nabla n({\bf r})) {\rm d}^3r $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;while van der Waals interactions are induced dipole - induced dipole interactions which are by definition non-local and have a &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; behavior.&lt;/p&gt;&#xA;&lt;p&gt;However, van der Waals effects can often be successfully modeled with empirical atom-pair corrections, as in e.g. Grimme's DFT-D3 or DFT-D4 methods.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-03-28T20:02:54.103" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8865" PostTypeId="2" ParentId="8861" CreationDate="2022-03-28T20:04:50.523" Score="13" Body="&lt;p&gt;Yes, you can surely do full CI without Hartree-Fock. However, the reason why one typically starts from Hartree-Fock is that this guarantees a good conditioning of the FCI matrix, which becomes diagonally dominant and thereby iterative diagonalization becomes tractable.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-03-28T20:04:50.523" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8866" PostTypeId="2" ParentId="8674" CreationDate="2022-03-29T07:01:45.560" Score="3" Body="&lt;p&gt;If you like me prefer working in the &lt;code&gt;python&lt;/code&gt; ecosystem, I suggest using &lt;a href=&quot;https://github.com/peteboyd/lammps_interface&quot; rel=&quot;nofollow noreferrer&quot;&gt;lammps-interface&lt;/a&gt; and &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/peteboyd/lammps_interface&quot; rel=&quot;nofollow noreferrer&quot;&gt;lammps-interface&lt;/a&gt; is a python code that interfaces crystal structures in &lt;code&gt;cif&lt;/code&gt; format to &lt;code&gt;lammps&lt;/code&gt; input files.&lt;/p&gt;&#xA;&lt;p&gt;It is easy to install and use, simply pip install it and run:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lammps-interface cif_file.cif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By default, this gives you the input files for &lt;a href=&quot;https://doi.org/10.1021/ja00051a040&quot; rel=&quot;nofollow noreferrer&quot;&gt;the Universal Force Field (UFF)&lt;/a&gt;. There are a few other options, including the &lt;a href=&quot;https://doi.org/10.1021/j100389a010&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dreiding force field&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to convert your crystal structure to cif format, use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="291" LastActivityDate="2022-03-29T07:01:45.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8867" PostTypeId="1" CreationDate="2022-03-29T12:47:21.130" Score="8" ViewCount="198" Body="&lt;p&gt;I have a coarse-grained model of a surface which is almost planar/flat in 2D. Now, I want to compute some of its mechanical properties to test it. Young's modulus is one of the properties that come to my mind. So, conceptually, is it doable in GROMACS?&lt;/p&gt;&#xA;&lt;p&gt;I think, I can keep one end of the surface fixed with position restraint, and the other end is linked to a spring, and is pulled at a constant velocity (Steered Molecular Dynamics), and with elongation, I may be able to compute the Young's Modulus. Is it a correct way of doing, though I don't know its limitations? Any suggestions, if there are other methods available as well. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="7" LastEditDate="2022-03-29T13:57:14.007" LastActivityDate="2022-04-01T07:03:54.863" Title="Young's modulus from MD simulation" Tags="|molecular-dynamics|gromacs|coarse-grained|" AnswerCount="0" CommentCount="3" ClosedDate="2022-10-30T19:08:20.353" ContentLicense="CC BY-SA 4.0" />
  <row Id="8868" PostTypeId="1" CreationDate="2022-03-29T12:55:15.397" Score="6" ViewCount="207" Body="&lt;p&gt;Are there any opensource and freely distributed codes available which can be used to develop classical potentials for LAMMPS?&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465515001964&quot; rel=&quot;noreferrer&quot;&gt;MEAMfit&lt;/a&gt; code is free and opensource, but the input needs to be from VASP. Because of this, the tool is not actually available for someone without access to VASP.&lt;/p&gt;&#xA;&lt;p&gt;I am looking to work with Heusler materials containing elements such as Zr, Ni, Ir, Sn etc.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2022-04-12T21:22:08.750" Title="Are there any open source codes that can generate LAMMPS potentials from DFT calculations?" Tags="|ab-initio-calculations|lammps|" AnswerCount="1" CommentCount="2" ClosedDate="2022-04-16T01:31:27.843" ContentLicense="CC BY-SA 4.0" />
  <row Id="8869" PostTypeId="2" ParentId="8845" CreationDate="2022-03-29T17:11:48.673" Score="6" Body="&lt;p&gt;After a few days of pondering this issue, I've realized that the code Multiwfn has the option to calculate this quantity that I am looking for.&lt;/p&gt;&#xA;" OwnerDisplayName="user4626" LastActivityDate="2022-03-29T17:11:48.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8870" PostTypeId="1" CreationDate="2022-03-29T23:26:05.890" Score="5" ViewCount="88" Body="&lt;p&gt;I have a problem with running DDEC6 when I used &lt;strong&gt;Palladium (Pd)&lt;/strong&gt; cluster, the main issue was that there were no &lt;code&gt;DDEC6_even_templered_net_atomic_charges.xyz&lt;/code&gt; files came out at all. I noticed that the &lt;strong&gt;summed density is a negative value&lt;/strong&gt;, &lt;strong&gt;which should be zero instead&lt;/strong&gt;. I think it is probably an error from Pd metal because I have already tried it with another metal, and it's working.&lt;/p&gt;&#xA;&lt;p&gt;I have been trying to change the parameters in INCAR when I ran the single-point calculation from VASP to get CHGCAR and AECCAR2, but it has not worked still (for instance, changing ALGO, ISPIN, or ADDGRID).&lt;/p&gt;&#xA;&lt;p&gt;I would greatly appreciate it if you could give me any suggestions for solving this problem.&lt;/p&gt;&#xA;" OwnerUserId="5183" LastEditorUserId="5" LastEditDate="2022-03-30T03:20:12.117" LastActivityDate="2022-03-30T03:20:12.117" Title="&quot;Failed&quot; running DDEC6 Atomic Charge when using Palladium (Pd) cluster model" Tags="|vasp|charge-density|metals|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T22:39:34.597" ContentLicense="CC BY-SA 4.0" />
  <row Id="8871" PostTypeId="1" CreationDate="2022-03-30T05:00:10.183" Score="4" ViewCount="481" Body="&lt;p&gt;It's well known that VASP can print three orthogonal spin projections at each k point corresponding to each band in the file &lt;a href=&quot;https://www.vasp.at/wiki/index.php/PROCAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;PROCAR&lt;/a&gt; controlled by the tags &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LORBIT&quot; rel=&quot;nofollow noreferrer&quot;&gt;LORBIT&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/RWIGS&quot; rel=&quot;nofollow noreferrer&quot;&gt;RWIGS&lt;/a&gt;. Is there a way&#xA;to obtain the same information from calculations done by QE?&lt;/p&gt;&#xA;&lt;p&gt;This problem is also discussed &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2022-March/048896.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Regards,&#xA;HZ&lt;/p&gt;&#xA;" OwnerUserId="5128" LastEditorUserId="5128" LastEditDate="2022-03-30T05:05:15.493" LastActivityDate="2022-06-02T18:20:42.817" Title="How to compute spin projections in QE?" Tags="|quantum-espresso|spin-orbit-coupling|spin|spin-polarization|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8873" PostTypeId="1" CreationDate="2022-03-30T13:54:54.020" Score="5" ViewCount="61" Body="&lt;p&gt;I am looking for a software to build my own chice of lattice nanotube and get the lammps input file for it.&lt;/p&gt;&#xA;&lt;p&gt;Do you have any suggestions?&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="5" LastEditDate="2022-03-30T14:15:41.307" LastActivityDate="2022-04-12T20:57:10.033" Title="Which software can I use to model a nanotube with a triangular lattice shape and extract from it the lammps input file?" Tags="|software-recommendations|lammps|software-input-file-request|nanostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8874" PostTypeId="1" CreationDate="2022-03-30T19:10:15.140" Score="8" ViewCount="1516" Body="&lt;p&gt;I have &lt;code&gt;atom_row&lt;/code&gt; from ase_db.&#xA;I have tried various methods but they all fail. Seems like I'm missing a lattice, but I don't know what that is and where I can get it for my structure.&lt;/p&gt;&#xA;" OwnerUserId="4910" LastEditorUserId="7" LastEditDate="2022-04-15T16:36:20.057" LastActivityDate="2022-04-15T16:36:20.057" Title="Convert ase atoms to pymatgen structure" Tags="|computational-chemistry|electron-correlation|pymatgen|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8875" PostTypeId="1" CreationDate="2022-03-30T19:50:04.093" Score="4" ViewCount="247" Body="&lt;p&gt;I have xyz positions of my atoms in a &lt;code&gt;.txt&lt;/code&gt; file, how can I extract  information about bonding using VMD?&lt;/p&gt;&#xA;&lt;p&gt;I want to create a LAMMPS input file that contains not only the positions, but also information about the bonding of the structure.&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="7" LastEditDate="2022-03-30T20:21:23.457" LastActivityDate="2022-03-30T20:21:23.457" Title="Extracting bond information from the xyz positions of atoms?" Tags="|software|lammps|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8876" PostTypeId="2" ParentId="8875" CreationDate="2022-03-30T20:19:21.817" Score="6" Body="&lt;p&gt;This seems to be what the &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/plugins/topotools/&quot; rel=&quot;noreferrer&quot;&gt;TopoTools&lt;/a&gt; plugin is used for. This has commands for manipulating bonds/angles/dihedrals in VMD and then writing the corresponding information to a LAMMPS input file.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-03-30T20:19:21.817" CommentCount="3" CommunityOwnedDate="2022-03-30T20:19:29.623" ContentLicense="CC BY-SA 4.0" />
  <row Id="8877" PostTypeId="1" CreationDate="2022-03-30T14:16:53.183" Score="7" ViewCount="148" Body="&lt;p&gt;As far as I understand, sigma profile in COSMO - RS is a probability distribution of screening charge density for certain molecular surface segment.&lt;/p&gt;&#xA;&lt;p&gt;In COSMO - RS, molecular surface area is segmented into smaller surface segments and interactions between molecules are modelled via interaction of these segments.&lt;/p&gt;&#xA;&lt;p&gt;However, I see that sigma profiles are made for whole molecules which doesn't make sense given their definition. Shouldn't sigma profile be made for certain molecular segment rather than whole molecule?&lt;/p&gt;&#xA;" OwnerUserId="5192" OwnerDisplayName="Dario Mirić" LastActivityDate="2022-03-30T21:24:30.490" Title="Sigma Profile in COSMO - RS model" Tags="|thermodynamics|quantum-chemistry|intermolecular-forces|" AnswerCount="0" CommentCount="6" ClosedDate="2022-10-30T19:08:42.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="8878" PostTypeId="1" AcceptedAnswerId="8909" CreationDate="2022-03-31T14:10:48.267" Score="4" ViewCount="113" Body="&lt;p&gt;I am learning about COSMO model used in chemical engineering for calculating chemical potential and similiar quantites (actitvity coefficients) for solutes in solutions/mixtures.&lt;/p&gt;&#xA;&lt;p&gt;In the model, it is assumed that solvent is a continuum with some dielectric constant. Solute is placed inside cavities of such medium. Solute molecules are modeled as having certain shape and size with particular surface area and volume characteristic for molecules of different compounds.&lt;/p&gt;&#xA;&lt;p&gt;On wikipedia page: COSMO Solvation Model, it is said that if solvent were perfect conductor than electric potential on the surface of the cavity ,where solute is placed, is zero. I don't understand why this is. What law of nature supports this claim?&lt;/p&gt;&#xA;&lt;p&gt;I suppose it has something to do with electrostatic condition which says that if no current flows in a conductor, electric field must be zero at its every point or to be more precise electrochemical potential of charge carriers is the same in every point of the conductor since differences in chemical potential can drive current as well.&lt;/p&gt;&#xA;&lt;p&gt;I am not sure if electrostatic condition has something to do with this question.&lt;/p&gt;&#xA;" OwnerUserId="5192" LastEditorUserId="5192" LastEditDate="2022-03-31T14:20:34.673" LastActivityDate="2022-04-07T16:58:24.597" Title="COSMO Model and Electric Potential on the Surface of the Cavity Inside Perfect Conductor" Tags="|quantum-chemistry|thermodynamics|electric-field|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8879" PostTypeId="2" ParentId="8839" CreationDate="2022-03-31T14:40:47.620" Score="2" Body="&lt;p&gt;You don't need to set the &lt;code&gt;MAGMOM&lt;/code&gt; tag in the second step.&lt;/p&gt;&#xA;&lt;p&gt;This is because the charge density (including the spin density which is the charge difference between spin-up and spin-down) is read in from &lt;code&gt;CHGCAR&lt;/code&gt; and kept constant throughout the calculation due to &lt;code&gt;ICHARG = 11&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1804" LastActivityDate="2022-03-31T14:40:47.620" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8880" PostTypeId="1" CreationDate="2022-03-31T18:14:09.663" Score="6" ViewCount="54" Body="&lt;p&gt;I am using the framework &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt; to do computational chemistry calculations. I am using the calculator &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/&quot; rel=&quot;noreferrer&quot;&gt;GPAW&lt;/a&gt; with it.&lt;/p&gt;&#xA;&lt;p&gt;How do I extract data that is internal to the calculator? I mostly want to get the electric potential field, but, I am also interested in the electric field (if it keeps this) and the electron density.&lt;/p&gt;&#xA;&lt;p&gt;I am not very opposed to switching calculators if this info simply can't extracted from GPAW.&lt;/p&gt;&#xA;" OwnerUserId="5193" LastEditorUserId="7" LastEditDate="2022-03-31T20:33:06.453" LastActivityDate="2022-03-31T20:33:06.453" Title="Getting Internal Calculator Data in ASE" Tags="|density-functional-theory|computational-chemistry|python|atomic-simulation-environment|gpaw|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T22:38:42.090" ContentLicense="CC BY-SA 4.0" />
  <row Id="8881" PostTypeId="1" CreationDate="2022-04-01T08:10:46.957" Score="5" ViewCount="401" Body="&lt;p&gt;I am a new user of Quantum Espresso. I have to use Deuterium instead of Hydrogen for my work in DFT studies. Hydrogen Pseudopotential file is available in QE website. Please clarify what parameters I have to set in the QE input file in order to simulate Deuterium in QE.&lt;/p&gt;&#xA;" OwnerUserId="3687" LastEditorUserId="7" LastEditDate="2022-04-04T17:24:21.640" LastActivityDate="2022-04-07T00:48:14.177" Title="Quantum Espresso calculation for Deuterium" Tags="|density-functional-theory|quantum-espresso|pseudopotentials|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8882" PostTypeId="2" ParentId="8861" CreationDate="2022-04-01T15:14:38.207" Score="3" Body="&lt;p&gt;Full CI often indicates the exact solution of the electronic Schroedinger equation that can also be determined without starting with the Hartree-Fock reference wavefunction. For example, the Hylleraas method for Helium does not require Hartree-Fock or SCF and one can determine the ground state energy to high precision.&lt;/p&gt;&#xA;" OwnerUserId="5025" LastActivityDate="2022-04-01T15:14:38.207" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8883" PostTypeId="1" AcceptedAnswerId="8892" CreationDate="2022-04-02T08:34:51.940" Score="6" ViewCount="1354" Body="&lt;p&gt;In gromacs using the commands, &lt;a href=&quot;https://manual.gromacs.org/documentation/current/onlinehelp/gmx-insert-molecules.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;command_1&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx insert-molecules -f run03.pdb -ci CL.pdb -o out.pdb -nmol 119&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;will distribute CL ions in the system randomly, but how to specify a specific location to put the ions or molecules. For example if my periodic box is &lt;span class=&quot;math-container&quot;&gt;$\pu{5*5*10 nm^3}$&lt;/span&gt; I want to put the ions to the location of &lt;span class=&quot;math-container&quot;&gt;$\pu{x &amp;lt; 5 nm, y &amp;lt; 5 nm }$&lt;/span&gt; but &lt;span class=&quot;math-container&quot;&gt;$\pu{ z &amp;gt; 8 nm}$&lt;/span&gt; (of course randomly but specific) in another words top part of the box I have also tried, &lt;a href=&quot;https://manual.gromacs.org/documentation/current/onlinehelp/gmx-genion.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;command 2&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx genion -s ions.tpr -o out.pdb -p system.top -pname NA -nname CL -neutral&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But this command only replaces the SOL molecules (water) or some another residue in system.&lt;/p&gt;&#xA;&lt;p&gt;Can someone help me, many thanks may be some other software can edit the pdb file but adding lot of ions one by one is quite annoying.&lt;/p&gt;&#xA;" OwnerUserId="4536" LastEditorUserId="4536" LastEditDate="2022-12-26T07:44:55.300" LastActivityDate="2022-12-26T07:44:55.300" Title="How to add molecules to a specific location in periodic box using gromacs?" Tags="|molecular-modeling|gromacs|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8884" PostTypeId="1" CreationDate="2022-04-02T17:03:03.517" Score="4" ViewCount="524" Body="&lt;p&gt;I want to calculate elastic constants with VASP &amp;quot;by hand&amp;quot; (not by, e.g., DFPT) as I have a big structure (64 atoms). For this, I am making tests on &lt;span class=&quot;math-container&quot;&gt;$\ce{Si}$&lt;/span&gt; at the moment.&lt;/p&gt;&#xA;&lt;p&gt;So, I have done it for &lt;span class=&quot;math-container&quot;&gt;$C_{11}$&lt;/span&gt; for which I have obtained &lt;span class=&quot;math-container&quot;&gt;$C_{11}=\pu{1543.75 kbar}$&lt;/span&gt;, as compared with &lt;span class=&quot;math-container&quot;&gt;$\pu{1543.48 kbar}$&lt;/span&gt; with DFPT.&lt;/p&gt;&#xA;&lt;p&gt;Now, I want to calculate &lt;span class=&quot;math-container&quot;&gt;$C_{44}$&lt;/span&gt;. I have used, e.g., the following strain matrix:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0.0  0.0  0.0&#xA;0.0  0.0  0.0015&#xA;0.0  0.0015 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which leads to the cell vector matrix:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     5.4664034019782948    0.0000000000000000    0.0000000000000000&#xA;     0.0000000000000000    5.4664034019782948    0.0150000000000000&#xA;     0.0000000000000000    0.0150000000000000    5.4664034019782948&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have run the SCF calculations for which I have the following results (energies in eV):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-0.00150 -43.37379723&#xA;-0.00075 -43.37495130&#xA; 0.00000 -43.37531894&#xA; 0.00075 -43.37495130&#xA; 0.00150 -43.37379723&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I fit the curve with the polynomial &lt;span class=&quot;math-container&quot;&gt;$f(x)=a+bx^2$&lt;/span&gt;, to find &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;, and calculate &lt;span class=&quot;math-container&quot;&gt;$C_{44}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$C_{44}=\frac{2b}{V}$&lt;/span&gt; (as I do for &lt;span class=&quot;math-container&quot;&gt;$C_{11}$&lt;/span&gt;), I find:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$b=\pu{679.563 eV}$&lt;/span&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$V=\pu{163.34 Å^3}$&lt;/span&gt;&lt;br&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$C_{44}=\pu{13326 kbar}$&lt;/span&gt;&lt;br&gt;&#xA;which is obviously wrong as &lt;span class=&quot;math-container&quot;&gt;$C_{44}=\pu{1001.53 kbar}$&lt;/span&gt; from DFPT, if one does not account for the ionic relaxation (=&lt;span class=&quot;math-container&quot;&gt;$\pu{-251.1746 kbar}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know what's wrong in what I am doing?&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&lt;br&gt;&#xA;Pascal&lt;/p&gt;&#xA;" OwnerUserId="5200" LastEditorUserId="7" LastEditDate="2022-04-02T18:50:32.303" LastActivityDate="2022-04-03T06:00:51.260" Title="Elastic constant calculation" Tags="|vasp|elasticity|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8885" PostTypeId="1" CreationDate="2022-04-02T19:52:12.177" Score="6" ViewCount="250" Body="&lt;p&gt;I would like to know for which DF is useless to add dispersion corrections.&#xA;For example, I suppose that for the nonlocal density-based functionals such as wB97M-V it is unnecessary because the dispersion effect is included inside the VV10 nonlocal correlation part. I am wrong?&#xA;Can you list functionals (at least among the most used) for which is useless to add dispersion correction such as D3, D4 and so on?&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2022-04-05T00:30:13.477" Title="For what DFT functional is useless to add D3 or similar corrections?" Tags="|density-functional-theory|quantum-chemistry|functional|dispersion-correction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8886" PostTypeId="2" ParentId="8863" CreationDate="2022-04-02T20:49:21.253" Score="11" Body="&lt;p&gt;I'll turn my comment as an answer, as requested by the OP and Nike.&lt;/p&gt;&#xA;&lt;p&gt;Susi Lehtola's answer has already pointed out that dispersion (which may be a more accurate term than van der Waals interaction here) is by definition a non-local phenomenon, and semilocal functionals are at least unsuitable for describing dispersion. While it's not easy to prove that semilocal functionals can never describe dispersion accurately for Coulombic systems, one can at least show that for some (not necessarily realistic) external potential, semilocal functionals fail to describe dispersion at all. For example consider two helium atoms, each being placed at the center of an infinitely deep potential well. Then move the two atoms (together with their wells) from infinitely far away to a finite distance from each other. Any semilocal density functional will predict a zero energy change, because there is no mechanism for any of the helium atoms to sense whether the other helium atom is near or not: inside the wells none of the density derivatives change due to the incoming helium atom, while outside the wells all density derivatives vanish. However the true energy of course decreases as the helium atoms approach each other, since even strictly confined densities can interact with each other via dispersion. This is a case where semilocal functionals not only fail to describe dispersion accurately, but actually fail to describe it at all.&lt;/p&gt;&#xA;&lt;p&gt;In order for the functional to describe at least some dispersion in the two strictly confined helium atoms case, one must at least use a double integral over two spatial coordinates, such that every spatial point can know about the density behavior of any other spatial point. For example, a GGA-level dispersion functional (like &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3521275&quot; rel=&quot;noreferrer&quot;&gt;VV10&lt;/a&gt;) has the following form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_c = \frac{1}{2}\iint n(\mathbf{r}) \Phi(\mathbf{r}-\mathbf{r}', n(\mathbf{r}), \nabla n(\mathbf{r}), n(\mathbf{r}'), \nabla n(\mathbf{r}')) n(\mathbf{r}') d\mathbf{r} d\mathbf{r}' \tag{1}&#xA;$$&lt;/span&gt;&#xA;where, unlike the single-integral case, &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt; is allowed to depend on the spatial coordinates directly, but only through &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}-\mathbf{r}'$&lt;/span&gt;, otherwise one will break translational invariance. In VV10 the functional form is further restricted so that the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}-\mathbf{r}'$&lt;/span&gt; dependence is only through &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{r}-\mathbf{r}'|$&lt;/span&gt;, and there are no dot products like &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{r}-\mathbf{r}')\cdot\nabla n(\mathbf{r})$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\nabla n(\mathbf{r})\cdot\nabla n(\mathbf{r}')$&lt;/span&gt;, but one can also imagine functionals without such restrictions. (By the way, the use of such a functional form to describe the whole exchange-correlation energy, instead of just the dispersion energy, seems to be an under-researched direction, and I strongly believe that one can get much better functionals by using a VV10-like functional form to describe exchange and/or correlation.) Interestingly, one can show that even Eq. (1) cannot describe dispersion exactly, because it predicts that the dispersion energy of three non-overlapping densities is exactly the sum of the three pairwise dispersion energies, while in reality this is not the case due to the &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1723844&quot; rel=&quot;noreferrer&quot;&gt;Axilrod-Teller-Muto three-body dispersion term&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, there are still a bunch of semilocal functionals that try to describe dispersion without even a form like Eq. (1). While they certainly cannot describe dispersion when the densities of the interacting molecules do not overlap, they may still yield some attractive interaction when the densities overlap. The trick is to notice that if a system is dispersion-bound, this usually means that there are regions where the density is small and the density gradient is even smaller. Only directly contacting but nonbonded atom pairs can create such regions. Therefore, any semilocal functional that gives a sufficiently negative XC energy density (&lt;span class=&quot;math-container&quot;&gt;$\epsilon_{xc}$&lt;/span&gt;) when &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is small and &lt;span class=&quot;math-container&quot;&gt;$\nabla n$&lt;/span&gt; is even smaller, but a less negative &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{xc}$&lt;/span&gt; when &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is small and &lt;span class=&quot;math-container&quot;&gt;$\nabla n$&lt;/span&gt; is not too small, can potentially give a dispersion-like attraction; the former requirement stabilizes dispersion-bounded dimers while the latter destabilizes isolated molecules. By tuning the functional behavior in the small-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; region, one may even make the functional at least semi-quantitatively reproduce experimental vdW binding energies.&lt;/p&gt;&#xA;&lt;p&gt;An early example is the &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.475428&quot; rel=&quot;noreferrer&quot;&gt;mPW family of functionals&lt;/a&gt;, where the exchange energy density has a minimum w.r.t. &lt;span class=&quot;math-container&quot;&gt;$x=|\nabla n|/n^{4/3}$&lt;/span&gt; when &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; is large, and becomes less and less negative as &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; increases beyond this minimum. Because &lt;span class=&quot;math-container&quot;&gt;$n^{4/3}$&lt;/span&gt; decays faster than &lt;span class=&quot;math-container&quot;&gt;$|\nabla n|$&lt;/span&gt; as one goes into the density tail, the large &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; behavior of the functional is responsible for the description of weak interactions, and in the case of mPW, this means that molecules can reduce their energy by forming non-covalent complexes, because this reduces the total volume in which &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; is large: in the middle of these two molecules, &lt;span class=&quot;math-container&quot;&gt;$|\nabla n|$&lt;/span&gt; is reduced and &lt;span class=&quot;math-container&quot;&gt;$n^{4/3}$&lt;/span&gt; is increased due to the superposition of the molecular densities. The later development of the Minnesota functionals, from the earliest M05/M05-2X and the extremely popular M06-2X to the later M11L, MN15-L etc., incorporate the kinetic energy in their functional form, which provided greater flexibility for fine-tuning the dispersion energy of different systems.&lt;/p&gt;&#xA;&lt;p&gt;However, this kind of functionals have two inherent problems:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The computed dispersion energy depends almost exclusively on the density tails, while the actual dispersion interaction is equally, if not more, dependent on the bulk of the density. This is because dispersion is, to put it loosely, the attraction of instant, fluctuating dipoles, and the dipoles do no need to localize at the periphery of the molecules, but can as well be located deep inside molecules, even near atomic nuclei. Thus, semilocal functionals that try to get dispersion right have to use the information in the density tails to guess the location and intensity of the fluctuating dipoles inside the molecules. This may be possible (due to some holographic principle, for example), but it completely misses the physics.&lt;/li&gt;&#xA;&lt;li&gt;The functional likely does not describe dispersion between next nearest neighbors correctly. This is because the density overlap of a molecule with its next nearest neighbors is obstructed by the density of its nearest neighbors. There is no easy mechanism for a molecule to know whether it lives in a small cluster with only a single solvation layer, or if it lives in bulk solvent.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, I'd like to discuss the question of whether semilocal functionals can reproduce the &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; behavior of the dispersion energy. Although no common functional seems to have demonstrated this, it appears that this is in fact possible. Note that the density decays as &lt;span class=&quot;math-container&quot;&gt;$n(r) = \exp(-\alpha r)$&lt;/span&gt; for some &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8600/do-we-know-for-sure-that-all-atomic-and-molecular-wavefunctions-decay-exponentia/8601#8601&quot;&gt;my answer to another question&lt;/a&gt;). So if we have &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{xc} = O(|\ln n|^\beta/n)$&lt;/span&gt; in the small &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; limit for some number &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, the contribution of the density to the total energy will decay polynomially w.r.t. &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. This will yield a polynomially decaying interaction energy between molecules, and it is conceivable that we can make the decay behavior be like &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt;. However we would still suffer from the two problems mentioned above, and now there is a third problem: the &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; behavior will be lost if we use Gaussian basis sets, or any other basis set that does not decay exponentially, and if we use a basis set with a finite spatial extent (like a numerical AO basis set) we lose the dispersion interaction completely.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;TL;DR:&lt;/strong&gt; (1) There exist model systems where all semilocal functionals necessarily yield zero dispersion energy; (2) semilocal functionals can yield an attraction between non-polar molecules, and by empirical tuning one can make it resemble dispersion quantitatively, but even so they get the right answer for the wrong reason; (3) semilocal functionals fail to describe non-nearest-neighbor dispersion, and will be less and less accurate for large systems where non-nearest-neighbor interactions are abundant; (4) basically none of the existing semilocal functionals reproduce the &lt;span class=&quot;math-container&quot;&gt;$r^{-6}$&lt;/span&gt; behavior of dispersion (so they fail for molecules that are much farther than their vdW equilibrium distance), and while one may design a new semilocal functional that does so, the functional will be extremely sensitive to the basis set; (5) to describe dispersion accurately while not departing from the Kohn-Sham framework (i.e. neither leaning to the more empirical side and use DFT-D, nor leaning to the more wavefunction-theory side and use double hybrid DFT), one should use non-local functionals such as the VV10 family, which describe two-body dispersion in the correct way, but even they fail to capture at least some of the three-body dispersion effects.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="142" LastEditDate="2022-04-05T00:31:23.963" LastActivityDate="2022-04-05T00:31:23.963" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8887" PostTypeId="2" ParentId="8884" CreationDate="2022-04-03T06:00:51.260" Score="3" Body="&lt;p&gt;The deformation parameter (&lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;) in your strain matrix (&lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;=0.0015) seems to be 10 times smaller than the increment (&lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;=0.015) in the lattice-vector matrix.&lt;/p&gt;&#xA;&lt;p&gt;To correct for this, you can fit to &lt;span class=&quot;math-container&quot;&gt;$E=a+b(10 \times x)^2$&lt;/span&gt; and to get &lt;span class=&quot;math-container&quot;&gt;$a = -43.3753$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$b = 6.7956$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$C_{44}=$&lt;/span&gt;133.3108 kilobar.&lt;/p&gt;&#xA;&lt;p&gt;To find C&lt;span class=&quot;math-container&quot;&gt;$_{44}$&lt;/span&gt;, the strain matrix used actually is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0.0   0.0   0.0  &#xA;0.0   0.0   q/2  &#xA;0.0   q/2   0.0  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To account for the denominator 2 in the strain vectors, You can fit to &lt;span class=&quot;math-container&quot;&gt;$E=a+b(2\times 10 \times x)^2$&lt;/span&gt;. Now, we get &lt;span class=&quot;math-container&quot;&gt;$b = 1.6989$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$C_{44}=$&lt;/span&gt;33.3277 kilobar (&lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is same as before).&lt;/p&gt;&#xA;&lt;p&gt;If the fitting is done using a dimensionless deformation parameter (in units of the lattice constant), by fitting to &lt;span class=&quot;math-container&quot;&gt;$E=a+b(2\times 10 \times x/5.4664034019782948)^2$&lt;/span&gt;, we get &lt;span class=&quot;math-container&quot;&gt;$b=50.7660$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_{44}=$&lt;/span&gt;995.8838 kilobar which is close to the DFPT value. This last step makes sure correctly that the dimension of &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; is eV and the dimension of (2&lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;/&lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;) to be eV/&lt;span class=&quot;math-container&quot;&gt;$Å^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Sometimes, the strain matrix used for &lt;span class=&quot;math-container&quot;&gt;$C_{44}$&lt;/span&gt; includes a small diagonal element and has the form&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;q**2/(4-q**2) 0.0   0.0  &#xA;0.0           0.0   q/2  &#xA;0.0           q/2   0.0  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;See for example &lt;a href=&quot;https://github.com/ryokbys/vasp-utils/blob/master/elastic_constants.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt;. If you try with this strain matrix, you may get results in better agreement with DFPT.&lt;/p&gt;&#xA;" OwnerUserId="5025" LastActivityDate="2022-04-03T06:00:51.260" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8888" PostTypeId="1" CreationDate="2022-04-03T06:32:57.723" Score="7" ViewCount="103" Body="&lt;p&gt;When using most molecular electron structure codes that use GTOs for the density or wavefunction, it is possible to project the first-order density matrix onto 'natural orbitals' with MOs expressed using GTOs.&lt;/p&gt;&#xA;&lt;p&gt;What open-source codes are currently available to fit (presumably in a least-squares sense) MOs expressed using GTOs to:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;An arbitrary 3-D gridded density (with either vacuum or 3-D periodic boundary conditions)&lt;/li&gt;&#xA;&lt;li&gt;Wavefunction/density representations (plane waves, e.g. Quantum Espresso; Augmented plane waves, e.g. EXCITEing, etc.). In the latter case, presumably the 'augmented' part involves GTOs that could be used as at least a starting point for fitting to a 'GTOs only' representation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Additional background: I want to be able to accurately determine the topology of an arbitrary 3-D distribution of electron density rho(r), together with all the first and second partial derivatives with respect to the spatial coordinates. I also need an accurate quantum stress tensor, also at arbitrary points. Though gridded data introduces a discretization error, e.g. plane waves also introduce such a error as one uses a finite set of g-vectors from the FFT grid. Software I want to use expects GTOs, but if code exists to get the quantities above by other means with minimal spurious effects, then that's OK.&#xA;And yes, everyone, no matter their chosen representation, is fighting against numerical noise and effects caused by the electronic structure algorithm producing the density. 'Best effort' is what I am going for.&lt;/p&gt;&#xA;&lt;p&gt;Pointers to code repos gratefully received!&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: some progress - Frank Jensen below has kindly pointed out his recent work projecting onto GTOs, of which I was previously aware. The author of MultiWFN confirmed that this code can directly use wavefunctions from CP2K, and it seems that 'projwfc' from the Quantum-Espresso suite generates GTOs as an intermediate step to get Lowdin population analysis numbers from a plane-wave wavefunction, though it is currently not clear exactly how to get these GTOs out in Molden/WFX/other useable form. No significant progress on the 'fitting GTOs to an arbitrary 3-D density grid' yet, though.&lt;/p&gt;&#xA;" OwnerUserId="577" LastEditorUserId="577" LastEditDate="2022-04-09T00:29:05.897" LastActivityDate="2022-04-09T00:29:05.897" Title="Fitting GTOs to other density/wavefunction representations - state of the art?" Tags="|electronic-structure|gaussian|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="8889" PostTypeId="1" CreationDate="2022-04-03T09:28:47.937" Score="5" ViewCount="240" Body="&lt;p&gt;I need to get the optimal number of layers of (110) niobium that is a good representative of the behavior of the material, but I am facing two problems using Quantum Espresso,&lt;/p&gt;&#xA;&lt;p&gt;I Keep getting the following warning when relaxing the bulk material:&#xA;&lt;code&gt;SCF correction compared to forces is large: reduce conv_thr to get better values&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried reducing &lt;code&gt;conv_thr&lt;/code&gt;, increasing &lt;code&gt;ecutwfc&lt;/code&gt; and/or K-mesh,  and occupations but no success yet.&lt;/p&gt;&#xA;&lt;p&gt;The surface energy I get from the (110) slab I cleave from this bulk structure is continuously increasing with increasing number of layers, I am confused whether I am having a problem with the bulk or my surface calculations or even the PP I am using (I need to keep using NCPP as I am going to look into phonon bands), I also examined using dipole cancellation  but it does not make a significant difference.&lt;/p&gt;&#xA;&lt;p&gt;input file for bulk :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA; calculation=  'vc-relax',&#xA; title='ml_gr',&#xA; prefix='ml_gr',&#xA; verbosity='high',&#xA; restart_mode=   'from_scratch',&#xA; nstep=200,&#xA; iprint=1,&#xA; tprnfor=.true.,&#xA; outdir='./tmp',&#xA; disk_io='default',&#xA; pseudo_dir='../pp_sg15_oncv/',  ! vanderbilt  NC PBE,&#xA; forc_conv_thr=1.0d-6,&#xA;/&#xA;&#xA;&#xA;&amp;amp;SYSTEM&#xA;ibrav=0,&#xA;nat = 2 ,                            &#xA;ntyp = 1,&#xA;ecutwfc =  55.0 ,   &#xA;ecutrho =  440.0,&#xA;nosym=.true.,&#xA;occupations='smearing', smearing='cold', degauss=0.02,&#xA;&#xA;&#xA;vdw_corr='grimme-d3',&#xA;input_dft='PBE',&#xA;&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;startingwfc='random',&#xA;diagonalization='cg',&#xA;conv_thr = 1.0e-12,&#xA;mixing_beta = 0.2,&#xA;electron_maxstep=200,&#xA;&#xA;/&#xA;&amp;amp;IONS&#xA;ion_dynamics='bfgs',&#xA;upscale=20.0,&#xA;/&#xA;&#xA;&amp;amp;CELL&#xA;press_conv_thr = 0.5D0,&#xA;press = 0.D0,&#xA;cell_dynamics = 'bfgs',&#xA;cell_dofree = 'all',&#xA;cell_factor = 1.5D0,&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Nb 92.906  Nb_ONCV_PBE-1.2.upf  ! [Kr] 4d4 5s1,&#xA;&#xA;&#xA;K_POINTS automatic&#xA;12 12 12 0 0 0&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;        3.3205199242         0.0000000000         0.0000000000&#xA;        0.0000000000         3.3205199242         0.0000000000&#xA;        0.0000000000         0.0000000000         3.3205199242&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Nb     0.000000000         0.000000000         0.000000000&#xA;Nb     0.500000000         0.500000000         0.500000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;input script for slab :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA; calculation=  'relax'&#xA; title='ml_gr'&#xA; prefix='ml_gr'&#xA; verbosity='high'&#xA; restart_mode=    'from_scratch'&#xA; nstep=60&#xA; iprint=1&#xA; tprnfor=.true.&#xA; outdir='./tmp'&#xA; disk_io='default'&#xA; pseudo_dir='../pp_sg15_oncv/'  ! vanderbilt  NC PBE&#xA; forc_conv_thr=1.0d-6,&#xA; tefield=.true.&#xA; dipfield=.true.&#xA;/&#xA;&#xA;&#xA;&amp;amp;SYSTEM&#xA;eamp = 0.001  ! default = 0.001 Hartree&#xA;edir = 3&#xA;emaxpos= 0.9&#xA;eopreg= 0.05&#xA;&#xA;ibrav=0,&#xA;nat = 10 ,                             &#xA;ntyp = 1,&#xA;ecutwfc = 50   &#xA;ecutrho = 440  &#xA;nosym=.true.,&#xA;occupations='smearing', smearing='cold', degauss=0.02&#xA;&#xA;&#xA;!vdw_corr='grimme-d3'&#xA;!input_dft='PBE'&#xA;&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;startingwfc='random'&#xA;diagonalization='cg'&#xA;conv_thr = 1.0e-12&#xA;mixing_beta = 0.2&#xA;electron_maxstep=200&#xA;mixing_mode= 'local-TF'&#xA;/&#xA;&amp;amp;IONS&#xA;ion_dynamics='bfgs'&#xA;upscale=20.0&#xA;/&#xA;&#xA;&#xA;ATOMIC_SPECIES&#xA;Nb 92.906  Nb_ONCV_PBE-1.2.upf  ! [Kr] 4d4 5s1&#xA;&#xA;&#xA;K_POINTS automatic&#xA;12 12 1 0 0 0&#xA;&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;        4.6764001846         0.0000000000         0.0000000000&#xA;        0.0000000000         3.3066999912         0.0000000000&#xA;        0.0000000000         0.0000000000        24.3547992706&#xA;&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Nb           -0.0000000048       -0.0000000013        0.7645284914&#xA;Nb            0.4999999930        0.4999999972        0.7645331978&#xA;Nb           -0.0000000009       -0.0000000008        0.5760377744&#xA;Nb            0.5000000008       -0.0000000057        0.6725692685&#xA;Nb            0.0000000027        0.5000000010        0.6725616708&#xA;Nb            0.5000000005        0.4999999955        0.5760366470&#xA;Nb            0.0000000061        0.0000000081        0.3875391377&#xA;Nb            0.4999999975       -0.0000000019        0.4795087546&#xA;Nb           -0.0000000008        0.5000000095        0.4795079850&#xA;Nb            0.5000000059        0.4999999984        0.3875406089&#xA;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1963" LastEditorUserId="1963" LastEditDate="2022-04-19T20:07:53.163" LastActivityDate="2022-04-19T20:07:53.163" Title="electronic structure of (110) Nb" Tags="|quantum-espresso|electronic-structure|surfaces|" AnswerCount="0" CommentCount="6" ClosedDate="2022-11-02T00:28:50.060" ContentLicense="CC BY-SA 4.0" />
  <row Id="8890" PostTypeId="1" AcceptedAnswerId="8899" CreationDate="2022-04-03T13:42:45.977" Score="3" ViewCount="352" Body="&lt;p&gt;I calculate the atomic charge using restricted electrostatic potential (RESP) and compute with the Hartree Fock method. This method is OK for organic compounds, but for complexes that contain transition metals, I need to use keyword &lt;code&gt;Pop=(ReadRadii,MK)&lt;/code&gt; and read the radius of the metal in the input.&lt;/p&gt;&#xA;&lt;p&gt;How can I know the correct radius for my transition metal? I looked on Google, and they always use 2.0 for copper or other atoms, etc.&lt;/p&gt;&#xA;&lt;p&gt;Also, is there anyway where I can set a charge (charge that I want) on a specific atom in the Gaussian input?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="7" LastEditDate="2022-04-04T00:46:54.717" LastActivityDate="2022-04-05T20:37:21.497" Title="Calculate the atomic charge for transition metal using RESP?" Tags="|molecular-dynamics|gaussian|qmmm|amber|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8891" PostTypeId="2" ParentId="8682" CreationDate="2022-04-03T15:48:20.160" Score="4" Body="&lt;p&gt;The simplest way to check the correlation between &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;-type basis functions in a high-symmetry point group (say &lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt;) and in its Abelian subgroup (say &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;) or any other subgroup is to compare their character tables from &lt;a href=&quot;http://symmetry.jacobs-university.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://symmetry.jacobs-university.de/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt;&#xA;&lt;a href=&quot;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=1001&amp;amp;option=4&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=1001&amp;amp;option=4&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;&#xA;&lt;a href=&quot;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=602&amp;amp;option=4&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://symmetry.jacobs-university.de/cgi-bin/group.cgi?group=602&amp;amp;option=4&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here's how the correlation looks like for the 7 spherical &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt;-type functions.&lt;/p&gt;&#xA;&lt;h4&gt;Correlation table&lt;/h4&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: left;&quot;&gt;basis functions&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt;&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$z^3$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Sigma_u^+$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$xz^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Pi_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$yz^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Pi_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$y(3x^2-y^2)$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$x(x^2-3y^2)$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$xyz$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$A_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$z(x^2-y^2)$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: left;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta_u$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;So, you can write &lt;span class=&quot;math-container&quot;&gt;$\Phi_u$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$B_{2u} \bigoplus B_{3u}$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5025" LastEditorUserId="5025" LastEditDate="2022-04-04T02:54:30.280" LastActivityDate="2022-04-04T02:54:30.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8892" PostTypeId="2" ParentId="8883" CreationDate="2022-04-03T23:50:17.840" Score="4" Body="&lt;p&gt;&lt;code&gt;GROMACS&lt;/code&gt; should be able to do this using the &lt;code&gt;-ip&lt;/code&gt; &lt;code&gt;-dr&lt;/code&gt; options associated with the tool &lt;code&gt;insert-molecules&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have not used this myself, but the &lt;a href=&quot;https://manual.gromacs.org/documentation/current/onlinehelp/gmx-insert-molecules.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS insert-molecules&lt;/a&gt; documentation seems to indicate that these will do what you want. (now that you have tried them and they do work... well, now we know.)&lt;/p&gt;&#xA;&lt;p&gt;As was also mentioned in the comments by @Vasista, the venerable &lt;a href=&quot;http://leandro.iqm.unicamp.br/m3g/packmol/home.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;Packmol&lt;/a&gt; can  do this too.&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2022-04-03T23:50:17.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8893" PostTypeId="1" CreationDate="2022-04-04T03:01:44.520" Score="5" ViewCount="3739" Body="&lt;p&gt;I got below mentioned error while trying to optimise a Ru transition metal complex using&#xA;6-311++G(d,p)&lt;/p&gt;&#xA;&lt;p&gt;Can you please assist me to resolve this problem&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error termination in NtrErr:&#xA; NtrErr Called from FileIO.`&#xA;&#xA; Number            698           701           710           711           780           989&#xA; Base          4650052       4650400       2276811       3677828       9027123       2037482&#xA; End           4650400       4772209       2280541       4130096       9978828       2057482&#xA; End1          4650400       4772209       2280541       4130096       9978828       2057482&#xA; Wr Pntr       4650052       4650400       2276811       3677828       9027123       2037482&#xA; Rd Pntr       4650052       4650400       2276811       3677828       9978828       2037482&#xA; Length            348        121809          3730        452268        951705         20000&#xA;&#xA; Number            993           997           998&#xA; Base          2057482       2057682         40990&#xA; End           2057682       2058800         41190&#xA; End1          2057682       2058800         41190&#xA; Wr Pntr       2057482       2057682         40990&#xA; Rd Pntr       2057482       2057682         41190&#xA; Length            200          1118           200&#xA;&#xA;&#xA; dumping /fiocom/, unit = 3 NFiles =     1 SizExt =    524288 WInBlk =      1024&#xA;                   defal = T LstWrd =       65536 FType=2 FMxFil=10000&#xA;&#xA; Number              0&#xA; Base            40960&#xA; End             65536&#xA; End1            65536&#xA; Wr Pntr         40960&#xA; Rd Pntr         40960&#xA; Length          24576&#xA; Error termination in NtrErr:&#xA; NtrErr Called from FileIO.&#xA;&amp;quot;NeutralB3LYPmethanoloptimizationCl6-311+gdprestart.log&amp;quot; 3353L, 226558&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=4GB&#xA;%nprocshared=4&#xA;%chk=NeutralB3LYPmethanoloptimizationCl6-311+gdprestart.chk&#xA;# opt freq b3lyp/genecp scrf=(solvent=methanol) guess=save&#xA;geom=connectivity&#xA;&#xA;Neutral Fluoride Complex from the X-ray crystal structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5206" LastEditorUserId="7" LastEditDate="2022-04-04T13:45:00.230" LastActivityDate="2022-04-04T13:45:00.230" Title="Gausian 09 error: NtrErr Called from FileIO" Tags="|gaussian|" AnswerCount="0" CommentCount="7" ClosedDate="2022-09-07T22:38:13.763" ContentLicense="CC BY-SA 4.0" />
  <row Id="8894" PostTypeId="2" ParentId="8885" CreationDate="2022-04-05T00:30:13.477" Score="4" Body="&lt;p&gt;You should not apply empirical dispersion corrections to functionals that are overbinding already without dispersion. LDA functionals are a prominent example: even LDA exchange is overbinding by itself!&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-04-05T00:30:13.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8895" PostTypeId="1" AcceptedAnswerId="9190" CreationDate="2022-04-05T10:43:33.917" Score="7" ViewCount="624" Body="&lt;p&gt;The Schrödinger equation, the fundamental basis of wavefunction-based methods, cannot be solved in closed form per se. One can, however, solve it by using a finite number of closed-form basis sets (and the corresponding closed-form Slater determinants) and letting the basis set tend toward the complete basis set; this is similar to how most mathematical functions, that cannot be written in closed form per se, can be written as  limits of sequences of closed-form functions.&lt;/p&gt;&#xA;&lt;p&gt;It is currently unknown whether the exact exchange-correlation functional in DFT can be written in closed form or not. However, it should be able to be written as some limit of some sequence closed-form formulae, since the end result, i.e. the solution, is (vide supra) and the exchange-correlation functional can be written in a closed form expression when the end result is explicitly included as a term. (I'm a mathematics student, so I know what I'm talking about)&lt;/p&gt;&#xA;&lt;p&gt;Now comes my main question- is my reasoning correct; i.e. is there any explicit series of closed-form &amp;quot;approximate DFT functionals' that mathematically converges to the exact potential?&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: After reading the answer that a sequence of neural networks can converge to the exact potential, which was not the type of answer that I wanted, I'm editing this post to re-ask a more intended question.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-06-03T04:06:25.363" LastActivityDate="2022-06-03T04:32:56.153" Title="Is there a sequence/sum of commonly used, closed-form &quot;DFT functional&quot;s that mathematically converges to the exact exchange-correlation potential?" Tags="|density-functional-theory|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8896" PostTypeId="2" ParentId="8895" CreationDate="2022-04-05T12:06:41.323" Score="9" Body="&lt;p&gt;There is one, although I'm afraid it is not what you want. The exchange energy is a continuous and non-singular functional of the density, so thanks to the universal approximation theorem, it can be approximated by a one-layer neural network that takes the density as input, to arbitrary precision. One therefore has a sequence of increasingly large neural networks that converge to the exact exchange functional. Taking the functional derivative of this sequence gives a series of better and better approximations to the exact exchange potential, and they converge pointwise to the exact exchange potential.&lt;/p&gt;&#xA;&lt;p&gt;Likewise, one can prove that there is an explicit closed-form sequence that converges to the exact exchange-correlation potential, or the exact kinetic potential, etc.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-04-05T13:01:29.250" LastActivityDate="2022-04-05T13:01:29.250" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8897" PostTypeId="2" ParentId="8895" CreationDate="2022-04-05T17:26:35.670" Score="4" Body="&lt;p&gt;The exact exchange potential is not a problem. We know the exact exchange functional, and we also know how to build an optimized effective potential from it.&lt;/p&gt;&#xA;&lt;p&gt;The problem is many-particle quantum mechanics, that is, correlation. The whole division into exchange vs correlation arises from the Hartree-Fock model: the model by definition captures all exchange, and the remaining bit is called correlation.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-04-05T17:26:35.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8898" PostTypeId="1" CreationDate="2022-04-05T16:38:57.560" Score="1" ViewCount="1197" Body="&lt;p&gt;I have been trying to perform some calculations in Quantum espresso on mono-layer Borophene. Initially, I have optimized the structure which succeeds. Subsequently, I am trying to use this optimized geometry to perform a band structure calculation. However, at this step, the job abruptly stops and the output file ends with the following error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine potinit (1):&#xA;     starting and expected charges differ&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;     Error in routine potinit (1):&#xA;     starting and expected charges differ&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have not been able to rectify this problem. Following is my input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation   = &amp;quot;bands&amp;quot;&#xA;    forc_conv_thr =  1.00000e-03&#xA;    max_seconds   =  8.62000e+04&#xA;    nstep         = 100&#xA;    pseudo_dir    = &amp;quot;/scratch/15mt91r01/pseudopot&amp;quot;&#xA;    restart_mode  = &amp;quot;from_scratch&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;    a           =  1.52100e+01&#xA;    b           =  1.17200e+01&#xA;    c           =  2.00000e+01&#xA;    degauss     =  1.00000e-02&#xA;    ecutrho     =  2.25000e+02&#xA;    ecutwfc     =  5.20000e+01&#xA;    ibrav       = 8&#xA;    nat         = 60&#xA;    nbnd        = 240&#xA;    ntyp        = 1&#xA;    occupations = &amp;quot;smearing&amp;quot;&#xA;    smearing    = &amp;quot;gaussian&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  7.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;BANDS&#xA;    lsym           = .FALSE.&#xA;    spin_component = 1&#xA;/&#xA;&#xA;K_POINTS {tpiba_b}&#xA;16&#xA;gG     20&#xA;X      20&#xA;S      20&#xA;Y      20&#xA;gG     20&#xA;Z      20&#xA;U      20&#xA;R      20&#xA;T      20&#xA;Z      0&#xA;Y      20&#xA;T      0&#xA;U      20&#xA;X      0&#xA;S      20&#xA;R      0&#xA;&#xA;ATOMIC_SPECIES&#xA;B      10.81100  B.pbe-n-van_ak.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;B       0.000000   0.000000   5.000000&#xA;B       1.689998   0.000000   5.000000&#xA;B       3.380002   0.000000   5.000000&#xA;B       0.845002   1.465000   5.000000&#xA;B       2.535000   1.465000   5.000000&#xA;B       0.000000   2.930000   5.000000&#xA;B       1.689998   2.930000   5.000000&#xA;B       3.380002   2.930000   5.000000&#xA;B       0.845002   4.395000   5.000000&#xA;B       2.535000   4.395000   5.000000&#xA;B       0.000000   5.860000   5.000000&#xA;B       1.689998   5.860000   5.000000&#xA;B       3.380002   5.860000   5.000000&#xA;B       0.845002   7.325000   5.000000&#xA;B       2.535000   7.325000   5.000000&#xA;B       0.000000   8.790000   5.000000&#xA;B       1.689998   8.790000   5.000000&#xA;B       3.380002   8.790000   5.000000&#xA;B       0.845002  10.255000   5.000000&#xA;B       2.535000  10.255000   5.000000&#xA;B       5.070000   0.000000   5.000000&#xA;B       6.759998   0.000000   5.000000&#xA;B       8.450002   0.000000   5.000000&#xA;B       5.915002   1.465000   5.000000&#xA;B       7.605000   1.465000   5.000000&#xA;B       5.070000   2.930000   5.000000&#xA;B       6.759998   2.930000   5.000000&#xA;B       8.450002   2.930000   5.000000&#xA;B       5.915002   4.395000   5.000000&#xA;B       7.605000   4.395000   5.000000&#xA;B       5.070000   5.860000   5.000000&#xA;B       6.759998   5.860000   5.000000&#xA;B       8.450002   5.860000   5.000000&#xA;B       5.915002   7.325000   5.000000&#xA;B       7.605000   7.325000   5.000000&#xA;B       5.070000   8.790000   5.000000&#xA;B       6.759998   8.790000   5.000000&#xA;B       8.450002   8.790000   5.000000&#xA;B       5.915002  10.255000   5.000000&#xA;B       7.605000  10.255000   5.000000&#xA;B      10.140000   0.000000   5.000000&#xA;B      11.829998   0.000000   5.000000&#xA;B      13.520002   0.000000   5.000000&#xA;B      10.985002   1.465000   5.000000&#xA;B      12.675000   1.465000   5.000000&#xA;B      10.140000   2.930000   5.000000&#xA;B      11.829998   2.930000   5.000000&#xA;B      13.520002   2.930000   5.000000&#xA;B      10.985002   4.395000   5.000000&#xA;B      12.675000   4.395000   5.000000&#xA;B      10.140000   5.860000   5.000000&#xA;B      11.829998   5.860000   5.000000&#xA;B      13.520002   5.860000   5.000000&#xA;B      10.985002   7.325000   5.000000&#xA;B      12.675000   7.325000   5.000000&#xA;B      10.140000   8.790000   5.000000&#xA;B      11.829998   8.790000   5.000000&#xA;B      13.520002   8.790000   5.000000&#xA;B      10.985002  10.255000   5.000000&#xA;B      12.675000  10.255000   5.000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="753" OwnerDisplayName="Avrana" LastEditorUserId="753" LastEditDate="2022-04-06T08:07:24.813" LastActivityDate="2022-04-21T00:07:29.877" Title="Repeated error in Quantum Espresso &quot;Error in routine potinit (1)&quot;" Tags="|quantum-espresso|software|band-structure|quantum-chemistry|software-assistance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8899" PostTypeId="2" ParentId="8890" CreationDate="2022-04-05T20:37:21.497" Score="0" Body="&lt;p&gt;The radius (specifically the van der Waals radius) of the atoms is used during the Merz-Kollman procedure to determine what set of points should be sampled to get a reasonably accurate fit of the ESP. For some metals, the van der Waals radii can simply be looked up in a &lt;a href=&quot;https://en.wikipedia.org/wiki/Van_der_Waals_radius#Table_of_Van_der_Waals_radii&quot; rel=&quot;nofollow noreferrer&quot;&gt;table&lt;/a&gt;. If you are unable to find radii for a particular element, an alternative would be to use the keyword &lt;code&gt;mkuff&lt;/code&gt;. This uses radii computed with the Universal Force Field, which are available for every element in the periodic table.&lt;/p&gt;&#xA;&lt;p&gt;As for specifying the charge, in principle you can apply almost any constraint on the charges during the fitting to the ESP. In practice, Gaussian allows you to set the charge before the fitting by including the &lt;code&gt;pop=uncharged&lt;/code&gt; keyword, which only fits any initially unset charges. A simple example might look like, where I'm considering &lt;span class=&quot;math-container&quot;&gt;$\ce{H3O+}$&lt;/span&gt; surrounded by point charges that are taking the place of surrounding water molecules:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p HF/3-21g nosym pop=(esp,uncharged)&#xA;&#xA;H3O+&#xA;&#xA;1 1&#xA;O       0 -0.50964188 1.00550963 0.00000000&#xA;H       0 0.45035812 1.00550963 0.00000000&#xA;H       0 -0.83009647 1.91044546 0.00000000&#xA;H       0 -1.06370126 0.22153373 0.00000000&#xA;O-#6--0.6465214       0 -4.03581272 -0.34435261 0.00000000&#xA;H-#6-0.5119446       0 -3.07581272 -0.34435261 0.00000000&#xA;H-#6-0.4903441       0 -4.35626731 0.56058322 0.00000000&#xA;O-#6--1.0214505       0 2.38292014 2.90633604 0.00000000&#xA;H-#6-0.3316260       0 3.34292014 2.90633604 0.00000000&#xA;H-#6-0.2799662       0 2.06246555 3.81127188 0.00000000&#xA;O-#6--0.9783521       0 -3.70523421 3.56749306 0.00000000&#xA;H-#6-0.1651149       0 -2.74523421 3.56749306 0.00000000&#xA;H-#6-0.3022461       0 -4.02568879 4.47242889 0.00000000&#xA;O-#6--0.7575957       0 2.13498625 -0.56473828 0.00000000&#xA;H-#6-0.4518826       0 3.09498625 -0.56473828 0.00000000&#xA;H-#6-0.1925964       0 1.81453167 0.34019755 0.00000000&#xA;O-#6--0.5969358       0 -0.60425725 1.07007829 -1.97552048&#xA;H-#6-0.5439027       0 0.35574275 1.07007829 -1.97552048&#xA;H-#6-0.2754568       0 -0.92471184 1.97501412 -1.97552048&#xA;O-#6--0.6915599       0 -0.76708769 1.14464887 2.43407203&#xA;H-#6-0.4910393       0 0.19291231 1.14464887 2.43407203&#xA;H-#6-0.2999107       0 -1.08754227 2.04958470 2.43407203&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You specify the MM atom type and charge directly after each element.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-04-05T20:37:21.497" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8900" PostTypeId="2" ParentId="8888" CreationDate="2022-04-06T07:07:18.243" Score="4" Body="&lt;p&gt;Not clear to me exactly what you want, but we have shown that any valid electron density can be represented by a set of orbitals in a single Slater determinant:&#xA;P. Jakobsen, F. Jensen &amp;quot;Representing exact electron densities by a single Slater determinant in finite basis sets.&amp;quot; J. Chem. Theory Comp. 17 (2021) 269-276.&#xA;One can think of these as &amp;quot;natural orbitals&amp;quot; but with occupation numbers of exactly 2 (and 0). The code for determining these orbitals is available, but is 'research grade'. We used this for determining a set of orbitals reproducing the full-CI electron density.&#xA;This is using the reference density expressed in GTOs and the orbitals also expanded in GTOs, where the latter usually needs to be larger than the former for achieving a sufficient accuracy.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2022-04-06T07:07:18.243" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8901" PostTypeId="1" CreationDate="2022-04-06T12:25:35.667" Score="5" ViewCount="120" Body="&lt;p&gt;I'm trying to calculate the thermal properties of Silicene with hydrogen and halogen atoms. My problem is that, there's seems no available potential  for Tersoff and Stillinger Weber Potential. and I'm  looking everywhere to find one. Where I can get one tho? I'm still new to this hope you all understand.&lt;/p&gt;&#xA;" OwnerUserId="5119" LastActivityDate="2022-08-04T18:28:13.207" Title="Where to find/ to get Tersoff and Stillinger Weber Potentials for MD simulation using LAMMPS" Tags="|molecular-dynamics|lammps|forcefields|interatomic-potentials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8902" PostTypeId="1" AcceptedAnswerId="8903" CreationDate="2022-04-06T15:58:40.177" Score="5" ViewCount="331" Body="&lt;p&gt;I run into this article&lt;sup&gt;[1]&lt;/sup&gt; in which they figure out that if you want to correctly simulate electronic spectra you have to consider the &lt;em&gt;non-equilibrium&lt;/em&gt; solvation.&lt;/p&gt;&#xA;&lt;p&gt;I've made research into the documentation of Orca, but I couldn't find anything about how set this type of calculation.&lt;/p&gt;&#xA;&lt;p&gt;I'm using CPCM n-hexane. Does someone know how to include non-equilibrium implicit solvation effects in Orca?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Cammi, R.; Corni, S.; Mennucci, B.; Tomasi, J. &lt;a href=&quot;https://doi.org/10.1063/1.1867373&quot; rel=&quot;noreferrer&quot;&gt;Electronic excitation energies of molecules in solution: State specific and linear response methods for nonequilibrium continuum solvation models.&lt;/a&gt; &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2005,&lt;/strong&gt; &lt;em&gt;122&lt;/em&gt; (10), 104513. DOI: 10.1063/1.1867373.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="7" LastEditDate="2022-04-06T16:25:50.317" LastActivityDate="2022-04-06T16:39:53.050" Title="Non-equilibrium CPCM for Orca Absorption Spectra" Tags="|orca|implicit-solvent|nonequilibrium|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8903" PostTypeId="2" ParentId="8902" CreationDate="2022-04-06T16:39:53.050" Score="5" Body="&lt;p&gt;ORCA by default uses non-equilibrium solvation for single-point TDDFT calculations, and equilibrium solvation when the TDDFT gradient is requested (e.g. when doing excited state geometry optimization, numerical frequency and molecular dynamics calculations). Thus in most cases it is not necessary to explicitly request for equilibrium/non-equilibrium solvation, as the default choice is usually the correct one. If it is desired to override the default behavior, one can use the CPCMEQ keyword in the %tddft block. For example, the following input block calculates 5 non-equilibrium solvated states, regardless of whether the gradient is requested:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%tddft&#xA;nroots 5&#xA;cpcmeq false&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Contrarily, setting CPCMEQ to true requests equilibrium solvation.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-04-06T16:39:53.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8904" PostTypeId="2" ParentId="8881" CreationDate="2022-04-07T00:48:14.177" Score="7" Body="&lt;p&gt;The main difference between deuterium and hydrogen is the mass, so you need to set the mass of the &amp;quot;hydrogen&amp;quot; so that it matches deuterium. I'm not a Quantum Espresso expert, but I think you do this by setting the &lt;code&gt;ATOMIC_SPECIES&lt;/code&gt; card, see:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#ATOMIC_SPECIES&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/INPUT_PW.html#ATOMIC_SPECIES&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, you need to be clear about what effects you are wanting to simulate, because many common simulation tasks are not affected by the nuclear mass at all.&lt;/p&gt;&#xA;&lt;p&gt;The pseudopotential doesn't care about the nuclear mass, so you don't need to change anything. For the same reason, the electronic ground state will be identical between hydrogen and deuterium, since Quantum Espresso uses an adiabatic approximation to decouple the nuclear and electronic  wavefunctions. If you look at the &amp;quot;electronic&amp;quot; Kohn-Sham equations, the nuclear mass doesn't appear at all.&lt;/p&gt;&#xA;&lt;p&gt;The optimised geometry of your material or molecule will also be the same; this is because Quantum Espresso optimises the structure at zero Kelvin and treats the atoms semi-classically, so there is no quantum delocalisation/zero-point motion for the nuclei - essentially, there is no nuclear kinetic energy term. If there is no temperature and no nuclear quantum effects, then the nuclear mass doesn't enter any of the equations and deuterium will give the same answer as hydrogen.&lt;/p&gt;&#xA;&lt;p&gt;The mass &lt;em&gt;will&lt;/em&gt; affect molecular dynamics and path-integral/ring-polymer molecular dynamics, and it will also affect any vibrational properties such as phonons (though the force constant matrix will be the same as for hydrogen). Other nuclear properties might be relevant for some kinds of simulations, such as the nuclear spin (e.g. for NMR chemical shifts).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-04-07T00:48:14.177" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8905" PostTypeId="1" CreationDate="2022-04-07T03:41:38.303" Score="4" ViewCount="45" Body="&lt;p&gt;I have a peptide X of length 50aa. Alphafold2 predicted the structure which takes a helix form and with high average  pLDDT score (&amp;gt;90).&lt;/p&gt;&#xA;&lt;p&gt;But during actual experiment (e.g. crystallography, spectroscopy), peptide X is determined to have a &lt;em&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Random_coil&quot; rel=&quot;nofollow noreferrer&quot;&gt;random coil&lt;/a&gt;&lt;/em&gt; structure.&lt;/p&gt;&#xA;&lt;p&gt;My question is how can I resolve the difference between AF2 prediction and crystallography?&#xA;To what extend we can use AF2 peptide structure prediction for downstream analysis (e.g. docking, etc)?&lt;/p&gt;&#xA;" OwnerUserId="4479" LastEditorUserId="4479" LastEditDate="2022-11-09T08:35:55.773" LastActivityDate="2022-11-09T08:35:55.773" Title="How reliable is Alphafold 2 for folding random-coil peptide" Tags="|proteins|protein-folding|" AnswerCount="0" CommentCount="2" ClosedDate="2022-12-12T15:13:19.467" ContentLicense="CC BY-SA 4.0" />
  <row Id="8907" PostTypeId="1" CreationDate="2022-04-07T09:53:34.390" Score="4" ViewCount="89" Body="&lt;p&gt;I was wondering whether you know if there is any sort of literature discussing whether periodic boundary conditions or spherical potentials could be better or worse for QM/MM or MM simulations, their impact in the dynamics... Any sort of material is welcome. What would you choose?&lt;/p&gt;&#xA;&lt;p&gt;I know periodic boundary conditions are more broadly used but I want to know the pros of the spherical potentials too.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2022-04-07T09:53:34.390" Title="Periodic boundary conditions or spherical potential?" Tags="|molecular-dynamics|intermolecular-forces|qmmm|periodic-boundary-conditions|" AnswerCount="0" CommentCount="3" ClosedDate="2022-09-07T22:37:36.567" ContentLicense="CC BY-SA 4.0" />
  <row Id="8908" PostTypeId="1" CreationDate="2022-04-07T13:36:03.497" Score="6" ViewCount="93" Body="&lt;p&gt;I am considering a material that exhibits metallic properties from the four probe measurements between 50-400K. Its electrical conductivity is about 15-20 S/cm and kept almost unchanged with temperatures. However, I estimated the density of states using the GGA+U for transition metal and compared it with the HSE06 method. Both show that the material has a large band gap, suggesting a semiconductor instead. I wonder which factors would cause this?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2022-09-07T14:28:55.957" LastActivityDate="2022-09-07T14:28:55.957" Title="Why do both my GGA+U and HSE06 calculations suggest that my material is a semiconductor, when I know it should be a conductor?" Tags="|electronic-transport|" AnswerCount="0" CommentCount="9" ClosedDate="2022-10-26T13:12:30.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="8909" PostTypeId="2" ParentId="8878" CreationDate="2022-04-07T14:50:42.510" Score="4" Body="&lt;p&gt;First of all, the&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;method used in chemical engineering for calculating chemical potential and similar quantities (actitvity coefficients) for solutes in solutions/mixtures&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is called COSMO-RS and not COSMO. Almost the same name, but very different meaning :-)&lt;/p&gt;&#xA;&lt;p&gt;COSMO is a continuum solvation model often used in quantum chemistry. To learn more about it either try to get a copy of the book that was already mentioned in the comment, or google also for CPCM which is just another name for the same model.&#xA;COSMO-RS uses the &lt;strong&gt;output&lt;/strong&gt; of COSMO calculations to do thermodynamics from which chemical potentials in liquids are derived.  OK, but that was not your question...&lt;/p&gt;&#xA;&lt;p&gt;COSMO generates a cavity around the molecule (based on some kind of solvent-accessible surface) and assumes it to have a dielectric constant of infinity. That's a property metals have (and what &amp;quot;perfect conductor&amp;quot; refers to: an ideal metal).&lt;/p&gt;&#xA;&lt;p&gt;So why is the electrostatic potential on a metal zero?&#xA;The correct answer is that it is not zero but constant. As there is no absolute value for potentials (as only differences are physically meaningful), COSMO simply sets this constant to zero. Another wording for that is: It defines the reference state. So all values of the electrostatic potential at each point in space in a COSMO calculation are relative to the value on the cavity surface (which is set to zero for practical reasons).&lt;/p&gt;&#xA;&lt;p&gt;The reason why an electrostatic potential is constant on a metal indeed stems from standard electrostatics (check your physics book):&lt;/p&gt;&#xA;&lt;p&gt;The work (W) caused by an electric force (= electric field E) on a test charge q moved in space from &lt;span class=&quot;math-container&quot;&gt;$r_1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$r_2$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$dr=r_2-r_1$&lt;/span&gt;):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ dW = - F  dr $$&lt;/span&gt;&#xA;with the force F:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ F = q E$$&lt;/span&gt;&#xA;So you need to 'spend' a work &lt;span class=&quot;math-container&quot;&gt;$dW$&lt;/span&gt; to move a charge in an electric field.&lt;/p&gt;&#xA;&lt;p&gt;The work done by an electrostatic force is the negative of the change in potential energy, &lt;span class=&quot;math-container&quot;&gt;$dU$&lt;/span&gt; (so &lt;span class=&quot;math-container&quot;&gt;$dW = dU$&lt;/span&gt; ):&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$dU = -q  E  dr$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; (or better: the difference in the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, so something like &lt;span class=&quot;math-container&quot;&gt;$V(r_2) - V(r_1)$&lt;/span&gt; ) is defined as the change in potential energy divided by the test charge q:  &lt;span class=&quot;math-container&quot;&gt;$V_{12} = - E  (r_2-r_1)$&lt;/span&gt; for a constant electric field E, otherwise you need the integral of E with respect to r...&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$dV = dU / q$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;On a metal the electrons can move freely, so there is no difference in potential energy &lt;span class=&quot;math-container&quot;&gt;$dU$&lt;/span&gt; - because if there WAS a force between two points in the same metal, the electrons would simply move until the force vanishes. We are looking at a conductor in equilibrium...&lt;/p&gt;&#xA;&lt;p&gt;So &lt;span class=&quot;math-container&quot;&gt;$dU$&lt;/span&gt; is zero. And if the difference in potential energy is zero, also the difference in the electrostatic potential is zero, &lt;span class=&quot;math-container&quot;&gt;$dV=0$&lt;/span&gt;, and hence the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is constant at any place on the metal cavity (that is called an &amp;quot;equipotential surface&amp;quot;).&lt;/p&gt;&#xA;" OwnerUserId="1997" LastEditorUserId="7" LastEditDate="2022-04-07T16:58:24.597" LastActivityDate="2022-04-07T16:58:24.597" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8910" PostTypeId="2" ParentId="6564" CreationDate="2022-04-07T22:58:13.700" Score="3" Body="&lt;p&gt;One way to model a multistep complex mechanism is to built a microkinetic model from the rate constants for of all relevant elementary reactions (forward and reverse).&lt;/p&gt;&#xA;&lt;p&gt;For example, for reaction 1 you have&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{H2 + O2 -&amp;gt;[k_1] 2OH}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$k_1(T)$&lt;/span&gt; given by some parameters in a modified Arrhenius expression like &lt;span class=&quot;math-container&quot;&gt;$k(T) = AT^b e^{-E_\mathrm{A}/RT} $&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$k(T) = A(T/T_0)^b e^{-E_\mathrm{A}/RT}$&lt;/span&gt;. It is hard to say which one is used, or if it is some other form, or to be sure of the units without more information.&lt;/p&gt;&#xA;&lt;p&gt;The net reaction rate, &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, can be expressed as the rate of formation of any chosen product of the consumption of any chosen reactant and it is generally a complex function of the rate constants for all of its elementary steps and the thermodynamics of all of its reaction intermediates.&lt;/p&gt;&#xA;&lt;p&gt;For example:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ r = -\frac{d\ce{[H2]}}{dt}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And the concentration of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; is affected by every elementary reaction that produces or consumes it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{d\ce{[H2]}}{dt} = -k_1 \ce{[H2][O2]} + k_{-1}\ce{[OH]^2} - k_2\ce{[OH][H2]} + k_{-2}\ce{[H2O][H]} - k_4\ce{[O][H2]}  + k_{-4}\ce{[OH][H]} + k_{10}\ce{[H]^2[M]} - k_{-10}\ce{[H2][M]} +k_{11}\ce{[H]^2[H2]} - k_{-11}\ce{[H2]^2} + k_{12}\ce{[H]^2[H2O]} - k_{-12}\ce{[H2][H2O]} + k_{16}\ce{[H][HO2]} - k_{-16}\ce{[H2][O2]} + k_{19}\ce{[H][H2O2]} - k_{-19}\ce{[HO2][H2]}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$k_i$&lt;/span&gt; are the rate constant for reaction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k_{-i}$&lt;/span&gt; is the rate for the reverse of &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. Both rate constants are related to each other by the equilibrium constant&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ K_i = \frac{k_i}{k_{-i}} = \exp(-\Delta_\mathrm{rxn}G_i/RT)$$&lt;/span&gt;&#xA;and &lt;span class=&quot;math-container&quot;&gt;$\Delta_\mathrm{rxn}G_i$&lt;/span&gt; is the Gibbs free energy change for reaction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One can integrate the concentrations of all species involved for a given set of initial conditions.&lt;/p&gt;&#xA;&lt;p&gt;To identify which elementary steps in the complex mechanisms are most important to the overall reaction rate one can use the degree of rate control &lt;span class=&quot;math-container&quot;&gt;$X_{\mathrm{RC} i}$&lt;/span&gt; for elementary step &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$X_{\mathrm{RC}, i}=\frac{k_{i}}{r}\left(\frac{\partial r}{\partial k_{i}}\right)_{k_{j \neq i} K_{i}}=\left(\frac{\partial \ln r}{\partial \ln k_{i}}\right)_{k_{j \neq i}, K_{i}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The larger the numeric value of &lt;span class=&quot;math-container&quot;&gt;$X_{\mathrm{RC}, i}$&lt;/span&gt; is for a given step, the bigger is the influence of its rate constant on the overall reaction rate &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Of course that one can do more complicated things such as including the heat and mass transfer across the system.&lt;/p&gt;&#xA;&lt;h2&gt;References&lt;/h2&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;D. A. McQuarrie, Physical chemistry: A molecular approach (University Science Books, Sausalito, CA, 1997).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;C. Stegelmann, A. Andreasen, C. T. Campbell, Degree of rate control: how much the energies of intermediates and transition states control rates. J. Am. Chem. Soc. 131, 8077–8082 (2009).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://kinetics.nist.gov/kinetics/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://kinetics.nist.gov/kinetics/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="878" LastActivityDate="2022-04-07T22:58:13.700" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8911" PostTypeId="1" CreationDate="2022-04-08T09:01:47.607" Score="3" ViewCount="47" Body="&lt;p&gt;I'm totally new to programming and computational chemistry.&#xA;I'm using Vega ZZ as a free software to compute geometry optimization via MM (AMMP) in order to optimize the geometry of the found minima with DFT (ORCA) afterwords.&#xA;My usual geometry optimization process is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Sketching a molecule with the Ketcher editor in Vega ZZ&lt;/li&gt;&#xA;&lt;li&gt;Sending the molecule to Vega ZZ and selecting the desired torsion angles&lt;/li&gt;&#xA;&lt;li&gt;Starting a conformational research (with energy minimization) in AMMP based on the given torsion angles&lt;/li&gt;&#xA;&lt;li&gt;Opening the .dcd file (what i believe is the trajectory file) in Vega with the Analysis function&lt;/li&gt;&#xA;&lt;li&gt;Exporting the iteration/energy vector to Excel in order to sort-out the best iterations (in a 10Kcal/mol energy window, per say)&lt;/li&gt;&#xA;&lt;li&gt;Going back to Vega ZZ and Saving each .xyz file INDIVIDUALLY from the best selected iterations&lt;/li&gt;&#xA;&lt;li&gt;Starting a multijob DFT geometry optimization on ORCA (can do)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The most annoying steps as you can see are 4,5,6. Is there any way to automatize this process?&#xA;Thanks in advance!&lt;/p&gt;&#xA;" OwnerDisplayName="nuniwo" LastActivityDate="2022-04-08T09:39:36.047" Title="Building a script to automatically save .xyz format files from geometry optimization with AMMP in VegaZZ" Tags="|computational-chemistry|molecular-mechanics|" AnswerCount="0" CommentCount="2" ClosedDate="2022-09-07T22:37:19.190" ContentLicense="CC BY-SA 4.0" />
  <row Id="8912" PostTypeId="2" ParentId="8776" CreationDate="2022-04-08T10:10:09.027" Score="6" Body="&lt;p&gt;As others have commented, discretization does not matter.&lt;/p&gt;&#xA;&lt;p&gt;Below you can see a picture that tries to explain this point. The &lt;span class=&quot;math-container&quot;&gt;$\mathrm{d}r$&lt;/span&gt;, or more correctly for the approximation we are making the &lt;span class=&quot;math-container&quot;&gt;$\Delta r$&lt;/span&gt;, is just the distance between the two circles.&lt;/p&gt;&#xA;&lt;p&gt;When you are working on a grid, this simply amounts to counting the number of valid squares with their center in between the two circles.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QsAFm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QsAFm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Script used to generate the figure &lt;a href=&quot;https://github.com/erikkjellgren/Shared_scripts/blob/main/notebooks/rdf_grid.ipynb&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="210" LastActivityDate="2022-04-08T10:10:09.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8913" PostTypeId="1" CreationDate="2022-04-08T16:02:49.613" Score="8" ViewCount="524" Body="&lt;p&gt;Implementations of CCSD(T) are almost too numerous to list, but CCSDT and CCSDT(Q) are much more rare. I have compiled a list of such programs below, and I would be interested to hear if anyone is aware of more.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MRCC: Supports arbitrary order CC and CC() methods.&lt;/li&gt;&#xA;&lt;li&gt;NWchem: Supports CCSDT and CCSDTQ. No CCSDT(Q).&lt;/li&gt;&#xA;&lt;li&gt;CFOUR: Supports CCSDT. CCSDT(Q) and CCSDTQ are &amp;quot;not part of the public release&amp;quot;, whatever that means.&lt;/li&gt;&#xA;&lt;li&gt;CC(t;3) PSI4 Plugin: Can perform CCSDT. No parallelization, AFAIK. Appears to be unmaintained, but still works.&lt;/li&gt;&#xA;&lt;li&gt;GAMESS-US: Can perform CCSDT.&lt;/li&gt;&#xA;&lt;li&gt;Aquarius: Uses the Cyclops Tensor Framework. Can do CCSDT, CCSDT(Q) and CCSDTQ. Lightly documented.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5225" LastEditorUserId="7" LastEditDate="2022-04-10T17:54:49.333" LastActivityDate="2022-04-10T17:54:49.333" Title="List of programs for post-CCSD(T) calculations" Tags="|software|quantum-chemistry|software-recommendations|one-topic-per-answer|coupled-cluster|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8915" PostTypeId="1" AcceptedAnswerId="8916" CreationDate="2022-04-09T13:00:37.263" Score="8" ViewCount="627" Body="&lt;p&gt;A year ago my surface pro's ssd crashed when I ran a optimization job for 40-50 molecules. I am not sure if that is the sole reason or not but the laptop which was working fine for a year or so got damaged that very day. Now I have always been avoiding running DFT calculations from then on my personal hardware.&lt;/p&gt;&#xA;&lt;p&gt;Currently I own a predator helios which is a heavy gaming laptop. Is it possible that this could get damaged if I ran some Optimization and TD-DFT jobs for less than 12-13 atoms?? Obviously there are a lot of variables but some advice from more experienced people is much appreciated!&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2022-04-09T17:13:21.610" Title="Is it possible for my laptop to get damaged when I perform DFT calculations on Small molecules" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8916" PostTypeId="2" ParentId="8915" CreationDate="2022-04-09T17:13:21.610" Score="11" Body="&lt;p&gt;As someone who owns that laptop (or at least in the same model line) I can say that it really should be capable of running at 100% for an extended time.  However, you need to make sure cooling is adequate.  However, the fans in this laptop are at the back not the bottom so it is difficult to block them unless you push it up against a wall.&lt;/p&gt;&#xA;&lt;p&gt;If you have extra concerns, you can always limit the calculation to some percentage of the CPU cores.  Ideally you should get access to a workstation that can handle larger / more intensive calculations but you will be surprised at what's possible even on gaming laptop due to the hardware being much better than the average normal laptop.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-04-09T17:13:21.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8918" PostTypeId="2" ParentId="8913" CreationDate="2022-04-10T13:42:56.320" Score="1" Body="&lt;p&gt;Also ORCA can perform that type of calculation.&#xA;You can check it on &lt;a href=&quot;https://www.orcasoftware.de/tutorials_orca/react/actibar.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-04-10T13:42:56.320" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8920" PostTypeId="1" CreationDate="2022-04-11T07:58:08.907" Score="8" ViewCount="204" Body="&lt;p&gt;I'm attempting to optimize n-alkane dimers using MP2/DFT in Gaussian09. However the first one or two frequencies are always negative. Can these modes be ignored or do I need to do a tighter optimization?&lt;/p&gt;&#xA;" OwnerUserId="5236" LastEditorUserId="7" LastEditDate="2022-04-11T14:11:31.340" LastActivityDate="2022-09-12T17:23:34.277" Title="Optimizing (DFT/MP2) small molecule dimers" Tags="|density-functional-theory|gaussian|optimization|" AnswerCount="1" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="8921" PostTypeId="1" CreationDate="2022-04-11T12:00:52.710" Score="7" ViewCount="762" Body="&lt;p&gt;I have a question related to parameterize Lennard-Jones interaction to get sigma &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and epsilon &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; to include in amber force field to do the Molecular Dynamics.&lt;/p&gt;&#xA;&lt;p&gt;I searched a lot, they always said you should do scan between two atoms and then fit with Lennard-Jones Equation, but they don't explain which atom should I select or depend on what should I select the atoms. I am a bit confused.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I have a complex where I have two transition metals (Ru, Pt), where Ru have 6 bond with Nitrogen and Pt have two bonds with Chloro and two bonds with Nitrogen. I want to get the &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; for both. But I don't understand which distance I should select to do the scan.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone help me to understand this point?&lt;/p&gt;&#xA;&lt;p&gt;Here is the structure.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gKOtC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gKOtC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="4657" LastEditDate="2022-04-12T14:58:10.403" LastActivityDate="2022-04-13T16:08:28.607" Title="Parameterising a Lennard-Jones interaction: Which atoms should I scan to build potential energy surface?" Tags="|molecular-dynamics|computational-chemistry|interatomic-potentials|potential-energy-surface|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8922" PostTypeId="2" ParentId="8921" CreationDate="2022-04-11T12:46:13.210" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I searched a lot, they always said you should do scan between two atoms and then fit with Lennard-Jones Equation, but they don't explain which atom should I select or depend on what should I select the atoms. I am a bit confused.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Normally, pairs of atoms connected by chemical bonds are excluded from computation of non-bonded interactions because bonded energy terms replace non-bonded interactions.&#xA;Also, it is common that in biomolecular force fields all pairs of connected atoms separated by up to 2 bonds (1-2 and 1-3 pairs) are excluded from non-bonded interactions.&#xA;For example, in the image below, only the atoms 1 and 4 are considered for non-bonded interactions &lt;a href=&quot;https://computecanada.github.io/molmodsim-md-theory-lesson-novice/01-Force_Fields_and_Interactions/index.html&quot; rel=&quot;noreferrer&quot;&gt; [1]&lt;/a&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/85l7e.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/85l7e.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;But I don't understand which distance I should select to do the scan.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You create a new system with only the two atoms you want to calculate the interaction energy. You put them apart a fixed distance. Giving the &lt;em&gt;x, y, z&lt;/em&gt; coordinates: you can select for example: &lt;span class=&quot;math-container&quot;&gt;$x_1=0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y_1=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z_1=0$&lt;/span&gt; for the first atom, and &lt;span class=&quot;math-container&quot;&gt;$x_2=d$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y_2=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z_2=0$&lt;/span&gt; for the second one with &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; being the distance between them. You start with &lt;span class=&quot;math-container&quot;&gt;$d=1$&lt;/span&gt;, do a single point energy, then increase &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;, do a single point energy, and so. At the end, you will have the data to plot the energy vs &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; and then do the fitting.&lt;/p&gt;&#xA;&lt;p&gt;Be aware that, if your atoms are not parametrized by the fore field you are interested in, you will need to obtain all the other force fields parameters as well (take a look here).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-04-11T12:46:13.210" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8923" PostTypeId="1" CreationDate="2022-04-12T01:13:59.753" Score="5" ViewCount="112" Body="&lt;p&gt;The anti-symmetric rank-3 and rank-4 tensors hold the following properties:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\sigma_{mnk}  &amp;amp;=-\sigma_{nmk} \\&#xA;\sigma_{mnkp} &amp;amp;=-\sigma_{nmkp}&#xA;\end{align}&lt;/span&gt;&#xA;Note I'm using antisymmetric to mean at least antisymmetric in the first two indices, rather than necessarily having all indices be antisymmetric.&lt;/p&gt;&#xA;&lt;p&gt;Are there examples of physical properties that correspond to antisymmetric rank-3 and rank-4 tensors?&#xA;And what about the symmetric rank-3 and rank-4 physical tensors?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2022-04-12T20:25:48.093" LastActivityDate="2022-11-06T23:54:49.873" Title="Examples of anti-symmetric rank-3/4 tensors?" Tags="|symmetry|physical-properties-of-materials|response-theory|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8924" PostTypeId="2" ParentId="8921" CreationDate="2022-04-12T03:20:18.187" Score="5" Body="&lt;p&gt;You linked to &lt;a href=&quot;https://chemistry.stackexchange.com/a/127823/5017&quot;&gt;my answer&lt;/a&gt;  about parameterizing force fields. For reference, this isn't my area of expertise, although a colleague's group does this frequently.&lt;/p&gt;&#xA;&lt;p&gt;My understanding of your question is that you want to get the non-bonded interactions between the Ru and Pt atoms in the larger complex.&lt;/p&gt;&#xA;&lt;p&gt;What you describe is going to be tricky, even with automated force field methods like I described on Chem.SE.&lt;/p&gt;&#xA;&lt;p&gt;In your case, you don't have neutral metal ions - you have transition metals with a surrounding ligand sphere.&lt;/p&gt;&#xA;&lt;p&gt;Ordinarily, you'd pick the relevant elements, maybe start from the initial distance between them, scan closer and scan farther until you see a full minima. (You want at least parts of the repulsive and attractive regions to fit the potential energy curve.)&lt;/p&gt;&#xA;&lt;p&gt;For metals, it's more complicated. There are a few approaches.&lt;/p&gt;&#xA;&lt;p&gt;I'd probably go with the &amp;quot;dummy atom&amp;quot; method - you surround the metal ions (Ru and Pt in your case) with partially charged dummy atoms, so the net charge is identical, but the ion is properly surrounded with the right coordination environment and has some charge delocalization.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ACH9Et.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ACH9Et.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A fairly readable article is &lt;a href=&quot;https://doi.org/10.1021/jp501737x&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Force Field Independent Metal Parameters Using a Nonbonded Dummy Model&amp;quot;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So you'd add some dummy atoms to the Ru and Pt at the positions relevant in the complex (e.g., remove the carbon atoms and hydrogen around both, then change the nitrogen atoms around the Ru to dummy (Du) and the two nitrogen and two chlorine atoms around the Pt atom.&lt;/p&gt;&#xA;&lt;p&gt;Then map the curve .. again starting near the distance in the complex, going shorter and longer until you've mapped out the LJ curve.&lt;/p&gt;&#xA;&lt;p&gt;Since it looks like you're using Avogadro, you can use the &amp;quot;Align&amp;quot; tool, click on the Ru atom to make that the origin, then the Pt atom to make that along one of the axes (e.g, x-axis). Then you can select the Pt+dummy &amp;quot;molecule&amp;quot; and use the manipulate tool to translate it forward and backwards.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nmDXO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nmDXO.png&quot; alt=&quot;Moving two water molecules closer along the x-axis&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Merz also has a series of articles talking about the development of parameters for water models (TIP3P, etc.). These are probably less relevant to your needs, but discuss some of the challenges.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/ct400146w&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Rational Design of Particle Mesh Ewald Compatible Lennard-Jones Parameters for +2 Metal Cations in Explicit Solvent&amp;quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/jp505875v&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Parameterization of Highly Charged Metal Ions Using the 12-6-4 LJ-Type Nonbonded Model in Explicit Water&amp;quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I'm probably leaving off relevant papers.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2022-04-13T16:08:28.607" LastActivityDate="2022-04-13T16:08:28.607" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8925" PostTypeId="2" ParentId="8800" CreationDate="2022-04-12T19:41:36.297" Score="1" Body="&lt;p&gt;In my group we develop continuous symmetry and chirality measures that can be used to quantify the distortion of a structure, given the 3D coordinates.&lt;/p&gt;&#xA;&lt;p&gt;Please see: &lt;a href=&quot;https://csm.ouproj.org.il/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://csm.ouproj.org.il/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;See also a related method to calculate continuous shape measures by S. Alvarez and coworkers:&#xA;&lt;a href=&quot;http://www.ee.ub.edu/index.php?option=com_content&amp;amp;view=article&amp;amp;id=72&amp;amp;Itemid=469&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.ee.ub.edu/index.php?option=com_content&amp;amp;view=article&amp;amp;id=72&amp;amp;Itemid=469&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5240" LastActivityDate="2022-04-12T19:41:36.297" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8927" PostTypeId="2" ParentId="8874" CreationDate="2022-04-12T20:38:31.440" Score="7" Body="&lt;p&gt;Try &lt;code&gt;AseAtomsAdaptor.get_structure&lt;/code&gt; method from &lt;a href=&quot;https://github.com/materialsproject/pymatgen/blob/master/pymatgen/io/ase.py&quot; rel=&quot;noreferrer&quot;&gt;pymatgen.io.ase&lt;/a&gt;, it actually serves exactly this purpose.&lt;/p&gt;&#xA;" OwnerUserId="1750" LastActivityDate="2022-04-12T20:38:31.440" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8928" PostTypeId="2" ParentId="8873" CreationDate="2022-04-12T20:57:10.033" Score="1" Body="&lt;p&gt;You can build your nanotube with the recent versions of the &lt;a href=&quot;https://www.crystal.unito.it&quot; rel=&quot;nofollow noreferrer&quot;&gt;CRYSTAL&lt;/a&gt; code (see &lt;a href=&quot;http://tutorials.crystalsolutions.eu/tutorial.html?td=nanotube&amp;amp;tf=nanotube&quot; rel=&quot;nofollow noreferrer&quot;&gt;their tutorial&lt;/a&gt;). Using the &lt;a href=&quot;https://github.com/tilde-lab/pycrystal&quot; rel=&quot;nofollow noreferrer&quot;&gt;pycrystal&lt;/a&gt; Python library you then extract an &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE Atoms object&lt;/a&gt; and &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/io/lammpsdata.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;convert it&lt;/a&gt; into the LAMMPS input format.&lt;/p&gt;&#xA;" OwnerUserId="1750" LastActivityDate="2022-04-12T20:57:10.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8929" PostTypeId="2" ParentId="8868" CreationDate="2022-04-12T21:22:08.750" Score="3" Body="&lt;p&gt;Yes, have a look at the &lt;a href=&quot;https://openkim.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;Open KIM&lt;/a&gt; platform. It &lt;a href=&quot;https://www.google.com/search?q=lammps%20site%3Aopenkim.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;supports&lt;/a&gt; LAMMPS potentials.&lt;/p&gt;&#xA;" OwnerUserId="1750" LastActivityDate="2022-04-12T21:22:08.750" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8930" PostTypeId="1" AcceptedAnswerId="8931" CreationDate="2022-04-13T10:16:58.763" Score="10" ViewCount="637" Body="&lt;p&gt;I have been using molecular fingerprints like ECFP (extended connectivity fingerprint), APFP (atom-pair fingerprint) etc. in my research to predict spectral properties of organic molecules with machine learning (basically a QSAR project). Now, I have got very good results from the machine learning models, but I want to understand what exactly the model is learning i.e. some kind of interpretable chemical information which can be understood by an organic chemist for example.&lt;/p&gt;&#xA;&lt;p&gt;However, I am not sure how to do that, because from the trained model, all I can possibly get are importances or effects of each position of the fingerprint. But then I am lost because fingerprints like ECFP are &lt;strong&gt;hashed&lt;/strong&gt; fingerprints, so I do not know what the number in each position actually means. &lt;strong&gt;Is there any way to link hashed fingerprints to some chemical structure or feature that is easy to understand?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I only found &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2020/sc/d0sc03115a&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one paper&lt;/a&gt; that attempts to reverse-engineer ECFP with neural networks, but I am looking for something simpler.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2022-07-07T14:00:57.863" LastActivityDate="2022-07-28T16:33:08.960" Title="Getting interpretable chemical information from hashed molecular fingerprints" Tags="|machine-learning|cheminformatics|qsar|fingerprint|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8931" PostTypeId="2" ParentId="8930" CreationDate="2022-04-13T16:30:18.237" Score="12" Body="&lt;p&gt;Using RDKit, it's fairly easy to depict bits on example molecules - it's even an example in the &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#generating-images-of-fingerprint-bits&quot; rel=&quot;noreferrer&quot;&gt;documentation &amp;quot;Generating Images of Fingerprint Bits&amp;quot;&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import Draw&#xA;mol = Chem.MolFromSmiles('c1ccccc1CC1CC1')&#xA;bi = {}&#xA;fp = AllChem.GetMorganFingerprintAsBitVect(mol, radius=2, bitInfo=bi)&#xA;bi[872]&#xA;((6, 2),)&#xA;mfp2_svg = Draw.DrawMorganBit(mol, 872, bi, useSVG=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To quote the documentation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The default highlight colors for the Morgan bits indicate:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;blue: the central atom in the environment&lt;/li&gt;&#xA;&lt;li&gt;yellow: aromatic atoms&lt;/li&gt;&#xA;&lt;li&gt;gray: aliphatic ring atoms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As an example from the &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#generating-images-of-fingerprint-bits&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KINiKt.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KINiKt.png&quot; alt=&quot;Morgan depiction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2022-04-13T21:35:07.857" LastActivityDate="2022-04-13T21:35:07.857" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="8932" PostTypeId="1" CreationDate="2022-04-14T07:55:17.137" Score="7" ViewCount="1631" Body="&lt;p&gt;can anyone give me some list recommendations of software or open source that can generate potential&lt;/p&gt;&#xA;" OwnerUserId="5119" LastEditorUserId="5279" LastEditDate="2022-04-21T13:55:10.870" LastActivityDate="2022-11-30T17:09:09.590" Title="What are some open-source codes that can generate potentials?" Tags="|lammps|interatomic-potentials|" AnswerCount="4" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8933" PostTypeId="2" ParentId="8932" CreationDate="2022-04-14T09:14:29.903" Score="8" Body="&lt;p&gt;&lt;em&gt;&lt;strong&gt;My answer is based on &lt;em&gt;Lammps&lt;/em&gt;&lt;/strong&gt;&lt;/em&gt;&lt;br /&gt;&#xA;Creating interatomic-potential which predicts every property of different phase is a nightmare job. There are few database which is already available for inter-atomic potential where people have contributed their work.&lt;br /&gt;&#xA;&lt;strong&gt;Step 1:&lt;/strong&gt;&lt;br /&gt;&#xA;kindly check these website before you put your effort in creating new potential.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://openkim.org/&quot; rel=&quot;noreferrer&quot;&gt;https://openkim.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ctcms.nist.gov/potentials&quot; rel=&quot;noreferrer&quot;&gt;https://www.ctcms.nist.gov/potentials&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://sites.google.com/site/eampotentials/Home&quot; rel=&quot;noreferrer&quot;&gt;https://sites.google.com/site/eampotentials/Home&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Even lammps package contain so many well tested inter atomic-potentials&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 2:&lt;/strong&gt;&lt;br /&gt;&#xA;If step 1 is not helpful, find literature where people have tested your system for different property or created new potential. Potentials can be hybrid as well. If you find new interatomic potential which is already published, Best idea to mail the author and most of the time author provides new inter-atomic potentials. If not you can fit those parameters in software to generate potential files &lt;br /&gt;&#xA;for fitting check &lt;a href=&quot;https://atsimpotentials.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;https://atsimpotentials.readthedocs.io/en/latest/&lt;/a&gt; &lt;br /&gt;&#xA;&lt;strong&gt;Step 3:&lt;/strong&gt;&lt;br /&gt;&#xA;If someone really want to break the shackle, you need four thing,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Target value corresponding to property of system&lt;/li&gt;&#xA;&lt;li&gt;functional form of potential&lt;/li&gt;&#xA;&lt;li&gt;Engine like lammps which will run again and again with different potential parameters.&lt;/li&gt;&#xA;&lt;li&gt;Multi-objective optimization tool. There are several evolutionary algorithm like genetic-algorithm can optimize your unknown coefficient.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;some package which can be used to create your new potential&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/costrouc/dftfit&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/costrouc/dftfit&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.atomicrex.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.atomicrex.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/qzhu2017/PyXtal_FF&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/qzhu2017/PyXtal_FF&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/deepmodeling/deepmd-kit&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/deepmodeling/deepmd-kit&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;http://cpc.cs.qub.ac.uk/summaries/AEWY_v1_0.html&quot; rel=&quot;noreferrer&quot;&gt;http://cpc.cs.qub.ac.uk/summaries/AEWY_v1_0.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/ranndip/project_page&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/ranndip/project_page&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/openkim/kliff&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/openkim/kliff&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/MDIL-SNU/SIMPLE-NN&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/MDIL-SNU/SIMPLE-NN&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/sabernaserifar/Force-Field-Optimizer&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/sabernaserifar/Force-Field-Optimizer&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/knc6/JARVIS-FF&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/knc6/JARVIS-FF&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/BenPalmer1983/eampa_v3&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/BenPalmer1983/eampa_v3&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Many other tools are also available which can be used to fit either DFT data or output of experiment/DFT.&lt;/p&gt;&#xA;&lt;p&gt;-&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-04-14T11:39:46.167" LastActivityDate="2022-04-14T11:39:46.167" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8934" PostTypeId="2" ParentId="8874" CreationDate="2022-04-14T10:14:51.563" Score="1" Body="&lt;p&gt;This is how I wound up getting things working.&lt;/p&gt;&#xA;&lt;p&gt;I saved atom as xyz:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atoms = row.toatoms()&#xA;atoms.write(f&amp;quot;./{dir_}/{i}_{str(atoms.symbols)}.xyz&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, I opened the xyz in pymatgen:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Molecule&#xA;structures = [Molecule.from_file(train_path &#xA;               + '/' + file) for file in train_files]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4910" LastEditorUserId="7" LastEditDate="2022-04-15T16:35:53.767" LastActivityDate="2022-04-15T16:35:53.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8935" PostTypeId="1" CreationDate="2022-04-15T08:07:46.570" Score="2" ViewCount="231" Body="&lt;p&gt;I am getting the following error&lt;/p&gt;&#xA;&lt;p&gt;error in routine phq_readin (1):&#xA;reading xq&lt;/p&gt;&#xA;&lt;p&gt;I don't understand what is this error about.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2022-04-15T08:07:46.570" Title="Phonon dispersion calculation error" Tags="|quantum-espresso|phonon-dispersion|" AnswerCount="0" CommentCount="4" ClosedDate="2022-10-28T13:42:04.280" ContentLicense="CC BY-SA 4.0" />
  <row Id="8938" PostTypeId="1" CreationDate="2022-04-15T23:54:49.570" Score="3" ViewCount="393" Body="&lt;p&gt;I am trying to learn the BSE GW calculations in VASP. Using the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Dielectric_properties_of_Si_using_BSE&quot; rel=&quot;nofollow noreferrer&quot;&gt;procedure&lt;/a&gt; described on the VASP website.&lt;/p&gt;&#xA;&lt;p&gt;I am stuck at the last step 5 (BSE calculation). I didn't get any error in the 5th step but calculations are not proceeding. Here I am adding the tail of output corresponding to 5th step:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LDA part: xc-table for Pade appr. of Perdew\&#xA;found WAVECAR, reading the header\&#xA;POSCAR, INCAR and KPOINTS ok, starting setup\&#xA;WARNING: small aliasing (wrap around) errors must be expected\&#xA;FFT: planning ...\&#xA; reading WAVECAR\&#xA; the WAVECAR file was read sucessfully\&#xA; initial charge from wavefunction\&#xA; the WAVEDER file was read successfully\&#xA;energies w=\&#xA;&#xA; responsefunction array rank= 176\&#xA; allocating   0 responsefunctions rank=   176\&#xA; allocating   0 responsefunctions rank=   176\&#xA; Doing            0  frequencies in blocks of            0\&#xA; allocating two-electron 4 orbital integral table   4   8   4   8\&#xA; BSE (scaLAPACK) single prec attempting allocation of   0.019 Gbyte  rank=   6170\&#xA; BSE setting up matrix\&#xA; reading now WFULL0001.tmp\&#xA; reading now WFULL0003.tmp\&#xA; reading now WFULL0006.tmp\&#xA; reading now WFULL0008.tmp\&#xA; reading now WFULL0011.tmp\&#xA; reading now WFULL0012.tmp\&#xA; reading now WFULL0007.tmp\&#xA; reading now WFULL0015.tmp\&#xA;| reading now WFULL0005.tmp\&#xA; reading now WFULL0014.tmp\&#xA; reading now WFULL0016.tmp\&#xA; reading now WFULL0009.tmp\&#xA; reading now WFULL0002.tmp\&#xA; reading now WFULL0004.tmp\&#xA;.reading now WFULL0010.tmp\&#xA;........|......... BSE redistributing all elements\&#xA;&#xA; BSE diagonalizing matrix (scaLAPACKaware)\&#xA; BSE calculating oscillator strength\&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After this, calculations are not proceeding. I tried with some other settings as well and tried many attempts but nothing works out. If someone is familiar with these calculations, please suggest.&lt;/p&gt;&#xA;" OwnerUserId="5256" LastEditorUserId="7" LastEditDate="2022-04-16T13:12:16.603" LastActivityDate="2022-04-16T13:12:16.603" Title="Problem while performing the BSE GW calculations in VASP" Tags="|vasp|gw-bse|" AnswerCount="0" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="8939" PostTypeId="1" CreationDate="2022-04-16T00:15:36.090" Score="2" ViewCount="45" Body="&lt;p&gt;If I have a system of two &amp;quot;non-interacting electrons&amp;quot; and I want to mimic its density using another non-interacting system (KS system). Would the KS potential contain the exchange potential?&lt;/p&gt;&#xA;" OwnerUserId="5257" LastActivityDate="2022-04-16T00:15:36.090" Title="Exchange potential for a non-interacting system" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="2" ClosedDate="2022-11-04T15:54:35.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="8941" PostTypeId="1" CreationDate="2022-04-16T14:18:21.227" Score="4" ViewCount="122" Body="&lt;p&gt;I built a force field for a complex. How can I check if the force field is working well or no?&lt;/p&gt;&#xA;&lt;p&gt;I did a short molecular dynamics using AMBER only for the complex using the parameters I built. It worked well, but what can I do more ?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2022-10-27T09:05:32.010" Title="How can we test the force field (parameter) for a complex?" Tags="|molecular-dynamics|computational-chemistry|forcefields|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="8942" PostTypeId="1" CreationDate="2022-04-16T20:53:01.423" Score="5" ViewCount="416" Body="&lt;p&gt;So I have a list of molecules. They all have a common substructure, but different substitution patterns.&lt;/p&gt;&#xA;&lt;p&gt;For example, in the figure below, the leftmost molecule is the base, and the center and rightmost molecules are both a (1,4)-substituted variants of the base.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PmlLF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PmlLF.png&quot; alt=&quot;base molecule (left) and substituted variants (center/right)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Because the different substitution patterns result in a different numbering of the atoms, identifying the substitution locations is very difficult. Using the method &lt;code&gt;mol.HasSubstructureMatch(some_substituition)&lt;/code&gt;, I can find the location of the substitution, but since the base pattern keeps changing, this location is meaningless for my purposes (e.g. center molecule is (4,16)-substituted, and the rightmost molecule is (4,13)-substituted)&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to modify the substituted molecules such that the base substructure always has a consistent numbering pattern (e.g. make it so both molecules above are (4,12)-substituted)? Any ideas on how to systematically identify the substitution pattern would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="5281" OwnerDisplayName="guest" LastEditorUserId="7" LastEditDate="2022-04-17T14:09:00.397" LastActivityDate="2022-04-19T20:19:23.917" Title="How do you determine substitution patterns using RDKit?" Tags="|computational-chemistry|rdkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8943" PostTypeId="1" CreationDate="2022-04-17T18:53:21.360" Score="4" ViewCount="71" Body="&lt;p&gt;I know one book -&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Molecular Simulation of Fluids Theory, Algorithms, and Object-Orientation; Richard J. Sadus.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This book supplies source code. However, it is not targeted at polymers or biomolecules.&lt;/p&gt;&#xA;&lt;p&gt;Can you recommend a better book?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="142" LastEditDate="2022-04-18T17:42:52.750" LastActivityDate="2022-04-18T17:42:52.750" Title="Can you recommend a molecular modeling book targeted at polymers or biomolecules that supplies programming examples?" Tags="|reference-request|" AnswerCount="0" CommentCount="4" ClosedDate="2022-11-17T14:11:48.727" ContentLicense="CC BY-SA 4.0" />
  <row Id="8944" PostTypeId="1" CreationDate="2022-04-18T03:00:37.357" Score="5" ViewCount="416" Body="&lt;p&gt;Using collinear spin-flip(SF) TD-DFT with the Tamm-Dancoff approximation, BHanHLYP and a simple test molecule (ethene, with a singlet ground state).&lt;/p&gt;&#xA;&lt;p&gt;It's my understanding, using ethene as an example, that spin-flip DFT starts with a unrestricted Kohn-Sham single-reference triplet reference state, then generates the other TD-DFT 'excited' states using the MOs and occupancies from that reference state and a calculated excitation vector. The relative &lt;em&gt;energy&lt;/em&gt; of the ground state can be calculated, and, at least in ORCA, the molecular geometry can be optimized on this ground-state PES. So far, so good.&lt;/p&gt;&#xA;&lt;p&gt;My question is: can the wavefunction of the resulting singlet SF &lt;em&gt;ground&lt;/em&gt; state, which appears as an effective negative-energy 'excited' state, have its electron density distribution represented (and written in machine-readable form), as another set of &lt;em&gt;only&lt;/em&gt; MOs and occupancies?&lt;/p&gt;&#xA;&lt;p&gt;It doesn't matter if this output set is single-reference or multi-reference, for my purposes, just so long as it can be output as &lt;em&gt;only&lt;/em&gt; MOs and occupations.&lt;/p&gt;&#xA;&lt;p&gt;If this is implementation-dependent, which codes implementing spin-flip TD-DFT can do this? Does the Tamm-Dancoff approximation need to be dropped in order to achieve this?&lt;/p&gt;&#xA;" OwnerUserId="577" LastEditorUserId="577" LastEditDate="2022-04-18T03:11:24.717" LastActivityDate="2022-04-18T21:43:54.217" Title="Can a spin-flip TD-DFT singlet ground state wavefunction be written as a sum over MOs with occupancy information?" Tags="|td-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8945" PostTypeId="1" AcceptedAnswerId="8946" CreationDate="2022-04-18T07:32:12.890" Score="4" ViewCount="384" Body="&lt;p&gt;For &lt;a href=&quot;https://www.basissetexchange.org/basis/sto-3g/format/nwchem/?version=1&amp;amp;elements=3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lithium STO-3G&lt;/a&gt; basis set&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;BASIS &amp;quot;ao basis&amp;quot; PRINT&#xA;#BASIS SET: (6s,3p) -&amp;gt; [2s,1p]&#xA;Li    S&#xA;      0.1611957475E+02       0.1543289673E+00&#xA;      0.2936200663E+01       0.5353281423E+00&#xA;      0.7946504870E+00       0.4446345422E+00&#xA;Li    SP&#xA;      0.6362897469E+00      -0.9996722919E-01       0.1559162750E+00&#xA;      0.1478600533E+00       0.3995128261E+00       0.6076837186E+00&#xA;      0.4808867840E-01       0.7001154689E+00       0.3919573931E+00&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I see the for representing Lithium wave function (Single Slater's Determitatn) I need 3 basis STO-functions (STO(1s), STO(2s) and one STO(2p)) for compilation spin-orbitals. For Lithium we have &lt;span class=&quot;math-container&quot;&gt;$1s^22s$&lt;/span&gt;-eclectronic structure, so I need compile:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\chi_{1s} = \sum\limits_{j = 1}^{K} C_{(1s)_j} STO_j,\\&#xA;\phi_{1s} = \sum\limits_{j = 1}^{L} D_{(1s)_j} STO_j,\\&#xA;\chi_{2s} = \sum\limits_{j = 1}^{M} C_{(2s)_j} STO_j.\\&#xA;\ldots.&#xA;\end{align}&lt;/span&gt;&#xA;(As I understand)&lt;/p&gt;&#xA;&lt;p&gt;So, I started to calculate with ORCA Lithium atom&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! UHF STO-3G&#xA;   &#xA;%coords&#xA;    CTyp xyz       # the type of coordinates = xyz or internal&#xA;    Charge 0       # the total charge of the molecule&#xA;    Mult 2         # the multiplicity = 2S+1&#xA;    Units Angs     # the unit of length = angs or bohrs&#xA;    coords&#xA;        Li        0.000000       0.00000        0.00000&#xA;    end&#xA;end&#xA;%output&#xA;    Print[ P_Basis ] 2&#xA;    Print[ P_MOs ] 1&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and get information&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;------------------&#xA;MOLECULAR ORBITALS&#xA;------------------&#xA;                      0         1         2         3         4   &#xA;                  -2.36917  -0.18012   0.13013   0.13013   0.13013&#xA;                   1.00000   1.00000   0.00000   0.00000   0.00000&#xA;                  --------  --------  --------  --------  --------&#xA;  0Li  1s         0.992528 -0.276813  0.000000  0.000000 -0.000000&#xA;  0Li  2s         0.029310  1.029989 -0.000000 -0.000000  0.000000&#xA;  0Li  1pz       -0.000000  0.000000 -0.607531  0.786960 -0.107701&#xA;  0Li  1px       -0.000000  0.000000 -0.176173 -0.265720 -0.947816&#xA;  0Li  1py       -0.000000  0.000000  0.774512  0.556854 -0.300075&#xA;&#xA;                      0         1         2         3         4   &#xA;                  -2.33786   0.10225   0.19092   0.19092   0.19092&#xA;                   1.00000   0.00000   0.00000   0.00000   0.00000&#xA;                  --------  --------  --------  --------  --------&#xA;  0Li  1s         0.991218 -0.281468  0.000000  0.000000  0.000000&#xA;  0Li  2s         0.034144  1.029840 -0.000000 -0.000000 -0.000000&#xA;  0Li  1pz       -0.000000 -0.000000  0.170191 -0.976799  0.129992&#xA;  0Li  1px       -0.000000 -0.000000 -0.983678 -0.160587  0.081175&#xA;  0Li  1py       -0.000000 -0.000000 -0.058416 -0.141685 -0.98818&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, how can I determine &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; numbers and &lt;span class=&quot;math-container&quot;&gt;$C_{(1s)_j}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$D_{(1s)_j}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_{(2s)_j}$&lt;/span&gt; coefitients?&lt;/p&gt;&#xA;" OwnerUserId="5264" LastActivityDate="2022-04-18T08:22:11.243" Title="ORCA: meaning of numbers in ORCA.out of MOLECULAR ORBITALS for STO-3G Lithium" Tags="|quantum-chemistry|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8946" PostTypeId="2" ParentId="8945" CreationDate="2022-04-18T08:22:11.243" Score="4" Body="&lt;p&gt;Firstly, note that the STO-3G basis set are not STOs, but approximations of STOs by the linear combination of three Gaussians.&lt;/p&gt;&#xA;&lt;p&gt;In your case, you have 5 STO functions, of which two are s basis functions and three are p basis functions. Since p functions have zero contribution to the 1s and 2s orbitals, you may write &lt;span class=&quot;math-container&quot;&gt;$K=L=M=2$&lt;/span&gt;, or if you count zero coefficients as coefficients as well, you can write &lt;span class=&quot;math-container&quot;&gt;$K=L=M=5$&lt;/span&gt; instead. The MO coefficients are read from the columns of the ORCA printout, but note that the 1s and 2s in the ORCA output file denote the first and second s functions, respectively, not the 1s and 2s orbitals (you may also notice this fact by observing that there are &amp;quot;1p&amp;quot; entries, which obviously can only refer to basis functions, not molecular orbitals). Keeping this in mind, you can read off the required coefficients as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C_{(1s)_1} = 0.992528, C_{(1s)_2} = 0.029310&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{(1s)_1} = 0.991218, D_{(1s)_2} = 0.034144&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;C_{(2s)_1} = -0.276813, C_{(2s)_2} = 1.029989&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that to actually use these coefficients, you have to use normalized basis functions instead of unnormalized ones.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-04-18T08:22:11.243" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8947" PostTypeId="2" ParentId="8944" CreationDate="2022-04-18T10:12:51.427" Score="4" Body="&lt;p&gt;What you are looking for are the natural orbitals of the spin-flip ground state wavefunction. As a matter of fact, the one-electron density matrix from any electronic wavefunction, no matter whether it is multireferential or whether it is an excited state wavefunction, can be written as a linear combination of contributions of natural orbitals (NOs):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D = \sum_i n_i |\psi_i\rangle \langle\psi_i| \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Given the one-electron density matrix in an orthogonal basis, one can find the NOs and the corresponding occupation numbers by diagonalizing the density matrix. If the density matrix is only available in a non-orthogonal basis (such as the AO basis), one can transform it to an orthogonal AO basis (via either Schmidt orthogonalization or symmetric orthogonalization. EDIT: other more robust orthogonalization methods also exist, see Susi's comment below), diagonalize the density matrix, and transform the NO coefficients back to the AO basis. The density matrix does not contain all the information in the wavefunction, but it contains sufficient information for determining the electronic density.&lt;/p&gt;&#xA;&lt;p&gt;Any decent program that supports SF-TDDFT or SF-TDA can generate the natural transition orbitals (NTOs) or difference density matrices of the spin-flip states (both the ground state and the excited states), or both; the former can be transformed to the latter by plugging the NTOs and their occupation numbers into Eq. (1). To get the NOs of a spin-flip state, one must add the difference density matrix to the density matrix of the reference state to get the density matrix of the spin-flip state. Diagonalizing this density matrix yields the NOs and their occupation numbers. Depending on the computational chemistry software that you use, there is a good chance that some or all of these post-processing steps can be done by Multiwfn.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-04-18T21:43:54.217" LastActivityDate="2022-04-18T21:43:54.217" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8948" PostTypeId="1" AcceptedAnswerId="8950" CreationDate="2022-04-18T17:27:04.623" Score="1" ViewCount="203" Body="&lt;p&gt;I have an output from induced fit docking (IFD) in Maestro.&#xA;I want to calculate the MM-GBSA for the output obtained from IFD in Maestro (Schrodinger) for which poseviewer file (.pv.maegz) is required.&#xA;Can someone tell me how to export/convert .maegz file in .pv.maegz format.&#xA;Or, how can I split my complex in ligand and receptor files.&#xA;I tried using the schrodinger script for the conversion but that did not work.&lt;/p&gt;&#xA;&lt;p&gt;Any help would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance,&lt;/p&gt;&#xA;" OwnerUserId="5252" LastActivityDate="2022-04-18T18:48:27.037" Title="Exporting IFD output to poseviewer file" Tags="|docking|schrodinger-software|energy|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8949" PostTypeId="2" ParentId="8932" CreationDate="2022-04-18T17:41:27.640" Score="3" Body="&lt;p&gt;If you want to calculate potential data &lt;span class=&quot;math-container&quot;&gt;$V(\{{\bf R}_i\})$&lt;/span&gt; with &lt;em&gt;ab initio&lt;/em&gt; methods to fit to some analytical form, you can find a recent listing of free and open source electronic structure codes in our open access review article in WIREs Computational Molecular Science, &lt;a href=&quot;https://doi.org/10.1002/wcms.1610&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1002/wcms.1610&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The codes are classified by the employed approach:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Programs for molecular calculations with Gaussian basis sets, Section 3.1&lt;/li&gt;&#xA;&lt;li&gt;Programs for solid-state calculations with various numerical approaches, Section 3.2&lt;/li&gt;&#xA;&lt;li&gt;Programs employing fully numerical methods, Section 3.3&lt;/li&gt;&#xA;&lt;li&gt;Programs employing semiempirical methods, Section 3.4&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Gaussian-basis calculations afford all-electron calculations, post-Hartree-Fock calculations as well as analytical integrals, which simplifies the calculation of higher-order derivatives like geometric Hessians.&lt;/p&gt;&#xA;&lt;p&gt;Solid-state codes tend to employ pseudopotentials and DFT, that is, only the valence electrons are explicitly modeled.&lt;/p&gt;&#xA;&lt;p&gt;Modern fully numerical methods can perform all-electron calculations and yield very high precision, although the level of theory is often limited.&lt;/p&gt;&#xA;&lt;p&gt;Semiempirical methods can be really fast, and force field type models like &lt;a href=&quot;https://doi.org/10.1002/anie.202004239&quot; rel=&quot;nofollow noreferrer&quot;&gt;GFN-FF&lt;/a&gt; have also been proposed recently; these methods can easily handle systems with thousands of atoms.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-04-18T17:41:27.640" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8950" PostTypeId="2" ParentId="8948" CreationDate="2022-04-18T18:48:27.037" Score="1" Body="&lt;p&gt;From the Knowledge Base &lt;a href=&quot;https://www.schrodinger.com/kb/1568?original_search=GBSA&quot; rel=&quot;nofollow noreferrer&quot;&gt;post&lt;/a&gt; in the Schrodinger site:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;How do I run Prime MM-GBSA on a complex in a Maestro file from the command line?&lt;/p&gt;&#xA;&lt;p&gt;The command to use for Prime MM-GBSA is:&lt;/p&gt;&#xA;&lt;p&gt;\$SCHRODINGER/prime_mmgbsa [options] structure_file.mae[gz]&lt;/p&gt;&#xA;&lt;p&gt;Run with -h to see all options.   Note the -ligand option that will allow you to specify the part of the input complex that should be considered as the ligand for the MM-GBSA calculation&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Alternatively, the complex file can be converted to a poseviewer file before running the job. You can generate the pose viewer file by importing the complex to Maestro, splitting the entry into receptor and ligand and then exporting again. There is also a script that you can run from the command line, pv_convert.py.&lt;/strong&gt; Use the following command to see usage and options:&lt;/p&gt;&#xA;&lt;p&gt;$SCHRODINGER/run pv_convert.py -h&lt;/p&gt;&#xA;&lt;p&gt;Use the -mode split_pv option.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-04-18T18:48:27.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8951" PostTypeId="1" CreationDate="2022-04-19T05:15:07.880" Score="3" ViewCount="498" Body="&lt;p&gt;The problem that I face is the ASE software can't read the trajectory file and throws this error &lt;code&gt;ValueError: buffer is smaller than requested size&lt;/code&gt;. My assumption is that it can be ascribed to the big file size of the &lt;code&gt;nve_traj&lt;/code&gt; (~500MB).&lt;/p&gt;&#xA;&lt;p&gt;I checked that the indexing method worked previously with smaller size file. Also, I get the same error when I truly to visualise the file in the ASE-GUI.&#xA;Incase someone ask why I need to index the file, &lt;code&gt;m = traj.get_masses() &lt;/code&gt;.&#xA;I would be grateful if someone can give a working solution to either the ValueError or suggest a method to get masses from the trajectory.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;from ase.io.trajectory import Trajectory&#xA;&#xA;traj  = ase.io.read('nve.traj', index=':', format='traj')&#xA;&#xA;# to replace the some atoms e.g. H&#xA;m = traj.get_masses()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As suggested the whole error,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ValueError                                Traceback (most recent call last)&#xA;Input In [4], in &amp;lt;cell line: 1&amp;gt;()&#xA;----&amp;gt; 1 traj = ase.io.read('md.traj', index= &amp;quot;-1&amp;quot;)&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\formats.py:736, in read(filename, index, format, parallel, do_not_split_by_at_sign, **kwargs)&#xA;    733     return list(_iread(filename, index, format, io, parallel=parallel,&#xA;    734                        **kwargs))&#xA;    735 else:&#xA;--&amp;gt; 736     return next(_iread(filename, slice(index, None), format, io,&#xA;    737                        parallel=parallel, **kwargs))&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\parallel.py:275, in parallel_generator.&amp;lt;locals&amp;gt;.new_generator(*args, **kwargs)&#xA;    269 @functools.wraps(generator)&#xA;    270 def new_generator(*args, **kwargs):&#xA;    271     if (world.size == 1 or&#xA;    272         args and getattr(args[0], 'serial', False) or&#xA;    273         not kwargs.pop('parallel', True)):&#xA;    274         # Disable:&#xA;--&amp;gt; 275         for result in generator(*args, **kwargs):&#xA;    276             yield result&#xA;    277         return&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\formats.py:803, in _iread(filename, index, format, io, parallel, full_output, **kwargs)&#xA;    801 # Make sure fd is closed in case loop doesn't finish:&#xA;    802 try:&#xA;--&amp;gt; 803     for dct in io.read(fd, *args, **kwargs):&#xA;    804         if not isinstance(dct, dict):&#xA;    805             dct = {'atoms': dct}&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\trajectory.py:406, in read_traj(fd, index)&#xA;    404 trj = TrajectoryReader(fd)&#xA;    405 for i in range(*index.indices(len(trj))):&#xA;--&amp;gt; 406     yield trj[i]&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\trajectory.py:259, in TrajectoryReader.__getitem__(self, i)&#xA;    257 if isinstance(i, slice):&#xA;    258     return SlicedTrajectory(self, i)&#xA;--&amp;gt; 259 b = self.backend[i]&#xA;    260 if 'numbers' in b:&#xA;    261     # numbers and other header info was written alongside the image:&#xA;    262     atoms = read_atoms(b, traj=self)&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\ulm.py:584, in Reader.__getitem__(self, index)&#xA;    582 def __getitem__(self, index):&#xA;    583     &amp;quot;&amp;quot;&amp;quot;Return Reader for item *index*.&amp;quot;&amp;quot;&amp;quot;&#xA;--&amp;gt; 584     data = self._read_data(index)&#xA;    585     return Reader(self._fd, index, data, self._little_endian)&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\ulm.py:577, in Reader._read_data(self, index)&#xA;    575 def _read_data(self, index):&#xA;    576     self._fd.seek(self._offsets[index])&#xA;--&amp;gt; 577     size = int(readints(self._fd, 1)[0])&#xA;    578     data = decode(self._fd.read(size).decode(), False)&#xA;    579     self._little_endian = data.pop('_little_endian', True)&#xA;&#xA;File ~\AppData\Roaming\Python\Python38\site-packages\ase\io\ulm.py:187, in readints(fd, n)&#xA;    186 def readints(fd, n):&#xA;--&amp;gt; 187     a = np.frombuffer(fd.read(int(n * 8)), dtype=np.int64, count=n)&#xA;    188     if not np.little_endian:&#xA;    189         # Cannot use in-place byteswap because frombuffer()&#xA;    190         # returns readonly view&#xA;    191         a = a.byteswap()&#xA;&#xA;ValueError: buffer is smaller than requested size&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="4219" LastEditDate="2022-04-19T19:00:21.780" LastActivityDate="2022-04-19T19:00:21.780" Title="Atomic Simulation Environment (ASE) is unable to read a big trajectory file" Tags="|molecular-dynamics|computational-chemistry|python|visualization-software|atomic-simulation-environment|" AnswerCount="0" CommentCount="6" ClosedDate="2022-10-26T13:17:49.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="8952" PostTypeId="2" ParentId="8942" CreationDate="2022-04-19T20:19:23.917" Score="3" Body="&lt;p&gt;You can get the corresponding indices of the two structures with &lt;code&gt;GenerateDepictionMatching2DStructure&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The code was made in a Jupyter notebook.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import rdDepictor&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;IPythonConsole.molSize = (350, 350)&#xA;IPythonConsole.drawOptions.addAtomIndices = True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Compute the coordinates of the reference mol.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ref_mol = Chem.MolFromSmiles('O=C1c2ccccc2C(=O)c2ccccc12')&#xA;rdDepictor.Compute2DCoords(ref_mol)&#xA;ref_mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/b4ipq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/b4ipq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now match the the target mol with the reference mol.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tar_mol = Chem.MolFromSmiles('CC(C)(C)c1cccc2C(=O)c3c(cccc3C(C)(C)C)C(=O)c12')&#xA;idx_pair = rdDepictor.GenerateDepictionMatching2DStructure(tar_mol, ref_mol)&#xA;tar_mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VnU1F.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VnU1F.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;After matching, you will get the pairs of corresponding indices. First value is from the reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;idx_pair&#xA;&#xA;((0, 10),&#xA; (1, 9),&#xA; (2, 8),&#xA; (3, 7),&#xA; (4, 6),&#xA; (5, 5),&#xA; (6, 4),&#xA; (7, 23),&#xA; (8, 21),&#xA; (9, 22),&#xA; (10, 12),&#xA; (11, 13),&#xA; (12, 14),&#xA; (13, 15),&#xA; (14, 16),&#xA; (15, 11))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Lets find the substitutions.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;patt = Chem.MolFromSmarts('cC(C)(C)C')&#xA;idx_tar = tar_mol.GetSubstructMatches(patt)&#xA;print(idx_tar)&#xA;tar_mol&#xA;&#xA;((4, 1, 0, 2, 3), (16, 17, 18, 19, 20))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9f0cZ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9f0cZ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And now you can get the corresponding indices for 4 and 16&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for t in idx_tar:&#xA;    for p in idx_pair:&#xA;        if t[0] == p[1]:&#xA;            print('Substitute on:', p[0])&#xA;&#xA;Substitute on: 6&#xA;Substitute on: 14&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2022-04-19T20:19:23.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8953" PostTypeId="2" ParentId="8932" CreationDate="2022-04-20T05:49:34.180" Score="12" Body="&lt;p&gt;There are different flavors of interatomic potentials, from the classical Lennard-Jones and Morse models to more recent machine learning models. I will limit the answer to reactive potential models without considering bonded force fields.&lt;/p&gt;&#xA;&lt;h2&gt;Check existing potentials repository&lt;/h2&gt;&#xA;&lt;p&gt;Before fitting a new model, first try searching the repositories&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;OpenKIM (&lt;a href=&quot;https://openkim.org&quot; rel=&quot;noreferrer&quot;&gt;https://openkim.org&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;NIST (&lt;a href=&quot;https://www.ctcms.nist.gov/potentials/&quot; rel=&quot;noreferrer&quot;&gt;https://www.ctcms.nist.gov/potentials/&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;to see whether you can find one that satisfies your needs.&#xA;Via the KIM API (&lt;a href=&quot;https://openkim.org/kim-api&quot; rel=&quot;noreferrer&quot;&gt;https://openkim.org/kim-api&lt;/a&gt;), models archived on OpenKIM can be used in various molecular simulation codes, such as LAMMPS, ASE, DL_POLY, GULP, and ASAP. OpenKIM also provides analysis of each model (e.g. citation analysis and tests on canonical properties like cohesive energy and elastic constant), which may help you to decide whether a model satisfies your need. For an example, see &lt;a href=&quot;https://openkim.org/id/EAM_Dynamo_Ackland_1992_Ti__MO_748534961139_005&quot; rel=&quot;noreferrer&quot;&gt;https://openkim.org/id/EAM_Dynamo_Ackland_1992_Ti__MO_748534961139_005&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Build new potentials&lt;/h2&gt;&#xA;&lt;p&gt;If none satisfies the need, there are basically three steps to create a new model.&lt;/p&gt;&#xA;&lt;h3&gt;Assemble a dataset&lt;/h3&gt;&#xA;&lt;p&gt;Traditionally, potentials are fit to reproduce a set of experimental properties, but nowadays most potentials are fit to more easily obtainable properties from quantum mechanical calculations.&lt;/p&gt;&#xA;&lt;p&gt;Here are some DFT codes that can be used to generate a dataset of energy, forces, and stress for training the model.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Quantum Espresso (open source) &lt;a href=&quot;https://www.quantum-espresso.org&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;VASP (commercial) &lt;a href=&quot;https://www.vasp.at&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;ABINIT (open source) &lt;a href=&quot;https://www.abinit.org&quot; rel=&quot;noreferrer&quot;&gt;https://www.abinit.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;SIESTA (open source) &lt;a href=&quot;https://departments.icmab.es/leem/siesta/&quot; rel=&quot;noreferrer&quot;&gt;https://departments.icmab.es/leem/siesta/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;CP2K (open source) &lt;a href=&quot;https://www.cp2k.org&quot; rel=&quot;noreferrer&quot;&gt;https://www.cp2k.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you do not want to generate a dataset by yourself, some computational materials databases may have DFT data that can be used for fitting a potential, such as&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Materials Project &lt;a href=&quot;https://materialsproject.org&quot; rel=&quot;noreferrer&quot;&gt;https://materialsproject.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;AFLOW &lt;a href=&quot;http://www.aflowlib.org&quot; rel=&quot;noreferrer&quot;&gt;http://www.aflowlib.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;OQMD &lt;a href=&quot;https://oqmd.org&quot; rel=&quot;noreferrer&quot;&gt;https://oqmd.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;NOMAD &lt;a href=&quot;https://nomad-lab.eu&quot; rel=&quot;noreferrer&quot;&gt;https://nomad-lab.eu&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;JARVIS &lt;a href=&quot;https://jarvis.nist.gov&quot; rel=&quot;noreferrer&quot;&gt;https://jarvis.nist.gov&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Train the model&lt;/h3&gt;&#xA;&lt;p&gt;Given a dataset, many open-source codes can be used to fit a potential. Below are some widely used ones, and I categorize them into codes that build physics-based models (e.g. Tersoff) or build machine learning models (e.g. neural network).&lt;/p&gt;&#xA;&lt;h4&gt;Physics based&lt;/h4&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;potfit &lt;a href=&quot;https://www.potfit.net/wiki/doku.php&quot; rel=&quot;noreferrer&quot;&gt;https://www.potfit.net/wiki/doku.php&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;KLIFF &lt;a href=&quot;https://github.com/openkim/kliff&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/openkim/kliff&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;atomicrex &lt;a href=&quot;https://www.atomicrex.org&quot; rel=&quot;noreferrer&quot;&gt;https://www.atomicrex.org&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h4&gt;Machine learning&lt;/h4&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;KLIFF (general purpose) &lt;a href=&quot;https://github.com/openkim/kliff&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/openkim/kliff&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;MAML (general purpose) &lt;a href=&quot;https://github.com/materialsvirtuallab/maml&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/materialsvirtuallab/maml&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;GAP (Gaussian approximation potential) &lt;a href=&quot;https://libatoms.github.io&quot; rel=&quot;noreferrer&quot;&gt;https://libatoms.github.io&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;MTP (Moment tensor potential) &lt;a href=&quot;https://mlip.skoltech.ru&quot; rel=&quot;noreferrer&quot;&gt;https://mlip.skoltech.ru&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;SNAP (Spectral neighbor analysis potential) &lt;a href=&quot;https://github.com/FitSNAP/FitSNAP&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/FitSNAP/FitSNAP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;PANNA (Behler--Parrinello type neural network) &lt;a href=&quot;https://gitlab.com/PANNAdevs/panna&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/PANNAdevs/panna&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;AMP (Behler--Parrinello type neural network) &lt;a href=&quot;https://bitbucket.org/andrewpeterson/amp&quot; rel=&quot;noreferrer&quot;&gt;https://bitbucket.org/andrewpeterson/amp&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;aenet (Behler--Parrinello type neural network) &lt;a href=&quot;http://ann.atomistic.net&quot; rel=&quot;noreferrer&quot;&gt;http://ann.atomistic.net&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;DeePMD &lt;a href=&quot;https://github.com/deepmodeling/deepmd-kit&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/deepmodeling/deepmd-kit&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;SchNet (graph neural network) &lt;a href=&quot;https://github.com/atomistic-machine-learning/schnetpack&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/atomistic-machine-learning/schnetpack&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;NequIP (equivariant graph neural network) &lt;a href=&quot;https://github.com/mir-group/nequip&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/mir-group/nequip&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Deploy the model&lt;/h3&gt;&#xA;&lt;p&gt;Most of the fitting codes listed above do have an interface to either LAMMPS or ASE, or both. So deploying the fitted model for simulation is typically not a problem. PANNA, potfit, and KLIFF have interfaces to the KIM API, and potentials created with them can be used in multiple simulation codes.&lt;/p&gt;&#xA;&lt;h4&gt;Disclaimer&lt;/h4&gt;&#xA;&lt;p&gt;I am the author of KLIFF.&lt;/p&gt;&#xA;" OwnerUserId="5279" LastEditorUserId="5279" LastEditDate="2022-04-20T05:54:54.610" LastActivityDate="2022-04-20T05:54:54.610" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8955" PostTypeId="2" ParentId="8898" CreationDate="2022-04-21T00:07:29.877" Score="2" Body="&lt;p&gt;Not sure if you figured this out but if your scf calculation was fine and converged you should know that QE will read some info from the scf run as well as this input so they must match. You should check to see that there to no differences between your scf input file  and your bands input file - as in spaces, blank lines or ordering of information in your Atomic_Species or _Positions cards.&lt;/p&gt;&#xA;&lt;p&gt;See this forum response: &lt;a href=&quot;https://pw-forum.pwscf.narkive.com/Q2GT5FYn/error-in-routine-potinit-1-starting-and-expected-charges-differ&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pw-forum.pwscf.narkive.com/Q2GT5FYn/error-in-routine-potinit-1-starting-and-expected-charges-differ&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also (and maybe unrelated) are you sure you need to define anything in the &amp;amp;ELECTRONS section other than the mixing_beta flag?&lt;/p&gt;&#xA;" OwnerUserId="892" LastActivityDate="2022-04-21T00:07:29.877" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8956" PostTypeId="1" CreationDate="2022-04-21T13:45:45.117" Score="1" ViewCount="454" Body="&lt;p&gt;I have the following problem to run a calculation using Gaussian 9. The calculation starts running and after a few hours stop. The &lt;code&gt;nohup&lt;/code&gt; file has the following message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;error: hangup&#xA;rax fffffffffffffffc, rbx 00007fff0bd4e160, rcx ffffffffffffffff&#xA;rdx 0000000000000000, rsp 00007fff0bd4e128, rbp 00000000000000001&#xA;rsi 00007fff0bd4e160, rdi 000000000000828d, r8 00002b17bcdec700&#xA;r9 0000000000000000, r10 0000000000000000, r11 00000000000000246&#xA;r12 00007fff0bd4e180, r13 0000000000000064, r14 00000000000000000&#xA;r15 00007fff0bd54b40&#xA;--- traceback not available&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the logs of &lt;code&gt;/var/log/message&lt;/code&gt; there is the following message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Apr 19 20:28:10 ws1 abrt-hook-ccpp: Process 15059 (g09) of user 1002 killed by SIGABRT - dumping core&#xA;Apr 19 20:28:10 ws1 abrt-hook-ccpp: Process 15060 (l502.exe) of user 1002 killed by SIGABRT - dumping core&#xA;Apr 19 20:28:40 ws1 systemd-logind: Removed session 4.&#xA;Apr 19 20:28:40 ws1 systemd: Removed slice User Slice of xx.&#xA;Apr 19 20:28:41 ws1 abrtd: Size of '/var/spool/abrt' &amp;gt;= 5000 MB (MaxCrashReportsSize), deleting new directory 'ccpp-2022-04-19-20:28&#xA;:10-15060'&#xA;Apr 19 20:28:41 ws1 abrt-server: Lock file '.lock' is locked by process 12809. Waiting...&#xA;Apr 19 20:28:42 ws1 abrt-server: Generating core_backtrace&#xA;Apr 19 20:28:43 ws1 abrt-server: Duplicate: core backtrace&#xA;Apr 19 20:28:43 ws1 abrt-server: DUP_OF_DIR: /var/spool/abrt/ccpp-2022-04-01-10:32:53-214966&#xA;Apr 19 20:28:43 ws1 abrt-server: Deleting problem directory ccpp-2022-04-19-20:28:10-15059 (dup of ccpp-2022-04-01-10:32:53-214966)&#xA;Apr 19 20:28:43 ws1 abrt-server: Sender email address was not specified. Would you like to do it now? If not, 'user@localhost'&#xA; is being used [y/N]&#xA;Apr 19 20:28:43 ws1 abrt-server: Receiver email address not specified. Would you like to do it now? If not, 'root@localhos&#xA;t' is being used [y/N]&#xA;Apr 19 20:28:43 ws1 abrt-server: Undefined variable outside of [[ ]] bracket&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input file settings:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=20GB&#xA;%nprocshared=4&#xA;#p opt mp2/aug-cc-pvtz scrf=(solvent=acetonitrile,pcm) maxdisk=600GB&#xA;geom=connectivity density=current gfinput iop(6/7=3)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Doing the same calculation with PM6 worked fine. The problem only appears with highly demanding calculations, as optimization and frequency at MP2/aug-cc-pVTZ level. It no longer generates log files other than the ones I put.&#xA;Current machine settings is 93GB RAM and 32 CPUs. I don't know if it can be the machine's configuration, during the calculation the maximum memory it uses is 30GB.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone had this problem? Any idea what it could be? Here are the last few line of the log file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; GePol: Maximum weight of points                     =    0.20577&#xA; GePol: Number of points with low weight             =      78&#xA; GePol: Fraction of low-weight points (&amp;lt;1% of avg)   =       4.99%&#xA; GePol: Cavity surface area                          =    206.571 Ang**2&#xA; GePol: Cavity volume                                =    211.021 Ang**3&#xA; Leave Link  301 at Wed Apr 20 20:37:01 2022, MaxMem=  2684354560 cpu:         0.3&#xA; (Enter /opt/ohpc/pub/apps/gaussian/09d01-pgi-14.3/g09/l302.exe)&#xA; NPDir=0 NMtPBC=     1 NCelOv=     1 NCel=       1 NClECP=     1 NCelD=      1&#xA;         NCelK=      1 NCelE2=     1 NClLst=     1 CellRange=     0.0.&#xA; One-electron integrals computed using PRISM.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5301" OwnerDisplayName="jaqueline" LastEditorUserId="7" LastEditDate="2022-04-25T19:09:40.840" LastActivityDate="2022-04-25T19:09:40.840" Title="Error: hangup in Gaussian 09" Tags="|computational-chemistry|gaussian|geometry-optimization|" AnswerCount="0" CommentCount="5" ClosedDate="2022-10-26T13:14:32.643" ContentLicense="CC BY-SA 4.0" />
  <row Id="8957" PostTypeId="1" AcceptedAnswerId="8962" CreationDate="2022-04-21T16:22:26.690" Score="9" ViewCount="325" Body="&lt;p&gt;CCSDT(Q) and CCSDTQ calculations are extraordinarily expensive, both in terms of FLOP count and RAM capacity requirements, eg. CCSDTQ requires a computational effort that scales as ~&lt;span class=&quot;math-container&quot;&gt;$N^{10}$&lt;/span&gt;, where N is the number of (contracted) basis functions. Given that, it is easy to see why running CCSDTQ calculations with fewer basis functions would be advantageous.&lt;/p&gt;&#xA;&lt;p&gt;The obvious way to reduce N is to use a smaller basis set. While there is some evidence [&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0009261419307912&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;,&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0011674&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;] that the &lt;code&gt;CCSDT(Q)-CCSDT&lt;/code&gt; and especially the &lt;code&gt;CCSDTQ-CCSDT(Q)&lt;/code&gt; contributions converge to the basis set limit faster than lower complexity contributions, CCSDT(Q)/cc-pVDZ can still be extremely demanding.&lt;/p&gt;&#xA;&lt;p&gt;The other alternative would be to create basis sets optimized specifically for the purpose of post-CCSD(T) (CCSDT, CCSDT(Q), ...) calculations, with fewer contracted basis functions per atom. One could really crank up the number of primitive gaussians per basis function, if required, and integral evaluation time would still be utterly negligible compared to the time spent in the CCSDT(Q) code.&#xA;Something like a hypothetical &amp;quot;ANO-CCQ&amp;quot; basis set might make CSSDT(Q) calculations more feasible.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;/p&gt;&#xA;&lt;p&gt;Has anyone ever developed or seen a basis set specifically optimized for post-CCSD(T) calculations?&lt;/p&gt;&#xA;" OwnerUserId="5225" LastEditorUserId="5225" LastEditDate="2022-05-09T14:23:49.643" LastActivityDate="2022-05-09T14:23:49.643" Title="Basis sets optimized for CCSDT(Q) calculations" Tags="|quantum-chemistry|basis-sets|coupled-cluster|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8958" PostTypeId="1" AcceptedAnswerId="8960" CreationDate="2022-04-21T18:59:40.043" Score="4" ViewCount="1399" Body="&lt;p&gt;I am trying to raise the temperature of my model and keep the temperature at 300K, with an NVT ensemble and Nose-Hoover thermostat. &lt;br&gt;&#xA;I am doing this job with VASP, here is the &lt;code&gt;INCAR&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DFT+U Calculation&#xA;LDAU   = .TRUE.        (Activate DFT+U)&#xA;LDATYPE=  2            (Dudarev; only U-J matters)&#xA;LDAUL  =  -1 -1 -1 -1 2 -1        (Orbitals for each species)&#xA;LDAUU  =  0 0 0 0  6  0       (U for each species)&#xA;LDAUJ  =  0 0 0 0 0 0        (J for each species)&#xA;LMAXMIX=  4            (Mixing cut-off; 4-d, 6-f)&#xA; &#xA;Global Parameters&#xA;ISTART =  1            (Read existing wavefunction; if there)&#xA;ISPIN  =  2            (Non-Spin polarised DFT)&#xA;#MAGMOM = 4*0 4*0 48*0 24*1 1*1&#xA;LREAL  = Auto       (Projection operators: automatic)&#xA;ENCUT  =  520        (Cut-off energy for plane wave basis set, in eV)&#xA;PREC   =  Normal       (Precision level)&#xA;LWAVE  = .FALSE.        (Write WAVECAR or not)&#xA;LCHARG = .FALSE.        (Write CHGCAR or not)&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)&#xA;# LVTOT  = .TRUE.      (Write total electrostatic potential into LOCPOT or not)&#xA;# LVHAR  = .TRUE.      (Write ionic + Hartree electrostatic potential into LOCPOT or not)&#xA;# NELECT =             (No. of electrons: charged cells; be careful)&#xA;# LPLANE = .TRUE.      (Real space distribution; supercells)&#xA;NCORE   = 8           (Max is no. nodes; dont set for hybrids)&#xA; &#xA;Electronic Relaxation&#xA;ISMEAR =  0            (Gaussian smearing; metals:1)&#xA;SIGMA  =  0.05         (Smearing value in eV; metals:0.2)&#xA;NELM   =  90           (Max electronic SCF steps)&#xA;NELMIN =  6            (Min electronic SCF steps)&#xA;EDIFF  =  1E-06        (SCF energy convergence; in eV)&#xA;PREC=Low&#xA;ISYM=0&#xA;MAXMIX = 40  &#xA;IWAVPR=11&#xA;############################# MD setting #####################################&#xA;# canonic (Nose) MD with XDATCAR updated every 10 steps&#xA;IBRION = 0&#xA;MDALGO = 2                     ä switch to select thermostat&#xA;SMASS =  1                     # Nose mass&#xA;ISIF = 2                       # this tag selects the ensemble in combination with the thermostat&#xA;NSW =1000&#xA;POTIM = 1&#xA;TEBEG = 300&#xA;TEEND = 300&#xA;NBLOCK = 4&#xA;##############################################################################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the screenshot of my model:&lt;br&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/pkOvQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pkOvQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;Why does the temperature fluctuate so much during AIMD?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yjJHQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yjJHQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is an result after I run 5ps AIMD:&lt;br&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5Lpid.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5Lpid.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-04-23T08:27:32.910" LastActivityDate="2022-04-23T08:27:32.910" Title="Why does the temperature fluctuate severely during the AIMD using an NVT ensemble?" Tags="|vasp|molecular-dynamics|aimd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8959" PostTypeId="1" AcceptedAnswerId="8967" CreationDate="2022-04-21T19:15:46.187" Score="5" ViewCount="2845" Body="&lt;p&gt;I am trying to do geometry optimization of TiO2 with VASP.&#xA;Here is the &lt;code&gt;POSCAR&lt;/code&gt; file, which I get from the Materials Project.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TiO2_mp-390_primitive&#xA;1.0&#xA;        5.5664000511         0.0000000000         0.0000000000&#xA;        2.9685780783         4.7087528839         0.0000000000&#xA;       -4.2674858950        -2.3543746932         2.6889205026&#xA;   Ti    O&#xA;    2    4&#xA;Cartesian&#xA;     2.783201610         0.000000874         1.344460251&#xA;     0.000000000         0.000000000         0.000000000&#xA;     4.542772778         0.970757411         1.344460251&#xA;     6.775406962         3.737996347         0.000000000&#xA;     1.023630465        -0.970755627         1.344460251&#xA;     1.759571040         0.970756466         0.000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I generate the K-Points with &lt;code&gt;vaspkit&lt;/code&gt; tool:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Spacing Value to Generate K-Mesh: 0.030&#xA;0&#xA;Gamma&#xA;   9   9  12&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I found that there is an error message about the mismatch between Reciprocal lattice and k-lattice. Here is the error message:&lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; VERY BAD NEWS! internal error in subroutine IBZKPT:&#xA; Reciprocal lattice and k-lattice belong to different class of lattices. Often results are still useful...      60&#xA;&#xA;&#xA; VERY BAD NEWS! internal error in subroutine IBZKPT:&#xA; Reciprocal lattice and k-lattice belong to different class of lattices. Often results are still useful...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And if I use the following K-Points, there would be no errors.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Points&#xA;0&#xA;Gamma&#xA;   9   9  9&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This seems weird, because it is obvious the three lattice vectors' lengths aren't the same, why would I have to use the same number of K points in three different directions?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-04-22T23:29:58.250" Title="Reciprocal lattice and k-lattice belong to different groups in VASP" Tags="|vasp|geometry-optimization|k-points|space-groups|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8960" PostTypeId="2" ParentId="8958" CreationDate="2022-04-21T20:08:07.267" Score="7" Body="&lt;p&gt;The primary reason is that your simulation time is too short. To thermally equilibrate a system, the simulation time must be much longer than the period of the slowest phonon mode, so that even the slowest vibration has taken place multiple times. Taking a conservative estimate that the lowest phonon mode of your system is &lt;span class=&quot;math-container&quot;&gt;$100 \mathrm{~cm}^{-1}$&lt;/span&gt;, we see that the period of this mode is about &lt;span class=&quot;math-container&quot;&gt;$300 \mathrm{~fs}$&lt;/span&gt; (note that this correlates very well with the oscillation period of the total energy!), so that you must perform the AIMD for at least a few picoseconds before the slowest vibration damps out.&lt;/p&gt;&#xA;&lt;p&gt;Another, probably secondary, reason is that any small system will have notable thermal fluctuations even when already equilibrated. Your system is not particularly large, so this inherent thermal fluctuation may also contribute somewhat to the observed fluctuations.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-04-21T20:08:07.267" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="8962" PostTypeId="2" ParentId="8957" CreationDate="2022-04-22T09:01:49.680" Score="14" Body="&lt;p&gt;To the best of my knowledge, there have not been basis sets optimized for post-CCSD(T) calculations. Note that the cc-pVXZ have been optimized using CISD. One would expect these to be also close to optimum for CCSD and beyond. We have played with optimizing basis sets at the CCSD(T) level, but they offer marginal improvement compared to the standard cc-pVXZ, and we have never published this.&lt;/p&gt;&#xA;&lt;p&gt;Now I guess you are asking for optimizing the accuracy vs. effort for composite methods involving high-level CC, such as the Wn methods, i.e. using different basis sets for each higher CC-excitation level. Fundamentally one would not expect that e.g. the Q-contributions would have a lower basis set requirements than the SD contributions, if different, probably the Q-contributions would have a larger basis set requirement. But the absolute Q-contribution is much smaller than the SD-contribution, and one can thus tolerate a much larger relative Q-error for the same absolute error, and this is the argument for using small(er) basis sets for the higher CC-excitation levels. Another reason is of course that high CC-excitation levels are only possible in small(er) basis sets....&lt;/p&gt;&#xA;&lt;p&gt;One could try to establish the 'optimum' basis set size for each CCSDnnn(m) level, and also perform explicit basis set optimization. This could be done analogous to the cc-pVXZ by calculating the energy contribution at a given CCSDnnn(m) level as a function of the basis set composition and exponents. This is certainly doable, but not a trivial endeavour, with the risk that the answer is that e.g. the standard cc-pVXZ or ANO are close to optimum.&lt;/p&gt;&#xA;&lt;p&gt;It is difficult to believe that basis sets smaller than DZP quality can be used for high-CC excitations, as one anticipates that a balance between radial and angular correlation will be important, and e.g. the ANO includes a large number of primitive functions that likely effectively saturates the exponent space.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2022-04-22T09:01:49.680" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8963" PostTypeId="1" AcceptedAnswerId="8966" CreationDate="2022-04-22T14:52:42.357" Score="8" ViewCount="1311" Body="&lt;p&gt;Suppose I have the following Hamiltonian to start&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H_0 = \begin{pmatrix} 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 2 &amp;amp; 0\\ 0 &amp;amp; 2 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \end{pmatrix} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and now I add some pertubation &lt;span class=&quot;math-container&quot;&gt;$H_1$&lt;/span&gt; to it to have the total Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H = H_0 + H_1 = \begin{pmatrix} 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 2 &amp;amp; 0\\ 0 &amp;amp; 2 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \end{pmatrix} + \begin{pmatrix} -0.1 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; -0.1 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0.1 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0.1 \end{pmatrix} = \begin{pmatrix} -0.1 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; -0.1 &amp;amp; 2 &amp;amp; 0\\ 0 &amp;amp; 2 &amp;amp; 0.1 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0.1 \end{pmatrix} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that the lowest eigenvalue of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^H = -2.00249844 $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The lowest eigenvalue of &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^{H_0} = -2 $&lt;/span&gt; with corresponding normalized eigenvector &lt;span class=&quot;math-container&quot;&gt;$|\lambda_0^{H_0}  \rangle = \begin{pmatrix} 0 \\ -1/\sqrt{2} \\ 1/\sqrt{2}  \\ 0 \end{pmatrix}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now to get the first order energy correction, &lt;span class=&quot;math-container&quot;&gt;$\delta E_1$&lt;/span&gt;, we can evaluate &lt;span class=&quot;math-container&quot;&gt;$\langle \lambda_0^{H_0}  | H_1 | \lambda_0^{H_0}   \rangle$&lt;/span&gt; but &lt;strong&gt;this is always equal to 0&lt;/strong&gt; as one can see from the form of &lt;span class=&quot;math-container&quot;&gt;$H_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\lambda_0^{H_0}  \rangle $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; How can you correct for this perturbation? That is to get back close &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^H$&lt;/span&gt; after obtaining &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^{H_0}  $&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|\lambda_0^{H_0}  \rangle $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;As a side additional note:&lt;/strong&gt; If &lt;span class=&quot;math-container&quot;&gt;$ H_0 = \begin{pmatrix} 0 &amp;amp; 0 &amp;amp; 1 &amp;amp; -1\\ 0 &amp;amp; 0 &amp;amp; 1 &amp;amp; 1\\ 1 &amp;amp; 1 &amp;amp; 0 &amp;amp; 0\\ -1 &amp;amp; 1 &amp;amp; 0 &amp;amp; 0 \end{pmatrix} $&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H_1 = \begin{pmatrix} -0.1 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0.1 &amp;amp; 0 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; -0.1 &amp;amp; 0\\ 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0.1 \end{pmatrix} $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;then &lt;span class=&quot;math-container&quot;&gt;$H = H_0 + H_1$&lt;/span&gt; has lowest eigenvalue of &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^H = -1.48660687$&lt;/span&gt;. The lowest eigenvalue of &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^{H_0} = -1.4142135623 $&lt;/span&gt; with corresponding normalized eigenvector &lt;span class=&quot;math-container&quot;&gt;$|\lambda_0^{H_0}  \rangle = \begin{pmatrix} -1/\sqrt{2} \\ 0 \\ 1/2  \\ 1/2 \end{pmatrix}$&lt;/span&gt;. Then from here you can see that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\delta E_1 = \langle \lambda_0^{H_0}  | H_1 | \lambda_0^{H_0}   \rangle = -0.05$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus, adding this back bring me closer to the true value &lt;span class=&quot;math-container&quot;&gt;$\lambda_0^H = -1.48660687$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1711" LastActivityDate="2022-04-24T16:10:15.067" Title="What does it mean when the first order correction energy is 0?" Tags="|computational-chemistry|mathematical-modeling|quantum-mechanics|many-body-perturbation-theory|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8964" PostTypeId="1" CreationDate="2022-04-22T17:59:00.923" Score="1" ViewCount="67" Body="&lt;p&gt;I am absolutely new to Polymer simulation. I am trying to understand the simulation by analyzing source code written by others.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone tell me what are the differences between the following three source code in terms of their objectives?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/mwb0506/Monte-Carlo-simulation-of-polymers&quot; rel=&quot;nofollow noreferrer&quot;&gt;Monte-Carlo-simulation-of-polymers&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/tianchuliang/PolymerPhysicsSimulation&quot; rel=&quot;nofollow noreferrer&quot;&gt;PolymerPhysicsSimulation&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/amir-saadat/Polymer-MonteCarlo&quot; rel=&quot;nofollow noreferrer&quot;&gt;Polymer-MonteCarlo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For example, I want to know:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;if they achieve the same objectives, i.e., polymer growth.&lt;/li&gt;&#xA;&lt;li&gt;if they represent bio-polymers (e.g. proteins) or synthetic polymers.&lt;/li&gt;&#xA;&lt;li&gt;if they are lattice-based or off-lattice simulations.&lt;/li&gt;&#xA;&lt;li&gt;if they represent hard-polymers or soft-polymers.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-04-22T18:07:14.397" LastActivityDate="2022-04-22T18:07:14.397" Title="Polymer simulation" Tags="|monte-carlo|polymers|atomistic-simulation|" AnswerCount="0" CommentCount="2" ClosedDate="2022-10-28T13:33:48.333" ContentLicense="CC BY-SA 4.0" />
  <row Id="8965" PostTypeId="1" CreationDate="2022-04-22T18:42:44.610" Score="5" ViewCount="126" Body="&lt;p&gt;Can anyone recommend code (preferably open-source) for the simulation of EPR spectra from electronic structure calculations?&lt;/p&gt;&#xA;&lt;p&gt;I found &lt;a href=&quot;https://www.easyspin.org&quot; rel=&quot;noreferrer&quot;&gt;EasySpin&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;EasySpin is an open-source MATLAB toolbox for simulating Electron Paramagnetic Resonance (EPR) spectra&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But it requires MATLAB. Are there any good alternatives?&lt;/p&gt;&#xA;" OwnerUserId="878" LastEditorUserId="7" LastEditDate="2022-04-22T20:56:46.067" LastActivityDate="2022-04-22T20:56:46.067" Title="EPR spectrum simulation" Tags="|software-recommendations|spectroscopy|open-source|" AnswerCount="0" CommentCount="8" ClosedDate="2022-11-03T15:49:05.320" ContentLicense="CC BY-SA 4.0" />
  <row Id="8966" PostTypeId="2" ParentId="8963" CreationDate="2022-04-22T20:00:41.733" Score="11" Body="&lt;p&gt;The first-order correction &lt;span class=&quot;math-container&quot;&gt;$\langle \psi_0|H|\psi_0\rangle$&lt;/span&gt; vanishes since &lt;span class=&quot;math-container&quot;&gt;$H|\psi_0 \rangle$&lt;/span&gt; is orthogonal to &lt;span class=&quot;math-container&quot;&gt;$|\psi_0\rangle$&lt;/span&gt;. You need to go higher in perturbation theory to get a correction that differs from zero, or adjust your zeroth order Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;Such events often occur in physics. Take for instance the hydrogen atom in an electric field, &lt;span class=&quot;math-container&quot;&gt;${\bf E}=(0,0,E)$&lt;/span&gt;, for which the potential is often chosen as &lt;span class=&quot;math-container&quot;&gt;$V=V(z)=Ez$&lt;/span&gt;. The hydrogen atom ground state is spherically symmetric, so the expectation value for the first-order term is zero.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="181" LastEditDate="2022-04-22T21:01:25.660" LastActivityDate="2022-04-22T21:01:25.660" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8967" PostTypeId="2" ParentId="8959" CreationDate="2022-04-22T23:29:58.250" Score="5" Body="&lt;p&gt;The DFT code will typically reduce the number of Brillouin-zone sampling &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points to the irreducible Brillouin zone by applying point group operations. For this approach to work, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid must transform to itself under these point group operations. Depending on number of grid subdivisions or shifts of the overall mesh, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid can break the point group symmetry of the system, as was the case in the example of the OP.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grids corresponding to the primitive cells of body-centered tetragonal structures (such as rutile TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; considered by the OP) are cases where indeed having equal number of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points along each reciprocal unit cell vector solves the problem of otherwise broken symmetries. A smart alternative for generating a symmetry-compatible &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point without the requirement of equal grid subdivisions for such cases is given in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/KPOINTS&quot; rel=&quot;noreferrer&quot;&gt;VASP manual&lt;/a&gt; (which will work with other DFT codes, too): generate a &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid for the conventional tetragonal unit cell (i.e. a cell containing twice as many atoms with orthogonal unit cell vectors) and explicitly provide this full grid as input to VASP together with the atomic structure input of the primitive cell (i.e., the POSCAR in the question). VASP will then reduce this grid to the irreducible Brillouin zone corresponding to the primitive cell.&lt;/p&gt;&#xA;" OwnerUserId="5250" LastActivityDate="2022-04-22T23:29:58.250" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8969" PostTypeId="1" AcceptedAnswerId="8990" CreationDate="2022-04-23T18:28:58.147" Score="5" ViewCount="347" Body="&lt;p&gt;I have finished the NEB calculation, but it seems all the energy I got is Internal energy instead of Gibbs free energy, so do I need to do Gibbs free energy modification? Is there any standard procedure for it?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-04-29T02:48:32.313" Title="Gibbs free energy modification after finishing NEB?" Tags="|vasp|transition-state|free-energy|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8970" PostTypeId="1" CreationDate="2022-04-23T19:14:16.027" Score="4" ViewCount="73" Body="&lt;p&gt;As far as I understand:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pruning means deleting something.&lt;/li&gt;&#xA;&lt;li&gt;Enrich means to enhance/increase weight.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Now my question is, in the case of &lt;a href=&quot;https://arxiv.org/abs/1107.1214&quot; rel=&quot;nofollow noreferrer&quot;&gt;pruned-enriched Rosenbluth method&lt;/a&gt; (PERM):&lt;/p&gt;&#xA;&lt;p&gt;For pruning/enriching, are we deleting/adding to some polymers chains or are we deleting/adding some beads in all polymer chains?&lt;/p&gt;&#xA;&lt;p&gt;Basically, when we are updating the weights, what are we replacing them with?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="7" LastEditDate="2022-04-24T13:44:18.973" LastActivityDate="2022-04-24T13:44:18.973" Title="What does it mean by pruning and enrichment in the case of Rosenbluth method?" Tags="|monte-carlo|polymers|atomistic-simulation|" AnswerCount="0" CommentCount="2" ClosedDate="2022-11-02T00:31:39.560" ContentLicense="CC BY-SA 4.0" />
  <row Id="8971" PostTypeId="1" AcceptedAnswerId="8972" CreationDate="2022-04-24T12:53:14.263" Score="3" ViewCount="61" Body="&lt;p&gt;Suppose, a polymer has 3 monomers in its chain:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\ce{A1-A2-A3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;When calculating total LJ potential, do I need to calculate like this:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E(r_{12})+E(r_{23})+E(r_{31})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or, do I calculate: &lt;span class=&quot;math-container&quot;&gt;$$E(r_{12})+E(r_{23})$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="7" LastEditDate="2022-04-24T14:07:56.750" LastActivityDate="2022-04-24T15:19:43.353" Title="How should I calculate total potential in a polymer chain?" Tags="|monte-carlo|polymers|atomistic-simulation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8972" PostTypeId="2" ParentId="8971" CreationDate="2022-04-24T15:14:03.233" Score="3" Body="&lt;p&gt;You'll want to add up all interactions that you can, up to some appropriately chosen cutoff distance. Choose the VDW cutoff such that the total energy doesn't change much if you further increase this number.&lt;/p&gt;&#xA;&lt;p&gt;In your case, it's likely you'll want to include all three interactions, unless the monomers themselves are very large such that &lt;span class=&quot;math-container&quot;&gt;$E(r_{31})$&lt;/span&gt; is very small relative to the other two terms.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-04-24T15:19:43.353" LastActivityDate="2022-04-24T15:19:43.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8973" PostTypeId="2" ParentId="8963" CreationDate="2022-04-24T16:00:27.853" Score="5" Body="&lt;p&gt;There are already good answers to your immediate question, so I won't address it directly here. Instead, I'd like to delve slightly deeper into your question itself, in the hope that it might highlight the answer more clearly.&lt;/p&gt;&#xA;&lt;p&gt;Whenever you have a perturbation, you should always have a parameter which represents the strength of that perturbation; let's call it &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;. We now define &lt;em&gt;not&lt;/em&gt; a single perturbed matrix &lt;span class=&quot;math-container&quot;&gt;$\mathrm{H}$&lt;/span&gt;, but a continuous family of matrices &lt;span class=&quot;math-container&quot;&gt;$\mathrm{H}(\alpha)$&lt;/span&gt; such that,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{H}(\alpha) = \mathrm{H}_0 + \alpha \mathrm{H}_1.&#xA;$$&lt;/span&gt;&#xA;Clearly, if &lt;span class=&quot;math-container&quot;&gt;$\alpha=0$&lt;/span&gt; then we recover the original matrix, with its original eigenvalues and eigenvectors, which we assume are known already.&lt;/p&gt;&#xA;&lt;p&gt;Let &lt;span class=&quot;math-container&quot;&gt;$\lambda_i(\alpha)$&lt;/span&gt; be the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th eigenvalue of the perturbed matrix, with the corresponding eigenvector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_i(\alpha)$&lt;/span&gt;, and note that we already know &lt;span class=&quot;math-container&quot;&gt;$\lambda_i(0)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_i(0)$&lt;/span&gt; for all &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The fundamental question perturbation theory addresses is: for small perturbations, how do &lt;span class=&quot;math-container&quot;&gt;$\lambda_i(\alpha)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{u}_i(\alpha)$&lt;/span&gt; depend on &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;When we refer to a &amp;quot;first-order change&amp;quot;, we mean the change which is first-order &lt;em&gt;in the strength of the perturbation&lt;/em&gt;, i.e. &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; in our nomenclature.&lt;/p&gt;&#xA;&lt;p&gt;Now let us turn to your specific example. In this case,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ &#xA;H(\alpha) = H_0 + \alpha H_1 = &#xA;\begin{pmatrix} &#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ &#xA;0 &amp;amp; 0 &amp;amp; 2 &amp;amp; 0\\ &#xA;0 &amp;amp; 2 &amp;amp; 0 &amp;amp; 0\\ &#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 &#xA;\end{pmatrix} &#xA;+ \alpha\begin{pmatrix} &#xA;-0.1 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0\\ &#xA;0 &amp;amp; -0.1 &amp;amp; 0 &amp;amp; 0\\ &#xA;0 &amp;amp; 0 &amp;amp; 0.1 &amp;amp; 0\\ &#xA;0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0.1 &#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&#xA;You ask about the change in the lowest eigenvalue, so let's actually examine it. Varying &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; from -1 to 1, we obtain:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hmCae.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hmCae.png&quot; alt=&quot;Plot of lowest eigenvalue with respect to alpha. The curve is parabolic, with a maximum at alpha=0.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The variation appears parabolic, and by symmetry we can see that the gradient of the curve is zero at &lt;span class=&quot;math-container&quot;&gt;$\alpha=0$&lt;/span&gt;, i.e. &lt;em&gt;the first-order change is zero&lt;/em&gt;, which is what you had already calculated. In other words, the eigenvalue does not actually change appreciably for small perturbations of this form, so the correction is zero.&lt;/p&gt;&#xA;&lt;p&gt;Another way of expressing this is to say that first-order perturbation theory tells you the linear change in the eigenvalue with respect to the perturbation. As you can see from the graph, the linear change is zero at &lt;span class=&quot;math-container&quot;&gt;$\alpha=0$&lt;/span&gt; (your reference Hamiltonian). Clearly, this is not the same as saying that the eigenvalue doesn't change!&lt;/p&gt;&#xA;&lt;p&gt;If you wish to correct the eigenvalue, therefore, you need to either go to a higher order of perturbation, as noted in the other answers, or to change your reference matrix. From the graph, you can see that any matrix with &lt;span class=&quot;math-container&quot;&gt;$\alpha&amp;gt;0$&lt;/span&gt; would give a first-order change in the right direction (though second-order perturbation theory would still be more accurate, of course).&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-04-24T16:10:15.067" LastActivityDate="2022-04-24T16:10:15.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8974" PostTypeId="1" CreationDate="2022-04-24T17:39:29.100" Score="4" ViewCount="61" Body="&lt;p&gt;I need to simulate the off-lattice movement of a polymer chain in a 3D space using Monte Carlo simulation. Note this is not a simulation of polymer growth; rather this is about polymer movement/motion.&lt;/p&gt;&#xA;&lt;p&gt;My polymer is 30 units long, and it should use the bead-spring model.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;From the Page-148 of the book &lt;a href=&quot;https://link.springer.com/book/10.1007/978-3-642-96788-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;Applications of the Monte Carlo Method in Statistical Physics&lt;/a&gt; by K. Binder, I know that bead-spring models use the following Lennard-Jones energy function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$V(r)=&#xA;\begin{cases}&#xA;-V_0\ln\big(1-(\frac{r}{r_0})^2)&amp;amp;; r_0\ge r\\&#xA;0&amp;amp;; r_0\lt r&#xA;\end{cases}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, my professor gave me another function called harmonic spring energy function and told me that I need to use that in combination with the Lennard-Jones energy function:&lt;/p&gt;&#xA;&lt;p&gt;Then the energy of each spring between atoms &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$i+1$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$V=k(d_{i, i+1} - 3.8)^2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where should I apply this function exactly?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-04-24T19:38:24.223" LastActivityDate="2022-04-24T19:38:24.223" Title="Where should I apply the harmonic spring function in the case of polymer simulation?" Tags="|monte-carlo|polymers|atomistic-simulation|energy|" AnswerCount="0" CommentCount="4" ClosedDate="2022-10-30T19:07:46.420" ContentLicense="CC BY-SA 4.0" />
  <row Id="8976" PostTypeId="1" CreationDate="2022-04-25T14:58:28.827" Score="6" ViewCount="704" Body="&lt;p&gt;I'm trying to convert an ORCA output file into MOLDEN file (via molden itself).&lt;/p&gt;&#xA;&lt;p&gt;I hit the &amp;quot;Write&amp;quot; button and it converts the file, yes, but the &lt;em&gt;displacement vector&lt;/em&gt; s are zeros. I need that information in that specific file formatting.&lt;/p&gt;&#xA;&lt;p&gt;What can I do?&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-04-25T14:58:28.827" Title="MOLDEN file from ORCA output" Tags="|orca|molden|" AnswerCount="0" CommentCount="11" ClosedDate="2023-12-09T23:01:20.147" ContentLicense="CC BY-SA 4.0" />
  <row Id="8977" PostTypeId="1" CreationDate="2022-04-25T15:04:02.607" Score="4" ViewCount="59" Body="&lt;p&gt;I am studying nanoclusters in which I have searched the DFT energy landscape and data mining was performed. As the next step, I am trying to prepare a few bulk cut structures but I have no experience in it.&lt;/p&gt;&#xA;&lt;p&gt;What is the general method for obtaining the bulk cut structures?&lt;/p&gt;&#xA;&lt;p&gt;Do you obtain the structures by leaving a structure with correct stoichiometry and removing the rest of the atoms?&lt;/p&gt;&#xA;" OwnerUserId="748" LastEditorUserId="5" LastEditDate="2022-10-26T03:18:41.657" LastActivityDate="2022-10-26T03:18:41.657" Title="How are bulk cut structures obtained?" Tags="|structure|nanostructures|nanoparticles|" AnswerCount="0" CommentCount="5" ClosedDate="2022-12-30T01:43:06.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="8978" PostTypeId="1" AcceptedAnswerId="9038" CreationDate="2022-04-25T16:17:18.597" Score="4" ViewCount="216" Body="&lt;p&gt;I am trying to determine the position of oxygen vacancy in &lt;span class=&quot;math-container&quot;&gt;$\ce{TiO2}$&lt;/span&gt;, is it reasonable to decide it by choosing the configuration with the lowest energy?&lt;/p&gt;&#xA;&lt;p&gt;It doesn't feel quite right to always choose the configuration with the lowest energy, because it means this configuration is quite stable, if I wanna use it as a catalyst, I might want it to be active.&lt;/p&gt;&#xA;&lt;p&gt;What is the rule for deciding the position of defects?&lt;/p&gt;&#xA;&lt;p&gt;According to the minimum energy criterion, the oxygen-3 should be lost and form a vacancy, but it doesn't fit the EXAFS experiment, because when oxygen-3 is lost, there would be two nearest Ti atoms around the Cu atom, but the experiment results show there is only one nearest Ti atom.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RwtMb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RwtMb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-05-08T13:25:14.667" LastActivityDate="2022-05-08T13:25:14.667" Title="Decide the position of oxygen vacancy via the configuration with the lowest energy?" Tags="|density-functional-theory|vasp|geometry-optimization|defects|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="8980" PostTypeId="1" CreationDate="2022-04-25T19:19:57.573" Score="3" ViewCount="79" Body="&lt;p&gt;I was reading a manual on magnetic materials. It discussed the origin of hysteresis of ferromagnetic materials, but it is not clear to me whether or not it depends on anisotropy. I understand that the existence of anisotropy is not necessary for a hysteresis cycle, but I am not sure.&lt;/p&gt;&#xA;" OwnerUserId="1744" LastEditorUserId="5" LastEditDate="2022-08-18T08:12:01.003" LastActivityDate="2022-08-18T08:12:01.003" Title="Does hysteresis depend on anisotropy?" Tags="|magnetism|magnetic-field|" AnswerCount="0" CommentCount="2" ClosedDate="2022-10-26T13:10:09.403" ContentLicense="CC BY-SA 4.0" />
  <row Id="8981" PostTypeId="1" CreationDate="2022-04-26T00:43:04.310" Score="3" ViewCount="81" Body="&lt;p&gt;Are there any methods to find materials in terms of the assigned magnetic point group?&lt;/p&gt;&#xA;&lt;p&gt;For example, I know the magnetic point groups &lt;span class=&quot;math-container&quot;&gt;$6'mm'$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$6'22'$&lt;/span&gt;, and I want to find the corresponding antiferromagnetic materials. How can I do this?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-10-26T03:15:07.043" LastActivityDate="2022-12-12T02:26:56.623" Title="How to find magnetic materials in terms of magnetic point groups?" Tags="|magnetism|symmetry|anti-ferromagnetic|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="8982" PostTypeId="1" AcceptedAnswerId="8983" CreationDate="2022-04-26T04:33:31.477" Score="3" ViewCount="403" Body="&lt;p&gt;I found this source code written by someone:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def get_energy_of_one_atom(atoms_vec,&#xA;                           period_box_len__int,&#xA;                           atom_index__int,&#xA;                           min_atom_distance__float,&#xA;                           max_atom_distance__float):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Evaluates the energy of a single atom&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    en = 0&#xA;    for i in range(len(atoms_vec)):&#xA;        if i == atom_index__int:&#xA;            continue&#xA;        dx = abs(atoms_vec[atom_index__int][0] - atoms_vec[i][0])&#xA;        dy = abs(atoms_vec[atom_index__int][1] - atoms_vec[i][1])&#xA;        &#xA;        dx = dx if dx &amp;lt; period_box_len__int / 2 else period_box_len__int - dx&#xA;        dy = dy if dy &amp;lt; period_box_len__int / 2 else period_box_len__int - dy&#xA;&#xA;        d = math.sqrt(dx ** 2 + dy ** 2)&#xA;        &#xA;        if d &amp;lt; min_atom_distance__float:&#xA;            en += 10000000&#xA;        elif d &amp;lt; max_atom_distance__float:&#xA;            en += -1&#xA;    return en&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This source code calculates the energy of one gas atom in a box.&lt;/p&gt;&#xA;&lt;p&gt;What formula was used here?&lt;/p&gt;&#xA;&lt;p&gt;Can you supply me with a reference?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-04-26T07:12:38.843" Title="Where can I find this formula?" Tags="|molecular-modeling|atomistic-simulation|binding-energy|energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8983" PostTypeId="2" ParentId="8982" CreationDate="2022-04-26T07:12:38.843" Score="8" Body="&lt;p&gt;The formulas that the code is using can be directly read off from the code. The code simulates a two-dimensional periodic box, and calculates the distance of each atom to each other atom, namely d. If d is very small, increase the energy by a very large number. If d is small but not that small, decrease the energy by a very small number.&lt;/p&gt;&#xA;&lt;p&gt;Obviously what the code does here is to treat all atoms as essentially rigid balls with a finite-ranged attraction potential:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V(r) = \left\{\begin{array}{ll}10000000,&amp;amp; r&amp;lt;r_0 \\ -1,&amp;amp; r_0\le r&amp;lt;r_1 \\ 0,&amp;amp; r\ge r_1\end{array} \right.&#xA;$$&lt;/span&gt;&#xA;and compute the energy of the total system. The resulting energy is the exact energy of an atom but with an extremely simplified and unrealistic interaction potential. The code is only applicable for calculating the energy of an atom in that particular toy model, and must be modified if realistic potentials (such as the Lennard-Jones potential) are used. There is no need to give a reference; it's even faster to work out the formulas by yourself than to look for a reference.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-04-26T07:12:38.843" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8984" PostTypeId="1" CreationDate="2022-04-26T09:30:26.883" Score="3" ViewCount="60" Body="&lt;p&gt;I'm researching FePt L10 nanoparticles and want to know how their surfaces affect their magnetic properties. However, I can't seem to find any papers on this topic.&lt;/p&gt;&#xA;&lt;p&gt;Specifically, I would like to know what the magnetic behaviour at {111} surfaces in FePt L10 is like, and how this might affect the behaviour of the particle in general.&lt;/p&gt;&#xA;&lt;p&gt;Questions of interest would be: &amp;quot;Does the {111} surface have significantly lower anisotropy than the {100} and {001} surfaces?&amp;quot;, and &amp;quot;How does a nanoparticle's surface affect its coercivity?&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Is it practically possible to investigate this using DFT or an experiment?&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2022-11-02T17:43:04.187" LastActivityDate="2022-11-02T17:43:04.187" Title="Can you Calculate Magnetism at a Material's Surface?" Tags="|density-functional-theory|surfaces|nanostructures|nanoparticles|" AnswerCount="0" CommentCount="11" ClosedDate="2023-12-09T23:01:02.547" ContentLicense="CC BY-SA 4.0" />
  <row Id="8985" PostTypeId="2" ParentId="8969" CreationDate="2022-04-26T17:59:08.367" Score="2" Body="&lt;p&gt;It depends on why you've made the NEB.&#xA;If to find a possible reaction coordinate, you can use the ∆E as an indicator.&lt;/p&gt;&#xA;&lt;p&gt;Another thing is that you can't perform the &amp;quot;traditional&amp;quot; thermochemistry correction (so diagonalizing the Hessian matrix) because you aren't on a stationary point. I know there are some methods, but I'm not an expert on this so unfortunately, I can't help you by pointing out some literature.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-04-26T17:59:08.367" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8986" PostTypeId="1" CreationDate="2022-04-26T18:19:29.307" Score="3" ViewCount="73" Body="&lt;p&gt;I am using the &lt;strong&gt;Bead-spring model&lt;/strong&gt; to model a polymer chain.&lt;/p&gt;&#xA;&lt;p&gt;Suppose, the polymer has 3 monomers in its chain:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\ce{A1-A2-A3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And,&lt;/p&gt;&#xA;&lt;p&gt;I can use the following formula to calculate the total Lennard-Jones potential:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$U_{LJ}(r) = U_{12}(r_{12}) + U_{23}(r_{23}) + U_{31}(r_{31})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U_{ij}(r_{ij}) = 4 \cdot \epsilon \cdot \left[ \left(\frac{\sigma}{r_{ij}}\right)^{12} -\left(\frac{\sigma}{r_{ij}}\right)^{6} \right]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since we also have two springs here, we have to use the following formula to model the total spring potential:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U_{spring}=U_{1, 2}(r_{1,2}) + U_{2, 3}(r_{2,3})$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U_{i, i+1}=k(r_{i, i+1} - 3.8)^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, the total potential of the polymer chain would be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U_{total} = U_{ij}(r_{ij})+U_{spring}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Now, as far as I know, total &lt;strong&gt;potential&lt;/strong&gt; and total &lt;strong&gt;energy&lt;/strong&gt; are two different things in the case of a polymer.&lt;/p&gt;&#xA;&lt;p&gt;What formula should I use to calculate the total energy of a linear polymer chain?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-04-26T22:54:39.900" Title="What formula should I use to calculate the total energy of a linear polymer chain?" Tags="|monte-carlo|polymers|interatomic-potentials|atomistic-simulation|energy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8987" PostTypeId="1" AcceptedAnswerId="8989" CreationDate="2022-04-26T20:27:19.377" Score="7" ViewCount="383" Body="&lt;p&gt;I'm studing DFT and I would like to know if there is an analytic expression for the first and second order derivatives of the PES obtained through the functional B3LYP. If so, I would need some articles about it.&lt;/p&gt;&#xA;" OwnerUserId="5294" LastActivityDate="2022-04-27T06:27:29.147" Title="Analytic gradient and hessian for B3LYP" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8988" PostTypeId="2" ParentId="8986" CreationDate="2022-04-26T22:52:24.063" Score="4" Body="&lt;p&gt;The difference between total potential energy and total energy is just the kinetic energy, which is the sum of the kinetic energies of your particles, &lt;span class=&quot;math-container&quot;&gt;$$E_K = \frac{1}{2}\sum_{i=1}^3 m_i v_i^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt; are masses and &lt;span class=&quot;math-container&quot;&gt;$v_i$&lt;/span&gt; are velocities.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-04-26T22:54:39.900" LastActivityDate="2022-04-26T22:54:39.900" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8989" PostTypeId="2" ParentId="8987" CreationDate="2022-04-27T06:27:29.147" Score="10" Body="&lt;p&gt;Yes, the expressions for the first and second order derivatives of most common functionals are known. However they include a term (the XC term) that requires numerical integration to calculate. So, although the expressions are analytic, they cannot be evaluated analytically, but rather have to be evaluated numerically.&lt;/p&gt;&#xA;&lt;p&gt;The formulas of DFT energy first order derivatives, including explicit expressions for B3LYP, were reported &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.464906&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, while those of the second order derivatives were reported &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.466887&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-04-27T06:27:29.147" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8990" PostTypeId="2" ParentId="8969" CreationDate="2022-04-27T06:32:28.857" Score="2" Body="&lt;p&gt;To get the Gibbs Free energy from the internal energy, you have to consider the configurational entropy. I anticipate you need the Gibbs Free energy to calculate the activation barrier as a function of the temperature. There are two ways to calculate the activation barrier as a function of temperature, namely, molecular dynamics, and NEB followed by kinetic Monte Carlo. Details of these methods can be found in section 4 of this &lt;a href=&quot;https://www.annualreviews.org/doi/abs/10.1146/annurev-matsci-081420-041617&quot; rel=&quot;nofollow noreferrer&quot;&gt;review&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3923" LastEditorUserId="1788" LastEditDate="2022-04-27T15:16:56.397" LastActivityDate="2022-04-27T15:16:56.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8991" PostTypeId="1" CreationDate="2022-04-27T13:16:59.267" Score="4" ViewCount="53" Body="&lt;p&gt;I want to simulate the collision between two gas giants, the inner layer of gas giant contains the layer of metallic hydrogen and a solid core, if two gas giants collide then the abrubt variation of pressure and temperature may cause the phase change of metallic hydrogen, so in order to simulate the collision between two gas giants precisely we must consider the phase change of metallic hydrogen, so could you please recommend some textbook or paper on the large scale simulation about phase change of metallic hydrogen during the change of pressure and temperature?&lt;/p&gt;&#xA;" OwnerUserId="5319" LastEditorUserId="5" LastEditDate="2022-05-02T04:57:23.723" LastActivityDate="2022-05-02T04:57:23.723" Title="Recommendation for some papers on simulation of metallic metal" Tags="|reference-request|high-performance-computing|physical-properties-of-materials|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="8992" PostTypeId="1" CreationDate="2022-04-27T16:03:24.543" Score="16" ViewCount="632" Body="&lt;p&gt;Through this post I am looking to create a resourceful list of textbooks for any one interested in electronic structure theory.&lt;/p&gt;&#xA;&lt;p&gt;The focus here is to create mostly a mutually exclusive list of answers with some insightful comments or notes. These include books on molecular electronic structure or text specifically focusing on computational aspects.&lt;/p&gt;&#xA;" OwnerDisplayName="user784" LastEditorUserId="7" LastEditDate="2022-04-27T20:44:26.323" LastActivityDate="2022-05-11T14:39:12.607" Title="Textbooks for electronic structure theory" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|electronic-structure|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8993" PostTypeId="2" ParentId="8992" CreationDate="2022-04-27T20:46:32.190" Score="10" Body="&lt;p&gt;(We should add short descriptions to each of these as well as any new additions. Additionally, it would be good to break this list into categories, e.g. general, DFT, post-HF and many-body theories):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;McWeeny, R. (1989). Method of molecular quantum mechanics. 2nd edition.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Szabo, A., &amp;amp; Ostlund, N. S. (2012). Modern quantum chemistry: introduction to advanced electronic structure theory.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Levine, I. N. (2000). Quantum chemistry.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Parr, R. G. (1980). Density functional theory of atoms and molecules. Springer, Dordrecht.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Cook, D. B. (2005). Handbook of computational quantum chemistry. Courier Corporation.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Piela, Lucjan. (2006). Ideas of quantum chemistry. Elsevier&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Koch, W., &amp;amp; Holthausen, M. C. (2015). A chemist's guide to density functional theory. John Wiley &amp;amp; Sons.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Helgaker, T., Jorgensen, P., &amp;amp; Olsen, J. (2014). Molecular electronic-structure theory. John Wiley &amp;amp; Sons.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Wilson, S. (2014). Electron correlation in molecules. Courier Corporation.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Jensen, Frank (2017). Introduction to Quantum Chemistry. 3rd ed. Wiley&lt;/strong&gt;:&#xA;This is an introductory book about quantum chemistry in general. It covers a broad range of topics, starting from the basics of Schrodinger equation, to Hartree-Fock, preturbation theory, coupled-cluster and configuration interaction, relativistic methods. It also deals with basis sets, wave function analyses, calculation of molecular properties, semi-empirical methods and empirical force fields. Mathematical derivations and formulae are provided but they are not the main focus of the book. Overall an excellent book that touches on almost all aspects of modern computational chemistry&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Cramer, Christopher (2004). Essentials of Computational Chemistry: Theories and Models, 2nd Edition, Wiley&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7" LastEditorDisplayName="user784" LastEditDate="2022-05-11T14:39:12.607" LastActivityDate="2022-05-11T14:39:12.607" CommentCount="2" CommunityOwnedDate="2022-04-27T20:46:32.190" ContentLicense="CC BY-SA 4.0" />
  <row Id="8995" PostTypeId="1" CreationDate="2022-04-28T00:01:25.090" Score="5" ViewCount="51" Body="&lt;p&gt;The 0001 and 000-1 surfaces of ZnO are polar, while the other surfaces like 101̅0 and 112̅0 are nonpolar (see &lt;a href=&quot;https://doi.org/10.1021/acs.chemmater.7b01487&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;).&#xA;How can one determine what is the polarity of any surface?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2022-08-18T08:15:40.087" LastActivityDate="2022-08-18T08:15:40.087" Title="How to find the polarity of a surface (such as ZnO 000-1)?" Tags="|surfaces|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="8996" PostTypeId="1" CreationDate="2022-04-28T00:21:33.207" Score="3" ViewCount="130" Body="&lt;p&gt;Suppose, a polymer has &lt;em&gt;N&lt;/em&gt; monomers in its chain. I want to simulate its movement using the &lt;strong&gt;bead-spring&lt;/strong&gt; model.&lt;/p&gt;&#xA;&lt;p&gt;So, I wrote the following program in &lt;em&gt;&lt;strong&gt;Python&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/mns-csharp/PolymerSimulation__Python/blob/master/polymer.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;Polymer chain simulation with Monte Carlo method&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I am using 0.1 million steps. The energy is not fluctuating as expected. After several steps, the curve goes totally flat.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/g9X1R.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/g9X1R.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The X-axis is steps. Y-axis is total energy.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone check the source code and tell me what I should change?&lt;/p&gt;&#xA;&lt;p&gt;N.B. I am especially concerned with the function that calculates the total energy of the polymer.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-05-03T04:23:50.720" LastActivityDate="2022-05-03T04:23:50.720" Title="Molecular MC simulation is not equilibrating" Tags="|python|monte-carlo|polymers|atomistic-simulation|" AnswerCount="0" CommentCount="19" ClosedDate="2022-08-20T01:40:14.207" ContentLicense="CC BY-SA 4.0" />
  <row Id="8997" PostTypeId="1" AcceptedAnswerId="8998" CreationDate="2022-04-28T14:24:13.617" Score="6" ViewCount="141" Body="&lt;p&gt;I want to solve a Jellium-DFT like problem. Does any of the self-consistent/DFT software packages available allow to solve for the case of a Jellium configuration (no lattice)?&lt;/p&gt;&#xA;&lt;p&gt;If not I would like to find a hand-on solution to a similar problem. I want to understand how to apply Kohn-Sham equations to a metal surface. I understand the equations but I would like to understand the ansatz and the numerical methods.&lt;/p&gt;&#xA;" OwnerUserId="5321" LastActivityDate="2022-04-28T16:24:08.660" Title="Are there any available tools to implement Jellium models?" Tags="|density-functional-theory|potential-energy-surface|metals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8998" PostTypeId="2" ParentId="8997" CreationDate="2022-04-28T16:24:08.660" Score="4" Body="&lt;p&gt;The GPAW density functional theory code has a jellium mode (tutorials &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/tutorialsexercises/electrostatics/jellium/jellium.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). There is, e.g., a &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/_modules/gpaw/jellium.html#JelliumSlab&quot; rel=&quot;nofollow noreferrer&quot;&gt;JelliumSlab&lt;/a&gt; class, where the charge neutralizing jellium background does not extend over all space, but is confined to a slab to model jellium surfaces.&lt;/p&gt;&#xA;" OwnerUserId="5250" LastActivityDate="2022-04-28T16:24:08.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="8999" PostTypeId="1" AcceptedAnswerId="9001" CreationDate="2022-04-28T20:38:12.413" Score="2" ViewCount="596" Body="&lt;p&gt;According to &lt;a href=&quot;https://en.wikipedia.org/wiki/Periodic_boundary_conditions&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia&lt;/a&gt; -&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Periodic boundary conditions (PBCs) are a set of boundary conditions that are often chosen for approximating a large (infinite) system by using a small part called a unit cell.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When we are generating new locations in a box/cell, we can use a random number generator such that the locations never cross the boundary of that box/cell. Therefore, from the implementation point of view, we don't need periodic boundary conditions.&lt;/p&gt;&#xA;&lt;p&gt;So, my question is, why do we even need periodic boundary conditions?&lt;/p&gt;&#xA;&lt;p&gt;Wouldn't our simulations attain equilibration if we only use random numbers?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-04-29T01:59:29.457" Title="Why do we even need periodic boundary conditions?" Tags="|monte-carlo|atomistic-simulation|periodic-boundary-conditions|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9000" PostTypeId="1" CreationDate="2022-04-29T01:06:10.830" Score="1" ViewCount="82" Body="&lt;p&gt;I optimize the ecutwfc for one sulphur vacancy on 221 MoS2 monolayer in Quantum Espresso. From the attached data, which is the correct converged ecutwfc.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Wq4zJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Wq4zJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XhOhP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XhOhP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3687" LastActivityDate="2022-05-27T20:51:40.147" Title="Convergence of ecutwfc for Sulphur vacant 221MoS2 monolayer" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9001" PostTypeId="2" ParentId="8999" CreationDate="2022-04-29T01:41:30.360" Score="4" Body="&lt;p&gt;In (Metropolis) Monte Carlo one should be generating random changes in coordinates such that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    X_{new} = X_{old} + \Delta X&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and we used a random number to generate &lt;span class=&quot;math-container&quot;&gt;$\Delta X$&lt;/span&gt;. So by all means, the particles have no reason to stop at a boundary provided the &lt;span class=&quot;math-container&quot;&gt;$\Delta X$&lt;/span&gt; tells them to cross it. I don't know how one would keep particles inside a boundary &lt;em&gt;without&lt;/em&gt; periodic boundary conditions.&lt;/p&gt;&#xA;&lt;p&gt;If one was to bias the generation of &lt;span class=&quot;math-container&quot;&gt;$\Delta X$&lt;/span&gt; in some way, we would probably not be maintaining &lt;a href=&quot;https://en.wikipedia.org/wiki/Detailed_balance&quot; rel=&quot;nofollow noreferrer&quot;&gt;detailed balance&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There are cases where particles cannot cross a boundary, however, one needs to account for a physical boundary, such as in a nanopore or molecular sieve, by making a real boundary that interacts with particles.&lt;/p&gt;&#xA;&lt;p&gt;If there is no periodic boundary conditions, rather than simulating a bulk fluid we will be simulating some cluster of molecules with a very real surface tension contribution that cannot be ignored. Some people study droplets, so this makes sense. However, if we want to study bulk fluids, we cannot have a system with such a large surface tension contribution.&lt;/p&gt;&#xA;&lt;p&gt;It is a good idea to compare the simulation with what one is trying to model, and make sure the simulation reflects the reality of ones interests.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-04-29T01:59:29.457" LastActivityDate="2022-04-29T01:59:29.457" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9002" PostTypeId="1" CreationDate="2022-04-29T02:39:44.610" Score="4" ViewCount="139" Body="&lt;p&gt;I am trying to do DFPT, during the process of moving in different directions, even I set &lt;code&gt;EIDFF=1E-8&lt;/code&gt;, the corresponding ionic step is not converged, the relative error is very large, so why doesn't VASP continue the iteration process until it converges?&lt;/p&gt;&#xA;&lt;p&gt;Here is the output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1     0.943832900927E+04    0.94383E+04   -0.31019E+05  1568   0.155E+03&#xA;DAV:   2     0.120322296929E+04   -0.82351E+04   -0.77605E+04  1600   0.482E+02&#xA;DAV:   3    -0.566044087668E+03   -0.17693E+04   -0.17269E+04  1984   0.216E+02&#xA;DAV:   4    -0.730799870749E+03   -0.16476E+03   -0.16421E+03  2448   0.706E+01&#xA;DAV:   5    -0.746630469831E+03   -0.15831E+02   -0.15819E+02  2672   0.179E+01    0.116E+02&#xA;DAV:   6    -0.555587568867E+03    0.19104E+03   -0.36240E+02  2432   0.560E+01    0.544E+01&#xA;DAV:   7    -0.531278321675E+03    0.24309E+02   -0.26762E+02  2384   0.354E+01    0.311E+01&#xA;DAV:   8    -0.531683478231E+03   -0.40516E+00   -0.74971E+01  2304   0.206E+01    0.253E+01&#xA;DAV:   9    -0.529663432837E+03    0.20200E+01   -0.79646E+00  2256   0.806E+00    0.118E+01&#xA;DAV:  10    -0.529236425075E+03    0.42701E+00   -0.46911E+00  2400   0.699E+00    0.472E+00&#xA;DAV:  11    -0.529378614859E+03   -0.14219E+00   -0.91241E-01  2288   0.386E+00    0.268E+00&#xA;DAV:  12    -0.529464524587E+03   -0.85910E-01   -0.16204E-01  2432   0.129E+00    0.174E+00&#xA;DAV:  13    -0.529468617306E+03   -0.40927E-02   -0.10825E-01  2144   0.130E+00    0.614E-01&#xA;DAV:  14    -0.529480576235E+03   -0.11959E-01   -0.14206E-02  2368   0.319E-01    0.341E-01&#xA;DAV:  15    -0.529481318684E+03   -0.74245E-03   -0.43508E-03  2384   0.195E-01    0.237E-01&#xA;DAV:  16    -0.529482513141E+03   -0.11945E-02   -0.28780E-03  2352   0.118E-01    0.161E-01&#xA;DAV:  17    -0.529482663314E+03   -0.15017E-03   -0.78386E-04  2640   0.100E-01    0.940E-02&#xA;DAV:  18    -0.529482716807E+03   -0.53493E-04   -0.64189E-04  2368   0.579E-02    0.676E-02&#xA;DAV:  19    -0.529482786496E+03   -0.69688E-04   -0.15945E-04  2496   0.355E-02    0.508E-02&#xA;DAV:  20    -0.529482815409E+03   -0.28914E-04   -0.59057E-05  2528   0.303E-02    0.242E-02&#xA;DAV:  21    -0.529482810547E+03    0.48627E-05   -0.27668E-05  2240   0.154E-02    0.155E-02&#xA;DAV:  22    -0.529482810966E+03   -0.41971E-06   -0.70934E-06  2480   0.805E-03    0.110E-02&#xA;DAV:  23    -0.529482810372E+03    0.59453E-06   -0.37045E-06  2368   0.663E-03    0.373E-03&#xA;DAV:  24    -0.529482809499E+03    0.87283E-06   -0.74638E-07  2256   0.249E-03    0.220E-03&#xA;DAV:  25    -0.529482809648E+03   -0.14864E-06   -0.15244E-07  2320   0.115E-03    0.139E-03&#xA;DAV:  26    -0.529482809339E+03    0.30858E-06   -0.37618E-08  1952   0.738E-04    0.741E-04&#xA;DAV:  27    -0.529482809357E+03   -0.18343E-07   -0.56623E-09  1584   0.579E-04    0.354E-04&#xA;DAV:  28    -0.529482809319E+03    0.38337E-07    0.71730E-09   976   0.252E-04    0.172E-04&#xA;DAV:  29    -0.529482809318E+03    0.14479E-08    0.14346E-08   864   0.172E-04&#xA;   1 F= -.52948281E+03 E0= -.52948281E+03  d E =-.306981E-07  mag=     1.0000&#xA; Linear response reoptimize wavefunctions&#xA;DAV:   1    -0.529482809344E+03   -0.26288E-07    0.15377E-08   864   0.136E-04&#xA;DAV:   2    -0.529482809343E+03    0.12224E-08    0.16366E-08   864   0.694E-05&#xA;DAV:   3    -0.529482809342E+03    0.29104E-09    0.16838E-08   864   0.460E-05&#xA; Linear response DOF=         159&#xA; Linear response progress:&#xA;  Degree of freedom:   1/159&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;RMM:   1    -0.366569662500E+00   -0.36657E+00    0.14851E-01  3571   0.732E-01&#xA;RMM:   2    -0.347281208720E+00    0.19288E-01   -0.33190E-02  3401   0.234E-01    0.233E-01&#xA;RMM:   3    -0.342371021787E+00    0.49102E-02   -0.45993E-03  3743   0.803E-02    0.183E-01&#xA;RMM:   4    -0.342236118255E+00    0.13490E-03   -0.51509E-03  3981   0.449E-02    0.121E-01&#xA;RMM:   5    -0.342405405393E+00   -0.16929E-03   -0.39179E-03  3769   0.377E-02    0.388E-02&#xA;RMM:   6    -0.342664154463E+00   -0.25875E-03   -0.30982E-03  4296   0.204E-02    0.259E-02&#xA;RMM:   7    -0.342527856828E+00    0.13630E-03   -0.38206E-03  4349   0.123E-02    0.183E-02&#xA;RMM:   8    -0.342519133662E+00    0.87232E-05   -0.46169E-03  4228   0.928E-03    0.577E-03&#xA;RMM:   9    -0.342319480517E+00    0.19965E-03   -0.35038E-03  4393   0.671E-03    0.419E-03&#xA;RMM:  10    -0.342399184298E+00   -0.79704E-04   -0.41299E-03  4472   0.513E-03    0.347E-03&#xA;RMM:  11    -0.342345713946E+00    0.53470E-04   -0.37327E-03  4378   0.434E-03    0.254E-03&#xA;RMM:  12    -0.342325211772E+00    0.20502E-04   -0.34263E-03  4399   0.391E-03    0.174E-03&#xA;RMM:  13    -0.342353781636E+00   -0.28570E-04   -0.37494E-03  4427   0.360E-03    0.168E-03&#xA;RMM:  14    -0.342351252543E+00    0.25291E-05   -0.38598E-03  4359   0.345E-03    0.985E-04&#xA;RMM:  15    -0.342306093782E+00    0.45159E-04   -0.33549E-03  4313   0.337E-03    0.403E-04&#xA;RMM:  16    -0.342430722702E+00   -0.12463E-03   -0.44952E-03  4420   0.328E-03    0.391E-04&#xA; Linear response progress:&#xA;  Degree of freedom:   2/159&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="1788" LastEditDate="2022-05-04T14:30:26.887" LastActivityDate="2022-05-04T14:30:49.067" Title="The ionic step is not convergent when doing DFPT in VASP" Tags="|vasp|dfpt|" AnswerCount="0" CommentCount="7" ClosedDate="2022-12-12T15:17:00.323" ContentLicense="CC BY-SA 4.0" />
  <row Id="9003" PostTypeId="2" ParentId="8969" CreationDate="2022-04-29T02:48:32.313" Score="4" Body="&lt;p&gt;I think the first question you have to ask is whether you can get an accurate free energy for your reaction barrier in VASP. If you have a reaction with a small molecule on an oxide surface under vacuum, the configurational entropy may be insignificant. In this case, a vibrational analysis (correcting for ZPE and possibly vibrational entropy) at the transition state may be appropriate. The total correction will likely be small in this case.&lt;/p&gt;&#xA;&lt;p&gt;For a vibrational calculation, you can just use IBRION=-5 and NFREE=2 as shown on the VASPwiki. For the TS, you should get a single nonreal frequency because you're at a saddlepoint. You can use these frequencies to get the ZPE correction and the vibrational entropy from the harmonic oscillator equations. I'll reproduce the harmonic oscillator entropy equation here:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation} S = -Nk_{b}(1-e^{-\beta \epsilon }) + Nk_{b}\frac{\beta \epsilon }{e^{\beta \epsilon } -1} \end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, for a molecule in solution or a solvated interface, simple vibrational analysis will not describe the entropy of the system very well. Unless you're willing to use a more advanced sampling method, you may just want to report the enthalpic barrier.&lt;/p&gt;&#xA;" OwnerUserId="5199" LastActivityDate="2022-04-29T02:48:32.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9004" PostTypeId="1" AcceptedAnswerId="9013" CreationDate="2022-04-29T13:32:16.677" Score="3" ViewCount="903" Body="&lt;p&gt;When I try to calculate the vibration frequency of TiO2, I set IBRION=5 in VASP, but it turns out I couldn't use NCORE&amp;gt;1 in this situation, once I use NCORE&amp;gt;1, VASP would run for only one ionic step, and then stop.&lt;br&gt;&#xA;Is this some kind of bug or there is a more complicated reason?&lt;/p&gt;&#xA;&lt;p&gt;Here is the error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA; running on   64 total cores&#xA; distrk:  each k-point on   16 cores,    4 groups&#xA; distr:  one band on   16 cores,    1 groups&#xA; vasp.6.3.0 20Jan22 (build Apr 21 2022 08:28:17) gamma-only                     &#xA;  &#xA; POSCAR found type information on POSCAR H C O TiCu&#xA; POSCAR found :  5 types and      79 ions                                                                           &#xA; scaLAPACK will be used&#xA; WARNING: type information on POSCAR and POTCAR are incompatible&#xA; POTCAR overwrites the type information in POSCAR&#xA; typ   2 type information:  C  H &#xA; LDA part: xc-table for Pade appr. of Perdew&#xA; POSCAR found type information on POSCAR H C O TiCu&#xA; POSCAR found :  5 types and      79 ions&#xA; POSCAR, INCAR and KPOINTS ok, starting setup&#xA; FFT: planning ... GRIDC&#xA; FFT: planning ... GRID_SOFT&#xA; FFT: planning ... GRID&#xA; WAVECAR not read&#xA; WARNING: random wavefunctions but no delay for mixing, default for NELMDL&#xA; entering main loop&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1     0.962189968479E+04    0.96219E+04   -0.31354E+05  1592   0.156E+03&#xA;DAV:   2     0.120501156595E+04   -0.84169E+04   -0.79375E+04  1648   0.488E+02&#xA;DAV:   3    -0.572351588775E+03   -0.17774E+04   -0.17336E+04  1832   0.220E+02&#xA;DAV:   4    -0.739169994137E+03   -0.16682E+03   -0.16573E+03  2264   0.724E+01&#xA;DAV:   5    -0.761486083389E+03   -0.22316E+02   -0.22300E+02  2984   0.236E+01    0.117E+02&#xA;DAV:   6    -0.584545650497E+03    0.17694E+03   -0.37934E+02  2344   0.560E+01    0.549E+01&#xA;DAV:   7    -0.557399994994E+03    0.27146E+02   -0.28287E+02  2392   0.362E+01    0.304E+01&#xA;DAV:   8    -0.557759287444E+03   -0.35929E+00   -0.66876E+01  2232   0.188E+01    0.246E+01&#xA;DAV:   9    -0.556156575211E+03    0.16027E+01   -0.77852E+00  2192   0.798E+00    0.110E+01&#xA;DAV:  10    -0.556308157936E+03   -0.15158E+00   -0.35423E+00  2520   0.597E+00    0.479E+00&#xA;DAV:  11    -0.556383556331E+03   -0.75398E-01   -0.65556E-01  2304   0.385E+00    0.275E+00&#xA;DAV:  12    -0.556459162071E+03   -0.75606E-01   -0.17827E-01  2496   0.156E+00    0.146E+00&#xA;DAV:  13    -0.556467749346E+03   -0.85873E-02   -0.82389E-02  2288   0.116E+00    0.625E-01&#xA;DAV:  14    -0.556480246505E+03   -0.12497E-01   -0.14617E-02  2288   0.331E-01    0.379E-01&#xA;DAV:  15    -0.556481372663E+03   -0.11262E-02   -0.45098E-03  2352   0.197E-01    0.255E-01&#xA;DAV:  16    -0.556483184852E+03   -0.18122E-02   -0.29763E-03  2312   0.151E-01    0.163E-01&#xA;DAV:  17    -0.556483432934E+03   -0.24808E-03   -0.11567E-03  2600   0.113E-01    0.908E-02&#xA;DAV:  18    -0.556483568698E+03   -0.13576E-03   -0.45184E-04  2368   0.612E-02    0.620E-02&#xA;DAV:  19    -0.556483608223E+03   -0.39525E-04   -0.10142E-04  2560   0.309E-02    0.524E-02&#xA;DAV:  20    -0.556483626361E+03   -0.18139E-04   -0.30529E-05  2432   0.294E-02    0.287E-02&#xA;DAV:  21    -0.556483616771E+03    0.95909E-05   -0.27797E-05  2336   0.183E-02    0.151E-02&#xA;DAV:  22    -0.556483613639E+03    0.31321E-05   -0.84747E-06  2288   0.829E-03    0.110E-02&#xA;DAV:  23    -0.556483612230E+03    0.14088E-05   -0.43880E-06  2328   0.576E-03    0.608E-03&#xA;DAV:  24    -0.556483609819E+03    0.24112E-05   -0.10952E-06  2280   0.400E-03    0.348E-03&#xA;DAV:  25    -0.556483609611E+03    0.20781E-06   -0.62687E-07  2272   0.185E-03    0.185E-03&#xA;DAV:  26    -0.556483609690E+03   -0.78908E-07   -0.69696E-08  1816   0.737E-04    0.159E-03&#xA;DAV:  27    -0.556483609605E+03    0.85107E-07   -0.26865E-08  1400   0.463E-04    0.141E-03&#xA;DAV:  28    -0.556483609564E+03    0.40040E-07   -0.72716E-09   960   0.259E-04    0.137E-03&#xA;DAV:  29    -0.556483609543E+03    0.21508E-07   -0.34761E-09   880   0.201E-04    0.135E-03&#xA;DAV:  30    -0.556483609552E+03   -0.86002E-08   -0.18163E-09   880   0.131E-04&#xA;   1 F= -.55648361E+03 E0= -.55648209E+03  d E =-.304676E-02  mag=     1.0400&#xA; Finite differences POTIM= 0.01000 DOF= 141&#xA; -----------------------------------------------------------------------------&#xA;|                                                                             |&#xA;|     EEEEEEE  RRRRRR   RRRRRR   OOOOOOO  RRRRRR      ###     ###     ###     |&#xA;|     E        R     R  R     R  O     O  R     R     ###     ###     ###     |&#xA;|     E        R     R  R     R  O     O  R     R     ###     ###     ###     |&#xA;|     EEEEE    RRRRRR   RRRRRR   O     O  RRRRRR       #       #       #      |&#xA;|     E        R   R    R   R    O     O  R   R                               |&#xA;|     E        R    R   R    R   O     O  R    R      ###     ###     ###     |&#xA;|     EEEEEEE  R     R  R     R  OOOOOOO  R     R     ###     ###     ###     |&#xA;|                                                                             |&#xA;|     VASP internal routines have requested a change of the k-point set.      |&#xA;|     Unfortunately, this is only possible if NPAR=number of nodes.           |&#xA;|     Please remove the tag NPAR from the INCAR file and restart the          |&#xA;|     calculation.                                                            |&#xA;|                                                                             |&#xA;|       ----&amp;gt;  I REFUSE TO CONTINUE WITH THIS SICK JOB ... BYE!!! &amp;lt;----       |&#xA;|                                                                             |&#xA; -----------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="697" LastEditDate="2022-04-30T17:39:56.783" LastActivityDate="2022-04-30T17:39:56.783" Title="NCORE bigger than 1 when performing phonon/vibrational calculation(IBRION=5) in VASP?" Tags="|vasp|software-assistance|vibrations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9005" PostTypeId="1" AcceptedAnswerId="9007" CreationDate="2022-04-29T16:13:22.070" Score="7" ViewCount="311" Body="&lt;p&gt;I am trying to reproduce the cyclooctatetraene isometrization process pulished &lt;a href=&quot;https://pubmed.ncbi.nlm.nih.gov/23508351/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;In figure 3 of the paper, it shows the potential energy surface as a variable of the polar angle using the CAS(8,8) method. I am new to this field and I already learnt how to optimize the molecular geometry with simple control of degrees of freedom, like fix the bond dimension for certain atoms. However, generating the molecular geometry for system that complex seems challenging. Can someone tell me how to do this?&lt;/p&gt;&#xA;" OwnerUserId="2043" LastActivityDate="2022-04-29T20:54:41.997" Title="Molecular geometry optimization for cyclooctatetraene with pyscf" Tags="|geometry-optimization|pyscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9006" PostTypeId="1" AcceptedAnswerId="9009" CreationDate="2022-04-29T17:11:04.693" Score="5" ViewCount="332" Body="&lt;p&gt;I want to understand ORCA output for CIS calculations.&#xA;From the input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! RHF 6-31G&#xA;%cis&#xA;    Nroots 1&#xA;    MaxDim 2&#xA;end&#xA;    &#xA;%coords&#xA;    CTyp xyz       # the type of coordinates = xyz or internal&#xA;    Charge 0       # the total charge of the molecule&#xA;    Mult 1         # the multiplicity = 2S+1&#xA;    Units Angs     # the unit of length = angs or bohrs&#xA;    coords&#xA;        He        0.000000       0.00000        0.00000&#xA;    end&#xA;end&#xA;%output&#xA;    Print[ P_Basis ] 2&#xA;    Print[ P_MOs ] 1&#xA;end &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get SCF results&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;----------------&#xA;ORBITAL ENERGIES&#xA;----------------&#xA;&#xA;  NO   OCC          E(Eh)            E(eV) &#xA;   0   2.0000      -0.914127       -24.8747 &#xA;   1   0.0000       1.399859        38.0921 &#xA;------------------&#xA;MOLECULAR ORBITALS&#xA;------------------&#xA;                      0         1   &#xA;                  -0.91413   1.39986&#xA;                   2.00000   0.00000&#xA;                  --------  --------&#xA;  0He  1s        -0.592081  1.149818&#xA;  0He  2s        -0.513586 -1.186959&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and CIS results&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-----------------------------&#xA;CIS-EXCITED STATES (SINGLETS)&#xA;-----------------------------&#xA;&#xA;the weight of the individual excitations are printed if larger than 1.0e-02&#xA;&#xA;STATE  1:  E=   1.911194 au     52.006 eV   419458.5 cm**-1 &amp;lt;S**2&amp;gt; =   0.000000&#xA;     0a -&amp;gt;   1a  :     1.000000 (c=  1.00000000)&#xA;-----------------------&#xA;CIS/TD-DFT TOTAL ENERGY&#xA;-----------------------&#xA;&#xA;    E(SCF)  =     -2.855160426 Eh&#xA;    DE(CIS) =      1.911193623 Eh (Root  1)&#xA;    ----------------------------- ---------&#xA;    E(tot)  =     -0.943966803 Eh&#xA;&#xA;&#xA;-------------------------   --------------------&#xA;FINAL SINGLE POINT ENERGY        -0.943966803492&#xA;-------------------------   --------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The CIS method states&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The solution of the Hartree-Fock equations gives a set of &lt;span class=&quot;math-container&quot;&gt;$ M $&lt;/span&gt; spin orbitals, and&#xA;to construct Slater's determinant use only &lt;span class=&quot;math-container&quot;&gt;$ N $&lt;/span&gt;, which orrespond to the minimum orbital energies (Aufbau principle).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Some of the remaining &lt;span class=&quot;math-container&quot;&gt;$ M-N $&lt;/span&gt; functions (corresponding to virtual orbitals) are used to construct additional Slater determinants.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;em&gt;These determinants are obtained by substituting a certain number of spin orbitals of the original determinant &lt;span class=&quot;math-container&quot;&gt;$ \Phi^{0} $&lt;/span&gt; for the corresponding number of virtual spin orbitals. The obtained determinants are called excited and are denoted as &lt;span class=&quot;math-container&quot;&gt;$\Phi_K $&lt;/span&gt;.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;The wave function has the form:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation*}\label{}&#xA;                \Phi = \Phi^{0} + \sum_{K = 1}^{L} C_K\Phi_K.&#xA;            \end{equation*}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;The search for &lt;span class=&quot;math-container&quot;&gt;$ \Phi $&lt;/span&gt; is reduced to the variational problem of minimizing electronic energy by varying the coefficients &lt;span class=&quot;math-container&quot;&gt;$ C_K $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When forming the set &lt;span class=&quot;math-container&quot;&gt;$ \{\Phi_K\}_ {1, \ldots, L} $&lt;/span&gt; often are limited to determinants, single- and double-excited with respect to &lt;span class=&quot;math-container&quot;&gt;$ \Phi^{0} $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{multline*}\label{ECIS}\tag{ECIS}&#xA;E_{CI} = \langle{\Phi^{0} + \sum_{K = 1}^{L} C_K\Phi_K}{|\hat{H}|}{\Phi^{0} + \sum_{P = 1}^{L} C_P\Phi_P}\rangle = \\&#xA;= \langle{\Phi^{0}}{|\hat{H}|}{\Phi^{0}\rangle} + \langle{\sum_{K = 1}^{L} C_K\Phi_K}{|\hat{H}|}{\sum_{P = 1}^{L} C_P\Phi_P}\rangle \\ \approx E_{HF} + \Delta E.&#xA;\end{multline*}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$L = 2$&lt;/span&gt;, for example, from \eqref{ECIS}&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;   E_{CI} = E_{HF} + |C_1|^2 H_{11} + |C_2|^2 H_{22} + 2C_1C_2 H_{12}&#xA;$$&lt;/span&gt;&#xA;So, where &lt;span class=&quot;math-container&quot;&gt;$C_K$&lt;/span&gt;'s in ORCA output and how did it calculate the excitation energy (where to read the sane information)? Globally, what do all the obtained values mean and how can they be compared with the theory?&lt;/p&gt;&#xA;" OwnerUserId="5264" LastEditorUserId="5264" LastEditDate="2022-04-29T19:23:55.210" LastActivityDate="2022-04-30T05:25:09.007" Title="ORCA: CIS calculation for Helium atom" Tags="|orca|configuration-interaction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9007" PostTypeId="2" ParentId="9005" CreationDate="2022-04-29T17:15:27.283" Score="9" Body="&lt;p&gt;I'm not 100% sure I know what you want. But let's walk through creating rough geometries for the different structures in the paper.&lt;/p&gt;&#xA;&lt;p&gt;I'm going to use Avogadro, but it should be possible to do this in most editors.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;First off, I created the planar &lt;span class=&quot;math-container&quot;&gt;$D_{4h}$&lt;/span&gt; geometry.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CDP7Om.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CDP7Om.png&quot; alt=&quot;planar cyclooctatetraene&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I drew this planar, then optimized with a constraint that only the X and Y positions could change and Z was constrained.&lt;/p&gt;&#xA;&lt;p&gt;If you're optimizing this in a quantum program, you probably want to use a z-matrix and constrain the angles and dihedrals, see below.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Next, there's the fully planar &lt;span class=&quot;math-container&quot;&gt;$D_{8h}$&lt;/span&gt; starting point. This is not stable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Going from the planar &lt;span class=&quot;math-container&quot;&gt;$D_{4h}$&lt;/span&gt; geometry, you can tweak the z-matrix input to ensure there's only one average C-C bond length, one C-C angle, one C-H length, C-H angle, etc., e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C  &#xA;C   1 B1&#xA;C   2 B1 1 A2&#xA;C   3 B1 2 A2 1 D3&#xA;C   4 B1 3 A2 2 D4&#xA;C   5 B1 4 A2 3 D5&#xA;C   6 B1 5 A2 4 D6&#xA;C   1 B1 2 A2 3 D7&#xA;Variables:&#xA;B1        1.40&#xA;A2      135.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Finally, you need to create one of the &lt;span class=&quot;math-container&quot;&gt;$D_{2d}$&lt;/span&gt; &amp;quot;tub&amp;quot; geometries. I find these the easiest to make. If you just nudge some atoms up and down in the Z-direction, this will optimize fully. (In the z-matrix, just make the dihedral angles individual variables.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zYVgXm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zYVgXm.png&quot; alt=&quot;&amp;quot;tub&amp;quot; cyclooctatetraene&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In principal, you should restrict &lt;em&gt;some&lt;/em&gt; of the dihedral angle variables for the &lt;span class=&quot;math-container&quot;&gt;$D_{2d}$&lt;/span&gt; geometry so they're identical. My experience is that with modern codes, if you break the plane and start to optimize, you should end up with the &lt;span class=&quot;math-container&quot;&gt;$D_{2d}$&lt;/span&gt; geometry or very close to it (such that you can run a symmetry-broken optimization, then enforce symmetry and re-run).&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="7" LastEditDate="2022-04-29T20:54:41.997" LastActivityDate="2022-04-29T20:54:41.997" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9008" PostTypeId="1" CreationDate="2022-04-30T03:19:55.177" Score="10" ViewCount="900" Body="&lt;p&gt;I want to calculate phonon band structure using VASP for a double perovskite &lt;span class=&quot;math-container&quot;&gt;$\ce{A2BB'X6}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Most of the perovskites are well known for dynamical instability at &lt;span class=&quot;math-container&quot;&gt;$\pu{0K}$&lt;/span&gt; but show a dynamically stable nature at &lt;span class=&quot;math-container&quot;&gt;$\pu{300K}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can I calculate phonon band structure using VASP at &lt;span class=&quot;math-container&quot;&gt;$\pu{300K}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="789" LastEditorUserId="7" LastEditDate="2022-04-30T17:34:20.620" LastActivityDate="2022-05-09T13:00:28.720" Title="How to calculate temperature dependent phonon band structure in VASP" Tags="|vasp|phonons|temperature|perovskites|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9009" PostTypeId="2" ParentId="9006" CreationDate="2022-04-30T05:25:09.007" Score="5" Body="&lt;p&gt;What you have obtained in this calculation is the energy of the first excited state according to CIS. In practice, the CI expansion coefficients are obtained as the eigenvectors of the Hamiltonian matrix. The corresponding eigenvalues give the CI electronic energies.&lt;/p&gt;&#xA;&lt;p&gt;For the 6-31G basis set, you have two AOs, hence two MOs. This allows you to have two configuration state functions in CIS: &lt;span class=&quot;math-container&quot;&gt;$\Psi_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$^1{\Psi_1^2}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The Hamiltonian matrix is defined by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\left[\begin{array}{cc}&#xA;\langle\Psi_0|\hat{H}|\Psi_0 \rangle &amp;amp; \langle\Psi_0|\hat{H}|^1{\Psi_1^2} \rangle \\&#xA;\langle ^1{\Psi_1^2} | \hat{H}|\Psi_0 \rangle &amp;amp; \langle ^1{\Psi_1^2} | \hat{H}|^1{\Psi_1^2} \rangle \\&#xA;\end{array}\right]&#xA;=&#xA;\left[\begin{array}{cc}&#xA;H_{11} &amp;amp; H_{12} \\&#xA;H_{21} &amp;amp; H_{22}&#xA;\end{array}\right]&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The matrix element &lt;span class=&quot;math-container&quot;&gt;$\langle\Psi_0|\hat{H}|\Psi_0 \rangle =H_{11}$&lt;/span&gt; is the Hartree-Fock energy, &lt;span class=&quot;math-container&quot;&gt;$E_{\rm HF}$&lt;/span&gt; (which is &lt;code&gt;E(SCF)  =     -2.855160426 Eh&lt;/code&gt; in your calculation). The above matrix is usually presented by subtracting this energy from the diagonal elements.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left[\begin{array}{cc}&#xA;H_{11} - E_{\rm HF} &amp;amp; H_{12} \\&#xA;H_{21} &amp;amp; H_{22}- E_{\rm HF}&#xA;\end{array}\right]&#xA;= &#xA;\left[\begin{array}{cc}&#xA;0 &amp;amp; H_{12} \\&#xA;H_{21} &amp;amp; H_{22}- E_{\rm HF}&#xA;\end{array}\right]&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;CIS of He atom with 6-31 G basis set is actually not a great choice because &lt;span class=&quot;math-container&quot;&gt;$H_{12}$&lt;/span&gt; (and &lt;span class=&quot;math-container&quot;&gt;$H_{21}$&lt;/span&gt;, since the Hamiltonian matrix is Hermitian) vanishes according to Brillouin's theorem.&lt;/p&gt;&#xA;&lt;p&gt;So, we have a &lt;span class=&quot;math-container&quot;&gt;$2\times 2$&lt;/span&gt; diagonal matrix, where the element &lt;span class=&quot;math-container&quot;&gt;$H_{22}-E_{\rm HF}$&lt;/span&gt; has the value &lt;code&gt;DE(CIS) =      1.911193623 Eh (Root  1)&lt;/code&gt; according to your Orca calculation.&lt;/p&gt;&#xA;&lt;p&gt;The first excited state's energy is &lt;span class=&quot;math-container&quot;&gt;$H_{22}=E_{\rm HF}+1.911193923$&lt;/span&gt;, which is &lt;code&gt;    E(tot)  =     -0.943966803 Eh&lt;/code&gt; in your calculation.&lt;/p&gt;&#xA;&lt;p&gt;A somewhat non-trivial example where you will not have a diagonal matrix, hence you can learn about correlation energy correction to the ground state, could be He atom's CISD with the same basis set.&lt;/p&gt;&#xA;" OwnerUserId="5025" LastActivityDate="2022-04-30T05:25:09.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9010" PostTypeId="2" ParentId="9008" CreationDate="2022-04-30T05:30:44.063" Score="3" Body="&lt;p&gt;You can try the library &lt;a href=&quot;http://ollehellman.github.io/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TDEP&lt;/a&gt;, which has an example to calculate &lt;a href=&quot;http://ollehellman.github.io/page/workflows/minimal_example_6.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phonons dispersions as a function of temperature&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5025" LastActivityDate="2022-04-30T05:30:44.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9011" PostTypeId="1" CreationDate="2022-04-30T05:58:46.810" Score="7" ViewCount="155" Body="&lt;p&gt;I have recently encountered this &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465519302309&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; in which the authors have formulated Kohn-Sham equations using the finite elements package &lt;a href=&quot;https://www.dealii.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;deal.II&lt;/a&gt;, leading to an open-source software called &lt;a href=&quot;https://sites.google.com/umich.edu/dftfe/home?authuser=0&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT-FE&lt;/a&gt;.&#xA;It stated in the paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;DFT-FE was significantly faster than QE for all the systems considered, with speedups for smaller system sizes (2550–6034 electrons) to speedups for larger system sizes (14,322–20,470 electrons)&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Can somebody comment on the theory and resulting scaling of speed? As the package is recently developed, what are the challenges that will come on the practical side for calculating properties of materials in the future?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2022-12-10T14:37:01.733" LastActivityDate="2022-12-10T14:37:01.733" Title="Scaling and speed-up of real-space DFT calculations using finite elements approach" Tags="|density-functional-theory|kohn-sham|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9012" PostTypeId="2" ParentId="4284" CreationDate="2022-04-30T10:06:54.117" Score="5" Body="&lt;p&gt;Here is the code that I currently used. i hope it could be helpful for other's research.&#xA;To obtain the integrals, the first step is to run a Hartree Fock approximation and check if it has converged.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;m = M(atom=atoms, basis=&amp;quot;sto3g&amp;quot;, spin=spin, charge=charge)&#xA;hf = m.RHF()&#xA;hf.kernel()&#xA;  for j in range(10):&#xA;    mo = hf.stability()[0]&#xA;    if np.allclose(mo, hf.mo_coeff):&#xA;       break&#xA;    dm = hf.make_rdm1(mo, hf.mo_occ)&#xA;    hf = hf.run(dm)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, one can extract the one- &lt;code&gt;h1e&lt;/code&gt; and two-body &lt;code&gt;h2e&lt;/code&gt; integral from the molecular class.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;h1e = m.intor(&amp;quot;int1e_kin&amp;quot;) + m.intor(&amp;quot;int1e_nuc&amp;quot;)&#xA;h2e = m.intor(&amp;quot;int2e&amp;quot;)&#xA;scf_c = hf.mo_coeff&#xA;nuclear_repulsion = m.energy_nuc()&#xA;constant = nuclear_repulsion&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If the molecular system that one considers is too large, the complete active space method can also be used similarly:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;mycas = hf.CASCI(len(active_indices), n_elec).run()&#xA;h1e, constant = mycas.get_h1cas()&#xA;h2e = mycas.get_h2cas()&#xA;h2e = pyscf.ao2mo.addons.restore('1', h2e, len(active_indices))&#xA;h2e = h2e.transpose(0, 2, 3, 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The last step is to rotate the basis to the computed Hartree Fock basis as follows.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# Get the one and two electron integral in the Hatree Fock basis&#xA;h1e = scf_c.T @ h1e @ scf_c&#xA;for i in range(4):&#xA;   h2e = np.tensordot(h2e, scf_c, axes=1).transpose(3, 0, 1, 2)&#xA;h2e = h2e.transpose(0, 2, 3, 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2043" LastEditorUserId="2043" LastEditDate="2022-05-07T08:16:59.923" LastActivityDate="2022-05-07T08:16:59.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9013" PostTypeId="2" ParentId="9004" CreationDate="2022-04-30T13:04:45.980" Score="4" Body="&lt;p&gt;This is an error caused by symmetry breaking as the IBRION=5 routine runs, the simple answer is to simply set ISYM=0 and disable symmetry.  This happens even if you have (1, 1, 1) k-points, counterintuitively when you read what this message seems to be about.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-04-30T13:04:45.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9014" PostTypeId="1" CreationDate="2022-04-30T21:14:06.547" Score="6" ViewCount="351" Body="&lt;p&gt;I am looking for common software packages that implement UFF ideally with an example of how to run it to calculate forces and energies.  I see that Rdkit should be capable of doing this for example, but it is unclear how to do so.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-05-01T14:38:03.613" Title="What software implements UFF" Tags="|software-recommendations|forcefields|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9015" PostTypeId="1" AcceptedAnswerId="9016" CreationDate="2022-05-01T00:56:34.280" Score="3" ViewCount="166" Body="&lt;p&gt;Suppose, the size of my simulation box is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Width = 200&lt;/li&gt;&#xA;&lt;li&gt;Height = 100&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Where,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Top-left corner = (0, 0)&lt;/li&gt;&#xA;&lt;li&gt;Bottom-right corner = (200,100)&lt;/li&gt;&#xA;&lt;li&gt;Center of the coordinate is at (100, 50)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;What would be the size of the periodic boundary?&lt;/p&gt;&#xA;&lt;p&gt;Is that the same size as the dimensions of the simulation box, or is it different?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-01-04T00:22:19.530" Title="What is the relationship between periodic boundary and the simulation box?" Tags="|molecular-modeling|atomistic-simulation|periodic-boundary-conditions|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9016" PostTypeId="2" ParentId="9015" CreationDate="2022-05-01T02:15:43.057" Score="4" Body="&lt;p&gt;Some pseudo-code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;x_length = 200&#xA;y_length = 100&#xA;&#xA;if x &amp;lt; 0: x += x_length&#xA;if x &amp;gt; x_length: x -= x_length&#xA;if y &amp;lt; 0: y += y_length&#xA;if y &amp;gt; y_length: y -= y_length&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you have alluded to, periodic boundary conditions adjust a coordinate by the size of the simulation box in that dimension.&lt;/p&gt;&#xA;&lt;p&gt;I recommend &lt;a href=&quot;https://www.amazon.ca/Understanding-Molecular-Simulation-Algorithms-Applications/dp/0122673514&quot; rel=&quot;nofollow noreferrer&quot;&gt;Understanding Molecular Simulation Algorithms by Frenkel &amp;amp; Smit&lt;/a&gt; and &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0198803206&quot; rel=&quot;nofollow noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computer Simulation of Liquids by Allen &amp;amp; Tildesley&lt;/a&gt;. They are a rich source of simulation knowledge.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-05-01T02:52:09.403" LastActivityDate="2022-05-01T02:52:09.403" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9017" PostTypeId="1" CreationDate="2022-05-01T08:39:08.420" Score="9" ViewCount="211" Body="&lt;p&gt;I am trying to understand how to do the time-dependent simulation of the electron transfer, I find that the popular method is surface hopping, but I am not sure if there is any software that could surface hopping simulation.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;Is there any open-source software that could do surface hopping?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-03T13:52:09.280" Title="Any software that could do surface hopping?" Tags="|software-recommendations|td-dft|excited-states|born-oppenheimer-approximation|non-adiabatic|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9018" PostTypeId="1" CreationDate="2022-05-01T12:25:24.900" Score="3" ViewCount="51" Body="&lt;p&gt;To study SiO2, polyamide and two-layer SiO2-polyamide as the membranes in the reverse osmosis desalination of saline water; I used the Materials Studio software to model the systems. My question is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can the pressures of two sides of the membrane be defined in the software?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5330" LastEditorUserId="5" LastEditDate="2022-08-18T08:18:41.937" LastActivityDate="2022-08-18T08:18:41.937" Title="How may I define the pressures of two sides of a membrane in Materials Studio?" Tags="|molecular-dynamics|water|membranes|materials-studio|" AnswerCount="0" CommentCount="2" ClosedDate="2022-08-18T14:23:58.890" ContentLicense="CC BY-SA 4.0" />
  <row Id="9019" PostTypeId="2" ParentId="9014" CreationDate="2022-05-01T14:38:03.613" Score="8" Body="&lt;p&gt;Many codes implement UFF, including LAMMPS, RDKit, Open Babel.&lt;/p&gt;&#xA;&lt;p&gt;A few caveats... First off, the original UFF paper is known to have &lt;a href=&quot;http://towhee.sourceforge.net/forcefields/uff.html&quot; rel=&quot;noreferrer&quot;&gt;typos and errors&lt;/a&gt;. One consistent pain point is that the angle terms have a minimum at 0° so atoms can collapse on each other easily. Most implementations add an harmonic or exponential barrier to avoid this.&lt;/p&gt;&#xA;&lt;p&gt;Also, there are now a few flavors of UFF, including UFF4MOF .. I don't know of any implementation outside of LAMMPS and friends have indicated that it's still tricky to use.&lt;/p&gt;&#xA;&lt;h2&gt;RDKit Example&lt;/h2&gt;&#xA;&lt;p&gt;Something like this should be what you want. I'm adapting from &lt;a href=&quot;https://github.com/dkoes/rdkit-scripts/blob/master/rdconf.py&quot; rel=&quot;noreferrer&quot;&gt;David Koes's conformer generation script&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import AllChem as Chem&#xA;&#xA;mol = Chem.MolFromSmiles(&amp;quot;C1CCCCC1&amp;quot;)&#xA;Chem.SanitizeMol(mol)&#xA;mol = Chem.AddHs(mol)&#xA;conf_ids = Chem.EmbedMultipleConfs(mol, 50, Chem.ETKDG())&#xA;&#xA;for conf in conf_ids:&#xA;    converged = not Chem.UFFOptimizeMolecule(mol,confId=conf)                      &#xA;    energy = Chem.UFFGetMoleculeForceField(mol,confId=conf).CalcEnergy()&#xA;    forces = Chem.UFFGetMoleculeForceField(mol,confId=conf).CalcGrad()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Open Babel / Pybel Example&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = pybel.readstring(&amp;quot;smi&amp;quot;, &amp;quot;C1CCCCC1&amp;quot;)&#xA;# or read from a file&#xA;pybel._builder.Build(mol.OBMol)&#xA;mol.addh()&#xA;&#xA;ff = pybel._forcefields[&amp;quot;uff&amp;quot;]&#xA;success = ff.Setup(mol.OBMol)&#xA;ff.ConjugateGradients(100, 1.0e-3)&#xA;&#xA;energy = ff.Energy()&#xA;# I don't remember if this is fully adapted to numpy&#xA;gradients = ff.GetGradientPtr()&#xA;print(type(gradients))&#xA;&#xA;# This definitely works&#xA;for atom in mol.atoms:&#xA;    grad = ff.GetGradient(atom.OBAtom)&#xA;    print(grad.GetX(), grad.GetY(), grad.GetZ())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-05-01T14:38:03.613" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9020" PostTypeId="1" AcceptedAnswerId="9022" CreationDate="2022-05-02T10:18:51.887" Score="6" ViewCount="587" Body="&lt;p&gt;I'm trying to compute the energy of the benzyl bromide with orca. I need it to be at ωB97x-d4/6-31g(d) level. Orca throws me the following error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;** There are no main   basis functions on atom number  14 (Br) **&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also tried the &lt;code&gt;! NORI&lt;/code&gt;  keyword, but nothing changed.&lt;/p&gt;&#xA;&lt;p&gt;can somebody help me?&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2024-02-08T06:36:59.140" Title="Bromine basis set problem" Tags="|orca|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9021" PostTypeId="1" CreationDate="2022-05-02T10:27:59.523" Score="5" ViewCount="387" Body="&lt;p&gt;Fermi level is electron chemical potential at 0K and we can obtain it from DFT calculation. However, the chemical potential is dependent on temperature. But I only find the equation for gas or simple compounds. Is there any way to estimate the chemical potential of electrons in solid crystals at finite temperature?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="4515" LastEditDate="2022-07-19T16:37:36.210" LastActivityDate="2022-07-23T18:03:21.270" Title="How to estimate chemical potential at a temperature?" Tags="|physical-properties-of-materials|statistical-thermodynamics|thermodynamics|free-energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9022" PostTypeId="2" ParentId="9020" CreationDate="2022-05-02T10:43:25.413" Score="8" Body="&lt;p&gt;You can download it from this site:&#xA;Basis Set Exchange: &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.basissetexchange.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the requested basis set for Br in ORCA format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!----------------------------------------------------------------------&#xA;! Basis Set Exchange&#xA;! Version v0.9&#xA;! https://www.basissetexchange.org&#xA;!----------------------------------------------------------------------&#xA;!   Basis set: 6-31G(d,p)&#xA;! Description: 6-31G + polarization on all atoms&#xA;!        Role: orbital&#xA;!     Version: 1  (Data from Gaussian 09/GAMESS)&#xA;!----------------------------------------------------------------------&#xA;&#xA;&#xA;$DATA&#xA;&#xA;BROMINE&#xA;S   6&#xA;1         0.1137182000E+06       0.1717696000E-02&#xA;2         0.1707444000E+05       0.1316744000E-01&#xA;3         0.3889576000E+04       0.6504553000E-01&#xA;4         0.1097096000E+04       0.2269505000E+00&#xA;5         0.3520624000E+03       0.4768357000E+00&#xA;6         0.1207002000E+03       0.3583677000E+00&#xA;L   6&#xA;1         0.2471138000E+04       0.2243687000E-02       0.3790182000E-02&#xA;2         0.5893838000E+03       0.2994853000E-01       0.2995979000E-01&#xA;3         0.1918738000E+03       0.1256009000E+00       0.1318228000E+00&#xA;4         0.7295339000E+02      -0.9832786000E-03       0.3432708000E+00&#xA;5         0.3005839000E+02      -0.6013141000E+00       0.4642345000E+00&#xA;6         0.1252927000E+02      -0.4913983000E+00       0.2079387000E+00&#xA;L   6&#xA;1         0.1096411000E+03      -0.5975683000E-02      -0.6907483000E-02&#xA;2         0.3858948000E+02       0.5542122000E-01      -0.3041432000E-01&#xA;3         0.1637818000E+02       0.2681200000E+00       0.4602725000E-01&#xA;4         0.7221836000E+01      -0.1543606000E+00       0.3650689000E+00&#xA;5         0.3263697000E+01      -0.7206306000E+00       0.4949232000E+00&#xA;6         0.1465499000E+01      -0.3316437000E+00       0.2090394000E+00&#xA;L   3&#xA;1         0.2103651000E+01       0.3029029000E+00      -0.2826714000E-01&#xA;2         0.7547050000E+00      -0.2152659000E+00       0.3503065000E+00&#xA;3         0.3005140000E+00      -0.9633941000E+00       0.7182446000E+00&#xA;L   1&#xA;1         0.1090710000E+00       0.1000000000E+01       0.1000000000E+01&#xA;D   3&#xA;1         0.6225514000E+02       0.7704229000E-01&#xA;2         0.1731284000E+02       0.3707384000E+00&#xA;3         0.5607915000E+01       0.7097628000E+00&#xA;D   1&#xA;1         0.1746486000E+01       1.0000000&#xA;D   1&#xA;1         0.4366000000E+00       1.0000000&#xA;&#xA;$END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-05-02T10:43:25.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9023" PostTypeId="2" ParentId="9017" CreationDate="2022-05-02T17:05:40.330" Score="7" Body="&lt;p&gt;Here are some options. Depending on what you want you may use on-the-fly electronic structure calculations for energies, gradients, and couplings and some of the codes can take care of integrating the trajectories and the surface hopping. Or you may want to fit the potential energy surfaces and couplings to some analytic from and interface this code to the trajectory code.&lt;/p&gt;&#xA;&lt;h2&gt;SHARC2.1&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The SHARC (Surface Hopping including ARbitrary Couplings) molecular dynamics program suite is a software package developed by the González group in Vienna to study the excited-state dynamics of molecules.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://sharc-md.org&quot; rel=&quot;noreferrer&quot;&gt;https://sharc-md.org&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;ANT 2020&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A Molecular Dynamics Program for Performing Classical and Semiclassical Trajectory Simulations for Electronically Adiabatic and Nonadiabatic Processes for Gas-Phase and Materials Systems&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://comp.chem.umn.edu/ant/&quot; rel=&quot;noreferrer&quot;&gt;https://comp.chem.umn.edu/ant/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Dint - version 2.0&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Dint is a parallel Fortran computer program for performing classical and semiclassical trajectory simulations of electronically adiabatic and nonadiabatic processes. Dint - version 2.0 can be used for dynamics governed either by a single potential energy surface (electronically adiabatic processes) or by two or more coupled potential energy surfaces (electronically nonadiabatic processes). Dint - version 2.0 can handle reactive trajectories, bimolecular inelastic collisions, and unimolecular processes. Dint - version 2.0 can be run at fixed energy or for thermal ensembles. Dint - version 2.0 can also perpare initial conditions of a molecule according to a fixed-energy microcanonical ensemble.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://comp.chem.umn.edu/dint/&quot; rel=&quot;noreferrer&quot;&gt;https://comp.chem.umn.edu/dint/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="878" LastActivityDate="2022-05-02T17:05:40.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9025" PostTypeId="1" AcceptedAnswerId="9026" CreationDate="2022-05-03T02:26:21.567" Score="7" ViewCount="282" Body="&lt;p&gt;From what I'm reading, simulation of auto-ionization in liquid substances is hard to do using gas phase DFT or AIMD [1][2][3]. I am using ORCA to do my work and I must confess that I'm shocked to see that when using modern functionals like wB97X-D3 and r2SCAN-D3, and even when going with a triple zeta basis set I wasn't able to see a single auto-ionization at 300 K in a box containing 50 water molecules or 30 DMSO molecules after 2000 1-fs steps or more.&lt;/p&gt;&#xA;&lt;p&gt;My silly question is: &lt;strong&gt;is this calculation possible without using more specialized software like CP2K or am I doing something terribly wrong?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Y. Fu, L. Liu, R.-Q. Li, R. Liu and Q.-X. Guo, J. Am. Chem. Soc.,&#xA;2004, 126, 814–822.&lt;/li&gt;&#xA;&lt;li&gt;L. R. Pestana, N. Mardirossian, M. Head-Gordon&#xA;and T. Head-Gordon, Chem. Sci., 2017, 8, 3554–3565.&lt;/li&gt;&#xA;&lt;li&gt;P. L. Geissler,&#xA;C. Dellago, D. Chandler, J. Hutter and M. Parrinello, Science, 2001,&#xA;291, 2121–2124.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="557" LastEditorUserId="5" LastEditDate="2023-03-08T15:31:37.280" LastActivityDate="2023-03-08T15:31:37.280" Title="Simulating autoionization of small molecules using DFT or AIMD" Tags="|density-functional-theory|molecular-dynamics|orca|aimd|water|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9026" PostTypeId="2" ParentId="9025" CreationDate="2022-05-03T06:56:56.403" Score="12" Body="&lt;p&gt;This is because autoionization is very thermodynamically unfavored near room temperature. I don't know much about water in a water-DMSO mixture, but let's take pure water as an example. The equilibrium constant of the autoionization&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;2\ce{H2O} \to \ce{H3O+} + \ce{OH-}&#xA;$$&lt;/span&gt;&#xA;is well-known to be &lt;span class=&quot;math-container&quot;&gt;$3.2\times 10^{-18}$&lt;/span&gt; (this differs from the more familiar figure &lt;span class=&quot;math-container&quot;&gt;$K_{\rm{w}} = [\ce{H3O+}][\ce{OH-}] = 1.0\times 10^{-14} \rm{M}^2$&lt;/span&gt; by the square of the bulk concentration of liquid water, &lt;span class=&quot;math-container&quot;&gt;$55.6 \rm{M}$&lt;/span&gt;). The &lt;a href=&quot;https://en.wikipedia.org/wiki/Self-ionization_of_water&quot; rel=&quot;noreferrer&quot;&gt;rate constant of the reverse reaction is&lt;/a&gt; &lt;span class=&quot;math-container&quot;&gt;$1.3\times 10^{11} \rm{M}^{-1} \rm{s}^{-1}$&lt;/span&gt;. Thus, from detailed balance, the rate constant of the forward reaction is &lt;span class=&quot;math-container&quot;&gt;$4.1\times 10^{-7} \rm{M}^{-1} \rm{s}^{-1}$&lt;/span&gt;. Taking into account the bulk concentration of water, this means that one must wait about 12 hours for any given water molecule to be engaged in an autoionization event. Since you have 50 water molecules, the required time is shortened to about 14 minutes, but this is still orders of magnitude longer than the 2 ps simulation that you have done! Obviously no software package, not even CP2K, can do a 14 minute AIMD simulation in the foreseeable future.&lt;/p&gt;&#xA;&lt;p&gt;The lesson is that, a (perhaps surprisingly) large fraction of reactions cannot be studied by plain AIMD (or by even classical MD) due to the timescale involved, but rather necessitate enhanced sampling techniques. People tend to be interested in reactions that can most conveniently be studied in a wet lab, namely those reactions that take seconds to hours to finish under room temperature, but the timescale of AIMD simulations is over 10 orders of magnitude shorter, such that it does not overlap with the timescale of these reactions at all.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-05-03T06:56:56.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9027" PostTypeId="1" CreationDate="2022-05-03T10:47:57.927" Score="6" ViewCount="705" Body="&lt;p&gt;I am trying to learn how to calculate Gibbs free energy for a reaction. Assuming a reaction for two-dimensional TMDCs:&lt;/p&gt;&#xA;&lt;p&gt;MoS2 (solid) + 2Se(gas) ---&amp;gt; MoSe2 (solid)+ 2S (gas)&lt;/p&gt;&#xA;&lt;p&gt;I can calculate the energies of terms, e.g., single-layer MoS2 (solid) and MoSe2 (solid). Perhaps for S and Se energies of a single atom is a box but all these values are at 0K and does not includes temperature (T) effects.&lt;/p&gt;&#xA;&lt;p&gt;Now, I am wondering: How can I study this reaction?&lt;/p&gt;&#xA;&lt;p&gt;It would be extremely useful to have some insight.&#xA;Thanks&lt;/p&gt;&#xA;&lt;p&gt;Update:&#xA;For S(gas), I performed frequency analysis. For a given value of temperature and pressure, using vaspkit, it shows the following result. &lt;a href=&quot;https://i.stack.imgur.com/4Wjh3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4Wjh3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It shows that the thermal correction to G(T) is -1.603737. Should I add this value to the E_0?&#xA;i.e., S(gas) = E_0 + G(T) = -0.03107224-1.6037 = −1.63477224&#xA;and this will be the energy for S(gas) with Gibbs free energy correction?&lt;/p&gt;&#xA;" OwnerUserId="879" LastEditorUserId="24" LastEditDate="2022-05-09T12:16:58.127" LastActivityDate="2022-05-09T12:16:58.127" Title="How to calculate the Gibbs free energy for a reaction?" Tags="|vasp|thermodynamics|free-energy|" AnswerCount="0" CommentCount="7" ClosedDate="2022-12-11T13:45:53.680" ContentLicense="CC BY-SA 4.0" />
  <row Id="9028" PostTypeId="2" ParentId="9017" CreationDate="2022-05-03T13:52:09.280" Score="6" Body="&lt;h1&gt;Newton-X&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Newton-X is a general program for molecular dynamics simulations beyond the Born-Oppenheimer approximation. It has been primarily used for simulations of ultrafast processes (femtosecond to picosecond time scale) in photoexcited molecules. It has also been used for simulation of band envelops of absorption and emission spectra.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://newtonx.org/&quot; rel=&quot;noreferrer&quot;&gt;https://newtonx.org/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Newton-X is mainly intended for ab inito on-the-fly nonadiabatic dynamics simulations. Interfaces to various quantum chemistry programs are provided.&lt;/p&gt;&#xA;&lt;p&gt;For a specific application of Newton-X to electron transfer dynamics and a discussion of the underlying physics, you can see &lt;a href=&quot;http://dx.doi.org/10.1063/1.3526697&quot; rel=&quot;noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt;, &lt;strong&gt;134&lt;/strong&gt;, 034309 (2011)&lt;/a&gt; .&lt;/p&gt;&#xA;" OwnerUserId="115" LastActivityDate="2022-05-03T13:52:09.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9029" PostTypeId="1" CreationDate="2022-05-03T14:09:07.167" Score="7" ViewCount="704" Body="&lt;p&gt;I know that coupled cluster is considered to provide better accuracy than DFT, but I am not sure for which materials science applications or types of molecules that this higher accuracy is considered desirable. For example, which of the following materials science areas would require the accuracy that CC provides:&lt;/p&gt;&#xA;&lt;p&gt;organic electronics&#xA;polymers&#xA;consumer packaged goods&#xA;catalysts/reactive systems&#xA;semi-conductors&#xA;energy capture and storage&#xA;metals alloys and ceramics&#xA;complex formulations ?&lt;/p&gt;&#xA;" OwnerUserId="3392" LastActivityDate="2022-05-03T21:07:20.740" Title="When is coupled cluster preferred over DFT?" Tags="|density-functional-theory|quantum-chemistry|coupled-cluster|algorithms|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9030" PostTypeId="2" ParentId="9029" CreationDate="2022-05-03T20:58:11.130" Score="5" Body="&lt;p&gt;Coupled cluster is theoretically more accurate that DFT, as it's limiting behaviour is an exact solution to the Schrödinger equation. By limiting behaviour, I mean including all possible excitations (singles, doubles, triples, etc.) and a complete orbital basis set. There is no such guarantee of limiting accuracy with any known DFT method today, as we do not yet know the exact exchange-correlation functional. However, in principle an exact XC functional does exist and some modern DFT functionals can get very impressive accuracy.&lt;/p&gt;&#xA;&lt;p&gt;I think all domains of materials science would benefit from the accuracy available in coupled cluster theory. The problem with applying canonical coupled cluster theory is its computational cost scales unfavorably with system size. The computational cost of full coupled cluster scales combinatorically with the number of electrons and orbital basis functions included in the calculation. This unfavorable scaling can be mitigated by only including up to single, double, triple, etc excitations or limiting one's active space in some way, at the cost of reduced accuracy, but this approach can only be taken so far before the accuracy drops below that of DFT. I'd say about the largest molecule you could expect to calculate accurately using canonical CC theory is benzene, and even that would be very expensive. In recent years, much work had been done to decrease the computational cost of coupled cluster methods by applying approximations of various kinds, but it remains a relatively expensive method.&lt;/p&gt;&#xA;&lt;p&gt;Most DFT methods scale much more favorably with system size, so they remain the most popular option available for quantum mechanical calculation of systems beyond the size of benzene or so. Local and semi-local exchange-correlation implementations of DFT scale with the cube of the number of basis functions, although hybrid and double-hybrid functionals have worse scaling.&lt;/p&gt;&#xA;&lt;p&gt;As S R Maiti pointed out, coupled cluster is also difficult to implement and costly for periodic systems and remains an &lt;a href=&quot;https://www.frontiersin.org/articles/10.3389/fmats.2019.00123/full&quot; rel=&quot;noreferrer&quot;&gt;active area of research&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-05-03T21:07:20.740" LastActivityDate="2022-05-03T21:07:20.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9031" PostTypeId="2" ParentId="4702" CreationDate="2022-05-03T21:35:02.727" Score="3" Body="&lt;p&gt;&lt;strong&gt;Good Chemistry&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A new company called &lt;a href=&quot;https://goodchemistry.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Good Chemistry&lt;/a&gt;, a spinoff company of &lt;a href=&quot;https://1qbit.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;1QBit&lt;/a&gt;, has released a beta-version of their &lt;a href=&quot;https://goodchemistry.com/qemist-cloud/&quot; rel=&quot;nofollow noreferrer&quot;&gt;QEMIST Cloud&lt;/a&gt; service which purports to do exactly what you're asking about. From their website:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;QEMIST Cloud is an engine that enables faster, more accurate, and scalable ways to perform computational chemistry simulations. Our new platform leverages easily and readily accessible computers on the cloud to perform chemistry simulations that were previously intractable even on expensive, high-performance computing environments.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1443" LastActivityDate="2022-05-03T21:35:02.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9033" PostTypeId="2" ParentId="8992" CreationDate="2022-05-05T10:29:20.843" Score="4" Body="&lt;p&gt;I read &lt;code&gt;Electronic Structure Basic Theory and Practical Methods&lt;/code&gt; by Richard M. Martin, University of Illinois, Urbana-Champaign. Here is the link &lt;a href=&quot;https://www.cambridge.org/core/books/electronic-structure/DDFE838DED61D7A402FDF20D735BC63A&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electronic structure&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2022-05-05T10:29:20.843" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9034" PostTypeId="1" AcceptedAnswerId="9037" CreationDate="2022-05-06T03:55:53.497" Score="15" ViewCount="1590" Body="&lt;p&gt;I am currently reading Dickenson et al. (2013) &lt;a href=&quot;https://arxiv.org/pdf/1304.6390.pdf&quot; rel=&quot;noreferrer&quot;&gt;The Fundamental Vibration of Molecular Hydrogen&lt;/a&gt;.&#xA;I am trying to understand why this calculation is important for the field beyond basic scientific curiosity.&lt;/p&gt;&#xA;&lt;p&gt;Should we expect researchers to keep pushing the accuracy?&lt;/p&gt;&#xA;&lt;p&gt;Apologies for this extremely stupid question.&lt;/p&gt;&#xA;" OwnerUserId="5197" LastEditorUserId="201" LastEditDate="2022-05-07T23:15:25.630" LastActivityDate="2022-05-09T20:53:15.593" Title="What's the point of doing high accuracy spectroscopy calculations?" Tags="|molecular-modeling|spectroscopy|vibrations|high-precision|" AnswerCount="5" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9035" PostTypeId="2" ParentId="9034" CreationDate="2022-05-06T07:20:12.697" Score="8" Body="&lt;p&gt;Your arguments can be said about numerous &lt;em&gt;other&lt;/em&gt; articles (if not all but a very few ones).&lt;/p&gt;&#xA;&lt;p&gt;What seems negligible in scientific impact at the publication time might be heavily influenced by other developments in the future.&lt;/p&gt;&#xA;&lt;p&gt;As such &lt;em&gt;any&lt;/em&gt; small step along a given scientific direction is in-significant in its sole entity, but by combining different scientific contributions they might lead to significant advances. It might also be the paper that spurred interest in author X in year Y which led to the discovery of the property Z which allows anti-gravity boots, who knows?&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-05-06T07:20:12.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9036" PostTypeId="2" ParentId="9034" CreationDate="2022-05-06T16:18:04.167" Score="11" Body="&lt;p&gt;One of the eternal questions in computational modeling is whether we truly understand all the relevant contributions.&lt;/p&gt;&#xA;&lt;p&gt;I believe the combination of experiment and theory in the paper suggest that if there's unknown physics, the effects are very small in this system.&lt;/p&gt;&#xA;&lt;p&gt;From the paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In view of this development, the high level of agreement between the most accurate theory and experiment for the molecular hydrogen level energies may be interpreted to constrain effects of possible long-range hadron-hadron interactions. … In this sense precision molecular spectroscopy opens an avenue to search for new physics.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In a more general sense, there are often advantages to pursuing precision spectroscopy. The development of &lt;a href=&quot;https://en.wikipedia.org/wiki/Atomic_clock&quot; rel=&quot;noreferrer&quot;&gt;atomic clocks&lt;/a&gt; led to accurate &lt;a href=&quot;https://en.wikipedia.org/wiki/Global_Positioning_System&quot; rel=&quot;noreferrer&quot;&gt;GPS&lt;/a&gt; systems.&lt;/p&gt;&#xA;&lt;p&gt;Certainly, I can imagine the work in this paper can lead to improved accuracy of quantum chemical methods, improved molecular spectroscopy, etc.&lt;/p&gt;&#xA;&lt;p&gt;Generally, when you apply for grant funding, one must indicate potential impacts both to the broader scientific field, and to society. In the US, the National Science Foundation calls this &amp;quot;Broader Impacts&amp;quot; and it's specifically a criteria for reviewer evaluation. (The other main NSF criteria is &amp;quot;Scientific Impact&amp;quot;.) Thus, grant agencies and reviewers already balance such concerns.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-05-06T16:18:04.167" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9037" PostTypeId="2" ParentId="9034" CreationDate="2022-05-06T18:51:44.177" Score="21" Body="&lt;p&gt;The paper in your question currently has 159 citations and was published in one of the most prestigious journals (Physical Review Letters). It is about high-precision spectoscopy on &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, which is the simplest neutral molecule, and is therefore of &lt;em&gt;fundamental&lt;/em&gt; interest as a building block to our understanding of all molecules,  just as understanding &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; is a building block to understanding bigger atoms. You are basically asking &amp;quot;what value is there to &lt;a href=&quot;/questions/tagged/spectroscopy&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;spectroscopy&amp;#39;&quot; rel=&quot;tag&quot;&gt;spectroscopy&lt;/a&gt; beyond scientific curiosity?&amp;quot;.&lt;/p&gt;&#xA;&lt;h4&gt;Story time:&lt;/h4&gt;&#xA;&lt;p&gt;4 years before that &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; paper I made high-precision &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; potentials &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.3264688&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (for the singlet states) and &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (for the triplet states).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://scholar.google.com/citations?user=bazhkEYAAAAJ&amp;amp;hl=en&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kirk Madison&lt;/a&gt;'s group needed these to be extremely accurate in order to do some experiments. They wanted to make ultra-cold optical lattices using &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt;, because these can be used for quantum computing. &lt;strong&gt;But how do you make &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt;?&lt;/strong&gt; It's not done the way you make glucose, for example. Photoassociation (using &lt;em&gt;photons&lt;/em&gt; to &lt;em&gt;associate&lt;/em&gt; two atoms) is the only way that ultra-cold &lt;span class=&quot;math-container&quot;&gt;$\ce{Li2}$&lt;/span&gt; has been made, and it requires knowing the molecular energy levels to extremely high precision. You shine a laser at the atoms, and adjust the wavelength of the light until the photons exactly match the energy difference between the &amp;quot;atomic&amp;quot; and &amp;quot;molecular&amp;quot; states. If you know what the molecular energy levels are to within &lt;span class=&quot;math-container&quot;&gt;$\pm 1 \times 10^{-4}$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; and your laser's wavelength is being adjusted by &lt;span class=&quot;math-container&quot;&gt;$10^{-5}$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; for each measurement (any bigger and you could miss the signal that you're seeking), then you would have to do about 20 measurements. If you only know the energy level to within &lt;span class=&quot;math-container&quot;&gt;$\pm 1$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;, &lt;strong&gt;then you would have to 200,000 measurements.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-05-09T20:21:49.013" LastActivityDate="2022-05-09T20:21:49.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9038" PostTypeId="2" ParentId="8978" CreationDate="2022-05-06T20:49:27.893" Score="5" Body="&lt;h1&gt;Introduction&lt;/h1&gt;&#xA;&lt;p&gt;&lt;em&gt;Skip at your own risk&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; has an equilibrium concentration &lt;span class=&quot;math-container&quot;&gt;$c_{eq}$&lt;/span&gt; of all symmetry-unique oxygen vacancies, which is given by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$c_{eq} = \frac{N_{O_i}}{N_O} = \exp \left( -\frac{\Delta G_{vac}}{k_B T} \right)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$N_{O_i}$&lt;/span&gt; is the number of oxygen (&lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt;) of symmetry type &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; in a sample or simulation cell of TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$N_O$&lt;/span&gt; is the total number of oxygen in the same sample or simulation cell, &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt; is the Boltzmann constant, and &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the temperature.&lt;/p&gt;&#xA;&lt;p&gt;Note that this equation assumes that the oxygen vacancies do not interact, which allows the use of the mixing entropy of an ideal solution. This equation also assumes the formation of a neutral oxygen vacancy, i.e., O&lt;span class=&quot;math-container&quot;&gt;$^{2-}$&lt;/span&gt; donates two electrons to TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, which usually reduces two neighboring Ti&lt;span class=&quot;math-container&quot;&gt;$^{4+}$&lt;/span&gt; to Ti&lt;span class=&quot;math-container&quot;&gt;$^{3+}$&lt;/span&gt;, as it leaves to form half a mole of O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; gas. Since TiO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; has a bandgap, it also can form charged vacancies (you can find an excellent and very recent summary of this here, &lt;a href=&quot;https://doi.org/10.1038/s41578-022-00433-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1038/s41578-022-00433-0&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta G_{vac}$&lt;/span&gt; is the Gibbs free energy (&lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;) of oxygen vacancy (&lt;span class=&quot;math-container&quot;&gt;$vac$&lt;/span&gt;) formation, which contains the O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; gas pressure dependence and the effect of changes in the vibrational entropy.&lt;/p&gt;&#xA;&lt;h1&gt;The answer&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question 1:&lt;/strong&gt; &lt;em&gt;is it reasonable to decide it by choosing the configuration with the lowest energy?&amp;quot;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;If one oxygen vacancy configuration has a much lower formation energy than the others, &lt;strong&gt;probably&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question 2:&lt;/strong&gt; &lt;em&gt;What is the rule for deciding the position of defects?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;All defect positions (i.e., symmetry-unique sites) have an equilibrium concentration...some larger than others...some experimentally detectable, others not. The &amp;quot;rules&amp;quot; deciding their concentrations are the first and second laws of thermodynamics, which give the equation for &lt;span class=&quot;math-container&quot;&gt;$c_{eq}$&lt;/span&gt; above.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;it doesn't feel quite right to always choose the configuration with the lowest energy, because it means this configuration is quite stable, if I wanna use it as a catalyst, I might want it to be active.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, we don't get to choose the lowest energy – or, better yet, highest concentration – defect configuration. This is controlled by crystal bond strengths (O&lt;span class=&quot;math-container&quot;&gt;$^{2-}$&lt;/span&gt;–Ti&lt;span class=&quot;math-container&quot;&gt;$^{4+}$&lt;/span&gt;), cation reducibility (Ti&lt;span class=&quot;math-container&quot;&gt;$^{4+} \rightarrow$&lt;/span&gt; Ti&lt;span class=&quot;math-container&quot;&gt;$^{3+}$&lt;/span&gt;), the bandgap, polymorph stability (Rutile vs. Anatase vs. Brookite), etc. (&lt;em&gt;Shameless plug:&lt;/em&gt; To learn more about the factors controlling neutral oxygen vacancy formation in metal oxides, check out &lt;a href=&quot;https://doi.org/10.1021/jacs.1c05570&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jacs.1c05570&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;I agree that sometimes a material isn't active enough (i.e., it doesn't form oxygen vacancies easily enough) to be a catalyst. First, you need to identify what is active enough, i.e., an acceptable range for the oxygen vacancy formation energy for your catalysis application; this is a prerequisite for catalyst design! Then, you can search for either (1) bulk materials with good oxygen vacancy formation energies or (2) dopants that tune a material's oxygen vacancy formation energies to within the acceptable range.&lt;/p&gt;&#xA;&lt;p&gt;I hope this is helpful!&lt;/p&gt;&#xA;" OwnerUserId="801" LastEditorUserId="801" LastEditDate="2022-05-08T12:44:15.493" LastActivityDate="2022-05-08T12:44:15.493" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9039" PostTypeId="1" CreationDate="2022-05-06T21:02:29.953" Score="7" ViewCount="436" Body="&lt;p&gt;I am new to solid state calculation. When I was reading about the pseudopotential documents, I always ran into a diagram that shows how pseudopotential will help to smooth the all-electron wavefunction. Figure from Wikipedia&lt;a href=&quot;https://i.stack.imgur.com/8BjBM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8BjBM.png&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the diagram, it makes sense that the real potential will goes to negative infinity because the electron will get closer to the core. Then the wavefunctions have lots of nodes.&lt;/p&gt;&#xA;&lt;p&gt;However, I am confused that how to explain the shape of the pseudopotential (red solid line). For example, why there is a bump for the V-pseudo inside of the cutoff radius? How to use the V-pseudo shape to explain the shape for the pseudo-wavefunction above? Why the V-pseudo starts at a negative value but the pseudo-wavefunction starts from 0? Why the bump in the V-pseudo does not have any effect on the pseudo-wave function?&lt;/p&gt;&#xA;&lt;p&gt;I really appreciate any comments on this question.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Pseudopotential#/media/File:Sketch_Pseudopotentials.png&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Pseudopotential#/media/File:Sketch_Pseudopotentials.png&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5351" LastActivityDate="2022-05-08T23:25:15.820" Title="Understanding Illustration for Pseudopotential" Tags="|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9040" PostTypeId="2" ParentId="6872" CreationDate="2022-05-07T00:58:54.940" Score="5" Body="&lt;p&gt;The Python package &lt;a href=&quot;https://pypi.org/project/mayavi/&quot; rel=&quot;noreferrer&quot;&gt;mayavi&lt;/a&gt; uses &lt;a href=&quot;https://vtk.org/&quot; rel=&quot;noreferrer&quot;&gt;VTK&lt;/a&gt; for 3D visualization and offers thus several poptions for plotting volumetric data. &lt;a href=&quot;https://pypi.org/project/ase/&quot; rel=&quot;noreferrer&quot;&gt;ase&lt;/a&gt; has an interface to mayavi and facilitates IO of electronic structure grid formats such as cube files.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python3 -m ase.visualize.mlab file.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;will visualize the grid data from &lt;code&gt;file.cube&lt;/code&gt;. To plot from within your own python code, use the method &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/_modules/ase/visualize/mlab.html#plot&quot; rel=&quot;noreferrer&quot;&gt;ase.visualize.mlab.plot&lt;/a&gt;, which takes an ase atoms object, the grid data, and a list of floats to plot iso-surfaces at as parameters.&lt;/p&gt;&#xA;" OwnerUserId="5250" LastActivityDate="2022-05-07T00:58:54.940" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9042" PostTypeId="1" CreationDate="2022-05-07T08:16:54.367" Score="4" ViewCount="89" Body="&lt;p&gt;I am trying to calculate the reaction enthalpy change of &lt;span class=&quot;math-container&quot;&gt;$\ce{2H2 + O2-&amp;gt;2H2O}$&lt;/span&gt;, my plan is to calculate the energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2, O2 \text{and} H2O}$&lt;/span&gt;, respectively, then do the simple math.&lt;/p&gt;&#xA;&lt;p&gt;But I find some papers don't do it this way: They calculate the energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, look up the reaction enthalpy change from an experimental database, then calculate the energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt;, because DFT couldn't calculate the energy of magnetic diatomic molecules accurately.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&#xA;Why must the energy be calculated this way (or what is wrong with DFT in this case)?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-05-07T13:52:32.967" LastActivityDate="2022-05-07T13:52:32.967" Title="Why can't DFT calculate the energy of magnetic diatomic molecules accurately?" Tags="|density-functional-theory|molecular-modeling|magnetism|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9043" PostTypeId="1" CreationDate="2022-05-07T18:00:35.450" Score="7" ViewCount="383" Body="&lt;p&gt;I am trying to do a DFT calculation of Oxygen atoms with the VASP code. My settings follow the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/O_atom_spinpolarized_low_symmetry&quot; rel=&quot;nofollow noreferrer&quot;&gt;official tutorial on the Oxygen atom of VASP&lt;/a&gt;. But it turns out the energy levels of the two spin components are very different, which is obviously wrong. My question is:&lt;/p&gt;&#xA;&lt;p&gt;Why can't DFT describe the electronic configuration and energy level of a single atom?&#xA;Is this issue related to the concept of &amp;quot;unrestricted-spin DFT&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;Here is the result:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Fermi energy:        -7.3248173814&#xA;&#xA; spin component 1&#xA;&#xA; k-point     1 :       0.0000    0.0000    0.0000&#xA;  band No.  band energies     occupation&#xA;      1     -25.0682      1.00000&#xA;      2     -10.7441      1.00000&#xA;      3     -10.7433      1.00000&#xA;      4      -8.6436      1.00000&#xA;      5      -0.5792      0.00000&#xA;      6       1.8046      0.00000&#xA;      7       1.9955      0.00000&#xA;      8       2.0142      0.00000&#xA; Fermi energy:        -7.3248173814&#xA;&#xA; spin component 2&#xA;&#xA; k-point     1 :       0.0000    0.0000    0.0000&#xA;  band No.  band energies     occupation&#xA;      1     -21.4031      1.00000&#xA;      2      -7.3891      1.00000&#xA;      3      -6.2821      0.00000&#xA;      4      -6.2806      0.00000&#xA;      5      -0.3297      0.00000&#xA;      6       1.9176      0.00000&#xA;      7       2.1797      0.00000&#xA;      8       2.4480      0.00000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="7" LastEditDate="2022-05-08T13:21:55.260" LastActivityDate="2022-05-08T13:21:55.260" Title="Why can't DFT calculate the accurate electronic configuration of the Oxygen atom?" Tags="|density-functional-theory|vasp|spin-polarization|atomic-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9044" PostTypeId="2" ParentId="9043" CreationDate="2022-05-07T22:34:05.127" Score="5" Body="&lt;p&gt;I am unfamiliar with this exact tutorial but this looks fine to me, you have 4 electrons in one spin and 2 in the other, giving a net 2 unpaired electrons.  This is correct when you look at the ground state of oxygen and is consistent with that tutorial page.  I do not think there is any reason DFT cannot describe a single atom correctly, although molecular oxygen will be problematic (maybe you are thinking of this).&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-05-07T22:34:05.127" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9045" PostTypeId="2" ParentId="9034" CreationDate="2022-05-07T23:34:50.520" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;What's the point of doing high accuracy spectroscopy calculations?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think there's a more fundamental answer.&lt;/p&gt;&#xA;&lt;p&gt;But I'm going to argue from the experimental side. Of course implicit in my answer is the idea that these higher accuracy experiments will then require higher accuracy calculations, which will then demand higher accuracy experiments...&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;How does science progress?&lt;/p&gt;&#xA;&lt;p&gt;We:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;look at the world&lt;/li&gt;&#xA;&lt;li&gt;spot some thing interesting&lt;/li&gt;&#xA;&lt;li&gt;make a model&lt;/li&gt;&#xA;&lt;li&gt;test the model&lt;/li&gt;&#xA;&lt;li&gt;despair when it works perfectly, rejoice when it breaks down&lt;/li&gt;&#xA;&lt;li&gt;revise the model or throw it out and build a new one&lt;/li&gt;&#xA;&lt;li&gt;lather, rinse, repeat (i.e. back to step #4)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The more accurate the measurement is, usually the more it challenges a model. Most models these days include implicit or explicit approximations, and the deviations between models and accurate measurements challenge the models limits.&lt;/p&gt;&#xA;&lt;p&gt;Talk about the very fundamental &lt;a href=&quot;https://en.wikipedia.org/wiki/Standard_Model&quot; rel=&quot;noreferrer&quot;&gt;The Standard Model&lt;/a&gt; which has continued to fit new measurements in high energy particle physics. What has bothered at least some physicists is that predictions of this model has continued to agree with new experimental results better than it should. Some might say better than it &amp;quot;has a right to.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;It makes some folks at least uncomfortable.&lt;/p&gt;&#xA;&lt;p&gt;Suddenly there is news:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Nature: &lt;a href=&quot;https://www.nature.com/articles/d41586-022-01014-5&quot; rel=&quot;noreferrer&quot;&gt;Particle’s surprise mass threatens to upend the standard model&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Phys.org: &lt;a href=&quot;https://phys.org/news/2021-03-result-lhcb-theory-physics.html&quot; rel=&quot;noreferrer&quot;&gt;New result from the LHCb experiment challenges leading theory in physics&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Contrary to popular headlines, there is much rejoicing!&lt;/p&gt;&#xA;&lt;p&gt;Finally sufficiently accurate measurement has been made that &lt;em&gt;disagrees&lt;/em&gt; with the best model available. This is gold for theorists, a chance to find either a refinement/adjustment of the current model or a new model (or perhaps new particle or new effect).&lt;/p&gt;&#xA;&lt;p&gt;Another example is &lt;a href=&quot;https://phys.washington.edu/people/eric-adelberger&quot; rel=&quot;noreferrer&quot;&gt;Eric Adelberger&lt;/a&gt;'s (also &lt;a href=&quot;https://phys.washington.edu/people/eric-adelberger&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) and the &lt;a href=&quot;https://www.npl.washington.edu/eotwash/&quot; rel=&quot;noreferrer&quot;&gt;The Eöt-Wash Group&lt;/a&gt;'s insistence on super high accuracy of gravitation attraction between two objects in his lab.&lt;/p&gt;&#xA;&lt;p&gt;Who else would stack lead bricks around their experiment to cancel the gravitational quadrupole moment of the hill behind the physics building?&lt;/p&gt;&#xA;&lt;p&gt;These super-duper accurate torsional pendulum measurements have put serious constraints on theories of gravity and space.&lt;/p&gt;&#xA;&lt;p&gt;Science often advances by measuring the next few digits of a quantity that models can predict. Nobody knows when and where the surprise will happen, so we simply pursue higher and higher accuracy wherever we can.&lt;/p&gt;&#xA;" OwnerUserId="201" LastActivityDate="2022-05-07T23:34:50.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9046" PostTypeId="2" ParentId="9039" CreationDate="2022-05-08T18:18:26.263" Score="6" Body="&lt;p&gt;These are quite a few questions and it is difficult to grab the essence of what you actually want to know, but maybe I can clarify a few aspects that help to understand these things.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Besides the potential &lt;span class=&quot;math-container&quot;&gt;$V(r) \approx -\frac{Z}{r}$&lt;/span&gt; there is also the kinetic energy operator in the Kohn-Sham equations. For such spherical problems this equation can be reformulated such that the radial and the angular part of the kinetic energy operator are separated and the angular part can analytically be integrated. As a result one obtains the angular-momentum barrier &lt;span class=&quot;math-container&quot;&gt;$\propto \frac{l(l+1)}{2r^2}$&lt;/span&gt; as part of the radial Kohn-Sham equation. As the radius enters this term quadratically it is clear that for very small radii and finite angular momenta &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; it is much larger than the potential and has the opposite sign. It implies that a large value of the wave function near the nucleus is also related to a very large energy. The smaller the radius the larger the needed energy. This leads to a vanishing of the wave function near the nucleus. Obviously this consideration is independent of whether one uses a pseudopotential or the real potential. But it depends on the angular momentum &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;. Actually the radial behavior of the wave function near the nucleus is &lt;span class=&quot;math-container&quot;&gt;$\propto r^l$&lt;/span&gt;. For &lt;span class=&quot;math-container&quot;&gt;$l=0$&lt;/span&gt; one can thus have a finite value of the wave function near the nucleus. The illustration you show is a little bit inconsistent as it seems to sketch all-electron and pseudo wave functions for different &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;. In general illustrations are never perfect. :D&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The oscillatory behavior of the all-electron wave function stems from the singularity of the real potential at the atomic nucleus. This leads to a high kinetic energy contribution and thus to such an oscillatory behavior. To suppress this oscillatory behavior one has to construct a potential that has no singularity and is also not near this. The absolute values of the potential should not become large. One condition on the pseudopotential is that it agrees with the all-electron potential outside the critical radius and due to its construction principle it is also continuous in value and slope. This implies a large negative slope near the critical radius, leading to large negative values for small radii. As indicated before this is not wanted because it leads to the oscillatory behavior of the wave function. One thus obtains a bump of the potential to keep its absolute values small everywhere in space. The bump in the pseudopotential definitely has an effect on the wavefunction: It keeps it from oscillating.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In general I think one should see the pseudopotential approximation in the opposite direction. One starts with a pseudo-wavefunction for some prototype system and defines this wave function such that it fulfills certain conditions. It should have no nodes, it should nicely converge with respect to a plane-wave expansion, it should coincide with the all-electron wave function outside the critical radius, and its energy eigenvalue should agree with that of the all-electron wave function. There may also be a normalization condition. With this starting point one then constructs a pseudopotential that leads to such a pseudo-wavefunction. So, in the end it is not the wavefunction that one obtains from the pseodopotential, but the pseudopotential is a consequence of what properties you define for your pseudo-wavefunction. The hope then is that this construction also transfers to a good approximation of the physics in chemical environments deviating from your prototype system. For good pseudopotential constructions this often is the case.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2022-05-08T23:25:15.820" LastActivityDate="2022-05-08T23:25:15.820" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9047" PostTypeId="1" CreationDate="2022-05-09T08:38:59.433" Score="6" ViewCount="386" Body="&lt;p&gt;Effective mass of holes was measured using DFT. The hole value is different for each band, is there a way to get the average or standard value of this value?&#xA;It was calculated using the VASP program.&#xA;Or what kind of band should I calculate the effective mass of holes with VASP?&lt;/p&gt;&#xA;" OwnerUserId="5358" LastEditorUserId="24" LastEditDate="2022-05-09T10:50:09.247" LastActivityDate="2022-05-09T11:59:07.970" Title="Effective mass of holes was measured using DFT" Tags="|density-functional-theory|vasp|effective-mass|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9048" PostTypeId="1" AcceptedAnswerId="9050" CreationDate="2022-05-09T11:19:50.983" Score="6" ViewCount="534" Body="&lt;p&gt;I found that there is a type of substance in which two atoms exist in the same coordinate position in the lattice, for example, &lt;code&gt;FeF3(H2O)3&lt;/code&gt;, here is its &lt;a href=&quot;http://www.crystallography.net/cod/2310500.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;crystal structure file from Crystallography Open Database&lt;/a&gt;, the &lt;code&gt;O&lt;/code&gt; atom and &lt;code&gt;F&lt;/code&gt; atom exist at the same coordinate position.&lt;br&gt;&#xA;It also shows the &lt;code&gt;F&lt;/code&gt; atom and &lt;code&gt;H2O&lt;/code&gt; are at the same coordinate in the &lt;a href=&quot;https://journals.iucr.org/q/issues/1964/11/00/a04410/a04410.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;original paper&lt;/a&gt;, which measures the structure of &lt;code&gt;FeF3(H2O)3&lt;/code&gt;&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;When I try to do geometry optimization and calculate the thermal properties of this kind of substance, how should I set up my model? My plan is to build a supercell and distribute &lt;code&gt;F&lt;/code&gt; and &lt;code&gt;O&lt;/code&gt; atoms averagely, but I am wondering if there is any standard procedure for this job?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="24" LastEditDate="2022-05-09T11:55:10.430" LastActivityDate="2022-05-09T11:55:10.430" Title="How to do simulation when two atoms exist in the same coordinate position in the lattice?" Tags="|density-functional-theory|vasp|lattice-thermal-conductivity|disorder|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9049" PostTypeId="2" ParentId="9047" CreationDate="2022-05-09T11:21:04.260" Score="7" Body="&lt;p&gt;The easier way to calculate the &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;noreferrer&quot;&gt;effective mass&lt;/a&gt; (&lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;) is assuming the band as parabolic and calculate it from the equation below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E(\vec{k}) = E_0 + \frac{\hbar^2\vec{k}^2}{2m^*}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This means that &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt;, is dependent on the selected band and direction (i.e. &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; direction). This imply that, prior to do some calculations, you need to know what physical process you are interested in. Then, you need to identify which bands are involved in such process and then calculate the &lt;span class=&quot;math-container&quot;&gt;$m^*$&lt;/span&gt; for them.&lt;/p&gt;&#xA;&lt;p&gt;In Semiconductor Physics one processes of interested is the electron conductivity of the material. In such case, only the conduction band is used. Considering that the conduction band can be anisotropic (i.e. a different parabolicity for each direction), you can have a longitudinal (&lt;span class=&quot;math-container&quot;&gt;$m_l$&lt;/span&gt;) and two transversal ((&lt;span class=&quot;math-container&quot;&gt;$m_t$&lt;/span&gt;)) effective mass. In such case, the electron conductivity mass can be calculated as the inverse sum of those mass:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$m^*_{e,cond}=\frac{3}{\frac{1}{m_l} + \frac{1}{m_t} + \frac{1}{m_t}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Other process of interested can be the semiconductor LED/laser physics where the transitions between the valence bands and conduction bands are important. In that cases, the corresponding effective mass for the valence bands (hole effective mass) are also calculated.&lt;/p&gt;&#xA;&lt;p&gt;Always you are talking about holes, you have to use the valence bands to calculate the effective mass.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2022-05-09T11:59:07.970" LastActivityDate="2022-05-09T11:59:07.970" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9050" PostTypeId="2" ParentId="9048" CreationDate="2022-05-09T11:45:12.383" Score="9" Body="&lt;p&gt;You cannot have two atoms at the same coordinate position. The idea behind fraction occupancy is that, in a sufficient large cell, some positions will be occupied &amp;quot;alternated&amp;quot; by two different atoms. This can pass the wrong idea of two atoms at the same position.&lt;/p&gt;&#xA;&lt;p&gt;You can use several ways to consider this issue.&lt;br /&gt;&#xA;One is using the so called Virtual Crystal approximation [&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.61.7877&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;,&lt;a href=&quot;https://arxiv.org/abs/cond-mat/9908364&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;], where you &amp;quot;create&amp;quot; a new atom which is composed by the contribution of the disordered atoms. A similar approach is the Coherent Potential Approximation (CPA).&lt;br /&gt;&#xA;Other one is to use a sufficient large supercell where you interchange the atoms positions.&lt;br /&gt;&#xA;Finally, you can use the Special Quasi-random Structures (SQS) theory [&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.65.353&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt;] were you create small cells using from the analysis of the probabilities.&lt;/p&gt;&#xA;&lt;p&gt;A comparison of using some of those method with DFT for a given disordered material is discussed &lt;a href=&quot;https://arxiv.org/abs/2203.16498&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-05-09T11:45:12.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9051" PostTypeId="2" ParentId="9008" CreationDate="2022-05-09T13:00:28.720" Score="8" Body="&lt;p&gt;There are two main contributions that can be included in the DFT context when calculating phonons at finite temperature:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Thermal expansion.&lt;/strong&gt; As temperature increases, the volume of materials changes (typically increases). If you have the volume as a function of temperature, then you can calculate the phonons at each of these volumes to obtain the thermal expansion contribution to finite temperature phonons. To calculate the volumes at each temperature, a commonly used approach is the &lt;em&gt;quasi-harmonic approximation&lt;/em&gt;. In this method, you minimize the free energy at a given temperature with respect to the volume of the system, where the free energy is calculated using the harmonic approximation at each volume. To do these calculations in VASP, you simply need to do a series of harmonic phonon calculations at different volumes.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Phonon-phonon interactions.&lt;/strong&gt; As temperature increases, the harmonic approximation (in which phonons are non-interacting) becomes increasingly worse, and anharmonic phonon-phonon interactions become important. These interactions change with temperature, and lead to a renormalization of phonon frequencies with temperature. There are multiple ways in which these corrections can be incorporated, for example using the &lt;em&gt;self-consistent harmonic approximation&lt;/em&gt;, which, roughly speaking, finds the &amp;quot;best&amp;quot; harmonic fit to the anharmonic energy. I do not think that any of these methods are natively available in VASP, and instead you will probably have to use another code (potentially interfaced with VASP), such as &lt;a href=&quot;http://www.uquantchem.com/scaild.html&quot; rel=&quot;noreferrer&quot;&gt;SCAILD&lt;/a&gt; or &lt;a href=&quot;http://sscha.eu&quot; rel=&quot;noreferrer&quot;&gt;SSCHA&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Overall, both effects can be important. I am not familiar with the structures you are interested in, but in the oxide perovskties (e.g. BaTiO&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;) which also exhibit temperature driven phase transitions between different structures, phonon-phonon interactions are the dominant mechanism.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-05-09T13:00:28.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9052" PostTypeId="1" CreationDate="2022-05-09T13:27:23.510" Score="4" ViewCount="245" Body="&lt;p&gt;I used py4vasp to calculate structure from data and then I displayed them in a structure viewer (Viewer3d) by this line: &lt;code&gt;calc.structure[:].plot()&lt;/code&gt;. It returns a visualization of the structures as a 3d figure.&lt;/p&gt;&#xA;&lt;p&gt;How I can save this 3d figure?&lt;/p&gt;&#xA;&lt;p&gt;Also, If I read the structural information into a dictionary by this: &lt;code&gt;calc.structure[:].read()&lt;/code&gt;, how I can plot the structures?&lt;/p&gt;&#xA;&lt;p&gt;Here is the code which I used in the Jupyter notebook:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from py4vasp import Calculation&#xA;calc = Calculation.from_path(&amp;quot;.&amp;quot;)&#xA;calc.structure[:].plot()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5361" LastEditorUserId="5" LastEditDate="2023-05-01T16:26:40.920" LastActivityDate="2023-05-01T16:26:40.920" Title="How to save the generated 3d representation of the structure(s) by Viewer3d in Py4vasp?" Tags="|density-functional-theory|vasp|python|visualization-software|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9053" PostTypeId="1" AcceptedAnswerId="9063" CreationDate="2022-05-09T20:52:19.163" Score="5" ViewCount="594" Body="&lt;p&gt;I calculate LiH with ORCA&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%method&#xA;runtyp SP&#xA;end&#xA;%scf&#xA;  hftyp RHF        # Selects closed-shell SCF&#xA;end&#xA;%basis&#xA;    Basis &amp;quot;def2-QZVPP &amp;quot; # The orbital expansion basis set  &#xA;end&#xA;   &#xA;%coords&#xA;    CTyp xyz       # the type of coordinates = xyz or internal&#xA;    Charge 0       # the total charge of the molecule&#xA;    Mult 1         # the multiplicity = 2S+1 ; S = +1/2 - 1/2  = 1/2 &#xA;    Units Angs     # the unit of length = angs or bohrs&#xA;    coords&#xA;        Li        0.000000       0.00000        0.00000&#xA;        H         1.594900       0.00000        0.00000&#xA;    end&#xA;end&#xA;%output&#xA;    Print[ P_Basis ] 2&#xA;    Print[ P_MOs ] 1&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Results is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------&#xA;INTERNAL COORDINATES (A.U.)&#xA;---------------------------&#xA; Li     0   0   0     0.000000000000     0.00000000     0.00000000&#xA; H      1   0   0     3.013924210991     0.00000000     0.00000000&#xA;&#xA;-----------------------&#xA;MULLIKEN ATOMIC CHARGES&#xA;-----------------------&#xA;   0 Li:    0.299997&#xA;   1 H :   -0.299997&#xA;Sum of atomic charges:    0.0000000&#xA;&#xA;-------------&#xA;DIPOLE MOMENT&#xA;-------------&#xA;                                X             Y             Z&#xA;Electronic contribution:     -3.84433       0.00000       0.00000&#xA;Nuclear contribution   :      1.48516       0.00000       0.00000&#xA;                        -----------------------------------------&#xA;Total Dipole Moment    :     -2.35917       0.00000       0.00000&#xA;                        -----------------------------------------&#xA;Magnitude (a.u.)       :      2.35917&#xA;Magnitude (Debye)      :      5.99653&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Ok. I know the charges on atoms (by Mulliken) &lt;span class=&quot;math-container&quot;&gt;$q = 0.299997$&lt;/span&gt; a.u.с., also I know the distance between atoms &lt;span class=&quot;math-container&quot;&gt;$d = 3.013924210991$&lt;/span&gt; a.u. So, using classical formula for dipole momentum, I get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu = q\cdot d =  0.299997 \cdot 3.013924210991 =0.9041 \text{ a.u.} &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but ORCA calculations gives me &lt;span class=&quot;math-container&quot;&gt;$\mu = 2.35917$&lt;/span&gt; a.u.&lt;/p&gt;&#xA;&lt;p&gt;Why such a difference? Why are these charges on atoms needed if they cannot even be used to calculate the dipole moment?&lt;/p&gt;&#xA;" OwnerUserId="5264" LastEditorUserId="5264" LastEditDate="2022-05-10T06:15:30.153" LastActivityDate="2022-05-12T19:03:06.947" Title="ORCA: Dipole moment of LiH from SP calculation" Tags="|quantum-chemistry|ab-initio-calculations|orca|dipole|" AnswerCount="2" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9054" PostTypeId="2" ParentId="9034" CreationDate="2022-05-09T20:53:15.593" Score="5" Body="&lt;p&gt;If you want to test how good your theory is, you need a precise calculation produced using that theory, and you need a precise measurement to compare it against.&lt;/p&gt;&#xA;&lt;p&gt;Spectroscopy is generally the best way to make very precise and accurate physical measurements, so often it is the case that more precise spectroscopic results are what motivate the hard work required to do more precise spectroscopic calculations. The &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.030801&quot; rel=&quot;noreferrer&quot;&gt;electron g-2 measurement&lt;/a&gt;, which is the most precise match between theory and experiment in all of physics (as mentioned in the abstract of the paper you reference), is a type of spectroscopy. Doing the equivalent in helium can probe a whole host of potential extensions of the standard model, see the 2nd paragraph of &lt;a href=&quot;https://arxiv.org/pdf/1807.07923.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; for specific examples.&lt;/p&gt;&#xA;" OwnerUserId="5365" LastActivityDate="2022-05-09T20:53:15.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9056" PostTypeId="1" AcceptedAnswerId="9057" CreationDate="2022-05-10T08:35:40.960" Score="9" ViewCount="325" Body="&lt;p&gt;I am looking for the electron transport study in a single gold atom, like the system of single carbon atom shown in transiesta paper by Nick Papior et al. &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2016.09.022&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computer Physics Communications, 212, 8-24, (2017)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have connected the gold atom with linear chains of silver atoms, and has studied the effect of symmetric variation of Ag-Au separation. (Figure attached here)&lt;/p&gt;&#xA;&lt;p&gt;I am getting transmission peaks at energy slightly below the 4eV, while there is no energy level in the discrete levels of single gold, and the PDOS plot. Moreover, the position of a peak near the Fermi level is not consistent with the position of the discrete system.&lt;/p&gt;&#xA;&lt;p&gt;To mention these calculations are done for zero bias, so in principle, resonant tunneling is expected.&lt;/p&gt;&#xA;&lt;p&gt;Also, as a result of increasing Ag-Au separation, there is more suppression of transmission in some channels, while some attain the same height. Last subplot show discrete levels of gold atom.&lt;/p&gt;&#xA;&lt;p&gt;I have these queries:&lt;/p&gt;&#xA;&lt;p&gt;(a) Why is transiesta giving the peaks where there is no energy level?&lt;/p&gt;&#xA;&lt;p&gt;(b) Is the separation in peaks here describe the weak Ag-Au coupling?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5P8GH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5P8GH.png&quot; alt=&quot;electron transport in a single gold atom, black line for up-spin and red line for down-spin channels. Last subplot show discrete levels of gold atom&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5366" LastEditorUserId="1518" LastEditDate="2022-05-11T16:36:04.363" LastActivityDate="2022-05-11T16:36:04.363" Title="Transiesta output through a single gold atom" Tags="|density-functional-theory|siesta|electronic-transport|charge-transfer|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9057" PostTypeId="2" ParentId="9056" CreationDate="2022-05-10T08:55:00.227" Score="7" Body="&lt;p&gt;With a single atom there might be leakage current. Probably, if you had more Au atoms the transmission would be fully suppressed.&lt;/p&gt;&#xA;&lt;p&gt;The 4 eV peak is likely close to a van-Hove singularity of the electrode chains and hence the DOS goes to infinity. So any small(tiny) transmission probability will show it self when the DOS is exceedingly large.&lt;/p&gt;&#xA;&lt;p&gt;You can clearly see that the longer separation yields a narrower Lorentizian meaning that you are very weakly coupling the single-atom.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-05-10T08:55:00.227" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9059" PostTypeId="1" AcceptedAnswerId="9061" CreationDate="2022-05-11T12:18:30.233" Score="8" ViewCount="397" Body="&lt;p&gt;I have recently come across this very intriguing paper “&lt;a href=&quot;https://arxiv.org/pdf/1304.6390.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Fundamental Vibration of Molecular Hydrogen&lt;/a&gt;”.&lt;/p&gt;&#xA;&lt;p&gt;I have asked the authors the following naïve questions directly via email:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;What was the amount of computer memory used by the full &lt;em&gt;ab initio&lt;/em&gt; calculation?&lt;/li&gt;&#xA;&lt;li&gt;What was the time-to-solution of the full &lt;em&gt;ab initio&lt;/em&gt; calculation?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;While I wait for their response, could anyone help me to make a ball park estimate of those two answers?&lt;/p&gt;&#xA;" OwnerUserId="5197" LastEditorUserId="5" LastEditDate="2022-05-11T22:27:48.443" LastActivityDate="2022-05-11T22:27:48.443" Title="How much does it cost (RAM and CPU) to calculate the energy of H2?" Tags="|molecular-modeling|high-performance-computing|spectroscopy|vibrations|high-precision|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9060" PostTypeId="1" AcceptedAnswerId="9062" CreationDate="2022-05-11T16:13:51.703" Score="3" ViewCount="399" Body="&lt;p&gt;I want to calculate the bond coefficient values to be used in bond_coeff command in LAMMPS input file. According to LAMMPS documentation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://docs.lammps.org/units.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.lammps.org/units.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;x*=x/sigma gives me the unitless (lj units) value of distance. my question is what is the related sigma and epsilon for Carbon-Carbon ? (I have a triangular lattice)&lt;/p&gt;&#xA;&lt;p&gt;In general how or where to find the sigma and epsilon values for different materials?&lt;/p&gt;&#xA;&lt;p&gt;Does any body know the C-C bond coeffiecient value in lj units?&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-05-11T18:03:16.560" Title="How to choose sigma and epsilon value for carbon to calculate the bond coeff (lj units) in LAMMPS?" Tags="|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9061" PostTypeId="2" ParentId="9059" CreationDate="2022-05-11T16:52:29.947" Score="6" Body="&lt;p&gt;Out of all authors on that paper, most of them are experimentalists, but Krzysztof Pachucki is known as the &amp;quot;&lt;strong&gt;King of H&lt;sub&gt;2&lt;/sub&gt; calculations&lt;/strong&gt;&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Three years after the paper you mentioned, Pachucki made the software freely available &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465516302120&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. The abstract of the associated paper mentions that the paper provides &lt;strong&gt;benchmark results up to 18 digits&lt;/strong&gt;, for example see this table of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; energies (it actually looks like the energies are converged even if rounded at the 19th or 20th digits):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uboAb.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uboAb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In terms of RAM, the paper says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;RAM: From several Mbytes to 512 Gbytes, depending on the size of the basis.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In terms of CPU time the paper says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Running time: From seconds to days, depending on the size of the basis.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But keep in mind that the paper is talking about converging to energy to 18+ a.u. digits in the most extreme cases, whereas the 2013 paper mentioned in your question is only talking about precision on the &lt;span class=&quot;math-container&quot;&gt;$10^{-4}$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; scale, which means no more than 11 a.u. digits. So I would ignore the &amp;quot;512GB of RAM&amp;quot;  and &amp;quot;days of CPU time&amp;quot; which are listed as the upper limits of the algorithm's cost, and I'd just focus on the lower limits which are &amp;quot;several MB of RAM&amp;quot; and &amp;quot;seconds of CPU time&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Also, the paper says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The parallelization of the calculation&#xA;of integrals in H2SOLV is almost 100% efficient, so that the evaluation time&#xA;is inversely proportional to the number of available cores (threads).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So whatever the CPU time is, you can make it half of that by doubling the number of cores (something that's usually quite easy to do these days).&lt;/p&gt;&#xA;&lt;p&gt;The one place where &amp;quot;CPU&amp;quot; appears in the paper is here:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The computation time of H2SOLV with the input example specified above&#xA;is about a minute on a dual processor Intel Xeon CPU E5-2680 v3 2.50GHz.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-05-11T16:52:29.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9062" PostTypeId="2" ParentId="9060" CreationDate="2022-05-11T18:03:16.560" Score="5" Body="&lt;p&gt;You can search for literature where people have used different potentials for your elements. LJ potential is fine to start with, but it has very less degree of freedom so that many different properties cannot be matched.&#xA;A well know database given in open-kim website for different elements in periodic table and corresponding LJ parameters.&#xA;&lt;a href=&quot;https://openkim.org/files/MO_959249795837_003/LennardJones612_UniversalShifted.params&quot; rel=&quot;noreferrer&quot;&gt;https://openkim.org/files/MO_959249795837_003/LennardJones612_UniversalShifted.params&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-05-11T18:03:16.560" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9063" PostTypeId="2" ParentId="9053" CreationDate="2022-05-11T18:18:05.947" Score="9" Body="&lt;p&gt;As suggested by Tyberius, I now expand my comment into an answer.&lt;/p&gt;&#xA;&lt;p&gt;The true charge density of a molecule is a sum of nuclear and electronic contributions. While the former is a sum of delta functions (under the Born-Oppenheimer approximation and neglecting the finite nuclear size effects), the latter has the form of an electronic cloud. Thus, the usual picture that Li bears some positive charge and H bears some negative charge is necessarily a simplification, since the electrons do not just reside on the Li and H centers, but are floating around them; moreover they do not float around the nuclei in a &amp;quot;symmetric&amp;quot; fashion, but will spend more time between the nuclei, compared to what would be expected if the electron density of LiH is simply a sum of two spherically symmetric densities.&lt;/p&gt;&#xA;&lt;p&gt;The important corollary is that, no atomic charge can exactly reproduce the electric field of the LiH molecule, or essentially any molecule with more than one atom. With diatomic molecules, one is lucky enough that there is a choice of atomic charges that exactly reproduces the dipole moment (and the choice is unique). But this only means that they reproduce the leading order (&lt;span class=&quot;math-container&quot;&gt;$R^{-3}$&lt;/span&gt;) term of the electric field exactly; the higher order terms (quadrupole &lt;span class=&quot;math-container&quot;&gt;$R^{-4}$&lt;/span&gt;, octupole &lt;span class=&quot;math-container&quot;&gt;$R^{-5}$&lt;/span&gt; etc.) are not necessarily calculated exactly or even accurately. As all chemistry happens at a finite distance from a molecule, one is rarely solely interested in reproducing the dipole moment alone. That is to say, yes, the dipole moment is more important than the quadrupole moments, even more than the octupole moments, etc., but one is usually happy to sacrifice a little accuracy in the dipole moment for a large improvement of the higher multipole moments. Thus, although it is usually a good thing to have the atomic charges reproduce the dipole moments approximately, there is basically no practical gain with reproducing them exactly.&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless, you can see that the dipole moment predicted by the Mulliken charges does not even approximately reproduce the correct dipole moment calculated at the same level of theory. Why? Well, this simply means that Mulliken charges are generally not very useful, as already mentioned in the link that Geoff posted in his comment. Nevertheless, quantum chemistry programs usually calculate them (plus the similarly unreliable Löwdin charges), because they are trivial to implement and extremely cheap to calculate, so that calculating them does more good than bad. Besides, one important application of atomic charges is to rationalize experimental observations (like chemical reactivity), in which case the atomic charges need not be quantitatively accurate; rather, they only need to change in the correct direction when you change the substituents, conformation, etc., of the molecule. Usually, almost all atomic charge models satisfy this requirement. For more quantitative studies that require e.g. plotting the logarithm of reaction rate constant against an atomic charge, there is a more stringent requirement that the atomic charge must be approximately a linear function of the &amp;quot;true&amp;quot; atomic charge with a positive slope, but Mulliken charges usually satisfy even this requirement. Nevertheless, more robust charges like Hirshfeld and NPA charges are not much more expensive than Mulliken charges, and it is generally recommended to use these charges even when Mulliken charges probably suffice, at the cost of merely a few seconds to minutes of additional computational time. For example, see &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.macromol.9b02066&quot; rel=&quot;noreferrer&quot;&gt;my article&lt;/a&gt; which plotted the logarithms of polymerization rate constants against the NPA charges of the radical centers of the polymer chain radicals, and obtained a nice linear relation; one can thus predict the polymerization rates of novel monomers by an NPA calculation, instead of a much more expensive transition state search.&lt;/p&gt;&#xA;&lt;p&gt;Finally, if your application specifically requires that the charges should reproduce the electric field of the molecule as closely as possible, you should use atomic charges that are obtained by fitting the molecular electrostatic potential, such as the RESP, MK or CHELPG charges (ORCA supports the last one, which should be explicitly requested by the &amp;quot;! CHELPG&amp;quot; keyword). This usually happens when you want to fit a force field. As I said before, these give charges that reproduce the dipole moment very accurately, but not exactly, as the methods also take care to approximately reproduce the higher multipole moments, which compromises the accuracy of the dipole moment.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-05-11T18:18:05.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9064" PostTypeId="1" CreationDate="2022-05-11T18:51:29.017" Score="6" ViewCount="81" Body="&lt;p&gt;Can we somehow predict what sort of modulation doping will do to a material without actually running any calculations? For instance, could we use the already known density of states (DOS) of Zn to predict whether the band gap of CdSe will decrease or increase when Zn is added as a dopant?&lt;/p&gt;&#xA;&lt;p&gt;I am currently attempting to modulate certain properties and considering potential dopants. Typically, people conduct experiments first and then seek justification. However, it would be quite interesting if there is a method of prediction. I am not claiming it will always work, but having a logical reasoning path for this type of situation would be intriguing.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="1554" LastEditDate="2023-12-27T10:59:52.140" LastActivityDate="2023-12-27T10:59:52.140" Title="Predicting the band gap or some other properties of materials before running any calculations" Tags="|density-functional-theory|physical-properties-of-materials|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-28T00:31:38.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="9065" PostTypeId="1" CreationDate="2022-05-12T07:03:27.503" Score="6" ViewCount="642" Body="&lt;p&gt;I am a sort-of-beginner in Quantum Espresso. I do understand certain terminology in the INPUT file but I am faced with a dilemma. I have been trying to optimize &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}(110)$&lt;/span&gt; system of 100 atoms using the &lt;code&gt;relax&lt;/code&gt; keyword. I would like to know if my input file has any mistakes, as I am not able to achieve convergence even after a 1000 iterations.&lt;/p&gt;&#xA;&lt;p&gt;Below, I have added the INPUT and OUTPUT files.&lt;/p&gt;&#xA;&lt;p&gt;I realize that the Total Energy is very different at every iteration, but is it supposed to be like that after 1000 iterations. Any help or advice would be much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;INPUT&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation   = &amp;quot;relax&amp;quot;&#xA;forc_conv_thr =  1.00000e-03&#xA;max_seconds   =  1.72800e+05&#xA;nstep         = 201&#xA;pseudo_dir    = &amp;quot;C:\Users\ECR2017-001147-SYS-2\.burai\.pseudopot&amp;quot;&#xA;/&#xA;&amp;amp;SYSTEM&#xA;a                         =  2.02685e+01&#xA;angle1(1)                 =  0.00000e+00&#xA;angle2(1)                 =  0.00000e+00&#xA;b                         =  1.43320e+01&#xA;c                         =  3.02685e+01&#xA;degauss                   =  2.00000e-02&#xA;ecutrho                   =  3.00000e+02&#xA;ecutwfc                   =  3.00000e+01&#xA;ibrav                     = 9&#xA;nat                       = 100&#xA;nspin                     = 1&#xA;ntyp                      = 1&#xA;occupations               = &amp;quot;smearing&amp;quot;&#xA;smearing                  = &amp;quot;marzari-vanderbilt&amp;quot;&#xA;starting_magnetization(1) =  0.00000e+00&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;conv_thr         =  1.00000e-06&#xA;electron_maxstep = 1000&#xA;mixing_beta      =  4.00000e-01&#xA;startingpot      = &amp;quot;atomic&amp;quot;&#xA;startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&amp;amp;IONS&#xA;ion_dynamics = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&amp;amp;CELL&#xA;/&#xA;K_POINTS {gamma}&#xA;ATOMIC_SPECIES&#xA;Fe     55.84500  Fe.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Fe      0.000000   0.000000  22.161105&#xA;Fe      0.000000   0.000000  26.214807  0 0 0&#xA;Fe     -2.026851   1.433200  22.161105&#xA;Fe     -2.026851   1.433200  26.214807  0 0 0&#xA;Fe     -4.053702   2.866400  22.161105&#xA;Fe     -4.053702   2.866400  26.214807  0 0 0&#xA;Fe     -6.080553   4.299600  22.161105&#xA;Fe     -6.080553   4.299600  26.214807  0 0 0&#xA;Fe     -8.107403   5.732800  22.161105&#xA;Fe     -8.107403   5.732800  26.214807  0 0 0&#xA;Fe      2.026851   1.433200  22.161105&#xA;Fe      2.026851   1.433200  26.214807  0 0 0&#xA;Fe      0.000000   2.866400  22.161105&#xA;Fe      0.000000   2.866400  26.214807  0 0 0&#xA;Fe     -2.026851   4.299600  22.161105&#xA;Fe     -2.026851   4.299600  26.214807  0 0 0&#xA;Fe     -4.053702   5.732800  22.161105&#xA;Fe     -4.053702   5.732800  26.214807  0 0 0&#xA;Fe     -6.080553   7.166000  22.161105&#xA;Fe     -6.080553   7.166000  26.214807  0 0 0&#xA;Fe      4.053702   2.866400  22.161105&#xA;Fe      4.053702   2.866400  26.214807  0 0 0&#xA;Fe      2.026851   4.299600  22.161105&#xA;Fe      2.026851   4.299600  26.214807  0 0 0&#xA;Fe      0.000000   5.732800  22.161105&#xA;Fe      0.000000   5.732800  26.214807  0 0 0&#xA;Fe     -2.026851   7.166000  22.161105&#xA;Fe     -2.026851   7.166000  26.214807  0 0 0&#xA;Fe     -4.053702   8.599200  22.161105&#xA;Fe     -4.053702   8.599200  26.214807  0 0 0&#xA;Fe      6.080553   4.299600  22.161105&#xA;Fe      6.080553   4.299600  26.214807  0 0 0&#xA;Fe      4.053702   5.732800  22.161105&#xA;Fe      4.053702   5.732800  26.214807  0 0 0&#xA;Fe      2.026851   7.166000  22.161105&#xA;Fe      2.026851   7.166000  26.214807  0 0 0&#xA;Fe      0.000000   8.599200  22.161105&#xA;Fe      0.000000   8.599200  26.214807  0 0 0&#xA;Fe     -2.026851  10.032400  22.161105&#xA;Fe     -2.026851  10.032400  26.214807  0 0 0&#xA;Fe      8.107403   5.732800  22.161105&#xA;Fe      8.107403   5.732800  26.214807  0 0 0&#xA;Fe      6.080553   7.166000  22.161105&#xA;Fe      6.080553   7.166000  26.214807  0 0 0&#xA;Fe      4.053702   8.599200  22.161105&#xA;Fe      4.053702   8.599200  26.214807  0 0 0&#xA;Fe      2.026851  10.032400  22.161105&#xA;Fe      2.026851  10.032400  26.214807  0 0 0&#xA;Fe      0.000000  11.465600  22.161105&#xA;Fe      0.000000  11.465600  26.214807  0 0 0&#xA;Fe      0.000000   1.433200  24.187956&#xA;Fe      0.000000   1.433200  28.241658  0 0 0&#xA;Fe     -2.026851   2.866400  24.187956&#xA;Fe     -2.026851   2.866400  28.241658  0 0 0&#xA;Fe     -4.053702   4.299600  24.187956&#xA;Fe     -4.053702   4.299600  28.241658  0 0 0&#xA;Fe     -6.080553   5.732800  24.187956&#xA;Fe     -6.080553   5.732800  28.241658  0 0 0&#xA;Fe     -8.107403   7.166000  24.187956&#xA;Fe     -8.107403   7.166000  28.241658  0 0 0&#xA;Fe      2.026851   2.866400  24.187956&#xA;Fe      2.026851   2.866400  28.241658  0 0 0&#xA;Fe      0.000000   4.299600  24.187956&#xA;Fe      0.000000   4.299600  28.241658  0 0 0&#xA;Fe     -2.026851   5.732800  24.187956&#xA;Fe     -2.026851   5.732800  28.241658  0 0 0&#xA;Fe     -4.053702   7.166000  24.187956&#xA;Fe     -4.053702   7.166000  28.241658  0 0 0&#xA;Fe     -6.080553   8.599200  24.187956&#xA;Fe     -6.080553   8.599200  28.241658  0 0 0&#xA;Fe      4.053702   4.299600  24.187956&#xA;Fe      4.053702   4.299600  28.241658  0 0 0&#xA;Fe      2.026851   5.732800  24.187956&#xA;Fe      2.026851   5.732800  28.241658  0 0 0&#xA;Fe      0.000000   7.166000  24.187956&#xA;Fe      0.000000   7.166000  28.241658  0 0 0&#xA;Fe     -2.026851   8.599200  24.187956&#xA;Fe     -2.026851   8.599200  28.241658  0 0 0&#xA;Fe     -4.053702  10.032400  24.187956&#xA;Fe     -4.053702  10.032400  28.241658  0 0 0&#xA;Fe      6.080553   5.732800  24.187956&#xA;Fe      6.080553   5.732800  28.241658  0 0 0&#xA;Fe      4.053702   7.166000  24.187956&#xA;Fe      4.053702   7.166000  28.241658  0 0 0&#xA;Fe      2.026851   8.599200  24.187956&#xA;Fe      2.026851   8.599200  28.241658  0 0 0&#xA;Fe      0.000000  10.032400  24.187956&#xA;Fe      0.000000  10.032400  28.241658  0 0 0&#xA;Fe     -2.026851  11.465600  24.187956&#xA;Fe     -2.026851  11.465600  28.241658  0 0 0&#xA;Fe      8.107403   7.166000  24.187956&#xA;Fe      8.107403   7.166000  28.241658  0 0 0&#xA;Fe      6.080553   8.599200  24.187956&#xA;Fe      6.080553   8.599200  28.241658  0 0 0&#xA;Fe      4.053702  10.032400  24.187956&#xA;Fe      4.053702  10.032400  28.241658  0 0 0&#xA;Fe      2.026851  11.465600  24.187956&#xA;Fe      2.026851  11.465600  28.241658  0 0 0&#xA;Fe      0.000000  12.898800  24.187956&#xA;Fe      0.000000  12.898800  28.241658  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;OUTPUT&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; iteration #997     ecut=    30.00 Ry     beta= 0.40&#xA; Davidson diagonalization with overlap&#xA; ethr =  1.00E-02,  avg # of iterations = 12.0&#xA;&#xA; negative rho (up, down):  1.395E-02 0.000E+00&#xA;&#xA; total cpu time spent up to now is    22170.2 secs&#xA;&#xA; total energy              =   -5973.86651878 Ry&#xA; estimated scf accuracy    &amp;lt;    5458.14010799 Ry&#xA;&#xA; iteration #998     ecut=    30.00 Ry     beta= 0.40&#xA; Davidson diagonalization with overlap&#xA; ethr =  1.00E-02,  avg # of iterations = 10.0&#xA;&#xA; negative rho (up, down):  1.534E-02 0.000E+00&#xA;&#xA; total cpu time spent up to now is    22192.6 secs&#xA;&#xA; total energy              =   -5974.20572642 Ry&#xA; estimated scf accuracy    &amp;lt;    5314.30707048 Ry&#xA;&#xA; iteration #999     ecut=    30.00 Ry     beta= 0.40&#xA; Davidson diagonalization with overlap&#xA; ethr =  1.00E-02,  avg # of iterations = 11.0&#xA;&#xA; negative rho (up, down):  1.396E-02 0.000E+00&#xA;&#xA; total cpu time spent up to now is    22216.5 secs&#xA;&#xA; total energy              =   -5975.49792049 Ry&#xA; estimated scf accuracy    &amp;lt;    5150.12853865 Ry&#xA;&#xA; iteration #***     ecut=    30.00 Ry     beta= 0.40&#xA; Davidson diagonalization with overlap&#xA; ethr =  1.00E-02,  avg # of iterations = 10.0&#xA;&#xA; negative rho (up, down):  1.289E-02 0.000E+00&#xA;&#xA; total cpu time spent up to now is    22239.0 secs&#xA;&#xA; total energy              =   -5926.34136165 Ry&#xA; estimated scf accuracy    &amp;lt;    6965.42552475 Ry&#xA;&#xA; End of self-consistent calculation&#xA;&#xA; convergence NOT achieved after *** iterations: stopping&#xA;&#xA; Writing config to output data dir ./pwscf.save/&#xA; Message from routine punch:&#xA; wavefunctions written to file&#xA;&#xA; init_run     :      6.72s CPU      7.14s WALL (       1 calls)&#xA; electrons    :  21312.84s CPU  22231.70s WALL (       1 calls)&#xA;&#xA; Called by init_run:&#xA; wfcinit      :      3.38s CPU      3.61s WALL (       1 calls)&#xA; potinit      :      1.01s CPU      1.05s WALL (       1 calls)&#xA; hinit0       :      1.33s CPU      1.37s WALL (       1 calls)&#xA;&#xA; Called by electrons:&#xA; c_bands      :  19475.35s CPU  20150.60s WALL (    1000 calls)&#xA; sum_band     :   1204.55s CPU   1345.18s WALL (    1000 calls)&#xA; v_of_rho     :    219.62s CPU    234.73s WALL (    1001 calls)&#xA; newd         :    342.84s CPU    427.16s WALL (    1001 calls)&#xA; mix_rho      :     44.44s CPU     46.55s WALL (    1000 calls)&#xA;&#xA; Called by c_bands:&#xA; init_us_2    :     65.20s CPU     65.53s WALL (    2001 calls)&#xA; init_us_2:cp :     65.18s CPU     65.52s WALL (    2001 calls)&#xA; regterg      :  19356.44s CPU  20031.09s WALL (    1000 calls)&#xA;&#xA; Called by *egterg:&#xA; rdiaghg      :   4324.36s CPU   4337.94s WALL (   11588 calls)&#xA; h_psi        :   9622.94s CPU  10165.80s WALL (   11589 calls)&#xA; s_psi        :   1153.42s CPU   1157.94s WALL (   11589 calls)&#xA; g_psi        :     37.50s CPU     37.78s WALL (   10588 calls)&#xA;&#xA; Called by h_psi:&#xA; h_psi:calbec :   1276.51s CPU   1321.47s WALL (   11589 calls)&#xA; vloc_psi     :   7109.30s CPU   7597.77s WALL (   11589 calls)&#xA; add_vuspsi   :   1148.67s CPU   1157.60s WALL (   11589 calls)&#xA;&#xA; General routines&#xA; calbec       :   1422.99s CPU   1473.42s WALL (   12589 calls)&#xA; fft          :    133.28s CPU    146.87s WALL (   11011 calls)&#xA; ffts         :      4.20s CPU      4.74s WALL (    2001 calls)&#xA; fftw         :   4916.73s CPU   5316.44s WALL ( 4112726 calls)&#xA; interpolate  :     15.78s CPU     17.07s WALL (    1001 calls)&#xA; davcio       :      0.01s CPU      0.22s WALL (      19 calls)&#xA;&#xA;&#xA;&#xA;  Parallel routines&#xA;&#xA;     PWSCF        :      5h55m CPU      6h10m WALL&#xA;&#xA;&#xA;   This run was terminated on:  22:47:47  11May2022            &#xA;&#xA;=------------------------------------------------------------------------------=&#xA;   JOB DONE.&#xA;=------------------------------------------------------------------------------=&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5378" LastEditorUserId="7" LastEditDate="2022-06-01T16:28:44.677" LastActivityDate="2022-07-20T05:40:43.490" Title="Converging geometry of iron slab" Tags="|quantum-espresso|geometry-optimization|cell-optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9066" PostTypeId="1" AcceptedAnswerId="9090" CreationDate="2022-05-12T07:40:51.913" Score="2" ViewCount="290" Body="&lt;p&gt;I've installed presumably the latest executable version of &lt;a href=&quot;https://en.wikipedia.org/wiki/LAMMPS&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS&lt;/a&gt; for macOS from  &lt;a href=&quot;https://docs.lammps.org/Install_mac.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.lammps.org/Install_mac.html&lt;/a&gt; and tried to run the following tutorial &lt;a href=&quot;https://github.com/mrkllntschpp/lammps-tutorials&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/mrkllntschpp/lammps-tutorials&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I scroll down and see &lt;a href=&quot;https://github.com/mrkllntschpp/lammps-tutorials/blob/master/LAMMPS-Tutorials-01.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;Click here to open Tutorial 1.&lt;/a&gt; Run LAMMPS! Learn how to calculate the minimum energy lattice structure&lt;/p&gt;&#xA;&lt;p&gt;The final lines of the example output on that page are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Total # of neighbors = 280&#xA;Ave neighs/atom = 70&#xA;Neighbor list builds = 0&#xA;Dangerous builds = 0&#xA;Total energy (eV) = -13.4399999527352;&#xA;Number of atoms = 4;&#xA;Lattice constant (Angstoms) = 4.05000466178543;&#xA;Cohesive energy (eV) = -3.3599999881838;&#xA;All done!&#xA;Total wall time: 0:00:00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;That's certainly the right lattice constant for fcc bulk aluminum.&lt;/p&gt;&#xA;&lt;p&gt;I'm &lt;a href=&quot;https://academia.stackexchange.com/questions/184841/scientific-paper-with-3d-scatterplot-in-supplementary-information-i-can-add-a-v#comment497387_184842&quot;&gt;not yet&lt;/a&gt; a Jupyter notebook user and prefer to work directly from a command line. I've located and downloaded the Al99.eam.alloy potential mentioned in the linked tutorial by clicking on aluminum on the periodic table of elements here &lt;a href=&quot;https://www.ctcms.nist.gov/potentials/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ctcms.nist.gov/potentials/&lt;/a&gt; and searching for the name of the potential.&lt;/p&gt;&#xA;&lt;p&gt;I cd to the directory containing these files and enter&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; lmp_serial &amp;lt; calc_fcc.in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and get the results shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Total # of neighbors = 560&#xA;Ave neighs/atom = 70.000000&#xA;Neighbor list builds = 0&#xA;Dangerous builds = 0&#xA;Total energy (eV) = -26.8799999054703;&#xA;Number of atoms = 8;&#xA;Lattice constant (Angstoms) = 5.72757152037121;&#xA;Cohesive energy (eV) = -3.35999998818379;&#xA;All done!&#xA;Total wall time: 0:00:00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are a few obvious differences besides lattice constant, Total # of neighbors is 560 instead of 280 and Number of atoms is 8 instead of 4.&lt;/p&gt;&#xA;&lt;p&gt;Any ideas what I've got to change to get the correct results?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;my copy/paste reconstructed &lt;code&gt;calc_fcc.in&lt;/code&gt; from the tutorial:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# writefile calc_fcc.in&#xA;######################################&#xA;# LAMMPS INPUT SCRIPT&#xA;# Find minimum energy fcc (face-centered cubic) atomic configuration&#xA;# Mark Tschopp&#xA;# Syntax, lmp_exe &amp;lt; calc_fcc.in&#xA;&#xA;######################################&#xA;# INITIALIZATION&#xA;clear &#xA;units metal &#xA;dimension 3 &#xA;boundary p p p &#xA;atom_style atomic &#xA;atom_modify map array&#xA;&#xA;######################################&#xA;# ATOM DEFINITION&#xA;lattice fcc 4 orient x 1 1 0 orient y -1 1 0 orient z 0 0 1  &#xA;region box block 0 1 0 1 0 1 units lattice&#xA;create_box 1 box&#xA;create_atoms 1 box&#xA;replicate 1 1 1&#xA;&#xA;######################################&#xA;# DEFINE INTERATOMIC POTENTIAL&#xA;pair_style eam/alloy &#xA;pair_coeff * * Q_Al99.eam.alloy Al&#xA;neighbor 2.0 bin &#xA;neigh_modify delay 10 check yes &#xA; &#xA;######################################&#xA;# DEFINE COMPUTES &#xA;compute eng all pe/atom &#xA;compute eatoms all reduce sum c_eng &#xA;&#xA;#####################################################&#xA;# MINIMIZATION&#xA;reset_timestep 0 &#xA;fix 1 all box/relax iso 0.0 vmax 0.001&#xA;thermo 10 &#xA;thermo_style custom step pe lx ly lz press c_eatoms &#xA;min_style cg &#xA;minimize 1e-25 1e-25 5000 10000 &#xA;&#xA;variable natoms equal &amp;quot;count(all)&amp;quot; &#xA;variable teng equal &amp;quot;c_eatoms&amp;quot;&#xA;variable length equal &amp;quot;lx&amp;quot;&#xA;variable ecoh equal &amp;quot;v_teng/v_natoms&amp;quot;&#xA;&#xA;print &amp;quot;Total energy (eV) = &lt;span class=&quot;math-container&quot;&gt;${teng};&quot;&#xA;print &quot;Number of atoms = $&lt;/span&gt;{natoms};&amp;quot;&#xA;print &amp;quot;Lattice constant (Angstoms) = &lt;span class=&quot;math-container&quot;&gt;${length};&quot;&#xA;print &quot;Cohesive energy (eV) = $&lt;/span&gt;{ecoh};&amp;quot;&#xA;&#xA;print &amp;quot;All done!&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It's 30,006 lines long but here are the first and last few lines of my &lt;code&gt;Al99.eam.alloy&lt;/code&gt; for verification purposes:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Al EAM from Phys. Rev. B 59, 3393 (1999) in the LAMMPS setfl format.    &#xA; Conversion by C. A. Becker from Y. Mishin files.                        &#xA; 30 December 2008.  http://www.ctcms.nist.gov/potentials                 &#xA;            1 Al  &#xA;10000   0.2000000000000000E-03   10000  0.6287210000000000E-03  0.6287210000000000E+01&#xA;   13    0.2698200000E+02    0.4050000000E+01      fcc                                                                     &#xA;   0.1042222107228152E-09&#xA;  -0.2833153928160009E-02&#xA;  -0.5663286303573338E-02&#xA;  -0.8490398933217783E-02&#xA;  -0.1131449372829334E-01&#xA;  -0.1413557260000000E-01&#xA;  -0.1695363745953778E-01&#xA;  -0.1976869021810666E-01&#xA;  -0.2258073278690667E-01&#xA;  -0.2538976707713778E-01&#xA;&#xA;[...]&#xA;&#xA;  -0.3352109479779516E-07&#xA;  -0.2444230228083147E-07&#xA;  -0.1717018845557266E-07&#xA;  -0.1150495861170407E-07&#xA;  -0.7246423756161589E-08&#xA;  -0.4194276244510321E-08&#xA;  -0.2147863624012600E-08&#xA;  -0.9062527475633544E-09&#xA;  -0.2684334141141742E-09&#xA;  -0.3337655546827989E-10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2022-05-12T07:48:37.900" LastActivityDate="2022-05-16T02:23:09.263" Title="Okay, I've installed LAMMPS I: My first try of an example gives different &amp; incorrect output" Tags="|lammps|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9067" PostTypeId="1" CreationDate="2022-05-12T07:49:15.597" Score="1" ViewCount="73" Body="&lt;p&gt;I am considering simulating the size effect of nanoparticles, the size expands from 0.2nm to 50nm, but when trying to build the model, I am not sure how to reflect the size correctly, for example, if I wanna build a supercell which is 50nm long, then it would contain thousands of atoms. It is gonna very expansive to do DFT simulation for such a big supercell.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;Is there any method that allows me to analyze the size effect without building a huge supercell?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-12T07:49:15.597" Title="how to simulate the size effect with DFT theory?" Tags="|density-functional-theory|vasp|quantum-size-effects|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-01T21:52:05.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="9068" PostTypeId="1" AcceptedAnswerId="9084" CreationDate="2022-05-12T07:58:22.657" Score="5" ViewCount="694" Body="&lt;p&gt;I've installed and can run &lt;a href=&quot;https://en.wikipedia.org/wiki/LAMMPS&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS&lt;/a&gt; on macOS as desdribed in &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9066/201&quot;&gt;Okay, I&amp;#39;ve installed LAMMPS I: My first try of an example gives different &amp;amp; incorrect output&lt;/a&gt; and I'm looking forward to my first Xene experience! I've found &lt;a href=&quot;https://lammpstutorials.github.io/tutorials/04-Graphene.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://lammpstutorials.github.io/tutorials/04-Graphene.html&lt;/a&gt; which begins:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://lammpstutorials.github.io/tutorials/04-Graphene.html#Graphene&quot; rel=&quot;nofollow noreferrer&quot;&gt;Graphene sheet&lt;/a&gt; - First, a graphene sheet will be generated using VMD-topotool. The sheet will be deformed using applied displacement.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and that section begins:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Generation of the system&#xA;The initial configuration (atoms positions, bonds, angles, etc.) is generated using VMD. Open &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VMD&lt;/a&gt;, and go to Extensions, Modeling, Nanotube Builder. A window named Carbon Nanostructures opens, and from this window it is possible to generate a sheet of graphene or BN, as well as a nanotube. For now tutorial, we are going to generate a 4 nm per 4 nm sheet of graphene. Simply change the values of &amp;quot;Edge length along x&amp;quot; and &amp;quot;Edge length along y&amp;quot; to 4, and click on &amp;quot;Generate Sheet(s)&amp;quot;. You shoud see this:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PCh5h.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PCh5h.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, at least from where I live I can not even get the following links to work:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ks.uiuc.edu/Research/vmd/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/plugins/topotools/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ks.uiuc.edu/Research/vmd/plugins/topotools/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and in any event I'll be building my own honeycomb structure to include buckling and defects. So I'd like to ask:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; I'd like to make a small graphene flake for a LAMMPS simulation using my Python script (not someone else's program), but how?&lt;/p&gt;&#xA;&lt;p&gt;I was hoping on reverse-engineering the output file from the VMD-toptool and generating a new one from my python script but now I have nothing to go on. I'm assuming it's a text file with atomic positions on a honeycomb lattice but not sure what else needs to be in it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;update 1:&lt;/strong&gt; this tutorial looks promising&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=eIHQHlbxtmk&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=eIHQHlbxtmk&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;update 2:&lt;/strong&gt; potentially very helpful!&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6718/201&quot;&gt;How to make input script file for nanoparticle using LAMMPS?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="201" LastEditorUserId="30" LastEditDate="2022-05-15T19:05:47.947" LastActivityDate="2022-05-15T19:05:47.947" Title="How can I create a small graphene flake for LAMMPS?" Tags="|lammps|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9069" PostTypeId="2" ParentId="9053" CreationDate="2022-05-12T08:22:17.000" Score="5" Body="&lt;p&gt;&lt;strong&gt;Dipole moment in Quantum Mechanicl&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I dare to expand the answer of wzkchem5, taking into account how I understood (with some math).&lt;/p&gt;&#xA;&lt;p&gt;The dipole moment of molecular system (which is described by wave function &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt;) is an observabe, so in QM we can write:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation*}&#xA;    \vec{\mu} = \int \Phi^* \hat{\mu} \,\, \Phi \vec{r}.&#xA;\end{equation*}&lt;/span&gt;&#xA;which leads to&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\label{DM}\tag{DM}&#xA;    \vec{\mu} = \int\limits_V \vec{r} \left[\sum Z_A \delta(\vec{r} - \vec{R}_A) - \rho(x,y,x)\right]  d\vec{r},&#xA;\end{equation}&lt;/span&gt;&#xA;or in nucleus - electrons separated form&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\label{N-e}\tag{N - e}&#xA;\vec{\mu} = \sum_a Z_a \vec{R}_a - \int \vec{r} \rho(x,y,x) d\vec{r},&#xA;\end{equation}&lt;/span&gt;&#xA;This formula from quantum mechanics is similar to classical one, where &lt;span class=&quot;math-container&quot;&gt;$\rho (x,y,z)$&lt;/span&gt; --- electron charge density.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Calculation of dipole moment by RHF method&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In RHF (with MO LCAO) approximation, the \eqref{DM} leads to&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\label{DM LCAO} \tag{DM from LCAO}&#xA;\vec{\mu} = \sum_A Z_A\vec{R}_A - 2 \sum_p\sum_q P_{pq}\int_V \vec{r} \chi_p^* \chi_q  d\vec{r},&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\{P_{pq}\}$&lt;/span&gt; -- density matrix, &lt;span class=&quot;math-container&quot;&gt;$\chi_q$&lt;/span&gt; --- basis set functions.&lt;/p&gt;&#xA;&lt;p&gt;Quantum chemistry software calculates this with the HF method using the formula \eqref{DM LCAO}.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;As for the charges on the atoms.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;From another side, an atomic partial charges &lt;span class=&quot;math-container&quot;&gt;$q_A$&lt;/span&gt; are a central concept in general chemistry and widely used as mentioned wzkchem5. But, unfortunately, they do not correspond to a single well-defined quantum mechanical observable, so we have't operator &lt;span class=&quot;math-container&quot;&gt;$\hat{q}_A$&lt;/span&gt; and as a concequence, their definition is quite arbitrary and they are not required to accurately reproduce the electrical characteristics of the molecule.&lt;/p&gt;&#xA;&lt;p&gt;The calculation according to the formula (for diatomic molecule)&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\label{QR}\tag{QR}&#xA;    \vec{\mu}_{q} = q_{Li} \vec{R_{Li}} - q_H \vec{R_{H}} = q \vec R_{Li-H},&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R_{Li-H}$&lt;/span&gt; - the distence between atoms,&#xA;&lt;strong&gt;takes into account only a part of the contribution to the dipole moment of the molecule&lt;/strong&gt; associated with interatomic charge transfer.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UVfip.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UVfip.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's show it.&lt;/p&gt;&#xA;&lt;p&gt;Let's introduce &lt;span class=&quot;math-container&quot;&gt;$\vec r = \vec R_{Li} + \vec r_{Li}$&lt;/span&gt; and substitute into the formula\eqref{N-e}&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\vec{\mu} =  \left(Z_{Li}  - \int \rho(x,y,x) d\vec{r} \right) \vec R_{Li}  + \left(Z_{H}  - \int \rho(x,y,x) d\vec{r} \right) \vec R_{H} - \int \vec (\vec r_{H} + \vec r_{Li}) \rho(x,y,x) d\vec{r} = q_{Li} \vec R_{Li} + q_{H} \vec R_{H} -  \int (\vec r_{H} + \vec r_{Li})  \rho(x,y,x) d\vec{r} = q_{Li} \vec R_{Li - H} -  \int (\vec r_{H} + \vec r_{Li}) \rho(x,y,x) d\vec{r} = \mu_{q} - \int (\vec r_{H} + \vec r_{Li}) \rho(x,y,x) d\vec{r}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The last term &lt;span class=&quot;math-container&quot;&gt;$- \int (\vec r_{H} + \vec r_{li}) \rho(x,y,x) d\vec{r}$&lt;/span&gt; takes into account the fact that the eletron density distribution of the bound atom is not spherically symmetric, and each atom acquires a dipole electric polarization, relative to its nucleus.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;So, we can see, the &lt;span class=&quot;math-container&quot;&gt;$\vec{\mu}_q = q_{Li} \vec R_{Li-H}$&lt;/span&gt; which is determined by the partial charge&#xA;on the atom is just a part of total dipole moment of molecule &lt;span class=&quot;math-container&quot;&gt;$\vec{\mu}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There are many methods for determining partial charges. In paper T&lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cphc.202000040&quot; rel=&quot;nofollow noreferrer&quot;&gt;he Atomic Partial Charges Arboretum: Trying to See the Forest for the Trees&lt;/a&gt; the classification of charges is given, depending on the methods of their determination:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Class I charges are derived from experimentally measurable&#xA;properties, e.g., from observed deformation densities, from the electronegativity&#xA;equalization principle, or from, e.g., dipole moments of diatomic and&#xA;small (usually highly symmetric) polyatomic molecules.&lt;/li&gt;&#xA;&lt;li&gt;Class II charges are extracted from the molecular orbitals (Mulliken, NPA,…)&#xA;or the electron density (Bader QTAIM, Hirshfeld,…).&lt;/li&gt;&#xA;&lt;li&gt;Class III charges are extracted from the wave function or electron density by fitting a physical observable (e.g., the electrostatic potential) derived from    it.&lt;/li&gt;&#xA;&lt;li&gt;Class IV charges are based on semiempirical adjustment of a&#xA;well-defined Class II or Class III model to better reproduce one or&#xA;more physical observables (e.g. the dipole moment).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5264" LastEditorUserId="5264" LastEditDate="2022-05-12T19:03:06.947" LastActivityDate="2022-05-12T19:03:06.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9071" PostTypeId="1" CreationDate="2022-05-12T09:21:01.510" Score="3" ViewCount="221" Body="&lt;p&gt;I have a Gromacs NVT simulation with a constant external electric field using the option &amp;quot;electric-field-z = 1.5 0 0 0&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;When calling gmx energy -f (...).edr to calculate the potential energy of the system, is the energy due to interaction with the electric field included or not?&lt;/p&gt;&#xA;&lt;p&gt;Particularly, I have a lot of molecular dipoles in the system which can align wrt to the electric field. I want to know if the dipole - field interaction energy is contained in the potential from gmx energy, and if not, how I can quantify it.&lt;/p&gt;&#xA;" OwnerUserId="5379" LastEditorUserId="5379" LastEditDate="2022-05-12T10:11:57.593" LastActivityDate="2022-12-12T15:23:45.350" Title="Is the energy due to external electric field included in gromacs energy?" Tags="|molecular-dynamics|molecular-modeling|gromacs|potential-energy-surface|electric-field|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9072" PostTypeId="1" CreationDate="2022-05-12T09:15:28.740" Score="5" ViewCount="144" Body="&lt;p&gt;I want to run a SCRF calculation in Gaussian for a molecule. This has been done as standard with several geometries without issue using the &lt;code&gt;aug-cc-pvtz&lt;/code&gt; basis and the &lt;code&gt;externaliteration&lt;/code&gt; keyword.&lt;/p&gt;&#xA;&lt;p&gt;I've run into an issue when attempting to run Iodine, as the basis i chose does not include it. I've tried running the following input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#P PBEPBE/gen Integral=(DKH2,Acc2E=12) SCRF=(IEFPCM,ExternalIteration,Read)&#xA;&#xA;Comment&#xA;&#xA;0 1&#xA;  6    3.3201280000    0.0000090000    0.0000180000&#xA;  6    2.6240380000    1.2000870000    0.0000140000&#xA;  6    1.2356900000    1.2073170000    0.0000040000&#xA;  6    0.5527080000   -0.0000250000    0.0000060000&#xA;  6    1.2357050000   -1.2073240000    0.0000120000&#xA;  6    2.6240810000   -1.2000630000    0.0000170000&#xA;  1    4.4010450000    0.0000380000    0.0000230000&#xA;  1    3.1592970000    2.1397220000    0.0000150000&#xA;  1    0.6936620000    2.1421070000   -0.0000010000&#xA;  1    0.6937300000   -2.1421460000    0.0000100000&#xA;  1    3.1593300000   -2.1397030000    0.0000200000&#xA; 53   -1.5407770000    0.0000000000   -0.0000090000&#xA;&#xA;Eps=2.0&#xA;PrintSpheres&#xA;NSph=12&#xA;&#xA;3.3201280000    0.0000090000    0.0000180000    3.21    1.1&#xA;2.6240380000    1.2000870000    0.0000140000    3.21    1.1&#xA;1.2356900000    1.2073170000    0.0000040000    3.21    1.1&#xA;0.5527080000    -0.0000250000    0.0000060000    3.21    1.1&#xA;1.2357050000    -1.2073240000    0.0000120000    3.21    1.1&#xA;2.6240810000    -1.2000630000    0.0000170000    3.21    1.1&#xA;4.4010450000    0.0000380000    0.0000230000    2.27    1.1&#xA;3.1592970000    2.1397220000    0.0000150000    2.27    1.1&#xA;0.6936620000    2.1421070000    -0.0000010000    2.27    1.1&#xA;0.6937300000    -2.1421460000    0.0000100000    2.27    1.1&#xA;3.1593300000    -2.1397030000    0.0000200000    2.27    1.1&#xA;-1.5407770000    0.0000000000    -0.0000090000    3.74    1.1&#xA;&#xA;C H 0&#xA;aug-cc-pvtz&#xA;****&#xA;I 0&#xA;dgdzvp&#xA;****&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This crashes on execution.&lt;/p&gt;&#xA;&lt;p&gt;I have ran the same calculation without the SCRF related keywords and section without issue, so it must be something with the way i'm putting the solvent specifications.&lt;/p&gt;&#xA;&lt;p&gt;I have tried switching places of the SCRF section and the basis set specification but it still doesn't run.&lt;/p&gt;&#xA;&lt;p&gt;How does one go about running this?&lt;/p&gt;&#xA;&lt;p&gt;edit: output from gaussian gives the following line before quitting&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ----------------------------------------------------------------------&#xA; #P PBEPBE/gen Integral=(DKH2,Acc2E=12) SCRF=(IEFPCM,ExternalIteration&#xA; ,Read)&#xA; ----------------------------------------------------------------------&#xA; External iterations require gradients.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5380" OwnerDisplayName="ggerez" LastEditorUserId="5380" LastEditDate="2022-05-18T11:05:26.283" LastActivityDate="2022-07-04T14:25:05.100" Title="How to run SCRF in Gaussian with extra basis?" Tags="|software|computational-chemistry|gaussian|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9074" PostTypeId="1" CreationDate="2022-05-12T15:15:08.293" Score="7" ViewCount="357" Body="&lt;p&gt;I have been told to use VASPKIT in order to obtain the KPOINTS, but VASPKIT only works for Primitive cell and I am currently using a super cell. The super cell has a repeated primitive cell about one of the directions, the reason I am creating a super cell is because I have to create a particular Anti Ferromagnetic state for which I need to make a structure which has a particular kind of repetitions of up and down spins that is not possible to create with the primitive cell.&lt;/p&gt;&#xA;&lt;p&gt;Now for this I tried converging the KPOINTs but I am quite confused, a paper which has worked with the exact same super cell uses a 4x4x2 k grid. But there are a lot of permutations and combinations here our of which 4x4x2 seems to have a higher energy. I believe 4x4x4 or perhaps 5x5x5 will do a better job&#xA;&lt;a href=&quot;https://i.stack.imgur.com/NHEXN.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NHEXN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, how should I choose the Kpoints for the Band structure. Originally I planned on using VASPKIT but I dont think that is a good idea anymore. I tried obtaining a k point file and the file has different k points from  the one in paper.&lt;/p&gt;&#xA;&lt;p&gt;Will the Kpoints be same for the unit cell and the super cell ? Considering that they are the high symmetry points of the Wigner–Seitz, shouldn't the wigner-seitz cell remain same??&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2022-05-12T15:15:08.293" Title="How to choose K point for a super cell" Tags="|k-points|vaspkit|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-09T23:00:51.233" ContentLicense="CC BY-SA 4.0" />
  <row Id="9075" PostTypeId="1" AcceptedAnswerId="9076" CreationDate="2022-05-12T19:16:44.710" Score="8" ViewCount="1910" Body="&lt;p&gt;I'm trying to simulate a supercell that contains thousands of atoms with the DFT method, but it seems VASP couldn't handle such a large system, its parallel efficiency is relatively low, when I try to run such a large system, it is gonna take too much time.&lt;br&gt;&#xA;Is there any mainstream DFT code that could handle such a large system with a good parallel efficiency?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-15T20:14:07.213" Title="DFT code for simulating thousands of atoms in a supercell" Tags="|density-functional-theory|vasp|software|software-recommendations|" AnswerCount="4" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="9076" PostTypeId="2" ParentId="9075" CreationDate="2022-05-12T19:52:07.690" Score="11" Body="&lt;p&gt;The SIESTA method and its implementation offer an efficient and flexible simulation paradigm based on the use of strictly localized basis sets, this allows the implementation of reduced scaling algorithms, and its accuracy and cost can be tuned in a wide range. SIESTA’s baseline efficiency can be scaled up to ever-larger systems by parallelization. Both distributed (MPI) and shared-memory (OpenMP) parallelization options are implemented in the code.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;SIESTA has excellent performance for finite systems such as slabs, surfaces, clusters, nanotubes and molecules.&lt;/li&gt;&#xA;&lt;li&gt;SIESTA can easily tackle computationally demanding systems (&amp;gt;10000 atoms), which are out of the reach of plane-wave codes.&lt;/li&gt;&#xA;&lt;li&gt;SIESTA has efficient parallelisation implemented over orbitals or over k-points.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;To Download and start working with SIESTA :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.simuneatomistics.com/products/siesta-code/&quot; rel=&quot;noreferrer&quot;&gt;https://www.simuneatomistics.com/products/siesta-code/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To learn more about SIESTA&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://aip.scitation.org/doi/am-pdf/10.1063/5.0005077&quot; rel=&quot;noreferrer&quot;&gt;https://aip.scitation.org/doi/am-pdf/10.1063/5.0005077&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I also suggest :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.youtube.com/c/PRITAMPANDApritampkp15&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/c/PRITAMPANDApritampkp15&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To get some basic introductory videos about the code, its installation and compilation, and some utilities as well.&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2022-05-12T19:52:07.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9077" PostTypeId="2" ParentId="9075" CreationDate="2022-05-13T01:36:03.057" Score="13" Body="&lt;p&gt;ONETEP &lt;a href=&quot;https://www.onetep.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.onetep.org/&lt;/a&gt; is a &lt;strong&gt;linear-scaling&lt;/strong&gt; DFT code suitable and efficient for such large simulations. The main purpose of it, in the first place, was to lower the computational cost of conventional DFT codes (e.g. CASTEP and VASP) which scale as the cube of the system size N.&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="5364" LastEditDate="2022-05-15T20:14:07.213" LastActivityDate="2022-05-15T20:14:07.213" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9078" PostTypeId="1" CreationDate="2022-05-13T06:05:37.580" Score="5" ViewCount="217" Body="&lt;p&gt;I have a (possibly trivial) question regarding the METADISE code. I can find the documentation related to this code, but I cannot find the download page or tarball anywhere.&lt;/p&gt;&#xA;&lt;p&gt;Can someone kindly share any information in this regard?&lt;/p&gt;&#xA;&lt;p&gt;Any help would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2022-08-21T17:31:38.633" LastActivityDate="2022-08-21T17:31:38.633" Title="How to download METADISE code?" Tags="|software|software-assistance|solid-state-physics|metadise|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9079" PostTypeId="2" ParentId="9075" CreationDate="2022-05-13T07:09:04.137" Score="9" Body="&lt;p&gt;To make a recommendation more details are really needed, as noted in the comments. However &lt;a href=&quot;https://www.crystal.unito.it/index.php&quot; rel=&quot;noreferrer&quot;&gt;CRYSTAL&lt;/a&gt; (full disclosure - I am an author of the code) has been used for calculations on over a thousand atoms. For instance &lt;a href=&quot;https://doi.org/10.1021/acs.jpcc.9b06533&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/acs.jpcc.9b06533&lt;/a&gt; discusses calculations involving structural optimizations of around 3,000 atoms, the calculations being run on around 1,000 cores.&lt;/p&gt;&#xA;" OwnerUserId="269" LastActivityDate="2022-05-13T07:09:04.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9080" PostTypeId="1" CreationDate="2022-05-13T12:55:05.903" Score="5" ViewCount="352" Body="&lt;p&gt;I am using an AMD Linux cloud-based instance to ran general optimisation and transition state calculations in parallel. I have noticed that I can run gas phase calculations in parallel but the run fails when I include a solvent in the input file. Additionally, I have a local Intel workstation, and I face no issues on there. The same input file that fails on my cloud instance, works on my local workstation.&lt;/p&gt;&#xA;&lt;p&gt;Log file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt; An error occurred in MPI_Type_match_size reported by process&#xA;&amp;gt; [4120707073,1] on communicator MPI_COMM_WORLD &#xA;&amp;gt; &#xA;&amp;gt; MPI_ERR_ARG: invalid argument of some other kind MPI_ERRORS_ARE_FATAL&#xA;&amp;gt; (processes in this communicator will now abort, ***    and potentially&#xA;&amp;gt; your MPI job) &#xA;&amp;gt; &#xA;&amp;gt; PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198 6&#xA;&amp;gt; more processes have sent help message help-mpi-errors.txt /&#xA;&amp;gt; mpi_errors_are_fatal &#xA;&amp;gt; &#xA;&amp;gt; Set MCA parameter &amp;quot;orte_base_help_aggregate&amp;quot; to 0 to see all help /&#xA;&amp;gt; error messages[file orca_tools/qcmsg.cpp, line 465]:  .... aborting&#xA;&amp;gt; the run&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Failure in output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--------------------&#xA;CPCM SOLVATION MODEL&#xA;--------------------&#xA;CPCM parameters:&#xA;  Epsilon                                         ...      80.4000&#xA;  Refrac                                          ...       1.3300&#xA;  Rsolv                                           ...       1.3000&#xA;  Surface type                                    ... GAUSSIAN VDW&#xA;  Epsilon function type                           ...         CPCM&#xA;Radii:&#xA; Radius for C  used is    3.8550 Bohr (=   2.0400 Ang.)&#xA; Radius for O  used is    3.4469 Bohr (=   1.8240 Ang.)&#xA; Radius for H  used is    2.4944 Bohr (=   1.3200 Ang.)&#xA;Calculating surface                               ...        done! (  0.0s)&#xA;GEPOL surface points                              ...         1252&#xA;GEPOL Volume                                      ...    1244.2933&#xA;GEPOL Surface-area                                ...     725.8299&#xA;Calculating surface distance matrix               ...        done! (  0.0s)&#xA;Performing Cholesky decomposition &amp;amp; store         ...        &#xA;ORCA finished by error termination in SCF&#xA;Calling Command: mpirun -np 16  /opt/orca503/orca_scf_mpi g_acoh_gp.gbw b g_acoh_gp &#xA;[file orca_tools/qcmsg.cpp, line 465]: &#xA;  .... aborting the run&#xA;&#xA;&#xA;&#xA;Orca version: Program Version 5.0.3 -  RELEASE  -&#xA;&#xA;Open MPI version: mpiexec --version: mpiexec (OpenRTE) 4.1.1&#xA;&#xA;AMD processor: AMD EPYC Processor (with IBPB)&#xA;&#xA;Intel Processor: Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not using a scheduler, running the Orca command at the prompt.&lt;/p&gt;&#xA;&lt;p&gt;What could be the issue?&lt;/p&gt;&#xA;" OwnerUserId="4313" LastEditorUserId="4313" LastEditDate="2022-05-13T20:54:11.390" LastActivityDate="2022-05-19T09:34:43.700" Title="Successfully running parallel gas phase calculation on AMD cloud instance but implicit solvent fails (Local Intel workstation successfully runs both)" Tags="|density-functional-theory|high-performance-computing|orca|implicit-solvent|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9081" PostTypeId="2" ParentId="9075" CreationDate="2022-05-14T00:57:04.183" Score="3" Body="&lt;p&gt;Well, maybe you can first specify the calculations you would like to do, given it maybe relaxation/MD; I suggest you start with cheap method like Tight binding DFT with quite efficient parametric as implanted in &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://xtb-docs.readthedocs.io/en/latest/contents.html&lt;/a&gt; or DFTB+ and other flagship codes then apply fancy implantation or functional on the outcome&lt;/p&gt;&#xA;" OwnerUserId="5394" LastActivityDate="2022-05-14T00:57:04.183" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9082" PostTypeId="1" CreationDate="2022-05-14T14:33:06.657" Score="5" ViewCount="401" Body="&lt;p&gt;I am searching for functional groups in RDKit molecules and want to get the corresponding atom indices. Using &lt;code&gt;GetSubstructMatches()&lt;/code&gt; however does not return some (implicit?) hydrogen indices.&#xA;My code is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;&#xA;patt = Chem.MolFromSmarts(&amp;quot;[CH3;X4]&amp;quot;)&#xA;patt = Chem.AddHs(patt, explicitOnly=True)&#xA;&#xA;mol = Chem.MolFromSmiles(&amp;quot;CC(=O)Br&amp;quot;)&#xA;mol = Chem.AddHs(mol)&#xA;&#xA;match_indices = mol.GetSubstructMatches(patt)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This only returns the index of the carbon atom. How could I get the hydrogen indices as well?&lt;/p&gt;&#xA;" OwnerDisplayName="gloomy5k" LastEditorUserId="30" LastEditDate="2022-05-15T19:35:39.767" LastActivityDate="2022-05-15T19:35:39.767" Title="How to get hydrogen indices in RDKit substructure matches" Tags="|cheminformatics|" AnswerCount="0" CommentCount="2" ClosedDate="2022-08-18T14:21:21.733" ContentLicense="CC BY-SA 4.0" />
  <row Id="9083" PostTypeId="1" CreationDate="2022-05-14T17:45:58.007" Score="4" ViewCount="772" Body="&lt;p&gt;As they advise everywhere, SKF should be considered without SOC, and already in NSCF, spin-orbit interaction should be included. But what is the actual question, as I know, band splitting occurs with SOC calculations and then the DOS that I take from SCF gives another band gap. How to deal with it?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eTy3x.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eTy3x.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5373" LastActivityDate="2022-05-16T14:42:04.643" Title="Why I have difference between DOS and BAND gap?" Tags="|vasp|band-structure|spin-orbit-coupling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9084" PostTypeId="2" ParentId="9068" CreationDate="2022-05-15T11:10:43.807" Score="4" Body="&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE&lt;/a&gt; has a build-in method that can produce what you want:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ase.build.graphene_nanoribbon(n, m, type='zigzag',&#xA;          saturated=False, C_H=1.09, C_C=1.42, vacuum=None,&#xA;          magnetic=False, initial_mag=1.12, sheet=False, &#xA;          main_element='C', saturate_element='H')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then write it to a LAMMPS file using ASE directly, or to another format and convert it to LAMMPS with &lt;a href=&quot;https://atomsk.univ-lille.fr/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomsk&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2022-05-15T14:17:26.610" LastActivityDate="2022-05-15T14:17:26.610" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9086" PostTypeId="1" CreationDate="2022-05-15T18:18:00.320" Score="5" ViewCount="437" Body="&lt;p&gt;I'm a graduate student beginning research in condensed matter physics. Naturally, I am very interested in mathematics. I am aware that, in condensed matter physics, theorists employ tools from pure mathematics and high energy physics. For example, recent research in topological quantum phases of matter seems to involve ideas in algebraic topology and geometry. On the other hand, a standard approach to investigate real-world material systems is the density functional theory formalism. In contrast to theoretical tools, such as cohomology theory, homotopy groups, etc. that I am more interested in, I find DFT less theoretically attractive; it seems to involve a re-formulation of the many-body Schrodinger equation as a one-electron Schrodinger equation. Much of the interesting mathematics and physics ideas seem to be hidden. I have two questions:&lt;/p&gt;&#xA;&lt;p&gt;1 - To what extent is DFT is useful if one wants to understand questions, such as topological quantum computing? Is DFT a good starting point if one is interested in studying aspects of condensed matter, such as quantum spin liquids, topological quantum computation, etc. ? or is it better to study these systems using tight-binding lattice models without going through the DFT phase?&lt;/p&gt;&#xA;&lt;p&gt;2- How important will DFT be in the near future? are people looking for alternatives?&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastEditorDisplayName="user5405" LastEditDate="2022-05-15T18:19:21.017" LastActivityDate="2022-05-15T22:02:35.817" Title="Future and limitations of DFT" Tags="|density-functional-theory|quantum-chemistry|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9088" PostTypeId="2" ParentId="9086" CreationDate="2022-05-15T22:02:35.817" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;1 - To what extent is DFT is useful if one wants to understand questions, such as topological quantum computing? Is DFT a good starting point if one is interested in studying aspects of condensed matter, such as quantum spin liquids, topological quantum computation, etc. ? or is it better to study these systems using tight-binding lattice models without going through the DFT phase?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It largely depends on what specific questions you're interested in, and where on the abstract-to-concrete scale you want to work / feel at home. Part of the beauty of condensed matter physics is its broad span in topics, tools, and energy and length scales. In a lot of cases DFT or other quantum chemistry methods can be sufficient, but in other cases it's not a very natural starting point. For a graduate student starting out, I would recommend finding a problem that interests you deeply, and then learning methods appropriate to that problem. Maybe those are pen-and-paper analytical methods, maybe they are DFT methods, maybe something else. There are a lot of possible paths.&lt;/p&gt;&#xA;&lt;p&gt;For example, if you want to understand the mathematics and principles of quantum spin liquids, you're usually better off focusing on effective low-energy theories, e.g. spin models and lattice gauge theories. There are specific methods well-suited to analyzing such systems. Similarly, the language of topological quantum computing is often framed in its own set of effective low-energy models. At this end of the scale, we are often interested in new emergent phases and quasiparticles that tend to be hard to capture or notice in more realistic models. However, these low-energy models can often be obtained as a limit of a more concrete model.&lt;/p&gt;&#xA;&lt;p&gt;For example, the Kitaev chain was originally written down as a toy model for a system that might be used as a topological qubit. It was subsequently realized that this model emerges at low energy in e.g. spin-orbit-coupled semiconducting nanowires when subject to a magnetic field and proximate to a superconductor. But note what the ingredients of that recipe are: nanowires and superconductors. To go even more concrete, we need to think of actual materials which may be used to realize these components. Similarly, Kitaev's honeycomb model hosting a quantum spin liquid was first considered a toy model. It was then argued it could occur in systems of certain crystal structure and electron configuration. DFT is very useful in finding materials realizing those conditions, and thus candidate materials to realize the Kitaev spin liquid. But it'd be very difficult to start with a DFT calculation taking into account complexities of real materials and try to infer spin liquid behavior directly.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;2- How important will DFT be in the near future? are people looking for alternatives?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;DFT is not going away anytime soon. It's still fast compared to similar methods, useful, and continuously being improved in different directions. But it has its &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/526/671&quot;&gt;limitations&lt;/a&gt;. These weaknesses do motivate a lot of work on e.g. so-called post-DFT methods. Overall, the space of possible materials and systems we want to model is vast, and realistically this requires a variety of approaches.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2022-05-15T22:02:35.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9090" PostTypeId="2" ParentId="9066" CreationDate="2022-05-16T02:23:09.263" Score="1" Body="&lt;p&gt;Lattice parameter of Aluminum is indeed 4.05 angstrom. Once you create region either in units of lattice/angstrom using &lt;em&gt;region&lt;/em&gt; command followed by create box in that region, atoms will sit based on previously defined lattice command. In former case, simulation box was created using &amp;lt;100&amp;gt; &amp;lt;010&amp;gt; &amp;lt;001&amp;gt; axes system which lead to 4 atom unit cell and outcome was 4.05 angstrom as length of x. In second case simulation box was created using &amp;lt;110&amp;gt; &amp;lt;-110&amp;gt; &amp;lt;001&amp;gt; axes system, hence simulation box was large with number of atoms equal to 8. As a result of that, length along x axis was relaxed to &lt;span class=&quot;math-container&quot;&gt;$4.05*\sqrt2=5.7275 $&lt;/span&gt; angstrom.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-05-16T02:23:09.263" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9091" PostTypeId="1" CreationDate="2022-05-16T07:26:56.383" Score="6" ViewCount="193" Body="&lt;p&gt;I am working on a goethite system, and wish to fill the unit cell with water molecules for AIMD simulation using quantum espresso. For this, some papers[1],[2] indicated the use of Grand Canonical Monte Carlo (GCMC) simulations using Towhee to find out the number of water molecules, which also pre-equilibrates the water molecules for the AIMD run.&lt;/p&gt;&#xA;&lt;p&gt;I am totally new to MD and MC simulations. Can someone give some guidance as to how the cell can be filled with water molecules?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Leung, K.; Criscenti, L. J. &lt;a href=&quot;https://doi.org/10.1088/1361-648x/aa7e4f&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lead and Selenite Adsorption at Water-goethite Interfaces from First Principles&lt;/a&gt;. J. Phys. Condens. Matter 2017, 29 (36), 365101. &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Leung, K.; Criscenti, L. J. &lt;a href=&quot;https://doi.org/10.1088/0953-8984/24/12/124105_&quot; rel=&quot;nofollow noreferrer&quot;&gt;Predicting the Acidity Constant of a Goethite Hydroxyl Group from First Principles&lt;/a&gt;. J. Phys. Condens. Matter 2012, 24 (12), 124105.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2022-05-16T19:32:05.180" LastActivityDate="2022-05-16T19:32:05.180" Title="Regarding use of GCMC to add water molecules" Tags="|molecular-dynamics|quantum-espresso|monte-carlo|aimd|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9092" PostTypeId="1" AcceptedAnswerId="9094" CreationDate="2022-05-16T12:44:21.490" Score="5" ViewCount="156" Body=" &#xA;&lt;p&gt;STO-3G has exponent parameters which can be found in a reference book. Can these parameters be calculated using, for instance, a Hartree–Fock equation for one atom? Or using another way?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5" LastEditDate="2022-05-16T19:30:13.800" LastActivityDate="2022-05-16T19:30:13.800" Title="How are the exponents in a STO-nG basis set obtained?" Tags="|ab-initio-calculations|quantum-mechanics|basis-sets|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9093" PostTypeId="2" ParentId="9083" CreationDate="2022-05-16T14:42:04.643" Score="3" Body="&lt;p&gt;The DOS and Band Structure normally use a different set of k-points and I will assume that is what happened here.  There are two possibilities for what we are seeing right now.&lt;/p&gt;&#xA;&lt;p&gt;The first is that your lines for the band gap on both plots is not actually drawn correctly or aligned.  You should use what looks like &lt;a href=&quot;https://smtg-ucl.github.io/sumo/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sumo&lt;/a&gt; to actually get a numerical value for both.&lt;/p&gt;&#xA;&lt;p&gt;The second is that the DOS may not have hit the correct k-points to actually see the correct valence band minimum or conductance band maximum.  This would effect the DOS gap as well, showing it to be artificially too big.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-05-16T14:42:04.643" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9094" PostTypeId="2" ParentId="9092" CreationDate="2022-05-16T19:26:55.237" Score="4" Body="&lt;p&gt;You are right that the STO-nG basis sets are optimized separately for each individual element (as an isolated atom, rather than as an ion or an atom within a bigger molecule). The exponents are obtained by by a least squares fit of the Gaussian orbitals to a single &lt;a href=&quot;https://en.wikipedia.org/wiki/Slater-type_orbital&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slater-type orbital (STO)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For other basis sets (not named STO-nG but named something else, like cc-pCVDZ), the exponents are calculated by doing Hartree-Fock and CISD calculations, for example.&lt;/p&gt;&#xA;&lt;p&gt;If you want to know more about how Gaussian basis sets are optimized, you might find the following thread interesting: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3728/5&quot;&gt;Optimization of Gaussian basis sets within the Hartree-Fock Method&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There's also been some discussion about STO-3G specifically and why different sources have different exponent values for STO-3G: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6559/5&quot;&gt;Difference between original STO-3G and BSE STO-3G&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-05-16T19:26:55.237" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9095" PostTypeId="1" AcceptedAnswerId="9106" CreationDate="2022-05-16T20:30:17.477" Score="8" ViewCount="1978" Body="&lt;p&gt;Does anyone have any experience simulating Raman spectra in Quantum ESPRESSO? Following the &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/tree/master/PHonon/examples/example15/reference&quot; rel=&quot;noreferrer&quot;&gt;example 15&lt;/a&gt; that comes with QE, I have attempted to simulate the Raman spectrum of MgO. I know the lraman flag must be set to .true., and I have used norm-conserving pseudopotentials. My code runs without error, and prints the IR activities, but the Raman activities are missing.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know how to make QE print the Raman activities?&lt;/p&gt;&#xA;&lt;p&gt;Edit: I should also mention that I'm running version 7.0 of Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;Edit 2: Following the example 15, I'm able to simulate the Raman intensities of bulk Si. Does anyone know why QE will print the intensities for bulk Si but not MgO? Do I need to treat the case of MgO differently? I'm attaching my input files below. Any help would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;pw.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;      calculation = 'scf',&#xA;      prefix = 'MgO',&#xA;      outdir = '/home/cw279/',&#xA;      pseudo_dir = '/usr/share/espresso/pseudo',&#xA;    /&#xA;&#xA;    &amp;amp;SYSTEM&#xA;      ibrav = 2,&#xA;      celldm(1) = 8.043589,&#xA;      nat = 2,&#xA;      ntyp = 2,&#xA;      ecutwfc = 80.0,&#xA;      occupations = 'fixed',&#xA;    /&#xA;&#xA;    &amp;amp;ELECTRONS&#xA;    /&#xA;&#xA;    ATOMIC_SPECIES&#xA;      Mg  24.305   Mg.pz-hgh.UPF&#xA;      O   15.999   O.pz-hgh.UPF&#xA;&#xA;    K_POINTS {automatic}&#xA;      4 4 4  1 1 1&#xA;&#xA;    ATOMIC_POSITIONS {crystal}&#xA;      Mg  0.000000  0.000000  0.000000&#xA;      O   0.500000  0.500000  0.500000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;ph.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;INPUTPH&#xA;      tr2_ph = 1.0d-18,&#xA;      prefix = 'MgO',&#xA;      amass(1) = 24.305,&#xA;      amass(2) = 15.999,&#xA;      outdir = '/home/cw279/',&#xA;      epsil = .true.,&#xA;      trans = .true.,&#xA;      lraman = .true.,&#xA;      fildyn = 'MgO.dyn',&#xA;    /&#xA;    0.0 0.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;dynmat.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;INPUT&#xA;      fildyn = 'MgO.dyn',&#xA;      asr = 'crystal',&#xA;    /&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5408" LastEditorUserId="5408" LastEditDate="2022-05-17T17:37:57.853" LastActivityDate="2023-06-15T08:32:36.217" Title="Raman Spectra in Quantum Espresso" Tags="|density-functional-theory|quantum-espresso|software|ab-initio-calculations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9096" PostTypeId="2" ParentId="4209" CreationDate="2022-05-16T21:31:34.440" Score="4" Body="&lt;p&gt;You may like to read this 2012 JCP paper to know TAO-DFT:&#xA;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3703894&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.3703894&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even with the exact exchange-correlation energy functional in KS-DFT, one still needs to obtain the ground-state electron density and the associated KS orbitals (i.e., by solving the KS equations self-consistently) in order to evaluate the total energy. However, for an electronic system with pronounced static correlation, the ground-state electron density may not be representable within the framework of KS-DFT, in which case even the exact KS-DFT will fail.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the KS partition is not the only partition for the HK universal functional, and different partitions may yield different representations of ground-state electron density, which may be obtained by adopting different reference systems. In this work, TAO-DFT (a DFT with fractional orbital occupations given by the Fermi-Dirac distribution function) is proposed, adopting a noninteracting reference system at some fictitious temperature. Note that the fictitious temperature is not related to the physical temperature (0 K), but related to the strength of static correlation of the electronic system at 0 K. TAO-DFT with zero fictitious temperature is reduced to KS-DFT. Unlike FT-DFT, TAO-DFT is developed for the ground-state systems at 0 K, just like KS-DFT. In TAO-DFT, the entropy contribution is found to capture static correlation, when the orbital occupation numbers are close to the natural orbital occupation numbers.&lt;/p&gt;&#xA;&lt;p&gt;A series of papers about TAO-DFT, its extensions, and applications can be found in the following website:&#xA;&lt;a href=&quot;http://web.phys.ntu.edu.tw/jdchai/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://web.phys.ntu.edu.tw/jdchai/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5410" LastEditorUserId="5410" LastEditDate="2022-05-17T14:40:18.683" LastActivityDate="2022-05-17T14:40:18.683" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9097" PostTypeId="1" CreationDate="2022-05-17T07:52:07.683" Score="5" ViewCount="547" Body="&lt;p&gt;I am trying to create a vector image of TiO2 crystal because all journals require vector images. When I build the model for calculation, I use &lt;code&gt;BIOVIA Materials Studio&lt;/code&gt; and &lt;code&gt;VESTA&lt;/code&gt;, but &lt;code&gt;BIOVIA Materials Studio&lt;/code&gt;doesn't provide any option to export vector images, and the vector images exported from &lt;code&gt;VESTA&lt;/code&gt; are blurry.&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;What is the mainstream software for creating a good vector image for crystal structures?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-18T05:48:20.657" Title="How to create the vector image of crystal structure?" Tags="|software-recommendations|crystallography|visualization-software|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9098" PostTypeId="1" CreationDate="2022-05-17T08:56:41.630" Score="3" ViewCount="452" Body="&lt;p&gt;GROMACS version:version 2021.3-MODIFIED&#xA;GROMACS modification: Yes&lt;/p&gt;&#xA;&lt;p&gt;Hi, I have a small system with 87 residues of a protein. And I want to maintain the tertiary structure of the protein, so I came up with some restraints which I am supplying in the topology file under the [bonds] directive. It is as follows&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;137  1188     6    3.253    8000&#xA;   271  1125     6    3.043    8000&#xA;    82  1004     6    1.386    8000&#xA;   319   979     6    2.600    8000&#xA;    82   923     6    1.309    8000&#xA;     7   764     6    2.059    8000&#xA;   257   662     6    2.415    8000&#xA;   319   829     6    1.809    8000&#xA;   151   371     6    1.859    8000&#xA;   371   500     6    1.752    8000&#xA;   462   764     6    1.440    8000&#xA;   923  1049     6    1.770    8000&#xA;  1004  1188     6    2.215    8000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Initially, I have a water padding of 1 nm (total number of atoms ~ 60k) and without the above restraints the simulation runs fine, but when I add the restraints, I got the following error. So, I am pretty sure that my type 6 restraints are causing the problem.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Fatal error: There is no domain decomposition for 96 ranks that is&#xA;compatible with the given box and a minimum cell size of 4.21705 nm&#xA;Change the number of ranks or mdrun option -rdd or -dds Look in the&#xA;log file for details on the domain decomposition&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I have searched the gromacs mailing list and other websites and found that if you increase the water padding (or make the box larger) you can avoid this error. So I tried going for 60-angstrom padding, but still have the same error and my total number of atoms reach close to 700k.&lt;/p&gt;&#xA;&lt;p&gt;Is there a workaround for this problem? I do not want to simulate a bigger system because of my limited computational resources&lt;/p&gt;&#xA;&lt;p&gt;I am attaching my log file for the NVT run.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://drive.google.com/file/d/1dtinDwU8WSWB3jmxrqwYNaQnjHF-CVhj/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;NVT.log&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="5" LastEditDate="2022-12-14T13:38:13.553" LastActivityDate="2022-12-14T13:38:13.553" Title="Domain decomposition error while applying bonded restraints - GROMACS" Tags="|molecular-dynamics|gromacs|software-assistance|proteins|structural-biology|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9099" PostTypeId="1" CreationDate="2022-05-17T10:34:11.937" Score="4" ViewCount="73" Body="&lt;p&gt;Are there any benchmarks of low-level and high-level math operations from different Math libraries on corresponding architectures?&lt;/p&gt;&#xA;&lt;p&gt;Here are a few packages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;LAPACK / BLAS  + ATLAS (&lt;a href=&quot;https://www.netlib.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;stock version from netlib&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.openblas.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenBLAS&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/api-based-programming/intel-oneapi-math-kernel-library-onemkl.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Intel MKL&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;ACML (AMD core math library)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://developer.apple.com/accelerate/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Apple Accelerate&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerDisplayName="user784" LastActivityDate="2022-05-17T10:34:11.937" Title="Benchmarks for optimised Math Libraries across platforms" Tags="|software|computational-chemistry|high-performance-computing|computational-frameworks|" AnswerCount="0" CommentCount="3" ClosedDate="2022-08-18T14:21:41.900" ContentLicense="CC BY-SA 4.0" />
  <row Id="9100" PostTypeId="1" CreationDate="2022-05-17T14:52:55.543" Score="4" ViewCount="138" Body="&lt;p&gt;I have installed LAMMPS on my mac-pro (OS Monetery), using &lt;a href=&quot;https://docs.lammps.org/Install_mac.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I installed Homebrew and then LAMMPS. I need to install &lt;a href=&quot;https://docs.lammps.org/Packages_details.html#pkg-dpd-react&quot; rel=&quot;nofollow noreferrer&quot;&gt;DPD-REACT&lt;/a&gt; package. I tried &lt;code&gt;-D PKG_DPD-REACT=on&lt;/code&gt; in my terminal following &lt;a href=&quot;https://docs.lammps.org/Packages_details.html#pkg-dpd-react&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, but it said &lt;code&gt;command not found: -D &lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I also tried the &lt;code&gt;make&lt;/code&gt; command, and got: &lt;code&gt;make yes-DPD-REACT make: *** No rule to make target yes-DPD-REACT'.  Stop&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am not sure how to install my DPD-REACT package. Can anybody help me with that please?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="5" LastEditDate="2023-02-07T02:26:22.820" LastActivityDate="2023-02-07T02:26:22.820" Title="How to install the optional LAMMPS package DPD-REACT in MacOS?" Tags="|lammps|software-assistance|apple-operating-system|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9101" PostTypeId="1" CreationDate="2022-05-17T19:44:27.947" Score="6" ViewCount="1429" Body="&lt;p&gt;I am new to solid state calculation. I have a question about the pseudopotential in terms of the relativistic effect. In solid-state calculations, ultrasoft pseudopotential using PBE functionals are widely used. I opened my ultrasoft pseudopotential file, I saw it says&lt;/p&gt;&#xA;&lt;p&gt;'The Pseudo was generated with a Scalar-Relativistic Calculation'.&lt;/p&gt;&#xA;&lt;p&gt;My question is, what is the definition of Scalar-Relativistic Calculation? I have a hard time finding the exact definition from a textbook. Are there any resources I can read about the scalar-relativistic effect?&lt;/p&gt;&#xA;&lt;p&gt;Also, in order to generate the pseudopotential, the all-electron wavefunction needs to be calculated first, in ultrasoft pseudopotential, what kind of method do people use to calculate the all-electron wavefunction?&lt;/p&gt;&#xA;&lt;p&gt;I really appreciate any comments on this.&#xA;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="5351" LastActivityDate="2022-05-17T20:16:03.657" Title="Scalar relativistic Calculation for pseudopotential" Tags="|pseudopotentials|relativistic|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9102" PostTypeId="2" ParentId="9101" CreationDate="2022-05-17T20:16:03.657" Score="5" Body="&lt;p&gt;There is no scalar-relativistic effect. &amp;quot;Scalar-relativistic&amp;quot; is an approximation to the fully relativistic treatment. The main simplification in this technique is the neglection of &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin%E2%80%93orbit_interaction&quot; rel=&quot;noreferrer&quot;&gt;spin-orbit coupling&lt;/a&gt;. As a consequence, instead of a 4-component wavefunction, in this approach one deals with two-component wavefunctions for each spin. In a nonrelativistic treatment you only have a single component.&lt;/p&gt;&#xA;&lt;p&gt;Here are two papers that introduce and discuss this approximation:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1088%2F0022-3719%2F10%2F16%2F019&quot; rel=&quot;noreferrer&quot;&gt;Koelling, D D; Harmon, B N (28 August 1977). &amp;quot;A technique for relativistic spin-polarised calculations&amp;quot;. Journal of Physics C: Solid State Physics. 10 (16): 3107–3114.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1007%2FBF01322185&quot; rel=&quot;noreferrer&quot;&gt;Takeda, T. (March 1978). &amp;quot;The scalar relativistic approximation&amp;quot;. Zeitschrift für Physik B. 32 (1): 43–48.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I hope you have access to these journals. I'm sure there are also nice chapters on this in several text books but for that someone else has to give suggestions.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2022-05-17T20:16:03.657" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9103" PostTypeId="1" CreationDate="2022-05-18T00:48:55.933" Score="5" ViewCount="86" Body="&lt;p&gt;In general, my understanding is that free radicals and non-equilibrium molecules sometimes need multireference electronic structure calculations, mainly because of different electronic states being close in energy.&lt;/p&gt;&#xA;&lt;p&gt;When I want to describe the electron density of a free atom with a multiplicity given by Hund's rule (that is, triplet carbon and sulfur, for example), then there's two arguments that I could be making:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;There is degeneracy, but only in the ground state, but the degenerate states are completely equivalent by symmetry; and&lt;/li&gt;&#xA;&lt;li&gt;From experimental spectroscopy I can assume that there's a large HOMO-LUMO gap.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The first argument would point me to the need of multireference (but not convincingly), but the second point suggests that a single determinant is enough.&lt;/p&gt;&#xA;&lt;p&gt;So, in general, can I get correct electron densities for free atoms from let's say coupled cluster calculations, or do I need to do multireference?&lt;/p&gt;&#xA;" OwnerDisplayName="user5418" LastActivityDate="2022-05-27T19:30:48.683" Title="Are multiplet free atoms multireference?" Tags="|electronic-structure|coupled-cluster|electron-correlation|multi-reference|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9104" PostTypeId="2" ParentId="9097" CreationDate="2022-05-18T05:48:20.657" Score="1" Body="&lt;p&gt;You can adjust the resolution of atoms and bonds in VESTA using the properties menu (Ctrl+Shift+P). I recommend doubling the normal numbers and changing the color to black.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/U0344.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/U0344.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5199" LastActivityDate="2022-05-18T05:48:20.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9106" PostTypeId="2" ParentId="9095" CreationDate="2022-05-18T15:02:40.443" Score="5" Body="&lt;p&gt;It would seem that if a crystal system has no Raman-active modes, QE simply won't print out the Raman intensities. To verify this, I tried to simulate the Raman activity of &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt; (also a member of the m3m point group, like &lt;span class=&quot;math-container&quot;&gt;$\ce{MgO}$&lt;/span&gt;), and again, QE didn't print anything. This would also explain why the intensities for &lt;span class=&quot;math-container&quot;&gt;$\ce{ZnO}$&lt;/span&gt; (m3m) in example 15 didn't print either.&lt;/p&gt;&#xA;&lt;p&gt;However, QE &lt;em&gt;will&lt;/em&gt; print the Raman intensities for &lt;span class=&quot;math-container&quot;&gt;$\ce{Si}$&lt;/span&gt; (diamond) and &lt;span class=&quot;math-container&quot;&gt;$\ce{GaAs}$&lt;/span&gt; (zincblende). I will leave below my input files for &lt;span class=&quot;math-container&quot;&gt;$\ce{GaAs}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If I'm incorrect that QE doesn't print the Raman intensities for a Raman-inactive point group, please let me know!&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;GaAs input files:&lt;/p&gt;&#xA;&lt;p&gt;pw.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;      calculation='scf',&#xA;      restart_mode='from_scratch',&#xA;      prefix='GaAs'&#xA;      pseudo_dir = '/usr/share/espresso/pseudo',&#xA;      outdir='/home/cw279/',&#xA;    /&#xA;&#xA;    &amp;amp;SYSTEM&#xA;      ibrav = 2,&#xA;      celldm(1) = 10.4455,&#xA;      nat = 2,&#xA;      ntyp = 2,&#xA;      ecutwfc = 60.0,&#xA;      occupations = 'fixed',&#xA;    /&#xA;&#xA;    &amp;amp;ELECTRONS&#xA;    /&#xA;&#xA;    ATOMIC_SPECIES&#xA;      Ga  69.723   Ga.pz-hgh.UPF   ! QE throws error unless PP is LDA&#xA;      As  74.9216  As.pz-hgh.UPF   ! and norm-conserving&#xA;&#xA;    K_POINTS {automatic}&#xA;      4 4 4  1 1 1&#xA;&#xA;    ATOMIC_POSITIONS {crystal}&#xA;      Ga  0.000000 0.000000 0.000000&#xA;      As  0.250000 0.250000 0.250000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;ph.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;INPUTPH&#xA;      tr2_ph = 1.0d-19,&#xA;      prefix = 'GaAs',&#xA;      amass(1) = 69.723,&#xA;      amass(2) = 74.92160,&#xA;      outdir = '/home/cw279',&#xA;      epsil = .true.,&#xA;      trans = .true.,&#xA;      lraman = .true.,&#xA;      fildyn = 'GaAs.dyn',&#xA;    /&#xA;    0.0 0.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;dynmat.x calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;INPUT&#xA;      fildyn = 'GaAs.dyn',&#xA;      asr = 'simple',&#xA;      q(1) = 1.0,        !to correct for LO-TO splitting&#xA;      q(2) = 0.0,&#xA;      q(3) = 0.0,&#xA;    /&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5408" LastEditorUserId="5408" LastEditDate="2022-05-19T16:41:31.990" LastActivityDate="2022-05-19T16:41:31.990" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9107" PostTypeId="1" CreationDate="2022-05-18T15:26:09.530" Score="8" ViewCount="451" Body="&lt;p&gt;I believe CP2K by default implements Born–Oppenheimer MD. I have seen many recent papers that use 2nd generation Car–Parrinello MD using CP2K. But I couldn't find any direct way of switching to 2nd-gen CPMD in the CP2K documentation.&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="1195" LastEditDate="2022-06-03T13:10:13.757" LastActivityDate="2022-12-11T10:45:18.200" Title="How to run 2nd generation CPMD in CP2K?" Tags="|molecular-dynamics|ab-initio-calculations|cp2k|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9108" PostTypeId="2" ParentId="1513" CreationDate="2022-05-18T15:50:22.470" Score="4" Body="&lt;p&gt;TAO-DFT: Thermally-Assisted-Occupation DFT&lt;/p&gt;&#xA;&lt;p&gt;J.-D. Chai, J. Chem. Phys. 136, 154104 (2012).&#xA;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3703894&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.3703894&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even with the exact exchange-correlation energy functional in Kohn-Sham DFT (KS-DFT), one still needs to obtain the ground-state electron density and the associated Kohn-Sham (KS) orbitals (by solving the KS equations self-consistently) to evaluate the total energy. However, for an electronic system with strong static correlation, the ground-state electron density may not be representable in KS-DFT (i.e., &amp;quot;not&amp;quot; noninteracting pure-state vs-representable), in which case even the exact KS-DFT will fail.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the KS partition is not the only partition for the Hohenberg-Kohn (HK) universal functional, and different partitions may yield different representations of ground-state electron density, which may be obtained by adopting different reference systems. TAO-DFT (a DFT with fractional orbital occupations given by the Fermi-Dirac distribution function) is proposed, adopting a noninteracting reference system at some fictitious temperature.&lt;/p&gt;&#xA;&lt;p&gt;Note that the fictitious temperature is &amp;quot;not&amp;quot; related to the real electronic temperature (0 K), but related to the strength of static correlation of the electronic system at 0 K. Note that finite-temperature DFT (FT-DFT, also called Mermin-Kohn-Sham theory) is developed for systems in thermal equilibrium at some real electronic temperature, while TAO-DFT is developed for the ground-state properties of electronic systems at 0 K (just like KS-DFT). For ground-state systems at real electronic temperature = 0 K, FT-DFT (i.e., Mermin-Kohn-Sham theory) is reduced to KS-DFT, while TAO-DFT (with non-vanishing fictitious temperature) can be different from KS-DFT.&lt;/p&gt;&#xA;&lt;p&gt;In TAO-DFT, the entropy contribution is found to capture static correlation, when the fictitious temperature is so chosen that the corresponding orbital occupation numbers are close to the exact natural orbital occupation numbers.&lt;/p&gt;&#xA;&lt;p&gt;A series of papers about TAO-DFT, its extensions (LDA, GGA, and hybrid functionals in TAO-DFT, determination of TAO-DFT fictitious temperature, and TAO-DFT-based ab initio molecular dynamics), and its applications (strongly correlated electron systems at the nanoscale) can be found in the following website:  &lt;a href=&quot;http://web.phys.ntu.edu.tw/jdchai/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://web.phys.ntu.edu.tw/jdchai/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5410" LastEditorUserId="5410" LastEditDate="2022-05-18T15:56:41.990" LastActivityDate="2022-05-18T15:56:41.990" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9110" PostTypeId="1" AcceptedAnswerId="10389" CreationDate="2022-05-19T05:32:37.743" Score="7" ViewCount="195" Body="&lt;p&gt;I want to study the adsorption energies of many different atoms to some surfaces. For that, I need to calculate the energies of free atoms (adsorbates) in a vacuum.&lt;/p&gt;&#xA;&lt;p&gt;I understand that I am supposed to put an atom into a large cell to minimize its interactions with its periodic images.&lt;/p&gt;&#xA;&lt;p&gt;However, I am confused, what kind of cell should I use.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Symmetric or asymmetric?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the &lt;a href=&quot;https://www.materialssquare.com/blog/5-short-but-important-calculation-of-a-single-atom&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Square&lt;/a&gt; site, they advise an asymmetric (orthorhombic) cell in order to avoid partial occupation of orbitals by electrons. VASP wiki also advises low symmetry (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/O_atom_spinpolarized_low_symmetry&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Calculation_of_atoms&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;However, in the &lt;a href=&quot;https://compmatphys.epotentia.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Materials Physics&lt;/a&gt; course, I learned that it is better to put an atom into an FCC cell because the atom in that cell has the largest number of nearest neighbors which makes their influence on the atom as isotropic as possible and thus minimizes interactions caused by the finite size of the cell.&lt;/p&gt;&#xA;&lt;p&gt;Which cell is better? A highly symmetric FCC, a slightly distorted orthorhombic, or some other one?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="81" LastEditorUserId="5" LastEditDate="2023-02-08T18:12:12.797" LastActivityDate="2023-02-08T18:12:12.797" Title="What is the best cell shape to calculate the energy of a free atom with a periodic DFT code (VASP)?" Tags="|density-functional-theory|vasp|reference-request|symmetry|software-input-file-request|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9111" PostTypeId="1" CreationDate="2022-05-19T06:33:51.023" Score="3" ViewCount="470" Body="&lt;p&gt;Just recently got into DFT and I've been doing a few calculations on my own on Quantum Espresso. I've come up with electronic band structures for materials that I've been looking at and I was hoping to see if I'm coming up with the right conclusion regarding them. Two of them are shown below (used EV-GGA to calculate for these, could have used others, but I'm sticking to the Engel-Vosko for now)&lt;a href=&quot;https://i.stack.imgur.com/zkJYv.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zkJYv.jpg&quot; alt=&quot;Band structure 1&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vZcx5.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vZcx5.jpg&quot; alt=&quot;Band structure 2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;These are undoped materials, and so I'm seeing that these are metallic in nature. I guess my main question is, what makes the Fermi level pass through the valence or conduction band? Is it the interaction of the orbitals of the atoms in the crystal? And would doping have an effect on the position of the Fermi level in these materials (electron doping in the first case, and hole doping in the second case)?&lt;/p&gt;&#xA;" OwnerUserId="5108" LastActivityDate="2022-05-28T19:46:30.390" Title="What does it mean if the Fermi level crosses into the valence band? How about into the conduction band?" Tags="|density-functional-theory|quantum-espresso|band-structure|semiconductor|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9112" PostTypeId="2" ParentId="9080" CreationDate="2022-05-19T09:34:43.700" Score="3" Body="&lt;p&gt;Turns out the issue is that Fortran is required to run solvent-based calculations in parallel. My cloud instances did not have it installed. Problem was solved after installing Fortran. Answer was from &lt;a href=&quot;https://orcaforum.kofo.mpg.de/viewtopic.php?f=9&amp;amp;t=7566&amp;amp;hilit=MPI_Type_match_size&amp;amp;start=30#p32678&quot; rel=&quot;nofollow noreferrer&quot;&gt;Orca Forum&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4313" LastActivityDate="2022-05-19T09:34:43.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9113" PostTypeId="1" AcceptedAnswerId="9115" CreationDate="2022-05-19T10:48:35.703" Score="4" ViewCount="607" Body="&lt;p&gt;Let’s suppose that&#xA;(1) it’s required to calculate a crystal with certain parameters of a crystal lattice;&#xA;(2) this crystal has some defects (let it be Frenkel defects for simplicity);&#xA;(3) these defects are distributed into a crystal without any pattern, or distributed with a pattern, which is not related to a periodicity of a crystal lattice.&#xA;Are the following statements correct?&#xA;(1) a Kohn–Sham (KSh) equation is not fit for such a calculation;&#xA;(2) KSh equation would be fit if a way would exist which could take into account positions of defects in a crystal. Maybe could it be a probability density function constructed by a special manner;&#xA;(3) a Hartree–Fock (HF) equation in this case would be fit better than KSh equation, but in this case a boundary conditions of a crystal must be taken into account, because HF equation doesn’t include an infinite periodicity unlike KSh equation.&lt;/p&gt;&#xA;&lt;p&gt;Is there a thing combining a periodicity and a crystal defect distribution?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5025" LastEditDate="2022-05-20T12:51:42.243" LastActivityDate="2022-05-27T19:10:04.307" Title="Which formalism is better suited to model a crystal with defects: Hartree–Fock, Kohn–Sham, or something else?" Tags="|density-functional-theory|ab-initio-calculations|crystallography|hartree-fock|defects|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9115" PostTypeId="2" ParentId="9113" CreationDate="2022-05-19T11:51:08.460" Score="7" Body="&lt;p&gt;Let me first clarify a few things.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Whether a calculation is Kohn-Sham or Hartree-Fock has nothing to do with whether the calculation is periodic or not. In fact, both Kohn-Sham and Hartree-Fock can be applied to both finite-sized clusters &lt;em&gt;and&lt;/em&gt; periodic systems. Some programs may only support some of the 2x2=4 combinations, for example it is well possible that some program can do Kohn-Sham calculations on both periodic systems and clusters, and Hartree-Fock calculations on clusters, but not Hartree-Fock calculations on periodic systems. But then this is a limitation of that particular program, not a fundamental property of Kohn-Sham and/or Hartree-Fock. One may, however, easily have the false impression that Kohn-Sham is inherently periodic and Hartree-Fock is inherently non-periodic, if they learned the Kohn-Sham equation from a condensed matter physics course (which typically only mentions the periodic case), and the Hartree-Fock equation from a computational chemistry course (which typically only mentions the non-periodic case).&lt;/li&gt;&#xA;&lt;li&gt;Regardless of whether Kohn-Sham or Hartree-Fock is used, defects that are not periodically distributed can only be approximately modeled, either by using a large enough but finite-sized cluster, or a large enough (periodic) super cell. This is because you can only describe a finite number of atoms, otherwise it takes infinite amount of time just to write the input file, let alone for the calculation to finish. The cluster or super cell can however be extremely large, so large that the periodicity and finite size effects are effectively negligible, especially if you use linear-scaling DFT or machine learning methods to speed up the calculation. You can also use a series of increasingly large clusters or super cells and extrapolate the results to infinite size. (Nevertheless, if the non-periodically distributed defect is distributed in a more or less regular manner, for example following the lattice of some quasicrystal, then it is conceivable that an exact simulation is possible; however I don't know if exact simulations of quasicrystals have been reported. Even if yes, such techniques are not commonplace yet and probably involve very complicated mathematics.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;With these being said, it is apparent that both the Hartree-Fock and Kohn-Sham equations can be used to simulate defects, but only after either the crystal is truncated to a finite size, or the distribution of the defects are approximated as periodic; these two approximations can however be made very good. So which one is better for simulating defects? Theoretically the answer is Kohn-Sham, since the Hartree-Fock method lacks correlation completely, so that adding any DFT correlation term on top of HF gives us a DFT functional that is usually better than HF. In practice, however, some programs may support pure functionals and HF, but no DFT functionals with 100% HF exchange; in this case, it may turn out that all functionals supported by these particular programs perform worse than HF, especially for those defects where self-interaction error plays a significant role. However, again this is a problem of the program, not a problem of the theories.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-05-19T11:51:08.460" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9116" PostTypeId="2" ParentId="9113" CreationDate="2022-05-19T15:23:15.647" Score="6" Body="&lt;p&gt;I would like to add a few aspects to the answer of wzkchem5.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Considering local or semilocal xc functionals for the KS equations, one difference between HF and KS is that HF is computationally more expensive. One thus has stricter limitations on supercell and cluster sizes if such a setup is used for calculating the effects of having an impurity in the system.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There is also the question of what quantity one is interested in. One may be interested in defect states appearing in a band gap. In such a research effort one should be aware that KS-DFT with LDA or GGA functionals underestimates the band gap, while HF overestimates it. None of these approaches is thus perfect. I don't know whether in a generalized Kohn-Sham scheme hybrid functionals help in such situations. While hybrid functionals often predict a better band gap, it is unclear to me whether defect states are placed at the correct energy. Hybrid functionals also come at the cost of the HF approach. One may, however, also be interested in other impurity-related properties where such issues do not arise.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;There actually is at least one DFT approach capable to treat nonperiodic, single impurities in an otherwise perfect periodic host crystal. One can base such a calculation on the Korringa-Kohn-Rostoker (KKR) method, which is nowadays often implemented as a Green's function method. If you base the formulation of KS-DFT on Green's functions instead of wavefunctions, you obtain a Dyson equation in the formalism. This connects a final Green's function to a Green's function of some prototype system and to the deviations from this prototype system. The formulation thus opens an elegant path to investigate deviations or distortions from a known potential. Such a deviation can be due to a single impurity in an otherwise periodic material. For the HF method you need wavefunctions, so that this cannot be elegantly combined with a Green's function KKR KS-DFT approach. There are probably also other approaches allowing a similarly elegant formulation of such impurity setups. In 1D, for example, one may also think about a setup similar to what can be realized in the TranSIESTA code. Of course, the treatment of single impurities does not cover all possible impurity distributions, but such calculations may be good starting points for model-based approaches for such distributions.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="142" LastEditDate="2022-05-27T19:10:04.307" LastActivityDate="2022-05-27T19:10:04.307" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9117" PostTypeId="1" CreationDate="2022-05-19T17:20:07.247" Score="3" ViewCount="98" Body="&lt;p&gt;In the coupled cluster code of PySCF, is the four index tensor stored in memory or in disk?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="671" LastEditDate="2022-05-19T22:03:37.247" LastActivityDate="2022-05-19T22:03:37.247" Title="Is the 4-index tensor in the coupled cluster code of PySCF stored in memory or on disk?" Tags="|coupled-cluster|pyscf|" AnswerCount="0" CommentCount="5" ClosedDate="2023-06-14T01:03:58.550" ContentLicense="CC BY-SA 4.0" />
  <row Id="9118" PostTypeId="1" CreationDate="2022-05-19T18:08:03.220" Score="1" ViewCount="45" Body="&lt;p&gt;I found this figure:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/ax0Ks.png&quot; width=&quot;400&quot;/&gt;&#xA;&lt;p&gt;In the following paper:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.preprints.org/manuscript/202202.0213/v1&quot; rel=&quot;nofollow noreferrer&quot;&gt;A Review on Multiscale Modelling and Simulation for Polymer Nanocomposites&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, I am skeptical about its correctness, as this paper is not peer-reviewed.&lt;/p&gt;&#xA;&lt;p&gt;I think:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Red is OK&lt;/li&gt;&#xA;&lt;li&gt;blue and green have misleading titles. I should make the green “molecular scale”, and blue should be the “sub-molecular scale”&lt;/li&gt;&#xA;&lt;li&gt;I should remove DFDT  from green&lt;/li&gt;&#xA;&lt;li&gt;I should move Molecular Dynamics (should be abbreviated MD) to green&lt;/li&gt;&#xA;&lt;li&gt;I should move MC to green&lt;/li&gt;&#xA;&lt;li&gt;I should add DFT and QMMD (Quantum Mechanics Molecular Dynamics) do blue&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Can anyone supply me with a reference (book or article) so that I can study the correct relationships between various techniques of various scales?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2022-05-19T20:37:09.983" LastActivityDate="2022-05-19T20:37:09.983" Title="Interlink among different length scales of simulation and modelling techniques" Tags="|reference-request|molecular-modeling|atomistic-simulation|" AnswerCount="0" CommentCount="7" ClosedDate="2023-02-07T02:38:07.857" ContentLicense="CC BY-SA 4.0" />
  <row Id="9119" PostTypeId="1" CreationDate="2022-05-20T07:07:50.997" Score="3" ViewCount="468" Body="&lt;p&gt;I plan to study the Diffusion-Coefficient of my simulation outputs, for this, I want to use ASE.&#xA;Sadly I am not entirely sure of how to proceed, has anyone done this and if yes, please share your suggestions.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;class &#xA;ase.md.analysis.DiffusionCoefficient(traj, timestep, atom_indices=None, molecule=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also provide the source code,&#xA;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/_modules/ase/md/analysis.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/_modules/ase/md/analysis.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="4219" LastActivityDate="2022-05-20T07:07:50.997" Title="Calculating the Diffusion coffecients from Trajectory file in ASE" Tags="|molecular-dynamics|computational-chemistry|python|" AnswerCount="0" CommentCount="0" ClosedDate="2022-07-21T17:39:21.397" ContentLicense="CC BY-SA 4.0" />
  <row Id="9120" PostTypeId="1" CreationDate="2022-05-20T12:02:07.690" Score="2" ViewCount="49" Body="&lt;p&gt;I want to find out how to get subdivisions from vasprun.xml of Brillouin zone. Does anyone know how to do this?&lt;/p&gt;&#xA;" OwnerUserId="5373" LastEditorUserId="1256" LastEditDate="2022-05-20T19:17:35.267" LastActivityDate="2022-05-20T19:17:35.267" Title="How do I find out the subdivisions N_1, N_2 and N_3 in BAND STRUCTURE?" Tags="|vasp|k-points|" AnswerCount="0" CommentCount="3" ClosedDate="2022-12-12T15:20:16.990" ContentLicense="CC BY-SA 4.0" />
  <row Id="9121" PostTypeId="1" AcceptedAnswerId="10371" CreationDate="2022-05-20T13:52:37.987" Score="7" ViewCount="113" Body="&lt;p&gt;I know that it is impossible for real electrons and nuclei. In the Kohn and Sham approach, a system of interacting electrons is approximated by a system of non-interacting Kohn-Sham particles in an effective potential.&lt;/p&gt;&#xA;&lt;p&gt;My question refers not to a real chemical system. Rather, I am asking about a system of toy particles that don't necessarily correspond to reality.&lt;/p&gt;&#xA;&lt;p&gt;Is there such a system of multiple interacting quantum particles for which density can be obtained analytically for arbitrary number of particles, at least in terms of some special functions, say, hypergeometric functions?&lt;/p&gt;&#xA;&lt;p&gt;The particles may be point particles, they may interact not necessarily at contact, may be only pairwise interactions, maybe in 1D, etc.&lt;/p&gt;&#xA;" OwnerUserId="81" LastEditorUserId="5" LastEditDate="2023-02-07T02:22:46.880" LastActivityDate="2023-02-07T02:22:46.880" Title="Is there a system of multiple interacting quantum particles for which the density can be obtained analytically?" Tags="|density-functional-theory|reference-request|ab-initio-calculations|model-hamiltonians|many-body-physics|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9123" PostTypeId="1" CreationDate="2022-05-20T22:20:36.680" Score="2" ViewCount="389" Body="&lt;p&gt;I am trying to compare the CPU and GPU versions of VASP.6.3.0, it seems that the GPU version consumes a lot of time on the STRESS item, does it represent the time for calculation stress tensor?&lt;/p&gt;&#xA;&lt;p&gt;Here is the time statistic of the GPU version for running an electronic step:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    CHARGE:  cpu time      1.9418: real time      1.9387&#xA;    FORLOC:  cpu time      0.0368: real time      0.0368&#xA;    FORNL :  cpu time     12.8479: real time     12.8406&#xA;    STRESS:  cpu time     40.6397: real time     40.6181&#xA;    FORCOR:  cpu time      0.0939: real time      0.0936&#xA;    FORHAR:  cpu time      0.0465: real time      0.0465&#xA;    MIXING:  cpu time      0.2403: real time      0.2405&#xA;    OFIELD:  cpu time      0.0000: real time      0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the time statistic of the CPU version:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    CHARGE:  cpu time      0.3036: real time      0.3050&#xA;    FORLOC:  cpu time      0.0392: real time      0.0393&#xA;    FORNL :  cpu time      1.3977: real time      1.4043&#xA;    STRESS:  cpu time      4.2436: real time      4.2663&#xA;    FORCOR:  cpu time      0.2220: real time      0.2232&#xA;    FORHAR:  cpu time      0.0584: real time      0.0587&#xA;    MIXING:  cpu time      0.0468: real time      0.0469&#xA;    OFIELD:  cpu time      0.0000: real time      0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-20T22:20:36.680" Title="Why does the GPU version of VASP consume a lot of time on STRESS calculation?" Tags="|vasp|high-performance-computing|software-assistance|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-07T02:39:38.363" ContentLicense="CC BY-SA 4.0" />
  <row Id="9124" PostTypeId="2" ParentId="3704" CreationDate="2022-05-21T03:56:33.247" Score="4" Body="&lt;p&gt;Let's start by unpacking Eq. (1), which we rewrite here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;(H_{SCF} - \varepsilon_n)\lvert \Delta \psi_n \rangle = -(\Delta V_{SCF} + \Delta \varepsilon_n) \lvert \psi_n \rangle.&#xA;\tag{1}\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Well, we know (Eq. (28) of &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.515&quot; rel=&quot;nofollow noreferrer&quot;&gt;Baroni et al.&lt;/a&gt;) that the variation in wavefunction &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; can be written as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;\Delta \psi_n(r) = \sum_{m \neq n} \frac{\langle \psi_m | \Delta V_{SCF} | \psi_n \rangle}{\varepsilon_n - \varepsilon_m} \psi_m(r),&#xA;\tag{28}\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$n, m$&lt;/span&gt; range over both occupied states, &lt;span class=&quot;math-container&quot;&gt;$\lvert \psi \rangle \in occ$&lt;/span&gt;, and virtual states, denoted &lt;span class=&quot;math-container&quot;&gt;$\lvert \phi \rangle \not\in occ$&lt;/span&gt;. (Note that our expressions will lack a factor of 2 compared to Baroni et al. because we are counting up and down spin orbitals separately.)&lt;/p&gt;&#xA;&lt;p&gt;Now, the response to the electron density is only summed over &lt;em&gt;occupied&lt;/em&gt; states. So, taking &lt;span class=&quot;math-container&quot;&gt;$z^*$&lt;/span&gt; as the complex conjugate of &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;, Eqs. (23) and (29) of Baroni et al. read&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{align}&#xA;\Delta n(r) &amp;amp;= \sum_{n \in occ} \left[ \Delta \psi_n^*(r) \psi_n(r) + \psi_n^*(r) \Delta \psi_n(r) \right] \tag{23} \\\\&#xA;&amp;amp;= \sum_{n \in occ} \sum_{m \neq n} \left[ \psi_m^*(r) \frac{\langle \psi_n | \Delta V_{SCF} | \psi_m \rangle}{\varepsilon_m - \varepsilon_n} \psi_n(r) + \psi_n^*(r) \frac{\langle \psi_m | \Delta V_{SCF} | \psi_n \rangle}{\varepsilon_n - \varepsilon_m} \psi_m(r) \right]. \tag{29}&#xA;\end{align}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we let &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; range over occupied states, we notice that the contributions to &lt;span class=&quot;math-container&quot;&gt;$\Delta n$&lt;/span&gt; coming from orbitals &lt;span class=&quot;math-container&quot;&gt;$m,n$&lt;/span&gt; and from &lt;span class=&quot;math-container&quot;&gt;$n,m$&lt;/span&gt; cancel; so we can take &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; to range over the virtual states only. This is succinctly described a little later in Baroni et al.:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the response of the system to an external perturbation depends only on the component of the perturbation that couples the occupied-state manifold with the empty-state one.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Let's return to Eq. (1) above. &lt;strong&gt;Implicit in passing to Eq. (2) is the idea that &lt;span class=&quot;math-container&quot;&gt;$\lvert \psi_n \rangle$&lt;/span&gt; is an occupied state&lt;/strong&gt;: that means that &lt;span class=&quot;math-container&quot;&gt;$\lvert \Delta \psi_n \rangle$&lt;/span&gt; lives in the virtual manifold. That's why we multiply the right side of Eq. (2) onto &lt;span class=&quot;math-container&quot;&gt;$P_c$&lt;/span&gt;, the unoccupied projector. What we really meant was&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;(H_{SCF} - \varepsilon_n)\lvert \Delta \psi_n \rangle = - P_v (\Delta V_{SCF} + \Delta \varepsilon_n) \lvert \psi_n \rangle - P_c (\Delta V_{SCF} + \Delta \varepsilon_n) \lvert \psi_n \rangle,&#xA;\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but the components of &lt;span class=&quot;math-container&quot;&gt;$\lvert \Delta \psi_n \rangle \in \text{span}\ {P_v}$&lt;/span&gt; are all zero, so we can just neglect to write it. This gives us the original Eq. (2):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;(H_{SCF} + \alpha P_v - \varepsilon_n) \lvert \Delta \psi_n \rangle = -P_c \Delta V_{SCF} \lvert \psi_n \rangle, \qquad n \in occ.&#xA;\tag{2}\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But the occupied-virtual coupling goes both ways! If we let &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; in Eq. (29) index the (infinitely many, so we just handwave away the functional analysis issues) virtual states, then &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; has to index occupied states. So if we assume &lt;span class=&quot;math-container&quot;&gt;$\lvert \psi_n \rangle$&lt;/span&gt; is an unoccupied state in Eq. (1), then &lt;span class=&quot;math-container&quot;&gt;$\lvert \Delta \psi_n \rangle$&lt;/span&gt; must belong to the occupied manifold, and we can write&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA; (H_{SCF} - \varepsilon_n) \lvert \Delta \psi_n \rangle = -P_v \Delta V_{SCF} \lvert \psi_n \rangle \qquad n \not\in occ;&#xA;\tag{3}\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(note that &lt;span class=&quot;math-container&quot;&gt;$\Delta \epsilon_n = \langle \psi_n | \Delta V_{SCF} | \psi_n \rangle$&lt;/span&gt; goes away upon the projection just like in the question's equation &lt;span class=&quot;math-container&quot;&gt;$1 \to 2$&lt;/span&gt;), and we can fix singularities in &lt;span class=&quot;math-container&quot;&gt;$H_{SCF} - \varepsilon_n$&lt;/span&gt; by adding a small amount of an operator we know acts trivially on &lt;span class=&quot;math-container&quot;&gt;$\lvert \Delta \psi_n \rangle$&lt;/span&gt;. So at long last&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{equation}&#xA;(H_{SCF} + \alpha P_c - \epsilon_n) \lvert \Delta \psi_n \rangle = -P_v \Delta V_{SCF} \lvert \psi_n \rangle, \qquad n \not\in occ. \tag{4}&#xA;\end{equation}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2022-05-21T03:56:33.247" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9125" PostTypeId="1" CreationDate="2022-05-21T06:49:37.363" Score="4" ViewCount="103" Body="&lt;p&gt;I have performed a MD simulation using GROMACS for a system of 100  caffeine molecules in water. It is expected caffeine  form aggregates.&lt;/p&gt;&#xA;&lt;p&gt;I have calculated the radius of gyration for the simulation time of 25 ns for the system.&lt;/p&gt;&#xA;&lt;p&gt;What is the impact/ means this radius of gyration parameter tells on aggregate formation since system contain aggregates in several position inside the simulation box?&lt;/p&gt;&#xA;" OwnerUserId="5431" LastActivityDate="2022-05-21T06:49:37.363" Title="Radius of gyration and aggregates" Tags="|molecular-dynamics|computational-chemistry|gromacs|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-07T04:10:46.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="9127" PostTypeId="1" CreationDate="2022-05-21T11:02:41.847" Score="2" ViewCount="104" Body="&lt;p&gt;I know that the following can be simulated:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;secondary/tertiary structure prediction&lt;/li&gt;&#xA;&lt;li&gt;protein-surface/protein-protein interaction tests&lt;/li&gt;&#xA;&lt;li&gt;protein-ligand binding test&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I wonder if references or explanations could be given for these and any other things I've missed on this list.&lt;/p&gt;&#xA;&lt;p&gt;What do we simulate with the molecular simulation of proteins in theoretical or academic research?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-02-06T21:25:08.147" LastActivityDate="2023-02-13T16:56:27.490" Title="What do we simulate with molecular simulation of proteins in the theoretical research?" Tags="|reference-request|one-topic-per-answer|proteins|atomistic-simulation|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9128" PostTypeId="1" CreationDate="2022-05-21T15:28:17.950" Score="3" ViewCount="84" Body="&lt;p&gt;As far as I understand, both MD and MC simulation methods use Force Fields.&lt;/p&gt;&#xA;&lt;p&gt;Are there any other similarities between them?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-05-21T15:43:56.623" LastActivityDate="2022-05-21T15:43:56.623" Title="What are the similarities between MD and MC in the case of protein simulation?" Tags="|molecular-dynamics|monte-carlo|" AnswerCount="0" CommentCount="9" ClosedDate="2023-02-07T02:39:17.900" ContentLicense="CC BY-SA 4.0" />
  <row Id="9129" PostTypeId="1" AcceptedAnswerId="9132" CreationDate="2022-05-21T20:21:16.893" Score="7" ViewCount="390" Body="&lt;p&gt;According to &lt;a href=&quot;https://en.wikipedia.org/wiki/Force_field_(chemistry)#Transferability&quot; rel=&quot;noreferrer&quot;&gt;Wikipedia&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Functional forms and parameter sets have been defined by the developers of interatomic potentials and feature variable degrees of self-consistency and transferability. When functional forms of the potential terms vary, the parameters from one interatomic potential function can typically not be used together with another interatomic potential function.[19] In some cases, modifications can be made with minor effort, for example, between 9-6 Lennard-Jones potentials to 12-6 Lennard-Jones potentials.[9] Transfers from Buckingham potentials to harmonic potentials, or from Embedded Atom Models to harmonic potentials, on the contrary, would require many additional assumptions and may not be possible.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I haven't really understood this.&lt;/p&gt;&#xA;&lt;p&gt;Can you give me a layman's definition of &amp;quot;Transferable&amp;quot; FF?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-05-21T20:29:00.117" LastActivityDate="2022-05-23T13:21:32.947" Title="What does it mean by &quot;transferable&quot; in the case of a force field?" Tags="|forcefields|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9130" PostTypeId="1" CreationDate="2022-05-22T01:45:53.807" Score="6" ViewCount="159" Body="&lt;p&gt;For hydrogen, the 3-21G basis set (in CFOUR format) is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H:3-21G&#xA;3-21G Split-valence basis set&#xA;&#xA;  1&#xA;    0&#xA;    2&#xA;    3&#xA;&#xA;0.5447178000D+01 0.8245472400D+00 0.1831915800D+00 &#xA;&#xA;0.1562849787D+00 0.00000000 &#xA;0.9046908767D+00 0.00000000 &#xA;0.00000000 1.0000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My interpretation is that this defines two orbitals:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\phi_1 = 0.1562849787g(0.5447178) + 0.9046908767g(0.8245472400)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_2 = 1.0g(0.18319158)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But how are these two orbitals combined to form an orbital for the lone electron?&lt;/p&gt;&#xA;" OwnerUserId="5435" LastActivityDate="2022-05-22T02:50:51.737" Title="How exactly are valence orbitals combined in split valence basis sets such as 3-21G?" Tags="|computational-chemistry|gaussian|basis-sets|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9131" PostTypeId="2" ParentId="9130" CreationDate="2022-05-22T02:50:51.737" Score="6" Body="&lt;p&gt;They are combined into the final orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi_i$&lt;/span&gt; through a linear combination, &lt;span class=&quot;math-container&quot;&gt;$\sum_j c_{ij} \phi_j$&lt;/span&gt;. Determining the coefficients &lt;span class=&quot;math-container&quot;&gt;$c_{ij}$&lt;/span&gt; of that combination is the entire goal of the calculation.&lt;/p&gt;&#xA;" OwnerUserId="1440" LastActivityDate="2022-05-22T02:50:51.737" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9132" PostTypeId="2" ParentId="9129" CreationDate="2022-05-22T02:51:05.877" Score="10" Body="&lt;p&gt;A forcefield defining the interactions of an atom is said to be transferrable if it can be successfully used in chemical simulations outside of where it was originally designed or fit.&lt;/p&gt;&#xA;&lt;p&gt;For example: you are given interaction potential parameters for a particular model of water that recreates the correct experimental melting point and structure of water. The model is &lt;em&gt;transferred&lt;/em&gt; to a simulation of a supersaturated solution of &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt; in water, with some interaction potential of &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt; defined using the same functional form (e.g. Lennard-Jones). The interaction parameters between water and the ions are then defined by some combining rules. If the simulation gives useful results, the water model is said to be transferrable to simulations of supersaturated &lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt; in water.&lt;/p&gt;&#xA;&lt;p&gt;Transferability basically refers to the ability of an interaction potential to be useful/accurate between different chemical environments.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-05-22T02:56:52.860" LastActivityDate="2022-05-22T02:56:52.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9133" PostTypeId="1" AcceptedAnswerId="9135" CreationDate="2022-05-21T23:48:21.560" Score="9" ViewCount="619" Body="&lt;p&gt;I'm trying to code an integral library for my own QC software from scratch. I need to use the spherical basis functions like in any other popular program. So, a D basis function is supposed to make five MOs, an F function is supposed to make seven, and so on.&lt;/p&gt;&#xA;&lt;p&gt;But how do I find the representations for each D and higher AM basis function? Is there a general formula that can be conveniently applied to generate as many representations as necessary for angular momenta up to…  I?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$x^iy^jz^k\exp\left(-\alpha r^2\right) \quad \text{with} \quad i + j + k = n$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Suppose, the total angular momentum is &lt;span class=&quot;math-container&quot;&gt;$2,$&lt;/span&gt; the number of representations thus will be &lt;span class=&quot;math-container&quot;&gt;$2n + 1 = 5,$&lt;/span&gt; thus it is five primitive basis functions with the same centers and same exponent values, but what exactly are these representations?&lt;/p&gt;&#xA;" OwnerUserId="5447" OwnerDisplayName="Dmitry Govorov" LastEditorUserId="269" LastEditDate="2022-05-22T17:22:51.690" LastActivityDate="2022-05-27T19:06:59.797" Title="How to build cartesian representations of spherical Gaussian basis functions?" Tags="|quantum-chemistry|basis-sets|algorithms|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9134" PostTypeId="1" AcceptedAnswerId="9175" CreationDate="2022-05-22T12:09:47.217" Score="4" ViewCount="154" Body="&lt;p&gt;What are the definitions of the terms &amp;quot;&lt;strong&gt;modeling&lt;/strong&gt;&amp;quot; and &amp;quot;&lt;strong&gt;simulation&lt;/strong&gt;&amp;quot; in the context of biomolecules and/or proteins?&lt;/p&gt;&#xA;&lt;p&gt;Examples will be highly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Also, please, back them up with authoritative references.&lt;/p&gt;&#xA;&lt;p&gt;The definitions I found don't reflect molecular biology or related fields. E.g. &lt;a href=&quot;https://books.google.pl/books?id=QrTJiwTwSG8C&amp;amp;printsec=copyright&amp;amp;redir_esc=y#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Principles of Modeling and Simulation A Multidisciplinary Approach&lt;/em&gt; (edited by John A. Sokolowski and Catherine M. Bank)&lt;/a&gt; contains those definitions.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;MODELS: APPROXIMATIONS OF REAL - WORLD EVENTS&lt;/p&gt;&#xA;&lt;p&gt;A model is a representation of an event and/or things that is real (a case study) or contrived (a use - case). It can be a representation of an actual system. It can be something used in lieu of the real thing to better understand a certain aspect about that thing. To produce a model you must abstract from reality a description of a vibrant system. The model can depict the system at some point of abstraction or at multiple levels of the abstraction with the goal of representing the system in a mathematically reliable fashion. A simulation is an applied methodology that can describe the behavior of that system using either a mathematical model or a symbolic model [4] . Simply, simulation is the imitation of the operation of a real - world process or system over a period of time [3] . As you will see there are many uses of M &amp;amp; S. M &amp;amp; S can be used to determine the ordering policies of Wal - Mart ’ s extensive inventory system, or it can be used to analyze the prospects and rate of rehabilitation of a patient who just underwent knee - replacement surgery, or it can be used to evaluate ocean currents and waves to better understand weather patterns.&lt;/p&gt;&#xA;&lt;p&gt;M &amp;amp; S begins with 1) developing computer simulation or a design based on a model of an actual or theoretical physical system, then 2) executing that model on a digital computer, and 3) analyzing the output. Models and the ability to act out with those models is a credible way of understanding the complexity and particulars of a real entity [4] . From these three steps you can see that M &amp;amp; S facilitates the simulation of a system and then a testing of the hypothesis about that system. For example, if you wanted to determine how many cashiers are needed to process a certain number of customers during rush hour with the assurance that the store ’ s high level of quality service was not compromised, you must fi rst research the current system of processing customers.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However, I am not sure if they are applicable for molecular or biomolecular modeling.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-05-24T13:36:13.247" LastActivityDate="2022-05-31T06:39:06.153" Title="Definition of the terms &quot;modeling&quot; and &quot;simulation&quot; in the context of biomolecules and/or proteins" Tags="|reference-request|molecular-modeling|terminology|atomistic-simulation|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9135" PostTypeId="2" ParentId="9133" CreationDate="2022-05-22T12:35:20.800" Score="9" Body="&lt;p&gt;Following Helgaker &lt;em&gt;et al.&lt;/em&gt; in &amp;quot;&lt;a href=&quot;https://www.wiley.com/en-gb/Molecular+Electronic+Structure+Theory-p-9780471967552&quot; rel=&quot;noreferrer&quot;&gt;Molecular Electronic-Structure Theory&lt;/a&gt;&amp;quot; a real valued spherical harmonic GTO can be written as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\chi_{\alpha_{nl}lm}^{GTO}=N_{\alpha_{nl}lm}^{GTO}S_{lm}e^{-\alpha_{nl}r^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$N_{\alpha_{nl}lm}^{GTO}$&lt;/span&gt; is a normalisation constant, and &lt;span class=&quot;math-container&quot;&gt;$S_{lm}$&lt;/span&gt; is a real solid harmonic, which is the polynomial you want. The real solid harmonics obey the recurrence relations&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S_{00}=1$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{l+1,l+1}=\sqrt{2^{\delta_{l0}}{{2l+1}\over{2l+2}}}[xS_{l,l}-(1-\delta_{l0})yS_{l,-l}]$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{l+1,-l-1}=\sqrt{2^{\delta_{l0}}{{2l+1}\over{2l+2}}}[yS_{l,l}+(1-\delta_{l0})xS_{l,-l}]$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$S_{l+1,m}={{(2l+1)zS_{lm}-\sqrt{(l+m)(l-m)}{r^2}S_{l-1,m}}\over{\sqrt{(l+m+1)(l-m+1)}}} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is sufficient to evaluate the (form of the) polynomials.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively explicit formulae for the coefficients in the polynomials have been published in &lt;a href=&quot;https://doi.org/10.1002/qua.560540202&quot; rel=&quot;noreferrer&quot;&gt;Schlegel, H.B. and Frisch, M.J. (1995), Transformation between Cartesian and pure spherical harmonic Gaussians. Int. J. Quantum Chem., 54: 83-87&lt;/a&gt; . Again from Helgaker &lt;em&gt;et al.&lt;/em&gt; these are given as follows: If &lt;span class=&quot;math-container&quot;&gt;$G_{lm}({\bf r},a,{\bf A})$&lt;/span&gt; represents a spherical-harmonic GTO with exponent &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and centered at &lt;span class=&quot;math-container&quot;&gt;${\bf R_A}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$G_{x,y,z}({\bf r},a,{\bf A})$&lt;/span&gt; similarly for a Cartesian GTO then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_{lm}({\bf r},a,{\bf A})=N^{S}_{lm}&#xA;\sum_{t=0}^{[(l-\left|m\right|)/2]}&#xA;\sum_{u=0}^{t}&#xA;\sum_{v=v_m}^{[\left|m\right|/2-v_m]+v_m}&#xA;C_{tuv}^{lm}G_{2t+\left|m\right|-2(u+v),2(u+v),l-2t-\left|m\right|}({\bf r},a,{\bf A})&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$N^{S}_{lm}={1\over{2^{\left|m\right|}l!}}\sqrt{{2(l+\left|m\right|)!(l-\left|m\right|)!}\over{2^{}\delta_{0m}}}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$C_{tuv}^{lm}=(-1)^{t+v-v_m}{1\over 4}^t&#xA;\binom{l}{t}&#xA;\binom{l-t}{\left|m\right|+t}&#xA;\binom{t}{u}&#xA;\binom{\left|m\right|}{2v}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ v_m = 0 \space for \space m \ge 0, {1\over 2} \space for \space m&amp;lt;0$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I strongly suggest you check the above formulae from the original sources for typos!&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="269" LastEditDate="2022-05-22T15:31:29.793" LastActivityDate="2022-05-22T15:31:29.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9136" PostTypeId="1" CreationDate="2022-05-22T15:55:04.013" Score="6" ViewCount="122" Body="&lt;p&gt;In order to relate results from quantum chemical calculations to experiment, it&#xA;is essential to compute quantities that are directly available from measurements.&lt;/p&gt;&#xA;&lt;p&gt;Properties describe the &amp;quot;response&amp;quot; of the molecular system to an external&#xA;perturbation &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$&#xA;        E(\lambda) = E(0) +&#xA;        \left(\frac{\partial E}{\partial \lambda}\right)_{0}\lambda +&#xA;        \frac{1}{2!}\left(\frac{\partial^2 E}{\partial \lambda^2}\right)_0\lambda^2 +&#xA;        \frac{1}{3!}\left(\frac{\partial^3 E}{\partial \lambda^3}\right)_0\lambda^3 +&#xA;        \ldots&#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;That is, to calculate any property of a molecule, it is necessary to take these derivatives by &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;'s. There are two ways to do this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Finite-differentiation techniques (so-called &amp;quot;finite-field&amp;quot; calculations).&lt;/li&gt;&#xA;&lt;li&gt;The alternative to numerical differentiation is &lt;em&gt;analytic differentiation&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;So, for the finite-differentiation techniques we must know how the energy depends on the field &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; and calculate the finite differences:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\frac{dE}{d\lambda} \approx \frac{E(\lambda + \delta\lambda) - E(\lambda)}{\Delta\lambda}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's consider &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/qua.560160825&quot; rel=&quot;nofollow noreferrer&quot;&gt;Derivative studies in hartree-fock and møller-plesset theories by Pople at all&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Formula from which to start for taking the first derivative is (22)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$&#xA;\frac{\partial E_{HF}}{\partial\lambda} = \sum_{\mu\nu} P_{\mu\nu} \left(\frac{\partial h_{\mu\nu}}{\partial\lambda}\right) + &#xA;+ \frac12 \sum_{\mu\nu\lambda\sigma} P_{\mu\nu}P_{\lambda\sigma} \frac{\partial}{\partial\lambda} (\mu\lambda|\nu\sigma) + \frac{\partial V_\text{nuclei}}{\partial\lambda} - \sum_{\mu\nu}W_{\mu\nu} \left(\frac{\partial S_{\mu\nu}}{\partial\lambda}\right)&#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then dances with a tambourine begin around how to take these derivatives caled coupled perturbed Hartree-Fock theory. To parametrize for this purpose the MO coefficient derivatives in the following way:&#xA;&lt;span class=&quot;math-container&quot;&gt;$&#xA;c_{\mu i}(\lambda) = \sum_{p} c_{\mu p}(0) u_{pi}(\lambda)&#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or for derivative&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$&#xA;\frac{\partial c_{\mu i}(\lambda)}{\partial\lambda} = \sum_{p} c_{\mu p}(0) \frac{\partial u_{pi}(\lambda)}{{\partial\lambda}} &#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;coeffcients &lt;span class=&quot;math-container&quot;&gt;$u_{pi}(\lambda)$&lt;/span&gt; as the parameters to be determined.&lt;/p&gt;&#xA;&lt;p&gt;I still have some misunderstanding: where do these initial derivatives come from? Indeed, from the Hartree-Fock method, we obtain only numerical values of the orbital coefficients. But, as shown in the article, there you already need to know their derivatives with respect to the field. How to set these initial derivatives?&lt;/p&gt;&#xA;&lt;p&gt;What is the meaning of the method of analytical derivatives using in all computational Chemistry soft?&lt;/p&gt;&#xA;&lt;p&gt;The result of the QCh calculations is the value of ground state energy &lt;span class=&quot;math-container&quot;&gt;$E(0)$&lt;/span&gt;. Is it really necessary for the method to set some field value &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;, or does the method do without them?&lt;/p&gt;&#xA;&lt;p&gt;(There are a lot of formulas with derivatives in many textbooks, but the very zest of the method escapes me)&lt;/p&gt;&#xA;&lt;p&gt;Algorithm (from &lt;a href=&quot;https://www.researchgate.net/publication/273182083_A_Coupled-Perturbed_SCF_Approach_for_Calculating_Static_Polarizabilities_and_Hyperpolarizabilities_with_Non-Orthogonal_Localized_Molecular_Orbitals&quot; rel=&quot;nofollow noreferrer&quot;&gt;article&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ibEVq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ibEVq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5264" LastEditorUserId="5264" LastEditDate="2022-05-23T07:37:23.050" LastActivityDate="2022-05-23T07:37:23.050" Title="Analytical derivative method in ab initio molecular properties calculations" Tags="|quantum-chemistry|physical-properties-of-materials|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-09T23:00:30.953" ContentLicense="CC BY-SA 4.0" />
  <row Id="9137" PostTypeId="1" CreationDate="2022-05-23T11:54:21.597" Score="3" ViewCount="58" Body="&lt;p&gt;How to obtain the relation between &lt;span class=&quot;math-container&quot;&gt;$G_{ab}(\tau,0,0,0)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$G_{ab}(\beta-\tau,0,0,0)$&lt;/span&gt; for two-particle fermion Green function&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$G_{ab}(\tau_1,\tau_2,\tau_3,\tau_4)=\langle \mathcal{T}a^\dagger(\tau_1)a(\tau_2)b^{\dagger}(\tau_3)b(\tau_4)\rangle$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$0&amp;lt;\tau&amp;lt;\beta$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="4741" LastEditorUserId="24" LastEditDate="2022-05-24T12:38:59.030" LastActivityDate="2022-05-24T12:38:59.030" Title="Green function KMS boundary condition" Tags="|quantum-mechanics|greens-functions|many-body-physics|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-14T01:04:49.930" ContentLicense="CC BY-SA 4.0" />
  <row Id="9138" PostTypeId="2" ParentId="9129" CreationDate="2022-05-23T13:21:32.947" Score="4" Body="&lt;p&gt;I believe Hayden's answer is the correct one based on how the term transferability is typically used in this regard. However, the Wikipedia article you site seems to be describing a slightly different sense of the term in that paragraph. From what they describe, and the linked papers they cite, they seem to mean &amp;quot;transferability&amp;quot; as the ability to transfer parameters from one force field model to another. The example they give is taking the parameters used to fit a 9-6 Lennard-Jones potential and repurposing them to use in a 12-6 &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lennard-Jones potential&lt;/a&gt;. So that paragraph seems to be more about whether the model parameters can be meaningfully converted between different models, rather than whether the force field is applicable for systems/properties beyond those for which the parameters were initially fit.&lt;/p&gt;&#xA;&lt;p&gt;This is definitely nonstandard terminology, as neither of the papers Wikipedia cites use the term &amp;quot;transferability&amp;quot; to describe what they are doing.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-05-23T13:21:32.947" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9139" PostTypeId="1" CreationDate="2022-05-24T03:59:50.327" Score="4" ViewCount="93" Body="&lt;p&gt;I'm trying to implement the Rys Quadrature method for integrations of Gaussians, from scratch. I'm using &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.540110809&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper as a reference.&lt;/p&gt;&#xA;&lt;p&gt;So, how does the overall recursion relation for evaluating 1D integrals (18) look like in the code? Python or C/C++ or anything similar that you can use would be fine.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PHWCO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PHWCO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As I see it, the recursive relation starts from calling the function calculating (18) which calls itself with different arguments until arguments equal 0. In this case, (11) is calculated. Which means I need nested if-else conditions, but what would they be like? The formulae (15) and (16) confuse me a lot, because they both correspond to &lt;em&gt;j&lt;/em&gt; = 0, &lt;em&gt;l&lt;/em&gt; = 0. And, also, what do &lt;em&gt;n&lt;/em&gt; and &lt;em&gt;m&lt;/em&gt; mean in the authors' notation?&lt;/p&gt;&#xA;&lt;p&gt;In the text (15) and (16) are both referenced as Ix(ix + jx, 0, kx + lx, 0) which doesn't make any sense to me:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rulJj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rulJj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5447" LastEditorUserId="269" LastEditDate="2022-05-24T05:17:03.667" LastActivityDate="2022-05-24T05:17:03.667" Title="Rys Quadrature method for integrating over Gaussian basis functions: 1D integral recursion relation" Tags="|hartree-fock|integrals|algorithms|" AnswerCount="0" CommentCount="6" ClosedDate="2023-02-07T03:09:30.000" ContentLicense="CC BY-SA 4.0" />
  <row Id="9140" PostTypeId="2" ParentId="3896" CreationDate="2022-05-24T04:50:32.743" Score="2" Body="&lt;p&gt;The following paper is quite nice, in my opinion:&lt;/p&gt;&#xA;&lt;p&gt;Shang et al., Temperature-dependent elastic stiffness constants of α- and θ-Al2O3 from first-principles calculations, J. Phys. Condens. Matter 22 (2010) 375403 &lt;a href=&quot;https://doi.org/10.1088/0953-8984/22/37/375403&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1088/0953-8984/22/37/375403&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The key concept is outlined in Section 2.2, which is the same approach suggested by Pranav. To summarize:&lt;/p&gt;&#xA;&lt;ol start=&quot;0&quot;&gt;&#xA;&lt;li&gt;Construct a set of volumes to build an equation of state for a quasiharmonic approximation.&lt;/li&gt;&#xA;&lt;li&gt;For each volume, compute the elastic constants at 0K, creating some relationship for your elastic constants, &lt;span class=&quot;math-container&quot;&gt;$c_{ij}(V)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Use the quasiharmonic approximation (&lt;span class=&quot;math-container&quot;&gt;$\min_V F(V,T)$&lt;/span&gt;) to find the equilibrium volume as a function of temperature, &lt;span class=&quot;math-container&quot;&gt;$V_{eq}(T)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;At each temperature of interest, you know the equilibrium volume at that temperature from (2) and you can obtain the elastic constants at that temperature using the calculations from (1), i.e. &lt;span class=&quot;math-container&quot;&gt;$c_{ij}(T) = c_{ij}(V=V_{eq}(T))$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1179" LastActivityDate="2022-05-24T04:50:32.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9141" PostTypeId="1" CreationDate="2022-05-24T05:54:12.660" Score="3" ViewCount="374" Body="&lt;p&gt;In DFT, the Coulomb energy is defined as the sum of Hartree energy, nuclear-electron attraction, and nuclear-nuclear repulsion. In VASP output, we can find the Hartree energy, and also the nuclear-nuclear repulsion (sum of alpha Z and Ewald energy). My question is, how to get the nuclear-electron attraction term?&lt;/p&gt;&#xA;" OwnerUserId="5448" LastActivityDate="2023-04-20T19:01:25.137" Title="Coulomb energy in VASP" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9142" PostTypeId="1" CreationDate="2022-05-24T11:54:47.417" Score="4" ViewCount="210" Body="&lt;p&gt;This is the example of &lt;a href=&quot;https://www.science.smith.edu/cmbs/wp-content/uploads/sites/36/2015/09/Qubit-Protein-Assay.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Qubit™ Protein Assay&lt;/a&gt; curve.&#xA;It relates the concentration (x-axis) with fluorescence (y-axis).&#xA;&lt;strong&gt;What is the curve-fitting method it use for this?&lt;/strong&gt; Clearly this is not simple linear fitting model.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dwXes.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dwXes.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2022-12-10T17:31:42.447" LastActivityDate="2022-12-10T17:31:42.447" Title="What is the curve fitting model used for the &quot;Qubit™ Protein Assay Kit&quot;?" Tags="|mathematical-modeling|proteins|commercial-products|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9143" PostTypeId="1" AcceptedAnswerId="9148" CreationDate="2022-05-25T09:01:18.633" Score="7" ViewCount="99" Body="&lt;p&gt;&lt;strong&gt;Aim:&lt;/strong&gt;&lt;br /&gt;&#xA;I want to obtain a reasonably accurate ionization energy (or work function in other terms) for a 2-dimensional hBN monolayer. The exact material does not matter much respective to the question, the point is it being a 2D periodic material.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Method:&lt;/strong&gt;&lt;br /&gt;&#xA;The GW model, in general, gives a pretty accurate ionization potential. For an isolated molecule, the SCM code (in the AMS package) works, I've tested it for isolated h-passivated hBN nanoparticles. However, the code does not implement GW for periodic systems, and I couldn't reach a convergent territories by increasing the nanoparticle size before running out of computer resources. Therefore, I turned to Yambo.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Doubt:&lt;/strong&gt;&lt;br /&gt;&#xA;If I'd want to obtain &lt;span class=&quot;math-container&quot;&gt;$I_p$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;) from a Quantum Espresso DFT calculation, I would have to calculate the vacuum energy (from the average potential), and subtract this from the HOMO value. On the other hand, the SCM documentation (specifically, &lt;a href=&quot;https://www.scm.com/doc/Tutorials/OpticalPropertiesElectronicExcitations/GW.html#results&quot; rel=&quot;nofollow noreferrer&quot;&gt;the G0W0 tutorial&lt;/a&gt;) states that the resulting HOMO energy from a G0W0 calculation, &lt;span class=&quot;math-container&quot;&gt;$E_{GW}^{HOMO}$&lt;/span&gt;, is the negative of the ionization potential,&lt;span class=&quot;math-container&quot;&gt;$I_p$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;I_p = - E_{G_0W_0}^{HOMO}&#xA;$$&lt;/span&gt;&#xA;However, &lt;strong&gt;they give no reference to this statement&lt;/strong&gt;, and I couldn't find anything useful.&lt;/p&gt;&#xA;&lt;p&gt;The various tutorials of Yambo (e.g. &lt;a href=&quot;http://www.yambo-code.org/wiki/index.php?title=How_to_obtain_the_quasi-particle_band_structure_of_a_bulk_material:_h-BN&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;) on G0W0 only use the GW energies to obtain the band gap value. This is a relative energy between two bands, so tells me nothing if the absolute values are WRT vacuum.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is it a fundamental property of G0W0 that &lt;span class=&quot;math-container&quot;&gt;$E_{GW}^{HOMO} = -I_p$&lt;/span&gt;, or is this specific to the SCM code?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If no, is it at least true for Yambo as well?&lt;/p&gt;&#xA;" OwnerUserId="968" LastEditorUserId="968" LastEditDate="2022-05-27T08:36:24.467" LastActivityDate="2022-05-27T08:39:51.467" Title="Is the HOMO energy obtained from GW calculation always a value relative to the vacuum energy (-Ip)?" Tags="|density-functional-theory|gw-bse|binding-energy|yambo|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9144" PostTypeId="1" AcceptedAnswerId="9146" CreationDate="2022-05-25T09:13:27.607" Score="8" ViewCount="215" Body="&lt;p&gt;I read that ORCA runs a QuasiRRHO calculation based on Grimme approximation, at the end of a &lt;em&gt;freq&lt;/em&gt; calculation.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, I wasn't able to find the default value for the CutOffFreq. In Grimme's article, I can't figure out which is the suggested value.&#xA;Comparing the value to the value that comes out from GoodVibes and from Shermo the difference is very little (some decimals of kcal/mol or the 5th decimal of Hartree).&lt;/p&gt;&#xA;&lt;p&gt;Is possible to assume that the default value is &lt;span class=&quot;math-container&quot;&gt;$100\ cm^{-1}$&lt;/span&gt; as in these two scripts?&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-05-25T13:47:27.127" Title="QuasiRRHO in Orca" Tags="|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9145" PostTypeId="1" CreationDate="2022-05-25T10:22:46.323" Score="6" ViewCount="598" Body="&lt;p&gt;I have tried to use &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Machine_learning_force_field_calculations:_Basics&quot; rel=&quot;noreferrer&quot;&gt;VASP's machine learning force field calculation&lt;/a&gt; during running molecular dynamics simulation with a supercell including some elements of Ti, O, Cu, etc. It does increase the speed dramatically, but I am wondering if I could use the generated force field in other calculations. &lt;br&gt;&#xA;For example, I want to simulate a new supercell including elements of Fe, Ti, O, etc.  According to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Machine_learning_force_field_calculations:_Basics&quot; rel=&quot;noreferrer&quot;&gt;vasp wiki website&lt;/a&gt;, &lt;code&gt;It is permissible to change the number of atoms or even to add new elements, when the training is continued.&lt;/code&gt;&lt;br&gt;&#xA;My question is:&lt;br&gt;&#xA;If I train the force field every time I run a new molecular simulation, no matter what elements I am using. Is it possible to build a force field that suits all elements? Or it is gonna fall into some trap of overfitting?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2023-02-06T21:13:15.217" LastActivityDate="2023-02-06T21:13:15.217" Title="Is it possible to build a force field that suits all elements based on VASP's machine learning result?" Tags="|density-functional-theory|vasp|molecular-dynamics|machine-learning|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9146" PostTypeId="2" ParentId="9144" CreationDate="2022-05-25T13:47:27.127" Score="8" Body="&lt;p&gt;I have access to ORCA's source code, and I can assure you that ORCA indeed uses &lt;span class=&quot;math-container&quot;&gt;$\omega_0 = 100 \rm{~cm^{-1}}$&lt;/span&gt;. However &lt;span class=&quot;math-container&quot;&gt;$\omega_0$&lt;/span&gt; is hard-coded in ORCA and not controlled by the input parameter CutOffFreq; if the user specifies the latter, it means that all frequencies smaller than CutOffFreq are neglected in the calculation of the partition function, which is a completely different thing than what &lt;span class=&quot;math-container&quot;&gt;$\omega_0$&lt;/span&gt; does.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/chem.201200497&quot; rel=&quot;noreferrer&quot;&gt;Grimme's paper&lt;/a&gt;, it has actually been explicitly mentioned that &amp;quot;We chose a value of &lt;span class=&quot;math-container&quot;&gt;$\omega_0 = 100 \rm{~cm^{-1}}$&lt;/span&gt; as a default&amp;quot; (right after Eq. (8)). Therefore the people who wrote the corresponding chapter in the ORCA manual probably didn't bother to stress that again. That being said, the same paper also said that &lt;span class=&quot;math-container&quot;&gt;$\omega_0$&lt;/span&gt; can be anywhere between &lt;span class=&quot;math-container&quot;&gt;$50 \rm{~cm^{-1}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$150 \rm{~cm^{-1}}$&lt;/span&gt; without deteriorating the results, and indeed some papers did choose other values (such as &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2021/SC/D1SC00621E&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt; which chose &lt;span class=&quot;math-container&quot;&gt;$50 \rm{~cm^{-1}}$&lt;/span&gt;). Given this, I may consider mentioning &lt;span class=&quot;math-container&quot;&gt;$\omega_0 = 100 \rm{~cm^{-1}}$&lt;/span&gt; in the ORCA manual so that future users can exactly reproduce the procedure that ORCA is using.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-05-25T13:47:27.127" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9147" PostTypeId="1" CreationDate="2022-05-26T20:07:02.140" Score="10" ViewCount="280" Body="&lt;p&gt;I would like to analyze a Slater-Koster tight binding model for some materials. I have the data for both the Hamiltonian as a matrix-valued map on the reciprocal lattice &lt;span class=&quot;math-container&quot;&gt;$H_{mn}(\vec{T})$&lt;/span&gt; and the overlap matrix &lt;span class=&quot;math-container&quot;&gt;$S_{mn}(\vec{T})$&lt;/span&gt;. My question is: what are the tools available that generate the band structure and calculate topological indices? I know that several tools exist, such as Z2Pack and Wanniertools. Can these tools work with Slater-Koster models? For example, in Slater-Koster models, one has to deal with non orthonormal basis vectors. In this case, one needs to supply the overlap matrices, but I am not sure if these tools automatically assume that the overlap matrices are unity.&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastEditorDisplayName="user5405" LastEditDate="2022-05-26T20:29:43.233" LastActivityDate="2022-08-01T20:21:29.587" Title="Tools for working with tight-binding models" Tags="|tight-binding|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9148" PostTypeId="2" ParentId="9143" CreationDate="2022-05-27T08:29:10.940" Score="4" Body="&lt;p&gt;In the meantime, &lt;strong&gt;Daniele Varsano&lt;/strong&gt; answered me on the Yambo forum. I quote him below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;In Yambo, the zero of the energy is set at the valence band maximum&lt;/strong&gt; (VBM). The GW will give you the correction to the corresponding KS eigenvalue.&lt;br /&gt;&#xA;If you want this value relative to the vacuum you will need to align it wrt the vacuum energy calculated by QE in the way you described, ie apply the QP correction to the work function you calculated with QE.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The zero-point of the GW energy in Yambo is thus &lt;em&gt;not&lt;/em&gt; always the vacuum energy, that was an SCM-specific property.&lt;/p&gt;&#xA;&lt;p&gt;Link to the thread: &lt;a href=&quot;http://www.yambo-code.org/forum/viewtopic.php?p=11888#p11888&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.yambo-code.org/forum/viewtopic.php?p=11888#p11888&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="968" LastEditorUserId="968" LastEditDate="2022-05-27T08:39:51.467" LastActivityDate="2022-05-27T08:39:51.467" CommentCount="1" CommunityOwnedDate="2022-05-27T08:29:10.940" ContentLicense="CC BY-SA 4.0" />
  <row Id="9149" PostTypeId="1" AcceptedAnswerId="9200" CreationDate="2022-05-27T14:56:52.767" Score="7" ViewCount="785" Body="&lt;p&gt;I'm working with QE 7.0 for the computation of some properties of solids.&#xA;My working theory requires me to access all the information inside the wfc#c.dat/h5 files, created in the prefix.save directory for further post-processing.&#xA;For the post-processing I created a python script, that works well with the .h5 files. &lt;br /&gt;&#xA;My issue is that for a few of my system the calculations were made with a version of QE that was compiled without hdf5, and since the calculation is very large for the size of the HPC I have access to, I prefer not to redo the calculation with another compilation of QE.&lt;/p&gt;&#xA;&lt;p&gt;I'm now trying to read the data in the wfc#k.dat files, but can't figure out exactly how. I've tried using &lt;code&gt;scipy.io.FortranFile&lt;/code&gt; but I can't manage to figure it out. I've also tried looking for converters for the .dat files to .h5 format, but couldn't find any.&lt;/p&gt;&#xA;&lt;p&gt;I have close to no experience with Fortran, and no experience at all with Fortran unformatted binary files, so the information in the QE snippets &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/snippets/1869208&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/snippets/1869208&lt;/a&gt; and &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/snippets/1869202&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/snippets/1869202&lt;/a&gt; are of no help to me.&lt;/p&gt;&#xA;&lt;p&gt;I'd highly appreciate any help with this issue.&lt;/p&gt;&#xA;&lt;p&gt;edit: In the meanwhile I've managed to redo the calculation with a hdf5-enabled version, but out of curiosity I'd still appreciate insights into this.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastEditorUserId="5481" LastEditDate="2022-05-31T10:46:36.060" LastActivityDate="2022-06-10T08:30:12.700" Title="How to read QE's wfc*.dat files with python" Tags="|quantum-espresso|python|fortran|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9151" PostTypeId="2" ParentId="9103" CreationDate="2022-05-27T19:30:48.683" Score="4" Body="&lt;p&gt;Open shell atoms are multireference pretty much by definition. Take fluorine, for example, which has a &lt;span class=&quot;math-container&quot;&gt;$1s^2 2s^2 2p^5$&lt;/span&gt; electron configuration and a &lt;span class=&quot;math-container&quot;&gt;$^2P$&lt;/span&gt; ground state. We know that the electronic Hamiltonian commutes with the &lt;span class=&quot;math-container&quot;&gt;$\hat{L}^2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{L}_z$&lt;/span&gt; operators. If you use a single-determinant method such as Hartree-Fock (HF) or Kohn-Sham density functional theory (DFT), you will not get an eigenstate of &lt;span class=&quot;math-container&quot;&gt;$\hat{L}^2$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2$&lt;/span&gt;; instead, you will get symmetry breaking.&lt;/p&gt;&#xA;&lt;p&gt;However, this is not considered a huge issue in practice; DFT practitioners happily carry out calculations on open shell atoms to determine singlet-triplet gaps or atomization energies, for instance. The calculations can just be hard to converge due to the plethora of local minima caused by open shells, especially for transition metals or lanthanides and actinides.&lt;/p&gt;&#xA;&lt;p&gt;Coupled cluster theory is exact in principle. The question there is whether you are going to high enough rank in the excitations to capture the effects of strong correlation. For main group elements single reference CCSD is already quite accurate, as far as I know, and it is also commonly used by the atomic physics community. CCSD was also used in the &lt;a href=&quot;https://www.science.org/doi/10.1126/science.aah5975&quot; rel=&quot;nofollow noreferrer&quot;&gt;famous study by Medvedev et al&lt;/a&gt; to calculate reference electron densities for ions with 2, 4 and 10 electrons. It should also be feasible to compute electron densities with CCSDT or CCSDTQ with modern quantum chemistry codes, and doing so observe how the density converges with improved description of electron correlation.&lt;/p&gt;&#xA;&lt;p&gt;PS. Note that the atomic physics community has a &lt;em&gt;different&lt;/em&gt; definition for HF: their HF is not a single-determinant method, but a single (atomic) configuration method where the wave function ansatz is a proper eigenstate of &lt;span class=&quot;math-container&quot;&gt;$\hat{L}^2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2$&lt;/span&gt;. Similarly, DFT people tend to assume spherical symmetric densities for atoms; this amounts to using fractional occupations in the calculation so one is screwing up physics to some extent. The same words are used for different methods, so one has to be careful about which meaning is used in what context.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-05-27T19:30:48.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9152" PostTypeId="2" ParentId="1924" CreationDate="2022-05-27T20:14:23.763" Score="4" Body="&lt;p&gt;The command for calculating &lt;code&gt;vacf&lt;/code&gt; is:&lt;/p&gt;&#xA;&lt;p&gt;• &lt;code&gt;compute velacf all vacf&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can use &lt;code&gt;fix ave/time&lt;/code&gt; command to export &lt;code&gt;compute&lt;/code&gt; results into a file. From lammps doc, by &lt;code&gt;compute vacf&lt;/code&gt; command &amp;quot;A vector of four quantities is calculated&amp;quot;. So you can specify which columns you'd want to export by using &lt;code&gt;c_velacf[x]&lt;/code&gt;   &lt;code&gt;x: 1,2,3,4, c: compute ID&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The syntax for &lt;code&gt;fix ave/time&lt;/code&gt; is as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;fix ID group-ID ave/time Nevery Nrepeat Nfreq value1 value2 ... keyword args ...&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;More can be found in the doc pages but simply divide your Simulation timesteps (i.e. 10,000) by &lt;code&gt;Nfreq&lt;/code&gt; (i.e. 100), and you'll have the results printed for 100 times. So using this should do it:&lt;/p&gt;&#xA;&lt;p&gt;• &lt;code&gt;fix myvacf all ave/time 1 1 100 c_vac[1] c_vac[2] c_vac[3] c_vac[4] file vacf.dat&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="5483" LastActivityDate="2022-05-27T20:14:23.763" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9153" PostTypeId="2" ParentId="9000" CreationDate="2022-05-27T20:51:40.147" Score="1" Body="&lt;p&gt;It really depends on your criterion for convergence. For many applications convergence up to 1 meV is more than enough, and then the ecutwfc of 70eV is perfect, and probably 60eV is also good enough.&#xA;For other applications convergence up to ~10meV is excellent, and then you could even go lower towards 50eV or even 40eV.&lt;/p&gt;&#xA;&lt;p&gt;Fromy experience, for monolayer MoS2 70eV is usually a good value to use.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-05-27T20:51:40.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9154" PostTypeId="2" ParentId="9111" CreationDate="2022-05-28T19:46:30.390" Score="3" Body="&lt;p&gt;The 0-energy outputted by QE does not necessarily correspond with the Fermi energy.&#xA;Depending on what keywords you use in your input, you can get the actual Fermi-energy outputted - you should try looking for &amp;quot;Fermi energy&amp;quot; in you scf output.&#xA;In any all other cases you should get the energy of the highest occupied level - try looking for &amp;quot;highest occupied level&amp;quot; in your scf output.&lt;/p&gt;&#xA;&lt;p&gt;After getting this value, you can always shift your band structures so that the 0-energy corresponds to either the valence band maximum, the fermi energy, or any other value of interest.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-05-28T19:46:30.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9155" PostTypeId="2" ParentId="9065" CreationDate="2022-05-28T19:54:20.023" Score="2" Body="&lt;p&gt;You could try to relax a (much smaller) unit cell for iron, then after that is relaxed you can create and relax the slab with initial guess as the already pre-relaxed coordinates for the irons, which should be much easier.&#xA;In case it is needed - you can find a tutorial on how to get the slab from the unit cell using VESTA in &lt;a href=&quot;https://www.youtube.com/watch?v=6xx29-CQJiA&amp;amp;ab_channel=NickelandCopper&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In any case, if it continues like this you should ask for larger convergence thresholds - both for energy and for the forces, and only after it converges for these larger values then you begin tightening them.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-05-28T19:54:20.023" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9156" PostTypeId="1" AcceptedAnswerId="9159" CreationDate="2022-05-29T11:10:55.123" Score="1" ViewCount="564" Body="&lt;p&gt;How can I express speed in Angstroms/second after application of a force that's in eV/Angstrom (given the mass, original velocity and time elapsed)?&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2022-05-29T16:47:44.403" LastActivityDate="2022-05-29T16:47:44.403" Title="I have a force in eV/Angstroms. How do I convert it so that the speed I calculate is in Angstroms/second?" Tags="|molecular-dynamics|soft-question|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="9157" PostTypeId="1" CreationDate="2022-05-29T15:56:16.380" Score="2" ViewCount="47" Body="&lt;p&gt;As we all know computer science, electrical engineering, etc. knowledge can be used in developing software and electronics/electrical products that can be sold to end-users (B2C).&lt;/p&gt;&#xA;&lt;p&gt;Can protein modeling and simulation be used to develop such products other than drug discovery?&lt;/p&gt;&#xA;&lt;p&gt;Or, is it just about scientific/academic research meant for B2B clients?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2022-05-29T17:32:43.930" LastActivityDate="2022-05-29T17:32:43.930" Title="Can protein modeling and simulation be used in developing a marketable product?" Tags="|molecular-modeling|proteins|atomistic-simulation|" AnswerCount="0" CommentCount="7" ClosedDate="2023-02-07T04:11:08.133" ContentLicense="CC BY-SA 4.0" />
  <row Id="9158" PostTypeId="1" AcceptedAnswerId="9164" CreationDate="2022-05-29T16:10:07.607" Score="3" ViewCount="682" Body="&lt;p&gt;In the paper &amp;quot;&lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5027645&quot; rel=&quot;nofollow noreferrer&quot;&gt;DeePCG: Constructing coarse-grained models via deep neural networks&lt;/a&gt;&amp;quot;, it says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In molecular dynamics (MD), we are often faced with two types of coarse-graining tasks.&lt;/p&gt;&#xA;&lt;p&gt;In a ﬁrst set of applications, we are interested in evaluating the Landau free energy, which is a function of a small subset of coarse-grained (CG) variables. In this case, the CG variables are either scalar or low dimensional vector variables.&lt;/p&gt;&#xA;&lt;p&gt;In a second set of applications, we are interested in sampling with molecular dynamics (MD) or with Monte Carlo (MC) the conﬁgurations of an extensive set of CG variables.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In my opinion, the sentence:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;em&gt;In molecular dynamics (MD), we are often faced with two types of coarse-graining tasks.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;should have been:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;em&gt;In molecular modeling ...&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Am I correct?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="671" LastEditDate="2022-05-29T19:32:19.857" LastActivityDate="2022-06-01T10:58:14.233" Title="Is it correct to say &quot;in molecular dynamics we are faced with...&quot; or should it be &quot;in molecular modeling we are faced with&quot;?" Tags="|molecular-modeling|terminology|publishing|coarse-grained|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9159" PostTypeId="2" ParentId="9156" CreationDate="2022-05-29T16:41:47.190" Score="1" Body="&lt;p&gt;Applying a force &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; acting on a mass &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;, the acceleration according to classical mechanics is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;a = \frac{F}{m}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Given the speed &lt;span class=&quot;math-container&quot;&gt;$v(0)$&lt;/span&gt; at time &lt;span class=&quot;math-container&quot;&gt;$t=0$&lt;/span&gt; and the acceleration, we can obtain the speed at any time by one of the &amp;quot;&lt;a href=&quot;https://www.physicsclassroom.com/class/1DKin/Lesson-6/Kinematic-Equations&quot; rel=&quot;nofollow noreferrer&quot;&gt;big four&lt;/a&gt;&amp;quot; kinematic equations which are usually taught in high school physics, and most certainly taught in every first-year university physics curriculum on the planet. The relevant kinematic equation for your question is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;v(t) = v(0) + a\cdot t.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Substituting Eq. (1) into Eq. (2) gives us:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;v(t) = v(0) + \frac{F}{m}t.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$v(0)$&lt;/span&gt; is given to you in Angstroms/second, we simply need to ensure that &lt;span class=&quot;math-container&quot;&gt;$Ft/m$&lt;/span&gt; is also in Angstroms/second. If &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is given to you in eV/Angstrom, &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; is given to you in kg, and &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is being measured in seconds, we can start by converting the Force into SI units:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}{\tiny&#xA;F ~~\textrm{[eV/Angstrom}] \times \left( \frac{1.60218\times10^{-19} \textrm{J}}{\textrm{eV}}\right) \times \left( 1 ~~\frac{\textrm{kg}\cdot {\textrm{m}}^2/\textrm{s}^2}{{\textrm{J}}}\right)\times \left(\frac{10^{10} \textrm{Angstroms}}{\textrm{m}}\right)^2 = F~~\textrm{[kg $\cdot$ Angstroms/s$^2$]}}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So your force in eV/Angstrom just needs to be multiplied by 16.0218 to get a force in kg&lt;span class=&quot;math-container&quot;&gt;$\cdot$&lt;/span&gt;Angstroms/s&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;. You can then multiply it by the time in seconds, and divide by the mass in kg, and you will get the &amp;quot;change in speed&amp;quot; in Angstroms/s from the starting speed of &lt;span class=&quot;math-container&quot;&gt;$v(0)$&lt;/span&gt; which is also given in Angstroms/s, therefore yielding a final speed in Angstroms/s.&lt;/p&gt;&#xA;&lt;p&gt;Note that all of this assumes that the acceleration is constant, which means the force needs to be constant.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-05-29T16:41:47.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9160" PostTypeId="2" ParentId="9158" CreationDate="2022-05-29T17:16:00.787" Score="5" Body="&lt;p&gt;From a grammatical perspective, I agree with you.&lt;/p&gt;&#xA;&lt;p&gt;It would have been better for them to have said &amp;quot;in molecular dynamics &lt;strong&gt;calculations&lt;/strong&gt;...&amp;quot;. instead of just &amp;quot;in molecular dynamics...&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;In fact, an even better sentence would be &amp;quot;when using molecular dynamics for molecular modeling...&amp;quot; and your suggestion is in this spirit.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;However, every single scientific paper ever published has sentences which can be improved far more than that sentence which you singled out in your question here.&lt;/strong&gt; Pick the paper that you think is the most perfect out of all papers, and I'll find a sentence that can be significantly improved. The improvement that you have suggested here is what most people in scientific &lt;a href=&quot;/questions/tagged/publishing&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;publishing&amp;#39;&quot; rel=&quot;tag&quot;&gt;publishing&lt;/a&gt; would consider to be extremely &lt;em&gt;&lt;strong&gt;minor&lt;/strong&gt;&lt;/em&gt;, and if you point out matters like this to the authors of such papers, it might be significantly &lt;em&gt;&lt;strong&gt;harmful to your academic career.&lt;/strong&gt;&lt;/em&gt; Likewise, I am fairly certain that if I didn't edit your question (including my edit of your original title), and/or write this answer, it would have had a negative effect on your reputation as a Stack Exchange user, leading the community to take your future questions less seriously. Therefore, my advice would be for you to &lt;strong&gt;focus on the science.&lt;/strong&gt; Keep in mind that every scientific paper that has ever been published, has issues like the one you found here, and hopefully knowing this will help you make better decisions on where to spend your precious time, energy and focus throughout the rest of your scientific career :)&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-05-29T17:16:00.787" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9161" PostTypeId="1" AcceptedAnswerId="9162" CreationDate="2022-05-29T18:53:37.153" Score="6" ViewCount="229" Body="&lt;p&gt;I am somewhat confused by the use of a Kronecker Product in Madsen, Georg K. H. et al. “BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients.” &lt;a href=&quot;https://arxiv.org/pdf/1712.07946.pdf&quot; rel=&quot;noreferrer&quot;&gt;Comput. Phys. Commun. 231 (2018): 140-145&lt;/a&gt;. (Link to paper on arXiv). The equation I'm having trouble with is equation 8 which reads&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma(\epsilon,T)=\int \sum_b &#xA;{\bf v}_{b,{\bf k}}\otimes {\bf v}_{b,{\bf k}}\tau_{b,{\bf k}}&#xA;\delta(\epsilon-\epsilon_{b,{\bf k}}){{d{\bf k}}\over{8\pi^3}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kronecker_product&quot; rel=&quot;noreferrer&quot;&gt;Kronecker product&lt;/a&gt; supposed to do here? My understanding is that the result of such an operation should be a matrix but that makes no mathematical sense to me in this context, so what is going on?&lt;/p&gt;&#xA;" OwnerUserId="269" LastActivityDate="2022-05-29T20:22:33.640" Title="Meaning of Kronecker Product in Transport Theory behind BoltzTrap2" Tags="|electronic-structure|electronic-transport|transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9162" PostTypeId="2" ParentId="9161" CreationDate="2022-05-29T20:18:41.453" Score="5" Body="&lt;p&gt;Yes, that operation yields a matrix result. The charge conductivity &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is also a matrix (often called the conductivity tensor) so the equation looks correct. It may be clearer if written out with indices:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma^{\alpha\beta}(\epsilon,T)=\int \sum_b &#xA;{ v}^\alpha_{b,{\bf k}} { v}^\beta_{b,{\bf k}}\tau_{b,{\bf k}}&#xA;\delta(\epsilon-\epsilon_{b,{\bf k}}){{d{\bf k}}\over{8\pi^3}}.&#xA;$$&lt;/span&gt;&#xA;In general crystal structures, &lt;span class=&quot;math-container&quot;&gt;$\sigma^{\alpha\beta}$&lt;/span&gt; can have off-diagonal elements. Another way of saying that is that the electric current &lt;span class=&quot;math-container&quot;&gt;$\mathbf{J}_e$&lt;/span&gt; need not (even in the absence of a temperature gradient) be parallel to the electric field &lt;span class=&quot;math-container&quot;&gt;$\mathbf{E}$&lt;/span&gt; unless &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is constrained to be diagonal by symmetry.&lt;/p&gt;&#xA;&lt;p&gt;If you need more background than the BoltzTraP2 paper provides, Boltzmann transport theory is treated in standard textbooks. But note that different books use subtly different conventions - especially when it comes to the definition of the &lt;span class=&quot;math-container&quot;&gt;$\mathcal{L}^{(a)}$&lt;/span&gt; symbols - so be careful if using formulas from multiple sources. The convention used in the paper appears to be the same as in Marder's Condensed Matter Physics book, which is different from the convention used by e.g. Ashcroft &amp;amp; Mermin.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2022-05-29T20:22:33.640" LastActivityDate="2022-05-29T20:22:33.640" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9163" PostTypeId="1" CreationDate="2022-05-30T06:11:50.433" Score="3" ViewCount="54" Body="&lt;p&gt;Gold schmidt parameter was created in order to see if a perovskite crystal structure would have crystal distortion in feasible range or not. This parameter has been extended to various other forms of perovskite, recently to layered double perovskite&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemmater.9b04021&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Basically one needs to find the shannon ionic radii of all the elements present in the perovskite material(&lt;span class=&quot;math-container&quot;&gt;$A_4 M^{2+} M^{3+}_2 X_{12}$&lt;/span&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fSNXP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fSNXP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;then you see if t and &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; lie in the range or not.&lt;/p&gt;&#xA;&lt;p&gt;I have been trying to calculate this for a few different combinations but I am a bit confused.&lt;/p&gt;&#xA;&lt;p&gt;How can I be sure what is the coordination number for a given position. I actually tried using VESTA for this. We could see which atom is almost touching to the other atoms in the unit cell. One approach would be to look at the number of bonds that it forms(with whatever atom is the closest) or the other is to take in consideration the size of each ion and then see how many atoms are touching to a particular atom(even then there is some confusion as almost all the atoms has some space in between them and due to which some are bit closer and some a bit farther)&lt;/p&gt;&#xA;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemmater.9b04021&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemical Diversity in Lead-Free, Layered Double Perovskites: A Combined Experimental and Computational Approach&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-05-30T11:15:40.240" LastActivityDate="2022-05-30T11:15:40.240" Title="Gold schmidt parameter calculation for perovskite materials" Tags="|crystallography|perovskites|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-07T04:11:36.723" ContentLicense="CC BY-SA 4.0" />
  <row Id="9164" PostTypeId="2" ParentId="9158" CreationDate="2022-05-30T06:26:16.407" Score="4" Body="&lt;p&gt;Technically, I think you are correct: if you are talking about both molecular dynamics simulations and Monte Carlo methods, then you are talking about molecular modelling.&lt;/p&gt;&#xA;&lt;p&gt;But why not get even &lt;em&gt;more&lt;/em&gt; technical? After all, neural network potentials are almost all interatomic. None of them are, therefore, &lt;em&gt;molecular&lt;/em&gt;. Surely anybody who uses DeepCG is therefore not doing molecular dynamics or molecular modelling -- they are doing &lt;em&gt;atomistic&lt;/em&gt; modelling.&lt;/p&gt;&#xA;&lt;p&gt;Ah! But nobody actually models atoms: what they're &lt;em&gt;really&lt;/em&gt; doing is modelling &lt;em&gt;nuclear motion&lt;/em&gt;, with the fiction that electrons are continuously-variable point charges that just sit on top of the nuclei at all times. Very well, nobody is allowed to say &amp;quot;molecular dynamics&amp;quot;, or &amp;quot;molecular modelling&amp;quot;, or &amp;quot;atomistic simulations&amp;quot;, or any portmanteau of components therein; what we are all &lt;em&gt;really&lt;/em&gt; doing is point-orbitalized Born-Oppenheimer nuclear dynamics. POBOND is not a bad acronym at all!&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;You need to ask yourself if the &lt;em&gt;precision of terminology&lt;/em&gt; you want to encourage (understandably!) will actually help answer a &lt;em&gt;scientific question&lt;/em&gt;. In the context of what you are writing, will a reader make a significant mistake -- wind up with a wrong force field, or think her results have converged when they haven't -- if she mistakes &amp;quot;molecular dynamics&amp;quot; for &amp;quot;molecular modelling&amp;quot;? If yes, then you should be able to make a cogent argument for the distinction. If not, then you're distracting yourself and your readers unnecessarily.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-05-30T06:26:16.407" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9165" PostTypeId="1" CreationDate="2022-05-30T07:06:26.257" Score="5" ViewCount="102" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/711215/matrix-elements-langle-n-kxn-k-rangle-for-bloch-states%5D&quot;&gt;Cross posted at Physics.SE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe this is just elementary QM, but I'm getting awfully confused. The question is drawn from &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/1/8/007&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; on Wannier-Stark localization (but is self-contained).&lt;/p&gt;&#xA;&lt;p&gt;Let:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;|n,k\rangle = e^{ikx}u_{n,k}(x),\tag{1}&#xA;\end{equation}&lt;/span&gt;&#xA;be a Bloch state, where &lt;span class=&quot;math-container&quot;&gt;$u_{n,k}(x+a)=u_{n,k}(x)$&lt;/span&gt; is the periodic part. We wish to calculate the matrix element &lt;span class=&quot;math-container&quot;&gt;$\langle n,k|x|n',k'\rangle$&lt;/span&gt;, which the authors claim can be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\langle n,k|x|n',k'\rangle = i\delta_{n,n'}\delta_{k,k'}\tag{2}\frac{\partial}{\partial k} + i\delta_{k,k'}X_{n,n'},&#xA;\end{equation}&lt;/span&gt;&#xA;in which:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;X_{n,n'} = iN\int_0^ae^{i(k-k')x}u_{n,k}^*(x)\frac{\partial}{\partial k}u_{n',k'}(x) \;\mathrm{d}x.\tag{3}&#xA;\end{equation}&lt;/span&gt;&#xA;This latter term is physically the inter-band coupling. Note that I am not sure what &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is, as I can't see it defined in the paper. Also, the equation for &lt;span class=&quot;math-container&quot;&gt;$X_{n,n'}$&lt;/span&gt; is as written in the paper, with &lt;span class=&quot;math-container&quot;&gt;$\partial_k$&lt;/span&gt; acting on &lt;span class=&quot;math-container&quot;&gt;$u_{n',k'}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question&lt;/strong&gt;: show the above.&lt;/p&gt;&#xA;&lt;p&gt;I've tried writing &lt;span class=&quot;math-container&quot;&gt;$x=-i\partial_k e^{ikx}$&lt;/span&gt; and integrating by parts, but do not get their expression. I am also generally confused as to how a matrix element &lt;span class=&quot;math-container&quot;&gt;$\langle n,k|x|n',k'\rangle$&lt;/span&gt; (which should be a number...?) can be equal to a derivative &lt;span class=&quot;math-container&quot;&gt;$\partial_k$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5490" LastEditorUserId="5" LastEditDate="2022-11-05T00:05:44.600" LastActivityDate="2022-11-05T00:05:44.600" Title="Cross-post: Matrix elements &lt;n,k|x|n',k'&gt; for Bloch states" Tags="|band-structure|mathematical-modeling|quantum-mechanics|derivations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9166" PostTypeId="2" ParentId="9158" CreationDate="2022-05-30T09:00:15.517" Score="4" Body="&lt;p&gt;I disagree. Generally the term &amp;quot;molecular dynamics&amp;quot; (MD) is used of a particular kind of simulation, to wit the kind where you model the forces that act on atoms and then calculate their movement. To me, &amp;quot;molecular modeling&amp;quot; sounds like a less specific term. It could refer to e.g. calculating the electronic structure of a molecule (say with DFT) without modeling the movement of atoms.&lt;/p&gt;&#xA;&lt;p&gt;I'd say it's better to use MD because it's an established term even if it's not the most descriptive.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I might add that you can say e.g. &amp;quot;molecular dynamics simulation&amp;quot; if you want to make it extra clear that you are talking about modeling/simulation.&lt;/p&gt;&#xA;" OwnerUserId="5491" LastEditorUserId="5491" LastEditDate="2022-06-01T10:58:14.233" LastActivityDate="2022-06-01T10:58:14.233" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9167" PostTypeId="1" AcceptedAnswerId="9172" CreationDate="2022-05-30T11:58:25.967" Score="4" ViewCount="594" Body="&lt;p&gt;I use &lt;code&gt;grep&lt;/code&gt; to find the string &lt;code&gt;&amp;quot;Converged?&amp;quot;&lt;/code&gt; with the terminal in several folders to read the output from my gaussian calculations.&lt;/p&gt;&#xA;&lt;p&gt;My command is&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;grep -r -i -A4 Converged?&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I get as output is in minimal example this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;start_struc.log:         Item               Value     Threshold  Converged?&#xA;start_struc.log- Maximum Force            0.000022     0.000450     YES&#xA;start_struc.log- RMS     Force            0.000005     0.000300     YES&#xA;start_struc.log- Maximum Displacement     0.010813     0.001800     NO &#xA;start_struc.log- RMS     Displacement     0.002734     0.001200     NO &#xA;--&#xA;start_struc.log:         Item               Value     Threshold  Converged?&#xA;start_struc.log- Maximum Force            0.000001     0.000450     YES&#xA;start_struc.log- RMS     Force            0.000000     0.000300     YES&#xA;start_struc.log- Maximum Displacement     0.001210     0.001800     YES&#xA;start_struc.log- RMS     Displacement     0.000312     0.001200     YES&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I just want the last time grep finds &lt;code&gt;Converged?&lt;/code&gt; with the next four Lines.&#xA;I looked up different internet forums and the manual of grep but I think I did not find  a flag I can use. Because the problem is, I get up to 50 hits before and I don't want to print them out in terminal.&#xA;Has someone an idea or search for the convergence the same way?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="1680" LastActivityDate="2022-05-31T01:02:54.173" Title="Find with grep in terminal last hit in log file" Tags="|gaussian|programming|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9168" PostTypeId="1" CreationDate="2022-05-30T12:34:27.743" Score="4" ViewCount="101" Body="&lt;p&gt;I tried a three-step job file for gaussian. This is my input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=start_struc.chk&#xA;%mem=50GB&#xA;%nprocshared=8&#xA;#p opt=calcall ub3lyp/6-31g(2df,p) empiricaldispersion=gd3bj nosymm guess=always integral=grid=superfine test&#xA;&#xA;Titel&#xA;&#xA;Molecular Specification&#xA;&#xA;--Link1--&#xA;%oldchk=start_struc.chk&#xA;%chk=start_struc_stab.chk&#xA;%mem=20GB&#xA;%nprocshared=8&#xA;# stable=opt UHF/6-31g(2df,p) geom=check&#xA;&#xA;Titel &#xA;&#xA;Charge/Multi&#xA;&#xA;--Link1--&#xA;%oldchk=start_struc_stab.chk&#xA;%chk=start_struc_freq.chk&#xA;%mem=80GB&#xA;%nprocshared=8&#xA;&#xA;Title &#xA;&#xA;Charge/Multi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The calculation worked and I got an log file that says: &lt;code&gt;Normal termination of Gaussian 16 at&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;So my problem is that in the optimization I got convergence at the end of the calculation. But in the frequency calculation after the stability check, the structure does not converge anymore? Do I make a systematic mistake?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="1680" LastActivityDate="2022-05-30T12:34:27.743" Title="Optimization converged but frequency calculation does not" Tags="|density-functional-theory|gaussian|" AnswerCount="0" CommentCount="9" ClosedDate="2022-12-12T15:17:42.807" ContentLicense="CC BY-SA 4.0" />
  <row Id="9169" PostTypeId="1" AcceptedAnswerId="9192" CreationDate="2022-05-30T12:53:28.003" Score="4" ViewCount="275" Body="&lt;p&gt;We usually plot electronic bands with the help of high symmetry points of the irreducible zone of primitive cell of particular material. But if we want to plot bands with conventional cell, we have to map the high symmetry points from primitive cell to conventional cell.&#xA;so how can we map the high symmetry points from primitive cell to conventional cell ?? basically how can we transform the points ?&lt;/p&gt;&#xA;" OwnerUserId="5492" LastActivityDate="2022-06-03T08:12:24.077" Title="How to map high symmetry points from primitive cell to conventional cell?" Tags="|condensed-matter|physical-properties-of-materials|solid-state-physics|materials-design|materials-engineering|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9171" PostTypeId="1" CreationDate="2022-05-30T13:23:20.467" Score="1" ViewCount="253" Body="&lt;p&gt;I am trying to use the &lt;a href=&quot;http://www.cohp.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;lobster program&lt;/a&gt; to calculate COHP, according to the &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/jcc.24300&quot; rel=&quot;nofollow noreferrer&quot;&gt;explanation in the literature&lt;/a&gt;, it is better to add unoccupied atom orbitals into the basis set.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The initial step in projection is finding a suitable choice of local&#xA;auxiliary basis functions. For reasons of simple chemical&#xA;interpretation, LOBSTER employs minimal basis sets that nonetheless&#xA;carry the correct nodal behavior in the core region, which is&#xA;necessary to fit PAW wavefunctions. LOBSTER first came with contracted&#xA;primitive Slater-type orbitals (STOs) fitted to atomic functions,14 a&#xA;reasonable choice for post-processing bonding information. There are&#xA;also systems, however, where the bonding situation requires additional&#xA;basis functions which deviate from those of the corresponding free&#xA;atoms. In elemental beryllium, for example, its 2p levels are&#xA;unoccupied in the free atom. For bulk Be, however, the 2p levels do&#xA;get involved into bonding and define the metallic character, so the Be&#xA;basis set must also include 2p functions.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For example, here is an input file for lobster to analyze COHP between &lt;code&gt;Ni&lt;/code&gt; and &lt;code&gt;Fe&lt;/code&gt; elements, whose valence electrons are in &lt;code&gt;3d&lt;/code&gt; and &lt;code&gt;4s&lt;/code&gt; orbitals, but the input file also uses &lt;code&gt;4p&lt;/code&gt; orbitals.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COHPstartEnergy  -10&#xA;COHPendEnergy     6&#xA;usebasisset pbeVaspFit2015&#xA;basisfunctions Fe 3d 4s 4p&#xA;basisfunctions Ni 3d 4s 4p&#xA;&#xA;cohpbetween atom 1 and atom 2&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Could I also use &lt;code&gt;4d&lt;/code&gt;, &lt;code&gt;4f&lt;/code&gt; etc. for elements like &lt;code&gt;Ni&lt;/code&gt; and &lt;code&gt;Fe&lt;/code&gt;?&lt;/li&gt;&#xA;&lt;li&gt;How should I decide how many unoccupied atom orbitals I should add into the basis set?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-05-30T13:23:20.467" Title="how to choose a basis set when calculating COHP?" Tags="|vasp|plane-waves|" AnswerCount="0" CommentCount="1" ClosedDate="2022-06-01T16:21:00.353" ContentLicense="CC BY-SA 4.0" />
  <row Id="9172" PostTypeId="2" ParentId="9167" CreationDate="2022-05-30T13:24:54.800" Score="9" Body="&lt;p&gt;I think this requires &lt;a href=&quot;https://www.geeksforgeeks.org/piping-in-unix-or-linux/&quot; rel=&quot;noreferrer&quot;&gt;piping&lt;/a&gt;, see these &lt;a href=&quot;https://serverfault.com/q/197123&quot;&gt;ServerFault&lt;/a&gt; or &lt;a href=&quot;https://stackoverflow.com/q/24014194/7492468&quot;&gt;StackOverFlow&lt;/a&gt; questions. For a single file, the two main approaches would be using &lt;code&gt;tail&lt;/code&gt; or &lt;code&gt;tac&lt;/code&gt;. I tend to use the &lt;code&gt;tail&lt;/code&gt; approach most myself, as I find it easier to remember or to just slap onto the end of a preceding grep statement.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;grep -i -A4 Converged? file | tail&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;will print the last 10 lines from grep's output. To specify it further, make it print only the last 5 lines corresponding to the last entry:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;grep -i -A4 Converged? file | tail -n 5&lt;/code&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Alternatively, use &lt;code&gt;tac&lt;/code&gt; to &amp;quot;&lt;code&gt;cat&lt;/code&gt;&amp;quot; a file backwards, and then &lt;code&gt;grep -m 1&lt;/code&gt; to print only the first match:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;code&gt;tac file | grep -i -m 1 -B4 Converged? | tac&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Again, &lt;code&gt;tac&lt;/code&gt; outputs the file backwards so we need to use -B4 instead of -A4 to get the additional lines. The final pipe to &lt;code&gt;tac&lt;/code&gt; reverses the line order again, to match that in the file.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;To do this for many files, you can use a &lt;code&gt;for&lt;/code&gt; loop, either in a shell script or as a one-liner:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;code&gt;for a in files; do tac $a | grep -i -B4 -m 1 Converged? | tac; done&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;where you need to replace &amp;quot;files&amp;quot; by an appropriate path to the different files.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2022-05-30T13:35:29.467" LastActivityDate="2022-05-30T13:35:29.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9173" PostTypeId="1" AcceptedAnswerId="9186" CreationDate="2022-05-30T21:40:54.987" Score="2" ViewCount="560" Body="&lt;p&gt;I am trying to calculate elastic constant when strain is applied on a material.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://dalcorso.github.io/thermo_pw/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Thermo_pw&lt;/a&gt; has a command which says in the documentation&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For each strain, the code relaxes the ions to their equilibrium positions if frozen_ions=.FALSE. or keeps them in the strained positions if&#xA;frozen_ions=.TRUE.. Note that elastic constant calculations with frozen&#xA;_ions=.FALSE. might require smaller force convergence threshold than standard calculations.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What does this mean? What is the theory behind it? So, do I have to use &lt;code&gt;frozen_ions=.TRUE.&lt;/code&gt; for my strained structure calculation?&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="7" LastEditDate="2022-05-31T00:34:48.610" LastActivityDate="2022-06-01T15:48:06.743" Title="Calculating Elastic constant using thermo_pw: What does frozen_ions mean?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9174" PostTypeId="2" ParentId="9167" CreationDate="2022-05-31T01:02:54.173" Score="0" Body="&lt;p&gt;You could also use Ex.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ex file &amp;lt;&amp;lt;&amp;lt; '?Converged?,+4p'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or to print until the end of the file instead of just 4 lines,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ex file &amp;lt;&amp;lt;&amp;lt; '?Converged?,$p'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5494" LastActivityDate="2022-05-31T01:02:54.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9175" PostTypeId="2" ParentId="9134" CreationDate="2022-05-31T06:39:06.153" Score="3" Body="&lt;p&gt;You simply cannot go past Allen and Tildesley's &lt;a href=&quot;https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198803195.001.0001/oso-9780198803195&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computer Simulation of Liquids&lt;/a&gt; as a standard textbook on molecular dynamics. Here is a particularly illuminating diagram:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RZmKt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RZmKt.png&quot; alt=&quot;The connection between experiment, theory and simulation, explained in a flowchart which is described in the following text.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As the diagram says: (italics for nouns in rounded boxes, bold for verbs in cornered boxes)&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;When you have some &lt;em&gt;real liquids&lt;/em&gt;, you can &lt;strong&gt;perform experiments&lt;/strong&gt; to obtain some &lt;em&gt;experimental results&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;li&gt;You can also &lt;strong&gt;make models&lt;/strong&gt; of your &lt;em&gt;real liquids&lt;/em&gt; to obtain &lt;em&gt;model liquids&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;li&gt;When you have some &lt;em&gt;model liquids&lt;/em&gt;, you can &lt;strong&gt;carry out computer simulations&lt;/strong&gt; to obtain &lt;em&gt;results for the model liquid&lt;/em&gt;. You must &lt;strong&gt;compare&lt;/strong&gt; these results with the &lt;em&gt;experimental results&lt;/em&gt; as a &lt;em&gt;test of your models&lt;/em&gt;!&lt;/li&gt;&#xA;&lt;li&gt;And when you have some &lt;em&gt;model liquids&lt;/em&gt;, you can also &lt;strong&gt;construct approximate theories&lt;/strong&gt; to obtain &lt;em&gt;theoretical predictions&lt;/em&gt;. You must &lt;strong&gt;compare these predictions&lt;/strong&gt; with the &lt;em&gt;model results&lt;/em&gt; as a &lt;em&gt;test of your theories&lt;/em&gt;!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;So, as a protein-specific example, real proteins are experimentally observed to have one stable structure. The theory for this is &lt;a href=&quot;https://en.wikipedia.org/wiki/Anfinsen%27s_dogma&quot; rel=&quot;nofollow noreferrer&quot;&gt;Anfinsen's dogma&lt;/a&gt;. A &lt;em&gt;computer model&lt;/em&gt; for a protein would be to describe the protein (and the water and ions around it) as a bunch of particles, each corresponding to an atom. (It would be a computer model because it's impractical to make any predictions from it without a computer.)&lt;/p&gt;&#xA;&lt;p&gt;Two essential ingredients for the model would be the &lt;em&gt;dynamics integration&lt;/em&gt; of the particles -- usually Newtonian dynamics with thermostatting, the latter of which is not trivial, and the algorithm by which you evolve the equations with a finite timestep -- and the &lt;em&gt;force fields&lt;/em&gt; that say what forces go into the Newtonian dynamics, as a function of the particles' positions and other input.&lt;/p&gt;&#xA;&lt;p&gt;From a bunch of (statistically independent) initial positions, we would then run &lt;em&gt;simulations&lt;/em&gt; of the model and see what final states we get. A realistic protein force field will predict that the protein folds up into one well-defined state. If we didn't see that in our simulations, we might have a bad model, but we might also have not run our simulations for long enough to get good statistics.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As such, ideally, well-run simulations of an informative model would give us valuable insight into a real-world phenomenon (in the example, helping us understand the molecular mechanisms behind protein folding). But well-run simulations will not help us if our model is not informative (the bane of all computational chemists!), for example if it is too simple, or biased, or too complex to make useful inferences. Or we might have an informative model, but poorly-run simulations will not help us (if the program has bugs, or our computers are not fast enough to run large enough simulations).&lt;/p&gt;&#xA;&lt;p&gt;Or, worse still, you might have a poorly-run simulation of an uninformative model -- in which case you will not learn anything about the real world. (Even if the work gets published, which is sadly still quite likely!)&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-05-31T06:39:06.153" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9176" PostTypeId="1" CreationDate="2022-05-31T09:17:12.307" Score="4" ViewCount="2240" Body="&lt;p&gt;I try to optimize and compute frequencies for the system built up from C, O, H, and Co atoms in the following functionals: &lt;strong&gt;B2PLYP, B2PLYP-D3, B3LYP, B3LYP-D3, BLYP, BLYP-D3, DSD-PBEP86, PBE, PBE-D3, WB97X-D3&lt;/strong&gt;.&#xA;The basis set I use is &lt;strong&gt;aug-cc-pVTZ aug-cc-pVTZ/C def2/J&lt;/strong&gt; with &lt;strong&gt;SDD&lt;/strong&gt; on Co.&#xA;The input is common and looks like that:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! BLYP D3ZERO aug-cc-pVTZ aug-cc-pVTZ/C def2/J verytightopt freq&#xA;%basis&#xA;    newECP Co &amp;quot;SDD&amp;quot; end&#xA;end&#xA;%geom&#xA;%MAXCORE 3428&#xA;%PAL NPROCS 28 END&#xA;* xyzfile 1 1 BLYP-D3.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In each case I got an error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Nuc. rep. gradient       (SHARK) ... done (  0.0 sec)&#xA;HCore &amp;amp; Overlap gradient (SHARK) ... done ( 32.0 sec)&#xA;ECP gradient             (SHARK) ... done ( 47.0 sec)&#xA;RI-J gradient            (SHARK) ... &#xA;ORCA finished by error termination in SCF gradient&#xA;Calling Command: mpirun -np 28  /home/users/john/orca503/orca_5_0_3_linux_x86-64_shared_openmpi411/orca_scfgrad_mpi BLYP-D3.scfgrad.inp BLYP-D3 &#xA;[file orca_tools/qcmsg.cpp, line 465]: &#xA;  .... aborting the run&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I use single node, which has 2 processors, each 14 cores (2x14) and up to 128GB. The queue system is SLURM and hence I specify there:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --nodes=1&#xA;#SBATCH --ntasks=28&#xA;#SBATCH --ntasks-per-node=28&#xA;#SBATCH --cpus-per-task=1&#xA;#SBATCH --mem=128000MB&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8524" OwnerDisplayName="user1247" LastEditorUserId="5" LastEditorDisplayName="user1247" LastEditDate="2022-12-10T16:40:44.647" LastActivityDate="2022-12-10T16:40:44.647" Title="ORCA finished by error termination in SCF gradient" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|orca|" AnswerCount="0" CommentCount="16" ClosedDate="2022-12-11T13:44:13.480" ContentLicense="CC BY-SA 4.0" />
  <row Id="9177" PostTypeId="2" ParentId="8871" CreationDate="2022-05-31T10:52:53.713" Score="2" Body="&lt;p&gt;If you do a noncollinear calculation, you can then get the spin projections along the x, y and z axes by utilizing the post-processing executable &lt;code&gt;pp.x&lt;/code&gt; and choosing &lt;code&gt;plot_num=7&lt;/code&gt; and &lt;code&gt;spin_component=1/2/3&lt;/code&gt;.&#xA;You can see other options in the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PP.html#idm22&quot; rel=&quot;nofollow noreferrer&quot;&gt;input documentation&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-05-31T10:52:53.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9178" PostTypeId="1" AcceptedAnswerId="9179" CreationDate="2022-05-31T14:41:52.320" Score="5" ViewCount="272" Body="&lt;p&gt;I'm running an IRCs calculation on the TS (transition state) in Gaussian, and I see this table at the end of the calculation with the following header:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; --------------------------------------------------------------------------&#xA;    Summary of reaction path following&#xA; --------------------------------------------------------------------------&#xA;                        Energy    RxCoord&#xA;   1                   -0.03023  -3.43818&#xA;   2                   -0.02737  -3.09539&#xA;   3                   -0.02379  -2.75177&#xA;   4                   -0.01970  -2.40792&#xA;   5                   -0.01541  -2.06395&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm wondering how Gaussian calculates that &lt;code&gt;RxCoord&lt;/code&gt; parameter. I was searching on the internet but I haven't found anything.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="5" LastEditDate="2022-05-31T15:09:51.397" LastActivityDate="2022-05-31T19:36:11.783" Title="IRC (intrinsic reaction coordinate) &quot;RxCoord&quot; calculation in Gaussian" Tags="|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9179" PostTypeId="2" ParentId="9178" CreationDate="2022-05-31T19:36:11.783" Score="3" Body="&lt;p&gt;From reference [1]:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The reaction coordinate is a composite variable spanning all of the degrees of freedom of the potential energy surface.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And from the Gaussian &lt;a href=&quot;https://gaussian.com/irc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;site&lt;/a&gt; for IRC documentation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;IRC&lt;/strong&gt;&lt;br /&gt;&#xA;This calculation type keyword requests that a reaction path be&#xA;followed by integrating the intrinsic reaction coordinate [2,3].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;From reference [2], the internal coordinates &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; are defined from the Cartesian coordinates as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vlBpA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vlBpA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Together with the conditions in equation (6) that assures a zero total momentum and zero total angular momentum motion.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;br /&gt;&#xA;[1] JamesB. Foresman, Aleen Frisch. Exploring Chemistry With Electronic Structure Methods: A Guide to Using Gaussian. 2nd edition.&lt;br /&gt;&#xA;[2] K. Fukui, “The path of chemical-reactions – The IRC approach,” Acc. Chem. Res., 14 (1981) 363-68. DOI: 10.1021/ar00072a001&lt;br /&gt;&#xA;[3] H. P. Hratchian and H. B. Schlegel, in Theory and Applications of Computational Chemistry: The First 40 Years, Ed. C. E. Dykstra, G. Frenking, K. S. Kim, and G. Scuseria (Elsevier, Amsterdam, 2005) 195-249.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-05-31T19:36:11.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9180" PostTypeId="1" CreationDate="2022-05-31T20:15:13.290" Score="8" ViewCount="742" Body="&lt;p&gt;Let's say we have a decomposition reaction&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\tag{1}A \rightarrow B + C$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;how would I go about calculating the Enthalpy of this chemical reaction using VASP. I am gonna describe what I am thinking below please let me know what you guys think. We are actually trying to see the thermodynamic stability of A. So we have the structure(cif file) for A in which we want to see the stability, B and C are compounds which have been experimentally synthesized so we will use the most common structures.&lt;/p&gt;&#xA;&lt;p&gt;We start by doing geometrical optimization on all the compounds and then running an SCF calculation using the converged system(POSCAR). Now the ground state energy found from this will be used,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta H = H_{products} - H_{reactants}\tag{2}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and so&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta H = H_{B} + H_{C} - H_{A}\tag{3}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$H_i$&lt;/span&gt; is the ground state energy obtained from the SCF calculation for i.&lt;/p&gt;&#xA;&lt;p&gt;Now as VASP does calculation with &lt;span class=&quot;math-container&quot;&gt;$T = 0$&lt;/span&gt; and,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\tag{4}\Delta G = \Delta H - T \Delta S$&lt;/span&gt; we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\tag{5}\Delta H = \Delta G$&lt;/span&gt; so our enthalpy can be used to predict the stability.&lt;/p&gt;&#xA;&lt;p&gt;Let me know if I am going wrong somewhere or not. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="838" LastEditDate="2023-02-08T11:12:24.410" LastActivityDate="2023-03-16T16:01:06.303" Title="Calculating enthalpy of a chemical reaction using DFT" Tags="|free-energy|reaction-mechanism|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9181" PostTypeId="1" CreationDate="2022-06-01T02:15:52.810" Score="2" ViewCount="54" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.481505&quot; rel=&quot;nofollow noreferrer&quot;&gt;A five-site model for liquid water and the reproduction of the density anomaly by rigid, nonpolarizable potential functions&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;What does it mean by a &amp;quot;&lt;strong&gt;site&lt;/strong&gt;&amp;quot; in the case of a coarse-grained (CG) model in the above article?&lt;/p&gt;&#xA;&lt;p&gt;Plz, describe it in layman's terms.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="181" LastEditDate="2022-06-01T11:05:51.020" LastActivityDate="2022-06-01T17:34:11.297" Title="What does it mean by a &quot;site&quot; in the case of a CG model?" Tags="|molecular-modeling|atomistic-simulation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9182" PostTypeId="1" AcceptedAnswerId="10374" CreationDate="2022-06-01T06:11:46.150" Score="2" ViewCount="291" Body="&lt;p&gt;I am trying to study surface reconstructions of metal oxides using Quantum ESPRESSO. For this, I am creating slabs using python tools: ASE, Pymatgen, and catgen. However, I am unable to terminate the bottom (or the top) of the slabs using hydrogens using these tools.&#xA;Can someone guide how this can be done using these codes or suggest some alternate free tools to passivate the dangling bonds on the surfaces with hydrogen atoms?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2023-02-06T21:18:26.573" LastActivityDate="2023-02-06T21:18:26.573" Title="How to terminate a surface with hydrogens" Tags="|quantum-espresso|surfaces|atomic-simulation-environment|pymatgen|surface-passivation|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9185" PostTypeId="1" CreationDate="2022-06-01T15:28:24.243" Score="5" ViewCount="427" Body="&lt;p&gt;I have a set of data (heat flow) values in x, y and z directions for which I have to calculate the auto-correlation function to get the thermal conductivity. I have written a small Fortran90 code but something is wrong because I get irrelevant results. I am not sure whether this a problem of units or a problem of coding the algorithm.&lt;/p&gt;&#xA;&lt;p&gt;The data look like this (I am adding comments):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;10000      ! number of data&#xA;3.0000     ! time step (dt)&#xA;1281.4610  ! cell volume (V)&#xA;2000.0     ! temperature (T)&#xA;64         ! number of atoms&#xA;9.746633E-03 -1.185578E-02 -2.107013E-02&#xA;3.909507E-02 -5.904692E-05 -3.044154E-03&#xA;7.439500E-02 2.270370E-02 3.536638E-03&#xA;1.027890E-01 3.875051E-02 1.377188E-02&#xA;1.218158E-01 4.606921E-02 2.570092E-02&#xA;1.306354E-01 4.482340E-02 3.692641E-02&#xA;...    !   10000 such lines&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The function to calculate is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{1}{3Vk_BT^{3/2}}\int_0^{+\infty}{\langle q(0)q(t)\rangle dt}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Fortran code I wrote is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;program kappa&#xA;&#xA;    implicit none&#xA;    &#xA;    integer, parameter :: dp=selected_real_kind(15,307)&#xA;    &#xA;    real(dp), parameter :: kB=1.380649d-23&#xA;    real(dp), parameter :: eV2J = 1.602d-19&#xA;    real(dp), parameter :: ang2m = 1.0d-10&#xA;    real(dp), parameter :: fs2s = 1.0d-15&#xA;    &#xA;    real(dp), dimension(:,:), allocatable :: q ! heat flow&#xA;    real(dp), dimension(3) :: q_0, q_t, int_q ! reference heat flow, integrated heat flow at t, and integrated heat flow&#xA;    real(dp) :: dt ! time step&#xA;    real(dp) :: V, T ! Volume and temperature&#xA;    integer :: count_q ! number of steps (corresponds to number of line of HEAT)&#xA;    integer :: natoms&#xA;    integer :: ios, i, j&#xA;    &#xA;    &#xA;    int_q(:) = 0.0_dp&#xA;    &#xA;    &#xA;    read( 10, * ) count_q&#xA;    allocate(q(count_q,3))&#xA;    &#xA;    read( 10, * ) dt&#xA;    read( 10, * ) V&#xA;    read( 10, * ) T&#xA;    read( 10, * ) natoms&#xA;    &#xA;    open(20, file='thermal_cond.dat', status='unknown', action='write')&#xA;    &#xA;    &#xA;    ! store all the heat flow values in q(:,:)&#xA;    lp1: do i = 1, count_q&#xA;        read( 10, *, iostat=ios ) q(i,:) &#xA;        if (ios &amp;lt; 0) exit lp1 ! unexpected end of file: this should not happen&#xA;    end do lp1&#xA;    &#xA;    ! for each q_0(:) up to t/2 (t=total time of the simulation) &#xA;    ! calculate the autocorrelation function &amp;lt;q(0)q(t)&amp;gt;&#xA;    do i = 1, int(count_q / 2)&#xA;        q_0(:) = q(i,:) ! shift the reference heat flow by one step&#xA;        q_t(:) = 0.0_dp ! initialize the value of &amp;lt;q(0)q(t)&amp;gt;&#xA;        &#xA;        do j = i + 1, int(count_q / 2) + (i - 1) ! shift the right end of the interval to have it constant (length of count_q/2)&#xA;            q_t(:) = q_t(:) + q(j,:) * q_0(:)&#xA;        end do&#xA;&#xA;        q_t(:) = q_t(:) * eV2J**2 / ( int(count_q / 2) * natoms * 3.0 * V * ang2m**3 * kB * T**2 ) * dt * fs2s&#xA;        int_q(:) = int_q(:) + q_t(:) &#xA;&#xA;        write(20, '(4F15.9)') (i - 1) * dt, q_t(:)&#xA;&#xA;    end do&#xA;    &#xA;    &#xA;    &#xA;    &#xA;    write(6,*) 'Kappa(x) = ', int_q(1)&#xA;    write(6,*) 'Kappa(y) = ', int_q(2)&#xA;    write(6,*) 'Kappa(z) = ', int_q(3)&#xA;    write(6,*) '&amp;lt; Kappa &amp;gt; = ', sqrt(int_q(1)**2 + int_q(2)**2 + int_q(3)**2)&#xA;    &#xA;    close(20)&#xA;&#xA;&#xA;end program kappa_ml&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could anyone tell me if something is wrong in the program?&#xA;Thank you&lt;/p&gt;&#xA;" OwnerUserId="5200" LastEditorUserId="7" LastEditDate="2022-06-01T16:19:17.583" LastActivityDate="2022-06-07T12:35:39.983" Title="Programming auto-correlation function calculation" Tags="|correlation-functions|fortran|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9186" PostTypeId="2" ParentId="9173" CreationDate="2022-06-01T15:48:06.743" Score="3" Body="&lt;p&gt;At the ground state, the atomic positions and cell vectors are such that the energy is minimised, and the atomic forces and cell stresses are zero.&lt;/p&gt;&#xA;&lt;p&gt;Straining a material means perturbing the lattice, so that it is no longer at the ground state. The stress on the cell will no longer be zero; what about the atomic forces? The forces &lt;em&gt;might&lt;/em&gt; be zero, or they might not. If the forces are non-zero, should we:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Keep the atoms where they are, meaning the same fractional positions (e.g. Wykoff sites); or&lt;/li&gt;&#xA;&lt;li&gt;Move the atoms to the new optimised locations, where the atomic forces are zero&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In QE this choice is made by setting &lt;code&gt;frozen_ions&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Your choice here can affect the computed properties significantly, so it may require some careful thought. You might also want to consider what situation or experiment you are really intending to model, for example if the strain is caused by a rapidly-changing external field of some kind, the atoms may not have time to respond to the strain.&lt;/p&gt;&#xA;&lt;p&gt;Also be aware that even when the atomic forces are zero, they may be zero simply because atoms are on high-symmetry sites. It can be necessary to perturb the atoms slightly, in order to have non-zero forces and allow them to relax to their new locations (they may, of course, simply relax back to the symmetry sites!).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-06-01T15:48:06.743" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9187" PostTypeId="2" ParentId="9181" CreationDate="2022-06-01T17:34:11.297" Score="1" Body="&lt;p&gt;As the comments have already noted, a site in an atomistic model is the location in space at which interactions occur. The most obvious thing to do is to place all interaction sites at the atomic centers. This is exactly the case for TIP3P. That is, there are fixed charges placed on the oxygen and hydrogen atoms.&lt;/p&gt;&#xA;&lt;p&gt;TIP3P did not do particularly well at modeling many properties of water, so TIP4P added another interaction site, which is slightly displaced from the oxygen atom along the HOH bisector. So, there are the three atomic interaction sites plus a fourth one which is usually called the M-site. The idea is that this fourth one is closer to the center of charge and hence might better capture the multipolar interactions. Because one is interested in the forces on a particular atom, one must then redistribute the forces at this M-site onto the atoms.&lt;/p&gt;&#xA;&lt;p&gt;TIP5P just adds another M-site. From what I've heard, TIP5P is actually not much of an improvement at all over TIP4P and is more expensive, so TIP4P is usually preferred over TIP5P.&lt;/p&gt;&#xA;&lt;p&gt;As an aside, the same principle can be used for polarizable force fields. For instance, many polarizable force fields for water place the polarizable centers off of the actual oxygen atom.&lt;/p&gt;&#xA;&lt;p&gt;For the most part, I think only water models go to the trouble of placing interaction sites off of the actual atoms. With larger molecules, it would be rather tedious and possibly unnecessary to go to this trouble.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-06-01T17:34:11.297" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9188" PostTypeId="2" ParentId="8871" CreationDate="2022-06-02T14:43:29.117" Score="1" Body="&lt;p&gt;I noticed &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2022-March/048904.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;the following answer&lt;/a&gt; on QE mail list from &lt;a href=&quot;https://scholar.google.ru/citations?user=bmIgwLYAAAAJ&amp;amp;hl=en&quot; rel=&quot;nofollow noreferrer&quot;&gt;Thomas Brumme&lt;/a&gt;, which is inconsistent with the answer suggested by Maxim-s:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Dear Luiz,&lt;/p&gt;&#xA;&lt;p&gt;the correct tool you search is bands.x - if you look at the&#xA;description of it, you will find the key word&lt;/p&gt;&#xA;&lt;p&gt;lsigma(i), i=1,3 which does the job. Usually, bands.x is used for&#xA;paths along high symmetry lines in the BZ but you can also provide a&#xA;full MP grid if you want to plot the spin texture in the whole BZ. I&#xA;actually did this for a manuscript which is in the&#xA;still-to-be-finalized stage since ages...&lt;/p&gt;&#xA;&lt;p&gt;Kind regards&lt;/p&gt;&#xA;&lt;p&gt;Thomas&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5128" LastEditorUserId="7" LastEditDate="2022-06-02T18:20:42.817" LastActivityDate="2022-06-02T18:20:42.817" CommentCount="4" CommunityOwnedDate="2022-06-02T18:18:22.617" ContentLicense="CC BY-SA 4.0" />
  <row Id="9189" PostTypeId="2" ParentId="8423" CreationDate="2022-06-02T15:36:17.003" Score="1" Body="&lt;p&gt;The OLCAO program can calculate XANES and it is open source.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-8984/21/10/104202&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://iopscience.iop.org/article/10.1088/0953-8984/21/10/104202&lt;/a&gt;&#xA;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0921509306000189&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/abs/pii/S0921509306000189&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/UMKC-CPG/olcao&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/UMKC-CPG/olcao&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5504" LastActivityDate="2022-06-02T15:36:17.003" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9190" PostTypeId="2" ParentId="8895" CreationDate="2022-06-03T04:20:27.047" Score="1" Body="&lt;p&gt;A quick Google search led me to a very recent(2019) open-access article, &lt;a href=&quot;https://www.nature.com/articles/s41467-019-12467-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;readable here&lt;/a&gt;, that such a series/sequence does exist. Again, my being a mathematics student, I could understand the basic idea of the article- one can pick a set of some small molecules with some desired property, calculate the pair ((ab initio density, exact functional)) for each molecule, and use machine learning techniques to extrapolate the pairs into an approximate functional that is intended to be used in any molecule, of any size, posessing the aforementioned property.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-06-03T04:32:56.153" LastActivityDate="2022-06-03T04:32:56.153" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9191" PostTypeId="2" ParentId="6141" CreationDate="2022-06-03T07:50:10.267" Score="5" Body="&lt;p&gt;&lt;strong&gt;Background.&lt;/strong&gt; Let &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{p_1},\mathbf{a}_{p_2},\mathbf{a}_{p_3})$&lt;/span&gt; be your primitive cell lattice vectors, and let &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{s_1},\mathbf{a}_{s_2},\mathbf{a}_{s_3})$&lt;/span&gt; be your supercell lattice vectors. We can then define a supercell matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}$&lt;/span&gt; relating the two as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{1}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{s}_1}\\&#xA;\mathbf{a}_{\text{s}_2}\\&#xA;\mathbf{a}_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11}&amp;amp;S_{12}&amp;amp;S_{13}\\&#xA;S_{21}&amp;amp;S_{22}&amp;amp;S_{23}\\&#xA;S_{31}&amp;amp;S_{32}&amp;amp;S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{p}_1}\\&#xA;\mathbf{a}_{\text{p}_2}\\&#xA;\mathbf{a}_{\text{p}_3}&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&#xA;Note that &lt;span class=&quot;math-container&quot;&gt;$S_{ij}\in\mathbb{Z}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The reciprocal primitive lattice has basis vectors:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{2}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{\text{p}_1}\\&#xA;\mathbf{b}_{\text{p}_2}\\&#xA;\mathbf{b}_{\text{p}_3}&#xA;\end{pmatrix}&#xA;=2\pi&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{p}_1}\\&#xA;\mathbf{a}_{\text{p}_2}\\&#xA;\mathbf{a}_{\text{p}_3}&#xA;\end{pmatrix}^{-\text{T}},&#xA;\end{equation}&lt;/span&gt;&#xA;while the reciprocal superlattice has basis vectors:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}\tag{3}&#xA;\mathbf{b}_{\text{s}_1}\\&#xA;\mathbf{b}_{\text{s}_2}\\&#xA;\mathbf{b}_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;\bar{S}_{11}&amp;amp;\bar{S}_{12}&amp;amp;\bar{S}_{13}\\&#xA;\bar{S}_{21}&amp;amp;\bar{S}_{22}&amp;amp;\bar{S}_{23}\\&#xA;\bar{S}_{31}&amp;amp;\bar{S}_{32}&amp;amp;\bar{S}_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{\text{p}_1}\\&#xA;\mathbf{b}_{\text{p}_2}\\&#xA;\mathbf{b}_{\text{p}_3}&#xA;\end{pmatrix},&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\bar{S}_{ij}=(S^{-1})_{ji}$&lt;/span&gt;. A &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; point can be written in fractional coordinates in terms of either the reciprocal primitive or reciprocal supercell basis vectors, and these two options are related by:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{4}&#xA;\begin{pmatrix}&#xA;k_{\text{s}_1}\\&#xA;k_{\text{s}_2}\\&#xA;k_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11}&amp;amp;S_{12}&amp;amp;S_{13}\\&#xA;S_{21}&amp;amp;S_{22}&amp;amp;S_{23}\\&#xA;S_{31}&amp;amp;S_{32}&amp;amp;S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;k_{\text{p}_1}\\&#xA;k_{\text{p}_2}\\&#xA;k_{\text{p}_3}&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Your case.&lt;/strong&gt; The first step is always to determine what the supercell matrix is. In your case, you can easily confirm that:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}\tag{5}&#xA;\mathbf{S}=&#xA;\begin{pmatrix}&#xA;1&amp;amp;1&amp;amp;0\\&#xA;-1&amp;amp;1&amp;amp;0\\&#xA;0&amp;amp;0&amp;amp;1&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&#xA;It then follows that, if &lt;span class=&quot;math-container&quot;&gt;$(k_{\text{p}_1},k_{\text{p}_2},k_{\text{p}_3})=(\frac{1}{2},0,0)$&lt;/span&gt;, we get:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;k_{\text{s}_1}\\&#xA;k_{\text{s}_2}\\&#xA;k_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;1&amp;amp;1&amp;amp;0\\&#xA;-1&amp;amp;1&amp;amp;0\\&#xA;0&amp;amp;0&amp;amp;1&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\frac{1}{2}\\&#xA;0\\&#xA;0&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;\frac{1}{2}\\&#xA;-\frac{1}{2}\\&#xA;0&#xA;\end{pmatrix}&#xA;\,.\tag{6}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="792" LastEditorUserId="5" LastEditDate="2023-03-28T21:34:14.910" LastActivityDate="2023-03-28T21:34:14.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9192" PostTypeId="2" ParentId="9169" CreationDate="2022-06-03T08:12:24.077" Score="4" Body="&lt;p&gt;&lt;strong&gt;Note.&lt;/strong&gt; This answer is adapted from an answer to a related question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6141/translating-fractional-coordinates-resulting-from-conventional-cell-and-primitiv&quot;&gt;Translating fractional coordinates resulting from conventional cell and primitive cell&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{p_1},\mathbf{a}_{p_2},\mathbf{a}_{p_3})$&lt;/span&gt; be your primitive cell lattice vectors, and let &lt;span class=&quot;math-container&quot;&gt;$(\mathbf{a}_{s_1},\mathbf{a}_{s_2},\mathbf{a}_{s_3})$&lt;/span&gt; be your supercell lattice vectors. The key ingredient you need to answer your question is the supercell matrix &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}$&lt;/span&gt; relating the two as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{s}_1}\\&#xA;\mathbf{a}_{\text{s}_2}\\&#xA;\mathbf{a}_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11}&amp;amp;S_{12}&amp;amp;S_{13}\\&#xA;S_{21}&amp;amp;S_{22}&amp;amp;S_{23}\\&#xA;S_{31}&amp;amp;S_{32}&amp;amp;S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{p}_1}\\&#xA;\mathbf{a}_{\text{p}_2}\\&#xA;\mathbf{a}_{\text{p}_3}&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&#xA;Note that &lt;span class=&quot;math-container&quot;&gt;$S_{ij}\in\mathbb{Z}$&lt;/span&gt;, and the size of the supercell is given by the determinant of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The reciprocal primitive lattice has basis vectors:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{\text{p}_1}\\&#xA;\mathbf{b}_{\text{p}_2}\\&#xA;\mathbf{b}_{\text{p}_3}&#xA;\end{pmatrix}&#xA;=2\pi&#xA;\begin{pmatrix}&#xA;\mathbf{a}_{\text{p}_1}\\&#xA;\mathbf{a}_{\text{p}_2}\\&#xA;\mathbf{a}_{\text{p}_3}&#xA;\end{pmatrix}^{-\text{T}},&#xA;\end{equation}&lt;/span&gt;&#xA;and we can obtain the basis vectors of the reciprocal superlattice as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{\text{s}_1}\\&#xA;\mathbf{b}_{\text{s}_2}\\&#xA;\mathbf{b}_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;\bar{S}_{11}&amp;amp;\bar{S}_{12}&amp;amp;\bar{S}_{13}\\&#xA;\bar{S}_{21}&amp;amp;\bar{S}_{22}&amp;amp;\bar{S}_{23}\\&#xA;\bar{S}_{31}&amp;amp;\bar{S}_{32}&amp;amp;\bar{S}_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\mathbf{b}_{\text{p}_1}\\&#xA;\mathbf{b}_{\text{p}_2}\\&#xA;\mathbf{b}_{\text{p}_3}&#xA;\end{pmatrix},&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\bar{S}_{ij}=(S^{-1})_{ji}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Any &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; point, for example one corresponding to a high-symmetry point in the irreducible Brillouin zone, can be written in fractional coordinates in terms of either the reciprocal primitive basis vectors, &lt;span class=&quot;math-container&quot;&gt;$(k_{\text{p}_1},k_{\text{p}_2},k_{\text{p}_3})$&lt;/span&gt;, or in terms of the reciprocal supercell basis vectors, &lt;span class=&quot;math-container&quot;&gt;$(k_{\text{s}_1},k_{\text{s}_2},k_{\text{s}_3})$&lt;/span&gt;. You can relate the two with:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;k_{\text{s}_1}\\&#xA;k_{\text{s}_2}\\&#xA;k_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;S_{11}&amp;amp;S_{12}&amp;amp;S_{13}\\&#xA;S_{21}&amp;amp;S_{22}&amp;amp;S_{23}\\&#xA;S_{31}&amp;amp;S_{32}&amp;amp;S_{33}&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;k_{\text{p}_1}\\&#xA;k_{\text{p}_2}\\&#xA;k_{\text{p}_3}&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example.&lt;/strong&gt; Imagine you have an orthogonal primitive cell, and let the supercell be simply twice as large along the first direction compared to the primitive cell. In this example:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\mathbf{S}=&#xA;\begin{pmatrix}&#xA;2&amp;amp;0&amp;amp;0\\&#xA;0&amp;amp;1&amp;amp;0\\&#xA;0&amp;amp;0&amp;amp;1&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&#xA;Now imagine that you consider a &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point at the boundary of the irreducible Brillouin zone of the primitive cell, such that &lt;span class=&quot;math-container&quot;&gt;$(k_{\text{p}_1},k_{\text{p}_2},k_{\text{p}_3})=(\frac{1}{2},0,0)$&lt;/span&gt;. The same point in terms of the reciprocal supercell basis vectors becomes:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\begin{pmatrix}&#xA;k_{\text{s}_1}\\&#xA;k_{\text{s}_2}\\&#xA;k_{\text{s}_3}&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;2&amp;amp;0&amp;amp;0\\&#xA;0&amp;amp;1&amp;amp;0\\&#xA;0&amp;amp;0&amp;amp;1&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;\frac{1}{2}\\&#xA;0\\&#xA;0&#xA;\end{pmatrix}&#xA;=&#xA;\begin{pmatrix}&#xA;1\\&#xA;0\\&#xA;0&#xA;\end{pmatrix}.&#xA;\end{equation}&lt;/span&gt;&#xA;Conceptually, as we have doubled the size of the cell in real space along the first direction, the size of the supercell in reciprocal space halves along the same direction. Thus we need to go twice as far to get to the same point in reciprocal space.&lt;/p&gt;&#xA;&lt;p&gt;As an additional comment, note that when you plot a band structure in a supercell, you will get band folding. In the example above where we double the size of the primitive cell, you will get twice as many bands at every &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; point.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-06-03T08:12:24.077" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9193" PostTypeId="1" CreationDate="2022-06-03T12:10:40.303" Score="5" ViewCount="93" Body="&lt;p&gt;I would like to do a phonon band-resolved harmonic sampling, following the recipes from the paper by West and Estreicher (&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.96.115504&quot; rel=&quot;nofollow noreferrer&quot;&gt;harmonic sampling&lt;/a&gt;). In fact, the method presented in the paper is already implemented in some codes devoted to the lattice dynamics (TDEP, fhi-vibes) at finite temperature.&lt;/p&gt;&#xA;&lt;p&gt;The methodology is described in details in &lt;a href=&quot;https://ollehellman.github.io/program/canonical_configuration.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TDEP manual&lt;/a&gt;. Thus, I would just point to the equations (2)-(6) in the mentioned manual.&lt;/p&gt;&#xA;&lt;p&gt;In this approach eigenvectors and eigenvalues of the dynamical matrix computed at the Gamma-point are used. In other words, we got data from the commensurate q-points.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I would like to do displacements using particular phonon branch. Which means that I should take only those eigenvectors and eigenstates of the dynamical matrix, which are related to the same phonon branch. Consequently, is there anyone who knows a method to assign phonon branch label to the specific eigenvector, eigenvalue? Any hints on how to do that are highly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Since I already spend some time trying to figure it out on my own I would share what I have found at the moment. First of all, I looked if phonopy has anything related to this problem. It turned out that in phonopy during the plotting of the phonon dispersion there is a function, which estimates which q-points to connect (estimate_band_connection in the &lt;a href=&quot;https://github.com/phonopy/phonopy/blob/develop/phonopy/phonon/band_structure.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;phonopy/phonon&lt;/a&gt;)  and it works simply based on the scalar product between different eigenvectors at neighboring qpoints. I am not sure that this method is completely reliable, i.e. what do to with band-crossing (use symmetry representation of phonons of this branches?). In addition to that I have found out this paper (&lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2515-7639/ab2b7c&quot; rel=&quot;nofollow noreferrer&quot;&gt;How to resolve a phonon-associated property into&#xA;contributions of basic phonon modes&lt;/a&gt;), but this methodology seems to be similar to the one used in Phonopy and I am also not sure if this is what I need.&lt;/p&gt;&#xA;&lt;p&gt;Sincerely,&#xA;Nikita Rybin PhD student at the FHI, Berlin&lt;/p&gt;&#xA;" OwnerUserId="5508" LastEditorUserId="5" LastEditDate="2023-02-06T21:20:03.140" LastActivityDate="2023-02-06T21:20:03.140" Title="Phonon branch-resolved harmonic sampling" Tags="|phonons|phonopy|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9194" PostTypeId="2" ParentId="315" CreationDate="2022-06-03T12:21:41.623" Score="2" Body="&lt;p&gt;I think one could try to utilize a functionality of &lt;a href=&quot;https://hiphive.materialsmodeling.org/tutorial/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;hiPhive&lt;/a&gt; or &lt;a href=&quot;https://ollehellman.github.io/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TDEP&lt;/a&gt; to fit the data from MD-simulations. hiPhive is probably an easier way since it is installed pretty easy using pip. In case of hiPhive once the force-field trained on the MD data is created, generation of the phonon spectrum is straightforward and discussed in the tutorial section.&lt;/p&gt;&#xA;" OwnerUserId="5508" LastEditorUserId="118" LastEditDate="2022-06-03T12:29:47.373" LastActivityDate="2022-06-03T12:29:47.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9195" PostTypeId="1" AcceptedAnswerId="9199" CreationDate="2022-06-03T14:10:12.103" Score="6" ViewCount="2816" Body="&lt;p&gt;In GROMACS I have used the &lt;a href=&quot;https://manual.gromacs.org/archive/5.0.1/programs/gmx-msd.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;command&lt;/a&gt; below to calculate mean square displacement (MSD) over time,&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;gmx msd -f ../run01/run01.trr -s ../run01/run01.tpr -s ../setup/index.ndx -o msd01.xvg -tu ns -type z&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the equation,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = \frac{1}{6t} \langle(r(t) - r(0))^{2}\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I suppose that in GROMACS the default resetting time for &lt;span class=&quot;math-container&quot;&gt;$r(0)$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\pu{10 ps}$&lt;/span&gt; thus &lt;span class=&quot;math-container&quot;&gt;$t=\pu{10 ps}$&lt;/span&gt;. However my most confusing part is selecting the correct linear region. Is there proper mathematical method to find correct linear region?&lt;/p&gt;&#xA;&lt;p&gt;In GROMACS, the args &lt;code&gt;-beginfit -endfit&lt;/code&gt; defaulted to fitting the curve between 10% and 90%. That means I should select linear region as between 10% to 90% along the x axis?&lt;/p&gt;&#xA;&lt;p&gt;An example graph,&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UqvJy.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UqvJy.png&quot; alt=&quot;Example MSD plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4536" LastEditorUserId="7" LastEditDate="2022-06-03T17:23:40.867" LastActivityDate="2022-06-07T12:15:42.547" Title="How to calculate diffusion coefficient from MSD graph using GROMACS?" Tags="|molecular-dynamics|gromacs|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9196" PostTypeId="2" ParentId="6630" CreationDate="2022-06-03T19:30:59.233" Score="7" Body="&lt;p&gt;In the paper mentioned in the question, the &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;-correction is applied to the semi-core &lt;span class=&quot;math-container&quot;&gt;$4d$&lt;/span&gt; states of indium to increase the band gap of In&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt;, which is underestimated by DFT. The band gap is important here, because the focus of the paper are charged defect formation energies, and for those the valence and conduction band edge energies are important. Otherwise, it is not too common to apply &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;-corrections to completely filled shells.&lt;/p&gt;&#xA;&lt;p&gt;Yes, generally, for the calculation of the formation energy of a compound, the constituents must be calculated using the same theory as the compound. In the example of the paper, bulk indium must then also be treated with LDA&lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;. There are no &lt;span class=&quot;math-container&quot;&gt;$U-$&lt;/span&gt;corrections applied to oxygen in this example, so the oxygen reference will simply be computed using LDA.&lt;/p&gt;&#xA;&lt;p&gt;DFT is relatively good at describing delocalized metallic states, and applying &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;-corrections to metals is problematic (the density of states is adversely affected: reduction near the Fermi level, e.g.). Therefore, as mentioned by @Tristan Maxson, at the materials project, metallic phases are computed with DFT, and transition metal oxides with partially filled &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-shells and self-interaction-error problems with DFT&lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt;. Oxide formation energies are calculated by adding a constant correction energy per &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;-corrected ion, which was fitted against a number of experimental heats of formation. This requires a constant &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt; value for a given transition metal ion. Optimal &lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt; values will however depend on the coordination of the transition metal ion, its oxidation state, etc., and the materials project correction scheme (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.84.045115&quot; rel=&quot;noreferrer&quot;&gt;Jain et al., PRB 84, 045115 (2011)&lt;/a&gt;) has been extended to oxide-specific &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;-values (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.90.115105&quot; rel=&quot;noreferrer&quot;&gt;Aykol and Wolverton, PRB 90, 115105 (2014)&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1088/2399-6528/ac6069&quot; rel=&quot;noreferrer&quot;&gt;Voss, J. Phys. Commun. 6 035009 (2022)&lt;/a&gt;). With these methods one can thus compute formation energies by combining DFT and DFT&lt;span class=&quot;math-container&quot;&gt;$+U$&lt;/span&gt; calculations, with &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;-values appropriate for a given system (even &lt;span class=&quot;math-container&quot;&gt;$U=0$&lt;/span&gt; for metallic systems).&lt;/p&gt;&#xA;" OwnerUserId="5250" LastActivityDate="2022-06-03T19:30:59.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9197" PostTypeId="2" ParentId="6825" CreationDate="2022-06-04T02:41:11.603" Score="2" Body="&lt;p&gt;Ironically, there exist no on-lattice software for such a Flory-Huggins software. This is primarily because there are no set standards for running such simulations!&lt;/p&gt;&#xA;&lt;p&gt;Most people run their own DIY code to do this stuff.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-06-04T02:41:11.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9198" PostTypeId="1" CreationDate="2022-06-04T02:59:32.950" Score="6" ViewCount="46" Body="&lt;p&gt;I am running on-lattice simulations of polymers. I am testing out different Hamiltonians and testing different regimes to test if they yield interesting behavior. My question is, how do I rigorously prove the existence of a coil-globule transition, in the event I see signatures of a collapse, or signatures of expansion in my polymer?&lt;/p&gt;&#xA;&lt;p&gt;For example, I am running a simple Flory-Huggins-type simulation of a single chain on a lattice with solvent. The monomer units and solvent occupy the same volume. There is no solvent-solvent interaction, but there is monomer-monomer interaction &lt;span class=&quot;math-container&quot;&gt;$E_{mm}$&lt;/span&gt; and a monomer-solvent interactino &lt;span class=&quot;math-container&quot;&gt;$E_{ms}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;From FH theory, I see that for &lt;span class=&quot;math-container&quot;&gt;$E_{ms} &amp;gt; 2 E_{mm}$&lt;/span&gt;, it is considered a good solvent, and for &lt;span class=&quot;math-container&quot;&gt;$E_{ms} &amp;lt; 2 E_{mm}$&lt;/span&gt;, the solvent is considered a bad solvent.&lt;/p&gt;&#xA;&lt;p&gt;If I run a simulation of a polymer in a bad solvent, I see that it starts of in a collapsed (small &lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt;) state and then expands. My question is, when can I say it went from a collaped (globule) to a expanded (coil) state?&lt;/p&gt;&#xA;&lt;p&gt;What is the battery of tests that I perform on my simulation to prove that at in certain energetic regimes one can see this kind of behavior? I am following this paper, but what I do not get is how they obtained the theta condition. When I have &lt;span class=&quot;math-container&quot;&gt;$E_{ms} = 2 E_{mm}$&lt;/span&gt;, I see excluded volume like behavior &lt;span class=&quot;math-container&quot;&gt;$\nu = 0.58$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$\nu = 0.5$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I see kinks in &lt;span class=&quot;math-container&quot;&gt;$C_v$&lt;/span&gt;, I see drops in &lt;span class=&quot;math-container&quot;&gt;$R_g$&lt;/span&gt; and an associated increase in monomer-monomer contacts, but is this sufficient to prove that a coil-globule transition is taking place?&lt;/p&gt;&#xA;&lt;p&gt;I am following this paper: 10.1002/polb.21024.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, how are the authors finding the theta-point? In Fig. 1, they plot radius of gyration. But my question is, at what temperature are these calculations being performed? How do I find the theta energy if the Radius of Gyration of the polymer is also dependent on temperature?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice or experience that you have with breaking down this phenomena!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="1169" LastEditDate="2022-06-04T15:46:44.977" LastActivityDate="2022-06-04T15:46:44.977" Title="How to rigorously prove the existence of a coil-globule transition of polymers in an on-lattice simulation?" Tags="|monte-carlo|polymers|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-07T03:03:40.210" ContentLicense="CC BY-SA 4.0" />
  <row Id="9199" PostTypeId="2" ParentId="9195" CreationDate="2022-06-06T09:25:58.380" Score="4" Body="&lt;p&gt;MSD accuracy decreases as a function of the lag-time &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;, because for large &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; there are fewer pairs of time slices of interval &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; to average over. Think of the limit in calculating MSD for the largest possible lag-time interval of a simulation. In that case you can only use the initial and final frame to calculate the MSD at that &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. Whereas for small &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;, you can average this over many sets of nearby time frames.&lt;/p&gt;&#xA;&lt;p&gt;The above is why, beyond &lt;span class=&quot;math-container&quot;&gt;$\ce{15 ns}$&lt;/span&gt;, your MSD curve becomes highly non-linear. You simply don't have good statistics here. Very short times are also not ideal to use for &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;, as displacements are ballistic prior to a particle's first collision and the MSD slope is usually very steep at short &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. Hence, choose the large smooth region in the middle of your MSD plot to calculate the slope. As long as your simulation is not changing it's diffusion properties over time, and you have sufficient data to average over, this region of the MSD should have a constant slope.&lt;/p&gt;&#xA;&lt;p&gt;In your case, it looks like you either don't quite have enough data to generate a perfectly smooth MSD beyond &lt;span class=&quot;math-container&quot;&gt;$\ce{6 ns}$&lt;/span&gt;, or your simulation may be changing in some way over time. However, the medium-time MSD is smooth enough to calculate a diffusion constant. Just use the region from about &lt;span class=&quot;math-container&quot;&gt;$\ce{1 ns}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$\ce{5 ns}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;By the way, you can improve MSD statistics by using a shorter reset time (this also increases computational cost).&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-06-06T09:36:42.787" LastActivityDate="2022-06-06T09:36:42.787" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9200" PostTypeId="2" ParentId="9149" CreationDate="2022-06-06T11:07:04.853" Score="10" Body="&#xA;&lt;p&gt;With python, you can open a binary file using the &lt;code&gt;'rb'&lt;/code&gt; option in your &lt;code&gt;open&lt;/code&gt; statement.&#xA;Then using &lt;a href=&quot;https://numpy.org/doc/stable/reference/generated/numpy.fromfile.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;numpy.fromfile&lt;/code&gt;&lt;/a&gt; you can read the file provided you know the datatypes that are in the file.&lt;/p&gt;&#xA;&lt;p&gt;First you have to know that, when you write an unformatted file in Fortran, each time you use a &lt;code&gt;write&lt;/code&gt; statement, the program will also write, before the data, 4  bytes that tells the size of the data that is contained in the &amp;quot;data block&amp;quot;, then the actual data, and then on  4 bytes again, the size of the data that is contained in the &amp;quot;data block&amp;quot;. As this size doesn't matter in your case, you can just skip all of these blocks using python's &lt;code&gt;file.seek&lt;/code&gt; method that allows you to move the cursor.&lt;/p&gt;&#xA;&lt;p&gt;Looking at the &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/wikis/Developers/Format-of-wfc-files&quot; rel=&quot;nofollow noreferrer&quot;&gt;wiki&lt;/a&gt;, you'll see that the format of the wfc file is the following :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ik, xk, ispin, gamma_only, scalef&lt;br /&gt;&#xA;ngw, igwx, npol, nbnd&lt;br /&gt;&#xA;b1, b2, b3&lt;br /&gt;&#xA;mill(1:3,1:igwx)&lt;br /&gt;&#xA;evc(1:npol&lt;em&gt;igwx,1)&lt;br /&gt;&#xA;evc(1:npol&lt;/em&gt;igwx,2)&lt;br /&gt;&#xA;...&lt;br /&gt;&#xA;evc(1:npol*igwx,nbnd)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Where the datatypes are :&lt;/p&gt;&#xA;&#xA;&lt;pre class=&quot;lang-fortran prettyprint-override&quot;&gt;&lt;code&gt;  INTEGER :: ik&#xA;  REAL(8) :: xk(3)&#xA;  INTEGER :: ispin&#xA;  LOGICAL :: gamma_only&#xA;  REAL(8) :: scalef&#xA;  INTEGER :: ngw&#xA;  INTEGER :: igwx&#xA;  INTEGER :: npol&#xA;  INTEGER :: nbnd&#xA;  REAL(8) :: b1(3), b2(3), b3(3)&#xA;  INTEGER :: mill(3,igwx)&#xA;  COMPLEX(8) :: evc(npol*igwx,nbnd)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&#xA;&lt;p&gt;Then, you'll need to know the conversion from the fortran types to the numpy ones&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;INTEGER becomes int32&lt;/li&gt;&#xA;&lt;li&gt;REAL(8) becomes float64&lt;/li&gt;&#xA;&lt;li&gt;COMPLEX(8) becomes complex128&lt;/li&gt;&#xA;&lt;li&gt;LOGICAL is written on 4 bytes, you can just read it as an int32&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here's a quick and dirty way to read these files, you can group the &lt;code&gt;np.fromfile&lt;/code&gt; if you define correctly the types, but I thought that it would be clearer doing it step by step.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-python prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;&#xA;with open('wfc1.dat', 'rb') as f:&#xA;    # Moves the cursor 4 bytes to the right&#xA;    f.seek(4)&#xA;&#xA;    ik = np.fromfile(f, dtype='int32', count=1)[0]&#xA;    xk = np.fromfile(f, dtype='float64', count=3)&#xA;    ispin = np.fromfile(f, dtype='int32', count=1)[0]&#xA;    gamma_only = bool(np.fromfile(f, dtype='int32', count=1)[0])&#xA;    scalef = np.fromfile(f, dtype='float64', count=1)[0]&#xA;&#xA;    # Move the cursor 8 byte to the right&#xA;    f.seek(8, 1)&#xA;&#xA;    ngw = np.fromfile(f, dtype='int32', count=1)[0]&#xA;    igwx = np.fromfile(f, dtype='int32', count=1)[0]&#xA;    npol = np.fromfile(f, dtype='int32', count=1)[0]&#xA;    nbnd = np.fromfile(f, dtype='int32', count=1)[0]&#xA;&#xA;    # Move the cursor 8 byte to the right&#xA;    f.seek(8, 1)&#xA;&#xA;    b1 = np.fromfile(f, dtype='float64', count=3)&#xA;    b2 = np.fromfile(f, dtype='float64', count=3)&#xA;    b3 = np.fromfile(f, dtype='float64', count=3)&#xA;&#xA;    f.seek(8,1)&#xA;    &#xA;    mill = np.fromfile(f, dtype='int32', count=3*igwx)&#xA;    mill = mill.reshape( (igwx, 3) ) &#xA;&#xA;    evc = np.zeros( (nbnd, npol*igwx), dtype=&amp;quot;complex128&amp;quot;)&#xA;&#xA;    f.seek(8,1)&#xA;    for i in range(nbnd):&#xA;        evc[i,:] = np.fromfile(f, dtype='complex128', count=npol*igwx)&#xA;        f.seek(8, 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope it helped.&lt;/p&gt;&#xA;" OwnerUserId="5523" LastEditorUserId="5523" LastEditDate="2022-06-10T08:30:12.700" LastActivityDate="2022-06-10T08:30:12.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9201" PostTypeId="2" ParentId="8712" CreationDate="2022-06-06T16:53:36.363" Score="1" Body="&lt;p&gt;Path U-Γ is not wrong, but it is illogical because they are very far from each other. Atoms in these two positions within the band will weakly interact with each other rather than interacting with X or Z. So you will likely find an abrupt change in band structure.&lt;/p&gt;&#xA;" OwnerUserId="4805" LastEditorUserId="7" LastEditDate="2022-06-08T02:46:01.320" LastActivityDate="2022-06-08T02:46:01.320" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9202" PostTypeId="1" CreationDate="2022-06-07T02:42:54.733" Score="2" ViewCount="168" Body="&lt;p&gt;I am using SIESTA 3.2, which seems to only support the .psf pseudopotential format, is there any tools that allow me to convert the pseudopotential files into another format? Or when generating the pseudopotential, could I assign another format?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-06-07T02:42:54.733" Title="Any software that could convert the format of pseudopotential files?" Tags="|density-functional-theory|pseudopotentials|siesta|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-07T03:03:25.213" ContentLicense="CC BY-SA 4.0" />
  <row Id="9203" PostTypeId="1" AcceptedAnswerId="9207" CreationDate="2022-06-07T08:02:08.763" Score="7" ViewCount="504" Body="&lt;p&gt;I want to calculate the Hessian matrix for molecular configurations that are not at the minimum of the Potential Energy Surface, using cp2k. But it seems that cp2k requires the configuration to be geometrically optimized. In the Vibrational Analysis section of the cp2k manual, it says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The analysis assumes a stationary state (minimum or TS), i.e. tight geometry optimization (MAX_FORCE) is needed as well.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What would happen if I just use cp2k to calculate Hessian for the not-geometrically-optimized configurations? Will it give the correct answer?&lt;/p&gt;&#xA;" OwnerUserId="5532" LastEditorUserId="7" LastEditDate="2022-06-08T02:21:12.483" LastActivityDate="2022-06-10T09:07:48.053" Title="Calculate Hessian for configurations that are not at the minimum of the Potential Energy Surface" Tags="|density-functional-theory|cp2k|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9204" PostTypeId="1" CreationDate="2022-06-07T09:24:24.123" Score="4" ViewCount="185" Body="&lt;p&gt;I need to calculate the electric dipole moment of molecules like HD, in which the electric dipole moment is zero in the Born-Oppenheimer approximation (meaning that it's absolutely necessary to include corrections to it).&lt;/p&gt;&#xA;&lt;p&gt;CFOUR can do it but only in CCSD. Could Molpro or PSI or something else do it?&lt;/p&gt;&#xA;" OwnerUserId="5534" LastEditorUserId="5" LastEditDate="2022-06-07T18:32:17.273" LastActivityDate="2022-06-07T18:32:17.273" Title="Which programs can calculate corrections to the Born-Oppenheimer approximation?" Tags="|software-recommendations|high-precision|mrcc|born-oppenheimer-approximation|cfour|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9205" PostTypeId="2" ParentId="9195" CreationDate="2022-06-07T12:15:42.547" Score="4" Body="&lt;p&gt;If you can obtain the raw data used in that plot, as a purely statistical and numerical exercise you can determine the interval which will give you minimum uncertainty in the estimate of the gradient.&lt;/p&gt;&#xA;&lt;p&gt;A short line segment will inherently have higher uncertainty in estimated gradient simply because you are using fewer sample points. But, for your data, a too-long line segment will also begin to have higher uncertainty in estimated gradient because the segment will start including clearly non-linear, noisy data. This implies that there will be some optimum segment of the line to use. Find that optimum and use it, and as a byproduct you also get an estimate of the uncertainty for free.&lt;/p&gt;&#xA;&lt;p&gt;However, this is only correct as a matter of abstract statistics. The uncertainty will be drastically underestimated (relative to the ground truth of &amp;quot;if I ran a completely independent simulation would I get a similar gradient&amp;quot;), because molecular dynamics snapshots are correlated instead of being statistically independent. If you need to be very accurate in stating the uncertainty (and you may not need to) then you should be referring to this recent paper and choosing a good methodology from it: &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/5.0008312&quot; rel=&quot;nofollow noreferrer&quot;&gt;Optimal estimates of self-diffusion coefficients from molecular dynamics simulations&lt;/a&gt;. Note that the paper authors have made available a python script which implements their recommendation, the generalised least-squares approach.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-06-07T12:15:42.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9206" PostTypeId="2" ParentId="9185" CreationDate="2022-06-07T12:35:39.983" Score="1" Body="&lt;p&gt;I cannot comment on the Fortran code, but in general, calculating the integrated autocorrelation correctly is a subtle exercise. There is increasing uncertainty in estimating correlation at increasing time lags, as you will see if you plot your integrand as a function of &lt;em&gt;t&lt;/em&gt;, which means that the more of your autocorrelation series you try to integrate over the noisier your final estimate will be.&lt;/p&gt;&#xA;&lt;p&gt;One thing you need to do is to &lt;em&gt;censor&lt;/em&gt; your integral -- instead of taking it to infinite time, stop it at some T which is a suitable multiple of the correlation time. A typical value is between 5 to 10 correlation times. For more details on why this works, and an implementation in Python, see: &lt;a href=&quot;https://dfm.io/posts/autocorr/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Autocorrelation time estimation&lt;/a&gt;. (The autocorrelation integral you need is simply the autocorrelation time multiplied by the variance.)&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-06-07T12:35:39.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9207" PostTypeId="2" ParentId="9203" CreationDate="2022-06-07T13:31:12.873" Score="6" Body="&lt;p&gt;It is difficult to understand what you mean by &amp;quot;correct&amp;quot; answer, especially when we are discussing a &amp;quot;not-geometrically-optimized configuration&amp;quot; as you have called it, so I will try to go through the principles.&lt;/p&gt;&#xA;&lt;p&gt;This matrix of all possible second derivatives of the energy with respect to the nuclear displacements of the atoms in your structure is referred to as the Hessian matrix. The Hessian can be diagonalized to obtain harmonic force constants, vibrational frequencies, and normal modes.&lt;/p&gt;&#xA;&lt;p&gt;The vibrational frequencies of the normal modes and the eigenvectors give the amplitudes of motion along each the mass-weighted Cartesian coordinates that belong to each mode. If this same kind of analysis were performed at a geometry corresponding a &amp;quot;not-geometrically-optimized configuration&amp;quot; you would get negative modes which would essentially characterize a &amp;quot;downward&amp;quot; curvature of the energy surface. There is a peculiar case when you have exactly one negative mode, this would usually correspond to a transition state in a configuration or reaction analysis. Here is a good reference on this :&#xA;&lt;a href=&quot;https://simons.hec.utah.edu/ITCSecondEdition/chapter3.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://simons.hec.utah.edu/ITCSecondEdition/chapter3.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, this means that if you do your calculations on your proposed non-optimized structure, you would get several negative frequencies. Does that make them correct or incorrect ? They would technically be correct for that structure itself. However, the structure itself is non-optimized. So maybe the best answer would be that the values are correct but have no real scientific value.&lt;/p&gt;&#xA;&lt;p&gt;Another good reference :&#xA;&lt;a href=&quot;https://kthpanor.github.io/echem/docs/hessians.html&quot; rel=&quot;noreferrer&quot;&gt;https://kthpanor.github.io/echem/docs/hessians.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2022-06-07T13:31:12.873" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9208" PostTypeId="2" ParentId="9204" CreationDate="2022-06-07T18:31:53.993" Score="2" Body="&lt;h3&gt;CFOUR + MRCC&lt;/h3&gt;&#xA;&lt;p&gt;You asked about MOLPRO and Psi4. As recently as 2021, &lt;a href=&quot;https://github.com/psi4/psi4/issues/2149&quot; rel=&quot;nofollow noreferrer&quot;&gt;DBOC (diagonal Born-Oppenheimer correction) wasn't implemented in Psi4&lt;/a&gt;. The same is true for MOLPRO. No other types of Born-Oppenheimer corrections are available in those programs as far as I know. You mentioned that CFOUR can only do DBOC with CCSD, but with the MRCC interface you can actually do CCSDT, CCSDTQ, CCSDTQP, etc. (though these will not be helpful for the HD molecule since it only has two electrons!).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/C/DBOC/aug-cc-pCVTZ-NR/CFOUR-MRCC_CCSDT.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Here you can see my input and output files for a DBOC calculation with CCSDT using CFOUR with the MRCC interface&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the carbon atom with the aug-cc-pCVTZ basis set from the EMSL Basis Set Exchange (&lt;em&gt;circa&lt;/em&gt; 2018), this was the result of my DBOC calculation with CCSDT:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  The total diagonal Born-Oppenheimer correction (DBOC) is:      0.0017104162 a.u.&#xA;  The total diagonal Born-Oppenheimer correction (DBOC) is:        375.392974 cm-1&#xA;  The total diagonal Born-Oppenheimer correction (DBOC) is:             4.491 kJ/mole&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you explore my &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES&quot; rel=&quot;nofollow noreferrer&quot;&gt;AI Energies&lt;/a&gt; database (a database of completed &lt;em&gt;ab initio&lt;/em&gt; calculations including the relevant input files and output files), you'll see that I frequently did DBOC calculations with CCSDTQ and even beyond that.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-06-07T18:31:53.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9209" PostTypeId="1" CreationDate="2022-06-07T18:31:55.017" Score="5" ViewCount="30" Body="&lt;p&gt;I found the nice &lt;code&gt;userd&lt;/code&gt; example with the standard functional in the latest MRCC manual but I wonder if one can also use &lt;code&gt;ssr&lt;/code&gt; (local-scaling approximation) for the &lt;code&gt;userd&lt;/code&gt; functional.&lt;/p&gt;&#xA;&lt;p&gt;For example, as shown in example 18 on page 74, doing &lt;strong&gt;XYG9[f2]@B44LYP&lt;/strong&gt; but substituting the LDA correlation part into &lt;strong&gt;ssrLDA_C_VWN&lt;/strong&gt; with &lt;code&gt;omega=0.5&lt;/code&gt; at the second &lt;code&gt;userd&lt;/code&gt; block.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for the help!&lt;/p&gt;&#xA;" OwnerUserId="790" LastEditorUserId="5" LastEditDate="2022-06-07T18:37:16.510" LastActivityDate="2023-02-07T22:23:18.063" Title="ssr functional for the dft=userd in MRCC package" Tags="|density-functional-theory|mrcc|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9210" PostTypeId="5" CreationDate="2022-06-07T18:34:15.723" Score="0" Body="&lt;p&gt;The CFOUR website: &lt;a href=&quot;http://www.cfour.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.cfour.de/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-06-07T18:34:15.723" LastActivityDate="2022-06-07T18:34:15.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9211" PostTypeId="4" CreationDate="2022-06-07T18:34:15.723" Score="0" Body="Questions about the CFOUR software (CCCC = Coupled Cluster for Computational Chemistry)" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-06-07T18:34:15.723" LastActivityDate="2022-06-07T18:34:15.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9213" PostTypeId="2" ParentId="9203" CreationDate="2022-06-08T02:42:11.973" Score="5" Body="&lt;p&gt;You could in principle compute the entire Hessian for any configuration of a molecule. The problem is that we are typically not interested in the entire Hessian: we want the Hessian for the internal coordinates/vibrations, with rotations and translations projected out.&lt;/p&gt;&#xA;&lt;p&gt;To separate out translations and rotations, we can use the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Eckart_conditions&quot; rel=&quot;noreferrer&quot;&gt;Eckhart conditions&lt;/a&gt;, which define a reference frame that translates/rotates with the molecule. These Eckhart conditions are not satisfied for a nonstationary point, i.e. a point where the nuclear gradients are not all zero. In this case, we can't cleanly separate rotations/translations from vibrations.&lt;/p&gt;&#xA;&lt;p&gt;So you could compute the Hessian at a nonstationary point and compute it's eigenvectors/values, but away from a stationary point they won't have a clear connection to the vibrational modes/frequencies you are likely interested in computing.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-06-08T02:42:11.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9214" PostTypeId="1" CreationDate="2022-06-08T03:43:27.263" Score="2" ViewCount="96" Body="&lt;p&gt;I would like to ask how to use &lt;code&gt;PHONOPY&lt;/code&gt; to define which band is &lt;code&gt;LO&lt;/code&gt;, &lt;code&gt;TO&lt;/code&gt; or &lt;code&gt;LA&lt;/code&gt;, &lt;code&gt;TA&lt;/code&gt;.&#xA;I have read the answer: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3856/how-to-determine-la-ta-za-zo-and-lo-to-by-phonopy&quot;&gt;other matter modeling answer&lt;/a&gt;, it's very helpful.&#xA;In this answer, @Xivi76 provides a way to see the eigenvectors of the modes and then compare to the 'q' shift of supercell. I'm confused how to see the 'q' shift, when creating a supercell, &lt;code&gt;phonopy&lt;/code&gt; give us several supercell files, but each file only has one fixed shift.&lt;/p&gt;&#xA;&lt;p&gt;Besides, I still meet some problems for my system, it's chemical disorder and I use a 32 atom supercell to calculate the phonon.&lt;/p&gt;&#xA;&lt;p&gt;The mesh file I got is this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;frequency:    -0.0019387126&#xA;    eigenvector:&#xA;    - # atom 1&#xA;      - [  0.10015311494775,  0.00000000000000 ]&#xA;      - [  0.14574730400284,  0.00000000000000 ]&#xA;      - [  0.00001729724040,  0.00000000000000 ]&#xA;    - # atom 2&#xA;      - [  0.10013379473130,  0.00000000000000 ]&#xA;      - [  0.14580803218871,  0.00000000000000 ]&#xA;      - [  0.00000000032891,  0.00000000000000 ]&#xA;    - # atom 3&#xA;      - [  0.10015311494775,  0.00000000000000 ]&#xA;      - [  0.14574730400285,  0.00000000000000 ]&#xA;      - [ -0.00001729658241,  0.00000000000000 ]&#xA;    - # atom 4&#xA;      - [  0.10013946626706,  0.00000000000000 ]&#xA;      - [  0.14581888880191,  0.00000000000000 ]&#xA;      - [  0.00000000032896,  0.00000000000000 ]&#xA;    - # atom 5&#xA;      - [  0.10015738736556,  0.00000000000000 ]&#xA;      - [  0.14580019696621,  0.00000000000000 ]&#xA;      - [  0.00002316713376,  0.00000000000000 ]&#xA;    ……&#xA;    - # atom 32&#xA;      - [  0.09997189974928,  0.00000000000000 ]&#xA;      - [  0.14553902989387,  0.00000000000000 ]&#xA;      - [ -0.00002282659679,  0.00000000000000 ]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It seems the vibration mode is too complexity, how can I deal it?&lt;/p&gt;&#xA;" OwnerUserId="5537" LastEditorUserId="181" LastEditDate="2022-06-08T16:49:52.953" LastActivityDate="2022-06-08T16:49:52.953" Title="How to determine the TA/LA by phonopy" Tags="|ab-initio-calculations|phonons|phonopy|phonon-dispersion|" AnswerCount="0" CommentCount="0" ClosedDate="2023-02-07T03:09:19.683" ContentLicense="CC BY-SA 4.0" />
  <row Id="9215" PostTypeId="1" CreationDate="2022-06-08T09:55:17.023" Score="5" ViewCount="73" Body="&lt;p&gt;my question is not related to material or modeling, but I guess many people in this community face it. I took a figure of a crystal structure by cropping the VESTA app on my laptop screen; band and DOS figures were plotted and exported from Gnuplot. I would like to combine them into one with high resolution for thesis and publication. I tried Microsoft PowerPoint to group and then export to a png file. The problem is that the obtained figure does not have a high resolution and its size does not fit the requirements of the journal. Can you suggest some tips or softwares that may export not only crystal structure but also merge figures?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2022-06-08T09:55:17.023" Title="Ask tips: For merging small figures into a big one with high resolution" Tags="|software|visualization-software|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-09T23:00:19.653" ContentLicense="CC BY-SA 4.0" />
  <row Id="9216" PostTypeId="1" AcceptedAnswerId="9217" CreationDate="2022-06-08T12:27:28.897" Score="4" ViewCount="132" Body="&lt;p&gt;I have already performed a FREQ calculation on my system. Following the manual, I then changed the scalar factor accordingly to the theory level I've done my calculation.&lt;/p&gt;&#xA;&lt;p&gt;As procedure suggested in the manual, I then ran &lt;code&gt;orca_vib myjob_scaled_freq.hess&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can I obtain the Free Gibbs Energy from this new hessian file?&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-06-08T20:39:58.460" Title="Recalc entropy and free energy from scaled hessian" Tags="|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9217" PostTypeId="2" ParentId="9216" CreationDate="2022-06-08T20:39:58.460" Score="4" Body="&lt;p&gt;This is from the online Orca &lt;a href=&quot;https://www.orcasoftware.de/tutorials_orca/prop/thermo.html#changing-the-temperature-after-the-calculation&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! PrintThermoChem&#xA;%geom&#xA;  inhessname &amp;quot;basename.hess&amp;quot;&#xA;end&#xA;%freq temp 298 end&#xA;&#xA;*xyzfile 0 1 geometry.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This reads the Hessian and prints the theormochemical analysis at the temperature specified.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2022-06-08T20:39:58.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9218" PostTypeId="1" CreationDate="2022-06-09T05:56:37.487" Score="14" ViewCount="258" Body="&lt;p&gt;Can anyone please explain the differences between Anderson and Mott insulator-metal transition? I found some information in the book named &amp;quot;The_Physics_of_Amorphous_Solids&amp;quot;. &lt;a href=&quot;https://i.stack.imgur.com/VABIT.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VABIT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2023-03-23T07:05:58.550" LastActivityDate="2023-04-14T11:19:48.603" Title="What are differences between Mott and Anderson transitions?" Tags="|condensed-matter|terminology|transport|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9220" PostTypeId="1" AcceptedAnswerId="9223" CreationDate="2022-06-09T14:44:26.713" Score="7" ViewCount="303" Body="&lt;p&gt;How does one obtain the value of dispersion coefficient &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; for elements that come after Xe. I am going through the original paper [&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/jcc.20495&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;]. I can see that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}C^a_6 = 0.05N(I^a \alpha^a),$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\alpha^a$&lt;/span&gt; is the dipole polarization and &lt;span class=&quot;math-container&quot;&gt;$I^a$&lt;/span&gt; is ionization potential. This does not seem that complicated but in the subsequent paragraphs they tend to complicate things. Where they are talking about if the element in the compounds vary a lot from free elements then we need to derive coefficients from molecular properties and there is quite a lot of other things too.&lt;/p&gt;&#xA;&lt;p&gt;Is there any simpler way to go about doing this?&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2022-06-09T18:55:08.293" LastActivityDate="2022-06-10T06:41:01.990" Title="Are dispersion constant calculated differently for elements that are heavier than Xe?" Tags="|density-functional-theory|dispersion-correction|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9221" PostTypeId="1" AcceptedAnswerId="9222" CreationDate="2022-06-08T21:47:11.753" Score="4" ViewCount="32" Body="&lt;p&gt;Can anyone spare me a clue on this?&lt;/p&gt;&#xA;&lt;p&gt;I'm a self-taught student of Molecular Geometry trying to learn more about methods in modeling.  After some extensive reading and study, it felt like it should be easy enough to find an open-source modeling framework with an out-of-the-box force field to just run a basic newtonian model to find a minimum energy state that'd tell you the distance between, say, two Oxygen atoms in O2 or two Hydrogen atoms in H2.&lt;/p&gt;&#xA;&lt;p&gt;I'm using Atomic Simulation Environment in Python and their EMT() force-field/calculator plus the BFGS optimizer, but am getting terrible results.  Simulations repeatedly reporting the interatomic distance between O and O at 1.56 when the real distance is around 1.21&lt;/p&gt;&#xA;&lt;p&gt;I've gotten decent results on interatomic distances for H2O using EMT() [despite its limits], but these diatomic molecules remain a challenge.&lt;/p&gt;&#xA;&lt;p&gt;Here's a code snippet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;o2 = molecule('O2', vacuum=3.0)&#xA;o2.calc = EMT()&#xA;&#xA;dyn = BFGS(o2)&#xA;dyn.run(fmax=0.025)&#xA;&#xA;write('O2.xyz', o2)&#xA;distVecs = o2.get_all_distances()&#xA;r = np.linalg.norm(distVecs[0]-distVecs[1])&#xA;print(&amp;quot;Distance between molecules is %.2f&amp;quot; % r)&#xA;print(&amp;quot;          ---&amp;gt; Target for O2: %.2f&amp;quot; % 1.208)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which gives me results like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      Step     Time          Energy         fmax&#xA;BFGS:    0 14:43:25        0.922681        3.7034&#xA;BFGS:    1 14:43:25        0.650383        1.2520&#xA;BFGS:    2 14:43:25        0.628230        0.4958&#xA;BFGS:    3 14:43:25        0.624772        0.0393&#xA;BFGS:    4 14:43:25        0.624750        0.0011&#xA;Distance between molecules is 1.56&#xA;          ---&amp;gt; Target for O2: 1.21&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5542" OwnerDisplayName="krowney" LastEditorUserId="5" LastEditDate="2022-06-09T18:11:27.960" LastActivityDate="2022-06-09T18:11:27.960" Title="What's a quick way to get a molecular bond length using a Newtonian model?" Tags="|intermolecular-forces|molecular-dynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9222" PostTypeId="2" ParentId="9221" CreationDate="2022-06-09T03:22:17.557" Score="7" Body="&lt;p&gt;The quality of force fields depends a lot on the parameters.&lt;/p&gt;&#xA;&lt;p&gt;For example, if I use &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;Avogadro&lt;/a&gt; and draw out O=O and optimize using the default (MMFF94) I get an O-O distance of 1.282 Å. If I optimize using UFF, I get an O-O distance of 1.151 Å.&lt;/p&gt;&#xA;&lt;p&gt;Instead, if I use the GFN2 approximate DFT method, I get an O-O distance of 1.21 Å.&lt;/p&gt;&#xA;&lt;p&gt;If you look at the &lt;a href=&quot;https://databases.fysik.dtu.dk/ase/ase/calculators/emt.html&quot; rel=&quot;noreferrer&quot;&gt;EMT documentation from ASE&lt;/a&gt;, it says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The EMT parameters for the metals are quite realistic for many&#xA;purposes, whereas the H, C, N and O parameters are just for fun!&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="30" OwnerDisplayName="Geoff Hutchison" LastActivityDate="2022-06-09T03:22:17.557" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9223" PostTypeId="2" ParentId="9220" CreationDate="2022-06-09T18:52:24.497" Score="6" Body="&lt;p&gt;There's many ways to calculate a &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; value, for which it doesn't matter whether the element is heavier or lighter than Xe.&lt;/p&gt;&#xA;&lt;p&gt;One of the simplest equations for &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; is in the &lt;em&gt;&lt;strong&gt;abstract&lt;/strong&gt;&lt;/em&gt; of a &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.37.682&quot; rel=&quot;noreferrer&quot;&gt;1931 paper by Slater and Kirkwood&lt;/a&gt; (often called the Slater-Kirkwood approximation):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TZfWv.png,&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TZfWv.png,&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore we have (in the notation of &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.1742536&quot; rel=&quot;noreferrer&quot;&gt;Brandt in 1955&lt;/a&gt;, and probably others between 1931-1955):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;C_6 = -\frac{3}{4}\left(a_0N\alpha^3\right)^{1/2}e^2,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$a_0$&lt;/span&gt; being the Bohr radius, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; being the number of electrons in the molecular valence shell, &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; being the average dipole polarizability, and &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt; being the charge of an electron.&lt;/p&gt;&#xA;&lt;p&gt;For a heteronuclear system another simple formula is given &lt;a href=&quot;https://en.wikipedia.org/wiki/London_dispersion_force&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;C_6^{AB} = -\frac{3}{2}\frac{I_AI_B}{I_A+I_B}\alpha_A\alpha_B,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$I_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$I_B$&lt;/span&gt; being the first ionization energies for the systems &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\alpha_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_B$&lt;/span&gt; being again their average dipole polarizabilities.&lt;/p&gt;&#xA;&lt;p&gt;You are correct that other formulas exist, for example, I found at least two in &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0953-4075/43/20/202001/meta&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q81AHl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q81AHl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Bd4Ywl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Bd4Ywl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried to turn the question &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/63/5&quot;&gt;What are the different ways of calculating dispersion constants?&lt;/a&gt; into a list of all the known methods to approximate &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt;, but I wanted it to be in the form of &lt;a href=&quot;/questions/tagged/one-topic-per-answer&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;one-topic-per-answer&amp;#39;&quot; rel=&quot;tag&quot;&gt;one-topic-per-answer&lt;/a&gt; with each user explaining just one method (otherwise you might get 10 answers from me, which I think would look weird).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Beyond the element Xe, relativistic effects will become quite important when attempting to calculate the dipole polarizability &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; or the ionization energy &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; using &lt;em&gt;ab initio&lt;/em&gt; methods. Another famous relativistic effect was described in &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.73.360&quot; rel=&quot;noreferrer&quot;&gt;this 1948 paper by Casimir and Polder&lt;/a&gt;, in which they showed that for &lt;em&gt;very&lt;/em&gt; large distances the &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; actually becomes a &lt;span class=&quot;math-container&quot;&gt;$C_7$&lt;/span&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-06-09T19:43:53.647" LastActivityDate="2022-06-09T19:43:53.647" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9224" PostTypeId="1" AcceptedAnswerId="9240" CreationDate="2022-06-09T14:07:12.270" Score="6" ViewCount="2085" Body="&lt;p&gt;To support my laboratory result, I'm searching for an MD/statistical mechanics approach to predict translational diffusion coefficients in the liquid phase.&lt;/p&gt;&#xA;&lt;p&gt;I'm aiming to describe small peptides and small organic molecules and in future proteins and protein aggregates.&lt;/p&gt;&#xA;" OwnerUserId="5562" OwnerDisplayName="Giuseppe Basile" LastEditorUserId="5" LastEditDate="2022-06-09T20:42:44.373" LastActivityDate="2022-06-15T16:11:21.003" Title="How are diffusion coefficients calculated?" Tags="|proteins|thermodynamics|biomaterials|structural-biology|organic-chemistry|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9225" PostTypeId="2" ParentId="9224" CreationDate="2022-06-09T23:45:54.590" Score="4" Body="&lt;p&gt;I decided to make my comment an answer...&lt;/p&gt;&#xA;&lt;p&gt;Diffusion coefficients are simple to calculate in molecular dynamics. GROMACS has built in software specifically for this calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://manual.gromacs.org/current/onlinehelp/gmx-msd.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS diffusion coefficient manual&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You simply run your &amp;quot;normal&amp;quot; NVT or NPT simulation, and then call this function&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;gmx msd -f *.trr&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;adding additional options as you see fit, and replacing the wildcard &lt;code&gt;*&lt;/code&gt; with the actual file name if more than one &lt;code&gt;.trr&lt;/code&gt; file exists in the folder. GROMACS will ask you what molecules or groups you would like to know the diffusion coefficient for, and there you go.&lt;/p&gt;&#xA;&lt;p&gt;This will probably take less than 1 hour of calculation time, perhaps a couple if you really want to equilibrate and sample well (note: time depends on cpu or gpu ratio to number of atoms - longer times may occur if there are few computational resources thrown at the simulation). The amount of time taken by &lt;code&gt;gmx msd&lt;/code&gt; is in the seconds to minutes... it is quite fast.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-06-10T18:32:52.150" LastActivityDate="2022-06-10T18:32:52.150" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9226" PostTypeId="1" CreationDate="2022-06-09T23:59:01.257" Score="9" ViewCount="137" Body="&lt;p&gt;I want to try to model the electornic structure of atoms in a confining potential, eg. add a term to the Hamiltonian either of a constant value &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; after certain distance from the origin or just the form &lt;span class=&quot;math-container&quot;&gt;$r^n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I've came across &lt;a href=&quot;https://github.com/pyscf/pyscf.github.io/blob/master/examples/scf/40-apply_electric_field.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this example&lt;/a&gt; which adds an electric field to the molecule, and it is done using an extra term of the form &lt;span class=&quot;math-container&quot;&gt;$E r$&lt;/span&gt; as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def apply_field(E):&#xA;    mol.set_common_orig([0, 0, 0])  # The gauge origin for dipole integral&#xA;    h =(mol.intor('cint1e_kin_sph') + mol.intor('cint1e_nuc_sph') + numpy.einsum('x,xij-&amp;gt;ij', E, mol.intor('cint1e_r_sph', comp=3)))&#xA;    mf = scf.UHF(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This led to me understanding that there's a &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/pyscf/gto/moleintor.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;set of integrals&lt;/a&gt; that can be more or less directly added to the Hamiltonian (after taking care of the dimension issues I assume). However this list is rather limited and I am not sure how to add either an &lt;span class=&quot;math-container&quot;&gt;$r^n$&lt;/span&gt; term or a step function term - is there something that I can do to add a general operator?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; I assume it comes down to the fact that I should cast a specific operator onto the basis in which the Hamiltonian is written. Is there a nice way of doing this?&lt;/p&gt;&#xA;" OwnerDisplayName="user5418" LastEditorDisplayName="user5418" LastEditDate="2022-06-22T07:32:01.230" LastActivityDate="2022-06-22T07:32:25.250" Title="How to add confining potentials in PySCF?" Tags="|model-hamiltonians|pyscf|" AnswerCount="0" CommentCount="0" ClosedDate="2023-02-07T04:11:29.540" ContentLicense="CC BY-SA 4.0" />
  <row Id="9227" PostTypeId="2" ParentId="9220" CreationDate="2022-06-10T06:41:01.990" Score="3" Body="&lt;p&gt;You already have a potentially good answer from Nike Dattani, however I might frame this as an entirely different question.  Unless you have a good reason to determine you own dispersion constants / corrections, can you just use an existing dispersion correction such as DFT-D4 (rather than D2).  Dispersion should work with any element on the periodic table, as of this &lt;a href=&quot;https://github.com/dftd4/dftd4/commit/8e9944982e89a66889d19d2754cb0ca86e736fff&quot; rel=&quot;nofollow noreferrer&quot;&gt;commit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can interface this onto any calculator using the &lt;a href=&quot;https://github.com/dftd4/dftd4/tree/main/python&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE-D4&lt;/a&gt; calculator if you need to.  This &lt;strong&gt;might&lt;/strong&gt; solve your issue from a practical standpoint, even if this isn't your original question.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-06-10T06:41:01.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9228" PostTypeId="2" ParentId="9203" CreationDate="2022-06-10T09:07:48.053" Score="5" Body="&lt;p&gt;The Hessian at a non-stationary point is well-defined, since it is the second derivative of the energy wrt. nuclear coordinates. The transformation to vibrational normal coordinates, however, assumes that the gradient is zero. In practice, this is never the case, but &amp;quot;sufficiently small&amp;quot; is normally good enough. At non-stationary points, one can define 3N-7 generalized vibrations by projecting out the translational and rotational degrees of freedom and the gradient. This have been used in &amp;quot;reaction path methods&amp;quot; for including the effects of nuclear motion perpendicular to the reaction coordinate, for example defined by the IRC path.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2022-06-10T09:07:48.053" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9229" PostTypeId="1" CreationDate="2022-06-10T14:44:20.233" Score="2" ViewCount="559" Body="&lt;p&gt;the last few days I've tried to calculate the phonon-dispersion of SrTiO3 (STO) and EuTiO3 (ETO) using the PHonon package of QE. SCF, DOS, PDOS and Bandsctructure calculation worked well on these materials, I've used a Hubbard-correction for both. My scf.in file for STO looks as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;STO:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation = 'scf'&#xA;    outdir = './out/'&#xA;    prefix      = 'STO_gamma'&#xA;    pseudo_dir  = './nc-sr-04_pbe_stringent_upf/'&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ! a = 3.94513 # old value before vc-relax.x&#xA;  A = 3.93795&#xA;  degauss =   0.005&#xA;  ecutwfc =   80&#xA;  lda_plus_u=.true.&#xA;  lda_plus_u_kind = 0&#xA;  hubbard_u(1) = 0&#xA;  hubbard_u(2) = 5.6&#xA;  hubbard_u(3) = 4&#xA;  ibrav = 0&#xA;  nbnd = 33&#xA;  nat = 5&#xA;  nosym = .false.&#xA;  nspin = 2&#xA;  ntyp = 3&#xA;  occupations = 'smearing'&#xA;  starting_magnetization(1) =   1.0d-01&#xA;  starting_magnetization(2) =   1.0d-01&#xA;  starting_magnetization(3) =   4.16d-01&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr =  1.d-10&#xA;    mixing_beta = 0.7&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Sr    87.62000  Sr.upf&#xA;Ti   47.86700  Ti.upf&#xA;O   15.99940  O.upf&#xA;&#xA;CELL_PARAMETERS {alat}&#xA;   0.998180509   0.000000000   0.000000000&#xA;   0.000000000   0.998180509   0.000000000&#xA;   0.000000000   0.000000000   0.998180509&#xA;&#xA;ATOMIC_POSITIONS {crystal}&#xA;Sr           0.0000000000       0.0000000000       0.0000000000&#xA;Ti           0.5000000000       0.5000000000       0.5000000000&#xA;O            0.5000000000       0.0000000000       0.5000000000&#xA;O            0.5000000000       0.5000000000       0.0000000000&#xA;O            0.0000000000       0.5000000000       0.5000000000&#xA;&#xA;K_POINTS {automatic}&#xA;16 16 16&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The pesudopotentials are the norm conserving potentials from pseudo-dojo.org. The bandstructure shows an energy gap of about 3.2 eV with these settings. &lt;a href=&quot;https://i.stack.imgur.com/Juoh6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Juoh6.png&quot; alt=&quot;STO Bandstructure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The ph.x input looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonon calculation at Gamma point.&#xA;&amp;amp;inputph&#xA;  outdir = './out/'&#xA;  prefix      = 'STO_gamma'&#xA;  tr2_ph = 1.0d-3&#xA;  nmix_ph = 10&#xA;  epsil = .false.&#xA;  amass(1) = 87.62000&#xA;  amass(2) = 47.86700&#xA;  amass(3)  = 15.99940&#xA;  fildyn = 'STO_phonon.dyn'&#xA;/&#xA;0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output generated by dynmat.x after applying the acustic sum rule = crystal looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# mode   [cm-1]    [THz]      IR&#xA;    1  -6235.76 -186.9435    0.0000&#xA;    2  -6235.76 -186.9435    0.0000&#xA;    3  -6235.76 -186.9435    0.0000&#xA;    4  -4352.85 -130.4953    0.0000&#xA;    5  -4352.85 -130.4953    0.0000&#xA;    6  -4352.85 -130.4953    0.0000&#xA;    7  -4105.78 -123.0883    0.0000&#xA;    8  -4105.78 -123.0883    0.0000&#xA;    9  -4105.78 -123.0883    0.0000&#xA;   10  -2138.73  -64.1174    0.0000&#xA;   11  -2138.73  -64.1174    0.0000&#xA;   12  -2138.73  -64.1174    0.0000&#xA;   13      0.00    0.0000    0.0000&#xA;   14      0.00    0.0000    0.0000&#xA;   15      0.00    0.0000    0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This calculation alone took over 3 hours only for the gamma point.&#xA;The input file for my scf calculation of ETO looks like&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;ETO:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './out/'&#xA;  prefix = 'EuTiO3'&#xA;  pseudo_dir = './pseudo/'&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  a = 3.9611945300&#xA;  degauss = 0.01&#xA;  ecutrho =   600&#xA;  ecutwfc =   75&#xA;  lda_plus_u=.true.&#xA;  lda_plus_u_kind = 0&#xA;  hubbard_u(1) = 9&#xA;  hubbard_u(2) = 0&#xA;  hubbard_u(3) = 0&#xA;  ibrav = 1&#xA;  nat = 5&#xA;  nosym = .false.&#xA;  nspin = 2&#xA;  ntyp = 3&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  starting_magnetization(1) =   4.1176470588d-01&#xA;  starting_magnetization(2) =   1.0000000000d-01&#xA;  starting_magnetization(3) =   4.1666666667d-01&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.0000000000d-06&#xA;  electron_maxstep = 1000&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Eu     151.964 Eu.GGA-PBE-paw-v1.0.UPF&#xA;O      15.9994 O.pbe-n-kjpaw_psl.0.1.UPF&#xA;Ti     47.867 ti_pbe_v1.4.uspp.F.UPF&#xA;&#xA;ATOMIC_POSITIONS {crystal}&#xA;Eu           0.0000000000       0.0000000000       0.0000000000 &#xA;Ti           0.5000000000       0.5000000000       0.5000000000 &#xA;O            0.5000000000       0.5000000000       0.0000000000 &#xA;O            0.5000000000       0.0000000000       0.5000000000 &#xA;O            0.0000000000       0.5000000000       0.5000000000 &#xA;&#xA;K_POINTS {automatic}&#xA;6 6 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Bandstructure with band gap of about 1.05 eV:&lt;a href=&quot;https://i.stack.imgur.com/0tn4s.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0tn4s.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;The ph.x input is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!phonons of EuTiO3 at Gamma&#xA;&amp;amp;inputph&#xA;  prefix = 'EuTiO3'&#xA;  outdir = './out/'&#xA;  tr2_ph = 1.0d-14&#xA;  amass(1) = 151.964&#xA;  amass(2) = 15.9994&#xA;  amass(3) =  47.867&#xA;  ! epsil = .true.&#xA;  ! lraman .true.&#xA;  fildyn='EuTiO3.dynG'&#xA; /&#xA;0.000000000000000   0.000000000000000   0.000000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which got me the following phonon frequencies (again asr = crystal):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# mode   [cm-1]    [THz]      IR&#xA;    1   -636.90  -19.0939    0.0000&#xA;    2   -636.90  -19.0939    0.0000&#xA;    3   -636.90  -19.0939    0.0000&#xA;    4   -547.18  -16.4041    0.0000&#xA;    5   -547.18  -16.4041    0.0000&#xA;    6   -547.18  -16.4041    0.0000&#xA;    7   -401.41  -12.0340    0.0000&#xA;    8   -401.41  -12.0340    0.0000&#xA;    9   -401.41  -12.0340    0.0000&#xA;   10     -0.00   -0.0000    0.0000&#xA;   11     -0.00   -0.0000    0.0000&#xA;   12      0.00    0.0000    0.0000&#xA;   13     64.61    1.9371    0.0000&#xA;   14     64.61    1.9371    0.0000&#xA;   15     64.61    1.9371    0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have a question about these results:&lt;/p&gt;&#xA;&lt;p&gt;Why is it not possible to set epsil = .true., lraman .true. ?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;I hope you are still around and thank you for reading :)&lt;/p&gt;&#xA;&lt;p&gt;Have a nice day,&lt;/p&gt;&#xA;&lt;p&gt;Simon&lt;/p&gt;&#xA;" OwnerUserId="5535" LastEditorUserId="5" LastEditDate="2022-06-10T14:56:26.237" LastActivityDate="2022-06-17T15:45:44.483" Title="Phonon Dispersion of SrTiO3, EuTiO3 using Quantum Espresso (DFT-U)" Tags="|quantum-espresso|dft-u|hubbard-model|perovskites|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9230" PostTypeId="1" CreationDate="2022-06-10T15:00:11.737" Score="5" ViewCount="189" Body="&lt;p&gt;I understand that the task of implementing machine learning in DFT and Hartree–Fock (HF) algorithm has already been solved, perhaps to some extent, but it is interesting to think about how to implement, for example, a neural network (NN) such a way that NN would be balanced towards the speed of calculation execution rather than training: (1) using several NNs in various parts of the algorithm; (2) using one single NN into one part of the algorithm; (3) using one common NN for the entire algorithm; (4) or something else?&lt;/p&gt;&#xA;&lt;p&gt;I have seen that NNs are used for the matrix diagonalization procedure. The procedure is used, for example, by the HF algorithm.&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2022-09-29T07:06:19.507" Title="In which part of the Hartree–Fock algorithm (or DFT one) could a neural network be most effectively used?" Tags="|density-functional-theory|ab-initio-calculations|hartree-fock|machine-learning|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9231" PostTypeId="1" CreationDate="2022-06-10T17:33:09.487" Score="3" ViewCount="34" Body="&lt;p&gt;I want to make a graphene-based conductive ink with cyclohexanone pr terpinol as the solvent and ethyl cellulose as the binder. How can I do that?&lt;/p&gt;&#xA;" OwnerUserId="5546" LastEditorUserId="5" LastEditDate="2022-06-10T19:32:13.357" LastActivityDate="2022-06-10T19:32:13.357" Title="Making a graphene based conductive ink" Tags="|materials-design|materials-engineering|graphene|materials-informatics|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-07T04:11:53.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="9232" PostTypeId="1" CreationDate="2022-06-10T18:23:15.440" Score="11" ViewCount="493" Body="&lt;p&gt;I am new in solid-state calculation field.&lt;/p&gt;&#xA;&lt;p&gt;There has been pretty well-known to use DFT or DFT+U method to calculate the electronic properties such as the band gap for metal, and semiconductors.&lt;/p&gt;&#xA;&lt;p&gt;When I read the papers, I can always see that people say their band gap calculation is close to the experimental data. From what I know, band gap values are related to temperature, and the experimental condition is about the room temperature, but the calculation from DFT is at 0K! Can we compare the band gap at totally different temperatures? Also how about pressure?&lt;/p&gt;&#xA;&lt;p&gt;I really appreciate any comments on this. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="5351" LastActivityDate="2022-06-26T15:23:15.360" Title="Temperature Effect on Band gap in solid state calculation" Tags="|band-structure|d-band|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9233" PostTypeId="2" ParentId="9232" CreationDate="2022-06-10T19:29:30.213" Score="9" Body="&lt;p&gt;You are absolute right: the electronic band gap depends on the temperature and pressure of the system.&lt;/p&gt;&#xA;&lt;p&gt;One of the &amp;quot;problems&amp;quot; of DFT is that it fails calculating the band gap for several semiconductors materials. Even using DFT+U, the values may be far from experimental ones (sometime it is better just to use a scissor operator).&lt;/p&gt;&#xA;&lt;p&gt;When comparing calculated with experimental values, it is only to have an idea of the band gap value, compare with previous publications and to check if the material does not change its conduction type (from semiconductor to semimetal/metal, for example).&lt;/p&gt;&#xA;&lt;p&gt;The figure below show the calculated band gap temperature dependence for &lt;span class=&quot;math-container&quot;&gt;$\ce{GaAs}$&lt;/span&gt; following the work of Blakemore [1]. The value for &lt;span class=&quot;math-container&quot;&gt;$0\,K$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$1.5\,eV$&lt;/span&gt; and for &lt;span class=&quot;math-container&quot;&gt;$300\,K$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$1.43\,eV$&lt;/span&gt; which are very close.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2B3pe.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2B3pe.gif&quot; alt=&quot;temperature dependence for GaAs&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Recently, I came across with a publication that uses deep neural networks together with DFT to do calculations at finite temperatures [2]. Their workflow if available from GitHub [3].&lt;/p&gt;&#xA;&lt;p&gt;Dependence with pressure is easier to consider as in most of the DFT software, you can set the pressure under the calculation will run.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;br /&gt;&#xA;[1] J.S. Blakemore. &lt;em&gt;Semiconducting and other major properties of gallium arsenide&lt;/em&gt;. J. Appl. Phys. 53, R123 (1982); &lt;a href=&quot;https://doi.org/10.1063/1.331665&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1063/1.331665&lt;/a&gt;&lt;br /&gt;&#xA;[2] J.A. Ellis, L. Fiedler, G.A. Popoola, N.A. Modine, J.A. Stephens, A.P. Thompson, A. Cangi, and S. Rajamanickam, &lt;em&gt;Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks&lt;/em&gt;. Phys. Rev. B 104, 035120 (2021); &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.104.035120&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI: 10.1103/PhysRevB.104.035120&lt;/a&gt; (OpenAcess)&lt;br /&gt;&#xA;[3] Github: &lt;a href=&quot;https://github.com/mala-project/mala&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/mala-project/mala&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="625" LastEditDate="2022-06-22T22:33:59.943" LastActivityDate="2022-06-22T22:33:59.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9234" PostTypeId="1" AcceptedAnswerId="9235" CreationDate="2022-06-10T20:38:55.150" Score="6" ViewCount="113" Body="&lt;p&gt;My aim is to model the potential energy surface for two colliding H2 molecules. More specifically, I needed the order of magnitude of the slope of the potential at the moment when two colliding H2 molecules &amp;quot;touch&amp;quot;. How do I obtain this?&lt;/p&gt;&#xA;" OwnerUserId="1810" LastEditorUserId="5" LastEditDate="2022-06-10T22:01:57.050" LastActivityDate="2022-06-10T22:01:57.050" Title="Slope of the potential when both molecules &quot;touch&quot;?" Tags="|reference-request|ab-initio-calculations|spectroscopy|geometry|potential-energy-surface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9235" PostTypeId="2" ParentId="9234" CreationDate="2022-06-10T22:01:37.097" Score="5" Body="&lt;p&gt;If you have two atoms colliding, we rarely talk about them &amp;quot;touching&amp;quot; because the potential energy between them will tend to infinity as the internuclear distance tends to zero. For example, you can see what the potential looks like as &lt;span class=&quot;math-container&quot;&gt;$r \rightarrow 0$&lt;/span&gt; in the figure of my answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1004/5&quot;&gt;Converting adsorption binding energy to absolute temperature&lt;/a&gt;. This is often called the &amp;quot;united-atom limit&amp;quot; (there's many papers with that term in the title!) and the slope is just obtained from the Coulomb &lt;span class=&quot;math-container&quot;&gt;$1/r$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;But what you're asking, is essentially about four hydrogen atoms, two of them forming one &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecule, and the other two of them forming a second &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecule. Are they colliding in a &amp;quot;T&amp;quot; shape (one &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; is perpendicular to the other &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;), or in an &amp;quot;I&amp;quot; shape (collinear, with the left &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; atom of one molecule hitting the right &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; atom of the other one), or with a shape like &amp;quot;=&amp;quot; in whcih both molecules are parallel?&lt;/p&gt;&#xA;&lt;p&gt;You can calculate the potential energy surface with an &lt;em&gt;ab initio&lt;/em&gt; quantum chemistry software, depending on your desired initial and final &lt;em&gt;&lt;strong&gt;geometry&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have made hundreds of input files and output files for such calculations, available for free &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One example of a homonuclear 4-atom system (very similar to having four &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; atoms, but the atoms are &lt;span class=&quot;math-container&quot;&gt;$\ce{C}$&lt;/span&gt; instead) is &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/C4%2B/def2-TZVPP/out.50042728&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The input file is as follows (in this case the software used was MRCC, and I've made slight changes to make it simpler for you):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#TITLE&#xA;basis=def2-TZVPP&#xA;calc=CC(4)&#xA;mem=12GB&#xA;&#xA;unit=angs&#xA;geom=xyz&#xA;4&#xA;&#xA;C  1.2247  0.0000 0.0000&#xA;C -1.2247  0.0000 0.0000&#xA;C  0.0000 -0.7286 0.0000&#xA;C  0.0000  0.7286 0.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can simply change the lines starting with &lt;code&gt;C&lt;/code&gt; to start with &lt;code&gt;H&lt;/code&gt;, and pick a geometry (x,y,z coordinates for each &lt;code&gt;H&lt;/code&gt;) that you desire. The program will give you an &lt;em&gt;ab initio&lt;/em&gt; energy. Then you repeat the process for different geometries as two of the (bounded) &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; atoms collide with the other two, in whatever configuration you desire (&amp;quot;T&amp;quot; shape, &amp;quot;I&amp;quot; shape, &amp;quot;=&amp;quot; shape, etc.).&lt;/p&gt;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;$\ce{H}$&lt;/span&gt; is the first element of the periodic able, studies of it are considered quite &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9037/5&quot;&gt;fundamental&lt;/a&gt;&amp;quot;, so you may even be able to find the potential energy surface online!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-06-10T22:01:37.097" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9236" PostTypeId="1" CreationDate="2022-06-12T10:08:07.360" Score="3" ViewCount="145" Body="&lt;p&gt;I want to do a simple SCF calculation for an entropy stabilised oxide using VASP (DFT code). The chemical formula is (CuCoMgNiZn)O (Rock salt structure) and it is anti-ferromagnetic in nature. I am using the mcsqs code from ATAT (Alloy theoretic automated toolkit) as the structure needs to be random in nature. But the problem is I am getting the overall magnetic moment as 4 (after the DFT calculation) which should ideally be 0 for an anti-ferromagnetic system.&lt;/p&gt;&#xA;&lt;p&gt;I found one paper stating &amp;quot;As the magnetic structure of the rocksalt (MgCoNiCuZn)O is antiferromagnetic in its ground state, we also considered the arrangement of atomic spins where (111) planes contain magnetic moments alternatively parallel and antiparallel with the spin direction along [211]. Each cation is equally populated in the two magnetic sites:&#xA;(Mg0.2 Co0.1(spin-up) Co0.1(spin-down) Ni0.1(spin-up) Ni0.1(spin-down) Cu0.2 Zn0.2)O&amp;quot; to deal with the magnetism. The link to the paper &lt;a href=&quot;https://www.nature.com/articles/s41524-022-00780-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/s41524-022-00780-0&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The magnetic moment portion of my input file is copied here for your reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INCAR&#xA;..........&#xA;..........&#xA;ISPIN = 2&#xA;MAGMOM = 4x0 2x3 2x-3 20x0 2x4 2x-4 4x0 4x0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;0 = magnetic moment of Mg, O, Zn,Cu,&#xA;3 = magnetic moment of Ni,&#xA;4 = magnetic moment of Co&lt;/p&gt;&#xA;&lt;p&gt;Order of atoms in the POSCAR =  Mg  Ni   O  Co  Zn  Cu&lt;/p&gt;&#xA;&lt;p&gt;I think there is an issue with the way I write the order of the magnetic moment. But I don't know how to deal with this issue.&lt;/p&gt;&#xA;&lt;p&gt;Any suggestions would be highly appreciable.&lt;/p&gt;&#xA;" OwnerUserId="1178" LastActivityDate="2022-06-12T10:08:07.360" Title="Anti ferromagnetism of the Entropy Stabilized Oxide (ESO)" Tags="|vasp|anti-ferromagnetic|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-14T01:05:02.913" ContentLicense="CC BY-SA 4.0" />
  <row Id="9237" PostTypeId="1" AcceptedAnswerId="9239" CreationDate="2022-06-12T16:10:47.950" Score="2" ViewCount="120" Body="&lt;p&gt;Is there any software that could generate the atom configurations used in the .fdf files? I am currently using wxDragon to convert the .cif file, but it would automatically reduce the atom number by taking advantage of symmetry. Besides, wxDragon seems doesn’t allow me to modify the structure.&#xA;I am wondering what the mainstream tools for this kind of job?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-06-13T15:25:04.667" Title="Any software for creating the atom configuration used in the siesta input file?" Tags="|crystallography|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9238" PostTypeId="1" CreationDate="2022-06-13T09:37:21.930" Score="6" ViewCount="102" Body="&lt;p&gt;I have built a CG (Martini) model of a 2D Nanomaterial. For now, I want to calculate its bending rigidity. As far as I know, the bending modulus can be computed by making the nanomaterial infinite - i.e. cross over the PBC which will allow stretching.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone done similar work with gromacs? and is my current level of knowledge is correct on making the nanomaterial infinite by adding the bonded terms between the two ends.&lt;/p&gt;&#xA;&lt;p&gt;Looking forward to some suggestions with regards to this. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2022-06-13T09:37:21.930" Title="Calculating bending modulus of a CG model of a surface from MD simulation" Tags="|molecular-dynamics|gromacs|martini|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-09T23:05:10.450" ContentLicense="CC BY-SA 4.0" />
  <row Id="9239" PostTypeId="2" ParentId="9237" CreationDate="2022-06-13T15:25:04.667" Score="3" Body="&lt;h1&gt;GDIS&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A visualization program for the display, manipulation, and analysis of&#xA;isolated molecules and periodic structures.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Although GDIS supports output files from a large number of codes, input files can be created and run within GDIS for:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GULP&#xA;GAMESS&#xA;SIESTA&#xA;Monty&#xA;VASP&#xA;USPEX&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It can be downloaded from GitHub site: &lt;a href=&quot;https://github.com/arohl/gdis&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/arohl/gdis&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Below are some snapshots from the old &lt;a href=&quot;http://gdis.seul.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;site&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jzwJI.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jzwJI.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/XVdGT.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XVdGT.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KJ1v7.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KJ1v7.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/A3vIe.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/A3vIe.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-06-13T15:25:04.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9240" PostTypeId="2" ParentId="9224" CreationDate="2022-06-13T20:37:00.717" Score="6" Body="&lt;p&gt;There are several different methods to calculate diffusion coefficients depending on the problem and some nuances to consider.&lt;/p&gt;&#xA;&lt;h2&gt;Mean square displacement&lt;/h2&gt;&#xA;&lt;p&gt;The most common way to calculate diffusion coefficients in homogeneous media is to calculate the mean square displacement. This is what the Gromacs tool described in the other answer does. However, these calculations are relatively easy to do on your own (using a script in Python, MathLab, or whatever language you like or even a spreadsheet). The general formula is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = \frac{1}{2} \lim_{t\rightarrow \infty} \left&amp;lt; \left[ x(t)-x(0) \right]^2 \right&amp;gt;/t$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the mean &lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt; \cdots \right&amp;gt;$&lt;/span&gt; is over many different trajectories (probably at least 20). These trajectories can be from multiple simulations with different initial conditions, multiple molecules in the same simulation, or even different time intervals of a single molecule in a single simulation.&lt;/p&gt;&#xA;&lt;p&gt;You can &lt;a href=&quot;https://doi.org/10.1021/jp003020w&quot; rel=&quot;nofollow noreferrer&quot;&gt;shift your time origin&lt;/a&gt; to &lt;span class=&quot;math-container&quot;&gt;$t'$&lt;/span&gt; to make use of different intervals. If your system is three-dimensional and isotropic (all directions are the same), you can use the vector displacement along all three axes to get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = \frac{1}{6} \lim_{t\rightarrow \infty} \left&amp;lt; \left| \mathbf{r}(t - t')-\mathbf{r}(t') \right|^2 \right&amp;gt;/t$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The plot below from &lt;a href=&quot;https://doi.org/10.1021/jp003020w&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mark et al.&lt;/a&gt; shows some mean squared displacements for the TIP3P water molecule as a function of time, &lt;span class=&quot;math-container&quot;&gt;$\mathsf{MSD}(t) = \left&amp;lt; \left| \mathbf{r}(t - t')-\mathbf{r}(t') \right|^2 \right&amp;gt;$&lt;/span&gt;. Here the mean is calculated over all 901 water molecules in the system. The different curves represent different time origins. From here, you can calculate the slope of the curve using a least squares fit (I'm not sure this is the best way in terms of error analysis, but this is often how its done). In the graph below, the mean square displacement is roughly 300 Å&lt;sup&gt;2&lt;/sup&gt; in 100 ps, so &lt;span class=&quot;math-container&quot;&gt;$D \approx \frac{1}{6} 300~Å^2/(100~\mathrm{ps}) = 0.5~Å^2/\mathrm{ps}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dHiCb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dHiCb.png&quot; alt=&quot;Plot of mean square displacements from Mark et al. 2001 DOI: 10.1021/jp003020w&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Given that you have a limited simulation time, you usually have to choose between having more subtrajectories to get better statistics or having a longer time (&lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;) for each subtrajectory. More subtrajectories give you better statistics, but if your trajectories are too short, they will not yet be in the diffusive regime (&lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt;x^2 \right&amp;gt; \sim t$&lt;/span&gt;). As shown in the MSD graph below from &lt;a href=&quot;https://doi.org/10.1103/PhysRevE.79.011907&quot; rel=&quot;nofollow noreferrer&quot;&gt;Flenner et al.&lt;/a&gt; for lateral diffusion of lipids in bilayer membrane, different regimes can exist at different timescales. At short times motion is ballistic (the particles move a near constant velocity and &lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt;x^2 \right&amp;gt; \sim t^2$&lt;/span&gt;). At longer times, there is an intermediate subdiffusive regime (&lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt;x^2 \right&amp;gt; \sim t^{0.7}$&lt;/span&gt;). Standard diffusion (&lt;span class=&quot;math-container&quot;&gt;$\left&amp;lt;x^2 \right&amp;gt; \sim t$&lt;/span&gt;) only appears after many nanoseconds.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MMfOy.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MMfOy.png&quot; alt=&quot;Log-log plot of mean square displacement for lateral diffusion of lipids. Several different regimes can seen at different time scales. Taken from Flenner et al. 2009 DOI: 10.1103/PhysRevE.79.011907&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Finite-size effects&lt;/h2&gt;&#xA;&lt;p&gt;The diffusion coefficient that you measure will be biased somewhat due to the small size of the simulation system, which leads to hydrodynamic interactions between particles and their periodic images. How small is too small? For the periodic boundary conditions typically used in molecular dynamics simulations, you can use the correction of &lt;a href=&quot;https://doi.org/10.1021/jp0477147&quot; rel=&quot;nofollow noreferrer&quot;&gt;Yeh and Hummer&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D_\mathrm{corrected} = D_\mathrm{PBC} + 2.84 k_\mathrm{B}T/(6 \pi \eta L),$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$D_\mathrm{PBC}$&lt;/span&gt; is the diffusion coefficient calculated in the simuilation, &lt;span class=&quot;math-container&quot;&gt;$k_\mathrm{B}$&lt;/span&gt; is Boltzmann's constant, &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the temperature, &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; is the shear viscosity of the solvent, and &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is the dimension of the cubic box. With modern computers, you can usually make your systems big enough to where this correction is negligible.&lt;/p&gt;&#xA;&lt;h2&gt;Velocity autocorrelation&lt;/h2&gt;&#xA;&lt;p&gt;While the MSD method is the most common for homogeneous systems, there are other methods, such as the &lt;a href=&quot;https://doi.org/10.1016/j.bpc.2006.03.019&quot; rel=&quot;nofollow noreferrer&quot;&gt;velocity autocorrelation method&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = \int_0^\infty \left&amp;lt; v(0) v(t) \right&amp;gt; \, \mathrm{d}t.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For isotropic system in 3D, you can write,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D = \frac{1}{3} \int_0^\infty \left&amp;lt; \mathbf{v}(0) \cdot \mathbf{v}(t) \right&amp;gt; \, \mathrm{d}t.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Inhomogeneous systems&lt;/h2&gt;&#xA;&lt;p&gt;Things get much more difficult if your system is not homogeneous in the direction that you need to calculate the diffusion coefficient. In this case, the diffusion coefficient likely varies with position, &lt;span class=&quot;math-container&quot;&gt;$D(x)$&lt;/span&gt;. Furthermore, in inhomogeneous systems the particles typically experience systematic forces in addition to the random forces of the medium. The effect of these position-dependent forces, &lt;span class=&quot;math-container&quot;&gt;$F(x)$&lt;/span&gt;, also must be considered.&lt;/p&gt;&#xA;&lt;p&gt;To calculate the diffusion coefficients along the coordinate, you can restrain your particle harmonically to different positions. For the case of a particle in an approximately harmonic well, an unbiased diffusion coefficient can be calculated based on the &lt;a href=&quot;https://doi.org/10.1088/1367-2630/7/1/034&quot; rel=&quot;nofollow noreferrer&quot;&gt;Generalized Langevin Equation&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D(z) = \frac{\left&amp;lt;\delta z^2 \right&amp;gt;^2}{\int_0^\infty \left&amp;lt; \delta z(t) \delta z(0) \right&amp;gt; \, \mathrm{d}t},$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\delta z(t) = z(t) - \left&amp;lt;z\right&amp;gt;$&lt;/span&gt; is the displacement from the mean position in the well.&lt;/p&gt;&#xA;&lt;p&gt;This method is commonly used for inhomogeneous systems in the context of umbrella sampling calculations (which also obtain the free energy and its gradient, the mean force &lt;span class=&quot;math-container&quot;&gt;$F(x) = -\nabla A(x)$&lt;/span&gt;). however, more robust methods based on Bayesian inference have been proposed and can obtain &lt;span class=&quot;math-container&quot;&gt;$D(x)$&lt;/span&gt; in the case of arbitrary position-dependent forces. See &lt;a href=&quot;https://doi.org/10.1088/1367-2630/7/1/034&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hummer 2005&lt;/a&gt; &lt;a href=&quot;https://doi.org/10.1016/j.bpj.2012.01.063&quot; rel=&quot;nofollow noreferrer&quot;&gt;and&lt;/a&gt; &lt;a href=&quot;https://doi.org/10.1021/ct300867e&quot; rel=&quot;nofollow noreferrer&quot;&gt;others&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2022-06-15T16:11:21.003" LastActivityDate="2022-06-15T16:11:21.003" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9241" PostTypeId="1" CreationDate="2022-06-14T09:05:28.403" Score="5" ViewCount="205" Body="&lt;p&gt;Are there any options I should optimize in the input file to maximize the parallel efficiency? Like in the VASP, there are two options &lt;code&gt;NCORE&lt;/code&gt; and &lt;code&gt;KPAR&lt;/code&gt; controlling how to configure parallel running.&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-11-18T21:19:34.003" Title="How to maximise the parallel efficiency of siesta?" Tags="|high-performance-computing|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9243" PostTypeId="1" CreationDate="2022-06-14T10:08:58.847" Score="1" ViewCount="99" Body="&lt;p&gt;I am starting to learn how to write UMATs in Abaqus, so I took the most simple example, which is linear elasticity (Hooke's law), and implemented it. I tested it on a 3D-rectangular body with a fixed bottom and a displacement boundary on top (tension).&lt;/p&gt;&#xA;&lt;p&gt;When I use the following code...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SUBROUTINE UMAT(STRESS,STATEV,DDSDDE,SSE,SPD,SCD,&#xA;     1 RPL,DDSDDT,DRPLDE,DRPLDT,&#xA;     2 STRAN,DSTRAN,TIME,DTIME,TEMP,DTEMP,PREDEF,DPRED,CMNAME,&#xA;     3 NDI,NSHR,NTENS,NSTATV,PROPS,NPROPS,COORDS,DROT,PNEWDT,&#xA;     4 CELENT,DFGRD0,DFGRD1,NOEL,NPT,LAYER,KSPT,KSTEP,KINC)&#xA;!&#xA;      INCLUDE 'ABA_PARAM.INC'&#xA;!&#xA;      CHARACTER*80 CMNAME&#xA;      DIMENSION STRESS(NTENS),STATEV(NSTATV),&#xA;     1 DDSDDE(NTENS,NTENS),DDSDDT(NTENS),DRPLDE(NTENS),&#xA;     2 STRAN(NTENS),DSTRAN(NTENS),TIME(2),PREDEF(1),DPRED(1),&#xA;     3 PROPS(NPROPS),COORDS(3),DROT(3,3),DFGRD0(3,3),DFGRD1(3,3)&#xA;     &#xA;!   elastic UMAT&#xA;&#xA;      PARAMETER (ONE=1.0D0, TWO=2.0D0)&#xA;        E = PROPS(1)&#xA;        NU = PROPS(2)&#xA;        ALAMBDA = E/(ONE+NU)/(ONE-TWO*NU)&#xA;        BLAMBDA = ONE-NU&#xA;        CLAMBDA = (ONE-TWO*NU)/TWO &#xA;        DO I=1,NTENS&#xA;          DO J=1,NTENS&#xA;            DDSDDE(I,J)=0.0D0&#xA;          ENDDO&#xA;        ENDDO   &#xA;        DDSDDE(1,1)=(ALAMBDA*BLAMBDA)&#xA;        DDSDDE(2,2)=(ALAMBDA*BLAMBDA)&#xA;        DDSDDE(3,3)=(ALAMBDA*BLAMBDA)&#xA;        DDSDDE(4,4)=(ALAMBDA*CLAMBDA)&#xA;        DDSDDE(5,5)=(ALAMBDA*CLAMBDA)&#xA;        DDSDDE(6,6)=(ALAMBDA*CLAMBDA)&#xA;        DDSDDE(1,2)=(ALAMBDA*NU)&#xA;        DDSDDE(1,3)=(ALAMBDA*NU)&#xA;        DDSDDE(2,3)=(ALAMBDA*NU)&#xA;        DDSDDE(2,1)=(ALAMBDA*NU)&#xA;        DDSDDE(3,1)=(ALAMBDA*NU)&#xA;        DDSDDE(3,2)=(ALAMBDA*NU)&#xA;        DO I=1,NTENS&#xA;          DO J=1,NTENS&#xA;            STRESS(I)=STRESS(I)+DDSDDE(I,J)*DSTRAN(J)&#xA;          ENDDO&#xA;        ENDDO&#xA;      &#xA;      &#xA;      &#xA;      RETURN&#xA;      END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;... the output is wrong. When I change the variable name &amp;quot;NU&amp;quot; to e.g. &amp;quot;ANU&amp;quot;, the code all of a sudden gives the right solution, which is equivalent to the Abaqus Elastic Material result. This is confusing me a lot.&lt;/p&gt;&#xA;&lt;p&gt;Does &amp;quot;NU&amp;quot; happen to be some kind of protected keyword, or am I missing some sort of declaration?&lt;/p&gt;&#xA;" OwnerUserId="4197" LastEditorUserId="7" LastEditDate="2023-02-07T03:14:56.457" LastActivityDate="2023-02-07T03:14:56.457" Title="Why does naming a variable &quot;NU&quot; instead of e.g. &quot;ANU&quot; change the output of my UMAT? (Abaqus/Fortran)" Tags="|fortran|abaqus|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9244" PostTypeId="2" ParentId="9243" CreationDate="2022-06-14T11:00:47.357" Score="2" Body="&lt;p&gt;Actually, I think it is a problem with the variable declaration.&lt;/p&gt;&#xA;&lt;p&gt;When I add&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DOUBLE PRECISION :: E, NU, ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;all works well.&lt;/p&gt;&#xA;" OwnerUserId="4197" LastActivityDate="2022-06-14T11:00:47.357" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9245" PostTypeId="1" AcceptedAnswerId="10369" CreationDate="2022-06-14T14:45:34.183" Score="3" ViewCount="129" Body="&lt;p&gt;Let’s assume that a crystal has been calculated by Hartree–Fock (HF) method (or DFT one), i.d., so to speak, the &amp;quot;first characteristics&amp;quot;, which are eigenvalues and eigenvectors, as well as Fock matrix on a final step of iteration, have been done. Using these &amp;quot;first characteristics&amp;quot;, can I obtain the electrical conductivity tensor (ECT)?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5403" LastEditorUserId="5" LastEditDate="2022-06-14T15:12:58.093" LastActivityDate="2023-02-06T19:11:13.597" Title="Can the electrical conductivity tensor of a crystal be obtained from a Hartree-Fock calculation?" Tags="|density-functional-theory|ab-initio-calculations|hartree-fock|electronic-transport|electric-field|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9246" PostTypeId="1" AcceptedAnswerId="9248" CreationDate="2022-06-14T20:34:19.040" Score="5" ViewCount="333" Body="&lt;p&gt;Hi  I have a system that belongs to the C1 point group which is polycyclic and contains heteroatomes ,when calculating the excited states by TDDFT and after visualising the MOs that are envolved on transitions . How can I distinguish between pi-pi* and n-pi* transition.&lt;/p&gt;&#xA;" OwnerUserId="5563" LastActivityDate="2022-06-15T08:34:17.263" Title="how can I distiguish between pi-pi* or n-pi* while doing a TDDFT calculus on gaussian?" Tags="|computational-chemistry|td-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9247" PostTypeId="1" AcceptedAnswerId="9252" CreationDate="2022-06-15T04:23:43.923" Score="6" ViewCount="552" Body="&lt;p&gt;When drawing the band structure, I need to transform the coordinate of k-points into a k-path, but I am not sure what the formula is.&lt;/p&gt;&#xA;&lt;p&gt;I checked the result of &lt;code&gt;siesta&lt;/code&gt;, Here is the coordinates of some k-points&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;siesta: Band k vectors (Bohr**-1):&#xA;  ik            k&#xA;   1    -0.158058    -0.000000     0.000000&#xA;   2    -0.152790    -0.000000     0.000000&#xA;   3    -0.147521    -0.000000     0.000000&#xA;   4    -0.142253    -0.000000     0.000000&#xA;   5    -0.136984    -0.000000     0.000000&#xA;   6    -0.131715    -0.000000     0.000000&#xA;   7    -0.126447    -0.000000     0.000000&#xA;   8    -0.121178    -0.000000     0.000000&#xA;   9    -0.115910    -0.000000     0.000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the range of the k-path&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# k_min, k_max      =     0.0000    0.3722&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;What is the formula I should use to transform k-points coordinates into k-path?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-09-06T18:25:47.540" Title="How to transform the k coordinate into the k path used in the band structure?" Tags="|vasp|band-structure|crystallography|k-points|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9248" PostTypeId="2" ParentId="9246" CreationDate="2022-06-15T08:34:17.263" Score="6" Body="&lt;p&gt;There are a few methods, that are equivalent as long as the excited state is either an almost pure pi-pi* state or an almost pure n-pi* state (i.e. no appreciable mixings between these two types of transitions).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Plot the difference density between the desired excited state and the ground state. If there is a density depletion in a pi orbital and a density accumulation in a pi* orbital, then it is a pi-pi* state; if the density depletion is in an n orbital instead, then it is an n-pi* state. Pro: applicable even if the state is a heavy mixture of many transitions. Con: some visualization programs do not support this natively.&lt;/li&gt;&#xA;&lt;li&gt;Plot the natural transition orbitals (NTOs) of the desired excited state. If most of the transitions are from pi orbitals, then it is a pi-pi* state; if they are mainly from n orbitals instead, then it is an n-pi* state. Pro: any software that can visualize orbitals can be used, provided that the NTOs are already generated. Con: one must first generate the NTOs, and depending on the computational chemistry software, if one forgot to request for NTOs when writing the input file, one may need to run the calculation again (with the correct keyword(s) added) to get the NTOs.&lt;/li&gt;&#xA;&lt;li&gt;Plot the frontier orbitals to see their character (n, pi, pi* etc.), and assign the excited state based on the canonical MO composition of the state (that are normally printed in the output file of the TDDFT calculation). Pro: any software that can visualize orbitals can be used, and there is no need to perform additional calculations such as the generation of NTOs. Con: when the state is a heavy mixture of many transitions, the amount of work required by this approach is higher than the previous two approaches.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-06-15T08:34:17.263" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9249" PostTypeId="2" ParentId="267" CreationDate="2022-06-15T09:38:54.500" Score="4" Body="&lt;p&gt;A probably more useful heuristic is that the highest frequency mode of the perturbation is smaller than the excitation energy of the first excited state that is dominated by double (or higher) excitations. In the linear response regime, this rationale can be justified by the following argument: the adiabatic approximation recovers all single excitations but no double and higher excitations, while the latter are described exactly by the full non-adiabatic XC kernel. Therefore, when the external potential varies at a higher and higher rate, the first time that the adiabatic approximation fails qualitatively is when the external potential oscillates at the frequency consistent with the first state that is missed by the adiabatic approximation, where the exact response diverges, but the approximate response does not have any divergences at that frequency, not even at nearby frequencies.&lt;/p&gt;&#xA;&lt;p&gt;Of course the heuristic is not completely rigorous, for the following reasons: (1) the true response is not necessarily in the linear-response regime; (2) even though the heuristic rules out qualitative errors, there may still be large quantitative errors. Ultimately, to conclusively say when an approximation is valid, one must also provide the desired precision of the simulation; an approximation that is valid for a crude calculation is not necessarily valid for an accurate one.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-06-15T09:38:54.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9250" PostTypeId="1" AcceptedAnswerId="9259" CreationDate="2022-06-15T11:14:33.670" Score="5" ViewCount="302" Body="&lt;p&gt;I &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9246/how-can-i-distiguish-between-pi-pi-or-n-pi-while-doing-a-tddft-calculus-on-gau&quot;&gt;recently asked&lt;/a&gt; about how to distinguish between transition types. I got an answer there about determining the character or type of the orbitals.&lt;/p&gt;&#xA;&lt;p&gt;My problem now is that I'm not sure how to determine the type of an orbital. How can you distinguish, either by inspection or some algorithm, whether an orbital is &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\pi^*$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; on a system that contains double bonds and heteroatoms? For example what are the types of the HOMO and LUMO shown below.&lt;/p&gt;&#xA;&lt;p&gt;LUMO orbital &lt;a href=&quot;https://i.stack.imgur.com/pSJGa.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pSJGa.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;HOMO orbital&lt;a href=&quot;https://i.stack.imgur.com/eHFSx.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eHFSx.jpg&quot; alt=&quot;Homo &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="7" LastEditDate="2022-06-15T12:55:10.470" LastActivityDate="2022-06-16T09:54:15.407" Title="How can I distinguish between n, pi, pi* orbitals when looking for excited states?" Tags="|computational-chemistry|symmetry|orbitals|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9252" PostTypeId="2" ParentId="9247" CreationDate="2022-06-15T13:13:09.323" Score="4" Body="&lt;p&gt;In SIESTA, what I used to do is:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Select the high symmetry points&lt;/li&gt;&#xA;&lt;li&gt;Define de number of k points between them&lt;/li&gt;&#xA;&lt;li&gt;Wrote the k path&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For example, take a look at the Brillouin zone bellow:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ceOoP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ceOoP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the recommended path, lets take only the first four points &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-X-M-&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;.  The corresponding coordinates for &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;, X and M are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Gamma: 0 0 0&#xA;X: 0 1/2 0&#xA;M: 1/2 1/2 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, in SIESTA, you add lines like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1  0.0  0.0  0.0  \Gamma&#xA;4  0.0  0.5  0.0  X&#xA;4  0.5  0.5  0.0  M&#xA;4  0.0  0.0  0.0  \Gamma&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This means that the bands will be calculated with only 4 points between (0,0,0) and (0,0.5,0) (for the first segment &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-X), 4 points between (0,0.5,0) and (0.5,0.5,0), etc.&#xA;The points for the first segment will be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0.0 0.0 0.0&#xA;0.0 0.1 0.0&#xA;0.0 0.2 0.0&#xA;0.0 0.3 0.0&#xA;0.0 0.4 0.0&#xA;0.0 0.5 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Of course that using only 4 points is an example here to play with the numbers. Using 4 points will give you a segmented band structures, so you need to use more (I usually use 200 and got a smooth curve)&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2022-09-06T18:25:47.540" LastActivityDate="2022-09-06T18:25:47.540" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9253" PostTypeId="2" ParentId="7000" CreationDate="2022-06-15T15:41:45.373" Score="2" Body="&lt;p&gt;I have been working on evaluating the electron relaxation time in these structures for some time now. From what I found out using Deformation Potential theory calculations, the assumption I made earlier was incorrect. I calculated the average electron relaxation time in all the structures, and there were sufficiently significant differences between them.&lt;/p&gt;&#xA;&lt;p&gt;Although I have seen some published articles using a constant 1fs electron relaxation time just to eliminate the per relaxation time component of the electronic transport properties, I saw that the relaxation time in my cases varied between 2.5fs (Structure A) and 6.7fs (Structure B). If I had used the same 1fs relaxation time for both structures, the thermo-electric performance of structure A would have been better. However in reality, it had worse performance than Structure B. Because of this, it would probably be the best to actually evaluate the electron relaxation time if possible.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2022-06-15T15:41:45.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9254" PostTypeId="1" AcceptedAnswerId="9257" CreationDate="2022-06-15T16:14:16.657" Score="5" ViewCount="91" Body="&lt;p&gt;I am trying to make a script to adapt and modify the distances between two monomers I do have. I have build a xyz structure and use Openbabel to construct the Z-matrix of the system. However, I am not sure if there is a simple way of modifying it to adapt the distances of the monomers. For example, for two water molecules, which zmatrix is given by:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 1&#xA;O1&#xA;H2 1 r1&#xA;H3 1 r2 2 a1&#xA;O5 2 r3 4 a2 1 180.&#xA;H6 5 r4 2 a3 4 d1&#xA;H7 5 r4 2 a3 4 -d1&#xA;Variables&#xA;r1 = 1.0&#xA;r2 = 1.0&#xA;r3 = 1.8&#xA;r4 = 1.0&#xA;a1 = 104.52&#xA;a2 = 90.&#xA;a3 = 120.&#xA;d1 = 80.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How would you proceed if you want to keep varying the distances using a small &amp;quot;distance step&amp;quot; to compute properties of the system? For example, between atom 2 and 5.&lt;/p&gt;&#xA;" OwnerUserId="3382" LastActivityDate="2022-06-15T22:29:28.330" Title="How to modify Gaussian Z-matrix to adjust distances between monomers" Tags="|gaussian|visualization-software|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9255" PostTypeId="1" CreationDate="2022-06-15T18:48:28.250" Score="5" ViewCount="72" Body="&lt;p&gt;I am trying to simulate the dynamic response of semiconductors to laser impulse, but I am not sure how to do it with TDDFT in siesta, I checked the &lt;a href=&quot;https://docs.siesta-project.org/projects/siesta/tutorials/td-dft/index.html&quot; rel=&quot;noreferrer&quot;&gt;siesta-doc&lt;/a&gt;, and it seems I need to construct an excited state, and then begin TDDFT.&#xA;So How could I simulate the response to laser impulse?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-06-15T18:48:28.250" Title="simulate dynamic response to laser impulse with TDDFT in SIESTA" Tags="|siesta|td-dft|response-theory|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-06T19:56:16.160" ContentLicense="CC BY-SA 4.0" />
  <row Id="9256" PostTypeId="1" AcceptedAnswerId="10368" CreationDate="2022-06-15T21:00:25.007" Score="2" ViewCount="42" Body="&lt;p&gt;I'm trying to perform an NTO analysis (Natural transition orbitals) for my system. I first used TDDFT to calculate the excited states and then generated my chk file and copied it under the name of state_3.chk. I seemed to get a 2070 error.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;%chk=state_3.chk # B3LYP/6-31G* Geom=AllCheck Guess=(Read,Only) Density=(Check,Transition=3) Pop=(Minimal,NTO,SaveNTO)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Error&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; dumping /fiocom/, unit = 3 NFiles =     1 SizExt =    524288 WInBlk =       512&#xA;                   defal = T LstWrd =       67072 FType=2 FMxFil=10000&#xA;&#xA; Number           0&#xA; Base         20480&#xA; End          67072&#xA; End1         67072&#xA; Wr Pntr      20480&#xA; Rd Pntr      20480&#xA; Length       46592&#xA; Error termination in NtrErr:&#xA; NtrErr Called from FileIO.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5" LastEditDate="2023-02-07T02:26:59.590" LastActivityDate="2023-02-07T02:26:59.590" Title="Error termination while performing NTO analysis in G09?" Tags="|computational-chemistry|gaussian|symmetry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9257" PostTypeId="2" ParentId="9254" CreationDate="2022-06-15T22:29:28.330" Score="6" Body="&lt;p&gt;The general problem with auto-generated z-matrices (e.g., this one) is that they may not define distances the way you want.&lt;/p&gt;&#xA;&lt;p&gt;In this case, it seems as if you just need to change &lt;code&gt;r3&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Gaussian, like many programs, has built-in support for energy scans.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;r3 1.8  10 0.1&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;This would take 10 steps, each 0.1 in size. This has the advantage of starting each step with a good initial guess for SCF from the previous geometry.&lt;/p&gt;&#xA;&lt;p&gt;More generally, even as an Open Babel developer, I agree with the comment by @Camps. Pick your favorite script language (e.g., Python) and you can move distances and angles as you wish.&lt;/p&gt;&#xA;&lt;p&gt;Pseudo-code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# write xyz coordinates of one monomer&#xA;for step in range(10):&#xA;    for atom in monomer1:&#xA;        new_xyz = atom.xyz + [ step * 0.1, 0.0, 0.0 ]&#xA;        # write out atom at new_xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-06-15T22:29:28.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9258" PostTypeId="1" AcceptedAnswerId="10172" CreationDate="2022-06-16T02:21:01.283" Score="2" ViewCount="57" Body="&lt;p&gt;I want to make a movie using VMD, but when I follow the instructions it can just produce the image frames in the ppm format. I noticed I need to preinstall some packages for VMD to be able to make a movie. I figured that I need to install Flink and it guided me to a browser which requires me to download and install xCode app. It is just taking forever to download the app. I also tried using Quick time maker to make a movie from image frames but it seems it cannot read ppm files. Can anybody help me wit the issue? how can I make a movie from ppm files or how can I make VMD movie maker work without using xCode?&lt;/p&gt;&#xA;&lt;p&gt;Than you so much&lt;/p&gt;&#xA;" OwnerUserId="4924" LastActivityDate="2022-12-31T03:15:38.187" Title="Flink installation question on MacOS Monterey?" Tags="|vmd|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9259" PostTypeId="2" ParentId="9250" CreationDate="2022-06-16T09:54:15.407" Score="4" Body="&lt;p&gt;Both orbitals look like &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; orbitals, as both have nodes at the plane of the molecule, which is characteristic for &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; systems. Occupied valence orbitals are usually considered to be bonding while excited unoccupied orbitals are often antibonding. In this particular case I woudn't say that the distinction between bonding and antibonding is 100% clear, but I'd call the LUMO &lt;span class=&quot;math-container&quot;&gt;$\pi^*$&lt;/span&gt; in this case since the nodal structure can clearly be seen.  I would also call this a charge transfer transition since you have a clear transfer of density from the left benzodioxole group to the central indene(?) group and the right benzene group.&lt;/p&gt;&#xA;&lt;p&gt;But orbital characterization is not clear cut process. As you know yourself, there is no clear definition of these terms except in the most basic systems and I would recommend not to overthink the characterization. Just make sure that you you don't go against already established characterizations in literature.&lt;/p&gt;&#xA;&lt;p&gt;Remark:&lt;/p&gt;&#xA;&lt;p&gt;I would have preferred to post this as a comment as I don't provide a general methodology to solve the characterisation problem. But my comment didn't fit in the comments field.&lt;/p&gt;&#xA;" OwnerUserId="2289" LastActivityDate="2022-06-16T09:54:15.407" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9260" PostTypeId="1" CreationDate="2022-06-16T18:08:33.583" Score="4" ViewCount="138" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubmed.ncbi.nlm.nih.gov/34685447/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiscale Enhanced Sampling Using Machine Learning&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Multiscale enhanced sampling (MSES) allows for enhanced sampling of all-atom protein structures by coupling with the accelerated dynamics of the associated coarse-grained (CG) model. In this paper, we propose an MSES extension to replace the CG model with the dynamics on the reduced subspace generated by a machine learning approach, the variational autoencoder (VAE).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As far as I understood:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The combination of MSES and the accelerated dynamics of the corresponding CG model is a superior way of sampling AA protein structures.&lt;/li&gt;&#xA;&lt;li&gt;In this paper the author proposes a novel model as an extension to the MSES technique.&lt;/li&gt;&#xA;&lt;li&gt;This new model is supposed to replace dynamic CG models.&lt;/li&gt;&#xA;&lt;li&gt;... ... ??&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I haven't understood the last part of the quote.&lt;/p&gt;&#xA;&lt;p&gt;However, in short:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Moritsugu offers an extension to multiscale enhanced sampling (MSES) so that dynamic CG models can be replaced using a machine learning technique called variational autoencoder.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Can anyone help me either by explaining or paraphrasing it?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-02-06T19:03:13.450" LastActivityDate="2023-10-01T16:05:26.690" Title="Understanding use of Machine Learning in Multiscale Enhanced Sampling" Tags="|molecular-modeling|machine-learning|atomistic-simulation|coarse-grained|multiscale-modeling|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9261" PostTypeId="1" CreationDate="2022-06-17T04:43:04.297" Score="5" ViewCount="96" Body="&lt;p&gt;I have relaxed atomic coordinates of bilayer graphene obtained from LAMMPS MD simulations.&lt;/p&gt;&#xA;&lt;p&gt;I want to extract hopping parameters (tight binding model or continuum model) to obtain the band structure of the system.&lt;/p&gt;&#xA;&lt;p&gt;Can someone assist me.&lt;/p&gt;&#xA;" OwnerUserId="5206" LastActivityDate="2022-06-17T04:43:04.297" Title="Extracting hopping parameters for band structure calculations from Atomic coordinates" Tags="|band-structure|lammps|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-09T23:04:40.290" ContentLicense="CC BY-SA 4.0" />
  <row Id="9262" PostTypeId="1" AcceptedAnswerId="9264" CreationDate="2022-06-17T05:36:21.523" Score="3" ViewCount="447" Body="&lt;p&gt;We are planning on comparing the results of Quantum dots and Bulk materials for our systems so we are planning to use Gaussian for QD and VASP for Bulk. Considering that we will be comparing their results we should perform the same calculations(same corrections, same functionals and all) so should we hard code the constants used in Dispersion correction(DFT-D2)? So should we use the same constants such as &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt;, vdW_radius, scaling factors, etc ??&lt;/p&gt;&#xA;&lt;p&gt;If setting them the same is perhaps the correct path. Then we will be using the ones given by Gaussian as we can directly print them out using &lt;code&gt;IOp(3/33=3)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Thanks and any help is greatly appreciated !!&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-06-17T06:21:39.187" LastActivityDate="2022-06-17T06:41:00.910" Title="DFT-D2 calculations in VASP and Gaussian" Tags="|vasp|gaussian|dispersion-correction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9264" PostTypeId="2" ParentId="9262" CreationDate="2022-06-17T06:41:00.910" Score="7" Body="&lt;p&gt;The error due to the basis set will likely be larger than any difference in the DFT-D2 treatment. This is because you cannot use the same basis set in a (non-periodic) Gaussian calculation and a VASP calculation, as the former uses Gaussian functions while the latter uses plane waves. Thus, for maximum comparability of the results, you should use VASP also for the QD calculation, by specifying a periodic box that is much larger than the size of the QD so as to minimize the spurious interactions of the QD with its periodic images.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, if comparability is not a concern, then using Gaussian to calculate the QD is a good idea, since less computational resources are wasted in describing the empty space surrounding the QD. In that case, however, you may use DFT-D3 instead of DFT-D2, since the former is also supported by Gaussian and offers higher accuracy. If you use ORCA, you can even go to DFT-D4.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-06-17T06:41:00.910" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9265" PostTypeId="1" CreationDate="2022-06-17T13:45:54.417" Score="3" ViewCount="77" Body="&lt;p&gt;In gromacs, if we use SMD to pull one end of the molecule, how can we compute the stress applied if we know the force. I am using plumed to define a colvar, and pulling one end of my molecule. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2022-06-17T13:45:54.417" Title="Stress on pulling in MD simulation" Tags="|gromacs|plumed|" AnswerCount="0" CommentCount="1" ClosedDate="2023-01-22T19:50:33.280" ContentLicense="CC BY-SA 4.0" />
  <row Id="9267" PostTypeId="2" ParentId="9229" CreationDate="2022-06-17T15:45:44.483" Score="2" Body="&lt;p&gt;Follow up: Using a fixed occupation it was possible to get the dielectric constant since then QE won't treat the system as a metal anymore. Since STO is not stable at 0K, ph.x only showed imaginary frequencies (see &lt;a href=&quot;https://arxiv.org/pdf/1506.02382.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/1506.02382.pdf&lt;/a&gt;). As for ETO it might be similar but I am not sure yet.&lt;/p&gt;&#xA;" OwnerUserId="5535" LastActivityDate="2022-06-17T15:45:44.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9269" PostTypeId="1" AcceptedAnswerId="10367" CreationDate="2022-06-18T14:26:48.077" Score="4" ViewCount="172" Body="&lt;p&gt;I'm a little bit lost with NBO (natural bond orbital) analysis in Gaussian. I was told that &lt;code&gt;pop=NBO&lt;/code&gt; in Gaussian gives me the charges of atoms, but that the NBO program can give the composition of a &amp;quot;localized orbitals&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to perform this latter type of analysis in Gaussian or can we only extract NBO charges?&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5" LastEditDate="2023-02-07T02:28:19.323" LastActivityDate="2023-02-07T02:28:19.323" Title="What is the difference between NBO program and NBO that we find in Gaussian?" Tags="|computational-chemistry|gaussian|orbitals|population-analysis|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9272" PostTypeId="1" CreationDate="2022-06-19T21:22:10.443" Score="7" ViewCount="227" Body="&lt;p&gt;Classically in Hartree-Fock implementations we define the wave-function in term of a basis set:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_i = \sum_{\alpha} C_{\alpha i}\chi_\alpha$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If I understand correctly the problem is reduced to find a set of these coefficients which minimise the total energy. Again, if my understanding is correct these coefficients are initially given in the basis set. If you look at STO-3G for example, there are always two numbers: the coefficient and the exponent.&lt;/p&gt;&#xA;&lt;p&gt;What I am confused about is: In the algorithm we have to get a &amp;quot;first guess&amp;quot; of the density matrix. The density matrix is defined as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D_{uv} = \sum_{i} C_{ui}C_{vi}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why not just take the one given in the basis set as an initial guess?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2022-06-26T19:11:32.067" Title="Simple question about Hartree-Fock algorithm" Tags="|hartree-fock|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9273" PostTypeId="1" CreationDate="2022-06-19T21:53:11.857" Score="11" ViewCount="150" Body="&lt;p&gt;I'm working with an amorphous system. With oxygen, my system has both covalent and ionic bond forming cations. I utilise the Wannier centre approach to define a covalent bond, and my theory is that if the Wannier centre is near to the line connecting the cation and anion, it is a covalent bond.&lt;/p&gt;&#xA;&lt;p&gt;However, this method fails to identify an ionic bond as there is no region of high electronic charge density which can be localized to obtain Wannier center. How can an ionic bond be defined using a computational technique?&lt;/p&gt;&#xA;&lt;p&gt;Let's imagine I have an AO2 system in which A is known to form a covalent bond. When we add the modifier B2O, we get a binary glass. Now, if no minima can be found using the Pair distribution function, how should I analyse the local environment, such as the coordination number of B cation?&lt;/p&gt;&#xA;" OwnerUserId="5590" LastActivityDate="2022-06-19T21:53:11.857" Title="How to define a chemical bond computationally?" Tags="|density-functional-theory|computational-chemistry|ab-initio-calculations|amorphous-materials|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-06T19:56:02.440" ContentLicense="CC BY-SA 4.0" />
  <row Id="9274" PostTypeId="1" CreationDate="2022-06-20T05:22:06.223" Score="3" ViewCount="46" Body="&lt;p&gt;What are the basic steps and methodologies used in creating inter-atomic force field potential for CHARMM/Amber style for energetic materials with the help of DFT? What are the best possible free tools available for the task?&lt;/p&gt;&#xA;" OwnerUserId="5591" LastEditorUserId="7" LastEditDate="2022-06-21T15:12:43.267" LastActivityDate="2022-06-21T15:12:43.267" Title="Creating Amber/CHARMM style force field potential for energetic materials using DFT" Tags="|density-functional-theory|molecular-dynamics|forcefields|charmm|amber|" AnswerCount="0" CommentCount="3" ClosedDate="2023-01-22T19:49:57.893" ContentLicense="CC BY-SA 4.0" />
  <row Id="9275" PostTypeId="1" AcceptedAnswerId="9327" CreationDate="2022-06-20T06:24:55.043" Score="6" ViewCount="104" Body="&lt;p&gt;How to effectively plot an octahedron along with the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals of the metal atom at the center of the octahedron? Here is &lt;a href=&quot;https://commons.wikimedia.org/wiki/File:D_orbitals_in_an_octahedron.jpg&quot; rel=&quot;noreferrer&quot;&gt;an example&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/t56nem.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/t56nem.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What kind of software can be used to draw this illustration? I'm not sure whether this question is suitable for this site, but I think it is related to presentation of results in matter modeling. If there is a more suitable site for this question, please tell me.&lt;/p&gt;&#xA;" OwnerUserId="1483" LastActivityDate="2022-07-04T06:37:30.190" Title="A question about plotting: how to plot octahedrons as well as d orbitals effectively?" Tags="|visualization-software|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9276" PostTypeId="1" AcceptedAnswerId="9277" CreationDate="2022-06-21T08:11:00.863" Score="4" ViewCount="324" Body="&lt;p&gt;I am using VASP to perform a structural relaxation of &lt;span class=&quot;math-container&quot;&gt;$\ce{CuNCN}$&lt;/span&gt;. I am using the PAW-PBE POTCAR files for the same and the KPOINTS have been generated using a script. The POSCAR file has been generated from the CIF file obtained via PXRD measurements. Even after multiple iterations (using the CONTCAR as POSCAR in subsequent calculations), the CONTCAR data is nowhere close to my POSCAR data, i.e. the structure is relaxing to an incorrect energy minimum. Note that I am using the DFT-D3 dispersion scheme for the optimization. In the literature, dispersion has been employed for &lt;span class=&quot;math-container&quot;&gt;$\ce{PbNCN}$&lt;/span&gt;, which has a similar layered structure.&lt;/p&gt;&#xA;&lt;p&gt;My POSCAR structure:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/DHM0M.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DHM0M.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My CONTCAR structure (After 5 runs):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/d4swU.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/d4swU.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;ICHARG = 2&#xA;PREC = Accurate&#xA;ISIF = 3&#xA;IBRION = 2&#xA;EDIFF = 0.00000001&#xA;EDIFFG = -0.0005&#xA;NSW = 200&#xA;NELM = 100&#xA;ENCUT = 400&#xA;PSTRESS = 0&#xA;IVDW = 12&#xA;ISMEAR = 0&#xA;SIGMA = 0.1&#xA;ISYM = 1&#xA;LMAXMIX = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3561" LastEditorUserId="7" LastEditDate="2022-06-21T15:11:18.080" LastActivityDate="2022-06-23T00:56:42.207" Title="VASP structure relaxes to an incorrect ground state" Tags="|density-functional-theory|vasp|cell-optimization|" AnswerCount="2" CommentCount="0" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9277" PostTypeId="2" ParentId="9276" CreationDate="2022-06-21T14:42:05.220" Score="3" Body="&lt;p&gt;This still looks okay to me, the bonds you see in VESTA are not real in the sense that they don't mean a covalent bond exists.  There may be some weak bonding between layers (Are you certain this material forms this structure exact or is it something you propose?).  The bond lengths between layers look very long, so I would not overthink it.&lt;/p&gt;&#xA;&lt;p&gt;The only other option I can think of is to check if other functionals produce the same &amp;quot;incorrect&amp;quot; structure at the end.  I don't see you specifying a particular functional, so it will default to LDA.  PBE and PBEsol might be good checks to see if this happens still.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-06-21T14:42:05.220" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9278" PostTypeId="2" ParentId="9272" CreationDate="2022-06-21T16:24:15.910" Score="1" Body="&lt;p&gt;Actually, it does sometimes.&#xA;If you remember that HF scheme is to solve the pseudo-eigenvalue-eigenvector problem, the equation is FC=SCE where F is the Fock matrix and the C is the molecular orbital coefficient as shown in your equation.&#xA;For a crude assumption, the initial Fock matrix can be the summation of the kinetic T and external potential V which is often referred core-hamiltonian H (all operators here are represented as the atomic orbital basis).&#xA;For H, the only thing you need is the atomic orbital basis set information, and the initial C can be guessed with this H matrix.&#xA;In your comment &amp;quot;matrix C is a square matrix&amp;quot;, I think this is because the program deleted the unoccupied coefficient information for the sake of calculating the density matrix D. When making D, the occupation number is also multiplied there and, since the unoccupied occupation number is 0, coefficient matrix often treated like that.&lt;/p&gt;&#xA;" OwnerUserId="790" LastActivityDate="2022-06-21T16:24:15.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9280" PostTypeId="1" CreationDate="2022-06-21T21:04:46.510" Score="2" ViewCount="1927" Body="&lt;p&gt;I have been working with a material in which Cu has an unpaired electron due to which the material can exist in various magnetic configurations. I wish to see how various properties change as I switch between Antiferromagnetic and ferromagnetic configurations. Due to this I have been running spin polarized calculations and have been setting MAGMOM tag accordingly.&lt;/p&gt;&#xA;&lt;p&gt;Till now my MAGMOM tag looked something like &lt;code&gt;MAGMOM = 16*0 8*0 2 -2 2 -2 32*0&lt;/code&gt; where I was assigning 0 to all the atoms which did not have unpaired electrons and &lt;code&gt;-2&lt;/code&gt; and &lt;code&gt;2&lt;/code&gt; based on the configuration. The final magnetization obtained can be seen below where 25,26,27 and 28 are actually Cu atoms and the atoms which are directly bonded to them also posses some magnetic moment as can be seen below(I confirmed that these are the molecules bonded with Cu only due to which we observe polarization)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gp58p.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gp58p.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For different magnetic configurations we vary the initial magnetic moment of Cu atoms, but what about the atoms which do not possess any unpaired electrons??&lt;/p&gt;&#xA;&lt;p&gt;Speaking from a theoretical point of view the spin up and down should cancel each others so should we take the initial magnetic moment(which is specified by MAGMOM tag in vasp) to be equal to zero when no unpaired electrons can be found for example - Sb +3.&lt;/p&gt;&#xA;&lt;p&gt;My main question is that - Should we take the initial magnetic moment = 0 for atoms with unpaired electrons.&lt;/p&gt;&#xA;&lt;p&gt;Some pointers to take into consideration:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The material is quite new so I do not have any experimental data about magnetic moments&lt;/li&gt;&#xA;&lt;li&gt;If we take the spins of all the atoms into consideration we will have to analyse a lot more anti ferro and ferro magnetic configurations into account than have been described in earlier works(they only talk about varying the spin of Cu)&lt;/li&gt;&#xA;&lt;li&gt;I tried using some different MAGMOMs by giving initial magnetic moments to atoms with unpaired electrons but the calculation failed and in a similar fashion as has been described &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?t=18458&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-06-23T19:52:42.580" LastActivityDate="2022-06-23T21:12:57.707" Title="Setting MAGMOM in VASP for possible Magnetic configurations" Tags="|vasp|magnetism|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-06T19:56:32.980" ContentLicense="CC BY-SA 4.0" />
  <row Id="9281" PostTypeId="1" CreationDate="2022-06-22T01:54:36.517" Score="4" ViewCount="144" Body="&lt;p&gt;I am interested in quantifying the coordination number of some atoms in metals and am curious what approaches to defining a coordination number are possible for an atom.  In particular, I am curious if there are any continuous coordination number approaches that do not result in a hard change 12 to 11 for example when an atom moves just outside of the coordination shell.&lt;/p&gt;&#xA;&lt;p&gt;It seems like the generalized coordination number solves this issue to some degree, but it is unclear to me if there are any better approaches.  One requirement of this approach is that each atom should have its own coordination number assigned and not be an average value over the entire structure (as is seen in some liquid definitions).&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="1554" LastEditDate="2024-01-09T23:41:41.563" LastActivityDate="2024-01-10T09:09:30.877" Title="Continuous Coordination Number Definition" Tags="|crystallography|atomic-simulation-environment|metals|coordination|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9282" PostTypeId="1" CreationDate="2022-06-22T13:00:15.183" Score="4" ViewCount="127" Body="&lt;p&gt;In continuation of the question of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9245/can-the-electrical-conductivity-tensor-of-a-crystal-be-obtained-from-a-hartree-f&quot;&gt;obtaining an electrical conductivity tensor (ECT) from the “first characteristics”&lt;/a&gt;, will my following suggestion be correct? Since a crystal with an applied-to-it constant external electric field is known to be able to give a nonlinear current-voltage characteristic, then if a goal is to obtain ECT at different voltages applied to a crystal then this circumstance must be taken into account in the Hartree–Fock (or Kohn–Sham) equation such a way that an additional term defining a constant external electric field should be included into the equation.&lt;/p&gt;&#xA;&lt;p&gt;Thus in order to obtain ECT for one single voltage applied to a crystal, there must be required one solution of the equation, for another voltage – another solution, and so on.&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5403" LastEditDate="2022-06-23T23:28:49.480" LastActivityDate="2022-06-23T23:28:49.480" Title="Is it possible to obtain the current-voltage characteristic for a crystal using the Hartree–Fock (or DFT) calculation?" Tags="|density-functional-theory|ab-initio-calculations|hartree-fock|electronic-transport|electric-field|" AnswerCount="0" CommentCount="6" ClosedDate="2023-02-07T03:03:07.773" ContentLicense="CC BY-SA 4.0" />
  <row Id="9283" PostTypeId="1" CreationDate="2022-06-22T14:14:43.813" Score="2" ViewCount="592" Body="&lt;p&gt;I need to make this transformation because I need to grow up my unit cell using a code with Python. But, I'm studying it yet and I need some help.&lt;/p&gt;&#xA;" OwnerUserId="5608" LastEditorUserId="85" LastEditDate="2022-07-07T03:56:27.790" LastActivityDate="2022-07-07T03:56:27.790" Title="How to transform fractional coordinates into cartesian?" Tags="|python|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9284" PostTypeId="1" AcceptedAnswerId="9285" CreationDate="2022-06-22T18:27:49.380" Score="5" ViewCount="154" Body="&lt;p&gt;Looking at some historical data about water, I noticed that people were determining bond angles from infrared spectra. How is this done? Aside from having a bunch of absorption frequencies indicating the modes?&lt;/p&gt;&#xA;" OwnerUserId="5321" LastActivityDate="2022-06-22T20:58:02.383" Title="Determining bond angle from infrared spectra?" Tags="|molecular-dynamics|spectroscopy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9285" PostTypeId="2" ParentId="9284" CreationDate="2022-06-22T20:58:02.383" Score="4" Body="&lt;p&gt;&lt;strong&gt;This is done the same way that &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1690/5&quot;&gt;bond length is determined from infrared spectra&lt;/a&gt;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;We fit the spectra to a potential energy surface (PES), such that when the PES is fed through the Schroedinger equation, the differences in eigenvalues  correspond as closely as possible to the energies of the spectral lines. The parameters of the PES are changed at each iteration until the fit to the spectral energies no longer improves significantly. The bond angles, bond lengths, and atomization energies are usually &lt;strong&gt;parameters&lt;/strong&gt; of the PES model, so fitted values for them (along with their uncertainties) are obtained quite &lt;strong&gt;directly&lt;/strong&gt; (for this reason, &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853&quot; rel=&quot;nofollow noreferrer&quot;&gt;the procedure is often called a &lt;strong&gt;Direct&lt;/strong&gt; Potential Fit or DPF&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-06-22T20:58:02.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9286" PostTypeId="2" ParentId="9276" CreationDate="2022-06-23T00:56:42.207" Score="1" Body="&lt;p&gt;Two structures of POSCAR and CONTCAR you show are the same. When you open VESTA, you choose Edit --&amp;gt; Bond, then you edit a same Max. length. VESTA would show the same.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2022-06-23T00:56:42.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9287" PostTypeId="1" AcceptedAnswerId="9322" CreationDate="2022-06-23T02:46:38.937" Score="6" ViewCount="557" Body="&lt;p&gt;I want to study the properties of thin films using DFT calculation. I have done the bulk crystal calculations in Quantum ESPRESSO but have no idea how can I construct the thin film of desired thickness. What changes do I have to make in PWscf input file. Please help me with how can I do this.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2023-05-31T01:07:59.657" Title="How to construct thin film structure of desired thickness in quantum espresso?" Tags="|density-functional-theory|quantum-espresso|2d-lattice|supercell|monolayer|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9288" PostTypeId="1" CreationDate="2022-06-23T12:48:47.293" Score="6" ViewCount="2493" Body="&lt;p&gt;Is there a way  to show the orientation axis in Pymol?&lt;/p&gt;&#xA;&lt;p&gt;It's something like this in VMD. I much prefer Pymol rendering.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XXci5l.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XXci5l.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4475" LastActivityDate="2023-06-24T11:09:42.557" Title="How to show orientation axis in Pymol" Tags="|proteins|vmd|structural-biology|pdb|pymol|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9289" PostTypeId="2" ParentId="9288" CreationDate="2022-06-23T15:03:11.733" Score="5" Body="&lt;p&gt;As far as I know, there is no built in way to display the coordinate vectors. Fortunately, on the PyMOLWiki I was able to find &lt;a href=&quot;https://pymolwiki.org/index.php/Axes&quot; rel=&quot;noreferrer&quot;&gt;a page with a number of scripts you can use to do this&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5167" LastActivityDate="2022-06-23T15:03:11.733" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9290" PostTypeId="1" CreationDate="2022-06-24T00:34:55.910" Score="7" ViewCount="141" Body="&lt;p&gt;I am a high schooler and a part-time programmer. I want to become a material scientist. I am looking for a gentle introduction to Material Modelling and Materials Science, preferably at a high school or undergraduate level.&lt;/p&gt;&#xA;" OwnerUserId="5617" LastEditorUserId="6468" LastEditDate="2023-03-03T22:44:42.170" LastActivityDate="2023-03-03T22:44:42.170" Title="How to gain an understanding of Material Science topics?" Tags="|quantum-chemistry|python|" AnswerCount="0" CommentCount="8" ClosedDate="2023-03-03T22:49:42.673" ContentLicense="CC BY-SA 4.0" />
  <row Id="9292" PostTypeId="1" AcceptedAnswerId="9300" CreationDate="2022-06-24T09:36:32.743" Score="6" ViewCount="157" Body="&lt;p&gt;The Hall conductivity is given by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{xy}^{2D}=\frac{e^2}{\hbar} \int \frac{d\vec{k}}{(2\pi)^d} f(\epsilon(\vec{k}))\Omega_{k_xk_y} \tag{1} $$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the Fermi distribution function and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; the Berry curvature.&#xA;If we write the Berry curvature in terms of the Berry vector potential and integrate Eq.&lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; by part, one finds&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{xy}^{2D}=\frac{e^2}{\hbar} \int \frac{d\vec{k}}{(2\pi)^d} &#xA;\left( \frac{\partial f}{\partial k_y} \mathcal{A}_{k_x}-\frac{\partial f}{\partial k_x} \mathcal{A}_{k_y} \right) \tag{2}.$$&lt;/span&gt;&#xA;Note that the Fermi distribution function &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is a step function at the Fermi energy.&#xA;If we assume the Fermi surface is a closed loop in the Brillouin zone, then we have:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{xy}^{2D}=\frac{e^2}{2\pi\hbar}\oint d\vec{k}\cdot\vec{\mathcal{A}} \tag{3}.$$&lt;/span&gt;&#xA;The integral is nothing but the Berry phase along the Fermi circle in the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;My question is how to derive the formula Eq.&lt;span class=&quot;math-container&quot;&gt;$(3)$&lt;/span&gt; from Eq.&lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt;? One can get the Eq.&lt;span class=&quot;math-container&quot;&gt;$(3)$&lt;/span&gt;&#xA;from Eq.&lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; by Stokes theorem.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="671" LastEditDate="2022-06-27T02:34:24.787" LastActivityDate="2022-06-27T02:41:17.877" Title="How to transform the two-dimensional Berry curvature integral into a loop integral along Fermi circle?" Tags="|berry-phase|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9293" PostTypeId="2" ParentId="6486" CreationDate="2022-06-24T18:14:57.637" Score="4" Body="&lt;p&gt;If you want to achieve this using VESTA you can follow what Shahid said in his answer but you have to keep in mind how lattice vectors are defined in VESTA which in turn will change the rotation matrix. For example I show here an unit cell of TaS2, notice how a and b vectors are defined on the lower left corner&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rPWfd.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rPWfd.jpg&quot; alt=&quot;TaS2 unit cell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then look at the left side of the transformation matrix option in VESTA, se how they are defined, which matrix element are getting multiplied with which lattice vector.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TP7Ir.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TP7Ir.png&quot; alt=&quot;VESTA transformation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So the correct matrix for VESTA would be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{bmatrix}1&amp;amp;1&amp;amp;0\\-1&amp;amp;2&amp;amp;0\\0&amp;amp;0&amp;amp;1\end{bmatrix}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which will give you the correct root3 x root3 x 1 supercell&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZcV30.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZcV30.jpg&quot; alt=&quot;TaS2 root3 x root3 x 1 supercell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5621" LastActivityDate="2022-06-24T18:14:57.637" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9295" PostTypeId="1" CreationDate="2022-06-25T10:18:44.350" Score="6" ViewCount="144" Body="&lt;p&gt;I want to build unit cells for Pd surface oxide models, but I am not sure how to begin as I am new to using VESTA. On Pd(100), the most stable surface oxide structure is √5x√5 R27o. On Pd(111), the most stable structure involves a √6x√7 arrangement of O atoms with a Pd4O5 stoichiometry. Does anyone have any suggestions for the best way to model such structures? Thank you!&lt;/p&gt;&#xA;" OwnerUserId="5625" LastActivityDate="2022-07-28T07:18:38.400" Title="Modelling Pd(111) and Pd(100) Surface Oxides Through VESTA" Tags="|molecular-modeling|vesta|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9296" PostTypeId="2" ParentId="9232" CreationDate="2022-06-26T15:23:15.360" Score="3" Body="&lt;p&gt;I think you can use yambo-code to calculate the temperature dependent correction to the electronic states from your ground state DFT calculation and in turn get the quasi-particle band structure and band gap at a finite temperature.&lt;/p&gt;&#xA;&lt;p&gt;Take a look at their wiki page for electron-phonon coupling:&#xA;&lt;a href=&quot;https://www.yambo-code.eu/wiki/index.php/Electron_Phonon_Coupling&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.yambo-code.eu/wiki/index.php/Electron_Phonon_Coupling&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5621" LastActivityDate="2022-06-26T15:23:15.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9297" PostTypeId="2" ParentId="9295" CreationDate="2022-06-26T17:20:36.070" Score="0" Body="&lt;p&gt;This doesn't exactly answer your question but I'd recommend using one of the following Python modules instead of VESTA for surface creation: &lt;a href=&quot;https://pymatgen.org/pymatgen.core.surface.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyMatGen&lt;/a&gt; or &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="4776" LastActivityDate="2022-06-26T17:20:36.070" CommentCount="1" CommunityOwnedDate="2022-07-27T11:26:01.847" ContentLicense="CC BY-SA 4.0" />
  <row Id="9298" PostTypeId="2" ParentId="9272" CreationDate="2022-06-26T19:11:32.067" Score="6" Body="&lt;p&gt;The question is confusing two things: the linear combination of atomic orbitals (LCAO) scheme where the molecular orbitals are expanded as a sum of the atomic orbitals&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\psi_{i\sigma} ({\bf r}) = \sum_{\alpha} C_{\alpha i} \chi_\alpha ({\bf r}) \label{eq:lcao}&#xA;\end{equation}&lt;/span&gt;&#xA;and the actual definition for the atomic basis functions, which in the case of contracted Gaussian basis functions is&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\chi_\alpha ({\bf r}) = r^{l_\alpha} \left[\sum_{k} d_{k \alpha} \exp(-\zeta_kr^2)\right] Y_{l_\alpha}^{m_\alpha}(\hat{\bf r})&#xA;\end{equation}&lt;/span&gt;&#xA;where I have assumed a pure spherical basis for ease of notation. The LCAO scheme is not limited to Gaussian basis sets; the linear expansion ansatz is used in every basis set method, regardless of the nature of the basis functions (e.g. Gaussian or Slater-type orbital, numerical atomic orbital, plane waves, finite elements, etc). I have recently written two open access review articles on these topics, see &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25968 (2019)&lt;/a&gt; for discussion on various kinds of basis functions and &lt;a href=&quot;https://doi.org/10.3390/molecules25051218&quot; rel=&quot;noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt; for the self-consistent field algorithm.&lt;/p&gt;&#xA;&lt;p&gt;It is true that the contracted functions in many basis sets such as the cc-pVXZ basis sets represent occupied atomic orbitals in Hartree-Fock calculations. However, this is not true for all basis sets. As programs tend to aim for generality, they typically aim to implement initial guesses that are not basis set dependent, such as the superposition of atomic densities - which is equivalent to occupying the contracted functions in certain basis sets but also works for basis sets where the individual basis functions do not look like occupied orbitals. Refer to &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 1593 (2019)&lt;/a&gt; for further discussion on initial guesses.&lt;/p&gt;&#xA;&lt;p&gt;I would like to note that unlike stated in the comments, the matrix &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; is not square in general; this is unfortunately still a very common misconception in computational chemistry. There are often linear dependencies in the basis set (e.g. a basis function on one atom can be also well-described by the sum of basis functions on the neighboring atoms), and removing them removes some columns from &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt;. Stereotypical cases of this happening are when you use diffuse functions that are needed to describe long-range interactions and weakly bound electrons, or when two nuclei are close together. However, &lt;a href=&quot;https://doi.org/10.1063/1.5139948&quot; rel=&quot;noreferrer&quot;&gt;even such pathological linear dependencies can be cured&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.101.032504&quot; rel=&quot;noreferrer&quot;&gt;Coulomb barriers to nuclear fusion modeled&lt;/a&gt; when suitable numerical algorithms are chosen to pick a suitable sub-basis (see the links). The choice of the linearly independent basis is also discussed in the overview on SCF theory linked above.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-06-26T19:11:32.067" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9299" PostTypeId="1" AcceptedAnswerId="10175" CreationDate="2022-06-27T01:54:59.787" Score="8" ViewCount="186" Body="&lt;p&gt;I performed DFT calculations for a box of 64 water molecules under Periodic Boundary Condition using CP2K. I found that the forces on each atom do not sum up to zero, as shown in the attached figure. But the total force should be zero due to translational symmetry of the system. Any idea of what happened?&lt;/p&gt;&#xA;&lt;p&gt;I used revPBE functional with TZV2P basis set.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pxAMJ.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pxAMJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5532" LastEditorUserId="5" LastEditDate="2023-01-01T15:05:27.453" LastActivityDate="2023-01-01T15:05:27.453" Title="Total force calculated with cp2k not zero" Tags="|density-functional-theory|cp2k|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9300" PostTypeId="2" ParentId="9292" CreationDate="2022-06-27T02:34:30.497" Score="4" Body="&lt;p&gt;If the distribution function has a step discontinuity at the Fermi surface, its derivatives are Dirac delta functions which reduce the integral to one over the Fermi surface. I will illustrate this for the simple case of a 2D system with a rectangular Fermi surface, but the full argument for 2D and 3D can be found in Haldane's &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.93.206602&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. Lett. &lt;strong&gt;93&lt;/strong&gt;, 206602 (2004)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/0408417&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;]. A related paper is X. Wang, D. Vanderbilt, J. R. Yates and I. Souza's &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.76.195109&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. B 76, 195109 (2009)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/0708.0858&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;]. (The rectangle is topologically equivalent to the circle, but makes it easy to work with an explicit coordinate system, thus making the problem concrete.)&lt;/p&gt;&#xA;&lt;p&gt;We start with your Eq. (2),&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{xy}^{2D}=\frac{e^2}{\hbar} \int \frac{d\vec{k}}{(2\pi)^2} &#xA;\left( \frac{\partial f}{\partial k_y} \mathcal{A}_{k_x}-\frac{\partial f}{\partial k_x} \mathcal{A}_{k_y} \right) \tag{4}.$$&lt;/span&gt;&#xA;Now, assume a rectangular distribution function. A simple way to write one is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;f = \left[ \theta \left( k_x \right) - \theta \left( k_x -k_{\mathrm{F},x} \right) \right] \left[ \theta \left( k_y \right) - \theta \left( k_y -k_{\mathrm{F},y} \right) \right], \tag{5}&#xA;$$&lt;/span&gt;&#xA;which is constant and equal to 1 in the crosshatched area of the figure below, and vanishes outside it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ffuNF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ffuNF.png&quot; alt=&quot;Rectangular Fermi surface and integral contours&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It of course follows that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial f}{\partial k_x} = \left[ \delta \left( k_x \right) - \delta \left( k_x -k_{\mathrm{F},x} \right) \right] \left[ \theta \left( k_y \right) - \theta \left( k_y -k_{\mathrm{F},y} \right) \right], \tag{6}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial f}{\partial k_y} = \left[ \theta\left( k_x \right) - \theta\left( k_x -k_{\mathrm{F},x} \right) \right] \left[ \delta\left( k_y \right) - \delta \left( k_y -k_{\mathrm{F},y} \right) \right]. \tag{7}&#xA;$$&lt;/span&gt;&#xA;Substituting these expressions into (4) and carrying out integrals over the Delta functions we obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{xy}^{2D}=\frac{e^2}{\hbar} \int \frac{dk_x}{\left( 2\pi\right)^2} \left[ \theta \left( k_x \right) - \theta \left( k_x -k_{\mathrm{F},x} \right) \right] \left[ \mathcal{A}_{k_x}|_{k_y=0} - \mathcal{A}_{k_x}|_{k_y=k_{\mathrm{F},y}} \right]\\&#xA;- \frac{e^2}{\hbar} \int \frac{dk_y}{\left( 2\pi\right)^2} \left[ \theta \left( k_y \right) - \theta \left( k_y -k_{\mathrm{F},y} \right) \right] \left[ \mathcal{A}_{k_y}|_{k_x=0} - \mathcal{A}_{k_y}|_{k_x=k_{\mathrm{F},x}} \right], \tag{8}$$&lt;/span&gt;&#xA;where the notation &lt;span class=&quot;math-container&quot;&gt;$f|_{x=0}$&lt;/span&gt; indicates that &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is evaluated at &lt;span class=&quot;math-container&quot;&gt;$x=0$&lt;/span&gt;. Now it is just a matter of identifying the different terms with different paths in the figure, which yields&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma_{xy}^{2D}=\frac{e^2}{\hbar} \left[ \int_{\Gamma_1} \mathcal{A}_{k_x} dk_x + \int_{\Gamma_2} \mathcal{A}_{k_y} dk_y + \int_{\Gamma_3} \mathcal{A}_{k_x} dk_x + \int_{\Gamma_4} \mathcal{A}_{k_y} dk_y \right]. \tag{9}&#xA;$$&lt;/span&gt;&#xA;Since &lt;span class=&quot;math-container&quot;&gt;$\Gamma=\Gamma_1+\Gamma_2+\Gamma_3+\Gamma_4$&lt;/span&gt; is a closed contour we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma_{xy}^{2D}=\frac{e^2}{\hbar \left( 2\pi\right)^2} \oint_\Gamma \vec{\mathcal{A}} \cdot \vec{dk}, \tag{10}$$&lt;/span&gt;&#xA;which matches your Eq. (3) up to a factor of &lt;span class=&quot;math-container&quot;&gt;$2\pi$&lt;/span&gt;, and agrees with Haldane's result in the article mentioned above. Finding the source of this discrepancy is left as an exercise.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2022-06-27T02:41:17.877" LastActivityDate="2022-06-27T02:41:17.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9301" PostTypeId="1" CreationDate="2022-06-27T11:26:30.307" Score="2" ViewCount="57" Body="&lt;p&gt;I want to read a PDB file and display/render the atoms using a graphics engine.&lt;/p&gt;&#xA;&lt;p&gt;If I consider each residue in the protein file as a solid sphere, what would be the radius of the sphere?&lt;/p&gt;&#xA;&lt;p&gt;How can I calculate it? Or, is there any database for that?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-06-27T12:36:24.440" LastActivityDate="2022-06-27T12:36:24.440" Title="How can I calculate the radius of a residue?" Tags="|proteins|protein-folding|" AnswerCount="0" CommentCount="2" ClosedDate="2023-01-04T00:14:25.623" ContentLicense="CC BY-SA 4.0" />
  <row Id="9302" PostTypeId="1" CreationDate="2022-06-27T11:28:19.467" Score="5" ViewCount="416" Body="&lt;p&gt;I'm using DFT+&lt;em&gt;U&lt;/em&gt; implemented in VASP to calculate the electronic density of states of anatase TiO2.&lt;/p&gt;&#xA;&lt;p&gt;In order to more accurately reproduce the experimental bandgap of anatase TiO2 (as compared to standard PBE functional), a &lt;em&gt;U&lt;/em&gt; value of 4 eV was applied to the Ti &lt;em&gt;d&lt;/em&gt; orbital by adding the settings below to a standard INCAR file (the first atomic species in POSCAR is Ti, and the second one is O)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# DFT+U Calculation&#xA; LDAU   = TRUE&#xA; LDATYPE=  2&#xA; LDAUL  =  2 -1&#xA; LDAUU  =  4 0&#xA; LDAUJ  =  0 0&#xA; LMAXMIX=  4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the as obtained DFT+&lt;em&gt;U&lt;/em&gt; results seems to be incorrect. From the density of states as shown in the figure,&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FvB9q.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FvB9q.png&quot; alt=&quot;dos&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;rather than the Ti &lt;em&gt;d&lt;/em&gt; orbital on which the &lt;em&gt;U&lt;/em&gt; value is applied, it is the Ti &lt;em&gt;s&lt;/em&gt; and &lt;em&gt;p&lt;/em&gt; orbitals that are pushed to lower energy values. &lt;strong&gt;More confusingly, the energy values of Ti &lt;em&gt;d&lt;/em&gt; bonding orbitals barely changes, while the anti-bonding Ti &lt;em&gt;d&lt;/em&gt; orbitals are shifted to higher energy values.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why this happens?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastEditorUserId="1483" LastEditDate="2022-06-28T08:20:36.720" LastActivityDate="2022-06-29T11:39:39.660" Title="VASP DFT+U on Ti d orbital, why d orbitals are not affected but s and p orbitals are pushed lower?" Tags="|density-functional-theory|vasp|" AnswerCount="0" CommentCount="8" ClosedDate="2023-02-10T03:07:19.860" ContentLicense="CC BY-SA 4.0" />
  <row Id="9304" PostTypeId="1" CreationDate="2022-06-28T15:21:05.017" Score="2" ViewCount="116" Body="&lt;p&gt;I am trying to generate the &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}\times\sqrt{3}R30^\circ$&lt;/span&gt; representation of a Pt111 slab, I start by generating the &lt;span class=&quot;math-container&quot;&gt;$1\times1$&lt;/span&gt; using ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atoms = fcc111(&amp;quot;Pt&amp;quot;, size=(1, 1, 5), vacuum=20, orthogonal=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I apply a matrix transformation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;transformation_matrix = [[math.sqrt(3)*math.cos(math.pi/6), math.sqrt(3)*math.sin(math.pi/6), 0], [-math.sqrt(3)*math.sin(math.pi/6), math.sqrt(3)*math.cos(math.pi/6), 0], [0, 0, 1]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which gives the right unit cell when done manually using np.matmul. Now I use the make_supercell functional of ASE, but it gives me a weird unit cell:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;np.matmul(atoms.cell, transformation_matrix) = [[4.20477064e+00 2.42762546e+00 0.00000000e+00] [5.35035667e-16 4.85525092e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00 4.00000000e+01]]&#xA;&#xA;ase.build.make_supercell(atoms, transformation_matrix) = [5.418583372710122, 2.1023853208798973, 0.0] [-0.3252401410207554, 3.6414381928509796, 0.0] [0.0, 0.0, 40.0]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And thus the structure given by ASE is wrong, is this a bug, or am I missing something?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2022-06-28T15:21:05.017" Title="Slab rotation with ASE, unexpected behaviour" Tags="|crystallography|surfaces|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-06T19:55:33.370" ContentLicense="CC BY-SA 4.0" />
  <row Id="9305" PostTypeId="1" CreationDate="2022-06-28T15:58:35.607" Score="2" ViewCount="102" Body="&lt;p&gt;I want to replicate &lt;a href=&quot;https://www.mdpi.com/2073-4352/9/10/497&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, but somehow I cannot get the same results, most important as shown in table 2. Can anyone help me with this?&lt;/p&gt;&#xA;&lt;p&gt;I have attached the INCAR file. If any correction is needed, please suggest them.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INCAR file tags&#xA;SYSTEM = YBa2Cu3O7&#xA;   ISTART = 0&#xA;   ICHARG = 2&#xA;   EDIFF  = 0.1E-4&#xA;   EDIFFG = -0.001&#xA;   ENCUT = 500&#xA;   ISIF = 3&#xA;   ISMEAR =  0&#xA;   SIGMA = 0.1&#xA;&#xA;   IBRION = 1&#xA;  POTIM = 0.5&#xA;   NSW  = 500&#xA;   &#xA;   PSTRESS = 0&#xA;   ISPIN = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="7" LastEditDate="2022-06-28T16:48:21.337" LastActivityDate="2022-06-28T16:48:21.337" Title="study of elastic properties under pressure using VASP" Tags="|density-functional-theory|vasp|quantum-espresso|physical-properties-of-materials|elasticity|" AnswerCount="0" CommentCount="7" ClosedDate="2023-02-07T02:36:33.547" ContentLicense="CC BY-SA 4.0" />
  <row Id="9306" PostTypeId="1" CreationDate="2022-06-28T18:59:52.600" Score="3" ViewCount="460" Body="&lt;p&gt;I am planning to use HSEO6 to calculate the band structure and DOS of a perovskite super cell. My cell has about 80 atoms. Furthermore I have also used dispersion correction and I will also have to use SOC for heavy metals.&lt;/p&gt;&#xA;&lt;p&gt;I have tried playing with ALGO = All/Damped and TIME, but still the calculations are very slow, due to some reason the calculations tend to slow down after 6-7 iterations. So much so that one iteration takes atleast 5-6 hours.&lt;/p&gt;&#xA;&lt;p&gt;Are there any other things that I can try out which could help me speed up the calculations.&lt;/p&gt;&#xA;&lt;p&gt;P.S I have tried running calculations without dispersion correction and they tend to move a lot faster, but even with dispersion correction the DOS calculation took days to end, even after that it did not converge. What should I do ? Should I change the Exchange correlational functional ??&lt;/p&gt;&#xA;&lt;p&gt;Any advice is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2022-06-28T18:59:52.600" Title="Tips for using Hybrid Functionals in VASP" Tags="|vasp|functional|" AnswerCount="0" CommentCount="5" ClosedDate="2023-02-07T02:36:26.903" ContentLicense="CC BY-SA 4.0" />
  <row Id="9307" PostTypeId="1" CreationDate="2022-06-29T01:05:08.047" Score="9" ViewCount="124" Body="&lt;p&gt;I have developed a Python tool that extracts the plane wave coefficients and Gvectors from a &lt;code&gt;WAVECAR&lt;/code&gt; file and I'm able to get the real space wavefunction for that particular Bloch state with a Fourier transform.&lt;/p&gt;&#xA;&lt;p&gt;I want to be able to get the wavefunction and/or plane wave coefficients for a symmetrically related kpoint in the 1st BZ. The &lt;code&gt;WAVECAR&lt;/code&gt; only contains Bloch states from an irreducible region if the ISYMM parameter is &amp;gt; 0, hence wanting to re-expand this set to the whole BZ.&lt;/p&gt;&#xA;&lt;p&gt;The documentation for another DFT software, ABINIT outlines the following relationships:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon_{\mathbf{Rk}} = \epsilon_{\mathbf{k}}\tag{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$u_{\mathbf{Rk}}(\mathbf{r}) = u_{\mathbf{k}}(\mathbf{R^{-1}r})\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is the energy eignenvalue, &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{k}}(\mathbf{r})$&lt;/span&gt; is the Bloch-periodic part of the wavefunction at Bloch state (&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;), &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; is some operation matrix. I have tried implenting this relationship where I get a set of &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; operators from the space group of the BZ. The implementation fails on the first test, where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}$&lt;/span&gt; corresponds to the time-inversion operator (i.e. &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}=-\mathbf{I}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;At first I thought it was my code (it possible still is!), but after looking at the above relationships, if we substitute &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}=-\mathbf{I}$&lt;/span&gt; into &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{Rk}}(\mathbf{r}) = u_{\mathbf{k}}(\mathbf{R^{-1}r})$&lt;/span&gt;, we get:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$u_{\mathbf{-k}}(\mathbf{r}) = u_{\mathbf{k}}(\mathbf{-r})\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(since &lt;span class=&quot;math-container&quot;&gt;$(-\mathbf{I})^{-1}=-\mathbf{I}$&lt;/span&gt;)&lt;/p&gt;&#xA;&lt;p&gt;I was under the understanding that for time inversion symmetry,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$u_{\mathbf{-k}}(\mathbf{r}) = u^{\dagger}_{\mathbf{k}}(\mathbf{r})\tag{4}$$&lt;/span&gt;&#xA;which would only hold in this case if &lt;span class=&quot;math-container&quot;&gt;$u_{\mathbf{k}}(\mathbf{r})$&lt;/span&gt; has even symmetry in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; for the real part and odd for the imaginary.&lt;/p&gt;&#xA;&lt;p&gt;I'm not convinced this is the case for all wavefunctions.&#xA;Furthermore, if we apply this operation to the zone centred wavefunction (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{k=0}$&lt;/span&gt;), we get:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$u_{\mathbf{k}}(\mathbf{r}) = u_{\mathbf{k}}(\mathbf{-r})\tag{5}$$&lt;/span&gt;&#xA;(since &lt;span class=&quot;math-container&quot;&gt;$-\mathbf{k}=\mathbf{k}$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k=0}$&lt;/span&gt;)&#xA;Wouldn't this imply that such a wavefunction must have even symmetry, or should time inversion not apply to  &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k=0}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;My question is quite general and applies if the above is true:&lt;/p&gt;&#xA;&lt;p&gt;How do you apply the BZ symmetry operations to wavefunction data in an irreducible region to reconstruct the full k-point mesh?&lt;/p&gt;&#xA;" OwnerUserId="5642" LastEditorUserId="5" LastEditDate="2022-12-31T03:42:05.637" LastActivityDate="2022-12-31T03:42:05.637" Title="How can I apply symmetry operations to wavefunctions obtained via VASP to map them to the whole BZ from the irreducible wedge?" Tags="|density-functional-theory|vasp|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-06T19:55:17.393" ContentLicense="CC BY-SA 4.0" />
  <row Id="9308" PostTypeId="1" AcceptedAnswerId="9312" CreationDate="2022-06-29T10:55:20.140" Score="2" ViewCount="294" Body="&lt;p&gt;As can be read in the pyscf.dft documentation, there should be the possibility of generating the coordinates of the grid for numerical integration. According to the &lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.dft.html#module-pyscf.dft.gen_grid&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;, one can generate the coordinates with the &lt;code&gt;get_partition&lt;/code&gt; function, which is part of the &lt;code&gt;pyscf.dft.gen_grid&lt;/code&gt; module.&lt;/p&gt;&#xA;&lt;p&gt;My question is the following: If the &lt;code&gt;get_partition&lt;/code&gt; function returns the mesh grid coordinates and the corresponding grid weights, how can one directly access and manipulate the generated data (printing, shaping arrays, etc.)? I tried to print the grid coordinates, which are returned as an array according to the documentation, but it is not specified under which name the grid coordinates are returned.&lt;/p&gt;&#xA;" OwnerUserId="5646" LastEditorUserId="7" LastEditDate="2022-06-29T12:44:41.157" LastActivityDate="2022-06-30T08:18:04.760" Title="Generate grid coordinates from PySCF DFT package for plotting grid points" Tags="|density-functional-theory|python|pyscf|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9309" PostTypeId="1" CreationDate="2022-06-29T17:24:45.783" Score="2" ViewCount="128" Body="&lt;p&gt;I am trying to understand the Quantum espresso input file and I intend to do DFT calculation on an Energetic material (TKX-50) consisting of C, H, O, AND N. I have seen that &amp;quot;smearing&amp;quot; should be set as occupation for metals, but what &amp;quot;Occupation&amp;quot; should be used for my material.&lt;/p&gt;&#xA;" OwnerUserId="5591" LastActivityDate="2022-07-03T09:42:42.170" Title="What occupation should be used for non metallic energetic materials in Quantum espresso?" Tags="|density-functional-theory|quantum-espresso|quantum-chemistry|quantum-mechanics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9312" PostTypeId="2" ParentId="9308" CreationDate="2022-06-30T08:17:29.450" Score="3" Body="&lt;p&gt;What I usually do is I generate the grid with &lt;code&gt;pyscf.dft.gen_grid&lt;/code&gt; as you mentioned, for example&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def __init__(self, mol, calc):&#xA;    self._grid = pyscf.dft.gen_grid.Grids(self._mol)&#xA;    self._grid.level = 8 # level of accuracy of the grid. 8 is pretty dense, you might be OK with the default (maybe 5?)&#xA;    self._grid.build()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Doing this I will have access to &lt;code&gt;self._grid.coords&lt;/code&gt; and &lt;code&gt;self._grid.weights&lt;/code&gt;. Then all you need to do is apply whatever function you want to the coordinates and take the dot product of this quantity with the weights to do a quadrature&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;desired_quantity = apply_function(self._grid.coords)&#xA;res = self._grid.coords * self._grid.weights&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5648" LastEditDate="2022-06-30T08:18:04.760" LastActivityDate="2022-06-30T08:18:04.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9313" PostTypeId="1" CreationDate="2022-07-01T02:40:33.123" Score="4" ViewCount="268" Body="&lt;p&gt;I have asked a question in &lt;a href=&quot;https://chemistry.stackexchange.com/questions/166139/how-to-propose-reaction-mechanism&quot;&gt;chemistry&lt;/a&gt;, and I found someone already asked &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6792/methods-to-study-reaction-mechanisms-in-solid-state-reactions-and-identifying-in&quot;&gt;question&lt;/a&gt;, but no answer yet. So I post again with the hope of suggestions. I have an initial compound A (such as Fe3O4) and I know a final product B (such as FeO). I would like to know intermediate compounds in the reaction from A to B, and maybe activation energy. Is there any computational method/technique to predict intermediate products of a reaction?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2022-07-31T15:55:52.350" LastActivityDate="2022-07-31T15:55:52.350" Title="How to propose reaction mechanism" Tags="|software-recommendations|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9314" PostTypeId="2" ParentId="9313" CreationDate="2022-07-01T11:56:05.247" Score="6" Body="&lt;p&gt;My answer is focused on molecules, and not solids (like your question suggests). I also assume boring organic molecules, with not so many atoms, and one clear reaction path.&lt;/p&gt;&#xA;&lt;p&gt;There's two relatively user-friendly ways to find a reaction path. For both of these methods, you first need to have a good knowledge of both the reactants and the products - meaning well-optimized, local minimum geometries.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Method 1&lt;/strong&gt; You kinda guess the transition state - for boring organic molecules, this can be done somewhat easily with some experience. Then, you start from your guess, and you optimize to find a saddle point. Most electronic structure codes can do this quite easily. You know that you have reached a transition state when you have one imaginary frequency vibration, and that mode is sort of along the expected reaction path. Then, having these three points, you can find algorithms that interpolate a reaction path between the structures: &lt;a href=&quot;https://gaussian.com/qst2/&quot; rel=&quot;noreferrer&quot;&gt;I've had good experience with the QTS keyword in Gaussian.&lt;/a&gt;. Note two things about this implementation in particular: there's an option to start from an approximate transition state too, so you don't really need to optimize it fist, and, in principle, &lt;a href=&quot;https://gaussian.com/irc/&quot; rel=&quot;noreferrer&quot;&gt;you can even avoid having the two local minima (although finding them is the easiest of all of this).&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Method 2&lt;/strong&gt; If you have no idea about the transition state, there's some promising methods &lt;a href=&quot;https://nwchemgit.github.io/Nudged-Elastic-Band-and-Zero-Temperature-String-Methods.html&quot; rel=&quot;noreferrer&quot;&gt;such as the nudged elastic band method implemented in NWChem&lt;/a&gt;. These methods (called minimum energy path optimizations) are probably the closest you can get to what you have in mind. I don't have good experience with these methods, however, because if you have a reaction that's not overly trivial, there can be thousands of competing reaction paths, and it's very hard to find them automatically. Still, these methods are out there, and for simple systems, they do work.&lt;/p&gt;&#xA;&lt;p&gt;So if your reaction is really simple, you can get automatic reaction paths probably; if it has a normal complexity, then you will have more luck guessing at least the transition state, and you can use much better algorithms from there.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; If you only need the activation energy, you don't need the full path, only the initial state and the saddle point.&lt;/p&gt;&#xA;" OwnerUserId="5648" LastActivityDate="2022-07-01T11:56:05.247" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9315" PostTypeId="1" AcceptedAnswerId="9317" CreationDate="2022-07-01T22:42:00.783" Score="8" ViewCount="217" Body="&lt;p&gt;That is, is the following statement true of approximate density functionals? What about for the exact density functional?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[\rho]=E_{xc}[\rho_A]+E_{xc}[\rho_B]&#xA;$$&lt;/span&gt;&#xA;where,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho=\rho_A+\rho_B&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho_B$&lt;/span&gt; here are two arbitrary electron densities. I suspect this is not true in general (but my suspicions are often wrong :) ). Is it ever true in the case the densities have nonzero overlap?&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-07-02T07:31:08.353" Title="Are density functionals distributive over densities?" Tags="|density-functional-theory|quantum-chemistry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9316" PostTypeId="1" AcceptedAnswerId="9366" CreationDate="2022-07-02T07:13:36.290" Score="9" ViewCount="218" Body="&lt;p&gt;I calculated energies per atom of bulk configurations of transition metals in VASP in order to use them as reference energies for adsorption on surfaces, etc. I downloaded POSCAR files from the material project, calculated their energies in VASP, and divided by the number of atoms in the unit cell. I used PAW PBE pseudopotentials. This is what I got.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hwwIi.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hwwIi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then I decided to do similar calculations in DFTK.jl also in PBE. It uses Hartwigsen-Goedeker-Hutter (HGH) pseudopotentials. DFTK.jl gives energies in Hartree, I multiplied them by 27.2114 and got the following picture with completely different numbers:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GrFbL.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GrFbL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I understand that different pseudopotentials use different references and cannot be straightforwardly compared. I just did not expect that the numbers would be &lt;em&gt;that&lt;/em&gt; different.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to take one pseudopotential, make some calculation on it, and compare it with another pseudopotential or to some calculation on that pseudopotential?&lt;/p&gt;&#xA;&lt;p&gt;I just want know how to check if I have any mistakes in calculations, and to understand what to do and what not to do when using different software for different parts of calculations. For example, I used the same cutoff energies but it probably does not make sense because the cutoff should be different for different pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, for certain atoms, DFTK.jl has different versions of a hgh pseudopotential and each gives very different result, so I am confused, which of them to use., e.g. for Ir:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ir-q9:   -20.225468 Ha/atom&#xA;ir-q17: -104.765948 Ha/atom &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="81" LastActivityDate="2022-07-11T19:53:26.330" Title="Can energies obtained with different pseudopotentials be compared?" Tags="|density-functional-theory|software|pseudopotentials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9317" PostTypeId="2" ParentId="9315" CreationDate="2022-07-02T07:31:08.353" Score="10" Body="&lt;p&gt;You are right, this is not true in general.&lt;/p&gt;&#xA;&lt;p&gt;Proof by contradiction. If your statement is true, then we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[\rho] = \sum_i E_{xc}[\rho_i] \tag{1}&#xA;$$&lt;/span&gt;&#xA;whenever&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho = \sum_i \rho_i \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, every density can be expressed as an infinite sum of delta functions. Since the sum is on all points in &lt;span class=&quot;math-container&quot;&gt;$\mathbb{R}^3$&lt;/span&gt;, we may prefer to write it as an integral instead:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho = \int \rho_{\mathbf{r}'} d\mathbf{r}', \quad \rho_{\mathbf{r}'}(\mathbf{r}) = \rho(\mathbf{r}')\delta(\mathbf{r}-\mathbf{r}') \tag{3}&#xA;$$&lt;/span&gt;&#xA;This means that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[\rho] = \int E_{xc}[\rho_{\mathbf{r}'}] d\mathbf{r}' \tag{4}&#xA;$$&lt;/span&gt;&#xA;Since &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[\rho_{\mathbf{r}'}]$&lt;/span&gt; only depends on the value of &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; at the point &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}'$&lt;/span&gt;, Eq. (4) means that &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[\rho]$&lt;/span&gt; is an LDA functional:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[\rho] = \int \epsilon_{xc}(\rho(\mathbf{r})) d\mathbf{r}, \quad \epsilon_{xc}(\rho(\mathbf{r})) = E_{xc}[\rho_{\mathbf{r}}] \tag{5}&#xA;$$&lt;/span&gt;&#xA;By now we have proved that your statement can only apply to LDA functionals, therefore definitely not to the exact density functional. However, most LDA functionals do not satisfy your statement either. To see this, consider two densities &lt;span class=&quot;math-container&quot;&gt;$\rho_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rho_B$&lt;/span&gt; such that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho_A(\mathbf{r})=N\rho_B(\mathbf{r}) \quad \forall \mathbf{r} \tag{6}&#xA;$$&lt;/span&gt;&#xA;From Eq. (1) we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{xc}[\rho_A]=NE_{xc}[\rho_B] \tag{7}&#xA;$$&lt;/span&gt;&#xA;or&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon_{xc}(\rho_A(\mathbf{r}))=N\epsilon_{xc}(\rho_B(\mathbf{r})) \quad \forall \mathbf{r} \tag{8}&#xA;$$&lt;/span&gt;&#xA;This means&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon_{xc}(Nx)=N\epsilon_{xc}(x) \quad \forall x \tag{9}&#xA;$$&lt;/span&gt;&#xA;Obviously, only a linear functional of the type&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon_{xc}(x)=kx \tag{10}&#xA;$$&lt;/span&gt;&#xA;satisfies Eq. (9). Since the number of electrons of a system is the integral of the density over &lt;span class=&quot;math-container&quot;&gt;$\mathbb{R}^3$&lt;/span&gt;, we have that &lt;span class=&quot;math-container&quot;&gt;$E_{xc}$&lt;/span&gt; is proportional to the number of electrons. This is such a bad approximation that no functional, not even the worst approximate ones, has this property. QED.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-07-02T07:31:08.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9318" PostTypeId="1" AcceptedAnswerId="9328" CreationDate="2022-07-02T14:52:21.893" Score="4" ViewCount="236" Body="&lt;p&gt;I have recently installed SIESTA v.4.1.5 in ubuntu 22.04 LTS without any error.&#xA;But, it's taking a very large time for the same SCF calculations done in past.&lt;/p&gt;&#xA;&lt;p&gt;Does this issue occur due to versions of libraries or compilers?&lt;/p&gt;&#xA;&lt;p&gt;Please suggest some solution. I have attached arch.make file here.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# &#xA;# Copyright (C) 1996-2016   The SIESTA group&#xA;#  This file is distributed under the terms of the&#xA;#  GNU General Public License: see COPYING in the top directory&#xA;#  or http://www.gnu.org/copyleft/gpl.txt.&#xA;# See Docs/Contributors.txt for a list of contributors.&#xA;#&#xA;.SUFFIXES:&#xA;.SUFFIXES: .f .F .o .a .f90 .F90&#xA;&#xA;SIESTA_ARCH=x86_64-unknown-linux-gnu--Gfortran&#xA;&#xA;FPP=&#xA;FPP_OUTPUT= &#xA;FC=mpif90&#xA;CC=mpicc&#xA;RANLIB=echo&#xA;&#xA;SYS=nag&#xA;&#xA;SP_KIND=4&#xA;DP_KIND=8&#xA;KINDS=&lt;span class=&quot;math-container&quot;&gt;$(SP_KIND) $&lt;/span&gt;(DP_KIND)&#xA;&#xA;# Add any other sensible compilation flags here&#xA;FFLAGS=-g -O2 -fallow-argument-mismatch&#xA;&#xA;FPPFLAGS= -DMPI -DFC_HAVE_FLUSH -DFC_HAVE_ABORT -DCDF -DGRID_DP -DPHI_GRID_SP&#xA;LDFLAGS= -L/usr/lib/x86_64-linux-gnu/hdf5/openmpi -L//usr/lib/x86_64-linux-gnu/  &#xA;&#xA;ARFLAGS_EXTRA=&#xA;&#xA;FCFLAGS_fixed_f=&#xA;FCFLAGS_free_f90=&#xA;FPPFLAGS_fixed_F=&#xA;FPPFLAGS_free_F90=&#xA;&#xA;INCFLAGS=  -I/usr/include -I.&#xA;BLAS_LIBS= -lblas&#xA;LAPACK_LIBS= -llapack&#xA;BLACS_LIBS=&#xA;SCALAPACK_LIBS=/usr/lib/x86_64-linux-gnu/libscalapack-openmpi.so&#xA;&#xA;&#xA;&#xA;NETCDF_LIBS=-lnetcdff -lnetcdf&#xA;NETCDF_INTERFACE=libnetcdf_f90.a&#xA;&#xA;COMP_LIBS += libncdf.a libfdict.a &#xA;FPPFLAGS += -DNCDF -DNCDF_4 &#xA;&#xA;&#xA;#FPPFLAGS += -DSIESTA__ELPA -I/usr/local/include/elpa-2017.11.001/modules -I/usr/local/include/elpa-2017.11.001/elpa&#xA;&#xA;LIBS= &lt;span class=&quot;math-container&quot;&gt;$(NETCDF_LIBS) $&lt;/span&gt;(SCALAPACK_LIBS) &lt;span class=&quot;math-container&quot;&gt;$(BLACS_LIBS) $&lt;/span&gt;(LAPACK_LIBS) $(BLAS_LIBS) -lhdf5_fortran -lhdf5 -lz&#xA;#LIBS += -L/usr/local/lib -lelpa&#xA;#SIESTA needs an F90 interface to MPI&#xA;#This will give you SIESTA's own implementation&#xA;#If your compiler vendor offers an alternative, you may change&#xA;#to it here.&#xA;MPI_INTERFACE=libmpi_f90.a&#xA;MPI_INCLUDE=.&#xA;&#xA;#Dependency rules are created by autoconf according to whether&#xA;#discrete preprocessing is necessary or not.&#xA;.F.o:&#xA;    &lt;span class=&quot;math-container&quot;&gt;$(FC) -c $&lt;/span&gt;(FFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(INCFLAGS) $&lt;/span&gt;(FPPFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(FPPFLAGS_fixed_F)  $&lt;/span&gt;&amp;lt; &#xA;.F90.o:&#xA;    &lt;span class=&quot;math-container&quot;&gt;$(FC) -c $&lt;/span&gt;(FFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(INCFLAGS) $&lt;/span&gt;(FPPFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(FPPFLAGS_free_F90) $&lt;/span&gt;&amp;lt; &#xA;.f.o:&#xA;    &lt;span class=&quot;math-container&quot;&gt;$(FC) -c $&lt;/span&gt;(FFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(INCFLAGS) $&lt;/span&gt;(FCFLAGS_fixed_f)  &lt;span class=&quot;math-container&quot;&gt;$&amp;lt;&#xA;.f90.o:&#xA;    $&lt;/span&gt;(FC) -c &lt;span class=&quot;math-container&quot;&gt;$(FFLAGS) $&lt;/span&gt;(INCFLAGS) &lt;span class=&quot;math-container&quot;&gt;$(FCFLAGS_free_f90)  $&lt;/span&gt;&amp;lt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5366" LastEditorUserId="24" LastEditDate="2022-07-02T15:09:20.030" LastActivityDate="2022-07-04T10:01:24.117" Title="SIESTA Compilation" Tags="|density-functional-theory|siesta|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="9319" PostTypeId="1" CreationDate="2022-07-02T16:23:40.547" Score="3" ViewCount="39" Body="&lt;p&gt;I am trying to make Hartree potential of bcc Tungsten(001).&#xA;My software is VASP.&#xA;5-layer should have 5 bound states.&#xA;But I don't have them&#xA;I heard it is a layer-layer spacing issue.&#xA;I built slab of bcc structre :&lt;/p&gt;&#xA;&lt;p&gt;POSCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a1 = a(1 0 0)&#xA;a2 = a(0 1 0)&#xA;a3 = a(0 0 50)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and with direct,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0    0    0.02&#xA;0.5  0.5  0.01&#xA;0    0    0&#xA;0.5  0.5 -0.01&#xA;0    0   -0.02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rRFhi.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rRFhi.jpg&quot; alt=&quot;My result&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;the z space should be 1/(2*50) = 0.01?&lt;/p&gt;&#xA;&lt;p&gt;It seems z-direction spacing has a problem.&lt;/p&gt;&#xA;" OwnerUserId="5635" LastEditorUserId="5635" LastEditDate="2022-07-02T16:25:39.587" LastActivityDate="2022-07-03T16:03:45.503" Title="Spacing issues about multiple-layer bcc structure" Tags="|density-functional-theory|vasp|crystallography|physical-properties-of-materials|computational-frameworks|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9320" PostTypeId="1" CreationDate="2022-07-02T23:41:35.160" Score="1" ViewCount="105" Body="&lt;p&gt;As an example, I have seen the phrase &amp;quot;dynamics of proteins&amp;quot; or &amp;quot;dynamics of biomolecules&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The review paper &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0034-4885/47/1/001/pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Protein Dynamics&amp;quot; by J A McCammon&lt;/a&gt; has the word in its title, but what does the author mean by &amp;quot;dynamics&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2022-07-08T20:37:00.810" LastActivityDate="2022-07-08T20:37:00.810" Title="What does &quot;dynamics&quot; mean in matter modeling?" Tags="|molecular-dynamics|proteins|terminology|biomaterials|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9321" PostTypeId="2" ParentId="9309" CreationDate="2022-07-03T09:42:42.170" Score="3" Body="&lt;p&gt;Usually for materials with a band gap you can just not specify any option for &lt;code&gt;occupations&lt;/code&gt; and the calculation runs perfectly fine.&#xA;I'm not familiar with TKX-50, but if it is an insulator (with a wide band-gap) and you really want to specify &lt;code&gt;occupations&lt;/code&gt; you can use the &lt;code&gt;fixed&lt;/code&gt; keyword.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-07-03T09:42:42.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9322" PostTypeId="2" ParentId="9287" CreationDate="2022-07-03T09:53:09.920" Score="4" Body="&lt;p&gt;You can't construct the thin film itself with Quantum Espresso, but only calculate it's properties.&#xA;You first have to create the unit cell of the thin film with some other software. As an example &lt;a href=&quot;https://www.youtube.com/watch?v=6xx29-CQJiA&amp;amp;ab_channel=NickelandCopper&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; is a tutorial for creating a slab with a specific facet of Au, using VESTA.&lt;/p&gt;&#xA;&lt;p&gt;Then you put the resulting unit cell in QE's input file, and you can run the calculation.&#xA;For thin layers it is important to note that you have to add a large-enough vacuum along the out-of-plane direction in order to avoid fictitious interactions of the layer with it's reciprocal images.&#xA;For a layer located on the XY plane this is really easy - you just manually enlarge the value of the Z direction of the unit cell.&#xA;You should check for convergence of the total energy if you want accurate results, or just try some 1-2 nm as a rule of thumb.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-07-03T09:53:09.920" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9323" PostTypeId="1" CreationDate="2022-07-03T10:19:38.050" Score="2" ViewCount="64" Body="&lt;p&gt;Usually, the first-principles packages like VASP and QE involve many aspects to totally figure out what their subroutines do. For example, to output Berry connection &lt;span class=&quot;math-container&quot;&gt;$\mathcal{A}^\alpha_{nn}$&lt;/span&gt; used by these codes to calculate electronic polarization is hard and time-consuming, especially for those like me who don't read these source codes. So my question here resorts to those people who read these source codes. Namely, how to output Berry connection and identify the gauge by modifying the VASP or QE source code?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2022-07-03T10:19:38.050" Title="How to output Berry connection and identify the gauge by changing VASP or QE source code?" Tags="|vasp|quantum-espresso|berry-phase|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-09T22:59:31.660" ContentLicense="CC BY-SA 4.0" />
  <row Id="9324" PostTypeId="2" ParentId="9319" CreationDate="2022-07-03T16:03:45.503" Score="3" Body="&lt;p&gt;You might be overlapping the W atoms on the unit cell.&#xA;Try taking a bulk unit cell of W, creating a slab along the (001) direction with the desired thickness using the &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA software&lt;/a&gt; according to the instructions in &lt;a href=&quot;https://www.youtube.com/watch?v=6xx29-CQJiA&amp;amp;ab_channel=NickelandCopper&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial&lt;/a&gt;.&#xA;VESTA is capable of exporting for you the POSCAR, which you can then use in VASP, and you will get the correct Coulomb potential.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-07-03T16:03:45.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9325" PostTypeId="1" CreationDate="2022-07-03T17:18:04.650" Score="9" ViewCount="454" Body="&lt;p&gt;While performing phonon calculation using finite difference method, we get normal modes printed in the outcar file. Now there is a distinction between two different types of modes in the outcar file.&lt;/p&gt;&#xA;&lt;p&gt;The first type of mode is the one where a number if followed by 'f' which indicated vibrationally stable mode. The other mode is represented by a number followed by 'f/i' which is called as 'soft mode' and this mode is imaginary.&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Phonons_from_finite_differences&quot; rel=&quot;noreferrer&quot;&gt;Link&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now the soft mode represents a certain kind of movement of atoms where the crystal translates from higher symmetry to lower symmetry with respect to the change in temperature. However I fail to understand if this actually states that the structure becomes unstable.&lt;a href=&quot;https://www.researchgate.net/post/What_is_soft_phonon_in_ferroelectrics&quot; rel=&quot;noreferrer&quot;&gt;Link&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5610" LastActivityDate="2022-10-03T14:56:07.480" Title="Stability using Phonon Calculation" Tags="|density-functional-theory|computational-chemistry|crystallography|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9326" PostTypeId="1" CreationDate="2022-07-03T19:31:48.433" Score="4" ViewCount="105" Body="&lt;p&gt;I am reading Statistical Physics of Particles by Kardar. I am struggling with problem 12d, in chapter 2, about semi-flexible polymers in two dimensions. The problem is as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Configurations of a model polymer can be described by either a set of vectors &lt;span class=&quot;math-container&quot;&gt;$\{ t_i \}$&lt;/span&gt; of length &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; in two dimensions (for &lt;span class=&quot;math-container&quot;&gt;$i=1,\ldots, N$&lt;/span&gt;), or alternatively by angles &lt;span class=&quot;math-container&quot;&gt;$\{ \phi _i \}$&lt;/span&gt; between successive vectors. The polymer is set at temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, and subject to energy&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ H = -k \sum _{i=1}^{N-1} t_i \cdot t_{i+1} = -ka^2 \sum _{i=1}^{N-1} \cos \phi _i $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The probability of a certain configuration is given by &lt;span class=&quot;math-container&quot;&gt;$\exp (-H/kT)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If the end of the polymer are pulled apart by a force &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;, the probabilities for polymer configurations are modified by the Boltzmann weight &lt;span class=&quot;math-container&quot;&gt;$\exp (\mathbf{F}\cdot \mathbf{R}/kT)$&lt;/span&gt;, by expanding this weight, or otherwise, show that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle \mathbf{R} \rangle = K^{-1} \mathbf{F} + O\left( F^3 \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I know that &lt;span class=&quot;math-container&quot;&gt;$$\langle \mathbf{R} \rangle = \frac{\int \mathbf{R} \exp [-\beta H + \beta (\mathbf{F}\cdot \mathbf{R})] d\phi}{\int \exp [-\beta H + \beta (\mathbf{F}\cdot \mathbf{R})] d\phi} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the previous parts of the problem, I know the &lt;span class=&quot;math-container&quot;&gt;$\langle \mathbf{R} \rangle = 0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\langle R^2 \rangle = a^2 N \coth \frac{1}{2\xi}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\xi$&lt;/span&gt; is the persistence length.&lt;/p&gt;&#xA;&lt;p&gt;My question is, how do I expand &lt;span class=&quot;math-container&quot;&gt;$\langle \mathbf{R} \rangle$&lt;/span&gt;? Can anyone give me a mathematically rigorous introduction to expanding such functions? I understand what Taylor expansions are, but how do I apply those principles to an object like &lt;span class=&quot;math-container&quot;&gt;$\langle \mathbf{R} \rangle$&lt;/span&gt; described above?&lt;/p&gt;&#xA;&lt;p&gt;I see that &lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\exp(\beta({\bf F}\cdot {\bf R}))&#xA;= 1 + &#xA;\beta({\bf F}\cdot {\bf R})&#xA;+\frac{1}{2}\left [\beta({\bf F}\cdot {\bf R})\right]^2&#xA;+\frac{1}{3!}\left [\beta({\bf F}\cdot {\bf R})\right]^3+...&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I do not see how to use this to get the desired result.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="7" LastEditDate="2022-07-03T20:14:44.310" LastActivityDate="2022-07-03T20:14:44.310" Title="Statistical properties of semi-flexible polymers" Tags="|statistical-thermodynamics|polymers|" AnswerCount="0" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9327" PostTypeId="2" ParentId="9275" CreationDate="2022-07-04T06:37:30.190" Score="2" Body="&lt;p&gt;Before you can draw the orbitals, you first have to compute the wavefunctions for the material. This can be done with any number of software, a free example of this could be using &lt;a href=&quot;https://www.quantum-espresso.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum Espresso (QE)&lt;/a&gt; for DFT calculation.&#xA;After you have the wavefunctions for the system you should export them in a plottable format, such as xsf (in QE this is doeable with the pp.x executable).&#xA;You can then plot the orbitals, polyhedra, and many more properties with, again, any number of software such as &lt;a href=&quot;https://avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;avogadro&lt;/a&gt;, &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt;, &lt;a href=&quot;http://www.xcrysden.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;XCrysDen&lt;/a&gt;, and many more.&#xA;An easy way (though not very flexible in my opinion) for doing all of this in a single software, but only for relatively simple systems, would be to use &lt;a href=&quot;https://burai.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;burai&lt;/a&gt;. This is a nice way of generating input files for QE, making simple DFT calculations and visualizing some aspects of the output.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-07-04T06:37:30.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9328" PostTypeId="2" ParentId="9318" CreationDate="2022-07-04T10:01:24.117" Score="1" Body="&lt;p&gt;Turning my comment into an answer...&lt;/p&gt;&#xA;&lt;p&gt;From what you have said it looks as though you are fully populating the cores on your machine with MPI processes, generally a good idea provided the problem you are trying to solve is big enough to exploit the parallelism so available. Now this is should be a good idea. Unfortunately many BLAS and LAPACK implementations assume that if you do &lt;em&gt;not&lt;/em&gt; set the environment variable &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; to a value then whatever operation is being done by that library should set the number of threads equal to the number of cores available in the machine. For an MPI code this is &lt;em&gt;extremely&lt;/em&gt; irritating, as it  can lead to massive overpopulation of the machine.&lt;/p&gt;&#xA;&lt;p&gt;For instance let us say you have a quad-core machine, such as the laptop I am now on, and so logically start a job using 4 MPI processes. The problem is that when your job enter a BLAS or LAPACK routine each of those 4 processes will spawn 4 threads, so your code is now trying to run 4x4=16 threads of execution despite you only have 4 cores available! Nett result, slooooooooooow running of the code as you have observed. To avoid this use&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export OMP_NUM_THREADS=1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to limit the number of threads per MPI process to 1, and so avoiding the overpopulation described above.&lt;/p&gt;&#xA;&lt;p&gt;Just to take the argument a little further another sensible set up would be to run 2 MPI processes and set &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; to 2, thus giving you 2 processes each with 2 threads, and so running on the 4 cores available.&lt;/p&gt;&#xA;&lt;p&gt;Most BLAS and LAPACK implementations nowadays are threaded, and this is undoubtedly a good thing in general. However most (all?) implementations have the default behaviour of assuming that each call should grab all resources available if &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; is not set - something that annoys me no end, it should just use 1 thread in such circumstances IMO. Thus I recommend you always set &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; before you run a program that uses BLAS or LAPACK, and if it is purely MPI parallelism you require you should set it to 1.&lt;/p&gt;&#xA;" OwnerUserId="269" LastActivityDate="2022-07-04T10:01:24.117" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9329" PostTypeId="1" CreationDate="2022-07-04T11:19:16.923" Score="5" ViewCount="283" Body="&lt;p&gt;I am looking for literature on various scales (time, length, etc.) in atomistic or molecular simulation.&lt;/p&gt;&#xA;&lt;p&gt;So far I have found bits and pieces here and there. E.g. &lt;a href=&quot;https://www.molbnl.it/node/116#:%7E:text=By%20definition%2C%20multiscale%20molecular%20modeling,to%20the%20different%20pertaining%20scale.&quot; rel=&quot;noreferrer&quot;&gt;this is one of them&lt;/a&gt;. However, this is not a citable reference.&lt;/p&gt;&#xA;&lt;p&gt;I am looking for a research article or a book chapter dedicated to this topic.&lt;/p&gt;&#xA;&lt;p&gt;Can you supply me with one or more references?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-07-05T23:00:07.033" Title="Scales for simulation" Tags="|multiscale-modeling|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9330" PostTypeId="1" CreationDate="2022-07-04T12:08:03.547" Score="5" ViewCount="53" Body="&lt;p&gt;I have been trying to understand the concept of dielectric polarization in material science mostly by following &lt;a href=&quot;https://arxiv.org/abs/1202.1831&quot; rel=&quot;noreferrer&quot;&gt;Nicola Spaldin's lecture notes&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am confused by the claim that the polarization of a non-polar chain (with alternating equal and equally spaced positive and negative point charges) is a lattice &lt;span class=&quot;math-container&quot;&gt;$\pm \frac{1}{2}, \pm\frac{3}{2},...$&lt;/span&gt;. This is consistent with the modern theory of polarization, but I could not verify this explicitly by computation.&lt;/p&gt;&#xA;&lt;p&gt;I was able to choose two unit cells such that the simple computation gives polarizations &lt;span class=&quot;math-container&quot;&gt;$\pm \frac{1}{2}$&lt;/span&gt;, but what are the calculations that give the other values in the polarization lattice (i.e. &lt;span class=&quot;math-container&quot;&gt;$\pm \frac{3}{2},..$&lt;/span&gt;)?&lt;/p&gt;&#xA;&lt;p&gt;I tried choosing different supercells containing arbitrary numbers of positive and negative pairs, but the answers always come out as &lt;span class=&quot;math-container&quot;&gt;$\pm \frac{1}{2}$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastActivityDate="2022-07-04T12:08:03.547" Title="The polarization lattice of a non-polar one dimensional chain" Tags="|condensed-matter|solid-state-physics|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-06T19:54:59.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="9331" PostTypeId="2" ParentId="9329" CreationDate="2022-07-04T12:13:35.433" Score="6" Body="&lt;h1&gt;Multiscale Simulation Methods in Molecular Sciences&lt;/h1&gt;&#xA;&lt;p&gt;Edited by&#xA;Johannes Grotendorst&lt;br /&gt;&#xA;Norbert Attig&lt;br /&gt;&#xA;Stefan Blügel&lt;br /&gt;&#xA;Dominik Marx&lt;/p&gt;&#xA;&lt;p&gt;Winter School, 2 - 6 March 2009&lt;br /&gt;&#xA;Forschungszentrum Jülich, Germany&lt;br /&gt;&#xA;Lecture Notes&lt;/p&gt;&#xA;&lt;p&gt;Summary:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Methodological Foundations&lt;/li&gt;&#xA;&lt;li&gt;Multiscale Simulation Methods for Solids and&#xA;Material&lt;/li&gt;&#xA;&lt;li&gt;Multiscale Simulation Methods for Soft Matter and&#xA;Biological Systems&lt;/li&gt;&#xA;&lt;li&gt;Numerical Methods and Parallel Computing&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Download link: &lt;a href=&quot;https://juser.fz-juelich.de/record/3737/files/nic-series-volume42.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://juser.fz-juelich.de/record/3737/files/nic-series-volume42.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-07-04T12:13:35.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9332" PostTypeId="2" ParentId="9072" CreationDate="2022-07-04T14:25:05.100" Score="5" Body="&lt;p&gt;You may try to add the keyword 'force' into the Route Section of Gaussian. But there are some other things to be noted: all-electron relativistic basis set (e.g. ANO-RCC series, cc-pVnZ-DK, etc) should be used with the DKH2 Hamiltonian. The usage of common all-electron basis set aug-cc-pvtz for H, C and dgdzvp for I is not that reasonable/rational.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2022-07-04T14:25:05.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9333" PostTypeId="1" CreationDate="2022-07-04T14:38:08.223" Score="5" ViewCount="179" Body="&lt;p&gt;When we work on the topological insulator (protected by time reversal symmetry ), it is often said that the SOC is the main ingredient because it is a way to open a gap when the band inversion present. I want to ask what is the mechanism cause the gap to be opened ? More precisely, I found that SOC will cause the splitting of energy band. Let’s say if the system contain both time reversal and inversion symmetry, each energy band must be 2-fold degenerate. However the SOC term don’t violate these symmetries, where is the splitting come from ?&lt;/p&gt;&#xA;" OwnerUserId="621" LastActivityDate="2022-07-04T14:38:08.223" Title="About the mechanism of opening of the band gap in topological insulator with the inclusion of SOC" Tags="|band-structure|condensed-matter|symmetry|spin-orbit-coupling|topological-insulators|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-07T03:00:56.393" ContentLicense="CC BY-SA 4.0" />
  <row Id="9334" PostTypeId="1" CreationDate="2022-07-05T01:55:49.683" Score="1" ViewCount="53" Body="&lt;p&gt;The following table is taken from page#434 of the book &lt;em&gt;Schlick, Tamar. Molecular modeling and simulation: an interdisciplinary guide. Vol. 2. New York: Springer, 2010.&lt;/em&gt;&lt;/p&gt;&#xA;  &lt;img src=&quot;https://i.stack.imgur.com/nv9Up.png&quot; width=&quot;400&quot; /&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;What would the same items look like if we put them on a length scale?&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-07-05T01:55:49.683" Title="What would the items look like if we put them on a length scale?" Tags="|multiscale-modeling|" AnswerCount="0" CommentCount="5" ClosedDate="2023-02-06T19:54:44.087" ContentLicense="CC BY-SA 4.0" />
  <row Id="9335" PostTypeId="1" CreationDate="2022-07-05T14:32:25.623" Score="9" ViewCount="664" Body="&lt;p&gt;I am trying to use the atomic positions in geometry optimized crystal structure to get the radial distribution function.&lt;/p&gt;&#xA;&lt;p&gt;I know that some codes can read the positions of the atoms from the CONTCAR file (VASP), but I cannot get a similar file from CASTEP.&lt;/p&gt;&#xA;&lt;p&gt;Can someone that works with CASTEP explain to me how to get the positions of the atoms after geometry optimization from CASTEP?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="5686" LastActivityDate="2022-08-06T00:27:21.063" Title="Which output file from CASTEP after geometry optimization is like with the CONTCAR from VASP?" Tags="|geometry-optimization|castep|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9336" PostTypeId="1" CreationDate="2022-07-05T15:09:47.643" Score="7" ViewCount="194" Body="&lt;p&gt;I am doing calculations with &lt;a href=&quot;https://github.com/openmopac/MOPAC&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOPAC&lt;/a&gt; semi-empirical package.&lt;/p&gt;&#xA;&lt;p&gt;As I have many systems (around 40), extracting the date manually, besides being tiring it can cause errors.&lt;/p&gt;&#xA;&lt;p&gt;I already worked with ASE, but the data it can extract is very limited.&lt;/p&gt;&#xA;&lt;p&gt;My question is: &lt;strong&gt;Are there available scripts (Bach, Python, etc.) to automatically extract data from MOPAC calculations?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note: I am thinking in extracting all (or most all) the useful data: heat of formation, molecular orbitals (w/, w/o spin polarization), energies, frequencies, thermochemistry data, forces, etc.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2023-02-24T00:16:21.597" LastActivityDate="2023-02-24T00:16:21.597" Title="Scripts to extract data from MOPAC calculations?" Tags="|python|semi-empirical-method|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9337" PostTypeId="2" ParentId="9335" CreationDate="2022-07-05T20:10:42.537" Score="10" Body="&lt;p&gt;The main structural output of a geometry optimization in Castep is in the file with the &amp;quot;.geom&amp;quot; extension. That file contains blocks with lattice parameters and atomic positions at each step of a geometry optimization, and the final structure would be the last block in the file. More details about this file can be found in the Castep manual &lt;a href=&quot;https://www.tcm.phy.cam.ac.uk/castep/Geom_Opt/node21.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-07-05T20:10:42.537" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9338" PostTypeId="2" ParentId="9329" CreationDate="2022-07-05T20:19:56.103" Score="3" Body="&lt;p&gt;I have found another reference in addition to what &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9331/3990&quot;&gt;Camps&lt;/a&gt; has supplied.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://link.springer.com/content/pdf/10.1007/978-3-662-53224-9.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Steinhauser, Martin Oliver. &lt;em&gt;&lt;strong&gt;Computational multiscale modeling of fluids and solids.&lt;/strong&gt;&lt;/em&gt; Berlin: Springer, 2017.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Chapter 1 (Introduction) of this book gives a moderately well coverage of time and length scales for modeling and simulation.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2022-07-05T23:00:07.033" LastActivityDate="2022-07-05T23:00:07.033" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9340" PostTypeId="2" ParentId="9283" CreationDate="2022-07-06T06:38:25.740" Score="6" Body="&lt;p&gt;If I understand correctly your question, you have the fractional coordinates of the atoms in the unit cell, and (I'm assuming) that you also have the unitcell (or supercell) vectors. In this case the transformation is quite simply a basis-change transformation.&lt;/p&gt;&#xA;&lt;p&gt;To illustrate this, let's assume that the cartesian cell vectors are given by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\left(\matrix{\vec{a}\\\vec{b}\\\vec{c}}\right) = \left( \matrix{a_1&amp;amp;a_2&amp;amp;a_3 \\ b_1&amp;amp;b_2&amp;amp;b_3 \\ c_1&amp;amp;c_2&amp;amp;c_3} \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And the fractional coordinates of an atom given by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\vec{x}=\left( \matrix{x_1,x_2,x_3}\right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then the cartesian coordinate vector &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; for the atom is just:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \vec{x} \bullet \left(\matrix{\vec{a}\\\vec{b}\\\vec{c}}\right) = x_1\vec{a}+x_2\vec{b}+x_3\vec{c}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This can be implemented easily with the &lt;code&gt;numpy&lt;/code&gt; (imported as &lt;code&gt;np&lt;/code&gt; below) &lt;code&gt;dot()&lt;/code&gt; function:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cvec #= 3 by 3 matrix of unit cell vectors (each vector in a row)&#xA;fracAtomCoords #= natom by 3 matrix of fractional atom coordinates (each atom in a row)&#xA;cartAtomCoords = np.dot(fracAtomCoords, cvec) # natom by 3 matrix of cartesian atom coorodinates (each atom in a row)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2022-07-06T06:38:25.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9341" PostTypeId="1" CreationDate="2022-07-06T07:08:44.077" Score="5" ViewCount="2342" Body="&lt;p&gt;I am doing elastic calculations using VASP code in which&#xA;&lt;code&gt;OUTCAR&lt;/code&gt; contains four different elastic moduli: &lt;code&gt;ELASTIC MODULI&lt;/code&gt; , &lt;code&gt;SYMMETRIZED ELASTIC MODULI&lt;/code&gt;, &lt;code&gt;TOTAL ELASTIC MODULI&lt;/code&gt;&#xA;&lt;code&gt;(?)TOTAL ELASTIC MODULI&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can anyone tell me which one I should use for further calculations?&#xA;If its possible please share your reviews for all those data and their physical meaning.&lt;/p&gt;&#xA;" OwnerUserId="4238" LastEditorUserId="7" LastEditDate="2022-07-11T13:39:14.193" LastActivityDate="2022-07-27T07:57:27.873" Title="Elastic constants calculation" Tags="|density-functional-theory|vasp|physical-properties-of-materials|elasticity|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9342" PostTypeId="1" CreationDate="2022-07-06T12:01:49.387" Score="2" ViewCount="48" Body="&lt;p&gt;When we put a certain number of molecules in a small cubic box, and put it inside a large cubic box, under NVT simulation, the water cubic box is supposed to be spherical in shape to reach a minimum energy state. However, the Martini 3 water is not becoming spherical at all. Is this an issue with Martini 3 water, though obviously, CG representation of water is a coarser version? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="181" LastEditDate="2022-07-06T18:42:44.193" LastActivityDate="2022-07-06T18:42:44.193" Title="Martini 3 CG water cluster is not becoming spherical under NVT conditions" Tags="|molecular-dynamics|gromacs|martini|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-06T19:54:22.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="9343" PostTypeId="2" ParentId="4317" CreationDate="2022-07-06T12:03:20.393" Score="9" Body="&lt;p&gt;First I mention this &lt;a href=&quot;https://physics.stackexchange.com/questions/692489/spin-and-wavefunction-of-excitons&quot;&gt;very similar question&lt;/a&gt; on Physics SE and the related answer.&lt;/p&gt;&#xA;&lt;p&gt;Then, a couple of points which are not well addressed in the previous answer in my opinion. First of all we are here discussing excitons in extended systems. The word &amp;quot;exciton&amp;quot; is sometimes used also in isolated systems, but with a slightly different meaning.&lt;/p&gt;&#xA;&lt;p&gt;Second we are discussing systems in which the spin is a good quantum number. This happens when spin-orbit coupling SOC is neglected. Otherwise the discussion is true only in an approximated way.&lt;/p&gt;&#xA;&lt;p&gt;Third we have to distinguish between spin S and orbital &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; angular momentum. Excitons can also have an angular momentum &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt;, or, in presence of SOC, of their combination &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;. However the definition of &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is always approximated, since &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is a good quantum number in presence of &lt;span class=&quot;math-container&quot;&gt;$SO(3)$&lt;/span&gt; invariance, while, the exact symmetry of the exciton will depend on the underlying crystal lattice symmetry &lt;span class=&quot;math-container&quot;&gt;$O_l$&lt;/span&gt;. The approximation is better for more delocalized (i.e. Wannier like) excitons.&lt;/p&gt;&#xA;&lt;p&gt;The discussion on heavy holes is related to the angular momentum &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;. For localized, i.e. Frenkel excitons, one should look into the irreps of &lt;span class=&quot;math-container&quot;&gt;$O_l$&lt;/span&gt;, as seen in this &lt;a href=&quot;https://chemistry.stackexchange.com/a/82922/125277&quot;&gt;Chem SE answer&lt;/a&gt;. Excitons can have &lt;span class=&quot;math-container&quot;&gt;$S=0,1$&lt;/span&gt; and potentially any &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt;. (However no &lt;span class=&quot;math-container&quot;&gt;$S=2$&lt;/span&gt; for obvious reasons!)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Bright excitons are always with &lt;span class=&quot;math-container&quot;&gt;$S=0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$L=0,1$&lt;/span&gt; due to electric dipole selection rules.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This means that the valence band from which the electron is removed and the conduction band into which the electron is added have the same spin. However, as correctly pointed out in the question, the convention is that the spin of the hole is the opposite of the one of the valence from which it is removed. Also notice that the election and the hole does not stay in a specific state in the two bands, but they can be expressed using these bands as a basis-set. So the discussion specify which state in the basis set can be used. Notice that instead S=1 excitons (i.e. magnons if &lt;span class=&quot;math-container&quot;&gt;$S_z=\pm1$&lt;/span&gt;) can be generated via magnetic fields. L=1 usually require instead circularly polarized light.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For first principles simulations, the state of the art is the Bethe-Salpeter equation (BSE). For systems with &lt;span class=&quot;math-container&quot;&gt;$S=0$&lt;/span&gt; ground state, this is always constructed and solved in the singlet &lt;span class=&quot;math-container&quot;&gt;$S=0$&lt;/span&gt; channel. For magnetic systems both S=0 and S=1 solutions can be obtained (but always with &lt;span class=&quot;math-container&quot;&gt;$S_z=0$&lt;/span&gt;). For the case with SOC all excitons are computed. This is discussed in details in one of my recent &lt;a href=&quot;https://arxiv.org/abs/2103.02266&quot; rel=&quot;nofollow noreferrer&quot;&gt;arxiv articles&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally let me add a comment on other possible approaches beyond BSE. For extended system quantum chemistry approaches are not feasible. TDDFT cannot capture the physics of the exciton at &lt;span class=&quot;math-container&quot;&gt;$q=0$&lt;/span&gt;, one would need TDPolarizationDFT or do the &lt;span class=&quot;math-container&quot;&gt;$q\rightarrow0$&lt;/span&gt; limit of finite momentum TDDFT. However for neither there exist good functionals able to properly describe excitons. One of the reasons is that the exciton requires a long range interaction which cannot be easily captured by these theories. Despite all this, the structure of the TDDFT equations is the same as the one of BSE. So all the above considerations for BSE apply. Instead I'm not an expert on quantum Monte Carlo and I cannot add much on this.&lt;/p&gt;&#xA;" OwnerUserId="5685" LastEditorUserId="7" LastEditDate="2022-07-11T13:37:37.070" LastActivityDate="2022-07-11T13:37:37.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9344" PostTypeId="2" ParentId="9341" CreationDate="2022-07-07T02:32:24.233" Score="5" Body="&lt;p&gt;The Elastic constants are calculated within vasp using IBRION=6 and ISIF=3. The Elastic constants are calculated from stress-strain relationship by applying finite distortion of lattice and ions. POTIM and NFREE are important parameter here.The elastic tensor is calculated both, for rigid ions, as well, as allowing for relaxation of the ions.&lt;/p&gt;&#xA;&lt;p&gt;The elastic moduli for rigid ions are written after the line &lt;strong&gt;SYMMETRIZED ELASTIC MODULI (kBar)&lt;/strong&gt;.&#xA;The final elastic moduli including both, the contributions for distortions with rigid ions and the contributions from the ionic relaxations are written in &lt;strong&gt;TOTAL ELASTIC MODULI (kBar)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not a great fan of IBRION=6 which calculates elastic constants from stress-strain relationship. I prefer energy-stain relationship, where based on symmetry of crystal, we distort the crystal by several finite value followed by fitting the curve into second order polynomial to extract component of second order elastic constants. You can look into &lt;code&gt;vaspkit&lt;/code&gt; manual or any other package for performing calculation. It will cutdown computational cost by several fold.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT: 1&lt;/strong&gt; &lt;br /&gt;&#xA;Recently we have also developed a python based tool to calculate second order elastic constants from strain-energy method.&#xA;&lt;a href=&quot;https://github.com/prnvrvs/elastic_vasp&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/prnvrvs/elastic_vasp&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-07-27T07:57:27.873" LastActivityDate="2022-07-27T07:57:27.873" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9345" PostTypeId="1" CreationDate="2022-07-07T14:13:33.737" Score="5" ViewCount="1226" Body="&lt;p&gt;I am currently working on a machine learning with spectroscopy. I had learnt about the Franck-Condon principle and the vibronic coupling in photochemistry courses in my undergraduate lectures. However, in computational chemistry when electronic spectra (absorption) are calculated with TD-DFT for example, I find the usage of the terms &amp;quot;vertical excitation&amp;quot; and &amp;quot;0-0 transition&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;I am struggling to understand what they mean and what their link with the peak in experimental absoroption spectrum is. For example, here is a UV-visible absorption spectrum of BODIPY dye:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xbs7zm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xbs7zm.png&quot; alt=&quot;BODIPY UV-visible absorption spectrum with peak at 498 nm&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now I used to think that the absorption peak here (498 nm) corresponds closest to results of the &amp;quot;vertical excitation&amp;quot;, since the light absorption in experiment is faster than nuclear movement. But recently I saw a paper where they were using &amp;quot;0-0 transitions&amp;quot; to compare against experiment. I had the impression from the photochemistry lectures that the &amp;quot;0-0 transition&amp;quot; is usually not the peak in experimental spectrum due to Franck-Condon effects:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/k6V2mm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k6V2mm.png&quot; alt=&quot;Frank-Condon excitation&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could someone please help me understand these terms and what their link to the experimental spectrum is?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="5" LastEditDate="2022-07-07T18:03:39.780" LastActivityDate="2022-07-09T16:05:11.810" Title="Vertical transition, 0-0 transition, and experimental spectra" Tags="|spectroscopy|td-dft|excited-states|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9346" PostTypeId="2" ParentId="9345" CreationDate="2022-07-07T16:29:41.470" Score="7" Body="&lt;p&gt;Yes, the absorption maximum is usually close to (but not necessarily exactly equal to) the vertical excitation from the ground state, due to the Franck-Condon principle. However, this does not mean that the 0-0 excitation energy is not experimentally measurable. The point is that, when one approximates the ground and excited state potential energy surfaces as quadratic surfaces with the same quadrature, one can show that the 0-0 energy is exactly the average of the Franck-Condon absorption energy and the Franck-Condon fluorescence energy. Therefore, one can derive an experimental estimate of the 0-0 energy from an average of the experimental absorption and fluorescence energies. Some similar but slightly different alternatives are (1) averaging the absorption and fluorescence wavelengths instead (which is not equivalent to averaging the excitation energies due to the non-linear relationship between wavelengths and excitation energies), and (2) plotting both the absorption and fluorescence spectra, find the intersection point of the two spectra, and read off the corresponding excitation energy. I'm not sure which of the three strategies is the best, but mathematically they should give quite similar results for systems whose Stokes shift is not too large; when the Stokes shift is very large, all methods should become unreliable since the quadratic approximation of the PESs break down (EDIT: this holds for most, if not all, realistic molecular PESs, but does not necessarily hold for artificial PESs, such as those that are by construction globally quadratic. Thanks Hans Wurst for pointing this out).&lt;/p&gt;&#xA;&lt;p&gt;Moreover, some experiments may probe the 0-0 energy directly. One obvious example is the high-precision experiments that exhaustively enumerate all low-lying vibronic levels, fit potential energy surfaces based on the data and read off the 0-0 energy from the PESs. Another example is to extract the 0-0 energy from ground state and excited state reactions. Say you have measured the equilibrium constants of the reactions &lt;span class=&quot;math-container&quot;&gt;$A + B \to A^+ + B^-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A^* + C \to A^+ + C^-$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$A^*$&lt;/span&gt; is one of the excited states of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, and you know the redox potentials of the &lt;span class=&quot;math-container&quot;&gt;$B/B^-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C/C^-$&lt;/span&gt; couples. Then you can calculate the 0-0 Gibbs free energy of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;; extrapolation to zero temperature yields the 0-0 energy of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Finally, there is a trivial case for gas phase measurements of very small molecules. In this case the vibronic levels are usually highly resolved, and chances are that the 0-0 excitation appears as an isolated peak that does not overlap excessively with other vibronic peaks. In this case you can directly obtain the 0-0 excitation energy from experiment, provided that you can correctly assign the 0-0 peak.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-07-09T16:05:11.810" LastActivityDate="2022-07-09T16:05:11.810" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9347" PostTypeId="2" ParentId="9345" CreationDate="2022-07-07T18:27:39.630" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I find the usage of the terms &amp;quot;vertical excitation&amp;quot; and &amp;quot;0-0 transition&amp;quot;. I am struggling to understand what they mean&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The 0-0 transition is from &lt;span class=&quot;math-container&quot;&gt;$v^{\prime\prime}=0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$v^\prime = 0$&lt;/span&gt;, whereas &amp;quot;vertical&amp;quot; means that it's vertical on a plot of the energy vs the nuclear geometry: the blue &lt;span class=&quot;math-container&quot;&gt;$v^{\prime\prime}=0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$v^\prime = 2$&lt;/span&gt; line in your plot.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Now I used to think that the absorption peak here (498 nm) corresponds closest to results of the &amp;quot;vertical excitation&amp;quot;, since the light absorption in experiment is faster than nuclear movement. But recently I saw a paper where they were using &amp;quot;0-0 transitions&amp;quot; to compare against experiment.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It depends on the type of experiment. Without seeing the original paper containing the absorption peak  at 498 nm, or the original paper that uses 0-0 transitions to compare to experiment, it's hard to give a general answer.&lt;/p&gt;&#xA;&lt;p&gt;If the experiment uses a laser to excite the molecule, and the laser's peak wavelength exactly matches the energy gap between &lt;span class=&quot;math-container&quot;&gt;$v^{\prime\prime}=0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$v^\prime = 0$&lt;/span&gt;, it won't be a surprise if the peak in the absorption corresponds to a &amp;quot;0-0 transition&amp;quot;. In two-color phooassociation experiments,  a molecule is created in an arbitrary &lt;span class=&quot;math-container&quot;&gt;$v^\prime$&lt;/span&gt; state, then de-excited to an arbitrary &lt;span class=&quot;math-container&quot;&gt;$v^{\prime\prime}$&lt;/span&gt; depending on the two &amp;quot;colors&amp;quot; of the laser.&lt;/p&gt;&#xA;&lt;p&gt;If you shine light on a molecule with a wide spectrum of equally distribted frequencies, then the peak absorption would likely happen where the Franck-Condon overlap is greatest. &lt;strong&gt;This can be calculated by obtaining the wavefunctions of the ground and excited states and doing an integral.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the case of the BODIPY figure in your question, perhaps you can calculate the &lt;span class=&quot;math-container&quot;&gt;$v=0$&lt;/span&gt; energy of the ground state and the excited state, and see if 498nm is much greater than the difference. If it's much greater, then perhaps we're looking at a 0-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; transition where &lt;span class=&quot;math-container&quot;&gt;$n&amp;gt;0$&lt;/span&gt; (and perhaps it's vertical, but I won't say that it's guaranteed!).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-07-07T18:27:39.630" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9348" PostTypeId="1" CreationDate="2022-07-07T20:41:17.000" Score="8" ViewCount="59" Body="&lt;p&gt;The concept of an atom in a molecule is undefined in quantum mechanics. Consequently, very useful properties like atomic charges, bond orders, and so on cannot be rigorously defined. There are many methods for defining these and other atomic quantities for atoms in a molecule. All of these methods are arbitrary and just try to satisfy principles that one might expect to be important.&lt;/p&gt;&#xA;&lt;p&gt;One of the main strategies for defining atomic charges is based on partitioning the electron density into atomic regions and integrating the density of this atomic region.&lt;/p&gt;&#xA;&lt;p&gt;A big reason one would want to define an atomic charge is to parameterize a force field. Force fields often work by calculating an energy for every atom in a system and then summing these atomic energies to get the total energy.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Have there been any attempts to directly define an atomic energy from a density partitioning scheme?&lt;/strong&gt; In particular, &lt;strong&gt;is there any way to divide the total electronic energy of a molecular system into atomic components describing the electronic stabilization contributed by a particular atom?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This would be a rather strange quantity in many ways, but it is also a quantity commonly calculated in force fields, so even an approximate definition of this based on quantum mechanically calculated densities seems like it would be of interest.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="24" LastEditDate="2022-07-07T23:07:03.773" LastActivityDate="2022-07-08T13:00:17.917" Title="Attempts to define atomic energies based on electron density?" Tags="|reference-request|electronic-structure|forcefields|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9349" PostTypeId="1" CreationDate="2022-07-07T23:14:56.747" Score="7" ViewCount="772" Body="&lt;p&gt;The one-electron reduced density matrix (1RDM) contains information useful for the prediction of molecular properties (for instance, dipole moments). As an example, the 1RDM can be easily obtained in pySCF for the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt; by:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf&#xA;&#xA;mol = pyscf.M(&#xA;    atom = 'H 0 0 0; F 0 0 1.1',&#xA;    basis = 'ccpvdz')&#xA;&#xA;mf = mol.HF().run()&#xA;mycc = mf.CISD().run()&#xA;&#xA;dm1 = mycc.make_rdm1()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;giving:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;array([[ 1.99994077e+00, -1.99162245e-04, -7.87231222e-05,&#xA;        -9.53691579e-19, -9.50673436e-20, -2.30038238e-05,&#xA;         1.84071578e-05, -2.70900398e-17,  1.47460417e-16,&#xA;        -1.60886286e-04, -1.14196814e-16, -1.91359638e-16,&#xA;         1.67836021e-04, -2.20982363e-04, -4.94641186e-19,&#xA;         6.25007588e-18,  5.02802627e-18, -1.03628178e-17,&#xA;         1.11486983e-05],&#xA;       [-1.99162245e-04,  1.98848063e+00,  6.13179991e-03,&#xA;         4.08139213e-18, -9.19419529e-19,  1.76764571e-03,&#xA;        -2.80098013e-03,  2.23749372e-16,  1.96829216e-17,&#xA;         6.47137404e-03,  1.34300623e-16,  8.07794933e-18,&#xA;         4.05861098e-03, -3.70627178e-04, -8.38703764e-19,&#xA;         5.35827360e-18, -9.79839661e-18,  4.01319679e-19,&#xA;         4.31669973e-04],&#xA;       [-7.87231222e-05,  6.13179991e-03,  1.96133369e+00,&#xA;        -1.06540989e-17,  3.71419450e-18, -2.13975050e-02,&#xA;        -1.34538561e-02,  1.24728207e-17, -3.65798882e-16,&#xA;        -1.07773571e-02, -7.72135156e-17, -2.80257053e-16,&#xA;        -1.70765070e-02, -2.41959181e-03,  3.03116775e-18,&#xA;         5.42133662e-19,  7.04961364e-20, -1.81295382e-17,&#xA;         2.56630622e-03],&#xA;       [-9.53691579e-19,  4.08139213e-18, -1.06540989e-17,&#xA;         1.98087586e+00, -2.42526709e-18, -4.00633524e-16,&#xA;         6.82988337e-17,  1.45808332e-03, -7.75567418e-03,&#xA;         2.02353702e-17, -3.90555928e-04, -2.27416768e-03,&#xA;         3.59002056e-19,  1.15318072e-16, -2.66714325e-17,&#xA;         3.79612632e-16,  2.00404079e-04,  4.35714707e-04,&#xA;        -1.76355694e-17],&#xA;       [-9.50673436e-20, -9.19419529e-19,  3.71419450e-18,&#xA;        -2.42526709e-18,  1.98087586e+00,  7.68379095e-17,&#xA;         2.96383736e-17, -7.75567418e-03, -1.45808332e-03,&#xA;         2.03613686e-18, -2.27416768e-03,  3.90555928e-04,&#xA;         3.18752574e-17,  8.58758188e-18,  1.32729655e-17,&#xA;         1.15457073e-17,  4.35714707e-04, -2.00404079e-04,&#xA;         1.01725219e-17],&#xA;       [-2.30038238e-05,  1.76764571e-03, -2.13975050e-02,&#xA;        -4.00633524e-16,  7.68379095e-17,  1.84368423e-02,&#xA;         1.45015635e-02, -5.82749480e-18, -1.19950717e-17,&#xA;        -5.16805460e-03, -4.05467609e-18, -3.32237435e-18,&#xA;        -7.52408964e-03, -7.56030680e-04,  2.06258966e-19,&#xA;        -6.79531535e-19,  2.36816792e-19,  1.29010476e-20,&#xA;        -1.38189704e-05],&#xA;       [ 1.84071578e-05, -2.80098013e-03, -1.34538561e-02,&#xA;         6.82988337e-17,  2.96383736e-17,  1.45015635e-02,&#xA;         1.25647125e-02, -5.04136605e-18, -3.79435707e-18,&#xA;        -4.41175502e-03, -4.92110092e-18, -7.88552981e-18,&#xA;        -5.56377189e-03, -2.23572205e-03,  3.62979262e-19,&#xA;        -9.42389633e-19,  8.25935435e-19,  1.18034368e-18,&#xA;         3.96084024e-04],&#xA;       [-2.70900398e-17,  2.23749372e-16,  1.24728207e-17,&#xA;         1.45808332e-03, -7.75567418e-03, -5.82749480e-18,&#xA;        -5.04136605e-18,  1.00099863e-02,  2.38122851e-17,&#xA;        -2.52114787e-18, -5.12613672e-03,  1.90552589e-03,&#xA;         2.95515608e-18,  1.00932446e-18, -8.80853860e-18,&#xA;         2.26350025e-18,  7.41491643e-04, -5.25910649e-04,&#xA;         4.53998014e-19],&#xA;       [ 1.47460417e-16,  1.96829216e-17, -3.65798882e-16,&#xA;        -7.75567418e-03, -1.45808332e-03, -1.19950717e-17,&#xA;        -3.79435707e-18,  2.38122851e-17,  1.00099863e-02,&#xA;         1.48963223e-17, -1.90552589e-03, -5.12613672e-03,&#xA;         9.27272866e-18, -1.90427871e-19,  1.78058821e-18,&#xA;        -3.70031467e-18,  5.25910649e-04,  7.41491643e-04,&#xA;         1.86549196e-19],&#xA;       [-1.60886286e-04,  6.47137404e-03, -1.07773571e-02,&#xA;         2.02353702e-17,  2.03613686e-18, -5.16805460e-03,&#xA;        -4.41175502e-03, -2.52114787e-18,  1.48963223e-17,&#xA;         6.93767668e-03,  2.20079534e-18, -1.64256033e-18,&#xA;         1.03536996e-03,  2.60881775e-03,  7.83668113e-20,&#xA;        -1.47994181e-18,  3.62037203e-19,  1.58980841e-18,&#xA;         1.11321275e-03],&#xA;       [-1.14196814e-16,  1.34300623e-16, -7.72135156e-17,&#xA;        -3.90555928e-04, -2.27416768e-03, -4.05467609e-18,&#xA;        -4.92110092e-18, -5.12613672e-03, -1.90552589e-03,&#xA;         2.20079534e-18,  4.45577120e-03,  1.51402375e-17,&#xA;         3.46729881e-18, -5.01502863e-19, -2.15430415e-18,&#xA;         4.61799403e-18,  7.25292075e-04, -1.93732359e-04,&#xA;        -7.52894088e-19],&#xA;       [-1.91359638e-16,  8.07794933e-18, -2.80257053e-16,&#xA;        -2.27416768e-03,  3.90555928e-04, -3.32237435e-18,&#xA;        -7.88552981e-18,  1.90552589e-03, -5.12613672e-03,&#xA;        -1.64256033e-18,  1.51402375e-17,  4.45577120e-03,&#xA;         6.08876803e-18,  2.82738131e-18,  2.46975026e-18,&#xA;         6.50590972e-18,  1.93732359e-04,  7.25292075e-04,&#xA;        -7.55165672e-19],&#xA;       [ 1.67836021e-04,  4.05861098e-03, -1.70765070e-02,&#xA;         3.59002056e-19,  3.18752574e-17, -7.52408964e-03,&#xA;        -5.56377189e-03,  2.95515608e-18,  9.27272866e-18,&#xA;         1.03536996e-03,  3.46729881e-18,  6.08876803e-18,&#xA;         5.26811829e-03, -1.01060468e-03, -2.64539985e-19,&#xA;         1.60654807e-18, -1.37431011e-19,  8.03483700e-19,&#xA;        -5.26829940e-04],&#xA;       [-2.20982363e-04, -3.70627178e-04, -2.41959181e-03,&#xA;         1.15318072e-16,  8.58758188e-18, -7.56030680e-04,&#xA;        -2.23572205e-03,  1.00932446e-18, -1.90427871e-19,&#xA;         2.60881775e-03, -5.01502863e-19,  2.82738131e-18,&#xA;        -1.01060468e-03,  3.76975815e-03, -1.88963598e-19,&#xA;        -4.45613527e-20,  3.86855826e-19,  5.15586386e-19,&#xA;        -7.78185559e-04],&#xA;       [-4.94641186e-19, -8.38703764e-19,  3.03116775e-18,&#xA;        -2.66714325e-17,  1.32729655e-17,  2.06258966e-19,&#xA;         3.62979262e-19, -8.80853860e-18,  1.78058821e-18,&#xA;         7.83668113e-20, -2.15430415e-18,  2.46975026e-18,&#xA;        -2.64539985e-19, -1.88963598e-19,  2.88726905e-03,&#xA;         3.41776421e-10,  1.32473979e-18, -1.84940088e-18,&#xA;         3.59982084e-19],&#xA;       [ 6.25007588e-18,  5.35827360e-18,  5.42133662e-19,&#xA;         3.79612632e-16,  1.15457073e-17, -6.79531535e-19,&#xA;        -9.42389633e-19,  2.26350025e-18, -3.70031467e-18,&#xA;        -1.47994181e-18,  4.61799403e-18,  6.50590972e-18,&#xA;         1.60654807e-18, -4.45613527e-20,  3.41776421e-10,&#xA;         2.88726834e-03, -2.09437953e-18, -1.29027293e-18,&#xA;        -1.79752988e-18],&#xA;       [ 5.02802627e-18, -9.79839661e-18,  7.04961364e-20,&#xA;         2.00404079e-04,  4.35714707e-04,  2.36816792e-19,&#xA;         8.25935435e-19,  7.41491643e-04,  5.25910649e-04,&#xA;         3.62037203e-19,  7.25292075e-04,  1.93732359e-04,&#xA;        -1.37431011e-19,  3.86855826e-19,  1.32473979e-18,&#xA;        -2.09437953e-18,  2.55700661e-03,  1.80635235e-18,&#xA;         4.73014873e-20],&#xA;       [-1.03628178e-17,  4.01319679e-19, -1.81295382e-17,&#xA;         4.35714707e-04, -2.00404079e-04,  1.29010476e-20,&#xA;         1.18034368e-18, -5.25910649e-04,  7.41491643e-04,&#xA;         1.58980841e-18, -1.93732359e-04,  7.25292075e-04,&#xA;         8.03483700e-19,  5.15586386e-19, -1.84940088e-18,&#xA;        -1.29027293e-18,  1.80635235e-18,  2.55700661e-03,&#xA;         2.13939315e-19],&#xA;       [ 1.11486983e-05,  4.31669973e-04,  2.56630622e-03,&#xA;        -1.76355694e-17,  1.01725219e-17, -1.38189704e-05,&#xA;         3.96084024e-04,  4.53998014e-19,  1.86549196e-19,&#xA;         1.11321275e-03, -7.52894088e-19, -7.55165672e-19,&#xA;        -5.26829940e-04, -7.78185559e-04,  3.59982084e-19,&#xA;        -1.79752988e-18,  4.73014873e-20,  2.13939315e-19,&#xA;         1.69602024e-03]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am interested in how to derive properties from the 1RDM and if there are any open source codes that can be used to calculate properties in this way. For instance, how does one obtain the dipole moment.&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2022-07-16T02:08:20.720" LastActivityDate="2022-09-27T10:23:24.567" Title="What information does the 1RDM contain?" Tags="|quantum-chemistry|ab-initio-calculations|software-recommendations|pyscf|reduced-density-matrix|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9351" PostTypeId="1" AcceptedAnswerId="10183" CreationDate="2022-07-08T00:56:00.003" Score="14" ViewCount="166" Body="&lt;p&gt;I know it is possible to measure electron densities from certain types of scattering experiments.&lt;/p&gt;&#xA;&lt;p&gt;Have these densities ever been fed into density functionals to calculate energies and other properties? If so, is this useful for testing the veracity of functionals in any way? Can functionals be designed such that the converged density is consistent with these experimental densities?&lt;/p&gt;&#xA;&lt;p&gt;If not, what are the difficulties associated with doing these calculations?&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2023-01-03T07:44:58.980" Title="Have experimental electron densities ever been used in a DFT calculation?" Tags="|density-functional-theory|electronic-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9352" PostTypeId="1" AcceptedAnswerId="11280" CreationDate="2022-07-08T03:11:38.857" Score="6" ViewCount="85" Body="&lt;p&gt;Are there any repositories of crystal surfaces?  Due to orientation / termination of surfaces, occasionally it is non-trivial to decide how exactly to cut a surface for things such as oxides.  I imagine there is some effort to do this for binding energies of common adsorbates and the sort, but I am more interested in something like Materials Project but for surface energies and structures.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2023-08-07T20:34:45.640" Title="Repository of Common Surfaces" Tags="|reference-request|crystallography|surfaces|databases|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9353" PostTypeId="2" ParentId="9348" CreationDate="2022-07-08T13:00:17.917" Score="2" Body="&lt;p&gt;Disclaimer: This is not a full answer to your question.&lt;/p&gt;&#xA;&lt;p&gt;However, an interesting idea regarding electron partitioning between atoms is presented in this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.166403&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. They use the topology of the wave function, together with Berry phase-like quantities, and are able to, for example, define oxidation states in solids.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-07-08T13:00:17.917" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9354" PostTypeId="1" CreationDate="2022-07-08T13:33:36.283" Score="5" ViewCount="162" Body="&lt;p&gt;Bloch's theorem can be stated as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;|\Psi_{n\vec{k}}\rangle=e^{i\vec{k}\cdot\vec{r}}|u_{n\vec{k}}(\vec{r})\rangle \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$|\Psi_{n\vec{k}}\rangle$&lt;/span&gt; is the solution of single electron Schrodinger equation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;(T+V)|\psi_n(\vec{k})\rangle=H|\psi_{n\vec{k}}\rangle =E_{n\vec{k}}|\psi_{n\vec{k}}\rangle  \tag{2}&#xA;$$&lt;/span&gt;&#xA;with &lt;span class=&quot;math-container&quot;&gt;$V(\vec{r}+\vec{R})=V(\vec{r})$&lt;/span&gt; [&lt;span class=&quot;math-container&quot;&gt;$\vec{R}$&lt;/span&gt; is the translational vector in real space], and &lt;span class=&quot;math-container&quot;&gt;$u_{n\vec{k}}(\vec{r})$&lt;/span&gt; in Eq.(1) is periodical in &lt;span class=&quot;math-container&quot;&gt;$\vec{R}$&lt;/span&gt;. By multiplying &lt;span class=&quot;math-container&quot;&gt;$e^{-i\vec{k}\cdot\vec{r}}$&lt;/span&gt; on both sides of Eq.(2), we find:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\bar{H}|u_{n\vec{k}}(\vec{r})=E_{n\vec{k}}|u_{n\vec{k}}\rangle \tag{3}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\bar{H} \equiv e^{-i\vec{k}\cdot\vec{r}} H e^{+i\vec{k}\cdot\vec{r}}$&lt;/span&gt;. From this eigenequation, we can obtain the completeness relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sum_n |u_{n\vec{k}}(\vec{r})\rangle \langle u_{n\vec{k}}(\vec{r})|=1 \tag{4}&#xA;$$&lt;/span&gt;&#xA;and also this completeness relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\int d\vec{k} \sum_n |u_{n\vec{k}}(\vec{r})\rangle \langle u_{n\vec{k}}(\vec{r})|=1 \tag{5}&#xA;$$&lt;/span&gt;&#xA;Now my question is which one is correct? It seems that Eq.(4) is usually used in the community of solid-state physics while Eq.(5) is generally used in the community of nonlinear optics. &lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-07-08T18:27:19.137" LastActivityDate="2022-07-10T02:14:52.627" Title="What's the completeness relation of Bloch band?" Tags="|condensed-matter|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9355" PostTypeId="1" AcceptedAnswerId="9357" CreationDate="2022-07-08T17:02:55.403" Score="2" ViewCount="655" Body="&lt;p&gt;I am studying a system with TD-DFT method implemented in Gaussian. I am not sure whether this two inputs are adequate by the mean of output - optimization of T1?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p b3lyp/6-31G* TD=(triplets,root=1) opt&#xA;&#xA;title&#xA;&#xA;0 1&#xA;&amp;lt;geometry&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p b3lyp/6-31G* TD=(triplets,root=1) opt&#xA;&#xA;title&#xA;&#xA;0 3&#xA;&amp;lt;geometry&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5606" LastEditorUserId="5606" LastEditDate="2022-07-08T17:25:33.553" LastActivityDate="2022-07-08T18:58:37.153" Title="A different way to optimize triplets?" Tags="|density-functional-theory|gaussian|geometry-optimization|td-dft|photochemistry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9356" PostTypeId="2" ParentId="9354" CreationDate="2022-07-08T18:57:10.447" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;From this eigenequation, we can obtain the completeness relation&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You don't need that eigenequation to obtain the completeness relation. As long as you have a &amp;quot;complete&amp;quot; set of orthonormal vectors in a Hilbert Space (for example &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; linearly independent vectors in an &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-dimensional Hilbert space) the completeness relation holds. &lt;a href=&quot;https://physics.stackexchange.com/q/251803/134583&quot;&gt;More about this has been discussed on the Physics Stack Exchange&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Some Hilbert spaces have a finite dimension (for example, the operators describing spin-1/2 particles) and the completeness relation is  &lt;span class=&quot;math-container&quot;&gt;$\sum_n |\psi_n\rangle \langle \psi_n | $&lt;/span&gt; where the number of terms in the sum is the dimension of the Hilbert space (which is finite, and equal to 2 in the case of spin-1/2 particles, equal to in the case of spin-1 particles, equal to 4 in the case of spin-3/2 particles, etc.).  But some Hilbert spaces are used for continuous quantum mechanical variables such as the position &lt;span class=&quot;math-container&quot;&gt;$\hat{x}$&lt;/span&gt;, in which the completeness relation is &lt;span class=&quot;math-container&quot;&gt;$\int |\psi_x\rangle \langle \psi_x|\textrm{d}x$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What you're seeing in Eq. 5 is the combination of two completeness relations. For example if you have wavefunctions which depend on spin &lt;span class=&quot;math-container&quot;&gt;$\hat{s}$&lt;/span&gt; and position &lt;span class=&quot;math-container&quot;&gt;$\hat{x}$&lt;/span&gt; at the same time, then we have the following two completeness relations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\sum_s |\psi_{sx}\rangle \langle \psi_{sx}| &amp;amp;= 1 \tag{1}\\&#xA;\int  |\psi_{sx}\rangle \langle \psi_{sx}| \textrm{d}x&amp;amp;= 1. \tag{2}\\&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Combining the two, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\int \sum_s |\psi_{sx}\rangle \langle \psi_{sx}|\textrm{d}x &amp;amp;= 1.\tag{3}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-07-08T18:57:10.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9357" PostTypeId="2" ParentId="9355" CreationDate="2022-07-08T18:58:37.153" Score="5" Body="&lt;p&gt;At least when the ground state of the molecule is a singlet state, the first one is correct, and the second one is wrong. Note that when &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; is the ground state of the molecule, a triplet ground state calculation, such as from the following input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p b3lyp/6-31G* opt&#xA;&#xA;title&#xA;&#xA;0 3&#xA;&amp;lt;geometry&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;actually calculates the &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state, because in this case the lowest triplet state is &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt; (which does not exist). Therefore, your second input file calculates the first triplet state that is above the triplet ground state, i.e. it calculates &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;An immediate follow-up question is: should you use your first input file or the input file that I just mentioned, given that both calculate the &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state? Actually, when the exact functional and an infinite basis set are used, the two calculations are equivalent. So the best choice is the one that provides the best cost/performance ratio for approximate functionals. Specifically:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Use your first input file when your &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; state is single-referential and your &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state is multireferential. Only by this way can you have a single-referential reference state, and minimize errors due to static correlation.&lt;/li&gt;&#xA;&lt;li&gt;Use my input file when either (1) your &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state is single-referential and your &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; state is multireferential; (2) your &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; state has a triplet instability or a near triplet instability; (3) your &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state has significant charge-transfer character, but for some reason you have to use B3LYP which is known to perform poorly for charge transfer excitations; or (4) your &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; state has significant double excitation character when viewed from a &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; reference. Either one of these four situations make the linear response TDDFT calculation of &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; unreliable, or at least much less reliable than it would otherwise be.&lt;/li&gt;&#xA;&lt;li&gt;When the two methods are equally good in terms of accuracy, use my input file, since it is computationally faster.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-07-08T18:58:37.153" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9358" PostTypeId="2" ParentId="9320" CreationDate="2022-07-08T20:35:44.560" Score="2" Body="&lt;p&gt;Unfortunately there's &lt;a href=&quot;https://en.wikipedia.org/wiki/Dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;so many uses&lt;/a&gt; of the term &lt;a href=&quot;https://en.wiktionary.org/wiki/dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;dynamics&amp;quot;&lt;/a&gt; that it can be hard for a beginner to figure out what it means, even if they're highly experienced in internet searches and dictionary usage!&lt;/p&gt;&#xA;&lt;p&gt;It's the study of &lt;em&gt;&lt;strong&gt;how things change&lt;/strong&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately every definition I see online, for example &lt;a href=&quot;https://en.wikipedia.org/wiki/Dynamics_(mechanics)&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, is less clear, so this is probably just learned over time by seeing it used in more and more places until you develop confidence that you mean the same things as others in your field, and they mean the same as you, when using the term.&lt;/p&gt;&#xA;&lt;p&gt;The paper that you mentioned, despite being called &amp;quot;protein dynamics&amp;quot;, doesn't actually use the word &amp;quot;dynamics&amp;quot; a lot, and doesn't define it, and doesn't use it until quite late into the paper. However they do mention the term &amp;quot;molecular dynamics&amp;quot;, which &lt;strong&gt;does&lt;/strong&gt; have a fairly decent &lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;encyclopedia article&lt;/a&gt;. I have also given my own (hopefully simpler and easier to follow) explanations of molecular dynamics in these MMSE answers:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4735/5&quot;&gt;How to calculate the volumetric energy density of a molecule?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4817/5&quot;&gt;How do I simulate the interaction between two atoms?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6871/5&quot;&gt;How would one find a material's equilibrium structure at any specific temperature?&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;/questions/tagged/molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;molecular-dynamics&lt;/a&gt; is the most popular dynamics tag on this site. Most of the time when you see the word &amp;quot;dynamics&amp;quot; in the matter modeling community, it will be in the phrase &amp;quot;molecular dynamics&amp;quot;. There's also terms like &lt;a href=&quot;/questions/tagged/quantum-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;quantum-dynamics&amp;#39;&quot; rel=&quot;tag&quot;&gt;quantum-dynamics&lt;/a&gt;, which is the study of how a quantum mechanical wavefunction changes, but this term is far less popular overall, and almost unheard of when studying proteins and biomolecules (which was the focus of your question). If you see the term &amp;quot;dynamics&amp;quot; in a matter modeling article with no indication as to whether the author is discussing molecular dynamics, quantum dynamics, electrodynamics, metadynamics, or something else,  &lt;strong&gt;just remember that the author is most likely talking about something that is moving or changing&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-07-08T20:35:44.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9360" PostTypeId="1" CreationDate="2022-07-09T15:53:46.080" Score="2" ViewCount="175" Body="&lt;p&gt;I am new to CP2K and doing a geometry optimization for a cluster. At the beginning everything looks good, each SCF step takes about 13 seconds, the energy drops quickly and the convergence looks like it converges in a few steps.&#xA;But after some time, the SCF step time quickly increased to a few hundred seconds and then to 3000 seconds. I checked everything but found no error.&lt;a href=&quot;https://i.stack.imgur.com/ronpH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ronpH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could you please provide me with some advise, thank you !&lt;/p&gt;&#xA;&lt;p&gt;Best,&#xA;Jessie&lt;/p&gt;&#xA;" OwnerUserId="5703" LastActivityDate="2022-07-09T15:53:46.080" Title="CP2K geometry optimization SCF takes 3000s for a step" Tags="|geometry-optimization|cp2k|energy-conversion|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-07T02:36:16.553" ContentLicense="CC BY-SA 4.0" />
  <row Id="9361" PostTypeId="2" ParentId="9354" CreationDate="2022-07-09T21:25:11.810" Score="5" Body="&lt;p&gt;I start from the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9356/5&quot;&gt;other existing answer&lt;/a&gt;, but I elaborate. Also in the question, the source of confusion is in part due to the bad notation.&lt;/p&gt;&#xA;&lt;p&gt;One can consider a wave function which depends on spin &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; and position &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, i.e. &lt;span class=&quot;math-container&quot;&gt;$\psi_{N}(x,s)$&lt;/span&gt;. Now, suppose you can write it as &lt;span class=&quot;math-container&quot;&gt;$\psi_{n\sigma}(x,s)=\phi_{n\sigma}(x)\chi_\sigma(s)$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$N=\{n\sigma\}$&lt;/span&gt; (this is possible if spin orbit coupling (SOC) is neglected in condensed matter). Then you have&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\sum_\sigma |\chi_\sigma\rangle\langle\chi_\sigma|=1 \tag{1}\\&#xA;\sum_n |\phi_{n\sigma}\rangle\langle\phi_{n\sigma}|=1 \tag{2}&#xA;\end{eqnarray}&lt;/span&gt;&#xA;and in general&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\sum_\sigma \sum_n |\psi_{n\sigma}\rangle\langle\psi_{n\sigma}|=1 \tag{3}&#xA;\end{eqnarray}&lt;/span&gt;&#xA;Notice that, for each spin channel &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; there is a complete basis set generated by the eigenstates of the spin dependent Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$h_\sigma$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you see the parallel with block states, you can do the same and define&#xA;&lt;span class=&quot;math-container&quot;&gt;$\Psi_{nk}(r+R)=u_{nk}(r)e^{ik(r+R)}$&lt;/span&gt;. Let me define &lt;span class=&quot;math-container&quot;&gt;$e_k(x)=e^{ikx}$&lt;/span&gt; the exponential function. You obtain&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\sum_n |u_{nk}\rangle\langle u_{nk}|=1 \tag{4}\\&#xA;\int dk |e_k\rangle\langle e_k|=1 \tag{5}&#xA;\end{eqnarray}&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\sum_n \int dk |\Psi_{nk}\rangle\langle\Psi_{nk}|=1\tag{6}&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5685" LastEditorUserId="5" LastEditDate="2022-07-10T02:14:52.627" LastActivityDate="2022-07-10T02:14:52.627" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9363" PostTypeId="1" AcceptedAnswerId="9364" CreationDate="2022-07-11T02:23:32.810" Score="4" ViewCount="493" Body="&lt;p&gt;I have been trying to model ZrNiSn Half Heusler using the eam potential in LAMMPS MD package. For this I use a single eam potential file with the descriptions of all the species available in it. Also, I want to see the effect of the addition of Ti atoms on the thermal conductivity. However, the eam potential file which I have supports only Zr, Ni and Sn.&lt;/p&gt;&#xA;&lt;p&gt;Even though I can find the eam potential for Ti on the &lt;a href=&quot;https://www.ctcms.nist.gov/potentials/system/Tl/&quot; rel=&quot;nofollow noreferrer&quot;&gt;internet&lt;/a&gt;, I am not sure about the ability of LAMMPS to model the Ti interactions with other species.&lt;/p&gt;&#xA;&lt;p&gt;Can someone confirm whether it is possible to use such a separate file to model the Ti interactions. Would LAMMPS be supplied with the required data on the interactions of Ti with other species if this is done?&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2022-07-11T04:21:53.733" Title="Is it possible to use multiple files to define eam potential in LAMMPS?" Tags="|lammps|interatomic-potentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9364" PostTypeId="2" ParentId="9363" CreationDate="2022-07-11T04:21:53.733" Score="8" Body="&lt;p&gt;In general, It is not recommended to mix two inter-atomic potential, Let me go through the consequences, You want to mix &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt;  &lt;code&gt;EAM&lt;/code&gt; potential to &lt;span class=&quot;math-container&quot;&gt;$\ce{Zr-Ni-Sn}$&lt;/span&gt;. You can do simply in lammps using pair style/overlays&#xA;For example&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pair_style hybrid lj/cut/coul/cut 10.0 eam lj/cut 5.0&#xA;pair_coeff 1*2 1*2 eam niu3&#xA;pair_coeff 3 3 lj/cut/coul/cut 1.0 1.0&#xA;pair_coeff 1*2 3 lj/cut 0.5 1.2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But Do you know interaction parameters for &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\ce{Zr}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Sn}$&lt;/span&gt;. In broader sense, for &lt;code&gt;EAM&lt;/code&gt; potential, you need three thing&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Embedded function&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Density function&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Pair-wise interaction&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Even If embedded function/density of &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti}$&lt;/span&gt; is same as &lt;span class=&quot;math-container&quot;&gt;$\ce{Zr}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Sn}$&lt;/span&gt;, you must know pairwise parameters for &lt;span class=&quot;math-container&quot;&gt;$\ce{Zr-Ti}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni-Ti}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Sn-Ti}$&lt;/span&gt; for &lt;code&gt;EAM/alloy&lt;/code&gt;. Things will be difficult if you want &lt;code&gt;EAM/fs&lt;/code&gt; where density function for each cross-term is needed. Don't forget, all parameters should also be fitted for some properties as well. It is also worthy to note that fitting X number of parameters of material doesn't guarantee to give qualitative results for different Y number of parameters.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-07-11T04:21:53.733" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9366" PostTypeId="2" ParentId="9316" CreationDate="2022-07-11T19:53:26.330" Score="6" Body="&lt;p&gt;As a first approximation, the total energy will depend on the number of electrons in valence for a given pseudo -potential. This should explain the huge difference in between the two set of calculations.&lt;/p&gt;&#xA;&lt;p&gt;Then, even if you consider pseudo potentials with the same number of electrons in valence there are many details which will influence the total energy. What makes more sense is to compute energy differences which can be related to some physical quantities.&lt;/p&gt;&#xA;&lt;p&gt;As suggested in one of the comments, you can for example compute the cohesive energy, i.e. The energy gain to form the material, by subtracting the energy of free atoms to the energy of the same atoms forming the solid. This will be comparable in between different pseudo potentials.&lt;/p&gt;&#xA;" OwnerUserId="5685" LastActivityDate="2022-07-11T19:53:26.330" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9367" PostTypeId="1" CreationDate="2022-07-12T00:40:29.017" Score="5" ViewCount="58" Body="&lt;p&gt;I understand the general concept of simulated annealing and have seen various criteria in papers, but I was wondering if there is a general rule of thumb for selecting a final structure, how many replicates one has to do, equilibration time (I’ve seen that it’s generally a few picoseconds) and selecting a max temperature when there isn’t an experimental melting curve. I used alpha fold to predict the structure of a small protein and want to do simulated annealing before starting extensive MD simulations - I could really use some general guidance on establishing a protocol.&lt;/p&gt;&#xA;" OwnerUserId="5711" LastActivityDate="2022-07-12T00:40:29.017" Title="Simulated annealing of small protein" Tags="|molecular-dynamics|proteins|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-01T03:47:14.023" ContentLicense="CC BY-SA 4.0" />
  <row Id="9369" PostTypeId="2" ParentId="4443" CreationDate="2022-07-12T08:05:39.173" Score="3" Body="&lt;p&gt;Well, certainly TD-DFT is not perfect, there are more accurate methods, but it's so popular since it's so efficient and much faster when compared to these other methods. Anyway, regarding your question, this a new paper published recently, and it shows very good correspondence with experimental data using TD-DFT:&#xA;&lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.12.011012&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.12.011012&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5070" LastActivityDate="2022-07-12T08:05:39.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9370" PostTypeId="1" CreationDate="2022-07-12T13:03:29.017" Score="4" ViewCount="33" Body="&lt;p&gt;By substituting a Ti atom in anatase &lt;span class=&quot;math-container&quot;&gt;$\text{TiO}_2$&lt;/span&gt; lattice with a Al atom, an oxygen hole &lt;span class=&quot;math-container&quot;&gt;$\text{O}^-$&lt;/span&gt; will be created considering a formal charge of +4 for Ti, -2 for O and +3 for Al .&lt;/p&gt;&#xA;&lt;p&gt;In this paper &amp;quot;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp407736f&quot; rel=&quot;nofollow noreferrer&quot;&gt;Intrinsic Oxygen Vacancy and Extrinsic Aluminum Dopant Interplay: A Route to the Restoration of Defective TiO2&lt;/a&gt;&amp;quot;, the authors applied the method of DFT+&lt;i&gt;U&lt;/i&gt; to investigate the energy level of such oxygen hole. By increasing the &lt;i&gt;U&lt;/i&gt; value, the energy level of oxygen hole was gradually raised from the top of the valance band of &lt;span class=&quot;math-container&quot;&gt;$\text{TiO}_2$&lt;/span&gt; to somewhere near the bottom of the conduction band. The authors stated that the reason to increase the &lt;i&gt;U&lt;/i&gt; value is for localizing the oxygen hole (displaying a rather localized charge density in real space).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My confusion is&lt;/strong&gt;: Why it is necessary for the oxygen hole to be localized?&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1483" LastEditorUserId="5" LastEditDate="2022-07-12T17:24:18.110" LastActivityDate="2022-07-12T17:24:18.110" Title="Understand the energy level of &quot;oxygen hole&quot; created by substitutional Al doping in TiO2" Tags="|electronic-structure|doping|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-10T03:07:14.707" ContentLicense="CC BY-SA 4.0" />
  <row Id="9371" PostTypeId="1" AcceptedAnswerId="9377" CreationDate="2022-07-12T16:42:38.033" Score="6" ViewCount="165" Body="&lt;p&gt;I am looking for databases for the solubility of pharmaceuticals (small drug molecules up to 1500 g/mol MW) in a variety of pure and mixed solvents.&lt;/p&gt;&#xA;&lt;p&gt;There is the &lt;a href=&quot;https://www.worldcat.org/title/handbook-of-solubility-data-for-pharmaceuticals/oclc/423572634&quot; rel=&quot;nofollow noreferrer&quot;&gt;Handbook of solubility data for pharmaceuticals&lt;/a&gt;, which can be purchased. Nowadays, I would expect there to be Git repo's similar to the FreeSolv database for hydration free energies. I am finding some data, and aqueous solubilities seem much more numerous i.e., &lt;a href=&quot;https://www.kaggle.com/datasets/sorkun/aqsoldb-a-curated-aqueous-solubility-dataset&quot; rel=&quot;nofollow noreferrer&quot;&gt;AqSolDB&lt;/a&gt;, but I would like data for training and testing models on solvents other than water as well.&lt;/p&gt;&#xA;&lt;p&gt;Open source would be great.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-07-14T13:47:10.577" LastActivityDate="2022-07-14T13:47:10.577" Title="Pharmaceutical solubility databases?" Tags="|databases|solubility|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9372" PostTypeId="1" AcceptedAnswerId="9375" CreationDate="2022-07-12T17:12:49.320" Score="4" ViewCount="591" Body="&lt;p&gt;I am trying to calculate the cohesive energy of certain metal oxides. However, I am only able to find a formula that is applicable to systems with a single element (say &lt;span class=&quot;math-container&quot;&gt;$\ce{Cu}$&lt;/span&gt; metal or &lt;span class=&quot;math-container&quot;&gt;$\ce{Si}$&lt;/span&gt; crystal), that is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_\text{cohesion} = E_\text{bulk(per atom)} - E_\text{isolated_atom}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(consider the example given &lt;a href=&quot;https://www.materialssquare.com/blog/3-1-how-to-calculate-cohesive-energy&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;What will be the formula to calculate the cohesive energy for a metal oxide such as &lt;span class=&quot;math-container&quot;&gt;$\ce{CuO}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\ce{SiO2}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="7" LastEditDate="2022-07-12T19:23:52.103" LastActivityDate="2022-07-13T05:25:27.053" Title="Cohesive Energy of a metal oxide" Tags="|quantum-espresso|semiconductor|metal-oxide|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9373" PostTypeId="1" AcceptedAnswerId="9417" CreationDate="2022-07-12T23:32:42.010" Score="1" ViewCount="94" Body="&lt;p&gt;I am planning to use python to get a plot like this &lt;a href=&quot;https://i.stack.imgur.com/Cd4dB.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cd4dB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;But, I am only able to get this, &lt;a href=&quot;https://i.stack.imgur.com/jWTtA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jWTtA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So, I would appreciate it if someone helps me with this issue,&#xA;(Maybe how to format the data):  &lt;strong&gt;How to have lower X-axis values highlighted like in the original plot.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Please check the code below and looking forward to your suggestions.&#xA;Numpy and Matplotlib are being used.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    x = [192, 188/4, 168/24, 144/48, 96/96]&#xA;    ys = [[2.20, 0.758, 0.691], [1.44, 0.708, 0.733], [0.491, 0.379, 0.440], [0.349, 0.350, 0.165], [0.199, 0.157, 0.163]]&#xA;    &#xA;    print(len(x), len(ys))&#xA;    colors = [[&amp;quot;r&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;g&amp;quot;], [&amp;quot;r&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;g&amp;quot;], [&amp;quot;r&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;g&amp;quot;], [&amp;quot;r&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;g&amp;quot;], [&amp;quot;r&amp;quot;, &amp;quot;y&amp;quot;, &amp;quot;g&amp;quot;]]&#xA;    print(colors)&#xA;    &#xA;    for y, x, c in zip(ys, x, colors):&#xA;    #     print(y, [x])&#xA;    #     print([x]*len(y))&#xA;        plt.scatter([x]*len(y), y, color = c)    &#xA;        &#xA;    &#xA;    plt.xticks([192, 188/4, 168/24, 144/48, 96/96])&#xA;    plt.xlabel(&amp;quot;Si/Al Ratio&amp;quot;)&#xA;    plt.ylabel(&amp;quot;Diff Coeff (Ang**2)&amp;quot;)&#xA;    # plt.legend(['Water_Cubic{}'.format(i) for i in [12, 24, 48]], loc=2, bbox_to_anchor=(1.05, 1), borderaxespad=0., fontsize=11)&#xA;    plt.title(&amp;quot;Si/Al vs Diff Coeff at 300k for Water Content (12, 24, 48)&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="5" LastEditDate="2022-07-13T01:41:35.703" LastActivityDate="2022-07-21T14:21:29.460" Title="Suggestion for getting a type of plot" Tags="|python|visualization-software|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9374" PostTypeId="1" AcceptedAnswerId="9402" CreationDate="2022-07-13T05:19:05.763" Score="8" ViewCount="2516" Body="&lt;p&gt;can anyone explain the pros and cons of using the Langevin vs Nosé–Hoover thermostat? I wonder how to choose a suitable thermostat for a system, such as oxide, organic materials.&lt;/p&gt;&#xA;" OwnerUserId="1352" LastActivityDate="2022-07-19T21:56:23.113" Title="Langevin vs Nosé–Hoover thermostat" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9375" PostTypeId="2" ParentId="9372" CreationDate="2022-07-13T05:25:27.053" Score="5" Body="&lt;p&gt;Calculate the total energy of the unit cell. Take each unique atom from your unit cell and calculate its energy in isolation. Take the full unit cell energy and subtract off the energy of each lone atom in your unit cell. That's the cohesive energy of your unit cell. Often you'll divide this by the number of formula units or atoms in the unit cell to obtain your cohesive energy per formula unit or atom, respectively.&lt;/p&gt;&#xA;&lt;p&gt;Putting this all together&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;E_{\mathrm{cohesion}} = \frac{E_{\mathrm{UC}} - \sum_{i}^{N} E_{i}}{F}&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{UC}}$&lt;/span&gt; is the total energy of the unit cell, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of atoms in the unit cell, and &lt;span class=&quot;math-container&quot;&gt;$E_{i}$&lt;/span&gt; is the energy of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th atom in the unit cell. &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is either the number of formula units or number of atoms per unit cell, depending on how you'd like to express your cohesive energy.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastActivityDate="2022-07-13T05:25:27.053" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9377" PostTypeId="2" ParentId="9371" CreationDate="2022-07-13T13:52:34.383" Score="5" Body="&lt;p&gt;The largest dataset I've seen for molecular solubilities, both computed solvation energies and experimental solvation free energies and &lt;span class=&quot;math-container&quot;&gt;$\log S$&lt;/span&gt; values is &lt;a href=&quot;https://zenodo.org/record/5970538#.Ys7Mmi-B1pR&quot; rel=&quot;noreferrer&quot;&gt;SolProp&lt;/a&gt; by the Green group, published as part of three papers:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/jacs.2c01768&quot; rel=&quot;noreferrer&quot;&gt;Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/acs.jcim.1c01103&quot; rel=&quot;noreferrer&quot;&gt;Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/j.cej.2021.129307&quot; rel=&quot;noreferrer&quot;&gt;Transfer learning for solvation free energies: From quantum chemistry to experiments&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I don't remember off-hand if they include AquaSol, but that database is known to have issues with some compounds.&lt;/p&gt;&#xA;&lt;p&gt;They explicitly do &lt;em&gt;not&lt;/em&gt; include the &lt;a href=&quot;https://comp.chem.umn.edu/mnsol/&quot; rel=&quot;noreferrer&quot;&gt;MNSol&lt;/a&gt; database of solvation free energies because of license issues. (MNSol is not for commercial use without paid license.)&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-07-13T13:52:34.383" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9378" PostTypeId="1" AcceptedAnswerId="9380" CreationDate="2022-07-13T15:38:56.460" Score="8" ViewCount="291" Body="&lt;p&gt;I consider that &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is a Hamiltonian describing a quantum system of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; spin-1/2 particles (or qubits). I assume it can be written as (the &lt;span class=&quot;math-container&quot;&gt;$\alpha_k^i$&lt;/span&gt; are real coefficients):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}H=\sum_{i=1}^3  \sum_{k=1}^{\textrm{Poly}(n)} \alpha^{i}_k P_i^{(k)},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where each &lt;span class=&quot;math-container&quot;&gt;$P_i^{(k)}$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$i=1,2,3$&lt;/span&gt;, is a tensor product of &lt;span class=&quot;math-container&quot;&gt;$\sigma_0\equiv\mathbb{I}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma_i$&lt;/span&gt; single spin Pauli operators. For instance, for &lt;span class=&quot;math-container&quot;&gt;$n=3$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$P_1^{(1)}=X \otimes X \otimes \mathbb{I}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$P_1^{(2)}=X \otimes X \otimes X$&lt;/span&gt; are allowed but &lt;span class=&quot;math-container&quot;&gt;$X \otimes \color{red}Z\color{black} \otimes X$&lt;/span&gt; is not (because it mixes &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt;). &lt;span class=&quot;math-container&quot;&gt;$\textrm{Poly}(n)$&lt;/span&gt; means that the number of terms in my sum is a polynomial in &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume that a quantum computer can find a good estimation of &lt;span class=&quot;math-container&quot;&gt;$\langle \psi | H | \psi \rangle$&lt;/span&gt; for an arbitrary &lt;span class=&quot;math-container&quot;&gt;$| \psi \rangle$&lt;/span&gt; in a short amount of time. What are some interesting applications I could do with this?&lt;/p&gt;&#xA;&lt;p&gt;More precisely, I am aware of the Heisenberg models which belong to this category for instance. But I am interested in particular in models where the &lt;span class=&quot;math-container&quot;&gt;$P_i^{(k)}$&lt;/span&gt; ideally acts on &lt;strong&gt;all&lt;/strong&gt; the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; qubits (the Heisenberg model has the &lt;span class=&quot;math-container&quot;&gt;$P_i^{(k)}$&lt;/span&gt; that acts on &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; qubits &lt;em&gt;maximum&lt;/em&gt;). If they do not act on all, they could act on a set of maybe &lt;span class=&quot;math-container&quot;&gt;$\log(n)$&lt;/span&gt; qubits or &lt;span class=&quot;math-container&quot;&gt;$\textrm{Poly}(n)$&lt;/span&gt; qubits for instance (I basically want it to be the case that when we increase the size of the Hamiltonian, the Pauli operators act on an increasing portion of the qubits). Are there interesting problems (i.e. that would have applications for quantum chemistry or simulation of materials) that one could find in such case?&lt;/p&gt;&#xA;" OwnerUserId="5716" LastEditorUserId="5" LastEditDate="2022-07-13T18:38:52.953" LastActivityDate="2022-07-14T17:16:14.400" Title="Are there interesting applications of estimating the energy for generalizations of the Heisenberg model?" Tags="|condensed-matter|model-hamiltonians|spin-models|heisenberg-model|quantum-computing|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9379" PostTypeId="2" ParentId="9378" CreationDate="2022-07-13T19:00:03.533" Score="5" Body="&lt;p&gt;When you have more than two Pauli operators in a single term, you can model multipolar terms, as described &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/1742-6596/145/1/012057/meta&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... multipolar correlators of order &lt;span class=&quot;math-container&quot;&gt;$p=1$&lt;/span&gt; (spin, dipolar), &lt;span class=&quot;math-container&quot;&gt;$p=2$&lt;/span&gt; (quadrupolar), &lt;span class=&quot;math-container&quot;&gt;$p=3$&lt;/span&gt; (octupolar), and &lt;span class=&quot;math-container&quot;&gt;$p=4$&lt;/span&gt; (spin, hexadecupolar)&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle S_0^+S_r^-+\text{h.c.}\rangle=2\langle S_0^x S_r^x\rangle+2\langle S_0^y S_r^y\rangle\to 2S^2\cos^2(\nu)\cos(qr)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle S_0^+S_1^+S_r^-S_{r+1}^-+\text{h.c.}\rangle\to 2S^4\cos^4(\nu)\cos(qr)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle S_0^+S_1^+S_2^+S_r^-S_{r+1}^-S_{r+2}^-+\text{h.c.}\rangle\to 2S^6\cos^6(\nu)\cos(qr)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle S_0^+S_1^+S_2^+S_3^+S_r^-S_{r+1}^-S_{r+2}^-S_{r+3}^-+\text{h.c.}\rangle\to 2S^8\cos^8(\nu)\cos(qr)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Several examples of compounds for which multipolar terms are sometimes used (usually due to there being especially strong spin-orbit coupling) are listed &lt;a href=&quot;https://en.wikipedia.org/wiki/Multipolar_exchange_interaction&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, most, if not all of these &amp;quot;uniform&amp;quot; k-local terms can be &lt;a href=&quot;https://arxiv.org/abs/1901.04405&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;quadratized&lt;/strong&gt;&lt;/a&gt; efficiently, meaning that your model might not provide any additional value compared to an ordinary Heisenberg model, from a computational complexity perspective.&lt;/p&gt;&#xA;&lt;p&gt;If you have a quantum computer that's powerful enough to do this type of calculation fast, then I would recommend spending energy on figuring out how to use it for solving more realistic models such as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_Hamiltonian&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular Hamiltonian&lt;/a&gt; which quantum computing advocates have been promising to do for a long time now!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2022-07-14T13:51:54.790" LastActivityDate="2022-07-14T13:51:54.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9380" PostTypeId="2" ParentId="9378" CreationDate="2022-07-14T02:33:10.493" Score="4" Body="&lt;p&gt;It is probably worth mentioning that, in the context of strongly correlated electron system / antiferromagnetism / superexchange, the spin-spin interactions arise from perturbation theory. In the textbook case we consider a Hubbard Hamiltonian,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = t \sum_{\langle i,j\rangle,\sigma} \left( c_{i\sigma}^\dagger c_{j\sigma} + \mathrm{H.c.} \right) + U\sum_i n_{i\uparrow}n_{i\downarrow},&#xA;$$&lt;/span&gt;&#xA;at half-filling and near the &lt;span class=&quot;math-container&quot;&gt;$U\rightarrow\infty$&lt;/span&gt; limit. To second order in &lt;span class=&quot;math-container&quot;&gt;$t/U$&lt;/span&gt;, one obtains a Heisenberg model with strength &lt;span class=&quot;math-container&quot;&gt;$J\propto t^2/U$&lt;/span&gt;. However, if the expansion is continued to higher order in &lt;span class=&quot;math-container&quot;&gt;$t/U$&lt;/span&gt;, one also finds terms that are products of more than two spin operators. Although such terms are often neglected in practice, there are cases where they cause  interesting physics. In particular this tends to happen with cyclic ring- or plaquette exchanges, where the product involves all sites around some lattice motif, e.g. triangular or rectangular plaquettes. See e.g. &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.78.3939&quot; rel=&quot;nofollow noreferrer&quot;&gt;A. A. Nersesyan and A. M. Tsvelik, Phys. Rev. Lett. &lt;strong&gt;78&lt;/strong&gt;, 3939 (1997)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/cond-mat/9612014&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;], &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.127.087201&quot; rel=&quot;nofollow noreferrer&quot;&gt;T. Cookmeyer, J. Motruk, and J. E. Moore, Phys. Rev. Lett. &lt;strong&gt;127&lt;/strong&gt;, 087201 (2021)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/2103.07438&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;] for some inspiration.&lt;/p&gt;&#xA;&lt;p&gt;Another direction could be &lt;a href=&quot;https://en.wikipedia.org/wiki/Fracton_(subdimensional_particle)&quot; rel=&quot;nofollow noreferrer&quot;&gt;fracton&lt;/a&gt; models, which tend to involve products of relatively large (but intensive) numbers of spin operators. The so-called X-cube model features terms with 12 operators, for example. Fracton models (especially those where the products feature many sites) are more interesting from a theoretical physics perspective than a materials one, however. One reference is &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.94.235157&quot; rel=&quot;nofollow noreferrer&quot;&gt;S. Vijay, J. Haah, and L. Fu, Phys. Rev. B &lt;strong&gt;94&lt;/strong&gt;, 235157 (2016)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/1603.04442&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;But I am interested in particular in models where the &lt;span class=&quot;math-container&quot;&gt;$P_i^{(k)}$&lt;/span&gt; ideally acts on &lt;strong&gt;all&lt;/strong&gt; the &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; qubits (the Heisenberg model has the &lt;span class=&quot;math-container&quot;&gt;$P_i^{(k)}$&lt;/span&gt; that acts on &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; qubits &lt;em&gt;maximum&lt;/em&gt;). If they do not act on all, they could act on a set of maybe &lt;span class=&quot;math-container&quot;&gt;$\log(n)$&lt;/span&gt; qubits or &lt;span class=&quot;math-container&quot;&gt;$\textrm{Poly}(n)$&lt;/span&gt; qubits for instance (I basically want it to be the case that when we increase the size of the Hamiltonian, the Pauli operators act on an increasing portion of the qubits). Are there interesting problems (i.e. that would have applications for quantum chemistry or simulation of materials) that one could find in such case?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Unfortunately, that just is not a very realistic scenario in materials where spin interactions are local and ultimately come about due to 2-body Coulomb interactions that decay with distance. Of course, there is some theoretical literature on fully connected (i.e. featuring interactions connecting all sites to all) spin systems with &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;-body interactions, see e.g. &lt;a href=&quot;https://doi.org/10.1209/0295-5075/89/40004&quot; rel=&quot;nofollow noreferrer&quot;&gt;T. Jörg et al., Europhys. Lett. &lt;strong&gt;89&lt;/strong&gt; 40004 (2010)&lt;/a&gt; [&lt;a href=&quot;https://arxiv.org/abs/0912.4865&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv version&lt;/a&gt;]. This presents many mathematical physics questions, but unless &lt;span class=&quot;math-container&quot;&gt;$p\ll n$&lt;/span&gt; it seems unlikely to me that such Hamiltonians would be used to model realistic materials.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2022-07-14T17:16:14.400" LastActivityDate="2022-07-14T17:16:14.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9381" PostTypeId="1" CreationDate="2022-07-14T06:41:08.770" Score="2" ViewCount="248" Body="&lt;p&gt;Does anybody have experience in electric field calculations using VASP? I gave the electric field to an already relaxed structure and it shows &lt;code&gt;electronic self consistency is not achieved&lt;/code&gt;. I even tried &lt;code&gt;NELM=300&lt;/code&gt; but still the ground state energy has not been converged.&lt;/p&gt;&#xA;&lt;p&gt;If I use the &lt;code&gt;ISIF&lt;/code&gt; tag along with the electric field tag, the calculations end abruptly and show an error. Is there anything else we can do? Would it be right if I take the &lt;code&gt;CONTCAR&lt;/code&gt; after giving the electric field and relax it again using &lt;code&gt;ISIF&lt;/code&gt; tags?&lt;/p&gt;&#xA;" OwnerUserId="5722" LastEditorUserId="5" LastEditDate="2023-01-31T21:34:08.407" LastActivityDate="2023-01-31T21:34:08.407" Title="Electric field calculations VASP" Tags="|density-functional-theory|vasp|electronic-structure|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:47:24.280" ContentLicense="CC BY-SA 4.0" />
  <row Id="9382" PostTypeId="1" CreationDate="2022-07-14T07:25:31.493" Score="2" ViewCount="86" Body="&lt;p&gt;I have generated the following pdb file for a polymer:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COMPND    MY_POLYMER&#xA;AUTHOR    SAT&#xA;ATOM       1  M1  POL 1        2.0     0.0     3.0   1.0   1.0         MM&#xA;ATOM       2  M1  POL 1        3.0     0.0     3.0   1.0   1.0         MM&#xA;ATOM       3  M1  POL 1        3.0     1.0     2.0   1.0   1.0         MM&#xA;ATOM       4  M1  POL 1        2.0     0.0     2.0   1.0   1.0         MM&#xA;ATOM       5  M1  POL 1        1.0     0.0     1.0   1.0   1.0         MM&#xA;ATOM       6  M1  POL 1        0.0     1.0     1.0   1.0   1.0         MM&#xA;ATOM       7  M1  POL 1        1.0     0.0     2.0   1.0   1.0         MM&#xA;ATOM       8  M1  POL 1        0.0     0.0     3.0   1.0   1.0         MM&#xA;ATOM       9  M1  POL 1        1.0     1.0     4.0   1.0   1.0         MM&#xA;ATOM      10  M1  POL 1        0.0     1.0     3.0   1.0   1.0         MM&#xA;ATOM      11  M1  POL 1        0.0     1.0     4.0   1.0   1.0         MM&#xA;ATOM      12  M1  POL 1       -1.0     2.0     4.0   1.0   1.0         MM&#xA;ATOM      13  M1  POL 1        0.0     2.0     3.0   1.0   1.0         MM&#xA;ATOM      14  M1  POL 1        1.0     2.0     4.0   1.0   1.0         MM&#xA;ATOM      15  M1  POL 1        1.0     3.0     3.0   1.0   1.0         MM&#xA;ATOM      16  M1  POL 1        0.0     2.0     4.0   1.0   1.0         MM&#xA;ATOM      17  M1  POL 1        0.0     2.0     5.0   1.0   1.0         MM&#xA;ATOM      18  M1  POL 1        0.0     3.0     4.0   1.0   1.0         MM&#xA;ATOM      19  M1  POL 1        1.0     3.0     4.0   1.0   1.0         MM&#xA;ATOM      20  M1  POL 1        0.0     3.0     3.0   1.0   1.0         MM&#xA;ATOM      21  M1  POL 1       -1.0     2.0     2.0   1.0   1.0         MM&#xA;ATOM      22  M1  POL 1       -1.0     2.0     3.0   1.0   1.0         MM&#xA;ATOM      23  M1  POL 1       -1.0     1.0     2.0   1.0   1.0         MM&#xA;ATOM      24  M1  POL 1        0.0     0.0     2.0   1.0   1.0         MM&#xA;ATOM      25  M1  POL 1       -1.0     1.0     3.0   1.0   1.0         MM&#xA;ATOM      26  M1  POL 1       -1.0     1.0     4.0   1.0   1.0         MM&#xA;ATOM      27  M1  POL 1        0.0     1.0     5.0   1.0   1.0         MM&#xA;ATOM      28  M1  POL 1        1.0     2.0     5.0   1.0   1.0         MM&#xA;ATOM      29  M1  POL 1        1.0     1.0     5.0   1.0   1.0         MM&#xA;ATOM      30  M1  POL 1        2.0     0.0     4.0   1.0   1.0         MM&#xA;ATOM      31  M1  POL 1        1.0     0.0     5.0   1.0   1.0         MM&#xA;ATOM      32  M1  POL 1        2.0     1.0     5.0   1.0   1.0         MM&#xA;ATOM      33  M1  POL 1        1.0     0.0     4.0   1.0   1.0         MM&#xA;ATOM      34  M1  POL 1        0.0     0.0     4.0   1.0   1.0         MM&#xA;ATOM      35  M1  POL 1        1.0     0.0     3.0   1.0   1.0         MM&#xA;ATOM      36  M1  POL 1        1.0     1.0     3.0   1.0   1.0         MM&#xA;ATOM      37  M1  POL 1        2.0     1.0     4.0   1.0   1.0         MM&#xA;ATOM      38  M1  POL 1        2.0     1.0     3.0   1.0   1.0         MM&#xA;ATOM      39  M1  POL 1        2.0     2.0     4.0   1.0   1.0         MM&#xA;ATOM      40  M1  POL 1        3.0     2.0     3.0   1.0   1.0         MM&#xA;ATOM      41  M1  POL 1        2.0     3.0     4.0   1.0   1.0         MM&#xA;ATOM      42  M1  POL 1        2.0     2.0     5.0   1.0   1.0         MM&#xA;ATOM      43  M1  POL 1        3.0     1.0     4.0   1.0   1.0         MM&#xA;ATOM      44  M1  POL 1        3.0     2.0     4.0   1.0   1.0         MM&#xA;ATOM      45  M1  POL 1        3.0     1.0     3.0   1.0   1.0         MM&#xA;ATOM      46  M1  POL 1        3.0     2.0     2.0   1.0   1.0         MM&#xA;ATOM      47  M1  POL 1        2.0     2.0     2.0   1.0   1.0         MM&#xA;ATOM      48  M1  POL 1        1.0     2.0     3.0   1.0   1.0         MM&#xA;ATOM      49  M1  POL 1        2.0     3.0     3.0   1.0   1.0         MM&#xA;ATOM      50  M1  POL 1        3.0     3.0     3.0   1.0   1.0         MM&#xA;ATOM      51  M1  POL 1        2.0     3.0     2.0   1.0   1.0         MM&#xA;ATOM      52  M1  POL 1        2.0     2.0     3.0   1.0   1.0         MM&#xA;ATOM      53  M1  POL 1        1.0     3.0     2.0   1.0   1.0         MM&#xA;ATOM      54  M1  POL 1        2.0     2.0     1.0   1.0   1.0         MM&#xA;ATOM      55  M1  POL 1        1.0     1.0     2.0   1.0   1.0         MM&#xA;ATOM      56  M1  POL 1        1.0     2.0     2.0   1.0   1.0         MM&#xA;ATOM      57  M1  POL 1        0.0     3.0     2.0   1.0   1.0         MM&#xA;ATOM      58  M1  POL 1        0.0     2.0     2.0   1.0   1.0         MM&#xA;ATOM      59  M1  POL 1        1.0     1.0     1.0   1.0   1.0         MM&#xA;ATOM      60  M1  POL 1        0.0     2.0     1.0   1.0   1.0         MM&#xA;ATOM      61  M1  POL 1        0.0     1.0     2.0   1.0   1.0         MM&#xA;ATOM      62  M1  POL 1        1.0     2.0     1.0   1.0   1.0         MM&#xA;ATOM      63  M1  POL 1        2.0     1.0     2.0   1.0   1.0         MM&#xA;ATOM      64  M1  POL 1        2.0     1.0     1.0   1.0   1.0         MM&#xA;CONECT    1    2&#xA;CONECT    2    3&#xA;CONECT    3    4&#xA;CONECT    4    5&#xA;CONECT    5    6&#xA;CONECT    6    7&#xA;CONECT    7    8&#xA;CONECT    8    9&#xA;CONECT    9   10&#xA;CONECT   10   11&#xA;CONECT   11   12&#xA;CONECT   12   13&#xA;CONECT   13   14&#xA;CONECT   14   15&#xA;CONECT   15   16&#xA;CONECT   16   17&#xA;CONECT   17   18&#xA;CONECT   18   19&#xA;CONECT   19   20&#xA;CONECT   20   21&#xA;CONECT   21   22&#xA;CONECT   22   23&#xA;CONECT   23   24&#xA;CONECT   24   25&#xA;CONECT   25   26&#xA;CONECT   26   27&#xA;CONECT   27   28&#xA;CONECT   28   29&#xA;CONECT   29   30&#xA;CONECT   30   31&#xA;CONECT   31   32&#xA;CONECT   32   33&#xA;CONECT   33   34&#xA;CONECT   34   35&#xA;CONECT   35   36&#xA;CONECT   36   37&#xA;CONECT   37   38&#xA;CONECT   38   39&#xA;CONECT   39   40&#xA;CONECT   40   41&#xA;CONECT   41   42&#xA;CONECT   42   43&#xA;CONECT   43   44&#xA;CONECT   44   45&#xA;CONECT   45   46&#xA;CONECT   46   47&#xA;CONECT   47   48&#xA;CONECT   48   49&#xA;CONECT   49   50&#xA;CONECT   50   51&#xA;CONECT   51   52&#xA;CONECT   52   53&#xA;CONECT   53   54&#xA;CONECT   54   55&#xA;CONECT   55   56&#xA;CONECT   56   57&#xA;CONECT   57   58&#xA;CONECT   58   59&#xA;CONECT   59   60&#xA;CONECT   60   61&#xA;CONECT   61   62&#xA;CONECT   62   63&#xA;CONECT   63   64&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I view this PDB using VMD, I see the following image:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/VzKZT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VzKZT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I do not understand why I see this perfectly connected web of particles, when all I want is for each consecutive particle to be connected. How should I go about solving this visualization issue?&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2023-01-31T21:47:55.647" Title="Why is my pdb looking so weird?" Tags="|molecular-dynamics|visualization-software|vmd|pdb|" AnswerCount="1" CommentCount="3" ClosedDate="2023-02-01T03:46:25.937" ContentLicense="CC BY-SA 4.0" />
  <row Id="9383" PostTypeId="1" CreationDate="2022-07-14T08:40:10.933" Score="2" ViewCount="110" Body="&lt;p&gt;Dear Quantum ESPRESSO users,&#xA;I was trying to calculate the |psi|^2 calculation (1D) for diamond structure silicon at a single kpoint (gamma point). I have used the semicore pseudopotential that consists of 12 electrons (anyone can use non-semicore pseudopotential with 4 electrons too). After scf and pp.x post processing calculations done (both shows &lt;strong&gt;JOB DONE&lt;/strong&gt; in the output files - indicating successful job run), I see that there are twelve band files generated for 1D plot (|psi|^2 vs r). My concern is, I see that the distance (r) column of first band file extends from 0 to 41.45 alat, while the other bands (2-12) extend from 0 to 1 alat. I am not sure why they are showing full data set for the first band file only and stopping at exactly 1 alat for the other bands. Could you please inform me the possible reason for this, and way to solve it so that I can get the full data set (r value from 0 to 41.45 alat) for all twelve bands?&lt;/p&gt;&#xA;&lt;p&gt;I am sending the scf and pp.x input files, and their outputs below for convenience.&lt;/p&gt;&#xA;&lt;p&gt;Hope to get your cordial cooperation to solve this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;SCF (pw.x) input file:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;   prefix = 'silicon'&#xA;   calculation = 'scf'&#xA;   restart_mode = 'from_scratch'&#xA;   wf_collect = .false.&#xA;   tstress = .true.&#xA;   tprnfor = .true.&#xA;   outdir = './'&#xA;   wfcdir = './'&#xA;   pseudo_dir = './'&#xA;   verbosity = 'low'&#xA;/&#xA;&amp;amp;system&#xA;   ibrav = 2&#xA;   celldm(1) = 10.33517&#xA;   nat = 2&#xA;   ntyp = 1&#xA;   ecutwfc = 150,&#xA;   occupations='smearing',&#xA;   smearing='gaussian',&#xA;   degauss=0.022,&#xA;/&#xA;&amp;amp;electrons&#xA;   electron_maxstep = 100&#xA;   conv_thr = 1.0d-10&#xA;   mixing_mode = 'plain'&#xA;   mixing_beta = 0.7&#xA;   mixing_ndim = 8&#xA;   diagonalization = 'david'&#xA;   diago_david_ndim = 4&#xA;   diago_full_acc = .true.&#xA;/&#xA;ATOMIC_SPECIES&#xA;  Si  28.086  Si.upf&#xA;ATOMIC_POSITIONS crystal&#xA;  Si  -0.125000000  -0.125000000  -0.125000000&#xA;  Si   0.125000000   0.125000000   0.125000000&#xA;K_POINTS automatic&#xA;8 8 8 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Post-processing (pp.x) input file:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA;  prefix=&amp;quot;silicon&amp;quot;&#xA;  outdir=&amp;quot;./&amp;quot;&#xA;  filplot=&amp;quot;psi2_e3_f&amp;quot;&#xA;  plot_num=7&#xA;  kband(1)=1&#xA;  kband(2)=12&#xA;  kpoint(1)=1&#xA;/&#xA;&amp;amp;PLOT&#xA;  nfile = 1&#xA;  iflag = 1&#xA;  output_format = 0&#xA;  fileout = &amp;quot;.gnu&amp;quot;&#xA;x0(1)=0.375&#xA;x0(2)=0.125&#xA;x0(3)=0.625&#xA;e1(1)=12.5&#xA;e1(2)=37.5&#xA;e1(3)=-12.5&#xA;nx=10000&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;First 10 lines of band-1 file (extends from 0 to 41.45 alat, with 10000 data row):&lt;/strong&gt;&#xA;more psi2_e3_f_K001_B001.gnu&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        0.0000000000        0.5774665488&#xA;        0.0041461956        0.5739151472&#xA;        0.0082923912        0.5633830748&#xA;        0.0124385868        0.5462309811&#xA;        0.0165847824        0.5230407530&#xA;        0.0207309780        0.4945872344&#xA;        0.0248771736        0.4618000344&#xA;        0.0290233693        0.4257172175&#xA;        0.0331695649        0.3874334770&#xA;        0.0373157605        0.3480461457&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Last 10 lines of band-1 file (extends from 0 to 41.45 alat, with 10000 data row):&lt;/strong&gt;&#xA;cat psi2_e3_f_K001_B001.gnu&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;       41.4204941190        0.0000000001&#xA;       41.4246403146        0.0000000001&#xA;       41.4287865102        0.0000000000&#xA;       41.4329327058        0.0000000000&#xA;       41.4370789014        0.0000000000&#xA;       41.4412250970        0.0000000000&#xA;       41.4453712926        0.0000000000&#xA;       41.4495174882        0.0000000000&#xA;       41.4536636838        0.0000000000&#xA;       41.4578098794        0.0000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;First 10 lines of band-2 file (extends from 0 to 1 alat, with 10000 data row):&lt;/strong&gt;&#xA;more psi2_e3_f_K001_B002.gnu&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        0.0000000000       -0.0000000000&#xA;        0.0001000100        0.0000000712&#xA;        0.0002000200        0.0000002849&#xA;        0.0003000300        0.0000006413&#xA;        0.0004000400        0.0000011403&#xA;        0.0005000500        0.0000017822&#xA;        0.0006000600        0.0000025670&#xA;        0.0007000700        0.0000034948&#xA;        0.0008000800        0.0000045656&#xA;        0.0009000900        0.0000057795&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Last 10 lines of band-2 file (extends from 0 to 1 alat, with 10000 data row):&lt;/strong&gt;&#xA;cat psi2_e3_f_K001_B002.gnu&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        0.9990999100        0.0070165649&#xA;        0.9991999200        0.0070205456&#xA;        0.9992999300        0.0070245267&#xA;        0.9993999400        0.0070285081&#xA;        0.9994999500        0.0070324898&#xA;        0.9995999600        0.0070364717&#xA;        0.9996999700        0.0070404539&#xA;        0.9997999800        0.0070444361&#xA;        0.9998999900        0.0070484185&#xA;        1.0000000000        0.0070524009&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For &lt;strong&gt;B003-B012&lt;/strong&gt;.gnu files, the data stops at &lt;strong&gt;1 alat&lt;/strong&gt;, similarly like psi2_e3_f_K001_B002.gnu file. They should stop at &lt;strong&gt;41.45 alat&lt;/strong&gt;, similarly like  psi2_e3_f_K001_B001.gnu file to make a consistent calculation output.&lt;/p&gt;&#xA;&lt;p&gt;[The full output data is not supported here to paste (due to character limit). So I pasted here the first and last 10 lines for each of the two files, and mentioned the number of data row for both files.]&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2023-01-31T21:36:52.773" LastActivityDate="2023-01-31T21:36:52.773" Title="|psi|^2 calculation (1D) for diamond structure silicon not showing full dataset for all bands: Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|charge-density|wavefunctions|" AnswerCount="0" CommentCount="12" ClosedDate="2023-12-20T03:27:43.597" ContentLicense="CC BY-SA 4.0" />
  <row Id="9384" PostTypeId="1" AcceptedAnswerId="9569" CreationDate="2022-07-14T16:00:05.613" Score="6" ViewCount="379" Body="&lt;p&gt;When using plane-wave codes for solid-state calculations, which computational parameter is more significant in increasing the computational cost: number of electrons or number of k-points?&lt;/p&gt;&#xA;&lt;p&gt;I ask this question because I am planning a large-scale calculation (512-atom supercell, HSE06, VASP), but I doubt my accessible computational resources have the enough memory.&lt;/p&gt;&#xA;" OwnerUserId="1688" LastEditorUserId="5" LastEditDate="2022-08-20T04:19:04.843" LastActivityDate="2022-08-20T04:19:04.843" Title="Number of k-points vs number of electrons: which is more significant in terms of computational cost for plane-wave calculations?" Tags="|density-functional-theory|vasp|supercell|hse06|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9385" PostTypeId="2" ParentId="9349" CreationDate="2022-07-14T18:52:47.637" Score="8" Body="&lt;p&gt;I (think that I) can only help with the part in the title of the question.&#xA;The following answer won't be mathematical rigorous and nothing will be proved, but references are provided at the end.&lt;/p&gt;&#xA;&lt;p&gt;Notation: Let &lt;span class=&quot;math-container&quot;&gt;$ \mathfrak h$&lt;/span&gt; denote a (complex) single-particle Hilbert space and &lt;span class=&quot;math-container&quot;&gt;$H_N:=\wedge^N \mathfrak h$&lt;/span&gt; the corresponding (complex) Hilbert space of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; identical fermions&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;. We denote by &lt;span class=&quot;math-container&quot;&gt;$\psi \in H_N$&lt;/span&gt; a normalized &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-particle state, the inner product on a complex Hilbert space &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\langle \cdot,\cdot\rangle_{h}$&lt;/span&gt; and the trace as &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Tr}_h$&lt;/span&gt;.  The inner product is defined to be anti-linear in the first and linear in the second argument. We'll also work in second quantization, which however is just a matter of taste. To this end, we use the creation and annihilation operators &lt;span class=&quot;math-container&quot;&gt;$a^\dagger(f)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$a(f)$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$f\in \mathfrak h$&lt;/span&gt; as usual. For a self-adjoint operator &lt;span class=&quot;math-container&quot;&gt;$o$&lt;/span&gt; on &lt;span class=&quot;math-container&quot;&gt;$\mathfrak h$&lt;/span&gt;, the corresponding one-body operator on &lt;span class=&quot;math-container&quot;&gt;$H_N$&lt;/span&gt; is written as &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt;. As a last point,  we will use &lt;span class=&quot;math-container&quot;&gt;$\{f_j\}_{j\in J}$&lt;/span&gt; to denote an orthonormal and complete basis on &lt;span class=&quot;math-container&quot;&gt;$\mathfrak h$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;For &lt;span class=&quot;math-container&quot;&gt;$\psi \in H_N$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f,g\in \mathfrak h$&lt;/span&gt;, we define the one-body reduced density matrix (1-RDM) by the relation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \langle f,\gamma_\psi g\rangle_{\mathfrak h} := \langle \psi, a^\dagger(g)\, a(f)\,\psi\rangle_{H_N}\quad.\tag{1}$$&lt;/span&gt;&#xA;By construction, &lt;span class=&quot;math-container&quot;&gt;$\gamma_\psi$&lt;/span&gt; is positive semi-definite and trace-class (and thus self-adjoint) [1]. The definition can be generalized to include mixed states on &lt;span class=&quot;math-container&quot;&gt;$H_N$&lt;/span&gt; as well.&lt;/p&gt;&#xA;&lt;p&gt;Now recall that we can write a one-body operator on &lt;span class=&quot;math-container&quot;&gt;$H_N$&lt;/span&gt; as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$  O = \sum\limits_{i,j\in J} \langle f_i,o\,  f_j\rangle_{\mathfrak h}\,a^\dagger(f_i)\, a(f_j) \tag{2} \quad ,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which in turn means that we can compute the expectation value of &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; in the state &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; with&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \langle \psi, O\,\psi\rangle_{H_N} = \mathrm{Tr}_{\mathfrak h}\, \gamma_\psi\, o \quad .\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This means that, at least in principle, we don't need the full wave function &lt;span class=&quot;math-container&quot;&gt;$\psi \in H_N$&lt;/span&gt; to compute the expectation values of one-body operators; the corresponding 1-RDM &lt;span class=&quot;math-container&quot;&gt;$\gamma_\psi$&lt;/span&gt; suffices.&lt;/p&gt;&#xA;&lt;p&gt;To proceed, consider a Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; on &lt;span class=&quot;math-container&quot;&gt;$H_N$&lt;/span&gt; consisting of the sum of a one and two-body operator, which we'll write as &lt;span class=&quot;math-container&quot;&gt;$H=T+ W$&lt;/span&gt;. An example is the Hamiltonian of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons in a solid in the Born-Oppenheimer approximation, where &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the kinetic energy plus external potential and &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; the Coulomb interaction. It is very-well known that the (here assumed to be) non-degenerate ground state of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is in one-to-one relation with its corresponding 1-RDM, which we will discuss in detail now.&lt;/p&gt;&#xA;&lt;p&gt;The situation is very similar to the density functional case: Indeed, note that the density operator is a one-body operator and that given &lt;span class=&quot;math-container&quot;&gt;$\gamma_\psi$&lt;/span&gt;, we can obtain the density of &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; from it. So for a local external potential and a non-degenerate ground state, the ground state density is in one-to-one correspondence with the ground state (Hohenberg-Kohn) and thus with the ground state 1-RDM. So the Hohenberg-Kohn theorem immediately applies to the 1-RDM too, at least in the case of local external potentials.  However, as shown by Gilbert [2], the ground state 1-RDM also is in one-to-one correspondence with the ground state if the external potential is non-local. Yet, in general, there is no one-to-one correspondence between the ground state 1-RDM and the external potential anymore.&lt;/p&gt;&#xA;&lt;p&gt;Similarly as in density functional theory (DFT), this means that all ground state properties are functionals of the ground state 1-RDM. This in particular includes the ground state energy, for which we can also formulate a variational principle. Let &lt;span class=&quot;math-container&quot;&gt;$\mathcal V$&lt;/span&gt; denote the set of &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representable 1-RDMs&lt;span class=&quot;math-container&quot;&gt;$^{2}$&lt;/span&gt;. Then the ground state energy can be found as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_0 =\min\limits_{\gamma \in \mathcal V}\, \mathrm{Tr}_{\mathfrak h} \gamma_ \, t + W[\gamma] \tag{4} \quad ,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$$W[\gamma] := \langle \psi[\gamma],W\,\psi[\gamma]\rangle_{H_N} \tag{5}$$&lt;/span&gt; is the so-called universal functional and &lt;span class=&quot;math-container&quot;&gt;$\psi[\gamma]$&lt;/span&gt; is the ground state associated to the ground state 1-RDM &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;. However, again similar to the DFT case, the problem is that we can't efficiently characterize the set &lt;span class=&quot;math-container&quot;&gt;$\mathcal V$&lt;/span&gt;. To circumvent this problem, we can also formulate a Levy-Lieb constrained search [3,4]. For if &lt;span class=&quot;math-container&quot;&gt;$\mathcal P$&lt;/span&gt; denotes the set of pure state &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representable 1-RDMs, then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_0 = \min\limits_{\gamma \in \mathcal P}\, \mathrm{Tr}_{\mathfrak h} \gamma_ \, t  + F[\gamma] \tag{6} \quad , $$&lt;/span&gt;&#xA;where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$  F[\gamma] : = \min\limits_{\psi \in H_N | \gamma_\psi = \gamma}\,  \langle \psi, W\,\psi\rangle_{H_N}  \quad . \tag{7}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that this construction removes the problems regarding degeneracies and &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representability. As briefly stated in the footnotes, the (pure state) &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability problem can be solved in principle, i.e. we know the set &lt;span class=&quot;math-container&quot;&gt;$\mathcal P$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt; Most of the discussion can readily be applied to identical bosons, too [9-11]. Furthermore, Bose-Einstein condensation is defined in terms of the 1-RDM.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt; Here it is assumed that the reader is familiar with the notion of &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;- and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability. It might be of interest to note that the fermionic pure state &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability problem was solved only (more or less) recently, see [5,6]. The bosonic pure state &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability problem is trivial. For both cases, the ensemble &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability problems are well-known, cf. [7-9]. In contrast, the &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representability problem remains unknown (with a few exceptions).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;References and further reading:&lt;/p&gt;&#xA;&lt;p&gt;[1] &lt;em&gt;Solovej, J. P. (2007). Many body quantum mechanics. Lecture Notes.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] &lt;em&gt;Gilbert, T. L. (1975). Hohenberg-Kohn theorem for nonlocal external potentials. Physical Review B, 12(6), 2111.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[3] &lt;em&gt;Levy, M. (1979). Universal variational functionals of electron densities, first-order density matrices, and natural spin-orbitals and solution of the v-representability problem. Proceedings of the National Academy of Sciences, 76(12), 6062-6065.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[4] &lt;em&gt;Lieb, E. H. (2002). Density functionals for Coulomb systems. In Inequalities (pp. 269-303). Springer, Berlin, Heidelberg.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[5] &lt;em&gt;Klyachko, A. A. (2006, April). Quantum marginal problem and N-representability. In Journal of Physics: Conference Series (Vol. 36, No. 1, p. 014). IOP Publishing.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[6] &lt;em&gt;Altunbulak, M., &amp;amp; Klyachko, A. (2008). The Pauli principle revisited. Communications in Mathematical Physics, 282(2), 287-322.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[7] &lt;em&gt;Coleman, A. J. (1963). Structure of fermion density matrices. Reviews of modern Physics, 35(3), 668.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[8] &lt;em&gt;Valone, S. M. (1980). Consequences of extending 1‐matrix energy functionals from pure–state representable to all ensemble representable 1 matrices. The Journal of Chemical Physics, 73(3), 1344-1349.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[9] &lt;em&gt;Giesbertz, K. J., &amp;amp; Ruggenthaler, M. (2019). One-body reduced density-matrix functional theory in finite basis sets at elevated temperatures. Physics Reports, 806, 1-47.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[10] &lt;em&gt;Benavides-Riveros, C. L., Wolff, J., Marques, M. A., &amp;amp; Schilling, C. (2020). Reduced density matrix functional theory for bosons. Physical Review Letters, 124(18), 180603.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;[11] &lt;em&gt;Liebert, J., &amp;amp; Schilling, C. (2021). Functional theory for Bose-Einstein condensates. Physical Review Research, 3(1), 013282.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2022-09-27T10:23:24.567" LastActivityDate="2022-09-27T10:23:24.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9387" PostTypeId="1" CreationDate="2022-07-15T00:07:40.230" Score="4" ViewCount="215" Body="&lt;p&gt;I would like to assign a &amp;quot;Boltzmann weight&amp;quot; i.e. &lt;span class=&quot;math-container&quot;&gt;$\exp(-E/kT)$&lt;/span&gt; to interactions between particles based on the relative energies. But wouldn't the largest particle-particle energies have the smallest weighting? Shouldn't it be the opposite? I'm hoping someone can explain this to me.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorDisplayName="user2026" LastEditDate="2022-07-15T00:14:53.060" LastActivityDate="2022-07-15T14:33:09.127" Title="How to assign a &quot;Boltzmann weight&quot;?" Tags="|molecular-dynamics|statistical-thermodynamics|thermodynamics|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9388" PostTypeId="2" ParentId="9387" CreationDate="2022-07-15T01:07:42.617" Score="2" Body="&lt;p&gt;Short answer is your instinct is correct, a large energy will have a small weight.&lt;/p&gt;&#xA;&lt;p&gt;As a simple case, lets look at the energy of interaction between two Lennard-Jones particles&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/80jbp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/80jbp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;At the most favorable distance, &lt;span class=&quot;math-container&quot;&gt;$r/\sigma = r_m$&lt;/span&gt;, the energy of interaction is the most negative it can be, which is the equilibrium point. The Boltzmann weight at this distance would also be the largest possible out of any interactions.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, at &lt;span class=&quot;math-container&quot;&gt;$r/\sigma=1$&lt;/span&gt;, the particles begin overlapping and the energy gets positive(repulsive), very fast. The Boltzmann weight would be very small, becoming vanishingly small the more the particles overlap.&lt;/p&gt;&#xA;&lt;p&gt;Using the dimensions in the image, the largest Boltzmann factor is at &lt;span class=&quot;math-container&quot;&gt;$r/\sigma = r_m$&lt;/span&gt; which is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E=-1 \rightarrow \exp(-[-1]) = 2.718$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;meanwhile, on the other hand, positive values are quite small i.e. for &lt;span class=&quot;math-container&quot;&gt;$r/\sigma &amp;lt; 1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E=1 \rightarrow \exp(-[1]) = 0.368$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E=3 \rightarrow \exp(-[3]) = 0.05$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We expect overlapping particles to have a smaller weight since energy of interaction becomes repulsive. The most favorable interaction is at &lt;span class=&quot;math-container&quot;&gt;$r/\sigma = r_m$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In reality, however, it is the free energy, not the potential energy, that determines where equilibrium is.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2022-07-15T14:33:09.127" LastActivityDate="2022-07-15T14:33:09.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9390" PostTypeId="1" CreationDate="2022-07-15T11:38:33.540" Score="3" ViewCount="407" Body="&lt;p&gt;I have the following Ramachandran plot generated by &lt;strong&gt;&lt;a href=&quot;https://www2.mrc-lmb.cam.ac.uk/personal/pemsley/coot/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Coot&lt;/a&gt;&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5YfJEm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5YfJEm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that it has high outliers content (red dots). I want to manually drag those&#xA;red dots into some part of the region. Eventually, I expect it to be reflected&#xA;in the coordinates so that I can save it as a new PDB file.&lt;/p&gt;&#xA;&lt;p&gt;How can I achieve this?&lt;/p&gt;&#xA;&lt;p&gt;G.V.&lt;/p&gt;&#xA;" OwnerUserId="4475" LastActivityDate="2022-07-20T03:18:47.580" Title="How to fix outliers in Ramachandran plot using Coot" Tags="|crystallography|proteins|pdb|" AnswerCount="0" CommentCount="2" ClosedDate="2023-02-10T03:06:49.953" ContentLicense="CC BY-SA 4.0" />
  <row Id="9391" PostTypeId="1" CreationDate="2022-07-14T12:49:54.807" Score="4" ViewCount="103" Body="&lt;p&gt;I am carrying out a project which involves obtaining the RHF result and the integrals for the chromium dimer (Cr2) under Ahlrichs' SV basis. In the literature against which we attempt to benchmark, the Mg core of each Cr is frozen, yielding 30 orbitals and 24 electrons in total. I thus wonder how should I set up in Molpro to get the cores frozen. My guess is that one should first do something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;basis = SV &#xA;{hf&#xA;core}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to obtain the occupied orbitals for a dual Mg system under the same geometry as Cr2's, and next freeze these orbitals in Cr2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{hf&#xA;core,a1,a2,...a8}&#xA;&#xA;{fci, dump = name&#xA;core,a1,a2,...a8}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But is this correct? If not, what is the correct way to freeze the cores? Thanks for the help in advance!&lt;/p&gt;&#xA;" OwnerUserId="5727" OwnerDisplayName="Izzy Vang" LastEditorUserId="5" LastEditDate="2023-01-31T21:39:19.890" LastActivityDate="2023-01-31T21:39:19.890" Title="Setting a frozen core in Molpro" Tags="|computational-chemistry|quantum-chemistry|ab-initio-calculations|casscf|molpro|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9394" PostTypeId="2" ParentId="9335" CreationDate="2022-07-16T20:07:13.720" Score="5" Body="&lt;p&gt;As mentioned by @ProfM, you can use the last step of the .geom file.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, a particularly helpful parameter that I use is &lt;code&gt;write_cell_structure&lt;/code&gt;. If set to true in your .param file, then CASTEP will output a formatted cell file for you with the optimised geometry. This will include the parameters used in the calculation, e.g pseudopotential string, kpoint grid, symmetries, etc.&lt;/p&gt;&#xA;&lt;p&gt;In your .param file, add, &lt;code&gt;write_cell_structure : true&lt;/code&gt;.&#xA;The file will be named XX-out.cell with XX being your calculation prefix.&lt;/p&gt;&#xA;" OwnerUserId="5735" LastEditorUserId="7" LastEditDate="2022-07-18T12:50:45.720" LastActivityDate="2022-07-18T12:50:45.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9396" PostTypeId="1" AcceptedAnswerId="9438" CreationDate="2022-07-17T15:27:23.923" Score="4" ViewCount="175" Body="&lt;p&gt;As far as I understood, molecular simulation works in two types of scales:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;temporal scale - how much time is required to simulate the model.&lt;/li&gt;&#xA;&lt;li&gt;spatial scale - how much memory-space is required to simulate the model.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The more accurate the model is, the more time and memory it takes. I believe this is called the &lt;strong&gt;scale mismatch&lt;/strong&gt; problem. Connectedly, &lt;strong&gt;Bridging of scale&lt;/strong&gt; would refer to adopting techniques to simulate a more accurate model in less time and use less space in the memory.&lt;/p&gt;&#xA;&lt;p&gt;Are my definitions of the bolded terms correct?&lt;/p&gt;&#xA;&lt;p&gt;If YES, can you supply me with a reference that I can use to support my definitions? I haven't found a reference that explicitly states these definitions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Scale-mismatch =&amp;gt; &lt;a href=&quot;https://scholar.google.pl/scholar?q=%22multiscale%20modeling%22%20%22scale-mismatch%22&amp;amp;hl=en&amp;amp;as_sdt=0&amp;amp;as_vis=1&amp;amp;oi=scholart&quot; rel=&quot;nofollow noreferrer&quot;&gt;GoogleScholar search&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Bridging of scale =&amp;gt; &lt;a href=&quot;https://link.springer.com/book/10.1007/978-3-540-75117-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Multiscale Modeling of Fluids and Solids - Theory and Applications, Page-253&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-07-18T13:50:51.090" LastActivityDate="2022-07-26T08:28:40.407" Title="What does it mean by &quot;scale mismatch&quot; and &quot;bridging of scales&quot;?" Tags="|reference-request|terminology|multiscale-modeling|" AnswerCount="2" CommentCount="1" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9397" PostTypeId="1" CreationDate="2022-07-18T01:58:42.460" Score="3" ViewCount="115" Body="&lt;p&gt;In this &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssr.201800234&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; &amp;quot;Role of Aluminum Doping in Anatase-to-Rutile Transformation from Thermodynamic View Point&amp;quot;, the authors simulated different synthesis environment (either reducing or oxidizing) by adjusting the fermi level of Al doped TiO2, as shown in Figure 3 of the paper.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/o6RrGl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/o6RrGl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My confusion is: Why the synthesis environment can be approximated by different fermi levels? Is it easier to obtain n-type TiO2 in reducing environment than oxidizing environment? Moreover, for substitutional Al-doped TiO2, the doping induced level is located right above valance band maximum of TiO2, so is it unphysical to calculate its formation energy with a fermi level close to conduction band minimum?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastActivityDate="2022-07-18T07:02:07.013" Title="Is it easier to obtain n-type TiO2 in reducing environment than in oxidizing environment?" Tags="|density-functional-theory|fermi-energy|formation-energy|doping|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9398" PostTypeId="2" ParentId="9397" CreationDate="2022-07-18T07:02:07.013" Score="2" Body="&lt;p&gt;The synthesis environment can be modeled by the chemical potential of chemical component elements, not by the chemical potential (or Fermi level) of eletrons. When O is rich, the material would probably be Ti poor, so Ti vacancy is easy to form.&lt;/p&gt;&#xA;&lt;p&gt;The formation energy depends on chemical potential of electrons: when close to valence band, donor defects will have reduced formation energy, when close to conduction band, acceptor defects will have reduced formation energy.&lt;/p&gt;&#xA;&lt;p&gt;You can check the formula for the formation energy of point defects.&lt;/p&gt;&#xA;" OwnerUserId="1688" LastActivityDate="2022-07-18T07:02:07.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9399" PostTypeId="1" CreationDate="2022-07-14T11:16:16.800" Score="11" ViewCount="113" Body="&lt;p&gt;In computational quantum chemistry the STO-3G basis is a popular minimal choice for basic work – the parameters to an expansion of primitive Gaussian functions are commonly deduced by a nonlinear least squares fit that maximises the overlap with a given Slater-type orbital (STO) (e.g. &lt;a href=&quot;http://dx.doi.org/10.1063/1.1672392&quot; rel=&quot;nofollow noreferrer&quot;&gt;W. J. Hehre, R. F. Stewart and J. A. Pople, J. Chem. Phys. 1969, 51, 2657&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;For example, for the simplest STO,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_\mathrm{1s}(\zeta_1, \mathbf{r}) = &#xA;  (\zeta_1^3/\pi)^{1/2}\exp(-\zeta_1 \mathbf{r})\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;the STO-3G basis function is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_\mathrm{1s}'(\mathbf{r}) = &#xA;  \sum_k^{N=3} c_k\,g_\mathrm{1s}(\alpha_k,\mathbf{r})\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;g_\mathrm{1s}(\alpha_k, \mathbf{r}) = &#xA;  (2\alpha_k/\pi)^{3/4}\exp(-\alpha_k \mathbf{r}^2).&#xA;\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the coefficients &lt;span class=&quot;math-container&quot;&gt;$c_k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_k$&lt;/span&gt; that maximise &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_\mathrm{1s}'(\mathbf{r}) | \phi_\mathrm{1s}(\zeta_1, \mathbf{r}) \rangle$&lt;/span&gt; are sought.&lt;/p&gt;&#xA;&lt;p&gt;Why is &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_\mathrm{1s}'(\mathbf{r}) | \phi_\mathrm{1s}(\zeta_1, \mathbf{r}) \rangle$&lt;/span&gt; the target instead the goal being to minimize &lt;span class=&quot;math-container&quot;&gt;$\langle E \rangle = \langle \phi_\mathrm{1s}'(\mathbf{r}) | \hat{H} | \phi_\mathrm{1s}'(\mathbf{r}) \rangle$&lt;/span&gt;? Would the coefficients corresponding to the latter condition not be a better representation of the STO?&lt;/p&gt;&#xA;&lt;p&gt;I did the fits myself and it seems so (I get within 0.60% of the true H 1s orbital energy (&lt;span class=&quot;math-container&quot;&gt;$-0.5 E_h$&lt;/span&gt;) compared with 1.02%)&lt;/p&gt;&#xA;&lt;p&gt;Minimizing &lt;span class=&quot;math-container&quot;&gt;$\langle E \rangle$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8Y2eO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8Y2eO.png&quot; alt=&quot;minimize &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Maximizing overlap:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kNTWS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kNTWS.png&quot; alt=&quot;maximising overlap&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="issy" LastEditorUserId="5" LastEditDate="2022-07-22T20:01:18.297" LastActivityDate="2022-07-22T20:01:18.297" Title="Why fit the STO-nG basis functions to maximise overlap rather than to minimize the energy?" Tags="|quantum-chemistry|computational-chemistry|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9400" PostTypeId="1" CreationDate="2022-07-18T12:17:21.587" Score="4" ViewCount="147" Body="&lt;p&gt;In the same line of thoughts as &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9378/are-there-interesting-applications-of-estimating-the-energy-for-generalizations/9380#9380&quot;&gt;this&lt;/a&gt; post, I am trying to understand better in which cases quantum computers could be useful to simulate materials under some constraints on what the quantum computer can do.&lt;/p&gt;&#xA;&lt;p&gt;I consider a class of Hamiltonians among which we can find the Ising models without external magnetic field:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=\sum_{i=1}^{\textrm{Poly}(n)} c_i P^{(i)}_Z  \tag{1}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$P^{(i)}_Z$&lt;/span&gt; is an n-Pauli operator which is a tensor product of &lt;span class=&quot;math-container&quot;&gt;$\mathbb{I}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\textrm{Poly}(n)$&lt;/span&gt; means that my sum contains a polynomial number of terms as a function of the number of qubits &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;. The Ising model in the absence of an external magnetic field, being written &lt;span class=&quot;math-container&quot;&gt;$H=\sum_{\langle i,j\rangle} J_{ij} Z_i Z_j$&lt;/span&gt; is then one particular choice for &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's assume that I am able to evaluate &lt;span class=&quot;math-container&quot;&gt;$\langle \psi | H | \psi \rangle$&lt;/span&gt; efficiently, for any entangled state &lt;span class=&quot;math-container&quot;&gt;$|\psi\rangle$&lt;/span&gt;. Is there anything useful I could access in terms of physics with that?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;More context&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know that one &amp;quot;hot question&amp;quot; about the Ising model is to be able to find its ground state. However this ground state in the absence of magnetic field is necessarily a tensor product (so it is not very useful to consider an entangled state in this case). Also, to find it, a brute-force approach would be to try exponentially many ansatz (hence even if &lt;span class=&quot;math-container&quot;&gt;$\langle \psi | H | \psi \rangle$&lt;/span&gt; is &amp;quot;easy&amp;quot; to evaluate it is not enough to do something interesting).&lt;/p&gt;&#xA;&lt;p&gt;That being said, it could be that in some cases it is interesting to study the properties of this Ising model with initial entangled state. I don't have any specific idea in mind but I don't find a reason why such cases would necessarily be un-interesting.&lt;/p&gt;&#xA;&lt;p&gt;I hope it provides a little bit more context behind my question.&lt;/p&gt;&#xA;" OwnerUserId="5716" LastEditorUserId="5" LastEditDate="2022-07-18T17:13:17.683" LastActivityDate="2022-07-18T18:00:53.817" Title="Is there any useful application to estimating the expectation value for an Ising model without magnetic field?" Tags="|condensed-matter|magnetism|model-hamiltonians|ising-model|quantum-computing|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9401" PostTypeId="2" ParentId="9400" CreationDate="2022-07-18T18:00:53.817" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I know that one &amp;quot;hot question&amp;quot; about the Ising model is to be able to find its ground state. However this ground state in the absence of magnetic field is necessarily a tensor product (so it is not very useful to consider an entangled state in this case).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is not only true for the ground state. All eigenstates of your Eq. 1 can be written as a tensor product of single spin states.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Also, to find it, a brute-force approach would be to try exponentially many ansatze (hence even if ⟨ψ|H|ψ⟩ is &amp;quot;easy&amp;quot; to evaluate it is not enough to do something interesting).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It's true that you can find the ground state by trying exponentially many ansatze and seeing which one gives you the lowest energy. This doesn't mean that finding the ground state is not enough to do something interesting. Finding the ground state of an Ising model can solve many problems such as &lt;a href=&quot;https://arxiv.org/abs/1411.6758&quot; rel=&quot;nofollow noreferrer&quot;&gt;factoring integers&lt;/a&gt; and &lt;a href=&quot;https://arxiv.org/abs/1508.07190&quot; rel=&quot;nofollow noreferrer&quot;&gt;finding Ramsey numbers&lt;/a&gt; along with many others. Perhaps you mean that simply being able to calculate ⟨ψ|H|ψ⟩ efficiently is not enough to find the ground state efficiently, which is correct because there's an infinite number of possible states |ψ⟩ in the Hilbert space. However, quantum computers can already calculate the &lt;em&gt;&lt;strong&gt;ground&lt;/strong&gt;&lt;/em&gt; state of H efficiently, without calculating ⟨ψ|H|ψ⟩ for all possible |ψ⟩ by brute force. Therefore, it would seem that by saying &amp;quot;constraints on what the quantum computer can do&amp;quot; you meant that the quantum calculator can do ⟨ψ|H|ψ⟩ efficiently but &lt;em&gt;&lt;strong&gt;nothing&lt;/strong&gt;&lt;/em&gt; else directly (i.e. it can't find the ground state efficiently).&lt;/p&gt;&#xA;&lt;p&gt;In that case, it's still useful to be able to calculate ⟨ψ|H|ψ⟩ when |ψ⟩ is an arbitrary tensor product of single spin states (i.e. |ψ⟩ is not necessarily the ground state). &lt;strong&gt;This would tell you the energy of the ↑↓↓↑↑↑↓↑ configuration of electron spins, under the given Hamiltonian, for example.&lt;/strong&gt; Beyond the realm of physics, there's also many applications of &lt;a href=&quot;https://or.stackexchange.com/q/828/727&quot;&gt;QUBO&lt;/a&gt; in classical computing, and being able to evaluate the energy for a particular configuration of {0,1}&lt;sup&gt;n&lt;/sup&gt; could be helpful in many QUBO applications, &lt;em&gt;&lt;strong&gt;assuming your the quantum calculator can evaluate ⟨ψ|H|ψ⟩ efficiently with respect to the number of spins, rather than with respect to the number of states in the Hilbert space.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;That being said, it could be that in some cases it is interesting to study the properties of this Ising model with initial entangled state.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If the state is entangled, then it is not an eigenstate of Eq. 1, so it's unlikely that it would have many useful applications in physics. The following code shows this for &lt;span class=&quot;math-container&quot;&gt;$Z_1Z_2$&lt;/span&gt; acting on a Bell state, and can easily be verified &lt;a href=&quot;https://octave-online.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;z1 = kron([1 0 ; 0 -1],eye(2)); z2 = kron(eye(2),[1 0 ; 0 -1]);&#xA;H = z1*z2;&#xA;psi = (1/sqrt(2))*[1; 0 ; -1 ; 0 ];&#xA;H*psi;&#xA;[H*psi psi]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result is a matrix whose first column is H|ψ⟩ and the second column is |ψ⟩ and they are not scalar multiples of each other, so |ψ⟩ is not an eigenstate of H.&lt;/p&gt;&#xA;&lt;p&gt;Most of physics concerns states that are eigenstates of their Hamiltonian, so applications of your quantum calculator are limited by that. States that are not eigenstates of their Hamiltonian can still exist (maybe not for long!) and they are sometimes called &amp;quot;resonance states&amp;quot;, which are very unstable. Perhaps there's applications there, or elsewhere, but likely not anything worth a large investment (even fully-fledged &amp;quot;universal&amp;quot; quantum computers will be very limited in terms of practical applications that are useful to society).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-07-18T18:00:53.817" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9402" PostTypeId="2" ParentId="9374" CreationDate="2022-07-19T15:41:45.727" Score="8" Body="&lt;h4&gt;General Thermostatting&lt;/h4&gt;&#xA;&lt;p&gt;The point of thermostatting is to maintain the velocities of simulated particles in rough correspondence to a temperature. This matters for the simulation of a temperature-controlled ensemble, which implies that the simulated particles interact not only with each other, but also with a &amp;quot;bath&amp;quot;. (NVE ensemble cares less about this). This necessarily means that the &amp;quot;bath&amp;quot;, which is a virtual object not physically present in the simulation volume, can exert some forces accelerating particles, and absorb some energy decelerating particles. Thermostats differ in how the &amp;quot;bath&amp;quot; and the system's interaction with it are implemented, and these implementations affect the system in various ways. Simulation codes implement thermostats to varying degrees of completeness and complexity (looking at you, &lt;a href=&quot;https://www.vasp.at/wiki/index.php/MDALGO&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h4&gt;Nose-Hoover&lt;/h4&gt;&#xA;&lt;p&gt;The Nose thermostat treats the bath as an extra degree of freedom. There is effectively an extra (big, virtual) particle, or chain of particles (Nose chain), in the simulation. The specific equations of motion for this degree of freedom / chain can differ between implementations, but generally it is constrained. So when simulation particles push the thermostat too far, the thermostat pushes back and slows them down. Compare, for example, the implementations in &lt;a href=&quot;https://docs.lammps.org/fix_nh.html&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt; versus &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Nose-Hoover_thermostat&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt;, the first uses a time constant, while the second uses an effective mass. This thermostat generally needs a bit of &amp;quot;time&amp;quot; to initialize at the beginning of the simulation, as its degree of freedom likely starts from a zero velocity, and simulation particles likely start by dumping energy into it, which means simulation temperature can be off the set point for a little while, and then it may oscillate. The thermostat is &amp;quot;equilibrated&amp;quot; or &amp;quot;initialized&amp;quot; when its degree of freedom moves more or less chaotically.&lt;/p&gt;&#xA;&lt;h4&gt;Langevin&lt;/h4&gt;&#xA;&lt;p&gt;Langevin thermostat parallels the Langevin equation of motion: it accelerates particles with a random force, and imposes a friction/damping on the velocities of the particles. The strength of the random force is proportional to the damping: more damping, more forcing. The random force transfers kinetic energy to the simulation, and the friction takes kinetic energy out of the simulation. Compare the implementations, for example, between &lt;a href=&quot;https://docs.lammps.org/fix_langevin.html&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Langevin_thermostat&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt;. The key to making the Langevin thermostat work well is to ensure the random force couples to some reasonable physical vibration in the system and actually transfers energy to the system by driving it. Dynamics faster than that timescale/frequency, however, could be suspect. Sometimes, this can be done with separate constants for different parts or species. See also a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4245/selection-of-appropriate-langevin-damping-parameter-for-md-of-solid-metal?noredirect=1&amp;amp;lq=1&quot;&gt;related question + good answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Odds and Ends&lt;/h4&gt;&#xA;&lt;p&gt;In AIMD, thermostats work on nuclear motions, not on the electronic excitations.&lt;/p&gt;&#xA;&lt;p&gt;In my limited experience, Langevin can equilibrate faster, but also can have more noise in the total energy when compared to the Nose for the same simulated system.&lt;/p&gt;&#xA;&lt;h4&gt;Other Thermostats&lt;/h4&gt;&#xA;&lt;p&gt;Check out also the &lt;a href=&quot;https://docs.lammps.org/fix_temp_csvr.html&quot; rel=&quot;noreferrer&quot;&gt;CSVR aka Bussi-Donadio-Parrinello&lt;/a&gt; thermostat, generally considered more advanced. Linking LAMMPS documentation here, which is not bad for an intro, and which links the original papers that introduce the thermostat.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-07-19T21:56:23.113" LastActivityDate="2022-07-19T21:56:23.113" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9403" PostTypeId="2" ParentId="4443" CreationDate="2022-07-19T15:50:12.070" Score="5" Body="&lt;p&gt;A recent non-obvious one has been the use of TD-DFT to look at vibrational couplings in singlet fission in pentacene. The sequence of electronic transitions works like this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Optical absorption creates a spin-singlet excited state. This is fast.&lt;/li&gt;&#xA;&lt;li&gt;But that has a spin-allowed and energy- and entropy-favorable transition to a bound triplet pair. So this lives for 30-80 fs only.&lt;/li&gt;&#xA;&lt;li&gt;Triplet pair dissociates, and triplets are long-lived (nano- to microseconds).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The excited state was found to couple to a few vibrations, most notably a 1-THz one. The TD-DFT results agreed with experimental ultrafast electron diffraction.&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://www.science.org/doi/full/10.1126/sciadv.abg0869&quot; rel=&quot;noreferrer&quot;&gt;https://www.science.org/doi/full/10.1126/sciadv.abg0869&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4515" LastActivityDate="2022-07-19T15:50:12.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9405" PostTypeId="1" CreationDate="2022-07-20T05:51:05.580" Score="1" ViewCount="543" Body="&lt;p&gt;In Quantum Espresso, there is a parameter called &lt;code&gt;nspin&lt;/code&gt;, which I understand to include in INPUT if there is a paramagnetic species, like &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt;. Thus, we also include &lt;code&gt;starting_magnetization&lt;/code&gt; parameter.&lt;/p&gt;&#xA;&lt;p&gt;I have an &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt; slab now and require to study adsorption of &lt;span class=&quot;math-container&quot;&gt;$\ce{PO4^{3-}}$&lt;/span&gt; (phosphate species) onto the &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt; slab. Must I include &lt;code&gt;starting_magnetization&lt;/code&gt; for &lt;span class=&quot;math-container&quot;&gt;$\ce{PO4^{3-}}$&lt;/span&gt;? I am assuming that the electronic configurations of &lt;span class=&quot;math-container&quot;&gt;$\ce{P}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$2\mathrm{p}^3$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$\ce{O}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$2\mathrm{p}^4$&lt;/span&gt;) has unpaired electrons, just like &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe}$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$3\mathrm{d}^6$&lt;/span&gt;)!&lt;/p&gt;&#xA;&lt;p&gt;Along with Fe, must I include the parameter &lt;code&gt;starting_magnetization(2)&lt;/code&gt; and &lt;code&gt;starting_magnetization(3)&lt;/code&gt; for &lt;span class=&quot;math-container&quot;&gt;$\ce{P}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{O}$&lt;/span&gt; atoms?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5378" LastEditorUserId="7" LastEditDate="2022-07-21T18:13:07.647" LastActivityDate="2022-07-27T05:50:21.147" Title="nspin and starting_magnetization in Quantum Espresso" Tags="|quantum-espresso|magnetism|spin|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9406" PostTypeId="1" CreationDate="2022-07-20T07:12:34.633" Score="3" ViewCount="764" Body="&lt;p&gt;Has someone made some experience with installing GaussView for Linux on an Ubuntu ARM64 virtuelle maschine? I work with an Mac M1 Chip MacBook Pro and GaussView is the only program I need to run on linux. So my idea was to set up a parallels VM for Linux Ubuntu and install GaussView on this VM.&lt;/p&gt;&#xA;&lt;p&gt;Is there a problem with running GaussView for Linux on Ubuntu ARM 64? Or should it work?&lt;/p&gt;&#xA;&lt;p&gt;I tried to install GaussView but it does not work. Maybe the problem is with me and not with the VM, because I try to install GaussView for the first time.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for help and ideas!&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="5" LastEditDate="2023-01-31T21:45:49.033" LastActivityDate="2023-01-31T21:45:49.033" Title="Installation of GaussView on Linux Ubuntu 20.04.2 ARM" Tags="|gaussian|software-assistance|apple-operating-system|" AnswerCount="0" CommentCount="8" ClosedDate="2023-06-14T01:07:22.643" ContentLicense="CC BY-SA 4.0" />
  <row Id="9407" PostTypeId="2" ParentId="9021" CreationDate="2022-07-20T08:05:18.773" Score="2" Body="&lt;p&gt;I guess the you are working on doping. Suppose in the following we consider only semiconductors.&lt;/p&gt;&#xA;&lt;p&gt;I disagree with &amp;quot;Fermi level is electron chemical potential at 0K and we can obtain it from DFT calculation.&amp;quot; First, I would not be bothered by the textbook to consider &amp;quot;Fermi level is electron chemical potential at 0K&amp;quot;. Instead, I simply think &amp;quot;Charge is exchanged with a reservoir of&#xA;electrons, the energy of which is the electron chemical potential, in other words, the Fermi energy&amp;quot; (see the review paper &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.86.253&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;First-principles calculations for point defects in solids&amp;quot;&lt;/a&gt;). Second, DFT calculations only give an artificial Fermi level for 0K calculation of a pure system.&lt;/p&gt;&#xA;&lt;p&gt;Usually, the electron temperature equals the ionic temperature. At finite temperature, the Fermi level is determined by self-consistent solution of the charge neutral condition (see the review paper). A special case is when your system does not contain a defect, then the Fermi level can be obtained by n=p (still the charge neutral condition), where n is free electron concentration (you can sum the occupations in the conduction bands), and p is the free hole concentration (you can sum the unoccupations in the valence band). You can adjust the Fermi level position, this will mimic free-carrrier doping, i.e., the so-called rigid-band approximation in the literature.&lt;/p&gt;&#xA;" OwnerUserId="1688" LastEditorUserId="142" LastEditDate="2022-07-23T18:03:21.270" LastActivityDate="2022-07-23T18:03:21.270" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9408" PostTypeId="1" CreationDate="2022-07-20T10:17:01.070" Score="7" ViewCount="310" Body="&lt;p&gt;I want to freeze some of the orbitals (e.g 1s orbital for all of the atoms in my molecule) in GAMESS-US, to save computation time. I guess I need to use $MOFRZ but I'm not sure how to. So far, I've created the input file as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &lt;span class=&quot;math-container&quot;&gt;$CONTRL SCFTYP=RHF CCTYP=CCSD(T) RUNTYP=ENERGY ICHARG=1&#xA;       UNITS=ANGS ISPHER=1 $&lt;/span&gt;END&#xA;!   &#xA; &lt;span class=&quot;math-container&quot;&gt;$SCF DIIS=.TRUE. $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$GUESS GUESS=MOREAD NORB=69 $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$MOFRZ FRZ=.TRUE. IFRZ(1)=1,10,19,28 $&lt;/span&gt;END&#xA;!&#xA; &lt;span class=&quot;math-container&quot;&gt;$SYSTEM MWORDS=1500 $&lt;/span&gt;END&#xA;!&#xA;  &lt;span class=&quot;math-container&quot;&gt;$VEC   &#xA; 1  1-9.95521651E-06-3.24237240E-06-5.54660060E-06-2.93436786E-04 1.30027027E-02&#xA;.&#xA;.&#xA;.&#xA;69 55-9.89984798E-03-1.24161440E-03-4.86737205E-04 2.96787026E-03-1.28394192E-03&#xA;69 56 1.26297389E-02-3.44011121E-02-9.31840053E-04-1.12673533E-03-2.64710788E-03&#xA; $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$DATA&#xA;C1&#xA;.&#xA;.&#xA;.&#xA; $&lt;/span&gt;END&#xA; &lt;span class=&quot;math-container&quot;&gt;$BASIS&#xA;    GBASIS=KTZVP&#xA; $&lt;/span&gt;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I run this input, I get the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                   * * * * * WARNING * * * * *&#xA; POSSIBLE LINEAR DEPENDENCE PROBLEMS DETECTED, INPUT QMTTOL= 1.0E-06,&#xA; WITH     2 OVERLAP EIGENVALUES LYING BETWEEN 1.0E-05 AND QMTTOL.&#xA; IF YOU EXPERIENCE SCF CONVERGENCE DIFFICULTIES WITH THE DENSITY ALMOST BUT&#xA; NOT QUITE CONVERGED, YOU MAY NEED TO LOOSEN -QMTTOL- BY A FACTOR 5 TO 10.&#xA; NO $VEC INPUT FOUND - STOP &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I solve my problem? Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5755" OwnerDisplayName="Alert" LastEditorUserId="1380" LastEditDate="2022-07-22T10:30:27.463" LastActivityDate="2022-07-22T10:30:27.463" Title="How to freeze molecular orbitals in GAMESS-US?" Tags="|computational-chemistry|quantum-chemistry|gamess|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9409" PostTypeId="2" ParentId="8790" CreationDate="2022-07-20T11:36:15.237" Score="4" Body="&lt;h4&gt;TL;DR&lt;/h4&gt;&#xA;&lt;p&gt;Thermostatting / barostatting in ensembles such as NVT, NPT, etc, introduces an exchange of energy between the simulated system and a virtual &amp;quot;bath&amp;quot;. You should ensure that whatever you are observing in simulation is a property of the system, not of its coupling to the thermostat / barostat. For a first pass, I would recommend equilibrating the system in a relevant ensemble, then switching to NVE for the excitation and subsequent dynamics.&lt;/p&gt;&#xA;&lt;h4&gt;The Physics&lt;/h4&gt;&#xA;&lt;p&gt;It looks like you are interested in exciting some species in a simulation volume, and tracking where that energy subsequently goes. Most likely, (1) you have some species or degrees of freedom to which energy can be transferred, and (2) the excitation is with an electric field / photon. Quantum-mechanically, the absorption of a photon is fast. In a classical potentials-based molecular-dynamics simulation, a classical interaction of charged particles with a field can also be simulated - ignoring polarizability or including it with a shell model.&lt;/p&gt;&#xA;&lt;p&gt;Most likely, absorption / excitation is the fastest process. The next slower one is the coupling of the initially excited degree of freedom (electronic / phononic / translation / rotation) to others within the system. Most likely (see &amp;quot;nonlinearity&amp;quot; in limitations), the excited degree of freedom will transfer energy to lower-energy ones, which are definitionally lower frequency and work on longer timescales. If excitations are sparse and/or localized, there will ultimately be some heat diffusion happening as well. While all of this is happening, the system has more energy than it should, and is out of equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;Here is the most important part: in simulation, the thermal coupling to &amp;quot;bath&amp;quot; is usually much faster than in experiment, because simulation is a much smaller system than in reality. Heat transfer from something like an excited molecule to the substrate on which it sits takes &lt;em&gt;nanoseconds&lt;/em&gt; in real life, see for example &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.195411&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fig 7 in this paper&lt;/a&gt;. But we cannot tolerate a thermostat that takes so long in simulation, which means that thermostatting pulls energy from the simulation more rapidly than is really physical. It does so by coupling to higher-energy degrees of freedom in the system and slowing them down.&lt;/p&gt;&#xA;&lt;p&gt;Practically, this means that thermostatting will affect more dynamics than is physical in a non-equilibrium simulation with excitations. The easiest solution to this is to equilibrate the system first, then simulate the non-equilibrium dynamics in NVE, and note the temperature rise. The next easiest is to simulate a range of thermostatting parameters, and only trust the results in the range where changing the thermostat does not change the observed dynamics.&lt;/p&gt;&#xA;&lt;h4&gt;Literature&lt;/h4&gt;&#xA;&lt;p&gt;There is a rigorous body of work simulating the excitations of molecular motions and vibrations in liquids. Notably, they have used both classical MD and ab initio MD. The ab initio lets them study polarizability and second-order (induced-dipole) effects. In approximate chronological order, there are a few pure simulation papers, &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jpcb.5b02860&quot; rel=&quot;nofollow noreferrer&quot;&gt;one&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.032124&quot; rel=&quot;nofollow noreferrer&quot;&gt;two&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jpca.8b00828&quot; rel=&quot;nofollow noreferrer&quot;&gt;three&lt;/a&gt;, and a few experiment + simulation papers: &lt;a href=&quot;https://www.nature.com/articles/s41467-018-04481-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;one&lt;/a&gt; and &lt;a href=&quot;https://www.science.org/doi/full/10.1126/sciadv.aay7074&quot; rel=&quot;nofollow noreferrer&quot;&gt;two&lt;/a&gt; and &lt;a href=&quot;https://www.nature.com/articles/s41557-022-00977-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;three&lt;/a&gt;. I am not sure what to say or highlight about these works other than they have looked at a variety of aspects of this type of simulation, and benchmarked them with experiments. A keen reader could pay attention to the analyses used to track the partitioning of energy between various degrees of freedom, and how the simulated excitation strengths correspond to the experimental ones.&lt;/p&gt;&#xA;&lt;p&gt;Absolutely shameless plug of my own work: I've used classical MD to look at the excitation of ionic translations with light, &lt;a href=&quot;https://arxiv.org/abs/2110.06522&quot; rel=&quot;nofollow noreferrer&quot;&gt;pre-print here&lt;/a&gt;. I took five steps to ensure I could trust the results: (1) used a system with the fewest possible confounding degrees of freedom (2) used NVE and noted the temperature rise (3) made a very large simulation to get enough rare-event statistics (4) used an excitation field that is equal to the experimental one to minimize confounding contributions from nonlinearity (5) interpreted only the most salient, qualitative trends rather than the quantitative rates. The simulation is probably quantitatively wrong, but the trends are probably qualitatively right.&lt;/p&gt;&#xA;&lt;h4&gt;Limitations&lt;/h4&gt;&#xA;&lt;p&gt;First, this answer deals mostly with classical, nuclear-dynamics stuff. It &lt;em&gt;may&lt;/em&gt; be possible to just put a field into an ab initio simulation and simulate electronic excitations. But I don't know for sure. If you want to do a proper electronic excitation, someone else should answer with how best to do it in ab initio, TD-DFT, etc.&lt;/p&gt;&#xA;&lt;p&gt;Second, the excitation and dynamics of interest may be rare; beware averages. This happens most at higher frequencies / energies as quantum effect become prominent. See for example &lt;a href=&quot;https://www.nature.com/articles/s41586-021-03793-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper about water&lt;/a&gt; (disclosure: I worked with some of these people), where to match the simulated effect to experiment the excitation fraction had to be taken into account. Experimental excitation strength / density may be much smaller than what is practical to simulate while still getting a simulated signal - but the dynamics at simulate-able strength may not be the same as at an experimental one. Separately, the dynamics of interest could also be a small shoulder superimposed on some larger effect you may not care about, as in my work linked above.&lt;/p&gt;&#xA;&lt;p&gt;Third, nonlinearity happens. Nonlinearity and anharmonicity of vibrations are integral to the transfer of energy between degrees of freedom, and to heat transport in the first place. Polarizability and induced-dipole effects may happen. If electrons are involved, weird stuff like impact ionization may happen. Nonlinear processes such as phonon upconversion turn on with excitation strength. In general, I recommend being very careful about the excitation strength used in simulation as that will affect subsequent dynamics: try a few, or go as low as possible, or match an experiment.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-07-20T11:42:28.670" LastActivityDate="2022-07-20T11:42:28.670" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9410" PostTypeId="1" AcceptedAnswerId="9428" CreationDate="2022-07-20T11:54:29.320" Score="4" ViewCount="584" Body="&lt;p&gt;I am looking for a way to easily evaluate individual molecular orbitals on a grid(assuming a single determinant method for now) in PySCF.&lt;/p&gt;&#xA;&lt;p&gt;I am aware on how to generate efficient grids for real-space integration &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9308/generate-grid-coordinates-from-pyscf-dft-package-for-plotting-grid-points&quot;&gt;(see here for example)&lt;/a&gt;, and I've also managed to find out how to evaluate the electron density on these grid points, with the following general code for example&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def gen_matrix_element(function_to_eval, molecule, myhf, args):&#xA;    matelements = np.asarray([])&#xA;&#xA;    for position in grid.coords:&#xA;        real_space_value = function_to_eval(r, theta, phi, args) &#xA;        matelements = np.append(matelements, real_space_value)&#xA;&#xA;    dm1 = myhf.make_rdm1(ao_repr=True)[0] + myhf.make_rdm1(ao_repr=True)[1]&#xA;    ao_value =  dft.numint.eval_ao(molecule, grid.coords, deriv=0)&#xA;    rho = dft.numint.eval_rho(molecule, ao_value, dm1) # Density on the same grid&#xA;&#xA;    combined = grid.weights * matelements&#xA;    integral = np.dot(rho.T, combined.T)&#xA;    return integral&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not quite certain, however, what is the procedure if I would want to return the integral value for each molecular orbital individually. Is there a similar function to &lt;code&gt;dft.numint.eval_rho&lt;/code&gt; for molecular orbitals?&lt;/p&gt;&#xA;&lt;p&gt;I also assume that if I sum over all the occupied molecular orbitals, I get the same result as I would get having used the full electron density - is this correct?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; I've tried the implementation suggested above, but I am a bit unsure on what the numbers mean.&lt;/p&gt;&#xA;&lt;p&gt;My current code is the following&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import numpy as np&#xA;import pyscf&#xA;from pyscf import gto, scf, tools, dft, ao2mo&#xA;from scipy.special import sph_harm&#xA;import math as m&#xA;&#xA;###&#xA;# Initialize the molecule and the calculation&#xA;###&#xA;def setup_system():&#xA;    mol = gto.M( # Change atom here&#xA;        atom = [[&amp;quot;He&amp;quot;, (0.0, 0.0, 0.0)], [&amp;quot;He&amp;quot;, (1.0, 0.0, 0.0)]],&#xA;        basis = {'He': 'aug-cc-pvtz'},&#xA;        spin=0,&#xA;        charge=0,&#xA;        verbose=0&#xA;    )&#xA;    mol.build()&#xA;&#xA;    # Unperturbed calculators&#xA;    mf0 = dft.UKS(mol)&#xA;    mf0.xc = 'PBE0'&#xA;    e0 = mf0.kernel()&#xA;&#xA;    # Grid for spatial integration&#xA;    grid = pyscf.dft.gen_grid.Grids(mol)&#xA;    grid.level = 7&#xA;    grid.build()&#xA;&#xA;    return mol, mf0, grid, e0&#xA;&#xA;def print_mo_on_grid(molecule, calculator, grid):&#xA;    ao = molecule.eval_gto('GTOval', grid.coords)&#xA;    mo = np.einsum('gi,xij-&amp;gt;xgj', ao, calculator.mo_coeff)&#xA;    return ao, calculator.mo_coeff, mo&#xA;&#xA;&#xA;molecule, calculator, grid, e0 = setup_system() # setting up the calculation&#xA;&#xA;ao_vals, mo_coeff, mo_vals = print_mo_on_grid(molecule, calculator, grid)&#xA;&#xA;print(&amp;quot;ao vals shape: &amp;quot;,ao_vals.shape)&#xA;print(&amp;quot;mo vals shape: &amp;quot;,mo_vals.shape)&#xA;print(&amp;quot;mo coeff shape: &amp;quot;,mo_coeff.shape)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This code results in the following printout:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ao vals shape:  (79368, 46)&#xA;mo vals shape:  (2, 79368, 46)&#xA;mo coeff shape:  (2, 46, 46)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I understand the shape of the &lt;code&gt;ao_vals&lt;/code&gt; variable: for 79368 grid points, I get the value of each of the 46 basis functions. I already don't fully get the shape of the MO coeff tensor - I assume the first number is 2 because of the UKS calculation I'm doing, but why is that even needed? Can't I have a (46, 46) matrix? And I guess this weird shape messes up the &lt;code&gt;mo_vals&lt;/code&gt; variable too - I'd have expected a vector of 79368 elements, but I don't know how to interpret the current shape at all.&lt;/p&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5648" LastEditDate="2022-08-12T13:57:49.437" LastActivityDate="2022-08-14T21:06:14.727" Title="Molecular orbital values on grid points in PySCF?" Tags="|hartree-fock|orbitals|pyscf|integrals|electron-density|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9411" PostTypeId="2" ParentId="9408" CreationDate="2022-07-20T13:19:57.230" Score="6" Body="&lt;p&gt;Firstly, the error &lt;code&gt;NO $VEC INPUT FOUND&lt;/code&gt; means that GAMESS did not find molecular orbitals to read in. This is because you wrote two spaces before &lt;code&gt;$VEC&lt;/code&gt; in the input file, i.e. &lt;code&gt;  $VEC&lt;/code&gt;. But it is supposed to be only 1 space, i.e. &lt;code&gt; $VEC&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, I suggest that put the &lt;code&gt;$VEC&lt;/code&gt; section into the final paragraph/section in the input file. This makes the input more readable since we should first know the coordinates and the basis set, and then we(or the program) determine the size of arrays to hold overlap integrals, molecular coefficients, etc. I'm not sure that whether the &lt;code&gt;$VEC&lt;/code&gt; section can be put before coordinates and basis set.&lt;/p&gt;&#xA;&lt;p&gt;Thirdly, frozen core is default for CCSD(T) in GAMESS. The default is the number of chemical core orbitals. For example, 1s for the oxygen atom. You can check the number of frozen orbitals in output via searching &lt;code&gt;NUMBER OF FROZEN CORE MOS&lt;/code&gt;. If you do not want the default one, you can specify &lt;code&gt;NCORE=n&lt;/code&gt; in &lt;code&gt;$CCINP&lt;/code&gt;, where n is the number of frozen orbitals you want. Besides, you can freeze some highest virtual orbitals if you are an experienced user (&lt;code&gt;NFZV=m&lt;/code&gt; in &lt;code&gt;$CCINP&lt;/code&gt;, default is 0). As far as I know, &lt;code&gt;$MOFRZ&lt;/code&gt; is used in RHF, ROHF and GVB (i.e. SCF-type jobs), but not in post-HF calculations.&lt;/p&gt;&#xA;&lt;p&gt;If you want more customized frozen cores, I guess you should first run a HF calculation, visualize the occupied orbitals, alter/permute orbitals to make sure the orbitals to be frozen lies in the lowest occupied ones. In this case, you may still use &lt;code&gt;NCORE=n&lt;/code&gt; since orbitals have been permuted as you wish.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastEditorUserId="5172" LastEditDate="2022-07-20T13:26:33.457" LastActivityDate="2022-07-20T13:26:33.457" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9412" PostTypeId="1" CreationDate="2022-07-20T17:09:12.943" Score="3" ViewCount="48" Body="&lt;p&gt;I am trying to construct a convex hull for a battery cathode with the following reactions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;2\ce{Li_2O} \leftrightarrow \ce{Li_2O_2 + 2Li^+} \tag{1} \\ &#xA;2\ce{Li_2O} \leftrightarrow \ce{LiO_2 + 3Li^+} \tag{2}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and I am not sure how to get started. As in, should look at &lt;span class=&quot;math-container&quot;&gt;$\ce{Li_xO_2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$Li_2O_y$&lt;/span&gt; possible structures individually? Do I need to consider all &lt;span class=&quot;math-container&quot;&gt;$Li_xO_y$&lt;/span&gt; possible structures? Given that the reaction involves only delithiation (with no change in the number of oxygen atoms), should I consider it as one would an intercalation reaction and set the formation energy to the following equation?&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_f(Li_xO_2) = E(Li_xO_2) - xE(LiO_2)-(1-x)E(O_2).\tag{3}$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5752" LastEditorUserId="5" LastEditDate="2023-01-31T21:49:32.900" LastActivityDate="2023-01-31T21:49:32.900" Title="Constructing a convex hull for Li2O/O2 reaction" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:46:11.750" ContentLicense="CC BY-SA 4.0" />
  <row Id="9413" PostTypeId="1" CreationDate="2022-07-20T23:20:32.890" Score="5" ViewCount="505" Body="&lt;p&gt;Dear fellow matter modelers, I am trying to model the zig-zag antiferromagnetic material &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;-RuCl&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt; using QUANTUM ESPRESSO. My end goal is to include DFT + U + SOC, however, including too many of these things together seems to hurt convergence. I am using a supercell with 8 Ru atoms and 32 Cl atoms to accommodate the zig-zag magnetic structure as reported in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.92.235119&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phys. Rev. B 92, 235119&lt;/a&gt;. I have succeeded in getting the zig-zag magnetic structure to converge without SOC or DFT by first converging for colinear magnetism, then using that as the charge density input for the noncolinear calculation as described in &lt;a href=&quot;https://pranabdas.github.io/espresso/hands-on/soc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial&lt;/a&gt;. However, when adding a Hubbard_U term to the Ru atoms, the SCF error does not decrease beyond roughly 0.05 Ry. I have tried modifying &lt;code&gt;mixing_beta&lt;/code&gt;, different types of smearing, different k_point grids, and fixing the total magnetization. Any help or advice with this would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Cheers!&lt;/p&gt;&#xA;&lt;p&gt;My input file is below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;   calculation     =  'scf'&#xA;   outdir          =  '.'&#xA;   prefix          =  'rucl3'&#xA;   pseudo_dir      =  '.'&#xA;   restart_mode    =  'from_scratch'&#xA; /&#xA;&#xA; &amp;amp;SYSTEM&#xA;   A               =  5.97620&#xA;   Hubbard_U(2)    =  4.8&#xA;   Hubbard_U(3)    =  4.8&#xA;   degauss         =  0.005&#xA;   ecutrho         =  200&#xA;   ecutwfc         =  50&#xA;   ibrav           =  0&#xA;   lda_plus_u      =  .TRUE.&#xA;   nat             =  32&#xA;   nspin           =  2&#xA;   ntyp            =  3&#xA;   occupations     =  'smearing'&#xA;   smearing        =  'gauss'&#xA;   starting_magnetization(2) =  1&#xA;   starting_magnetization(3) =  -1&#xA; /&#xA;&#xA; &amp;amp;ELECTRONS&#xA;   conv_thr        =  1e-6&#xA;   mixing_beta     =  0.1&#xA; /&#xA;&#xA;ATOMIC_SPECIES &#xA;  Cl    35.453   Cl.pbe.ONCVPSP.fr.upf &#xA;  Ru1    101.07   Ru.pbe.ONCVPSP.fr.upf &#xA;  Ru2    101.07   Ru.pbe.ONCVPSP.fr.upf &#xA;&#xA;&#xA;CELL_PARAMETERS alat&#xA;    1.0000000000000000   0.0000000000000000   0.0000000000000000&#xA;    0.0000000000000000   1.7305311067233360   0.0000000000000000&#xA;   -0.6508271189589490   0.0000000000000000   1.9041632824171890&#xA;&#xA;ATOMIC_POSITIONS crystal&#xA;  Ru1      0.000000000000   0.334410000000   0.000000000000&#xA;  Ru2      0.000000000000   0.665590000000   0.000000000000&#xA;  Ru2      0.500000000000   0.834410000000   0.000000000000&#xA;  Ru1      0.500000000000   0.165590000000   0.000000000000&#xA;  Ru1      0.000000000000   0.334410000000   0.500000000000&#xA;  Ru2      0.000000000000   0.665590000000   0.500000000000&#xA;  Ru2      0.500000000000   0.834410000000   0.500000000000&#xA;  Ru1      0.500000000000   0.165590000000   0.500000000000&#xA;  Cl       0.751380000000   0.173500000000   0.383095000000&#xA;  Cl       0.248620000000   0.173500000000   0.116905000000&#xA;  Cl       0.248620000000   0.826500000000   0.116905000000&#xA;  Cl       0.748620000000   0.673500000000   0.116905000000&#xA;  Cl       0.748620000000   0.326500000000   0.116905000000&#xA;  Cl       0.751380000000   0.826500000000   0.383095000000&#xA;  Cl       0.251380000000   0.673500000000   0.383095000000&#xA;  Cl       0.251380000000   0.326500000000   0.383095000000&#xA;  Cl       0.751380000000   0.173500000000   0.883095000000&#xA;  Cl       0.248620000000   0.173500000000   0.616905000000&#xA;  Cl       0.248620000000   0.826500000000   0.616905000000&#xA;  Cl       0.748620000000   0.673500000000   0.616905000000&#xA;  Cl       0.748620000000   0.326500000000   0.616905000000&#xA;  Cl       0.751380000000   0.826500000000   0.883095000000&#xA;  Cl       0.251380000000   0.673500000000   0.883095000000&#xA;  Cl       0.251380000000   0.326500000000   0.883095000000&#xA;  Cl       0.730230000000   0.000000000000   0.119475000000&#xA;  Cl       0.269770000000   0.000000000000   0.380525000000&#xA;  Cl       0.769770000000   0.500000000000   0.380525000000&#xA;  Cl       0.230230000000   0.500000000000   0.119475000000&#xA;  Cl       0.730230000000   0.000000000000   0.619475000000&#xA;  Cl       0.269770000000   0.000000000000   0.880525000000&#xA;  Cl       0.769770000000   0.500000000000   0.880525000000&#xA;  Cl       0.230230000000   0.500000000000   0.619475000000&#xA;&#xA;K_POINTS automatic&#xA;  5   5   5   1   1   1 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5753" LastEditorUserId="5753" LastEditDate="2022-07-21T00:21:11.803" LastActivityDate="2022-07-21T04:41:40.120" Title="Issues converging with DFT+U and magnetism in Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|magnetism|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9415" PostTypeId="2" ParentId="9413" CreationDate="2022-07-21T04:41:40.120" Score="3" Body="&lt;p&gt;As a solution, you should check if convergence is difficult due to the magnitude of your Ru U correction.  Try smaller corrections and see if that helps.  You can also try applying a correction to the Cl p orbitals.  Something like linear response will allow you to calculate a proper number to use, although some other methods such as the method used in the Cedar paper can alternatively be used.&lt;/p&gt;&#xA;&lt;p&gt;I have also seen cases where the U needs to be &amp;quot;ramped&amp;quot; from a small value to a larger value while saving charge density and wavefunctions.  You start from 0, then move to 0.5, then to 1 and so on. This helps to find a solution, but obviously can cost a bit of computational time.&lt;/p&gt;&#xA;&lt;p&gt;I am surprised you are adding a U correction to Ru.  How did you determine you need this?  I can't say that its unreasonable but I feel I have never seen it applied to Ru before.  The method used to determine it (was it just taken from the paper) might be useful to include in your question because it might highlight if the correction is way too large for some reason.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-07-21T04:41:40.120" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9416" PostTypeId="1" AcceptedAnswerId="10339" CreationDate="2022-07-21T13:49:43.437" Score="3" ViewCount="71" Body="&lt;p&gt;I am doing &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465519302048&quot; rel=&quot;nofollow noreferrer&quot;&gt;defect calculations using the SC-FERMI package&lt;/a&gt;. However, one of the inputs is the degeneracy of the charge states of each defect. &lt;strong&gt;I know degeneracy is the number of states with the same energy, but am unsure how to use that to determine the degeneracy of defect charge states.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I checked the literature in which SC-FERMI is used (i.e., &lt;a href=&quot;https://pubs.rsc.org/en/content/articlepdf/2021/cp/d1cp02794h&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;), but it does not explain how this value is obtained. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4192" LastEditorUserId="5" LastEditDate="2023-01-31T21:53:02.983" LastActivityDate="2023-02-01T23:15:20.033" Title="How to determine defect charge state degeneracies?" Tags="|software|defects|sc-fermi|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9417" PostTypeId="2" ParentId="9373" CreationDate="2022-07-21T14:21:29.460" Score="2" Body="&lt;p&gt;It is very unclear what you are asking about.&#xA;&amp;quot;How to have lower X-axis values highlighted like in the original plot.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;There is no x-axis highlighting in any of the plots.&lt;/p&gt;&#xA;&lt;p&gt;I tried to convert your data into a plot that looks a lot like the one you aimed for, here is my best guess:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/L3MMq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/L3MMq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code used to generate the plot can be found at &lt;a href=&quot;https://github.com/erikkjellgren/Shared_scripts/blob/main/notebooks/sial_plot.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/erikkjellgren/Shared_scripts/blob/main/notebooks/sial_plot.ipynb&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="210" LastActivityDate="2022-07-21T14:21:29.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9419" PostTypeId="1" CreationDate="2022-07-22T03:46:11.040" Score="3" ViewCount="229" Body="&lt;p&gt;I'm starting to learn LAMMPs with the intention of replacing my simple Python model for equilibrium configurations of adatoms on a crystal surface. Here's an example of what I do now, using a Lennard-Jones or harmonic oscillator potential between bonded atoms, and a static hexagonal potential imitating the imposed periodic potential of a surface, and I currently use just a simple damped ODE solver to find equilibrium positions at zero temperature:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/z5EMq.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/z5EMqm.jpg&quot; alt=&quot;hexagonal island on a periodic potential&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/a7wAh.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a7wAhm.jpg&quot; alt=&quot;hexagonal island on a periodic potential&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since the lattice constant of the adatoms is about 20% larger than that of the substrate potential, they &lt;em&gt;tend to&lt;/em&gt; seek various rotational angles where higher order coincidences can be found.&lt;/p&gt;&#xA;&lt;p&gt;I've built a chunk of fcc crystal with the top face as the (111) surface and a nearest-neighbor distance of 1.0, using lj units and the lj/cut potential.&lt;/p&gt;&#xA;&lt;p&gt;I set the sigma values at 2&lt;sup&gt;1/6&lt;/sup&gt; for the substrate atoms and about 20% larger for the adatoms, and I understand that LAMMPS will us a geometrical average for the 1 2 pairings.&lt;/p&gt;&#xA;&lt;p&gt;I've applied periodic boundary conditions in all three directions.&lt;/p&gt;&#xA;&lt;p&gt;The .in file is below as well as the first bit of the .input file. The full input file with all the initial atom positions is long so I've put it here&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pastebin.com/YD8RN270&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pastebin.com/YD8RN270&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What happened when I ran the energy minimization at 10 degrees Kelvin? I understand that this is not an &lt;em&gt;accurate&lt;/em&gt; model yet, I can see that the substrate atoms expanded vertically a little bit and the periodic boundary conditions prevented it from doing so laterally, so I need to tune my sigma or my atom spacing to a more relaxed situation.&lt;/p&gt;&#xA;&lt;p&gt;But because I am new to LAMMPS it's hard to understand if this has really reached a minimum energy configuration. &lt;strong&gt;I don't see any big motion in the adatoms, which is the thing I'd like to study.&lt;/strong&gt; Perhaps I need to fix the positions of the substrate atoms using something like &lt;code&gt;fix freeze substrate 0 0 0&lt;/code&gt; or similar? Would that help the minimizer focus more on the adatoms?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BoIaa.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BoIaa.gif&quot; alt=&quot;fundump.dump&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;GIF generated by Ovito looking at the .dump file &lt;a href=&quot;https://pastebin.com/rurbzFi9&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pastebin.com/rurbzFi9&lt;/a&gt;  I haven't been able to get Ovito to draw the atoms with smaller size yet.&lt;/p&gt;&#xA;&lt;h3&gt;log.lammps&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;LAMMPS (29 Sep 2021)&#xA;# ------------- Initialization&#xA;units       lj&#xA;dimension   3&#xA;atom_style  atomic&#xA;pair_style  lj/cut 2.5&#xA;&#xA;boundary    p p p&#xA;&#xA;read_data        fccbox_v02_input.data&#xA;Reading data file ...&#xA;  orthogonal box = (-0.17677670 -0.10206207 -4.4907312) to (13.823223 12.022294 1.8177570)&#xA;  1 by 1 by 1 MPI processor grid&#xA;  reading atoms ...&#xA;  1237 atoms&#xA;  read_data CPU = 0.003 seconds&#xA;&#xA;&#xA;&#xA;# ------------- System definition&#xA;# region  myregion block -0.1767767 13.8232233 -0.10206207 12.02229358 -4.4907312 2.25&#xA;&#xA;# create_box    2 myregion&#xA;&#xA;&#xA;# ------------- Simulation settings&#xA;# mass      1 1&#xA;# mass      2 1&#xA;&#xA;# pair_coeff       1 1 1.0 1.0 1.0   # these are in input.data&#xA;# pair_coeff       2 2 1.0 1.0 1.21&#xA;&#xA;neighbor 0.3 bin        # This is an extra skin for neighbors units of sigma&#xA;&#xA;&#xA;dump fundump all atom 100 fundump.dump&#xA;&#xA;velocity all create 10.0 42 rot no dist gaussian&#xA;&#xA;# ------------- Run&#xA;thermo      10&#xA;minimize    1.0e-4 1.0e-6 1000 10000&#xA;WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (src/min.cpp:188)&#xA;Neighbor list info ...&#xA;  update every 1 steps, delay 0 steps, check yes&#xA;  max neighbors/atom: 2000, page size: 100000&#xA;  master list distance cutoff = 1.6602422&#xA;  ghost atom cutoff = 1.6602422&#xA;  binsize = 0.83012109, bins = 17 15 8&#xA;  1 neighbor lists, perpetual/occasional/extra = 1 0 0&#xA;  (1) pair lj/cut, perpetual&#xA;      attributes: half, newton on&#xA;      pair build: half/bin/atomonly/newton&#xA;      stencil: half/bin/3d&#xA;      bin: standard&#xA;Per MPI rank memory allocation (min/avg/max) = 5.338 | 5.338 | 5.338 Mbytes&#xA;Step Temp E_pair E_mol TotEng Press &#xA;       0           10  -0.34005694            0    14.647817    59.679297 &#xA;       6           10   -2.5987468            0    12.389127    42.827225 &#xA;Loop time of 0.0170679 on 1 procs for 6 steps with 1237 atoms&#xA;&#xA;97.5% CPU use with 1 MPI tasks x no OpenMP threads&#xA;&#xA;Minimization stats:&#xA;  Stopping criterion = linesearch alpha is zero&#xA;  Energy initial, next-to-last, final = &#xA;    -0.340056939447598  -2.59874682375032  -2.59874682375032&#xA;  Force two-norm initial, final = 1156.0012 320.30496&#xA;  Force max component initial, final = 64.284628 33.671989&#xA;  Final line search alpha, max atom move = 1.2865070e-10 4.3319251e-09&#xA;  Iterations, force evaluations = 6 57&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 0.012193   | 0.012193   | 0.012193   |   0.0 | 71.44&#xA;Neigh   | 0.0014319  | 0.0014319  | 0.0014319  |   0.0 |  8.39&#xA;Comm    | 0.00075269 | 0.00075269 | 0.00075269 |   0.0 |  4.41&#xA;Output  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Modify  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Other   |            | 0.002691   |            |       | 15.76&#xA;&#xA;Nlocal:        1237.00 ave        1237 max        1237 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Nghost:        1619.00 ave        1619 max        1619 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;Neighs:        7441.00 ave        7441 max        7441 min&#xA;Histogram: 1 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 7441&#xA;Ave neighs/atom = 6.0153597&#xA;Neighbor list builds = 2&#xA;Dangerous builds = 0&#xA;Total wall time: 0:00:00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;.in&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;# ------------- Initialization&#xA;units       lj&#xA;dimension   3&#xA;atom_style  atomic&#xA;pair_style  lj/cut 2.5&#xA;&#xA;boundary    p p p&#xA;&#xA;read_data        fccbox_v02_input.data&#xA;&#xA;&#xA;&#xA;# ------------- System definition&#xA;# region  myregion block -0.1767767 13.8232233 -0.10206207 12.02229358 -4.4907312 2.25&#xA;&#xA;# create_box    2 myregion&#xA;&#xA;&#xA;# ------------- Simulation settings&#xA;# mass      1 1&#xA;# mass      2 1&#xA;&#xA;# pair_coeff       1 1 1.0 1.0 1.0   # these are in input.data&#xA;# pair_coeff       2 2 1.0 1.0 1.21&#xA;&#xA;neighbor 0.3 bin        # This is an extra skin for neighbors units of sigma&#xA;&#xA;&#xA;dump fundump all atom 100 fundump.dump&#xA;&#xA;velocity all create 10.0 42 rot no dist gaussian&#xA;&#xA;# ------------- Run&#xA;thermo      10&#xA;minimize    1.0e-4 1.0e-6 1000 10000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;beginning of.data&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;Data File created by fcc_box_v02.py&#xA;&#xA;1237 atoms&#xA;2 atom types&#xA;&#xA;-0.17677669529663687 13.823223304703363 xlo xhi&#xA;-0.10206207261596577 12.022293580366178 ylo yhi&#xA;-4.4907311951024935 1.8177570093457944 zlo zhi&#xA;&#xA;Masses&#xA;&#xA;1 1.0&#xA;2 1.9202965708989803&#xA;&#xA;Pair Coeffs&#xA;&#xA;1 1 1.0 1.122462048309373&#xA;2 2 1.0 1.360242170692667&#xA;&#xA;Atoms&#xA;&#xA;1 1 0.0 0.0 0.0&#xA;2 1 0.0 1.7320508075688774 0.0&#xA;3 1 0.0 3.464101615137755 0.0&#xA;4 1 0.0 5.196152422706632 0.0&#xA;5 1 0.0 6.92820323027551 0.0&#xA;6 1 0.0 8.660254037844387 0.0&#xA;7 1 0.0 10.392304845413264 0.0&#xA;8 1 1.0 0.0 0.0&#xA;9 1 1.0 1.7320508075688774 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="201" LastActivityDate="2022-07-22T03:46:11.040" Title="Did my Lennard-Jones potential LAMMPS simulation of a metal island on an FCC crystal surface find an energy minimum? (don't understand output)" Tags="|lammps|surfaces|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9420" PostTypeId="1" AcceptedAnswerId="9429" CreationDate="2022-07-22T09:23:43.903" Score="3" ViewCount="168" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/H4xF6.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/H4xF6.jpg&quot; alt=&quot;Fig. 1&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As a simple problem setting,&#xA;consider a one-dimensional linear crystal of NaCl with only 1s orbitals,&#xA;where the atomic distance between Na and Cl is also assumed to be 0.5 Å&#xA;for simplicity (Fig. 1).&#xA;In this problem setting, I would like to calculate&#xA;the tight-binding approximation (TBA) of the 1s orbitals of Na and Cl.&lt;/p&gt;&#xA;&lt;p&gt;First, for example, if I use the 6-31G(d,p) basis set,&#xA;the 1s orbitals of Na and Cl can be easily constructed&#xA;using the contraction coefficients and orbital exponents.&#xA;I write each atomic orbital as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\text{Na}: \phi_{\text{1s}} (r, R) =&#xA;\sum_{n=1}^6 \alpha_n e^{-\zeta_n ||r - R||^2}, (1)&#xA;\\&#xA;\text{Cl}: \psi_{\text{1s}} (r, R) =&#xA;\sum_{n=1}^6 \beta_n e^{-\gamma_n ||r - R||^2}, (2)&#xA;\end{eqnarray}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$||r - R||$&lt;/span&gt; is the distance between &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; is the contraction coefficient,&#xA;and &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; is the orbital exponent.&#xA;The concrete values for these coefficients and exponents can be obtained from&#xA;the BasisSetExchange website (&lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.basissetexchange.org/&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Next, I write the Bloch sum of the above atomic orbitals as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\text{Na}: \Phi_k (r) =&#xA;e^{-ik R_1} \phi_{\text{1s}} (r, R_1) +&#xA;e^{-ik R_2} \phi_{\text{1s}} (r, R_2) + \cdots +&#xA;e^{-ik R_N} \phi_{\text{1s}} (r, R_N), (3)&#xA;\\&#xA;\text{Cl}: \Psi_k (r) =&#xA;e^{-ik R_1} \psi_{\text{1s}} (r, R_1) +&#xA;e^{-ik R_2} \psi_{\text{1s}} (r, R_2) + \cdots +&#xA;e^{-ik R_N} \psi_{\text{1s}} (r, R_N), (4)&#xA;\end{eqnarray}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is the wavenumber and&#xA;&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of atomic positions considered in the Bloch sum.&lt;/p&gt;&#xA;&lt;p&gt;Finally, I consider the coefficients as the same as&#xA;the linear combination of atomic orbitals (LCAO) for molecules as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\text{NaCl}: \Omega_k (r) = c_\text{Na} \Phi_k (r) + c_\text{Cl} \Psi_k (r), (5)&#xA;\end{eqnarray}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$c_\text{Na}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$c_\text{Cl}$&lt;/span&gt; are the coefficient values in TBA,&#xA;which can be found by minimizing the energy as the same as LCAO.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here, I have a question.&lt;/strong&gt; In the above three processes,&#xA;I know the concrete values of the contraction coefficient&#xA;and orbital exponent in Eqs. (1) and (2) thanks to the BasisSetExchange,&#xA;and also know how to find the coefficient in TBA/LCAO in Eq. (5);&#xA;&lt;strong&gt;however, I do not know the concrete value of the wave number &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;&#xA;in Eqs. (3) and (4) and how to determine it.&lt;/strong&gt;&#xA;Is this &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; value arbitrarily determined (e.g., &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;, 1/2&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;, and 3&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;)?&#xA;For example, in the actual DFT calculation based on TBA,&#xA;do we have the best (or better) &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; value for Na, Cl, and other atoms?&lt;/p&gt;&#xA;&lt;p&gt;(I am already familiar with the LCAO calculation for organic molecules,&#xA;but not familiar with inorganic crystals, so I have the above question.&#xA;The molecular LCAO does not have the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; value in the actual calculation&#xA;and requires only &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;.)&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2022-07-22T09:29:23.537" LastActivityDate="2022-07-24T00:14:15.470" Title="How to determine the concrete value for the wavenumber in tight-binding approximation" Tags="|crystallography|orbitals|tight-binding|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9421" PostTypeId="1" CreationDate="2022-07-22T09:30:53.397" Score="2" ViewCount="710" Body="&lt;p&gt;I work now with larger job files and use the &lt;code&gt;--Link1--&lt;/code&gt; keyword to organize up to 10 jobs in one job file. This works very well for me. But I got a lot of job series with numbered consecutively in the Titel section and the name of the specified chk-files.&lt;/p&gt;&#xA;&lt;p&gt;This is a small sample of my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=x0_ground_low.chk&#xA;%mem=80GB&#xA;%nprocshared=8&#xA;#p opt b3lyp/6-311+g(2d,p) nosymm&#xA;&#xA;low optimization no.x0 ground&#xA;&#xA;0 1&#xA;C         -0.65829        1.17916        0.00108&#xA;C         -1.36344       -0.02375        0.00285&#xA;C          0.73771        1.19337       -0.00082&#xA;C         -0.65909       -1.22650        0.00278&#xA;C          1.43195       -0.01475       -0.00091&#xA;C          0.73888       -1.22664        0.00093&#xA;Cl        -1.53314       -2.71418        0.00498&#xA;Cl        -1.52136        2.66877        0.00121&#xA;O          2.79865       -0.02609       -0.00280&#xA;O          1.44835       -2.39879        0.00087&#xA;H         -2.44987       -0.02276        0.00427&#xA;H          1.26734        2.14102       -0.00216&#xA;H          3.13615        0.88329       -0.00455&#xA;H          0.80881       -3.13311        0.00244&#xA;&#xA;--Link1--&#xA;%oldchk=x0_ground_low.chk&#xA;%chk=x0_ground_high.chk&#xA;%mem=80GB&#xA;%nprocshared=8&#xA;#p opt=(tight,calcfc,recalcfc=3) geom=check scf=qc b3lyp/6-311+g(2d,p) nosymm int=ultrafine&#xA;&#xA;high optimization no.x0 ground&#xA;&#xA;0 1 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So what I am now looking for is to number up automatically &lt;code&gt;x0 to x1, x2 ... xn&lt;/code&gt; in the Titelsection with&#xA;&lt;code&gt;low optimization no.x0&lt;/code&gt; ground and high o&lt;code&gt;ptimization no.x0 ground&lt;/code&gt; and also in the checkpoint files: &lt;code&gt;%chk=x0_ground_low.chk %oldchk=x0_ground_low.chk %chk=x0_ground_high.chk&lt;/code&gt;&#xA;Is it possible to include variables for the x0 like in a bash-script and just change the variable at each file?&#xA;I can not write a bash script because I use slurm in a cluster as management system. So I got my slurm file which opens the .gjf-file from gaussian. So it would be nice just to modify the .gjf-file.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="5" LastEditDate="2023-01-31T21:56:45.380" LastActivityDate="2023-01-31T21:56:45.380" Title="Gaussian Job File with Variables and Link1" Tags="|quantum-chemistry|gaussian|high-performance-computing|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-20T03:28:32.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="9422" PostTypeId="1" CreationDate="2022-07-22T12:18:35.570" Score="3" ViewCount="69" Body="&lt;p&gt;Can anyone tell what happens to the position coordinates of the nearest neighbors when we choose to study supercell of the same material. That remains intact or any changes will be there?&lt;/p&gt;&#xA;&lt;p&gt;For example if we have a cubic lattice then its lattice parameters are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; [1.0, 0.0, 0.0],[0.0, 1.0, 0.0],[0.0, 0.0, 1.0] &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and nearest neighbour coordinates are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; [1,0,0],[0,1,0],[0,0,1],[-1,0,0],[0,-1,0],[0,0,-1]. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If we take 2&lt;em&gt;2&lt;/em&gt;2 supercell of it then the position coordinates will be changed or remains same?&lt;/p&gt;&#xA;" OwnerUserId="5492" LastEditorUserId="5" LastEditDate="2022-07-22T19:56:07.493" LastActivityDate="2022-07-23T12:13:02.907" Title="What happens to the position coordinates of the nearest neighbors in supercell studies?" Tags="|density-functional-theory|condensed-matter|solid-state-physics|supercell|doping|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9423" PostTypeId="2" ParentId="9399" CreationDate="2022-07-22T18:00:35.067" Score="2" Body="&lt;p&gt;The STO-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;G basis sets were one of the first Gaussian basis sets. They were proposed in &lt;a href=&quot;https://doi.org/10.1063/1.1672392&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 51, 2657 (1969)&lt;/a&gt;. The idea was merely to formulate Gaussian basis versions of a pre-existing minimal Slater-type orbital (STO) basis set that had been optimized for molecules.&lt;/p&gt;&#xA;&lt;p&gt;The biggest issue with the STO-&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;G basis sets is that they are minimal basis sets that are known to be unreliable for chemistry. Another big issue is that the naming is misleading: STO-&lt;span class=&quot;math-container&quot;&gt;$\infty$&lt;/span&gt;G would converge to the original minimal STO basis. Both of these features originate from the obsolete nature of the basis set.&lt;/p&gt;&#xA;&lt;p&gt;Loads of advances in basis set design have been taken since the days of Pople, Hehre and coworkers. For instance, Davidson and Feller wrote almost 40 years ago&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The first molecular calculations used a minimum set&#xA;of STO's, with exponents chosen by Slater’s rules.&#xA;Later, exponents were chosen to minimize the SCF&#xA;energy of the atom.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;in &lt;a href=&quot;https://doi.org/10.1021/cr00074a002&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Rev. 86, 681 (1986)&lt;/a&gt;. Modern basis sets are indeed typically designed by minimization of energy for atoms and/or molecules, and come in systematic families ranging from small, split-valence basis sets for qualitative calculations to large polarized multiple-&lt;span class=&quot;math-container&quot;&gt;$\zeta$&lt;/span&gt; basis sets that afford quantitative accuracy. Several recent reviews of basis sets can be found in the literature; see e.g. &lt;a href=&quot;https://doi.org/10.1002/qua.24355&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hill, Int. J. Quantum Chem. 113, 21 (2012)&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1002/wcms.1123&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jensen, WIREs CMS 3, 273 (2013)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2022-07-22T19:53:43.317" LastActivityDate="2022-07-22T19:53:43.317" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9424" PostTypeId="1" CreationDate="2022-07-22T21:13:00.867" Score="6" ViewCount="412" Body="&lt;p&gt;I have a problem with a Transiesta calculation, I could not get the transmission (TBT calculation) as well DOS and current. I perform the I-V for graphene nanoribbons (electrode containing 20 atom , and al device 140 atoms). Just to validate at first the calculation for 0 voltage. So&#xA;For the Transiesta calculation, the running gives me a not-perfect electrode (as you see in Figure). I refer to the Siesta 4.1 b4 manual and I add the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TS.Elecs.Neglect.Principal&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;also this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; TBT.Elecs.Coord.EPS 0.02 Ang&#xA; TS.Elecs.Coord.EPS 0.02 Ang&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;at now it doesnt work and it still give me :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Electrode connectivity is not perfect, refer to the manual for achieving a perfect electrode.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jJFzW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jJFzW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Stopping Program from Node:    0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XQkcU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XQkcU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="887" LastEditDate="2024-03-08T11:34:27.883" LastActivityDate="2024-03-08T11:36:05.600" Title="TBtrans/Transiesta, error: &quot;connectivity is not perfect&quot;" Tags="|density-functional-theory|siesta|transport|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9425" PostTypeId="2" ParentId="9241" CreationDate="2022-07-23T05:46:05.633" Score="4" Body="&lt;p&gt;There are a couple of levels of parallelism:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;For big systems the general rule of thumb is that the diagonalization is the bottleneck for the Siesta calculation. Here, only one flag exists for optimizing the parallel efficiency:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;Diag.ParallelOverK true&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By default, Siesta uses all cores to diagonalize every k-point. However, if the system is &amp;quot;small&amp;quot;, but you have many k-points, say &lt;span class=&quot;math-container&quot;&gt;$N_k&amp;gt;N_{processors}$&lt;/span&gt;, then using &lt;code&gt;Diag.ParallelOverK&lt;/code&gt; might improve efficiency significantly.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Another part is the grid, generally this is very well parallelised and there is not much to gain, the defaults are standardly good.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2022-11-18T21:19:34.003" LastActivityDate="2022-11-18T21:19:34.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9426" PostTypeId="2" ParentId="9422" CreationDate="2022-07-23T06:24:07.360" Score="1" Body="&lt;p&gt;In solid-state calculations, DFT code does not know whether you give it a crystalline unit cell or a supercell. Instead, it treats every input structure as a &amp;quot;unit cell&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;So my answer is &amp;quot;remains same&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="1688" LastActivityDate="2022-07-23T06:24:07.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9427" PostTypeId="2" ParentId="9422" CreationDate="2022-07-23T11:13:19.637" Score="3" Body="&lt;p&gt;DFT calculations based on a supercell method utilize the periodicity of a perfect, infinite lattice by imposing periodic boundary conditions onto the wavefunction of the system (Bloch's theorem). In this approach all calculations must be performed on a periodic system, even when the periodicity is superficial. Thus, for example, a crystal surface must be represented by a finite-length slab. Similarly, to study molecules it is necessary to assume that they are in a box and treat them as periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;The main advantage of imposing periodic boundary conditions relates to Bloch's theorem, which states that in a periodic system each electronic wavefunction &lt;span class=&quot;math-container&quot;&gt;$\psi_{n, k} (\pmb{r})$&lt;/span&gt; can be written as a product of a cell-periodic part &lt;span class=&quot;math-container&quot;&gt;$u(\pmb{r})$&lt;/span&gt; and a wavelike phase factor &lt;span class=&quot;math-container&quot;&gt;$e^{ik\cdot\pmb{r}}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{n, k} (\pmb{r}) = u(\pmb{r}) \:e^{ik\cdot\pmb{r}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus there are always an infinite array of periodic units in the background of such simulations. When simulating a single unit cell, calculations are explicitly performed on the electrons and ions contained within this unit cell. Nontheless, the periodic images identical to your cell are always accounted for implicitly. That is why in a study of a single defect, for example, it is essential to introduce enough separation between artificial images (i.e., build a big supercell) of such nonperiodic objects to ensure that there is no appreciable interaction between them. The situation is similar for surface calculations that are carried out in a slab geometry. The vacuum layer should be sufficiently thick to eliminate artificial interactions between the slabs.&lt;/p&gt;&#xA;&lt;p&gt;To answer your question in short, physical properties calculated from a unit cell and any supercell size built from this unit cell are exactly the same. &lt;strong&gt;The position coordinates remain the same.&lt;/strong&gt; Of course, this statement is no longer correct as soon as you introduce a defect (e.g. Doping) into your supercell.&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="7" LastEditDate="2022-07-23T12:13:02.907" LastActivityDate="2022-07-23T12:13:02.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9428" PostTypeId="2" ParentId="9410" CreationDate="2022-07-23T18:01:57.287" Score="5" Body="&lt;p&gt;You can evaluate molecular orbitals on a grid by first evaluating the AOs on the grid with&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ao = mol.eval_gto('GTOval', coords)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and then contracting with the orbital coefficients&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \psi_{i\sigma} = \sum_\alpha C^\sigma_{i\alpha} \chi_\alpha $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't remember off-hand which way the indices are in PySCF, but this should be easy to figure out. The code should look something like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mo = lib.einsum('gi,xij-&amp;gt;xgj', ao, mf.mo_coeff)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;addendum regarding edit above:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ao vals shape:  (79368, 46)&#xA;mo vals shape:  (2, 79368, 46)&#xA;mo coeff shape:  (2, 46, 46)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This means you have 79368 grid points, 46 basis functions, and 46 spatial molecular orbitals (in general you may have fewer molecular orbitals than atomic orbitals as the atomic orbital basis set may have linear dependencies). For unrestricted wave functions, PySCF uses arrays with additional indices for the spin; I believe [0] is spin-up and [1] is spin-down.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-08-14T21:06:14.727" LastActivityDate="2022-08-14T21:06:14.727" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9429" PostTypeId="2" ParentId="9420" CreationDate="2022-07-24T00:14:15.470" Score="4" Body="&lt;p&gt;It depends what you are trying to calculate. The possible k points that you care about are those in the first Brillouin zone. You can find a definition of that in a solid state physics textbook. In 1D it will be between pi/a and -pi/a. In 1D you don’t have to worry about a path through the Brillouin zone in the same way that you would in higher dimensions (since there’s only one path possible), so you should just sample the points from -pi/a to pi/a uniformly.&lt;/p&gt;&#xA;&lt;p&gt;So what you want to do is plug in values of k for k in the range -pi/a to pi/a, and then if you have a dense enough number of points, then you will see something that looks like the bands in your system. You can look at the part of solid state physics textbooks that do tight binding in 1D to see the sort of plot that you should expect to get. In textbook examples, they usually pick ones that are analytically solvable with simple functional forms, so you just get the energy as a function of k, and then you can plot it in Mathematica or something like you would with any other function, but if you instead have more complicated functional forms that you might get out of an actual tight binding calculation with more complex forms for the orbitals where they have a bunch of coefficients, you can instead just plug in values for k on some regular interval to generate your plot.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-07-24T00:14:15.470" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9430" PostTypeId="1" CreationDate="2022-07-24T03:03:31.607" Score="3" ViewCount="105" Body="&lt;p&gt;In this paper (e.g. doi:10.1021/cs500093h and other applied QM/MM studies), it is demonstrated several transition states, intermediates, and products of given set of biomolecules (several residues, metal ions, and its substrates). What makes me it is interesting is that they depicted carefully the lose and gain of the atoms on each molecules. I have seen on some places that the showed bonds can be reproduced from some molecular docking softwares (e.g. Schrodinger Maestro, etc.) but it would be also interesting if a software could also draw the electron flow arrows (reaction mechanism) for each states. I have seen some research papers about docking studies before but they only depicted the bonds without giving any information of whether an atom had newly made or unreactive (the paper I cited clearly showed the lose of hydrogen and the bond forming on intermediate state).&lt;/p&gt;&#xA;&lt;p&gt;How do they model the states? Is it that we have to manually draw the molecules on each states and put the protonated/deprotonated and dissociated/bonded forms combinatorically for the states and we evaluate the energy for each of these scenarios? Or the softwares could also make and break those bonds automatically and showed the energy for each of them? Which software? On the cited paper, I can not find any specific line that mentioning this and I am curious with the line on the paper, stated &amp;quot;&lt;em&gt;the QM/MM boundaries crossed carbon-carbon bonds, and hydrogen atoms were used as “link” atoms&lt;/em&gt;&amp;quot;. Is this one?&lt;/p&gt;&#xA;" OwnerUserId="5771" LastEditorUserId="5" LastEditDate="2022-07-24T04:28:15.740" LastActivityDate="2022-07-24T07:45:19.570" Title="How to model TS for given a small biomolecular system?" Tags="|software-recommendations|qmmm|reaction-mechanism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9431" PostTypeId="1" CreationDate="2022-07-24T06:10:31.230" Score="5" ViewCount="123" Body="&lt;p&gt;I have seen some research papers on molecular docking studies using some conformer-generating softwares like CORINA, OMEGA, etc. and they used these softwares to generate conformers of a molecule and they used these conformers for the later docking. Is this really necessary? The docking programs will calculate and remodel the conformers again later though. I was thinking, perhaps, if we dock these conformers but the docking programs have to only &lt;em&gt;fit&lt;/em&gt; (evaluate), not doing any change to the structure of the molecule. Can AutoDock or any other software be limited to perform this step only?&lt;/p&gt;&#xA;" OwnerUserId="5771" LastActivityDate="2023-06-26T20:22:45.167" Title="Is generating conformers necessary for molecular docking studies?" Tags="|software-recommendations|docking|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9432" PostTypeId="2" ParentId="9430" CreationDate="2022-07-24T07:45:19.570" Score="3" Body="&lt;p&gt;So let me summarize your questions: (1) is it possible for a software to automatically draw the electron flow arrows? (2) must the user add and remove the atoms manually, when modelling a TS?&lt;/p&gt;&#xA;&lt;p&gt;The answer to (1): In principle yes, but usually a quantum chemistry program only outputs (a) the bond order between each pair of atoms, and (b) the charge of each atom. When you have these information for the reactant(s), the TS and the product(s), you know where the electrons are before, during, and after the reaction. You can then trivially draw the electron flow arrows. (With stepwise concerted mechanisms, you may need to calculate the bond orders and atomic charges of additional structures along the IRC in order to correctly draw the arrows, but this is a minor technicality.) Nevertheless, I'm not aware of any software that can do the last arrow-drawing step automatically, partly because it is easy enough for humans to do.&lt;/p&gt;&#xA;&lt;p&gt;The answer to (2): Sometimes, but not always. The most straightforward, although not very robust, approach is to come up with a guess of the TS structure and then optimize it with a quantum chemistry program. This is prone to non-convergence unless you have at least some chemical intuition about how a TS should look like. A second class of methods (e.g. QST2, NEB) is to automatically find the TS through two user-supplied structures, namely the reactant complex and the product complex; these can be made more robust if the user can also specify a rough guess of the TS structure (as in the QST3 method). Still another class of methods (e.g. GRRM) only require that you supply a reactant structure, and will automatically find all possible reactions from this reactant, as well as the associated transition states; however this is extremely costly, since the program has no idea about which reactions you are mostly interested in, so most of the time are wasted in finding totally uninteresting TSs, like the TSs of methyl rotations.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-07-24T07:45:19.570" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9433" PostTypeId="2" ParentId="9431" CreationDate="2022-07-24T14:30:10.967" Score="1" Body="&lt;p&gt;Autodock vina is a docking software that doesn't need to manually add every conformers of the ligand because they will be generated on the basis of rotable bonds of the ligand.&lt;/p&gt;&#xA;" OwnerUserId="982" LastActivityDate="2022-07-24T14:30:10.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9434" PostTypeId="1" CreationDate="2022-07-25T02:02:41.787" Score="4" ViewCount="86" Body="&lt;p&gt;I'm planning to analyse an extremely complex molecule on NWChem(it's practically the only free computational package available package here, and the molecule is so large that running a seemingly simple HF/STO-3G calculation the Gaussian module on e.g. the WebMO Demo server would certainly go way past the 30s limit on the Demo), via DFT, using the Karlsruhe basis sets and subsequent complete basis set(CBS) extrapolation.&lt;/p&gt;&#xA;&lt;p&gt;After not being able to find any CBS methods (aside from the one using MP2/aug-cc-CBS, which is much too expensive for a gigantic molecule) implemented in the NWChem user manual, I decided to look for a way to extrapolate to the CBS limit by hand.&lt;/p&gt;&#xA;&lt;p&gt;A simple Google search led me to a page talking about how cc-pVNZ SCF (resp. corr) energies converge at a speed of O(exp(-a√n))(resp. O(z^(-n))), a(resp. z) being fixed constants, but I could not find any such equation, to solve by hand, for the def2 basis sets.&lt;/p&gt;&#xA;&lt;p&gt;The only extrapolation I could do by hand at the moment is the one that assumes an O(exp(-b*n)) convergence with both the b and the constant implicit in the big-O expression being unknown. This requires a  three-point extrapolation(I know what I'm talking about, I'm literally majoring in mathematics); since the def2 basis sets are (def2-)SVP, TZVPP, and QZVPP, this requires including a part of the def2-SVP energies in the extrapolation, a thing that is not favored in QC(N.B. the automatic CBS extrapolation that ORCA says it supports uses a two-point extrapolation, which would mean that the constant b, or its equivalent thereof should the equation be slightly different from what is written above, is explicitly known).&lt;/p&gt;&#xA;&lt;p&gt;So I'm stuck at a dead end, unless I get to know how to extrapolate NWChem results to the CBS limit(even if I end up having to export the NWChem results and put them in a seperate package to do it- one already needs to do it that way to compute NBO's via NWChem IIRC), or (more simply) find an explicit systematic convergence rate for the def2 basis sets. What should I do?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-07-25T02:02:41.787" Title="How to perform a DFT/def2-PPCBS extrapolation on NWChem" Tags="|density-functional-theory|computational-chemistry|numerical-convergence|nwchem|basis-set-superposition-error|" AnswerCount="0" CommentCount="3" ClosedDate="2023-02-01T03:44:59.493" ContentLicense="CC BY-SA 4.0" />
  <row Id="9435" PostTypeId="1" CreationDate="2022-07-25T10:27:57.673" Score="4" ViewCount="142" Body="&lt;p&gt;I wish to explore the possibility of performing free radical based DFT calculations over my Fe(110) slab.&lt;/p&gt;&#xA;&lt;p&gt;I have gone over the internet to see if there is any possibility of carrying this via Quantum Espresso. It would be helpful if I could receive any suggestions as to whether I could achieve this computationally. If so, I would appreciate it if anyone could also explain it with respect to an Quantum Espresso INPUT file.&lt;/p&gt;&#xA;&lt;p&gt;Cheers!&lt;/p&gt;&#xA;" OwnerUserId="5378" LastActivityDate="2022-08-26T06:01:00.123" Title="Free radical based DFT calculations using Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9437" PostTypeId="2" ParentId="9396" CreationDate="2022-07-25T11:50:28.210" Score="2" Body="&lt;p&gt;Multi-scale modelling refers to the modelling of a physical problems which involves the description of different time or space-scales. Think for example to the modelling of nonequilibrium dynamics of electrons and ions initiated by ultra-short laser pulses in condensed-matter.&lt;/p&gt;&#xA;&lt;p&gt;At first a lase pulse of few femto-seconds (fs) may excite electrons in a nonequilibrium configuration. There will be a coherent electron dynamics on the time scale of few hundreds of fs. Coherences will eventually de-phase leading to non-coherent and non-thermal electron population dynamics. Electrons will reach a quasi-equilibrium statistical distribution at very high temperature and, on an even longer time-scale cool down. Due to the interaction with the lattice, also the phonons will evolve, in general on a longer time-scale compared to the electrons. There could be coherent phonons at first and later non-termal phonon distributions, phonon heating and cooling. On even longer time scales both electron diffusion may take place, as well as structural distortion of the material. See here for more info: &lt;a href=&quot;https://www.nature.com/articles/nmat767&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nature Materials&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;While a fully quantum mechanical approach could describe all these phenomena, the approach would be non feasible for all the phenomena (and also not needed). The fully quantum description would be useful to capture the initial coherent dynamics, Boltzmann rate equations to capture the non thermal occupations, effective temperature models to describe the cooling processes, etc ...&lt;/p&gt;&#xA;&lt;p&gt;However each of the above mentioned approaches works on a specific aspect and on a different time scale. This means that there is a time (and space) scale mismatch. Putting together different kind of simulations is what I would call a &amp;quot;many scales&amp;quot; approach, i.e. you kind of partition the physical process in sub-problems. What a real &amp;quot;multi scales&amp;quot; approach would do instead, is to somehow interface the different approaches and enable one method to continue from the output of the previous. A &amp;quot;multi scales&amp;quot; approach would enable &amp;quot;scale bridging&amp;quot; physical problems with a &amp;quot;scale mismatch&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="5685" LastEditorUserId="5685" LastEditDate="2022-07-26T08:28:40.407" LastActivityDate="2022-07-26T08:28:40.407" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9438" PostTypeId="2" ParentId="9396" CreationDate="2022-07-25T15:08:31.167" Score="0" Body="&lt;p&gt;&lt;strong&gt;Scale-mismatch&lt;/strong&gt;, more appropriately, &lt;strong&gt;Scale-gap&lt;/strong&gt;, is the difference between the scale at which chemical or physical laws are available and the scales at which we want to study a phenomenon.&lt;/p&gt;&#xA;&lt;p&gt;This gap can be present either on the temporal scale or spatial scale.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kc67G.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kc67G.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;Image source: &lt;a href=&quot;https://www.mdpi.com/1422-0067/19/11/3401/htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.mdpi.com/1422-0067/19/11/3401/htm&lt;/a&gt;&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For instance&lt;/strong&gt;, in the above image, protein-folding takes place at the &amp;quot;seconds&amp;quot; time scale. However, the chemical or physical laws governing protein-folding occur at the femtosecond or picoseconds scale.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, this is an example of a temporal scale gap.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2022-07-25T15:14:52.030" LastActivityDate="2022-07-25T15:14:52.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9440" PostTypeId="1" CreationDate="2022-07-26T06:09:54.933" Score="4" ViewCount="226" Body="&lt;p&gt;I am trying to plot 3D band structure of my system of interest. I have used Quantum Espresso software for calculating the band structure and plotted 2D band diagram. But from here I am unable to understand how to plot 3D band structure i.e. E vs (kx, ky) plot. Can anyone please suggest me how to do this? Is there any visualizer to do this automatically from quantum espresso output file?&lt;/p&gt;&#xA;" OwnerUserId="5787" LastActivityDate="2022-07-27T01:59:17.710" Title="3D band structure plot" Tags="|density-functional-theory|quantum-espresso|band-structure|2d-lattice|periodic-system|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9441" PostTypeId="1" AcceptedAnswerId="9442" CreationDate="2022-07-26T15:27:21.220" Score="6" ViewCount="239" Body="&lt;p&gt;Suppose we have a parametrized molecular Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H(R)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; are the nuclear coordinates. If we let &lt;span class=&quot;math-container&quot;&gt;$B(R)$&lt;/span&gt; be some chosen atomic basis set (like STO-3G) centred at &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, then using &lt;span class=&quot;math-container&quot;&gt;$B(R)$&lt;/span&gt;, we let &lt;span class=&quot;math-container&quot;&gt;$C(R)$&lt;/span&gt; denote the transition matrix from atomic to molecular orbitals at &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In general, there are many different choices for &lt;span class=&quot;math-container&quot;&gt;$C(R)$&lt;/span&gt; at a given &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, as HF can converge to different unique solutions. However, I want &lt;span class=&quot;math-container&quot;&gt;$C(R)$&lt;/span&gt; to vary continuously over some range of &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;. In general, is it possible to enforce this condition when performing Hartree-Fock? If so, how?&lt;/p&gt;&#xA;&lt;p&gt;I tried starting at a set of parameters &lt;span class=&quot;math-container&quot;&gt;$R_0$&lt;/span&gt;, computed &lt;span class=&quot;math-container&quot;&gt;$C(R_0)$&lt;/span&gt;, and then computed &lt;span class=&quot;math-container&quot;&gt;$C(R_0 + \Delta)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C(R_0 + 2\Delta), ...$&lt;/span&gt; iteratively by using the density matrix yielded by the previous Hartree-Fock step, but this didn't seem to work: I'm still getting some large jump discontinuities in &lt;span class=&quot;math-container&quot;&gt;$C(R)$&lt;/span&gt; at certain values of &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3693" LastActivityDate="2022-07-26T19:28:40.900" Title="Continuously-varying Hartree-Fock transition matrix?" Tags="|hartree-fock|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9442" PostTypeId="2" ParentId="9441" CreationDate="2022-07-26T19:28:40.900" Score="7" Body="&lt;p&gt;First, notes on terminology: &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; are molecular orbital coefficients, not transition matrices. In general one has many nuclei so you have a set of nuclear coordinates &lt;span class=&quot;math-container&quot;&gt;$\{{\bf R}_A\}$&lt;/span&gt; instead of a single vector &lt;span class=&quot;math-container&quot;&gt;${\bf R}$&lt;/span&gt;; atomic basis sets are typically (but not always!) centered on the individual atoms &lt;span class=&quot;math-container&quot;&gt;${\bf R}_A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The actual question does not in fact depend on the basis set at all; instead, the question is whether the Hartree-Fock orbitals are continuous across geometries.&#xA;The answer is negative: some solutions disappear when the molecular geometry is changed.&lt;/p&gt;&#xA;&lt;p&gt;Tracking the solutions individually can be done e.g. using holomorphic Hartree-Fock theory, which is reviewed in e.g. &lt;a href=&quot;https://manual.q-chem.com/5.2/Ch4.S9.SS4.html&quot; rel=&quot;noreferrer&quot;&gt;the Q-Chem manual&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-07-26T19:28:40.900" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9443" PostTypeId="2" ParentId="9431" CreationDate="2022-07-26T21:00:53.673" Score="4" Body="&lt;p&gt;No, you don't need to generate a library of conformers before docking.&lt;/p&gt;&#xA;&lt;p&gt;I personally advise again that, except if you have a chemical/biological justification to use your own library.&lt;/p&gt;&#xA;&lt;p&gt;One of the strength that a package has is the method it uses to search for the complex best pose.&lt;/p&gt;&#xA;&lt;p&gt;Software like GOLD used genetic algorithm to generate its library whereas GLIDE make use of systematic search, for example.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-07-26T21:00:53.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9444" PostTypeId="2" ParentId="9440" CreationDate="2022-07-27T01:59:17.710" Score="2" Body="&lt;p&gt;Usually people just do it by picking a path through the Brillouin zone and then plotting it in one dimension. You can use the seekpath or pymatgen (I think pymatgen has this) tools to generate paths through k space that connect high symmetry points, or you can just look at textbooks or even the Wikipedia page on the Brillouin zone to see what high symmetry points are typically used for different structure types. If you see a band structure of a bulk solid in a textbook or paper, plotting the band energies along high symmetry paths is the most common way to represent it visually. The density of states can also be a useful way to visualize which energy levels are available in your system and how many electrons are in a given energy window.&lt;/p&gt;&#xA;&lt;p&gt;You can also make it a 3D plot where you have the x and y axes corresponding to slices of the Brillouin zone and the z axis is the energy; this is the sort of plot you might have generated for 2D materials. Such a plot can in principle also be made for 3D materials by just fixing a k point along the third direction. This approach might be useful for layered solids, for example.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-07-27T01:59:17.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9445" PostTypeId="2" ParentId="9405" CreationDate="2022-07-27T05:50:21.147" Score="1" Body="&lt;p&gt;If you anticipate having unpaired electrons, you typically want to initialize those atomic species to have a non-zero magnetization. In some systems, you can initialize the spins to all be 0 and you will still end up with a non-zero magnetization, but in many there’s a local minimum where all of the spins are zero, so if you don’t initialize the spins then you will end up stuck in a state with no net magnetization.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-07-27T05:50:21.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9446" PostTypeId="2" ParentId="9435" CreationDate="2022-07-27T05:56:23.170" Score="2" Body="&lt;p&gt;You can certainly make a slab of Fe and put a molecule over it and see what happens. This sort of calculation is done often; I haven’t seen it done with free radicals, but there’s no reason you can’t try. If you have a charged molecule, like you mentioned in another question that you asked, then you might have to think about what sized supercell might be needed to eliminate spurious electrostatic interactions between periodic images, but in principle there shouldn’t be much of a problem with setting up a system with a charged molecule near a slab.&lt;/p&gt;&#xA;&lt;p&gt;One caveat for all of this, is that while you can set up the calculation and relax the structure, there’s no guarantee that the results will be accurate. Your choice of things like supercell size and exchange-correlation functional might end up being important, and it would be good to find papers on other slab calculations people have done to see what sorts of choices are typical, and how accurate you might hope your calculation can be.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-07-27T05:56:23.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9447" PostTypeId="1" CreationDate="2022-07-27T07:05:53.700" Score="1" ViewCount="93" Body="&lt;p&gt;I'm trying to analyse an extremely complex molecule's electron affinity; the molecule is much too large to perform post-HF methods on, meaning that open-shell DFT is the only option available. While I was searching in the literature for the functional that would be the most similar one, w.r.t the exact XC, for my molecule, I began to wonder if any modified versions of Kohn-Sham DFT and the exact XC functional could, at least theoretically, exactly describe the ground state densities of open-shell molecules, just like how they do for closed-shell molecules.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- given an open-shell molecule, is there any such modification that is theoretically exact, i.e. ignoring &amp;quot;subtle&amp;quot; facts like how the exact closed-shell XC functional is unknown?&lt;/p&gt;&#xA;&lt;p&gt;P.S. I'm asking the same question for both nonrelativistic and relativistic calculations.&lt;/p&gt;&#xA;&lt;p&gt;P.S. 2: I'm not asking for the explicit exact functional- I'm asking whether such an exact potential theoretically exists at all.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-07-27T10:24:25.763" LastActivityDate="2022-07-27T10:24:25.763" Title="Do there exist a theoretically exact DFT method and XC functional, possibly modified from those for closed-shell molecules, for open-shell molecules?" Tags="|density-functional-theory|spin|exchange-correlation|" AnswerCount="0" CommentCount="4" ClosedDate="2023-02-01T03:45:58.797" ContentLicense="CC BY-SA 4.0" />
  <row Id="9448" PostTypeId="1" AcceptedAnswerId="9483" CreationDate="2022-07-27T07:06:09.683" Score="9" ViewCount="634" Body="&lt;p&gt;This term pops up through out Hartree-Fock and DFT. Does this term have any physical significance to actual(real) system or it is a mathematical by-product?&lt;/p&gt;&#xA;" OwnerUserId="5619" LastActivityDate="2023-05-30T09:03:01.750" Title="What is the physical meaning of the term &quot;non-local interaction&quot;?" Tags="|density-functional-theory|hartree-fock|electron-correlation|exchange-correlation|" AnswerCount="2" CommentCount="2" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9449" PostTypeId="1" CreationDate="2022-07-26T01:49:03.467" Score="5" ViewCount="173" Body="&lt;p&gt;I have enumerated a large set of carbocations all of the formula C10H17+, all of course with differing structures. I know there are many different approaches of computing similarity between molecules, however most work best for molecules with differing formulas. I was wondering if anyone knew what the best method would be to compute similarity of different molecules of the same formula. I am thinking of using some sort of graph based method, but I wanted some advice/guidance on what people may think would be the optimal approach if possible.&lt;/p&gt;&#xA;&lt;p&gt;I am working on a paper in which I am looking to define some sort of pathway space for the formation of terpenes starting from their carbocation precursors. Eventually I want to build a model that will predict which molecules are most likely to be the next intermediate in a cyclisation reaction, given a certain carbocation as input. I want to start by computing the similarity between the carbocations in some way.&lt;/p&gt;&#xA;" OwnerUserId="5795" OwnerDisplayName="BanAckerman" LastActivityDate="2022-07-27T19:10:45.903" Title="What is the best way to measure similarity between molecules of the same formula?" Tags="|cheminformatics|machine-learning|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9450" PostTypeId="1" CreationDate="2022-07-27T16:50:41.300" Score="4" ViewCount="122" Body="&lt;p&gt;I want to run MD simulations of a polymer, but I want to start from different physical conformations. My question is, how do I obtain these conformations? Is there a software which performs this?&lt;/p&gt;&#xA;&lt;p&gt;Let's say I want to run a MD simulation for a polymer in an &amp;quot;extended&amp;quot; state and from a &amp;quot;collapsed&amp;quot; state. I obtain PDBs from CHARMM, but they are always in the extended state. How do I cleanly obtain a collapsed state, using something like Rotational Isomeric State model, or something along those lines.&lt;/p&gt;&#xA;&lt;p&gt;Any advice you have would be appreciated!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2022-09-23T22:18:31.410" LastActivityDate="2022-10-01T11:45:38.427" Title="How to generate a polymer in different conformations?" Tags="|molecular-dynamics|polymers|structure|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9451" PostTypeId="2" ParentId="9449" CreationDate="2022-07-27T19:10:45.903" Score="8" Body="&lt;h2&gt;tldr; The most common approach is to use fingerprints and compute the Tanimoto similarity&lt;/h2&gt;&#xA;&lt;p&gt;There are a variety of ways to compute &lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_similarity&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;molecular similarity&amp;quot;&lt;/a&gt; but the most common approach is to generate molecular fingerprints (e.g., ECFP4 or similar) and then use the Tanimoto coefficient to determine similarity.&lt;/p&gt;&#xA;&lt;p&gt;For an example of doing this in RDKit, you can adapt &lt;a href=&quot;https://stackoverflow.com/questions/51681659/how-to-use-rdkit-to-calculte-molecular-fingerprint-and-similarity-of-a-list-of-s&quot;&gt;code from Stack Overflow&lt;/a&gt; or the &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#topological-fingerprints&quot; rel=&quot;noreferrer&quot;&gt;RDKit manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Multiple reviews have considered how appropriate this method including:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1186/s13321-015-0069-3&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?&amp;quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/ci300261r&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets&amp;quot;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For your particular case, it's possible you can come up with a custom fingerprint that encodes the graph, but the ECFP4 / ECFP6 / Morgan fingerprints do a pretty good job of encoding atom environments.&lt;/p&gt;&#xA;&lt;p&gt;Even if you eventually use a different metric, it's probably a good place to start.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-07-27T19:10:45.903" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9452" PostTypeId="1" CreationDate="2022-07-21T03:03:17.770" Score="5" ViewCount="107" Body="&lt;p&gt;I have been learning some basics of molpro and quantum chemistry, however I am deeply confused now.&lt;/p&gt;&#xA;&lt;p&gt;As a very simple example, I want to compute the energy of a carbon atom using D2h group&lt;/p&gt;&#xA;&lt;p&gt;For its ground state, if I give this input:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;occ,2,1,1,0,0,0,0,0  closed,1,0,0,0,0,0,0,0  wf,6,4,2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The reason why I used this input is that I want to compute a specific electron configuration which  has one alpha electron in the 2px orbital and the other alpha electron in 2py&lt;/p&gt;&#xA;&lt;p&gt;And my understanding for this input text is that:&lt;/p&gt;&#xA;&lt;p&gt;2 Ag irreps (for 1s and 2s orbital) and 1 B3u (for 2px) and 1 B2u(for 2py), then the total symetry is B3u*B2u=B3g which coresponds to the number 4 in my WF input, both electrons are spin-up so S=2 for WF input&lt;/p&gt;&#xA;&lt;p&gt;Is this the correct way to do it?&#xA;Following this thought I changed my input to&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;occ,2,0,1,0,1,0,0,0  closed,1,0,0,0,0,0,0,0  wf,6,7,2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;occ,2,1,0,0,1,0,0,0  closed,1,0,0,0,0,0,0,0  wf,6,6,2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;for the configuration where the 2 aplha electrons are in 2py+2pz and 2px+2pz orbitals.&lt;/p&gt;&#xA;&lt;p&gt;These 3 inputs actually returned me exactly the same energy which makes sense to me if I think in the way that B1g B2g and B3g should be the same for a single atom because it doesn't matter how I pick my x y and z for a sphere.&lt;/p&gt;&#xA;&lt;p&gt;However then i tried have those 2 electrons paird in just one orbitals, then there will be 3 possible configurations which are just a pair of electrons in one of the three p orbitals. Here I am confused, beacuse if I think like that there is no difference which axis I should call it as my z axis (as in there is no difference of x y and z axis in the case of an atom) then then the px/pz/pz should give me the same value of energy, which it is the case what molpro tells me, but when we write out the term symbol shouldn't that be like when the electrons are both in px or py orbital then the term is 1D, and when the electrons are both in pz then it is a 1S term? According to the energy level of carbon, 1D and 1S should not be have the same energy, so there is a conflict obviously, what did I miss here? I am pretty sure that I was not using the software in a correct way, but what should be the rigorous way of specifying a electron configuration in molpro?&lt;/p&gt;&#xA;" OwnerUserId="5805" OwnerDisplayName="ZHIBO LIU" LastEditorUserId="5" LastEditDate="2022-07-28T13:54:42.180" LastActivityDate="2022-07-28T13:54:42.180" Title="Compute the energy of carbon atom with Molpro" Tags="|software|quantum-chemistry|molpro|" AnswerCount="0" CommentCount="7" ClosedDate="2023-02-01T03:49:03.690" ContentLicense="CC BY-SA 4.0" />
  <row Id="9453" PostTypeId="2" ParentId="9295" CreationDate="2022-07-28T07:18:38.400" Score="1" Body="&lt;p&gt;Using ASE you can do this simply. Take a look this link: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html?highlight=surfa&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html?highlight=surfa&lt;/a&gt;&#xA;Here you can build common surfaces as well as root surfaces.&lt;/p&gt;&#xA;" OwnerUserId="5787" LastActivityDate="2022-07-28T07:18:38.400" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9454" PostTypeId="2" ParentId="8930" CreationDate="2022-07-28T16:33:08.960" Score="4" Body="&lt;p&gt;I don't know of any simpler methods.&#xA;Heuristic methods such as Neural Networks are likely your better option if you wish to actually reconstruct the original molecule.&lt;/p&gt;&#xA;&lt;p&gt;Keep in mind that an active bit in one position doesn't necessarily encode only one information.&#xA;If you want that to happen in order to have a more easily interpretable model you should use something like structural key fingerprints or molecular descriptors.&#xA;In hashed fingerprints you might have &amp;quot;bit collision&amp;quot;, this means that two different structural features might activate the same bit.&#xA;Moreover, one feature might activate more than one bit.&lt;/p&gt;&#xA;&lt;p&gt;Since you just want to understand what one single bit represents, if you only need to do this on a few bits you could do the following:&#xA;Take a few molecules that have that bit enabled and manually calculate the fingerprint identifiers up to the hashing point.&#xA;Take note of which substructures are associated to each identifier.&#xA;Follow the hashing algorithm and understand which bits get activated by each identifier.&#xA;To simplify the decoding of the hashing, you could run the hashing function on the set of identifiers, removing one identifier at a time until you find the one that activates that particular bit.&#xA;Since there could be bit collision you might have to remove couples of identifiers and so on.&lt;/p&gt;&#xA;&lt;p&gt;You need to do this with several (or all) molecules with that bit active, in order to identify all substructures that activate it.&lt;/p&gt;&#xA;" OwnerUserId="4376" LastActivityDate="2022-07-28T16:33:08.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9455" PostTypeId="1" CreationDate="2022-07-28T22:35:52.930" Score="2" ViewCount="906" Body="&lt;p&gt;I have a range of systems consisting of multiple peptide chains, some of which are one residue (i.e. single amino acids), which I'd like to analyse using molecular dynamics and AMBER-flavour forcefields. Each peptide fragment is a connected chain with unique chain IDs, separated by TER records.&lt;/p&gt;&#xA;&lt;p&gt;Is there a scripted or automated tool out there to add neutral terminal caps - e.g. n-methyl (NME) and methyl-acetate (ACE)?&lt;/p&gt;&#xA;&lt;p&gt;Some options that work well but don't seem to help with this specifically:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;tleap: requires manual editing to change the residue name of one atom at the end of each chain into NME and ACE. After this, tleap can add missing atoms, but the key step is manual&lt;/li&gt;&#xA;&lt;li&gt;pdbfixer: can add charged terminal caps, but not NME/ACE&lt;/li&gt;&#xA;&lt;li&gt;pdb2gmx: does not add NME/ACE; requires manual editing of the PDB file&lt;/li&gt;&#xA;&lt;li&gt;CHARMM-GUI: not scripted/automated&lt;/li&gt;&#xA;&lt;li&gt;HTMD / Maestro: apparently these would work but I don't have a license!&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="5" LastEditDate="2022-07-31T15:17:04.153" LastActivityDate="2022-08-25T02:39:28.883" Title="Is there a scripted tool to add neutral terminal caps (e.g. NME, ACE) to peptide chains for use with AMBER forcefields?" Tags="|molecular-dynamics|amber|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9456" PostTypeId="1" AcceptedAnswerId="10392" CreationDate="2022-07-29T10:56:36.430" Score="2" ViewCount="544" Body="&lt;p&gt;I need to generate a contour plot from a file (named abc.gnu) which has X, Y and Z columns of data. It has 1000000 rows of data. I have got the contour plot with a python code (shown at the end). What I need is to know the 'Z' values in any arbitrary place of choice (or to see 'Z' values in different regions of the contour plot). If I zoom any particular region, still the color bar is showing the same min and max values, so I can't get any information of 'Z' values in the zoomed region as well. Do you have any idea to solve this for my used file. I have given my used python script at the end. Any other idea to get more effective 2D contour plot is also welcome.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JT0TN.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JT0TN.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Used Python Code for the contour plot&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pandas as pd&#xA;import matplotlib.pyplot as plt&#xA;import numpy as np&#xA;&#xA;data=pd.read_csv('abc.gnu',delimiter='      ',header=None,engine='python')&#xA;data_M=np.array(data)&#xA;&#xA;X=data_M[:,0]&#xA;Y=data_M[:,1]&#xA;Z=data_M[:,2]&#xA;Xs=X.reshape((1000,1000))&#xA;Ys=Y.reshape((1000,1000))&#xA;Zs=Z.reshape((1000,1000))&#xA;&#xA;fig = plt.figure(figsize=(10,8))&#xA;left, bottom, width, height = 0.1, 0.1, 0.8, 0.8&#xA;ax = fig.add_axes([left, bottom, width, height])&#xA;&#xA;cp = plt.contourf(Xs, Ys, Zs)&#xA;plt.colorbar(cp)&#xA;&#xA;ax.set_title('Contour Plot')&#xA;ax.set_xlabel('X')&#xA;ax.set_ylabel('Y')&#xA;&#xA;x = np.linspace(0, 5, 150)&#xA;y = np.linspace(0, 5, 150)&#xA;&#xA;X, Y = np.meshgrid(x, y)&#xA;&#xA;plt.xlim(0, 25)&#xA;plt.ylim(0, 4)&#xA;&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2022-07-31T13:52:02.923" LastActivityDate="2023-02-09T15:53:23.707" Title="2D charge density contour plot (how to get arbitrary 'Z' values in the plot using python)" Tags="|quantum-espresso|python|charge-density|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9457" PostTypeId="1" CreationDate="2022-07-29T12:19:32.057" Score="2" ViewCount="1527" Body="&lt;p&gt;First of all, I already did electronic structure calculations in the past, but I am a total beginner regarding the use of Gaussian. Currently I am trying to use Gaussian16 through the terminal on linux and I keep getting an error message for basically all inputs I submit. The error that is raised right after the submission of the input is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error: segmentation violation&#xA;   rax 0000000000000000, rbx ffffffffffffffff, rcx 00002b30b4daf237&#xA;   rdx 000000000000c510, rsp 00007ffc7d2bf378, rbp 00007ffc7d2bf8f0&#xA;   rsi 000000000000000b, rdi 000000000000c510, r8  0000000000000020&#xA;   r9  00002b30b4eb0850, r10 000000007c998911, r11 0000000000000206&#xA;   r12 00007ffc7d2bf938, r13 0000000000000000, r14 0000000000000000&#xA;   r15 00000000000003e6&#xA;  /lib64/libpthread.so.0(+0x10c10) [0x2b30b486ac10]&#xA;  /lib64/libc.so.6(kill+0x7) [0x2b30b4daf237]&#xA;  /opt/g16/l301.exe() [0x627740]&#xA;  /opt/g16/l301.exe() [0x6462b1]&#xA;  /opt/g16/l301.exe() [0x6bfdb1]&#xA;  /opt/g16/l301.exe() [0x4073f7]&#xA;  /opt/g16/l301.exe() [0x4038e0]&#xA;  /opt/g16/l301.exe() [0x40381d]&#xA;  /lib64/libc.so.6(__libc_start_main+0xf5) [0x2b30b4d9a725]&#xA;  /opt/g16/l301.exe(sched_setaffinity+0xa1) [0x403729]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is an example of an input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=methanetest.chk&#xA;# HF/6-31G&#xA;&#xA;methane energy&#xA;&#xA;0 1&#xA;C   -0.000000   -0.000000   -0.000000 &#xA;H   0.633663    0.633663    0.633663&#xA;H   -0.633663   -0.633663    0.633663&#xA;H   0.633663   -0.633663   -0.633663&#xA;H   -0.633663    0.633663   -0.633663&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I cannot  tell if there is anything wrong with my input or if there is another problem. Any help is highly appreciated, because I did not find anything related elsewhere.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt;&#xA;Calculations with small molecules are working now, but if I want to run calculations on molecules I need to do for my research I encounter the same error again. Here is the input of my molecule:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=8&#xA;%chk=org_Te_01.chk&#xA;# HF/6-31G(d,p)&#xA;&#xA;Organotellurium compound test&#xA;&#xA;0 1&#xA;C      0.759205    2.343926   -0.396326&#xA;C      0.334605    0.988926    0.138474&#xA;C      0.661405   -0.183574   -0.755726&#xA;N      1.489405   -0.164274   -1.735426&#xA;O      1.653505   -1.303674   -2.379926&#xA;Te     0.622905   -2.856074   -1.619726&#xA;Cl    -1.167795   -2.437974   -3.173926&#xA;C     -0.019895   -1.450074   -0.505326&#xA;C     -1.125495   -1.514574    0.476374&#xA;C     -1.641995   -0.362774    0.957674&#xA;C     -1.179595    0.979926    0.397574&#xA;C     -1.566395    2.162426    1.259774&#xA;C     -0.951095    3.345526    1.063574&#xA;C      0.170305    3.455126    0.089374&#xA;H      1.555505    2.431126   -1.129126&#xA;H      0.813105    0.830526    1.131374&#xA;H     -1.501695   -2.473974    0.817174&#xA;H     -2.413795   -0.400874    1.720574&#xA;H     -1.652695    1.117826   -0.602426&#xA;H     -2.352895    2.075826    2.003474&#xA;H     -1.267095    4.221626    1.620574&#xA;H      0.514605    4.434526   -0.226426&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am starting to get really confused now. What am I doing wrong ? (Thanks in advance !)&lt;/p&gt;&#xA;" OwnerUserId="5646" LastEditorUserId="7" LastEditDate="2022-08-01T00:34:19.120" LastActivityDate="2022-08-01T00:34:19.120" Title="Cause of segfault from simple Gaussian16 input?" Tags="|electronic-structure|gaussian|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9459" PostTypeId="2" ParentId="9457" CreationDate="2022-07-29T15:31:25.363" Score="5" Body="&lt;p&gt;The input looks otherwise correct but is missing the terminating blank line that is expected by Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;Add in the blank line at the end, and the input runs successfully.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; as to the addendum of the question, the problem is that - exactly like Gaussian reports&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Atomic number out of range for 6-31G basis set.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;as the 6-31G** basis set is limited to light atoms.&lt;/p&gt;&#xA;&lt;p&gt;My advice is to forget about obsolete Pople basis sets, and switch to modern basis set families that not only cover the whole periodic table but also come in systematic hierarchies of accuracy.&lt;/p&gt;&#xA;&lt;p&gt;Changing the basis input from &lt;code&gt;6-31G(d,p)&lt;/code&gt; to &lt;code&gt;def2SVP&lt;/code&gt;, which is a similar size basis from the Karslruhe family of Ahlrichs and coworkers but is available for the whole periodic table from H to Rn and efficiently includes relativistic effects through effective core potentials, the calculation runs.&lt;/p&gt;&#xA;&lt;p&gt;PS. if you are doing research on such molecules, you definitely will want to use some other method than HF which yields poor chemistry.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-07-31T20:26:37.960" LastActivityDate="2022-07-31T20:26:37.960" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9460" PostTypeId="1" CreationDate="2022-07-31T15:19:19.160" Score="4" ViewCount="720" Body="&lt;p&gt;I found several AIMD analyzers to estimate mean square displacement and ionic diffusivity such as &lt;a href=&quot;https://github.com/materialsvirtuallab/pymatgen-analysis-diffusion&quot; rel=&quot;nofollow noreferrer&quot;&gt;pymatgen&lt;/a&gt;, &lt;a href=&quot;https://github.com/mogroupumd/aimd&quot; rel=&quot;nofollow noreferrer&quot;&gt;mo&lt;/a&gt;, &lt;a href=&quot;https://vaspkit.com/tutorials.html#other-functions&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspkit&lt;/a&gt;. I tried some tests and found that the same data set might result in different MSD slops by using different analyzers. The ways of calculating MSD are not similar (I do not see vaspkit source code). I wonder which way/script is reliable and its obtained results are accepted?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="1352" LastEditDate="2022-08-01T00:50:57.483" LastActivityDate="2022-08-01T00:50:57.483" Title="Scripts to calculate ionic diffusivity" Tags="|vasp|molecular-dynamics|software-recommendations|ergodicity|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9461" PostTypeId="2" ParentId="9460" CreationDate="2022-07-31T22:16:20.747" Score="6" Body="&lt;h5&gt;Short Version&lt;/h5&gt;&#xA;&lt;p&gt;The differences have to do with possible discrepancies in the order of operations when computing MSD's, or with lengths of trajectories in different studies.&lt;/p&gt;&#xA;&lt;p&gt;For software packages, in addition to the ones listed in the question, there is also &lt;a href=&quot;https://kinisi.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;kinisi&lt;/a&gt;. There is also &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.26699&quot; rel=&quot;noreferrer&quot;&gt;CHAMPION&lt;/a&gt;, which is not published but possible to reverse engineer, and is nicer for complex fluids. See especially Figure 7 in the CHAMPION paper for an example of where differences between approaches come from.&lt;/p&gt;&#xA;&lt;p&gt;Personally, I would bias towards verifying the underlying physics over trusting any code which does not show it to me.&lt;/p&gt;&#xA;&lt;h5&gt;Long Version: Computing MSD Properly&lt;/h5&gt;&#xA;&lt;p&gt;Nomenclature:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\bar{x} = \frac{1}{\Delta} \int_0^\Delta x(\delta) d\delta$&lt;/span&gt; for time-averaging single-ion quantities over multiple starting points in the simulation trajectory of length &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;. We are interested in the displacements over time intervals &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$x_1(t,\delta) = r_i(t+\delta) - r_i(\delta)$&lt;/span&gt;, and squared displacements, &lt;span class=&quot;math-container&quot;&gt;$x_2(t,\delta) = (r_i(t+\delta) - r_i(\delta))^2$&lt;/span&gt;. Here, little &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; is the integrand of the time averaging.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\langle x \rangle = \frac{1}{N} \sum_1^N x$&lt;/span&gt; for the ensemble averaging over all ions &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; in the simulation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are three operations to keep track of: taking the square of the displacements for a given interval &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; and starting point &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;, taking the time average, and taking the ensemble average.&lt;/p&gt;&#xA;&lt;p&gt;The proper way of computing the self diffusivity is to first compute single-ion MSD's, then average them over the ensemble of the ions in a simulation, i.e. &lt;span class=&quot;math-container&quot;&gt;$\Big\langle \bar{r^2} \Big\rangle$&lt;/span&gt; - bar inside the brackets. I'll call this quantity tMSD. When this quantity is linear with time interval (not simulation length), Fickian diffusion can be assumed and the self diffusion coefficient extracted.&lt;/p&gt;&#xA;&lt;p&gt;Computing tMSD properly requires custom code because simulation engines pack trajectories by time point (&lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;), not by ion. Hence all the packages. I have tried to understand what exactly pymatgen and others compute, but in finite time was not able to for layers of abstraction. Hopefully some of the developers can comment in more detail.&lt;/p&gt;&#xA;&lt;p&gt;Sometimes the computation is done either in reverse order, i.e. take the square, then the ensemble average, then time-average, or skipping the time-averaging. This makes built-in methods such as the computes &lt;code&gt;msd&lt;/code&gt; and &lt;code&gt;msd/nongauss&lt;/code&gt; in LAMMPS not give reliable answers: they only sample one starting point. I would not recommend using either.&lt;/p&gt;&#xA;&lt;p&gt;A third order of operations, i.e. first computing the ensemble center-of-mass displacement, then its square, &lt;span class=&quot;math-container&quot;&gt;$\langle r \rangle^2$&lt;/span&gt;, and then averaging over times, gives the &amp;quot;jump&amp;quot; diffusion coefficient, which yields conductivity rather than diffusivity. Both for real physics and for having effectively one particle, this takes a very long trajectory to converge. I am bringing this up because often from AIMD a unity Haven ratio is assumed, and the self diffusion coefficient used in place of the jump one - which is not always a good assumption.&lt;/p&gt;&#xA;&lt;h5&gt;Long Version : How Long is Long Enough?&lt;/h5&gt;&#xA;&lt;p&gt;Besides possible errors in the order of operations, sometimes the (AI)MD trajectories are simply not long enough, and the results will vary with changing the length of the trajectory. So how does one tell whether a trajectory is &amp;quot;long enough&amp;quot; and a long-time limit is reached? There are a few ways.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The one used most often for self diffusivity is to verify linearity of tMSD (if done correctly) on a log-log plot vs the time interval &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;. That involves human judgement over when the long-time linear regime starts, i.e. how close to 1 is &amp;quot;good enough&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;The maximum-entropy distribution with the constraints of a mean and a variance is a Gaussian. This means that distributions of tMSD's over longer and longer time intervals will asymptotically tend towards Gaussians. So an indirect test for &amp;quot;long enough&amp;quot; is whether the distributions of tMSD's are Gaussian. This is why the non-Gaussian parameter (NGP) is sometimes used. It has the same drawback: it does not go to zero at finite interval &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt;, but approaches it asymptotically.&lt;/li&gt;&#xA;&lt;li&gt;Next, there is the ergodicity breaking parameter, &lt;span class=&quot;math-container&quot;&gt;$EB(t,\Delta)$&lt;/span&gt;, which is the &lt;em&gt;relative&lt;/em&gt; variance of the tMSD, very similar to Mandel's Q parameter. This is typically computed for a fixed small-ish &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; over increasing trajectory lengths &lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;. The benefit of using &lt;span class=&quot;math-container&quot;&gt;$EB$&lt;/span&gt; is that it can have a well-defined cutoff for a long-time limit, i.e. you can tell when a trajectory is &amp;quot;long enough&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;Fourth, there is the correlation of the diffusion kernel &lt;span class=&quot;math-container&quot;&gt;$C_D$&lt;/span&gt;, which is another test loosely based on when nonlinear path-dependent effects, which are represented by higher-exponent averages of displacements, become negligible relative to tMSD. Like the &lt;span class=&quot;math-container&quot;&gt;$EB$&lt;/span&gt;, it has a well-defined long-time limit, and reaches that limit at finite time intervals. The drawback is that it involves a Laplace transform and an inverse Laplace transform, which may need to be tuned numerically.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://github.com/apoletayev/anomalous_ion_conduction&quot; rel=&quot;noreferrer&quot;&gt;python code&lt;/a&gt; I wrote for a recent paper is far from great, and is not a package. But as of the time of this writing (July 31, 2022), it is to my knowledge the only one that implements the three metrics above (NGP, &lt;span class=&quot;math-container&quot;&gt;$EB$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_D$&lt;/span&gt;) for verifying that the &amp;quot;infinite-time&amp;quot; limit has been reached in the simulation.&lt;/p&gt;&#xA;&lt;h5&gt;References&lt;/h5&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Song et al. Transport dynamics of complex fluids. &lt;em&gt;PNAS&lt;/em&gt; &lt;strong&gt;2019&lt;/strong&gt;, &lt;em&gt;116&lt;/em&gt; (26), 12733.&lt;/li&gt;&#xA;&lt;li&gt;He, Burov, Metzler, Barkai. Random Time-Scale Invariant Diffusion and Transport Coefficients. &lt;em&gt;PRL&lt;/em&gt; &lt;strong&gt;2008&lt;/strong&gt;, &lt;em&gt;101&lt;/em&gt;, 058101.&lt;/li&gt;&#xA;&lt;li&gt;Jeon et al. Protein Crowding in Lipid Bilayers Gives Rise to Non-Gaussian Anomalous Lateral Diffusion of Phospholipids and Proteins. &lt;em&gt;PRX&lt;/em&gt; &lt;strong&gt;2016&lt;/strong&gt;, &lt;em&gt;6&lt;/em&gt;, 021006.&lt;/li&gt;&#xA;&lt;li&gt;Lanoiselée, Grebenkov. A model of non-Gaussian diffusion in&#xA;heterogeneous media. &lt;em&gt;J. Phys. A.&lt;/em&gt; &lt;strong&gt;2018&lt;/strong&gt;, &lt;em&gt;51&lt;/em&gt;, 145602.&lt;/li&gt;&#xA;&lt;li&gt;Poletayev, Dawson, Islam, Lindenberg. Defect-driven anomalous transport in fast-ion conducting solid electrolytes. &lt;em&gt;Nat. Mater.&lt;/em&gt; &lt;strong&gt;2022&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="7" LastEditDate="2022-08-01T00:38:50.673" LastActivityDate="2022-08-01T00:38:50.673" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9462" PostTypeId="1" CreationDate="2022-07-31T22:42:37.420" Score="2" ViewCount="44" Body="&lt;p&gt;I am working with x&lt;span class=&quot;math-container&quot;&gt;$\ce{M_2O}$&lt;/span&gt;-(1-x)&lt;span class=&quot;math-container&quot;&gt;$\ce{SiO_2}$&lt;/span&gt; binary glass having two different fractions of modifier (x=0.2 and 0.4). Glass with a 40% modifier has a higher density than glass with a 20% modifier. The intensity of the Si-O peak that corresponds to 40% of the modifier is less than the intensity that corresponds to 20% when plotting the total pair distribution function (PDF); however, the reverse trend has been seen when plotting the partial &lt;span class=&quot;math-container&quot;&gt;$\ce{Si-O}$&lt;/span&gt; PDF. I don't understand why?&lt;/p&gt;&#xA;" OwnerUserId="5590" LastEditorUserId="5" LastEditDate="2023-01-31T22:01:00.430" LastActivityDate="2023-01-31T22:01:00.430" Title="Why I am seeing opposing trend in the partial PDF (pair distribution function) when compared to Total PDF?" Tags="|radial-distribution-function|amorphous-materials|" AnswerCount="0" CommentCount="1" ClosedDate="2024-01-11T14:38:41.990" ContentLicense="CC BY-SA 4.0" />
  <row Id="9463" PostTypeId="2" ParentId="3550" CreationDate="2022-07-31T22:46:25.210" Score="4" Body="&lt;h2&gt;Cluster Expansion Codes&lt;/h2&gt;&#xA;&lt;p&gt;Several codes can help with fitting a cluster expansion (CE) to this problem. A cluster expansion uses (small-cell) computed DFT energies and maps them to short-range multi-body cluster interactions on the assumption that all species occupy lattice sites. In this particular example, the assumption will be that the O occupy some well-defined interstitial sites. The codes will take care of the symmetry elements in generating the reference structures for DFT, see e.g. structure enumeration in ICET linked below. The upside of using a cluster expansion is that it eliminates the need to try all the available structures. You can start training the cluster expansion with something like 50, then add structures and re-train as needed until test / validation errors are acceptable.&lt;/p&gt;&#xA;&lt;p&gt;Ultimately, from small-cell reference computations, once the CE is well-trained, an arbitrarily large cell can be extrapolated, and its ground state (lowest-energy ordering) found by simulated annealing.&lt;/p&gt;&#xA;&lt;p&gt;Examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ICET &lt;a href=&quot;https://icet.materialsmodeling.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://icet.materialsmodeling.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;CLEASE &lt;a href=&quot;https://clease.readthedocs.io/en/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://clease.readthedocs.io/en/stable/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-07-31T22:56:59.877" LastActivityDate="2022-07-31T22:56:59.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9465" PostTypeId="1" AcceptedAnswerId="9469" CreationDate="2022-08-01T17:40:54.770" Score="5" ViewCount="243" Body="&lt;p&gt;For a given molecule, we can determine the normal modes of vibration and the corresponding vibrational frequencies by calculating the molecular Hessian of second-order energy derivatives, and finding the eigenvectors/eigenvalues. However, I've also seen approaches to finding the normal modes which rely only on the molecule's equilibrium geometry, and some group-theoretic tools.&lt;/p&gt;&#xA;&lt;p&gt;In general, is it possible to precisely determine a molecules normal modes using only its equilibrium geometry, or does this type of analysis only give a qualitative understanding? Is it &amp;quot;easier&amp;quot; to find the normal modes of vibration, as opposed to finding the normal modes and the corresponding frequencies through diagonalizing the Hessian?&lt;/p&gt;&#xA;" OwnerUserId="3693" LastActivityDate="2022-08-03T01:17:28.600" Title="Finding normal mode vectors vs. vibrational frequencies?" Tags="|vibrations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9466" PostTypeId="1" CreationDate="2022-08-01T18:33:41.180" Score="3" ViewCount="26" Body="&lt;p&gt;What are the standard computational methods used in obtaining the edge and corner states of higher-order topological insulators? From my understanding, the DFT code calculates the bulk properties of a system with periodic boundary conditions, which is then used to generate a tight-binding model.&lt;/p&gt;&#xA;&lt;p&gt;If we consider a square lattice in two dimensions. I think that the way one computes edge modes is to construct a geometry that has four boundaries, so there is no periodicity in either the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; or the &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; direction. One then computes the edge and corner states using the given geometry, by diagonalizing a finite-dimensional hopping Hamiltonian. Is this correct?&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastActivityDate="2022-08-01T18:33:41.180" Title="boundary states of higher-order topological insulators" Tags="|topological-insulators|tight-binding|" AnswerCount="0" CommentCount="1" ClosedDate="2023-02-18T13:21:47.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="9467" PostTypeId="2" ParentId="9147" CreationDate="2022-08-01T20:21:29.587" Score="7" Body="&lt;p&gt;The &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;noreferrer&quot;&gt;sisl&lt;/a&gt; Python package can deal with Hamiltonians (and other physical matrices) in orthogonal &lt;em&gt;and&lt;/em&gt; non-orthogonal basis sets.&lt;/p&gt;&#xA;&lt;p&gt;A simple example for graphene would be something like:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;&#xA;# graphene with bond-length 1.42&#xA;graphene = sisl.geom.graphene()&#xA;H = sisl.Hamiltonian(graphene, orthogonal=False)&#xA;H[0, 0] = (0, 1) # on-site value, overlap element&#xA;H[0, 1] = (-2.7, 0.11) # hopping element, overlap element&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;sisl provides other extensive tools and constructs to make these things easier and faster.&lt;/p&gt;&#xA;&lt;p&gt;Once you have a Hamiltonian you can create the band-structures. The below routines automatically determines whether it is non-orthogonal or orthogonal and calls the appropriate routine.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;band = BandStructure(H, [[0, 0, 0], [0, 0.5, 0],&#xA;                         [1/3, 2/3, 0], [0, 0, 0]], 400,&#xA;                        [r'&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;', r'&lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;',&#xA;                         r'&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;', r'&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;'])&#xA;&#xA;# calculate all eigenvalues for the bands&#xA;eigs = band.apply.array.eigh()&#xA;# get linear band-structure (so the distances between special points&#xA;# are correctly calculated in reciprocal space)&#xA;lk, kt, kl = band.lineark(True)&#xA;import matplotlib.pyplot as plt&#xA;plt.xticks(kt, kl)&#xA;plt.xlim(0, lk[-1])&#xA;plt.ylim([-3, 3])&#xA;plt.ylabel('&lt;span class=&quot;math-container&quot;&gt;$E-E_F$&lt;/span&gt; [eV]')&#xA;for bk in bs.T:&#xA;    plt.plot(lk, bk)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;disclaimer: I am the author of sisl&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-08-01T20:21:29.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9468" PostTypeId="1" CreationDate="2022-08-02T02:25:32.617" Score="3" ViewCount="180" Body="&lt;p&gt;Can it be determined whether a biorthogonalized molecular orbitals is singly occupied just from its shape?&lt;/p&gt;&#xA;&lt;p&gt;You can see the picture below, describing biorthogonalized molecular orbitals' shapes of &lt;span class=&quot;math-container&quot;&gt;$\ce{FeO}$&lt;/span&gt; (Red is Oxygen and the other is Iron) by using Gaussian software (UAFPD functional with 6-311+G(2d,p) basis, quartet spin).&lt;/p&gt;&#xA;&lt;p&gt;According to the reference of the image&lt;span class=&quot;math-container&quot;&gt;$^{1}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;With this representation, it is clear that the molecule has five singly occupied orbitals consisting of four alpha unpaired electrons localized on the iron atom...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Unfortunately, I have no idea to figure out whether one orbital is singly occupied or not from the picture.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;James B. Foresman_ Aeleen Frisch - Exploring Chemistry with Electronic Structure Methods (2015) page 55&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OH29w.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OH29w.png&quot; alt=&quot;FeO Biorthogonalized Molecular Orbitals near Fermi Energy&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5806" LastEditorUserId="7" LastEditDate="2022-08-08T20:45:15.307" LastActivityDate="2022-08-08T20:49:12.830" Title="Determining orbital occupation through MO shape (Biorthogonalized molecular orbital)" Tags="|computational-chemistry|molecular-modeling|gaussian|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9469" PostTypeId="2" ParentId="9465" CreationDate="2022-08-02T13:27:04.933" Score="5" Body="&lt;p&gt;This is an interesting question. The Hessian diagonalization one is general, however.&#xA;Group theory is helpful when dealing with small symmetric molecules.&lt;/p&gt;&#xA;&lt;p&gt;Although we have monograph for this topic, I can provide a concrete example.&lt;/p&gt;&#xA;&lt;p&gt;Say the molecule H&lt;sub&gt;2&lt;/sub&gt;O. We know that it has three vibrational modes, one for bending, and one for symmetric stretching and another for antisymmetric.  From the point group point of view, the former two are symmetric (&lt;span class=&quot;math-container&quot;&gt;$A_1$&lt;/span&gt;), and the last one is antisymmetric (&lt;span class=&quot;math-container&quot;&gt;$B_2$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;If we use the group theory trick, which should work if, according to the orthogonality of normal modes, only one mode belongs to an irreducible representation,&#xA;otherwise modes in the same irreducible rep will mix with each other,&#xA;which cannot be separated with only group theory.&#xA;We also know that Hessian relies on the underlying quantum chemistry (QC) computation.&lt;/p&gt;&#xA;&lt;p&gt;So if we compute the frequencies of H&lt;sub&gt;2&lt;/sub&gt;O, but with different QC method/basis set, we should have the displacements in the normal mode of antisymmetric stretching remain exactly the same. However, because the symmetric stretching and bending are both of &lt;span class=&quot;math-container&quot;&gt;$A_1$&lt;/span&gt;, the displacement vectors of those modes will change with the choice of the QC method/basis set.&lt;/p&gt;&#xA;&lt;p&gt;Note that when doing this test, we should &lt;em&gt;NOT&lt;/em&gt; perform the geometry optimization,&#xA;which ensure that the &amp;quot;equilibrium&amp;quot; geometry is the same (although not, optimized or not will only raise a warning in most QC programs).&lt;/p&gt;&#xA;&lt;p&gt;Here are the results from Molpro.&#xA;HF/6-31g:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   Normal Modes&#xA;&#xA;                                1 A1        2 A1        3 B2&#xA;   Wavenumbers [cm-1]         1826.82     3645.93     3770.62&#xA;   Intensities [km/mol]        104.40        1.26       33.92&#xA;   Intensities [relative]      100.00        1.21       32.49&#xA;             OX1             -0.00000     0.00000    -0.00000&#xA;             OY1             -0.00000    -0.00000    -0.06913&#xA;             OZ1             -0.07127    -0.04375    -0.00000&#xA;             HX2              0.00000     0.00000     0.00000&#xA;             HY2             -0.36845     0.60026     0.54867&#xA;             HZ2              0.56568     0.34722     0.39634&#xA;             HX3             -0.00000    -0.00000     0.00000&#xA;             HY3              0.36845    -0.60026     0.54867&#xA;             HZ3              0.56568     0.34722    -0.39634&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;HF/6-311g:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   Normal Modes&#xA;&#xA;                                1 A1        2 A1        3 B2&#xA;   Wavenumbers [cm-1]         1834.52     3613.18     3733.07&#xA;   Intensities [km/mol]        108.14        0.08       26.20&#xA;   Intensities [relative]      100.00        0.07       24.23&#xA;             OX1              0.00000    -0.00000     0.00000&#xA;             OY1             -0.00000    -0.00000    -0.06913&#xA;             OZ1             -0.07144    -0.04347     0.00000&#xA;             HX2              0.00000    -0.00000    -0.00000&#xA;             HY2             -0.36610     0.60169     0.54867&#xA;             HZ2              0.56703     0.34501     0.39634&#xA;             HX3             -0.00000     0.00000    -0.00000&#xA;             HY3              0.36610    -0.60169     0.54867&#xA;             HZ3              0.56703     0.34501    -0.39634&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You will find our theory is correct.&lt;/p&gt;&#xA;" OwnerUserId="339" LastEditorUserId="4515" LastEditDate="2022-08-03T01:17:28.600" LastActivityDate="2022-08-03T01:17:28.600" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9470" PostTypeId="1" CreationDate="2022-08-03T20:01:59.920" Score="6" ViewCount="1341" Body="&lt;p&gt;When compiling VASP, I am wondering why the&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; OFLAG = -O2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;is suggested as default. For performance reason, I would use&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; OFLAG = -O3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could someone help explain the reason?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I asked this question because I used the DFT code FHI-aims, whose compilation is suggested with optimization level:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;FFLAGS = -O3 -ip -fp-model precise&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA; In addition, I use intel compiler. &#xA;" OwnerUserId="1688" LastEditorUserId="5" LastEditDate="2022-08-04T14:32:46.197" LastActivityDate="2022-08-04T14:32:46.197" Title="Why does VASP use -O2 optimization by default rather than -O3?" Tags="|vasp|programming|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9471" PostTypeId="2" ParentId="9470" CreationDate="2022-08-03T21:02:03.607" Score="12" Body="&lt;p&gt;This is a great question! Only a VASP developer involved in making that decision would be able to tell you precisely why they made that decision, but I will give you as many useful pieces of information related to this topic as I can. Many of these are from a 10-year old thread in StackOverflow that currently has 144,000+ views: &amp;quot;&lt;a href=&quot;https://stackoverflow.com/a/11546263/1271772&quot;&gt;Is optimisation level -O3 dangerous in g++?&lt;/a&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Applying &lt;code&gt;-O3&lt;/code&gt; to an &lt;strong&gt;entire program&lt;/strong&gt; that is as large as VASP, can cause it to run slower because it would generate more machine code than &lt;code&gt;-O2&lt;/code&gt; which would then make the program unable to fit in the L1 cache. For &amp;quot;large&amp;quot; programs this can also be true for &lt;code&gt;-O2&lt;/code&gt; vs &lt;code&gt;-O1&lt;/code&gt; or &lt;code&gt;-O0&lt;/code&gt;. VASP is a &amp;quot;large&amp;quot; program, but I don't know if it's large enough for &lt;code&gt;-O2&lt;/code&gt; to cause this type of slow-down (hopefully the developers who decided to set &lt;code&gt;-O2&lt;/code&gt; to be the default, considered this carefully enough). &lt;strong&gt;The &lt;a href=&quot;https://stackoverflow.com/a/19985801/1271772&quot;&gt;intended&lt;/a&gt; use of &lt;code&gt;-O3&lt;/code&gt; is that you manually apply it to a &lt;em&gt;small&lt;/em&gt; number of files &lt;em&gt;if&lt;/em&gt; they contain  critical inner loops that actually benefit from these aggressive space-for-speed tradeoffs.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;code&gt;-O3&lt;/code&gt; has also been known to have many &lt;a href=&quot;https://stackoverflow.com/a/11546263/1271772&quot;&gt;bugs&lt;/a&gt; in the past, but the most upvoted answer in the linked StackOverflow thread says that this was &amp;quot;over a decade ago&amp;quot; (and since that answer was written in July 2012, it would now be over &amp;quot;two decades ago&amp;quot; that this was a problem). It's possible that the tendency for &lt;code&gt;-O3&lt;/code&gt; to have bugs was a factor 20+ years ago in making the decision to make &lt;code&gt;-O2&lt;/code&gt; the default. However, while the top-voted answer in that thread says that the bugs were only a problem 20+ years before 2022, an &lt;a href=&quot;https://stackoverflow.com/a/39154063/1271772&quot;&gt;answer in 2016&lt;/a&gt; from a compiler developer, says that it was still a problem recently.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;code&gt;-O3&lt;/code&gt; generally will make compilation take longer (often by a very significant amount), and will make the size of the overall program's executables take up much more space. For a big program like VASP, space can be a concern, and even the time to compile can be a concern (a much smaller program called &lt;a href=&quot;/questions/tagged/mrcc&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;mrcc&amp;#39;&quot; rel=&quot;tag&quot;&gt;mrcc&lt;/a&gt; has sometimes taken me more than 24 hours to compile, which can be enough for your compilation to be interrupted/cut-off due to it being a &amp;quot;job&amp;quot; that takes too long on a shared supercomputer). The longer compile time and larger space required for &lt;code&gt;-O3&lt;/code&gt; in VASP is probably insignificant when compared to the amount of time that VASP is being run (i.e. the use that you're getting out of the compilation), but certainly for smaller programs like my &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465513002294&quot; rel=&quot;noreferrer&quot;&gt;FeynDyn software&lt;/a&gt; for numerical Feynman integrals for quantum dynamics, I chose a lot of default settings with the overall user experience in mind rather than only the speed and accuracy of the calculations. I would rather them be able to get started very quickly and without trouble (i.e. bugs in using &lt;code&gt;-O3&lt;/code&gt; and time/space increases causes by &lt;code&gt;-O3&lt;/code&gt; would not be preferred) than to have slightly faster calculations in a program &lt;em&gt;&lt;strong&gt;that is already super fast for most calculations no matter what level of optimization is used.&lt;/strong&gt;&lt;/em&gt; This bullet point applies to most scientific software in general rather than just to VASP.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Optimization often requires care and attention rather than just blindly using the command with the largest number in it. In &lt;a href=&quot;https://news.ycombinator.com/item?id=28895896&quot; rel=&quot;noreferrer&quot;&gt;this thread&lt;/a&gt; where someone was complaining about a &lt;a href=&quot;https://en.wikipedia.org/wiki/Bubble_sort&quot; rel=&quot;noreferrer&quot;&gt;bubble sort&lt;/a&gt; program being slower with &lt;code&gt;-O3&lt;/code&gt; when compared to &lt;code&gt;-O2&lt;/code&gt;, someone posted the following code timings:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre&gt;&lt;code&gt;-O2 -g: 1.07s&#xA;-O3 -g: 1.17s&#xA;-O3 -g -fprofile-generate/use: 0.84s&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2022-08-04T01:05:51.673" LastActivityDate="2022-08-04T01:05:51.673" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="9472" PostTypeId="1" AcceptedAnswerId="9493" CreationDate="2022-08-04T10:57:32.413" Score="3" ViewCount="80" Body="&lt;p&gt;I want to simulate neutron pair distribution functions that will be compared to experimental scattering data. I have structure files, and I can make reasonable assumptions on the thermal broadening of pairwise distances.&lt;/p&gt;&#xA;&lt;p&gt;What packages could compute a neutron-weighted pair distribution function for me? So far, I have found &lt;a href=&quot;https://subversion.xray.aps.anl.gov/trac/pyGSAS&quot; rel=&quot;nofollow noreferrer&quot;&gt;GSAS&lt;/a&gt;, but looking for other options if they exist.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Not&lt;/strong&gt; looking for packages such as VESTA that generate a list of single-point &lt;strong&gt;peaks&lt;/strong&gt; for e.g. diffraction.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastActivityDate="2022-08-10T02:15:32.343" Title="Packages for simulating neutron PDF" Tags="|software-recommendations|neutron-scattering|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9474" PostTypeId="1" AcceptedAnswerId="9650" CreationDate="2022-08-04T18:09:54.923" Score="5" ViewCount="273" Body="&lt;p&gt;I am currently interested in using pySCF to generate density matrices (first order single particle density matrices) and then using them in Molpro. In principle, this should be possible if the matrix coefficients refer to the same basis set.&lt;/p&gt;&#xA;&lt;p&gt;However, the &lt;code&gt;matrop&lt;/code&gt; program of Molpro has some conventions and pySCF has some conventions for writing these and they are probably not identical. Ideally somebody already would have written a converter. However, if somebody can point me toward the conventions (I only found this &lt;a href=&quot;https://www.molpro.net/info/current/doc/manual/node36.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;dead link&lt;/a&gt;) that would also be useful.&lt;/p&gt;&#xA;" OwnerUserId="5815" LastEditorUserId="7" LastEditDate="2022-08-05T19:55:21.590" LastActivityDate="2022-09-10T21:51:02.273" Title="Interface between PySCF and Molpro" Tags="|pyscf|molpro|reduced-density-matrix|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9475" PostTypeId="2" ParentId="8901" CreationDate="2022-08-04T18:28:13.207" Score="2" Body="&lt;p&gt;The comments are correct in directing you towards literature and the LAMMPS potential directory. For future reference as well, NIST maintains a page which contains many empirical potentials for most elements: &lt;a href=&quot;https://www.ctcms.nist.gov/potentials/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ctcms.nist.gov/potentials/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5433" LastActivityDate="2022-08-04T18:28:13.207" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9476" PostTypeId="1" AcceptedAnswerId="9481" CreationDate="2022-08-05T03:46:56.280" Score="15" ViewCount="2714" Body="&lt;p&gt;I'm a student and now studying quantum chemistry but also interested in machine learning (ML) and materials informatics (MI).&lt;/p&gt;&#xA;&lt;p&gt;In order to understand an ML method for MI, I tried to use &lt;a href=&quot;https://singroup.github.io/dscribe/latest/tutorials/descriptors/soap.html&quot; rel=&quot;noreferrer&quot;&gt;the smooth overlap of atomic positions (SOAP)&lt;/a&gt;, which is a widely-used descriptor for molecules. Using the SOAP descriptor as the input, I implemented a simple neural network (NN) model in PyTorch (see Fig.1 (a)). After training the NN model with the energy, the accuracy was very good, and then I transferred the trained NN model to the HOMO-LUMO gap. I obtained the results as Fig.1 (b) and (c).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/07wuL.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/07wuL.jpg&quot; alt=&quot;Fig.1 (a)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fig.1: (a) The SOAP descriptor input-based NN model. (b) Learning curve for the atomization energy (eV) provided by &lt;a href=&quot;http://quantum-machine.org/datasets/&quot; rel=&quot;noreferrer&quot;&gt;the QM9 database&lt;/a&gt;, which is a famous benchmark database in MI. Test error of energy is about 2.0 eV. (c) Transfer learning for the HOMO-LUMO gap with the pre-trained model.&lt;/p&gt;&#xA;&lt;p&gt;I found that &lt;strong&gt;the transfer result was very poor&lt;/strong&gt; (the random and pre-trained accuracies (errors) are the same, about 1.2 eV as shown in Fig.1 (c))... For my study, I tried to use other ML models (e.g., &lt;a href=&quot;https://github.com/gasteigerjo/dimenet&quot; rel=&quot;noreferrer&quot;&gt;graph neural network&lt;/a&gt; and &lt;a href=&quot;https://www.nature.com/articles/s41467-022-30687-9&quot; rel=&quot;noreferrer&quot;&gt;neural network potential&lt;/a&gt;), but the results were also very poor or much worse...&lt;/p&gt;&#xA;&lt;p&gt;Here, I have a question; &lt;strong&gt;does this mean that the above NN model just fitted to only the energy, did not learn physics at all?&lt;/strong&gt; In addition, &lt;strong&gt;do most of the ML models that just fit only the energy make sense from the view point of DFT?&lt;/strong&gt; In DFT, as far as I have studied, solving the Kohn-Sham equation yields the ground state energy and density by variational principle, and also provides the eigenvalues (i.e., orbital energies), so we can know various physical properties such as the HOMO and LUMO.&lt;/p&gt;&#xA;&lt;p&gt;My impression is that ML models just predict &amp;quot;similar molecules have similar energies (see Fig.2)&amp;quot;, and it is very easy if we have a large number of similar molecules and their energies in the database. However, even in this case, can we say that &amp;quot;ML can approximate the DFT calculation&amp;quot;? (In fact, most of the research papers in ML and MI claim so, and I'm honestly very confused…)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HGzjD.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HGzjD.jpg&quot; alt=&quot;Fig.2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fig.2: The energy of the right-side molecule must be close to about -86.7X eV (the actual energy is -86.75 eV), but this is very easy to predict because we already know the energies of the left-side molecules as the training data samples, which are very similar to the right-side molecule.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Postscript: actually, I'm now interested in the &amp;quot;foundation model&amp;quot; in AI/ML research (&lt;a href=&quot;https://arxiv.org/pdf/2108.07258.pdf&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/pdf/2108.07258.pdf&lt;/a&gt;). I would like to know whether AI/ML can solve various tasks (e.g., not only predict the total energy but also provide the HOMO LUMO eigenvalues, density, and other physical properties) with one (pre-trained) model. I would like to ask about the possibility as another question.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2022-08-06T01:28:24.360" LastActivityDate="2022-08-07T05:30:13.490" Title="What does machine learning learn about DFT?" Tags="|density-functional-theory|machine-learning|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9477" PostTypeId="1" CreationDate="2022-08-05T04:51:03.963" Score="1" ViewCount="77" Body="&lt;p&gt;Example Molecule: C60 (Fullerene)&lt;/p&gt;&#xA;&lt;p&gt;Route Section: #p B3LYP/6-311G(d) guess = read geom = check pop = full&lt;/p&gt;&#xA;&lt;p&gt;Question: What information can I get from atomic orbital contributions?&lt;/p&gt;&#xA;&lt;p&gt;I've calculated atomic orbital contribution of molecule with following procedure:&#xA;The keyword 'pop=full' gives all atomic orbital coefficients, composing molecular orbitals. So I did absolute sum of S orbitals(1s,2s,3s)' coefficients, P orbitals(2px,2py,...,3pz)' coefficients, and D orbitals' coefficients denoted by S_coef, P_coef, and D_coef respectively.  Then I defined the contribution of S, P, and D by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S_{contri} = \frac{S_{coef}}{S_{coef} + P_{coef} + D_{coef}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(As you may noticed, P and D contribution is nothing but replacing the numerator with its coefficients)&lt;/p&gt;&#xA;&lt;p&gt;The result is following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0dGi0.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0dGi0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;X axis is molecular numbers and y axis is contribution of S, P, D atomic orbitals of C60. And its Homo is at the 180th orbital on the x axis. I find the result reasonable, since S_contribution is greater in the group of inner molecular orbitals(small orbital numbers), and P_contribution become dominant as the molecular number gets greater. But I am afraid if there is something that i missed from the result. Otherwise, Is it just OK to check which atomic orbital is dominant near HOMO or inner shell?&lt;/p&gt;&#xA;" OwnerUserId="5806" LastActivityDate="2022-08-05T04:51:03.963" Title="Gaussian(Software): What does atomic orbital contribution mean?" Tags="|computational-chemistry|molecular-modeling|gaussian|atomic-physics|population-analysis|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T21:51:49.960" ContentLicense="CC BY-SA 4.0" />
  <row Id="9478" PostTypeId="1" CreationDate="2022-08-05T05:35:15.237" Score="5" ViewCount="233" Body="&lt;p&gt;I have observed in research papers that the k-path chosen for electronic band structure and for phonon band structure to be different. I am currently using VASPKIT in order to obtain the path for electronic calculation. But how do I obtain the one for phonon.&lt;/p&gt;&#xA;&lt;p&gt;I think they should be same, but why do some articles use different path. I plan on using phonopy for the calculation of the phonon bands.&lt;/p&gt;&#xA;&lt;p&gt;Thanks, any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="5" LastEditDate="2023-02-18T05:54:29.793" LastActivityDate="2023-02-18T05:54:29.793" Title="k-path for phonon band structure" Tags="|phonons|k-points|phonopy|vaspkit|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9479" PostTypeId="2" ParentId="9476" CreationDate="2022-08-05T07:36:50.083" Score="8" Body="&lt;p&gt;It could just be that the features you are using are well suited for describing total energies in these sorts of systems, but not in describing the differences of eigenvalues. When people do ML to try to capture trends from DFT calculations, usually they do so with specific quantities in mind, and don’t expect to get everything from the DFT calculation correct. For example, neural network potentials can very accurately give you the total energy and forces for a range of systems, but they would likely be poor for giving you the charge density or eigenvalues unless you trained on those quantities in particular. When people say that the ML agrees with DFT, they aren’t necessarily saying that it does so for everything that DFT outputs, instead they usually have a more limited scope.&lt;/p&gt;&#xA;&lt;p&gt;Second, the gap between occupied and unoccupied states is not a physical quantity that DFT should be expected to get accurate, even with the unknown exact exchange correlation functional. The fundamental gap and the optical gap are not ground state quantities, and the DFT orbitals and eigenvalues don’t rigorously correspond to molecular orbitals or molecular orbital energies. In practice, DFT can often give reasonable values for the band gap of solids, or things like molecular orbitals in molecules, but unlike with the total energy and the electron density, quantities like the wavefunctions and eigenvalues aren’t really meant to be compared with physical observables.&lt;/p&gt;&#xA;&lt;p&gt;The reason why people often do this anyway, and why often the DFT results aren’t bad in many cases is that the Hamiltonian from DFT and the Hamiltonian you get from a many body perturbation theory (typically in solids) or wave function based method (like coupled cluster) ends up being somewhat similar. In solids, a method like GW produces eigenvalues that rigorously correspond to the band gap. It just so happens that in GW, the difference between the exchange correlation energy and the GW self-energy is small enough in some systems that the DFT results can be sort of interpreted as giving you a value for the band gap.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-08-05T07:36:50.083" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9480" PostTypeId="1" AcceptedAnswerId="9482" CreationDate="2022-08-05T08:01:10.793" Score="10" ViewCount="684" Body="&lt;p&gt;I like to calculate pka values for two different H atoms in one molecule. Is it possible to do so with computational methods? I have gaussian and orca as software to use. I searched in the internet for articles about it. I often found QSAR. But I don't want to do QSAR calculation, because the can only perform pka values for the hole molecule in one. So I can get not different steps. And may do additional calculations with the geometry. So has anyone an idea if it is possible with DFT calculations or something similar?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastActivityDate="2022-08-30T13:43:14.373" Title="Is it possible to calculate the pka value of different H atoms on one molecule?" Tags="|density-functional-theory|qsar|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9481" PostTypeId="2" ParentId="9476" CreationDate="2022-08-05T09:14:53.253" Score="15" Body="&lt;p&gt;Total energies and HOMO-LUMO gaps are very different quantities, and naturally necessitate very different neural network designs (including the choice of descriptors and architectures) in order to describe efficiently and accurately. For example:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The total energy is a size-extensive property, while the HOMO-LUMO gap is size-intensive. Two non-interacting copies of the same molecule have exactly twice the energy as the single molecule, and exactly the same HOMO-LUMO gap (not twice of it) as the single molecule. Many neural networks designed to predict total energies work by expressing the total energy as a sum of atomic energies, and predict the atomic energies; this guarantees size-extensivity by construction, but which also means that the same neural networks are completely unsuitable for predicting size-intensive properties.&lt;/li&gt;&#xA;&lt;li&gt;The total energy is a relatively local property, but the HOMO-LUMO gap is very non-local. Imagine a large molecule where the HOMO is localized on one side while the LUMO is localized on the other side. A neural network cannot correctly estimate the HOMO-LUMO gap of the system by only looking at a portion of it, not even when it computes estimates for many small portions of the molecule and then pools the results. At some point of the neural network prediction, there has to be a subtraction of two quantities computed from two arbitrarily far parts of the molecule. This also rules out many common neural network architectures. By contrast, all through-space interactions involved in the total energy decay at least as &lt;span class=&quot;math-container&quot;&gt;$1/R$&lt;/span&gt;, and much faster than that if the system does not contain ions.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Besides, there are some issues that affect both total energy and HOMO-LUMO gap predictions, but are much more severe for the latter:&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;The HOMO-LUMO gap is a non-differentiable function of the molecular geometry. Consider a system whose ground state and the first excited state form a conical intersection (e.g. a first-order Jahn-Teller system), and we vary the geometry continuously from one side of the conical intersection, till we pass the intersection point. The HOMO-LUMO gap will decrease approximately linearly. Then at the intersection point, the HOMO and LUMO suddenly swap, and the HOMO-LUMO gap increases approximately linearly again. No neural network built from smooth activation functions can reproduce this behavior. While neural networks that use, e.g. ReLU activation functions do possess derivative discontinuities, it is a difficult task to ensure that the derivative discontinuities only occur at (or at least near) conical intersections.&lt;/li&gt;&#xA;&lt;li&gt;The HOMO-LUMO gap sometimes depend on whether there are an even number or an odd number of a certain functional group. This is best exemplified by the Hückel 4n+2 rule: conjugated rings with 4n+2 electrons are aromatic and have relatively large HOMO-LUMO gaps, while those with 4n electrons are antiaromatic and have small HOMO-LUMO gaps. It is extremely challenging to learn this fact with a neural network except by hard-coding the rule and/or intentionally including a large number of different aromatic and antiaromatic systems in the training set.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;These may explain why it is difficult to predict the HOMO-LUMO gap to high accuracy. I would personally recommend predicting the Fock matrix instead, and then obtain the HOMO-LUMO gap by diagonalizing the Fock matrix. The Fock matrix is a much more well-behaved object than the HOMO-LUMO gap: the matrix elements are mostly determined from nearby atoms, do not have strong derivative discontinuities, and do not have the even-odd alternations as the HOMO-LUMO gap has for conjugated rings. Moreover, I believe that there are well-established techniques for predicting the Fock matrix via machine learning.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-08-05T09:14:53.253" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9482" PostTypeId="2" ParentId="9480" CreationDate="2022-08-05T10:56:13.960" Score="10" Body="&lt;p&gt;Yes. Simply calculate the pKa from the definition:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rm{pK_a} = \lg \frac{[AH]}{[A^-][H^+]} \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The equilibrium constant in the logarithm is computed from the Gibbs free energy of the protonation reaction &lt;span class=&quot;math-container&quot;&gt;$A^- + H^+ \to AH$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{[AH]}{[A^-][H^+]} = e^{-\Delta G/RT} \tag{2}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta G = G(AH_{aq}) - G(A^-_{aq}) - G(H^+_{aq}) \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since in aqueous solution, the three species (especially &lt;span class=&quot;math-container&quot;&gt;$A^-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H^+$&lt;/span&gt;) interact strongly with water molecules, it may be necessary to include some explicit water molecules, i.e. instead of Eq. (3), we have (note the subscript &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;; we will return to this issue later. Also note that the formula does not require that &lt;span class=&quot;math-container&quot;&gt;$m-n-k \ge 0$&lt;/span&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta G = G((AH(H_2O)_m)_{aq}) - G((A^-(H_2O)_n)_{aq}) - G((H^+(H_2O)_k)_{aq}) \\&#xA; - (m-n-k)G((H_2 O)_{l}) \tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Some researchers use the following, slightly different form, where instead of calculating the Gibbs free energy of one water molecule and multiply by &lt;span class=&quot;math-container&quot;&gt;$(m-n-k)$&lt;/span&gt;, they calculate a single water cluster with &lt;span class=&quot;math-container&quot;&gt;$(m-n-k)$&lt;/span&gt; molecules. This has advantages and disadvantages, and I'm not sure if this is a more common (or more justified) approach:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta G = G((AH(H_2O)_m)_{aq}) - G((A^-(H_2O)_n)_{aq}) - G((H^+(H_2O)_k)_{aq}) \\&#xA; - G(((H_2 O)_{(m-n-k)})_{l}) \tag{5}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(this obviously assumes that &lt;span class=&quot;math-container&quot;&gt;$m-n-k \ge 0$&lt;/span&gt;. When &lt;span class=&quot;math-container&quot;&gt;$m-n-k &amp;lt; 0$&lt;/span&gt;, one should use &lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta G = G((AH(H_2O)_m)_{aq}) - G((A^-(H_2O)_n)_{aq}) - G((H^+(H_2O)_k)_{aq}) + G(((H_2 O)_{(n+k-m)})_{l})&#xA;$$&lt;/span&gt;&#xA;instead.)&lt;/p&gt;&#xA;&lt;p&gt;Frequently (but not always), &lt;span class=&quot;math-container&quot;&gt;$k=4$&lt;/span&gt; is used. The values of &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; depend on the structure of the acid &lt;span class=&quot;math-container&quot;&gt;$AH$&lt;/span&gt;; normally, they are chosen as the minimum numbers necessary to describe all strong hydrogen bonds between the solute and the water. Here &amp;quot;strong hydrogen bonds&amp;quot; can be loosely understood as hydrogen bonds that are significantly stronger than the hydrogen bonds between water molecules.&lt;/p&gt;&#xA;&lt;p&gt;Now the only remaining problem is the calculation of Gibbs free energies involved in Eq. (4) or Eq. (5). There are lots of tutorials for this, like &lt;a href=&quot;http://gaussian.com/videos/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://gaussian.com/videos/&lt;/a&gt; (for Gaussian) and &lt;a href=&quot;https://www.orcasoftware.de/tutorials_orca/prop/thermo.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.orcasoftware.de/tutorials_orca/prop/thermo.html&lt;/a&gt; (for ORCA). I would just stress some points that are missed or not sufficiently highlighted by these tutorials:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A configurational search is recommended before the geometry optimization, in order to guarantee that you are working on representative, low-energy molecular configurations, and is absolutely necessary if you have explicit water molecules (otherwise you cannot determine the correct orientations or even locations of the water molecules). Instead of just picking the lowest energy (or lowest Gibbs free energy) conformer, an even better alternative is to pick many low energy conformers, do Gibbs free energy calculations on all of them and take the Boltzmann average of the results. Configurational searches are best done by external programs like &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/crest.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CREST&lt;/a&gt;, &lt;a href=&quot;http://www.keinsci.com/research/molclus.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molclus&lt;/a&gt; or &lt;a href=&quot;http://zhjun-sci.com/software-abcluster-download.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;ABCluster&lt;/a&gt;, at semiempirical (preferentially GFN2-xTB) levels of theory.&lt;/li&gt;&#xA;&lt;li&gt;It is recommended to use a solvation model during the geometry optimization. The SMD model is the most accurate among common implicit solvation models, but some people say that it is less numerically stable than PCM and CPCM, which can prevent geometry convergence. Thus, the PCM (for Gaussian) and CPCM (for ORCA) solvation models can be recommended for the geometry optimization.&lt;/li&gt;&#xA;&lt;li&gt;The dispersion correction must be added during the geometry optimization, frequency calculation and the single point energy calculation, unless the method already fully takes dispersion into account (e.g. M06-2X, wB97M-V, DLPNO-CCSD(T)).&lt;/li&gt;&#xA;&lt;li&gt;After the frequency calculation, the user must check for imaginary frequencies, and if there are any, eliminate them. Otherwise the Gibbs free energies can have errors up to 2~3 kcal/mol (see my answer here &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3942/is-it-right-to-neglect-very-small-imaginary-frequencies/8678#8678&quot;&gt;Is it right to neglect very small imaginary frequencies?&lt;/a&gt;), corresponding to a pKa error of 1~2 units, for each imaginary frequency.&lt;/li&gt;&#xA;&lt;li&gt;For the single point energy calculation, it is recommended to go to at least the DLPNO-CCSD(T)/cc-pVTZ level of theory. If possible, the TightPNO keyword and/or the F12 correction may be added to recover more correlation. If DLPNO-CCSD(T)/cc-pVTZ is not affordable, a double hybrid functional (e.g. PWPB95-D3) plus a triple-zeta basis set (e.g. def2-TZVPP) may be recommended. These may sound like an overkill for the average Gaussian user who is accustomed to a B3LYP/6-311+G(d,p) level single point calculation, but since even these high-level single point energy calculations are not much more expensive than the opt+freq calculations (at least when done by ORCA), there is little reason to not use these high-level methods.&lt;/li&gt;&#xA;&lt;li&gt;Solvation effects are absolutely essential at the single point energy level. The accurate SMD method is in general recommended. It can be directly combined with DLPNO-CCSD(T) and double hybrids, although in the former case some people may prefer to do the DLPNO-CCSD(T) calculation in vacuum and add the solvation free energy calculated at e.g. the B3LYP/def2-TZVP level, citing that the SMD method is not thoroughly tested in conjunction with coupled cluster methods. Still another approach is to calculate the solvation free energy at the M05-2X/6-31G* (or the very similar M06-2X/6-31G*) level, which is justified by the fact that the SMD method was parameterized at the M05-2X/6-31G* level. There seems to be no clear consensus as to which of the three methods is the best.&lt;/li&gt;&#xA;&lt;li&gt;The Gibbs free energies, as obtained by adding the Gibbs free energy corrections to the single point energies, must be further manually corrected for concentration effects. This is because the Gibbs free energies generated by most quantum chemistry programs are calculated at 1 atm (i.e. the standard state of ideal gases), which is a different state than the standard state of aqueous solutions (1 mol/L) and liquid water (55.6 mol/L). This point is frequently overlooked, especially the fact that the standard state of water in an aqueous solution is liquid water, not a &amp;quot;1 mol/L aqueous solution of water&amp;quot;. To correct a Gibbs free energy from concentration &lt;span class=&quot;math-container&quot;&gt;$c_1$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$c_2$&lt;/span&gt;, the following equation is used:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G_2 - G_1 = RT\ln \frac{c_2}{c_1} \tag{6}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Finally, note that even when one is only interested in the first deprotonation, the above procedure is still much more reliable than QSAR, and is recommended whenever the computational resources permit. The only advantage of QSAR is that it is extremely fast to calculate, and is suitable for real-time estimation of pKa or the large-scale screening of the pKas of thousands or millions of molecules.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="7" LastEditDate="2022-08-30T13:43:14.373" LastActivityDate="2022-08-30T13:43:14.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9483" PostTypeId="2" ParentId="9448" CreationDate="2022-08-05T11:12:25.883" Score="9" Body="&lt;p&gt;The non-local operator in Hartree Fock is the Exchange operator. Locality is a mathematical property. Look at the Coulomb operator first which acts like this:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \hat v_H\;\varphi_s(r) = \sum_i^{N_\textrm{occ}}\int dr' \frac{\varphi_i(r') \varphi_i(r')}{|r-r'|} \varphi_s(r).\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It's value depends for the function (which I call here &lt;span class=&quot;math-container&quot;&gt;$\varphi_s$&lt;/span&gt;) on which it acts only on the value of the function at &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now look at the Exchange Operator which acts like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat v_x\;\varphi_s(r) = \sum_i^{N_\textrm{occ}}\int dr' \frac{\varphi_i(r') \varphi_s(r')}{|r-r'|} \varphi_i(r).\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see &lt;span class=&quot;math-container&quot;&gt;$\varphi_s$&lt;/span&gt; is now inside the integral, in order to evaluate the &amp;quot;effect&amp;quot; of the operator you will need knowledge the function &lt;span class=&quot;math-container&quot;&gt;$\varphi_s$&lt;/span&gt; at all positions of space. Hence the designation non-local.&lt;/p&gt;&#xA;&lt;p&gt;The physical meaning of it is that it reflects the permutation symmetry of the fermionic system. This effect is sometimes called Fermi-correlation. Just follow the derivation of Hartree Fock and it will become obvious. A book which contains this derivation is &amp;quot;&lt;a href=&quot;https://books.google.de/books/about/Modern_Quantum_Chemistry.html?id=k-DcCgAAQBAJ&amp;amp;redir_esc=y&quot; rel=&quot;nofollow noreferrer&quot;&gt;Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory (Dover Books on Chemistry)&lt;/a&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varphi$&lt;/span&gt; is a Fock orbital. The index &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; refers to occupied orbitals. The index &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; refers to all orbitals. &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the coordinate of a particle in space while &lt;span class=&quot;math-container&quot;&gt;$r'$&lt;/span&gt; is the coordinate of another particle in space. &lt;span class=&quot;math-container&quot;&gt;$v_H$&lt;/span&gt; is the Coulomb Potential, &lt;span class=&quot;math-container&quot;&gt;$\hat v_x$&lt;/span&gt; is the exchange potential. Often in the context of Hartree Fock &lt;span class=&quot;math-container&quot;&gt;$\hat v_H$&lt;/span&gt; is denoted as &lt;span class=&quot;math-container&quot;&gt;$\hat J$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat v_x$&lt;/span&gt; is denoted as &lt;span class=&quot;math-container&quot;&gt;$\hat K$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5815" LastEditorUserId="5" LastEditDate="2022-08-07T22:49:25.730" LastActivityDate="2022-08-07T22:49:25.730" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9484" PostTypeId="2" ParentId="9474" CreationDate="2022-08-05T13:21:41.793" Score="6" Body="&lt;p&gt;Interoperability between quantum chemistry packages is almost non-existent when it comes to more complicated data structures, and there is no real standard for wavefunction or density matrix interchange. There are some exceptions to this, where one QC package has implemented the idiosyncratic file format of some other other QC package, like the interface to MRCC in Molpro, the CFOUR and MRCC interface in Psi4, and similar, but even still these interfaces are not always well maintained and sometimes break upon updating one of the QC packages.&lt;/p&gt;&#xA;&lt;p&gt;The closest thing I am aware of that can transfer wavefunctions between PySCF and Molpro is MOKIT by Jingxiang Zou (&lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/jxzou/mokit&lt;/a&gt;). Unfortunately it does not offer direct conversions between most QC packages' file formats, the writers can only take the Gaussian .fch as inputs, and the readers can only overwrite the coefficients of an already existing .fch file for the system.&lt;/p&gt;&#xA;&lt;p&gt;So as of now, you would first need to run Gaussian with the same basis set/charge/multiplicity to get a correctly structured .fch file, then use the MOKIT tools to overwrite its innards with your PySCF results, then finally convert it to a format that Molpro can use.&lt;/p&gt;&#xA;&lt;p&gt;The MOKIT project is open source, and I think this is definitely an area where patches would be welcome.&lt;/p&gt;&#xA;" OwnerUserId="5225" LastActivityDate="2022-08-05T13:21:41.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9485" PostTypeId="2" ParentId="9448" CreationDate="2022-08-05T18:36:17.250" Score="6" Body="&lt;p&gt;It's all hollow words if no proper definition is given. The definition I know is the following: For a one-body operator &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, define&#xA;&lt;span class=&quot;math-container&quot;&gt;$$A(x,x^\prime):=\langle x|A|x^\prime\rangle \tag{1} \quad . $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We call &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; &lt;em&gt;local&lt;/em&gt; if the following holds:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$  A(x,x^\prime)= \delta(x-x^\prime)\, A(x),\tag{2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and otherwise it's &lt;em&gt;non-local&lt;/em&gt;. Here we employed a usual abuse of notation in equation &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt;. An example for a local operator would be a local external potential, e.g. the external potential for an electron interacting with some nuclei in the Born-Oppenheimer approximation.&lt;/p&gt;&#xA;&lt;p&gt;Whether or not an external potential is local becomes important in e.g. the Hohenberg-Kohn theorem.&lt;/p&gt;&#xA;&lt;p&gt;Reference: &lt;em&gt;Density-Functional Theory of Atoms and Molecules. Parr and Yang. 1989&lt;/em&gt;, section 2.1, p.23, equation (2.13) and (2.14) as well as the corresponding discussion.&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="5" LastEditDate="2022-08-07T22:50:55.597" LastActivityDate="2022-08-07T22:50:55.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9486" PostTypeId="2" ParentId="9335" CreationDate="2022-08-06T00:27:21.063" Score="2" Body="&lt;p&gt;Others have explained how to get the information from CASTEP, and you could probably also use ASE to convert the files for you, but do you really need to generate a CONTCAR? Most tools I know accept input from many DFT codes directly, including CASTEP; for example &lt;a href=&quot;https://mdanse.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDANSE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Even CASTEP's old &lt;a href=&quot;http://www.tcm.phy.cam.ac.uk/castep/MD/node19.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDTEP&lt;/a&gt; tool will give you an RDF, if that's all you want, although its user interface is definitely showing its age...&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-08-06T00:27:21.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9487" PostTypeId="1" CreationDate="2022-08-06T07:04:26.137" Score="1" ViewCount="107" Body="&lt;p&gt;What kind of chemistry background to get to pursue computational chemistry from an IT background?&lt;/p&gt;&#xA;&lt;p&gt;I have no background in chemistry, and there might be others like me. But I know about computer models.&lt;/p&gt;&#xA;&lt;p&gt;What kind of chemistry do I need to know in order to pursue computational chemistry models?&lt;/p&gt;&#xA;&lt;p&gt;It's intuitive that getting a M.Sc. worth of chemistry on top of M.Sc. worth of IT is not effective. But possibly something that allows one to discuss with chemists and understand the problems that they hand to a data scientist.&lt;/p&gt;&#xA;&lt;p&gt;Also, does computational chemistry mean that one ought to focus more on analytic chemistry or theoretical chemistry or that sorts?&lt;/p&gt;&#xA;&lt;p&gt;What about reading only &amp;quot;Mathematical models of ...&amp;quot; types of resources?&lt;/p&gt;&#xA;" OwnerUserId="5821" LastEditorUserId="5821" LastEditDate="2022-08-06T07:14:37.407" LastActivityDate="2022-08-06T07:14:37.407" Title="What kind of chemistry background to get to pursue computational chemistry from an IT background?" Tags="|mathematical-modeling|education|" AnswerCount="0" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="9488" PostTypeId="1" CreationDate="2022-08-06T09:54:00.263" Score="1" ViewCount="83" Body="&lt;p&gt;does anyone have experience with calculations involving the ESM method? Effective screening medium.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to study a PbTiO3 slab which is polarized in the z direction and I need to cut the coulomb interaction along the z direction. I have tried using large vacuum regions but this is not working and in the long run I reach the FFT limit.&lt;/p&gt;&#xA;&lt;p&gt;I have seen that ESM provides a way to immerse the slab in an effective medium and can deploy different type of boundary conditions. One is vacuum-slab-vacuum and this is what I need. But here is where I get confused.&lt;/p&gt;&#xA;&lt;p&gt;I need to prepare my slab with vacuum regions in the z directions. The question is, in this case how much vacuum do I need if the whole thing is supposed to be immersed in vacuum? What sort of convergence do I need to perform to figure out the needed vacuum region?&lt;/p&gt;&#xA;&lt;p&gt;Cheers,&lt;/p&gt;&#xA;&lt;p&gt;Lucian&lt;/p&gt;&#xA;" OwnerUserId="843" LastActivityDate="2022-08-06T09:54:00.263" Title="quantum espresso ESM calculation" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-01T21:51:35.763" ContentLicense="CC BY-SA 4.0" />
  <row Id="9489" PostTypeId="1" AcceptedAnswerId="9490" CreationDate="2022-08-06T15:24:05.773" Score="9" ViewCount="146" Body="&lt;p&gt;I am trying to understand FEP in the context of a water dimer. Let's say I want to calculate &lt;span class=&quot;math-container&quot;&gt;$\Delta A$&lt;/span&gt;, the free energy change for the following reaction:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ce{H_2O +H_2O\rightarrow H_2O-H_2O},\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which the right hand side denotes a dimerized water molecule. Let's call the left side state 1 and right side state 2. In the left side there is no H-bond.&lt;/p&gt;&#xA;&lt;p&gt;Now as per Zwanzig, the FEP equation is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Delta A=kT\ln \left\langle e^{(-[E_2 - E_1]/kT)}\right\rangle_1,\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt; is the energy of a water dimer, &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; is the energy of two non-interacting molecules, and the sampling is done in two non-interacting water molecule states.&lt;/p&gt;&#xA;&lt;p&gt;Now the total number of particles is 6 (four H atoms, and 2 O atoms). Now when I am sampling at state 1, the conformational coordinate of say the oxygen atom (in the second water molecule), is also the coordinate of the second O atom in the dimer, because I am passing the same coordinate space to the dimer as well. Here is where I am struggling to understand: The coordinates of 6 atoms are the same in both state 1 and state 2, but the only difference is the H-bond which will come into effect in the dimer. So in the &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; context, lets say for simplicity we have one H-bond between H atom #3 (of the first water molecule) and O atom #5 (of the second water molecule). Then we can define the Lennard-Jones potential between atom #3 and atom #5 as,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_ {(3,5)}(\lambda)=\lambda \sigma_ {(3,5)},\tag{3}$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$\lambda=0$&lt;/span&gt; denotes state 1, and &lt;span class=&quot;math-container&quot;&gt;$\lambda=1$&lt;/span&gt; denotes state 2. This way we will have full blown Lennard-Jones in state 2. &lt;strong&gt;Is this how it is modeled in this particular case?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;My second question is on electrostatic interaction, say at particular lambda (say &lt;span class=&quot;math-container&quot;&gt;$\lambda =0$&lt;/span&gt;), we have to run MD on state 1, which at this value of lambda represents non-interacting state. But when we run two such water molecules in MD, the electrostatic interaction will take place nevertheless between these water molecules. I mean I can parametrize away the Lennard-Jones, but it seems I can't kill the inter-molecular electrostatic interaction, as I don't seem to have parameter which I can set at zero at &lt;span class=&quot;math-container&quot;&gt;$\lambda=0$&lt;/span&gt;. Hence it seems to me I can't satisfy the non-interacting criteria in state 1. &lt;strong&gt;Where am I going wrong on electrostatic part?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5822" LastEditorUserId="5" LastEditDate="2023-02-24T12:27:55.767" LastActivityDate="2023-02-24T12:27:55.767" Title="Water dimer and Free Energy Perturbation (FEP)" Tags="|molecular-dynamics|molecular-modeling|statistical-thermodynamics|free-energy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9490" PostTypeId="2" ParentId="9489" CreationDate="2022-08-07T01:01:59.557" Score="7" Body="&lt;p&gt;You are on the right track, but there are a few more details, typically. For one, for a FEP, we calculate the change over many windows. We generally also used soft-core potentials. Soft-core potentials avoid numerical problems at the endpoints when doing perturbations. Also, we don't calculate the energy of a dimer, and subtract the energy of two monomers. You can do this, but it wouldn't be free energy perturbation.&lt;/p&gt;&#xA;&lt;p&gt;Free energy perturbation, in this case, I believe only needs to sample the differences in potential energy as two monomers go from not interacting, to fully interacting (or vice versa).&lt;/p&gt;&#xA;&lt;p&gt;Usually we turn off the electrostatic interactions between the two monomers first, typically in 10 windows(small changes provide more accurate results).&lt;/p&gt;&#xA;&lt;p&gt;NOTE: we keep all interactions alive in each monomer. It is only the interactions between monomers we turn off gradually. This tells us the free energy difference between two monomers fully interacting (a dimer) and two monomers only interacting via LJ potential energy functions.&lt;/p&gt;&#xA;&lt;p&gt;We then turn off the LJ interaction between the two monomers over (often) about 20 windows. We use soft-core potentials for the LJ interactions between the two monomers to avoid the end-point-catastrophe.&lt;/p&gt;&#xA;&lt;p&gt;This second part tells us the difference in free energy between two monomers interacting with each other only with LJ potentials, and two monomers not interacting at all with each other.&lt;/p&gt;&#xA;&lt;p&gt;We can combine the electrostatic decoupling free energy, with the LJ decoupling free energy to get the total free energy difference between a dimer, and two monomers not interacting.&lt;/p&gt;&#xA;&lt;p&gt;We could, rather than decoupling i.e., going from a dimer to two monomers, start at two monomers, and gradually turn on LJ potential energy interactions between the monomers, and then gradually turn on the electrostatic interactions. All that changes is the sign of the free energy change.&lt;/p&gt;&#xA;&lt;p&gt;Also, we can also decouple the electrostatic and LJ interactions simultaneously. Infact, there are a lot of games that can be played.&lt;/p&gt;&#xA;&lt;p&gt;Finally, there are many different Lambda parameters. You do not scale a single one.&lt;/p&gt;&#xA;&lt;p&gt;See the &lt;a href=&quot;https://manual.gromacs.org/current/user-guide/mdp-options.html#free-energy-calculations&quot; rel=&quot;noreferrer&quot;&gt;Gromacs manual and online support (for example)&lt;/a&gt; for more details, but here is a screenshot to help illustrate:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/lu8Km.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lu8Km.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can perturb whatever we want so long as we do it correctly...&lt;/p&gt;&#xA;" OwnerUserId="181" LastActivityDate="2022-08-07T01:01:59.557" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9493" PostTypeId="2" ParentId="9472" CreationDate="2022-08-07T23:27:33.467" Score="4" Body="&lt;p&gt;I haven't used it myself, but &lt;a href=&quot;https://mdanse.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MDANSE&lt;/a&gt; should be able to do this. The name MDANSE comes from &lt;strong&gt;M&lt;/strong&gt;olecular &lt;strong&gt;D&lt;/strong&gt;ynamics &lt;strong&gt;A&lt;/strong&gt;nalysis for &lt;strong&gt;N&lt;/strong&gt;eutron &lt;strong&gt;S&lt;/strong&gt;cattering &lt;strong&gt;E&lt;/strong&gt;xperiments, and it offers graphical and interactive analyses of MD.&lt;/p&gt;&#xA;&lt;p&gt;Its capabilities include general MD analysis (e.g. position and velocity autocorrelation functions) as well as calculations of X-ray and neutron scattering observables (e.g. neutron total dynamic structure factor), and it is fairly actively developed, with new major releases roughly every 2 years. Furthermore, it's an open source Python package so should be fairly easy to extend, if there are gaps in its functionality that you need.&lt;/p&gt;&#xA;&lt;p&gt;As of the latest release (1.5.1) it supports MD trajectories from:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;CASTEP&lt;/li&gt;&#xA;&lt;li&gt;CHARMM&lt;/li&gt;&#xA;&lt;li&gt;DFTB&lt;/li&gt;&#xA;&lt;li&gt;Discover&lt;/li&gt;&#xA;&lt;li&gt;DL_POLY&lt;/li&gt;&#xA;&lt;li&gt;DMol&lt;/li&gt;&#xA;&lt;li&gt;Forcite&lt;/li&gt;&#xA;&lt;li&gt;Gromacs&lt;/li&gt;&#xA;&lt;li&gt;LAMMPS&lt;/li&gt;&#xA;&lt;li&gt;NAMD&lt;/li&gt;&#xA;&lt;li&gt;PDB&lt;/li&gt;&#xA;&lt;li&gt;VASP&lt;/li&gt;&#xA;&lt;li&gt;XPLOR&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-08-10T02:15:32.343" LastActivityDate="2022-08-10T02:15:32.343" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9494" PostTypeId="1" AcceptedAnswerId="9498" CreationDate="2022-08-08T15:41:53.950" Score="8" ViewCount="1520" Body="&lt;p&gt;I have a question regarding spin-orbit coupling (SOC) calculation in VASP.&lt;/p&gt;&#xA;&lt;p&gt;For applying SOC in any system, should tags related to SOC be included in relaxation or in the SCF cycle? If it is in the SCF cycle, then for the calculation of formation energy, should one consider the ground state energy of the system from relaxation output or from the SCF (SOC included) output?&lt;/p&gt;&#xA;" OwnerUserId="5256" LastEditorUserId="7" LastEditDate="2022-08-08T20:33:10.833" LastActivityDate="2022-08-08T20:33:10.833" Title="SOC calculations in VASP" Tags="|density-functional-theory|vasp|spin-orbit-coupling|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9495" PostTypeId="1" CreationDate="2022-08-08T15:55:18.597" Score="7" ViewCount="568" Body="&lt;p&gt;I am aware of the fact that Full Configuration Interaction scales poorly. Taking into account that the number of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-times excited Slater determinants of an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-particle System with &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; basis functions is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA; N \\&#xA;n&#xA;\end{pmatrix}&#xA;\begin{pmatrix}&#xA;2M-N\\ n&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and that you can exchange up to &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; orbitals of your reference determinant makes clear that we won't go far with it. Sure there is Brillouines-Theorem and there is at most two particle operators in the electronic Hamiltonian, which makes the FCI Hamiltonian matrix sparse, but that doesn't change that this method is doomed to run into the &amp;quot;exponential-wall.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;What I want to know is where this wall lies exactly. I am vaguely aware that some calculations of 10 electron systems have been made in the past with this method, but it must be possible to conclusively argue where the exponential wall lies and how it comes to be.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any information on this or can point me to a publication?&lt;/p&gt;&#xA;&lt;p&gt;Cheers,&lt;/p&gt;&#xA;&lt;p&gt;J.Erhard&lt;/p&gt;&#xA;" OwnerUserId="5815" LastEditorUserId="5" LastEditDate="2022-08-09T06:55:23.800" LastActivityDate="2022-08-11T04:37:28.637" Title="What are the limitations of FCI?" Tags="|quantum-chemistry|ab-initio-calculations|electronic-structure|numerical-convergence|full-configuration-interaction|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9496" PostTypeId="1" CreationDate="2022-08-08T17:22:30.363" Score="2" ViewCount="107" Body="&lt;p&gt;I am trying to simulate the DOS of a disordered semiconductor (Cd&lt;sub&gt;0.5&lt;/sub&gt;Zn&lt;sub&gt;0.5&lt;/sub&gt;S), my plan is to get the .cif file of &lt;code&gt;CdS&lt;/code&gt; first, and build a supercell, then I should replace some of the &lt;code&gt;Cd&lt;/code&gt; atoms with &lt;code&gt;Zn&lt;/code&gt; atoms to simulate the random replacement, but I am not sure how should I choose which &lt;code&gt;Cd&lt;/code&gt; atoms should be replaced. Is there any theory to help me understand this issue? Or any tools for this kind of job?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-08-08T17:22:30.363" Title="How to create the supercell to simulate a disordered solid solution?" Tags="|density-functional-theory|vasp|condensed-matter|disorder|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-20T03:27:18.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="9498" PostTypeId="2" ParentId="9494" CreationDate="2022-08-08T20:28:29.003" Score="9" Body="&lt;p&gt;Sometimes the forces will be similar with and without SOC, so you can relax without SOC, and then do a single point calculation on the relaxed structure with SOC. When you do that calculation, you will be able to see if the forces from the structure relaxed without SOC are similar to the forces calculated on the static structure with SOC, and that could give you a sense for the impact of relaxing with and without SOC.&lt;/p&gt;&#xA;&lt;p&gt;For the magnetic moments, it’s similar. Sometimes, the site integrated or cell integrated magnetization magnitude will be similar with and without SOC. Other times it won’t be. Really, you just have to check it if you are hoping that you can get away without including SOC in your system since it can vary from system to system.&lt;/p&gt;&#xA;&lt;p&gt;I would suggest doing the following:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Relax the atomic positions of the initial and final states without SOC, but with collinear magnetism turned on if you have a magnetic system&lt;/li&gt;&#xA;&lt;li&gt;Calculate the formation energy or binding energy by subtracting the total energies without including SOC&lt;/li&gt;&#xA;&lt;li&gt;Run a single point calculation from the relaxed geometries with SOC&lt;/li&gt;&#xA;&lt;li&gt;Calculate the formation energy or binding energy by subtracting the total energies from the single point calculation while including SOC&lt;/li&gt;&#xA;&lt;li&gt;Compare the forces from the last relaxation step and the SOC single point calculation and also the magnitude of the magnetization between the two to see how similar they are&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;One reminder is that if you do a variable cell relaxation, you will want to do a single point calculation at the end even without SOC. This is because of Pulay stress, which you can read about in the VASP manual.&lt;/p&gt;&#xA;&lt;p&gt;If you find that the forces, binding energies, or magnetizations are pretty different with and without SOC, you might want to go back to your original structure and relax it with SOC. This would probably mainly be relevant in large systems with flexible degrees of freedom (like molecules or porous structures) to make sure that you don’t end up relaxing to a different local minimum with and without SOC.&lt;/p&gt;&#xA;&lt;p&gt;If you have a simpler geometry, like many inorganic systems that are relatively small, then you could also try doing a relaxation without SOC, then turning SOC on and continuing the relaxation if the forces in the single point SOC calculation are high. This approach can also be used with systems with more complicated geometry (and in fact might be needed for computational efficiency), but you in theory run the risk of ending up in a local minimum that is different from the local minimum that you would get if you just relaxed the original structure with SOC the whole time.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-08-08T20:28:29.003" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9499" PostTypeId="2" ParentId="9468" CreationDate="2022-08-08T20:49:12.830" Score="1" Body="&lt;p&gt;They aren't determining the occupation from the shape of the orbital. The orbitals are computed with an unrestricted scheme, meaning &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spin electron are not required to pair up in the same spatial orbital. In other words, all orbitals in this case are either singly occupied or empty.&lt;/p&gt;&#xA;&lt;p&gt;The five simply comes from the fact that the HOMO and HOMO-n orbitals will be occupied and the LUMO and LUMO+n orbitals will be unoccupied.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-08-08T20:49:12.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9500" PostTypeId="1" CreationDate="2022-08-08T20:49:39.873" Score="3" ViewCount="97" Body="&lt;p&gt;I am trying to run an exciation energy calculation for a lithium atom. Is there a way to force the initial HF calculation to follow a specific excited state configuration, i.e. to skip or leave some shells empty?&lt;/p&gt;&#xA;&lt;p&gt;For example, I want to compute the energy of the state &amp;quot;1s2 3s1&amp;quot; so 2s orbital is skipped, but I received an error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCC input inconsistent with ms2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My input section looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;occ,1.1,3.1;WF,3,1,1;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5805" LastEditorUserId="5" LastEditDate="2023-02-18T05:58:12.783" LastActivityDate="2023-07-18T06:08:41.070" Title="Excited states of Lithium in MOLPRO" Tags="|excited-states|molpro|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9501" PostTypeId="2" ParentId="9495" CreationDate="2022-08-08T23:24:50.310" Score="7" Body="&lt;p&gt;Assuming that you have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; spatial orbitals, the total number of electron configurations that can be built is &lt;span class=&quot;math-container&quot;&gt;$$ N_{\rm confs} = {K  \choose N_\alpha} {K  \choose N_\beta} \approx {K  \choose N/2}^2 $$&lt;/span&gt; since typically &lt;span class=&quot;math-container&quot;&gt;$N_\alpha \approx N_\beta$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The exact solution is found by diagonalizing the configuration interaction (CI) Hamiltonian matrix, &lt;span class=&quot;math-container&quot;&gt;$H_{IJ} = \langle I | \hat{H} | J\rangle$&lt;/span&gt;. Although the matrix is typically huge (this is an understatement!), &lt;span class=&quot;math-container&quot;&gt;$N_{\rm confs} \times N_{\rm confs}$&lt;/span&gt;, it is also extremely sparse due to the &lt;a href=&quot;https://en.wikipedia.org/wiki/Slater%E2%80%93Condon_rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slater-Condon rules&lt;/a&gt;; the matrix elements between any two configurations that differ by more than a double excitation vanish. Moreover, the Hamiltonian is diagonally dominant, because the diagonal elements &lt;span class=&quot;math-container&quot;&gt;$H_{II}$&lt;/span&gt; are single-configuration (i.e. Hartree-Fock) energies.&lt;/p&gt;&#xA;&lt;p&gt;As a result, the lowest eigenstates of the full CI Hamiltonian matrix can be routinely determined with iterative methods; the famous &lt;a href=&quot;https://doi.org/10.1016/0021-9991(75)90065-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;Davidson method&lt;/a&gt; was designed for this purpose in the 1970s. Thanks to development of computers and algorithms, matrix sizes of a billion &lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt; a billion became feasible in the late 1980s, see &lt;a href=&quot;https://doi.org/10.1016/0009-2614(90)85633-N&quot; rel=&quot;nofollow noreferrer&quot;&gt;Olsen et al&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, due to the unforgiving exponential scaling of the number of configurations, the limits have not moved much since then. Tabulating the number of configurations obtained for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons in &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; orbitals, typically denoted as (&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;e,&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;o), one finds the following&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{array}{ll|ll}&#xA;N &amp;amp; N_\text{confs} &amp;amp; N &amp;amp; N_\text{confs} \\&#xA;\hline&#xA;\hline&#xA;1 &amp;amp; 1 &amp;amp; 11 &amp;amp; 2.1\times10^5 \\&#xA;2 &amp;amp; 4 &amp;amp; 12 &amp;amp; 8.5\times10^5 \\&#xA;3 &amp;amp; 9 &amp;amp; 13 &amp;amp; 2.9\times10^6 \\&#xA;4 &amp;amp; 36 &amp;amp; 14 &amp;amp; 1.2\times10^7 \\&#xA;5 &amp;amp; 100 &amp;amp; 15 &amp;amp; 4.1\times10^7 \\&#xA;6 &amp;amp; 400 &amp;amp; 16 &amp;amp; 1.7\times10^8 \\&#xA;7 &amp;amp; 1225 &amp;amp; 17 &amp;amp; 5.9\times10^8 \\&#xA;8 &amp;amp; 4900 &amp;amp; 18 &amp;amp; 2.4\times10^9 \\&#xA;9 &amp;amp; 15876 &amp;amp; 19 &amp;amp; 8.5\times10^9 \\&#xA;10 &amp;amp; 63504 &amp;amp; 20 &amp;amp; 3.4\times10^{10}&#xA;\end{array}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The (18e,18o) problem was thus feasible in the early 1990s. However, due to the unforgiving exponential scaling of the number of configurations, the limits have not moved that much since then. If you look at the literature, people often write (depending on the code and hardware at their use!) that full CI is limited in practice to (14e,14o) or (16e,16o) or (18e,18o).&lt;/p&gt;&#xA;&lt;p&gt;The largest full CI calculations I know were reported in &lt;a href=&quot;https://doi.org/10.1063/1.4989858&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 147, 184111 (2017)&lt;/a&gt;. The authors write in the abstract that (20e,20o) is routine with their new implementation and that they did a (22e,22o) calculation and a single CI iteration for the (24e,24o) problem; however, the text in Section V looks like only a single CI iteration was attempted for the (22e,22o) problem as well.&lt;/p&gt;&#xA;&lt;p&gt;So, in summary, FCI is still limited in practice to somewhere around (16e,16o) - unless you want to waste a lot of computational resources to correlate a few more electrons.&lt;/p&gt;&#xA;&lt;p&gt;The exponential scaling wall can, however, be pushed back a bit by being smart and leveraging the baked-in sparsity of the FCI problem with stochastic or selected CI methods developed by various authors. (You can see our recent paper &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b01255&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Another round is, of course, to reformulate the theory. We've done approximate (192e,192o) CASSCF for polyacenes with subtensor truncations of CCSDTQ56, see &lt;a href=&quot;https://doi.org/10.1080/00268976.2017.1342009&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mol. Phys. 116, 547 (2018)&lt;/a&gt;. For the (50e,50o) pi-space calculation, we captured over 95% of the exact correlation energy. The full-valence calculation for 12acene just adds in sigma correlation, which is more localized and thus should be pretty much exactly captured by the used method.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-08-11T04:37:28.637" LastActivityDate="2022-08-11T04:37:28.637" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9502" PostTypeId="1" AcceptedAnswerId="9504" CreationDate="2022-08-09T04:18:35.110" Score="12" ViewCount="2619" Body="&lt;p&gt;Since &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9476/what-does-machine-learning-learn-about-dft&quot;&gt;my previous question&lt;/a&gt; seems to have a large number of views, I would like to ask my central question.&lt;/p&gt;&#xA; I am a student now and should decide my major to research soon. AI/ML is a very hot research field and I am very interested in it, but I have some doubts before I study AI/ML.&lt;br&gt;&lt;Br&gt;&#xA;&lt;p&gt;For example, &lt;a href=&quot;https://arxiv.org/abs/2003.03123&quot; rel=&quot;noreferrer&quot;&gt;a paper&lt;/a&gt; that my professor told me is a famous research and has about 300 citations in two years. However, I found &lt;a href=&quot;https://github.com/gasteigerjo/dimenet/issues/13&quot; rel=&quot;noreferrer&quot;&gt;the GitHub issue of this paper&lt;/a&gt;, and &lt;strong&gt;the high-accurate ML model (called &lt;a href=&quot;https://github.com/gasteigerjo/dimenet&quot; rel=&quot;noreferrer&quot;&gt;DimeNet&lt;/a&gt;, which is a graph neural network model) can not predict the energy of hydrogen molecule at all (the error is over 100 kcal/mol!)&lt;/strong&gt;. The reason, according to the author of this paper, is that the training dataset (this paper used the benchmark &lt;a href=&quot;http://quantum-machine.org/datasets/&quot; rel=&quot;noreferrer&quot;&gt;QM9&lt;/a&gt;) does not include the hydrogen molecule. (&lt;strong&gt;It feels like an AI can not translate the sentence &amp;quot;I like cats&amp;quot; into German because &amp;quot;Ich liebe Katzen (I like cats)&amp;quot; does not exist in the training dataset.&lt;/strong&gt;)&lt;/p&gt;&#xA;&lt;p&gt;I have examined the QM9 benchmark dataset and display some molecules and their energies as follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FC3Te.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FC3Te.jpg&quot; alt=&quot;Fig.1&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As shown in this figure, many data samples have very similar molecular structures and energies, so I believe that &lt;strong&gt;even children can easily guess&lt;/strong&gt; the right-side (test) molecular energy by looking at the left-side (training) ones. Of course, the children has not solved the Kohn-Sham equation; the children just look and guess. That is, &lt;strong&gt;this is just a pattern matching&lt;/strong&gt; and I think this seems not to be physics at all.&lt;/p&gt;&#xA;&lt;p&gt;As I have posted the previous question, I now understand that transferring to different properties is a very difficult task. However, I believe that &lt;strong&gt;a physically-meaningful AI/ML model should be able to be transferred to various physical properties&lt;/strong&gt;; such a model is called &amp;quot;foundation model&amp;quot; in recent AI/ML. However, current research can not predict the hydrogen molecular energy if the training dataset does not include the hydrogen molecular energy.&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="5" LastEditDate="2022-08-09T21:14:09.723" LastActivityDate="2022-08-11T15:14:27.627" Title="Artificial intelligence is a hot topic, but should I pursue it if I'm interested in Matter Modeling?" Tags="|density-functional-theory|mathematical-modeling|machine-learning|education|cheminformatics|" AnswerCount="3" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="9503" PostTypeId="2" ParentId="9495" CreationDate="2022-08-09T05:51:50.993" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;it must be possible to conclusively argue where the exponential wall lies and how it comes to be.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The location of the &amp;quot;wall&amp;quot; depends on which &amp;quot;wall&amp;quot;. With FCI you will hit a wall if you:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;try to correlate too many electrons (even if you keep everything else the same), or&lt;/li&gt;&#xA;&lt;li&gt;try to have too many orbitals in your basis set (even if you keep everything else the same).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For example, &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9501/5&quot;&gt;Susi's answer correctly shows that&lt;/a&gt; if you want to correlate 20 electrons, then involving 20 spatial orbitals would be quite difficult. However, with 4 electrons, I found it extremely easy to (&lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/B%2B/7z_i.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;for example&lt;/a&gt;) do an FCI calculation involving 377 spatial orbitals many years ago.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps a better &amp;quot;wall&amp;quot; to consider is the wall that you hit when you:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;try to involve too many Slater determinants.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you would like to do a calculation involving (22e,22o) and all ~34 billion Slater determinants with double precision (8 bytes per real number), then storing the amplitudes of the determinants alone would require about 8 x 34 billion = 272 GB and storing the bit-strings associated with these determinants would require approximately another (20 x 2 x 34 billion)/8 =  170 GB (20 spatial orbitals x 2 spin orbitals per spatial orbital x 34 billion bit-strings, divided by 8 bits for each byte). In total, storing this data alone would require 442 GB, and:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;it would be too slow if this were to be stored on a hard drive, and&lt;/li&gt;&#xA;&lt;li&gt;storing this data in the RAM across multiple nodes&#xA;would significantly complicate things, to the extent that this is not typically done in the high-performance FCI codes available today,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;so you would likely need a single node with at least 512GB to do this (20e,20o) calculation. This is not uncommon at the &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1515/5&quot;&gt;various supercomputing centres&lt;/a&gt; that have been discussed on this site, but nodes with this much RAM are still considered a precious commodity and even among the &amp;quot;elite&amp;quot; people who have access to such machines, the vast majority will rarely get an opportunity to run an FCI calculation on such a machine for long enough to get convergence. There is also a way to reduce the RAM required without ignoring any of the Slater determinants, and this is what would &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/7138/5&quot;&gt;allow MRCC to do trillion-determinant FCI calculations with fewer than 8 trillion bytes of RAM&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;But&lt;/strong&gt;&lt;/em&gt; not all FCI Slater determinants are needed in order to get the FCI energy correctly to within nano-hartree precision (for example) and real-world applications rarely find more than the micro-hartree digit to be relevant.&lt;/p&gt;&#xA;&lt;p&gt;The next and probably the &lt;em&gt;&lt;strong&gt;most important&lt;/strong&gt;&lt;/em&gt; &amp;quot;wall&amp;quot; that you can hit is the one which you reach when you want to involve too many &amp;quot;important&amp;quot; determinants for your specific application. I think the most I ever used in &lt;a href=&quot;https://arxiv.org/abs/2006.14956&quot; rel=&quot;nofollow noreferrer&quot;&gt;FCIQMC&lt;/a&gt; was 130 billion determinants for a (54e,54o) calculation on FeMoco but I never published it, largely because of the rise of improved methods which can estimate the FCI energy more accurately with smaller resources. The calculation with about 130 billion determinants gave an energy of about -13482.174 Hartree which is 2-3 mH higher than with FCIQMC-PT2 when using only 100 million determinants, and 4 mH higher than obtained with extrapolated SHCI-PT2 calculations, and about 8 mH higher than some of the lowest estimates I found overall.&lt;/p&gt;&#xA;&lt;p&gt;To conclude, &lt;strong&gt;perhaps the largest published serious attempt at an FCI calculation was for the (54e,54o) system in &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5063376&quot; rel=&quot;nofollow noreferrer&quot;&gt;my FeMoco paper&lt;/a&gt;&lt;/strong&gt;, in which the energy we obtained is the correct FCI energy with an error bar of &amp;quot;only&amp;quot; a few kcal/mol (I say &amp;quot;only&amp;quot; because this is a calculation for a system which has about 4 x 10^30 determinants!), but anyone can do a calculation on a slightly larger (55e,55o) system and just not converge the energy to the accuracy that we did, so this is why I said it's perhaps the largest published &amp;quot;serious&amp;quot; attempt at an FCI calculation.&lt;/p&gt;&#xA;&lt;p&gt;In a comment you mentioned that you're interested in density matrices. Density matrix calculations typically require twice as much RAM and twice as much CPU time compared to basic energy calculations that are calculated while involving nothing more than a wavefunction. Denisty matrices have indeed been calculated for that (54e,54o) system (for example in the above-mentioned FCIQMC-PT2 calculation).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="142" LastEditDate="2022-08-11T04:15:23.547" LastActivityDate="2022-08-11T04:15:23.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9504" PostTypeId="2" ParentId="9502" CreationDate="2022-08-09T06:46:28.860" Score="15" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I am a student now and should decide my major to research soon. AI/ML is a very hot research field and I am very interested in it, but I have some doubts before I study AI/ML.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;AI is indeed a hot topic, and there's plenty of reasons to have doubts before committing yourself 100% to a field, but:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I found the GitHub issue of this paper, and the high-accurate ML model (called DimeNet, which is a graph neural network model) cannot predict the energy of hydrogen molecule at all (the error is over 100 kcal/mol!). The reason, according to the author of this paper, is that the training dataset (this paper used the benchmark QM9) does not include the hydrogen molecule.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But this is what the author &lt;em&gt;&lt;strong&gt;actually&lt;/strong&gt;&lt;/em&gt; said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;From a physical perspective the H2 molecule is certainly the simplest molecule there is, but from the QM9 data perspective this is an extreme outlier. There are no H-H bonds in the QM9 dataset&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Saying that a dataset does not involve &amp;quot;any H-H bonds&amp;quot; is different from saying that it &amp;quot;does not include the hydrogen molecule&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;You're making it seem like machine learning doesn't work unless it has been trained on exactly the same system for which you want to make a prediction, which is not true. For example, to predict the energy for C&lt;sub&gt;2&lt;/sub&gt;, the author is &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; claiming that you would need C&lt;sub&gt;2&lt;/sub&gt; to be in the training set, as long as enough molecules with C-C bonds (like most organic molecules) were to be in the training set.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I believe that &lt;strong&gt;even children can easily guess&lt;/strong&gt; the right-side (test) molecular energy by looking at the left-side (training) ones.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Perhaps that's true in this one very specific case from a cherry-picked paper. &lt;strong&gt;It does not mean that all machine learning papers demonstrate no more than what &amp;quot;children&amp;quot; can predict on their own.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;AI is a very hot field for a good reason. &lt;em&gt;&lt;strong&gt;AI more than just machine learning.&lt;/strong&gt;&lt;/em&gt; Machine learning is also more than just pattern recognition. For example &lt;a href=&quot;https://en.wikipedia.org/wiki/Reinforcement_learning&quot; rel=&quot;noreferrer&quot;&gt;reinforcement learning&lt;/a&gt; is what was used when AlphaGo beat a human at Go, and has applications in self-driving cars and other autonomous vehicles (&lt;a href=&quot;https://uwaterloo.ca/watonobus/&quot; rel=&quot;noreferrer&quot;&gt;the University of Waterloo already offers people on campus an autonomous bus&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;In terms of matter modeling, DeepMind (the same company that made AlphaGo) made AlphaFold for protein folding, and AlphaFold has won competitions. DeepMind also made &lt;a href=&quot;https://github.com/deepmind/ferminet&quot; rel=&quot;noreferrer&quot;&gt;FermiNet&lt;/a&gt; which does seem to calculate variational electronic &lt;em&gt;ab initio&lt;/em&gt; energies of some systems, which are lower than any other energies calculated (using for example variational Monte Carlo, or diffusion Monte Carlo, or direct &lt;a href=&quot;/questions/tagged/full-configuration-interaction&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;full-configuration-interaction&amp;#39;&quot; rel=&quot;tag&quot;&gt;full-configuration-interaction&lt;/a&gt; solvers). This is truly state-of-the-art research and its thanks to the enormous wealth of valuable insight that artificial intelligence researchers have brought to the world in recent years. Many other examples of applications can be found in our &lt;a href=&quot;/questions/tagged/machine-learning&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;machine-learning&amp;#39;&quot; rel=&quot;tag&quot;&gt;machine-learning&lt;/a&gt; tag.&lt;/p&gt;&#xA;&lt;p&gt;Finally, I do very much appreciate that there's still reasons to be skeptical about how useful AI will be to matter modeling, but I would not at all discourage you from entering the field of AI. Jobs in AI are far more abundant than jobs in matter modeling and often pay 10x more (it is no exaggeration that a lot of AI researchers at Google, Apple, OpenAI and other places earn more than \$1 million/year). Even someone as young as Ian Goodfellow, who did not have a single paper published before 2009, &lt;a href=&quot;https://www.forbes.com/sites/samshead/2018/04/20/ai-geniuses-are-being-paid-over-1-million-at-elon-musks-openai/?sh=42e45c29113b&quot; rel=&quot;noreferrer&quot;&gt;had a salary of \$800,000/year almost immediately after completing his PhD&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Even outside of science, people working in law, education, writing, finance, and many other fields are increasingly using AI, and in many ways it's becoming a form of literacy. Saying that you're too skeptical about it would be like saying you're skeptical about learning math, or computer programming.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-08-09T06:46:28.860" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9505" PostTypeId="5" CreationDate="2022-08-09T06:55:45.040" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-09T06:55:45.040" LastActivityDate="2022-08-09T06:55:45.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9506" PostTypeId="4" CreationDate="2022-08-09T06:55:45.040" Score="0" Body="Questions about electron transport." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-09T06:55:45.040" LastActivityDate="2022-08-09T06:55:45.040" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9507" PostTypeId="1" CreationDate="2022-08-09T09:16:12.233" Score="1" ViewCount="36" Body="&lt;p&gt;We know the magnetic susceptibility for a non-interacting tight-binding model has the Lindhardt form, for which I express as product of matsubara Green's functions&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi^{(0)}(q,\omega)=-\beta\sum_{k,\nu,abcd} G^{ad}(k,\nu)G^{cb}(k+q,\nu+\omega) $$&lt;/span&gt;&lt;span class=&quot;math-container&quot;&gt;$abcd$&lt;/span&gt; are orbital index.&#xA;Specifically, provide no SOC, the &lt;span class=&quot;math-container&quot;&gt;$zz-$&lt;/span&gt;component&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi^{(0)}_{zz}=\langle S^z S^z\rangle=\frac{1}{2} [ \chi^{(0)}_{\uparrow\uparrow\uparrow\uparrow}\ -\chi^{(0)}_{\uparrow\uparrow\downarrow\downarrow}\ \ ]=\frac{1}{2}  \chi^{(0)}_{\uparrow\uparrow\uparrow\uparrow}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, if we rotate the Hamiltonian to a different basis set, for example from spherical harmonics to cubic harmonics by matrix &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, then the Green's functions are replaced as &lt;span class=&quot;math-container&quot;&gt;$T^\dagger GT$&lt;/span&gt;, and the invariance of &lt;span class=&quot;math-container&quot;&gt;$\chi^{(0)}$&lt;/span&gt; is broke. However in principle it should be invariance since it associated with neutron scattering experiment.&lt;/p&gt;&#xA;&lt;p&gt;Where is the problem?&lt;/p&gt;&#xA;" OwnerUserId="4741" LastEditorUserId="4741" LastEditDate="2022-08-09T09:45:10.467" LastActivityDate="2022-08-09T09:45:10.467" Title="Invariance of magnetic susceptibility when rotating a tight-binding Hamiltonian" Tags="|condensed-matter|model-hamiltonians|greens-functions|neutron-scattering|lindhard-theory|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T21:50:59.863" ContentLicense="CC BY-SA 4.0" />
  <row Id="9508" PostTypeId="2" ParentId="9502" CreationDate="2022-08-09T10:32:33.343" Score="8" Body="&lt;p&gt;I did my master's research project in predicting absorption spectra using machine learning (with fingerprints). So, my research is somewhat in the field of material modelling you can say. I want to add my two cents to the discussion.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As shown in this figure, many data samples have very similar molecular structures and energies, so I believe that even children can easily guess the right-side (test) molecular energy by looking at the left-side (training) ones. Of course, the children has not solved the Kohn-Sham equation; the children just look and guess. That is, this is just a pattern matching and I think this seems not to be physics at all.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;It is absolutely true that machine learning models are essentially looking for patterns in the training dataset. But I don't think it is a bad thing. Because looking for patterns is all we do, in fact, I would argue that it is the only thing we can do. You are making a distinction between physics and pattern matching, but I think this distinction is an illusion.&lt;/p&gt;&#xA;&lt;p&gt;It's not like we have access to the source code of the universe. So what we do (our brains) is look for patterns of events that seem to follow the same rule. For example, we see that oppositely charged particles attract each other, and same charged particles repel. We look at the pattern, and we guess that there must be a rule the particles are following. Then we measure the forces, and find that we can write the rule down as a mathematical equation—this is the Coulomb force. But please notice that there has to be a pattern for us to perceive in the first place.&lt;/p&gt;&#xA;&lt;p&gt;If that sounds too philosophical, look at it from a practical point of view. When we are dealing with forces between charged particles, the patterns are simple enough to be represented perfectly by a simple analytical expression. When we are predicting the energy of a molecule from its structure, there is no simple expresssion that we have found. But our intuition tells us there must be a pattern, so we use machine learning models. We feed the model huge amounts of data, in the hope that it can find the underlying pattern that is actually there. If the ML model does not work, that means it did not find the actual pattern, but it does not mean the whole methodology has to be discarded.&lt;/p&gt;&#xA;&lt;p&gt;Ideally, your ML model would work on any new molecule that you throw at it, but in practice it never does. ML models work best if they have seen molecules similar to it in the training set (similar, not same). For example, in my research, I found that molecules had &lt;span class=&quot;math-container&quot;&gt;$&amp;lt; 0.02$&lt;/span&gt; eV error in predicting excitation energies, if the training set had &lt;span class=&quot;math-container&quot;&gt;$&amp;gt; 10$&lt;/span&gt; molecules with &lt;span class=&quot;math-container&quot;&gt;$&amp;gt;0.7$&lt;/span&gt; similarity coefficient.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2022-08-09T10:32:33.343" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9509" PostTypeId="1" CreationDate="2022-08-10T07:27:44.083" Score="9" ViewCount="517" Body="&lt;p&gt;The Kohn-Sham equations are given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(-\frac{\hbar^2}{2m} \nabla_{i}^{2}+V_{s}\left(\hat{\boldsymbol{r}}_{i}\right)+V_{H}\left(\hat{\boldsymbol{r}}_{i}\right)+V_{X C}\left(\hat{\boldsymbol{r}}_{i}\right)\right) \psi_{i}(\boldsymbol{r})=\epsilon_{i} \psi_{i}(\boldsymbol{r})&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$V_s$&lt;/span&gt; is the electrostatic potential due to &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; nuclei felt by the &lt;span class=&quot;math-container&quot;&gt;$i^{\text {th}}$&lt;/span&gt; electron,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{s}\left(\boldsymbol{r}_{i}\right)=-\frac{e^{2}}{4 \pi \epsilon_{0}} \sum_{I=1}^{N} \frac{Z_{I}}{\left|\boldsymbol{r}_{i}-\boldsymbol{R}_{I}\right|} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the mean-field potential (also called the Hartree potential) felt by the &lt;span class=&quot;math-container&quot;&gt;$i^{\text {th}}$&lt;/span&gt; electron is given by averaging the remaining &lt;span class=&quot;math-container&quot;&gt;$(n-1)$&lt;/span&gt; electrons as a smooth distribution of negative charge with electron number density &lt;span class=&quot;math-container&quot;&gt;$\rho_{n}$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{H}\left(\boldsymbol{r}_{i}\right)=\frac{e^{2}}{4 \pi \epsilon_{0}} \int \frac{\rho_{n}\left(\boldsymbol{r}^{\prime}\right)}{\left|\boldsymbol{r}_{i}-\boldsymbol{r}^{\prime}\right|} d \boldsymbol{r}^{\prime}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$V_{XC}({\boldsymbol{r}})$&lt;/span&gt; is the exchange-correlation &amp;quot;potential&amp;quot; felt by the &lt;span class=&quot;math-container&quot;&gt;$i^{\text {th}}$&lt;/span&gt; electron,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{XC}(\boldsymbol{r}_i)=\frac{\delta E_{X C}\left[\rho_{n}\right]}{\delta \rho_{n}(\boldsymbol{r}_i)}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The exchange-corelation functional contains all the many-body effects. It includes all classical and quantum effects and corrections not already accounted for by &lt;span class=&quot;math-container&quot;&gt;$V_s$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt;. These include the exchange effects due to the Pauli exclusion principle, the short-range Coulomb correlations not accounted by the Hartree term, and the kinetic energy difference between the interacting and non-interacting electrons.&lt;/p&gt;&#xA;&lt;p&gt;My question is how come the Kohn-Sham equations are considered &lt;strong&gt;single-particle&lt;/strong&gt; equations when the &lt;span class=&quot;math-container&quot;&gt;$V_{XC}$&lt;/span&gt; term is essentially a &lt;strong&gt;many-particle&lt;/strong&gt; quantity?&lt;/p&gt;&#xA;&lt;p&gt;I found a related question here &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4680/how-can-we-say-that-the-ks-equation-is-describing-a-noninteracting-many-electron&quot;&gt;How can we say that the KS equation is describing a noninteracting many-electron system?&lt;/a&gt; which is similar to my question; however, the question there is about &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; not &lt;span class=&quot;math-container&quot;&gt;$V_{XC}$&lt;/span&gt;. I can perceive that &lt;span class=&quot;math-container&quot;&gt;$V_s$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V_H$&lt;/span&gt; are external potentials coming from the nuclei and the mean-field approximation of the electrons, but how the presence of a many-body term is reconciled with this single-particle picture?&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="5" LastEditDate="2022-08-20T15:03:36.957" LastActivityDate="2022-08-20T15:03:36.957" Title="Why Kohn-Sham equations are regarded as single-particle equations?" Tags="|density-functional-theory|kohn-sham|exchange-correlation|" AnswerCount="2" CommentCount="4" FavoriteCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9510" PostTypeId="2" ParentId="9424" CreationDate="2022-08-10T10:15:42.520" Score="4" Body="&lt;p&gt;I will quote the manual. :)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It is &lt;em&gt;extremely&lt;/em&gt; important that the electrodes only interact&#xA;with one neighboring supercell due to the self-energy&#xA;calculation &lt;a href=&quot;http://iopscience.iop.org/0305-4608/15/4/009&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, TranSiesta will print out a block as this&#xA;(&lt;code&gt;&amp;lt;&amp;gt;&lt;/code&gt; is the electrode name):&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;lt;&amp;gt; principal cell is perfect!&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;if the electrode is correctly setup and it only interacts with its&#xA;neighboring supercell.&lt;br /&gt;&#xA;In case the electrode is erroneously setup, something similar to the&#xA;following will be shown in the output file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;lt;&amp;gt; principal cell is extending out with 96 elements:&#xA;Atom 1 connects with atom 3&#xA;Orbital 8 connects with orbital 26&#xA;Hamiltonian value: |H(8,6587)|@R=-2 =  0.651E-13 eV&#xA;Overlap          :  S(8,6587)|@R=-2 =   0.00    &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It is imperative that you have a &lt;em&gt;perfect&lt;/em&gt; electrode as otherwise&#xA;nonphysical results will occur. This means that you need to add more&#xA;layers in your electrode calculation (and hence also in your&#xA;scattering region). An example is an ABC stacking electrode. If the&#xA;above error is shown one &lt;em&gt;has&lt;/em&gt; to create an electrode with ABCABC&#xA;stacking in order to retain periodicity.&lt;br /&gt;&#xA;By default TranSiesta will die if there are connections beyond the&#xA;principal cell. One may control whether this is allowed or not by&#xA;using &lt;code&gt;TS.Elecs.Neglect.Principal&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To expand on this.&lt;/p&gt;&#xA;&lt;p&gt;The self-energy calculation has these restrictions on the connectivity &lt;em&gt;along the semi-infinite direction&lt;/em&gt;. There are no restrictions on the transverse directions.&lt;br /&gt;&#xA;In fact, TranSiesta/TBtrans can get much better performance if one can utilize Bloch's theorem (see the &lt;code&gt;Bloch&lt;/code&gt; keyword in the electrode block).&#xA;It only requires the ordering of the electrode region to be set in a specific manner.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2024-03-08T11:36:05.600" LastActivityDate="2024-03-08T11:36:05.600" CommentCount="0" CommunityOwnedDate="2022-08-10T23:00:55.383" ContentLicense="CC BY-SA 4.0" />
  <row Id="9511" PostTypeId="1" AcceptedAnswerId="9527" CreationDate="2022-08-10T20:07:34.113" Score="3" ViewCount="412" Body="&lt;p&gt;I've run some calculations with the &lt;code&gt;xtb&lt;/code&gt; software. From its output I got &lt;code&gt;XYZ&lt;/code&gt; and &lt;code&gt;MOL&lt;/code&gt; files with the system's structure information, and also a &lt;code&gt;charge&lt;/code&gt; file with the calculated charges.&lt;/p&gt;&#xA;&lt;p&gt;I would like to merge these two files into one or to create a new one (one that supports the charges like &lt;code&gt;MOL&lt;/code&gt; or &lt;code&gt;MOL2&lt;/code&gt;) with the charges added.&lt;/p&gt;&#xA;&lt;p&gt;As there are a lot of files to merge, making the process automatic will decrease the errors.&lt;/p&gt;&#xA;&lt;p&gt;Here is the &lt;code&gt;MOL&lt;/code&gt; output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; xtb: 6.5.1 (579679a)&#xA;          08092221593D&#xA;&#xA;140170  0     0  0            999 V2000&#xA;    2.6154    6.4064    0.9956 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.8578    2.7738    1.5382 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    8.7755    1.6888    2.8422 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.3803    4.0139    3.6724 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   14.4811    8.0604    3.5495 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   14.7628   12.5956    3.8804 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.2314   15.9121    5.2439 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    8.0491   16.1020    6.2971 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.3849   13.8269    6.4268 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.9317   10.3116    6.0240 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.5655    5.6280    2.1771 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    5.1268    2.3726    2.8718 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.0773    2.2650    4.1013 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.0035    5.2635    4.2054 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.5944    9.1063    3.2349 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.8120   13.3380    3.1439 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.1970   16.3391    4.3698 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    7.1033   16.0816    5.2396 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.7923   13.4377    5.2013 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.8727    9.6802    4.7586 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.3785    7.7477    1.0115 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.9239    3.7276    1.2646 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    7.4778    1.5634    2.4333 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.4867    2.9689    3.6452 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   14.0231    6.7778    3.7699 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   14.8634   11.2314    3.7574 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.2537   15.1192    4.8081 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.3682   16.3578    6.0715 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    5.3899   14.7451    6.4745 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.4918   11.5427    6.1782 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.0483    6.2519    3.3426 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.1735    2.7427    3.8532 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    8.0189    2.3406    5.0369 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.7860    5.3145    4.9239 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.2136    8.7905    3.1968 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.1029   12.6442    2.1282 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.4425   16.2051    2.9792 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    7.5166   16.6283    3.9997 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.1292   14.1863    4.0465 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.2291   10.4449    3.6202 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.7997    5.4842    4.5093 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.3387    2.3324    5.2019 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    8.1671    3.0483    6.2595 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.1209    6.5319    5.2123 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.2534    9.6203    2.5774 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.3500   13.3264    1.1466 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.5758   16.8019    2.0305 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    6.5915   16.7546    2.9314 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.5515   13.8555    2.7932 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.1840    9.8586    2.3280 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.1162    8.4415    2.2180 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.1644    4.3427    2.2940 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    6.3936    1.8785    3.2932 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.2644    3.0226    4.3495 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.6538    6.5197    3.9629 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.8757   10.5024    3.0610 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   13.2525   14.6070    3.4858 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.8563   16.6076    4.7638 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    5.8565   15.3993    5.3093 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.9690   12.2844    5.0728 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.8844    7.6630    3.3789 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.1807    3.7133    3.5633 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    6.6914    2.0049    4.6747 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.0670    4.1338    5.2103 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.7676    7.6173    3.8365 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.9660   11.2456    2.2735 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.3952   15.2449    2.5579 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    8.8910   16.8909    3.7647 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    5.1088   15.2137    4.1167 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.6925   11.7802    3.7750 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.1823    6.1326    5.6093 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.2381    2.5050    6.0837 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    7.2235    2.8209    7.2901 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.1335    6.5533    6.2147 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.8922    9.4440    2.8898 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.4589   12.5836    0.3322 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.8812   16.6308    0.6495 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    7.0004   17.5061    1.7965 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    3.7126   14.7775    1.7314 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.3234   10.7199    1.2150 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.5821    8.2989    4.6110 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.3389    4.1816    4.6048 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    5.6556    2.0803    5.6374 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.0411    4.1580    6.1804 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   10.4451    7.5992    4.3331 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   11.7517   10.6933    1.7928 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   12.2292   14.7312    1.2441 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    9.3032   17.2384    2.4518 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA; 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97137  1  0  0  0  0&#xA; 98138  1  0  0  0  0&#xA; 99139  1  0  0  0  0&#xA;100140  1  0  0  0  0&#xA;M  END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the &lt;code&gt;charge&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   -0.03722231&#xA;   -0.03646360&#xA;   -0.03466408&#xA;   -0.03460579&#xA;   -0.03700567&#xA;   -0.03830432&#xA;   -0.03743637&#xA;   -0.03678821&#xA;   -0.03708334&#xA;   -0.03759946&#xA;    0.00341706&#xA;    0.00262820&#xA;    0.00029768&#xA;    0.00086030&#xA;    0.00393716&#xA;    0.00505315&#xA;    0.00341478&#xA;    0.00243039&#xA;    0.00241051&#xA;    0.00266387&#xA;   -0.03697613&#xA;   -0.03683137&#xA;   -0.03764684&#xA;   -0.03827265&#xA;   -0.03653021&#xA;   -0.03436292&#xA;   -0.03497639&#xA;   -0.03671793&#xA;   -0.03724731&#xA;   -0.03728009&#xA;    0.00104757&#xA;    0.00049263&#xA;    0.00207651&#xA;    0.00321830&#xA;    0.00222174&#xA;    0.00127540&#xA;    0.00206366&#xA;    0.00229686&#xA;    0.00224290&#xA;    0.00189821&#xA;    0.00330899&#xA;    0.00455347&#xA;    0.00472102&#xA;    0.00365930&#xA;    0.00259012&#xA;    0.00170297&#xA;    0.00134970&#xA;    0.00213949&#xA;    0.00282399&#xA;    0.00313627&#xA;    0.00237572&#xA;    0.00250757&#xA;    0.00375430&#xA;    0.00511583&#xA;    0.00341053&#xA;    0.00041637&#xA;    0.00067468&#xA;    0.00294210&#xA;    0.00339482&#xA;    0.00307549&#xA;    0.00225484&#xA;    0.00229451&#xA;    0.00190616&#xA;    0.00130541&#xA;    0.00249185&#xA;    0.00319625&#xA;    0.00168094&#xA;    0.00045411&#xA;    0.00125032&#xA;    0.00200113&#xA;   -0.03773413&#xA;   -0.03747374&#xA;   -0.03777553&#xA;   -0.03792015&#xA;   -0.03639454&#xA;   -0.03541961&#xA;   -0.03566344&#xA;   -0.03655314&#xA;   -0.03719833&#xA;   -0.03727186&#xA;    0.00273925&#xA;    0.00195800&#xA;    0.00134150&#xA;    0.00181929&#xA;    0.00281034&#xA;    0.00384329&#xA;    0.00486636&#xA;    0.00431232&#xA;    0.00314034&#xA;    0.00260470&#xA;   -0.03713453&#xA;   -0.03636143&#xA;   -0.03555836&#xA;   -0.03549570&#xA;   -0.03669229&#xA;   -0.03802718&#xA;   -0.03766679&#xA;   -0.03750089&#xA;   -0.03776054&#xA;   -0.03752020&#xA;    0.03161620&#xA;    0.03281056&#xA;    0.03326035&#xA;    0.03226115&#xA;    0.03226474&#xA;    0.03351993&#xA;    0.03406948&#xA;    0.03286813&#xA;    0.03183449&#xA;    0.03171993&#xA;    0.03197441&#xA;    0.03313788&#xA;    0.03413108&#xA;    0.03325210&#xA;    0.03214467&#xA;    0.03243500&#xA;    0.03333614&#xA;    0.03256787&#xA;    0.03146893&#xA;    0.03150533&#xA;    0.03233615&#xA;    0.03409028&#xA;    0.03608529&#xA;    0.03407825&#xA;    0.03155533&#xA;    0.03339691&#xA;    0.03529538&#xA;    0.03388412&#xA;    0.03228017&#xA;    0.03141505&#xA;    0.03254266&#xA;    0.03420700&#xA;    0.03527684&#xA;    0.03276537&#xA;    0.03177783&#xA;    0.03467319&#xA;    0.03596630&#xA;    0.03361589&#xA;    0.03217072&#xA;    0.03167577&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2022-08-13T04:26:20.647" LastActivityDate="2022-08-13T04:26:20.647" Title="How to merge two files (molecule structure and file property) into one?" Tags="|python|geometry|programming|xtb|charged-molecules|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9512" PostTypeId="1" CreationDate="2022-08-11T01:04:10.680" Score="5" ViewCount="94" Body="&lt;p&gt;I am trying to learn to do Green's function calculations. Are there any good introductory books about the Green's function method?&lt;/p&gt;&#xA;" OwnerUserId="5532" LastEditorUserId="5" LastEditDate="2022-08-11T03:37:50.643" LastActivityDate="2022-08-11T03:37:50.643" Title="Good books about green's function method" Tags="|reference-request|greens-functions|" AnswerCount="0" CommentCount="5" ClosedDate="2023-02-18T13:22:04.823" ContentLicense="CC BY-SA 4.0" />
  <row Id="9513" PostTypeId="2" ParentId="9509" CreationDate="2022-08-11T04:28:54.613" Score="2" Body="&lt;p&gt;I would argue that because the exact potential, like the ground state density, is a property of the system. The Hohenberg-Kohn theorems show that there is a scalar single-particle potential &lt;span class=&quot;math-container&quot;&gt;$v({\bf r})$&lt;/span&gt; that generates orbitals that minimize the energy, no? And the Kohn-Sham equation for the exact potential is a single-particle equation.&lt;/p&gt;&#xA;&lt;p&gt;It does not matter that the potential depends implicitly on the orbitals, since it is still only a single-particle operator unlike the real molecular Hamiltonian that has terms that couple orbitals together.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-08-11T13:40:56.280" LastActivityDate="2022-08-11T13:40:56.280" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="9514" PostTypeId="2" ParentId="9502" CreationDate="2022-08-11T15:14:27.627" Score="4" Body="&lt;p&gt;While machine learning is becoming very important, I think &lt;strong&gt;physics-based models continue to be necessary in matter modeling&lt;/strong&gt;. ML models are good for systems where there is a lot of data available. On the other hand, physics-based models can often be applied for more exotic systems that have been poorly studied in the past. Indeed, physics-based models are often needed to supply data to the AI models.&lt;/p&gt;&#xA;&lt;p&gt;For example, consider that you want the energy of the molecules in the study you cited, but instead of in gas phase, you want the energy at a silicon (111) surface. Or under a high magnetic field. Or instead of organic molecules you are interested in the energies of boron–oxygen and boron–nitrogen clusters. For these situations, you will probably find very little data available and will need to perform quantum chemistry calculations to get the data necessary to train the AI model.&lt;/p&gt;&#xA;&lt;p&gt;So, if you like physical models, there is probably still plenty of room for developing expertise in physical models. However, I think there is no doubt you will also find ML to be useful in analyzing the results of the physical models and developing useful predictions from them.&lt;/p&gt;&#xA;&lt;p&gt;But as ML and physics-based methods get increasingly complex, people will probably tend to specialize in one or other. In the future, matter modeling will probably have experts in ML who dabble in physics-based methods and experts in physics-based methods who dabble in ML.&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2022-08-11T15:14:27.627" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9515" PostTypeId="1" CreationDate="2022-08-12T00:38:00.730" Score="7" ViewCount="458" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/g7GBHs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/g7GBHs.png&quot; alt=&quot;Dark Gray atoms are carbons, and read is an oxygen&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you know, oxygen has two available states. However, the picture above illustrates oxygen (red) has a just one bonding with one carbon. I am kind of afraid it makes differences compared that an oxygen has two bondings with another carbon. To my knowledge bonding is nothing but overlapping &amp;quot;probability clouds&amp;quot; to find electrons between two atoms. Bonding is just chemical expression to see it intuitively.&lt;/p&gt;&#xA;&lt;p&gt;Do you think my result is different with the one has additional bonding with another carbon atom?&lt;/p&gt;&#xA;" OwnerUserId="5806" LastEditorUserId="5" LastEditDate="2022-08-13T14:10:22.063" LastActivityDate="2022-08-13T14:10:22.063" Title="Do bonds between the atoms influence ab-initio energies?" Tags="|computational-chemistry|molecular-modeling|ab-initio-calculations|electronic-structure|gaussian|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9516" PostTypeId="2" ParentId="9515" CreationDate="2022-08-12T01:47:50.967" Score="13" Body="&lt;p&gt;The bonds you draw or see in Gaussview should have no effect on the calculation (besides some minor effects in choosing internal coordinates for a geometry optimization). As you note, a bond is a chemical concept rather than a quantum mechanical one; an electronic structure calculation depends on the molecular Hamiltonian (or some approximation of it) which doesn't include any notion of individual bonds, just charges and distances between them.&lt;/p&gt;&#xA;&lt;p&gt;Programs like Gaussview try to give a chemists view of a molecule by drawing bonds. The way it decides what is bonded generally isn't too sophisticated; usually a bond is drawn if a pair of elements A-B is closer than some threshold value chosen to represent a typical bond for those two species.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-08-12T01:47:50.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9517" PostTypeId="1" CreationDate="2022-08-12T08:51:33.380" Score="5" ViewCount="110" Body="&lt;p&gt;Is there a book or tabulated work where the configuration state functions of atoms have been documented? Just as useful would be information about computer programs that are able to predict the CSFs.&lt;/p&gt;&#xA;" OwnerUserId="5837" LastEditorUserId="5" LastEditDate="2022-08-12T20:02:20.543" LastActivityDate="2022-08-12T20:19:00.210" Title="Finding the Configuration State Functions of Atoms" Tags="|computational-chemistry|reference-request|configuration-interaction|atomic-physics|graphical-unitary-group-approach|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9518" PostTypeId="1" AcceptedAnswerId="9543" CreationDate="2022-08-12T16:16:48.023" Score="5" ViewCount="182" Body="&lt;p&gt;I am currently working on python script that does Hartree-Fock-Calculations. I try to avoid packages as good as possible. I've figured out how to calculate the one electron integrals when it comes to the Roothaan-Hall-Equations through this &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/2007/2007.12057.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. I am now stuck however at calculating the two electron integrals. I've gathered that there are several recursive methods one can use since the analytical methods are quite inefficient for the vast amount of integrals that are needed to be calculated. I am however struggling with figuring out which algorithm is best for my problem and where to find literature on that. I am using a STO-3G basis set and maybe a 6-31G one. There are no shells that surpass an angular-momentum quantum number of 2.&lt;/p&gt;&#xA;&lt;p&gt;Therefore my question is: &lt;strong&gt;What algorithm is the best for a closed shell molecule when I'm using a STO-3G / 6-31G basis set?&lt;/strong&gt; Can you provide me with literature that is at least somewhat easy to understand?&lt;/p&gt;&#xA;" OwnerUserId="5707" LastEditorUserId="5" LastEditDate="2022-08-12T20:04:33.423" LastActivityDate="2022-08-15T16:58:28.713" Title="What is the best algorithm for ERIs of contracted gaussian atomic orbitals" Tags="|quantum-chemistry|quantum-mechanics|basis-sets|hartree-fock|integrals|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9519" PostTypeId="1" AcceptedAnswerId="9520" CreationDate="2022-08-12T17:50:45.223" Score="4" ViewCount="172" Body="&lt;p&gt;Is there an online database having information on molecules with a certain number of atoms? For example, properties of tri-atomic molecules?&lt;/p&gt;&#xA;&lt;p&gt;There is this &lt;a href=&quot;https://www.nist.gov/pml/triatomic-spectral-database/triatomic-spectral-database-appendix&quot; rel=&quot;nofollow noreferrer&quot;&gt;table&lt;/a&gt; that I got from NIST which gives a few, but it would be nice to know if more such lists exist.&lt;/p&gt;&#xA;&lt;p&gt;It would be even better if these molecules could be further categorized according to their type of geometry (for example, not just &amp;quot;triatomic molecules&amp;quot; but &amp;quot;linear triatomic molecules&amp;quot;) but the example that I gave from NIST doesn't go this far.&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2022-08-12T19:51:20.540" LastActivityDate="2022-08-12T19:51:20.540" Title="List of properties of molecules categorized by the number of atoms?" Tags="|reference-request|molecular-modeling|spectroscopy|databases|geometry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9520" PostTypeId="2" ParentId="9519" CreationDate="2022-08-12T19:47:49.363" Score="2" Body="&lt;h2&gt;CRC Handbook of Chemistry and Physics&lt;/h2&gt;&#xA;&lt;p&gt;The example you gave from NIST gives about 55 geometries for triatomic molecules.  The CRC Handbook gives a plethora of properties for diatomics (just search &amp;quot;diatomic&amp;quot; in a PDF version of the book) and also gives electron affinities (at least) for triatomics. In the 97th Edition (2016), which is the newest version for which I immediately have a PDF available, the data is organized as follows for electron affinities, with properties for atoms in alphabetical order first, followed by the diatomic molecules in alphabetical order next:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Nmf0B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Nmf0B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&lt;br&gt;&#xA;&lt;p&gt;&lt;strong&gt;After the last diatomics that they have alphabetically are finished, triatomics are listed in alphabetical order:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UCAg1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UCAg1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;After the last triatomics that they have alphabetically are finished, polyatomics are listed in alphabetical order:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cwSCL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cwSCL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The triatomics list here is significantly longer than the one in your example from NIST.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-08-12T19:47:49.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9521" PostTypeId="2" ParentId="9517" CreationDate="2022-08-12T20:01:00.807" Score="2" Body="&lt;p&gt;A configuration state function (CSF) is a symmetry-adapted linear combination of Slater determinants. Even for a small basis set, there can be trillions of CSFs. Those will surely not all be tabulated in a book!&lt;/p&gt;&#xA;&lt;p&gt;However you asked about computer programs to generate CSFs, and some of these are listed at the bottom of &lt;a href=&quot;https://en.wikipedia.org/wiki/Configuration_state_function&quot; rel=&quot;nofollow noreferrer&quot;&gt;this page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For atoms there's &lt;strong&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0010465593900247?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;LSGEN&lt;/a&gt;&lt;/strong&gt; by Sturesson and Froese Fischer.&lt;/p&gt;&#xA;&lt;p&gt;For molecules there's &lt;strong&gt;ALCHEMY II&lt;/strong&gt;: A Research Tool for Molecular Electronic Structure and Interactions, by McLean &lt;em&gt;et al.&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-12T20:19:00.210" LastActivityDate="2022-08-12T20:19:00.210" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9522" PostTypeId="5" CreationDate="2022-08-12T20:02:43.433" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Graphical_unitary_group_approach&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Graphical_unitary_group_approach&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-12T20:02:43.433" LastActivityDate="2022-08-12T20:02:43.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9523" PostTypeId="4" CreationDate="2022-08-12T20:02:43.433" Score="0" Body="Questions about or related to GUGA (the graphical unitary group approach)." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-12T20:02:43.433" LastActivityDate="2022-08-12T20:02:43.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9524" PostTypeId="2" ParentId="9515" CreationDate="2022-08-12T20:17:26.440" Score="6" Body="&lt;p&gt;Adding to the (correct) &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9516/5&quot;&gt;answer by Tyberius&lt;/a&gt;, I'll just point out that &lt;em&gt;ab initio&lt;/em&gt; calculations of electronic energies of a molecule depend on a small number of things, most notably:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(1) spin multiplicity,&lt;/li&gt;&#xA;&lt;li&gt;(2) charge (or total number of electrons),&lt;/li&gt;&#xA;&lt;li&gt;(3) &lt;strong&gt;geometry.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The two most popular ways to describe the geometry geometry are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(A) The XYZ format (Cartesian coordinates):&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C     0.000000     0.000000     0.000000&#xA;H     0.000000     0.000000     1.089000&#xA;H     1.026719     0.000000    -0.363000&#xA;H    -0.513360    -0.889165    -0.363000&#xA;H    -0.513360     0.889165    -0.363000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;(B) The &lt;a href=&quot;https://en.wikipedia.org/wiki/Z-matrix_(chemistry)&quot; rel=&quot;noreferrer&quot;&gt;Z-Matrix&lt;/a&gt; format:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C&#xA;H   1 1.089000&#xA;H   1 1.089000  2  109.4710&#xA;H   1 1.089000  2  109.4710  3  120.0000&#xA;H   1 1.089000  2  109.4710  3 -120.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice that in both the XYZ format and the ZMat format, we just give the (x,y,z) positions of the nuclei (in the XYZ case) or the bond lengths and angles (in the ZMat case) &lt;strong&gt;without any mention at all about what is &amp;quot;bonded&amp;quot;.&lt;/strong&gt; The idea is that the quantum chemistry calculation itself will figure out the &amp;quot;bonding&amp;quot; based on just the geometry, charge and spin multiplicity.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-08-12T20:17:26.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9525" PostTypeId="1" CreationDate="2022-08-12T21:17:40.883" Score="3" ViewCount="31" Body="&lt;p&gt;I am running a lattice simulation of a single chain polymer on a lattice with every other site occupied by solvent. The additional wrinkle is that every particle on the lattice has a number/spin orientation associated with it, which is subject to change throughout the simulation. There are &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; spins possible for every particle. The range of interaction is a nearest-neighbor interaction. Two particles cannot occupy the same site.&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;&amp;amp;\mathcal{H} = \sum _{(i,j)} \epsilon _{ij} \\&#xA;&amp;amp;\epsilon_{ij} =&#xA;\begin{cases}&#xA;\epsilon ^a, \text{ if spins at locations $i, j$ are the same }\\&#xA;\epsilon^n, \text{ if spins at locations $i, j$ spins are not the same}&#xA;\end{cases} &#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$(i,j)$&lt;/span&gt; are two lattice sites which are nearest neighbor to one another. Once I plant a polymer on such a lattice and fill up every other site on the lattice with solvent, I want to sample this system. How do I perform polymer configuration moves, such as configurational bias chain regrowth (CBCR)? This is how I would run CBCR if I did not have solvent:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pick a uniformly random monomer on the chain.&lt;/li&gt;&#xA;&lt;li&gt;Pick a side where you want to regrow polymer.&lt;/li&gt;&#xA;&lt;li&gt;Regrow polymer one monomer at a time. Calculate all the possible energetic states of the monomer per Rosenbluth sampling.&lt;/li&gt;&#xA;&lt;li&gt;Include Rosenbluth weights in acceptance criterion.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;But how do I do this type of regrowth if I have a lattice full of solvent? Every time I go to a new spot, I have to displace a solvent molecule. How do I account for the fact that every move involves some sort of solvent displacement. If required, I can give more explanation of the system I am performing.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-11-02T13:00:14.703" Title="How do I calculate the acceptance criterion for configuration bias sampling of my polymer?" Tags="|monte-carlo|polymers|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9526" PostTypeId="2" ParentId="9511" CreationDate="2022-08-12T21:43:04.137" Score="1" Body="&lt;p&gt;I have managed to make files called &lt;code&gt;charge_MOL&lt;/code&gt; and &lt;code&gt;MOL_charge&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;charge_MOL&lt;/code&gt; has the charges added as the &lt;em&gt;first&lt;/em&gt; column, as in the MOL_v2000 format (as explained in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9511/how-to-merge-two-files-molecule-structure-and-file-property-into-one#comment19874_9511&quot;&gt;your comment&lt;/a&gt;).  Here's the first few lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-0.03722231      2.6154    6.4064    0.9956 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03646360      4.8578    2.7738    1.5382 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03466408      8.7755    1.6888    2.8422 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03460579     12.3803    4.0139    3.6724 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03700567     14.4811    8.0604    3.5495 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03830432     14.7628   12.5956    3.8804 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03743637     12.2314   15.9121    5.2439 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03678821      8.0491   16.1020    6.2971 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03708334      4.3849   13.8269    6.4268 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;-0.03759946      1.9317   10.3116    6.0240 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;MOL_charge&lt;/code&gt; has them added as the &lt;em&gt;last&lt;/em&gt; column, as your same comment describes for the MOL2  format. Here's the first few lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.6154    6.4064    0.9956 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03722231&#xA; 4.8578    2.7738    1.5382 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03646360&#xA; 8.7755    1.6888    2.8422 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03466408&#xA;12.3803    4.0139    3.6724 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03460579&#xA;14.4811    8.0604    3.5495 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03700567&#xA;14.7628   12.5956    3.8804 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03830432&#xA;12.2314   15.9121    5.2439 C   0  0  0  0  0  0  0  0  0  0  0  0      -0.03743637&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/9511&quot; rel=&quot;nofollow noreferrer&quot;&gt;this GitHub repository&lt;/a&gt; there's a folder called &amp;quot;original&amp;quot; which has three &lt;code&gt;MOL&lt;/code&gt; files and three &lt;code&gt;charge&lt;/code&gt; files. I did the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cp -r original demonstration    # So the original files are saved (just in case)&#xA;sed -i '1,4d' MOL*              # Remove lines 1-4 in all files strating with &amp;quot;MOL&amp;quot;&#xA;paste charge1 MOL1 &amp;gt; charge_MOL # Creates file with charges in 1st column, then MOL&#xA;paste MOL1 charge1 &amp;gt; MOL_charge # Creates file with MOL, then charges in last col.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then modify this to do the last two lines in a loop, using the following resources:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.cyberciti.biz/faq/bash-for-loop/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bash for loop blog post&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://stackoverflow.com/q/20796200/1271772&quot;&gt;How to loop over files in directory and change path and add suffix to filename&lt;/a&gt; (StackOverflow)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For the horizontal concatenation, I used the &lt;code&gt;paste&lt;/code&gt; command as it was the most highly upvoted answer to: &lt;a href=&quot;https://unix.stackexchange.com/q/8986/78288&quot;&gt;Horizontal file concatenation&lt;/a&gt; (Unix/Linux Stack Exchange). The other answer recommends to use &lt;code&gt;join&lt;/code&gt; but doesn't tell us how to use it.&lt;/p&gt;&#xA;&lt;p&gt;For the removal of the first 4 lines, I slightly modified the second most highly upvoted answer from here: &lt;a href=&quot;https://stackoverflow.com/q/339483/1271772&quot;&gt;How can I remove the first line of a text file using bash/sed script?&lt;/a&gt; (StackOverflow). The most highly upvoted answer uses &lt;code&gt;tail&lt;/code&gt; instead of &lt;code&gt;sed&lt;/code&gt;, but I chose to use &lt;code&gt;sed&lt;/code&gt; since I use it frequently for this type of thing (especially the &lt;code&gt;-i&lt;/code&gt; option which allows us to avoid using &lt;code&gt;&amp;gt; output.txt&lt;/code&gt;  to output the file to &lt;code&gt;output.txt&lt;/code&gt;).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-08-12T21:43:04.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9527" PostTypeId="2" ParentId="9511" CreationDate="2022-08-13T03:42:15.900" Score="1" Body="&lt;p&gt;I used to really like the &lt;code&gt;mol2&lt;/code&gt; format because it was relatively well-supported and included partial charges.&lt;/p&gt;&#xA;&lt;p&gt;The main problem is that support is really variable, so it's hard to rely on.&lt;/p&gt;&#xA;&lt;p&gt;As it turns out, the &lt;code&gt;sdf&lt;/code&gt; version of the &lt;code&gt;MOL&lt;/code&gt; format, allows you to include properties.&lt;/p&gt;&#xA;&lt;p&gt;For example, here's a file from PubChem:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;19681234&#xA;  -OEChem-08122223273D&#xA;&#xA; 32 32  0     0  0  0  0  0  0999 V2000&#xA;    1.4401    1.9561   -2.1702 Cl  0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.9365   -2.5423    1.8946 Cl  0  0  0  0  0  0  0  0  0  0  0  0&#xA;    4.2090   -2.4867   -1.0788 Cl  0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.1431    1.9226    0.8003 S   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -0.1372    1.6756    2.2019 O   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6636    3.2080    0.3757 O   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -1.2354    1.5538   -0.1239 N   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -3.3697    0.3545   -0.2414 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -4.0707   -0.9995   -0.1299 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -1.8701    0.2233   -0.0046 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -5.5689   -0.8747   -0.4053 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;[.. omitted ..]&#xA;    3.1687   -0.2515   -2.4240 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;  1 14  1  0  0  0  0&#xA;  2 16  1  0  0  0  0&#xA;  3 18  1  0  0  0  0&#xA;  4  5  2  0  0  0  0&#xA;  4  6  2  0  0  0  0&#xA;  4  7  1  0  0  0  0&#xA;  4 12  1  0  0  0  0&#xA;[ .. omitted .. ]&#xA; 16 18  2  0  0  0  0&#xA; 17 18  1  0  0  0  0&#xA; 17 32  1  0  0  0  0&#xA;M  END&#xA;&amp;gt; &amp;lt;PUBCHEM_COMPOUND_CID&amp;gt;&#xA;19681234&#xA;&#xA;&amp;gt; &amp;lt;PUBCHEM_MMFF94_PARTIAL_CHARGES&amp;gt;&#xA;17&#xA;1 -0.18&#xA;10 0.36&#xA;12 -0.01&#xA;14 0.18&#xA;15 -0.15&#xA;16 0.18&#xA;17 -0.15&#xA;18 0.18&#xA;2 -0.18&#xA;27 0.42&#xA;3 -0.18&#xA;31 0.15&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What I want to note is that the calculated partial charges are stored in a property. (The PubChem files store MMFF94 charges that are non-zero and for some reason list by alphabetically-sorted atom numbers, thus 1-10-12...)&lt;/p&gt;&#xA;&lt;p&gt;It would be really easy to merge your files, e.g.;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for molfile in *.mol; do&#xA;  sdfile=${molfile%%.mol}.sdf # remove the .mol extension and add a .sdf&#xA;  cat ${molfile} &amp;gt;${sdfile}&#xA;  echo '&amp;gt; &amp;lt;PARTIAL_CHARGES&amp;gt;' &amp;gt;&amp;gt;${sdfile}&#xA;  cat charges &amp;gt;&amp;gt;${sdfile}&#xA;  echo &amp;gt;&amp;gt;${sdfile} # add an extra blank line&#xA;  echo '$$$$' &amp;gt;&amp;gt;${sdfile}&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The resulting files will be readable by anything that reads &lt;code&gt;.mol&lt;/code&gt; or &lt;code&gt;.sdf&lt;/code&gt; files and the partial charges will be saved and/or processed later.&lt;/p&gt;&#xA;&lt;p&gt;I'm using this scheme in Avogadro2 - it will look for &amp;quot;PARTIAL_CHARGES&amp;quot; fields in SDF files.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-08-13T03:42:15.900" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9528" PostTypeId="1" AcceptedAnswerId="9589" CreationDate="2022-08-13T14:29:38.343" Score="4" ViewCount="64" Body="&lt;p&gt;As a example, I ran the following DFT single point energy calculation on &lt;a href=&quot;https://en.wikipedia.org/wiki/NWChem&quot; rel=&quot;nofollow noreferrer&quot;&gt;NWChem&lt;/a&gt;, to get a cube file with electron density data for &lt;a href=&quot;https://en.wikipedia.org/wiki/1.1.1-Propellane&quot; rel=&quot;nofollow noreferrer&quot;&gt;1.1.1-Propellane&lt;/a&gt; (the geometry was optimized beforehand):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/aug-pcS-1/pcS-0&amp;quot;&#xA;charge 0&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;C      0.913139    0.913139    0.000000&#xA;H      0.676070    1.981751    0.000000&#xA;C      0.000000    0.000000    0.780217&#xA;C      0.000000    0.000000   -0.780217&#xA;H      1.378212   -1.576370    0.000000&#xA;C      0.334232   -1.247371    0.000000&#xA;H      1.981751    0.676070    0.000000&#xA;C     -1.247371    0.334232    0.000000&#xA;H     -0.405381   -2.054282    0.000000&#xA;H     -2.054282   -0.405381    0.000000&#xA;H     -1.576370    1.378212    0.000000&#xA;end&#xA;&#xA;basis&#xA;  H library pcS-0&#xA;  C library aug-pcS-1&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE propellane&#xA; LimitXYZ&#xA; -4.0 4.0 10&#xA; -4.0 4.0 10&#xA; -2.0 2.0 10&#xA; spin total&#xA; gaussian&#xA; output propel_density.cube&#xA;end&#xA;&#xA;task dplot&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I got a cube file with this data:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Cube file generated by NWChem&#xA; propellane&#xA;   11   -7.558906   -7.558906   -3.779453&#xA;   11    1.511781    0.000000    0.000000&#xA;   11    0.000000    1.511781    0.000000&#xA;   11    0.000000    0.000000    0.755891&#xA;    6    6.000000    1.725582    1.725582    0.000000&#xA;    1    1.000000    1.277588    3.744967    0.000000&#xA;    6    6.000000    0.000000    0.000000    1.474396&#xA;    6    6.000000    0.000000    0.000000   -1.474396&#xA;    1    1.000000    2.604442   -2.978907    0.000000&#xA;    6    6.000000    0.631607   -2.357189    0.000000&#xA;    1    1.000000    3.744967    1.277588    0.000000&#xA;    6    6.000000   -2.357189    0.631607    0.000000&#xA;    1    1.000000   -0.766060   -3.882030    0.000000&#xA;    1    1.000000   -3.882030   -0.766060    0.000000&#xA;    1    1.000000   -2.978907    2.604442    0.000000&#xA;  0.62208E-07  0.77410E-07  0.92090E-07  0.10495E-06  0.11406E-06  0.11740E-06&#xA;  0.11406E-06  0.10495E-06  0.92090E-07  0.77410E-07  0.62208E-07&#xA;  0.21734E-06  0.28304E-06  0.36147E-06  0.44672E-06  0.51767E-06  0.54588E-06&#xA;  0.51767E-06  0.44672E-06  0.36147E-06  0.28304E-06  0.21734E-06&#xA;  0.65034E-06  0.99144E-06  0.15603E-05  0.23422E-05  0.30897E-05  0.34065E-05&#xA;  0.30897E-05  0.23422E-05  0.15603E-05  0.99144E-06  0.65034E-06&#xA;  0.16630E-05  0.33686E-05  0.69696E-05  0.12679E-04  0.18613E-04  0.21229E-04&#xA;  0.18613E-04  0.12679E-04  0.69696E-05  0.33686E-05  0.16630E-05&#xA;  0.29916E-05  0.77058E-05  0.19044E-04  0.38515E-04  0.59765E-04  0.69369E-04&#xA;  0.59765E-04  0.38515E-04  0.19044E-04  0.77058E-05  0.29916E-05&#xA;  0.28476E-05  0.79756E-05  0.21303E-04  0.45290E-04  0.72158E-04  0.84435E-04&#xA;  0.72158E-04  0.45290E-04  0.21303E-04  0.79756E-05  0.28476E-05&#xA;  0.16204E-05  0.40253E-05  0.10603E-04  0.22809E-04  0.36692E-04  0.43066E-04&#xA;  0.36692E-04  0.22809E-04  0.10603E-04  0.40253E-05  0.16204E-05&#xA;  0.10892E-05  0.21250E-05  0.47475E-05  0.93855E-05  0.14518E-04  0.16847E-04&#xA;  0.14518E-04  0.93855E-05  0.47475E-05  0.21250E-05  0.10892E-05&#xA;  0.74767E-06  0.11678E-05  0.20155E-05  0.33355E-05  0.46941E-05  0.52901E-05&#xA;  0.46941E-05  0.33355E-05  0.20155E-05  0.11678E-05  0.74767E-06&#xA;  0.36524E-06  0.49768E-06  0.68962E-06  0.93195E-06  0.11530E-05  0.12448E-05&#xA;  0.11530E-05  0.93195E-06  0.68962E-06  0.49768E-06  0.36524E-06&#xA;  0.12318E-06  0.15671E-06  0.19351E-06  0.23025E-06  0.25898E-06  0.27005E-06&#xA;  0.25898E-06  0.23025E-06  0.19351E-06  0.15671E-06  0.12318E-06&#xA;  0.21734E-06  0.28304E-06  0.36147E-06  0.44672E-06  0.51767E-06  0.54588E-06&#xA; 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 0.49128E-02  0.22790E-02  0.86122E-03  0.27164E-03  0.68932E-04&#xA;  0.12282E-04  0.48297E-04  0.15308E-03  0.35379E-03  0.58836E-03  0.69853E-03&#xA;  0.58836E-03  0.35379E-03  0.15308E-03  0.48297E-04  0.12282E-04&#xA;  0.22212E-05  0.61099E-05  0.16662E-04  0.36152E-04  0.58261E-04  0.68404E-04&#xA;  0.58261E-04  0.36152E-04  0.16662E-04  0.61099E-05  0.22212E-05&#xA;  0.72273E-06  0.11040E-05  0.18825E-05  0.31048E-05  0.43685E-05  0.49240E-05&#xA;  0.43685E-05  0.31048E-05  0.18825E-05  0.11040E-05  0.72273E-06&#xA;  0.36524E-06  0.49768E-06  0.68962E-06  0.93195E-06  0.11530E-05  0.12448E-05&#xA;  0.11530E-05  0.93195E-06  0.68962E-06  0.49768E-06  0.36524E-06&#xA;  0.11049E-05  0.20297E-05  0.38907E-05  0.67599E-05  0.96941E-05  0.10978E-04&#xA;  0.96941E-05  0.67599E-05  0.38907E-05  0.20297E-05  0.11049E-05&#xA;  0.33378E-05  0.80700E-05  0.19005E-04  0.37333E-04  0.57048E-04  0.65896E-04&#xA;  0.57048E-04  0.37333E-04  0.19005E-04  0.80700E-05  0.33378E-05&#xA;  0.66847E-05  0.16678E-04  0.40860E-04  0.82835E-04  0.12925E-03  0.15046E-03&#xA;  0.12925E-03  0.82835E-04  0.40860E-04  0.16678E-04  0.66847E-05&#xA;  0.96434E-05  0.22694E-04  0.54979E-04  0.11231E-03  0.17633E-03  0.20559E-03&#xA;  0.17633E-03  0.11231E-03  0.54979E-04  0.22694E-04  0.96434E-05&#xA;  0.19352E-04  0.59181E-04  0.16317E-03  0.36193E-03  0.61978E-03  0.75598E-03&#xA;  0.61978E-03  0.36193E-03  0.16317E-03  0.59181E-04  0.19352E-04&#xA;  0.23959E-04  0.84511E-04  0.24993E-03  0.59675E-03  0.11273E-02  0.14464E-02&#xA;  0.11273E-02  0.59675E-03  0.24993E-03  0.84511E-04  0.23959E-04&#xA;  0.10552E-04  0.37263E-04  0.11006E-03  0.24759E-03  0.41422E-03  0.49632E-03&#xA;  0.41422E-03  0.24759E-03  0.11006E-03  0.37263E-04  0.10552E-04&#xA;  0.22212E-05  0.61099E-05  0.16662E-04  0.36152E-04  0.58261E-04  0.68404E-04&#xA;  0.58261E-04  0.36152E-04  0.16662E-04  0.61099E-05  0.22212E-05&#xA;  0.72421E-06  0.10805E-05  0.19383E-05  0.34106E-05  0.50073E-05  0.57244E-05&#xA;  0.50073E-05  0.34106E-05  0.19383E-05  0.10805E-05  0.72421E-06&#xA;  0.35006E-06  0.41830E-06  0.50737E-06  0.62164E-06  0.72978E-06  0.77564E-06&#xA;  0.72978E-06  0.62164E-06  0.50737E-06  0.41830E-06  0.35006E-06&#xA;  0.12318E-06  0.15671E-06  0.19351E-06  0.23025E-06  0.25898E-06  0.27005E-06&#xA;  0.25898E-06  0.23025E-06  0.19351E-06  0.15671E-06  0.12318E-06&#xA;  0.31420E-06  0.43996E-06  0.61864E-06  0.83795E-06  0.10337E-05  0.11140E-05&#xA;  0.10337E-05  0.83795E-06  0.61864E-06  0.43996E-06  0.31420E-06&#xA;  0.67845E-06  0.10556E-05  0.16973E-05  0.25895E-05  0.34476E-05  0.38124E-05&#xA;  0.34476E-05  0.25895E-05  0.16973E-05  0.10556E-05  0.67845E-06&#xA;  0.11652E-05  0.18470E-05  0.30987E-05  0.49400E-05  0.67731E-05  0.75649E-05&#xA;  0.67731E-05  0.49400E-05  0.30987E-05  0.18470E-05  0.11652E-05&#xA;  0.17810E-05  0.29861E-05  0.53758E-05  0.90667E-05  0.12849E-04  0.14504E-04&#xA;  0.12849E-04  0.90667E-05  0.53758E-05  0.29861E-05  0.17810E-05&#xA;  0.27829E-05  0.59880E-05  0.13092E-04  0.24717E-04  0.37027E-04  0.42502E-04&#xA;  0.37027E-04  0.24717E-04  0.13092E-04  0.59880E-05  0.27829E-05&#xA;  0.29571E-05  0.71888E-05  0.16991E-04  0.33441E-04  0.51142E-04  0.59084E-04&#xA;  0.51142E-04  0.33441E-04  0.16991E-04  0.71888E-05  0.29571E-05&#xA;  0.16749E-05  0.36422E-05  0.81279E-05  0.15589E-04  0.23565E-04  0.27128E-04&#xA;  0.23565E-04  0.15589E-04  0.81279E-05  0.36422E-05  0.16749E-05&#xA;  0.72273E-06  0.11040E-05  0.18825E-05  0.31048E-05  0.43685E-05  0.49240E-05&#xA;  0.43685E-05  0.31048E-05  0.18825E-05  0.11040E-05  0.72273E-06&#xA;  0.35006E-06  0.41830E-06  0.50737E-06  0.62164E-06  0.72978E-06  0.77564E-06&#xA;  0.72978E-06  0.62164E-06  0.50737E-06  0.41830E-06  0.35006E-06&#xA;  0.00000E+00  0.00000E+00  0.00000E+00  0.00000E+00  0.00000E+00  0.00000E+00&#xA;  0.00000E+00  0.00000E+00  0.00000E+00  0.00000E+00  0.00000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now I want to know, for this molecule, how much volume around it is bound by the isosurface that corresponds to a given electronic density, for example, 0.001 e/angstrom^3. But the cube file doesn't contain any surfaces, just a grid of points sampling values of calculated electronic density. So I tried to estimate the desired volume just counting the fraction of points above the given density threshold, and multiplying by the entire volume of the cube, similar to the &lt;a href=&quot;https://rosettacode.org/wiki/Monte_Carlo_methods&quot; rel=&quot;nofollow noreferrer&quot;&gt;simple procedure&lt;/a&gt; to calculate an approximation for pi by Monte Carlo method, but in this case the points are not distributed randomly. I've done it through the following Pýthon script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import re&#xA;&#xA;def main():&#xA;    with open('propel_density.cube', 'r') as f:&#xA;        text = f.read()&#xA;&#xA;    ##Matches data in format the cube file uses to store&#xA;    ##density values, like 0.77410E-07 or 0.38588E+01.&#xA;    p = re.compile(r&amp;quot;0\.\d{5}E[-+]\d{2}&amp;quot;)&#xA;&#xA;    cube_volume = 8*8*4 ## From the LimitXYZ section in the input file.&#xA;    isosurface_threshold = 0.001&#xA;&#xA;    data = p.findall(text)&#xA;    numeric_data = [float(value) for value in data]&#xA;    fraction_inside = len([density&#xA;                           for density in numeric_data&#xA;                           if density &amp;gt;= isosurface_threshold]) / len(numeric_data)&#xA;&#xA;    bound_volume = cube_volume * fraction_inside&#xA;    print(bound_volume)&#xA;&#xA;main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives a estimate close to 72.5 cubic angstroms. But surely there is a error due to the raggedness of the grid. One possible solution is just run the job again increasing the number of points in the grid, but I'm not sure if the resolution can be cranked up indefinitely, or if there's a upper bound to the fidelity of the underlying data in the cube file, past which is moot to try get it more fine-grained. So I ask, what is the proper way to estimate this bound volume?&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2022-08-25T20:32:31.080" Title="How to properly compute volume bound by surface with uniform electronic density, from data in a cube file?" Tags="|density-functional-theory|open-source|electron-density|nwchem|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9529" PostTypeId="1" CreationDate="2022-08-14T01:42:10.327" Score="6" ViewCount="2960" Body="&lt;p&gt;I have a .xyz file, and I would like to change the format to .gjf (Gaussian Input File) by converting the name of format.&lt;/p&gt;&#xA;&lt;p&gt;Do you know how to prevent my situation?&lt;/p&gt;&#xA;&lt;p&gt;(Originally I talked about 'gif' and 'GIF'(Graphics Interchange...), since I thought the name of extension of gaussian input file is gif like GIF. I hope I make no more confusion for future readers. Gaussian input file has '.gjf' extension, not gif. And it will surely work if you convert the extension of .xyz by changing the name as well as format of data like real gaussian input files.(maybe starting with % section)&lt;/p&gt;&#xA;" OwnerUserId="5806" LastEditorUserId="5806" LastEditDate="2022-08-15T11:15:06.163" LastActivityDate="2022-10-09T08:02:41.650" Title="Convert .xyz format to Gaussian Input file (.gjf)" Tags="|gaussian|software-input-file-request|" AnswerCount="4" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9530" PostTypeId="2" ParentId="9529" CreationDate="2022-08-14T02:36:17.037" Score="2" Body="&lt;p&gt;The easiest way to convert .xyz to .gif(Gaussian input file) without being interfered by .GIF(Graphics Interchange) is to use Gaussian 09W (or your version of Gaussian software) and excel.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;open your .xyz file with excel (It is encouraged to change .xyz format to .txt before open the file with excel)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;refer all your cells by dragging them (perhaps on A1 column). Click 'Data' on the menu bar and select 'Text to columns'.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/kkPy8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kkPy8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Click next until you can see split lines like the picture below. Then double click the black arrow so that split xyz data from unnecessary data, for example, integers at the end of xyz float points.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;After split, leave only 'Atom X Y Z'. In my case 'C X Y Z'. And copy and paste them on Gaussian 09w 'Molecule Specification' section.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Q6vkJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Q6vkJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Save file as .gif or click the third button on the right side bar, which is depicted as putting a molecule in a folder.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Then you can see the molecular structure like below&#xA;&lt;a href=&quot;https://i.stack.imgur.com/y018B.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y018B.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5806" LastActivityDate="2022-08-14T02:36:17.037" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9531" PostTypeId="2" ParentId="9529" CreationDate="2022-08-14T05:58:41.680" Score="9" Body="&lt;p&gt;If you have a python installation, you can use ASE to do this in one line.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ase-gui structure.xyz -o structure.gjf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;(I have always seen it as gjf not gif)&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you don't have python, you can download anaconda and &lt;code&gt;pip install ase&lt;/code&gt; in the anaconda prompt.  I can confirm the most recent version of ASE does correctly install in windows and even the GUI is functional.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2022-08-14T14:45:53.350" LastActivityDate="2022-08-14T14:45:53.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9532" PostTypeId="1" AcceptedAnswerId="10798" CreationDate="2022-08-14T08:37:43.267" Score="5" ViewCount="206" Body="&lt;p&gt;I am trying to write a small python script which will symmetrize an elastic tensor based on rotational symmetry of the space group. I started with this &lt;a href=&quot;https://gist.github.com/terencezl/4e65b18c7ad76b9863940ebd8dc9fa32#user-content-fn-7-c9df14ee6bdfb5d27fd4c5b8dcfe9478&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; and created a new python script as below.&lt;/p&gt;&#xA;&lt;p&gt;I started with cubic elastic constants in Voigt form and expected to get same results as input. But the final result shows C12=C14 which is not correct. &lt;strong&gt;What might I be doing wrong?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Structure, Lattice&#xA;from pymatgen.symmetry.analyzer import SpacegroupAnalyzer&#xA;import numpy as np&#xA;from pymatgen.analysis.elasticity.elastic import ElasticTensor&#xA;&#xA;&#xA;structure = Structure.from_spacegroup(&#xA;    &amp;quot;Fm-3m&amp;quot;, Lattice.cubic(1.0), [&amp;quot;element&amp;quot;], [[0, 0, 0]])&#xA;sga = SpacegroupAnalyzer(SpacegroupAnalyzer(structure).find_primitive())&#xA;ops_list = sga.get_symmetry_operations(cartesian=True)&#xA;ops_rotation_list = [op.rotation_matrix for op in ops_list]&#xA;&#xA;C = np.array([[271.64, 141.6, 141.6,0,0,0],&#xA;              [141.6,271.64,141.6,0,0,0],&#xA;              [141.6,141.6,271.64,0,0,0],&#xA;              [0,0,0,105.18,0,0],&#xA;              [0,0,0,0,105.18,0],&#xA;              [0,0,0,0,0,105.18]])&#xA;C_prime_sum = 0&#xA;&#xA;CC = ElasticTensor(ElasticTensor.from_voigt(C).symmetrized)&#xA;for idx, op in enumerate(ops_rotation_list):&#xA;         # perform the 4th order tensor rotation.&#xA;        C_prime = ElasticTensor(&#xA;            np.einsum('im,jn,mnop,ok,pl', op, op, CC, op.T, op.T), tol=1e-5)&#xA;        C_prime_sum += C_prime&#xA;C_prime = C_prime_sum / (idx + 1)&#xA;A=C_prime.voigt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Expected output&lt;/strong&gt; (Same as input matrix C)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C = np.array([[271.64, 141.6, 141.6,0,0,0],&#xA;              [141.6,271.64,141.6,0,0,0],&#xA;              [141.6,141.6,271.64,0,0,0],&#xA;              [0,0,0,105.18,0,0],&#xA;              [0,0,0,0,105.18,0],&#xA;              [0,0,0,0,0,105.18]])&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;current output&lt;/strong&gt; (Which is not correct)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[271.64 117.32 117.32   0.     0.     0.  ]&#xA; [117.32 271.64 117.32   0.     0.     0.  ]&#xA; [117.32 117.32 271.64   0.     0.     0.  ]&#xA; [  0.     0.     0.   117.32   0.     0.  ]&#xA; [  0.     0.     0.     0.   117.32   0.  ]&#xA; [  0.     0.     0.     0.     0.   117.32]]&#xA;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-09-01T16:09:15.027" LastActivityDate="2023-04-28T07:07:51.593" Title="Symmetrization of elastic constants based on rotational symmetry in Pymatgen" Tags="|python|programming|pymatgen|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9533" PostTypeId="1" CreationDate="2022-08-14T09:48:53.397" Score="9" ViewCount="132" Body="&lt;p&gt;To check whether electronic transitions are allowed between valence band maximum (VBM) and conduction band minimum (CBM) as per Laporte's rule, the parity of VBM/CBM is needed to be known. &lt;a href=&quot;https://www.nature.com/articles/s43246-021-00172-9&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt; discusses this in the second paragraph of page no.5. I would like to know how one can find out the parity of VBM/CBM of the material using the data generated in DFT calculations.&lt;/p&gt;&#xA;" OwnerUserId="5138" LastActivityDate="2022-08-14T09:48:53.397" Title="How to do parity analysis of band extrema?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|solid-state-physics|wien2k|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9534" PostTypeId="2" ParentId="9529" CreationDate="2022-08-14T13:33:40.417" Score="5" Body="&lt;p&gt;There are two independent issues here: (1) How to convert &lt;code&gt;XYZ&lt;/code&gt; to Gaussian input file and (2) How to make Windows to not associate it with Graphics Interchange Format.&lt;/p&gt;&#xA;&lt;p&gt;(1) You can use &lt;a href=&quot;http://openbabel.org/wiki/Main_Page&quot; rel=&quot;noreferrer&quot;&gt;OpenBabel&lt;/a&gt; to convert &lt;code&gt;XYZ&lt;/code&gt; (or any other chemical format) to Gaussian input. In this case, the suggested extensions are &lt;code&gt;gjf&lt;/code&gt;, &lt;code&gt;gjc&lt;/code&gt;, &lt;code&gt;gau&lt;/code&gt;, &lt;code&gt;com&lt;/code&gt;. This extension will also recognized by GaussView.&lt;/p&gt;&#xA;&lt;p&gt;(2) If you would like that when you double-click on the file, it opens with GaussView or Gaussian executable instead any image reading program, you need to &lt;a href=&quot;https://support.microsoft.com/en-us/office/change-the-file-association-for-an-email-attachment-6fa9ac47-4e57-4ab8-9234-2422e3ea507f&quot; rel=&quot;noreferrer&quot;&gt;change the Windows association&lt;/a&gt; to your file:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Many types of files can be opened by more than one program. For&#xA;example, you can open a photo with the Photos program or with Paint,&#xA;among others. Follow these steps to change the default program that&#xA;Windows uses to open each type of file.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In Windows 7, Windows 8, and Windows 10, choose Start and then    type Control Panel.&lt;/li&gt;&#xA;&lt;li&gt;Choose Programs &amp;gt; Make a file type always    open in a specific program. If you don't see Programs, choose Default Programs.&lt;/li&gt;&#xA;&lt;li&gt;Associate a file type or protocol with a program.&lt;/li&gt;&#xA;&lt;li&gt;In the Set Associations tool, select the file type you want to change the program for, then choose Change program.&lt;/li&gt;&#xA;&lt;li&gt;Once you've chosen the new program to use to open that file type, choose OK.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Other way to open your file with the program you want, is clicking with the right mouse button, and look for &lt;code&gt;Open with another program&lt;/code&gt; (in this case, you will need to do it everytime).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-08-14T13:33:40.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9535" PostTypeId="1" AcceptedAnswerId="9542" CreationDate="2022-08-14T16:40:08.587" Score="3" ViewCount="245" Body="&lt;p&gt;I recently installed Intel® oneAPI Base Toolkit and Intel® oneAPI HPC Toolkit using the cimmands:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo yum install intel-basekit&#xA;sudo yum install intel-hpckit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The packages are installed in &lt;code&gt;/opt/intel/oneapi&lt;/code&gt; but when I run &lt;code&gt;./configure&lt;/code&gt; it usually specifies other compilers:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;directory QEHeat/src : ok okkokCI : ok&#xA;directory ACFDT/src : not present in /rhome/pkgs/QE/qe-7.1/install&#xA;directory KCW/PP : okk&#xA;all dependencies updated successfully&#xA;checking build system type... x86_64-pc-linux-gnu&#xA;checking ARCH... x86_64&#xA;checking setting AR... ... ar&#xA;checking setting ARFLAGS... ... ruv&#xA;checking for gfortran... gfortran&#xA;checking whether the Fortran compiler works... yes&#xA;checking for Fortran compiler default output file name... a.out&#xA;checking for suffix of executables...&#xA;checking whether we are cross compiling... no&#xA;checking for suffix of object files... o&#xA;checking whether we are using the GNU Fortran compiler... yes&#xA;checking whether gfortran accepts -g... yes&#xA;checking for mpiifort... no&#xA;checking for mpif90... no&#xA;checking for ifort... no&#xA;checking for nvfortran... no&#xA;checking for pgf90... no&#xA;checking for nagfor... no&#xA;checking for gfortran... gfortran&#xA;checking whether we are using the GNU Fortran compiler... yes&#xA;checking whether gfortran accepts -g... yes&#xA;checking version of gfortran... gfortran 4.8&#xA;checking for Fortran flag to compile .f90 files... none&#xA;setting F90... gfortran&#xA;setting MPIF90... gfortran&#xA;checking for cc... cc&#xA;checking whether we are using the GNU C compiler... yes&#xA;checking whether cc accepts -g... yes&#xA;checking for cc option to accept ISO C89... none needed&#xA;setting CC... cc&#xA;setting CFLAGS... -O3&#xA;using F90... gfortran&#xA;setting FFLAGS... -O3 -g&#xA;setting F90FLAGS... &lt;span class=&quot;math-container&quot;&gt;$(FFLAGS) -cpp&#xA;setting FFLAGS_NOOPT... -O0 -g&#xA;setting CPP... cpp&#xA;setting CPPFLAGS... -P -traditional -Uvector&#xA;setting LD... gfortran&#xA;setting LDFLAGS... -g&#xA;checking whether make sets $&lt;/span&gt;(MAKE)... yes&#xA;checking whether Fortran files must be preprocessed... no&#xA;checking whether we are using the GNU Fortran 77 compiler... yes&#xA;checking whether gfortran accepts -g... yes&#xA;checking for library containing dgemm... no&#xA;MKL not found&#xA;in /opt/intel/mkl/lib/intel64: checking for library containing dgemm... no&#xA;MKL not found&#xA;checking for library containing dgemm... no&#xA;in /usr/local/lib: checking for library containing dgemm... no&#xA;checking for library containing dgemm... -lblas&#xA;setting BLAS_LIBS... -lblas&#xA;checking for library containing dspev... -llapack&#xA;in /usr/local/lib: checking for library containing dspev... -llapack&#xA;checking FFT... checking for library containing dfftw_execute_dft... no&#xA;in /usr/local/lib: checking for library containing dfftw_execute_dft... no&#xA;using internal copy of FFTW&#xA;&#xA;checking MASS...&#xA;checking for library containing mpi_init... no&#xA;checking ELPA...&#xA;checking for Environ... not used&#xA;checking for ranlib... ranlib&#xA;checking for wget... wget -O&#xA;setting WGET... wget -O&#xA;checking for git... git&#xA;setting DFLAGS... -D__FFTW&#xA;setting IFLAGS... -I. -I&lt;span class=&quot;math-container&quot;&gt;$(TOPDIR)/include -I$&lt;/span&gt;(TOPDIR)/FoX/finclude&#xA;configure: creating ./config.status&#xA;config.status: creating install/make_lapack.inc&#xA;config.status: creating include/configure.h&#xA;config.status: creating make.inc&#xA;config.status: creating configure.msg&#xA;config.status: creating install/make_wannier90.inc&#xA;config.status: creating include/qe_cdefs.h&#xA;--------------------------------------------------------------------&#xA;ESPRESSO can take advantage of several optimized numerical libraries&#xA;(essl, fftw, mkl...).  This configure script attempts to find them,&#xA;but may fail if they have been installed in non-standard locations.&#xA;If a required library is not found, the local copy will be compiled.&#xA;&#xA;The following libraries have been found:&#xA;  BLAS_LIBS= -lblas&#xA;  LAPACK_LIBS=-L/usr/local/lib -llapack  -lblas&#xA;  FFT_LIBS=&#xA;&#xA;&#xA;&#xA;Please check if this is what you expect.&#xA;&#xA;If any libraries are missing, you may specify a list of directories&#xA;to search and retry, as follows:&#xA;  ./configure LIBDIRS=&amp;quot;list of directories, separated by spaces&amp;quot;&#xA;&#xA;Parallel environment not detected \(is this a parallel machine?\).\&#xA;Configured for compilation of serial executables.&#xA;&#xA;For more info, read the ESPRESSO User's Guide (Doc/users-guide.tex).&#xA;--------------------------------------------------------------------&#xA;configure: success&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How to force &lt;code&gt;./configure&lt;/code&gt; to choose intel oneAPI compilers?&lt;/p&gt;&#xA;" OwnerUserId="5853" LastEditorUserId="5" LastEditDate="2022-08-14T17:18:23.193" LastActivityDate="2022-08-15T14:09:03.630" Title="QUANTUM ESPRESSO, How to force ./configure to use intel oneAPI compilers?" Tags="|quantum-espresso|software-assistance|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9536" PostTypeId="1" AcceptedAnswerId="9537" CreationDate="2022-08-14T19:05:14.213" Score="5" ViewCount="1251" Body="&lt;p&gt;As is well known, the compilation and &lt;code&gt;./configure&lt;/code&gt; stage is the most tricky part in installing QE. As it depends on the environment of the operating system and the availability of many auxiliary packages.&#xA;So my question is if there are pre-compiled QE in which I can directly run my calculations?&lt;/p&gt;&#xA;" OwnerUserId="5853" LastEditorUserId="5" LastEditDate="2022-08-14T21:16:22.777" LastActivityDate="2022-08-15T14:50:58.960" Title="Is there a pre-compiled Quantum ESPRESSO?" Tags="|quantum-espresso|software|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9537" PostTypeId="2" ParentId="9536" CreationDate="2022-08-14T21:08:20.463" Score="7" Body="&lt;p&gt;Pre-compiled Quantum ESPRESSO is available on:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Fedora Linux, see &lt;a href=&quot;https://src.fedoraproject.org/rpms/quantum-espresso&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;Debian &lt;a href=&quot;https://packages.debian.org/search?keywords=quantum-espresso&amp;amp;searchon=names&amp;amp;suite=all&amp;amp;section=all&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;Ubuntu &lt;a href=&quot;https://packages.ubuntu.com/search?keywords=quantum-espresso&amp;amp;searchon=names&amp;amp;suite=all&amp;amp;section=all&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2022-08-14T21:15:08.673" LastActivityDate="2022-08-14T21:15:08.673" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9538" PostTypeId="2" ParentId="9536" CreationDate="2022-08-15T00:06:28.807" Score="8" Body="&lt;p&gt;If you are running QE on a cluster, then unless your cluster provides a compiled version (which is common with many scientific clusters), you likely will get poor performance with precompiled code. You need to specify the mpi and linear algebra libraries that are appropriate for the libraries your cluster has available in order to get good performance. If you just want to run in serial or just want to run very light calculations, then you might be ok with precompiled versions that haven’t been specifically compiled for your cluster.&lt;/p&gt;&#xA;&lt;p&gt;If you have trouble compiling QE on a cluster, you should ask the cluster tech support (if that exists). They are often very helpful and are used to helping people with this sort of thing. My experience compiling QE on a cluster is that you have to know which mpi and math libraries you have to run “module load” on (assuming your cluster used such a module system for packages for all users), and then once you do that the ./configure works and then you just have to run make&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-08-15T00:06:28.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9540" PostTypeId="2" ParentId="9536" CreationDate="2022-08-15T08:47:05.847" Score="6" Body="&lt;p&gt;Pre-complied QE is available for Ubuntu and it's &lt;a href=&quot;https://packages.ubuntu.com/search?keywords=quantum-espresso&amp;amp;searchon=names&amp;amp;suite=all&amp;amp;section=all&quot; rel=&quot;noreferrer&quot;&gt;included&lt;/a&gt; in the default repo:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-sh prettyprint-override&quot;&gt;&lt;code&gt;sudo apt install quantum-espresso&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;&lt;strong&gt;However&lt;/strong&gt;&lt;/em&gt;, it is not the most recent version (6.7 instead of 7.0 as of now, and even older for Ubuntu versions below 21.10), and it will lack some optimizations you and/or your compiler could do if you're compiling it on your own. Generally, for most scientific software, you should always prefer to compile it on your own.&lt;/p&gt;&#xA;&lt;p&gt;Quantum espresso, in my experience, is a relatively straightforward compilation if you don't change the defaults (in which case, you &lt;em&gt;a)&lt;/em&gt; would know what you're doing, and &lt;em&gt;b)&lt;/em&gt; a pre-complied package wouldn't do it anyhow.) The nontrivial dependencies are included in the download package.&lt;/p&gt;&#xA;" OwnerUserId="968" LastEditorUserId="968" LastEditDate="2022-08-15T14:50:58.960" LastActivityDate="2022-08-15T14:50:58.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9541" PostTypeId="1" CreationDate="2022-08-15T12:09:10.960" Score="6" ViewCount="415" Body="&lt;p&gt;I would like to explore the global optimisation of Lennard-Jones clusters in Python. I do not come from a physical chemistry background. I would like to be able to calculate the cluster energy pointwise. That is, I would like a python function &lt;span class=&quot;math-container&quot;&gt;$f : X \rightarrow \mathbb{R}$&lt;/span&gt; which I can use to test my methods on.&lt;/p&gt;&#xA;&lt;p&gt;Do there exist simple python packages that have this functionality, or how can the clusters be implemented in python?&lt;/p&gt;&#xA;" OwnerUserId="5860" LastEditorUserId="5" LastEditDate="2023-02-18T05:52:27.713" LastActivityDate="2023-03-21T12:02:42.663" Title="Lennard Jones Clusters in Python" Tags="|molecular-dynamics|software-recommendations|python|geometry-optimization|jax-md|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9542" PostTypeId="2" ParentId="9535" CreationDate="2022-08-15T14:09:03.630" Score="1" Body="&lt;p&gt;This is not specific to Quantum Espresso. As explained in the instructions to use the Intel compilers on Linux you need to set a number of environment variables, this being usually achieved by running a script provided by Intel. If you installed the compilers in the default place, &lt;code&gt;/opt/intel&lt;/code&gt; , this is achieved by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;. /opt/intel/oneapi/setvars.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Don't miss out the initial dot! It's important that the script is run in the current shell.&lt;/p&gt;&#xA;&lt;p&gt;Note this doesn't necessarily solve all configuration problems, it depends on exactly how the configure scripts search for the required software. It may also be necessary to explicitly set the compiler by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export FC=mpiifort&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or similar after you have run &lt;code&gt;setvars.sh&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="269" LastActivityDate="2022-08-15T14:09:03.630" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9543" PostTypeId="2" ParentId="9518" CreationDate="2022-08-15T16:58:28.713" Score="5" Body="&lt;p&gt;I will consider both your question and the comments to your question in this answer.&lt;/p&gt;&#xA;&lt;p&gt;I understand your motivation is related to making a high school project, you say&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I would use a package but since it's a graded paper I feel like using packages for the calculations would take a way too much work.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think you should talk with your teacher about this point.&#xA;The integral calculation is technically challenging, but you learn essentially very little about quantum chemistry by doing it on your own.&lt;/p&gt;&#xA;&lt;p&gt;If the more general concepts of quantum chemistry such as SCF, eigenvalues, etc. are of interest I would recommend using a library that exposes integrals to Python, an example could be &lt;a href=&quot;https://daltonproject.readthedocs.io/en/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;Dalton Project&lt;/a&gt;, an example script that uses integrals is; &lt;a href=&quot;https://gitlab.com/daltonproject/daltonproject/-/blob/master/examples/geo_diff_integrals.py&quot; rel=&quot;noreferrer&quot;&gt;geo_diff_integrals.py&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you do want to implement the integrals on your own, there is two ways you can go.&#xA;The &amp;quot;easy&amp;quot; (less hard) but very slow evaluation as described in &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/0486443078&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Handbook of Computational Quantum Chemistry&lt;/a&gt;.&#xA;Going this route an example of a Python implementation as a reference for the electron-eletron integral and the electron-nuclear integral can be found &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant/blob/89d95ace76a2b84f86fc51d095114b12982555fa/MolecularIntegrals.py&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The other way to go about implementing integrals would be a little more sophisticated using recurrence relations, a very good guide for this is &lt;a href=&quot;https://joshuagoings.com/2017/04/28/integrals/&quot; rel=&quot;noreferrer&quot;&gt;A (hopefully) gentle guide to the computer implementation of molecular integrals over Gaussian basis functions&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As a very general note about the integral implementation. Do NOT worry about the speed before you have a working implementation.&lt;/p&gt;&#xA;" OwnerUserId="210" LastActivityDate="2022-08-15T16:58:28.713" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9544" PostTypeId="1" CreationDate="2022-08-15T16:52:39.330" Score="5" ViewCount="776" Body="&lt;p&gt;I have to do the TS optimization of a very large structure.&#xA;Initially, I used the typical &lt;code&gt;opt(ts,calcfc,noeigentest)&lt;/code&gt; at the route section, but during the optimization process (after the &lt;code&gt;CalcFC&lt;/code&gt; part) the job was interrupted and terminated.&lt;/p&gt;&#xA;&lt;p&gt;I want to continue the job by using the opt(restart) option and the chk file of the interrupted job. Below is what I found in the &lt;a href=&quot;https://gaussian.com/faq2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;FAQ page&lt;/a&gt; of the Gaussian website:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If CalcFC or RCFC was among the original options, then you can omit it if you do not need to compute/retrieve force constants, e.g., if the optimization was beyond the first step. On the other hand, if you add CalcFC to the option list along with Restart, the force constant will be computed at the beginning/next point of the restarted optimization.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However I also found this from the &lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Optimization page&lt;/a&gt; (example tab) of the Gaussian website:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Note that you must include CalcFC to compute the Hessian at the first point of the restarted job.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This made me confused, because (from my understanding) according to the first source the &lt;code&gt;CalcFC&lt;/code&gt; option can be omitted but from the second source it can't be omitted.&lt;/p&gt;&#xA;&lt;p&gt;I want to skip the &lt;code&gt;CalcFC&lt;/code&gt; part because it took a long time to compute, so I omitted the &lt;code&gt;CalcFC&lt;/code&gt; option, i.e. I just used&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;opt(restart,ts,noeigentest) geom(check) guess(read)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;but it ended with an error saying that the &lt;code&gt;CalcFC&lt;/code&gt; is needed.&lt;/p&gt;&#xA;&lt;p&gt;Is there any way to restart/continue the interrupted TS optimization job without the &lt;code&gt;CalcFC&lt;/code&gt; option?&lt;/p&gt;&#xA;" OwnerUserId="5865" OwnerDisplayName="Duffoon" LastEditorUserId="7" LastEditDate="2022-08-15T20:28:15.177" LastActivityDate="2022-08-16T13:56:46.270" Title="How to restart an interrupted TS optimization job in Gaussian16 without the CalcFC option from the chk file?" Tags="|computational-chemistry|gaussian|geometry-optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9545" PostTypeId="1" CreationDate="2022-08-16T05:51:08.033" Score="6" ViewCount="229" Body="&lt;p&gt;I am writing my own (orbital-free, for now) 3D density functional theory code from scratch. It currently works correctly for the simple harmonic oscillator potential &lt;span class=&quot;math-container&quot;&gt;$V_\text{ext}(\mathbf r) = \frac12\omega^2 |\mathbf r|^2$&lt;/span&gt;, yielding a ground state energy of &lt;span class=&quot;math-container&quot;&gt;$\frac32\omega$&lt;/span&gt; (atomic units). I am trying to extend this to find the GS energy of a hydrogen atom.&lt;/p&gt;&#xA;&lt;p&gt;The SHM code uses the von-Weizsäcker KE functional and the external potential term &lt;span class=&quot;math-container&quot;&gt;$\int d\mathbf r\ n(\mathbf r)V_\text{ext}(\mathbf r)$&lt;/span&gt;. However substituting &lt;span class=&quot;math-container&quot;&gt;$V_\text{ext}$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$-1/r$&lt;/span&gt; (the potential generated by a proton at the origin) yields an energy of around -12 eV, which is too high. Moreover, unlike for the SHM, the obtained GS energy seems to vary depending on the grid size and spacing, suggesting that I am not including the correct functionals in the energy calculation. Further evidence for this is the energy of the explicit 1s orbital density also being slightly too high (~11 eV).&lt;/p&gt;&#xA;&lt;p&gt;So my question is: am I using the wrong kinetic energy functional? Should I be adding other terms to the energy expression? What is the setup to correctly obtain the correct GS for the H atom?&lt;/p&gt;&#xA;" OwnerUserId="5866" LastActivityDate="2022-08-16T07:43:49.357" Title="Which functionals should I include for a simple hydrogen atom system?" Tags="|density-functional-theory|ab-initio-calculations|programming|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9546" PostTypeId="2" ParentId="9545" CreationDate="2022-08-16T07:43:49.357" Score="7" Body="&lt;p&gt;As far as I know, the issue of the kinetic energy functional is how people first came to use orbital based functionals in any capacity. Meaning the von Weizsäcker functional, albeit the best orbital free approximation for the kinetic energy there is, is not very accurate.&lt;/p&gt;&#xA;&lt;p&gt;Orbital free DFT is an active field of research that only moves very slowly. I recommend this review from 2015: &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0065327615000052&quot; rel=&quot;noreferrer&quot;&gt;Frank Discussion of the Status of Ground-State Orbital-Free DFT&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5837" LastActivityDate="2022-08-16T07:43:49.357" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9548" PostTypeId="1" AcceptedAnswerId="9553" CreationDate="2022-08-16T13:23:02.050" Score="5" ViewCount="168" Body="&lt;p&gt;In &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.7b02120&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, in the first sentence of page no.6723, the authors attribute a particular section of band structure (in momentum space) to the bonds/ atoms in real space. I would like to know methods to find such contributors from real space. My query is particularly related to DFT band structure calculations and any answer with reference to DFT data would help me understand this better.&lt;/p&gt;&#xA;" OwnerUserId="5138" LastActivityDate="2022-08-16T19:44:05.103" Title="How to find which atoms/bonds contribute to the particular section of band structure?" Tags="|density-functional-theory|quantum-espresso|band-structure|solid-state-physics|brillouin-zone|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9549" PostTypeId="2" ParentId="9544" CreationDate="2022-08-16T13:56:46.270" Score="1" Body="&lt;p&gt;As your error message suggests, even after a restart, an optimization to a transition state requires either force constants or specifying to use &lt;code&gt;ModRedundant&lt;/code&gt; coordinates. So if you don't want to eat the cost of running &lt;code&gt;CalcFC&lt;/code&gt; again, you could try adding &lt;code&gt;ModRedundant&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, I have generally found &lt;code&gt;opt=ts&lt;/code&gt; to be tricky, where you have to play with a lot of settings to get convergence. If you have reasonable guess structures for the reactant/ts/product, you may want to try a &lt;code&gt;QST2&lt;/code&gt; or &lt;code&gt;QST3&lt;/code&gt; calculation to search for the transition state. The same caveats apply of needing force constants or mod redundant coordinates, but having information about the various states of the reaction tends to help with convergence.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-08-16T13:56:46.270" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9550" PostTypeId="1" AcceptedAnswerId="9563" CreationDate="2022-08-16T14:00:24.333" Score="3" ViewCount="212" Body="&lt;p&gt;I'd like to generate a supercell of Cd0.5Zn0.5S which includes 108 atoms, and I tried to use &lt;code&gt;mpirun -np 64 mcsqs -n 108&lt;/code&gt; to get the supercell, but according to the log of &lt;code&gt;mcsqs&lt;/code&gt;, the program runs very slowly, how could I make the program run faster?&lt;/p&gt;&#xA;&lt;p&gt;Here is the log of mcsqs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OObjective_function= -0.944454&#xA;Correlations_mismatch=  0.000000    0.000000    0.000000    0.000000    0.000000    0.111111    -0.111111   -0.111111   -0.111111   -0.111Objective_function= -0.944454&#xA;Correlations_mismatch=  0.000000    0.000000    0.000000    0.000000    0.000000    -0.111111   -0.111111   0.111111    -0.111111   -0.111111&#xA;0.111111    0.111111&#xA;454&#xA;Correlations_mismatch=  0.000000    0.000000    0.000000    0.000000    0.000000    0.111111    0.111111    -0.111111   -0.111111   -0.111111&#xA;11  0.111111&#xA;Objective_function= -0.944454&#xA;Correlations_mismatch=  0.000000    0.000000    0.000000    0.000000    0.000000    0.111111    -0.111111   -0.111111   -0.111111   -0.111111&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the result I got after running &lt;code&gt;mcsqs&lt;/code&gt; for a few days which doesn't seems quite good:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/0Xyku.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0Xyku.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-08-16T19:08:05.637" LastActivityDate="2022-08-19T01:41:34.377" Title="How to accelerate mcsqs to get quasi-random structure?" Tags="|special-quasirandom-structures|alloy-theoretic-automated-toolkit|disorder|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9551" PostTypeId="1" CreationDate="2022-08-16T17:38:05.087" Score="1" ViewCount="106" Body="&lt;p&gt;I am trying to generate quasi-random structures (SQS)  for a system which contains 128 atoms, but when I tried to use &lt;code&gt;mcsqs&lt;/code&gt; for &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;atat toolkit&lt;/a&gt;, it runs very slowly, after  a few days, the structure I got is still not very satisfying, and it takes days to generate a new structure.&lt;/p&gt;&#xA;&lt;p&gt;Is there any software that is suit for generateing SQS for large systems?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-08-16T19:07:52.223" LastActivityDate="2022-08-16T19:07:52.223" Title="Software to generate quasi-random structures (SQS) for larges systems?" Tags="|special-quasirandom-structures|alloy-theoretic-automated-toolkit|disorder|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-01T21:50:46.397" ContentLicense="CC BY-SA 4.0" />
  <row Id="9552" PostTypeId="1" CreationDate="2022-08-16T18:25:45.607" Score="1" ViewCount="40" Body="&lt;p&gt;I am studying the  &lt;a href=&quot;https://artistoo.net/explorables/Explorable-CPM.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cellular Potts Model Tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, this doesn't say anything about the grid/lattice initialization.&lt;/p&gt;&#xA;&lt;p&gt;How do I initialize the lattice/grid in a Potts Model?&lt;/p&gt;&#xA;&lt;p&gt;I.e., how do I assign initial pixel values before running the Monte Carlo loop?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-02-18T05:55:43.363" LastActivityDate="2023-02-18T05:55:43.363" Title="How do I initialize the lattice/grid in a Potts Model?" Tags="|model-hamiltonians|monte-carlo|ising-model|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9553" PostTypeId="2" ParentId="9548" CreationDate="2022-08-16T19:44:05.103" Score="7" Body="&lt;p&gt;You can calculate an orbital projected density of states and band structure to see what atomic states correspond to features in the DOS and band structure. That’s one of the things that they plot in that paper.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-08-16T19:44:05.103" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9554" PostTypeId="1" AcceptedAnswerId="10435" CreationDate="2022-08-16T23:35:01.523" Score="1" ViewCount="70" Body="&lt;p&gt;I am working with Heusler and Half Heusler materials on LAMMPS. Currently the study follows the properties in individual lattice directions such as [100] [110] etc. As of now, I am obtaining the unit cell coordinates from the &lt;a href=&quot;https://materialsproject.org/materials/mp-924130/#&quot; rel=&quot;nofollow noreferrer&quot;&gt;materials project&lt;/a&gt; website and replicating the atoms in the desired directions. When doing this, evaluating the properties in directions such as [110] or [111] require a tremendous effort to ensure that the periodicity etc. is retained.&lt;/p&gt;&#xA;&lt;p&gt;Instead, is there a way to determine the orthogonal unit cell with a specific rotation applied to it? For example, to determine the unit cell with the x axis set in [111] direction such that using the atomic coordinates in LAMMPS is made easier and more straightforward?&lt;/p&gt;&#xA;&lt;p&gt;** I have read the reply for &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2417/lattice-representation-change-of-unit-cell&quot;&gt;this post&lt;/a&gt; but that did not properly answer my question.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="5" LastEditDate="2023-02-18T05:57:02.193" LastActivityDate="2023-02-18T05:57:02.193" Title="Is there a robust and reliable software to change the lattice vectors of unit cells?" Tags="|density-functional-theory|crystallography|lammps|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9555" PostTypeId="1" CreationDate="2022-08-17T04:49:26.503" Score="5" ViewCount="81" Body="&lt;p&gt;From an input in ORCA 5.0.3&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! PBE 6-31G*&#xA;%TDDFT NROOTS&#xA;3&#xA;END&#xA;* xyz  0 1&#xA; H      0.  0.  0.&#xA; H      0.  0.  0.7414&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the output includes&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;STATE  1:  E=   0.549785 au     14.960 eV   120663.8 cm**-1 &amp;lt;S**2&amp;gt; =   0.000000&#xA;     0a -&amp;gt;   1a  :     0.986865 (c= -0.99341072)&#xA;     0a -&amp;gt;   3a  :     0.013135 (c=  0.11460862)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My question is, does the main part (&amp;gt;90%) of the above excitation describe&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(\sigma_g)_2 \to (\sigma_g)_\beta (\sigma_u)_\alpha \tag{1}\label{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$(\sigma_g)_2 \to (\sigma_g)_b (\sigma_u)_\alpha + (\sigma_g)_\alpha (\sigma_u)_\beta  \tag{2}\label{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or are (1)&amp;amp;(2) equivalent in energy (or some other option entirely)?&lt;/p&gt;&#xA;&lt;p&gt;(1) is only alpha electron excited; (2) I guess is from two singly occupied orbitals forming a spin adapted wavefunction and will have two Slater determinants. However, spin adaption is mainly from wavefunction based theory (WFT) perspective, not necessarily justified in KS-DFT. But, even a CIS wavefunction can have multiple determinants, if I am not mistaken.&lt;/p&gt;&#xA;" OwnerUserId="5873" LastEditorUserId="7" LastEditDate="2022-08-18T14:34:15.130" LastActivityDate="2022-08-18T14:34:15.130" Title="Does a TD-DFT excitation from a closed-shell determinant only include the alpha electron part?" Tags="|density-functional-theory|orca|kohn-sham|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9556" PostTypeId="1" CreationDate="2022-08-17T12:54:54.037" Score="4" ViewCount="31" Body="&lt;p&gt;I want to see the bending response of my 2D nanomaterial, where the force is applied at the midpoint of the sheet using SMD (constant-velocity). Here, I have kept the two ends fixed. So, I want to observe the vertical deflection (along z) as the material is subjected to the force. However, in both distance, and direction settings for pull code, we need to have 2 pull groups. Here, I have only one pull group(middle part of the sheet), and want to apply force in z direction at this particular pull group. Which settings do I need to use for that in my pull code of gromacs? Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2022-08-17T12:54:54.037" Title="Three point bending test on a 2D nanomaterial with SMD in gromacs" Tags="|gromacs|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9558" PostTypeId="1" CreationDate="2022-08-18T07:42:09.957" Score="3" ViewCount="49" Body="&lt;p&gt;I would like to know if there is any correlation between the ELF values with materials in the electronic phase, versus with the &lt;a href=&quot;https://en.wikipedia.org/wiki/Electride&quot; rel=&quot;nofollow noreferrer&quot;&gt;electride&lt;/a&gt; phase?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2023-12-19T20:37:03.780" LastActivityDate="2023-12-19T20:37:03.780" Title="Is there any relation between electride and an electron localization function (ELF)?" Tags="|density-functional-theory|quantum-espresso|condensed-matter|charge-density|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9559" PostTypeId="5" CreationDate="2022-08-18T08:21:43.173" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-18T08:21:43.173" LastActivityDate="2022-08-18T08:21:43.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9560" PostTypeId="4" CreationDate="2022-08-18T08:21:43.173" Score="0" Body="Questions about METADISE." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-18T08:21:43.173" LastActivityDate="2022-08-18T08:21:43.173" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9561" PostTypeId="2" ParentId="9509" CreationDate="2022-08-18T13:42:04.127" Score="1" Body="&lt;p&gt;You are exactly correct in saying the Kohn-Sham equations are single particle equations&lt;/p&gt;&#xA;&lt;p&gt;The top equation is the classic eigenvalue equation with the spin orbitals being the eignfunctions and the associated eigenvalue being the energy of that  spin orbital. Here the set of spin orbitals (psi in top equation) represent the single particle basis. Hence &amp;quot;single particle equations&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;What is somewhat confusing is how standard DFT approximates the exchange-correlation energy. This is due to some approximate exchange-correlation functional being evaulated, which usually requires integration over a real space grid (the Vxc matrix is built in a similar fashion). Normally this doesn't describe a systems true exchange-correlation and is why DFT is approximate; however, once the approximation is made then yes you are just solving single particle equations (the top equation you posted).&lt;/p&gt;&#xA;&lt;p&gt;HOWEVER, you can completely ignore this step and use wavefunction methods to generate the TRUE exchange-correlation energy. This is known as the Levy-Lieb density functional and very much shows how the ground state can be an entangled superposition state.&lt;/p&gt;&#xA;&lt;p&gt;^Further info on Levy-Lieb. Lots of wavefunctions give a single electron density... the idea of Levy-Lieb density functional is given a particular electron denstiy find all wavefunctions that will give that particular electron density. Then evaluate the true Colomb and Exchange operators using wavefucntion methods for all these wavefunctions and pick the wavefunction that gives the lowest energy. This will be the ground state!&lt;/p&gt;&#xA;" OwnerUserId="4349" LastEditorUserId="4349" LastEditDate="2022-08-18T13:47:15.970" LastActivityDate="2022-08-18T13:47:15.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9563" PostTypeId="2" ParentId="9550" CreationDate="2022-08-18T20:41:11.730" Score="4" Body="&lt;p&gt;mcsqs is not supported by mpi. Each process of mcsqs can be run on only one core. However, as a Monte Carlo method, you can still parallelize. You can concurrently run multiple processes on different cores, but with each process having a different random seed.&lt;/p&gt;&#xA;&lt;p&gt;For example,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcsqs -n=108 -ip=1 -sd=933009 &amp;amp;&#xA;mcsqs -n=108 -ip=2 -sd=112980 &amp;amp;&#xA;.&#xA;.&#xA;.&#xA;&#xA;mcsqs -n=108 -ip=64 -sd=933009 &amp;amp;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Extra resource: &lt;a href=&quot;https://cniu.me/2017/08/05/SQS.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;How to use SQS for disordered materials&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5880" LastEditorUserId="7" LastEditDate="2022-08-19T01:41:34.377" LastActivityDate="2022-08-19T01:41:34.377" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9565" PostTypeId="1" CreationDate="2022-08-19T10:42:50.543" Score="3" ViewCount="1383" Body="&lt;p&gt;I have a computer equipped with two Intel Xeon cpus(6 core @2.67GHz each) and 64GB RAM.&lt;/p&gt;&#xA;&lt;p&gt;I think there is no problem in my gaussian input file except for link0 section. I selected 6 cores and 10GB ram. I guessed it is quite doable for my pc. But Gaussian 09W gave me the &amp;quot;link died&amp;quot;(#2070). The reason why I am pretty sure there is no problem on other section is computation works well if I choose 1GB ram and 1 core.&lt;/p&gt;&#xA;&lt;p&gt;Do you have an idea to select link0 (mem and cpu core) properly?&lt;/p&gt;&#xA;" OwnerUserId="5806" LastActivityDate="2022-08-19T10:42:50.543" Title="Gaussian Software Package: #2070 error (maybe on link0)" Tags="|computational-chemistry|molecular-modeling|gaussian|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-09T23:02:18.180" ContentLicense="CC BY-SA 4.0" />
  <row Id="9566" PostTypeId="1" AcceptedAnswerId="9578" CreationDate="2022-08-19T10:50:59.270" Score="7" ViewCount="457" Body="&lt;p&gt;I have been working on trying to calculate the  effective mass in different directions by fitting a parabola to the VBM and CBM and using the fitted parameters to calculate &lt;span class=&quot;math-container&quot;&gt;$\frac{d^2E}{dk^2}$&lt;/span&gt;. And then we evaluate the value of effective mass using this. First we start by calculating the band structure along the high symmetry points and we use this in order to identify the location of CBM and VBM.&lt;/p&gt;&#xA;&lt;p&gt;Once we know the exact location of the k point, we plan on the performing variation along different directions in order to get &lt;span class=&quot;math-container&quot;&gt;$m^*_{hkl}$&lt;/span&gt;, but I am a bit confused about how do I choose the said [hkl] direction. Furthermore how is the [hkl] direction even realized in the reciprocal space, I do know that the [hkl] direction is perpendicular wrt the (hkl) plane in real space. But how would I vary the coordinates in the k space. Like let's say my high symmetry point lies at (0,0.5,0)&#xA;How should I do the small variations that would span some space.&lt;/p&gt;&#xA;&lt;p&gt;Two possible ways to do this that I can think of -&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;We do the variation along (x,y,z) directions as is defined by Quantum Espresso. But I am not sure how would we explain it, because we are also uncertain about the miller indices we have to assign to it.&lt;/li&gt;&#xA;&lt;li&gt;We would define longitudinal and transverse directions, longitudinal direction is the direction joining Gamma - and the high symmetry point which has CBM or VBM. The transverse will be simply perpendicular to this. This has been done &lt;a href=&quot;https://docs.quantumatk.com/tutorials/effective_mass/effective_mass.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;http://apachepersonal.miun.se/%7Egorthu/halvledare/Effective%20mass%20in%20semiconductors.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. But how would we define directions for Gamma point&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Thanks!!&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5602" LastEditDate="2022-08-19T22:25:46.920" LastActivityDate="2022-08-25T10:58:29.227" Title="How does one decide the directions in which they will calculate effective mass?" Tags="|crystallography|effective-mass|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9567" PostTypeId="1" CreationDate="2022-08-19T12:10:30.247" Score="2" ViewCount="455" Body="&lt;p&gt;This is a follow-up question to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9518/5707&quot;&gt;this one&lt;/a&gt; I asked a few days ago. I in the meantime talked to my teacher and generate all the necessary integrals in PySCF. For the one electron integrals that isn't an issue since It's a simple &lt;span class=&quot;math-container&quot;&gt;$n^2$&lt;/span&gt; matrix that's being returned. This is my code for the one electron integrals&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pyscf import gto&#xA;&#xA;mol = gto.M(atom=&amp;quot;Ne 0 0 0&amp;quot;, basis=&amp;quot;STO-3G&amp;quot;)&#xA;S = mol.intor(&amp;quot;int1e_ovlp&amp;quot;, hermi=1)&#xA;T = mol.intor(&amp;quot;int1e_nuc&amp;quot;, hermi=1)&#xA;K = mol.intor(&amp;quot;int1e_kin&amp;quot;, hermi=1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I calculate the two electron integrals this way&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;EE = mol.intor(&amp;quot;int2e&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here now comes the problem. I can't quite figure out how to retrieve the necessary integrals for a certain element in the fock matrix. While working on restricted hartree fock theory in my paper I defined one element of the fock matrix as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$F_{\mu \nu } = H_{\mu \nu }^{core} + \sum_{\lambda = 1}^{K} \sum_{\sigma = 1}^{K} P_{\lambda \sigma} \left( \left( \mu \sigma \mid \hat{h}_{2} \mid \nu \lambda \right) - \frac{1}{2} \left( \mu \sigma \mid \hat{h}_2 \mid \lambda \nu \right) \right),$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ P_{\lambda \sigma} = 2 \sum_{c=1}^{N/2} C_{\lambda c} C_{\sigma c}^{*}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$H_{\mu \nu }^{core}$&lt;/span&gt; part isn't an issue since that would just be a sum of my T- and K-matrix. But how do I find the right integrals to use as &lt;span class=&quot;math-container&quot;&gt;$\left( \mu \sigma \mid \hat{h}_{2} \mid \nu \lambda \right)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\left( \mu \sigma \mid \hat{h}_2 \mid \lambda \nu \right)$&lt;/span&gt; in the EE-matrix?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can anyone explain the structure of the matrix to me that is returned by pyscf?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5707" LastEditorUserId="5" LastEditDate="2022-08-19T14:52:08.677" LastActivityDate="2022-08-19T14:52:08.677" Title="How to read two electron integrals from pyscf" Tags="|hartree-fock|self-consistent-field|pyscf|integrals|fcidump|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-20T03:20:05.823" ContentLicense="CC BY-SA 4.0" />
  <row Id="9568" PostTypeId="1" CreationDate="2022-08-19T23:34:26.917" Score="4" ViewCount="65" Body="&lt;h3&gt;Background:&lt;/h3&gt;&#xA;&lt;p&gt;Surface science experiments very often start with &lt;em&gt;atomically smooth&lt;/em&gt; crystal surfaces as substrates. After one experiment ends the surface is sputter cleaned with cycles of keV energy argon ions alternated with moderate thermal anneals of the local surface damage induced by the ions to recover a crystalline surface.&lt;/p&gt;&#xA;&lt;p&gt;However &lt;em&gt;newly manufactured&lt;/em&gt; crystal substrates are diced with a saw from a large crystal than abrasively ground only to optical or &amp;quot;mirror-smoothness&amp;quot; with roughness of the order of 100 Å rms. For a typical metal fcc(111) surface that may be 40 monolayers rms.&lt;/p&gt;&#xA;&lt;p&gt;Thermal anneals can produce local &lt;em&gt;atomic smoothness&lt;/em&gt; such that surface states appear in &lt;a href=&quot;https://en.wikipedia.org/wiki/Angle-resolved_photoemission_spectroscopy&quot; rel=&quot;nofollow noreferrer&quot;&gt;angle resolved photoemission spectroscopy (ARPES)&lt;/a&gt; but since these can occur on vicinal surfaces with several degrees of miscut from (111) they don't require planarity. In these cases &lt;a href=&quot;https://en.wikipedia.org/wiki/Low-energy_electron_diffraction&quot; rel=&quot;nofollow noreferrer&quot;&gt;low energy electron diffraction (LEED) patterns&lt;/a&gt; confirm the absence of any single well-defined crystal plane.&lt;/p&gt;&#xA;&lt;p&gt;Thus for new samples whose surfaces are still rough at tens of monolayers, a higher temperature anneal may be required in order to induce &amp;quot;surface melting&amp;quot; or at least high mobility of the atoms at the surface in order for them to move distances of the order of microns and &amp;quot;fill in&amp;quot; the valleys and reduce the peaks, with the ultimate goal of establishing large areas of atomic planarity with an acceptable density of individual step edges consistent with the global surface miscut from the target crystal plane.&lt;/p&gt;&#xA;&lt;h3&gt;Enquiry:&lt;/h3&gt;&#xA;&lt;p&gt;In order to understand roughly what temperature will be necessary to &amp;quot;melt the surface&amp;quot; and achieve atomic planarization of this mechanically ground metal surface, I'd like to understand better:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What are the basic principles (and vocabulary&lt;sup&gt;1&lt;/sup&gt;) necessary to begin modeling&lt;sup&gt;2&lt;/sup&gt; the rate of atom surface diffusion and thermal planarization of rough metal surfaces?&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt;Answers to the &amp;quot;vocabulary&amp;quot; bit will help me to pursue further reading on my own.&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt;Since &amp;quot;melting the mountains and filling in the lakes&amp;quot; requires &lt;a href=&quot;http://www.roentzsch.org/SurfDiff/&quot; rel=&quot;nofollow noreferrer&quot;&gt;vicinal surface diffusion&lt;/a&gt; I'm afraid this will be challenging to model with a simple &lt;em&gt;ad hoc&lt;/em&gt; program, even in 1D, but I would like to try. Perhaps there are surface energies for various surfaces that I can use in a simple model to estimate mobilities and therefore an approximate time vs temperature plot. We obviously don't want to melt the bulk or get even close to that, but I think &amp;quot;surface melting&amp;quot; concept applies here.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I think that the thermally-induced relaxation and planarization of nanofabricated artificial structures on metal surfaces has been studied in the past (gold is &lt;em&gt;especially&lt;/em&gt; mobile in this regard) but that was decades ago and so far I can't find evidence of that line of research in the literature because I simply haven't found the right combinations of terms of the era to search for. See for example the (currently unanswered) question in Physics SE &lt;a href=&quot;https://physics.stackexchange.com/q/334656/83380&quot;&gt;&amp;quot;half-life&amp;quot; of a holographic grating imprinted on gold?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2022-08-21T15:41:42.297" LastActivityDate="2022-08-25T13:26:42.667" Title="Basic principles (and vocabulary) necessary to begin modeling the rate of atom surface diffusion and thermal planarization of ground metal surfaces?" Tags="|crystallography|surfaces|terminology|metals|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9569" PostTypeId="2" ParentId="9384" CreationDate="2022-08-20T01:01:58.547" Score="8" Body="&lt;p&gt;There are two major computational resources we should consider: the computational time, and the computational storage (RAM).&lt;/p&gt;&#xA;&lt;h3&gt;Computational time&lt;/h3&gt;&#xA;&lt;p&gt;In conventional DFT, the computational time scales linearly with the number of k-points, and cubically with the number of electrons (in the limit of large simulations; for modest simulation sizes it may appear to scale quadratically).&lt;/p&gt;&#xA;&lt;p&gt;The reason it scales linearly with k-points is straightforward: the Kohn-Sham equations have a k-point index on all quantities:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}^{KS}_k[\rho]\psi_{bk} = \epsilon_{bk} \psi_{bk},\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; is a band index (essentially an electron index) and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is a k-point index. Therefore the states at different k-points are independent of each other, and the cost of more k-points is just the cost of the calculations at the extra k-points.&lt;/p&gt;&#xA;&lt;p&gt;The solutions at different k-points are coupled via the density,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho(r) = \sum_{bk}f_{bk}\vert\psi_{bk}(r)\vert^2,\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt; are the band-occupancies. However, this cost also scales linearly with k-points.&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham wavefunctions must form an orthonormal set, and must be eigenstates of the Hamiltonian in the computed subspace. Both of these involve constructing a band-band matrix, and either inverting (orthonormalisation) or diagonalising (finding the eigenstates of the subspace Hamiltonian). Matrix inversion and matrix diagonalisation both scale as the cube of the number of matrix rows, hence this part of a DFT calculation scales cubically with the number of bands, and thus cubically with the number of electrons.&lt;/p&gt;&#xA;&lt;h3&gt;Computational storage&lt;/h3&gt;&#xA;&lt;p&gt;The computational storage scales linearly with the number of k-points, for the same reasons as for computational time. The scaling with the number of electrons is, &lt;em&gt;strictly-speaking&lt;/em&gt;, quadratic, since the band-overlap and subspace Hamiltonian matrices scale quadratically with the number of electrons. However, in practice the storage is usually dominated by the Kohn-Sham wavefunctions and the non-local pseudopotential projectors (if stored in the full representation), both of which scale linearly with the number of electrons.&lt;/p&gt;&#xA;&lt;h3&gt;Conclusion&lt;/h3&gt;&#xA;&lt;p&gt;Since the scaling with the number of electrons is always a higher-order than the scaling with k-points, the number of electrons is more significant in determining the computational cost of a large simulation.&lt;/p&gt;&#xA;&lt;h3&gt;Subtleties and details&lt;/h3&gt;&#xA;&lt;h5&gt;Parallel complications&lt;/h5&gt;&#xA;&lt;p&gt;On a high-performance computer, it is relatively trivial to parallelise over k-points since almost all calculations only require summations over the k-points, but parallelising over electrons (i.e. Kohn-Sham bands) requires all-to-all communications; thus, it is much more efficient to run a many-k-point calculation than a many-electron calculation.&lt;/p&gt;&#xA;&lt;h5&gt;Non-local/hybrid functionals&lt;/h5&gt;&#xA;&lt;p&gt;A straightforward implementation of generalised DFT with non-local or hybrid functionals (e.g. HSE06) causes the computational time to scale quadratically with the number of k-points, rather than linearly. However, VASP has various approximate forms for non-local functionals, some of which ignore the interactions between k and k', which means they scale linearly with k-points again (but aren't strictly correct...)&lt;/p&gt;&#xA;&lt;p&gt;These classes of functionals also scale quadratically in time with the number of electrons, but this is better scaling than other operations in DFT so doesn't affect the large-system behaviour.&lt;/p&gt;&#xA;&lt;h5&gt;Linear-scaling DFT&lt;/h5&gt;&#xA;&lt;p&gt;So far, I've focused on conventional DFT such as is implemented in VASP (or ABINIT, CASTEP, Quantum Espresso...). There are also linear-scaling DFT programs (e.g. ONETEP, CONQUEST; also some operational modes of SIESTA, CP2K etc) and in these cases both the computational time and storage should scale linearly with the number of electrons (band) as well as k-points.&lt;/p&gt;&#xA;&lt;h5&gt;Caveats&lt;/h5&gt;&#xA;&lt;p&gt;I've assumed that &lt;em&gt;only&lt;/em&gt; the numbers of electrons and/or k-points are changing; in particular, I have assumed that the simulation volume is constant.&lt;/p&gt;&#xA;&lt;p&gt;I've only considered the computational cost of calculating the Kohn-Sham ground state. Certain properties scale differently, for example Fermi-surface integrals require double-integrals over k-points, so scale quadratically with k-points; they also only involve states on (or near) the Fermi surface, so there are far fewer bands active in this part of the calculation and it tends to scale sub-linearly with the number of electrons (roughly speaking, as the square-root).&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="5" LastEditDate="2022-08-20T04:17:09.727" LastActivityDate="2022-08-20T04:17:09.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9570" PostTypeId="1" CreationDate="2022-08-20T21:17:40.013" Score="6" ViewCount="1076" Body="&lt;p&gt;I am using RDKit to generate Morgan Fingerprints (similar to ECFP) and then obtaining the bit information. I need the bit information in order to generate a statistics of substructures for each position of fingerprint.&lt;/p&gt;&#xA;&lt;p&gt;I am using the code that is given in the RDkit getting started page (&lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html#explaining-bits-from-morgan-fingerprints&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;). My code looks something like this (unimportant parts are edited out):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.rdMolDescriptors import GetHashedMorganFingerprint&#xA;&#xA;# for loop begins&#xA;mol = Chem.MolFromSmiles('CCCNCCC=O') # or some other SMILES&#xA;bit_info = {}&#xA;fp = GetHashedMorganFingerprint(mol, 3, bitInfo=bit_info) # eqv to ECFP6&#xA;&#xA;atomidx, radius = bit_info[118][0] # 118 is the position that I am studying for example&#xA;env = Chem.FindAtomEnvironmentOfRadiusN(mol, radius, atomidx) # returns rdkit vector&#xA;submol = Chem.PathToSubmol(mol,env)&#xA;# store SMARTS somehow&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now this submol should contain the substructure fragment that is hashed into the 118 bit position in fingerprint.&lt;/p&gt;&#xA;&lt;p&gt;I want to convert this substructure fragment into a SMARTS pattern (not a SMILES string). RDkit does allow me to use &lt;code&gt;Chem.MolToSmarts()&lt;/code&gt; on &lt;code&gt;submol&lt;/code&gt;. However, if I run it on position 118, then I get this SMARTS, visualised by SMARTS plus:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OebFe.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OebFe.png&quot; alt=&quot;CCC=O fragment&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I want the SMARTS to include information on the bonds that are attached to the outside of the fragment, because that information is also used by the fingerprint. So I want my SMARTS to show this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lGw9N.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lGw9N.png&quot; alt=&quot;new SMARTS, shows connectivity&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know that these images can be produced by &lt;code&gt;rdkit.Chem.Draw.DrawMorganBit&lt;/code&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/OPmS4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OPmS4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;But I cannot use images as I need to sort through ~ 3000 molecules.&lt;/strong&gt; So I need those substructures in SMARTS form so that I can compare them.&lt;/p&gt;&#xA;&lt;p&gt;Another big problem is that &lt;code&gt;PathToSubmol()&lt;/code&gt; does not seem to work if you set &lt;code&gt;radius=0&lt;/code&gt; which is true for many bit positions in fingerprint. But DrawMorganBit can handle the cases where radius=0.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So, I essentially need what the &lt;code&gt;DrawMorganBit&lt;/code&gt; is showing, but in SMARTS format.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;After I have the SMARTS, I can essentially compare fragments and different bit positions (that's a part of analysis for my research). I cannot use only the &lt;code&gt;submol&lt;/code&gt; because it has missing connectivity information which is relevant during the hashing, so it determines the bit position where the fragment appears.&lt;/p&gt;&#xA;&lt;p&gt;How can I achieve this?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2022-08-25T17:10:38.213" Title="How to obtain fingerprint bits as SMARTS pattern in RDKit" Tags="|python|rdkit|cheminformatics|fingerprint|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9571" PostTypeId="2" ParentId="9570" CreationDate="2022-08-21T16:52:30.193" Score="4" Body="&lt;p&gt;I'm not entirely sure I understand your question. You want a SMARTS that matches &lt;code&gt;DrawMorganBit&lt;/code&gt; but with an extra &lt;code&gt;*&lt;/code&gt; added?&lt;/p&gt;&#xA;&lt;p&gt;If you look at the code for &lt;code&gt;DrawMorganBit&lt;/code&gt; you can see it boils down to an &lt;a href=&quot;https://github.com/rdkit/rdkit/blob/0e7871dc5ed7a690cae9607de0ce866e49a886b4/rdkit/Chem/Draw/__init__.py#L736&quot; rel=&quot;noreferrer&quot;&gt;internal method _getMorganEnv&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  if not mol.GetNumConformers():&#xA;    rdDepictor.Compute2DCoords(mol)&#xA;  bitPath = Chem.FindAtomEnvironmentOfRadiusN(mol, radius, atomId)&#xA;&#xA;  # get the atoms for highlighting&#xA;  atomsToUse = set((atomId, ))&#xA;  for b in bitPath:&#xA;    atomsToUse.add(mol.GetBondWithIdx(b).GetBeginAtomIdx())&#xA;    atomsToUse.add(mol.GetBondWithIdx(b).GetEndAtomIdx())&#xA;&#xA;  #  enlarge the environment by one further bond&#xA;  enlargedEnv = set()&#xA;  for atom in atomsToUse:&#xA;    a = mol.GetAtomWithIdx(atom)&#xA;    for b in a.GetBonds():&#xA;      bidx = b.GetIdx()&#xA;      if bidx not in bitPath:&#xA;        enlargedEnv.add(bidx)&#xA;  enlargedEnv = list(enlargedEnv)&#xA;  enlargedEnv += bitPath&#xA;  # … (more code to get coordinates, etc.)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In other words, you can do &lt;em&gt;exactly&lt;/em&gt; the same thing to enlarge your &lt;code&gt;submol&lt;/code&gt; if that's what you want.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-08-21T16:52:30.193" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9572" PostTypeId="2" ParentId="9078" CreationDate="2022-08-21T17:28:40.700" Score="3" Body="&lt;p&gt;Since the &amp;quot;Getting started&amp;quot; link &lt;a href=&quot;https://archive.ph/8eSOb&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; is broken, and neither the word &amp;quot;download&amp;quot; nor &amp;quot;install&amp;quot; appear &lt;a href=&quot;https://people.bath.ac.uk/chsscp/teach/metadise.bho/pages/metadise.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; or &lt;a href=&quot;https://people.bath.ac.uk/chsscp/group/programs/programs.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, and &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/1996/ft/ft9969200433&quot; rel=&quot;nofollow noreferrer&quot;&gt;this 1996 paper&lt;/a&gt; about &amp;quot;this new computer simulation code METADISE&amp;quot; doesn't mention anything about the code's availability, I think it's fair to assume that this code is not available for anyone from the public to download it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://people.bath.ac.uk/chsscp/teach/metadise.bho/pages/metadise_blog.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;This tutorial&lt;/a&gt; which appears to be for students at the University of Bath tells students to begin by following this instruction:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Copy all source files of latest version from Aragonite/data2/Steve&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;which suggests that even for people doing a class about METADISE, the only way (or at least, the easiest way) to obtain the software was to copy it directly from Steve Parker's folder, which would require you to have access to a very specific computer.&lt;/p&gt;&#xA;&lt;p&gt;I agree with &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9078/how-to-download-metadise-code?noredirect=1#comment18952_9078&quot;&gt;the suggestion by Tyberius&lt;/a&gt; which was to contact the author directly. &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9078/how-to-download-metadise-code?noredirect=1#comment19962_9078&quot;&gt;Since you did that multiple times already&lt;/a&gt;, you might want to see if other people who claim to have used the software (for example, the authors of &lt;a href=&quot;https://ceramics.onlinelibrary.wiley.com/doi/pdf/10.1111/jace.14858&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; can shed light on how they obtained it!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-08-21T17:28:40.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9573" PostTypeId="1" CreationDate="2022-08-22T06:31:09.377" Score="5" ViewCount="96" Body="&lt;p&gt;I am trying to find the most stable facet for a crystal, but since there are many possible choices, like (1 0 0),(1 1 0),(1 1 1),(2 1 0), etc. My questions is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am wondering how should I determine the potential stable facets and then do more precise calculations to verify which one is the most stable facet?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-08-22T15:02:42.963" LastActivityDate="2022-08-22T15:02:42.963" Title="How to find the most stable facet for a crystal?" Tags="|density-functional-theory|crystallography|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9574" PostTypeId="1" CreationDate="2022-08-22T07:22:15.547" Score="5" ViewCount="284" Body="&lt;p&gt;Using the same inputs in &lt;a href=&quot;https://github.com/matbinder/pyprocar-example/blob/master/pyprocar.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; I re-implemented the band structure and projected density of state calculations using Quantum Espresso, then I used the same command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyprocar&#xA;pyprocar.bandsplot(code='qe',mode='plain', elimit=[-18,-8])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to plot the bands using PyProcar, I get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/B89dw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B89dw.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which is clearly different from the original one &lt;a href=&quot;https://github.com/matbinder/pyprocar-example/blob/master/pyprocar.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. It seems to me the bands have been shifted by 2E_F.&lt;/p&gt;&#xA;&lt;p&gt;Is there any explanation?&lt;/p&gt;&#xA;" OwnerUserId="5853" LastEditorUserId="671" LastEditDate="2022-10-19T13:59:28.013" LastActivityDate="2022-10-19T13:59:28.013" Title="Bands shift in PyProcar and quantum espresso" Tags="|quantum-espresso|pyprocar|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9575" PostTypeId="1" AcceptedAnswerId="9619" CreationDate="2022-08-22T07:43:33.507" Score="2" ViewCount="185" Body="&lt;p&gt;I would like to know if I can get/generate semicore pseudopotentials (some core electrons are also considered along with valence electrons) to be used in Quantum Espresso DFT. Actually, it would be more helpful to know the steps/procedure to get semicore pseudopotentials of any materials of the periodic table.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-09-02T18:26:15.487" Title="Need help about how I can get/generate semicore pseudopotentials to be used in Quantum Espresso DFT?" Tags="|density-functional-theory|quantum-espresso|electronic-structure|pseudopotentials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9576" PostTypeId="5" CreationDate="2022-08-22T15:01:07.257" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-22T15:01:07.257" LastActivityDate="2022-08-22T15:01:07.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9577" PostTypeId="4" CreationDate="2022-08-22T15:01:07.257" Score="0" Body="Questions about PyProcar." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-08-22T15:01:07.257" LastActivityDate="2022-08-22T15:01:07.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9578" PostTypeId="2" ParentId="9566" CreationDate="2022-08-23T13:22:08.123" Score="7" Body="&lt;p&gt;The effective mass of a particle is not a scalar, but a &lt;em&gt;rank-2 tensor&lt;/em&gt;, defined by,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(\frac{1}{m}\right)_{ij} = \frac{1}{\hbar^2}\frac{d^2E}{dk_idk_j}, \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; label reciprocal-space directions, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the band energy and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is a reciprocal-space vector.&lt;/p&gt;&#xA;&lt;p&gt;The eigenvalues of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{m}$&lt;/span&gt; are the effective masses, and the eigenvectors are the corresponding directions; these directions give the basis in which the effective mass tensor is diagonal, and so form a natural basis in which to specify the effective masses.&lt;/p&gt;&#xA;&lt;p&gt;This means that, in general, &lt;em&gt;you should calculate all nine elements of the tensor&lt;/em&gt; (although it's symmetric, so only six are independent) and diagonalise it to find the eigenvectors and eigenvalues. This is more work than a single direction, but it means that you don't have to worry about &amp;quot;getting the direction wrong&amp;quot; because the natural directions will be calculated for you.&lt;/p&gt;&#xA;&lt;h5&gt;Isotropic systems&lt;/h5&gt;&#xA;&lt;p&gt;If your system is isotropic, then all of the effective masses are the same. In this case, the tensor will be diagonal in any coordinate system and you can just talk about a single scalar as &amp;quot;the effective mass&amp;quot;. An obvious example of this is free space, where we write equations such as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{F} = m\vec{a}, \tag{2}&#xA;$$&lt;/span&gt;&#xA;(where &lt;span class=&quot;math-container&quot;&gt;$\vec{F}$&lt;/span&gt; is a force, and &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; an acceleration) and we often forget that &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; is actually of rank 2 (not 0).&lt;/p&gt;&#xA;&lt;h3&gt;Calculating the effective mass tensor&lt;/h3&gt;&#xA;&lt;p&gt;In principle, it's straightforward to calculate the effective mass tensor by finite difference of either the band energy directly, or its reciprocal-space gradient, &lt;span class=&quot;math-container&quot;&gt;$\nabla_kE$&lt;/span&gt;. However, in practice the units of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points can be rather confusing, both in terms of formulating the mathematics correctly, and implementing it in your &lt;em&gt;ab initio&lt;/em&gt; modelling program of choice.&lt;/p&gt;&#xA;&lt;p&gt;When k-points are specified in fractional coordinates, they are fractions of the reciprocal-lattice vectors; e.g. a k-point specified as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{k} = (0.2 , 0.4, 0.5), \tag{3}&#xA;$$&lt;/span&gt;&#xA;actually means the vector&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{k} = 0.2\vec{A}^\ast + 0.4\vec{B}^\ast + 0.5\vec{C}^\ast, \tag{4}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\vec{A}^\ast$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\vec{B}^\ast$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{C}^\ast$&lt;/span&gt; are the reciprocal-lattice vectors.&lt;/p&gt;&#xA;&lt;p&gt;When we calculate the effective mass tensor by finite-difference, it's common to change the &lt;em&gt;fractional&lt;/em&gt; coordinates of &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt;, but the derivative is defined in terms of the change in actual reciprocal-space coordinates, so you need to convert the &lt;span class=&quot;math-container&quot;&gt;$\delta\vec{k}$&lt;/span&gt; into a reciprocal-distance by multiplying by the reciprocal-lattice vectors.&lt;/p&gt;&#xA;&lt;h3&gt;Why mass is a rank-2 tensor&lt;/h3&gt;&#xA;&lt;p&gt;It's easy to state that mass is a rank-2 tensor, but it may not be clear why this is so. Newton's 2nd Law tells us that force, &lt;span class=&quot;math-container&quot;&gt;$\vec{F}$&lt;/span&gt;, and acceleration &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt; are linearly related, and that mass is the constant of proportionality.&lt;/p&gt;&#xA;&lt;h5&gt;Scalars and linear relationships&lt;/h5&gt;&#xA;&lt;p&gt;We are trained from an early age to think about mass as a scalar (rank-0 tensor) quantity, such that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{F} = m\vec{a}&#xA;\Rightarrow F_i = ma_i, \tag{5}&#xA;$$&lt;/span&gt;&#xA;i.e. the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th component of the force vector is &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; times the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th component of the acceleration.&lt;/p&gt;&#xA;&lt;p&gt;Thus, when mass is a scalar, the force and acceleration are &lt;em&gt;always&lt;/em&gt; parallel. We are used to this physically, as we expect an object to accelerate in the direction in which we pull it.&lt;/p&gt;&#xA;&lt;h5&gt;General linear relationships&lt;/h5&gt;&#xA;&lt;p&gt;An expression where &lt;span class=&quot;math-container&quot;&gt;$F_i$&lt;/span&gt; depends only on &lt;span class=&quot;math-container&quot;&gt;$a_i$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt; the most general linear relationship. There is no fundamental reason why, for example, the 1st component of the force should not be linearly related to the 3rd component of the acceleration,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_1 = m_{13} a_3,\tag{6}&#xA;$$&lt;/span&gt;&#xA;(for some constant &lt;span class=&quot;math-container&quot;&gt;$m_{13}$&lt;/span&gt;) or even a combination of all the components of &lt;span class=&quot;math-container&quot;&gt;$\vec{a}$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_1 = m_{11} a_1 + m_{12} a_2 + m_{13} a_3 = \sum_j m_{1j}a_j,\tag{7}&#xA;$$&lt;/span&gt;&#xA;with the additional constants &lt;span class=&quot;math-container&quot;&gt;$m_{11}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m_{12}$&lt;/span&gt; as well. The same holds for &lt;span class=&quot;math-container&quot;&gt;$F_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$F_3$&lt;/span&gt;, and so we can write a more general expression,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_i = \sum_{j} m_{ij}a_j.\tag{8}&#xA;$$&lt;/span&gt;&#xA;which is a general linear relationship between all of the components of the force and all of the components of the acceleration. If we look at this expression mathematically, we see that it is exactly the same as the matrix-vector product in component form,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_i = \left(\mathrm{M}\vec{a}\right)_i,\tag{9}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\matrix{M}$&lt;/span&gt; is a rank-2 tensor (expressed as a matrix in any given coordinate system).&lt;/p&gt;&#xA;&lt;h5&gt;Physical meaning&lt;/h5&gt;&#xA;&lt;p&gt;Since mass is a rank-2 tensor, then there can be cases where we exert a force on an object and it accelerates in a &lt;em&gt;different&lt;/em&gt; direction (not parallel to the force). Empirically, we might observe such an effect if we pull a wheeled vehicle at an angle not parallel to the direction of the wheels; the vehicle will preferentially accelerate in the direction the wheels are pointing in, rather than parallel to the force.&lt;/p&gt;&#xA;&lt;p&gt;The effective mass of a particle arises due to interactions between the particle and the material, and if the material is not isotropic then there is no reason to expect that the mass will be isotropic either. In the everyday case of electrons flowing in a wire, the electrons will flow down the wire even if the electric field is not parallel to the wire.&lt;/p&gt;&#xA;&lt;p&gt;This is why it's risky to try to determine the direction of propagation first, and then compute the effective mass (energy curvature) in this direction. You will always get a curvature, and so you'll have &amp;quot;an effective mass&amp;quot; for that direction, but unless your chosen direction is an eigenvector of the effective mass tensor, your results doesn't mean what you think it means, because to make the particle travel along that direction would require a force &lt;em&gt;in a different direction, that you haven't calculated!&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-08-25T10:58:29.227" LastActivityDate="2022-08-25T10:58:29.227" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9579" PostTypeId="1" CreationDate="2022-08-23T15:55:20.293" Score="5" ViewCount="119" Body="&lt;p&gt;I am using Orca 4.2.1 for the ab initio calculation. Scanning the redundant coordinates I am trying to scan potential surface for different type of bonds, angles and dihedrals. How can I do so for improper dihedrals in Orca? I will use these surface scanning for forcefield potential fitting.&lt;/p&gt;&#xA;" OwnerUserId="5591" OwnerDisplayName="Md. Rifat Hossain Kawshik" LastEditorUserId="6687" LastEditDate="2023-03-08T08:11:44.947" LastActivityDate="2023-03-08T08:11:44.947" Title="How to scan Improper Dihedral in Orca?" Tags="|density-functional-theory|ab-initio-calculations|orca|" AnswerCount="0" CommentCount="1" ClosedDate="2023-04-20T17:14:55.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="9580" PostTypeId="2" ParentId="9455" CreationDate="2022-08-25T02:39:28.883" Score="2" Body="&lt;p&gt;you can try use pymol to do this.&lt;/p&gt;&#xA;&lt;p&gt;use &lt;strong&gt;Ctrl+middle click&lt;/strong&gt; to pick an atom,e.g.the N atom of first residue,&lt;/p&gt;&#xA;&lt;p&gt;then &amp;gt;&amp;gt;Build&amp;gt;&amp;gt;adresidue&amp;gt;&amp;gt;Ace. same as NME.&lt;/p&gt;&#xA;&lt;p&gt;and save the new structure.&lt;/p&gt;&#xA;" OwnerUserId="5897" LastActivityDate="2022-08-25T02:39:28.883" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9581" PostTypeId="1" AcceptedAnswerId="9584" CreationDate="2022-08-25T08:46:58.823" Score="6" ViewCount="1951" Body="&lt;p&gt;I am using Gaussian 16 to optimize a paraquat molecule on top of a bulk of gold atoms. Some of these gold atoms are frozen, so I use the option &lt;code&gt;opt=modredundant&lt;/code&gt;. I also want to use different basis sets for the calculation of different atoms. I found the option of using &lt;code&gt;gen&lt;/code&gt;.  My root section is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%cpu=48-63&#xA;%mem=50GB&#xA;%chk=paraquat+goldbulk1656.chk&#xA;#p opt=modredundant b3lyp/gen nosymm int=ultrafine&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After the root section, I specify the title, charge, and multiplicity. The &lt;code&gt;.gjf&lt;/code&gt; file includes the coordinates for the atoms and the information on which atoms should be frozen (e.g. &lt;code&gt;X 54 F&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Do I put the code to specify the basis sets after the coordinates, after the frozen atoms, or at the very end of the &lt;code&gt;.gjf&lt;/code&gt; file?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H C N 0&#xA;aug-cc-PVTZ&#xA;&#xA;Au 0&#xA;lanl2dz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you for your answers!&lt;/p&gt;&#xA;" OwnerUserId="5900" LastActivityDate="2022-08-25T11:28:55.267" Title="How to add different basis sets to different atoms in a calculation (Gaussian 16) when freezing certain atoms?" Tags="|gaussian|basis-sets|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9582" PostTypeId="1" AcceptedAnswerId="9585" CreationDate="2022-08-25T09:19:47.357" Score="5" ViewCount="286" Body="&lt;p&gt;I am currently looking at isotropic properties and let's say I want to determine my property in the [100] direction. Now, I basically want that my [100] direction be the same as the [100] direction in an experimental setup.&lt;/p&gt;&#xA;&lt;p&gt;If I switch between the conventional unit cell and primitive unit cell, the direction changes. It changes with respect to the symmetry of an infinite crystal lattice (the primitive cell is a diagonal part of the conventional standard).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/db3qe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/db3qe.png&quot; alt=&quot;Enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8Q1iK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8Q1iK.png&quot; alt=&quot;Enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How do I go about resolving this problem? There must be some standard to set the underlying coordinate systems, otherwise everyone would be getting confused by this.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5" LastEditDate="2022-08-26T11:52:35.297" LastActivityDate="2022-08-26T11:52:35.297" Title="How does one make sure that the [hkl] direction in ab-inito calculations is the same as in experimental calculations?" Tags="|crystallography|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9583" PostTypeId="1" CreationDate="2022-08-25T11:07:13.477" Score="3" ViewCount="73" Body="&lt;p&gt;I am trying to optimize the geometry of a paraquat molecule interacting with a gold bulk. The optimization is stopping after a few steps. The error shown in the &lt;code&gt;.log&lt;/code&gt; file is &amp;quot;Error: hangup&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Is there a posibility to restart the optimization after the hangup error from the &lt;code&gt;.chk&lt;/code&gt; file? If so, how does the new &lt;code&gt;.gjf&lt;/code&gt; file look like?&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your answers!&lt;/p&gt;&#xA;&lt;p&gt;Edit: Here is the Error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error: hangup&#xA;Error: hangup&#xA;   rax 0000000000001318, rbx 00002ab521c484e8, rcx 00002ab521c429e8&#xA;   rdx 00002ab521c08528, rsp 00007ffedcbb6600, rbp 00007ffedcbb6a30&#xA;   rsi 00002ab521c440a8, rdi 00002ab521c09be8, r8  00002ab521c45768&#xA;   r9  00002ab521c0b2a8, r10 00002ab521c46e28, r11 00002ab521c0c968&#xA;   r12 00002ab521c0e028, r13 00002ab521c49ba8, r14 00002ab521c262e8&#xA;   r15 00002ab521c0f6e8&#xA;   rax fffffffffffffffc, rbx 00007ffd823b4610, rcx 00002b3e3d62424a&#xA;   rdx 0000000000000000, rsp 00007ffd823b45d8, rbp 0000000000000001&#xA;   rsi 00007ffd823b4610, rdi 0000000000004d5a, r8  00002b3e3d9063c0&#xA;   r9  00007ffd823b4530, r10 0000000000000000, r11 0000000000000246&#xA;   r12 00007ffd823b4630, r13 00007ffd823ba000, r14 0000000000000000&#xA;   r15 00007ffd823bb000&#xA;  /lib64/libpthread.so.0(+0x11c00) [0x2ab51f8fbc00]&#xA;  /opt/g16/l502.exe() [0x102d3ff]&#xA;  /opt/g16/l502.exe() [0x1029914]&#xA;  /opt/g16/l502.exe() [0xe2d93d]&#xA;  /opt/g16/l502.exe() [0x95b896]&#xA;  /opt/g16/l502.exe() [0x92f836]&#xA;  /opt/g16/l502.exe() [0x6db95b]&#xA;  /opt/g16/l502.exe() [0x4ced25]&#xA;  /opt/g16/l502.exe() [0x4d5515]&#xA;  /opt/g16/l502.exe() [0x4bc6fe]&#xA;  /opt/g16/l502.exe() [0x523c36]&#xA;  /opt/g16/l502.exe() [0x429326]&#xA;  /opt/g16/l502.exe() [0x41b189]&#xA;  /opt/g16/l502.exe() [0x412b1b]&#xA;  /opt/g16/l502.exe() [0x412a24]&#xA;  /lib64/libc.so.6(__libc_start_main+0xf5) [0x2ab51fe27a35]&#xA;  /opt/g16/l502.exe() [0x40d169]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5900" LastEditorUserId="5900" LastEditDate="2022-09-01T06:54:43.813" LastActivityDate="2022-09-01T06:54:43.813" Title="Restart geometry optimization in Gaussian after hangup error" Tags="|gaussian|geometry-optimization|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-14T01:07:52.897" ContentLicense="CC BY-SA 4.0" />
  <row Id="9584" PostTypeId="2" ParentId="9581" CreationDate="2022-08-25T11:28:55.267" Score="6" Body="&lt;p&gt;(1) &lt;code&gt;int=ultrafine&lt;/code&gt; is the default option for g16, so there is no need to write it.&lt;/p&gt;&#xA;&lt;p&gt;(2) You need to use &lt;code&gt;genecp&lt;/code&gt; rather than &lt;code&gt;gen&lt;/code&gt; since LANL2DZ for Au includes ECP. &lt;code&gt;gen&lt;/code&gt; can only deal with all-electron basis set. Alternatively, &lt;code&gt;gen pseudo=read&lt;/code&gt; will also work.&lt;/p&gt;&#xA;&lt;p&gt;(3) aug-cc-pVTZ may be unnecessarily large for a DFT computation. If your &amp;quot;paraquat molecule&amp;quot; is neutral, i.e. net charge is zero, the basis set def2-TZVP is enough (If you want to change it to def2-TZVP, note that &lt;code&gt;def2-TZVP&lt;/code&gt; is used in papers/reference, but &lt;code&gt;def2TZVP&lt;/code&gt; is used in Gaussian input file).&lt;/p&gt;&#xA;&lt;p&gt;(4) The functional B3LYP cannot deal with dispersion or weak interactions correctly. In your case &amp;quot;a paraquat molecule on top of a bulk of gold atoms&amp;quot;, such interactions should be important. You are recommended to use B3LYP-D3(BJ), which should be written as &lt;code&gt;B3LYP em=GD3BJ&lt;/code&gt;. If combined with &lt;code&gt;genecp&lt;/code&gt;, it turns into &lt;code&gt;B3LYP genecp em=GD3BJ&lt;/code&gt; or &lt;code&gt;B3LYP/genecp em=GD3BJ&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(5) Since there may be many gold atoms to be frozen, it becomes tedious if you use &lt;code&gt;opt=modredundant&lt;/code&gt;. You can try another way of freezing, for example,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C  0  0.0   0.0   0.0&#xA;H  0  0.0   0.0   1.0&#xA;Au -1 0.0   0.0   5.0&#xA;...&#xA;Au -1 0.0  10.0   6.0&#xA;&#xA;H C N 0&#xA;def2TZVP&#xA;****&#xA;Au 0&#xA;LANL2DZ&#xA;****&#xA;&#xA;Au 0&#xA;LANL2DZ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;-1&lt;/code&gt; after the element means frozen during geometry optimizations, and &lt;code&gt;0&lt;/code&gt; means its position can be optimized. Do not write &lt;code&gt;opt=modredundant&lt;/code&gt; if you adopt this way of freezing atoms. Besides, the usage of mixed basis set is shown above. Remember to type &lt;strong&gt;two blank lines&lt;/strong&gt; after the final LANL2DZ, Gaussian needs blank lines to detect where it is the end of a file.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2022-08-25T11:28:55.267" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9585" PostTypeId="2" ParentId="9582" CreationDate="2022-08-25T12:06:42.070" Score="6" Body="&lt;p&gt;The Miller indices are defined with respect to your choice of unit cell. Usually, people use the same conventional unit cell, so they mean the same direction by [100]. If not, then they need to somehow sort it out to make sure that they talk about the same direction.&lt;/p&gt;&#xA;&lt;p&gt;From &lt;a href=&quot;http://xrayweb.chem.ou.edu/notes/symmetry.html&quot; rel=&quot;noreferrer&quot;&gt;http://xrayweb.chem.ou.edu/notes/symmetry.html&lt;/a&gt; :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When researchers discuss a particular material, they need to work from one standard or conventional description of the unit cell for that material. Thus crystallographers have chosen the following criteria for selecting unit cells. By convention the unit cell edges are chosen to be &lt;em&gt;right-handed&lt;/em&gt; (&lt;em&gt;a&lt;/em&gt; × &lt;em&gt;b&lt;/em&gt; is the direction of &lt;em&gt;c&lt;/em&gt;), to have the &lt;em&gt;highest symmetry&lt;/em&gt;, and to have the &lt;em&gt;smallest cell volume&lt;/em&gt;. If other symmetry considerations do not override, then the cell is chosen so that &lt;em&gt;a&lt;/em&gt; ≤ &lt;em&gt;b&lt;/em&gt; ≤ &lt;em&gt;c&lt;/em&gt;, and α, β, and γ all &amp;lt; 90° or all ≥ 90°.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In crystallography, it sometimes happens that similar crystals are processed with a different choice of the unit cell (different space group setting). Bringing them to the same reference setting is called re-indexing.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2022-08-25T12:06:42.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9586" PostTypeId="2" ParentId="9582" CreationDate="2022-08-25T12:09:42.750" Score="4" Body="&lt;p&gt;The conventional unit cell and primitive unit cell are just physical concepts used to explore the symmetry of the system. You do the calculation in such cells and then &amp;quot;expand&amp;quot; it to the whole system using symmetry operations.&lt;/p&gt;&#xA;&lt;p&gt;Experimental techniques where you can growth single crystal will produce your material in a, let say, given crystal phase. For that phase, you can identify the conventional and primitive cells. Even if you use a method like &lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular-beam_epitaxy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Beam Epitaxy&lt;/a&gt; and use an oriented substrate, you will have a single crystal where you can define both type of cells.&lt;/p&gt;&#xA;&lt;p&gt;The issue here is that if you run your calculations in a given direction, then the experimental measurements should be done in such a way that the property can be determine in the same direction of your calculations. Or if the experiment was already done, you can use its setup and run the calculation accordingly.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-08-25T12:09:42.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9587" PostTypeId="1" AcceptedAnswerId="9733" CreationDate="2022-08-25T13:13:22.290" Score="6" ViewCount="220" Body="&lt;p&gt;I am trying to understand how long range forces are calculated under the following situation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;SYSTEM-&amp;gt;&lt;/strong&gt; Lets say we have a single protein surrounded by water molecules. Now I would like to run MD simulation for this system. It's NOT a crystal, just single protein and water.&lt;/p&gt;&#xA;&lt;p&gt;Lets first consider short-range forces, i.e. Lennard-Jones. Here we first enclose (for simplicity) our single protein + water molecules in a cubic box. Lets also assume that edge of the cubic box is larger than the cutoff distance, hence the protein can not see its own image. Which is perfect.&lt;/p&gt;&#xA;&lt;p&gt;Now lets consider long range forces. Here the primary tool discussed is Ewald Algorithm. But Ewald sum is based upon calculating potential due to images, i.e. instead of single protein, the algorithm is also taking into account the potential contributed by image proteins which is not the case in LJ potential due to cutoff. Now this algorithm is perfect for crystals, but, as per my understanding, NOT for the system I have described above.&lt;/p&gt;&#xA;&lt;p&gt;Hence I am very confused on calculation of long range forces in my system. Can someone throw some light on this? I am using Gromacs.&lt;/p&gt;&#xA;&lt;p&gt;The only solution I see is to calculate &lt;span class=&quot;math-container&quot;&gt;$\frac {1}{2}\sum_i\sum_j q_jq_j/r_{ij}$&lt;/span&gt; for all pairs of the protein atoms, which will be of &lt;span class=&quot;math-container&quot;&gt;$O(n^2)$&lt;/span&gt; complexity OR Fast Multipole Method using Tree Algorithm, and there is no other way around for my system!&lt;/p&gt;&#xA;" OwnerUserId="5822" LastEditorUserId="5822" LastEditDate="2022-08-25T14:27:15.163" LastActivityDate="2022-10-01T11:15:34.583" Title="Long Range Forces in Protein MD Simuation" Tags="|molecular-dynamics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9588" PostTypeId="2" ParentId="9570" CreationDate="2022-08-25T17:10:38.213" Score="4" Body="&lt;p&gt;Based on your code and the code found by Geoff.&lt;/p&gt;&#xA;&lt;p&gt;Additionally you have to find the neighbors and change their identity.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem.rdMolDescriptors import GetHashedMorganFingerprint&#xA;&#xA;mol = Chem.MolFromSmiles('CCCNCCC=O')&#xA;&#xA;bit_info = {}&#xA;fp = GetHashedMorganFingerprint(mol, 3, bitInfo=bit_info)&#xA;&#xA;atomidx, radius = bit_info[118][0]&#xA;env = Chem.FindAtomEnvironmentOfRadiusN(mol, radius, atomidx)&#xA;&#xA;atomsToUse = set((atomidx, ))&#xA;for b in env:&#xA;    atomsToUse.add(mol.GetBondWithIdx(b).GetBeginAtomIdx())&#xA;    atomsToUse.add(mol.GetBondWithIdx(b).GetEndAtomIdx())&#xA;&#xA;enlargedEnv = set()&#xA;for atom in atomsToUse:&#xA;    a = mol.GetAtomWithIdx(atom)&#xA;    for b in a.GetBonds():&#xA;      bidx = b.GetIdx()&#xA;      if bidx not in env:&#xA;        enlargedEnv.add(bidx)&#xA;&#xA;enlargedEnv = list(enlargedEnv)&#xA;enlargedEnv += env&#xA;&#xA;# find all relevant neighbors&#xA;anyAtoms = []&#xA;for a in atomsToUse:&#xA;    neighbors = mol.GetAtomWithIdx(a).GetNeighbors()&#xA;    for n in neighbors:&#xA;        anyIdx = n.GetIdx()&#xA;        if anyIdx not in atomsToUse:&#xA;            anyAtoms.append(anyIdx)&#xA;&#xA;# replace atomic number to zero (there is no number for any atom)&#xA;for aA in anyAtoms:&#xA;    mol.GetAtomWithIdx(aA).SetAtomicNum(0)&#xA;&#xA;submol = Chem.PathToSubmol(mol, enlargedEnv)&#xA;&#xA;# change [0] to *&#xA;MorganBitSmarts = Chem.MolToSmarts(submol).replace('[#0]', '*')&#xA;print(MorganBitSmarts)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives you &lt;code&gt;*-[#6]-[#6]-[#6]=[#8]&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2022-08-25T17:10:38.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9589" PostTypeId="2" ParentId="9528" CreationDate="2022-08-25T20:32:31.080" Score="4" Body="&lt;p&gt;Your solution is fine in principle, but skirts over a problem in the data: the volume enclosed by the 0.001 boundary is not enclosed within the bounds of the grid a.k.a. watertight!&lt;/p&gt;&#xA;&lt;p&gt;You can generate an isosurface, as suggested by Geoff:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import meshplot as mp&#xA;from skimage import measure&#xA;import trimesh&#xA;&#xA;def parse_cube(filename):&#xA;    #from: https://github.com/psi4/psi4numpy/blob/6ed03e715689ec82bf96fbb23c1855fbe7835b90/Tutorials/14_Visualization/vizualize.ipynb&#xA;    &amp;quot;&amp;quot;&amp;quot; Parses a cube file, returning a dict of the information contained.&#xA;        The cubefile itself is stored in a numpy array. &amp;quot;&amp;quot;&amp;quot;&#xA;    with open(filename) as fp:&#xA;        results = {}&#xA;&#xA;        # skip over the title&#xA;        fp.readline()&#xA;        fp.readline()&#xA;&#xA;        origin = fp.readline().split()&#xA;        natoms = int(origin[0])&#xA;        results['minx'] = minx = float(origin[1])&#xA;        results['miny'] = miny = float(origin[2])&#xA;        results['minz'] = minz = float(origin[3])&#xA;&#xA;        infox = fp.readline().split()&#xA;        numx = int(infox[0])&#xA;        incx = float(infox[1])&#xA;        results['incx'] = incx&#xA;        results['numx'] = numx&#xA;        results['maxx'] = minx + incx * numx&#xA;&#xA;        infoy = fp.readline().split()&#xA;        numy = int(infoy[0])&#xA;        incy = float(infoy[2])&#xA;        results['incy'] = incy&#xA;        results['numy'] = numy&#xA;        results['maxy'] = miny + incy * numy&#xA;&#xA;        infoz = fp.readline().split()&#xA;        numz = int(infoz[0])&#xA;        incz = float(infoz[3])&#xA;        results['incz'] = incz&#xA;        results['numz'] = numz&#xA;        results['maxz'] = minz + incz * numz&#xA;&#xA;        atnums = []&#xA;        coords = []&#xA;        for atom in range(natoms):&#xA;            coordinfo = fp.readline().split()&#xA;            atnums.append(int(coordinfo[0]))&#xA;            coords.append(list(map(float, coordinfo[2:])))&#xA;        results['atom_numbers'] = np.array(atnums)&#xA;        results['atom_coords'] = np.array(coords)&#xA;&#xA;        data = np.array([ float(entry) for line in fp for entry in line.split() ])&#xA;        if len(data) != numx*numy*numz:&#xA;            raise Exception(&amp;quot;Amount of parsed data is inconsistent with header in Cube file!&amp;quot;)&#xA;        results['data'] = data.reshape((numx,numy,numz))&#xA;&#xA;        return results&#xA;&#xA;data = parse_cube('./dat.cube')&#xA;&#xA;#print the grid spacing (if this is Angstrom, it's way too large to be useful)&#xA;print(data['incx'], data['incy'], data['incz'])&#xA;#print the bounds of the density to make sure we choose a sensible cutting point:&#xA;print(data['data'].min(), data['data'].max())&#xA;&#xA;&#xA;#make the isosurface (mesh), cutting at density=0.001 &#xA;vert, faces, norm, values= measure.marching_cubes(data['data'], &#xA;                                                  0.001,&#xA;                                                  spacing=(data['incx'],&#xA;                                                           data['incy'],&#xA;                                                          data['incz']))&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now the vertices and face indices define a mesh that encloses the density higher than the cutoff. The volume can be calculated with trimesh. The volume is negative, indicating the mesh is inside out (not sure why that is):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;m =trimesh.Trimesh(vert, faces)&#xA;print(m.volume)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, note that the mesh is not watertight. You can ask trimesh to calculate that, or verify it visually by seeing the big holes with meshplot:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(m.is_watertight)&#xA;mp.plot(vert, faces)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You could increase the density cutoff until the mesh is watertight, but note that the volumes won't be accurate anyway because the grid spacing is so large. I recommend using 0.3 spacing or less - the grid will be way larger, but the mesh will hug the density more closely, making the volume accurate.&lt;/p&gt;&#xA;" OwnerUserId="2225" LastActivityDate="2022-08-25T20:32:31.080" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9590" PostTypeId="1" CreationDate="2022-08-26T06:43:18.583" Score="3" ViewCount="518" Body="&lt;p&gt;I have a GROMACS trajectory of MD simulation. I want to make a contour plot of density as a function of two coordinates, namely X and Z. Is it possible to get this using &lt;code&gt;gmx density&lt;/code&gt;? If not, is there any other way?&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="3593" LastEditDate="2022-12-20T14:01:25.967" LastActivityDate="2023-08-23T18:38:45.583" Title="How to compute 2D density maps in GROMACS?" Tags="|molecular-dynamics|gromacs|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9591" PostTypeId="1" CreationDate="2022-08-26T18:12:09.567" Score="4" ViewCount="417" Body="&lt;p&gt;The Grand Unified Theory of Classical Physics (GUTCP) is sort of a non-mainstream theory proposed by Mills, &lt;a href=&quot;https://brilliantlightpower.com/book-download-and-streaming/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://brilliantlightpower.com/book-download-and-streaming/&lt;/a&gt;&#xA;Looks like the books showed remarkable accuracy for the energies of atoms:&#xA;E.g., page 253,  24.58741 eV, which is similar to experimental ionization energy&#xA;−24.587387936(25) eV&#xA;&lt;a href=&quot;https://en.wikipedia.org/wiki/Helium_atom&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Helium_atom&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And tables in &lt;a href=&quot;http://www.millsian.com/papers/modeling101208S.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.millsian.com/papers/modeling101208S.pdf&lt;/a&gt;, with a few exceptions e.g., CoF2, ~0.3 eV&lt;/p&gt;&#xA;&lt;p&gt;There are criticisms on &lt;a href=&quot;https://www.physicsforums.com/threads/details-of-millsian-program.303955/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.physicsforums.com/threads/details-of-millsian-program.303955/&lt;/a&gt;, but I found they were mainly on the standard quantum chemical methods side.&lt;/p&gt;&#xA;&lt;p&gt;I have two questions&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Page 253, &amp;quot; With the contribution of the magnetic energy (Eqs. (7.44) and (7.46))), the binding energy of either of the equivalent electrons of helium (Eqs. (7.44-7.46)) is E_B(He) = 24.58741 eV &amp;quot;, How the magnetic energy was evaluated?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Is there any kind of random test for the accuracy of GUTCP? E.g., newly synthesized molecules?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5909" LastEditorUserId="697" LastEditDate="2022-08-26T19:12:52.777" LastActivityDate="2022-08-26T19:12:52.777" Title="Is the Grand Unified Theory of Classical Physics (GUTCP) valid/accurate for atoms and molecules?" Tags="|computational-chemistry|electronic-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9592" PostTypeId="2" ParentId="9591" CreationDate="2022-08-26T19:11:53.997" Score="6" Body="&lt;p&gt;A review of this author and his adventures in this field of &amp;quot;hydrinos&amp;quot; quickly reveals this is likely completely invalid. Their observations in some cases may have been observed experimentally, however it seems they are analyzing artifacts of methods outside of their limits and coming to the conclusion they wish to.&lt;/p&gt;&#xA;&lt;p&gt;Anything and everything related to this theory is likely riddled with issues and should be disregarded in general.  I will note that there are publications on this topic, but publications do not imply correctness.  Even if there is a good agreement on some test set of data in some cases, it is meaningless if it cannot predict a diverse dataset and/or predict new data.&lt;/p&gt;&#xA;&lt;p&gt;Further, it seems this particular paper that gives good agreement is suspect for even being legitimate.  I &lt;a href=&quot;https://www.physicsforums.com/threads/details-of-millsian-program.303955/&quot; rel=&quot;noreferrer&quot;&gt;have found a discussion&lt;/a&gt; where it turns out that the values listed in the paper are not consistent with the databases they list.  They also do not report how they performed these calculations, failing to provide data they must need such as force convergence, etc. To me, this resembles a paper written by someone attempting to emulate real papers but not quite understanding what they are doing.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-08-26T19:11:53.997" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9594" PostTypeId="1" AcceptedAnswerId="9607" CreationDate="2022-08-27T14:10:51.530" Score="5" ViewCount="127" Body="&lt;p&gt;Absolute newbie in quantum chemistry here. I was recently looking through some Fortran libraries from my university to see if I understand all of the mathematics. In a Hartree-Fock library, I found the following code snippet for calculation of the overlap-integral between two contracted s-type GTOs.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; rab = sum( (r_a-r_b)**2 )&#xA;&#xA;    do i=1,npa&#xA;        do j=1,npb&#xA;            eab = alp(i)+bet(j)&#xA;            oab = 1.0_wp/eab&#xA;            cab = ci(i)*cj(j)&#xA;            xab = alp(i)*bet(j)*oab&#xA;            est = rab*xab&#xA;            ab = exp(-est)&#xA;            s00 = cab*ab*sqrt(pi*oab)**3&#xA;&#xA;            !overlap&#xA;            sab = sab+s00&#xA;        enddo&#xA;    enddo&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;with &lt;code&gt;r_a&lt;/code&gt; and &lt;code&gt;r_b&lt;/code&gt; being the positions of the two gaussians in cartesian coordinates and &lt;code&gt;alp(i)&lt;/code&gt; and &lt;code&gt;bet(i)&lt;/code&gt; containing the orbital coefficients of the primitives. From this code snippet I read that the overlap-integral is calculated via:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;K_{AB}=e^{-r_{AB}(\frac{\alpha \beta}{\alpha+\beta})}\tag{1}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S= K_{AB} \cdot \sqrt{\frac{\pi}{\alpha+\beta}}^3\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But if I try to get to this formula myself, I get a slightly different result:&lt;/p&gt;&#xA;&lt;p&gt;For the overlap integral of two Gaussians &lt;span class=&quot;math-container&quot;&gt;$\phi_{A}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi_{B}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_{A}(\alpha,r-R_A)=e^{-\alpha(r-R_A)^2}\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_{B}(\beta,r-R_B)=e^{-\beta(r-R_B)^2}\tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;we can use the Gaussian-product-theorem to combine both Gaussians to one function &lt;span class=&quot;math-container&quot;&gt;$\phi_{AB}$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_{A}(\alpha,r-R_A) \cdot \phi_{B}(\beta,r-R_B) = K_{AB} \cdot \phi_{AB}(\alpha+\beta,r-\frac{\alpha R_A + \beta R_B}{\alpha + \beta})\tag{5}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_{AB} = K_{AB} \cdot \left (\frac{2\alpha\beta}{(\alpha+\beta)\pi} \right )^{\frac{3}{4}} \cdot e^{-\alpha\beta(r-\frac{\alpha R_A+\beta R_B}{\alpha+\beta})^2}\tag{6}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now integrating this Gaussian should yield the overlap integral between our starting functions. The integral of an arbitrary gaussian can be solved via:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\int \phi_A(\alpha ,r-R_A) = \sqrt{\frac{\pi}{\alpha}}\tag{7}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{8}&#xA;\int\phi_{AB}=K_{AB} \cdot \left (\frac{2\alpha\beta}{(\alpha+\beta)\pi}\right )^{\frac{3}{4}} \cdot \sqrt{\frac{\pi}{\alpha\beta}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which, as far as I can see, is already a different equation to the one I read from the code. Where is my mistake? I know this is some pretty basic stuff, any help is appreciated.&lt;/p&gt;&#xA;" OwnerUserId="5912" LastEditorUserId="5" LastEditDate="2022-09-01T19:43:52.263" LastActivityDate="2022-09-01T19:45:22.730" Title="Implementation of one-elecron integrals in a Hartree-Fock program" Tags="|hartree-fock|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9595" PostTypeId="1" AcceptedAnswerId="9615" CreationDate="2022-08-27T16:25:07.667" Score="5" ViewCount="333" Body="&lt;p&gt;I am working on a high school graduation paper on Hartree Fock and have gotten pretty far already. With help from this community, I managed to generate all the necessary integrals and implement the algorithm in python. I am currently checking whether the algorithm is actually doing what it's supposed to do. I compare my values with the ones provided by pyscf. See &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/pyscf/scf/hf.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; example.&lt;/p&gt;&#xA;&lt;p&gt;For noble gases I get correct values. If I try my implementation for molecules however I get too high values. I've tried &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{F2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt;, and  &lt;span class=&quot;math-container&quot;&gt;$\ce{HF}$&lt;/span&gt;. My algorithm works totally fine for atoms so I feel like there can't be something wrong with the implementation itself. I've also tried generating completely random initial guesses. I get the exact same results as well. I therefore feel like the algorithm is stopping on a local minimum or saddle point. Does anybody have an idea how to fix it or whether HF just returns such bad results?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/lela2011/Maturaarbeit/tree/main/HartreeFock&quot; rel=&quot;nofollow noreferrer&quot;&gt;This is my code&lt;/a&gt; if someone wants to check it out and give feedback. It only runs on MacOS and Linux distributions since pyscf can't run on Windows. Help is greatly appreciated since the due date for the paper is getting closer and closer ;)&lt;/p&gt;&#xA;&lt;p&gt;TLDR: &lt;strong&gt;Restricted Hartree Fock SCF Algorithm returns too high orbital energies for molecules, but not for Atoms. How can I fix that?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update:&lt;/strong&gt;&#xA;Here is a list of what I've tried:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;I first checked my code by using a zero matrix as the initial guess. This I compared to the PySCF HF kernels result. The energies are too high.&lt;/li&gt;&#xA;&lt;li&gt;I then checked whether the algorithm is doing anything anyway. I therefore used a completely random initial guess with values ranging between -100 and 100. The algorithm returned the same energies as with the zero matrix as the initial guess.&lt;/li&gt;&#xA;&lt;li&gt;I then checked whether all the matrices are correct. I used PySCF &lt;code&gt;get_hcore(), get_ovlp(), get_veff(), get_fock()&lt;/code&gt; for a given density matrix. All my matrices are the same as the ones generated by PySCF.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here a quick explanation of my implementation of the algorithm:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Initial guess density Matrix &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is a zero matrix&lt;/li&gt;&#xA;&lt;li&gt;Generate transformation matrix &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$S^{-1/2}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Generate Fock matrix with given &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Transform Fock matrix as &lt;span class=&quot;math-container&quot;&gt;$F^{'} = X^{\dagger}FX$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Diagonalize &lt;span class=&quot;math-container&quot;&gt;$F^{'}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Transform coefficients &lt;span class=&quot;math-container&quot;&gt;$C^{'}$&lt;/span&gt; back as &lt;span class=&quot;math-container&quot;&gt;$C =  X C^{'}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Use &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; to generate new &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; and repeat till energies meet convergence criteria. I assume that if the sum of orbital energies minus the sum of the last orbital energies is an absolute value of less than 0.0001 it converges.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There is no implementation of DIIS, level shifting or damping. I hope this makes it clearer.&lt;/p&gt;&#xA;" OwnerUserId="5707" LastEditorUserId="5707" LastEditDate="2022-08-31T21:19:14.713" LastActivityDate="2022-09-02T20:22:32.663" Title="Hartree Fock Algorithm too high values for Molecules" Tags="|computational-chemistry|quantum-chemistry|hartree-fock|self-consistent-field|pyscf|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9596" PostTypeId="1" AcceptedAnswerId="9597" CreationDate="2022-08-27T06:05:12.203" Score="8" ViewCount="439" Body="&lt;p&gt;I am a bit new to computational chemistry, but I've been looking into a reaction of a molecule that contains C, H, and F reacting with AgF in a polar solvent. I am looking into one pathway that involves the coordination of &lt;span class=&quot;math-container&quot;&gt;$\ce{Ag+}$&lt;/span&gt; to the molecule, but I am unsure of what basis set to use. I tried the 6-311+G** basis set, but it doesn't seem to be compatible with silver. I also just tried to do a calculation with a mixed basis set 6-311+G**(C,H,F) and LANL2DZ(Ag) but the geometry did not converge for the given CPU space. I was wondering whether this combination of basis sets is appropriate for this analysis or would a different one work better?&lt;/p&gt;&#xA;" OwnerUserId="5914" OwnerDisplayName="M.L" LastEditorUserId="5" LastEditDate="2022-08-27T21:54:06.870" LastActivityDate="2022-09-04T13:35:51.043" Title="Basis Set to analyze a molecule that involves silver" Tags="|computational-chemistry|basis-sets|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9597" PostTypeId="2" ParentId="9596" CreationDate="2022-08-28T11:03:53.777" Score="9" Body="&lt;p&gt;Firstly, 6-311+G** for C,H,F is usually good enough for DFT calculations (assuming you are using DFT). If F elements are the only possible elements which can be or become anion F&lt;sup&gt;-&lt;/sup&gt; in your studied system, there is a more computationally cost-effective scheme: using 6-311G** for C,H and 6-311+G* for F. Proper diffuse functions can often save computational cost and avoid possible convergence issues in SCF or CP-SCF.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, LANL2DZ for Ag is somewhat small/insufficient, especially for computational resource nowadays. LANL2TZ or def2-TZVP would be better. If your system contains &amp;lt;50 atoms, using LANL2TZ(f) for Ag is also a good choice, especially if your Ag is involved in catalysis.&lt;/p&gt;&#xA;&lt;p&gt;Thirdly, &amp;quot;the geometry did not converge for the given CPU space&amp;quot; is hard to tell why. For example, a wrong syntax of LANL2 ECP written in the input file may lead to strange behavior of geometry optimization. So you may want to post your input file (no need to show Cartesian coordinates) and we can check if there is anything inappropriate.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2022-08-28T11:03:53.777" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9599" PostTypeId="1" CreationDate="2022-08-30T02:22:00.060" Score="3" ViewCount="235" Body="&lt;p&gt;I have seen descriptions of &lt;em&gt;ab initio&lt;/em&gt; thermodynamics where the phase energy diagram for the oxidation of metal surfaces can be constructed in terms of minimizing the grand potential or the Gibbs free energy of adsorption. I was wondering what the difference is between the two and which is the &amp;quot;more correct&amp;quot; description for &lt;em&gt;ab initio&lt;/em&gt; thermodynamics?&lt;/p&gt;&#xA;" OwnerUserId="5625" LastEditorUserId="24" LastEditDate="2022-08-30T13:09:20.627" LastActivityDate="2022-09-02T03:33:18.033" Title="Grand potential vs. Gibbs free energy of adsorption for ab initio thermodynamics" Tags="|density-functional-theory|ab-initio-calculations|statistical-thermodynamics|thermodynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9600" PostTypeId="1" CreationDate="2022-08-30T03:03:11.783" Score="2" ViewCount="94" Body="&lt;p&gt;What is the fundamental relationship between grand potential and free energy? In other words, what assumptions need to be made in order to obtain the free energy equation rather than the grand potential?&lt;/p&gt;&#xA;" OwnerUserId="5625" LastActivityDate="2023-10-13T21:28:48.160" Title="Relationship between grand potential and free energy?" Tags="|ab-initio-calculations|statistical-thermodynamics|thermodynamics|free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9602" PostTypeId="1" AcceptedAnswerId="9605" CreationDate="2022-08-30T06:47:43.647" Score="5" ViewCount="427" Body="&lt;p&gt;Is there any possibility to calculate with computational methods the pH dependency of protonation states for small molecules? For example I want to calculate which chemical structure formic acid will have at pH 2 and pH 15. This is a super easy example. I want to calculate it for intermediate products to see if they are stable and part of a possible pathway for some reaction.&#xA;Does anyone have an idea? I have gaussian software package. Is there maybe a way to have a workaround with explicit water atoms or H+ atoms?&#xA;We tried it with the acidity for the molecules &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9480/is-it-possible-to-calculate-the-pka-value-of-different-h-atoms-on-one-molecule&quot;&gt;(MM article)&lt;/a&gt;, but my supervisor always asks me to calculate the state of the molecule at specific pH values. She wants me to give a few different pHs to the calculation and have a look what structure will be calculated. I have no clue how to do so, even if it makes sense if I am honest.&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="4515" LastEditDate="2022-08-31T08:05:00.273" LastActivityDate="2022-08-31T08:05:00.273" Title="Calculation of pH dependence for small molecules" Tags="|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9603" PostTypeId="1" CreationDate="2022-08-30T09:00:08.030" Score="12" ViewCount="180" Body="&lt;p&gt;In a few months, I will complete my PhD and I'm considering leaving experimental chemistry and looking for a postdoc on computational chemistry. During my PhD I used some computational tools like CASTEP and Gaussian, to be honest, I used these tools without understanding a lot of the physics behind them and I guess that should be the step forward.&lt;/p&gt;&#xA;&lt;p&gt;I would like to keep working on heterogeneous catalysis, but I'm interested in exploring computational approaches like molecular dynamics, machine learning, some data science, and computing observable properties (spectroscopy?)&lt;/p&gt;&#xA;&lt;p&gt;I do understand that I will be a bit behind other people that did PhDs in computational chemistry, and for that reason, I want to learn as much as I can before I apply for such positions. I did some googling and found a lot of books about computational chemistry, but they are so many that it is difficult to select the one that would make the transition “easy and fast”. A bit like a catalyst?!&lt;/p&gt;&#xA;&lt;p&gt;With all that said I was wondering if someone could give their opinion about what topics I should focus my study on and provide some resources that cover those same topics. I’m trying to define a path forward that would make this transition efficient and not spend hours learning stuff that is important but not essential&lt;/p&gt;&#xA;" OwnerUserId="5923" LastActivityDate="2022-12-17T18:01:07.863" Title="Best resources for someone going from experimental to computational chemistry" Tags="|density-functional-theory|computational-chemistry|databases|machine-learning|catalysis|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9604" PostTypeId="1" CreationDate="2022-08-30T13:07:34.750" Score="4" ViewCount="100" Body="&lt;p&gt;I produced a spherical droplet of water by having a box of water (sufficient water molecules inside the box to give the right density of water) on top of a 2d sheet-like graphene. The box becomes a spherical droplet under nvt when the graphene is kept in a large box). However, when I calculate the density of water, like along z, I find the density of water low compared to what I started with. Presumably, because the droplet is in a large box now, how can I fix that? or is it what I should expect?&lt;a href=&quot;https://i.stack.imgur.com/0tg5T.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0tg5T.png&quot; alt=&quot;Density of water along z-axis&quot; /&gt;&lt;/a&gt; Also, for the perspective, I have attached herewith the image of the set-up as well. &lt;a href=&quot;https://i.stack.imgur.com/a1cK9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a1cK9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="1791" LastEditDate="2022-08-30T14:02:02.210" LastActivityDate="2022-08-30T14:02:02.210" Title="Density of a spherical droplet of water on top of graphene" Tags="|molecular-dynamics|gromacs|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9605" PostTypeId="2" ParentId="9602" CreationDate="2022-08-30T14:38:38.787" Score="6" Body="&lt;p&gt;What quantum chemistry programs can give you is the pKa values of each functional group in your molecule. Using the pKa values, you can calculate the dominant form (dominant protonation state) of your molecule under different pHs from basic analytical chemistry formulas, without the further aid of a quantum chemistry program. As far as I know, no quantum chemistry program can directly give the dominant forms of a molecule under different pHs, but only Gibbs free energies of the relevant species, because it is trivial to calculate the pKa and then the pH dependence of the dominant form of your molecule from the Gibbs free energy data by hand (or, particularly if you have a lot of molecules and/or a lot of pH values to calculate, by the mathematical formula functionality of Excel, which saves you from typing the same formula over and over again on your calculator).&lt;/p&gt;&#xA;&lt;p&gt;A simple example: suppose that your molecule is a diprotic acid (&lt;span class=&quot;math-container&quot;&gt;$H_2 A$&lt;/span&gt;), and you have calculated the two pKas of the acid:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;H_2 A &amp;amp;= HA^- + H^+ \quad &amp;amp;\rm{pKa_1} \\&#xA;HA^- &amp;amp;= A^{2-} + H^+ \quad &amp;amp;\rm{pKa_2}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;First of all, convert the pKa values to Ka values (equilibrium constants), and the pH value to &lt;span class=&quot;math-container&quot;&gt;$[H^+]$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rm{K_a} = 10^{-\rm{pKa}} \\&#xA;[H^+] = 10^{-\rm{pH}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, use the definition of the equilibrium constants to calculate the ratios of the different species:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rm{K_{a1}} = \frac{[H^+][HA^-]}{[H_2 A]} \\&#xA;\rm{K_{a2}} = \frac{[H^+][A^{2-}]}{[HA^-]}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From these one obtains &lt;span class=&quot;math-container&quot;&gt;$[HA^-]/[H_2 A]$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$[A^{2-}]/[HA^-]$&lt;/span&gt;, which can be trivially converted to the relative proportions of each species with respect to all species, &lt;span class=&quot;math-container&quot;&gt;$[H_2 A]/([H_2 A]+[HA^-]+[A^{2-}])$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$[HA^-]/([H_2 A]+[HA^-]+[A^{2-}])$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$[A^{2-}]/([H_2 A]+[HA^-]+[A^{2-}])$&lt;/span&gt;. If the first one is the largest, then &lt;span class=&quot;math-container&quot;&gt;$H_2 A$&lt;/span&gt; is the dominant form at the given pH. Same for &lt;span class=&quot;math-container&quot;&gt;$HA^-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A^{2-}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If your supervisor insists on seeing the molecular structure at a given pH, then it is done as follows: now that you have calculated &lt;span class=&quot;math-container&quot;&gt;$\rm{pKa_1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\rm{pKa_2}$&lt;/span&gt;, you surely have already optimized the structures of &lt;span class=&quot;math-container&quot;&gt;$H_2 A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$HA^-$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A^{2-}$&lt;/span&gt;. Suppose also that by the above manual calculations, you found that &lt;span class=&quot;math-container&quot;&gt;$HA^-$&lt;/span&gt; is the dominant form of your molecule at the given pH. Then you simply report the optimized structure of &lt;span class=&quot;math-container&quot;&gt;$HA^-$&lt;/span&gt;. Now you see that, the process is more like to compute all possible structures and then using some calculations to pick the correct one and to discard the wrong ones; the wrong ones have to be calculated anyway because they are involved in the calculations that determine which structure is the correct one. What your supervisor had in mind might be that you tell the program the pH and the program spits out the correct structure without also spitting out the wrong structures, but this is not how things actually work in ab initio calculations.&lt;/p&gt;&#xA;&lt;p&gt;To stress again: no quantum computation needs to be redone if you want to do the calculation at a second pH. You simply calculate all the pKa values of your molecule, then use the pKa values to manually calculate the dominant form of your molecule under different pHs, and finally pick the structure of that particular protonation state from your calculation results.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-08-30T14:38:38.787" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9606" PostTypeId="1" CreationDate="2022-08-31T08:56:33.933" Score="4" ViewCount="344" Body="&lt;p&gt;I am learning how to write POSCAR for monolayer and multiple layers of 2D materials like Bi2Se3, could you please provide some useful hints how to write POSCAR quickly especially for multiple layers, for instance, 3 layers?&lt;/p&gt;&#xA;" OwnerUserId="5929" LastActivityDate="2022-10-24T15:55:07.590" Title="Writing POSCAR for monolayer and mulitiple layers for 2D materials" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9607" PostTypeId="2" ParentId="9594" CreationDate="2022-08-31T16:11:28.123" Score="4" Body="&lt;p&gt;There is a bunch of errors in your question.&lt;/p&gt;&#xA;&lt;p&gt;First of all you seem to ignore the contraction coefficients in your code snippet. If however you ignore them (set them to 1 and pick only one pair &lt;span class=&quot;math-container&quot;&gt;$i,j$&lt;/span&gt;), still, your code calculates:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$    S_{00} =   e^{-\left (|\vec R_{AB}|^2  \frac{\alpha \beta}{\alpha+\beta}\right ) } \sqrt{\frac{\pi}{\alpha+\beta}}^3\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which means you missed the square in what you call &lt;span class=&quot;math-container&quot;&gt;$K_{AB}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then you try to compare to a &amp;quot;by hand&amp;quot; calculation that you do yourself, for which you use the Gaussian product rule in principle correctly stating that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_{A}(\alpha,r-R_A) \cdot \phi_{B}(\beta,r-R_B) = K_{AB} \cdot \phi_{AB}\left(\alpha+\beta,r-\frac{\alpha R_A + \beta R_B}{\alpha + \beta}\right)\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, in the next line, you write&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\phi_{AB} = K_{AB} \cdot \left (\frac{2\alpha\beta}{(\alpha+\beta)\pi} \right )^{\frac{3}{4}} \cdot e^{-\alpha\beta\left(r-\frac{\alpha R_A+\beta R_B}{\alpha+\beta}\right)^2}\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which suffers from three issues, for one your definition of &lt;span class=&quot;math-container&quot;&gt;$K_{AB}$&lt;/span&gt; is incorrect since you missed the square, additionally your pre-exponential factor is suddenly &lt;span class=&quot;math-container&quot;&gt;$\alpha \beta$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$\alpha + \beta$&lt;/span&gt;. Moreover, it is unclear where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\left (\frac{2\alpha\beta}{(\alpha+\beta)\pi} \right )^{\frac{3}{4}}\tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;is coming from.&lt;/p&gt;&#xA;&lt;p&gt;To the best of my knowledge the gaussian product rule should have resulted in:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\phi_{AB} = K_{AB} e^{-(\alpha + \beta)r_P}\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\vec r_P$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\vec r - \vec P$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$ \vec P$&lt;/span&gt; is the place:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;    \vec P = \frac{\alpha \vec R_A -  \beta \vec R_B}{\alpha + \beta}\tag{6}&#xA;\end{eqnarray}&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ K_{AB} = &#xA;e^{-\frac{\alpha \; \beta }{\alpha + \beta} \vec R_{AB}^2}\tag{7}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You than carry these errors into your result.&lt;/p&gt;&#xA;&lt;p&gt;I guess all that was needed was some double checking on your formulas.&lt;/p&gt;&#xA;" OwnerUserId="5815" LastEditorUserId="5" LastEditDate="2022-09-01T19:45:22.730" LastActivityDate="2022-09-01T19:45:22.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9608" PostTypeId="1" CreationDate="2022-08-31T17:58:34.743" Score="8" ViewCount="567" Body="&lt;p&gt;I am a beginning PhD student studying topological materials and strongly-correlated systems, such as high Tc superconductivity. I am using density functional theory in my work. I am wondering what I need to know in order to master DFT calculations using vasp (and also QE). I currently have some level of understanding of the theoretical basis of DFT (the Kohn-Sham equations, the Hohenberg-Kohn theorem, the Levy-Lieb functional etc.), but I do not have a lot of understanding on the pseudo-potential formalism (e.g. PAW), and the algorithms used in VASP to calculate the electronic ground state (e.g. the blocked Davidson algorithm and the RMM-DIIS algorithms).&lt;/p&gt;&#xA;&lt;p&gt;I am wondering if it pays to spend time trying to understand how the DFT code actually works and if so, what is the best way to do that. My principal goal is to do DFT calculations to understand topological systems and strongly-correlated material systems. This involves building tight-binding models etc.&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastEditorDisplayName="user5405" LastEditDate="2022-08-31T18:13:07.977" LastActivityDate="2022-08-31T20:06:11.750" Title="Learning how the DFT codes work" Tags="|vasp|reference-request|soft-question|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9609" PostTypeId="2" ParentId="9608" CreationDate="2022-08-31T20:06:11.750" Score="5" Body="&lt;p&gt;You should start off with running DFT calculations and then over time you can learn about theoretical and implementation details that interest you or are important for what you are doing. Based on what you've said, you should have the requisite knowledge to understand what is going on initially; once you've done calculations, you will have a better sense for what additional theoretical topics you will need to cover.&lt;/p&gt;&#xA;&lt;p&gt;Different people with different research aims will need to spend more or less time on different subtopics. For example, many people don't need to learn much more about PAW than having some vague understanding of the &amp;quot;PAW formalism&amp;quot; section of the VASP wiki, whereas other people will have to go deep into the details and even implement code that must take into account the PAW formalism.&lt;/p&gt;&#xA;&lt;p&gt;If you will be working on tight binding models and DFT, then Wannier90 likely will end up being useful. Perhaps you could do some DFT tutorials in VASP or QE and then also follow some of the Wannier90 tutorials. Along the way, you'll probably run into questions or things that interest you that can help inform what topics you will spend more time working with.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-08-31T20:06:11.750" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9610" PostTypeId="2" ParentId="8852" CreationDate="2022-08-31T21:56:46.680" Score="1" Body="&lt;p&gt;There are certain quantities that become poorly defined when you have a charged system. This could be what the author was referring to if you are studying the adsorption of ions or studying adsorption processes under an applied electrical bias. If you are not studying a charged system, then I believe esol and usol carry physical meaning. However, if you are interested in computing solvation free energies of neutral species, you should compute the energy difference between the solvated and non-solvated system. I believe esol refers to the excess chemical potential of solvation. Absolute solvation free energies for charged species are less well-defined unfortunately since you must account for the air-water dipole potential contribution, which itself is ill-defined and not included in the model. I can double check some of this and get back to you. If this is still an open question, I would also encourage you to post on the QE user forum. You can get a direct (and usually prompt) response from the developers there.&lt;/p&gt;&#xA;&lt;h2&gt;Some more details&lt;/h2&gt;&#xA;&lt;p&gt;The divergence of usol is a consequence of how ESM-RISM solves the Poisson equation of the composite quantum-classical cell. Essentially, the quantum and solvent charge densities are determined self-consistently, where the electron density is iteratively optimized for a frozen set of solvent distributions (solvent charge density), the potential generated by the new electron density is then used to re-optimize the solvent distributions, and this cycle continues until you reach your convergence criterion. As a result, the two charge densities are necessarily determined separately, and the total electrostatic potential of the composite quantum-classical cell is given by the sum of the quantum and classical potentials.&lt;/p&gt;&#xA;&lt;p&gt;If the quantum region carries a net charge, the electrostatic potentials of the solvent and quantum solute regions must diverge (in opposite directions) since the integrated charges of the solute and solvent carry opposite signs. When summed, the diverging potentials cancel and you obtain a flat potential far from the interface. This is a non-issue though if the quantum region is neutral, since no divergence in the potential occurs.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-08-31T22:59:59.037" LastActivityDate="2022-08-31T22:59:59.037" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9611" PostTypeId="1" AcceptedAnswerId="9617" CreationDate="2022-09-01T01:21:37.777" Score="9" ViewCount="650" Body="&lt;p&gt;When doing DFT calculations on certain magnetic materials, convergence can be difficult. This problem can be solved by changing the mixing parameters (e.g. AMIN and BMIX in the INCAR file of VASP). My question is how charge mixing occurs and what is the underlying reason for convergence issues in magnetic systems ?&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastActivityDate="2022-09-04T13:21:05.563" Title="How does charge mixing work?" Tags="|density-functional-theory|vasp|reference-request|numerical-convergence|algorithms|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9612" PostTypeId="1" CreationDate="2022-09-01T04:48:27.760" Score="2" ViewCount="65" Body="&lt;p&gt;After reading &lt;a href=&quot;https://doi.org/10.1021%2Facs.chemrev.8b00722&quot; rel=&quot;nofollow noreferrer&quot;&gt;this 2019 open-access paper&lt;/a&gt;, which states that NBO 3.0 correctly represents the valence participation of the np orbital(s) of transition metals, an explicit example of which participation being linked in the article(also open-access), but higher versions do not, I began to worry if the latest (2021) version of the NBO, NBO 7.0.10, still wrongly does not represent the valence participation of aforementioned orbitals in aforementioned  atoms- a molecule that I've been designing in silico has a magnesium cluster inside it, and the paper explicitly says that NBO treats magnesium 3p orbitals as Rydberg orbitals, under which circumstances highly inaccurate results (cf. QTAIM, the most rigorous form of modern VB theory- again, see article) could occur.&lt;/p&gt;&#xA;&lt;p&gt;Is this the case, i.e. NBO 7.0.10 treats magnesium 3p and (say) iron 4p as Rydberg orbitals, or is this (correctly) not the case?&lt;/p&gt;&#xA;" OwnerUserId="4231" OwnerDisplayName="Kanghun Kim" LastActivityDate="2022-09-01T04:57:12.673" Title="Question on NBO 7.0.10, the latest version of the NBO program" Tags="|computational-chemistry|valence-bond-theory|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-15T04:43:53.623" ContentLicense="CC BY-SA 4.0" />
  <row Id="9613" PostTypeId="1" CreationDate="2022-09-01T16:27:26.617" Score="2" ViewCount="103" Body="&lt;p&gt;I am interested in trying to re-parametrize existing force fields in LAMMPS (let's say ReaxFF or MYP0) but I am not able to find any clear tutorial or information on how to do so. Do you know of good resources or documentation?&lt;/p&gt;&#xA;&lt;p&gt;The idea would be to parametrize or correct a FF according to DFT or higher-level calculations... I have read that it is possible to be done with the AMS suit of programs but unfortunately, the FF is not available...&lt;/p&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="3382" LastEditDate="2022-09-02T06:26:56.533" LastActivityDate="2022-09-02T06:26:56.533" Title="Re-parametrization of force fields in LAMMPS" Tags="|density-functional-theory|molecular-dynamics|lammps|forcefields|molecular-mechanics|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-20T03:19:24.060" ContentLicense="CC BY-SA 4.0" />
  <row Id="9614" PostTypeId="2" ParentId="9599" CreationDate="2022-09-01T21:03:07.927" Score="3" Body="&lt;p&gt;In principle you could use either thermodynamic potential to describe the adsorption process, but the grand potential is a bit more natural to use. Which one you select in the end kind of depends on what you are trying to describe and what thermodynamic parameters you want to consider to be fixed.&lt;/p&gt;&#xA;&lt;p&gt;Typically, when working with Gibbs free energies of adsorption, this will be plotted against a composition axis (such as surface coverage) since the Gibbs free energy depends directly on particle number&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G \equiv G(T, P, N) \to dG = -SdT + VdP + \mu dN&#xA;$$&lt;/span&gt;&#xA;Note that at fixed temperature and pressure, we have &lt;span class=&quot;math-container&quot;&gt;$dG = \mu dN$&lt;/span&gt;. In this case, the chemical potential is a quantity to be measured or computed, and is a function of &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu(T, P, N) = \left(\frac{\partial G}{\partial N} \right)_{T, P}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;When working with grand potentials, the data will be presented as grand potential vs chemical potential since chemical potential is a natural variable of the grand potential&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Phi \equiv \Phi(T, V, \mu) \to d\Phi = -SdT -PdV - Nd\mu&#xA;$$&lt;/span&gt;&#xA;Note that at fixed temperature and volume, we have &lt;span class=&quot;math-container&quot;&gt;$d\Phi = -N d\mu$&lt;/span&gt;. Hence, the number of adsorbates on the surface is a quantity to be computed or measured and is a function of &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;-N(T, V, \mu) = \left(\frac{\partial \Phi}{\partial \mu} \right)_{T, V}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The reason why I say the grand potential is more natural to use is that experimentally, we can control the partial pressure of oxygen gas (and hence its chemical potential) much more easily than we can directly control the surface coverage of adsorbates. On the other hand, computationally, it is easier to directly sample surface coverage than it is to control the chemical potential of adsorbates.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-09-02T03:33:18.033" LastActivityDate="2022-09-02T03:33:18.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9615" PostTypeId="2" ParentId="9595" CreationDate="2022-09-02T00:39:17.390" Score="7" Body="&lt;p&gt;Since you've done such an excellent job so far I thought I'd just give you some hints in the &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/61905044#61905044&quot;&gt;chat&lt;/a&gt;, but after banging your head on it for a week I think you deserve a proper answer. And with the new version of your code it's even easier to fix.&lt;/p&gt;&#xA;&lt;p&gt;The Hartree-Fock orbitals are defined as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \psi_i = \sum_j^N c_{ij}\phi_j $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\phi_j$&lt;/span&gt; are the basis functions, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of basis functions, and &lt;span class=&quot;math-container&quot;&gt;$c_{ij}$&lt;/span&gt; are your expansion coefficients. From the orbitals, you construct the density matrix:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ K_{ij} = \sum_k^N f_k c_{ik} c_{jk}^{*}. $$&lt;/span&gt;&#xA;Here the values &lt;span class=&quot;math-container&quot;&gt;$f_k$&lt;/span&gt; have been introduced. &lt;span class=&quot;math-container&quot;&gt;$f_k$&lt;/span&gt; is the occupation number of the orbital &lt;span class=&quot;math-container&quot;&gt;$\psi_k$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Inside your code, you construct the density matrix with the following (abbreviated) routine:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i in range(i_range):&#xA;  for k in range(k_range):&#xA;    row_i = old_matrix[i]&#xA;    row_k = old_matrix[k]&#xA;    product_array = np.multiply(row_i, row_k)&#xA;    matrix[i, k] = 2 * np.sum(product_array)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Having just reviewed the equations, you can see the missing ingredient: &lt;span class=&quot;math-container&quot;&gt;$f_k$&lt;/span&gt;. In fact, the multiplication you do by two essentially is assigning an occupation of &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; to every orbital.&lt;/p&gt;&#xA;&lt;p&gt;So why did it work for atoms and not molecules? It's just an artifact of the atoms you choose. Consider the Helium atom: it has one basis function and two electrons which doubly occupy the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt; subshell (&lt;span class=&quot;math-container&quot;&gt;$1s^2$&lt;/span&gt;). Neon was your second test, which has &lt;span class=&quot;math-container&quot;&gt;$10$&lt;/span&gt; electrons and has configuration &lt;span class=&quot;math-container&quot;&gt;$1s^22s^22p^6$&lt;/span&gt;, which means the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt; is doubly occupied, as is the &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt;, as well as the &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt;. So multiplying by &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; worked.&lt;/p&gt;&#xA;&lt;p&gt;Now consider the test I showed you: Carbon. It has &lt;span class=&quot;math-container&quot;&gt;$5$&lt;/span&gt; basis functions, but just &lt;span class=&quot;math-container&quot;&gt;$6$&lt;/span&gt; electrons (&lt;span class=&quot;math-container&quot;&gt;$1s^22s^22p^2$&lt;/span&gt;). And so the occupation numbers are &lt;span class=&quot;math-container&quot;&gt;$[2, 2, 2, 0, 0]$&lt;/span&gt;. This is why Carbon did not work, multiplication by &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; was not sufficient. You can thus fix your density matrix routine by adding an additional argument which are the occupation numbers, and multiplying by them.&lt;/p&gt;&#xA;" OwnerUserId="5167" LastEditorUserId="5" LastEditDate="2022-09-02T20:22:32.663" LastActivityDate="2022-09-02T20:22:32.663" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9616" PostTypeId="1" CreationDate="2022-09-02T02:19:01.360" Score="2" ViewCount="244" Body="&lt;p&gt;I am doing the DFT calculations in Quantum ESPRESSO code. I have 2 different pwscf input file of the same crystal. I am confused which one is representing primitive, conventional and supercell structures. Actually I want to introduce disorder/doping in the system, so I am trying to create the supercell structure. Two input files with required information are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;4 atoms file:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;SYSTEM&#xA;                       ibrav = 2,&#xA;                   celldm(1) = 10.703022167,&#xA;                         nat = 4,&#xA;                        ntyp = 3,&#xA;                     ecutwfc = 300 ,&#xA;                     ecutrho = 1200 ,&#xA;&#xA; /&#xA;&#xA;ATOMIC_SPECIES&#xA;   Co   58.933195 Co.rel-pbe-spn-kjpaw_psl.0.3.1.UPF&#xA;   Mn   54.938    Mn.rel-pbe-spn-kjpaw_psl.0.3.1.UPF     &#xA;   Al   26.98154  Al.rel-pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS alat&#xA;   Mn      0.000000000    0.000000000    0.000000000&#xA;   Al      0.500000000    0.500000000    0.500000000&#xA;   Co      0.750000000    0.750000000    0.750000000&#xA;   Co      0.250000000    0.250000000    0.250000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For this crystal structure, I am seeing to different structures in Xcrysden. I am confused which one in primitive and conventional in it. How Xcrysden is generating the complete cubic structure (second one with 35 atoms)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eW78n.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eW78n.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/FrlIO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FrlIO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;16 atoms file:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;SYSTEM&#xA;                       ibrav = 0,&#xA;                         nat = 16,&#xA;                        ntyp = 3,&#xA;                     ecutwfc = 300 ,&#xA;                     ecutrho = 1200 ,&#xA;                &#xA; /&#xA; &#xA;ATOMIC_SPECIES&#xA;   Co   58.933195 Co.rel-pbe-spn-kjpaw_psl.0.3.1.UPF&#xA;   Mn   54.938    Mn.rel-pbe-spn-kjpaw_psl.0.3.1.UPF     &#xA;   Al   26.98154  Al.rel-pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;  Al   0.50000000  0.00000000  0.00000000  &#xA;  Al   0.50000000  0.50000000  0.50000000  &#xA;  Al   0.00000000  0.00000000  0.50000000  &#xA;  Al   0.00000000  0.50000000  0.00000000  &#xA;  Mn   0.00000000  0.00000000  0.00000000 &#xA;  Mn   0.00000000  0.50000000  0.50000000  &#xA;  Mn   0.50000000  0.00000000  0.50000000  &#xA;  Mn   0.50000000  0.50000000  0.00000000  &#xA;  Co   0.25000000  0.25000000  0.75000000  &#xA;  Co   0.25000000  0.75000000  0.75000000  &#xA;  Co   0.25000000  0.75000000  0.25000000  &#xA;  Co   0.25000000  0.25000000  0.25000000  &#xA;  Co   0.75000000  0.25000000  0.25000000  &#xA;  Co   0.75000000  0.75000000  0.25000000  &#xA;  Co   0.75000000  0.75000000  0.75000000  &#xA;  Co   0.75000000  0.25000000  0.75000000  &#xA;   &#xA;CELL_PARAMETERS angstrom&#xA;    5.6637953940    0.0000000000    0.0000000000&#xA;    0.0000000000    5.6637953940    0.0000000000&#xA;    0.0000000000    0.0000000000    5.6637953940&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For 16 atoms structure following two unit cells are displayed in Xcrysden. I am confused which one is primitive and conventional? How Xcrysden is generating the complete cubic structure (second one with 35 atoms)?&lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ctThg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ctThg.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KapW7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KapW7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I am not able to perform doping/disorder in these structure due to&#xA;less sizes? How can I create the supercell of bigger size?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Should I create the 1x1x2 sized supercell of 16 atoms structure which&#xA;will consist of 32 atoms but will not be cubic?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Should I create 35 atoms cubic structure manually as displayed above&#xA;by giving the coordinates of each atom in angstrom? In that case will&#xA;it be primitive cell or conventional unit cell?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Please clarify my doubts.&lt;/p&gt;&#xA;" OwnerUserId="1361" LastActivityDate="2022-09-02T02:19:01.360" Title="Confusion in primitive, conventional and supercell crystal structure" Tags="|density-functional-theory|quantum-espresso|crystallography|supercell|disorder|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T22:59:07.810" ContentLicense="CC BY-SA 4.0" />
  <row Id="9617" PostTypeId="2" ParentId="9611" CreationDate="2022-09-02T02:33:35.550" Score="9" Body="&lt;p&gt;Density mixing is a type of self-consistent field (SCF) method, which tries to find the closest density to the Kohn-Sham (or Hartree-Fock etc) ground state density by mixing previous densities and density changes.&lt;/p&gt;&#xA;&lt;h4&gt;The self-consistent field method&lt;/h4&gt;&#xA;&lt;p&gt;In the density mixing SCF method, a trial density &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{in}(\vec{r})$&lt;/span&gt; is used to construct the Kohn-Sham Hamiltonian, and then a set of trial states &lt;span class=&quot;math-container&quot;&gt;$\left\{\psi_{bk}\right\}$&lt;/span&gt; is computed by solving the Kohn-Sham equations,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H}\left[n_\mathrm{in}\right]\psi_{bk}=E_{bk}\psi_{bk}. \tag{1}&#xA;$$&lt;/span&gt;&#xA;These equations may be solved either by conventional matrix diagonalisation (if the basis set is compact, e.g. atom-centred Gaussians) or by iterative diagonalisation (if the basis set is large, e.g. plane-waves, such as VASP uses).&lt;/p&gt;&#xA;&lt;p&gt;However equation (1) is solved, an important thing to note is that the density &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{in}$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt; changed as the states are updated; yet the density should be related to the states by,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n(\vec{r}) = \sum_{bk}f_{bk}\left\vert\psi_{bk}(\vec{r})\right\vert^2, \tag{2}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt; are the band occupancies. We define this density to be &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{out}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Only when &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{out}=n_\mathrm{in}$&lt;/span&gt; have we computed the correct Kohn-Sham ground state, where the density obtained from our states is the same as the density used to define the Hamiltonian; the solution in this case is said to be &lt;em&gt;self-consistent&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In general, &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{out}\neq n_\mathrm{in}$&lt;/span&gt;, in which case the &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt; we computed are not for the ground state Hamiltonian. The question thus arises: given an initial input density &lt;span class=&quot;math-container&quot;&gt;$n^{(0)}_\mathrm{in}$&lt;/span&gt; and resultant output density &lt;span class=&quot;math-container&quot;&gt;$n^{(0)}_\mathrm{out}$&lt;/span&gt;, how can we find an improved guess for the input density, &lt;span class=&quot;math-container&quot;&gt;$n^{(1)}_\mathrm{in}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Let us define the change in &lt;span class=&quot;math-container&quot;&gt;$n^{(0)}_\mathrm{in}$&lt;/span&gt; to be &lt;span class=&quot;math-container&quot;&gt;$\delta n^{(0)}_\mathrm{in}$&lt;/span&gt;, and write&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n^{(1)}_\mathrm{in} = n^{(0)}_\mathrm{in} + \delta n^{(0)}_\mathrm{in}. \tag{3}&#xA;$$&lt;/span&gt;&#xA;Similarly, we write the new output density as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n^{(1)}_\mathrm{out} = n^{(0)}_\mathrm{out} + \delta n^{(0)}_\mathrm{out}. \tag{4}&#xA;$$&lt;/span&gt;&#xA;We wish these two densities to be the same, since that corresponds to the self-consistent solution of the Kohn-Sham equations. Thus,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n^{(0)}_\mathrm{in} + \delta n^{(0)}_\mathrm{in} = n^{(0)}_\mathrm{out} + \delta n^{(0)}_\mathrm{out}. \tag{5}&#xA;$$&lt;/span&gt;&#xA;If we are near to the solution, then we can approximate &lt;span class=&quot;math-container&quot;&gt;$\delta n_\mathrm{out}$&lt;/span&gt; as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\delta n_\mathrm{out} \approx \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\delta n_\mathrm{in}, \tag{6}&#xA;$$&lt;/span&gt;&#xA;which we substitute into equation (5) to obtain,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{lrcl}&#xA;&amp;amp; n^{(0)}_\mathrm{in} + \delta n^{(0)}_\mathrm{in} &amp;amp;\approx&amp;amp; n^{(0)}_\mathrm{out} + \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\delta n_\mathrm{in}\\&#xA;\Rightarrow &amp;amp; \delta n^{(0)}_\mathrm{in} - \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\delta n_\mathrm{in} &amp;amp;\approx&amp;amp; n^{(0)}_\mathrm{out} - n^{(0)}_\mathrm{in}\\ &#xA;\Rightarrow &amp;amp; \left(1 - \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\right)\delta n_\mathrm{in} &amp;amp;\approx&amp;amp; n^{(0)}_\mathrm{out} - n^{(0)}_\mathrm{in}\\ &#xA;\Rightarrow &amp;amp; \delta n_\mathrm{in} &amp;amp;\approx&amp;amp; \left(1 - \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\right)^{-1} \left(n_\mathrm{out}-n_\mathrm{in}\right).  \tag{7}&#xA;\end{array}&#xA;$$&lt;/span&gt;&#xA;The quantity &lt;span class=&quot;math-container&quot;&gt;$\left(n_\mathrm{out}-n_\mathrm{in}\right)$&lt;/span&gt; is the density &lt;em&gt;residual&lt;/em&gt;, which is the difference between the input and output densities; at the solution, this should be zero.&lt;/p&gt;&#xA;&lt;p&gt;The term&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(1 - \frac{\delta n_\mathrm{out}}{\delta n_\mathrm{in}}\right)^{-1}&#xA;$$&lt;/span&gt;&#xA;is a matrix inversion. This may not be immediately apparent, since I omitted the positional variables for brevity; re-inserting them, we have,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(1 - \frac{\delta n_\mathrm{out}(\vec{r})}{\delta n_\mathrm{in}(\vec{r}^\prime)}\right)^{-1}, \tag{8}&#xA;$$&lt;/span&gt;&#xA;which reflects the fact that a change in the input density at a point &lt;span class=&quot;math-container&quot;&gt;$\vec{r}^\prime$&lt;/span&gt; can cause a change in the output density at a different point, &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;We don't know what this matrix is &lt;em&gt;a priori&lt;/em&gt;, so how should we proceed? One physics point to note is that the response of the density (&lt;span class=&quot;math-container&quot;&gt;$\delta n_\mathrm{out}$&lt;/span&gt;) to a perturbing potential (which is what changing the input density by &lt;span class=&quot;math-container&quot;&gt;$\delta n_\mathrm{in}$&lt;/span&gt; does) is the &lt;em&gt;dielectric&lt;/em&gt; response, and this matrix is the &lt;em&gt;inverse dielectric tensor&lt;/em&gt; of the system.&lt;/p&gt;&#xA;&lt;h4&gt;Linear mixing&lt;/h4&gt;&#xA;&lt;p&gt;As a first assumption, we may simply approximate the matrix by a scalar times the identity,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(1 - \frac{\delta n_\mathrm{out}(\vec{r})}{\delta n_\mathrm{in}(\vec{r}^\prime)}\right)^{-1} \approx \alpha \mathrm{I}. \tag{9}&#xA;$$&lt;/span&gt;&#xA;Inserting this into equation (7) yields,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{lrcl}&#xA;&amp;amp; \delta n_\mathrm{in} &amp;amp; \approx &amp;amp; \alpha \left(n_\mathrm{out}-n_\mathrm{in}\right)\\&#xA;\Rightarrow &amp;amp; n^{(1)}_\mathrm{in} &amp;amp;=&amp;amp; n^{(0)}_\mathrm{in} + \delta n^{(0)}_\mathrm{in} \\&#xA;&amp;amp;  &amp;amp; \approx &amp;amp; n^{(0)}_\mathrm{in} + \alpha \left(n^{(0)}_\mathrm{out}-n^{(0)}_\mathrm{in}\right) \\&#xA;&amp;amp;  &amp;amp; = &amp;amp; (1-\alpha) n^{(0)}_\mathrm{in} + \alpha n^{(0)}_\mathrm{out}. \tag{10}&#xA;\end{array}&#xA;$$&lt;/span&gt;&#xA;We see that the new input density,&lt;span class=&quot;math-container&quot;&gt;$n^{(1)}_\mathrm{in}$&lt;/span&gt; is a linear mixture of the previous input and output densities, and it is usually referred to simply as &lt;em&gt;linear mixing&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Linear mixing is very simple and easy to implement. For small systems it can be surprisingly effective, but it quickly becomes unstable for systems larger and/or more complex.&lt;/p&gt;&#xA;&lt;h4&gt;Dielectric preconditioning&lt;/h4&gt;&#xA;&lt;p&gt;The problems with linear mixing are largely due to the crude approximation of a matrix by a scaled identity. We &lt;em&gt;could&lt;/em&gt; compute the dielectric tensor (e.g. with density functional perturbation theory), but since the system may be quite a long way from the ground state in these early SCF cycles, that may require a lot of computational effort which must be redone every SCF cycle.&lt;/p&gt;&#xA;&lt;p&gt;A popular alternative is to approximate the dielectric by that of the homogeneous electron gas (also known as jellium). The dielectric response of jellium is diagonal in reciprocal-space, so it is convenient to express it not in terms of &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{r}^\prime$&lt;/span&gt;, but in terms of the reciprocal lattice vectors &lt;span class=&quot;math-container&quot;&gt;$\vec{G}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{G}^\prime$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(1 - \frac{\delta n_\mathrm{out}(\vec{G})}{\delta n_\mathrm{in}(\vec{G}^\prime)}\right)^{-1} \approx \delta_{\vec{G}\vec{G}^\prime}\frac{\vert\vec{G}\vert^2}{\vert\vec{G}\vert^2+\vert G_0\vert^2}, \tag{11}&#xA;$$&lt;/span&gt;&#xA;where the parameter &lt;span class=&quot;math-container&quot;&gt;$G_0$&lt;/span&gt; is related to the Thomas-Fermi screening wavevector, and &lt;span class=&quot;math-container&quot;&gt;$\delta_{\vec{G}\vec{G}^\prime}$&lt;/span&gt; is the Kronecker delta (i.e. it means the matrix is diagonal).&lt;/p&gt;&#xA;&lt;p&gt;The important thing to note about this expression is that for small wavevectors it is approximately &lt;span class=&quot;math-container&quot;&gt;$\frac{\vert\vec{G}\vert^2}{\vert G_0\vert^2}$&lt;/span&gt;, which is small. Thus, it has the effect of damping the small &lt;span class=&quot;math-container&quot;&gt;$\vec{G}$&lt;/span&gt; components of the residual and, since a small reciprocal-space vector corresponds to large real-space changes, this means it suppresses the long-range density changes which are especially problematic when simulating metals.&lt;/p&gt;&#xA;&lt;p&gt;It is common practice to also include a mixing parameter &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, so that the actual density is given by,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{array}{lrcl}&#xA;&amp;amp; n^{(1)}_\mathrm{in}(\vec{G}) &amp;amp;=&amp;amp; n^{(0)}_\mathrm{in}(\vec{G}) + \delta n^{(0)}_\mathrm{in}(\vec{G}) \\&#xA;&amp;amp;  &amp;amp; \approx &amp;amp; n^{(0)}_\mathrm{in}(\vec{G}) + \frac{\alpha\vert\vec{G}\vert^2}{\vert\vec{G}\vert^2+\vert G_0\vert^2}  \left(n^{(0)}_\mathrm{out}(\vec{G})-n^{(0)}_\mathrm{in}(\vec{G})\right). \tag{12}&#xA;\end{array}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To my knowledge, this approach was first used by &lt;a href=&quot;https://doi.org/10.1088/0305-4608/3/12/011&quot; rel=&quot;noreferrer&quot;&gt;J Arponen, P Hautojärvi, R Nieminen and E Pajanne&lt;/a&gt; in their studies of electron and positron defects in metals, but it was &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.23.3082&quot; rel=&quot;noreferrer&quot;&gt;Kerker&lt;/a&gt; who proposed it as a general method for self-consistent electronic-structure calculations (in a comment on a later &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.12.4012&quot; rel=&quot;noreferrer&quot;&gt;M Manninen, R Nieminen, P Hautojärvi and J Arponen paper&lt;/a&gt;), and this approach is usually known as &lt;em&gt;Kerker mixing&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Quasi-Newton methods&lt;/h4&gt;&#xA;&lt;p&gt;As the calculation proceeds, we see how the system actually responded to the new input densities, and so we gain more and more information about the actual dielectric response of the system. There is a whole field of optimisation theory to draw on when approximating a matrix by its application to sample vectors (in our case, the density residuals). The most widespread methods are probably those of &lt;a href=&quot;https://doi.org/10.2307/2003941&quot; rel=&quot;noreferrer&quot;&gt;Broyden&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1016/0009-2614(80)80396-4&quot; rel=&quot;noreferrer&quot;&gt;Pulay&lt;/a&gt; (or, equivalently, &lt;a href=&quot;https://doi.org/10.1145/321296.321305&quot; rel=&quot;noreferrer&quot;&gt;Anderson&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;All of these methods involve constructing a matrix in the basis of the densities and residuals your system has used, and so the result is that your new input density is usually a mixture of all previous densities.&lt;/p&gt;&#xA;&lt;p&gt;For plane-wave based methods, these methods are almost always combined with Kerker preconditioning so that effectively the quasi-Newton method builds up a model of the &lt;em&gt;difference&lt;/em&gt; between the actual dielectric response, and the jellium model.&lt;/p&gt;&#xA;&lt;h4&gt;Spin and magnetism&lt;/h4&gt;&#xA;&lt;p&gt;Now we come to the heart of your question: why are magnetic systems harder to converge? There are several reasons, but probably the two most generally problematic are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Magnetic systems typically have many local energy minima&lt;br /&gt;&#xA;These minima correspond to different atomic magnetic states; quasi-Newton methods often perform poorly for multiple minima problems&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The Kerker model is less appropriate&lt;br /&gt;&#xA;The Kerker model is based on jellium's &lt;em&gt;charge&lt;/em&gt; response, but it is usually used to precondition the &lt;em&gt;spin&lt;/em&gt; mixing as well (albeit with different parameters for the mixing amplitude and screening wavevector). Using the charge dielectric model for the spin mixing is generally found to be an improvement over linear mixing, but it is not clear that it is actually an appropriate model.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The Kerker model may also be derived from the Kohn-Sham equations directly, assuming that the change in potential is dominated by the change in the Hartree potential; however, the Hartree potential has &lt;em&gt;no contribution from the spin at all&lt;/em&gt; so it is not at all clear that the same model will be a good approximation to the spin response.&lt;/p&gt;&#xA;&lt;h4&gt;Other approaches&lt;/h4&gt;&#xA;&lt;p&gt;I think I have covered all of the key machinery VASP uses, but these aren't the only possible approaches. For a fuller discussion of the different &lt;em&gt;density mixing&lt;/em&gt; methods, and the causes of instabilities, you might find &lt;a href=&quot;https://doi.org/10.1088/1361-648X/ab31c0&quot; rel=&quot;noreferrer&quot;&gt;this paper from my group&lt;/a&gt; useful, and the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/495/difficult-cases-for-converging-kohn-sham-scf-calculations/679#679&quot;&gt;discussion of &amp;quot;difficult cases&amp;quot; here&lt;/a&gt;. This focuses on the quasi-Newton part of the problem, not the dielectric preconditioning.&lt;/p&gt;&#xA;&lt;p&gt;Many quantum chemistry packages use a density &lt;em&gt;matrix&lt;/em&gt; mixing method, which has some additional advantages, since the energy can be expressed directly as the trace of the density matrix times the Hamiltonian. These were &lt;em&gt;not&lt;/em&gt; covered in the above paper, as we did that in the CASTEP plane-wave program and density matrix methods are very awkward to implement in a plane-wave basis.&lt;/p&gt;&#xA;&lt;p&gt;Some packages also use more sophisticated models for the dielectric, for example computing the dielectric matrix (perhaps in a reduced basis, or implicitly via perturbation theory), or the auxiliary Thomas-Fermi model of &lt;a href=&quot;https://www.doi.org/10.1103/PhysRevB.64.121101&quot; rel=&quot;noreferrer&quot;&gt;Raczkowski and Canning&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="142" LastEditDate="2022-09-04T13:21:05.563" LastActivityDate="2022-09-04T13:21:05.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9618" PostTypeId="1" CreationDate="2022-09-02T13:43:52.033" Score="3" ViewCount="50" Body="&lt;p&gt;As per Boltzmann distribution, the variance, or the fluctuation in length squared is given by &lt;span class=&quot;math-container&quot;&gt;$$\sigma^2 = \frac{k_BT}{k_{spring}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;$k_{spring}$&lt;/span&gt; determines how strong the force I am applying to pull, I was wondering how can I determine the appropriate value of &lt;span class=&quot;math-container&quot;&gt;$k_{spring}$&lt;/span&gt; I need to use to let the atom/atoms I am pulling vibrate at their thermal fluctuation value. Is there any rule of thumb, or a way of determining this force constant? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2022-09-02T13:43:52.033" Title="Appropriate choice of force constant of spring to use for Steered molecular dynamics" Tags="|molecular-dynamics|molecular-modeling|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9619" PostTypeId="2" ParentId="9575" CreationDate="2022-09-02T15:05:48.543" Score="4" Body="&lt;p&gt;There are many pseudopotential libraries available to choose from. Below is a (most definitely incomplete) list of pseudopotential libraries compatible with Quantum ESPRESSO that are either curated or original reference libraries:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.materialscloud.org/discover/sssp/table/efficiency&quot; rel=&quot;nofollow noreferrer&quot;&gt;SSSP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.pseudo-dojo.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;PseudoDojo&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.quantum-simulation.org/potentials/sg15_oncv/&quot; rel=&quot;nofollow noreferrer&quot;&gt;SG15 ONCV&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://www.physics.rutgers.edu/gbrv/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GBRV&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://dalcorso.github.io/pslibrary/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PSLibrary&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These libraries will provide norm-conserving, ultra soft, and PAW potentials to choose from. Some are harder (contain more semi-core states) than others, so take a look to see if these meet your requirements.&lt;/p&gt;&#xA;&lt;p&gt;Otherwise, if you are dead set on generating your own pseudopotentials, take a look at &lt;a href=&quot;http://www.fisica.uniud.it/%7Egiannozz/Atom/doc.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;these notes&lt;/a&gt; prepared by Paolo Giannozzi. You can create pseudopotentials using the atomic (ld1.x) code in QE. Generating good pseudopotentials is a bit of an art and requires a lot of testing. Paolo's notes are definitely worth a read before starting to generate your own pseudos.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="7" LastEditDate="2022-09-02T18:26:15.487" LastActivityDate="2022-09-02T18:26:15.487" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9620" PostTypeId="1" CreationDate="2022-09-03T20:21:40.110" Score="3" ViewCount="116" Body="&lt;p&gt;I would like to know what are the different types of mixing procedures to be applied to the density matrix (Broyden mixing, Pulay mixing) and their pros and cons?&lt;/p&gt;&#xA;" OwnerUserId="1195" LastEditorUserId="5" LastEditDate="2022-09-03T22:23:20.000" LastActivityDate="2022-10-14T11:55:48.420" Title="What are the types of density matrix mixing methods?" Tags="|density-functional-theory|one-topic-per-answer|optimization|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9621" PostTypeId="1" AcceptedAnswerId="9920" CreationDate="2022-09-04T07:34:00.947" Score="2" ViewCount="440" Body="&lt;p&gt;I am trying to create the espresso input for magnetic calculation, reading the data from a cif file.&lt;/p&gt;&#xA;&lt;p&gt;The ase code for the same is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Input&#xA; # Reading Input from CIF&#xA;  filename = args.cif&#xA;  system = aio.read(filename)&#xA;# Adding the magmom&#xA;  system.magmom = [3]&#xA;  print(system.magmom)&#xA; &#xA; &#xA;  # vcrelax&#xA;  input_data = {&#xA;      'calculation': 'vc-relax',&#xA;      'outdir': odir,&#xA;      'occupations': 'smearing',&#xA;      'degauss': 0.05,&#xA;      'nspin': 2,&#xA;      'smearing': 'gaussian',&#xA;      &amp;quot;starting_magnetization(1)&amp;quot;: 3.0&#xA;  }&#xA;  calc = Espresso(pseudopotentials=pseudo_list,&#xA;                  pseudo_dir=pseudodir,&#xA;                  input_data=input_data,&#xA;                  crystal_coordinates=True,&#xA;                  tstress=True,&#xA;                  tprnfor=True,&#xA;                  kpts=(6, 6, 6))&#xA;  system.calc = calc&#xA;  print(system.get_potential_energy())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am expecting the generated input with 'starting_magnetization(1)=3',&#xA;But I am getting the input as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;SYSTEM&#xA;   starting_magnetization(1) = 0.0&#xA;   occupations      = 'smearing'&#xA;   degauss          = 0.05&#xA;   smearing         = 'gaussian'&#xA;   nspin            = 2&#xA;   ntyp             = 1&#xA;   nat              = 2&#xA;   ibrav            = 0&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hence, my scf is showing 0 absolute magnetizations.&lt;/p&gt;&#xA;&lt;p&gt;How I can use ase to create a proper spin-DFT input for QE using ASE?&lt;/p&gt;&#xA;" OwnerUserId="5946" LastEditorUserId="5" LastEditDate="2022-09-04T12:45:10.373" LastActivityDate="2022-11-03T16:15:41.453" Title="Generate quantum espresso spin-polarized input using ASE" Tags="|quantum-espresso|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9622" PostTypeId="2" ParentId="9596" CreationDate="2022-09-04T13:35:51.043" Score="9" Body="&lt;p&gt;This is a question which is constantly popping up on the forum. The Pople basis sets are outdated. Modern basis set families, like the Karlsruhe def2 series, span (almost) the whole periodic table, include relativistic effects which are missing in the Pople sets, and are defined in a systematic hierarchy of balanced accuracy:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;def2-SV is a split-valence basis like 6-31G&lt;/li&gt;&#xA;&lt;li&gt;def2-SVP is a polarized split-valence basis like 6-31G**; def2-SV(P) omits polarization functions on hydrogen like 6-31G*&lt;/li&gt;&#xA;&lt;li&gt;def2-TZVP is a triple-zeta valence polarized basis&lt;/li&gt;&#xA;&lt;li&gt;def2-QZVP is a quadruple-zeta valence polarized basis&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The sets are consistent for all elements and are available for H to Rn. Diffuse functions are available with the D suffix (e.g. def2-SVP -&amp;gt; def2-SVPD);  for post-Hartree-Fock calculations one should add additional polarization functions (def2-TZVPP or def2-QZVPP).&lt;/p&gt;&#xA;&lt;p&gt;The basic def2 sets are also included in Gaussian.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-09-04T13:35:51.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9623" PostTypeId="1" CreationDate="2022-09-05T15:55:57.983" Score="7" ViewCount="564" Body="&lt;p&gt;I want to compute the ZPE and entropic terms for my platinum slab covered by a bilayer of water (network). I have performed a phonon calculation on a 3x3 q-point grid (my unit cell is ~ 4 Å long)&lt;/p&gt;&#xA;&lt;p&gt;The calculation is finished and now I am not sure about a few things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;I keep reading in the literature that one must calculate the ZPE/entropic terms using the adsorbate's vibration modes, the thing is that all the modes are coupled with the substrate, it is not possible to &amp;quot;isolate&amp;quot; the adsorbate's vibration.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I am pretty sure I need to average these quantities over the q-points grid but I can't find information about that.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;One of my colleagues tells me that I should compute the ZPE/entropic terms of the substrate alone and then subtract them to get the contribution of the adsorbate alone.&lt;/p&gt;&#xA;&lt;p&gt;Could someone give more details?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2022-09-06T16:57:57.767" Title="Details about ZPE and entropy of adsorbates" Tags="|quantum-espresso|phonons|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9624" PostTypeId="2" ParentId="9623" CreationDate="2022-09-05T16:18:30.137" Score="3" Body="&lt;p&gt;You might be overthinking things if the system looks like what I expect it does.  You can calculate all the terms for the platinum and subtract out their contribution, this is perfectly fine if you want to go this route.&lt;/p&gt;&#xA;&lt;p&gt;In practice however, this involves a massive number of displacements with nearly no purpose.  The vibrations of a water layer on platinum is unlikely to be very strongly coupled to the surface due to the relative weights of H2O and Pt.  A reasonable assumption is that the surface does not move significantly in the time of a H2O vibration, leading the approximation that you fix the entire surface in its optimized position.  This also has the advantage or removing Pt from the ZPE/entropy terms.&lt;/p&gt;&#xA;&lt;p&gt;This answer assumes you are using displacements to calculate phonons.  If you are using the DFPT in QE, then your original approach is probably the only way to do it.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-09-05T16:18:30.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9625" PostTypeId="1" CreationDate="2022-09-06T16:37:16.793" Score="4" ViewCount="247" Body="&lt;p&gt;I am currently looking at band structure mainly for a few magnetic compounds. Due to having a large super-cell my calculations have not converged with the HSE06 functional. So I looked at what else is possible, and I came accross a couple of papers (for example &lt;a href=&quot;https://www.nature.com/articles/s41524-020-00360-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt;) which were comparing different functionals. According to them, HSE06 and mBJ are the most reliable functionals for band Structure calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/154/how-trustworthy-is-the-tran-blaha-modified-becke-johnson-potential-and-how-does&quot;&gt;This&lt;/a&gt; post and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/154/5&quot;&gt;this post&lt;/a&gt; talk about how the TBmBJ functional is not reliable and I am wondering if the same thing can be said for mBJ.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5" LastEditDate="2023-06-13T11:48:09.983" LastActivityDate="2023-06-13T12:22:26.207" Title="Is the mBJ functional reliable for band structure calculations in VASP?" Tags="|density-functional-theory|functional|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9626" PostTypeId="2" ParentId="9623" CreationDate="2022-09-06T16:57:57.767" Score="2" Body="&lt;p&gt;Usually for an isolated species, you would just compute the vibrational modes (phonon modes) at the gamma point and sum the modes to compute the molecular ZPE&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E^{ZP} = \frac{h}{2} \sum_{i=1}^{3N-6} \nu_i&#xA;$$&lt;/span&gt;&#xA;You would use the same set of frequencies in your entropic corrections.&lt;/p&gt;&#xA;&lt;p&gt;But for a periodic system, what you would want to do is compute the phonon density of states (PDOS) of the system. So, to compute the ZPE of a periodic system, you would integrate over the frequency-weighted PDOS&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E^{ZP} = \frac{h}{2}\int_0^\infty \nu g(\nu) d\nu&#xA;$$&lt;/span&gt;&#xA;where the PDOS &lt;span class=&quot;math-container&quot;&gt;$g(\nu)$&lt;/span&gt; is just the number of phonon modes that exist at a specific frequency &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; (across all &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;-points in your BZ). So no averaging procedure is needed, just compute the PDOS. You should be able to use the PDOS to also compute entropic corrections for the periodic system.&lt;/p&gt;&#xA;&lt;p&gt;If you are using the &lt;code&gt;ph.x&lt;/code&gt; code from QE to compute phonon modes, you can set the variable &lt;code&gt;nat_todo&lt;/code&gt; (see the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PH.html#idm371&quot; rel=&quot;nofollow noreferrer&quot;&gt;phonon code's documentation for details&lt;/a&gt;). This lets you compute the vibrational modes for a subset of atoms. Likely, you can neglect the vibrational modes of Pt since they are so much heavier than O and H. The frequencies of the Pt slab won't be very different between the isolated slab system and water bilayer system.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can also use &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phonopy&lt;/a&gt; to compute vibrational modes, and you should also be able to select subsets of atoms there as well.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastActivityDate="2022-09-06T16:57:57.767" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9627" PostTypeId="1" AcceptedAnswerId="9634" CreationDate="2022-09-06T19:04:56.583" Score="6" ViewCount="426" Body="&lt;p&gt;I have been using &lt;code&gt;OpenBabel&lt;/code&gt; as a handy-tool for converting small files without any issues.&lt;/p&gt;&#xA;&lt;p&gt;Now, I am working with graphene-like systems with hundreds or even thousands of atoms, and the conversion of a 1360-line &lt;code&gt;XYZ&lt;/code&gt; file to &lt;code&gt;MOL2&lt;/code&gt; format is taking more than 48 hours! My notebook is running Ubuntu 22.04 (64-bit), with an Intel i7 12-core processor and 24GB RAM.&lt;/p&gt;&#xA;&lt;p&gt;There seems to be a problem with trying to do this using &lt;code&gt;OpenBabel&lt;/code&gt;, whether directly or via third-party programs that use it as a plugin (like MAESTRO, Avogadro, etc.).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there any other tool for file conversion than does not use &lt;code&gt;OpenBabel&lt;/code&gt; (or any library from it) that can be used for large files?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2022-09-07T21:52:51.213" LastActivityDate="2022-09-07T21:52:51.213" Title="Alternatives to OpenBabel for converting *large* files?" Tags="|software|software-recommendations|one-topic-per-answer|openbabel|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9628" PostTypeId="2" ParentId="8624" CreationDate="2022-09-07T07:37:48.950" Score="4" Body="&lt;p&gt;Elastic constants can be derived from constitutive relationship by calculating  stresses from a strained system&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{ij}=C_{ijkl}\epsilon_{kl}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Once the crystal is deformed by some finite strain and stresses can be&#xA;extracted from the output of any DFT packages.&lt;/p&gt;&#xA;&lt;p&gt;Another method is to use strain energy function, where you distort the crystal and measures change in energy with respect to reference configurations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C_{ij}=\frac{\partial^{2}E}{e_{i}e_{j}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For 2D system, the process of calculating elastic constants is same as bulk 3D crystal. The system is distorted by series of strains and fitted with second order polynomials.&#xA;In the commercial package VASP, &lt;code&gt;IBRION=6&lt;/code&gt; and &lt;code&gt;NFREE=4&lt;/code&gt; is good place to start or otherwise calculate elastic constants using external packages such as &lt;a href=&quot;https://vaspkit.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspkit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A few examples from the literature where stability criteria and methods for 2D materials are given which will be a good start:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Choudhary, K.; Cheon, G.; Reed, E.; Tavazza, F. Elastic Properties of Bulk and Low-Dimensional Materials Using van Der Waals Density Functional. Physical Review B, 2018, 98. &lt;a href=&quot;https://doi.org/10.1103/physrevb.98.014107&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Yuan, J.N.; Cheng, Y.; Zhang, X.Q.; Chen, X.R.; Cai, L.C. First-Principles Study of Electronic and Elastic Properties of Hexagonal Layered Crystal MoS2 Under Pressure. Zeitschrift für Naturforschung A, 2015, 70, 529–537. &lt;a href=&quot;https://doi.org/10.1515/zna-2015-0102&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Maździarz, M. Comment on ‘The Computational 2D Materials Database: High-Throughput Modeling and Discovery of Atomically Thin Crystals.’ 2D Materials, 2019, 6, 048001. &lt;a href=&quot;https://doi.org/10.1088/2053-1583/ab2ef3&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-09-24T19:48:59.617" LastActivityDate="2022-09-24T19:48:59.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9630" PostTypeId="2" ParentId="5088" CreationDate="2022-09-07T12:35:00.377" Score="3" Body="&lt;p&gt;I'll answer my own question.&lt;/p&gt;&#xA;&lt;p&gt;I recently co-authored a &lt;a href=&quot;https://arxiv.org/abs/2206.05727&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; titled &lt;em&gt;Mismatched Estimation in the Distance Geometry Problem&lt;/em&gt; that tackles this exact topic. This paper was recently accepted for publication at the 56th Asilomar Conference on Signals, Systems, and Computers. Here is the abstract:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We investigate mismatched estimation in the context of the distance geometry problem (DGP). In the DGP, for a set of points, we are given noisy measurements of pairwise distances between the points, and our objective is to determine the geometric locations of the points. A common approach to deal with noisy measurements of pairwise distances is to compute least-squares estimates of the locations of the points. However, these least-squares estimates are likely to be suboptimal, because they do not necessarily maximize the correct likelihood function. In this paper, we argue that more accurate estimates can be obtained when an estimation procedure using the correct likelihood function of noisy measurements is performed. Our numerical results demonstrate that least-squares estimates can be suboptimal by several dB.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="3676" LastActivityDate="2022-09-07T12:35:00.377" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9632" PostTypeId="2" ParentId="8309" CreationDate="2022-09-07T13:15:04.710" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://nninc.cnf.cornell.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://nninc.cnf.cornell.edu/&lt;/a&gt; This URL has expired.&#xA;&lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/periodictable-gga-abinit.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://departments.icmab.es/leem/SIESTA_MATERIAL/Databases/Pseudopotentials/periodictable-gga-abinit.html&lt;/a&gt;. Some of the pseudopotentials of this URL are really inaccurate, you might try this.&#xA;&lt;a href=&quot;https://www.simuneatomistics.com/siesta-pro/siesta-pseudos-and-basis-database/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.simuneatomistics.com/siesta-pro/siesta-pseudos-and-basis-database/&lt;/a&gt;.&#xA;On the other hand you need to put these into the fdf file.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/XfzxJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XfzxJ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5960" LastActivityDate="2022-09-07T13:15:04.710" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9633" PostTypeId="1" AcceptedAnswerId="9641" CreationDate="2022-09-07T16:08:31.257" Score="3" ViewCount="182" Body="&lt;p&gt;I am interested in calculating the following expectation value for atoms using a converged Slater deteminant from in DFT&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \left&amp;lt; \Psi \left| \sum_{i,j=1}^N r_i^a r_j^b\right| \Psi \right&amp;gt; \; ,\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$a,b$&lt;/span&gt; being some small integers (let's say &lt;span class=&quot;math-container&quot;&gt;$a=b=1$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$i,j$&lt;/span&gt; run over each individual electron up to the total number of electrons &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; being the operator corresponding to the distance of electron &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; from the nucleus. I want to use PySCF because the code should contain all tools I need.&lt;/p&gt;&#xA;&lt;p&gt;Originally I assumed I can just use the converged electron density to calculate the expectation values, but I believe I would lose the exchange terms as opposed to explicitly writing out the Slater determinant on both sides.&lt;/p&gt;&#xA;&lt;p&gt;I've figured that I will be needing one and two electron integrals. For example if &lt;span class=&quot;math-container&quot;&gt;$a=1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b=0$&lt;/span&gt; I think the matrix element reduces to&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \left&amp;lt; \Psi \left| \sum_{i=1}^N r_i\right| \Psi \right&amp;gt; = \frac{1}{N} \left( \sum_n \left&amp;lt; \phi_n|r|\phi_n \right&amp;gt; + \sum_{m,n} \sum_n \left&amp;lt; \phi_m|r|\phi_n \right&amp;gt;  \right)\; ,\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which should correspond to the standard one electron integral with the Slater determinant ansatz. I also believe if &lt;span class=&quot;math-container&quot;&gt;$b \neq 0$&lt;/span&gt; I should be  getting a two electron integral. Based on my &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9410/molecular-orbital-values-on-grid-points-in-pyscf&quot;&gt;previous question&lt;/a&gt;, I also have a code that can calculate an arbitrary one-electron integral between any molecular orbitals. I don't know yet how to do it for two electron integrals.&lt;/p&gt;&#xA;&lt;p&gt;However, I believe calculating matrix elements of Slater determinants should not be a rare problem, so I think there must be a standard way in PySCF of doing this.&lt;/p&gt;&#xA;&lt;p&gt;What is the best approach of calculating the matrix element I am looking for?&lt;/p&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5648" LastEditDate="2022-09-08T11:31:26.113" LastActivityDate="2022-09-08T16:07:29.473" Title="How to get a two-electron expectation value for atoms in PySCF?" Tags="|density-functional-theory|pyscf|wavefunctions|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9634" PostTypeId="2" ParentId="9627" CreationDate="2022-09-07T20:04:25.867" Score="7" Body="&lt;p&gt;Large files aren't a problem &lt;em&gt;per se&lt;/em&gt;. Open Babel easily handles 25k atom proteins. You're hitting slow conversion because you have files with many fused aromatic rings, e.g., graphene flakes, nanotubes, etc.&lt;/p&gt;&#xA;&lt;p&gt;The problem you're describing is based on the need to perceive bond orders. (The &lt;code&gt;mol2&lt;/code&gt; format requires bond orders and aromaticity to define types, etc.)&lt;/p&gt;&#xA;&lt;p&gt;The current algorithm in Open Babel uses &lt;strong&gt;backtracking&lt;/strong&gt; when finding the correct Kekulé assignment. This can require a &lt;em&gt;lot&lt;/em&gt; of time on fused ring systems because there are a lot of potential paths to check.&lt;/p&gt;&#xA;&lt;p&gt;It's possible to turn off bond order assignment when reading XYZ files, using the &lt;code&gt;-as&lt;/code&gt; flag (i.e., read single bonds only)&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;obabel file.xyz -O file.mol2 -as&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here's benzene:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@&amp;lt;TRIPOS&amp;gt;MOLECULE&#xA;benzene example&#xA; 12 12 0 0 0&#xA;SMALL&#xA;GASTEIGER&#xA;&#xA;@&amp;lt;TRIPOS&amp;gt;ATOM&#xA;      1 C           0.0000    1.4027    0.0000 C.3     1  UNL1       -0.0309&#xA;      2 H           0.0000    2.4903    0.0000 H       1  UNL1        0.0309&#xA;      3 C          -1.2148    0.7014    0.0000 C.3     1  UNL1       -0.0309&#xA;      4 H          -2.1567    1.2451    0.0000 H       1  UNL1        0.0309&#xA;      5 C          -1.2148   -0.7014    0.0000 C.3     1  UNL1       -0.0309&#xA;      6 H          -2.1567   -1.2451    0.0000 H       1  UNL1        0.0309&#xA;      7 C           0.0000   -1.4027    0.0000 C.3     1  UNL1       -0.0309&#xA;      8 H           0.0000   -2.4903    0.0000 H       1  UNL1        0.0309&#xA;      9 C           1.2148   -0.7014    0.0000 C.3     1  UNL1       -0.0309&#xA;     10 H           2.1567   -1.2451    0.0000 H       1  UNL1        0.0309&#xA;     11 C           1.2148    0.7014    0.0000 C.3     1  UNL1       -0.0309&#xA;     12 H           2.1567    1.2451    0.0000 H       1  UNL1        0.0309&#xA;@&amp;lt;TRIPOS&amp;gt;BOND&#xA;     1     1     2    1&#xA;     2     1     3    1&#xA;     3     1    11    1&#xA;     4     3     4    1&#xA;     5     3     5    1&#xA;     6     5     6    1&#xA;     7     5     7    1&#xA;     8     7     8    1&#xA;     9     7     9    1&#xA;    10     9    10    1&#xA;    11     9    11    1&#xA;    12    11    12    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now that seems useless, since all the carbon atoms are &lt;code&gt;C.3 &lt;/code&gt; instead of &lt;code&gt;C.ar&lt;/code&gt; .. but it's trivial using Python or another script to find-and-replace the atom typings.&lt;/p&gt;&#xA;&lt;p&gt;The other thing is to fix the C-C bonds:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@&amp;lt;TRIPOS&amp;gt;BOND&#xA;     1     1     2    1&#xA;     2     1     3   ar&#xA;     3     1    11   ar&#xA;     4     3     4    1&#xA;     5     3     5   ar&#xA;     6     5     6    1&#xA;     7     5     7   ar&#xA;     8     7     8    1&#xA;     9     7     9   ar&#xA;    10     9    10    1&#xA;    11     9    11   ar&#xA;    12    11    12    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Besides Open Babel, it's possible to use RDKit with the &lt;a href=&quot;https://github.com/jensengroup/xyz2mol&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;xyz2mol&lt;/code&gt; package&lt;/a&gt; and save to &lt;code&gt;SDF&lt;/code&gt; format, converting the resulting &lt;code&gt;.mol&lt;/code&gt; or &lt;code&gt;.sdf&lt;/code&gt; file to &lt;code&gt;.mol2&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-09-07T20:04:25.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9635" PostTypeId="2" ParentId="8532" CreationDate="2022-09-07T21:31:00.547" Score="1" Body="&lt;p&gt;Turns out the best way to spot phase transitions in polymers is to run the extended cell simulations and calculate surface tension, as seen in this paper: &lt;a href=&quot;http://dx.doi.org/10.1063/1.3227905&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dx.doi.org/10.1063/1.3227905&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-09-07T21:31:00.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9636" PostTypeId="2" ParentId="8626" CreationDate="2022-09-07T21:42:12.383" Score="1" Body="&lt;p&gt;The problem with this moveset is that it is too local. The best way to decorrelate polymer configurations is to run simulations with more aggressive moves, such as chain regrowth.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2022-09-07T21:42:12.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9637" PostTypeId="2" ParentId="4472" CreationDate="2022-09-08T02:28:08.203" Score="0" Body="&lt;p&gt;First, the lattice optimization is performed, and then the atomic position is optimized. After the stable position is obtained, the static calculation can be performed, and then the k-point path is set to obtain the energy band.&lt;/p&gt;&#xA;" OwnerUserId="5960" LastActivityDate="2022-09-08T02:28:08.203" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9638" PostTypeId="1" CreationDate="2022-09-07T12:58:17.710" Score="5" ViewCount="71" Body="&lt;p&gt;I need to access to the DICTNRY File of GAMESS-US, I need to ivestigate the overlap matrix elements (&lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/GAMESS_Manual/prog.pdf&quot; rel=&quot;noreferrer&quot;&gt;written as &amp;quot;12&amp;quot; in the Programmer's Reference Tools&lt;/a&gt;) and change them to &amp;quot;trick&amp;quot; the GAMESS to calculate the transiton matrix elements to compute the FSD of a molecule. In short, How can I access this so called DICTNRY files? I'm looking into the &amp;quot;source&amp;quot; directory in gamess files but I can't find anything in there. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="5755" OwnerDisplayName="Alert" LastActivityDate="2023-03-18T07:28:13.140" Title="How to access Master &quot;DICTNRY&quot; file of GAMESS" Tags="|computational-chemistry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9639" PostTypeId="1" AcceptedAnswerId="9643" CreationDate="2022-09-08T14:58:54.497" Score="8" ViewCount="845" Body="&lt;p&gt;I feel like this is a really stupid question, and I've been ashamed to ask for a while...&lt;/p&gt;&#xA;&lt;p&gt;When I'm about to run some electronic structure calculation on a  molecule, how do I know if I need to use an open-shell method (e.g. ROHF, UHF) as the first step in a correlated method like coupled cluster?&lt;/p&gt;&#xA;&lt;p&gt;I understand that a single atom with an odd number of electrons will obviously have an unpaired electron. And, free radicals would be an obvious generalization of that.&lt;/p&gt;&#xA;&lt;p&gt;I also understand that a molecule with (nearly-)degenerate frontier orbitals will need the multi-reference aspect of an open-shell method.&lt;/p&gt;&#xA;&lt;p&gt;But how do I know about that degeneracy beforehand? Is it symmetry?&lt;/p&gt;&#xA;&lt;p&gt;When I look at a molecule, what do I do to decide that RHF is not applicable?&lt;/p&gt;&#xA;" OwnerUserId="5965" LastEditorUserId="5" LastEditDate="2022-09-09T02:33:36.413" LastActivityDate="2022-09-09T07:05:40.683" Title="How to detect an &quot;open shell&quot; molecule?" Tags="|ab-initio-calculations|electronic-structure|hartree-fock|spin|multi-reference|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9640" PostTypeId="1" CreationDate="2022-09-08T15:38:44.410" Score="2" ViewCount="271" Body="&lt;p&gt;I am looking at simulating solar cells using COMSOL software. Majorly speaking we are working on A2BX6 perovskites where we plan to simulate solar cells for different doped versions of the perovskite. However the difficulty here is that because most of the doped versions have not been syntesized yet so we do not have access to various parameters that would be required for solar cell simulation. For example I refered to this video - &lt;a href=&quot;https://www.youtube.com/watch?v=a4Yfa6Al-D0&quot; rel=&quot;nofollow noreferrer&quot;&gt;COMSOL simulation of PN junction&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is there any other software or method we can use to simulate solar cells efficiently and easily.&lt;/p&gt;&#xA;" OwnerUserId="5610" LastActivityDate="2022-09-08T15:38:44.410" Title="Perovskites Solar design using COMSOL" Tags="|density-functional-theory|computational-chemistry|perovskites|solar-cells|multi-junction-photovoltaics|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T23:04:54.753" ContentLicense="CC BY-SA 4.0" />
  <row Id="9641" PostTypeId="2" ParentId="9633" CreationDate="2022-09-08T16:07:29.473" Score="2" Body="&lt;p&gt;First of all, the &amp;quot;diagonal&amp;quot; contribution of Eq. (1),&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \Psi | \sum_i^N r_i^{a+b} | \Psi \rangle \tag{3}&#xA;$$&lt;/span&gt;&#xA;is the expectation value of a one-body operator, so you already know how to deal with it. The rest of my answer deals with the remaining term &lt;span class=&quot;math-container&quot;&gt;$2\langle \Psi | \sum_{i&amp;lt;j}^N r_i^a r_j^b | \Psi \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The expectation value of an arbitrary two-body operator &lt;span class=&quot;math-container&quot;&gt;$\hat{G} = \sum_{i&amp;lt;j} \hat{g}(i,j)$&lt;/span&gt; over Slater determinants is given by the &lt;a href=&quot;https://en.wikipedia.org/wiki/Slater%E2%80%93Condon_rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slater-Condon rules&lt;/a&gt; (regardless of whether there is only atom in the system, and regardless of the form of the operator except that it's two-body)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \Psi | \hat{G} | \Psi \rangle = \frac{1}{2} \sum_m \sum_n \left( \langle \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) | \hat{g} | \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) \rangle - \langle \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) | \hat{g} | \phi_n(\vec{r}_1) \phi_m(\vec{r}_2) \rangle \right) \tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In your case, you'll have two-electron integrals of the form &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) | r_1^a r_2^b | \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) | r_1^a r_2^b | \phi_n(\vec{r}_1) \phi_m(\vec{r}_2) \rangle$&lt;/span&gt;. Since the integrands are a product of a function of &lt;span class=&quot;math-container&quot;&gt;$\vec{r}_1$&lt;/span&gt; and a function of &lt;span class=&quot;math-container&quot;&gt;$\vec{r}_2$&lt;/span&gt;, the integrals are separable, e.g.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) | r_1^a r_2^b | \phi_m(\vec{r}_1) \phi_n(\vec{r}_2) \rangle = \langle \phi_m(\vec{r}_1) | r_1^a | \phi_m(\vec{r}_1) \rangle \langle \phi_n(\vec{r}_2) | r_2^b | \phi_n(\vec{r}_2) \rangle \tag{5}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;By now, the problem is completely reduced to the calculation of one-electron integrals.&lt;/p&gt;&#xA;&lt;p&gt;For arbitrary two-electron operators, the separation Eq. (5) is generally not possible. However, it is always possible to write the two-electron integral as a &lt;em&gt;sum&lt;/em&gt; of products of one-electron integrals, say via the &lt;a href=&quot;https://en.wikipedia.org/wiki/Multipole_expansion&quot; rel=&quot;nofollow noreferrer&quot;&gt;multipole expansion&lt;/a&gt;, although the sum may be an infinite series such that it can only be evaluated approximately. Even so, this separation is nevertheless sometimes used to speed up the evaluation of the two-electron term in e.g. DFT and TDDFT calculations, as in program packages like Dmol3 and &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.5143173&quot; rel=&quot;nofollow noreferrer&quot;&gt;BDF&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-09-08T16:07:29.473" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9642" PostTypeId="1" CreationDate="2022-09-08T18:20:57.100" Score="2" ViewCount="90" Body="&lt;p&gt;Can I repeat high symmetry points manually by copying the sequence on input file?&lt;/p&gt;&#xA;" OwnerUserId="5968" LastActivityDate="2022-09-10T17:33:37.663" Title="How to increase high symmetry points in band structure?" Tags="|band-structure|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9643" PostTypeId="2" ParentId="9639" CreationDate="2022-09-08T18:29:43.317" Score="6" Body="&lt;p&gt;When you're doing an electronic structure calculation, the input will include the following things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Geometry&lt;/li&gt;&#xA;&lt;li&gt;Basis set&lt;/li&gt;&#xA;&lt;li&gt;Number of electrons&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;&lt;strong&gt;Spin multiplicity&lt;/strong&gt;&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If the &lt;em&gt;&lt;strong&gt;spin multiplicity&lt;/strong&gt;&lt;/em&gt; is not 1 (i.e. you are not dealing with a singlet state), then you're certainly dealing with an open-shell system.&lt;/p&gt;&#xA;&lt;p&gt;The only case where this becomes highly non-trivial is when you're dealing with an &lt;em&gt;&lt;strong&gt;open-shell singlet&lt;/strong&gt;&lt;/em&gt;, meaning that there's a bunch of unpaired electrons, but overall the entire system still has a net spin multiplicity of 1.&lt;/p&gt;&#xA;&lt;p&gt;Open shell singlets can be notoriously complicated. They arise (for example) in studies of one of the most difficult problems in all of quantum chemistry, which is to accurately study the electronic structure of FeMoco (arguably the most complicated enzyme known) as we discussed open-shell singlets &lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.5063376&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this paper&lt;/a&gt;. The answers to the question &amp;quot;&lt;a href=&quot;https://www.reddit.com/r/chemhelp/comments/1q0ufg/can_someone_explain_how_describing_a_molecule_as/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Why is &amp;quot;open-shell singlet&amp;quot; not an oxymoron&lt;/a&gt;&amp;quot; are a good starting point to understand why such states arise.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So how do you know whether or not the system that you're studying needs to be modeled as an open-shell singlet?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Sometimes you know based on spectroscopic experiments what the occupation numbers of the valence orbitals should be (see the &amp;quot;configuration&amp;quot; column in my answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4495/5&quot;&gt;How to determine occupied and closed orbitals for a Molpro CASSCF calculation?&lt;/a&gt;). For example, you might already know by looking through the experimental literature, that the ground electronic state of the molecule in which you're interested has an equal (and non-zero) number of unpaired spin-up versus unpaired spin-down electrons.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What if there's not enough experimental data?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then often the computational scientist's task is to do calculations for various values of the spin multiplicity (try making the molecule a singlet, triplet, etc.) and various electronic configurations to see which one gives the lowest energy. For very simple molecules you can infer what the ground state electronic configuration will be, but my answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1243/5&quot;&gt;Total spin and/or multiplicity for transition metal ions?&lt;/a&gt; shows that even for a molecule with only two atoms (like the diatomic iron dimer) we don't know &lt;em&gt;&lt;strong&gt;experimentally nor theoretically&lt;/strong&gt;&lt;/em&gt; what the spin multiplicity of the ground electronic state is! My answer to the above-linked CASSCF question also shows examples where the ground state electronic configuration is still unknown. Another related thread is here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6470/5&quot;&gt;How to find out the multiplicities of molecules containing d and f block species?&lt;/a&gt;. So often we do not know in advance whether the system's ground state electronic configuration corresponds to an open-shell system or a closed-shell system, in fact we often don't even know the spin multiplicity so we frequently find ourselves doing calculations for many different configurations and attempting to determine which one has the lowest energy &lt;strong&gt;so that scientists in the future don't have to.&lt;/strong&gt; In this regard, a literature search can be helpful: see if others have studied the same molecule and what they said about the open-shell vs closed-shell character of the ground electronic state.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Apart from what I've discussed above for ground electronic states&lt;/strong&gt;, many people are also just interested in excited state chemistry, meaning that they're doing electronic structure calculations for many different states (including open-shell singlets, for example). In this case the decision is a lot easier :)&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="838" LastEditDate="2022-09-09T07:05:40.683" LastActivityDate="2022-09-09T07:05:40.683" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9645" PostTypeId="1" CreationDate="2022-09-10T09:07:08.927" Score="3" ViewCount="121" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IEHUa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IEHUa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;During band structure calculations in Quantum espresso I found that the bands are coming in Linear form and not curvature. Why is this happening? Is there any explanation for this? Which parameters cause it and need correction?&lt;/p&gt;&#xA;&lt;p&gt;Edit: I added a plot for reference.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="2077" LastEditDate="2022-10-27T06:23:37.233" LastActivityDate="2022-10-27T06:23:37.233" Title="Zig zag straight lines bands from Quantum Espresso calculations" Tags="|quantum-espresso|band-structure|electronic-structure|" AnswerCount="0" CommentCount="6" ClosedDate="2023-06-14T01:08:33.467" ContentLicense="CC BY-SA 4.0" />
  <row Id="9646" PostTypeId="2" ParentId="9642" CreationDate="2022-09-10T09:20:07.820" Score="1" Body="&lt;p&gt;High Symmetry points for a particular system can be found in the literature and online sources. Such as, the work entitle &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2016.10.015&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Band structure diagram paths based on crystallography&lt;/em&gt;&lt;/a&gt;. Also, you can check online tools like &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;nofollow noreferrer&quot;&gt;SeeK-path&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Performing calculations by this, you will understand which path suits your structure best and you will know to increase the number of points as well as eigenvalues that need to be computed in a path.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="24" LastEditDate="2022-09-10T17:33:37.663" LastActivityDate="2022-09-10T17:33:37.663" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9647" PostTypeId="1" CreationDate="2022-09-10T10:21:11.550" Score="3" ViewCount="39" Body="&lt;p&gt;I would like to build a regression model to predict a property of molecules not yet synthesized. I have calculated 5666 alvadesc descriptors for each SMILES in my experimental dataset, but comparing various models with LazyPredict I get poor R^2 values. I would like to know how to effectively select the minimum number of most relevant descriptors and if this can help me increase the value of R^2. I have tried using featurewiz with poor results.&lt;/p&gt;&#xA;" OwnerUserId="4955" LastEditorUserId="5" LastEditDate="2022-09-10T12:25:55.003" LastActivityDate="2022-09-10T12:25:55.003" Title="How to select the best features for a drug discovery model?" Tags="|machine-learning|biomaterials|" AnswerCount="0" CommentCount="2" ClosedDate="2023-06-14T01:09:43.107" ContentLicense="CC BY-SA 4.0" />
  <row Id="9648" PostTypeId="1" CreationDate="2022-09-10T13:14:23.160" Score="5" ViewCount="490" Body="&lt;p&gt;How can I know which one is direct bandgap material and which one is indirect?&lt;/p&gt;&#xA;&lt;p&gt;Why does Germanium have an indirect bandgap? How can be it become a direct bandgap material?&lt;/p&gt;&#xA;&lt;p&gt;Here, I have attached a picture where I have calculated the direct and indirect bandgap of Germamium.&lt;/p&gt;&#xA;&lt;p&gt;I increased its pressure by reducing the cellsize.&lt;/p&gt;&#xA;&lt;p&gt;Is there any way of understanding, which one has a direct bandgap and which one has an indirect band gap?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vGZeq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vGZeq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5968" LastEditorUserId="24" LastEditDate="2022-09-13T12:33:38.663" LastActivityDate="2022-09-13T13:16:48.843" Title="Direct and Indirect bandgap" Tags="|bandgap|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9649" PostTypeId="2" ParentId="9648" CreationDate="2022-09-10T17:25:53.677" Score="6" Body="&lt;p&gt;In order to know if your material has direct/indirect band gap, you need to calculate the electronic band structure: Energy vs &lt;strong&gt;k&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then, you look for the smaller &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; between the bottom of the conduction band (BCB) and the top of the valence band (TVB). If this &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; occurs for the same value of &lt;strong&gt;k&lt;/strong&gt;, then you have a direct band gap material, otherwise, you will have an indirect band gap material.&lt;/p&gt;&#xA;&lt;p&gt;The image bellow correspond to the Germanium&lt;sup&gt;&lt;a href=&quot;http://www.ioffe.ru/SVA/NSM/Semicond/Ge/bandstr.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;&lt;/sup&gt;. As you can see, the smaller &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; occurs between the BCB at  &lt;strong&gt;k&lt;/strong&gt; = &lt;span class=&quot;math-container&quot;&gt;$\langle 111 \rangle$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; point) and TVB at &lt;strong&gt;k&lt;/strong&gt; &lt;span class=&quot;math-container&quot;&gt;$= \langle 000 \rangle$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9whcO.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9whcO.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;About &lt;em&gt;&lt;strong&gt;Why?&lt;/strong&gt;&lt;/em&gt;, I recommend to watch the Richard Feynman interview about magnets &lt;a href=&quot;https://youtu.be/36GT2zI8lVA&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="142" LastEditDate="2022-09-13T13:16:48.843" LastActivityDate="2022-09-13T13:16:48.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9650" PostTypeId="2" ParentId="9474" CreationDate="2022-09-10T21:51:02.273" Score="3" Body="&lt;p&gt;So what I originally wanted is possible, with a little python scripting.&lt;/p&gt;&#xA;&lt;p&gt;To achieve this, a fcidump file containing h1 and h2 needs to be created by moplro.&lt;/p&gt;&#xA;&lt;p&gt;This entails running an SCF in molpro calculation prior, in my case a HF calculation.&lt;/p&gt;&#xA;&lt;p&gt;From this SCF, the orbitals have to be stored.&lt;/p&gt;&#xA;&lt;p&gt;Now in pyscf there is the  &amp;quot;tools.fcidump.to_scf&amp;quot; function, which can be used to read in the h1 and h2 and parse them correctly.  They will however be given in terms of the Hartree Fock orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The output of the function &amp;quot;tools.fcidump.to_scf&amp;quot; is a &amp;quot;scf&amp;quot; object. Use its method &amp;quot;.run()&amp;quot; and you will rediagonalize the HF hamiltonian. This generates all the data you need in order to run the FCI algorithm of pyscf with respect to the same integrals as molpro. Now from the fcivectors obtained using pySCFs FCI method, density matrices can be generated.&lt;/p&gt;&#xA;&lt;p&gt;These density matrices are incompatible if read into molpro. This is because molpro expects density matrices to be given with respect to the integrals that would be generated within the basis set indicated in the molpro input (i.e. sto-3g, aug-cc-pvdz or similar).&lt;/p&gt;&#xA;&lt;p&gt;To resolve this issue transform the density matrix back into the AO basis using the orbitals and hence generate density matrices that will be identical to molpros density matrices.&lt;/p&gt;&#xA;&lt;p&gt;I wrote a short &lt;a href=&quot;https://github.com/JannisErhard/molpro_to_pyscf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pythonscript&lt;/a&gt; that does all this, of course you will need molpro input data, as described, the fcidump file, the orbitals and alos pySCF.&lt;/p&gt;&#xA;&lt;p&gt;At this point it will probably only function for atoms. I tested this so far for Be sto-3g.&lt;/p&gt;&#xA;" OwnerUserId="5815" LastActivityDate="2022-09-10T21:51:02.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9651" PostTypeId="2" ParentId="8835" CreationDate="2022-09-12T09:38:34.527" Score="5" Body="&lt;p&gt;Answer: band folding is a little more subtle than I originally thought. I'd only really come across band folding in the textbook example of 1D and rather naively assumed that in higher dimensions if you were 'ignoring' the dimension that had a supercell that it could be neglected. This is emphatically &lt;em&gt;not&lt;/em&gt; the case.&lt;/p&gt;&#xA;&lt;p&gt;An example that illustrates this: Consider a tight binding model in 2D, where we have a supercell along x of length 2. The hoppings in all directions are, say, 0.1 and the onsite energies 1. We neglect the hoppings along y for now; the (folded) band structure along k_x is plainly given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zPdjY.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zPdjY.jpg&quot; alt=&quot;foldedbandstruc&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now we turn on the hoppings along y. We will be interested in the bandstructure along the (0, k_y) line. My naive assertion was that as k_x = 0 we ignore the supercell folding, but this is incorrect. The above graph has &lt;strong&gt;2&lt;/strong&gt; energies at the Gamma point, as under the folding k_x = pi is identified with k_x = 0. So, the complete bandstructure should look something like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ibqlN.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ibqlN.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And if we take the desired cut along (0, k_y) we see essentially the same thing I was seeing with my example above:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vGIgx.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vGIgx.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This of course solves the problem. Many thanks for the help! The minimal answer is I guess that folding in general changes the number of bands at the gamma point, so even if you're setting that direction to zero it still contributes.&lt;/p&gt;&#xA;" OwnerUserId="5154" LastActivityDate="2022-09-12T09:38:34.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9652" PostTypeId="2" ParentId="4653" CreationDate="2022-09-12T17:14:51.733" Score="1" Body="&lt;p&gt;Just to preserve ProfM's comments that seem to to answer the question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In principle yes, but its accuracy will depend somehow on the specific features of your current TB model and what you want for the new one. For example, if you only have nearest neighbour hoppings between layers, then it should be relatively easy to increase the number of layers, whereas if you want hoppings between distant layers, then you may not have enough information. If you specify some more the details of your current model, I can provide a full answer.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In response to a comment about whether the TB matrix could be expanded simply by copying existing layers:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If the interlayer hopping is weak, then I would say it is reasonable to truncate it at say the first nearest neighbour. In this way, you should be able to stack together the TB model you have to increase the number of layers.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-09-12T17:14:51.733" CommentCount="0" CommunityOwnedDate="2022-09-12T17:14:56.860" ContentLicense="CC BY-SA 4.0" />
  <row Id="9653" PostTypeId="2" ParentId="8920" CreationDate="2022-09-12T17:23:34.277" Score="2" Body="&lt;p&gt;Summarizing the OP's comment that describes how they managed to remove negative (imaginary) frequencies for their system:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Ensure correct symmetry of the molecular geometry&lt;/li&gt;&#xA;&lt;li&gt;Include D3 dispersion for the DFT calculation&lt;/li&gt;&#xA;&lt;li&gt;Use an ultrafine integration grid for the SCF&lt;/li&gt;&#xA;&lt;li&gt;Use the DFT-D3 Hessians as a guess to perform the MP2 optimization/Freq.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-09-12T17:23:34.277" CommentCount="0" CommunityOwnedDate="2022-09-12T17:23:34.277" ContentLicense="CC BY-SA 4.0" />
  <row Id="9654" PostTypeId="2" ParentId="8672" CreationDate="2022-09-12T19:58:53.720" Score="3" Body="&lt;p&gt;Its a bit tough to prove a negative, but currently I believe this isn't possible with VASP or any other QM package. Searching the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP Wiki&lt;/a&gt; returns no hits for &amp;quot;circular dichroism&amp;quot; or &amp;quot;optical rotation&amp;quot; (a close cousin of CD, which requires a lot of the same machinery to compute).&lt;/p&gt;&#xA;&lt;p&gt;In fact, optical rotation, which is arguably somewhat easier to implement than CD, was not available for periodic systems until very recently, when it was &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.1c00243&quot; rel=&quot;nofollow noreferrer&quot;&gt;implemented in CRYSTAL&lt;/a&gt;. My thesis was actually  focused (in part) on developing OR methods for periodic systems and as part of that I also did an extensive lit search for existing OR/CD implementations with Periodic Boundary Conditions (PBC). My search didn't yield anything and it seems CD simply hasn't been implemented for periodic systems yet.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-09-12T19:58:53.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9655" PostTypeId="1" CreationDate="2022-09-13T14:53:11.420" Score="3" ViewCount="52" Body="&lt;p&gt;In the literature&lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.92.086102&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1&lt;/a&gt;,&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.89.081305&quot; rel=&quot;nofollow noreferrer&quot;&gt;2]&lt;/a&gt;, when calculating GaAs or GaN surfaces by DFT (using package VASP), pseudohydrogen atoms with q=0.75e for the dangling bond of As and N, and q=1.25e for the dangling bond of Ga. I guess it is to make the overall surface charge neutral, but I am not exactly sure how 1.25e and 0.75e are obtained. Do we need to do a Bader analysis or something or is it just a common empirical number that I can use for all cases for GaAs GaN surfaces? Thank you!&lt;/p&gt;&#xA;" OwnerUserId="4101" LastEditorUserId="4101" LastEditDate="2022-09-13T20:35:33.857" LastActivityDate="2022-09-13T20:35:33.857" Title="Why do pseudohydrogen atoms have a charge of 0.75e when calculating GaAs surfaces?" Tags="|density-functional-theory|vasp|surface-passivation|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9656" PostTypeId="2" ParentId="6859" CreationDate="2022-09-14T01:02:26.617" Score="2" Body="&lt;p&gt;With the help of the PW forum and after digging a bit, I have gained some understanding of what went wrong.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;My job had&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;way too many processes spanning way too many threads for a single&#xA;node.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(from an answer to my question at &lt;a href=&quot;https://www.mail-archive.com/users@lists.quantum-espresso.org/msg41170.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PW forum&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;The suggestion was to first use OMP_NUM_THREADS=1 (turning off OpenMP - MPI coupling; i.e., run job on a single thread), such that the process ran on 1 MPI running on 1 GPU, and then start increasing the threads.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;From the &lt;strong&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=KMT-9sGXj38&quot; rel=&quot;nofollow noreferrer&quot;&gt;MaX School on QE: Hands-on QE on HPC and GPU systems&lt;/a&gt;&lt;/strong&gt;, I gained a little more insight into how calculations should be run on GPU systems.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Suppose we have 8 cores on the system and 2 GPUs, it is advisable that the number of MPIs and GPUs are kept the same. That is, each MPI process should communicate with a single GPU. Adding more MPI processes to the same number of GPUs (say, each GPU being accessed by 2 or more MPI processes) might enhance the performance but could also give the same performance or even degrade it. So, the best combination of MPIs, and GPUs needs to be figured out for the system to get optimal performance.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps.&lt;/p&gt;&#xA;&lt;p&gt;( I am new to GPU acceleration and MPI-related things. So any more insights by users will be highly appreciated.)&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2022-09-14T01:02:26.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9657" PostTypeId="1" CreationDate="2022-09-13T11:09:55.013" Score="5" ViewCount="80" Body="&lt;p&gt;In order to train GANs (Generative Adversarial Networks) on QM9 dataset, the dataset is converted to graph format as graph-structured molecules are invariant to the ordering of atoms. I want to understand why graph-structured molecules are invariant to the ordering of atoms.&lt;/p&gt;&#xA;" OwnerUserId="5978" OwnerDisplayName="Vinay Sharma" LastEditorUserId="142" LastEditDate="2022-09-17T19:17:03.037" LastActivityDate="2022-09-17T19:17:03.037" Title="Why are graph-structured molecules invariant to the ordering of atoms?" Tags="|computational-chemistry|machine-learning|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-09T23:02:05.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="9658" PostTypeId="2" ParentId="6688" CreationDate="2022-09-14T04:21:27.627" Score="3" Body="&lt;p&gt;This is not a complete answer with complete reasoning behind what had happened. However, I am giving this answer in case someone faces the same situation in the future.&lt;/p&gt;&#xA;&lt;p&gt;What had happened was, I did not use surface passivated nano-wires. This means that the atoms on the surface of the structure had dangling bonds due to the lack of neighboring atoms. This caused the structures to show surface states of electrons which cause band lines inside the gap of the material. A brief overview of the phenomenon can be found on the &lt;a href=&quot;https://en.wikipedia.org/wiki/Surface_states&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia page&lt;/a&gt; and a better insight can be obtained through this &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.100.115417&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In order to avoid this complication (for the case of nanostructures), the best way would be to terminate the surface bonds using hydrogen atoms (Sometimes -OH and -NH3 terminations are also used if I remember correctly).&lt;/p&gt;&#xA;&lt;p&gt;To do this, I tried a lot of software packages such as &lt;a href=&quot;https://pymol.org/2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymol&lt;/a&gt; and &lt;a href=&quot;https://www.olexsys.org/olex2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Olex2&lt;/a&gt; etc, but ended up having issues on the resultant structure near the periodic boundaries. Eventually I used my own code to calculate the number of neighbors and added the H atoms based on that. However this wasn't the most convenient or reliable approach since I had to manually verify every structure before the DFT calculations.&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2022-09-14T04:21:27.627" CommentCount="0" CommunityOwnedDate="2022-09-14T04:21:27.627" ContentLicense="CC BY-SA 4.0" />
  <row Id="9659" PostTypeId="1" CreationDate="2022-09-15T04:31:15.933" Score="4" ViewCount="155" Body="&lt;p&gt;I was analyzing &lt;a href=&quot;https://www.researchgate.net/publication/308901977_2d_Ising_model_simulation_code&quot; rel=&quot;nofollow noreferrer&quot;&gt;this source code of the Ising model&lt;/a&gt;. I found the term &amp;quot;&lt;em&gt;&lt;strong&gt;transient state&lt;/strong&gt;&lt;/em&gt;&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;I also found the term &lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.168537?cookieSet=1&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this text&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There are two absorbing states in this Markov chain because once either Jane or Eddie wins, the game is over, and the die is not rolled again. That the winner’s side of the die remains up forever is reflected in the value of unity along the diagonal and the value of zero in the nondiagonal elements for states 1 and 2. Also note that one of the 10 sides must be up, and so the sum of all the elements in each row of M&lt;sub&gt;die&lt;/sub&gt; must be unity. We multiply the matrix M&lt;sub&gt;die&lt;/sub&gt; on the left-hand side by a unit row vector VT with a 1 in the state the die is in before it is rolled. For the game to start the initial vector must be in the transient state, that is, it must be in state 3.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And, in &lt;a href=&quot;https://books.google.pl/books?id=dlLWaUNWBzwC&amp;amp;pg=PA207&amp;amp;dq=%22transient+state%22+%22ising%22+-markov&amp;amp;hl=en&amp;amp;sa=X&amp;amp;ved=2ahUKEwjpzar70Zb6AhXysYsKHSlfDXcQ6AF6BAgLEAI#v=onepage&amp;amp;q=%22transient%20state%22%20%22ising%22%20-markov&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;this text&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dJSYB.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dJSYB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What is a &amp;quot;transient&amp;quot; state or value or result in the Ising model?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="7" LastEditDate="2022-09-22T20:23:27.393" LastActivityDate="2022-09-22T20:23:27.393" Title="What is a &quot;transient&quot; state?" Tags="|quantum-mechanics|terminology|ising-model|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9660" PostTypeId="1" CreationDate="2022-09-15T07:09:23.060" Score="6" ViewCount="2621" Body="&lt;p&gt;I found that people often measure &amp;quot;electrical conductivity&amp;quot;, but some may say &amp;quot;electronic conductivity&amp;quot;. Can anyone explain the terms &amp;quot;electrical&amp;quot; and &amp;quot;electronic&amp;quot; in the context of conductivity?&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2022-09-15T12:37:02.620" LastActivityDate="2022-09-16T09:08:22.093" Title="Difference between &quot;electrical&quot; and &quot;electronic&quot;?" Tags="|physical-properties-of-materials|terminology|electronic-transport|" AnswerCount="3" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9661" PostTypeId="1" CreationDate="2022-09-15T11:21:10.020" Score="9" ViewCount="214" Body="&lt;p&gt;I have been trying to optimize the parallelization parameters in VASP. By varying the parameters(such as KPAR and NCORE) I am trying to reduce the &lt;em&gt;Elapsed time&lt;/em&gt; that is printed at the end of each line. But during this attempt I have realized the that running VASP with same input multiple times takes different amount of time and produces different results.&lt;/p&gt;&#xA;&lt;p&gt;Jobs that we were run within an hour have almost similar time consumption but jobs that were ran at different times of the day produced significantly different amount of time. This leads me to thinking perhaps the time depends upon amount of people using the HPC system but as I have reserved my cores using Job scheduler so the compute time should not depend upon usage of other HPC by other people.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore as the results(converged energy of the system) also varies, perhaps this leads to different amount of time consumption.&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;S No.&lt;/th&gt;&#xA;&lt;th&gt;Converged Energy&lt;/th&gt;&#xA;&lt;th&gt;Elapsed Time(sec)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;-245.41622996&lt;/td&gt;&#xA;&lt;td&gt;945.162&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;-245.41628055&lt;/td&gt;&#xA;&lt;td&gt;985.194&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;-245.41623049&lt;/td&gt;&#xA;&lt;td&gt;2141.557&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;-257.83322281&lt;/td&gt;&#xA;&lt;td&gt;3220.462&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;The above table shows different amount of time consumed along with different energies obtained. If we do get different result and time consumption with each case how does one compare efficiency between two different runs ??&lt;/p&gt;&#xA;&lt;p&gt;INCAR file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM   =  Perovskite&#xA;# Electronic minimization   &#xA;&#xA;                                                                                          &#xA;ISTART  = 0&#xA;ICHARG  = 2&#xA;# ALGO    = Normal &#xA;IALGO = 48&#xA;PREC= Accurate&#xA;ENCUT   = 390&#xA;NELM    = 100&#xA;LREAL   = Auto.&#xA;EDIFF   = 1E-6&#xA;EDIFFG  =-0.03&#xA;LWAVE   =.FALSE.&#xA;&#xA;&#xA;IVDW    = 11&#xA;&#xA;# Ionic minimization&#xA;NSW     = 0&#xA;IBRION  = -1&#xA;ISIF    = 3&#xA;POTIM   = 0.5&#xA;&#xA;# Exchange correlational functional&#xA;GGA = PE&#xA;ISMEAR   = 0&#xA;SIGMA    = 0.026&#xA;&#xA;KPAR = 4&#xA;NCORE = 16&#xA;&#xA;            &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;OUTCAR end&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)&#xA;---------------------------------------------------&#xA;free  energy   TOTEN  =      -245.41623049 eV&#xA;energy  without entropy=     -245.41518985&#xA;energy(sigma-&amp;gt;0) =     -245.41571017&#xA;--------------------------------------------------------------------------------------------------------&#xA;POTLOK:  cpu time    0.6164: real time    0.6195&#xA;--------------------------------------------------------------------------------------------------------&#xA;LOOP+:  cpu time 1509.6030: real time 2126.4977&#xA;4ORBIT:  cpu time    0.0000: real time    0.0000&#xA;total amount of memory used by VASP MPI-rank0   239488. kBytes&#xA;=======================================================================                                                                                                                                                                            base      :      30000. kBytes&#xA;nonlr-proj:      13629. kBytes&#xA;fftplans  :      29230. kBytes&#xA;grid      :      60261. kBytes&#xA;one-center:        155. kBytes&#xA;wavefun   :     106213. kBytes&#xA;General timing and accounting informations for this job:&#xA;========================================================&#xA;Total CPU time used (sec):     1522.199&#xA;User time (sec):     1449.966&#xA;System time (sec):       72.233&#xA;Elapsed time (sec):     2141.557&#xA;Maximum memory used (kb):      317960.&#xA;Average memory used (kb):           0.&#xA;Minor page faults:       552929&#xA;Major page faults:        13110&#xA;Voluntary context switches:        18856&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Script used for running the jobs&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#PBS -S /bin/bash&#xA;#PBS -N dp&#xA;#PBS -l select=1:ncpus=8&#xA;#PBS -l walltime=240:00:00&#xA;#PBS -o out.txt&#xA;#PBS -e err.txt&#xA;#PBS -joe&#xA;#PBS -q externalq&#xA;# ## export environment variable from current session to job run-time ... better to use this always.&#xA;#PBS -V&#xA;# ulimit -l unlimited&#xA;module load intel/2018.3.222 gcc/6.1.0&#xA;module load vasp/5.4.4&#xA;cd &lt;span class=&quot;math-container&quot;&gt;$PBS_O_WORKDIR&#xA;NPROCS=`wc -l &amp;lt; $&lt;/span&gt;PBS_NODEFILE`&#xA;echo &lt;span class=&quot;math-container&quot;&gt;$NPROCS&#xA;#export AMBERHOME=/scf-data/software/AMBER/amber18_intel/&#xA;#PATH=/scf-data/software/AMBER/amber18_intel/bin:$&lt;/span&gt;PATH&#xA;#source /scf-data/software/AMBER/amber18_intel/amber.sh&#xA;#export OMP_NUM_THREADS=1&#xA;#export I_MPI_PRINT_VERSION=1&#xA;mpirun -np 32  /scf-data/apps/vasp/vasp-5.4.4/vasp&#xA;exit&#xA;                                                                                         &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3672" LastEditorUserId="3672" LastEditDate="2022-09-15T18:18:45.917" LastActivityDate="2022-09-17T19:19:47.250" Title="Different Results obtained while doing multiple runs from same inputs in VASP" Tags="|vasp|high-performance-computing|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9662" PostTypeId="2" ParentId="9660" CreationDate="2022-09-15T11:50:51.473" Score="6" Body="&lt;p&gt;The adjective&#xA;&lt;a href=&quot;https://www.merriam-webster.com/dictionary/electric&quot; rel=&quot;noreferrer&quot;&gt;electric&lt;/a&gt; refers to the current (a technical quantity), while &lt;a href=&quot;https://www.merriam-webster.com/dictionary/electronic&quot; rel=&quot;noreferrer&quot;&gt;electronic&lt;/a&gt;, especially if used in contrast, refers to the fermionic particle.&lt;/p&gt;&#xA;" OwnerUserId="5837" LastEditorUserId="5" LastEditDate="2022-09-15T12:38:14.927" LastActivityDate="2022-09-15T12:38:14.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9663" PostTypeId="2" ParentId="9659" CreationDate="2022-09-15T12:31:19.870" Score="4" Body="&lt;p&gt;The excerpt that you gave us defines a steady state as one in which the state is not changing (&lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}\rho}{\textrm{d}t} = 0$&lt;/span&gt;) and a transient state in which the state is changing (&lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}\rho}{\textrm{d}t} \ne 0$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;This makes sense because before the word &amp;quot;transient&amp;quot; was used in this scientific context, it was a word used in the English language meaning &amp;quot;unsteady&amp;quot; or &amp;quot;changing&amp;quot;. The word has been used in one form or another &lt;a href=&quot;https://www.oxfordlearnersdictionaries.com/definition/english/transient_2&quot; rel=&quot;nofollow noreferrer&quot;&gt;since the late 16th century&lt;/a&gt;, with its roots coming from the Latin-based prefix &amp;quot;&lt;em&gt;trans&lt;/em&gt;&amp;quot;  which means to go across or switch (in this case the state is switching its form over time).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-09-15T12:31:19.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9664" PostTypeId="1" CreationDate="2022-09-15T12:50:12.230" Score="3" ViewCount="190" Body="&lt;p&gt;I want to understand how the current (or electron) is normally transported in a device like a graphene,  under the Transiesta code. It is based on which principle: a gate is applied, or there is a difference in potential between two electrodes is applied?&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2022-09-15T13:34:45.933" LastActivityDate="2022-10-14T15:33:50.670" Title="Quantum transport in device (Transiesta code)" Tags="|density-functional-theory|quantum-espresso|siesta|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9665" PostTypeId="1" CreationDate="2022-09-15T13:35:42.320" Score="3" ViewCount="74" Body="&lt;p&gt;What is the difference between this figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NzIVN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NzIVN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and this figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yNFVN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yNFVN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2022-09-15T13:43:44.773" LastActivityDate="2022-09-15T13:43:44.773" Title="Current curve (Transiesta code)" Tags="|density-functional-theory|siesta|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9666" PostTypeId="2" ParentId="9660" CreationDate="2022-09-15T17:30:56.040" Score="9" Body="&lt;p&gt;Electric conductivity can be created by particles other than electrons (like ions in solution), or by electrons moving in some more sophisticated way than straightforward (hole conductivity in semiconductors). Electronic conductivity is a conductivity created by electrons and can be compared with other kinds of conductivity.&lt;/p&gt;&#xA;" OwnerUserId="5982" LastActivityDate="2022-09-15T17:30:56.040" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9667" PostTypeId="1" AcceptedAnswerId="9668" CreationDate="2022-09-15T20:12:22.190" Score="3" ViewCount="120" Body="&lt;p&gt;Hi I'm trying to optimise a molecule by using the b3lyp/6-31G(d) method , the calculus took more than 2 days and the energy never converged .&lt;/p&gt;&#xA;&lt;p&gt;Here is my input code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=S-21.chk&#xA;&#xA;# opt freq  B3LYP/6-31G*  SCRF=(PCM,read,solvent=CH2Cl2)&#xA;&#xA;S-21&#xA;&#xA;0 1&#xA; C                 -1.75068100    0.37734700    0.81263500&#xA; C                 -2.62257500   -0.29227700   -0.14373800&#xA; C                 -4.10723100   -0.09641000   -0.01731400&#xA; C                 -4.61852400    0.73486000    1.04941400&#xA; C                 -3.74681500    1.31785500    1.90876500&#xA; C                 -2.31430800    1.13987700    1.79050600&#xA; H                 -5.69934800    0.85871100    1.11964000&#xA; H                 -4.10201200    1.94778900    2.72638200&#xA; H                 -1.68650000    1.64617500    2.52642700&#xA; N                 -4.80498300   -0.74379100   -0.93998600&#xA; N                 -2.28519800   -1.08000700   -1.15378200&#xA; S                 -3.70847600   -1.57391000   -1.94372300&#xA; C                 -0.28701900    0.19538500    0.70641300&#xA; C                  0.55775500    1.19398300    0.34091700&#xA; C                  0.21097700   -1.14867100    0.99271500&#xA; C                  2.05755400    0.97694800    0.39853600&#xA; C                  1.50838800   -1.47640300    0.80224900&#xA; H                 -0.52454700   -1.88180100    1.32139800&#xA; C                  2.47232700   -0.47418800    0.32746700&#xA; C                  0.10593100    2.52300100   -0.07746100&#xA; C                  0.93014100    3.38020900   -0.71164500&#xA; C                  2.31062000    3.02195300   -1.00934000&#xA; C                  2.84013300    1.86879500   -0.54543500&#xA; H                 -0.93897900    2.77149900    0.10783000&#xA; H                  0.59157200    4.36097200   -1.04420600&#xA; H                  2.87715100    3.70674700   -1.63618300&#xA; H                  2.36087800    1.32019000    1.44439100&#xA; C                  4.20468100    1.44278400   -0.87492700&#xA; C                  4.61668300    0.17803800   -0.66911800&#xA; C                  3.71092200   -0.82964300   -0.11389200&#xA; H                  4.85713200    2.19281800   -1.32106100&#xA; H                  5.62508700   -0.14589500   -0.92529400&#xA; C                  4.14879800   -2.22396900   -0.04913700&#xA; C                  1.99749300   -2.88270200    1.03166300&#xA; C                  3.36272400   -3.17101600    0.48626400&#xA; H                  5.13572700   -2.45364800   -0.44739700&#xA; H                  1.27197900   -3.60363700    0.58826800&#xA; H                  1.99321400   -3.09445600    2.12663400&#xA; H                  3.67769000   -4.21084800    0.55589600&#xA;&#xA; radii=UAKS&#xA;&#xA;                                                                                     &#xA;&#xA;                                                  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the errors that I got&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error termination request processed by link 9999.&#xA; Error termination via Lnk1e&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Information about geom opt convergence&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Item               Value     Threshold  Converged?&#xA; Maximum Force            0.043390     0.000450     NO &#xA; RMS     Force            0.003584     0.000300     NO &#xA; Maximum Displacement     0.044852     0.001800     NO &#xA; RMS     Displacement     0.004028     0.001200     NO &#xA;                                                     &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the output structure (the bond between C(16)-H(27) 16 got broken) I don't know how to fix these issues&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eN7JS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eN7JS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="7" LastEditDate="2022-09-15T23:54:23.513" LastActivityDate="2022-09-16T07:32:06.830" Title="Failure to converge geometry of ringed structure" Tags="|computational-chemistry|gaussian|geometry-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9668" PostTypeId="2" ParentId="9667" CreationDate="2022-09-16T07:32:06.830" Score="3" Body="&lt;p&gt;The bond breaking is expected, because the C-H bond is much weaker than an average C-H bond due to extensive hyperconjugative effects. The C-H bond thus elongates to such a degree that GaussView does not think the atoms are bonded anymore.&lt;/p&gt;&#xA;&lt;p&gt;The geometry non-convergence is likely an unrelated issue, probably due to some dihedral being too flexible. This may at least in part be due to that you forgot to add the dispersion correction (em=gd3bj). Without the dispersion correction, not only will some loose degrees of freedom (dihedrals, distances between non-covalently interacting atoms) be poorly described and lead to poor convergence, but also your results will be unreliable even if your calculation does converge. Thus, you may try adding the dispersion correction and continue the optimization, starting from the last geometry of your present job.&lt;/p&gt;&#xA;&lt;p&gt;Another thing that may or may not have a negative influence on the reliability of your results, is that you have a large and not that conventional conjugated system, which may be susceptible to self-interaction error. Using a functional with higher HF exchange (e.g. M06-2X, wB97XD) may put you on the safe side, but note that M06-2X tends to worsen the geometry convergence due to its potential energy surface being relatively non-smooth.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-09-16T07:32:06.830" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9670" PostTypeId="2" ParentId="9660" CreationDate="2022-09-16T09:08:22.093" Score="2" Body="&lt;p&gt;Electrical or electronic conductivity could refer to the device that is conducting.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Electrical devices have electrical conductivity.&lt;/li&gt;&#xA;&lt;li&gt;Electronic devices have electronic conductivity.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A good generic definition for electrical vs electronic devices cannot be given.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Traditionally, electrical devices are for handling electric power whereas electronic devices are for handling information/data. This definition is not holding up for, for example PV convertors or &lt;a href=&quot;https://en.wikipedia.org/wiki/Switched-mode_power_supply&quot; rel=&quot;nofollow noreferrer&quot;&gt;SMPS's&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Electrical devices are mostly mechanical. For example: wire, switches, and relays.&#xA;Electronic devices are made of semiconductors.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5986" LastActivityDate="2022-09-16T09:08:22.093" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9671" PostTypeId="2" ParentId="9659" CreationDate="2022-09-16T09:50:20.353" Score="3" Body="&lt;p&gt;Transient state can be defined as a state in which &lt;span class=&quot;math-container&quot;&gt;$\frac{\text{d} \rho}{\text{dt}} \neq 0$&lt;/span&gt;, which, in an Ising Model MCMC (or any step-based) simulation, could be translated to &lt;span class=&quot;math-container&quot;&gt;$\frac{\text{d} M}{\text{dt}} \neq 0$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; the magnetization of the system.&lt;/p&gt;&#xA;&lt;p&gt;In a simulation, fluctuations are going to be happening inevitably. The non-transient states are the ones where the system has converged to a steady state.&lt;/p&gt;&#xA;" OwnerUserId="5987" LastEditorUserId="5" LastEditDate="2022-09-16T12:29:41.183" LastActivityDate="2022-09-16T12:29:41.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9672" PostTypeId="1" CreationDate="2022-09-16T15:25:13.220" Score="2" ViewCount="617" Body="&lt;p&gt;Cross-posted on &lt;a href=&quot;https://chemistry.stackexchange.com/q/167872/27342&quot;&gt;Chemistry.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to make pdbqt files from pdb files for Docking with Autodock vina but getting errors while running the &lt;a href=&quot;https://github.com/sahrendt0/Scripts/blob/master/docking_scripts/prepare_receptor4.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;prepare_receptor4.py&lt;/a&gt; script present in the &lt;a href=&quot;https://www.scripps.edu/sanner/python/documentation/installationInstruction-binary-1-3alpha2.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;mgltools&lt;/a&gt; directory. The script converts pdb to pdbqt.&lt;/p&gt;&#xA;&lt;p&gt;Usage&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;prepare_receptor4.py -r input.pdb -o output.pdbqt &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;input.pdb&lt;/code&gt; is the input pdb file, &lt;code&gt;output.pdbqt&lt;/code&gt; is the output pdbqt file&lt;/p&gt;&#xA;&lt;p&gt;I got the errors with &lt;a href=&quot;https://www.rcsb.org/structure/7RTT&quot; rel=&quot;nofollow noreferrer&quot;&gt;7RTT.pdb&lt;/a&gt; and &lt;a href=&quot;https://www.rcsb.org/structure/7WDA&quot; rel=&quot;nofollow noreferrer&quot;&gt;7WDA.pdb&lt;/a&gt; input files.&lt;/p&gt;&#xA;&lt;p&gt;What are these errors and how can I resolve them? Any help will be highly appreciated.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/Utilities24/prepare_receptor4.py&amp;quot;, line 204, in &amp;lt;module&amp;gt;&#xA;    dict=dictionary)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 558, in __init__&#xA;    version=version, delete_single_nonstd_residues=delete_single_nonstd_residues)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 141, in __init__&#xA;    self.addCharges(mol, charges_to_add)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 227, in addCharges&#xA;    chargeCalculator.addCharges(mol.allAtoms)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/MolKit/chargeCalculator.py&amp;quot;, line 80, in addCharges&#xA;    babel.assignHybridization(atoms)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/PyBabel/atomTypes.py&amp;quot;, line 143, in assignHybridization&#xA;    self.check_for_amides()&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/PyBabel/atomTypes.py&amp;quot;, line 511, in check_for_amides&#xA;    if conn.babel_type==&amp;quot;Cac&amp;quot; or conn.babel_type==&amp;quot;Sox&amp;quot; or \&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/MolKit/molecule.py&amp;quot;, line 409, in __getattr__&#xA;    raise AttributeError('member %s not found'%member)&#xA;AttributeError: member babel_type not found&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/Utilities24/prepare_receptor4.py&amp;quot;, line 204, in &amp;lt;module&amp;gt;&#xA;    dict=dictionary)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 558, in __init__&#xA;    version=version, delete_single_nonstd_residues=delete_single_nonstd_residues)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 141, in __init__&#xA;    self.addCharges(mol, charges_to_add)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/AutoDockTools/MoleculePreparation.py&amp;quot;, line 227, in addCharges&#xA;    chargeCalculator.addCharges(mol.allAtoms)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/MolKit/chargeCalculator.py&amp;quot;, line 80, in addCharges&#xA;    babel.assignHybridization(atoms)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/PyBabel/atomTypes.py&amp;quot;, line 127, in assignHybridization&#xA;    a.babel_atomic_number = self.get_atomic_number(a.babel_type)&#xA;  File &amp;quot;/mnt/d/Download/mgltools/MGLToolsPckgs/PyBabel/atomTypes.py&amp;quot;, line 103, in get_atomic_number&#xA;    (name,_name) )&#xA;ValueError: Could not find atomic number for A A&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5990" LastEditorUserId="5" LastEditDate="2022-09-19T14:53:27.370" LastActivityDate="2022-09-19T14:53:27.370" Title="Autodock prepare_receptor4.py script gives error while converting pdb files to pdbqt files" Tags="|software-assistance|docking|from-chem-se|openbabel|autodock|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-10T00:22:21.207" ContentLicense="CC BY-SA 4.0" />
  <row Id="9673" PostTypeId="2" ParentId="9587" CreationDate="2022-09-17T06:26:19.193" Score="3" Body="&lt;p&gt;The Ewald (or usually the faster particle-mesh Ewald or PME) treatment of long-range nonbonded forces seems to be standard in molecular dynamics of proteins.  Typically the protein is surrounded by a &amp;quot;water box&amp;quot; (padding the protein by a certain amount, enough that it doesn't end up too close to an image of itself) and the system simulated consists of an infinite periodic grid of exact copies of this protein+waterbox. Note that typically there is no gap between copies - the water going from one copy to the next image over is continuous.&lt;/p&gt;&#xA;&lt;p&gt;How realistic this is - that's a good question!  I think the feeling of most people working in this field is that avoiding any weird effects at the edges of the system (eg very strong preference for water molecules to orient so there are no loose hydrogen bonds at the edge) is probably more important than the interaction between images.  How to give a water box or water droplet an edge that behaves as though there is more water next to it, without making it periodic, seems to be an unsolved problem.&lt;/p&gt;&#xA;&lt;p&gt;There is an alternative treatment called &amp;quot;reaction field&amp;quot; (RF) - this assumes everything outside a certain cutoff distance is a uniform polarizable dielectric (typically the cutoff needs to be a bit longer than for PME, around 2nm).  It seems RF is considered less accurate than PME, and it may be (much) slower with long cutoffs as well.  Note that a non-periodic water box with RF still has an edge issue - from the perspective of a water molecule at the edge, everything outside the box from distance zero to the cutoff is vacuum; only further than the cutoff it becomes the uniform dielectric.&lt;/p&gt;&#xA;&lt;p&gt;In other words: Ewald or PME solves two issues simultaneously, a fast calculation of long range interactions and a water box with edges that behave as though they’re facing bulk water; at the cost of introducing non-physical interactions between images. The first of these could be solved in other ways, the second doesn’t really have a good alternative.&lt;/p&gt;&#xA;&lt;p&gt;A couple of links to the documentation of various simulation packages:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://docs.openmm.org/latest/userguide/theory/02_standard_forces.html?highlight=reaction#coulomb-interaction-with-cutoff&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenMM manual&lt;/a&gt; - &amp;quot;18.6.3. Coulomb Interaction With Cutoff&amp;quot; describes reaction field&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ambermd.org/doc12/Amber22.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Amber manual&lt;/a&gt; - look at &amp;quot;20.7.2. Particle Mesh Ewald&amp;quot; and &amp;quot;20.7.3. Using IPS for the calculation of nonbonded interactions&amp;quot; for an alternative - as far as I can tell, it is possible to turn off PME is Amber, but not to replace it with RF - PME-off just means vacuum.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2022-09-18T12:16:41.880" LastActivityDate="2022-09-18T12:16:41.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9674" PostTypeId="1" AcceptedAnswerId="9683" CreationDate="2022-09-17T08:12:01.543" Score="7" ViewCount="189" Body="&lt;p&gt;Which equation makes it possible to calculate the forces of attraction between a surface and molecules? Is there any free software that implements such a calculation?&lt;/p&gt;&#xA;&lt;p&gt;[Clarification 1] Between a surface and molecules there is no chemical reaction, no absorption, adsorption may be but unlikely.&lt;/p&gt;&#xA;&lt;p&gt;[Clarification 2] Between a surface and molecules of another substance I expect something like &lt;em&gt;adhesion&lt;/em&gt;. Such a property is possessed by, for example, &lt;em&gt;honey&lt;/em&gt;, &lt;em&gt;clay&lt;/em&gt;, &lt;em&gt;glue&lt;/em&gt; as well. Undoubtedly some substances may be corrosive in interaction with the surface, but I expect that their being corrosive will be very weakly and appears in a very long time. Thus, I guess, corrosivity can be neglected if to consider not so long time intervals. I suppose that this aspect will allow to simplify a model of this interaction. Another question is how big is a contribution of this aspect into a general force fond? An interesting question is as well how big is a contribution of hydrogen bonds if any?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5403" LastEditDate="2022-09-25T12:35:13.573" LastActivityDate="2022-09-25T12:35:13.573" Title="Which equation makes it possible to calculate the forces of attraction between a surface and molecules?" Tags="|molecular-dynamics|software|intermolecular-forces|molecular-interactions|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9675" PostTypeId="1" AcceptedAnswerId="9676" CreationDate="2022-09-17T08:59:02.233" Score="6" ViewCount="771" Body="&lt;p&gt;What I understand is that the only difference between the Ising and Potts models is that Ising has two types of spins, and Potts has &lt;em&gt;n&lt;/em&gt; types of spins.&lt;/p&gt;&#xA;&lt;p&gt;However, I am wondering if the Hamiltonian (energy formula) is the same or different.&lt;/p&gt;&#xA;&lt;p&gt;Are the Hamiltonianas the same or different?&lt;/p&gt;&#xA;&lt;p&gt;What other differences do they have?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-09-18T17:33:50.317" Title="What is the fundamental difference between the Ising and Potts models?" Tags="|ising-model|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9676" PostTypeId="2" ParentId="9675" CreationDate="2022-09-17T15:24:15.187" Score="7" Body="&lt;p&gt;Fundamentally, there is not much of a difference. A Potts model is a kind of generalized Ising model that includes more spin states. The Hamiltonians can be written with similar forms.&lt;/p&gt;&#xA;&lt;p&gt;The Ising model can be written as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H(\vec\sigma) = -\sum_{\langle i,j\rangle} J_{i,j}\sigma_i \sigma_j -\mu \sum_i \sigma_i,\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\langle i,j \rangle$&lt;/span&gt; denotes nearest neighbor pairs, and &lt;span class=&quot;math-container&quot;&gt;$\sigma_i \in \{-1, +1\}$&lt;/span&gt; are the lattice spin states. &lt;span class=&quot;math-container&quot;&gt;$J_{i,j}$&lt;/span&gt; is a  nearest neighbor interaction energy that can be spin-pair dependent, and &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is an on-site energy term. Alternatively, if you use spin values of &lt;span class=&quot;math-container&quot;&gt;$\sigma_i \in \{0, 1\}$&lt;/span&gt; we call this a lattice gas model. The model parameters can be updated to give equivalent results with either choice of spin states.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt;-state Potts model can be written similarly:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H(\vec\sigma) = -\sum_{\langle i,j\rangle} J_{i,j}\delta_{\sigma_i,\sigma_j} - \sum_i \mu_i\sigma_i \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\sigma_i \in \{0, 1, 2, \dots, Q\}$&lt;/span&gt; are the &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; spin states and &lt;span class=&quot;math-container&quot;&gt;$\delta_{\sigma_i,\sigma_j}$&lt;/span&gt; is the Kronecker delta.&lt;/p&gt;&#xA;&lt;p&gt;There are also other extensions of the Ising model that include more than just nearest neighbor and on-site interactions. In my opinion, the most general model (often found in alloy modeling literature) is referred to as the “cluster expansion”. This model accounts for many-body interactions in the system and can be expressed as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H(\vec\sigma) = J_0 + \sum_i J_i \sigma_i + \sum_{i,j} J_{i,j}\sigma_i \sigma_j + \sum_{i,j,k} J_{i,j,k}\sigma_i\sigma_j\sigma_k + \dots \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Unlike the Ising model and Potts model shown above, the sums are not restricted to nearest neighbors, but run over all possible pairs, triplets, quadruplets, etc. of sites in the spin lattice. &lt;a href=&quot;https://doi.org/10.1016/0378-4371(84)90096-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;Sanchez, Ducastelle, and Gratias&lt;/a&gt; have shown that, provided an orthonormal set of spin functions (such as discrete Chebyshev polynomials), one can construct a complete and orthonormal basis set of cluster functions (products of spin functions), that can provide a formally exact description of the energy of a spin-lattice system. Because the cluster expansion is infinite in nature, it must be truncated for practical work. Clearly, the Ising model is a special case of the more general cluster expansion.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-09-18T17:33:50.317" LastActivityDate="2022-09-18T17:33:50.317" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9677" PostTypeId="2" ParentId="9674" CreationDate="2022-09-17T19:15:53.383" Score="6" Body="&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Schr%C3%B6dinger_equation&quot; rel=&quot;noreferrer&quot;&gt;Schrödinger&lt;/a&gt; (or relativistic &lt;a href=&quot;https://en.wikipedia.org/wiki/Dirac_equation&quot; rel=&quot;noreferrer&quot;&gt;Dirac&lt;/a&gt;) equation is what essentially determine the interaction, and there are many free and open source programs that can perform such calculations; a recent listing can be found in &lt;a href=&quot;https://doi.org/10.1002/wcms.1610&quot; rel=&quot;noreferrer&quot;&gt;our open access WIREs CMS paper&lt;/a&gt;. Since you are dealing with gas phase, atomic-orbital approaches will be likely most cost efficient for this as periodicity will only have to be included in the two slab directions.&lt;/p&gt;&#xA;&lt;p&gt;However, running such calculations can be quite costly and requires much expertise to be able to set up the calculation properly. One needs to not only choose the right quantum chemical model (e.g. density functional), but also converge the many parameters of the calculation (e.g. basis set, slab depth, k point sampling, etc).&lt;/p&gt;&#xA;&lt;p&gt;Depending on the calculation, force field methods may be a more suitable approach, as they tend to be somewhat easier to use and much faster to run calculations with. For instance, the &lt;a href=&quot;https://www.lammps.org/&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt; code might have suitable force fields for such calculations; however, if no suitable force fields exist, one may still have to resort to electronic structure methods.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-09-17T19:15:53.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9678" PostTypeId="1" AcceptedAnswerId="9679" CreationDate="2022-09-18T04:23:20.853" Score="5" ViewCount="943" Body="&lt;p&gt;I need to use a diffuse basis set for my highly delocalised molecule, consisting of C, N, O, Cl, S, Mg, Al, B and Si only, since it has many non-covalent interactions inside it. After reading some more papers, regarding its predictable properties(sorry, but there are things called personal research secrets. They are irrelevant to the core of this question anyway), I decided that 6-311++G(3df,3pd) and def2-TZVPPD are the only choices I could use.&lt;/p&gt;&#xA;&lt;p&gt;However, neither basis set is truly completely diffuse- 6-311++G(3df,3pd) augments only with p &amp;amp; d functions, while def2-TZVPPD does it only with s &amp;amp; d functions. Checked the BSSE website- same there.&lt;/p&gt;&#xA;&lt;p&gt;What I need to know right now are the IP, EA, band gap and dipole moment- which basis set of the two should I use for these properties?&lt;/p&gt;&#xA;&lt;p&gt;P.S. the functional I'll be using is M11-L.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-09-18T04:29:08.153" LastActivityDate="2022-09-18T10:34:08.287" Title="Choosing between 6-311++G(3df,3pd) and def2-TZVPPD for certain type of diffuse system" Tags="|basis-sets|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9679" PostTypeId="2" ParentId="9678" CreationDate="2022-09-18T10:34:08.287" Score="8" Body="&lt;p&gt;Do not use Pople basis sets.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;They are not systematical, as evidenced by the plethora of possible augmentations&lt;/li&gt;&#xA;&lt;li&gt;They are only available for a small fraction of the periodic table (the first 3 periods)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1063/1.457301&quot; rel=&quot;noreferrer&quot;&gt;6-311G in specific is not a triple zeta basis set&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/ja0630285&quot; rel=&quot;noreferrer&quot;&gt;The augmented basis sets lead to qualitatively wrong geometries&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Instead, use systematic basis set families. Good choices include&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the Karlsruhe def2 basis sets, available for most of the periodic table, suitable for both Hartree-Fock / density functional theory as well as post-Hartree-Fock calculations (when augmented with the second set of polarization functions)&lt;/li&gt;&#xA;&lt;li&gt;for post-Hartree-Fock calculations, Dunning's correlation consistent family (cc-pVXZ)&lt;/li&gt;&#xA;&lt;li&gt;for density functional calculations, Jensen's polarization consistent family (pc-n or pcseg-n)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;These modern basis set families come in systematic sequences of levels of accuracy, ranging from split-valence (def2 and pc families) or valence polarized double zeta (cc family) to fully converged (polarized quadruple-zeta for def2, quintuple-zeta for pc-n, hextuple-zeta for cc family).&lt;/p&gt;&#xA;&lt;p&gt;Accordingly, you should be able to converge whatever property you are interested in to the basis set limit, and then trace back what basis set is the smallest to give you a value that is close enough.&lt;/p&gt;&#xA;&lt;p&gt;Note also that &lt;a href=&quot;https://doi.org/10.1021/ct400660j&quot; rel=&quot;noreferrer&quot;&gt;M11-L is a pathological functional&lt;/a&gt; and as a semilocal functional lacks the ability to describe long-range dispersion. &lt;a href=&quot;https://doi.org/10.1080/00268976.2017.1333644&quot; rel=&quot;noreferrer&quot;&gt;A recent review&lt;/a&gt; should be of help to pick a suitable functional and basis set combination.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-09-18T10:34:08.287" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9681" PostTypeId="1" AcceptedAnswerId="9682" CreationDate="2022-09-19T01:56:03.580" Score="5" ViewCount="295" Body="&lt;p&gt;The cc-, pc- and def2- basis sets are often described as &amp;quot;systematic&amp;quot;, in the sense that the results of these basis sets at different cardinal numbers (i.e. the number of ζ's) can be extrapolated, by a closed-form equation involving the cardinal number, to the CBS limit.&lt;/p&gt;&#xA;&lt;p&gt;However, as a mathematics student, I began to wonder if these equations are mathematically exact. Of course, an exact CI is computationally prohibitively expensive, and an exact DFT is not even known in closed form, but the least of mathematical rigour is important to the minds of those who study mathematics.&lt;/p&gt;&#xA;&lt;p&gt;My question is now clear: Assuming exact CI/DFT, can the sequences of the results of an ever increasing cardinal number of the cc/pc/def2 basis sets mathematically shown to converge exactly to the CBS limit, according to the &amp;quot;CBS extrapolation equations&amp;quot; known in the literature?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="5" LastEditDate="2022-09-19T03:01:44.793" LastActivityDate="2022-09-23T13:56:38.210" Title="Do the cc/pc/def2 basis sets mathematically converge to the CBS limit, assuming exact CI/DFT?" Tags="|mathematical-modeling|basis-sets|convergence-test|basis-set-superposition-error|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9682" PostTypeId="2" ParentId="9681" CreationDate="2022-09-19T02:40:39.790" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Assuming exact CI/DFT, can the sequences of the results of an ever increasing cardinal number of the cc/pc/def2 basis sets mathematically shown to converge exactly to the CBS limit, according to the &amp;quot;CBS extrapolation equations&amp;quot; known in the literature?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Given an &lt;span class=&quot;math-container&quot;&gt;$\epsilon &amp;gt; 0$&lt;/span&gt;, there exists an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; such that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;|E_{\textrm{cc-pVNZ}} - E_{\textrm{Exact}}| &amp;lt;\epsilon.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;So by the definition of convergence, it does converge.&lt;/p&gt;&#xA;&lt;p&gt;This also means that pretty much any sensible function that you fit to the &lt;span class=&quot;math-container&quot;&gt;$E_{\textrm{cc-pVNZ}}$&lt;/span&gt; sequence will give you an extrapolated energy that is within &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; of &lt;span class=&quot;math-container&quot;&gt;$E_{\textrm{Exact}}$&lt;/span&gt;&#xA;&lt;em&gt;&lt;strong&gt;provided that &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is large enough to satisfy Eq. (1).&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, if your &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is (for example) 1 micro-Hartree, the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; required will be huge, &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;nofollow noreferrer&quot;&gt;even for a single atom&lt;/a&gt;. I have done calculations with &lt;span class=&quot;math-container&quot;&gt;$N=10$&lt;/span&gt; for triatomic molecules but beyond that it would be extremely impractical even to do the 2-electron integrals with currently existing software and hardware, so you won't likely be seeing CISD done with &lt;span class=&quot;math-container&quot;&gt;$N&amp;gt;10$&lt;/span&gt; for more than 3 atoms, and for most molecules of interest you won't even be seeing &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; go past 4.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I began to wonder if these equations are mathematically exact.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is large enough, almost any sensible &amp;quot;equation&amp;quot; will get you within &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; of the exact energy. If you are asking whether or not the equations are &amp;quot;exact&amp;quot; in the sense that they will help you extrapolate correctly to the CBS limit &lt;em&gt;&lt;strong&gt;for any chosen value of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;&lt;/strong&gt;&lt;/em&gt; then the answer is no. People can't even agree on which formula to use! The notion that we typically see in the literature, that the extrapolation formula should involve &lt;span class=&quot;math-container&quot;&gt;$1/N^3$&lt;/span&gt; comes from studies of the helium atom, where some mathematics is actually possible, but then these formulas are reused for modeling the rest of the universe (with some authors choosing to make minor tweaks, such as making &lt;span class=&quot;math-container&quot;&gt;$N=3.5$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$N=4$&lt;/span&gt;; see my linked paper above for examples).&lt;/p&gt;&#xA;&lt;p&gt;These formulas are far from being &amp;quot;exact&amp;quot; in terms of being able to predict &amp;quot;exact&amp;quot; energies for some fixed value of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;. However they work &lt;em&gt;&lt;strong&gt;extremely&lt;/strong&gt;&lt;/em&gt; well, in that using these formulas with calculations that take a few seconds (for example &lt;span class=&quot;math-container&quot;&gt;$N=3$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$N=4$&lt;/span&gt;) can give extrapolated energies that are &lt;em&gt;&lt;strong&gt;better&lt;/strong&gt;&lt;/em&gt; than what you'd get from calculations that take days (for example with &lt;span class=&quot;math-container&quot;&gt;$N=9$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;One final remark, the &amp;quot;exactness&amp;quot; of the CI is not so important. Based on what you're saying about &amp;quot;exact CI&amp;quot; being prohibitively expensive, you mean &amp;quot;full CI&amp;quot; not &amp;quot;exact CI&amp;quot;, and whether its full CI or CISD doesn't matter for what I wrote above. Given a large enough &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, the finite-basis-set CISD energies will converge to the CBS limit of the CISD energy, and likewise for CISDT, CISDTQ, ..., FCI.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-09-19T03:52:06.263" LastActivityDate="2022-09-19T03:52:06.263" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="9683" PostTypeId="2" ParentId="9674" CreationDate="2022-09-19T04:09:15.610" Score="7" Body="&lt;p&gt;The long-range (non-chemical) interaction between a neutral molecule and a surface is dominated by van der Waals interactions. The simplest model you could use for this is a Lennard-Jones potential, which captures the approximate long-range &lt;span class=&quot;math-container&quot;&gt;$R^{-6}$&lt;/span&gt; dependence of the attractive potential. This is an approximation, of course, that tries to model the effective attraction between fluctuating electrical multipoles.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.pnas.org/doi/pdf/10.1073/pnas.1118245108&quot; rel=&quot;noreferrer&quot;&gt;As summarized by Tao, Perdew, and Ruzsinszky&lt;/a&gt;, the van der Waals energy can be written as series expansion&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{vdw} = -\frac{C_6}{R^6} -\frac{C_8}{ R^8} - \frac{C_{10}}{R^{10}} - \dots \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where “&lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; describes the instantaneous dipole-dipole interaction, &lt;span class=&quot;math-container&quot;&gt;$C_8$&lt;/span&gt; describes the dipole-quadrupole interaction, and &lt;span class=&quot;math-container&quot;&gt;$C_{10}$&lt;/span&gt; describes the quadrupole-quadrupole and dipole-octupole interactions.” For many applications, the leading &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; term is often considered to be sufficient and many models stick with this. The higher order &lt;span class=&quot;math-container&quot;&gt;$C_8$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_{10}$&lt;/span&gt; can be important, but they’re much harder to compute and can’t be directly measured so they are somewhat scarce in the literature. Many of the density functional approximations that are designed to accurately reproduce van der Waals interactions incorporate &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; in some way or another. This is especially prominent in Grimme’s DFT-D methods, for example.&lt;/p&gt;&#xA;&lt;p&gt;Most planewave DFT codes implement VDW functionals, so you could use something like Quantum ESPRESSO, CP2K (this actually uses the GPW method), or VASP (if you have a license) to compute these interactions. Alternatively, if you have validated force field parameters and want to study larger numbers of molecules interacting with a surface, you can use an MD code like LAMMPS or GROMACS to run classical simulations.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-09-19T04:20:57.813" LastActivityDate="2022-09-19T04:20:57.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9684" PostTypeId="1" AcceptedAnswerId="9686" CreationDate="2022-09-19T09:58:04.227" Score="5" ViewCount="155" Body="&lt;p&gt;It is often said that the optical band gap, i.e. the first excitation energy, of a species is exactly equal to the difference between the (Kohn-Sham) HOMO and LUMO. This would mean that the state of the wavefunction corresponding to the density constructed by summing a set of filled K-S orbitals, except for the &amp;quot;original&amp;quot; HOMO, which is replaced by the &amp;quot;original&amp;quot; LUMO, is higher in energy (exactly by the optical band gap) than the ground state.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- does this fact actually hold, assuming exact DFT functional- if it does, can it be generalised to (the cases where the orbitals being &amp;quot;swapped&amp;quot; before summation are not necessarily the HOMO/LUMO, just a filled K-S orbital and an unfilled K-S orbital), and/or to the cases where two filled orbitals are swapped with two unfilled orbitals(etc)?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-09-20T00:27:40.267" LastActivityDate="2022-09-20T03:41:53.710" Title="Question on generalised Kohn-Sham &quot;band gap&quot;" Tags="|density-functional-theory|kohn-sham|excited-states|bandgap|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9685" PostTypeId="1" CreationDate="2022-09-19T02:30:22.997" Score="3" ViewCount="50" Body="&lt;p&gt;I am able to &lt;a href=&quot;https://gaussian.com/cubegen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;generate cube&lt;/a&gt; file with (-3) medium resolution. But the map is cutoff at &amp;lt; -7.71 or &amp;gt;7.71.  To extend the cube coverage, I tried to set 120 points per side, but output cubefile has min and max remains  at -7.71 and 7.71, because resolution is higher than medium.&lt;/p&gt;&#xA;&lt;p&gt;It looks like the program also can read the cube specification from the input stream or from a second cube file. So I tried to type in numbers based the four line format, it gives error.&lt;/p&gt;&#xA;&lt;p&gt;Any step-by-step codes would be great help!&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;cubegen 8 fdensity=mp2 Ar.fchk Ar.cube 120&lt;/strong&gt;         min and max coordinates in cube file did not extend...&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;cubegen 8 fdensity=mp2 Ar.fchk Ar.cube -1&lt;/strong&gt;          hit enter, prompt for input, then I typed in:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   1   -10.00000   -10.00000   -10.00000&#xA; 120    0.166667    0.000000    0.000000&#xA; 120    0.000000    0.166667    0.000000&#xA; 120    0.000000    0.000000    0.166667&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;no cube file generated.&lt;/p&gt;&#xA;" OwnerDisplayName="cocoslover" LastEditorUserId="5" LastEditDate="2022-09-19T21:21:56.780" LastActivityDate="2022-09-19T21:21:56.780" Title="How to extend the sides of cube file in cubegen along with medium resolution?" Tags="|density-functional-theory|from-chem-se|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-14T01:09:59.650" ContentLicense="CC BY-SA 4.0" />
  <row Id="9686" PostTypeId="2" ParentId="9684" CreationDate="2022-09-19T21:40:22.570" Score="5" Body="&lt;p&gt;The optical band gap is not expected to equal the DFT band gap since excitonic effects are not included.&lt;/p&gt;&#xA;&lt;p&gt;What you are referring to is the fundamental gap. The fundamental gap is related to electron addition and removal energies, while the optical gap is lower than the fundamental gap due to the attraction between electrons and holes.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, if we focus your question to the fundamental gap, then I’m not sure if what you’re saying holds either. You can read some of the introductory material in &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/ct2009363&quot; rel=&quot;noreferrer&quot;&gt;this paper &lt;/a&gt;, especially the section “fundamental gaps from KS theory.”&lt;/p&gt;&#xA;&lt;p&gt;Briefly, they say that while the highest occupied orbital energy has a physical interpretation as the negative of the ionization potential, but there isn’t a corresponding expression for the lowest occupied molecular orbital that is rigorously true. They cite &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.51.1884&quot; rel=&quot;noreferrer&quot;&gt;another paper&lt;/a&gt; which argues that the exact exchange correlation functional would underestimate the fundamental gap similarly to how local or semi local approximations underestimate it. You might also be interested in &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.51.1888&quot; rel=&quot;noreferrer&quot;&gt;another paper that they cite&lt;/a&gt; which talks about related issues too.&lt;/p&gt;&#xA;&lt;p&gt;You can, however, compute the fundamental gap of a molecule by computing the total energy of the +1 and -1 version of the molecule you are considering and this procedure is rigorous in KS DFT.&lt;/p&gt;&#xA;&lt;p&gt;One method that has been proposed to calculate the fundamental gap from a difference of molecular orbital energies is described in this paper: a generalized Kohn-Sham system (which refers to one with Fock exchange included) can restore the derivative discontinuity that is missing in KS DFT.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastEditorUserId="5770" LastEditDate="2022-09-20T03:41:53.710" LastActivityDate="2022-09-20T03:41:53.710" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9688" PostTypeId="1" AcceptedAnswerId="9691" CreationDate="2022-09-21T07:02:23.437" Score="6" ViewCount="213" Body="&lt;p&gt;In &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9686/4231&quot;&gt;an answer&lt;/a&gt; to my question regarding the theoretical rigour in computing excitation energies using only the Kohn-Sham orbital energies, the rigour turned out to be nonexistent.&lt;/p&gt;&#xA;&lt;p&gt;After looking this matter up, I began to wonder if the exact excitation energies (whose definition is explicitly written in my question, whose answer is linked above, and shall not be re-stated here) could be written in closed form using the relevent K-S orbital energies AND the exact XC functional, for example as the sum of a constant times the K-S &amp;quot;band gap&amp;quot; plus another constant times the derivative of the exact XC applied to the exact density(rough guess and potentially true, potentially false example to express the spirit I'm having here)&lt;/p&gt;&#xA;&lt;p&gt;Does such a closed-form expression, ignoring facts like how &amp;quot;the exact XC functional is currently unknown&amp;quot;, exist at least in theory?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-09-21T07:07:24.530" LastActivityDate="2022-09-21T21:33:16.703" Title="Closed-form expression for excitation energies, given the exact XC functional" Tags="|density-functional-theory|orbitals|kohn-sham|excited-states|exchange-correlation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9689" PostTypeId="1" CreationDate="2022-09-21T07:59:12.893" Score="4" ViewCount="74" Body="&lt;p&gt;According to an answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9684/4231&quot;&gt;my question&lt;/a&gt; on whether the Kohn-Sham orbital energies theoretically exactly capture arbitrary ionisation potentials and/or excitation energies, the answer is no for both questions &amp;quot;due to the neglect of attractions between electrons and holes in K-S theory&amp;quot;- a reason I could not grasp.&lt;/p&gt;&#xA;&lt;p&gt;I then looked the Kohn-Sham equations up on Wikipedia and found a concept called &amp;quot;Dyson orbitals&amp;quot; that are mathematically constructed purely from the N-electron wavefunction and the N+-1-electron wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Since both of these are pure quantum chemical entities, a set of Dyson orbitals constructed from ground-state N-electron wavefunction(s) and ground-state N+-1-electron wavefunction(s), packed with their energies, should capture the exact energies of &amp;quot;everything&amp;quot;- from the arbitrary ionisation potentials and electron affinities (defined by the energy difference of the ground state and arbitarily ionised states) to excitation energies of arbitrary excited states.&lt;/p&gt;&#xA;&lt;p&gt;Is this correct? (I'm asking this question because I found a couple of open-source papers on Dyson orbitals, only to realise that I could not grasp it at all)&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-09-24T23:56:20.513" Title="Do the orbital energies of ground-state Dyson orbitals exactly capture arbitrary excitation energies and/or ionisation potentials/electron affinities?" Tags="|orbitals|excited-states|wavefunctions|bandgap|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-15T04:44:07.497" ContentLicense="CC BY-SA 4.0" />
  <row Id="9690" PostTypeId="2" ParentId="9688" CreationDate="2022-09-21T20:33:56.677" Score="6" Body="&lt;p&gt;No, they cannot be obtained from a DFT calculation. As the first paper I linked in the previous response says, DFT is a ground state theory, and it should not be expected to get excited state properties correct. For excited state properties you can use TDDFT, GW/BSE, and also wave function based methods that are common in quantum chemistry. You can even use these methods to rigorously get core level excitations (which is something that you alluded to in your previous question).&lt;/p&gt;&#xA;&lt;p&gt;These methods all can yield values that are meant to be compared with excited state properties, and TDDFT is formally exact in a similar sense that DFT is for ground state properties.&lt;/p&gt;&#xA;&lt;p&gt;You mentioned not having access to the journals. Here’s a pdf from one of the co-author’s website &lt;a href=&quot;http://vintage.fh.huji.ac.il/%7Eroib/Postscripts/JCTC_Perspectives%20-%20final.pdf&quot; rel=&quot;noreferrer&quot;&gt;http://vintage.fh.huji.ac.il/~roib/Postscripts/JCTC_Perspectives%20-%20final.pdf&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-09-21T20:33:56.677" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9691" PostTypeId="2" ParentId="9688" CreationDate="2022-09-21T21:33:16.703" Score="5" Body="&lt;p&gt;Do you consider the exact frequency-dependent XC kernel as part of &amp;quot;the exact XC functional&amp;quot;? And do you allow the use of additional ingredients like two-electron integrals?&lt;/p&gt;&#xA;&lt;p&gt;If both of your answers are &amp;quot;yes&amp;quot;, then you can construct the Casida equation with these ingredients, and you can solve it to get the excitation energies. However, in this case the equation to be solved is a non-linear eigenvalue problem, which in general must be solved iteratively. So in general there is no closed-form expression of excitation energies (indeed, even if the eigenvalue problem is linear, the eigenvalues are still in general not expressible in closed form as a function of the matrix elements). Of course, there is the theoretical possibility that the exact frequency-dependent XC kernel has some peculiar property that allows the eigenvalue problem to be solved in closed form, but if such property exists, it would likely have such a very deep physical reason, that someone has already discovered it. In practice, however, the reverse seems to be true.&lt;/p&gt;&#xA;&lt;p&gt;So, while mathematically we probably cannot rule out the possibility of a (possibly extremely convoluted) closed-form expression of excitation energies, like we probably can never rule out that &lt;span class=&quot;math-container&quot;&gt;$\pi+e$&lt;/span&gt; is a rational number, I hope that the above analysis will convince you that such a closed-form expression is extremely unlikely to exist.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-09-21T21:33:16.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9692" PostTypeId="1" AcceptedAnswerId="9696" CreationDate="2022-09-22T06:25:08.863" Score="3" ViewCount="295" Body="&lt;p&gt;It is often said that &amp;quot;while cobalt(III) per se is strongly oxidising, hexamminecobalt(III) chloride is stable, even in concentrated hydrochloric acid, due to the strong donor properties of the ammine ligands&amp;quot;. However, &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/General_Chemistry/Map%3A_General_Chemistry_(Petrucci_et_al.)/24%3A_Complex_Ions_and_Coordination_Compounds/24.10%3A_Some_Kinetic_Considerations&quot; rel=&quot;nofollow noreferrer&quot;&gt;according to LibreTexts&lt;/a&gt;, the cation is actually only kinetically stable in the presence of hydronium ions, eventually turning into hexaaquocobalt(III) (which is strongly oxidising) and ammonium ions in the thermodynamic limit.&lt;/p&gt;&#xA;&lt;p&gt;In pure water, the hydronium ion only exists in minute amounts, due to the high equilibrium constant of the generalised Comproportionation of hydronium and hydroxide to water. This might or might not counterbalance the high thermodynamic instability of the hexamminecobalt(III) ion against ligand exchange in acidic water.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- is the hexamminecobalt(III) cation thermodynamically stable in pure water?&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: All reaction conditions are assumed to be STP.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-09-22T13:37:15.397" LastActivityDate="2022-09-23T01:29:14.257" Title="Is hexaamminecobalt(III) chloride thermodynamically stable in pure water?" Tags="|thermodynamics|water|metal-complexes|coordination|redox|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9694" PostTypeId="1" CreationDate="2022-09-22T13:51:17.810" Score="3" ViewCount="43" Body="&lt;p&gt;I'm working on a Machine Learning project applied to the materials science field, but without having consolidated domain knowledge of the latter.&#xA;What I'm trying to figure out is the following: let's say we are given a (for example) quaternary chemical system made by &lt;span class=&quot;math-container&quot;&gt;$A_xB_yC_zD_w$&lt;/span&gt; where capital letters represent chemical elements and lower cases represent the number of atoms. Is there a way I could classify &lt;em&gt;a priori&lt;/em&gt; what kind of material I have? (for example metal, semiconductor or insulator..?) Could we potentially rely on the set of elements (phase field) that form the composition? Even just giving an estimate with a certain probability would be interesting.&lt;/p&gt;&#xA;" OwnerUserId="2017" LastEditorUserId="5" LastEditDate="2022-09-22T14:46:34.727" LastActivityDate="2022-09-23T00:35:24.287" Title="Classifying a materials' type by chemical formula" Tags="|materials-design|materials-engineering|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9695" PostTypeId="2" ParentId="6782" CreationDate="2022-09-22T16:05:43.473" Score="4" Body="&lt;p&gt;The &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.88.155427&quot; rel=&quot;nofollow noreferrer&quot;&gt;Effective Screening Medium&lt;/a&gt; (ESM) is a method that allows performing calculations in a 2D framework. The method is using Green functions, depending on the boundary conditions of these functions, different conditions can be imposed within the unit cell:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;bc1&amp;quot; Vacuum-Slab-Vacuum&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;bc2&amp;quot; Metal-Slab-Metal&lt;/li&gt;&#xA;&lt;li&gt;&amp;quot;bc3&amp;quot; Vacuum-Slab-Metal&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As you might have guessed, the method focuses on electrochemistry and can be used to perform grand-canonical DFT. The authors put an emphasis on two advantages: With ESM the electrostatic potential is not ill-defined anymore even in a plane-wave code, and the method gives the correct &amp;quot;image charge contribution&amp;quot; (if someone in the comment could give more details about this...)&lt;/p&gt;&#xA;&lt;p&gt;Practically in Quantum Espresso one has to activate the ESM with &lt;code&gt;assume_isolated = &amp;quot;esm&amp;quot;&lt;/code&gt; and specify the boundary condition with &lt;code&gt;esm_bc = &amp;quot;bcX&amp;quot;&lt;/code&gt;. When activated the unit cell will not span from &lt;span class=&quot;math-container&quot;&gt;$[0 ; z]$&lt;/span&gt; but from &lt;span class=&quot;math-container&quot;&gt;$[-z/2 ; z/2]$&lt;/span&gt;. The slab must be centred around 0, which in this case is the centre of the cell. You still need enough vacuum on both sides for the electronic density to decay to 0 before reaching the screening medium. (~ 10 Å of vacuum)&lt;/p&gt;&#xA;&lt;p&gt;To my understanding, this is some kind of improved &amp;quot;dipole correction&amp;quot; because you get completely rid of the periodicity along one dimension. But if someone could precise what are the advantage over a regular dipole correction this would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2022-09-22T16:05:43.473" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9696" PostTypeId="2" ParentId="9692" CreationDate="2022-09-22T16:57:27.287" Score="3" Body="&lt;p&gt;I think it is tricky to do the analysis in &amp;quot;pure water&amp;quot;, since you cannot have a charged solution. Maybe what you mean is an aqueous solution at neutral pH?&lt;/p&gt;&#xA;&lt;p&gt;Based on what I saw in the LibreTexts link you shared, it looks like you can do some back of the envelope type analysis. They give us the following ligand exchange reaction&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\ce{[Co(NH_3)_6]^{3+}} + 6\ce{H_3O^+} \to \ce{[Co(H_2O)_6]^{3+}} + 6\ce{NH_4^+}, \tag{1}&#xA;$$&lt;/span&gt;&#xA;which has an equilibrium constant of &lt;span class=&quot;math-container&quot;&gt;$K_{eq} = 10^{64}$&lt;/span&gt;. The standard state reaction free energy at &lt;span class=&quot;math-container&quot;&gt;$T = 298.15$&lt;/span&gt; K can be computed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Δ G^\circ = -k_B T \ln K_{eq} = -3.79~\text{eV}. \tag{2}&#xA;$$&lt;/span&gt;&#xA;Under more general conditions, you can write the thermodynamic driving force as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Δ G = Δ G^\circ + k_B T \ln\left(\frac{a_{\ce{[Co(H_2O)_6]^{3+}}} ~ a_{\ce{NH_4^+}}^6 }{ a_{\ce{[Co(NH_3)_6]^{3+}}} ~ a_{\ce{H_3O^+}}^6  } \right), \tag{3} &#xA;$$&lt;/span&gt;&#xA;which can be rewritten as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;Δ G = Δ G^\circ + k_B T\ln\left(\frac{a_{\ce{[Co(H_2O)_6]^{3+}}} ~ a_{\ce{NH_4^+}}^6 }{ a_{\ce{[Co(NH_3)_6]^{3+}}}} \right) + 6\ln(10)k_B T \times \text{pH}. \tag{4}&#xA;$$&lt;/span&gt;&#xA;Now unfortunately this analysis is still going to be a little limited since you would need to define the ionic strength of the solution to compute mean ion activity coefficients (using something like the extended Debye-Hückel equation). You also need to take into account other possible reactions that could occur, such as conversion of ammonium into ammonia gas, maybe buffering effects from dissolved CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; gas, etc. But what you can do from here is at least check the conditions under which the hexamminecobalt(III) complex will be stable (i.e., for what set of ion activities will &lt;span class=&quot;math-container&quot;&gt;$Δ G &amp;gt; 0$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Setting &lt;span class=&quot;math-container&quot;&gt;$Q$&lt;/span&gt; to be the activity ratio in the Eq. 4, you can make a plot like the one below, which plots the logarithm of the activity ratio against pH. The dashed line denotes where &lt;span class=&quot;math-container&quot;&gt;$Δ G = 0$&lt;/span&gt;. From this, you can get an idea of the stability of the complex under a variety of conditions (barring any additional reactions taking place). You can see that you'd need to push the reaction pretty far to the right in order for the reverse reaction to become thermodynamically favorable again. That is a long winded way to say that hexamminecobalt(III) is pretty unstable under most conditions within the scope of this analysis.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/80Q72m.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/80Q72m.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-09-23T01:29:14.257" LastActivityDate="2022-09-23T01:29:14.257" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9697" PostTypeId="1" AcceptedAnswerId="9706" CreationDate="2022-09-22T17:32:31.713" Score="6" ViewCount="305" Body="&lt;p&gt;I have this Green's function matrix &lt;span class=&quot;math-container&quot;&gt;$G^r= (E \mathbb{I} - \hat{H})^{-1}$&lt;/span&gt; in the &lt;span class=&quot;math-container&quot;&gt;$|\textrm{site}\rangle\otimes|\textrm{orbital}\rangle\otimes|\textrm{spin}\rangle$&lt;/span&gt; Hilbert space, and I am curious if there is a way to pull the density of states of the projection onto different quantum operators.&lt;/p&gt;&#xA;&lt;p&gt;It would be easy to get the density of states for an operator within the same basis, say &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt;, by simply summing up all of the &lt;span class=&quot;math-container&quot;&gt;$m = 1/2$&lt;/span&gt; states and &lt;span class=&quot;math-container&quot;&gt;$m = -1/2$&lt;/span&gt; states separately, instead of just taking &lt;span class=&quot;math-container&quot;&gt;$\frac{-1}{\pi}\textrm{Tr}(\textrm{Im}(G^r))$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;But I am curious if one could do more with the green's function to get the density of states of &lt;span class=&quot;math-container&quot;&gt;$S_x$&lt;/span&gt;, for example.&lt;/p&gt;&#xA;&lt;p&gt;Any insight or resources would be appreciated!&lt;/p&gt;&#xA;" OwnerUserId="5754" LastEditorUserId="5" LastEditDate="2022-09-23T00:38:07.637" LastActivityDate="2022-09-24T15:01:43.463" Title="How can I get the projected density of states within the Green's function method?" Tags="|electronic-structure|density-of-states|electronic-transport|greens-functions|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9699" PostTypeId="2" ParentId="8458" CreationDate="2022-09-22T23:27:31.617" Score="3" Body="&lt;p&gt;Yes. Take a look at SIESTA: the &amp;quot;Spanish Initiative for Electronic Simulations with Thousands of Atoms&amp;quot;. Love that name.&lt;/p&gt;&#xA;&lt;p&gt;It is much more efficient than the plane-wave DFT codes for this type of calculation, since it considers wavefunctions using a tight-binding basis and exploits matrix sparsity.&lt;/p&gt;&#xA;&lt;p&gt;I have not used it, but another student in my group has. It still took a while to converge the wavefunctions and atomic positions for a massive supercell, but it is worth a cursory glance. Especially if you are simply inputting the atomic positions, converging the wavefunctions, and running very simple landauer transport.&lt;/p&gt;&#xA;&lt;p&gt;Depending on your supercell/atomic complexity, you might alternatively be able to construct a simple tight-binding model and build up green's functions and electrodes to model transport. Take a look at Supriyo Datta's course on nanohub.&lt;/p&gt;&#xA;&lt;p&gt;Out of curiosity, what is the system you are trying to consider? I understand if you don't want to answer.&lt;/p&gt;&#xA;" OwnerUserId="5754" LastActivityDate="2022-09-22T23:27:31.617" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9700" PostTypeId="2" ParentId="8458" CreationDate="2022-09-23T00:03:16.360" Score="3" Body="&lt;p&gt;There are a lot of detailed considerations when computing electronic transport, but in general the answer is &amp;quot;yes&amp;quot;, &lt;em&gt;provided&lt;/em&gt; you can calculate (or estimate) a model Hamiltonian. For example, a DFT calculation may be used to compute the parameters for a model tight-binding Hamiltonian (e.g. using a local basis set, or Wannier90) which can then be used for much larger transport calculations.&lt;/p&gt;&#xA;&lt;p&gt;Many studies use the (linearised) Boltzmann Transport Equations (BTE), for example as implemented in &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2&quot; rel=&quot;nofollow noreferrer&quot;&gt;BoltzTraP2&lt;/a&gt; or &lt;a href=&quot;https://www.wannier.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;BoltzWann&lt;/a&gt;. A more sophisticated approach is to solve the quantum transport problem directly from the tight-binding Hamiltonian, for example the &lt;a href=&quot;https://quantum-kite.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum Kite&lt;/a&gt; software of my colleague Aires Ferreira and coworkers.&lt;/p&gt;&#xA;&lt;p&gt;Although a few thousand atoms would usually require a small computer cluster for DFT (depending on the basis set), the tight-binding Hamiltonian can be solved much more quickly. A common limiting factor is computer RAM, and you may need to invest in more RAM to perform large calculations.&lt;/p&gt;&#xA;&lt;p&gt;These methods typically give you the electrical conductivity &lt;em&gt;per unit of time&lt;/em&gt;; the actual conductivity will depend on how long it takes for conduction electrons to relax back down to the (non-conducting) valence state, which is called the &amp;quot;relaxation time&amp;quot;. The main factor affecting this is usually the electron-phonon interaction, but calculating that is computationally intensive. The common method is to use DFT, but this will not be practical for your situation; even if you did have the computational resources for a DFT calculation, an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-atom system has &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; phonons, and you need one DFT calculation for each phonon!&lt;/p&gt;&#xA;&lt;p&gt;It may be possible to estimate the relaxation time, for example by calculating it for a prototypical bulk system (which has far fewer atoms), or by using acoustic deformation potential theory. Even if you do not know the relaxation time, you can still investigate differences in conductivity per unit time, and if you assume that the relaxation time is similar across the various structures then this trend should be reflected in the actual conductivity.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-09-23T00:37:15.083" LastActivityDate="2022-09-23T00:37:15.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9701" PostTypeId="2" ParentId="9694" CreationDate="2022-09-23T00:14:22.887" Score="5" Body="&lt;p&gt;No, there is no way to do this, at least not in the way you have in mind. As a simple example, consider the unary system of elemental carbon:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If the carbon is in the diamond structure, you will get a wide band-gap insulator;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If the carbon is in the graphite (or graphene) structure, you will have 2D planar conductivity;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If the carbon forms nanotubes, the conductivity depends on how the hexagons wrap around the tube (multiples of three lead to metallic nanotubes; others are insulating);&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If the carbon forms nanoribbons, then the conductivity depends on the direction and edges of the ribbon.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note that all of these forms are stable at ambient pressure and temperature. If you consider more extreme conditions, even richer behaviour can arise!&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-09-23T00:35:24.287" LastActivityDate="2022-09-23T00:35:24.287" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9702" PostTypeId="2" ParentId="6890" CreationDate="2022-09-23T10:06:25.930" Score="2" Body="&lt;p&gt;This should be possible. You should impose &lt;code&gt;noncollin = .true.&lt;/code&gt;, then &lt;code&gt;constrained_magnetization = 'atomic direction'&lt;/code&gt;.&#xA;Finally with &lt;code&gt;angle1&lt;/code&gt; and &lt;code&gt;angle2&lt;/code&gt;, you can set the precise direction.&lt;/p&gt;&#xA;" OwnerUserId="5414" LastEditorUserId="7" LastEditDate="2022-09-23T14:55:10.940" LastActivityDate="2022-09-23T14:55:10.940" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9704" PostTypeId="2" ParentId="9681" CreationDate="2022-09-23T13:56:38.210" Score="2" Body="&lt;p&gt;To supplement Nike's answer, I would like to point out that the situation is even worse when you look at heavier atoms. While Gaussians do a pretty good job for the first periods of the periodic table, by the time you get to the heavy and superheavy elements you end up making microhartree errors even in Hartree-Fock atomic energies, as I demonstrated recently in &lt;a href=&quot;https://doi.org/10.1063/1.5144964&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 152, 134108 (2020)&lt;/a&gt;. Gaussian basis sets have global support and do not allow one to freely refine the accuracy of the basis set representation in space. For polyatomic calculations you end up with even worse problems since the basis functions on different atoms are non-orthonormal. Fully numerical methods, &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;nofollow noreferrer&quot;&gt;reviewed here&lt;/a&gt;, are a better alternative, which can be mathematically shown to converge to the CBS limit. Modern multiresolution approaches allow reaching microhartree accuracy for self-consistent field calculations with small- to moderate-size molecules; post-Hartree-Fock methods are still a work in progress.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-09-23T13:56:38.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9705" PostTypeId="2" ParentId="9697" CreationDate="2022-09-23T15:06:27.327" Score="1" Body="&lt;p&gt;I'm not sure I fully understand the question here. The local density of states is as you defined (see equation 10 of&#xA;&lt;a href=&quot;https://arxiv.org/pdf/1907.11302.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/1907.11302.pdf&lt;/a&gt; too)&lt;/p&gt;&#xA;&lt;p&gt;Could you define what you mean by  density of states of the projection onto different quantum operators. As you are measuring the inverse of a complex shifted Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;The only way I could think of getting G for certain operators is by projecting the quantum state into a desired subspace. For example one could project the quantum state into a subspace of singlet states or a subspace of triplet states (which fixes the spin angular momentum operator [S]).&lt;/p&gt;&#xA;&lt;p&gt;I apologise if I've misunderstood your question, but I hope you understand what I mean.&lt;/p&gt;&#xA;" OwnerUserId="4349" LastActivityDate="2022-09-23T15:06:27.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9706" PostTypeId="2" ParentId="9697" CreationDate="2022-09-23T22:27:44.237" Score="3" Body="&lt;p&gt;I believe that you can get what you want using the spectral density,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\rho({\bf r},{\bf r'},E) = -\frac{1}{\pi}{\rm Im}[G({\bf r},{\bf r'},E)]\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then the total density of states would be an integral over all space r and r', while a projected density of states would be&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\textrm{PDOS}_i(E) = -\frac{1}{\pi}{\rm Im} \langle O_i |G | O_i \rangle\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$O_i$&lt;/span&gt; denotes whichever states you like, and can certainly be the eigenstates of an operator &lt;span class=&quot;math-container&quot;&gt;$\bf O$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you already have the Green's function in a basis &lt;span class=&quot;math-container&quot;&gt;$|\alpha\rangle$&lt;/span&gt;, then you would have,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\textrm{PDOS}_i(E) = -\frac{1}{\pi}{\rm Im} \langle O_i|G|O_i \rangle = -\frac{1}{\pi}{\rm Im}\sum_{\alpha,\alpha'}{\langle O_i |\alpha\rangle G_{\alpha\alpha'}\langle \alpha'|O_i\rangle}\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="6025" LastEditorUserId="6025" LastEditDate="2022-09-24T15:01:43.463" LastActivityDate="2022-09-24T15:01:43.463" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9707" PostTypeId="1" AcceptedAnswerId="9708" CreationDate="2022-09-24T06:46:41.960" Score="5" ViewCount="301" Body="&lt;h3&gt;Introduction/Preamble&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/8762/201&quot;&gt;@SusiLehtola's answer to &lt;em&gt;Basics of numerical energy minimization techniques used in molecular dynamics?&lt;/em&gt;&lt;/a&gt; mentions conjugate gradients, BFGS for energy minimization, Metropolis Monte Carlo, and the FIRE algorithm for dynamical simulations.&lt;/p&gt;&#xA;&lt;p&gt;The FIRE algorithm was introduced in the 2006 Phys. Rev. Letter &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.170201&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structural Relaxation Made Simple&lt;/a&gt; (Bitzek, Koskinen, Gähler, Moseler and Gumbsch, PRL &lt;strong&gt;97&lt;/strong&gt;, 170201, also available &lt;a href=&quot;https://www.math.uni-bielefeld.de/%7Egaehler/papers/fire.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://www.researchgate.net/publication/6644744_Structural_Relaxation_Made_Simple&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;, &lt;a href=&quot;https://www.math.uni-bielefeld.de/%7Egaehler/papers/fire_old.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;3&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Consider a blind skier searching for the fastest way to the bottom of a valley in an unknown mountain range described by the potential energy landscape &lt;span class=&quot;math-container&quot;&gt;$E(x)$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$x = (x_1,x_2)$&lt;/span&gt;. Assuming that the skier is able to retard and steer we would recommend him to use the following equation of motion:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{\dot{v}}(t) = \mathbf{F}(t)/m - \gamma(t) |\mathbf{v}(t)| \left(\mathbf{\hat{v}}(t) - \mathbf{\hat{F}}(t) \right) \tag{1}\label{eq1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with the mass m, the velocity &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} = \mathbf{\dot{x}}$&lt;/span&gt;, the force &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F} =  \nabla E(\mathbf{x})$&lt;/span&gt;, and hat for a unit vector. We recommend as strategy that the skier introduces acceleration in a direction that is ‘steeper’ than the current direction of motion via the function &lt;span class=&quot;math-container&quot;&gt;$\gamma(t)$&lt;/span&gt;  if the power &lt;span class=&quot;math-container&quot;&gt;$P(t) = \mathbf{F}(t) \cdot \mathbf{v}(t)$&lt;/span&gt;is positive, and in order to avoid uphill motion he simply stops as soon as the power becomes negative. On the other hand, &lt;span class=&quot;math-container&quot;&gt;$\gamma(t)$&lt;/span&gt; should not be too large, because the current velocities carry information about the reasonable ‘average’ descent direction and energy scale.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and later:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The numerical treatment of the algorithm is simple. Any common MD integrator can be used as the basis for the propagation due to the conservative forces. The MD trajectory is continuously re-adjusted by two kinds of velocity modifications: a) the above mentioned immediate stop upon uphill motion and b) a simple mixing of the global (&lt;span class=&quot;math-container&quot;&gt;$3N_{atoms}$&lt;/span&gt; dimensional) velocity and force vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow (1-\alpha) \mathbf{v} + \alpha \mathbf{\hat{F}} |\mathbf{v}|$&lt;/span&gt; resulting from an &lt;strong&gt;Euler-discretization of the last term in eq. (1)&lt;/strong&gt; with time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha = \gamma \Delta t$&lt;/span&gt;. Both &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; are treated as dynamically adaptive quantities.&lt;/p&gt;&#xA;&lt;p&gt;Explicitly, the FIRE algorithm uses the following propagation rules (given initial values for &lt;span class=&quot;math-container&quot;&gt;$\Delta t, \alpha = \alpha_{start}$&lt;/span&gt; and for the global vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}=0$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MD: calculate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{x}, \mathbf{F} = -\nabla E(\mathbf{x})$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}$&lt;/span&gt; using any common MD integrator; check for convergence&lt;/li&gt;&#xA;&lt;li&gt;F1: calculate &lt;span class=&quot;math-container&quot;&gt;$P = \mathbf{F} \cdot \mathbf{v}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F2: set &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow (1-\alpha) \mathbf{v} + \alpha \mathbf{\hat{F}} |\mathbf{v}|$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F3: if &lt;span class=&quot;math-container&quot;&gt;$P &amp;gt; 0$&lt;/span&gt; and the number of steps since &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; was negative is larger than &lt;span class=&quot;math-container&quot;&gt;$N_{min}$&lt;/span&gt;, increase the time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t \rightarrow \min(\Delta t f_{inc}, \Delta t_{max})$&lt;/span&gt; and decrease &lt;span class=&quot;math-container&quot;&gt;$\alpha \rightarrow \alpha f_{\alpha}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F4: if &lt;span class=&quot;math-container&quot;&gt;$P \le 0$&lt;/span&gt;, decrease time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t \rightarrow \Delta t f_{dec}$&lt;/span&gt;, freeze the system &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v} \rightarrow 0$&lt;/span&gt; and set &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; back to &lt;span class=&quot;math-container&quot;&gt;$\alpha_{start}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;F5: return to MD&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;In relaxation an accurate calculation of the atomic trajectories is not necessary&lt;/strong&gt;, and the adaptive time step allows FIRE to increase &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; until either the largest stable time step &lt;span class=&quot;math-container&quot;&gt;$\Delta t_{max}$&lt;/span&gt; is reached, or an energy minimum along the current direction of motion (&lt;span class=&quot;math-container&quot;&gt;$P &amp;lt; 0$&lt;/span&gt;) is encountered.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Actual Question&lt;/h3&gt;&#xA;&lt;p&gt;Despite the lengthy preamble, my question is fairly short.&lt;/p&gt;&#xA;&lt;p&gt;In my pure python implementation of FIRE (for educational purposes) in two dimensions, force and velocity vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}$&lt;/span&gt; are 2 x N arrays.  &lt;code&gt;P = (F * v).sum(axis=0)&lt;/code&gt; returns a one dimensional array of length N.&lt;/p&gt;&#xA;&lt;p&gt;Do I go atom by atom and test its P(i) to decide which branch of the condition to use for it, or should I use just a single scalar &lt;code&gt;P = (F * v).sum()&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2022-09-26T13:55:48.917" LastActivityDate="2022-09-26T13:55:48.917" Title="How to apply FIRE to many atoms where P=F·v seems to be a vector rather than a scalar?" Tags="|molecular-dynamics|python|mathematical-modeling|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9708" PostTypeId="2" ParentId="9707" CreationDate="2022-09-24T10:05:56.323" Score="4" Body="&lt;p&gt;Your code is wrong. Your excerpt of the FIRE paper states &amp;quot;a simple mixing of the global (3Natoms dimensional) velocity and force vectors&amp;quot;, meaning &lt;span class=&quot;math-container&quot;&gt;$\mathbf{F}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{v}$&lt;/span&gt; are both vectors with dimension &lt;span class=&quot;math-container&quot;&gt;$3N_\text{atoms}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$P(t) = \mathbf{F}(t) \cdot \mathbf{v}(t)$&lt;/span&gt; is a scalar function. The correct implementation in Python is simply&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;P = numpy.dot(F, v)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;when you use the proper array types.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2022-09-26T13:53:26.823" LastActivityDate="2022-09-26T13:53:26.823" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9709" PostTypeId="2" ParentId="9707" CreationDate="2022-09-24T12:38:49.947" Score="5" Body="&lt;p&gt;As Susi noted, for your 2D case (as a subset of the more general 3D case) this dot product is assumed to be using the velocity/force written as &lt;span class=&quot;math-container&quot;&gt;$2N$&lt;/span&gt; dimensional vectors rather than &lt;span class=&quot;math-container&quot;&gt;$(2,N)$&lt;/span&gt; arrays.&lt;/p&gt;&#xA;&lt;p&gt;However, it can certainly be convenient to have them as arrays when you want to more easily index into the array and grab the, say, the &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; dimension of the 5th atom. If you want to keep the &lt;span class=&quot;math-container&quot;&gt;$(2,N)$&lt;/span&gt; arrays while still being able to do the appropriate dot product, the quickest way is just to temporarily reshape your array as needed, e.g. &lt;code&gt;P=np.dot(F.flatten(),v.flatten())&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;If performance is a concern, you should be able to use &lt;code&gt;F.reshape(-1)&lt;/code&gt; (same for &lt;code&gt;v&lt;/code&gt;) to obtain a &lt;em&gt;view&lt;/em&gt; of the array with the correct dimensions rather than constructing a copy.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-09-24T12:38:49.947" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9710" PostTypeId="1" CreationDate="2022-09-25T11:15:33.087" Score="3" ViewCount="41" Body="&lt;p&gt;Usually, the unit-cell of a crystal is made up of lattice points and basis, but all the crystallography software like VESTA doesn't show the &lt;code&gt;basis&lt;/code&gt;, is there any software that could show the basis?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2022-09-25T11:15:33.087" Title="How to visualize the basis in the unit cell of crystals?" Tags="|software-recommendations|crystallography|visualization-software|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9711" PostTypeId="1" CreationDate="2022-09-25T12:08:09.253" Score="3" ViewCount="264" Body="&lt;p&gt;I am following &lt;a href=&quot;https://dannyvanpoucke.be/vasp-tutor-creating-a-unit-cell-from-a-super-cell-en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial&lt;/a&gt; to transform a conventional cell to a primitive cell, but I am not sure how to determine the primitive copy of some atom in the conventional cell.&lt;/p&gt;&#xA;&lt;p&gt;For example, in the diamond structure of carbon, there are many carbon atoms in the conventional cell.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/woNzM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/woNzM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;br&gt;&#xA;&lt;strong&gt;How should I determine (by hand!) the primitive copy of some atom in the conventional cell?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2023-06-11T16:29:21.610" LastActivityDate="2023-06-11T16:29:21.610" Title="How to transform the conventional cell to primitive cell, by hand?" Tags="|crystallography|symmetry|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9712" PostTypeId="1" CreationDate="2022-09-26T05:19:51.537" Score="4" ViewCount="417" Body="&lt;p&gt;I was trying to perform an MD of a protein (Mrgprx2) in a lipid bilayer.&lt;/p&gt;&#xA;&lt;p&gt;The domain of the protein looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JCSXvm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JCSXvm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thus I'd like to have the transmembrane part of the protein to be buried in lipid membrane,&#xA;and the extracellular part of it to be placed outside membrane.&lt;/p&gt;&#xA;&lt;p&gt;I was following the &lt;strong&gt;&lt;a href=&quot;http://www.mdtutorials.com/gmx/membrane_protein/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gromacs Membrane Protein Tutorial&lt;/a&gt;&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However the protein orientation I get is not as I expected:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YGE6W.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YGE6W.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that the whole protein is buried in the lipid and in tilted position instead of perpendicular with respect to the lipid bilayer.&#xA;How can I properly orient the protein in the membrane?&lt;/p&gt;&#xA;&lt;p&gt;G.V.&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2022-09-26T05:48:04.220" LastActivityDate="2022-09-27T03:03:34.993" Title="How to orient the protein for lipid bilayer simulation in Gromacs" Tags="|molecular-dynamics|gromacs|membranes|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9713" PostTypeId="1" AcceptedAnswerId="9716" CreationDate="2022-09-26T12:42:05.327" Score="15" ViewCount="1058" Body="&lt;p&gt;Is there somewhere in the internet a good simple free working code (with a minimal number of lines in its presentation) that implements a calculation of eigenvalues with Hartree–Fock (or DFT) algorithm for &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{He}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{Li}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt; (or something else, something simple) on Python, Octave, C/C++, Fortran or pseudocode (no matter), maybe an article with a description of the code? In other words, writing a code for a concrete simple molecule (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;), what is a number of lines of the code which could be spent in minimum? (Naturally, not filling one line up to the maximum, but transferring the code to a next line within the meaning.)&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5" LastEditDate="2022-09-26T13:11:23.307" LastActivityDate="2022-12-01T22:46:01.447" Title="Is there a simple free working code that implements Hartree–Fock or DFT?" Tags="|density-functional-theory|quantum-chemistry|software-recommendations|one-topic-per-answer|hartree-fock|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9714" PostTypeId="1" CreationDate="2022-09-26T13:16:46.260" Score="3" ViewCount="103" Body="&lt;p&gt;I need to put two interactions of &lt;code&gt;ffields&lt;/code&gt; in the same code, but, I don't know what is the problem with the way I tried it. The code shows me &lt;code&gt;ERROR 309&lt;/code&gt; (see below), however I tried everything and it didn't work.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**error:** LAMMPS (9 Oct 2020)&#xA;OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. &#xA;(src/comm.cpp:94) using 1 OpenMP thread(s) per MPI task&#xA;Reading data file ... orthogonal box = (0.0000000 0.0000000 0.0000000) to (79.999989 79.999989 79.999989)&#xA;1 by 1 by 1 MPI processor grid&#xA;reading atoms ... 1352 atoms&#xA;read_data CPU = 0.003 seconds&#xA;WARNING: Changed valency_val to valency_boc for X (src/USER-REAXC/reaxc_ffield.cpp:315)&#xA;ERROR: Incorrect args for pair coefficients (src/USER-REAXC/pair_reaxc.cpp:309)&#xA;Last command: pair_coeff * * ffield_Co_Li_O.reax.txt Co O &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;SIMULATION:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Inicializacão---------------------------------------------&#xA;units           real&#xA;dimension       3&#xA;boundary        p p p&#xA;atom_style      charge&#xA;&#xA;#Posições iniciais dos atomos---------------------------&#xA;read_data       Pd_Co_O.txt&#xA;&#xA;#Potencial-----------------------&#xA;pair_style      reax/c NULL&#xA;pair_coeff      1 2 ffield_Pd_O_C_H.ajust.reax.txt Pd O NULL&#xA;pair_coeff      1 3 ffield_Co_Li_O.reax.txt Co O&#xA;&#xA;&#xA;#Minimização-----------------------&#xA;neighbor        0.3 bin&#xA;neigh_modify    every 10 delay 0 check no&#xA;velocity        all create 333.15 300288 dist gaussian mom yes rot yes&#xA;&#xA;&#xA;#Computando valores----------------------------------------------&#xA;compute  reax  all pair reax/c&#xA;variable eb    equal c_reax[1]&#xA;variable ea    equal c_reax[2]&#xA;variable elp   equal c_reax[3]&#xA;variable emol  equal c_reax[4]&#xA;variable ev    equal c_reax[5]&#xA;variable epen  equal c_reax[6]&#xA;variable ecoa  equal c_reax[7]&#xA;variable ehb   equal c_reax[8]&#xA;variable et    equal c_reax[9]&#xA;variable eco   equal c_reax[10]&#xA;variable ew    equal c_reax[11]&#xA;variable ep    equal c_reax[12]&#xA;variable efi   equal c_reax[13]&#xA;variable eqeq  equal c_reax[14]&#xA;&#xA;&#xA;#Definindo grupos de atomos-----------------------------------------&#xA;group          paladio  type    1&#xA;group          cobalto  type    2&#xA;group        oxigenio   type    3&#xA;&#xA;&#xA;#Fix---------------------------------------------------------&#xA;reset_timestep 0&#xA;timestep       0.2&#xA;fix            1 all nve&#xA;fix            2 all qeq/reax 1 0.0 10.0 1.0e-6 reax/c&#xA;fix            3 all temp/berendsen 333.15 333.15 10.0&#xA;&#xA;#Resultados------------------------------------------------------&#xA;&#xA;thermo         100&#xA;thermo_style   custom step temp epair etotal press v_eb v_ea v_elp v_emol v_ev v_epen v_ecoa v_ehb v_et v_eco v_ew v_ep v_efi v_eqeq&#xA;fix            4 oxigenio reax/c/species 1 10 100 species_coh.out element Pd Co O&#xA;dump           5 all custom 100 dump.reaxc id type x y z&#xA;&#xA;&#xA;run            1000&#xA;write_data     sistema_final_pdcoo.data &#xA;&#xA;print          &amp;quot;Fim da Simulação&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;CODE FFIELD 1:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Reactive MD-force field: Pd/O/C/H&#xA; 39 ! Number of general parameters&#xA; 50.0000 !Overcoordination parameter&#xA; 9.5469 !Overcoordination parameter&#xA; 26.5405 !Valency angle conjugation parameter&#xA; 1.7224 !Triple bond stabilisation parameter&#xA; 6.8702 !Triple bond stabilisation parameter&#xA; 60.4850 !C2-correction&#xA; 1.0588 !Undercoordination parameter&#xA; 4.6000 !Triple bond stabilisation parameter&#xA; 12.1176 !Undercoordination parameter&#xA; 13.3056 !Undercoordination parameter&#xA; -70.5044 !Triple bond stabilization energy&#xA; 0.0000 !Lower Taper-radius&#xA; 10.0000 !Upper Taper-radius&#xA; 2.8793 !Not used&#xA; 33.8667 !Valency undercoordination&#xA; 6.0891 !Valency angle/lone pair parameter&#xA; 1.0563 !Valency angle&#xA; 2.0384 !Valency angle parameter&#xA; 6.1431 !Not used&#xA; 6.9290 !Double bond/angle parameter&#xA; 0.3989 !Double bond/angle parameter: overcoord&#xA; 3.9954 !Double bond/angle parameter: overcoord&#xA; -2.4837 !Not used&#xA; 5.7796 !Torsion/BO parameter&#xA; 10.0000 !Torsion overcoordination&#xA; 1.9487 !Torsion overcoordination&#xA; -1.2327 !Conjugation 0 (not used)&#xA; 2.1645 !Conjugation&#xA; 1.5591 !vdWaals shielding&#xA; 0.1000 !Cutoff for bond order (*100)&#xA; 2.1365 !Valency angle conjugation parameter&#xA; 0.6991 !Overcoordination parameter&#xA; 50.0000 !Overcoordination parameter&#xA; 1.8512 !Valency/lone pair parameter&#xA; 0.5000 !Not used&#xA; 20.0000 !Not used&#xA; 5.0000 !Molecular energy (not used)&#xA; 0.0000 !Molecular energy (not used)&#xA; 2.6962 !Valency angle conjugation parameter&#xA; 5 ! Nr of atoms; cov.r; valency;a.m;Rvdw;Evdw;gammaEEM;cov.r2;#&#xA; alfa;gammavdW;valency;Eunder;Eover;chiEEM;etaEEM;n.u.&#xA; cov r3;Elp;Heat inc.;n.u.;n.u.;n.u.;n.u.&#xA; ov/un;val1;n.u.;val3,vval4&#xA; C 1.3817 4.0000 12.0000 1.8903 0.1838 0.9000 1.1341 4.0000&#xA; 9.7559 2.1346 4.0000 34.9350 79.5548 5.9666 7.0000 0.0000&#xA; 1.2114 0.0000 202.5551 8.9539 34.9289 13.5366 0.8563 0.0000&#xA; -2.8983 2.5000 1.0564 4.0000 2.9663 0.0000 0.0000 0.0000 &#xA; H 0.8930 1.0000 1.0080 1.3550 0.0930 0.8203 -0.1000 1.0000&#xA; 8.2230 33.2894 1.0000 0.0000 121.1250 3.7248 9.6093 1.0000&#xA; -0.1000 0.0000 61.6606 3.0408 2.4197 0.0003 1.0698 0.0000&#xA; -19.4571 4.2733 1.0338 1.0000 2.8793 0.0000 0.0000 0.0000&#xA; O 1.2450 2.0000 15.9990 2.3890 0.1000 1.0898 1.0548 6.0000&#xA; 9.7300 13.8449 4.0000 37.5000 116.0768 8.5000 8.3122 2.0000&#xA; 0.9049 0.4056 59.0626 3.5027 0.7640 0.0021 0.9745 0.0000&#xA; -3.5500 2.9000 1.0493 4.0000 2.9225 0.0000 0.0000 0.0000&#xA; X -0.1000 2.0000 1.0080 2.0000 0.0000 1.0000 -0.1000 6.0000&#xA; 10.0000 2.5000 4.0000 0.0000 0.0000 3.5000 85.0000 0.0000&#xA; -0.1000 0.0000 -2.3700 8.7410 13.3640 0.6690 0.9745 0.0000&#xA; -11.0000 2.7466 1.0338 6.2998 2.8793 0.0000 0.0000 0.0000&#xA; Pd 1.8582 2.0000 106.4200 2.0113 0.2465 1.0000 -1.0000 2.0000&#xA; 12.5712 6.0083 2.0000 0.0000 0.0000 5.5005 6.6477 0.0000&#xA; -1.0000 0.0000 89.8000 27.2704 1.8727 0.1586 0.8563 0.0000&#xA; -13.0000 1.7287 1.0338 5.0000 2.5791 0.0000 0.0000 0.0000&#xA; 10 ! Nr of bonds; Edis1;LPpen;n.u.;pbe1;pbo5;13corr;pbo6&#xA; pbe2;pbo3;pbo4;n.u.;pbo1;pbo2;ovcorr&#xA; 1 1 158.2004 99.1897 78.0000 -0.7738 -0.4550 1.0000 37.6117 0.4147&#xA; 0.4590 -0.1000 9.1628 1.0000 -0.0777 6.7268 1.0000 0.0000&#xA; 1 2 169.4760 0.0000 0.0000 -0.6083 0.0000 1.0000 6.0000 0.7652&#xA; 5.2290 1.0000 0.0000 1.0000 -0.0500 6.9136 0.0000 0.0000&#xA; 2 2 153.3934 0.0000 0.0000 -0.4600 0.0000 1.0000 6.0000 0.7300&#xA; 6.2500 1.0000 0.0000 1.0000 -0.0790 6.0552 0.0000 0.0000&#xA; 1 3 158.6946 107.4583 23.3136 -0.4240 -0.1743 1.0000 10.8209 1.0000&#xA; 0.5322 -0.3113 7.0000 1.0000 -0.1447 5.2450 0.0000 0.0000&#xA; 3 3 142.2858 145.0000 50.8293 0.2506 -0.1000 1.0000 29.7503 0.6051&#xA; 0.3451 -0.1055 9.0000 1.0000 -0.1225 5.5000 1.0000 0.0000 &#xA; 2 3 160.0000 0.0000 0.0000 -0.5725 0.0000 1.0000 6.0000 0.5626&#xA; 1.1150 1.0000 0.0000 0.0000 -0.0920 4.2790 0.0000 0.0000&#xA; 1 5 195.8048 0.0000 0.0000 -0.2150 -0.2000 1.0000 16.0000 0.1001&#xA; 10.7579 -0.2000 15.0000 1.0000 -0.1606 4.0000 1.0000 0.0000&#xA; 2 5 67.5406 0.0000 0.0000 0.6327 0.0000 1.0000 6.0000 0.2077&#xA; 0.7493 1.0000 0.0000 1.0000 -0.0547 4.0000 0.0000 0.0000&#xA; 3 5 56.7412 0.0000 0.0000 0.7149 -0.2000 1.0000 16.0000 0.1000&#xA; 11.9839 -0.2000 15.0000 1.0000 -0.3000 4.7089 1.0000 0.0000&#xA; 5 5 90.7003 0.0000 0.0000 -0.1661 -0.2000 0.0000 16.0000 0.2578&#xA; 3.0618 -0.2000 15.0000 1.0000 -0.0914 5.4665 0.0000 0.0000&#xA; 6 ! Nr of off-diagonal terms; Ediss;Ro;gamma;rsigma;rpi;rpi2&#xA; 1 2 0.1239 1.4004 9.8467 1.1210 -1.0000 -1.0000&#xA; 1 3 0.1156 1.8520 9.8317 1.2854 1.1352 1.0706&#xA; 2 3 0.0283 1.2885 10.9190 0.9215 -1.0000 -1.0000&#xA; 1 5 0.1169 2.3000 9.2890 1.6264 -1.0000 -1.0000&#xA; 2 5 0.1445 1.1103 13.0000 1.5714 -1.0000 -1.0000&#xA; 3 5 0.2237 1.6610 10.6568 1.7139 -1.0000 -1.0000&#xA; 36 ! Nr of angles;at1;at2;at3;Thetao,o;ka;kb;pv1;pv2&#xA; 1 1 1 59.0573 30.7029 0.7606 0.0000 0.7180 6.2933 1.1244&#xA; 1 1 2 65.7758 14.5234 6.2481 0.0000 0.5665 0.0000 1.6255&#xA; 2 1 2 70.2607 25.2202 3.7312 0.0000 0.0050 0.0000 2.7500&#xA; 1 2 2 0.0000 0.0000 6.0000 0.0000 0.0000 0.0000 1.0400&#xA; 1 2 1 0.0000 3.4110 7.7350 0.0000 0.0000 0.0000 1.0400&#xA; 2 2 2 0.0000 27.9213 5.8635 0.0000 0.0000 0.0000 1.0400&#xA; 1 1 3 49.6811 7.1713 4.3889 0.0000 0.7171 10.2661 1.0463&#xA; 3 1 3 77.7473 40.1718 2.9802 -25.3063 1.6170 -46.1315 2.2503&#xA; 2 1 3 65.0000 13.8815 5.0583 0.0000 0.4985 0.0000 1.4900&#xA; 1 3 1 73.5312 44.7275 0.7354 0.0000 3.0000 0.0000 1.0684&#xA; 1 3 3 79.4761 36.3701 1.8943 0.0000 0.7351 67.6777 3.0000&#xA; 3 3 3 80.7324 30.4554 0.9953 0.0000 1.6310 50.0000 1.0783&#xA; 1 3 2 70.1880 20.9562 0.3864 0.0000 0.0050 0.0000 1.6924&#xA; 2 3 3 75.6935 50.0000 2.0000 0.0000 1.0000 0.0000 1.1680&#xA; 2 3 2 85.8000 9.8453 2.2720 0.0000 2.8635 0.0000 1.5800&#xA; 1 2 3 0.0000 25.0000 3.0000 0.0000 1.0000 0.0000 1.0400&#xA; 3 2 3 0.0000 15.0000 2.8900 0.0000 0.0000 0.0000 2.8774&#xA; 2 2 3 0.0000 8.5744 3.0000 0.0000 0.0000 0.0000 1.0421&#xA; 5 3 5 53.8540 30.0000 2.0649 0.0000 1.0000 0.0000 1.7008&#xA; 3 5 5 55.7429 4.8907 3.9242 0.0000 0.1000 0.0000 1.0000&#xA; 3 3 5 90.0000 30.0000 1.6813 0.0000 1.0000 0.0000 1.9155&#xA; 3 5 3 0.0100 30.0000 8.0000 0.0000 1.0000 0.0000 2.4156&#xA; 2 5 2 25.6680 10.1984 7.6844 0.0000 1.0000 0.0000 1.2474&#xA; 2 2 5 83.9156 13.0474 0.9983 0.0000 1.0001 0.0000 3.1381&#xA; 5 2 5 0.9367 12.0943 6.6344 0.0000 1.0000 0.0000 1.0115&#xA; 2 5 5 40.0354 9.2882 8.0000 0.0000 1.0000 0.0000 2.7288 &#xA; 1 1 5 23.3470 30.0000 4.9485 0.0000 0.1000 0.0000 2.6345&#xA; 3 1 5 0.0100 30.0000 7.8334 0.0000 0.1000 0.0000 1.1134&#xA; 1 5 5 81.4675 17.7241 8.0000 0.0000 0.1000 0.0000 3.3824&#xA; 1 5 1 76.1959 30.0000 8.0000 0.0000 0.1000 0.0000 1.3967&#xA; 5 1 5 0.0100 30.0000 7.8334 0.0000 0.1000 0.0000 1.1134&#xA; 2 1 5 81.2014 30.0000 0.5384 0.0000 1.0000 0.0000 1.9241&#xA; 1 5 2 90.0000 0.2503 0.0100 0.0000 1.0000 0.0000 2.1438&#xA; 1 2 5 6.0617 0.0100 7.5704 0.0000 0.0000 0.0000 3.9408&#xA; 2 3 5 50.4877 0.1082 1.9877 0.0000 1.0000 0.0000 1.3192&#xA; 2 5 3 17.8836 0.0100 1.7426 0.5000 1.0000 0.0000 1.1872&#xA; 25 ! Nr of torsions;at1;at2;at3;at4;;V1;V2;V3;V2(BO);vconj;n.u;n&#xA; 1 1 1 1 -0.2500 34.7453 0.0288 -6.3507 -1.6000 0.0000 0.0000&#xA; 1 1 1 2 -0.2500 29.2131 0.2945 -4.9581 -2.1802 0.0000 0.0000&#xA; 2 1 1 2 -0.2500 31.2081 0.4539 -4.8923 -2.2677 0.0000 0.0000&#xA; 1 1 1 3 -0.3495 22.2142 -0.2959 -2.5000 -1.9066 0.0000 0.0000&#xA; 2 1 1 3 0.0646 24.3195 0.6259 -3.9603 -1.0000 0.0000 0.0000&#xA; 3 1 1 3 -0.5456 5.5756 0.8433 -5.1924 -1.0180 0.0000 0.0000&#xA; 1 1 3 1 1.7555 27.9267 0.0072 -2.6533 -1.0000 0.0000 0.0000&#xA; 1 1 3 2 -1.4358 36.7830 -1.0000 -8.1821 -1.0000 0.0000 0.0000&#xA; 2 1 3 1 -1.3959 34.5053 0.7200 -2.5714 -2.1641 0.0000 0.0000&#xA; 2 1 3 2 -2.5000 70.0597 1.0000 -3.5539 -2.9929 0.0000 0.0000&#xA; 1 1 3 3 0.6852 11.2819 -0.4784 -2.5000 -2.1085 0.0000 0.0000&#xA; 2 1 3 3 0.1933 80.0000 1.0000 -4.0590 -3.0000 0.0000 0.0000&#xA; 3 1 3 1 -1.9889 76.4820 -0.1796 -3.8301 -3.0000 0.0000 0.0000&#xA; 3 1 3 2 0.2160 72.7707 -0.7087 -4.2100 -3.0000 0.0000 0.0000&#xA; 3 1 3 3 -2.5000 71.0772 0.2542 -3.1631 -3.0000 0.0000 0.0000&#xA; 1 3 3 1 2.5000 -0.6002 1.0000 -3.4297 -2.8858 0.0000 0.0000&#xA; 1 3 3 2 -2.5000 -3.3822 0.7004 -5.4467 -2.9586 0.0000 0.0000&#xA; 2 3 3 2 2.5000 -4.0000 0.9000 -2.5000 -1.0000 0.0000 0.0000&#xA; 1 3 3 3 1.2329 -4.0000 1.0000 -2.5000 -1.7479 0.0000 0.0000&#xA; 2 3 3 3 0.8302 -4.0000 -0.7763 -2.5000 -1.0000 0.0000 0.0000&#xA; 3 3 3 3 -2.5000 -4.0000 1.0000 -2.5000 -1.0000 0.0000 0.0000 &#xA; 5 3 3 5 1.7276 50.0000 0.0100 -2.5000 -1.0000 0.0000 0.0000&#xA; 1 1 1 5 2.1746 45.0000 0.6721 -2.5000 0.0000 0.0000 0.0000&#xA; 5 1 1 5 5.5647 24.5181 8.0000 -2.5173 0.0000 0.0000 1.1091&#xA; 2 1 1 5 0.0100 11.4523 2.1450 -3.5000 0.0000 0.0000 1.0000&#xA; 1 ! Nr of hydrogen bonds;at1;at2;at3;Rhb;Dehb;vhb1&#xA; 3 2 3 2.1200 -3.5800 1.4500 19.5000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;CODE FFIELD 2&lt;/strong&gt; :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Co-Li-O&#xA;rc = 4.8&#xA;delr = 0.1&#xA;augt1 = 0&#xA;erose_form = 2&#xA;ialloy = 2&#xA;# Co-Co&#xA;zbl(1,1) = 0&#xA;nn2(1,1) = 1&#xA;rho0(1) =     0.5000&#xA;Ec(1,1) =     1.6500&#xA;re(1,1) =     3.0200&#xA;alpha(1,1) =  3.09825956&#xA;repuls(1,1) =     0.0500&#xA;attrac(1,1) =     0.0500&#xA;Cmin(1,1,1) =     0.1600&#xA;Cmax(1,1,1) =     2.8000&#xA;# Li-Li&#xA;zbl(2,2) = 0&#xA;nn2(2,2) = 1&#xA;rho0(2) =     1.0000&#xA;Ec(2,2) =     4.4100&#xA;re(2,2) =     2.5000&#xA;alpha(2,2) =  5.23561475&#xA;repuls(2,2) =     0.0000&#xA;attrac(2,2) =     0.0000&#xA;Cmin(2,2,2) =     0.4900&#xA;Cmax(2,2,2) =     2.0000&#xA;# O-O&#xA;zbl(3,3) = 0&#xA;nn2(3,3) = 1&#xA;rho0(3) =    12.0000&#xA;Ec(3,3) =     2.5600&#xA;re(3,3) =     1.2100&#xA;alpha(3,3) =  6.88000000&#xA;repuls(3,3) =     0.0000&#xA;attrac(3,3) =     0.0000&#xA;Cmin(3,3,3) =     2.0000&#xA;Cmax(3,3,3) =     2.8000&#xA;# Co-Li&#xA;zbl(1,2) = 0&#xA;nn2(1,2) = 1&#xA;lattce(1,2) = 'b1'&#xA;Ec(1,2) =     2.1178&#xA;re(1,2) =     2.3134&#xA;alpha(1,2) =  3.97495801&#xA;repuls(1,2) =     0.0000&#xA;attrac(1,2) =     0.0000&#xA;Cmin(1,1,2) =     1.8000&#xA;Cmin(2,2,1) =     0.1600&#xA;Cmin(1,2,1) =     0.3000&#xA;Cmin(2,1,1) =     0.3000&#xA;Cmin(1,2,2) =     0.3000&#xA;Cmin(2,1,2) =     0.3000&#xA;Cmax(1,1,2) =     3.6000&#xA;Cmax(2,2,1) =     2.8000&#xA;Cmax(1,2,1) =     2.8000&#xA;Cmax(2,1,1) =     2.8000&#xA;Cmax(1,2,2) =     2.8000&#xA;Cmax(2,1,2) =     2.8000&#xA;# Co-O&#xA;zbl(1,3) = 0&#xA;nn2(1,3) = 1&#xA;lattce(1,3) = 'b1'&#xA;Ec(1,3) =     1.6836&#xA;re(1,3) =     1.9500&#xA;alpha(1,3) =  7.31510556&#xA;repuls(1,3) =     0.0700&#xA;attrac(1,3) =     0.0700&#xA;Cmin(1,1,3) =     1.0000&#xA;Cmin(3,3,1) =     0.3000&#xA;Cmin(1,3,1) =     0.7000&#xA;Cmin(3,1,1) =     0.7000&#xA;Cmin(1,3,3) =     0.6000&#xA;Cmin(3,1,3) =     0.6000&#xA;Cmax(1,1,3) =     1.5500&#xA;Cmax(3,3,1) =     1.5500&#xA;Cmax(1,3,1) =     1.3500&#xA;Cmax(3,1,1) =     1.3500&#xA;Cmax(1,3,3) =     2.1500&#xA;Cmax(3,1,3) =     2.1500&#xA;# Li-O&#xA;zbl(2,3) = 0&#xA;nn2(2,3) = 1&#xA;lattce(2,3) = 'b1'&#xA;Ec(2,3) =     1.7917&#xA;re(2,3) =     2.0785&#xA;alpha(2,3) =  6.10015156&#xA;repuls(2,3) =     0.0200&#xA;attrac(2,3) =     0.0000&#xA;Cmin(2,2,3) =     4.0000&#xA;Cmin(3,3,2) =     0.1000&#xA;Cmin(2,3,2) =     0.5000&#xA;Cmin(3,2,2) =     0.5000&#xA;Cmin(2,3,3) =     0.5000&#xA;Cmin(3,2,3) =     0.5000&#xA;Cmax(2,2,3) =     5.0000&#xA;Cmax(3,3,2) =     1.8000&#xA;Cmax(2,3,2) =     4.0000&#xA;Cmax(3,2,2) =     4.0000&#xA;Cmax(2,3,3) =     4.0000&#xA;Cmax(3,2,3) =     4.0000&#xA;# Co-Li-O&#xA;Cmin(1,2,3) =     1.2000&#xA;Cmin(2,1,3) =     1.2000&#xA;Cmin(1,3,2) =     4.0000&#xA;Cmin(3,1,2) =     4.0000&#xA;Cmin(2,3,1) =     2.5000&#xA;Cmin(3,2,1) =     2.5000&#xA;Cmax(1,2,3) =     4.1000&#xA;Cmax(2,1,3) =     4.1000&#xA;Cmax(1,3,2) =     6.0000&#xA;Cmax(3,1,2) =     6.0000&#xA;Cmax(2,3,1) =     5.0000&#xA;Cmax(3,2,1) =     5.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6032" LastEditorUserId="5" LastEditDate="2022-09-26T18:01:41.327" LastActivityDate="2022-09-26T18:01:41.327" Title="How do I put two forcefields in the same LAMMPS code?" Tags="|lammps|forcefields|" AnswerCount="0" CommentCount="7" ClosedDate="2023-06-12T14:47:23.047" ContentLicense="CC BY-SA 4.0" />
  <row Id="9716" PostTypeId="2" ParentId="9713" CreationDate="2022-09-26T13:22:51.657" Score="11" Body="&lt;h1&gt;SlowQuant&lt;/h1&gt;&#xA;&lt;p&gt;There's dozens of free, working, open source codes for Hartree-Fock and DFT available online. See &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/142/susi-lehtola&quot;&gt;Susi&lt;/a&gt; Lehtola's &lt;a href=&quot;https://wires.onlinelibrary.wiley.com/doi/10.1002/wcms.1610?af=R&quot; rel=&quot;noreferrer&quot;&gt;review paper about open source quantum chemistry software&lt;/a&gt;. I'm not sure which one is the shortest or simplest, so maybe we can play a bit of &lt;a href=&quot;https://codegolf.stackexchange.com/&quot;&gt;code golf&lt;/a&gt; here.&lt;/p&gt;&#xA;&lt;p&gt;One program does come to my mind though, which is &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant&quot; rel=&quot;noreferrer&quot;&gt;SlowQuant&lt;/a&gt; because the author put an emphasis on readability rather than speed (which is unusual for quantum chemistry software, where speed is usually or at least traditionally was the priority):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;SlowQuant is a molecular quantum chemistry program written in python.&#xA;&lt;strong&gt;Even the computational demanding parts are written in python&lt;/strong&gt;, so it&#xA;lacks speed, thus the name SlowQuant.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4496/5&quot;&gt;author of SlowQuant is also active here at MMSE&lt;/a&gt; which is an added bonus if you have any questions about it here. On the other hand the GitHub page suggests that the code hasn't been actively developed in the last 5 years, except for some small changes that were made slightly more than 12 months ago.&lt;/p&gt;&#xA;&lt;p&gt;The Hartree-Fock part is in &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant/tree/master/slowquant/hartreefock&quot; rel=&quot;noreferrer&quot;&gt;this folder&lt;/a&gt;. The &lt;code&gt;HartreeFock.py&lt;/code&gt; file contains 129 lines but more than 29 lines are either whitespace or comments, so it's actually under 100 lines of &amp;quot;code&amp;quot; (the &lt;code&gt;UHF.py&lt;/code&gt; file &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant/blob/master/slowquant/hartreefock/UHF.py&quot; rel=&quot;noreferrer&quot;&gt;is only a bit longer&lt;/a&gt;, whereas the &lt;code&gt;uhf.py&lt;/code&gt; file in &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/pyscf/scf/uhf.py&quot; rel=&quot;noreferrer&quot;&gt;PySCF&lt;/a&gt; contains more than 1000 lines!):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import scipy.linalg&#xA;from slowquant.hartreefock import DIIS&#xA;&#xA;def diagonlize(M):&#xA;    eigVal, eigVec = np.linalg.eigh(M)&#xA;    return eigVal, eigVec&#xA;&#xA;def symm_orth(eigVal, eigVec):&#xA;    diaVal = np.diag(eigVal)&#xA;    M = np.dot(np.dot(eigVec,scipy.linalg.sqrtm(np.linalg.inv(np.diag(eigVal)))),np.matrix.transpose(eigVec))&#xA;    return M&#xA;&#xA;def HartreeFock(input, VNN, Te, S, VeN, Vee, deTHR=10**-6,rmsTHR=10**-6,Maxiter=100, DO_DIIS='Yes', DIIS_steps=6, print_SCF='Yes'):&#xA;    # ###############################&#xA;    #&#xA;    # VNN = nuclear repulsion&#xA;    # Te  = kinetic energy&#xA;    # S   = overlap integrals&#xA;    # VeN = nuclear attraction&#xA;    # Vee = two electron integrals&#xA;    # &#xA;    # ###############################&#xA;    &#xA;    #Core Hamiltonian&#xA;    Hcore = VeN+Te&#xA;    &#xA;    #Diagonalizing overlap matrix&#xA;    Lambda_S, L_S = diagonlize(S)&#xA;    #Symmetric orthogonal inverse overlap matrix&#xA;    S_sqrt = symm_orth(Lambda_S, L_S)&#xA;    &#xA;    #Initial Density&#xA;    F0prime = np.dot(np.dot(np.matrix.transpose(S_sqrt),Hcore),np.matrix.transpose(S_sqrt))&#xA;    eps0, C0prime = diagonlize(F0prime)&#xA;    &#xA;    C0 = np.matrix.transpose(np.dot(S_sqrt, C0prime))&#xA;    &#xA;    #Only using occupied MOs&#xA;    C0 = C0[0:int(input[0,0]/2)]&#xA;    C0T = np.matrix.transpose(C0)&#xA;    D0 = np.dot(C0T, C0)        &#xA;    &#xA;    # Initial Energy&#xA;    E0el = 0&#xA;    for i in range(0, len(D0)):&#xA;        for j in range(0, len(D0[0])):&#xA;            E0el += D0[i,j]*(Hcore[i,j]+Hcore[i,j])&#xA;    &#xA;    #SCF iterations&#xA;    &#xA;    if print_SCF == 'Yes':&#xA;        print(&amp;quot;Iter\t Eel\t&amp;quot;)&#xA;        &amp;quot;&amp;quot;&amp;quot;&#xA;        output = open('out.txt', 'a')&#xA;        output.write('Iter')&#xA;        output.write(&amp;quot;\t&amp;quot;)&#xA;        output.write('Eel')&#xA;        output.write(&amp;quot;\t \t \t \t \t&amp;quot;)&#xA;        output.write('Etot')&#xA;        output.write(&amp;quot;\t \t \t \t&amp;quot;)&#xA;        output.write('dE')&#xA;        output.write(&amp;quot;\t \t \t \t \t&amp;quot;)&#xA;        output.write('rmsD')&#xA;        if DO_DIIS == 'Yes':&#xA;            output.write(&amp;quot;\t \t \t \t \t&amp;quot;)&#xA;            output.write('DIIS')&#xA;        output.write(&amp;quot;\n&amp;quot;)&#xA;        output.write('0')&#xA;        output.write(&amp;quot;\t \t&amp;quot;)&#xA;        output.write(&amp;quot;{:14.10f}&amp;quot;.format(E0el))&#xA;        output.write(&amp;quot;\t \t&amp;quot;)&#xA;        output.write(&amp;quot;{:14.10f}&amp;quot;.format(E0el+VNN[0]))&#xA;        &amp;quot;&amp;quot;&amp;quot;&#xA;    &#xA;    for iter in range(1, Maxiter):&#xA;        #New Fock Matrix&#xA;        J = np.einsum('pqrs,sr-&amp;gt;pq', Vee,D0)&#xA;        K = np.einsum('psqr,sr-&amp;gt;pq', Vee,D0)&#xA;        F = Hcore + 2.0*J-K&#xA;        &#xA;        if DO_DIIS == 'Yes':&#xA;            #Estimate F by DIIS&#xA;            if iter == 1:&#xA;                F, errorFock, errorDens, errorDIIS = DIIS.runDIIS(F,D0,S,iter,DIIS_steps,0,0)&#xA;            else:&#xA;                F, errorFock, errorDens, errorDIIS  = DIIS.runDIIS(F,D0,S,iter,DIIS_steps,errorFock, errorDens)&#xA;            &#xA;        Fprime = np.dot(np.dot(np.transpose(S_sqrt),F),S_sqrt)&#xA;        eps, Cprime = diagonlize(Fprime)&#xA;        &#xA;        C = np.dot(S_sqrt, Cprime)&#xA;        &#xA;        CT = np.matrix.transpose(C)&#xA;        CTocc = CT[0:int(input[0,0]/2)]&#xA;        Cocc = np.matrix.transpose(CTocc)&#xA;        &#xA;        D = np.dot(Cocc, CTocc)&#xA;        &#xA;        #New SCF Energy&#xA;        Eel = 0&#xA;        for i in range(0, len(D)):&#xA;            for j in range(0, len(D[0])):&#xA;                Eel += D[i,j]*(Hcore[i,j]+F[i,j])&#xA;&#xA;        #Convergance&#xA;        dE = Eel - E0el&#xA;        rmsD = 0&#xA;        for i in range(0, len(D0)):&#xA;            for j in range(0, len(D0[0])):&#xA;                rmsD += (D[i,j] - D0[i,j])**2&#xA;        rmsD = (rmsD)**0.5&#xA;        &#xA;        if print_SCF == 'Yes':&#xA;            if DO_DIIS == 'Yes':&#xA;                if errorDIIS != 'None':&#xA;                    print(iter,&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel),&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel+VNN[0]),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(dE),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(rmsD),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(errorDIIS))&#xA;                else:&#xA;                    print(iter,&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel),&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel+VNN[0]),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(dE),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(rmsD))&#xA;            else:&#xA;                print(iter,&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel),&amp;quot;\t&amp;quot;,&amp;quot;{:14.10f}&amp;quot;.format(Eel+VNN[0]),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(dE),&amp;quot;\t&amp;quot;,&amp;quot;{: 12.8e}&amp;quot;.format(rmsD))&#xA;    &#xA;        D0 = D&#xA;        E0el = Eel&#xA;        if np.abs(dE) &amp;lt; deTHR and rmsD &amp;lt; rmsTHR:&#xA;            break&#xA;&#xA;    &#xA;    return Eel+VNN[0], C, F, 2*D&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It depends on a &lt;code&gt;DIIS.py&lt;/code&gt; subroutine which is only a few dozen lines long:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from time import sleep&#xA;&#xA;def DIIS(F,D,S,Efock,Edens,numbF):&#xA;    &#xA;    Edens[1:] = Edens[:len(Edens)-1]&#xA;    Efock[1:] = Efock[:len(Efock)-1]&#xA;    Edens[0] = D&#xA;    Efock[0] = F&#xA;    &#xA;    Err = np.zeros((numbF,len(F),len(F)))&#xA;    for i in range(0, numbF):&#xA;        Err[i] =  np.dot(np.dot(Efock[i],Edens[i]),S)&#xA;        Err[i] -= np.dot(np.dot(S, Edens[i]),Efock[i])&#xA;    Emax = np.max(np.abs(Err))&#xA;    &#xA;    #Construct B and b0&#xA;    B = -1*np.ones((numbF+1,numbF+1))&#xA;    B[numbF,numbF] = 0&#xA;    b0 = np.zeros(numbF+1)&#xA;    b0[numbF] = -1&#xA;    &#xA;    for i in range(0, numbF):&#xA;        for j in range(0, numbF):&#xA;            B[i,j] = np.trace(np.dot(Err[i], Err[j]))&#xA;    &#xA;    c = np.linalg.solve(B, b0)&#xA;&#xA;    Fprime = np.zeros((len(F),len(F)))&#xA;    &#xA;    for i in range(0, numbF):&#xA;        Fprime += c[i]*Efock[i]&#xA;    &#xA;    return Fprime, Efock, Edens, Emax&#xA;    &#xA;&#xA;def runDIIS(Fnew,Dnew,Snew,iter,Steps,errF,errD):&#xA;    &#xA;    if iter == 1:&#xA;        Efock = np.zeros((Steps, len(Fnew), len(Fnew)))&#xA;        Edens = np.zeros((Steps, len(Fnew), len(Fnew)))&#xA;        Efock[0] = Fnew&#xA;        Edens[0] = Dnew&#xA;        F = Fnew&#xA;        Emax = 'None'&#xA;    else:&#xA;        if iter &amp;lt; Steps:&#xA;            F, Efock, Edens, Emax = DIIS(Fnew,Dnew,Snew,errF,errD,iter)&#xA;        else:&#xA;            F, Efock, Edens, Emax = DIIS(Fnew,Dnew,Snew,errF,errD,Steps)&#xA;    &#xA;    return F, Efock, Edens, Emax&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;While it appears above that the Hartree-Fock algorithm was implemented in SlowQuant with only about 100 lines of actual code, there's also &lt;a href=&quot;https://github.com/erikkjellgren/SlowQuant/tree/master/slowquant/molecularintegrals&quot; rel=&quot;noreferrer&quot;&gt;about 150 more lines of code for the integrals&lt;/a&gt;. This could all be made more compact at the expense of readability, and certainly MATLAB (Octave) and/or Julia would allow for even more compact code.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-09-26T14:11:47.127" LastActivityDate="2022-09-26T14:11:47.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9718" PostTypeId="2" ParentId="9712" CreationDate="2022-09-26T20:24:12.767" Score="4" Body="&lt;p&gt;In the &lt;a href=&quot;http://www.mdtutorials.com/gmx/membrane_protein/01_pdb2gmx.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Step One: Prepare the Topology&lt;/a&gt;, second paragraph, you can find the following information:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The peptide was prepared in-house using the xLeap module of&#xA;AmberTools, using ideal backbone geometry of an α-helix (φ = -60°, ψ =&#xA;-40°). The .pdb file was oriented along the z-axis using editconf -princ, followed by a rotation about the y axis. Note that in GROMACS-3.3.x, the -princ option oriented the long axis of the&#xA;structure (in this case, the helix axis) along the z-axis by default,&#xA;but this option has changed as of GROMACS-4.0.4, which orients the&#xA;long axis along the x-axis. If you want to skip the construction of&#xA;this peptide, the properly oriented structure can be found here.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think that before setting up your system, you can prepare (rotate) your protein and use it in the orientation you want.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-09-26T20:24:12.767" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9719" PostTypeId="1" CreationDate="2022-09-27T02:02:04.243" Score="2" ViewCount="29" Body="&lt;p&gt;I want to find the doped structure of a compound. So i need to know how we can find the possible structures after substitution or interstitial doping? for example i want the possible structures for 6:120&#xA;P.S: I am new to this situation, before I studied 2D materials where the doping etc was easy. if any great mind can give me time and full details of how we can create the structures and then how we can analyze that huge number of structures. I will be in more than Thankful.&lt;/p&gt;&#xA;" OwnerUserId="6030" LastActivityDate="2022-09-27T02:02:04.243" Title="How to create doped possible structures for the calculation in VASP" Tags="|density-functional-theory|vasp|crystallography|" AnswerCount="0" CommentCount="1" ClosedDate="2022-09-27T16:52:03.950" ContentLicense="CC BY-SA 4.0" />
  <row Id="9720" PostTypeId="2" ParentId="9712" CreationDate="2022-09-27T02:57:49.250" Score="3" Body="&lt;p&gt;I used &lt;a href=&quot;https://www.youtube.com/watch?v=d-iyn88b830&quot; rel=&quot;nofollow noreferrer&quot;&gt;VMD to re-orient the protein&lt;/a&gt; in combination with &lt;code&gt;editconf&lt;/code&gt; rotation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;gmx editconf -f myprotein_processed.gro -rotate 0 90 0  -o myprotein_newbox.gro -c -box 6.41840 6.44350 6.59650&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;It worked.&lt;/p&gt;&#xA;&lt;p&gt;The final result I got is this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WI7i7.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WI7i7.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="4475" LastEditDate="2022-09-27T03:03:34.993" LastActivityDate="2022-09-27T03:03:34.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9721" PostTypeId="1" CreationDate="2022-09-27T03:37:24.163" Score="2" ViewCount="151" Body="&lt;p&gt;I was trying to perform  lipid bilayer MD for my protein based on &lt;a href=&quot;http://www.mdtutorials.com/gmx/membrane_protein/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS's Membrane Protein Tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I can &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9720/5&quot;&gt;successfully&lt;/a&gt; orient the protein in the lipid (turquoise) as you can see in the image below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/t22vc.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/t22vc.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I would like to control the thickness A, B, C of the lipid (before the actual MD run), since I'd like to allow some area of the protein to be exposed outside the lipid (they're extracellular region of the protein).&lt;/p&gt;&#xA;&lt;p&gt;How can I achieve that with GROMACS?&lt;/p&gt;&#xA;" OwnerUserId="4475" LastEditorUserId="5" LastEditDate="2022-09-27T04:26:20.993" LastActivityDate="2022-10-01T11:22:33.343" Title="How to control the thickness of lipid bilayer with GROMACS" Tags="|molecular-dynamics|gromacs|biomaterials|structural-biology|membranes|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9723" PostTypeId="1" CreationDate="2022-09-27T20:43:35.057" Score="3" ViewCount="100" Body="&lt;p&gt;I'm studying the adsorption of several molecules in metal organic frameworks (MOFs) using both experimental and computational methods. Experimetally I can easily obtain the temperature at which a molecule is adsorbed from the material. But I was wondering if there is a way to get the same information computationally.&lt;/p&gt;&#xA;&lt;p&gt;Someone asked something similar &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1004/converting-adsorption-binding-energy-to-absolute-temperature?noredirect=1#comment20084_1004&quot;&gt;here&lt;/a&gt;, but to my understanding the OP did not got a satisfatory answer, or at least did not pursue the topic. I do have interaction energy calculated, i.e. &lt;span class=&quot;math-container&quot;&gt;$$E_\text{Int}= E_\text{MOF+Ads} - (E_\text{MOF} + E_\text{Ads})$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5923" LastEditorUserId="7" LastEditDate="2022-09-28T02:04:07.920" LastActivityDate="2022-09-28T02:04:07.920" Title="Is there a way to estimate the energy of desorption of an adsorbed molecule?" Tags="|physical-properties-of-materials|binding-energy|adsorption|" AnswerCount="0" CommentCount="12" ClosedDate="2023-06-12T14:47:28.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="9725" PostTypeId="1" CreationDate="2022-09-28T09:12:25.120" Score="5" ViewCount="102" Body="&lt;p&gt;Once you mapped the high symmetry points from primitive cell to the super cell, you need to plot the downfolded bands.&lt;/p&gt;&#xA;&lt;p&gt;As we know in DFT output of band structure calculation we get a set of E vs &lt;strong&gt;k&lt;/strong&gt; data. Here, energy values are give w.r.t corresponding &lt;strong&gt;k&lt;/strong&gt;-point distances. So, how to plot these energy values w.r.t the downfolded &lt;strong&gt;k&lt;/strong&gt;-points?&lt;/p&gt;&#xA;" OwnerUserId="5492" LastEditorUserId="5492" LastEditDate="2022-09-28T13:07:51.707" LastActivityDate="2023-07-11T17:01:55.237" Title="How to plot downfolded bands from DFT bands?" Tags="|density-functional-theory|computational-chemistry|condensed-matter|dft-u|many-body-perturbation-theory|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9726" PostTypeId="1" AcceptedAnswerId="9751" CreationDate="2022-09-28T12:58:55.257" Score="3" ViewCount="116" Body="&lt;p&gt;&lt;a href=&quot;https://arxiv.org/pdf/2209.08364.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;In this paper,&lt;/a&gt; the author discusses the following nonlinear response relation:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\delta s_a=\alpha_{abc}E_bE_c \tag{1},$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\delta s_a$&lt;/span&gt; represents the spin polarization generated by the current driven by the electric field &lt;span class=&quot;math-container&quot;&gt;$E_b/E_c$&lt;/span&gt;. In Eq.(1), &lt;span class=&quot;math-container&quot;&gt;$E_b/E_c$&lt;/span&gt; are time-reversal-invariant quantities: if &lt;span class=&quot;math-container&quot;&gt;$\delta s_a$&lt;/span&gt; is reversed by time-reversal symmetry (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;), we conclude that &lt;span class=&quot;math-container&quot;&gt;$\alpha_{abc}$&lt;/span&gt; is a T-odd tensor; if &lt;span class=&quot;math-container&quot;&gt;$\delta s_a$&lt;/span&gt; is not reversed by time-reversal symmetry, we conclude that &lt;span class=&quot;math-container&quot;&gt;$\alpha_{abc}$&lt;/span&gt; is a T-even quantity.&lt;/p&gt;&#xA;&lt;p&gt;However, in the paper cited before, the author claims&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\alpha_{abc}=\alpha_{abc}^{even}+\alpha_{abc}^{odd} \tag{2}$$&lt;/span&gt;&#xA;I don't understand why this partition is legitimate. Is it due to the sign change of &lt;span class=&quot;math-container&quot;&gt;$\delta s_{a}$&lt;/span&gt; under time-reversal symmetry being indefinite?&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, consider the nonlinear current response:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$j_a=\sigma_{abc}E_bE_c \tag{3}$$&lt;/span&gt;&#xA;where the current density &lt;span class=&quot;math-container&quot;&gt;$j_a$&lt;/span&gt; will change its sign under time-reversal symmetry and the electric field &lt;span class=&quot;math-container&quot;&gt;$E_b/E_c$&lt;/span&gt; will remain unchanged under time-reversal symmetry. As a result, we find:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{T}\sigma_{abc}=-\sigma_{abc}$$&lt;/span&gt;&#xA;namely, the nonlinear conductivity should be a T-odd tensor. However, &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.127.277201&quot; rel=&quot;nofollow noreferrer&quot;&gt;in another paper&lt;/a&gt;, the author seems to also admit a similar partition:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\sigma_{abc}=\sigma_{abc}^{even}+\sigma_{abc}^{odd}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How could this be true? The current density is not reversed by time-reversal symmetry? This can not be the case.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="7" LastEditDate="2022-09-28T13:11:05.250" LastActivityDate="2022-10-04T12:36:28.567" Title="Why can this tensor have a T-odd and T-even part at the same time?" Tags="|symmetry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9727" PostTypeId="1" CreationDate="2022-09-28T14:05:28.363" Score="2" ViewCount="53" Body="&lt;p&gt;&lt;em&gt;Previously, a question was asked about &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9674/which-equation-makes-it-possible-to-calculate-the-forces-of-attraction-between-a&quot;&gt;an equation that is able to calculate the forces of attraction between a surface and molecules&lt;/a&gt; (of another substance). During the discussion of the question a thought for a new question arose.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let us suppose that a surface and molecules of another substance interact to each other. The substance is something like honey, clay, glue, or resin, i.e. one has an adhesion property. Besides, some of the substances can be corrosive in relation to the surface. (Undoubtedly, corrosive substances may not have an adhesion property as well.) Corrosion can affect in different ways that depends on its activity (strong/weak/medium etc.).&lt;/p&gt;&#xA;&lt;h2&gt;Interesting questions appear.&lt;/h2&gt;&#xA;&lt;p&gt;Due to an action of corrosion an exchange of atoms between the surface and molecules of the substance can appear. Therefore the system will have moving cores of atoms and in this case the Hamiltonian of the cores of the atoms cannot be neglected. Is it right? Does Hartee–Fock and DFT theory allow taking into account moving cores of atoms?&#xA;Maybe is there a phenomenological theory doing a calculation of attraction forces of the system without solving Hartree–Fock or Kohn–Sham equation? In the process of the interaction, hydrogen bonds can appear. How can they be taken into account?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2022-09-28T14:05:28.363" Title="How to calculate the forces of attraction between a surface and molecules of a substance at a corrosion affection?" Tags="|density-functional-theory|ab-initio-calculations|hartree-fock|model-hamiltonians|molecular-interactions|" AnswerCount="0" CommentCount="3" ClosedDate="2022-10-30T19:04:05.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="9728" PostTypeId="2" ParentId="8796" CreationDate="2022-09-28T19:49:01.793" Score="3" Body="&lt;p&gt;For Bulk we start with a small number of K-points and then increase it step by step until we get convergence with respect to the target property. This is generally done with respect to the SCF energy that is obtained at the end. The procedure to be used here is quite similar to convergence of cutoff energy as has been shown &lt;a href=&quot;https://www.youtube.com/watch?v=HY0IX55ieFI&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The key difference between nano structures and Bulk systems is that in nano structures electrons are confined in a few directions(for Quantum Dots electrons are confined in all 3 directions), whereas in bulk they are allowed to move in all directions. This leads to flat bands in the case of a nano structure, due to which a single k-point should be enough.&lt;/p&gt;&#xA;&lt;p&gt;Another way to look at this is when performing calculations on such systems with plane wave codes we need to introduce vacuum around our system, such that one particular quantum dot does not interact with itself image. In order to know the amount of vacuum to be inserted we need to again perform convergence testing. The addition of vacuum generally leads to big cells. As you must know bigger the real cell smaller the k space. So in order to traverse this small k-space a single k point is enough.&lt;/p&gt;&#xA;&lt;p&gt;Now only one question stands if taking more k points leads to some problems for optical properties and DOS. I am not sure about this but I think that the answers obtained should be correct, it would just be much more inefficient.&lt;/p&gt;&#xA;&lt;p&gt;Key takeaway is that if you are performing calculations with Bulk run convergence tests with K point and if calculations are being run with Quantum Dots choose a single k point.&lt;/p&gt;&#xA;" OwnerUserId="3672" LastActivityDate="2022-09-28T19:49:01.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9729" PostTypeId="2" ParentId="9230" CreationDate="2022-09-29T07:06:19.507" Score="3" Body="&lt;p&gt;I want neural-networks that are super good at &lt;strong&gt;Geometry optimization&lt;/strong&gt;.  Every HF calculation requires correct geometry to produce meaningful results.  Bad geometries that are far from optimal can exacerbate the convergence issues Hartree-Fock already has.  But if you could avoid that by getting good initial atomic positions from a neural-network, you could both speed up HF convergence significantly and reduce the total number of times it needs to be called.&lt;/p&gt;&#xA;" OwnerUserId="5992" LastActivityDate="2022-09-29T07:06:19.507" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9730" PostTypeId="1" CreationDate="2022-09-29T12:31:35.390" Score="1" ViewCount="69" Body="&lt;p&gt;Lets suppose that I have an atom chain like system 1 below. Now, some interaction made one atom to move out of the chain, like shown in system 2 (the moved atom remains bounded but in another position). This change is permanent.&lt;/p&gt;&#xA;&lt;p&gt;Knowing all the coordinates for all the atoms: &lt;strong&gt;Is it possible to define a property like strain to characterize the structural change?&lt;/strong&gt;&lt;br /&gt;&#xA;(I'm not sure if the RMSD could be a good parameter to use here)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System 1: ************&#xA;&#xA;&#xA;               *          &#xA;System 2: ***** ******&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-09-29T20:01:06.113" Title="Is it possible to define a property like strain to characterize the structural change?" Tags="|condensed-matter|stress-strain|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9731" PostTypeId="2" ParentId="9730" CreationDate="2022-09-29T20:01:06.113" Score="2" Body="&lt;p&gt;I would select a group of atoms and calculate the relative deviation along the 3 dimensions. So I would take the initial (x&lt;sub&gt;i&lt;/sub&gt;, y&lt;sub&gt;i&lt;/sub&gt;, z&lt;sub&gt;i&lt;/sub&gt;) and final (x&lt;sub&gt;f&lt;/sub&gt;, y&lt;sub&gt;f&lt;/sub&gt;, z&lt;sub&gt;f&lt;/sub&gt;) coordinates and then calculate the 3N-dimensional distance using&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\sqrt{(x_f-x_i)^2 + (y_f-y_i)^2 + (z_f-z_i)^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Those atoms there were not affected will have values zero, and values other than zero would reflect the extent change.&lt;/p&gt;&#xA;" OwnerUserId="3401" LastActivityDate="2022-09-29T20:01:06.113" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9732" PostTypeId="2" ParentId="8273" CreationDate="2022-09-30T10:05:04.863" Score="3" Body="&lt;p&gt;If you follow the derivation of the Swendsen-Wang method as described on Wikipedia (&lt;a href=&quot;https://en.m.wikipedia.org/wiki/Swendsen%E2%80%93Wang_algorithm&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;), you will see that it works whether the quantity &lt;span class=&quot;math-container&quot;&gt;$J_{nm}$&lt;/span&gt; is same for all links or different for different kinds of links.&lt;/p&gt;&#xA;&lt;p&gt;So you should bond / unbond all nearest neighbour interactions as per the method. You must simply ensure that the bonding probability for each link is correctly related to that particular link's ferromagnetic coupling strength.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-09-30T10:05:04.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9733" PostTypeId="2" ParentId="9587" CreationDate="2022-10-01T11:15:34.583" Score="3" Body="&lt;p&gt;You're almost right, but: The standard simulation methods put up with infinite images precisely &lt;em&gt;because&lt;/em&gt; electrostatic forces are long-ranged!&lt;/p&gt;&#xA;&lt;p&gt;As you yourself have pointed out, the standard LJ cutoffs (1-2 nm) are not acceptable for electrostatic interactions. And so, instead of using ever larger cutoffs to treat electrostatic interactions locally, we can use Ewald / grid methods to calculate these forces using FFTs of complexity &lt;span class=&quot;math-container&quot;&gt;$O(n \ln n)$&lt;/span&gt;,  including long range forces &lt;em&gt;from inside the same cell&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Historically MD has always been done with periodic boundaries for computational reasons: it's easier and more predictable to have a particle &amp;quot;wrap around&amp;quot; when it encounters a boundary, instead of using &amp;quot;open&amp;quot; boundary conditions which require complex algorithms for adding and removing particles at the edges and maintaining a &lt;span class=&quot;math-container&quot;&gt;$\mu V T$&lt;/span&gt; ensemble. But the periodic boundaries dovetail nicely with Ewald / grid long range electrostatics, giving a system which is certainly mathematically consistent.&lt;/p&gt;&#xA;&lt;p&gt;Are these models &lt;em&gt;accurate&lt;/em&gt;? Certainly for fluids where large structures are not of concern at the molecular level. The effect of having an infinite lattice of proteins is probably small if there is enough water between them, and can be shown to be so (simply run a few runs with more water and show that the protein behaves similarly); any inaccuracy is (1) diagnosable and (2) likely far less than the discontinuities in, say, an RF treatment.&lt;/p&gt;&#xA;&lt;p&gt;There &lt;em&gt;are&lt;/em&gt; situations where PBC has significant effect. The best known of this is on diffusivities, where finite size corrections are known. Biophysically, when simulating lipid bilayers in 3D PBC, their effect on the membrane &amp;quot;ripples&amp;quot; must be accounted for carefully. But again, it's clear how to diagnose and treat these inaccuracies: make larger and larger systems and either hit convergence or identify asymptotic corrections. Far more cleverness is required to improve systematically on other methods for long range electrostatics.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-10-01T11:15:34.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9734" PostTypeId="2" ParentId="9721" CreationDate="2022-10-01T11:22:33.343" Score="2" Body="&lt;p&gt;You can adjust the thickness of the water layer* by initialising your simulation with more or less water in it.&lt;/p&gt;&#xA;&lt;p&gt;The thickness of the &lt;em&gt;lipid bilayer&lt;/em&gt; is determined by the types of lipids you use, and the force field. Presumably if you build lipids with longer (or shorter) tails you will have a thicker (or thinner) hydrophobic region. You will have to determine for yourself whether the resulting lipid composition is biologically feasible or not.&lt;/p&gt;&#xA;&lt;p&gt;*If you are simulating in 3D periodic boundary conditions you actually only have one water layer, alternating with the lipid bilayer.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-10-01T11:22:33.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9735" PostTypeId="2" ParentId="9450" CreationDate="2022-10-01T11:45:38.427" Score="2" Body="&lt;p&gt;You could try to run a GROMACS simulation with COLVARS, which takes the radius of gyration as a possible collective variable. Running an umbrella sampling simulation with a suitable set of weights should give you an ensemble of snapshots with the desired distribution of radii of gyration.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you could run an MD simulation but with every particle of the polymer harmonically tethered (with a very weak force constant!) to the simulation cell origin. Making the force constant larger or smaller would then make the average radius of gyration smaller or larger.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-10-01T11:45:38.427" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9736" PostTypeId="1" AcceptedAnswerId="9737" CreationDate="2022-10-01T13:35:50.243" Score="4" ViewCount="1662" Body="&lt;p&gt;I am a user of the VASP code. I relax the atomic positions of a supercell containing an impurity atom. For relaxation, I set&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISYM = 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, I try to perform a static calculation. For this step, I set&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISYM = 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I got an error along with suggestion:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;VERY BAD NEWS! internal error in subroutine INVGRP:&#xA;inverse of rotation matrix was not found (increase SYMPREC)       2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Following the suggestion, I increase SYMPREC (from the default value &lt;span class=&quot;math-container&quot;&gt;$10^{-5}$&lt;/span&gt;) to &lt;span class=&quot;math-container&quot;&gt;$10^{-4}$&lt;/span&gt;, and the error happened again. Instead, when I decrease SYMPREC to &lt;span class=&quot;math-container&quot;&gt;$10^{-6}$&lt;/span&gt;, the error is gone.&lt;/p&gt;&#xA;&lt;p&gt;I am confused that what does &amp;quot;increase SYMPREC&amp;quot; mean in the above suggestion. Could someone help explain? What are the side effects when tuning the SYMPREC?&lt;/p&gt;&#xA;" OwnerUserId="1688" LastEditorUserId="5" LastEditDate="2022-10-01T13:37:42.383" LastActivityDate="2024-03-12T07:22:21.827" Title="VASP symmetry related error" Tags="|vasp|symmetry|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9737" PostTypeId="2" ParentId="9736" CreationDate="2022-10-01T16:36:06.523" Score="5" Body="&lt;p&gt;This is symmetry related problem, somehow VASP subroutine is unable to find point symmetry. This problem can be solved by switching off symmetry (&lt;code&gt;ISYM=0&lt;/code&gt;) or by setting more tight tolerance &lt;code&gt;SYMPREC=1e-8 (default: 1e-5)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYMPREC defines precision of atomic position to determine symmetry&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There is no problem in changing &lt;code&gt;SYMPREC&lt;/code&gt;, it will only increase computational cost if certain symmetry is broken.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-10-01T16:36:06.523" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9738" PostTypeId="1" CreationDate="2022-10-01T17:31:19.267" Score="3" ViewCount="116" Body="&lt;p&gt;I have a problem installing Amber.&#xA;First, I enter the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./configure --with-python /usr/bin/python3 --with-netcdf $AMBERHOME/netCDF gnu&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Than make:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;make FFLAGS=&amp;quot;-fallow-argument-mismatch&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this results in following errors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;usr/bin/ld: /home/dre/amber18/lib/libcifparse.a(lex.cifp.o):(.bss+0x8): multiple definition of `cifpin'; /home/dre/amber18/lib/libcifparse.a(cifparse.o):(.bss+0x0): first defined here&#xA;collect2: error: ld returned 1 exit status&#xA;make[2]: *** [Makefile:173: antechamber] Error 1&#xA;make[2]: Leaving directory '/home/dre/amber18/AmberTools/src/antechamber'&#xA;make[1]: *** [Makefile:29: serial] Error 2&#xA;make[1]: Leaving directory '/home/dre/amber18/AmberTools/src'&#xA;make: *** [Makefile:7: install] Error 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The Ubuntu system was freshly installed yesterday, but all the required drivers are already installed.&#xA;Obviously, multiple definition of `cifpin' is the problem.&#xA;I guess there are some problems with fortran flags.&#xA;Please, help me to fix this mistake!&lt;/p&gt;&#xA;&lt;p&gt;Best regards,&lt;/p&gt;&#xA;&lt;p&gt;Andrey&lt;/p&gt;&#xA;" OwnerUserId="6057" LastActivityDate="2022-10-01T17:31:19.267" Title="I have a problem with Amber18 configuration at the make install step" Tags="|molecular-dynamics|amber|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-12T14:47:34.633" ContentLicense="CC BY-SA 4.0" />
  <row Id="9739" PostTypeId="1" AcceptedAnswerId="9774" CreationDate="2022-10-02T01:22:13.063" Score="4" ViewCount="289" Body="&lt;p&gt;My question is related to the Wikipedia page of spin-forbidden reactions &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin-forbidden_reactions&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Spin-forbidden_reactions&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;When a reaction converts a metal from a singlet to triplet state (or vice versa):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The energy of the two spin states must be nearly equal, as dictated by temperature,&lt;/li&gt;&#xA;&lt;li&gt;A mechanism is required to change spin states.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Strong spin-orbital coupling can satisfy the 2nd condition.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But, in &lt;a href=&quot;https://en.wikipedia.org/wiki/Spin%E2%80%93orbit_interaction&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Spin%E2%80%93orbit_interaction&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It can be shown that the five operators &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$J^2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$L^2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$J_z$&lt;/span&gt; all commute with each other and with &lt;span class=&quot;math-container&quot;&gt;$\Delta H$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The above quotation would imply under the spin-orbit coupling operator in the spin-orbit interaction Wikipedia page, &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; is a good quantum number, and the expectation value of &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; will not change, though &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt; could change.&lt;/p&gt;&#xA;&lt;p&gt;Though in Sakurai's Advanced Quantum Mechanics, the author mentioned the Dirac equation for the hydrogen atom, the Hamiltonian commutes with &lt;span class=&quot;math-container&quot;&gt;$K, J^2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$J_z$&lt;/span&gt;, no longer commutes with &lt;span class=&quot;math-container&quot;&gt;$L^2$&lt;/span&gt;, I assume it won't commute with &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt;. That leads to my question(s):&lt;/p&gt;&#xA;&lt;p&gt;Does the spin-forbidden reaction Wikipedia page implies another way of introducing spin-orbit interaction, make &lt;span class=&quot;math-container&quot;&gt;$[H, S^2]\neq 0$&lt;/span&gt;? Or means &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt; is not a good quantum number; Or when people talk about this issue, people imply the full Dirac equation or anything possibly equivalent to it somehow (exact 2-component method)? Or anything else?&lt;/p&gt;&#xA;" OwnerUserId="6061" LastEditorUserId="5" LastEditDate="2022-10-12T04:24:44.430" LastActivityDate="2022-10-12T04:24:44.430" Title="How spin-orbit coupling makes spin-forbidden reactions possible?" Tags="|quantum-chemistry|quantum-mechanics|spin-orbit-coupling|relativistic|reactivity|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9740" PostTypeId="1" CreationDate="2022-10-02T12:55:46.247" Score="4" ViewCount="93" Body="&lt;p&gt;I am trying to passivate the surface of &lt;span class=&quot;math-container&quot;&gt;$\ce{ZnO}$&lt;/span&gt; quantum dot using siesta. I generated pseudo-hydrogens with fractional charges of 1.5e (to passivate Zn) and .5e (to passivate O) using the siesta utility code. To begin with, I tried to passivate each separately to see if it is working (eventually I want to passivate both Zn and O). My initial attempts give me the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;initatom: Reading input for the pseudopotentials and atomic orbitals ----------&#xA;Species number:   1 Atomic number:    8 Label: O&#xA;Species number:   2 Atomic number:   30 Label: Zn&#xA;Species number:   3 Atomic number:    1 Label: H-Fraction-0.50000&#xA; &#xA;Ground state valence configuration:   2s02  2p04&#xA;Reading pseudopotential information in formatted form from O.psf&#xA;&#xA;Valence configuration for pseudopotential generation:&#xA;2s( 2.00) rc: 1.47&#xA;2p( 4.00) rc: 1.47&#xA;3d( 0.00) rc: 1.47&#xA;4f( 0.00) rc: 1.47&#xA;Ground state valence configuration:   4s02  3d10&#xA;Reading pseudopotential information in formatted form from Zn.psf&#xA;&#xA;Valence configuration for pseudopotential generation:&#xA;4s( 2.00) rc: 2.43&#xA;4p( 0.00) rc: 2.37&#xA;3d(10.00) rc: 2.09&#xA;4f( 0.00) rc: 2.82&#xA;Ground state valence configuration:   1s01&#xA;Reading pseudopotential information in formatted form from H-Fraction-0.50000.psf&#xA;ERROR expected valence charge for species H-Fraction-0.50000  &#xA;ERROR and the value read from the vps file&#xA;ERROR differ:  Zval(expected)=  1.000 Zval(vps)=  0.500&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A similar error message for H-Fraction-1.50000, but with &lt;code&gt;Zval(vps)=1.500&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My block for synthetic atoms for H-Fraction-0.500 is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block SyntheticAtoms&#xA;3&#xA; 1 2 3 4&#xA; 0.50000 0.00000 0.00000 0.00000&#xA;%endblock SyntheticAtoms&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why do I get the error message? I used the siesta utility to generate the pseudo hydrogen psfs.&lt;/p&gt;&#xA;" OwnerUserId="6067" LastEditorUserId="5" LastEditDate="2022-10-02T18:40:25.933" LastActivityDate="2022-10-16T20:57:08.997" Title="Siesta surface passivation" Tags="|siesta|surface-passivation|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9741" PostTypeId="1" CreationDate="2022-10-02T19:07:48.280" Score="7" ViewCount="175" Body="&lt;p&gt;I'm interested in studying some simple periodic model systems representing proteins.  For that I'd like to make pdb files of an alpha helix or beta sheet with idealized coordinates which is infinitely periodic.  For an alpha helix it would be just periodic along the axis, and for a beta sheet it should be flat and periodic in two dimensions, with the unit cell info in the pdb (CRYST1 record) set correctly.&lt;/p&gt;&#xA;&lt;p&gt;If possible, I'd like to be able to make these structures programmatically, with any sequence of amino acids I want; the unit cell would just be made of a repeat of both the sequence and geometry.  Since swapping side chains is relatively easy, some pre-made infinite periodic systems of poly-alanine would be a good start.&lt;/p&gt;&#xA;&lt;p&gt;I know of a few tools which do &lt;em&gt;part&lt;/em&gt; of this:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PyMOL has the &lt;a href=&quot;https://pymolwiki.org/index.php/Builder&quot; rel=&quot;nofollow noreferrer&quot;&gt;Builder&lt;/a&gt; interface which allows making an idealized alpha helix or single strand of a beta sheet.  It doesn't seem to have the ability to make a whole beta sheet - I couldn't find a function that would put two strands next to each other in the right geometry.  It also doesn't seem to have any ability to get the right unit cell vectors.&lt;/li&gt;&#xA;&lt;li&gt;UCSF Chimera has the &lt;a href=&quot;https://www.cgl.ucsf.edu/chimera/docs/UsersGuide/midas/addaa.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;addaa command&lt;/a&gt; which also builds an alpha helix or single strand of a beta sheet.  Same issues - no way to put strands next to each other, and no unit cell.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Is there another tool which would do this out of the box?  If not, what's a good way to take what PyMOL or Chimera outputs and make it into a periodic system?&lt;/p&gt;&#xA;&lt;p&gt;P.S. Possibly tricky parts: if the periodicity of the helix can be described as a coordinate transform &lt;code&gt;M*x+v&lt;/code&gt; which can include rotation and translation, then any number of residues (including one) can form an infinite system.  But if the periodicity is made just using translations (a triclinic Bravais lattice), then it is necessary to find a way to reproduce an integer number of turns using a translation along the axis, which may not be always possible.  If a residue corresponds to exactly 100 degrees turn, then 36 residues = 3600 degrees = 10 turns, which would also repeat using translation.  But if not exactly 100 degrees (and not 360 times an integer fraction) it may not have an exact repeat at all.  Beta sheets are easier since they are already made by translation.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="5" LastEditDate="2023-12-11T06:03:41.167" LastActivityDate="2023-12-11T06:03:41.167" Title="How to make an idealized infinite alpha helix or beta sheet?" Tags="|software-recommendations|proteins|pymol|" AnswerCount="0" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9742" PostTypeId="1" AcceptedAnswerId="9749" CreationDate="2022-10-03T11:37:07.893" Score="4" ViewCount="237" Body="&lt;p&gt;I'm modelling molecules confined within porous materials and I was wondering which molecular properties would you consider to access the confinement.&lt;/p&gt;&#xA;&lt;p&gt;Í'm thinking about looking into long-range dispersion forces, the interaction energy, and the RMSD of MD runs. But I think other features might be more important.&lt;/p&gt;&#xA;" OwnerUserId="5923" LastEditorUserId="142" LastEditDate="2022-10-03T12:01:29.493" LastActivityDate="2022-10-03T19:13:30.043" Title="Which properties would you study to evaluate spatial confinement of a molecule" Tags="|solid-state-physics|configuration-interaction|materials-informatics|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9743" PostTypeId="1" AcceptedAnswerId="9779" CreationDate="2022-10-03T13:57:56.633" Score="4" ViewCount="236" Body="&lt;p&gt;My question is, if there is a way to continue an earlier FCI calculation in PySCF.&lt;/p&gt;&#xA;&lt;p&gt;Imagine you initially just need energies converged up to a certain threshold:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  cisolver = pyscf.fci.FCI(an_scf_object)&#xA;  cisolver.conv_tol = 1e-5&#xA;  e, fcivec = cisolver.kernel(verbose=5)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and later you decide that you need very accurate energies and CI vectors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  cisolver = pyscf.fci.FCI(an_scf_object)&#xA;  cisolver.conv_tol = 1e-9&#xA;  e, fcivec = cisolver.kernel(verbose=5)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What properties could you write down after the initial run in order to restart from there?&lt;/p&gt;&#xA;" OwnerUserId="5815" LastEditorUserId="5" LastEditDate="2023-01-05T02:26:32.037" LastActivityDate="2023-01-05T02:27:46.437" Title="Restarting an FCI calculation in PySCF" Tags="|python|pyscf|full-configuration-interaction|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9744" PostTypeId="2" ParentId="9325" CreationDate="2022-10-03T14:56:07.480" Score="7" Body="&lt;p&gt;The basic quantity you build when performing a phonon calculation is the matrix of force constants, given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{i\alpha,i^{\prime}\alpha^{\prime}}(\mathbf{R}_p,\mathbf{R}_{p^{\prime}})=\frac{\partial^2 E}{\partial u_{p\alpha i}\partial u_{p^{\prime}\alpha^{\prime}i^{\prime}}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the potential energy surface in which the nuclei move, &lt;span class=&quot;math-container&quot;&gt;$u_{p\alpha i}$&lt;/span&gt; is the displacement of atom &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; (of all atoms in the basis), in Cartesian direction &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;), and located in the cell within the supercell at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_p$&lt;/span&gt;. Mathematically speaking, this matrix of force constants is the Hessian matrix of the potential energy function &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;. As for any Hessian matrix, its eigenvalues give the curvature of the function &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; along the direction of the associated eigenvectors, and we can have:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Positive eigenvalue: the curvature is positive, which means that the function &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is a minimum along that direction.&lt;/li&gt;&#xA;&lt;li&gt;Negative eigenvalue: the curvature is negative, which means that the function &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is a maximum along that direction.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;To relate this to your question, note that the phonon frequencies are the &lt;em&gt;square root&lt;/em&gt; of the eigenvalues above, so positive eigenvalues give positive phonon frequencies and negative eigenvalues give imaginary phonon frequencies (your soft modes).&lt;/p&gt;&#xA;&lt;p&gt;This means that imaginary frequencies are associated with maxima of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, so that displacing that atoms along the corresponding eigenvectors will lower the energy (make &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; smaller). As a dynamically stable structure is one defined at a (local) minimum of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, then whenever you have imaginary frequencies you are not at a local minimum (you are at a saddle point), so the structure is unstable. By distorting the structure along the eigenvector associated with the imaginary mode, you will be able to find a lower energy structure.&lt;/p&gt;&#xA;&lt;p&gt;The addition of temperature can stabilize an otherwise unstable structure, but for that one needs to include anharmonic terms in the calculation (i.e. phonon-phonon interactions), so the harmonic calculations you are performing cannot resolve this question of stability at finite temperature.&lt;/p&gt;&#xA;" OwnerUserId="792" LastActivityDate="2022-10-03T14:56:07.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9745" PostTypeId="2" ParentId="4615" CreationDate="2022-10-03T16:59:01.740" Score="3" Body="&lt;p&gt;I recommend using the underlying function &lt;code&gt;ase.io.write()&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;from ase.build import bulk&#xA;&#xA;atoms = bulk('Ag')&#xA;ase.io.write('ag.xyz', atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using the function is more general because one could write a series of geometries to one file by providing a list of Atoms objects&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ase.io.write('ag.xyz', [atoms, atoms])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6085" LastEditorUserId="6085" LastEditDate="2022-10-03T19:06:11.107" LastActivityDate="2022-10-03T19:06:11.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9746" PostTypeId="2" ParentId="467" CreationDate="2022-10-03T17:12:31.987" Score="6" Body="&lt;h2&gt;3Dmol&lt;/h2&gt;&#xA;&lt;p&gt;3Dmol is rather easy to use &lt;a href=&quot;https://3dmol.csb.pitt.edu/&quot; rel=&quot;noreferrer&quot;&gt;https://3dmol.csb.pitt.edu/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is easy to use in web on Jupyter notebooks&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://william-dawson.github.io/using-py3dmol.html&quot; rel=&quot;noreferrer&quot;&gt;https://william-dawson.github.io/using-py3dmol.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://first-principle-tools.ew.r.appspot.com&quot; rel=&quot;noreferrer&quot;&gt;https://first-principle-tools.ew.r.appspot.com&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6085" LastEditorUserId="24" LastEditDate="2022-10-03T17:33:39.240" LastActivityDate="2022-10-03T17:33:39.240" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9747" PostTypeId="1" CreationDate="2022-10-03T17:21:30.813" Score="1" ViewCount="59" Body="&lt;p&gt;I'm just getting started with VESTA. SO I'm fairly new to it. Can anyone suggest me how to build a 2D structure of Silicon Carbide (SiC)? Or any documentation would also help.&#xA;Thanks .&lt;/p&gt;&#xA;" OwnerUserId="6086" LastActivityDate="2022-10-03T17:21:30.813" Title="How Can I Create a 2D Silicon Carbide Structure using VESTA" Tags="|density-functional-theory|quantum-espresso|band-structure|density-of-states|vesta|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-12T02:51:52.927" ContentLicense="CC BY-SA 4.0" />
  <row Id="9748" PostTypeId="2" ParentId="9742" CreationDate="2022-10-03T18:47:53.573" Score="3" Body="&lt;p&gt;The KS spectrum should change: the more confined is the molecule, the larger should be the HOMO-LUMO gap.&lt;/p&gt;&#xA;" OwnerUserId="6085" LastActivityDate="2022-10-03T18:47:53.573" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9749" PostTypeId="2" ParentId="9742" CreationDate="2022-10-03T19:13:30.043" Score="5" Body="&lt;p&gt;The vibrational properties of the molecule should change under confinement. You could compute IR spectra or more simply vibrational spectra of the molecule to probe this. The benefit of this is that you could compare this directly with experiments.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastActivityDate="2022-10-03T19:13:30.043" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9750" PostTypeId="1" CreationDate="2022-10-03T21:57:36.597" Score="6" ViewCount="106" Body="&lt;p&gt;I am aware that a standard way to build tight-binding models for realistic crystalline systems is by using the Maximally-localized Wannier Functions (MLWFs) as implemented in the Wannier90 Fortran code.&lt;/p&gt;&#xA;&lt;p&gt;My question is: what are the other methods used today in building tight-binding models for crystalline systems? I am interested in building minimal models (e.g. using 2 x 2 or 4 x 4 Bloch Hamiltonians, say). Can one use Wannier90 for this calculation? are there other better approaches?&lt;/p&gt;&#xA;&lt;p&gt;My main goal is to build minimal tight-binding models to study topological systems (e.g. topological insulators, superconductors etc.). I also would like to be able to build minimal tight-binding models for strongly-correlated system. Any suggestions will be appreciated&lt;/p&gt;&#xA;" OwnerDisplayName="user5405" LastEditorDisplayName="user5405" LastEditDate="2022-10-04T00:42:09.163" LastActivityDate="2022-10-04T00:42:09.163" Title="Methods to build tight-binding models for realistic materials" Tags="|density-functional-theory|reference-request|one-topic-per-answer|tight-binding|wannier90|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-12T02:50:14.660" ContentLicense="CC BY-SA 4.0" />
  <row Id="9751" PostTypeId="2" ParentId="9726" CreationDate="2022-10-03T23:49:52.277" Score="5" Body="&lt;p&gt;I don't think this is a statement about the particular tensors &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, this is a general result.&lt;/p&gt;&#xA;&lt;h4&gt;Tensors as sums of even and odd terms&lt;/h4&gt;&#xA;&lt;p&gt;Suppose we have a tensor &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;, and an operator &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; with eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\pm 1$&lt;/span&gt; (an &lt;em&gt;idempotent&lt;/em&gt; operator, e.g. a parity operator). We can always write:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;M &amp;amp;= M + \frac{1}{2}\left(\mathcal{T}M - \mathcal{T}M\right)\\&#xA;&amp;amp;= \frac{1}{2}\left[(M + \mathcal{T}M) + (M - \mathcal{T}M)\right] \tag 1&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Consider now the first term, &lt;span class=&quot;math-container&quot;&gt;$(M + \mathcal{T}M)$&lt;/span&gt;; if we apply &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; to it, we get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mathcal{T}(M + \mathcal{T}M) &amp;amp;= (\mathcal{T}M + \mathcal{T}^2M) \\&#xA;&amp;amp;= \mathcal{T}M +M \\&#xA;&amp;amp;= \left(M + \mathcal{T}M\right)  \tag 2&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;where we have used the fact that &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}^2=\mathrm{I}$&lt;/span&gt; (the identity), since it is idempotent; i.e. its eigenvalues are all +1 or -1, so the squared eigenvalues are all +1.&lt;/p&gt;&#xA;&lt;p&gt;Equation &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; shows that &lt;span class=&quot;math-container&quot;&gt;$(M + \mathcal{T}M)$&lt;/span&gt; is unchanged when we apply &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;, so this first term in equation &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-even.&lt;/p&gt;&#xA;&lt;p&gt;Now we repeat this for the second term in equation &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mathcal{T}(M - \mathcal{T}M) &amp;amp;= (\mathcal{T}M - \mathcal{T}^2M) \\&#xA;&amp;amp;= \mathcal{T}M -M\\&#xA;&amp;amp;= -\left(M - \mathcal{T}M\right). \tag 3&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;Now we see that applying &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; has resulted in &lt;em&gt;minus&lt;/em&gt; what we started with, and therefore this term is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-odd.&lt;/p&gt;&#xA;&lt;p&gt;Thus, equation &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; expresses the tensor &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; as a sum of a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-even and a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-odd tensor. At no point have we assumed anything about our tensor &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;, and so this expression holds generally.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;M &amp;amp;= \frac{1}{2}\left(M + \mathcal{T}M\right) + \frac{1}{2}\left(M - \mathcal{T}M)\right)\\&#xA;&amp;amp;= M^\mathrm{even} + M^\mathrm{odd} \tag 4&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h4&gt;When &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; &lt;em&gt;is&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-even or odd&lt;/h4&gt;&#xA;&lt;p&gt;If the tensor &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; &lt;em&gt;does&lt;/em&gt; have a particular &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry, then all that happens is that one of the terms in equation &lt;span class=&quot;math-container&quot;&gt;$(4)$&lt;/span&gt; is zero (i.e. either &lt;span class=&quot;math-container&quot;&gt;$M^\mathrm{even}=0$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$M^\mathrm{odd}=0$&lt;/span&gt;). For example, if &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-odd, then &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}M=-M$&lt;/span&gt; and we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;M^\mathrm{even} &amp;amp;= \frac{1}{2}\left(M + \mathcal{T}M\right) \\&#xA; &amp;amp;= \frac{1}{2}\left(M + (-M)\right) \\&#xA; &amp;amp;= 0;&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;and, correspondingly,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;M^\mathrm{odd} &amp;amp;= \frac{1}{2}\left(M - \mathcal{T}M\right) \\&#xA; &amp;amp;= \frac{1}{2}\left(M - (-M)\right) \\&#xA; &amp;amp;= \frac{1}{2}\left(2M\right) \\&#xA; &amp;amp;= M,&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;which is as expected, since in this example &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-odd!&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-10-04T12:36:28.567" LastActivityDate="2022-10-04T12:36:28.567" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9752" PostTypeId="2" ParentId="6412" CreationDate="2022-10-04T00:25:44.653" Score="3" Body="&lt;p&gt;The thirdorder program uses the symmetry library &amp;quot;spglib&amp;quot;, and needs its header files (files ending &lt;code&gt;.h&lt;/code&gt;). The error you're seeing is telling you that the compiler can't find these header files, probably because they haven't been installed on your machine.&lt;/p&gt;&#xA;&lt;p&gt;The files aren't usually installed if you just select the spglib library in your package manager, you will usually have to install the spglib &lt;em&gt;developer&lt;/em&gt; package; on Ubuntu, the relevant package is &lt;code&gt;libsymspg-dev&lt;/code&gt;. While you're installing it, it's worth getting the Python bindings as well, which is &lt;code&gt;python3-spglib&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-10-04T00:25:44.653" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9753" PostTypeId="2" ParentId="9529" CreationDate="2022-10-04T16:24:02.430" Score="3" Body="&lt;p&gt;One could do such a conversion online with &lt;a href=&quot;https://first-principle-tools.ew.r.appspot.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tool&lt;/a&gt;. The user could start uploading of an xyz file. After upload, an interactive ball-and-stick model is shown, the unit cell parameters are reported as well as the detected spacegroup symbol. Moreover, the conversion to popular formats is offered. Apart from the xyz format, many others are understood (pdb, cif, mol, sdf, etc). Here's the result:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HtoTO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HtoTO.png&quot; alt=&quot;Conversion of .xyz -&amp;gt; Gaussian format&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6085" LastEditorUserId="6085" LastEditDate="2022-10-09T08:02:41.650" LastActivityDate="2022-10-09T08:02:41.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9754" PostTypeId="1" CreationDate="2022-10-04T18:29:10.723" Score="3" ViewCount="67" Body="&lt;p&gt;Is there a software/standalone tool that can perform energy minimization of a large number of protein-dna complex models (more than 1000)?&lt;/p&gt;&#xA;&lt;p&gt;I know of GROMACS or Chimera or the online servers but is there a downloadable tool which I can use to minimize all the complexes and say for example, include in my script for further processing of said models?&lt;/p&gt;&#xA;" OwnerUserId="6092" LastEditorUserId="5" LastEditDate="2022-10-04T19:04:35.523" LastActivityDate="2023-07-11T23:06:05.730" Title="Perform energy minimization of multiple models of protein-dna complexes" Tags="|software-recommendations|gromacs|proteins|atomistic-simulation|chimera-software|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9756" PostTypeId="1" CreationDate="2022-10-05T05:15:16.833" Score="6" ViewCount="114" Body="&lt;p&gt;Let there be some ground-state N-electron species named A. A Dyson orbital for Q is defined as the overlap between Q and (Q with one electron removed). The extended Koopmans theorem &lt;a href=&quot;https://doi.org/10.1021/acs.jpclett.1c02494&quot; rel=&quot;nofollow noreferrer&quot;&gt;now states that&lt;/a&gt; the set of Dyson orbitals mathematically spans the same space as do the set of Natural Orbitals from &amp;quot;standard&amp;quot; correlated theories. Since it talks about the &amp;quot;set&amp;quot; of Dyson orbitals, there must be more than one Dyson orbital(w.l.o.g, since an one-electron system can be solved in closed form anyway). The Dyson HOMO(s) can now be defined as the overlap between (ground-state) A and the most stable electronic state(s) of A+. Everything is normal.&lt;/p&gt;&#xA;&lt;p&gt;The main ambiguity occurs when trying to define the Dyson HOMO-1(s). The most natural approach would be to define it(them) as the overlap between the most stable electronic state(s) of A+ and A(2+), resp. The paper supports this definition by discussing the &amp;quot;kth ionisation potential&amp;quot;, which cannot be determined by the latter method(vide infra).&lt;/p&gt;&#xA;&lt;p&gt;However, the paper, which I could not fully grasp, also seems to define the Dyson HOMO-1(s) as the overlap between ground-state A and (A with the second electron removed). Not only is this nonintuitive, this leads to a circular argument, as one needs to define what orbitals are in the first place to define what the &amp;quot;second electron&amp;quot; is. Defining the Dyson HOMO-1(s) as the overlap between A and (the second-lowest state(s) of A+) also leads to a problem; the paper explicitly discusses multiconfigurational states, for which the exact determination of &amp;quot;the second-lowest state(s)&amp;quot; itself is not straightforward.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- does the paper (vide infra) define Dyson orbitals in the former way or the latter way(s)?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="142" LastEditDate="2022-10-25T15:30:15.287" LastActivityDate="2022-10-25T15:30:15.287" Title="Basic but fundamental question on the extended Koopman theorem using Dyson orbitals" Tags="|computational-chemistry|orbitals|wavefunctions|explicitly-correlated-methods|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-10T16:59:54.587" ContentLicense="CC BY-SA 4.0" />
  <row Id="9757" PostTypeId="2" ParentId="9739" CreationDate="2022-10-05T11:22:12.313" Score="9" Body="&lt;p&gt;&lt;strong&gt;TL;DR: The statement &lt;span class=&quot;math-container&quot;&gt;$[H,S^2]=0$&lt;/span&gt; indeed holds for no-pair (i.e. without considering the production of electron-positron pairs) calculations of hydrogen-like ions, but not for general atoms and molecules. It also fails when the creation of electron-positron pairs is considered.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A hydrogen-like ion has only one electron, so all scalar states of a hydrogen-like ion must be doublet. The (no-pair) spin-orbit interaction, which mixes different scalar states but does not create new electrons, thus invariably leads to pure doublet states, so &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; commutes with &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; because the latter is a constant operator within the Hilbert space studied.&lt;/p&gt;&#xA;&lt;p&gt;The situation changes when the full Dirac equation is solved (EDIT: when not only the full Dirac equation is solved, but also you take into account the Dirac sea), where you'll have additional states with e.g. two electrons and one positron, which can potentially constitute a quartet state. These quartet states may then mix with the one-electron doublet states, giving states that are not eigenstates of &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt;. But of course, these quartet states are ~1 MeV above the ground state, so their mixings into the ground state are negligible, except possibly for ultra high-precision spectroscopies. (EDIT: when you solve the full Dirac equation for a hydrogenic ion but assume that all the negative energy states are empty, you should still get &lt;span class=&quot;math-container&quot;&gt;$[H,S^2]=0$&lt;/span&gt;, for the same reason as above: the use of the Dirac equation does not change the fact that the electron spin is exactly 1/2, and since there is only one electron, all the Dirac eigenstates must be pure doublets.)&lt;/p&gt;&#xA;&lt;p&gt;Even more importantly, &lt;span class=&quot;math-container&quot;&gt;$[H,S^2]=0$&lt;/span&gt; fails for multi-electron systems even under the no-pair approximation, and in this case the violation should be orders of magnitudes larger than the one found in the hydrogen atom. This is because we can now construct scalar states of different multiplicities even without creating electron-positron pairs. Now the scalar states are at best only a few eVs (frequently just a fraction of an eV) apart, so their mixings are sufficiently large to have observable consequences even without the aid of high-precision spectrometry, like spin-forbidden reactions, intersystem crossing and phosphorescence.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-10-05T20:00:18.007" LastActivityDate="2022-10-05T20:00:18.007" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9758" PostTypeId="1" CreationDate="2022-10-05T15:05:17.700" Score="4" ViewCount="118" Body="&lt;p&gt;I'm trying to learn molecular &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_functional_theory#Classical_density_functional_theory&quot; rel=&quot;nofollow noreferrer&quot;&gt;classical DFT&lt;/a&gt; to model the adsorption of gases, particularly cryogenic hydrogen, in carbonaceous microporous solids. I'm totally new to this, just starting my thesis.&lt;/p&gt;&#xA;&lt;p&gt;Do you think classical DFT is applicable for low temperature hydrogen? I originally thought about cryogenic hydrogen so about 30-70 K. But now that seems difficult.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Basically what I'm trying to simulate is hydrogen adsorption in carbonaceous solids, ideally at cryogenic temperatures. Since I'm just starting my Chemical Engineering Thesis I'm trying to do a basic approach via DFT (because that's what I've mostly seen in papers) and then add corrections , like I said I don't know about all the different theories that can be used for this. For example, &lt;a href=&quot;https://doi.org/10.1016/j.ces.2021.116905&quot; rel=&quot;nofollow noreferrer&quot;&gt;this is the paper&lt;/a&gt; that I'm currently trying to follow, but sadly they only simulate CO2 and CH4 in fairly normal conditions, hence my question.&lt;/p&gt;&#xA;&lt;p&gt;Do you have any recommendations on how to approach this? &lt;/p&gt;&#xA;&lt;p&gt;I'm adamant on using DFT because my guiding professor knows quite a bit about it and I hope he can guide my through this theory.&lt;/p&gt;&#xA;" OwnerUserId="6095" LastEditorUserId="5" LastEditDate="2022-10-07T20:28:05.513" LastActivityDate="2022-10-07T20:28:05.513" Title="How to get started with Classical Density Functional Theory?" Tags="|density-functional-theory|cdft|" AnswerCount="0" CommentCount="7" ClosedDate="2023-06-12T02:52:50.447" ContentLicense="CC BY-SA 4.0" />
  <row Id="9759" PostTypeId="1" CreationDate="2022-10-06T00:24:41.167" Score="7" ViewCount="224" Body="&lt;p&gt;For example: &lt;code&gt;gto.basis.load(&amp;quot;6-31g&amp;quot;, &amp;quot;Li&amp;quot;)&lt;/code&gt; will show:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[0,&#xA;  [642.41892, 0.0021426],&#xA;  [96.798515, 0.0162089],&#xA;  [22.091121, 0.0773156],&#xA;  [6.2010703, 0.245786],&#xA;  [1.9351177, 0.470189],&#xA;  [0.6367358, 0.3454708]],&#xA; [0, [2.3249184, -0.0350917], [0.6324306, -0.1912328], [0.0790534, 1.0839878]],&#xA; [0, [0.035962, 1.0]],&#xA; [1, [2.3249184, 0.0089415], [0.6324306, 0.1410095], [0.0790534, 0.9453637]],&#xA; [1, [0.035962, 1.0]]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is a list with 5 elements (which are also lists). The first element of each of these 5 lists represents angular momentum. In this example, there are 3 lists starting with a 0; how does pyscf determine if the list of &lt;code&gt;[exponent, coefficient]&lt;/code&gt; that follow are for the 1s or 2s orbitals?&lt;/p&gt;&#xA;" OwnerUserId="5435" LastActivityDate="2022-10-07T10:58:03.540" Title="How does pyscf's internal basis format distinguish between 1s and 2s orbitals?" Tags="|basis-sets|pyscf|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9760" PostTypeId="2" ParentId="9759" CreationDate="2022-10-06T03:11:16.497" Score="5" Body="&lt;p&gt;The difference between &amp;quot;S&amp;quot; and &amp;quot;P&amp;quot; is quite significant in that S-type basis functions have a different mathematical form compared to P-type functions (and therefore the shapes of these functions are fundamentally different), but the difference between the &amp;quot;1&amp;quot; and the &amp;quot;2&amp;quot; is not as significant: The 1 just denotes the first orbital of a particular type, whereas the 2 denotes the next one.&lt;/p&gt;&#xA;&lt;p&gt;So which orbital is labeled with a 1 and which one is labeled with a 2? If you need to label the orbitals numerically like this, what would make the most sense is to label them in a way consistent with the way everyone learns about orbitals starting from high school and early-undergraduate-level chemistry classes: the 1s orbital is closest to the nucleus, the 2s is further out, etc.&lt;/p&gt;&#xA;&lt;p&gt;Usually basis sets are presented with the S-type orbital values appearing in order, so the first number you see is for the 1s, the second is for the 2s, etc. This happens to be true for the basis set in your question. But in case you doubted that the basis set was presented &amp;quot;in order&amp;quot; like this, you can look at the size of the exponents. &lt;code&gt;642.41892&lt;/code&gt; is much larger than &lt;code&gt;96.798515&lt;/code&gt;, so if you were to plot the corresponding two basis functions, you'd find the first one to resemble the &amp;quot;1s&amp;quot; vs the one with the smaller number representing the &amp;quot;2s&amp;quot; orbital.&lt;/p&gt;&#xA;&lt;p&gt;For the record I'll put the basis set from your question in ACESII/CFOUR/MRCC format below, since it's less confusing (at least to me), and also because the numbers in your version seem to be truncated, which would cause you to get energies inconsistent with other 6-31G calculations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    LI:6-31G&#xA;    6-31G valence double-zeta&#xA;    &#xA;      2&#xA;        0    1&#xA;        3    2&#xA;       10    4&#xA;    &#xA;    0.6424189150D+03 0.9679851530D+02 0.2209112120D+02 0.6201070250D+01 0.2324918408D+01 &#xA;    0.1935117680D+01 0.6367357890D+00 0.6324303556D+00 0.7905343475D-01 0.3596197175D-01 &#xA;    &#xA;    0.2142607810D-02 0.00000000       0.00000000 &#xA;    0.1620887150D-01 0.00000000       0.00000000 &#xA;    0.7731557250D-01 0.00000000       0.00000000 &#xA;    0.2457860520D+00 0.00000000       0.00000000 &#xA;    0.00000000      -0.3509174574D-01 0.00000000 &#xA;    0.4701890040D+00 0.00000000       0.00000000 &#xA;    0.3454708450D+00 0.00000000       0.00000000 &#xA;    0.00000000      -0.1912328431D+00 0.00000000 &#xA;    0.00000000       0.1083987795D+01 0.00000000 &#xA;    0.00000000       0.00000000       0.1000000000D+01 &#xA;    &#xA;    0.2324918408D+01 0.6324303556D+00 0.7905343475D-01 0.3596197175D-01 &#xA;    &#xA;    0.8941508043D-02 0.00000000 &#xA;    0.1410094640D+00 0.00000000 &#xA;    0.9453636953D+00 0.00000000 &#xA;    0.00000000       0.1000000000D+01 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-10-06T03:11:16.497" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9761" PostTypeId="1" AcceptedAnswerId="11084" CreationDate="2022-10-06T17:31:43.340" Score="4" ViewCount="93" Body="&lt;p&gt;I have one query about data obtained in the optical calculation (absorption coefficient) using GGA. The output came in the format energy xx yy zz xy yz zx for bulk system. I have seen in the literature while showing for absorption coefficient, only two components E||a, and E||c have been shown. In my case, how I can decide which component is a or c. I potted xx yy and zz components separately. All three show different absorption peaks. Please suggest the correct way of representing it. I am not aware of the format obtained in the output.&#xA;Please see Fig.6 in the attached reference.&#xA;&lt;a href=&quot;https://www.nature.com/articles/srep07131&quot; rel=&quot;noreferrer&quot;&gt;https://www.nature.com/articles/srep07131&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5256" LastActivityDate="2023-06-11T16:52:58.753" Title="Query about optical absorption spectra" Tags="|density-functional-theory|vasp|optical-properties|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9763" PostTypeId="2" ParentId="9759" CreationDate="2022-10-07T10:58:03.540" Score="6" Body="&lt;p&gt;There is no distinction of any basis functions in PySCF. Basis functions are just that: basis functions, a mathematical abstraction. The individual basis functions do not have to represent orbitals; all that matters is the span of the basis set. The 1s and 2s orbitals in atoms, for instance, will be variationally found by optimizing the self-consistent field energy in the defined basis set.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-07T10:58:03.540" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9764" PostTypeId="1" CreationDate="2022-10-07T19:52:03.003" Score="8" ViewCount="213" Body="&lt;p&gt;I switched to using OpenMM recently and have got up and running without too much of a learning curve.&lt;/p&gt;&#xA;&lt;p&gt;My general workflow is as follows, using a cloud based GPU to actually run the simulation:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Prepare the protein (cap, fill missing loops etc)&lt;/li&gt;&#xA;&lt;li&gt;Set up the system (fill box with water, neutralise and add ‘salt’)&lt;/li&gt;&#xA;&lt;li&gt;Run MD&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If the protein has a ligand, it’s straightforward to parametrise and generate a forcefield for this.&lt;/p&gt;&#xA;&lt;p&gt;What I’m unable to find info about is running a mixed solvent /cryptic pocket type experiment (where for example there is a certain % of a probe such as benzene).  In other tools I’ve used previously there are functions to do this and randomly place the probe similar to how ions are placed,  but I find no info about this in the OpenMM documentation.&lt;/p&gt;&#xA;&lt;p&gt;Adding x molecules of probe psuedo- randomly does not seem prudent&lt;/p&gt;&#xA;" OwnerUserId="6104" LastEditorUserId="5" LastEditDate="2022-10-07T20:27:26.950" LastActivityDate="2023-05-01T16:40:29.617" Title="Mixed Solvent MD using OpenMM" Tags="|molecular-dynamics|molecular-mechanics|graphical-processing-unit|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-12T14:47:52.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="9765" PostTypeId="1" CreationDate="2022-10-07T19:54:09.947" Score="6" ViewCount="319" Body="&lt;p&gt;I would like to know available software that can do Molecular Dynamics (MD) simulations for any type of system, specifically inorganic and organic ones.&lt;/p&gt;&#xA;&lt;p&gt;The must cited MD packages (GROMACS, AMBER, GROMOS, NAMD, DESMOND) are dedicated to biological systems (protein, membranes, etc.).&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2022-10-07T20:25:38.267" LastActivityDate="2022-10-08T09:45:30.507" Title="Software for Molecular Dynamics in Material Science" Tags="|molecular-dynamics|software-recommendations|one-topic-per-answer|physical-properties-of-materials|amorphous-materials|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9766" PostTypeId="1" CreationDate="2022-10-07T19:58:15.143" Score="6" ViewCount="487" Body="&lt;p&gt;Searching the LAMMPS site, I found some software capable to prepare LAMMPS inputs but they are not free and other software to analyze the output.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know other package (with Graphical User Interface) capable to prepare the input files in order to run a molecular dynamics simulation using LAMMPS.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2022-10-07T20:25:03.153" LastActivityDate="2023-03-03T08:58:04.443" Title="Free Graphical User Interface to prepare inputs for LAMMPS" Tags="|molecular-dynamics|software-recommendations|lammps|graphical-user-interface|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9767" PostTypeId="2" ParentId="9765" CreationDate="2022-10-07T22:23:44.973" Score="9" Body="&lt;p&gt;Looking at &lt;a href=&quot;https://atomistic.software/#/&quot; rel=&quot;noreferrer&quot;&gt;atomistic.software&lt;/a&gt; and filtering engines that provide force fields, the top-cited packages missing from your list are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://lammps.sandia.gov/&quot; rel=&quot;noreferrer&quot;&gt;LAMMPS&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Discovery_Studio&quot; rel=&quot;noreferrer&quot;&gt;Discovery Studio&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.chemcomp.com/&quot; rel=&quot;noreferrer&quot;&gt;MOE&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.charmm.org/&quot; rel=&quot;noreferrer&quot;&gt;CHARMM&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://openmopac.net/&quot; rel=&quot;noreferrer&quot;&gt;MOPAC&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.cp2k.org/&quot; rel=&quot;noreferrer&quot;&gt;CP2K&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;LAMMPS is the most obvious omission, and it can certainly be used for inorganic and organic systems. CP2K can be interesting if you're planning to switch between force fields, semi-empirical methods and density-functional theory. [1]&lt;/p&gt;&#xA;&lt;p&gt;I have no experience with the other packages, but perhaps worth having a look.&lt;/p&gt;&#xA;&lt;p&gt;[1] P.S. CP2K has recently been used to perform &lt;a href=&quot;http://arxiv.org/abs/2104.08245&quot; rel=&quot;noreferrer&quot;&gt;molecular-dynamics of HIV-1 in solution (62.5M atoms)&lt;/a&gt; on the JUWELS HPC system using the semi-empirical xTB method.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2022-10-08T09:45:30.507" LastActivityDate="2022-10-08T09:45:30.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9768" PostTypeId="1" CreationDate="2022-10-08T12:07:40.060" Score="3" ViewCount="88" Body="&lt;p&gt;The low-energy effective model for Weyl semimetals (WSM) at a single Weyl point can be written as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H_{w}=\chi \vec{k} \cdot \vec{\sigma}, \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; is the chirality index, &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; is the crystal momentum, and &lt;span class=&quot;math-container&quot;&gt;$\vec{\sigma}$&lt;/span&gt; is the vector of Pauli matrices. The symmetry behavior for &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$\vec{\sigma}$&lt;/span&gt; under time-reversal (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;) and inversion (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;) operations is well-known:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}\vec{\sigma}=-\vec{\sigma}; \mathcal{T}\vec{k}=-\vec{k}$&lt;/span&gt;;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\vec{\sigma}=+\vec{\sigma}; \mathcal{P}\vec{k}=-\vec{k}$&lt;/span&gt;;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;On the other hand, the Weyl semimetal can be classified as nonmagnetic and magnetic ones. Consider the first one, the system respects &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; but breaks &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; (we assume there is a total of four Weyl points), we can conclude that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{T}\chi=\chi \tag{2}$$&lt;/span&gt;&#xA;For the second case, the system respects &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; but breaks &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; (we assume there is a total of two Weyl points), we can conclude that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{P}\chi=-\chi \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Eq.(2) and Eq.(3) are correct? If not, how Eq.(1) can be used to describe the magnetic and nonmagnetic WSMs simultaneously?&#xA;Or how does the low-energy model by considering all possible Weyl points respect the original symmetry that the system holds?&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="1218" LastEditDate="2022-10-13T02:40:34.450" LastActivityDate="2023-06-16T02:43:28.520" Title="Symmetry for the low-energy effective model of Weyl semimetal" Tags="|condensed-matter|symmetry|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9769" PostTypeId="1" CreationDate="2022-10-08T12:34:31.830" Score="2" ViewCount="37" Body="&lt;p&gt;This is quite surprising, at least for me, that many papers performed molecular docking of an unsimulated (original) protein structure and MD simulation of a protein in a timescale to check the stability of the protein structure but none of them performed molecular docking of a simulated protein structure, let alone the MD of protein-ligand after the docking process from previous simulated one. Is this a novel idea &lt;strong&gt;or some research labs have already made it on this case?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5771" LastEditorUserId="5" LastEditDate="2023-06-11T16:54:51.887" LastActivityDate="2023-06-11T16:54:51.887" Title="Literature applying molecular docking into MD-simulated structures of proteins" Tags="|molecular-dynamics|reference-request|docking|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9770" PostTypeId="1" CreationDate="2022-10-08T18:20:56.720" Score="5" ViewCount="79" Body="&lt;p&gt;I am trying to load my MD trajectory to postprocess the velocities. Although I use the same exact script on the &lt;a href=&quot;http://openpathsampling.org/latest/index.html&quot; rel=&quot;noreferrer&quot;&gt;OPS website&lt;/a&gt;, I get the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;trajectory_from_mdtraj requires simtk.unit, which is not installed&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried to pip install simtk which didn't solve the issue. Any suggestion would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="6115" LastActivityDate="2022-10-10T12:46:52.840" Title="trajectory_from_mdtraj requires simtk.unit, which is not installed" Tags="|python|openpathsampling|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9772" PostTypeId="1" AcceptedAnswerId="9776" CreationDate="2022-10-09T07:47:21.897" Score="4" ViewCount="335" Body="&lt;p&gt;I wish to know whether someone here was able to install Gaussian16 on Mac computer with ARM processor? According to the instructions, UNIX environment variables shall be added either to tcsh or bash shell UNIX files. On M1/M2 Macs, however, ZSH is default one. I know that .zshenv equivalent to .bash_profile, but the variables installation instruction tells to export are taken from the Gaussian-written g16.login (tcsh) or g16.profile (bash) files, so they won't import to ZSH.&lt;/p&gt;&#xA;&lt;p&gt;Regarding th second part of the question. I managed to install just Gaussian Utilities and run GaussView6. Unfortunately, I find all the text to be blurred. This is very unpleasant feeling, exhausting for longer time work, and while in the previous MacOS versions there was an option to turn off font smoothing, it is no more in MacOS Monterey (in any other program the font is perfectly fine!)&lt;/p&gt;&#xA;&lt;p&gt;I have sent email to Gaussian Inc. few weeks ago but still no answer...&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2022-10-10T11:58:48.503" Title="How to install pre-compiled Gaussian16 (Rev.A.03) and blurred font of GaussView6 on ARM Mac" Tags="|computational-chemistry|quantum-chemistry|gaussian|apple-operating-system|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9773" PostTypeId="1" CreationDate="2022-10-09T09:17:43.503" Score="4" ViewCount="157" Body="&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.69.235206&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, the authors discuss the three response relations or Ohm's law for spin/charge transport. The first one is the spin Hall effect described by:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$J_j^i=\sigma_{s}\epsilon_{ijk}E_k \tag{1},$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$J_j^i$&lt;/span&gt; is the current of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th component of the spin along&#xA;the direction &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{ijk}$&lt;/span&gt; is the totally antisymmetric tensor in&#xA;three dimensions and &lt;span class=&quot;math-container&quot;&gt;$E_k$&lt;/span&gt; is the applied electric field. The authors argue that Eq.(1) offers a kind of dissipationless transport by:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;However, unlike Ohm’s law, this fundamental response equation Eq.(1) describes a&#xA;purely topological and dissipationless spin current. It is important to note here that the spin current is even under the&#xA;time-reversal operation &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;. When the direction of the arrow of&#xA;time is reversed, both the direction of the current and the&#xA;spin are reversed and the spin current remains unchanged.&#xA;Since both the spin current and the electric field in Eq. (1)&#xA;are even under time reversal &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;, the transport coefficient &lt;span class=&quot;math-container&quot;&gt;$\sigma_s$&lt;/span&gt; is&#xA;called “reactive” and can be purely nondissipative. This is in sharp contrast to Ohm’s law&#xA;&lt;span class=&quot;math-container&quot;&gt;$$J_i=\sigma E_i$$&lt;/span&gt;&#xA;relating the charge current &lt;span class=&quot;math-container&quot;&gt;$J_i$&lt;/span&gt; to the electric field &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt;. In this case,&#xA;the charge current &lt;span class=&quot;math-container&quot;&gt;$J_i$&lt;/span&gt; changes sign under time reversal &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;,&#xA;while the electric field is even under &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;. Since Ohm’s law&#xA;relates quantities of different symmetries under time reversal&#xA;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;, the charge conductivity &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; breaks the time-reversal symmetry and describes the inevitable joule heating and dissipation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The second one is the quantum Hall effect with the following Ohm's law:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$J_i=\sigma_{H}\epsilon_{ij}E_j \tag{2}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\sigma_H \propto \vec{B}$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\vec{B}$&lt;/span&gt; the magnetic field. The authors argue that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Quantum Hall current, which is transverse to the electric field and dissipationless, has a feature similar to Eq.&#xA;(1), but the time-reversal symmetry is compensated by the&#xA;external magnetic field.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The final case is:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Dissipationless current without time-reversal symmetry breaking is extremely important and fundamental in solid-state physics, the most celebrated example&#xA;of which is the superconducting current. It is described by&#xA;the London equation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$J_i=\rho_s A_i, \quad E_i=\partial_t A_i, \quad (e=m=c=1) \tag{3}$$&lt;/span&gt;&#xA;where the current &lt;span class=&quot;math-container&quot;&gt;$J_i$&lt;/span&gt; is related to the vector potential &lt;span class=&quot;math-container&quot;&gt;$A_i$&lt;/span&gt; instead of the electric field. In the London equation, both &lt;span class=&quot;math-container&quot;&gt;$J_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A_i$&lt;/span&gt; are odd under time reversal &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;, therefore, the transport coefficient &lt;span class=&quot;math-container&quot;&gt;$\rho_s$&lt;/span&gt; also called the superfluid density, describes the reversible and dissipationless flow of the supercurrent.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;By studying the three cases, I have the following question:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If the system respects time-reversal symmetry, does the T-even anti-symmetric conductivity tensor indicate a dissipationless transport?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2023-06-11T16:56:57.647" LastActivityDate="2023-06-11T16:56:57.647" Title="If the system respects time-reversal symmetry, does the T-even anti-symmetric conductivity tensor indicate a dissipationless transport?" Tags="|condensed-matter|symmetry|transport|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9774" PostTypeId="2" ParentId="9739" CreationDate="2022-10-10T05:10:16.527" Score="-3" Body="&lt;p&gt;Inspired by wzkchem5's answer, I tried to figure out some formulae on my own (I still think Dirac sea &lt;span class=&quot;math-container&quot;&gt;$\neq$&lt;/span&gt; QFT, but the latter issue will be beyond the scope of this question)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;There is one mistake in my question, for the exact solution of the Dirac equation of the hydrogen atom (without any pair production), &lt;span class=&quot;math-container&quot;&gt;$[H, S^2]= 0$&lt;/span&gt;. Since one may construct &lt;span class=&quot;math-container&quot;&gt;$S^2 :=  \Sigma^2 = \begin{bmatrix} \sigma^2 &amp;amp;0\\0&amp;amp;\sigma^2\end{bmatrix} = 3 \mathbf{I}_{4\times4} $&lt;/span&gt;, which would commute with the Hamiltonian. Here &lt;span class=&quot;math-container&quot;&gt;$  \Sigma_p:= \begin{bmatrix} \sigma_p &amp;amp;0\\0&amp;amp; \sigma_p \end{bmatrix}  $&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p=x,y,z$&lt;/span&gt;. The notation of &lt;span class=&quot;math-container&quot;&gt;$S^2$&lt;/span&gt; may not be standard here, since it is commonly denoted to 2-component Pauli matrices directly.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Concerning many-electron systems, the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{S}^2$&lt;/span&gt; may be constructed as &lt;span class=&quot;math-container&quot;&gt;$ \left( \sum_i \mathbf{S}_i \right)^2 $&lt;/span&gt; and the spin-orbit term may be written  as &lt;span class=&quot;math-container&quot;&gt;$ \mathbf{\Sigma}_i \cdot \mathbf{L}_i = \mathbf{S}_i \cdot \mathbf{L}_i$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$i=1,2,\cdots N_e$&lt;/span&gt; (&lt;a href=&quot;https://arxiv.org/pdf/1306.0479.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/1306.0479.pdf&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Here is the thing,&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$  \mathbf{S}^2 = \sum_i \mathbf{S}_i^2 + 2 \sum_{i \neq j} \mathbf{S}_i \cdot \mathbf{S}_j \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first term at the right-hand side of the above equation will commute with the spin-orbit coupling, not the second. Take a two-electron system for example,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \sum_{pq} 2 [S_1^p S_2^p, S_1^q L_1^q + S_2^q L_2^q]\ \,\,\,\,\,\, p,q, =x,y,z\tag{2}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2 \sum_{pq}  [S_1^p,S_1^q]  S_2^p L_1^q +  [S_2^p,S_2^q]  S_1^p L_2^q  \tag{3}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2i \sum_{pq}  \varepsilon_{pqr} S_1^r S_2^p L_1^q  +   \varepsilon_{pqr}  S_2^r S_1^p L_2^q  \tag{4}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2i \sum_{pq}  \varepsilon_{pqr} S_1^r S_2^p L_1^q  +   \varepsilon_{pqr}  S_1^p S_2^r  L_2^q  \tag{5}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2i \sum_{pq}  \varepsilon_{pqr} S_1^r S_2^p L_1^q  +   \varepsilon_{rqp}  S_1^r S_2^p  L_2^q  \tag{6}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2i \sum_{pq}  \varepsilon_{pqr} S_1^r S_2^p L_1^q -   \varepsilon_{pqr}  S_1^r S_2^p  L_2^q  \tag{7}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;= 2i \sum_{pq}  \varepsilon_{pqr} S_1^r S_2^p \left( L_1^q  -  L_2^q  \right)\tag{8}&#xA;$$&lt;/span&gt;&#xA;which is not zero in general. Hopefully that's right.&lt;/p&gt;&#xA;" OwnerUserId="6061" LastEditorUserId="5" LastEditDate="2022-10-12T03:30:25.480" LastActivityDate="2022-10-12T03:30:25.480" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9776" PostTypeId="2" ParentId="9772" CreationDate="2022-10-10T11:58:48.503" Score="3" Body="&lt;p&gt;Solution was to change shell to bash for the installation and then, if one wants, may return to zsh. I did and this didn't affect G16. It is still working.&#xA;Regarding blurred font, I forward answer from reddit user geoffth2016:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This is because GaussView is not set to run in high resolution. So macOS is doing its best to display a low-resolution font. Naturally that's blurry on your high-dpi screen. In the Finder, go to the app, right-click or control-click to bring up &amp;quot;Show Package Contents&amp;quot;. Go into the Contents folder and there should be an &amp;quot;Info.plist&amp;quot; file. You can open this in Xcode or any text editor (probably easier). There should be a bunch of properties, like: (This is for Avogadro, not GaussView, but they should be very similar.)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;        &amp;lt;key&amp;gt;LSMinimumSystemVersion&amp;lt;/key&amp;gt;&#xA;        &amp;lt;string&amp;gt;10.8.0&amp;lt;/string&amp;gt;&#xA;        &amp;lt;key&amp;gt;CFBundleDevelopmentRegion&amp;lt;/key&amp;gt;&#xA;        &amp;lt;string&amp;gt;English&amp;lt;/string&amp;gt;&#xA;        &amp;lt;key&amp;gt;CFBundleDisplayName&amp;lt;/key&amp;gt;&#xA;        &amp;lt;string&amp;gt;Avogadro&amp;lt;/string&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;You want to add:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;        &amp;lt;key&amp;gt;NSHighResolutionCapable&amp;lt;/key&amp;gt;&#xA;        &amp;lt;string&amp;gt;True&amp;lt;/string&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;You should now get high-resolution fonts.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2022-10-10T11:58:48.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9777" PostTypeId="2" ParentId="9770" CreationDate="2022-10-10T12:46:52.840" Score="3" Body="&lt;p&gt;The error message here is out of date -- &lt;code&gt;simtk.unit&lt;/code&gt; was renamed to &lt;code&gt;openmm.unit&lt;/code&gt; by the OpenMM maintainers. So this really means that you don't have OpenMM installed on your system. (Error message will be fixed in &lt;a href=&quot;https://github.com/openpathsampling/openpathsampling/pull/1122&quot; rel=&quot;nofollow noreferrer&quot;&gt;this pull request&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;If you're not planning to use OpenMM for dynamics, then you probably want to load a trajectory using something like the solution in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/6974/2004&quot;&gt;this answer&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you &lt;em&gt;are&lt;/em&gt; planning to use OpenMM for dynamics (as the examples do), then you'll definitely want to install OpenMM! You can do that with &lt;code&gt;conda install -c conda-forge openmm&lt;/code&gt;. Note that OpenMM can not (yet) be installed with &lt;code&gt;pip&lt;/code&gt;. You can see other optional installations that are supported by OPS in the docs on &lt;a href=&quot;http://openpathsampling.org/latest/install.html#integration-with-other-packages&quot; rel=&quot;nofollow noreferrer&quot;&gt;integration with other packages&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastActivityDate="2022-10-10T12:46:52.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9778" PostTypeId="1" CreationDate="2022-10-10T16:30:54.580" Score="4" ViewCount="119" Body="&lt;p&gt;Lets' say I have a solid nanomaterial made with &lt;em&gt;N&lt;/em&gt; atoms in a simulation box with a volume of &lt;em&gt;V&lt;/em&gt; as shown below. In this case, the number density of my material is simply &lt;span class=&quot;math-container&quot;&gt;$\frac{N}{Volume\; of \; occupied\;3D\; space}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6MhmE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6MhmE.png&quot; alt=&quot;Solid Sphere&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;but what if I have a nanomaterial with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms in the same simulation box, but &lt;span class=&quot;math-container&quot;&gt;$N_{1}$&lt;/span&gt; atoms are in the solid phase and &lt;span class=&quot;math-container&quot;&gt;$N_{2}$&lt;/span&gt; atoms are in the gas phase &lt;span class=&quot;math-container&quot;&gt;$\left( N_{1} + N_{2} = N \right)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ssyUF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ssyUF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How should I calculate the number density of my material in this case? Do I consider the whole box volume &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;? do I have to find an average over the whole material?&lt;/p&gt;&#xA;" OwnerUserId="605" LastEditorUserId="605" LastEditDate="2022-10-18T04:53:51.887" LastActivityDate="2022-10-18T04:53:51.887" Title="How do I define the density of system?" Tags="|molecular-dynamics|statistical-thermodynamics|thermodynamics|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-09T22:48:30.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="9779" PostTypeId="2" ParentId="9743" CreationDate="2022-10-11T10:35:40.043" Score="5" Body="&lt;p&gt;What you can do, is save the CI vector of your calculation and then use it as  starting point in a subsequent calculation, like so:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;e, c = cisolver.kernel(verbose=5,ci0=c0) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where c0 is a numpy array containing the solution of another run.&#xA;I tested this for carbon in a STO-3G basis. First ran to a convergence of &lt;code&gt;1e-5&lt;/code&gt;, saved the vector, then converged with saved vector to &lt;code&gt;1e-9&lt;/code&gt;. This I compared to a run from scratch which was converged to &lt;code&gt;1e-9&lt;/code&gt;. The continuation took 4.15s to converge while the calculation from scratch took 5.21s.&lt;/p&gt;&#xA;" OwnerUserId="5837" LastEditorUserId="5" LastEditDate="2023-01-05T02:27:46.437" LastActivityDate="2023-01-05T02:27:46.437" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9780" PostTypeId="2" ParentId="3899" CreationDate="2022-10-12T03:51:11.810" Score="6" Body="&lt;p&gt;For those looking for random packing, I suggest you look at &lt;a href=&quot;https://github.com/VasiliBaranov/packing-generation&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/VasiliBaranov/packing-generation&lt;/a&gt; (I am not affiliated).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It supports the Lubachevsky–Stillinger, Jodrey–Tory, and force-biased generation algorithms; it can calculate the particle insertion probability, Steinhardt Q6 global and local order measures, coordination numbers for non-rattler particles, pair correlation function, structure factor, and reduced pressure after pressure equilibration. It doesn't require any preinstalled libraries and is multiplatform (Windows/nix).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In particular, there is the &lt;code&gt;-lsgd&lt;/code&gt; flag:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;-lsgd: Lubachevsky–Stillinger with gradual densification: the LS generation is run until the non-equilibrium reduced pressure is high enough (e.g., a conventional value of 1e12), then compression rate is decreased (devided by 2) and the LS generation is run again, until the pressure is high enough again; this procedure is repeated until the compression rate is low enough (1e-4). See Baranau and Tallarek (2014) Random-close packing limits for monodisperse and polydisperse hard spheres, doi:10.1039/C3SM52959B.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can specify an arbitrary particle size distribution by specifying the diameter of each particle, and you can also specify the initial locations of the particles if you prefer that over random location assignment. The code takes some fiddling with the diameters for post-processing, and it seems best in terms of time/performance tradeoff if you run certain algorithms in succession (&lt;code&gt;-fba&lt;/code&gt;, then &lt;code&gt;-ls&lt;/code&gt;, then &lt;code&gt;-lsgd&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I put together a Jupyter notebook that should run a random hard sphere packing simulation to completion.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://colab.research.google.com/gist/sgbaird/4168b7b3fcc97ec0891776e948a8b56f/packing-generation.ipynb&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://colab.research.google.com/assets/colab-badge.svg&quot; alt=&quot;Open In Colab&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1371" LastActivityDate="2022-10-12T03:51:11.810" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9781" PostTypeId="1" CreationDate="2022-10-12T06:51:48.877" Score="0" ViewCount="40" Body="&lt;p&gt;This question is related to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9739/how-spin-orbit-coupling-makes-spin-forbidden-reactions-possible&quot;&gt;How spin-orbit coupling makes spin-forbidden reactions possible? - Matter Modeling Stack Exchange&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Even more importantly, [H,S2]=0 fails for multi-electron systems even under the no-pair approximation, and in this case the violation should be orders of magnitudes larger than the one found in the hydrogen atom. This is because we can now construct scalar states of different multiplicities even without creating electron-positron pairs. Now the scalar states are at best only a few eVs (frequently just a fraction of an eV) apart, so their mixings are sufficiently large to have observable consequences even without the aid of high-precision spectrometry, like spin-forbidden reactions, intersystem crossing and phosphorescence.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I would like to understand how &amp;quot;construct scalar states of different multiplicities&amp;quot; would let spin-forbidden reactions happen.&lt;/p&gt;&#xA;&lt;p&gt;From a comment from Nike Dattani&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;you can make the electrons paired (leading to a spin multiplicity of 1) or you can have them unpaired (leading to different multiplicities).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;if I use two electrons to form singlet and triplet (if they are &amp;quot;scalar states&amp;quot;), for a non-relativistic Hamiltonian, they still commute with the Hamiltonian. Where is the role of letting spin-forbidden reactions happen?&lt;/p&gt;&#xA;&lt;p&gt;Does it imply one starts from some scalar relativistic Hamiltonian, obtains eigenstate &lt;span class=&quot;math-container&quot;&gt;$|I\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$|J\rangle$&lt;/span&gt; with different multiplicities as &amp;quot;scalar states&amp;quot;, adds spin-orbit coupling into the Hamiltonian, and sees the&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle I | \hat{H}_{\mathrm{SO}} | J \rangle \neq 0 \tag{1} $$&lt;/span&gt;, then why different multiplicity will let (1) non vanish?  &lt;a href=&quot;https://doi.org/10.1080/00268976.2013.785611&quot; rel=&quot;nofollow noreferrer&quot;&gt;Eq. (12) in &amp;quot;Combining spin-adapted open-shell TD-DFT with spin–orbit coupling&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6061" LastEditorUserId="6061" LastEditDate="2022-10-12T07:01:50.450" LastActivityDate="2022-10-12T14:34:33.660" Title="How do scalar states with different multiplities make spin-forbidden reactions possible?" Tags="|quantum-chemistry|quantum-mechanics|spin-orbit-coupling|relativistic|reactivity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9782" PostTypeId="2" ParentId="9781" CreationDate="2022-10-12T08:21:43.630" Score="3" Body="&lt;p&gt;No, the presence of scalar states with different multiplicities is only a necessary condition for spin-forbidden reaction to take place (because otherwise there are no spin-forbidden reactions), but not a sufficient condition. Indeed, one may easily come up with a two-orbital two-electron system with just 3 singlet states and 1 triplet state, and set all the SOC matrix elements to zero; now you have a system with scalar states with different multiplicities, but no spin-forbidden reactivity at all.&lt;/p&gt;&#xA;&lt;p&gt;However, in reality, any system with at least one electron has an infinite number of eigenstates (and if you consider pair production effects, then even the vacuum has an infinite number of eigenstates). It then becomes exceedingly unlikely that all of the infinite number of possible SOC matrix elements are zero. And as long as there are scalar states with different multiplicities, an infinite number of SOC matrix elements will couple them, so that if even one of the matrix elements are zero, spin-forbidden reactions will be possible. Mathematically proving that spin-forbidden reactions must be always (or almost always) possible when there is more than one electron, is a different matter and does not seem as trivial as I thought, but I strongly believe that this is possible.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2022-10-12T14:34:33.660" LastActivityDate="2022-10-12T14:34:33.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9783" PostTypeId="1" CreationDate="2022-10-12T09:00:53.350" Score="2" ViewCount="42" Body="&lt;p&gt;The phonon number is not a conserved quantity, they add up as dictated by the dispersion relation until the Planck distribution is reached. However, I would need the k=PI/a phonons not to disappear from the system.&lt;/p&gt;&#xA;" OwnerUserId="6129" LastActivityDate="2022-10-12T09:00:53.350" Title="Can we create a phonon with a specific wavenumber that persists in the system for a long time?" Tags="|solid-state-physics|phonon-density-of-state|phonon-dispersion|" AnswerCount="0" CommentCount="4" ClosedDate="2023-06-12T14:48:00.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="9784" PostTypeId="1" CreationDate="2022-10-12T13:38:32.370" Score="4" ViewCount="59" Body="&lt;p&gt;I abandoned the use of M11-L and instead turned to B2PLYP for my molecule in my previous question, as M11-L seemed in fact to be very poor for my application. Since B2PLYP contains MP2, I looked up the NWChem manual to see if it supports RI-MP2 approximations. The manual did say that it supported RI-MP2, with explicit syntax rules on the fitting basis, but said nothing on RI-DH, let alone where to put the fitting bases in the code.&lt;/p&gt;&#xA;&lt;p&gt;My question is now clear- does NWChem support RI approximations for the MP2 part of double hybrids, and, if it does, where does one put the fitting basis line in? Q-Chem seems to have the answers to both but I cannot use commercial packages outside of the WebMO demo server.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-10-12T13:38:32.370" Title="Does NWChem support RI approximations in the MP2 part of double hybrids?" Tags="|nwchem|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-09T22:50:31.227" ContentLicense="CC BY-SA 4.0" />
  <row Id="9785" PostTypeId="1" CreationDate="2022-10-12T16:31:36.700" Score="4" ViewCount="66" Body="&lt;p&gt;When using Quantum Espresso to perform phonon calculations, one can specify a grid of q-point using ldisp=.true. (Monkhorst-Pack grid)&lt;/p&gt;&#xA;&lt;p&gt;If I ask for a AxBxC grid, the code will reduce this grid taking under consideration the symmetry. Some of these points will then have a higher weight factor.&lt;/p&gt;&#xA;&lt;p&gt;I want to calculate thermodynamics properties, so I should consider these weighting factors in my average, however QE does not print them anywhere (I believe).&lt;/p&gt;&#xA;&lt;p&gt;Am I wrong here, or should I retrieve the weights myself?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2022-10-12T16:49:17.027" LastActivityDate="2022-10-12T16:49:17.027" Title="q-points weighting factor in QE" Tags="|density-functional-theory|phonons|q-points|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-09T22:50:55.043" ContentLicense="CC BY-SA 4.0" />
  <row Id="9786" PostTypeId="1" AcceptedAnswerId="9791" CreationDate="2022-10-13T04:20:25.407" Score="4" ViewCount="553" Body="&lt;p&gt;It is often said that the resolution of the identity (RI) method accelerates the basis set convergence rate of MP2 &amp;quot;by one more zeta&amp;quot;, e.g. that RI-MP2/cc-pVTZ/cc-pVTZ results are close to those of MP2/cc-pVQZ. If this is true, this would be very useful for my double-hybrid B2PLYP calculations (see here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9784/5&quot;&gt;Does NWChem support RI approximations in the MP2 part of double hybrids?&lt;/a&gt;) as both the QC packages (with Gaussian clearly distorting orbitals even for first-row diatomic molecules and Q-Chem upright refusing to show them, all calculations done on the WebMO demo server) and the NBO package (the latest version of which, used by Q-Chem, upright refusing to calculate anything with g-functions in it) seem to have serious problems with QZ sets.&lt;/p&gt;&#xA;&lt;p&gt;My question is- is this acceleration phenomenon true in general?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="5" LastEditDate="2022-10-13T14:31:48.637" LastActivityDate="2022-10-14T08:31:13.060" Title="Does the RI method actually accelerate basis convergence of MP2, &quot;by one more zeta&quot;?" Tags="|quantum-chemistry|ab-initio-calculations|molecular-modeling|electronic-structure|basis-sets|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9787" PostTypeId="2" ParentId="9786" CreationDate="2022-10-13T07:49:50.143" Score="6" Body="&lt;p&gt;The RI method is an approximation, that accelerates the calculation rate but not the basis set convergence rate. So the timings of RI-MP2/cc-pVTZ may be similar to those of MP2/cc-pVDZ, but the results of RI-MP2/cc-pVTZ are nowhere close to MP2/cc-pVQZ; in fact the results of RI-MP2/cc-pVTZ are very close to MP2/cc-pVTZ, and can for almost all intents and purposes be treated as of the same quality as MP2/cc-pVTZ. Therefore, while RI can be useful for making an otherwise unaffordable MP2/cc-pVQZ calculation affordable (i.e. one can do RI-MP2/cc-pVQZ instead), it is not useful for getting rid of g functions without compromising the accuracy.&lt;/p&gt;&#xA;&lt;p&gt;There is a similarly termed method called R12, that belongs to explicitly correlated methods, which can do what you want, i.e. attain QZ accuracy (perhaps 5Z?) using a TZ basis set. However the R12 method has largely been substituted by the F12 method, which has better cost-to-performance ratios. I'm not an expert in this field, but I think Nike Dattani knows much more than I do about explicit correlation and may have some comments on that.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-10-13T07:49:50.143" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9788" PostTypeId="2" ParentId="9786" CreationDate="2022-10-13T09:21:47.880" Score="4" Body="&lt;p&gt;Resolution of Identity is typically introduced to treat the 4-index integrals in your code and reduces the order of magnitude in which your  calulation time scales with the number of electrons in your system, i.e. in Hartree Fock roughly from &lt;span class=&quot;math-container&quot;&gt;$N^4$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$N^3$&lt;/span&gt; if N is the number of particles.&lt;/p&gt;&#xA;&lt;p&gt;It can ,as wkzchem5 already mentioned, only approximate the result you would get without RI.&lt;/p&gt;&#xA;" OwnerUserId="5815" LastActivityDate="2022-10-13T09:21:47.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9789" PostTypeId="1" CreationDate="2022-10-13T09:49:17.453" Score="4" ViewCount="211" Body="&lt;p&gt;Hello Dear StackExchange Comunity,&#xA;Based on some interesting papers related to quantum transport calculation (Transiesta published paper...), the voltage applied in the device shifts the Fermi level in order to have two different electrochemical potentials in both electrodes (Left and Right):&#xA;&lt;strong&gt;At non-equilibrium:&lt;/strong&gt;&#xA;µ1=Ef+(eV/2)&#xA;µ2=Ef-(eV/2)&#xA;and V=µ1-µ2,&#xA;For that I have these related Questions that I would like to know:&#xA;&lt;strong&gt;What about the band gap Eg: the relationship between this parameter and the voltage (or the two µ)&lt;/strong&gt;&#xA;**** In my calculation, the gap measured in transmission increases with a bias voltage (that's why I ask how ?)&#xA;(****related to other works, I saw that the Homo and Luomo energy change)&#xA;&lt;strong&gt;And how can I find the Homo and Lumo energies in my Transiesta calculation&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you for help&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2022-10-13T10:05:51.667" LastActivityDate="2022-10-13T11:30:37.997" Title="The relation between applied voltage and band gap in Transport calculation (DFT+NEGF)" Tags="|density-functional-theory|ab-initio-calculations|siesta|electronic-transport|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9790" PostTypeId="2" ParentId="9789" CreationDate="2022-10-13T11:30:37.997" Score="4" Body="&lt;p&gt;When dealing with open boundary problems with a bias, the full system Fermi-level is somewhat ill-defined. Consider that the left electrode is in equilibrium at its &lt;span class=&quot;math-container&quot;&gt;$\mu_L= e_F + V/2$&lt;/span&gt; and the right at &lt;span class=&quot;math-container&quot;&gt;$\mu_R = e_F - V/2$&lt;/span&gt;. This means that there are already two different Fermi levels and that the Fermi levels are well-defined far away in the electrodes (that is the whole basis of NEGF in transiesta), but the full systems Fermi level is not.&lt;/p&gt;&#xA;&lt;p&gt;In the same way it becomes difficult to assess how band gaps behave under bias. An increasing band gap (in terms of transmission) may be due to various things such as, two neighbouring gaps overlapping, destructive interference, or some other physical behaviour. Similarly an applied bias may also close transmission band gaps (consider a semi-conductor and the threshold voltage).&lt;br /&gt;&#xA;So, there is no simple relation between applied bias and the band gap in a semi-conducting material between two metallic electrodes.&lt;/p&gt;&#xA;&lt;p&gt;With an open boundary system there is also no such thing as HOMO and LUMO. The electrodes &lt;em&gt;should&lt;/em&gt; be metallic, and hence the electronic spectrum is extremely closely positioned. Any molecule sandwiched between these electrodes will have their spectrum spread out due to the coupling to the electrodes. I would go as far as say, the HOMO and LUMO does not exist for molecules with high coupling strength to the electrodes.&lt;br /&gt;&#xA;For weakly coupled molecules, one might argue that one can see the HOMO and LUMO positions by examining projected DOS and/or transmission peaks resembling the characteristics of the lone molecules HOMO/LUMO. This is commonly done but it shouldn't be confused with &lt;em&gt;proper&lt;/em&gt; HOMO/LUMO states of a molecule.&lt;br /&gt;&#xA;In any case one should be careful and clear about the interpretations in such analysis.&lt;/p&gt;&#xA;&lt;p&gt;Please do note that TranSiesta relies on using metallic electrodes, using semi-conductors as electrodes is not recommended.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-10-13T11:30:37.997" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9791" PostTypeId="2" ParentId="9786" CreationDate="2022-10-13T14:29:45.950" Score="5" Body="&lt;p&gt;Others have correctly pointed out that the &amp;quot;resolution of identity&amp;quot; method by itself is just used to help obtain approximate energies within a particular basis set. Indeed, the abstract of &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0009261498008628&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; discusses the RI-MP2 approach, and says that the RI approximation resulted in approximate MP2 energies that were within 60 milli-hartree of the true MP2 energies (over a set of more than 350 molecules). More details can also be found &lt;a href=&quot;https://manual.q-chem.com/5.2/Ch6.S6.SS1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What you're describing in your question, about stepping up by &amp;quot;one zeta&amp;quot; in convergence to the complete basis set limit, is something slightly related. For example, the abstract of &lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/1.3254836&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; says that 4Z quality energies can be obtained by using a 2Z basis set when using &amp;quot;the R12 technology&amp;quot;. The first paragraph of the introduction section also says that you can get 5Z quality with a 3Z basis set. The R12 technology requires evaluation of 4-electron integrals, which would ordinarily be very difficult, but are made simpler with the resolution of the identity approach (see the introduction section of &lt;a href=&quot;https://arxiv.org/abs/1605.07065&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; for example). This attempt at obtaining energies that are roughly equal in quality to the energies that you &lt;em&gt;would&lt;/em&gt; ordinarily get with a higher-Z basis set, is also exemplified by methods such as RI-MP2-F12, which you can see is implemented as described &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/mp2-mp3&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I'll point out though, that a lot of people say things like &amp;quot;explicitly correlated methods like R12 and F12 gain you two zetas&amp;quot; without understanding that this &amp;quot;two zeta&amp;quot; rule is more of a &amp;quot;rule of thumb&amp;quot; than a rigorous theorem. &lt;em&gt;&lt;strong&gt;Observations&lt;/strong&gt;&lt;/em&gt; in &lt;em&gt;some&lt;/em&gt; datasets suggest that you can get 4Z quality energies with a 2Z basis set, or 5Z quality energies with a 3Z basis set (as described above), but this does not mean that you'll always observe a 2Z jump in quality; and the word &amp;quot;quality&amp;quot; is also open to interpretation. Some people might observe a 1Z jump (as you described in your question), and some people might observe less than a 1Z jump (i.e. barely any jump at all), and some people observe something closer to a 3Z jump in some cases. This &amp;quot;2Z jump&amp;quot; has been observed mainly for obtaining 4Z quality with 2Z basis sets and 5Z quality with 3Z basis sets, but not as much (or at all) for obtaining 7Z quality with 5Z basis sets (for example), largely because (for example) the auxiliary basis sets needed were not available to do such 5Z calculations. People have said that the higher you go up in Z, the more benefit you'll get from these explicitly correlated methods (like R12/F12), but what they don't usually seem to realize is that when you're doing calculations with a high Z (for example 5Z or 6Z), the reason is to get high-accuracy results, and the approximations associated with using these R12/F12 methods can outweigh the benefits that they provide in terms of approaching the CBS limit (and the lack of RI auxiliary basis sets for higher Z values can also be an obstacle). &lt;strong&gt;R12/F12 methods often in fact overshoot the CBS limit, meaning that they often give energies that are lower than the variational principle would allow.&lt;/strong&gt; This shouldn't be a problem for you in this particular case though, since you said that you're using double-hybrids (which means that your error in the electron correlation treatment might be bigger than your basis set error anyway), but it's something to be mindful of when people tell you that you can get an  2Z jump for an arbitrary calculation by using an R12/F12 method.&lt;/p&gt;&#xA;&lt;p&gt;I'll finally point out that since your question points out that Gaussian, Q-Chem and NBO didn't work out for you, it may be worthwhile for you to try &lt;a href=&quot;/questions/tagged/mrcc&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;mrcc&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;mrcc&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;mrcc-container&quot;&gt;mrcc&lt;/a&gt; which is available for free and very good for double-hybrid calculations, and calculations on huge systems (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1352/5&quot;&gt;here&lt;/a&gt; for example).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="142" LastEditDate="2022-10-14T08:31:13.060" LastActivityDate="2022-10-14T08:31:13.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9792" PostTypeId="1" CreationDate="2022-10-14T06:10:27.137" Score="3" ViewCount="93" Body="&lt;p&gt;I am an experimentalist who is interested in getting hands on experience with how simulations play into our understanding of liquid crystal formation. I have tried to read several reviews on the topic (10.1080/00268976.2019.1612957 and 10.1063/1.168726) and while they gave me a better idea of how the theory behind different types of liquid crystal models, I am still having difficulty coding simulations.&lt;/p&gt;&#xA;&lt;p&gt;What are some beginner resources that could help me tackle this topic? For example, something appropriate to show a first year grad student or even upper level undergrad who is learning to code their first few simulations in soft matter modeling.&lt;/p&gt;&#xA;&lt;p&gt;I have taught myself a bit of electronic structure theory (Hartree Fock and DFT), and resources like this were extremely helpful: &lt;a href=&quot;https://github.com/CrawfordGroup/ProgrammingProjects&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/CrawfordGroup/ProgrammingProjects&lt;/a&gt; . Ideally I would be looking for something similar here. I am comfortable in C++ and python.&lt;/p&gt;&#xA;&lt;p&gt;My ideal place to end up would be to take a candidate molecule and use simulations to predict if it forms a thermotropic liquid crystalline phase over a range of experimentally accessible temperatures.&lt;/p&gt;&#xA;" OwnerUserId="6138" LastActivityDate="2022-10-14T06:10:27.137" Title="How to get started modeling liquid crystals?" Tags="|molecular-dynamics|software-recommendations|statistical-thermodynamics|atomistic-simulation|many-body-physics|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-12T02:19:38.840" ContentLicense="CC BY-SA 4.0" />
  <row Id="9794" PostTypeId="1" CreationDate="2022-10-14T15:20:57.453" Score="2" ViewCount="24" Body="&lt;p&gt;I'm trying to investigate the possibility of martensitic transformation in a non-iron alloy, described as a single-phase alpha-solid-solution (Nickel-Silver &lt;span class=&quot;math-container&quot;&gt;$\ce{CuNi12Zn25Pb1}$&lt;/span&gt;, CW404J).&lt;/p&gt;&#xA;&lt;p&gt;I know that Cu-Ni-Zn alloys with higher zinc amounts show even shape memory effects and that &lt;span class=&quot;math-container&quot;&gt;$\ce{CuNi12Zn25Pb1}$&lt;/span&gt; is no Shape Memory Alloy.&#xA;I also know that Nickel-Silver alloys with Zn&amp;gt;32% are two-phase (alpha-Beta) solid solutions.&lt;/p&gt;&#xA;&lt;p&gt;So I wonder (and searched) whether there is causality or correlation between being a two-phase (and not single-phase) solid solution and having the ability of martensitic transformation (and Shape Memory Effect)?&lt;/p&gt;&#xA;" OwnerUserId="3950" LastEditorUserId="7" LastEditDate="2022-10-15T23:28:17.070" LastActivityDate="2022-10-15T23:28:17.070" Title="Can a single-phase solid solution have a martensitic transformation?" Tags="|alloys|phase-transitions|" AnswerCount="0" CommentCount="2" ClosedDate="2023-06-12T14:48:38.837" ContentLicense="CC BY-SA 4.0" />
  <row Id="9795" PostTypeId="2" ParentId="9664" CreationDate="2022-10-14T15:33:50.670" Score="3" Body="&lt;p&gt;I guess this is more of a physics question than it is specific to TranSIESTA.&lt;/p&gt;&#xA;&lt;p&gt;I will provide an answer that can help you get a general picture but it is by no means a formal explanation of how transport takes place. For that I suggest you to find resources that explain it in depth (I suggest some at the end).&lt;/p&gt;&#xA;&lt;p&gt;In transport devices you have a situation like the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0ODYg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0ODYg.png&quot; alt=&quot;transport device&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the voltage window is the voltage you &amp;quot;apply&amp;quot; between the two electrodes. From this you can already see that there are some electrons in the left electrode that are at a very high energy and would like to go to the empty states of the right electrode at lower energies. However, to go there, they need some electronic state in between that they can use to move from left to right. Certainly, in this specific situation, there are no states in the device at the energies where the electrons would like to move. So basically there is no transport of electrons.&lt;/p&gt;&#xA;&lt;p&gt;The bottomline is that in order for transport to take place, there must be some &lt;strong&gt;states in the device that are inside the voltage window&lt;/strong&gt;. So, as long as you can put some states in that window you will have transport. The way you get states in the window is specific to your own system and device, but there are two general, easy to understand, approaches:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Increasing the voltage. This makes the voltage window larger and therefore you are likely to include more states. This strategy is pictured below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/X08Vq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/X08Vq.png&quot; alt=&quot;transport device more voltage&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Applying a gate. A gate makes electrons in the device feel &amp;quot;more comfortable&amp;quot; (lower energy) or &amp;quot;less comfortable&amp;quot; (higher energy). Therefore it induces a shift in all the energies of the device's states. In this way you might make some of the states enter the voltage window. This is pictured below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/DMo08.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DMo08.png&quot; alt=&quot;transport device gate&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As I said, you should check resources to understand the issue more in depth. This whole playlist on nanoelectronics I would say is a good start: &lt;a href=&quot;https://www.youtube.com/watch?v=p5nsWUKiG9k&amp;amp;list=PLtkeUZItwHK6lvGu8kFKBdhz3XaIZQDFj&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=p5nsWUKiG9k&amp;amp;list=PLtkeUZItwHK6lvGu8kFKBdhz3XaIZQDFj&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2022-10-14T15:33:50.670" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9796" PostTypeId="1" AcceptedAnswerId="9798" CreationDate="2022-10-14T16:45:52.537" Score="9" ViewCount="699" Body="&lt;p&gt;This question is about ions in water, both in reality and as handled by MD (explicit solvent) and  QM methods (eg AIMD).  Basically the question is this:  why are ions not always paired?&lt;/p&gt;&#xA;&lt;p&gt;For a back of the envelope calculation take K+ with radius 0.14nm and Cl- with radius 0.18nm or so.  The electrostatic energy to separate the ion pair to infinity is 138/(0.14+0.18) = 430kJ/mol.  Water (eg TIP3P model) has diameter around 0.3nm and partial charges around -0.8 on oxygen and +0.4 on hydrogen; the energy to separate a water-water pair is 20-30kJ/mol (lower in vacuum, higher if surrounded by water).  If we think of inserting a water between an ion pair as breaking two water-water pairs (+50kJ/mol), separating the ions by the diameter of a water (+200kJ/mol or so) and adding two favorable ion-water interactions - I’m really having a hard time seeing how the ion-water interactions would add up to more than the energy needed to separate the ions.  And that’s just for adding one water directly in between; separating the ions all the way (until they’re fully hydrated and almost fully screened so they can float around independently) would be even less favorable.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone explain intuitively what drives the separation of ion pairs? (hydration by multiple waters, overpolarization of the waters, small diameter of the hydrogen atoms allowing them to get closer to negative ion, etc). Is there a simple MD model that would show how that works?&lt;/p&gt;&#xA;&lt;p&gt;Have there been any studies (either MD or QM) that specifically compare the potential energy (or free energy) of an ion pair in water vs two separate ions in water?&lt;/p&gt;&#xA;" OwnerUserId="40" LastActivityDate="2022-10-16T10:38:06.323" Title="Why are ions in water not paired?" Tags="|free-energy|water|solvation|hydrogen-bonds|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9798" PostTypeId="2" ParentId="9796" CreationDate="2022-10-14T23:20:54.943" Score="12" Body="&lt;p&gt;There actually is ion pairing in aqueous solutions, but the concentration of paired ions is usually much lower than fully dissociated ions. You should also take into account that typical concentrations of dissolved salt is much lower than the concentration of bulk water (55.5 M). The water molecules tend to also form tight hydration shells around the ions which act to screen the ionic charge. In some cases, water interacts chemically with the ions, which further stabilizes the ion in solution by forming a “complex ion”, which is chemically distinct from a bare ion.&lt;/p&gt;&#xA;&lt;p&gt;You already talked about screening effects, but it’s pretty important for stabilizing concentrated salt solutions. The screening effect is captured by the dielectric constant (~78 for bulk water) in the coulomb potential. The dielectric constant is usually lower around ions due to dielectric saturation (where the waters are rigidly oriented around the ion because of the electric field), but larger in bulk water where waters are randomly oriented. The dielectric screening weakens the effective long range interaction of ions, so neighboring ions can’t really “feel” each other as much as if they were at the same distance in vacuum. Hence, the potential energy of ions embedded in a dielectric medium is lower compared to the same arrangement in vacuum.&lt;/p&gt;&#xA;&lt;p&gt;And finally, there is a large entropic driving force to homogeneously disperse ions into the solution. You can do a back of the envelope calculation treating this as an ideal mixture (obviously it’s far from ideal). This is probably the most important effect for stabilizing the solution. If you read up on this, you’ll see for example that the concentration where salts precipitate are highly temperature-dependent, and that the temperature dependence is related to the entropy of solution.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-10-14T23:43:57.163" LastActivityDate="2022-10-14T23:43:57.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9799" PostTypeId="1" CreationDate="2022-10-15T01:12:00.810" Score="3" ViewCount="400" Body="&lt;p&gt;The following problem arises when I use Vina for virtual screening. Vina seems to have only one calculation program, so how do I add the required atomic force field parameters?&#xA;&amp;quot;ATOM syntax incorrect: &amp;quot;Si&amp;quot; is not a valid AutoDock type. Note that AutoDock atom types are case-sensitive.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="6145" LastActivityDate="2022-10-15T01:12:00.810" Title="How to add atom types in Autodock Vina" Tags="|docking|autodock|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-12T14:49:39.150" ContentLicense="CC BY-SA 4.0" />
  <row Id="9800" PostTypeId="1" CreationDate="2022-10-15T04:38:39.170" Score="3" ViewCount="147" Body="&lt;p&gt;I am trying to do LAMMPS calculations but I have noticed that when I dump to &lt;code&gt;.xyz&lt;/code&gt; that ASE cannot read the elements because they are simply not output!  Is there a good way to specify elements to atoms in LAMMPS?&lt;/p&gt;&#xA;&lt;p&gt;I am using the following dump command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dump dump_all all custom 20 output.xyz id type x y z vx vy vz fx fy f&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The data file looks something like this as well&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/scratch/tgmaxson/data (written by ASE)&#xA;&#xA;45       atoms&#xA;3  atom types&#xA;0.0      8.4770495136049657  xlo xhi&#xA;0.0      8.5867434566153804  ylo yhi&#xA;0.0      8.8601981847873912  zlo zhi&#xA;&#xA;&#xA;Atoms&#xA;&#xA;     1   0   3   0.0     0.19840304286794558      2.6071741694272772      7.2188474839438452&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-10-15T04:38:39.170" Title="Assign elements correctly in LAMMPS output (xyz)" Tags="|lammps|atomic-simulation-environment|" AnswerCount="0" CommentCount="2" ClosedDate="2023-06-12T14:49:19.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="9801" PostTypeId="1" AcceptedAnswerId="9806" CreationDate="2022-10-15T05:54:48.560" Score="8" ViewCount="297" Body="&lt;p&gt;In their landmark paper of 1964, &lt;a href=&quot;https://journals.aps.org/pr/pdf/10.1103/PhysRev.136.B864&quot; rel=&quot;noreferrer&quot;&gt;Inhomogeneous Electron Gas&lt;/a&gt;, Hohenberg and Kohn wrote down:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We shall be considering a collection of an arbitrary number of&#xA;electrons, enclosed in a large box and moving under the influence of&#xA;an external potential &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{r})$&lt;/span&gt; and the mutual Coulomb&#xA;repulsion. The Hamiltonian has the form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=T+V+U \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where[...atomic units are used.]&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray*}&#xA; T &amp;amp;\equiv&amp;amp; \frac{1}{2} \int \nabla \psi^*(\mathbf{r}) \ \nabla\psi(\mathbf{r}) \ d \mathbf{r} \tag{2} \\&#xA;  V &amp;amp;\equiv&amp;amp; \int v(\mathbf{r}) \ \psi^*(\mathbf{r}) \ \psi(\mathbf{r}) \ d\mathbf{r} \tag{3} \\ &#xA;  U &amp;amp;=&amp;amp; \frac{1}{2} \int \frac{1}{|\mathbf{r}-\mathbf{r}^{\prime}|} \ \psi^\ast(\mathbf{r}) \ \psi^*(\mathbf{r}^{\prime}) \ \psi(\mathbf{r}^{\prime}) \ \psi(\mathbf{r}) \ d \mathbf{r} \ d \mathbf{r}^{\prime} \tag{4} \end{eqnarray*}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;After applying the Born-Oppenheimer approximation, one obtains the following &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron Hamiltonian,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{H} = - \frac{1}{2} \sum_{i=1}^N \nabla_i^2 + \sum_{i=1}^N v(\hat{\mathbf{r}_i}) + \frac{1}{2} \sum_{i \neq j} \frac{1}{|\hat{\mathbf{r}}_i-\hat{\mathbf{r}}_j|} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the time-independent Schrodinger equation,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat{H} \ \psi(\mathbf{r}_1, \mathbf{r}_2, ..., \mathbf{r}_N) = E \ \psi(\mathbf{r}_1, \mathbf{r}_2, ..., \mathbf{r}_N) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is how to obtain Eq. (4) given the above Hamiltonian and Schrodinger equation?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know Eq. (4) represents the classical Hartree energy and it can be deduced from Electrodynamics arguments (of course not in terms of the wavefunction form depicted above but in terms of the charge density of a charge distribution), BUT how to obtain it from the expectation value of the above Hamiltonian, i.e.,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;U = \int_{\mathbb{R}^3} \ldots \int_{\mathbb{R}^3} \ d \mathbf{r}_1 \ldots d \mathbf{r}_N \ \psi^*(\mathbf{r}_1, ..., \mathbf{r}_N) \ \left(\frac{1}{2} \sum_{i \neq j} \frac{1}{|\hat{\mathbf{r}}_i-\hat{\mathbf{r}}_j|}\right) \ \psi(\mathbf{r}_1, ..., \mathbf{r}_N)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="5364" LastEditDate="2022-10-15T09:03:14.007" LastActivityDate="2022-10-17T07:05:16.283" Title="Equation (4) in Hohenberg-Kohn Paper" Tags="|density-functional-theory|quantum-mechanics|expectation-values|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9802" PostTypeId="2" ParentId="9801" CreationDate="2022-10-15T14:24:11.433" Score="4" Body="&lt;p&gt;The expectation value of two-electron operators such as the interelectronic Coulomb operator can be computed with the &lt;a href=&quot;https://en.wikipedia.org/wiki/Slater%E2%80%93Condon_rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Slater-Condon rules&lt;/a&gt;, for example. Another alternative is to use second quantization and &lt;a href=&quot;https://en.wikipedia.org/wiki/Wick%27s_theorem&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wick's theorem&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For a one-determinant wave function &lt;span class=&quot;math-container&quot;&gt;$|\Psi\rangle$&lt;/span&gt;, the expectation value &lt;span class=&quot;math-container&quot;&gt;$\langle \Psi |r_{12}^{-1}|\Psi\rangle$&lt;/span&gt; gives you the classical Coulomb term&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ U = \frac 1 2 \int \frac {n({\bf r}) n({\bf r})} {|{\bf r}-{\bf r}'|} {\rm d}^3 r {\rm d}^3 r' $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the quantum mechanical &lt;a href=&quot;https://en.wikipedia.org/wiki/Exchange_interaction&quot; rel=&quot;nofollow noreferrer&quot;&gt;exchange interaction&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-15T14:24:11.433" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9803" PostTypeId="2" ParentId="158" CreationDate="2022-10-15T14:28:32.080" Score="3" Body="&lt;p&gt;To complement Michael's answer, Pulay forces can actually be dampened by a suitable design of the basis set, as noted by Pulay in 1977. We have recently shown in &lt;a href=&quot;https://arxiv.org/abs/2207.03587&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:2207.03587&lt;/a&gt; that accurate Hellmann-Feynman forces can be evaluated with density functional theory using Gaussian basis sets that are not much bigger than established state-of-the-art triple-zeta basis sets.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-15T14:28:32.080" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9804" PostTypeId="2" ParentId="9796" CreationDate="2022-10-15T21:01:31.367" Score="2" Body="&lt;p&gt;It's the entropy – suggested reading, &lt;a href=&quot;http://materias.df.uba.ar/ft3a2013c1/files/2012/07/Jaynes-information-theory-and-statistical-mechanic-II2.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;ET Jaynes: Information theory and statistical mechanics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the same reason, water vapour exists already at room temperatur (~1 mol/m³, &lt;a href=&quot;https://www.iap.tuwien.ac.at/www/surface/vapor_pressure&quot; rel=&quot;nofollow noreferrer&quot;&gt;TU Wien: Vapor Pressure Calculator&lt;/a&gt;), where the heat of vaporization of 44 kJ/mol (&lt;a href=&quot;https://chem.libretexts.org/Bookshelves/General_Chemistry/Book%3A_ChemPRIME_(Moore_et_al.)/10%3A_Solids_Liquids_and_Solutions/10.10%3A_Enthalpy_of_Fusion_and_Enthalpy_of_Vaporization&quot; rel=&quot;nofollow noreferrer&quot;&gt;Moore et al.: ChemPRIME&lt;/a&gt;) is ~18&lt;em&gt;RT&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6149" LastEditorUserId="6149" LastEditDate="2022-10-16T10:38:06.323" LastActivityDate="2022-10-16T10:38:06.323" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9805" PostTypeId="1" CreationDate="2022-10-16T15:29:02.957" Score="6" ViewCount="1047" Body="&lt;p&gt;So, I am developing a GUI for a python computational chemistry software (with PyQt5). The Qt part of the GUI will handle running the python software (calling the proper functions with proper arguments etc. i.e. will replace the need to write python code to use the software). However, the GUI also needs to be able to draw molecules and feed that information to the software. (The software by default can take SMILES, xyz, mol2 as input.)&lt;/p&gt;&#xA;&lt;p&gt;So I essentially need a molecule drawing software that can be called from python GUI and will provide information about the drawn molecule back to the GUI. (Think something like the pubchem sketcher, where you click a button to open a sketcher and when you close it, the molecule gets passed to pubchem). Bonus points if the sketcher is 3D, like Avogadro or GaussView. I can also do with 2D sketchers like ChemDraw or Marvin if 3D is unavailable.&lt;/p&gt;&#xA;&lt;p&gt;I know that Avogadro is supposed to have a python interface, but documentation is so sparse, that I have not been able to understand how to run it. &lt;strong&gt;So, is there a molecule builder or drawer software that can be interfaced to python easily&lt;/strong&gt;? I need the molecule drawer to be callable or executable from within python. &lt;strong&gt;I am looking for molecule sketching softwares where the users can draw their molecules in the GUI by hand, I do not mean visualisation softwares!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-02-09T15:02:57.977" LastActivityDate="2023-02-09T21:57:45.793" Title="A python compatible GUI chemical drawing library/software" Tags="|software-recommendations|python|one-topic-per-answer|visualization-software|graphical-user-interface|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9806" PostTypeId="2" ParentId="9801" CreationDate="2022-10-16T15:38:36.960" Score="5" Body="&lt;p&gt;You're confusing things: The operators are written in second quantization, so &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\psi^*$&lt;/span&gt; (or &lt;span class=&quot;math-container&quot;&gt;$\psi^\dagger$&lt;/span&gt;) denote (fermionic) the field operators. There are no expectation values involved and in particular &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; does not denote any wave function (and thus &lt;span class=&quot;math-container&quot;&gt;$\psi^*$&lt;/span&gt; not some complex conjugated wave function). So your Hamiltonian is the very same as the Hamiltonian in the paper, term by term (if interpreted correctly).&lt;/p&gt;&#xA;&lt;p&gt;For example, a (fermionic) two-body operator  of the form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ W:=\frac{1}{2}\sum\limits_{i\neq j}^Nw(x_i,x_j) \tag{1} $$&lt;/span&gt;&#xA;can be written in second quantization as (modulo typos)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ W=\frac{1}{2} \int\mathrm dx_1 \int \mathrm dx_2\, \psi^\dagger(x_1)\, \psi^\dagger(x_2)\,w(x_1,x_2)\, \psi(x_2)\, \psi(x_1)\ \tag{2} \quad ,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where we've employed a notation which is more common in (many-body) physics (the &lt;span class=&quot;math-container&quot;&gt;$^*$&lt;/span&gt; is used in more mathematical oriented texts). The derivation is given in pretty much any book concerning second quantization. Similar reasoning applies to the &lt;span class=&quot;math-container&quot;&gt;$T+V$&lt;/span&gt; term.&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2022-10-17T07:05:16.283" LastActivityDate="2022-10-17T07:05:16.283" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9807" PostTypeId="2" ParentId="9740" CreationDate="2022-10-16T20:57:08.997" Score="2" Body="&lt;p&gt;Leopold is right. According to the output you show, H is entered with an atomic number of 1, while it should have, say, an &amp;quot;atomic number&amp;quot; of 201. This is the mechanism used  by Siesta to tag an species as &amp;quot;synthetic&amp;quot; and process the rest of the relevant information (i.e. the actual valence charge).&lt;/p&gt;&#xA;" OwnerUserId="1519" LastActivityDate="2022-10-16T20:57:08.997" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9808" PostTypeId="2" ParentId="7044" CreationDate="2022-10-16T21:08:06.147" Score="3" Body="&lt;p&gt;An alternative way to explore the states around a given energy is to compute the &amp;quot;local density of states&amp;quot;, which is a kind of &amp;quot;charge density&amp;quot; obtained from the states in a given energy range.&lt;/p&gt;&#xA;&lt;p&gt;If you want wave-functions, you can select a more interesting set by using energy filters. From the &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Manuals/siesta-4.1-b4.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The user can narrow the energy-range used (and save some file space) by&#xA;using the &lt;code&gt;WFS.Energy.Min&lt;/code&gt; and &lt;code&gt;WFS.Energy.Max&lt;/code&gt; options&#xA;(both take an energy (with units) as extra argument),&#xA;and/or the &lt;code&gt;WFS.Band.Min&lt;/code&gt; and &lt;code&gt;WFS.Band.Max&lt;/code&gt; options.&#xA;Care should be taken to make sure that the actual values&#xA;of the options make sense.&lt;/p&gt;&#xA;&lt;p&gt;Note that the band range options could also affect the output&#xA;of wave-functions associated to bands (see section 6.15.2),&#xA;and that the energy range options could also affect the output&#xA;of user-selected wave-functions with the WaveFuncKPoints block&#xA;(see section 6.16).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1519" LastEditorUserId="7" LastEditDate="2022-10-16T23:15:11.827" LastActivityDate="2022-10-16T23:15:11.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9810" PostTypeId="1" AcceptedAnswerId="9811" CreationDate="2022-10-17T02:49:31.697" Score="6" ViewCount="975" Body="&lt;p&gt;As far as I know, we need force fields such as Tersoff/Coulomb potentials when performing MD simulations. In AIMD, we use pseudopotentials similar to DFT.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which method should we classify AIMD to: a group of MD methods or a group of DFT methods?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1352" LastEditorUserId="5" LastEditDate="2022-10-17T04:18:28.470" LastActivityDate="2022-10-17T14:38:43.837" Title="Is AIMD classified as MD or DFT?" Tags="|density-functional-theory|molecular-dynamics|aimd|" AnswerCount="2" CommentCount="0" FavoriteCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9811" PostTypeId="2" ParentId="9810" CreationDate="2022-10-17T04:11:02.837" Score="8" Body="&lt;p&gt;Purely classical MD would use a classical forcefield to do MD, &lt;br&gt;&#xA;whereas &lt;em&gt;ab initio&lt;/em&gt; MD (AIMD) would usually involve DFT calculations to obtain the forces, then the same type of MD procedure can be used for the dynamics.&lt;/p&gt;&#xA;&lt;p&gt;Technically the forces could also be calculated with MP2 or coupled cluster methods, or any other &lt;em&gt;ab initio&lt;/em&gt; method, so it does not need to involve DFT to be &amp;quot;&lt;em&gt;ab initio&lt;/em&gt; MD&amp;quot;, but in practice people don't usually use these &amp;quot;other&amp;quot; &lt;em&gt;ab initio&lt;/em&gt; methods for the forcefields, and that is for good reasons (e.g. it could make the calculations too slow).&lt;/p&gt;&#xA;&lt;p&gt;As for your question of whether AIMD is classified as an MD method or a DFT method, I'd say it's an MD method that usually uses DFT (but does not have to use DFT). More simply: it's a flavor of MD. It's not a DFT method, or a flavour of MD, it just usually uses DFT as one part of the procedure.&lt;/p&gt;&#xA;&lt;p&gt;You might also be interested in this thread:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1523/5&quot;&gt;What are the types of ab initio Molecular Dynamics?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-10-17T04:11:02.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9812" PostTypeId="1" CreationDate="2022-10-17T14:08:43.767" Score="2" ViewCount="48" Body="&lt;p&gt;I am planning to conduct an MD simulation research on graphene growth on a metal substrate using lammps. I recently learned to form a crystal lattice using lammps. But I have no idea what to look for next. Any suggestions?&lt;/p&gt;&#xA;" OwnerUserId="6153" LastActivityDate="2022-10-17T14:08:43.767" Title="What are the key things I need to learn before I can simulate graphene growth on a metal substrate using LAMMPS?" Tags="|molecular-dynamics|lammps|graphene|" AnswerCount="0" CommentCount="2" ClosedDate="2022-12-16T03:56:17.317" ContentLicense="CC BY-SA 4.0" />
  <row Id="9813" PostTypeId="2" ParentId="9810" CreationDate="2022-10-17T14:38:43.837" Score="5" Body="&lt;p&gt;Ab initio molecular dynamics (AIMD) involves both ab initio and molecular dynamics (MD).  If the ab initio is done by density functional theory (DFT), the method is &lt;strong&gt;both&lt;/strong&gt; a density functional and MD method, and the question is based on a false dichotomy.&lt;/p&gt;&#xA;&lt;p&gt;Nike's answer correctly points out that the ab initio calculations can also be run with another method. I would like to add that the sentence in the question&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In AIMD, we use pseudopotentials similar to DFT.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is not necessarily true; AIMD calculations are often run with DFT also without pseudopotentials.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-17T14:38:43.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9814" PostTypeId="1" CreationDate="2022-10-18T03:14:41.987" Score="5" ViewCount="100" Body="&lt;p&gt;I need to implement the molecular dynamics method to simulate a simple fluid that interacts through the Lennard-Jones potential in a 2D simulation. The idea is to explore how the total energy of the system (kinetic + potential) and the particle trajectories depend on the size of the chosen time step.&lt;/p&gt;&#xA;&lt;p&gt;I took a piece of code that does part of the job(I will upload it here) but I would like a algorithm to helpe-me to finish. I  will try to summarize what I understood until now:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Initially it sets the physical parameters and parameters of simulation&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;temperature&lt;/li&gt;&#xA;&lt;li&gt;density&lt;/li&gt;&#xA;&lt;li&gt;number of particles&lt;/li&gt;&#xA;&lt;li&gt;size of the box&lt;/li&gt;&#xA;&lt;li&gt;Lennard-Jones cut-radius&lt;/li&gt;&#xA;&lt;li&gt;Verlet-list radius&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;It initializes the vectors and lattice&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;position and velocity vectors x,y and vx,vy&lt;/li&gt;&#xA;&lt;li&gt;distributes the particles in a square centered lattice&lt;/li&gt;&#xA;&lt;li&gt;Chooses velocities uniformly on a unit circle&lt;/li&gt;&#xA;&lt;li&gt;Normalizes the velocities according to the energy equipartition&#xA;theore&lt;/li&gt;&#xA;&lt;li&gt;make the total momentum of the particles equal to zero&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Creates a verlet list to define neighbors&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;My doubts are:&lt;/p&gt;&#xA;&lt;p&gt;How and when to use Lennard Jones potential and Verlet Velocities in the code ?&#xA;Does someone have an example algorithm or can put it in a manner that I can follow the steps?&lt;/p&gt;&#xA;&lt;p&gt;The code until now:&#xA;&lt;a href=&quot;https://github.com/danielrflor/public/blob/e5e0b05373a820b5e36b34f385136c906b1b6ec6/2D-MolecularDynamics.ipynb&quot; rel=&quot;noreferrer&quot;&gt;MolecularDynamics_2DfluidSimulation&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6155" LastActivityDate="2023-07-11T22:06:00.693" Title="Molecular dynamics method to simulate a simple fluid" Tags="|molecular-dynamics|molecular-modeling|2d-lattice|fluid-dynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9815" PostTypeId="1" CreationDate="2022-10-18T03:57:44.690" Score="3" ViewCount="163" Body="&lt;p&gt;I've been trying to implement neural network as a customised exchange-correlation functional in PySCF but with no success. Below is the example code for customised XC functional. Anyone has any idea how to do that?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto&#xA;from pyscf import dft&#xA;&#xA;mol = gto.M(&#xA;    atom='''&#xA;    O  0.   0.       0.&#xA;    H  0.   -0.757   0.587&#xA;    H  0.   0.757    0.587 ''',&#xA;    basis='ccpvdz')&#xA;&#xA;# half-half exact exchange and GGA functional&#xA;hybrid_coeff = 0.5&#xA;&#xA;&#xA;def eval_xc(xc_code, rho, spin=0, relativity=0, deriv=1, verbose=None):&#xA;    # A fictitious XC functional to demonstrate the usage&#xA;    rho0, dx, dy, dz = rho[:4]&#xA;    gamma = (dx**2 + dy**2 + dz**2)&#xA;    exc = .01 * rho0**2 + .02 * (gamma+.001)**.5&#xA;    vrho = .01 * 2 * rho0&#xA;    vgamma = .02 * .5 * (gamma+.001)**(-.5)&#xA;    vlapl = None&#xA;    vtau = None&#xA;    vxc = (vrho, vgamma, vlapl, vtau)&#xA;    fxc = None  # 2nd order functional derivative&#xA;    kxc = None  # 3rd order functional derivative&#xA;&#xA;    # Mix with existing functionals&#xA;    pbe_xc = dft.libxc.eval_xc('pbe,pbe', rho, spin, relativity, deriv,&#xA;                               verbose)&#xA;    exc += pbe_xc[0] * 0.5&#xA;    vrho += pbe_xc[1][0] * 0.5&#xA;    vgamma += pbe_xc[1][1] * 0.5&#xA;    return exc, vxc, fxc, kxc&#xA;&#xA;&#xA;mf = dft.RKS(mol)&#xA;mf = mf.define_xc_(eval_xc, 'GGA', hyb=hybrid_coeff)&#xA;mf.verbose = 4&#xA;mf.kernel()&#xA;&#xA;# half exact exchange in which 40% of the exchange is computed with short&#xA;# range part of the range-separation Coulomb operator (omega = 0.8)&#xA;beta = 0.2&#xA;rsh_coeff = (0.8, hybrid_coeff-beta, beta)&#xA;mf = dft.RKS(mol)&#xA;mf = mf.define_xc_(eval_xc, 'GGA', rsh=rsh_coeff)&#xA;mf.verbose = 4&#xA;mf.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6156" LastActivityDate="2022-10-19T07:10:14.823" Title="Neural network as a customised XC functional in PySCF?" Tags="|density-functional-theory|python|machine-learning|pyscf|kohn-sham|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9816" PostTypeId="1" CreationDate="2022-10-18T10:13:36.453" Score="3" ViewCount="53" Body="&lt;p&gt;Reference-like introductory resources for molecular modelling in drug discovery?&lt;/p&gt;&#xA;&lt;p&gt;Particularly I want to cover:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Underlying chemical phenomena and methods&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Mathematical methods that have been demonstrated to be useful&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Some common practices in the field, such as 3D-QSAR&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5821" LastActivityDate="2022-10-19T18:27:00.703" Title="Reference-like introductory resources for molecular modelling in drug discovery?" Tags="|molecular-modeling|drug-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9817" PostTypeId="1" CreationDate="2022-10-18T12:33:20.820" Score="2" ViewCount="46" Body="&lt;p&gt;Any philosophical insight to the concept of &amp;quot;usefulness&amp;quot; in drug discovery?&lt;/p&gt;&#xA;&lt;p&gt;I mean, I started to naively view drug design and computational drug design as some sort of holy grail (we can design the things we need/want).&lt;/p&gt;&#xA;&lt;p&gt;Then after reading few papers I'm finding that the studied phenomena seem quite complicated. There are different risks, models and multiple interactions.&lt;/p&gt;&#xA;&lt;p&gt;This made me question whether drug design is useful at all. Or when is it?&lt;/p&gt;&#xA;&lt;p&gt;I'm looking for an answer that answers e.g.:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;When are drugs useful?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Perceptions on costs (time, money, stress) vs benefits of drugs and drug design.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Perceptions on the efficiency of &amp;quot;accurate models&amp;quot; in drug design.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This is e.g. because (naive example):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Exercise is as effective as a SSRI, but it costs little to produce and has well-known side-effects.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5821" LastActivityDate="2022-10-18T12:33:20.820" Title="Any philosophical insight to the concept of &quot;usefulness&quot; in drug discovery?" Tags="|drug-design|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T22:51:28.543" ContentLicense="CC BY-SA 4.0" />
  <row Id="9818" PostTypeId="1" CreationDate="2022-10-18T13:02:21.347" Score="1" ViewCount="49" Body="&lt;p&gt;What are some useful databases for performance-enhancing compounds?&lt;/p&gt;&#xA;&lt;p&gt;I've been interested in cognitive enhancers etc.&lt;/p&gt;&#xA;" OwnerUserId="5821" LastActivityDate="2022-10-19T18:41:00.210" Title="What are some useful databases for performance-enhancing compounds?" Tags="|drug-design|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9819" PostTypeId="2" ParentId="4749" CreationDate="2022-10-18T16:12:14.190" Score="3" Body="&lt;p&gt;Different docking programs can be tried for a benchmark.&lt;/p&gt;&#xA;&lt;p&gt;The re-docking technique can be used: you separate the receptor experimental structure from the ligand and re-dock back the ligand into the receptor with different docking programs.&lt;/p&gt;&#xA;&lt;p&gt;Docking can be evaluated with an RMSD calculation. However, no measurement is robust by itself, so the optimum might also be to visualize the key interactions that the ligand makes with the receptor and compare them with the literature.&lt;/p&gt;&#xA;&lt;p&gt;Classical positional distance-based measurement is the RMSD calculation while the interaction-based measurement is the investigation of key residues in the specific case of study. For instance, a specific class of receptors have key residues that interact with endogenous ligands.&lt;/p&gt;&#xA;&lt;p&gt;We have recently developed a free web server for positional distance-based and interaction-based analysis of docking results (&lt;a href=&quot;https://pegasus.lbic.unibo.it/pacdock/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pegasus.lbic.unibo.it/pacdock/index.php&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I hope you find it useful.&lt;/p&gt;&#xA;" OwnerUserId="6158" LastActivityDate="2022-10-18T16:12:14.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9820" PostTypeId="1" CreationDate="2022-10-19T00:22:39.687" Score="2" ViewCount="118" Body="&lt;p&gt;Fleeces typically exhibit low thermal conductivity, and are often used in winter clothing for their insulating properties.&#xA;I am seeking a material for a radiant heat application that is soft to the touch like fleece, but transmits heat well.&lt;/p&gt;&#xA;&lt;p&gt;Measuring thermal conductivity in Watts per meter-Kelvin.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://inpressco.com/wp-content/uploads/2019/01/Paper241675-1678.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;This study&lt;/a&gt; found 15 fleece samples to all have thermal conductivity below 0.004 W/mK. Textiles with higher thermal conductivity include &lt;a href=&quot;http://lib.buet.ac.bd:8080/xmlui/bitstream/handle/123456789/2996/Full%20Thesis.pdf?sequence=1&amp;amp;isAllowed=y&quot; rel=&quot;nofollow noreferrer&quot;&gt;leather&lt;/a&gt; (0.1 to 0.15 W/mK) and &lt;a href=&quot;https://thermtest.com/how-thermal-conductivity-decides-what-you-put-in-your-closet&quot; rel=&quot;nofollow noreferrer&quot;&gt;linen&lt;/a&gt; (0.188 W/mK).&lt;/p&gt;&#xA;&lt;p&gt;I understand that the air trapped within fleece will impede heat flow. So a heat-transmitting fleece might have very dense 'hairs' to shrink air pockets. Alternatively, the hairs may be shorter.&lt;/p&gt;&#xA;&lt;p&gt;Heated blankets often incorporate fleeces. Do these blankets use particular fabrics to reduce insulative loss? Or do they just put out enough heat to compensate for the loss through poor conductivity?&lt;/p&gt;&#xA;" OwnerUserId="6159" LastEditorUserId="6159" LastEditDate="2022-10-19T00:40:48.783" LastActivityDate="2022-10-19T00:40:48.783" Title="High thermal conductivity in soft, fleece-like textiles" Tags="|thermal|" AnswerCount="0" CommentCount="0" ClosedDate="2022-11-28T19:16:11.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="9821" PostTypeId="2" ParentId="9766" CreationDate="2022-10-19T00:38:08.300" Score="7" Body="&lt;p&gt;I’m currently working on something like this. It is called Atomify, and runs lammps, visualization and analysis in Python purely in the web browser. You can take a look at &lt;a href=&quot;https://andeplane.github.io/atomify/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://andeplane.github.io/atomify/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Would love some feedback and suggestions on what you need.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Oython is a rarely used language, so switched to Python!&lt;/p&gt;&#xA;" OwnerUserId="6160" LastEditorUserId="6160" LastEditDate="2023-03-03T08:58:04.443" LastActivityDate="2023-03-03T08:58:04.443" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9822" PostTypeId="1" AcceptedAnswerId="11652" CreationDate="2022-10-19T06:35:15.930" Score="5" ViewCount="875" Body="&lt;p&gt;I am doing a simulation of a 3D LJ system in LAMMPS, where I am heating an already equilibrated configuration at &lt;span class=&quot;math-container&quot;&gt;$T^* = 0.3$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$T^* = 0.4$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$1000000$&lt;/span&gt; steps then equilibrating the same at &lt;span class=&quot;math-container&quot;&gt;$T^* = 0.4$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$3000000$&lt;/span&gt; steps. My system consists of 14713 atoms, the &lt;em&gt;lj/cut&lt;/em&gt; parameters I am using are &lt;span class=&quot;math-container&quot;&gt;$\epsilon = 1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\sigma = 1$&lt;/span&gt;, and cutoff &lt;span class=&quot;math-container&quot;&gt;$4.0$&lt;/span&gt;. Timestep size is default &lt;em&gt;lj&lt;/em&gt; timestep size &lt;span class=&quot;math-container&quot;&gt;$0.005 \tau$&lt;/span&gt;, and the &lt;em&gt;neighbor&lt;/em&gt; skin distance is &lt;em&gt;0.3 bin&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now I have a few questions regarding the &lt;em&gt;neigh_modify&lt;/em&gt; command. I have done 4 simulations using the conditions specified above but changing the &lt;em&gt;neigh_modify&lt;/em&gt; command arguments as below -&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;neigh_modify every 1 delay 0 check yes&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;neigh_modify every 1 delay 0 check no&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;neigh_modify every 20 delay 0 check yes&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;neigh_modify every 20 delay 0 check no&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nta41.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nta41.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have plotted the Total Energy vs Timestep for these 4 simulations and compared them, and the plots are identical. My 1st question is &lt;strong&gt;if regardless of how we build the neighbor list, the results are the same, what is the need for this command? or am I making comparisons with the wrong properties and I need to validate with some other properties?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also, in the case of &lt;code&gt;neigh_modify every 20 delay 0 check yes&lt;/code&gt; I get &lt;span class=&quot;math-container&quot;&gt;$50000$&lt;/span&gt; &lt;em&gt;Dangerous builds&lt;/em&gt; (which is equal to my &lt;em&gt;Neighbor list builds&lt;/em&gt;). &lt;strong&gt;What is the significance of this, if the energy of the system is statistically the same no matter what?&lt;/strong&gt;&#xA;P.S. - the 4 simulations are also identical throughout the whole simulation, visually.&lt;/p&gt;&#xA;&lt;p&gt;And finally, when I use &lt;code&gt;neigh_modify every 1 delay 0 check no&lt;/code&gt; the simulation runs almost twice as slow compared to all other cases. (&lt;span class=&quot;math-container&quot;&gt;$915.333$&lt;/span&gt; &lt;em&gt;timesteps/s&lt;/em&gt; compared to &lt;span class=&quot;math-container&quot;&gt;$\approx 2201.750$&lt;/span&gt; &lt;em&gt;timesteps/s&lt;/em&gt; on average for other cases). &lt;strong&gt;Why this is happening?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your help.&lt;/p&gt;&#xA;" OwnerUserId="605" LastActivityDate="2023-09-22T19:46:00.323" Title="About neigh_modify and dangerous builds in LAMMPS" Tags="|molecular-dynamics|lammps|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9823" PostTypeId="2" ParentId="9815" CreationDate="2022-10-19T07:10:14.823" Score="4" Body="&lt;p&gt;This seems like too broad of a question to get a good answer here, in fact I think most of the fun of your project will be finding out the best way to do this. One good place to start is this paper:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Kirkpatrick, James, Brendan McMorrow, David HP Turban, Alexander L. Gaunt, James S. Spencer, Alexander GDG Matthews, Annette Obika et al. &amp;quot;Pushing the frontiers of density functionals by solving the fractional electron problem.&amp;quot; Science 374, no. 6573 (2021): 1385-1389.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And more importantly, the associated GitHub repository:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In this paper, a deep neural network is interfaced with PySCF. You can even run the functional yourself using the repository. I think studying their code will give you the right direction.&lt;/p&gt;&#xA;" OwnerUserId="5167" LastActivityDate="2022-10-19T07:10:14.823" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9824" PostTypeId="1" AcceptedAnswerId="9830" CreationDate="2022-10-19T08:47:14.143" Score="3" ViewCount="70" Body="&lt;p&gt;I am trying to model a metal oxide system with an adsorbate in Quantum Espresso with the Environ module. For this, I am following an example from the module itself, example04 which&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;shows how to use pw.x to model 2D periodic systems in contact with a continuum solvent.&#xA;(from README file)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The file further goes on to state that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Note that the keyword solvent_mode='full' is mandatory in this calculation, &lt;strong&gt;in order to remove the artifact of the Pt valence density, which presents a hole close to the position of ion, due to the missing core electrons&lt;/strong&gt;. In order to avoid the continuum solvent to enter such a hole, a quickly vanishing gaussian density is added at the position of the nuclei when defining the dielectric. The same problem is likely to occur in halogens and other transition metals.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Can anyone give some idea as to what this artifact is in the Pt valence density, the hole close to the ion, and missing core electrons are?&lt;/p&gt;&#xA;&lt;p&gt;(The pseudopotentials used in the example are: O.pbe-rrkjus.UPF C.pbe-rrkjus.UPF Pt.pbe-nd-rrkjus.UPF)&lt;/p&gt;&#xA;&lt;p&gt;Any insights would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2022-10-21T06:36:08.300" Title="What is the artifact of the Pt valence density referred to in example04 of the Environ module?" Tags="|quantum-espresso|metals|implicit-solvent|metal-oxide|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9825" PostTypeId="2" ParentId="9574" CreationDate="2022-10-19T10:43:21.460" Score="4" Body="&lt;p&gt;I encountered the same problem and solved it just by setting the Fermi level to 0 eV.&#xA;&lt;code&gt;pyprocar.bandsplot(code = 'qe', mode='plain',repair = False,color=&amp;quot;r&amp;quot;,elimit=[-1,1],fermi = 0.000)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hope that helps!&lt;/p&gt;&#xA;" OwnerUserId="6161" LastEditorUserId="7" LastEditDate="2022-10-19T11:44:26.667" LastActivityDate="2022-10-19T11:44:26.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9826" PostTypeId="2" ParentId="9816" CreationDate="2022-10-19T18:27:00.703" Score="3" Body="&lt;p&gt;I really loved these two books:&lt;/p&gt;&#xA;&lt;h3&gt;Graham L. Patrick. &lt;a href=&quot;https://global.oup.com/uk/orc/chemistry/patrick6e/&quot; rel=&quot;nofollow noreferrer&quot;&gt;An Introduction to Medicinal Chemistry&lt;/a&gt;. Fifth Edition. Oxford University Press.&lt;/h3&gt;&#xA;&lt;p&gt;The structure of the book is the following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Part A contains six chapters that cover the structure&#xA;and function of important drug targets, such as receptors, enzymes, and nucleic acids. Students with a&#xA;strong background in biochemistry will already know&#xA;this material, but may find these chapters a useful&#xA;revision of the essential points.&lt;/li&gt;&#xA;&lt;li&gt;Part B covers pharmacodynamics in Chapters 7–10&#xA;and pharmacokinetics in Chapter 11. Pharmacodynamics is the study of how drugs interact with their molecular targets and the consequences of those interactions. Pharmacokinetics relates to the issues involved in a drug reaching its target in the first place.&lt;/li&gt;&#xA;&lt;li&gt;Part C covers the general principles and strategies&#xA;involved in discovering and designing new drugs and&#xA;developing them for the marketplace.&lt;/li&gt;&#xA;&lt;li&gt;Part D looks at particular ‘tools of the trade’ which are&#xA;invaluable in drug design, i.e. QSAR, combinatorial&#xA;synthesis, and computer-aided design.&lt;/li&gt;&#xA;&lt;li&gt;Part E covers a selection of specific topics within&#xA;medicinal chemistry—antibacterial, antiviral and&#xA;anti cancer agents, cholinergics and anti-cholinesterases, adrenergics, opioid analgesics, and anti-ulcer agents. To some extent, those chapters reflect the changing emphasis in medicinal chemistry research.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;Torsten Schwede and Manuel C Peitsch. &lt;a href=&quot;https://doi.org/10.1142/6659&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computational Structural Biology: Methods and Applications&lt;/a&gt;. Word Scientific.&lt;/h3&gt;&#xA;&lt;p&gt;The structure of the book is the following:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Structure Prediction and Assessment Methods: Protein Fold Recognition and Threading. Assessment of Protein Structure Predictions.&lt;/li&gt;&#xA;&lt;li&gt;From Structure to Function to Design: Evolution of Protein Folds. Atomistic Simulations of Reactions and Transition States Protein-Protein Interactions and Aggregation Processes.&lt;/li&gt;&#xA;&lt;li&gt;Drug Discovery and Pharmacology: Molecular Dynamics-Based Free Energy Simulations. Structure-Based Computational Approaches to Drug Metabolism.&lt;/li&gt;&#xA;&lt;li&gt;New Frontiers in Experimental Methods: New Frontiers in X-Ray Crystallography. New Frontiers in Characterizing Structure and Dynamics by NMR.&lt;/li&gt;&#xA;&lt;li&gt;Selected Topics: Docking for Neglected Diseases as Community Efforts. Protein Structure Databases. Molecular Graphics in Structural Biology.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-10-19T18:27:00.703" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9827" PostTypeId="2" ParentId="9818" CreationDate="2022-10-19T18:41:00.210" Score="4" Body="&lt;h3&gt;&lt;a href=&quot;https://go.drugbank.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;DrugBank&lt;/a&gt;&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Knowledge base for drug interactions, pharmacology, chemical structures, targets, metabolism, &amp;amp; more. Download limited datasets, free for academic &amp;amp; non-commercial researchers. 500,000 drugs &amp;amp; drug products.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;a href=&quot;https://zinc.docking.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Zinc&lt;/a&gt;&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free database of commercially-available compounds for virtual screening. ZINC contains over 230 million purchasable compounds in ready-to-dock, 3D formats. ZINC also contains over 750 million purchasable compounds you can search for analogs in under a minute.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h3&gt;&lt;a href=&quot;https://www.ccdc.cam.ac.uk/solutions/csd-core/components/csd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Cambridge Structural Database (CSD)&lt;/a&gt;&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Organic crystal structures include: Drugs and pharmaceuticals.     Agrochemicals. Pigments. Explosives. Protein ligands.&lt;/li&gt;&#xA;&lt;li&gt;Metal-Organic crystal structures include: Metal Organic Frameworks (MOFs). Models for new catalysts. Porous frameworks for gas storage. Fundamental chemical bonding.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-10-19T18:41:00.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9828" PostTypeId="1" AcceptedAnswerId="9843" CreationDate="2022-10-20T05:31:41.123" Score="6" ViewCount="118" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{V}(\mathbf{r}^N)=\sum_\text{bonds}\frac{k_i}{2}(l_i-l_{i,0})^2 + \sum_\text{angles}\frac{k_i}{2}(\theta_i-\theta_{i,0})^2 + \sum_\text{torsions}\frac{V_n}{2}(1+\cos(n\omega-\gamma) + \sum^N_{i=1}\sum^N_{j=i+1}\left(4\varepsilon_{ij}\left[\left(\frac{\sigma_{ij}}{r_{ij}} \right)^{12} - \left(\frac{\sigma_{ij}}{r_{ij}} \right)^6 \right] + \frac{q_iq_j}{4\pi\varepsilon_0 r_{ij}} \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above is potential energy expression for a molecule in vacuum. This part is clear to me!&lt;/p&gt;&#xA;&lt;p&gt;Now lets put this molecule (in my case protein) in water and run molecular dynamics. Now I have to take solvent effect in my MD. As far as I know, there are two ways:&lt;/p&gt;&#xA;&lt;p&gt;** SYSTEM = Protein + Water **&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Change the &lt;span class=&quot;math-container&quot;&gt;$ \epsilon _0 =1 $&lt;/span&gt;  to &lt;span class=&quot;math-container&quot;&gt;$ \epsilon  =80 $&lt;/span&gt; (water has dielectric const. of 80) which will reduce my electrostatic force, and that is all the effect the solvent has on the system.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Now second way is to model the waters as rigid 3-sites molecule with formal charge on oxygen and hydrogen such as TIP3P etc. Now in this model we don't change the dielectric constant, that is we keep &lt;span class=&quot;math-container&quot;&gt;$ \epsilon =1$&lt;/span&gt; while simulating the system. Now while calculating the potential energy of the molecule we have to add extra terms in the above expression, which can be expressed as &lt;span class=&quot;math-container&quot;&gt;$$\sum_{i=0}^N \sum _{j=0}^{3M}   {q_i q_j} /{\epsilon _0 r(ij) }$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is the number of water molecules. So this additional electrostatic part is energy due to interaction between all sites of every water molecule in the system and each atom in our protein molecule. Please note that &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the total number of atoms in our protein molecule and &lt;span class=&quot;math-container&quot;&gt;$r(ij)$&lt;/span&gt; is the distance between &lt;span class=&quot;math-container&quot;&gt;$i^{th}$&lt;/span&gt; site and &lt;span class=&quot;math-container&quot;&gt;$j^{th}$&lt;/span&gt; site. Now one more additional part is due to Van der Walls interaction between protein and water, which can be expressed in similar manner as above.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;One more overhead in the second way is that I also have to calculate potential energy of each water molecule in similar fashion as above. And during the entire process in second way the dielectric constant is set to 1 (i.e. vacuum).&lt;/p&gt;&#xA;&lt;p&gt;Is my description of working of the second way is correct?? Can someone please shed some light?&lt;/p&gt;&#xA;" OwnerUserId="5822" LastEditorUserId="7" LastEditDate="2022-10-24T21:11:34.017" LastActivityDate="2022-10-25T19:00:07.650" Title="Protein Molecular Dynamics in water" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9829" PostTypeId="1" CreationDate="2022-10-20T12:43:14.363" Score="5" ViewCount="100" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/jcc.23330&quot; rel=&quot;nofollow noreferrer&quot;&gt;High–quality protein backbone reconstruction from alpha carbons using Gaussian mixture models&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The above research paper is about a software tool for reconstructing a protein's main chain model only from its alpha-carbon backbone (aka, C-alpha trace).&lt;/p&gt;&#xA;&lt;p&gt;This tool provides two options: conversion (1) with energy minimization, and (2) without energy minimization.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.intechopen.com/chapters/74105&quot; rel=&quot;nofollow noreferrer&quot;&gt;Energy Minimization&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The above paper says that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;...&lt;br /&gt;&#xA;The goal of energy Minimization is to find a set of coordinates representing the minimum energy conformation for the given structure.&lt;br /&gt;&#xA;...&lt;br /&gt;&#xA;In molecular modeling we tend to are particularly curious about minimum points on the energy surface. Minimum energy arrangements of the atoms correspond to stable states of the system; any movement off from a minimum provides a configuration with a better energy.&lt;br /&gt;&#xA;...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I haven't understood the quote from the second paper.&lt;/p&gt;&#xA;&lt;p&gt;Why do we need to know the minimum energy conformation of a protein chain? I.e., why do we want to do &lt;em&gt;energy minimization&lt;/em&gt;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2022-10-21T05:10:40.157" LastActivityDate="2023-11-08T21:05:25.640" Title="Why do we need to find minimum energy in a protein chain?" Tags="|proteins|energy|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9830" PostTypeId="2" ParentId="9824" CreationDate="2022-10-20T15:28:01.380" Score="4" Body="&lt;p&gt;I saw your post on the google group. I guess you haven’t gotten a response there yet. So the problem stems from the fact that pseudopotentials don’t have core electrons. If you were to compute the electron density using pseudopotentials, you’d see spherical holes centered on the nuclei with radii equal to the radial cutoffs of the pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;Now why do we want to remove core electrons? Because it greatly improves the computational cost of the simulation, and since core electrons don’t participate in chemical bond formation, it’s safe to do so. If you left the core electrons (that is to say, you performed an all electron calculation) you’d need to use extremely high planewave cutoffs to capture the small / high frequency oscillations associated with core electron orbitals and the associated potential. This is standard practice in all planewave pseudopotential DFT codes.&lt;/p&gt;&#xA;&lt;p&gt;Now what Environ tries to do is to fill the vacuum region in a DFT cell with an electron density-dependent dielectric permittivity function. The problem with this is that, with pseudopotentials, there is essentially vacuum in the core region due to the missing explicit electrons there. So to prevent implicit solvent from filling the core regions, auxiliary Gaussian charges are added to trick the code into thinking there is finite electron density in the core region, thereby preventing solvent from being accidentally added inside of the atoms.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-10-21T06:36:08.300" LastActivityDate="2022-10-21T06:36:08.300" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9831" PostTypeId="1" CreationDate="2022-10-21T09:47:32.277" Score="3" ViewCount="49" Body="&lt;p&gt;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.127.277201&quot; rel=&quot;nofollow noreferrer&quot;&gt;In this paper&lt;/a&gt;, the authors argue the following response relation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$j_a=\sigma_{abc}E_bE_c \tag{1}$$&lt;/span&gt;&#xA;can occur in systems with &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-symmetry with &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; the time-reversal symmetry and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; the inversion symmetry, where we assume that&#xA;&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is free of the relaxation time &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;. This is due to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{T}j_a \rightarrow -j_a, \mathcal{T}E_b \rightarrow E_b, \mathcal{P}j_a=-j_a,&#xA;\mathcal{P}E_b\rightarrow -E_b, $$&lt;/span&gt;&#xA;therefore, we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{P}\mathcal{T} \sigma_{abc}=\sigma_{abc}$$&lt;/span&gt;&#xA;which means the response relation can be appeared in &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-symmetric systems. The analysis seems reasonable. Following the same strategy, let's look at the response relation for the spin Hall effect:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$j^a_b=\sigma_{abc}^{SHE}E_c \tag{2},$$&lt;/span&gt;&#xA;in which the spin current &lt;span class=&quot;math-container&quot;&gt;$j_b^a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_c$&lt;/span&gt; remain unchanged under &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;, Eq.(2) can exist in &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetric systems. Now let's consider the inversion symmetry &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;, we find that &lt;span class=&quot;math-container&quot;&gt;$j_b^a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_c$&lt;/span&gt; also remain unchanged under &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;, and we conclude that Eq.(2) can exist in &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetric systems.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Therefore, I conclude that the spin Hall effect can only exist in systems with both&#xA;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Is this right? I guess the answer is no.&lt;/p&gt;&#xA;&lt;p&gt;Because &lt;a href=&quot;https://journals-aps-org-s.libyc.nudt.edu.cn/prl/abstract/10.1103/PhysRevLett.117.146403&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this paper&lt;/a&gt;, the authors predicted the spin Hall effect in the Weyl semimetals TaAs family, in which &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; is preserved but &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt; is broken.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Following this, can I think that the spin hall effect can also be supported by the magnetic Weyl semimetals with &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetry?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2023-06-16T02:58:08.790" Title="When we can justify the response to be hold in terms of symmetry?" Tags="|symmetry|electronic-transport|response-theory|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9832" PostTypeId="1" AcceptedAnswerId="10448" CreationDate="2022-10-21T10:46:00.517" Score="4" ViewCount="153" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://combichem.blogspot.com/2013/08/aligning-pdb-structures-with-biopython.html?sc=1666327420775#c409902795252634833&quot; rel=&quot;nofollow noreferrer&quot;&gt;Aligning PDB structures with Biopython&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The following source code is obtained from the above link:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    import Bio.PDB    &#xA;    # Select what residues numbers you wish to align&#xA;    # and put them in a list&#xA;    start_id = 1&#xA;    end_id   = 70&#xA;    atoms_to_be_aligned = range(start_id, end_id + 1)&#xA;    &#xA;    # Start the parser&#xA;    pdb_parser = Bio.PDB.PDBParser(QUIET = True)&#xA;    &#xA;    # Get the structures&#xA;    ref_structure = pdb_parser.get_structure(&amp;quot;reference&amp;quot;, &amp;quot;c:/home/bbq_input_pdb/pdb1a6j.pdb&amp;quot;)&#xA;    sample_structure = pdb_parser.get_structure(&amp;quot;sample&amp;quot;, &amp;quot;c:/home/bbq_output_pdb/1a6j.pdb&amp;quot;)&#xA;    &#xA;    # Use the first model in the pdb-files for alignment&#xA;    # Change the number 0 if you want to align to another structure&#xA;    ref_model    = ref_structure[0]&#xA;    sample_model = sample_structure[0]&#xA;    &#xA;    # Make a list of the atoms (in the structures) you wish to align.&#xA;    # In this case we use CA atoms whose index is in the specified range&#xA;    ref_atoms = []&#xA;    sample_atoms = []&#xA;    &#xA;    # Iterate of all chains in the model in order to find all residues&#xA;    for ref_chain in ref_model:&#xA;      # Iterate of all residues in each model in order to find proper atoms&#xA;      for ref_res in ref_chain:&#xA;        # Check if residue number ( .get_id() ) is in the list&#xA;        if ref_res.get_id()[1] in atoms_to_be_aligned:&#xA;          # Append CA atom to list&#xA;          ref_atoms.append(ref_res['CA'])&#xA;    &#xA;    # Do the same for the sample structure&#xA;    for sample_chain in sample_model:&#xA;      for sample_res in sample_chain:&#xA;        if sample_res.get_id()[1] in atoms_to_be_aligned:&#xA;          sample_atoms.append(sample_res['CA'])&#xA;    &#xA;    # Now we initiate the superimposer:&#xA;    super_imposer = Bio.PDB.Superimposer()&#xA;    super_imposer.set_atoms(ref_atoms, sample_atoms)&#xA;    super_imposer.apply(sample_model.get_atoms())&#xA;    &#xA;    # Print RMSD:&#xA;    print(&amp;quot;RMSD = &amp;quot;, super_imposer.rms)&#xA;    &#xA;    ## Save the aligned version of 1UBQ.pdb&#xA;    #io = Bio.PDB.PDBIO()&#xA;    #io.set_structure(sample_structure)&#xA;    #io.save(&amp;quot;1UBQ_aligned.pdb&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This source code compares two PDB protein files and computes their RMSD values.&lt;/p&gt;&#xA;&lt;p&gt;However, I observed that:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;This tool gives different values than that of PyMOL with the same files&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Can anyone tell me where the bug is, as I cannot locate it?&lt;/p&gt;&#xA;&lt;p&gt;Note: It shows values even if we compare a file with itself - in PyMOL, it is not possible to compare a file with itself&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-02-20T06:28:11.803" Title="Why is this source code giving incorrect RMSD value?" Tags="|python|proteins|pdb|pymol|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9833" PostTypeId="1" CreationDate="2022-10-21T21:17:24.947" Score="2" ViewCount="29" Body="&lt;p&gt;I constructed a PDB file of main-chain from its CA-trace using &lt;code&gt;pd2_ca2main&lt;/code&gt; app. I used &lt;a href=&quot;https://zhanggroup.org/TM-align/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;TMalign&lt;/code&gt;&lt;/a&gt; to compute RMSD values from those two files.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1084323/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The research paper of TMaligh&lt;/a&gt; says that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;TM-align only employs the backbone Cα coordinates of the given protein structures; however, the methodology is readily generalized to any type of atom.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Therefore, the source PDB and the resultant PDB have the same CAs. Right? If so, why do I see a deviation when I compare the source PDB and the resultant PDB?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-07-11T20:02:55.337" Title="Why do I see a deviation when I compare PDBs using TMalign?" Tags="|proteins|pdb|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9834" PostTypeId="1" AcceptedAnswerId="9850" CreationDate="2022-10-22T14:01:45.877" Score="6" ViewCount="149" Body="&lt;p&gt;I know that the HOMO, LUMO, and its gap are useful in understanding the physical properties and chemical reactions of molecules.&lt;/p&gt;&#xA;&lt;p&gt;Here, are there any phenomena in physics or chemistry that other orbitals are very important than the HOMO and LUMO?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastActivityDate="2022-10-25T15:18:13.230" Title="Importance of orbitals other than HOMO and LUMO" Tags="|quantum-chemistry|orbitals|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9835" PostTypeId="1" AcceptedAnswerId="9836" CreationDate="2022-10-22T20:53:40.073" Score="6" ViewCount="153" Body="&lt;p&gt;I have a set of files like this in a directory named 'test':&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cij_000.POSCAR cij_001.POSCAR cij_002.POSCAR ....... cij_029.POSCAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It has also four other files in the same 'test' directory as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INCAR POSCAR POTCAR KPOINTS&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What I want is, I want to create subdirectories within the 'test' directory according to the 'cij_xxx.POSCAR' file name (for example, as 'calc-xxx' are the subdirectory names), and then copy/link the other files (except the POSCAR file), and finally copy/link the 'cij_xxx.POSCAR' file to that subdirectory ('calc-xxx') as the name 'POSCAR'.&lt;/p&gt;&#xA;&lt;p&gt;I tried the following bash script, somehow it is not doing anything (not creating the 'calc' directory and not linking the files thereby).&lt;/p&gt;&#xA;&lt;p&gt;Could you please suggest me what should I correct, or any revised bash script suggestion?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;&lt;p&gt;The bash script I tried (which didn't work unfortunately):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;&#xA;for s in &lt;span class=&quot;math-container&quot;&gt;$* ; do&#xA;    d=$&lt;/span&gt;{s%%.POSCAR}&#xA;    echo -n  &lt;span class=&quot;math-container&quot;&gt;$d &quot;: &quot;&#xA;mkdir calc-$&lt;/span&gt;d&#xA;    (   &#xA;        cd calc-&lt;span class=&quot;math-container&quot;&gt;$d&#xA;    ln -s ../INCAR ../KPOINTS ../POTCAR .&#xA;    ln -s ../$&lt;/span&gt;s POSCAR&#xA;    )&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-10-22T23:20:05.343" Title="Bash script - making set of subdirectories according to some file names in the directory" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9836" PostTypeId="2" ParentId="9835" CreationDate="2022-10-22T23:20:05.343" Score="8" Body="&lt;p&gt;A useful way to debug bash scripts is to &lt;code&gt;echo&lt;/code&gt; each variable as it's set. At least on my system your for loop doesn't actually list all files, and the part where you extract the number &lt;code&gt;xxx&lt;/code&gt; also does not work.. You could try&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;for filename in ./*.POSCAR ; do&#xA;    echo &lt;span class=&quot;math-container&quot;&gt;$filename&#xA;    d=$&lt;/span&gt;(echo &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$filename&quot; | grep -o -E '[0-9]+')&#xA;    echo -n $&lt;/span&gt;d &amp;quot;: \n&amp;quot;&#xA;    mkdir -p calc-&lt;span class=&quot;math-container&quot;&gt;$d&#xA;    cd calc-$&lt;/span&gt;d&#xA;    ln -sf ../INCAR ../KPOINTS ../POTCAR .&#xA;    ln -sf ../$filename POSCAR&#xA;    cd ..&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;mkdir -p&lt;/code&gt; and &lt;code&gt;ln -f&lt;/code&gt; flags removes errors from directories already existing, and makes &lt;code&gt;ln&lt;/code&gt; overwrite any previous link.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2022-10-22T23:20:05.343" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9837" PostTypeId="1" CreationDate="2022-10-23T20:45:13.093" Score="2" ViewCount="45" Body="&lt;p&gt;I am working with protein PDB files.&lt;/p&gt;&#xA;&lt;p&gt;Application 'A' generated 3884 PDB files from the protein's CA-trace. Application 'B' did the same.&lt;/p&gt;&#xA;&lt;p&gt;So, I calculated the CRMSD values of each pair of files for both 'A' and 'B.' I.e., I have 3884 CRMSD valued for 'A' and another 3884 for 'B.'&lt;/p&gt;&#xA;&lt;p&gt;Now, I want to find out which application is better.&lt;/p&gt;&#xA;&lt;p&gt;How can I do that?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2022-10-23T20:45:13.093" Title="How can I compute the performance of an application software?" Tags="|proteins|pdb|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-09T22:52:19.260" ContentLicense="CC BY-SA 4.0" />
  <row Id="9838" PostTypeId="1" CreationDate="2022-10-24T07:24:41.017" Score="3" ViewCount="28" Body="&lt;p&gt;It has been answered to my previous question that RI-MP2/cc-pVTZ/cc-pVTZ gives results of the same quality as MP2/cc-pVTZ. I then started to think about RI-MP2/cc-pVTZ/cc-pVQZ.&lt;/p&gt;&#xA;&lt;p&gt;The term &amp;quot;basis set&amp;quot; literally comes from Fourier analysis in mathematics, and in Fourier analysis the &amp;quot;errors&amp;quot; systematically &amp;quot;cancel out&amp;quot;, for example when integrating a Fourier series expansion to find out the coefficients. This might somehow mean that the TZ errors cancel out and leave only the QZ errors, smaller than the original TZ errors behind; i.e. RI-MP2/cc-pVTZ/cc-pVQZ might be of the same quality as MP2/cc-pVQZ.&lt;/p&gt;&#xA;&lt;p&gt;Is my logic (approximately of course, but still at least qualitatively) true?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-10-25T15:11:23.347" Title="Does the accuracy of RI-MP2 follow the higher number of zetas of the main and fitting bases?" Tags="|basis-sets|wavefunctions|basis-set-superposition-error|fourier-transform|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9839" PostTypeId="1" AcceptedAnswerId="9848" CreationDate="2022-10-24T09:10:45.153" Score="3" ViewCount="52" Body="&lt;p&gt;Yes, it is about my molecule that you've heard of (but never seen) in my previous questions. The molecule, which contains only C, Al, B, Cl, Mg, N, O, S and Si, is macromolecular with quite crowded monomers- cyanide-like ultrashort bonds, nonbonded distances a mere 0.3Å longer than the sum of covalent radii, bridge-bonded (as in the two borons of diborane) Al-Al distances of less than 2Å and so on.&lt;/p&gt;&#xA;&lt;p&gt;I'm using a double hybrid so I need to adjust the MP2 part of the total cost- are frozen-core approximations appropriate for bond lengths, vertical ionisation energies/electron affinities, and NBO orbital occupancies/populations of specific orbitals of bonds given as results by NBO, or would a full-electron treatment be more appropriate for the calculation of the aforementioned properties? I'm at the level RI-B2PLYP-D3/def2-TZVPPD/def2-TZVPPD.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-10-25T15:09:53.500" Title="Are frozen-core approximations for the elements of first or second row accurate for potentially extremely short bond distances present in the molecule" Tags="|density-functional-theory|electronic-structure|electron-correlation|wavefunctions|valence-bond-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9840" PostTypeId="1" CreationDate="2022-10-24T09:45:14.227" Score="6" ViewCount="592" Body="&lt;p&gt;My question is mainly one about consistency in the smearing method used for a standard &amp;quot;geometry relaxation + band structure (BS) + density of states (DOS)&amp;quot; set of calculations. This is a general query, but I make heavy reference to the Vienna Ab initio Simulation Package (VASP).&lt;/p&gt;&#xA;&lt;p&gt;For gapped systems, I understand that the tetrahedron method (&lt;code&gt;ISMEAR = -5&lt;/code&gt; in VASP) is recommended for a high-quality DOS (Ref: the VASP &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISMEAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;wiki&lt;/a&gt; this &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S277294942200002X?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;). However, if I were to do a BS calculation with a &lt;code&gt;line mode&lt;/code&gt; &lt;code&gt;KPOINTS&lt;/code&gt; file such as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Line_mode KPOINTS file&#xA;20&#xA;Line_mode&#xA;Reciprocal&#xA;0.0 0.0 0.0 ! \Gamma&#xA;0.3333333333333333 0.3333333333333333 0.0 ! K&#xA;&#xA;0.3333333333333333 0.3333333333333333 0.0 ! K&#xA;0.5 0.0 0.0 ! M&#xA;&#xA;0.5 0.0 0.0 ! M&#xA;0.0 0.0 0.0 ! \Gamma&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the tetrahedron method would of course be incompatible and give the following error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;The linear tetrahedron method can not  be used with the KPOINTS file   |&#xA;|      (generation of strings of k-points)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this case, it would be necessary, for example, to use Gaussian smearing (&lt;code&gt;ISMEAR = 0&lt;/code&gt; in VASP).&lt;/p&gt;&#xA;&lt;p&gt;Hence, my concern is that we can't seem to consistently use the same smearing method for the entire &amp;quot;geometry relaxation (e.g. with &lt;code&gt;ISIF = 3&lt;/code&gt;) + BS + DOS&amp;quot; set of calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;As the optimized geometry using both smearing methods is effectively indistinguishable within some small tolerance (based on my tests), my main question is if it is acceptable / standard practice to, for example, perform the geometry relaxation (and BS calculation) with Gaussian smearing (&lt;code&gt;ISMEAR = 0&lt;/code&gt;) and only switch over to the tetrahedron method (&lt;code&gt;ISMEAR = -5&lt;/code&gt;) for the DOS calculations (besides other changes like increasing the k-point density)?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="6131" LastEditDate="2022-10-24T13:29:41.000" LastActivityDate="2023-06-12T04:01:51.413" Title="Standard Practice for Relaxation, Band Structure and Density of States Calculations wrt smearing method" Tags="|vasp|band-structure|density-of-states|smearing|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9841" PostTypeId="1" AcceptedAnswerId="9851" CreationDate="2022-10-24T15:04:28.297" Score="5" ViewCount="92" Body="&lt;p&gt;I am using &lt;strong&gt;GIMIC&lt;/strong&gt; for evaluating DFT-calculations of aromatic compounds and visualizing magnetically induced aromatic ring currents. There is a nice way of visualizing them via a so called stream line plot, but I have to do it in another way. In the GIMIC docs (&lt;a href=&quot;https://gimic.readthedocs.io/en/latest/interpretation.html&quot; rel=&quot;noreferrer&quot;&gt;https://gimic.readthedocs.io/en/latest/interpretation.html&lt;/a&gt;) there is a kind of visualization, which I have seen in different papers. This is the exact type of visualization I need to do and the authors call it &amp;quot;&lt;strong&gt;line integral convolution on a surface&lt;/strong&gt;&amp;quot; and on the website (see link) there is the corresponding figure.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately there is no explanation whatsoever how to create this plot in the recommended program &lt;em&gt;ParaView&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know how to create this kind of plot ? Any help is heavily appreciated.&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2022-10-25T18:51:34.517" Title="How to use GIMIC for &quot;line integral convolution on a surface&quot; in ParaView?" Tags="|density-functional-theory|quantum-chemistry|nuclear-magnetic-resonance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9842" PostTypeId="2" ParentId="9606" CreationDate="2022-10-24T15:55:07.590" Score="4" Body="&lt;p&gt;If you're starting out from bulk structures (which can be obtained from databases like &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project&lt;/a&gt;), I've found &lt;a href=&quot;https://pymatgen.org/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymatgen&lt;/a&gt;'s &lt;a href=&quot;https://pymatgen.org/pymatgen.core.surface.html#pymatgen.core.surface.SlabGenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;SlabGenerator&lt;/a&gt; to be useful. Its class definition looks like this.&#xA;&lt;code&gt;SlabGenerator(initial_structure, miller_index, min_slab_size, min_vacuum_size, lll_reduce=False, center_slab=False, in_unit_planes=False, primitive=True, max_normal_search=None, reorient_lattice=True)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can choose which plane to cut (&lt;code&gt;miller_index&lt;/code&gt;), how many layers you want to include (&lt;code&gt;min_slab_size&lt;/code&gt;), etc, which should simplify the generation of monolayer or multi-layer &lt;code&gt;POSCAR&lt;/code&gt;s from bulk inputs.&lt;/p&gt;&#xA;&lt;p&gt;If you start with monolayer structures (for example, you could get the &lt;code&gt;POSCAR&lt;/code&gt;s from &lt;a href=&quot;http://www.2dmatpedia.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;2DMatPedia&lt;/a&gt;), I'm not sure if there's any out-of-the-box method to generate &lt;code&gt;POSCAR&lt;/code&gt;s for multi-layered structures directly, but you can use Pymatgen's &lt;a href=&quot;https://pymatgen.org/pymatgen.core.structure.html#pymatgen.core.structure.Structure&quot; rel=&quot;nofollow noreferrer&quot;&gt;Structure&lt;/a&gt; class and other utilities to get the job done rather conveniently.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-10-24T15:55:07.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9843" PostTypeId="2" ParentId="9828" CreationDate="2022-10-24T16:06:38.700" Score="6" Body="&lt;h2&gt;Method 2 is essentially correct&lt;/h2&gt;&#xA;&lt;p&gt;Your description of the method 2, which is usually called &lt;strong&gt;explicit-solvent simulation&lt;/strong&gt;, is essentially correct. In explicit-solvent calculations, atoms of water are in principle treated the same as atoms of the protein. As you suggest, the dielectric constant is taken to be 1. In a simplified picture, there are nonbonded forces between all non-excluded pairs of atoms (atoms covalently bonded to each other or covalently bonded to a third shared atom are usually excluded from nonbonded forces). However, for computational efficiency, Lennard-Jones forces for pairs with separation distances larger than some value (e.g. 12 Å), are ignored, and Coulomb interactions are approximated using the &lt;a href=&quot;https://doi.org/10.1063/1.464397&quot; rel=&quot;nofollow noreferrer&quot;&gt;PME method&lt;/a&gt; or other algorithms that reduced the computational complexity from &lt;span class=&quot;math-container&quot;&gt;$O(N^2)$&lt;/span&gt; to something more manageable (&lt;span class=&quot;math-container&quot;&gt;$O(N \log N)$&lt;/span&gt; for PME). Recently, using a PME-like algorithm for Lennard-Jones interactions has become more common as well. As an added complication, the common water models (TIP3P, TIP4P variants, OPC, SPC/E) used are typically held rigid (rigid bonds and rigid angles). Popular protein models use rigid bonds with hydrogen atoms as well (CHARMM and Amber).&lt;/p&gt;&#xA;&lt;h2&gt;Method 1 is very crude and not used with atomistic models&lt;/h2&gt;&#xA;&lt;p&gt;The alternative to explicit-solvent simulation is &lt;strong&gt;implicit-solvent&lt;/strong&gt; simulation. However, the method you described of simply using a dielectric constant of 80 is a very poor model of reality for molecular simulations. Consider the hydrogen bonds inside of a protein alpha helix. No water molecules are present inside the helix and there is no room for water molecules between hydrogen bonding groups of the helix (NH and C=O groups); however, in this method, you are reducing the electrostatic energy by a factor of 80 as if these interactions were fully screened by water. &lt;strong&gt;The discrete size of water molecules for molecular interactions plays an important role and cannot by represented by a dielectric continuum.&lt;/strong&gt; Furthermore, entropic effects must be considered as well: water molecules hydrogen-bonded to protein groups are less free to reorient in response to external electric fields. Implicit solvent methods usually include implicit screening from dissolved ions as well. Hence, implicit-solvent methods are more complicated than what you've described. The most common method used today for implicit-solvent molecular dynamics simulations is probably the &lt;a href=&quot;https://doi.org/10.1002/1097-0282(2000)56:4%3C275::AID-BIP10024%3E3.0.CO;2-E&quot; rel=&quot;nofollow noreferrer&quot;&gt;generalized Born surface-area&lt;/a&gt; method, which is implemented in many MD codes such as Amber, NAMD, and OpenMM. Other more accurate methods may be beginning to supersede it, however.&lt;/p&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2022-10-25T19:00:07.650" LastActivityDate="2022-10-25T19:00:07.650" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9844" PostTypeId="1" CreationDate="2022-10-24T18:36:54.807" Score="6" ViewCount="315" Body="&lt;p&gt;Let suppose that, for a given reason, a PDB file (with all the residues/chains/heteratom/cofactor/ligand information inside) is converted to a XYZ file. Doing that, all protein information  is lost.&lt;/p&gt;&#xA;&lt;p&gt;Converting XYZ to PDB is straight forward using software like OpenBabel, Mercury, etc., but those package do a direct conversion, so I end with a PDB with atoms and coordinates and no protein specific information.&lt;/p&gt;&#xA;&lt;p&gt;I wonder: &lt;strong&gt;Is there a way to convert the XYZ file back to PDB but recovering the protein information (residues/chain) now?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-10-25T20:08:56.797" Title="Is it possible to recover the protein structure after conversions PDB-&gt;XYZ-&gt;PDB?" Tags="|software-recommendations|proteins|openbabel|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9845" PostTypeId="2" ParentId="9844" CreationDate="2022-10-25T05:17:31.867" Score="8" Body="&lt;p&gt;Yes, it is possible.  Of course, the original residue numbering will be lost; but you can certainly recover the sequence, and number the residues within any contiguous chain.&lt;/p&gt;&#xA;&lt;p&gt;How to do it really depends on what software you have access to.  I don't know of any software that would do it off the shelf.  OpenEye toolkit would do a decent job of inferring bond orders and formal charges from coordinates; I have used that before successfully to convert a large xyz to mol2, although not quite at the scale of a full protein.  After that you'd have to do some work to iterate the bonds and determine which bonds and atoms form the backbone, and from there which atoms are in the same aminoacid (each backbone N-C-C(=O) and everything connected to the Calpha, following bonds recursively).  The Chemical Component Dictionary &lt;a href=&quot;http://www.wwpdb.org/data/ccd&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.wwpdb.org/data/ccd&lt;/a&gt; would give a list of both standard and modified aminoacids that you can match to to get the residue name and assign atom names within it.  There will still be a bit of ambiguity in symmetric aminoacids, for example in glutamic acid you might not know which oxygen was OE1 and which OE2 in the original pdb; but they are interchangeable anyway.&lt;/p&gt;&#xA;&lt;p&gt;If you ever get this fully working, please make it an open source project :)&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2022-10-25T20:08:56.797" LastActivityDate="2022-10-25T20:08:56.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9846" PostTypeId="1" AcceptedAnswerId="9847" CreationDate="2022-10-25T06:59:13.417" Score="4" ViewCount="323" Body="&lt;p&gt;I'm interested in running CASSCF calculations to get a dissociation curve for a number of systems of the form: atom-atom, atom-diatomic or diatomic-diatomic (e.g. Li+ ... O-, K+ ... O2, or N(3-) ... Ar).  The two interacting species can be charged, but usually would not involve any radicals.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to get the right number of electrons and number of orbitals to use in CASSCF from just knowing what atoms or diatomic species are involved?&lt;/p&gt;&#xA;&lt;p&gt;P.S. I'm using Orca.  The manual says to run an MP2 calculation and then &amp;quot;occupation numbers between 1.98 and 0.02 should be in the active space&amp;quot;; but also it seems like there is trial and error after that.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="5" LastEditDate="2022-10-25T16:03:05.973" LastActivityDate="2022-10-25T16:03:05.973" Title="How many electrons and orbitals should I include in a CASSCF calculation?" Tags="|orbitals|orca|casscf|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9847" PostTypeId="2" ParentId="9846" CreationDate="2022-10-25T14:52:14.340" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is there a way to get the right number of electrons and number of orbitals to use in CASSCF from just knowing what atoms or diatomic species are involved?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The &amp;quot;right&amp;quot; number of electrons and orbitals, is &amp;quot;all electrons&amp;quot; and &amp;quot;all orbitals&amp;quot; if you want to get the correct energy for your given basis set to within 1 Hz precision, for example. This is why &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9846/how-many-electrons-and-orbitals-should-i-include-in-a-casscf-calculation#comment20737_9846&quot;&gt;wzchem5's comment&lt;/a&gt; says that it all depends on your &lt;strong&gt;desired precision&lt;/strong&gt; and &lt;strong&gt;computational budget&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the other extreme, you can use what is called a &amp;quot;full valence active space&amp;quot; which is often considered a &amp;quot;minimum active space&amp;quot;. Here you would include all &lt;em&gt;valence&lt;/em&gt; electrons of the constituent atoms, and all orbitals in the appropriate shell. For example the carbon atom has electrons in only two p-orbitals, but you'd have to include all three p-orbitals (px,py,pz) because it would not be appropriate to pick only (px,py) or only (py,pz), for example.&lt;/p&gt;&#xA;&lt;p&gt;If this &amp;quot;minimal active space&amp;quot; isn't good enough for your purposes, there's many options to grow the active space. For example you can include the next shell of empty orbitals, or the next shell of occupied orbitals, or both, or even more. This all depends on the accuracy you want, and the resources that you have available.&lt;/p&gt;&#xA;&lt;p&gt;This &amp;quot;rule of thumb&amp;quot; that you mentioned, in which the arbitrary limits of 1.98 and 0.02 are chosen for the occupation numbers, is likely meant for systems that are too large for the above strategy. For the systems that you described as examples in your post, it doesn't seem necessary to resort to such an &lt;em&gt;arbitrary&lt;/em&gt; choice. For &lt;span class=&quot;math-container&quot;&gt;$\ce{Li+-O-}$&lt;/span&gt; there's only 2 possible electrons coming from Li+, and at most 9 electrons coming from O-. If you were to include the 1s and 2s orbitals for Li+ and the 1s,2s,2px,2py,2pz orbitals for O-, then you have only 7 spatial orbitals in total. A CAS(11e,7o)SCF calculation is usually no problem on a computer from this century (it was fun to use the word &amp;quot;century&amp;quot; like this, but &amp;quot;this decade&amp;quot; or even &amp;quot;the last two decades&amp;quot; wouldn't be enough!). Next you can add the three p-orbitals for Li+ and the next s- and p-orbitals for O-, which would take you to a CAS(11e,14o) calculation, which is also easy and probably accurate enough for almost all purposes! Similar analysis will lead to the same conclusion for the other examples that you gave in your question.&lt;/p&gt;&#xA;&lt;p&gt;Finally I'll say that recently, for example &lt;a href=&quot;https://arxiv.org/abs/1602.03835&quot; rel=&quot;noreferrer&quot;&gt;in 2016&lt;/a&gt; people have published papers about &amp;quot;automatically&amp;quot; choosing active spaces, but over the 4.2 decades since &lt;a href=&quot;https://www.molcas.org/roos.html&quot; rel=&quot;noreferrer&quot;&gt;Bjorn Roos &lt;em&gt;et al.&lt;/em&gt; described CASSCF in 1980&lt;/a&gt; the idea of &amp;quot;automatically&amp;quot; choosing CAS spaces was not very popular, and this was for good reasons. Many experts in the field are still skeptical about the various &amp;quot;automatic&amp;quot; methods for selecting CAS spaces, and there is indeed a &amp;quot;fine art&amp;quot; to the selection of active spaces, which comes with years (or in many cases, decades) of experience.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="142" LastEditDate="2022-10-25T14:55:53.637" LastActivityDate="2022-10-25T14:55:53.637" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9848" PostTypeId="2" ParentId="9839" CreationDate="2022-10-25T15:09:53.500" Score="2" Body="&lt;p&gt;Due to the errors associated with your choice of functional (even if it's a double hybrid functional), I think there is not much value in unfreezing the core with regards to getting more accurate energies in the realm of &amp;quot;extremely short bond distances&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The regime of &amp;quot;extremely short bond distances&amp;quot; is one in which no matter what you do, there will likely be a fairly big discrepancy between what you get with two different equally accurate methods, when compared to what you'd find at other less-extreme parts of the potential. DFT (even with double-hybrid functionals) is already so poor at capturing electron correlation, so I wouldn't read very much into its results in the &amp;quot;extremely short bond distance&amp;quot; regime, and I would say the same for the &lt;em&gt;much more&lt;/em&gt; accurate coupled cluster methods and even FCI (which is numerically &lt;em&gt;&lt;strong&gt;exact&lt;/strong&gt;&lt;/em&gt; for a given basis set and active space).&lt;/p&gt;&#xA;&lt;p&gt;Therefore I don't see much value in adding so many extra electrons and orbitals to your active space  in this regime which is so-much limited by other issues that likely can't be fixed at all.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-10-25T15:09:53.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9849" PostTypeId="2" ParentId="9838" CreationDate="2022-10-25T15:11:23.347" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;The term &amp;quot;basis set&amp;quot; literally comes from Fourier analysis in mathematics, and in Fourier analysis the &amp;quot;errors&amp;quot; systematically &amp;quot;cancel out&amp;quot;, for example when integrating a Fourier series expansion to find out the coefficients.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;False. The term comes from linear algebra. We have a vector space spanned by our basis functions.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It has been answered to my previous question that RI-MP2/cc-pVTZ/cc-pVTZ gives results of the same quality as MP2/cc-pVTZ. I then started to think about RI-MP2/cc-pVTZ/cc-pVQZ.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am not sure what you mean by your notation.&lt;/p&gt;&#xA;&lt;p&gt;However, RI-MP2 is simply MP2 where one uses the RI approximation for the two-electron integrals, see &lt;a href=&quot;https://doi.org/10.1016/0009-2614(93)87156-W&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chem. Phys. Lett. 208, 359 (1993)&lt;/a&gt;. The accuracy of the RI-MP2 calculation is determined by&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the orbital basis&lt;/li&gt;&#xA;&lt;li&gt;the auxiliary basis used to generate the integrals&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;If one uses an accurate enough auxiliary basis set, RI-MP2 recovers MP2 theory; for example, see &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.1c00607&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 17, 6886 (2021)&lt;/a&gt; for a recent demonstration with automatically generated auxiliary basis sets for any given orbital basis set.&lt;/p&gt;&#xA;&lt;p&gt;The cost of RI-MP2 is mainly determined by the size of the orbital basis, as one needs to compute &lt;span class=&quot;math-container&quot;&gt;$o^2v^2$&lt;/span&gt; excitations (&lt;span class=&quot;math-container&quot;&gt;$o$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; are the number of occupied and virtual orbitals). The cost is essentially linear in the auxiliary basis, excluding its setup.&lt;/p&gt;&#xA;&lt;p&gt;Using a mismatched orbital/auxiliary basis combination gives you poorer results than a properly matched combination. You either spend unnecessary effort by using a too large auxiliary basis, or waste the calculation by compromising the results of the large-orbital-basis calculation by using an insufficient auxiliary basis set.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-25T15:11:23.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9850" PostTypeId="2" ParentId="9834" CreationDate="2022-10-25T15:18:13.230" Score="5" Body="&lt;p&gt;The lower occupied orbitals are immensely important for all of chemistry and physics - especially physical properties and chemical reactions - because of Pauli repulsion. If the orbitals were not occupied, chemistry and physics would look completely different. Repulsion at short ranges arises from the Pauli potential; you cannot fit two electrons onto the same orbital.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-25T15:18:13.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9851" PostTypeId="2" ParentId="9841" CreationDate="2022-10-25T18:51:34.517" Score="3" Body="&lt;p&gt;In the repo, we have the Paraview state file called 3D-LIC.pvsm&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/qmcurrents/gimic/tree/master/tools/Visualization&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/qmcurrents/gimic/tree/master/tools/Visualization&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You need to download it, open it with Paraview and choose the vti and cml files from your calculation instead of the default paths.&lt;/p&gt;&#xA;&lt;p&gt;Let me know if you need further help.&lt;/p&gt;&#xA;" OwnerUserId="6183" LastActivityDate="2022-10-25T18:51:34.517" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9852" PostTypeId="1" CreationDate="2022-10-26T04:17:48.463" Score="3" ViewCount="103" Body="&lt;p&gt;I wish to run DFT calculations on Quantum Espresso for the calculation of quantum capacitance. I have gone through literature, specifically, &amp;quot;Graphitic carbon nitride decorated with FeNi3 nanoparticles for flexible planar micro-supercapacitor with ultrahigh energy density and quantum storage capacity&amp;quot;, wherein (in Figure 4e) they have, in short, mentioned calculation of quantum capacitance and have given equations.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering on how to go about this. Do I have to perform DOS or bandstructure before proceeding? Happy if anyone can help and guide on how and what Quantum Espresso calculations need to be carried out.&lt;/p&gt;&#xA;" OwnerUserId="5378" LastEditorUserId="5" LastEditDate="2022-10-26T11:50:21.523" LastActivityDate="2022-10-26T11:50:21.523" Title="Calculation of quantum capacitance for materials using Quantum Espresso" Tags="|quantum-espresso|physical-properties-of-materials|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-12T14:48:15.957" ContentLicense="CC BY-SA 4.0" />
  <row Id="9853" PostTypeId="1" AcceptedAnswerId="9891" CreationDate="2022-10-26T07:25:43.437" Score="4" ViewCount="395" Body="&lt;p&gt;I am a beginner in learning DFT calculation with VASP. I have just done a relaxation calculation. I want to learn calculating two properties of materials, using VASP. One is the &lt;strong&gt;elastic properties&lt;/strong&gt; (elastic constants, stress strain relation etc), and the other is calculating the &lt;strong&gt;dipole tensor&lt;/strong&gt;. I am currently considering silicon as a test material.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone suggest me how to calculate the elastic properties in VASP? Also it would be great to know how to calculate the dipole tensor (provided that we have &lt;span class=&quot;math-container&quot;&gt;$P_{ij}=-V_{cell}\sigma_{ij}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$V_{cell}$&lt;/span&gt; is the volume of the simulation cell, &lt;span class=&quot;math-container&quot;&gt;$\sigma_{ij}$&lt;/span&gt; is the difference bteween the average macroscopic stress in the cell, and &lt;span class=&quot;math-container&quot;&gt;$P_{ij}$&lt;/span&gt; is the dipole tensor)?&lt;/p&gt;&#xA;&lt;p&gt;A step by step suggestion would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Any resource link, python file etc (along with the steps for a beginner) would be very helpful.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-11-01T09:37:31.213" Title="Elastic Calculation and dipole tensor calculation using VASP" Tags="|density-functional-theory|vasp|conceptual-dft|vaspkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9854" PostTypeId="1" AcceptedAnswerId="9855" CreationDate="2022-10-26T09:30:40.777" Score="5" ViewCount="260" Body="&lt;p&gt;I am trying to evaluate the Hartree--Fock exchange energy density on grids in pyscf with an instance of class &amp;quot;UKS&amp;quot;, in order to test some functionals depending on the exchange energy density such as Becke05. I have noticed that there is an example in &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/dft/31-xc_value_on_grid.py&quot; rel=&quot;noreferrer&quot;&gt;31-xc_value_on_grid.py&lt;/a&gt;, but it seems that the function &lt;code&gt;dft.libxc.eval_xc&lt;/code&gt; does not contain the Hartree--Fock exchange energy, that&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ao_value = numint.eval_ao(mol, coords, deriv=1)&#xA;rho = numint.eval_rho(mol, ao_value, dm, xctype='GGA')    &#xA;exc, vxc = dft.libxc.eval_xc('.2*HF + .08*SLATER + .72*B88, .81*LYP + .19*VWN', rho)[:2]&#xA;print('Exc = %.12f  ref = -7.520014202688' % numpy.einsum('i,i,i-&amp;gt;', exc, rho[0], weights))&#xA;exc, vxc = dft.libxc.eval_xc('.08*SLATER + .72*B88, .81*LYP + .19*VWN', rho)[:2]&#xA;print('Exc = %.12f  ref = -7.520014202688' % numpy.einsum('i,i,i-&amp;gt;', exc, rho[0], weights))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Exc = -7.520014211805  ref = -7.520014202688&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Exc = -7.520014211805  ref = -7.520014202688&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So is there some functions in pyscf to evalue the HF exchange energy density on grids? Thanks in advance for the help!&lt;/p&gt;&#xA;" OwnerUserId="6185" LastActivityDate="2022-10-27T07:35:33.123" Title="How to evaluate Hartree--Fock exchange energy density on grids in pyscf?" Tags="|density-functional-theory|python|hartree-fock|pyscf|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9855" PostTypeId="2" ParentId="9854" CreationDate="2022-10-26T10:43:19.683" Score="5" Body="&lt;p&gt;Exact exchange is not included in the DFT grid since exact exchange is not DFT. PySCF does implement seminumerical schemes for evaluating exchange energies; this is documented in the user guide in &lt;a href=&quot;https://pyscf.org/user/sgx.html&quot; rel=&quot;noreferrer&quot;&gt;https://pyscf.org/user/sgx.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-10-26T10:43:19.683" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9856" PostTypeId="1" AcceptedAnswerId="9865" CreationDate="2022-10-26T13:25:31.220" Score="6" ViewCount="668" Body="&lt;p&gt;I want to run multiple Gaussian jobs (one after one). I have a folder which contains more than 30 molecules and I want my calculation to start with molecule 1 then when the job is finished, start the next job for molecule 2 automatically and so on ...&lt;/p&gt;&#xA;&lt;p&gt;I know how to do it in Windows by using a batch file and executing in the utilities menu but, on Linux, I don't know how does it works.&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="142" LastEditDate="2023-06-23T10:30:06.377" LastActivityDate="2023-06-23T10:32:03.227" Title="How to run multiple Gaussian jobs one after another in Linux" Tags="|computational-chemistry|molecular-modeling|gaussian|high-performance-computing|" AnswerCount="3" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9857" PostTypeId="1" CreationDate="2022-10-26T17:31:59.720" Score="7" ViewCount="1387" Body="&lt;p&gt;I want to perform NVT simulation to study defect dynamics in sic. I want to study dynamics at 1500K. despite of giving initial and final temperature 1500K (also damping parameter as required part of command) in fix nvt command (input and log file is given below), I can see an exponential increase in temperature. I want to understand the implementation, why lammps is not starting the simulation directly form 1500K.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;units           metal&#xA;dimension       3&#xA;atom_style      atomic&#xA;pair_style      tersoff&#xA;boundary        p p p&#xA;&#xA;read_data 3csic555_cvac&#xA;#reset_atom_ids sort no&#xA;&#xA;#set atomic attributes&#xA;&#xA;velocity all create 1500.0 348769 rot yes dist gaussian loop geom&#xA;#giving atominc interactions&#xA;newton on on&#xA;pair_style      tersoff&#xA;pair_coeff      * * /usr/local/Cellar/lammps/20220623/share/lammps/potentials/SiC.tersoff Si C&#xA;&#xA;#for time intergraion and other constraints&#xA;&#xA;fix             1 all nvt temp 1500.0 1500.0 100.0&#xA;#fix             2 all nve&#xA;timestep 0.001&#xA;dump            mydmp all atom 500 dump.min&#xA;&#xA;&#xA;&#xA;&#xA;&#xA;thermo 500&#xA;&#xA;run             500000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Logfile:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Per MPI rank memory allocation (min/avg/max) = 3.834 | 3.834 | 3.834 Mbytes&#xA;Step Temp E_pair E_mol TotEng Press&#xA;       0          500   -6141.8538            0    -6077.353   -76639.045&#xA;   10000    276.43509   -6112.3713            0   -6076.7108    -68125.88&#xA;   20000    273.32228   -6110.8914            0   -6075.6324   -66875.866&#xA;   30000    285.43628   -6111.2779            0   -6074.4562   -66917.301&#xA;   40000    278.13412   -6109.1826            0   -6073.3029   -65746.928&#xA;   50000    289.22109   -6109.3216            0   -6072.0116   -65597.833&#xA;   60000    301.54955   -6109.4815            0   -6070.5811   -64343.259&#xA;   70000    306.81328   -6108.5685            0   -6068.9891   -66579.906&#xA;   80000    302.67689     -6106.38            0   -6067.3342   -64186.072&#xA;   90000    313.68726   -6106.1345            0   -6065.6683   -64413.954&#xA;  100000    326.02443   -6105.9705            0   -6063.9128   -63213.492&#xA;  110000    328.27444   -6104.3621            0   -6062.0141   -62684.361&#xA;  120000    340.34542   -6103.8526            0   -6059.9475   -60997.521&#xA;  130000    352.93407   -6103.3545            0   -6057.8254   -62076.109&#xA;  140000     357.1562   -6101.3489            0   -6055.2752   -59137.752&#xA;  150000    381.54196   -6102.2911            0   -6053.0716   -57748.092&#xA;  160000     387.1425   -6100.4918            0   -6050.5498   -58410.882&#xA;  170000    380.66263   -6097.0521            0    -6047.946   -54899.128&#xA;  180000     403.8425   -6096.9102            0   -6044.8139   -57878.013&#xA;  190000    412.23799   -6095.2316            0   -6042.0522   -51955.885&#xA;  200000    421.22362   -6093.2239            0   -6038.8854   -51065.847&#xA;  210000    433.73796   -6091.7092            0   -6035.7563   -49607.731&#xA;  220000    442.23856   -6089.7646            0   -6032.7151   -45590.764&#xA;  230000    469.97452   -6089.9588            0   -6029.3313   -45771.141&#xA;  240000    498.00504   -6089.9526            0   -6025.7092   -47410.634&#xA;  250000    472.52756    -6082.563            0   -6021.6062   -38739.338&#xA;  260000    512.67791   -6083.8665            0   -6017.7302   -44930.882&#xA;  270000    539.24371   -6083.2532            0   -6013.6898   -37262.625&#xA;  280000    547.50321   -6080.2904            0   -6009.6616   -36256.739&#xA;  290000    591.67329   -6081.3809            0   -6005.0541   -38453.659&#xA;  300000    589.01562    -6076.237            0    -6000.253   -33055.161&#xA;  310000    612.20655   -6074.1156            0     -5995.14   -25625.661&#xA;  320000     628.9901   -6071.3865            0   -5990.2457   -27308.343&#xA;  330000    663.26313   -6070.0644            0   -5984.5024   -21724.991&#xA;  340000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6188" LastEditorUserId="5" LastEditDate="2022-10-26T22:12:09.277" LastActivityDate="2022-10-28T10:22:52.653" Title="LAMMPS: Why does the NVT fix vary in temprature step-by-step even though I am giving an initial and final temp of 1500K?" Tags="|lammps|temperature|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9859" PostTypeId="2" ParentId="9856" CreationDate="2022-10-26T22:07:39.750" Score="3" Body="&lt;p&gt;Loops in Linux are possible, but I personally find it more convenient to make a batch-processing script. The following is an example for my &lt;a href=&quot;https://github.com/HPQC-LABS/potfit&quot; rel=&quot;nofollow noreferrer&quot;&gt;PotFit program&lt;/a&gt;, in which the command to run the program is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;brdpot [input_filename]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For example, I would create a file called &lt;code&gt;batch.x&lt;/code&gt; that looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;brdpot input1&#xA;brdpot input2&#xA;brdpot input3&#xA;brdpot input4&#xA;brdpot input5&#xA;brdpot input6&#xA;brdpot input7&#xA;brdpot input8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By running the command &lt;code&gt;chmod +x batch.x&lt;/code&gt;, it becomes an &amp;quot;executable&amp;quot; file. You can then execute it from the directory in which it lives, by running the command &lt;code&gt;./batch.x&lt;/code&gt; and this will get the computer to run the command &lt;code&gt;brdpot input1&lt;/code&gt;, then when that job is complete it will get the computer to run the command &lt;code&gt;brdpot input2&lt;/code&gt;, etc. &lt;strong&gt;In other words, the PotFit program will be run for several input files, one-after-the-other until all jobs have been run.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've found this approach extremely helpful because in VIM, I can just &amp;quot;yank&amp;quot; a line in the &lt;code&gt;batch.x&lt;/code&gt; file and repeat it hundreds of times, then change the number in the file name in a batch too.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-10-26T22:07:39.750" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9860" PostTypeId="1" CreationDate="2022-10-27T06:13:44.987" Score="3" ViewCount="572" Body="&lt;p&gt;I'm doing a static calculation. IBRION is set to-1, but NSW forgot to set it to 0. I found that the energy of the second ion step is not the same as that of the first ion step. The structure has not changed, so why is the energy different? Which result is reliable?&lt;/p&gt;&#xA;&lt;p&gt;INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ALGO = Fast&#xA;EDIFF = 1E-5&#xA;EDIFFG = -2E-2&#xA;ENCUT = 520&#xA;IBRION = -1&#xA;ICHARG = 1&#xA;ISIF = 2&#xA;ISMEAR = 0&#xA;POTIM = 0.05&#xA;ISPIN = 2&#xA;ISTART = 1&#xA;LORBIT = 11&#xA;LREAL = Auto&#xA;#ADDGRID = True&#xA;LWAVE = False&#xA;LCHARG = False&#xA;#MAGMOM = 30*0.6&#xA;NELM = 400&#xA;NSW = 000&#xA;PREC = Accurate&#xA;SIGMA = 0.05&#xA;#SYMPREC = 1E-4&#xA;#ISYM = 0&#xA;&#xA;IVDW = 1&#xA;&#xA;NCORE = 4&#xA;&#xA;LMAXMIX = 4&#xA;# DFT+U&#xA;LDAU = True&#xA;LDAUTYPE = 2&#xA;LDAUL = 0 0 2   0&#xA;LDAUU = 0 0 5.3 0&#xA;LDAUJ = 0 0 0   0&#xA;LDAUPRINT = 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   1 F= -.12046558E+04 E0= -.12046422E+04  d E =-.272572E-01  mag=     2.0115&#xA;   2 F= -.12047406E+04 E0= -.12047334E+04  d E =-.145517E-01  mag=     1.7560&#xA;   3 F= -.12047407E+04 E0= -.12047334E+04  d E =-.145535E-01  mag=     1.7565&#xA;   4 F= -.12047407E+04 E0= -.12047334E+04  d E =-.146082E-01  mag=     1.7569&#xA;   5 F= -.12047407E+04 E0= -.12047333E+04  d E =-.146615E-01  mag=     1.7573&#xA;   6 F= -.12047407E+04 E0= -.12047334E+04  d E =-.145626E-01  mag=     1.7575&#xA;   7 F= -.12047407E+04 E0= -.12047334E+04  d E =-.145611E-01  mag=     1.7575&#xA;   8 F= -.12047407E+04 E0= -.12047334E+04  d E =-.145244E-01  mag=     1.7579&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I guess the result may be related to ICHARG=1, which causes the subsequent calculation to read the previous CHGCAR. If so, the energy of static calculation should be set to NSW=0 or NSW&amp;gt;1, and the convergent energy should be used.&lt;/p&gt;&#xA;" OwnerUserId="6191" LastActivityDate="2022-11-03T16:59:07.837" Title="The result of vasp static calculation is different when NSW= 0 and ≠ 0" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9861" PostTypeId="2" ParentId="9854" CreationDate="2022-10-27T07:35:33.123" Score="2" Body="&lt;p&gt;I find this can be calculated by a similar procedure as in &lt;code&gt;pyscf.tools.cubegen.mep&lt;/code&gt;, where a delta function at a grid is approximated by a Gaussian with efficiently large exponent. Here is my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def get_ExxDen(ks,coords=None):&#xA;    if(type(coords)==type(None)): coords = ks.grids.coords&#xA;    mol = ks.mol&#xA;    dm = ks.make_rdm1()&#xA;    fakemol = gto.fakemol_for_charges(coords)&#xA;    ints = df.incore.aux_e2(mol, fakemol)&#xA;    if dm.ndim == 2:  # RHF DM&#xA;        dm = numpy.asarray((dm*.5,dm*.5))&#xA;    ni = ks._numint&#xA;    ao = ni.eval_ao(mol,coords)&#xA;    ExxDen = [0,0] # ExxDen for alpha and beta spin&#xA;    for idm in range(2):&#xA;        ExxDen[idm] = einsum('pi,ij-&amp;gt;pj', ao, dm[idm])&#xA;        ExxDen[idm] = einsum('pj,jkp-&amp;gt;pk', ExxDen[idm], ints)&#xA;        ExxDen[idm] = einsum('pk,lk-&amp;gt;pl', ExxDen[idm], dm[idm])&#xA;        ExxDen[idm] = einsum('pl,pl-&amp;gt;p', ExxDen[idm], ao)&#xA;    return ExxDen[0],ExxDen[1]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6185" LastActivityDate="2022-10-27T07:35:33.123" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9862" PostTypeId="2" ParentId="8941" CreationDate="2022-10-27T09:05:32.010" Score="2" Body="&lt;p&gt;I tested the force field in two ways.&lt;/p&gt;&#xA;&lt;p&gt;1-I performed a short-time MD for my system in vacuum using my force field and the same time of AIMD simulation for my system. Then I started to compare the evolution of the distance, the angle, and the dihedral between MD and AIMD. For example, &lt;code&gt;Ru-N&lt;/code&gt;, &lt;code&gt;N1-Ru-N2&lt;/code&gt; etc.&lt;/p&gt;&#xA;&lt;p&gt;2-Following the first step, I attempted to add more to compare by calculating the spectrum. As a result, I took 50 structures from the MD and AIMD simulations, ran the calculation, and plotted the spectrum for both (MD and AIMD).&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2022-10-27T09:05:32.010" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9863" PostTypeId="2" ParentId="9857" CreationDate="2022-10-27T09:28:18.203" Score="9" Body="&lt;p&gt;As a consequence of these commands:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix 1 all nvt temp 1500.0 1500.0 100&#xA;timestep 0.001&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;you are running your system with a Nose-Hoover thermostat whose time constant is 100,000 timesteps.&lt;/p&gt;&#xA;&lt;p&gt;A Nose-Hoover thermostat will correct deviations from the preset temperature within a time scale of a few time constants. Since you begin with a system 1250K(1) away from the preset, it is not surprising that three time constants later your system has not reached its preset.&lt;/p&gt;&#xA;&lt;p&gt;The LAMMPS documentation has quite a bit of information about what a thermostat actually does and how a proper time constant should be set -- make sure you read it!&lt;/p&gt;&#xA;&lt;p&gt;(1) You initially set your system to 500K, but most likely the system was exactly at an energy minimum. So within the first few thousand timesteps the thermal kinetic energy was redistributed into potential energy, as the &lt;code&gt;thermo&lt;/code&gt; output table indicates.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2022-10-28T10:22:52.653" LastActivityDate="2022-10-28T10:22:52.653" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9864" PostTypeId="1" CreationDate="2022-10-27T11:06:13.277" Score="4" ViewCount="146" Body="&lt;p&gt;I want pyscf to read the single-particle reduced density matrix computed by GAMESS.&#xA;However, I am having trouble because the matrix sizes in GAMESS and pyscf are different.&#xA;For example, the AO-displayed matrix in GAMESS are of the form 25 times 25 for a single molecule of H2O using the cc-pvdz basis function.&lt;/p&gt;&#xA;&lt;p&gt;The matrix indexes of GAMESS are shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    1  O  1  S   &#xA;    2  O  1  S   &#xA;    3  O  1  S   &#xA;    4  O  1  X   &#xA;    5  O  1  Y   &#xA;    6  O  1  Z   &#xA;    7  O  1  X   &#xA;    8  O  1  Y   &#xA;    9  O  1  Z   &#xA;   10  O  1 XX   &#xA;   11  O  1 YY   &#xA;   12  O  1 ZZ   &#xA;   13  O  1 XY   &#xA;   14  O  1 XZ   &#xA;   15  O  1 YZ&#xA;   16  H  2  S   &#xA;   17  H  2  S   &#xA;   18  H  2  X   &#xA;   19  H  2  Y   &#xA;   20  H  2  Z&#xA;   21  H  3  S   &#xA;   22  H  3  S   &#xA;   23  H  3  X   &#xA;   24  H  3  Y   &#xA;   25  H  3  Z&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;On the other hand, in pyscf, the density matrix for a single molecule of H2O with the same basis function takes the form 24times 24.&#xA;This is probably because pyscf uses five different basis functions(d&lt;span class=&quot;math-container&quot;&gt;$_{xy}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{yz}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{zx}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{x^2-y^2}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{z^2}$&lt;/span&gt;) to display d orbitals, while GAMESS uses six different basis functions, XX, YY, ZZ, XY, XZ, and YZ.&lt;/p&gt;&#xA;&lt;p&gt;Is there any way to convert a density matrix obtained in GAMESS using 6 different bases, XX, YY, ZZ, XY, XZ, YZ for the d orbitals, to a representation using 5 general basis functions(d&lt;span class=&quot;math-container&quot;&gt;$_{xy}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{yz}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{zx}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{x^2-y^2}$&lt;/span&gt;, d&lt;span class=&quot;math-container&quot;&gt;$_{z^2}$&lt;/span&gt;)?&lt;/p&gt;&#xA;" OwnerUserId="6193" LastActivityDate="2022-10-27T11:06:13.277" Title="Convert reduced density matrix in A.O. basis from GAMESS to pyscf" Tags="|computational-chemistry|quantum-chemistry|pyscf|gamess|" AnswerCount="0" CommentCount="4" ClosedDate="2023-06-12T14:48:21.580" ContentLicense="CC BY-SA 4.0" />
  <row Id="9865" PostTypeId="2" ParentId="9856" CreationDate="2022-10-27T12:03:13.967" Score="7" Body="&lt;p&gt;Lets suppose that you have several Gaussian input files with extension &lt;code&gt;gjf&lt;/code&gt; inside a folder.&lt;/p&gt;&#xA;&lt;p&gt;Supposing you are in the folder where all the input files are and the command to run Gaussian is &lt;code&gt;g16&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Open a plain text editor and create a file with the content below (Use &lt;code&gt;nano&lt;/code&gt;, &lt;code&gt;vim&lt;/code&gt;, &lt;code&gt;gedit&lt;/code&gt;. Don't use &lt;code&gt;LibreOffice&lt;/code&gt;, &lt;code&gt;OpenOffice&lt;/code&gt; or similar).&lt;/li&gt;&#xA;&lt;li&gt;Save the file, for example, as: &lt;code&gt;run_gaussian_jobs.sh&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;In the command prompt, turn the file an executable: &lt;code&gt;chmod +x run_gaussian_jobs.sh&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Run the script as &lt;code&gt;./run_gaussian_jobs.sh&lt;/code&gt;. You can also move your script to a folder that is in your path (for example &lt;code&gt;~/bin&lt;/code&gt;). In that case you can use the script in any other folder where you have Gaussian input files running it as &lt;code&gt;run_gaussian_jobs.sh&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Text to use:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;&#xA;for file in *.gjf; do&#xA;  extension=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;${file##*.}&quot;&#xA;  filename=&quot;$&lt;/span&gt;{file%.*}&amp;quot;&#xA;&#xA;  g16 &amp;lt; &lt;span class=&quot;math-container&quot;&gt;$file &amp;gt; $&lt;/span&gt;filename.log&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using this approach, you can add any number of Gaussian input files to the folder without the need to known the filenames, modify the script, etc.&lt;/p&gt;&#xA;&lt;p&gt;An aside note: running as mention before, the jobs will be running in the terminal, so, you can not close it because you will end the jobs. A better approach is to add &lt;code&gt;&amp;amp;&lt;/code&gt; at the end of the running command: &lt;code&gt;./run_gaussian_jobs &amp;amp;&lt;/code&gt;. Now the jobs will run in the background. You can use this if you are running the jobs in a remote computer.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="403" LastEditDate="2023-06-20T23:07:06.547" LastActivityDate="2023-06-20T23:07:06.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9866" PostTypeId="2" ParentId="9857" CreationDate="2022-10-27T13:43:13.507" Score="10" Body="&lt;p&gt;The instantaneous temperature will almost always fall to half of its original value when thermal equilibrium is established when we attribute velocities to the atoms in a crystal.&#xA;The equipartition energy theorem is mainly responsible for this.&#xA;The Hamiltonian of solids at temperatures much below their melting point mimics a set of coupled harmonic oscillators, hence&#xA;the average kinetic energy and average potential energy of a harmonic system are equally distributed throughout.&#xA;In an NVE-ensemble simulation, the total energy is conserved, hence the kinetic energy must fall by half if the potential energy (which starts off at zero). In case of NVT, after each certain time step velocity of the system are rescaled to reach final temperature. In the initial run, when velocity corresponds to 500K was applied, overall system temperature drops to 250K and slowly it start gaining temperature as you run further. NVT can be thought as series of NVE simulation connected by event when velocity is being rescaled.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; fix 1 all nvt temp Tstart Tstop Tdamp&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The LAMMPS manual says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The desired temperature at each timestep is a ramped value during the run from Tstart to Tstop. The Tdamp parameter is specified in time units and determines how rapidly the temperature is relaxed. For example, a value of 10.0 means to relax the temperature in a timespan of (roughly) 10 time units&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="7" LastEditDate="2022-10-28T02:39:04.720" LastActivityDate="2022-10-28T02:39:04.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9867" PostTypeId="1" CreationDate="2022-10-28T06:17:02.453" Score="5" ViewCount="88" Body="&lt;p&gt;I am trying to duplicate the results of this &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.8b08449&quot; rel=&quot;nofollow noreferrer&quot;&gt;study&lt;/a&gt; using VASP. Where they have observed that the structure of &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs_2SnI_6}$&lt;/span&gt; switches from Fm-3m to I2/m upon application of pressure more than 3.3 GPa. They have also validated there experimental results using DFT but for that they have calculated the energy of various possible space groups and found that I2/m has lesser energy as compared to Fm-3m above 3.3 GPa. I want to do this using Geometry relaxation directly.&lt;/p&gt;&#xA;&lt;p&gt;Directly running geometry relaxation with Pressure does not work because VASP maintains the symmetry. I also tried running with &lt;code&gt;ISYM=0&lt;/code&gt; that did not help either.&lt;/p&gt;&#xA;&lt;p&gt;Another idea is to distort the structure manually as has been done &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1597/dealing-with-symmetry-of-ordered-primitive-cell-during-dft-structure-relaxation&quot;&gt;here&lt;/a&gt; but this switches the symmetry from Fm-3m to let's say some X symmetry.Now this X symmetry is maintained even through the geometry relaxation.&lt;/p&gt;&#xA;&lt;p&gt;What do you think is the best method to solve this issue ??&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5" LastEditDate="2022-10-28T11:45:54.293" LastActivityDate="2022-11-01T13:43:45.660" Title="Change in space group upon application of stress during geometry relaxation in VASP" Tags="|vasp|geometry-optimization|symmetry|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="9868" PostTypeId="1" CreationDate="2022-10-28T19:47:20.193" Score="3" ViewCount="1475" Body="&lt;p&gt;I have two silicon in an unit cell, for a test calculation. Each silicon as 12 electrons in the pseudopotential (1s is frozen). I have done the partial density of states (PDOS) calculation using DFT with QUANTUM ESPRESSO.  What I need to know is, I have been suggested to do the following two tasks (which instructs like):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Take your PDOS summed over the different atomic orbitals (2s, 2p, 3s, 3p, 3d), and summed over energies up to the Fermi level (i.e. all the occupied states)&lt;/li&gt;&#xA;&lt;li&gt;Then subtract this from the total number of electrons in the unit cell. It will find the number of electrons that are not in those atomic orbitals (this is the ultimate goal of the task).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Could you please suggest me how to solve these two to get the number of electrons that are not in those atomic orbitals&lt;/strong&gt; (any process or modification of input files or steps or resource links would be greatly appreciated)?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-----------------------------------------END OF QUERY------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note (optional, in case it gives more insight): I got the Fermi energy value as 21.653 eV from the DOS calculation.&#xA;My DOS input code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;DOS&#xA;    prefix='silicon'&#xA;    outdir='.',&#xA;    DeltaE=0.2,&#xA;    Emin=-119.233,&#xA;    Emax=109.567,&#xA;    fildos='si.dos',&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And my PDOS input was&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;projwfc&#xA; prefix='silicon'&#xA; outdir='./'&#xA; degauss=0.2&#xA; DeltaE=0.2&#xA; filpdos='si.pdos.dat'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From DOS calculation, the output data obtained is like this (shown portion to get idea):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#  E (eV)   dos(E)     Int dos(E) EFermi =   21.653 eV&#xA;-119.233  0.1148E-84  0.2295E-85&#xA;-119.033  0.1148E-84  0.4591E-85&#xA;-118.833  0.1148E-84  0.6886E-85&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And from the PDOS calculation, the output data files from one atom are (shown portions to get ideas):&lt;/p&gt;&#xA;&lt;p&gt;For 2s:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# E (eV)   ldos(E)   pdos(E)   &#xA;-119.233  0.379E-04  0.379E-04&#xA;-119.033  0.589E-04  0.589E-04&#xA;-118.833  0.907E-04  0.907E-04&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For 2p:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# E (eV)   ldos(E)   pdos(E)    pdos(E)    pdos(E)   &#xA;-119.233  0.174E-08  0.580E-09  0.580E-09  0.580E-09&#xA;-119.033  0.271E-08  0.902E-09  0.902E-09  0.902E-09&#xA;-118.833  0.416E-08  0.139E-08  0.139E-08  0.139E-08&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For 3s:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# E (eV)   ldos(E)   pdos(E)   &#xA;-119.233  0.327E-06  0.327E-06&#xA;-119.033  0.511E-06  0.511E-06&#xA;-118.833  0.788E-06  0.788E-06&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for 3p:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# E (eV)   ldos(E)   pdos(E)    pdos(E)    pdos(E)   &#xA;-119.233  0.149E-05  0.498E-06  0.498E-06  0.498E-06&#xA;-119.033  0.232E-05  0.773E-06  0.773E-06  0.773E-06&#xA;-118.833  0.356E-05  0.119E-05  0.119E-05  0.119E-05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The PDOS image for this case is:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/2SYQP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2SYQP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-10-28T19:47:20.193" Title="PDOS calculation with Quantum Espresso (need help for further analysis)" Tags="|density-functional-theory|quantum-espresso|density-of-states|charge-density|" AnswerCount="0" CommentCount="10" ClosedDate="2023-12-09T22:52:47.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="9869" PostTypeId="1" CreationDate="2022-10-28T19:51:12.307" Score="3" ViewCount="1982" Body="&lt;p&gt;Cross-posted on &lt;a href=&quot;https://ai.stackexchange.com/q/37669/19524&quot;&gt;AI Stack Exchange&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;We are running alphafold2 multimer on Google Colab to predict the association between two proteins.&lt;/p&gt;&#xA;&lt;p&gt;It generally works fine, but we get an asymmetric PAE plot for a specific pair. Does anyone know why this might happen? I assumed these must always be symmetrical.&lt;/p&gt;&#xA;&lt;p&gt;I have provided a figure below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4hKTom.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4hKTom.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6199" LastEditorUserId="5" LastEditDate="2022-10-28T20:31:22.663" LastActivityDate="2022-10-29T02:00:11.517" Title="Why is the Alphafold PAE (predicted aligned error) not symmetric?" Tags="|mathematical-modeling|proteins|machine-learning|biomaterials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9870" PostTypeId="2" ParentId="9869" CreationDate="2022-10-28T23:23:04.093" Score="2" Body="&lt;p&gt;Predicted alignment error is not always symmetric. &lt;a href=&quot;https://alphafold.ebi.ac.uk/faq&quot; rel=&quot;nofollow noreferrer&quot;&gt;This page&lt;/a&gt; from the European Bioinformatics Institute says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;&lt;code&gt;predicted_aligned_error&lt;/code&gt;: The PAE value of the residue pair, rounded to the closest integer. For the PAE value at position (i, j), i is the residue on which the structure is aligned, j is the residue on which the error is predicted.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So if when aligning on residue &lt;code&gt;i&lt;/code&gt; we get a bad prediction at residue &lt;code&gt;j&lt;/code&gt;, but when aligning on residue  &lt;code&gt;j&lt;/code&gt; we get a good prediction at residue &lt;code&gt;i&lt;/code&gt;, then the PAE plot will be asymmetric.&lt;/p&gt;&#xA;&lt;p&gt;Below I present two PAE plots from &lt;a href=&quot;https://www.rbvi.ucsf.edu/chimerax/data/pae-apr2022/pae.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this website by Tom Goddard (5 April 2022) hosted by UCSF&lt;/a&gt;. The first one looks quite symmetric at first, but I did find some subtle asymmetries, which I've boxed with a red outline:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ErIPwl.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ErIPwl.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;The second one is more obviously asymmetric:&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xJIJQl.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xJIJQl.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-10-29T01:56:35.070" LastActivityDate="2022-10-29T01:56:35.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9872" PostTypeId="1" CreationDate="2022-10-29T02:26:17.387" Score="5" ViewCount="170" Body="&lt;p&gt;In a project, I have to simulate the reaction between carbon nanotube (C) and molten silicon (Si) using LAMMPS. As far as I learned, there is not a classical force field capable to simulate the Si-C reaction, except for density-functional tight-binding calculations with LATTE library.&lt;/p&gt;&#xA;&lt;p&gt;However, to use LATTE library, I still need two input files/folders: &lt;code&gt;latte.in&lt;/code&gt; and &lt;code&gt;TBparams&lt;/code&gt;. Where can I find a set of suitable parameters describing Si-C interation in order to configure the two input files/folders? Are there tutorial or documentation that explain the parameters and the standard way to prepare the two input files/folders?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastEditorUserId="1483" LastEditDate="2022-11-04T06:21:22.227" LastActivityDate="2022-11-04T06:21:22.227" Title="How to set up tight-binding calculations for Si-C system in LAMMPS?" Tags="|lammps|tight-binding|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-09T22:53:10.087" ContentLicense="CC BY-SA 4.0" />
  <row Id="9873" PostTypeId="1" AcceptedAnswerId="9909" CreationDate="2022-10-29T02:59:59.353" Score="7" ViewCount="185" Body="&lt;p&gt;I am somewhat of a novice in computational chemistry of materials, and have been tasked to replicate simulations from a relevant paper. The paper is a bit scant on details so I am trying to recreate its exact input, as closely as possible from their description. I have fundamental understanding of pseudo potentials and basis sets, but I could not figure out what the following line implies:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;... Goedecker pseudopotentials used in all simulations. Kohn-Sham orbitals expanded in triple-zeta plus polarization Gaussian-type basis and the charge density expanded in&#xA;plane waves with a 300 Ry cut-off.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What is meant by &amp;quot;gaussian basis for KS&amp;quot; and &amp;quot;plane-wave for charge density&amp;quot;? Is charge density not derived from the KS orbitals? How and why mix two different kind of basis?&lt;/p&gt;&#xA;&lt;p&gt;I apologize in advance if what I asked is too naïve, most of my quantum chemistry knowledge is text book level, not research paper level!&lt;/p&gt;&#xA;&lt;p&gt;Just as I posted this, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/163/what-are-the-positives-and-negatives-of-periodic-dft-codes-that-dont-use-plane&quot;&gt;this&lt;/a&gt; showed up in the side bar, which gave me a thread to start exploring (GAPW). That answers one of my three questions I believe.&lt;/p&gt;&#xA;" OwnerUserId="785" LastEditorUserId="671" LastEditDate="2022-10-29T16:21:20.010" LastActivityDate="2022-11-02T12:20:39.577" Title="Mixing pseudopotentials with gaussian and plane wave basis" Tags="|density-functional-theory|basis-sets|pseudopotentials|plane-waves|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9874" PostTypeId="1" AcceptedAnswerId="9876" CreationDate="2022-10-29T05:07:36.687" Score="2" ViewCount="132" Body="&lt;p&gt;This is another question about my molecule; as I'm not doing this as an academical affiliate(I'm currently majoring in mathematics), I have only NWChem and my personal laptop on the mix, and thus need to save time and/or CPU usage.&lt;/p&gt;&#xA;&lt;p&gt;I noticed, already on the WebMO demo server, that DFT calculations on elements no larger than Ar often fail at the 45-second CPU time limit (de jure 30, de facto 45) on said server if they contain f functions in their basis sets.&lt;/p&gt;&#xA;&lt;p&gt;WebMO Basic and NWChem are both free without any official CPU time limits- the problem is that I use my laptop to code things (that are completely irrelevant to computational chemistry) already and thus do not want to &amp;quot;torture&amp;quot; my laptop unnecessarily more.&lt;/p&gt;&#xA;&lt;p&gt;I mentioned f (polarisation) functions on both the title and the body of the question- the desired question and its reasons are now clear.&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: My question was originally about freezing f-functions from the TZ basis set ONLY in the MP2 part of the calculations; i.e. doing a full TZ H-F calculation AND THEN freezing the virtual f-functions in the forecoming MP2 calculation(See MP2 page in the NWChem manual to see what I'm talking about). The question somehow got changed to something entirely different so I'm adding this here for more clarity.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-10-30T05:43:21.393" LastActivityDate="2022-11-06T12:03:39.473" Title="Can I freeze f functions from a TZ basis set during MP2 (but not during H-F) to speed up calculations?" Tags="|computational-chemistry|basis-sets|wavefunctions|many-body-perturbation-theory|basis-set-superposition-error|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9875" PostTypeId="1" CreationDate="2022-10-29T09:18:38.933" Score="7" ViewCount="129" Body="&lt;p&gt;Double hybrid approximate functionals have &amp;quot;unoccupied&amp;quot; Kohn-Sham orbitals in their formulations due to their MP2 component; however, the &amp;quot;exact functional&amp;quot; depends only on the &amp;quot;occupied&amp;quot; K-S orbitals.&lt;/p&gt;&#xA;&lt;p&gt;Thus the only way double hybrid approximations could approximate the &amp;quot;exact&amp;quot; functional is that the &amp;quot;exact&amp;quot; DFT density be theoretically invariant under MP2, or at least MPn where n tends to infinity.&lt;/p&gt;&#xA;&lt;p&gt;This would mean that- should one apply MPn to a set of K-S orbitals, let n tend to infinity, and sum the squares of the resulting &amp;quot;MPn occupied orbitals&amp;quot;(like one theoretically does when trying to compute the density from an &amp;quot;unperturbed&amp;quot; K-S set), one should get the same density as the one computed without MPn being applied.&lt;/p&gt;&#xA;&lt;p&gt;Is it mathematically true?&lt;/p&gt;&#xA;&lt;p&gt;*I'm assuming exact functional here, not accounting for the fact that its exact form is unknown.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-11-17T09:32:55.920" Title="Is an &quot;exact&quot; double hybrid density the same as the &quot;exact&quot; DFT density?" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|convergence-test|many-body-perturbation-theory|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="9876" PostTypeId="2" ParentId="9874" CreationDate="2022-10-29T21:37:29.747" Score="2" Body="&lt;p&gt;It depends on what you're intending to do:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If you are comparing to benchmark results with this basis set, then likely &lt;em&gt;&lt;strong&gt;no&lt;/strong&gt;&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If accuracy is very important to you, then likely &lt;em&gt;&lt;strong&gt;no&lt;/strong&gt;&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If you are intending to do a basis set extrapolation, then it might compromise the quality of your extrapolation, although &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3671610&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jacek Koput took the k-type functions out of the aug-cc-pCV7Z basis set&lt;/a&gt; before doing extrapolations, and those extrapolations &lt;a href=&quot;https://arxiv.org/abs/1408.33010&quot; rel=&quot;nofollow noreferrer&quot;&gt;still gave excellent results&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If you don't care too much about accuracy, then &lt;em&gt;&lt;strong&gt;sure, remove the f-type functions&lt;/strong&gt;&lt;/em&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It all depends on the level of accuracy you want, and what price you're willing to pay to achieve that level of accuracy. You can remove some f-type functions, and you'll most likely get slightly less accurate results because your basis set is smaller and offers less variety, but your results will still likely be far more accurate than what you would get by reducing the basis set by an entire zeta value.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If you have enough computer power and you care about accuracy, it would be best to include the f-type functions. If you don't have enough computer power, there's nothing wrong with removing the f-type functions &lt;em&gt;as long as you do it for all energies involved in the energy-difference calculations&lt;/em&gt;, so that you get &amp;quot;parallel errors&amp;quot;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;It may also be a good idea to do some tests to find out how much of an impact those f-type functions are making. Perhaps find a similar molecule that's a bit smaller, so that you can do calculations with and without the f-type functions, and see how big of an impact this has on the final energies. The difference in those energies can be incorporated into your analysis of the uncertainty for your final calculations in the system in which you're truly interested.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-10-29T21:37:29.747" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9877" PostTypeId="1" CreationDate="2022-10-30T17:26:01.690" Score="2" ViewCount="296" Body="&lt;p&gt;I wanted to calculate the HSEO6 crystal lattice parameter. From which stage of the PBE calculation do I copy the WAVECAR? Is it after &lt;code&gt;relax&lt;/code&gt; or &lt;code&gt;scf&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="6203" LastEditorUserId="5" LastEditDate="2022-10-30T17:42:55.987" LastActivityDate="2022-10-30T20:17:30.547" Title="How do I do an HSE06 calculation in VASP?" Tags="|density-functional-theory|vasp|hse06|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9878" PostTypeId="2" ParentId="9877" CreationDate="2022-10-30T20:17:30.547" Score="5" Body="&lt;p&gt;You can do it at any stage. You don’t even have to do a PBE calculation first. It can help to do a PBE calculation so you can get a converged charge density to help speed up the first HSE scf cycle, but you don’t have to do this.&lt;/p&gt;&#xA;&lt;p&gt;If you already have a PBE calculation that you’ve done, then you can use its output to start the HSE calculation, otherwise you can try the HSE calculation, and if the first scf cycle is much too slow, you can try starting off with a PBE calculation.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-10-30T20:17:30.547" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9879" PostTypeId="1" CreationDate="2022-10-30T22:23:55.060" Score="3" ViewCount="56" Body="&lt;p&gt;Perovskite materials form as a combination of &lt;span class=&quot;math-container&quot;&gt;$\ce{BX_6}$&lt;/span&gt; octahdera along with A cation. Some perovskites display tilted octahedras. I am currently trying to run calculations for different tilted versions, but how do I tilt only one small part of a whole cif file.&lt;/p&gt;&#xA;&lt;p&gt;Assume that I have to the modification shown below. I know I can not use VESTA, are there any software out there capable of doing this?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WyjPt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WyjPt.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5" LastEditDate="2022-10-31T02:14:17.600" LastActivityDate="2022-10-31T02:14:17.600" Title="Tilting Octahedra of Perovskite structures in structure file" Tags="|crystallography|perovskites|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T22:53:21.353" ContentLicense="CC BY-SA 4.0" />
  <row Id="9880" PostTypeId="1" CreationDate="2022-10-30T22:33:34.270" Score="3" ViewCount="28" Body="&lt;p&gt;I'm new in the field of research and modelling matter.&lt;/p&gt;&#xA;&lt;p&gt;I got results from DFT calculations but I don't know how to interpret them and I wonder if anyone can suggest to me books for interpreting results (molecular properties).&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5" LastEditDate="2022-10-30T22:46:17.670" LastActivityDate="2022-10-30T22:46:17.670" Title="Book that can interpret molecular properties of organic coumpounds?" Tags="|density-functional-theory|quantum-chemistry|reference-request|soft-question|" AnswerCount="0" CommentCount="2" ClosedDate="2023-06-12T02:20:11.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="9881" PostTypeId="1" CreationDate="2022-10-31T06:03:06.290" Score="5" ViewCount="586" Body="&lt;p&gt;Do I do rest, scf, dos steps when calculating DOS like PBE in HSE06? Can anyone help me with this?&lt;/p&gt;&#xA;" OwnerUserId="6203" LastEditorUserId="6203" LastEditDate="2022-10-31T06:40:13.610" LastActivityDate="2022-10-31T07:24:31.683" Title="Calculation of DOS in HSE06" Tags="|density-functional-theory|vasp|software|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9882" PostTypeId="2" ParentId="9881" CreationDate="2022-10-31T07:24:31.683" Score="5" Body="&lt;p&gt;You will often want to relax the structure first. This can be done with PBE or HSE (you can use PBE if HSE is too slow). I suppose the “can” is vague. The code will allow you to calculate the DOS with HSE on any structure you give it, so in that since, you can relax with PBE or HSE, or not relax at all and then do a HSE calculation. In terms of what is good practice, it depends a lot more on the system and what you want to calculate. If you’re looking at a system with a well established crystal structure, then it might be reasonable to not relax at all and do an HSE DOS. Sometimes the PBE and HSE structures will be similar, other times they will be different. Sometimes two sufficiently similar structures will yield basically the same DOS. If you’re concerned with the impact of these different choices on your results, you can calculate the DOS for different choices and see how much it changes. In some cases this won’t be computationally feasible, and you’ll have to hope that you can get good results with whatever choice you make, but you should try to understand what sort of impact these different choices regarding relaxing or not typically has in similar systems. It might be that there isn’t a computational feasible way to generate data that should be accurate.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the scf calculation before the DOS, typically with HSE calculations, one doesn’t do something like with PBE where you do a coarse k grid calculation to generate the charge density and then do a much finer k grid calculation non-self-consistently. Hybrid calculations require calculating terms involving wave functions and eigenvalues at different k points, so you can’t just do a nscf calculation like you can with non-hybrids. One often just has to do a scf calculation with a larger k mesh, or do something like Wannier interpolation (which can also be used for band structures).&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-10-31T07:24:31.683" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9883" PostTypeId="1" CreationDate="2022-10-31T08:17:58.770" Score="2" ViewCount="377" Body="&lt;p&gt;I optimized the structure in PBE. Can anyone help me with HSE06 to calculate the optics and DOS of the material from this step? I would be grateful if you could write step by step.&lt;/p&gt;&#xA;" OwnerUserId="6203" LastEditorUserId="6131" LastEditDate="2022-11-05T16:56:33.813" LastActivityDate="2022-11-05T16:56:33.813" Title="Studying computing on HSE06 in VASP" Tags="|density-functional-theory|vasp|software|density-of-states|optical-properties|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9884" PostTypeId="1" CreationDate="2022-10-31T10:23:37.313" Score="3" ViewCount="65" Body="&lt;p&gt;The literature seems to be very diverse in measuring the bending rigidity of the nanomaterial from MD simulation. I have seen people often use this relation from continuum mechanics &lt;span class=&quot;math-container&quot;&gt;$$k = \frac{Eh^3}{12(1-\nu^2)}$$&lt;/span&gt; for measuring the bending rigidity, but with the cubic dependence of this relation on the thickness of the material, and not a precise way of finding poisson's ratio (&lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt;), it seems to be difficult. Has anyone tried this method, or any others, to compute the bending rigidity, which gives results similar to the experiments? Thanks.&lt;/p&gt;&#xA;&lt;p&gt;With best regards&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="5" LastEditDate="2022-10-31T11:52:23.140" LastActivityDate="2022-11-01T10:51:19.353" Title="Bending rigidity of the nanomaterial from MD simulation" Tags="|molecular-dynamics|lammps|gromacs|physical-properties-of-materials|nanoparticles|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9885" PostTypeId="2" ParentId="6798" CreationDate="2022-10-31T14:01:09.747" Score="4" Body="&lt;p&gt;This is an older question, but I faced something similar. Not sure if what I'm about to say applies to this case, but it might be a useful to have a record of this as a possible thing to troubleshoot for, for anybody who stumbles upon this post with similar issues.&lt;/p&gt;&#xA;&lt;p&gt;Having followed similar steps as OP and got a similarly strange looking band structure, I found out my mistake was that I did not change the number of k-points on the second line of the &lt;code&gt;KPOINTS&lt;/code&gt; file (it was left as the original number in the &lt;code&gt;IBZKPT&lt;/code&gt; file). It should have been that value plus the number of zero-weighted k-points in the band structure path that was appended to the renamed &lt;code&gt;IBZKPT&lt;/code&gt;-&amp;gt;&lt;code&gt;KPOINTS&lt;/code&gt; file. What my band structure plot showed was a 'k-path' through a uniform k-point mesh rather than through the desired high-symmetry k-point path.&lt;/p&gt;&#xA;&lt;p&gt;I noticed my mistake upon a closer look at&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;VASP Wiki's &lt;a href=&quot;https://www.vasp.at/wiki/index.php/KPOINTS&quot; rel=&quot;nofollow noreferrer&quot;&gt;KPOINTS&lt;/a&gt; page, under &amp;quot;&lt;em&gt;Explicit k-point mesh&lt;/em&gt;&amp;quot; where it specifies &amp;quot;&lt;em&gt;Provide the number of k points on the second line.&lt;/em&gt;&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;VASP Wiki's &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;HSE&lt;/a&gt; band structure tutorial, in the &lt;code&gt;KPOINTS&lt;/code&gt; file under &amp;quot;&lt;em&gt;Procedure 2: 0-weight (Fake) SC procedure (PBE &amp;amp; Hybrids)&lt;/em&gt;&amp;quot;, where they explicitly put the number of k-points as the number of weighted k-points that form a mesh, and the zero-weighted k-points on the high-symmetry path for band structure plotting. (The &lt;code&gt;IBZKPT&lt;/code&gt; file from a previous regular-meshed k-point calculation only has the number of mesh k-points in its second line)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-10-31T14:01:09.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9888" PostTypeId="1" CreationDate="2022-10-31T20:36:24.400" Score="5" ViewCount="889" Body="&lt;p&gt;I already built a copper surface using BURAI and I used an SCF calculation to find the total energy of this surface. Now, what is the next step to finding the adsorption energy of one H2 molecule on this surface?&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5" LastEditDate="2022-10-31T20:39:43.740" LastActivityDate="2022-11-01T03:25:14.467" Title="Adsorption calcs using Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|surfaces|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9889" PostTypeId="1" CreationDate="2022-10-31T21:51:56.940" Score="6" ViewCount="1053" Body="&lt;p&gt;What I am trying to simulate is an evaporation of ammonia water, after being heated by a gold plate underneath. But I have received a lost atom error during minimization. If I removed the minimization command along with the velocity command, it gives bond atom missing error.&lt;/p&gt;&#xA;&lt;p&gt;I am assuming that it is due to the water penetrating the gold plate but I have tried out all the fix/wall commands and fix/addforce command, the results are still the same.&lt;/p&gt;&#xA;&lt;p&gt;Below are my input script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Create a simulation box&#xA;units real&#xA;dimension 3&#xA;atom_style      full&#xA;bond_style      hybrid morse harmonic&#xA;angle_style     harmonic&#xA;dihedral_style  charmm&#xA;improper_style  umbrella&#xA;special_bonds   dreiding&#xA;pair_style      hybrid/overlay lj/cut/coul/long 12.0 hbond/dreiding/lj 4 6 6.5 90 &#xA;kspace_style    pppm 1.0e-4&#xA;kspace_modify   slab 3.0&#xA;dielectric      1.0&#xA;boundary p p f&#xA;&#xA;region awmix block 0 40.07 0 40.07 -5 100.07  #ammonia water region&#xA;create_box 4 awmix bond/types 2 angle/types 2 extra/bond/per/atom 3 extra/angle/per/atom 3 extra/dihedral/per/atom 3 extra/improper/per/atom 3 extra/special/per/atom 3&#xA;read_data ATLASparticle.data add append&#xA;&#xA;region plate block 0 40.07 0 40.07 -5 -1 # gold plate&#xA;lattice fcc 4.08&#xA;create_atoms 4 region plate&#xA;lattice none 1.0&#xA;&#xA;group liquid type 2 3 &#xA;group solid type 4&#xA;&#xA;# Define interaction potential&#xA;pair_coeff 1 1 lj/cut/coul/long 0.0 0.0&#xA;pair_coeff 1 2 lj/cut/coul/long 0.00278209 3.0544905&#xA;pair_coeff 1 3 lj/cut/coul/long 0.00309354 2.939787&#xA;pair_coeff 2 2 lj/cut/coul/long 0.21 3.36 &#xA;pair_coeff 2 2 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 2 2 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;pair_coeff 2 3 lj/cut/coul/long 0.08606498 3.1478565&#xA;pair_coeff 2 3 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 2 3 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;pair_coeff 3 3 lj/cut/coul/long 0.1553 3.166&#xA;pair_coeff 3 3 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 3 3 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;bond_coeff 1 morse 101.905 2.3470 1.0124&#xA;bond_coeff 2 harmonic 600.0 1.0&#xA;angle_coeff 1 103.045 106.67&#xA;angle_coeff 2 75.0 109.47&#xA;&#xA;mass 4 196.96657 # gold&#xA;&#xA;pair_coeff 4 4 lj/cut/coul/long 11.697 2.574&#xA;&#xA;pair_coeff 1 4 lj/cut/coul/long 0.0 0.0&#xA;pair_coeff 2 4 lj/cut/coul/long 0.0 0.0&#xA;pair_coeff 3 4 lj/cut/coul/long 2.8675 0.0554&#xA;pair_coeff 3 4 lj/cut/coul/long 2.8675 0.0114&#xA;&#xA;# Count molecule&#xA;variable oxygen atom &amp;quot;type==3&amp;quot;&#xA;variable nitrogen atom &amp;quot;type==2&amp;quot;&#xA;group oxygen dynamic all var oxygen&#xA;group nitrogen dynamic all var nitrogen&#xA;variable nO equal count(oxygen)&#xA;variable nN equal count(nitrogen)&#xA;fix oxy all ave/time 1000 1 1000 v_nO file number_oxygen.dat&#xA;fix nit all ave/time 1000 1 1000 v_nN file number_nitrogen.dat&#xA;&#xA;# Count energy&#xA;variable kinetic_energy equal ke&#xA;variable potential_energy equal pe&#xA;variable pressure equal press&#xA;variable temperature equal temp&#xA;variable volume equal vol&#xA;fix myat1 all ave/time 1000 1 1000 v_kinetic_energy v_potential_energy v_pressure v_temperature v_volume file energy.dat&#xA;&#xA;#Provide initial velocity to the atoms by setting temperature of our system = 298.15K&#xA;velocity all create 298.15 102939 dist gaussian mom yes rot yes&#xA;&#xA;#Perform minimization&#xA;minimize 2.0e-5 0.001 10000 10000&#xA;timestep 1&#xA;reset_timestep 0&#xA;&#xA;#Setting system&#xA;neigh_modify    every 1 delay 0 check yes&#xA;&#xA;# Results&#xA;dump dump03 all custom 1000 dump03.lammpstrj id type x y z ix iy iz vx vy vz&#xA;thermo_style custom step time temp pe ke etotal press vol&#xA;thermo 1000&#xA;&#xA;# run&#xA;fix wall solid addforce 1.0 0.0 0.0 region plate&#xA;fix 2 all nve/limit 1&#xA;fix 3 all temp/berendsen 80 80 1&#xA;timestep 0.1&#xA;run 50000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm not sure if it is related to the data file (ATLASparticle.data = ammonia water data file) but I don't think that's the case because I have run similar simulation (same data file and parameters) and there is no overlapping.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Create a simulation box&#xA;units real&#xA;dimension 3&#xA;atom_style      full&#xA;bond_style      hybrid morse harmonic&#xA;angle_style     harmonic&#xA;dihedral_style  charmm&#xA;improper_style  umbrella&#xA;special_bonds   dreiding&#xA;pair_style      hybrid/overlay lj/cut/coul/long 12.0 hbond/dreiding/lj 4 6 6.5 90 &#xA;kspace_style    pppm 1.0e-4&#xA;dielectric      1.0&#xA;boundary p p p&#xA;&#xA;region awmix block -50 58.63 -50 58.63 -50 58.63  #ammonia water region&#xA;create_box 3 awmix bond/types 2 angle/types 2 extra/bond/per/atom 3 extra/angle/per/atom 3 extra/dihedral/per/atom 3 extra/improper/per/atom 3 extra/special/per/atom 3&#xA;read_data ATLASparticle.data add append&#xA;&#xA;group vapor type 2 3&#xA;&#xA;#Define interaction potential&#xA;pair_coeff 1 1 lj/cut/coul/long 0.0 0.0&#xA;pair_coeff 1 2 lj/cut/coul/long 0.00278209 3.0544905&#xA;pair_coeff 1 3 lj/cut/coul/long 0.00309354 2.939787&#xA;pair_coeff 2 2 lj/cut/coul/long 0.21 3.36 &#xA;pair_coeff 2 2 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 2 2 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;pair_coeff 2 3 lj/cut/coul/long 0.08606498 3.1478565&#xA;pair_coeff 2 3 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 2 3 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;pair_coeff 3 3 lj/cut/coul/long 0.1553 3.166&#xA;pair_coeff 3 3 hbond/dreiding/lj 2 i 4.0 2.75 4&#xA;pair_coeff 3 3 hbond/dreiding/lj 2 j 4.0 2.75 4&#xA;bond_coeff 1 morse 101.905 2.3470 1.0124&#xA;bond_coeff 2 harmonic 600.0 1.0&#xA;angle_coeff 1 103.045 106.67&#xA;angle_coeff 2 75.0 109.47&#xA;&#xA;#Provide initial velocity to the atoms by setting temperature of our system = 298.15K&#xA;velocity all create 298.15 102939 dist gaussian mom yes rot yes&#xA;&#xA;#Perform minimization&#xA;minimize 2.0e-5 0.001 10000 10000&#xA;timestep 1&#xA;reset_timestep 0&#xA;&#xA;#Setting system&#xA;neigh_modify    delay 10 every 1 check yes&#xA;&#xA;variable oxygen atom &amp;quot;type==3&amp;quot;&#xA;variable nitrogen atom &amp;quot;type==2&amp;quot;&#xA;group oxygen dynamic all var oxygen&#xA;group nitrogen dynamic all var nitrogen&#xA;variable nO equal count(oxygen)&#xA;variable nN equal count(nitrogen)&#xA;fix oxy all ave/time 1000 1 1000 v_nO file number_oxygen_test.dat&#xA;fix nit all ave/time 1000 1 1000 v_nN file number_nitrogen_test.dat&#xA;&#xA;dump dumpMIX all custom 1000 dumpMIXtest.lammpstrj id type x y z ix iy iz vx vy vz&#xA;thermo_style custom step time temp pe ke etotal press vol&#xA;thermo 1000&#xA;&#xA;variable kinetic_energy equal ke&#xA;variable potential_energy equal pe&#xA;variable pressure equal press&#xA;variable temperature equal temp&#xA;variable volume equal vol&#xA;fix myat1 all ave/time 1000 1 1000 v_kinetic_energy v_potential_energy v_pressure v_temperature v_volume file energy_test.dat&#xA;&#xA;#run&#xA;fix         2 all nve&#xA;fix         3 all temp/berendsen 413.15 413.15 100.0&#xA;fix         4 all temp/rescale 1 413.15 413.15 0.05 1.0&#xA;fix         5 all press/berendsen iso 4.0 4.0 1000.0&#xA;timestep 0.1&#xA;run 1000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;*You can get the data file from link below:&#xA;&lt;a href=&quot;https://github.com/JackyXes/ATLASparticle/blob/main/ATLASparticle.data&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/JackyXes/ATLASparticle/blob/main/ATLASparticle.data&lt;/a&gt;&#xA;Please ignore the coordinate values because I changed them for 2 different scripts.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;&lt;p&gt;*Edit&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/OTVTf.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OTVTf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see, there are molecules entering the bottom plate. I tried using fix wall/region on the plate region but I got a illegal command error instead.&lt;/p&gt;&#xA;" OwnerUserId="6208" LastEditorUserId="5" LastEditDate="2022-11-01T16:28:17.927" LastActivityDate="2022-11-01T16:28:17.927" Title="Lost atoms in LAMMPS" Tags="|lammps|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="9890" PostTypeId="2" ParentId="9888" CreationDate="2022-11-01T03:25:14.467" Score="4" Body="&lt;p&gt;&lt;strong&gt;Step 1&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Calculate energy of copper slab with hydrogen molecule on slab: &lt;span class=&quot;math-container&quot;&gt;$E(Cu+H_2) $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 2&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Calculate energy of copper slab: &lt;span class=&quot;math-container&quot;&gt;$E(Cu) $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Step 3&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Calculate energy of hydrogen molecule: &lt;span class=&quot;math-container&quot;&gt;$E(H_2) $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E^{ad}(H_2)$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$E(Cu+H_2)$&lt;/span&gt; -&#xA;&lt;span class=&quot;math-container&quot;&gt;$E(Cu)$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$E(H_2)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hydrogen adsoption on copper surface will vary with different binding sites such as hollow/Bridge site and with different crystallography orientation (For example &lt;span class=&quot;math-container&quot;&gt;$E(100)\neq E(110)$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-01T03:25:14.467" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9891" PostTypeId="2" ParentId="9853" CreationDate="2022-11-01T04:51:40.117" Score="4" Body="&lt;p&gt;We already have lot of discussion on calculations of elastic constants using stress-strain relationship or energy-strain relationship&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2229/problem-related-to-the-calculation-of-elastic-constant-with-vasp5-4-4?rq=1&quot;&gt;Problem related to the calculation of elastic constant with VASP5.4.4&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3896/temperature-effect-on-elastic-constant-using-vasp?rq=1&quot;&gt;Temperature effect on elastic constant using VASP&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8884/elastic-constant-calculation?rq=1&quot;&gt;Elastic constant calculation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4856/why-vasp-calculates-the-elastic-constant-for-another-trigonal-space-group?rq=1&quot;&gt;Why VASP calculates the elastic constant for another trigonal space group?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8624/how-to-start-with-the-elastic-properties-of-2d-materials-using-the-vasp-code?rq=1&quot;&gt;How to start with the elastic properties of 2D materials using the VASP code?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For calculating &lt;strong&gt;elastic-dipole tensor&lt;/strong&gt; there is two major general procedure can be adopted&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;1. Fixed cell method&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Insert a defect such as self interstitial atom in your simulation cell and allow atoms to relax with fix dimension of unit cell. Calculate the average stress on unit cell (in VASP : &lt;code&gt;grep 'in kB' OUTCAR&lt;/code&gt;).&#xA;The dipole tensor can be calculated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$P_{ij} = \int_{V_{cell}} \sigma dV$&lt;/span&gt; = -&lt;span class=&quot;math-container&quot;&gt;$V_{cell}\langle\sigma\rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;2. Applied strain&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Relax the simulation box fully (both atomic position and cell vectors) such that macroscopic stress  &lt;span class=&quot;math-container&quot;&gt;$\langle\sigma\rangle$&lt;/span&gt; vanishes. This as same effect as application of external strain on unrelaxed system. One can even calculate equivalent applied strain from relaxed configuration&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$P_{ij} = -V_{cell}(C_{ijkl}\epsilon_{kl}^{ext}-\langle\sigma\rangle)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.033602&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.033602&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2022-11-01T09:37:31.213" LastActivityDate="2022-11-01T09:37:31.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9892" PostTypeId="2" ParentId="9889" CreationDate="2022-11-01T09:46:35.777" Score="6" Body="&lt;p&gt;You have made many changes between the second attached input (which is a bulk ammonia-water mixture at 413K -- albeit with a very strange choice of two thermostats) and the first input. The first input has an ammonia-water mixture:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;with one non-periodic axis&lt;/li&gt;&#xA;&lt;li&gt;in an extremely inhomogeneous box (there's vacuum!)&lt;/li&gt;&#xA;&lt;li&gt;and a slab of gold&lt;/li&gt;&#xA;&lt;li&gt;all thermostatted together&lt;/li&gt;&#xA;&lt;li&gt;at 80K&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Any of those changes, or combination of those changes could have broken your simulation (and remember -- just because your first simulation ran does not even guarantee that &lt;em&gt;it&lt;/em&gt; is correct). You have to test them one by one and proceed via elimination.&lt;/p&gt;&#xA;&lt;p&gt;(Note that &amp;quot;my input crashed&amp;quot; questions are usually not easily answered on StackExchange because the diagnostic process invariably involves some back-and-forth. The process is more suited to a forum, such as the LAMMPS forum at MatSci.org.)&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-11-01T09:46:35.777" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9893" PostTypeId="2" ParentId="9884" CreationDate="2022-11-01T10:14:39.363" Score="5" Body="&lt;p&gt;Finally, a question involving my PhD! In my work I studied the nano-rigidity of DNA duplexes to see if they were good materials for making nano-walkers. (Spoiler alert: duplexes aren't great; origami is probably rigid enough.)&lt;/p&gt;&#xA;&lt;p&gt;You are absolutely right to be skeptical about applying continuum equations carelessly to nanostructures. If a nanostructure is soft / small enough that significant deformations only require energies on the order of a few &lt;span class=&quot;math-container&quot;&gt;$k_BT$&lt;/span&gt;, then the canonical ensemble of the nanostructure will include significant contributions from deformed states, and you need polymer theoretical physics to inform you about the free energy of deformation.&lt;/p&gt;&#xA;&lt;p&gt;As a practical example, the lower graph from &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acsomega.7b01692&quot; rel=&quot;nofollow noreferrer&quot;&gt;my paper&lt;/a&gt; shows the free energy released upon bending a DNA duplex &amp;quot;back in on itself&amp;quot;, thanks to &amp;quot;sticky ends&amp;quot; on each side, with the sticky ends glued together in two different ways. Note that both graphs are very nonlinear, with the bending energy hardly changing with DNA duplex length after about 30-40 base pairs -- this is more consistent with a thermalized worm-like chain than any rigid theory.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Aa6wV.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Aa6wV.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;EDIT: from there, the best way to proceed is (1) quantify just how deformation is measured in the nanosystem (2) define that in terms of a reaction co-ordinate measurable in an MD simulation (3) use importance sampling methods, like umbrella sampling or forward flux sampling, to obtain a free energy surface in that reaction co-ordinate, and thus the energy of deformation.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2022-11-01T10:51:19.353" LastActivityDate="2022-11-01T10:51:19.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9894" PostTypeId="1" AcceptedAnswerId="9896" CreationDate="2022-11-01T12:01:06.253" Score="5" ViewCount="253" Body="&lt;p&gt;Do you know how to compute binding energy using Gaussian? I have optimized binding pocket with ligand using ONIOM methodology implemented in Gaussian16. For the high layer B3LYP/6-31+G(d,p) was used, while low layer with PM6 method. Then, I recomputed the system without ligand and hence used only PM6 for the aminoacids. I though the way would be to subtract the energies of the system with and without ligand but it actually makes no sense for ONIOM total energy equals -1029.031167au and PM6 energy is -1.261231au.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance !&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2022-11-01T17:38:42.340" Title="Binding energy with ONIOM" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|molecular-modeling|gaussian|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9895" PostTypeId="2" ParentId="9867" CreationDate="2022-11-01T13:43:45.660" Score="2" Body="&lt;p&gt;Potential energy of a system depends on relative positions of different atoms which is basically a n-dimesional energy landscape. Imposing certain symmetry on the crystal system represents same symmetry in energy landscape as well. For example, It is enough to use 1D energy-volume relationship for cubic system to find minimum energy configuration while for hexagonal system, two dimensional surface is required. From n-dimesnional hypersurface which is unknown to us and computational algorithm as well, we choose certain starting point on that hypersurface. Assuming a convex smooth hypersurface, minimization algorithm tries to find energy minima local to the starting point. Once it reaches local minima algorithm stops, now question is whether that local minima is a global minima or not, it is difficult to say, until other configurations are known.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-01T13:43:45.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9896" PostTypeId="2" ParentId="9894" CreationDate="2022-11-01T14:05:20.823" Score="4" Body="&lt;p&gt;You have to also compute the energy of the free ligand at the DFT level, and subtract that too. A binding process is the reaction of a protein with a free ligand to form the protein-ligand complex, rather than a protein gaining a ligand from nowhere. So the energy of the free ligand must enter the equation of the binding energy.&lt;/p&gt;&#xA;&lt;p&gt;Some comparatively minor but still important points:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The basis set 6-31+G(d,p) is unreliable for single point energies, although it may be enough for geometry optimizations. The single point energies must be computed with a basis set that is at least a triple-zeta basis set, such as 6-311+G(d,p) (or even better, def2-TZVP)&lt;/li&gt;&#xA;&lt;li&gt;Don't forget to add the dispersion correction&lt;/li&gt;&#xA;&lt;li&gt;As you are almost certainly interested in the binding process in water, as opposed to in vacuum, you should add a solvation model&lt;/li&gt;&#xA;&lt;li&gt;Make sure to fully sample the binding conformations (for example under the PM6 level) and compute their Boltzmann average. Using a single hand-drawn binding pose is almost always unacceptable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastEditorUserId="7" LastEditDate="2022-11-01T17:38:42.340" LastActivityDate="2022-11-01T17:38:42.340" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9897" PostTypeId="2" ParentId="8695" CreationDate="2022-11-01T19:38:29.573" Score="3" Body="&lt;h1&gt;LAMMPS&lt;/h1&gt;&#xA;&lt;p&gt;Any popular MD software is likely to allow you to study phase transitions with increasing temperature. LAMMPS slightly beats &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1222/5&quot;&gt;GROMACS&lt;/a&gt; in terms of activity here on MMSE, since the &lt;a href=&quot;/questions/tagged/lammps&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;lammps-container&quot;&gt;lammps&lt;/a&gt; tag has 82 questions in total and 38 asked this year, whereas the &lt;a href=&quot;/questions/tagged/gromacs&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gromacs&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;gromacs&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;gromacs-container&quot;&gt;gromacs&lt;/a&gt; tag comes in a close second with 69 questions in total and 36 asked this year. Our &lt;a href=&quot;https://chat.stackexchange.com/rooms/109805/lammps&quot;&gt;LAMMPS chat room&lt;/a&gt; is also a bit older than our &lt;a href=&quot;https://chat.stackexchange.com/rooms/120383/gromacs&quot;&gt;Gromacs chat room&lt;/a&gt; and the LAMMPS one has more active users and more messages from users in it.&lt;/p&gt;&#xA;&lt;p&gt;Here's some information about LAMMPS:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Free, and open-source (GNU GPL license).&lt;/li&gt;&#xA;&lt;li&gt;Long history: First released in 1995 (4 years after Gromacs in 1991, although  Gromacs was based on an earlier program called GROMOS from 1978).&lt;/li&gt;&#xA;&lt;li&gt;Under very active development: For many codes, the majority of the development was done years or decades ago, &lt;a href=&quot;https://github.com/gromacs/gromacs/graphs/contributors&quot; rel=&quot;nofollow noreferrer&quot;&gt;but the development of LAMMPS seems only to have grown&lt;/a&gt;, not waned. This is also true for Gromacs, but LAMMPS has 220 contributors on GitHub whereas Gromacs only has 81. &lt;strong&gt;I've even seen a LAMMPS simulation being done on a smartphone back in 2018, and I could see a plot that was changing in real-time as the calculation was being done!&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;Since the very beginning (decades ago), it was designed to run in parallel (i.e. fast). In fact the &amp;quot;&lt;strong&gt;MP&lt;/strong&gt;&amp;quot; in LAM&lt;strong&gt;MP&lt;/strong&gt;S&amp;quot; stands for &amp;quot;massively parallel&amp;quot;! There's also &lt;a href=&quot;https://docs.lammps.org/Speed_gpu.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;support for GPUs&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Basically all of the advantages listed above are also true of Gromacs (and Gromacs has been developed for longer, but LAMMPS has more developers currently, which is probably more important in the long-run).&lt;/li&gt;&#xA;&lt;li&gt;According to Steve Plimpton, &lt;a href=&quot;https://lammps.sandia.gov/threads/msg05362.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;a fator of 2x speed-up in GROMACS compared to LAMMPS is &amp;quot;not surprising&amp;quot;&lt;/a&gt; because GROMACS has pairwise interactions implemented in assembly code.&lt;/li&gt;&#xA;&lt;li&gt;It is primarily a classical MD code, so quantum effects are not the focus. QM/MM is possible, but would require using one of the interfaces.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-11-01T19:38:29.573" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9898" PostTypeId="2" ParentId="8797" CreationDate="2022-11-01T20:09:31.367" Score="3" Body="&lt;p&gt;Based on the comments, it seems that this is not possible in VASPKIT.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-11-01T20:09:31.367" CommentCount="0" CommunityOwnedDate="2022-11-01T20:09:31.367" ContentLicense="CC BY-SA 4.0" />
  <row Id="9899" PostTypeId="1" CreationDate="2022-11-01T21:14:05.130" Score="4" ViewCount="66" Body="&lt;p&gt;Occasionally a med-chemist will remark that they think a particular molecule has a 'reactive centre' and so should be de-prioritised (in the context of hit- and drug- discovery).&lt;/p&gt;&#xA;&lt;p&gt;Leaving aside known metabolic enzymes, which will catalyse certain reactions, speeding them up beyond what you'd see passively, is there some metric available to highlight 'reactive centres'? Perhaps Fukui indices are suitable here - but, as &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/sp.html#fukui-index&quot; rel=&quot;nofollow noreferrer&quot;&gt;noted on the XTB website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;As the Fukui indexes depend on occupation numbers and population analysis (see Properties), they are sensitive toward basis set changes. Therefore Fukui indexes should not be recognized as absolute numbers but as relative parameters in the same system.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="5" LastEditDate="2022-11-02T12:37:59.037" LastActivityDate="2022-11-02T12:37:59.037" Title="Is there a computationally-accessible metric of &quot;reactivity&quot; in the medicinal-chemistry sense?" Tags="|xtb|reactivity|" AnswerCount="0" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9900" PostTypeId="1" CreationDate="2022-11-01T23:27:05.060" Score="4" ViewCount="98" Body="&lt;p&gt;I'm annealing a system and setting multiple fixes in the same input script to change the thermostat parameters. When the below is contained in the input file (for example), the simulation completes and all other output files write successfully - but the trajectory file is empty.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix            ID all nvt temp 300.0 400.0 100.0 tchain 1 #anneal 300K to 400K&#xA;run            500000&#xA;fix            ID all nvt temp 400.0 400.0 100.0 tchain 1 #hold at 400K&#xA;run            500000&#xA;&#xA;dump           ID all dcd 10000 trajectory.dcd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, when removing all but one of the fixes (i.e., to run a simulation at constant T) - keeping everything else in the input file the same - the trajectory file is written as normal.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix            ID all nvt temp 300.0 300.0 100.0 tchain 1 #hold at 300k&#xA;run            500000&#xA;&#xA;dump           ID all dcd 10000 trajectory.dcd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6213" LastActivityDate="2022-11-02T06:07:39.907" Title="Empty trajectory files when setting multiple fixes in LAMMPS" Tags="|lammps|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9901" PostTypeId="1" CreationDate="2022-11-02T06:06:51.207" Score="3" ViewCount="164" Body="&lt;p&gt;In Kohn-Sham DFT, the exact density of the ground-state wavefunction is given by summing the squares of the filled K-S orbitals.&lt;/p&gt;&#xA;&lt;p&gt;Suppose now that one only needs the exact density (and nothing else w.l.o.g; see &lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2022/cp/d2cp01585d&quot; rel=&quot;nofollow noreferrer&quot;&gt;this open-access article e.g. for the derivation of the exact optical gap from the excited density&lt;/a&gt; of, say, the lowest doubly (for each spin) excited state, of the molecule in question. Does summing the squares of the K-S orbitals, except for the HOMO (which would now be swapped with the LUMO) give the desired density of said state?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I meant the lowest doubly excited SINGLET state with the ground state also being singlet.&lt;/p&gt;&#xA;&lt;p&gt;EDIT 2: wzkchem5's counterexample seems to be mostly correct, but their formation of their answer likely implies that the ground state of the total wavefunction itself is degenerate. So I'm explicitly adding in the condition that the ground state is non-degenerate, as is in the theoretical foundation of K-S DFT.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-11-03T09:05:18.697" LastActivityDate="2022-11-03T15:17:55.157" Title="Is this method of obtaining only the exact &quot;other&quot; densities, and no other properties w.l.o.g, correct?" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|excited-states|electron-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9902" PostTypeId="2" ParentId="9900" CreationDate="2022-11-02T06:07:39.907" Score="4" Body="&lt;p&gt;First of all, if you are using multiple &lt;code&gt;fix&lt;/code&gt; with different conditions, you must &lt;code&gt;unfix&lt;/code&gt; the previous &lt;code&gt;fix&lt;/code&gt; before going into the next condition, else you would still have the first &lt;code&gt;fix&lt;/code&gt; in place along with a new &lt;code&gt;fix&lt;/code&gt;. This is a very bad practice and may generate dubious results.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, you have used the &lt;code&gt;dump&lt;/code&gt; command after &lt;code&gt;run&lt;/code&gt;, which means you are asking LAMMPS to store trajectories after the simulation is completed. This will not store the trajectories as you have requested (every &lt;span class=&quot;math-container&quot;&gt;$10000$&lt;/span&gt; step).&lt;/p&gt;&#xA;" OwnerUserId="605" LastActivityDate="2022-11-02T06:07:39.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9903" PostTypeId="2" ParentId="9822" CreationDate="2022-11-02T06:16:19.537" Score="3" Body="&lt;p&gt;I am answering this question based on the reply I was receiving from Axel Kohlmeyer in the LAMMPS community discussion forum.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;My 1st question is if regardless of how we build the neighbor list, the results are the same, what is the need for this command? or am I making comparisons with wrong properties and I need to validate with some other properties?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The results are not going to be the “same”. The longer the delay between neighbor list rebuilds, the larger the chance that you are missing the contribution of interacting pairs of atoms within the cutoff because they have moved inside the cutoff range since the last neighbor list rebuild. Since you are using a rather large cutoff the differences (in potential energy) due to the missed contributions will be very small. A setting for “delay 20” is at the limit of what is an acceptable choice for your kind of system. The total energy is not a good parameter since the differences due to the missed interactions is small relative to the total energy.&lt;/p&gt;&#xA;&lt;p&gt;Regardless of whether the neighborlist rebuilds are done sufficiently frequent or not, if you build neighbor lists on different timesteps, you will change the order in which forces are summed up, which will lead to small numerical differences on the forces (due to limitations of floating point math) and thus to exponentially diverging trajectories. They will still be statistically equivalent.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;What is the significance of this, if the energy of the system statistically the same no matter what?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Dangerous builds are a consequence of the neighbor list skin and a check that LAMMPS is doing when a neigh_modify check yes setting is used. This is based on a heuristic: if any atom has moved more than half the neighbor list skin distance since the last neighbor list build, the current update is considered “dangerous”, i.e. there is a risk, that some interacting pair has been missed in the force computation of the time step(s) before the one where the neighbor list build happens. This heuristic of a half the skin distance is very conservative, so you can have dangerous builds and still correct neighbor lists. However, if you have no dangerous builds, it is certain that all neighbor lists were correct.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why this is happening?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, that is because the time consuming rebuild of the neighbor list is deferred until the neighbor list check heuristic is reached, and the check for it is fast. Please have a look at the timing summary and the number of neighbor list rebuilds. Your second case enforces a neighbor list rebuild in every step and that is not needed at all. About every 10 steps should be a safe choice and every 20 is probably still acceptable, even if you may miss a very distant pair occasionally since your cutoff is so large.&lt;/p&gt;&#xA;&lt;p&gt;Link to original answer - &lt;a href=&quot;https://matsci.org/t/about-neigh-modify-command-and-dangerous-builds/44988/4&quot; rel=&quot;nofollow noreferrer&quot;&gt;About neigh_modify command and dangerous builds&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="605" LastActivityDate="2022-11-02T06:16:19.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9904" PostTypeId="2" ParentId="9901" CreationDate="2022-11-02T07:43:22.813" Score="3" Body="&lt;p&gt;In general, no. Consider an infinitely stretched dihydrogen molecule, in its ground (singlet) state. Obviously the HOMO is the in-phase linear combination of the 1s orbitals of the neutral hydrogen atoms, and the LUMO is their out-of-phase linear combination. (The shape of the HOMO follows from the fact that the density of the system must be equal to a sum of the densities of two neutral hydrogen atoms, and the shape of the LUMO follows from the fact that the Kohn-Sham potential is local, thus the LUMO of this molecule must be locally identical to the HOMO up to a phase.) A corollary is that, the square of the LUMO is the same as the square of the HOMO. (EDIT: more rigorously speaking, their difference is non-zero for finitely stretched hydrogen molecules but vanishes in the infinitely stretched limit.)&lt;/p&gt;&#xA;&lt;p&gt;Now excite the molecule to the lowest doubly excited singlet state. It follows that in this state, at least one of the electrons must populate an atomic orbital other than the 1s orbital (EDIT: a molecular orbital involving significant contribution from a non-1s atomic orbital), since there are only three singlet states constructible from the two 1s orbitals and two electrons (the ground state and two charge transfer states:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{\sqrt{2}}(\psi_{\rm H1}(r_1)\psi_{\rm H2}(r_2) + \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_1)), \psi_{\rm H1}(r_1)\psi_{\rm H2}(r_1), \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_2)$$&lt;/span&gt;&#xA;The fourth linear combination constructible from the four Slater determinants, &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{\sqrt{2}}(\psi_{\rm H1}(r_1)\psi_{\rm H2}(r_2) - \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_1))$&lt;/span&gt;, is a triplet state), none of which is a doubly excited state. Therefore the density of this excited state cannot be given as twice the square of the LUMO. QED.&lt;/p&gt;&#xA;&lt;p&gt;The conclusion may seem a bit non-intuitive; many will immediately say &amp;quot;isn't the &lt;span class=&quot;math-container&quot;&gt;$({\rm HOMO})_2 \to ({\rm LUMO})_2$&lt;/span&gt; excitation a double excitation?&amp;quot; This reveals a fundamental difference between the Kohn-Sham and HF descriptions of this system. In HF, the closed-shell ground state wavefunction of this system can be expanded in atomic orbitals (neglecting the spin part):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi_{\rm HF} = \frac{1}{2}(\psi_{\rm H1}(r_1)\psi_{\rm H2}(r_2) + \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_1) + \psi_{\rm H1}(r_1)\psi_{\rm H2}(r_1) + \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_2)) \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The latter two terms are spurious intermixtures of charge transfer states, which are famously responsible for the size-inconsistency of RHF. In this case we can formally write the &lt;span class=&quot;math-container&quot;&gt;$({\rm LUMO})_2$&lt;/span&gt; determinant&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tilde{\psi}_{\rm HF} = \frac{1}{2}(\psi_{\rm H1}(r_1)\psi_{\rm H2}(r_2) + \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_1) - \psi_{\rm H1}(r_1)\psi_{\rm H2}(r_1) - \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_2)) \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But this is just as unphysical as the RHF description of the ground state, again due to the charge transfer state contributions.&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham wavefunction can of course be expanded as Eq. (1) as well, but a more important thing is that, the ground state Kohn-Sham density must equal the exact density, given by the exact wavefunction:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi_{\rm exact} = \frac{1}{\sqrt{2}}(\psi_{\rm H1}(r_1)\psi_{\rm H2}(r_2) + \psi_{\rm H1}(r_2)\psi_{\rm H2}(r_1)) \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;while the exact wavefunction of the first doubly excited state inevitably involves the 2s and/or 2p orbitals (EDIT: inevitably involves molecular orbitals that have large contributions from the 2s and/or 2p orbitals), and cannot have any simple relation with the exact ground state wavefunction, as we do in the RHF case. Therefore, while &lt;span class=&quot;math-container&quot;&gt;$({\rm LUMO})_2$&lt;/span&gt; is a valid KS determinant, it does not have any simple relation with the density of the first doubly excited state.&lt;/p&gt;&#xA;&lt;p&gt;Finally, there is one more thing to consider: doubly excited states are not well-defined concepts, especially in complex molecules, because the doubly excited determinants may mix extensively with singly excited determinants, making it impossible to unambiguously assign some states as singly or doubly excited. Thus, in some cases your question may not even be well-defined.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="142" LastEditDate="2022-11-03T15:17:55.157" LastActivityDate="2022-11-03T15:17:55.157" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="9905" PostTypeId="1" CreationDate="2022-11-02T10:28:01.250" Score="3" ViewCount="356" Body="&lt;p&gt;Compared to say the DFT-D3 type of dispersion corrections (set with &lt;a href=&quot;https://www.vasp.at/wiki/index.php/IVDW&quot; rel=&quot;nofollow noreferrer&quot;&gt;IVDW&lt;/a&gt; in VASP),  I've found the nonlocal vdW-DF functionals (described here in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Nonlocal_vdW-DF_functionals&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP Wiki&lt;/a&gt;) to be much more difficult to converge to similar levels of accuracy (which &lt;em&gt;I guess&lt;/em&gt; should be expected given the nature of the vdW correction). My monolayer calculations with the optB88-vdW functional led to some geometry optimizations with several consecutive unconverged electronic optimization steps (even with &lt;code&gt;NELM = 90&lt;/code&gt;, i.e. 90 SCF steps), when starting from a converged structure from a database.&lt;/p&gt;&#xA;&lt;p&gt;My first impression was that my use of &lt;code&gt;EDIFF=1E-07&lt;/code&gt; (VASP's &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EDIFF&quot; rel=&quot;nofollow noreferrer&quot;&gt;electronic convergence parameter&lt;/a&gt;) and &lt;code&gt;EDIFFG = -0.002&lt;/code&gt; (VASP's &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EDIFFG&quot; rel=&quot;nofollow noreferrer&quot;&gt;geometry convergence parameter&lt;/a&gt;) was too fine, which seemed somewhat in line with what I thought was a rougher convergence criterion by &lt;a href=&quot;http://www.2dmatpedia.org/guide&quot; rel=&quot;nofollow noreferrer&quot;&gt;2DMatPedia&lt;/a&gt; (a 2D materials database which used the optB88-vdW functional and an ionic convergence criterion that the energy difference is below &lt;span class=&quot;math-container&quot;&gt;$10^{-4}$&lt;/span&gt; eV for structure relaxations). However, the &lt;a href=&quot;https://jarvis-materials-design.github.io/dbdocs/jarvisdft/&quot; rel=&quot;nofollow noreferrer&quot;&gt;JARVIS&lt;/a&gt; database, which also contains 2D monolayers, &lt;em&gt;seemed&lt;/em&gt; to be able to do calculations with optB88-vdW and (what I thought were) stricter convergence criteria:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;&lt;em&gt;Both the internal atomic positions and the lattice constants are allowed to relax in spin-unrestricted calculations until the maximal residual Hellmann–Feynman forces on atoms are smaller than &lt;span class=&quot;math-container&quot;&gt;$0.001$&lt;/span&gt; eV Å&lt;span class=&quot;math-container&quot;&gt;$^{−1}$&lt;/span&gt; and energy-tolerance of &lt;span class=&quot;math-container&quot;&gt;$10^{-7}$&lt;/span&gt; eV with accurate precision setting (PREC=Accurate).&lt;/em&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;This leads me to my question.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are the convergence difficulties I've faced with optB88-vdW expected (and so it is reasonable to relax my convergence criteria)? Or are there other things that I can tweak to achieve the tighter convergence criteria that would be important for later phonon and elastic constants calculations for example?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have played around with just trying to converge static calculations tightly (&lt;code&gt;EDIFF=1E-07&lt;/code&gt;), by changing the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ALGO&quot; rel=&quot;nofollow noreferrer&quot;&gt;electronic minimization algorithm&lt;/a&gt; to &lt;code&gt;ALGO = Normal&lt;/code&gt; or &lt;code&gt;ALGO = ALL&lt;/code&gt; (I usually use &lt;code&gt;ALGO = Fast&lt;/code&gt;), or playing around with &lt;code&gt;IMIX&lt;/code&gt; (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/IMIX&quot; rel=&quot;nofollow noreferrer&quot;&gt;density mixing&lt;/a&gt;). However, I could not find a convenient general setting for successful convergence all the time. Different combinations have helped me achieved convergence for the 4-6 different monolayers I've tested, but I had to 'babysit' each calculation.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-11-21T07:22:45.227" Title="Electronic Convergence Issues with Nonlocal vdW-DF Functionals (in VASP)" Tags="|density-functional-theory|vasp|numerical-convergence|dispersion-correction|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9906" PostTypeId="2" ParentId="9874" CreationDate="2022-11-02T11:34:37.887" Score="2" Body="&lt;p&gt;The answer is no. Post-Hartree-Fock methods are famously slow to converge to the complete basis set limit due to their dependence on the unoccupied orbitals. Modern basis sets, such as the Dunning cc-pVXZ series and the Karlsruhe def2 series are designed to achieve the best compromise of accuracy and performance. By freezing the &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; orbitals, you compromise this accuracy, especially since the &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; orbitals are more important at the MP2 level than the HF level!&lt;/p&gt;&#xA;&lt;p&gt;I would also like to point out that while NWChem is not known to be competitive on single-node performance; its focus is on massively parallel calculations. As we have recently discussed in our open access review in &lt;a href=&quot;https://doi.org/10.1002/wcms.1610&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wiley Interdiscip. Rev. Comput. Mol. Sci. 12, e1610 (2022)&lt;/a&gt;, there is a wide variety of free and open source codes that can be easily installed on personal hardware and be used for realistic computational chemistry.&lt;/p&gt;&#xA;&lt;p&gt;Psi4 and PySCF are two personal favorites of mine: Psi4 is easy to use while PySCF offers a powerful toolbox for designing new methods. Psi4 is especially attractive for its focus on choosing fast algorithms by default: it makes using density fitting methods easy, which can significantly speed up MP2 calculations, for instance. Psi4 also implements &lt;a href=&quot;https://psicode.org/psi4manual/master/fnocc.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;frozen natural orbital methods&lt;/a&gt;, which are a safe way to economize coupled-cluster calculations by freezing out natural orbitals that have small occupations at the MP2 level of theory. Psi4 also has &lt;a href=&quot;https://psicode.org/psi4manual/master/cbs.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;built-in support for basis set extrapolation&lt;/a&gt;, which likewise offer an easy way to economize on the cost of calculations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2022-11-03T15:24:07.870" LastActivityDate="2022-11-03T15:24:07.870" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9907" PostTypeId="1" AcceptedAnswerId="12191" CreationDate="2022-11-02T11:43:31.033" Score="4" ViewCount="122" Body="&lt;p&gt;I am using classical molecular dynamics (MD) to observe a non-covalent interaction between my complex and the DNA, but there is a problem in that the complex interacts with the terminal of the DNA for a very long time, which is irrelevant in the biological system because the end (terminal) of the DNA cannot be located there. As a result, I want to take some action to reduce the interaction between the complex and DNA.&#xA;Does anyone know how to help with this problem?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="5" LastEditDate="2022-11-02T12:42:44.557" LastActivityDate="2024-01-06T18:18:55.283" Title="Non-Covalent Interaction between drug and DNA?" Tags="|molecular-dynamics|molecular-interactions|biomaterials|structural-biology|amber|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="9909" PostTypeId="2" ParentId="9873" CreationDate="2022-11-02T12:20:39.577" Score="3" Body="&lt;p&gt;This is the hybrid Gaussian and plane wave method described in &lt;a href=&quot;https://doi.org/10.1080/002689797170220&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mol. Phys. 92, 477 (1997)&lt;/a&gt;, in which you expand the orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi_{i\sigma}$&lt;/span&gt; in a Gaussian basis set, but compute the Coulomb interaction of the charge density with itself with a plane-wave expansion employing Fast Fourier Transforms. The benefit of this approach is that you have simultaneously a compact orbital basis in which you can use dense diagonalization to find the orbitals from the Fock matrix, and a faster way to compute the Madelung sums. The pseudopotential is necessary to eliminate the core orbitals, which can't be represented in the plane wave basis; it also allows for the use of a smaller Gaussian basis set as tight exponents are not needed in the basis set.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-02T12:20:39.577" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9910" PostTypeId="2" ParentId="9525" CreationDate="2022-11-02T13:00:14.703" Score="2" Body="&lt;p&gt;From my little experience I would start by defining a spin value for &amp;quot;this site has solvent instead of polymer&amp;quot;. (It could replace your existing &amp;quot;no polymer here&amp;quot; spin value, or be a new one if you really expect voids without either polymer or solvent.)&lt;/p&gt;&#xA;&lt;p&gt;From there you can just do standard lattice statistical mechanics. How does a solvent-ed site &amp;quot;feel&amp;quot; about being next to other solvent-ed sites? Next to polymer sites? Being flipped into a polymer site? Well, all those will be encoded in &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{ij}$&lt;/span&gt; neighbour terms and &lt;span class=&quot;math-container&quot;&gt;$\mu_i$&lt;/span&gt; field terms. If your terms are well-chosen, you should have a reasonable model.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-11-02T13:00:14.703" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9911" PostTypeId="2" ParentId="9883" CreationDate="2022-11-02T15:26:02.827" Score="4" Body="&lt;p&gt;As per my comment,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If OP is referring to dielectric tensor for &amp;quot;optics&amp;quot;, examples can be found &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Optical_properties_and_dielectric_response_-_Tutorial&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; from the VASP Wiki.&lt;/li&gt;&#xA;&lt;li&gt;For the density-of-states (DOS), the VASP Wiki has a tutorial &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Fcc_Si_DOS&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;HSE06 tutorials on the VASP Wiki can be found &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Si_HSE_bandstructure&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NiO_HSE06&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;HSE06 DOS tutorial can be found &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Fcc_Ni_DOS_with_hybrid_functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I suggested that OP can click on the INCAR settings in these pages to understand what they do, and combine them appropriately for OP's specific use case of HSE06 DOS calculations.&lt;/p&gt;&#xA;&lt;p&gt;I'll also give a more &amp;quot;step-by-step&amp;quot; answer, with the caveat that this is just one possible way of doing things that makes sense to me.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Structure relaxation with PBE&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;We could have done the structure relaxation with HSE06 but that's going to be very expensive. Use the &lt;code&gt;CONTCAR&lt;/code&gt; from the PBE structure relaxation as the &lt;code&gt;POSCAR&lt;/code&gt; for all subsequent steps.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Static PBE calculation (optional)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I would suggest performing a static calculation with PBE to generate a &lt;code&gt;WAVECAR&lt;/code&gt; file (set &lt;code&gt;LWAVE = .TRUE.&lt;/code&gt;). I believe that starting the HSE06 calculation with the PBE converged orbitals should speed up convergence.&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;HSE06 DOS&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For the actual HSE06 calculation, you'd want these &lt;code&gt;INCAR&lt;/code&gt; settings, which can be found in VASP Wiki's HSE06 tutorials linked above. Of course, some of them can be tweaked accordingly.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  LHFCALC  = .TRUE. ! Hartree-Fock / DFT hybrid&#xA;  ALGO     = Damped&#xA;  TIME     = 0.5&#xA;  HFSCREEN = 0.2    ! HSE06&#xA;  AEXX     = 0.25   ! fraction of exact exchange&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you did the previous step of getting a PBE converged &lt;code&gt;WAVECAR&lt;/code&gt;, move it to the directory for this HSE06 calculation. It should be detected when you&#xA;start the calculation, but you could explicitly set &lt;code&gt;ISTART=1&lt;/code&gt; for certainty.&lt;/p&gt;&#xA;&lt;p&gt;For the DOS, include in the &lt;code&gt;INCAR&lt;/code&gt; file &lt;code&gt;ISMEAR = -5&lt;/code&gt; (the tetrahedron method), which is important for getting high-quality DOS (see &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISMEAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and this &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S277294942200002X?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;), and &lt;code&gt;LORBIT = 11 &lt;/code&gt; to generate &lt;code&gt;DOSCAR&lt;/code&gt; and &lt;code&gt;PROCAR&lt;/code&gt; files.&lt;/p&gt;&#xA;&lt;p&gt;If OP wants practice, it looks like the files can be downloaded for this &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Fcc_Ni_DOS_with_hybrid_functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt; from the VASP Wiki (near the bottom of the page).&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-11-02T15:26:02.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9912" PostTypeId="1" CreationDate="2022-11-02T16:02:32.683" Score="2" ViewCount="170" Body="&lt;p&gt;I am trying to calculate magnetic properties in my material with VASP, much like Fig 3b of &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.100.134438&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. The paper says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;To understand the origin of the SIAin monolayer MnBi2Te4, we performed the atom-resolved SIA calculations by changing the SOC strength of the atoms separately. As shown in Fig.3(a), when we take into account only one kind of the element’s SOC, the SIA is much smaller than that in the real situation (denoted by the black line). In other words, the SOC of each element alone cannot cause the SIA. Actually, the SIA mainly originates from the joint SOC effect of Mn and Te atoms, because the calculated SIA approaches the correct value only when the SOC of the Mn and Te atoms is considered simultaneously [see Fig.3(b)].&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jxvHNm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jxvHNm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do I calculate the curves that only involve Bi and Te, or Bi and Mn, or Mn and Te, for example?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The paper says: &amp;quot;Our DFT calculations were performed using the Viennaab initiosimulation package (VASP)&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="6217" LastEditorUserId="5" LastEditDate="2022-11-03T03:15:02.940" LastActivityDate="2022-11-03T03:15:02.940" Title="How to include the spin-orbit coupling strength of only two or three elements in VASP?" Tags="|vasp|spin-orbit-coupling|reproducing-data-from-papers|" AnswerCount="0" CommentCount="7" ClosedDate="2023-05-28T16:18:10.607" ContentLicense="CC BY-SA 4.0" />
  <row Id="9914" PostTypeId="1" CreationDate="2022-11-02T23:02:07.407" Score="1" ViewCount="43" Body="&lt;p&gt;In DFT calculations one isn't able to set up a system which has no magnetic ordering but has local magnetic moments that are non-zero. &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4162/how-can-i-properly-represent-paramagnetic-materials-in-dft-calculations&quot;&gt;This&lt;/a&gt; answer talks about how one can try to use a very large supercell where the magnetic ions' magnetic moments are initialized randomly, and I've also seen several papers which go the opposite direction and just turn the spin off in the calculation so that there are no unpaired electrons.&lt;/p&gt;&#xA;&lt;p&gt;I know that DMFT calculations are able to capture the properties of systems with local magnetic moments that are not ordered, but I was wondering if there are other approaches that are able to work, even if they aren't commonly used or it hasn't been implemented so that it works. For example, is it possible in approaches based on Hedin's equations, FCI, Monte Carlo methods, etc. to get paramagnetic behavior? I would guess that many methods are limited by having periodic boundary conditions that assume that the magnetic moment of an ion in one cell is the same as the magnetic moment in another cell, but it would be a bit surprising to me if DMFT were the only method that could handle paramagnetism without having randomly distributed magnetic moments in extremely large supercells.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2022-11-02T23:02:07.407" Title="What methods are able to capture the properties of paramagnetic materials?" Tags="|density-functional-theory|dynamical-mean-field-theory|" AnswerCount="0" CommentCount="12" ClosedDate="2023-06-01T02:28:21.413" ContentLicense="CC BY-SA 4.0" />
  <row Id="9915" PostTypeId="1" CreationDate="2022-11-03T09:16:09.140" Score="3" ViewCount="32" Body="&lt;p&gt;(For context, see my other question &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9901/4231&quot;&gt;here&lt;/a&gt;; this has been disproven (albeit contestedly), and is not even well-defined in the first place, so I'm going to ask a slightly different (and well-defined) question here, in a way that wzkchem5's ctrxmpl. might not hold* here)&lt;/p&gt;&#xA;&lt;p&gt;Let A be a singlet molecule with a non-degenerate ground state and a non-degenerate first excited state. Let X be the set of exact restricted Kohn-Sham orbitals of the ground state of A. The sum of the squares of the &amp;quot;occupied&amp;quot; parts of X equals the exact density of the ground state of A.&lt;/p&gt;&#xA;&lt;p&gt;Suppose one does the same &amp;quot;summing&amp;quot; process again, except for α-orbital of the HOMO which is swapped with the β-orbital of the LUMO(w.l.o.g, since the α and β orbitals corresponding to an element of X must be the same in their orbit part anyway).&lt;/p&gt;&#xA;&lt;p&gt;Would this process yield the exact density of the first excited state(non-degenerate by assumption)?&lt;/p&gt;&#xA;&lt;p&gt;*If one were to apply the finite truncations of wzkchem5's ctrxmpl. to my question and let the distance go to infinity, the &amp;quot;first excited state&amp;quot; might have a chance to converge to the ground state of the limit of the wavefunctions, instead of the first excited state of said limit. I'm a mathematics student so I know what I'm talking about.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-11-03T09:23:19.030" LastActivityDate="2022-11-03T09:23:19.030" Title="Is this method of obtaining only the exact &quot;first excited state&quot; density correct, under select conditions that makes it mathematically non-ambiguous?" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|excited-states|electron-density|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T22:53:32.707" ContentLicense="CC BY-SA 4.0" />
  <row Id="9916" PostTypeId="1" AcceptedAnswerId="9918" CreationDate="2022-11-03T10:07:27.510" Score="3" ViewCount="209" Body="&lt;p&gt;I want a simple phonon dispersion calculation, the lighter the program the better I do not want to install some huge package like QuantumExpresso just for that. Another way would be to find a database with phonon dispersion data for different materials, it's there any?&lt;/p&gt;&#xA;" OwnerUserId="5321" LastEditorUserId="5321" LastEditDate="2022-11-03T13:12:36.910" LastActivityDate="2022-11-04T19:02:28.867" Title="Simple and quick way to get phonon dispersion?" Tags="|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9917" PostTypeId="1" CreationDate="2022-11-03T11:29:21.143" Score="4" ViewCount="58" Body="&lt;p&gt;Anyone know introductory computational drug design literature of great value.&lt;/p&gt;&#xA;&lt;p&gt;I found plenty from web stores, but some of these cost €100 or more. I'm not sure if all of them are as worthwhile.&lt;/p&gt;&#xA;&lt;p&gt;Ideally looking for a ~45 euros book that's brilliant. Since I've found these in other disciplines.&lt;/p&gt;&#xA;" OwnerUserId="5821" LastEditorUserId="5" LastEditDate="2023-12-09T17:21:10.753" LastActivityDate="2023-12-09T17:31:01.580" Title="Great value introductory computational drug design literature?" Tags="|reference-request|one-topic-per-answer|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9918" PostTypeId="2" ParentId="9916" CreationDate="2022-11-03T14:37:15.293" Score="2" Body="&lt;h3&gt;The &lt;a href=&quot;https://next-gen.materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project&lt;/a&gt;&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Harnessing the power of supercomputing and state-of-the-art methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;The &lt;a href=&quot;https://next-gen.materialsproject.org/api#accessing-data&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project API&lt;/a&gt;&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Materials Project API allows anyone to have direct access to&#xA;current, up-to-date information from the Materials Project database in&#xA;a structured way.&lt;/p&gt;&#xA;&lt;p&gt;This allows for analysis, development of automated tools, machine&#xA;learning, downloading personal copies of the Materials Project&#xA;database and more on a large scale.&lt;/p&gt;&#xA;&lt;p&gt;The API is offered with the hopes of making Materials Project data&#xA;more useful to you. We want you to use our data! As such, the API is&#xA;offered free-of-charge and we support several tools to help you get&#xA;started.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Example of phonon dispersion for &lt;span class=&quot;math-container&quot;&gt;$\ce{GaAs}$&lt;/span&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/TVscn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TVscn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2022-11-04T19:02:28.867" LastActivityDate="2022-11-04T19:02:28.867" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="9920" PostTypeId="2" ParentId="9621" CreationDate="2022-11-03T16:15:41.453" Score="3" Body="&lt;p&gt;&lt;em&gt;Need to scale magmom by number of valance electron&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.spacegroup import crystal&#xA;from ase.io import read&#xA;a = 4.05&#xA;al = crystal('Al', [(0, 0, 0)], spacegroup=225, cellpar=[a, a, a, 90, 90, 90])&#xA;al.write('al.cfg',format='cfg')&#xA;&#xA;#=========above are optional just to generate cfg file===============&#xA;&#xA;&#xA;system = read('al.cfg')&#xA;scale=3 # valance_electron of Al&#xA;&#xA;&#xA;&#xA;system.set_initial_magnetic_moments(magmoms=4*[3*scale])&#xA;input_data = {&#xA;      'calculation': 'vc-relax',&#xA;      'outdir': './out',&#xA;      'occupations': 'smearing',&#xA;      'degauss': 0.05,&#xA;      'ispin': 2,&#xA;      'tprnfor':True,&#xA;      'tstress':True,&#xA;      'smearing': 'gaussian'&#xA;  }&#xA;system.write('Al.in',format='espresso-in',input_data=input_data,pseudopotentials={'Al': 'Al.pbe-rrkjus.UPF'},kpts=(10, 10, 10))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;OUTPUT&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;   calculation      = 'vc-relax'&#xA;   tstress          = .true.&#xA;   tprnfor          = .true.&#xA;   outdir           = './out'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;   occupations      = 'smearing'&#xA;   degauss          = 0.05&#xA;   smearing         = 'gaussian'&#xA;   nspin            = 2&#xA;   starting_magnetization(1) = 3.0&#xA;   ntyp             = 1&#xA;   nat              = 4&#xA;   ibrav            = 0&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Al  26.981538 Al.pbe-rrkjus.UPF&#xA;&#xA;K_POINTS automatic&#xA;10 10 10  0 0 0&#xA;&#xA;CELL_PARAMETERS angstrom&#xA;4.05000000000000 0.00000000000000 0.00000000000000&#xA;0.00000000000000 4.05000000000000 0.00000000000000&#xA;0.00000000000000 0.00000000000000 4.05000000000000&#xA;&#xA;ATOMIC_POSITIONS angstrom&#xA;Al  0.0000000000 0.0000000000 0.0000000000&#xA;Al  0.0000000000 2.0250000000 2.0250000000&#xA;Al  2.0250000000 0.0000000000 2.0250000000&#xA;Al  2.0250000000 2.0250000000 0.0000000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-03T16:15:41.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9921" PostTypeId="2" ParentId="9860" CreationDate="2022-11-03T16:59:07.837" Score="2" Body="&lt;p&gt;My &lt;em&gt;guess&lt;/em&gt; is that electronic convergence (to the desired accuracy) has not been achieved in the first step.&lt;/p&gt;&#xA;&lt;p&gt;Looking at the &lt;code&gt;EDIFF&lt;/code&gt; setting from the VASP Wiki (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/EDIFF&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;), my impression is that the SCF terminates at the first instance when the energy difference is below &lt;code&gt;EDIFF = 1E-5&lt;/code&gt;, but it is not guaranteed that the next SCF iteration must have an energy difference below &lt;code&gt;EDIFF&lt;/code&gt; (&lt;em&gt;this is my understanding, but it would be good for someone more experienced / familiar with VASP's underlying code to weigh in&lt;/em&gt;).&lt;/p&gt;&#xA;&lt;p&gt;You didn't seem to have set &lt;code&gt;NELMIN&lt;/code&gt; (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/NELMIN&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;), so it takes the default value of &lt;code&gt;NELMIN = 2&lt;/code&gt;, which means that 2 SCF steps will be taken in each subsequent &amp;quot;geometry optimization&amp;quot; step (where the structure actually stays constant). But this means that the orbitals and charge density are likely to continue being optimized at each step, which also explains how you can see the &lt;code&gt;mag&lt;/code&gt; parameter getting converged over the fake &amp;quot;geometry optimization&amp;quot; steps.&lt;/p&gt;&#xA;&lt;p&gt;You could try doing a series of static calculations with &lt;code&gt;EDIFF = 1E-5&lt;/code&gt;, &lt;code&gt;EDIFF = 1E-6&lt;/code&gt;, &lt;code&gt;EDIFF = 1E-7&lt;/code&gt; and so on to check how the &lt;code&gt;E0&lt;/code&gt; and &lt;code&gt;mag&lt;/code&gt; values converge with respect to &lt;code&gt;EDIFF&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-11-03T16:59:07.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9922" PostTypeId="1" CreationDate="2022-11-03T21:13:26.383" Score="7" ViewCount="310" Body="&lt;p&gt;I copied my question to this community as the advice of a user on &lt;a href=&quot;https://physics.stackexchange.com/questions/735128/how-is-temperature-changes-implemented-in-a-molecular-dynamics-simulation&quot;&gt;Physics SE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;MD simulations are always associated with a temperature that represents the natural state of a system.&lt;/p&gt;&#xA;&lt;p&gt;However, some techniques, like Simulated Annealing Molecular Dynamics where temperature fluctuates up and down to allow the system to escape local minima, use a non-constant temperature.&lt;/p&gt;&#xA;&lt;p&gt;In such a case, how is this applied to the system?&lt;/p&gt;&#xA;&lt;p&gt;I found a very &lt;a href=&quot;https://physics.stackexchange.com/questions/432470/how-do-we-take-temperature-into-account-in-ab-initio-molecular-dynamics-simulati&quot;&gt;closely related question&lt;/a&gt;, but the answer goes beyond my knowledge. If I am looking at Langevin dynamics, is it accurate to say that the temperature is being applied primarily as an increase in particle acceleration?&lt;/p&gt;&#xA;" OwnerUserId="6226" LastActivityDate="2023-06-11T17:30:04.857" Title="How is temperature changes implemented in a molecular dynamics simulation?" Tags="|molecular-dynamics|atomistic-simulation|temperature|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9924" PostTypeId="1" CreationDate="2022-11-04T09:33:37.923" Score="11" ViewCount="579" Body="&lt;p&gt;I am new to DFT calculations and I would like to get the electronic and phonon band structures of FeSn (1 kagome layer and 1 Sn layer in between). My question is, is it absolutely necessary to first do a geometry optimisation before performing the electronic and phonon band structures? I will be using the density functional perturbation theory (DFPT) method to calculate the phonon dispersion. The code I shall be using is Elk.&lt;/p&gt;&#xA;" OwnerUserId="6120" LastActivityDate="2022-11-04T12:50:11.370" Title="Should one perform geometry optimisation before calculating electronic/phonon band structures via DFT?" Tags="|density-functional-theory|band-structure|electronic-structure|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9925" PostTypeId="2" ParentId="9924" CreationDate="2022-11-04T10:28:28.453" Score="9" Body="&lt;ol&gt;&#xA;&lt;li&gt;For the &lt;strong&gt;electronic band structure&lt;/strong&gt;, I'd say it's debatable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For consistency reasons, it would make sense for example to perform a geometry optimization with PBE and calculate its PBE band structure. So we'd be reporting the PBE band structure of a PBE optimized structure.&lt;/p&gt;&#xA;&lt;p&gt;On the flip side, it is common for people to do PBE geometry optimization and use a hybrid (HSE06 for example) for the band structure calculation, because doing a geometry optimization with a hybrid is very expensive. So, in this case we'd report a HSE06 band structure of a PBE optimized structure.&lt;/p&gt;&#xA;&lt;p&gt;Of course, the next relevant question is whether we can use an experimentally obtained structure that might not be the most stable configuration in our DFT calculations. I &lt;em&gt;have&lt;/em&gt; seen examples of this for experimental papers where DFT was used to give insight or corroborate the experimental results, but for purely computational studies I find that people usually relax the structures according to the level of DFT theory (LDA, GGA, hybrid, etc) and choice of parameters (k-point mesh, plane-wave cutoffs, etc). This is just my impression, so take it with a pinch of salt.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;For the &lt;strong&gt;phonon band structure&lt;/strong&gt;, I'd say it's necessary.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I think it is a technical requirement to perform the geometry optimization first if you're working in the harmonic approximation where you assume that you are at the bottom of a quadratically shaped basin (with respect to the ionic displacements) in the energy landscape. This is explained clearly by ProfM &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation?rq=1&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9325/stability-using-phonon-calculation&quot;&gt;here&lt;/a&gt;. This &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2107/6131&quot;&gt;discussion&lt;/a&gt; on how low the forces should be to converge phonon energies also seems useful for you to look at. I suspect that one might face convergence issues and &lt;em&gt;maybe&lt;/em&gt; artificial soft modes if the geometry optimization is not performed beforehand.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="6131" LastEditDate="2022-11-04T12:50:11.370" LastActivityDate="2022-11-04T12:50:11.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9926" PostTypeId="2" ParentId="9165" CreationDate="2022-11-04T19:45:29.253" Score="2" Body="&lt;p&gt;If you look at the paper, they cite the work of &lt;a href=&quot;https://doi.org/10.1088/0022-3719/5/9/006&quot; rel=&quot;nofollow noreferrer&quot;&gt;M. Saitoh in J. Phys. C: Solid State Phys. 5, 914 (1972)&lt;/a&gt; for the matrix element.&lt;/p&gt;&#xA;&lt;p&gt;Saitoh writes in Eqs 6 and 7&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ X_{j{\bf p},c{\bf k}} = \int {\rm d}^3 r \psi_{j{\bf p}}^* ({\bf r}) x \psi_{c{\bf k}}({\bf r}) = i\delta_{jc} \delta_{\bf pk} \frac {\partial} {\partial k_x} $$&lt;/span&gt;&#xA;which for sure is abuse of notation since the elements of &lt;span class=&quot;math-container&quot;&gt;${\bf X}$&lt;/span&gt; clearly should be scalars. However, Saitoh then proceeds to use the &lt;strong&gt;action of &lt;span class=&quot;math-container&quot;&gt;${\mathbf X}$&lt;/span&gt;&lt;/strong&gt; onto the eigenvalue equation in his Eq 5, and proceeds by integrating the resulting differential equation.&lt;/p&gt;&#xA;&lt;p&gt;You should thus not think of the elements of &lt;span class=&quot;math-container&quot;&gt;${\bf X}$&lt;/span&gt; as scalars, but as operators: &lt;span class=&quot;math-container&quot;&gt;${\bf X}$&lt;/span&gt; only makes sense when applied to a function, such as &lt;span class=&quot;math-container&quot;&gt;$\sum_{j p_x} X_{j{\bf p},c{\bf k}} A_j({\bf p})$&lt;/span&gt; in Saitoh's Eq 5 or &lt;span class=&quot;math-container&quot;&gt;$\sum_{n'} X_{nn'} C(n',k)$&lt;/span&gt; in Leo and McKinnon's article.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-04T19:45:29.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9929" PostTypeId="1" CreationDate="2022-11-06T02:32:44.737" Score="6" ViewCount="125" Body="&lt;p&gt;What are the best books on the use of machine learning in condensed matter, focusing on density functional theory and many-body physics?&lt;/p&gt;&#xA;" OwnerUserId="6232" LastEditorUserId="5" LastEditDate="2022-11-06T02:38:30.493" LastActivityDate="2022-11-06T02:38:30.493" Title="Books on machine learning and condensed matter?" Tags="|density-functional-theory|reference-request|machine-learning|many-body-physics|" AnswerCount="0" CommentCount="6" ClosedDate="2022-12-16T03:57:32.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="9930" PostTypeId="2" ParentId="9874" CreationDate="2022-11-06T11:16:03.833" Score="1" Body="&lt;p&gt;I'm not sure if freezing at the basis set level makes sense... However, you can make an MP2 calculation easier, by doing an active space approximation (freezing certain orbitals). You will need to have manual control going from the atomic orbitals to molecular orbitals.&lt;/p&gt;&#xA;&lt;p&gt;All you need to do is after the Hartree-Fock calculation, when you convert the atomic orbitals to molecular orbitals, you then need to make an active space approximation (find the core constant energy, arising from the occupied frozen orbs then remove them).&lt;/p&gt;&#xA;&lt;p&gt;I don't use NWChem, but PySCF will do let you do this. See (subsection Frozen orbitals):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pyscf.org/user/mp.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pyscf.org/user/mp.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'd just use this, as you won't have to reinvent the wheel then :)&lt;/p&gt;&#xA;" OwnerUserId="4349" LastEditorUserId="4349" LastEditDate="2022-11-06T12:03:39.473" LastActivityDate="2022-11-06T12:03:39.473" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9931" PostTypeId="1" CreationDate="2022-11-06T20:09:31.533" Score="4" ViewCount="319" Body="&lt;p&gt;I'm trying to do a geometry optimization of a paraquat molecule ontop of a goldbulk consisting of four layers. Two of those layers are fixed. The input file looks like the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%cpu=16-31&#xA;%mem=120GB&#xA;%chk=mychk.chk&#xA;#p opt b3lyp/genecp nosymm int=ultrafine&#xA;&#xA;title&#xA;&#xA;2 2&#xA;C 0 8.29256346 -1.77584455 6.71957144&#xA;N 0 7.01616228 -2.44803618 6.31406805&#xA;C 0 6.15166862 -2.90727492 7.26967799&#xA;C 0 4.99476528 -3.59917666 6.91326232&#xA;C 0 4.69746661 -3.83580056 5.55116288&#xA;C 0 5.61233204 -3.34791231 4.58370498&#xA;C 0 6.75906414 -2.66573184 4.98812963&#xA;H 0 7.49092507 -2.2999946 4.2781678&#xA;H 0 5.47355565 -3.52974232 3.52457489&#xA;C 0 3.50515803 -4.62098617 5.14441683&#xA;C 0 3.03689444 -5.6915301 5.93988213&#xA;C 0 1.95600465 -6.46277758 5.51155339&#xA;N 0 1.32757473 -6.19245305 4.32995917&#xA;C 0 1.76115824 -5.16728842 3.53542831&#xA;C 0 2.83888632 -4.37295286 3.92100924&#xA;H 0 3.13422947 -3.5616365 3.2653502&#xA;H 0 1.22991791 -5.00732082 2.60540607&#xA;C 0 0.21761679 -7.08683285 3.87327092&#xA;H 0 -0.45556376 -7.2893041 4.70953912&#xA;H 0 0.65539728 -8.02329804 3.50851655&#xA;H 0 -0.33886341 -6.59914796 3.0713439&#xA;H 0 1.59077204 -7.30783464 6.08188303&#xA;H 0 3.52243201 -5.9708836 6.86728718&#xA;H 0 4.33354916 -3.92830506 7.70670577&#xA;H 0 6.4066222 -2.70684036 8.30318156&#xA;H 0 8.55449396 -1.01492896 5.98161263&#xA;H 0 9.08581616 -2.52876751 6.77856604&#xA;H 0 8.16023712 -1.29869759 7.6923691&#xA;Au 0 -0.10658791 -0.106921953 -0.106690731&#xA;Au 0 1.962673477 -0.108146433 1.967644211&#xA;Au 0 -0.104312471 1.962824173 1.96310486&#xA;Au 0 1.962220846 1.968008833 -0.108468191&#xA;Au 0 4.029052369 -0.113085184 -0.113315722&#xA;Au 0 6.100413428 -0.107515425 1.963537211&#xA;Au 0 4.027379147 1.957131265 1.956852168&#xA;Au 0 6.100891806 1.96315078 -0.107153726&#xA;Au -1 -0.108432478 4.029817671 -0.106900538&#xA;Au -1 1.966063731 4.035475821 1.957133099&#xA;Au -1 -0.107699713 6.10022317 1.963471746&#xA;Au -1 1.96334103 6.105285747 -0.113099315&#xA;Au -1 4.031227295 4.025096026 -0.108559409&#xA;Au -1 6.096793033 4.030440023 1.962747495&#xA;Au -1 4.029966357 6.101404983 1.967749875&#xA;Au -1 6.099422231 6.100547277 -0.107291631&#xA;Au 0 -0.107736128 -0.107293668 4.029462667&#xA;Au 0 1.963383929 -0.112698271 6.105685109&#xA;Au 0 -0.108455559 1.963028094 6.099907542&#xA;Au 0 1.966151805 1.957296424 4.035602077&#xA;Au 0 4.030467415 -0.108378488 4.025383791&#xA;Au 0 6.099475812 -0.107691576 6.10027262&#xA;Au 0 4.030711294 1.968064547 6.101647758&#xA;Au 0 6.096755631 1.962292106 4.030192249&#xA;Au -1 -0.104246292 4.030229057 4.030157401&#xA;Au -1 1.962014634 4.025121721 6.101404005&#xA;Au -1 -0.107187056 6.10015712 6.09984544&#xA;Au -1 1.962631286 6.101182934 4.025368963&#xA;Au -1 4.0272297 4.035507714 4.035779287&#xA;Au -1 6.100784367 4.029654954 6.099793808&#xA;Au -1 4.029316571 6.105543384 6.105809512&#xA;Au -1 6.100357877 6.100269913 4.029261219&#xA;Au 0 8.173484232 -0.107257541 -0.106967104&#xA;Au 0 10.2426731 -0.10800139 1.967581809&#xA;Au 0 8.175595408 1.962573792 1.96288082&#xA;Au 0 10.24210072 1.96779256 -0.108506954&#xA;Au 0 12.30958154 -0.112865775 -0.113025501&#xA;Au 0 14.38050861 -0.107372838 1.963614389&#xA;Au 0 12.30746675 1.957538422 1.956915328&#xA;Au 0 14.38121226 1.963465707 -0.107028802&#xA;Au -1 8.171668329 4.029977538 -0.106926707&#xA;Au -1 10.24618233 4.035401227 1.957135362&#xA;Au -1 8.172682989 6.100220211 1.963118804&#xA;Au -1 10.24383858 6.105431827 -0.113127362&#xA;Au -1 12.31113776 4.025295034 -0.108490865&#xA;Au -1 14.37675695 4.030834106 1.962942431&#xA;Au -1 12.31055328 6.101381386 1.967741887&#xA;Au -1 14.37974656 6.100351584 -0.10715489&#xA;Au 0 8.17242271 -0.10720197 4.029906451&#xA;Au 0 10.24390116 -0.112721363 6.105757939&#xA;Au 0 8.172037308 1.962992304 6.099907521&#xA;Au 0 10.24624213 1.957509237 4.035546755&#xA;Au 0 12.31037637 -0.108185085 4.025464664&#xA;Au 0 14.37978242 -0.107527714 6.100084777&#xA;Au 0 12.31122283 1.968045494 6.10164273&#xA;Au 0 14.37665552 1.962356799 4.030403516&#xA;Au -1 8.175757467 4.030101225 4.029869405&#xA;Au -1 10.24244723 4.024991727 6.101675348&#xA;Au -1 8.173500953 6.100134157 6.099898359&#xA;Au -1 10.24296627 6.101136447 4.025207108&#xA;Au -1 12.30732913 4.035741234 4.036158699&#xA;Au -1 14.38111729 4.02949595 6.099999196&#xA;Au -1 12.30997416 6.105689433 6.105867222&#xA;Au -1 14.38049004 6.100330203 4.02933331&#xA;Au 0 -0.110675599 -0.10692626 8.173385353&#xA;Au 0 1.964395467 -0.110650578 10.23303171&#xA;Au 0 -0.105337606 1.962681536 10.24274555&#xA;Au 0 1.963576452 1.953386788 8.168981444&#xA;Au 0 4.033984919 -0.106497996 8.173258141&#xA;Au 0 6.098423867 -0.107472902 10.24226983&#xA;Au 0 4.027896284 1.963608742 10.24368626&#xA;Au 0 6.098687574 1.961927149 8.172900262&#xA;Au -1 -0.106356748 4.03031267 8.173012052&#xA;Au -1 1.965494778 4.029194988 10.2435807&#xA;Au -1 -0.10574068 6.100281467 10.24291691&#xA;Au -1 1.957977111 6.099463582 8.173302307&#xA;Au -1 4.029169465 4.039905504 8.168828641&#xA;Au -1 6.097972078 4.030047441 10.24315388&#xA;Au -1 4.02852714 6.103771506 10.23281613&#xA;Au -1 6.103955516 6.100017782 8.173392305&#xA;Au 0 -0.105742597 -0.107250925 12.31006325&#xA;Au 0 1.958219527 -0.106407399 14.37981901&#xA;Au 0 -0.106318609 1.962591757 14.37998728&#xA;Au 0 1.965496162 1.9640177 12.30950882&#xA;Au 0 4.028809863 -0.110936508 12.32041903&#xA;Au 0 6.103803063 -0.107126394 14.37978038&#xA;Au 0 4.029545447 1.952813846 14.38413203&#xA;Au 0 6.097946043 1.962549282 12.31025073&#xA;Au -1 -0.10541945 4.030493698 12.30990333&#xA;Au -1 1.9636217 4.039699677 14.38397381&#xA;Au -1 1.964152272 6.103690334 12.32002979&#xA;Au -1 4.027937847 4.029141231 12.309527&#xA;Au -1 6.099026591 4.03096867 14.38011203&#xA;Au -1 4.034166199 6.099507849 14.37986718&#xA;Au -1 6.098221034 6.100471253 12.31074101&#xA;Au 0 8.169303897 -0.107088897 8.172998013&#xA;Au 0 10.24429637 -0.110818714 10.23312609&#xA;Au 0 8.174763135 1.962539691 10.24305171&#xA;Au 0 10.24427889 1.953172282 8.169145352&#xA;Au 0 12.31443364 -0.106617427 8.173157632&#xA;Au 0 14.37859285 -0.107580526 10.24238667&#xA;Au 0 12.307872 1.963716285 10.24354675&#xA;Au 0 14.37890404 1.961905252 8.172955331&#xA;Au -1 8.174068129 4.030284854 8.173192708&#xA;Au -1 10.24565854 4.029153839 10.24360727&#xA;Au -1 8.174669921 6.100093377 10.24289344&#xA;Au -1 10.23886588 6.099407109 8.173367256&#xA;Au -1 12.30974664 4.040056972 8.168745349&#xA;Au -1 14.3778573 4.030393781 10.2427932&#xA;Au -1 12.30896384 6.103801617 10.23270602&#xA;Au -1 14.38430447 6.100160741 8.173368684&#xA;Au 0 8.174358566 -0.107334796 12.31025502&#xA;Au 0 10.23882241 -0.106481136 14.37989878&#xA;Au 0 8.17374741 1.962409134 14.38011457&#xA;Au 0 10.24562189 1.9638841 12.30971547&#xA;Au 0 12.30896575 -0.110907628 12.32012273&#xA;Au 0 14.38364416 -0.106773053 14.3794082&#xA;Au 0 12.30973836 1.953108318 14.38412088&#xA;Au 0 14.37794273 1.962847693 12.30988596&#xA;Au -1 8.174772567 4.030251307 12.31001218&#xA;Au -1 10.24368676 4.039594667 14.38402548&#xA;Au -1 8.169160822 6.100241203 14.3798991&#xA;Au -1 10.24475746 6.103654283 12.32021449&#xA;Au -1 12.30797253 4.029302002 12.3092692&#xA;Au -1 14.37912548 4.030811334 14.38014928&#xA;Au -1 12.31462635 6.099478716 14.38002931&#xA;Au -1 14.3785305 6.100462042 12.31074091&#xA;&#xA;H C N 0&#xA;def2TZVP&#xA;****&#xA;Au 0&#xA;LANL2DZ&#xA;****&#xA;&#xA;Au 0&#xA;LANL2DZ&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After 128 cycles the calculation terminated due to an error. The ending of the .log file looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Cycle 127  Pass 1  IDiag  1:&#xA; RMSU=  1.40D-06    CP:  1.00D+00 -2.25D+00 -2.73D-01  2.44D+00 -3.00D+00&#xA;                    CP:  7.55D-01&#xA; E= -17784.2869983765     Delta-E=       -0.000000032014 Rises=F Damp=F&#xA; DIIS: error= 6.70D-06 at cycle 127 NSaved=  14.&#xA; NSaved=14 IEnMin= 9 EnMin= -17784.2870124687     IErMin=14 ErrMin= 6.70D-06&#xA; ErrMax= 6.70D-06  0.00D+00 EMaxC= 1.00D-01 BMatC= 3.40D-07 BMatP= 2.30D-07&#xA; IDIUse=1 WtCom= 1.00D+00 WtEn= 0.00D+00&#xA; Large coefficients: NSaved= 14 BigCof=   13.54 CofMax=   10.00 Det=-3.94D-11&#xA; Inversion failed.  Reducing to 13 matrices.&#xA; Large coefficients: NSaved= 13 BigCof=   10.03 CofMax=   10.00 Det=-4.35D-11&#xA; Inversion failed.  Reducing to 12 matrices.&#xA; Coeff-Com:  0.166D+00 0.282D+00 0.433D+00 0.348D+00 0.160D+01 0.988D+00&#xA; Coeff-Com: -0.604D+01 0.266D+01 0.198D+00 0.131D+00 0.175D+00 0.573D-01&#xA; Coeff:      0.166D+00 0.282D+00 0.433D+00 0.348D+00 0.160D+01 0.988D+00&#xA; Coeff:     -0.604D+01 0.266D+01 0.198D+00 0.131D+00 0.175D+00 0.573D-01&#xA; Gap=     0.014 Goal=   None    Shift=    0.000&#xA; Gap=     0.016 Goal=   None    Shift=    0.000&#xA; RMSDP=1.23D-04 MaxDP=2.26D-02 DE=-3.20D-08 OVMax= 1.36D-02&#xA;&#xA; Cycle 128  Pass 1  IDiag  1:&#xA; RMSU=  9.96D-07    CP:  1.00D+00  4.61D-01  6.36D-01  5.27D-01 -1.83D+00&#xA;                    CP:  3.23D-01  7.69D-01&#xA; E= -17784.2870030630     Delta-E=       -0.000004686532 Rises=F Damp=F&#xA; DIIS: error= 7.00D-06 at cycle 128 NSaved=  13.&#xA; NSaved=13 IEnMin= 9 EnMin= -17784.2870124687     IErMin=12 ErrMin= 6.70D-06&#xA; ErrMax= 7.00D-06  0.00D+00 EMaxC= 1.00D-01 BMatC= 4.72D-07 BMatP= 2.30D-07&#xA; IDIUse=1 WtCom= 1.00D+00 WtEn= 0.00D+00&#xA; Large coefficients: NSaved= 13 BigCof=   10.76 CofMax=   10.00 Det=-5.44D-11&#xA; Inversion failed.  Reducing to 12 matrices.&#xA; Coeff-Com:  0.218D+00 0.291D+00 0.398D+00 0.325D+00 0.190D+01 0.117D+01&#xA; Coeff-Com: -0.702D+01 0.314D+01 0.194D+00 0.150D+00 0.986D-01 0.137D+00&#xA; Coeff:      0.218D+00 0.291D+00 0.398D+00 0.325D+00 0.190D+01 0.117D+01&#xA; Coeff:     -0.702D+01 0.314D+01 0.194D+00 0.150D+00 0.986D-01 0.137D+00&#xA; Gap=     0.014 Goal=   None    Shift=    0.000&#xA; Gap=     0.016 Goal=   None    Shift=    0.000&#xA; RMSDP=8.66D-06 MaxDP=1.38D-03 DE=-4.69D-06 OVMax= 9.27D-04&#xA;&#xA; &amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt; Convergence criterion not met.&#xA;SCF Done:  E(UB3LYP) =  -17784.2870031     A.U. after  129 cycles&#xA;            NFock=128  Conv=0.87D-05     -V/T= 3.9415&#xA; &amp;lt;Sx&amp;gt;= 0.0000 &amp;lt;Sy&amp;gt;= 0.0000 &amp;lt;Sz&amp;gt;= 0.5000 &amp;lt;S**2&amp;gt;= 1.7335 S= 0.9084&#xA; &amp;lt;L.S&amp;gt;=  0.00000000000    &#xA; KE= 6.045904443211D+03 PE=-4.699311015858D+05 EE= 2.294861147025D+05&#xA; Annihilation of the first spin contaminant:&#xA; S**2 before annihilation     1.7335,   after     0.7928&#xA; Convergence failure -- run terminated.&#xA; Error termination via Lnk1e in /opt/g16/l502.exe at Fri Nov  4 12:04:39 2022.&#xA; Job cpu time:     139 days 18 hours 50 minutes 34.0 seconds.&#xA; Elapsed time:       8 days 17 hours 44 minutes 29.2 seconds.&#xA; File lengths (MBytes):  RWF=  11366 Int=      0 D2E=      0 Chk=    334 Scr=      1&#xA;Error: segmentation violation&#xA;   rax 0000000000000000, rbx ffffffffffffffff, rcx 00002b90b86e5577&#xA;   rdx 000000000000ff77, rsp 00007fff42825978, rbp 00007fff42825ef0&#xA;   rsi 000000000000000b, rdi 000000000000ff77, r8  0000000000000020&#xA;   r9  0000000000000401, r10 000000007c998911, r11 0000000000000206&#xA;   r12 00007fff42825f38, r13 0000000000000000, r14 0000000000000000&#xA;   r15 00000000000003e6&#xA;  /lib64/libpthread.so.0(+0x11c00) [0x2b90b81a4c00]&#xA;  /lib64/libc.so.6(kill+0x7) [0x2b90b86e5577]&#xA;  /opt/g16/l502.exe() [0x4747c5]&#xA;  /opt/g16/l502.exe() [0x499bda]&#xA;  /opt/g16/l502.exe() [0x51679b]&#xA;  /opt/g16/l502.exe() [0x4f58bf]&#xA;  /opt/g16/l502.exe() [0x41df52]&#xA;  /opt/g16/l502.exe() [0x412b1b]&#xA;  /opt/g16/l502.exe() [0x412a24]&#xA;  /lib64/libc.so.6(__libc_start_main+0xf5) [0x2b90b86d0a35]&#xA;  /opt/g16/l502.exe() [0x40d169]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am now trying to restart the calculation at this point but can't seem to make it work. I tried different methods shown at this &lt;a href=&quot;https://gaussian.com/faq2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My header looked like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%cpu=16-31&#xA;%mem=120GB&#xA;%chk=mychk.chk&#xA;#p Opt=Restart b3lyp/genecp nosymm int=ultrafine&#xA;&#xA;title&#xA;&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%cpu=0-15&#xA;%mem=120GB&#xA;%oldchk=mychk.chk&#xA;%Chk=newchk.chk&#xA;#p opt b3lyp/genecp nosymm int=ultrafine Geom=(AllCheck,Step=128) Guess=Read&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;No matter what I try I'm getting an error looking like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;...&#xA; dumping /fiocom/, unit = 3 NFiles =     1 SizExt =    524288 WInBlk =       512&#xA;                   defal = F LstWrd =       65536 FType=2 FMxFil=10000&#xA;&#xA; Number              0&#xA; Base            40448&#xA; End             65536&#xA; End1            65536&#xA; Wr Pntr         40448&#xA; Rd Pntr         40448&#xA; Length          25088&#xA; Int.Num             1&#xA; FileIO operation on non-existent file.&#xA; FileIO: IOper= 2 IFilNo(1)=  -997 Len=          20 IPos=           0 Q=  140725376322144&#xA; Error termination in NtrErr:&#xA; NtrErr Called from FileIO.&#xA;Error: segmentation violation&#xA;   rax 0000000000000000, rbx 0000000006070a30, rcx 00002b18d0862577&#xA;   rdx 0000000000001437, rsp 00007ffd2e1105f8, rbp 00007ffd2e110630&#xA;   rsi 000000000000000b, rdi 0000000000001437, r8  0000000000000020&#xA;   r9  0000000000000401, r10 000000007c998911, r11 0000000000000202&#xA;   r12 00007ffd2e110a00, r13 00007ffd2e110968, r14 00007ffd2e110a60&#xA;   r15 000000000608d710&#xA;  /lib64/libpthread.so.0(+0x11c00) [0x2b18d0321c00]&#xA;  /lib64/libc.so.6(kill+0x7) [0x2b18d0862577]&#xA;  /opt/g16/l103.exe() [0x474e65]&#xA;  /opt/g16/l103.exe() [0x4f3f19]&#xA;  /opt/g16/l103.exe() [0x4a7625]&#xA;  /opt/g16/l103.exe() [0x53d1a8]&#xA;  /opt/g16/l103.exe() [0x53cc31]&#xA;  /opt/g16/l103.exe() [0x4928cf]&#xA;  /opt/g16/l103.exe() [0x4922ee]&#xA;  /opt/g16/l103.exe() [0x412c3b]&#xA;  /opt/g16/l103.exe() [0x4126a2]&#xA;  /opt/g16/l103.exe() [0x4125a4]&#xA;  /lib64/libc.so.6(__libc_start_main+0xf5) [0x2b18d084da35]&#xA;  /opt/g16/l103.exe() [0x40cce9]&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't understand what I am doing wrong and I would much appreciate any tips or input from the community.&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much in advance.&lt;/p&gt;&#xA;" OwnerUserId="5900" LastEditorUserId="5" LastEditDate="2022-11-06T22:17:45.243" LastActivityDate="2022-11-16T11:24:26.687" Title="Problems with restarting an optimization file in Gaussian" Tags="|gaussian|geometry|optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9932" PostTypeId="2" ParentId="8923" CreationDate="2022-11-06T23:54:49.873" Score="3" Body="&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/2107.11210&quot; rel=&quot;nofollow noreferrer&quot;&gt;In this paper&lt;/a&gt;, the authors discuss the following nonlinear current response under an electric field:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$j_a=\chi_{abc}^{int}E_bE_c \tag{1}$$&lt;/span&gt;&#xA;in which&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi_{abc}^{int}=\int \dfrac{d\vec{k}}{(2\pi)^d} \Lambda_{abc}(\vec{k}) \tag{2}$$&lt;/span&gt;&#xA;with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Lambda_{abc}=-\sum_n (\partial_a G_{bc}^n-\partial_b G_{ac}^n)f_0 \tag{3},$$&lt;/span&gt;&#xA;from which we see &lt;span class=&quot;math-container&quot;&gt;$\chi_{abc}^{int}$&lt;/span&gt; is a rank-3 anti-symmetric tensor.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/2209.15442&quot; rel=&quot;nofollow noreferrer&quot;&gt;In another paper&lt;/a&gt;, the authors generalize the response relation &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; to third-order (also driven by Berry curvature) and therefore a rank-4 anti-symmetric tensor is found.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2022-11-06T23:54:49.873" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9933" PostTypeId="1" CreationDate="2022-11-07T08:46:20.787" Score="3" ViewCount="35" Body="&lt;p&gt;I downloaded the &lt;a href=&quot;https://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI:2909&quot; rel=&quot;nofollow noreferrer&quot;&gt;SDF&lt;/a&gt; of atisine structure and imported it into my ChemDraw. From there, I basically made the skeleton of it (SMILES &lt;code&gt;C12C3(CCCC2CN4CCOC34)C5C6(CCC(CC6)C5)CC1&lt;/code&gt;) and exported it to a new SDF. The new SDF was opened with &lt;a href=&quot;https://openmolecules.org/datawarrior&quot; rel=&quot;nofollow noreferrer&quot;&gt;DataWarrior&lt;/a&gt; and I ran the conformer generator. Here is the result in ChemDraw.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/dfDpr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dfDpr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried to remove all hydrogens present using &lt;a href=&quot;https://chemaxon.com/products/marvin&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemAxon MarvinSketch&lt;/a&gt;. Here are the pictures of before and after the hydrogens removed. So far, it was working as expected.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mlgZX.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mlgZX.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Am6CL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Am6CL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, here we go, there are lots of CH2 labels here. I know these atoms are CH2 indeed and those are chemically correct but why it does have to be expanded while other CH2 atoms are remain hidden. Those shown CH2 should not appear though so I thought the MarvinSketch was not removed the hydrogens correctly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pOE4L.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pOE4L.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In another attempt, I tried to use &lt;a href=&quot;http://www.mayachemtools.org/Download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;MayaChemTools RDKitStandardizeMolecules.py&lt;/a&gt; and ran &lt;code&gt;./RDKitStandardizeMolecules.py --standardizeParams &amp;quot;cleanupRemoveHydrogens,yes&amp;quot; -i atisineminimal_mmff941.sdf -o atisineminimal_mmff941clean.sdf&lt;/code&gt; in Terminal. Here is the result in ChemDraw.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/MTrhD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MTrhD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think it is the fault of these MarvinSketch and RDKit because the DataWarrior-generated SDF doesn't make any CH2 labels, nor does the original and modified SDF of atisine.&lt;/p&gt;&#xA;&lt;p&gt;Anyone have a better way to remove these hydrogens without making those CH2?&lt;/p&gt;&#xA;" OwnerUserId="5771" LastEditorUserId="5771" LastEditDate="2022-11-07T09:08:34.987" LastActivityDate="2022-11-07T09:08:34.987" Title="After removed H atoms in MarvinSketch and MayaChemTools RDKitStandardizeMolecules.py, got lots of CH2 flags in ChemDraw" Tags="|cheminformatics|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-12T14:48:28.667" ContentLicense="CC BY-SA 4.0" />
  <row Id="9934" PostTypeId="1" CreationDate="2022-11-07T20:52:58.330" Score="5" ViewCount="359" Body="&lt;p&gt;I am a beginner in QE and I have a question. During I was reading about Output file, I saw a part where have it:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;The calculation goes on step by step until convergence is reached. Then we show all the energies of all bands (eigenvalues of the Kohn-Shan orbitals) for each k-point, the Fermi energy, the total energy, the contributions of all the terms to the total energy, and the calculation time used by each subroutine of the program.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;Output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;...&#xA;iteration #  9     ecut=   100.00 Ry     beta=0.70&#xA;Davidson diagonalization with overlap&#xA;ethr =  1.00E-13,  avg # of iterations =  1.0&#xA;&#xA;negative rho (up, down):  1.151E-06 0.000E+00&#xA;&#xA;total cpu time spent up to now is       28.4 secs&#xA;&#xA;End of self-consistent calculation&#xA;&#xA;     k = 0.0000 0.0000 0.0000 (  3909 PWs)   bands (ev):&#xA;&#xA;-17.8569  -5.9595  -1.3957  -1.3957   4.4242   9.2594   9.9561   9.9561&#xA;&#xA;     k = 0.0000 0.0550 0.0000 (  3909 PWs)   bands (ev):&#xA;&#xA;-17.8034  -5.8955  -1.6155  -1.5115   4.4968   9.3266   9.9837  10.1886&#xA;...&#xA;-10.9411 -10.9411  -8.9101   1.6562   1.6562  12.4084  14.2298  14.2298&#xA;&#xA;the Fermi energy is     1.6562 ev&#xA;&#xA;!    total energy              =     -22.80493136 Ry&#xA;Harris-Foulkes estimate   =     -22.80493136 Ry&#xA;estimated scf accuracy    &amp;lt;          1.5E-15 Ry&#xA;&#xA;The total energy is the sum of the following terms:&#xA;&#xA;one-electron contribution =     -44.02527202 Ry&#xA;hartree contribution      =      24.36506286 Ry&#xA;xc contribution           =      -6.99363523 Ry&#xA;ewald contribution        =       3.85762303 Ry&#xA;Dispersion Correction     =      -0.00870488 Ry&#xA;smearing contrib. (-TS)   =      -0.00000512 Ry&#xA;&#xA;convergence has been achieved in   9 iterations&#xA;&#xA;Writing output data file grafeno.save&#xA;&#xA;init_run     :      2.26s CPU      2.29s WALL (       1 calls)&#xA;electrons    :     20.10s CPU     20.24s WALL (       1 calls)&#xA;&#xA;...&#xA;&#xA;Parallel routines&#xA;fft_scatter  :      4.35s CPU      4.44s WALL (   23020 calls)&#xA;&#xA;PWSCF        :    28.46s CPU        28.70s WALL&#xA;&#xA;&#xA;This run was terminated on:  11:51: 0   5Sep2017            &#xA;&#xA;=------------------------------------------------------------------------------=&#xA;JOB DONE.&#xA;=------------------------------------------------------------------------------=&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5" LastEditDate="2022-11-07T21:09:26.253" LastActivityDate="2022-11-08T11:38:11.647" Title="What does &quot;The calculation has reached convergence&quot; mean in Quantum ESPRESSO?" Tags="|quantum-espresso|self-consistent-field|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9935" PostTypeId="1" CreationDate="2022-11-08T08:31:06.457" Score="3" ViewCount="47" Body="&lt;p&gt;I want to optimize an enzyme with a metal ion bound to the active site of the enzyme.&#xA;Using PyMOL software I placed the metal ion in the active site of the enzyme and the metal-enzyme structure was used for the optimization using gaussian 09.&#xA;I tried to optimize the structure in the ground state with DFT (B3LYP) method and 6-31G (d) basis set.&lt;/p&gt;&#xA;&lt;p&gt;When I start the optimization, first get an out-of-memory error and I continue the optimization with the suggestion given &lt;code&gt;Use %mem=1050MW&lt;/code&gt; to provide the minimum amount of memory required to complete this step.&#xA;However, the next problem is the process terminates without mentioning the error specifically.&#xA;The final lines printed in the process are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; H(PDBName=1H,ResName=HOH,ResNum=486_A) 0    -15.62485  -15.07272  -38.775   L &#xA; H(PDBName=2H,ResName=HOH,ResNum=486_A) 0    -15.71863  -16.63759  -38.775   L &#xA; H(PDBName=1H,ResName=HOH,ResNum=487_A) 0    -28.25085  -22.36872  -12.833   L &#xA; H(PDBName=2H,ResName=HOH,ResNum=487_A) 0    -28.34463  -23.93359  -12.833   L &#xA; H(PDBName=1H,ResName=HOH,ResNum=488_A) 0    -31.65985  -20.74372  -10.48    L &#xA; H(PDBName=2H,ResName=HOH,ResNum=488_A) 0    -31.75363  -22.30859  -10.48    L &#xA; H(PDBName=1H,ResName=HOH,ResNum=489_A) 0    -30.88785  -21.47372  -13.087   L &#xA; H(PDBName=2H,ResName=HOH,ResNum=489_A) 0    -30.98163  -23.03859  -13.087   L&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone please help me to solve this?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="210" LastEditDate="2022-11-08T12:00:17.567" LastActivityDate="2022-11-08T12:00:17.567" Title="Gaussian calculation error when optimizing an enzyme bound with a metal ion?" Tags="|gaussian|optimization|" AnswerCount="0" CommentCount="1" ClosedDate="2023-05-28T16:17:08.577" ContentLicense="CC BY-SA 4.0" />
  <row Id="9936" PostTypeId="2" ParentId="9934" CreationDate="2022-11-08T11:38:11.647" Score="5" Body="&lt;p&gt;Let suppose that you want to do a geometry optimization. You need a criterion to said &amp;quot;the geometry is optimized&amp;quot;. When the structure geometry is optimized, it will be in a local minimum of the potential energy surface. In such point the forces are zero over all the atoms. Due to precision and numerical errors, it will be very difficult to attain zero forces for all atoms. Instead, the user set up a threshold value &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;: if the forces are below such value, then the geometry optimization is said to converge. But depending on how low &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; is, this process can take a lot of time (or even forever) so, you need to define a maximum value of steps (iterations) to be run.&lt;/p&gt;&#xA;&lt;p&gt;In case of Self Consistent Field (SCF) methods, the electrons are &amp;quot;moved&amp;quot;, and the system energy is calculated. In this case the criterion (normally) used is also defining a threshold value &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; but instead for the energy, it is used for the difference between two consecutive energies values, i.e. &lt;span class=&quot;math-container&quot;&gt;$E_n-E_{n-1}$&lt;/span&gt;. If after &amp;quot;moving&amp;quot; all the electrons, &lt;span class=&quot;math-container&quot;&gt;$E_n-E_{n-1}&amp;lt;\epsilon$&lt;/span&gt;, it is said that the system converged. Here again, we need to define the maximum steps allowed.&lt;/p&gt;&#xA;&lt;p&gt;In Molecular Mechanics (including Molecular Mechanics), only the first type of convergence is used. When working with &lt;em&gt;ab initio&lt;/em&gt;, DFT or semiempirical methods, both type of convergence test are used.&lt;/p&gt;&#xA;&lt;p&gt;At the end, your calculations stop because:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;attained the maximum number of steps: this is bad.&lt;/li&gt;&#xA;&lt;li&gt;attained the convergence criteria: this is good.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note 1: the values of &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; strongly depends on what type of calculations you need to run and the type of your system. My recommendations is to look at the literature for inspiration.&lt;br /&gt;&#xA;Note 2: In general, you will need both convergence: forces and energies, but you can run a calculation for optimizing the geometry first, and then use the optimized geometry to run all the other calculations (as single point calculations).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-11-08T11:38:11.647" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9937" PostTypeId="1" CreationDate="2022-11-08T14:28:13.637" Score="7" ViewCount="569" Body="&lt;p&gt;Given the SMILES of my molecule, how can I get a weighted adjacency matrix where the weights are the bond lengths, using the Rdkit package and Python?&lt;/p&gt;&#xA;" OwnerUserId="6241" LastEditorUserId="5" LastEditDate="2022-11-09T03:26:22.687" LastActivityDate="2023-02-02T14:41:20.967" Title="Rdkit: How can I get a weighted adjacency matrix where the weights are bond lengths, from the SMILES of my molecule?" Tags="|molecular-modeling|python|rdkit|smiles|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9938" PostTypeId="1" CreationDate="2022-11-09T04:47:27.110" Score="2" ViewCount="429" Body="&lt;p&gt;I might be missing something obvious, but I am unable to find the option to download the primitive unit cell from the new materials project website.&#xA;All the options given by the export button give the conventional cell only.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ovNuU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ovNuU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is the option to download primitive unit cell still available, or has it been removed completely?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2023-05-28T04:29:12.943" Title="How to obtain the primitive unit cell from the new materials project website?" Tags="|materials-project|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="9939" PostTypeId="1" AcceptedAnswerId="9946" CreationDate="2022-11-09T09:56:53.330" Score="8" ViewCount="496" Body="&lt;p&gt;I have a question concerning the screened Coulomb interaction in periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;Many first-principle DFT codes provide the possibility to compute linear response functions, such as the irreducible polarisability &lt;span class=&quot;math-container&quot;&gt;$\chi(\mathbf{q}, \mathbf{G}, \mathbf{G'})$&lt;/span&gt; or a related quantity to the latter - the dielectric function &lt;span class=&quot;math-container&quot;&gt;$\epsilon^{-1}(\mathbf{q}, \mathbf{G}, \mathbf{G'}) = \delta_{\mathbf{G}, \mathbf{G'}} - v(\mathbf{q}, \mathbf{G})\chi(\mathbf{q}, \mathbf{G}, \mathbf{G'})$&lt;/span&gt; - which contains the bare Coulomb potential &lt;span class=&quot;math-container&quot;&gt;$v(\mathbf{q}, \mathbf{G})$&lt;/span&gt;. With help of the dielectric function the screened Coulomb interaction can be constructed as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\small W(\mathbf{q}, \mathbf{G}, \mathbf{G'}) = \epsilon^{-1}(\mathbf{q}, \mathbf{G}, \mathbf{G'}) v(\mathbf{q}, \mathbf{G}) = \left[\delta_{\mathbf{G}, \mathbf{G'}} -  v(\mathbf{q}, \mathbf{G}) \chi(\mathbf{q}, \mathbf{G}, \mathbf{G'}) \right] v(\mathbf{q}, \mathbf{G}') ~ . \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the end I want to use this Coulomb potential expressed in reciprocal space to evaluate real-space integrals of the form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle i j |W(\mathbf{r}, \mathbf{r}')| \alpha \beta\rangle \quad , \tag{1.5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$W(\mathbf{r}, \mathbf{r}')$&lt;/span&gt; is expressed by its Fourier transform and &lt;span class=&quot;math-container&quot;&gt;$i,j,\alpha,\beta$&lt;/span&gt; are single-particle wave functions.&#xA;Looking into several forums and theory sections of plane-wave base DFT codes I found &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/bse/bse.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; transformation, namely the equations&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{|\mathbf{r}- \mathbf{r}'|} = \frac{1}{\Omega} \sum_\limits{\mathbf{q}, \mathbf{G}} \frac{4 \pi}{|\mathbf{q}+\mathbf{G}|^2} e^{i(\mathbf{q}+\mathbf{G})\cdot(\mathbf{r}-\mathbf{r}')} \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\small \int \mathrm{d}\mathbf{r}'' \frac{\epsilon^{-1}(\mathbf{r}, \mathbf{r}'')}{|\mathbf{r}'' - \mathbf{r}'|} = \frac{1}{\Omega} \sum_\limits{\mathbf{q}, \mathbf{G}, \mathbf{G}'} e^{i(\mathbf{q}+\mathbf{G}) \cdot \mathbf{r}} \frac{4 \pi \epsilon^{-1} (\mathbf{q}, \mathbf{G}, \mathbf{G}')}{|\mathbf{q} + \mathbf{G}|^2} e^{-i(\mathbf{q}+\mathbf{G}')\cdot \mathbf{r}'} ~ . \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first equation seems reasonable, if you consider periodic boundary conditions and then express the potential in terms of a Fourier series. I am having trouble arriving at the expression of the second equation. It looks like the convolution theorem of the Fourier transformation is needed, but I could not manage to prove the identity.&lt;/p&gt;&#xA;&lt;p&gt;Maybe someone could provide a detailed derivation on how to end up on the RHS of the last stated equation.&lt;/p&gt;&#xA;" OwnerUserId="2088" LastEditorUserId="1484" LastEditDate="2022-11-12T11:26:15.073" LastActivityDate="2023-06-15T10:45:35.377" Title="Screened Coulomb interaction and its direct Fourier transform" Tags="|density-functional-theory|condensed-matter|solid-state-physics|periodic-system|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9940" PostTypeId="1" CreationDate="2022-11-09T12:42:24.617" Score="3" ViewCount="147" Body="&lt;p&gt;I want to calculate the proton affinities for each atom of my molecule using DFT in gaussian.&#xA;For a conjugated organic system that contains an heteroatome one or more...etc composed of about 20 atoms in a ch2cl2 solvent.&#xA;Is it something to do with thermochemistry for example enthalpies values . Or is there a way to obtain the values of affinities directly from a keyword in gaussian&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5563" LastEditDate="2022-11-09T16:24:14.570" LastActivityDate="2022-11-09T16:24:14.570" Title="How to calculate proton affinities for each atom in a molecule using DFT in gaussian?" Tags="|density-functional-theory|gaussian|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-28T16:16:34.067" ContentLicense="CC BY-SA 4.0" />
  <row Id="9941" PostTypeId="1" CreationDate="2022-11-09T21:40:15.890" Score="5" ViewCount="123" Body="&lt;p&gt;I have calculated the charge densities (in 1D, 2D and 3D formats) with the help of Quantum Espresso DFT.&lt;/p&gt;&#xA;&lt;p&gt;The system (/material) is simple, two atoms in an unit cell.&lt;/p&gt;&#xA;&lt;p&gt;However, I want to determine the number of electrons (in the interstitial position between the two atoms). Is there any python code with numerical approximation methods anyone can guide? It would be great to get your detailed suggestion.&lt;/p&gt;&#xA;&lt;p&gt;For example, the following image is for the charge densities (in atomic units) of that material under different conditions. I need to know the number of electrons near the region 2 alat (where there is interstitial bumps), which is in between two atoms (two black dotted vertical lines), one reference atom and it's nearest neighbor atom. The image is plotted from an 1D data set of charge density vs distance for different structures.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9kZaK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9kZaK.png&quot; alt=&quot;This is from the 1D charge density data&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;More information (optional):&lt;/p&gt;&#xA;&lt;p&gt;Lattice constant (for one structure): 4.5 Bohr&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Ref. atom   x   y   z&#xA;&#xA;alat    0.375   0.125   0.625&#xA;&#xA;Bohr    1.6875  0.5625  2.8125&#xA;&#xA;Angstrom    0.89298619  0.297662    1.48831031&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Nearest neighbor atom&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;alat    0.625   0.875   0.375&#xA;&#xA;Bohr    2.8125  3.9375  1.6875&#xA;&#xA;Angstrom  1.48831031    2.083634    0.89298619&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The interstitial position might be considered maybe halfway between the two atoms (I am not sure though).&lt;/p&gt;&#xA;&lt;p&gt;Here is the 3D charge density file for same structure (for which the lattice constant is given above): &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/10048/si_psuedo.code&quot; rel=&quot;nofollow noreferrer&quot;&gt;3D cube file&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The total charge (number of electrons) can be calculated from here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import numpy as np&#xA;import sys&#xA;&#xA;class CHD():&#xA;  def __init__(self):&#xA;    #This simply allocates the different data structures we need:&#xA;    self.natoms = 0&#xA;    self.grid = np.zeros(0)&#xA;    self.v = np.zeros([3,3])&#xA;    self.N = np.zeros([3])&#xA;    self.dV = 0&#xA;&#xA;  def set_dV(self):&#xA;    #The charge density is stored per volume. If we want to integrate the charge density&#xA;    #we need to know the size of the differential volume &#xA;    self.dV = 0&#xA;    x = self.v[:,0]&#xA;    y = self.v[:,1]&#xA;    z = self.v[:,2]&#xA;    self.dV = np.dot(x,np.cross(y,z))&#xA;&#xA;  def integrate(self):&#xA;    #This allows us to integrate the stored charge density&#xA;    return(np.sum(self.grid)*self.dV)&#xA; &#xA;#The following function reads the charge density from a cube file &#xA;def read(cubefile):&#xA;  density = CHD()&#xA;  f = open(cubefile,'r')&#xA;  #skip two header lines&#xA;  next(f)&#xA;  next(f)&#xA;  line = next(f)&#xA;  #Get the number of atoms if we want to store it&#xA;  density.natoms = int(line.split()[0])&#xA;  #This gets the nx,ny,nz info of the charge density&#xA;  #As well as the differential volume&#xA;  for i in range(0,3):&#xA;    line = next(f).split()&#xA;    density.N[i] = int(line[0])&#xA;    for j in range(1,4):&#xA;      density.v[i][j-1] = float(line[j])&#xA;&#xA;  #As of now we dont care about the positions of the atoms,&#xA;  #But if you did you could read them here:&#xA;  for i in range(0,density.natoms):&#xA;    next(f)&#xA;&#xA;  density.set_dV()&#xA;  density.grid = np.zeros(int(density.N[0]*density.N[1]*density.N[2]))&#xA;&#xA;  #This reads the data into a 1D array of size nx*ny*nz&#xA;  count = 0&#xA;  for i in f:&#xA;    for j in i.split():&#xA;      density.grid[count] = float(j)&#xA;      count+=1&#xA;  f.close()&#xA;  &#xA;  return density&#xA;&#xA;if __name__ == &amp;quot;__main__&amp;quot;:&#xA;  if len(sys.argv) != 2:&#xA;    print(&amp;quot;Incorrect number of arguments, run as ./ChargeDensity.py CUBEFILELOCATION&amp;quot;)&#xA;    sys.exit(6)&#xA;  density = read(sys.argv[1])  &#xA;  #For the main function I care about the total number of electrons&#xA;  print(density.integrate())&#xA;# Code source (from Dr. Levi): https://github.com/levilentz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This python code runs as (and gives output as 24, which is the total charge of the unit cell):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python ChargeDensity.py si_pseudo.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So again, we need to modify the python code in a way so that it can determine the interstitial charge from the 3D cube file of charge density. Hope to get your cordial cooperation.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5723" LastEditDate="2022-12-15T05:31:46.430" LastActivityDate="2022-12-15T05:33:08.507" Title="How to calculate the number of interstital electrons from Quantum Espresso charge density outputs?" Tags="|density-functional-theory|quantum-espresso|quantum-chemistry|charge-density|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-09T22:53:59.263" ContentLicense="CC BY-SA 4.0" />
  <row Id="9943" PostTypeId="1" CreationDate="2022-11-10T08:47:00.180" Score="7" ViewCount="327" Body="&lt;p&gt;I have some directories, named ‘abc-000, abc-001, abc-002, …… abc-100’. The path of the directory can be, for example, \home\abc-000 and so on.&lt;/p&gt;&#xA;&lt;p&gt;Inside each directory, there is a file named ‘OUTCAR’. The ‘OUTCAR’ file consists of many lines including the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GAdy2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GAdy2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;It's noted that, this paragraph appears 5 times with same headings (but with different values) in the same 'OUTCAR' file, and we need to extract data from the final (last) paragraph only.&lt;/p&gt;&#xA;&lt;p&gt;Now, the 9 elements of the stress matrix can be represented by the following symbols:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gSVUu.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gSVUu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I need to use a python or bash code that will read each of those ‘OUTCAR’ files, and then it will save the data from those ‘OUTCAR’ files in one single text or excel file (named: stress.txt or stress.xlsx) in the following way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;abc-000    ii  ij   ik  ji  jj   jk   ki  kj   kk   ForceTotal    StressTotal&#xA;&#xA;abc-001    ii  ij   ik  ji  jj   jk   ki  kj   kk   ForceTotal    StressTotal&#xA;…………………………………………………….…………………………………………………………………………………………….……………………………………………………&#xA;…………………………………………………….…………………………………………………………………………………………….……………………………………………………&#xA;abc-100    ii  ij   ik  ji  jj   jk   ki  kj   kk   ForceTotal    StressTotal&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;As I am new in coding, can anyone please suggest me how to do it? Any kind of help is greatly appreciated.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;View and/or download link of the OUTCAR file: &lt;a href=&quot;https://ucmerced.box.com/s/25ezagedhi9sisckjqhsa2rk7uyik0lc&quot; rel=&quot;nofollow noreferrer&quot;&gt;click here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5723" LastEditDate="2022-11-10T19:00:31.663" LastActivityDate="2023-01-08T23:58:39.360" Title="Extracting data from a file, using python or bash. Requesting help" Tags="|density-functional-theory|vasp|python|programming|vaspkit|" AnswerCount="3" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="9944" PostTypeId="1" AcceptedAnswerId="9945" CreationDate="2022-11-10T10:48:03.117" Score="11" ViewCount="422" Body="&lt;p&gt;I am at the beginning of computational materials modeling.&#xA;My objective is to calculate the electrical conductivity of a system that consists of several thousand atoms, and running DFT calculations is not an option due to the lack of computational resources.&lt;/p&gt;&#xA;&lt;p&gt;Therefore,&#xA;I want to construct electronic band structures using the tight-binding model and then calculate the electrical conductivity.&#xA;I have tried by PYBINDING package, however, it did not work for 3D materials.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;RuntimeError: 3D Brillouin zones are not currently supported.&lt;/li&gt;&#xA;&lt;li&gt;Pybinding has no option to specify the atom type.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I want to know freely available software packages to build the electronic band structure of solids using the tight-binding model.&lt;/p&gt;&#xA;&lt;p&gt;It will be a great starting point If an introductory reference is mentioned related to the tight-binding modeling of materials.&#xA;Thank You in advance.&lt;/p&gt;&#xA;" OwnerUserId="6198" LastEditorUserId="5" LastEditDate="2022-11-11T01:20:00.353" LastActivityDate="2023-12-19T12:53:14.120" Title="Software recommendations to construct band structures using tight binding" Tags="|band-structure|software-recommendations|physical-properties-of-materials|tight-binding|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9945" PostTypeId="2" ParentId="9944" CreationDate="2022-11-10T11:29:10.353" Score="9" Body="&lt;p&gt;The &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt; package can do exactly what you need. It should be easily extendible if you need some routines not implemented.&lt;/p&gt;&#xA;&lt;p&gt;There is also some tutorials, which has a focus on transport using the NEGF method, but one needs not focus on that: &lt;a href=&quot;https://github.com/zerothi/ts-tbt-sisl-tutorial&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/zerothi/ts-tbt-sisl-tutorial&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a quick reference see &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9147/tools-for-working-with-tight-binding-models/9467#9467&quot;&gt;Tools for working with tight-binding models&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;sisl&lt;/code&gt; package has a set of default geometries implemented in the &lt;code&gt;sisl.geom&lt;/code&gt; sub-package.&lt;/p&gt;&#xA;&lt;p&gt;So when creating the graphene geometry (&lt;code&gt;graphene = sisl.geom.graphene()&lt;/code&gt;) that method already has everything, 1) lattice parameters, 2) atomic species and 3) the periodicities of the geometry.&lt;br /&gt;&#xA;On the other hand one can manually define the geometries:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;bond = 1.42&#xA;lattice = sisl.Lattice([[1.5 * bond, -3**0.5 / 2 * bond, 0],&#xA;                            [1.5 * bond, 3**0.5 / 2 * bond, 0],&#xA;                            [0, 0, 100]], nsc=[3, 3, 1])&#xA;# nsc is the number of supercell connections (periodicities)&#xA;geometry = sisl.Geometry([[0, 0, 0], [bond, 0, 0]], &amp;quot;C&amp;quot;, lattice=lattice)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above is almost the same as what the default graphene lattice looks like. So you are free to do your own geometries if needed.&lt;/p&gt;&#xA;&lt;p&gt;For 3D geometries, you simply define your own lattice vectors, and/or use the built-in geometries, say &lt;code&gt;fcc&lt;/code&gt;, &lt;code&gt;bcc&lt;/code&gt;, etc.&lt;/p&gt;&#xA;&lt;p&gt;I refrain from adding a longer answer since this might be duplicated by the above referenced question.&lt;/p&gt;&#xA;&lt;p&gt;Disclaimer: I am the author of sisl&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-12-19T12:53:14.120" LastActivityDate="2023-12-19T12:53:14.120" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9946" PostTypeId="2" ParentId="9939" CreationDate="2022-11-10T14:14:27.313" Score="5" Body="&lt;p&gt;The following is not mathematical rigorous. Most importantly, I want to stress that it is hard to make precise statements without knowing the conventions and definitions of the source (which doesn't put them after all). So the following might not be coherent with the computations done in the source and I indeed obtain a different result for the screened interaction, see also the brief discussion at the end of this answer.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;We put our system in a box &lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt; with volume &lt;span class=&quot;math-container&quot;&gt;$|\Lambda|:=\mathrm{Vol}(\Lambda)$&lt;/span&gt; and employ periodic boundary conditions. If &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; denotes a function of two variables, then we can construct a new &lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt;-periodic (in each argument) function by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$f_\Lambda(x,x^\prime):=\sum\limits_{kk^\prime}e^{ikx}\, e^{ik^\prime x^\prime}\, \hat{f}_\Lambda(k,k^\prime) \quad , \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the Fourier coefficients for a function of two variables are defined as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat f_{\Lambda}(k,k^\prime) := \frac{1}{|\Lambda|^2}\, \int\limits_{\Lambda\times \Lambda}\mathrm dx\,\mathrm dx^\prime e^{-ikx}\, e^{-ik^\prime x^\prime} \,f(x,x^\prime) \tag{2} \quad .$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a function of a single variables, we make obvious changes in &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; and the corresponding coefficients are defined with one integration and one inverse volume factor less. The summation in &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; runs over all wave vectors respecting the periodicity conditions.&lt;/p&gt;&#xA;&lt;p&gt;To proceed, given a &lt;span class=&quot;math-container&quot;&gt;$\Lambda$&lt;/span&gt;-periodic function &lt;span class=&quot;math-container&quot;&gt;$f_\Lambda:\mathbb R^3\longrightarrow \mathbb R$&lt;/span&gt;, we can define another function &lt;span class=&quot;math-container&quot;&gt;$h_\Lambda:\mathbb R^3\times \mathbb R^3 \longrightarrow  \mathbb R$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$h_\Lambda(x,y) :=f_\Lambda(x-y)$&lt;/span&gt;. It holds that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat h_\Lambda(k,k^\prime) = \delta_{k+k^\prime,0}\, \hat f_\Lambda(k) \tag{3} \quad . $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can apply this to the Fourier expansion of the periodic Coulomb potential &lt;span class=&quot;math-container&quot;&gt;$V=1/|\cdot|$&lt;/span&gt;, yielding (by a mild abuse of notation)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{|x-x^\prime|} = \sum\limits_{k} e^{ik(x-x^\prime)}\, \hat V_\Lambda(k)  \quad . \tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The authors now, I assume, replaced the integration in equation &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; with the integration over the whole space; put differently, they've replaced the coefficient in the Fourier series with the Fourier transform (modulo some volume factor(s)). This is for example discussed/used/explained in Ref. 1-3. Doing so readily yields&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{|x-x^\prime|} = \frac{1}{|\Lambda|}\sum\limits_{k}e^{ik(x-x^\prime)}\, \frac{4\pi}{|k|^2} \quad ,\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which coincides with equation &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; of the question if we write &lt;span class=&quot;math-container&quot;&gt;$k=q+G$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; form the first Brillouin zone and &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; a reciprocal lattice vector. We've defined the (d-dimensional) Fourier transform of a function of two variables as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \hat f(k)=\mathcal F(f)(k,k^\prime) := \int\mathrm{d}x\,\mathrm dx^\prime \, e^{-ikx}\,e^{-ik^\prime x^\prime}f(x,x^\prime) \quad  .\tag{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For a function of a single variable we make appropriate changes.&lt;/p&gt;&#xA;&lt;p&gt;Let met stress once more that equation &lt;span class=&quot;math-container&quot;&gt;$(4)$&lt;/span&gt; is &lt;em&gt;not&lt;/em&gt; the Coulomb potential; both functions agree only if &lt;span class=&quot;math-container&quot;&gt;$x-x^\prime \in \Lambda$&lt;/span&gt;. Moreover, equation &lt;span class=&quot;math-container&quot;&gt;$(5)$&lt;/span&gt; is not the Fourier series of the corresponding periodic potential. In the thermodynamic limit, however, these replacements are justified, cf. Ref 1-3.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The second example, the screened interaction denoted here as &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;, is a bit more complicated and we have to make further assumptions. First, we assume that &lt;span class=&quot;math-container&quot;&gt;$\epsilon^{-1}(x,x^\prime) = \epsilon^{-1} (x+L,x^\prime+L)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is any direct lattice vector, cf. Ref 4. We conclude from this (exercise) that the Fourier transform &lt;span class=&quot;math-container&quot;&gt;$\hat \epsilon^{-1}(k,k^\prime)$&lt;/span&gt; vanishes if &lt;span class=&quot;math-container&quot;&gt;$k+k^\prime\neq G^\prime$&lt;/span&gt; for some reciprocal lattice vector &lt;span class=&quot;math-container&quot;&gt;$G^\prime$&lt;/span&gt;. Second, I think that the source defined the Fourier transform differently compared to our equation &lt;span class=&quot;math-container&quot;&gt;$(6)$&lt;/span&gt;, namely as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tilde\epsilon^{-1}(k,k^\prime):=\int\mathrm dx\mathrm \, dx^\prime\, e^{-ikx}\, e^{+ik^\prime x^\prime } \epsilon^{-1}(x,x^\prime) = \hat\epsilon^{-1}(k,-k^\prime) ~ ,\tag{6.5} $$&lt;/span&gt;&#xA;see again e.g. Ref. 4.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;With these things in mind, we can proceed. The strategy is the very same as above and we again replace the coefficient in the Fourier series by the Fourier transform (up to the volume factors). To this end, we compute the Fourier transform of the considered function &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; by making use of the  shift-property of the Fourier transform:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}{\small \mathcal F(W)(k,k^\prime) }&amp;amp;= \small{\int \mathrm dx\,e^{-ikx}\,\int\mathrm dx^{\prime\prime}\,\epsilon^{-1}(x,x^{\prime\prime}) \underbrace{\int\mathrm dx^\prime \,e^{-ik^\prime x^\prime}\, \frac{1}{|x^\prime-x^{\prime \prime}|}}_{=\mathcal F(1/|\cdot|)(k^\prime) \, e^{-ik^\prime x^{\prime\prime}}} \tag{7}}\\&#xA;&amp;amp;= \frac{4\pi}{|k^\prime|^2}\,\int \mathrm dx\,e^{-ikx}\,\int\mathrm dx^{\prime\prime}\,\epsilon^{-1}(x,x^{\prime\prime})\, e^{-ik^\prime x^{\prime\prime}} \tag{8} \\&#xA;&amp;amp;= \frac{4\pi}{|k^\prime|^2}\,\hat\epsilon^{-1}(k,k^\prime) \quad . \tag{9}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now by plugging this in the respective Fourier series of &lt;span class=&quot;math-container&quot;&gt;$W_\Lambda$&lt;/span&gt;, and making use of our aforementioned considerations, we obtain (with a mild abuse of notation)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\small  W(x,x^\prime) = \frac{1}{|\Lambda|^2}\,\sum\limits_{k G^\prime} e^{ikx}\, e^{-i(k-G^\prime)x^\prime} \,\frac{4\pi}{|k^\prime|^2}\, \hat\epsilon^{-1}(k,-(k-G^\prime)) \tag{10} \quad.}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Further, by again writing &lt;span class=&quot;math-container&quot;&gt;$k=q+G$&lt;/span&gt; this becomes&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\!\!\!\!\!\!\!\!{\scriptsize W(x,x^\prime) = \frac{1}{|\Lambda|^2}\,\sum\limits_{qGG^\prime}e^{i(q+G)x} \,e^{-i(q+G-G^\prime)x^\prime}\, \frac{4\pi}{|q+G-G^\prime|^2}\,\hat\epsilon^{-1}(q+G,-(q+G-G^\prime)) \tag{11} ~ . }$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think the very last thing we can do here is to shift the index of the &lt;span class=&quot;math-container&quot;&gt;$G^\prime$&lt;/span&gt; summation (note that we sum over all reciprocal lattice vectors), i.e. for each fixed &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;, we shift the summation as &lt;span class=&quot;math-container&quot;&gt;$G^\prime\rightarrow -G^\prime +G$&lt;/span&gt;, and make use of the different convention regarding the Fourier transform we've employed, which yields&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$${\scriptsize W(x,x^\prime) = \frac{1}{|\Lambda|^2}\,\sum\limits_{qGG^\prime}e^{i(q+G)x} \,e^{-i(q+G^\prime)x^\prime}\, \frac{4\pi}{|q+G^\prime|^2}\,\underbrace{\tilde\epsilon^{-1}(q+G,q+G^\prime)}_{=:\tilde \epsilon^{-1}_{GG^\prime}(q)}\tag{12} ~ .}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The definition of &lt;span class=&quot;math-container&quot;&gt;$\tilde\epsilon^{-1}_{GG^\prime}(q)$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$(12)$&lt;/span&gt; is used in the paper which is cited in the reference given in the question (although even there I could not find the &lt;em&gt;very&lt;/em&gt; definition).&lt;/p&gt;&#xA;&lt;p&gt;As mentioned at the very beginning, this is nearly the result posed in the question, but with a different index in the Fourier transform of the Coulomb potential and an additional inverse volume factor. Yet, for me this makes sense, as the &lt;span class=&quot;math-container&quot;&gt;$x^\prime$&lt;/span&gt; variable in &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; is plugged in the Coulomb interaction, and the corresponding &amp;quot;conjugated&amp;quot; variable to &lt;span class=&quot;math-container&quot;&gt;$x^\prime$&lt;/span&gt; here is &lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt;. The additional volume factor for me makes sense, too, by purely dimensional grounds. But it could also be that the reference puts the volume factors also partially to the Fourier transform, which would then solve this pre-factor issue.&lt;/p&gt;&#xA;&lt;p&gt;Finally, another argument for why these things seem correct (or at least, not &amp;quot;totally wrong&amp;quot;) is that we can recover &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; from equation &lt;span class=&quot;math-container&quot;&gt;$(12)$&lt;/span&gt;, or equivalently &lt;span class=&quot;math-container&quot;&gt;$(10)$&lt;/span&gt;, in the thermodynamic limit which however seems not possible if we had only one inverse volume factor and the different index.&lt;/p&gt;&#xA;&lt;p&gt;As a last point, I don't quite understand why the authors refer to &lt;span class=&quot;math-container&quot;&gt;$|\Lambda|$&lt;/span&gt; as the &lt;em&gt;unit cell&lt;/em&gt; volume.&lt;/p&gt;&#xA;&lt;p&gt;I admit that all of this looks very &amp;quot;constructed&amp;quot;; so take everything with a grain of salt. Perhaps someone can spot a mistake - I'd be very grateful for any hint.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Many-Body Problems and Quantum Field Theory: An Introduction. Martin and Rothen. Section 3.2 page 111 and section 4 pages 135-137.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Nonequilibrium many-body theory of quantum systems. Stefanucci and Leuuwen. Appendix E, page 529&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Response Theory of the Electron-Phonon Coupling. Starke and Schober. Sections 2.2.1 and A.5&lt;/em&gt;. &lt;a href=&quot;https://arxiv.org/abs/1606.00012&quot; rel=&quot;nofollow noreferrer&quot;&gt;arxiv&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Quantum Theory of the Solid State: An Introduction. Kantorovich. Section 5.4.5.2, equations &lt;span class=&quot;math-container&quot;&gt;$(5.201)$&lt;/span&gt;  and &lt;span class=&quot;math-container&quot;&gt;$(5.209)$&lt;/span&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For a discussion on the imposed periodicity, &lt;a href=&quot;https://physics.stackexchange.com/questions/728199/operators-and-periodic-boundary-conditions&quot;&gt;this&lt;/a&gt; physics stackexchange question might be of interest.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2023-06-15T10:45:35.377" LastActivityDate="2023-06-15T10:45:35.377" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="9947" PostTypeId="1" CreationDate="2022-11-10T15:28:09.243" Score="4" ViewCount="519" Body="&lt;p&gt;I have been trying to use the RDKit's reaction substructure matching for some time. I want to match all reactions where a C-H bond is being broken to form a new C-C bond.&lt;/p&gt;&#xA;&lt;p&gt;This is my code:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit.Chem import AllChem&#xA;from rdkit.Chem import rdChemReactions&#xA;&#xA;c_h_template = AllChem.ReactionFromSmarts('[#6:1]-[#1]&amp;gt;&amp;gt;[#6:1]~[#6]')&#xA;x = AllChem.ReactionFromSmarts('C1=[CH:1]C=CC=C1.C[CH:2]=C.[Pd]&amp;gt;&amp;gt;C[C:2](=C)[CH:1]1=CC=CC=C1',useSmiles=True)&#xA;result = rdChemReactions.HasReactionSubstructMatch(x,c_h_template)&#xA;print(result) # always False&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result is always False, even though the reaction pattern should match.&lt;/p&gt;&#xA;&lt;p&gt;The template, and the reaction are shown below (in jupyter notebook):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CKcv1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CKcv1.png&quot; alt=&quot;picture of jupyter nptebook&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not sure what I am doing wrong here. I have read about SMARTS from daylight website, and I think the atom mapping is correct, and it should match. Any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-02-19T16:24:43.310" Title="How to do SMARTS reaction substructure mapping with RDKit" Tags="|python|rdkit|cheminformatics|smiles|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9948" PostTypeId="1" CreationDate="2022-11-10T18:39:16.043" Score="6" ViewCount="380" Body="&lt;p&gt;Let say we need to determine the total number of electrons of an FCC material (let say, two silicon atoms in the unit cell, using &lt;strong&gt;numerical/mathematical approach&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can we get the total number of electrons using 'spherical integration' of density of states or partial density of states? If there's equations or diagrams that could help explain this, that would be welcome too.&lt;/p&gt;&#xA;&lt;p&gt;(I have quantum espresso DOS and PDOS outputs. The answer can be based on this, or can be based on purely numerical/mathematical approach)&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2022-11-10T19:58:03.217" LastActivityDate="2022-11-16T01:44:48.343" Title="Total number of electrons from DOS and PDOS - what's the theory behind it?" Tags="|density-functional-theory|numerical-convergence|charge-density|conceptual-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9949" PostTypeId="1" CreationDate="2022-11-10T18:53:12.340" Score="7" ViewCount="306" Body="&lt;p&gt;I have been looking for a way to change some parameters included in the calculations of PySCF (e.g., changing the mass of the electron to the mass of a muon, so forming an exotic molecule). I know the whole code is on GitHub as it is a collaborative project, but I don't seem to find it. Has someone worked with something like this and knows where to find these parameters?&#xA;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6252" LastEditorUserId="5" LastEditDate="2022-11-10T19:56:12.957" LastActivityDate="2022-11-16T11:15:26.400" Title="How can I change the mass of an electron in the hamiltonian on a PySCF calculation?" Tags="|model-hamiltonians|pyscf|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9950" PostTypeId="1" CreationDate="2022-11-10T18:54:09.207" Score="3" ViewCount="145" Body="&lt;p&gt;Do you set &lt;code&gt;NCORE&lt;/code&gt; when performing hybrid-functional calculations?&lt;/p&gt;&#xA;&lt;p&gt;I heard that &lt;code&gt;NCORE&lt;/code&gt; can be set for VASP6, but when I do &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; set them, I still get the warning: &amp;quot;Unfortunately you need to use the default for GW and RPA calculations (for HF &lt;code&gt;NCORE&lt;/code&gt; is supported but not extensively tested yet)&amp;quot;. From this warning, it seems &lt;code&gt;NCORE&lt;/code&gt; should not be set for hybrid-functional calculations even with VASP6.&lt;/p&gt;&#xA;" OwnerUserId="1688" LastEditorUserId="1688" LastEditDate="2022-11-12T14:35:06.327" LastActivityDate="2022-11-12T14:35:06.327" Title="NCORE tag when performing hybrid-functional calculations" Tags="|vasp|hse06|" AnswerCount="0" CommentCount="1" ClosedDate="2023-05-28T16:27:06.147" ContentLicense="CC BY-SA 4.0" />
  <row Id="9951" PostTypeId="2" ParentId="9949" CreationDate="2022-11-10T20:50:21.563" Score="5" Body="&lt;p&gt;I'm afraid I don't think PySCF has the functionality... (I could be wrong!)&lt;/p&gt;&#xA;&lt;p&gt;PySCF uses &lt;a href=&quot;https://github.com/sunqm/libcint&quot; rel=&quot;nofollow noreferrer&quot;&gt;libcint&lt;/a&gt; to calculate all atomic orbital integrals. You would likely need to modify this codebase / find a different library that can calculate such integrals for muons. You could also write everything from scratch, but this would be quite involved.&lt;/p&gt;&#xA;&lt;p&gt;Once you have the integrals you can feed them into PySCF and do all the chemistry stuff you'd like. As we normally work in atomic units (aka how the Hamiltonian is written), you will need to correct any terms where electron mass appears (replacing with that for muons). Terms not involving electrons, such as nuclear kinetic term will remain the same.&lt;/p&gt;&#xA;" OwnerUserId="4349" LastEditorUserId="4349" LastEditDate="2022-11-11T14:15:45.740" LastActivityDate="2022-11-11T14:15:45.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9952" PostTypeId="2" ParentId="9949" CreationDate="2022-11-10T22:14:51.590" Score="7" Body="&lt;p&gt;The electron mass is set in &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/b43166583a4f609e48ef9f61b8e6d60d8205adbb/pyscf/data/nist.py#L29&quot; rel=&quot;noreferrer&quot;&gt;pyscf/data/nist.py&lt;/a&gt; along with other physical constants,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;G_ELECTRON = 2.00231930436182   # http://physics.nist.gov/cgi-bin/cuu/Value?gem&#xA;E_MASS = 9.10938356e-31         # kg https://physics.nist.gov/cgi-bin/cuu/Value?me&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Whether or not it's sufficient to change these is unclear to me. Note that the rest of the PySCF codebase appears to use the proton-to-electron mass ratio &lt;code&gt;MP_ME = PROTON_MASS / E_MASS&lt;/code&gt; rather than &lt;code&gt;E_MASS&lt;/code&gt; directly.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2022-11-10T22:14:51.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9953" PostTypeId="1" CreationDate="2022-11-11T03:52:27.357" Score="6" ViewCount="538" Body="&lt;p&gt;where can I find a file for molecules e.g: H2&lt;/p&gt;&#xA;&lt;p&gt;For solids, I am using AMCSD (American Mineralogist Crystal Structure Database), but where can I find molecule files?&lt;/p&gt;&#xA;" OwnerUserId="5898" LastActivityDate="2022-11-11T12:58:58.700" Title="Files for molecules to Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|materials-design|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9954" PostTypeId="1" CreationDate="2022-11-11T05:11:11.317" Score="6" ViewCount="512" Body="&lt;p&gt;I'm using Avogadro to generate an input for ORCA, however, when I'm trying to run that input in ORCA it says:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;INPUT ERROR UNRECOGNIZED OR DUPLICATED KEYWORD(S) IN SIMPLE INPUT LINE DEF2-SVP/J&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(I don't even know what I'm doing help D;)&lt;/p&gt;&#xA;&lt;p&gt;Input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# avogadro generated ORCA input file &#xA;# Basic Mode&#xA;# &#xA;! BP RI SP def2-SVP def2-SVP/J &#xA;&#xA;* xyz 0 1&#xA;   H        0.77899       -0.00348       -0.13267&#xA;   O       -0.14793        0.02998       -0.34219&#xA;   H       -0.63110       -0.02651        0.47487&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6253" LastEditorUserId="24" LastEditDate="2022-11-11T12:49:02.883" LastActivityDate="2023-03-07T14:29:33.980" Title="Unrecognized or duplicated keyword error using ORCA DFT calculations using avogadro" Tags="|computational-chemistry|quantum-chemistry|orca|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9955" PostTypeId="2" ParentId="9943" CreationDate="2022-11-11T06:05:03.900" Score="7" Body="&lt;p&gt;This is a basic &lt;strong&gt;bash script&lt;/strong&gt; that can be used. One can make this code better too&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for fold in `ls -d test-*/`; &#xA;do&#xA;line_no=`grep -n 'stress matrix after NEB' OUTCAR|tail -n 1|cut -d ':' -f1`&#xA;sig11=`sed -n &amp;quot;$((${line_no}+1))p&amp;quot; OUTCAR|awk '{print $1}'`&#xA;sig12=`sed -n &amp;quot;$((${line_no}+1))p&amp;quot; OUTCAR|awk '{print $2}'`&#xA;sig13=`sed -n &amp;quot;$((${line_no}+1))p&amp;quot; OUTCAR|awk '{print $3}'`&#xA;sig21=`sed -n &amp;quot;$((${line_no}+2))p&amp;quot; OUTCAR|awk '{print $1}'`&#xA;sig22=`sed -n &amp;quot;$((${line_no}+2))p&amp;quot; OUTCAR|awk '{print $2}'`&#xA;sig23=`sed -n &amp;quot;$((${line_no}+2))p&amp;quot; OUTCAR|awk '{print $3}'`&#xA;sig31=`sed -n &amp;quot;$((${line_no}+3))p&amp;quot; OUTCAR|awk '{print $1}'`&#xA;sig32=`sed -n &amp;quot;$((${line_no}+3))p&amp;quot; OUTCAR|awk '{print $2}'`&#xA;sig33=`sed -n &amp;quot;$((${line_no}+3))p&amp;quot; OUTCAR|awk '{print $3}'`&#xA;total_force=`grep 'FORCE total' OUTCAR|tail -n 1|awk '{print $6}'`&#xA;total_stress=`grep 'Stress total' OUTCAR|tail -n 1|awk '{print $6}'`&#xA;&#xA;echo &lt;span class=&quot;math-container&quot;&gt;${fold%?} $&lt;/span&gt;{sig11} &lt;span class=&quot;math-container&quot;&gt;${sig12} $&lt;/span&gt;{sig13} &lt;span class=&quot;math-container&quot;&gt;${sig21} $&lt;/span&gt;{sig22} &lt;span class=&quot;math-container&quot;&gt;${sig23} $&lt;/span&gt;{sig31} &lt;span class=&quot;math-container&quot;&gt;${sig32} $&lt;/span&gt;{sig33} &lt;span class=&quot;math-container&quot;&gt;${total_force} $&lt;/span&gt;{total_stress}&amp;gt;&amp;gt; result.csv&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;results.csv&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;test-000 -467.71245 24.34138 7.71803 24.34138 -314.11534 -3.45455 7.71803 -3.45455 -371.79956 0.039198 676.007623&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-11T06:05:03.900" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9956" PostTypeId="2" ParentId="9953" CreationDate="2022-11-11T07:56:16.997" Score="7" Body="&lt;p&gt;It is easy to create input of &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; molecule inside QE input file directly or Generate cif or xyz file using &lt;strong&gt;ASE&lt;/strong&gt;, &lt;strong&gt;VESTA&lt;/strong&gt;, &lt;strong&gt;ATOMSK&lt;/strong&gt; and other tool&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import build&#xA;model=build.molecule('H2',vacuum=5)&#xA;model.write('H2.cif',format='cif')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;QE input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation = 'relax'&#xA;    prefix = 'h2'&#xA;    pseudo_dir = '/home/anonymous/quantumEspresso_2019/SSSP_precision_pseudos'&#xA;/&#xA;&amp;amp;system&#xA;    ibrav=1, celldm(1) =20, &#xA;    nat=2, ntyp=1,&#xA;    ecutwfc=30.0&#xA;/&#xA;&amp;amp;electrons&#xA;    conv_thr=1e-8&#xA;/&#xA;&amp;amp;ions&#xA;    ion_dynamics='bfgs'&#xA;/&#xA;ATOMIC_SPECIES&#xA; H  1.00784  H_ONCV_PBE-1.0.oncvpsp.upf&#xA;ATOMIC_POSITIONS (angstrom)&#xA; H 0.00 0.00 0.00&#xA; H 1.00 0.00 0.00&#xA;K_POINTS (automatic)&#xA;  1 1 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-11T07:56:16.997" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9957" PostTypeId="2" ParentId="9953" CreationDate="2022-11-11T12:58:58.700" Score="6" Body="&lt;p&gt;If you need structures for other, more complex, molecules, you can use several online databases like:&lt;/p&gt;&#xA;&lt;h1&gt;&lt;a href=&quot;https://zinc.docking.org/&quot; rel=&quot;noreferrer&quot;&gt;ZINC&lt;/a&gt;&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Welcome to ZINC, a free database of commercially-available compounds&#xA;for virtual screening. ZINC contains over 230 million purchasable&#xA;compounds in ready-to-dock, 3D formats. ZINC also contains over 750&#xA;million purchasable compounds you can search for analogs in under a&#xA;minute.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h1&gt;&lt;a href=&quot;http://www.chemspider.com/&quot; rel=&quot;noreferrer&quot;&gt;ChemSpider&lt;/a&gt;&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ChemSpider is a free chemical structure database providing fast text&#xA;and structure search access to over 100 million structures from&#xA;hundreds of data sources.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can download your structure from one of these sites and then convert to QE input format.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-11-11T12:58:58.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9958" PostTypeId="1" CreationDate="2022-11-12T05:16:49.517" Score="4" ViewCount="131" Body="&lt;p&gt;I want to optimize an enzyme in the presence of a metal ion.&#xA;I started the optimization for the system in the ground state with DFT (B3LYP) method using 6-31G(d) basis set.&#xA;But, this gave an error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error parsing secondary structure:&#xA; QPErr --- A syntax error was detected in the input line.&#xA;  1 3 1.0 2 1.0 4 1.0 5 1.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And, I have no idea on this. So can anyone please help me to solve this?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="7" LastEditDate="2022-11-12T14:12:27.633" LastActivityDate="2022-11-12T14:12:27.633" Title="Gaussian error in optimization" Tags="|gaussian|optimization|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-28T16:26:50.017" ContentLicense="CC BY-SA 4.0" />
  <row Id="9959" PostTypeId="1" CreationDate="2022-11-13T16:56:48.640" Score="2" ViewCount="23" Body="&lt;p&gt;So, I've seen some videos about laser induced graphene and its use as either a supercapacitor or as a low-voltage heater.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://youtu.be/RKcUgdXUf9Y?t=554&quot; rel=&quot;nofollow noreferrer&quot;&gt;this video&lt;/a&gt; the person only uses two electrodes on each end of the LIG tape to make such low-voltage heater. But one of the remarks he makes is that the heater will only work until the kapton tape fails due to its temperature.&lt;/p&gt;&#xA;&lt;p&gt;So I was wondering if extracting the LIG from the Kapton tape, the graphene would still work. But I don't know how such thing would be achieved.&lt;/p&gt;&#xA;" OwnerUserId="6259" LastEditorUserId="5" LastEditDate="2022-11-13T17:33:36.353" LastActivityDate="2022-11-13T17:33:36.353" Title="Does laser-induced graphene (LIG) stay functional after being extracted from the substrate?" Tags="|materials-engineering|graphene|" AnswerCount="0" CommentCount="4" ClosedDate="2023-05-28T16:26:41.993" ContentLicense="CC BY-SA 4.0" />
  <row Id="9960" PostTypeId="1" CreationDate="2022-11-13T22:06:57.697" Score="5" ViewCount="51" Body="&lt;p&gt;When you are using Monte Carlo scheme to simulate equilibrium phases of convex hard-core molecules, namely, whose energy is infinite when in contact and 0 otherwise in a standard, cubic simulation box, all upscaling box moves are guaranteed not to introduce overlaps - the distances between all shapes are increased, and since they are convex, they cannot overlap. Of course this is not true for concave shapes.&lt;/p&gt;&#xA;&lt;p&gt;I am interested in generalizing skipping the overlap check to general moves in a general, triclinic box. To put it more precisely, consider a box given by 3 vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}_1, \mathbf{m}_2, \mathbf{m}_3$&lt;/span&gt; with a common origin coinciding with coordinate system origin, which span parallelpiped describing the simulation box. Each convex shape is described by its relative coordinates &lt;span class=&quot;math-container&quot;&gt;$a_i \in [0, 1), i=1,2,3$&lt;/span&gt;, so the absolute position is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r} = a_1 \mathbf{m}_1 + a_2 \mathbf{m}_2 + a_3 \mathbf{m}_3&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, most general box move is just choosing different box vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}'_1, \mathbf{m}'_2, \mathbf{m}'_3$&lt;/span&gt; by some perturbations of the old ones and redefining all absolute positions as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r}' = a_1 \mathbf{m}'_1 + a_2 \mathbf{m}'_2 + a_3 \mathbf{m}'_3&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;without any changes in relative coordinates or orientations of shapes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The question is:&lt;/strong&gt; how can I, just by comparing &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{m}'_i$&lt;/span&gt; in some way, determine that the move is guaranteed not to introduce any overlaps for some arbitrary convex shapes, like it can be easily done for cubic box (for orthorhombic box it is also easy)?&lt;/p&gt;&#xA;&lt;p&gt;When I dove into it, it is harder than is looks. First thought would be to make sure that the box transformation increases all distances, so we take a transformation matrix, subtract identity matrix and check if the resulting matrix is positive-definite. But that is incorrect - take for example cubes with almost-touching walls and perform a rotation of the box. Of course the distances now are the same, but the box rotated and cubes orientations didn't rotate with it (because of how I defined a box move), so they start overlapping.&lt;/p&gt;&#xA;&lt;p&gt;Any ideas? I can also accept some estimated solutions - the ones that may not detect all cases, but the definitely don't skip moves that &lt;strong&gt;can&lt;/strong&gt; introduce overlaps.&lt;/p&gt;&#xA;" OwnerUserId="6261" LastActivityDate="2022-11-15T00:56:09.807" Title="Generalization of always accepting box upscaling moves in Monte Carlo for a triclinic box" Tags="|molecular-dynamics|molecular-modeling|monte-carlo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9961" PostTypeId="1" AcceptedAnswerId="9962" CreationDate="2022-11-14T13:00:05.700" Score="6" ViewCount="288" Body="&lt;p&gt;I'm setting up a simple Hartree-Fock problem in pyscf with ECPs to test things out. However, the numbers I get do not make sense to me as the energies are very different. I have never used ECPs before so I don't know exactly what to expect. Here is my code and outputs. Without ECPs (using sto-3g) I get&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = gto.M(atom=&amp;quot;Li 0. 0. 0.; H  0.  0.  1.&amp;quot;, basis={'Li':'sto3g', 'H':'sto3g'}, verbose=0)&#xA;mf = scf.RHF(mol)&#xA;print(mf.kernel())&#xA;&#xA;Output: -7.76736&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and with ECP for lithium I get&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = gto.M(atom=&amp;quot;Li 0. 0. 0.; H  0.  0.  1.&amp;quot;, basis={'Li':'stuttgart', 'H':'sto3g'}, ecp = {'Li':'stuttgart'}, verbose=0)&#xA;mf = scf.RHF(mol)&#xA;print(mf.kernel())&#xA;&#xA;Output: -0.63098&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can notice the energies are very different in these two cases. Is this normal or is something wrong here?&lt;/p&gt;&#xA;" OwnerUserId="6264" LastActivityDate="2022-11-14T14:15:05.060" Title="Effective core potential (ECP) calculations" Tags="|computational-chemistry|hartree-fock|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9962" PostTypeId="2" ParentId="9961" CreationDate="2022-11-14T14:15:05.060" Score="8" Body="&lt;p&gt;This is perfectly normal.&lt;/p&gt;&#xA;&lt;p&gt;In ab initio calculations, the energy zero point is usually chosen as the state where all explicitly described particles are infinitely far from each other and each possessing zero kinetic energy. Thus, in an all-electron calculation of LiH, the calculated energy is versus the state where the lithium nucleus, the hydrogen nucleus, and the 4 electrons are infinitely separated from each other.&lt;/p&gt;&#xA;&lt;p&gt;However, in your ECP calculation, the core electrons of lithium are not described explicitly. So the energy zero point is the state where a &lt;span class=&quot;math-container&quot;&gt;$\ce{Li+}$&lt;/span&gt; cation, a &lt;span class=&quot;math-container&quot;&gt;$\ce{H+}$&lt;/span&gt;, and two electrons are infinitely far away from each other. This is of course a considerably lower reference energy than the all-electron case, because the two core electrons of lithium are not ionized. Therefore, in the ECP calculation, the total energy of LiH is much higher in number.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-11-14T14:15:05.060" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9963" PostTypeId="2" ParentId="9960" CreationDate="2022-11-15T00:56:09.807" Score="4" Body="&lt;p&gt;Thank you for the interesting question, that was definitely some food for thought. I think I am on the right track but couldn't manage to find an analytical solution so I am giving you a numerical procedure that &lt;em&gt;should&lt;/em&gt; work and you could follow up with an analytical simplification if it exists!&lt;/p&gt;&#xA;&lt;p&gt;My first observation was that in your case you want all possible distances to be always increased or unchanged, but never decreased. That is to say, for a squared distance between any two points we have &lt;span class=&quot;math-container&quot;&gt;$\Delta r^2=\sum_{i,j}\Delta a_i \Delta a_j\bf{m}_i.\bf{m}_j$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$0 \leq \Delta a_i^2 \leq 1$&lt;/span&gt; for each &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, and the scaled squared distance will be &lt;span class=&quot;math-container&quot;&gt;$\Delta {r'}^2=\sum_{i,j}\Delta a_i \Delta a_j\bf{m'}_i.\bf{m'}_j$&lt;/span&gt; and we always have a good move if &lt;span class=&quot;math-container&quot;&gt;$f(\bf{\Delta a}) = \Delta {r'}^2 - \Delta {r}^2 \geq 0$&lt;/span&gt; for &lt;em&gt;all&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$0 \leq \Delta a_i^2 \leq 1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now you can define a matrix &lt;span class=&quot;math-container&quot;&gt;$\bf{M}$&lt;/span&gt; with entries &lt;span class=&quot;math-container&quot;&gt;$M_{i,j} = \bf{m'}_i.\bf{m'}_j - \bf{m}_i.\bf{m}_j$&lt;/span&gt; and you can turn this into an optimisation problem: if you minimise &lt;span class=&quot;math-container&quot;&gt;$f(\bf{\Delta a}) = \bf{\Delta a}^T\bf{M}\bf{\Delta a}$&lt;/span&gt; w.r.t. &lt;span class=&quot;math-container&quot;&gt;$\bf{\Delta a}$&lt;/span&gt; subject to the above constraints and the resulting minimised value is still greater than or equal to 0, then you will never shrink any distances. This is a fairly simple inequality constraint problem so it should be readily soluble numerically. There might be a closed-form solution but I don't have the time to figure it out so I am going to leave it to you. I hope that helps!&lt;/p&gt;&#xA;" OwnerUserId="710" LastActivityDate="2022-11-15T00:56:09.807" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="9964" PostTypeId="2" ParentId="8782" CreationDate="2022-11-15T03:12:50.240" Score="2" Body="&lt;p&gt;There is a way to manually install p4vasp on higher version of ubuntu, I have tested on ubuntu 20.04.&#xA;The step wise manual for installation&#xA;&lt;a href=&quot;https://github.com/HaoyuYang59/p4vasp/blob/master/README.Ubuntu&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/HaoyuYang59/p4vasp/blob/master/README.Ubuntu&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2022-11-15T03:12:50.240" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9965" PostTypeId="1" CreationDate="2022-11-15T11:16:43.333" Score="3" ViewCount="33" Body="&lt;p&gt;I'm trying to install Multiwell including Thermo. The &lt;a href=&quot;https://multiwell.engin.umich.edu/wp-content/uploads/sites/569/2022/05/MultiWell-User-Manual-2022.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; says under 1.4. that I have to install openmpi before. So I followed the instructions from the multiwell manual but get an error at 8.) &amp;quot;make all install&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;This is my error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/Users/andrea/Downloads/openmpi-4.0.7/opal/mca/pmix/pmix3x/pmix/src/atomics/sys/gcc_builtin/atomic.h:197:12: error: address argument to atomic operation must be a pointer to integer or pointer ('pmix_atomic_int128_t *' (aka '_Atomic(pmix_int128_t) *') invalid)&#xA;    return __atomic_compare_exchange_n (addr, oldval, newval, false,&#xA;           ^                            ~~~~&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The manual says that my version of Multiwell can used on Linux and Mac. Maybe the problem is I got a MacBook Pro with M1 Chip? I had no problem installing Multiwell on my old MacBook Air with Intel Chip.&lt;/p&gt;&#xA;&lt;p&gt;But the error looks to me like there is something wrong with mpi? I tried to go on with Multiwell Installation but it doesn't work, like I expected.&lt;/p&gt;&#xA;&lt;p&gt;Can some one give me a tip how to work around?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="7" LastEditDate="2022-11-15T23:54:58.177" LastActivityDate="2022-11-15T23:54:58.177" Title="Problem with installation of Multiwell Software package and open mpi" Tags="|software|high-performance-computing|software-assistance|apple-operating-system|" AnswerCount="0" CommentCount="1" ClosedDate="2023-05-28T16:20:07.770" ContentLicense="CC BY-SA 4.0" />
  <row Id="9966" PostTypeId="1" AcceptedAnswerId="9967" CreationDate="2022-11-15T16:59:45.573" Score="3" ViewCount="753" Body="&lt;p&gt;I don't know how  to install the g16 with gv under Linux. According to the internet the installation seems to require a file called a tar.gz which I don't find in the g16 folder. I have a lot of files with the extensions &lt;code&gt;.exe&lt;/code&gt;, &lt;code&gt;.prm&lt;/code&gt;, &lt;code&gt;.help&lt;/code&gt; and so on, and some subfolders inside the g16 folder. I have fedora version .&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="-1" LastEditDate="2022-11-16T14:21:27.557" LastActivityDate="2022-11-16T14:21:27.557" Title="problem with the installation of g16 with gaussview under Linux" Tags="|software|gaussian|software-assistance|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9967" PostTypeId="2" ParentId="9966" CreationDate="2022-11-15T20:44:10.767" Score="4" Body="&lt;p&gt;All the information you need to install Gaussian and GaussView in your system, you can obtain it from the &lt;a href=&quot;https://gaussian.com/techsupport/#install&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian.com support&lt;/a&gt; site.&lt;/p&gt;&#xA;&lt;p&gt;Installation Instructions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gaussian.com/g16/g16src_install.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian 16 source code&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gaussian.com/g16/g16bin_install.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian 16 UNIX binary&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gaussian.com/g16/gv_install.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;GaussView 6 for UNIX&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also, you can visit the Gaussian Technical support &lt;a href=&quot;https://gaussian.com/help/&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-11-15T20:44:10.767" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9968" PostTypeId="2" ParentId="9948" CreationDate="2022-11-16T01:44:48.343" Score="6" Body="&lt;p&gt;If you integrate the DOS, &lt;span class=&quot;math-container&quot;&gt;$g(E)$&lt;/span&gt;, up to the Fermi-level, &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt;, the area should be very close to the number of electrons, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;; i.e.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;N \approx \int_{-\infty}^{E_f} g(E) dE \tag{1}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You'll have to be careful what the normalisation is for the DOS, but this will only affect the definition of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, e.g. whether it's the number of electrons per unit cell, or per unit volume, or per atom etc.&lt;/p&gt;&#xA;&lt;p&gt;The reason the integral is usually only &amp;quot;close&amp;quot; to the number of electrons, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, is because it is standard practice to apply a smearing function in the calculation to better approximate the integral over the Brillouin zone. If you include this smearing function, &lt;span class=&quot;math-container&quot;&gt;$f(E-E_F)$&lt;/span&gt;, in the integrand and integrate over all energies, then the result should be exact:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;N = \int_{-\infty}^{\infty} f(E-E_F) g(E) dE \tag{2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This relationship is actually the definition of the Fermi energy &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt;, so it really should be reliable. If you find that you don't get the correct answer, you should check that you are using the same broadening function and width - e.g. some programs ask for the smearing width as the standard deviation of the broadening, and some as the full-width half-maximum (FWHM).&lt;/p&gt;&#xA;&lt;p&gt;There may also be some small discrepancies in the electron count if you use a Fermi energy calculated on one k-point grid, and then do the integral on the DOS from a different k-point grid. In practice, this usually arises when the Fermi energy is from the self-consistent (SCF) ground state calculation, and the DOS is calculated from a non-self-consistent calculation performed on a finer k-point grid.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-11-16T01:44:48.343" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="9969" PostTypeId="1" CreationDate="2022-11-16T04:16:31.857" Score="2" ViewCount="91" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9875/4231&quot;&gt;In my previous question&lt;/a&gt;, I was basically asking whether the results of the double hybrid using the exact XC functional are the same as those of just the exact XC functional.&lt;/p&gt;&#xA;&lt;p&gt;Even that sentence is hard to grasp, so I'm going to ask something more simple- is there an analogue of the K-S theorem for double hybrids, where the &amp;quot;double&amp;quot; part &amp;quot;climbing the ladder&amp;quot; from MP2 to MPn to CISD(T) to full CI, AND the &amp;quot;hybrid&amp;quot; part simply being the exact XC, that yields the exact density of the ground state of the system of interest?&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: I was talking strictly about mathematical rigour, ignoring facts like how &amp;quot;the exact XC is unknown&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;UPDATE 2: To make everything clear- given a set of exact K-S orbitals, does applying MP2, CI(etc) on these orbitals (as if they were H-F orbitals) and summing their squares give the exact ground-state density as well, mathematically?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="142" LastEditDate="2022-11-18T08:54:11.637" LastActivityDate="2022-11-18T08:54:11.637" Title="Is there an analogue of the K-S theorem for double hybrids" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|convergence-test|many-body-perturbation-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9970" PostTypeId="2" ParentId="9875" CreationDate="2022-11-16T10:41:58.750" Score="1" Body="&lt;p&gt;The question is false. There is no &amp;quot;exact&amp;quot; double hybrid density. The problem is that at the point you approximate the exact functional with a double hybrid, the functional is no longer exact. You can find the ground-state solution to the double hybrid functional, but it will not be the exact ground state density of the Schrödinger equation.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-16T10:41:58.750" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="9971" PostTypeId="2" ParentId="9969" CreationDate="2022-11-16T10:48:00.913" Score="3" Body="&lt;p&gt;There is no Kohn-Sham theorem. There are the three Hohenberg-Kohn theorems that demonstrate that the density and the potential are two ways to approach the ground state problem: the potential defines the density, and the density defines the potential (up to an additive constant).&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham approach is to remove the need for a kinetic energy functional by approximating the kinetic energy with the Hartree-Fock kinetic energy of the Kohn-Sham orbitals. The difference between the many-body kinetic energy and the single-determinant kinetic energy is added to the exchange-correlation energy.&lt;/p&gt;&#xA;&lt;p&gt;The question is the same misunderstanding as in &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9875/4231&quot;&gt;Is an &amp;quot;exact&amp;quot; double hybrid density the same as the &amp;quot;exact&amp;quot; DFT density?&lt;/a&gt;. The exact functional is not a double hybrid. You can build various density functional approximations (DFAs), but they will not give you the exact solution. The functional error is commonly decomposed into &amp;quot;functional error&amp;quot;, which the difference of the approximate energy evaluated at the exact density to the exact energy functional at the exact density, and the &amp;quot;density driven error&amp;quot;, which is the contribution of the density relaxation driven by the functional error.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-16T10:48:00.913" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="9972" PostTypeId="2" ParentId="9949" CreationDate="2022-11-16T11:15:26.400" Score="2" Body="&lt;p&gt;As already stated above, PySCF works with atomic units. This means that the electron mass is implicityly baked in the equations.&lt;/p&gt;&#xA;&lt;p&gt;In the molecular Hamiltonian, the only term that depends on the mass is the kinetic energy. In atomic units, the kinetic energy is &lt;span class=&quot;math-container&quot;&gt;$\hat{T} = \hat{p}^2/2\mu = -\frac 1 2 \nabla^2$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the reduced mass &lt;span class=&quot;math-container&quot;&gt;$$ \mu = \frac {mM} {m+M}$$&lt;/span&gt; which is chosen to be &lt;span class=&quot;math-container&quot;&gt;$\mu=1$&lt;/span&gt; in atomic units. Note that for the hydrogen atom &lt;span class=&quot;math-container&quot;&gt;$m_e \ll m_p$&lt;/span&gt; so the reduced mass is close to the electron mass&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mu =  m_e \frac {1} {1 + \frac {m_e} {m_p}} =  m_e \frac {1} {1 + 0.0005446170215} \approx 0.999455679425 m_e $$&lt;/span&gt;&#xA;but this won't be the case for heavier leptons as already for the muon one has &lt;span class=&quot;math-container&quot;&gt;$m_\mu/m_p \approx 0.1126095$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To get the muonic operator, you would thus take &lt;span class=&quot;math-container&quot;&gt;$\hat{T} \to \mu_e/\mu_\mu \hat{T} $&lt;/span&gt;. Note, however, that the change of mass also significantly affects other parts of the calculation. The basis set requirements are different, since the muonic wave functions are more compact, and there will be significant muon-electron correlation effects.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-16T11:15:26.400" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9973" PostTypeId="2" ParentId="9931" CreationDate="2022-11-16T11:24:26.687" Score="2" Body="&lt;p&gt;The excerpt you pasted states that the SCF calculation failed, and one cannot tell when this happened. Was it at the initial geometry? You may get the calculation to work with SCF=XQC.&lt;/p&gt;&#xA;&lt;p&gt;However, I have further comments on the input.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Why do you not use def2TZVP for gold as well? def2TZVP is available for the whole periodic table up to &lt;span class=&quot;math-container&quot;&gt;$Z=86$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Usually it helps to preoptimize with a smaller basis set, if the initial geometry is bad. The xtb program is often very useful as well, as the tight binding calculations run very quickly and rarely have convergence issues, and the geometries are much improved if you start from a poor guess. Alternatively, you could preoptimize the geometry with def2SVP, or def2-SV(P) on all atoms. &lt;a href=&quot;https://gaussian.com/basissets/&quot; rel=&quot;nofollow noreferrer&quot;&gt;These are available in Gaussian as def2SVP and def2SVPP.&lt;/a&gt; SCF convergence should likewise be less of an issue in the smaller basis, and you should be able to afford the quadratic convergence procedure. The preoptimized geometry will likewise work a lot better in the TZVP calculation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-16T11:24:26.687" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9974" PostTypeId="1" CreationDate="2022-11-16T11:55:12.557" Score="4" ViewCount="640" Body="&lt;p&gt;I have a LAMMPS data file with roughly 1000 water molecules, with constituent atoms defined by an atom type (i.e, OW = type 1, HW = type 2), while the molecule itself is not defined explicitly. Therefore, there are approx. 3000 'water atoms' in the system.&lt;/p&gt;&#xA;&lt;p&gt;The system also contains 50 polymer chains with the total system size being around 20,000 atoms.&lt;/p&gt;&#xA;&lt;p&gt;I need to triple the number of water molecules in the system while keeping the box size constant (and avoiding overlapping atoms). How would I do this? I'm aware of the create_atoms command, although how this would be used in this case I'm unsure.&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="6213" LastActivityDate="2022-11-17T20:57:07.287" Title="Adding water molecules to a system in LAMMPS" Tags="|molecular-dynamics|lammps|water|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9976" PostTypeId="1" CreationDate="2022-11-17T14:12:13.333" Score="1" ViewCount="69" Body="&lt;p&gt;I'm use the &lt;a href=&quot;https://tfrederiksen.github.io/inelastica/docs/latest/api-gen/Inelastica.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Inelastica package&lt;/a&gt; to compute MPSH states and analyze the  (HOMO/LUMO). For that, I run the &lt;a href=&quot;https://tfrederiksen.github.io/inelastica/docs/latest/api-gen/Inelastica.EigenChannels.html#scripting&quot; rel=&quot;nofollow noreferrer&quot;&gt;Eigenchannels&lt;/a&gt; command with :&#xA;&lt;code&gt;Eigenchannels -f /*fdf -M 1 -w cube MPSH/&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;This results in the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/usr/local/bin/EigenChannels&amp;quot;, line 12, in &amp;lt;module&amp;gt;&#xA;    Module.main(options)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/Inelastica/EigenChannels.py&amp;quot;, line 134, in main&#xA;    options.DeviceAtoms[1]+L,lasto)&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/Inelastica/SiestaIO.py&amp;quot;, line 1326, in BuildBasis&#xA;    ions[int(CSL[i][0])] = ReadIonNCFile(head+'/%s.ion.nc'%CSL[i][2])&#xA;  File &amp;quot;/usr/local/lib/python2.7/dist-packages/Inelastica/SiestaIO.py&amp;quot;, line 1275, in ReadIonNCFile&#xA;    file = NC4.Dataset(filename,'r')&#xA;  File &amp;quot;netCDF4/_netCDF4.pyx&amp;quot;, line 1848, in netCDF4._netCDF4.Dataset.__init__ (netCDF4/_netCDF4.c:13983)&#xA;IOError: No such file or directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="887" LastEditDate="2022-11-18T17:30:24.280" LastActivityDate="2022-11-18T17:30:24.280" Title="Inelastica Pakage" Tags="|density-functional-theory|siesta|density-of-states|charge-density|" AnswerCount="0" CommentCount="7" ClosedDate="2023-07-31T13:22:08.023" ContentLicense="CC BY-SA 4.0" />
  <row Id="9978" PostTypeId="2" ParentId="9974" CreationDate="2022-11-17T20:57:07.287" Score="3" Body="&lt;p&gt;Here's what I would do in your situation:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Replicate the box three times (&lt;code&gt;replicate 3 1 1&lt;/code&gt; let's say)&lt;/li&gt;&#xA;&lt;li&gt;Use &lt;code&gt;region&lt;/code&gt; to define the &amp;quot;middle box&amp;quot;. Create a &lt;code&gt;group&lt;/code&gt; for the polymers in the middle box, create a &lt;code&gt;group&lt;/code&gt; with all the other polymers using &lt;code&gt;subtract&lt;/code&gt;, and then use &lt;code&gt;delete_atoms&lt;/code&gt; to remove the two copies of polymers (leaving two copies of pure water boxes).&lt;/li&gt;&#xA;&lt;li&gt;Run a short NVT run, using &lt;code&gt;fix deform&lt;/code&gt; to shrink the box from 3x back to its original size.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This definitely isn't the fastest way to do things. Packmol would quickly insert new water molecules where you want to, or you could even use raw text editing to manually add in new water molecules to the data file. But this method has the advantage of being completely reproducible in LAMMPS, not requiring you to learn any new software, and will give you more LAMMPS experience which should come in handy in future.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2022-11-17T20:57:07.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9980" PostTypeId="1" CreationDate="2022-11-18T10:01:51.210" Score="1" ViewCount="124" Body="&lt;p&gt;I'm running a Berny optimization and I need to include the keyword &lt;code&gt;maxstep=1&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Observing the output, in the convergence summary table I can see that the &lt;code&gt;Max Displacement&lt;/code&gt; value does not equal the one I set, but it is greather.&#xA;I surfed online and I found that I need to add the &lt;code&gt;NoTrust&lt;/code&gt; keyword, but I still don't understand it.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone explain it?&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2022-11-18T10:01:51.210" Title="maxstep Gaussian keywords" Tags="|gaussian|geometry-optimization|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-09T22:58:35.590" ContentLicense="CC BY-SA 4.0" />
  <row Id="9982" PostTypeId="1" CreationDate="2022-11-18T12:54:34.090" Score="3" ViewCount="831" Body="&lt;p&gt;People I am using a script to calculate the best &lt;strong&gt;ecutwfc&lt;/strong&gt; value for my system, however, what should be the value for &lt;strong&gt;ecutrho&lt;/strong&gt;? My script should test different values for ecutrho too or I do not need to put this variable in my input file during tests?&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5" LastEditDate="2022-12-09T02:35:59.547" LastActivityDate="2022-12-09T02:35:59.547" Title="How to perform calc to ecutwfc and ecutrho in Quantum ESPRESSO" Tags="|quantum-espresso|materials-design|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9984" PostTypeId="1" CreationDate="2022-11-19T04:38:02.617" Score="1" ViewCount="50" Body="&lt;p&gt;&lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;source=web&amp;amp;rct=j&amp;amp;url=https://www.nature.com/articles/s41467-019-12467-0&amp;amp;ved=2ahUKEwjF4sfMtLn7AhXBCIgKHX7DAIQQFnoECAcQAQ&amp;amp;usg=AOvVaw21qTk3Cx8uJloAv-uXy7sV&quot; rel=&quot;nofollow noreferrer&quot;&gt;This paper&lt;/a&gt; analytically solves the &amp;quot;inverse DFT problem&amp;quot; of mapping the ground-state density to the exact XC functional. And the exact density, i.e. the FCC/FCI density, can be expressed as an infinite series of basis sets with transcendentally analytically expressable coefficients(all one-variable polynomial equations are known to be solvable in analytic form using transcendental functions). This means that the exact XC functional can be expressed as an infinite series of analytically expressable terms.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- is there any known way to find out any &amp;quot;cancellations&amp;quot; in the expansion before (truncating it to yield approximations)?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-11-19T04:38:02.617" Title="Question on known expression (see post) of exact XC functional in analytic (but not closed) form" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|wavefunctions|full-configuration-interaction|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-01T21:51:12.360" ContentLicense="CC BY-SA 4.0" />
  <row Id="9985" PostTypeId="1" CreationDate="2022-11-19T04:51:56.437" Score="1" ViewCount="60" Body="&lt;p&gt;Dyson orbitals are mathematically meaningful, in the sense that they, unlike the DFT orbitals for instance, are actual observables of the wavefunction, instead of being &amp;quot;the other way around&amp;quot;. They are defined as the overlap integral between the N-electron wavefunction and the (N-1)-electron wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Suppose one tries to theoretically compute Dyson orbitals, using the FCC/FCI method for the computation of wavefunctions and using the mathematically complete basis set for both sub-computations. This results in an integral, over the whole space, of two infinite series.&lt;/p&gt;&#xA;&lt;p&gt;And, in Fourier analysis, such integrals often lead to many mathematically rigorous cancellations(believe me, I'm literally a mathematics student), the &amp;quot;leftover parts&amp;quot; being much simplified.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- does this &amp;quot;cancellation&amp;quot; occur for my specific case of FCC/FCI-Dyson orbitals as well?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-11-19T04:51:56.437" Title="Question on possible cancellations in the computation of Dyson orbitals from FCC/FCI wavefunctions" Tags="|mathematical-modeling|orbitals|coupled-cluster|full-configuration-interaction|fourier-transform|" AnswerCount="0" CommentCount="1" ClosedDate="2022-12-01T04:30:29.930" ContentLicense="CC BY-SA 4.0" />
  <row Id="9986" PostTypeId="1" CreationDate="2022-11-19T05:09:46.573" Score="3" ViewCount="45" Body="&lt;p&gt;I am trying to use energy conservative dissipative dynamic (edpd) model to simulate heating a flexible CNT which is floating inside a liquid (water). Using create_atoms command I am creating my liquid beads. I used VMD nanotube builder to create the CNT and got the initial CNT data file from VMD using topo tools, so that I can use read_data command in my input file to read the CNT data file.&lt;/p&gt;&#xA;&lt;p&gt;My question is which atom_style do I define in companion with edpd atom_style to be able to read all the bonds, angles dihedrals and impropers of my CNT? I tried&lt;/p&gt;&#xA;&lt;p&gt;atome_style hybrid edpd full&lt;/p&gt;&#xA;&lt;p&gt;but that also gives me &amp;quot; Incorrect atom format in data file &amp;quot; error.&lt;/p&gt;&#xA;&lt;p&gt;I did use atome_style hybrid edpd bond angle&lt;/p&gt;&#xA;&lt;p&gt;which does not still support the dihedrals and impropers.&lt;/p&gt;&#xA;&lt;p&gt;Any idea how to fix this issue?&lt;/p&gt;&#xA;&lt;p&gt;Thanks a lot&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="4924" LastEditDate="2022-11-19T06:23:31.113" LastActivityDate="2022-11-19T06:23:31.113" Title="which atom_style to be able to simulate a heating a CNT in water in edpd model?" Tags="|molecular-dynamics|lammps|vmd|" AnswerCount="0" CommentCount="4" ClosedDate="2023-05-28T16:19:54.590" ContentLicense="CC BY-SA 4.0" />
  <row Id="9987" PostTypeId="1" AcceptedAnswerId="9994" CreationDate="2022-11-19T13:46:01.657" Score="3" ViewCount="818" Body="&lt;p&gt;I tried to compile Quantum ESPRESSO using the Intel compilers and the MKL libraries. But it went sideways with an error as follows,&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/16GND.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/16GND.png&quot; alt=&quot;Compiling Error&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What I did was as follows,&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Started with a fresh Ubuntu distro in windows 10 wsl&lt;/li&gt;&#xA;&lt;li&gt;Download and install the Intel oneAPI Base and HCP toolkits&lt;/li&gt;&#xA;&lt;li&gt;source the setvars.sh script by Intel to set the environment variables&lt;/li&gt;&#xA;&lt;li&gt;Extract the Quantum ESPRESSO source code&lt;/li&gt;&#xA;&lt;li&gt;Custom configure QE by executing the configure file (./configure MPIF90=mpiifort CC=mpiicc F90=ifort F77=mpiifort -enable-parallel)&lt;/li&gt;&#xA;&lt;li&gt;Edit the make.inc by setting the &amp;quot;BLAS_LIBS=&amp;quot;, &amp;quot;LAPACK_LIBS=&amp;quot;, &amp;quot;SCALAPACK_LIBS=&amp;quot;, and &amp;quot;FFT_LIBS=&amp;quot; to &amp;quot;-L${MKLROOT}/lib/intel64 -lmkl_scalapack_lp64 -lmkl_intel_lp64 -lmkl_sequential -lmkl_core -lmkl_blacs_intelmpi_lp64 -lpthread -lm -ldl&amp;quot; as given by Intel link line advisor.&lt;/li&gt;&#xA;&lt;li&gt;Edit the make.inc by setting the &amp;quot;MPI_LIBS=&amp;quot; to &amp;quot;-L/opt/intel/oneapi/mpi/2021.7.1/lib -lmpi&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;Compiling QE by make pw&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I can't figure out the problem here and would appreciate the view from an expert on the matter.&lt;/p&gt;&#xA;&lt;p&gt;Thank you, Best Regards.&lt;/p&gt;&#xA;&lt;p&gt;Chamara&lt;/p&gt;&#xA;" OwnerUserId="6279" LastEditorUserId="6279" LastEditDate="2022-11-19T16:31:53.727" LastActivityDate="2023-04-19T09:42:01.037" Title="ERROR: Quantum ESPRESSO compiling under Intel oneAPI" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9988" PostTypeId="1" AcceptedAnswerId="9992" CreationDate="2022-11-20T22:00:54.087" Score="5" ViewCount="162" Body="&lt;p&gt;I came across a &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwjF4rvb4L37AhVUSWwGHWNYCNUQFnoECBIQAQ&amp;amp;url=https%3A%2F%2Flink.aps.org%2Fpdf%2F10.1103%2FPhysRevB.99.184105&amp;amp;usg=AOvVaw2j15m9Zd6KHPMRZDydUtIV&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;  which talks about &lt;span class=&quot;math-container&quot;&gt;$Cs_2SnI_6$&lt;/span&gt; the material is well researched and there are dozens of experimental papers which say that the material exists in Fm3m space group(FCC), the particular paper I am talking about talks about the phase transition from cubic to monocilinic as the tempreature decreases although this theoretical calculation does not really go with &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwia4peO4L37AhWTSGwGHS2fC1kQFnoECAkQAQ&amp;amp;url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2F10.1021%2Facs.chemmater.8b01549&amp;amp;usg=AOvVaw1VuSihB3FMkealGWa3IXAO&quot; rel=&quot;noreferrer&quot;&gt;experimental evidence&lt;/a&gt;. My point is that the they show the phonon band structure as &lt;a href=&quot;https://i.stack.imgur.com/j3L2s.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/j3L2s.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the red lines show unstable modes. So is this calculation wrong(as I have heard this would be a dynamically unstable mode, but the material does exist) or can materials with negative phonon modes also exist?&lt;/p&gt;&#xA;&lt;p&gt;P.S there are studies which talk about the anharmonic lattice dynamics of Cs2SnI6 saying that the material shows quite a lot of anharmonicity.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="5" LastEditDate="2022-11-21T06:13:10.817" LastActivityDate="2022-11-22T08:22:46.877" Title="Can a material have negative phonon modes in the phonon spectrum but still exist?" Tags="|phonons|vibrations|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9989" PostTypeId="2" ParentId="9905" CreationDate="2022-11-21T07:22:45.227" Score="2" Body="&lt;p&gt;I've managed to converge my optB88-vdW &lt;strong&gt;geometry relaxations&lt;/strong&gt; to within forces of 0.002 eV/Å (&lt;code&gt;EDIFFG=0.002&lt;/code&gt;), with an electronic convergence tolerance of &lt;span class=&quot;math-container&quot;&gt;$10^{-6}$&lt;/span&gt; eV (&lt;code&gt;EDIFF=1E-6&lt;/code&gt;). This was achieved partly by using a finer &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-point mesh and the conjugate gradient algorithm (&lt;code&gt;IBRION=2&lt;/code&gt;), with &lt;code&gt;ALGO=Fast&lt;/code&gt;. I think my convergence difficulties stemmed from using the qusi-Newton algorithm (&lt;code&gt;IBRION=1&lt;/code&gt;) with the default step-size (&lt;code&gt;POTIM=0.5&lt;/code&gt;) which should have been tuned.&lt;/p&gt;&#xA;&lt;p&gt;For &lt;strong&gt;static calculations&lt;/strong&gt;, I found that &lt;code&gt;ALGO=All&lt;/code&gt; has been successful most if not all of the time.&lt;/p&gt;&#xA;&lt;p&gt;My subsequent phonon and elastic constants calculations seemed to work out fine with my &amp;quot;tighter&amp;quot; geometry relaxations. However, I did find this paper titled &amp;quot;&lt;em&gt;Energy, Phonon, and Dynamic Stability Criteria of Two-Dimensional Materials&lt;/em&gt;&amp;quot; (&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acsami.9b01261&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACS Appl. Mater. Interfaces 2019, 11, 28, 24876–24884&lt;/a&gt;) which used optB88-vdW in &lt;code&gt;VASP&lt;/code&gt; with ionic relaxation force tolerances of 0.01 eV/Å. They managed to get nice-looking phonon dispersion curves, which perhaps indicates that a higher force tolerance may be good enough.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-11-21T07:22:45.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9990" PostTypeId="1" AcceptedAnswerId="9991" CreationDate="2022-11-21T12:46:25.610" Score="7" ViewCount="384" Body="&lt;p&gt;In DFT and Hartree-Fock bonding orbitals have negative energies while antibonding orbitals have positive energies. Why is this the case? It seems this is due to the zero-point energy being defined for bare nuclei and electrons at infinite separation. See:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/questions/128544/for-molecular-orbitals-how-is-an-energy-of-zero-set-or-defined&quot;&gt;https://chemistry.stackexchange.com/questions/128544/for-molecular-orbitals-how-is-an-energy-of-zero-set-or-defined&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.quora.com/Why-do-antibonding-molecular-orbitals-have-higher-energy-than-bonding-molecular-orbitals&quot; rel=&quot;noreferrer&quot;&gt;https://www.quora.com/Why-do-antibonding-molecular-orbitals-have-higher-energy-than-bonding-molecular-orbitals&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.researchgate.net/post/Why_are_the_HOMO_LUMO_energies_I_calculated_using_Gaussian_below_zero&quot; rel=&quot;noreferrer&quot;&gt;https://www.researchgate.net/post/Why_are_the_HOMO_LUMO_energies_I_calculated_using_Gaussian_below_zero&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is this correct and are there any textbooks / peer reviewed references that state/explain this?&lt;/p&gt;&#xA;&lt;p&gt;Does this all just derive from the &lt;a href=&quot;https://en.wikipedia.org/wiki/Binding_energy&quot; rel=&quot;noreferrer&quot;&gt;binding energy&lt;/a&gt;?&lt;/p&gt;&#xA;" OwnerUserId="4349" LastEditorUserId="4349" LastEditDate="2022-11-21T12:52:32.113" LastActivityDate="2022-11-21T15:34:19.500" Title="How is the zero energy defined for molecular orbitals?" Tags="|density-functional-theory|molecular-modeling|electronic-structure|hartree-fock|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9991" PostTypeId="2" ParentId="9990" CreationDate="2022-11-21T15:34:19.500" Score="9" Body="&lt;p&gt;The zero point of orbital energies is usually defined as the vacuum level, i.e. the energy of a hypothetical orbital that is infinitely diffuse and does not come close to any nuclei or other electron. Note that this is not quite the same thing as &amp;quot;bare nuclei and electrons at infinite separation&amp;quot; as mentioned in the linked answer. The latter is the zero point of the total energy, not the zero point of the orbital energy. Orbital energies are the energies of single electron wavefunctions, so referencing orbital energies against the energy of a multiparticle system does not make sense.&lt;/p&gt;&#xA;&lt;p&gt;However, antibonding orbitals do not necessarily have positive energies! Very small molecules do frequently have positive antibonding orbital energies, and most textbooks mention small molecules only, which may lead to the false impression that this holds for larger molecules as well. Calculate the antibonding orbitals of moderately sized and electron deficient molecules, such as 2,4,6-trinitrotoluene, and you'll probably find that quite a few of the antibonding orbitals have negative energies, particularly if you use DFT instead of HF. For DFT calculations of large conjugated molecules, negative LUMO energies are probably the rule rather than the exception.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, bonding orbitals do not necessarily have negative energies, although exceptions are considerably rarer. A trivial example is a molecule surrounded by a sufficient number of negative ions. Negative ions raise both the bonding and the antibonding orbital energies due to their Coulomb potential, so with a sufficient number of negative ions, the bonding orbital of the molecule will be raised above vacuum level; it will then spontaneously ionize, but under favorable conditions the spontaneous ionization may be slow enough such that the unionized molecule is experimentally observable.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-11-21T15:34:19.500" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9992" PostTypeId="2" ParentId="9988" CreationDate="2022-11-22T08:22:46.877" Score="3" Body="&lt;p&gt;My answer will be a more general one about soft modes and not too specifically-related to the system OP cited as these ideas are probably generally applicable to other structures.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, I would say that phonon calculations can be qualitatively &amp;quot;wrong&amp;quot; if the soft modes arise from &lt;strong&gt;convergence problems&lt;/strong&gt; rather than anything physical. This could be a result of&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Poor electronic convergence&lt;/strong&gt;. The forces might not be well-converged.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Poor geometry relaxation convergence&lt;/strong&gt;. The forces might not small enough, which would be problematic for say computing the force constants matrix with finite differences.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Poor supercell convergence&lt;/strong&gt;. The phonon dispersion values at the &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points commensurate with the supercell used may not exhibit soft modes, but Fourier interpolating those points for values in between those commensurate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{q}$&lt;/span&gt;-points may lead to artificial soft modes that might disappear when larger supercells are used. (see this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2155/best-practices-for-q-points-convergence-in-phonon-density-of-states-calculatio/2169#2169&quot;&gt;Q&amp;amp;A&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If the soft modes are still present, they can be physically interpreted as indicative of &lt;strong&gt;dynamical instability&lt;/strong&gt; as OP pointed out. This &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1635/how-to-deduce-phase-transitions-from-a-phonon-calculation/1637#1637&quot;&gt;Q&amp;amp;A&lt;/a&gt; provides a comprehensive discussion relevant to OP's question. In short, we can rationalize the experimental observation of a structure with a soft mode by thinking of the structure as a saddle point in the potential energy landscape that could become a minima in the free energy landscape above some critical temperature.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2022-11-22T08:22:46.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9993" PostTypeId="1" AcceptedAnswerId="10066" CreationDate="2022-11-22T09:43:26.357" Score="4" ViewCount="211" Body="&lt;p&gt;I'm trying to run a quite complicated NEB optimization with (hopefully) one intermediate structure.&lt;/p&gt;&#xA;&lt;p&gt;But before losing time, I was wondering:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;how does ORCA treat that intermediate?&lt;/li&gt;&#xA;&lt;li&gt;does ORCA optimize both the CIs?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;On the ORCA forum, I wasn't able to find any of these answers&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="142" LastEditDate="2022-12-13T11:11:45.207" LastActivityDate="2022-12-13T11:11:45.207" Title="How does ORCA treat intermediates in Nudged Elastic Band (NEB) calculations" Tags="|geometry-optimization|orca|transition-state|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="9994" PostTypeId="2" ParentId="9987" CreationDate="2022-11-22T11:04:03.457" Score="5" Body="&lt;p&gt;To compile QE v.7.1 it requires m4 utility [1]. After installing m4, it went smoothly.&lt;/p&gt;&#xA;&lt;p&gt;[1] - &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/wikis/home&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/wikis/home&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Chamara&lt;/p&gt;&#xA;" OwnerUserId="6279" LastActivityDate="2022-11-22T11:04:03.457" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="9996" PostTypeId="1" CreationDate="2022-11-22T23:09:01.270" Score="5" ViewCount="269" Body="&lt;p&gt;I have a collection of pdb files (15), and I want to basically apply the same visualization settings on each one of them and render the image.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/I297P.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/I297P.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want the above settings, with a certain, resolution and scale for Bonds and VDW. The material is Goodsell for all of them.&lt;/p&gt;&#xA;&lt;p&gt;It is the same system, just in different configuraitons. All the chemical species present in the system are the same. How do I go about writing a tcl script which applies these to the system and all the atoms? Does anyone have an example where they have played with all of these properties in their tcl scripts?&lt;/p&gt;&#xA;&lt;p&gt;I would greatly value any advice you have for me!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2022-11-23T19:56:12.243" LastActivityDate="2022-11-23T19:56:12.243" Title="How to apply colors and graphics to VMD from Tcl?" Tags="|molecular-dynamics|visualization-software|vmd|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9997" PostTypeId="2" ParentId="9996" CreationDate="2022-11-22T23:38:14.007" Score="5" Body="&lt;p&gt;Take a look at the options in the &lt;code&gt;Menu --&amp;gt; File --&amp;gt; Log Tcl Commands to File&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9kkAN.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9kkAN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-11-22T23:38:14.007" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="9998" PostTypeId="1" CreationDate="2022-11-23T10:07:55.693" Score="4" ViewCount="328" Body="&lt;p&gt;How to carry out  Spin-projected band structure   using VASP?&#xA;I couldn't find any good source for this kind of plotting, is there a code for this kind of plotting ?&lt;/p&gt;&#xA;" OwnerUserId="4793" LastEditorUserId="4793" LastEditDate="2023-12-15T20:48:19.057" LastActivityDate="2023-12-16T02:51:46.417" Title="How to carry out Spin-projected band structure calculation" Tags="|density-functional-theory|vasp|band-structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="9999" PostTypeId="1" CreationDate="2022-11-23T11:15:53.163" Score="2" ViewCount="161" Body="&lt;p&gt;I successfuly installed g16 and gview6 under fedora linux , the issue  that I have is when I open gview after few seconds it stopped and a message is displayed on my screen &lt;a href=&quot;https://i.stack.imgur.com/j0nMF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/j0nMF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5" LastEditDate="2022-11-23T19:51:51.047" LastActivityDate="2022-11-23T19:51:51.047" Title="&quot;Gview.exe&quot; in Linux is not responding" Tags="|software|computational-chemistry|gaussian|visualization-software|" AnswerCount="0" CommentCount="9" ClosedDate="2023-05-28T16:16:18.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="10000" PostTypeId="1" AcceptedAnswerId="10004" CreationDate="2022-11-23T14:58:14.493" Score="6" ViewCount="224" Body="&lt;p&gt;I have recently started calculating transport properties using Transiesta and TBTrans. However, I have noticed that:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the TS.Contours.Eq.Pole value recommended is the default. In the last version of siesta, this is 1.5eV but the value printed by tselecs.sh is 2.5eV. Does anyone know where this difference comes from?&lt;/li&gt;&#xA;&lt;li&gt;In TBTrans options, the TBT.Contours default is 'line'. I have seen online that also 'neq' is a possibility. However, in the manual, I haven't found any explanation of the difference between the two. Does anyone have any documentation about this?&lt;/li&gt;&#xA;&lt;li&gt;Lastly, is there any recommendation on the values of TBT.T.Eig and the Eta (I guess 1e-4 should be enough)?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-01-27T15:45:59.293" Title="Transport calculations using Transiesta" Tags="|ab-initio-calculations|siesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10002" PostTypeId="1" AcceptedAnswerId="10475" CreationDate="2022-11-23T23:55:55.627" Score="4" ViewCount="147" Body="&lt;p&gt;I've recently begun experimenting with drawing molecules from smiles expressions for use in an educational website. I am looking for a way to create simple structural representations of various molecules in metabolic pathways (Kreb's cycle, Gluconeogenesis, etc) in what I believe is Fisher projections (or similar?), as is often encountered in text books, for example the molecule Citrate:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gqZmx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gqZmx.png&quot; alt=&quot;Citrate Lewis&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since I'm creating my website in python I tried using rdkit but so far have only been able to create drawings with 110° angles.&lt;a href=&quot;https://i.stack.imgur.com/NyQLM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NyQLM.png&quot; alt=&quot;Citrate 110&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The smiles formula I used here is courtesy of pubchem:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;C(C(=O)[O-])C(CC(=O)[O-])(C(=O)[O-])O&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Is there any open source tool (preferably in python) that I could use to create images of the Fischer projections? Or is there a &amp;quot;trick&amp;quot; of how to do this with rdkit? I would be grateful for any help and please excuse if I have botched any of the terminology in question. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6299" LastEditorUserId="6299" LastEditDate="2022-11-24T08:37:21.450" LastActivityDate="2023-02-25T07:20:15.767" Title="How to create png files of right angle Lewis notation" Tags="|python|rdkit|smiles|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10003" PostTypeId="1" CreationDate="2022-11-24T16:36:22.500" Score="3" ViewCount="164" Body="&lt;p&gt;How can I append my pipeline in Ovito?&lt;br /&gt;&#xA;I tried to append DislocationAnalysisModifier with Selected atom:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ovito.io import import_file &#xA;from ovito.modifiers import SelectTypeModifier, CommonNeighborAnalysisModifier, PolyhedralTemplateMatchingModifier, DislocationAnalysisModifier &#xA;from ovito.data import DislocationNetwork &#xA;&#xA;pipeline = import_file(&amp;quot;./0.dat&amp;quot;) &#xA;# Insert a CNA modifier to determine the structural type of each atom: &#xA;pipeline.modifiers.append(PolyhedralTemplateMatchingModifier()) &#xA;&#xA;# Apply the SelectTypeModifier to select all atoms of FCC and HCP type: pipeline.modifiers.append(SelectTypeModifier(&#xA;   operate_on = &amp;quot;particles&amp;quot;, &#xA;   property = &amp;quot;Structure Type&amp;quot;, &#xA;   types = { PolyhedralTemplateMatchingModifier.Type.FCC,&#xA;             PolyhedralTemplateMatchingModifier.Type.HCP } &#xA;   ))&#xA; &#xA;# Extract dislocation lines from a crystal with FCC:&#xA;&#xA;pipeline.modifiers.append(DislocationAnalysisModifier( &#xA;      only_selected = True)) &#xA;&#xA;data = pipeline.compute() &#xA;&#xA;total_line_length = data.attributes['DislocationAnalysis.total_line_length'] &#xA;&#xA;cell_volume = data.attributes['DislocationAnalysis.cell_volume'] &#xA;&#xA;print(&amp;quot;Dislocation density: %f&amp;quot; % (total_line_length / cell_volume)) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the output was:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;Traceback (most recent call last): &#xA;File &amp;quot;nn.py&amp;quot;, line 20, in &amp;lt;module&amp;gt; only_selected = True)) &#xA;AttributeError: Object type DislocationAnalysisModifier does not have an attribute named 'only_selected'. &#xA;ERROR: The Python script 'nn.py' has exited with an error. &#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I just want to know how to append &amp;quot;only_selected&amp;quot; in DislocationAnalysisModifier?&lt;/p&gt;&#xA;&lt;p&gt;Using &lt;code&gt;Ovito 3.0.0-dev155&lt;/code&gt;, with &lt;code&gt;Python 3.9.13&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6301" LastEditorUserId="24" LastEditDate="2022-11-25T12:33:28.623" LastActivityDate="2022-11-26T00:19:53.167" Title="Ovito dislocation analysis" Tags="|molecular-dynamics|molecular-modeling|lammps|ovito|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10004" PostTypeId="2" ParentId="10000" CreationDate="2022-11-24T20:28:26.173" Score="6" Body="&lt;ol&gt;&#xA;&lt;li&gt;On testing a few systems it showed to not depend too much on these two values. The reason is that typical systems use 300 K as the electronic temperature, and the number of poles for a fixed pole energy scales as &lt;span class=&quot;math-container&quot;&gt;$2N kT\pi\ge E_{pole} $&lt;/span&gt; with N being the lowest integer. So a lower energy means fewer integration points at the possible cost of accuracy.&lt;/li&gt;&#xA;&lt;li&gt;There is no difference. Just allowing users to use 2 words,should have been documented... Sorry.&lt;/li&gt;&#xA;&lt;li&gt;TBT.T.Eig should be an integer such that the lowest transmitting eigenchannels is approx 0, but it depends on what you are interested in. This number is only used to determine which transmission eigenvalues to save, and thus the result does not depend on the integer. If you take too high a number it will be cut to the maximum allowed. Do note that the disk space required for the output file depends on this number.&lt;/li&gt;&#xA;&lt;li&gt;The eta value should generally be as low as possible. A too high value will smear out the states a lot and will not require a dense energy grid. A too low value might require your energy grid to be very dense to capture the states. Recall that the Eta value is the smearing in a Lorentzian distribution. Note that this applies to both TranSiesta &lt;em&gt;and&lt;/em&gt; Tbtrans runs.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-01-27T15:45:59.293" LastActivityDate="2023-01-27T15:45:59.293" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10005" PostTypeId="1" AcceptedAnswerId="10007" CreationDate="2022-11-24T21:19:46.537" Score="3" ViewCount="84" Body="&lt;p&gt;This was inspired by a recent question &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9990/6302&quot;&gt;How is the zero energy defined for molecular orbitals?&lt;/a&gt; which made me pause to think if I understood clearly or not about the zero of energy of an MO.&lt;/p&gt;&#xA;&lt;p&gt;For example, I know you cannot compare the total electronic energy of one molecule to another (as computed by any conventional HF or DFT code for example) since the zero is different - since they have different numbers/types of nuclei.&lt;/p&gt;&#xA;&lt;p&gt;But is the same true of a MO energy, for example HOMO energy?  That post I linked above had an answer describing how the zero of MO energy is an infinitely diffuse orbital of a single electron, which I take to mean irrespective of how many nuclei the system has or where they are.    Consequently - is it possible to compare for example the HOMO energy of one molecule to the HOMO energy of some other molecule of different size, constituents, etc?  Whether that comparison is useful is another question, of course!&lt;/p&gt;&#xA;&lt;p&gt;(Energy differences like HOMO-LUMO gaps can be compared safely, that at least seems intuitive to me)&lt;/p&gt;&#xA;" OwnerUserId="6302" LastActivityDate="2022-11-25T06:37:51.430" Title="Can a MO energy computed from a HF or DFT calculation for one molecule be directly compared to that of another molecule?" Tags="|quantum-chemistry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10006" PostTypeId="1" CreationDate="2022-11-25T06:11:56.173" Score="4" ViewCount="30" Body="&lt;p&gt;I am currently looking to predict the structure of a material who we know exists under the conditions I am intrusted in(pressure), but the cif file does not exist. Now I have to first make the cif file, for which I need multiple parameters(like the lattice parameters and the octahedral tilts, in order to keep things simple lets say there is one structure parameter S). I created multiple structures with variations in S and optimized all of them with a variable cell, originally I planned of looking at the structure which would yield the lowest energy(so basically I would be looking at the global minima).&lt;/p&gt;&#xA;&lt;p&gt;But almost all the optimized structures have very similar values of S(~0.1 Angstrom), furthermore almost all the energy values are also quite similar(~10 meV variation). Which makes me think that why are there so many local minimas around one spot.&lt;/p&gt;&#xA;&lt;p&gt;Now although I do not have S but I have some other parameter(let's say T) and they indicate the structures with lower energy are closer to the true value of T. So would it better to perhaps take a weighted sum of the parameter S with energy. So something like&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S =  \frac{\sum_i S_i E_i}{\sum_i E_i}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;With this my chances of ending with a wrong structure would reduce. I would have a bit of an average solution but that should have a lesser risk factor of being wrong perhaps? Like if I am not exactly at the global minima.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2022-11-30T14:40:03.213" Title="Predicting parameters by taking a weighted average of multiple possible structures with energy rather than the structure with least energy" Tags="|geometry-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10007" PostTypeId="2" ParentId="10005" CreationDate="2022-11-25T06:37:51.430" Score="4" Body="&lt;p&gt;Yes, orbital energies can be compared amongst different molecules.&lt;/p&gt;&#xA;&lt;p&gt;Suppose you have two molecules, A and B, and you want to compare their HOMO levels. Now consider the supermolecule consisting of A and B separated by an infinite distance, and suppose that there is no electron transfer between the molecules*. Then the HOMO levels of A and B are both occupied orbital levels of the supermolecule, although only one of them remains the HOMO, while the other becomes a more deeply buried occupied orbital**. Since you already know that the different orbitals of the same system can be compared, this proves that orbitals of different molecules can be compared. This reasoning works equally well for all orbitals.&lt;/p&gt;&#xA;&lt;p&gt;Another way to understand this is to observe that the HOMO level is related to ionization potentials, via the Koopmans' and Janak's theorem for HF and DFT, respectively. Therefore the difference between the HOMO levels of molecules represents the difference of ionization potentials, which is of course a meaningful quantity. This argument does not work so well for LUMOs, and even less so for other orbitals.&lt;/p&gt;&#xA;&lt;p&gt;*Even if the electron transfer is energetically favorable, we can still converge to the state where the electron transfer has not taken place, and the state remains meaningful as an excited state of the system. This is reminiscent to the DeltaSCF method for charge transfer states.&lt;/p&gt;&#xA;&lt;p&gt;**When the HOMOs of A and B are degenerate, they can mix up to an arbitrary phase in the supermolecule. But in this case we can always choose the phase to be 0 or &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;, so that the supermolecule orbitals remain localized on the respective molecules.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2022-11-25T06:37:51.430" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10008" PostTypeId="1" AcceptedAnswerId="10057" CreationDate="2022-11-25T07:24:42.780" Score="4" ViewCount="139" Body="&lt;p&gt;I would like to find a robust way to compute formation energies of perovskites from their precursors in solution at the DFT level of theory. I have been looking at the literature and I have only been able to find approaches in which the authors use the chemical potential of the different elements (e.g. for &lt;span class=&quot;math-container&quot;&gt;$\ce{CsPbI3}$&lt;/span&gt; the chemical potentials of Cs, Pb and I in solid or vapour phases). Is there any approach consistent on considering reactions such as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ce{2 PbI_{2} + 2 HA -&amp;gt; H_{2}PbI_{4} + PbA_{2}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ce{H_{2}PbI_{4} + CsM -&amp;gt; CsPbI_{3} + HI + MH}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\ce{HA}$&lt;/span&gt; is an acid and &lt;span class=&quot;math-container&quot;&gt;$\ce{CsM}$&lt;/span&gt; is a precursor compound. Then considering this reactions, how would you calculate the formation energy of the resulting &lt;span class=&quot;math-container&quot;&gt;$\ce{CsPbI3}$&lt;/span&gt; perovskite? I do have the chemical potentials and total energies of the different compounds from the reactions and also of the bulk perovskite phase.&lt;/p&gt;&#xA;" OwnerUserId="3382" LastEditorUserId="7" LastEditDate="2022-11-27T14:36:29.697" LastActivityDate="2022-12-22T15:17:59.877" Title="Perovskite formation energy from precursors" Tags="|reaction-mechanism|perovskites|formation-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10009" PostTypeId="1" CreationDate="2022-11-25T07:40:55.603" Score="2" ViewCount="57" Body="&lt;p&gt;Basically, I'm working on spherical colloids and investigating the phase behavior of these monodisperse colloids using Monte Carlo simulations (Fortran 77 coding). Now I want to introduce size polydispersity expressed in the gaussian distribution model into my code. Can anyone help?&#xA;I need the size polydispersity formula and how to write it using f77&lt;/p&gt;&#xA;" OwnerUserId="6304" LastEditorUserId="6304" LastEditDate="2022-11-25T09:14:23.990" LastActivityDate="2022-11-25T09:14:23.990" Title="how to incorporate size polydispersity in colloidal suspensions" Tags="|molecular-modeling|mathematical-modeling|monte-carlo|atomic-simulation-environment|fortran|" AnswerCount="0" CommentCount="7" ClosedDate="2023-05-06T02:20:27.320" ContentLicense="CC BY-SA 4.0" />
  <row Id="10010" PostTypeId="2" ParentId="10003" CreationDate="2022-11-25T13:07:00.133" Score="2" Body="&lt;p&gt;While it seems like other modifiers can accept this argument, from &lt;a href=&quot;https://www.ovito.org/docs/current/python/modules/ovito_modifiers.html#ovito.modifiers.DislocationAnalysisModifier&quot; rel=&quot;nofollow noreferrer&quot;&gt;the ovito python docs&lt;/a&gt;, it looks like &lt;code&gt;only_selected&lt;/code&gt; needs to be specified as a property.&lt;/p&gt;&#xA;&lt;p&gt;Try changing that line to something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DAM = DislocationAnalysisModifier()&#xA;DAM.only_selected = True&#xA;pipeline.modifiers.append(DAM)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2022-11-26T00:19:53.167" LastActivityDate="2022-11-26T00:19:53.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10011" PostTypeId="1" AcceptedAnswerId="10063" CreationDate="2022-11-25T15:10:04.150" Score="5" ViewCount="90" Body="&lt;p&gt;I have noticed some difficulties in converging Transiesta calculations when including empty orbitals in the basis set, particularly when a non-zero bias is applied.&#xA;In particular, I have tried to simply converge graphene structure and I&#xA;could easily converge the calculation by excluding the empty orbitals. Including them, I could still converge zero-bias case but not the non-zero cases. Since I used quite long tails, I extended the divide region to approx. 6/7 layers. I understand that in the case of graphene, the energy window of interest is well described even by excluding these orbitals. However, I will include some atoms in which I included empty orbitals to properly describe their pristine band structure (in particular, B and N and I reproduced hBN band structure).&#xA;My question is: is it advised not to include empty orbitals in transiesta calculations?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2022-11-30T15:01:31.217" LastActivityDate="2022-12-08T11:46:03.537" Title="Empty orbitals in Transiesta" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10014" PostTypeId="1" AcceptedAnswerId="10020" CreationDate="2022-11-27T11:32:56.093" Score="4" ViewCount="474" Body="&lt;p&gt;I have tried to run some calculations on transiesta/tbtrans with a non-zero voltage. I started with a zero voltage calculation and copied the .TSDE file to run a calculation with V=0.25. However, I still receive the error:&#xA;You have to calculate the 0 V and re-use the TSDE from that calculation.&#xA;So, should the calculations be executed like this:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;electrode to produce the TSHS for the bulk electrode (siesta --electrode).&lt;/li&gt;&#xA;&lt;li&gt;Use the TSHS electrode file to calculate the 0V TSDE+TSHS scattering region with transiesta (siesta executable).&lt;/li&gt;&#xA;&lt;li&gt;Use the TSHS and TSDE scattering region files (and the electrode TSHS) to compute the 'final' properties at non-zero voltage (only tbtrans executable).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Lastly, even if the tbtrans calculation finishes without errors, no 0_Normal_exit file is produced?&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="887" LastEditDate="2022-11-28T12:09:19.447" LastActivityDate="2022-12-07T12:11:00.433" Title="What is the transiesta+tbtrans procedure?" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10015" PostTypeId="2" ParentId="8672" CreationDate="2022-11-27T18:38:02.870" Score="4" Body="&lt;p&gt;The difficulty lies in the fact that the magnetic dipole &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}$&lt;/span&gt; and electric quadrupole &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt; operators are ill-defined for periodic systems due to the unbound position operator &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt;. However, with a sum over states formulation, the matrix elements of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{M}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{Q}$&lt;/span&gt; can be calculated now. &lt;a href=&quot;https://arxiv.org/abs/2211.09845&quot; rel=&quot;nofollow noreferrer&quot;&gt;The VASP implementation&lt;/a&gt; of the OR and CD calculations have appeared within the independent particle approximation.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2022-11-27T18:38:02.870" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10016" PostTypeId="1" AcceptedAnswerId="10017" CreationDate="2022-11-27T18:51:33.603" Score="4" ViewCount="609" Body="&lt;p&gt;I wish to calculate the distance of all the atoms from a particular atom(atom A) in my cell. But I also want to include the atoms that might lie just beyond the periodic unit cell boundary.( In figure, besides distance of A with 1,2,3 i also want distance with 4). I am using get_distance from ASE, but it will not include atom outside(atom 4) the boundary. I am printing the nearest atoms to A to confirm this. What can be done to consider this?&lt;a href=&quot;https://i.stack.imgur.com/v6R5r.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/v6R5r.jpg&quot; alt=&quot;Example structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code I am using is(Atom A is &amp;quot;Cu&amp;quot; and atom 1,2,3,4 is &amp;quot;O&amp;quot;) :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase.io import read,write&#xA;from ase.geometry import get_distances&#xA;from ase.neighborlist import NeighborList,natural_cutoffs,build_neighbor_list,first_neighbors,get_connectivity_matrix,neighbor_list&#xA;&#xA;structure= read(&amp;quot;1985check.cif&amp;quot;)&#xA;&#xA;atom_count=structure.get_chemical_symbols()&#xA;#atom_count=supercell.get_chemical_symbols()&#xA;&#xA;for i in range(len(atom_count)):&#xA;        if(atom_count[i]=='Cu'):&#xA;            index=i&#xA;            break&#xA;&#xA;neighbor_list=[]&#xA;j_list=[]&#xA;for j in range(len(atom_count)):&#xA;       &#xA;          if(j!=index):  &#xA;            neighbor_list.append(structure.get_distance(index,j,mic=True))&#xA;            j_list.append(j)&#xA; &#xA;keys= sorted(range(len(neighbor_list)), key=lambda k: neighbor_list[k])    &#xA;&#xA;check_list=[]&#xA;for c in range(len(keys)):&#xA;        #print(structure.get_chemical_symbols()[j_list[keys[c]]])&#xA;        check_list.append(structure.get_chemical_symbols()[j_list[keys[c]]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output of check_list is ['O','O','O', 'Cu'...] while I expect ['O','O','O', &lt;strong&gt;'O'&lt;/strong&gt;...]&lt;/p&gt;&#xA;&lt;p&gt;The cif file is &lt;a href=&quot;https://www.dropbox.com/s/ucro7otg8dn4doy/1985check.cif?dl=0&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.dropbox.com/s/ucro7otg8dn4doy/1985check.cif?dl=0&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6313" LastEditorUserId="6313" LastEditDate="2022-11-27T20:13:13.697" LastActivityDate="2022-11-28T14:06:54.500" Title="Measuring distance with ASE" Tags="|python|crystallography|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10017" PostTypeId="2" ParentId="10016" CreationDate="2022-11-28T08:44:02.330" Score="4" Body="&lt;p&gt;I think the answer to your problem lies in the CIF file. With reference to the figure below, two out of four of the O neighbors of Cu are actually &amp;quot;the same atom&amp;quot; (only one of them is present as an entry in the unit cell and the other is a periodic image of the one in the unit cell). ASE's &lt;code&gt;.get_distance()&lt;/code&gt; and &lt;code&gt;mic=True&lt;/code&gt; (Minimum Image Convention) works as expected, by only giving you the minimum distance from the Cu atom chosen to that O atom (considering the O atom in the simulation cell and its periodic image), or else it would be double counting to get the results you expect.&lt;/p&gt;&#xA;&lt;p&gt;To get the results you were expecting, you could create a supercell with that structure and use your previous code, picking a Cu atom in the center of the cell so that it will definitely have all four nearest neighbor O atoms in the simulation cell.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GaawC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GaawC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="6131" LastEditDate="2022-11-28T14:06:54.500" LastActivityDate="2022-11-28T14:06:54.500" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10018" PostTypeId="1" CreationDate="2022-11-28T08:56:44.893" Score="3" ViewCount="107" Body="&lt;p&gt;Let's think we want to do a Gaussian optimisation. We first download the pdb coordinates of the query protein from the protein data bank. Then using Chimera software we add hydrogen and charge for the protein and save the file in .pdb format. And, we open this .pdb file using GaussView software define the basis set for the optimisation and save t as a gaussian input file (.gjf). This input file contains coordinates and the connectivity of the atoms of the protein.&#xA;&lt;strong&gt;My question is in this method is it NECESSARY to add charge to the protein and isn't it necessary to have the connectivity of atoms in the .gjf file?&lt;/strong&gt;&#xA;When I started a gaussian job it terminated with an error &lt;code&gt;QPErr --- A syntax error was detected in the input line. 1 3 1.0 2 1.0 4 1.0 5 1.0&lt;/code&gt; Then I deleted all the lines that give connectivity and restarted the gaussian job. The job completed without an error. I thought that it is necessary to give the connectivity of the atoms in .gjf file. Am I wrong because my gaussian job completed even though I removed connectivity.&lt;/p&gt;&#xA;" OwnerUserId="6239" LastActivityDate="2022-12-09T12:00:42.230" Title="Is it necessary to give connectivity and charge of a molecule to start a Gaussian job?" Tags="|gaussian|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10019" PostTypeId="1" CreationDate="2022-11-28T10:23:27.607" Score="3" ViewCount="162" Body="&lt;p&gt;I started to optimise a protein. But due to a power failure the process terminated before completion. So I need to restart my calculation. There were several suggestions on using &lt;code&gt;opt=restart&lt;/code&gt;. I tried that but it did not work. What I did was, saved the interrupted Gaussian output as a new input file. Then opened the new input file in Gaussian09 and kept everything above coordinates section as it was except &lt;strong&gt;opt&lt;/strong&gt; in the route section. I changed &lt;strong&gt;opt&lt;/strong&gt; in to &lt;strong&gt;opt=restart&lt;/strong&gt; and gave the run but this did not work.&#xA;Can anyone please tell me what is the mistake? Or is my method wrong?&#xA;&lt;a href=&quot;https://drive.google.com/drive/folders/14hV4kxh_hwFZbdt4y1eUFuGhGq7hWgc0?usp=share_link&quot; rel=&quot;nofollow noreferrer&quot;&gt;Link to the gaussian files&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="6239" LastEditDate="2022-11-29T06:00:11.660" LastActivityDate="2022-11-29T06:00:11.660" Title="How can we restart an interrupted Gaussian job?" Tags="|gaussian|" AnswerCount="0" CommentCount="3" ClosedDate="2023-06-14T01:11:20.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="10020" PostTypeId="2" ParentId="10014" CreationDate="2022-11-28T12:08:55.140" Score="3" Body="&lt;p&gt;You got it a bit wrong.&lt;/p&gt;&#xA;&lt;h2&gt;TranSiesta&lt;/h2&gt;&#xA;&lt;p&gt;This program (a sub-module in Siesta) self-consistently solves the NEGF equations to calculate the system at a finite bias. Upon self-consistency, the Siesta program will write out the Hamiltonian under the effect of the bias as given in the input file.&lt;br /&gt;&#xA;This effectively means that for each bias-point one needs to self-consistently solve the NEGF equations to obtain the &lt;em&gt;true&lt;/em&gt; electronic structure for a given bias point.&lt;/p&gt;&#xA;&lt;p&gt;Since the electrodes are in equilibrium (even under finite bias) one can use the same electrode Hamiltonian for &lt;em&gt;all&lt;/em&gt; bias points, by definition!&lt;/p&gt;&#xA;&lt;h2&gt;TBtrans&lt;/h2&gt;&#xA;&lt;p&gt;This program can calculate elastic transport by inputting the electronic structure of the electrodes (still under equilibrium) and the device region for a given bias point. If the electronic structure for the device region is solved for a given bias &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, then TBtrans can &lt;em&gt;only&lt;/em&gt; correctly calculate the transport for that same bias &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, if you give TBtrans any &lt;span class=&quot;math-container&quot;&gt;$V'\neq V$&lt;/span&gt; your calculation will be wrong.&lt;/p&gt;&#xA;&lt;p&gt;What TBtrans &lt;em&gt;can&lt;/em&gt; provide is a way to interpolate the electronic structure of several bias-points (several TSHS files calculated with TranSiesta for different bias points) and thus give an estimate of the true transport characteristics for a bias point where the electronic structure has not been explicitly calculated. This interpolation should of course be done with care and before-hand knowledge of the electronic structure should give you details about adequate interpolation ranges. Say for one system you can interpolate in a range of 0.5 V, whereas for another system, you can only interpolate in a range of 0.25 V.&lt;/p&gt;&#xA;&lt;p&gt;TBtrans does &lt;em&gt;not&lt;/em&gt; create the &lt;code&gt;0_NORMAL_EXIT&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;h2&gt;The procedure&lt;/h2&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculate the electrode electronic structure&lt;/li&gt;&#xA;&lt;li&gt;Calculate the 0 bias case using TranSiesta&lt;/li&gt;&#xA;&lt;li&gt;Calculate any non-bias cases using TranSiesta and by using the &lt;em&gt;closests&lt;/em&gt; bias point previously calculated using TranSiesta (copy that TSDE file). Be sure to set the flag: &lt;code&gt;DM.UseSaveDM T&lt;/code&gt; in your input.&lt;/li&gt;&#xA;&lt;li&gt;Finally, calculate the transmission for the bias points done in steps 2 and 3&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2022-12-07T12:11:00.433" LastActivityDate="2022-12-07T12:11:00.433" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10021" PostTypeId="1" CreationDate="2022-11-28T12:31:46.157" Score="6" ViewCount="215" Body="&lt;p&gt;I am currently trying to reproduce the results of [1], wherein they have pressurized &lt;span class=&quot;math-container&quot;&gt;$\ce{Cs_2SnI_6}$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$20$&lt;/span&gt; GPa.&lt;/p&gt;&#xA;&lt;p&gt;I ran calculations with PBEsol and used the PSTRESS tag in order to optimize the cubic structure. But even though a similar trend is followed, I observe a difference of &lt;span class=&quot;math-container&quot;&gt;$0.2$&lt;/span&gt;Å  between the experimental data and the simulated one. I will also attach my INCAR file, please let me know if there is anything wrong with it.&lt;/p&gt;&#xA;&lt;h3&gt;Results&lt;/h3&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;PSTRESS&lt;/th&gt;&#xA;&lt;th&gt;PBESol&lt;/th&gt;&#xA;&lt;th&gt;PBESol+D3&lt;/th&gt;&#xA;&lt;th&gt;Experimental&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;0&lt;/td&gt;&#xA;&lt;td&gt;11.5661&lt;/td&gt;&#xA;&lt;td&gt;11.5379&lt;/td&gt;&#xA;&lt;td&gt;12.0655(materials project)/11.65 (other papers)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;0.2&lt;/td&gt;&#xA;&lt;td&gt;11.5046&lt;/td&gt;&#xA;&lt;td&gt;11.4745&lt;/td&gt;&#xA;&lt;td&gt;11.647&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3.1&lt;/td&gt;&#xA;&lt;td&gt;10.9858&lt;/td&gt;&#xA;&lt;td&gt;10.9796&lt;/td&gt;&#xA;&lt;td&gt;11.157&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;7.2&lt;/td&gt;&#xA;&lt;td&gt;10.6099&lt;/td&gt;&#xA;&lt;td&gt;10.5977&lt;/td&gt;&#xA;&lt;td&gt;10.801&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&lt;h3&gt;INCAR&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt; SYSTEM   =  Perovskite&#xA;&#xA;# Electronic minimization&#xA;  ISTART  = 0&#xA;  ICHARG  = 2&#xA;  IALGO    = 48&#xA;  PREC= Normal&#xA;  ENCUT   = 360&#xA;  NELM    = 100 &#xA;  LREAL   = Auto.&#xA;  EDIFF   = 1E-6&#xA;  EDIFFG  =-0.03&#xA;  LWAVE   =.FALSE.&#xA;  IVDW    = 11&#xA;&#xA;# Ionic minimization&#xA;  NSW     = 100&#xA;  IBRION  = 2&#xA;  ISIF    = 3&#xA;  POTIM   = 0.5&#xA;  PSTRESS = 31&#xA;&#xA;# Exchange correlational functional &#xA;  GGA = PS&#xA;&#xA; ISMEAR   = 0&#xA; SIGMA    = 0.026&#xA;&#xA;  NCORE = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Bounos, G.; Karnachoriti, M.; Kontos, A. G.; Stoumpos, C. C.; Tsetseris, L.; Kaltzoglou, A.; Guo, X.; Lü, X.; Raptis, Y. S.; Kanatzidis, M. G.; Falaras, P. Defect Perovskites under Pressure: Structural Evolution of Cs2SnX6 (X = Cl, Br, I). The Journal of Physical Chemistry C, 2018, 122, 24004–24013. &lt;a href=&quot;https://doi.org/10.1021/acs.jpcc.8b08449&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acs.jpcc.8b08449&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="7" LastEditDate="2022-11-28T19:01:38.077" LastActivityDate="2022-11-28T19:01:38.077" Title="Optimizing geometry of materials under pressure using VASP" Tags="|vasp|geometry-optimization|" AnswerCount="0" CommentCount="5" ClosedDate="2023-05-28T16:16:11.317" ContentLicense="CC BY-SA 4.0" />
  <row Id="10022" PostTypeId="2" ParentId="6143" CreationDate="2022-11-29T09:15:54.307" Score="2" Body="&lt;p&gt;Another way is to use Amber file with NAMD!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://ambermd.org/tutorials/advanced/tutorial8/loop3.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;Amber tleap&lt;/a&gt; is more user friendly, you can set the box size with &lt;code&gt;box mol {x y z}&lt;/code&gt;. The only difference is you need to use top and crd files, not psf and pdb, in the NAMD configure file.&lt;/p&gt;&#xA;" OwnerUserId="5897" LastEditorUserId="7" LastEditDate="2022-12-08T14:01:54.863" LastActivityDate="2022-12-08T14:01:54.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10023" PostTypeId="1" CreationDate="2022-11-30T07:19:30.803" Score="2" ViewCount="48" Body="&lt;p&gt;Can anyone help me understand what is Phonon Angular Momentum? How does it affect thermal properties? Any relevant books and papers are welcome, if you have suggestions.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2022-11-30T07:19:30.803" Title="Phonon Angular Momentum" Tags="|phonons|phonopy|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10025" PostTypeId="1" AcceptedAnswerId="10031" CreationDate="2022-11-30T10:00:58.900" Score="3" ViewCount="128" Body="&lt;p&gt;I am planning to do some work using grand-canonical DFT, I believe that the Fermi energy depends on the pseudo-potentials used (like the total energy).&lt;/p&gt;&#xA;&lt;p&gt;My understanding is that the Fermi energy has to be referenced to a specific level, for example the vacuum level (workfunction) for it to be comparable in plane-wave DFT context.&lt;/p&gt;&#xA;&lt;p&gt;With methods like ESM, the Fermi energy is automatically referenced to the vacuum level, and different pseudo-potentials should give the same value (with different levels of accuracy of course). Thus, in this case, fixing the Fermi energy to a specific value makes sense (4.44 V abs value of the SHE typically). But how one would do for a bulk material?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="5" LastEditDate="2022-11-30T15:34:00.760" LastActivityDate="2022-11-30T20:05:23.347" Title="In a plane-wave code, does the Fermi energy depend on the pseudopotentials used?" Tags="|density-functional-theory|plane-waves|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10026" PostTypeId="1" CreationDate="2022-11-30T13:55:23.343" Score="3" ViewCount="142" Body="&lt;p&gt;Is there any way we can calculate thermal conductivity in GROMACS? I can see the equilibrium Green-Kubo method algorithm, or non-equilibrium Muller-Plathe algorithm implemented in LAMMPS, but don't think either of these algorithms is implemented in GROMACS. Any suggestions? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="24" LastEditDate="2022-11-30T14:28:28.680" LastActivityDate="2022-11-30T14:28:28.680" Title="Thermal conductivity in GROMACS?" Tags="|molecular-dynamics|gromacs|thermal|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-14T01:11:43.663" ContentLicense="CC BY-SA 4.0" />
  <row Id="10027" PostTypeId="2" ParentId="10006" CreationDate="2022-11-30T14:40:03.213" Score="4" Body="&lt;p&gt;If there are really many closely lying minima, this may mean that the material doesn't really have a structure as several of the minima will be populated at room temperature of around 26 meV. One should then look at ensemble averages, instead. For instance, the Boltzmann probability &lt;span class=&quot;math-container&quot;&gt;$p_i$&lt;/span&gt; of finding the system in the state &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ p_i =  \exp (-E_i/k_BT)/ \left[\sum_j \exp (-E_j/k_BT)\right] $$&lt;/span&gt;&#xA;and you might compute observables &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}$&lt;/span&gt; as weighted averages of the state-specific values &lt;span class=&quot;math-container&quot;&gt;$\mathcal{O}_i$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \langle \mathcal{O} \rangle = \sum_i p_i \mathcal{O}_i $$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-11-30T14:40:03.213" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10028" PostTypeId="1" CreationDate="2022-11-30T15:34:31.293" Score="4" ViewCount="121" Body="&lt;p&gt;I am interested in geometry optimization at the CCSD(T) or DF-CCSD(T) level, with MRCC.&#xA;The calculation, however, crashes when executing prop:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ************************ 2022-11-30 15:42:32 *************************&#xA; Executing prop...&#xA;&#xA; Allocation of 500.0 Mbytes of memory...&#xA;&#xA; Number of integral batches:                      1&#xA;&#xA; Fatal error in exec prop.&#xA; Program will stop.&#xA;&#xA; ************************ 2022-11-30 15:42:32 *************************&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;giving the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;forrtl: severe (24): end-of-file during read, unit 26, file /data/test-opt-mrcc/CCDENSITIES&#xA;Image              PC                Routine            Line        Source&#xA;prop               0000000005C2DC58  Unknown               Unknown  Unknown&#xA;prop               0000000005C6486A  Unknown               Unknown  Unknown&#xA;prop               000000000045DB46  Unknown               Unknown  Unknown&#xA;prop               0000000000405AD5  Unknown               Unknown  Unknown&#xA;prop               0000000000400DF2  Unknown               Unknown  Unknown&#xA;prop               0000000005D12DF9  Unknown               Unknown  Unknown&#xA;prop               0000000000400CCA  Unknown               Unknown  Unknown&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I suspect that it is because of the &lt;code&gt;ccprog=ccsd&lt;/code&gt; option, i.e., one can do geometry optimization only when &lt;code&gt;ccprog=mrcc&lt;/code&gt;. Is that the case?&lt;/p&gt;&#xA;&lt;p&gt;A test input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# CCSD geometry optimization for water with the cc-pVDZ basis set&#xA;basis=cc-pVDZ&#xA;calc=ccsd(t)&#xA;ccprog=ccsd&#xA;mem=500MB&#xA;gopt=full&#xA;&#xA;unit=bohr&#xA;geom&#xA;H&#xA;O 1 R1&#xA;H 2 R1 1 A&#xA;&#xA;R1=2.00000000000&#xA;A=104.2458898548&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6296" LastEditorUserId="5" LastEditDate="2022-12-03T12:37:40.397" LastActivityDate="2022-12-03T12:37:40.397" Title="Crash of DF-CCSD or DF-CCSD(T) geometry optimization (MRCC package)" Tags="|ab-initio-calculations|geometry-optimization|coupled-cluster|mrcc|cfour|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10029" PostTypeId="1" CreationDate="2022-11-30T16:11:32.357" Score="5" ViewCount="44" Body="&lt;p&gt;I have a combined mW water and FCC111 Aluminium substrate model to study ice nucleation and adhesion. This simulation is performed at 251K which is the temperature for the actual real-world experiment. At the end of this simulation, I write a data file for the end structure.&lt;/p&gt;&#xA;&lt;p&gt;My question is that - can this end structure/data file obtained from the previous simulation be reused in a separate simulation where I simply initialise it at 268K directly in NVT ensemble? Or should I initialise the structure at 251K and slowly raise the temperature to 268K before performing other operations (application of tensile force etc.)&lt;/p&gt;&#xA;&lt;p&gt;Any help or insight on this is appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6323" LastActivityDate="2022-11-30T16:11:32.357" Title="Can an atomic structure created after a simulation performed at 251K in LAMMPS be initialized directly to 268K in a separate simulation?" Tags="|molecular-dynamics|molecular-modeling|lammps|nucleation|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-28T16:15:58.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="10030" PostTypeId="2" ParentId="8932" CreationDate="2022-11-30T17:09:09.590" Score="3" Body="&lt;p&gt;MEAMfit can fit LAMMPS-compatible RF-MEAM potentials to either VASP or CASTEP data. (There's also support for Quantum Espresso PWscf, but this is still in development). It is open-source: &lt;a href=&quot;https://gitlab.com/AndyDuff123/meamfit&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/AndyDuff123/meamfit&lt;/a&gt; . Full disclosure though, I am the author of that software.&lt;/p&gt;&#xA;" OwnerUserId="6324" LastActivityDate="2022-11-30T17:09:09.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10031" PostTypeId="2" ParentId="10025" CreationDate="2022-11-30T19:50:51.880" Score="2" Body="&lt;p&gt;Your understanding is correct; you need to have a well-defined reference level for the Fermi level if you want to make comparisons between different systems (for example, comparing work functions of different surfaces for the same metal or different metals). In addition to subtle variations due to pseudopotential selection, you'll also have different Fermi level / work function predictions depending on how many layers of material you include, how many layers you are freezing, whether you are using a symmetric or asymmetric slab, etc. For example, for metals, it's well-known that the work function converges somewhat slowly in an oscillatory fashion with respect to layer thickness.&lt;/p&gt;&#xA;&lt;p&gt;For condensed phases with 3D periodicity, you don't have a well-defined reference level. You also cannot have a bulk system that has a finite charge; it's electrostatic potential energy is undefined (in reciprocal space, the electrostatic potential diverges at the gamma point) since you'd have a periodic collection of charged cells. Most planewave DFT codes will insert a uniform background charge (equivalent to setting the electrostatic potential at the gamma point to zero) to cancel the net charge to avoid this and still enable the calculation to converge. For these reasons, you couldn't build an electrochemical model for a bulk (3D periodic) structure or easily use a GC-SCF method.&lt;/p&gt;&#xA;&lt;p&gt;But essentially, the work function and electrode potential are inherently surface-dependent properties because they require the presence of an interface to even define them in the first place. You'd also need to include some sort of compensating charge distribution (like an electrical double layer) to keep the system at a net neutral charge.&lt;/p&gt;&#xA;" OwnerUserId="5935" LastEditorUserId="5935" LastEditDate="2022-11-30T20:05:23.347" LastActivityDate="2022-11-30T20:05:23.347" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10032" PostTypeId="1" CreationDate="2022-11-30T22:51:40.923" Score="2" ViewCount="107" Body="&lt;p&gt;Recently I am learning VASP. I am trying to see different properties of two-level system (TLS). For example, checking amorphous silicon as a test case (along with it's vacancy structures as well). From these structures, I have the following information for different structures so far:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Stress tensors: ii, ij, ik, ji, jj, jk, ki, kj, kk &#xA;&#xA;Elastic tensors: C_11, C_22, C_33, C_12, C_13, C_23, C_44, C_55, C_66,  C_16, C_26, C_36, C_46, C_56, C_14, C_15, C_25, C_45&#xA;&#xA;Volume&#xA;&#xA;Total Energy&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, it would be great to get your detailed suggestion about how can I calculate an elastic dipole and strain field from a TLS?&lt;/p&gt;&#xA;&lt;p&gt;More specifically, this would be the difference in the strain field between the two different atomic configurations?  Do we need just the elastic dipole difference of the TLS and the elastic constants of the material? Or do we need something else?&lt;/p&gt;&#xA;&lt;p&gt;Any detailed theoretical idea (as well as any software suggestions including their tutorials - if needed) and/or coding idea would be greatly appreciated - as I am new in learning this. Thanks in advance for your cooperation.&lt;/p&gt;&#xA;&lt;p&gt;This paper might be helpful to get answers for the above (though I have not been able to figure it out from it): &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0927025618300673&quot; rel=&quot;nofollow noreferrer&quot;&gt;Paper&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5723" LastEditDate="2022-12-02T07:50:48.443" LastActivityDate="2022-12-05T05:41:42.227" Title="Calculating strain field. Need idea on how to do that" Tags="|vasp|dipole|elasticity|stress-strain|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-09T22:54:07.227" ContentLicense="CC BY-SA 4.0" />
  <row Id="10033" PostTypeId="2" ParentId="9713" CreationDate="2022-12-01T07:23:53.113" Score="6" Body="&lt;p&gt;As mentioned above, there is practically a myriad of free working quantum chemistry codes with implementations of Hartree-Fock and Density-Functional Theory.&lt;/p&gt;&#xA;&lt;p&gt;As a counter-example to the code mentioned above, I want to highlight a recent quantum chemistry code:&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;QUantum Interaction Computational Kernel (QUICK)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It's FOSS (Free and Open Source Software), meaning you can become a developer!&lt;/li&gt;&#xA;&lt;li&gt;It's easy to use, and &lt;em&gt;made for speed&lt;/em&gt;. It's a good code for large-scale and multi-scale quantum chemistry, with a niche but growing community.&lt;/li&gt;&#xA;&lt;li&gt;The code is young but is made &amp;quot;the right way&amp;quot;, meaning that at it's core is the acceleration of electron repulsion integrals (ERIs).&lt;/li&gt;&#xA;&lt;li&gt;It has MPI parallelization for CPU platforms&lt;/li&gt;&#xA;&lt;li&gt;Massive parallel GPU acceleration through CUDA for NVIDIA GPUs&lt;/li&gt;&#xA;&lt;li&gt;Multi-GPU support via MPI + CUDA, also across multiple compute nodes&lt;/li&gt;&#xA;&lt;li&gt;HF, UHF, DFT and QM/MM (with some new developments soon... stay tuned!)&lt;/li&gt;&#xA;&lt;li&gt;Makes use of &lt;a href=&quot;https://www.softxjournal.com/article/S2352-7110(17)30060-2/fulltext&quot; rel=&quot;noreferrer&quot;&gt;LIBXC&lt;/a&gt;, so you can use your favorite functional!&lt;/li&gt;&#xA;&lt;li&gt;Supports DFT-D (e.g. can perform B3LYP-D3(BJ) calculations, wB97X-D)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Here is a sample DFT input file for pSB3 from the QUICK test suite:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; DFT LIBXC=HYB_GGA_XC_B3LYP BASIS=6-31G DIPOLE CUTOFF=1.0d-10 DENSERMS=1.0d-6 CHARGE=+1 &#xA; C -2.74724163 -0.83655480  0.85891890&#xA; C -1.45690243 -0.47166414  0.99917288&#xA; C -0.62772841 -0.22145348 -0.15324144&#xA; C  0.68944541  0.15260156 -0.20171919&#xA; C  1.48823343  0.36448923  0.95078019&#xA; N  2.73140279  0.71794292  0.90370531&#xA; H  1.15299007  0.29662735 -1.16123028&#xA; H -1.11028708 -0.34629454 -1.10667741&#xA; H  1.08266370  0.23672479  1.93583665&#xA; H -1.04825008 -0.36804581  1.98774361&#xA; H  3.26866760  0.85959058  1.73675486&#xA; H  3.20838915  0.86445595  0.03379823&#xA; H -3.36885475 -1.02411938  1.71303219&#xA; H -3.20113376 -0.95331433 -0.10812450&#xA;   #TOTAL_ENERGY=  -249.766901607&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;This input file calls the LIBXC version of B3LYP; there is a native B3LYP functional as well in QUICK.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Easy to git ; easy to compile; easy to run.&#xA;If you're interested in looking &amp;quot;under the hood&amp;quot;, the modules (e.g. one-electron integrals module) are well-documented and referenced. The DIIS algorithm is the default, and you can choose from several basis sets. It's pretty solid!&lt;/p&gt;&#xA;&lt;p&gt;You can get QUICK here:  &lt;a href=&quot;https://github.com/merzlab/QUICK&quot; rel=&quot;noreferrer&quot;&gt;QUICK GitHub&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Learn QUICK here with tutorials:  &lt;a href=&quot;https://quick-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;noreferrer&quot;&gt;QUICK user manual&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;DFT implementation paper in JCTC &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.0c00290&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;QM/MM implementation paper in JCIM &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jcim.1c00169&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Massive multi-GPU acceleration of HF and DFT&#xA;paper in JCTC &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jcim.1c00169&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I think QUICK is a nice code: easy to use, free and fast! Definitely check it out.&lt;/p&gt;&#xA;" OwnerUserId="175" LastActivityDate="2022-12-01T07:23:53.113" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10034" PostTypeId="1" AcceptedAnswerId="10037" CreationDate="2022-12-01T10:09:26.573" Score="8" ViewCount="949" Body="&lt;p&gt;I am trying to account for Vander waals correction in VASP. Now doing this for PBE is easy all one has to do is set &lt;code&gt;IVDW=11&lt;/code&gt; but the VASP webpage for &lt;a href=&quot;https://www.vasp.at/wiki/index.php/DFT-D3&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT-D3&lt;/a&gt; says that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Mind: The default values for the damping function parameters are available for the following functionals: PBE (GGA=PE), RPBE (GGA=RP), revPBE (GGA=RE) and PBEsol (GGA=PS). If another functional is used, the user has to define these parameters via the corresponding tags in the INCAR file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Furthermore they also specify that, among all of the parameters in the damping function, &lt;span class=&quot;math-container&quot;&gt;$s_{R,6}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$s_8$&lt;/span&gt; are the ones whose values depend upon the functional. But I can not find what value to choose when I am doing electronic calculations with HSE06. Considering that HSE06 is a combination of PBE and Exact coorelation, perhaps the value for PBE(default one) should work fine. But I am not sure!!&lt;/p&gt;&#xA;" OwnerUserId="5602" LastEditorUserId="7" LastEditDate="2022-12-01T13:47:10.707" LastActivityDate="2022-12-01T13:52:32.120" Title="VdW-D3 correction with HSE06 functional in VASP" Tags="|vasp|correlation-functions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10035" PostTypeId="1" AcceptedAnswerId="10036" CreationDate="2022-12-01T10:28:54.940" Score="6" ViewCount="477" Body="&lt;p&gt;From my understanding, programs like CCDC Mercury and VESTA are able to extract some information from imported .CIF files of molecules but then complete calculations to output a simulated X-ray diffraction pattern. Does anyone know the steps that CCDC Mercury takes to calculate the peak positions and the intensities? (From what I've read, some programs seem to use the molecule's structure factor or the Debye scattering formula.)&lt;/p&gt;&#xA;" OwnerUserId="6342" LastEditorUserId="6342" LastEditDate="2022-12-01T10:30:00.413" LastActivityDate="2022-12-02T11:06:04.923" Title="How are the simulated powder diffraction patterns calculated in CCDC Mercury?" Tags="|spectroscopy|vesta|cif|x-ray-diffraction|ccdc|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10036" PostTypeId="2" ParentId="10035" CreationDate="2022-12-01T11:33:12.570" Score="7" Body="&lt;p&gt;Program's website &lt;a href=&quot;https://www.ccdc.cam.ac.uk/support-and-resources/support/case/?caseid=20bb8eb9-edd5-4e73-9d98-8a8d9ebe762f&quot; rel=&quot;nofollow noreferrer&quot;&gt;has this question&lt;/a&gt; in FAQ, but it doesn't provide an answer, only refers to a standard textbook.&lt;/p&gt;&#xA;&lt;p&gt;The program doesn't use Debye's formula. This formula uses whole crystal (thousands or millions of atoms) as an input, it's computationally intensive and tends to produce wide peaks without Miller indices.&#xA;See &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/xrdebye.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;an example in ASE docs&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;CCDC Mercury calculates a pattern similarly to programs in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/142/how-to-calculate-diffraction-pattern-from-a-model-of-unit-cell&quot;&gt;this question&lt;/a&gt;.&#xA;In general:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Bragg's Law determines peak positions,&lt;/li&gt;&#xA;&lt;li&gt;intensity is calculated as |F&lt;sub&gt;hkl&lt;/sub&gt;|&lt;sup&gt;2&lt;/sup&gt; (squared structure factor) with additional corrections commonly used in powder diffraction,&lt;/li&gt;&#xA;&lt;li&gt;the width and shape of peaks is somewhat arbitrary -- in the experiment peak broadening depends on the crystallites size and strain, but such characteristics are not known when simulating the pattern.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Mercury User Guide (&lt;a href=&quot;https://www.ccdc.cam.ac.uk/support-and-resources/CCDCResources/Mercury_UserGuide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mercury_UserGuide.pdf&lt;/a&gt;) provides more details. Below I copied part of the relevant section.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;16.3 Technical Details of the Powder Pattern Simulation&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The Lorentz-polarisation correction assumes a laboratory X-ray source. No absorption is simulated. Fixed slit widths are assumed. No background is included.&lt;/li&gt;&#xA;&lt;li&gt;All non-hydrogen atoms are assumed to have isotropic atomic displacement parameters (Uiso) of 0.05 Å&lt;sup&gt;2&lt;/sup&gt;. […]&lt;/li&gt;&#xA;&lt;li&gt;The powder pattern simulator takes site occupation factors into account. […]&lt;/li&gt;&#xA;&lt;li&gt;All reflections have a symmetric pseudo-Voight peak shape with a full width half maximum of 0.1 degree 2θ, corresponding to medium resolution laboratory data.&lt;/li&gt;&#xA;&lt;li&gt;Experimental displacement parameters, either isotropic or anisotropic, are taken into account in the calculation if available […]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="126" LastEditorUserId="126" LastEditDate="2022-12-02T11:06:04.923" LastActivityDate="2022-12-02T11:06:04.923" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10037" PostTypeId="2" ParentId="10034" CreationDate="2022-12-01T13:52:32.120" Score="6" Body="&lt;p&gt;There is a DFT-D3 implementation from the Grimme group on Github that has a &lt;a href=&quot;https://github.com/dftd3/simple-dftd3/blob/main/assets/parameters.toml&quot; rel=&quot;noreferrer&quot;&gt;parameter file&lt;/a&gt; containing these values for HSE06. From here, it seems that for HSE06:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$s_{R,6}=1.129\text{, }s_8=0.109$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-12-01T13:52:32.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10038" PostTypeId="2" ParentId="9713" CreationDate="2022-12-01T22:46:01.447" Score="4" Body="&lt;p&gt;I will complement the above answers by highlighting the work that culminated in &lt;a href=&quot;https://github.com/psi4/psi4numpy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Psi4NumPy distributed on github&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b00286&quot; rel=&quot;nofollow noreferrer&quot;&gt;described in a paper&lt;/a&gt;.&#xA;Here the authors focused on creating a workflow to quickly and efficiently develop new algorithms and implementations for useful quantum chemical code.&lt;/p&gt;&#xA;&lt;p&gt;The main &lt;a href=&quot;https://github.com/psi4/psi4&quot; rel=&quot;nofollow noreferrer&quot;&gt;psi4 is distributed separately&lt;/a&gt;, but the freedom to use all of python's libraries and numpy's array programming with a fast and FOSS package is notable.&lt;/p&gt;&#xA;&lt;p&gt;In my experience, the relative performance of the few free (as in beer) computational chemistry software packages I have actually used for production purposes is as follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Scripting: psi4 &amp;gt; ORCA &amp;gt; NWChem&lt;/li&gt;&#xA;&lt;li&gt;Stability: ORCA &amp;gt; NWChem &amp;gt; psi4&lt;/li&gt;&#xA;&lt;li&gt;Speed: ORCA &amp;gt; psi4 &amp;gt; NWChem&lt;/li&gt;&#xA;&lt;li&gt;Accuracy: ORCA &amp;gt; psi4 &amp;gt; NWChem&lt;/li&gt;&#xA;&lt;li&gt;Freedom: psi4 &amp;gt; NWChem &amp;gt; ORCA&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="6345" LastActivityDate="2022-12-01T22:46:01.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10039" PostTypeId="1" CreationDate="2022-12-02T02:09:14.413" Score="13" ViewCount="236" Body="&lt;p&gt;What are some good textbooks or online resources to improve my skills in C++, C and Fortran, specifically for computational chemistry.&lt;/p&gt;&#xA;&lt;p&gt;For example, I am interested in learning about parallelisation with openMP or MPI, depending on the algorithm/task at hand.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5884" LastEditorUserId="5" LastEditDate="2022-12-03T15:34:25.750" LastActivityDate="2022-12-06T22:48:25.363" Title="Improving my programming for computational chemistry/physics" Tags="|software|computational-chemistry|reference-request|programming|fortran|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10040" PostTypeId="2" ParentId="467" CreationDate="2022-12-02T03:02:41.217" Score="8" Body="&lt;h1&gt;CrysX - 3D Viewer&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.bragitoff.com/crysx-3d-viewer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.bragitoff.com/crysx-3d-viewer/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;strong&gt;Disclaimer&lt;/strong&gt;: I am the developer of this software.)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The crystal visualizer tool is available for &lt;a href=&quot;https://www.bragitoff.com/crysx-3d-viewer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Windows&lt;/a&gt;, &lt;a href=&quot;https://www.bragitoff.com/crysx-3d-viewer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MacOS&lt;/a&gt;, &lt;a href=&quot;https://www.bragitoff.com/crysx-3d-viewer/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Linux&lt;/a&gt; and &lt;a href=&quot;https://play.google.com/store/apps/details?id=com.bragitoff.CrysXViewer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Android&lt;/a&gt; devices. The visualizer enables the users to open popular .cif, .xyz, .cub, .mol, etc.format files to visualise crystal as well as molecular structures and isosurfaces. The visualizer is built using a gaming engine (Unity3d) ensuring stellar, never-before seen graphics on any other molecule/crystal visualizer. This makes the app really useful for researchers to prepare illustrations and figures for their research papers, thesis and dissertation. The app lets the users visualize lattice planes, and draw vectors to indicate electric/magnetic fields.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2019/07/CrysX_2560x1440.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2022/05/Crystal_Viewer_screenGrab_2022-05-14_20-00-33.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2022/05/Crystal_Viewer_screenGrab_2019-07-16_17-15-18.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2022/05/Crystal_Viewer_screenGrab_2022-05-23_01-00-40.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2022/05/Crystal_Viewer_screenGrab_2022-05-18_14-02-56.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://www.bragitoff.com/wp-content/uploads/2022/05/Crystal_Viewer_screenGrab_2022-05-19_15-02-42.png&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://pubs.acs.org/pb-assets/images/_journalCovers/jctcce/jctcce_v018i011-2.jpg?0.6456770585461251&quot; alt=&quot;&quot; /&gt;&#xA;&lt;img src=&quot;https://pbs.twimg.com/media/EKY1X6rWsA40NLU?format=png&amp;amp;name=4096x4096&quot; alt=&quot;&quot; /&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="user6041" LastEditorDisplayName="user6041" LastEditDate="2022-12-04T16:14:53.240" LastActivityDate="2022-12-04T16:14:53.240" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10041" PostTypeId="2" ParentId="10028" CreationDate="2022-12-03T12:35:54.620" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://www.mrcc.hu/MRCC/manual/html/single/manual_sp.xhtml#S6.SS2&quot; rel=&quot;nofollow noreferrer&quot;&gt;The MRCC manual suggests that analytic gradients are not available for CCSD(T)&lt;/a&gt;, they are only available for the following 12 categories of methods:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;h4&gt;6.2 Geometry optimizations and first-order properties&lt;/h4&gt;&#xA;&lt;h5&gt;Available methods&lt;/h5&gt;&#xA;&lt;p&gt;Geometry optimizations and first-order property calculations can be&#xA;performed using analytic gradient techniques with the following&#xA;methods. See also Tables LABEL:GrTable and LABEL:ExTable for the&#xA;availability of analytic gradients for ground- and excited-state&#xA;models, respectively.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;conventional and DF (RI) HF-SCF (Ref. 137): RHF and UHF&lt;/li&gt;&#xA;&lt;li&gt;conventional and DF (RI) DFT (Ref. 71): RKS and UKS with LDA, GGA, meta-GGA (depending only on kinetic-energy density), and hybrid functionals as well as dispersion corrections&lt;/li&gt;&#xA;&lt;li&gt;double hybrid density functional methods (Ref. 71), such as B2PLYP, B2PLYP-D3, B2GPPLYP, etc. (current limitations: only MP2 correlation, closed shell RKS, no spin-component scaling, no meta-GGA functionals, only DH functionals for which the DFT contribution to the energy is stationary with respect to the variation of the MO coefficients)&lt;/li&gt;&#xA;&lt;li&gt;DF-MP2 (RI-MP2), currently only for RHF references (Ref. 71)&lt;/li&gt;&#xA;&lt;li&gt;arbitrary single-reference coupled-cluster methods (Refs. 69 and 60): CCSD, CCSDT, CCSDTQ, CCSDTQP, …, CC(n)&lt;/li&gt;&#xA;&lt;li&gt;arbitrary single-reference configuration-interaction methods (Refs. 69 and 60): CIS, CISD, CISDT, CISDTQ, CISDTQP, …, CI(n), …, full CI&lt;/li&gt;&#xA;&lt;li&gt;multi-reference CI approaches (Refs. 70 and 60)&lt;/li&gt;&#xA;&lt;li&gt;multi-reference CC approaches using a state-selective ansatz (Refs. 70 and 60)&lt;/li&gt;&#xA;&lt;li&gt;CIS and TD-HF methods using RHF references&lt;/li&gt;&#xA;&lt;li&gt;arbitrary single-reference linear-response (equation-of-motion, EOM) CC methods (Refs. 60 and 62): LR-CCSD (EOM-CCSD), LR-CCSDT (EOM-CCSDT), LR-CCSDTQ (EOM-CCSDTQ), LR-CCSDTQP (EOM-CCSDTQP), …, LR-CC(n) [EOM-CC(n)]&lt;/li&gt;&#xA;&lt;li&gt;linear-response (equation-of-motion) MRCC schemes (Refs. 60 and 62)&lt;/li&gt;&#xA;&lt;li&gt;The ONIOM approach with arbitrary number of layers [85]. Currently, only the IMOMO [57] part of ONIOM is available in the standalone version of Mrcc with mechanical embedding and automated link atom handling. ONIOM gradients with electronic embedding are also available with perturbation independent point charges.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you are okay with using numerical gradients, then you can do the geometry optimization manually or via the CFOUR interface:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Geometry optimizations and first-order property calculations can also be performed via numerical differentiation for all methods available in Mrcc using the Cfour interface.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;The upshot of using MRCC is that analytic gradients are available for CCSDT, CCSDTQ, etc., and also for RHF-DF-MP2, but unfortunately not for CCSD(T) or DF-CCSD. CFOUR can do analytic gradients for CCSD(T) but likely not for DF-CCSD or DF-MP2, so with each program there's some unique features, and some missing features.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-12-03T12:35:54.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10042" PostTypeId="2" ParentId="10039" CreationDate="2022-12-03T15:32:28.180" Score="13" Body="&lt;h1&gt;My Story&lt;/h1&gt;&#xA;&lt;p&gt;As an undergrad doing my first computational research project, I was told that I would be programming in FORTRAN. I remember being very nervous about this because I had never touched FORTRAN before, and neither had anyone that I knew (including people much older than me), plus I had heard horror stories about it, such as &amp;quot;indentation matters&amp;quot; (which is ironically no longer true since Fortran 90, yet it's true for Python which is one of the most popular languages in 2022).&lt;/p&gt;&#xA;&lt;p&gt;I was also a perfectionist when it came to academia, and I had enormous respect for my soon-to-be research supervisor, so I certainly wanted to impress him. I went to the library and borrowed a couple beginner-level books about FORTRAN, and hoped to actually be useful on day 1 of the job. I don't think I got past the first page of either of those books though, and the books basically sat on my desk collecting dust all the way until the last day of the summer job.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So how did I learn FORTRAN?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;By doing.&lt;/p&gt;&#xA;&lt;p&gt;I remember being quite relieved when I learned that the project would involve more of &amp;quot;running&amp;quot; programs than &amp;quot;writing&amp;quot; programs, but in the final weeks when my supervisor asked me to write some programs, and &lt;strong&gt;I remember it being a &lt;em&gt;daunting&lt;/em&gt; task at first since I had no idea where to begin, and I had told my supervisor that I had programming experience, and didn't quite realize that this doesn't mean I'm expected to know FORTRAN.&lt;/strong&gt; I can't recall using the books much (if at all) though.&lt;/p&gt;&#xA;&lt;p&gt;The first FORTRAN program I can recall writing was actually a stand-alone program that my supervisor wanted me to write, to obtain the long-range tails of potential energy curves at various distances in a transformed coordinate system, after being given the &lt;code&gt;R&lt;/code&gt; and &lt;code&gt;V(R)&lt;/code&gt; values in an input file, along with the &lt;code&gt;C3&lt;/code&gt;,&lt;code&gt;C6&lt;/code&gt;,&lt;code&gt;C8&lt;/code&gt;,&lt;code&gt;C10&lt;/code&gt; for the long-range potential, and another input parameter to tell the program what type of transformation the user would like the program to make on the data. The &lt;code&gt;END&lt;/code&gt; statement was on line 127 and about 44 lines of whitespace or comments.&lt;/p&gt;&#xA;&lt;p&gt;The basis for me writing this program was whatever little I could find on the internet back then. I got my supervisor to help me get the program running, because I &lt;em&gt;thought&lt;/em&gt; that I couldn't do it myself, but I was quite amazed in the end, when we got it running the first time. &lt;strong&gt;I don't ever recall looking at a FORTRAN book since then&lt;/strong&gt;. I then wrote more and more complicated programs, often requiring me to use other people's programs as a subroutine to mine, and often requiring me to interface my program within much larger programs. I also went into other people's programs and modified them or corrected them on many occasions. &lt;strong&gt;My guidance throughout all this time was the internet, not books.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;What I recommend for anyone&lt;/h1&gt;&#xA;&lt;p&gt;If you want to get better at Fortran or C++, I would recommend to just get involved in a project in one of those languages, and learn as you go (referring to the world-wide-web as often as you need). &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b00532&quot; rel=&quot;noreferrer&quot;&gt;OpenMolcas&lt;/a&gt; is written in FORTRAN and is open-source, allowing you to go through &lt;a href=&quot;https://gitlab.com/Molcas/OpenMolcas/-/issues&quot; rel=&quot;noreferrer&quot;&gt;this issues list&lt;/a&gt; and work on something of your choice. This would be the best way to learn Fortran in my opinion. Psi4 uses a lot of C++ and you can similarly volunteer to help on their &lt;a href=&quot;https://github.com/psi4/psi4/issues&quot; rel=&quot;noreferrer&quot;&gt;issues list&lt;/a&gt; too.&lt;/p&gt;&#xA;&lt;p&gt;As with me, having a supervisor, or just someone with more experience in the language, working with you (or just readily available to answer any questions) can be immensely useful in terms of saving time when you're stuck. If you want me to help you in this way for learning Fortran, there's plenty of OpenMolcas projects we can work on together (you can email me at nike@hpqc.org).&lt;/p&gt;&#xA;&lt;h1&gt;Learning more advanced features&lt;/h1&gt;&#xA;&lt;p&gt;The technique to learn more advanced features (you mentioned OpenMP and MPI) surprisingly is the same! When you want to do something, just look it up online! It can help to have an already-parallelized Fortran program like OpenMolcas or &lt;a href=&quot;https://github.com/ghb24/NECI_STABLE&quot; rel=&quot;noreferrer&quot;&gt;NECI&lt;/a&gt; to use as a template. &lt;strong&gt;An undergrad student of mine (David Wilkins) had no Fortran experience and yet wrote an OpenMP paralellized hierarchical equations of motion program in Fortran without my help, within one week (believe it or not, I'm not exaggerating!).&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've also taken free crash courses / workshops on OpenMP and MPI from SHARCNET, which seemed to be helpful since we did hands-on exercises in which we actually wrote parallel programs using OpenMP/MPI, but in the end almost all of the OpenMP/MPI coding I did was either based on using existing codes as templates, or based on help I found online. Occasionally I got help from extremely highly skilled IT support staff at supercomputing centres (essentially the people who teach courses like the SHARCNET ones I mentioned earlier in this paragraph).&lt;/p&gt;&#xA;&lt;h1&gt;Since you asked, here's some resources:&lt;/h1&gt;&#xA;&lt;p&gt;From the SHARNET tutorials I mentioned in the previous section, here's some resources you can use if you prefer to learn this way (i.e. learning &amp;quot;in advance&amp;quot; rather than by &amp;quot;doing&amp;quot;):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=__xs0sr6gWc&quot; rel=&quot;noreferrer&quot;&gt;Youtube: Introduction to OpenMP Parallel Programming&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://helpwiki.sharcnet.ca/wiki/images/8/84/Jemmy_openmp_2016.pdf&quot; rel=&quot;noreferrer&quot;&gt;PDF: Introduction to OpenMP Parallel Programming&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://sharcnet.ca/help/images/f/f3/Sn_openmp_jemmy.pdf&quot; rel=&quot;noreferrer&quot;&gt;PDF: Parallel Programming with OpenMP&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://staff.sharcnet.ca/jemmyhu/tutorials/MPI+OpenMP_2016.pdf&quot; rel=&quot;noreferrer&quot;&gt;PDF: Hybrid MPI and OpenMP Parallel Programming&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Conclusion&lt;/h1&gt;&#xA;&lt;p&gt;I can't really recommend books for programming anymore! Even when I was an undergrad student, I found whatever existed online back then to be &amp;quot;infinitely&amp;quot; more useful than the programming books that I did borrow from the library.&lt;/p&gt;&#xA;&lt;p&gt;In order of effectiveness, I recommend:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;doing&amp;quot; projects (and searching online when you get stuck),&lt;/li&gt;&#xA;&lt;li&gt;in-person workshops like the SHARCNET one I mentioned in the previous section,&lt;/li&gt;&#xA;&lt;li&gt;Youtube videos or PDF online tutorials like the SHARCNET ones I mentioned in the previous section&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;SHARCNET regularly offers free beginner, intermediate, and advanced-level workshops in parallel computing and Fortran/C/C++/Python/etc. These are available to all of my group members (for example), and if you're interested in attending one of these, you can let me know at nike@hpqc.org.&lt;/p&gt;&#xA;&lt;h1&gt;Post-script&lt;/h1&gt;&#xA;&lt;p&gt;After writing this answer, I wanted to share your question with the &lt;a href=&quot;https://stackoverflow.com/tags/fortran/topusers&quot;&gt;Fortran King&lt;/a&gt; to try to attract more attention to your question, and while doing so I discovered that a similar question was asked on MMSE before: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6252/5&quot;&gt;How to master Fortran with minimal effort?&lt;/a&gt; and some books were recommended there.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-03T21:22:55.190" LastActivityDate="2022-12-03T21:22:55.190" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10043" PostTypeId="2" ParentId="10039" CreationDate="2022-12-03T18:07:30.550" Score="6" Body="&lt;p&gt;Dr. Victor Eijkhout at Texas Advanced Computing Center (TACC) has some excellent resources at his website &lt;a href=&quot;https://theartofhpc.com&quot; rel=&quot;noreferrer&quot;&gt;The Art of HPC&lt;/a&gt;, including freely available textbooks on&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Introduction to High-Performance Scientific Computing&lt;/li&gt;&#xA;&lt;li&gt;Parallel Programming for Science and Engineering&lt;/li&gt;&#xA;&lt;li&gt;Introduction to Scientific Programming&lt;/li&gt;&#xA;&lt;li&gt;HPC Carpentry&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Of these, &lt;a href=&quot;https://theartofhpc.com/pcse.html&quot; rel=&quot;noreferrer&quot;&gt;Parallel Programming for Science and Engineering&lt;/a&gt; is the one that introduces MPI and OpenMP, with examples in C, C++, Fortran, and (for MPI only) Python. However, for a first introduction to the topics his slides for one-day training sessions may be more accessible. You can find them &lt;a href=&quot;https://web.corral.tacc.utexas.edu/CompEdu/pdf/pcse/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2022-12-03T18:07:30.550" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10045" PostTypeId="1" CreationDate="2022-12-04T12:34:01.377" Score="4" ViewCount="150" Body="&lt;p&gt;I want to calculate the electronic band structure for CuWO4 using the GGA+U method. Is it necessary to optimize the structure using the same GGA+U method or only we can incorporate GGA+U parameter in the bandstructure calculation? Actually, I don't have any idea regarding the GGA+U calculation so could you please help me in this regard?&#xA;Thanking you&#xA;with regards&#xA;Jyotirmoy&lt;/p&gt;&#xA;" OwnerUserId="6358" LastActivityDate="2022-12-05T23:59:58.447" Title="Query related to GGA+U calculation in SIESTA" Tags="|siesta|dft-u|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10047" PostTypeId="1" CreationDate="2022-12-04T20:46:41.593" Score="2" ViewCount="20" Body="&lt;p&gt;For many molecules, the gas-phase molecular polarizability, &lt;span class=&quot;math-container&quot;&gt;$\alpha_{gas}$&lt;/span&gt; is approximately the same as that in the liquid, &lt;span class=&quot;math-container&quot;&gt;$\alpha_{liq.}$&lt;/span&gt;. For instance, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, has roughly the same average &lt;span class=&quot;math-container&quot;&gt;$\alpha_{liq.}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\alpha_{gas}$&lt;/span&gt;. Many ions, especially anions, however, have much smaller &lt;span class=&quot;math-container&quot;&gt;$\alpha_{liq}$&lt;/span&gt; than &lt;span class=&quot;math-container&quot;&gt;$\alpha_{gas}$&lt;/span&gt;, often by greater than 50%.&lt;/p&gt;&#xA;&lt;p&gt;My question, is whether or not there is any simple theoretical framework, for understanding the decrease. I am well aware of the connection between polarizability and a measure of the atomic volume. It makes sense the atomic volume of an anion will be smaller in the condensed phase, but it is not clear what effects overcome the energetic penalty of shrinking the atomic volume.&lt;/p&gt;&#xA;&lt;p&gt;There are many thoughts that come to mind:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;By decreasing the volume, one increases the charge density allowing for stronger coulomb interactions&lt;/li&gt;&#xA;&lt;li&gt;The polarizability is decreased due to charge transfer out of the anion (that is, the anion charge is smaller than in the gas-phase)&lt;/li&gt;&#xA;&lt;li&gt;The decreased anion volume is a result of balancing out the cavitation energy (that is, by shrinking, the solvent is better able to interact with itself)&lt;/li&gt;&#xA;&lt;li&gt;Some linear combination of the above&lt;/li&gt;&#xA;&lt;li&gt;Additional effects I am missing&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Any references about the leading effect (if there is one) explaining why polarizabilities decrease in the condensed phase would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Also, any discussion of the relationship between partial charges and atomic polarizability would be appreciated. My pet theory, which I have no evidence to support, is that charge transfer from anion to solvent, is a large portion of the decrease. On that note, if I had an anion with a partial charge of -0.9 instead of -1.0, how much smaller should I expect the polarizability to be? Does it decrease linearly, quadratically, cubically? Put another way, what is the relationship between partial charge of an atom and its atomic radius?&lt;/p&gt;&#xA;&lt;p&gt;Finally, any references to anion polarizability damping in non-water solvents would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-12-04T20:46:41.593" Title="Simple models for the energetic stabilization associated with damped polarizabilities of anions in solution" Tags="|reference-request|molecular-interactions|polarizability|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-10T00:24:21.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="10048" PostTypeId="1" CreationDate="2022-12-04T21:14:00.833" Score="1" ViewCount="86" Body="&lt;p&gt;I have a test material- two silicon atoms in an unit cell. This particular structure shows evidence of having interstitial charge between the two atoms. I need to find out the amount of this interstitial charge. I have the cube file of the charge density (name: &lt;code&gt;si_pseudo.cube&lt;/code&gt;). So far I have been able to find out the total charge (24, twelve electrons from each atom) in the system by a python script (&lt;code&gt;ChargeDensity.py&lt;/code&gt;) with command:&lt;/p&gt;&#xA;&lt;h2&gt;Could you please answer in details about the python script to determine the interstitial charge?&lt;/h2&gt;&#xA;&lt;p&gt;The interstitial charge needs to be determined using a suitable numerical approximation method (may be spherical integration).&lt;/p&gt;&#xA;&lt;p&gt;The following python script reads the charge density file and determines the total charge. But I need to determine the interstitial charge (it is usually found in the mid position between the two atoms).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import numpy as np&#xA;import sys&#xA;&#xA;class CHD():&#xA;  def __init__(self):&#xA;    #This simply allocates the different data structures we need:&#xA;    self.natoms = 0&#xA;    self.grid = np.zeros(0)&#xA;    self.v = np.zeros([3,3])&#xA;    self.N = np.zeros([3])&#xA;    self.dV = 0&#xA;&#xA;  def set_dV(self):&#xA;    #The charge density is stored per volume. If we want to integrate the charge density&#xA;    #we need to know the size of the differential volume &#xA;    self.dV = 0&#xA;    x = self.v[:,0]&#xA;    y = self.v[:,1]&#xA;    z = self.v[:,2]&#xA;    self.dV = np.dot(x,np.cross(y,z))&#xA;&#xA;  def integrate(self):&#xA;    #This allows us to integrate the stored charge density&#xA;    return(np.sum(self.grid)*self.dV)&#xA; &#xA;#The following function reads the charge density from a cube file &#xA;def read(cubefile):&#xA;  density = CHD()&#xA;  f = open(cubefile,'r')&#xA;  #skip two header lines&#xA;  next(f)&#xA;  next(f)&#xA;  line = next(f)&#xA;  #Get the number of atoms if we want to store it&#xA;  density.natoms = int(line.split()[0])&#xA;  #This gets the nx,ny,nz info of the charge density&#xA;  #As well as the differential volume&#xA;  for i in range(0,3):&#xA;    line = next(f).split()&#xA;    density.N[i] = int(line[0])&#xA;    for j in range(1,4):&#xA;      density.v[i][j-1] = float(line[j])&#xA;&#xA;  #As of now we dont care about the positions of the atoms,&#xA;  #But if you did you could read them here:&#xA;  for i in range(0,density.natoms):&#xA;    next(f)&#xA;&#xA;  density.set_dV()&#xA;  density.grid = np.zeros(int(density.N[0]*density.N[1]*density.N[2]))&#xA;&#xA;  #This reads the data into a 1D array of size nx*ny*nz&#xA;  count = 0&#xA;  for i in f:&#xA;    for j in i.split():&#xA;      density.grid[count] = float(j)&#xA;      count+=1&#xA;  f.close()&#xA;  &#xA;  return density&#xA;&#xA;if __name__ == &amp;quot;__main__&amp;quot;:&#xA;  if len(sys.argv) != 2:&#xA;    print(&amp;quot;Incorrect number of arguments, run as ./ChargeDensity.py CUBEFILELOCATION&amp;quot;)&#xA;    sys.exit(6)&#xA;  density = read(sys.argv[1])  &#xA;  #For the main function I care about the total number of electrons&#xA;  print(density.integrate())&#xA;# Code source (from Dr. Levi): https://github.com/levilentz&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above python script worked for me as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python ChargeDensity.py si_pseudo.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And it results a value: 24, which is the total charge of the unit cell)&lt;/p&gt;&#xA;&lt;p&gt;The charge density cube file is &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/10048/si_psuedo.code&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2022-12-04T21:49:14.637" LastActivityDate="2023-01-02T14:36:29.590" Title="Interstitial charge from a cube file: Need help in python coding" Tags="|density-functional-theory|python|charge-density|programming|conceptual-dft|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10049" PostTypeId="2" ParentId="467" CreationDate="2022-12-05T06:00:14.440" Score="6" Body="&lt;h1&gt;Multiwfn&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Multiwfn&lt;/strong&gt; is an extremely powerful program for realizing electronic wavefunction analysis, which is a key ingredient of quantum chemistry.&lt;/p&gt;&#xA;&lt;p&gt;Multiwfn is free, open-source, high-efficient, very user-friendly and flexible, it supports almost all of the most important wavefunction analysis methods.&lt;/p&gt;&#xA;&lt;p&gt;Multiwfn is maintained by Tian Lu at Beijing Kein Research Center for Natural Sciences (&lt;a href=&quot;http://www.keinsci.com&quot; rel=&quot;noreferrer&quot;&gt;http://www.keinsci.com&lt;/a&gt;). Multiwfn is always in active development, the original paper is J. Comput. Chem., 33, 580-592 (2012).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Here is the resource link: &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fjU1q.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fjU1q.jpg&quot; alt=&quot;Image taken from a video tutorial of Multiwfn&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="671" LastEditDate="2022-12-05T06:33:19.557" LastActivityDate="2022-12-05T06:33:19.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10050" PostTypeId="1" CreationDate="2022-12-05T20:21:59.417" Score="4" ViewCount="302" Body="&lt;p&gt;Can anyone suggest some free software that can visualize the charge density and/or electron localization function (ELF)? More importantly, can we determine/know those values (charge density and/or ELF) to any arbitrary position of the structure - i.e. not just the color map?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2022-12-05T20:26:50.907" LastActivityDate="2022-12-06T01:07:14.527" Title="Is there any free software that helps to know specific charge densities or ELFs at any position of the material?" Tags="|density-functional-theory|software-recommendations|visualization-software|charge-density|conceptual-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10051" PostTypeId="2" ParentId="10050" CreationDate="2022-12-05T20:37:32.517" Score="4" Body="&lt;p&gt;Yes, for example the Python package &lt;a href=&quot;https://chemtools.org/auto_examples/index.html#electron-localization-function-elf&quot; rel=&quot;nofollow noreferrer&quot;&gt;chemtools&lt;/a&gt; gives several examples of calculating the ELF from a Gaussian cube or similar wavefunction file.&lt;/p&gt;&#xA;&lt;p&gt;At the moment, it will generate a Gaussian-compatible cube, but you can interpolate to whatever point you want. (I haven't gone through the Python code in detail, but I suspect you could get the ELF or other metric at points without generating the cube.)&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="5" LastEditDate="2022-12-06T01:07:14.527" LastActivityDate="2022-12-06T01:07:14.527" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10052" PostTypeId="1" CreationDate="2022-12-05T20:44:11.867" Score="4" ViewCount="220" Body="&lt;p&gt;How do you specify a symmetric vacuum region (along z) above and below an inorganic substrate using PACKMOL? I tried to increase the box size in .pdb and use that in packmol. But it changes the box dimensions and places the substrate diagonally across?&lt;/p&gt;&#xA;&lt;p&gt;The input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tolerance 2.0 &#xA;filetype pdb &#xA;output interface.pdb&#xA;structure TiO2-110.pdb &#xA;number 24 &#xA;inside box &#xA;0.0 0.0 0.0 &#xA;11.152 7.604 17.0 &#xA;end structure &#xA;structure styrene.pdb &#xA;number 11 &#xA;inside box&#xA;0. 0. 5.0&#xA;5.0 5.0 10.0 &#xA;end structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6363" LastEditorUserId="7" LastEditDate="2022-12-06T16:33:08.587" LastActivityDate="2022-12-11T19:54:05.157" Title="Adding vacuum region in PACKMOL" Tags="|molecular-dynamics|packmol|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10053" PostTypeId="5" CreationDate="2022-12-05T21:18:57.500" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://leandro.iqm.unicamp.br/m3g/packmol/home.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://leandro.iqm.unicamp.br/m3g/packmol/home.shtml&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-05T21:18:57.500" LastActivityDate="2022-12-05T21:18:57.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10054" PostTypeId="4" CreationDate="2022-12-05T21:18:57.500" Score="0" Body="Questions about (or related to) the PACKMOL software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-05T21:18:57.500" LastActivityDate="2022-12-05T21:18:57.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10055" PostTypeId="2" ParentId="10045" CreationDate="2022-12-05T23:54:18.733" Score="4" Body="&lt;p&gt;I'm not entirely sure why you're asking the question, but I'm going to assume that geometry optimisation with a GGA is straightforward, and it's the Hubbard U which you're concerned about - perhaps because it is harder to converge the SCF, or it takes more computational time.&lt;/p&gt;&#xA;&lt;p&gt;Generally speaking, you should always optimise your system's geometry with the same exchange-correlation functional that you're using to compute its properties. However, it is often found that varying the Hubbard U term does not affect the forces very much in practice, so you &lt;em&gt;may&lt;/em&gt; be able to optimise with the GGA only. If you do, you should definitely check that the forces for the GGA-optimised geometry are still small when you include the Hubbard U term.&lt;/p&gt;&#xA;&lt;p&gt;See:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8581/do-the-u-values-affect-structure-optimization-with-the-dftu-simulation-to-optim&quot;&gt;Do the U values affect structure optimization with the DFT+U simulation to optimize crystal structure?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;for a similar discussion (also linked by Tyberius).&lt;/p&gt;&#xA;&lt;p&gt;I'm afraid I've never used SIESTA so I can't tell you anything about how to actually do the calculations with it. There is an online tutorial here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://docs.siesta-project.org/projects/siesta/tutorials/dft%2Bu/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.siesta-project.org/projects/siesta/tutorials/dft%2Bu/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-12-05T23:59:58.447" LastActivityDate="2022-12-05T23:59:58.447" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10056" PostTypeId="2" ParentId="8828" CreationDate="2022-12-06T00:47:23.257" Score="14" Body="&lt;p&gt;I'd suggest having a look at &lt;a href=&quot;http://www.physics.rutgers.edu/pythtb/&quot; rel=&quot;noreferrer&quot;&gt;PythTB&lt;/a&gt; by Sinisa Coh and David Vanderbilt, which I found very useful and easy to use.&lt;/p&gt;&#xA;&lt;p&gt;Here's a stab at recreating the band structure of the 2d square lattice shown above&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&amp;quot;&amp;quot;&amp;quot;s and p orbitals on 2d square lattice.&#xA;&#xA; - nearest neighbor hopping only&#xA; - no hopping between orbitals of different type (e.g. s &amp;lt;&amp;gt; pz)&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;from pythtb import tb_model&#xA;import matplotlib.pyplot as plt&#xA;&#xA;# 2d square lattice&#xA;lat=[[1.0, 0.0],[0.0, 1.0]]&#xA;# one s and 3 p orbitals (at the same site)&#xA;orb=[[0.,0.] for _ in range(1+3)]&#xA;&#xA;# 2-dimensional k-space, 2-dimensional real space&#xA;my_model=tb_model(dim_r=2,dim_k=2,lat=lat,orb=orb)&#xA;&#xA;# p-orbitals are at higher energy&#xA;my_model.set_onsite([0,3,3,3])&#xA;&#xA;# set hoppings (one for each connected pair of orbitals)&#xA;# (amplitude, i, j, [lattice vector to cell containing j])&#xA;&#xA;# isotropic nearest-neighbor hopping for s and pz&#xA;for neighbor in [ [1,0], [0,1]]:&#xA;    my_model.set_hop(-0.5, 0, 0, neighbor) # s&#xA;    my_model.set_hop(-0.25, 3, 3, neighbor) # pz&#xA;&#xA;# directional nearest-neighbor hopping for px and py&#xA;my_model.set_hop(+0.25, 1, 1, [1,0])&#xA;my_model.set_hop(-0.25, 1, 1, [0,1])&#xA;my_model.set_hop(-0.25, 2, 2, [1,0])&#xA;my_model.set_hop(+0.25, 2, 2, [0,1])&#xA;&#xA;# generate list of k-points following a segmented path in the BZ&#xA;k_label=[r&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;&amp;quot;,r&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt;&amp;quot;, r&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;&amp;quot;, r&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;&amp;quot;]&#xA;path=[[0.0,0.0], [0.5,0.0], [0.5, 0.5], [0.0,0.0]]&#xA;(k_vec,k_dist,k_node)=my_model.k_path(path,100)&#xA;&#xA;# solve model&#xA;evals=my_model.solve_all(k_vec)&#xA;&#xA;# plot band structure&#xA;fig, ax = plt.subplots()&#xA;for band in evals:&#xA;    ax.plot(k_dist, band)&#xA;ax.set_title(&amp;quot;s and p orbitals on 2d square lattice&amp;quot;)&#xA;ax.set_xlabel(&amp;quot;Path in k-space&amp;quot;)&#xA;ax.set_ylabel(&amp;quot;Band energy&amp;quot;)&#xA;ax.set_xticks(k_node)&#xA;ax.set_xticklabels(k_label)&#xA;ax.set_xlim(k_node[0],k_node[-1])&#xA;for n in range(len(k_node)):&#xA;  ax.axvline(x=k_node[n], linewidth=0.5, color='k')&#xA;fig.tight_layout()&#xA;fig.savefig(&amp;quot;s_and_p.pdf&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hQFqO.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hQFqO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that matplotlib colors the lines by band energy at each k-point, not by the orbital symmetry of the band.&lt;/p&gt;&#xA;&lt;p&gt;This may be suitable as a first simple model to understand how the hopping matrix elements influence the band structure.&lt;/p&gt;&#xA;&lt;p&gt;From here, there are a number of possible extensions to learn more / make it more realistic:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the nearest-neighbor hopping matrix elements between different orbitals are not entirely independent parameters and can be expressed in terms of bond integrals using the &lt;a href=&quot;https://en.wikipedia.org/wiki/Tight_binding#Table_of_interatomic_matrix_elements&quot; rel=&quot;noreferrer&quot;&gt;Slater-Koster tables&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;double the size of the unit cell, look at band folding and/or introduce site-dependent onsite energies (e.g. to simulate symmetry breaking when adsorbing a 2d material on a substrate)&lt;/li&gt;&#xA;&lt;li&gt;go 3d&lt;/li&gt;&#xA;&lt;li&gt;look at the effect of introducing 2nd- and 3rd-nearest neighbor hopping (e.g. in graphene, 2nd-nearest neighbor hopping affects the electronic structure near the Fermi level only by a rigid shift, while 3rd-nearest neighbor hopping plays a significant role)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The extensions above are still within the tight-binding framework, treating electrons as non-interacting Fermions, and can be modeled with pythtb.&lt;/p&gt;&#xA;&lt;p&gt;P.S. Another conceptually very interesting extension would be to introduce an on-site Coulomb repulsion term between electrons, i.e. to move from tight binding to the Hubbard model. The Hubbard model is no longer solvable exactly (except for 1d), but a solution to its mean-field approximation can be found by iteration to self-consistency (similar to what DFT codes do, but on a lattice).&#xA;This is not very difficult to do, but it goes beyond the scope of pythtb and I am not aware of a similar, easy-to-use software package that implements this functionality. If someone does, please let me know, I think it would make for a great addition to this toolbox.&lt;/p&gt;&#xA;&lt;p&gt;P.P.S. There have been at least two attempts (one by me) to convince the authors to host the pythtb source code on GitHub to make it easy to contribute back (e.g. I made some minor modifications for my Ph.D. thesis). So far, they have been reluctant due to possible maintenance/supervision involved, but it may be worth trying again.&lt;/p&gt;&#xA;" OwnerUserId="873" LastEditorUserId="873" LastEditDate="2023-03-10T16:52:46.670" LastActivityDate="2023-03-10T16:52:46.670" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10057" PostTypeId="2" ParentId="10008" CreationDate="2022-12-06T02:12:06.660" Score="8" Body="&lt;p&gt;You should definitely &lt;em&gt;not&lt;/em&gt; use the chemical potentials of the constituent elemental materials in general, since for multi-elemental compounds they are not internally consistent. As an example, Pb and I would form an iodide, so it is not reasonable to assume the chemical potentials must be of Pb metal and I&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; gas.&lt;/p&gt;&#xA;&lt;p&gt;I'm going to start with the fundamentals of how to calculate chemical potentials, but if you already know all this you can skip to the end of this post.&lt;/p&gt;&#xA;&lt;h3&gt;Concept&lt;/h3&gt;&#xA;&lt;p&gt;The chemical potential of an atom is basically the energy required to bring it into your chemical system &lt;em&gt;from somewhere else&lt;/em&gt;. This energy depends on both your system and where the atom came from. The key to working out chemical potentials is to think about the two extreme elemental cases:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;there is a lot of element A compared to other elements, usually called &amp;quot;A-rich&amp;quot; conditions; or&lt;/li&gt;&#xA;&lt;li&gt;there is very little of element A compared to other elements, usually called &amp;quot;A-poor&amp;quot; conditions,&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;and similarly for the other elements.&lt;/p&gt;&#xA;&lt;p&gt;If your system is A-rich, it means that there is so much of element A that some of it will be forced to be in its elemental form, simply because there aren't enough other atoms to form compounds with it. In this case, atoms of A are in chemical equilibrium with the elemental form, and its chemical potential &lt;span class=&quot;math-container&quot;&gt;$\mu_A$&lt;/span&gt; is the same as the total energy per atom of its elemental form, &lt;span class=&quot;math-container&quot;&gt;$E(A)$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu_A = E(A) \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Binary Compounds&lt;/h3&gt;&#xA;&lt;p&gt;If there are only two elements in your material, A and B, and you only consider these two elements, then A-rich necessarily means B-poor, and &lt;em&gt;vice versa&lt;/em&gt;. If you only consider the chemical reactions involving these elements, then in A-rich conditions the energy of the compound material determines the chemical potential of B. In other words, we assume that all the B has reacted to form the compound, and there is excess A which forms the elemental material.&lt;/p&gt;&#xA;&lt;p&gt;Let us consider the case of a simple compound with chemical formula AB. Note that I'll be using A and B (and, later on, C) as generic chemical symbols, and B should not be interpreted as necessarily boron, nor C as carbon!&lt;/p&gt;&#xA;&lt;h4&gt;A-rich&lt;/h4&gt;&#xA;&lt;p&gt;In A-rich conditions, all the B reacts to form AB and there is still A left over. The excess A will form A's elemental compound.&lt;/p&gt;&#xA;&lt;p&gt;2A + B &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; A + AB&lt;/p&gt;&#xA;&lt;p&gt;Energetically, we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;2\mu_A + \mu_B = \mu_A + E(AB) \tag{2}&#xA;$$&lt;/span&gt;&#xA;i.e.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu_B = E(AB) - \mu_A \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since we're under A-rich conditions, and A is in chemical equilibrium with its elemental form, we use equation (1) and obtain:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mu_A^\mathrm{A-rich} &amp;amp;= E(A)\\&#xA;\mu_B^\mathrm{A-rich} &amp;amp;= E(AB) - E(A) \tag{4}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h4&gt;B-rich (A-poor)&lt;/h4&gt;&#xA;&lt;p&gt;In B-rich conditions, all the A reacts to form AB and there is still B left over. We follow the analogous process to the A-rich case, and assume that the excess B will form B's elemental compound.&lt;/p&gt;&#xA;&lt;p&gt;A + 2B &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; AB + B,&lt;/p&gt;&#xA;&lt;p&gt;which leads to:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mu_A^\mathrm{B-rich} &amp;amp;= E(AB) - E(B)\\&#xA;\mu_B^\mathrm{B-rich} &amp;amp;= E(B) \tag{5}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that, by definition, &lt;span class=&quot;math-container&quot;&gt;$\mu_A + \mu_B = E(AB)$&lt;/span&gt; under all conditions.&lt;/p&gt;&#xA;&lt;h4&gt;What are the actual chemical potentials?&lt;/h4&gt;&#xA;&lt;p&gt;You'll notice that we now have two different values of &lt;span class=&quot;math-container&quot;&gt;$\mu_A$&lt;/span&gt; (and &lt;span class=&quot;math-container&quot;&gt;$\mu_B$&lt;/span&gt;), corresponding to the two extremes of chemical conditions (A-rich and A-poor).  This is correct, there is no single value for chemical potential which covers all environments; in fact, real environments are usually neither fully rich nor fully poor in their elements, so it is common practice to consider these values to be the extrema of the range of possible chemical potentials.&lt;/p&gt;&#xA;&lt;h3&gt;Ternary compounds&lt;/h3&gt;&#xA;&lt;p&gt;Adding another chemical element, C, makes the situation more complicated, but the basic idea is the same. Now if we have A-rich conditions, we have to consider whether there is more B than C, or &lt;em&gt;vice versa&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Suppose we have a ternary compound, ABC. We now have more possible scenarios, depending on the relative abundance of all three elements. For the purpose of this discussion, let's consider the particular case where we have more A than B, and more B than C, i.e. &amp;quot;A-rich, C-poor&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;In this case, all the C reacts with A and B to form ABC. The remaining B reacts with A to form AB. The excess A forms its elemental material. For example,&lt;/p&gt;&#xA;&lt;p&gt;3A + 2B + C &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; A + AB + ABC&lt;/p&gt;&#xA;&lt;p&gt;Energetically, we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;3\mu_A + 2\mu_B + \mu_C = \mu_A + E(AB) + E(ABC) \tag{6}&#xA;$$&lt;/span&gt;&#xA;i.e.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mu_C = E(ABC) + E(AB) - 2\mu_A -2\mu_B \tag{7}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since we're under A-rich conditions, and A is in chemical equilibrium with its elemental form, we use &lt;span class=&quot;math-container&quot;&gt;$\mu_A^\mathrm{A-rich}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mu_B^\mathrm{A-rich}$&lt;/span&gt; from equation (4) and obtain:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mu_C &amp;amp;= E(ABC) + E(AB) - 2\mu_A -2\mu_B \\&#xA;      &amp;amp;= E(ABC) + E(AB) - 2E(A) - 2 \left\{E(AB) - E(A)\right\}\\&#xA;      &amp;amp;= E(ABC) - E(AB) &#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;Notice that in this case, the energies of the elemental A and B have disappeared! That's a direct consequence of the fact that &lt;span class=&quot;math-container&quot;&gt;$\mu_A +\mu_B = E(AB)$&lt;/span&gt;. In fact, in chemical reaction terms the key reaction is:&lt;/p&gt;&#xA;&lt;p&gt;AB + C &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; ABC&lt;/p&gt;&#xA;&lt;p&gt;and as long as A and B are in chemical equilibrium with AB, it doesn't matter whether it's A-rich or B-rich.&lt;/p&gt;&#xA;&lt;p&gt;The situation changes if there is more C, however, because then we need to consider the formation of AC or BC, depending on the relative abundance of A and B. Nevertheless, the basic procedure is exactly the same.&lt;/p&gt;&#xA;&lt;h3&gt;Multiple stoichiometries&lt;/h3&gt;&#xA;&lt;p&gt;Suppose A and B can actually form two different materials, A&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;B&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; and A&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;B. In these cases, it can usually be assumed that A&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;B will form under A-rich conditions (since it uses more A per B) and A&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;B&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; will form under A-poor/B-rich conditions (since it uses more B per A). This breaks the symmetry between the calculations for A and B, but the procedure is otherwise identical.&lt;/p&gt;&#xA;&lt;p&gt;A-rich: 3A + B &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; A&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;B + A &lt;br /&gt;&#xA;B-rich: 3A + 5B &lt;span class=&quot;math-container&quot;&gt;$\leftrightarrow$&lt;/span&gt; A&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;B&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; + B&lt;/p&gt;&#xA;&lt;p&gt;which leads to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mu_A^\mathrm{A-rich} &amp;amp;= E(A)\\&#xA;\mu_B^\mathrm{A-rich} &amp;amp;= E(A_2B) - 2E(A) \tag{8}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\mu_A^\mathrm{B-rich} &amp;amp;= \frac{1}{3}\left(E(A_3B_4) - 4E(B)\right)\\&#xA;\mu_B^\mathrm{B-rich} &amp;amp;= E(B) \tag{9}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;respectively. Note that in equation (9) we have divided by 3 in the formula for &lt;span class=&quot;math-container&quot;&gt;$\mu_A$&lt;/span&gt; because the compound has 3 A atoms per formula unit.&lt;/p&gt;&#xA;&lt;h3&gt;Real life&lt;/h3&gt;&#xA;&lt;p&gt;Remember that a real chemical environment will usually include more elements than simply the reagents. In the presence of air, oxygen will usually need to be considered (nitrogen is less reactive, so might be less important), and possibly water as well. In growth chambers, there may be contaminants from previous growth processes, or substrates; silicon is quite common. Hydrogen is extremely difficult to get rid of, even in ultrahigh vacuum. A more comprehensive study would also include these other elements from the environment.&lt;/p&gt;&#xA;&lt;h3&gt;Example: CsPbI&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;&lt;/h3&gt;&#xA;&lt;p&gt;This is a ternary compound, so immediately we need to consider several combinations of rich and poor conditions. There may also be many possible binary compounds, for example the stable alloys of Cs and Pb. You should calculate the energy per formula unit of all the (likely) binary and ternary compounds, and determine the ranges of chemical potentials. In addition, you (correctly) point out that a realistic chemical synthesis may easily start from reagents with other elements, such as your HA and MH.&lt;/p&gt;&#xA;&lt;p&gt;A comprehensive study of all these elements, and all the possible situations, can be very time-consuming. However, you can often use some reasonable assumptions to reduce the scenarios; for example, is it likely that you have H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; gas at any point? You may be able to ignore the H-rich conditions and consider just the binary and ternary H-compounds. Will there really be elemental Cs left at the end of the actual experiments you're modelling? What compound(s) would you expect excess Cs to form? Perhaps you actually have experimental data, and already know what the Cs compounds are.&lt;/p&gt;&#xA;&lt;p&gt;You also only care about the extremes of the chemical potentials, since they can fall anywhere within that range anyway, in practice - so if you can see that, for example, &lt;span class=&quot;math-container&quot;&gt;$\mu_H^\mathrm{Cs-rich}$&lt;/span&gt; will lie somewhere in between &lt;span class=&quot;math-container&quot;&gt;$\mu_H^\mathrm{Pb-rich}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mu_H^\mathrm{I-rich}$&lt;/span&gt;, then there may be no need to compute it.&lt;/p&gt;&#xA;&lt;p&gt;How comprehensive a job you need to do is up to you. There are &lt;em&gt;always&lt;/em&gt; approximations involved, and you need to keep asking &amp;quot;is this reasonable?&amp;quot; For example, we've been using E(AB) etc. to mean the energy per formula unit of AB, but &lt;em&gt;what&lt;/em&gt; energy? Strictly, it should be the free energy, including zero-point, entropic and temperature contributions. We've assumed large amounts of reagents, and so ignored surface energies and interactions, as well as solvation effects...&lt;/p&gt;&#xA;&lt;p&gt;This can seem daunting, but in fact you can often gain a lot of insight with a more modest set of calculations, and then expand on them later. Provided you are clear about what you have done, and the assumptions you have made, you can publish your calculations and analyses without having completely exhausted all possibilities.&lt;/p&gt;&#xA;&lt;p&gt;For example, a while ago I published a paper which included some modelling of a potentially rather complicated growth process (BaFe&lt;span class=&quot;math-container&quot;&gt;$_{12}$&lt;/span&gt;O&lt;span class=&quot;math-container&quot;&gt;$_{19}$&lt;/span&gt; grown on SiC), but in fact we had very good experimental data on which phases were actually forming, and just needed the modelling to help to understand &lt;em&gt;why&lt;/em&gt; some phases were favoured in certain growth phases. Even a fairly modest set of simulations was enough to shed some light on it; see&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://aip.scitation.org/doi/pdf/10.1063/1.3559496&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/pdf/10.1063/1.3559496&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;where I only really considered the three conditions Ba-rich, Fe-rich and O-rich, and only considered a subset of the possible phases. E.g. for the iron oxide, I only considered Fe&lt;span class=&quot;math-container&quot;&gt;$_3$&lt;/span&gt;O&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt;, since the main question was why that was forming in the initial growth phase.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2022-12-22T15:17:59.877" LastActivityDate="2022-12-22T15:17:59.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10058" PostTypeId="1" CreationDate="2022-12-06T14:41:08.703" Score="3" ViewCount="135" Body="&lt;p&gt;I am trying to set up a LAMMPS simulation for depositing graphene on a nickel substrate. I am using ReaxFF forcefield. However, the carbon atoms just pass through the nickel atoms. Can anyone help me with this? This is the link to my input file:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/AnishD11/LAMMPS&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/AnishD11/LAMMPS&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;# sample surface deposition script for atoms&#xA;&#xA;units       real&#xA;atom_style      full&#xA;boundary        p p f&#xA;&#xA;lattice     fcc 4.154&#xA;region          box block 0 10 0 10 0 10&#xA;create_box      2 box&#xA;&#xA;region      substrate block INF INF INF INF INF 3&#xA;create_atoms    1 region substrate&#xA;&#xA;pair_style  reaxff NULL&#xA;pair_coeff  * * ffield.reax.FC Ni C&#xA;fix 1 all qeq/reaxff 1 0.0 1.0 1.0e-6 reaxff&#xA;timestep 0.01&#xA;mass        1 58.7&#xA;mass            2 12.0&#xA;&#xA;neigh_modify    delay 0&#xA;neigh_modify    one 1000&#xA;&#xA;group       addatoms type 2&#xA;region          mobile block 0 5 0 5 2 INF&#xA;group       mobile region mobile&#xA;&#xA;compute     add addatoms temp&#xA;compute_modify  add dynamic/dof yes extra/dof 0&#xA;&#xA;fix     2 addatoms nve&#xA;fix     3 mobile temp/berendsen 800.0 800.0 10.0&#xA;fix     4 mobile nve&#xA;&#xA;region          slab block 0 5 0 5 8 9&#xA;fix     5 addatoms deposit 100 2 100 12345 region slab near 1.0 &amp;amp;&#xA;                vz -1.0 -1.0&#xA;fix     6 addatoms wall/reflect zhi EDGE&#xA;&#xA;thermo_style    custom step atoms temp epair etotal press&#xA;thermo          100&#xA;thermo_modify   temp add&#xA;&#xA;dump        1 all atom 10 dump.deposit.atom&#xA;&#xA;#dump       2 all image 50 image.*.jpg type type &amp;amp;&#xA;#       axes yes 0.8 0.02 view 80 -30&#xA;#dump_modify    2 pad 5&#xA;&#xA;#dump       3 all movie 50 movie.mpg type type &amp;amp;&#xA;#       axes yes 0.8 0.02 view 80 -30&#xA;#dump_modify    3 pad 5&#xA;&#xA;run             1000&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6153" LastEditorUserId="201" LastEditDate="2022-12-08T06:04:49.063" LastActivityDate="2022-12-08T06:04:49.063" Title="What causes atoms to not interact in LAMMPS?" Tags="|molecular-dynamics|lammps|forcefields|graphene|doping|" AnswerCount="0" CommentCount="6" ClosedDate="2023-05-28T16:15:53.717" ContentLicense="CC BY-SA 4.0" />
  <row Id="10059" PostTypeId="2" ParentId="10039" CreationDate="2022-12-06T22:48:25.363" Score="4" Body="&lt;p&gt;Just to complement previous and more detailed answers by @Nike Dattani and @Anyon.&#xA;I found a very useful reference to review Modern Fortran and paralellization the book by Milan Curcic: &lt;a href=&quot;https://milancurcic.com/book/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Milan Curcic, Modern Fortran: Building Efficient Parallel Applications, Manning (2020)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I found the book very readable and oriented to learning by doing. The code in the book is accesible in GitHub and probably you can get an electronic copy if you need it.&lt;/p&gt;&#xA;" OwnerUserId="2048" LastActivityDate="2022-12-06T22:48:25.363" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10060" PostTypeId="1" CreationDate="2022-12-07T05:45:32.760" Score="2" ViewCount="42" Body="&lt;p&gt;I'm using Burai, the gui version of Quantum Espresso to carry out SCF calculations for a material. I followed the excellent tutorial series from &lt;a href=&quot;https://www.youtube.com/watch?v=CZS2In5PQqg&amp;amp;list=PLUhYFZgYOn8ejBZZqyK4LsjERNd7KtC8R&amp;amp;index=8&amp;amp;ab_channel=PhysWhiz&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; which carries out the calculations on the silicon example that comes with Burai. I was able to replicate the results successfully.&lt;/p&gt;&#xA;&lt;p&gt;For my own material however the log file shows no iterations. I presume that is because of some problem with my input file.&lt;/p&gt;&#xA;&lt;p&gt;I've uploaded the cif, QE scf input, and log files in this google drive folder &lt;a href=&quot;https://drive.google.com/drive/folders/1UAl6to4rbgUDNkFwjwU_yqBFbsam5gND?usp=share_link&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. For a quick glance, my scf input file opens like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;SYSTEM&#xA;    a                         =  2.18630e+01&#xA;    b                         =  1.29505e+01&#xA;    c                         =  6.12070e+00&#xA;    cosac                     = -2.10096e-01&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  4.10902e+02&#xA;    ecutwfc                   =  4.56558e+01&#xA;    ibrav                     = -12&#xA;    nat                       = 164&#xA;    nspin                     = 1&#xA;    ntyp                      = 4&#xA;    occupations               = &amp;quot;fixed&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  0.00000e+00&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;    starting_magnetization(3) =  0.00000e+00&#xA;    starting_magnetization(4) =  2.00000e-01&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  4.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 4  4  4  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any help would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6361" LastActivityDate="2022-12-08T08:22:43.527" Title="Quantum Espresso log shows no iterations" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-10T00:25:09.477" ContentLicense="CC BY-SA 4.0" />
  <row Id="10061" PostTypeId="1" CreationDate="2022-12-07T07:35:36.220" Score="6" ViewCount="348" Body="&lt;p&gt;I am currently working with a perovskite material which shows forbidden transitions. Older studies used bigger values of &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; in HSE06 calcualtions(to match with experimental Band Gap) but a recent &lt;a href=&quot;https://www.google.com/url?sa=t&amp;amp;rct=j&amp;amp;q=&amp;amp;esrc=s&amp;amp;source=web&amp;amp;cd=&amp;amp;cad=rja&amp;amp;uact=8&amp;amp;ved=2ahUKEwihl6Kv7ub7AhV1TWwGHQyqCWYQFnoECBEQAQ&amp;amp;url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2F10.1021%2Fjacs.6b03207&amp;amp;usg=AOvVaw0h5mP90RuhYjpUYZCYrxYb&quot; rel=&quot;noreferrer&quot;&gt;study&lt;/a&gt; showed that this is not the case. Rather the electronic BG is around 0.98 and optical one is around 1.3. This got me thinking how can we differentiate between the two using DFT? I believe the answer should lie in absorption coefficient or the dielectric constant.&lt;/p&gt;&#xA;&lt;p&gt;In general how can one determine the Optical band gap?&lt;/p&gt;&#xA;&lt;p&gt;A few possible solutions that I have been thinking about&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;strong&gt;Tauc plot -&lt;/strong&gt; we could use the absorption coefficient calculated in order to calculate the BG, obviosuly this is motivated from general experimental methodology.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Using absorption coefficient -&lt;/strong&gt; One can look at the critical values of absorption coefficient in order to see where the Optical BG might be. An example is this &lt;a href=&quot;https://www.researchgate.net/publication/343296983_Physical_properties_of_lead-free_double_perovskites_A2SnI6_A_Cs_Rb_using_ab-initio_calculations_for_solar_cell_applications&quot; rel=&quot;noreferrer&quot;&gt;study&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Using imaginary part of dielectric constant -&lt;/strong&gt; The study in point (2) also says that BG can be determined by looking at the critical BG of imaginary part of dielectric constant but they obtain a different value as compared to Optical BG using (2).&lt;/li&gt;&#xA;&lt;li&gt;Using &lt;strong&gt;Penn's model&lt;/strong&gt;(&lt;span class=&quot;math-container&quot;&gt;$\epsilon(0) \approx1+(\hbar\omega_p/E_g)^2$&lt;/span&gt;) one can relate the static dielectric function and the BG. Again (2) as a example.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Furthermore why don't people generally talk about this? Is it because calculation of Optical properties is more computationally costlier than calculation of Electronic ones?&lt;/p&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2022-12-14T23:00:23.380" Title="Optical Band gap determination from absorption coeffecient using DFT" Tags="|band-structure|electronic-structure|optical-properties|bandgap|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10062" PostTypeId="1" AcceptedAnswerId="10071" CreationDate="2022-12-07T10:12:39.860" Score="2" ViewCount="156" Body="&lt;p&gt;As the title says, I'm interested in performing Transiesta calculations with a device region that needs to be optimized. I read the slides reported here: &lt;a href=&quot;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/tlv14/slides12.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://departments.icmab.es/leem/SIESTA_MATERIAL/Docs/Tutorials/tlv14/slides12.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, I was wondering about the specific procedure regarding the connectivity atoms between the device region and the electrodes. In my case, I don't have a molecule but rather a bulk material presenting defects in the device region. This material is the same as used in the electrode, but without the defects. So should the procedure be:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Define the device region and completely relax it&lt;/li&gt;&#xA;&lt;li&gt;Add one/two electrode layers, relax the structure but constraining the latter layers&lt;/li&gt;&#xA;&lt;li&gt;Add another one/two layers and relax the whole structure constraing the latter added layers&lt;/li&gt;&#xA;&lt;li&gt;Add the 'bulk' electrode with the converged amount of layers, relax the whole structure by constraining the bulk electrode and one/two connectivity layers.&lt;/li&gt;&#xA;&lt;li&gt;Proceed with the transport calculations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I'm still unsure about step 4 and whether I should relax the connectivity layers.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, since in my case the structure is a simple graphene monolayer with an atomic defect in the device region, I was wondering if I should actually do this step by step or go directly to step 4 (and thus construct the whole scattering region and relax the structure by freezing the electrodes+connectivity atoms) would be sufficient.&#xA;Thanks for your help!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2022-12-07T11:46:25.990" LastActivityDate="2022-12-08T19:15:16.150" Title="Transiesta procedure when relaxing the structure" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10063" PostTypeId="2" ParentId="10011" CreationDate="2022-12-07T12:10:16.377" Score="3" Body="&lt;p&gt;There is &lt;em&gt;per see&lt;/em&gt; nothing to prohibit the use of empty orbitals in TranSiesta calculations. In fact, in some cases they are very much required (vacuum spaces between STM tip and sample for instance).&lt;/p&gt;&#xA;&lt;p&gt;However, there are a few details that require extra care.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Adding empty orbitals in the scattering region, but not in the electrodes, may require an extended region of electrode layers between the actual electrode and the device region.&lt;/li&gt;&#xA;&lt;li&gt;The placement of empty orbitals can greatly affect the self-consistency depending on their relative position and how close they are to other orbitals.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;So the answer is &lt;em&gt;no&lt;/em&gt; to your question. But extra care should be taken when using empty orbitals in the device region and not in the electrode region.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2022-12-08T11:46:03.537" LastActivityDate="2022-12-08T11:46:03.537" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10064" PostTypeId="2" ParentId="10061" CreationDate="2022-12-07T20:51:35.340" Score="2" Body="&lt;p&gt;This is not the actual answer that you asked, but you can get some insight from here. I believe the optical gap is equal to the direct electronic gap at T=0K at a certain k point. Still some more points:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The terms optical vs. eletronic gap are typical when talking about solar cell materials (or the reverse process of electroluminescence). This basically goes back to a distinction between different methods of measuring (or using) the energy gap. When you measure the gap opitcally (e.g. you measure optical absorption as a function of wavelength), you do a kind of excitation spectroscopy: the method doesn't change the charge state of the material, i.e., the number of electrons before and after excitation from valence band to conduction band remains the same. If, however, you measure the position of the bands via electron spectroscopy (e.g. photoemission for the valence band and inverse photoemission for the conduction band, or tunneling spectroscopy to masure both), an extra electron is eihter injected into or taken out of the solid during the process. In order to be able to get that extra electron in, you have to overcome the Coulomb repulsion caused by all the other electrons.&lt;/p&gt;&#xA;&lt;p&gt;Therefore an electronic gap is usually larger than an optical gap, and the difference is the Coulomb energy for the particular system. In solids with rather delocalized states, this effect may be negligibly small, but in systems with high spatial localization of the valence and conduction states it can be large (especially in organic solar cells or OLEDs).&lt;/p&gt;&#xA;&lt;p&gt;This efect is not only important for spectroscopy. Also when actually using a device, it makes a difference. In a solar cell, the only important value is the optical gap, because you excite by photons and then separate electrons and holes. In a light-emitting diode, however, applying a bias that correspnds to the optical gap won'tbe enough You have to apply a bias corresponding to the electronic gap, because you first have to inject electrons and holes into the system before they recombine to emit a photon.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Reference: Wegner, Daniel. (2012). Re: What is the basic difference between optical band gap and electrical band gap?. Retrieved from: &lt;a href=&quot;https://www.researchgate.net/post/What_is_the_basic_difference_between_optical_band_gap_and_electrical_band_gap/50741c57e24a460962000000/citation/download&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.researchgate.net/post/What_is_the_basic_difference_between_optical_band_gap_and_electrical_band_gap/50741c57e24a460962000000/citation/download&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="7" LastEditDate="2022-12-14T23:00:23.380" LastActivityDate="2022-12-14T23:00:23.380" CommentCount="4" CommunityOwnedDate="2022-12-14T23:00:31.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="10065" PostTypeId="1" CreationDate="2022-12-07T21:20:32.310" Score="2" ViewCount="75" Body="&lt;p&gt;I have a 3D charge density file, calculated from Quantum Espresso DFT.&lt;/p&gt;&#xA;&lt;p&gt;If someone calculates the total charge (number of electrons) of an unit cell from that cube file (using a numerical approximation method, for example, a spherical integration), what should be the basic mathematical equation to express that?&lt;/p&gt;&#xA;&lt;p&gt;If needed to see the charge density file: &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/10048/si_psuedo.code&quot; rel=&quot;nofollow noreferrer&quot;&gt;3D cube file&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, the DOS integration gives us the electron density at T=0 K using the following equation:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/SKRtB.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SKRtB.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now need to know the equation for total charge (using spherical integration) for the 3D cube file of charge density. Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-12-09T11:46:52.807" Title="What is the basic equation for total charge calculation from a 3D cube file of charge density file?" Tags="|density-functional-theory|charge-density|conceptual-dft|charge-transfer|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10066" PostTypeId="2" ParentId="9993" CreationDate="2022-12-08T00:58:16.900" Score="4" Body="&lt;p&gt;As far as I know, there's no method available for optimizing intermediates with NEB. Same goes for multiple TS. CI-NEB only has &lt;strong&gt;one&lt;/strong&gt; climbing image, which will converge towards the highest point on the band.&lt;/p&gt;&#xA;&lt;p&gt;The workarounds you have is to use a sufficiently large number of images in hope that you get an image close to the intermediate, which you can then use as a starting point for a geometry optimization. To get the other TS, you can then do another CI-NEB from the intermediate to the product or educt depending on which TS is still missing.&lt;/p&gt;&#xA;" OwnerUserId="2044" LastActivityDate="2022-12-08T00:58:16.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10068" PostTypeId="2" ParentId="6304" CreationDate="2022-12-08T08:34:05.617" Score="1" Body="&lt;p&gt;You can choose E-E_best value to be less than 0.01 eV (magnitude) per atom. The E_best is the highest ecutwfc (110 Ry) you considered.&lt;/p&gt;&#xA;&lt;p&gt;So 40 Ry is a rough idea to consider, seeing your results. Though you need to do the kpoint convergence as well to get final decision.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-12-08T08:34:05.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10069" PostTypeId="1" CreationDate="2022-12-08T10:38:17.363" Score="1" ViewCount="299" Body="&lt;p&gt;I have gone through this &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0167732219360416&quot; rel=&quot;nofollow noreferrer&quot;&gt;article&lt;/a&gt; attached, where in the methodology section they mentioned about the simulation being started with NPT ensemble keeping the box constant for 2 ns. And, I have a question regarding that, we usually start with NVT ensemble first to equilibrate and reach desired temperature for the system and then do the NPT to achieve correct density. Also, during NPT, box vector fluctuates to keep the pressure constant. Can anyone explain me.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastEditorUserId="4034" LastEditDate="2022-12-08T10:39:25.260" LastActivityDate="2023-01-08T15:39:26.080" Title="Regarding Simulation Equilibration process" Tags="|molecular-dynamics|computational-chemistry|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10070" PostTypeId="1" CreationDate="2022-12-08T10:44:51.367" Score="1" ViewCount="190" Body="&lt;p&gt;Suppose I have a test calculation, for two atoms in an unit cell. I have the charge density files in 1D and 3D, calculated using pseudopotential approach. How can I do the Bader analysis with QUANTUM ESPRESSO DFT?&lt;/p&gt;&#xA;&lt;p&gt;Could you please explain each steps in easier way with necessary screenshots/codes?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-12-08T10:44:51.367" Title="How to perform Bader charge analysis in QUANTUM ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|charge-density|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-10T17:00:44.627" ContentLicense="CC BY-SA 4.0" />
  <row Id="10071" PostTypeId="2" ParentId="10062" CreationDate="2022-12-08T19:15:16.150" Score="2" Body="&lt;p&gt;The referred slides are just an example of how to fast get a relaxed geometry for complex geometries. Relaxing a geometry with 1000 constraints is slower than relaxing two geometries with 500 constraints (conceptually). So segmenting it for speeding up the process can in some cases be ideal.&lt;/p&gt;&#xA;&lt;p&gt;It is definitely &lt;em&gt;not&lt;/em&gt; a requirement to follow the procedure. Generally, relaxing all in one go is the most generic and accurate procedure, and sometimes (if your initial configuration is a good guess) isn't that much longer than the referenced procedure.&lt;/p&gt;&#xA;&lt;p&gt;Typically the connectivity region should also be somewhat un-relaxed (same relative coordinates as the electrodes), but they can move a little. And it is thus recommended to have 1 or 2 layers with the same relative coordinates as the electrodes. But as everything, testing and knowing your electronic structure will let you bypass general recommendations. Testing is always a good idea.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2022-12-08T19:15:16.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10072" PostTypeId="2" ParentId="10065" CreationDate="2022-12-08T19:24:28.693" Score="3" Body="&lt;p&gt;The cube file contains the density for each grid point.&lt;/p&gt;&#xA;&lt;p&gt;The general formula for calculating the total number of electrons for that unit-cell would be:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n = \iiint \rho(x,y,z)dxdydz&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Each grid point &lt;span class=&quot;math-container&quot;&gt;$\rho(x,y,z)$&lt;/span&gt; contains the energy integrated density &lt;span class=&quot;math-container&quot;&gt;$$\rho(x,y,z)=\int_{-\infty}^{E_F} DOS(E,x,y,z) dE$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In some cases, the cube files may contain LDOS quantities, that is charge in some energy range so that the 2nd equation has different bounds, but that may be code specific (I am not sure what QE can do here).&lt;/p&gt;&#xA;&lt;p&gt;Numerically, say in Python, one would just do: &lt;code&gt;np.sum(grid) * volume / grid.size&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2022-12-09T11:46:52.807" LastActivityDate="2022-12-09T11:46:52.807" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10074" PostTypeId="2" ParentId="9982" CreationDate="2022-12-09T02:34:02.270" Score="4" Body="&lt;p&gt;The short answer is that you should test &lt;code&gt;ecutrho&lt;/code&gt; as well, which is why Quantum Espresso (and other plane-wave DFT programs) allow you to set it as a semi-independent parameter. The range of good choices depends on other details of your calculation, in particular the:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;wavefunction cut-off energy, &lt;code&gt;ecutwfc&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;pseudopotential method&lt;/li&gt;&#xA;&lt;li&gt;exchange-correlation functional&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As a rough guide, a reasonable compromise between accuracy and computational efficiency is often found for &lt;code&gt;ecutrho&lt;/code&gt; between  4&lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt;&lt;code&gt;ecutwfc&lt;/code&gt; and 9&lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt;&lt;code&gt;ecutwfc&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Wavefunction cut-off energy&lt;/h3&gt;&#xA;&lt;p&gt;The so-called &amp;quot;soft&amp;quot; density, &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt;, is related to the Kohn-Sham wavefunctions by,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho(r) = \sum_{bk}f_{bk} \left\vert\psi_{bk}(r)\right\vert^2, \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f_{bk}$&lt;/span&gt; is the band occupancy (and I've ignored spin degeneracy and k-point weights, for simplicity).&lt;/p&gt;&#xA;&lt;p&gt;Since the density depends on the wavefunctions to the power of &lt;em&gt;two&lt;/em&gt;, the density has Fourier components up to &lt;em&gt;twice&lt;/em&gt; the wavevector. We may write,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G_\mathrm{cut}^\rho = 2 G_\mathrm{cut}^\psi \tag{2}&#xA;$$&lt;/span&gt;&#xA;where the two &lt;span class=&quot;math-container&quot;&gt;$G_\mathrm{cut}$&lt;/span&gt; scalars refer to the cut-off reciprocal lattice vectors for the density and wavefunctions.&lt;/p&gt;&#xA;&lt;p&gt;The cut-off energy depends on the wavevector &lt;em&gt;squared&lt;/em&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;E_\mathrm{cut}^\psi &amp;amp;\propto \left\vert G_\mathrm{cut}^\psi\right\vert^2\\&#xA;E_\mathrm{cut}^\rho &amp;amp;\propto \left\vert G_\mathrm{cut}^\rho\right\vert^2\\&#xA;                    &amp;amp;= \left\vert 2G_\mathrm{cut}^\psi\right\vert^2\\&#xA;                    &amp;amp;= 4\left\vert G_\mathrm{cut}^\psi\right\vert^2\\&#xA;                    &amp;amp;= 4E_\mathrm{cut}^\psi. \tag{3}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;Thus we see that for the &amp;quot;soft&amp;quot; density, we require &lt;code&gt;ecutrho&lt;/code&gt; (&lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt;) to be four times &lt;code&gt;ecutwfc&lt;/code&gt; (&lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\psi$&lt;/span&gt;) in order to capture all of the contributions from &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Short-cuts&lt;/h4&gt;&#xA;&lt;p&gt;At high cut-off energies, the plane-wave coefficients (&lt;span class=&quot;math-container&quot;&gt;$c_{Gbk}$&lt;/span&gt;) for the plane-waves with the highest kinetic energy are very small (&lt;span class=&quot;math-container&quot;&gt;$c_{Gbk}\rightarrow 0$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\vert G \vert\rightarrow \infty$&lt;/span&gt;). The Fourier components of the density are a convolution of the wavefunction's Fourier components, which means that the large wavevector components of the density go to zero even quicker than the wavefunction's plane-wave coefficients.&lt;/p&gt;&#xA;&lt;p&gt;For sufficiently high &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\psi$&lt;/span&gt;, the large &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; components of the density may be neglected, in which case a value of &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; less than &lt;span class=&quot;math-container&quot;&gt;$4E_\mathrm{cut}^\psi$&lt;/span&gt; may be used safely. This is an approximation, but can speed up calculations on smaller systems where the Fourier transforms are a relatively large proportion of the computational effort, and reduce memory because the density grid storage is a significant fraction of the storage required.&lt;/p&gt;&#xA;&lt;h3&gt;Pseudopotential method&lt;/h3&gt;&#xA;&lt;p&gt;For conventional norm-conserving pseudopotentials, the &amp;quot;soft&amp;quot; density is the only contribution to the electronic density, &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt;; however, modern pseudopotentials often include &lt;em&gt;charge augmentation&lt;/em&gt; (ultrasoft, PAW, even modern norm-conserving pseudopotentials) and so,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho(r) = \rho^\mathrm{soft}(r) + \rho^\mathrm{aug}(r). \tag{4}&#xA;$$&lt;/span&gt;&#xA;In contrast to &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{soft}(r)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{aug}(r)$&lt;/span&gt; does &lt;em&gt;not&lt;/em&gt; principally depend on the wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;, but on the pseudoatomic augmentation charges &lt;span class=&quot;math-container&quot;&gt;$Q(r)$&lt;/span&gt;, which are properties of the pseudopotential. These augmentation charges are actually &lt;em&gt;designed&lt;/em&gt; to contain the high-wavevector components of the charge density, and so they typically require significantly finer real-space grids (and hence larger Fourier wavevectors) to represent them accurately.&lt;/p&gt;&#xA;&lt;p&gt;When performing calculations with these pseudopotentials, &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; is typically a higher multiple of &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\psi$&lt;/span&gt; than it would be for conventional norm-conserving potentials. If your simulation has chemical elements with dense semicore states (e.g. &lt;span class=&quot;math-container&quot;&gt;$d-$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$f-$&lt;/span&gt; states), then the charge augmentation functions &lt;span class=&quot;math-container&quot;&gt;$Q(r)$&lt;/span&gt; will have very large Fourier components, and you will probably need &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; to be much larger than &lt;span class=&quot;math-container&quot;&gt;$4E_\mathrm{cut}^\psi$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note that &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; is higher &lt;em&gt;as a multiple of &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\psi$&lt;/span&gt;&lt;/em&gt;, but it is &lt;em&gt;not&lt;/em&gt; usually much larger in absolute terms, since the same physical charge density features should be present regardless of the pseudopotential formalism chosen. The advantage of the charge augmentation approach, however, is that by moving the high-wavevector components into &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{aug}$&lt;/span&gt;, they no longer have to be represented by &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{soft}$&lt;/span&gt; and so a lower plane-wave cut-off energy may be used for the wavefunctions.)&lt;/p&gt;&#xA;&lt;h3&gt;Exchange-correlation functional&lt;/h3&gt;&#xA;&lt;p&gt;At first glance, the choice of exchange-correlation functional would not appear to have any bearing on &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt;, beyond any effect on the pseudopotential augmentation charges (since we use pseudopotentials generated with the same exchange-correlation functional). However, &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; defines the Fourier and real-space grids used not only for the &lt;em&gt;densities&lt;/em&gt;, but also the &lt;em&gt;potentials&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If we look at the Hartree potential &lt;span class=&quot;math-container&quot;&gt;$\widetilde{V}_H(G)$&lt;/span&gt; in Fourier space, we see that,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\widetilde{V}_H(G) \propto \frac{\widetilde{\rho}(G)}{\vert G\vert^2} \tag{5}&#xA;$$&lt;/span&gt;&#xA;and so the large &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; components of the density are actually &lt;em&gt;suppressed&lt;/em&gt; (because they are divided by &lt;span class=&quot;math-container&quot;&gt;$\vert G\vert^2$&lt;/span&gt;), and we could even use a &lt;em&gt;lower&lt;/em&gt; cut-off energy for this contribution. (Side-note: the small &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; components of the density are &lt;em&gt;enhanced&lt;/em&gt;, which is a major contributor to charge-sloshing instabilities in SCF methods.)&lt;/p&gt;&#xA;&lt;p&gt;If we look at the local density approximation to exchange-correlation, we have,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{xc}^{LDA}(r) \propto \rho(r)^\frac{1}{3}  \tag{6}&#xA;$$&lt;/span&gt;&#xA;which also suppresses the contributions for large &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;, since the power is less than 1.&lt;/p&gt;&#xA;&lt;p&gt;When we consider more sophisticated exchange-correlation functionals, they often include terms with the gradient of the density, &lt;span class=&quot;math-container&quot;&gt;$\nabla \rho$&lt;/span&gt;. In Fourier space, a real-space derivative multiplies each Fourier coefficient by &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; times its corresponding wavevector (&lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;), i.e.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\widetilde{\nabla \rho}(G) \propto iG \widetilde{\rho}(G), \tag{7}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is the imaginary number. This actually &lt;em&gt;enhances&lt;/em&gt; contributions from the coefficients for large &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;-vectors, and means that it is common for GGA exchange-correlation functionals to need larger values for &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}^\rho$&lt;/span&gt; than the corresponding LDA calculations. This is even more pronounced for meta-GGAs, as well as any functionals involving multiple density (or wavefunction) products, such as hybrid functionals.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-12-09T02:34:02.270" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10075" PostTypeId="1" CreationDate="2022-12-09T04:30:49.290" Score="6" ViewCount="591" Body="&lt;p&gt;I have a cube file of charge density. The unit cell consists two silicon atoms.&lt;/p&gt;&#xA;&lt;p&gt;If I use a python code to calculate the net charge of the system, it results around 24, which is ok because the pseudopotential of each silicon atom consists 12 electrons. The code is given at the end, if needed to see.&lt;/p&gt;&#xA;&lt;p&gt;Now, I would request your help to have a python code that can actually calculate charge of an individual Si atom from that cube file (rather than considering both the atoms)? I think the charge should be around 12 for this case (for individual atom). May be a spherical integration up to a certain cutoff limit can help (I am not sure though about how to select that limit/radius). Please help, if you have some time.&lt;/p&gt;&#xA;&lt;p&gt;Here is the cube file: &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/blob/master/10048/si_psuedo.code&quot; rel=&quot;noreferrer&quot;&gt;3D charge density&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the python code that can calculate the total charge from that cube file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import numpy as np&#xA;import sys&#xA;&#xA;class CHD():&#xA;  def __init__(self):&#xA;    #This simply allocates the different data structures we need:&#xA;    self.natoms = 0&#xA;    self.grid = np.zeros(0)&#xA;    self.v = np.zeros([3,3])&#xA;    self.N = np.zeros([3])&#xA;    self.dV = 0&#xA;&#xA;  def set_dV(self):&#xA;    #The charge density is stored per volume. If we want to integrate the charge density&#xA;    #we need to know the size of the differential volume &#xA;    self.dV = 0&#xA;    x = self.v[:,0]&#xA;    y = self.v[:,1]&#xA;    z = self.v[:,2]&#xA;    self.dV = np.dot(x,np.cross(y,z))&#xA;&#xA;  def integrate(self):&#xA;    #This allows us to integrate the stored charge density&#xA;    return(np.sum(self.grid)*self.dV)&#xA; &#xA;#The following function reads the charge density from a cube file &#xA;def read(cubefile):&#xA;  density = CHD()&#xA;  f = open(cubefile,'r')&#xA;  #skip two header lines&#xA;  next(f)&#xA;  next(f)&#xA;  line = next(f)&#xA;  #Get the number of atoms if we want to store it&#xA;  density.natoms = int(line.split()[0])&#xA;  #This gets the nx,ny,nz info of the charge density&#xA;  #As well as the differential volume&#xA;  for i in range(0,3):&#xA;    line = next(f).split()&#xA;    density.N[i] = int(line[0])&#xA;    for j in range(1,4):&#xA;      density.v[i][j-1] = float(line[j])&#xA;&#xA;  #As of now we dont care about the positions of the atoms,&#xA;  #But if you did you could read them here:&#xA;  for i in range(0,density.natoms):&#xA;    next(f)&#xA;&#xA;  density.set_dV()&#xA;  density.grid = np.zeros(int(density.N[0]*density.N[1]*density.N[2]))&#xA;&#xA;  #This reads the data into a 1D array of size nx*ny*nz&#xA;  count = 0&#xA;  for i in f:&#xA;    for j in i.split():&#xA;      density.grid[count] = float(j)&#xA;      count+=1&#xA;  f.close()&#xA;  &#xA;  return density&#xA;&#xA;if __name__ == &amp;quot;__main__&amp;quot;:&#xA;  if len(sys.argv) != 2:&#xA;    print(&amp;quot;Incorrect number of arguments, run as ./ChargeDensity.py CUBEFILELOCATION&amp;quot;)&#xA;    sys.exit(6)&#xA;  density = read(sys.argv[1])  &#xA;  #For the main function I care about the total number of electrons&#xA;  print(density.integrate())&#xA;# Code source (from Dr. Levi): https://github.com/levilentz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above python script runs as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python ChargeDensity.py si_pseudo.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2022-12-09T15:35:09.977" Title="How to calculate the individual atomic charge from a cube file of charge density?" Tags="|density-functional-theory|python|charge-density|conceptual-dft|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10076" PostTypeId="2" ParentId="10075" CreationDate="2022-12-09T11:05:40.933" Score="3" Body="&lt;p&gt;I do not have a python code for you.&#xA;But I could direct 2 post-processing open software you could use to calculate individual charge of your atoms.&lt;/p&gt;&#xA;&lt;p&gt;(1) MultiWfn (&lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/multiwfn/&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;(2) Bader Charge Analysis (&lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://theory.cm.utexas.edu/henkelman/code/bader/&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Bader Charge Analysis is based on charge density partitioning developed by, you guessed it, Bader.&#xA;Multiwfn can do other charge integration based on different partitioning such as tessellations.&lt;/p&gt;&#xA;&lt;p&gt;I suggest trying them out with tutorial samples before applying it for your system.&lt;/p&gt;&#xA;&lt;p&gt;Cheers!&lt;/p&gt;&#xA;" OwnerUserId="4558" LastActivityDate="2022-12-09T11:05:40.933" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10077" PostTypeId="2" ParentId="10018" CreationDate="2022-12-09T12:00:42.230" Score="3" Body="&lt;p&gt;Quick answer: &lt;strong&gt;No,&lt;/strong&gt; connectivity is not required to start a Gaussian job.&lt;/p&gt;&#xA;&lt;p&gt;The error message in your gjf file says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;QPErr --- A syntax error was detected in the input line. 1 3 1.0 2 1.0 4 1.0 5 1.0&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This simply means that your file was written in the &lt;em&gt;&lt;strong&gt;wrong format&lt;/strong&gt;&lt;/em&gt;.&#xA;Take note of line spacing and such when manually preparing your gjf.&#xA;If you can post your original gjf file, maybe we can help.&lt;/p&gt;&#xA;" OwnerUserId="4558" LastActivityDate="2022-12-09T12:00:42.230" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10078" PostTypeId="1" AcceptedAnswerId="10124" CreationDate="2022-12-09T14:05:30.420" Score="1" ViewCount="74" Body="&lt;p&gt;Installing the basic version of PSI4 on my personal LG Gram 360 (with a Windows OS), used as a my-own WebMO Basic server, was done according to the WebMO tutorial. I then tried to compute the energy of hexaiodostannate(IV) at the wB97X-2(TQZ)/def2-TZVPPD level of theory, a level that is outside of the 45sec CPU time limit of the WebMO demo server- turned out that I needed the beta5 (or at least beta3) version of the package to use said functional.&lt;/p&gt;&#xA;&lt;p&gt;A quick Google search lead to a precompiled zip file that is supoosed to be &amp;quot;directly usable w.r.t. WebMO&amp;quot;; I don't know what exactly I should do with that file, so I need help.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2022-12-11T14:28:59.797" LastActivityDate="2022-12-19T10:14:24.563" Title="How do I install the beta5 version of PSI4 on my WebMO Basic server?" Tags="|software|software-assistance|psi4|windows-operating-system|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10079" PostTypeId="2" ParentId="10075" CreationDate="2022-12-09T15:35:09.977" Score="4" Body="&lt;p&gt;If you have a .CUB or .CUBE file already then it is as simple as using this python library- &lt;a href=&quot;https://github.com/funkymunkycool/Cube-Toolz&quot; rel=&quot;nofollow noreferrer&quot;&gt;CubeToolz&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It can perform the following operations:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Read and write Gaussian cube files&lt;/li&gt;&#xA;&lt;li&gt;Translate and rotate cube data&lt;/li&gt;&#xA;&lt;li&gt;Integrate around a particular atom&lt;/li&gt;&#xA;&lt;li&gt;Integrate around a sphere&lt;/li&gt;&#xA;&lt;li&gt;Integrate around the whole cube file&lt;/li&gt;&#xA;&lt;li&gt;Take the planar average&#xA;Add/subtract/multiply cube files&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The relevant option for you is to integrate the whole cube file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cube_tools.py -i file.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is one of my go-to libraries for analyzing densities in .CUBE format.&lt;/p&gt;&#xA;" OwnerDisplayName="user6041" LastActivityDate="2022-12-09T15:35:09.977" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10080" PostTypeId="2" ParentId="142" CreationDate="2022-12-09T15:52:36.967" Score="5" Body="&lt;p&gt;You can also simulate powder diffraction patterns from a .CIF file, right on your Android smartphone using my app:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://play.google.com/store/apps/details?id=com.bragitoff.powderdiffractionsimulator&quot; rel=&quot;noreferrer&quot;&gt;CrysX-Crystallographic Tools&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It works best with .CIF files obtained from &lt;a href=&quot;https://materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;materialsproject.org&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VZAuLm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VZAuLm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/cfG4Um.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cfG4Um.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/q7fQAm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q7fQAm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is a YouTube tutorial:&#xA;&lt;a href=&quot;https://www.youtube.com/watch?v=lkCeZgS35b8&quot; rel=&quot;noreferrer&quot;&gt;https://www.youtube.com/watch?v=lkCeZgS35b8&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For further information on how the calculation is done, you can refer to my blog posts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.bragitoff.com/2018/10/x-ray-diffraction-xrd-pattern-simulator-c-program-ver-2-tutorial/&quot; rel=&quot;noreferrer&quot;&gt;https://www.bragitoff.com/2018/10/x-ray-diffraction-xrd-pattern-simulator-c-program-ver-2-tutorial/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.bragitoff.com/2018/10/atomic-form-factor-calculator-table/&quot; rel=&quot;noreferrer&quot;&gt;https://www.bragitoff.com/2018/10/atomic-form-factor-calculator-table/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.bragitoff.com/2018/10/structure-factor-calculator-c-program/&quot; rel=&quot;noreferrer&quot;&gt;https://www.bragitoff.com/2018/10/structure-factor-calculator-c-program/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerDisplayName="user6041" LastActivityDate="2022-12-09T15:52:36.967" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10081" PostTypeId="2" ParentId="9142" CreationDate="2022-12-10T17:14:20.290" Score="2" Body="&lt;p&gt;This is Fig 3 of the PDF that you linked to us, as pointed out in the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9142/what-is-the-curve-fitting-model-used-for-qubit-protein-assay#comment19110_9142&quot;&gt;comment by Anyon&lt;/a&gt;. The captio to Fig 3 is:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Figure  3. The  curve-fitting  algorithm  used  to  determine  concentration  in  the  Qubit™  protein  assay.  The  Qubit®  2.0 Fluorometer  generates  concentration  data  based  on  the  relationship  between  the  two  standards  used  in  calibration. This  plot  shows  the  line  corresponding  to  the  curve-fitting  algorithm  (a  modified  Hill  plot)  used  in  the  calculation  of concentration data for the Qubit™ protein assay. For reference, the positions of the standards and a set of data points from an actual experiment are shown superimposed onto the line, demonstrating that the curve-fitting algorithm gives accurate values for quantitation.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The curve in the figure also does look like one that you would get from a &lt;a href=&quot;https://en.wikipedia.org/wiki/Hill_equation_(biochemistry)&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hill equation&lt;/a&gt; (nevermind the log-log &amp;quot;&lt;a href=&quot;https://chem.libretexts.org/Courses/CSU_Chico/CSU_Chico%3A_CHEM_451_-_Biochemistry_I/CHEM_451_Test/07%3A_Binding/7.3%3A_Model_Binding_Systems/C3._Mathematical_Analysis_of_Cooperative_Binding_-_Hill_Plot&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hill plot&lt;/a&gt;&amp;quot; which is different). The word Hill only appears in that 9-page PDF document once (in precisely the quote figure caption above), so it doesn't look like they wanted to tell you any more.&lt;/p&gt;&#xA;&lt;p&gt;At the top of the PDF we see two commercial company's names, &lt;a href=&quot;https://en.wikipedia.org/wiki/Invitrogen&quot; rel=&quot;nofollow noreferrer&quot;&gt;Invitrogen&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_Probes&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Probes&lt;/a&gt; and the PDF is about the trademarked &amp;quot;Qubit™ Protein Assay Kits For use with the Qubit® 2.0 Fluorometer&amp;quot;, which means that we're probably not dealing with open accecss science, but with commercial products, which rarely disclose details about calculations to the extent that (some!) scientists more often do when publishing academic papers.&lt;/p&gt;&#xA;&lt;p&gt;You can try to contact them (all this information was fortunately in the PDF to which you provided a link), but I'm not sure if the model matters to you enough to bother with that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Molecular Probes, Inc.  &lt;br&gt;&#xA;29851 Willow Creek Road &lt;br&gt;&#xA;Eugene, OR 97402&lt;br&gt;&#xA;Phone: (541) 465-8300 &lt;br&gt;&#xA;Fax: (541) 335-0504&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Customer Service:&#xA;6:00 am to 4:30 pm (Pacific Time) &lt;br&gt;&#xA;Phone: (541) 335-0338 &lt;br&gt;&#xA;Fax: (541) 335-0305 &lt;br&gt;&#xA;probesorder@invitrogen.com&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Toll-Free Ordering for USA: &lt;br&gt;&#xA;Order Phone: (800) 438-2209 &lt;br&gt;&#xA;Order Fax: (800) 438-0228 &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Technical Service:8:00 am to 4:00 pm (Pacific Time)&lt;br&gt;&#xA;Phone: (541) 335-0353 &lt;br&gt;&#xA;Toll-Free (800) 438-2209 &lt;br&gt;&#xA;Fax: (541) 335-0238&lt;br&gt;&#xA;probestech@invitrogen.com&lt;/p&gt;&#xA;&lt;p&gt;Invitrogen European Headquarters Invitrogen, Ltd.&lt;br&gt;&#xA;3 Fountain Drive&lt;br&gt;&#xA;Inchinnan Business Park Paisley PA4 9RF, UK &lt;br&gt;&#xA;Phone: +44 (0) 141 814 6100 &lt;br&gt;&#xA;Fax: +44 (0) 141 814 6260 &lt;br&gt;&#xA;Email: euroinfo@invitrogen.com&lt;br&gt;&#xA;Technical Services: eurotech@invitrogen.com&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The link that you gave us happened to be hosted on a &lt;a href=&quot;https://www.smith.edu&quot; rel=&quot;nofollow noreferrer&quot;&gt;Smith College&lt;/a&gt; server for the &amp;quot;&lt;a href=&quot;https://www.science.smith.edu/cmbs&quot; rel=&quot;nofollow noreferrer&quot;&gt;Center for Molecular Biology (CMB)&lt;/a&gt;&amp;quot;  but there's not &amp;quot;About us&amp;quot; or &amp;quot;People&amp;quot; page so it's hard to see who the contact person would be. Likely the PDF was not on the Smith College website due to them having anything to do with product, other than the fact that it's &lt;a href=&quot;https://www.science.smith.edu/cmbs/equipment/&quot; rel=&quot;nofollow noreferrer&quot;&gt;equipment&lt;/a&gt; that's available to their students. The only email address I found on the CMB website after a few clicks and a couple minutes was given here:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Users will need to be granted access to use the equipment by the CMB’s ITI, Riccardo Racicot, at rracicot@smith.edu&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-12-10T17:14:20.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10082" PostTypeId="5" CreationDate="2022-12-10T17:33:22.927" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Proprietary_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Proprietary_software&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-10T17:33:22.927" LastActivityDate="2022-12-10T17:33:22.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10083" PostTypeId="4" CreationDate="2022-12-10T17:33:22.927" Score="0" Body="Careful! It can be very difficult to answer a question about a commercial product without asking the creator of the product directly. Please be considerate of that before asking a question about a proprietary or commercial or closed-source product." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-10T17:33:22.927" LastActivityDate="2022-12-10T17:33:22.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10084" PostTypeId="1" CreationDate="2022-12-11T01:22:16.473" Score="4" ViewCount="238" Body="&lt;p&gt;Suppose you have a two atom cubic cell, and you have calculated the atomic PDOS.&#xA;Does integrating the atomic PDOS and summing them to Fermi energy give exactly the total charge of a system?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="403" LastEditDate="2022-12-11T19:58:04.887" LastActivityDate="2022-12-11T19:58:04.887" Title="Does integrating PDOS give total charge of a system?" Tags="|density-of-states|charge-density|conceptual-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10085" PostTypeId="2" ParentId="10084" CreationDate="2022-12-11T02:24:54.430" Score="7" Body="&lt;p&gt;You shouldn't integrate to the Fermi energy, unless you want the T = 0 K result and that was what you computed with your DFT program (which is actually quite difficult to get).&lt;/p&gt;&#xA;&lt;p&gt;The correct expression is the integral over all energies of the DOS multiplied by the broadening function (the occupation of the states), and if you want to get the total number of electrons then you should use exactly the same function and smearing width as the DFT program used.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;N = \int_{-\infty}^\infty f\left(\frac{E-E_F}{\sigma}\right)g(E)dE \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of electrons, &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the broadening function with width &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and Fermi energy &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; is the DOS.&lt;/p&gt;&#xA;&lt;p&gt;Note that, in practice, you don't actually have to integrate to &lt;span class=&quot;math-container&quot;&gt;$\infty$&lt;/span&gt; since the broadening function decays to zero for &lt;span class=&quot;math-container&quot;&gt;$E&amp;gt;&amp;gt;E_F$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you integrate the PDOS rather than the DOS, then you will usually get a slightly smaller value from the integral, because of the spilling factor; i.e. not all of the states of a real material or molecule can be represented as a sum of a few atomic-like (usually hydrogenic or pseudoatomic) orbitals.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-12-11T02:24:54.430" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10086" PostTypeId="1" CreationDate="2022-12-11T08:59:34.757" Score="7" ViewCount="283" Body="&lt;p&gt;I have been studying liquid systems (particularly deep eutectic solvents) using classical molecular dynamics (MD) simulations. The main drawback of classical MD is the arbitrariness of the potential parameters and hence it doesn't give accurate results for different experiments. I am planning to pursue &lt;em&gt;ab initio&lt;/em&gt; MD simulations for such kind of systems, but I have no experience in any kind of &lt;em&gt;ab initio&lt;/em&gt; methods.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can you guys suggest tools (preferably free to use academic software) to start with such &lt;em&gt;ab initio&lt;/em&gt; MD simulation for liquid systems?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5103" LastEditorUserId="5" LastEditDate="2022-12-11T22:56:12.500" LastActivityDate="2022-12-12T18:26:16.797" Title="Ab-initio molecular dynamics of liquid systems: best tools and resources" Tags="|molecular-dynamics|ab-initio-calculations|software-recommendations|one-topic-per-answer|cp2k|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10088" PostTypeId="2" ParentId="9107" CreationDate="2022-12-11T10:45:18.200" Score="5" Body="&lt;p&gt;A similar question has been &lt;a href=&quot;https://groups.google.com/g/cp2k/c/kkZDig18nE4&quot; rel=&quot;noreferrer&quot;&gt;asked&lt;/a&gt; on the cp2k mailing list.&lt;/p&gt;&#xA;&lt;p&gt;The relevant settings are the &lt;code&gt;MOTION&lt;/code&gt; / &lt;code&gt;MD&lt;/code&gt; / &lt;code&gt;ENSEMBLE&lt;/code&gt; keyword (set to &lt;code&gt;LANGEVIN&lt;/code&gt;), and the&#xA;&lt;code&gt;MOTION&lt;/code&gt; / &lt;code&gt;MD&lt;/code&gt; / &lt;code&gt;LANGEVIN&lt;/code&gt; section.&lt;/p&gt;&#xA;&lt;p&gt;Further suggestions from Marcella Iannuzzi in the thread:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Always start sgcpmd from a well converged wfn obtained along a standard BOMD run with diagonalisation and smearing&lt;/li&gt;&#xA;&lt;li&gt;Let the first steps run on many scf iterations if needed, i.e., set MAX_SCF large enough&lt;/li&gt;&#xA;&lt;li&gt;But use a relative large eps_scf. The wfn is not going to be optimised as in the BOMD, energy convergence  around 10^-5 is&#xA;desirable&lt;/li&gt;&#xA;&lt;li&gt;Use FULL_ALL preconditioner + ASPC&lt;/li&gt;&#xA;&lt;li&gt;Use a small time step&lt;/li&gt;&#xA;&lt;li&gt;Tune properly GAMMA and NOISY_GAMMA&lt;/li&gt;&#xA;&lt;li&gt;Monitor the conservation of energy and the temperature per kind or per region : TEMP_KIND&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="873" LastActivityDate="2022-12-11T10:45:18.200" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10089" PostTypeId="2" ParentId="10052" CreationDate="2022-12-11T19:20:51.400" Score="1" Body="&lt;p&gt;You can specify &lt;code&gt;outside box A B C D E F&lt;/code&gt; for a particular species or structure to be placed outside a region. This statement goes inside the &lt;code&gt;structure&lt;/code&gt; block the same way as the &lt;code&gt;inside box A B C D E F&lt;/code&gt; statement, where A B C are minimum coordinates and D E F are maximum coordinates.&lt;/p&gt;&#xA;&lt;p&gt;Then if you make all molecules of all kinds and structures be &lt;code&gt;outside&lt;/code&gt; of a particular region, that will be your vacuum.&lt;/p&gt;&#xA;&lt;p&gt;To ensure that the total dimensions are approximately what you request, use &lt;code&gt;add_box_sides X&lt;/code&gt; at the end of the packmol input script after all the &lt;code&gt;structure&lt;/code&gt; blocks. That will add explicit dimensions to the output file if that file is &lt;code&gt;xyz&lt;/code&gt; and make the total dimensions be &lt;em&gt;approximately&lt;/em&gt; (largest box dimension) + 2 * X. I am not sure why the correspondence between the resulting output and (box size) + 2 * X is not always exact, but it has always been close enough for my personal applications.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-12-11T19:54:05.157" LastActivityDate="2022-12-11T19:54:05.157" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10090" PostTypeId="2" ParentId="8981" CreationDate="2022-12-12T02:08:22.353" Score="2" Body="&lt;p&gt;Finally, I figured out how to arrive at that. The way I found is using the &lt;a href=&quot;http://webbdcrista1.ehu.es/magndata/index.php?adser=1&amp;amp;ord=id&amp;amp;ord_mode=asc&amp;amp;0px=0px&amp;amp;1p0px=1p0px&amp;amp;1px=1px&amp;amp;2px=2px&amp;amp;3px=3px&amp;amp;1p1px=1p1px&quot; rel=&quot;nofollow noreferrer&quot;&gt;MAGNDATA database&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Just by choosing the &lt;em&gt;parent space group&lt;/em&gt;, for example, &lt;em&gt;hexagonal&lt;/em&gt;, you can obtain many structures, listed in a table. At the last line of that table, you can find the corresponding MPG, for example, &lt;span class=&quot;math-container&quot;&gt;$6'mm'$&lt;/span&gt;. Note that there are many choices you can pick rather than the &lt;em&gt;parent space group&lt;/em&gt; to narrow the content of the table.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastEditorUserId="5" LastEditDate="2022-12-12T02:26:56.623" LastActivityDate="2022-12-12T02:26:56.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10091" PostTypeId="2" ParentId="9098" CreationDate="2022-12-12T10:22:05.310" Score="2" Body="&lt;p&gt;The answer is not the actual solution to the error posted but a workaround.&lt;/p&gt;&#xA;&lt;p&gt;This is what I learned from the GROMACS mailing list:&lt;/p&gt;&#xA;&lt;p&gt;There is a minimum cell length for each domain decomposition cell in each dimension, which depends on the chosen cutoff radii and possibly&#xA;other inter-atomic constraints. So this is normally just a technical&#xA;limitation and not a problem with the MD system. [&lt;a href=&quot;https://www.mail-archive.com/gromacs.org_gmx-users@maillist.sys.kth.se/msg23780.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Source&lt;/a&gt;]&lt;/p&gt;&#xA;&lt;p&gt;For a successful domain decomposition, your box size must be twice your system's largest bond (couldn't find the reference, sorry). Since my restraints are quite large in length compared to a typical bond, I see this error often.  So, I came up with the idea of not using bonded restraints in this case. Instead, use pulling, but keep the rate of pulling to &lt;code&gt;zero&lt;/code&gt;, such that you are maintaining the distance between the atoms to be pulled fixed.&lt;/p&gt;&#xA;&lt;p&gt;Here is the snippet of pull-code I used&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pull-group1-name     = R1&#xA;pull-group2-name     = R2&#xA;pull-coord1-groups   = 1 2&#xA;pull-coord1-type     = umbrella&#xA;pull-coord1-geometry = distance&#xA;pull-coord1-dim      = Y Y Y&#xA;pull-coord1-k        = 3000&#xA;pull-coord1-init     = 1.2130461160248225&#xA;pull-coord1-rate     = 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The domain-decomposition error can also arise in a normal system without any bonded restraints; It is usually due to the size of the system. If the size of your system is small and the requested number of cores is large, then you may have a bad domain decomposition. The only way to overcome this is to increase your system size by increasing your box size (viz. adding more water molecules) or decreasing the total number of cores. A good rule of thumb is ~100 atoms per core.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="3593" LastEditDate="2022-12-12T14:46:26.420" LastActivityDate="2022-12-12T14:46:26.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10092" PostTypeId="2" ParentId="1215" CreationDate="2022-12-12T12:29:08.770" Score="2" Body="&lt;h2&gt;NAMD&lt;/h2&gt;&#xA;&lt;p&gt;A MD simulation software which can run any system but has been particularly developed for the target audience that study biomolecular systems (proteins, lipid bilayers, etc.)&lt;/p&gt;&#xA;&lt;p&gt;They have multiple pre-compiled versions for running in Windows machines, including versions that can be used in HPCs and GPU based accelaration using CUDA. (You can download CUDA toolkit for Windows from &lt;a href=&quot;https://developer.nvidia.com/cuda-downloads?target_os=Windows&amp;amp;target_arch=x86_64&amp;amp;target_version=10&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Win64 (Windows 7, 8, 10, etc.)&lt;/li&gt;&#xA;&lt;li&gt;Win64-CUDA (NVIDIA CUDA acceleration)&lt;/li&gt;&#xA;&lt;li&gt;Win64-MPI (Windows HPC Server, multi-copy algorithms)&lt;/li&gt;&#xA;&lt;li&gt;Win64-MPI-smp-CUDA (HPC Server with CUDA)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You can download these different &lt;a href=&quot;https://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=NAMD&quot; rel=&quot;nofollow noreferrer&quot;&gt;binaries&lt;/a&gt; from here, they're free to use for academic users.&lt;/p&gt;&#xA;&lt;p&gt;They also have a nice &lt;a href=&quot;https://www.ks.uiuc.edu/Training/Tutorials/namd/namd-tutorial-win.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt; for starting and running simple MD simulation for their Windows version of NAMD.&lt;/p&gt;&#xA;&lt;p&gt;The visualization software &lt;a href=&quot;http://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VMD&lt;/a&gt; is also developed by the same group and therefore NAMD has multiple functionalities that can be availed through VMD - like running a MD simulation, analysing MD trajectories from NAMD etc.&lt;/p&gt;&#xA;" OwnerUserId="5103" LastEditorUserId="5103" LastEditDate="2022-12-12T12:35:29.987" LastActivityDate="2022-12-12T12:35:29.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10094" PostTypeId="2" ParentId="9071" CreationDate="2022-12-12T15:23:45.350" Score="1" Body="&lt;p&gt;This was answered after being re-asked on the &lt;a href=&quot;https://gromacs.bioexcel.eu/t/gmx-energy-with-external-electric-field/4158/9&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS forum&lt;/a&gt;. Quoting Hess's answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In general it is not possible to define an energy, so this is not computed by mdrun. If you only have neutral molecules, you can compute this energy afterwards from the net dipole of the system. I forgot if mdrun always stores the dipole in the energy file. If not, you can use an analysis tool.&lt;/p&gt;&#xA;&lt;p&gt;Note that you need to think about the choice of boundary condition at infinity (surface_epsilon mdp parameter) when using an electric field.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7" LastActivityDate="2022-12-12T15:23:45.350" CommentCount="0" CommunityOwnedDate="2022-12-12T15:23:45.350" ContentLicense="CC BY-SA 4.0" />
  <row Id="10095" PostTypeId="1" AcceptedAnswerId="10096" CreationDate="2022-12-12T16:52:00.747" Score="3" ViewCount="251" Body="&lt;p&gt;I would like to follow how some variables are changing during an OpenMolcas calculation, and adding &lt;code&gt;WRITE&lt;/code&gt; statements has become too tedious. I've compiled with the &lt;code&gt;-DCMAKE_BUILD_TYPE=Debug&lt;/code&gt; option:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cmake ../OpenMolcas_HPQC_LEVEL -DCMAKE_BUILD_TYPE=Debug&#xA;make -j8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I've set the &lt;code&gt;PATH&lt;/code&gt; accordingly:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pymolcas&#xA;&amp;gt; MOLCAS has been found at /home/nike/build_OpenMolcas_HPQC_LEVEL_Debug&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Attempts to use gdb have failed, for example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gdb --args pymolcas&#xA;&amp;gt; &amp;quot;/home/nike/build_OpenMolcas_HPQC_LEVEL_Debug/pymolcas&amp;quot;: not in executable format: file format not recognized&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When searching the word &amp;quot;debug&amp;quot; on the &lt;a href=&quot;https://molcasforum.univie.ac.at/search.php?search_id=792551514&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molcas forum&lt;/a&gt; I got about 29 results, but most of them were about running calculations in parallel (I am not), or just had the word &lt;code&gt;debug&lt;/code&gt; in the post because it was part of the &lt;code&gt;CMAKE&lt;/code&gt; output, even if the post had nothing to do with debugging. The most relevant results that I found there were:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;code&gt;-D DEBUG_DEFS=_DEVEL_&lt;/code&gt; was recommended &lt;a href=&quot;https://molcasforum.univie.ac.at/viewtopic.php?pid=2401#p2401&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; but that was in the context of turning errors into warnings (which is not what I'm trying to do).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://molcasforum.univie.ac.at/viewtopic.php?pid=1873#p1873&quot; rel=&quot;nofollow noreferrer&quot;&gt;This post&lt;/a&gt;) includes an output file that says &amp;quot;To debug your program, run it with the --sync command line option&amp;quot;, but it's in the context of LUSCUS and &lt;code&gt;pymolcas -h&lt;/code&gt; suggests that &lt;code&gt;--sync&lt;/code&gt; isn't an option for &lt;code&gt;pymolcas&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I also searched the documentation, and found that there's a &lt;code&gt;MOLCAS_DEBUGGER&lt;/code&gt; environment variable but running &lt;code&gt;export MOLCAS_DEBUGGER=gdb&lt;/code&gt; before the above &lt;code&gt;gdb&lt;/code&gt; command leads to the same error (and I assume this environment variable affects the running of &lt;code&gt;molcas&lt;/code&gt; rather than &lt;code&gt;pymolcas&lt;/code&gt;). The word &amp;quot;debug&amp;quot; shows up a few times in the &lt;a href=&quot;https://molcas.gitlab.io/OpenMolcas/Manual.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Documentation PDF&lt;/a&gt; (18 times to be exact) but mainly in the context of printing more output, in addition to the afformentioned &lt;code&gt;CMAKE&lt;/code&gt; build type and the &lt;code&gt;MOLCAS_DEBUGGER&lt;/code&gt; variable&lt;/p&gt;&#xA;&lt;p&gt;The word debug appears another 71 times in the &lt;a href=&quot;https://github.com/Molcas/OpenMolcas/blob/master/CMakeLists.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;CMakeLists file&lt;/a&gt; but rather than going through every possibility there, if there's perhaps a set of &lt;em&gt;instructions&lt;/em&gt; on how to use &lt;code&gt;gdb&lt;/code&gt; with OpenMolcas (perhaps in the documentation), it would be helpful if you could let me know them!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2022-12-13T16:04:32.250" LastActivityDate="2022-12-13T16:04:32.250" Title="How to use the GDB debugger with OpenMolcas?" Tags="|python|programming|fortran|open-molcas|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10096" PostTypeId="2" ParentId="10095" CreationDate="2022-12-12T17:04:48.233" Score="5" Body="&lt;p&gt;&lt;code&gt;pymolcas&lt;/code&gt; runs each program as a separate process, so you need to insert &lt;code&gt;gdb&lt;/code&gt; before each individual program call, and not before &lt;code&gt;pymolcas&lt;/code&gt;. This is what &lt;code&gt;MOLCAS_DEBUGGER&lt;/code&gt; is supposed to achieve. Try:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MOLCAS_DEBUGGER=gdb pymolcas ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS: For OpenMolcas-specific questions you can use &lt;a href=&quot;https://openmolcas.zulipchat.com/&quot; rel=&quot;noreferrer&quot;&gt;https://openmolcas.zulipchat.com/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6397" LastActivityDate="2022-12-12T17:04:48.233" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10097" PostTypeId="2" ParentId="10086" CreationDate="2022-12-12T18:10:25.780" Score="5" Body="&lt;h2&gt;&lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0007045&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, &lt;strong&gt;liquid&lt;/strong&gt;, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art &lt;strong&gt;ab initio molecular dynamics simulations&lt;/strong&gt;. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I recommend reading through their latest paper for an overview of CP2K's design, including strengths and weaknesses. One thing to note is that, unlike VASP, CP2K's DFT module (QuickStep) uses Gaussian + Augmented plane wave basis sets, rather than simply plane waves. This has both advantages and disadvantages; while it makes the code run efficiently, it introduces the problem of choosing an appropriate Gaussian basis set for your application. Sometimes the ideal Gaussian basis set just doesn't exist for your system of interest!&lt;/p&gt;&#xA;&lt;p&gt;I have used CP2K in my research, and my experience is that while the software is extremely powerful and efficient, the documentation is lacking for many of the advanced or highly-specialized features. Even some of the more basic features sometimes have very terse descriptions in the documentation. However, you can usually find complete explanations in the scientific literature, and the documentation problem seems to be getting better over time.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.cp2k.org/howto&quot; rel=&quot;nofollow noreferrer&quot;&gt;An installation Guide can be found here.&lt;/a&gt; To start out, I recommend going through the &lt;a href=&quot;https://www.cp2k.org/exercises&quot; rel=&quot;nofollow noreferrer&quot;&gt;exercises given here&lt;/a&gt;. Once you get going, you'll be referring often to the &lt;a href=&quot;https://manual.cp2k.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Thankfully, when it comes to the molecular dynamics of the situation, ab initio MD as implemented in CP2K (Born-Oppenheimer MD) works essentially the same as classical MD. The difference is really just in the force field, which is calculated on-the-fly via density functional theory methods.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2022-12-12T18:26:16.797" LastActivityDate="2022-12-12T18:26:16.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10098" PostTypeId="1" CreationDate="2022-12-13T02:25:13.257" Score="3" ViewCount="54" Body="&lt;p&gt;I am optimizing &lt;span class=&quot;math-container&quot;&gt;$\ce{NiCuWO4}$&lt;/span&gt;/&lt;span class=&quot;math-container&quot;&gt;$\textrm{g}\ce{C3N4}$&lt;/span&gt; system but the calculation terminated showing the error SCF did not converge after the maximum number of steps. As per the suggestion given by Prof. Nick Papior in this site, I have played with the mixing weight. Initially, I kept mixing weight at 0.05 and then gradually decreased up to 0.005. Also, I have checked with 0.1.  Kindly suggest to me how to solve this issue. The input is given below for your reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; # System Descriptor&#xA; SystemName Au-m-GGA&#xA; SystemLabel   Au-m-GGA&#xA; &#xA; NumberOfAtoms                64&#xA; NumberOfSpecies               6&#xA; &#xA; %block Chemical_Species_Label&#xA; 1      6     C&#xA; 2      7     N&#xA; 3      8     O&#xA; 4     28     Ni&#xA; 5     29     Cu&#xA; 6     74     W&#xA; %endblock Chemical_Species_Label&#xA; &#xA; %block PAO.BasisSizes&#xA;C       DZP&#xA;N       DZP&#xA;O       DZP&#xA;Ni      DZP&#xA;Cu      DZP&#xA;W       DZP&#xA; %endblock PAO.BasisSizes&#xA; &#xA; AtomicCoordinatesFormat Ang&#xA; AtomicCoorFormatOut     Ang&#xA; &#xA; %block AtomicCoordinatesAndAtomicSpecies&#xA;      6.1181      0.2377      8.9015   1   C&#xA;     14.0667      0.2266      8.9379   1   C&#xA;      8.5620      0.2227      9.8949   2   N&#xA;     16.6416      0.2593      9.5216   2   N&#xA;      4.7633      0.2686      8.4995   2   N&#xA;     12.6415      0.2331      8.7549   2   N&#xA;      7.8646      1.3452      9.6715   1   C&#xA;     15.8991      1.3550      9.4135   1   C&#xA;      6.5377      1.3437      9.5268   2   N&#xA;     14.5631      1.3590      9.4256   2   N&#xA;      2.8185      1.4865      9.2632   2   N&#xA;     10.6990      1.4556      9.5692   2   N&#xA;      3.9955      1.4942      8.6207   1   C&#xA;     11.8798      1.4554      8.9112   1   C&#xA;      2.0582      2.5677      8.9699   1   C&#xA;      9.9427      2.5337      9.2359   1   C&#xA;      4.5645      2.5679      8.0819   2   N&#xA;     12.4332      2.5358      8.3880   2   N&#xA;      8.5324      2.5453      9.4850   2   N&#xA;     16.5545      2.5725      9.2130   2   N&#xA;      3.8523      3.6750      8.3137   1   C&#xA;     11.7238      3.6485      8.5906   1   C&#xA;      2.5330      3.6915      8.4518   2   N&#xA;     10.3940      3.6484      8.6732   2   N&#xA;      6.6399      3.7903      8.6184   2   N&#xA;     14.5366      3.7629      8.6102   2   N&#xA;      7.7725      3.7751      9.3234   1   C&#xA;     15.7790      3.7873      9.1163   1   C&#xA;      7.1860      3.4905     12.1308   3   O&#xA;     12.5170      3.4736     12.1603   3   O&#xA;     17.8287      3.3294     11.8556   3   O&#xA;      4.7235      3.4211     11.0232   3   O&#xA;     10.1279      3.6009     11.4827   3   O&#xA;     15.3016      3.5078     11.5531   3   O&#xA;      3.5314      4.0003     12.2647   6   W&#xA;      8.8020      4.1758     12.5571   6   W&#xA;     14.0880      4.0945     12.7350   6   W&#xA;      5.7370      2.1356     12.0801   5   Cu&#xA;     16.3440      2.1376     12.3887   5   Cu&#xA;      3.9125      1.1743     12.1378   3   O&#xA;      9.1847      1.3617     12.5343   3   O&#xA;     14.4883      1.2723     12.6153   3   O&#xA;      6.3382      1.0687     13.5843   3   O&#xA;     11.7842      1.0491     13.7621   3   O&#xA;     17.0620      0.8026     13.5558   3   O&#xA;      3.9419      3.5444     13.9598   3   O&#xA;      9.1980      3.7155     14.2521   3   O&#xA;     14.4497      3.6325     14.4455   3   O&#xA;      6.3955      3.4453     15.3869   3   O&#xA;     11.7086      3.4316     15.5716   3   O&#xA;     17.1209      3.2374     15.3809   3   O&#xA;      6.7890      0.6192     15.2771   6   W&#xA;     12.1170      0.6076     15.4809   6   W&#xA;     17.4962      0.4177     15.2683   6   W&#xA;      4.6283      2.4363     15.3917   5   Cu&#xA;     15.2799      2.3537     15.6275   5   Cu&#xA;      5.6302      1.2253     16.5228   3   O&#xA;     10.8726      1.2066     16.6388   3   O&#xA;     16.3371      1.0134     16.5152   3   O&#xA;      3.2299      1.0492     15.5874   3   O&#xA;      8.4222      1.2208     15.6806   3   O&#xA;     13.7330      1.2036     15.9717   3   O&#xA;      9.9109      2.4789     15.5498   4   Ni&#xA;     11.0499      2.1820     12.3846   4   Ni&#xA; %endblock AtomicCoordinatesAndAtomicSpecies&#xA; LatticeConstant    1.00 Ang&#xA; &#xA; %block LatticeVectors&#xA;     15.9064      0.0000      0.0000&#xA;     -0.2517      4.6287      0.0000&#xA;      4.1859     -0.3183     22.8650&#xA; %endblock LatticeVectors&#xA; %block kgrid_Monkhorst_Pack&#xA; 3   0   0 0.0&#xA; 0   3   0 0.0&#xA; 0   0   1 0.0&#xA; %endblock kgrid_Monkhorst_Pack&#xA; &#xA; XC.functional           GGA&#xA; XC.authors              PBE&#xA; SpinPolarized           .true.&#xA; MeshCutoff              300. Ry&#xA; MaxSCFIterations        300&#xA; DM.MixingWeight         0.05&#xA; DM.Tolerance            5.d-5&#xA; DM.NumberPulay          5&#xA; SolutionMethod          diagon&#xA; ElectronicTemperature   300 K&#xA; MD.TypeOfRun            cg&#xA; MD.VariableCell         .true.&#xA; MD.NumCGsteps           800&#xA; MD.MaxForceTol   0.01 eV/Ang&#xA;&#xA; WriteCoorInitial&#xA; WriteCoorStep&#xA; WriteCoorXmol           .true.&#xA; WriteKpoints            .true.&#xA; WriteEigenvalues        .true.&#xA; WriteKbands             .true.&#xA; WriteBands              .true.&#xA; WriteMullikenPop        1&#xA; WriteMDCoorXmol         .false.&#xA; WriteMDhistory          .false.&#xA; DM.UseSaveDM&#xA; MD.UseSaveXV            .true.&#xA; SaveRho&#xA; SaveDeltaRho&#xA; SaveElectrostaticPotential .true.&#xA; WriteSiestaDim          .true.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6358" LastEditorUserId="5" LastEditDate="2022-12-13T02:29:29.360" LastActivityDate="2022-12-13T02:29:29.360" Title="Error during siesta calculation" Tags="|siesta|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-28T16:28:19.963" ContentLicense="CC BY-SA 4.0" />
  <row Id="10099" PostTypeId="1" CreationDate="2022-12-13T09:14:16.917" Score="8" ViewCount="289" Body="&lt;p&gt;There are few questions in this SE about the advantages/disadvantages of machine-learned interatomic potentials in molecular dynamics, but there is not much discussion on how to make them. I thought it might a good question to ask:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How to construct a machine-learned interatomic potential for a system of our interest?&lt;/strong&gt; (e.g., I am interested in studying deep eutectic solvents involving acetamide and lithium perchlorate).&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5103" LastEditorUserId="5" LastEditDate="2022-12-13T14:36:57.460" LastActivityDate="2022-12-13T17:05:32.287" Title="Developing a machine-learned interatomic potential for molecular dynamics" Tags="|molecular-dynamics|lammps|machine-learning|interatomic-potentials|intermolecular-forces|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10100" PostTypeId="2" ParentId="10095" CreationDate="2022-12-13T16:02:14.177" Score="2" Body="&lt;p&gt;The following eventually worked for me, especially after &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10095/how-do-i-use-gdb-with-openmolcas#comment21417_10096&quot;&gt;Jellby's most recent comment&lt;/a&gt;:&lt;/p&gt;&#xA;&#xA;&lt;h2&gt;Compiling:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;cmake ../OpenMolcas_HPQC_LEVEL -DCMAKE_BUILD_TYPE=Debug&#xA;make -j8&#xA;export PATH=$PATH:/home/nike/build_OpenMolcas_HPQC_LEVEL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Debugging:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;MOLCAS_DEBUGGER=gdb pymolcas inputFile.input&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Unlike some programs, in which you might run something like &lt;code&gt;gdb --args ~/path/to/program/level.exe&lt;/code&gt; followed by &lt;code&gt;run &amp;lt; inputFile.input&lt;/code&gt; to have &lt;code&gt;level.exe&lt;/code&gt; run with the input file &lt;code&gt;inputFile.input&lt;/code&gt;, the &lt;code&gt;run&lt;/code&gt; command is not used at this stage because the above command involving &lt;code&gt;MOLCAS_DEBUGGER&lt;/code&gt; will invoke Molcas to &lt;strong&gt;start running immediately&lt;/strong&gt; with the input file &lt;code&gt;inputFileinput&lt;/code&gt;. After parsing the input file it will start running &lt;code&gt;gdb&lt;/code&gt; before running the &amp;quot;module&amp;quot; or &amp;quot;program&amp;quot; within Molcas that your input file wishes to invoke. In my case the first line of the input file was &lt;code&gt;&amp;amp;LEVEL&lt;/code&gt; so after parsing and printing (in the command window) the input file, it printed:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--- Start Module: level at Tue Dec 13 07:19:04 2022 ---&#xA;GNU gdb (Gentoo 9.1 vanilla) 9.1&#xA;Copyright (C) 2020 Free Software Foundation, Inc.&#xA;License GPLv3+: GNU GPL version 3 or later &amp;lt;http://gnu.org/licenses/gpl.html&amp;gt;&#xA;This is free software: you are free to change and redistribute it.&#xA;There is NO WARRANTY, to the extent permitted by law.&#xA;Type &amp;quot;show copying&amp;quot; and &amp;quot;show warranty&amp;quot; for details.&#xA;This GDB was configured as &amp;quot;x86_64-pc-linux-gnu&amp;quot;.&#xA;Type &amp;quot;show configuration&amp;quot; for configuration details.&#xA;For bug reporting instructions, please see:&#xA;&amp;lt;https://bugs.gentoo.org/&amp;gt;.&#xA;Find the GDB manual and other documentation resources online at:&#xA;    &amp;lt;http://www.gnu.org/software/gdb/documentation/&amp;gt;.&#xA;&#xA;For help, type &amp;quot;help&amp;quot;.&#xA;Type &amp;quot;apropos word&amp;quot; to search for commands related to &amp;quot;word&amp;quot;...&#xA;Reading symbols from /home/nike/build_OpenMolcas_HPQC_LEVEL_Debug/bin/level.exe...&#xA;(gdb)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;At the &lt;code&gt;gdb&lt;/code&gt; prompt I was able to set my breakpoint and to run the &amp;quot;module&amp;quot; or &amp;quot;program&amp;quot;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(gdb) b level.f:10&#xA;(gdb) r&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This was the output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Starting program: /home/nike/build_OpenMolcas_HPQC_LEVEL_Debug/bin/level.exe &#xA;[Thread debugging using libthread_db enabled]&#xA;Using host libthread_db library &amp;quot;/cvmfs/soft.computecanada.ca/gentoo/2020/lib64/libthread_db.so.1&amp;quot;.&#xA;&#xA;()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()&#xA;&#xA;                                               &amp;amp;LEVEL&#xA;&#xA;                                   only a single process is used&#xA;                       available to each process: 2.0 GB of memory, 1 thread?&#xA;                                             pid: 34832&#xA;()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()&#xA;&#xA;&#xA;Breakpoint 1, level (rc=7844255429672472576) at /home/nike/OpenMolcas_HPQC_LEVEL/src/level/level.f:76&#xA;76        NLEV2= -1&#xA;(gdb) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which is exactly what I was hoping to achieve &lt;/p&gt;&#xA;&lt;h2&gt;Summary:&lt;/h2&gt;&#xA;&lt;p&gt;Compile with the above commands, then debug/run with &lt;code&gt;MOLCAS_DEBUGGER=gdb pymolcas inputFile.input&lt;/code&gt; and you should then be able to use &lt;code&gt;gdb&lt;/code&gt; in the way that you're familiar.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-12-13T16:02:14.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10101" PostTypeId="2" ParentId="10099" CreationDate="2022-12-13T17:05:32.287" Score="3" Body="&lt;p&gt;I think this paper can help you:&lt;/p&gt;&#xA;&lt;p&gt;Quantum neural networks force fields generation&lt;br /&gt;&#xA;Oriel Kiss, Francesco Tacchino, Sofia Vallecorsa and Ivano Tavernelli&lt;br /&gt;&#xA;Mach. Learn.: Sci. Technol. 3 035004 (2022)&lt;br /&gt;&#xA;DOI: &lt;a href=&quot;https://doi.org/10.1088/2632-2153/ac7d3c&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1088/2632-2153/ac7d3c&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Abstract:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Accurate molecular force fields are of paramount importance for the efficient implementation of molecular dynamics techniques at large scales. In the last decade, machine learning (ML) methods have demonstrated impressive performances in predicting accurate values for energy and forces when trained on finite size ensembles generated with ab initio techniques. At the same time, quantum computers have recently started to offer new viable computational paradigms to tackle such problems. On the one hand, quantum algorithms may notably be used to extend the reach of electronic structure calculations. On the other hand, quantum ML is also emerging as an alternative and promising path to quantum advantage. Here we follow this second route and establish a direct connection between classical and quantum solutions for learning neural network (NN) potentials. To this end, we design a quantum NN architecture and apply it successfully to different molecules of growing complexity. The quantum models exhibit larger effective dimension with respect to classical counterparts and can reach competitive performances, thus pointing towards potential quantum advantages in natural science applications via quantum ML.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-12-13T17:05:32.287" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10102" PostTypeId="1" AcceptedAnswerId="10104" CreationDate="2022-12-13T19:09:23.407" Score="3" ViewCount="161" Body="&lt;p&gt;I am a bit perplexed to see substantive differences in forces (as taken from OUTCAR with ASE) computed when I take AIMD frames and run static electronic relaxations on each one (no additional ionic steps, NSW=0, EDIFFG does not matter). All conditions are the same: EDIFF=1e-4, ALGO=VeryFast. All other parameters are identical. Electronic convergence is reached in both cases. The calculation is collinear spin-polarized, but all magnetic moments are rigorously zero (only Ca, O, and H atoms are in the calculation). VASP 6.3.0, r2SCAN+rVV10, 2x2x2 k-points, again everything identical.&lt;/p&gt;&#xA;&lt;p&gt;This occurs independently of the thermostat (Langevin / npt and Nosé / nvt). Changing POTIM for the electronic relaxation does not matter. Changing the algorithm introduces only minute differences and does not change the overall picture.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example plot of the difference in forces (30 frames, 66 atoms each, NVT / Nosé):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cSYEh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cSYEh.png&quot; alt=&quot;forces example&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is another example (also 30 frames, 66 atoms, but NPT / Langevin and double the POTIM):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/efI64.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/efI64.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I can probably live with the bulk of it when the differences are below 5 meV/angstrom. But the outliers towards 20 meV/angstrom and above are scaring me. Context: the forces are fed to training ML potentials.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What could be the reason(s) for this discrepancy in forces?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4515" LastEditorUserId="4515" LastEditDate="2022-12-13T19:22:35.637" LastActivityDate="2022-12-14T04:48:04.890" Title="Discrepancy in forces between AIMD and relaxation" Tags="|density-functional-theory|vasp|aimd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10103" PostTypeId="1" AcceptedAnswerId="10105" CreationDate="2022-12-14T04:07:59.870" Score="5" ViewCount="3987" Body="&lt;p&gt;In terminal, I run a python code like this way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python code.py file.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or it might also work as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./code.py file.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where the 'python' command is for running the job, 'code.py' is the python script and 'file.txt' is the file on which the code is working.&lt;/p&gt;&#xA;&lt;p&gt;Now my query is, if I use the same code script in Jupyter notebook (i.e. not in the terminal, but from the laptop installed software), how should I execute the run in Jupyter notebook, as it requires the 'file.txt' file as well?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="5" LastEditDate="2022-12-14T13:08:36.080" LastActivityDate="2022-12-14T13:08:36.080" Title="How may I run a .py file in a Jupyter notebook?" Tags="|python|programming|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10104" PostTypeId="2" ParentId="10102" CreationDate="2022-12-14T04:48:04.890" Score="3" Body="&lt;p&gt;This is a bad EDIFF for what you are trying to do I suspect.  Your forces will not be converged to the same value that your energies are converged to since the forces are the gradient of energy.  If you want to get 1e-4 force accuracy then you will need roughly 1e-9 ediff by the &amp;quot;2n+1 theorem&amp;quot; (I suspect this has a better name but I don't recall it at the moment).&lt;/p&gt;&#xA;&lt;p&gt;By solving for an n value, given &amp;quot;4=2n+1&amp;quot;, we get n=1.5 corresponding to a force error of roughly 31 meV (1e-1.5).  It may be that it is better as you see in some cases, but you can't expect agreement better than that in general.  If you perform the MD with better EDIFF, you should see better agreement between this and the single points.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2022-12-14T04:48:04.890" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10105" PostTypeId="2" ParentId="10103" CreationDate="2022-12-14T04:54:23.307" Score="7" Body="&lt;p&gt;From jupyter-notebook, you can do:&lt;/p&gt;&#xA;&lt;p&gt;!python script.py&lt;/p&gt;&#xA;&lt;p&gt;I hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="6411" LastActivityDate="2022-12-14T04:54:23.307" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10106" PostTypeId="1" CreationDate="2022-12-14T18:29:25.267" Score="2" ViewCount="47" Body="&lt;p&gt;I am trying to read this paper&lt;/p&gt;&#xA;&lt;p&gt;Chiral Anomaly from Strain-Induced Gauge Fields in Dirac and Weyl Semimetals&#xA;&lt;a href=&quot;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041021&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041021&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In section II the authors introduce a matrix hamiltonian derived from first principles calculation that models the band structure. Later, in order to introduce gradients in hopping amplitudes, they use &amp;quot;lattice regularization&amp;quot; to get a different hamiltonian notated &lt;span class=&quot;math-container&quot;&gt;$H^{lat}$&lt;/span&gt;.&#xA;What is the process to get from equation (2.1) to (2.3)? What does this hamiltonian operate on and what are the terms &lt;span class=&quot;math-container&quot;&gt;$\tau^x,\tau^y,\tau^z$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;I'd appreciate a reference where this process is explained, as a search for relevant keywords gave nothing.&lt;/p&gt;&#xA;" OwnerUserId="6416" LastActivityDate="2022-12-14T18:29:25.267" Title="What is a lattice regularization scheme?" Tags="|band-structure|model-hamiltonians|tight-binding|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-10T00:25:19.107" ContentLicense="CC BY-SA 4.0" />
  <row Id="10107" PostTypeId="2" ParentId="10061" CreationDate="2022-12-14T21:06:30.727" Score="3" Body="&lt;p&gt;You can calculate the optical gap with TDDFT or GW/BSE. GW/BSE is more common in solids. These are more expensive calculations than DFT calculations, but they are commonly done in metal-halide perovskites.&lt;/p&gt;&#xA;&lt;p&gt;If I understand that paper correctly, their HSE band gap is smaller than the experimental optical gap. This isn’t necessarily too surprising, since it’s possible that the GW fundamental gap is larger than the HSE fundamental gap, so that excitonic effects would make the optical gap line up with the experimental gap. In some systems, HSE has a comparable fundamental gap as GW, so perhaps this isn’t the case. If you want to compare the fundamental gap to the optical gap, then GW for the fundamental gap and BSE for the optical gap might be your best bet.&lt;/p&gt;&#xA;&lt;p&gt;They mention a GW0 calculation that had a similarly low band gap; it’s possible that this was underconverged, or that there was some starting point dependence issue that was ran into, or maybe the GW gap actually is close to the HSE gap. This system might be challenging for existing computational methods, so it’s also possible that good agreement with experiment will be tough to achieve.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastEditorUserId="5770" LastEditDate="2022-12-14T21:12:44.957" LastActivityDate="2022-12-14T21:12:44.957" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10108" PostTypeId="1" CreationDate="2022-12-14T22:18:54.687" Score="8" ViewCount="95" Body="&lt;p&gt;I am planning on calculating optical properties mainly dielectric constant using LOPTICS tag in VASP. Now for my electronic calculations I have been using HSE06 mainly because of higher accuracy of electronic propetrties with hybrid functionals. For my Structural calculations GGA is good enough. But as I am required to use &lt;code&gt;ALGO=Exact&lt;/code&gt; and doubling/tripling the required number of bands(recommended on VASP web page &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Dielectric_properties_of_SiC&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LOPTICS&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;) I don't wanna unnecessarily use a computationally demanding functional like HSE06.&lt;/p&gt;&#xA;&lt;p&gt;Is PBE good enough for calculation of optical properties? There is a lot of literature on underestimation of band gap in DFT but very little about optical properties.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2022-12-14T22:18:54.687" Title="Which Exchange Correlational Functional should be chosen for calculation of optical properties in VASP using LOPTICS tag?" Tags="|vasp|optical-properties|correlation-functions|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-09T22:49:12.810" ContentLicense="CC BY-SA 4.0" />
  <row Id="10109" PostTypeId="2" ParentId="4088" CreationDate="2022-12-15T13:40:41.680" Score="8" Body="&lt;p&gt;As one of the members of the &lt;a href=&quot;https://www.yambo-code.eu&quot; rel=&quot;noreferrer&quot;&gt;Yambo group&lt;/a&gt; I can answer for the developments, in the &lt;a href=&quot;https://doi.org/10.1088/1361-648X/ab15d0&quot; rel=&quot;noreferrer&quot;&gt;Yambo code&lt;/a&gt;, in particular related to GW and BSE. One important aspect is the code optimization, and the connected porting on GPU cards (see the &lt;a href=&quot;http://www.max-centre.eu&quot; rel=&quot;noreferrer&quot;&gt;Max Centre of excellence&lt;/a&gt;). Work was done in optimizing GW and BSE for 2D materials, see for example the &lt;a href=&quot;https://arxiv.org/abs/2205.11946&quot; rel=&quot;noreferrer&quot;&gt;RIM-W method&lt;/a&gt; and the &lt;a href=&quot;https://arxiv.org/abs/2109.01532&quot; rel=&quot;noreferrer&quot;&gt;multi-plasmon pole approximation&lt;/a&gt;; adding &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.103.155152&quot; rel=&quot;noreferrer&quot;&gt;support for spin-orbit&lt;/a&gt; coupling both in GW and BSE; and computing finite momentum exciton dispersion, which, for example, opens the way to compute &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.125.107401&quot; rel=&quot;noreferrer&quot;&gt;exciton-phonon coupling&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The modelling of excitons out of equilibrium is one of the new subjects of interest for the community. Starting from the formulation of &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.84.245110&quot; rel=&quot;noreferrer&quot;&gt;the real-time BSE&lt;/a&gt;, the recent developments include the study of &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.122.187401&quot; rel=&quot;noreferrer&quot;&gt;exciton-phonon coupling in photoluminescence&lt;/a&gt;, the signature of excitons in &lt;a href=&quot;https://doi.org/10.1103/PhysRevMaterials.5.083803&quot; rel=&quot;noreferrer&quot;&gt;ARPES&lt;/a&gt; and &lt;a href=&quot;https://arxiv.org/abs/2211.12241&quot; rel=&quot;noreferrer&quot;&gt;transient Absorption spectroscopy&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Going beyond what is in the Yambo code, recent ongoing activity on exciton dynamics both &lt;a href=&quot;https://journals.aps.org/prresearch/accepted/af071J0cKe918f06407b54657dc2510775de52c7b&quot; rel=&quot;noreferrer&quot;&gt;numerical&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.128.016801&quot; rel=&quot;noreferrer&quot;&gt;theoretical&lt;/a&gt;. Also very recent theoretical works include the use of MBPT to go from electron-phonon &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.122.246403&quot; rel=&quot;noreferrer&quot;&gt;to the modelling of polarons&lt;/a&gt;, and ongoing activity to capture exciton-polaron interaction. It is of course not exhaustive, and mostly focused on (part of) my research activity, with also few new recent works that I like on the subject.&lt;/p&gt;&#xA;&lt;p&gt;Finally a short comment for GW and BSE not in plane wave. There are packages, such as for example the &lt;a href=&quot;http://perso.neel.cnrs.fr/xavier.blase/fiesta/&quot; rel=&quot;noreferrer&quot;&gt;Fiesta&lt;/a&gt; code of the &lt;a href=&quot;http://www.molgw.org/&quot; rel=&quot;noreferrer&quot;&gt;MolGW&lt;/a&gt; code focused on isolated systems, and for extended systems code such as &lt;a href=&quot;https://elk.sourceforge.io/&quot; rel=&quot;noreferrer&quot;&gt;Elk&lt;/a&gt; and &lt;a href=&quot;http://exciting.wikidot.com/&quot; rel=&quot;noreferrer&quot;&gt;Exciting&lt;/a&gt;. The list is not at all exhaustive. The &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.5b00453&quot; rel=&quot;noreferrer&quot;&gt;GW100 initiative&lt;/a&gt; is also a good reference for many other codes.&lt;/p&gt;&#xA;" OwnerUserId="5685" LastActivityDate="2022-12-15T13:40:41.680" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10110" PostTypeId="1" CreationDate="2022-12-15T16:26:14.833" Score="2" ViewCount="35" Body="&lt;p&gt;I would like to simulate the bonding process using compressive pressure for two layers of the same material. Applying a uniaxial strain and using the deform tag in LAMMPS requires PBC in all directions. I am trying to fix the box and apply a load along the z-direction. How do I get this in LAMMPS?&lt;/p&gt;&#xA;" OwnerUserId="6363" LastActivityDate="2022-12-15T16:26:14.833" Title="How to bond two laminates (same material) separated by distance using compressive pressure in LAMMPS?" Tags="|molecular-dynamics|lammps|stress-strain|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10111" PostTypeId="1" CreationDate="2022-12-16T14:08:42.587" Score="4" ViewCount="169" Body="&lt;p&gt;I'm trying to run an opt+ freq calculation using B3LYP/Lanl2DZ for an organic molecule that contains 4 &lt;span class=&quot;math-container&quot;&gt;$\ce{CF3}$&lt;/span&gt; groups, my gaussian suddenly crashed, so I did the calculation in two steps: first opt then freq. I noticed that my Gaussian stopped in the second step &amp;quot;freq&amp;quot; so I supposed that my geometry is optimized.&lt;/p&gt;&#xA;&lt;p&gt;I want to know how can I fix this issue in order to get the vibrations too.&lt;/p&gt;&#xA;&lt;p&gt;Here is where my gaussian crashed and no error is displayed:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     **** Warning!!: The largest alpha MO coefficient is  0.11043379D+02&#xA;&#xA;   1 Symmetry operations used in ECPInt.&#xA; ECPInt:  NShTT=   20100 NPrTT=  168365 LenC2=   14854 LenP2D=   62313.&#xA; LDataN:  DoStor=T MaxTD1= 4 Len=   56&#xA; Symmetrizing basis deriv contribution to polar:&#xA; IMax=3 JMax=2 DiffMx= 0.00D+00&#xA; G2DrvN: will do    46 centers at a time, making    1 passes.&#xA; Calling FoFCou, ICntrl=  3107 FMM=F I1Cent=   0 AccDes= 0.00D+00.&#xA; NEqPCM:  Using equilibrium solvation (IEInf=0, Eps=   8.9300, EpsInf=   2.0283)&#xA; G2PCM: DoFxE=T DoFxN=T DoGrad=T DoDP/DQ/DG/TGxP=FFFF NFrqRd=   0 IEInf=0 SqF1=F DoCFld=F IF1Alg=4.&#xA; End of G2Drv F.D. properties file   721 does not exist.&#xA; End of G2Drv F.D. properties file   722 does not exist.&#xA; End of G2Drv F.D. properties file   788 does not exist.&#xA;          IDoAtm=111111111111111111111111111111111111111111111&#xA; NEqPCM:  Using equilibrium solvation (IEInf=0, Eps=   8.9300, EpsInf=   2.0283)&#xA;          Differentiating once with respect to electric field.&#xA;                with respect to dipole field.&#xA;          Differentiating once with respect to nuclear coordinates.&#xA; Keep R1 ints in memory in canonical form, NReq=1869758414&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="30" LastEditDate="2022-12-18T06:01:25.323" LastActivityDate="2022-12-18T06:01:25.323" Title="Gaussian crash while calculating vibrational frequencies for an organic molecule" Tags="|gaussian|" AnswerCount="0" CommentCount="9" ClosedDate="2023-05-28T16:19:40.430" ContentLicense="CC BY-SA 4.0" />
  <row Id="10112" PostTypeId="1" CreationDate="2022-12-16T18:56:15.353" Score="7" ViewCount="132" Body="&lt;p&gt;I am following along a publication titled &amp;quot;Density-functional tight-binding for beginners&amp;quot; (P. Koskinen, V. Mäkinen, &lt;em&gt;Computational Materials Science&lt;/em&gt; &lt;strong&gt;2009&lt;/strong&gt;, 47, 237–253) and I get stomped by a step in their derivation.&lt;/p&gt;&#xA;&lt;p&gt;The authors start with the following expression for the Kohn-Sham DFT energy:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E[n]=\sum_{a}f_{a}\langle\psi_{a}|\left(-\frac{1}{2}\,\nabla^{2}+\int V_{\mathrm{ext}}(r)n(r)dr\right)|\psi_{a}\rangle + \frac{1}{2}\int\int\frac{n n^{\prime}}{\left|r-r^{\prime}\right|}dr^{\prime}dr+E_{x c}[n]+E_{I I}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f_a \in [0, 2]$&lt;/span&gt; is the occupation of a single-particle state &lt;span class=&quot;math-container&quot;&gt;$\psi_a$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is a position vector in 3D, &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; is the function of electron density and &lt;span class=&quot;math-container&quot;&gt;$V_{ext}(r)$&lt;/span&gt; is an external potential. &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n]$&lt;/span&gt; is the exchange-correlation functional which has an unknown form at this point and &lt;span class=&quot;math-container&quot;&gt;$E_{II}$&lt;/span&gt; is the internuclear repulsion which can be taken as constant.&lt;/p&gt;&#xA;&lt;p&gt;I believe that the second term in the first parenthesis should instead be just &lt;span class=&quot;math-container&quot;&gt;$V_{ext}(r)$&lt;/span&gt;, but I could be wrong.&lt;/p&gt;&#xA;&lt;p&gt;The authors then write the following:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Consider a system with density &lt;span class=&quot;math-container&quot;&gt;$n_0(r)$&lt;/span&gt; that is composed of atomic densities, as if atoms in the system were free and neutral. Hence &lt;span class=&quot;math-container&quot;&gt;$n_0(r)$&lt;/span&gt; contains (artificially) no charge transfer. The density &lt;span class=&quot;math-container&quot;&gt;$n_0(r)$&lt;/span&gt; does not minimize the functional &lt;span class=&quot;math-container&quot;&gt;$E[n(r)]$&lt;/span&gt;, but neighbors the true minimizing density &lt;span class=&quot;math-container&quot;&gt;$n_{min}(r) = n_0(r) + \delta n_0(r)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\delta n_0(r)$&lt;/span&gt; is supposed to be small. Expanding &lt;span class=&quot;math-container&quot;&gt;$E[n]$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$n_0(r)$&lt;/span&gt; to second order in fluctuation &lt;span class=&quot;math-container&quot;&gt;$\delta n(r)$&lt;/span&gt; the energy reads:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E[\delta n]\approx\sum_{a}f_{a}\langle\psi_{a}|-\frac{1}{2}\nabla^{2}+V_{\mathrm{ext}}+V_{H}[n_{0}]+V_{x c}[n_{0}]|\psi_{a}\rangle \\&#xA;+\frac{1}{2}\int\int\biggl(\frac{\delta^{2}E_{x c}[n_{0}]}{\delta n\delta n^{\prime}}+\frac{1}{|r-r^{\prime}|}\biggr)\delta n\delta n^{\prime}dr^{\prime}dr-\frac{1}{2}\int V_{H}[n_{0}](r)n_{0}(r)dr \\&#xA;+\,E_{x c}[n_{0}]+E_{I I}-\int V_{x c}[n_{0}]n_{0}(r)dr&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;They note that the linear terms in &lt;span class=&quot;math-container&quot;&gt;$\delta n$&lt;/span&gt; vanish, which I suppose is because we are considering the ground-state density, and thus the derivative of the energy with regards to the density is 0 since we are at a minimum.&lt;/p&gt;&#xA;&lt;p&gt;The first term and &lt;span class=&quot;math-container&quot;&gt;$E_{II}$&lt;/span&gt; form the zeroth order term, simple enough. I also managed to derive the second order term (the double integral, the second term). However, I cannot figure out where the three other terms come from and what they mean. Isn't &lt;span class=&quot;math-container&quot;&gt;$E_{xc}[n_0] = \int V_{xc}[n_0]n_0(r)dr$&lt;/span&gt;? And why is there another term for &lt;span class=&quot;math-container&quot;&gt;$E_{H}$&lt;/span&gt; which is equivalent (?) to the one in the zeroth order term, after some manipulations?&lt;/p&gt;&#xA;" OwnerUserId="6427" LastEditorUserId="142" LastEditDate="2022-12-19T10:00:25.253" LastActivityDate="2022-12-21T19:39:05.440" Title="How is the tight binding model derived from the Kohn-Sham DFT energy?" Tags="|derivations|density-functional-tight-binding|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10113" PostTypeId="1" CreationDate="2022-12-17T04:42:17.517" Score="4" ViewCount="152" Body="&lt;p&gt;Is there any publicly available software to simulate this or some other method to see if one substance can be dissolved by the other (and preferably to see how fast)?&lt;/p&gt;&#xA;" OwnerDisplayName="Ya Y" LastEditorUserId="30" LastEditDate="2022-12-17T17:33:36.467" LastActivityDate="2022-12-17T17:33:36.467" Title="How to simulate on a computer dissolution of one substance by another?" Tags="|molecular-dynamics|software|reactivity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10114" PostTypeId="1" AcceptedAnswerId="10136" CreationDate="2022-12-17T11:41:17.963" Score="3" ViewCount="89" Body="&lt;p&gt;I gave up on the wB97X-2(TQZ) functional, which would have an exact decay rate of -1/r, re: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10078/4231&quot;&gt;my previous question&lt;/a&gt; and decided to use DSD-PBEPBE-D3BJ, which is available on vanilla Psi4. I then looked up the decay rate of said functional- pure PBE seems to have exponential decay but there is absolutely no mention of the decay rate of the hybrid PBE0, let alone the double hybrid DSD-PBEPBE-D3BJ.&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- is there a closed-form, or even an approximate-form, decay rate of DSD-PBEPBE(-D3BJ) in the literature?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2022-12-21T11:12:55.820" Title="Decay rate of DSD-PBEPBE-D3BJ" Tags="|density-functional-theory|mathematical-modeling|kohn-sham|functional|psi4|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10115" PostTypeId="2" ParentId="10113" CreationDate="2022-12-17T13:58:11.840" Score="4" Body="&lt;p&gt;Sure, this is done all the time in predicting solvation free energies using molecular dynamics.&lt;/p&gt;&#xA;&lt;p&gt;For example:&#xA;&lt;a href=&quot;https://doi.org/10.1021/ct900587b&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Prediction of Absolute Solvation Free Energies using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We also compare the performance of absolute solvation free energies obtained using the OPLS_2005 force field with two other commonly used small molecule force fields—general AMBER force field (GAFF) with AM1-BCC charges and CHARMm-MSI with CHelpG charges.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1002/jcc.10294&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Free energy of solvation from molecular dynamics simulations for low dielectric solvents&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The solvation free energy is computed as the sum of three contributions originated at the cavitation of the solute by the solvent, the solute-solvent repulsion and dispersion interactions, and the electrostatic solvation of the solute.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The basic idea is that you use MD (and either a good force field or quantum chemical method) to simulate the molecule in solvent and consider the relevant thermodynamic cycle.&lt;/p&gt;&#xA;&lt;p&gt;For the most part, the focus has been on the thermodynamics, not the kinetics. In principal, you could start an MD simulation with a solid packing of your molecule of interest and your solvent (e.g., water) next to it. In that case, you'll probably want to do some sort of &lt;a href=&quot;https://doi.org/10.1146/annurev-biophys-070816-033834&quot; rel=&quot;nofollow noreferrer&quot;&gt;weighted ensemble&lt;/a&gt; MD calculation to get accurate kinetics of the solvation process.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-12-17T13:58:11.840" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10116" PostTypeId="2" ParentId="9603" CreationDate="2022-12-17T18:01:07.863" Score="9" Body="&lt;p&gt;There are advantages for someone who has experience with both experiments and simulations. You don't mention your specific experimental expertise, but looking for topics (or postdocs) that bridge between those experiences could be good (e.g., if you did experimental spectroscopy, exploring groups doing photocatalysis prediction/design).&lt;/p&gt;&#xA;&lt;p&gt;For solid materials, there are several good resources, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://materialsproject.org&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; - in addition to a huge database of computed properties and extracted data, they run a &lt;a href=&quot;https://materialsproject.org/community/seminar&quot; rel=&quot;noreferrer&quot;&gt;seminar series&lt;/a&gt; including on Machine Learning (e.g., &lt;a href=&quot;https://youtu.be/0lO7QNAexRc&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Inverse Design, Why Aren't We There Yet&amp;quot;&lt;/a&gt; or &lt;a href=&quot;https://youtu.be/e7zYrz6fgog&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Data Driven Chemical Understanding&amp;quot;&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://opencatalystproject.org&quot; rel=&quot;noreferrer&quot;&gt;Open Catalysis Project&lt;/a&gt; - &amp;quot;To enable the broader research community to participate in this important project, we have released the Open Catalyst 2020 (OC20) and 2022 (OC22) datasets for training ML models. These datasets altogether contain 1.3 million molecular relaxations with results from over 260 million DFT calculations.&amp;quot;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://oqmd.org/documentation/publications&quot; rel=&quot;noreferrer&quot;&gt;Open Quantum Materials Database&lt;/a&gt; - this focuses on the formation energies (e.g., is a particular material going to be stable).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There are several efforts to understand stability and synthetic accessibility, and some experimental background could help significantly with that. Between workshops and tutorials on particular projects (e.g., CASTEP or CP2K, etc.), going through some machine learning tutorials, or attending a workshop for a larger project (e.g., Materials Project) there are several ways to gain more experience with computational efforts.&lt;/p&gt;&#xA;&lt;p&gt;And of course, there's always &lt;a href=&quot;https://mattermodeling.stackexchange.com/&quot;&gt;MM.SE&lt;/a&gt; to ask questions!&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-12-17T18:01:07.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10117" PostTypeId="1" CreationDate="2022-12-18T02:23:39.033" Score="2" ViewCount="55" Body="&lt;p&gt;After writing out this question, I actually figured out the answer, but I am surprised I haven't seen this detail mentioned in almost any paper on the topic, so I will answer my own question here in case anyone gets confused by this like I did.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;In many polarizable force fields, the polarization is represented by induced dipoles located at each atom in the system. The dipoles are induced by the field produced by permanent multipoles in the system. For simplicity, let's assume the field is only produced by charges.&lt;/p&gt;&#xA;&lt;p&gt;In many models, the atomic polarizabilities are isotropic, meaning that the polarization is equal in the x, y, and z directions.&lt;/p&gt;&#xA;&lt;p&gt;In general, one might wish to define a polarizability that is anisotropic. In this case, for some chosen orthogonal reference frame of the molecule, the polarizability tensor need not be diagonal or have equal diagonal elements.&lt;/p&gt;&#xA;&lt;p&gt;The system of equations that needs to be solved in induced dipole models is,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{bmatrix}&#xA;\alpha_1^{-1} &amp;amp; -T_{12}^{dd} &amp;amp; \dots &amp;amp; -T_{1N}^{dd} \\&#xA;-T_{21}^{dd} &amp;amp; \ddots &amp;amp; \dots &amp;amp; \vdots \\&#xA;\vdots &amp;amp; &amp;amp; &amp;amp; \\&#xA;-T_{N1}^{dd} &amp;amp; \dots &amp;amp; &amp;amp; \alpha_N^{-1} \\&#xA;\end{bmatrix}&#xA;\begin{bmatrix}&#xA;\mu_1 \\&#xA;\mu_2 \\&#xA;\vdots \\&#xA;\mu_N&#xA;\end{bmatrix}&#xA;=&#xA;\begin{bmatrix}&#xA;E_1^q \\&#xA;E_2^q \\&#xA;\vdots \\&#xA;E_N^q&#xA;\end{bmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$T_{ij}^{dd}$&lt;/span&gt; is the dipole-dipole interaction tensor between atoms &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\alpha_i^{-1}$&lt;/span&gt; is the inverse polarzability tensor. &lt;span class=&quot;math-container&quot;&gt;$\mu_i$&lt;/span&gt; is the dipole induced by the field of permanent charges at that atom, &lt;span class=&quot;math-container&quot;&gt;$E_i^q$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The polarization energy of the induced dipoles is then given by,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{pol}=-\frac12\sum_i\mu_i\cdot E_i^q&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the polarizability tensor is symmetric, then this will trivially result in a rotationally invariant energy.&lt;/p&gt;&#xA;&lt;p&gt;However, if the polarizability is anisotropic, then the polarizability elements are defined relative to a local axis frame and some rotation must be made to result in a rotationally invariant polarization energy.&lt;/p&gt;&#xA;&lt;p&gt;I am somewhat surprised that I can't find a good discussion of this. I have an implementation of this model which I've been playing around with and can't seem to get the energy to be rotationally invariant when using anisotropic polarizabilities.&lt;/p&gt;&#xA;&lt;p&gt;If anyone can point me towards some references that discuss this specific detail or if anyone knows, then that would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-12-18T02:23:39.033" Title="Rotational invariance of anisotropic polarization models" Tags="|forcefields|intermolecular-forces|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10118" PostTypeId="2" ParentId="10117" CreationDate="2022-12-18T02:23:39.033" Score="2" Body="&lt;p&gt;The answer is actually extremely simple, but wasn't obvious to me at first. It is clear that the elements of the anisotropic polarizability tensor are easiest to define relative to a local axis system. For instance, if one were parameterizing the polarizability of an oxygen atom in water, then one would choose a specific x, y, and z relative to the atoms in water.&lt;/p&gt;&#xA;&lt;p&gt;The system of linear equations described is extremely convenient to solve in the global axis system, so we must ask how to transform the polarizability from some arbitrary orientation to the reference axis system.&lt;/p&gt;&#xA;&lt;p&gt;We can find this rotation matrix, &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, by computing the &lt;a href=&quot;https://en.wikipedia.org/wiki/Direction_cosine&quot; rel=&quot;nofollow noreferrer&quot;&gt;direction cosine matrix&lt;/a&gt; to compute the transformation from the global axis system to the reference axis system (and back again with the transpose).&lt;/p&gt;&#xA;&lt;p&gt;With this matrix in hand, we can make the polarization energy rotationally invariant with an appropriate modification of the inverse polarizability, &lt;span class=&quot;math-container&quot;&gt;$\alpha_i^{-1}$&lt;/span&gt;. Namely, we must compute the &lt;a href=&quot;https://en.wikipedia.org/wiki/Matrix_similarity&quot; rel=&quot;nofollow noreferrer&quot;&gt;similarity transformation&lt;/a&gt; of &lt;span class=&quot;math-container&quot;&gt;$\alpha_i^{-1}$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$R^{-1}\alpha_i^{-1}R$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you think about this operation being applied to the induced dipoles, the product &lt;span class=&quot;math-container&quot;&gt;$R^{-1}\alpha_i^{-1}R\mu_i$&lt;/span&gt;, has the effect of rotating the dipoles into the reference axis system, appropriately applying the scaling by the inverse polarizability and then rotating back to the global axis system.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this is helpful to someone. It's a bit obvious in retrospect, but I was very confused :)&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-12-18T02:23:39.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10119" PostTypeId="1" CreationDate="2022-12-18T07:47:29.353" Score="5" ViewCount="105" Body="&lt;p&gt;Let's assume a scenario:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We have extracted electron density &lt;em&gt;F&lt;/em&gt; for ground electronic state &lt;em&gt;S&lt;/em&gt; of molecule &lt;strong&gt;A&lt;/strong&gt; and electron density &lt;em&gt;G&lt;/em&gt; for a frank-condon excited state &lt;em&gt;E&lt;/em&gt; of the same molecule &lt;strong&gt;A&lt;/strong&gt;. We have extracted both &lt;em&gt;F&lt;/em&gt; and &lt;em&gt;G&lt;/em&gt; in a standard Gaussian cube format such that:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The voxels of cubes are sufficiently fine to account for any significant distortion in electron cloud.&lt;/li&gt;&#xA;&lt;li&gt;The cube dimensions are sufficiently large that the electronic density lying outside the cube can be truncated to zero.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Having these conditions, are there any metrics via which we can differentiate and highlight difference between these cubes? We can project the charge density to partial charges on atoms of &lt;strong&gt;A&lt;/strong&gt; or maybe use general physical features like number of nodes, phase, etc., but are there any other metrics for 3-D data that we can use to numerically quantify the difference between &lt;em&gt;F&lt;/em&gt; and &lt;em&gt;G&lt;/em&gt;?&lt;/p&gt;&#xA;&lt;p&gt;(For ex.: For a 2-D distribution we can &lt;a href=&quot;https://en.wikipedia.org/wiki/Statistical_dispersion&quot; rel=&quot;nofollow noreferrer&quot;&gt;statistical dispersion&lt;/a&gt; to calculate skewness and variance of the dataset.)&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="5" LastEditDate="2022-12-28T00:09:20.280" LastActivityDate="2022-12-28T11:55:38.353" Title="Comparing 3-D quantities (e.g. electron densities)" Tags="|electron-density|methodology|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10120" PostTypeId="1" AcceptedAnswerId="10126" CreationDate="2022-12-18T16:39:49.987" Score="8" ViewCount="1966" Body="&lt;p&gt;I made a 3nm×3nm×3nm supercell mesh of pbs atoms which contains about 2000 atoms and QE  gave me a 13256 GB requirement of RAM. What am I doing wrong? Many people have already done this calculation, but surely no one has 13TB of RAM available on a single node for a calculation like this.&lt;/p&gt;&#xA;" OwnerUserId="6434" LastEditorUserId="5" LastEditDate="2022-12-19T05:22:47.787" LastActivityDate="2022-12-19T11:47:42.907" Title="Why does Quantum ESPRESSO need 13TB of RAM for a (3x3x3)nm supercell?" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|quantum-dots|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10121" PostTypeId="2" ParentId="10120" CreationDate="2022-12-18T17:30:10.857" Score="9" Body="&lt;p&gt;2000 atoms is quite a lot. If you see 3x3x3, often that's the primitive cell repeated by that much.  A 3 nm particle will involve a lot of computational power even with approximations.  Be sure you are using only the gamma point as well and not using excessive vacuum.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2022-12-19T05:23:33.753" LastActivityDate="2022-12-19T05:23:33.753" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10122" PostTypeId="2" ParentId="1685" CreationDate="2022-12-18T19:29:11.480" Score="3" Body="&lt;p&gt;I can comment on externally corrected coupled-cluster (ec-CC) methods, as I have some direct experience in this topic.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Externally Corrected CC&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Externally corrected CC methods seek to improve the results of standard single-reference (SR) CC computations in situations characterized by stronger multireference (MR) correlations by incorporating information about the higher-than-two-body clusters extracted from an external, non-CC source. Historically, the first ec-CC methods used non-CC sources obtained from projected UHF, valence bond, and small-scale MRCI. The latter method goes under the name of reduced multireference CCSD (RMR-CCSD). These days, one is more likely to use one of the modern alternatives to traditional CI/MRCI or CASSCF, such as FCIQMC, selected CI, or DMRG. In any case, once you've chosen an external CI source, &lt;span class=&quot;math-container&quot;&gt;$|\Psi^{(\text{CI})}\rangle = (1 + C)|\Phi\rangle$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$|\Phi\rangle$&lt;/span&gt; is the reference determinant and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is the CI excitation operator, most ec-CC methods proceed by defining the ec-CC state as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$|\Psi\rangle = e^{T_1 + T_2 + T_3^{(\text{ext})} + T_4^{(\text{ext})}}|\Phi\rangle,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt; are the usual one- and two-body cluster components, and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T_3^{(\text{ext})} = C_3 - C_1C_2 + \frac{1}{3}C_1^3$$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T_4^{(\text{ext})} = C_4 - C_1C_3  - \frac{1}{2}C_2^2 + C_1^2C_2 - \frac{1}{4}C_1^4$$&lt;/span&gt;&#xA;are defined using the above expressions obtained by cluster analysis of the external non-CC state (cluster analysis means translating &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt;'s into &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;'s using the formula &lt;span class=&quot;math-container&quot;&gt;$T = \log(1 + C)$&lt;/span&gt;). Once &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt; are computed, they are frozen at these values, and the ec-CC computation proceeds by solving for &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt; iteratively in the presence of these &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt; clusters using a familiar CCSD-like set of amplitude equations,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle \Phi_{i}^{a} | (H e^{T_1+T_2+T_3^{(\text{ext})}})_C|\Phi\rangle = 0$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle \Phi_{ij}^{ab} | (He^{T_1+T_2+T_3^{(\text{ext})}+T_4^{(\text{ext})}})_C|\Phi\rangle = 0,$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with the resulting ec-CC energy computed by&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E = \langle \Phi | (He^{T_1+T_2})_C|\Phi\rangle.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the limiting case that the external source &lt;span class=&quot;math-container&quot;&gt;$|\Psi^{(\text{CI})}\rangle$&lt;/span&gt; is the exact, full CI state, then the derived &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt; clusters would take on the values associated with their full CC counterparts. Then, the &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt; clusters solved within their presence would also be exact, resulting in the exact, full CI energy. In practice, &lt;span class=&quot;math-container&quot;&gt;$|\Psi^{(\text{CI})}\rangle$&lt;/span&gt; would never be exact, but if it is &amp;quot;good enough,&amp;quot; meaning that it provides a reasonable description of the leading MR correlations that might otherwise hamper the accuracy of the conventional CCSD method, then the resulting &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt; obtained in the ec-CC procedure would improve CCSD and provide a much more accurate energy. Of course, the question of how good the external source needs to be is a delicate one, but most computations indicate that you can get away with using rather small CI wave functions that may be cheaply computed to give a minimal description of the relevant MR correlations, so you can think of ec-CC methods as using CC to handle dynamical correlations and CI to handle non-dynamical correlations, thus playing to the strengths of both types of wave function ansätze. That being said, there exist many good ways to deal with MR correlation within an entirely CC framework, just as there exist methods that fix the description of dynamical correlation within CI/MRCI. Nonetheless, ec-CC is a conceptually and computationally appealing hybrid CI/CC approach, particularly in situations characterized by strong correlations (e.g., breaking many bonds at once or metal-insulator Mott transitions). The computational benefit of ec-CC is one of its selling points. Because you are solving CCSD-like equations to obtain &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt;, the cost of the method is essentially that of CCSD. Although in theory, the presence of &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{\text{ext})}$&lt;/span&gt; in these equations introduce terms that scale greater than &lt;span class=&quot;math-container&quot;&gt;$N^6$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is a measure of the system size, these are one-time computations and you can find ways to take advantage of sparsity of the underlying CI state to compute these very efficiently.&lt;/p&gt;&#xA;&lt;p&gt;I should mention that the ec-CC method I've described is an externally corrected extension of CCSD (it's sometimes called ec-CCSD). Externally corrected CC methods form a hierarchy like conventional CC, so you can have ec-CCSDT, where you iterate &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$T_3$&lt;/span&gt; in the presence of &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_5^{(\text{ext})}$&lt;/span&gt; obtained from CI, and ec-CCSDTQ where you iterate &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$T_3$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$T_4$&lt;/span&gt; in the presence of &lt;span class=&quot;math-container&quot;&gt;$T_5^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_6^{(\text{ext})}$&lt;/span&gt;, and so on. While methods like ec-CCSDT or ec-CCSDTQ proceed at essentially the cost of CCSDT and CCSDTQ respectively, making them unappealing, one could imagine using lower-scaling approximations of CCSDT/CCSDTQ to perform the iterative steps, like CCSDt or CCSDtq (active-space CC methods). In fact, these kinds of methods would be extremely powerful and reasonably affordable for medium-sized systems, however, their implementation is laborious enough to keep most people away. The only example I know of is the work on ec-CCSDt using a CASSCF external source from the group of Prof. Shuai Li in Nanjing. Unfortunately, using CASSCF is a poor choice for external correction, and they did not see amazing performance. Finally, I also want to point out that I framed the usage of ec-CC methods as improving conventional CC methods, like CCSD, in situations characterized by stronger MR correlations. This makes them interesting to people in the CC development community, but it can equivalently be viewed as a way to improve the results of the underlying CI computation. So if you work hard and produce a high-quality, say, selected CI wave function and want a cheap routine on top of it that can account for missing dynamical correlations, ec-CC could be something useful (see J. Chem. Theory Comput. 2021, 17, 7, 4006–4027 for an in-depth discussion of exactly how and when this can happen; there are pitfalls). In this context, ec-CC plays a role similar to the MR-MBPT(2)-type corrections commonly employed in selected CI computations.&lt;/p&gt;&#xA;&lt;p&gt;Now, I think I'll just fire off answers to your questions in the context of ec-CC&lt;/p&gt;&#xA;&lt;p&gt;(1) Formula for how energy and/or wave function is calculated&lt;/p&gt;&#xA;&lt;p&gt;This is provided in the above description. If you have a working CCSD code, just implement cluster analysis and tack on the few terms brought by &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt;, and you are good to go.&lt;/p&gt;&#xA;&lt;p&gt;(2) &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-body RDM requirements&lt;/p&gt;&#xA;&lt;p&gt;I'm poorly versed in the business of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability conditions and related topics. I assume that since you have an effective CC state (meaning that it handles like a CC state with exponential parameterization via cluster amplitudes), you can use the same formulae for RDM's you might have from CCSD. Again, you should in theory include &lt;span class=&quot;math-container&quot;&gt;$T_3^{(\text{ext})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{(\text{ext})}$&lt;/span&gt; in your expressions, but I might start by assuming that it's a decent approximation to compute properties using just &lt;span class=&quot;math-container&quot;&gt;$T_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(3) size-consistency&lt;/p&gt;&#xA;&lt;p&gt;The ec-CC methods I described are not size-extensive (and thus not size-consistent), unless your external CI source is size-extensive (e.g., it's full CI or a corner case providing a specific instance of size-extensive CI). That being said, passing the CI information through CC iterations generally reduces the size-extensivity error by a lot (see papers on RMR-CCSD by Paldus and Li).&lt;/p&gt;&#xA;&lt;p&gt;(4) Ability to parallelize&lt;/p&gt;&#xA;&lt;p&gt;The method is as parallelizable as any other CC method, like CCSD.&lt;/p&gt;&#xA;&lt;p&gt;(5) spin-contamination error&lt;/p&gt;&#xA;&lt;p&gt;Except for computations using the RHF reference, ec-CC methods will be susceptible to spin-contamination error just like any conventional CC method. You can fix this by turning to orthgonally spin-adapted CC, but nobody has really figured out how to do it efficiently. You will also have to worry about spin-contamination brought in by the underlying CI source.&lt;/p&gt;&#xA;&lt;p&gt;(6) invariance to orbital rotations&lt;/p&gt;&#xA;&lt;p&gt;It gets interested here. Traditional CC methods are largely invariant to orbital rotations due to Thouless Theorem (not strictly invariant, but highly insensitive), but CI methods are not. Since the &lt;span class=&quot;math-container&quot;&gt;$T_3^{\text{ext}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_4^{\text{ext}}$&lt;/span&gt; clusters are obtained from CI, they will most likely break the strong orbital invariance of CC methods. I say probably because I've never tested this, and I haven't read any papers that examine this issue much.&lt;/p&gt;&#xA;&lt;p&gt;(7) intruder states&lt;/p&gt;&#xA;&lt;p&gt;As I've described it, ec-CC is a computation that is run for the ground state within a conventional single-reference CC formalism. Therefore, there is no risk of intruder states. That being said, the RMR-CCSD method of Paldus and Li includes externally corrected extensions of the genuine state-universal MRCC theory based on the Jeziorski-Monkhorst ansatz, so you could formulate a multiroot ec-CC theory in which you might worry about intruder states. In the case of RMR-CCSD, they formulated it using the generalized model space concept, so they can avoid problems with intruder states by picking CI spaces for each root appropriately.&lt;/p&gt;&#xA;&lt;p&gt;(8) software packages&lt;/p&gt;&#xA;&lt;p&gt;These methods are not common enough to be implemented by the big quantum chemistry codes. Most likely, all the ec-CC implementations exist as research codes held by the various groups that develop them. I have an ec-CC code compatible with selected CI wave functions implemented within my software package called ccpy, which you can try out here if you're interested, &lt;a href=&quot;https://github.com/piecuch-group/ccpy&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/piecuch-group/ccpy&lt;/a&gt;. There should also exist an implementation of ec-CC written in Julia within in the Fermi.jl package.&lt;/p&gt;&#xA;" OwnerUserId="6436" LastEditorUserId="5" LastEditDate="2022-12-19T05:32:12.753" LastActivityDate="2022-12-19T05:32:12.753" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10123" PostTypeId="1" AcceptedAnswerId="10125" CreationDate="2022-12-18T23:26:28.547" Score="3" ViewCount="527" Body="&lt;p&gt;My molecule is aligned along x-axis, and I want to pull this molecule along x-axis with one end defined as the first pull group, and another end as the second pull group. I have two pull codes, which I think should produce the same result. However, I am a bit confused now since they are not essentially giving me the same result. Can anyone tell me what's the difference between these two pull codes, and which one is the correct one to use while pulling the molecule along x-axis.&lt;/p&gt;&#xA;&lt;p&gt;This is the first one with distance defined as the pull_coord1_geometry.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pull                     = yes&#xA;pull-ngroups             = 2&#xA;pull-group1-name         = end1&#xA;pull-group2-name         = end2&#xA;pull-ncoords             = 1&#xA;pull-coord1-geometry     = distance&#xA;pull-coord1-groups       = 1 2&#xA;pull-coord1-type         = umbrella&#xA;pull-coord1-k            = 5000.0&#xA;pull-coord1-rate         = 0.002&#xA;pull-coord1-dim          = Y N N&#xA;pull-print-ref-value     = yes&#xA;pull-coord1_start        = yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this is the second one with the direction defined as the pull_coord1_geometry.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pull                     = yes&#xA;pull-ngroups             = 2&#xA;pull-group1-name         = end1&#xA;pull-group2-name         = end2&#xA;pull-ncoords             = 1&#xA;pull-coord1-geometry     = direction&#xA;pull-coord1-groups       = 1 2&#xA;pull-coord1-type         = umbrella&#xA;pull-coord1-k            = 5000.0&#xA;pull-coord1-rate         = 0.002&#xA;pull-coord1-vec          = 1 0 0&#xA;pull-print-ref-value     = yes&#xA;pull-coord1_start        = yes&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="1791" LastEditDate="2022-12-19T08:58:07.337" LastActivityDate="2022-12-19T10:19:20.517" Title="Difference between two pull codes in gromacs (SMD)" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10124" PostTypeId="2" ParentId="10078" CreationDate="2022-12-19T10:14:24.563" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I then tried to compute the energy of hexaiodostannate(IV) at the wB97X-2(TQZ)/def2-TZVPPD level of theory&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;wB97X-2(TQZ), published by Chai and Head-Gordon in &lt;a href=&quot;https://dx.doi.org/10.1063/1.3244209&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1063/1.3244209&lt;/a&gt; is a double hybrid functional. The list of double hybrids available in Psi4 is given at&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://psicode.org/psi4manual/master/dft_byfunctional.html#double-hybrid&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://psicode.org/psi4manual/master/dft_byfunctional.html#double-hybrid&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and wB97X-2(TQZ) is not on the list. A quick google search suggests that only Q-Chem (who Chai and Head-Gordon are coauthors of) implements this functional, see&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://manual.q-chem.com/latest/sect_DFTexchangecorrelation.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://manual.q-chem.com/latest/sect_DFTexchangecorrelation.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Q-Chem can be used with WebMO (see installation instructions &lt;a href=&quot;https://www.webmo.net/support/binaries_linux.html#qchem&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;] but it is commercial software and you need to pay $$$ for a license.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;turned out that I needed the beta5 (or at least beta3) version of the package to use said functional&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That is not a version. Which version do you think you need? Where is it said that Psi4 has that functional?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A quick Google search lead to a precompiled zip file that is supoosed to be &amp;quot;directly usable w.r.t. WebMO&amp;quot;; I don't know what exactly I should do with that file, so I need help.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As instructed by Campos in the comments above, you need to look at the WebMO installation instructions at &lt;a href=&quot;https://www.webmo.net/support/binaries_linux.html#psi4&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.webmo.net/support/binaries_linux.html#psi4&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-12-19T10:14:24.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10125" PostTypeId="2" ParentId="10123" CreationDate="2022-12-19T10:19:20.517" Score="5" Body="&lt;p&gt;It is very common to pull along the direction of the vector connecting the two pull groups, i.e., &lt;code&gt;pull-coord1-geometry = distance&lt;/code&gt;. If you want to pull in the direction of a specific vector, then you should use &lt;code&gt;pull-coord1-geometry = direction&lt;/code&gt;. But this will create an extra torque in the system unless you pull against a fixed orientation group. If your reference group does not have a fixed orientation, then you should use &lt;code&gt;pull-coord1-geometry = distance-relative&lt;/code&gt;. In the case of &lt;code&gt;pull-coord1-geometry = distance-relative&lt;/code&gt;, you should supply four groups instead of two.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2022-12-19T10:19:20.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10126" PostTypeId="2" ParentId="10120" CreationDate="2022-12-19T11:47:42.907" Score="15" Body="&lt;p&gt;Memory use to store the KS orbitals in a plane wave DFT calculation is proportional to cell-volume*number-of-states, and in turn proportional to the square of the number of atoms in the large limit. So 13 TB does not surprise me at all.  I once computed 4096 Si atoms using CASTEP but that was on a supercomputer, and might easily have used a few TB of RAM.&lt;/p&gt;&#xA;&lt;p&gt;I respectfully suggest that your claim that &amp;quot;many people have done this calculation&amp;quot; is in error, and that the calculations you may have seen either did not use plane-wave DFT, and/or used a massively parallel supercomputer.&lt;/p&gt;&#xA;&lt;p&gt;If you still wish to use full KS-DFT for this system, one of the O(N) or linear-scaling local basis set codes would be a more reasonable choice.&lt;/p&gt;&#xA;" OwnerUserId="498" LastActivityDate="2022-12-19T11:47:42.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10127" PostTypeId="1" CreationDate="2022-12-19T17:06:50.550" Score="4" ViewCount="102" Body="&lt;p&gt;I have used &lt;code&gt;Siesta&lt;/code&gt; in the example attached with &lt;code&gt;phonopy&lt;/code&gt; to run phonon for graphene, and when I typed the command to create force sets:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy --siesta -f disp-001/Gr.FA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I have got this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Number of files to be read (1) don't match to&#xA;&#xA;the number of displacements (2) in phonopy_disp.yaml.&#xA;&#xA;FORCE_SETS could not be created.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thanks in advance to all&lt;/p&gt;&#xA;" OwnerUserId="6444" LastEditorUserId="24" LastEditDate="2022-12-19T17:08:23.803" LastActivityDate="2022-12-19T17:08:23.803" Title="An issue of running Phonopy for graphene using Siesta" Tags="|density-functional-theory|phonons|siesta|phonopy|supercell|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-28T16:19:15.167" ContentLicense="CC BY-SA 4.0" />
  <row Id="10129" PostTypeId="1" CreationDate="2022-12-20T09:29:58.010" Score="5" ViewCount="83" Body="&lt;p&gt;I am trying to investigate a hydride transfer reaction of a transition-metal complex like the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\ce{[M]-H + Ph3C+ -&amp;gt; [M]+ + Ph3CH}  &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For this I want to investigate the influence of solvation on the qualitative free Gibbs energies of the reaction. However, I am unsure about the proper procedure. These options come to mind:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Single-Point calculation of the gas-phase structure with added solvation model + using the thermochemical corrections from the gas-phase&lt;/li&gt;&#xA;&lt;li&gt;Re-optimizing the gas-phase structure with added solvation model + new frequency calculation to obtain the thermochemical corrections&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A look through literature did not really reveal a best-practice way on how to handle this. Would there be anything wrong with either procedure?&lt;/p&gt;&#xA;" OwnerUserId="4303" LastActivityDate="2022-12-20T09:29:58.010" Title="Energy calculation with implicit solvation" Tags="|gaussian|solvation|" AnswerCount="0" CommentCount="7" ClosedDate="2023-05-28T16:19:09.633" ContentLicense="CC BY-SA 4.0" />
  <row Id="10130" PostTypeId="1" AcceptedAnswerId="10144" CreationDate="2022-12-20T11:28:09.653" Score="5" ViewCount="156" Body="&lt;p&gt;I am trying to simulate the electron transfer from adsorbed H2O molecule to the electrode with AIMD. I guess I need to set up an external electric field, so the electron inside the H2O molecule would be driven to the electrode. But I haven't seen any paper to do this kind of simulation. My question is:&lt;bR&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is my thought appropriate to simulate the interfacial electron transfer in OER (oxygen evolution reaction)?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2022-12-25T03:17:04.413" LastActivityDate="2022-12-25T03:17:04.413" Title="How to simulate the electron transfer during OER with AIMD?" Tags="|vasp|electronic-transport|electric-field|aimd|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10132" PostTypeId="2" ParentId="9590" CreationDate="2022-12-20T13:14:41.643" Score="4" Body="&lt;p&gt;&lt;a href=&quot;https://manual.gromacs.org/current/onlinehelp/gmx-density.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;gmx density&lt;/a&gt; can help in finding partial densities either along a particular axis (generally z axis) or with respect to the center of the box. It does not make a contour plot. However, &lt;a href=&quot;https://manual.gromacs.org/current/onlinehelp/gmx-densmap.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;gmx densmap&lt;/a&gt; can be used for computing 2D density maps. Both the commands need trajectory file as input files.&lt;/p&gt;&#xA;" OwnerUserId="6422" LastEditorUserId="6422" LastEditDate="2022-12-22T04:22:50.100" LastActivityDate="2022-12-22T04:22:50.100" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10133" PostTypeId="1" CreationDate="2022-12-20T17:23:46.067" Score="3" ViewCount="332" Body="&lt;p&gt;I am trying to create an interface between the metadynamics and the LAMMPS code. Both the codes are written in two different languages. How can I proceed to create an interface.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="5827" LastActivityDate="2023-02-08T14:50:26.853" Title="Interface between metadynamics and LAMMPS" Tags="|molecular-dynamics|lammps|metadynamics|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10134" PostTypeId="1" CreationDate="2022-12-20T21:30:05.077" Score="6" ViewCount="89" Body="&lt;p&gt;For a liquid, the peaks in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; are typically associated with the solvation shells: nearest neighbors, next-nearest neighbors, and so on. However, the &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; is averaging over many configurations, so are all sub-populations (molecules under the same peak) necessarily in the same solvation shell? If not, how do you determine the fraction of molecules in each shell for each peak?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: &lt;a href=&quot;http://dx.doi.org/10.1063/1.4937376&quot; rel=&quot;nofollow noreferrer&quot;&gt;This&lt;/a&gt; article appears to suggest that a simple way to define the solvation shells can be to use a cutoff based on the minima in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt;, calculate the corresponding nearest, next-nearest, etc. neighbors for each molecule in a configuration, and then build up a histogram. But I don't see how that would tell you if peak 1 in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; corresponds to &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; fraction of molecules from shell 1, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; fraction from shell 2, etc. I would appreciate any insight.&lt;/p&gt;&#xA;" OwnerDisplayName="user2026" LastEditorUserId="5184" LastEditDate="2022-12-22T07:21:32.463" LastActivityDate="2022-12-27T19:13:39.047" Title="Are all molecules under the same peak in g(r) always found in the same solvation shell?" Tags="|molecular-dynamics|structure|radial-distribution-function|amorphous-materials|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10135" PostTypeId="1" AcceptedAnswerId="10189" CreationDate="2022-12-21T00:20:22.993" Score="7" ViewCount="195" Body="&lt;p&gt;I am trying to calculate chemical shifts for Tellurium in an organotellurium compound with Gaussian16 but the calculated values do not match experimental values at all. I know that NMR calculation with heavier atoms can be problematic because of relativistic effects but there is another problem I can not make sense of. I calculated chemical shifts (B3LYP/def2-TZVP, GIAO) for a set of other organotellurium compounds and the values I obtain are nowhere around the calculated reference values, which were obtained using a similiar method. I know that to obtain a chemical &lt;strong&gt;shift&lt;/strong&gt; from chemical &lt;strong&gt;shieldings&lt;/strong&gt;, one has to calculate the difference between a reference compound (for Te-NMR: Dimethyltelluride, calculated isotropic shielding value: 387.4 ppm) and the compound of interest. But using this relation I obtain values that do not match any of the experimental or theoretical values I have seen so far. Did anyone do similiar calculations for Te compounds and is there something I am not getting right ?&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;The references I compared my results to are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.0c05780&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jpca.0c05780&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.7b03198&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jpca.7b03198&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The output with the tellurium chemical shieldings for the reference compound (Me2Te) looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCF GIAO Magnetic shielding tensor (ppm):                    &#xA;     1  Te   Isotropic =   384.9991   Anisotropy =    39.7993&#xA;  XX=   411.5320   YX=    -0.0030   ZX=    -0.0004           &#xA;  XY=    -0.0014   YY=   371.8145   ZY=     0.0002           &#xA;  XZ=    -0.0003   YZ=     0.0002   ZZ=   371.6507           &#xA;  Eigenvalues:   371.6507   371.8145   411.5320              &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And for an organotellurium example (Tellurophene):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     4  Te   Isotropic =   379.3320   Anisotropy =    16.7719&#xA;  XX=   390.5132   YX=    -0.0006   ZX=     0.0000           &#xA;  XY=     0.0001   YY=   367.0601   ZY=     0.0000           &#xA;  XZ=     0.0000   YZ=    -0.0000   ZZ=   380.4225   &#xA;  Eigenvalues:   367.0601   380.4225   390.5132        &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Those results were obtained using Gaussian16 on the B3LYP/def2-TZVP level and the GIAO method. The structures were optimized on the same level.&lt;/p&gt;&#xA;" OwnerUserId="5646" LastEditorUserId="5646" LastEditDate="2022-12-21T02:06:43.367" LastActivityDate="2023-01-04T15:55:43.327" Title="Calculating Te chemical shifts with Gaussian" Tags="|computational-chemistry|gaussian|relativistic|metals|nuclear-magnetic-resonance|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10136" PostTypeId="2" ParentId="10114" CreationDate="2022-12-21T11:12:55.820" Score="4" Body="&lt;p&gt;I guess the OP is referring to the asymptotic potential which is -1/r with the optimized effective potential (OEP) but which decays exponentially with density functionals as well as Hartree-Fock exchange in the usual orbital-dependent formulation. I doubt wB97X-2(TQZ) would have -1/r asymptotic form; no reference is given for the claim. In any case, PBE is a semilocal functional and its potential decays exponentially. The usual implementation of PBE0 has the same feature since the 25% fraction of Hartree-Fock exchange does not change the picture. An implementation using the true OEP or approximations thereof like the Krieger-Li-Iafrate (KLI) method would yield an asymptotic potential of -0.25/r for PBE0.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2022-12-21T11:12:55.820" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10137" PostTypeId="2" ParentId="10112" CreationDate="2022-12-21T19:39:05.440" Score="7" Body="&lt;p&gt;The additional terms come from the Kohn-Sham equations. Everything is detailed quite nicely in W. M. C. Foulkes, R. Haydock, Phys. Rev. B 1989, 39, 12520–12536. Here is a summary of mine:&lt;/p&gt;&#xA;&lt;p&gt;We start by considering a fictitious system of non-interacting electrons with the same groundstate density &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; as the real system. From the Schrödinger equation, we know the energy of each electron in the fictitious system:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left( \frac{1}{2}\nabla^2 + V(r) \right)\psi_i(r) = \epsilon_i \psi_i(r)&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; is the potential which yields the groundstate density &lt;span class=&quot;math-container&quot;&gt;$n(r)$&lt;/span&gt; in this non-interacting system. The total energy is then simply the sum of one-electron energies &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt;. We now consider this case from a DFT perspective:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;    E[n] = T_s[n] + F[n]&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$T_s[n]$&lt;/span&gt; is the kinetic energy functional for non-interacting electrons and &lt;span class=&quot;math-container&quot;&gt;$F[n]$&lt;/span&gt; is the energy associated with the potential &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt;. In the first equation, we can left-multiply both sides by &lt;span class=&quot;math-container&quot;&gt;$\psi_i^*(r)$&lt;/span&gt; and derive the following relationship:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;    \int \psi_i^*(r)\frac{1}{2}\nabla^2\psi_id^3r = T_s[n] = \sum_{i=1}^N\epsilon_i - \int V(r)n(r) d^3r&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, we consider the condition that we want a groundstate density, meaning that &lt;span class=&quot;math-container&quot;&gt;$\delta E[n]/\delta n(r) = 0$&lt;/span&gt;. Starting from the second equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;    \int \frac{\delta E[n]}{\delta n(r)}\delta n(r) d^3r &amp;amp;= \int\frac{\delta T_s[n]}{\delta n(r)}\delta n(r) d^3r + \int\frac{\delta F[n]}{\delta n(r)}\delta n(r) d^3r \approx 0 \\&#xA;    &amp;amp;= \int \left(-V(r) + \frac{\delta F[n]}{\delta n(r)}\right)\delta n(r) d^3r \approx 0 \\&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We conclude that &lt;span class=&quot;math-container&quot;&gt;$V(r) = \delta F[n]/\delta n(r) = V_H[n](r) + V_{ext}(r) + \mu_{xc}[n](r)$&lt;/span&gt; for this to be true. Putting it all together:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;    E_0[n_0] &amp;amp;= \sum_{i=1}^N\epsilon_i - \int V(r)n_0(r)d^3r + F[n_0(r)] \\&#xA;    &amp;amp;= \sum_{i=1}^N\epsilon_i - \int \left.\frac{\delta F}{\delta n}\right|_{n_0(r)} n_0(r)d^3r + F[n_0(r)] \\&#xA;    &amp;amp;= \sum_{i=1}^N\epsilon_i - \int \left(V_{ext}(r) + V_H[n_0(r)] + \mu_{xc}[n_0(r)]\right)n_0(r)d^3r + E_{ext}[n_0(r)] + E_H[n_0(r)] + E_{xc}[n_0(r)] \\&#xA;    &amp;amp;= \sum_{i=1}^N\epsilon_i - \int V_H[n_0(r)]n_0(r)d^3r - \int\mu_{xc}[n_0(r)]n_0(r)d^3r + E_H[n_0(r)] + E_{xc}[n_0(r)] \\&#xA;    &amp;amp;= \sum_{i=1}^N\epsilon_i - 2E_H[n_0(r)] - \int\mu_{xc}[n_0(r)]n_0(r)d^3r + E_H[n_0(r)] + E_{xc}[n_0(r)] \\&#xA;    &amp;amp;= \sum_{i=1}^N\epsilon_i - E_H[n_0(r)] - \int\mu_{xc}[n_0(r)]n_0(r)d^3r + E_{xc}[n_0(r)] \\&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And this is the true zeroth order term in the functional expansion. The second order terms are added to this to yield the final expression.&lt;/p&gt;&#xA;" OwnerUserId="6427" LastActivityDate="2022-12-21T19:39:05.440" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10138" PostTypeId="1" CreationDate="2022-12-22T10:38:16.787" Score="3" ViewCount="213" Body="&lt;p&gt;People, I am a beginner in material modeling (I am studing solid state in Quantum ESPRESSO) and I am having a lot of difficulty with basic terms like &amp;quot;k-points&amp;quot;, &amp;quot;Miller Indices&amp;quot;, &amp;quot;Band Structure&amp;quot; etc. I have never studied any subject about the solid state in my course. However, I saw an introduction course about material science (the main bibliography is &lt;strong&gt;Materials Science and Engineering: An Introduction, by Callister Jr and Rethwisch&lt;/strong&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Do you think that this is an appropriate course or there are others more important for me to take?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cQ53E.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cQ53E.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5" LastEditDate="2023-03-02T18:13:56.970" LastActivityDate="2023-03-02T18:13:56.970" Title="I'm considering to take an introduction course with textbook &quot;Materials Science and Engineering: An Introduction&quot;, as a beginner QE user. Is it okay?" Tags="|quantum-espresso|reference-request|solid-state-physics|k-points|education|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10142" PostTypeId="2" ParentId="9943" CreationDate="2022-12-22T20:09:40.787" Score="9" Body="&lt;p&gt;I have condensed the bash script by using arrays.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for x in 'abc-*/';&#xA;do&#xA;read a[{1..9}] &amp;lt;&amp;lt;&amp;lt;&lt;span class=&quot;math-container&quot;&gt;$(cat $&lt;/span&gt;{x%?} | grep &amp;quot;stress matrix&amp;quot; -A6 | tail -6 | head -3 | xargs)&#xA;read b[{1,2}] &amp;lt;&amp;lt;&amp;lt;&lt;span class=&quot;math-container&quot;&gt;$(cat $&lt;/span&gt;{x%?} | grep &amp;quot;stress matrix&amp;quot; -A6 | tail -2 | awk '{print &lt;span class=&quot;math-container&quot;&gt;$6}'| xargs)&#xA;echo $&lt;/span&gt;{x%?} &lt;span class=&quot;math-container&quot;&gt;${a[*]} $&lt;/span&gt;{b[*]} &amp;gt;&amp;gt;test.csv&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;test.csv shows the same results&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;abc-000 -467.71245 24.34138 7.71803 24.34138 -314.11534 -3.45455 7.71803 -3.45455 -371.79956 0.039198 676.007623&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6422" LastActivityDate="2022-12-22T20:09:40.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10143" PostTypeId="1" CreationDate="2022-12-24T01:29:54.247" Score="2" ViewCount="178" Body="&lt;p&gt;I want to calculate the transition levels of charged defect using Quantum Espresso, I want to know if there's something analogous to NELECT and NUPDOWN in QE like in VASP?&lt;/p&gt;&#xA;" OwnerUserId="4827" LastActivityDate="2022-12-24T01:29:54.247" Title="Quantum Espresso: Select number of valence electrons" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-10T00:25:33.437" ContentLicense="CC BY-SA 4.0" />
  <row Id="10144" PostTypeId="2" ParentId="10130" CreationDate="2022-12-24T19:21:01.257" Score="3" Body="&lt;p&gt;When a bias is applied to an electrode that drives OER, the bias is versus a counter electrode. The counter electrode is a macroscopic distance away, and I have yet to see an AIMD simulation that maintains distinct Fermi levels within one box. It is possible to apply an electric field in a simulation box, but I would be skeptical of the results. There are two other approaches you can take: driving the nuclear coordinate, and using the grand canonical ensemble.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Including an electric field&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is doable in common packages, such as &lt;a href=&quot;https://www.vasp.at/wiki/index.php/EFIELD&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP&lt;/a&gt; and &lt;a href=&quot;https://manual.cp2k.org/cp2k-2022_1-branch/CP2K_INPUT/FORCE_EVAL/DFT/EFIELD.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K&lt;/a&gt;. I doubt that confining such a field to the interface is implemented, and I am not sure what it would take to do this &lt;em&gt;credibly&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Driving the nuclear coordinate&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Within AIMD, the nuclear coordinate drives the electronic structure, under the assumption that the electronic degrees of freedom are in a ground state for the particular nuclear coordinates. So one can make the nuclear coordinates move and then the electron &lt;em&gt;may&lt;/em&gt; at some point transfer. This is broadly under the umbrella of metadynamics. Common codes such as &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Category:Metadynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP&lt;/a&gt; and &lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/MOTION/FREE_ENERGY/METADYN.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K&lt;/a&gt; allow for metadynamics.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcc.0c09108&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1021/acs.jpcc.0c09108&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is a CP2K tutorial: &lt;a href=&quot;https://www.cp2k.org/exercises:2015_cecam_tutorial:mtd1&quot; rel=&quot;nofollow noreferrer&quot;&gt;NHO3 on graphite&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The downside is that to convince a reviewer that your sampling of pathways is comprehensive you will need multiple trajectories and most likely to simulate the reverse process as well.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Grand canonical&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can use the grand-canonical ensemble to include effects of solvents, capacitances, and biases. This method is ultimately closer to solving the structures statically and looking at the frontier orbitals. I am not an expert and cannot offer a more detailed explanation.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.9b12474&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1021/jacs.9b12474&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the method reference for VASP: &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jctc.5b00170&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1021/acs.jctc.5b00170&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4515" LastActivityDate="2022-12-24T19:21:01.257" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10145" PostTypeId="1" AcceptedAnswerId="10190" CreationDate="2022-12-25T07:45:17.590" Score="4" ViewCount="639" Body="&lt;p&gt;I am trying to write a basic &lt;a href=&quot;https://github.com/HemanthHaridas/plank.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hartree-Fock code&lt;/a&gt; to compute orbital energies and total energy of a molecule at almost all basis sets. I wrote the integral code in Cython/Python and is very slow. I would like to use libint to compute the integrals. However, I am unable to find references to use the libint library in python. Any pointers to use libint library in python would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2022-12-27T03:20:04.913" LastActivityDate="2023-01-04T16:00:25.080" Title="How to use libint with Python" Tags="|quantum-chemistry|python|hartree-fock|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10146" PostTypeId="1" CreationDate="2022-12-25T17:44:18.073" Score="4" ViewCount="57" Body="&lt;p&gt;In eq. 1 of &lt;a href=&quot;https://arxiv.org/abs/1709.08310&quot; rel=&quot;nofollow noreferrer&quot;&gt;this reference&lt;/a&gt;, the authors present the following Hamiltonian for the 2-band gapped chiral fermion model that can describe many systems including various semiconductors, N-layer graphene, etc:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;    {H}({k}) = &#xA;    \begin{pmatrix}&#xA;    \Delta &amp;amp; \alpha(|{k}|)e^{i w \phi_k}\\&#xA;    \alpha(|{k}|)e^{-i w \phi_k} &amp;amp; -\Delta &#xA;    \end{pmatrix},&#xA;$$&lt;/span&gt;&#xA;where the energy gap is &lt;span class=&quot;math-container&quot;&gt;$2\Delta$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$\phi_{{k}}=\tan^{-1}({k_y}/{k_x})$&lt;/span&gt;&#xA;and&#xA;&lt;span class=&quot;math-container&quot;&gt;$\alpha(|{k}|)=\alpha|{k}|^\gamma$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know where this Hamiltonian was first used in the literature (specifically in condensed matter)? All the several works I have seen use it (or some version of it) take its form for granted. For instance, I looked at citations [5-10], [12-17] of the referenced work. Additionally I looked at some Google Scholar results (including &lt;a href=&quot;https://kilthub.cmu.edu/articles/thesis/Topological_Effects_in_Two-Dimensional_Systems/10293428/1/files/18679250.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this thesis&lt;/a&gt;).&#xA;But could not find it. Perhaps because it probably was not named 'gapped chiral fermion' in its original form?&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2022-12-26T03:51:31.330" LastActivityDate="2023-12-11T20:21:39.707" Title="Original reference for gapped chiral fermion k·p model?" Tags="|reference-request|condensed-matter|model-hamiltonians|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10147" PostTypeId="1" CreationDate="2022-12-26T17:16:49.160" Score="3" ViewCount="453" Body="&lt;p&gt;I'm trying to fully understand the notion of crystal structures with some basic implications. I understand that it is conveniently described by a &lt;em&gt;lattice&lt;/em&gt; which is the infinite repetition of points in three-dimensional euclidean space given by the integer linear combinations of some &lt;em&gt;lattice vectors&lt;/em&gt;. I'm taking the example of Silicon (Si) for which we should have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;x&lt;/strong&gt; = (5.44, 0, 0)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;y&lt;/strong&gt; = (0, 5.44, 0)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;z&lt;/strong&gt; = (0, 0, 5.44)&lt;/p&gt;&#xA;&lt;p&gt;as the three lattice vectors. Additionally I read about the concept of &lt;em&gt;unit cell&lt;/em&gt; which is given by linear combinations of fractional coefficients (not integers, this time) given by ratios of the lattice vectors &lt;strong&gt;x&lt;/strong&gt;_i as well as the notion of &lt;em&gt;supercell&lt;/em&gt;&#xA;, which in my understanding is just a stack of multiple unit cells ...?&lt;/p&gt;&#xA;&lt;p&gt;I just can't seem to fit well all these different notions together and have a clear view of the underlying object. I tried to visualize the silicon structure and this resulted in even more confusion as I cannot understand what it does represent. For Si, I expect to have a single atom of silicon, while here probably the visualization refers to a supercell?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/W11hu.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/W11hu.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2017" LastActivityDate="2022-12-26T18:05:04.430" Title="How do the notions of Crystal structure, unit cell and supercell fit together?" Tags="|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10148" PostTypeId="2" ParentId="10147" CreationDate="2022-12-26T18:05:04.430" Score="2" Body="&lt;h3&gt;Crystal structure:&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Crystal structure is a description of the ordered arrangement of&#xA;atoms, ions or molecules in a crystalline material. Ordered&#xA;structures occur from the intrinsic nature of the constituent&#xA;particles to form symmetric patterns that repeat along the principal&#xA;directions of three-dimensional space in matter &lt;a href=&quot;https://archive.org/details/solidstatephysic11cole_0&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Bravais (conventional) Lattice&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Bravais lattice is the basic building block from which all&#xA;crystals can be constructed. The concept originated as a topological&#xA;problem of finding the number of different ways to arrange points in&#xA;space where each point would have an identical “atmosphere”. That is&#xA;each point would be surrounded by an identical set of points as any&#xA;other point, so that all points would be indistinguishable from each&#xA;other. Mathematician Auguste Bravais discovered that there were 14&#xA;different collections of the groups of points, which are known as&#xA;Bravais lattices. These lattices fall into seven different &amp;quot;crystal systems”, as differentiated by the relationship between the angles between sides of the “unit cell” and the distance between points in the unit cell. The unit cell is the smallest group of atoms, ions or molecules that, when repeated at regular intervals in three dimensions, will produce the lattice of a crystal system.  &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Physical_Methods_in_Chemistry_and_Nano_Science_(Barron)/07%3A_Molecular_and_Solid_State_Structure/7.01%3A_Crystal_Structure&quot; rel=&quot;nofollow noreferrer&quot;&gt;[2]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Primitive cell&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A primitive cell is a unit cell that contains exactly one lattice&#xA;point. For unit cells generally, lattice points that are shared by n&#xA;cells are counted as 1/n of the lattice points contained in each of&#xA;those cells; so for example a primitive unit cell in three dimensions&#xA;which has lattice points only at its eight vertices is considered to&#xA;contain 1/8 of each of them. An alternative conceptualization is to consistently pick only one of the n lattice points to belong to the&#xA;given unit cell (so the other 1-n lattice points belong to adjacent&#xA;unit cells) &lt;a href=&quot;https://www.doitpoms.ac.uk/tlplib/crystallography3/unit_cell.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;[3]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Wigner–Seitz cell&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A Wigner–Seitz cell is an example of a primitive cell, which is a unit&#xA;cell containing exactly one lattice point. For any given lattice,&#xA;there are an infinite number of possible primitive cells. However&#xA;there is only one Wigner–Seitz cell for any given lattice. It is the&#xA;locus of points in space that are closer to that lattice point than to&#xA;any of the other lattice points.&lt;/p&gt;&#xA;&lt;p&gt;A Wigner–Seitz cell, like any primitive cell, is a fundamental domain&#xA;for the discrete translation symmetry of the lattice. The primitive&#xA;cell of the reciprocal lattice in momentum space is called the&#xA;Brillouin zone &lt;a href=&quot;https://archive.org/details/solidstatephysic00ashc/page/73&quot; rel=&quot;nofollow noreferrer&quot;&gt;[4]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;Super cell&lt;/h3&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In solid-state physics and crystallography, a crystal structure is&#xA;described by a unit cell. There are an infinite number of unit cells&#xA;with different shapes and sizes which can describe the same crystal.&#xA;Say that a crystal structure is described by a unit cell &lt;strong&gt;U&lt;/strong&gt;. The&#xA;supercell &lt;strong&gt;S&lt;/strong&gt; of unit cell &lt;strong&gt;U&lt;/strong&gt; is a cell which describes the same crystal,&#xA;but has larger volume than cell U. Many methods which use a supercell&#xA;perturbate it somehow to determine properties which cannot be&#xA;determined by the initial cell &lt;a href=&quot;https://en.wikipedia.org/wiki/Supercell_(crystal)&quot; rel=&quot;nofollow noreferrer&quot;&gt;[5]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For example: Disordered compounds are crucially important for&#xA;fundamental science and industrial applications. Yet most available&#xA;methods to explore solid-state material properties require ideal&#xA;periodicity, which, strictly speaking, does not exist in this type of&#xA;materials. The supercell approximation is a way to imply periodicity&#xA;to disordered systems while preserving “disordered” properties at the&#xA;local level &lt;a href=&quot;https://doi.org/10.1186%2Fs13321-016-0129-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;[6]&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-12-26T18:05:04.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10149" PostTypeId="1" CreationDate="2022-12-26T23:35:24.660" Score="4" ViewCount="255" Body="&lt;p&gt;I'm trying to learn how to plot emission spectrum for my system, but, as an initial test case, I'm trying to do this for methane.&lt;/p&gt;&#xA;&lt;p&gt;I calculated the optimized geometry of the ground state, then I launched a single point  &lt;code&gt;TD(nstates=5)&lt;/code&gt; calculation, which is how we obtain the absorption spectra since absorption spectra is obtained from the optimized ground state geometry.&lt;/p&gt;&#xA;&lt;p&gt;From this latter output file, I launched an &lt;code&gt;opt td(nstates=5,singlets,root=1)&lt;/code&gt; in order to optimize the geometry of the first excited state. However, the Gaussian calculation crashed with the error link1e. How can I fix this issue and obtain the emission spectrum?&lt;/p&gt;&#xA;&lt;p&gt;here are my steps&#xA;first step: optimization of GS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=CH4.chk&#xA;# B3lyp/3-21g opt freq SCRF=(PCM,read,solvent=CH2Cl2)&#xA;&#xA;opt first step  ground state optimization&#xA;&#xA;0 1&#xA; C                  0.62913910   -0.49668873    0.00000000&#xA; H                  0.98579352   -1.50549874    0.00000000&#xA; H                  0.98581194    0.00770946    0.87365150&#xA; H                  0.98581194    0.00770946   -0.87365150&#xA; H                 -0.44086090   -0.49667555    0.00000000&#xA;&#xA;&#xA;   radii=UAKS&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;second step: calculating excited states&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=CH4TD.chk&#xA;#  b3lyp/3-21g  TD(NStates=5) SCRF=(PCM,read,solvent=CH2Cl2)&#xA;&#xA;second  step calculating excited states &#xA;&#xA;0 1&#xA; C                  0.00000000    0.00000000    0.00000000&#xA; H                  0.63143400    0.63143400    0.63143400&#xA; H                 -0.63143400   -0.63143400    0.63143400&#xA; H                 -0.63143400    0.63143400   -0.63143400&#xA; H                  0.63143400   -0.63143400   -0.63143400&#xA;&#xA;   radii=UAKS&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;third step: optimization of the first ES&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=CH4emission.chk&#xA;# opt td=(nstates=5,singlets,root=1) b3lyp/3-21g scrf=(solvent=ch2cl2,read,pcm) &#xA;&#xA;&#xA;optimizing first excited state&#xA;&#xA;0 1&#xA; C                  0.00000000    0.00000000    0.00000000&#xA; H                  0.63143400    0.63143400    0.63143400&#xA; H                 -0.63143400   -0.63143400    0.63143400&#xA; H                 -0.63143400    0.63143400   -0.63143400&#xA; H                  0.63143400   -0.63143400   -0.63143400&#xA;&#xA;&#xA; radii=UAKS&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the optimization failled with this error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error termination request processed by link 9999.&#xA; Error termination via Lnk1e in C:\G09W\l9999.exe&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5563" LastEditDate="2022-12-27T09:37:12.193" LastActivityDate="2022-12-30T10:16:03.933" Title="How to plot emission spectrum using gaussian?" Tags="|gaussian|spectroscopy|excited-states|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-10T00:24:59.113" ContentLicense="CC BY-SA 4.0" />
  <row Id="10152" PostTypeId="1" AcceptedAnswerId="10158" CreationDate="2022-12-27T03:54:46.977" Score="6" ViewCount="417" Body="&lt;p&gt;Sometimes I have observed this phenomenon where my calculations' SCF iterations keep on fluctuating between two values, and not converging. I have observed it in all sort of systems, ranging from molecules and materials.&lt;/p&gt;&#xA;&lt;p&gt;What is the reason for this see-saw behavior and how to alleviate it? My google search was bit inconclusive&lt;/p&gt;&#xA;&lt;p&gt;I have had similar problems once before in some gold clusters as well, but that project got scrapped so I never properly followed up that time.&lt;/p&gt;&#xA;&lt;p&gt;CP2K input and output files for replication (I am not the most well versed guy in DFT so please highlight any obvious error as well!).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;GLOBAL&#xA;  PROJECT &amp;quot;Sb8 | Energy | SZV-GTH&amp;quot;&#xA;  RUN_TYPE ENERGY&#xA;  PRINT_LEVEL LOW&#xA;&amp;amp;END GLOBAL&#xA;&#xA;&amp;amp;FORCE_EVAL&#xA;  METHOD QUICKSTEP&#xA;&#xA;    &amp;amp;DFT&#xA;    BASIS_SET_FILE_NAME  BASIS_MOLOPT_UCL&#xA;    POTENTIAL_FILE_NAME  GTH_POTENTIALS&#xA;    &amp;amp;SCF&#xA;      MAX_SCF 300&#xA;      EPS_SCF 1e-05&#xA;      SCF_GUESS ATOMIC&#xA;       &amp;amp;SMEAR ON&#xA;        METHOD FERMI_DIRAC&#xA;        ELECTRONIC_TEMPERATURE [K] 300&#xA;      &amp;amp;END SMEAR&#xA;      !&amp;amp;DIAGONALIZATION&#xA;      !  ALGORITHM STANDARD&#xA;      !&amp;amp;END DIAGONALIZATION&#xA;      ADDED_MOS 80&#xA;    &amp;amp;END SCF&#xA;    &amp;amp;XC&#xA;      &amp;amp;XC_FUNCTIONAL PBE&#xA;      &amp;amp;END XC_FUNCTIONAL&#xA;    &amp;amp;END XC&#xA;     &amp;amp;MGRID&#xA;      NGRIDS 5&#xA;      CUTOFF 650&#xA;      REL_CUTOFF 65&#xA;    &amp;amp;END MGRID&#xA;    &amp;amp;QS&#xA;      EPS_RHO      1.0E-12&#xA;      EPS_PGF_ORB  1.0E-07&#xA;    &amp;amp;END QS&#xA;  &amp;amp;END DFT&#xA;&#xA;  &amp;amp;SUBSYS&#xA;    &amp;amp;KIND Sb&#xA;      ELEMENT Sb&#xA;      BASIS_SET TZVP-MOLOPT-SR-GTH-q5&#xA;      POTENTIAL GTH-PBE-q5&#xA;    &amp;amp;END KIND&#xA;    &amp;amp;CELL&#xA;      A       8.6168003       0.0000000       0.0000000&#xA;      B      -4.3084006       7.4623675       0.0000000&#xA;      C      -0.0000010      -0.0000017      22.5480003&#xA;    &amp;amp;END CELL &#xA;    &amp;amp;COORD&#xA;      Sb      -0.00000     -0.00000      2.63237&#xA;      Sb      -0.00000     -0.00000     13.90637&#xA;      Sb      -2.15420      3.73118      2.63237&#xA;      Sb       2.15420      3.73118     13.90637&#xA;    &amp;amp;END COORD&#xA;  &amp;amp;END SUBSYS&#xA;&amp;amp;END FORCE_EVAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt; Step     Update method      Time    Convergence         Total energy    Change&#xA;  ------------------------------------------------------------------------------&#xA;...&#xA;    46 P_Mix/Diag. 0.40E+00    4.1     0.83462647       -21.3544184161  1.19E-07&#xA;    47 P_Mix/Diag. 0.40E+00    4.1     0.83462647       -21.3544185344 -1.18E-07&#xA;    48 P_Mix/Diag. 0.40E+00    4.1     0.83462647       -21.3544184158  1.19E-07&#xA;    49 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544185342 -1.18E-07&#xA;    50 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    51 P_Mix/Diag. 0.40E+00    4.3     0.83462647       -21.3544185342 -1.19E-07&#xA;    52 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    53 P_Mix/Diag. 0.40E+00    4.1     0.83462647       -21.3544185342 -1.19E-07&#xA;    54 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    55 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544185341 -1.19E-07&#xA;    56 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    57 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544185341 -1.19E-07&#xA;    58 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    59 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544185341 -1.19E-07&#xA;    60 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544184156  1.19E-07&#xA;    61 P_Mix/Diag. 0.40E+00    4.2     0.83462647       -21.3544185341 -1.19E-07&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="785" LastEditorUserId="7" LastEditDate="2022-12-28T21:24:19.767" LastActivityDate="2022-12-29T01:02:47.160" Title="SCF energy keeps on fluctuating between two values, instead of converging, why?" Tags="|self-consistent-field|numerical-convergence|cp2k|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10153" PostTypeId="1" CreationDate="2022-12-27T14:36:02.450" Score="4" ViewCount="442" Body="&lt;p&gt;I was calculating the Band structure for HSE06 Functional using VASPKIT as has been described &lt;a href=&quot;https://vaspkit.com/tutorials.html#pre-process-band-structure-hybrid-functional&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. But some seniors of mine told me that this method is not reliable in order to calculate the Band Structure. According to them one needs to run PBE scf, copy WAVECAR &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; run HSE scf, copy WAVECAR, CHGCAR and generate KPOINTS &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; HSE Band Structure.&#xA;Now according to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1987/how-to-make-a-good-hse06-bandstructure-for-tmdc-monolayer-material-e-g-ws2-i&quot;&gt;this old answer&lt;/a&gt; I see that the main reason for doing HSE SCF is to create the KPOINTS file for hybrid calcualtion. Furthermore from this discussion on research gate I realized that CHGCAR can not be used in order to calculate the Bandstructure using ICHARG=11 for hybrid calculation.&lt;/p&gt;&#xA;&lt;p&gt;So is the VASPKIT procedure good enough or do I need to follow the whole procedure including HSE SCF and creating &lt;code&gt;KPOINTS&lt;/code&gt; from &lt;code&gt;IBZKPT&lt;/code&gt; file? According to them VASPKIT is not at all reliable, but I found my experiments to be going along pretty well with literature(&lt;span class=&quot;math-container&quot;&gt;$\Delta E_g &amp;lt; 0.1 eV$&lt;/span&gt;) and various other experienced groups have used VASPKIT for there post and pre processing.&lt;/p&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2022-12-27T14:36:02.450" Title="VASPKIT usage for Band structure calculation for HSE06 calculation" Tags="|vasp|band-structure|hse06|vaspkit|" AnswerCount="0" CommentCount="1" ClosedDate="2023-05-28T16:19:02.727" ContentLicense="CC BY-SA 4.0" />
  <row Id="10154" PostTypeId="2" ParentId="10134" CreationDate="2022-12-27T19:13:39.047" Score="5" Body="&lt;p&gt;Yes, it is possible for configurations which contribute to a particular peak in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; to be outside of that solvation shell.&lt;/p&gt;&#xA;&lt;p&gt;As pointed out in the comments, this is only possible if you have a  definition of solvation shells that makes more sense than just defining the minima of &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; as the solvation shells. For things like Lennard-Jones fluids that don't have strongly directional interactions, the &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; definition probably always makes the most sense.&lt;/p&gt;&#xA;&lt;p&gt;For water, however, where hydrogen bonds are well-understood to be the dominant stabilizing interaction within the liquid, the &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt; definition may not always be the best definition. For instance, in ref. [1], the authors report the average number of hydrogen bonds to each water under various definitions and find it to be around 3.6. On the other hand, if you integrate the area until the first minimum in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt;, you find a coordination number of around 4.3. If you compare the configurations you get from each of these, some of them clearly are not hydrogen-bonded configurations and hence would not be considered as meaningfully contributing to the solvation of that water molecule.&lt;/p&gt;&#xA;&lt;p&gt;So, there are situations where one might reasonably define the solvation shells differently than corresponding to the minima in &lt;span class=&quot;math-container&quot;&gt;$g(r)$&lt;/span&gt;, but this is the exception. Even so, integrating that area contains useful information. For instance, if you didn't count up the hydrogen bonds in water, one might not expect to have a meaningful number of non-hydrogen bonded interactions at such short distance in the liquid.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Also, I am not aware of any other system where this distinction between coordination number and solvation environment is regularly made. One could of course do this for any solutes in water or probably for systems like ammonia, but I don't think it's common in other contexts.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;[1]: Kumar, R., Schmidt, J. R., &amp;amp; Skinner, J. L. (2007). Hydrogen bonding definitions and dynamics in liquid water. The Journal of chemical physics, 126(20), 05B611.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2022-12-27T19:13:39.047" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10155" PostTypeId="1" CreationDate="2022-12-27T18:09:29.497" Score="2" ViewCount="83" Body="&lt;p&gt;I've run into some issues with NAMD that cause me to get the following error whenever I try to begin a simulation run:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;namd2 +idlepoll minimization.namd &amp;gt; minimization.log&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;FATAL ERROR: CUDA error cudaMalloc(pp, sizeofT*(*curlen)) in file C:\cygwin64\usr\tmp\NAMD-build-2020-Aug-05-31699-Win64-CUDA\namd2\src\CudaUtils.C, function reallocate_device_T, line 130 on Pe 0 (roshan device 0 pci 0:1:0): out of memory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So far, what led to this happening was that my NAMD installation was previously functional, but after installing and seemingly uninstalling Cygwin on my Windows machine I started getting this error. I then reset and wiped my PC completely and reinstalled Windows, but the error persists.&lt;/p&gt;&#xA;&lt;p&gt;If anyone else has gotten this error or solved this problem, I'd greatly appreciate the help. Thank you so much!&lt;/p&gt;&#xA;" OwnerDisplayName="Roshan Pathak" LastEditorUserId="5" LastEditDate="2022-12-28T00:14:27.200" LastActivityDate="2022-12-28T00:14:27.200" Title="CUDA memory Error when using NAMD, mentions cygwin even though cygwin isn't installed?" Tags="|molecular-dynamics|computational-chemistry|high-performance-computing|graphical-processing-unit|" AnswerCount="0" CommentCount="2" ClosedDate="2023-05-28T16:27:51.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="10156" PostTypeId="1" CreationDate="2022-12-26T09:45:58.523" Score="2" ViewCount="57" Body="&lt;p&gt;How to find the matrix of Bond lengths between atoms in an hydrogen depleted molecule given the smiles with explicit hydrogen=true.&#xA;Also how to find the geometric distance between atoms  in an hydrogen depleted molecule given the smiles with explicit hydrogen=true.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# -*- coding: utf-8 -*-&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;Created on Wed Nov 16 09:37:44 2022&#xA;&#xA;@author: Sriram&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;import matplotlib.pyplot as plt&#xA;from pysmiles import read_smiles&#xA;from rdkit.Chem import AllChem as Chem&#xA;from rdkit.Chem import rdMolTransforms&#xA;from rdkit.Chem.Draw import rdMolDraw2D, rdDepictor, IPythonConsole&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from IPython.display import Image&#xA;import networkx as nx&#xA;import numpy as np&#xA;from scipy import sparse&#xA;smiles = 'CCC(C)CC(C)C'&#xA;import sys&#xA;import numpy&#xA;numpy.set_printoptions(threshold=sys.maxsize)&#xA;# 3D for lengths&#xA;mol3d = Chem.MolFromSmiles(smiles)&#xA;Chem.EmbedMolecule(mol3d, randomSeed=42)&#xA;Chem.MMFFOptimizeMolecule(mol3d)&#xA;&#xA;# 2D for depiction&#xA;mol2d = Chem.MolFromSmiles(smiles)&#xA;rdDepictor. Compute2DCoords(mol2d)&#xA;&#xA;bonds = [(x.GetBeginAtomIdx(), x.GetEndAtomIdx()) for x in mol3d.GetBonds()]&#xA;mol = read_smiles(smiles,explicit_hydrogen=False)&#xA;#WNM=nx.to_numpy_matrix(mol)&#xA;#print(WNM)&#xA;m=np.array(nx.to_numpy_matrix(mol))&#xA;#G=nx.from_numpy_array(m)&#xA;#G.edges(data=True)&#xA;#print(nx.number_of_edges(G))&#xA;#A=sparse.csc_matrix(nx.to_numpy_matrix(mol))&#xA;#print(A)&#xA;#G=nx.Graph(A)&#xA;&#xA;#print(nx.adjacency_matrix(G))&#xA;&#xA;conf = mol3d.GetConformer()&#xA;&#xA;b_lengths = []&#xA;&#xA;for b in bonds:&#xA;    bl = rdMolTransforms.GetBondLength(conf,b[0],b[1])&#xA;    b_lengths.append(str(round(bl,2)))&#xA;    m[b[0]][b[1]]=round(bl,2)&#xA;    m[b[1]][b[0]]=round(bl,2)&#xA;G = nx.from_numpy_matrix(np.matrix(np.asmatrix(m)))&#xA;layout = nx.spring_layout(G)&#xA;nx.draw(G, layout, node_size=1000, with_labels=True, font_weight='bold',    font_size=15)&#xA;labels = nx.get_edge_attributes(G,'weight')&#xA;nx.draw_networkx_edge_labels(G,pos=layout,edge_labels=labels)&#xA;plt.show()&#xA;d = rdMolDraw2D.MolDraw2DCairo(600, 400)&#xA;for n in range(len(b_lengths)):&#xA;    mol2d.GetBondWithIdx(n).SetProp('bondNote', b_lengths[n])&#xA;A=np.asmatrix(m)&#xA;#K=np.asmatrix(m)&#xA;#DimK=K.shape&#xA;#print(f&amp;quot;{'['}&amp;quot;)&#xA;#for i in range(DimK[0]+1):&#xA; #   print(f&amp;quot;{'['}&amp;quot;)&#xA;  #  for j in range(DimK[0]+1):&#xA;   #     namek=K[i][j]&#xA;    #    print(f&amp;quot;{namek},\n&amp;quot;)&#xA;    #print(f&amp;quot;{']'}&amp;quot;)&#xA;for i in range(len(A)):&#xA;        flag=0&#xA;        if (i==0):&#xA;            print(&amp;quot;[[&amp;quot;, end =&amp;quot;&amp;quot;)&#xA;        else:&#xA;            print(&amp;quot;[&amp;quot;, end =&amp;quot;&amp;quot;)&#xA;        for j in range(len(A)):&#xA;            if (flag==0):&#xA;                print(&amp;quot;%.2f,&amp;quot;%(A[i,j]), end =&amp;quot;&amp;quot;)&#xA;                flag=1&#xA;            else:&#xA;                print(&amp;quot;%.2f,&amp;quot;%(A[i,j]), end =&amp;quot;&amp;quot;)&#xA;        if (i==len(A)-1):&#xA;            print(&amp;quot;]]&amp;quot;)&#xA;        else:&#xA;            print(&amp;quot;]&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't know if my code is correct for my bond length problem&#xA;Similarly how to to do for geometric distance kind help.&#xA;Here i want to do with explicit hydrogen=true&#xA;I believe my code might result in wrong answer can some help validate and help please kind kind help as I am new to rdkit package.&lt;/p&gt;&#xA;" OwnerUserId="6241" OwnerDisplayName="sriram" LastEditorUserId="5" LastEditDate="2022-12-27T21:42:36.993" LastActivityDate="2022-12-27T21:42:36.993" Title="Program for distance matrix using Rdkit" Tags="|rdkit|organic-chemistry|" AnswerCount="0" CommentCount="2" ClosedDate="2023-03-03T22:50:36.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="10157" PostTypeId="2" ParentId="10119" CreationDate="2022-12-28T11:55:38.353" Score="4" Body="&lt;p&gt;If your CUBE file has the basis set info included, you can use the &lt;a href=&quot;http://sobereva.com/multiwfn&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multiwfn&lt;/a&gt; software. From the program site:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Outputting all supported real space functions as well as gradient and Hessian at a point.&lt;/li&gt;&#xA;&lt;li&gt;Calculating real space function along a line and plot curve map (Electron density, Gradient norm of electron density, Laplacian of electron density, Value of orbital wavefunction, Electron spin density&#xA;Hamiltonian kinetic energy density K(r), Lagrangian kinetic energy density G(r), Electrostatic potential,&#xA;Electron localization function (ELF), Localized orbital locator (LOL), Local information entropy, Electrostatic potential (ESP), etc.).&lt;/li&gt;&#xA;&lt;li&gt;Topology analysis for any real space function, such as electron density (AIM analysis).&lt;/li&gt;&#xA;&lt;li&gt;Critical points (CPs) can be located, topology paths and interbasin surfaces.&lt;/li&gt;&#xA;&lt;li&gt;Population analysis. Hirshfeld, Hirshfeld-I, VDD, Mulliken, Löwdin, Modified Mulliken (including three methods: SCPA, Stout &amp;amp; Politzer, Bickelhaupt), Becke, ADCH (Atomic dipole moment corrected Hirshfeld), CM5, 1.2*CM5, CHELPG, Merz-Kollmann, RESP (Restrained ElectroStatic Potential), RESP2, AIM (Atoms-In-Molecules), EEM (Electronegativity Equalization Method) and PEOE (Gasteiger).&lt;/li&gt;&#xA;&lt;li&gt;Orbital composition analysis. Mulliken, Stout &amp;amp; Politzer, SCPA, Hirshfeld, Hirshfeld-I, Becke, natural atomic orbital (NAO) and AIM.&lt;/li&gt;&#xA;&lt;li&gt;Bond order/strength analysis.&lt;/li&gt;&#xA;&lt;li&gt;Charge decomposition analysis (CDA) and extended CDA analysis.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2022-12-28T11:55:38.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10158" PostTypeId="2" ParentId="10152" CreationDate="2022-12-29T01:02:47.160" Score="8" Body="&lt;p&gt;The cause of the oscillations in the SCF energies is probably a &amp;quot;sloshing instability&amp;quot;; the two most common types are &amp;quot;charge sloshing&amp;quot; and &amp;quot;occupancy sloshing&amp;quot;.&lt;/p&gt;&#xA;&lt;h4&gt;Sloshing instabilities&lt;/h4&gt;&#xA;&lt;p&gt;Sloshing instabilities arise in the self-consistent field (SCF) method because the trial solutions to the Kohn-Sham equations are optimised for a &lt;em&gt;fixed&lt;/em&gt; Kohn-Sham potential, and &lt;em&gt;then&lt;/em&gt; the potential is updated. There are many ways to think about why this happens, but for a physical picture consider this scenario with a very simple SCF method:&lt;/p&gt;&#xA;&lt;p&gt;At the start of some iteration &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; of the SCF optimisation, one region (A) of the system has too high an electron density, and another region (B) has too low an electron density.&lt;/p&gt;&#xA;&lt;p&gt;We construct the Kohn-Sham potential for this iteration, &lt;span class=&quot;math-container&quot;&gt;$V^{(i)}(r)$&lt;/span&gt;, from the density. The electrostatic repulsion (Hartree term) means that &lt;span class=&quot;math-container&quot;&gt;$V^{(i)}(r)$&lt;/span&gt; is very large in region A, whereas it is low in region B.&lt;/p&gt;&#xA;&lt;p&gt;The Kohn-Sham states are optimised by minimising the energy of the system, &lt;em&gt;keeping the potential&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$V^{(i)}(r)$&lt;/span&gt; &lt;em&gt;fixed&lt;/em&gt;. Electronic density is moved from region A (high potential) to region B (low potential).&lt;/p&gt;&#xA;&lt;p&gt;Note: as electronic density is removed from A, the potential in that region should be reduced; conversely, the potential in region B should increase as electron density is moved into that region. However, since the optimisation is performed for a &lt;em&gt;fixed&lt;/em&gt; potential, this doesn't happen in the simulation. The result is that the optimisation moves more electron density from A to B than it should.&lt;/p&gt;&#xA;&lt;p&gt;Once the new optimised states have been computed, the new electron density is calculated. Since too much density was moved from A to B, the electron density is now too low in region A and too high in region B.&lt;/p&gt;&#xA;&lt;p&gt;The new Kohn-Sham potential is calculated from the density, and used as the input to the next iteration, &lt;span class=&quot;math-container&quot;&gt;$V^{(i+1)}(r)$&lt;/span&gt;. The electrostatic repulsion means that the &lt;span class=&quot;math-container&quot;&gt;$V^{(i+1)}(r)$&lt;/span&gt; is low in region A, and very large in region B.&lt;/p&gt;&#xA;&lt;p&gt;The next optimisation is performed for fixed &lt;span class=&quot;math-container&quot;&gt;$V^{(i+1)}(r)$&lt;/span&gt;, and now electron density is moved from region B (where the potential is now high) back to region A (because its potential is now low). We are now back where we started!&lt;/p&gt;&#xA;&lt;h4&gt;Stabilising convergence&lt;/h4&gt;&#xA;&lt;p&gt;Sloshing instabilities are extremely common, and in fact the simple SCF method in the previous section almost never converges. Real-life software doesn't just take the output of one SCF iteration as the input to the next, it &amp;quot;damps&amp;quot; the changes by mixing together the outputs from two or more iterations. These methods are called &amp;quot;density mixing&amp;quot; or &amp;quot;potential mixing&amp;quot;, depending on whether it is the density or potential which is mixed. I'll assume density mixing here for brevity, but you can just replace &amp;quot;density&amp;quot; with &amp;quot;potential&amp;quot; for potential mixing.&lt;/p&gt;&#xA;&lt;p&gt;Most mixing methods are based on the behaviour of a parameterised model system (e.g. the homogeneous electron gas), with a method to dynamically update the model (e.g. Pulay/Anderson or Broyden). The key user parameter is the total amount of the density change to &amp;quot;mix in&amp;quot; to the previous input, usually defined such that 0 means don't change the density at all, and 1 means just use the new density (the simple SCF method from the previous section). In CP2K the relevant parameter is &lt;code&gt;DFT/SCF/MIXING/ALPHA&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The smaller you set this mixing parameter, the smaller the changes you allow the software to make each SCF iteration. This has the effect of making the SCF more stable, but could slow the convergence. Conversely, a large mixing parameter makes much larger changes to the density, so the SCF could converge very rapidly, but could also become unstable.&lt;/p&gt;&#xA;&lt;h4&gt;Summary&lt;/h4&gt;&#xA;&lt;p&gt;What you're seeing is a common instability in SCF methods, and you can often suppress it by reducing the mixing amplitude parameter. For a fuller discussion of density mixing, see:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9611/how-does-charge-mixing-work/9617#9617&quot;&gt;How does charge mixing work?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and a related discussion on the mixing amplitude and stability:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8795/the-relationship-between-average-eigenvalue-and-convergence-performance-in-vasp/&quot;&gt;The relationship between average eigenvalue and convergence performance in VASP?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;One of my former students, Nick Woods, looked into this in some detail, so if you'd like to know more you might find his Masters thesis and paper useful:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;On the Nature of Self-Consistency in Density Functional Theory&amp;quot;, N. Woods; &lt;a href=&quot;https://arxiv.org/abs/1803.01763&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/1803.01763&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Computing the Self-Consistent Field in Kohn-Sham Density Functional Theory&amp;quot;, N. Woods, P. Hasnip, M. C. Payne, &lt;em&gt;J. Phys.: Condens. Matter&lt;/em&gt;, &lt;strong&gt;31&lt;/strong&gt;, 453001 (2019); &lt;a href=&quot;https://doi.org/10.1088/1361-648X/ab31c0&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1088/1361-648X/ab31c0&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-12-29T01:02:47.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10159" PostTypeId="1" CreationDate="2022-12-29T03:50:42.073" Score="2" ViewCount="74" Body="&lt;p&gt;I am trying to optimize the geometry of (C5H14N2)[CuCl4] using g09. However, the calculation is not converging at any level of theory in 250 cycles. I am new to this field and I think I have made a serious mistake with this structure. here is my input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt pm6&#xA; scf=(tight,noincfock,novaracc,maxcycle=250)&#xA;&#xA; Title Card Required&#xA;&#xA;0 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1&#xA;Cu(Fragment=4)     0.62103285    7.44978542    4.73411720&#xA;Cl(Fragment=4)     0.64538745    5.31663924    5.47586345&#xA;Cl(Fragment=4)     0.62509283    8.16087851    6.90430314&#xA;Cl(Fragment=4)     0.65868548    9.60132385    4.04814493&#xA;Cl(Fragment=4)     0.59879168    6.72458646    2.59526409&#xA;N(Fragment=6)     -0.27473404    3.44967132   10.97721414&#xA;H(Fragment=6)     -0.97947170    2.95052692   11.26414189&#xA;H(Fragment=6)      0.48331453    3.05081973   11.28551493&#xA;N(Fragment=6)      0.58340804    5.65159919    8.75294034&#xA;H(Fragment=6)     -0.24688321    5.74007440    8.39049213&#xA;H(Fragment=6)      1.17308410    6.00559408    8.15662767&#xA;C(Fragment=6)     -0.37544999    4.79286456   11.59672265&#xA;H(Fragment=6)     -1.22894013    5.20213883   11.30732878&#xA;C(Fragment=6)      0.69793915    5.72385264   11.30126475&#xA;H(Fragment=6)      1.55006623    5.22050782   11.31498924&#xA;C(Fragment=6)      0.62933920    6.49183944    9.98719190&#xA;H(Fragment=6)     -0.17527040    7.06737502   10.00271535&#xA;H(Fragment=6)      1.41924360    7.08568131    9.93049496&#xA;C(Fragment=6)      0.87377888    4.19571564    8.86254569&#xA;H(Fragment=6)      1.69183611    4.07127043    9.40554490&#xA;H(Fragment=6)      1.05478929    3.83524771    7.95782501&#xA;C(Fragment=6)     -0.24973338    3.40892100    9.48443692&#xA;H(Fragment=6)     -1.11018239    3.76097242    9.14364768&#xA;H(Fragment=6)     -0.17590003    2.46564513    9.19413762&#xA;Cu(Fragment=1)     2.48247578   14.20279790    7.77706647&#xA;Cu(Fragment=3)     3.66909961    8.22341458    7.17950788&#xA;Cu(Fragment=2)     2.76609907    0.38681458   10.69092973&#xA;Cl(Fragment=1)     2.45812119   12.06965172    7.03532023&#xA;Cl(Fragment=3)     3.64474501   10.35656076    6.43776163&#xA;Cl(Fragment=2)     2.79045367    2.51996076   11.43267598&#xA;Cl(Fragment=2)     0.51726582    0.34041772   10.89511005&#xA;Cl(Fragment=3)     3.66503963    7.51232149    5.00932194&#xA;Cl(Fragment=1)     4.73130904   14.24919476    7.57288616&#xA;Cl(Fragment=2)     2.74174447   -1.74633160    9.94918348&#xA;Cl(Fragment=3)     3.63144698    6.07187615    7.86548015&#xA;Cl(Fragment=1)     2.50819803   16.29268259    8.63311180&#xA;Cl(Fragment=1)     2.50471695   13.47759894    9.91591958&#xA;Cl(Fragment=3)     3.69134078    8.94861354    9.31836099&#xA;Cl(Fragment=2)     2.74385791    1.11201354    8.55207662&#xA;N(Fragment=5)      0.63483273   11.28627132    6.89322347&#xA;N(Fragment=8)      4.56486650   12.22352868    0.93641093&#xA;N(Fragment=7)      3.65529973    4.38692868    5.02040161&#xA;H(Fragment=5)      1.33957038   10.78712692    6.60629572&#xA;H(Fragment=8)      5.26960415   12.72267308    0.64948318&#xA;H(Fragment=7)      2.95056208    4.88607308    5.30732935&#xA;H(Fragment=5)     -0.12321584   10.88741973    6.58492268&#xA;H(Fragment=8)      3.80681793   12.62238027    0.62811014&#xA;H(Fragment=7)      4.41334830    4.78578027    5.32870240&#xA;N(Fragment=5)     -0.22330935   13.48819919    9.11749727&#xA;N(Fragment=8)      3.70672442   10.02160081    3.16068473&#xA;N(Fragment=7)      4.51344181    2.18500081    2.79612781&#xA;H(Fragment=5)      0.60698189   13.57667440    9.47994549&#xA;H(Fragment=8)      4.53701566    9.93312560    3.52313295&#xA;H(Fragment=7)      3.68315056    2.09652560    2.43367959&#xA;H(Fragment=5)     -0.81298542   13.84219408    9.71380995&#xA;H(Fragment=8)      3.11704835    9.66760592    3.75699741&#xA;H(Fragment=7)      5.10311787    1.83100592    2.19981513&#xA;C(Fragment=5)      0.73554867   12.62946456    6.27371496&#xA;C(Fragment=8)      4.66558244   10.88033544    0.31690243&#xA;C(Fragment=7)      3.55458378    3.04373544    5.63991011&#xA;H(Fragment=5)      1.58903881   13.03873883    6.56310883&#xA;H(Fragment=8)      5.51907258   10.47106117    0.60629629&#xA;H(Fragment=7)      2.70109364    2.63446117    5.35051624&#xA;H(Fragment=5)      0.78233501   12.51301268    5.29147232&#xA;H(Fragment=7)      3.50779744    3.16018732    6.62215276&#xA;C(Fragment=5)     -0.33784046   13.56045264    6.56917287&#xA;C(Fragment=8)      3.59219331    9.94934736    0.61236033&#xA;C(Fragment=7)      4.62797292    2.11274736    5.34445221&#xA;H(Fragment=8)      2.74006623   10.45269218    0.59863583&#xA;H(Fragment=5)     -0.37719554   14.22214380    5.83351843&#xA;H(Fragment=7)      4.66732800    1.45105620    6.08010664&#xA;C(Fragment=5)     -0.26924051   14.32843944    7.88324571&#xA;C(Fragment=8)      3.66079326    9.18136056    1.92643317&#xA;C(Fragment=7)      4.55937297    1.34476056    4.03037936&#xA;H(Fragment=5)      0.53536908   14.90397502    7.86772226&#xA;H(Fragment=8)      4.46540285    8.60582498    1.91090972&#xA;H(Fragment=7)      3.75476338    0.76922498    4.04590282&#xA;H(Fragment=5)     -1.05914491   14.92228131    7.93994265&#xA;H(Fragment=8)      2.87088886    8.58751869    1.98313012&#xA;H(Fragment=7)      5.34927737    0.75091869    3.97368242&#xA;C(Fragment=5)     -0.51368020   12.03231564    9.00789192&#xA;C(Fragment=8)      3.41635357   11.47748436    3.05107938&#xA;C(Fragment=7)      4.80381266    3.64088436    2.90573316&#xA;H(Fragment=8)      2.59829634   11.60192957    2.50808018&#xA;H(Fragment=5)     -0.69469061   11.67184771    9.91261261&#xA;H(Fragment=8)      3.23534316   11.83795229    3.95580007&#xA;H(Fragment=7)      4.98482306    4.00135229    2.00101247&#xA;C(Fragment=5)      0.60983207   11.24552100    8.38600069&#xA;C(Fragment=8)      4.53986584   12.26427900    2.42918815&#xA;C(Fragment=7)      3.68030039    4.42767900    3.52762438&#xA;H(Fragment=5)      1.47028107   11.59757242    8.72678994&#xA;H(Fragment=8)      5.40031485   11.91222758    2.76997740&#xA;H(Fragment=7)      2.81985138    4.07562758    3.18683514&#xA;H(Fragment=5)      0.53599871   10.30224513    8.67629999&#xA;H(Fragment=8)      4.46603248   13.20755487    2.71948746&#xA;H(Fragment=7)      3.75413374    5.37095487    3.23732508&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iW1hS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iW1hS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6481" LastEditorUserId="6481" LastEditDate="2022-12-29T04:01:50.983" LastActivityDate="2022-12-29T04:01:50.983" Title="Perovskite Optimization does not converge using gaussian" Tags="|density-functional-theory|gaussian|geometry-optimization|perovskites|" AnswerCount="0" CommentCount="7" ClosedDate="2023-05-28T16:27:46.563" ContentLicense="CC BY-SA 4.0" />
  <row Id="10160" PostTypeId="1" CreationDate="2022-12-29T05:32:27.437" Score="5" ViewCount="143" Body="&lt;p&gt;As a follow up to my previous question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10145/how-to-use-libint-with-python&quot;&gt;here&lt;/a&gt;, I am now trying to implement symmetry detection in my code. I am following the paper by &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/jcc.23493&quot; rel=&quot;nofollow noreferrer&quot;&gt;Beruski et. al&lt;/a&gt; to understand the background required. I am able to find the Principal Axes of Inertia and the Moments of Intertia using the following code&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import  numpy           as  np&#xA;import  math            as  mt&#xA;import  numpy.linalg    as  linalg&#xA;&#xA;def translateCoordinates(coords: np.ndarray, mass: np.ndarray) -&amp;gt; np.ndarray:&#xA;    com =   np.sum(np.transpose(coords) * mass, axis=1)/ np.sum(mass)&#xA;    translated  =   []&#xA;    for coord in coords:&#xA;        translated.append(np.subtract(coord, com))&#xA;    translated  =   np.array(translated)&#xA;    return translated&#xA;&#xA;def generateIntertiaTensor(coords: np.ndarray, mass: np.ndarray) -&amp;gt; np.ndarray:&#xA;    inertiatensor    =   np.zeros((3,3))&#xA;    for coord, mass in zip(coords, mass):&#xA;        inertiatensor[0][0] =   inertiatensor[0][0] +    mass * pow(coord[1], 2) + mass * pow(coord[2], 2)&#xA;        inertiatensor[1][1] =   inertiatensor[1][1] +    mass * pow(coord[0], 2) + mass * pow(coord[2], 2)&#xA;        inertiatensor[2][2] =   inertiatensor[2][2] +    mass * pow(coord[1], 2) + mass * pow(coord[0], 2)&#xA;&#xA;        inertiatensor[1][0] =   inertiatensor[1][0] +   -1 * mass * coord[0] * coord[1]&#xA;        inertiatensor[2][0] =   inertiatensor[2][0] +   -1 * mass * coord[0] * coord[2]&#xA;        inertiatensor[1][2] =   inertiatensor[1][2] +   -1 * mass * coord[1] * coord[2]&#xA;&#xA;    inertiatensor[0][1]  =   inertiatensor[1][0]&#xA;    inertiatensor[0][2]  =   inertiatensor[2][0]&#xA;    inertiatensor[2][1]  =   inertiatensor[1][2]&#xA;&#xA;    moments, axes   =   linalg.eigh(inertiatensor)&#xA;    axes            =   np.transpose(axes)&#xA;    &#xA;    # gram-schmidt orthogonalization&#xA;    orthogonalaxes      =   np.zeros((3,3))&#xA;    orthogonalaxes[:,0] =   axes[:,0]&#xA;    orthogonalaxes[:,1] =   axes[:,1] - (np.dot(axes[:,0], axes[:,1])/np.dot(axes[:,0], axes[:,0]))*axes[:,0]&#xA;    orthogonalaxes[:,2] =   axes[:,2] - (np.dot(axes[:,0], axes[:,2])/np.dot(axes[:,0], axes[:,0]))*axes[:,0] - (np.dot(orthogonalaxes[:,1], axes[:,2])/np.dot(orthogonalaxes[:,1], orthogonalaxes[:,1]))*orthogonalaxes[:,1]&#xA;    &#xA;    orthogonalaxes[:,0] =   orthogonalaxes[:,0] / np.linalg.norm(orthogonalaxes[:,0])&#xA;    orthogonalaxes[:,1] =   orthogonalaxes[:,1] / np.linalg.norm(orthogonalaxes[:,1])&#xA;    orthogonalaxes[:,2] =   orthogonalaxes[:,2] / np.linalg.norm(orthogonalaxes[:,2])&#xA;&#xA;    return orthogonalaxes&#xA;&#xA;def printAxes(axes: np.ndarray) -&amp;gt; None:&#xA;    for vec in axes:&#xA;        print(&amp;quot;{:10.3f}{:10.3f}{:10.3f}&amp;quot;.format(vec[0], vec[1], vec[2]))&#xA;&#xA;def printCoords(coords: np.ndarray) -&amp;gt; None:&#xA;    for coord in coords:&#xA;        print(&amp;quot;{:10.3f}{:10.3f}{:10.3f}&amp;quot;.format(coord[0], coord[1], coord[2]))&#xA;&#xA;def printDistanceMatrix(distancematrix: np.ndarray) -&amp;gt; None:&#xA;    for row in distancematrix:&#xA;        print(row)&#xA;&#xA;def generateDistanceMatrix(coords: np.ndarray) -&amp;gt; np.ndarray:&#xA;    natoms  =   coords.shape[0]&#xA;    distancematrix  =   np.zeros((natoms, natoms))&#xA;    for index_i, coord_i in enumerate(coords):&#xA;        for index_j, coord_j in enumerate(coords):&#xA;            distancematrix[index_i][index_j]    =   round(mt.sqrt(np.dot(coord_i-coord_j, coord_i-coord_j)),3)&#xA;&#xA;    unique, count = np.unique(distancematrix, axis=0, return_counts=True)&#xA;    repeated_groups = unique[count &amp;gt; 1]&#xA;    print(unique)&#xA;&#xA;#    for repeated_group in repeated_groups:&#xA;#        repeated_idx = np.argwhere(np.all(distancematrix == repeated_group, axis=1))&#xA;#        print(repeated_idx.ravel())&#xA;    return distancematrix&#xA;&#xA;def readCoords(filename: str) -&amp;gt; np.ndarray:&#xA;    coords  =   []&#xA;    with open(filename) as f:&#xA;        for line in f:&#xA;            line    =   line.split()&#xA;            tcoord  =   [float(x) for x in line[1:]]&#xA;            coords.append(tcoord)&#xA;    coords  =   np.array(coords)&#xA;    return coords&#xA;&#xA;coords  =   readCoords(&amp;quot;methane.dat&amp;quot;)&#xA;mass    =   [12.004, 1.008, 1.008, 1.008, 1.008]&#xA;distancematrix  =   generateDistanceMatrix(coords)&#xA;printDistanceMatrix(distancematrix)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I am stuck at finding the symmetry equivalent atoms from the distance matrix. A brute force comparision would be &lt;em&gt;O(N&lt;span class=&quot;math-container&quot;&gt;$^2$&lt;/span&gt;)&lt;/em&gt;, and would soon become very expensive even for moderately sized molecules. Is there a better way to do it?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edited to add Further Information:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I got around the detection of point group of the molecule using openbabel package in python and C++. However, this came at the cost of needing to create a OBMol object just for symmetry detection and coordinate reorientation. I am still interested in a naive but somewhat optimal way (which can be implemented in C++ or python) to identify the symmetry equivalent atoms, without the need to create extra objects.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-05-28T06:25:08.380" LastActivityDate="2023-05-28T06:25:08.380" Title="Locating Symmetry Equivalent Atoms from Distance Matrix?" Tags="|computational-chemistry|molecular-modeling|python|symmetry|hartree-fock|" AnswerCount="0" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="10163" PostTypeId="1" AcceptedAnswerId="10165" CreationDate="2022-12-29T15:44:02.473" Score="5" ViewCount="131" Body="&lt;p&gt;I need to run several large systems using AIMD. I would like to benchmark same phase transition phenomenon using different thermostats (like Nose vs Langevin). For that it is crucial that I pick most optimal parameters for thermostats. But most &amp;quot;recipes&amp;quot; seem to suggest manual parameter sweep (&lt;a href=&quot;https://groups.google.com/g/cp2k/c/fmZX3_2kivc&quot; rel=&quot;noreferrer&quot;&gt;e.g.&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;So I was wondering if I stay within same software, say CP2K (to avoid any implementation difference), &lt;strong&gt;can I optimize my thermostat parameters using classical MD, then just use the same parameters in AIMD production runs?&lt;/strong&gt; I could not think of a counter-argument.&lt;/p&gt;&#xA;" OwnerUserId="785" LastActivityDate="2022-12-29T22:36:55.587" Title="Are thermostat parameters transferable between AIMD and classical MD?" Tags="|molecular-dynamics|aimd|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10164" PostTypeId="2" ParentId="10145" CreationDate="2022-12-29T16:34:57.853" Score="4" Body="&lt;h3&gt;Some background:&lt;/h3&gt;&#xA;&lt;p&gt;The following answer by &lt;a href=&quot;https://mattermodeling.stackexchange.com/users/6472/anycorn&quot;&gt;Anycorn&lt;/a&gt; was &amp;quot;accepted&amp;quot; by the OP:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I wrote python bindings for libint. Did you look in python/tests? there are two tests, including sample hf program&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;but it was deleted due to being &amp;quot;&lt;a href=&quot;https://math.meta.stackexchange.com/q/15224/202425&quot;&gt;very low quality&lt;/a&gt;&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Geoff's &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10145/how-to-use-libint-with-python#comment21544_10145&quot;&gt;comment&lt;/a&gt; was even better, as it gave the exact URL to a complete script, rather than just suggesting for the OP to look in a folder where they may or may not find what they need.&lt;/p&gt;&#xA;&lt;h3&gt;Conclusion:&lt;/h3&gt;&#xA;&lt;p&gt;Using libint with Python has been demonstrated for the &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt; molecule in &lt;a href=&quot;https://github.com/evaleev/libint/blob/master/python/tests/test_hf.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this complete script&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="30" LastEditDate="2022-12-30T00:45:16.810" LastActivityDate="2022-12-30T00:45:16.810" CommentCount="1" CommunityOwnedDate="2022-12-29T16:34:57.853" ContentLicense="CC BY-SA 4.0" />
  <row Id="10165" PostTypeId="2" ParentId="10163" CreationDate="2022-12-29T22:36:55.587" Score="9" Body="&lt;p&gt;Yes, provided the nature and timescales of the dynamics are the same it should be safe to use the same thermostat (and time-step, barostat etc) parameters for the &lt;em&gt;ab initio&lt;/em&gt; MD and the classical MD. The thermostat parameters are chosen according to the characteristic times for the dynamics, they don't particularly care what the details of the dynamics are. If applicable, you should make sure you're using the same constraints and restraints in both simulations, as they can also affect the timescales of the dynamics.&lt;/p&gt;&#xA;&lt;p&gt;There are some exceptions, such as if your classical MD used a coarse-grained model; in that case, the classical dynamics would be much slower than the &lt;em&gt;ab initio&lt;/em&gt; dynamics. I'm not quite sure whether you'd have to do anything different if you were actually doing Car-Parrinello dynamics for your AIMD, since in that case the &lt;em&gt;ab initio&lt;/em&gt; dynamics would include electron (really, Kohn-Sham particle) dynamics, which are not present in classical MD and happen on a much shorter timescale. Those dynamics might be integrated out well enough that they don't affect your thermostat etc, but it would be worth checking.&lt;/p&gt;&#xA;&lt;p&gt;One difference between AIMD and most classical MD is the possibility to change the atomic interactions dynamically, e.g. by breaking or forming chemical bonds. If this happens during your simulation, then you may want to check the time-step and thermostat parameters again, because this could affect the time-scales signficantly.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2022-12-29T22:36:55.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10166" PostTypeId="2" ParentId="9015" CreationDate="2022-12-30T10:06:32.227" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Simulation box/cell: It is the box or the defined region with specified dimension that you build to study your system with specific number of molecules (based on density). Your system size should be large enough to avoid the finite size effect but small enough to avoid undue computation time.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Periodic Boundary: In terms of dimension, as you asked it will be the same. But in technical sense, periodic boundary is a method which replicates your simulation cell into an infinite lattice.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Dimension will be the same of your simulation box size but two are different in technical meaning.&lt;/p&gt;&#xA;&lt;p&gt;As @B.kelly answered, you could go through number of good reference books to understand the concept well (Computer Simulation of Liquids by Allen and Tidsley). This book is well known among those working with MD simulations.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastEditorUserId="7" LastEditDate="2023-01-04T00:22:19.530" LastActivityDate="2023-01-04T00:22:19.530" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10168" PostTypeId="1" CreationDate="2022-12-30T10:34:08.387" Score="3" ViewCount="76" Body="&lt;p&gt;Does System Configuration on which we run MD simulation (to obtain a trajectory for the system under investigation) affects the analysis results.&lt;/p&gt;&#xA;&lt;p&gt;If it does, then could anybody explain me to what extent (significant figures) does it affects.&lt;/p&gt;&#xA;&lt;p&gt;I tried to look for answers but couldn't find it.&lt;br /&gt;&#xA;I came across the results, that doing simulation with different simulation software does affects the results to some significant extent but regarding system configuration I couldn't find.&lt;/p&gt;&#xA;&lt;p&gt;Since I got to know (from some sources), that if one needs to compare different force field parameters for some molecule (let say water), one has to run simulation in a single system in order to not affect the results by any means (effects of system configuration such as cpu or gpu).&lt;/p&gt;&#xA;&lt;p&gt;Hope someone could clarify my doubts.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastActivityDate="2022-12-30T17:20:45.060" Title="Effect of System Configuration on MD simulation results" Tags="|computational-chemistry|atomistic-simulation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10169" PostTypeId="2" ParentId="6480" CreationDate="2022-12-30T10:47:57.993" Score="0" Body="&lt;p&gt;An RDF is the ratio of local density to bulk density of your system. You can look for the equation in number of good books (e.g. Allen and Tidsley).&lt;/p&gt;&#xA;&lt;p&gt;For a simulated system with a defined periodic boundary, you need to consider the effect of PBCs otherwise you might end up getting incorrect distances for atoms present at the surface with elongated bonds.&lt;/p&gt;&#xA;&lt;p&gt;To solve this you can again look for a very basic code available in the Allen and Tidsely book.&lt;/p&gt;&#xA;&lt;p&gt;The results that you are getting might differ due to the size of bin one chooses for binning the atoms at a particular distance.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastEditorUserId="5" LastEditDate="2022-12-30T15:45:21.060" LastActivityDate="2022-12-30T15:45:21.060" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10170" PostTypeId="1" CreationDate="2022-12-30T12:43:05.967" Score="4" ViewCount="699" Body="&lt;p&gt;I need some cutoff radii to count bonds between different atoms in my system. When a .cif file is opened in Vesta, there are some default values of min and max bond lengths between two atomic species. While the minimum is always 0, the maximum values are different. How is this maximum value determined? Is it good enough cutoff to describe actual bonds in the system?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yiuSa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yiuSa.png&quot; alt=&quot;Screengrab of Edit&amp;gt; Bonds option in Vesta&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6313" LastActivityDate="2023-01-02T08:20:06.487" Title="Maximum bond length in Vesta" Tags="|crystallography|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10171" PostTypeId="2" ParentId="10168" CreationDate="2022-12-30T17:20:45.060" Score="6" Body="&lt;p&gt;If you are running a particular algorithm, then different codes should in principle give the same results. However, often algorithms require random numbers that are generated with seeds within the code. This can lead to problems with reproducibility - especially if the seeds cannot be set manually.&lt;/p&gt;&#xA;&lt;p&gt;I think the best approach here is use statistical tools to estimate the error of a given calculation. If anyone ever does a single MD simulation (a single computation) the result is meaningless, as the data obtained could have been an outlier. The experiment should be repeated multiple times and then the appropriate statstical analysis done. I'm a big fan of bootstrapping. One would hope that results from different codes will then match-up (up to certain errors). If not, then it would be a major problem in field.&lt;/p&gt;&#xA;&lt;p&gt;I don't directly work in MD, but I know they use ensembles to estimate error. For example see: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.1c00526&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jctc.1c00526&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4349" LastActivityDate="2022-12-30T17:20:45.060" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10172" PostTypeId="2" ParentId="9258" CreationDate="2022-12-31T03:15:38.187" Score="2" Body="&lt;p&gt;This question was &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9258/flink-installation-question-on-macos-monterey#comment19353_9258&quot;&gt;answered by Geoff&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ffmpeg&lt;/code&gt; can be installed with &lt;a href=&quot;https://brew.sh/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Homebrew&lt;/a&gt; this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9258/flink-installation-question-on-macos-monterey#comment19354_9258&quot;&gt;worked&lt;/a&gt; for the OP.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2022-12-31T03:15:38.187" CommentCount="0" CommunityOwnedDate="2022-12-31T03:15:38.187" ContentLicense="CC BY-SA 4.0" />
  <row Id="10173" PostTypeId="1" CreationDate="2022-12-31T09:07:32.320" Score="4" ViewCount="158" Body="&lt;p&gt;I have written this code using RdKit to find topographic distance&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import AllChem&#xA;from rdkit.Chem import rdDistGeom as molDG&#xA;dm=AllChem.Get3DDistanceMatrix('example.mol')&#xA;print(dm)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm not quite sure if the general form of the code is correct, but it also leads to an error message I don't know how to fix.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;AllChem.Get3DDistanceMatrix('example.mol')&#xA;ArgumentError: Python argument types in&#xA;    rdkit.Chem.rdmolops.Get3DDistanceMatrix(str)&#xA;did not match C++ signature:&#xA;    Get3DDistanceMatrix(class RDKit::ROMol {lvalue} mol, int confId=-1, bool useAtomWts=False, bool force=False, char const * __ptr64 prefix='')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I would like some help either correcting this error or just getting an example of computing topographic distance with rdkit.&lt;/p&gt;&#xA;" OwnerUserId="6241" LastEditorUserId="7" LastEditDate="2022-12-31T15:30:26.303" LastActivityDate="2022-12-31T17:42:27.420" Title="How to find topographic distance of molecule from mol format" Tags="|rdkit|cheminformatics|drug-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10174" PostTypeId="2" ParentId="10173" CreationDate="2022-12-31T17:42:27.420" Score="5" Body="&lt;p&gt;First off, it's important to know that some (most?) mol files do not include 3D coordinates. So you'd need to generate them (e.g., from &lt;code&gt;rdDistGeom&lt;/code&gt; or ETKDG).&lt;/p&gt;&#xA;&lt;p&gt;Your problem is that you're supplying a filename string to a method that requires a molecule object.&lt;/p&gt;&#xA;&lt;p&gt;Let's assume your &lt;code&gt;example.mol&lt;/code&gt; file has 3D coordinates already.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import AllChem&#xA;from rdkit.Chem import rdDistGeom as molDG&#xA; &#xA;mol = Chem.MolFromMolFile('example.mol')&#xA;# either of these should work&#xA;bm = molDG.GetMoleculeBoundsMatrix(mol)&#xA;# .. or what you asked&#xA;dm = AllChem.Get3DDistanceMatrix(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If (more likely) you need to generate 3D coordinates, you'll want something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = Chem.MolFromMolFile('example.mol')&#xA;# always add hydrogens before generating 3D coordinates&#xA;m2 = Chem.AddHs(mol)&#xA;AllChem.EmbedMolecule(m2)&#xA;# if you don't want to consider the hydrogens you can remove them&#xA;# before calculating the distance matrix&#xA;dm = AllChem.Get3DDistanceMatrix(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2022-12-31T17:42:27.420" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10175" PostTypeId="2" ParentId="9299" CreationDate="2023-01-01T00:39:21.837" Score="9" Body="&lt;p&gt;There are generally two main reasons why the total force can be nonzero (in any DFT code):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Your forces are only correct when the calculation has converged fully to the ground state, and so in practice there will be errors. These errors can cause the force sum to be nonzero, and are particularly large with density-mixing (or potential-mixing) SCF methods. The errors can be reduced by tightening the convergence tolerances so that the computed solution is closer to the ground state;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The physical reason forces should sum to zero is because of a continuous translational symmetry, which is not actually present in the calculation - there are finite real-space grids, local basis set centres and a whole host of objects which are not continuously translationally invariant. These errors are reduced with finer grids (eg higher plane-wave cut-off energies), Pulay force corrections etc.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For both of these reasons, the total force on the system can be a useful indicator of the quality of your calculation.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-01-01T00:39:21.837" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10177" PostTypeId="2" ParentId="10170" CreationDate="2023-01-02T08:20:06.487" Score="3" Body="&lt;p&gt;Minimum and maximum atomic distances can be selected by users. From the crystallographic point of view the nearest neighbour distances depend on the atomic sizes of the involved elements (C-C distance is shorter than U-U distance, for example).&lt;/p&gt;&#xA;&lt;p&gt;In any case, the best thing is to plot the structure; then, you can measure the distance between selected atoms using the &amp;quot;Distance&amp;quot; tool in the vertical panel on the left (see the image). &lt;a href=&quot;https://i.stack.imgur.com/yPcRi.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yPcRi.jpg&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;  At this point you have an idea of the distange range and you can select the minimum and maximum atomic distances to be considered in the &amp;quot;bonds&amp;quot; window.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2023-01-02T08:20:06.487" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10178" PostTypeId="1" CreationDate="2023-01-02T12:37:50.390" Score="3" ViewCount="85" Body="&lt;p&gt;I requested a copy of GAMESS, downloaded it, installed ATLAS because the config file said &amp;quot;please download a math library&amp;quot; and built ATLAS. I then tried to compile it using the compall file. Got &amp;quot;command not found&amp;quot; compilation errors(no pics as I tried taking a pic of the screen and it was over 2MB)- no matter how many times do I re-configure GAMESS and select various compilers. How do I fix this problem? My device is a Surface, using Windows/WSL.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2023-01-10T07:58:48.137" LastActivityDate="2023-01-12T03:33:23.267" Title="Error when trying to compile (after everything else has been done) GAMESS on Windows/WSL" Tags="|software-assistance|gamess|windows-operating-system|webmo|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10179" PostTypeId="2" ParentId="10048" CreationDate="2023-01-02T14:36:29.590" Score="2" Body="&lt;p&gt;After visualising the cube file in VMD, it was found that the coordinates of one of Si atoms (-3.9375, 3.9375, 3.9375) is beyond the 30x30x30 voxels system (interpreting 0.075 atomic units as width of a voxel from the cube file).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hmvAI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hmvAI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hence, Spherical Integration is not possible as volumetric data provided seems to be insufficient. It would rather be appropriate to use  &lt;a href=&quot;http://theory.cm.utexas.edu/henkelman/code/bader/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bader Charge Analysis&lt;/a&gt; to find total charge associated with each atom, and the zero flux surfaces which might give a better picture about the interstitial charge of the 2 Si atom system.&lt;/p&gt;&#xA;" OwnerUserId="6422" LastActivityDate="2023-01-02T14:36:29.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10180" PostTypeId="1" CreationDate="2023-01-02T15:25:20.267" Score="4" ViewCount="213" Body="&lt;p&gt;I am unable to do a Quantum Espresso &amp;quot;nscf&amp;quot; calculation using ASE. I have created a &amp;quot;mwe&amp;quot; to show the problem, followed by the output. I will be grateful if someone helps me solve the problem.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import ase.io as aio&#xA;from ase.calculators.espresso import Espresso&#xA;from ase.constraints import ExpCellFilter&#xA;from ase.dft.dos import DOS&#xA;from ase.optimize import BFGS&#xA;&#xA;structure = aio.read(&amp;quot;Fe_mp-13_symmetrized.cif&amp;quot;)&#xA;pseudolst = {&amp;quot;Fe&amp;quot;: &amp;quot;Fe.pbe-spn-kjpaw_psl.1.0.0.UPF&amp;quot;}&#xA;&#xA;input_data = {&#xA;    &amp;quot;nspin&amp;quot;: 2,&#xA;    &amp;quot;degauss&amp;quot;: 0.04,&#xA;    'occupations': 'smearing',&#xA;    'smearing': 'gaussian',&#xA;}&#xA;structure.magmom = '3.0'&#xA;calc = Espresso(&#xA;    pseudopotentials=pseudolst,&#xA;    tstress=True,&#xA;    tprnfor=True,&#xA;    input_data=input_data,&#xA;    crystal_coordinates=True,&#xA;)&#xA;structure.calc = calc&#xA;ucf = ExpCellFilter(structure)&#xA;opt = BFGS(ucf, trajectory=&amp;quot;structure.traj&amp;quot;, restart=&amp;quot;structure.restart&amp;quot;)&#xA;opt.run(fmax=0.025)&#xA;structure.get_potential_energy()&#xA;dos = DOS(calc)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is giving error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python mwe.py&#xA;/home/rudra/.local/lib/python3.11/site-packages/ase/calculators/espresso.py:170: FutureWarning: Espresso calculator is being restructured.  Please use e.g. Espresso(profile=EspressoProfile(argv=['mpiexec', 'pw.x'])) to customize command-line arguments.&#xA;  warnings.warn(compatibility_msg, FutureWarning)&#xA;      Step     Time          Energy          fmax&#xA;BFGS:    0 20:30:39    -8965.356995         6.760408&#xA;BFGS:    1 20:30:48    -8966.058114         0.045096&#xA;BFGS:    2 20:30:58    -8966.058212         0.146969&#xA;BFGS:    3 20:31:09    -8966.058147         0.027810&#xA;BFGS:    4 20:31:18    -8966.058162         0.018795&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/home/rudra/Projects/ASE/QE/mwe.py&amp;quot;, line 31, in &amp;lt;module&amp;gt;&#xA;    dos = DOS(calc)&#xA;          ^^^^^^^^^&#xA;  File &amp;quot;/home/rudra/.local/lib/python3.11/site-packages/ase/dft/dos.py&amp;quot;, line 34, in __init__&#xA;    self.e_skn = np.array([[calc.get_eigenvalues(kpt=k, spin=s)&#xA;                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/rudra/.local/lib/python3.11/site-packages/ase/dft/dos.py&amp;quot;, line 34, in &amp;lt;listcomp&amp;gt;&#xA;    self.e_skn = np.array([[calc.get_eigenvalues(kpt=k, spin=s)&#xA;                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/rudra/.local/lib/python3.11/site-packages/ase/dft/dos.py&amp;quot;, line 34, in &amp;lt;listcomp&amp;gt;&#xA;    self.e_skn = np.array([[calc.get_eigenvalues(kpt=k, spin=s)&#xA;                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/rudra/.local/lib/python3.11/site-packages/ase/calculators/abc.py&amp;quot;, line 92, in get_eigenvalues&#xA;    return eigs[kpt, spin]&#xA;           ~~~~^^^^^^^^^^^&#xA;IndexError: index 1 is out of bounds for axis 1 with size 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5946" LastEditorUserId="5" LastEditDate="2023-03-11T18:52:36.483" LastActivityDate="2023-03-11T18:52:36.483" Title="Calculate DOS with Quantum Espresso and ASE" Tags="|quantum-espresso|atomic-simulation-environment|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-10T00:25:58.650" ContentLicense="CC BY-SA 4.0" />
  <row Id="10181" PostTypeId="2" ParentId="7263" CreationDate="2023-01-02T17:37:08.477" Score="1" Body="&lt;p&gt;When you change the lattice, you actually change the crystal structure (don't confuse the lattice, a geometrical object, with the crystal structure, a real object).&lt;/p&gt;&#xA;&lt;p&gt;First of all you have to consider the space group types of your starting and final structures and verify that a group-subgroup relationship holds between them. If yes, you can transform the structure.&lt;/p&gt;&#xA;&lt;p&gt;Than you can use the tools avaliable at the Bilbao Crystallographic Server for transforming your structure. It is imperatuve that you use a correct transfomation matrix. At this point the Server will give you the atomic positions in the Wyckoff sites for the new space group. You can save this structure as a CIF file and import it in Vesta.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2023-01-02T17:37:08.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10182" PostTypeId="1" CreationDate="2023-01-02T22:00:14.870" Score="3" ViewCount="75" Body="&lt;p&gt;I am running a MCTDH block relaxation for vibronic models and got the following error message:&lt;/p&gt;&#xA;&lt;p&gt;ERROR in subroutine rdavstep:&#xA;Illegal integration order&lt;/p&gt;&#xA;&lt;p&gt;My input file is as follow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RUN-SECTION&#xA;title = block improved water relaxation&#xA;name = h2o_ev&#xA;relaxation=0,olsen precon=50 orben&#xA;tout = 5.0 tfinal = 30.00&#xA;rlxunit=eV, 0.0&#xA;psi=double&#xA;end-run-section&#xA;&#xA;OPERATOR-SECTION&#xA;opname = h2o_ev&#xA;end-operator-section&#xA;&#xA;SPF-BASIS-SECTION&#xA;packet=1000, single-set&#xA;      v01      =  35&#xA;      v02      =  35&#xA;      v03      =  35&#xA;end-spf-basis-section&#xA;&#xA;PRIMITIVE-BASIS-SECTION&#xA;    v01    HO     35   0.0   1.0   1.0&#xA;    v02    HO     35   0.0   1.0   1.0&#xA;    v03    HO     35   0.0   1.0   1.0&#xA;    el     el     3&#xA;end-primitive-basis-section&#xA;&#xA;INTEGRATOR-SECTION&#xA;CMF/varphi = 0.5, 1.0d-08&#xA;RK8/spf = 1.0d-8, 0.1&#xA;rrDAV = 1000, 1.0d-11&#xA;end-integrator-section&#xA;&#xA;INIT_WF-SECTION&#xA;build&#xA;   init_state=2&#xA;-----------------------------------------------------------&#xA;#  mode   type  center  moment.  freq.    mass&#xA;-----------------------------------------------------------&#xA;    v01    HO     0.0    0.0      1.0     1.0&#xA;    v02    HO     0.0    0.0      1.0     1.0&#xA;    v03    HO     0.0    0.0      1.0     1.0&#xA;-----------------------------------------------------------&#xA;end-build&#xA;autoblock&#xA;end-init_wf-section&#xA;&#xA;end-input&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The goal of this calculation is to obtain energy eigenvalues of the low lying eigenstates of this vibronic model. Anyone knows the origin of this error?&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2023-01-02T22:00:14.870" Title="Error message on MCTDH block relaxation calculation" Tags="|mctdh|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-19T17:24:40.033" ContentLicense="CC BY-SA 4.0" />
  <row Id="10183" PostTypeId="2" ParentId="9351" CreationDate="2023-01-03T02:58:13.243" Score="7" Body="&lt;p&gt;The combination of the diffraction technique with functionals of the density functional theory has been used. It allows one to describe both the static charge distribution and picture the electron motion in terms of the local energy and related functions. It gives scope to calculate energies and other properties. Refer to &lt;a href=&quot;https://doi.org/10.1107/S010876730401339X&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There have been instances where researchers have tried to find the discrepancy between energy density (ED) functions calculated from the Hartree-Fock electron density using approximation and functions calculated using the model ED derived from X-ray diffraction experiments. The following reasons for discrepancy were mentioned:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;First, the rapid variation of&#xA;the electron density in the vicinity of the nuclei and its slow&#xA;variation in the valence electron shells prevents the existence&#xA;of the density functional approximation for g(r), which&#xA;provides a good description everywhere in the position space.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/laCFD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/laCFD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Second,the leading term in the kinetic energy density expansion (5) comes from the statistical Thomas-Fermi theory, which is valid for high-density regions. Quantum corrections improve the&#xA;local behavior of this function; however, discrepancy with the Hartree-Fock kinetic energy density still remains.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For deeper understanding, refer to &lt;a href=&quot;https://doi.org/10.1107/S0108768102005517&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Although multiple rigorous methods of density functional theory and correction terms have been mentioned in the &lt;a href=&quot;https://books.google.com/books?hl=en&amp;amp;lr=&amp;amp;id=QGwJEAAAQBAJ&amp;amp;oi=fnd&amp;amp;pg=PP1&amp;amp;dq=Electron%20Density%20and%20Bonding%20in%20Crystals&amp;amp;ots=mI0zOHf1Fq&amp;amp;sig=AufX79ixN1a_K-1s7uFXtqFwQuE&quot; rel=&quot;nofollow noreferrer&quot;&gt;book&lt;/a&gt; '&lt;em&gt;Electron Density and Bonding in Crystals:Principles, Theory and X-ray Diffraction Experiments in Solid State Physics and Chemistry&lt;/em&gt;' which provide less relative error, however I am sceptical about the part on converged density being consistent with the experimental densities as there are difficulties associated with construction of general rigorous DFT with electron density as basic variable.As written in the book aforementioned:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The main difficulty of the DFT lies in the construction of approximation to functional G[ρ] which contains both kinetic T[ρ] and exchange-correlation Fxc[ρ] energies in the total energy functional E[ρ].&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6422" LastEditorUserId="671" LastEditDate="2023-01-03T07:44:58.980" LastActivityDate="2023-01-03T07:44:58.980" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10184" PostTypeId="2" ParentId="9998" CreationDate="2023-01-03T04:27:09.673" Score="3" Body="&lt;p&gt;To perform spin-projected band structure calculations in VASP, you typically need to perform a self-consistent field (SCF) calculation first to generate CHGCAR file. The CHGCAR file is not directly involved in the spin projection process, but it is a necessary input file for the band structure calculation.&lt;/p&gt;&#xA;&lt;p&gt;You should include the following tags in your INCAR file for both SCF and bandstructure calculations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISPIN = 2    ! Set ISPIN to 2 to enable spin polarization.&#xA;LSORBIT = .TRUE.    ! Enable spin-orbit coupling if needed.&#xA;LNONCOLLINEAR = .TRUE.    ! Enable non-collinear spin calculations if needed.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Assuming you have a relaxed structure and did convergence tests for total energy of the system. The following is a sample file for SCF calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;ICHARG = 2&#xA;NELM = 100&#xA;EDIFF = 1E-8&#xA;ENCUT = 400&#xA;ALGO = Fast&#xA;IBRION = -1&#xA;ISIF = 2&#xA;POTIM = 0.5&#xA;NSW = 0&#xA;EDIFFG = -0.01&#xA;ISMEAR = -5&#xA;SIGMA = 0.2&#xA;PREC = Accurate&#xA;ISPIN = 2 ! spin-projection&#xA;LREAL = .F.&#xA;LWAVE = .T.&#xA;LCHARG = .T.  !write the CHGCAR file&#xA;LAECHG = .TRUE.&#xA;GGA = PE !GGA-PBE functional&#xA;IVDW = 11 !vdW correction&#xA;ADDGRID = .TRUE.&#xA;LASPH = .TRUE.&#xA;LORBIT = 11&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You need to check VASP documentation for further details. After getting the CHGCAR file from the SCF calculation, copy that file into a new directory where you intend to do the bandstructure calculation, remember to set the tags for reading the CHGCAR file. The following is a sample file for such calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;ICHARG = 11 ! Read CHGCAR file&#xA;NELM = 100&#xA;EDIFF = 1E-8&#xA;ENCUT = 400&#xA;ALGO = Fast&#xA;IBRION = -1&#xA;ISIF = 2&#xA;POTIM = 0.5&#xA;NSW = 0&#xA;EDIFFG = -0.01&#xA;ISMEAR = 0&#xA;SIGMA = 0.2&#xA;PREC = Accurate&#xA;ISPIN = 2&#xA;LREAL = .F.&#xA;LWAVE = .F.&#xA;LCHARG = .F.&#xA;LAECHG = .F.&#xA;GGA = PE&#xA;IVDW = 11&#xA;ADDGRID = .TRUE.&#xA;LASPH = .TRUE.&#xA;LORBIT = 11&#xA;NBANDS = 80&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have to mention that this is just an example and you need to understand the purpose of each of those tags for your own situation or structure.&lt;/p&gt;&#xA;&lt;p&gt;Now assuming that you have your spin-projected bandstructure calculations done, VASP will write an .xml file called vasprun.xml. You may use this file to do the plotting using &lt;a href=&quot;https://smtg-ucl.github.io/sumo/sumo-bandplot.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;sumo-bandplot&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In a directoty where you have your vasprun.xml file along with the KPOINTS used for the bandstructure calculation, you can just run&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sumo-bandplot --filenames vasprun.xml --spin 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;--spin will determines whether to plot the up spin (1) or down spin (-1). Further options such as projection of atomic contributions can be found in the documentation.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-12-16T02:51:46.417" LastActivityDate="2023-12-16T02:51:46.417" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10185" PostTypeId="1" CreationDate="2023-01-03T06:24:08.433" Score="3" ViewCount="41" Body="&lt;p&gt;When I try to plot wavefunctions in the Avogadro software I find that the orbitals are often clipped by a rectangular box. Does anyone know how to increase the size of this box so that I can plot larger orbital lobes?&lt;/p&gt;&#xA;" OwnerDisplayName="pQ12branch" LastEditorUserId="5" LastEditDate="2023-01-03T15:36:00.240" LastActivityDate="2023-01-03T15:36:00.240" Title="Prevent Avogadro from clipping wavefunction plots" Tags="|software|computational-chemistry|avogadro|" AnswerCount="0" CommentCount="1" ClosedDate="2023-06-14T01:11:29.647" ContentLicense="CC BY-SA 4.0" />
  <row Id="10186" PostTypeId="1" AcceptedAnswerId="10187" CreationDate="2023-01-03T15:32:06.463" Score="6" ViewCount="474" Body="&lt;p&gt;This is a general question about how we treat unbalanced charges in density functional theory (DFT), which might arise when we model charged defects. In &lt;code&gt;VASP&lt;/code&gt;, I would just change the &lt;code&gt;NELECT&lt;/code&gt; variable (number of valence electrons), but I'm interested in how this changes the implementation (if any). Some hints can be found in the &lt;code&gt;NELECT&lt;/code&gt; &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NELECT&quot; rel=&quot;noreferrer&quot;&gt;VaspWiki page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If the number of electrons is not compatible with the number derived from the valence and the number of atoms a homogeneous background charge is assumed.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I don't quite understand what assuming a &amp;quot;homogeneous background charge&amp;quot; entails. Is there a change to the implementation (e.g. additional terms to consider due to the &amp;quot;homogeneous background charge&amp;quot;, such as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Thomas%E2%80%93Fermi_model&quot; rel=&quot;noreferrer&quot;&gt;Thomas-Fermi&lt;/a&gt; kinetic energy for the background charge&amp;quot;, the &amp;quot;background charge&amp;quot; - &amp;quot;background charge&amp;quot;, &amp;quot;background charge&amp;quot; - &amp;quot;valence electrons&amp;quot;, and &amp;quot;background charge&amp;quot; - &amp;quot;ion core&amp;quot; interactions) or would we just proceed with the usual Kohn-Sham DFT scheme, but solving for more or less bands depending on whether electrons are added or removed (the assumption of the &amp;quot;homogeneous background charge&amp;quot; being some conceptual tool that doesn't affect the implementation)?&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-01-03T16:30:00.370" Title="DFT Treatment of Unbalanced Charges in Solids" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10187" PostTypeId="2" ParentId="10186" CreationDate="2023-01-03T16:30:00.370" Score="9" Body="&lt;p&gt;In periodic boundary conditions, the electrostatic energy of a charged unit cell diverges, so any attempt to calculate it will result in infinity. The solution is to add a &amp;quot;neutralising&amp;quot; homogeneous background charge, which makes the simulated cell charge-neutral and allows the energy to be well-defined again.&lt;/p&gt;&#xA;&lt;p&gt;This neutralising background charge is literally just a charge distribution, not a uniform electron gas or any other physical system, so there are no other terms required in the Hamiltonian. In fact, some simulation software (e.g. CASTEP) deals with this entirely implicitly, by not including the mean electrostatic potential contributions at all (the ion-ion, electron-electron, and electron-ion Coulomb contributions exactly cancel out, so the nett contribution is zero). Some care is required in the implementation, for example with non-Coulombic local pseudopotential contributions, but it's generally quite straightforward.&lt;/p&gt;&#xA;&lt;p&gt;The presence of the neutralising background does not change the charge density or the Kohn-Sham states, since it's a constant background field; however, it does change the energies, bands etc. so they aren't directly comparable between different charge states.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-01-03T16:30:00.370" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10188" PostTypeId="1" CreationDate="2023-01-03T18:19:59.850" Score="6" ViewCount="122" Body="&lt;p&gt;While I'm primarily interested in molecular normal modes, the question could also apply to calculating phonon spectra / vibrations in solids.&lt;/p&gt;&#xA;&lt;p&gt;There are many machine learning approaches to calculate energies of molecules and solids. Some have even been used for molecular dynamics and geometry optimizations.&lt;/p&gt;&#xA;&lt;p&gt;In principal, one could use the ML potential energy surface to derive the mass-weighted Hessian matrix, and solve for eigenvalues and eigenvectors. (For example, one could test whether the resulting vibrational frequencies are accurate.)&lt;/p&gt;&#xA;&lt;p&gt;Are there existing packages (e.g., in Python) which calculate the mass-weighted Hessian from a ML potential, convert units to frequencies, and compare the normal modes?&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-01-06T17:58:39.757" Title="Are there packages which calculate normal modes for ML potentials?" Tags="|vibrations|machine-learning|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10189" PostTypeId="2" ParentId="10135" CreationDate="2023-01-04T15:55:43.327" Score="7" Body="&lt;p&gt;def2-TZVP employs an effective core potential on Te, which describes the innermost 28 electrons only implicitly; this is almost certainly the cause of the problem. I am surprised the program even prints out shieldings for ECP containing centers!&lt;/p&gt;&#xA;&lt;p&gt;You will probably need to switch to an all-electron approach to be able to describe NMR spectroscopies on Te compounds. I do not know how important relativistic effects are, but this should be discussed in the papers you linked. If non-relativistic calculations are okay, then you just need to switch to an all-electron basis set for Te. On a quick glance at the periodic table and the results of the paper, relativity should be pretty important for NMR on Te.&lt;/p&gt;&#xA;&lt;p&gt;The two papers by Rusakova and coworkers you referenced above employed &lt;a href=&quot;http://www.diracprogram.org/doku.php&quot; rel=&quot;noreferrer&quot;&gt;the DIRAC program&lt;/a&gt; for the relativistic calculations. DIRAC is nowadays open source, and is free to download and install on any system. As far as I know, DIRAC has the best selection of relativistic methods, and my suggestion would be to look into how to install DIRAC and perform the modeling with it. The program you appear to be using does have some support for scalar relativistic calculations with the Douglas-Kroll-Hess (DKH) Hamiltonian, but I don't know if it can do NMR in combination with DKH.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-01-04T15:55:43.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10190" PostTypeId="2" ParentId="10145" CreationDate="2023-01-04T16:00:25.080" Score="5" Body="&lt;p&gt;&lt;a href=&quot;https://pyquante.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;PyQuante&lt;/a&gt; is one of the first quantum chemistry codes written in Python, and it has been around for a long time. There is a binding to Ed Valeev's libint version 1 in PyQuante, see &lt;a href=&quot;https://sourceforge.net/p/pyquante/code/HEAD/tree/trunk/Src/lib/clibint.c&quot; rel=&quot;noreferrer&quot;&gt;clibint.c&lt;/a&gt; and &lt;a href=&quot;https://sourceforge.net/p/pyquante/code/HEAD/tree/trunk/Src/lib/clibint.h&quot; rel=&quot;noreferrer&quot;&gt;clibint.h&lt;/a&gt;; I am sure these will be as much help to you as they were for me a decade ago when I wrote my own interface to libint.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-01-04T16:00:25.080" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10192" PostTypeId="2" ParentId="9743" CreationDate="2023-01-05T02:10:55.860" Score="2" Body="&lt;h1&gt;Preliminaries&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;The hint &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9779/5&quot;&gt;by Sverus Snape&lt;/a&gt; to use a numpy array was helpful, &lt;strong&gt;but how does one do that?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I found the answer at &lt;a href=&quot;https://stackoverflow.com/a/55058828/1271772&quot;&gt;How to save and load numpy.array() data properly?&lt;/a&gt; and since there's also so many different options given there (e.g. &lt;code&gt;np.fromfile&lt;/code&gt;, &lt;code&gt;np.loadtxt&lt;/code&gt;, &lt;code&gt;np.load&lt;/code&gt;, etc.) I would like to provide people with the solution that worked for me, and a minimum working example.  &lt;/p&gt;&#xA;&lt;h1&gt;Benchmark calculation (without restarting)&lt;/h1&gt;&#xA;&lt;p&gt;A calculation of the CISD energies for the lowest three electronic states of Ne in cc-pV5Z using this input with &lt;code&gt;conv_tol=1e-9&lt;/code&gt; required 9 Davidson iterations to converge the ground state energy to this precision, and more than 30 Davidson iterations to converge the third highest of these electronic states:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 34 5  |r|= 6.05e-05  e= [-0.33719767  0.80457309  0.80457311]  max|de|= -2.83e-09  lindep= 0.913&#xA;davidson 35 6  |r|= 3.02e-05  e= [-0.33719767  0.80457309  0.80457311]  max|de|= -1e-09  lindep= 0.738&#xA;root 2 converged  |r|= 2.1e-05  e= 0.8045731078550442  max|de|= -1.36e-10&#xA;converged 36 7  |r|= 2.1e-05  e= [-0.33719767  0.80457309  0.80457311]  max|de|= -1.36e-10&#xA;RCISD converged&#xA;RCISD root 0  E = -128.8839677954546&#xA;RCISD root 1  E = -127.7421970392584&#xA;RCISD root 2  E = -127.7421970216469&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Partial calculation (saves CI vector for later)&lt;/h1&gt;&#xA;&lt;p&gt;The example below does the same calculation but wtih &lt;code&gt;conv_tol=1e-5&lt;/code&gt; and it saves the numpy array of the CI vector.  I ended up using the answer with the &lt;em&gt;&lt;strong&gt;second&lt;/strong&gt;&lt;/em&gt; highest net score on the above StackOverflow thread, because it was more straightforward, and because binary &lt;code&gt;.npy&lt;/code&gt; files are more practically sized than ASCII &lt;code&gt;.txt&lt;/code&gt; files (a solution with &lt;code&gt;.h5&lt;/code&gt; would be even better, and for the PySCF coupled cluster code, they &lt;a href=&quot;https://pyscf.org/user/cc.html#saving-and-restarting&quot; rel=&quot;nofollow noreferrer&quot;&gt;do document&lt;/a&gt; such a solution).&#xA;The command that I used for saving the CI vector is in the last line below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import numpy as np&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, fci,ci&#xA;&#xA;mol = pyscf.M(atom = 'Ne 0 0 0',basis = 'cc-pv5z',verbose=5,output='out_1e-5_direct.txt')&#xA;mhf = scf.RHF(mol).run()&#xA;mci = ci.CISD(mhf).set(conv_tol=1e-5,nroots=3)&#xA;e, civec = mci.kernel()&#xA;np.save('civec.npy', civec)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Because of the lower convergence criterion, the ground state energy converged after only 5 Davidson iterations, and the highest of the three states sought had its energy converge at around the 19th Davidson iteration (all three energies are also &lt;em&gt;&lt;strong&gt;slightly&lt;/strong&gt;&lt;/em&gt; higher than in the previous calculation):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 17 6  |r|= 0.00551  e= [-0.33719763  0.80457337  0.80459828]  max|de|= -1.57e-05  lindep= 0.691&#xA;davidson 18 7  |r|= 0.00339  e= [-0.33719763  0.80457337  0.80459439]  max|de|= -3.89e-06  lindep= 0.443&#xA;root 2 converged  |r|= 0.00128  e= 0.8045935429617836  max|de|= -8.5e-07&#xA;converged 19 8  |r|= 0.00132  e= [-0.33719763  0.80457337  0.80459354]  max|de|= -8.5e-07&#xA;RCISD converged&#xA;RCISD root 0  E = -128.8839677596848&#xA;RCISD root 1  E = -127.7421967633118&#xA;RCISD root 2  E = -127.7421765865402&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My directory then had the following checkpoint file (not human-readible, since it's a binary file):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-rw-r----- 1 nike nike 4448072 Jan  4 17:42 civec.npy&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Calculation that reuses the saved CI vector&lt;/h1&gt;&#xA;&lt;p&gt;Now I'll recover the &amp;quot;benchmark&amp;quot; energies (&lt;code&gt;conv_tol=1e-9&lt;/code&gt;) using the &lt;code&gt;.npy&lt;/code&gt; file that was saved in the last line of the script in the previous section; it is reused in the last line of the following script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import numpy as np&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, fci,ci&#xA;&#xA;mol = pyscf.M(atom = 'Ne 0 0 0',basis = 'cc-pv5z',verbose=5,output='out_1e-9_restarted.txt')&#xA;mhf = scf.RHF(mol).run()&#xA;mci = ci.CISD(mhf).set(conv_tol=1e-9,nroots=3)&#xA;e, civec = mci.kernel(ci0=np.load('civec.npy'))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives roughly the same energies from the &amp;quot;benchmark&amp;quot; calculation, but with only about 2 Davidson iterations for the ground state energy, and about 12 iterations for the third energy sought:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0 3  |r|= 0.00132  e= [-0.33719763  0.80457337  0.80459354]  max|de|= 0.805  lindep= 0.816&#xA;davidson 1 6  |r|= 0.000962  e= [-0.33719767  0.80457312  0.80459334]  max|de|= -2.48e-07  lindep= 0.506&#xA;root 0 converged  |r|= 2.04e-05  e= -0.33719766591648676  max|de|= -8.9e-10&#xA;davidson 2 9  |r|= 0.000859  e= [-0.33719767  0.80457309  0.80459321]  max|de|= -1.32e-07  lindep= 0.63&#xA;davidson 3 11  |r|= 0.00165  e= [-0.33719767  0.80457309  0.80459283]  max|de|= -3.75e-07  lindep= 0.796&#xA;root 1 converged  |r|= 5.81e-06  e= 0.8045730910409581  max|de|= -6.13e-11&#xA;davidson 4 13  |r|= 0.00418  e= [-0.33719767  0.80457309  0.80458896]  max|de|= -3.88e-06  lindep= 0.939&#xA;davidson 5 14  |r|= 0.00519  e= [-0.33719767  0.80457309  0.80457749]  max|de|= -1.15e-05  lindep= 0.892&#xA;davidson 6 15  |r|= 0.00117  e= [-0.33719767  0.80457309  0.80457335]  max|de|= -4.14e-06  lindep= 0.914&#xA;davidson 7 16  |r|= 0.00041  e= [-0.33719767  0.80457309  0.80457318]  max|de|= -1.66e-07  lindep= 0.775&#xA;davidson 8 3  |r|= 0.00041  e= [-0.33719767  0.80457309  0.80457318]  max|de|= 9.11e-11  lindep= 0.999&#xA;davidson 9 4  |r|= 0.000371  e= [-0.33719767  0.80457309  0.80457314]  max|de|= -3.54e-08  lindep= 0.692&#xA;davidson 10 5  |r|= 0.000219  e= [-0.33719767  0.80457309  0.8045731 ]  max|de|= -4.39e-08  lindep= 0.929&#xA;davidson 11 6  |r|= 7.38e-05  e= [-0.33719767  0.80457309  0.80457309]  max|de|= -7.99e-09  lindep= 0.781&#xA;root 2 converged  |r|= 3.04e-05  e= 0.8045730916435243  max|de|= -7.2e-10&#xA;converged 12 7  |r|= 3.04e-05  e= [-0.33719767  0.80457309  0.80457309]  max|de|= -7.2e-10&#xA;RCISD converged&#xA;RCISD root 0  E = -128.8839677954263&#xA;RCISD root 1  E = -127.7421970385624&#xA;RCISD root 2  E = -127.7421970378585&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Extra remarks&lt;/h1&gt;&#xA;&lt;p&gt;It's remarkable that when following the &amp;quot;save and restart&amp;quot; method, the &lt;em&gt;&lt;strong&gt;total&lt;/strong&gt;&lt;/em&gt; number of Davidson iterations is actually smaller than what was required when setting &lt;code&gt;conv_tol=1e-9&lt;/code&gt; directly in one calculation.&lt;/p&gt;&#xA;&lt;p&gt;This procedure might also be useful for finding higher excited state energies if your &lt;code&gt;nroots&lt;/code&gt; parameter was set undesirably low during your first calculation. &lt;/p&gt;&#xA;&lt;h1&gt;Availability of above input and output files&lt;/h1&gt;&#xA;&lt;p&gt;The input and output files for all three calculations in this answer are provided &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/9743/cisd&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The files are described below:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Calculation&lt;/th&gt;&#xA;&lt;th&gt;Input file&lt;/th&gt;&#xA;&lt;th&gt;Output file&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Benchmark calculation (&lt;code&gt;conv_tol=1-e9&lt;/code&gt;) with no restart&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;inp_1e-9_direct.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;out_1e-9_direct.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Partial calculation (&lt;code&gt;conv_tol=1-e5&lt;/code&gt;), saves the checkpoint file&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;inp_1e-5_direct.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;out_1e-5_direct.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Benchmark recovery (&lt;code&gt;conv_tol=1-e9&lt;/code&gt;), using checkpoint file&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;inp_1e-9_restarted.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;out_1e-9_restarted.py&lt;/code&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-05T02:17:21.180" LastActivityDate="2023-01-05T02:17:21.180" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10194" PostTypeId="5" CreationDate="2023-01-05T16:38:55.577" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.fluxim.com/setfos-intro&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.fluxim.com/setfos-intro&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-05T16:38:55.577" LastActivityDate="2023-01-05T16:38:55.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10195" PostTypeId="4" CreationDate="2023-01-05T16:38:55.577" Score="0" Body="Questions about the Setfos software" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-05T16:38:55.577" LastActivityDate="2023-01-05T16:38:55.577" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10196" PostTypeId="2" ParentId="8636" CreationDate="2023-01-05T18:19:15.690" Score="7" Body="&lt;p&gt;Luckily, I had a need to do this recently, so I can answer with more confidence than I had when commenting before.&lt;/p&gt;&#xA;&lt;p&gt;Basically, the procedure is what you described. We need to:&#xA;(1) compute the interaction of our molecule in an applied electric field,&#xA;(2) compute the change in dipole moment in this field,&#xA;(3) compute the polarizability elements by finite difference.&lt;/p&gt;&#xA;&lt;p&gt;Let's leave aside step (1) for a second since it is slightly different depending on the model of polarization being used.&lt;/p&gt;&#xA;&lt;p&gt;The central equation needed for steps (2) and (3) is the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{P}^{ind}=\alpha\mathbf{E} \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or, to make things simpler, let's only consider applying a field in each direction &lt;span class=&quot;math-container&quot;&gt;$w=x,y,z$&lt;/span&gt; separately. Then, we have,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{P}^{\textrm{ind}}=\alpha\mathbf{E}_w \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, the induced dipole moment may still have a response in any direction, &lt;span class=&quot;math-container&quot;&gt;$q=x,y,z$&lt;/span&gt; due to the anisotropy of the polarizability. Taking the derivative with respect to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{E}_w$&lt;/span&gt; lets us write the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{dP^{ind}_{q}}{dE_w}=\alpha_{qw} \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now that we have an expression for the change of each element of the induced dipole &lt;span class=&quot;math-container&quot;&gt;$P^{ind}_{q}$&lt;/span&gt; when placed in a field &lt;span class=&quot;math-container&quot;&gt;$E_w$&lt;/span&gt;, we can compute each polarizability element by finite difference.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{qw} = \frac{P^{ind}_q(E_{+w}) - P^{ind}_q(E_{-w})}{2|E_w|} \tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$P^{ind}_q(E_{+w})$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;-component of the induced dipole when experiencing a field coming from the positive-&lt;span class=&quot;math-container&quot;&gt;$w$&lt;/span&gt; direction. We then repeat this procedure for each of cartesian axes to get all nine elements of the molecular polarizability.&lt;/p&gt;&#xA;&lt;p&gt;This procedure really has nothing to do with polarizable force fields and can equally well be used in electronic structure calculations (and it often is).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;So, the question now becomes: how do we compute the interaction of a molecule with an applied field in polarizable force field.&lt;/p&gt;&#xA;&lt;p&gt;I'll address induced dipole force fields and fluctuating charge force fields separately, since the answer is slightly different in each case.&lt;/p&gt;&#xA;&lt;p&gt;Starting with induced dipole force fields, the working equations are as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;\begin{bmatrix}&#xA;\alpha_1^{-1} &amp;amp; -T_{12}^{dd} &amp;amp; \dots &amp;amp; -T_{1N}^{dd} \\&#xA;-T_{21}^{dd} &amp;amp; \ddots &amp;amp; \dots &amp;amp; \vdots \\&#xA;\vdots &amp;amp; &amp;amp; &amp;amp; \\&#xA;-T_{N1}^{dd} &amp;amp; \dots &amp;amp; &amp;amp; \alpha_N^{-1} \\&#xA;\end{bmatrix}&#xA;\begin{bmatrix}&#xA;\mathbf{P}_1 \\&#xA;\mathbf{P}_2 \\&#xA;\vdots \\&#xA;\mathbf{P}_N&#xA;\end{bmatrix}&#xA;=&#xA;\begin{bmatrix}&#xA;\mathbf{E}_1^q \\&#xA;\mathbf{E}_2^q \\&#xA;\vdots \\&#xA;\mathbf{E}_N^q&#xA;\end{bmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$T_{12}^{dd}$&lt;/span&gt; is the dipole-dipole interaction tensor and everything else has the same meaning. For this model, it is rather simple to compute the interaction with the field. We just fill our solution vector with the field applied in each direction and use the finite difference scheme described above.&lt;/p&gt;&#xA;&lt;p&gt;Something I've never seen discussed in the literature is that you can actually compute the in-molecule atomic polarizabillities in this way and they well generally not equal the atomic polarizabilities used as parameters. This is because the interactions between induced dipoles within a molecule are strongly damped and hence can result in slight changes in the atomic polarizability (after accounting for changes due to orientation).&lt;/p&gt;&#xA;&lt;p&gt;If you are only interested in the molecular polarzability, then you just do the finite difference scheme on the induced dipole of the molecule which you get by summing the atomic induced dipoles,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{P}^{ind}_{mol}=\sum_{i=1}^{N_{atom}}\mathbf{P}^{ind}_i \tag{6}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you were using a fluctuating charge model, rather than a dipole-polarization model, the procedure is slightly different.&lt;/p&gt;&#xA;&lt;p&gt;We need to recognize that the molecular dipole can be computed from the cartesian coordinates and charges as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{P}_{mol}=\sum_{i=1}^{N_{atom}}q_i\mathbf{R}_i\tag{7}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;When charges are allowed to rearrange within a molecule, we get a changes to the charge at each atom, &lt;span class=&quot;math-container&quot;&gt;$\delta q$&lt;/span&gt;. Then, the total dipole (permanent plus induced dipole) is,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{P}_{mol}=\sum_{i=1}^{N_{atom}}(q_i+\delta q_i)\mathbf{R}_i\tag{8}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The permanent dipole doesn't contribute to the polarizability which is clear from the fact the &lt;span class=&quot;math-container&quot;&gt;$q_i$&lt;/span&gt; terms will go to zero when taking the derivative with respect to the field.&lt;/p&gt;&#xA;&lt;p&gt;I won't write it out in detail here, but in the fluctuating charge polarizabilty model, you end up adding a term to your solution vector which is &lt;span class=&quot;math-container&quot;&gt;$\mathbf{R}_i\cdot\mathbf{E}_w$&lt;/span&gt; since multiplying this by &lt;span class=&quot;math-container&quot;&gt;$\delta q_i$&lt;/span&gt; gives the interaction of the induced charge with the field.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Hopefully this clears things up. I can add more information if needed. I couldn't find any good references for how to do this in the induced dipole case, so I don't have much to cite but I am confident in the procedure since it's the same as what is done in electronic structure. I found one reference for the fluctuating charge case which I can't seem to locate anymore. I don't know why this hasn't been discussed more in the literature...&lt;/p&gt;&#xA;&lt;p&gt;Maybe because if you compute the polarizability hyper-surface and compare it with what you get from electronic structure, the comparison is not very favorable even for the best polarizable force fields. Maybe this is a research question that someone (I) could address in the future (present)... :)&lt;/p&gt;&#xA;" OwnerUserId="1170" LastEditorUserId="30" LastEditDate="2023-01-05T18:39:07.877" LastActivityDate="2023-01-05T18:39:07.877" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10198" PostTypeId="1" CreationDate="2023-01-06T11:19:37.293" Score="4" ViewCount="132" Body="&lt;p&gt;I have tried to calculate Residence time using the residence time auto-correlation function defined as&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$R(t) = \frac{\langle h(0)h(t)\rangle}{\langle h(0)h(0)\rangle}$$&lt;/span&gt;&lt;br /&gt;&#xA;In the calculation, I have used the definition of intermittent hydrogen bond where function &lt;span class=&quot;math-container&quot;&gt;$h(t)$&lt;/span&gt; is 1 if molecules stays in defined cutoff region and zero otherwise.&lt;/p&gt;&#xA;&lt;p&gt;After doing the calculation, I observed&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Relaxation of the function &lt;span class=&quot;math-container&quot;&gt;$R(t)$&lt;/span&gt; varies with the resolution of the trajectory taken for the calculation.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The length of the trajectory for same resolution (say &lt;span class=&quot;math-container&quot;&gt;$\pu{0.1ps}$&lt;/span&gt;) also has its effects on the relaxation of function &lt;span class=&quot;math-container&quot;&gt;$R(t)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am trying to understand what phenomenon actually contributes in the different relaxation time of function &lt;span class=&quot;math-container&quot;&gt;$R(t)$&lt;/span&gt; with varying resolution of the trajectory as well as the length of the trajectory for the same resolution.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastEditorUserId="7" LastEditDate="2023-01-06T13:42:12.590" LastActivityDate="2023-01-07T12:48:50.503" Title="Effect of trajectory length and resolution on the Residence Time" Tags="|molecular-dynamics|correlation-functions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10199" PostTypeId="2" ParentId="10188" CreationDate="2023-01-06T17:58:39.757" Score="6" Body="&lt;p&gt;Depending on the particular ML potential and which features they implement, there are some relatively simple options:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;There is an interface to some piece of software that can compute normal modes. The simplest example for this would be ASE: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/vibrations/modes.html&quot; rel=&quot;noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/vibrations/modes.html&lt;/a&gt;&#xA;ASE calculates a finite difference approximation to the Hessian, so you just need to provide a Calculator that can evaluate the energy of a configuration.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Effort: &amp;lt; 50 lines of code for the calculator, if not provided by the ML potential package.&lt;/p&gt;&#xA;&lt;p&gt;There are other options, some of which have been mentioned in the comments, e.g. phonopy.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;If your ML potentials is written in some automatic differentiation framework (Jax, PyTorch, TF, etc.), then obtaining the Hessian is straightforward.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Effort: ~50 lines of code, if not provided by the ML potential package.&lt;/p&gt;&#xA;" OwnerUserId="406" LastActivityDate="2023-01-06T17:58:39.757" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10200" PostTypeId="2" ParentId="10198" CreationDate="2023-01-07T12:48:50.503" Score="4" Body="&lt;p&gt;The autocorrelation function (HBond or any other property) gives you the time that takes the system to forget that state. If the length of your analysis window in trajectory is less than the autocorrelation time, you will see that the results are dependent on the analysis window, because the system has not yet forgotten the previous state. The general rule of thumb in calculating autocorrelation time is to start with the window spanning atleast half of your trajectory and continue reducing it till your results remain constant.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-01-07T12:48:50.503" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10201" PostTypeId="5" CreationDate="2023-01-08T03:54:55.013" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.webmo.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.webmo.net/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.youtube.com/watch?v=s3aX0C6YQWs&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=s3aX0C6YQWs&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-08T03:54:55.013" LastActivityDate="2023-01-08T03:54:55.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10202" PostTypeId="4" CreationDate="2023-01-08T03:54:55.013" Score="0" Body="Questions about or related to WebMO." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-08T03:54:55.013" LastActivityDate="2023-01-08T03:54:55.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10203" PostTypeId="2" ParentId="10069" CreationDate="2023-01-08T15:39:26.080" Score="1" Body="&lt;p&gt;You are correct that the dimensions of the simulation box will fluctuate during the NPT run, because the system is trying to achieve correct density. If your NPT run has been performed for sufficient time (order of few nanoseconds), you must then be able to start from the final state to do an NVT run to ensure that your solvent molecules has sampled all possible configurations. The important point to keep in mind is that the convergence in NPT runs are very slow to achieve. You can refer to this &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2021/NR/D0NR08796C&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; to see how we did an NPT followed by an NVT run, and was able to reproduce experimental results.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-01-08T15:39:26.080" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10204" PostTypeId="2" ParentId="9943" CreationDate="2023-01-08T23:58:39.360" Score="5" Body="&lt;h1&gt;Python3 alternative&lt;/h1&gt;&#xA;&lt;p&gt;You can save this to a .py file. I wrote and tested it under Python 3.10.6:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;'''&#xA;Seeks a folder and all subfolders it contains for files named 'OUTCAR', extracting data given by regexp pattern. Saves&#xA;data to CSV spreadsheet. Assuming this program is saved to a file named outcar2csv.py, is invoked from the linux command&#xA;line like this:&#xA;&#xA;python3 outcar2csv.py data_folder_path yourfile&#xA;&#xA;Where data_folder_path is the path to the folder to be recursively searched for files named 'OUTCAR', and yourfile is&#xA;the name of the csv file to be created to save the extracted data. This file is created in the same place where&#xA;outcar2csv.py is located.&#xA;'''&#xA;&#xA;import os&#xA;import re&#xA;import mmap&#xA;import csv&#xA;import time&#xA;import sys&#xA;&#xA;def process_file(file, tags, pattern):&#xA;    '''&#xA;    Function seeks regexp pattern in given file, returning data from the last match found as a&#xA;    dictionary of tag : data.&#xA;    '''&#xA;    with open(file, 'r') as f:&#xA;        m = mmap.mmap(f.fileno(), 0, access = mmap.ACCESS_READ)&#xA;        last_match = pattern.findall(m)[-1]&#xA;        return {tag : data.decode() for tag, data in zip(tags, last_match)}&#xA;&#xA;def row_saver(destination_file, tags):&#xA;    '''&#xA;    Generator that saves data one row a time in a CSV spreadsheet, where each row is&#xA;    passed as a dictionary compatible with DictWriter object from Python csv module.&#xA;    '''&#xA;    with open(destination_file, 'w', newline = '') as csvfile:&#xA;        fieldnames = ['folder']&#xA;        fieldnames.extend(tags)&#xA;        writer = csv.DictWriter(csvfile, fieldnames=fieldnames, dialect='unix')&#xA;        writer.writeheader()&#xA;        while True:&#xA;            writer.writerow((yield))&#xA;&#xA;def main():&#xA;    top_folder, destination_file = sys.argv[1:]&#xA;    &#xA;    t0 = time.time()&#xA;&#xA;    pattern = re.compile(b&amp;quot;&amp;quot;&amp;quot;&#xA;    \s stress \s matrix \s after \s NEB \s project \s \(eV\)&#xA;    \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+)&#xA;    \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+)&#xA;    \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+) \s+ (-?\d+\.\d+)&#xA;    \s+ FORCES: \s max \s atom, \s RMS .*&#xA;    \s+ FORCE \s total \s and \s by \s dimension \s+ (-?\d+\.\d+) .*&#xA;    \s+ Stress \s total \s and \s by \s dimension \s+ (-?\d+\.\d+) .*&#xA;    &amp;quot;&amp;quot;&amp;quot;, re.VERBOSE)&#xA;&#xA;    tags = ['ii', 'ij', 'ik',&#xA;            'ji', 'jj', 'jk',&#xA;            'ki', 'kj', 'kk',&#xA;            'ForceTotal', 'StressTotal']&#xA;&#xA;    saver = row_saver(destination_file, tags)&#xA;    saver.send(None)&#xA;&#xA;    how_many = 0&#xA;    for dirpath, dirnames, filenames in os.walk(top_folder):&#xA;        for name in filenames:&#xA;            if name == 'OUTCAR':&#xA;                how_many += 1&#xA;                file = os.path.join(dirpath, name)&#xA;                row = {'folder': os.path.split(dirpath)[-1]}&#xA;                row.update(process_file(file, tags, pattern))&#xA;                saver.send(row)&#xA;&#xA;    print(how_many, 'files processed in', round(time.time() - t0, 3), 'seconds.')&#xA;&#xA;if __name__ == '__main__':&#xA;    main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I created some mock data by modification of the OUTCAR file given, for testing it. The script can be used as exemplified below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;user@machine:~&lt;span class=&quot;math-container&quot;&gt;$ ls Downloads/mattermodelling&#xA;mockdata  outcar2csv.py&#xA;user@machine:~$&lt;/span&gt; cd Downloads/mattermodelling&#xA;user@machine:~/Downloads/mattermodelling&lt;span class=&quot;math-container&quot;&gt;$ ls mockdata/&#xA;abc-000  abc-002  abc-004  abc-006  abc-008  abc-010  abc-012  abc-014  abc-016  abc-018&#xA;abc-001  abc-003  abc-005  abc-007  abc-009  abc-011  abc-013  abc-015  abc-017  abc-019&#xA;user@machine:~/Downloads/mattermodelling$&lt;/span&gt; python3 outcar2csv.py ~/Downloads/mattermodelling/mockdata/ spreadsheet.csv&#xA;20 files processed in 0.377 seconds.&#xA;user@machine:~/Downloads/mattermodelling&lt;span class=&quot;math-container&quot;&gt;$ ls&#xA;mockdata  outcar2csv.py  spreadsheet.csv&#xA;user@machine:~/Downloads/mattermodelling$&lt;/span&gt; cat spreadsheet.csv &#xA;&amp;quot;folder&amp;quot;,&amp;quot;ii&amp;quot;,&amp;quot;ij&amp;quot;,&amp;quot;ik&amp;quot;,&amp;quot;ji&amp;quot;,&amp;quot;jj&amp;quot;,&amp;quot;jk&amp;quot;,&amp;quot;ki&amp;quot;,&amp;quot;kj&amp;quot;,&amp;quot;kk&amp;quot;,&amp;quot;ForceTotal&amp;quot;,&amp;quot;StressTotal&amp;quot;&#xA;&amp;quot;abc-007&amp;quot;,&amp;quot;-862.37367&amp;quot;,&amp;quot;50.67924&amp;quot;,&amp;quot;2.91086&amp;quot;,&amp;quot;76.73190&amp;quot;,&amp;quot;-612.12661&amp;quot;,&amp;quot;-4.15208&amp;quot;,&amp;quot;7.69324&amp;quot;,&amp;quot;-6.63256&amp;quot;,&amp;quot;-243.32872&amp;quot;,&amp;quot;3.217959&amp;quot;,&amp;quot;318.071499&amp;quot;&#xA;&amp;quot;abc-008&amp;quot;,&amp;quot;-491.44190&amp;quot;,&amp;quot;89.30117&amp;quot;,&amp;quot;6.58274&amp;quot;,&amp;quot;19.24851&amp;quot;,&amp;quot;-816.34700&amp;quot;,&amp;quot;-6.96243&amp;quot;,&amp;quot;1.26080&amp;quot;,&amp;quot;-2.61234&amp;quot;,&amp;quot;-743.36987&amp;quot;,&amp;quot;5.135049&amp;quot;,&amp;quot;572.092093&amp;quot;&#xA;&amp;quot;abc-016&amp;quot;,&amp;quot;-387.31784&amp;quot;,&amp;quot;93.66937&amp;quot;,&amp;quot;6.30587&amp;quot;,&amp;quot;52.19730&amp;quot;,&amp;quot;-605.28808&amp;quot;,&amp;quot;-2.26975&amp;quot;,&amp;quot;3.81523&amp;quot;,&amp;quot;-4.72937&amp;quot;,&amp;quot;-675.31002&amp;quot;,&amp;quot;5.550989&amp;quot;,&amp;quot;057.487611&amp;quot;&#xA;&amp;quot;abc-014&amp;quot;,&amp;quot;-809.19049&amp;quot;,&amp;quot;19.72927&amp;quot;,&amp;quot;3.31798&amp;quot;,&amp;quot;06.07626&amp;quot;,&amp;quot;-868.67673&amp;quot;,&amp;quot;-9.00880&amp;quot;,&amp;quot;8.43166&amp;quot;,&amp;quot;-1.77182&amp;quot;,&amp;quot;-047.79519&amp;quot;,&amp;quot;9.173462&amp;quot;,&amp;quot;527.617069&amp;quot;&#xA;&amp;quot;abc-001&amp;quot;,&amp;quot;-101.10447&amp;quot;,&amp;quot;65.32618&amp;quot;,&amp;quot;0.96934&amp;quot;,&amp;quot;10.07195&amp;quot;,&amp;quot;-343.88294&amp;quot;,&amp;quot;-0.12684&amp;quot;,&amp;quot;1.07403&amp;quot;,&amp;quot;-6.83529&amp;quot;,&amp;quot;-223.11711&amp;quot;,&amp;quot;1.132396&amp;quot;,&amp;quot;726.216061&amp;quot;&#xA;&amp;quot;abc-005&amp;quot;,&amp;quot;-458.47658&amp;quot;,&amp;quot;91.04737&amp;quot;,&amp;quot;9.53896&amp;quot;,&amp;quot;51.30511&amp;quot;,&amp;quot;-523.23447&amp;quot;,&amp;quot;-1.07006&amp;quot;,&amp;quot;0.63547&amp;quot;,&amp;quot;-9.55906&amp;quot;,&amp;quot;-425.59611&amp;quot;,&amp;quot;0.189480&amp;quot;,&amp;quot;709.950391&amp;quot;&#xA;&amp;quot;abc-009&amp;quot;,&amp;quot;-009.53367&amp;quot;,&amp;quot;71.75084&amp;quot;,&amp;quot;4.66395&amp;quot;,&amp;quot;11.19572&amp;quot;,&amp;quot;-466.63143&amp;quot;,&amp;quot;-2.06748&amp;quot;,&amp;quot;8.65482&amp;quot;,&amp;quot;-2.91662&amp;quot;,&amp;quot;-765.26647&amp;quot;,&amp;quot;5.337915&amp;quot;,&amp;quot;378.528833&amp;quot;&#xA;&amp;quot;abc-011&amp;quot;,&amp;quot;-089.14072&amp;quot;,&amp;quot;33.43878&amp;quot;,&amp;quot;6.52117&amp;quot;,&amp;quot;05.15536&amp;quot;,&amp;quot;-329.99575&amp;quot;,&amp;quot;-9.70646&amp;quot;,&amp;quot;9.67780&amp;quot;,&amp;quot;-6.04529&amp;quot;,&amp;quot;-632.04250&amp;quot;,&amp;quot;0.986787&amp;quot;,&amp;quot;539.275902&amp;quot;&#xA;&amp;quot;abc-003&amp;quot;,&amp;quot;-226.22536&amp;quot;,&amp;quot;85.58539&amp;quot;,&amp;quot;5.83980&amp;quot;,&amp;quot;27.83603&amp;quot;,&amp;quot;-170.95152&amp;quot;,&amp;quot;-5.91629&amp;quot;,&amp;quot;6.88458&amp;quot;,&amp;quot;-9.64086&amp;quot;,&amp;quot;-432.43266&amp;quot;,&amp;quot;9.142282&amp;quot;,&amp;quot;639.281772&amp;quot;&#xA;&amp;quot;abc-004&amp;quot;,&amp;quot;-426.08425&amp;quot;,&amp;quot;31.80692&amp;quot;,&amp;quot;1.78031&amp;quot;,&amp;quot;24.45488&amp;quot;,&amp;quot;-018.67193&amp;quot;,&amp;quot;-7.11674&amp;quot;,&amp;quot;3.13194&amp;quot;,&amp;quot;-9.94171&amp;quot;,&amp;quot;-751.95429&amp;quot;,&amp;quot;7.610343&amp;quot;,&amp;quot;967.272264&amp;quot;&#xA;&amp;quot;abc-015&amp;quot;,&amp;quot;-676.72436&amp;quot;,&amp;quot;21.50989&amp;quot;,&amp;quot;1.36015&amp;quot;,&amp;quot;04.46427&amp;quot;,&amp;quot;-937.33530&amp;quot;,&amp;quot;-4.04833&amp;quot;,&amp;quot;8.32037&amp;quot;,&amp;quot;-1.46997&amp;quot;,&amp;quot;-212.69520&amp;quot;,&amp;quot;8.042924&amp;quot;,&amp;quot;133.224298&amp;quot;&#xA;&amp;quot;abc-019&amp;quot;,&amp;quot;-230.94008&amp;quot;,&amp;quot;12.00516&amp;quot;,&amp;quot;7.90733&amp;quot;,&amp;quot;29.98929&amp;quot;,&amp;quot;-777.89241&amp;quot;,&amp;quot;-0.80954&amp;quot;,&amp;quot;5.72769&amp;quot;,&amp;quot;-6.88261&amp;quot;,&amp;quot;-671.07960&amp;quot;,&amp;quot;6.707047&amp;quot;,&amp;quot;524.685876&amp;quot;&#xA;&amp;quot;abc-000&amp;quot;,&amp;quot;-688.85233&amp;quot;,&amp;quot;72.06209&amp;quot;,&amp;quot;0.19069&amp;quot;,&amp;quot;50.47013&amp;quot;,&amp;quot;-548.46840&amp;quot;,&amp;quot;-7.30824&amp;quot;,&amp;quot;5.13827&amp;quot;,&amp;quot;-0.69694&amp;quot;,&amp;quot;-401.06181&amp;quot;,&amp;quot;7.933544&amp;quot;,&amp;quot;001.298579&amp;quot;&#xA;&amp;quot;abc-018&amp;quot;,&amp;quot;-656.39700&amp;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OwnerUserId="243" LastActivityDate="2023-01-08T23:58:39.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10205" PostTypeId="1" CreationDate="2023-01-09T12:31:10.540" Score="6" ViewCount="55" Body="&lt;p&gt;Let us consider the usual expression for Diffusion processes and diffusion coefficients in the Eyring's theory:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$D=\lambda^2k = \lambda^2 \frac{k_BT}{h}\frac{\Omega_\ddagger}{\Omega}e^{-\frac{\epsilon_0}{k_BT}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would like to use this formulation to relate molecular partition functions, molecular structure, and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;. To do so for aqueous solutions, I need to take in account, while evaluating rotational and vibrational partition functions, that internal motion is closely related to hydrogen bonding.&lt;/p&gt;&#xA;&lt;p&gt;I think that the main contribution to the alteration of degrees of freedom for a molecule in diffusion processes is the translational one, but taking in account that, it is likely that the movement of a molecule determines an alteration in the intermolecular interactions (which in water are not negligible). For that reason, I would like to know if there is a way to take that into account while evaluating the partition functions.&lt;/p&gt;&#xA;" OwnerUserId="5562" LastEditorUserId="7" LastEditDate="2023-01-09T16:16:37.343" LastActivityDate="2023-01-11T16:26:23.417" Title="Is it possible to evaluate rotational and vibrational partition functions for diffusion in the Eyring Theory of Absolute Rates?" Tags="|molecular-modeling|condensed-matter|statistical-thermodynamics|intermolecular-forces|hydrogen-bonds|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-10T00:26:12.640" ContentLicense="CC BY-SA 4.0" />
  <row Id="10206" PostTypeId="1" AcceptedAnswerId="10264" CreationDate="2023-01-09T14:36:05.317" Score="4" ViewCount="712" Body="&lt;p&gt;I'm trying to optimise the excited state of benzene using ORCA 5.0.1 software.&lt;/p&gt;&#xA;&lt;p&gt;I've already optimised the &lt;span class=&quot;math-container&quot;&gt;$S_0$&lt;/span&gt; geometry with CAS-SCF[6,5] with the following input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! printmos printbasis 6-31g* opt moread&#xA;&#xA;%moinp &amp;quot;opt_rot.gbw&amp;quot;&#xA;&#xA;%casscf&#xA;    norb 5&#xA;    nel 6&#xA;    nroots 3&#xA;    mult 1&#xA;end&#xA;&#xA;%pal&#xA;    nprocs 64&#xA;end&#xA;&#xA;* xyzfile 0 1 benzene.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I recall a keyword as &lt;code&gt;iroot&lt;/code&gt; or something similar, but I don't recall how to use it and if it's the correct keyword to do what I want to do.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="4895" LastEditDate="2023-01-09T14:43:41.187" LastActivityDate="2023-01-20T05:38:35.893" Title="Optimise S1 geometry with CASSCF in ORCA" Tags="|orca|excited-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10207" PostTypeId="2" ParentId="10178" CreationDate="2023-01-10T07:59:03.787" Score="2" Body="&lt;p&gt;I installed GFortran 9.4 and re-ran the &lt;code&gt;compall&lt;/code&gt; file. The compilation succeeded but the &lt;code&gt;gamess.00.x&lt;/code&gt; file was missing and GAMESS couldn't run. Then I re-configured it &lt;em&gt;&lt;strong&gt;without&lt;/strong&gt;&lt;/em&gt; turning on the &lt;code&gt;XMVB&lt;/code&gt; option: This was now successful.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2023-01-12T03:33:23.267" LastActivityDate="2023-01-12T03:33:23.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10208" PostTypeId="1" AcceptedAnswerId="10224" CreationDate="2023-01-10T18:34:29.987" Score="5" ViewCount="269" Body="&lt;p&gt;I am thinking about working on computational electrochemistry for a limited subject and don't have a huge amount of time I can invest to explore different software. The &lt;a href=&quot;https://jdftx.org/&quot; rel=&quot;noreferrer&quot;&gt;JDFTx&lt;/a&gt; software seems like a perfect fit for me. My concern is that I don't see it mentioned much in the literature (or even on MSME!).&lt;/p&gt;&#xA;&lt;p&gt;I am seeking software recommendations for computational electrochemistry (whether for JDFTx or a different software), in the format of the answer in similar questions before, such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6175/5&quot;&gt;Package for computing properties of excited vibrational states&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1695/5&quot;&gt;What packages exist for building quantum Monte Carlo simulations of spin or Hubbard Hamiltonians?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/8695/5&quot;&gt;What software should I use for an MD study of a temperature-dependent crystallographic phase transition?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/414/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="5" LastEditDate="2023-01-10T20:11:55.750" LastActivityDate="2023-01-24T15:04:50.650" Title="What is a good software for computational electrochemistry?" Tags="|software|software-recommendations|one-topic-per-answer|jdftx|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10209" PostTypeId="5" CreationDate="2023-01-10T20:01:15.557" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;Website: &lt;a href=&quot;https://jdftx.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://jdftx.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Paper: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2352711017300559&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/S2352711017300559&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-10T20:01:15.557" LastActivityDate="2023-01-10T20:01:15.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10210" PostTypeId="4" CreationDate="2023-01-10T20:01:15.557" Score="0" Body="Questions about (or related to) the software JDFTx." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-10T20:01:15.557" LastActivityDate="2023-01-10T20:01:15.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10211" PostTypeId="1" AcceptedAnswerId="10212" CreationDate="2023-01-11T23:00:47.593" Score="3" ViewCount="256" Body="&lt;p&gt;The procedure I've been following to build OpenMolcas with an Intel Fortran compiler in the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1516/5&quot;&gt;Compute Canada&lt;/a&gt; environment is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python&#xA;pip install pyparsing&#xA;mkdir build_OpenMolcas&#xA;git clone https://gitlab.com/Molcas/OpenMolcas.git&#xA;cd OpenMolcas&#xA;git submodule update --init External/lapack&#xA;cd ../build_OpenMolcas&#xA;module load intel&#xA;which ifort&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/cvmfs/restricted.computecanada.ca/easybuild/software/2017/Core/ifort/2016.4.258/compilers_and_libraries_2016.4.258/linux/bin/intel64/ifort&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So then I use that path:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cmake ../OpenMolcas -D CMAKE_Fortran_COMPILER=/cvmfs/restricted.computecanada.ca/easybuild/software/2020/Core/intel/2020.1.217/compilers_and_libraries_2020.1.217/linux/bin/intel64/ifort&#xA;make -j12 # USE -j2 IF IT'S ON A PERSONAL COMPUTER !!!!&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This works perfectly (reaches &lt;code&gt;[100%]&lt;/code&gt; after about 15 minutes of real/wall time). However if I then compile with &lt;code&gt;BIGOT=ON&lt;/code&gt; (in the same folder, I just run the following two commands immediately after the previously run &lt;code&gt;make&lt;/code&gt; command finishes):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cmake ../OpenMolcas -D BIGOT=ON -D CMAKE_Fortran_COMPILER=/cvmfs/restricted.computecanada.ca/easybuild/software/2020/Core/intel/2020.1.217/compilers_and_libraries_2020.1.217/linux/bin/intel64/ifort&#xA;make -j12 # USE -j2 IF IT'S ON A PERSONAL COMPUTER !!!!&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get vague errors which did not tell me what to fix, other than to contact Intel support (which does not have an email address, nor a phone number, at least for people in the North American continent). For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/home/nike/OpenMolcas_HPQC_2022_12_30/src/ldf_ri_util/ldf_sortcoefficients.f(108): internal error: Please visit 'http://www.intel.com/software/products/support' for assistance.&#xA;         Call LDF_SortCanonical(AB,l_Scr,Work(ip_Scr),&#xA;^&#xA;[ Aborting due to internal error. ]&#xA;compilation aborted for /home/nike/OpenMolcas_HPQC_2022_12_30/src/ldf_ri_util/ldf_sortcoefficients.f (code 1)&#xA;make[2]: *** [CMakeFiles/ldf_ri_util/CMakeFiles/ldf_ri_util_obj.dir/build.make:1623: CMakeFiles/ldf_ri_util/CMakeFiles/ldf_ri_util_obj.dir/ldf_sortcoefficients.f.o] Error 1&#xA;make[2]: *** Waiting for unfinished jobs....&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/home/nike/OpenMolcas_HPQC_2022_12_30/src/integral_util/k2loop.f(383): internal error: Please visit 'http://www.intel.com/software/products/support' for assistance.&#xA;                     Call NewPK(CoorM(1,1),CoorM(1,2),&#xA;^&#xA;[ Aborting due to internal error. ]&#xA;compilation aborted for /home/nike/OpenMolcas_HPQC_2022_12_30/src/integral_util/k2loop.f (code 1)&#xA;make[2]: *** [CMakeFiles/integral_util/CMakeFiles/integral_util_obj.dir/build.make:1714: CMakeFiles/integral_util/CMakeFiles/integral_util_obj.dir/k2loop.f.o] Error 1&#xA;make[2]: *** Waiting for unfinished jobs....&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/home/nike/OpenMolcas_HPQC_2022_12_30/src/aniso_util/transHam.f(124): internal error: Please visit 'http://www.intel.com/software/products/support' for assistance.&#xA;          Call prMom('transHam:: magnetic moment, coordinate '//&#xA;^&#xA;[ Aborting due to internal error. ]&#xA;compilation aborted for /home/nike/OpenMolcas_HPQC_2022_12_30/src/aniso_util/transHam.f (code 1)&#xA;make[2]: *** [CMakeFiles/aniso_util/CMakeFiles/aniso_util_obj.dir/build.make:713: CMakeFiles/aniso_util/CMakeFiles/aniso_util_obj.dir/transHam.f.o] Error 1&#xA;make[2]: *** Waiting for unfinished jobs....&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I encountered the same problem with other Intel compiler versions, and all Intel compilers that I have available are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;intel/2020.1.217     intel/2021.2.0     intel/2022.1.0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do others get the same error when compiling with &lt;code&gt;BIGOT=ON&lt;/code&gt; and Intel Fortran compilers (following exactly the procedure above, except perhaps the &lt;code&gt;module python&lt;/code&gt; and &lt;code&gt;module intel&lt;/code&gt; parts which I had to run ion Compute Canada machines to make sure that Intel compilers and Python were available in the environment, and &lt;strong&gt;don't use &lt;code&gt;-j12&lt;/code&gt; if it's on a personal computer, I recommend &lt;code&gt;-j2&lt;/code&gt; which takes about 20 minutes on a 2016 laptop&lt;/strong&gt;)?&lt;/p&gt;&#xA;&lt;p&gt;I would like to know if this error occurs for other people (outside of the Compute Canada environment, for example).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-12T05:35:27.340" LastActivityDate="2023-01-12T05:35:27.340" Title="Is this &quot;internal error&quot; reproducible when compiling OpenMolcas on other Intel compilers?" Tags="|high-performance-computing|software-assistance|programming|fortran|open-molcas|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10212" PostTypeId="2" ParentId="10211" CreationDate="2023-01-12T00:35:27.220" Score="2" Body="&lt;p&gt;I successfully compiled (using &lt;code&gt;BIGOT=ON&lt;/code&gt;) without any issue.&lt;/p&gt;&#xA;&lt;p&gt;My configuration:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Python 3.9.1&#xA;Compilers: Intel® oneAPI HPC Toolkit v2023.0 (Fortran compiler: version 2021.8.0 Build 20221119_000000)&#xA;CPU: Intel(R) Core(TM) i7-4770 CPU @ 3.40GHz&#xA;OS: openSUSE Leap 15.2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2023-01-12T05:33:46.747" LastActivityDate="2023-01-12T05:33:46.747" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10214" PostTypeId="2" ParentId="10211" CreationDate="2023-01-12T05:24:44.793" Score="2" Body="&lt;h4&gt;After two full work days of struggling with this, I've solved the problem!&lt;/h4&gt;&#xA;&lt;p&gt;On the Compute Canada environment (Cedar specifically) and with the settings described in my question, the only three error messages that I was given, were the ones provided in the initial post.  These were compeltely unhelpful and referred to very stable parts of the code that I never modified. These errors were occurring in my own fork (I didn't check the upstream Master branch because I was working with my own fork as a developer, and since these error messages referred to parts of the software that had nothing to do with the parts that I changed, I didn't think my instructions above for compiling the upstream Master would result in any behavior different from what I observed in my fork). Because the upstream Master compiled perfectly in the environment described &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10212/5&quot;&gt;in the answer by Camps&lt;/a&gt;, I switched to that environment and got the following (much more helpful!) error when building my fork with &lt;code&gt;make -j4&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ 84%] Building Fortran object CMakeFiles/localisation/CMakeFiles/localisation_obj.dir/get_etwo_act.F90.o&#xA;/home/nike/OpenMolcas/src/level/level.f(394): error #6634: The shape matching rules of actual arguments and dummy arguments have been violated.   [MMLR]&#xA;     2  MMLR,CMM,NCMM,IVSR,IDSTT,RHOAB)&#xA;--------^&#xA;/home/nike/OpenMolcas/src/level/level.f(525): error #6634: The shape matching rules of actual arguments and dummy arguments have been violated.   [MMLR]&#xA;     2  PARM,MMLR,CMM,NCMM,IVSR,IDSTT,RHOAB)&#xA;-------------^&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This was followed by a bunch of compiler progress:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ 84%] Building Fortran object CMakeFiles/loprop/CMakeFiles/loprop_obj.dir/dynamic_properties.F90.o&#xA;compilation aborted for /home/nike/OpenMolcas/src/level/level.f (code 1)&#xA;make[2]: *** [CMakeFiles/level/CMakeFiles/level_obj.dir/build.make:80: CMakeFiles/level/CMakeFiles/level_obj.dir/level.f.o] Error 1&#xA;make[1]: *** [CMakeFiles/Makefile2:8087: CMakeFiles/level/CMakeFiles/level_obj.dir/all] Error 2&#xA;make[1]: *** Waiting for unfinished jobs....&#xA;[ 84%] Building Fortran object CMakeFiles/localisation/CMakeFiles/localisation_obj.dir/get_nat_lorb.F90.o&#xA;[ 84%] Building Fortran object CMakeFiles/loprop/CMakeFiles/loprop_obj.dir/fluctuating.F90.o&#xA;[ 84%] Building Fortran object CMakeFiles/localisation/CMakeFiles/localisation_obj.dir/primo_localisation.F90.o&#xA;[ 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CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/prjmmh.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/psoao0_h.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/request_mclr_run.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/rtocore.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/rtosph.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/schint_mck.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/screen_mck.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/smadna.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/sort_mck.F90.o&#xA;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/srogrd_mck.F90.o&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and then an &amp;quot;internal error&amp;quot; message like the ones I described in the intial post (again in a totally unrelated part of the software, and even in a place unrelated to the three places in which this error was occuring before):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ 85%] Building Fortran object CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/srohss.F90.o&#xA;/home/nike/OpenMolcas/src/mckinley/srogrd_mck.F90(174): internal error: Please visit 'http://www.intel.com/software/products/support' for assistance.&#xA;        call SmAdNa(Array(ipFin),nt,rFinal,mop,loper,JndGrd,iuvwx,Indx,idcar,One,tr)&#xA;^&#xA;[ Aborting due to internal error. ]&#xA;compilation aborted for /home/nike/OpenMolcas/src/mckinley/srogrd_mck.F90 (code 1)&#xA;make[2]: *** [CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/build.make:1263: CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/srogrd_mck.F90.o] Error 1&#xA;make[2]: *** Waiting for unfinished jobs....&#xA;make[1]: *** [CMakeFiles/Makefile2:8792: CMakeFiles/mckinley/CMakeFiles/mckinley_obj.dir/all] Error 2&#xA;make: *** [Makefile:158: all] Error 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This means that the &lt;code&gt;integral error&lt;/code&gt; message can basically happen anywhere in the code, due to a totally unrelated warning (or &lt;code&gt;error&lt;/code&gt; in the case of the MOLCAS &lt;code&gt;BIGOT=ON&lt;/code&gt; option which uses &lt;code&gt;-Wall&lt;/code&gt; to turn &lt;code&gt;all&lt;/code&gt; warnings into errors) elsewhere. &lt;strong&gt;For some reason the warning/error that triggered these &amp;quot;internal error&amp;quot; messges, didn't show up in the Compute Canada environment,&lt;/strong&gt; but thankfully did in the environment described by Camps.&lt;/p&gt;&#xA;&lt;p&gt;By doing literally nothing else but changing &lt;code&gt;MMLR&lt;/code&gt; to &lt;code&gt;MMLR(3)&lt;/code&gt; in both suggested locations of &lt;code&gt;level.f&lt;/code&gt; and rerunning &lt;code&gt;make -j4&lt;/code&gt;, the compilation completed to 100% with no warnings/errors (the &amp;quot;internal errors&amp;quot; in other parts of the software were &amp;quot;fixed&amp;quot; by fixing this unrelated file).&lt;/p&gt;&#xA;&lt;h4&gt;Why did I change &lt;code&gt;MMLR&lt;/code&gt; to &lt;code&gt;MMLR(3)&lt;/code&gt;?&lt;/h4&gt;&#xA;&lt;p&gt;It's strange, because right next to &lt;code&gt;MMLR&lt;/code&gt; were &lt;code&gt;PARM&lt;/code&gt; and &lt;code&gt;CMM&lt;/code&gt; which should have sizes &lt;code&gt;4&lt;/code&gt; and &lt;code&gt;3&lt;/code&gt; respectively, and the compiler never complained about those (neither before changing &lt;code&gt;MMLR&lt;/code&gt; to &lt;code&gt;MMLR(3)&lt;/code&gt;, nor after).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://community.intel.com/t5/Intel-Fortran-Compiler/error-6634-the-shape-matching-rules-of-actual-arguments-and/m-p/1172775/highlight/true#M146434&quot; rel=&quot;nofollow noreferrer&quot;&gt;This thread on Intel Communities&lt;/a&gt; shows that &lt;code&gt;NASTRAN&lt;/code&gt; a finite-element  code developed by several companies for NASA starting in the 1960s, had the same error, and that the size of the array should be specified in the &lt;code&gt;CALL&lt;/code&gt; statement (i.e. the &amp;quot;actual&amp;quot; argument) even if it's not specified in the subroutine's first line (i.e. the &amp;quot;dummy&amp;quot; arguments).&lt;/p&gt;&#xA;&lt;p&gt;Before looking at the above Intel Community thread, I was unsuccessful in getting a solution from &lt;a href=&quot;https://stackoverflow.com/q/61487239/1271772&quot;&gt;this&lt;/a&gt; StackOverflow thread which had the same &lt;code&gt;shape matching rules&lt;/code&gt; error message, but I'm putting the link here in case it's useful to others. I had also opened tabs with &lt;a href=&quot;http://theory.cm.utexas.edu/forum/viewtopic.php?t=938&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://lists.mcs.anl.gov/mailman/htdig/petsc-users/2018-May/035324.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;http://feap.berkeley.edu/forum/index.php?topic=241.0&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=comp-fortran-90;5d4dcc2e.04&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://fortran53.rssing.com/chan-7461311/all_p134.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://www.myroms.org/forum/viewtopic.php?t=5339&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://www.tek-tips.com/viewthread.cfm?qid=1425919&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://community.intel.com/t5/Intel-Fortran-Compiler/The-shape-matching-rules-of-actual-arguments-and-dummy-arguments/td-p/764056&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; page, but that first Intel Community thread came up first, either by luck or because of Google watching precisely what I've been doing on my computer in the last two days, so I didn't need the other pages (but again I'm providing them here in case they're helpful to others with similar errors in the future).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-01-12T05:24:44.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10215" PostTypeId="1" AcceptedAnswerId="10263" CreationDate="2023-01-11T15:53:40.920" Score="6" ViewCount="171" Body="&lt;p&gt;I looked in the orca manual but didn't find anything, but in the case of having a molecule adsorbed in a cluster, is it possible to perform the frequency calculation only on the molecule and not on the entire system?&lt;/p&gt;&#xA;&lt;p&gt;Many Thanks&lt;/p&gt;&#xA;" OwnerUserId="6576" OwnerDisplayName="Mateus Augusto" LastEditorUserId="1151" LastEditDate="2023-03-08T08:13:17.513" LastActivityDate="2023-03-08T08:13:17.513" Title="Is it possible to restrict the calculation of frequencies in ORCA program?" Tags="|computational-chemistry|orca|vibrations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10216" PostTypeId="1" CreationDate="2023-01-12T09:27:00.963" Score="4" ViewCount="451" Body="&lt;p&gt;I am working in my final undergraduate Project about predicting belite (Ca2Si04) polymorphs using DFT calculations and I need to justify why my SIESTA run is looking for minimum enthalpy and not free energy. I have a vague  idea that is because  DFT is perfomed using T=0K but I cannot find any article that supports it. I need to use references, so please if you could provide it I'd grateful.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6544" LastActivityDate="2023-01-16T06:21:53.823" Title="How can I justify that in DFT entalphy is Gibbs free energy?" Tags="|density-functional-theory|siesta|free-energy|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10218" PostTypeId="1" CreationDate="2023-01-12T18:15:38.030" Score="2" ViewCount="55" Body="&lt;p&gt;&lt;a href=&quot;https://www.biostars.org/p/9550997/&quot; rel=&quot;nofollow noreferrer&quot;&gt;I asked this at Biostars&lt;/a&gt; but the post seems to have been deleted there.&lt;/p&gt;&#xA;&lt;p&gt;My professor told me to implement &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp071097f&quot; rel=&quot;nofollow noreferrer&quot;&gt;MARTINI ForceField-based coarse-grained model&lt;/a&gt; to simulate &lt;strong&gt;2GB1A&lt;/strong&gt; protein-folding using Python-3.5 and to use &lt;a href=&quot;https://github.com/psipred/psipred&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;*.ss2&lt;/code&gt;&lt;/a&gt; and &lt;code&gt;*.fasta_ss&lt;/code&gt; files as inputs.&lt;/p&gt;&#xA;&lt;p&gt;Thus far, I have used manual coordinates for protein simulation. I never even used PDB files as inputs. So, I have no idea how the mentioned file formats can be used for simulation.&lt;/p&gt;&#xA;&lt;p&gt;Do I need to extract point coordinates from &lt;code&gt;*.ss2&lt;/code&gt; and &lt;code&gt;*.fasta_ss&lt;/code&gt; files? If so, how?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://webdocs.cs.ualberta.ca/%7Eghlin/lingroup/Software/PSAtip/format.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;This is the link of PSRIRED VFORMAT&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The following is the content of &lt;code&gt;*.ss2&lt;/code&gt; file of &lt;strong&gt;2GB1A&lt;/strong&gt; protein:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# PSIPRED VFORMAT&#xA;&#xA;   1 M C   1.000  0.000  0.000&#xA;   2 T E   0.000  0.000  1.000&#xA;   3 Y E   0.000  0.000  1.000&#xA;   4 K E   0.000  0.000  1.000&#xA;   5 L E   0.000  0.000  1.000&#xA;   6 I E   0.000  0.000  1.000&#xA;   7 L E   0.000  0.000  1.000&#xA;   8 N C   1.000  0.000  0.000&#xA;   9 G C   1.000  0.000  0.000&#xA;  10 K C   1.000  0.000  0.000&#xA;  11 T C   1.000  0.000  0.000&#xA;  12 L C   1.000  0.000  0.000&#xA;  13 K C   1.000  0.000  0.000&#xA;  14 G E   0.000  0.000  1.000&#xA;  15 E E   0.000  0.000  1.000&#xA;  16 T E   0.000  0.000  1.000&#xA;  17 T E   0.000  0.000  1.000&#xA;  18 T E   0.000  0.000  1.000&#xA;  19 E E   0.000  0.000  1.000&#xA;  20 A C   1.000  0.000  0.000&#xA;  21 V C   1.000  0.000  0.000&#xA;  22 D C   1.000  0.000  0.000&#xA;  23 A H   0.000  1.000  0.000&#xA;  24 A H   0.000  1.000  0.000&#xA;  25 T H   0.000  1.000  0.000&#xA;  26 A H   0.000  1.000  0.000&#xA;  27 E H   0.000  1.000  0.000&#xA;  28 K H   0.000  1.000  0.000&#xA;  29 V H   0.000  1.000  0.000&#xA;  30 F H   0.000  1.000  0.000&#xA;  31 K H   0.000  1.000  0.000&#xA;  32 Q H   0.000  1.000  0.000&#xA;  33 Y H   0.000  1.000  0.000&#xA;  34 A H   0.000  1.000  0.000&#xA;  35 N H   0.000  1.000  0.000&#xA;  36 D C   1.000  0.000  0.000&#xA;  37 N C   1.000  0.000  0.000&#xA;  38 G C   1.000  0.000  0.000&#xA;  39 V C   1.000  0.000  0.000&#xA;  40 D C   1.000  0.000  0.000&#xA;  41 G C   1.000  0.000  0.000&#xA;  42 E E   0.000  0.000  1.000&#xA;  43 W E   0.000  0.000  1.000&#xA;  44 T E   0.000  0.000  1.000&#xA;  45 Y E   0.000  0.000  1.000&#xA;  46 D E   0.000  0.000  1.000&#xA;  47 D C   1.000  0.000  0.000&#xA;  48 A C   1.000  0.000  0.000&#xA;  49 T C   1.000  0.000  0.000&#xA;  50 K C   1.000  0.000  0.000&#xA;  51 T E   0.000  0.000  1.000&#xA;  52 F E   0.000  0.000  1.000&#xA;  53 T E   0.000  0.000  1.000&#xA;  54 V E   0.000  0.000  1.000&#xA;  55 T E   0.000  0.000  1.000&#xA;  56 E C   1.000  0.000  0.000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Its corresponding &lt;code&gt;fasta&lt;/code&gt; file is as follows (I haven't found a &lt;code&gt;fasta_ss&lt;/code&gt; example):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;2gb1A&#xA;MTYKLILNGKTLKGETTTEAVDAATAEKVFKQYANDNGVDGEWTYDDATKTFTVTE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-01-13T01:47:40.160" LastActivityDate="2023-01-13T18:38:31.707" Title="How can I use ss2 or FASTA files as inputs for protein-folding simulation using the MARTINI course-grained model?" Tags="|proteins|forcefields|structural-biology|protein-folding|martini|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10220" PostTypeId="1" CreationDate="2023-01-13T04:07:15.113" Score="2" ViewCount="51" Body="&lt;p&gt;could you please share a handy way (some concise and explicit step by step procedures) to generate semicore pseudopotentials - for novice learners?&lt;/p&gt;&#xA;&lt;p&gt;This question, how to generate semicore pseudopotential, was posted earlier (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9575/need-help-about-how-i-can-get-generate-semicore-pseudopotentials-to-be-used-in-q&quot;&gt;Link&lt;/a&gt;), and the comments/answers of that question has some hints to generate semicore pseudopotential. Still I did not get a suitable/easy step by step procedure to generate semicore pseudopotential of my own choice (i.e. how many electrons will be active/valence electrons, if there will be nonlinear core corrections or not, how to include higher angular momentum channel, etc).&lt;/p&gt;&#xA;&lt;p&gt;Any powerpoint slides or youtube video or PDF file with screenshots of steps can be of great help.&lt;/p&gt;&#xA;&lt;p&gt;[In addition, it would be great to discuss the 'make.inc' file to generate semicore pseudopotential -if possible]&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2023-01-15T07:53:57.657" Title="Could you please share a step by step to generate semicore pseudopotential? (for QUANTUM ESPRESSO)" Tags="|quantum-espresso|pseudopotentials|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10221" PostTypeId="1" CreationDate="2023-01-13T17:50:23.460" Score="1" ViewCount="56" Body="&lt;p&gt;BCC Na is the most stable structure of Na, and the most stable structure gives the pressure around 0 kbar.&#xA;But a paper named &amp;quot;&lt;em&gt;Structure stability in the simple element sodium under pressure&lt;/em&gt;&amp;quot;  says the lattice constant for bcc Na is 4.2908 Angstrom for ambient conditions.&#xA;When I calculate with lattice constant 4.2908 Angstrom and NC LDA type pseudopotential, which is  &amp;quot;&lt;a href=&quot;http://pseudopotentials.quantum-espresso.org/upf_files/Na.pw-mt_fhi.UPF&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://pseudopotentials.quantum-espresso.org/upf_files/Na.pw-mt_fhi.UPF&lt;/a&gt;&amp;quot;, I get pressure 121.71 kbar.&lt;/p&gt;&#xA;&lt;p&gt;I am attaching my input files below.&#xA;It will be a great help if anyone suggests to me the appropriate pseudopotential and atomic positions for BCC Na with 0 kbar pressure by using the lattice constant 4.2908 Angstrom?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  &amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  etot_conv_thr =   2.0000000000d-05&#xA;  forc_conv_thr =   1.0000000000d-04&#xA;  outdir = './out/'&#xA;  prefix = 'aiida'&#xA;  pseudo_dir = '.'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'low'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss =   1.4699723600d-02&#xA;  ecutrho =  700&#xA;  ecutwfc =  70&#xA;  celldm=8.108453484&#xA;  ibrav = 3&#xA;  nat = 2&#xA;  nosym = .false.&#xA;  ntyp = 1&#xA;  occupations = 'smearing'&#xA;  smearing = 'gaussian'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   4.0000000000d-10&#xA;  electron_maxstep = 80&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;ATOMIC_SPECIES&#xA;Na     22.98977 Na.pw-mt_fhi.UPF&#xA;ATOMIC_POSITIONS (crystal)&#xA;Na       0.000000000  -0.000000000   0.000000000&#xA;Na       0.500000000   0.500000000   0.5000000000 &#xA;K_POINTS automatic&#xA;9 9 9 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5968" LastEditorUserId="5" LastEditDate="2023-01-13T19:50:05.820" LastActivityDate="2023-01-13T19:50:05.820" Title="What are the appropriate lattice constant , pseudopotential and atomic positions for BCC Na with 0 kbar pressure? (for Quantum ESPRESSO)" Tags="|quantum-espresso|pseudopotentials|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-03T18:29:25.943" ContentLicense="CC BY-SA 4.0" />
  <row Id="10222" PostTypeId="1" AcceptedAnswerId="10229" CreationDate="2023-01-13T18:28:19.357" Score="4" ViewCount="95" Body="&lt;p&gt;Reading the transiesta manual, I understand that it would be sufficient to optimize the structure within siesta and then use the result for a transiesta run.&lt;/p&gt;&#xA;&lt;p&gt;However, I have also read that it would be necessary to re-run the optimization with transiesta if the forces obtained from the calculation at zero bias are particularly large. On the other hand, the forces shouldn't be trusted near the electrodes. So, what could be a threshold for forces in a transiesta run? Should one consider, for the latter, only the force on atoms far enough from the electrodes?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-01-16T08:24:03.240" Title="Transiesta geometry optimization" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10223" PostTypeId="2" ParentId="10218" CreationDate="2023-01-13T18:38:31.707" Score="2" Body="&lt;p&gt;In order to run Molecular Dynamics simulations (independent of the force-field and type of simulation) you need a file with the structure of your protein: type of atoms, residues and (X, Y, Z) coordinates.&lt;/p&gt;&#xA;&lt;p&gt;Normally, the starting file with all this information is in &lt;a href=&quot;https://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/introduction&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDB format&lt;/a&gt; like &lt;a href=&quot;https://files.rcsb.org/view/6LU7.pdb&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; example.&lt;/p&gt;&#xA;&lt;p&gt;You can search the &lt;a href=&quot;https://www.rcsb.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RCSB Protein Data Base&lt;/a&gt; and, if you are lucky, found the structure of your protein. There you will get structures determined by X-ray crystallography, NMR and CryoEM. If you aren't lucky, then you need to use the sequence (in  FASTA format, for example) and generate its structure using homology modeling. Right now, the &lt;a href=&quot;https://www.rcsb.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RCSB Protein Data Base&lt;/a&gt; also has available Computed Structure Models generated by &lt;a href=&quot;https://alphafold.ebi.ac.uk/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AlphaFoldDB&lt;/a&gt; and &lt;a href=&quot;https://www.ipd.uw.edu/2021/07/rosettafold-accurate-protein-structure-prediction-accessible-to-all/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RoseTTAFold&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Once you have the PDB file, you can go to online services like &lt;a href=&quot;https://charmm-gui.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CHARMM-GUI&lt;/a&gt; and generate the inputs for running Molecular Dynamic simulations for both all-atom and coarse-grained molecular dynamic.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-13T18:38:31.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10224" PostTypeId="2" ParentId="10208" CreationDate="2023-01-13T20:22:35.393" Score="9" Body="&lt;p&gt;I'm a computational electrochemistry researcher and I collaborate with the developers of JDFTx and use it as my main driver. The primary reason to use JDFTx is its built-in support for grand canonical models, which more realistically model the electrode at a fixed potential. My group now mostly does grand canonical calculations instead of using the Computational Hydrogen Electrode on calculations at the potential of zero charge. We have observed some interesting potential dependent trends that would be missed by the Computational Hydrogen Electrode, such as potential dependent surface rearrangement.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Advantages&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Open source with a solid tutorial in the documentation&lt;/li&gt;&#xA;&lt;li&gt;Built-in grand canonical models that are easy to use&lt;/li&gt;&#xA;&lt;li&gt;Strong solvent models: &lt;a href=&quot;https://doi.org/10.1063/1.4907731&quot; rel=&quot;nofollow noreferrer&quot;&gt;solvent paper&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Good support from the development team&lt;/li&gt;&#xA;&lt;li&gt;GPU build for blazing fast calculations&lt;/li&gt;&#xA;&lt;li&gt;Atomic Simulation Environment wrapper on &lt;a href=&quot;https://github.com/shankar1729/jdftx/tree/master/jdftx/scripts/ase&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disadvantages&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Not as fast using CPU as other periodic codes like VASP&lt;/li&gt;&#xA;&lt;li&gt;Doesn't have a large community of users&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="6549" LastEditorUserId="6549" LastEditDate="2023-01-24T15:04:50.650" LastActivityDate="2023-01-24T15:04:50.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10225" PostTypeId="1" CreationDate="2023-01-15T09:10:35.943" Score="7" ViewCount="351" Body="&lt;p&gt;There are two files named ‘OUTCAR’ and ‘POSCAR’.&lt;/p&gt;&#xA;&lt;p&gt;The ‘OUTCAR’ file consists of many lines including the following (Screenshot 1):&lt;/p&gt;&#xA;&lt;p&gt;(It is noted that, there are data for 48 ions in that OUTCAR file, though the screenshot-1 shows here a portion till 3rd ion)&lt;/p&gt;&#xA;&lt;p&gt;And the ‘POSCAR’ file consists of many lines including the following (Screenshot 2):&lt;/p&gt;&#xA;&lt;p&gt;(It is noted that, the screenshot-2 shows a portion of data. But we will be interested to consider up to 48th row of data, after the 'Direct' heading)&lt;/p&gt;&#xA;&lt;p&gt;What I need is, I need to extract and multiply data from the OUTCAR and POSCAR files in the following way (Screenshot 3):&lt;/p&gt;&#xA;&lt;p&gt;That is, the result will be,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;result = (1_22 * X_13) + (2_22 * X_23) + (3_22 * X_33) + . . . .+ (48_22 * X_483)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For example, according to the screenshot, the result will be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;result  = (1.01531*0.2396715232098912) + (1.01531*0.2396715232098912) + (1.01531*0.2603284767901088) + ..... till 48th&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Therefore, I need to get the calculation result for 48 ions, according to the screenshot-3.&lt;/p&gt;&#xA;&lt;p&gt;Then I need to print and save the &amp;quot;result&amp;quot; and the &amp;quot;list of the individual product&amp;quot; in an excel/text file.&lt;/p&gt;&#xA;&lt;p&gt;I am requesting how to do this with the help of Python? Any kind of help is greatly appreciated.&#xA;&lt;strong&gt;(Screenshot 1)&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/3Q1Sh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3Q1Sh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(Screenshot 2)&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/yD9OY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yD9OY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(Screenshot 3)&lt;/strong&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ZCXTd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZCXTd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For convenience, I have uploaded the OUTCAR and POSCAR files in this drive link: &lt;a href=&quot;https://ucmerced.box.com/s/awnjbp6f4bioelhl2q55u4o3m5r7rbuf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Downloadable Link&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(Optional: Somehow I could not upload it in the mattermodeling git link, it will be highly appreciated if the two files can be taken to there - in needed)&lt;/p&gt;&#xA;" OwnerUserId="6486" LastEditorUserId="6486" LastEditDate="2023-01-17T11:19:40.660" LastActivityDate="2023-01-20T17:05:57.787" Title="Python to extract data from two files, and then do a calculation with those data" Tags="|python|programming|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10227" PostTypeId="1" CreationDate="2023-01-15T13:58:07.903" Score="2" ViewCount="93" Body="&lt;p&gt;What is the procedure after using a diffraction grating (device used to see the spectrum) using python? We would see the entire electromagnetic spectrum emitted by an object but what then? how do I measure the wavelength of the light using Python?&lt;/p&gt;&#xA;&lt;p&gt;I am expecting the diffraction grating to project the entire spectrum of the an object (probably through an magnifying glass) to an camera, then I want the data from the camera to be analyzed, then the script to show the wavelength of the light emitted&lt;/p&gt;&#xA;&lt;p&gt;I suspect that OpenCV might be used&lt;/p&gt;&#xA;" OwnerDisplayName="user6553" LastEditorDisplayName="user6553" LastEditDate="2023-01-15T16:25:44.777" LastActivityDate="2023-01-15T16:25:44.777" Title="How do I get the wavelength of light from a diffraction experiment using Python?" Tags="|python|quantum-mechanics|experimental|soft-question|diffraction|" AnswerCount="0" CommentCount="4" ClosedDate="2023-01-17T17:45:20.960" ContentLicense="CC BY-SA 4.0" />
  <row Id="10228" PostTypeId="2" ParentId="10216" CreationDate="2023-01-16T05:01:36.847" Score="5" Body="&lt;p&gt;DFT is most commonly used to calculate minimized energy structures. This is likely what your project is on, unless you're doing ab initio molecular dynamics, or excited state DFT (e.g. time-dependent DFT) calculation. In this case, your calculations are equivalent to finding the lowest enthalpy ground state minus the vibrational zero point energy. Enthalpy &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; will be equal to the total energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; unless you're also applying some external stress (i.e. pressure), which would correct the enthalpy by a &lt;span class=&quot;math-container&quot;&gt;$PV$&lt;/span&gt; term.&lt;/p&gt;&#xA;&lt;p&gt;Since your calculations are at &lt;span class=&quot;math-container&quot;&gt;$T =0$&lt;/span&gt; (equations of motion are not even employed), the energy (or enthalpy) minimization is also equal to the Gibbs free energy &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to determine which polymorph is most stable at finite temperature and pressure (lowest &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt;), you need a more sophisticated calculation than straightforward DFT structure minimization. A common method is to correct the minimized energy for vibrational energy based on a harmonic or quasiharmonic vibrational calculation.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2023-01-16T06:21:53.823" LastActivityDate="2023-01-16T06:21:53.823" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10229" PostTypeId="2" ParentId="10222" CreationDate="2023-01-16T08:24:03.240" Score="4" Body="&lt;p&gt;Generally it would be sufficient to optimize the geometry in siesta since that geometry will likely be the same geometry as for V=0. The reason should be straightforwardly understood if one thinks about the requirements of the electrodes, &lt;em&gt;hint&lt;/em&gt; the electrodes needs to behave like a bulk electrode in the device region.&lt;/p&gt;&#xA;&lt;p&gt;Generally one should constrain the atoms close to the electrodes since various options in transiesta invalidates the force calculations on the atoms closest to the electrodes. This shouldn't be confused with actual physical properties (unless one does not have true bulk properties of the electrode region in the device).&lt;/p&gt;&#xA;&lt;p&gt;IFF you experience small forces in the Siesta run and relatively large forces in the V=0 calculation far from the electrode interface, then my first guess would be that your electrodes in the device region does &lt;em&gt;not&lt;/em&gt; behave like bulk electrodes, and hence your system is erroneously setup.&lt;/p&gt;&#xA;&lt;p&gt;Like all things, giving a number for tolerance is very difficult as &lt;em&gt;it depends on the chemistry etc.&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-01-16T08:24:03.240" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10230" PostTypeId="1" AcceptedAnswerId="10309" CreationDate="2023-01-16T08:34:06.387" Score="7" ViewCount="361" Body="&lt;p&gt;This is a general question regarding the practices of doing optical calculations and the role of the ionic contribution to the dielectric function (with heavy reference to VASP).&lt;/p&gt;&#xA;&lt;p&gt;Based on VASP's tutorial on dielectric properties&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Dielectric_properties_of_SiC&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dielectric properties of SiC&lt;/a&gt; and&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/Ionic_contributions_to_the_frequency_dependent_dielectric_function_of_NaCl&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ionic contributions to the frequency dependent dielectric function of NaCl&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;the ionic contribution to the dielectric function requires the force constants matrix and phonon eigenvalues obtained via density functional perturbation theory (DFPT) or finite differences. I infer from this that the structure has to be well-relaxed (zero forces).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does this mean that we can't use a different functional for the frequency-dependent dielectric function calculation (both electronic and ionic) than the one used to relax the structure?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For context, I would typically use PBE to do structure relaxations and compute band structures with a hybrid. I was expecting to be able to do something similar - PBE structure relaxations followed by using a hybrid for the dielectric function (electronic + ionic contributions), but this seems wrong if the ionic contribution is computed with the hybrid functional, which would likely yield non-zero forces for the structure.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="6131" LastEditorUserId="5" LastEditDate="2023-01-26T20:36:35.103" LastActivityDate="2023-01-27T21:26:10.930" Title="Do I have to use the same functional for dielectric function calculations, as the one used for relaxing the structure?" Tags="|vasp|geometry-optimization|structure|functional|dielectric-constants|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10231" PostTypeId="1" AcceptedAnswerId="10280" CreationDate="2023-01-16T14:35:18.677" Score="3" ViewCount="104" Body="&lt;p&gt;I was given a file containing computed data for the 3D electron density. I'm supposed to use gradient method to find maxima of electron density. I do not understand how these values represent the electron density, there seems to be 5 columns of data, however since there's 23436 values, these can't be evenly separated into 5 categories. Does anyone understand how to interpret these values so that I can use gradient method?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Total SCF Density                          R   N=       23436&#xA;  7.53710096E-01  1.30487351E+00  2.27925606E+00  4.37164331E-01  7.71062120E-01&#xA;  2.69049242E-01 -1.74000356E-01 -4.01322199E-01 -1.88432410E-01  6.03254492E-01&#xA;  4.84199909E-02  1.08019789E-01  5.27932031E-02 -1.72109352E-01  2.52445599E-01&#xA;  2.25106740E-02  5.04502363E-02  2.54241272E-02 -1.02459587E-01  1.39174445E-01&#xA;  1.16611165E-01 -2.77410219E-20 -7.03378933E-20 -7.31963902E-22 -4.71788885E-20&#xA; -6.66786760E-20  7.17294149E-20  1.21517942E-01 -6.69727513E-20 -1.69810696E-19&#xA; -1.76711718E-21 -1.13899913E-19 -1.60976564E-19  1.73170126E-19 -1.66978126E-31&#xA;  1.21517942E-01 -3.62436215E-03 -9.18963977E-03 -9.56310215E-05 -6.16391777E-03&#xA; -8.71156334E-03  9.37144194E-03 -2.93728981E-20 -7.09124489E-20  1.17680375E-01&#xA; -1.21527449E-19 -3.03747039E-19 -1.17531552E-20 -1.55769158E-19 -1.81883741E-19&#xA;  3.10102529E-19  4.31184147E-01 -7.37631169E-31 -1.27023864E-19  1.53322732E+00&#xA; -2.93393216E-19 -7.33310221E-19 -2.83746268E-20 -3.76060014E-19 -4.39106193E-19&#xA;  7.48653730E-19 -7.34549681E-31  4.31184147E-01 -3.06662735E-19 -3.11384353E-30&#xA;  1.53322732E+00 -1.58775509E-02 -3.96845247E-02 -1.53554873E-03 -2.03512272E-02&#xA; -2.37630952E-02  4.05148690E-02 -1.27023864E-19 -3.06662735E-19  4.14588490E-01&#xA; -5.42788920E-19 -1.31040837E-18  1.46231200E+00  1.25950982E-20  2.19965268E-20&#xA;  1.52953449E-20 -8.94555687E-20 -1.91482225E-19  2.02663774E-21  1.48080107E-01&#xA;  5.28667770E-31  4.08107247E-20  5.18084033E-01  1.68095166E-30  1.47410440E-19&#xA;  1.97330546E-01  3.04072568E-20  5.31043132E-20  3.69262291E-20 -2.15964847E-19&#xA; -4.62278986E-19  4.89273631E-21  5.27897398E-31  1.48080107E-01  9.85258051E-20&#xA;  1.68095166E-30  5.18084033E-01  3.55880282E-19  1.60526261E-30  1.97330546E-01&#xA;  1.64554850E-03  2.87384435E-03  1.99833551E-03 -1.16873624E-02 -2.50171364E-02&#xA;  2.64780048E-04  4.08107247E-20  9.85258051E-20  1.53412025E-01  1.47410440E-19&#xA;  3.55880282E-19  5.37343195E-01  6.66518682E-20  1.60911844E-19  2.06038607E-01&#xA; -1.78973045E-19 -3.86758003E-19 -2.03116522E-19  7.14546403E-19 -6.02909045E-19&#xA; -4.15079431E-19 -2.06122510E-02 -1.22385626E-30  1.59700595E-19 -8.42952817E-02&#xA; -3.50894806E-30  5.98630385E-19 -3.32835582E-03 -2.67936578E-30  1.15656106E-19&#xA;  1.49533724E-01 -4.32079152E-19 -9.33716416E-19 -4.90366663E-19  1.72506762E-18&#xA; -1.45555119E-18 -1.00209039E-18 -1.22375996E-30 -2.06122510E-02  3.85551343E-19&#xA; -3.50817769E-30 -8.42952817E-02  1.44522159E-18 -2.67938985E-30 -3.32835582E-03&#xA;  2.79218541E-19 -3.91108223E-29  1.49533724E-01 -2.33828131E-02 -5.05299002E-02&#xA; -2.65371564E-02  9.33554267E-02 -7.87700154E-02 -5.42300923E-02  1.59700595E-19&#xA;  3.85551343E-19  2.52618212E-04  5.98630385E-19  1.44522159E-18 -6.08427289E-03&#xA;  1.15656106E-19  2.79218541E-19  1.17821046E-02 -5.64165018E-19 -1.36201484E-18&#xA;  7.58256127E-02 -7.80693294E-21 -2.01269478E-20 -9.77441063E-21  2.45857952E-19&#xA; -4.91685314E-19 -5.54762891E-19  3.52822261E-03 -1.44039097E-30 -1.05078329E-19&#xA;  1.60364319E-02 -5.22711831E-30 -4.49517571E-19 -5.06602218E-03 -1.24153870E-30&#xA;  9.55821017E-21  2.88479798E-02 -6.02594591E-30  1.88494844E-19  3.30085209E-02&#xA; -1.88476034E-20 -4.85907503E-20 -2.35975147E-20  5.93553603E-19 -1.18703335E-18&#xA; -1.33931610E-18 -1.44036689E-30  3.52822261E-03 -2.53681527E-19 -5.22721461E-30&#xA;  1.60364319E-02 -1.08523142E-18 -1.24151463E-30 -5.06602218E-03  2.30755606E-20&#xA; -6.02556072E-30  2.88479798E-02  4.55066808E-19 -4.05206031E-30  3.30085209E-02&#xA; -1.01997512E-03 -2.62958402E-03 -1.27702592E-03  3.21213205E-02 -6.42386444E-02&#xA; -7.24797245E-02 -1.05078329E-19 -2.53681527E-19 -1.02002521E-02 -4.49517571E-19&#xA; -1.08523142E-18 -4.26930004E-02  9.55821017E-21  2.30755606E-20 -3.81724283E-03&#xA;  1.88494844E-19  4.55066808E-19  5.34748151E-02  2.69336227E-19  6.50235173E-19&#xA; 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-3.86328743E-19  1.21527449E-19  3.03747039E-19  1.17531552E-20  1.55769158E-19&#xA;  1.81883741E-19 -3.10102529E-19  4.31184147E-01 -7.37631169E-31 -1.27023864E-19&#xA;  1.53322732E+00  2.52417577E-19  6.46884701E-19  6.04395793E-19 -1.56781527E-18&#xA; -8.53637828E-20  4.04724039E-19  6.58938875E-31  1.88944604E-03  2.29857622E-19&#xA;  2.79645028E-30  9.80119947E-03  7.49496297E-19 -1.64101870E-30 -4.12882570E-03&#xA;  3.39992608E-19  1.53256598E-29  1.50479796E-02  8.99210521E-19  4.15631330E-30&#xA;  1.05242724E-02 -4.41238745E-21 -6.17390411E-18 -9.78170250E-31  1.17992933E-01&#xA; -2.18033162E-18  9.03122926E-19 -2.61888864E-18 -5.63640446E-31  4.46907655E-02&#xA; -8.25818006E-19  3.42065018E-19  3.10646880E-19 -3.51079947E-30 -2.09069397E-02&#xA;  3.86328743E-19 -1.60022605E-19  2.93393216E-19  7.33310221E-19  2.83746268E-20&#xA;  3.76060014E-19  4.39106193E-19 -7.48653730E-19 -7.34549681E-31  4.31184147E-01&#xA; -3.06662735E-19 -3.11384353E-30  1.53322732E+00  1.36600736E-02  3.50074378E-02&#xA; 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-1.34873010E-20  8.45138876E-03  6.22147594E-30  1.17043227E-19  2.01294877E-03&#xA;  1.11346436E-30  1.73324739E-20  1.03301971E-19 -3.86383207E-03  9.99957250E-31&#xA; -2.95739349E-20 -7.13977947E-20 -4.69782415E-20 -2.11380360E-03 -3.25032842E-32&#xA; -1.61791425E-20 -3.90599054E-20 -1.85276381E-20 -9.56670740E-04 -1.17690799E-30&#xA; -7.32239850E-21 -1.76778338E-20 -1.25950982E-20 -2.19965268E-20 -1.52953449E-20&#xA;  8.94555687E-20  1.91482225E-19 -2.02663774E-21  1.48080107E-01  5.28667770E-31&#xA;  4.08107247E-20  5.18084033E-01  1.68095166E-30  1.47410440E-19  1.97330546E-01&#xA; -1.32843305E-19 -3.28203900E-19  2.31414778E-20  1.58412823E-19 -4.22473417E-19&#xA; -3.41331482E-20 -5.25718690E-31 -9.75996184E-04  8.16604712E-20 -1.64101870E-30&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6558" LastEditorUserId="6558" LastEditDate="2023-01-16T17:51:17.997" LastActivityDate="2023-01-22T18:30:08.420" Title="What kind of self-consistent field (SCF) density representation is this?" Tags="|electron-density|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10233" PostTypeId="1" AcceptedAnswerId="10234" CreationDate="2023-01-16T21:40:30.283" Score="4" ViewCount="329" Body="&lt;p&gt;A simple question about PySCF, but nonetheless I could not find out how to do it: I have a system of atoms for which I already calculated a STO-3G basis in the usual form of MOs:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi = \sum_i c_i \phi_i\tag{1}$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; being Gaussian primitives. How can I then parse this basis into a form so that I can use it for integral calculations in PySCF?&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your time!&lt;/p&gt;&#xA;" OwnerUserId="6509" LastEditorUserId="5" LastEditDate="2023-01-17T00:28:54.343" LastActivityDate="2023-01-17T00:28:54.343" Title="Inputting custom STO-3G basis into PySCF" Tags="|basis-sets|pyscf|integrals|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10234" PostTypeId="2" ParentId="10233" CreationDate="2023-01-17T00:27:37.533" Score="6" Body="&lt;p&gt;Instead of:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    basis = STO-3G&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;you can get PySCF to read your own &amp;quot;custom&amp;quot; basis set file, for example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    basis = {&#xA;        'H' : parse_gaussian.load('H_av2z.gbs', 'H')&#xA;    },&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;code&gt;.gbs&lt;/code&gt; file in this case, is written in Gaussian's basis format (make sure you have &lt;code&gt;from pyscf.gto.basis import parse_gaussian&lt;/code&gt; at the top of your script).&lt;/p&gt;&#xA;&lt;p&gt;An example of a &lt;code&gt;.gbs&lt;/code&gt; file is &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/H/av2z.gbs&quot; rel=&quot;noreferrer&quot;&gt;this one&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;spherical&#xA;&#xA;****&#xA;H     0&#xA;S    4   1.00&#xA;      1.301000D+01           1.968500D-02&#xA;      1.962000D+00           1.379770D-01&#xA;      4.446000D-01           4.781480D-01&#xA;      1.220000D-01           5.012400D-01&#xA;S    1   1.00&#xA;      1.220000D-01           1.000000D+00&#xA;S    1   1.00&#xA;      0.0297400              1.0000000&#xA;P    1   1.00&#xA;      7.270000D-01           1.0000000&#xA;P    1   1.00&#xA;      0.1410000              1.0000000&#xA;****&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The full input file that works is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;'''&#xA;H in aug-cc-pV2Z&#xA;'''&#xA;&#xA;import pyscf&#xA;from pyscf.gto.basis import parse_gaussian&#xA;&#xA;mol = pyscf.M(&#xA;    atom = 'H 0 0 0',&#xA;    unit = 'bohr',&#xA;    basis = {&#xA;        'H' : parse_gaussian.load('avdz.gbs', 'H')&#xA;    },&#xA;    spin = 1,&#xA;    verbose = 4,&#xA;    symmetry = True,&#xA;    symmetry_subgroup = 'Dooh'&#xA;)&#xA;mf = mol.UHF()&#xA;mf.init_guess='1e'&#xA;mf.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the output file &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/H/PySCF_av2z.txt&quot; rel=&quot;noreferrer&quot;&gt;will be&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#INFO: **** input file is /project/6004934/nike/atomic/H/av2z/pyscf/H_av2z.py ****&#xA;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;'''&#xA;H in aug-cc-pV2Z&#xA;'''&#xA;&#xA;import pyscf&#xA;from pyscf.gto.basis import parse_gaussian&#xA;&#xA;mol = pyscf.M(&#xA;    atom = 'H 0 0 0',&#xA;    unit = 'bohr',&#xA;    basis = {&#xA;        'H' : parse_gaussian.load('avdz.gbs', 'H')&#xA;    },&#xA;    spin = 1,&#xA;    verbose = 4,&#xA;    symmetry = True,&#xA;    symmetry_subgroup = 'Dooh'&#xA;)&#xA;mf = mol.UHF()&#xA;mf.init_guess='1e'&#xA;mf.kernel()&#xA;&#xA;#INFO: ******************** input file end ********************&#xA;&#xA;&#xA;System: uname_result(system='Linux', node='cedar5.cedar.computecanada.ca', release='3.10.0-1160.53.1.el7.x86_64', version='#1 SMP Fri Jan 14 13:59:45 UTC 2022', machine='x86_64', processor='')  Threads 64&#xA;Python 3.8.10 (default, Jun 16 2021, 14:20:20) &#xA;[GCC 9.3.0]&#xA;numpy 1.23.0  scipy 1.9.3&#xA;Date: Sun Dec  4 15:57:07 2022&#xA;PySCF version 2.1.0&#xA;PySCF path  /home/nike/.local/lib/python3.8/site-packages/pyscf&#xA;&#xA;[CONFIG] conf_file None&#xA;[INPUT] verbose = 4&#xA;[INPUT] num. atoms = 1&#xA;[INPUT] num. electrons = 1&#xA;[INPUT] charge = 0&#xA;[INPUT] spin (= nelec alpha-beta = 2S) = 1&#xA;[INPUT] symmetry True subgroup Dooh&#xA;[INPUT] Mole.unit = bohr&#xA;[INPUT] Symbol           X                Y                Z      unit          X                Y                Z       unit  Magmom&#xA;[INPUT]  1 H      0.000000000000   0.000000000000   0.000000000000 AA    0.000000000000   0.000000000000   0.000000000000 Bohr   0.0&#xA;&#xA;nuclear repulsion = 0&#xA;point group symmetry = SO3, use subgroup Dooh&#xA;symmetry origin: [0. 0. 0.]&#xA;symmetry axis x: [1. 0. 0.]&#xA;symmetry axis y: [0. 1. 0.]&#xA;symmetry axis z: [0. 0. 1.]&#xA;num. orbitals of irrep A1g = 3&#xA;num. orbitals of irrep A1u = 2&#xA;num. orbitals of irrep E1uy = 2&#xA;num. orbitals of irrep E1ux = 2&#xA;number of shells = 5&#xA;number of NR pGTOs = 12&#xA;number of NR cGTOs = &#xA;basis = {'H': [[0, [13.01, 0.019685], [1.962, 0.137977], [0.4446, 0.478148], [0.122, 0.50124]], [0, [0.122, 1.0]], [0, [0.02974, 1.0]], [1, [0.727, 1.0]], [1, [0.141, 1.0]]]}&#xA;ecp = {}&#xA;CPU time:         1.66&#xA;&#xA;&#xA;******** 1 electron system ********&#xA;alpha HOMO (A1g) = -0.499334315439586  LUMO (A1g) = -0.121867194807439&#xA;converged SCF energy = -0.499334315439586  &amp;lt;S^2&amp;gt; = 0.75  2S+1 = 2&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-01-17T00:27:37.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10235" PostTypeId="1" AcceptedAnswerId="10237" CreationDate="2023-01-02T10:04:37.847" Score="5" ViewCount="91" Body="&lt;p&gt;I have a rather basic question about the (minimal) number of molecular orbitals that are needed for some computation work on the BeH2 molecule.&#xA;To my understanding, STO-3G forms a minimal basis set, which I want to use for reasons of computational constraints.&lt;/p&gt;&#xA;&lt;p&gt;For the BeH2 molecule in the ground state, we have 6 electrons, 4 in 1s orbitals and 2 in 2s orbitals. Thus I form the two different molecular orbitals in the standard way as a linear combination of 3 gaussian functions&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\chi = \sum_{i=1}^{N=3} c_i \phi_i$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now I have the two molecular orbitals &lt;span class=&quot;math-container&quot;&gt;$\chi^{1s}, \chi^{2s}$&lt;/span&gt;. Now I believe I am correct in saying that the product of 4 &lt;span class=&quot;math-container&quot;&gt;$\chi^{1s}$&lt;/span&gt; and 2 &lt;span class=&quot;math-container&quot;&gt;$\chi^{2s}$&lt;/span&gt; functions builds my basis set, for example the state could be&#xA;&lt;span class=&quot;math-container&quot;&gt;$$|\chi_1^{1s} \chi_2^{1s} \chi_3^{1s} \chi_4^{1s} \chi_5^{2s} \chi_6^{2s} \rangle  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now if I want to use the occupation number representation, I get&#xA;&lt;span class=&quot;math-container&quot;&gt;$$|b_1 b_2 \cdots b_6  \rangle$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$b_i$&lt;/span&gt; is 1 if orbital i is occupied by an electron and 0 otherwise.&lt;/p&gt;&#xA;&lt;p&gt;Here is what I have trouble understanding: It seems to me that the system will at all points in time be described by the ket &lt;span class=&quot;math-container&quot;&gt;$|111111 \rangle$&lt;/span&gt; since any other one would mean that an electron disappeared somehow into nothingness.&lt;/p&gt;&#xA;&lt;p&gt;Can anybody spot my issue? I am neither a chemist nor a physicist, unfortunately, so I might be wrong at about any point.&lt;/p&gt;&#xA;&lt;p&gt;Thanks for any help&lt;/p&gt;&#xA;" OwnerUserId="6509" OwnerDisplayName="greilchri" LastActivityDate="2023-01-17T09:46:08.370" Title="Molecular Basis set construction (STO-3G) for BeH2" Tags="|quantum-chemistry|computational-chemistry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10236" PostTypeId="1" CreationDate="2023-01-17T09:40:46.517" Score="5" ViewCount="697" Body="&lt;p&gt;The following makefile.include was supplied to me, which was used for an existing installation of vasp 6.2.0 without hdf5 support. I am trying to modify it to recompile vasp with hdf5 support, in order to be able to use py4vasp.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Precompiler options&#xA;CPP_OPTIONS= -DHOST=\&amp;quot;LinuxIFC\&amp;quot;\&#xA;             -DMPI -DMPI_BLOCK=8000 -Duse_collective \&#xA;             -DscaLAPACK \&#xA;             -DCACHE_SIZE=4000 \&#xA;             -Davoidalloc \&#xA;             -Dvasp6 \&#xA;             -Duse_bse_te \&#xA;             -Dtbdyn \&#xA;             -Dfock_dblbuf&#xA;&#xA;CPP        = fpp -f_com=no -free -w0  &lt;span class=&quot;math-container&quot;&gt;$*$&lt;/span&gt;(FUFFIX) &lt;span class=&quot;math-container&quot;&gt;$*$&lt;/span&gt;(SUFFIX) $(CPP_OPTIONS)&#xA;&#xA;FC         = mpiifort&#xA;FCL        = mpiifort -mkl=sequential&#xA;&#xA;FREE       = -free -names lowercase&#xA;&#xA;FFLAGS     = -assume byterecl -w -xHOST&#xA;OFLAG      = -O2&#xA;OFLAG_IN   = $(OFLAG)&#xA;DEBUG      = -O0&#xA;&#xA;MKL_PATH   = &lt;span class=&quot;math-container&quot;&gt;$(MKLROOT)/lib/intel64&#xA;BLAS       =&#xA;LAPACK     =&#xA;BLACS      = -lmkl_blacs_intelmpi_lp64&#xA;SCALAPACK  = $&lt;/span&gt;(MKL_PATH)/libmkl_scalapack_lp64.a $(BLACS)&#xA;&#xA;OBJECTS    = fftmpiw.o fftmpi_map.o fft3dlib.o fftw3d.o&#xA;&#xA;INCS       =-I$(MKLROOT)/include/fftw&#xA;&#xA;LLIBS      = &lt;span class=&quot;math-container&quot;&gt;$(SCALAPACK) $&lt;/span&gt;(LAPACK) $(BLAS)&#xA;&#xA;OBJECTS_O1 += fftw3d.o fftmpi.o fftmpiw.o&#xA;OBJECTS_O2 += fft3dlib.o&#xA;&#xA;# For what used to be vasp.5.lib&#xA;CPP_LIB    = &lt;span class=&quot;math-container&quot;&gt;$(CPP)&#xA;FC_LIB     = $&lt;/span&gt;(FC)&#xA;CC_LIB     = icc&#xA;CFLAGS_LIB = -O&#xA;FFLAGS_LIB = -O1&#xA;FREE_LIB   = $(FREE)&#xA;&#xA;OBJECTS_LIB= linpack_double.o getshmem.o&#xA;&#xA;# For the parser library&#xA;CXX_PARS   = icpc&#xA;LLIBS      += -lstdc++&#xA;&#xA;# Normally no need to change this&#xA;SRCDIR     = ../../src&#xA;BINDIR     = ../../bin&#xA;&#xA;#================================================&#xA;# GPU Stuff&#xA;&#xA;CPP_GPU    = -DCUDA_GPU -DRPROMU_CPROJ_OVERLAP -DUSE_PINNED_MEMORY -DCUFFT_MIN=28 -UscaLAPACK -Ufock_dblbuf&#xA;&#xA;OBJECTS_GPU= fftmpiw.o fftmpi_map.o fft3dlib.o fftw3d_gpu.o fftmpiw_gpu.o&#xA;&#xA;CC         = icc&#xA;CXX        = icpc&#xA;CFLAGS     = -fPIC -DADD_ -Wall -qopenmp -DMAGMA_WITH_MKL -DMAGMA_SETAFFINITY -DGPUSHMEM=300 -DHAVE_CUBLAS&#xA;&#xA;# Minimal requirement is CUDA &amp;gt;= 10.X. For &amp;quot;sm_80&amp;quot; you need CUDA &amp;gt;= 11.X.&#xA;CUDA_ROOT  ?= /usr/local/cuda/&#xA;NVCC       := &lt;span class=&quot;math-container&quot;&gt;$(CUDA_ROOT)/bin/nvcc -ccbin=icc -allow-unsupported-compiler&#xA;CUDA_LIB   := -L$&lt;/span&gt;(CUDA_ROOT)/lib64 -lnvToolsExt -lcudart -lcuda -lcufft -lcublas&#xA;&#xA;GENCODE_ARCH    := -gencode=arch=compute_60,code=\&amp;quot;sm_60,compute_60\&amp;quot; \&#xA;                   -gencode=arch=compute_70,code=\&amp;quot;sm_70,compute_70\&amp;quot; \&#xA;                   -gencode=arch=compute_80,code=\&amp;quot;sm_80,compute_80\&amp;quot;&#xA;&#xA;## For all legacy Intel MPI versions (before 2021)&#xA;#MPI_INC    = $(I_MPI_ROOT)/intel64/include/&#xA;&#xA;# Or when you are using the Intel oneAPI compiler suite&#xA;MPI_INC    = $(I_MPI_ROOT)/include/&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I appended these lines as explained in [1]&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Needed for py4vasp&#xA;CPP_OPTIONS+= -DVASP_HDF5&#xA;HDF5_ROOT  ?= /home/myname/hdf/HDF5-1.12.1-Linux/HDF_Group/HDF5/1.12.1&#xA;LLIBS      += -L&lt;span class=&quot;math-container&quot;&gt;$(HDF5_ROOT)/lib -lhdf5_fortran&#xA;INCS       += -I$&lt;/span&gt;(HDF5_ROOT)/include&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Adding these lines caused the following errors&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &#xA;:: initializing oneAPI environment ...&#xA;   slurm_script: BASH_VERSION = 5.1.4(1)-release&#xA;:: advisor -- latest&#xA;:: ccl -- latest&#xA;:: clck -- latest&#xA;:: compiler -- latest&#xA;:: dal -- latest&#xA;:: debugger -- latest&#xA;:: dev-utilities -- latest&#xA;:: dnnl -- latest&#xA;:: dpcpp-ct -- latest&#xA;:: dpl -- latest&#xA;:: inspector -- latest&#xA;:: intelpython -- latest&#xA;:: ipp -- latest&#xA;:: ippcp -- latest&#xA;:: ipp -- latest&#xA;:: itac -- latest&#xA;:: mkl -- latest&#xA;:: mpi -- latest&#xA;:: tbb -- latest&#xA;:: vpl -- latest&#xA;:: vtune -- latest&#xA;:: oneAPI environment initialized ::&#xA; &#xA;if [ ! -d build/std ] ; then mkdir build/std  ; fi;&#xA;cp src/makefile src/.objects src/makedeps.awk makefile.include build/std ;&#xA;make -C build/std VERSION=std cleandependencies -j1&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rm -f .depend&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make -C build/std VERSION=std all&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rsync -ru ../../src/lib .&#xA;cp makefile.include lib&#xA;make -C lib -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make libdmy.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[3]: 'libdmy.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;rsync -ru ../../src/parser .&#xA;cp makefile.include parser&#xA;make -C parser -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make libparser.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[3]: 'libparser.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;rsync -u ../../src/*.F ../../src/*.inc .&#xA;rm -f vasp ; make vasp ; cp vasp ../../bin/vasp_std&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;mpiifort -free -names lowercase -assume byterecl -w -xHOST -O2 -I/home/software/materia/intel_lib/mkl/2021.4.0/include/fftw -I/home/myname/hdf/HDF5-1.12.1-Linux/HDF_Group/HDF5/1.12.1/include  -c vhdf5_base.f90&#xA;vhdf5_base.F(6): error #7002: Error in opening the compiled module file.  Check INCLUDE paths.   [HDF5]&#xA;  use hdf5&#xA;------^&#xA;vhdf5_base.F(36): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5intermediategroup_id&#xA;----------^&#xA;vhdf5_base.F(37): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5infileid&#xA;----------^&#xA;vhdf5_base.F(38): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outfileid&#xA;----------^&#xA;vhdf5_base.F(39): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5wavefileid&#xA;----------^&#xA;vhdf5_base.F(40): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5ininputgroup_id&#xA;----------^&#xA;vhdf5_base.F(41): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outinputgroup_id&#xA;----------^&#xA;vhdf5_base.F(42): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outoriginalgroup_id&#xA;----------^&#xA;vhdf5_base.F(57): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T) :: create_inter_prop&#xA;----------^&#xA;vhdf5_base.F(204): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(218): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(232): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(247): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(263): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(274): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(316): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: fileid&#xA;------------^&#xA;vhdf5_base.F(344): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(346): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(357): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(370): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(372): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(387): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(389): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(410): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(426): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.F(451): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: groupid&#xA;------------^&#xA;vhdf5_base.F(457): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T) :: dset_id, attr_id, aspace, string_type&#xA;------------^&#xA;vhdf5_base.F(458): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: dimensions(1)&#xA;------------^&#xA;vhdf5_base.F(459): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: strlen&#xA;------------^&#xA;vhdf5_base.F(500): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.f90(2776): catastrophic error: Too many errors, exiting&#xA;compilation aborted for vhdf5_base.f90 (code 1)&#xA;make[2]: *** [makefile:181: vhdf5_base.o] Error 1&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;cp: cannot stat 'vasp': No such file or directory&#xA;make[1]: *** [makefile:146: all] Error 1&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make: *** [makefile:9: std] Error 2&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am using a virtual machine Linux #1 SMP Debian 5.10.140-1 (2022-09-02), where I installed&#xA;hdf5-1.12.1-Std-ubuntu2010_64.tar.gz from [2].&lt;/p&gt;&#xA;&lt;p&gt;[1]: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Makefile.include#HDF5_support_.28strongly_recommended.29&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Makefile.include#HDF5_support_.28strongly_recommended.29&lt;/a&gt;)&#xA;[2]: &lt;a href=&quot;https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.12/hdf5-1.12.1/bin/unix/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.12/hdf5-1.12.1/bin/unix/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;EDIT: Now I have tried building HDF5 from source rather than using the binary file, following these steps:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;         gunzip &amp;lt; hdf5-1.14.0.tar.gz | tar xf -&#xA;         cd hdf5-1.14.0&#xA;         ./configure --enable-fortran --enable-cxx&#xA;         make&#xA;         make check                # run test suite.&#xA;         make install&#xA;         make check-install        # verify installation&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After updating the HDF5_ROOT in vasp makefile.include, now the compiling job returns the following errors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;:: initializing oneAPI environment ...&#xA;   slurm_script: BASH_VERSION = 5.1.4(1)-release&#xA;:: advisor -- latest&#xA;:: ccl -- latest&#xA;:: clck -- latest&#xA;:: compiler -- latest&#xA;:: dal -- latest&#xA;:: debugger -- latest&#xA;:: dev-utilities -- latest&#xA;:: dnnl -- latest&#xA;:: dpcpp-ct -- latest&#xA;:: dpl -- latest&#xA;:: inspector -- latest&#xA;:: intelpython -- latest&#xA;:: ipp -- latest&#xA;:: ippcp -- latest&#xA;:: ipp -- latest&#xA;:: itac -- latest&#xA;:: mkl -- latest&#xA;:: mpi -- latest&#xA;:: tbb -- latest&#xA;:: vpl -- latest&#xA;:: vtune -- latest&#xA;:: oneAPI environment initialized ::&#xA; &#xA;if [ ! -d build/std ] ; then mkdir build/std  ; fi;&#xA;cp src/makefile src/.objects src/makedeps.awk makefile.include build/std ;&#xA;make -C build/std VERSION=std cleandependencies -j1&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rm -f .depend&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make -C build/std VERSION=std all&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rsync -ru ../../src/lib .&#xA;cp makefile.include lib&#xA;make -C lib -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make libdmy.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[3]: 'libdmy.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;rsync -ru ../../src/parser .&#xA;cp makefile.include parser&#xA;make -C parser -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make libparser.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[3]: 'libparser.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;rsync -u ../../src/*.F ../../src/*.inc .&#xA;rm -f vasp ; make vasp ; cp vasp ../../bin/vasp_std&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;mpiifort -free -names lowercase -assume byterecl -w -xHOST -O2 -I/home/software/materia/intel_lib/mkl/2021.4.0/include/fftw -I/home/myname/hdf5-1.14.0/hdf5/include  -c vhdf5_base.f90&#xA;vhdf5_base.F(6): error #7013: This module file was not generated by any release of this compiler.   [HDF5]&#xA;  use hdf5&#xA;------^&#xA;vhdf5_base.F(36): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5intermediategroup_id&#xA;----------^&#xA;vhdf5_base.F(37): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5infileid&#xA;----------^&#xA;vhdf5_base.F(38): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outfileid&#xA;----------^&#xA;vhdf5_base.F(39): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5wavefileid&#xA;----------^&#xA;vhdf5_base.F(40): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5ininputgroup_id&#xA;----------^&#xA;vhdf5_base.F(41): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outinputgroup_id&#xA;----------^&#xA;vhdf5_base.F(42): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outoriginalgroup_id&#xA;----------^&#xA;vhdf5_base.F(57): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T) :: create_inter_prop&#xA;----------^&#xA;vhdf5_base.F(204): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(218): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(232): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(247): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(263): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(274): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(316): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: fileid&#xA;------------^&#xA;vhdf5_base.F(344): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(346): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(357): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(370): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(372): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(387): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(389): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(410): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(426): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.F(451): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: groupid&#xA;------------^&#xA;vhdf5_base.F(457): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T) :: dset_id, attr_id, aspace, string_type&#xA;------------^&#xA;vhdf5_base.F(458): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: dimensions(1)&#xA;------------^&#xA;vhdf5_base.F(459): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: strlen&#xA;------------^&#xA;vhdf5_base.F(500): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.f90(2776): catastrophic error: Too many errors, exiting&#xA;compilation aborted for vhdf5_base.f90 (code 1)&#xA;make[2]: *** [makefile:181: vhdf5_base.o] Error 1&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;cp: cannot stat 'vasp': No such file or directory&#xA;make[1]: *** [makefile:146: all] Error 1&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make: *** [makefile:9: std] Error 2&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;EDIT2: Following @IanBush 's suggestion I have recompiled HDF5 with&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CXX=icpc CC=icc FC=ifort ./configure --enable-fortran --enable-cxx; make -j 4&#xA;make check &#xA;make install&#xA;make check-install&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but again when compiling vasp I obtained errors about the include path (I have checked that the directory HDF5_ROOT   ?= /home/myname/hdf5-1.14.0/hdf5 actually contains include folder)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;if [ ! -d build/std ] ; then mkdir build/std  ; fi;&#xA;cp src/makefile src/.objects src/makedeps.awk makefile.include build/std ;&#xA;make -C build/std VERSION=std cleandependencies -j1&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rm -f .depend&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make -C build/std VERSION=std all&#xA;make[1]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;rsync -ru ../../src/lib .&#xA;cp makefile.include lib&#xA;make -C lib -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make libdmy.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[3]: 'libdmy.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/lib'&#xA;rsync -ru ../../src/parser .&#xA;cp makefile.include parser&#xA;make -C parser -j1&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make libparser.a&#xA;make[3]: Entering directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[3]: 'libparser.a' is up to date.&#xA;make[3]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std/parser'&#xA;rsync -u ../../src/*.F ../../src/*.inc .&#xA;rm -f vasp ; make vasp ; cp vasp ../../bin/vasp_std&#xA;make[2]: Entering directory '/home/myname/vasp.6.2.0/build/std'&#xA;mpiifort -free -names lowercase -assume byterecl -w -xHOST -O2 -I/home/software/materia/intel_lib/mkl/2021.4.0/include/fftw -I/home/myname/hdf5-1.14.0/hdf5/include  -c vhdf5_base.f90&#xA;vhdf5_base.F(6): error #7002: Error in opening the compiled module file.  Check INCLUDE paths.   [HDF5]&#xA;  use hdf5&#xA;------^&#xA;vhdf5_base.F(36): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5intermediategroup_id&#xA;----------^&#xA;vhdf5_base.F(37): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5infileid&#xA;----------^&#xA;vhdf5_base.F(38): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outfileid&#xA;----------^&#xA;vhdf5_base.F(39): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5wavefileid&#xA;----------^&#xA;vhdf5_base.F(40): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5ininputgroup_id&#xA;----------^&#xA;vhdf5_base.F(41): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outinputgroup_id&#xA;----------^&#xA;vhdf5_base.F(42): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T):: ih5outoriginalgroup_id&#xA;----------^&#xA;vhdf5_base.F(57): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;  integer(HID_T) :: create_inter_prop&#xA;----------^&#xA;vhdf5_base.F(204): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(218): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(232): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(247): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(263): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(274): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) :: fileid&#xA;------------^&#xA;vhdf5_base.F(316): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: fileid&#xA;------------^&#xA;vhdf5_base.F(344): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(346): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(357): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(370): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(372): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(387): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   locid&#xA;------------^&#xA;vhdf5_base.F(389): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(out) ::  groupid&#xA;------------^&#xA;vhdf5_base.F(410): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) ::   groupid&#xA;------------^&#xA;vhdf5_base.F(426): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.F(451): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: groupid&#xA;------------^&#xA;vhdf5_base.F(457): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T) :: dset_id, attr_id, aspace, string_type&#xA;------------^&#xA;vhdf5_base.F(458): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: dimensions(1)&#xA;------------^&#xA;vhdf5_base.F(459): error #6683: A kind type parameter must be a compile-time constant.   [HSIZE_T]&#xA;    integer(HSIZE_T) :: strlen&#xA;------------^&#xA;vhdf5_base.F(500): error #6683: A kind type parameter must be a compile-time constant.   [HID_T]&#xA;    integer(HID_T), intent(in) :: locid&#xA;------------^&#xA;vhdf5_base.f90(2776): catastrophic error: Too many errors, exiting&#xA;compilation aborted for vhdf5_base.f90 (code 1)&#xA;make[2]: *** [makefile:181: vhdf5_base.o] Error 1&#xA;make[2]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;cp: cannot stat 'vasp': No such file or directory&#xA;make[1]: *** [makefile:146: all] Error 1&#xA;make[1]: Leaving directory '/home/myname/vasp.6.2.0/build/std'&#xA;make: *** [makefile:9: std] Error 2&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6513" LastEditorUserId="6513" LastEditDate="2023-01-22T17:20:52.710" LastActivityDate="2023-01-22T17:20:52.710" Title="Install pyvasp: how to compile vasp 6.2.0 with hdf5 support" Tags="|vasp|" AnswerCount="0" CommentCount="14" ClosedDate="2023-12-09T22:48:43.440" ContentLicense="CC BY-SA 4.0" />
  <row Id="10237" PostTypeId="2" ParentId="10235" CreationDate="2023-01-17T09:46:08.370" Score="3" Body="&lt;p&gt;The STO-3G basis set not only has two contracted s functions for Be, but also one contracted p function, which can be used to construct the 2p orbital of Be. Therefore you have 6 empty spin-orbitals, which are approximately the alpha and beta Be 2p orbitals (with some admixture of the s orbitals of H and Be). It is the presence of these 6 empty orbitals that make the SCF/FCI/... solution (and in particular, the time evolution) of BeH2 not completely trivial when using the STO-3G basis set, since the electrons can excite into these orbitals.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-01-17T09:46:08.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10238" PostTypeId="1" AcceptedAnswerId="10246" CreationDate="2023-01-17T17:12:10.967" Score="3" ViewCount="988" Body="&lt;p&gt;I am doing an exercise to calculate silicon crystal mobility using quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;I'm in a step where i should do a non self-consistent calculation on a 6x6x6 uniform and Γ-centered k-point grid with crystal coordinates in the interval [0,1].&lt;/p&gt;&#xA;&lt;p&gt;But I don't know how to generate this grid. Can anyone help me please (I didn't find any tutorial about how to that in the web)?&lt;/p&gt;&#xA;&lt;p&gt;I want to know also why they chose the interval [0,1].&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-01-19T09:15:46.660" LastActivityDate="2023-01-19T09:15:46.660" Title="How to generate k-point grid using Quantum ESPRESSO?" Tags="|quantum-espresso|k-points|vibrations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10239" PostTypeId="1" CreationDate="2023-01-17T17:57:42.130" Score="3" ViewCount="125" Body="&lt;p&gt;I have encountered a convergence problem in my structure device in Transiesta calculation, the calculation doesn't converge. Recently I try to decrease the mixing weight parameter to 0.00001. For some small structures, it stops at 300 iterations without convergence. For big sizes strucutre (even with 0V), it tacks more than a month without convergence.&#xA;I would be grateful if can any one solve my problem with this error&#xA;any suggestion will be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2023-01-17T22:52:32.507" LastActivityDate="2023-01-17T22:52:32.507" Title="Transiesta SCF not converged" Tags="|density-functional-theory|siesta|graphene|quantum-dots|transport|" AnswerCount="0" CommentCount="6" ClosedDate="2024-03-08T22:35:13.890" ContentLicense="CC BY-SA 4.0" />
  <row Id="10240" PostTypeId="1" AcceptedAnswerId="10243" CreationDate="2023-01-17T18:57:01.810" Score="3" ViewCount="99" Body="&lt;p&gt;I have followed the transiesta &lt;a href=&quot;https://github.com/siesta-project/tutorials/tree/master/QuantumTransport/09-IV&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt; regarding calculations with different bias. I am now using a similar input for my calculations.&lt;/p&gt;&#xA;&lt;p&gt;However, I found these input parameters&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TS.biasContour.Eta&#xA;TS.biasContour.NumPoints&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;that are not reported in the manual, but rather in the old version of transiesta. I understand that these two lines are referring to the non-equilibrium contour, and in the latter version of transiesta should be referred as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TS.Contours.nEq&#xA;  part line&#xA;  from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;  delta    0.026 eV&#xA;  method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the latter version of siesta, it was recommended to enlarge the number of points when increasing the bias calculated. How does this change in the last version of transiesta?&lt;/p&gt;&#xA;&lt;p&gt;Moreover, should also&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TBT.Contour.neq&#xA;  part line&#xA;   from   -1.00000 eV to    1.00000 eV&#xA;    delta    0.001 eV&#xA;     method mid-rule&#xA;%endblock TBT.Contour.neq&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;be considered in the changing?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-01-18T09:25:57.167" LastActivityDate="2023-01-18T09:36:25.060" Title="Transiesta calculation at non-zero bias" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10241" PostTypeId="1" AcceptedAnswerId="10242" CreationDate="2023-01-17T20:57:24.857" Score="3" ViewCount="283" Body="&lt;p&gt;I am using SIESTA 4.1.5 version,&#xA;I have done electrode Calculation using K-grid values 3X3X100 for both the electrodes, and&#xA;currently i am doing transmission calculation, I tried different K-grid values like 3 × 3 × 100, 3 × 3 × 1,3 × 3 × 3,3 × 3 × 300, etc. in transmission calculation but I am getting Error like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Electrode: Left is a Gamma-only calculation, this is not feasible.&#xA;Erroneous electrode setup, check out-put&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I fix this problem?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Thanks for this reply Sir,&#xA;I searched in the output file of electrode calculation, i was not unable find but it is written in output file of electrode calculation that the K-points displacement in the 3 input could be 0.0 0.5 other than this, I didn't found anything different.&lt;/p&gt;&#xA;&lt;p&gt;code for electrode and scattering region calculation input and output&#xA;electrode input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SystemName  leftAu&#xA;SystemLabel leftAu&#xA;&#xA;# Atomic coordinates&#xA;NumberOfAtoms 36&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;   1.705900000000      4.978000000000     -2.885900000000 1&#xA;   3.266300000000      5.634400000000     -0.551300000000 1&#xA;   3.440400000000      7.281600000000     -2.912000000000 1&#xA;   4.568100000000      4.627500000000     -2.919400000000 1&#xA;   5.000900000000      7.938100000000     -0.577400000000 1&#xA;   5.175000000000      9.585300000000     -2.938000000000 1&#xA;   6.128600000000      5.283900000000     -0.584800000000 1&#xA;   6.302600000000      6.931200000000     -2.945500000000 1&#xA;   7.430300000000      4.277000000000     -2.952900000000 1&#xA;   6.735400000000     10.241800000000     -0.603400000000 1&#xA;   6.909500000000     11.889000000000     -2.964100000000 1&#xA;   7.863100000000      7.587600000000     -0.610900000000 1&#xA;   8.037200000000      9.234800000000     -2.971500000000 1&#xA;   8.990800000000      4.933400000000     -0.618300000000 1&#xA;   9.164900000000      6.580700000000     -2.979000000000 1&#xA;  10.292500000000      3.926500000000     -2.986400000000 1&#xA;   8.470000000000     12.545400000000     -0.629500000000 1&#xA;   8.644100000000     14.192700000000     -2.990100000000 1&#xA;   9.597700000000      9.891300000000     -0.636900000000 1&#xA;   9.771700000000     11.538500000000     -2.997600000000 1&#xA;  10.725300000000      7.237100000000     -0.644400000000 1&#xA;  10.899400000000      8.884300000000     -3.005000000000 1&#xA;  11.853000000000      4.582900000000     -0.651800000000 1&#xA;  12.027100000000      6.230200000000     -3.012500000000 1&#xA;  13.154700000000      3.576000000000     -3.019900000000 1&#xA;  10.204600000000     14.849100000000     -0.655500000000 1&#xA;  10.378600000000     16.496300000000     -3.016200000000 1&#xA;  11.332200000000     12.194900000000     -0.663000000000 1&#xA;  11.506300000000     13.842200000000     -3.023600000000 1&#xA;  12.459900000000      9.540800000000     -0.670400000000 1&#xA;  12.634000000000     11.188000000000     -3.031100000000 1&#xA;  13.587500000000      6.886600000000     -0.677900000000 1&#xA;  13.761600000000      8.533800000000     -3.038500000000 1&#xA;  14.715200000000      4.232400000000     -0.685300000000 1&#xA;  14.889300000000      5.879700000000     -3.046000000000 1&#xA;  16.017000000000      3.225500000000     -3.053400000000 1         &#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;# UNIT CELL&#xA;&#xA;%block LatticeVectors&#xA;    18.00000    18.00000    18.00000&#xA;    18.00000    18.00000    18.00000&#xA;    18.00000    18.00000    18.00000&#xA;%endblock LatticeVectors&#xA;&#xA;&#xA;# K-points&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA;3    0   0    0.0&#xA;0    3   0    0.0&#xA;0    0   100  0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;&#xA;# Chemical species&#xA;&#xA;NumberOfSpecies 1&#xA;%block ChemicalSpeciesLabel&#xA;  1  79 Au &#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;# Basis set variables&#xA;PAO.BasisType split&#xA;PAO.SplitTailNorm true&#xA;PAO.SplitNorm 0.15&#xA;PAO.BasisSize SZP&#xA;&#xA;# General variables&#xA;&#xA;#NeglNonOverlapInt   True&#xA;ElectronicTemperature  300 K&#xA;SolutionMethod    diagon &#xA;MeshCutoff           150. Ry&#xA;xc.functional         GGA           # Exchange-correlation functional&#xA;xc.authors            PBE &#xA;SpinPolarized false &#xA;PAO.EnergyShift    0.01 eV&#xA;          # Exchange-correlation version&#xA;&#xA;# SCF variables&#xA;&#xA;DM.MixSCF1   T&#xA;MaxSCFIterations      1000           # Maximum number of SCF iter&#xA;DM.MixH               T    &#xA;DM.MixingWeight       0.01          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.d-5         # Tolerance in maximum difference&#xA;DM.UseSaveDM          .true.          # to use continuation files&#xA;DM.NumberPulay         5&#xA;&#xA;# MD variables&#xA;&#xA;MD.FinalTimeStep 1&#xA;MD.TypeOfRun CG &#xA;MD.NumCGsteps     000&#xA;MD.UseSaveXV     .true.&#xA;&#xA;# Output variables&#xA;&#xA;WriteMullikenPop                1&#xA;WriteBands                      .true.&#xA;SaveRho                         .true.&#xA;SaveDeltaRho                    .true.&#xA;SaveHS                          .true.&#xA;SaveElectrostaticPotential      yes&#xA;SaveTotalPotential              yes&#xA;WriteCoorXmol                   .true.&#xA;WriteMDXmol                     .true.&#xA;WriteMDhistory                  .true.&#xA;WriteEigenvalues                yes&#xA;SaveTotalPotential              .true.&#xA;&#xA;electrode output file:&#xA;&#xA;siesta: WARNING: XV file not found&#xA;&#xA;siesta: Atomic coordinates (Bohr) and species&#xA;siesta:      3.22369   9.40706  -5.45356  1        1&#xA;siesta:      6.17241  10.64748  -1.04181  1        2&#xA;siesta:      6.50142  13.76024  -5.50288  1        3&#xA;      ...........&#xA;&#xA;siesta: Automatic unit cell vectors (Ang):&#xA;siesta:   26.046637    0.000000    0.000000&#xA;siesta:    0.000000   24.902307    0.000000&#xA;siesta:    0.000000    0.000000   13.056737&#xA;&#xA;siesta: System type = molecule  &#xA;&#xA;initatomlists: Number of atoms, orbitals, and projectors:     36   324   684&#xA;&#xA;coxmol: Writing XMOL coordinates into file leftAu.xyz                                                          &#xA;&#xA;siesta: ******************** Simulation parameters ****************************&#xA;siesta:&#xA;siesta: The following are some of the parameters of the simulation.&#xA;siesta: A complete list of the parameters used, including default values,&#xA;siesta: can be found in file out.fdf&#xA;siesta:&#xA;redata: Spin configuration                          = none&#xA;redata: Number of spin components                   = 1&#xA;redata: Time-Reversal Symmetry                      = T&#xA;redata: Spin spiral                                 = F&#xA;redata: Long output                                 =   F&#xA;redata: Number of Atomic Species                    =        1&#xA;redata: Charge density info will appear in .RHO file&#xA;redata: Write Mulliken Pop.                         = Atomic and Orbital charges&#xA;redata: Matel table size (NRTAB)                    =     1024&#xA;redata: Mesh Cutoff                                 =   150.0000 Ry&#xA;redata: Net charge of the system                    =     0.0000 |e|&#xA;redata: Min. number of SCF Iter                     =        0&#xA;redata: Max. number of SCF Iter                     =     1000&#xA;redata: SCF convergence failure will abort job&#xA;redata: SCF mix quantity                            = Hamiltonian&#xA;redata: Mix DM or H after convergence               =   F&#xA;redata: Recompute H after scf cycle                 =   F&#xA;redata: Mix DM in first SCF step                    =   T&#xA;redata: Write Pulay info on disk                    =   F&#xA;redata: New DM Occupancy tolerance                  = 0.000000000001&#xA;redata: No kicks to SCF&#xA;redata: DM Mixing Weight for Kicks                  =     0.5000&#xA;redata: Require Harris convergence for SCF          =   F&#xA;redata: Harris energy tolerance for SCF             =     0.000100 eV&#xA;redata: Require DM convergence for SCF              =   T&#xA;redata: DM tolerance for SCF                        =     0.000010&#xA;redata: Require EDM convergence for SCF             =   F&#xA;redata: EDM tolerance for SCF                       =     0.001000 eV&#xA;redata: Require H convergence for SCF               =   T&#xA;redata: Hamiltonian tolerance for SCF               =     0.001000 eV&#xA;redata: Require (free) Energy convergence for SCF   =   F&#xA;redata: (free) Energy tolerance for SCF             =     0.000100 eV&#xA;redata: Using Saved Data (generic)                  =   F&#xA;redata: Use continuation files for DM               =   T&#xA;redata: Neglect nonoverlap interactions             =   F&#xA;redata: Method of Calculation                       = Diagonalization&#xA;redata: Electronic Temperature                      =   299.9978 K&#xA;redata: Fix the spin of the system                  =   F&#xA;redata: Dynamics option                             = Single-point calculation&#xA;mix.SCF: Pulay mixing                            = Pulay&#xA;mix.SCF:    Variant                              = stable&#xA;mix.SCF:    History steps                        = 5&#xA;mix.SCF:    Linear mixing weight                 =     0.010000&#xA;mix.SCF:    Mixing weight                        =     0.010000&#xA;mix.SCF:    SVD condition                        = 0.1000E-07&#xA;redata: Save all siesta data in one NC              =   F&#xA;redata: ***********************************************************************&#xA;&#xA;%block SCF.Mixers&#xA;  Pulay&#xA;%endblock SCF.Mixers&#xA;&#xA;%block SCF.Mixer.Pulay&#xA;  # Mixing method&#xA;  method pulay&#xA;  variant stable&#xA;&#xA;  # Mixing options&#xA;  weight 0.0100&#xA;  weight.linear 0.0100&#xA;  history 5&#xA;%endblock SCF.Mixer.Pulay&#xA;&#xA;DM_history_depth set to one: no extrapolation allowed by default for geometry relaxation&#xA;Size of DM history Fstack: 1&#xA;Total number of electrons:   396.000000&#xA;Total ionic charge:   396.000000&#xA;&#xA;* ProcessorY, Blocksize:    6   6&#xA;&#xA;&#xA;* Orbital distribution balance (max,min):    12     6&#xA;&#xA;k-point displ. along   3 input, could be:     0.00    0.50&#xA; Kpoints in:          459 . Kpoints trimmed:          455&#xA;&#xA;siesta: k-grid: Number of k-points =   455&#xA;siesta: k-grid: Cutoff (effective) =    37.353 Ang&#xA;siesta: k-grid: Supercell and displacements&#xA;siesta: k-grid:    3   0   0      0.000&#xA;siesta: k-grid:    0   3   0      0.000&#xA;siesta: k-grid:    0   0 100      0.000&#xA;&#xA;diag: Algorithm                                     = D&amp;amp;C&#xA;diag: Parallel over k                               =   F&#xA;diag: Use parallel 2D distribution                  =   T&#xA;diag: Parallel block-size                           = 6&#xA;diag: Parallel distribution                         =     6 x     8&#xA;diag: Used triangular part                          = Lower&#xA;diag: Absolute tolerance                            =  0.100E-15&#xA;diag: Orthogonalization factor                      =  0.100E-05&#xA;diag: Memory factor                                 =  1.0000&#xA;&#xA;&#xA;ts: **************************************************************&#xA;ts: Save H and S matrices                           =    T&#xA;ts: Save DM and EDM matrices                        =    T&#xA;ts: Only save the overlap matrix S                  =    F&#xA;ts: **************************************************************&#xA;&#xA;************************ Begin: TS CHECKS AND WARNINGS ************************&#xA;************************ End: TS CHECKS AND WARNINGS **************************&#xA;&#xA;&#xA;                     ====================================&#xA;                        Single-point calculation&#xA;                     ====================================&#xA;&#xA;outcell: Unit cell vectors (Ang):&#xA;       26.046637    0.000000    0.000000&#xA;        0.000000   24.902307    0.000000&#xA;        0.000000    0.000000   13.056737&#xA;&#xA;outcell: Cell vector modules (Ang)   :   26.046637   24.902307   13.056737&#xA;outcell: Cell angles (23,13,12) (deg):     90.0000     90.0000     90.0000&#xA;outcell: Cell volume (Ang**3)        :   8468.8790&#xA;&amp;lt;dSpData1D:S at geom step 0&#xA;  &amp;lt;sparsity:sparsity for geom step 0&#xA;    nrows_g=324 nrows=12 sparsity=.0285 nnzs=2990, refcount: 7&amp;gt;&#xA;  &amp;lt;dData1D:(new from dSpData1D) n=2990, refcount: 1&amp;gt;&#xA;refcount: 1&amp;gt;&#xA;new_DM -- step:     1&#xA;Initializing Density Matrix...&#xA;&#xA;Attempting to read DM from file... Failed...&#xA;DM filled with atomic data:&#xA;&amp;lt;dSpData2D:DM initialized from atoms&#xA;  &amp;lt;sparsity:sparsity for geom step 0&#xA;    nrows_g=324 nrows=12 sparsity=.0285 nnzs=2990, refcount: 8&amp;gt;&#xA;  &amp;lt;dData2D:DM n=2990 m=1, refcount: 1&amp;gt;&#xA;refcount: 1&amp;gt;&#xA;No. of atoms with KB's overlaping orbs in proc 0. Max # of overlaps:      30     230&#xA;New grid distribution:   1&#xA;           1       1:   96    1:   16    1:    7&#xA;           2       1:   96    1:   16    8:   14&#xA;           3       1:   96    1:   16   15:   20&#xA;          .......&#xA;&#xA;InitMesh: MESH =   192 x   192 x   100 =     3686400&#xA;InitMesh: (bp) =    96 x    96 x    50 =      460800&#xA;InitMesh: Mesh cutoff (required, used) =   150.000   150.176 Ry&#xA;ExtMesh (bp) on 0 =   168 x    92 x    79 =     1221024&#xA;New grid distribution:   2&#xA;           1      44:   96    1:   22    1:   34&#xA;           2      36:   43    1:   22    1:   40&#xA;           3      42:   96   23:   31   46:   50&#xA;           4      21:   35    1:   24   41:   45&#xA;           5       1:   20    1:   24    1:   40&#xA;          ....&#xA;Setting up quadratic distribution...&#xA;ExtMesh (bp) on 0 =   125 x    98 x   106 =     1298500&#xA;PhiOnMesh: Number of (b)points on node 0 =                39644&#xA;PhiOnMesh: nlist on node 0 =               232730&#xA;&#xA;stepf: Fermi-Dirac step function&#xA;&#xA;siesta: Program's energy decomposition (eV):&#xA;siesta: Ebs     =     -4008.186821&#xA;siesta: Eions   =     31343.136906&#xA;siesta: Ena     =       127.262206&#xA;siesta: Ekin    =     20794.072458&#xA;siesta: Enl     =    -15707.362626&#xA;siesta: Eso     =         0.000000&#xA;siesta: Edftu   =         0.000000&#xA;siesta: DEna    =        -4.980730&#xA;siesta: DUscf   =        13.886775&#xA;siesta: DUext   =         0.000000&#xA;siesta: Exc     =     -7721.736615&#xA;siesta: eta*DQ  =         0.000000&#xA;siesta: Emadel  =         0.000000&#xA;siesta: Emeta   =         0.000000&#xA;siesta: Emolmec =         0.000000&#xA;siesta: Ekinion =         0.000000&#xA;siesta: Eharris =    -33806.017259&#xA;siesta: Etot    =    -33841.995438&#xA;siesta: FreeEng =    -33842.068095&#xA;&#xA;        iscf     Eharris(eV)        E_KS(eV)     FreeEng(eV)     dDmax    Ef(eV) dHmax(eV)&#xA;   scf:    1   -33806.017259   -33841.995438   -33842.068095  0.383586 -4.299979  6.458168&#xA;timer: Routine,Calls,Time,% = IterSCF        1    1229.819  99.92&#xA;   scf:    2   -33843.275716   -33842.647545   -33842.720352  0.009007 -4.323171  5.968842&#xA;   scf:    3   -33846.714056   -33846.257633   -33846.334987  0.103917 -4.600736  1.648266 ....................&#xA;&#xA;SCF Convergence by DM+H criterion&#xA;max |DM_out - DM_in|         :     0.0000017710&#xA;max |H_out - H_in|      (eV) :     0.0007986776&#xA;SCF cycle converged after 36 iterations&#xA;&#xA;Using DM_out to compute the final energy and forces&#xA;No. of atoms with KB's overlaping orbs in proc 0. Max # of overlaps:      30     230&#xA;&#xA;siesta: E_KS(eV) =           -33847.9636&#xA;&#xA;siesta: E_KS - E_eggbox =    -33847.9636&#xA;&#xA;siesta: Atomic forces (eV/Ang):&#xA;----------------------------------------&#xA;   Tot    0.003138   -0.002314   -0.000862&#xA;----------------------------------------&#xA;   Max    1.995833&#xA;   Res    0.779961    sqrt( Sum f_i^2 / 3N )&#xA;----------------------------------------&#xA;   Max    1.995833    constrained&#xA;&#xA;I have not included some part of electrode output...&#xA;&#xA;scattering region input:&#xA;&#xA;SystemName  CpolyPTN2&#xA;SystemLabel CpolyPTN2&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SPECIES AND BASIS&#xA;&#xA;# Number of species &#xA;NumberOfSpecies 4&#xA;%block ChemicalSpeciesLabel &#xA;1 6 C&#xA;2 1 H&#xA;3 16 S&#xA;4 79 Au&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;%block PAO.BasisSizes&#xA;C  DZP&#xA;H  DZP&#xA;S  DZP&#xA;Au SZP&#xA;%endblock PAO.BasisSizes&#xA;&#xA;PAO.EnergyShift  0.01 eV&#xA;&#xA;==================================================&#xA;==================================================&#xA;# K-points&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA;3   0   0      0.0&#xA;0   3   0      0.0&#xA;0   0   100    0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;==================================================&#xA;==================================================&#xA;# UNIT CELL AND ATOMIC POSITIONS&#xA;&#xA;# UNIT CELL&#xA;&#xA;%block LatticeVectors&#xA;18.00000    00.00000    0.000000&#xA;00.00000    18.00000    0.000000&#xA;00.00000    00.00000    42.00000&#xA;%endblock LatticeVectors&#xA;&#xA;# Atomic coordinates&#xA;NumberOfAtoms 168&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;    1.705900000000      4.978000000000     -2.885900000000 4&#xA;    3.266300000000      5.634400000000     -0.551300000000 4&#xA;    3.440400000000      7.281600000000     -2.912000000000 4&#xA;    4.568100000000      4.627500000000     -2.919400000000 4&#xA;    5.000900000000      7.938100000000     -0.577400000000 4&#xA;    5.175000000000      9.585300000000     -2.938000000000 4&#xA;    6.128600000000      5.283900000000     -0.584800000000 4&#xA;    6.302600000000      6.931200000000     -2.945500000000 4&#xA;    7.430300000000      4.277000000000     -2.952900000000 4&#xA;    6.735400000000     10.241800000000     -0.603400000000 4&#xA;    6.909500000000     11.889000000000     -2.964100000000 4&#xA;    7.863100000000      7.587600000000     -0.610900000000 4&#xA;    8.037200000000      9.234800000000     -2.971500000000 4&#xA;    8.990800000000      4.933400000000     -0.618300000000 4&#xA;    9.164900000000      6.580700000000     -2.979000000000 4&#xA;   10.292500000000      3.926500000000     -2.986400000000 4&#xA;    8.470000000000     12.545400000000     -0.629500000000 4&#xA;    8.644100000000     14.192700000000     -2.990100000000 4&#xA;    9.597700000000      9.891300000000     -0.636900000000 4&#xA;    9.771700000000     11.538500000000     -2.997600000000 4&#xA;   10.725300000000      7.237100000000     -0.644400000000 4&#xA;   10.899400000000      8.884300000000     -3.005000000000 4&#xA;   11.853000000000      4.582900000000     -0.651800000000 4&#xA;   12.027100000000      6.230200000000     -3.012500000000 4&#xA;   13.154700000000      3.576000000000     -3.019900000000 4&#xA;   10.204600000000     14.849100000000     -0.655500000000 4&#xA;   10.378600000000     16.496300000000     -3.016200000000 4&#xA;   11.332200000000     12.194900000000     -0.663000000000 4&#xA;   11.506300000000     13.842200000000     -3.023600000000 4&#xA;   12.459900000000      9.540800000000     -0.670400000000 4&#xA;   12.634000000000     11.188000000000     -3.031100000000 4&#xA;   13.587500000000      6.886600000000     -0.677900000000 4&#xA;   13.761600000000      8.533800000000     -3.038500000000 4&#xA;   14.715200000000      4.232400000000     -0.685300000000 4&#xA;   14.889300000000      5.879700000000     -3.046000000000 4&#xA;   16.017000000000      3.225500000000     -3.053400000000 4&#xA;    4.826800000000      6.290800000000      1.783300000000 4&#xA;    6.387300000000      6.947300000000      4.117800000000 4&#xA;    6.561400000000      8.594500000000      1.757200000000 4&#xA;    7.947800000000      7.603700000000      6.452400000000 4&#xA;    8.121800000000      9.251000000000      4.091800000000 4&#xA;    7.689000000000      5.940400000000      1.749700000000 4&#xA;    9.249500000000      6.596800000000      4.084300000000 4&#xA;    8.295900000000     10.898200000000      1.731100000000 4&#xA;    9.682300000000      9.907400000000      6.426400000000 4&#xA;    9.856400000000     11.554600000000      4.065700000000 4&#xA;    9.423600000000      8.244000000000      1.723700000000 4&#xA;    9.508200000000      8.260200000000      8.787000000000 4&#xA;   10.810000000000      7.253200000000      6.418900000000 4&#xA;   10.984100000000      8.900500000000      4.058300000000 4&#xA;   10.551300000000      5.589900000000      1.716200000000 4&#xA;   12.111700000000      6.246300000000      4.050800000000 4&#xA;   10.030500000000     13.201900000000      1.705100000000 4&#xA;   11.158100000000     10.547700000000      1.697600000000 4&#xA;   12.285800000000      7.893500000000      1.690200000000 4&#xA;   13.413500000000      5.239400000000      1.682700000000 4&#xA;   ...... some coordintaes are removed because of limit in characters&#xA;%endblock AtomicCoordinatesAndAtomicSpecies  &#xA;==================================================&#xA;==================================================&#xA;# General variables&#xA;&#xA;PAO.SplitTailNorm  .true.&#xA;PAO.SplitNorm   0.15&#xA;ElectronicTemperature  300 K &#xA;MeshCutoff           150. Ry&#xA;xc.functional         GGA           # Exchange-correlation functional&#xA;xc.authors            PBE&#xA;SpinPolarized .false.&#xA;SolutionMethod transiesta&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SCF variables&#xA;&#xA;DM.MixSCF1   T&#xA;MaxSCFIterations      1000          &#xA;SCF.MixAfterConvergence  .false.&#xA;NeglNonOverlapInt     .true.       &#xA;DM.MixingWeight       0.01          &#xA;DM.Tolerance          1.d-5        &#xA;DM.UseSaveDM         .true.          &#xA;DM.Require.Energy.Convergence  .true.&#xA;DM.NumberPulay         5&#xA;Diag.DivideAndConquer  no&#xA;Diag.ParallelOverK     .true.&#xA;UseSaveData         .true.&#xA;LongOutput          .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;# MD variables&#xA;&#xA;MD.TypeOfRun       CG&#xA;MD.NumCGsteps      00&#xA;MD.MaxCGDispl    0.2 Ang&#xA;MD.UseSaveCG      .true.                 &#xA;MD.MaxForceTol   0.02 eV/Ang&#xA;MD.MaxStressTol  0.01 eV/Ang**3&#xA;MD.Targetpressure  0 GPa&#xA;WriteMDHistory   .true.&#xA;WriteMDXMol      .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;# Output variables&#xA;&#xA;WriteMullikenPop                1&#xA;WriteBands                      .true.&#xA;SaveRho                         .true.&#xA;SaveDeltaRho                    .true.&#xA;SaveHS                          .true.&#xA;SaveElectrostaticPotential      .true. &#xA;SaveTotalPotential              .true.&#xA;WriteCoorXmol                   .true.&#xA;WriteMDXmol                     .true.&#xA;WriteMDhistory                  .true.&#xA;WriteEigenvalues                .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;# Transiesta&#xA;&#xA;# Bias voltage&#xA;TS.Voltage 0.0 eV&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;&#xA;TS.Elecs.Bulk true&#xA;TS.Elecs.DM.Update none&#xA;TS.Elecs.GF.ReUse false&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&#xA;%block TS.Elec.Left&#xA;  TSHS ./leftAu.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a3&#xA;  elec-pos begin 1&#xA;  used-atoms 36&#xA;%endblock TS.Elec.Left&#xA;&#xA;%block TS.Elec.Right&#xA;  TSHS ./rightAu.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir  +a3&#xA;  elec-pos end -1&#xA;  used-atoms 36&#xA;%endblock TS.Elec.Right&#xA;&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.c-Left&#xA;  part circle&#xA;   from   -40.00000 eV + V/2 to -10. kT + V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Left&#xA;%block TS.Contour.t-Left&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Left&#xA;%block TS.Contour.c-Right&#xA;  part circle&#xA;   from   -40.00000 eV - V/2 to -10. kT - V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Right&#xA;%block TS.Contour.t-Right&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Right&#xA;&#xA;TS.Contours.nEq.Eta 0.0001 eV&#xA;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;    delta 0.01 eV&#xA;     method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA;&#xA;TBT.DOS.A.All T&#xA;TS.SolutionMethod btd&#xA;==================================================&#xA;==================================================&#xA;&#xA;scattering region output:&#xA;siesta: Automatic unit cell vectors (Ang):&#xA;siesta:   26.101199    0.000000    0.000000&#xA;siesta:    0.000000   25.083477    0.000000&#xA;siesta:    0.000000    0.000000   52.409897&#xA;&#xA;siesta: System type = molecule  &#xA;&#xA;initatomlists: Number of atoms, orbitals, and projectors:    168  1608  2912&#xA;&#xA;coxmol: Writing XMOL coordinates into file CpolyPTN2.xyz                                                       &#xA;&#xA;siesta: ******************** Simulation parameters ****************************&#xA;siesta:&#xA;siesta: The following are some of the parameters of the simulation.&#xA;siesta: A complete list of the parameters used, including default values,&#xA;siesta: can be found in file out.fdf&#xA;siesta:&#xA;redata: Spin configuration                          = none&#xA;redata: Number of spin components                   = 1&#xA;redata: Time-Reversal Symmetry                      = T&#xA;redata: Spin spiral                                 = F&#xA;redata: Long output                                 =   T&#xA;redata: Number of Atomic Species                    =        4&#xA;redata: Charge density info will appear in .RHO file&#xA;redata: Write Mulliken Pop.                         = Atomic and Orbital charges&#xA;redata: Matel table size (NRTAB)                    =     1024&#xA;redata: Mesh Cutoff                                 =   150.0000 Ry&#xA;redata: Net charge of the system                    =     0.0000 |e|&#xA;redata: Min. number of SCF Iter                     =        0&#xA;redata: Max. number of SCF Iter                     =     1000&#xA;redata: SCF convergence failure will abort job&#xA;redata: SCF mix quantity                            = Hamiltonian&#xA;redata: Mix DM or H after convergence               =   F&#xA;redata: Recompute H after scf cycle                 =   F&#xA;redata: Mix DM in first SCF step                    =   T&#xA;redata: Write Pulay info on disk                    =   F&#xA;redata: New DM Occupancy tolerance                  = 0.000000000001&#xA;redata: No kicks to SCF&#xA;redata: DM Mixing Weight for Kicks                  =     0.5000&#xA;redata: Require Harris convergence for SCF          =   F&#xA;redata: Harris energy tolerance for SCF             =     0.000100 eV&#xA;redata: Require DM convergence for SCF              =   T&#xA;redata: DM tolerance for SCF                        =     0.000010&#xA;redata: Require EDM convergence for SCF             =   F&#xA;redata: EDM tolerance for SCF                       =     0.001000 eV&#xA;redata: Require H convergence for SCF               =   T&#xA;redata: Hamiltonian tolerance for SCF               =     0.001000 eV&#xA;redata: Require (free) Energy convergence for SCF   =   T&#xA;redata: (free) Energy tolerance for SCF             =     0.000100 eV&#xA;redata: Using Saved Data (generic)                  =   T&#xA;redata: Use continuation files for DM               =   T&#xA;redata: Neglect nonoverlap interactions             =   T&#xA;redata: Method of Calculation                       = Transiesta&#xA;redata: Fix the spin of the system                  =   F&#xA;redata: Dynamics option                             = Single-point calculation&#xA;mix.SCF: Pulay mixing                            = Pulay&#xA;mix.SCF:    Variant                              = stable&#xA;mix.SCF:    History steps                        = 5&#xA;mix.SCF:    Linear mixing weight                 =     0.010000&#xA;mix.SCF:    Mixing weight                        =     0.010000&#xA;mix.SCF:    SVD condition                        = 0.1000E-07&#xA;redata: Save all siesta data in one NC              =   F&#xA;&#xA;&#xA;siesta: k-grid: Number of k-points =   455&#xA;siesta: k-grid: Cutoff (effective) =    37.625 Ang&#xA;siesta: k-grid: Supercell and displacements&#xA;siesta: k-grid:    3   0   0      0.000&#xA;siesta: k-grid:    0   3   0      0.000&#xA;siesta: k-grid:    0   0 100      0.000&#xA;&#xA;diag: Algorithm                                     = Expert&#xA;diag: Parallel over k                               =   T&#xA;diag: Use parallel 2D distribution                  =   T&#xA;diag: Parallel block-size                           = 24&#xA;diag: Parallel distribution                         =     4 x     6&#xA;diag: Used triangular part                          = Lower&#xA;diag: Absolute tolerance                            =  0.100E-15&#xA;diag: Orthogonalization factor                      =  0.100E-05&#xA;diag: Memory factor                                 =  1.0000&#xA;&#xA; Kpoints in:            6 . Kpoints trimmed:            5&#xA;&#xA;transiesta: ts_k-point coordinates (Bohr**-1) and weights:&#xA;transiesta:    1   -0.042462    0.000000    0.000000       0.222222&#xA;transiesta:    2    0.000000    0.000000    0.000000       0.111111&#xA;transiesta:    3   -0.042462    0.044185    0.000000       0.222222&#xA;transiesta:    4    0.000000    0.044185    0.000000       0.222222&#xA;transiesta:    5    0.042462    0.044185    0.000000       0.222222&#xA;&#xA;transiesta: k-grid: Number of Green function k-points =     5&#xA;transiesta: k-grid: Supercell and displacements&#xA;transiesta: k-grid:    3   0   0      0.000&#xA;transiesta: k-grid:    0   3   0      0.000&#xA;transiesta: k-grid:    0   0   1      0.000&#xA;Electrode: Left is a Gamma-only calculation, this is not feasible.&#xA;Erroneous electrode setup, check out-put&#xA;Stopping Program from Node:   19&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6561" LastEditorUserId="887" LastEditDate="2023-01-26T13:32:00.063" LastActivityDate="2023-01-26T13:32:00.063" Title="Gamma-only error for electrode in a device calculation" Tags="|siesta|k-points|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10242" PostTypeId="2" ParentId="10241" CreationDate="2023-01-18T07:55:14.220" Score="4" Body="&lt;p&gt;This error occurs if the electrode calculation was done &lt;em&gt;only&lt;/em&gt; at the Gamma-point.&lt;/p&gt;&#xA;&lt;p&gt;So I suspect that the flags you say you have put in the electrode calculation has not been accepted, the easiest way to check is to read the output of the electrode calculation. It should clearly specify the k-grid specification.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that there is no lattice constant definitions, and so the lattice-vectors turn to 0.  When the lattice vectors are 0, Siesta will automatically calculate the smallest unit-cell that ensures no supercell couplings, effectively doing a molecule calculation.&lt;/p&gt;&#xA;&lt;p&gt;This can be seen from your output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;siesta: Automatic unit cell vectors (Ang):&#xA;siesta:   26.101199    0.000000    0.000000&#xA;siesta:    0.000000   25.083477    0.000000&#xA;siesta:    0.000000    0.000000   52.409897&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is clearly &lt;em&gt;not&lt;/em&gt; what you put in the file.&lt;/p&gt;&#xA;&lt;p&gt;The reason for 4.0 to &lt;em&gt;work&lt;/em&gt; is that it does not check for supercell connections, it only checks that the k-grid used is not the Gamma point. So any calculations with 4.0 and older would result in an electrode self-energy that is the molecule self-energy, not a semi-infinite electrode! Thus any calculation with 4.0 and this electrode would be wrong!&lt;/p&gt;&#xA;&lt;p&gt;Please always check your output file to assert that the options you specify are correctly understood.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, your input lattice vectors like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block LatticeVectors&#xA;    18.00000    18.00000    18.00000&#xA;    18.00000    18.00000    18.00000&#xA;    18.00000    18.00000    18.00000&#xA;%endblock LatticeVectors&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;are not viable lattice vectors. Please adjust them appropriately!&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-01-26T11:17:34.187" LastActivityDate="2023-01-26T11:17:34.187" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10243" PostTypeId="2" ParentId="10240" CreationDate="2023-01-18T09:36:25.060" Score="3" Body="&lt;p&gt;In versions &amp;lt;= 4.0 the old flags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TS.biasContour.Eta&#xA;TS.biasContour.NumPoints&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;were used to determine the imaginary &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; of the Green function calculation and the number of points in the bias-window, respectively.&lt;br /&gt;&#xA;As mentioned having a fixed &lt;code&gt;NumPoints&lt;/code&gt; in the input was non-ideal since for different bias one needed to manually change the &lt;code&gt;NumPoints&lt;/code&gt; flag to achieve the same accuracy in the integration.&lt;/p&gt;&#xA;&lt;p&gt;This was changed in versions &amp;gt;= 4.1 to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;  from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;  delta    0.026 eV&#xA;  method mid-rule&#xA;%endblock&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that the key-point in this block is the &lt;code&gt;delta 0.026 eV&lt;/code&gt; which tells TranSiesta to always use a splitting of 26 meV between consecutive energy points. Therefore in 4.1 and later one need not change the input file for different bias points. It will always use the same energy spacing as defined by &lt;code&gt;delta&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Regarding TBtrans. Since no integration is done &lt;em&gt;in the code&lt;/em&gt;, the new way (&amp;gt;= 4.1) of doing it simply allows more flexibility, i.e. to generate two different ranges of energy grids:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TBT.Contours&#xA; first&#xA; second&#xA;%endblock&#xA;%block TBT.Contour.first&#xA;  part line&#xA;   from   0. eV to 1. eV&#xA;    delta    0.001 eV&#xA;     method mid-rule&#xA;%endblock&#xA;%block TBT.Contour.second&#xA;  part line&#xA;    from -2. eV to -1. eV&#xA;     delta 0.001 eV&#xA;      method mid-rule&#xA;%endblock&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above could not be done in &amp;lt;= 4.0.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-01-18T09:36:25.060" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10244" PostTypeId="1" CreationDate="2023-01-18T09:30:30.160" Score="5" ViewCount="191" Body="&lt;p&gt;With the Gaussian quantum chemistry program, I usually generate formatted checkpoint files (.fchk) that I then use to perform different atom-in-molecule analyses. I am currently facing the need of using Molpro as quantum chemistry program since it has specific features that I want to exploit. The problem is that I am not sure how to obtain a proper file (analogue to the .fchk one) from which I can run my atom-in-molecule analyses. I expect that the generation of &amp;quot;cube&amp;quot; files may be a solution but I fear that this may increase the noise in the AIM analysis. Can you give me any advice?&lt;/p&gt;&#xA;&lt;p&gt;PS: The AIM partitioning is done with HORTON in case this may give you more info&lt;/p&gt;&#xA;" OwnerUserId="410" OwnerDisplayName="wolfram" LastEditorUserId="5" LastEditDate="2023-01-18T16:27:49.617" LastActivityDate="2023-01-18T16:27:49.617" Title="MOLPRO: is there an analogue of the Gaussian FCHK file?" Tags="|software|quantum-chemistry|molpro|atoms-in-molecules|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10245" PostTypeId="2" ParentId="10244" CreationDate="2023-01-18T10:19:33.413" Score="5" Body="&lt;p&gt;Following the HORTON information webpage about supported &lt;a href=&quot;https://theochem.github.io/horton/2.1.1/tech_ref_file_formats.html#ref-file-formats&quot; rel=&quot;noreferrer&quot;&gt;data file formats&lt;/a&gt; from section &lt;em&gt;&lt;strong&gt;2.4.3. Wavefunction formats (using a Gaussian basis set)&lt;/strong&gt;&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;2.4.3.2. The .molden format&#xA;Load  Yes&#xA;Dump  Yes&#xA;Recognized by     File extension .molden&#xA;Interoperation    Molpro, Orca, PSI4, Molden, Turbomole&#xA;Always loading    coordinates numbers obasis exp_alpha pseudo_numbers signs&#xA;loading if present    title exp_beta&#xA;Derived when loading  natom&#xA;Required for dumping  coordinates numbers obasis exp_alpha&#xA;Optional for dumping  title exp_beta pseudo_numbers&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Now you need to setup MOLPRO to export the wavefunctions in &lt;code&gt;.molden&lt;/code&gt; format.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-18T10:19:33.413" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10246" PostTypeId="2" ParentId="10238" CreationDate="2023-01-18T15:17:31.333" Score="4" Body="&lt;ol&gt;&#xA;&lt;li&gt;You must be able to generate a uniform grid of kpoints using the utility kpoints.x that is available with the standard quantum espresso installation. This will give you a file containing the kpoints with the required symmetry.&lt;/li&gt;&#xA;&lt;li&gt;The crystal coordinates are defined in such a way that multiplying them with the cell vectors would give you the Cartesian coordinates. This the reason why crystal coordinates are in the range [0,1].&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-01-18T15:17:31.333" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10247" PostTypeId="1" CreationDate="2023-01-18T16:16:57.593" Score="4" ViewCount="104" Body="&lt;p&gt;I am attempting to implement an algorithm for transition state finding (in Python, but that's not important). The algorithm is called BITSS (Binary Image-pair Transition State Search). It defines a composite potential from reactant and product structures:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_\mathrm{BITSS} = E_1 + E_2 + k_e(E_1-E_2)^2 + k_d(d-d_i)^2$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where 1 and 2 are reactant and product respectively. &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; defines the molecular energy and d is the distance between them (defined as RMSD or something similar). The &lt;span class=&quot;math-container&quot;&gt;$d_i$&lt;/span&gt; is the target distance criteria. &lt;strong&gt;Then the composite potential is minimized across all Cartesian coordinates of both images, while the distance criteria is tightened in steps&lt;/strong&gt;. This essentially means that there is an artificial force that pushes the reactant and product towards each other (from the distance term), while not allowing one to jump over the barrier (due to the energy constraint that ensures the two are at similar energies). At convergence, both structures (images) reach the transition state.&lt;/p&gt;&#xA;&lt;p&gt;Now, in the paper, they only provide the equation for BITSS energy. I have been able to derive an analytic expression for the BITSS gradient myself, from the individual molecular gradients. However, for a BFGS or RFO like optimisation, I also need the Hessian of the BITSS energy, which has a very complicated expression.&lt;/p&gt;&#xA;&lt;p&gt;I remember reading somewhere, that if the optimisation is started with an identity matrix (1's on diagonal and 0 elsewhere) as Hessian guess, and then BFGS hessian updates are performed, then the Hessian will automatically get closer to the real value due to getting the gradient information in BFGS update.&lt;/p&gt;&#xA;&lt;p&gt;Is this true? Is it fine to start an optimisation with an identity matrix Hessian guess and then rely on the Hessian update procedure? I am not optimising a molecule per se, but a potential defined from two molecules. I am using Cartesian coordinates throughout.&lt;/p&gt;&#xA;&lt;p&gt;(Also, I have tried gradient descent steps, but they are too slow to converge)&lt;/p&gt;&#xA;&lt;p&gt;Reference - Samuel J. Avis, Jack R. Panter, and Halim Kusumaatmaja&#xA;, &amp;quot;A robust and memory-efficient transition state search method for complex energy landscapes&amp;quot;, J. Chem. Phys. 157, 124107 (2022) &lt;a href=&quot;https://doi.org/10.1063/5.0102145&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/5.0102145&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-01-18T21:21:11.180" LastActivityDate="2023-02-04T00:35:06.847" Title="Is it ok to start from an identity matrix Hessian guess for optimisation?" Tags="|geometry-optimization|optimization|transition-state|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10248" PostTypeId="1" CreationDate="2023-01-18T17:55:40.040" Score="3" ViewCount="51" Body="&lt;p&gt;VMD has a nanotube builder that I can use to build CNT and then using topotools I am able to produce the data file for LAMMPS. For my specific research I need to create a fake CNT with triangular lattice instead of hegxagonal. I can create that with mathematica but it explodes and I guess it is because I do not have the dihedral and other angle informations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is if you know of any (preferably free) software that I can use to create my own specific lattice shape nanotube and get the data file as an output?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you so much&lt;/p&gt;&#xA;" OwnerUserId="4924" LastEditorUserId="5" LastEditDate="2023-01-19T21:24:08.723" LastActivityDate="2023-01-19T21:24:15.410" Title="What package do I use to model a material and get the LAMMPS data file as an output?" Tags="|software-recommendations|lammps|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10249" PostTypeId="1" AcceptedAnswerId="10255" CreationDate="2023-01-18T22:17:26.580" Score="3" ViewCount="693" Body="&lt;p&gt;I'm trying to compute the free energy of solvation of a molecule in gaussian09 using the continuum solvation model, but I am haveing difficulties, I don't  know how to do it and gaussian manual does not help me. Someone has any input to me see the comand lines?&lt;/p&gt;&#xA;" OwnerUserId="6572" OwnerDisplayName="AlfredV" LastEditorUserId="4895" LastEditDate="2023-01-22T19:48:44.343" LastActivityDate="2023-01-22T19:48:44.343" Title="How to compute free energy for solvation using gaussian09?" Tags="|quantum-chemistry|gaussian|thermodynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10250" PostTypeId="1" CreationDate="2023-01-19T07:47:58.270" Score="1" ViewCount="31" Body="&lt;p&gt;Like the title says, in TranSiesta I can easily calculate the transmission curves. I know that it is related to the conductance. However, how can I calculate the conductance with tbtrans?&lt;/p&gt;&#xA;&lt;p&gt;Moreover, to calculate the Seeback coefficient, one should modify the T and extrapolate the value from -dV/dT. Can someone explain better how to perform calculations with gradients of temperature?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-01-19T09:19:25.567" LastActivityDate="2023-01-19T09:19:25.567" Title="Conductance and Seeback coefficient calculations with tbtrans" Tags="|siesta|electronic-transport|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T21:50:00.943" ContentLicense="CC BY-SA 4.0" />
  <row Id="10251" PostTypeId="1" CreationDate="2023-01-19T08:33:05.370" Score="3" ViewCount="4433" Body="&lt;p&gt;I want to create a set of lists using python, where the list names would be like:&#xA;a1 = []&#xA;a2 = []&#xA;a3 = []&#xA;.&#xA;.&#xA;.&#xA;a100 = []&#xA;And I would like to iteratively populate each list using python. Any idea on how to do that?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Actually I was trying to code something like below:&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;a1 = []&#xA;a2 = []&#xA;a3 = []&#xA;.&#xA;.&#xA;.&#xA;a100 = []&#xA;&#xA;for line in inp1:&#xA;    arr = line.split()&#xA;    a1.append(arr[1])&#xA;    a2.append(arr[2])&#xA;    a3.append(arr[3])&#xA;    .&#xA;    .&#xA;    .&#xA;    a100.append(arr[100])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;I wanted any idea on how can this be done with multiple lists? my file has 101 columns. I want to put every column in a list, then want to perform some analysis.&lt;/p&gt;&#xA;" OwnerUserId="4704" LastEditorUserId="7" LastEditDate="2023-01-20T14:12:21.913" LastActivityDate="2023-01-20T14:12:21.913" Title="Creating lists with variable names in python" Tags="|python|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10252" PostTypeId="1" AcceptedAnswerId="10259" CreationDate="2023-01-19T09:13:26.953" Score="7" ViewCount="1135" Body="&lt;p&gt;Lets consider the following code which uses the &lt;a href=&quot;https://pyscf.org/user/gto.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mole object&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf&#xA;mol = pyscf.M(&#xA;    atom = '''&#xA;        O&#xA;        H  1  0.9576257&#xA;        H  1  0.9576257  2 104.51&#xA;    '''&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there an easy way to print the chemical formula: &lt;code&gt;H2O&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;In the above-linked documentation page, I couldn't find any example that resembles this type of feature, and when I run a PySCF &lt;code&gt;kernel()&lt;/code&gt; the printout doesn't ever say &lt;code&gt;H2O&lt;/code&gt; so perhaps PySCF doesn't &amp;quot;know&amp;quot; that the molecule can be called &lt;code&gt;H2O&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I searched on Google for &amp;quot;chemical formula from ZMAT&amp;quot; and some variants of that search phrase, without any success. I understand that things can get quite complicated when there's even just a few atoms, but for atoms, diatomics, and millions of polyatomics, it doesn't seem unreasonable to have a &lt;strong&gt;utility that can print or at least guess a chemical formula, especially if the utility were to use a database of known molecules to assist it.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there a simple way to print the formula from the ZMAT or XYZ file that would work with PySCF?&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-19T19:31:18.413" LastActivityDate="2023-01-20T09:09:50.980" Title="Print chemical formula from list of atoms in Python?" Tags="|software|python|pyscf|geometry|software-online-tools|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10253" PostTypeId="2" ParentId="6403" CreationDate="2023-01-19T09:51:33.383" Score="1" Body="&lt;p&gt;there is this D3Q package that works seamlessly with Quantum Espresso.&lt;/p&gt;&#xA;&lt;p&gt;I used it in several papers such as PRB 98, 220301(R) (2018). Easier than the QE-phonopy-shengbte chain. Quite demanding computationally, though.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://anharmonic.github.io&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://anharmonic.github.io&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;G Fugallo et al., PRB 88, 045430 (2013)&lt;/p&gt;&#xA;" OwnerUserId="6571" LastActivityDate="2023-01-19T09:51:33.383" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10254" PostTypeId="2" ParentId="10251" CreationDate="2023-01-19T10:47:46.833" Score="5" Body="&lt;p&gt;Use dictionaries&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;&#xA;rows = [[1,2,3],[1,2,3],[1,2,3]]&#xA;dict_rows = {}&#xA;&#xA;for idx, i in enumerate(rows):&#xA;   dict_rows[f'a{idx}'] = i&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output of this little script is:&#xA;&lt;code&gt;{'a0': [1, 2, 3], 'a1': [1, 2, 3], 'a2': [1, 2, 3]}&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Dictionaries are iterable via keys.&lt;/p&gt;&#xA;&lt;p&gt;Note: maybe next time try to give some more info on the script. Otherwise, it's a bit difficult to understand the question. I've supposed you have a list of lists and you want to &amp;quot;give them a name&amp;quot;. If not, let me know&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit&lt;/strong&gt;&#xA;To create a dataframe from a table instead you can do&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import pandas as pd&#xA;&#xA;rows = [...] # or you can obtain from a sting with file.striplines()&#xA;d = {}&#xA;for line in rows:&#xA;    for idx, data in enumerate(line.split()):&#xA;        if f'a{idx}' not in d: &#xA;            d[f'a{idx}'] = []&#xA;        d[f'a{idx}'].append(data)&#xA;df = pd.DataFrame.from_dict(d)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="4895" LastEditDate="2023-01-19T15:31:13.543" LastActivityDate="2023-01-19T15:31:13.543" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10255" PostTypeId="2" ParentId="10249" CreationDate="2023-01-19T11:29:06.233" Score="4" Body="&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$\delta G_\text{solv}$&lt;/span&gt; can be computed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\delta G_\text{solv}=E_\text{opt in solv} - E_\text{opt in GP}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_\text{opt in solv}$&lt;/span&gt; is the energy of the optimised geometry using the &lt;code&gt;scrf=(METHOD,solvent=SOLVENT)&lt;/code&gt; keyword, and &lt;span class=&quot;math-container&quot;&gt;$E_\text{opt in GP}$&lt;/span&gt; is the energy of the optimised geometry in gas-phase.&lt;/p&gt;&#xA;&lt;p&gt;This requires the approximation that the thermochemical energy correction (arising from the hessian diagonalization) is equal in both geometries, which can be used for most of the cases.&lt;/p&gt;&#xA;&lt;p&gt;There are different methods to simulate the electrostatic potential of the solvents: SMD, PCM (in two versions), ALPB (not present neither in G09 nor G16), and GBSA (not present neither in G09 nor G16).&#xA;To choose among them have a little benchmark to understand which one helps you describe at its best the system solvation energy.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2023-01-19T11:29:06.233" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10256" PostTypeId="1" AcceptedAnswerId="10293" CreationDate="2023-01-19T12:04:57.170" Score="3" ViewCount="145" Body="&lt;p&gt;I calculated the Transmission curves and the Density of States using TBTrans. In particular, if I have pristine graphene (just for the sake of the example), I obtain as Transmission curve and DOS respectively:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/bfpyN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bfpyN.png&quot; alt=&quot;Transmission curve at V=0&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3mDi3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3mDi3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How come the DOS calculated by TBTrans has these peaks while the Transmission looks perfectly fine?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-01-24T19:35:35.790" LastActivityDate="2023-01-25T08:25:10.300" Title="DOS calculation with TBTrans" Tags="|siesta|density-of-states|electronic-transport|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10258" PostTypeId="2" ParentId="10252" CreationDate="2023-01-19T16:39:37.140" Score="7" Body="&lt;p&gt;The tricky part comes if you have multiple fragments and want disconnected formulas. But in general, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Chemical_formula#Hill_system&quot; rel=&quot;noreferrer&quot;&gt;Hill system&lt;/a&gt; for chemical formulas is used, and available in Open Babel, RDKit, etc.&lt;/p&gt;&#xA;&lt;p&gt;As indicated in the comments, you'd just iterate through the atoms and count the number of each. For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# this is pseudocode&#xA;elements = {} # amend the end point if you don't want to count transuranic&#xA;for atom in mol.elements:&#xA;   elements{atom} += 1&#xA;&#xA;# print in Hill order&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You'll want to make sure the C and H elements come first if they exist, otherwise it's in sorted alphabetical order.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-01-19T16:39:37.140" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10259" PostTypeId="2" ParentId="10252" CreationDate="2023-01-19T20:20:50.997" Score="3" Body="&lt;p&gt;I like &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10258/5&quot;&gt;Geoff's proposal&lt;/a&gt; to use the Hill system. Here's an implementation.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import collections&#xA;&#xA;def to_hill_notation(elements):&#xA;    c = collections.Counter(elements)&#xA;    if &amp;quot;C&amp;quot; in c:&#xA;        #C and H come first&#xA;        priority = lambda x: -1 if x in &amp;quot;CH&amp;quot; else 0&#xA;    else:&#xA;        #no special priority&#xA;        priority = lambda x: 0&#xA;    sorted_keys = sorted(c.keys(), key=lambda element: (priority(element), element))&#xA;    result = []&#xA;    for element in sorted_keys:&#xA;        amount = c[element]&#xA;        if amount == 1:&#xA;            result.append(element)&#xA;        else:&#xA;            result.append(element + str(amount))&#xA;    return &amp;quot;&amp;quot;.join(result)&#xA;&#xA;print(to_hill_notation(['O', 'H', 'H'])) #H20&#xA;print(to_hill_notation(['C', 'H', 'C', 'C', 'H', 'C', 'H', 'H', 'H', 'C', 'H', 'C'])) #C6H6&#xA;print(to_hill_notation(['O', 'H', 'O', 'H', 'H', 'C', 'O', 'C', 'C', 'H', 'H', 'O', 'C', 'H', 'H', 'O', 'H', 'O', 'O', 'C', 'H', 'H', 'H', 'C', 'H', 'C', 'H', 'C', 'O', 'C', 'H', 'H', 'C', 'H', 'C', 'H', 'H', 'H', 'O', 'O', 'H', 'O', 'H', 'C', 'H'])) #C12H22O11&#xA;print(to_hill_notation(['Cl', 'H', 'C', 'H', 'C', 'H'])) #C2H3Cl&#xA;print(to_hill_notation(['O', 'O', 'O', 'O', 'Fe', 'O', 'O', 'O', 'O', 'Fe', 'S', 'O', 'S', 'O', 'S', 'O', 'O'])) #Fe2O12S3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can't pass a Mole object to the function directly, but you should be able to get a list of the Mole's elements using &lt;code&gt;mol.elements&lt;/code&gt;. So the call would look something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(to_hill_notation(mol.elements))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6573" LastEditorUserId="5" LastEditDate="2023-01-19T20:46:07.553" LastActivityDate="2023-01-19T20:46:07.553" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10260" PostTypeId="2" ParentId="10252" CreationDate="2023-01-19T20:50:51.707" Score="2" Body="&lt;p&gt;I think &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10259/6574&quot;&gt;Kevin's answer&lt;/a&gt; is stellar (both in terms of understanding atoms and formulas), and the recommendation and hints from &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10258/6574&quot;&gt;Geoff's answer&lt;/a&gt; helped a lot in putting things into perspective, so here is the answer from a naive perspective:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;atoms_string = '''&#xA;        O&#xA;        H  1  0.9576257&#xA;        H  1  0.9576257  2 104.51&#xA;    '''&#xA;&#xA;elements = {}&#xA;for line in atoms_string.strip().split(&amp;quot;\n&amp;quot;):&#xA;    element = line.split()[0]&#xA;    if element in elements:&#xA;        elements[element] += 1&#xA;    else:&#xA;        elements[element] = 1&#xA;&#xA;formula = ''.join(f'{element}{count}' for element, count in elements.items())&#xA;print(formula)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which print &lt;code&gt;O1H2&lt;/code&gt;. I think the OP mentioned they would prefer it output &lt;code&gt;H2O&lt;/code&gt; in this case, but I don't know much about atoms and whatnot, compared to most people here...so this is just a naive implementation. It is however compact(?), but if you want better formatting for the output, Kevin's answer is a better fit.&lt;/p&gt;&#xA;&lt;p&gt;Note that the above depends heavily on the formatting of its input, and it may not work on different inputs.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: Still don't know what I'm doing, but the following output &lt;code&gt;H2O&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;atoms_string = '''&#xA;        O&#xA;        H  1  0.9576257&#xA;        H  1  0.9576257  2 104.51&#xA;    '''&#xA;&#xA;elements = {}&#xA;for line in atoms_string.strip().split(&amp;quot;\n&amp;quot;):&#xA;    element = line.split()[0]&#xA;    if element in elements:&#xA;        elements[element] += 1&#xA;    else:&#xA;        elements[element] = 1&#xA;&#xA;hill_order = sorted(elements.items(), key=lambda x: x[0])&#xA;hill_order = sorted(hill_order, key=lambda x: x[1], reverse=True)&#xA;&#xA;formula = ''.join(f'{element}{count if count &amp;gt; 1 else &amp;quot;&amp;quot;}' for element, count in hill_order)&#xA;print(formula)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried to implement Hill ordering and remove/ignore count when they were equal to 1. I don't think this will work on other inputs, but for the example above, this works.&lt;/p&gt;&#xA;" OwnerUserId="6574" LastEditorUserId="6574" LastEditDate="2023-01-20T09:09:50.980" LastActivityDate="2023-01-20T09:09:50.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10262" PostTypeId="2" ParentId="10248" CreationDate="2023-01-19T21:24:15.410" Score="3" Body="&lt;p&gt;First, can you clarify what you mean by &amp;quot;it explodes&amp;quot;? Have you ensured that there are no overlaps in your simulation and that the force-field parameters are correct?&lt;/p&gt;&#xA;&lt;p&gt;Moltemplate is another &lt;strike&gt;free, open source&lt;/strike&gt; powerful program for preparing LAMMPS datafiles. There is an extensive set of tutorials including one on &lt;a href=&quot;https://github.com/jewettaij/moltemplate/tree/master/examples/all_atom/force_field_explicit_parameters/nanotube+water#nanotube-water-capillary-system&quot; rel=&quot;nofollow noreferrer&quot;&gt;nanotubes&lt;/a&gt;. Moltemplate uses &lt;code&gt;.LT&lt;/code&gt; files that are basically the pieces that construct the system. Then using &lt;code&gt;system.lt&lt;/code&gt; file and with different options, you can create a LAMMPS datafile along with other optional input files. My suggestion: Try to read the actually very well-written manual. Start with a few simple examples found in examples folder and then try to find similar examples to your system.&lt;/p&gt;&#xA;" OwnerUserId="5483" LastActivityDate="2023-01-19T21:24:15.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10263" PostTypeId="2" ParentId="10215" CreationDate="2023-01-19T21:47:56.993" Score="4" Body="&lt;p&gt;Thank you Andrea Pellegrini, the solution for me was to use the partial hess flag with the number of atoms that I want to exclude of the vibrational calculation, like the exemple below, for the 21 first atoms.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%freq&#xA;partial_hess {0:20} end&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6576" LastActivityDate="2023-01-19T21:47:56.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10264" PostTypeId="2" ParentId="10206" CreationDate="2023-01-20T05:36:06.813" Score="6" Body="&lt;p&gt;I see two possibilities here:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;you adjust the weights of the roots such that the weight of the s0 root is 0.0 and the weight of the s1 root is 1.0. then you have to hope for the best that the s1 state stays the state that you want and optimize.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;if your system has symmetry and the two states have different symmetry, the you can turn on symmetry and optimize the lowest root in the irrep that corresponds to the S1 state.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;What is not yet available, is to do a state averaged CASSCF calculation and then do a state specific optimization. I hope that this will come in the future as it will make things like that much easier.&lt;/p&gt;&#xA;&lt;p&gt;Also, a future project is a root following algorithm in CASSCF. As it stands, you have to keep a keen eye on the optimization that it stays on the surface you want.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, if your system is not too exotic or difficult, you can also optimize excited state geometries with TD-DFT. That is actually pretty streamlined and there is a root following algorithm in place.&lt;/p&gt;&#xA;&lt;p&gt;Chances you are getting a detailed answer are better in the ORCA forum - 50000 users there who are familiar with the program.&lt;/p&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;" OwnerUserId="6577" LastActivityDate="2023-01-20T05:36:06.813" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10266" PostTypeId="1" CreationDate="2023-01-20T07:37:19.247" Score="2" ViewCount="629" Body="&lt;p&gt;I am new to quantum espresso, when I try to run the following input file for pw.x:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA; calculation = 'scf',&#xA; restart_mode = 'from_scratch',&#xA; prefix = 'ymno3',&#xA; tstress = .true.,&#xA; tprnfor = .true.,&#xA; pseudo_dir = '$pseudo_dir',&#xA; outdir = './'&#xA;/&#xA;&amp;amp;SYSTEM&#xA; ibrav = 1,&#xA; celldm(1) = 7.32,&#xA; nat = 5,&#xA; ntyp = 3,&#xA; ecutwfc = 30.0,&#xA; ecutrho = 240.0,&#xA; occupations = 'tetrahedra'&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA; diagonalization='david',&#xA; mixing_mode = 'plain',&#xA; mixing_beta = 0.3,&#xA; conv_thr =  1.0d-6,&#xA; electron_maxstep = 100,&#xA;/&#xA;ATOMIC_SPECIES&#xA; Y 88.9058 Y.rel-pbe-spn-kjpaw_psl.1.0.0.UPF&#xA; Mn 54.9380 Mn.rel-pbe-spn-kjpaw_psl.1.0.0.UPF&#xA; O 15.9999 O.rel-pbe-nl-kjpaw_psl.1.0.0.UPF&#xA;/&#xA;ATOMIC_POSITIONS alat&#xA; Y 0.0 0.0 0.0&#xA; Mn 0.5 0.5 0.5&#xA; O 0.5 0.5 0.0&#xA; O 0.5 0.0 0.5&#xA; O 0.0 0.5 0.5&#xA;K_POINTS automatic&#xA; &lt;span class=&quot;math-container&quot;&gt;$nkpts $&lt;/span&gt;nkpts $nkpts 1 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The following error occur:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;task #        15&#xA;     from  card_atomic_species   : error #         2&#xA;      two occurrences&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could anyone suggest any solution?&#xA;P.S. the wildcards is because I am using a bashscript this is not the problem&lt;/p&gt;&#xA;&lt;p&gt;Thank you all&lt;/p&gt;&#xA;" OwnerUserId="6578" LastEditorUserId="4895" LastEditDate="2023-01-20T11:58:32.323" LastActivityDate="2023-01-25T06:22:23.060" Title="Error in input file for pw.x in atomic species QE" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10269" PostTypeId="2" ParentId="10266" CreationDate="2023-01-20T10:59:49.760" Score="2" Body="&lt;p&gt;The properly formatted input file would be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL &#xA;    calculation     = 'scf', &#xA;    restart_mode    = 'from_scratch', &#xA;    prefix      = 'ymno3', &#xA;    tstress     = .true., &#xA;    tprnfor     = .true., &#xA;    pseudo_dir  = '$pseudo_dir', &#xA;    outdir      = './' &#xA;/ &#xA;&amp;amp;SYSTEM &#xA;    ibrav       = 1, &#xA;    celldm(1)   = 7.32, &#xA;    nat         = 5, &#xA;    ntyp        = 3, &#xA;    ecutwfc     = 30.0, &#xA;    ecutrho     = 240.0, &#xA;    occupations     = 'tetrahedra' &#xA;/&#xA;&amp;amp;ELECTRONS &#xA;    diagonalization ='david', &#xA;    mixing_mode     ='plain', &#xA;    mixing_beta     = 0.3, &#xA;    conv_thr    = 1.0d-6, &#xA;    electron_maxstep = 100, &#xA;/ &#xA;ATOMIC_SPECIES &#xA;    Y   88.9058 Y.rel-pbe-spn-kjpaw_psl.1.0.0.UPF &#xA;    Mn  54.9380 Mn.rel-pbe-spn-kjpaw_psl.1.0.0.UPF &#xA;    O   15.9999 O.rel-pbe-nl-kjpaw_psl.1.0.0.UPF &#xA;/ &#xA;ATOMIC_POSITIONS alat &#xA;    Y   0.0 0.0 0.0 &#xA;    Mn  0.5 0.5 0.5 &#xA;    O   0.5 0.5 0.0 &#xA;    O   0.5 0.0 0.5 &#xA;    O   0.0 0.5 0.5 &#xA;K_POINTS automatic &#xA;$nkpts $nkpts $nkpts 1 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now we can immediately see that there is an error in the &lt;code&gt;K_POINTS&lt;/code&gt; block where there is multiple nkpts definitions, while only one $nkpts was replaced by the bash script. If you edit for these errors, it must work.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-01-25T06:22:23.060" LastActivityDate="2023-01-25T06:22:23.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10270" PostTypeId="1" CreationDate="2023-01-20T11:53:55.870" Score="2" ViewCount="528" Body="&lt;p&gt;What are the criteria that one has to consider while chosing the number of roots in a CASSCF calculation?&lt;/p&gt;&#xA;" OwnerUserId="765" LastEditorUserId="5" LastEditDate="2023-01-20T15:35:12.347" LastActivityDate="2023-01-20T15:51:01.063" Title="How to choose the number of roots in a CASSCF calculation?" Tags="|quantum-chemistry|casscf|multi-reference|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10271" PostTypeId="2" ParentId="10225" CreationDate="2023-01-20T15:14:13.087" Score="5" Body="&lt;p&gt;Used pymatgen to parse born matrix&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from pymatgen.io.vasp.outputs import Outcar&#xA;vf = Outcar(&amp;quot;OUTCAR&amp;quot;)&#xA;born=vf.born&#xA;poscar=np.loadtxt('POSCAR',skiprows=8)[:48,:]&#xA;sum=0&#xA;for i in range(len(poscar)):&#xA;    sum=sum+poscar[i,2]*born[i,1,1]&#xA;      &#xA;    &#xA;print(sum)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2023-01-20T15:14:13.087" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10272" PostTypeId="2" ParentId="10270" CreationDate="2023-01-20T15:51:01.063" Score="3" Body="&lt;p&gt;The term &amp;quot;roots&amp;quot; refers to the number of &amp;quot;electronic states&amp;quot;. If you are only interested in the ground state, then you are seeking 1 root. If you want the ground state and the first 4 excited states, then your number of roots is 5. Basically the only factor that I consider when choosing the number of roots, is the computational cost (the calculation will take longer and need more computational resources if you want a lot of roots).&lt;/p&gt;&#xA;&lt;p&gt;When I searched &amp;quot;roots casscf&amp;quot; on Google, the first 4 results from software package documentation were from (in order of appearance):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/casscf-calculations&quot; rel=&quot;nofollow noreferrer&quot;&gt;ORCA&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Additional roots have to be included for excited state calculations. Then the number of roots (which corresponds to the number of states) is assigned by the nroots keyword (see State-averaging section below).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://gaussian.com/cas/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Calculations on excited states of molecular systems may be requested using the NRoot option. Note that a value of 1 specifies the ground state, not the first excited state (in contrast to usage with the CIS or TD keywords).&#xA;State-averaged CASSCF calculations may be performed using the StateAverage and NRoot options to specify the states to be used.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://vergil.chemistry.gatech.edu/manuals/molcas5/tutorials/node39.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molcas 5&lt;/a&gt; (this page, hosted by the lead author of Psi4,  contains a lot useful examples and detailed explanations about choosing the number of roots!):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;we expect to compute six A&lt;span class=&quot;math-container&quot;&gt;$_1$&lt;/span&gt; states and therefore we include six roots in the CASSCF state-average input. &amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.molcas.org/documentation/manual/node33.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molcas 8&lt;/a&gt; (official current documentation, this page also contains examples and some explanations about how to work with roots)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Keyword [CiRoot=  5  5  1] informs the program that we want to compute a total of five states, the ground state and the lowest four excited states at the CASSCF level and that all of them should have the same weight in the average procedure.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-01-20T15:51:01.063" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10273" PostTypeId="1" CreationDate="2023-01-20T16:52:14.547" Score="4" ViewCount="126" Body="&lt;p&gt;We know that bonds, &lt;em&gt;per se&lt;/em&gt;, are only characterized after topological studies but their visualizations is an easy and fast way to see if there are &amp;quot;connections&amp;quot; between some particles.&lt;/p&gt;&#xA;&lt;p&gt;I tested visualizations software like &lt;a href=&quot;https://jmol.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jmol&lt;/a&gt;, &lt;a href=&quot;http://www.cgl.ucsf.edu/chimera/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chimera&lt;/a&gt;, &lt;a href=&quot;https://www.schrodinger.com/products/maestro&quot; rel=&quot;nofollow noreferrer&quot;&gt;Maestro&lt;/a&gt;, &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt;, &lt;a href=&quot;https://ovito.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ovito&lt;/a&gt;, &lt;a href=&quot;https://two.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro&lt;/a&gt; and &lt;a href=&quot;https://www.ks.uiuc.edu/Research/vmd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VMD&lt;/a&gt; and each one is displaying the bonds in a different way.&lt;/p&gt;&#xA;&lt;p&gt;As a test, here is a small system of Ni atoms:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;4&#xA; energy: -19.116588819886 gnorm: 0.000358126128 xtb: 6.5.1 (863dcdc)&#xA;Ni           4.15720993928297       23.06900153804784        8.00195919232334&#xA;Ni           2.44935450390468       21.62046788970323        7.87888994741951&#xA;Ni           5.58700274720514       21.36098908827675        8.26402186547672&#xA;Ni           3.87913280960721       19.91244148397218        8.14092899478043&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The pictures below are the graphical representation in each of the software mentioned above.&lt;/p&gt;&#xA;&lt;p&gt;The question: &lt;strong&gt;Which is the best way to display bonds?&lt;/strong&gt; (or Which software is better representing the bonds for this system?)&lt;/p&gt;&#xA;&lt;p&gt;Jmol: &lt;img src=&quot;https://i.stack.imgur.com/I0Wr9.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;Chimera: &lt;img src=&quot;https://i.stack.imgur.com/7nN66.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;Maestro: &lt;img src=&quot;https://i.stack.imgur.com/1Lsk6.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;VESTA: &lt;img src=&quot;https://i.stack.imgur.com/1XsAH.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;Ovito: &lt;img src=&quot;https://i.stack.imgur.com/WrTXY.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;Avogadro: &lt;img src=&quot;https://i.stack.imgur.com/D0DLk.png&quot; width=&quot;300&quot;&gt;&lt;br /&gt;&#xA;VMD: &lt;img src=&quot;https://i.stack.imgur.com/xPh4p.png&quot; width=&quot;300&quot;&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-20T16:52:14.547" Title="Which is the best way to display bonds?" Tags="|visualization-software|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10274" PostTypeId="2" ParentId="10225" CreationDate="2023-01-20T17:05:57.787" Score="3" Body="&lt;p&gt;My version, tested on Python 3.10:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import re&#xA;from operator import mul&#xA;from itertools import chain&#xA;&#xA;def cars2list(poscar_file, outcar_file):&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    Function takes postcar file, outcar file, extracts data and returns a list that can be saved as a&#xA;    csv file using ; as a delimiter, following the model given in the question. Note this function is quite&#xA;    fragile in the sense the regexps used depend on precise character counts and spacings, at least for&#xA;    the poscar, and then rely input files in production are very similar to those given as examples in&#xA;    the question. So, if the files depart from the examples given, for example, containing other sections&#xA;    with data formated the same way, errors may occur. The only check done it to measure the amount of&#xA;    values recovered from both files, to see if the match.&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;    with open(poscar_file, 'r', newline='') as f:&#xA;        poscar_text = f.read()&#xA;    with open(outcar_file, 'r', newline='') as f:&#xA;        outcar_text = f.read()&#xA;&#xA;    pattern_poscar = re.compile(r&amp;quot;&amp;quot;&amp;quot;\s{1,2} -?0\.\d{16}&#xA;                                    \s{1,2} -?0\.\d{16}&#xA;                                    \s{1,2} (-?0\.\d{16})&#xA;                                    \n&#xA;                                 &amp;quot;&amp;quot;&amp;quot;,&#xA;                                re.VERBOSE)&#xA;    pattern_outcar = re.compile(r&amp;quot;&amp;quot;&amp;quot;\s ion \s+ \d+\n&#xA;                                    \s+ 1  \s+ -?\d+\.\d+ \s+&#xA;                                               -?\d+\.\d+ \s+&#xA;                                               -?\d+\.\d+\n&#xA;                                    \s+ 2  \s+ -?\d+\.\d+ \s+&#xA;                                               (-?\d+\.\d+ \s+)&#xA;                                               -?\d+\.\d+\n&#xA;                                 &amp;quot;&amp;quot;&amp;quot;,&#xA;                                re.VERBOSE)&#xA;&#xA;    poscar_data = [float(n) for n in pattern_poscar.findall(poscar_text)]&#xA;    outcar_data = [float(n) for n in pattern_outcar.findall(outcar_text)]&#xA;    assert len(poscar_data) == len(outcar_data), &amp;quot;Problem. Data recovered from POSCAR and OUTCAR are not the same size.&amp;quot;&#xA;    products = [x * y for x, y in zip(outcar_data, poscar_data)]&#xA;&#xA;    head = [('From OUTCAR', 'From POSCAR', 'Product')]&#xA;    body = zip(map(str, outcar_data), map(str, poscar_data), map(str, products))&#xA;    tail = [('', 'Sum:', str(sum(products)))]&#xA;    return [';'.join((colA, colB, colC + '\n')) for colA, colB, colC in chain(head, body, tail)]&#xA;&#xA;def main():&#xA;    L = cars2list('POSCAR', 'OUTCAR')&#xA;    with open('results.csv', 'w') as f:&#xA;        f.writelines(L)&#xA;    print('Done! Look for the file with results in the same folder as the .py file.')&#xA;&#xA;if __name__ == '__main__':&#xA;    main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The results are saved to a CSV file, where data can be further processed, or checked for correctness (note I hid some of the rows, so both begin and end of spreadsheet is visible):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pU4e1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pU4e1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2023-01-20T17:05:57.787" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10275" PostTypeId="1" CreationDate="2023-01-21T16:12:01.033" Score="2" ViewCount="173" Body="&lt;p&gt;I am trying to use EAM calculator in ASE. I want to perform simulation box relaxation with EAM potential. The code is working fine with EMT but fails in EAM as stress property is not implemented with EAM calculator. Any suggestion to solve this problem?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.calculators.eam import EAM&#xA;from ase.build import bulk&#xA;from ase.optimize.sciopt import SciPyFminCG as CG&#xA;from ase.constraints import UnitCellFilter as box_relax&#xA;from ase.optimize import BFGS&#xA;from ase.calculators.emt import EMT&#xA;s1 = bulk('Al', 'fcc', a=4.10,cubic=True)&#xA;&#xA;mishin = EAM(potential='Al99.eam.alloy')&#xA;s1.calc = mishin&#xA;ucf = box_relax(s1)&#xA;dyn = BFGS(ucf)&#xA;dyn.run(fmax=1e-6)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;ERROR&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;PropertyNotImplementedError: stress property not implemented&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="5" LastEditDate="2023-01-21T16:31:29.180" LastActivityDate="2023-02-01T09:25:25.533" Title="How to run simulation box relaxation with EAM callculator in ASE" Tags="|atomic-simulation-environment|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10276" PostTypeId="1" AcceptedAnswerId="10286" CreationDate="2023-01-21T20:29:36.617" Score="5" ViewCount="107" Body="&lt;h1&gt;Background&lt;/h1&gt;&#xA;&lt;p&gt;In the world of atomistic modeling with classical force fields, one is often given a force field defined by like interactions (e.g. argon-argon interactions). If one is working with a system involving multiple species, (e.g. argon + krypton), mixing rules are usually applied to derive the parameters of the cross-interactions (e.g. argon-krypton interactions).&lt;/p&gt;&#xA;&lt;p&gt;A common non-bonded pairwise force field class is the exp-6 or Buckingham potential, used to model close-range repulsive and dispersive-attractive van der Waals forces, which can be written in its tight form as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;U(r) = \underbrace{A e^{-Br}}_{U^{\mathrm{rep}}(r)} \underbrace{-\frac{C}{r^6}}_{U^{\mathrm{att}}(r)},\tag{1}\label{BH_tight}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; are empirical parameters and &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the internuclear separation. The potential is often transformed into the equivalent loose form,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;U(r)=\frac{\varepsilon}{1-\frac{6}{\gamma}}\left[\frac{6}{\gamma} e^{\gamma\left(1-\frac{r}{\sigma}\right)}-\left(\frac{\sigma}{r}\right)^6\right],\tag{2}\label{BH_loose}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A=\frac{6 \varepsilon e^\gamma}{\gamma-6}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B=\frac{\gamma}{\sigma}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C=\frac{\gamma \varepsilon}{\gamma-6} \sigma^6$&lt;/span&gt; define the transform between the two parameter spaces.&lt;/p&gt;&#xA;&lt;p&gt;While the loose form is perhaps a little uglier, it has the advantage of the length scale (&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;) and energy scale (&lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;) parameters being separate, defining the interaction well position and depth, respectively (assuming &lt;span class=&quot;math-container&quot;&gt;$\gamma &amp;gt;6$&lt;/span&gt;). The third unitless shape parameter &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; defines the repulsive wall steepness and well width.&lt;/p&gt;&#xA;&lt;p&gt;My question is about a commonly cited set of combining rules for this force field, usually referred to as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Combining_rules#Kong-Chakrabarty-rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kong-Chakrabarty rules&lt;/a&gt;, which take on the rather unwieldy form of&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\left[\frac{\epsilon_{ij} \gamma_{ij} e^{\gamma_{ij}}}{\left(\gamma_{ij}-6\right) \sigma_{ij}}\right]^{2 \sigma_{ij} / \gamma_{ij}} &amp;amp;= \left[\frac{\epsilon_{ii} \gamma_{ii} e^{\gamma_{ii}}}{\left(\gamma_{ii}-6\right) \sigma_{ii}}\right]^{\sigma_{ii} / \gamma_{ii}}\left[\frac{\epsilon_{jj} \gamma_{jj} e^{\gamma_{jj}}}{\left(\gamma_{jj}-6\right) \sigma_{jj}}\right]^{\sigma_{jj} / \gamma_{jj}}\tag{3}\label{rule_1},\\&#xA;\frac{\sigma_{ij}}{\gamma_{ij}} &amp;amp;= \frac{1}{2}\left(\frac{\sigma_{ii}}{\gamma_{ii}}+\frac{\sigma_{jj}}{\gamma_{jj}}\right)\tag{4}\label{rule_2},\\&#xA;\frac{\epsilon_{ij} \gamma_{ij} \sigma_{ij}^6}{\left(\gamma_{ij}-6\right)} &amp;amp;= \left[\frac{\epsilon_{ii} \gamma_{ii} \sigma_{ii}^6}{\left(\gamma_{ii}-6\right)} \frac{\epsilon_{jj} \gamma_{jj} \sigma_{jj}^6}{\left(\gamma_{jj}-6\right)}\right]^{\frac{1}{2}}\tag{5}\label{rule_3}.&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;According to the original papers (&lt;a href=&quot;https://aip.scitation.org/doi/abs/10.1063/1.1680358&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, and &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/j100640a019&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;), these combining rules are derived from the following ansatz:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;U_{ij}^{\mathrm{rep}}(r_{i} + r_{j}) &amp;amp;= \frac{1}{2}\left[U_{ii}^{\mathrm{rep}}\left(2 r_i\right)+U_{jj}^{\text {rep }}\left(2 r_j\right)\right]\tag{6}\label{ansatz_1},\\&#xA;\left[\frac{d U_{ii}^{\mathrm{rep}}(R) }{ d R} \right]_{R=2 r_i} &amp;amp;= \left[\frac{d U_{jj}^{\mathrm{rep}}(R) }{ d R}\right]_{R=2 r_j}\tag{7}\label{ansatz_2},\\&#xA;U_{ij}^{\mathrm{att}}(R) &amp;amp;= \left[U_{ii}^{\mathrm{att}}(R) U_{jj}^{\mathrm{att}}(R)\right]^{1/2},\tag{8}\label{ansatz_3}&#xA;\end{align}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$U_{ij}^{\mathrm{rep}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$U_{ij}^{\mathrm{att}}$&lt;/span&gt; refers to the repulsive and attractive components of the interaction between species &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, respectively. In general, the subscripts &lt;span class=&quot;math-container&quot;&gt;$ii$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$jj$&lt;/span&gt; refer to like-interactions with empirically derived parameters while the parameters labeled with &lt;span class=&quot;math-container&quot;&gt;$ij$&lt;/span&gt; are cross parameters defined by the mixing rules.&lt;/p&gt;&#xA;&lt;h1&gt;My Question&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;How does one derive combining rules (\ref{rule_1}) and (\ref{rule_2}) from the ansatz (\ref{ansatz_1}), (\ref{ansatz_2}), and possibly (\ref{ansatz_3})?&lt;/strong&gt; I have attempted the algebra myself to no avail, even going so far as to try with a computer algebra system, but I feel like I'm missing something here. The original papers offer little guidance in deriving these mixing rules, they are simply stated outright. Note that mixing rule (\ref{rule_3}) follows immediately from ansatz (\ref{ansatz_3}).&lt;/p&gt;&#xA;&lt;p&gt;You might ask why I care so much as to write up this question. Well, I would like to apply the same ansatz (\ref{ansatz_1}), (\ref{ansatz_2}), and (\ref{ansatz_3}) to a related but different force field (the &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ct300826t&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wang-Buckingham potential&lt;/a&gt;), but first would like to understand how it's done to the original Buckingham form. The Wang-Buckingham potential is essentially a damped version of the Buckingham potential, which eliminates the singularity at &lt;span class=&quot;math-container&quot;&gt;$r=0$&lt;/span&gt;, and takes the form of&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;U(r)=\frac{2 \epsilon}{1-\frac{3}{\gamma+3}}\left(\frac{\sigma^6}{\sigma^6+r^6}\right)\left[\frac{3}{\gamma+3} \mathrm{e}^{\gamma\left(1-\frac{r}{\sigma}\right)}-1\right].\tag{9}&#xA;$$&lt;/span&gt;&#xA;Note the three parameters of the Wang-Buckingham potential (&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;) are not equivalent to the Buckingham potential parameters.&lt;/p&gt;&#xA;&lt;h1&gt;My Attempts on Mathematica&lt;/h1&gt;&#xA;&lt;p&gt;I have attempted to solve this using Wolfram Mathematica as well as pen and paper. You can see my attempts using Mathematica.&#xA;&lt;a href=&quot;https://github.com/HScheiber/hogervorst_combining_rules&quot; rel=&quot;nofollow noreferrer&quot;&gt;Download my Wolfram Mathematica notebook here.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2023-01-23T01:46:47.663" LastActivityDate="2023-01-24T03:39:09.177" Title="How to Derive the Kong-Chakrabarty Mixing Rules" Tags="|mathematical-modeling|forcefields|interatomic-potentials|derivations|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10277" PostTypeId="1" AcceptedAnswerId="10298" CreationDate="2023-01-21T23:50:07.113" Score="2" ViewCount="232" Body="&lt;h1&gt;CCSD(T) works after an RHF calculation:&lt;/h1&gt;&#xA;&lt;h2&gt;Input:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, cc&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = ''' O&#xA;               H  1  0.9576257&#xA;               H  1  0.9576257  2 104.51 '''&#xA;mol.unit = 'angstrom'&#xA;mol.basis = 'STO-3G'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.verbose = 9&#xA;mol.symmetry = True&#xA;mol.symmetry_subgroup = 'C2v'&#xA;name = 'out'&#xA;#mol.output = name+'.txt' # only worked up to end of SCF (CC output went to stdout)&#xA;mol.build()&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;&#xA;mf = mol.RHF().set(chkfile = name + '.chk')&#xA;mf.kernel()&#xA;&#xA;#####################&#xA;## post-Hartree-Fock:&#xA;#####################&#xA;&#xA;mcc = cc.CCSD(mf).set(frozen=1,verbose=9)&#xA;e = mcc.kernel()&#xA;et = mcc.ccsd_t() # works only when not reading FCIDUMP file.&#xA;&#xA;#####################&#xA;## END OF INPUT &#xA;#####################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Output:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;I've included the last few lines here, but you can see a link to the full output file in the &amp;quot;Availability of files&amp;quot; section of this post. Notice the CCSD(T) energy at the end:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cycle = 7  E_corr(CCSD) = -0.0493362838011038  dE = -8.86095146e-08  norm(t1,t2) = 2.47391e-06&#xA;    CPU time for CCSD iter      3.58 sec, wall time      0.06 sec&#xA;    CPU time for CCSD     25.37 sec, wall time      0.46 sec&#xA;CCSD converged&#xA;E(CCSD) = -75.01232875135784  E_corr = -0.0493362838011038&#xA;    CPU time for CCSD integral transformation      4.66 sec, wall time      0.08 sec&#xA;irreps of each MO [0 3 0 2 0 3]&#xA;_sort_eri max_memory 3528.17  blksize 2&#xA;    CPU time for transpose 0:2      0.69 sec, wall time      0.01 sec&#xA;    CPU time for CCSD(T) sort_eri      1.39 sec, wall time      0.03 sec&#xA;max_memory 3920 MB (79 MB in use)&#xA;    CPU time for contract 0:2,0:2      0.14 sec, wall time      0.00 sec&#xA;    CPU time for CCSD(T)      1.79 sec, wall time      0.04 sec&#xA;CCSD(T) correction = -6.75066430370798e-05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;CCSD works, but not (T) when using FCIDUMP:&lt;/h1&gt;&#xA;&lt;h2&gt;Input:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, cc&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = ''' O&#xA;               H  1  0.9576257&#xA;               H  1  0.9576257  2 104.51 '''&#xA;mol.unit = 'angstrom'&#xA;mol.basis = 'STO-3G'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.verbose = 9&#xA;mol.symmetry = True&#xA;mol.symmetry_subgroup = 'C2v'&#xA;name = 'out'&#xA;#mol.output = name+'.txt' # only worked up to end of SCF (CC output went to stdout)&#xA;mol.build()&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;&#xA;mf = mol.RHF().set(chkfile = name + '.chk')&#xA;mf.kernel()&#xA;&#xA;pyscf.tools.fcidump.from_chkfile(name+'.fcidump',name+'.chk', tol=1e-18, float_format=' %.16g', molpro_orbsym=False, orbsym=None)&#xA;mf = pyscf.tools.fcidump.to_scf(name+'.fcidump', molpro_orbsym=False, mf=None)&#xA;mf.run()&#xA;&#xA;#####################&#xA;## post-Hartree-Fock:&#xA;#####################&#xA;&#xA;mcc = cc.CCSD(mf).set(frozen=1,verbose=9)&#xA;e = mcc.kernel()&#xA;et = mcc.ccsd_t() # works only when not reading FCIDUMP file.&#xA;&#xA;#####################&#xA;## END OF INPUT &#xA;#####################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Output:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Notice that the CCSD energy is &lt;code&gt;-75.012328751&lt;/code&gt; which agrees with the above case (when no FCIDUMP file was used) in all digits shown:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#INFO: **** input file is /home/nike/QCBugs/Issue022/inp_withDump.py ****&#xA;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, cc&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = ''' O&#xA;               H  1  0.9576257&#xA;               H  1  0.9576257  2 104.51 '''&#xA;mol.unit = 'angstrom'&#xA;mol.basis = 'STO-3G'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.verbose = 9&#xA;mol.symmetry = True&#xA;mol.symmetry_subgroup = 'C2v'&#xA;name = 'out'&#xA;#mol.output = name+'.txt' # only worked up to end of SCF (CC output went to stdout)&#xA;mol.build()&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;&#xA;mf = mol.RHF().set(chkfile = name + '.chk')&#xA;mf.kernel()&#xA;&#xA;pyscf.tools.fcidump.from_chkfile(name+'.fcidump',name+'.chk', tol=1e-18, float_format=' %.16g', molpro_orbsym=False, orbsym=None)&#xA;mf = pyscf.tools.fcidump.to_scf(name+'.fcidump', molpro_orbsym=False, mf=None)&#xA;mf.run()&#xA;&#xA;#####################&#xA;## post-Hartree-Fock:&#xA;#####################&#xA;&#xA;mcc = cc.CCSD(mf).set(frozen=1,verbose=9)&#xA;e = mcc.kernel()&#xA;et = mcc.ccsd_t() # works only when not reading FCIDUMP file.&#xA;&#xA;#####################&#xA;## END OF INPUT &#xA;#####################&#xA;#INFO: ******************** input file end ********************&#xA;&#xA;&#xA;System: uname_result(system='Linux', node='cedar1.cedar.computecanada.ca', release='3.10.0-1160.80.1.el7.x86_64', version='#1 SMP Tue Nov 8 15:48:59 UTC 2022', machine='x86_64', processor='')  Threads 64&#xA;Python 3.8.10 (default, Jun 16 2021, 14:20:20) &#xA;[GCC 9.3.0]&#xA;numpy 1.23.0  scipy 1.9.3&#xA;Date: Sat Jan 21 14:55:08 2023&#xA;PySCF version 2.1.1&#xA;PySCF path  /home/nike/.local/lib/python3.8/site-packages/pyscf&#xA;&#xA;[CONFIG] DEBUG = False&#xA;[CONFIG] MAX_MEMORY = 4000&#xA;[CONFIG] TMPDIR = /tmp&#xA;[CONFIG] UNIT = angstrom&#xA;[CONFIG] VERBOSE = 3&#xA;[CONFIG] conf_file = None&#xA;[INPUT] verbose = 9&#xA;[INPUT] max_memory = 4000 &#xA;[INPUT] num. atoms = 3&#xA;[INPUT] num. electrons = 10&#xA;[INPUT] charge = 0&#xA;[INPUT] spin (= nelec alpha-beta = 2S) = 0&#xA;[INPUT] symmetry True subgroup C2v&#xA;[INPUT] Mole.unit = angstrom&#xA;[INPUT] Symbol           X                Y                Z      unit          X                Y                Z       unit  Magmom&#xA;[INPUT]  1 O      0.000000000000   0.000000000000   0.000000000000 AA    0.000000000000   0.000000000000   0.000000000000 Bohr   0.0&#xA;[INPUT]  2 H      0.957625700000   0.000000000000   0.000000000000 AA    1.809650302845   0.000000000000   0.000000000000 Bohr   0.0&#xA;[INPUT]  3 H     -0.239932136496   0.000000000000   0.927081199883 AA   -0.453406026459   0.000000000000   1.751929563013 Bohr   0.0&#xA;[INPUT] ---------------- BASIS SET ---------------- &#xA;[INPUT] l, kappa, [nprim/nctr], expnt,             c_1 c_2 ...&#xA;[INPUT] O&#xA;[INPUT] 0    0    [3    /1   ]  130.70932         0.15432897&#xA;                                23.808861         0.53532814&#xA;                                6.4436083         0.44463454&#xA;[INPUT] 0    0    [3    /1   ]  5.0331513         -0.09996723&#xA;                                1.1695961         0.39951283&#xA;                                0.380389          0.70011547&#xA;[INPUT] 1    0    [3    /1   ]  5.0331513         0.15591627&#xA;                                1.1695961         0.60768372&#xA;                                0.380389          0.39195739&#xA;[INPUT] H&#xA;[INPUT] 0    0    [3    /1   ]  3.42525091        0.15432897&#xA;                                0.62391373        0.53532814&#xA;                                0.1688554         0.44463454&#xA;&#xA;nuclear repulsion = 9.19090095527734&#xA;point group symmetry = C2v&#xA;symmetry origin: [0.13562443 0.         0.17519296]&#xA;symmetry axis x: [-0. -1. -0.]&#xA;symmetry axis y: [ 0.790743    0.         -0.61214828]&#xA;symmetry axis z: [0.61214828 0.         0.790743  ]&#xA;num. orbitals of irrep A1 = 4&#xA;num. orbitals of irrep B1 = 1&#xA;num. orbitals of irrep B2 = 2&#xA;number of shells = 5&#xA;number of NR pGTOs = 21&#xA;number of NR cGTOs = 7&#xA;basis = STO-3G&#xA;ecp = {}&#xA;bas 0, expnt(s) = [130.70932    23.808861    6.4436083]&#xA;bas 1, expnt(s) = [5.0331513 1.1695961 0.380389 ]&#xA;bas 2, expnt(s) = [5.0331513 1.1695961 0.380389 ]&#xA;bas 3, expnt(s) = [3.42525091 0.62391373 0.1688554 ]&#xA;bas 4, expnt(s) = [3.42525091 0.62391373 0.1688554 ]&#xA;CPU time:         0.61&#xA;arg.atm = [[ 8 20  1 23  0  0]&#xA; [ 1 24  1 27  0  0]&#xA; [ 1 28  1 31  0  0]]&#xA;arg.bas = [[ 0  0  3  1  0 32 35  0]&#xA; [ 0  0  3  1  0 38 41  0]&#xA; [ 0  1  3  1  0 44 47  0]&#xA; [ 1  0  3  1  0 50 53  0]&#xA; [ 2  0  3  1  0 50 53  0]]&#xA;arg.env = [  0.           0.           0.           0.           0.&#xA;   0.           0.           0.           0.           0.&#xA;   0.           0.           0.           0.           0.&#xA;   0.           0.           0.           0.           0.&#xA;   0.           0.           0.           0.           1.8096503&#xA;   0.           0.           0.          -0.45340603   0.&#xA;   1.75192956   0.         130.70932     23.808861     6.4436083&#xA;  15.07274649  14.57770167   4.54323359   5.0331513    1.1695961&#xA;   0.380389    -0.848697     1.13520079   0.85675304   5.0331513&#xA;   1.1695961    0.380389     3.42906571   2.15628856   0.34159239&#xA;   3.42525091   0.62391373   0.1688554    0.98170675   0.94946401&#xA;   0.29590645]&#xA;ecpbas  = []&#xA;&#xA;&#xA;******** &amp;lt;class 'pyscf.scf.hf_symm.SymAdaptedRHF'&amp;gt; ********&#xA;method = SymAdaptedRHF-RHF&#xA;initial guess = minao&#xA;damping factor = 0&#xA;level_shift factor = 0&#xA;DIIS = &amp;lt;class 'pyscf.scf.diis.CDIIS'&amp;gt;&#xA;diis_start_cycle = 1&#xA;diis_space = 8&#xA;SCF conv_tol = 1e-09&#xA;SCF conv_tol_grad = None&#xA;SCF max_cycles = 50&#xA;direct_scf = True&#xA;direct_scf_tol = 1e-13&#xA;chkfile to save SCF result = out.chk&#xA;max_memory 4000 MB (current use 73 MB)&#xA;Freeze 0 electrons in irreps []&#xA;    10 free electrons in irreps A1 B1 B2&#xA;Set gradient conv threshold to 3.16228e-05&#xA;Nelec from initial guess = 9.86091385128042&#xA;E1 = -120.44790124439959  E_coul = 36.420426001819735&#xA;init E= -74.8365742873025&#xA;cond(S) = 5.636127957820105&#xA;    CPU time for initialize scf      3.84 sec, wall time      0.11 sec&#xA;HOMO (B1) = -0.393165985098286  LUMO (A1) = 0.426534016701304&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.529231880970381  LUMO = 0.426534016701304&#xA;   mo_energy = [-20.58868486  -1.58169821  -0.52923188   0.42653402]&#xA;B1 nocc = 1  HOMO = -0.393165985098286&#xA;   mo_energy = [-0.39316599]&#xA;B2 nocc = 1  HOMO = -0.70700906241869  LUMO = 0.535461984106062&#xA;   mo_energy = [-0.70700906  0.53546198]&#xA;E1 = -123.52134582056792  E_coul = 39.41763506881344&#xA;cycle= 1 E= -74.9128097964771  delta_E= -0.0762  |g|= 0.37  |ddm|= 1.69&#xA;    CPU time for cycle= 1      1.52 sec, wall time      0.03 sec&#xA;diis-norm(errvec)=0.396528&#xA;diis-c [-0.15723468  1.        ]&#xA;HOMO (B1) = -0.267738785133512  LUMO (A1) = 0.644179976979969&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.352143944372835  LUMO = 0.644179976979969&#xA;   mo_energy = [-19.99464164  -1.18585095  -0.35214394   0.64417998]&#xA;B1 nocc = 1  HOMO = -0.267738785133512&#xA;   mo_energy = [-0.26773879]&#xA;B2 nocc = 1  HOMO = -0.568463618483647  LUMO = 0.78199967411182&#xA;   mo_energy = [-0.56846362  0.78199967]&#xA;E1 = -122.28168196574782  E_coul = 38.128317769163004&#xA;cycle= 2 E= -74.9624632413075  delta_E= -0.0497  |g|= 0.0425  |ddm|= 0.56&#xA;    CPU time for cycle= 2      1.37 sec, wall time      0.03 sec&#xA;diis-norm(errvec)=0.04803&#xA;diis-c [-0.00136375  0.07217221  0.92782779]&#xA;HOMO (B1) = -0.389540380152414  LUMO (A1) = 0.605437533093365&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.45142028023944  LUMO = 0.605437533093365&#xA;   mo_energy = [-20.23992255  -1.26623695  -0.45142028   0.60543753]&#xA;B1 nocc = 1  HOMO = -0.389540380152414&#xA;   mo_energy = [-0.38954038]&#xA;B2 nocc = 1  HOMO = -0.619149296689157  LUMO = 0.740674985160102&#xA;   mo_energy = [-0.6191493   0.74067499]&#xA;E1 = -122.36417637689611  E_coul = 38.21031049049565&#xA;cycle= 3 E= -74.9629649311231  delta_E= -0.000502  |g|= 0.00858  |ddm|= 0.0428&#xA;    CPU time for cycle= 3      1.40 sec, wall time      0.03 sec&#xA;diis-norm(errvec)=0.00911032&#xA;diis-c [-1.16690863e-07 -2.14458345e-02 -3.04583446e-01  1.32602928e+00]&#xA;HOMO (B1) = -0.39123899548012  LUMO (A1) = 0.605339731487355&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.453040362493816  LUMO = 0.605339731487355&#xA;   mo_energy = [-20.24189604  -1.26825133  -0.45304036   0.60533973]&#xA;B1 nocc = 1  HOMO = -0.39123899548012&#xA;   mo_energy = [-0.391239]&#xA;B2 nocc = 1  HOMO = -0.617822333820714  LUMO = 0.742000301689417&#xA;   mo_energy = [-0.61782233  0.7420003 ]&#xA;E1 = -122.36388789989842  E_coul = 38.209994478823994&#xA;cycle= 4 E= -74.9629924657971  delta_E= -2.75e-05  |g|= 6.36e-05  |ddm|= 0.0153&#xA;    CPU time for cycle= 4      1.44 sec, wall time      0.03 sec&#xA;diis-norm(errvec)=6.74546e-05&#xA;diis-c [-1.26810441e-09  1.44163187e-03  1.86026098e-02 -8.35947904e-02&#xA;  1.06355055e+00]&#xA;HOMO (B1) = -0.391219211832674  LUMO (A1) = 0.605260710774646&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.452963884631979  LUMO = 0.605260710774646&#xA;   mo_energy = [-20.24179211  -1.26819569  -0.45296388   0.60526071]&#xA;B1 nocc = 1  HOMO = -0.391219211832674&#xA;   mo_energy = [-0.39121921]&#xA;B2 nocc = 1  HOMO = -0.617681162161389  LUMO = 0.741859345734213&#xA;   mo_energy = [-0.61768116  0.74185935]&#xA;E1 = -122.36402357493989  E_coul = 38.210130152276335&#xA;cycle= 5 E= -74.9629924673862  delta_E= -1.59e-09  |g|= 1.47e-05  |ddm|= 0.000101&#xA;    CPU time for cycle= 5      1.48 sec, wall time      0.03 sec&#xA;diis-norm(errvec)=1.4269e-05&#xA;diis-c [-6.89862228e-11  3.78913368e-04  5.83088134e-03 -2.43547175e-02&#xA; -2.27714492e-01  1.24585941e+00]&#xA;HOMO (B1) = -0.391222285213995  LUMO (A1) = 0.605265319359792&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.452965937366619  LUMO = 0.605265319359792&#xA;   mo_energy = [-20.2417999   -1.26820027  -0.45296594   0.60526532]&#xA;B1 nocc = 1  HOMO = -0.391222285213995&#xA;   mo_energy = [-0.39122229]&#xA;B2 nocc = 1  HOMO = -0.617689752981301  LUMO = 0.741862533680629&#xA;   mo_energy = [-0.61768975  0.74186253]&#xA;E1 = -122.36401253996894  E_coul = 38.21011911714349&#xA;cycle= 6 E= -74.9629924675481  delta_E= -1.62e-10  |g|= 3.68e-06  |ddm|= 4.23e-05&#xA;    CPU time for cycle= 6      1.48 sec, wall time      0.03 sec&#xA;HOMO (B1) = -0.391223261310395  LUMO (A1) = 0.605266801274786&#xA;irrep_nelec = [6, 2, 2]&#xA;A1 nocc = 3  HOMO = -0.452967068734555  LUMO = 0.605266801274786&#xA;   mo_energy = [-20.24180249  -1.26820185  -0.45296707   0.6052668 ]&#xA;B1 nocc = 1  HOMO = -0.391223261310395&#xA;   mo_energy = [-0.39122326]&#xA;B2 nocc = 1  HOMO = -0.617692480658258  LUMO = 0.741864183562906&#xA;   mo_energy = [-0.61769248  0.74186418]&#xA;E1 = -122.36400935331618  E_coul = 38.210115930482104&#xA;Extra cycle  E= -74.9629924675567  delta_E= -8.63e-12  |g|= 1.59e-06  |ddm|= 8.18e-06&#xA;    CPU time for scf_cycle     14.05 sec, wall time      0.32 sec&#xA;    CPU time for SCF     14.06 sec, wall time      0.32 sec&#xA;converged SCF energy = -74.9629924675567&#xA;irreps of each MO [0 0 3 0 2 0 3]&#xA;Parsing out.fcidump&#xA;converged SCF energy = -74.9629924675587&#xA;&#xA;******** &amp;lt;class 'pyscf.cc.ccsd.CCSD'&amp;gt; ********&#xA;CC2 = 0&#xA;CCSD nocc = 4, nmo = 6&#xA;frozen orbitals 1&#xA;max_cycle = 50&#xA;direct = 0&#xA;conv_tol = 1e-07&#xA;conv_tol_normt = 1e-05&#xA;diis_space = 6&#xA;diis_start_cycle = 0&#xA;diis_start_energy_diff = 1e+09&#xA;max_memory 4000 MB (current use 81 MB)&#xA;total FLOPs 19520.0&#xA;    CPU time for CCSD integral transformation      3.97 sec, wall time      0.07 sec&#xA;Init t2, MP2 energy = -74.998421719993  E_corr(MP2) -0.0354292524343585&#xA;    CPU time for init mp2      0.02 sec, wall time      0.00 sec&#xA;Init E_corr(CCSD) = -0.0354292524343585&#xA;    CPU time for vvvv [0:1]      0.56 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.50 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.10 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.49 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.73 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.14 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.97 sec, wall time      0.06 sec&#xA;DIIS for step 0&#xA;cycle = 1  E_corr(CCSD) = -0.0447960700300642  dE = -0.0093668176  norm(t1,t2) = 0.0288404&#xA;    CPU time for CCSD iter      3.87 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.58 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.47 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.09 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.48 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.73 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.94 sec, wall time      0.06 sec&#xA;diis-c [-1.08058489e-04  1.00000000e+00]&#xA;DIIS for step 1&#xA;cycle = 2  E_corr(CCSD) = -0.0476847828331966  dE = -0.0028887128  norm(t1,t2) = 0.0103951&#xA;    CPU time for CCSD iter      3.84 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.59 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.49 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.12 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.59 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.73 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.98 sec, wall time      0.05 sec&#xA;diis-c [-1.86787238e-06 -6.34417047e-01  1.63441705e+00]&#xA;DIIS for step 2&#xA;cycle = 3  E_corr(CCSD) = -0.0493281778291895  dE = -0.001643395  norm(t1,t2) = 0.004227&#xA;    CPU time for CCSD iter      3.87 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.60 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.61 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.23 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.39 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.61 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.96 sec, wall time      0.05 sec&#xA;diis-c [-7.50388430e-08  4.30384287e-01 -1.16894742e+00  1.73856314e+00]&#xA;DIIS for step 3&#xA;cycle = 4  E_corr(CCSD) = -0.0493382688445465  dE = -1.00910154e-05  norm(t1,t2) = 0.000646334&#xA;    CPU time for CCSD iter      3.84 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.61 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.49 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.13 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.47 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.71 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.97 sec, wall time      0.05 sec&#xA;diis-c [-9.52646963e-10 -1.43883755e-01  3.99052284e-01 -6.72110757e-01&#xA;  1.41694223e+00]&#xA;DIIS for step 4&#xA;cycle = 5  E_corr(CCSD) = -0.0493369549300818  dE = 1.31391446e-06  norm(t1,t2) = 9.16421e-05&#xA;    CPU time for CCSD iter      3.88 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.60 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.51 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.14 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.55 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.74 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      3.01 sec, wall time      0.05 sec&#xA;diis-c [-3.43384042e-11  3.55433625e-02 -9.83589196e-02  1.69088982e-01&#xA; -3.81924433e-01  1.27565101e+00]&#xA;DIIS for step 5&#xA;cycle = 6  E_corr(CCSD) = -0.0493361950942754  dE = 7.59835806e-07  norm(t1,t2) = 9.03218e-06&#xA;    CPU time for CCSD iter      3.91 sec, wall time      0.07 sec&#xA;    CPU time for vvvv [0:1]      0.59 sec, wall time      0.01 sec&#xA;    CPU time for vvvv [1:2]      1.47 sec, wall time      0.03 sec&#xA;    CPU time for vvvv      2.10 sec, wall time      0.04 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for vovv [0:2]      0.47 sec, wall time      0.01 sec&#xA;    CPU time for ovvv      0.71 sec, wall time      0.01 sec&#xA;max_memory 3918 MB,  nocc,nvir = 4,2  blksize = 2&#xA;    CPU time for voov [0:2]      0.13 sec, wall time      0.00 sec&#xA;    CPU time for update t1 t2      2.94 sec, wall time      0.05 sec&#xA;diis-c [-9.65793511e-13 -7.08208773e-03  1.94817874e-02 -3.55306407e-02&#xA;  8.95997177e-02 -5.61950607e-01  1.49548183e+00]&#xA;DIIS for step 6&#xA;cycle = 7  E_corr(CCSD) = -0.0493362837053574  dE = -8.8611082e-08  norm(t1,t2) = 2.4739e-06&#xA;    CPU time for CCSD iter      3.82 sec, wall time      0.07 sec&#xA;    CPU time for CCSD     27.04 sec, wall time      0.49 sec&#xA;CCSD converged&#xA;E(CCSD) = -75.01232875126405  E_corr = -0.04933628370535739&#xA;    CPU time for CCSD integral transformation      3.84 sec, wall time      0.07 sec&#xA;Overwritten attributes  get_ovlp get_hcore  of &amp;lt;class 'pyscf.scf.hf_symm.SymAdaptedRHF'&amp;gt;&#xA;/home/nike/.local/lib/python3.8/site-packages/pyscf/gto/mole.py:1193: UserWarning: Function mol.dumps drops attribute energy_nuc because it is not JSON-serializable&#xA;  warnings.warn(msg)&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;./inp_withDump.py&amp;quot;, line 39, in &amp;lt;module&amp;gt;&#xA;    et = mcc.ccsd_t() # works only when not reading FCIDUMP file.&#xA;  File &amp;quot;/home/nike/.local/lib/python3.8/site-packages/pyscf/cc/ccsd.py&amp;quot;, line 1129, in ccsd_t&#xA;    return ccsd_t.kernel(self, eris, t1, t2, self.verbose)&#xA;  File &amp;quot;/home/nike/.local/lib/python3.8/site-packages/pyscf/cc/ccsd_t.py&amp;quot;, line 51, in kernel&#xA;    orbsym = _sort_eri(mycc, eris, nocc, nvir, eris_vvop, log)&#xA;  File &amp;quot;/home/nike/.local/lib/python3.8/site-packages/pyscf/cc/ccsd_t.py&amp;quot;, line 140, in _sort_eri&#xA;    orbsym = symm.addons.label_orb_symm(mol, mol.irrep_id, mol.symm_orb,&#xA;  File &amp;quot;/home/nike/.local/lib/python3.8/site-packages/pyscf/symm/addons.py&amp;quot;, line 70, in label_orb_symm&#xA;    s_mo = numpy.dot(s, mo)&#xA;  File &amp;quot;&amp;lt;__array_function__ internals&amp;gt;&amp;quot;, line 180, in dot&#xA;ValueError: shapes (0,0) and (7,6) not aligned: 0 (dim 1) != 7 (dim 0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Availability of files&lt;/h1&gt;&#xA;&lt;p&gt;All input and output files, including also the FCIDUMP and &lt;code&gt;.chk&lt;/code&gt; files which are not included above, are available both at QCBugs &lt;a href=&quot;https://github.com/HPQC-LABS/QCBugs/tree/master/Issue022&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, and at MMSE's Modeling Matters Git repository &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/10277&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. (In the future I may connect those two folders &lt;a href=&quot;https://stackoverflow.com/q/75191754/1271772&quot;&gt;if this question gets answered&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;The final lines of the traceback for the attempt at calculating the (T) correction to CCSD after reading the integrals from an FCIDUMP file are here (copied from the end of the above output):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  File &amp;quot;/home/nike/.local/lib/python3.8/site-packages/pyscf/symm/addons.py&amp;quot;, line 70, in label_orb_symm&#xA;    s_mo = numpy.dot(s, mo)&#xA;  File &amp;quot;&amp;lt;__array_function__ internals&amp;gt;&amp;quot;, line 180, in dot&#xA;ValueError: shapes (0,0) and (7,6) not aligned: 0 (dim 1) != 7 (dim 0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h4&gt;Why are those shapes not aligned for the (T) correction, but are fine for the CCSD calculation?&lt;/h4&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2023-01-22T02:49:03.400" LastActivityDate="2023-01-27T02:16:30.683" Title="Why does CCSD work, but not CCSD(T), after reading an FCIDUMP in PySCF?" Tags="|python|software-assistance|pyscf|coupled-cluster|fcidump|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10278" PostTypeId="1" CreationDate="2023-01-22T06:17:32.443" Score="2" ViewCount="116" Body="&lt;p&gt;I am trying to generate the unit cell for a material from the optimized coordinates of a molecule. I am able to generate an orthorhombic unit cell from the coordinates using utilities in Avogadro. However, it is unable to reduce the orthorhombic cell to the primitive cell which is hexagonal. The cell that I am trying to build is (a) in the attached figure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://ars.els-cdn.com/content/image/1-s2.0-S138694771530117X-gr1.jpg&quot; alt=&quot;Figure&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;The cell that was identified by Avogadro is attached below.&lt;a href=&quot;https://i.stack.imgur.com/NUESM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NUESM.png&quot; alt=&quot;Figure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How can I reconcile both of these?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="1492" LastEditDate="2023-01-22T10:14:41.517" LastActivityDate="2023-01-22T10:14:41.517" Title="Generating unit cell from an optimized molecule in Avogadro?" Tags="|materials-design|avogadro|cell-optimization|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10279" PostTypeId="1" CreationDate="2023-01-22T06:18:08.717" Score="2" ViewCount="53" Body="&lt;p&gt;Is there any way to calculate the excited state frequencies of a period system using DFT?&lt;/p&gt;&#xA;" OwnerUserId="6457" LastActivityDate="2023-01-22T06:18:08.717" Title="Excited state frequency for periodic systems" Tags="|density-functional-theory|vasp|quantum-espresso|ab-initio-calculations|solid-state-physics|" AnswerCount="0" CommentCount="8" ClosedDate="2023-12-27T16:58:48.000" ContentLicense="CC BY-SA 4.0" />
  <row Id="10280" PostTypeId="2" ParentId="10231" CreationDate="2023-01-22T18:30:08.420" Score="2" Body="&lt;p&gt;That is clearly an excerpt of a formatted checkpoint file from the Gaussian program, where the density matrix&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ P_{\mu \nu} = 2 \sum_{i\rm{ occ}} C_{\mu i} C_{\nu i}$$&lt;/span&gt; which is symmetric &lt;span class=&quot;math-container&quot;&gt;$P_{\mu\nu} = P_{\nu \mu}$&lt;/span&gt; is stored in triangular format, &lt;span class=&quot;math-container&quot;&gt;$P_{\mu\leq \nu}$&lt;/span&gt;. The density matrix itself is insufficient to evaluate the electron density, you also need information on the basis set:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ n({\bf r}) = \sum_{\mu\nu}  P_{\mu \nu} \chi_\mu({\bf r}) \chi_\nu({\bf r}) $$&lt;/span&gt;&#xA;Our recent open access review article may be helpful for more information on the information content of these quantities, see &lt;a href=&quot;https://doi.org/10.3390/molecules25051218&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It is pretty simple to find some maxima, since there will be a maximum at every nucleus. Finding non-local maxima is a bit trickier, but it can be done as well, for instance by sampling space with density functional quadrature grids. My suggestion would be to use a program like PySCF that affords direct access to these quantities and more to formulate your algorithm.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-01-22T18:30:08.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10281" PostTypeId="1" CreationDate="2023-01-22T12:08:35.437" Score="4" ViewCount="564" Body="&lt;p&gt;I've been given the task to calculate the energy of the lowest unoccupied molecular orbital (eLUMO) using Spartan but I'm not really familiar with the said software, can anyone tell me a bit of an overview of how and where I can download and install? I'm using a windows-operated device.&lt;/p&gt;&#xA;&lt;p&gt;If you also know video tutorials (I'm trying to find some on my own as well) that could teach me how to download, it's very much appreciated. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="5972" OwnerDisplayName="Ellie" LastActivityDate="2023-03-18T11:59:37.900" Title="Does anyone know where and how I can download and install Spartan (the Molecular Modeling software)?" Tags="|quantum-chemistry|computational-chemistry|software|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10282" PostTypeId="1" CreationDate="2023-01-22T20:41:56.613" Score="2" ViewCount="135" Body="&lt;p&gt;I am looking at some raw POSCAR data of some Primitive Cells, and I wonder how I can get a simplified directional representation of the lattice vectors. I have two examples:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example 1:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;unknown system                          &#xA;   1.00000000000000     &#xA;     3.891768    0.000000    2.246913&#xA;     1.297256    3.669194    2.246913&#xA;     0.000000    0.000000    4.493827&#xA;   A   B&#xA;     2     1&#xA;Direct&#xA;  0.750000  0.750000  0.750000&#xA;  0.250000  0.250000  0.250000&#xA;  0.000000  0.000000  0.000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example 2:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;unknown system                          &#xA;   1.00000000000000     &#xA;    -2.015017    2.015017    2.856697&#xA;     2.015017   -2.015017    2.856697&#xA;     2.015017    2.015017   -2.856697&#xA;   P   Q   R&#xA;     2     1     1&#xA;Direct&#xA; -0.000000  0.000000  0.000000&#xA;  0.250000  0.750000  0.500000&#xA;  0.500000  0.500000 -0.000000&#xA;  0.750000  0.250000  0.500000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now here's the question: For &lt;em&gt;&lt;strong&gt;Example 1&lt;/strong&gt;&lt;/em&gt; I know that the lattice can be represented by the following primitive translation vector representation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     0.5    0.5    0.0&#xA;     0.0    0.5    0.5&#xA;     0.5    0.0    0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I know the above is correct because it is a basic FCC primitive cell. (Spacegroup: 225/Fm-3m | Lattice Angles: (60,60,60)).&lt;/p&gt;&#xA;&lt;p&gt;Now I wonder what would be the relevant primitive lattice vector representation for Example 2? I just have one extra info about &lt;em&gt;&lt;strong&gt;Example 2&lt;/strong&gt;&lt;/em&gt;: It is an FCC Primitive Cell (Spacegroup: 216/F-43m | Lattice Angles: (120,120,90)).&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2023-01-24T02:16:27.483" LastActivityDate="2023-01-24T02:16:27.483" Title="Primitive Translation Vectors from Lattice Vectors (with varying Space Groups)" Tags="|density-functional-theory|vasp|symmetry|space-groups|atomic-physics|" AnswerCount="0" CommentCount="8" ClosedDate="2023-11-23T19:26:55.103" ContentLicense="CC BY-SA 4.0" />
  <row Id="10283" PostTypeId="1" CreationDate="2023-01-23T15:38:40.537" Score="3" ViewCount="265" Body="&lt;p&gt;I have been trying to reproduce a geometry optimization from a research paper, where it was done by Avogadro.&lt;/p&gt;&#xA;&lt;p&gt;However, I cannot find the option for building a polymer from a monomer. I am using Avogadro 2.&lt;/p&gt;&#xA;" OwnerUserId="6592" LastEditorUserId="5" LastEditDate="2023-01-24T17:04:45.833" LastActivityDate="2023-01-24T17:04:45.833" Title="How can we build a polymer from a monomer in Avogadro?" Tags="|software|molecular-modeling|avogadro|" AnswerCount="0" CommentCount="5" ClosedDate="2023-11-05T16:23:07.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="10284" PostTypeId="1" CreationDate="2023-01-23T19:36:01.330" Score="5" ViewCount="68" Body="&lt;p&gt;I am looking for a program that can compare different structures and determine if they are equal or not. After performing DFT calculations, the obtained structures may be identical but for reasons like an alternative unit cell, numerical errors, etc., they might seem different.&lt;/p&gt;&#xA;&lt;p&gt;Do you know any program to compare structures?  The idea is that after DFT I will have loads of structures to compare and my aim is to find the different polymorphs. I know there is one called Sketch-map but my tutor says it is better to find another one.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6544" LastEditorUserId="5" LastEditDate="2023-01-23T19:42:50.067" LastActivityDate="2023-01-23T20:22:54.763" Title="Is there a program to compare different structures?" Tags="|density-functional-theory|geometry|structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10285" PostTypeId="2" ParentId="10284" CreationDate="2023-01-23T20:22:54.763" Score="2" Body="&lt;p&gt;If you have the crystal structure of each one of your systems, instead to try to overlay them and visually inspect each pair (depending on the number of structures this can be tedious and very feasible to errors), I strongly recommend you to generate the x-ray powder diffraction pattern for each crystal structure.&lt;/p&gt;&#xA;&lt;p&gt;Each polymorph will produce a different powder diffraction pattern. Then, you plot all at the same time in your preferred graphics tools (Excel, Gnuplot, Origin, etc.) and can determine the difference among them.&lt;/p&gt;&#xA;&lt;p&gt;The powder diffraction will take into account the cell parameters, the atomic positions and the type of atom in each position.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-23T20:22:54.763" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10286" PostTypeId="2" ParentId="10276" CreationDate="2023-01-24T02:43:21.537" Score="5" Body="&lt;p&gt;I will focus on deriving equations (3) and (4) from equations (6) and (7). In brief: we use equation (7) to derive &lt;span class=&quot;math-container&quot;&gt;$r_j$&lt;/span&gt; as a function of &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt;, and then differentiate (6) in &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; to derive the condition connecting the &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; coefficients.&lt;/p&gt;&#xA;&lt;p&gt;Then, we use (6) itself at &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; to derive the last condition connecting the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; coefficients. This second part is very gory and full of tricks -- the sort that, if this were a Math Olympiad question, would make me think there has to be a much neater solution to the whole thing, if one can only find the right substitution!&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;We have&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ U^{\mathrm{rep}}_{ii}(\mathrm{r}) \equiv A_{ii}e^{-B_{ii}\mathrm{r}} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(using roman typeface for variable &lt;span class=&quot;math-container&quot;&gt;$\mathrm{r}$&lt;/span&gt;) and thus&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \partial_{\mathrm{r}} U^{\mathrm{rep}}_{ii}(\mathrm{r}) = -B_{ii}A_{ii}e^{-B_{ii}\mathrm{r}} = -B_{ii} U^{\mathrm{rep}}_{ii}(\mathrm{r}). $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Substituting into equation (7) gives an expression for &lt;span class=&quot;math-container&quot;&gt;$r_j$&lt;/span&gt; in terms of &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$  B_{jj} A_{jj} e^{-2 B_{jj}r_j} = B_{ii} A_{ii} e^{-2 B_{ii}r_i} \Rightarrow r_j = b r_i - \frac{1}{2 B_{jj}} \ln ab, $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$a \equiv A_{ii}/A_{jj}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b \equiv B_{ii}/B_{jj}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now take &lt;em&gt;total&lt;/em&gt; derivatives of equation (6) in &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \begin{align} -(1+b)B_{ij}U^{\mathrm{rep}}_{ij}(r_i + r_j) &amp;amp;\stackrel{\mathrm{d}/\mathrm{d}r_{i}}= -[B_{ii}U_{ii}^{\mathrm{rep}}(2 r_i) + b B_{jj}U_{jj}^{\mathrm{rep}}(2r_j)] \\&#xA;&amp;amp;\stackrel{\mathrm{eq}(6)}= -2 B_{ii} U_{ij}^{\mathrm{rep}}(r_i + r_j) \\ &#xA;\Rightarrow \frac{1}{B_{ij}} = \frac{1}{2} \frac{1+b}{B_{ii}} &amp;amp;= \frac{1}{2} \left(\frac{1}{B_{ii}} + \frac{1}{B_{jj}} \right) \end{align} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is equation (4).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;It remains to tackle equation (6) in full gory detail, substituting our expression for &lt;span class=&quot;math-container&quot;&gt;$r_j$&lt;/span&gt;. The left-hand side expression is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ A_{ij} \exp \left(- B_{ij} \left[r_i + b r_i - \frac{1}{2 B_{jj}} \ln ab \right] \right). $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From earlier, recall that &lt;span class=&quot;math-container&quot;&gt;$(1+b)B_{ij} = 2 B_{ii}$&lt;/span&gt;, and with some work we also have &lt;span class=&quot;math-container&quot;&gt;$B_{ij}/(2B_{jj}) = b/(b+1)$&lt;/span&gt;, so that the above expression becomes&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ (ab)^{\frac{b}{b+1}}A_{ij}  e^{-2B_{ii} r_i}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now the right-hand side expression is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{1}{2} \left[ A_{ii}e^{-2 B_{ii} r_i} + A_{jj} e^{-2 B_{jj} r_j} \right] = \frac{1}{2} \left[ A_{ii}e^{-2 B_{ii} r_i} + A_{jj} ab \,e^{-2 B_{ii} r_i} \right].$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where we used the definition of &lt;span class=&quot;math-container&quot;&gt;$r_j$&lt;/span&gt; to simplify. Let's non-dimensionalize our expressions by defining &lt;span class=&quot;math-container&quot;&gt;$\alpha_i \equiv A_{ii}/A_{ij}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\alpha_j \equiv A_{jj}/A_{ij}$&lt;/span&gt;, and cancel out factors of &lt;span class=&quot;math-container&quot;&gt;$e^{-2 B_{ii} r_i}$&lt;/span&gt;, to give our simplified equation (6):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ (ab)^{\frac{b}{b+1}} = \frac{1}{2} \left( \alpha_i + \alpha_j ab \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here come two tricks: first, multiply through by &lt;span class=&quot;math-container&quot;&gt;$(ab)^{-1/2}$&lt;/span&gt; (motivated by the need to symmetrize between &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, after unceremoniously doing everything in &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; up to now). Then note that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{\alpha_i}{\sqrt{a}} = \alpha_j \sqrt{a} = \sqrt{\frac{A_{ii}A_{jj}}{A_{ij}A_{ij}}} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \sqrt{\frac{B_{ii}B_{jj}}{B_{ij}B_{ij}}} = \sqrt{B_{ii}B_{jj}} \times \frac{1}{2} \left(\frac{1}{B_{ii}} + \frac{1}{B_{jj}} \right) = \frac{1}{2} \left(\sqrt{b} + \frac{1}{\sqrt{b}} \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;to get&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ (ab)^{\frac{b}{b+1} - \frac{1}{2}} = \left(\frac{A_{ii}A_{jj}}{A^2_{ij}} \frac{B_{ii}B_{jj}}{B^2_{ij}}\right)^{1/2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Remembering that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ ab = (A_{ii}B_{ii})^1 \times (A_{jj}B_{jj})^{-1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;grouping powers and rewriting finally gives us&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ A_{ij} B_{ij} = (A_{ii}B_{ii})^{\frac{B_{ij}}{2B_{ii}}} (A_{jj}B_{jj})^{\frac{B_{ij}}{2B_{jj}}} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is equation (3).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-01-24T03:39:09.177" LastActivityDate="2023-01-24T03:39:09.177" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10287" PostTypeId="1" CreationDate="2023-01-24T12:36:00.267" Score="5" ViewCount="68" Body="&lt;p&gt;I need to visualize the exchange (Fermi) and correlation (Coulomb) hole of a hydrogen molecule to qualitatively illustrate the compensation of of both holes to form the total hole that is localized around the reference electron at the dissociation limit. I have found some resources which contain the corresponding plots (see F. Jensen: &lt;em&gt;Introduction to Computational Chemistry&lt;/em&gt;, 2. ed, John Wiley &amp;amp; Ltd, 2009, p. 244). Is there a way to create these plots with actual data for e. g. the PBE functional ? Which calculations do I have to carry out ? (I want to create them myself because of aesthetic reasons and I'm just curious.)&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2023-10-28T19:47:33.220" Title="Obtaining data for plotting Fermi and Coulomb holes of a hydrogen molecule" Tags="|density-functional-theory|quantum-chemistry|exchange-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10288" PostTypeId="1" CreationDate="2023-01-24T13:31:18.513" Score="2" ViewCount="60" Body="&lt;p&gt;I would like to simulate a liquid solvent (such as TEGDME) embedded into a polymeric cage (such as PEGDM). &lt;strong&gt;What is the most meaningful approach to estimate transport properties in such a system?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Three options that I have in mind are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Using a FF typically used for liquid electrolytes such as GAFF or OPLS/A,&lt;/li&gt;&#xA;&lt;li&gt;Use a machine learning interatomic potential such as ANI, M3Gnet or MTP,&lt;/li&gt;&#xA;&lt;li&gt;Being more cautious and looking into transition state theory (such as NEB).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But I am open to others.&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-11-06T15:00:32.777" LastActivityDate="2023-11-06T15:00:32.777" Title="Simulate liquid solvent mobility through a gel polymer electrolyte" Tags="|molecular-dynamics|molecular-modeling|atomistic-simulation|polymers|nudged-elastic-band|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10289" PostTypeId="1" AcceptedAnswerId="10294" CreationDate="2023-01-24T19:38:55.773" Score="2" ViewCount="76" Body="&lt;p&gt;I have been using transiesta and TBTrans to calculate the transmission curves of some materials. Could I theoretically compare the Transmission states with the states in the Density of States and the corresponding Local DOS?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-01-25T08:51:26.350" Title="Transmittive states plotting in TBTrans" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10290" PostTypeId="1" CreationDate="2023-01-24T22:54:18.680" Score="1" ViewCount="95" Body="&lt;p&gt;I am using vasp 6.2.0 to calculate bandstructure with HS06 hybrid functional. I have done&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;a DFT self-consistent calculation with GGA functional, on a uniform 20x20x20 grid; from this I copied the explicit list of 256 irreducible kpoints found in IBZKPT.&lt;/li&gt;&#xA;&lt;li&gt;a DFT bandstructure calculation along 6 high symmetry lines with 30 points per segment, starting from the previous point; from this I copied the k-path from OUTCAR and set the weight of these 180 k-points to 0.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I concatenated these two forming KPOINTS file, where I updated the total number of k-points as the sum of the two contributions&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Explicit k-point list&#xA;436&#xA;Reciprocal lattice&#xA;0.00000000000000 0.00000000000000 0.00000000000000 1&#xA;0.05000000000000 0.00000000000000 0.00000000000000 8&#xA;0.10000000000000 0.00000000000000 0.00000000000000 8&#xA;0.15000000000000 0.00000000000000 0.00000000000000 8&#xA;0.20000000000000 0.00000000000000 0.00000000000000 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functional&#xA;LHFCALC = .TRUE. ; HFSCREEN = 0.2 ; &#xA;ALGO = NORMAL &#xA;LFOCKACE = .TRUE.&#xA;ISTART=1&#xA;ISMEAR =  0&#xA;SIGMA  =  0.01&#xA;GGA    = PE&#xA;NCORE = 2 up to number-of-cores-per-socket (or number-of-cores-per-node)&#xA;NKRED = 4&#xA;KPAR=4&#xA;NWRITE = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However I got an error about using the wrong number of k-points&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; -----------------------------------------------------------------------------&#xA;|                     _     ____    _    _    _____     _                     |&#xA;|                    | |   |  _ \  | |  | |  / ____|   | |                    |&#xA;|                    | |   | |_) | | |  | | | |  __    | |                    |&#xA;|                    |_|   |  _ &amp;lt;  | |  | | | | |_ |   |_|                    |&#xA;|                     _    | |_) | | |__| | | |__| |    _                     |&#xA;|                    (_)   |____/   \____/   \_____|   (_)                    |&#xA;|                                                                             |&#xA;|     internal error in: fock_dbl.F  at line: 1502                            |&#xA;|                                                                             |&#xA;|     internal error in FOCK_FCC: number of k-points incorrect 5715 8000      |&#xA;|     4 4 4                                                                   |&#xA;|                                                                             |&#xA;|     If you are not a developer, you should not encounter this problem.      |&#xA;|     Please submit a bug report.                                             |&#xA;|                                                                             |&#xA; -----------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I think it might be because I'm using NKRED=4 to downsample the number of q-points to 5x5x5, out of a 20x20x20 k-points grid. If this is the case, how can I get the right k-points file which accounts for the downsampling?&lt;/p&gt;&#xA;" OwnerUserId="6513" LastActivityDate="2023-01-24T22:54:18.680" Title="VASP: HS06 hybrid functional bandstructure with downsampled fock operator" Tags="|vasp|band-structure|hse06|" AnswerCount="0" CommentCount="3" ClosedDate="2023-11-05T16:20:16.050" ContentLicense="CC BY-SA 4.0" />
  <row Id="10291" PostTypeId="1" CreationDate="2023-01-25T05:14:19.677" Score="2" ViewCount="360" Body="&lt;p&gt;I am confused regarding the steps when we use ICHARG=11.&#xA;This is used to plot the band structure.&#xA;This means we are starting the calculation from a pre-converged&#xA;CHGCAR file and keeping the density fixed throughout the calculation.&#xA;If we know the density, we can calculate the potential (at least upto&#xA;GGA level), and after solving the KS equation in one step, we can get&#xA;the eigenvalue at any k-point we want. But, when running with ICHARG=11,&#xA;there are some scf like steps in the output. From the VASP manual,&#xA;&amp;quot;charge density will be kept constant during the entire electronic minimization&amp;quot;.&#xA;What is the meaning of electronic minimization if we keep the density fixed?&lt;/p&gt;&#xA;" OwnerUserId="2052" LastActivityDate="2023-03-11T05:30:51.533" Title="Steps in case of ICHARG=11 in VASP" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10293" PostTypeId="2" ParentId="10256" CreationDate="2023-01-25T08:25:10.300" Score="2" Body="&lt;p&gt;First, it is not clear which DOS you are referring too? Is it Green function, spectral function or bulk DOS? In this case, try and plot them all!&lt;/p&gt;&#xA;&lt;p&gt;There are several aspects that determine the smoothness of the DOS and transmission plots:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; value that determines the imaginary part of the Green function, both for the device part &lt;em&gt;and&lt;/em&gt; the electrode part, a larger value will smooth out the DOS, at the cost of precision similarly to the electronic temperature in the fermi-dirac distribution. You should play with both &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; values to see how it influences the DOS/transmission&lt;/li&gt;&#xA;&lt;li&gt;The k-point resolution, you'll generally see some van-Hove singularities in the pristine graphene case, again, if you increase the k-point sampling you'll reduce the peaks and smoothen out the functions.&lt;/li&gt;&#xA;&lt;li&gt;The transmission is generally less spiky as it involves both incoming and outgoing states, so the numerical influences of the &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; becomes more apparent.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;You should play with the &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; and k-point sampling values to see how they are all connected.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-01-25T08:25:10.300" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="10294" PostTypeId="2" ParentId="10289" CreationDate="2023-01-25T08:51:26.350" Score="2" Body="&lt;p&gt;Sure, they are related since there can only be transmission if there are states.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;An electron can only be transmitted if it exists at that energy in the bulk electrode.&lt;/li&gt;&#xA;&lt;li&gt;Then the electron needs to transport across the device region, if there are no states at the electron energy it will &lt;em&gt;decay&lt;/em&gt; in the device region and likely not reach across to the other electrode.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;So they are definitely correlated. A low/high electrode DOS means a low/high transmission, provided a wide-band DOS of the device region.&lt;/p&gt;&#xA;&lt;p&gt;There is lots of information hidden when comparing DOS and transmission, such as whether some states are localized (non-transmittive) or not. Say if the electrode + device region DOS is large, but there is no transmission, then the states are likely extremely localized and one should investigate whether the device DOS are weakly coupled to the electrodes.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-01-25T08:51:26.350" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10295" PostTypeId="1" CreationDate="2023-01-25T09:49:36.567" Score="5" ViewCount="102" Body="&lt;p&gt;I am trying to calculate the DOS and PDOS for a graphene-DNA structure. Upon referring the manual, I understand that we need to have charges converged before computing the DOS. Following this, I have a question:&lt;/p&gt;&#xA;&lt;p&gt;I have computed the SCC in 4 sets of kpoint meshs (4x4x1 to 10x10x1), and see that the energies do not change till the third decimal place. Does this mean that I can use the lowest (4x4x1) grid for the DOS calculation? My experience from quantum espresso tells me that we need a denser grid for DOS calculations. Does it hold true here also?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="7" LastEditDate="2023-12-10T00:27:03.183" LastActivityDate="2023-12-10T00:27:03.183" Title="Calculation of DOS from DFTB+?" Tags="|density-of-states|dftb+|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10296" PostTypeId="1" CreationDate="2023-01-25T09:57:27.073" Score="2" ViewCount="46" Body="&lt;p&gt;I am currently running eABF(adaptive biasing) simulation using NAMD. I need to restrain a few terminal C-H bonds in the system. I tried including the additional definition for bond constraints in the existing colvar file, but the simulation terminates prematurely, giving the error 'Velocity too high for the H atom; simulation has become unstable'.&lt;/p&gt;&#xA;&lt;p&gt;The system is adequately minimized, and the classical MD simulations run perfectly. Is there any other way to eliminate the error when Colvars come into the picture other than reducing the timestep?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-01-25T09:57:27.073" Title="Restraining a specific bond in eABF simulations in NAMD?" Tags="|atomistic-simulation|namd|" AnswerCount="0" CommentCount="2" ClosedDate="2023-11-08T00:17:29.057" ContentLicense="CC BY-SA 4.0" />
  <row Id="10297" PostTypeId="1" CreationDate="2023-01-25T11:13:05.093" Score="2" ViewCount="40" Body="&lt;p&gt;I am using SIESTA version 4.1.5, when doing scattering region calculation using transiesta iam getting error as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Electrode: Left is a Gamma-only calculation, this is not feasible.&#xA;Electrode: Left is a Gamma-only calculation, this is not feasible.&#xA;Erroneous electrode setup, check out-put&#xA;Stopping Program from Node:   19       &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How may I fix this error?&lt;/p&gt;&#xA;" OwnerUserId="6561" LastEditorUserId="5" LastEditDate="2023-01-25T18:52:52.380" LastActivityDate="2023-01-25T18:52:52.380" Title="Getting Error while doing a scattering region calculation using transiesta in SIESTA version 4.1.5" Tags="|siesta|" AnswerCount="0" CommentCount="3" ClosedDate="2023-01-26T23:07:13.830" ContentLicense="CC BY-SA 4.0" />
  <row Id="10298" PostTypeId="2" ParentId="10277" CreationDate="2023-01-26T00:05:27.977" Score="3" Body="&lt;p&gt;FCIDUMP only contains limited information about the system (e.g. numbers of orbitals and electrons, spatial symmetries of orbitals, etc.) and 1- and 2-electron integrals in MO basis. The FCIDUMP format is defined in &lt;a href=&quot;https://doi.org/10.1016/0010-4655(89)90033-7&quot; rel=&quot;nofollow noreferrer&quot;&gt;Comp. Phys. Commun. 54, 75 (1989)&lt;/a&gt;. As @Tyberius and @NikeDattani discussed, FCIDUMP doesn't have enough information to recover atomic positions or AO basis. Thus, &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/c0c4dbcb97b5725b5bbec3257b78f18c63663c76/pyscf/tools/fcidump.py#L310&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;to_scf()&lt;/code&gt;&lt;/a&gt; only creates a Mole object with empty atoms/basis, which is why &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/c0c4dbcb97b5725b5bbec3257b78f18c63663c76/pyscf/symm/addons.py#L69&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;mol.intor_symmetric('int1e_ovlp')&lt;/code&gt;&lt;/a&gt; returns an empty overlap matrix &lt;code&gt;s&lt;/code&gt; that leads to the ValueError in &lt;code&gt;s_mo = numpy.dot(s, mo)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A simple solution, as suggested by @Tyberius, is to use &lt;code&gt;mf.get_ovlp()&lt;/code&gt; to get the overlap matrix instead. &lt;code&gt;mf.get_ovlp()&lt;/code&gt; is already redefined in &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/c0c4dbcb97b5725b5bbec3257b78f18c63663c76/pyscf/tools/fcidump.py#L343&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;to_scf()&lt;/code&gt;&lt;/a&gt; to return an identity matrix (think of the orthonormal MO orbitals as the new AO basis). I've made a &lt;a href=&quot;https://github.com/pyscf/pyscf/pull/1580&quot; rel=&quot;nofollow noreferrer&quot;&gt;pull request&lt;/a&gt; to reflect this change.&lt;/p&gt;&#xA;&lt;p&gt;Update 1/26/2023: The pull request has been merged into &lt;code&gt;master&lt;/code&gt; branch.&lt;/p&gt;&#xA;" OwnerUserId="6599" LastEditorUserId="6599" LastEditDate="2023-01-27T02:16:30.683" LastActivityDate="2023-01-27T02:16:30.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10299" PostTypeId="1" CreationDate="2023-01-26T13:37:34.223" Score="1" ViewCount="31" Body="&lt;p&gt;As far as I understand, it would be better to use metallic electrodes in a Transiesta calculation and avoid the usage of semiconducting electrodes. It should be related to the bad screening of the latter and the consequent usage of very big systems (along with the definition of Fermi energy in semiconductors and so on).&lt;/p&gt;&#xA;&lt;p&gt;Having said this, I would like to check the transport properties of some GNRs. I have already done some calculations on a doped monolayer graphene using graphene as electrodes, like the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/o4tEi.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/o4tEi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and I would like to study the same but in a nanoribbon case.&#xA;Should one keep using graphene (thus not nano-ribbons) as electrode also with GNR to avoid problems in the calculation?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-01-26T13:37:34.223" Title="Transiesta electrodes with GNR structures" Tags="|siesta|electronic-transport|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T17:50:42.190" ContentLicense="CC BY-SA 4.0" />
  <row Id="10300" PostTypeId="1" CreationDate="2023-01-26T16:21:28.277" Score="2" ViewCount="64" Body="&lt;p&gt;My question is related to the topic solved here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10256/dos-calculation-with-tbtrans&quot;&gt;DOS calculation with TBTrans&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, in the answer, the imaginary contour manipulation is proposed to smooth the DOS. I noticed, however, that doing this would change (in the order of the microA) the value of the current calculated in TBTrans.&lt;/p&gt;&#xA;&lt;p&gt;I would expect this to happen; however, I would consider the correct value (or the most accurate) the one calculated at the smallest eta possible for the electrodes and 0eV for the device. Would this be correct?&lt;/p&gt;&#xA;&lt;p&gt;In case needed, this is the input file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# -- NAME &amp;amp; LABEL --&#xA;&#xA;SystemName bnc &#xA;SystemLabel bnc&#xA;&#xA;    # -- MATERIAL --&#xA;&#xA;NumberOfSpecies 1&#xA;NumberOfAtoms 152&#xA;&#xA;%block Chemical_Species_label&#xA;1 6 C&#xA;%endblock Chemical_Species_label&#xA;&#xA;    # -- CELL-ATOMIC-POSITION --&#xA;&#xA;LatticeConstant 1.0 Ang&#xA;&#xA;%block LatticeVectors&#xA;        8.5893001556         0.0000000000         0.0000000000&#xA;        0.0000000000        26.4589004517         0.0000000000&#xA;        0.0000000000         0.0000000000        47.1099014282&#xA;%endblock LatticeVectors&#xA;&#xA;AtomicCoordinatesFormat      Ang&#xA;%block  AtomicCoordinatesAndAtomicSpecies&#xA;...&#xA;%endblock  AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;    # -- MONKHORST-PACK --&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA;6   0   0   0.0&#xA;0   1   0   0.0&#xA;0   0   3   0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;Diag.ParallelOverK   T&#xA;&#xA;&#xA;       # --BASIS SET DEFINITION-- #&#xA;&#xA;PAO.BasisSize DZP&#xA;PAO.SplitType Split&#xA;PAO.SoftDefault true&#xA;PAO.SoftPotential 40.0 Ry&#xA;PAO.SoftInnerRadius 0.9&#xA;&#xA;PAO.EnergyShift 10 meV&#xA;&#xA;%block PAO.Basis                 # Define Basis set&#xA;C        2                # We include 4 shells&#xA;n=2 0 2 S 0.3&#xA;0.000 0.000&#xA;1.000 1.000&#xA;n=2 1 2 S 0.3  P 1&#xA;0.000 0.000&#xA;1.000 1.000&#xA;%endblock PAO.Basis&#xA;&#xA;    # -- MOLECULAR DYNAMICS-CONJUGATE-GRADIENT-METHOD --&#xA;&#xA;MD.TypeOfRun            CG  &#xA;MD.NumCGsteps           0   &#xA;MD.MaxForceTol          0.02 eV/Ang&#xA;MD.VariableCell         F&#xA;Constant.Volume     T&#xA;MD.UseSaveXV            T&#xA;MD.UseSaveCG        T&#xA;MD.MaxStressTol         0.0010 eV/Ang**3&#xA;WriteMDHistory          T &#xA;WriteMDXMol         T&#xA;MD.MaxDispl           0.1 Bohr&#xA;SCF.MustConverge true&#xA;&#xA;    # -- SPIN FIELD --&#xA;&#xA;SpinPolarized       F       #If spin polarized the use T&#xA;&#xA;    # -- SELF-CONSISTENT FIELD --&#xA;&#xA;Mesh.Cutoff     400 Ry&#xA;XC.functional           GGA&#xA;XC.authors              PBE&#xA;MaxSCFIterations        5000&#xA;SolutionMethod          transiesta&#xA;     &#xA;        &#xA;    # -- SELF-CONSISTENT FIELD-MIXING --&#xA;&#xA;SCF.Mixer.Weight            0.1&#xA;SCF.Mixer.History       6&#xA;SCF.DM.Tolerance        1.d-5&#xA;SCF.FreeE.Converge   T&#xA;SCF.FreeE.Tolerance     1.d-5 eV&#xA;SCF.Mix.AfterConvergence F&#xA;SCF.H.Converge true&#xA;SCF.H.Tolerance 1.d-5 eV&#xA;DM.FormattedFiles       F&#xA;DM.FormattedOutput      F&#xA;&#xA;#####################TRANSIESTA###################&#xA;&#xA;TS.Voltage    0.00000 eV&#xA;&#xA;TBT.k [300 1 1]&#xA; &#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA; &#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA; &#xA;TS.Elecs.Bulk true&#xA;TS.Elecs.DM.Update cross-terms&#xA;TS.Elecs.GF.ReUse true&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA; &#xA;%block TS.Elec.Left&#xA;  HS ./electrode.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a3&#xA;  elec-pos begin 1&#xA;%endblock TS.Elec.Left&#xA; &#xA;%block TS.Elec.Right&#xA;  HS ./electrode.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir +a3&#xA;  elec-pos end -1&#xA;%endblock TS.Elec.Right&#xA; &#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.c-Left&#xA;  part circle&#xA;   from  -40.00000 eV + V/2 to -10. kT + V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Left&#xA;%block TS.Contour.t-Left&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Left&#xA;%block TS.Contour.c-Right&#xA;  part circle&#xA;   from  -40.00000 eV - V/2 to -10. kT - V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Right&#xA;%block TS.Contour.t-Right&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Right&#xA; &#xA;TS.Elecs.Eta    0.0001000000 eV&#xA;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;    delta 0.01 eV&#xA;     method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA; &#xA; &#xA; &#xA;# TBtrans options&#xA; &#xA;TBT.Elecs.Eta    0.0001 eV&#xA;TBT.DOS.Gf T&#xA;#TBT.DOS.A T&#xA; &#xA;%block TBT.Contours&#xA;  neq&#xA;%endblock TBT.Contours&#xA; &#xA;%block TBT.Contour.neq&#xA;  part line&#xA;   from   -2.00000 eV to    2.00000 eV&#xA;    delta    0.026 eV&#xA;     method mid-rule&#xA;%endblock TBT.Contour.neq&#xA;&#xA;TBT.BTD.Pivot.Device atom+Left&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-01-27T13:15:49.120" LastActivityDate="2023-01-27T13:15:49.120" Title="Current value changes with contour values in SIESTA" Tags="|siesta|electronic-transport|" AnswerCount="0" CommentCount="4" ClosedDate="2023-11-05T16:20:02.990" ContentLicense="CC BY-SA 4.0" />
  <row Id="10301" PostTypeId="1" CreationDate="2023-01-26T19:15:08.307" Score="2" ViewCount="74" Body="&lt;p&gt;While reading about push-pull systems in papers, I came across the term quinoid character. I looked for it in google here is what I've found:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In polyphenylene the ground state is a whole lot of aromatic rings joined together - very stable. Note that the bond joining the phenyls is a single bond. A quinoid state is one where the double bonds have shifted so that there is a double bond where that above single used to be. This is a high energy state.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I still don't get it and what is the purpose of a high quinoid character?&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="7" LastEditDate="2023-01-26T19:37:26.013" LastActivityDate="2023-01-26T19:37:26.013" Title="What is meant by &quot;quinoid character&quot;?" Tags="|organic-chemistry|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-01T14:44:18.520" ContentLicense="CC BY-SA 4.0" />
  <row Id="10303" PostTypeId="1" CreationDate="2023-01-27T09:11:26.980" Score="3" ViewCount="952" Body="&lt;p&gt;I am getting a segmentation fault error when running the following input file below. The calculation runs fine in gas phase and CPCM modes, but fails with SMD. What could be the issue? Some are saying it's a memory issue, so I tried &lt;code&gt;%maxcore  16000&lt;/code&gt; but it still failed the same. Using Orca 5.0.3 on Ubuntu 20.04.5 LTS.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!M062X def2-TZVP D3zero defgrid3&#xA;!OPT NUMFREQ&#xA;!printbasis largeprint printmos hirshfeld&#xA;&#xA;%geom&#xA;maxiter 1500&#xA;end&#xA;&#xA;%freq&#xA;Temp 273.15, 333.15 , 363.15, 393.15, 423.15&#xA;end&#xA;&#xA;%cpcm &#xA;smd true&#xA;SMDsolvent &amp;quot;water&amp;quot;&#xA;end&#xA;&#xA;%PAL NPROCS 16 END&#xA;&#xA;* xyz 1 1 &#xA;  O   0.56123548042902     -2.53178400059932     -0.73552177848428&#xA;  O   1.93006902944596     -0.28310610286172      1.59050637964507&#xA;  O   -2.25322066231326      1.45686409318794      0.13445019990513&#xA;  C   -0.21769263338272      0.55709527956065      0.91609610227100&#xA;  C   0.72709204009279      0.36149960694404      2.08807079322228&#xA;  C   -1.33249201356723      1.53658332136523      1.26362531485318&#xA;  H   0.32718902198399      0.91703136919167      0.05902020476516&#xA;  H   0.24119787373457     -0.26386039463382      2.82201742312457&#xA;  H   0.98488111711202      1.31667081998840      2.52520529595833&#xA;  H   -0.95239525124047      2.54023932658851      1.37855902250321&#xA;  H   -1.83891465003821      1.22219694728280      2.16577884259076&#xA;  H   0.49500664972027     -3.49038816982874     -0.70559770260021&#xA;  H   2.52091618372824     -0.56377991082213      2.30117387184596&#xA;  H   -3.10743587049396      1.86833711484756      0.32491409874615&#xA;  H   1.64139278663855     -1.61588190212634     -1.01370250633890&#xA;  O   2.21465736765956     -0.76050990970803     -0.92717391857581&#xA;  H   2.30097830900400     -0.52564652584115      0.03407985604545&#xA;  H   1.95124369291577      0.05779163986123     -1.54103539946122&#xA;  O   -0.84082041570016     -0.71916347981864      0.61744950965258&#xA;  H   -1.67352602367103     -0.54487239771055      0.15131513724536&#xA;  H   -0.04531052175705     -2.05927417451677     -0.12534235471864&#xA;  O   1.43129577781953      1.19176824162515     -2.14587937470171&#xA;  H   0.44606576533647      1.31941944151051     -2.30645843699483&#xA;  H   1.97799395881196      1.86289813187552     -2.56630173929171&#xA;  O   -1.07534965367720      1.50936682810338     -2.33335072150496&#xA;  H   -1.64026589872463      1.46514297994161     -3.11198989801639&#xA;  H   -1.58918278886678      1.57839449659288     -1.50538620368552&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Error output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun noticed that process rank 0 with PID 383161 on node inst-2 exited on signal 11 (Segmentation fault).&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output file failure point:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ---------------------------------&#xA;          TRAH Step control &#xA; ---------------------------------&#xA;  predicted energy change = -0.019712&#xA;  actual energy  change   = 0.009209&#xA;  energy change ratio     = -0.467177&#xA;  old trust radius        = 0.576000&#xA;  new trust radius        = 0.403200&#xA;  reject step?            =  1&#xA;    4       -640.372663418982     4.795431e-02                     0.403 (TRAH MAcro)  Yes&#xA;    5       -640.372663418982     1.647962e-01                     0.403 (TRAH MAcro)   No&#xA;    5     dE    -8.684424e-04     1.735400e-01    -1.7367e-03      0.011 (TRAH MIcro)&#xA;    5     dE    -1.869723e-03     8.757554e-02    -3.7322e-03      0.044 (TRAH MIcro)&#xA;    5     dE    -5.442865e-03     2.638698e-01    -9.8867e-03      0.318 (TRAH MIcro)&#xA;    5     dE    -1.078388e-02     1.289838e-01    -8.3960e-02      0.377 (TRAH MIcro)&#xA;    5     dE    -1.233165e-02     6.082106e-02    -9.0467e-02      0.403 (TRAH MIcro)&#xA;    5     dE    -1.248328e-02     1.749079e-02    -9.2408e-02      0.403 (TRAH MIcro)&#xA;    5     dE    -1.250561e-02     7.965080e-03    -9.2741e-02      0.403 (TRAH MIcro)&#xA;    6       -640.373819937145     1.765091e-01                     0.282 (TRAH MAcro)   No&#xA;    6     dE    -1.296129e-03     1.959269e-01    -2.5917e-03      0.015 (TRAH MIcro)&#xA;    6     dE    -2.948125e-03     6.172675e-02    -5.8766e-03      0.058 (TRAH MIcro)&#xA;    6     dE    -3.158307e-03     2.368722e-02    -6.2843e-03      0.072 (TRAH MIcro)&#xA;    6     dE    -3.223818e-03     1.453900e-02    -6.4061e-03      0.081 (TRAH MIcro)&#xA;    6     dE    -3.240199e-03     8.753892e-03    -6.4358e-03      0.083 (TRAH MIcro)&#xA;    7       -640.377178455884     1.523546e-02                     0.339 (TRAH MAcro)   No&#xA;    7     dE    -3.786997e-06     3.076744e-02    -7.5740e-06      0.000 (TRAH MIcro)&#xA;    7     dE    -4.542041e-05     2.321384e-02    -9.0828e-05      0.012 (TRAH MIcro)&#xA;    7     dE    -7.816377e-05     1.880261e-02    -1.5622e-04      0.026 (TRAH MIcro)&#xA;    7     dE    -1.051186e-04     8.255461e-03    -2.0988e-04      0.041 (TRAH MIcro)&#xA;    7     dE    -1.118196e-04     7.299191e-03    -2.2316e-04      0.046 (TRAH MIcro)&#xA;    7     dE    -1.173708e-04     4.963343e-03    -2.3415e-04      0.050 (TRAH MIcro)&#xA;    7     dE    -1.197205e-04     4.089835e-03    -2.3879e-04      0.052 (TRAH MIcro)&#xA;    7     dE    -1.211130e-04     3.257178e-03    -2.4154e-04      0.053 (TRAH MIcro)&#xA;    7     dE    -1.226483e-04     3.418158e-03    -2.4455e-04      0.055 (TRAH MIcro)&#xA;    7     dE    -1.236563e-04     1.912360e-03    -2.4651e-04      0.057 (TRAH MIcro)&#xA;    7     dE    -1.239379e-04     9.480742e-04    -2.4706e-04      0.057 (TRAH MIcro)&#xA;    8       -640.377312118078     4.769246e-03                     0.406 (TRAH MAcro)   No&#xA;    8     dE    -7.967881e-07     9.492192e-03    -1.5936e-06      0.000 (TRAH MIcro)&#xA;    8     dE    -5.006794e-06     6.888137e-03    -1.0013e-05      0.004 (TRAH MIcro)&#xA;    8     dE    -7.302312e-06     4.464372e-03    -1.4604e-05      0.008 (TRAH MIcro)&#xA;    8     dE    -1.089891e-05     3.565172e-03    -2.1792e-05      0.016 (TRAH MIcro)&#xA;    8     dE    -1.192319e-05     2.503452e-03    -2.3838e-05      0.018 (TRAH MIcro)&#xA;    8     dE    -1.227765e-05     1.031000e-03    -2.4546e-05      0.019 (TRAH MIcro)&#xA;    8     dE    -1.235692e-05     7.599059e-04    -2.4704e-05      0.020 (TRAH MIcro)&#xA;    8     dE    -1.237956e-05     2.413903e-04    -2.4749e-05      0.020 (TRAH MIcro)&#xA;    9       -640.377325053764     8.112221e-04                           (NR   MAcro)&#xA;    9     dE    -5.386299e-08     4.311383e-04                           (NR   MIcro)&#xA;    9     dE    -7.910103e-08     2.964767e-04                           (NR   MIcro)&#xA;    9     dE    -1.060532e-07     4.642198e-04                           (NR   MIcro)&#xA;    9     dE    -1.305736e-07     3.815819e-04                           (NR   MIcro)&#xA;    9     dE    -1.446361e-07     2.118122e-04                           (NR   MIcro)&#xA;    9     dE    -1.489166e-07     1.121944e-04                           (NR   MIcro)&#xA;    9     dE    -1.497421e-07     5.199726e-05                           (NR   MIcro)&#xA;    9     dE    -1.499570e-07     2.825067e-05                           (NR   MIcro)&#xA;    9     dE    -1.500089e-07     1.219930e-05                           (NR   MIcro)&#xA;    9     dE    -1.500233e-07     7.718047e-06                           (NR   MIcro)&#xA;    9     dE    -1.500285e-07     4.890385e-06                           (NR   MIcro)&#xA;   10       -640.377325200271     4.503103e-05                           (NR   MAcro)&#xA;   10     dE    -9.903235e-11     1.045308e-05                           (NR   MIcro)&#xA;   10     dE    -1.064703e-10     6.444989e-06                           (NR   MIcro)&#xA;   10     dE    -1.109526e-10     5.282577e-06                           (NR   MIcro)&#xA;   10     dE    -1.135574e-10     4.577945e-06                           (NR   MIcro)&#xA;   10     dE    -1.164713e-10     4.333322e-06                           (NR   MIcro)&#xA;   10     dE    -1.184555e-10     3.584652e-06                           (NR   MIcro)&#xA;   10     dE    -1.193948e-10     1.858025e-06                           (NR   MIcro)&#xA;   10     dE    -1.196783e-10     9.214222e-07                           (NR   MIcro)&#xA;   11       -640.377325200540     1.652427e-06                           (NR   MAcro)&#xA;&#xA;               *****************************************************&#xA;               *                     SUCCESS                       *&#xA;               *           SCF CONVERGED AFTER 109 CYCLES          *&#xA;               *****************************************************&#xA;&#xA;Old exchange energy                            =    -43.661155305 Eh&#xA;New exchange energy                            =    -43.661170754 Eh&#xA;Exchange energy change after final integration =     -0.000015450 Eh&#xA;Total energy after final integration           =   -640.377340650 Eh&#xA;Final COS-X integration done in                =     6.090 sec&#xA;&#xA;ORCA finished by error termination in SCF&#xA;Calling Command: mpirun -np 16 --use-hwthread-cpus /opt/orca503/orca_scf_mpi 2_mag_h_4_h2o.gbw b 2_mag_h_4_h2o &#xA;Check for SCF-logfiles&#xA;[file orca_main/maingopt.cpp, line 1229]: ORCA finished with an error in the energy calculation&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4313" LastEditorUserId="5" LastEditDate="2023-01-27T17:46:07.590" LastActivityDate="2023-11-05T15:26:47.960" Title="ORCA: Getting the error &quot;mpirun noticed that process rank 0 with PID 383161 on node exited on signal 11 (Segmentation fault).&quot;" Tags="|geometry-optimization|software-assistance|orca|" AnswerCount="1" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="10304" PostTypeId="1" CreationDate="2023-01-27T10:34:57.420" Score="2" ViewCount="42" Body="&lt;p&gt;When determining the energy barrier, it is recommended to compute the energies of reactant molecules in isolation to account for the entropy change of forming the reactant complex (hence factoring this into the energy barrier). If I have explicit solvent molecules (using both implicit and explicit solvent) with two reactants, should I treat the solvent molecules as isolated reactants as well? (i.e. ran each solvent molecule in isolation?)&lt;/p&gt;&#xA;" OwnerUserId="4313" LastActivityDate="2023-01-27T10:34:57.420" Title="How to handle explicit solvent molecules when calculating energies of reactant molecules in isolation" Tags="|density-functional-theory|geometry-optimization|orca|explicit-solvent|" AnswerCount="0" CommentCount="7" ClosedDate="2023-10-20T01:34:12.167" ContentLicense="CC BY-SA 4.0" />
  <row Id="10305" PostTypeId="1" AcceptedAnswerId="10307" CreationDate="2023-01-27T16:06:43.487" Score="4" ViewCount="283" Body="&lt;p&gt;The following is the plot of my Ising Model simulation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0Mwys.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0Mwys.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The upper one is for &lt;span class=&quot;math-container&quot;&gt;$T=3.3$&lt;/span&gt;, and the lower one is for &lt;span class=&quot;math-container&quot;&gt;$T=1.5$&lt;/span&gt;. Otherwise, in both cases, boltzmann=&lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;, MC steps=&lt;span class=&quot;math-container&quot;&gt;$1000000$&lt;/span&gt;, and the lattice dimension are &lt;span class=&quot;math-container&quot;&gt;$40\times40$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can I identify phase transition in this plot?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-01-27T17:38:35.763" Title="How can I identify phase transition from a plot of Ising model?" Tags="|ising-model|phase-transitions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10306" PostTypeId="1" CreationDate="2023-01-27T16:54:26.167" Score="1" ViewCount="126" Body="&lt;p&gt;I am trying to optimize a cluster based structure using DFT. However, just before the calculation ends the gaussian give me an error termination without even specifying the cause of this error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;46 H 0.000000&#xA;47 H 2.379115 0.000000&#xA;Symmetry turned off by external request.&#xA;Stoichiometry      C16H22Br4C12CUN2(2)&#xA;Framework group    C1[(C16H22Br4C12CUN2)]&#xA;Deg. of freedom    135&#xA;Full point group   C1  NOp   1&#xA;Rotational constants (GHZ): 0.2369033    0.0272776   0.0265363&#xA;&#xA;&#xA;        EVOLUTION&#xA;IN THE BEGINNING GOD MADE MAN.&#xA;HE WORKED THE DIRT WITH HIS HANDS.&#xA;THEN GOD DECIDED TO GIVE MAN SCIENCE.&#xA;MAN SHOULD BE USEFUL (LIKE AN APPLIANCE.) &#xA;BUT SOON MAN'S KNOWLEDGE GREW TOO GREAT, &#xA;TO THE HEADING SCIENCE HE COULDN'T RELATE&#xA;SO GOD SAID &amp;quot;LETS HAVE DIFFERENT FIELDS, &#xA;WE'LL DIVIDE THEM UP, SEE WHAT IT YIELDS.&amp;quot;&#xA;ENTER PHYSICS, CHEMISTRY, BIO &#xA;THEY SPRANG UP AROUND THE NILE.&#xA;BUT CHEMISTRY SURPASSED THE REST&#xA;FAR AND AWAY IT WAS THE BEST.&#xA;EXPERIMENT WAS GOD'S DECREE&#xA;EXPERIMENT DID CHEMISTS WITH LOTS OF GLEE&#xA;BUT SOON THEIR TESTS BEGAN TO BOG, &#xA;THEY FOUND THEMSELVES DEEP IN A FOG.&#xA;&amp;quot;GIVE US SOME HELP&amp;quot; THEY CRIED TO GOD.&#xA;GOD LOOKED AROUND, THEN GAVE THE NOD.&#xA;ENTER EINSTEIN, HEISENBERG, BOHR, &#xA;REACTION PATHS WERE CLEAR ONCE MORE.&#xA;WITH THEORISTS GOD SEND DIRECTION &#xA;AND THEN HE STOPPED, HE'D MADE PERFECTION.&#xA;         - - THOMAS A. HOLME, 1981&#xA;Error termination request processed by link 9999.&#xA;Error termination via Lnkle in /opt/apps/gaussian/09b01/em64t/19999.exe at Fri Jan 27 11:06:54 2023.&#xA;Job cpu time: 0 days 0 hours 0 minutes 38.1 seconds.&#xA;File lengths (MBytes): RWF=  152 Int= 0 D2E= 0 Chk= 32 Scr=  8&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6481" LastEditorUserId="7" LastEditDate="2023-01-27T20:47:07.977" LastActivityDate="2023-01-27T20:47:07.977" Title="Gaussian: Error termination just before the calculation ends" Tags="|density-functional-theory|gaussian|perovskites|" AnswerCount="0" CommentCount="3" ClosedDate="2023-11-05T16:19:43.693" ContentLicense="CC BY-SA 4.0" />
  <row Id="10307" PostTypeId="2" ParentId="10305" CreationDate="2023-01-27T17:38:35.763" Score="5" Body="&lt;p&gt;For a having a phase transitions, small changes in parameters like temperature or pressure causes a large-scale, qualitative change in the state of a system.&lt;/p&gt;&#xA;&lt;p&gt;To characterize the state of the system, you can use several thermodynamic variables like internal energy, magnetization, specific heat, etc.&lt;/p&gt;&#xA;&lt;p&gt;The figure below show a phase transition:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7IqXl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7IqXl.png&quot; alt=&quot;sssss&quot; /&gt;&lt;/a&gt;&#xA;Caption: &lt;em&gt;Ising phase transition as seen from classical Monte Carlo simulations with t′=0.15t and U=10t. Panels (a), (b), and (c) show the temperature dependence of the magnetization, susceptibility, and Binder cumulant, respectively. The insets are zoomed-in plots of the same data over a narrower temperature range. The temperature is plotted in units of J=4t2/U, with kB taken to be unity. Panels (d), (e), and (f) show the same data after scaling using the critical exponents of the 2D Ising model.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Reference: M. Karmakar and R. Ganesh. &amp;quot;&lt;em&gt;Attractive Hubbard model as an SO(3) system of competing phases: Supersolid order and its thermal melting&lt;/em&gt;&amp;quot;. Phys. Rev. Research &lt;strong&gt;2&lt;/strong&gt;, 023304, 2020. DOI: &lt;a href=&quot;https://doi.org/10.1103/PhysRevResearch.2.023304&quot; rel=&quot;noreferrer&quot;&gt;10.1103/PhysRevResearch.2.023304&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Your plot is Energy vs Steps, but to detect phase transition, you need to plot Energy vs Temperature, for example. You can get an average energy for the last N steps for several temperatures and make a plot, then look for large variations in Energy.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-27T17:38:35.763" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10308" PostTypeId="2" ParentId="7146" CreationDate="2023-01-27T19:43:03.033" Score="4" Body="&lt;p&gt;I found that the highest voted answer solution works, but it is missing an important step.&lt;/p&gt;&#xA;&lt;p&gt;Before even installing homebrew, you should setup the rosetta emulator in your terminal app.&lt;/p&gt;&#xA;&lt;p&gt;The details are explained &lt;a href=&quot;https://www.courier.com/blog/tips-and-tricks-to-setup-your-apple-m1-for-development/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, then the install proceeds as if it is on an Intel chip.&lt;/p&gt;&#xA;&lt;p&gt;In my case, I had an anaconda installation prior to setting up rosetta, which I thought shouldn't interfere with the QE installation. However, I realized that the ld linker was getting picked up from the anaconda binaries from the older arm64 anaconda installation. The error in qe installation was saying as if my fortran executable is not able to compile as above. After erasing the anaconda installation, the method above worked perfectly (plus fftw installation through homebrew).&lt;/p&gt;&#xA;" OwnerUserId="3870" LastEditorUserId="5" LastEditDate="2023-01-27T21:32:27.013" LastActivityDate="2023-01-27T21:32:27.013" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10309" PostTypeId="2" ParentId="10230" CreationDate="2023-01-27T21:14:11.810" Score="3" Body="&lt;p&gt;After 7 days of the bounty period not attracting any answers, I'll answer this question to the best of my abilities.&lt;/p&gt;&#xA;&lt;h1&gt;General considerations&lt;/h1&gt;&#xA;&lt;h4&gt;Geometry optimization with one method, and properties with another&lt;/h4&gt;&#xA;&lt;p&gt;This is fairly ubiquitous in matter modeling. High-accuracy methods such as FCI, CCSDTQ, and even &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;double hybrid functionals&lt;/a&gt; are almost never used for geometry optimization because the computational cost would not be worth it, yet we still have those methods implemented and frequently used, meaning that they are frequently used on geometries that either come from experiments or from other computational methods.&lt;/p&gt;&#xA;&lt;h4&gt;Geometry optimization with one method, and dielectric functions with another&lt;/h4&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Ionic_contributions_to_the_frequency_dependent_dielectric_function_of_NaCl&quot; rel=&quot;nofollow noreferrer&quot;&gt;link you provided&lt;/a&gt; about ionic and electronic contributions to the dielectric function, doesn't say anything about needing to use the same functional as the one that was used for the geometry optimization. It provides some VASP output saying that meta-GGA functionals can't be used with DFPT (implying that they &lt;em&gt;&lt;strong&gt;can&lt;/strong&gt;&lt;/em&gt; be used when doing finite differences):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#The ionic dielectric function can be calculated in two ways:################&#xA;#1# DFPT (faster), but does not allow for METAGGA use. ######################&#xA;IBRION = 8; LEPSILON=.TRUE.&#xA;#2# Finite differences (slower). ############################################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but if it was so important for the functional used for the dielectric function to be the same as the one used for geometry optimization, then it's peculiar that they never mentioned anything about that in the tutorial. The words &amp;quot;forces&amp;quot; and &amp;quot;force&amp;quot; never show up in that article either.&lt;/p&gt;&#xA;&lt;p&gt;The article also cites two papers. &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.73.045112&quot; rel=&quot;nofollow noreferrer&quot;&gt;This one&lt;/a&gt; never mentions &amp;quot;force&amp;quot; or &amp;quot;forces&amp;quot; and &lt;a href=&quot;https://www.nature.com/articles/srep28618&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; barely does, but a deeper look at those papers would be needed to see if they use (or recommend) to use the same functional for the dielectric function calculation as for geometry optimization.&lt;/p&gt;&#xA;&lt;h1&gt;Pragmatic considerations&lt;/h1&gt;&#xA;&lt;p&gt;If it was pragmatic to do the geometry optimization with the hybrid functional, then you would (pragmatically) do it. So assuming you are limited to the cost of PBE for the geometry optimization, your choice is either to do the dielectric function calculations with PBE (same functional) or a different functional. &lt;strong&gt;When using the PBE geometry, does the dielectric result depend a lot on the functional?&lt;/strong&gt; If no, then you can report results with all functionals that you used and say how small the spread of results was.&lt;/p&gt;&#xA;&lt;p&gt;You can also do the geometry optimization with other functionals that have similar cost to using PBE. &lt;strong&gt;When using the hybrid functional for the dielectric function, for various geometries that were optimized with cheaper functionals, does it depend a lot on the geometry?&lt;/strong&gt; If no, then you can report results with all geometries that you used and say how small the spread of results was.&lt;/p&gt;&#xA;&lt;p&gt;What if there was strong dependence on the functional used for the dielectric function and/or the functional used for geometry optimization? Then it matters which functional you use, and from a theoretical standpoint the &amp;quot;best functional&amp;quot; for that system would &lt;em&gt;usually&lt;/em&gt; be the one that you feature more prominently in the paper. Let's assume that PBE is the best functional you can use for the geometry optimization step, then our question becomes a matter of which result is better:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;PBE (geometry) + &amp;quot;best&amp;quot; hybrid for system (dielectric function)&lt;/li&gt;&#xA;&lt;li&gt;PBE (geometry) + PBE (dielectric function)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;We can then return to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10230/do-i-have-to-use-the-same-functional-for-dielectric-function-calculations-as-th#comment21870_10230&quot;&gt;your idea&lt;/a&gt; of comparing to experiments. Does PBE+&amp;quot;best&amp;quot; consistently match experiments better than PBE+PBE? Another thing you can do is pick a smaller system for which much more accurate calculations can be done, and see which functional/functional-combination recovers the accurate &lt;em&gt;&lt;strong&gt;theory&lt;/strong&gt;&lt;/em&gt; results the best. This might mitigate some of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10230/do-i-have-to-use-the-same-functional-for-dielectric-function-calculations-as-th#comment21871_10230&quot;&gt;wzkchem5's concern about agreement with experiment being fortuitous&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Acceptance by others&lt;/h4&gt;&#xA;&lt;p&gt;In the same comment by wzkchem5 for which I provided a hyperlink directly above, there's a concern about acceptance by others (e.g. referees). As a researcher that finished your MPhil a few months ago (based on the website in your Stack Exchange profile), there would almost always be more senior co-authors that know more about what others in the same research field will accept (or at least they'd know people that could give advice about it), but not always. People sometimes work on projects outside of their comfort zone (which can be a good thing).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If no member of the research collaboration knows whether to use the same functional for both, or to use a better functional for the dielectric function,&lt;/strong&gt; and there's no one clearly saying that you shouldn't use different functionals on an MMSE question with a bounty that lasted for its maximum duration, and no co-authors could find any advice in published papers or by personal contacts, then you can submit the paper with (PBE + &amp;quot;best&amp;quot;), knowing that one or more referee(s) &lt;em&gt;might&lt;/em&gt; tell you that it should have been done with (PBE+PBE) or (&amp;quot;best&amp;quot;+&amp;quot;best&amp;quot;). By this time you'll probably be done the &amp;quot;best&amp;quot;+&amp;quot;best&amp;quot; calculation since it would usually take weeks or months to get referee feedback (plus whatever time it takes to prepare the paper for submission). Often, the better the journal, the better (and more scrutinizing) the referees (you can also try to give the journal good referee suggestions), but not everything gets caught by referees.&lt;/p&gt;&#xA;&lt;p&gt;If using (PBE+&amp;quot;best&amp;quot;) is really such a big deal (and was somehow ignored in that VASP webpage that you gave us), it's unlikely that no referee will comment on it, so you can be &lt;em&gt;fairly&lt;/em&gt; confident about acceptance at that point, and the final test will be whether or not the wider community of article readers accepts the paper. Apart from the due diligence you already did here at MMSE, and all the other things I mentioned that I'd expect from the more senior (if any) co-authors (e.g. asking experts directly), you could present the work at a conference before publishing it, but other than those things there's not much else you can do to guarantee that the paper will be accepted in this wider sense, and this is a risk that's taken whenever embarking on a project like this.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-27T21:26:10.930" LastActivityDate="2023-01-27T21:26:10.930" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10310" PostTypeId="1" CreationDate="2023-01-28T04:20:04.443" Score="4" ViewCount="663" Body="&lt;p&gt;I need the bond length in Å for &lt;span class=&quot;math-container&quot;&gt;$\ce{O_2^{--}}$&lt;/span&gt; from &lt;a href=&quot;https://cccbdb.nist.gov/geom1x.asp&quot; rel=&quot;nofollow noreferrer&quot;&gt;this geometry database page&lt;/a&gt; (type &amp;quot;O2--&amp;quot; for the input).&lt;/p&gt;&#xA;&lt;p&gt;I get a bunch of possible values. I don't know much about those yet but after researching all those terms, I've understood that it's highly case-dependent.&lt;/p&gt;&#xA;&lt;p&gt;I've read a few studies stating that the bond length error from 6-31G* basis sets is deficient with &amp;quot;GGA, hybrid-GGA and meta-GGA functionals&amp;quot;, but I truly don't know which method on the left I should take for that, any help? Which basis set and method listed on that page, gives the smallest error for the bond length?&lt;/p&gt;&#xA;" OwnerDisplayName="iwab" LastEditorUserId="5" LastEditDate="2023-01-30T17:01:25.023" LastActivityDate="2023-02-08T14:39:04.867" Title="What is the bond length of O2--?" Tags="|computational-chemistry|geometry-optimization|spectroscopy|databases|geometry|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10311" PostTypeId="2" ParentId="10310" CreationDate="2023-01-28T09:37:32.807" Score="6" Body="&lt;p&gt;Starting from the point that it's impossible to obtain a &amp;quot;correct&amp;quot; bond length from a DFT calculation, due to the unknown exchange-correlation functional. By the way, in general terms DFTs functionals can be sorted in the so-called Jacob's ladder:&lt;/p&gt;&#xA;&lt;ol start=&quot;0&quot;&gt;&#xA;&lt;li&gt;Hartree-Fock&lt;/li&gt;&#xA;&lt;li&gt;LDA&lt;/li&gt;&#xA;&lt;li&gt;GGA&lt;/li&gt;&#xA;&lt;li&gt;meta-GGA&lt;/li&gt;&#xA;&lt;li&gt;hybrid-GGA&lt;/li&gt;&#xA;&lt;li&gt;Generalized random phase&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The upper you go, the more accurate the calculation(with the same basis set) yet the more time-consuming.&lt;/p&gt;&#xA;&lt;p&gt;Another parameter to take into consideration is the basis set: usually the bigger it is, the more accurately is possible to correctly fit the Slater exponential function of the cartesian orbital.&lt;/p&gt;&#xA;&lt;p&gt;So to answer the question: the bond length of &lt;span class=&quot;math-container&quot;&gt;$\ce{O_2^{2-}}$&lt;/span&gt; depends on which calculation level you want to take into account. Still, as the site you linked says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Maximum atom distance is 1.6765Å&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To have another piece of data, you can try to use a different type of calculation changing the theory to Coupled Cluster (CC): the NIST is currently using these results as standard. From the site you linked&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;O-O distance at CCSD(T)=FULL/def2-TZVPP is 1.631 Å&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2023-01-28T09:37:32.807" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10312" PostTypeId="2" ParentId="10310" CreationDate="2023-01-28T16:32:41.933" Score="5" Body="&lt;p&gt;If your desire is to get the best bond length &lt;em&gt;&lt;strong&gt;from that website,&lt;/strong&gt;&lt;/em&gt; then&#xA;I would begin by looking for the largest basis set (in this case it's aug-cc-pVQZ) and the method that is expected to recover the most correlation energy (in this case it's CCSD(T)=FULL), so the CCSD(T)=FULL/aug-cc-pVQZ bond length of 1.540 Å is a good starting point.&lt;/p&gt;&#xA;&lt;p&gt;However there's caveats, and the most immediate ones that come to my mind are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Since double-augmentation caused the CCSD(T)=FULL/aug-cc-pVTZ bond length to drop by about 0.16 Å (that's huge!) with CCSD(T)=FULL/daug-cc-pVTZ, I would want to calculate CCSD(T)=FULL/daug-cc-pVQZ to see if the corresponding aug-cc-pVQZ bond length of 1.540 Å drops too.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;These calculations are likely done with a frozen core (only correlating 14 electrons instead of 18). Since it doesn't look like they've done any all-electron calculations (for which we'd see basis sets like cc-p&lt;em&gt;&lt;strong&gt;C&lt;/strong&gt;&lt;/em&gt;VXZ with the &lt;em&gt;&lt;strong&gt;C&lt;/strong&gt;&lt;/em&gt; being the important letter there), the best we can do is to use the calculation CCSD(T)=FULL that they said was done with an effective core potential and Def2TZVPP: 1.631  Å (this is the number in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10311/5&quot;&gt;Andrea's answer&lt;/a&gt;). However, this is again not with a QZ basis set, so it might be wise to look at how much the all-electron calculation changes the value of the frozen-core calculation with the same basis set (but for frozen-core calculations they don't explicitly mention Def2TZVP, only TZVP, for which the bond length dropped by about 0.02 Å when correlating the core electrons).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Finally I'll point out that the &amp;quot;composite&amp;quot; methods mentioned at the very top of the page are &lt;em&gt;meant&lt;/em&gt; to be better than single-energy calculations done with just one method and one basis set, but unfortunately the  &lt;a href=&quot;https://cccbdb.nist.gov/glossaryx.asp&quot; rel=&quot;noreferrer&quot;&gt;glossary&lt;/a&gt; doesn't say what &amp;quot;CBS-Q&amp;quot; means. I would hope that it means CCSD(T)=FULL with a basis set extrapolation done with the aug-cc-pVTZ and aug-cc-pVQZ results, which would mean 1.528  Å is likely the best bond length, with the caveat that this might go down by ~0.16 Å if doubly-augmenting the basis set, and it could go down by another ~0.02 Å if correlating all electrons (this is a very crude estimate of the all-electron correction). They also reported a bond length of 1.621 Å with the G4 composite method, which is not likely to be more accurate than CCSD(T)=FULL/CBS(aug-cc-pV(T,Q-&amp;gt; ∞)Z) but at least &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.2436888&quot; rel=&quot;noreferrer&quot;&gt;we know what it is&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Summary:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Method&lt;/th&gt;&#xA;&lt;th&gt;Corrections&lt;/th&gt;&#xA;&lt;th&gt;Bond Length (A)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/aug-cc-pVQZ&lt;/td&gt;&#xA;&lt;td&gt;None&lt;/td&gt;&#xA;&lt;td&gt;1.540&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/aug-cc-pVQZ&lt;/td&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/daug-cc-pVTZ - CCSD(T)=FULL/aug-cc-pVTZ&lt;/td&gt;&#xA;&lt;td&gt;≈1.380&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/aug-cc-pVQZ&lt;/td&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/daug-cc-pVTZ - CCSD(T)=FULL/aug-cc-pVTZ  &amp;amp; all-electron&lt;/td&gt;&#xA;&lt;td&gt;≈1.360&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CBS-Q&lt;/td&gt;&#xA;&lt;td&gt;None&lt;/td&gt;&#xA;&lt;td&gt;1.528&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CBS-Q&lt;/td&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/daug-cc-pVTZ - CCSD(T)=FULL/aug-cc-pVTZ&lt;/td&gt;&#xA;&lt;td&gt;≈1.37&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CBS-Q&lt;/td&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/daug-cc-pVTZ - CCSD(T)=FULL/aug-cc-pVTZ  &amp;amp; all-electron&lt;/td&gt;&#xA;&lt;td&gt;≈1.35&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;G4&lt;/td&gt;&#xA;&lt;td&gt;None  &amp;amp; all-electron&lt;/td&gt;&#xA;&lt;td&gt;≈1.360&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;CCSD(T)=FULL/Def2TZVPP&lt;/td&gt;&#xA;&lt;td&gt;None&lt;/td&gt;&#xA;&lt;td&gt;1.631 (Andrea's answer)&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;&lt;strong&gt;So the NR-CPN (non-relativistic, with clamped, point-sized nuclei) bond length is probably somewhere between 1.3 an 1.7 Å.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The real bond length could be obtained by doing a CBS extrapolation using FCI-level calculations with aug-cc-pCV8Z and aug-cc-pCV9Z, then adding corrections for relativity, QED, Born-Oppenheimer breakdown, finite nuclear size effects, etc.) and perhaps calculating a full potential energy curve and solving the rovibrational Schroedinger equation to find where the ground vibrational wavefucntion has its maximum (since a full non-Born-Oppenheimer calculation is &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/cr200419d&quot; rel=&quot;noreferrer&quot;&gt;unlikely to be possible for more than about 6 electrons&lt;/a&gt; and even less likely for an 14-18 electron system unless there's an algorithmic or hardware breakthrough).&lt;/p&gt;&#xA;&lt;p&gt;You can also get &lt;a href=&quot;https://cccbdb.nist.gov/expgeom1x.asp&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;experimental&amp;quot; geometries from that same site&lt;/a&gt;, but they don't seem to have one for this molecule.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-01-28T16:32:41.933" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10313" PostTypeId="1" AcceptedAnswerId="10322" CreationDate="2023-01-28T19:11:37.657" Score="4" ViewCount="84" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/questions/746687/why-does-the-delta-term-exist-in-the-density-density-correlation-for-simple-l&quot;&gt;Cross-posted from the PhysicsSE.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am reading &lt;em&gt;Theory of Simple Liquids&lt;/em&gt; by Hansen and McDonald, and they in chapter 3, they describe the density-density correlation for a simple liquid in the grand canonical ensemble. This is how they have defined it:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$H^{(2)}(r,r') = \langle [\rho (r) - \langle \rho (r) \rangle ][ \rho (r') - \langle \rho (r') \rangle ]\rangle \tag{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ = \rho ^{(2)}(r,r') - \rho ^{(1)}(r)\rho ^{(1)}(r') + \rho ^{(1)}(r) \delta (r-r').\tag{2}$$&lt;/span&gt;&#xA;This is my understanding of where the terms in the RHS comes from. I understand that the two-particle density &lt;span class=&quot;math-container&quot;&gt;$\rho^{(2)}$&lt;/span&gt; term arises from:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\langle \rho (r) \rho (r') \rangle\tag{3}$$&lt;/span&gt;&#xA;in the RHS.&lt;/p&gt;&#xA;&lt;p&gt;The second term in the RHS comes from expanding the the product and taking like terms together.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$-\rho ^{(1)}(r)\rho ^{(1)}(r') = -\langle \rho(r) \langle \rho (r') \rangle \rangle - \langle \rho(r') \langle \rho (r) \rangle \rangle + \rho ^{(1)}(r) \rho ^{(1)}(r'),\tag{4}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\rho^{(1)}(r)$&lt;/span&gt; is the average single-particle density at &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, for a homogeneous liquid.&lt;/p&gt;&#xA;&lt;p&gt;But I still do not get why that &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;-function exists there. Is the &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;-function just there to say that if the two particles are in the same spot (&lt;span class=&quot;math-container&quot;&gt;$r=r'$&lt;/span&gt;), the density correlation is... maximized? How does the &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; fall out of the averaging, mathematically?&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me!&lt;/p&gt;&#xA;" OwnerUserId="1169" LastEditorUserId="5" LastEditDate="2023-01-31T04:22:02.533" LastActivityDate="2023-01-31T05:22:34.217" Title="Why does the  (delta) term exist in the density-density correlation for simple liquids?" Tags="|statistical-thermodynamics|from-phys-se|derivations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10314" PostTypeId="1" AcceptedAnswerId="10315" CreationDate="2023-01-30T07:44:54.777" Score="4" ViewCount="154" Body="&lt;p&gt;I am having a doubt regarding electrode setup in scattering region calculation (transiesta) firstly, I have done molecular junction relaxation using using 3 layers of electrodes attached to both the sides of molecule. and after that I removed this 3 layers of electrodes and replaced it with 6 layers of electrode for scattering region calculation. My doubt is should I include .tshs files of electrode containing 6 layers or .tshs containing remaining 3 layer except layers used in junction relaxation.&lt;/p&gt;&#xA;&lt;p&gt;I am currently using remaining layers .tshs files except those layers invovled in junction relaxation is it ok or I need to change.&lt;/p&gt;&#xA;" OwnerUserId="6561" LastActivityDate="2023-01-30T14:38:59.830" Title="regarding electrode setup in scattering region" Tags="|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10315" PostTypeId="2" ParentId="10314" CreationDate="2023-01-30T12:17:56.370" Score="3" Body="&lt;p&gt;As far as I know, if the 3-layer electrode is enough to ensure the interaction with only one neighboring supercell along the transport direction, you can safely use the latter including the .TSHS file of the corresponding electrode size. The latter should be exactly the same coordinates as in the normal siesta run.&lt;/p&gt;&#xA;&lt;p&gt;When constructing the device+electrodes model, thus including the molecule, you should add some layers of the electrode that relax (and thus connect the molecule to the bulk electrode) and they shouldn't be included in the first electrode calculation (and thus the .TSHS file that you're using).&lt;/p&gt;&#xA;&lt;p&gt;Please, refer to the Siesta manual from pg. 135 for more insights about the electrode set-up.&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-01-30T14:38:59.830" LastActivityDate="2023-01-30T14:38:59.830" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10316" PostTypeId="1" CreationDate="2023-01-30T17:05:48.683" Score="4" ViewCount="123" Body="&lt;p&gt;I am struggling to find an explanation for the difference between a spectral band structure task and a normal band structure task. I have attached example .param files. Also, does the BS_XC_FUNCTIONAL have the same implementation as the SPECTRAL_XC_FUNCTIONAL parameters?&lt;a href=&quot;https://i.stack.imgur.com/M5bBK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/M5bBK.png&quot; alt=&quot;Spectral Bandstructure .param file&quot; /&gt;&lt;/a&gt;&#xA;[&lt;img src=&quot;https://i.stack.imgur.com/4wJu1.png&quot; alt=&quot;Normal CASTEP Bandstructure .param file&quot; /&gt;]&lt;a href=&quot;https://i.stack.imgur.com/4wJu1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6627" LastActivityDate="2023-01-31T01:55:10.560" Title="CASTEP Spectral Bandstructure Tasks" Tags="|band-structure|castep|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10317" PostTypeId="1" AcceptedAnswerId="10323" CreationDate="2023-01-30T17:15:50.413" Score="4" ViewCount="71" Body="&lt;p&gt;I'm now currently simulating the system in which charged peptide (ARG, LYS, ASP, GLU) is solvated in electrolyte solution. MD simulation was performed based on the AMBER14ffSB force field, but in here I'm not much sure whether this force field accurately models the peptide-ion interaction or not. For instance, trajectory shows a very strong binding between carboxylate ion (C-termini or ASP, GLU side-chain) and sodium ion. I once heard that there are some issues regarding such circumstances, as such some electrostatic interactions are too much overestimated compared to the experimental results. Below is the observed snapshot where blue particles are the sodium ion, coordinated with several carboxylate ions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/w3KPM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w3KPM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is there any preferred force field in bio-MD community that is known to be superior to other one for capturing such electrostatic interaction? Any recommendation is highly welcomed!&lt;/p&gt;&#xA;" OwnerUserId="1009" LastEditorUserId="5" LastEditDate="2023-01-30T18:42:55.013" LastActivityDate="2023-01-31T09:06:53.153" Title="Force field for charged peptide-ion system" Tags="|molecular-dynamics|proteins|forcefields|biomaterials|structural-biology|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10318" PostTypeId="1" AcceptedAnswerId="10325" CreationDate="2023-01-30T19:16:45.217" Score="2" ViewCount="246" Body="&lt;p&gt;I need  the number of independent atoms in the asymmetric unit&#xA;I have to introduce them in this form:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# [atom type] [number] [WP] [x] [y] [z]&#xA;Pb  1   4e  0.0000  0.0000  0.7500&#xA;Pb  2   8f  0.0000  0.0000  0.8563&#xA;P   1   8f  0.0000  0.0000  0.9511&#xA;O   1   8f  0.0000  0.0000  0.9145&#xA;O   2   8f  0.2715  0.7285  0.8885&#xA;O   3   8f  0.9570  0.5000  0.1170&#xA;O   4   8f  0.7285  0.2715  0.6115 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(this is just an example)&#xA;I only have data given like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a,b,c, alpha, beta, gamma&#xA; 5.801  5.801  7.906 90.00 90.00 90.00 Sym.group:  131&#xA;          occ      x             y           z&#xA;Ca1        1.0     0.500000      0.500000     0.25000&#xA;Ca1        1.0     0.500000      0.500000     0.74999&#xA;Ca1        1.0     0.500000      1.000000     0.24999&#xA;Ca1        1.0     1.000000      0.500000     0.75000&#xA;Si1        1.0     1.000000     0.500000     0.250000&#xA;Si1        1.0     0.500000     0.000000     0.750000&#xA;O1         1.0     0.000000     0.227421     0.250001&#xA;O1         1.0     1.000000     0.772579     0.250001&#xA;O1         1.0     0.227420     1.000000     0.749999&#xA;O1         1.0     0.772580     1.000000     0.749999&#xA;O1         1.0     0.000000     1.000000     0.000000&#xA;O1         1.0     0.000000     1.000000     0.500000&#xA;O1         1.0     0.500000     0.500000     0.000000&#xA;O1         1.0     0.500000     0.500000     0.500000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I extract which are the independent atoms in the asymmetric unit and the Wyckoff positions? I thought that if you knew the space group, then someone you could determine which atoms were within the asymmetric unit, but I've nothing about it. The same goes for the Wyckoff positions. I have tried with VESTA without success.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6544" LastEditorUserId="5" LastEditDate="2023-01-30T19:22:12.620" LastActivityDate="2023-01-31T11:11:41.817" Title="How do I know which is the asymmetric unit of a unit cell?" Tags="|crystallography|symmetry|vesta|geometry|space-groups|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10319" PostTypeId="2" ParentId="10275" CreationDate="2023-01-30T21:31:23.267" Score="1" Body="&lt;p&gt;I can't give you an elegant solution in that if a calculator does not supply stresses, then you cannot get them.  However, the definition of stress allows for a numerical approach to be taken and you may be able to use &lt;a href=&quot;https://gitlab.com/ase/ase/blob/master/ase/calculators/calculator.py#L848&quot; rel=&quot;nofollow noreferrer&quot;&gt;this function&lt;/a&gt; in ASE to do so.&lt;/p&gt;&#xA;&lt;p&gt;You may have to patch your calculator so that get_stress actually calls get_numerical_stress, but this is relatively simple if you derive a new class or simply run &lt;code&gt;calc.get_stress = calc.get_numerical_stress&lt;/code&gt;.  The performance will be much worse since it will do finite difference with respect to cell vectors, but if you need stress then this may be the only option.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2023-01-30T21:36:23.137" LastActivityDate="2023-01-30T21:36:23.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10320" PostTypeId="2" ParentId="10316" CreationDate="2023-01-31T01:55:10.560" Score="3" Body="&lt;p&gt;These input &lt;code&gt;param&lt;/code&gt; files both compute the same thing (the bandstructure or DOS, depending on the k-point set you provide) but the &amp;quot;spectral&amp;quot; route uses the newer spectral module, which has a more robust and efficient optimisation algorithm.&lt;/p&gt;&#xA;&lt;p&gt;In older versions of CASTEP the spectral module did not support all of the functionality of the bandstructure module, which is why both methods were supported. I'm not aware of any missing functionality in the spectral module now, and at some point in the future the old bandstructure module will be retired, and&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;task : bandstructure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;will be updated to just be an alias for&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;task : spectral&#xA;spectral_task : bandstructure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(the &lt;code&gt;spectral_task&lt;/code&gt; keyword is mostly to tell CASTEP not to bother computing things like optical matrix elements).&lt;/p&gt;&#xA;&lt;p&gt;There is one thing you have to be careful with, which is that a spectral calculation will read the spectral kpoint keywords from the cell file (&lt;code&gt;spectral_kpoint_path&lt;/code&gt; etc) whereas a bandstructure calculation will read the bandstructure k-point keywords (&lt;code&gt;bs_kpoint_path&lt;/code&gt; etc).&lt;/p&gt;&#xA;&lt;p&gt;As for the exchange-correlation functional keywords, I think the implementation is identical.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-01-31T01:55:10.560" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10321" PostTypeId="2" ParentId="10247" CreationDate="2023-01-31T02:29:21.830" Score="7" Body="&lt;p&gt;This is a difficult question to answer, because it really depends what you mean by &amp;quot;OK&amp;quot;. There is certainly no fundamental problem with an initial guess Hessian which is the identity matrix, and any quasi-Newton method will attempt to improve this iteratively. The improvements are done by approximating the second derivative matrix (Hessian) based on information from two consecutive force evaluations, by a term which is like the change in force divided by the change in configuration. I say &amp;quot;like&amp;quot; because both force and configuration are &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt;-dimensional vectors, so the division operation is not uniquely defined. In most schemes the Hessian update is explicit, but some schemes (e.g. conjugate gradients) use an implicit Hessian update.&lt;/p&gt;&#xA;&lt;p&gt;Although there is no fundamental technical problem to this choice of initial Hessian, the &lt;em&gt;performance&lt;/em&gt; and even &lt;em&gt;stability&lt;/em&gt; of the method is likely to depend quite strongly on how reasonable your initial Hessian is. Quasi-Newton methods assume your system is &amp;quot;near&amp;quot; to the minimum, in the sense that the energy landscape is well approximated by a quadratic (quasi-Newton methods ignore cubic and higher-order terms), and it's important that your system stays within this quadratic region. If you stray into areas of configuration space where the energy surface is highly non-quadratic and/or nearer to a maximum, then the Hessian updates can become dominated by the higher-order terms (effectively noise) which leads to poorer and poorer Hessian approximations.&lt;/p&gt;&#xA;&lt;p&gt;The efficiency of an optimisation method is generally related to what's called the &lt;em&gt;condition number&lt;/em&gt;, &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;, which is the ratio between the largest and smallest eigenvalues (&lt;span class=&quot;math-container&quot;&gt;$\lambda_i$&lt;/span&gt;) of the Hessian,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\theta = \left\vert\frac{\lambda_\mathrm{max}}{\lambda_\mathrm{min}}\right\vert. \tag{1}&#xA;$$&lt;/span&gt;&#xA;If &lt;span class=&quot;math-container&quot;&gt;$\theta=1$&lt;/span&gt;, then even a steepest descent method should converge to the minimum in a single iteration. More generally, the number of iterations steepest descent methods take scales as &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt;, whereas the number of iterations quasi-Newton methods take scales as &lt;span class=&quot;math-container&quot;&gt;$\sqrt{\theta}$&lt;/span&gt; (although these scaling arguments assume the initial configuration is in the quadratic well).&lt;/p&gt;&#xA;&lt;p&gt;Choosing a good initial Hessian is equivalent to &lt;em&gt;preconditioning&lt;/em&gt;, a technique to improve the condition number by changing the coordinate system to one in which the Hessian is &amp;quot;more spherical&amp;quot; (i.e. the eigenvalues are closer to each other). The identity matrix doesn't change the coordinates at all, and so it doesn't help (but it doesn't hurt either); however, even a reasonable guess of the extreme eigenvalues might improve the condition number by a factor of 10 or so, resulting in the method only needing approximately a third (&lt;span class=&quot;math-container&quot;&gt;$\frac{1}{\sqrt{10}}$&lt;/span&gt;) of the iterations and also being more stable.&lt;/p&gt;&#xA;&lt;p&gt;In the case of molecules, a large condition number can arise because stretching or compressing a bond is typically much more energetic than bond-bending or twisting; i.e. the diagonal elements of the Hessian corresponding to displacement a bond are large, but those relating to tangential displacements are small - a classic case of a poorly conditioned problem.&lt;/p&gt;&#xA;&lt;p&gt;There are lots of ways you could think of preconditioning it, you could estimate the bond directions and the ratio of the energy curvature along them to a tangential direction. One approach which can be very effective is to use a simple proxy model forcefield, like Lennard-Jones, and calculate its inverse Hessian. It won't be correct, but it has some of the right behaviour and might improve the condition number.&lt;/p&gt;&#xA;&lt;p&gt;You might find it helpful to look at the work of Christoph Ortner &amp;amp; James Kermode in this area, which includes work on Hessians for transition state searches:&lt;/p&gt;&#xA;&lt;p&gt;A &amp;quot;universal preconditioner&amp;quot; for materials' Hessians, Packwood et al, &lt;a href=&quot;https://doi.org/10.1063/1.4947024&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.4947024&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Preconditioning NEB transition state searches, Makri et al, &lt;a href=&quot;https://doi.org/10.1063/1.5064465&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.5064465&lt;/a&gt; .&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2023-02-04T00:35:06.847" LastActivityDate="2023-02-04T00:35:06.847" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10322" PostTypeId="2" ParentId="10313" CreationDate="2023-01-31T03:50:38.620" Score="3" Body="&lt;p&gt;While deriving this formula in Ch. 3 of your source, the author references equation 2.5.13,&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\rho_N^{(2)}\left(\mathbf{r}, \mathbf{r}^{\prime}\right)=\left\langle\sum_{i=1}^N \sum_{j=1}^N{}^{'} \delta\left(\mathbf{r}-\mathbf{r}_i\right) \delta\left(\mathbf{r}^{\prime}-\mathbf{r}_j\right)\right\rangle.\tag{2.5.13}&#xA;\end{equation}&lt;/span&gt;&#xA;The author calls &lt;span class=&quot;math-container&quot;&gt;$\rho^{(2)}\left(\mathbf{r},\mathbf{r}'\right)$&lt;/span&gt; an analogue of the above.&lt;/p&gt;&#xA;&lt;p&gt;Notice the second sum has a prime indicating it is missing a set of terms where &lt;span class=&quot;math-container&quot;&gt;$i = j$&lt;/span&gt;. Those missing terms are&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\left\langle\sum_{i=1}^{N}\delta\left(\mathbf{r} - \mathbf{r}_{i}\right)\delta\left(\mathbf{r}' - \mathbf{r}_{i}\right)\right\rangle = \left\langle\sum_{i=1}^{N}\delta\left(\mathbf{r} - \mathbf{r}_{i}\right)\right\rangle\delta\left(\mathbf{r} - \mathbf{r}'\right) =\rho^{(1)}\left(\mathbf{r} \right)\delta\left(\mathbf{r} - \mathbf{r}'\right),&#xA;\end{equation}&lt;/span&gt;&#xA;where the final equality comes from Eq. (3.1.2) in the source. Anytime &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r} \neq \mathbf{r}'$&lt;/span&gt;, the whole thing vanishes due to the two coupled &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt;-functions.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2023-01-31T05:22:34.217" LastActivityDate="2023-01-31T05:22:34.217" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10323" PostTypeId="2" ParentId="10317" CreationDate="2023-01-31T04:42:10.060" Score="5" Body="&lt;p&gt;If you are looking at the interactions between a charged peptide and ions, I would recommend that you look into polarizable FFs that are available in literature. I know that OPLS and CHARMM have polarizable FFs available. They would generally give you better results because the charges are able to respond to the local environment.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Longer Answer:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;why additive FF is generally not suitable for investigating interactions between charged molecules and ions?&lt;/p&gt;&#xA;&lt;p&gt;additive FFs are generally based on fixed-point charges, which mean that they are unable to account for charge transfer, ion-dipole, ion-induced dipole or any of such interactions. It might happen that few interactions are over-represented or under-represented while using such FFs. CHARMM has a mechanism called NBFIX, where you override the original value in the parameter file with an updated value, that is more appropriate for some systems.&lt;/p&gt;&#xA;&lt;p&gt;Please note that the parameters are built to be transferable across multiple molecules, and it is impractical to build specific parameters for every system that we encounter.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What improvement does use of Polarizable FF bring?&lt;/p&gt;&#xA;&lt;p&gt;Fair Note: I only have experience with Classical Drude polarizable FF in CHARMM, so I can comment only on that.&lt;/p&gt;&#xA;&lt;p&gt;In comparison to additive FF, Classical Drude polarizable FF has an extra particle (Drude particle) that helps in the capture of such interactions. Accurate capture of such interactions are important if you are looking at interactions between a charged molecule and an ion. You can refer to this &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2023/na/d2na00733a&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; to get a better understanding of why Drude is better than additive FFs.&lt;/p&gt;&#xA;&lt;p&gt;However, please note that employing Drude polarizable FF for your calculations would also mean that you would need to spend more computational resources at studying the same system, in comparison to additive FF simulations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-01-31T09:06:53.153" LastActivityDate="2023-01-31T09:06:53.153" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10324" PostTypeId="1" AcceptedAnswerId="10346" CreationDate="2023-01-31T09:07:05.223" Score="4" ViewCount="331" Body="&lt;p&gt;&lt;strong&gt;Edit3:&lt;/strong&gt; HemanthHaridas' answer explained why BURAI gave me the result. However, when I opened the same output file using XCrySDen, I got a completely different result (the correct one). So, even though I accepted the answer, I am opening this question again. Since XCrySDen is maintained in a more regular manner than BURAI, I trust the result of XCrySDen cannot understand the discrepancy between XCrySDen result and BURAI result (or alternatively, the result obtained using @HemanthHaridas' explanation).&lt;/p&gt;&#xA;&lt;p&gt;I was following a youtube tutorial for finding the lattice constant of Si crystal: &lt;a href=&quot;https://www.youtube.com/watch?v=v1LcTLSIkZI&quot; rel=&quot;nofollow noreferrer&quot;&gt;Project: 3.1 Si crystal constant and density | Quantum Espresso Tutorial 2019&lt;/a&gt;. The input file I used is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation = 'vc-relax'&#xA;    prefix = 'si'&#xA;    etot_conv_thr = 1e-5&#xA;    forc_conv_thr = 1e-4&#xA;/&#xA;&amp;amp;system&#xA;    ibrav=2 &#xA;    celldm(1) =14 &#xA;    nat=2 &#xA;    ntyp=1&#xA;    ecutwfc=30&#xA;/&#xA;&amp;amp;electrons&#xA;    conv_thr=1e-7&#xA;/&#xA;&amp;amp;ions&#xA;/&#xA;&amp;amp;cell&#xA;    cell_dofree='all'&#xA;/&#xA;ATOMIC_SPECIES&#xA; Si  28.0855  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS (alat)&#xA; Si 0.00 0.00 0.00 0 0 0 &#xA; Si 0.25 0.25 0.25 0 0 0&#xA;K_POINTS (automatic)&#xA;  4 4 4 0 0 0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I run this, I got the output file which gave me the (almost) correct value for the lattice constant of the Si which I found from the output/log file (5.48 Å). However, inside BURAI GUI, there is a window to view the convergence for geometric convergence which indicates a wrong result as can be seen from the image below. &lt;a href=&quot;https://i.stack.imgur.com/RVuTe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RVuTe.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is why is the lattice constant converging to a different (wrong) value in the graph, while the output file gives the correct lattice constant (within an error of 1%) after the end of the SCF iteration?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit1&lt;/strong&gt;: The output file &lt;em&gt;espresso.log.opt&lt;/em&gt; can be found &lt;a href=&quot;https://rentry.co/w577d/raw&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The cell parameters in each step and the volume can be found inside denoted by &lt;code&gt;CELL_PARAMETERS&lt;/code&gt; and &lt;code&gt;new unit-cell volume&lt;/code&gt;, respectively. To find the cell parameter in Bohr radius, I first divided the cell parameter by 0.5 and then multiplied by alat=14. To convert it to Å, one needs to multiply the Bohr radius by 0.529&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit2:&lt;/strong&gt; alat multiplier and the x, y and z axes lengths at each step&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 13.999998  0.696568  0.696568  0.696568&#xA; 13.999998  0.680759  0.680759  0.680759&#xA; 13.999998  0.657046  0.657046  0.657046&#xA; 13.999998  0.644397  0.644397  0.644397&#xA; 13.999998  0.625422  0.625422  0.625422&#xA; 13.999998  0.611748  0.611748  0.611748&#xA; 13.999998  0.591238  0.591238  0.591238&#xA; 13.999998  0.560472  0.560472  0.560472&#xA; 13.999998  0.514324  0.514324  0.514324&#xA; 13.999998  0.526698  0.526698  0.526698&#xA; 13.999998  0.523420  0.523420  0.523420&#xA; 13.999998  0.523121  0.523121  0.523121&#xA; 13.999998  0.523121  0.523121  0.523121&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="5" LastEditDate="2023-02-27T18:26:20.727" LastActivityDate="2023-02-27T18:26:20.727" Title="Why does BURAI give the correct output file but wrong graph?" Tags="|quantum-espresso|graphical-user-interface|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10325" PostTypeId="2" ParentId="10318" CreationDate="2023-01-31T11:11:41.817" Score="3" Body="&lt;p&gt;I recommend you to take a look at the &lt;a href=&quot;https://www.cryst.ehu.es/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bilbao Crystallographic Server&lt;/a&gt;. There are several tools can help you.&lt;/p&gt;&#xA;&lt;p&gt;One of them is inside the &lt;em&gt;Space-group symmetry&lt;/em&gt; section. Specifically the &lt;em&gt;Wyckoff Positions of Space Groups&lt;/em&gt; (WYCKPOS) where you input the space group and it returns a list of the positions AND, at the end, a section where you enter a position and it return which is the corresponding Wyckoff position:&lt;/p&gt;&#xA;&lt;p&gt;Input:&lt;br /&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/Tqiab.png&quot; height=&quot;400&quot;&gt;&lt;/p&gt;&#xA;&lt;p&gt;Output:&lt;br /&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/qnbbk.png&quot; height=&quot;400&quot;&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also, you can use the &lt;em&gt;Structure Data Converter &amp;amp; Editor&lt;/em&gt; tool (in the &lt;em&gt;Structure Utilities&lt;/em&gt; section) where you can convert between the following file formats:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;BCS: The Bilbao Crystallographic Server (BCS) file format is the&#xA;standard format used throughout the server's tools. It contains the&#xA;space-group, lattice and sites information (for the asymmetric unit&#xA;shell) assumed to be given in standard setting (one can use our&#xA;SETSTRU tool to convert to other settings). As of the moment, the&#xA;occupational and magnetic information are not supported.&lt;/p&gt;&#xA;&lt;p&gt;CIF: The&#xA;Crystallographic Information File format is developed by the&#xA;International Union of Crystallography and is a widely used,&#xA;standard-assumed file format. Although it has many supported tags for&#xA;defining additional structural information, unfortunately a consensus&#xA;on the representation of magnetic information hasn't been reached yet.&lt;/p&gt;&#xA;&lt;p&gt;mCIF: As the ISOCIF program, developed by Harold T. Stokes and Branton&#xA;J. Campbell started supporting magnetic space groups and magnetic&#xA;moment information, Stokes and Campbell extended the CIF dictionaries&#xA;by adding magnetic related tags such as&#xA;&amp;quot;_magnetic_space_group_BNS_number&amp;quot;,&#xA;&amp;quot;_magnetic_space_group_symop_operation_timereversal&amp;quot;,&#xA;&amp;quot;_magnetic_atom_site_moment_crystalaxis_mx&amp;quot;, etc.. To discern this&#xA;extended CIF file, they also relabeled the existing tags like&#xA;&amp;quot;_magnetic_cell_length_a&amp;quot;, &amp;quot;_magnetic_space_group_symop_operation_xyz&amp;quot;&#xA;and thus the mCIF format came into being. Although one can store all&#xA;magnetic related information to a mCIF file, its -for the moment-&#xA;incompatibility with most of the crystallographic software makes it&#xA;difficult to import the magnetic data contained within.&lt;/p&gt;&#xA;&lt;p&gt;VESTA:&#xA;Developed by Koichi Momma, VESTA is a highly advanced, yet simple to&#xA;use 3D visualization program for structural data. Even though it has&#xA;no direct support for magnetic space groups / magnetic moments,&#xA;nevertheless they can be represented by assigning vectors to atomic&#xA;sites.&lt;/p&gt;&#xA;&lt;p&gt;VASP: The Vienna Ab initio Simulation Package, developed by&#xA;Jürgen Hafner, Georg Kresse, Doris Vogtenhuber &amp;amp; Martijn Marsman, is&#xA;mainly an ab-initio calculation software, accepting its structure&#xA;input data in P1. Currently our Structure Data Converter &amp;amp; Editor tool&#xA;only supports the POSCAR/CONTCAR files with &amp;quot;Direct/Fractional&amp;quot; atomic&#xA;coordinates.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-01-31T11:11:41.817" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10326" PostTypeId="1" CreationDate="2023-01-31T14:06:00.473" Score="4" ViewCount="299" Body="&lt;p&gt;I am trying to optimize a copper supercell for the study of chalcones adsorption using Quantum ESPRESSO, however, the size of my supercell is large (&amp;gt;200 atoms) and QE can not handle it.&lt;/p&gt;&#xA;&lt;p&gt;What is an alternative for it?&lt;/p&gt;&#xA;" OwnerUserId="5898" LastActivityDate="2023-01-31T14:12:54.593" Title="Optimzation for Large supercell" Tags="|density-functional-theory|surfaces|solid-state-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10327" PostTypeId="2" ParentId="10326" CreationDate="2023-01-31T14:12:54.593" Score="5" Body="&lt;p&gt;It should be possible to use Quantum Espresso to handle more than 200 atoms.&lt;/p&gt;&#xA;&lt;p&gt;I guess you are studying a surface, in that case, please note that in PW-based codes the vacuum makes your calculation more expensive since it is considered as if it was matter. For this reason, you can try to lower a little the vacuum (while always ensuring convergence). Always on the 2D case, you can try to use a Coulomb potential along the non-periodic directions to ease the convergence.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, if you are optimizing the cell and you need to study absorption, you can try to consider the optimization of only 1/2 layers on the surface while keeping frozen the bottom layers.&lt;/p&gt;&#xA;&lt;p&gt;To finally answer your question, if you don't want to use Quantum Espresso, there are alternative PW codes (such as Abinit, VASP) and localized basis sets that would ease the fact that you are dealing with vacuum (such as Siesta).&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-01-31T14:12:54.593" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10328" PostTypeId="1" CreationDate="2023-01-31T15:58:37.187" Score="2" ViewCount="69" Body="&lt;pre&gt;&lt;code&gt;mol = gto.M(atom='O 0 0 0; O 0 0 1; O 0 1 0; O 0 1 1; &#xA;                  O 1 0 0; O 1 0 1; O 1 1 0; O 1 1 1;', basis='6-31G')&#xA;sparse_eri = mol.intor('int2e_sph', aosym='s8')&#xA;full_eri   = mol.intor('int2e_sph', aosym='a1')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For educational purposes, I'd like to understand how I could transform &lt;code&gt;sparse_eri&lt;/code&gt; into &lt;code&gt;full_eri&lt;/code&gt;; I'm interested in the general case, that is, something which would work independent of symmetries in the geometry or choice of basis set. &lt;strong&gt;Is there a simple way to relate the two so that I can code it?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;" OwnerUserId="6633" LastEditorUserId="6633" LastEditDate="2023-02-01T15:27:16.947" LastActivityDate="2023-02-01T15:27:16.947" Title="PySCF: Two electron integrals, translate between aosym=s8 and full tensor" Tags="|symmetry|pyscf|integrals|fcidump|" AnswerCount="0" CommentCount="6" ClosedDate="2023-10-01T14:43:48.657" ContentLicense="CC BY-SA 4.0" />
  <row Id="10331" PostTypeId="2" ParentId="9382" CreationDate="2023-01-31T21:47:55.647" Score="1" Body="&lt;p&gt;The reason this happens is that I was using the dynamic bonds setting in VMD. The solution to this is to simply change up how bonds are calculated in VMD.&lt;/p&gt;&#xA;" OwnerUserId="1169" LastActivityDate="2023-01-31T21:47:55.647" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10332" PostTypeId="2" ParentId="9937" CreationDate="2023-01-31T21:55:40.543" Score="9" Body="&lt;p&gt;Yes, this can be done using two different functions in RDkit, one for the adjacency matrix (A) and one for distance matrix (D). In this case, A*D is what you want.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit.Chem import MolFromSmiles, rdmolops&#xA;from rdkit.Chem import AllChem, AddHs&#xA;&#xA;# SMILES for methanol&#xA;smi='CO'&#xA;&#xA;# SMILES to mol&#xA;mol=MolFromSmiles(smi)&#xA;&#xA;# Add hydrogens&#xA;mol=AddHs(mol)&#xA;&#xA;# Print atom ordering&#xA;print(f'Ordering={[atom.GetSymbol() for atom in mol.GetAtoms()]}')&#xA;&#xA;# Print the adjacency matrix&#xA;A=rdmolops.GetAdjacencyMatrix(mol)&#xA;print(f'A={A}')&#xA;&#xA;# Make the distance matrix&#xA;AllChem.EmbedMolecule(mol) &#xA;D=AllChem.Get3DDistanceMatrix(mol)&#xA;&#xA;# The weighed adjacency matrix can be formed via&#xA;print(f'D={A*D}')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output should look like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;Ordering=['C', 'O', 'H', 'H', 'H', 'H']&#xA;A=[[0 1 1 1 1 0]&#xA; [1 0 0 0 0 1]&#xA; [1 0 0 0 0 0]&#xA; [1 0 0 0 0 0]&#xA; [1 0 0 0 0 0]&#xA; [0 1 0 0 0 0]]&#xA;D=[[0.         1.40928192 1.10391551 1.10763937 1.12250832 0.        ]&#xA; [1.40928192 0.         0.         0.         0.         0.97916277]&#xA; [1.10391551 0.         0.         0.         0.         0.        ]&#xA; [1.10763937 0.         0.         0.         0.         0.        ]&#xA; [1.12250832 0.         0.         0.         0.         0.        ]&#xA; [0.         0.97916277 0.         0.         0.         0.        ]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6637" LastEditorUserId="6637" LastEditDate="2023-02-02T14:41:20.967" LastActivityDate="2023-02-02T14:41:20.967" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10334" PostTypeId="5" CreationDate="2023-01-31T22:01:25.140" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/jbuckeridge/sc-fermi&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/jbuckeridge/sc-fermi&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-31T22:01:25.140" LastActivityDate="2023-01-31T22:01:25.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10335" PostTypeId="4" CreationDate="2023-01-31T22:01:25.140" Score="0" Body="Questions about the SC-FERMI software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-01-31T22:01:25.140" LastActivityDate="2023-01-31T22:01:25.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10336" PostTypeId="2" ParentId="10275" CreationDate="2023-02-01T09:25:25.533" Score="1" Body="&lt;p&gt;Calculating the virial tensor (and then the stress) is non-trivial for systems with many-body forces in a fully periodic simulation (see &lt;a href=&quot;https://aip.scitation.org/doi/10.1063/1.3245303&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/10.1063/1.3245303&lt;/a&gt; -- note that some of the authors are core LAMMPS devs). It is a lot more straightforward with pair-wise central forces.&lt;/p&gt;&#xA;&lt;p&gt;LAMMPS can do this calculation, but LAMMPS has very intricate programming &amp;quot;behind the scenes&amp;quot; to handle periodic images (this is why, for example, LAMMPS is not restricted by minimum image conventions). This is not something other packages may not bother to implement, especially if it is not asked for by most of their users. So the most straightforward way to proceed is to run this calculation in LAMMPS.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-02-01T09:25:25.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10337" PostTypeId="2" ParentId="6935" CreationDate="2023-02-01T10:43:53.370" Score="1" Body="&lt;p&gt;&lt;strong&gt;This answer is based on fuzzy knowledge, if something seems obviously wrong, it probably is. Comments are welcome, and a better answer will be accepted.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Addressing the issue of units first, please see this &lt;a href=&quot;https://physics.stackexchange.com/questions/684443/why-is-kelvin-used-for-energy-separation-in-atoms&quot;&gt;question and answer&lt;/a&gt;. Kelvin are used in studies like this because temperature is a key factor in the preservation of magnetic state. Thermal fluctuations can readily knock atomic spins out of global alignment and thus remove permanent magnetism. The average amount of energy in a thermal fluctuation is related to temperature by &lt;span class=&quot;math-container&quot;&gt;$k_BT$&lt;/span&gt;, so energies are given in Kelvin to indicate how well the state is preserved at temperature.&lt;/p&gt;&#xA;&lt;p&gt;This is where it gets a bit more speculative. Crystal Electric Field parameters are weighting parameters in a combined sum that defines the &amp;quot;crystal electric field&amp;quot; as a combination of underlying functions. The crystal electric field is the electric field produced by the subatomic particles of the crystal. It's called the &lt;em&gt;crystal&lt;/em&gt; electric field because the electric field is uniquely associated with the crystal's structure.&lt;/p&gt;&#xA;&lt;p&gt;I'm not aware of whether the underlying functions are analytical, or empirical. I suspect one could use either, but, hopefully, somebody with more domain knowledge can step in and give a definite answer.&lt;/p&gt;&#xA;" OwnerUserId="4220" LastEditorUserId="4220" LastEditDate="2023-02-01T14:48:56.523" LastActivityDate="2023-02-01T14:48:56.523" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10338" PostTypeId="1" CreationDate="2023-02-01T15:48:29.053" Score="2" ViewCount="190" Body="&lt;p&gt;After installing QUANTUM ESPRESSO on a i7-laptop I tried to do a scf calculation to see if the QUANTUM ESPRESSO works. I got an output, and the results seems to be OK. However, there is an error that appears in the terminal. It is annoying that it will appear in every calculation I do and also I don`t know if that error affects my calculations. The error appears like that&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/Desktop/folder$ mpirun '/homeDesktop/qe-7.0/bin/pw.x' -in scf.in&amp;gt; scf.out```&#xA;    ```Invalid MIT-MAGIC-COOKIE-1 keyNote: The following floating-point exceptions are signalling: IEEE_DENORMAL```&#xA;    ```Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;    Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone help me to fix this, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-01T16:07:23.883" LastActivityDate="2023-02-02T10:25:05.263" Title="Invalid MIT-MAGIC-COOKIE-1 keyNote when working with mpirun" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10339" PostTypeId="2" ParentId="9416" CreationDate="2023-02-01T22:08:08.400" Score="2" Body="&lt;p&gt;I used the method in &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.83.245207&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; and &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2014/cp/c4cp02870h&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; and it worked well:&lt;/p&gt;&#xA;&lt;p&gt;To summarize:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The defect degeneracy level (the total # of charge carriers created by the defect) should be determined.&lt;/li&gt;&#xA;&lt;li&gt;Combinatorics can be used to calculate the charge state degeneracy based on the charge state of the defect of interest.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4192" LastEditorUserId="5" LastEditDate="2023-02-01T23:15:20.033" LastActivityDate="2023-02-01T23:15:20.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10340" PostTypeId="1" CreationDate="2023-02-01T22:56:04.350" Score="1" ViewCount="53" Body="&lt;p&gt;The final system to model is an interface made of 2 surfaces of 12 fcc-Pt atoms each, with a NH3 molecule in between. I'm using ultra-soft pseudopotentials. If I take the energy cutoff (ecutwfc) that gives a converged lattice parameter within 0.01 Angstrom, I find 30 Rydberg for Pt and 40 for NH3 (NH bond length converged within 0.01 Angstrom).&lt;/p&gt;&#xA;&lt;p&gt;My question is, given a large number of atoms with lower cutoff and a minority number of atoms with larger cutoff, how should I pick the final cutoff? Should I always go for safer option (higher cutoff) even though it causes the majority of the system to be treated with a cutoff higher than needed, increasing computational time?&lt;/p&gt;&#xA;" OwnerUserId="6513" LastEditorUserId="5" LastEditDate="2023-02-01T23:15:57.413" LastActivityDate="2023-02-02T15:17:25.290" Title="Choose energy cutoff of surface + molecule (Quantum ESPRESSO)" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10341" PostTypeId="1" AcceptedAnswerId="10345" CreationDate="2023-02-02T03:24:18.893" Score="3" ViewCount="269" Body="&lt;p&gt;I am trying to run a Python script using ASE library, I have installed ASE using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/install.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this page&lt;/a&gt; and run my Python script using this library on my terminal. I have made a virtual env named 'MLC_env' and have already installed the ASE library there.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Python script&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;atoms = Atoms('N2')&#xA;print(atoms.positions)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Error: While trying to run the above python script&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(MLC_env) (base) anshumansinha@Anshumans-MacBook-Pro-3 Q1 % python3 struct.py&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/compat/py3k.py&amp;quot;, line 24, in &amp;lt;module&amp;gt;&#xA;    import pickle5 as pickle&#xA;  File &amp;quot;/Users/anshumansinha/.local/lib/python3.10/site-packages/pickle5/__init__.py&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;    from .pickle import *&#xA;  File &amp;quot;/Users/anshumansinha/.local/lib/python3.10/site-packages/pickle5/pickle.py&amp;quot;, line 33, in &amp;lt;module&amp;gt;&#xA;    from struct import pack, unpack&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/HW1/Q1/struct.py&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;    from ase import Atoms&#xA;ImportError: cannot import name 'Atoms' from partially initialized module 'ase' (most likely due to a circular import) (/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/ase/__init__.py)&#xA;&#xA;During handling of the above exception, another exception occurred:&#xA;&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/core/__init__.py&amp;quot;, line 23, in &amp;lt;module&amp;gt;&#xA;    from . import multiarray&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/core/multiarray.py&amp;quot;, line 10, in &amp;lt;module&amp;gt;&#xA;    from . import overrides&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/core/overrides.py&amp;quot;, line 8, in &amp;lt;module&amp;gt;&#xA;    from numpy.compat._inspect import getargspec&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/compat/__init__.py&amp;quot;, line 12, in &amp;lt;module&amp;gt;&#xA;    from . import py3k&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/compat/py3k.py&amp;quot;, line 26, in &amp;lt;module&amp;gt;&#xA;    import pickle&#xA;  File &amp;quot;/Users/anshumansinha/miniforge3/lib/python3.10/pickle.py&amp;quot;, line 33, in &amp;lt;module&amp;gt;&#xA;    from struct import pack, unpack&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/HW1/Q1/struct.py&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;    from ase import Atoms&#xA;ImportError: cannot import name 'Atoms' from partially initialized module 'ase' (most likely due to a circular import) (/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/ase/__init__.py)&#xA;&#xA;During handling of the above exception, another exception occurred:&#xA;&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/HW1/Q1/struct.py&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;    from ase import Atoms&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/ase/__init__.py&amp;quot;, line 17, in &amp;lt;module&amp;gt;&#xA;    from ase.atom import Atom&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/ase/atom.py&amp;quot;, line 3, in &amp;lt;module&amp;gt;&#xA;    import numpy as np&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/__init__.py&amp;quot;, line 141, in &amp;lt;module&amp;gt;&#xA;    from . import core&#xA;  File &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/numpy/core/__init__.py&amp;quot;, line 49, in &amp;lt;module&amp;gt;&#xA;    raise ImportError(msg)&#xA;ImportError: &#xA;&#xA;IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!&#xA;&#xA;Importing the numpy C-extensions failed. This error can happen for&#xA;many reasons, often due to issues with your setup or how NumPy was&#xA;installed.&#xA;&#xA;We have compiled some common reasons and troubleshooting tips at:&#xA;&#xA;    https://numpy.org/devdocs/user/troubleshooting-importerror.html&#xA;&#xA;Please note and check the following:&#xA;&#xA;  * The Python version is: Python3.10 from &amp;quot;/Users/anshumansinha/Desktop/MLC/MLC_env/bin/python3&amp;quot;&#xA;  * The NumPy version is: &amp;quot;1.24.1&amp;quot;&#xA;&#xA;and make sure that they are the versions you expect.&#xA;Please carefully study the documentation linked above for further help.&#xA;&#xA;Original error was: cannot import name 'Atoms' from partially initialized module 'ase' (most likely due to a circular import) (/Users/anshumansinha/Desktop/MLC/MLC_env/lib/python3.10/site-packages/ase/__init__.py)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6643" LastEditorUserId="1492" LastEditDate="2023-02-02T04:53:39.007" LastActivityDate="2023-02-02T16:55:39.730" Title="Error in running Python file using ASE library" Tags="|python|software-assistance|atomic-simulation-environment|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10342" PostTypeId="1" CreationDate="2023-02-02T06:19:34.413" Score="1" ViewCount="31" Body="&lt;p&gt;I am doing scattering region calculation when I checked the output file of scattering region calculation i got warning like this&lt;/p&gt;&#xA;&lt;p&gt;Begin: TS Checks and Warnings&#xA;Electrode Left will not update cross-terms or local region.&#xA;Electrode Right will not update cross-terms or local region.&#xA;End: TS Checks and Warnings&lt;/p&gt;&#xA;&lt;p&gt;What does it means&lt;/p&gt;&#xA;&lt;p&gt;is it a serious warning or should i carry calculation forward&lt;/p&gt;&#xA;&lt;p&gt;Thankyou.&lt;/p&gt;&#xA;" OwnerUserId="6561" LastEditorUserId="5" LastEditDate="2023-02-02T13:31:08.153" LastActivityDate="2023-02-02T13:31:08.153" Title="Regarding scattering region calculation" Tags="|siesta|scattering|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:06:47.483" ContentLicense="CC BY-SA 4.0" />
  <row Id="10344" PostTypeId="2" ParentId="10338" CreationDate="2023-02-02T07:59:03.677" Score="4" Body="&lt;p&gt;Neither of these messages are anything to worry about as far as running a MPI parallel version of Quantum Espresso are concerned.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Invalid MIT-MAGIC-COOKIE-1 key&lt;/code&gt; is to do with X permissions, and has been reported elsewhere, &lt;a href=&quot;https://www.reddit.com/r/linuxquestions/comments/njfvoq/invalid_mitmagiccookie1_key_when_running_mpi/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.reddit.com/r/linuxquestions/comments/njfvoq/invalid_mitmagiccookie1_key_when_running_mpi/&lt;/a&gt; for example, when using openMPI and certain flavours of Linux, mostly more modern versions of Ubuntu and variants thereon. Ignore it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Note: The following floating-point exceptions are signalling: IEEE_DENORMAL&lt;/code&gt; is telling you that your calculation produced some sub/&lt;a href=&quot;https://denormal&quot; rel=&quot;nofollow noreferrer&quot;&gt;denormal&lt;/a&gt; numbers. This is typical and almost certainly harmless. Ignore it.&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="269" LastEditDate="2023-02-02T10:25:05.263" LastActivityDate="2023-02-02T10:25:05.263" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10345" PostTypeId="2" ParentId="10341" CreationDate="2023-02-02T09:25:09.423" Score="6" Body="&lt;p&gt;There are few issues here:&lt;/p&gt;&#xA;&lt;p&gt;You have been calling the constructor to the atom object wrong:&#xA;If you refer to the ASE manual, and go to Atoms object section, you will see that you need to explicitly set the positions for the atoms in the molecule that you are creating. Consider the example of creating a carbon-monoxide molecule, you will do it as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms &#xA;d = 1.1 &#xA;co = Atoms('CO', positions=[(0, 0, 0), (0, 0, d)])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The error message in your case is trying to say that you have not set the positions for the atoms, but is then trying to access that property (which the system does not have)&lt;/p&gt;&#xA;&lt;p&gt;Editing the answer to address the comment by Cavenfish:&lt;/p&gt;&#xA;&lt;p&gt;Following the link in the error message, it seems that the issue is with the installation of ase. I tried installing ase in a virtualenv using two methods&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Normal &lt;code&gt;pip install --upgrade --user ase&lt;/code&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;pip install --upgrade git+https://gitlab.com/ase/ase.git@master&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In the first method, the installation completed, but had errors with the dependencies, particularly numpy. Using the second method, I was able to install and use ase without any issues.&lt;/p&gt;&#xA;&lt;p&gt;Thus it seems that OP might have used the first method, and inadvertently had some issues with the dependencies.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-02-02T16:55:39.730" LastActivityDate="2023-02-02T16:55:39.730" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10346" PostTypeId="2" ParentId="10324" CreationDate="2023-02-02T12:31:14.497" Score="3" Body="&lt;p&gt;&lt;strong&gt;TL;DR&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The results obtained by OP from BURAI has been independently verified to be correct using the attached Python script, and by redoing the calculation with cell vectors and positions set explicitly in units of angstrom. The results from both the calculations converged to the same final structure, as it should.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately, OP got confused between primitive and conventional cells. The main issue was that OP is trying to compare the cell parameters from the optimized primitive cell to the cell parameters of the conventional cell. If we transform the optimized primitive cell to a conventional cell, we get a cell parameter of &lt;strong&gt;5.50929172400000 Å&lt;/strong&gt; which is the value that OP is after (0.5% error compared to the value of 5.48 Å).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Longer answer&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Gist of the answer that I had previously written:&lt;/p&gt;&#xA;&lt;p&gt;The cell parameters that were extracted from the output file that OP had posted are as follows:&lt;/p&gt;&#xA;&lt;p&gt;The values for celldm(1) and cell parameters in x, y and z in units of angstrom are given below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  7.408477  5.160506  5.160506  5.160506&#xA;  7.408477  5.043389  5.043389  5.043389&#xA;  7.408477  4.867713  4.867713  4.867713&#xA;  7.408477  4.773997  4.773997  4.773997&#xA;  7.408477  4.633422  4.633422  4.633422&#xA;  7.408477  4.532122  4.532122  4.532122&#xA;  7.408477  4.380172  4.380172  4.380172&#xA;  7.408477  4.152247  4.152247  4.152247&#xA;  7.408477  3.810360  3.810360  3.810360&#xA;  7.408477  3.902034  3.902034  3.902034&#xA;  7.408477  3.877742  3.877742  3.877742&#xA;  7.408477  3.875530  3.875530  3.875530&#xA;  7.408477  3.875530  3.875530  3.875530&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The code that was used for the analysis is&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from numpy.linalg   import  norm&#xA;&#xA;with open(&amp;quot;raw&amp;quot;) as f: # give your output file name instead&#xA;    fileContents    =   f.readlines()&#xA;    for index, line in enumerate(fileContents):&#xA;        if &amp;quot;CELL_PARAMETERS&amp;quot; in line:&#xA;            reqdlines   =   fileContents[index:index+4]&#xA;            multiplier  =   float(reqdlines[0].split()[-1].strip(&amp;quot;)&amp;quot;))&#xA;            x_axis      =   [float(x) for x in reqdlines[1].split()]&#xA;            y_axis      =   [float(x) for x in reqdlines[2].split()]&#xA;            z_axis      =   [float(x) for x in reqdlines[3].split()]&#xA;            print(&amp;quot;{:10.6f}{:10.6f}{:10.6f}{:10.6f}&amp;quot;.format(multiplier*0.529177, norm(x_axis)*multiplier*0.529, norm(y_axis)*multiplier*0.529, norm(z_axis)*multiplier*0.529))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thus, in the previous iteration of question and answer, it was made clear that BURAI is giving the correct answer, and the tutorial that OP was following was wrong.&lt;/p&gt;&#xA;&lt;p&gt;Since OP is not convinced with the results, I redid the optimization of the Si cell using the same input file, but with the coordinates and cell vectors explicitly provided in units of angstrom.&lt;/p&gt;&#xA;&lt;p&gt;The cell vectors in x, y and z that were obtained by are as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  5.158930  5.158930  5.158930&#xA;  5.039445  5.039445  5.039445&#xA;  4.860218  4.860218  4.860218&#xA;  4.764030  4.764030  4.764030&#xA;  4.619749  4.619749  4.619749&#xA;  4.516518  4.516518  4.516518&#xA;  4.361672  4.361672  4.361672&#xA;  4.129403  4.129403  4.129403&#xA;  3.780998  3.780998  3.780998&#xA;  3.932265  3.932265  3.932265&#xA;  3.900708  3.900708  3.900708&#xA;  3.895402  3.895402  3.895402&#xA;  3.895658  3.895658  3.895658&#xA;  3.895658  3.895658  3.895658&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is clear that the optimization converges to the same structure regardless of whether we use alat or angstrom (which it must ideally).&lt;/p&gt;&#xA;&lt;p&gt;Just to drive the point home, reproduced below is the output from &lt;a href=&quot;https://aflow.org/aflow-online/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AFlow.org&lt;/a&gt; showing that BURAI output is the correct one.&lt;/p&gt;&#xA;&lt;p&gt;Input&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EXAMPLE POSCAR&#xA;1.000000&#xA;   0.000000000   2.754645862   2.754645862&#xA;   2.754645862   0.000000000   2.754645862&#xA;   2.754645862   2.754645862   0.000000000&#xA;Si&#xA;2 &#xA;Cartesian(2) [Si2]&#xA;0.000000000   0.000000000   0.000000000&#xA;4.131968792   1.377322931   4.131968792&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;REAL LATTICE&#xA; Real space lattice:&#xA;   0.0000e+00  2.7546e+00  2.7546e+00&#xA;   2.7546e+00  0.0000e+00  2.7546e+00&#xA;   2.7546e+00  2.7546e+00  0.0000e+00&#xA; a b c alpha beta gamma: 3.895657538 3.895657538 3.895657538 60 60 60&#xA; a b c alpha beta gamma: 7.361725291 7.361725291 7.361725291 60 60 60   Bohrs/Degs &#xA; Volume: 41.8&#xA; c/a = 1&#xA;BRAVAIS LATTICE OF THE CRYSTAL (pgroup_xtal)&#xA; Bravais Lattice Primitive        = FCC&#xA; Lattice Variation                = FCC&#xA; Lattice System                   = cubic&#xA; Pearson Symbol                   = cF8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Endnote: I strongly suspect that OP is making some mistake in measuring the cell parameters manually, and that is the origin for the confusion.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I have now identified the origin of the confusion for OP. OP did the calculations in primitive cell, and has the cell parameter value for the conventional cell. Once that transformation is made, we get a value of &lt;strong&gt;5.50929172400000&lt;/strong&gt; which is the value that OP is after.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-02-27T16:41:38.120" LastActivityDate="2023-02-27T16:41:38.120" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10347" PostTypeId="1" AcceptedAnswerId="10350" CreationDate="2023-02-02T13:52:20.747" Score="3" ViewCount="114" Body="&lt;p&gt;Is it possible to compute a 3D model of a calcium EDTA complex and it's energy? If so, how should I go about doing it or where can I obtain relevant information regarding computation methods?&lt;/p&gt;&#xA;&lt;p&gt;I searched through the docs of GROMACS and CP2K, but didn't find relevant information.&lt;/p&gt;&#xA;" OwnerUserId="6649" LastEditorUserId="5" LastEditDate="2023-02-02T14:22:05.130" LastActivityDate="2023-02-03T01:06:05.210" Title="Model coordination complex using GROMACS or CP2K" Tags="|molecular-modeling|gromacs|cp2k|soft-question|coordination|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10348" PostTypeId="2" ParentId="10340" CreationDate="2023-02-02T15:12:18.947" Score="1" Body="&lt;p&gt;Yes, you should always choose the largest cutoff for the combined system; otherwise, your molecular system won't be treated correctly.&lt;/p&gt;&#xA;&lt;p&gt;You can check out our paper on reaction pathways of a molecule on a Si surface here: &lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.6b04450&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.6b04450&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4494" LastEditorUserId="4494" LastEditDate="2023-02-02T15:17:25.290" LastActivityDate="2023-02-02T15:17:25.290" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10349" PostTypeId="1" AcceptedAnswerId="10419" CreationDate="2023-02-02T15:39:51.863" Score="1" ViewCount="349" Body="&lt;p&gt;Recently my question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10277/5&quot;&gt;Why does CCSD work, but not CCSD(T), after reading an FCIDUMP in PySCF?&lt;/a&gt; lead to a &lt;a href=&quot;https://github.com/pyscf/pyscf/pull/1580&quot; rel=&quot;nofollow noreferrer&quot;&gt;bug fix&lt;/a&gt; that allows users to do CCSD(T) calculations from an FCIDUMP file in PySCF. &lt;strong&gt;That was with the FCIDUMP file being in ASCII format though!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;When the FCIDUMP file is in ASCII format, it's easy to create an &amp;quot;SCF object&amp;quot; from  the dump file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mf = pyscf.tools.fcidump.to_scf(name+'.fcidump', molpro_orbsym=False, mf=None)&#xA;mf.run()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;That object is what's required to do CCSD calculations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc = cc.CCSD(mf)&#xA;e = mcc.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However the function that &amp;quot;loads&amp;quot; an FCIDUMP file in HDF5 format gives an &lt;code&gt;eri&lt;/code&gt; object instead of an &lt;code&gt;scf&lt;/code&gt; object:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eri = ao2mo.load(name+'.fcidump.h5',dataname='dummy_label')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Attempting to do CCSD from only the ERI object&lt;/h2&gt;&#xA;&lt;p&gt;If I were just to replace the above &lt;code&gt;mf&lt;/code&gt; with &lt;code&gt;eri&lt;/code&gt; as in the line below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc = cc.CCSD(eri)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;then it will trigger the &lt;code&gt;convert_to_rhf&lt;/code&gt; function in &lt;code&gt;pyscf/scf/addons.py&lt;/code&gt; which will crash at &lt;code&gt;assert (isinstance(mf, hf.SCF))&lt;/code&gt; presumably because &lt;code&gt;eri&lt;/code&gt; is &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; an instance of an &lt;code&gt;hf.SCF&lt;/code&gt; object.&lt;/p&gt;&#xA;&lt;p&gt;By simply doing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc = cc.CCSD()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;there will be a complaint about the required &lt;code&gt;mf&lt;/code&gt; input being missing. If we do:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc = pyscf.cc.ccsd.kernel(eris=eri, callback=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;there will be an error because &lt;code&gt;cc.ccsd.kernel()&lt;/code&gt; requries a &lt;code&gt;mycc&lt;/code&gt; object as an input argument. The following gets us closer:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc = pyscf.cc.ccsd.kernel(0,eris=eri, verbose=9,callback=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but ends in &lt;code&gt;pyscf/cc/ccsd.py&lt;/code&gt; at &lt;code&gt;mycc.get_init_guess(eris)&lt;/code&gt; presumably because the integer &lt;code&gt;0&lt;/code&gt; doesn't contain information about the initial guess for the CCSD calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;AttributeError: 'int' object has no attribute 'get_init_guess'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In most programs, asking for a CCSD calculation automatically triggers an MP2 calculation so that there's a decent initial guess for the CCSD, and I'm sure that's also happening in PySCF if I do &lt;code&gt;cc.CCSD(mf)&lt;/code&gt;, but it seems that if we run &lt;code&gt;pyscf.cc.ccsd.kernel()&lt;/code&gt; instead (due to not having an &lt;code&gt;mf&lt;/code&gt; object), then we need to do explicitly tell the program to do an MP2 calcualtion first. The brings us to the question:&lt;/p&gt;&#xA;&lt;h2&gt;Attempting to do MP2 from only the ERI object&lt;/h2&gt;&#xA;&lt;p&gt;Running &lt;code&gt;mf.MP2().run()&lt;/code&gt; requires an &lt;code&gt;mf&lt;/code&gt; object. The following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eri.MP2().run(verbose=9)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;won't work because &lt;code&gt;eri&lt;/code&gt; is a &lt;code&gt;load&lt;/code&gt; object and doesn't have an &lt;code&gt;mp2&lt;/code&gt; attribute:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;AttributeError: 'load' object has no attribute 'MP2'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In fact &lt;code&gt;pyscf.ci.cisd.CISD()&lt;/code&gt; would also complain about not having an &lt;code&gt;mf&lt;/code&gt; object.&lt;/p&gt;&#xA;&lt;h2&gt;Attempting to get an SCF object from an ERI object&lt;/h2&gt;&#xA;&lt;p&gt;As long as we can get an &lt;code&gt;mf&lt;/code&gt; object from the &lt;code&gt;eri&lt;/code&gt;, we can do CISD, MP2, CCSD and much more. Attempting to create the &lt;code&gt;mf&lt;/code&gt; object from the FCIDUMP in the way that we did when the FCIDUMP was in ASCII format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mf = pyscf.tools.fcidump.to_scf(name+'.fcidump.h5', molpro_orbsym=False, mf=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;just leads to a complaint which seems to be about the FCIDUMP file not being in ASCII format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python3.8/codecs.py&amp;quot;, line 322, in decode&#xA;    (result, consumed) = self._buffer_decode(data, self.errors, final)&#xA;UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There's &lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.tools.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;not much documentation for &lt;code&gt;pyscf.tools.fcidump.to_scf()&lt;/code&gt;&lt;/a&gt; but &lt;a href=&quot;https://pyscf.org/_modules/pyscf/tools/fcidump.html#to_scf&quot; rel=&quot;nofollow noreferrer&quot;&gt;the source code&lt;/a&gt; suggests that it will only work if the FCIDUMP file is in ASCII format. Perhaps it can be hacked to go into the HDF5 file and fetch the integrals, but I would think that since PySCF has the capability to &lt;code&gt;load&lt;/code&gt; the integrals with &lt;code&gt;ao2mo.load()&lt;/code&gt;, it would have the ability to &lt;em&gt;&lt;strong&gt;use&lt;/strong&gt;&lt;/em&gt; loaded integrals, meaning that there's already a way to get the &lt;code&gt;mf&lt;/code&gt; object from an &lt;code&gt;eri&lt;/code&gt; object.&lt;/p&gt;&#xA;&lt;p&gt;I've also looked at &lt;code&gt;pyscf.tools.fcidump.scf_from_fcidump()&lt;/code&gt; but it seems to require the user to already have an &lt;code&gt;mf&lt;/code&gt; object. Also in &lt;code&gt;pyscf/tools/fcidump.py&lt;/code&gt; there are the &lt;code&gt;from_mo()&lt;/code&gt; and &lt;code&gt;from_integrals()&lt;/code&gt;, but they are for writing FCIDUMP files, not loading them.&lt;/p&gt;&#xA;&lt;h2&gt;Question&lt;/h2&gt;&#xA;&lt;p&gt;My question was how to do CCSD from an FCIDUMP file in HDF5 format. Based on the above troubleshooting, I've discovered that it boils down to converting the &lt;code&gt;eri&lt;/code&gt; object obtained from the FCIDUMP.h5 file into an &lt;code&gt;scf&lt;/code&gt; object, which I don't know how to do!&lt;/p&gt;&#xA;&lt;p&gt;The following script will create the &lt;code&gt;FCIDUMP.h5&lt;/code&gt; file (only about 11 kB since I used a STO-3G basis set) and then will load the FCIDUMP.h5 file into an &lt;code&gt;eri&lt;/code&gt; object which is classified as a &amp;quot;load&amp;quot; object:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, cc&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = ''' O&#xA;               H  1  0.9576257&#xA;               H  1  0.9576257  2 104.51 '''&#xA;mol.unit = 'angstrom'&#xA;mol.basis = 'STO-3G'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.verbose = 9&#xA;mol.symmetry = True&#xA;mol.symmetry_subgroup = 'C2v'&#xA;name = 'out'&#xA;#mol.output = name+'.txt' # only worked up to end of SCF (CC output went to stdout)&#xA;mol.build()&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;&#xA;mf = mol.RHF().set(chkfile = name + '.chk')&#xA;mf.kernel()&#xA;&#xA;pyscf.ao2mo.kernel(mol, mf.mo_coeff, name+'.fcidump.h5', dataname='hdf5_group_name')&#xA;eri = ao2mo.load(name+'.fcidump.h5',dataname='dummy_label')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Running the above script will also give you an &lt;code&gt;mf&lt;/code&gt; object, but the question is how to continue to post-HF calculations without using it at all.&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-14T21:35:23.540" Title="PySCF: How to do CCSD calculations from an FCIDUMP file in HDF5 format?" Tags="|python|high-performance-computing|pyscf|integrals|fcidump|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10350" PostTypeId="2" ParentId="10347" CreationDate="2023-02-03T00:08:56.583" Score="3" Body="&lt;p&gt;Here is how you can get the structure from PubChem, read the SMILES into Avogadro2, do a MMFF94 (classical) optimization, and then a single-point energy calculation using NWChem (RHF, 6-31G*). The Avogadro2 Input builder will create a CP2K file if you prefer. For GROMACS, &lt;a href=&quot;https://manual.gromacs.org/current/manual-2022.4.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;there is extensive documentation&lt;/a&gt; that includes at least one example of how to set up a single-point calculation.&lt;/p&gt;&#xA;&lt;p&gt;Note: there are many choices for doing this procedure, including level of theory, basis sets, tools, and so on. That said, you can follow this flow and do the geometry optimization at a higher level of theory and follow that up with a single-point calculation if you choose.&lt;/p&gt;&#xA;&lt;p&gt;Everything here works fine on a stardard Ubuntu 22.04 LTS build.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Go to the PubChem entry for &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/compound/Calcium-disodium-EDTA&quot; rel=&quot;nofollow noreferrer&quot;&gt;Calcium disodium EDTA&lt;/a&gt;;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Scroll down to section 2.1.4 (Canonical SMILES) and copy the string:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;C(CNH+CC(=O)[O-])NH+CC(=O)[O-].[Na+].[Na+].[Ca+2]&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;into a text file and call it something like CaEDTA.smi (use the SMILES format extension);&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Open Avogadro2 and load the CaEDTA.smi file, you should see something like:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/CxRpC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CxRpC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Under the Extensions tab, go to Open Babel and Optimize Geometry, which will slightly change the positions of the atoms and give you an optimized geometry using the MMFF94 force field, which is more than adequate for the job;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Go to the Input tab and select NWChem; change the Filename Base to CaEDTA (or something more descriptive); change Calculation Type to Single Point; and  change Theory to RHF; and save this file as CaEDTA_MMFF94-opt_HF-631star_energy.nw;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nR60y.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nR60y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;6&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;If you have not installed NWChem, do &lt;code&gt;sudo apt install nwchem&lt;/code&gt;;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;On the command line run the following:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;code&gt;nwchem CaEDTA_MMFF94-opt_HF-631star_energy.nw &amp;gt;&amp;amp; CaEDTA_HF-6-31star_energy.out &amp;amp;&lt;/code&gt;;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;8&quot;&gt;&#xA;&lt;li&gt;After about 7 minutes, the job will finish. At that point, do the following:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;code&gt;grep -B2 -A5 &amp;quot;Total SCF energy&amp;quot; CaEDTA_MMFF94-opt_HF-631star_energy.out&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;which will print to screen:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FkRE4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FkRE4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;9&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Note that if you ingest the .out file into Avogadro2, you will see a wacky structure. This is not unexpected, nor is this &amp;quot;correct.&amp;quot; However, the steps are here. You might consider adding water molecules and/or using the COSMO (or related) solvent models; and&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Information about the all the above can be found (at least) in the &lt;a href=&quot;https://nwchemgit.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NWChem documents&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4544" LastEditorUserId="4544" LastEditDate="2023-02-03T01:06:05.210" LastActivityDate="2023-02-03T01:06:05.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10352" PostTypeId="1" AcceptedAnswerId="10355" CreationDate="2023-02-03T13:31:45.487" Score="5" ViewCount="123" Body="&lt;p&gt;While I was working today on Computational Materials Physics Course by Stefaan Cottenier, the platform suddenly stopped working. I got the following message.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Hmm. We’re having trouble finding that site.&lt;br&gt;&#xA;We can’t connect to the server at beta.compmatphys.org.&lt;br&gt;&#xA;If you entered the right address, you can:&lt;br&gt;&#xA;-Try again later&lt;br&gt;&#xA;-Check your network connection&lt;br&gt;&#xA;-Check that Firefox has permission to access the web (you might be connected but behind a firewall)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Firefox browser is working for me in the other websites except that one. I tried to browse from another laptop to that website and the same problem occur. Can anyone help me to solve this issue?&#xA;The website is: &lt;a href=&quot;http://beta.compmatphys.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://beta.compmatphys.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-04T00:04:59.547" LastActivityDate="2023-02-04T16:07:57.760" Title="Computational Materials Physics Course by Stefaan Cottenier (SERVER NOT FOUND)" Tags="|education|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10353" PostTypeId="2" ParentId="8585" CreationDate="2023-02-03T15:27:43.300" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;This would seem to result in a very large relative error in calculated GB radius. How is this approximation okay?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The systematic error is corrected in an average way by the scale parameters on page 125 of the Hawkins et al. paper.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Are there any systematic studies of the degree of error this introduces?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The mean-unsigned error in the polarization free energies between the pairwise method and the method that does not make ths simplification is 0.38 kcal/mol. See Table 2 of the Hawkins et al. paper.&lt;/p&gt;&#xA;" OwnerUserId="6654" LastEditorUserId="7" LastEditDate="2023-02-03T16:37:37.087" LastActivityDate="2023-02-03T16:37:37.087" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10354" PostTypeId="2" ParentId="10352" CreationDate="2023-02-04T00:12:54.843" Score="2" Body="&lt;p&gt;When I ran the &lt;code&gt;whois&lt;/code&gt; command, I learned that ownership of the domain compmatphys.org was renewed by the 2014 owner in 2021 until 2030:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Updated Date: 2021-10-05T06:43:55Z&#xA;Creation Date: 2014-11-18T14:18:09Z&#xA;Registry Expiry Date: 2030-11-18T14:18:09Z&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However the &lt;code&gt;ping&lt;/code&gt; command tells me that the website is unhosted or that the server hosting the site is down:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ping: unknown host compmatphys.org&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10352/computational-materials-physics-course-by-stefaan-cottenier-server-not-found#comment22061_10352&quot;&gt;Hemanth Haridas pointed out in this comment&lt;/a&gt;, a description of the course (with a link to compmatphys.org at the bottom) can be found &lt;a href=&quot;http://www.max-centre.eu/events/online-course-dft-simultaneous-hands-training-max-codes&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and it says that it was an online course associated with Ghent University from 23 September 2019 to 9 December 2019. The course was also advertised &lt;a href=&quot;https://psi-k.net/general-announcements/open-online-course-on-computational-materials-phys-2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you were working on the course earlier today and it suddenly went down, then it may just be that the server went down (hopefully not because you were viewing the course!).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-04T00:12:54.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10355" PostTypeId="2" ParentId="10352" CreationDate="2023-02-04T09:34:10.643" Score="8" Body="&lt;p&gt;The server went down (for  fewer than 24h) due to a ransomware attack. The people from the hosting company worked hard to get it cleaned, and right now the site is online again (it may have some limited downtime in the coming hours). A backup that is fewer than 48h-old is restored.&lt;/p&gt;&#xA;" OwnerUserId="6657" LastEditorUserId="5" LastEditDate="2023-02-04T16:07:57.760" LastActivityDate="2023-02-04T16:07:57.760" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10357" PostTypeId="2" ParentId="7198" CreationDate="2023-02-04T12:10:09.183" Score="2" Body="&lt;p&gt;You should not be thinking about a specific perturbation operator. The key thing here is that the orbitals are Kohn-Sham eigenfunctions, and that already reveals everything that is needed. Still, it took me a while to dig out the literature on how these orbital energy derivatives are calculated. However, eventually I landed on the paper &lt;a href=&quot;https://doi.org/10.1088/0305-4608/5/11/016&quot; rel=&quot;nofollow noreferrer&quot;&gt;Use of energy derivative of the radial solution in an augmented plane wave method: application to copper&lt;/a&gt; by Koelling and Arbman, which explains how.&lt;/p&gt;&#xA;&lt;p&gt;Shortly put, most atomic codes use finite differences for solving the radial orbitals. (Mine use finite elements instead, see &lt;a href=&quot;https://doi.org/10.1002/qua.25945&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25945 (2019)&lt;/a&gt; and the newest preprint on &lt;a href=&quot;https://arxiv.org/abs/2302.00440&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:2302.00440&lt;/a&gt;.) If you use finite differences, the radial functions &lt;span class=&quot;math-container&quot;&gt;$u_{nl}(r)$&lt;/span&gt; are found from the equations&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;\hat{h}_{nl}u_{nl}(r)  = &amp;amp; E_{nl} u_{nl}(r) \\&#xA;\hat{h}_{nl} =&amp;amp; -\frac{1}{r} \frac{{\rm d}^2} {{\rm d}r^2} r + \frac {l(l+1)} {r^2} + V(r)&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Koelling and Arbman's trick is to take the energy derivative &lt;span class=&quot;math-container&quot;&gt;$\partial / \partial E_{nl} = \dot{}$&lt;/span&gt; from the first equation, yielding&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{eqnarray}&#xA;(\hat{h}_{nl} -E_{nl}) \dot{u}_{nl}(r) = &amp;amp; u_{nl}(r)&#xA;\end{eqnarray}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is an inhomogeneous differential equation with &lt;span class=&quot;math-container&quot;&gt;$u_{nl}$&lt;/span&gt; as the homogeneous solution. Note that you already know &lt;span class=&quot;math-container&quot;&gt;$u_{nl}(r)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{nl}$&lt;/span&gt; here! Koellig and Arbman therefore simply solve this differential equation for &lt;span class=&quot;math-container&quot;&gt;$\dot{u}_{nl}(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Next, the requirement that the wave functions are orthonormal&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_0^\infty {\rm d}r r^2 u_{nl}(r) u_{n'l}(r) = \delta_{nn'} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;gives you the condition&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_0^\infty {\rm d}r r^2 [\dot{u}_{nl}(r) u_{n'l}(r) + u_{nl}(r) \dot{u}_{n'l}(r)] = 0 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which means that &lt;span class=&quot;math-container&quot;&gt;$u_{nl}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\dot{u}_{nl}$&lt;/span&gt; are supposed to be orthogonal. Koellig and Arbman simply orthogonalize the obtained numerical solution for &lt;span class=&quot;math-container&quot;&gt;$\dot{u}_{nl}(r)$&lt;/span&gt; against &lt;span class=&quot;math-container&quot;&gt;$u_{nl}(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h1&gt;Addendum&lt;/h1&gt;&#xA;&lt;p&gt;The finite difference schemes traditionally used in numerical atomic orbital calculations are not based on the spectral theorem, and instead rely on a number of tricks such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Shooting_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;the shooting method&lt;/a&gt; to solve the self-consistent field equations. I think that the orbital energy derivative scheme is inherently tied to the solution method, which makes the scheme mathematically ill-defined.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that we know that the spectrum of the Hamiltonian is discrete, and that its solutions form a complete set of states. This means that one should be able to expand the energy derivative wave functions in terms of the original wave functions, &lt;span class=&quot;math-container&quot;&gt;$|\dot{\psi}_i\rangle = |\psi_k\rangle R_{ki}$&lt;/span&gt;. However, it is easy to see that the equation used to define the energy derivative has no solutions.&lt;/p&gt;&#xA;&lt;p&gt;It is already clear from the definition of the Kohn-Sham-Fock matrix being diagonal in the canonical orbital basis &lt;span class=&quot;math-container&quot;&gt;$\hat{f} = \text{diag }{\boldsymbol{\epsilon}} $&lt;/span&gt; that the only perturbation that can affect the energy of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th orbital is a level shift &lt;span class=&quot;math-container&quot;&gt;$\Delta {\bf H}^{i} = s | i \rangle \langle i |$&lt;/span&gt;, which is an eigenoperator of the orbital &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and therefore does not result in a changed operator. I would be interested if anyone can prove me wrong on this point...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-02-06T10:02:36.223" LastActivityDate="2023-02-06T10:02:36.223" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10358" PostTypeId="1" AcceptedAnswerId="10362" CreationDate="2023-02-04T14:31:41.003" Score="5" ViewCount="1129" Body="&lt;p&gt;I am trying to understand the construction of Hessian matrix using numerical differentiation (NUMFREQ option in ORCA for example). I understand that Hessian is a square matrix containing second derivatives of energy with respect to 3N atomic coordinates. If I try to perform a NUMFREQ calculation in ORCA, I see that the atoms are displaced in +x,+y,+z,-x,-y,-z directions and energies are evaluated for each of those structures. I figured out the calculation of first derivatives from the corresponding SCF energies. But I am unclear on how to get second mixed partial derivatives from the first derivatives. I tried asking this question in ChatGPT, and I am attaching the answer I got below (after Andrea Pellegrini's &lt;a href=&quot;https://mattermodeling.stackexchange.com/review/suggested-edits/2342&quot;&gt;polishing of the formatting&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{d^2E}{(dR_idR_j)} = \frac{\frac{dE}{dR_i} \frac{dE}{dR_j}}{(2 \delta R)} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not sure if this expression is right. Any comments on how this calculation is actually done is welcome.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2023-02-05T11:33:15.397" LastActivityDate="2023-02-06T08:48:54.870" Title="Numerical Evaluation of Hessian?" Tags="|computational-chemistry|mathematical-modeling|hartree-fock|orca|numerical-frequency|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10359" PostTypeId="5" CreationDate="2023-02-04T14:37:29.260" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-02-04T14:37:29.260" LastActivityDate="2023-02-04T14:37:29.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10360" PostTypeId="4" CreationDate="2023-02-04T14:37:29.260" Score="0" Body="This tag can be used to tag questions that pertain to the evaluation of vibrational frequency which allows for the calculation of Numerical hessian." OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2023-02-20T19:40:44.260" LastActivityDate="2023-02-20T19:40:44.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10361" PostTypeId="1" AcceptedAnswerId="10366" CreationDate="2023-02-04T17:57:54.023" Score="6" ViewCount="191" Body="&lt;p&gt;Are there any online courses available that is on the application of ML in material science? Any recommendations?&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="5" LastEditDate="2023-02-04T18:34:46.137" LastActivityDate="2023-03-06T14:09:21.357" Title="Course on machine learning on application in material science" Tags="|machine-learning|education|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10362" PostTypeId="2" ParentId="10358" CreationDate="2023-02-04T18:18:37.513" Score="7" Body="&lt;h1&gt;Finite differences&lt;/h1&gt;&#xA;&lt;p&gt;Let's take a general &lt;span class=&quot;math-container&quot;&gt;$2n+1$&lt;/span&gt; point central finite difference rule with uniform grid spacing&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ f'(x) \approx h^{-1} \sum_{i=-n}^{n} w_i f(x+ ih), $$&lt;/span&gt;&#xA;such as two-point central finite differences with &lt;span class=&quot;math-container&quot;&gt;$n=1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf w}=(-1/2, 0, 1/2)$&lt;/span&gt; which yields the approximation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ f'(x) \approx \frac {f(x+h)-f(x-h)} {2h}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Geometry optimization&lt;/h1&gt;&#xA;&lt;p&gt;For geometrical gradients, our function is the energy &lt;span class=&quot;math-container&quot;&gt;$E(\{\bf R\})$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;${\bf R}_I = (X_I, Y_I, Z_I)$&lt;/span&gt; are the coordinates of the &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt;-th nucleus. (If we have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; nuclei, &lt;span class=&quot;math-container&quot;&gt;$\{\bf R\}$&lt;/span&gt; is a vector with &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; elements, consisting of the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; coordinates of each &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; nuclei.)&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-th component (&lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;) of the force acting on nucleus &lt;span class=&quot;math-container&quot;&gt;$I$&lt;/span&gt; is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ F_{Ik} = -\frac {\partial E} {\partial R_{Ik}}, $$&lt;/span&gt; and it can be evaluated efficiently with analytical methods for a lot of quantum chemical methods. Note that here I use two indices: one for the nucleus and another for the cartesian component.&lt;/p&gt;&#xA;&lt;h1&gt;Simplification of the notation with compound indices&lt;/h1&gt;&#xA;&lt;p&gt;I will now simplify the notation &lt;span class=&quot;math-container&quot;&gt;$Ik \to i$&lt;/span&gt;. If you number the nuclei from 0 to N-1, then the x, y, and z coordinates of the Ith nucleus will be stored at indices &lt;span class=&quot;math-container&quot;&gt;$i=3I$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$i=3I+1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$i=3I+2$&lt;/span&gt;, respectively. I will also denote the vector of nuclear coordinates with &lt;span class=&quot;math-container&quot;&gt;${\bf x}$&lt;/span&gt; and then the force is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ F_{i} = -\frac {\partial E} {\partial x_i}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Hessian&lt;/h1&gt;&#xA;&lt;p&gt;The Hessian is the second derivative, and like you said, it is a &lt;span class=&quot;math-container&quot;&gt;$3N \times 3N$&lt;/span&gt; square matrix. Analytical Hessians are less often available than analytical gradients, and they can be evaluated either seminumerically, if analytical gradients are available, or fully numerically by applying two rounds of finite differences.&lt;/p&gt;&#xA;&lt;p&gt;The Hessian is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ H_{ij} = \frac {\partial^2 E} {\partial x_i \partial x_j} $$&lt;/span&gt;&#xA;where I now use the compound indexing.&lt;/p&gt;&#xA;&lt;h2&gt;Seminumerical scheme&lt;/h2&gt;&#xA;&lt;p&gt;Note that if I know the gradients &lt;span class=&quot;math-container&quot;&gt;$g_i = \partial E / \partial x_i = -F_i$&lt;/span&gt;, I can evaluate the Hessian with finite differences as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H_{ij} = \frac {\partial^2 E} {\partial x_i \partial x_j} =\frac {\partial g_i} {\partial x_j} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This form is explicit, since it tells you that the Hessian measures how much the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th gradient changes when the &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;th coordinate is modified. How is this evaluated? Let's take the two-point equation above for simplicity&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H_{ij} =\frac {\partial g_i} {\partial x_j} \approx \frac {g_i({\bf x}+h\hat{e}_j)-g_i({\bf x}-h\hat{e}_j)} {2h}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;That is, for each column &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; in the Hessian, you get the row &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; by taking the difference of gradients of all the atoms where the gradients are evaluated with coordinates where the &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;-th coordinate has been modified. This means that for this rule, you need to do 2 gradient evaluations for every &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; columns, or &lt;span class=&quot;math-container&quot;&gt;$6N$&lt;/span&gt; gradient calculations.&lt;/p&gt;&#xA;&lt;p&gt;Note in the above that if the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; derivative is evaluated analytically and the &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; derivative with finite differences, the Hessian matrix will have numerical noise in column indices but not in row indices, and thereby will be asymmetric, even though it is supposed to be symmetric. This is why it is a good idea to re-symmetrize the Hessian, &lt;span class=&quot;math-container&quot;&gt;$$ H_{ij} \to \frac {H_{ij} + H_{ji}} 2 $$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Fully numerical scheme&lt;/h2&gt;&#xA;&lt;p&gt;What about the fully numerical Hessian? It is nothing more complicated than the above; you just use the finite difference equation again to expand &lt;span class=&quot;math-container&quot;&gt;$g_i$&lt;/span&gt; to get&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H_{ij} \approx \frac {E({\bf x}+h\hat{e}_i+h\hat{e}_j)-E({\bf x}-h\hat{e}_i+h\hat{e}_j)-E({\bf x}+h\hat{e}_i-h\hat{e}_j)+E({\bf x}-h\hat{e}_i-h\hat{e}_j)} {4h^2}. $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even though this example only used two-point rules, you can use higher-order ones as well, such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Finite_difference_coefficient&quot; rel=&quot;nofollow noreferrer&quot;&gt;the ones presented in Wikipedia&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-02-06T08:48:54.870" LastActivityDate="2023-02-06T08:48:54.870" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10363" PostTypeId="1" CreationDate="2023-02-04T20:38:49.817" Score="3" ViewCount="265" Body="&lt;p&gt;I am getting the following error when trying to plot band-structure using PyProcar. I posted a comment in author's github page as well (&lt;a href=&quot;https://github.com/romerogroup/pyprocar/issues/93&quot; rel=&quot;nofollow noreferrer&quot;&gt;see at the bottom&lt;/a&gt;). In the meantime, I wonder if anyone could please help? Thanks.&lt;/p&gt;&#xA;&lt;p&gt;P.S. Please note that, I was able to plot this same band-structure calculation using sumo-plot. I PyProcar has some additional functionalities (such as spin-projection) that sumo-plot doesn't have.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;pyprocar_band_spin.py&amp;quot;, line 25, in &amp;lt;module&amp;gt;&#xA;    pyprocar.bandsdosplot(bands_file='PROCAR',&#xA;  File &amp;quot;/dartfs-hpc/rc/home/m/f00656m/.local/lib/python3.8/site-packages/pyprocar/scriptBandsDosplot.py&amp;quot;, line 181, in bandsdosplot&#xA;    tick_labels = np.array(re.findall(&amp;quot;!\s(.*)&amp;quot;, KPmatrix[0]))&#xA;**IndexError: list index out of range**&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="603" LastEditorUserId="5" LastEditDate="2023-02-04T21:44:31.487" LastActivityDate="2023-02-04T22:28:59.703" Title="PyProcar band-structure plot error" Tags="|density-functional-theory|vasp|band-structure|python|pyprocar|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10364" PostTypeId="2" ParentId="10363" CreationDate="2023-02-04T22:28:59.703" Score="4" Body="&lt;p&gt;From their code, it looks like &lt;code&gt;KPmatrix = re.findall(&amp;quot;reciprocal[\s\S]*&amp;quot;, KPread)&lt;/code&gt;, so it tries to grab everything from the word &amp;quot;reciprocal&amp;quot; to the end of &lt;code&gt;KPread&lt;/code&gt; (the read in KPOINTS file.&lt;/p&gt;&#xA;&lt;p&gt;As far as I can tell, the surrounding code doesn't do any processing of &lt;code&gt;KPread&lt;/code&gt; prior to this point, so I think the fix may be as simple as writing &amp;quot;reciprocal&amp;quot; rather than &amp;quot;Reciprocal&amp;quot; in that line of your KPOINTS file.&lt;/p&gt;&#xA;&lt;p&gt;If that works, you can mention it as a fix in the GitHub issue, though I should note the script you are using is listed in the repo under&lt;code&gt;pyprocar/v1/scripts&lt;/code&gt; and there seems to be an updated script for later versions of PyProcar.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-02-04T22:28:59.703" CommentCount="2" CommunityOwnedDate="2023-02-04T22:28:59.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="10365" PostTypeId="1" CreationDate="2023-02-05T12:54:28.263" Score="2" ViewCount="34" Body="&lt;p&gt;These are the meanings I`ve found, but I do not completely understand them.&#xA;Isopointal: Two structures that have the same space-group type or belong to a pair of enantiomorphic space groups. And that the complete sequence of the occupied Wyckoff positions is the same for both structures when the structural data have been standarized.&lt;/p&gt;&#xA;&lt;p&gt;Isoconfigurational:Isopointal and for all corresponding Wyckoff positions, both the crystallographic configurations (crystallographic orbits) and their  geometric interrelationships are similar.&lt;/p&gt;&#xA;&lt;p&gt;I do not understand the difference regarding the Wyckoff positions. I thought that if the atomic positions in the Wyckoff positions are the same then, the configuration is also the same. Peharps the problem is that I do not know what a configuration actually means. If someone could give a brief explanation I would be grateful.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="6544" LastActivityDate="2023-02-05T12:54:28.263" Title="Difference and meaning of isopointal and isoconfigurational structures" Tags="|crystallography|symmetry|" AnswerCount="0" CommentCount="0" ClosedDate="2023-10-01T14:42:24.313" ContentLicense="CC BY-SA 4.0" />
  <row Id="10366" PostTypeId="2" ParentId="10361" CreationDate="2023-02-06T12:53:06.280" Score="9" Body="&lt;h2&gt;Machine Learning for Physicists&lt;/h2&gt;&#xA;&lt;p&gt;If you wish for a general introduction to a number of ML concepts and tools useful in physics (not entirely specific to &amp;quot;material science&amp;quot;), and taught for physicists, I recommend &lt;a href=&quot;https://pad.gwdg.de/s/HJtiTE__U#&quot; rel=&quot;noreferrer&quot;&gt;the online course &amp;quot;Machine Learning for Physicists&amp;quot; by Florian Marquardt.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;All the lectures are &lt;a href=&quot;https://www.youtube.com/playlist?list=PLemsnf33Vij4eFWwtoQCrt9AHjLe3uo9_&quot; rel=&quot;noreferrer&quot;&gt;available on YouTube&lt;/a&gt;, and the course is shipped with a number of tutorials which can be found on &lt;a href=&quot;https://github.com/FlorianMarquardt/machine-learning-for-physicists&quot; rel=&quot;noreferrer&quot;&gt;the associated github repository.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2023-02-06T12:53:06.280" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10367" PostTypeId="2" ParentId="9269" CreationDate="2023-02-06T19:00:25.767" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9269/what-is-the-difference-between-nbo-program-and-nbo-that-we-find-in-gaussian#comment21583_9269&quot;&gt;I asked&lt;/a&gt; if the comment &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9269/what-is-the-difference-between-nbo-program-and-nbo-that-we-find-in-gaussian#comment19391_9269&quot;&gt;by Tyberius&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Gaussian actually is generally packaged with version 3 of the NBO program, as well as having an interface to more recent versions of NBO. Could you clarify what you mean/what you want in terms of getting the composition of an orbital?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and the comment &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9269/what-is-the-difference-between-nbo-program-and-nbo-that-we-find-in-gaussian#comment19393_9269&quot;&gt;by Greg&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In short, different program packages contain different versions of the NOB program (and corresponding interface), see examples: nbo6.chem.wisc.edu/affil_css.htm @Tyberius I think you can/should expand your commnet to an answer.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;were enough to answer their question, &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9269/what-is-the-difference-between-nbo-program-and-nbo-that-we-find-in-gaussian#comment21600_9269&quot;&gt;and they replied with&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I think it's enough thank you.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So this question no longer needs to be in the unanswered queue, but it doesn't need to be closed either, since it got an &amp;quot;answer&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T19:00:25.767" CommentCount="0" CommunityOwnedDate="2023-02-06T19:00:25.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="10368" PostTypeId="2" ParentId="9256" CreationDate="2023-02-06T19:04:51.897" Score="0" Body="&lt;p&gt;From the [comment by wzkchem5](Usually, when the output file ends with &amp;quot;NtrErr Called from FileIO&amp;quot;, the final part of the output file (~a few hundred lines) does not contain any information about the source of the error. You have to scroll up and skip all the &amp;quot;dumping /.../&amp;quot; messages in order to find the real cause of the error.):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Usually, when the output file ends with &amp;quot;NtrErr Called from FileIO&amp;quot;, the final part of the output file (~a few hundred lines) does not contain any information about the source of the error. You have to scroll up and skip all the &amp;quot;dumping /.../&amp;quot; messages in order to find the real cause of the error.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T19:04:51.897" CommentCount="0" CommunityOwnedDate="2023-02-06T19:04:51.897" ContentLicense="CC BY-SA 4.0" />
  <row Id="10369" PostTypeId="2" ParentId="9245" CreationDate="2023-02-06T19:11:13.597" Score="2" Body="&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9245/can-the-electrical-conductivity-tensor-of-a-crystal-be-obtained-from-a-hartree-f#comment19329_9245&quot;&gt;comment by Ian Bush&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In a rush but both Kubo-Greenwood approaches (e.g. arxiv.org/abs/2201.12290) and Boltzmann Transport equation (e.g. aip.scitation.org/doi/10.1063/1.4986398) have been used&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;got 5 upvotes and there's been no request for further clarification, so I'm moving this out of the unanswered queue, but keeping it open so that it remains to get the opportunity of getting a more detailed answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T19:11:13.597" CommentCount="0" CommunityOwnedDate="2023-02-06T19:11:13.597" ContentLicense="CC BY-SA 4.0" />
  <row Id="10370" PostTypeId="2" ParentId="9100" CreationDate="2023-02-06T21:04:15.080" Score="1" Body="&lt;p&gt;The OP has figured out the answer to the question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Hello , yes I wanted to install a package of Lammps after installing the LAMMPS. I figured it out. Tyberius answer helped me&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;based on a comment by Tyberius:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I think your links relate to two different methods of installation. The first link refers to installing a binary of LAMMPS and in that case I don't think you have the ability to link it with other programs since it is already built (though it may already be included in the executable). If the program you are looking for is not included, you need to build LAMMPS from source with the appropriate complier flags, which are the commands mentioned in your second link. Someone who knows more about LAMMPS may be able to help you more.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T21:04:15.080" CommentCount="0" CommunityOwnedDate="2023-02-06T21:04:15.080" ContentLicense="CC BY-SA 4.0" />
  <row Id="10371" PostTypeId="2" ParentId="9121" CreationDate="2023-02-06T21:07:24.143" Score="2" Body="&lt;p&gt;Anyon suggested the Hubbard chain:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;How about the Hubbard chain?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;and Phil Hasnip suggested Hooke's atom:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;What about Hooke's atom? It's a 3D system of 2 fully-interacting electrons, which is exactly solvable.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;for certain &amp;quot;magic&amp;quot; values of the interaction strength:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I don't think so, and it's only soluble analytically for certain &amp;quot;magic&amp;quot; values of the interaction strength, but it's still a nice playground for multi-electron physics&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T21:07:24.143" CommentCount="0" CommunityOwnedDate="2023-02-06T21:07:24.143" ContentLicense="CC BY-SA 4.0" />
  <row Id="10372" PostTypeId="2" ParentId="9145" CreationDate="2023-02-06T21:12:59.197" Score="1" Body="&lt;p&gt;The comments, especially those by jheindel, seem to be enough of an answer. Tyberius said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;@jheindel I agree with Nike, I think those comments could reasonably be converted to an answer.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;jheindel:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;ML force fields often transfer poorly. Not only between different elements, which often doesn't work at all, but even between different configurations of the same element. If you do simulations which sample vastly different configurations than ones you've already seen, then the ML will likely do very poorly. I assume VASP will fall back to DFT or whatever model you are using as a reference in that case. I don't see any reason why you shouldn't just always keep training the model when you run simulations, but don't expect that your model will transfer well between very different systems.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Another thing to be aware of is that some ML models have been known to &amp;quot;forget&amp;quot; things over time. That is, if you continue training the same set of weights on vastly different configurations for a very long time, certain types of neural networks will lose accuracy on predictions of configurations it used to predict well. This is dependent on the type of network and lots of other details, so this may or may not be a problem for you, but in principle it could matter. Typically this only happens if the network doesn't have enough parameters to &amp;quot;remember&amp;quot; all the information it's seen.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Raghunathan Ramakrishnan:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The colabfit project (colabfit.github.io/colabfit-tools/html/index.html) aims to provide such a framework.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Greg:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In addition to the previous remarks, you will have scaling issues: you have to represent all the information in your network, and you need a large enough parameter space to do so. ML models scales poorly when you start introducing new chemical environments/elements, so an “all element forcefield” with the present methods is very impractical.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T21:12:59.197" CommentCount="0" CommunityOwnedDate="2023-02-06T21:12:59.197" ContentLicense="CC BY-SA 4.0" />
  <row Id="10374" PostTypeId="2" ParentId="9182" CreationDate="2023-02-06T21:18:00.340" Score="2" Body="&lt;p&gt;Phil Hasnip:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I don't know any tools to automate this, but as an opening guess I would create a slab with one extra atomic layer on the surface. Then I would remove all oxygen in the extra layer, and replace the cations with hydrogen - i.e. put hydrogen in the positions the cations would usually occupy. Finally, I would shorten the O-H bonds by calculating the average of the initial hydrogen positions and their nearest oxygen, and placing the hydrogen there instead. It's quite crude, but fairly easy to do (and script).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I'd also recommend fixing all the atoms except the hydrogen for the first geometry optimisation - otherwise, the optimisation will distort the otherwise-good slab geometry. &amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;OP:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Yes, @NikeDattani. The solution given by PhilHasnip worked.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T21:18:00.340" CommentCount="0" CommunityOwnedDate="2023-02-06T21:18:00.340" ContentLicense="CC BY-SA 4.0" />
  <row Id="10375" PostTypeId="2" ParentId="9193" CreationDate="2023-02-06T21:19:13.470" Score="1" Body="&lt;p&gt;OP:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Hello! Perhaps, the most general formalism, which would allow to perform such analysis is based on the Berry phase theory. There are a bunch of papers doing this, for example, journals.aps.org/prb/abstract/10.1103/PhysRevB.101.081403, and nature.com/articles/s41467-021-21293-2. Authors of the latter paper wrote that the code they developed can be shared. I haven't tried it, since in my case the link to the paper I mentioned in the text of the question worked.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-06T21:19:13.470" CommentCount="0" CommunityOwnedDate="2023-02-06T21:19:13.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="10376" PostTypeId="1" CreationDate="2023-02-07T02:45:49.293" Score="4" ViewCount="250" Body="&lt;p&gt;Looking at &lt;a href=&quot;https://www.rcsb.org/ligand/1UN&quot; rel=&quot;nofollow noreferrer&quot;&gt;nelfinavir&lt;/a&gt;, I get variable results from different compchem packages on whether the phenol hydroxyl oxygen should be rotatable (SP3) or non-rotatable (SP2). Which one is it?&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://cdn.rcsb.org/images/ccd/unlabeled/1/1UN.svg&quot; alt=&quot;pic&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;Feasibly, there are resonance forms where double bonds hop over to the oxygen from the benzene. The &lt;a href=&quot;https://www.rcsb.org/search?request=%7B%22query%22%3A%7B%22type%22%3A%22group%22%2C%22nodes%22%3A%5B%7B%22type%22%3A%22group%22%2C%22nodes%22%3A%5B%7B%22type%22%3A%22group%22%2C%22logical_operator%22%3A%22and%22%2C%22nodes%22%3A%5B%7B%22type%22%3A%22terminal%22%2C%22service%22%3A%22text%22%2C%22parameters%22%3A%7B%22attribute%22%3A%22rcsb_nonpolymer_instance_feature_summary.comp_id%22%2C%22operator%22%3A%22exact_match%22%2C%22value%22%3A%221UN%22%7D%7D%2C%7B%22type%22%3A%22terminal%22%2C%22service%22%3A%22text%22%2C%22parameters%22%3A%7B%22attribute%22%3A%22rcsb_nonpolymer_instance_feature_summary.type%22%2C%22operator%22%3A%22exact_match%22%2C%22value%22%3A%22HAS_COVALENT_LINKAGE%22%7D%7D%2C%7B%22type%22%3A%22terminal%22%2C%22service%22%3A%22text%22%2C%22parameters%22%3A%7B%22attribute%22%3A%22rcsb_nonpolymer_instance_feature_summary.count%22%2C%22value%22%3A0%2C%22operator%22%3A%22equals%22%7D%7D%5D%7D%5D%2C%22logical_operator%22%3A%22and%22%2C%22label%22%3A%22text%22%7D%5D%2C%22logical_operator%22%3A%22and%22%7D%2C%22return_type%22%3A%22entry%22%2C%22request_options%22%3A%7B%22paginate%22%3A%7B%22start%22%3A0%2C%22rows%22%3A25%7D%2C%22results_content_type%22%3A%5B%22experimental%22%5D%2C%22sort%22%3A%5B%7B%22sort_by%22%3A%22score%22%2C%22direction%22%3A%22desc%22%7D%5D%2C%22scoring_strategy%22%3A%22combined%22%7D%2C%22request_info%22%3A%7B%22query_id%22%3A%221de521366fa394c9988d39e00dd86123%22%7D%7D&quot; rel=&quot;nofollow noreferrer&quot;&gt;crystal structures&lt;/a&gt; are all pretty consistent, showing a hydrogen bond from the hydroxyl that keeps the hydrogen planar with the benzene ring (consistent with SP2).&lt;/p&gt;&#xA;&lt;p&gt;RDKit claims this oxygen is SP2:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import rdkit&#xA;print(rdkit.__version__)&#xA;from rdkit import Chem&#xA;mol = Chem.MolFromSmiles('Cc1c(cccc1O)C(=O)N[C@@H](CSc2ccccc2)[C@@H](C[N@@]3C[C@H]4CCCC[C@H]4C[C@H]3C(=O)NC(C)(C)C)O')&#xA;atom = mol.GetAtomWithIdx(7)&#xA;print(atom.GetAtomicNum(), atom.GetHybridization())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;out: &lt;code&gt;2022.09.1 \n 8 SP2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, some packages claim SP3. Here's one example (not picking on PIKAChU here):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pikachu.general import read_smiles&#xA;s = read_smiles('Cc1c(cccc1O)C(=O)N[C@@H](CSc2ccccc2)[C@@H](C[N@@]3C[C@H]4CCCC[C@H]4C[C@H]3C(=O)NC(C)(C)C)O')&#xA;pika_at = s.atoms[7]&#xA;print(pika_at.hybridisation)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;out: &lt;code&gt;sp3&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Similarly, some paid packages optimize the coordinates of the bound molecule in the crystal structures, and treat the hydroxyl as rotatable. As a result of the optimization, the H-bond is no longer in-plane with the benzene, which would indicate SP3.&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="2225" LastEditorUserId="5" LastEditDate="2023-05-04T18:02:47.730" LastActivityDate="2023-05-04T18:02:47.730" Title="Should this phenolic hydroxyl be rotatable?" Tags="|molecular-modeling|crystallography|rdkit|pikachu|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10377" PostTypeId="2" ParentId="10376" CreationDate="2023-02-07T10:54:12.283" Score="5" Body="&lt;p&gt;The experimental findings (and from higher theory levels) are:&lt;/p&gt;&#xA;&lt;p&gt;The phenolic OH group is in plane with the aromatic ring (best lone pair overlap), with the barrier for rotation around 3.5 kcal/mol. The situation is similar in 2,6-dimethylphenol. In your case, the system is less symmetric so that you can have a preference for one position of the O-H group.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the empirical assignment, SP2 is definitely wrong. The O-H is in plane of aromatic ring for different reasons, than SP2 hybridization.&lt;/p&gt;&#xA;" OwnerUserId="6673" LastEditorUserId="6673" LastEditDate="2023-02-07T13:24:42.483" LastActivityDate="2023-02-07T13:24:42.483" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10378" PostTypeId="1" CreationDate="2023-02-07T14:26:08.443" Score="1" ViewCount="25" Body="&lt;p&gt;&lt;strong&gt;Can I use &lt;a href=&quot;http://mariovalle.name/CrystalFp/html/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CrystalFp&lt;/a&gt; library to analyze different structures (e.g. of Ca2Si04) that don't have the same number of atoms?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want to compare e.g. structure_1 with composition [2,1,4] and structure_2 with composition [16,8,32]. Maybe both structures are the same but the second one is a supercell of the other.&lt;/p&gt;&#xA;&lt;p&gt;I have been reading and I do not know whether CrystalFp can do this if the  structures have different compositions.&lt;/p&gt;&#xA;" OwnerUserId="6544" LastEditorUserId="7" LastEditDate="2023-02-11T01:41:49.017" LastActivityDate="2023-02-11T01:41:49.017" Title="Can CrystalFp library be used to compare structures with different number of atoms?" Tags="|crystallography|visualization-software|crystal-field|crystalfp|" AnswerCount="0" CommentCount="0" ClosedDate="2023-02-11T01:42:52.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="10379" PostTypeId="5" CreationDate="2023-02-07T15:01:00.403" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://mariovalle.name/CrystalFp/html/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://mariovalle.name/CrystalFp/html/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-07T15:01:00.403" LastActivityDate="2023-02-07T15:01:00.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10380" PostTypeId="4" CreationDate="2023-02-07T15:01:00.403" Score="0" Body="Questions about CrystalFp, the crystal fingerprinting project." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-07T15:01:00.403" LastActivityDate="2023-02-07T15:01:00.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10381" PostTypeId="5" CreationDate="2023-02-07T15:44:35.593" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://jcheminf.biomedcentral.com/articles/10.1186/s13321-022-00616-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://jcheminf.biomedcentral.com/articles/10.1186/s13321-022-00616-5&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-07T15:44:35.593" LastActivityDate="2023-02-07T15:44:35.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10382" PostTypeId="4" CreationDate="2023-02-07T15:44:35.593" Score="0" Body="Questions about PIKAChU (Python-based informatics kit for analysing chemical units)" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-07T15:44:35.593" LastActivityDate="2023-02-07T15:44:35.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10383" PostTypeId="1" CreationDate="2023-02-07T18:39:24.757" Score="1" ViewCount="48" Body="&lt;p&gt;I am currently doing scattering region and transmission calculations using Siesta (4.1.5), the scattering region calculation is taking very long time to complete. I tried using different numbers of processors, like 48, 18, 36, etc., with paralleloverK as &amp;quot;true&amp;quot; and also tried divide and conquer as true , false, but I am unable to get faster results.&lt;/p&gt;&#xA;&lt;p&gt;how can I increase the speed of my calculation.&lt;/p&gt;&#xA;&lt;p&gt;Thankyou&lt;/p&gt;&#xA;" OwnerUserId="6561" LastActivityDate="2023-02-07T18:39:24.757" Title="how to speed up the scattering region calculation and transmission calculation in Transiesta" Tags="|siesta|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:06:56.900" ContentLicense="CC BY-SA 4.0" />
  <row Id="10384" PostTypeId="1" CreationDate="2023-02-07T20:18:56.527" Score="4" ViewCount="78" Body="&lt;p&gt;Is there a program to classify and compare structures with different composition?&lt;/p&gt;&#xA;&lt;p&gt;I want to compare e.g. structure_1 with composition [2,1,4] and structure_2 with composition [16,8,32]. Maybe both structures are the same but the second one is a supercell of the other.&lt;/p&gt;&#xA;&lt;p&gt;I'm considering the case in which the number of atoms is different, but with the same proportion of each one (the numbers of atoms of each type in one structure are integer &lt;strong&gt;multiples&lt;/strong&gt; of the numbers of atoms of each type in the other structure). I need a program that is able to identify a supercell and determine whether its unit cell is an integer multiple of another structure's unit cell or not.&lt;/p&gt;&#xA;&lt;p&gt;Automatically noticing that a given structure is a supercell and then being able to extract the unit cell  for comparison would be nice. I have created a lot of structures with varying composition and probably most of them are the same but in different &amp;quot;sizes&amp;quot; or &amp;quot;volumes&amp;quot;, so I need to know which ones are truly useful and new.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can I use &lt;a href=&quot;http://mariovalle.name/CrystalFp/html/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CrystalFp&lt;/a&gt; library to analyze different structures (e.g. of Ca2Si04) that don't have the same number of atoms?&lt;/strong&gt; I have been reading and I do not know whether CrystalFp can do this if the  structures have different compositions. If not, what about other programs?&lt;/p&gt;&#xA;" OwnerUserId="6544" LastEditorUserId="7" LastEditDate="2023-02-11T01:41:10.470" LastActivityDate="2023-10-01T05:23:15.930" Title="Program to classify structures of different composition?" Tags="|software-recommendations|one-topic-per-answer|crystallography|supercell|crystalfp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10385" PostTypeId="2" ParentId="9209" CreationDate="2023-02-07T22:23:18.063" Score="3" Body="&lt;p&gt;Here is an example input file (MINP) for calculating &lt;span class=&quot;math-container&quot;&gt;$E_{XC}=1.0E^{HF}_X+1.0E^{srLYP}_C$&lt;/span&gt; where the range separated omega value equals to 0.33.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;basis = 6-31g&#xA;symm  = off&#xA;dft   = userd&#xA;2&#xA;1.0 HFx&#xA;0.000000001 lrHFx 0.33&#xA;2&#xA;1.0 ssrGGA_C_LYP&#xA;0.000000001 lrHFx 0.33&#xA;&#xA;&#xA;mult     = 1&#xA;mem      = 5000MB&#xA;&#xA;unit=angs&#xA;geom=xyz&#xA;3&#xA;&#xA;O   0.0000   0.0000   0.0626&#xA;H  -0.7920   0.0000  -0.4973&#xA;H   0.7920   0.0000  -0.4973&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="790" LastActivityDate="2023-02-07T22:23:18.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10387" PostTypeId="2" ParentId="10310" CreationDate="2023-02-08T14:39:04.867" Score="5" Body="&lt;p&gt;Perhaps the question should be reformulated into under what circumstances O2 dianion is stable. There are no atoms that can bind two electrons, and given the electron affinity of O being 1.47 eV, and that of O2 being 0.9 eV, I would strongly expect that the O2 dianion is not stable in the gas phase. Indeed, the CCSD(T)/aug-cc-pV5Z energy for the dianion is significantly higher than the mono-anion. Yes, you can calculate the dianion species with the above methods, but even large basis sets like aug-cc-pV5Z do not allow the extra electron to escape. If more and more diffuse basis functions are added, the extra electron would drift to infinity, and you would be left with the monoanion. All of the above calculated results therefore are just artifacts of the chosen methods and basis set being unable to describe the real system. A O2 dianion can be stable in e.g. a matrix of cations, but if the stated question relates to the gas phase, then the answer is that there is no answer.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-02-08T14:39:04.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10388" PostTypeId="2" ParentId="10133" CreationDate="2023-02-08T14:50:26.853" Score="3" Body="&lt;p&gt;Colvars package is required to use collective variables and various methods of sampling such as metadynamics, umbrella sampling, ABF, etc. The package can be called using the &lt;code&gt;fix colvars&lt;/code&gt; command. However, it does not come with LAMMPS and must be installed separately.&lt;/p&gt;&#xA;&lt;p&gt;1- Based on your OS, To install LAMMPS and Colvars, &lt;strong&gt;carefully&lt;/strong&gt; follow the instructions at &lt;a href=&quot;https://docs.lammps.org/Build.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Build lammps&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;1.1. If using &lt;code&gt;cmake&lt;/code&gt;, use the flag &lt;code&gt;-D PKG_COLVARS=yes&lt;/code&gt;. For &lt;code&gt;make&lt;/code&gt;, use &lt;code&gt;make lib-colvars args=&amp;quot;-m g++-debug”&lt;/code&gt;. You may need to modify &lt;code&gt;Makefile.serial&lt;/code&gt; and &lt;code&gt;Makefile.mpi&lt;/code&gt; to include the following, for example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CC =        clang++&#xA;CCFLAGS =   -std=c++11 -stdlib=libc++&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;1.2. Additional packages, such as reaxff or molecules, may also be required. See &lt;a href=&quot;https://docs.lammps.org/Build_package.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; for the appropriate flags.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;After installing Colvars, you can use it in LAMMPS by calling &lt;code&gt;fix colvars&lt;/code&gt;. Colvars provides well-written manuals for different MD packages, including LAMMPS. Find the manual for LAMMPS &lt;a href=&quot;https://colvars.github.io/pdf/colvars-refman-lammps.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. From the manual (P. 75), to perform metadynamics, a colvar must be defined, for example:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;colvar {&#xA;  name r&#xA;  distance { ... }&#xA;  upperBoundary 15.0&#xA;  width 0.2&#xA;}&#xA;metadynamics {&#xA;  name meta_r&#xA;  colvars r&#xA;  hillWeight 0.001&#xA;  hillWidth 2.0&#xA;}&#xA;harmonicWalls {&#xA;  name wall_r&#xA;  colvars r&#xA;  upperWalls 13.0&#xA;  upperWallConstant 2.0&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;The core functionality of Colvars is consistent across different MD packages. For questions related to Colvars, the &lt;a href=&quot;https://www.ks.uiuc.edu/Research/namd/mailing_list/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NAMD Mailing List&lt;/a&gt; is a good resource.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5483" LastActivityDate="2023-02-08T14:50:26.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10389" PostTypeId="2" ParentId="9110" CreationDate="2023-02-08T17:10:18.200" Score="1" Body="&lt;p&gt;In the end, the OP &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9110/what-is-the-best-cell-shape-to-calculate-the-energy-of-a-free-atom-with-a-period?noredirect=1#comment22171_9110&quot;&gt;did the following&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;take a unit cell of the bulk of that metal, calculate its energy and then divide it by the number of atoms in the unit cell. &amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The question can stay open in case a better answer may come in the future, but the question also doesn't need to remain in the unanswered queue since the OP is not longer working on the project (see the same comment linked above).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-08T17:10:18.200" CommentCount="2" CommunityOwnedDate="2023-02-08T17:10:18.200" ContentLicense="CC BY-SA 4.0" />
  <row Id="10391" PostTypeId="2" ParentId="9805" CreationDate="2023-02-09T13:44:21.077" Score="6" Body="&lt;p&gt;You can use &lt;a href=&quot;http://www.rdkit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDkit&lt;/a&gt; to draw 2D structures of molecules.&lt;br /&gt;&#xA;You can use &lt;a href=&quot;http://www.rdkit.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDkit&lt;/a&gt; + &lt;a href=&quot;https://pypi.org/project/py3Dmol/&quot; rel=&quot;nofollow noreferrer&quot;&gt;py3Dmol&lt;/a&gt; to draw 3d structures of molecules.&lt;/p&gt;&#xA;&lt;p&gt;You can install them with pip like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pip install rdkit&#xA;pip install py3Dmol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;3D structures&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;import py3Dmol&#xA;from rdkit import Chem&#xA;from rdkit.Chem import AllChem&#xA;&#xA;def MolTo3DView(mol, size=(300, 300), style=&amp;quot;stick&amp;quot;, surface=False, opacity=0.5):&#xA;    &amp;quot;&amp;quot;&amp;quot;Draw molecule in 3D&amp;quot;&amp;quot;&amp;quot;&#xA;    assert style in ('line', 'stick', 'sphere', 'carton')&#xA;    mblock = Chem.MolToMolBlock(mol)&#xA;    viewer = py3Dmol.view(width=size[0], height=size[1])&#xA;    viewer.addModel(mblock, 'mol')&#xA;    viewer.setStyle({style:{}})&#xA;    if surface:&#xA;        viewer.addSurface(py3Dmol.SAS, {'opacity': opacity})&#xA;    viewer.zoomTo()&#xA;    return viewer&#xA;&#xA;def smi2conf(smiles):&#xA;    '''Convert SMILES to rdkit.Mol with 3D coordinates'''&#xA;    mol = Chem.MolFromSmiles(smiles)&#xA;    if mol is not None:&#xA;        mol = Chem.AddHs(mol)&#xA;        AllChem.EmbedMolecule(mol)&#xA;        AllChem.MMFFOptimizeMolecule(mol, maxIters=200)&#xA;        return mol&#xA;    else:&#xA;        return None&#xA;&#xA;smi = 'O=C(O)C(O)C(O)C(=O)O'&#xA;conf = smi2conf(smi)&#xA;# This will open an interactive image viewer&#xA;viewer = MolTo3DView(conf, size=(600, 300), style='sphere')&#xA;viewer.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9nija.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9nija.png&quot; alt=&quot;3d_structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;2D structures&lt;/h1&gt;&#xA;&lt;p&gt;Here is a sample code to draw 2D diagram of tartaric acid:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import Draw&#xA;&#xA;input_smiles = 'O=C(O)C(O)C(O)C(=O)O'&#xA;mol = Chem.MolFromSmiles(input_smiles)&#xA;Draw.MolToImage(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/R4bP3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/R4bP3.png&quot; alt=&quot;without_numbering&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can also specify options such as numbering the individual atoms like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import Draw&#xA;from rdkit.Chem.Draw import rdMolDraw2D&#xA;&#xA;input_smiles = 'O=C(O)C(O)C(O)C(=O)O'&#xA;mol = Chem.MolFromSmiles(input_smiles)&#xA;dos = Draw.MolDrawOptions()&#xA;dos.addAtomIndices=True&#xA;Draw.MolToImage(mol, options= dos)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TLu6s.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TLu6s.png&quot; alt=&quot;with_numbering&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-02-09T14:28:41.290" LastActivityDate="2023-02-09T14:28:41.290" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10392" PostTypeId="2" ParentId="9456" CreationDate="2023-02-09T15:53:23.707" Score="4" Body="&lt;p&gt;This can be achieved with a 3d interactive contour plot.&lt;br /&gt;&#xA;Here I have higlighted the current cursor position with a red dot.&lt;br /&gt;&#xA;It gives you all the x, y, z values at that point.&#xA;The below plot is generated with a small sample of your data from the screenshot of the x,y,z values.&#xA;I am plotting on a google colab notebook.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LGrtA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LGrtA.png&quot; alt=&quot;3d_contour_plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Install and initialize backend&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!pip install ipympl&#xA;&#xA;%matplotlib widget&#xA;&#xA;from google.colab import output&#xA;output.enable_custom_widget_manager()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Main code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pandas as pd&#xA;import matplotlib.pyplot as plt&#xA;import numpy as np&#xA;from mpl_toolkits import mplot3d&#xA;&#xA;data= [ [0,0,0.254], [0, 0.14,0.27], [0,0.29, 0.30], [0.1, 0.43, 0.31]] # Using a subset of your data&#xA;data_M = np.array(data)&#xA;&#xA;X=data_M[:,0]&#xA;Y=data_M[:,1]&#xA;Z=data_M[:,2]&#xA;&#xA;# change to 1000 for your original script&#xA;Xs=X.reshape((2,2))&#xA;Ys=Y.reshape((2,2))&#xA;Zs=Z.reshape((2,2))&#xA;&#xA;fig = plt.figure()&#xA;ax = plt.axes(projection='3d')&#xA;ax.contour3D(Xs, Ys, Zs)&#xA;&#xA;ax.set_title('Contour Plot')&#xA;ax.set_xlabel('X')&#xA;ax.set_ylabel('Y')&#xA;ax.set_zlabel('Z')&#xA;&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-02-09T15:53:23.707" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10393" PostTypeId="1" AcceptedAnswerId="10394" CreationDate="2023-02-09T19:27:45.167" Score="2" ViewCount="277" Body="&lt;p&gt;I want to calculate the thermodynamic parameters for a single molecule at a certain temperature. How may I do it with PySCF?&lt;/p&gt;&#xA;" OwnerUserId="6688" LastEditorUserId="5" LastEditDate="2023-02-09T19:45:23.537" LastActivityDate="2023-02-09T20:01:38.963" Title="How may I calculate free energy using PySCF?" Tags="|computational-chemistry|thermodynamics|pyscf|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10394" PostTypeId="2" ParentId="10393" CreationDate="2023-02-09T20:01:38.963" Score="1" Body="&lt;p&gt;An example in which the Gibbs free energy was calculated at 298.15 K was given &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/hessian/10-thermochemistry.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; by the lead author of PySCF:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;#&#xA;# Author: Qiming Sun &amp;lt;osirpt.sun@gmail.com&amp;gt;&#xA;#&#xA;&#xA;'''&#xA;Thermochemistry analysis based on nuclear Hessian.&#xA;'''&#xA;&#xA;from pyscf import gto&#xA;from pyscf.hessian import thermo&#xA;&#xA;# First compute nuclear Hessian.&#xA;mol = gto.M(&#xA;    atom = '''O    0.   0.       0&#xA;              H    0.   -0.757   0.587&#xA;              H    0.    0.757   0.587''',&#xA;    basis = '631g')&#xA;&#xA;mf = mol.RHF().run()&#xA;hessian = mf.Hessian().kernel()&#xA;&#xA;# Frequency analysis&#xA;freq_info = thermo.harmonic_analysis(mf.mol, hessian)&#xA;# Thermochemistry analysis at 298.15 K and 1 atmospheric pressure&#xA;thermo_info = thermo.thermo(mf, freq_info['freq_au'], 298.15, 101325)&#xA;&#xA;print('Rotation constant')&#xA;print(thermo_info['rot_const'])&#xA;&#xA;print('Zero-point energy')&#xA;print(thermo_info['ZPE'   ])&#xA;&#xA;print('Internal energy at 0 K')&#xA;print(thermo_info['E_0K'  ])&#xA;&#xA;print('Internal energy at 298.15 K')&#xA;print(thermo_info['E_tot' ])&#xA;&#xA;print('Enthalpy energy at 298.15 K')&#xA;print(thermo_info['H_tot' ])&#xA;&#xA;print('Gibbs free energy at 298.15 K')&#xA;print(thermo_info['G_tot' ])&#xA;&#xA;print('Heat capacity at 298.15 K')&#xA;print(thermo_info['Cv_tot'])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I found that by searching &amp;quot;free energy PySCF&amp;quot; in Google.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-09T20:01:38.963" CommentCount="0" CommunityOwnedDate="2023-02-09T20:01:38.963" ContentLicense="CC BY-SA 4.0" />
  <row Id="10395" PostTypeId="2" ParentId="9805" CreationDate="2023-02-09T21:57:45.793" Score="1" Body="&lt;p&gt;You may be interested in the venerable &lt;a href=&quot;https://jsme-editor.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;JSME&lt;/a&gt;, used by web applications like WebMO and the Automated Topology Builder, or &lt;a href=&quot;https://github.com/itayYaakov/SketChem&quot; rel=&quot;nofollow noreferrer&quot;&gt;SketChem&lt;/a&gt; which is now in development.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-02-09T21:57:45.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10396" PostTypeId="1" AcceptedAnswerId="10397" CreationDate="2023-02-10T02:20:23.170" Score="3" ViewCount="191" Body="&lt;p&gt;I am using the ASE library to compute the distance matrix with minimum image convention. In that, I have got the positions of all atoms in the cell.&lt;/p&gt;&#xA;&lt;p&gt;Now I wish to calculate the distance between each of them by considering the translation vector on the three Bravais lattice vectors. For example the position of atom is &lt;code&gt;pos1 = [0.11 , 0.23 , 0.156]&lt;/code&gt; now I have to translate this using the combinations of the three lattice vectors &lt;code&gt;(t1,t2,t3)&lt;/code&gt; with cell size &lt;code&gt;(a,b,c)&lt;/code&gt; respectively. That will be, like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pos1_1 = [0.11+a*t1 , 0.23 , 0.156]&#xA;pos1_2 =...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And so on.&lt;/p&gt;&#xA;&lt;p&gt;How can this be done with ASE?&lt;/p&gt;&#xA;" OwnerUserId="6643" LastEditorUserId="7" LastEditDate="2023-02-10T02:36:59.257" LastActivityDate="2023-02-10T14:00:12.600" Title="How to determine the lattice vector direction and magnitude in ASE" Tags="|python|atomic-simulation-environment|materials-design|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10397" PostTypeId="2" ParentId="10396" CreationDate="2023-02-10T14:00:12.600" Score="2" Body="&lt;p&gt;Offsets in positions is straightforwardly done in ASE:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# just a test system&#xA;from ase.build import bulk&#xA;ni = bulk('Ni', 'hcp', a=2.5, c=4.0)&#xA;&#xA;# now to process for an offset&#xA;t1 = 1&#xA;t2 = 2&#xA;t3 = 3&#xA;print(&amp;quot;cell = &amp;quot;)&#xA;print(ni.cell)&#xA;print(&amp;quot;before translation = &amp;quot;)&#xA;print(ni.positions)&#xA;ni.positions += (t1, t2, t3) @ ni.cell&#xA;print(&amp;quot;after translation = &amp;quot;)&#xA;print(ni.positions)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I think you should look into &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/neighborlist.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/neighborlist.html&lt;/a&gt; for details on getting actual neighbours in a faster fashion :)&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-02-10T14:00:12.600" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10398" PostTypeId="1" CreationDate="2023-02-10T22:29:08.130" Score="2" ViewCount="45" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/q/749574/134583&quot;&gt;Cross-posted on Physics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It makes sense that something like grain-oriented electrical steel would have good magnetic properties (e.g., magnetic permeability). I'm envisioning magnetic field lines being guided by regularly arranged atoms.&lt;/p&gt;&#xA;&lt;p&gt;I understand, however, that amorphous steel can also have good magnetic properties. How is this possible without a crystalline structure in the metal?&lt;/p&gt;&#xA;" OwnerUserId="6700" LastEditorUserId="5" LastEditDate="2023-02-10T22:56:05.193" LastActivityDate="2023-02-11T23:07:35.553" Title="How is it possible for amorphous metal to have good magnetic properties with randomly arranged atoms?" Tags="|crystallography|magnetism|from-phys-se|metals|magnetic-field|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10399" PostTypeId="5" CreationDate="2023-02-11T01:44:31.030" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://mariovalle.name/CrystalFp/html/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://mariovalle.name/CrystalFp/html/index.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-11T01:44:31.030" LastActivityDate="2023-02-11T01:44:31.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10400" PostTypeId="4" CreationDate="2023-02-11T01:44:31.030" Score="0" Body="Questions about CrystalFp, the crystal fingerprinting project." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-11T01:44:31.030" LastActivityDate="2023-02-11T01:44:31.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10401" PostTypeId="1" CreationDate="2023-02-11T09:20:37.327" Score="3" ViewCount="54" Body="&lt;p&gt;I am preparing to conduct a shock simulation for an energetic material in LAMMPS with the help of a classical forcefield. How can I apply shock front absorbing boundary condition so that I can gather information during shock properly?&lt;/p&gt;&#xA;" OwnerUserId="5591" LastActivityDate="2023-02-11T09:20:37.327" Title="How to apply shock front absorbing boundary condition in LAMMPS" Tags="|lammps|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:07:11.623" ContentLicense="CC BY-SA 4.0" />
  <row Id="10402" PostTypeId="1" CreationDate="2023-02-11T09:37:35.367" Score="1" ViewCount="254" Body="&lt;p&gt;I started to optimise a selected cavity of the enzyme with a metal ion using Gaussian 09 software. The basis set used for C,H,N and O atoms was 6-311+G(d) and for the Cd2+ ion was def2-tzvp. And, after few seconds of the Gaussian calculation, the job terminates with the memory error. Then I tried the suggested solution of using &amp;quot;%mem=1043MW&amp;quot; . But that did not work and the Gaussian run terminated after reading the coordinates and no error was mentioned.&#xA;How can I solve this issue and what might be the reason for this, any wrong in the method?&#xA;I have attached the link to my Gaussian files &lt;a href=&quot;https://raw.githubusercontent.com/HPQC-LABS/Modeling_Matters/master/10402/10402.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In preparing the input file I have included the all the hydrogen atoms.&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="7" LastEditDate="2023-02-17T16:36:43.263" LastActivityDate="2023-02-28T07:32:01.443" Title="Gaussian enzyme optimization fails, possible memory error?" Tags="|gaussian|optimization|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="10403" PostTypeId="1" AcceptedAnswerId="10404" CreationDate="2023-02-11T15:36:08.593" Score="4" ViewCount="138" Body="&lt;p&gt;I am given a list of edges: [a, b, c] and dihedral angles: [alpha, beta, gamma]. Can we determine the lattice vector directions of this unit cell?&lt;/p&gt;&#xA;&lt;p&gt;e.g Edge &lt;strong&gt;lengths:&lt;/strong&gt; &lt;code&gt;[5.25953209086, 6.08183093896, 6.17370692269]&lt;/code&gt; &lt;strong&gt;angles:&lt;/strong&gt; &lt;code&gt;[119.50892382300002, 107.841528116, 89.9999968787]&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I used &lt;code&gt;cell = Cell.fromcellpar([5.25953209086, 6.08183093896, 6.17370692269, 119.50892382300002, 107.841528116, 89.9999968787])&lt;/code&gt;. Such that it gave me the bravaise lattice as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(cell.get_bravais_lattice())&#xA;&#xA;&amp;gt; TRI(a=6.08183, b=5.25953, c=6.17371, alpha=107.842, beta=119.509,&#xA;&amp;gt; gamma=90)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How to find the directions of this unit cell? For example, if this unit cell has an atom positioned at &lt;code&gt;pos_atom = [0.3, 2.3, 1.8]&lt;/code&gt; then I may find the translated atom in the adjacent unit cell by travelling unit_cell length in some unit vector direction.&lt;/p&gt;&#xA;" OwnerUserId="6643" LastEditorUserId="5" LastEditDate="2023-02-11T15:47:22.280" LastActivityDate="2023-02-13T09:56:32.407" Title="Given cell edge lengths and dihedral angles, calculate lattice vectors?" Tags="|python|materials-engineering|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10404" PostTypeId="2" ParentId="10403" CreationDate="2023-02-11T19:36:32.080" Score="5" Body="&lt;p&gt;The data you presented ARE the cell parameters: a, b, c and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; . They are not called &amp;quot;edge lengths&amp;quot; neither &amp;quot;dihedral angles&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Also, you don't need to change your lattice to the Bravais one. If you want the position of an atom in (any of) the adjacent cell, the translation vector will be: &lt;span class=&quot;math-container&quot;&gt;$$\vec{T}=u_1\vec{a}+u_2\vec{b}+u_3\vec{c}\tag{1}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$u_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$u_2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$u_3$&lt;/span&gt; are integers. The final position of the atoms (&lt;span class=&quot;math-container&quot;&gt;$\vec{r}'$&lt;/span&gt;) will be: &lt;span class=&quot;math-container&quot;&gt;$$\tag{2}\vec{r}'=\vec{r}+\vec{T}$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\vec{r}$&lt;/span&gt; being the initial coordinate.&lt;/p&gt;&#xA;&lt;p&gt;Also, the directions are set using the Miller indices &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2023-02-11T19:49:08.713" LastActivityDate="2023-02-11T19:49:08.713" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10405" PostTypeId="2" ParentId="10398" CreationDate="2023-02-11T23:07:35.553" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/a/749592/134583&quot;&gt;Answer by Ján Lalinský that was accepted by OP on Physics.SE&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Amorphous means positions of atoms are random. But this still allows for aligned magnetic moments. Then for magnetization it does not matter where the atoms are, only that their moments are aligned.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-11T23:07:35.553" CommentCount="0" CommunityOwnedDate="2023-02-11T23:07:35.553" ContentLicense="CC BY-SA 4.0" />
  <row Id="10406" PostTypeId="1" CreationDate="2023-02-12T07:06:41.077" Score="3" ViewCount="410" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9937/rdkit-how-can-i-get-a-weighted-adjacency-matrix-where-the-weights-are-bond-leng&quot;&gt;Rdkit: How can I get a weighted adjacency matrix where the weights are bond lengths, from the SMILES of my molecule?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above link is code to get bond length matrix from smiles.&lt;/p&gt;&#xA;&lt;p&gt;Now are we able to convert to an XYZ file?&lt;/p&gt;&#xA;" OwnerUserId="6241" LastEditorUserId="5" LastEditDate="2023-02-12T11:32:25.543" LastActivityDate="2023-11-05T15:46:41.180" Title="Is it possible to convert the smiles to XYZ file after getting bond distance matrix as in link attached" Tags="|rdkit|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10407" PostTypeId="1" AcceptedAnswerId="10412" CreationDate="2023-02-12T15:36:46.533" Score="9" ViewCount="271" Body="&lt;p&gt;I am a beginner in DFT. Recently I have been working on calculating the energy (with zero point correction), and may be free energy in the future, for a structure in both stable and unstable configurations.&lt;/p&gt;&#xA;&lt;p&gt;Obviously, with the unstable structure, some of the phonon modes will be imaginary. I was wondering how to do zero-point correction in this case: &lt;strong&gt;do I just discard all imaginary modes or is there some sophisticated ways to do this properly?&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="6704" LastEditorUserId="5" LastEditDate="2023-02-12T18:23:33.037" LastActivityDate="2023-02-13T19:01:11.837" Title="Zero point correction and free energy calculation with imaginary modes?" Tags="|phonons|free-energy|zero-point-energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10408" PostTypeId="1" CreationDate="2023-02-13T05:31:19.897" Score="9" ViewCount="287" Body="&lt;p&gt;I originally &lt;a href=&quot;https://physics.stackexchange.com/q/748945/134583&quot;&gt;asked this on Physics.SE&lt;/a&gt; but was suggested to ask here instead.&lt;/p&gt;&#xA;&lt;p&gt;I'm a high school student interested in material simulation. I want to do a project involving density functional theory to simulate the molecular structure of a many-atom monomer (I am thinking about an aramid like Kevlar). I want to be able to simulate certain properties of many molecules like this. I have an abstract proposal with more specific details, but am not sure how to move forward from a software/simulation standpoint.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any training material or links on python for density functional theory, as well as learning more about the tool and practicality of my idea in general.&lt;/p&gt;&#xA;&lt;p&gt;Of course, I am not an expert and don’t know how feasible this actually is, so I am willing to make some adjustments to my idea.&lt;/p&gt;&#xA;&lt;p&gt;I am also looking for ways to find more granular guidance with the above.&lt;/p&gt;&#xA;" OwnerUserId="6706" LastEditorUserId="201" LastEditDate="2023-02-14T05:17:43.310" LastActivityDate="2023-02-15T07:20:35.987" Title="High school student that wants to do DFT calculations" Tags="|density-functional-theory|reference-request|python|from-phys-se|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10410" PostTypeId="2" ParentId="9127" CreationDate="2023-02-13T16:56:27.490" Score="1" Body="&lt;p&gt;As @Tyberius mentioned, you can study many different things using Molecular Dynamics simulations of proteins. My senior had studied the structure and dynamics of Intrinsically Disordered Proteins (IDPs) using MD simulations. You can refer to &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acschemneuro.1c00084&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jpcb.9b11720&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; to get an idea about what I just mentioned. You can also refer to this &lt;a href=&quot;https://www.science.org/doi/pdf/10.1126/sciadv.1700014&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; by Prof. Jagannath Mondal, where they studied the binding of an anti-cancer drug using MD simulations.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-02-13T16:56:27.490" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10411" PostTypeId="1" CreationDate="2023-02-13T17:12:48.663" Score="3" ViewCount="187" Body="&lt;p&gt;I'm working on an i7 laptop with the parallel version of Quantum ESPRESSO (8 processors are running). I ran a post-processing calculation by &lt;code&gt;pp.x -in ppinput.in &amp;gt; ppoutput.out&lt;/code&gt; and the following input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA;prefix='rocksalt',&#xA;outdir='.',&#xA;filplot='ppoutputfile.txt',&#xA;plot_num=9,&#xA;/&#xA;&amp;amp;PLOT&#xA;nfile=1,&#xA;iflag=3,&#xA;output_format=3,&#xA;fileout='rocksalt.xsf',&#xA;e1(1)=1.0,e1(2)=0.0,e1(3)=0.0,&#xA;e2(1)=0.0,e2(2)=1.0,e2(3)=0.0,&#xA;e3(1)=0.0,e3(2)=0.0,e3(3)=1.0,&#xA;x0(1)=0.0,x0(2)=0.0,x0(3)=0.0,&#xA;nx=101, ny=101, nz=101,&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The ppoutputfile.txt file was generated very quickly but the rocksalt.xsf file is not generated yet, knowing that it is been 9 hours now and the operation did not complete yet . When I open the ppoutput.out file it is written in the last line &lt;code&gt; Writing data to be plotted to file  rocksalt.xsf&lt;/code&gt; .&lt;/p&gt;&#xA;&lt;p&gt;Is it normal that the calculation still did not complete till now?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-13T17:24:21.067" LastActivityDate="2023-02-13T17:24:21.067" Title="Why is my post-processing calculation using Quantum ESPRESSO not complete after 9 hours?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|high-performance-computing|charge-density|" AnswerCount="0" CommentCount="5" ClosedDate="2023-10-22T20:08:19.853" ContentLicense="CC BY-SA 4.0" />
  <row Id="10412" PostTypeId="2" ParentId="10407" CreationDate="2023-02-13T19:01:11.837" Score="5" Body="&lt;p&gt;The two most common approaches for dealing with imaginary frequencies in free energy computations are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Compute the free energy using only the modes with real valued frequencies&lt;/li&gt;&#xA;&lt;li&gt;Reoptimize the structure to remove any imaginary frequencies&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Neither of these are ideal: 1 is not necessarily a reasonable approximation and 2 will likely distort the geometry relative to the configuration that you aim to study.&lt;/p&gt;&#xA;&lt;p&gt;The Grimme group recently developed the Single-Point (or Biased) Hessian approach for computing free energies of non-equilibrium structures &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c01306&quot; rel=&quot;noreferrer&quot;&gt;[1]&lt;/a&gt;. This approach reoptimizes the geometry under a constraining potential, aiming to remove imaginary frequencies while retaining the initial structure as much as possible. From the paper, this can lead to more accurate calculations of free energy and is a more rigorous way of handling non-equilibrium structures.&lt;/p&gt;&#xA;&lt;p&gt;Off-hand, I only know of this method being implemented in xTB, but the paper gives a description of a general implementation.&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Sebastian Spicher and Stefan Grimme&#xA;Journal of Chemical Theory and Computation 2021 17 (3), 1701-1714&#xA;DOI: &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.0c01306&quot; rel=&quot;noreferrer&quot;&gt;10.1021/acs.jctc.0c01306&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-02-13T19:01:11.837" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10413" PostTypeId="2" ParentId="10408" CreationDate="2023-02-13T23:07:09.030" Score="8" Body="&lt;p&gt;I'm happy to hear that you've chosen Matter Modeling for your high school project!&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;If your goal is to write a Python program from scratch for DFT calculations, then the following thread may help you: &lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1056/5&quot;&gt;How to write my own density functional theory (DFT) code in Python?&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If your goal is to use an existing Python program to &lt;em&gt;&lt;strong&gt;run&lt;/strong&gt;&lt;/em&gt; some DFT calculations, then the following thread may help you: &lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1053/how-to-get-my-feet-wet-in-density-functional-theory-by-simulating-a-water-mole&quot;&gt;How to &amp;quot;get my feet wet&amp;quot; in Density Functional Theory by simulating a water molecule using Python&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If your goal is to understand DFT as a high school student, then the following thread was &amp;quot;made&amp;quot; for you (!): &lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1269/5&quot;&gt;How would you explain Density Functional Theory to a high school student?&lt;/a&gt;&lt;/strong&gt; Another useful thread is: &lt;strong&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/123/5&quot;&gt;Are there any online course/video lectures available on Density functional theory?&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;We have indeed had high school students get help here for projects that involved Python coding of DFT/Hartree-Fock calculations, for example one student asked this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9595/5&quot;&gt;Hartree Fock Algorithm too high values for Molecules&lt;/a&gt; and this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9518/5&quot;&gt;What is the best algorithm for ERIs of contracted gaussian atomic orbitals&lt;/a&gt;, and eventually &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/62100788#62100788&quot;&gt;succeeded in finishing that project&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You also said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I am also looking for ways to find more granular guidance with the above.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;For guidance, it would work better in a chat room such as our &lt;a href=&quot;https://chat.stackexchange.com/rooms/112358/python-based-matter-modeling-software&quot;&gt;Python room&lt;/a&gt; (the same room in which the discussion with the above-mentioned high school student took place, which lead to their successful completion of their DFT/Hartree-Fock project in Python). Please feel free to ping anyone you see there by typing @ followed by their name. For example if you would like to ping me, just type @NikeDattani following by a greeting like &amp;quot;hello&amp;quot;, and I'll come and try to give you some guidance!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="201" LastEditDate="2023-02-14T05:19:50.143" LastActivityDate="2023-02-14T05:19:50.143" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10414" PostTypeId="1" AcceptedAnswerId="10418" CreationDate="2023-02-14T04:39:02.513" Score="8" ViewCount="414" Body="&lt;p&gt;I'm trying to model the silica-water interface using classical molecular dynamics. Hope to use LAMMPS for the simulations and CHARMM potential to model the atomic interactions. I wonder how to generate the initial atomic structure of the system. The &amp;quot;nanomaterial modeler&amp;quot; module in CHARMM-GUI comes in handy creating the atomic structure. But I do not have complete control over my structure if I use it. I need to attach the hydroxyl groups to the dangling silicon atoms in the interface as well. Therefore, it feels a bit complicated when defining the bonds and angles in the system using Matlab or python. As I'm using CHARMM potential, the relevant potential parameters need to be specified as well in the atomic data file. Any advice would be highly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;This is the system I could generate from CHARMM-GUI,&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7wzJB.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7wzJB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;Thanks&lt;/p&gt;&#xA;" OwnerUserId="6279" LastActivityDate="2023-02-14T20:23:48.863" Title="Silica (α-cristobalite) water system generation" Tags="|molecular-dynamics|molecular-modeling|lammps|molecular-interactions|charmm|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10415" PostTypeId="1" CreationDate="2023-02-14T14:56:42.917" Score="3" ViewCount="120" Body="&lt;p&gt;I'm a beginner in DFT and I want to study the properties of NiO and doped-NiO materials using Quantum ESPRESSO.I found in the internet that I should introduce the spin magnetization in the Input file (or CIF file)  because NiO is an antiferromagnetic material. The CIF file of conventional NiO (extracted from Materials Project website) is presented bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# generated using pymatgen&#xA;data_NiO&#xA;_symmetry_space_group_name_H-M   'P 1'&#xA;_cell_length_a   4.21661958&#xA;_cell_length_b   4.21661958&#xA;_cell_length_c   4.21661958&#xA;_cell_angle_alpha   90.00000000&#xA;_cell_angle_beta   90.00000000&#xA;_cell_angle_gamma   90.00000000&#xA;_symmetry_Int_Tables_number   1&#xA;_chemical_formula_structural   NiO&#xA;_chemical_formula_sum   'Ni4 O4'&#xA;_cell_volume   74.97099306&#xA;_cell_formula_units_Z   4&#xA;loop_&#xA; _symmetry_equiv_pos_site_id&#xA; _symmetry_equiv_pos_as_xyz&#xA;  1  'x, y, z'&#xA;loop_&#xA; _atom_site_type_symbol&#xA; _atom_site_label&#xA; _atom_site_symmetry_multiplicity&#xA; _atom_site_fract_x&#xA; _atom_site_fract_y&#xA; _atom_site_fract_z&#xA; _atom_site_occupancy&#xA;  Ni  Ni0  1  0.00000000  0.00000000  0.00000000  1&#xA;  Ni  Ni1  1  0.00000000  0.50000000  0.50000000  1&#xA;  Ni  Ni2  1  0.50000000  0.00000000  0.50000000  1&#xA;  Ni  Ni3  1  0.50000000  0.50000000  0.00000000  1&#xA;  O  O4  1  0.50000000  0.00000000  0.00000000  1&#xA;  O  O5  1  0.50000000  0.50000000  0.50000000  1&#xA;  O  O6  1  0.00000000  0.00000000  0.50000000  1&#xA;  O  O7  1  0.00000000  0.50000000  0.00000000  1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried to model antiferromagnetic  NiO by adopting two Ni-atom positions at  Ni0  (0.00000000  0.00000000  0.00000000) and Ni1  (0.00000000  0.50000000  0.50000000) for the spin up and two Ni-atom positions at Ni2 (0.50000000  0.00000000  0.50000000)&#xA;and Ni3 (0.50000000  0.50000000  0.00000000) for spin down [like in the CIF file above] then I wanted to pass the file through FINDSYM website. However I found in some papers a more complicated model like the one in the picture below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HXGLO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HXGLO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is the model in the picture the one that I should use, and how to include that in my input (or CIF) file?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-02-14T18:58:41.450" LastActivityDate="2023-02-15T01:19:49.517" Title="How to Model Antiferromagnetic NiO p-type semiconductor?" Tags="|density-functional-theory|quantum-espresso|molecular-modeling|physical-properties-of-materials|materials-design|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10416" PostTypeId="1" CreationDate="2023-02-14T15:54:20.790" Score="5" ViewCount="38" Body="&lt;p&gt;I ran a series of replica exchange molecular dynmaics for the different temperatures. I used WHAM to sample metastable states. From the results of WHAM, we can get probabilties (&lt;span class=&quot;math-container&quot;&gt;$p&#xA;$&lt;/span&gt;) from the energy distributions of the states, allowing to get free energy by &lt;span class=&quot;math-container&quot;&gt;$F=−\ln p$&lt;/span&gt;. But I want to have temperatures for the metastable states. Is there any fancy way to get temperatures? Any suggestions and questions about the problem are welcome.&lt;/p&gt;&#xA;" OwnerUserId="6716" LastActivityDate="2023-02-14T15:54:20.790" Title="How to get statistical temperature from WHAM?" Tags="|molecular-dynamics|statistical-thermodynamics|free-energy|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:08:55.210" ContentLicense="CC BY-SA 4.0" />
  <row Id="10417" PostTypeId="2" ParentId="10414" CreationDate="2023-02-14T16:09:34.083" Score="8" Body="&lt;p&gt;&lt;strong&gt;Proper Way&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you have access to CHARMM program, you can try writing a patch to passivate the dangling silicon atoms with OH groups. But if you decide to go this way, please be advised that you must have the corresponding bonds, angles, dihedral angle and charge parameters defined in a parameter file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Easy Way&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Instead you can try adding those hydrogens manually via some scripting language, and reopening the file in VMD and running the code to determine the bonds, angles and dihedrals again. This would give you a new .pdb file with the structure that you need.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-02-14T16:09:34.083" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10418" PostTypeId="2" ParentId="10414" CreationDate="2023-02-14T20:18:34.553" Score="5" Body="&lt;p&gt;As you note, any structure with dangling silicon atoms cannot be considered correct. I'm surprised CHARMM-GUI would produce a structure with undercoordinated (&amp;lt;4 bonds) silicon. I can't really tell what surface structure you have in the image, but here are some general warnings. You should be careful that your structure is consistent with the force field parameterization of the material. You can't expect parameters developed for elemental silicon to behave well for silicon dioxide or vice versa. You need to make sure that your silanol oxygen and hydrogen atoms are given the correct types and charges. Also, parameters for solid materials are often not well tested and may not be good for your purposes. Many of them, even those published in good venues can be very unbalanced. Also, the atomic structure of the surface may be more complex than you expect (metals often have thin oxide layers, for example).&lt;/p&gt;&#xA;&lt;p&gt;As suggested by @HemanthHaridas, you can write a script to generate psf and pdb files for your structures without having to define a CHARMM topology. Here is a VMD Tcl script that I wrote to add hydrogen to polycyclic aromatics. It could be altered for your purposes. You need a starting psf and pdb file. You give it a VMD selection (selText) of the atoms you want to add hydrogens to. It will generate a new pdb file with the original atoms of the system, plus the new hydrogen atoms. It then uses the VMD topotools plugin to generate bonds between the hydrogens and the atoms they are attached to. The angles and dihedrals in the psf file are regenerated using the VMD psfgen plugin.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# VMD Tcl script for adding hydrogen to dangling carbon atoms in polyaromatics&#xA;# Author: WaterMolecule&#xA;# Input parameters&#xA;set psf cut_graph_hexagon.psf&#xA;set pdb cut_graph_hexagon.pdb&#xA;set selText &amp;quot;numbonds!=3&amp;quot;&#xA;set type HGR61&#xA;set charge 0.115&#xA;set hydSegName H1&#xA;set lx 30.05&#xA;set ly 30.35&#xA;set lz 24.93&#xA;set outName H_graph_hexagon1&#xA;&#xA;# Other parameters&#xA;set cutoff 2.0&#xA;set hDist 1.1&#xA;&#xA;package require topotools&#xA;package require psfgen&#xA;&#xA;# Create a PDB ATOM line.&#xA;proc makePdbLine {serial segName resId name resName r beta} {&#xA;    set template &amp;quot;ATOM     42  HN  ASN X   4     -41.083  17.391  50.684  0.00  0.00      P1    &amp;quot;&#xA;&#xA;    foreach {x y z} &lt;span class=&quot;math-container&quot;&gt;$r {break}&#xA;    set record &quot;ATOM  &quot;&#xA;    set si [string range [format &quot;     %5i &quot; $&lt;/span&gt;serial] end-5 end]&#xA;    if {[string length &lt;span class=&quot;math-container&quot;&gt;$name] &amp;lt; 4} {&#xA;    set name [string range &quot; $name    &quot; 0 3]&#xA;    } else {&#xA;    set name [string range $name 0 3]&#xA;    }&#xA;    set resName [string range &quot; $&lt;/span&gt;resName     &amp;quot; 0 4]&#xA;    set chain &amp;quot;[string index &lt;span class=&quot;math-container&quot;&gt;$segName 0]&quot;&#xA;    set resId [string range &quot;    $&lt;/span&gt;resId&amp;quot;  end-3 end]&#xA;    set temp1 [string range &lt;span class=&quot;math-container&quot;&gt;$template  26 29]&#xA;    set sx [string range [format &quot;       %8.3f&quot; $&lt;/span&gt;x] end-7 end]&#xA;    set sy [string range [format &amp;quot;       %8.3f&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$y] end-7 end]&#xA;    set sz [string range [format &quot;       %8.3f&quot; $&lt;/span&gt;z] end-7 end]&#xA;    set temp2 [string range &lt;span class=&quot;math-container&quot;&gt;$template 54 59]&#xA;    set beta [string range [format &quot;       %6.2f&quot; $&lt;/span&gt;beta] end-5 end]&#xA;    set temp3 [string range &lt;span class=&quot;math-container&quot;&gt;$template 66 71]&#xA;    set segName [string range &quot;$&lt;/span&gt;segName    &amp;quot;  0 3]&#xA;    set tempEnd [string range $template 76 end]&#xA;&#xA;    # Construct the pdb line.&#xA;    return &amp;quot;&lt;span class=&quot;math-container&quot;&gt;${record}$&lt;/span&gt;{si}&lt;span class=&quot;math-container&quot;&gt;${name}$&lt;/span&gt;{resName}&lt;span class=&quot;math-container&quot;&gt;${chain}$&lt;/span&gt;{resId}&lt;span class=&quot;math-container&quot;&gt;${temp1}$&lt;/span&gt;{sx}&lt;span class=&quot;math-container&quot;&gt;${sy}$&lt;/span&gt;{sz}&lt;span class=&quot;math-container&quot;&gt;${temp2}$&lt;/span&gt;{beta}&lt;span class=&quot;math-container&quot;&gt;${temp3}$&lt;/span&gt;{segName}${tempEnd}&amp;quot;&#xA;}&#xA;&#xA;# Convert a vector to a unit vector.&#xA;proc vecUnit {v} {&#xA;    set len [veclength &lt;span class=&quot;math-container&quot;&gt;$v]&#xA;    return [vecscale [expr {1.0/$len}] $&lt;/span&gt;v]&#xA;}&#xA;&#xA;# Wrap a difference in coordinates for a periodic length &amp;quot;l&amp;quot;.&#xA;# The result is -0.5*l &amp;lt;= x &amp;lt; 0.5*l&#xA;proc wrapDiffReal {x l} {&#xA;    set l [expr {double(&lt;span class=&quot;math-container&quot;&gt;$l)}]&#xA;    set image [expr {int(floor($x/$l))}]&#xA;    set x [expr {$x - $image*$&lt;/span&gt;l}]&#xA;&#xA;    if {&lt;span class=&quot;math-container&quot;&gt;$x &amp;gt;= 0.5*$&lt;/span&gt;l} { set x [expr {&lt;span class=&quot;math-container&quot;&gt;$x - $&lt;/span&gt;l}] }&#xA;    return $x&#xA;}&#xA;&#xA;# Wrap a displacement for an orthogonal cell.&#xA;proc wrapDiffOrtho {r a b c} {&#xA;    foreach {x y z} $r { break }&#xA;    &#xA;    set x [wrapDiffReal &lt;span class=&quot;math-container&quot;&gt;$x $&lt;/span&gt;a]&#xA;    set y [wrapDiffReal &lt;span class=&quot;math-container&quot;&gt;$y $&lt;/span&gt;b]&#xA;    set z [wrapDiffReal &lt;span class=&quot;math-container&quot;&gt;$z $&lt;/span&gt;c]&#xA;    return [list &lt;span class=&quot;math-container&quot;&gt;$x $&lt;/span&gt;y $z]&#xA;}&#xA;&#xA;# Load the system.&#xA;mol new &lt;span class=&quot;math-container&quot;&gt;$psf&#xA;mol addfile $&lt;/span&gt;pdb waitfor all&#xA;molinfo top set a &lt;span class=&quot;math-container&quot;&gt;$lx&#xA;molinfo top set b $&lt;/span&gt;ly&#xA;molinfo top set c &lt;span class=&quot;math-container&quot;&gt;$lz&#xA;puts &quot;CELL: $&lt;/span&gt;lx &lt;span class=&quot;math-container&quot;&gt;$ly $&lt;/span&gt;lz&amp;quot;&#xA;set all [atomselect top all]&#xA;&#xA;foreach silent {0} {&#xA;    set bondList [topo getbondlist]&#xA;    set chargeList [&lt;span class=&quot;math-container&quot;&gt;$all get charge]&#xA;    set typeList [$&lt;/span&gt;all get type]&#xA;}&#xA;&#xA;# Write the pdb.&#xA;set out [open $outName.tmp.pdb w]&#xA;&#xA;# Write the existing atoms.&#xA;set j 0&#xA;set numOrig [&lt;span class=&quot;math-container&quot;&gt;$all num]&#xA;puts &quot;Original number of atoms: $&lt;/span&gt;numOrig&amp;quot;&#xA;foreach segName [&lt;span class=&quot;math-container&quot;&gt;$all get segname] resId [$&lt;/span&gt;all get resid] name [&lt;span class=&quot;math-container&quot;&gt;$all get name] resName [$&lt;/span&gt;all get resname] r [&lt;span class=&quot;math-container&quot;&gt;$all get {x y z}] {&#xA;    incr j&#xA;    puts $out [makePdbLine $j $segName $resId $name $resName $&lt;/span&gt;r 1.0]    &#xA;}&#xA;&#xA;# Add the hydrogens and write them.&#xA;set resId 1&#xA;set name H&#xA;set resName ADDH&#xA;set sel [atomselect top &lt;span class=&quot;math-container&quot;&gt;$selText]&#xA;puts &quot;Adding [$&lt;/span&gt;sel num] hydrogen atoms.&amp;quot;&#xA;set hydBondList {}&#xA;foreach index [&lt;span class=&quot;math-container&quot;&gt;$sel get index] pos [$&lt;/span&gt;sel get {x y z}] {&#xA;    &#xA;    set sum [veczero]&#xA;    set s [atomselect top &amp;quot;not index &lt;span class=&quot;math-container&quot;&gt;$index and pbwithin $&lt;/span&gt;cutoff of index &lt;span class=&quot;math-container&quot;&gt;$index&quot;]&#xA;    foreach p [$&lt;/span&gt;s get {x y z}] {&#xA;    set d [wrapDiffOrtho [vecsub &lt;span class=&quot;math-container&quot;&gt;$p $&lt;/span&gt;pos] &lt;span class=&quot;math-container&quot;&gt;$lx $&lt;/span&gt;ly &lt;span class=&quot;math-container&quot;&gt;$lz]&#xA;    set sum [vecadd $&lt;/span&gt;sum &lt;span class=&quot;math-container&quot;&gt;$d]&#xA;    }&#xA;    set hVec [vecscale $&lt;/span&gt;hDist [vecUnit [vecinvert &lt;span class=&quot;math-container&quot;&gt;$sum]]]&#xA;    $&lt;/span&gt;s delete&#xA;    set r [vecadd &lt;span class=&quot;math-container&quot;&gt;$pos $&lt;/span&gt;hVec]&#xA;&#xA;    incr resId&#xA;    incr j&#xA;    puts &lt;span class=&quot;math-container&quot;&gt;$out [makePdbLine $&lt;/span&gt;j &lt;span class=&quot;math-container&quot;&gt;$hydSegName $&lt;/span&gt;resId &lt;span class=&quot;math-container&quot;&gt;$name $&lt;/span&gt;resName $r 0.0]&#xA;&#xA;    lappend hydBondList [list [expr {&lt;span class=&quot;math-container&quot;&gt;$j-1}] $&lt;/span&gt;index]&#xA;}&#xA;close $out&#xA;&#xA;# Load the pdb we just created.&#xA;mol delete top&#xA;mol new &lt;span class=&quot;math-container&quot;&gt;$outName.tmp.pdb&#xA;set all1 [atomselect top all]&#xA;puts &quot;New structure has [$&lt;/span&gt;all1 num] atoms.&amp;quot;&#xA;&#xA;# Delete all bonds.&#xA;foreach bond [topo getbondlist] {&#xA;    topo delbond [lindex &lt;span class=&quot;math-container&quot;&gt;$bond 0] [lindex $&lt;/span&gt;bond 1]&#xA;}&#xA;&#xA;# Add the original bonds back in.&#xA;foreach bond &lt;span class=&quot;math-container&quot;&gt;$bondList {&#xA;    set i0 [lindex $bond 0]&#xA;    set i1 [lindex $bond 1]&#xA;    topo addbond $i0 $i1&#xA;}&#xA;# Add the bonds to the hydrogen atoms.&#xA;foreach bond $&lt;/span&gt;hydBondList {&#xA;    set i0 [lindex &lt;span class=&quot;math-container&quot;&gt;$bond 0]&#xA;    set i1 [lindex $&lt;/span&gt;bond 1]&#xA;    topo addbond &lt;span class=&quot;math-container&quot;&gt;$i0 $&lt;/span&gt;i1&#xA;}&#xA;&#xA;&#xA;# Set the original types and charges.&#xA;set s1 [atomselect top &amp;quot;index &amp;lt; &lt;span class=&quot;math-container&quot;&gt;$numOrig&quot;]&#xA;$&lt;/span&gt;s1 set type &lt;span class=&quot;math-container&quot;&gt;$typeList&#xA;$&lt;/span&gt;s1 set charge &lt;span class=&quot;math-container&quot;&gt;$chargeList&#xA;$&lt;/span&gt;s1 delete&#xA;&#xA;# Modify the types and charges of the hydrogen atoms and the charge of the attached atom.&#xA;foreach bond &lt;span class=&quot;math-container&quot;&gt;$hydBondList {&#xA;    set s [atomselect top &quot;index [lindex $bond 0]&quot;]&#xA;    $s set type $type&#xA;    $s set charge $charge&#xA;    $&lt;/span&gt;s delete&#xA;&#xA;    set s [atomselect top &amp;quot;index [lindex &lt;span class=&quot;math-container&quot;&gt;$bond 1]&quot;]&#xA;    $&lt;/span&gt;s set charge [expr {-&lt;span class=&quot;math-container&quot;&gt;$charge}]&#xA;    $&lt;/span&gt;s delete&#xA;}&#xA;&#xA;# Write psf with bonds and charges.&#xA;&lt;span class=&quot;math-container&quot;&gt;$all1 writepsf $&lt;/span&gt;outName.tmp.psf&#xA;&#xA;# Regenerate angles and dihedrals.&#xA;resetpsf&#xA;readpsf &lt;span class=&quot;math-container&quot;&gt;$outName.tmp.psf&#xA;coordpdb $&lt;/span&gt;outName.tmp.pdb&#xA;regenerate angles dihedrals&#xA;&#xA;# Write the final structure.&#xA;writepsf &lt;span class=&quot;math-container&quot;&gt;$outName.psf&#xA;writepdb $&lt;/span&gt;outName.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2023-02-14T20:23:48.863" LastActivityDate="2023-02-14T20:23:48.863" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10419" PostTypeId="2" ParentId="10349" CreationDate="2023-02-14T21:35:23.540" Score="3" Body="&lt;p&gt;Thanks for all these troubleshooting. As you noticed, &lt;code&gt;ao2mo.kernel&lt;/code&gt;&#xA;does not give &amp;quot;an FCIDUMP file in HDF5 format&amp;quot;, but only provides 2-electron integrals in MO basis. Similarly &lt;code&gt;ao2mo.load&lt;/code&gt; only loads 2-e integrals. You will need more information, such as 1-e integrals, to re-create a &lt;code&gt;mf&lt;/code&gt; object.&lt;/p&gt;&#xA;&lt;p&gt;If the FCIDUMP file in HDF5 format, instead of ASCII, is desired, basically you can change the relevant functions in &lt;code&gt;tools/fcidump.py&lt;/code&gt; to enable it. PySCF currently doesn't have a HDF5 counterpart for the FCIDUMP read/write functions. One reason is that there are no well-adopted standards to store the information in HDF5. Some programs may have their internal format, but this limits the transferability between programs. The text-based FCIDUMP format, on the other hand, has been adopted in the community for many years.&lt;/p&gt;&#xA;&lt;p&gt;As a temporary solution, I wrote a script to allow write and read HDF5 in a similar fashion to how you treat FCIDUMP. Please feel free to use/modify/optimize. Eventually, such codes can be merged into PySCF.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import h5py, numpy&#xA;import pyscf&#xA;from pyscf import gto, scf, ao2mo, cc, tools&#xA;from pyscf.tools.fcidump import TOL, DEFAULT_FLOAT_FORMAT, MOLPRO_ORBSYM&#xA;&#xA;#####################&#xA;## Redefine functions to enable HDF5 format (these functions mirror those in pyscf/tools/fcidump.py)&#xA;#####################&#xA;&#xA;# Write some basic information to HDF5&#xA;def write_head(fout, nmo, nelec, ms=0, orbsym=None):&#xA;    if not isinstance(nelec, (int, numpy.number)):&#xA;        ms = abs(nelec[0] - nelec[1])&#xA;        nelec = nelec[0] + nelec[1]&#xA;    fout['norb'] = nmo&#xA;    fout['nelec'] = nelec&#xA;    fout['ms2'] = ms&#xA;    if orbsym is not None and len(orbsym) &amp;gt; 0:&#xA;        fout['orbsym'] = numpy.asarray(orbsym) &#xA;    else:&#xA;        fout['orbsym'] = numpy.full(1, nmo) &#xA;    fout['isym'] = 1&#xA;&#xA;# Write 2-e integrals to HDF5&#xA;def write_eri(fout, eri, nmo, tol=TOL, float_format=DEFAULT_FLOAT_FORMAT):&#xA;    if eri.size == nmo**4:&#xA;        eri = ao2mo.restore(8, eri, nmo)&#xA;    fout.create_dataset('h2', data=eri)&#xA;&#xA;# Write 1-e integrals to HDF5&#xA;def write_hcore(fout, h, nmo, tol=TOL, float_format=DEFAULT_FLOAT_FORMAT):&#xA;    h = h.reshape(nmo,nmo)&#xA;    fout.create_dataset('h1', data=h)&#xA;&#xA;# Convert the given 1-electron and 2-electron integrals to HDF5 format&#xA;def hdf5_from_integrals(filename, h1e, h2e, nmo, nelec, nuc=0, ms=0, orbsym=None,&#xA;                        tol=TOL, float_format=DEFAULT_FLOAT_FORMAT):&#xA;    with h5py.File(filename, 'w') as fout:&#xA;        write_head(fout, nmo, nelec, ms, orbsym)&#xA;        write_eri(fout, h2e, nmo, tol=tol, float_format=float_format)&#xA;        write_hcore(fout, h1e, nmo, tol=tol, float_format=float_format)&#xA;        fout['nuc'] = nuc&#xA;&#xA;# Use the Hamiltonians stored in HDF5 format to build an SCF object&#xA;def hdf5_to_scf(filename, molpro_orbsym=MOLPRO_ORBSYM, mf=None, **kwargs):&#xA;    with h5py.File(filename, 'r') as f:&#xA;        mol = gto.M()&#xA;        mol.nelectron = int(f['nelec'][()])&#xA;        mol.spin = int(f['ms2'][()])&#xA;        norb = mol.nao = int(f['norb'][()])&#xA;        nuc = f['nuc'][()]&#xA;        mol.energy_nuc = lambda *args: nuc &#xA;        mol.incore_anyway = True&#xA;        if 'orbsym' in f.keys():&#xA;            mol.symmetry = True&#xA;            mol.groupname = 'N/A'&#xA;            orbsym = f['orbsym'][()]&#xA;            mol.irrep_id = list(set(orbsym))&#xA;            mol.irrep_name = [('IR%d' % ir) for ir in mol.irrep_id]&#xA;            so = numpy.eye(norb)&#xA;            mol.symm_orb = []&#xA;            for ir in mol.irrep_id:&#xA;                mol.symm_orb.append(so[:,orbsym==ir])&#xA;&#xA;        if mf is None:&#xA;            mf = mol.RHF(**kwargs)&#xA;        else:&#xA;            mf.mol = mol&#xA;        h1 = f['h1'][()]&#xA;        mf.get_hcore = lambda *args: h1&#xA;        mf.get_ovlp = lambda *args: numpy.eye(norb)&#xA;        &#xA;        norb_pair = norb * (norb+1) // 2&#xA;        h2e = f['h2'][()]&#xA;        mf._eri = h2e[numpy.tril_indices(norb_pair)]&#xA;&#xA;    return mf&#xA;&#xA;&#xA;#####################&#xA;## Input starts here&#xA;#####################&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = ''' O&#xA;               H  1  0.9576257&#xA;               H  1  0.9576257  2 104.51 '''&#xA;mol.unit = 'angstrom'&#xA;mol.basis = 'CC-PVTZ'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.verbose = 9&#xA;mol.symmetry = True&#xA;mol.symmetry_subgroup = 'C2v'&#xA;name = 'out'&#xA;mol.build()&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;&#xA;mf = mol.RHF().set(chkfile = name + '.chk')&#xA;mf.kernel()&#xA;&#xA;# Replace two functions in tools/fcidump.py if you want to store information as HDF5&#xA;store_as_h5 = True&#xA;if store_as_h5: &#xA;    from pyscf.tools import fcidump&#xA;    fcidump.from_integrals = hdf5_from_integrals&#xA;    fcidump.to_scf = hdf5_to_scf&#xA;    ext = 'h5'&#xA;else:&#xA;    ext = 'fcidump'&#xA;&#xA;tools.fcidump.from_chkfile(f'{name}.{ext}',name+'.chk', tol=1e-18, float_format=' %.16g', molpro_orbsym=False, orbsym=None)&#xA;mf = tools.fcidump.to_scf(f'{name}.{ext}', molpro_orbsym=False, mf=None)&#xA;mf.kernel()&#xA;&#xA;#####################&#xA;## post-Hartree-Fock:&#xA;#####################&#xA;&#xA;mcc = cc.CCSD(mf).set(frozen=1,verbose=9)&#xA;e = mcc.kernel()&#xA;et = mcc.ccsd_t()  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6599" LastActivityDate="2023-02-14T21:35:23.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10420" PostTypeId="2" ParentId="10415" CreationDate="2023-02-15T00:13:30.273" Score="3" Body="&lt;p&gt;The model in the picture is alright as far as it goes, but it is &lt;em&gt;not&lt;/em&gt; a magnetic unit cell, it is only a structural unit cell. If the cubic frame were a unit cell, the atoms at each corner would be identical by translational symmetry; however, in this picture half of the corner atoms are &amp;quot;spin up&amp;quot; and half &amp;quot;spin down&amp;quot;, so they are not simple translations of each other (e.g. look at the two atoms coupled by &amp;quot;J2&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;The smallest magnetic unit cell for NiO is (I think) the one oriented along the (111) direction, i.e. along the diagonal of the cube. Along this direction, the spins on the Ni alternate between up and down.&lt;/p&gt;&#xA;&lt;p&gt;You should also be aware that the self-interaction error of Ni &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-electrons is quite large with common local or semi-local exchange-correlation functionals. I'm not aware of any LDAs which would give an AFM insulating state, they usually converge to a non-magnetic metallic state. Some GGAs also have this problem, although PBE does predict the antiferromagnetic insulating state, but the band-gap is rather small and the state is quite fragile.&lt;/p&gt;&#xA;&lt;p&gt;The usual approach to modelling NiO, and other systems where self-interaction is a problem, is to add a small Hubbard U term to the Hamiltonian (&amp;quot;DFT+U&amp;quot;) which partially counteracts the effects of self-interaction. Alternatively, the RSCAN family of meta-GGAs do fairly well, and screened non-local exchange methods can also give good results.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2023-02-15T01:19:49.517" LastActivityDate="2023-02-15T01:19:49.517" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10421" PostTypeId="2" ParentId="10408" CreationDate="2023-02-15T07:20:35.987" Score="1" Body="&lt;p&gt;We used to use VASP in our University for pedagogical reasons, but if you want to write your own DFT code from scratch, well that has cost some of us a few years of College. It is tedious and long.&lt;/p&gt;&#xA;&lt;p&gt;IF you want to get into the topic (since you mention you are a high school student yourself) i would suggest to start with a self-study course in actual Linear Algebra + Numeric Linear algebra and Matrix factorization. A good example book would be the one titled the same from author Tom Lyche (it is what i used to use in Uni). Then move to Solid Matter theory later.&lt;/p&gt;&#xA;&lt;p&gt;You can alternatively use dftFit which is a Python Module:&#xA;&lt;a href=&quot;https://pypi.org/project/dftfit/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pypi.org/project/dftfit/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6719" LastActivityDate="2023-02-15T07:20:35.987" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10422" PostTypeId="1" CreationDate="2023-02-15T09:35:05.670" Score="4" ViewCount="106" Body="&lt;p&gt;I want to do a GGA+U calculation on the LaAlO3/SrTiO3 heterostructure to study the 2DEG formed at the interface. In all the references I came across they used U around 4eV-6eV on Ti 3d orbitals, I'm okay with this. However, they also use a high U value of 9eV-11eV on La 4f orbitals, &amp;quot;to avoid spurious mixing with Ti d bands&amp;quot;. I don't understand why is this important and why add U on f electrons which are not even valence electrons for La.&lt;/p&gt;&#xA;" OwnerUserId="6720" LastActivityDate="2023-02-15T09:35:05.670" Title="Hubbard U value on LaAlO3/SrTiO3 interface" Tags="|density-functional-theory|dft-u|electron-correlation|heterostructures|metal-oxide|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:09:24.197" ContentLicense="CC BY-SA 4.0" />
  <row Id="10423" PostTypeId="1" AcceptedAnswerId="10501" CreationDate="2023-02-15T17:18:07.207" Score="4" ViewCount="206" Body="&lt;p&gt;Cross-posted later &lt;a href=&quot;https://www.reddit.com/r/comp_chem/comments/116ftga/contribution_to_pressure_tensor_from_water/&quot; rel=&quot;nofollow noreferrer&quot;&gt;on Reddit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have an infinite CG model of the material solvated in water. I am trying to apply a uniaxial deformation along a particular x-axis; the mdp settings in GROMACS are below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tcoupl                   = v-rescale&#xA;tc-grps                  = SOLID W_ION&#xA;tau_t                    = 1.0 1.0&#xA;ref_t                    = 298 298&#xA;Pcoupl                   = parrinello-rahman&#xA;Pcoupltype               = anisotropic&#xA;tau_p                    = 12.0  &#xA;compressibility          = 0.0 3e-4 3e-4 0.0 0.0 0.0&#xA;ref_p                    = 0.0 1.0 1.0 0.0 0.0 0.0&#xA;deform                   = 0.002 0 0 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Stress is computed as negative of the pressure tensor &lt;span class=&quot;math-container&quot;&gt;$-P_{xx}$&lt;/span&gt;. &lt;em&gt;&lt;strong&gt;I wonder if water will affect my results&lt;/strong&gt;&lt;/em&gt;, as I believe the pressure is computed for the whole system. Previously, I used to pull one end of the model, keeping the other side fixed. Here, I am just pulling the box. &lt;em&gt;&lt;strong&gt;Would water affect my results?&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;The methodology for measuring the Young modulus was taken from this work: Modi V, Karttunen AJ. Molecular Dynamics Simulations on the Elastic Properties of Polypropylene Bionanocomposite Reinforced with Cellulose Nanofibrils. Nanomaterials. 2022; 12(19):3379.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="5" LastEditDate="2023-02-21T03:34:23.430" LastActivityDate="2023-07-28T18:04:15.567" Title="Contribution to pressure tensor from water" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10424" PostTypeId="1" CreationDate="2023-02-15T12:30:36.237" Score="4" ViewCount="48" Body="&lt;p&gt;I am studying the dependence of the rate of a specific process in a dimer from the relative positioning of molecules in the dimer. Currently, I am using 2000 descriptors from the padelpy for model training. In addition, I am using 8 different distances between atoms of the molecules in the dimer as descriptors. However, I have noticed that my ML model gives poor predictions, and I suspect that it may be due to insufficient information about the positioning of molecules in the dimer used for training.&lt;/p&gt;&#xA;&lt;p&gt;What descriptors can be used to describe the relative positioning of molecules in a dimer with respect to each other?&lt;/p&gt;&#xA;" OwnerDisplayName="Cyberturist" LastEditorUserId="5" LastEditDate="2023-02-16T03:22:35.013" LastActivityDate="2023-02-16T03:22:35.013" Title="Specific descriptors for dimers" Tags="|machine-learning|cheminformatics|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:09:39.130" ContentLicense="CC BY-SA 4.0" />
  <row Id="10425" PostTypeId="1" CreationDate="2023-02-16T12:00:07.890" Score="5" ViewCount="125" Body="&lt;p&gt;I want to study the properties of NiO as a hole transporting material adapted for perovskite solar cells using Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;From Materials Project website, I saw that NiO can exist in different crystal structures. I intended to choose the most stable structure, but from literature I see that researchers also work with other metastable crystal structures of a material.&lt;/p&gt;&#xA;&lt;p&gt;Knowing that any material can have more than 2 metastable structures, can someone explain to me why do I have to choose a structure and not another?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6468" LastEditDate="2023-02-16T14:35:50.350" LastActivityDate="2023-02-16T14:35:50.350" Title="Which crystal structure I have to choose for DFT calculations?" Tags="|density-functional-theory|quantum-espresso|crystallography|symmetry|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:09:47.743" ContentLicense="CC BY-SA 4.0" />
  <row Id="10426" PostTypeId="1" AcceptedAnswerId="10576" CreationDate="2023-02-16T17:35:47.727" Score="5" ViewCount="540" Body="&lt;p&gt;After the definition of the fragments in the geometry section of the calculation, is there a method to call, or a keyword to turn on, in order to obtain the energy of the fragments themselves?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! def2-svp b3lyp cpcm(water)&#xA;&#xA;*xyz 0 1 &#xA;O (1) 0 0 0&#xA;H (1) 0 1 0&#xA;H (2) 0 1 1&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4895" LastEditorUserId="5" LastEditDate="2023-02-16T17:52:21.590" LastActivityDate="2023-03-15T09:19:08.700" Title="Energy of each fragment in ORCA?" Tags="|computational-chemistry|quantum-chemistry|molecular-modeling|ab-initio-calculations|orca|" AnswerCount="3" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10427" PostTypeId="2" ParentId="10426" CreationDate="2023-02-16T20:44:15.210" Score="4" Body="&lt;p&gt;With ORCA, I don't know but...&lt;/p&gt;&#xA;&lt;p&gt;You can use the &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GAMESS&lt;/a&gt; software.&lt;/p&gt;&#xA;&lt;p&gt;From the manual:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The code for the Fragment Molecular Orbital (FMO) method has been a&#xA;part of the standard GAMESS package since  May 2004. The FMO method is&#xA;the successor of the EDA scheme developed by K. Kitaura and K.&#xA;Morokuma (known in GAMESS as Morokuma-Kitaura decomposition), however,&#xA;the FMO code was written independently.  In GAMESS only the full FMO&#xA;method is incorporated whereas in the literature one can also find a&#xA;simplified approach suited for molecular crystals.  Since &amp;quot;FMO&amp;quot; is&#xA;also used to mean &amp;quot;Frontier Molecular Orbitals&amp;quot; and the concept of&#xA;fragments is also introduced in the EFP method (see above), it is&#xA;stressed here that the FMO method bears no relation to either of the&#xA;two methods, that is to say, it is independent of the two, but might&#xA;be combined with either of them in the future just as EFPs are used in&#xA;e.g. RHF.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fragment_molecular_orbital&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fragment Molecular Orbital&lt;/a&gt; (FMO), your system can be divided in fragments (automatically or manually). As FMO is deeply interconnected with the energy decomposition analysis (EDA) the method will return the energy of each fragment.&lt;/p&gt;&#xA;&lt;p&gt;Within GAMESS, you can use different level of theory like  Hartree–Fock, Density functional theory (DFT), Multi-configurational self-consistent field (MCSCF), time-dependent DFT (TDDFT), configuration interaction (CI), second order Møller–Plesset perturbation theory (MP2), and coupled cluster (CC).&lt;/p&gt;&#xA;&lt;p&gt;Finally, to prepare the GAMESS input for FMO calculation, the software &lt;a href=&quot;http://zzzfelis.sakura.ne.jp/&quot; rel=&quot;nofollow noreferrer&quot;&gt;FACIO&lt;/a&gt;, &lt;a href=&quot;https://sourceforge.net/projects/fusuite/&quot; rel=&quot;nofollow noreferrer&quot;&gt;fu-suite&lt;/a&gt; and/or &lt;a href=&quot;https://github.com/FragIt/fragit-main&quot; rel=&quot;nofollow noreferrer&quot;&gt;FragIt&lt;/a&gt; can help.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-02-16T20:44:15.210" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10428" PostTypeId="1" CreationDate="2023-02-16T18:40:34.097" Score="5" ViewCount="311" Body="&lt;p&gt;I am trying to get the potential energy of a system at each frame of a molecular dynamics trajectory after running the simulation. My current approach is as follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Use MDAnalysis to iterate through the trajectory frames and write out the atom coordinates to separate topology files&lt;/li&gt;&#xA;&lt;li&gt;Iterate through each of the files and create a simulation using OpenMM and then use their getPotentialEnergy() method to extract the energy from the simulation state&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The issue is that when I test this using the same forcefield that was used for the simulation, I get potential energy values that differ on the order of 10% from the potential energy reported during the simulation. I have also noticed that the first topology file created by step one has atom coordinates that differ significantly from the input topology file, but I do not know why.&lt;/p&gt;&#xA;&lt;p&gt;What could the issues with my implementation be, or is there an alternate way to accomplish this accurately?&lt;/p&gt;&#xA;" OwnerDisplayName="mertvy" LastActivityDate="2023-02-17T01:41:46.070" Title="Is there an effective way to get the energy of a system from a MD trajectory in postprocessing?" Tags="|computational-chemistry|energy|molecular-dynamics|" AnswerCount="0" CommentCount="6" ClosedDate="2023-10-22T20:09:53.437" ContentLicense="CC BY-SA 4.0" />
  <row Id="10430" PostTypeId="1" CreationDate="2023-02-17T11:08:39.333" Score="3" ViewCount="88" Body="&lt;p&gt;I have run into trouble when I try to do transport calculations in TranSIESTA. I got this message in the output file, before reaching convergence:&#xA;&lt;strong&gt;&lt;code&gt;Error on inverting X6/C7 with error: 1&lt;/code&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;this is the input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;SolutionMethod        Transiesta&#xA;SystemName          scat&#xA;SystemLabel         scat&#xA;PAO.BasisSize    DZP&#xA;PAO.EnergyShift  0.005 Ry&#xA;XC.functional   VDW&#xA;XC.authors      KBM&#xA;&#xA;LatticeConstant             1.00 Ang&#xA;&#xA;%block LatticeVectors&#xA;      38.6768112183         0.0000000000         0.0000000000&#xA;       0.0000000000        18.6851730347         0.0000000000&#xA;       0.0000000000         0.0000000000        30.1042270660&#xA;%endblock LatticeVectors&#xA;&#xA;# ---------------------------------------------------------------------------&#xA;# Species and Atoms&#xA;# ---------------------------------------------------------------------------&#xA;&#xA;NumberOfSpecies        2&#xA;NumberOfAtoms         182&#xA;&#xA;%block ChemicalSpeciesLabel&#xA;  1   6    C&#xA;  2   1    H&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;# ---------------------------------------------------------------------------&#xA;# Atomic Coordinates&#xA;# ---------------------------------------------------------------------------&#xA;&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;10.074077    9.200517    1.487844   1&#xA;12.528448    9.200517    1.487844   1&#xA;14.982818    9.200517    1.487844   1&#xA;17.437189    9.200517    1.487844   1&#xA;19.891562    9.200517    1.487844   1&#xA; 8.846891    9.200517    3.613365   1&#xA;11.301263    9.200517    3.613365   1&#xA;13.755634    9.200517    3.613365   1&#xA;16.210005    9.200517    3.613365   1&#xA;18.664376    9.200517    3.613365   1&#xA;21.118749    9.200517    3.613365   1&#xA; 8.846878    9.200517    0.779387   1&#xA;11.301249    9.200517    0.779387   1&#xA;13.755620    9.200517    0.779387   1&#xA;16.209992    9.200517    0.779387   1&#xA;18.664364    9.200517    0.779387   1&#xA;21.118736    9.200517    0.779387   1&#xA;10.074065    9.200517    2.904908   1&#xA;12.528435    9.200517    2.904908   1&#xA;14.982807    9.200517    2.904908   1&#xA;17.437178    9.200517    2.904908   1&#xA;19.891548    9.200517    2.904908   1&#xA; 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7.879461    9.200519    5.585013   1&#xA; 7.879476    9.200522    7.408956   1&#xA;22.088700    9.200522    5.580086   1&#xA;22.088735    9.200524    7.413927   1&#xA; 10.074077   9.200517    10.089052  1&#xA;12.528448    9.200517   10.089052   1&#xA;14.982818    9.200517   10.089052   1&#xA;17.437189    9.200517   10.089052   1&#xA;19.891562    9.200517   10.089052   1&#xA; 8.846891    9.200517   12.214573   1&#xA;11.301263    9.200517   12.214573   1&#xA;13.755634    9.200517   12.214573   1&#xA;16.210005    9.200517   12.214573   1&#xA;18.664376    9.200517   12.214573   1&#xA;21.118749    9.200517   12.214573   1&#xA; 8.846878    9.200517    9.380595   1&#xA;11.301249    9.200517    9.380595   1&#xA;13.755620    9.200517    9.380595   1&#xA;16.209992    9.200517    9.380595   1&#xA;18.664364    9.200517    9.380595   1&#xA;21.118736    9.200517    9.380595   1&#xA;10.074065    9.200517   11.506116   1&#xA;12.528435    9.200517   11.506116   1&#xA;14.982807    9.200517   11.506116   1&#xA;17.437178    9.200517   11.506116   1&#xA;19.891548    9.200517   11.506116   1&#xA; 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7.879461    9.200519   18.486824   1&#xA; 7.879476    9.200522   20.310767   1&#xA;22.088700    9.200522   18.481898   1&#xA;22.088735    9.200524   20.315738   1&#xA; 0.074077    9.200517   22.990863   1&#xA;12.528448    9.200517   22.990863   1&#xA;14.982818    9.200517   22.990863   1&#xA;17.437189    9.200517   22.990863   1&#xA;19.891562    9.200517   22.990863   1&#xA; 8.846891    9.200517   25.116384   1&#xA;11.301263    9.200517   25.116384   1&#xA;13.755634    9.200517   25.116384   1&#xA;16.210005    9.200517   25.116384   1&#xA;18.664376    9.200517   25.116384   1&#xA;21.118749    9.200517   25.116384   1&#xA; 8.846878    9.200517   22.282406   1&#xA;11.301249    9.200517   22.282406   1&#xA;13.755620    9.200517   22.282406   1&#xA;16.209992    9.200517   22.282406   1&#xA;18.664364    9.200517   22.282406   1&#xA;21.118736    9.200517   22.282406   1&#xA;10.074065    9.200517   24.407927   1&#xA;12.528435    9.200517   24.407927   1&#xA;14.982807    9.200517   24.407927   1&#xA;17.437178    9.200517   24.407927   1&#xA;19.891548    9.200517   24.407927   1&#xA; 7.879461    9.200519   22.787428   1&#xA; 7.879476    9.200522   24.611371   1&#xA;22.088700    9.200522   22.782502   1&#xA;22.088735    9.200524   24.616342   1&#xA;10.074077    9.200517   27.291467   1&#xA;12.528448    9.200517   27.291467   1&#xA;14.982818    9.200517   27.291467   1&#xA;17.437189    9.200517   27.291467   1&#xA;19.891562    9.200517   27.291467   1&#xA; 8.846891    9.200517   29.416988   1&#xA;11.301263    9.200517   29.416988   1&#xA;13.755634    9.200517   29.416988   1&#xA;16.210005    9.200517   29.416988   1&#xA;18.664376    9.200517   29.416988   1&#xA;21.118749    9.200517   29.416988   1&#xA; 8.846878    9.200517   26.583010   1&#xA;11.301249    9.200517   26.583010   1&#xA;13.755620    9.200517   26.583010   1&#xA;16.209992    9.200517   26.583010   1&#xA;18.664364    9.200517   26.583010   1&#xA;21.118736    9.200517   26.583010   1&#xA;10.074065    9.200517   28.708531   1&#xA;12.528435    9.200517   28.708531   1&#xA;14.982807    9.200517   28.708531   1&#xA;17.437178    9.200517   28.708531   1&#xA;19.891548    9.200517   28.708531   1&#xA; 7.879461    9.200519   27.088032   1&#xA; 7.879476    9.200522   28.911975   1&#xA;22.088700    9.200522   27.083106   1&#xA;22.088735    9.200524   28.916946   1                &#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA; # K-points&#xA;%block kgrid_Monkhorst_Pack&#xA;  20    0    0   0.0&#xA;   0    1    0   0.0&#xA;   0    0   100   0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;DM.MixSCF1   T&#xA;MaxSCFIterations      300           # Maximum number of SCF iter&#xA;DM.MixingWeight       0.05          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.d-4         # Tolerance in maximum difference&#xA;DM.UseSaveDM          true          # to use continuation files&#xA;DM.NumberPulay        6&#xA;&#xA;==================================================&#xA;==================================================&#xA;# MD variables&#xA;&#xA;MD.FinalTimeStep 1&#xA;MD.TypeOfRun CG&#xA;MD.NumCGsteps     000&#xA;MD.UseSaveXV      .true.&#xA;WriteMullikenPop                1&#xA;WriteBands                      .false.&#xA;SaveRho                         .true.&#xA;SaveDeltaRho                    .true.&#xA;SaveHS                          .true.&#xA;SaveElectrostaticPotential      .true. &#xA;SaveTotalPotential              .true.&#xA;WriteCoorXmol                   .true.&#xA;WriteMDXmol                     .true.&#xA;WriteMDhistory                  .false.&#xA;WriteEigenvalues                .true.&#xA;XML.Write                       .true.&#xA;TS.HS.Save          .true.&#xA;TS.DE.Save          .true.&#xA;ParallelOverK       .true.&#xA;User.Basis          .true.&#xA;Diag.ParallelOverK  .true. &#xA;&#xA;==================================================&#xA;==================================================&#xA;#####################TRANSIESTA###################&#xA;&#xA;# Bias voltage&#xA;&#xA;&#xA;TS.Voltage 0.0 eV&#xA;&#xA;&#xA;&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;&#xA;TS.Elecs.Bulk true&#xA;TS.Elecs.DM.Update none&#xA;TS.Elecs.GF.ReUse false&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&#xA;%block TS.Elec.Left&#xA;  TSHS ./elec.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a3&#xA;  elec-pos begin 1&#xA;%endblock TS.Elec.Left&#xA;&#xA;%block TS.Elec.Right&#xA;  TSHS ./elec.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir +a3&#xA;  elec-pos end -1&#xA;%endblock TS.Elec.Right&#xA;&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.c-Left&#xA;  part circle&#xA;   from   -40.00000 eV + V/2 to -10. kT + V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Left&#xA;%block TS.Contour.t-Left&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Left&#xA;%block TS.Contour.c-Right&#xA;  part circle&#xA;   from   -40.00000 eV - V/2 to -10. kT - V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Right&#xA;%block TS.Contour.t-Right&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Right&#xA;&#xA;TS.Contours.nEq.Eta 0.0001 eV&#xA;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;    delta 0.01 eV&#xA;     method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA;#%block LocalDensityOfStates&#xA;#-2.21 0.00 eV&#xA;#%endblock LocalDensityOfStates&#xA;&#xA;TBT.DOS.A.All T&#xA;TBT.DOS.Gf   T&#xA;TS.SolutionMethod btd&#xA;TS.BTD.Pivot atom+Left&#xA;TS.Elecs.Neglect.Principal true&#xA;==================================================&#xA;==================================================&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After SCF calculation step; i got:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                  ***************************&#xA;                     *  WELCOME TO TRANSIESTA  *&#xA;                     ***************************&#xA;&#xA;ts-Vha: -0.11730E-01 eV&#xA;&#xA;transiesta: created H and S sparsity pattern:&#xA;  &amp;lt;sparsity:(M of: G ((UC of: T T T sparsity for geom step 0)))&#xA;    nrows_g=2366 nrows=2366 sparsity=.1333 nnzs=746036, refcount: 1&amp;gt;&#xA;&#xA;transiesta: created update sparsity pattern:&#xA;  &amp;lt;sparsity:G ((UC of: (M of: T T T sparsity for geom step 0)))&#xA;    nrows_g=2366 nrows=2366 sparsity=.1072 nnzs=599924, refcount: 1&amp;gt;&#xA;&#xA;transiesta: Determining an optimal tri-matrix using: atom+Left&#xA;transiesta: Established a near-optimal partition for the tri-diagonal matrix.&#xA;BTD partitions (9): &#xA;  [ 312, 364, [338] * 3, 325, 338, 1, 12 ]&#xA;transiesta: Matrix elements in % of full matrix:  38.63664 %&#xA;&#xA;transiesta: mem of electrodes (static):                     2.86MB&#xA;transiesta: mem of global update arrays (static):          41.08MB&#xA;transiesta: mem of tri-diagonal matrices:                  66.01MB&#xA;transiesta: Total memory usage:                           109.94MB&#xA;&#xA;transiesta: Charge distribution, target =    728.00000&#xA;Total charge                  [Q]  :   728.00000&#xA;Device                        [D]  :   514.03356&#xA;Left                          [E1] :    98.05875&#xA;Left                 / device [C1] :     5.94659&#xA;Right                         [E2] :    98.05467&#xA;Right                / device [C2] :     5.94168&#xA;Other                         [O]  :     5.96475&#xA;&#xA;Error on inverting X6/C7 with error: 1&#xA;Stopping Program from Node:    7&#xA;Error on inverting X6/C7 with error: 1&#xA;Stopping Program from Node:   18&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is causing this error?&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2023-02-24T10:02:29.417" LastActivityDate="2023-02-24T10:02:29.417" Title="Transiesta warning (Error on inverting X6/C7 with error: 1)" Tags="|siesta|electronic-transport|transport|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10432" PostTypeId="2" ParentId="10426" CreationDate="2023-02-17T15:26:25.373" Score="2" Body="&lt;p&gt;I don't have ORCA to test this, but it looks like the &lt;code&gt;LED&lt;/code&gt; (local energy decomposition) keyword, described in section 8.16.1 of the ORCA 4.2.1 manual would give you the energy of each fragment (as well as interaction energy between fragments).&lt;/p&gt;&#xA;&lt;p&gt;If that doesn't work for your case, section 9.12.4.2 describes various keywords for setting what methods are used to compute inter/intra fragment energies.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-02-17T15:26:25.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10433" PostTypeId="2" ParentId="10430" CreationDate="2023-02-17T20:51:24.367" Score="3" Body="&lt;p&gt;Inversion errors in TranSiesta happens when the system has 0's in the diagonal of the matrices. In this case the error either stems from a call to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   zgetrf&#xA;   zgetri&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in which case the error means that the &lt;code&gt;U(1,1)&lt;/code&gt; element is zero and thus the matrix is singular.&lt;/p&gt;&#xA;&lt;p&gt;From the question it is unclear whether this is related to some settings in the input, or whether it is a peculiar artefact from the geometry. Generally the matrices should &lt;em&gt;not&lt;/em&gt; be singular as one adds a fictitious imaginary value that ensures some broadening in the complex plane.&lt;/p&gt;&#xA;&lt;p&gt;However, it &lt;em&gt;may&lt;/em&gt; happen when two parts of the system are physically disconnected, in which case the imaginary part does not enter through the self-energies and then the chances of hitting a singular energy-point becomes much higher.&lt;/p&gt;&#xA;&lt;p&gt;I would highly suggest you to understand all options and their implications.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;you are using k-points along directions which are non-periodic&lt;/li&gt;&#xA;&lt;li&gt;the electrodes are using PDOS k-points along non-periodic directions&lt;/li&gt;&#xA;&lt;li&gt;the mesh-cutoff are different in the two calculations&lt;/li&gt;&#xA;&lt;li&gt;the basis sets are different in the two calculations&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;All in all you are not being consistent and this may be the root cause of your problems. Always ensure that electrode settings are equivalent to the electrode part of the device region!&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-02-22T08:17:35.637" LastActivityDate="2023-02-22T08:17:35.637" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10434" PostTypeId="2" ParentId="9500" CreationDate="2023-02-18T05:30:20.250" Score="1" Body="&lt;p&gt;The author of the question found a solution:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Hi Andrea and Tyberius, sorry for the late reply, my problem is already solved, thank you!&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If anyone (including the author of the question) would like to write an answer, they're welcome to flag for this answer to be removed.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-18T05:30:20.250" CommentCount="0" CommunityOwnedDate="2023-02-18T05:30:20.250" ContentLicense="CC BY-SA 4.0" />
  <row Id="10435" PostTypeId="2" ParentId="9554" CreationDate="2023-02-18T05:35:00.360" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9554/is-there-a-robust-and-reliable-software-to-change-the-lattice-vectors-of-unit-ce#comment19917_9554&quot;&gt;Answer by Pranav Kumar&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;VESTA&amp;gt;EDIT&amp;gt;put_rotation_matrix&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9554/is-there-a-robust-and-reliable-software-to-change-the-lattice-vectors-of-unit-ce#comment19919_9554&quot;&gt;Worked for the author of the question&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Thank you. It worked.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-18T05:35:00.360" CommentCount="0" CommunityOwnedDate="2023-02-18T05:35:00.360" ContentLicense="CC BY-SA 4.0" />
  <row Id="10436" PostTypeId="2" ParentId="9552" CreationDate="2023-02-18T05:36:23.090" Score="1" Body="&lt;p&gt;Suggestion &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9552/how-do-i-initialize-the-lattice-grid-in-a-potts-model#comment19918_9552&quot;&gt;by Erik Kjellgren&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;You can initialize it however you want, there is no correct way to initialize it. There might be better choices you can make depending on what you want to investigate.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If Erik or anyone else wants to write up a better answer, this answer can be flagged for deletion.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-18T05:36:23.090" CommentCount="0" CommunityOwnedDate="2023-02-18T05:36:23.090" ContentLicense="CC BY-SA 4.0" />
  <row Id="10438" PostTypeId="2" ParentId="9478" CreationDate="2023-02-18T05:51:56.560" Score="1" Body="&lt;p&gt;The question was:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;but why do some articles use different path&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;However, no article was provided that uses a different path. ProfM &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9478/k-path-for-phonon-band-structure#comment20512_9478&quot;&gt;said&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I agree there is no reason why the two paths should be different.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If someone would like to write a better answer, this one can be flagged for deletion.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-18T05:51:56.560" CommentCount="0" CommunityOwnedDate="2023-02-18T05:51:56.560" ContentLicense="CC BY-SA 4.0" />
  <row Id="10439" PostTypeId="5" CreationDate="2023-02-18T05:54:07.740" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/jax-md/jax-md&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/jax-md/jax-md&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-18T05:54:07.740" LastActivityDate="2023-02-18T05:54:07.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10440" PostTypeId="4" CreationDate="2023-02-18T05:54:07.740" Score="0" Body="Questions about the JAX MD package." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-18T05:54:07.740" LastActivityDate="2023-02-18T05:54:07.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10441" PostTypeId="1" CreationDate="2023-02-18T14:28:35.107" Score="7" ViewCount="219" Body="&lt;p&gt;I'm currently trying to understand &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.82.045122&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; explaining the origin of band inversion in the topological insulator Bi2Se3. In Fig. 2 (see below) they explain by means of 4 steps how certain atomic (and later bonding) bismuth and selenium p-orbitals behave under consideration of hybridization (I), the formation of chemical bonds (II), crystal field splitting and (III) and finally spin-orbit coupling (IV).&#xA;&lt;a href=&quot;https://i.stack.imgur.com/MRXJa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MRXJa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;I'm wondering why the energy of the &lt;span class=&quot;math-container&quot;&gt;$P2_z^-$&lt;/span&gt; state is increased while the one of &lt;span class=&quot;math-container&quot;&gt;$P1_z^+$&lt;/span&gt; is lowered. Maybe someone could explain to me why these states are affected by spin-orbit coupling in opposite ways?&lt;/p&gt;&#xA;" OwnerUserId="6741" LastEditorUserId="5" LastEditDate="2023-02-18T16:54:16.347" LastActivityDate="2023-02-18T16:54:16.347" Title="Spin-Orbit coupling effects in topological insulator Bi2Se3" Tags="|spectroscopy|spin-orbit-coupling|orbitals|topological-insulators|binding-energy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10442" PostTypeId="2" ParentId="10441" CreationDate="2023-02-18T15:34:36.790" Score="5" Body="&lt;p&gt;Welcome to MMSE! That's an interesting question! At first the &amp;quot;crossing&amp;quot; of energy levels seemed peculiar to me, but when I look at the energy levels for Se and for Bi separately, everything seems to follow a consistent pattern and the cross-over just happens as a matter of &lt;strong&gt;coincidence&lt;/strong&gt; because of how close the Bi and Se levels are to each other (at least in this figure's depiction).&lt;/p&gt;&#xA;&lt;p&gt;As for why the various perturbations seem to be affecting the Bi and Se levels in opposite ways, all I had to do is to notice that this was Figure 2, and then find where &amp;quot;Fig. 2&amp;quot; was mentioned in the text, and the answer was given in the same sentence:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Since all the Se layers are separated by Bi layers,the strongest coupling in this system is the coupling between Bi layers and Se layers. Such coupling causes level repulsion, so that the Bi energy levels are pushed up and form new hybridized states |B&amp;gt; and |B'&amp;gt; while the Se energy levels are pushed down and yield three states |S&amp;gt;,|S'&amp;gt;, and |S0&amp;gt;, as shown in Fig.2(I).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-18T15:34:36.790" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10443" PostTypeId="1" CreationDate="2023-02-18T15:56:19.330" Score="5" ViewCount="85" Body="&lt;p&gt;Say you have a small molecule or peptide that binds to a protein of interest. I'm interested in predicting the properties of the other type of ligand that might bind in a similar way.&lt;/p&gt;&#xA;&lt;p&gt;For example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;A)&lt;/strong&gt; peptide binds to target T. I want to computationally predict properties of a small molecule that might bind T in the same way&lt;/p&gt;&#xA;&lt;p&gt;OR&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;B)&lt;/strong&gt; small molecule binds to T. I want to computationally predict properties of a peptide that might bind T in the same way&lt;/p&gt;&#xA;&lt;p&gt;So I have a question: &lt;strong&gt;Is this unfeasible? Or do methods exist to do try to do this &lt;em&gt;in silico&lt;/em&gt;&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="6742" OwnerDisplayName="weddebege" LastEditorUserId="5" LastEditDate="2023-02-18T17:48:52.380" LastActivityDate="2023-02-18T17:48:52.380" Title="Computationally predicting small molecule/peptide based on others' binding to target protein" Tags="|computational-chemistry|proteins|from-chem-se|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-22T20:10:12.453" ContentLicense="CC BY-SA 4.0" />
  <row Id="10444" PostTypeId="1" AcceptedAnswerId="10481" CreationDate="2023-02-19T05:49:18.797" Score="3" ViewCount="169" Body="&lt;h1&gt;The problem&lt;/h1&gt;&#xA;&lt;p&gt;I've described how to restart a CISD calculation in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10192/5&quot;&gt;my answer&lt;/a&gt; to the question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9743/5&quot;&gt;Restarting an FCI calculation in PySCF&lt;/a&gt;, but this requires all iterations of the CISD calculation to finish, so that a &lt;code&gt;civec&lt;/code&gt; object is returned, which is the CISD vector, which can be saved by adding &lt;code&gt;np.save('civec.npy', civec)&lt;/code&gt; to the end of a PySCF input script. If a CISD calculation with a convergence tolerance of &lt;code&gt;1e-3&lt;/code&gt; is completed, the resulting &lt;code&gt;civec&lt;/code&gt; can be used as a starting point for a CISD calculation with a more stringent tolerance like &lt;code&gt;1e-5&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;However, what if the calculation with a convergence tolerance of &lt;code&gt;1e-3&lt;/code&gt; crashes before it completes?&lt;/h3&gt;&#xA;&lt;p&gt;Is it possible to print &lt;code&gt;civec&lt;/code&gt; after each Davidson iteration, so that if the job crashes during the 5th iteration (for example) without converging to the specified tolerance of &lt;code&gt;1e-3&lt;/code&gt;, we can use the saved &lt;code&gt;civec&lt;/code&gt; from the completed 4th iteration to restart the CISD calculation?&lt;/p&gt;&#xA;&lt;h1&gt;What I've found so far&lt;/h1&gt;&#xA;&lt;h4&gt;Checkpointing before full convergence seems possible with the MCSCF code:&lt;/h4&gt;&#xA;&lt;p&gt;I looked through all open and closed issues and pull requests on the &lt;a href=&quot;https://github.com/pyscf/pyscf/issues?page=2&amp;amp;q=chk&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF Git repository&lt;/a&gt; that were suggested when I searched &amp;quot;chk&amp;quot;, &amp;quot;checkfile&amp;quot;, &amp;quot;chkfile&amp;quot; and &amp;quot;restart&amp;quot;, and clicked on several of them that had promising titles, and the only one I think worth mentioning is &lt;a href=&quot;https://github.com/pyscf/pyscf/pull/8&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; because it showed me that the &lt;code&gt;/mcscf/&lt;/code&gt; folder has a &lt;code&gt;chkfile.py&lt;/code&gt; file, but such a file is not included in the &lt;code&gt;/ci/&lt;/code&gt; folder (also note that the keyword &lt;code&gt;dump_chk_ci=True&lt;/code&gt; is no longer in the current release PySCF, as I mentioned in a comment on that Pull Request).&lt;/p&gt;&#xA;&lt;p&gt;By running  &lt;code&gt;pyscf/examples/mcscf/13-load_chkfile.py&lt;/code&gt;, with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mci.chkfile = tmpchk.name &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;changed to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mci.chkfile = `mci.chk` &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I do get the chkfile &lt;code&gt;mci.chk&lt;/code&gt; printed, and by changing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mc.max_cycle_macro = 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mc.max_cycle_macro = 10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am able to confirm that the &lt;code&gt;.chk&lt;/code&gt; file is printed, then more output is produced, then the &lt;code&gt;.chk&lt;/code&gt; file is expanded, then more output is produced, etc., suggesting that the checkpoint is being updated after each macro-iteration.&lt;/p&gt;&#xA;&lt;h4&gt;I'm unable to do this with the CISD code:&lt;/h4&gt;&#xA;&lt;p&gt;The &lt;code&gt;pyscf/ci&lt;/code&gt; folder doesn't have a &lt;code&gt;chkfile.py&lt;/code&gt;, but I did notice that &lt;code&gt;pyscf/ci/cisd.py&lt;/code&gt; contains the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    def dump_chk(self, ci=None, frozen=None, mo_coeff=None, mo_occ=None):&#xA;        if not self.chkfile:&#xA;            return self&#xA;&#xA;        if ci is None: ci = self.ci&#xA;        if frozen is None: frozen = self.frozen&#xA;        # &amp;quot;None&amp;quot; cannot be serialized by the chkfile module&#xA;        if frozen is None:&#xA;            frozen = 0&#xA;&#xA;        ci_chk = {'e_corr': self.e_corr,&#xA;                  'ci': ci,&#xA;                  'frozen': frozen}&#xA;&#xA;        if mo_coeff is not None: ci_chk['mo_coeff'] = mo_coeff&#xA;        if mo_occ is not None: ci_chk['mo_occ'] = mo_occ&#xA;        if self._nmo is not None: ci_chk['_nmo'] = self._nmo&#xA;        if self._nocc is not None: ci_chk['_nocc'] = self._nocc&#xA;&#xA;        lib.chkfile.save(self.chkfile, 'cisd', ci_chk)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This &lt;code&gt;dump_chk&lt;/code&gt; code doesn't seem to be used though. Also, the following script produces all the correct output, except &lt;em&gt;&lt;strong&gt;unlike the mcscf program&lt;/strong&gt;&lt;/em&gt; it does not produce any &lt;code&gt;.chk&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf&#xA;from pyscf import gto, scf, ao2mo, fci,ci, lib&#xA;&#xA;mol = pyscf.M(atom = 'Ne 0 0 0',basis = 'cc-pvDz',verbose=5,output='out_1e-5_direct.txt')&#xA;mhf = scf.RHF(mol).run()&#xA;mci = ci.CISD(mhf).set(conv_tol=1e-5,nroots=3)&#xA;mci.chkfile = 'cisd.chk'&#xA;e, civec = mci.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h4&gt;Example files don't seem to involve checkpointing for CISD:&lt;/h4&gt;&#xA;&lt;p&gt;I have looked through various files in PySCF's &lt;a href=&quot;https://github.com/pyscf/pyscf/tree/master/examples&quot; rel=&quot;nofollow noreferrer&quot;&gt;example suite&lt;/a&gt;, based on file names in the &lt;a href=&quot;https://github.com/pyscf/pyscf/tree/master/examples/ci&quot; rel=&quot;nofollow noreferrer&quot;&gt;CI folder&lt;/a&gt; (specifically &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/ci/00-simple_cisd.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;00-simple_cisd.py&lt;/code&gt;&lt;/a&gt;, &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/ci/01-density_matrix.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;01-density-matrix&lt;/code&gt;&lt;/a&gt;, &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/ci/20-from_fci.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;20-from-fci.py&lt;/code&gt;&lt;/a&gt; and &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/ci/32-wfn_overlap.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;32-wfn_overlap.py&lt;/code&gt;&lt;/a&gt;), and the &lt;a href=&quot;https://github.com/pyscf/pyscf/tree/master/examples/fci&quot; rel=&quot;nofollow noreferrer&quot;&gt;FCI folder&lt;/a&gt; (&lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/fci/11-large_ci.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;11-large_ci.py&lt;/code&gt;&lt;/a&gt;). Unfortunately &lt;code&gt;chk&lt;/code&gt; and &lt;code&gt;check&lt;/code&gt; and &lt;code&gt;dump&lt;/code&gt; don't appear in any of those files! In the &lt;a href=&quot;https://github.com/pyscf/pyscf/tree/master/examples/mcscf&quot; rel=&quot;nofollow noreferrer&quot;&gt;MCSCF folder&lt;/a&gt; there's the above-mentioned &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/mcscf/13-load_chkfile.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;13-load_chkfile.py&lt;/code&gt;&lt;/a&gt; and also &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/mcscf/13-restart.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;13-restart.py&lt;/code&gt;&lt;/a&gt;, and &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/examples/mcscf/14-project_init_guess.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;14-project_init_guess.py&lt;/code&gt;&lt;/a&gt;), the former two giving examples of printing check point files for MCSCF, but not for CISD.&lt;/p&gt;&#xA;&lt;h4&gt;Other files associated with checkpointing don't show a clear way to do it for CISD:&lt;/h4&gt;&#xA;&lt;p&gt;The file &lt;code&gt;pyscf/pyscf/lib/chkfile.py&lt;/code&gt; has an example in the comments that contains &lt;code&gt;lib.chkfile.save('symm.chk', 'symm', ci)&lt;/code&gt;, but there's nothing like &lt;code&gt;mci.kernel&lt;/code&gt; in that example, for actually running a CISD calculation. The file &lt;a href=&quot;https://github.com/pyscf/pyscf/blob/master/pyscf/tools/chkfile_util.py%60&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;pyscf/tools/chkfile_util&lt;/code&gt;&lt;/a&gt; doesn't seem to have anything related to checkpointing CISD.&lt;/p&gt;&#xA;&lt;h1&gt;The question&lt;/h1&gt;&#xA;&lt;p&gt;Is there a native way to dump the CI vector after each Davidson iteration, when doing a CISD calculation in PySCF?&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-25T22:46:36.123" Title="Is PySCF able to print checkpoint files during a CISD calculation?" Tags="|quantum-chemistry|python|high-performance-computing|pyscf|configuration-interaction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10446" PostTypeId="2" ParentId="9947" CreationDate="2023-02-19T16:24:43.310" Score="3" Body="&lt;p&gt;I changed the &lt;code&gt;c_h_template&lt;/code&gt; to also use smiles and the substructMatch returns &lt;strong&gt;True&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am using rdkit version number: &lt;strong&gt;2022.9.4&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the full reproducible code.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import AllChem&#xA;from rdkit.Chem import rdChemReactions&#xA;c_h_template = AllChem.ReactionFromSmarts('[CH:1]&amp;gt;&amp;gt;[C:1]~[C:2]', useSmiles=True)&#xA;rxn = AllChem.ReactionFromSmarts('C1=[CH:1]-C=CC=C1.C[CH:2]=C.[Pd]&amp;gt;&amp;gt;C[C:2](=C)[CH:1]1=CC=CC=C1',useSmiles=True)&#xA;&#xA;result = rdChemReactions.HasReactionSubstructMatch(x,c_h_template)&#xA;print(result) # returns True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-02-19T16:24:43.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10447" PostTypeId="1" CreationDate="2023-02-19T19:16:44.827" Score="5" ViewCount="155" Body="&lt;p&gt;Thanks in advance for any help provided. I was trying to find the transition state of a diels alder reaction and considering my system's bulkiness I wanted to try a NEB calculation considering part of the structure in QM (MN15/DEF2-SVP) and part in MM. Unexpectedly at the end it failed, even if the MEP seemed quite right.&lt;/p&gt;&#xA;&lt;p&gt;I cannot find anything on this type of error, any advice would be appreciated :)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   LBFGS    48      4    0.042926    0.057420   0.003170  165.8529    0.027242    0.003767       &#xA;   LBFGS    49      4    0.043722    0.071380   0.004063  165.8515    0.041807    0.004877       &#xA;   LBFGS    50      6    0.048872    0.071381   0.004367  165.8515    0.005908    0.000851       &#xA;[file orca_tools/Tool-Misc/qcneb.cpp, line 540]: Error (ORCA/NEB): Failure in L-BFGS (division by very small number)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To be even more clear this was the neb.inp&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! QM/QM2  def2-svp NEB-TS cpcm(toluene) &#xA;&#xA;%neb&#xA;    TS &amp;quot;ts.xyz&amp;quot;&#xA;    product &amp;quot;product.xyz&amp;quot;&#xA;    preopt true&#xA;    nimages 8 &#xA;    NEB_TS_Image 4&#xA;end&#xA;&#xA;%method&#xA;    method dft&#xA;    functional hyb_mgga_x_mn15&#xA;end&#xA;&#xA;%pal&#xA;    nprocs 44&#xA;end&#xA;&#xA;%maxcore 4000&#xA;&#xA;%qmmm&#xA;    QM2CustomMethod &amp;quot;pbe&amp;quot;&#xA;    QM2CustomBasis &amp;quot;def2-svp&amp;quot;&#xA;    QMAtoms { 14 15 16 18 32:34 56:63 64:82 83:91 } end # atomi da trattare a MN15&#xA;    #14-18 caten cat. 32-34 hyd. 56-63 acido 64-82 diene 83-91 mal.&#xA;end&#xA;&#xA;*xyzfile 0 1 reagents.xyz&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6747" LastEditorUserId="7" LastEditDate="2023-02-20T13:05:35.823" LastActivityDate="2023-02-22T09:29:11.527" Title="ORCA failed during NEB-TS ONIOM" Tags="|quantum-chemistry|orca|optimization|transition-state|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:10:48.410" ContentLicense="CC BY-SA 4.0" />
  <row Id="10448" PostTypeId="2" ParentId="9832" CreationDate="2023-02-19T22:08:42.707" Score="3" Body="&lt;p&gt;Edit: CA does not refer to Calcium atoms. They refer to alpha carbon atoms as defined in the &lt;a href=&quot;https://www.cgl.ucsf.edu/chimera/docs/UsersGuide/tutorials/pdbintro.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PDB&lt;/a&gt; format.&lt;/p&gt;&#xA;&lt;p&gt;To get an accurate RMSD value between two molecules they would need to be first re-centered and then rotated unto each other to get the true minimal RMSD.&lt;/p&gt;&#xA;&lt;p&gt;The code that you posted compares only aligns alpha carbon atoms.&#xA;This can be seen in the following lines of the code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Select what residues numbers you wish to align&#xA;# and put them in a list&#xA;start_id = 1&#xA;end_id   = 70&#xA;&#xA;########&#xA;# Make a list of the atoms (in the structures) you wish to align.&#xA;# In this case we use CA atoms whose index is in the specified range&#xA;ref_atoms = []&#xA;sample_atoms = []&#xA;&#xA;#########&#xA;&#xA;ref_atoms.append(ref_res['CA'])&#xA;sample_atoms.append(sample_res['CA'])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To get an accurate RMSD value all of the atoms would need to re-centered and rotated accordingly. Not just alpha carbon atoms. Comparing only the alpha atoms could be a bug in case you were after the true minimal RMSD.&lt;/p&gt;&#xA;&lt;p&gt;I used the script posted above with the same PDB file of &lt;a href=&quot;https://www.rcsb.org/structure/1a6j&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.rcsb.org/structure/1a6j&lt;/a&gt; and it printed out the RMSD to be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RMSD =  1.2115634513933915e-14&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I used the &lt;a href=&quot;https://pypi.org/project/rmsd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;rmsd&lt;/a&gt; library, it gives me a better (true) RMSD value:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RMSD =  6.8963066943027425e-15&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-02-20T06:28:11.803" LastActivityDate="2023-02-20T06:28:11.803" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10450" PostTypeId="1" AcceptedAnswerId="10456" CreationDate="2023-02-20T14:11:09.380" Score="3" ViewCount="71" Body="&lt;p&gt;I want to create the CIF file of CuI using VESTA software.I used the following parameters to create my CIF : space group, lattice parameter, the angles (alpha, beta and gamma), atomic positions of Cu and I.&lt;/p&gt;&#xA;&lt;p&gt;In the experimental data of my material they mention : Rwp ,RI,Rf and atomic displacement parameter B, as shown in the picture bellow . I don't know the meaning of those parameters and if I should include them in my CIF file how to do that using VESTA?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ux0oz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ux0oz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Please, Clarify my doubts! It will be helpful to me in my learning process. Thank you&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-21T01:44:48.623" LastActivityDate="2023-02-21T14:06:12.280" Title="Do I have to use Rwp, RI, Rf and atomic displacement parameter B to create a CIF file?" Tags="|density-functional-theory|quantum-espresso|visualization-software|vesta|cif|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10451" PostTypeId="1" CreationDate="2023-02-20T16:46:55.263" Score="5" ViewCount="78" Body="&lt;p&gt;Is there a good reference textbook for calculating pressures/stress/strain/tensors in materials - vapor, liquids and solids? Pure physics is fine, but it would be a bonus if it also included force-field derivations, particularly electrostatics like Ewalds and the other flavors.&lt;/p&gt;&#xA;&lt;p&gt;I am hoping to find a good reference that kind of &amp;quot;derives it all&amp;quot; in a straightforward manner that I can use as an introductory textbook for teaching these concepts at  an undergraduate level.&lt;/p&gt;&#xA;&lt;p&gt;I am not after code that can do these calculations. I do not feel that citing the GROMACS manual is an acceptable source for these concepts for undergraduates. However, they should be able to write their own code for simple systems with the help of the reference.&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="5" LastEditDate="2023-10-21T15:51:00.127" LastActivityDate="2023-10-21T15:51:00.127" Title="Reference textbooks for calculating pressures/stress/strain/tensors?" Tags="|reference-request|physical-properties-of-materials|forcefields|stress-strain|" AnswerCount="0" CommentCount="2" ClosedDate="2024-02-21T04:11:47.980" ContentLicense="CC BY-SA 4.0" />
  <row Id="10452" PostTypeId="1" CreationDate="2023-02-20T21:07:38.917" Score="5" ViewCount="275" Body="&lt;p&gt;I'm looking to superimpose electron phonon coupling (EPC) constants per phonon band per k-point as is done in Figures 6c and 6d in this paper, essentially a &amp;quot;fat band&amp;quot; plot where the diameter of the circles on the phonon bands represents EPC magnitude &lt;a href=&quot;https://www.pnas.org/doi/10.1073/pnas.1704505114#sec-3&quot; rel=&quot;noreferrer&quot;&gt;https://www.pnas.org/doi/10.1073/pnas.1704505114#sec-3&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think this k-point dependent format is extremely helpful in showing how phonons couple to the electronic bands of the solid when in/out of phase between unit cells (ie at different k-points of high symmetry in the 1st Brilluoin zone), but every software I've seen will only compute DOS-like spectral functions or other k-point independent plots of EPC. I've examined EPC documentation for Quantum Espresso (which this paper lists as used in their methods) as well as other widely used softwares like EPW and Phonopy. The electronic bands I've plotted for my system are generated from DFT in VASP and the phonon bands (without EPC) are done with Vasp DFPT post-processed in Phonopy, but I'm open to using any software to get this sort of plot.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone tell me how I can go about making a phonon band diagram like this with EPC magnitude superimposed?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/LgJtL.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LgJtL.png&quot; alt=&quot;Figures 6c and 6d from the linked paper&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerDisplayName="user4763" LastActivityDate="2023-02-20T21:07:38.917" Title="Electron-phonon coupling plotted as function of phonon bands" Tags="|vasp|quantum-espresso|band-structure|phonon-dispersion|superconductivity|" AnswerCount="0" CommentCount="0" ClosedDate="2023-10-22T20:10:33.260" ContentLicense="CC BY-SA 4.0" />
  <row Id="10453" PostTypeId="1" CreationDate="2023-02-21T01:42:21.887" Score="3" ViewCount="99" Body="&lt;h1&gt;A case that works&lt;/h1&gt;&#xA;&lt;p&gt;In my answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9743/5&quot;&gt;Restarting an FCI calculation in PySCF&lt;/a&gt;, I provided a &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/9743/cisd&quot; rel=&quot;nofollow noreferrer&quot;&gt;folder full of input and output files&lt;/a&gt; that demonstrates saving (as a &lt;code&gt;numpy&lt;/code&gt; array) a CI vector from a converged CISD calculation with a certain convergence tolerance, and using it as the starting point for a CISD calculation with a tighter convergence tolerance, can lead to convergence with the tighter convergence tolerance in fewer &lt;em&gt;&lt;strong&gt;total&lt;/strong&gt;&lt;/em&gt; Davidson iterations.&lt;/p&gt;&#xA;&lt;p&gt;In particular, this is what it looks like when not using the above-described restrat procedure (I've removed the &lt;code&gt;e&lt;/code&gt; vectors that you would see in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10192/5&quot;&gt;my original answer&lt;/a&gt; in order to make the &lt;strong&gt;&lt;code&gt;max|de|&lt;/code&gt;&lt;/strong&gt; column more clear; and I've removed all lines that don't start with &lt;code&gt;davidson&lt;/code&gt; so that it's easier to see how &lt;strong&gt;&lt;code&gt;max|de|&lt;/code&gt;&lt;/strong&gt; progresses):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0 3   |r|= 2.82             max|de|=  0.967     lindep= 0.321&#xA;davidson 1 6   |r|= 1.67             max|de|= -0.374     lindep= 0.795&#xA;davidson 2 9   |r|= 0.119            max|de|= -0.1       lindep= 0.935&#xA;davidson 3 12  |r|= 0.0309           max|de|= -0.00137   lindep= 0.798&#xA;davidson 4 15  |r|= 0.015            max|de|= -9.09e-05  lindep= 0.838&#xA;davidson 5 18  |r|= 0.00676          max|de|= -4.81e-05  lindep= 0.839&#xA;davidson 6 3   |r|= 0.00676          max|de|= -2e-15     lindep=    1&#xA;davidson 7 6   |r|= 0.00341          max|de|= -6.44e-06  lindep= 0.808&#xA;davidson 8 9   |r|= 0.00545          max|de|= -5.05e-06  lindep= 0.519&#xA;davidson 9 12  |r|= 0.0266           max|de|= -8.54e-05  lindep= 0.797&#xA;davidson 10 14 |r|= 0.0367           max|de|= -0.000247  lindep= 0.769&#xA;davidson 11 16 |r|= 0.0169           max|de|= -0.00023   lindep= 0.745&#xA;davidson 12 3  |r|= 0.0169           max|de|=  3.33e-15  lindep= 0.857&#xA;davidson 13 5  |r|= 0.0155           max|de|= -5.47e-05  lindep= 0.521&#xA;davidson 14 7  |r|= 0.0199           max|de|= -5e-05     lindep= 0.54&#xA;davidson 15 9  |r|= 0.0072           max|de|= -5.41e-05  lindep= 0.868&#xA;davidson 16 11 |r|= 0.00248          max|de|= -8.5e-06   lindep= 0.946&#xA;davidson 17 12 |r|= 0.00141          max|de|= -1.45e-06  lindep= 0.805&#xA;davidson 18 13 |r|= 0.00467          max|de|= -4.16e-06  lindep= 0.954&#xA;davidson 19 14 |r|= 0.0131           max|de|= -2.79e-05  lindep= 0.916&#xA;davidson 20 15 |r|= 0.0129           max|de|= -0.000103  lindep= 0.938&#xA;davidson 21 16 |r|= 0.00397          max|de|= -2.14e-05  lindep= 0.879&#xA;davidson 22 3  |r|= 0.00397          max|de|=  5.03e-12  lindep= 0.995&#xA;davidson 23 4  |r|= 0.00169          max|de|= -1.86e-06  lindep= 0.818&#xA;davidson 24 6  |r|= 0.000331         max|de|= -2.66e-07  lindep= 0.92&#xA;davidson 25 8  |r|= 9.6e-05          max|de|= -1.48e-08  lindep= 0.892&#xA;davidson 26 9  |r|= 4.79e-05         max|de|= -1.45e-09  lindep= 0.775&#xA;davidson 27 10 |r|= 9.55e-05         max|de|= -7.29e-10  lindep= 0.446&#xA;davidson 28 11 |r|= 0.00012          max|de|= -1.91e-09  lindep= 0.607&#xA;davidson 29 13 |r|= 0.000161         max|de|= -8.3e-09   lindep=  0.9&#xA;davidson 30 15 |r|= 0.000134         max|de|= -7.21e-09  lindep= 0.894&#xA;davidson 31 17 |r|= 9.8e-05          max|de|= -4.61e-09  lindep= 0.838&#xA;davidson 32 3  |r|= 9.79e-05         max|de|=  9.03e-09  lindep= 0.999&#xA;davidson 33 4  |r|= 9.76e-05         max|de|= -2.65e-09  lindep= 0.835&#xA;davidson 34 5  |r|= 6.05e-05         max|de|= -2.83e-09  lindep= 0.913&#xA;davidson 35 6  |r|= 3.02e-05         max|de|= -1e-09     lindep= 0.738&#xA;converged 36 7 |r|= 2.1e-05          max|de|= -1.36e-10&#xA;RCISD converged&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is what it looks like when I do the above with &lt;code&gt;conv_tol=1e-5&lt;/code&gt; instead of &lt;code&gt;conv_tol=1e-9&lt;/code&gt; (notice that until the &lt;code&gt;davidson 16&lt;/code&gt; line, the &lt;strong&gt;&lt;code&gt;max|de|&lt;/code&gt;&lt;/strong&gt; values are almost identical to the above case):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0 3   |r|= 2.82             max|de|=  0.967     lindep= 0.321&#xA;davidson 1 6   |r|= 1.67             max|de|= -0.374     lindep= 0.795&#xA;davidson 2 9   |r|= 0.119            max|de|= -0.1       lindep= 0.935&#xA;davidson 3 12  |r|= 0.0309           max|de|= -0.00137   lindep= 0.798&#xA;davidson 4 15  |r|= 0.015            max|de|= -9.09e-05  lindep= 0.838&#xA;davidson 5 18  |r|= 0.00676          max|de|= -4.81e-05  lindep= 0.839&#xA;davidson 6 3   |r|= 0.00676          max|de|= -2e-15     lindep=    1&#xA;davidson 7 5   |r|= 0.00344          max|de|= -6.42e-06  lindep= 0.808&#xA;davidson 8 7   |r|= 0.00543          max|de|= -5.02e-06  lindep= 0.738&#xA;davidson 9 9   |r|= 0.0262           max|de|= -8.09e-05  lindep= 0.577&#xA;davidson 10 11 |r|= 0.0347           max|de|= -0.000254  lindep= 0.775&#xA;davidson 11 13 |r|= 0.0214           max|de|= -0.000281  lindep= 0.888&#xA;davidson 12 15 |r|= 0.0152           max|de|= -0.000131  lindep= 0.815&#xA;davidson 13 16 |r|= 0.0217           max|de|= -0.000125  lindep= 0.84&#xA;davidson 14 3  |r|= 0.0217           max|de|= 6e-15      lindep= 0.988&#xA;davidson 15 4  |r|= 0.00936          max|de|= -5.92e-05  lindep= 0.804&#xA;davidson 16 5  |r|= 0.00678          max|de|= -2.44e-05  lindep= 0.867&#xA;davidson 17 6  |r|= 0.00551          max|de|= -1.57e-05  lindep= 0.691&#xA;davidson 18 7  |r|= 0.00339          max|de|= -3.89e-06  lindep= 0.443&#xA;converged 19 8 |r|= 0.00132          max|de|= -8.5e-07&#xA;RCISD converged&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is what it looks like when restarting from the result directly above, and switching &lt;code&gt;conv_tol&lt;/code&gt; back to &lt;code&gt;1e-9&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0  3  |r|= 0.00132          max|de|=  0.805     lindep= 0.816&#xA;davidson 1  6  |r|= 0.000962         max|de|= -2.48e-07  lindep= 0.506&#xA;davidson 2  9  |r|= 0.000859         max|de|= -1.32e-07  lindep= 0.63&#xA;davidson 3  11 |r|= 0.00165          max|de|= -3.75e-07  lindep= 0.796&#xA;davidson 4  13 |r|= 0.00418          max|de|= -3.88e-06  lindep= 0.939&#xA;davidson 5  14 |r|= 0.00519          max|de|= -1.15e-05  lindep= 0.892&#xA;davidson 6  15 |r|= 0.00117          max|de|= -4.14e-06  lindep= 0.914&#xA;davidson 7  16 |r|= 0.00041          max|de|= -1.66e-07  lindep= 0.775&#xA;davidson 8  3  |r|= 0.00041          max|de|=  9.11e-11  lindep= 0.999&#xA;davidson 9  4  |r|= 0.000371         max|de|= -3.54e-08  lindep= 0.692&#xA;davidson 10 5  |r|= 0.000219         max|de|= -4.39e-08  lindep= 0.929&#xA;davidson 11 6  |r|= 7.38e-05         max|de|= -7.99e-09  lindep= 0.781&#xA;converged 12 7 |r|= 3.04e-05         max|de|= -7.2e-10&#xA;RCISD converged&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;A case that does not work&lt;/h1&gt;&#xA;&lt;p&gt;The following input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# Author: Nike Dattani, nike@hpqc.org&#xA;&#xA;import numpy as np&#xA;import pyscf&#xA;from pyscf.gto.basis import parse_gaussian&#xA;from pyscf import gto, scf, ao2mo, fci, ci&#xA;&#xA;mol = pyscf.M(&#xA;    atom = 'H 0 0 0; H 0 0 1.4011',&#xA;    unit = 'bohr',&#xA;    basis = {&#xA;            'H' : parse_gaussian.load('/home/nike/AI_ENERGIES/H/av6z.gbs', 'H')&#xA;    },&#xA;    charge = 0,&#xA;    spin = 0,&#xA;    verbose = 9,&#xA;    symmetry = True,&#xA;    symmetry_subgroup = 'Dooh',&#xA;)&#xA;&#xA;#####################&#xA;## Hartree-Fock:&#xA;#####################&#xA;mf = mol.RHF().set(conv_tol=1e-10,max_cycle=999,direct_scf_tol=1e-14,chkfile = 'a6z.chk')&#xA;#mf.init_guess='atom'&#xA;#mf.init_guess='a10z.chk'&#xA;mf.kernel()&#xA;&#xA;#####################&#xA;## post-Hartree-Fock:&#xA;#####################&#xA;&#xA;mci = ci.CISD(mf).set(conv_tol=1e-5,max_cycle=999,nroots=27)&#xA;#mci.direct = True&#xA;e, civec = mci.kernel()&#xA;#e, civec = mci.kernel(ci0=np.load('civec.npy'))&#xA;np.save('civec.npy', civec)&#xA;&#xA;#####################&#xA;## END OF INPUT&#xA;#####################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;gives the following output (again with the &lt;code&gt;e&lt;/code&gt; vectors removed and alignment adjustments so that the output is easier to raed):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0  27  |r|= 0.306    max|de|=  1.28      lindep= 0.317&#xA;davidson 1  54  |r|= 0.228    max|de|= -0.0578    lindep= 0.237&#xA;davidson 2  81  |r|= 0.361    max|de|= -0.041     lindep= 0.656&#xA;davidson 3  27  |r|= 0.361    max|de|= -1.16e-09  lindep= 0.723&#xA;davidson 4  54  |r|= 0.353    max|de|= -0.0399    lindep= 0.333&#xA;davidson 5  81  |r|= 0.332    max|de|= -0.0695    lindep= 0.355&#xA;davidson 6  27  |r|= 0.332    max|de|= -2.87e-08  lindep= 0.474&#xA;davidson 7  36  |r|= 0.251    max|de|= -0.0333    lindep= 0.362&#xA;davidson 8  43  |r|= 0.133    max|de|= -0.0115    lindep= 0.707&#xA;davidson 9  49  |r|= 0.0693   max|de|= -0.00816   lindep= 0.855&#xA;davidson 10 51  |r|= 0.0425   max|de|= -0.00192   lindep= 0.734&#xA;davidson 11 53  |r|= 0.0214   max|de|= -0.000329  lindep= 0.813&#xA;davidson 12 55  |r|= 0.0119   max|de|= -0.000104  lindep= 0.792&#xA;davidson 13 57  |r|= 0.00687  max|de|= -3.89e-05  lindep= 0.69&#xA;davidson 14 58  |r|= 0.00315  max|de|= -1.09e-05  lindep= 0.791&#xA;converged 15 59  |r|= 0.00244 max|de|= -2.53e-06&#xA;RCISD converged&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I &amp;quot;restart&amp;quot; this calculation with a smaller &lt;code&gt;conv_tol&lt;/code&gt; value and using the &lt;code&gt;civec.npy&lt;/code&gt; file from the previous calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mci = ci.CISD(mf).set(conv_tol=1e-6,max_cycle=999,nroots=28)&#xA;e, civec = mci.kernel(ci0=np.load('civec.npy'))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get &lt;em&gt;&lt;strong&gt;results that are significantly worse&lt;/strong&gt;&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0   27  |r|= 0.00244 max|de|=  1.02    lindep= 0.809&#xA;davidson 1   54  |r|= 3.26    max|de|= -0.0404  lindep= 0.694&#xA;davidson 2   66  |r|= 0.523   max|de|= -0.953   lindep= 0.278&#xA;davidson 3   28  |r|= 0.48    max|de|= -0.0422  lindep= 0.198&#xA;davidson 4   34  |r|= 0.178   max|de|= -0.032   lindep= 0.111&#xA;davidson 5   40  |r|= 1.07    max|de|=  0.11    lindep= 0.0356&#xA;davidson 6   46  |r|= 0.224   max|de|= -0.148   lindep= 0.00736&#xA;davidson 7   52  |r|= 1.55    max|de|=  0.614   lindep= 0.00343&#xA;davidson 8   59  |r|= 0.383   max|de|= -0.481   lindep= 0.000585&#xA;davidson 9   66  |r|= 1.43    max|de|=  0.481   lindep= 0.000675&#xA;davidson 10  28  |r|= 1.26    max|de|=  0.0416  lindep= 0.225&#xA;davidson 11  38  |r|= 0.183   max|de|= -0.0698  lindep= 0.0414&#xA;davidson 12  47  |r|=  1.3    max|de|=  0.76    lindep= 0.0137&#xA;davidson 13  57  |r|= 0.506   max|de|= -0.775   lindep= 0.00197&#xA;davidson 14  67  |r|= 0.335   max|de|= -0.0292  lindep= 0.00103&#xA;davidson 15  28  |r|= 0.213   max|de|=  0.055   lindep= 0.138&#xA;davidson 16  38  |r|= 0.72    max|de|= -0.0243  lindep= 0.0141&#xA;davidson 17  49  |r|= 0.286   max|de|= -0.184   lindep= 0.00154&#xA;davidson 18  60  |r|= 0.274   max|de|= -0.00263 lindep= 0.00017&#xA;davidson 19  71  |r|= 0.815   max|de|=  0.308   lindep= 7.68e-05&#xA;davidson 20  28  |r|= 0.815   max|de|=  0.0582  lindep= 0.128&#xA;davidson 21  41  |r|= 0.813   max|de|= -0.206   lindep= 0.0214&#xA;davidson 22  55  |r|= 1.17    max|de|=  0.165   lindep= 0.00475&#xA;davidson 23  70  |r|= 1.23    max|de|= -0.415   lindep= 0.00107&#xA;davidson 24  28  |r|=  1.3    max|de|=  0.0979  lindep= 0.123&#xA;davidson 25  44  |r|= 1.09    max|de|= -0.403   lindep= 0.00725&#xA;davidson 26  60  |r|= 1.24    max|de|=  0.401   lindep= 0.000936&#xA;davidson 27  77  |r|= 1.22    max|de|= -0.669   lindep= 0.00155&#xA;davidson 28  28  |r|= 1.22    max|de|=  0.291   lindep= 0.143&#xA;davidson 29  46  |r|= 1.51    max|de|= -0.406   lindep= 0.00606&#xA;davidson 30  66  |r|= 0.774   max|de|= -0.409   lindep= 0.0109&#xA;davidson 31  28  |r|= 0.628   max|de|=  0.122   lindep= 0.118&#xA;davidson 32  49  |r|= 0.73    max|de|= -0.107   lindep= 0.0052&#xA;davidson 33  71  |r|= 0.944   max|de|=  0.227   lindep= 0.000678&#xA;davidson 34  28  |r|= 0.955   max|de|=  0.181   lindep= 0.126&#xA;davidson 35  50  |r|= 0.907   max|de|= -0.216   lindep= 0.00234&#xA;davidson 36  68  |r|= 0.534   max|de|= -0.145   lindep= 0.000781&#xA;davidson 37  28  |r|= 0.391   max|de|=  0.0416  lindep= 0.0934&#xA;davidson 38  51  |r|= 0.896   max|de|=  0.0729  lindep= 0.00274&#xA;davidson 39  72  |r|= 1.05    max|de|=  0.261   lindep= 0.000494&#xA;davidson 40  28  |r|= 1.04    max|de|= -0.145   lindep= 0.132&#xA;davidson 41  54  |r|= 0.872   max|de|= -0.328   lindep= 0.00481&#xA;davidson 42  72  |r|=  1.2    max|de|=  0.265   lindep= 0.000577&#xA;davidson 43  28  |r|=  1.2    max|de|=  0.113   lindep= 0.123&#xA;davidson 44  56  |r|= 0.926   max|de|= -0.246   lindep= 0.00102&#xA;davidson 45  74  |r|= 0.515   max|de|= -0.244   lindep= 0.000294&#xA;davidson 46  28  |r|= 0.323   max|de|=  0.0482  lindep= 0.156&#xA;davidson 47  54  |r|= 0.15    max|de|= -0.0714  lindep= 0.0188&#xA;davidson 48  71  |r|= 0.39    max|de|=  0.00182 lindep= 0.00268&#xA;davidson 49  28  |r|= 0.398   max|de|=  0.0692  lindep= 0.123&#xA;davidson 50  54  |r|= 0.682   max|de|= -0.0383  lindep= 0.00184&#xA;davidson 51  66  |r|= 0.535   max|de|= -0.121   lindep= 0.000584&#xA;davidson 52  28  |r|= 0.522   max|de|=  0.0788  lindep= 0.217&#xA;davidson 53  52  |r|= 0.477   max|de|= -0.0799  lindep= 0.0475&#xA;davidson 54  65  |r|= 0.282   max|de|= -0.0426  lindep= 0.00548&#xA;davidson 55  75  |r|= 0.313   max|de|= -0.0138  lindep= 0.00125&#xA;davidson 56  28  |r|= 0.286   max|de|=  0.078   lindep= 0.183&#xA;davidson 57  50  |r|= 0.773   max|de|= -0.0439  lindep= 0.00725&#xA;davidson 58  65  |r|= 0.511   max|de|= -0.13    lindep= 0.00639&#xA;davidson 59  80  |r|= 0.561   max|de|= -0.0389  lindep= 0.00332&#xA;davidson 60  28  |r|= 0.436   max|de|=  0.139   lindep= 0.226&#xA;davidson 61  53  |r|=  0.7    max|de|= -0.0786  lindep= 0.295&#xA;davidson 62  70  |r|= 0.467   max|de|= -0.112   lindep= 0.0113&#xA;davidson 63  28  |r|= 0.411   max|de|=  0.131   lindep= 0.231&#xA;davidson 64  53  |r|= 0.593   max|de|= -0.0579  lindep= 0.06&#xA;davidson 65  71  |r|= 0.579   max|de|= -0.0811  lindep= 0.0167&#xA;davidson 66  28  |r|= 0.41    max|de|=  0.156   lindep= 0.221&#xA;davidson 67  56  |r|= 0.561   max|de|= -0.0616  lindep= 0.0926&#xA;davidson 68  76  |r|= 0.521   max|de|= -0.0812  lindep= 0.0288&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It continued like that until the calculation job timed out after &lt;code&gt;davidson 608&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 601 56  |r|= 0.419   max|de|= -0.0211  lindep= 0.0172&#xA;davidson 602 83  |r|= 0.37    max|de|= -0.13    lindep= 0.0116&#xA;davidson 603 28  |r|= 0.306   max|de|=  0.0743  lindep= 0.224&#xA;davidson 604 56  |r|= 0.402   max|de|= -0.0317  lindep= 0.0255&#xA;davidson 605 79  |r|= 0.35    max|de|= -0.0622  lindep= 0.0292&#xA;davidson 606 28  |r|= 0.271   max|de|=  0.0528  lindep= 0.222&#xA;davidson 607 56  |r|= 0.427   max|de|= -0.0196  lindep= 0.0186&#xA;davidson 608 81  |r|= 0.405   max|de|= -0.0856  lindep= 0.0531&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It's good to see that the &lt;code&gt;|r|&lt;/code&gt; values match:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;converged 15 59  |r|= 0.00244 max|de|= -2.53e-06&#xA;davidson 0   27  |r|= 0.00244 max|de|=  1.02    lindep= 0.809&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the &lt;code&gt;max|de|&lt;/code&gt; value for the &lt;code&gt;davidson 0&lt;/code&gt; in the &amp;quot;restarted&amp;quot; calculation is closer to what we had at the beginning of the &lt;em&gt;&lt;strong&gt;first&lt;/strong&gt;&lt;/em&gt; calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;davidson 0  27  |r|= 0.306    max|de|=  1.28      lindep= 0.317&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the &amp;quot;restarted&amp;quot; calculation, the &lt;code&gt;|r|&lt;/code&gt; value gets bad at &lt;code&gt;davidson 1&lt;/code&gt; and the &lt;code&gt;max|de|&lt;/code&gt; and &lt;code&gt;lindep&lt;/code&gt; values go bad very soon after.&lt;/p&gt;&#xA;&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;Why is the restart not working in the second case, like it did for the first case?&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T15:41:55.297" Title="Why is my CISD restart failing in PySCF?" Tags="|python|high-performance-computing|pyscf|configuration-interaction|high-precision|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10454" PostTypeId="1" CreationDate="2023-02-21T08:53:16.167" Score="3" ViewCount="182" Body="&lt;p&gt;&lt;a href=&quot;https://www.reddit.com/r/Chempros/comments/1168uor/questions_on_paper_geminalbased_electronic/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cross-posted on Reddit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have been reading through [1] to get a better understanding of geminal based methods. This is one of two questions that I'm asking about that paper on this site, the other one being: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10474/5&quot;&gt;Understanding the complexity of geminal-based wavefunctions&lt;/a&gt;. This question is: &lt;strong&gt;How does expression (1) relate to Eqs. (3) and (7)?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;P. Tecmer &amp;amp; K. Boguslawski Phys. Chem. Chem. Phys., 2022,24, 23026-23048 &lt;a href=&quot;https://doi.org/10.1039/D2CP02528K&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6757" LastEditorUserId="5" LastEditDate="2023-02-25T02:36:18.187" LastActivityDate="2023-02-25T02:36:18.187" Title="Understanding derivation of geminal based methods" Tags="|quantum-chemistry|electronic-structure|mathematical-modeling|wavefunctions|geminal-wavefunctions|" AnswerCount="0" CommentCount="9" ClosedDate="2023-03-12T22:25:10.267" ContentLicense="CC BY-SA 4.0" />
  <row Id="10455" PostTypeId="1" CreationDate="2023-02-21T10:21:30.283" Score="4" ViewCount="81" Body="&lt;p&gt;I study reaction A + B → C + D  in a water using DFT. I think I should apply some kind of correction over RRHO because it is not true in a solvent. I found the given work (&lt;a href=&quot;https://doi.org/10.1021/jp980229p&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jp980229p&lt;/a&gt;) and got to the point of calculating that &lt;code&gt;p=1358 atmospheres&lt;/code&gt;...&#xA;How could I now apply it for Gibbs free energies / reaction barriers?&#xA;Best&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-02-27T23:07:42.027" Title="How to apply solvent-correction to Gaussian derived Gibbs energies?" Tags="|density-functional-theory|quantum-chemistry|quantum-mechanics|statistical-thermodynamics|thermodynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10456" PostTypeId="2" ParentId="10450" CreationDate="2023-02-21T14:06:12.280" Score="2" Body="&lt;p&gt;Answer: no, you don't need to include those parameters (Rwp, RI, Rf) in your CIF file.&lt;/p&gt;&#xA;&lt;p&gt;If you want to visualize the space where the atom can move due thermal effects, you should add the atomic displacement parameter B.&lt;/p&gt;&#xA;&lt;p&gt;Those parameters (Rwp, RI, Rf) have to do with the &lt;a href=&quot;https://en.wikipedia.org/wiki/Rietveld_refinement&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rietveld refinement method&lt;/a&gt; and MEM-based pattern fitting used to determine the crystal structure from a powder diffraction pattern and electronic density data:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Figure of merits:&lt;br /&gt;&#xA;Since refinement depends on finding the best fit&#xA;between a calculated and experimental pattern, it is important to have&#xA;a numerical figure of merit quantifying the quality of the fit. Below&#xA;are the figures of merit generally used to characterize the quality of&#xA;a refinement. They provide insight to how well the model fits the&#xA;observed data.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;From Rietveld refinement&lt;/h3&gt;&#xA;&lt;p&gt;Profile residual (reliability factor):&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle R_{p}=\sum _{i}^{n}{\frac {|Y_{i}^{\text{obs}}-Y_{i}^{\text{calc}}|}{\sum _{i}^{n}Y_{i}^{\text{obs}}}}\times 100\%}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Weighted profile residual: Weighted profile residual:&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle R_{wp}=\left(\sum _{i}^{n}{\frac {w_{i}(Y_{i}^{\text{obs}}-Y_{i}^{\text{calc}})^{2}}{\sum _{i}^{n}w_{i}(Y_{i}^{\text{obs}})^{2}}}\right)^{\frac {1}{2}}\times 100\%}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Bragg residual:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle R_{B}=\sum _{j}^{m}{\frac {|I_{j}^{\text{obs}}-I_{j}^{\text{calc}}|}{\sum _{i}^{n}I_{j}^{\text{obs}}}}\times 100\%}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Expected profile residual:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle R_{\text{exp}}=\left({\frac {n-p}{\sum _{i}^{n}w_{i}(Y_{i}^{\text{obs}})^{2}}}\right)^{\frac {1}{2}}\times 100\%}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Goodness of fit:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle \mathrm {X} ^{2}=\sum _{i}^{n}{\frac {(Y_{i}^{\text{obs}}-Y_{i}^{\text{calc}})^{2}}{n-p}}=\left({\frac {R_{wp}}{R_{\text{exp}}}}\right)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;From Maximum Entropy Method (MEM) based pattern fitting (MPF)&lt;/h3&gt;&#xA;&lt;p&gt;Reliability factor:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$${\displaystyle R_{l}=\sum _{h}{\frac {|I^{\text{obs}}(h)-I^{\text{calc}}(h)|}{\sum _{h}I^{\text{obs}}(h)}}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;H. M. Rietveld. &lt;em&gt;A profile refinement method for nuclear and magnetic structures&lt;/em&gt;. Journal of Applied Crystallography, 2(2), 65–71 (1969). doi:&lt;a href=&quot;https://doi.org/10.1107/s0021889869006558&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1107/s0021889869006558&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;M. Takata , E. Nishibori and M. Sakata. &lt;em&gt;Charge density studies utilizing powder diffraction and MEM. Exploring of high Tc superconductors, C60 superconductors and manganites&lt;/em&gt;. Zeitschrift für Kristallographie - Crystalline Materials. 216, 71–86 (2001). doi:&lt;a href=&quot;https://doi.org/10.1524/zkri.216.2.71.20335&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1524/zkri.216.2.71.20335&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;F. Izumi. &lt;em&gt;Beyond the ability of Rietveld analysis: MEM-based pattern fitting.&lt;/em&gt;. Solid State Ionics 172, 1–6 (2004). doi:&lt;a href=&quot;https://doi.org/10.1016/j.ssi.2004.04.023&quot; rel=&quot;nofollow noreferrer&quot;&gt;10.1016/j.ssi.2004.04.023&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-02-21T14:06:12.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10457" PostTypeId="2" ParentId="9336" CreationDate="2023-02-21T14:27:11.700" Score="3" Body="&lt;p&gt;I created the script bellow to extract the data I'm interested in from all MOPAC out files put inside a given folder and create a CSV file with all the data:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/sh&#xA;#script to extract information from the output MOPAC file&#xA;#Use:&#xA;# ./fromMOPAC.sh folder_name&#xA;#&#xA;#The folder_name is a folder where all the MOPAC output files (.out) are located. A file with the name of the folder will be created with the data.&#xA;#&#xA;#&#xA;&#xA;for filename in $1/*.out&#xA;do&#xA;&#xA;HeatF=&lt;span class=&quot;math-container&quot;&gt;$(grep &quot;FINAL HEAT OF FORMATION =      &quot; $&lt;/span&gt;filename | grep '='| awk '{printf &amp;quot;%12.6f \n&amp;quot;,&lt;span class=&quot;math-container&quot;&gt;$6}')&#xA;TotalEnergy=$&lt;/span&gt;(grep &amp;quot;TOTAL ENERGY            =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$4}')&#xA;DispE=$&lt;/span&gt;(grep &amp;quot;DISPERSION ENERGY       =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$4}')&#xA;HBondE=$&lt;/span&gt;(grep &amp;quot;H-BOND ENERGY           =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$4}')&#xA;NHBonds=$&lt;/span&gt;(grep &amp;quot;No. OF HYDROGEN BONDS   =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$6}')&#xA;IonPot=$&lt;/span&gt;(grep &amp;quot;IONIZATION POTENTIAL    =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$4}')&#xA;AlphaSOMO=$&lt;/span&gt;(grep &amp;quot;ALPHA SOMO LUMO (EV)    =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$6}')&#xA;AlphaLUMO=$&lt;/span&gt;(grep &amp;quot;ALPHA SOMO LUMO (EV)    =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$7}')&#xA;BetaSOMO=$&lt;/span&gt;(grep &amp;quot;BETA  SOMO LUMO (EV)    =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$6}')&#xA;BetaLUMO=$&lt;/span&gt;(grep &amp;quot;BETA  SOMO LUMO (EV)    =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$7}')&#xA;HOMO=$&lt;/span&gt;(grep &amp;quot;HOMO LUMO ENERGIES (EV) =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$6}')&#xA;LUMO=$&lt;/span&gt;(grep &amp;quot;HOMO LUMO ENERGIES (EV) =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$7}')&#xA;CosmoArea=$&lt;/span&gt;(grep &amp;quot;COSMO AREA              =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$4}')&#xA;CosmoVolume=$&lt;/span&gt;(grep &amp;quot;COSMO VOLUME            =&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$filename | grep '='| awk '{printf &quot;%12.6f \n&quot;,$&lt;/span&gt;4}')&#xA;&#xA;var1=&lt;span class=&quot;math-container&quot;&gt;$(echo $&lt;/span&gt;TotalEnergy | cut -f1 -d' ')&#xA;var2=&lt;span class=&quot;math-container&quot;&gt;$(echo $&lt;/span&gt;TotalEnergy | cut -f2 -d' ')&#xA;TotalEkcal=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$var1&quot;&#xA;TotalEeV=&quot;$&lt;/span&gt;var2&amp;quot;&#xA;&#xA;if [ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$DispE&quot; = &quot;&quot; ];&#xA;then&#xA;   DispE=&quot;-----&quot;&#xA;fi&#xA;if [ &quot;$&lt;/span&gt;HBondE&amp;quot; = &amp;quot;&amp;quot; ];&#xA;then&#xA;   HBondE=&amp;quot;-----&amp;quot;&#xA;fi&#xA;if [ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$NHBonds&quot; = &quot;&quot; ];&#xA;then&#xA;   NHBonds=&quot;-----&quot;&#xA;fi&#xA;if [ &quot;$&lt;/span&gt;IonPot&amp;quot; = &amp;quot;&amp;quot; ];&#xA;then&#xA;   IonPot=&amp;quot;-----&amp;quot;&#xA;fi&#xA;if [ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$AlphaSOMO&quot; = &quot;&quot; ];&#xA;then&#xA;   AlphaSOMO=&quot;-----&quot;&#xA;fi&#xA;if [ &quot;$&lt;/span&gt;AlphaLUMO&amp;quot; = &amp;quot;&amp;quot; ];&#xA;then&#xA;   AlphaLUMO=&amp;quot;-----&amp;quot;&#xA;fi&#xA;if [ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$BetaSOMO&quot; = &quot;&quot; ];&#xA;then&#xA;   BetaSOMO=&quot;-----&quot;&#xA;fi&#xA;if [ &quot;$&lt;/span&gt;BetaLUMO&amp;quot; = &amp;quot;&amp;quot; ];&#xA;then&#xA;   BetaLUMO=&amp;quot;-----&amp;quot;&#xA;fi&#xA;if [ &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$HOMO&quot; = &quot;&quot; ];&#xA;then&#xA;   HOMO=&quot;-----&quot;&#xA;fi&#xA;if [ &quot;$&lt;/span&gt;LUMO&amp;quot; = &amp;quot;&amp;quot; ];&#xA;then&#xA;   LUMO=&amp;quot;-----&amp;quot;&#xA;fi&#xA;&#xA;&#xA;echo &lt;span class=&quot;math-container&quot;&gt;$filename, $&lt;/span&gt;HeatF, &lt;span class=&quot;math-container&quot;&gt;$TotalEkcal, $&lt;/span&gt;TotalEeV, &lt;span class=&quot;math-container&quot;&gt;$DispE, $&lt;/span&gt;HBondE, &lt;span class=&quot;math-container&quot;&gt;$NHBonds, $&lt;/span&gt;IonPot, &lt;span class=&quot;math-container&quot;&gt;$AlphaSOMO, $&lt;/span&gt;AlphaLUMO, &lt;span class=&quot;math-container&quot;&gt;$BetaSOMO, $&lt;/span&gt;BetaLUMO, &lt;span class=&quot;math-container&quot;&gt;$HOMO, $&lt;/span&gt;LUMO, &lt;span class=&quot;math-container&quot;&gt;$CosmoArea, $&lt;/span&gt;CosmoVolume &amp;gt;&amp;gt; &lt;span class=&quot;math-container&quot;&gt;$1.t379x24&#xA;done&#xA;echo 'Filename', 'Heat of formation (kcal/mol)', 'Total Energy (kcal/mol)', 'Total Energy (eV)', 'Dispersion Energy (eV)', 'H-BOND Ebergy (eV)', 'No. HBonds', 'Ionization Potential (eV)', 'AlphaSOMO (eV)', 'AlphaLUMO (eV)', 'BetaSOMO (eV)', 'BetaLUMO (eV)', 'HOMO (eV)', 'LUMO (eV)', 'COSMO AREA (square angstroms)', 'COSMO VOLUME (cubic angstroms)' &amp;gt;&amp;gt; t379x24&#xA;cat t379x24 $&lt;/span&gt;1.t379x24 &amp;gt; &lt;span class=&quot;math-container&quot;&gt;$1.csv&#xA;rm -f t379x24 $&lt;/span&gt;1.t379x24&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-02-21T14:27:11.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10458" PostTypeId="1" CreationDate="2023-02-21T16:46:31.217" Score="5" ViewCount="207" Body="&lt;p&gt;I primarily use Thermo-Calc so I will use that to describe my problem but I am interested to hear general CALPHAD insight as well.&lt;/p&gt;&#xA;&lt;p&gt;Using Thermo-Calc I can quickly get an idea of the phase regions present (isothermally) by running a phase diagram calculation &lt;em&gt;for a ternary&lt;/em&gt;. What appeals to me most about this is how fast the calculation is (as opposed to having to run ~5000 single eq calcs to get an idea of the phase regions). I have a vague understanding that behind the scenes Thermo-Calc is zeroing on each of the phase boundaries and so only has to do a limited number of calculations. In Thermo-Calc and TC-Python it only seems possible to do this for binary and ternary systems (e.g., using &amp;quot;with_phase_diagram_calculation()&amp;quot; in TC-Python it seems to only let me specify &amp;quot;with_first_axis&amp;quot; and &amp;quot;with_second_axis&amp;quot;). I guess they don't have this implemented because you can't easily visualize quaternaries,  etc., but I am interested in still extracting the data relating to the phase regions/boundaries. &lt;strong&gt;So, my question is how can I extract this phase data using TC-Python for an arbitrary system of elements?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;A secondary question I would be interested to hear an answer to is how exactly Thermo-Calc (or other CALPHAD implementations) calculate the phase region/boundary information so quickly.&lt;/p&gt;&#xA;" OwnerUserId="1410" LastActivityDate="2023-08-21T21:22:03.510" Title="How to calculate phase regions using CALPHAD for higher order systems (&gt;3 elements)?" Tags="|python|free-energy|calphad|thermo-calc|phase-diagram|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10460" PostTypeId="1" AcceptedAnswerId="11787" CreationDate="2023-02-21T21:58:53.157" Score="2" ViewCount="65" Body="&lt;p&gt;I created a CIF file using the experimental data from literature . After doing a 'vc-relax' calculation do I have to change the lattice parameter, CELL_PARAMETERS and ATOMIC_POSITIONS in my input file, and use this new input file to calculate all the properties of the material?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-10-22T06:34:03.130" Title="Are the cell parameters found after doing a 'vc-relax' calculation the ones used to calculate the material properties?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|physical-properties-of-materials|cell-optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10461" PostTypeId="1" AcceptedAnswerId="10549" CreationDate="2023-02-22T09:05:05.153" Score="5" ViewCount="172" Body="&lt;p&gt;I was wondering if there were any reliable algorithms out there that could allocate bond orders and formal charges of a given molecular structure if just the atomic coordinates (x,y,z) and atom type were present in a file (C, N, O, H, etc...). The atoms are most likely ones found in organic molecules so complicated heavy metals with multiple charged states are unlikely.&lt;/p&gt;&#xA;&lt;p&gt;In a step within a molecular modelling workflow, I only have a set of atomic coordinates but no explicit bond or charge information is kept so I need re-derive them as the coordinates have changed (within reasonable extents like bond lengths) relative to the ones from the input structure which has the bond and charge information. So taking the bond and charge information from the input structure probably won't be feasible.&lt;/p&gt;&#xA;&lt;p&gt;Any references to papers with code would be really helpful for this.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="6762" LastActivityDate="2023-04-13T15:27:26.850" Title="An algorithm for implicit bond order and charge allocation for atomic coordinates?" Tags="|computational-chemistry|structural-biology|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10462" PostTypeId="1" CreationDate="2023-02-22T13:40:18.180" Score="5" ViewCount="384" Body="&lt;p&gt;I want to dope my material by substitution, and I'm using Quantum Espresso. In previous works I found that they calculate the formation energy then plot a  diagrams as the picture bellow. Normally the fermi level is represented just by one value and in the picture there are more values of fermi level in the x-axis !&#xA;Can someone show me how can I make that kind of diagrams? Thank you!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/67ha7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/67ha7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-24T13:33:16.673" LastActivityDate="2023-02-24T13:33:16.673" Title="How to plot the formation energy versus Fermi level?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|doping|formation-energy|" AnswerCount="0" CommentCount="7" ClosedDate="2023-11-08T00:22:01.550" ContentLicense="CC BY-SA 4.0" />
  <row Id="10463" PostTypeId="1" CreationDate="2023-02-22T14:25:38.037" Score="4" ViewCount="614" Body="&lt;p&gt;I have written a python script to do global optimisation on interatomic potential (IP) using Metropolis Monte Carlo.&lt;/p&gt;&#xA;&lt;p&gt;I have attached the part of the script which is the Metropolis MC part.&lt;/p&gt;&#xA;&lt;p&gt;I have plotted the plot: IP energy (no Coulomb interaction in the energy) as a function of step number (from the first accepted order to the last).&lt;/p&gt;&#xA;&lt;p&gt;I expect the plot shows the negative trend data because I expect it converges as the step increases. However, it is not.&lt;/p&gt;&#xA;&lt;p&gt;Is the plot represent the Markov chain?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wsENF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wsENF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Initialize variables&#xA;energy_previous = 0.0&#xA;energy_vec = []&#xA;&#xA;while step_cnt &amp;lt; max_steps:&#xA;    # Calculate energy of proposed configuration&#xA;    IP_energy = calculate_energy(proposed_configuration)&#xA;&#xA;    if step_cnt == 0:&#xA;        energy_previous = IP_energy&#xA;        step_cnt = 1&#xA;    else:&#xA;        delta = IP_energy - energy_previous&#xA;        energy_tol = np.random.uniform()&#xA;&#xA;        # Accept or reject the new configuration based on the Metropolis-Hastings criterion&#xA;        if energy_tol &amp;lt; np.exp(-delta):&#xA;            energy_vec.append(IP_energy)    # store the accepted structure energy&#xA;            energy_previous = IP_energy&#xA;&#xA;        # update the proposed configuration for the next iteration&#xA;        proposed_configuration = update_configuration(proposed_configuration)&#xA;        step_cnt += 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the output of &lt;br&gt;&#xA;step_no, IP_energy, previous_energy, delta, energy_tol, np.exp(-delta), energy_tol &amp;lt; np.exp(-delta)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 1   -0.00179377    -0.00967768     0.00788391  0.08959475  0.99214709  True&#xA; 2   17.20824264    -0.00179377     17.21003641     0.47674332  0.00000003  False&#xA; 2   -0.02482590    -0.00179377     -0.02303213     0.94119261  1.02329942  True&#xA; 3   -0.02276726    -0.02482590     0.00205864  0.46212012  0.99794348  True&#xA; 4   -0.00245595    -0.02276726     0.02031131  0.03979358  0.97989358  True&#xA; 5   -0.01868081    -0.00245595     -0.01622486     0.76820130  1.01635720  True&#xA; 6   -0.00820708    -0.01868081     0.01047373  0.36041987  0.98958093  True&#xA; 7   -0.01322191    -0.00820708     -0.00501483     0.95599216  1.00502743  True&#xA; 8   -0.01875933    -0.01322191     -0.00553742     0.35053292  1.00555278  True&#xA; 9   3.28646223     -0.01875933     3.30522156  0.57247874  0.03669108  False&#xA; 9   -0.00338494    -0.01875933     0.01537439  0.44678120  0.98474319  True&#xA;10   0.00644749     -0.00338494     0.00983243  0.04497439  0.99021575  True&#xA;... so on&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="748" LastEditorUserId="5" LastEditDate="2023-02-23T17:08:17.457" LastActivityDate="2023-02-24T05:21:16.140" Title="Python script for Metropolis Monte Carlo (global optimisation)" Tags="|python|monte-carlo|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10464" PostTypeId="2" ParentId="10463" CreationDate="2023-02-22T17:47:31.453" Score="8" Body="&lt;p&gt;My original answer is below, but I don't think it solves your problem, because your problem is a bit deeper...&lt;/p&gt;&#xA;&lt;p&gt;if a move isn't accepted, you need to keep your old configuration, and make a new move from it. If it is accepted, then you make your next move from your new configuration. I do not see any mechanism for doing this properly in your code.&lt;/p&gt;&#xA;&lt;p&gt;The code appears to always update from the proposed configuration. You need to be able to revert back to the old configuration if the move is not accepted.&lt;/p&gt;&#xA;&lt;h2&gt;Old Answer - not wrong, but not quite right...&lt;/h2&gt;&#xA;&lt;p&gt;Your current code updates the configuration regardless of the Metropolis criteria passing or not - &lt;code&gt;proposed_configuration = update_configuration(proposed_configuration)&lt;/code&gt; needs to be indented into that &lt;code&gt;if&lt;/code&gt; statement above it.&lt;/p&gt;&#xA;&lt;p&gt;You are also only appending energy if the move succeeds, but, you should be appending the old energy if your move fails. This will mess up your average energy if you only save the energy of the configuration when a move is accepted. A failed move does not negate the current configuration, a failed move means the move was to the current configuration rather than the proposed configuration.&lt;/p&gt;&#xA;&lt;p&gt;Allen and Tildesley have lots of good Python code examples for Monte Carlo:&#xA;&lt;a href=&quot;https://github.com/Allen-Tildesley/examples/blob/master/python_examples/mc_nvt_lj.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Allen-Tildesley/examples/blob/master/python_examples/mc_nvt_lj.py&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="181" LastEditorUserId="181" LastEditDate="2023-02-23T04:38:14.273" LastActivityDate="2023-02-23T04:38:14.273" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10465" PostTypeId="1" AcceptedAnswerId="10467" CreationDate="2023-02-22T19:46:05.200" Score="7" ViewCount="385" Body="&lt;p&gt;I am trying to write a Python/C++ code that reads in a *.xyz file and varies the interatomic distances, angles etc. between distinct atoms in a molecule. In other words, a complete new structure with varied bond lengths should be generated. It's clear to me how to calculate the distance in cartesian coordinates between two points (atoms) P and Q.&lt;/p&gt;&#xA;&lt;p&gt;For a better understanding I used this Methanol structure provided by the Avogadro suite:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;6&#xA;H          0.84754        0.03474        1.03453&#xA;C          0.35048        0.00675        0.06084&#xA;H          0.63507        0.89276       -0.52007&#xA;H          0.66294       -0.89338       -0.48283&#xA;O         -1.01083       -0.00823        0.36439&#xA;H         -1.48520       -0.03263       -0.45685&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, when I manually vary the bond length between the atoms C-O by 0.1 Angstrom in Avogadro, e.g., in Methanol I have difficulties understanding how to find the new cartesian coordinates that are translated/transformed in the newly generated structure:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;6&#xA;H          0.94513        0.03581        1.01277&#xA;C          0.44807        0.00782        0.03908&#xA;H          0.73266        0.89383       -0.54183&#xA;H          0.76053       -0.89231       -0.50459&#xA;O         -1.01083       -0.00823        0.36439&#xA;H         -1.48520       -0.03263       -0.45685&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could someone explain to me the mathematical step for generating this new set of cartesian coordinates or direct me to an example?&lt;/p&gt;&#xA;&lt;p&gt;By looking into the Header files of Avogadro, I can tell that computationally one needs to or can use the API, i.e., the main module of Eigen which allows dense matrix and array manipulation.&lt;/p&gt;&#xA;&lt;p&gt;I am grateful for any help!&lt;/p&gt;&#xA;" OwnerUserId="6763" LastEditorUserId="5" LastEditDate="2023-02-23T17:07:01.110" LastActivityDate="2023-03-02T19:43:08.123" Title="Generate structure using atomic coordinates" Tags="|computational-chemistry|python|crystallography|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10466" PostTypeId="1" CreationDate="2023-02-22T23:26:45.043" Score="3" ViewCount="89" Body="&lt;p&gt;I have been trying to understand the &lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian optimiser&lt;/a&gt; (Berny optimiser algorithm) from what has been written in their manual. So far, I have understood most of it, but one part has been giving me trouble as there is no mathematical equation there.&lt;/p&gt;&#xA;&lt;p&gt;Copied from the manual:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If a minimum is sought, perform a linear search between the latest point and the best previous point (the previous point having lowest energy). If &lt;strong&gt;second derivatives are available&lt;/strong&gt; at both points and a minimum is sought, a quintic polynomial fit is attempted first; if it does not have a minimum in the acceptable range (see below) or if second derivatives are not available, a constrained quartic fit is attempted. This fits a quartic polynomial to the &lt;strong&gt;energy and first derivative (along the connecting line)&lt;/strong&gt; at the two points with the constraint that ...&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I understand that linear search is essentially doing a search in 1-dimension. If the 1D search is between two points, then I could project the gradient along the vector between the two points. The gradient is a N-dimensional vector, and the search dimension is also an N-dimensional vector (N is the total number of coordinates). So projection would be a straightforward dot product between the two vectors (taking the search direction as unit vector). This would give me the first derivative (gradient) along the search direction (&lt;span class=&quot;math-container&quot;&gt;$\hat{r}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$g_\mathrm{1D} = \vec{g}\cdot\hat{r}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But before that they mention that they use second derivatives (Hessian) if available. But Hessian is a (N &lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt; N) matrix, but for a 1D search, I need only the second derivative (which is only a scalar number) along the search direction. I can't think of a way to get a scalar number from a matrix and a vector. &lt;strong&gt;How do you get the second derivative along a vector direction from a full Hessian matrix?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have a vague understanding that Hessian would be a tensor (?), which would have to be treated differently than vectors but I do not have enough mathematical background to understand how to get the 1D second derivative from the full Hessian matrix (This question is kind of unrelated to Gaussian, because I am asking a general mathematical question). Also the Gaussian manual does not give any reference for that part so I didn't have a paper that I could read.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-02-25T11:44:19.080" LastActivityDate="2023-10-21T15:48:25.793" Title="How do you project the Hessian along a certain vector?" Tags="|geometry-optimization|optimization|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10467" PostTypeId="2" ParentId="10465" CreationDate="2023-02-23T10:57:36.283" Score="10" Body="&lt;p&gt;To understand the new coordinates after altering the bond length of the C-O bonds you can use the below approach:&lt;/p&gt;&#xA;&lt;p&gt;Let us first visualize the positions of all the atoms before and after altering the bond length:&lt;a href=&quot;https://i.stack.imgur.com/Sgffk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Sgffk.png&quot; alt=&quot;positions_of_atoms_in_CH3OH&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The atoms with * are the atoms at the new coordinates after bond altering.&lt;/p&gt;&#xA;&lt;p&gt;So imagine a vector from the O atom to the C atom.&#xA;We would like to get the new coordinates of the C atom after increasing the distance between the current C atom and the O atom by 0.1 Angstrom.&lt;/p&gt;&#xA;&lt;p&gt;This can be achieved by the following formula:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;D = dist_O_and_C_before_bond_alter + 0.1&#xA;C_atom_new_pos_vector = O_vector_atom_before_alter + D * OC_unit_vector&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So to calculate &lt;strong&gt;&lt;code&gt;C_atom_new_pos_vector&lt;/code&gt;&lt;/strong&gt; we need to calculate three other elements: &lt;code&gt;{2 scalars: (dist_O_and_C_before_bond_alter, D) and 1 vector: OC_unit_vector}&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code to calculate all these elements is shown below in python:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atom_coords_before_bond_alter = np.array([&#xA;[0.84754,0.03474,1.03453], # H&#xA;[0.35048,0.00675,0.06084], # C&#xA;[0.63507,0.89276,-0.52007], # H&#xA;[0.66294,-0.89338,-0.48283], # H&#xA;[-1.01083,-0.00823,0.36439], # O&#xA;[-1.48520,-0.03263,-0.45685] #H&#xA;])&#xA;&#xA;def get_dist(atom_1_coords, atom_2_coords):&#xA;  x_1 = atom_1_coords[0]&#xA;  y_1 = atom_1_coords[1]&#xA;  z_1 = atom_1_coords[2]&#xA;&#xA;  x_2 = atom_2_coords[0]&#xA;  y_2 = atom_2_coords[1]&#xA;  z_2 = atom_2_coords[2]&#xA;&#xA;  d = ( (x_1-x_2)**2 + (y_1-y_2)**2+ (z_1-z_2)**2 )**0.5&#xA;  return d&#xA;&#xA;dist_O_and_C_before_bond_alter = get_dist(atom_coords_before_bond_alter[1],atom_coords_before_bond_alter[4])&#xA;&#xA;C_vector_atom_before_alter = atom_coords_before_bond_alter[1]&#xA;O_vector_atom_before_alter = atom_coords_before_bond_alter[4]&#xA;OC_dir_vector = C_vector_atom_before_alter - O_vector_atom_before_alter&#xA;&#xA;OC_vector_magnitude = np.sqrt(np.sum([comp**2 for comp in OC_dir_vector]))&#xA;OC_unit_vector = OC_dir_vector/OC_vector_magnitude&#xA;D = dist_O_and_C_before_bond_alter + 0.1&#xA;&#xA;C_atom_new_pos_vector = O_vector_atom_before_alter + D * OC_unit_vector&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let us now print &lt;strong&gt;&lt;code&gt;C_atom_new_pos_vector&lt;/code&gt;&lt;/strong&gt;;&#xA;This outputs &amp;gt;&amp;gt; &lt;code&gt;array([0.44807731, 0.00782397, 0.03907739])&lt;/code&gt;&#xA;which matches the vector that you get from Avagadro for the new position&#xA;of the C atom after bond altering&lt;/p&gt;&#xA;&lt;p&gt;So similarly, you can calculate the new positions of the other atoms to understand the new coordinates of the other atoms.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-02-24T13:16:12.083" LastActivityDate="2023-02-24T13:16:12.083" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10468" PostTypeId="2" ParentId="10463" CreationDate="2023-02-23T11:43:21.570" Score="5" Body="&lt;p&gt;A properly-run Metropolis Monte Carlo algorithm does &lt;em&gt;not&lt;/em&gt; perform global optimisation. It returns the &lt;a href=&quot;https://www.probabilitycourse.com/chapter11/11_3_2_stationary_and_limiting_distributions.php#:%7E:text=In%20theory%2C%20we%20can%20find,%E2%86%92%E2%88%9EP(t).&quot; rel=&quot;nofollow noreferrer&quot;&gt;stationary distribution&lt;/a&gt; of a random process.&lt;/p&gt;&#xA;&lt;p&gt;In this case, you have specified an acceptance rule that higher energies should be accepted at an exponentially-decreasing rate. And guess what? Your plot indeed shows that higher energies occur, and exponentially less often as the energy increases. In other words you have &lt;em&gt;sampled the Boltzmann distribution&lt;/em&gt; of whatever process it is you were modelling.&lt;/p&gt;&#xA;&lt;p&gt;Global optimisation is a completely different problem. The only Monte Carlo approach I know of to global optimisation is simulated annealing, which is not what you have implemented.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-02-24T05:21:16.140" LastActivityDate="2023-02-24T05:21:16.140" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10469" PostTypeId="1" CreationDate="2023-02-23T18:25:22.447" Score="3" ViewCount="90" Body="&lt;p&gt;when I produce a band structure plot using XMGRACE after running a CASTEP Bandstructure calculation I would like to have the bottom of the band gap to be zeroed. Is there an easy way to shift the axis, or have the initial calculation run such that the gap us inline with 0 eV?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Hqo1G.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Hqo1G.png&quot; alt=&quot;TiO2 Bandstructure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6627" LastEditorUserId="5" LastEditDate="2023-02-23T18:55:57.350" LastActivityDate="2023-02-26T18:20:15.267" Title="Adjusting y-axis of CASTEP band structure plots" Tags="|band-structure|visualization-software|castep|xmgrace|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10470" PostTypeId="5" CreationDate="2023-02-23T18:56:57.197" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Grace_(plotting_tool)&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Grace_(plotting_tool)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-23T18:56:57.197" LastActivityDate="2023-02-23T18:56:57.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10471" PostTypeId="4" CreationDate="2023-02-23T18:56:57.197" Score="0" Body="Questions about or related to the plotting software Grace/XMgrace." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-23T18:56:57.197" LastActivityDate="2023-02-23T18:56:57.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10472" PostTypeId="1" AcceptedAnswerId="10482" CreationDate="2023-02-23T19:24:26.907" Score="3" ViewCount="352" Body="&lt;p&gt;I'm trying to do a SCAN calculation in the ORCA program version 5.0.3 in which, at a certain moment of the carbon-carbon bond breakage, the following error message appears:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WARNING! Potentially linear dependencies in the auxiliary basis&#xA;===&amp;gt;&amp;gt;    At the moment, SHARK is not equipped to deal with this&#xA;[file orca_tools/Tool-GTO-Integrals/SHARK/shark.cpp, line 334, Process 0]:  ... sorry, have to bail out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input header is this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! wb97x-d3 def2-SVP def2/J def2-SVP/C opt RIJCOSX AutoAux MINIPRINT &#xA;%geom Scan B 0 1 = 1.52, 4.00, 50 end end&#xA;* xyz 0 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Would this error come out if I remove the auxiliary bases? or just use a better base like def2-TZVP? or both?&lt;/p&gt;&#xA;" OwnerUserId="6576" LastActivityDate="2023-02-25T05:57:26.930" Title="Orca calculation with scan error related with auxiliary basis" Tags="|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10473" PostTypeId="1" CreationDate="2023-02-23T23:28:30.267" Score="4" ViewCount="47" Body="&lt;p&gt;Within the Poisson-Boltzmann formalism the boundary conditions are often chosen such as &lt;span class=&quot;math-container&quot;&gt;$\phi^{S}$&lt;/span&gt;, the electrostatic potential in bulk solution far away from the interface (Galvani potential) is equal to 0. Additionally because the nature of the interaction are only electrostatic in the solution we have &lt;span class=&quot;math-container&quot;&gt;$\mu_{e}^{S} = 0$&lt;/span&gt; as well.&lt;/p&gt;&#xA;&lt;p&gt;So if we want to compute the absolute potential in this framework we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{abs}^{mPB} = \mu_{e}^{S} - \mu_{e}^{M} - (\phi^{S} - \phi^{M}) = - \mu_{e}^{M} + \phi^{M} = -\tilde{\mu_{e}}^{M}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;a href=&quot;https://doi.org/10.1063/1.5047829&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.5047829&lt;/a&gt; II.E)&lt;/p&gt;&#xA;&lt;p&gt;First of all, I am confused because for me the inner potential of the electrode (&lt;span class=&quot;math-container&quot;&gt;$\phi^{M}$&lt;/span&gt;) was always equal to the Fermi energy (with a sign) = &lt;span class=&quot;math-container&quot;&gt;$-\mu_{e}^{M}$&lt;/span&gt; which doesn't make sense here, could someone clarify?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: It's been a while since I asked this question and I can now add some more details. The fermi Energy is &lt;span class=&quot;math-container&quot;&gt;$-\tilde{\mu_{e}}^{M}$&lt;/span&gt; the electrochemical potential and not &lt;span class=&quot;math-container&quot;&gt;$- \mu_{e}^{M}$&lt;/span&gt; if we trust the same paper. My question now is, how do we obtain &lt;span class=&quot;math-container&quot;&gt;$\phi_{M}$&lt;/span&gt; from a DFT calculation?&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="3934" LastEditDate="2023-10-21T17:24:38.687" LastActivityDate="2023-10-21T17:24:38.687" Title="Modified Poisson-Boltzmann confusion about chemical potential and electrostatic potential" Tags="|density-functional-theory|implicit-solvent|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10474" PostTypeId="1" AcceptedAnswerId="10476" CreationDate="2023-02-24T07:05:20.357" Score="2" ViewCount="106" Body="&lt;p&gt;&lt;a href=&quot;https://www.reddit.com/r/Chempros/comments/1168uor/questions_on_paper_geminalbased_electronic/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cross-posted on Reddit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10454/understanding-derivation-of-geminal-based-methods&quot;&gt;I have been reading&lt;/a&gt; through [1] to get a better understanding of geminal-based methods. Some short passages are included below:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The occupation of each orbital in the expansion above (Eq. 5) is indicated by the summation index &lt;span class=&quot;math-container&quot;&gt;$m_i$&lt;/span&gt;, while the total number of occupied orbitals in each Slater determinant has to equal the number of electron pairs. The APIG wave function thus includes &lt;span class=&quot;math-container&quot;&gt;$K\choose P$&lt;/span&gt; determinants (&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is number of orbitals, &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; the number of electron pairs).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The AGP ansatz in eqn (8), a tensor product of the same geminal, represents a computationally attractive correlated wave function with very few parameters; in the most general case, the AGP scales as &lt;span class=&quot;math-container&quot;&gt;$\frac{K(K-1)}{2}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is the number of spin-orbitals.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Why does this 2nd paragraph (shortly after Expression (10) in the paper) say that AGP has a complexity of &lt;span class=&quot;math-container&quot;&gt;$O(K^2)$&lt;/span&gt;, which contradicts its own sentences for the early paragraph after expression (5) about having binomial complexity?&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;P. Tecmer &amp;amp; K. Boguslawski Phys. Chem. Chem. Phys., 2022,24, 23026-23048 &lt;a href=&quot;https://doi.org/10.1039/D2CP02528K&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6757" LastEditorUserId="5" LastEditDate="2023-02-25T02:36:32.147" LastActivityDate="2023-02-25T02:36:32.147" Title="Understanding the complexity of geminal-based wavefunctions" Tags="|quantum-chemistry|mathematical-modeling|quantum-mechanics|wavefunctions|geminal-wavefunctions|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10475" PostTypeId="2" ParentId="10002" CreationDate="2023-02-24T12:53:38.423" Score="5" Body="&lt;p&gt;I have created a python library called &lt;a href=&quot;https://github.com/vandan-revanur/pychemprojections&quot; rel=&quot;nofollow noreferrer&quot;&gt;pychemprojections&lt;/a&gt; to create such visualisations of 2D molecule projections.  (Made the first release an hour ago )&lt;/p&gt;&#xA;&lt;p&gt;It can be installed with pip like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pip install git+https://github.com/vandan-revanur/pychemprojections&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After installing, one can visualize Fischer projections, like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pychemprojections.fischer.visualization import plot_fischer_projection&#xA;input_smiles_for_fischer = &amp;quot;[C@H](CC)(C)(CO)&amp;quot;&#xA;plot_fischer_projection(input_smiles_for_fischer)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This would output the following image:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MHCt7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MHCt7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;plot_fischer_projection&lt;/code&gt; only takes SMILES which contain one or more chiral carbon atom(s).&lt;/p&gt;&#xA;&lt;p&gt;Therefore to visualise the Citrate molecule, one can do a hacky method as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pychemprojections.fischer.drawingclasses import SingleChiralFischerNotation, DrawingInfo&#xA;from pychemprojections.fischer.visualization import plot_fisher_projection_single_chiral_center&#xA;&#xA;up = '&lt;span class=&quot;math-container&quot;&gt;$CH_{2}COO-$&lt;/span&gt;' &#xA;right = '&lt;span class=&quot;math-container&quot;&gt;$COOH$&lt;/span&gt;'&#xA;left = '&lt;span class=&quot;math-container&quot;&gt;$OH$&lt;/span&gt;'&#xA;down = '&lt;span class=&quot;math-container&quot;&gt;$CH_{2}COO-$&lt;/span&gt;'&#xA;    &#xA;drawing_info = DrawingInfo(input_smiles='_', canvas_width_pixels=1000, &#xA;canvas_height_pixels=1000, smiles_preprocessed=&amp;quot;_&amp;quot;, iupac_name=&amp;quot;&amp;quot;)&#xA;    &#xA;single_chiral_fischer_notation = SingleChiralFischerNotation(up=up, down=down, &#xA;left=left, right=right)&#xA;    &#xA;plot_fisher_projection_single_chiral_center(&#xA;single_chiral_fischer_notation, &#xA;drawing_info)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This outputs the following image:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/97Xvj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/97Xvj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Epilogue&lt;/h3&gt;&#xA;&lt;p&gt;Also the &lt;a href=&quot;https://github.com/vandan-revanur/pychemprojections&quot; rel=&quot;nofollow noreferrer&quot;&gt;pychemprojections&lt;/a&gt; library has other projections implemented such as &lt;code&gt;Newman projection&lt;/code&gt;, &lt;code&gt;WedgeDash projection&lt;/code&gt;. Please do have a look and feel free to contribute in any way as outlined in the &lt;a href=&quot;https://github.com/vandan-revanur/pychemprojections/blob/master/CONTRIBUTING.md&quot; rel=&quot;nofollow noreferrer&quot;&gt;CONTRIBUTING.md&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-02-25T07:20:15.767" LastActivityDate="2023-02-25T07:20:15.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10476" PostTypeId="2" ParentId="10474" CreationDate="2023-02-24T13:14:32.733" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Why does the paragraph after expression (10) says that AGP has a complexity of O(K^2) which contradicts its own sentences just after expression (5) about having binomial complexity?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Expression 10 and Expression 5 are about different things. Expression 10 is about AGP (antisymmetrized geminal power) and Expression 5 is about APIG (antisymmetric product of interacting geminals).&lt;/p&gt;&#xA;&lt;p&gt;After Expression 5, it says that APIG includes &lt;span class=&quot;math-container&quot;&gt;$K\choose P$&lt;/span&gt;  Slater determinants. After Expression 10, it implies that APG has &lt;span class=&quot;math-container&quot;&gt;$K(K-1)/2$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$K\choose2$&lt;/span&gt; parameters. &lt;strong&gt;The key point is that APIG and APG are not the same.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-24T16:47:09.370" LastActivityDate="2023-02-24T16:47:09.370" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10477" PostTypeId="5" CreationDate="2023-02-24T13:45:57.440" Score="0" Body="&lt;p&gt;Geminal wavefunctions are ansätze that involve pairs of electrons (geminals).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-24T13:45:57.440" LastActivityDate="2023-02-24T13:45:57.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10478" PostTypeId="4" CreationDate="2023-02-24T13:45:57.440" Score="0" Body="Questions about or related to geminal **wavefunctions**. For questions about geminals associated with basis sets, please use the basis-sets tag." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-02-24T13:45:57.440" LastActivityDate="2023-02-24T13:45:57.440" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10479" PostTypeId="1" AcceptedAnswerId="10480" CreationDate="2023-01-17T19:30:54.093" Score="4" ViewCount="142" Body="&lt;p&gt;I am trying to write a python code that checks the dipole moment and the polarisability of a certain molecule in order to determine if it will be Raman-active or IR-active.&lt;/p&gt;&#xA;&lt;p&gt;Raman-active molecules are those with a change in the polarisability (so net dipole moment is zero) and IR-active are those with a change in the dipole moment (so net dipole moment is different from zero).&lt;/p&gt;&#xA;&lt;p&gt;I was trying to use PySCF as it has an attribute for the dipole moment. However, I don't exactly understand the output that PySCF provides. Checking the dipole moment for &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt; give me the same results.&lt;/p&gt;&#xA;&lt;p&gt;The idea is that I should get a number (net dipole moment) and I would have to check if it is zero or not. Does someone know how I can do it?&lt;/p&gt;&#xA;&lt;p&gt;This is the code I have tried:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf&#xA;&#xA;# Define the H2O molecule&#xA;mol = gto.M(atom='O 0 0 0; H 0 1 0; H 0 0 1', basis='sto-3g')&#xA;&#xA;# Perform a RHF calculation for the ground state&#xA;mf = scf.RHF(mol)&#xA;mf.kernel()&#xA;&#xA;# Extract the dipole moment for the ground state&#xA;ground_state_dipole = mf.dip_moment()&#xA;&#xA;# Perform a RHF calculation for the perturbed state&#xA;mf = scf.RHF(mol)&#xA;mf.charge = -1&#xA;mf.kernel()&#xA;&#xA;# Extract the dipole moment for the perturbed state&#xA;perturbed_state_dipole = mf.dip_moment()&#xA;&#xA;# Calculate the change in dipole moment&#xA;dipole_diff = perturbed_state_dipole - ground_state_dipole&#xA;print(&amp;quot;Change in dipole moment of H2O:&amp;quot;, dipole_diff)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6252" OwnerDisplayName="Joan Grebol" LastEditorUserId="7" LastEditDate="2023-02-24T16:36:28.323" LastActivityDate="2023-02-24T16:36:28.323" Title="Check whether a simple molecule is Raman-active or IR-active using PySCF" Tags="|python|spectroscopy|pyscf|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10480" PostTypeId="2" ParentId="10479" CreationDate="2023-02-09T21:02:06.227" Score="4" Body="&lt;p&gt;The dipole moment that is calculated by &lt;code&gt;mf.dip_moment()&lt;/code&gt; is a vector where the three values returned &lt;code&gt;(µx, µy, and µz)&lt;/code&gt; which are the x, y and z components of dipole moment.&lt;/p&gt;&#xA;&lt;p&gt;So the resultant magnitude of the vector is :&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&quot;https://latex.codecogs.com/svg.image?%5Csqrt%7B(%5Cmu_x%5E%7B2%7D%20+%20%5Cmu_y%5E%7B2%7D%20%20+%20%5Cmu_z%5E%7B2%7D)%7D&quot; alt=&quot;resultant_vector_magnitude&quot; /&gt;&lt;/p&gt;&#xA;&lt;p&gt;So in terms of code, it would be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dipole_moment = mf.dip_moment()&#xA;total = 0&#xA;for component in dipole_moment:&#xA;    total+= component**2&#xA;&#xA;resultant_dipole_moment = total**0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then use this &lt;code&gt;resultant_dipole_moment&lt;/code&gt; to figure out whether the compound is raman active or IR active&lt;/p&gt;&#xA;" OwnerUserId="6687" OwnerDisplayName="Vandan Revanur" LastActivityDate="2023-02-09T21:02:06.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10481" PostTypeId="2" ParentId="10444" CreationDate="2023-02-24T15:11:59.367" Score="3" Body="&lt;p&gt;As far as I know, there isn't a native way to do this, e.g. an option that can be passed to CISD. The &lt;code&gt;dump_chk&lt;/code&gt; option is never passed to &lt;code&gt;cisd.py&lt;/code&gt;, so it clearly was not meant as an option to checkpoint the Davidson iterations.&lt;/p&gt;&#xA;&lt;p&gt;However, this can be easily implemented by adding a line which saves the most recent input for the Davidson iterator. In file &lt;code&gt;pyscf/lib/linalg_helper.py&lt;/code&gt; the iterations begin on line 416. If the following is added on line 417:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;numpy.save(f&amp;quot;/path/to/checkpoint/civec_i{icyc}.npy&amp;quot;, x0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;before the next line (&lt;code&gt;if fresh_start:&lt;/code&gt;) then it will save a checkpoint (labelled with the iteration number) to the specified path.&lt;/p&gt;&#xA;&lt;p&gt;I should point out that I am working on a merge request for &lt;code&gt;pyscf&lt;/code&gt; which will contain (among other things) an option to save checkpoints after each iteration.&lt;/p&gt;&#xA;" OwnerUserId="156" LastEditorUserId="156" LastEditDate="2023-02-25T22:46:36.123" LastActivityDate="2023-02-25T22:46:36.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10482" PostTypeId="2" ParentId="10472" CreationDate="2023-02-25T05:57:26.930" Score="2" Body="&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Use of RIJCOSX in ORCA requires the use of an auxiliary basis set. So you cannot remove that. However, from your input file, I see that you have an auxiliary basis set defined (def2-SVP/C) and is also requesting for automatic generation of the auxiliary basis set (AutoAux). You can try removing either the defined auxiliary basis set, or the AutoAux keyword, and see if it helps.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;A quick google search with the same error brings up this &lt;a href=&quot;http://bbs.keinsci.com/thread-16200-1-1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt;, where someone had previously run into issues using def2-SVP/C auxiliary basis set. The suggestion then was to use a larger auxiliary basis set like def2-TVP/C or larger.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-02-25T05:57:26.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10483" PostTypeId="2" ParentId="6987" CreationDate="2023-02-25T11:18:48.867" Score="3" Body="&lt;p&gt;In &lt;strong&gt;Pymol&lt;/strong&gt;, the polar contacts can be visualised in the following way:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Enable the sequence tab by clicking on : Display -&amp;gt; Sequence&lt;/li&gt;&#xA;&lt;li&gt;Select both the protein and ligand in sequence tab&lt;/li&gt;&#xA;&lt;li&gt;In the right side tab, next to the object name, click the &lt;strong&gt;'A'&lt;/strong&gt; button -&amp;gt; find -&amp;gt; polar contacts -&amp;gt; then you will get a list of options which you can choose -&amp;gt; for example you can choose : to any atoms.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The sequence of steps shown in the below picture uses the following protein ligand combination:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Protein : Beta chain of the Human Haemoglobin (PDB ID: 2hhb)&lt;/li&gt;&#xA;&lt;li&gt;Ligand:    Corresponding HEM of the beta chain&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5rnsF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5rnsF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The polar contacts will be shown as yellow lines as shown in below picture:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zyUSr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zyUSr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can replicate the same steps with your protein + ligand choose the relevant type of polar contact from the list.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-02-25T11:18:48.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10484" PostTypeId="1" CreationDate="2023-02-25T11:51:12.133" Score="3" ViewCount="25" Body="&lt;p&gt;After doing the convergence test, 'vc-relax' and 'scf' calculations for my material using Quantum ESPRESSO everything went well. But when I wanted to do a 'bands' calculation for bandstructure I got the message &lt;code&gt;Error in routine cdiaghg (283):S matrix not positive definite&lt;/code&gt;  in the output file.&#xA;So I increased 'diago_david_ndir' to '4', the default was '2'.And the problem was fixed. But I'm just wondering if I have to repeat the whole calculations from the beginning with diago_david_ndir=4 ( Convergence test, vc-relax, scf) then perform the 'bands' calculations.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-02-25T11:51:12.133" Title="Do I have to repeat my previous calculations after increasing 'diago_david_ndir' in the input file of the bandstructure calculations?" Tags="|density-functional-theory|quantum-espresso|band-structure|physical-properties-of-materials|density-of-states|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:10:57.510" ContentLicense="CC BY-SA 4.0" />
  <row Id="10486" PostTypeId="1" CreationDate="2023-02-25T16:48:44.200" Score="6" ViewCount="44" Body="&lt;p&gt;I am a retired microwave engineer (88 yrs old) and have not had the opportunity to study or learn anything about quantum physics. I designed and built radars for the military.&lt;/p&gt;&#xA;&lt;p&gt;We found a claim that stated you could find oil and gas seeps by pumping escaping gas molecules at a band resonant frequency and raise the energy level of that population. The lifetime in the excited state was reported to be very short and when it collapses some molecules will not return to their ground state leaving an energy level according to Planck’s law.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$∆E = hf$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This will be a different frequency band from the transmit frequency, so you can tune the receiver to this frequency and the ground clutter is eliminated. In other words, use it like a transponder and any targets displayed on the radar screen at the offset frequency would be escaping hydrocarbon gasses.&lt;/p&gt;&#xA;&lt;p&gt;We wanted to verify the lifetime and collision rate, but lacked the knowledge to calculate the parameters. Pressed for time we went to the field to test the claim. No radiation could ever be detected at the offset frequency.&lt;/p&gt;&#xA;&lt;p&gt;Was the &lt;span class=&quot;math-container&quot;&gt;$∆E$&lt;/span&gt; lost in heat from collisions?&lt;/p&gt;&#xA;&lt;p&gt;After all those years we still wonder about it. All assistance will be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6776" LastEditorUserId="7" LastEditDate="2023-02-26T00:29:25.293" LastActivityDate="2023-02-26T00:29:25.293" Title="What is the lifetime of propane at standard conditions transitioning from an excited rotational state back to ground state?" Tags="|quantum-chemistry|spectroscopy|excited-states|" AnswerCount="0" CommentCount="2" ClosedDate="2023-11-05T16:20:31.333" ContentLicense="CC BY-SA 4.0" />
  <row Id="10487" PostTypeId="2" ParentId="10469" CreationDate="2023-02-25T17:25:04.427" Score="5" Body="&lt;p&gt;Yes. xmgrace allows you to do arithmetic on datasets.  To shift the minimum of the bands to zero, you need to do the following steps.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Find the maximum of the valence band along the y-axis (the VBM).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Once that is done,&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Navigate to the menu &amp;quot;data&amp;quot;-&amp;gt;&amp;quot;transformations&amp;quot;-&amp;gt;&amp;quot;evaluate expression&amp;quot;,&#xA;select all of the datasets in both &amp;quot;source&amp;quot; and &amp;quot;destination&amp;quot;, enter the formula y=y-, substituting the value of the VBM, and click &amp;quot;apply&amp;quot;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="498" LastEditorUserId="498" LastEditDate="2023-02-26T18:20:15.267" LastActivityDate="2023-02-26T18:20:15.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10489" PostTypeId="1" CreationDate="2023-02-26T09:33:08.077" Score="6" ViewCount="218" Body="&lt;p&gt;I have been trying to obtain a plot of the phonon dispersion of a BCC metal using Quantum Espresso. In the literature it seems that a commonly reported path is &lt;code&gt;Gamma-H-P-Gamma-N&lt;/code&gt; and so I am attempting to use the same. However, when I look for the k-points (q-vectors) in fractional coordinates so that I can specify them in the interpolation part of the calculation (using &lt;strong&gt;&lt;code&gt;matdyn.x&lt;/code&gt;&lt;/strong&gt;) it seems that the following coordinates are reported (I also see the following when using &lt;strong&gt;&lt;code&gt;xcrysden&lt;/code&gt;&lt;/strong&gt;, etc):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Γ   0.0000000000    0.0000000000    0.0000000000&#xA;H   0.5000000000   -0.5000000000    0.5000000000&#xA;N   0.0000000000    0.0000000000    0.5000000000&#xA;P   0.2500000000    0.2500000000    0.2500000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using these values my dispersion looks completely wrong (too many bands in some segments, etc).&#xA;On the other hand, I have seen in various tutorials which do bandstructure calculations of BCC metals, the following coordinates are reported&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  0.000  1.000  0.000   !H   &#xA;  0.500  0.500  0.000   !N&#xA;  0.000  0.000  0.000   !gamma&#xA;  0.500  0.500  0.500   !P&#xA;  0.000  1.000  0.000   !H&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;using these (or related ones for the slightly different BCC basis I'm using) gives much better looking plots.&lt;/p&gt;&#xA;&lt;p&gt;I'm wondering if anyone can reconcile these observations for me? I'm at a loss to connect the two things and am unsure if it is a fundamental misunderstanding on my part or a particularity of how matdyn.x represents k-points.&lt;/p&gt;&#xA;" OwnerUserId="6777" LastEditorUserId="5" LastEditDate="2023-02-26T15:52:09.740" LastActivityDate="2023-02-26T20:31:19.500" Title="Confusion regarding specifying a k-point path for phonon dispersions/bandstructure plots" Tags="|quantum-espresso|band-structure|phonons|k-points|brillouin-zone|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10490" PostTypeId="2" ParentId="10458" CreationDate="2023-02-26T09:47:04.367" Score="3" Body="&lt;p&gt;I assume someone at TCSAB (which market Thermo-Calc) can answer this better but as I participated in developing TC a long time ago and now I work on a similar free software called OpenCalphad (I assume you use the version of TC which is free but limited to 3 elements). You can use OC for as many elements as you want PROVIDED you have a database with those elements.  A good database is expensive because it takes a lot of efforts and many months to collect all the experimental data and fit these data to models even for a binary system.  I worked with the Al-Fe system for more than a year before it could be published and a 10 component system has 45 binaries ...&#xA;With OC there is also a python interface if you prefer that, you can find links to OpenCalphad easily on the web.  But the limitation of the Calphad method is not the software, it is developing the databases which requires a lot of efforts.  You may find some free databases of varying quality and accuracy on the web also but you are most welcome to participate in the development if you find them useful.&lt;/p&gt;&#xA;" OwnerUserId="1092" LastActivityDate="2023-02-26T09:47:04.367" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10491" PostTypeId="2" ParentId="10489" CreationDate="2023-02-26T20:31:19.500" Score="5" Body="&lt;p&gt;Actually, I think I may understand now. I believe that the first set of coordinates that I listed are the coordinates of the high symmetry points in the basis of primitive reciprocal lattice vectors (either in the literature or in the input to xcrysden). On the other hand, it would seem that matdyn.x requires the Cartesian coordinates (in &lt;span class=&quot;math-container&quot;&gt;$\frac{2π}{a}$&lt;/span&gt; units). The latter set of coordinates make sense from that point of view.&lt;/p&gt;&#xA;" OwnerUserId="6777" LastActivityDate="2023-02-26T20:31:19.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10492" PostTypeId="1" AcceptedAnswerId="10499" CreationDate="2023-02-27T02:44:19.307" Score="3" ViewCount="341" Body="&lt;p&gt;Always at the end of the output of a scan type calculation in orca there are two tables one with the name &amp;quot;The Surface Calculated using the 'Actual Energy'&amp;quot; and the other &amp;quot;The Surface Calculated using the SCF energy&amp;quot;. Does anyone know the difference between them? It usually has the same relative energy.&lt;/p&gt;&#xA;&lt;p&gt;output exemple:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**** RELAXED SURFACE SCAN DONE ***&#xA;&#xA;                    SUMMARY OF THE CALCULATED SURFACE&#xA;&#xA;----------------------------&#xA;RELAXED SURFACE SCAN RESULTS&#xA;----------------------------&#xA;&#xA;Column   1: NONAME&#xA;&#xA;The Calculated Surface using the 'Actual Energy'&#xA;   1.50000000 -3201.57173598&#xA;   1.55102041 -3201.57066102&#xA;   1.60204082 -3201.56781233&#xA;   1.65306122 -3201.56367690&#xA;   1.70408163 -3201.55862728&#xA;   1.75510204 -3201.55294821&#xA;   1.80612245 -3201.54686651&#xA;   1.85714286 -3201.54056344&#xA;   1.90816327 -3201.53418950&#xA;&#xA;The Calculated Surface using the SCF energy&#xA;   1.50000000 -3201.54720589&#xA;   1.55102041 -3201.54612301&#xA;   1.60204082 -3201.54326595&#xA;   1.65306122 -3201.53912278&#xA;   1.70408163 -3201.53406164&#xA;   1.75510204 -3201.52836994&#xA;   1.80612245 -3201.52227300&#xA;   1.85714286 -3201.51595184&#xA;   1.90816327 -3201.50954958&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6576" LastEditorUserId="6576" LastEditDate="2023-02-27T04:23:20.333" LastActivityDate="2023-02-28T11:36:41.890" Title="What is the difference between actual energy vs scf energy in an orca scan" Tags="|orca|potential-energy-surface|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10493" PostTypeId="1" CreationDate="2023-02-27T05:15:40.190" Score="4" ViewCount="70" Body="&lt;p&gt;I have done TBtrans calculations using SIESTA (v4.0.2) and plotted transmission, as well as  PDOS Vs Energy graphs. I want to know how to locate HOMO-LUMO MOs in those graphs (or) how can I say which peak is HOMO-LUMO in those graphs? Does this requires different software or can I do this with just SIESTA?&lt;/p&gt;&#xA;" OwnerUserId="6561" LastEditorUserId="7" LastEditDate="2023-02-27T15:46:59.087" LastActivityDate="2023-02-27T15:46:59.087" Title="How to locate HOMO-LUMO molecular orbitals in Transmisson and PDOS graphs?" Tags="|ab-initio-calculations|siesta|electronic-transport|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-13T16:52:47.523" ContentLicense="CC BY-SA 4.0" />
  <row Id="10494" PostTypeId="1" CreationDate="2023-02-27T20:39:04.893" Score="0" ViewCount="71" Body="&lt;p&gt;The number of all the spin up and spin down atoms must be equal in the antiferromagnetic configuration? If I have a structure including 9 atoms what should I do?&lt;/p&gt;&#xA;" OwnerUserId="6459" LastActivityDate="2023-03-02T01:06:12.063" Title="Ferro and Antiferro magnetic" Tags="|quantum-espresso|anti-ferromagnetic|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10495" PostTypeId="1" CreationDate="2023-02-27T21:03:48.863" Score="5" ViewCount="89" Body="&lt;p&gt;GDIIS (Geometry optimisation with Direct Inversion of Iterative Subspace) is a well known method used by many QM codes for geometry optimisation. It is inspired from the almost universal DIIS method for converging SCF. The GDIIS method interpolates and extrapolates using the previous geometries and their gradients to obtain a new geometry that minimizes an error vector.&lt;/p&gt;&#xA;&lt;p&gt;The error vector in GDIIS at &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th is expressed as (in &lt;a href=&quot;https://schlegelgroup.wayne.edu/Pub_folder/251.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$e_i = H^{-1}f_i$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the &lt;span class=&quot;math-container&quot;&gt;$f_i$&lt;/span&gt; is the force (negative of gradient) at geometry &lt;span class=&quot;math-container&quot;&gt;$x_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is the estimated Hessian. Then the procedure involves minimizing &lt;span class=&quot;math-container&quot;&gt;$\sum c_i e_i$&lt;/span&gt; with some constraints, and after some maths, GDIIS generates the new geometry guess &lt;span class=&quot;math-container&quot;&gt;$x_{i+1}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I am confused about what the value of &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; is supposed to be - is it supposed to be the Hessian at the current step (&lt;span class=&quot;math-container&quot;&gt;$x_i$&lt;/span&gt;) for all the previous points? Or is it supposed to be the Hessian at &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th step for &lt;span class=&quot;math-container&quot;&gt;$e_i$&lt;/span&gt; (but the Hessian symbol has no subscript)?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The QChem &lt;a href=&quot;https://manual.q-chem.com/4.3/sect0080.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; mentions that early version of GDIIS often used a static matrix (the starting Hessian or unit matrix) as &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; in all cases. However, convergence is faster if a Hessian update scheme is used. This would indicate different Hessians used for different error vectors. But even in that page, the Hessian has not subscript. So I assume it means the Hessian at the current point has to be used for calculating the error vectors in the previous steps?&lt;/p&gt;&#xA;&lt;p&gt;Any insight is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-03-01T21:36:21.197" LastActivityDate="2023-03-01T21:36:21.197" Title="Hessian used for calculating GDIIS error vectors" Tags="|geometry-optimization|geometry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10496" PostTypeId="2" ParentId="10455" CreationDate="2023-02-27T23:07:42.027" Score="3" Body="&lt;p&gt;You can set the pressure (and temperature) for thermochemistry calculations in Gaussian: &lt;a href=&quot;https://gaussian.com/pressure/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gaussian.com/pressure/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you want to calculate manually from the partition function, see section 2.1 of Gaussian's Thermochemistry writeup: &lt;a href=&quot;https://gaussian.com/wp-content/uploads/dl/thermo.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gaussian.com/wp-content/uploads/dl/thermo.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'll reproduce the two equations needed here:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;q_{trans}=(2\pi Rm/h^2)^{3/2}(RT/P)&#xA;$$&lt;/span&gt;&#xA;Note that the above is the same as equation 16 in the Martin paper linked.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S_{trans}=R(lnq_{trans}+3/2)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="5199" LastActivityDate="2023-02-27T23:07:42.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10497" PostTypeId="2" ParentId="10495" CreationDate="2023-02-28T06:50:28.493" Score="4" Body="&lt;p&gt;According to my notes, which may be wrong, the Hessian is the (updated) Hessian at iteration k, i.e. the error vectors are re-defined in each iteration. I guess the argument is that the most recent updated Hessian has the most information. Whether this is what is actually implemented in various codes is difficult to know without actually looking into the codes.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-02-28T06:50:28.493" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10498" PostTypeId="2" ParentId="10402" CreationDate="2023-02-28T07:32:01.443" Score="2" Body="&lt;p&gt;I tried to solve the problem. Here what I did.&#xA;In the input, the first part, try to select the number of CPU or Gaussian will take the default=1, and in your case you need a lot of CPUs as you can because it is huge system.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=pk(i).chk&#xA;%mem=100GB&#xA;%nproc=20&#xA;# opt b3lyp/3-21g geom=connectivity&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The last part of the input.&#xA;I just defined the basis set for Cd2+ ions.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C 0&#xA;6-311+G(d)&#xA;****&#xA;N 0&#xA;6-311+G(d)&#xA;****&#xA;O 0&#xA;6-311+G(d)&#xA;****&#xA;H 0&#xA;6-311+G(d)&#xA;****&#xA;Cd 0&#xA;DEF2TZVP&#xA;****&#xA;&#xA;Cd 0&#xA;DEF2TZVP&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If it is ok for you in this way, the calculation is running well, but it will take time. Here is part of the output.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; HarFok:  IExCor=  402 AccDes= 0.00D+00 IRadAn=         5 IDoV= 1 UseB2=F ITyADJ=14&#xA; ICtDFT=  3500011 ScaDFX=  1.000000  1.000000  1.000000  1.000000&#xA; Defaulting to unpruned grid for atomic number  48.&#xA; FoFCou: FMM=F IPFlag=           0 FMFlag=      100000 FMFlg1=        2001&#xA;         NFxFlg=           0 DoJE=T BraDBF=F KetDBF=T FulRan=T&#xA;         wScrn=  0.000000 ICntrl=       500 IOpCl=  0 I1Cent=   200000004 NGrid=           0&#xA;         NMat0=    1 NMatS0=      1 NMatT0=    0 NMatD0=    1 NMtDS0=    0 NMtDT0=    0&#xA; Petite list used in FoFCou.&#xA; Initial guess &amp;lt;Sx&amp;gt;= 0.0000 &amp;lt;Sy&amp;gt;= 0.0000 &amp;lt;Sz&amp;gt;= 0.5000 &amp;lt;S**2&amp;gt;= 0.7500 S= 0.5000&#xA; Requested convergence on RMS density matrix=1.00D-08 within 128 cycles.&#xA; Requested convergence on MAX density matrix=1.00D-06.&#xA; Requested convergence on             energy=1.00D-06.&#xA; No special actions if energy rises.&#xA; CoulSu:  requested number of processors reduced to:  17 ShMem   1 Linda.&#xA; CalDSu:  requested number of processors reduced to:  17 ShMem   1 Linda.&#xA; Defaulting to unpruned grid for atomic number  48.&#xA; CoulSu:  requested number of processors reduced to:  17 ShMem   1 Linda.&#xA; CalDSu:  requested number of processors reduced to:  17 ShMem   1 Linda.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2023-02-28T07:32:01.443" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10499" PostTypeId="2" ParentId="10492" CreationDate="2023-02-28T11:36:41.890" Score="1" Body="&lt;p&gt;The 'Actual Energy' is the final single point energy, and in contrast to the SCF energy it contains things like the dispersion correction.&lt;/p&gt;&#xA;" OwnerUserId="6576" LastActivityDate="2023-02-28T11:36:41.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10500" PostTypeId="1" CreationDate="2023-02-28T14:53:10.740" Score="4" ViewCount="73" Body="&lt;p&gt;I want to implement Ueff​=U−J in a Quantum ESPRESSO input file, but I don't know how to do that.&lt;/p&gt;&#xA;&lt;p&gt;I found the following on the internet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;lda_plus_u = .TRUE.&#xA;&#xA;lda_plus_u_kind = 1&#xA;Hubbard_u(i) = U&#xA;Hubbard_J(k, i) = J_{ki}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I will replace U by a value that I'll extract from the literature, &lt;strong&gt;but I don't know what I should replace k and J with, or what their meaning is.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-02-28T16:45:45.163" LastActivityDate="2023-02-28T16:45:45.163" Title="How to implement Ueff​=U−J in a Quantum ESPRESSO input file?" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|software-input-file-request|hubbard-model|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:11:09.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="10501" PostTypeId="2" ParentId="10423" CreationDate="2023-02-28T17:23:25.130" Score="1" Body="&lt;p&gt;I spoke with one of the authors of the paper that you cited.&lt;/p&gt;&#xA;&lt;p&gt;He said that you had also emailed him, that he sent you an input file, and that the answer on Reddit was a good one. Unfortunately that answer seems to be removed now, if you remember any of it, please share in an answer to this question and I can remove this Community Wiki post.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-02-28T17:23:25.130" CommentCount="1" CommunityOwnedDate="2023-02-28T17:23:25.130" ContentLicense="CC BY-SA 4.0" />
  <row Id="10502" PostTypeId="1" CreationDate="2023-02-28T17:36:56.983" Score="2" ViewCount="69" Body="&lt;p&gt;How may I calculate the d-band center of metals using GPAW? In other words, how may I get the ASCII data from a &lt;code&gt;gpw&lt;/code&gt; file?&lt;/p&gt;&#xA;" OwnerUserId="6791" LastEditorUserId="5" LastEditDate="2023-02-28T18:17:24.070" LastActivityDate="2023-02-28T18:17:24.070" Title="d-band center calculation from GPAW code" Tags="|density-of-states|gpaw|d-band|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-12T16:02:39.767" ContentLicense="CC BY-SA 4.0" />
  <row Id="10503" PostTypeId="1" CreationDate="2023-03-01T09:16:58.097" Score="4" ViewCount="146" Body="&lt;p&gt;I am using transiesta, which works when the left and right electrode structures are consistent. Now I want to know how to set up the different left and right electrodes, how I should prepare the electrode input file and the input file of the whole system. The example under siesta/Test/TS/ the two ends seem to be the same right and left, while the three ends and four ends are not what I want, so it is difficult to understand how the different electrodes are set up. I'm really looking forward to a specific setup example or more detailed steps.&lt;/p&gt;&#xA;" OwnerUserId="6792" LastActivityDate="2023-06-13T15:01:59.870" Title="How to set the different left and right electrodes of transiesta？" Tags="|siesta|electronic-transport|transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10504" PostTypeId="1" AcceptedAnswerId="10507" CreationDate="2023-03-01T11:08:06.207" Score="5" ViewCount="1121" Body="&lt;p&gt;I'm running my calculations using Quantum ESPRESSO on a 10th generation i7 computer (Dell) with Ubuntu.&lt;/p&gt;&#xA;&lt;p&gt;When I run any calculation using the command &lt;code&gt;mpirun '/directory/ pw.x' -in  file.in&amp;gt; file.out&lt;/code&gt;, only 8 processors are used. However the output of &lt;code&gt;nproc&lt;/code&gt; gives me 16.&lt;/p&gt;&#xA;&lt;p&gt;I want my calculations to run faster. How can I increase the number CPUs used? Is it safe to do that?&lt;/p&gt;&#xA;&lt;p&gt;PS: I use the computer just for DFT calculations at the moment.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-03-01T22:13:47.220" LastActivityDate="2023-03-01T22:59:20.327" Title="How to increase the number of CPUs in my computer?" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|condensed-matter|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10505" PostTypeId="2" ParentId="10504" CreationDate="2023-03-01T11:47:52.820" Score="6" Body="&lt;p&gt;The specific details of how you are running QE are not clear. But here is a simple general overview of how to run QE in parallel settings.&lt;/p&gt;&#xA;&lt;p&gt;If you are using &lt;code&gt;mpirun&lt;/code&gt; command, then do the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mpirun -np 8 pw.x &amp;lt; file.in &amp;gt; file.out&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the &lt;code&gt;-np&lt;/code&gt; switch specifies the number of processes of QE to start. You can increase it from 8 to as long as you are not oversubscribing. But make sure you have enough available processors. For other programs such as dos.x, bands.x, etc., the syntax remains the same. For windows, you might have to change &lt;code&gt;.x&lt;/code&gt; to &lt;code&gt;.exe&lt;/code&gt;. Also, if the standard input symbol  &lt;code&gt;&amp;lt;&lt;/code&gt;  doesn't work, try &lt;code&gt;-inp&lt;/code&gt; or &lt;code&gt;-in&lt;/code&gt; or simply &lt;code&gt;-i&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, you can specify the number of processors used in each group by adding additional switches (&lt;code&gt;-nk&lt;/code&gt;, &lt;code&gt;-nb&lt;/code&gt;, &lt;code&gt;-nd&lt;/code&gt; etc). See &lt;a href=&quot;https://www.quantum-espresso.org/wp-content/uploads/2022/03/user_guide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this user guide&lt;/a&gt; for details.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-03-01T22:59:20.327" LastActivityDate="2023-03-01T22:59:20.327" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10506" PostTypeId="1" AcceptedAnswerId="10511" CreationDate="2023-03-01T17:20:23.523" Score="3" ViewCount="64" Body="&lt;p&gt;I was following the following &lt;a href=&quot;http://dipc.ehu.es/frederiksen/tstutorial/index.php/Zig-zag_graphene_nanoribbon&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; tutorial.&lt;/p&gt;&#xA;&lt;p&gt;As far as my understanding goes, one should use bulk-like metallic electrodes to avoid problems with screening and Fermi-level definition.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Can someone explain why GNRs (graphene nanoribbons) can be safely used as electrodes, since they would have a finite band gap?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="5" LastEditDate="2023-03-01T17:25:24.220" LastActivityDate="2023-03-02T07:39:22.097" Title="Why can graphene nanoribbons be safely used as electrdes, despite having a finite band gap?" Tags="|band-structure|siesta|electronic-transport|graphene|nanostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10507" PostTypeId="2" ParentId="10504" CreationDate="2023-03-01T21:10:10.833" Score="3" Body="&lt;h1&gt;Answer to the question in the title&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;How to increase the number of CPUs in my computer?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can either remove your current i7 &lt;a href=&quot;https://en.wikipedia.org/wiki/Microprocessor&quot; rel=&quot;nofollow noreferrer&quot;&gt;microprocessor&lt;/a&gt; from the &lt;a href=&quot;https://en.wikipedia.org/wiki/Motherboard&quot; rel=&quot;nofollow noreferrer&quot;&gt;motherboard&lt;/a&gt; and replace it with one that has more CPUs, or you could connect multiple motherboards together to form an HPC &amp;quot;cluster&amp;quot;. You might find the following &lt;a href=&quot;/questions/tagged/high-performance-computing&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;high-performance-computing&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;high-performance-computing&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-high-performance-computing-tooltip-container&quot;&gt;high-performance-computing&lt;/a&gt; threads useful if you're interesting in going in either of those directions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6165/5&quot;&gt;Should I connect 2-3 laptops to form a supercomputer?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/5018/5&quot;&gt;Are there critical mistakes to avoid when creating a workstation (32-128 cores)?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/7151/5&quot;&gt;Suggestions on laptops for matter modeling&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/883/5&quot;&gt;Should I buy a CPU or a GPU for doing calculations?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1125/5&quot;&gt;Materials Modeling with Raspberry Pi?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2112/5&quot;&gt;Is ARM64 the next big thing?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However, the rest of your question suggests that the title was not chosen so accurately. It seems that you're not &lt;strong&gt;trying to increase the number of CPUs in your computer&lt;/strong&gt; but you're trying to &lt;strong&gt;make use of more of the CPUs that already exist in your comptuer.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10504/how-to-increase-the-number-of-cpu-in-my-computer#comment22437_10505&quot;&gt;Nick Papior's comment&lt;/a&gt; pointed out that if &amp;quot;8 processors are used&amp;quot; (as your question says), then you're already using all of your processors! This is because the Intel i7 microprocessor does something called &lt;a href=&quot;https://en.wikipedia.org/wiki/Hyper-threading&quot; rel=&quot;nofollow noreferrer&quot;&gt;hyperthreading&lt;/a&gt; which means that each core can have two threads, so 8 physical cores means a total of 16 possible threads.&lt;/p&gt;&#xA;&lt;h1&gt;Is it safe to oversubscribe a computer?&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;How can I increase the number CPU used? Is it safe to do that?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I do not recommend for you to oversubscribe your machine. Nick Papior's above-linked comment mentioned that you can use &lt;code&gt;--oversubscribe&lt;/code&gt;, but it came with a big warning:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;but please test for something simple to see if this actually gives you anything!!!!&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I want to add to that warning, not to just test if it gives you speed-up, &lt;strong&gt;but also to test how safe this is: I wouldn't want you to crash your hardware&lt;/strong&gt;. In this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10211/5&quot;&gt;Is this &amp;quot;internal error&amp;quot; reproducible when compiling OpenMolcas on other Intel compilers?&lt;/a&gt;, I warned users not to even &amp;quot;fully subscribe&amp;quot; (let alone &amp;quot;over subscribe&amp;quot;) a personal  computer. In that specific case of compiling OpenMolcas, the compilation took about 20 minutes when using 2 cores, but took more than an hour when using 4 cores (which also caused me a big scare because the entire computer froze during that hour, and the fan seemed overworked as if the computer was going to overheat and permanently damage CPU components). &lt;/p&gt;&#xA;&lt;h1&gt;Conclusion&lt;/h1&gt;&#xA;&lt;p&gt;Welcome to the wonderful world of high-performance matter modeling :) It's really nice to have you in this community. Some of my greatest joys have been with doing calculations that gave me experiences like the one you're currently having. At some point we need to accept that we are doing the best we can with the resources that we have available, and we just need to find more resources (e.g. run the calculations on a supercomputer that has 1000s of cores), reduce the computational demands in the project (e.g. don't aim for such high accuracy), or wait longer for the calculations to run.&lt;/p&gt;&#xA;&lt;p&gt;If you are open to the idea of jumping off the bicycle (8-core CPU) and hopping into a racecar (supercomputer with 1000s of cores), the following threads might be helpful for you (also I have over 1000 CPU years available in total in case you want to try some calculations here):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1515/5&quot;&gt;Supercomputers around the world&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1613/5&quot;&gt;Supercomputers around the world, which allow access for researchers outside the country&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4635/5&quot;&gt;What are some cloud services for computing?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4702/5&quot;&gt;Solving the Schr&amp;#246;dinger equation as a service?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-03-01T21:10:10.833" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10508" PostTypeId="1" AcceptedAnswerId="10514" CreationDate="2023-03-02T00:10:57.280" Score="6" ViewCount="759" Body="&lt;p&gt;I am interested to learn the use of multifwn software. I have windows OS.&lt;/p&gt;&#xA;&lt;p&gt;Mostly I am interested to see the charge density and ELF, particularly in non-atomic locations. Can anyone guide me, starting from installation as well as which flags are important, etc (may be screenshots will be helpful)?&lt;/p&gt;&#xA;&lt;p&gt;I have 3D cube file of charge density.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2023-03-02T11:37:32.920" Title="How to use Multiwfn software (for charge density and ELF analysis)?" Tags="|charge-density|multiwfn|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10509" PostTypeId="2" ParentId="10494" CreationDate="2023-03-02T01:06:12.063" Score="4" Body="&lt;p&gt;In a perfect antiferromagnetic (AFM) system, the number of up and down &lt;em&gt;electrons&lt;/em&gt; is equal, not necessarily the atoms themselves. Having said that, simple AFM materials typically have only one &amp;quot;magnetic&amp;quot; species, so it is usually the case that their atomic magnetic moments have the same magnitude, and there are the same number of &amp;quot;up&amp;quot; and &amp;quot;down&amp;quot; atomic moments. Note that there are usually atoms of &lt;em&gt;other&lt;/em&gt; chemical species in the material which are non-magnetic.&lt;/p&gt;&#xA;&lt;p&gt;You don't say what your material is, so it's difficult to give a precise answer. Atoms which have atomic magnetic moments are usually open &lt;span class=&quot;math-container&quot;&gt;$d-$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$f-$&lt;/span&gt;shell elements, and I would usually expect a material including them to also include other, non-magnetic atoms. You say that there are 9 atoms in the simulation cell, but are they all expected to have magnetic moments? Are the magnetic moments the same between all the &amp;quot;magnetic atoms&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;Another important aspect is whether the 9 atom cell is the &lt;em&gt;magnetic&lt;/em&gt; unit cell, or merely the &lt;em&gt;structural&lt;/em&gt; unit cell. Simple AFM materials typically have magnetic unit cells which are twice as large as the structural cell; for example, NiO has a rocksalt atomic structure, but the Ni atoms' magnetic moments are antiferromagnetically ordered, so you cannot model NiO correctly with a primitive or conventional rocksalt structural cell. See:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10415/how-to-model-antiferromagnetic-nio-p-type-semiconductor/10420#10420&quot;&gt;How to Model Antiferromagnetic NiO p-type semiconductor?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;for a discussion on exactly this point. The O atoms in NiO have essentially no atomic magnetic moment.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-03-02T01:06:12.063" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10510" PostTypeId="1" CreationDate="2023-03-02T05:02:56.287" Score="5" ViewCount="89" Body="&lt;p&gt;For prediction of novel two dimensional materials using Density Functional Theory, what are the most important concepts one should check out before formulating new structures.&lt;/p&gt;&#xA;" OwnerUserId="5094" LastEditorUserId="5" LastEditDate="2023-03-02T05:11:34.633" LastActivityDate="2023-03-03T12:56:59.210" Title="What are most fundamental things you must check before theoretical prediction of novel 2d materials?" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10511" PostTypeId="2" ParentId="10506" CreationDate="2023-03-02T07:39:22.097" Score="1" Body="&lt;p&gt;From the tutorial it is obvious that the GNR used is metallic, i.e. has no band-gap.&lt;/p&gt;&#xA;&lt;p&gt;Please see the transmission functions at the end: &lt;a href=&quot;http://dipc.ehu.es/frederiksen/tstutorial/index.php/Nanoribbon_answers&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://dipc.ehu.es/frederiksen/tstutorial/index.php/Nanoribbon_answers&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But you are absolutely correct. DFT calculations with gapped materials are likely to give wrong answers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;because the fermi-level is ill-defined&lt;/li&gt;&#xA;&lt;li&gt;because the screening length of semi-conductors/insulators are excessively long. One &lt;em&gt;could&lt;/em&gt; mitigate this by having a device that is longer than the screening length, but that turns out to be unfeasible in DFT :)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-03-02T07:39:22.097" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10512" PostTypeId="2" ParentId="10508" CreationDate="2023-03-02T08:48:12.863" Score="9" Body="&lt;p&gt;The multiwfn &lt;a href=&quot;http://sobereva.com/multiwfn/&quot; rel=&quot;noreferrer&quot;&gt;homepage&lt;/a&gt; is well documented and loaded with all the information you need.&lt;/p&gt;&#xA;&lt;p&gt;I quote and perhaps paraphrase some of the relevant information here:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;You can find helpful videos Youtube channel with many demos:&#xA;&lt;a href=&quot;https://www.youtube.com/playlist?list=PLGZRmytlfpyPMknda9_tdJh8HPHjSECsW&quot; rel=&quot;noreferrer&quot;&gt;Multiwfn-Youtube-Channel&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Some possibly helpful videos for you:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://youtu.be/hy6m-cg3r4g&quot; rel=&quot;noreferrer&quot;&gt;Regarding ELF&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://youtu.be/xKvOLFbeGoc&quot; rel=&quot;noreferrer&quot;&gt;Regarding Charge of a molecule&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Detailed Installation Instructions here: &lt;a href=&quot;http://sobereva.com/167&quot; rel=&quot;noreferrer&quot;&gt;Instructions&lt;/a&gt; (Use a&#xA;default translator extension such as Google translate to translate&#xA;the webpage from Chinese to English. It does a fairly good job of&#xA;translating the page)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;FAQ page of Multiwfn: &lt;a href=&quot;http://sobereva.com/452&quot; rel=&quot;noreferrer&quot;&gt;FAQ&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Multiwfn Discussion forum page: &lt;a href=&quot;http://bbs.keinsci.com/forum-112-1.html&quot; rel=&quot;noreferrer&quot;&gt;Forum&lt;/a&gt;  (Again use a translator)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-03-02T08:48:12.863" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10513" PostTypeId="1" AcceptedAnswerId="10527" CreationDate="2023-03-02T11:13:52.513" Score="7" ViewCount="703" Body="&lt;p&gt;I hope this question finds you well. I am reaching out to seek your advice on using the exchange-correlation functional 'GGA' or 'LDA'approximation calculation in Quantum ESSPRESSO for Calculation of electronic and magnetic properties.&lt;/p&gt;&#xA;&lt;p&gt;I have been reading up on the topic and found on the Quantum ESPRESSO website that many exchange-correlation functionals, from LDA to generalized-gradient corrections to meta-GGA, exact exchange (HF), and hybrid functionals, can be used. However, I am still unsure of how to specify that I want to run a calculation using GGA and LDA approximation in the input file.&lt;/p&gt;&#xA;&lt;p&gt;Could you please guide me on how to include the appropriate keyword in the input file to specify the exchange-correlation functional? Also, I would greatly appreciate any advice on how to choose the best functional for my specific system and properties of interest.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your time and expertise.&lt;/p&gt;&#xA;" OwnerUserId="1905" LastEditorUserId="5" LastEditDate="2023-03-02T15:20:30.897" LastActivityDate="2023-03-05T19:32:35.893" Title="Query on using the exchange-correlation functional GGA or LDA approximation in Quantum ESPRESSO for electronic and magnetic property calculations?" Tags="|density-functional-theory|quantum-espresso|exchange-correlation|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10514" PostTypeId="2" ParentId="10508" CreationDate="2023-03-02T11:37:32.920" Score="8" Body="&lt;p&gt;Complementing the @VandanRevanur answer, the MULTIWFN manual (&lt;a href=&quot;http://sobereva.com/multiwfn/misc/Multiwfn_3.8_dev.pdf&quot; rel=&quot;noreferrer&quot;&gt;Development version: 3.8(dev)&lt;/a&gt;) has many examples about how to use the software. In particular, there are two examples about how to calculate the Electron Localization Function. The chapter 4 is dedicated to working &lt;strong&gt;Tutorials and Example&lt;/strong&gt; where you can find these two related:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;4.5.1 Electron localization function of chlorine trifluoride (page 479),&lt;/li&gt;&#xA;&lt;li&gt;4.5.3 Calculate ELF-&lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and ELF-&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; to study aromaticity of benzene (page 482).&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://youtu.be/vC48iEB8PwI&quot; rel=&quot;noreferrer&quot;&gt;Plotting electron localization function (ELF) isosurface using Multiwfn and ChimeraX&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also, there is forum in English: &lt;a href=&quot;http://sobereva.com/wfnbbs/&quot; rel=&quot;noreferrer&quot;&gt;http://sobereva.com/wfnbbs/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I also recommend that you get a look about the use of the &lt;code&gt;settings.ini&lt;/code&gt; file, where you can modify many parameters about drawing, exporting format/quality of images, number of processors, etc.&lt;/p&gt;&#xA;&lt;p&gt;Another useful recommendation is to use an input file with all the commands you need to get the calculations done. This will save you time and will ensure that you don't miss a command.&lt;/p&gt;&#xA;&lt;p&gt;For example, this input file I use to calculate the critical points, the Hirshfeld, Voronoi and corrected Hirshfeld atomic charges:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2   &amp;lt;- Topological analysis&#xA;2   &amp;lt;- Search CPs from nuclear positions&#xA;3   &amp;lt;- Search CPs from midpoint of atom pairs&#xA;8   &amp;lt;- Generate the path connected (3,-3) and (3,-1)    #9  &amp;lt;- Generate the path connected (3,+1) and (3,+3)&#xA;-5  &amp;lt;- Modify or print detail or export paths, or calculate property along a path&#xA;1   &amp;lt;- Print summary of paths&#xA;4       &amp;lt;- Save points of all paths to paths.txt in current folder&#xA;6       &amp;lt;- Export paths as paths.pdb file in current folder&#xA;0       &amp;lt;- Return&#xA;0   &amp;lt;- Print and visualize all generated CPs, paths and surfaces&#xA;-4  &amp;lt;- Modify or export CPs (critical points)&#xA;-1  &amp;lt;- Print summary of CPs (in Angstrom)&#xA;4   &amp;lt;- Save CPs to CPs.txt in current folder&#xA;6   &amp;lt;- Export CPs as CPs.pdb file in current folder&#xA;0   &amp;lt;- Return&#xA;7       &amp;lt;- Show real space function values at specific CP or all CPs&#xA;0       &amp;lt;- If input 0, then properties of all CPs will be outputted to CPprop.txt in current folder&#xA;-10 &amp;lt;- Return&#xA;7       &amp;lt;- Population analysis and calculation of atomic charge&#xA;1       &amp;lt;- Hirshfeld atomic charge&#xA;1       &amp;lt;- Use build-in sphericalized atomic densities in free-states (more convenient)&#xA;n&#xA;2       &amp;lt;- Voronoi deformation density (VDD) atom population&#xA;1       &amp;lt;- Use build-in sphericalized atomic densities in free-states (more convenient)&#xA;n&#xA;11      &amp;lt;- Atomic dipole corrected Hirshfeld atomic charge (ADCH) (recommended)&#xA;1       &amp;lt;- Use build-in sphericalized atomic densities in free-states (more convenient)&#xA;n&#xA;0       &amp;lt;- Return&#xA;-10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You use the input file as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Multiwfn wavefunction_file &amp;lt; input_file.in &amp;gt; output_file.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is another script I used to do the topological calculation and then export some properties (electron density, electron density Laplacian, ELF and LOL indexes) as 2D maps (with/without labels, level lines, colour, etc.):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2   &amp;lt;- Topological analysis&#xA;2   &amp;lt;- Search CPs from nuclear positions&#xA;3   &amp;lt;- Search CPs from midpoint of atom pairs&#xA;8   &amp;lt;- Generate the path connected (3,-3) and (3,-1)&#xA;9   &amp;lt;- Generate the path connected (3,+1) and (3,+3)&#xA;-5  &amp;lt;- Modify or print detail or export paths, or calculate property along a path&#xA;1   &amp;lt;- Print summary of paths&#xA;0       &amp;lt;- Return&#xA;0   &amp;lt;- Print and visualize all generated CPs, paths and surfaces&#xA;-4  &amp;lt;- Modify or export CPs (critical points)&#xA;-1  &amp;lt;- Print summary of CPs (in Angstrom)&#xA;4   &amp;lt;- Save CPs to CPs.txt in current folder&#xA;6   &amp;lt;- Export CPs as CPs.pdb file in current folder&#xA;0   &amp;lt;- Return&#xA;7       &amp;lt;- Show real space function values at specific CP or all CPs&#xA;0       &amp;lt;- If input 0, then properties of all CPs will be outputted to CPprop.txt in current folder&#xA;-10 &amp;lt;- Return&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;1   &amp;lt;- Electron Density&#xA;6   &amp;lt;- Gradient lines map with/without contour lines&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;-8  &amp;lt;- Change length unit of the graph to Angstrom&#xA;-3      &amp;lt;- Change other plotting settings&#xA;1       &amp;lt;- Toggle reversing ticks, current: No&#xA;0       &amp;lt;- Return&#xA;6   &amp;lt;- Generate and show interbasin paths&#xA;15  &amp;lt;- Draw a contour line of vdW surface (electron density=0.001)&#xA;0   &amp;lt;- Save the graph to a file   ! dislin.png ElectronDensityGradientLines_AtomLabels_vdW&#xA;1   &amp;lt;- Disable showing atom labels and reference point&#xA;0   &amp;lt;- Save the graph to a file    ! dislin_1.png ElectronDensityGradientLines_woAtomLabels_vdW&#xA;2   &amp;lt;- Enable showing isovalue on contour lines&#xA;35  &amp;lt;- Input label size   e.g. 30&#xA;0   &amp;lt;- Save the graph to a file       ! dislin_2.png ElectronDensityGradientLines_woAtomLabels_vdW_Isovalues&#xA;-5  &amp;lt;- Return to main menu&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;1   &amp;lt;- Electron Density&#xA;1   &amp;lt;- Color-filled map&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;4   &amp;lt;- Enable showing atom labels and reference point&#xA;5   &amp;lt;- Use which color for labelling atoms? (1/2/3/4/5 = Red/Green/Blue/White/Black 6/7/8/9/10 = Gray/Cyan/Yellow/Orange/Magenta 11/12/13/14 = Crimson/Dark green/Purple/Brown)&#xA;0   &amp;lt;- Save the graph to a file  ! dislin_3.png ElectronDensityColor_filledMap_AtomLabels&#xA;2   &amp;lt;- Enable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file  ! dislin_4.png ElectronDensityColor_filledMap_AtomLabels_CountorLines&#xA;15  &amp;lt;- Draw a contour line of vdW surface (electron density=0.001)&#xA;0   &amp;lt;- Save the graph to a file       ! dislin_5.png ElectronDensityColor_filledMap_AtomLabels_CountorLines_vdW&#xA;2   &amp;lt;- Disable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! dislin_6.png ElectronDensityColor_filledMap_AtomLabels_vdW&#xA;-5  &amp;lt;- Return to main menu&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;3   &amp;lt;-  Laplacian of electron density&#xA;1   &amp;lt;- Color-filled map&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;4    &amp;lt;- Disable showing atom labels and reference point&#xA;0   &amp;lt;- Save the graph to a file ! dislin_7.png LaplacianElectronDensityColor_filledMap&#xA;2   &amp;lt;- Enable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! dislin_8.png LaplacianElectronDensityColor_filledMap_CountorLines&#xA;15  &amp;lt;- Draw a contour line of vdW surface (electron density=0.001)&#xA;0   &amp;lt;- Save the graph to a file       ! dislin_9.png LaplacianElectronDensityColor_filledMap_CountorLines_vdW&#xA;2   &amp;lt;- Disable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! disli_10.png LaplacianElectronDensityColor_filledMap_vdW&#xA;-5      &amp;lt;- Return to main menu&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;9       &amp;lt;- Electron Localization Function (ELF)&#xA;1       &amp;lt;- Color-filled map&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;0   &amp;lt;- Save the graph to a file ! disli_11.png ELFColor_filledMap&#xA;2       &amp;lt;- Enable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! disli_12.png ELFColor_filledMap_CountorLines&#xA;15  &amp;lt;- Draw a contour line of vdW surface (electron density=0.001)&#xA;0   &amp;lt;- Save the graph to a file       ! disli_13.png ELFColor_filledMap_CountorLines_vdW&#xA;2   &amp;lt;- Disable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! disli_14.png ELFColor_filledMap_vdW&#xA;-5  &amp;lt;- Return to main menu&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;10      &amp;lt;- Localized orbital locator (LOL)&#xA;1       &amp;lt;- Color-filled map&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;0   &amp;lt;- Save the graph to a file ! disli_15.png LOLColor_filledMap&#xA;2   &amp;lt;- Enable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! disli_16.png LOLColor_filledMap_CountorLines&#xA;15  &amp;lt;- Draw a contour line of vdW surface (electron density=0.001)&#xA;0   &amp;lt;- Save the graph to a file       ! disli_17.png LOLColor_filledMap_CountorLines_vdW&#xA;2   &amp;lt;- Disable showing contour lines&#xA;0   &amp;lt;- Save the graph to a file ! disli_18.png LOLColor_filledMap_vdW&#xA;-5  &amp;lt;- Return to main menu&#xA;4   &amp;lt;- Output and plot specific property in a plane&#xA;1   &amp;lt;- Electron Density&#xA;6   &amp;lt;- Gradient lines map with/without contour lines&#xA;300,300 &amp;lt;- How many grids in the two dimensions respectively?&#xA;-1      &amp;lt;- Set translation and rotation of the map for plane types 4 and 5&#xA;0,0&#xA;&#xA;-73.5&#xA;4   &amp;lt;- Define the plane to be plotted: Define by three atoms&#xA;121,95,104  &amp;lt;- Number of atoms&#xA;-3      &amp;lt;- Change other plotting settings&#xA;1       &amp;lt;- Toggle reversing ticks, current: No&#xA;0       &amp;lt;- Return&#xA;18      &amp;lt;- Change style of atomic labels: Only plot element symbol&#xA;3       &amp;lt;- Plot both element symbol and atomic index&#xA;0   &amp;lt;- Save the graph to a file   ! disli_19.png ElectronDensityGradientLines_AtomLabels&#xA;-5  &amp;lt;- Return to main menu&#xA;-10 &amp;lt;- Exit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-03-02T11:37:32.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10515" PostTypeId="1" CreationDate="2023-03-02T16:34:45.263" Score="7" ViewCount="334" Body="&lt;p&gt;I'm currently working on  the simulation of  Uv-vis absorption spectra of some organic compounds, while performing TD-Dft the log file that we got contains the values of deltaE of the transition,wavelength, oscillatior strength f and the electronic contribution %&lt;/p&gt;&#xA;&lt;p&gt;for exemple&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Excited State   1:      Singlet-A      2.8918 eV  428.74 nm  f=0.4068  &amp;lt;S**2&amp;gt;=0.000&#xA;          71 -&amp;gt; 72         0.70317 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I got confused with all these parameters for choosing the londa max,&#xA;from what I've known the oscillator strength f : is the probability of a transition to occur , but i've found that the maximum value of f doesn't necessary involve the maximum londa ,&lt;/p&gt;&#xA;&lt;p&gt;even for  the value in ev deltaE bigger-xx-&amp;gt;londa max bigger ,&lt;/p&gt;&#xA;&lt;p&gt;can someone help me figure this out, thank you&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="6274" LastEditDate="2023-03-06T12:17:26.507" LastActivityDate="2023-03-06T12:17:26.507" Title="How to assign UV-vis maximum absorption wavelength theoretically by using td-DFT?" Tags="|gaussian|spectroscopy|td-dft|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10516" PostTypeId="2" ParentId="10138" CreationDate="2023-03-02T17:02:43.957" Score="7" Body="&lt;p&gt;I am no expert or experienced in this field. All my suggestions are based on my own experience as a beginner in matter modeling.&lt;/p&gt;&#xA;&lt;h3&gt;About the textbook&lt;/h3&gt;&#xA;&lt;p&gt;This textbook you mentioned is sufficient for a brief introduction to material science. In terms of matter modeling, you may find ch 3 and 4 of this textbook helpful which covered unit cells, cubic lattices, packing, imperfection, etc. Other chapters are not needed to understand basic concepts at the beginning.&lt;/p&gt;&#xA;&lt;h3&gt;A recommended book for beginner&lt;/h3&gt;&#xA;&lt;p&gt;Aside from this book, for an absolute beginner, arguably the best approach is to study ch 4,5, and 6 of &amp;quot;Computational Material Science&amp;quot; by June Gunn Lee. Ch 4 covers the basics of 'first-principle calculation&amp;quot; and ch 5 covers the concept related to DFT such as HK theorem, KS equations, XC functional, SCF procedure, etc. After &amp;quot;reading&amp;quot; these chapters, you can finally start reading ch 6 which covers pseudopotential (PP), plane-wave expansion (PW), Brillouin Zone (BZ), Periodic Boundary Conditions (PBC) or Bloch theorem, k-points, etc. This is the most important chapter.&lt;/p&gt;&#xA;&lt;h3&gt;Quantum ESPRESSO&lt;/h3&gt;&#xA;&lt;p&gt;At this stage, you now know all the basics and you can start doing simple calculations. There are a lot of software choices available. I recommend starting with Quantum ESPRESSO (QE) since it is free, nicely documented, and also has an active user forum. You can either follow the official QE tutorial on their website, or various youtube tutorials (such as QuantumNerd or PhysicsWhiz), or ch 7 of Lee's book to learn QE. Also, in 2023, a new book has been published focused solely on solid-state physics with QE, &lt;a href=&quot;https://books.google.com.tr/books?id=5pKdEAAAQBAJ&amp;amp;pg=PA#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;noreferrer&quot;&gt;see a preview here&lt;/a&gt;. (I think this is the first of its kind).&lt;/p&gt;&#xA;&lt;p&gt;This book is very good in terms of compatibility with the updated version, and it also teaches the reader about shell scripting, running batch jobs, parallel execution, etc. Most importantly, the installation instruction (which is usually the most hectic part) found in this book is the least confusing in my opinion.&lt;/p&gt;&#xA;&lt;h3&gt;GUI&lt;/h3&gt;&#xA;&lt;p&gt;A complete beginner might prefer to start with a Graphical User Interface (GUI) instead of the command-line approach suggested in the above-mentioned books/tutorials. something like BURAI. It will heavily simplify creating the input files, visualizing the materials, and managing the project. Later, once the user becomes comfortable, s/he can move to a command-line approach. But then again, for a slab or a lot of atoms, a GUI can be very helpful for efficiently producing the input files. Then the user can copy/inspect that input file and run that on an actual machine.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-02T17:02:43.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10518" PostTypeId="2" ParentId="10515" CreationDate="2023-03-02T18:44:10.053" Score="5" Body="&lt;p&gt;There are different ways to know the lambda max. You can visualize the output by using different programs, and you will find that there are different bands or only one band depending on the system. Each band is made up of the highest wavelength with the highest oscillator strength (this band is a transition between orbitals).&lt;/p&gt;&#xA;&lt;p&gt;For example, Molden.&#xA;As you can see in the attached image. There are two bands, one with a wavelength of 180 nm and another with a wavelength of 230 nm. Therefore, these two bands refer to the maximum wavelength with the highest oscillator strength. Note:: you can visualize the molecular orbital.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lRLOM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lRLOM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There are other programs like Avogadro, you can plot the spectrum easily. Another program Chemissian, it is not free, but in this program, you can visualize NTO orbitals.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2023-03-02T18:44:10.053" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10519" PostTypeId="2" ParentId="10465" CreationDate="2023-03-02T19:43:08.123" Score="4" Body="&lt;p&gt;The easiest way to do this IMHO is through Open Babel / Pybel, particularly if you want to set a lot of bonds.&lt;/p&gt;&#xA;&lt;p&gt;BTW, reading from XYZ, the bond orders are interpreted, but not always exactly.&lt;/p&gt;&#xA;&lt;p&gt;In Avogadro v1, this is basically the code for setting bond lengths. In Avogadro v2, it doesn't use Open Babel directly, but the code is quite similar.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import sys&#xA;import os&#xA;&#xA;from openbabel import pybel&#xA;# don't need to reimport openbabel&#xA;ob = pybel.ob&#xA;&#xA;# syntax:&#xA;# set-bondlength.py file.xyz &#xA;&#xA;# repeat through all the files on the command-line&#xA;# we can change this to use the glob module as well&#xA;#  e.g., find all the files in a set of folders&#xA;for argument in sys.argv[1:]:&#xA;    filename, extension = os.path.splitext(argument)&#xA;&#xA;    for i in range(len(filename), 0, -1):&#xA;        if filename[i-1].isalpha():&#xA;            field = filename[i:]&#xA;            break&#xA;&#xA;    # read all the molecules from the supplied file&#xA;    for mol in pybel.readfile(extension[1:], argument):&#xA;&#xA;        for bond in ob.OBMolBondIter(mol.OBMol):&#xA;            beginAtom = bond.GetBeginAtom()&#xA;            endAtom = bond.GetEndAtom()&#xA;&#xA;            # check if the bond is a C-C single bond&#xA;            if beginAtom.GetAtomicNum() == 6 \&#xA;                    and endAtom.GetAtomicNum() == 6 \&#xA;                    and bond.GetBondOrder() == 1:&#xA;&#xA;                # set the bond length to 1.54 Angstrom&#xA;                bond.SetLength(1.54)&#xA;        &#xA;        # write the molecule to a new file&#xA;        mol.write(&amp;quot;xyz&amp;quot;, filename + &amp;quot;_%s.xyz&amp;quot; % field, overwrite=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-03-02T19:43:08.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10520" PostTypeId="1" AcceptedAnswerId="10522" CreationDate="2023-03-02T21:49:32.320" Score="5" ViewCount="266" Body="&lt;p&gt;Silicon has 6 conduction bands of interest. In GPAW tutorials for the calculation of properties of silicon, the parameters &lt;code&gt;nbands&lt;/code&gt; which is referred as the &amp;quot;number of electronic bands&amp;quot; goes from 10 to 60 bands depending on the example. What does this parameter means? Also in the documentation introduction it says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For systems with the occupied states well separated from the unoccupied states, one could use just the number of bands needed to hold the occupied states. For metals, more bands are needed. Sometimes, adding more unoccupied bands will improve convergence.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What does this means for metals? For example for a conducting metal where only valence s electrons play a role, where are the unoccupied bands? The conduction band is not even fully filled, why cannot we just set &lt;code&gt;nband=1&lt;/code&gt;?&lt;/p&gt;&#xA;" OwnerUserId="5321" LastEditorUserId="5321" LastEditDate="2023-03-02T22:06:42.640" LastActivityDate="2023-03-03T01:06:41.140" Title="What is the number of bands in GPAW?" Tags="|band-structure|gpaw|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10522" PostTypeId="2" ParentId="10520" CreationDate="2023-03-03T01:06:41.140" Score="6" Body="&lt;p&gt;The number of bands you set is usually the &lt;em&gt;total&lt;/em&gt; number of bands, i.e. the number of valence bands plus the number of conduction bands. For the calculation of the ground state density, you need a minimum of all the occupied bands (valence bands); if your silicon pseudopotential has 4 valence electrons, that means you need at least 2 bands per silicon atom. These are the &lt;em&gt;valence bands&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For systems with a reasonably large band gap, you can usually calculate the ground state fairly reliably and quickly using &lt;em&gt;only&lt;/em&gt; the valence bands. However, even in these cases it is often found that including a small number of extra bands, i.e. &lt;em&gt;conduction bands&lt;/em&gt;, will speed up the calculation and make it more robust. For smaller band-gaps, it becomes more important to include some conduction bands, and the extreme case is a metal, where there is no band-gap and so you absolutely need to include some conduction bands.&lt;/p&gt;&#xA;&lt;h3&gt;Why do we need to compute conduction bands for the ground state?&lt;/h3&gt;&#xA;&lt;p&gt;Remember that your DFT program does not even know the correct Hamiltonian when it's trying to compute the Kohn-Sham states, because the Hamiltonian depends on the density, and the density depends on the Kohn-Sham states. The optimisation usually follows a self-consistent field (SCF) approach, where the states are optimised for a fixed Hamiltonian, then the Hamiltonian is improved and the states optimised again. This SCF &amp;quot;cycle&amp;quot; is repeated until (hopefully) it converges to both the correct Hamiltonian and the correct states.&lt;/p&gt;&#xA;&lt;p&gt;To see why you need to include some low-lying conduction states, let's imagine running the SCF process backwards. We start with the correct, self-consistent Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt; and the eigenstates &lt;span class=&quot;math-container&quot;&gt;$\{\psi_b^{(0)}\}$&lt;/span&gt; and eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\{\epsilon_b\}$&lt;/span&gt;, and then we add a small error to the Hamiltonian, &lt;span class=&quot;math-container&quot;&gt;$\Delta\hat{H}$&lt;/span&gt;; how do the Kohn-Sham states change? We can use perturbation theory, and write:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi_b(\mathbf{r}) = \sum_{b^\prime} \frac{\langle\psi_{b^\prime}\vert\Delta\hat{H}\vert\psi_{b}\rangle}{\epsilon_{b}-\epsilon_{b^\prime}}\psi_{b^\prime}(\mathbf{r}) \tag{1}&#xA;$$&lt;/span&gt;&#xA;Notice that the effect of adding error to the Hamiltonian is to make our eigenstates a mixture of the &amp;quot;true&amp;quot; states -- each band &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; gets a contribution from all the other bands  (&lt;span class=&quot;math-container&quot;&gt;$b^\prime$&lt;/span&gt; in the sum) -- and that the amount of mixing is greatest for bands where &lt;span class=&quot;math-container&quot;&gt;$\epsilon_b\approx\epsilon_{b^\prime}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This mixing doesn't affect the density if all the states have the same occupation, e.g. they are all valence (fully occupied) or all conduction (fully unoccupied); however, any mixing between valence and conduction states will lead to an additional error in the density, which in turn leads to an additional error in the Hamiltonian. This mixing is weak if the conduction states have energies much higher than the valence states (e.g. a wide-band-gap insulator), and the mixing is strong if the conduction states have very similar energies to the valence states (e.g. a metal).&lt;/p&gt;&#xA;&lt;h4&gt;Plane-wave DFT&lt;/h4&gt;&#xA;&lt;p&gt;In plane-wave DFT (or regularly-sampled real-space methods), there is an extra consideration. Because the size of a plane-wave basis is very large compared to the number of electrons, you don't diagonalise the Hamiltonian in the plane-wave basis directly, you diagonalise it iteratively and only calculate the bands you want in the plane-wave basis.&lt;/p&gt;&#xA;&lt;p&gt;If you optimised the Kohn-Sham bands entirely independently of each other, you would have the same problem of the mixing between the &amp;quot;true&amp;quot; bands as discussed above, and it would be extremely difficult to calculate the bands any time two or more were close in energy. To avoid this difficulty, we directly diagonalise the Hamiltonian &lt;em&gt;in the subspace of the bands we're calculating&lt;/em&gt;, i.e. we define the matrix &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; such that,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;h_{bb^\prime}=\langle \psi_b\vert\hat{H}\vert\psi_{b^\prime}\rangle \tag{2}&#xA;$$&lt;/span&gt;&#xA;and then we directly diagonalise &lt;span class=&quot;math-container&quot;&gt;$h$&lt;/span&gt; to obtain the best approximation to the &amp;quot;true&amp;quot; eigenstates, in the basis of our current &amp;quot;best guess&amp;quot; eigenstates.&lt;/p&gt;&#xA;&lt;p&gt;This step is often called &amp;quot;subspace diagonalisation&amp;quot; or &amp;quot;subspace rotation&amp;quot;, and it improves the convergence of the iterative methods enormously whenever any of the states of interest are close in energies to each other. However, in order to take advantage of it you need to make sure that you've included all of the bands which might mix with the ones you really care about; in other words, you need to ensure you've included enough conduction states that the mixing between the states you really care about (valence states, in a ground state calculation) and the lowest energy states &lt;em&gt;you aren't including in your calculation&lt;/em&gt; is low.&lt;/p&gt;&#xA;&lt;h4&gt;Partial occupancies&lt;/h4&gt;&#xA;&lt;p&gt;A further complication in real calculations is that we often use an energy broadening function, which near the Fermi energy leads to partial band occupancies, rather than each band being simply fully occupied or completely empty. The use of partial occupancies improves the stability of both the density optimisation and the Fermi-level description, but it means that some bands which used to be empty conduction states now gain a small occupation, and hence contribute to the density.&lt;/p&gt;&#xA;&lt;p&gt;In order to model your material accurately, you need to make sure that you've included in your calculation &lt;em&gt;all&lt;/em&gt; states which might have some occupancy, and of course we still might want to include higher-energy states which would mix unhelpfully with these partially-occupied states. As a rough guide, you want to include all the conduction states within a few &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; of your Fermi-energy, where &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is the standard-deviation of your energy broadening function, and &amp;quot;a few&amp;quot; is probably 5 or so (depending a little on the broadening function; some of them have long &amp;quot;tails&amp;quot;).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-03-03T01:06:41.140" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10523" PostTypeId="1" CreationDate="2023-03-03T05:50:49.873" Score="14" ViewCount="427" Body="&lt;p&gt;I am computing maximally localized Wannier functions (MLWFs) for several high-pressure phases of a system I am studying using wannier90. For some of these calculations, I see that the imaginary part of the MLWFs obtained is large. This can be seen in the following snippet from the output (Notice the larger than 1 Imaginary/Real ratio):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; *---------------------------------------------------------------------------*&#xA; |                               PLOTTING                                    |&#xA; *---------------------------------------------------------------------------*&#xA; &#xA;      Wannier Function Num:    1       Maximum Im/Re Ratio =    1.336516&#xA;      Wannier Function Num:    2       Maximum Im/Re Ratio =    1.095717&#xA;      Wannier Function Num:    3       Maximum Im/Re Ratio =    1.081907&#xA;      Wannier Function Num:    4       Maximum Im/Re Ratio =    1.179449&#xA;      Wannier Function Num:    5       Maximum Im/Re Ratio =    1.344709&#xA;      Wannier Function Num:    6       Maximum Im/Re Ratio =    1.360211&#xA;      Wannier Function Num:    7       Maximum Im/Re Ratio =    1.161190&#xA;      Wannier Function Num:    8       Maximum Im/Re Ratio =    1.302460&#xA;      Wannier Function Num:    9       Maximum Im/Re Ratio =    1.150868&#xA;      Wannier Function Num:   10       Maximum Im/Re Ratio =    1.230385&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From several &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/wannier/2013-February/000610.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;mailing list threads&lt;/a&gt;, &lt;a href=&quot;https://indico.ictp.it/event/8301/session/96/contribution/533/material/1/0.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt; and literature, I see that this means that the MLWFs have converged to a local minimum as opposed to the global minimum we are interested in. For example, in &lt;a href=&quot;https://link.aps.org/doi/10.1103/RevModPhys.84.1419&quot; rel=&quot;nofollow noreferrer&quot;&gt;this review&lt;/a&gt; it is mentioned that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It should be noted that the localization functional can display, in addition to the desired global minimum, multiple local minima that do not lead to the construction of meaningful localized orbitals. Heuristically, it is also found that the WFs corresponding to these local minima are intrinsically complex, while they are found to be real, apart from a single complex phase, at the desired global minimum (provided of course that the calculations do not include spin-orbit coupling)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Thus, assuming that the MLWFs I obtained are at a local minimum, I have tried some suggestions from these threads to solve this issue:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Better choice of initial guess:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;trying different initial guesses and&lt;/li&gt;&#xA;&lt;li&gt;using the SCDM approach (a method which doesn't require specifying an initial guess)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;If the system is metallic, include some unoccupied states in the procedure&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The system does not seem to be metallic.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But these have not solved the issue and the large imaginary components are still present in the MLWFs obtained.&lt;/p&gt;&#xA;&lt;p&gt;The above quoted literature mentions that MLWFs are supposed to be real at the global minimum, but I do not understand the reason for this. Is there a reason for the MLWFs to be real at the global minimum? Any literature regarding this would be helpful.&lt;/p&gt;&#xA;&lt;p&gt;Note: Alternatively, if there are any other methods that avoid these issues which I can use to obtain the MLWFs corresponding to the global minimum, I would also consider that an answer to my immediate problem.&lt;/p&gt;&#xA;" OwnerUserId="85" LastEditorUserId="85" LastEditDate="2023-03-28T04:49:27.533" LastActivityDate="2023-03-31T08:20:10.187" Title="Why are maximally localized Wannier functions supposed to be real?" Tags="|reference-request|wannier90|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10524" PostTypeId="2" ParentId="10510" CreationDate="2023-03-03T12:56:59.210" Score="4" Body="&lt;ol&gt;&#xA;&lt;li&gt;You must make sure that the structure that you predict 'makes sense.' This means that it must follow some logical reasoning in construction of the unit cell and the material. Fo example, consider that you are trying to predict &lt;span class=&quot;math-container&quot;&gt;$\textit{h}$&lt;/span&gt;-BN from graphene, the line of thought that you would ideally follow is a B-N segment is isoelectronic amd isolobal with a C-C segment, and can be replaced.&lt;/li&gt;&#xA;&lt;li&gt;Making sure that proper reasoning is followed in generating the structure would ensure that you would have a better chance synthesizing the material, provided it has the properties that are of interest to you.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-03-03T12:56:59.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10525" PostTypeId="1" AcceptedAnswerId="10526" CreationDate="2023-03-03T14:25:20.583" Score="5" ViewCount="333" Body="&lt;p&gt;After 'vc-relax' calculation I got the cell parameters in the picture bellow. I want to mention that my ibrav=1.&lt;/p&gt;&#xA;&lt;p&gt;I think the optimized lattice parameter in this case is A=11.44879234*1.006676454 .But I'm not sure because I don't know if I have to include the number 0.000089189 . Can someone correct me please?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/U8mQ4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/U8mQ4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="269" LastEditDate="2023-03-03T22:44:23.723" LastActivityDate="2023-03-03T22:44:23.723" Title="How to calculate lattice parameter?" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|cell-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10526" PostTypeId="2" ParentId="10525" CreationDate="2023-03-03T15:04:17.307" Score="6" Body="&lt;p&gt;In your output file, there should be a line at the beginning saying &amp;quot;crystal axes: cart. coord. in units of alat)&amp;quot; like the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     crystal axes: (cart. coord. in units of alat)&#xA;               a(1) = (   1.000000   0.000000   0.000000 )  &#xA;               a(2) = (   0.000000   1.000000   0.000000 )  &#xA;               a(3) = (   0.000000   0.000000   1.000000 )  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Check these three lines to obtain the lattice vector. For example, if it is like the above, then what you have done is correct. If it is, let's say 0.5 instead of 1, then you have to divide what you have got with 0.5.&lt;/p&gt;&#xA;&lt;p&gt;You don't have to consider other numbers to get the lattice parameter since for ibrav=1, the lattice vector components are 0. But it is always a good practice to check the output file to make sure your lattice vectors are as you would expect. Also note that the unit is in Bohr.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-03T15:04:17.307" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10527" PostTypeId="2" ParentId="10513" CreationDate="2023-03-03T17:36:57.570" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;However, I am still unsure of how to specify that I want to run a calculation using GGA and LDA approximation in the input file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Quantum ESPRESSO (QE) uses a plain-text input file and consists of the so-called &lt;em&gt;namelists&lt;/em&gt; and &lt;em&gt;cards&lt;/em&gt;. Inside the required namelist &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt;, you can set your preferred exchange-correlation (XC) functional by using the keyword &lt;code&gt;input_dft&lt;/code&gt;. For example, a very simple input file might look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  pseudo_dir= './pseudo/'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav=1&#xA;  celldm(1)=5&#xA;  nat=1&#xA;  ntyp=1&#xA;  ecutwfc=50&#xA;  input_dft='PBE'&#xA;/&#xA;&amp;amp;ELECTRONS &#xA;/&#xA;ATOMIC_SPECIES&#xA;X     0.00000     X.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;X           0.0000000000       0.0000000000       0.0000000000 &#xA;K_POINTS automatic&#xA;6 6 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can replace &lt;code&gt;PBE&lt;/code&gt; with &lt;code&gt;BLYP&lt;/code&gt; or with your preferred type of functionals.&lt;/p&gt;&#xA;&lt;h4&gt;However,&lt;/h4&gt;&#xA;&lt;p&gt;Just because you can do it does not mean you should do it. Care should be taken before using this keyword. First of all, why do you want to specify the type of XC functional? QE can automatically read the XC functional from the pseudopotential (PP) file, i.e., here in the above example &lt;code&gt;X.UPF&lt;/code&gt;. So unless you are treating a very special problem that requires a specific kind of PP or you want to use your own generated PP, you can safely proceed without specifying the type of XC functional (you only need to choose your PP).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Could you please guide me on how to include the appropriate keyword in the input file to specify the exchange-correlation functional?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you want access to more XC functionals, one such way is using &lt;a href=&quot;https://tddft.org/programs/libxc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Libxc&lt;/a&gt; - which is a library of exchange-correlation and kinetic energy functionals for density-functional theory - please refer to section 2.6 of &lt;a href=&quot;https://www.quantum-espresso.org/wp-content/uploads/2022/03/user_guide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this document&lt;/a&gt;. Take note that depending on the version of your QE, the &lt;code&gt;input_dft&lt;/code&gt; notation is fundamentally different.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!For v7.0 or later&#xA;input_dft='XC-000I-000I-101L-130L-000I-000I'&#xA;!For earlier versions&#xA;input_dft='gga_x_pbe gga_c_pbe'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By using Libxc functionals, you can specify more types of functionals (a complete list is &lt;a href=&quot;https://www.tddft.org/programs/libxc/functionals/libxc-6.1.0/&quot; rel=&quot;nofollow noreferrer&quot;&gt;available here&lt;/a&gt;). To understand the notation, check the above-linked user manuals.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Also, I would greatly appreciate any advice on how to choose the best functional for my specific system and properties of interest.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As Camps said in the comments that you need to search the literature. There is no one-in-all formula. You can try various types of functional with prototypes of your system before doing actual calculations. From my (very little) experience, people usually stick with the popular XC functional choices. See &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/266/6055&quot;&gt;this question&lt;/a&gt; to know about popular functionals.&lt;/p&gt;&#xA;&lt;p&gt;Just for the sake of completeness, if one wants to use hybrid or non-local functional, the official &lt;a href=&quot;https://www.quantum-espresso.org/faq/faq-pseudopotentials/&quot; rel=&quot;nofollow noreferrer&quot;&gt;QE website&lt;/a&gt; states:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;WHERE CAN I FIND PSEUDOPOTENTIAIS FOR HYBRID/NONLOCAL FUNCTIONALS?&#xA;Short answer: nowhere, for the time being. Use pseudopotentials for the non-hybrid functional that is closer to the hybrid you like: PBE for PBE0 and HSE, BLYP for B3LYP. Same for nonlocal (e.g. vdw-DF) functionals: use pseudopotentials generated for the closest GGA functional.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-03-05T19:32:35.893" LastActivityDate="2023-03-05T19:32:35.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10529" PostTypeId="1" CreationDate="2023-03-04T09:21:54.987" Score="6" ViewCount="97" Body="&lt;p&gt;Does Bioinformatics have any relationship with protein modeling and simulation?&lt;/p&gt;&#xA;&lt;p&gt;In other words, is there a research area where Bioinformatics uses protein modeling and simulation to achieve its goal or vice versa?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; No wet lab, only computer-based modeling, and simulation. E.g., Molecular Dynamics and Coarse-Grain Modeling with Monte Carlo for protein design.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-03-06T09:03:00.170" Title="Does Bioinformatics have any relationship with protein modeling and simulation?" Tags="|proteins|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10530" PostTypeId="1" AcceptedAnswerId="10558" CreationDate="2023-03-04T13:45:05.737" Score="7" ViewCount="655" Body="&lt;p&gt;If we sum over all the PDOS (Projected/Partial Density of States), will we have the total DOS or simply the DOS? This was not the case in my DOS and PDOS results for a simple Al atom. I am wondering what could be the reason.&lt;/p&gt;&#xA;&lt;p&gt;Is the choice of Wigner radius affecting the PDOS results? So, summing over the PDOS results might be a little less or a little more than the total DOS in my understanding because you cannot fill a square-edged box with spheres of finite radius.&lt;/p&gt;&#xA;&lt;p&gt;Is this explanation correct? Or is there another explanation such as this is a known issue only in Quantum ESPRESSO (QE)? Or should we get the DOS exactly by summing over all the projections (which means I made some mistakes during my calculation)?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; On page 24 of &lt;a href=&quot;https://www.fisica.uniud.it/%7Egiannozz/QE-Tutorial/handson_pwscf.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial&lt;/a&gt; by Giannozzi (author of QE), he mentioned that they are not exactly the same. He didn't explain the reason there though. So, I don't think this is a mistake. Now my question is, what could be the reason behind this discrepancy? What exactly is the role of the Wigner radius in the calculation of PDOS?&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-03-06T16:36:19.383" LastActivityDate="2023-03-11T01:24:58.203" Title="Why do we not get DOS by summing over all the PDOS?" Tags="|density-functional-theory|quantum-espresso|solid-state-physics|density-of-states|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10531" PostTypeId="1" AcceptedAnswerId="10537" CreationDate="2023-03-05T18:05:24.967" Score="6" ViewCount="172" Body="&lt;p&gt;This question is asked in the context of the famous &lt;a href=&quot;https://doi.org/10.1103/PhysRev.136.B864&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; on DFT by Hohenberg and Kohn. What makes the inhomogeneous electron gas more interesting than its homogeneous counterpart?&lt;/p&gt;&#xA;" OwnerUserId="5138" LastEditorUserId="142" LastEditDate="2023-03-06T17:49:44.937" LastActivityDate="2023-03-08T12:03:54.500" Title="What makes the inhomogeneous electron gas more interesting than its homogeneous counterpart?" Tags="|density-functional-theory|computational-chemistry|electronic-structure|solid-state-physics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10532" PostTypeId="1" CreationDate="2023-03-05T21:26:40.480" Score="3" ViewCount="66" Body="&lt;p&gt;&lt;strong&gt;Kohn Anomaly&lt;/strong&gt; and &lt;strong&gt;Avoided Crossing (Anticrossing/Level Repulsion)&lt;/strong&gt; are terms that are found to be used when discussing phonon dispersion. The former (&lt;a href=&quot;http://www.condmat.physics.manchester.ac.uk/pdf/mesoscopic/publications/graphene/Naturemat_2007Raman.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;see&lt;/a&gt; last paragraph, page 198) is related to electron-phonon coupling, while the latter (&lt;a href=&quot;https://doi.org/10.1016/j.mtphys.2018.02.005&quot; rel=&quot;nofollow noreferrer&quot;&gt;refer&lt;/a&gt; 2nd paragraph, page 55) is related to phonon-phonon coupling. Both phenomena lower the phonon frequency.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are these concepts same, related or different?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5138" LastEditorUserId="5138" LastEditDate="2023-03-06T06:23:04.713" LastActivityDate="2023-03-06T06:23:04.713" Title="Kohn anomaly and avoided crossing (or anticrossing/level repulsion)" Tags="|density-functional-theory|condensed-matter|quantum-mechanics|phonons|solid-state-physics|" AnswerCount="0" CommentCount="3" ClosedDate="2023-10-13T16:52:37.903" ContentLicense="CC BY-SA 4.0" />
  <row Id="10533" PostTypeId="1" CreationDate="2023-03-06T06:08:31.760" Score="4" ViewCount="202" Body="&lt;p&gt;I would like to ask how to calculate spin density like shown in Fig 2(f) in &lt;a href=&quot;https://www.nature.com/articles/s41467-022-29797-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; using Quantum ESPRESSO? A simple tutorial/example will be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aJYAq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aJYAq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4827" LastEditorUserId="6055" LastEditDate="2023-03-06T12:17:43.150" LastActivityDate="2023-03-06T12:17:43.150" Title="How to calculate spin density in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|spin-polarization|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-22T20:11:39.777" ContentLicense="CC BY-SA 4.0" />
  <row Id="10534" PostTypeId="2" ParentId="10529" CreationDate="2023-03-06T09:03:00.170" Score="6" Body="&lt;p&gt;Yes - protein and RNA folding has been a subject of research in bioinformatics for several decades, and have received much development in the last couple of years due to application of machine learning. Let me add a few more detailed comments:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Application of machine learning in bioinformatics is not a recent invention - see, e.g., &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/026202506X&quot; rel=&quot;noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bioinformatics: The Machine Learning Approach&lt;/a&gt; is a book published more than two decades ego, outlining the main uses of ML in bioinformatics, including protein and RNA folding. Of course, the general development of machine learning methods, computational capacities and importantly sequencing technologies in the last two decades mean that the topic is still very much relevant - but there is a lot to learn.&lt;/li&gt;&#xA;&lt;li&gt;When it comes to protein and RNA structure, there is a significant overlap between bioinformatics and biophysics, since predicting protein structure requires understanding and modeling of how amino-acids bind together, the mechanisms of this binding, etc. So sometimes one uses term &lt;em&gt;computational biology&lt;/em&gt;, using &lt;em&gt;bioinformatics&lt;/em&gt; in a narrower sense, as the subject concerned only with sequence analysis and mostly with the lower end sequence analysis (cleaning data, mapping reads, sequence assembly, etc.)&lt;/li&gt;&#xA;&lt;li&gt;RNA structure prediction is a domain in itself, rather different from protein modeling. There are some rather original and by now classical contributions here, compulsory in nearly every bioinformatics course, - like &lt;em&gt;Nussinov algorithm&lt;/em&gt; or the use of &lt;em&gt;context-free grammars&lt;/em&gt; - see, e.g., the book by Durbin et al. &lt;a href=&quot;https://www.amazon.fr/Biological-Sequence-Analysis-Probabilistic-Proteins/dp/0521629713&quot; rel=&quot;noreferrer&quot;&gt;Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I could suggest a few of my posts in other communities for further exploration:&lt;br /&gt;&#xA;&lt;a href=&quot;https://bioinformatics.stackexchange.com/a/15315/1813&quot;&gt;What are the applications of DNA or RNA pattern matching?&lt;/a&gt;&lt;br /&gt;&#xA;&lt;a href=&quot;https://physics.stackexchange.com/a/612999/247642&quot;&gt;How to model RNA-DNA and DNA-DNA binding as a “string matching&amp;quot; problem in statistical physics?&lt;/a&gt;&lt;br /&gt;&#xA;&lt;a href=&quot;https://physics.stackexchange.com/a/625539/247642&quot;&gt;Does physics explain why the laws and behaviors observed in biology are as they are?&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6274" LastActivityDate="2023-03-06T09:03:00.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10535" PostTypeId="2" ParentId="10361" CreationDate="2023-03-06T14:09:21.357" Score="5" Body="&lt;p&gt;Andrew White's resource on deep learning for molecules and materials, &lt;a href=&quot;https://dmol.pub/&quot; rel=&quot;noreferrer&quot;&gt;https://dmol.pub/&lt;/a&gt;, is not technically a course, but has enough volume and importantly enough python examples to have been useful to me. Compared to the series by Florian Marquardt, it covers more advanced topics including physical symmetry operations (invariance and equivariance) within machine learning.&lt;/p&gt;&#xA;" OwnerUserId="4515" LastActivityDate="2023-03-06T14:09:21.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10536" PostTypeId="1" CreationDate="2023-03-06T16:50:28.427" Score="5" ViewCount="169" Body="&lt;p&gt;I am trying to produce a band structure for TiO2, with the cell file shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%BLOCK Lattice_ABC&#xA;  4.853556 4.853556 3.018297&#xA;  90.0 90.0 89.989556&#xA;%ENDBLOCK Lattice_ABC&#xA;&#xA;%BLOCK Positions_Frac&#xA;  Ti 0.0 0.0 0.0&#xA;  Ti 0.5 0.5 0.5&#xA;  O  0.194689 0.805311 0.5&#xA;  O  0.805311 0.194689 0.5&#xA;  O  0.694707 0.694707 0.0&#xA;  O  0.305293 0.305293 0.0&#xA;%ENDBLOCK Positions_Frac&#xA;&#xA;SPECTRAL_KPOINT_PATH_SPACING: 0.1&#xA;&#xA;%BLOCK SPECTRAL_KPOINT_PATH&#xA;    0.0000000000     0.0000000000     0.0000000000 !    GAMMA&#xA;    0.0000000000     0.5000000000     0.0000000000 !    X&#xA;    0.5000000000     0.5000000000     0.0000000000 !    M&#xA;    0.0000000000     0.0000000000     0.0000000000 !    GAMMA&#xA;    0.0000000000     0.0000000000     0.5000000000 !    Z&#xA;    0.0000000000     0.5000000000     0.5000000000 !    R&#xA;    0.5000000000     0.5000000000     0.5000000000 !    A&#xA;    0.0000000000     0.0000000000     0.5000000000 !    Z&#xA;    BREAK&#xA;    0.0000000000     0.5000000000     0.0000000000 !    X&#xA;    0.0000000000     0.5000000000     0.5000000000 !    R&#xA;    BREAK&#xA;    0.5000000000     0.5000000000     0.0000000000 !    M&#xA;    0.5000000000     0.5000000000     0.5000000000 !    A&#xA;%ENDBLOCK SPECTRAL_KPOINT_PATH&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;&lt;p&gt;The band structure plot produced does not contain breaks between the K points, as can be seen below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6UoAc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6UoAc.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any help on why they are connected, and how to separate them to achieve something more like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/sZ71C.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sZ71C.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6627" LastEditorUserId="5" LastEditDate="2023-03-06T18:57:31.063" LastActivityDate="2023-03-07T14:01:10.227" Title="How to add a break into CASTEP k-point path" Tags="|band-structure|k-points|castep|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10537" PostTypeId="2" ParentId="10531" CreationDate="2023-03-06T17:53:04.120" Score="9" Body="&lt;p&gt;The homogeneous electron gas is a fiction: it represents a system that is completely uniform and that has a constant, smooth positive background charge to make the system charge neutral.&lt;/p&gt;&#xA;&lt;p&gt;However, the homogeneous electron gas is useful: since the electron density is the same at every point in space, there is a simple mapping from the density to the exact energy of the system. For instance, you can evaluate the exact energy with e.g. Quantum Monte Carlo for every value of the density, and then interpolate between the values.&lt;/p&gt;&#xA;&lt;p&gt;Real molecules and crystals do not have a homogeneous external field. Instead, the Coulomb potential of atomic nuclei is highly inhomogeneous. This is why the inhomogeneous electron gas is important in practice, and it is also more challenging to model than the theoretical homogeneous electron gas.&lt;/p&gt;&#xA;&lt;p&gt;The theories for the inhomogeneous electron gas, such as generalized gradient approximations (GGAs) and meta-GGAs, are commonly built as corrections to the LDA. For instance, exchange functionals are often written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E_{\rm xc} = \int n \epsilon^{\rm LDA}_{\rm xc} (n) F_x (\nabla n, \tau) {\rm d}^3r $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$F_x$&lt;/span&gt; is the enhancement function which modifies the LDA exchange energy density &lt;span class=&quot;math-container&quot;&gt;$n \epsilon^{\rm LDA}$&lt;/span&gt; depending on the gradient and local kinetic energy in the point, for a meta-GGA.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-03-08T12:03:54.500" LastActivityDate="2023-03-08T12:03:54.500" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10538" PostTypeId="1" CreationDate="2023-03-06T21:05:21.120" Score="4" ViewCount="553" Body="&lt;p&gt;I created a CIF file using the experimental parameters of my material, then I used it to create my input file for the unit cell using &lt;code&gt;Cif2Cell&lt;/code&gt;. After that, I relaxed the structure using &lt;code&gt;vc-relax&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If I want to create a supercell (of the same unit cell) to introduce a defect, do I have to use the CIF file with experimental parameters to create the supercell using &lt;code&gt;Cif2Cell&lt;/code&gt; then relax the structure using &lt;code&gt;vc-relax&lt;/code&gt;, or can I directly create a supercell using  my input file of the optimized unit cell (without optimizing the supercell)?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-04-10T17:29:53.603" LastActivityDate="2023-04-10T17:29:53.603" Title="What's the appropriate method to create a supercell for Quantum ESPRESSO?" Tags="|quantum-espresso|geometry-optimization|supercell|cif|cell-optimization|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10539" PostTypeId="1" AcceptedAnswerId="10544" CreationDate="2023-03-07T05:01:26.813" Score="7" ViewCount="2582" Body="&lt;p&gt;I'm a master's student and recently I started doing computational chemistry calculations using ORCA program.&lt;br /&gt;&#xA;This program works by command line and I saw that the majority of computational chemistry programs work in a similar way.&lt;/p&gt;&#xA;&lt;p&gt;My question is: is it possible to make them work through a Python script?&lt;br /&gt;&#xA;I think it would be very convenient since it could be possible to create new files and organize them with Python.&lt;br /&gt;&#xA;I tried this code (very easy HF ( Hartree-Fock) calculation for Hydrogen molecule):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import os&#xA;folder_name = &amp;quot;D:\\prove_orca\\Orca_con_Python\\Hydrogen_molecule&amp;quot;&#xA;file_name = &amp;quot;H2&amp;quot;&#xA;os.chdir(folder_name)&#xA;os.system(&amp;quot;D:\\ORCA\\orca&amp;quot; + &amp;quot; &amp;quot; + file_name + &amp;quot;.inp&amp;quot; + &amp;quot; &amp;quot; + &amp;quot;&amp;gt;&amp;quot; + &amp;quot; &amp;quot; + file_name + &amp;quot;.out&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Running the ORCA tool through Python&#xA;gives me a memory error. However if I run the calculation directly from the command line everything is fine.&lt;/p&gt;&#xA;&lt;p&gt;Here the code of the .inp file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! HF def2-svp&#xA;&#xA;%pal nprocs 16 # any number (positive integer)&#xA;end&#xA;&#xA;* xyzfile 0 1 coord.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The problem is not in the script, but in ORCA, that give me this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[file orca_tools/qcmem.cpp, line 1043, Process 5]:  OUT OF MEMORY ERROR! &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you have any advice or resources I can read?&lt;/p&gt;&#xA;" OwnerUserId="5294" OwnerDisplayName="Al1010" LastEditorUserId="5" LastEditDate="2023-03-10T12:07:07.423" LastActivityDate="2023-03-10T12:07:07.423" Title="Running an ORCA calculation from Python" Tags="|computational-chemistry|python|high-performance-computing|orca|programming|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10540" PostTypeId="2" ParentId="10539" CreationDate="2023-03-07T10:55:21.880" Score="3" Body="&lt;p&gt;What you are thinking of is a &lt;em&gt;workflow manager&lt;/em&gt;. I have recently had some success with &lt;a href=&quot;https://signac.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Signac&lt;/a&gt; -- it automates repetitive calculations over a parameter space, automatically saving state between subtasks that you can specify. Other similar packages include Snakemake and Fireworks, and you can always go back to good old CMake.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-03-07T10:55:21.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10541" PostTypeId="1" AcceptedAnswerId="10593" CreationDate="2023-03-07T12:50:38.247" Score="4" ViewCount="194" Body="&lt;p&gt;I found in the internet a method to generate a supercell from the input file using Phonopy code. And I have a question if someone can clarify my doubts please. The method is as following:&lt;/p&gt;&#xA;&lt;p&gt;We make an input file where the structure is defined by 'ibrav', 'nat', 'ntyp', 'ATOMIC_SPECIES', 'ATOMIC_POSITIONS', 'CELL_PARAMETERS'. It is noticeable that 'ibrav' must be 0 in the input files to use Phonopy, which means the 'CELL_PARAMETERS' must be defined for the structure. Also, the unit for 'ATOMIC_POSITIONS', 'CELL_PARAMETERS' do not need parentheses.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation='scf',&#xA;    outdir='temp',&#xA;    pseudo_dir = '.',&#xA;/&#xA; &amp;amp;system    &#xA;    ibrav= 0,&#xA;    celldm(1) =7.66,&#xA;    nat= 1,&#xA;    ntyp= 1,&#xA;    ecutwfc =60.0, &#xA;/&#xA;ATOMIC_SPECIES&#xA; Bi  208.9804 Bi.pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA; Bi 0.00000000 0.00000000 0.00000000&#xA;CELL_PARAMETERS angstrom&#xA;-2.025  2.025   2.025&#xA;2.025   -2.025  2.025&#xA;2.025   2.025   -2.025&#xA;K_POINTS automatic&#xA; 19 19 19 0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Run Phonopy&lt;/p&gt;&#xA;&lt;p&gt;To run Phonopy, just simply type :&#xA;&lt;code&gt;phonopy --qe -d --dim=&amp;quot;2 2 2&amp;quot; -c Bi.in&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this example, the 2&lt;em&gt;2&lt;/em&gt;2 supercell is created.&lt;/p&gt;&#xA;&lt;p&gt;The output will show the number of atoms and the 'CELL_PARAMETERS' and atom positions for supercell. Here is the output looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!    ibrav = 0, nat = 27, ntyp = 1&#xA;CELL_PARAMETERS bohr&#xA;  -11.4800862825768686   11.4800862825768686   11.4800862825768686&#xA;   11.4800862825768686  -11.4800862825768686   11.4800862825768686&#xA;   11.4800862825768686   11.4800862825768686  -11.4800862825768686&#xA;ATOMIC_SPECIES&#xA; Bi  208.98040   Bi.pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA; Bi   0.0000000000000000  0.0000000000000000  0.0000000000000000&#xA; Bi   0.3333333333333333  0.0000000000000000  0.0000000000000000&#xA; Bi   0.6666666666666666  0.0000000000000000  0.0000000000000000&#xA; Bi   0.0000000000000000  0.3333333333333333  0.0000000000000000&#xA; Bi   0.3333333333333333  0.3333333333333333  0.0000000000000000&#xA; Bi   0.6666666666666666  0.3333333333333333  0.0000000000000000&#xA; Bi   0.0000000000000000  0.6666666666666666  0.0000000000000000&#xA; Bi   0.3333333333333333  0.6666666666666666  0.0000000000000000&#xA; Bi   0.6666666666666666  0.6666666666666666  0.0000000000000000&#xA; Bi   0.0000000000000000  0.0000000000000000  0.3333333333333333&#xA; Bi   0.3333333333333333  0.0000000000000000  0.3333333333333333&#xA; Bi   0.6666666666666666  0.0000000000000000  0.3333333333333333&#xA; Bi   0.0000000000000000  0.3333333333333333  0.3333333333333333&#xA; Bi   0.3333333333333333  0.3333333333333333  0.3333333333333333&#xA; Bi   0.6666666666666666  0.3333333333333333  0.3333333333333333&#xA; Bi   0.0000000000000000  0.6666666666666666  0.3333333333333333&#xA; Bi   0.3333333333333333  0.6666666666666666  0.3333333333333333&#xA; Bi   0.6666666666666666  0.6666666666666666  0.3333333333333333&#xA; Bi   0.0000000000000000  0.0000000000000000  0.6666666666666666&#xA; Bi   0.3333333333333333  0.0000000000000000  0.6666666666666666&#xA; Bi   0.6666666666666666  0.0000000000000000  0.6666666666666666&#xA; Bi   0.0000000000000000  0.3333333333333333  0.6666666666666666&#xA; Bi   0.3333333333333333  0.3333333333333333  0.6666666666666666&#xA; Bi   0.6666666666666666  0.3333333333333333  0.6666666666666666&#xA; Bi   0.0000000000000000  0.6666666666666666  0.6666666666666666&#xA; Bi   0.3333333333333333  0.6666666666666666  0.6666666666666666&#xA; Bi   0.6666666666666666  0.6666666666666666  0.6666666666666666&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I didn't understand how did they calculate the lattice parameter of the supercell.I also want to know if something change in ATOMIC_POSITIONS of the unit cell when we replace alat by crystal?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-03-17T14:45:41.060" Title="How to calculate the lattice parameter of a supercell using Phonopy? (For Quantum ESPRESSO)" Tags="|density-functional-theory|quantum-espresso|geometry-optimization|phonopy|supercell|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10542" PostTypeId="1" CreationDate="2023-03-07T13:29:17.970" Score="5" ViewCount="393" Body="&lt;p&gt;I am trying to use Quantum ESPRESSO in ASE, but I keep getting the following error. When I run &lt;code&gt;pw.x&lt;/code&gt; directly from the terminal, it works, so Quantum ESPRESSO appears to be installed correctly and it's path is seen. I have no idea how to deal with this.&lt;/p&gt;&#xA;&lt;p&gt;Here is the complete error stack trace:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/optimize/lbfgs.py&amp;quot;, line 65, in __init__&#xA;Optimizer.__init__(self, atoms, restart, logfile, trajectory, master,&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/optimize/optimize.py&amp;quot;, line 234, in __init__&#xA;self.set_force_consistent()&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/optimize/optimize.py&amp;quot;, line 325, in set_force_consistent&#xA;self.atoms.get_potential_energy(force_consistent=True)&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/constraints.py&amp;quot;, line 2420, in get_potential_energy&#xA;atoms_energy = self.atoms.get_potential_energy(&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/atoms.py&amp;quot;, line 728, in get_potential_energy&#xA;energy = self._calc.get_potential_energy(&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/calculators/calculator.py&amp;quot;, line 709, in get_potential_energy&#xA;energy = self.get_property('energy', atoms)&#xA;&#xA; File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/calculators/calculator.py&amp;quot;, line 737, in get_property&#xA;self.calculate(atoms, [name], system_changes)&#xA;&#xA;File &amp;quot;/home/doug/.local/lib/python3.10/site-packages/ase/calculators/calculator.py&amp;quot;, line 938, in calculate&#xA;raise CalculationFailed(msg) ase.calculators.calculator.CalculationFailed: Calculator &amp;quot;espresso&amp;quot; failed with command &amp;quot;pw.x -in espresso.pwi failed in /home/doug/Documents/qetest with error code 127&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5193" LastEditorUserId="6687" LastEditDate="2023-03-11T14:36:18.187" LastActivityDate="2023-03-11T14:36:18.187" Title="Quantum ESPRESSO won't work in ASE" Tags="|density-functional-theory|quantum-espresso|python|atomic-simulation-environment|" AnswerCount="0" CommentCount="3" ClosedDate="2023-10-13T16:52:26.670" ContentLicense="CC BY-SA 4.0" />
  <row Id="10543" PostTypeId="2" ParentId="10536" CreationDate="2023-03-07T14:01:10.227" Score="2" Body="&lt;p&gt;Your &lt;code&gt;.cell&lt;/code&gt; file is correct, and CASTEP has added a break between the k-point path for the spectral kpoints; for example, there are no spectral k-points between the Z and X points.&lt;/p&gt;&#xA;&lt;p&gt;What you are seeing in your band-structure plot is that the plotting software is joining the bands directly between the points either side of the break. Your first plot looks like xmgrace, perhaps because you're using the simple &lt;code&gt;dispersion.pl&lt;/code&gt; script we distribute with CASTEP; I don't think that you can stop the points being joined by lines on a case-by-case basis, you'd have to either remove the lines entirely or leave it as it is. The CASTEP output is just a set of eigenvalues at a set of k-points, so there's no way for a plotting program to know whether they are to be &amp;quot;joined up&amp;quot; or not, you'd have to instruct it directly.&lt;/p&gt;&#xA;&lt;p&gt;For xmgrace, I think the only way would be to split the data sets around the &amp;quot;break&amp;quot; and plot them separately, and then move the x-coordinate of the different k-points together. Other plotting software might be more flexible in that respect.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-03-07T14:01:10.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10544" PostTypeId="2" ParentId="10539" CreationDate="2023-03-07T14:12:03.823" Score="11" Body="&lt;p&gt;I ran your script on my PC with Python and it ran perfectly fine.&lt;/p&gt;&#xA;&lt;p&gt;Here are all of the required PC specifications:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;System Specs&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Windows 11 Pro&#xA;8 GB RAM&#xA;Intel(R) Core(TM) i5-10310U CPU @ 1.70GHz   2.21 GHz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Software specs:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Python version 3.10&#xA;ORCA 5.0.4, Windows, 64bit&#xA;PyCharm 2022.3.2 (Community Edition)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Detailed steps:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I list all the steps in detail here so you can reproduce them:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Installed ORCA by downloading all the 3 zip files &lt;code&gt;(ORCA 5.0.4, Windows, 64bit, .zip Archive, Part 1, 2 and 3 )&lt;/code&gt; from the ORCA website and unzipping them into a folder : &lt;code&gt;C:\orca&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Altered the input file to use the coordinates inline like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! HF def2-svp&#xA;&#xA;%pal nprocs 16 # any number (positive integer)&#xA;end&#xA;&#xA;* xyzfile 0 1&#xA;H 0.0 0.0 -0.37&#xA;H 0.0 0.0  0.37&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Added &lt;code&gt;C:\orca&lt;/code&gt; folder to the PATH environment variable.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Installed Microsoft MPI from &lt;a href=&quot;https://learn.microsoft.com/en-us/message-passing-interface/microsoft-mpi&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; as per the orca manual&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ol start=&quot;5&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;Used the following Python code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import os&#xA;&#xA;os.system(&amp;quot;C:\\ORCA\\orca&amp;quot; + &amp;quot; &amp;quot; + &amp;quot;C:\Vandan\codes\chemistry\orca\hydrogen\hydrogen.inp&amp;quot; + &amp;quot; &amp;quot; + &amp;quot;&amp;gt;&amp;quot; + &amp;quot; &amp;quot; + &amp;quot;C:\Vandan\codes\chemistry\orca\hydrogen\hydrogen.out&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;It ran successfully and took about 4-5 seconds and creates an output file called &lt;code&gt;hydrogen.out&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;So possible reasons why it could be failing on your PC:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Maybe you have a 32-bit Python on a 64-bit Windows machine&lt;/li&gt;&#xA;&lt;li&gt;Maybe 16 processes are more than what your PC can accommodate, maybe try&#xA;reducing it&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-03-08T08:10:28.080" LastActivityDate="2023-03-08T08:10:28.080" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10545" PostTypeId="2" ParentId="9954" CreationDate="2023-03-07T14:29:33.980" Score="4" Body="&lt;p&gt;You need to change &lt;code&gt;def2-SVP def2-SVP/J&lt;/code&gt;  to &lt;code&gt;def2-SVP def2/J&lt;/code&gt; as per the &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/general-input&quot; rel=&quot;nofollow noreferrer&quot;&gt;ORCA manual&lt;/a&gt;, see the heading block input.&lt;/p&gt;&#xA;&lt;p&gt;I verified that this works on ORCA version : &lt;code&gt;ORCA 5.0.4, Windows, 64bit&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;The input file will look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# avogadro generated ORCA input file &#xA;# Basic Mode&#xA;# &#xA;! BP RI SP def2-SVP def2/J&#xA;&#xA;* xyz 0 1&#xA;   H        0.77899       -0.00348       -0.13267&#xA;   O       -0.14793        0.02998       -0.34219&#xA;   H       -0.63110       -0.02651        0.47487&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-03-07T14:29:33.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10546" PostTypeId="2" ParentId="10539" CreationDate="2023-03-07T18:20:57.830" Score="8" Body="&lt;p&gt;As the other answers and comments have suggested, the problem is probably coming from how Python is launching ORCA. Because I cannot see any reason the job should run from command line, but not from Python. Python's &lt;code&gt;os.system()&lt;/code&gt; calls the command shell directly, and runs the string as a command there.&lt;/p&gt;&#xA;&lt;p&gt;It might also be that you are running everything in a cluster (?). If that's the case, then the memory allocation needs to be fixed in the job submission script for the scheduler (like SLURM or SGE).&lt;/p&gt;&#xA;&lt;p&gt;I would also recommend using softwares that can write ORCA input files and run them automatically. For example, &lt;a href=&quot;https://github.com/duartegroup/autodE&quot; rel=&quot;noreferrer&quot;&gt;https://github.com/duartegroup/autodE&lt;/a&gt; provides a high-level interface to run common calculations with ORCA or Gaussian or other QM softwares (even though the program can also do other more specialised things like transition state finding etc.)&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import autode as ade&#xA;&#xA;# set ORCA as the QM engine&#xA;ade.Config.hcode = &amp;quot;ORCA&amp;quot;&#xA;ade.Config.ORCA.keywords.sp = ['SP','HF','def2-SVP']&#xA;# use 16 cores&#xA;ade.Config.n_cores = 16&#xA;&#xA;# read the molecule from xyz file&#xA;h2 = ade.Molecule(&amp;quot;h2.xyz&amp;quot;)&#xA;h2.single_point(method=ade.methods.ORCA())&#xA;print(h2.energy)  # gives -1.16401 Ha or something similar&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-03-07T18:20:57.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10547" PostTypeId="1" AcceptedAnswerId="10554" CreationDate="2023-03-07T21:40:06.817" Score="6" ViewCount="116" Body="&lt;p&gt;I know that one can determine which type of bond is present between different atoms in a molecule by analyzing the output of an NBO analysis. Furthermore the second order perturbation theory analysis can provide information about the presence interactions like hyperconjugation. But is there also a way to determine whether there are three-center four-electron bonds, i.e. hypervalency in a molecule by a NBO analysis ?&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2023-03-13T17:15:26.027" Title="NBO analysis of potentially hypervalent compounds" Tags="|computational-chemistry|electronic-structure|orbitals|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10548" PostTypeId="2" ParentId="10531" CreationDate="2023-03-08T08:41:44.857" Score="8" Body="&lt;p&gt;In contemporary Kohn-Sham DFT, the exchange and correlation energies are local quantities. If the electron density is slowly varying, the LDA form derived from a uniform electron gas is a zero'th order approximation. This is the underlying reason that the various XC functionals written in terms of density, density gradient, and possibly higher order information, often are required to revert to the LDA form when the derivatives become zero.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-03-08T08:41:44.857" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10549" PostTypeId="2" ParentId="10461" CreationDate="2023-03-08T11:53:21.157" Score="5" Body="&lt;p&gt;This can be achieved by a 2-step process:&lt;/p&gt;&#xA;&lt;p&gt;Step 1: Convert XYZ to SDF using this open source python library &lt;a href=&quot;https://github.com/jensengroup/xyz2mol&quot; rel=&quot;nofollow noreferrer&quot;&gt;xyz2mol&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Step 2: Use the SDF to get the bond order and formal charge information using Python + rdkit.&lt;/p&gt;&#xA;&lt;p&gt;Below is a fully reproducible example of both steps using Methanol as a sample compound.&#xA;All of the following can be run in a Google Colab notebook:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!git clone https://github.com/jensengroup/xyz2mol&#xA;%cd xyz2mol&#xA;!pip install -r requirements.txt&#xA;!pip install rdkit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Download the XYZ file of methanol from &lt;a href=&quot;https://github.com/nutjunkie/IQmol/blob/master/share/fragments/Molecules/Alcohols/Methanol.xyz&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Convert the XYZ to SDF like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!python xyz2mol.py path-to-methanol.xyz -o sdf &amp;gt; path-to-methanol.sdf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Use the SDF for extracting bond order and formal charge:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem.rdmolfiles import SDMolSupplier&#xA;from rdkit.Chem.rdmolops import GetFormalCharge&#xA;&#xA;suppl = SDMolSupplier('/content/drive/MyDrive/output/methanol.sdf',removeHs=False)&#xA;for mol in suppl:&#xA;   if mol is not None: &#xA;&#xA;     for bond in mol.GetBonds():&#xA;       print(bond.GetBeginAtom().GetSymbol(),  bond.GetEndAtom().GetSymbol(), bond.GetBeginAtomIdx(), bond.GetEndAtomIdx(), bond.GetBondTypeAsDouble()) &#xA;&#xA;&amp;gt;&amp;gt; This will output the following:&#xA;    C H 3 0 1.0&#xA;    H C 1 3 1.0&#xA;    H C 2 3 1.0&#xA;    C O 3 4 1.0&#xA;    O H 4 5 1.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here the last column is the bond order.&lt;/p&gt;&#xA;&lt;p&gt;And to get formal charge :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;GetFormalCharge(mol)&#xA;&#xA;&amp;gt;&amp;gt; 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Documentation on the &lt;code&gt;GetBondTypeAsDouble&lt;/code&gt; function is available on rdkit &lt;a href=&quot;https://www.rdkit.org/docs/source/rdkit.Chem.rdchem.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-04-13T15:27:26.850" LastActivityDate="2023-04-13T15:27:26.850" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10550" PostTypeId="2" ParentId="10461" CreationDate="2023-03-08T12:03:25.567" Score="3" Body="&lt;p&gt;This depends on your workflow purpose. It is usually straightforward to draw chemically sensible bonds between atoms -- this can be done in VMD using Topotools, as one example -- but partial charges are entirely different.&lt;/p&gt;&#xA;&lt;p&gt;If you simply want a sensible charge distribution for a snapshot somehow, you could try a single structure charge equilibration by loading your structure into LAMMPS and applying a suitable ReaxFF charge equilibration procedure (simply &lt;code&gt;run 0&lt;/code&gt; and write out the data file which will have updated charges).&lt;/p&gt;&#xA;&lt;p&gt;But you may need &lt;em&gt;transferable&lt;/em&gt; charges (every methanol O has the same charge, every acetonitrile N has the same charge, ...) for continuing on to do molecular dynamics (indeed, a good initial charge guess is also very helpful for the above mentioned ReaxFF procedure). In that case you're better off identifying the chemical species in your simulation and then going to either published force fields or something like the Automated Topology Builder for your force field.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-03-08T12:03:25.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10551" PostTypeId="1" CreationDate="2023-03-09T17:58:30.157" Score="3" ViewCount="31" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BOVmQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BOVmQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;After running the input pw_bands.in file execution is not stopping even after 10hrs , and the output is not updating anything further after 1 min of the output.&lt;/p&gt;&#xA;" OwnerUserId="6846" LastEditorUserId="5" LastEditDate="2023-03-09T19:50:14.453" LastActivityDate="2023-03-09T19:50:14.453" Title="Issue with getting pw_bands output file for ws2" Tags="|density-functional-theory|quantum-espresso|band-structure|electronic-structure|density-of-states|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:52:13.693" ContentLicense="CC BY-SA 4.0" />
  <row Id="10552" PostTypeId="1" AcceptedAnswerId="10555" CreationDate="2023-03-10T00:24:10.153" Score="3" ViewCount="55" Body="&lt;p&gt;There is this method called nucleus-independent chemical shift (NICS) to calculate the magnetic shielding values at different spatial coordinates of a molecular system. It can be used to estimate the aromatic character of a system by evaluating the magnetic shieldings inside a potentially aromatic cyclic system. The calculated values correspond to the magnetic shielding tensor, the elements of which are given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sigma = \frac{\partial^{2} E}{\partial B_{i} \partial m_{j}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Furthermore there is the method of gauge-including magnetically induced currents (GIMIC) which can also be used to estimate the aromaticity of a system based on ring currents of a conjugated cyclic system. In this case the current density susceptibility tensor is evaluated.&lt;/p&gt;&#xA;&lt;p&gt;Because the quantities studied by the aforementioned methods arise from the influence of external magnetic fields I am wondering how high the external magnetic field implied in these calculations actually is. Is there even an external magnetic field implied in these calculations or am I missing something here ? I know that chemical shifts are basically independent of the external magnetic field but only because of the use of an NMR standard, which eliminates this dependency. The answer seems simple but I am kind of caught in confusion by now.&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2023-03-10T10:20:28.007" Title="External magnetic field in magnetic shielding calculations" Tags="|computational-chemistry|magnetic-field|nuclear-magnetic-resonance|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10553" PostTypeId="1" AcceptedAnswerId="10556" CreationDate="2023-03-10T06:12:41.327" Score="5" ViewCount="174" Body="&lt;p&gt;I want to visualise MPSH (molecular projected self-consistent Hamiltonian) orbitals using SISL package of siesta, is there any manual or guide for it.&lt;/p&gt;&#xA;&lt;p&gt;I have searched in internet but didn't get any proper information about it.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="6561" LastEditorUserId="6687" LastEditDate="2023-03-11T14:35:47.253" LastActivityDate="2023-03-11T14:35:47.253" Title="Regarding SISL package of siesta" Tags="|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10554" PostTypeId="2" ParentId="10547" CreationDate="2023-03-10T10:05:00.777" Score="4" Body="&lt;p&gt;It is possible to determine such 3-centre bonds using an NBO analysis.&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample output of an NBO analysis obtained from this &lt;a href=&quot;https://nbo6.chem.wisc.edu/ex_nbo.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1bPG4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1bPG4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The number of 3C (3-centre) bonds can be seen in the Lewis Structure column.&lt;/p&gt;&#xA;&lt;p&gt;A really good resource is the &lt;a href=&quot;https://www.scm.com/doc/ADF/_downloads/f279f6aa6305a5e9760338b2d0fc33f5/nbo6_manual.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;NBO 6.0 Manual&lt;/a&gt; to read more about such 3-centre bonds.&lt;/p&gt;&#xA;&lt;p&gt;There is a chapter in the manual called: B.16 3-CENTER, 4-ELECTRON HYPERBOND SEARCH&lt;/p&gt;&#xA;&lt;p&gt;Additionally for some theory on a quantitative definition of hypervalency, this &lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2015/sc/c5sc02076j&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; discusses a method to determine hypervalency using various charge models, one of which is NBO analysis.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-03-10T10:05:00.777" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10555" PostTypeId="2" ParentId="10552" CreationDate="2023-03-10T10:20:28.007" Score="1" Body="&lt;p&gt;When calculating nuclear magnetic shieldings or gauge-including magnetically induced currents, one only needs to determine the response of the system to an external magnetic field, and the derivatives are evaluated in the absence of external fields. It is also possible to do calculations with explicit magnetic fields in some programs, which allows e.g. the determination of nuclear magnetic shieldings with the use of finite difference rules. In either case, it is important to use gauge including atomic orbitals (GIAOs), as this will strongly accelerate the convergence to the basis set limit.&lt;/p&gt;&#xA;&lt;p&gt;The other use for explicit magnetic fields is to investigate the electronic structure in astrophysical environments, such as neutron star atmospheres, where the magnetic fields can have significant effects on the electronic structure unlike the case of terrestrial magnetic fields, which usually have negligible effects. A challenge for such calculations is the strong effect that magnetic fields have on the electronic structure: (i) the field couples to the electronic spin, changing the character of the ground state, and (ii) the field introduces a parabolic constrainment potential perpendicular to the field axis. This qualitative change results in significant errors in linear combination of atomic orbitals (LCAO) approaches, as we have described in S. Lehtola, M. Dimitrova, and D. Sundholm, &lt;a href=&quot;https://doi.org/10.1080/00268976.2019.1597989&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mol. Phys. 118, e1597989 (2020)&lt;/a&gt; &lt;a href=&quot;http://arxiv.org/abs/1812.06274&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv:1812.06274&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-03-10T10:20:28.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10556" PostTypeId="2" ParentId="10553" CreationDate="2023-03-10T11:22:23.067" Score="4" Body="&lt;p&gt;Calculating the MPSH in &lt;code&gt;sisl&lt;/code&gt; is quite easy.&lt;br /&gt;&#xA;First recognize that one can calculate the eigenstates of the Hamiltonian as:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;eigenstate = H.eigenstate(k=[0, 0, 0]) # at Gamma-point&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;An MPSH is nothing but the eigenstate of the sub-system of atoms that comprise the molecule. In sisl we can extract a subset like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;Hsub = H.sub(range(10, 20)) # python is 0-based indexing&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which will take out 10 atoms, starting at atom 11 (starting from index 1) up to and including atom 20.&lt;/p&gt;&#xA;&lt;p&gt;Then subsequently you only need to plot the wavefunction. Please note that this will only work if the geometry contained in the Hamiltonian contains the radial grid information for all orbitals. Generally sisl will be able to read the information if you haven't deleted files.&lt;/p&gt;&#xA;&lt;p&gt;The complete example is something like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl&#xA;# read in the hamiltonian and basis set information from the files in the&#xA;# output directory, RUN.fdf should be your base fdf input file.&#xA;H = sisl.get_sile(&amp;quot;RUN.fdf&amp;quot;).read_hamiltonian()&#xA;# reduce the Hamiltonian to a subset of the atoms/orbitals&#xA;Hmolecule = H.sub([atomic indices for the MPSH])&#xA;# say H.sub(range(20, 50)) will take the atoms 21-50 as a molecule&#xA;# calculate the eigenstate at the Gamma-point&#xA;es = Hmolecule.eigenstate()&#xA;# initialize the grid we want to plot on&#xA;grid = sisl.Grid(0.075, sc=H.sc)&#xA;# reduce the eigenstate to only 1 value, it makes little sense to plot multiple eigenstates in one go&#xA;es.sub(2).wavefunction(grid)&#xA;grid.write(&amp;quot;MPHS_3.cube&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This tutorial might be helpful: &lt;a href=&quot;https://zerothi.github.io/sisl/tutorials/tutorial_es_1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://zerothi.github.io/sisl/tutorials/tutorial_es_1.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Please note that &lt;code&gt;sisl&lt;/code&gt; is not restricted to Hamiltonians from Siesta, it can also process user defined TB models, wannier90 Hamiltonians, and hopefully soon OpenMX Hamiltonians.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-03-10T12:10:43.453" LastActivityDate="2023-03-10T12:10:43.453" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10557" PostTypeId="1" CreationDate="2023-03-10T16:08:31.950" Score="3" ViewCount="110" Body="&lt;p&gt;I want to dope CuI conventional unit cell using Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;p&gt;In previous papers they used different formulas of defect formation energies,and they use supercell. So I'm confused.&lt;/p&gt;&#xA;&lt;p&gt;What's the formula of the formation energy of a defect in my case?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2024-03-21T17:23:16.267" Title="How to calculate the formation energy of a defect using the unit cell?" Tags="|density-functional-theory|quantum-espresso|supercell|defects|formation-energy|" AnswerCount="0" CommentCount="5" ClosedDate="2024-03-21T17:23:38.920" ContentLicense="CC BY-SA 4.0" />
  <row Id="10558" PostTypeId="2" ParentId="10530" CreationDate="2023-03-11T01:24:58.203" Score="7" Body="&lt;p&gt;The fundamental problem is that the basis set used for the partial density-of-states (PDOS) does not span the plane-wave basis set space, so it is not usually possible to represent the Kohn-Sham states exactly in the atom-centred basis used for PDOS. There are two main issues:&lt;/p&gt;&#xA;&lt;h3&gt;1. Finite radial extent&lt;/h3&gt;&#xA;&lt;p&gt;The atom-centred functions usually decay quite rapidly as they move away from their centres. Exactly how rapidly they decay depends on what the functions are, and there are many different choices used (e.g. Gaussians, hydrogenic orbitals (exponential) or pseudoatomic orbitals); however, they all have a limited distance. A covalent bond could easily be long enough that neither of the bonded atoms' atom-centred states could represent it well, and the problem is even worse when electrons are delocalised (e.g. metals or aromatic rings).&lt;/p&gt;&#xA;&lt;h3&gt;2. Limited spherical harmonics&lt;/h3&gt;&#xA;&lt;p&gt;The atom-centred states are the product of a radial part and a spherical harmonic, the latter corresponding to particular orbital angular momentum quantum numbers (l, m). However, orbital angular momentum is not a good quantum number for a material or molecular system, and there is no guarantee that the actual Kohn-Sham (or whatever) states can be represented well by a sum of spherical harmonics over a small range of orbital angular momenta.&lt;/p&gt;&#xA;&lt;h3&gt;Example&lt;/h3&gt;&#xA;&lt;p&gt;As a simple example, consider using only a hydrogenic 1s and 2s orbitals for the PDOS of bulk lithium. At first glance, you might expect this to be reasonably good, since lithium atoms only have s-states occupied in the simple hydrogenic picture, but there are some problems which arise immediately.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, the hydrogenic states ignore electron-electron repulsion, and so their radial components tend to be more compact than in real atoms; this means that the simple hydrogenic states cannot represent density a long way from the lithium atoms, because the states don't actually extend far enough from the nuclei.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, the s-states are spherically symmetric, so we cannot represent any directional dependence in the electron density near the atom at all, the only way to get any directionality at all is to mix the s-states of two or more lithium atoms.&lt;/p&gt;&#xA;&lt;h3&gt;Quantifying the problems&lt;/h3&gt;&#xA;&lt;p&gt;Since we have the original Kohn-Sham states, we can quantify the error in our PDOS projection by calculating the difference in total electron density between the total projected states and the original states. This quantity is called the &amp;quot;spilling&amp;quot;, and is often expressed as a percentage of the total density.&lt;/p&gt;&#xA;&lt;p&gt;Beware that the spilling is effectively the mean error, whereas you may care more about the worst error. For example, if the spilling is 0.5% you might think that is no problem at all, but if you have 400 electrons in your simulation, 0.5% spilling means your PDOS is missing 2 electrons' worth of density; if this is a 0.5% error in all the states it is probably fine, but what if the error is almost entirely in just one or two states? You could find that it's exactly the state you're interested in which is represented most poorly!&lt;/p&gt;&#xA;&lt;p&gt;In principle, the spilling should reduce if you include more states in the atom-centred basis. However, in a simple Mulliken-style PDOS the assignment of charges to atom-centred orbitals can become ambiguous when the atomic states overlap, which means you have the paradoxical situation where you want the atom-centred states to cover the whole simulation volume, but not overlap; this is not possible with spherical atomic states!&lt;/p&gt;&#xA;&lt;p&gt;Since this is only a post-processing step, it is not usually worth worrying too much about it. You will usually want your total spilling to be small (perhaps less than 1%) and I recommend always plotting the total PDOS and comparing to the DOS from the Kohn-Sham states, so you can see whether there are particular regions of energy which are poorly represented (and whether you care about those regions or not). Provided the errors are small, the results will be fine for qualitative analysis, which is the aim of this approach in the first place.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-03-11T01:24:58.203" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10559" PostTypeId="1" AcceptedAnswerId="10579" CreationDate="2023-03-11T01:53:23.153" Score="5" ViewCount="154" Body="&lt;p&gt;At some temperature a crystal lattice of a solid can be rearranged or to say it more precise - got new positions of its cores. This phenomenon is well-known to be called a second-order phase transition (SOPT). More precise specification of crystal lattice rearranging for different solids can be learned and studied from books and experiments, for example, with X-ray diffractometer or other tools (if any).&lt;/p&gt;&#xA;&lt;p&gt;Can a SOPT temperature and new positions of cores of a crystal lattice of a solid be obtained with Hartee-Fock (or DFT) calculation? Maybe it is possible to do based on data obtained from a solution of the Hartree-Fock (Kohn-Sham) equation. Can the Broyden algorithm be applied to implement this calculation?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5403" LastEditDate="2023-03-12T12:49:43.417" LastActivityDate="2023-03-15T16:30:26.250" Title="Can specifications of a second-order phase transition of a solid be obtained with the Hartree-Fock (or DFT) calculation?" Tags="|density-functional-theory|solid-state-physics|hartree-fock|phase-transitions|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10560" PostTypeId="2" ParentId="10291" CreationDate="2023-03-11T05:30:51.533" Score="1" Body="&lt;p&gt;This &lt;a href=&quot;https://www.vasp.at/tutorials/latest/molecules/part1/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP tutorial&lt;/a&gt; contains what you're looking for. Let's look at their stdout.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; entering main loop&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1     0.384469864424E+02    0.38447E+02   -0.96726E+02    16   0.293E+02&#xA;DAV:   2     0.345967752349E+01   -0.34987E+02   -0.34942E+02    32   0.450E+01&#xA;DAV:   3    -0.244421465184E+00   -0.37041E+01   -0.34307E+01    16   0.308E+01&#xA;DAV:   4    -0.312489880281E+00   -0.68068E-01   -0.66911E-01    16   0.508E+00&#xA;DAV:   5    -0.313453098582E+00   -0.96322E-03   -0.96305E-03    32   0.506E-01    0.307E-01&#xA;DAV:   6    -0.314470890869E+00   -0.10178E-02   -0.17849E-03    16   0.332E-01    0.155E-01&#xA;DAV:   7    -0.314569344422E+00   -0.98454E-04   -0.23774E-04    16   0.137E-01&#xA;   1 F= -.31456934E+00 E0= -.16030702E+00  d E =-.308525E+00&#xA; writing wavefunctions&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;They then explain below that segment that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The initial electronic charge density is read from the POTCAR file and&#xA;remains fixed for the first   4   steps. This is because the&#xA;Hamiltonian is iteratively diagonalized and, thus, the KS orbitals&#xA;used to update the charge density should only be trusted after a&#xA;warm-up period. Then, the charge density is updated before entering&#xA;the next iteration step, i.e., not in the final iteration step. See&#xA;rms(c) column.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To answer your question, optimizing the Kohn-Sham orbitals (even with a fixed electron density) is an iterative process, so that's what you're likely seeing during your &lt;code&gt;ICHARG=11&lt;/code&gt; calculations, specifically, the &lt;code&gt;rms&lt;/code&gt; column:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;rms&lt;/code&gt;  - weighted absolute value of the residual vector of the KS orbitals&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;rms(c)&lt;/code&gt;   - absolute value of the charge density residual vector&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-03-11T05:30:51.533" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10561" PostTypeId="1" AcceptedAnswerId="10565" CreationDate="2023-03-11T09:27:44.273" Score="5" ViewCount="723" Body="&lt;p&gt;I am processing some XYZ files using the &lt;code&gt;rdkit&lt;/code&gt; library in python. I came across some strange/unexpected behaviour.&lt;/p&gt;&#xA;&lt;p&gt;Consider a sample XYZ file of methanol with coordinates in Angstroms:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;6&#xA;Methanol&#xA;  H      1.2001      0.0363      0.8431&#xA;  H      0.9877      0.8943     -0.7114&#xA;  H      1.0155     -0.8918     -0.6742&#xA;  C      0.7031      0.0083     -0.1305&#xA;  O     -0.6582     -0.0067      0.1730&#xA;  H     -1.1326     -0.0311     -0.6482&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am using the following code to visualise this compound. I am running the below code on Google Colab.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!pip install rdkit&#xA;from rdkit.Chem.rdmolfiles import  MolFromXYZFile&#xA;&#xA;coord_filepath = '/content/drive/MyDrive/input_files/methanol.xyz'&#xA;mol = MolFromXYZFile(coord_filepath)&#xA;display(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output from the display looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/K2BBa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/K2BBa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am a bit puzzled about the extra Hydrogens in the image.&#xA;I tried to double check the atoms in the rdkit &lt;code&gt;mol&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for atom in mol.GetAtoms():&#xA;  print(atom.GetSymbol())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It displays as expected:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H&#xA;H&#xA;H&#xA;C&#xA;O&#xA;H&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With coordinates in nanometers, the behaviour persists, with a bit better spacing between the various atoms/molecules.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5W6Jm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5W6Jm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So is this behaviour a bug or am I missing something conceptually?&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-03-12T10:35:50.883" LastActivityDate="2023-03-12T15:03:29.893" Title="Unexpected atoms while working with XYZ files in rdkit" Tags="|python|rdkit|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10562" PostTypeId="2" ParentId="8828" CreationDate="2023-03-11T12:11:19.933" Score="8" Body="&lt;p&gt;Another package (&lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt;) can do the same thing, but a bit more verbose and dynamic. (disclaimer, I am the author).&lt;br /&gt;&#xA;One of sisl's main goal is to interact with large TB models, and thus the complexity of the TB models are a bit more verbose, but it allows greater flexibility when one can query stuff on the fly. It is also intrinsically 3D so one has to deal with the extra dimension not used. It may for instance also be used to read in the Hamiltonian from other DFT packages, such as Siesta and Wannier90.&lt;/p&gt;&#xA;&lt;p&gt;Here is the same TB models shown for the simple cubic, but also for &lt;code&gt;2x1&lt;/code&gt; and &lt;code&gt;2x2&lt;/code&gt; times the basic system, for checking band-folding as mentioned by @leopold.talirz&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import sisl&#xA;from matplotlib import pyplot as plt&#xA;&amp;quot;&amp;quot;&amp;quot;s and p orbitals on 2d square lattice.&#xA;&#xA; - nearest neighbor hopping only&#xA; - no hopping between orbitals of different type (e.g. s &amp;lt;&amp;gt; pz)&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;# lattice constant&#xA;alat = 1.0 # Ang&#xA;# Create a square lattice with lattice constant as defined above&#xA;# Each atom have s and p orbitals and their orbital ranges are alat + .01 Ang&#xA;# (just slightly above the lattice constant)&#xA;s = sisl.AtomicOrbital(&amp;quot;s&amp;quot;, R=alat + 0.01)&#xA;px = sisl.AtomicOrbital(&amp;quot;px&amp;quot;, R=alat + 0.01)&#xA;py = sisl.AtomicOrbital(&amp;quot;py&amp;quot;, R=alat + 0.01)&#xA;pz = sisl.AtomicOrbital(&amp;quot;pz&amp;quot;, R=alat + 0.01)&#xA;# Since each orbital has a specific orbital range, one can also&#xA;# use different ranges per orbital (if needed)&#xA;&#xA;# Create the atom, in sisl atoms needs to have a specie associated.&#xA;# They aren't internally used in the electronic structure calculation,&#xA;# so it doesn't matter which specie you choose here.&#xA;atom = sisl.Atom(&amp;quot;H&amp;quot;, [s, px, py, pz])&#xA;geometry = sisl.geom.sc(alat, atom)&#xA;# the sc is a simple cubic lattice, but we will truncate one dimension&#xA;# to make it 2D, the below code will remove periodicity along the 3rd&#xA;# lattice vector&#xA;geometry.set_nsc(c=1)&#xA;&#xA;# Now define how the tight-binding model is denoted&#xA;# Since there are 2 orbitals per atom, you need to do define a&#xA;# simple method that will create the hoppings&#xA;def construct(H, ia, atoms, atoms_xyz=None):&#xA;    # ia: is the atom that we are currently assigning hopping elements to&#xA;    # atoms: is a subset of all atoms that is ensured to be reachable by ia&#xA;    #        in this small example it isn't needed, but when very large&#xA;    #        TB models are made, it can greatly speed up the construction&#xA;    #        since it reduces the search space.&#xA;&#xA;    # convert to the first orbital on the atom&#xA;    io = H.geometry.a2o(ia)&#xA;    # this will give a list of:&#xA;    #   jas_onsite: R &amp;lt;= 0.1&#xA;    #   jas_nn: 0.1 &amp;lt; R &amp;lt;= s.R&#xA;    jas_onsite, jas_nn = H.geometry.close(ia, R=[0.1, s.R], atoms=atoms, atoms_xyz=atoms_xyz)&#xA;&#xA;    # we know that there are two orbitals per atom,&#xA;    # the 1st is s (as defined in the sisl.Atom(...)&#xA;    # the 2nd is pz&#xA;    jos_onsite = H.geometry.a2o(jas_onsite)&#xA;    H[io, jos_onsite] = 0 # s&#xA;    for i in (1, 2, 3):&#xA;        H[io+i, jos_onsite+i] = 3 # p&#xA;&#xA;    jos_nn = H.geometry.a2o(jas_nn)&#xA;    H[io, jos_nn] = -0.5 # s&#xA;    H[io+3, jos_nn+3] = -0.25 # pz&#xA;&#xA;    # Now the anisotropic hoppings for px, py&#xA;    # first we need to get the supercell hoppings&#xA;    jas_nn_isc = H.geometry.a2isc(jas_nn)&#xA;    for jo, isc in zip(jos_nn, jas_nn_isc):&#xA;        if isc[0] != 0:&#xA;            # this *must* be hopping along x&#xA;            H[io+1, jo+1] = +0.25 # px&#xA;            H[io+2, jo+2] = -0.25 # py&#xA;        elif isc[1] != 0:&#xA;            # this *must* be hopping along y&#xA;            H[io+1, jo+1] = -0.25 # px&#xA;            H[io+2, jo+2] = +0.25 # py&#xA;&#xA;# Define the Hamiltonian&#xA;H = sisl.Hamiltonian(geometry)&#xA;# Now construct the TB model&#xA;H.construct(construct)&#xA;&#xA;&#xA;def plot_bs(H):&#xA;    bs = sisl.physics.BandStructure(H,&#xA;                                    [[0, 0, 0], [0.5, 0, 0],&#xA;                                     [0.5, 0.5, 0], [0, 0, 0]],&#xA;                                    100, names=[&amp;quot;Gamma&amp;quot;, &amp;quot;X&amp;quot;, &amp;quot;M&amp;quot;, &amp;quot;Gamma&amp;quot;])&#xA;&#xA;    # Calculate the eigenvalues&#xA;    evals = bs.apply.ndarray.eigh()&#xA;&#xA;    # plot band structure&#xA;    fig, ax = plt.subplots()&#xA;    # retrieve the linear spacings of the k-points&#xA;    lk, kt, kl = bs.lineark(True)&#xA;&#xA;    ax.set_xticks(kt)&#xA;    for band in evals.T:&#xA;        ax.plot(lk, band)&#xA;    ax.set_title(&amp;quot;s and p orbitals on 2d square lattice&amp;quot;)&#xA;    ax.set_xlabel(&amp;quot;Path in k-space&amp;quot;)&#xA;    ax.set_ylabel(&amp;quot;Band energy&amp;quot;)&#xA;    ax.set_xticks(kt)&#xA;    ax.set_xticklabels(kl)&#xA;    fig.tight_layout()&#xA;&#xA;plot_bs(H)&#xA;# the same bandstructure, twice the size along x&#xA;plot_bs(H.tile(2, axis=0))&#xA;# the same bandstructure, twice the size along x and y&#xA;plot_bs(H.tile(2, axis=0).tile(2, axis=1))&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The same plot:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/64thp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/64thp.png&quot; alt=&quot;the 1 atom system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The 2x1 system:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/PMSAR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PMSAR.png&quot; alt=&quot;the 2 atom system (doubled along x)&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The 2x2 system:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/t2dUd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/t2dUd.png&quot; alt=&quot;the 4 atom system&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;See here for additional details: &lt;a href=&quot;https://zerothi.github.io/sisl/tutorials/tutorial_es_1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://zerothi.github.io/sisl/tutorials/tutorial_es_1.html&lt;/a&gt;&#xA;There one can also see how one can expand the eigenstates into real-space quantities.&lt;/p&gt;&#xA;&lt;p&gt;Please remark that this TB model is not efficiently solved in one Hamiltonian. Since all orbitals are disjointed from the each other, there is no need to have 1 Hamiltonian, instead for better efficiency one could do 4 Hamiltonians.&#xA;In &lt;code&gt;sisl&lt;/code&gt; extracting sub orbitals is a breeze:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;H_s = H.sub_orbital(atom, s)&#xA;# or via index&#xA;H_py = H.sub_orbital(atom, 2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;if you diagonalize and plot all 4 individually you'll see exactly the same band-structure.&lt;/p&gt;&#xA;&lt;p&gt;Note that &lt;a href=&quot;https://dipc-cc.github.io/hubbard/docs/latest/examples/periodic.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hubbard&lt;/a&gt; is based on &lt;code&gt;sisl&lt;/code&gt; and allows the Hubbard model quite easily.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-03-13T07:22:28.257" LastActivityDate="2023-03-13T07:22:28.257" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10563" PostTypeId="1" AcceptedAnswerId="10726" CreationDate="2023-03-11T23:49:32.820" Score="6" ViewCount="131" Body="&lt;p&gt;There was a two-week summer school on Density Functional Theory using Quantum ESPRESSO in the summer of 2014 organized by The Abdus Salam International Centre for Theoretical Physics (ICTP), jointly with the Indian Institute of Science Education and Research (IISER), Pune. It's called MASTANI - &lt;em&gt;MA&lt;/em&gt;terial &lt;em&gt;S&lt;/em&gt;imulations &lt;em&gt;T&lt;/em&gt;heory &lt;em&gt;A&lt;/em&gt;nd &lt;em&gt;N&lt;/em&gt;umer&lt;em&gt;I&lt;/em&gt;cs. I cannot find the presentation slides and tutorial files of this workshop.&lt;/p&gt;&#xA;&lt;p&gt;The program's website: &lt;a href=&quot;https://indico.ictp.it/event/a13246/&quot; rel=&quot;noreferrer&quot;&gt;https://indico.ictp.it/event/a13246/&lt;/a&gt; (working but does not have anything)&lt;/p&gt;&#xA;&lt;p&gt;Tutorial files and slides: &lt;a href=&quot;http://sites.iiserpune.ac.in/%7Esmr2626/talks-presentations.html&quot; rel=&quot;noreferrer&quot;&gt;http://sites.iiserpune.ac.in/~smr2626/talks-presentations.html&lt;/a&gt; (the link is broken)&lt;/p&gt;&#xA;&lt;p&gt;The Wayback machines has archived the sites but not every slides and files. Here is the archived link: &lt;a href=&quot;https://web.archive.org/web/20160414111506/http://www.iiserpune.ac.in/%7Esmr2626/talks-presentations.html&quot; rel=&quot;noreferrer&quot;&gt;https://web.archive.org/web/20160414111506/http://www.iiserpune.ac.in/~smr2626/talks-presentations.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If someone has access to all these files, could you share them somehow? Or can anyone reach to the organizers to let them know that the site is not working? From the content of their workshop, it seems promising.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-04-14T14:00:01.657" Title="Where can I find the MASTANI-2014 tutorial files?" Tags="|reference-request|education|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10564" PostTypeId="1" CreationDate="2023-03-12T13:37:22.360" Score="6" ViewCount="240" Body="&lt;p&gt;Let us say that I wish to create a function that may do the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; find_bond_energy(atom1=&amp;quot;C&amp;quot;, atom2=&amp;quot;O&amp;quot;, order=3)&#xA;1072 kJ/mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above example entails a triple covalent bond between carbon (C) and oxygen (O), with the hypothetical function returning the known dissociation energy. The same could then be applied to a wide range of covalent bonds.&lt;/p&gt;&#xA;&lt;p&gt;I have attempted to explore packages such as mendeleev, RDKit and others, with no luck. There is plenty of data available for arbitrary individual elements, but it seems to not be the case for arbitrary chemical bonds. Databases such as PubChem (along with its API) are useful for exploring properties of molecules, but again, I cannot find any useful equivalent for chemical bonds.&lt;/p&gt;&#xA;&lt;p&gt;There exist some educational websites which list limited tables of bond dissociation energies, however these are not exhaustive and also would require a less Pythonic web-scraping solution.&lt;/p&gt;&#xA;&lt;p&gt;Can any existing packages, APIs or databases (ideally tailored to Python scripting) help?&lt;/p&gt;&#xA;" OwnerUserId="6858" LastEditorUserId="5" LastEditDate="2023-03-12T15:43:27.870" LastActivityDate="2023-03-12T15:43:27.870" Title="Which Python packages, APIs or online databases may be used for a Python script to find bond dissociation energy between two arbitrary atoms?" Tags="|computational-chemistry|python|software-recommendations|one-topic-per-answer|databases|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10565" PostTypeId="2" ParentId="10561" CreationDate="2023-03-12T15:03:29.893" Score="5" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/rdkit/UGM_2022/blob/main/Notebooks/Landrum_WhatsNew.ipynb&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; is a demo how to work with &lt;code&gt;MolFromXYZ&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can choose &lt;code&gt;rdDetermineBonds.DetermineConnectivity&lt;/code&gt; for bonds or &lt;code&gt;rdDetermineBonds.DetermineBonds&lt;/code&gt;for bonds and bond orders.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import rdDetermineBonds&#xA;&#xA;xyz = '''6&#xA;Methanol&#xA;  H      1.2001      0.0363      0.8431&#xA;  H      0.9877      0.8943     -0.7114&#xA;  H      1.0155     -0.8918     -0.6742&#xA;  C      0.7031      0.0083     -0.1305&#xA;  O     -0.6582     -0.0067      0.1730&#xA;  H     -1.1326     -0.0311     -0.6482'''&#xA;&#xA;mol = Chem.MolFromXYZBlock(xyz)&#xA;&#xA;conn_mol = Chem.Mol(mol)&#xA;rdDetermineBonds.DetermineConnectivity(conn_mol)&#xA;conn_mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5eZdz.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5eZdz.png&quot; alt=&quot;mol&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2023-03-12T15:03:29.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10566" PostTypeId="2" ParentId="10564" CreationDate="2023-03-12T15:36:29.750" Score="4" Body="&lt;h1&gt;PySCF&lt;/h1&gt;&#xA;&lt;p&gt;Bond dissociation energies are either found by laboratory experiments followed by spectroscopic analysis, or by &lt;em&gt;ab initio&lt;/em&gt; calculations. &lt;a href=&quot;https://en.wikipedia.org/wiki/Secondary_research&quot; rel=&quot;nofollow noreferrer&quot;&gt;Secondary research&lt;/a&gt; could be done to find bond dissociation energies that have already been determined via one of the above two primary research methods, and databases that come to mind for that are NIST's &lt;a href=&quot;https://cccbdb.nist.gov/Calcdata.asp&quot; rel=&quot;nofollow noreferrer&quot;&gt;CCCBDB&lt;/a&gt; database (not well-maintained anymore), and my own &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES&quot; rel=&quot;nofollow noreferrer&quot;&gt;AI ENERGIES&lt;/a&gt; database (open source on GitHub and currently maintained regularly, but doesn't yet work well with Python). Since I don't know of any databases of bond dissociation energies that are tailored to Python scripting, and you're not looking for a wet-lab solution, &lt;em&gt;ab initio&lt;/em&gt; calculations seem ideal for you if you don't want to write a web-scraper do collect data from CCCBDB or AI ENERGIES; and PySCF is currently the most popular Python package for &lt;em&gt;ab initio&lt;/em&gt; calculations of molecular electronic energies.&lt;/p&gt;&#xA;&lt;p&gt;By doing a &lt;a href=&quot;https://pyscf.org/user/geomopt.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;geometry optimization&lt;/a&gt; in PySCF with &lt;code&gt;basis='cc-pVTZ'&lt;/code&gt; and the &lt;a href=&quot;https://pyscf.org/user/mcscf.html#casscf&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASSCF method&lt;/a&gt; with a &amp;quot;full valence active space&amp;quot;, you will be able to get a decent bond length without waiting for too long, for most diatomic molecules that involve elements up to the Kr atom. For molecules including heavier elements you would probably want to start doing relativistic calculations, which you could have been doing all along for the molecules containing lighter elements too, but for such calculations you would ideally use effective core potentials or uncontracted basis sets or basis sets contracted for relativistic Hamiltonians like the X2C one, which are all a bit further away from the &amp;quot;default&amp;quot; strategy explained in the first sentence of this paragraph and the linked webpage.&lt;/p&gt;&#xA;&lt;p&gt;This strategy can be turned into a function like what you proposed (but I've removed the &lt;code&gt;order=3&lt;/code&gt; part, because it's not necessary if you're just looking for dissociation energies of molecules in their ground electronic states):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;find_bond_energy(atom1=&amp;quot;C&amp;quot;, atom2=&amp;quot;O&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-03-12T15:36:29.750" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10568" PostTypeId="1" CreationDate="2023-03-12T21:37:57.777" Score="4" ViewCount="40" Body="&lt;p&gt;I have a new structure that I want to analyze (lets just call it a shape). For the shape, I have the coordinates that make it up. I even have a tcl script in VMD that allows me to create the shape using graphics (draw triangle and draw lines). However, I want to simulate the shape in response to force. I know the best way to do this is to use LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do I do this?&lt;/strong&gt; All the tutorials I find online use molecules, which makes sense since it is molecular dynamics, but I want to specifically analyze a shape.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a way I an input constraints from VMD into LAMMPS and test that, or something like that?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you for the help, I am new to this so any guidance would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="6861" LastEditorUserId="5" LastEditDate="2023-03-12T21:42:28.887" LastActivityDate="2023-03-12T21:42:28.887" Title="Using LAMMPS and VMD to analyze a new structure" Tags="|lammps|vmd|molecular-mechanics|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T07:29:23.067" ContentLicense="CC BY-SA 4.0" />
  <row Id="10569" PostTypeId="2" ParentId="9180" CreationDate="2023-03-13T00:24:40.447" Score="9" Body="&lt;p&gt;The main question here is whether the reaction is favourable or not, and for that we may need to go beyond the usual energies computed in a ground state DFT calculation, and consider the free energy. DFT's &amp;quot;total energy&amp;quot; is the same as the &amp;quot;internal energy&amp;quot;, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, in thermodynamics, and you can compute this for each reactant and product, as you note. However, in order to know whether a reaction is favourable under different experimental conditions, we might also need the &lt;span class=&quot;math-container&quot;&gt;$PV$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$TS$&lt;/span&gt; terms in order to calculate the appropriate free energy, where &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the pressure, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the volume, &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the temperature and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the entropy.&lt;/p&gt;&#xA;&lt;h3&gt;Pressure (stress)&lt;/h3&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$PV$&lt;/span&gt; term is straightforward, since the stress tensor is computable using perturbation theory, directly from the DFT solution - the relevant perturbation being an infinitesimal strain of the cell. Calculating the stress tensor does usually require an additional term (called the Pulay stress) due to how the basis set changes when the cell is strained, but this is well-known for plane-wave basis sets and ultrasoft/PAW formalisms such as those used by ABINIT, CASTEP, Quantum Espresso and VASP. The PV term is sufficient to calculate the enthalpy, &lt;span class=&quot;math-container&quot;&gt;$H = E + PV$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Note that if we have a particular environmental pressure, &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, then we should optimise the geometry of our system under this applied pressure (positive or negative), for which we will have to do a full variable-cell optimisation; i.e. the optimisation should be performed by varying the cell vectors, in addition to the atomic coordinates. In the past, not all DFT software was capable of variable-cell optimisation, so people sometimes used an energy-volume (E-V) plot and fit a Birch-Murnaghan equation of state; this is &lt;em&gt;not&lt;/em&gt; recommended, as it is extremely prone to error, and is not as accurate as a proper optimisation approach.&lt;/p&gt;&#xA;&lt;h3&gt;Entropy&lt;/h3&gt;&#xA;&lt;p&gt;The Helmholtz free energy, &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;, is defined as &lt;span class=&quot;math-container&quot;&gt;$F = E - TS$&lt;/span&gt;, so requires a calculation of &lt;span class=&quot;math-container&quot;&gt;$TS$&lt;/span&gt;; this is usually very difficult! &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; contains contributions from the vibrations of the system around its equilibrium (&amp;quot;vibrational entropy&amp;quot;) as well as contributions from all of the different ways the atoms could be arranged (&amp;quot;configurational entropy&amp;quot;). Vibrational entropy can be calculated in the quasi-harmonic approximation by computing the &lt;span class=&quot;math-container&quot;&gt;$\sim~3N$&lt;/span&gt; vibrational normal modes of your &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-atom system and thermally populating them; these modes are the &amp;quot;phonons&amp;quot; in a periodic material system, but in molecules you may need to consider other modes such as rotational modes. The configurational entropy is extremely difficult to compute, to the point where it is impractical in most cases. This is one of the reasons why &lt;span class=&quot;math-container&quot;&gt;$T = 0$&lt;/span&gt;K is so much easier to work with, because the entropic contribution is zero.&lt;/p&gt;&#xA;&lt;p&gt;If we have both &lt;span class=&quot;math-container&quot;&gt;$PV$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$TS$&lt;/span&gt; terms then we can calculate the Gibbs free energy, &lt;span class=&quot;math-container&quot;&gt;$G = E + PV - TS$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Conclusions&lt;/h3&gt;&#xA;&lt;p&gt;At low temperatures, using the DFT energy (&lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;) or enthalpy (&lt;span class=&quot;math-container&quot;&gt;$H = E + PV$&lt;/span&gt;), as appropriate, can often give a good indication of how favourable a reaction will be, and what energy will be released (or required). At higher temperatures, the entropic contribution (via &lt;span class=&quot;math-container&quot;&gt;$TS$&lt;/span&gt;) becomes significant, and this is very difficult to model accurately. It is possible to calculate the vibrational contributions to the entropy in the quasiharmonic approximation, via a phonon calculation, which is relatively accurate for modest temperatures, but it is not usually practical to calculate the configurational entropy.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="85" LastEditDate="2023-03-16T16:01:06.303" LastActivityDate="2023-03-16T16:01:06.303" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10570" PostTypeId="2" ParentId="10547" CreationDate="2023-03-13T17:15:26.027" Score="2" Body="&lt;p&gt;So I have found out that by default the NBO version implemented in GAUSSIAN 16 searches for 1c and 2c bonds but not for 3c bonds. One has to activate it by adding an NBO input at the end of the GAUSSIAN input file. An example looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%Chk=chk_file.chk&#xA;# B3LYP/def2tzvp pop=nboread&#xA;&#xA;nbo 3c bond analysis&#xA;&#xA;0 1&#xA;A x1 y1 z1&#xA;B x2 y2 z2&#xA;C x3 y3 z3&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$nbo&#xA;3CBOND&#xA;$&lt;/span&gt;end&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Using this input causes the program to also search for three-center bonds.&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2023-03-13T17:15:26.027" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10571" PostTypeId="1" CreationDate="2023-03-14T03:36:28.907" Score="4" ViewCount="224" Body="&lt;p&gt;I have build a carbon quantum dots model based on &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S002554082030413X?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. The model looks like this.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KTGX5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KTGX5.png&quot; alt=&quot;Carbon Quantum Dots&quot; /&gt;&lt;/a&gt;&#xA;I have calculated the density of states of the system, but does not get a desired plot as written on the paper, where I have used all the calculation parameters, and used the Martyna-Tuckerman isolation approximation. Do we have to place the carbon dots centered on the slab or not?&lt;/p&gt;&#xA;&lt;p&gt;here I attach the input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;    prefix='CD',&#xA;    calculation='nscf'&#xA;&#xA;    ! this is a comment: you can comment out variables&#xA;&#xA;    ! if &amp;quot;pseudo_dir&amp;quot; and &amp;quot;outdir&amp;quot; are not set then pw.x will use the&#xA;    ! values of ESPRESSO_PSEUDO and ESPRESSO_TMPDIR environmental&#xA;    ! variables instead&#xA;&#xA;    pseudo_dir = './' &#xA;    outdir     = './'&#xA;    forc_conv_thr = 1.D-3&#xA; /&#xA;&#xA; &amp;amp;SYSTEM&#xA;    assume_isolated      =  'martyna-tuckerman',&#xA;    &#xA;    ibrav = 0&#xA;&#xA;    ecutwfc =  40.0,&#xA;    ! ecutrho =  200.0,&#xA;&#xA;    nat =  36,&#xA;    ntyp =  2,&#xA;    occupations = 'tetrahedra'&#xA;   ! nbnd = 16&#xA; /&#xA;&#xA; &amp;amp;ELECTRONS&#xA; /&#xA; &amp;amp;IONS&#xA; /&#xA;&#xA;ATOMIC_SPECIES &#xA;   C   12.011   C.pbe-n-kjpaw_psl.1.0.0.UPF &#xA;   H    1.008   H.pbe-kjpaw_psl.1.0.0.UPF&#xA;&#xA;CELL_PARAMETERS angstrom&#xA;30.000  0.000   0.000&#xA; 0.000 30.000   0.000&#xA; 0.000  0.000  20.000&#xA;&#xA;ATOMIC_POSITIONS angstrom&#xA;C             8.5462621381        4.9352704182        2.1665564044&#xA;C             6.4373654591        6.1820127934        2.1703856013&#xA;C            12.8220212514        2.4973076753        2.1710347238&#xA;C            10.6869630940        3.7016165802        2.1666033071&#xA;C            10.6869977938        6.1690052966        2.1666679282&#xA;C             8.5473450969        7.4020250382        2.1689283141&#xA;H             6.5837867671        8.3207094980        2.1751996955&#xA;H            14.6031401577        3.6910972572        2.1750078567&#xA;C            12.8265277052        4.9352319145        2.1683557667&#xA;C            12.8218797269        7.3735673434        2.1710486116&#xA;C            10.6585604846        8.6197131665        2.1712617450&#xA;H             8.7348277727        0.3069708431        2.1753938040&#xA;H             8.7346720352        9.5642436965        2.1754142098&#xA;H             6.5837231039        1.5502809217        2.1751931456&#xA;H            14.6028741922        6.1797799841        2.1749918454&#xA;C            10.6585195064        1.2515604438        2.1712396897&#xA;C             8.5471647526        2.4689718575        2.1688499751&#xA;C             6.4370401843        3.6887382822        2.1703651805&#xA;C             9.2602441002        6.1688733768        2.1668738975&#xA;C             7.1255349047        7.3723867294        2.1710855921&#xA;C            13.5108411137        3.6879265513        2.1708509067&#xA;C            11.4011655841        4.9352403580        2.1665635098&#xA;C            11.3980457359        7.4030366334        2.1688980356&#xA;C             9.2832769042        8.6198688495        2.1714504976&#xA;C            13.5105659673        6.1826926707        2.1708532156&#xA;H            13.3648925590        8.3212521816        2.1750960061&#xA;H            11.2078389607        0.3073902866        2.1750886619&#xA;H            11.2080342434        9.5637915261        2.1750893667&#xA;C             9.2832602314        1.2514362035        2.1714129641&#xA;C             7.1253496881        2.4985921119        2.1710436800&#xA;H             5.3450905652        3.6925837470        2.1747413063&#xA;H            13.3649457028        1.5496390540        2.1750964762&#xA;C            11.3981895508        2.4678995614        2.1688455526&#xA;C             9.2602511487        3.7017697140        2.1668157323&#xA;C             7.1221650973        4.9352790632        2.1682921936&#xA;H             5.3454007203        6.1783603711        2.1747286010&#xA;&#xA;K_POINTS automatic ! gamma&#xA;10 10 1  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4827" LastEditorUserId="4827" LastEditDate="2023-03-14T05:42:04.330" LastActivityDate="2023-03-14T05:42:04.330" Title="Calculation of Carbon Quantum Dots using Quantum ESPRESSO" Tags="|quantum-espresso|quantum-dots|" AnswerCount="0" CommentCount="8" ClosedDate="2023-10-20T23:39:16.617" ContentLicense="CC BY-SA 4.0" />
  <row Id="10572" PostTypeId="2" ParentId="4757" CreationDate="2023-03-14T08:27:23.053" Score="6" Body="&lt;h1&gt;RDKIT&lt;/h1&gt;&#xA;&lt;p&gt;Getting the distance between atoms, angle and dihedral between atoms can be achieved with a python library called &lt;a href=&quot;https://www.rdkit.org/docs/&quot; rel=&quot;noreferrer&quot;&gt;rdkit&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the sake of brevity, I will demonstrate using a simple compound: &lt;strong&gt;Ethanamine&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Below I illustrate a minimal reproducible example&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import MolFromXYZBlock&#xA;from rdkit.Chem import rdDetermineBonds&#xA;from rdkit.Chem.rdMolTransforms import GetDihedralDeg, GetBondLength, GetAngleDeg&#xA;&#xA;xyz_block = &amp;quot;&amp;quot;&amp;quot;10&#xA;Ethanamine&#xA;  C      1.2277      0.4098     -0.0270&#xA;  C      0.0679     -0.5616      0.0680&#xA;  N     -1.2273      0.1369     -0.0900&#xA;  H      1.2237      0.9656     -0.9741&#xA;  H      1.2144      1.1497      0.7853&#xA;  H      0.1336     -1.1313      1.0206&#xA;  H      0.1307     -1.3142     -0.7430&#xA;  H     -1.2998      0.8711      0.5835&#xA;  H     -1.9719     -0.5117      0.0544&#xA;  H      2.1852     -0.1236      0.0348   &#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;mol = MolFromXYZBlock(xyz_block)&#xA;rdDetermineBonds.DetermineConnectivity(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;# To get an idea of the atom ids, symbols and the bond type&#xA;for bond in mol.GetBonds():&#xA;  print(bond.GetBeginAtom().GetSymbol(),  bond.GetEndAtom().GetSymbol(), bond.GetBeginAtomIdx(), bond.GetEndAtomIdx(), bond.GetBondTypeAsDouble()) &#xA;&#xA;conf = mol.GetConformers()[0]&#xA;&#xA;# Here I choose four of the atoms at random, for extracting various required informations&#xA;atom_1_id = 0&#xA;atom_2_id = 1&#xA;atom_3_id = 3&#xA;atom_4_id = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;GetDihedralDeg(conf, atom_1_id, atom_2_id, atom_3_id, atom_4_id) &#xA;# &amp;gt;&amp;gt; -32.793435222825245&#xA;&#xA;GetBondLength(conf, atom_1_id, atom_2_id)&#xA;# &amp;gt;&amp;gt; 1.5158426699364285&#xA;&#xA;GetAngleDeg(conf, atom_1_id, atom_2_id, atom_3_id)&#xA;# &amp;gt;&amp;gt; 27.824571764428438&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Documentation for the three functions used above can be found &lt;a href=&quot;https://www.rdkit.org/docs/source/rdkit.Chem.rdMolTransforms.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-03-14T08:27:23.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10573" PostTypeId="2" ParentId="6991" CreationDate="2023-03-14T15:52:24.933" Score="3" Body="&lt;p&gt;If you know the parameters for your new atom_type you can edit the&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;src/lib/atom_constants.h&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;file in the source code of vina to add those parameters (name, radius, depth, solvation parameter, volume, covalent radius) and then recompile the package.&lt;/p&gt;&#xA;&lt;p&gt;If you don't know these parameters for your new atom_type then you follow the method described in the above answer to determine them.&lt;/p&gt;&#xA;" OwnerUserId="6872" LastActivityDate="2023-03-14T15:52:24.933" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10574" PostTypeId="1" CreationDate="2023-03-15T08:42:18.617" Score="3" ViewCount="208" Body="&lt;p&gt;I want to calculate the optical, transport and electronic properties of my material. GGA underestimate the bandgap.&lt;/p&gt;&#xA;&lt;p&gt;I tried GGA+U but the bandgap is still underestimated and also when I tried to use it to calculate the restivity for example using EPW they say that DFT+U is not yet implemented.&lt;/p&gt;&#xA;&lt;p&gt;So I was wondering how can I apply the scissor operator to GGA? Is it a good method?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-10-12T16:45:25.957" Title="How to add the scissor operator in Quantum ESPRESSO input?" Tags="|density-functional-theory|quantum-espresso|band-structure|electronic-structure|electronic-transport|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10575" PostTypeId="1" AcceptedAnswerId="10577" CreationDate="2023-03-15T08:45:52.510" Score="5" ViewCount="914" Body="&lt;p&gt;I am trying to model isolated structures such as quantum dots or molecules in Quantum ESPRESSO (QE).&lt;/p&gt;&#xA;&lt;p&gt;QE uses 3D periodic boundary conditions (PBC) by default. That's why in order to reduce any interaction between the molecule and its images/replicas, we use very large supercells. Now, according to the QE pw.x &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm547&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;, we can use the &lt;code&gt;assume_isolated&lt;/code&gt; flag in the &lt;code&gt;SYSTEM&lt;/code&gt; namelist when we want &lt;em&gt;to perform calculation assuming the system to be isolated (a molecule or a cluster in a 3D supercell)&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now, the default setting is &lt;code&gt;assume_isolated='none'&lt;/code&gt; i.e. regular periodic calculation without any correction. But if we set &lt;code&gt;assume_isolated='martyna-tuckerman'&lt;/code&gt; or &lt;code&gt;assume_isolated='makov-payne',&lt;/code&gt; then do we also need to set the supercell large enough?&lt;/p&gt;&#xA;&lt;p&gt;According to &lt;a href=&quot;http://wiki.max-centre.eu/index.php/Electronic_properties_of_isolated_molecules&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; suggestion from &lt;em&gt;Max-centre&lt;/em&gt; for Electronic properties of isolated molecules calculation, one should set the &lt;code&gt;assume_isolated='martyna-tuckerman'&lt;/code&gt; and also set the supercell large. My question is why do we need to set the supercell large if we specify the molecule to be isolated? Isolated structure doesn't have any replicas.&lt;/p&gt;&#xA;&lt;p&gt;Does this mean when &lt;code&gt;assume_isolated&lt;/code&gt; is not set as &lt;code&gt;'none'&lt;/code&gt;, then we still have the 3D PBC applied? I am asking this because if setting &lt;code&gt;assume_isolated='mt'&lt;/code&gt; can specify the molecule as isolated, then we don't need to specify the supercell very large and the calculation should be much faster for a small supercell.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-03-15T08:55:23.557" LastActivityDate="2023-03-15T11:48:41.700" Title="How to model an isolated molecule with Quantum ESPRESSO?" Tags="|quantum-espresso|periodic-boundary-conditions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10576" PostTypeId="2" ParentId="10426" CreationDate="2023-03-15T09:19:08.700" Score="1" Body="&lt;p&gt;I solved the problem using the QM/QM2 method provided inside ORCA. To obtain the energy of the two fragments I set both DFT levels to B3LYP and then used the QMAtoms to divide the &amp;quot;fragments&amp;quot;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! QM/QM2 def2-svp b3lyp cpcm(water)&#xA;&#xA;%qmmm&#xA;    QM2CustomMethod &amp;quot;B3LYP&amp;quot;&#xA;    QM2CustomBasis &amp;quot;def2-svp&amp;quot;&#xA;    QMAtoms {0:1} end&#xA;end&#xA;&#xA;*xyz 0 1 &#xA;O 0 0 0&#xA;H 0 1 0&#xA;H 0 1 1&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With this calculation, I was able to obtain the two energy needed: whole system energy &amp;quot;low&amp;quot; level, and &amp;quot;high&amp;quot; level fragment energy. The difference between the two energies is the &amp;quot;low&amp;quot; level fragment's energy.&lt;/p&gt;&#xA;" OwnerUserId="4895" LastActivityDate="2023-03-15T09:19:08.700" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10577" PostTypeId="2" ParentId="10575" CreationDate="2023-03-15T11:48:41.700" Score="7" Body="&lt;p&gt;Quantum Espresso, like all plane-wave DFT software (e.g. ABINIT, CASTEP, VASP), has to have periodic boundary conditions, because the plane-waves themselves are periodic.&lt;/p&gt;&#xA;&lt;p&gt;When you want to study clusters (or any lower-dimensional system) the 3D periodicity is unwanted, but if you have sufficient vacuum surrounding your cluster then you would expect the results to be accurate, because the inter-cluster interaction would decay with distance. Unfortunately, this is not true for interaction forces which decay as &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{r^2}$&lt;/span&gt;, such as the electrostatic interaction, because although the individual cluster-cluster interactions decay as &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{r^2}$&lt;/span&gt;, there are &lt;span class=&quot;math-container&quot;&gt;$O(r^2)$&lt;/span&gt; clusters at this distance, because they are repeated periodically in 3D space. In fact the energy &lt;em&gt;per cluster&lt;/em&gt; does converge for neutral clusters, although it is only conditionally convergent, and it is usually calculated efficiently with an Ewald summation. (For charged systems the energy diverges, which is why plane-wave DFT codes always add a homogeneous neutralising background charge for such systems.)&lt;/p&gt;&#xA;&lt;p&gt;When the 3D periodicity is not desirable, the electrostatic terms are no longer what you want to compute. A different way is needed to calculate these long-range interactions, which does not assume 3D periodicity, and this is where methods such as Martyna-Tuckerman[1] are useful. These methods essentially compute a correction to the usual plane-wave DFT total energy, which removes the spurious effect of the enforced 3D periodicity from the long-range electrostatic interaction.&lt;/p&gt;&#xA;&lt;p&gt;This does not remove the periodicity of the density, potential etc. itself, and so it is still necessary to have a large enough vacuum gap that these quantities do not interact with their periodic images in neighbouring cells.&lt;/p&gt;&#xA;&lt;p&gt;[1] G.J. Martyna and M.E. Tuckerman, &amp;quot;A reciprocal space based method for treating long range interactions in ab initio and forcefield-based calculations in clusters&amp;quot;, &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;110&lt;/strong&gt;, 2810 (1999); &lt;a href=&quot;https://doi.org/10.1063/1.477923&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1063/1.477923&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-03-15T11:48:41.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10579" PostTypeId="2" ParentId="10559" CreationDate="2023-03-15T16:30:26.250" Score="3" Body="&lt;p&gt;In classic DFT approach you run geometry optimization for both phases which gives you electronic energies, then compute frequencies which gives you thermodynamic parameters, including tempurature-dependent free energy. Finally, you use the obtained G(T) to find a SOPT temperature G1(T) = G2(T).&lt;/p&gt;&#xA;&lt;p&gt;This functionality is available in any solid-state DFT software (VASP, CP2K, QEspresso, etc.), just search smth like &amp;quot;how to compute phase diagram in %YOUR_PACKAGE_NAME%&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;However, the plain DFT is not the best way to get the transition pathway. You can do it by localising a transition state (keywords are TS (transition state) and NEB (nudged elastic band)), but it will consider SOPT as a simultaneous process, and to the best of my knowledge it's not how it works.&lt;/p&gt;&#xA;&lt;p&gt;For the purpose you need run ab initio molecular dynamics, starting from the low-temperature structure and slowly increasing the simulation temperature. Though it's really time-demanding computations. The other way is to parameterized the MM force field specifically for your system, but this step can be challenging enough to drop the problem completely.&lt;/p&gt;&#xA;" OwnerUserId="6875" LastActivityDate="2023-03-15T16:30:26.250" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10580" PostTypeId="1" CreationDate="2023-03-15T19:04:32.110" Score="7" ViewCount="355" Body="&lt;p&gt;I'm delving into the world of superacids, acids with an acid strength greater than that of sulfuric acid at 100%. I've recently encountered some computational papers which suggest that the deprotonation energy of an acid is a useful measure of its strength.&lt;/p&gt;&#xA;&lt;p&gt;Assuming the following equilibrium&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\ce{HA -&amp;gt; H+ + A-}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;one can calculate the deprotonation energy (DPE) by &lt;span class=&quot;math-container&quot;&gt;$\ce{DPE = E_{H+} + E_{A-} - E_{HA}}$&lt;/span&gt;. It is my understanding that the energy of &lt;span class=&quot;math-container&quot;&gt;$\ce{H+}$&lt;/span&gt; derived from DFT should be zero because of the absence of electrons, and that the positive and negative charges of the unit cell should introduce some errors.&lt;/p&gt;&#xA;&lt;p&gt;While some paper refer to DPE, others mention deprotonation Gibb's free energy as measure of acid strength. There seems to be some correlation between the two but I can not identify the difference.&lt;/p&gt;&#xA;" OwnerUserId="5923" LastEditorUserId="7" LastEditDate="2023-03-16T21:12:46.673" LastActivityDate="2023-03-16T21:17:18.950" Title="Calculate deprotonation energy or Gibbs free energy of acids" Tags="|computational-chemistry|free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10581" PostTypeId="1" CreationDate="2023-03-15T20:46:00.040" Score="4" ViewCount="253" Body="&lt;p&gt;I have been trying to find the binding energy of a water molecule with a crystalline silica slab and want to use vasp. whenever I try to use vasp for this purpose i get this error. Also, can someone point out how to find the binding energy(dispersion corrected) for a succesful vasp run.&lt;/p&gt;&#xA;&lt;p&gt;INCAR file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM   = SCF of deprotonated silanol site &#xA; NWRITE   = 2&#xA;&#xA; PREC = Accurate&#xA;&#xA; Startparameter for this Run:&#xA;   ISTART =   0      #Default: ISTART = 1 if WAVECAR exists, = 0 else&#xA;   ICHARG =   2      #Default: ICHARG = 2 if ISTART=0, = 0 else&#xA;   #ISPIN  =   1&#xA;&#xA; Write flags&#xA;   NCORE  = 4           have all processors work on same wave functions&#xA;   LPLANE = .TRUE.    distribute each wave over processors&#xA;   LWAVE  =  .FALSE.  do not write WAVECAR file&#xA;   LCHARG = .FALSE.  do not write CHGCAR file&#xA;&#xA; Electronic Relaxation 1&#xA;#  ENCUT  = largest ENMAX from POTCAR-file&#xA;   EDIFF  = 1.00E-05 # stopping-criterion for ELM&#xA;   LREAL  = A # real-space projection&#xA;   &#xA; Ionic relaxation&#xA;   EDIFFG = -0.001 # stopping-criterion for IOM&#xA;   ISMEAR = 0&#xA;   SIGMA  = 0.05&#xA;   NSW    = 0&#xA;   IBRION = -1&#xA;   ISIF   = 2&#xA;   ISYM   = 0&#xA;   &#xA; Electronic relaxation 2&#xA;   ALGO   = Normal&#xA;   &#xA; vdW corrections&#xA;   IVDW   =  11&#xA;   &#xA; Exchange correlation treatment:&#xA;   GGA    = PE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;vasp log file :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DAV:  35    -0.398634684225E+04   -0.90636E-03   -0.26555E-03 15140   0.211E-02    0.142E-01&#xA;DAV:  36    -0.398634820622E+04   -0.13640E-02   -0.19706E-04 14710   0.141E-02    0.128E-01&#xA;DAV:  37    -0.398634870970E+04   -0.50349E-03   -0.33971E-04 12830   0.112E-02    0.100E-01&#xA;DAV:  38    -0.398634950378E+04   -0.79408E-03   -0.26015E-04 13120   0.950E-03    0.502E-02&#xA;DAV:  39    -0.398635001301E+04   -0.50923E-03   -0.12996E-04 10720   0.763E-03    0.926E-02&#xA;DAV:  40    -0.398635017043E+04   -0.15741E-03   -0.44403E-05  9740   0.507E-03    0.805E-02&#xA;DAV:  41    -0.398635035368E+04   -0.18326E-03   -0.80287E-05 10390   0.484E-03    0.388E-02&#xA;DAV:  42    -0.398635060039E+04   -0.24671E-03   -0.29288E-05  9470   0.397E-03    0.262E-02&#xA;&#xA;===================================================================================&#xA;=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES&#xA;=   RANK 20 PID 31874 RUNNING AT r15r20n02&#xA;=   KILLED BY SIGNAL: 9 (Killed)&#xA;===================================================================================&#xA;&#xA;===================================================================================&#xA;=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES&#xA;=   RANK 21 PID 31875 RUNNING AT r15r20n02&#xA;=   KILLED BY SIGNAL: 9 (Killed)&#xA;===================================================================================&#xA;&#xA;===================================================================================&#xA;=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES&#xA;=   RANK 22 PID 31876 RUNNING AT r15r20n02&#xA;=   KILLED BY SIGNAL: 9 (Killed)&#xA;===================================================================================&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the system contains 630 atoms.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-03-16T02:24:45.487" Title="VASP with VDW dispersion corrections for a large system" Tags="|vasp|molecular-interactions|binding-energy|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10582" PostTypeId="1" CreationDate="2023-03-15T21:49:28.213" Score="4" ViewCount="80" Body="&lt;p&gt;Is there any software on metals that can predicts orbital or induced currents in metals in the presence of a magnetic field or electromagnetic waves?&lt;/p&gt;&#xA;" OwnerUserId="5321" LastEditorUserId="5321" LastEditDate="2023-03-16T00:26:54.380" LastActivityDate="2023-03-16T08:51:01.013" Title="Any software that can model eddy currents?" Tags="|software-recommendations|one-topic-per-answer|electronic-transport|metals|magnetic-field|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10583" PostTypeId="2" ParentId="10581" CreationDate="2023-03-16T02:24:45.487" Score="2" Body="&lt;p&gt;It was killed, this indicates something externally killed it.  Likely a manager for the cluster preventing you from running long jobs on the front end or the job simply ran out of time.&lt;/p&gt;&#xA;&lt;p&gt;Simply submit the job to the queue with more time.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2023-03-16T02:24:45.487" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10584" PostTypeId="1" CreationDate="2023-03-16T03:04:22.397" Score="7" ViewCount="919" Body="&lt;p&gt;I have a system with box dimensions of 21.0 * 21.0 * 80.0 for x,y and z directions. How may I generate the KPOINTs mesh for this system for VASP simulation? Any reference on this is hugely appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastEditorUserId="5" LastEditDate="2023-03-17T01:52:34.623" LastActivityDate="2023-03-17T01:52:34.623" Title="Can someone guide me on how to get the k-point file for a VASP simulation?" Tags="|vasp|k-points|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10585" PostTypeId="2" ParentId="10584" CreationDate="2023-03-16T08:30:48.033" Score="4" Body="&lt;p&gt;Here's a Python function that uses &lt;a href=&quot;https://pymatgen.org/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymatgen&lt;/a&gt; to generate a &lt;code&gt;KPOINTS&lt;/code&gt; file based on the lattice in the &lt;code&gt;POSCAR&lt;/code&gt; file. I think it's similar in spirit (and maybe certain aspects of implementation) to what @Pranav kumar suggested and how &lt;a href=&quot;https://vaspkit.com/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASPKIT&lt;/a&gt; does it.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from pymatgen.core import Structure&#xA;from pymatgen.io.vasp.inputs import Kpoints&#xA;&#xA;def write_KPOINTS(kspace=0.04):&#xA;    assert kspace &amp;gt;= 0, 'argument kspace must not be negative'&#xA;    struc = Structure.from_file('POSCAR')&#xA;    b = np.array(struc.lattice.reciprocal_lattice.as_dict()['matrix'])&#xA;    if kspace == 0:  # Gamma only&#xA;        N = [1, 1, 1]&#xA;        comment = 'Gamma point only'&#xA;    else:&#xA;        N = np.maximum(np.array([1, 1, 1]), np.round(np.sqrt(np.sum(b**2, axis=1)) / (kspace * 2 * np.pi))).astype(np.int64)&#xA;        comment = 'Mesh generated with kspace = {} × 2π/Å'.format(kspace)&#xA;    k_dict = {'nkpoints': 0,&#xA;              'generation_style': 'Gamma',&#xA;              'kpoints': [[N[0], N[1], N[2]]],&#xA;              'usershift': [0, 0, 0],&#xA;              'comment': comment}&#xA;    kpoints = Kpoints.from_dict(k_dict)&#xA;    kpoints.write_file('KPOINTS')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;kspace&lt;/code&gt; represents the k-point density in units of &lt;span class=&quot;math-container&quot;&gt;$2\pi Å^{-1}$&lt;/span&gt; in each cartesian direction. I set &lt;code&gt;kspace=0&lt;/code&gt; to mean Gamma point sampling, which would be used for &amp;quot;isolated structures&amp;quot; as @Abdul Muhaymin suggested. If it were a crystal structure, it's also easier to do a convergence test by reducing a single variable &lt;code&gt;kspace&lt;/code&gt; until convergence (as opposed to three distinct mesh integers for the x,y, and z direction).&lt;/p&gt;&#xA;&lt;p&gt;Of course, your box looks very big, so it is likely that using a &amp;quot;conventionally tight&amp;quot; &lt;code&gt;kspace= 0.01 ~ 0.03&lt;/code&gt; may lead to a single kpoint, which seems related to your exchange with @Pranav kumar.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-03-16T08:30:48.033" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10586" PostTypeId="2" ParentId="10582" CreationDate="2023-03-16T08:51:01.013" Score="2" Body="&lt;p&gt;I found couple of tools online. Here I collate the ones I think are relevant:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://github.com/epardov/MEMEP3Dtool&quot; rel=&quot;nofollow noreferrer&quot;&gt;MEMEP3Dtool&lt;/a&gt;:&#xA;Three-dimensional (3D) electro-magnetic modeling tool for superconductors and normal conductors using the Minimum Electro-Magnetic Entropy Production (MEMEP) variational principle. (1)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://www.usc.es/en/proxectos/maxfem/description.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;MaxFEM&lt;/a&gt;:&#xA;This &lt;a href=&quot;https://link.springer.com/chapter/10.1007/978-3-319-02949-8_16&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; shows examples of how to use MaxFEM for analysis of eddy currents. (2)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://quickfield.com/index.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;QuickField&lt;/a&gt;:&#xA;Here is an &lt;a href=&quot;https://quickfield.com/advanced/hmagn5_induction_pump.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt; to simulate eddy currents in a liquid metal on the QuickField website. Quickfield has a free &amp;quot;student&amp;quot; edition. More info &lt;a href=&quot;https://quickfield.com/free_soft.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Enric Pardo, Milan Kapolka, 3D computation of non-linear eddy&#xA;currents: Variational method and superconducting cubic bulk, Journal&#xA;of Computational Physics, Volume 344,2017,Pages 339-363, ISSN&#xA;0021-9991, &lt;a href=&quot;https://doi.org/10.1016/j.jcp.2017.05.001&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1016/j.jcp.2017.05.001&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Bermúdez, A., Gómez, D., &amp;amp; Salgado, P. (2014). Eddy currents with maxfem. UNITEXT, 325–345. &lt;a href=&quot;https://doi.org/10.1007/978-3-319-02949-8_16&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1007/978-3-319-02949-8_16&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-03-16T08:51:01.013" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10587" PostTypeId="2" ParentId="10584" CreationDate="2023-03-16T11:42:44.830" Score="3" Body="&lt;p&gt;The VASP wiki has many explanations for setting up calculations. For k-spacing you can use the automatic grid generation with the KSPACING tag in the INCAR file, especially if you don't know your system well:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/KSPACING&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/KSPACING&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The number of k-points you need can differ between different problems. Therefore, you should try different numbers and look for convergence. The wiki recommends using the automatic generation only for first tries, and then continuing with regular k-meshes.&lt;/p&gt;&#xA;" OwnerUserId="2084" LastActivityDate="2023-03-16T11:42:44.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10588" PostTypeId="1" CreationDate="2023-03-16T14:36:26.940" Score="7" ViewCount="293" Body=" &#xA;&lt;p&gt;The following is the procedure I have been following:&lt;/p&gt;&#xA;&lt;h1&gt;Install PySCFad&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python/3.10 flexiblas libxc/5.1.3 qcint # modify accordingly based on the modules available on your supercomputer&#xA;virtualenv --no-download --clear ~/ve_pyscfad_wheel &amp;amp;&amp;amp; source ~/ve_pyscfad_wheel/bin/activate&#xA;pip install --no-index --upgrade pip&#xA;git clone https://github.com/fishjojo/pyscf.git --branch ad pyscf_ad&#xA;cd pyscf_ad&#xA;sed -i '38s/pyscf/pyscf-custom-ad/' setup.py&#xA;export VERBOSE=1; export CMAKE_CONFIGURE_ARGS=&amp;quot;-DBLA_VENDOR=Flexiblas -DBLAS_LIBRARIES=-lflexiblas -DBUILD_LIBCINT=0 -DBUILD_LIBXC=0&amp;quot;;&#xA;python setup.py bdist_wheel&#xA;&#xA;&#xA;# Install &amp;quot;ad&amp;quot; branch of PySCF in one line, then pyscfad and pyscf-properties next:&#xA;pip install --no-index dist/pyscf_custom_ad-2.1.1-cp310-cp310-linux_x86_64.whl&#xA;pip install --no-index pyscfad pyscf-properties&#xA;pip freeze &amp;gt; /home/nike/pyscfad-requirements.txt&#xA;&#xA;# Make the ~/.pyscfad_conf.py file contain only the following text:&#xA;pyscfad = True&#xA;pyscf_numpy_backend = 'jax'&#xA;pyscf_scipy_linalg_backend = 'pyscfad'&#xA;pyscf_scipy_backend = 'jax'&#xA;# The followings are optional&#xA;pyscfad_scf_implicit_diff = True&#xA;pyscfad_ccsd_implicit_diff = True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Submit job&lt;/h1&gt;&#xA;&lt;p&gt;My Python script is the following executable file called &lt;code&gt;00-simple.py&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import pyscf&#xA;from pyscfad import gto, scf&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;Analytic nuclear gradient for RHF computed by auto-differentiation&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom    = 'H 0 0 0; H 0 0 0.74'  # in Angstrom&#xA;mol.basis   = '631g'&#xA;mol.verbose = 5&#xA;mol.build()&#xA;&#xA;mf = scf.RHF(mol)&#xA;mf.kernel()&#xA;jac = mf.energy_grad()&#xA;print(f'Nuclaer gradient:\n{jac.coords}')&#xA;print(f'Gradient wrt basis exponents:\n{jac.exp}')&#xA;print(f'Gradient wrt basis contraction coefficients:\n{jac.ctr_coeff}')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My SLURM submission script contains the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python/3.10&#xA;virtualenv --no-download --clear &lt;span class=&quot;math-container&quot;&gt;$SLURM_TMPDIR/ENV &amp;amp;&amp;amp; source $&lt;/span&gt;SLURM_TMPDIR/ENV/bin/activate&#xA;pip install --no-index --upgrade pip&#xA;pip install --no-index -r /home/nike/pyscfad-requirements.txt&#xA;&#xA;export PYSCF_MAX_MEMORY=6000 # in MB&#xA;PYSCF_CONFIG_FILE=~/.pyscfad_conf.py&#xA;&#xA;./00-simple.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Output&lt;/h1&gt;&#xA;&lt;p&gt;The std output file contained:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Processing /home/nike/pyscfad/dist/pyscf_custom_ad-2.1.1-cp310-cp310-linux_x86_64.whl&#xA;...&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2/pyscf-2.2.0+computecanada-cp310-cp310-linux_x86_64.whl&#xA;...&#xA;Installing collected packages: typing_extensions, six, pyparsing, Pillow, packaging, numpy, kiwisolver, fonttools, cycler, absl_py, scipy, python-dateutil, opt-einsum, h5py, contourpy, pyscf-custom-ad, pyscf, matplotlib, jaxlib, pyscf_properties, jax, jaxopt, pyscfad&#xA;Successfully installed Pillow-9.4.0+computecanada absl_py-1.4.0+computecanada contourpy-1.0.7+computecanada cycler-0.11.0+computecanada fonttools-4.39.0+computecanada h5py-3.8.0+computecanada jax-0.4.2+computecanada jaxlib-0.4.2+cuda11.cudnn82.computecanada jaxopt-0.6+computecanada kiwisolver-1.4.4+computecanada matplotlib-3.7.0+computecanada numpy-1.24.2+computecanada opt-einsum-3.3.0+computecanada packaging-23.0+computecanada pyparsing-3.0.9+computecanada pyscf-2.2.0+computecanada pyscf-custom-ad-2.1.1 pyscf_properties-0.1.0+computecanada pyscfad-0.1.2+computecanada python-dateutil-2.8.2+computecanada scipy-1.10.1+computecanada six-1.16.0+computecanada typing_extensions-4.5.0+computecanada&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The error file contained the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/project/6004934/nike/basis-set-optimization/./00-simple.py&amp;quot;, line 4, in &amp;lt;module&amp;gt;&#xA;    from pyscfad import gto, scf&#xA;  File &amp;quot;/localscratch/nike.62605116.0/ENV/lib/python3.10/site-packages/pyscfad/scf/__init__.py&amp;quot;, line 3, in &amp;lt;module&amp;gt;&#xA;    from pyscfad.scf import rohf&#xA;  File &amp;quot;/localscratch/nike.62605116.0/ENV/lib/python3.10/site-packages/pyscfad/scf/rohf.py&amp;quot;, line 4, in &amp;lt;module&amp;gt;&#xA;    from pyscf.lib import stop_grad&#xA;ImportError: cannot import name 'stop_grad' from 'pyscf.lib' (/localscratch/nike.62605116.0/ENV/lib/python3.10/site-packages/pyscf/lib/__init__.py)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;How can I run this code without getting an error?&lt;/h2&gt;&#xA;&lt;p&gt;The input file is taken precisely from the &lt;code&gt;examples/scf/&lt;/code&gt; folder of the main branch of the PySCFad GitHub repository, and it works on a &amp;quot;personal&amp;quot; laptop that uses the same version of PySCFad (the version that was released two days ago).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-03-18T01:04:06.067" LastActivityDate="2024-04-02T23:42:20.977" Title="How can I build the wheels necessary for a quick installation of PySCFad on a &quot;compute node&quot;?" Tags="|python|high-performance-computing|pyscf|machine-learning|optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10589" PostTypeId="2" ParentId="10580" CreationDate="2023-03-16T15:06:05.503" Score="8" Body="&lt;p&gt;Despite the fact I'm not sure what your question is, I'll try to answer it :-)&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;the energy of H+ derived from DFT should be zero&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The idea is that a pure &lt;span class=&quot;math-container&quot;&gt;$\ce{H+}$&lt;/span&gt; ion exists in a gas phase only, whereas in a liquid state it's bound by a base, which is usually a solvent. For water solutions usually &lt;span class=&quot;math-container&quot;&gt;$\ce{H3O+}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H5O2+}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\ce{H3O+(H2O)3}$&lt;/span&gt; ions are considered. This approach is called the &amp;quot;explicit solvent approach&amp;quot;. In addition, you should add an implicit solvent model to your computations, e.g. PCM, CPCM, etc. Check &lt;a href=&quot;https://doi.org/10.1039/C002528C&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; [1] as an example.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;negative charges of the unit cell should introduce some errors&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Usually, such systems are computed without boundary conditions using non-periodic codes like Orca, Gaussian, GAMESS, etc. Therefore you can compute isolated ions without technical or theoretical problems.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;While some paper refer to DPE other mention deprotonation Gibbs free energy as measure of acid strength. There seems to be some correlation between the two but I can not identify the difference.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Deprotonation energy is computed using electronic energies, and deprotonation Gibbs free energy is computed via Gibbs energies. To obtain Gibbs energies and other thermodynamic parameters from DFT calculations, one needs to run frequency computation for the optimized structure.&lt;/p&gt;&#xA;&lt;p&gt;The final note: in some approaches, DFT is used to compute &lt;span class=&quot;math-container&quot;&gt;$E(\ce{AH})$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E(\ce{A-})$&lt;/span&gt; only, whereas for &lt;span class=&quot;math-container&quot;&gt;$E(\ce{H+})$&lt;/span&gt; (which actually is a proton solvation energy) the experimental value is used. Check &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.0c08283&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; [2] for more details.&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Steenken, S.; Reynisson, J. DFT Calculations on the Deprotonation Site of the One-Electron Oxidised Guanine–Cytosine Base Pair. Physical Chemistry Chemical Physics, 2010, 12, 9088. &lt;a href=&quot;https://doi.org/10.1039/c002528c&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1039/c002528c&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Dutra, F. R.; Silva, C. de S.; Custodio, R. On the Accuracy of the Direct Method to Calculate pKa from Electronic Structure Calculations. The Journal of Physical Chemistry A, 2020, 125, 65–73. &lt;a href=&quot;https://doi.org/10.1021/acs.jpca.0c08283&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/acs.jpca.0c08283&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6875" LastEditorUserId="7" LastEditDate="2023-03-16T21:17:18.950" LastActivityDate="2023-03-16T21:17:18.950" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10590" PostTypeId="2" ParentId="10588" CreationDate="2023-03-17T01:33:14.717" Score="7" Body="&lt;p&gt;I finally got it working!&lt;/p&gt;&#xA;&lt;h1&gt;Explanation of the error&lt;/h1&gt;&#xA;&lt;p&gt;The above procedure installed the &amp;quot;main&amp;quot; branch of &amp;quot;pyscf_properties&amp;quot;  rather than the &amp;quot;ad&amp;quot; branch. It seems that due to a requirement not being met, the original PySCF wheel on the cluster was being pulled, rather than installing the &amp;quot;ad&amp;quot; branch of PySCF.  The following build procedure, constructed with the help of Charles Coulombe from Compute Canada.&lt;/p&gt;&#xA;&lt;h1&gt;Build&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Set up the virtual environment, clone the &amp;quot;ad&amp;quot; branch of PySCF, add a custom tag to the version and build wheel:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python/3.10 flexiblas libxc/5.1.3 &#xA;virtualenv --no-download --clear ~/ve_pyscfad_wheel &amp;amp;&amp;amp; source ~/ve_pyscfad_wheel/bin/activate&#xA;pip install --no-index --upgrade pip&#xA;git clone https://github.com/fishjojo/pyscf.git --branch ad pyscf_ad&#xA;cd pyscf_ad&#xA;&#xA;sed -i '38s/2.1.1/2.1.1+ad/' pyscf/__init__.py &#xA;export VERBOSE=1; export CMAKE_CONFIGURE_ARGS=&amp;quot;-DBLA_VENDOR=Flexiblas -DBLAS_LIBRARIES=-lflexiblas -DBUILD_LIBCINT=1 -DBUILD_LIBXC=0&amp;quot;;&#xA;time python setup.py bdist_wheel&#xA;cd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Clone the &amp;quot;ad&amp;quot; branch of &amp;quot;pyscf_properties&amp;quot;, add a custom tag to the version and build wheel:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;git clone https://github.com/fishjojo/properties.git --branch ad pyscf_properties_ad&#xA;cd pyscf_properties_ad/&#xA;&#xA;sed -i '15s/0.1.0/0.1.0+ad/' pyscf/prop/__init__.py &#xA;python setup.py bdist_wheel&#xA;cd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Install the &amp;quot;ad&amp;quot; branch of PySCF, the &amp;quot;ad&amp;quot; branch of &amp;quot;pyscf_properties&amp;quot; and the main branch of PySCFad, then freeze requirements:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pip install --no-index $HOME/pyscf_ad/dist/pyscf-2.1.1+ad-cp310-cp310-linux_x86_64.whl $HOME/pyscf_properties_ad/dist/pyscf_properties-0.1.0+ad-py3-none-any.whl pyscfad # Somehow this was working with $HOME/pyscf_ad/ and $HOME/properties/ even though these folders didn't exist?&#xA;pip freeze &amp;gt; pyscfad-requirements.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Test to see if the error mentioned in the original question happens, then deactivate the virtual environment:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python -c 'from pyscfad import gto, scf' # Will only work if we've correctly installed the &amp;quot;ad&amp;quot; branch of pyscf_properties&#xA;deactivate&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Set the &lt;code&gt;~/.pyscfad_conf.py&lt;/code&gt; file exactly as described in the question:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pyscfad = True&#xA;pyscf_numpy_backend = 'jax'&#xA;pyscf_scipy_linalg_backend = 'pyscfad'&#xA;pyscf_scipy_backend = 'jax'&#xA;# The followings are optional&#xA;pyscfad_scf_implicit_diff = True&#xA;pyscfad_ccsd_implicit_diff = True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Run&lt;/h1&gt;&#xA;&lt;p&gt;The lines described for the SLURM submission script, which were mentioned in the &amp;quot;Submit job&amp;quot; section of the question, can seemingly remain unchanged.  I used &lt;code&gt;export PYSCF_CONFIG_FILE=~/.pyscfad_conf.py&lt;/code&gt; instead of just &lt;code&gt;PYSCF_CONFIG_FILE=~/.pyscfad_conf.py&lt;/code&gt; but the output when the example script is run, isn't affected by whether or not &lt;code&gt;export&lt;/code&gt; is included here. Add the following lines into your SLURM script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python/3.10&#xA;virtualenv --no-download --clear &lt;span class=&quot;math-container&quot;&gt;$SLURM_TMPDIR/ENV &amp;amp;&amp;amp; source $&lt;/span&gt;SLURM_TMPDIR/ENV/bin/activate&#xA;pip install --no-index --upgrade pip&#xA;pip install --no-index -r /home/nike/pyscfad-requirements.txt&#xA;&#xA;export PYSCF_MAX_MEMORY=6000 # in MB&#xA;export PYSCF_CONFIG_FILE=~/.pyscfad_conf.py&#xA;&#xA;./00-simple.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Just for completeness I'll include the &lt;code&gt;00-simple.py&lt;/code&gt; file from the original question here again:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;&#xA;import pyscf&#xA;from pyscfad import gto, scf&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;Analytic nuclear gradient for RHF computed by auto-differentiation&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom    = 'H 0 0 0; H 0 0 0.74'  # in Angstrom&#xA;mol.basis   = '631g'&#xA;mol.verbose = 5&#xA;mol.build()&#xA;&#xA;mf = scf.RHF(mol)&#xA;mf.kernel()&#xA;jac = mf.energy_grad()&#xA;print(f'Nuclaer gradient:\n{jac.coords}')&#xA;print(f'Gradient wrt basis exponents:\n{jac.exp}')&#xA;print(f'Gradient wrt basis contraction coefficients:\n{jac.ctr_coeff}')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-04-02T23:42:20.977" LastActivityDate="2024-04-02T23:42:20.977" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10591" PostTypeId="1" CreationDate="2023-03-17T09:50:13.527" Score="4" ViewCount="294" Body="&lt;p&gt;I have a structure with the parameters bellow:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ibrav = 0&#xA;&#xA; A = 6.05844&#xA;&#xA;CELL_PARAMETERS {alat}&#xA;&#xA;   0.497698628   0.497698628   0.000000000&#xA;&#xA;   0.497698628   0.000000000   0.497698628&#xA;&#xA;  -0.000000000   0.497698628   0.497698628&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can someone help me to convert them to cartesian coordinates, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-03-17T13:09:27.537" Title="How can I transform my unit cell positions to cartesian coordinates?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10592" PostTypeId="2" ParentId="10591" CreationDate="2023-03-17T13:09:27.537" Score="7" Body="&lt;p&gt;If the cell is cubic, converting fractional coordinates to Cartesian coordinates is straight forward: just multiply any fractional coordinate by the cell vector.&lt;/p&gt;&#xA;&lt;p&gt;Ex. Let suppose that the fractional coordinates are:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \begin{bmatrix}&#xA;a_1 &amp;amp; b_1 &amp;amp; c_1 \\&#xA;a_2 &amp;amp; b_2 &amp;amp; c_2 \\&#xA;a_3 &amp;amp; b_3 &amp;amp; c_3 &#xA;\end{bmatrix}  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the cell parameters are A, B, and C in Angstroms, then, the coordinates in Angstroms are:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \begin{bmatrix}&#xA;x_1=a_1*A &amp;amp; y_1=b_1*B &amp;amp; z_1=c_1*C \\&#xA;x_2=a_2*A &amp;amp; y_2=b_2*B &amp;amp; z_2=c_2*C \\&#xA;x_3=a_3*A &amp;amp; y_3=b_3*B &amp;amp; z_3=c_3*C &#xA;\end{bmatrix}  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the cell is not cubic, the conversion has to take into account the cell angles (&lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_2$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\alpha_3$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;${\begin{pmatrix}x_1\\y_2\\z_3\end{pmatrix}}={\begin{pmatrix}A\sin(\alpha _{2}){\sqrt {1-(\cot(\alpha _{1})\cot(\alpha _{2})-\csc(\alpha _{1})\csc(\alpha _{2})\cos(\alpha _{3}))^{2}}}&amp;amp;0&amp;amp;0\\&#xA;A\csc(\alpha _{1})\cos(\alpha _{3})-A\cot(\alpha _{1})\cos(\alpha _{2})&amp;amp;B\sin(\alpha _{1})&amp;amp;0\\&#xA;A\cos(\alpha _{2})&amp;amp;B\cos(\alpha _{1})&amp;amp;C\\\end{pmatrix}}{\begin{pmatrix}a_1\\b_2\\c_3\end{pmatrix}}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For more details, the &lt;a href=&quot;https://en.wikipedia.org/wiki/Fractional_coordinates&quot; rel=&quot;noreferrer&quot;&gt;Wiki link&lt;/a&gt; is a good starting point.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-03-17T13:09:27.537" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10593" PostTypeId="2" ParentId="10541" CreationDate="2023-03-17T14:45:41.060" Score="1" Body="&lt;p&gt;The process you described for obtaining a supercell can be found &lt;a href=&quot;https://icme.hpc.msstate.edu/mediawiki/index.php/How_to_make_Supercell_for_Quantum_ESPRESSO.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If the 1*1*1 unit cell has a lattice parameter of &lt;strong&gt;a&lt;/strong&gt;, then a 2*2*2 supercell will have a lattice parameter of &lt;strong&gt;2a&lt;/strong&gt;, a 3*3*3 supercell will have a lattice parameter of &lt;strong&gt;3a&lt;/strong&gt;, and so on. Note that different parameters have different units.&lt;/p&gt;&#xA;&lt;p&gt;In your example, it's a body-centered cubic cell with a more symmetric axis (instead of defining it by CELL_PARAMETERS card, you could have used &lt;code&gt;ibrav=-3&lt;/code&gt; and &lt;code&gt;celldm(1)=7.75575&lt;/code&gt;). In this case, your unit cell has:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS angstrom&#xA;-2.025  2.025   2.025&#xA;2.025   -2.025  2.025&#xA;2.025   2.025   -2.025&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, for a 2*2* supercell, you would expect you supercell CELL_PARAMETERS as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS angstrom&#xA;-4.05   4.05   4.05   &#xA;4.05   -4.05   4.05   &#xA;4.05   4.05   -4.05   &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I reproduced it using phononpy, I got:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS bohr&#xA;   -7.6533908550512457    7.6533908550512457    7.6533908550512457&#xA;    7.6533908550512457   -7.6533908550512457    7.6533908550512457&#xA;    7.6533908550512457    7.6533908550512457   -7.6533908550512457&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which is equivalent since 4.05 angstrom= -7.65339 bohr. The example you mentioned is incorrect in the sense that even though it talks about a 2*2*2 supercell, it actually calculated a 3*3*3 supercell. That's why you have 27 atoms whereas you should have 8 atoms in a 2*2*2 supercell. I attached the complete output for a 2*2*2 supercell calculation for the input file in the question:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!    ibrav = 0, nat = 8, ntyp = 1&#xA;CELL_PARAMETERS bohr&#xA;   -7.6533908550512457    7.6533908550512457    7.6533908550512457&#xA;    7.6533908550512457   -7.6533908550512457    7.6533908550512457&#xA;    7.6533908550512457    7.6533908550512457   -7.6533908550512457&#xA;ATOMIC_SPECIES&#xA; Bi  208.98040   Bi.pbe-dn-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA; Bi   0.0000000000000000  0.0000000000000000  0.0000000000000000&#xA; Bi   0.5000000000000000  0.0000000000000000  0.0000000000000000&#xA; Bi   0.0000000000000000  0.5000000000000000  0.0000000000000000&#xA; Bi   0.5000000000000000  0.5000000000000000  0.0000000000000000&#xA; Bi   0.0000000000000000  0.0000000000000000  0.5000000000000000&#xA; Bi   0.5000000000000000  0.0000000000000000  0.5000000000000000&#xA; Bi   0.0000000000000000  0.5000000000000000  0.5000000000000000&#xA; Bi   0.5000000000000000  0.5000000000000000  0.5000000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-17T14:45:41.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10594" PostTypeId="2" ParentId="9638" CreationDate="2023-03-17T19:45:37.957" Score="3" Body="&lt;p&gt;On &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/GAMESS_Manual/docs-prog.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;section 5&lt;/a&gt; of the GAMESS-US manual , it says the following.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For smaller data, such as CI vectors, where all processes want to&#xA;store exactly the same data, only the master process needs to maintain&#xA;the file.  This situation is DSKWRK=.FALSE.  When the data is to be&#xA;recovered from disk, only the master process reads the disk, after&#xA;which, the data is sent as a broadcast message to all other processes.&#xA;The special file DICTNRY is always processed in this second way, so&#xA;data recovered from it is the same (to the least significant bits) on&#xA;every process.  Another example of a file read by only one process is&#xA;the run's INPUT file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So from this, my understanding is that this DICTNRY file is written to disk during some processing.&lt;/p&gt;&#xA;&lt;p&gt;And I see that GAMESS-US is written using fortran from the manual:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;GAMESS will run on essentially any machine with a FORTRAN 77 compiler.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I tried to access the source code from &lt;a href=&quot;https://www.msg.chem.iastate.edu/gamess/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. However, I am hit with a non-responsive webpage. So my recommendation would be to look into the source with the following in mind.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Look for the files with the extensions .f, .for, f90. In those files,&#xA;look for the keywords: &lt;code&gt;OPEN&lt;/code&gt; and &lt;code&gt;WRITE&lt;/code&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;So the DICTNRY file will be written to disk in a statement like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OPEN(UNIT=some &#xA;number,FILE=DICTNRY_FILE_PATH,FORM='FORMATTED',STATUS='NEW')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So this statement will essentially create a file and connect it to a&lt;br /&gt;&#xA;unit defined by the number in the &lt;code&gt;UNIT&lt;/code&gt;.&#xA;And the data values will be written to the DICTNRY file in a    statemen&#xA;that looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WRITE(same number used with the UNIT before, either some datatypes like &#xA;'(4F10.5,A)' or *) &#xA;quantity_1,quantity_2,quantity_3,quantity_4,some_string&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the above WRITE statement, 4F10.5 means 4 float values with 10 digits in total with 5 decimal digits and A represents string.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;So you can look for the path to the &lt;strong&gt;DICTNRY&lt;/strong&gt; file in the &lt;code&gt;OPEN&lt;/code&gt; and then&#xA;double check it in the &lt;code&gt;WRITE&lt;/code&gt; statements by looking for some values of&#xA;quantities like Atomic coordinates or any of the 817 parameters that&#xA;are written to that file.&lt;/p&gt;&#xA;&lt;p&gt;Once you have path you can access it on the disk using the path during/after a run.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-03-18T07:28:13.140" LastActivityDate="2023-03-18T07:28:13.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10595" PostTypeId="1" CreationDate="2023-03-17T20:44:57.693" Score="4" ViewCount="182" Body="&lt;h2&gt;Context&lt;/h2&gt;&#xA;&lt;p&gt;I have two images from a Monte Carlo Basin Hopping where silicon (in yellow) is getting replaced by germanium (in blue). Both have 32 germanium atoms at Si/Ge = 2.5; only the Ge distribution is changing.&lt;/p&gt;&#xA;&lt;p&gt;There appears to be a clustering of the germanium in the the first structure with relative energy= 0 ev.&#xA;Whereas the higher energy structure has no such pattern.&#xA;I am trying to to correlate the energy and the clustering.&lt;/p&gt;&#xA;&lt;h2&gt;Question:&lt;/h2&gt;&#xA;&lt;p&gt;How could I verify this layering/clustering, to correlate the energy and the clustering, using some sort of metrics?&lt;/p&gt;&#xA;&lt;p&gt;Any of the following would be helpful for me.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Any links to any publication to gain ideas&lt;/li&gt;&#xA;&lt;li&gt;Suggestion of a metric or parameter.&lt;/li&gt;&#xA;&lt;li&gt;Any ML method or software that may help with this.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/a8vRn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a8vRn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="6687" LastEditDate="2023-03-27T09:14:05.323" LastActivityDate="2024-02-15T20:07:45.873" Title="Layer detection in a crystal structure" Tags="|python|crystallography|atomic-simulation-environment|monte-carlo|atomistic-simulation|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10596" PostTypeId="2" ParentId="10281" CreationDate="2023-03-18T09:54:34.853" Score="4" Body="&lt;p&gt;If it is for an assignment, then students ideally must not be expected to pay $50 to obtain the software for themselves just to complete an assignment.&lt;/p&gt;&#xA;&lt;h2&gt;Best Case Scenario&lt;/h2&gt;&#xA;&lt;p&gt;The University will usually have a license for the said software. You could possibly request and urge your professor to get a license. Here are the &lt;a href=&quot;https://www.wavefun.com/spartan-student-pricing&quot; rel=&quot;nofollow noreferrer&quot;&gt;pricing details&lt;/a&gt; on the Spartan page.&lt;/p&gt;&#xA;&lt;p&gt;Once you have a university license, you can use the university license server when prompted for the name of the Spartan license server.&lt;/p&gt;&#xA;&lt;p&gt;Here are detailed &lt;a href=&quot;https://spartan.ucsd.edu/installation&quot; rel=&quot;nofollow noreferrer&quot;&gt;instructions&lt;/a&gt; for a student of University of California San Diego (UCSD). So you can follow the instructions and change as per your university license server.&lt;/p&gt;&#xA;&lt;h2&gt;Worst Case Scenario:&lt;/h2&gt;&#xA;&lt;p&gt;In the worst case, that you are still expected to purchase this software, and you are not in a position to buy it, then you can utilise other alternative free open source tools such as Python to do this:&lt;/p&gt;&#xA;&lt;p&gt;Here is an &lt;a href=&quot;https://andersle.no/posts/2022/mo/mo.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;article&lt;/a&gt; which clearly explains how to calculate eLumo and eHomo using various python libraries. Both are free and open source.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-03-18T11:59:37.900" LastActivityDate="2023-03-18T11:59:37.900" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10598" PostTypeId="1" CreationDate="2023-03-18T18:07:30.230" Score="5" ViewCount="208" Body="&lt;p&gt;I am currently trying to implement a GS2 (Gonzalez-Schlegel second order) IRC algorithm in a python code. I am following the original paper ref(1).&lt;/p&gt;&#xA;&lt;p&gt;The main problem is in the constrained optimisation step of the GS2 algorithm. In this step, the geometry optimisation is done by holding the distance of the coordinates (euclidean distance) constant from the coordinates of a pivot point (fixed throughout optimisation).&lt;/p&gt;&#xA;&lt;p&gt;I will reproduce the main equations for the GS2 constrained optimisation step here:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$p' = x' - x^* \tag{1}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta x = x - x'\tag{2}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$p = p' + \Delta x = x - x^* \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$x'$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; are the old and new coordinates for the constrained optimisation; &lt;span class=&quot;math-container&quot;&gt;$x^*$&lt;/span&gt; is the pivot point that is constant. The &lt;span class=&quot;math-container&quot;&gt;$p'$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; similarly are the vectors from the old and new coordinates to the pivot point, respectively.&lt;/p&gt;&#xA;&lt;p&gt;The energy is minimised under the constraint &lt;span class=&quot;math-container&quot;&gt;$p^T\cdot p = k$&lt;/span&gt; (where k is some fixed scalar number). This is equivalent to optimization on the surface of a hypersphere. They express the optimisation problem with a Lagrange multiplier form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$L = E' + g^T \cdot \Delta x + \frac{1}{2} \Delta x^T\cdot H \cdot \Delta x - \frac{1}{2} \lambda [p^T\cdot p - k]\tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where the potential energy surface is expressed as a truncated Taylor series (as normal for QM stuff) and the &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; are the gradient vector and Hessian matrix as usual.&lt;/p&gt;&#xA;&lt;p&gt;What I don't understand here is the half sign in front of the Lagrange muliplier &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, after this, they mention that at convergence, that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta x = - (H - \lambda I)^{-1} \cdot (g- \lambda p')\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;They then put that expression into the expression for &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; (eqn. 3) and find the &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; (by doing a bracketing 1D scalar root search) for which the &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt; satisfies the constraint.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How does this expression follow from the above expression? I don't quite understand. Could anyone explain how this derivation works mathematically?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also, another problem with these equations is that the step size is too high in most iterations so there is unpredictable behaviour. Is there any way to restrict the step size for the constrained optimisation step? (In the paper, they have a linear interpolation formula to stabilize the quasi-NR step, but it does not help too much)&lt;/p&gt;&#xA;&lt;p&gt;References:&#xA;(1) C. Gonzalez, H. B. Schlegel, &lt;em&gt;J Chem. Phys.&lt;/em&gt;, 1989, &lt;strong&gt;90&lt;/strong&gt;(4), 2155&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-03-19T09:52:10.247" LastActivityDate="2023-03-19T16:20:49.400" Title="Constrained optimisation on a hypersphere" Tags="|python|geometry-optimization|mathematical-modeling|derivations|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10599" PostTypeId="2" ParentId="10598" CreationDate="2023-03-19T03:59:50.447" Score="6" Body="&lt;p&gt;I'll propose a slightly different Lagrangian expression:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ L = E' + g^T \Delta x + \frac{1}{2} \Delta x^T H \Delta x + \frac{1}{2} \gamma \Delta x^T \Delta x - \frac{1}{2} \lambda (p^T p - k). \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; is really a spring &lt;em&gt;constant&lt;/em&gt; (with the corresponding units) that penalizes large norms for &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt;. The sign of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; doesn't really matter since it's enforcing a constraint, so we keep it as per the expression given above in equation 4.&lt;/p&gt;&#xA;&lt;p&gt;Now, we would like to minimize the Lagrangian with respect to &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt;, and we will do so by completing squares. First we substitute in &lt;span class=&quot;math-container&quot;&gt;$p = p' + \Delta x$&lt;/span&gt; (equation 3), and collect terms in like powers of &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ L = \frac{1}{2}(\Delta x^T[H + \gamma I - \lambda I]\Delta x) - (\lambda p' - g)^T \Delta x + \cdots \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the dotted terms are constant with respect to &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt;. The term linear in &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt; combines a contribution from the forces &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; and a contribution from the &lt;span class=&quot;math-container&quot;&gt;$p^Tp$&lt;/span&gt; term of equation 4.&lt;/p&gt;&#xA;&lt;p&gt;Now hark back to your high school algebra: a quadratic expression &lt;span class=&quot;math-container&quot;&gt;$ax^2 - bx + c$&lt;/span&gt; is minimized at &lt;span class=&quot;math-container&quot;&gt;$x^* = (2a)^{-1} b$&lt;/span&gt; (by completing the square), and this is no different:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \Delta x^* \equiv \mathrm{arg min}\,L(\Delta x) = (H + \gamma I - \lambda I)^{-1}(\lambda p' - g) \tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Other than my proposed modification (equivalently, when &lt;span class=&quot;math-container&quot;&gt;$\gamma = 0$&lt;/span&gt;) this expression is exactly equation 5.&lt;/p&gt;&#xA;&lt;p&gt;So hopefully this answers your three questions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Why half &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;&lt;/em&gt;? Scaling your quadratic term by half leaves you with just &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; in the final answer, rather than &lt;span class=&quot;math-container&quot;&gt;$2 \lambda$&lt;/span&gt;. It's purely aesthetic -- but it also does leave you with one less factor of two to muck up when you're programming.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;How to get to equation 5&lt;/em&gt;? Expand in terms of &lt;span class=&quot;math-container&quot;&gt;$\Delta x$&lt;/span&gt; and complete the square.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;How to constrain the step size&lt;/em&gt;? To me the most natural way is to put in an explicit norm restraint. From my final equation you can see that when &lt;span class=&quot;math-container&quot;&gt;$\gamma \gg \lambda$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\gamma \gg ||H||$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\Delta x^*$&lt;/span&gt; will just be &lt;span class=&quot;math-container&quot;&gt;$(\lambda p' - g)/\gamma$&lt;/span&gt; -- that is, you'll simply be following the forces downwards, in ever decreasing step size as &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; increases.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="142" LastEditDate="2023-03-19T16:20:49.400" LastActivityDate="2023-03-19T16:20:49.400" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10600" PostTypeId="1" AcceptedAnswerId="10604" CreationDate="2023-03-19T18:50:21.863" Score="6" ViewCount="1025" Body="&lt;p&gt;I want to preface this by saying I am really new to computational chemistry and this kind of programming in general, but I am having real trouble figuring out how to use OpenBabel's &lt;code&gt;gen3d&lt;/code&gt; function in a Python notebook. I want to use it to make a single force field optimized conformer from a SMILES string but I don't really know how to call it on my SMILES string. Any help or links would be greatly appreciated! Thank you!&lt;/p&gt;&#xA;" OwnerUserId="6901" LastEditorUserId="5" LastEditDate="2023-03-19T18:55:12.027" LastActivityDate="2023-03-21T15:16:42.373" Title="Using OpenBabel's gen3d in a Python notebook" Tags="|computational-chemistry|python|smiles|openbabel|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10601" PostTypeId="2" ParentId="10600" CreationDate="2023-03-19T22:42:58.243" Score="7" Body="&lt;p&gt;From the openbabel &lt;a href=&quot;https://openbabel.org/docs/dev/Command-line_tools/babel.html#generating-conformers-for-structures&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; :&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Open Babel will not generate coordinates unless asked, so while a&#xA;conversion from SMILES to SDF will generate a valid SDF file, the&#xA;resulting file will not contain coordinates. To generate coordinates,&#xA;use either the --gen3d or the --gen2d option.&lt;/p&gt;&#xA;&lt;p&gt;The command line option --conformer allows performing conformer&#xA;searches using a range of different algorithms and options.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To generate 3D coordinates and conformer searching you can do the following:&lt;/p&gt;&#xA;&lt;p&gt;In a text editor add the SMILES, one per line, and save the file with .smi extension.&lt;/p&gt;&#xA;&lt;p&gt;For example add the following in a .smi file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CC&#xA;CCN&#xA;CO&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After that you can use the &lt;code&gt;--gen3d&lt;/code&gt; and &lt;code&gt;--conformer&lt;/code&gt; as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel infile.smi -O outfile.sdf --gen3d --conformer --nconf 20 --weighted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;nconf is the number of conformers.&lt;/p&gt;&#xA;&lt;p&gt;The output file will look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OpenBabel03192322333D&#xA;&#xA;  8  7  0  0  0  0  0  0  0  0999 V2000&#xA;    0.9292   -0.0246   -0.0664 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.4251   -1.1907    0.7537 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5744    0.9217    0.3526 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5744   -0.0990   -1.0987 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.0230   -0.0076   -0.0784 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.7799   -1.1164    1.7859 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -0.6687   -1.2078    0.7657 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.7799   -2.1371    0.3346 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;  1  2  1  0  0  0  0&#xA;  1  3  1  0  0  0  0&#xA;  1  4  1  0  0  0  0&#xA;  1  5  1  0  0  0  0&#xA;  2  6  1  0  0  0  0&#xA;  2  7  1  0  0  0  0&#xA;  2  8  1  0  0  0  0&#xA;M  END&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;&#xA; OpenBabel03192322333D&#xA;&#xA; 10  9  0  0  0  0  0  0  0  0999 V2000&#xA;    1.0339    0.0918    0.0081 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5341    0.6110   -1.3285 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.0092   -0.2403   -2.4112 N   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6799   -0.9278    0.1942 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6696    0.7287    0.8207 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.1284    0.0873    0.0482 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -0.5606    0.6263   -1.3329 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.8849    1.6362   -1.4846 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.7017    0.1435   -3.3037 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.0281   -0.2323   -2.4323 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;  1  2  1  0  0  0  0&#xA;  1  4  1  0  0  0  0&#xA;  1  5  1  0  0  0  0&#xA;  1  6  1  0  0  0  0&#xA;  2  3  1  0  0  0  0&#xA;  2  7  1  0  0  0  0&#xA;  2  8  1  0  0  0  0&#xA;  3  9  1  0  0  0  0&#xA;  3 10  1  0  0  0  0&#xA;M  END&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;&#xA; OpenBabel03192322333D&#xA;&#xA;  6  5  0  0  0  0  0  0  0  0999 V2000&#xA;    1.0511    0.0027    0.0995 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5766    0.8295    1.1462 O   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6845    0.3908   -0.8536 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6815   -1.0157    0.2421 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.1439    0.0081    0.0964 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.9177    0.4607    1.9788 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;  1  2  1  0  0  0  0&#xA;  1  3  1  0  0  0  0&#xA;  1  4  1  0  0  0  0&#xA;  1  5  1  0  0  0  0&#xA;  2  6  1  0  0  0  0&#xA;M  END&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-03-20T09:02:20.720" LastActivityDate="2023-03-20T09:02:20.720" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10602" PostTypeId="1" CreationDate="2023-03-20T11:36:18.527" Score="5" ViewCount="879" Body="&lt;p&gt;I used PBE0 in my calculations using Quantum ESPRESSO . I have ran a scf calculation then I used Boltztrap by running the command &lt;code&gt;btp2 -vv interpolate -m 3 ./&lt;/code&gt; then &lt;code&gt;btp2 -vv integrate interpolation.bt2 300:1001:100&lt;/code&gt; .&lt;/p&gt;&#xA;&lt;p&gt;I got the graph bellow, that I'm not able to modify. How can I extract the data and plot them using origin, please?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oEhcP.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oEhcP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-03-21T20:11:47.763" Title="Extracting band structure data using Boltztrap for Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|band-structure|bandgap|boltztrap|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10603" PostTypeId="1" CreationDate="2023-03-20T13:25:45.210" Score="4" ViewCount="127" Body="&lt;p&gt;I want to calculate the absorption spectra of molecules (and possibly ions) with TD-DFT.&lt;/p&gt;&#xA;&lt;p&gt;I have used Gaussian in the past and, to my knowledge, the application of TD-DFT is implemented in this code. However, when looking at descriptions, particularly the results in GaussView, the spectra are reported as UV/Vis. Why is this? Shouldn't it be possible in principle to study a larger range of spectra?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-03-20T13:25:45.210" Title="Absorption spectra with Gaussian" Tags="|gaussian|td-dft|optical-properties|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-22T20:12:09.773" ContentLicense="CC BY-SA 4.0" />
  <row Id="10604" PostTypeId="2" ParentId="10600" CreationDate="2023-03-20T16:41:50.630" Score="3" Body="&lt;p&gt;Here is a simple python recipe in addition to the CLI approach mentioned in the other answer, for more details see the &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/3DStructureGen/Overview.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;docs&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from openbabel import pybel as pb # pybel is syntax sugar for openbabel&#xA;&#xA;smiles = '[O-]C(=O)[C@H]([NH3+])Cc1ccc(O)cc1' # your smiles&#xA;mol = pb.readstring('smiles', smiles) # first argument is a string format&#xA;&#xA;mol.addh() # add Hs for 3D&#xA;mol.make3D() # generate 3D coordinates&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, my experience shows that open babel is not very reliable for 3D generation. I recommend looking through the &lt;a href=&quot;https://www.rdkit.org/docs/GettingStartedInPython.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;RDKit&lt;/a&gt; library, which is in my opinion more powerful and handy tool if you need to work with molecules:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit import Chem # main tools&#xA;from rdkit.Chem import AllChem # additional tools, including 3D&#xA;&#xA;smiles = '[O-]C(=O)[C@H]([NH3+])Cc1ccc(O)cc1' # your smiles&#xA;mol = Chem.MolFromSmiles(smiles) # initialize molecule&#xA;&#xA;mol = Chem.AddHs(mol) # adding explicit Hs for 3D generation&#xA;cid = AllChem.EmbedMolecule(mol) # returns the id of the generated conformer,&#xA;                                 # and -1 if no conformers were generated&#xA;&#xA;AllChem.MMFFOptimizeMolecule(mol) # optimize molecule with MMFF94&#xA;Chem.MolToMolFile(mol, 'some_amino_acid.mol') # save to MOL-file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For multiple conformers use &lt;code&gt;AllChem.EmbedMultipleConformers&lt;/code&gt; and &lt;code&gt;AllChem.MMFFOptimizeMoleculeConfs&lt;/code&gt;, for more details see the docs, they are written really nicely in contrast to OpenBabel.&lt;/p&gt;&#xA;" OwnerUserId="6875" LastActivityDate="2023-03-20T16:41:50.630" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10605" PostTypeId="2" ParentId="10602" CreationDate="2023-03-20T17:01:18.537" Score="5" Body="&lt;p&gt;I don't see a way to do this from the command-line, but as BoltzTraP2 is written in Python, you can add it in. This worked for me:&lt;/p&gt;&#xA;&lt;p&gt;Edit &amp;quot;interface.py&amp;quot; and go to the &amp;quot;parse_plotbands&amp;quot; routine. First, we open a file to put our data in, I called it &amp;quot;btp2_plotbands.dat&amp;quot; and put it in the variable &lt;code&gt;output_file&lt;/code&gt;, just after it creates the figure &lt;code&gt;plt.figure&lt;/code&gt;. I also put some meta-data in there, so I have a chance of remembering what the data was in the file, and then some headings for the subsequent output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    plt.figure()&#xA;    ax = plt.gca()&#xA;    ticks = []&#xA;    dividers = []&#xA;    offset = 0.&#xA;&#xA;    #####################################################################&#xA;    # Output to file; blame Phil Hasnip&#xA;    #####################################################################&#xA;&#xA;    output_file=open(&amp;quot;btp2_plotbands.dat&amp;quot;, &amp;quot;w&amp;quot;)&#xA;    print(&amp;quot;# Output data from btp2 plotbands subcommand&amp;quot;,file=output_file)&#xA;    print(&amp;quot;#&amp;quot;,file=output_file)&#xA;    print(&amp;quot;# &amp;quot;,data.fermi,&amp;quot; &amp;lt;-- Fermi energy from DFT (Ha)&amp;quot;,file=output_file)    &#xA;    print(&amp;quot;#&amp;quot;,file=output_file)&#xA;    print(&amp;quot;# Plot abscissa     energy          kpoint coords &amp;quot;,file=output_file)&#xA;    print(&amp;quot;#                                  kx    ky    kz&amp;quot;,file=output_file)&#xA;    #####################################################################&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A little later on in that routine, you'll see the code which interpolates the bands onto the fine Fourier-style mesh, and puts the eigenvalues into the &lt;code&gt;egrid&lt;/code&gt; variable, before plotting it in the figure; I added file output immediately after this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        # Create the plot&#xA;        nbands = egrid.shape[0]&#xA;        for i in range(nbands):&#xA;            plt.plot(dkp, egrid[i, :], lw=2.)&#xA;        ticks += dcl.tolist()&#xA;        dividers += [dcl[0], dcl[-1]]&#xA;        offset = dkp[-1]&#xA;&#xA;        #####################################################################&#xA;        # Write out the interpolated energy eigenvalues; blame Phil Hasnip&#xA;        #####################################################################&#xA;        for j in range(len(dkp)):&#xA;            print(dkp[j],kp[j][0],kp[j][1],kp[j][2],end=&amp;quot; &amp;quot;,file=output_file)&#xA;            for i in range(nbands):&#xA;                print(egrid[i,j],end=&amp;quot; &amp;quot;,file=output_file)&#xA;            print(&amp;quot; &amp;quot;,file=output_file)&#xA;&#xA;    # Now close the file&#xA;    output_file.close()&#xA;&#xA;        #####################################################################&#xA;&#xA;    ax.set_xticks(ticks)&#xA;    ax.set_xticklabels([])&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now when you run &lt;code&gt;btp2&lt;/code&gt; with the &amp;quot;plotbands&amp;quot; subcommand, it should print the interpolated band-structure data to the file &amp;quot;btp2_plotbands.dat&amp;quot;, as well as plotting it.&lt;/p&gt;&#xA;&lt;h4&gt;Example&lt;/h4&gt;&#xA;&lt;p&gt;Suppose you have output from your favourite supported electronic structure package in the current directory. First you use BoltzTraP2 to interpolate the eigenvalues from your electronic structure code onto a finer k-point grid, for example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;btp2 -vv interpolate -m 5 . &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &amp;quot;-vv&amp;quot; instructs &lt;code&gt;btp2&lt;/code&gt; to tell you what it's doing, &amp;quot;-m 5&amp;quot; tells it the fineness of the interpolated grid you want, and &amp;quot;.&amp;quot; means you want it to look for your electronic structure data in the current directory. The interpolated data will be put in the file &amp;quot;interpolation.bt2&amp;quot; (NB BoltzTraP2 doesn't handle multiple electronic structure calculations in the same directory).&lt;/p&gt;&#xA;&lt;p&gt;Now you want to take that interpolated data, determine the band-structure for some k-point path in the Brillouin zone, and plot it. For example,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; btp2 plotbands interpolation.bt2 [&amp;quot;[0.0, 0.0, 0.0], [0.5, 0.0, 0.0], [0.5, 0.5, 0.0]&amp;quot;]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, we're directly asking BoltzTraP2 to plot the bands (the &amp;quot;plotbands&amp;quot; subcommand) using the interpolated data in &amp;quot;interpolation.bt2&amp;quot;, which is just generated in the previous step, and to use the k-point path in the list (in fractional reciprocal-space coordinates). Note that the k-points we give in the list are the turning points of the path, BoltzTraP2 will automatically generate a fairly fine sampling along each path segment.&lt;/p&gt;&#xA;&lt;p&gt;This will generate a plot using matplotlib, as usual, but our changes to the code will mean that it &lt;em&gt;also&lt;/em&gt; writes the data to a file called &amp;quot;btp2_plotbands.dat&amp;quot;, in the current working directory.&lt;/p&gt;&#xA;&lt;p&gt;For more information on BoltzTraP2 itself, see the BoltzTraP2 documentation and tutorials, e.g. &lt;a href=&quot;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/tutorial&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/sousaw/BoltzTraP2/-/wikis/tutorial&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2023-03-21T20:11:47.763" LastActivityDate="2023-03-21T20:11:47.763" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10606" PostTypeId="2" ParentId="9541" CreationDate="2023-03-21T12:02:42.663" Score="4" Body="&lt;h1&gt;Potential&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lennard-Jones potential&lt;/a&gt; has a simple form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ V_{\rm LJ} (r) = 4\epsilon \left[ \left( \frac \sigma r \right)^{12} - \left( \frac \sigma r \right)^{6} \right]. $$&lt;/span&gt;&#xA;In python, this could be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def V_LJ(r, epsilon, sigma):&#xA;    '''Computes the Lennard-Jones potential'''&#xA;    return 4.0*epsilon*((sigma/r)**12 - (sigma/r)**6)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Application&lt;/h1&gt;&#xA;&lt;p&gt;To apply this potential, you just need to calculate&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ f = \sum_{i&amp;lt;j} V_{\rm LJ}(R_{ij}) $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R_{ij}$&lt;/span&gt; is the distance between atoms &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;. Assume that your coordinates are in a numpy array&#xA;&lt;code&gt;coords = numpy.zeros((3,Natoms))&lt;/code&gt;. Then, you can compute &lt;span class=&quot;math-container&quot;&gt;$R_{ij}$&lt;/span&gt; as &lt;code&gt;Rij = numpy.linalg.norm(coords[i]-coords[j])&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Evaluation of the full potential energy would then be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def LJ_potential(atoms):&#xA; '''Computes Lennard-Jones potential for atoms'''&#xA;Natoms = atoms.shape[1]&#xA;f = 0.0&#xA;for i in range(Natoms):&#xA;    for j in range(i):&#xA;        Rij = numpy.linalg.norm(coords[i]-coords[j])&#xA;        f += V_LJ(Rij, epsilon, sigma)&#xA;return f&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Gradient methods&lt;/h1&gt;&#xA;&lt;p&gt;Note that the function also has a simple gradient&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac {dV_{\rm LJ}} {dr} (r) = \frac {4\epsilon} {\sigma} \left[ -12  \left( \frac \sigma r \right)^{13} + 6 \left( \frac \sigma r \right)^{7} \right], $$&lt;/span&gt;&#xA;so you can also use gradient descent methods for optimization, or molecular dynamics methods.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-03-21T12:02:42.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10607" PostTypeId="2" ParentId="10600" CreationDate="2023-03-21T15:16:42.373" Score="4" Body="&lt;p&gt;The command-line &lt;code&gt;--gen3d&lt;/code&gt; option can do a variety of things, including coordinate generation, some force field cleanup, and a quick conformer search.&lt;/p&gt;&#xA;&lt;p&gt;As mentioned in another answer, Pybel has &lt;code&gt;make3D()&lt;/code&gt; which generates coordinates followed by a quick cleanup using MMFF94 or UFF (if MMFF94 doesn't work).&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the other answer suggests (correctly) to perform a conformer search, but not how to do that in Python...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from openbabel import pybel as pb # pybel is syntax sugar for openbabel&#xA;from openbabel import openbabel as ob&#xA;&#xA;smiles = '[O-]C(=O)[C@H]([NH3+])Cc1ccc(O)cc1' # your smiles&#xA;mol = pb.readstring('smiles', smiles) # first argument is a string format&#xA;&#xA;mol.make3D() # generate 3D coordinates - handles adding H atoms&#xA;# also handles a quick forcefield cleanup&#xA;&#xA;# now perform conformer searching&#xA;ff = pb._forcefields[&amp;quot;mmff94&amp;quot;]&#xA;success = ff.Setup(mol.OBMol)&#xA;if not success:&#xA;    ff = pb._forcefields[&amp;quot;uff&amp;quot;]&#xA;    success = ff.Setup(mol.OBMol)&#xA;    if not success:&#xA;        sys.exit(&amp;quot;Cannot set up forcefield&amp;quot;)&#xA;&#xA;# feel free to tweak these to your balance of time / quality&#xA;ff.ConjugateGradients(100, 1.0e-3)&#xA;ff.FastRotorSearch(true) # permute central bonds&#xA;ff.WeightedRotorSearch(100, 25) # 100 cycles, each with 25 forcefield ops&#xA;# final optimization&#xA;ff.ConjugateGradients(250, 1.0e-4)&#xA;# update the coordinates&#xA;ff.GetCoordinates(mol.OBMol)&#xA;&#xA;# or pick your favorite format or filename&#xA;mol.write(&amp;quot;sdf&amp;quot;, &amp;quot;optimized.sdf&amp;quot;, overwrite=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-03-21T15:16:42.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10608" PostTypeId="2" ParentId="9141" CreationDate="2023-03-21T18:14:23.443" Score="1" Body="&lt;p&gt;The OP has said in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9141/coulomb-energy-in-vasp?noredirect=1#comment22703_9141&quot;&gt;this comment&lt;/a&gt; that the problem is no longer a concern, this Community Wiki answer serves to remove the question out of the unanswered queue, but without closing it in case someone wants to write a better answer. If you do write a better answer, you can leave a comment on this one and I will delete this one :)&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-03-21T18:14:23.443" CommentCount="0" CommunityOwnedDate="2023-03-21T18:14:23.443" ContentLicense="CC BY-SA 4.0" />
  <row Id="10609" PostTypeId="1" CreationDate="2023-03-21T19:53:18.653" Score="3" ViewCount="122" Body="&lt;p&gt;I am performing a simulation in LAMMPS with granules (DEM) and I had a question regarding the conservation of energy. If an interaction happens where one granule is in the simulation box and the other atom is on the other side (i.e it is a ghost atom), will its contribution to the potential energy be approximately halved?&lt;/p&gt;&#xA;&lt;p&gt;I am guessing this because Newton's third law is not used for the ghost atoms? So even though the force is computed, it is only responsible for only half the resulting displacement? I see an overprediction in my total energy when I sum the constituent energies... It becomes greater than the total work done and I was wondering if this might be the cause?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt;&#xA;I am using the default hookean potential &lt;span class=&quot;math-container&quot;&gt;$f=kd$&lt;/span&gt; therefore the potential energy is &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}kd^2$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is a constant and &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; is the overlap. I am assuming there isn't any friction right now. The total potential energy is therefore just summing this energy over all contacts and the kinetic energy is &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{2}mv^2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The total work done is the energy input into the granular system: &lt;span class=&quot;math-container&quot;&gt;$$\int F_{piston}\cdot v_{piston} dt$$&lt;/span&gt; Where the force term is the force exerted on the piston and the velocity is the velocity of the piston. The energy input should equal the summation of the kinetic and potential energies of the system.&lt;/p&gt;&#xA;&lt;p&gt;The reason why I said mentioned Newton's 3rd law is because of&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;if (newton_pair || j &amp;lt; nlocal) {&#xA;          f[j][0] -= fx;&#xA;          f[j][1] -= fy;&#xA;          f[j][2] -= fz;&#xA;          torque[j][0] -= radj*tor1;&#xA;          torque[j][1] -= radj*tor2;&#xA;          torque[j][2] -= radj*tor3;&#xA;        }&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in the source code. If I am interpreting this correctly, ghost atoms won't feel the &lt;code&gt;f[j][:]&lt;/code&gt; force as they have j index greater than &lt;code&gt;nlocal&lt;/code&gt;. I am running a serial simulation btw.&lt;/p&gt;&#xA;&lt;p&gt;Although there exists a closed-form solution for the energy of a contact, if one looks at the incremental work done at a contact, it is given by the expression in (Asmar et al 2001 (Energy monitoring in distinct element models of particle&#xA;systems):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x2GTj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x2GTj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If this is the case, shouldn't the j term be excluded in the above equation if one of the atoms is a ghost?&lt;/p&gt;&#xA;" OwnerUserId="6911" LastEditorUserId="7" LastEditDate="2023-03-22T13:03:56.673" LastActivityDate="2023-03-22T13:03:56.673" Title="Energy balance in a molecular dynamics simulation with ghost atoms and periodic boundary conditions?" Tags="|molecular-dynamics|lammps|intermolecular-forces|energy|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10610" PostTypeId="1" CreationDate="2023-03-21T22:03:18.387" Score="5" ViewCount="308" Body="&lt;p&gt;When I run the command&#xA;&lt;code&gt;mpirun -np 48 mdrun_mpi -deffnm md -v&lt;/code&gt;, the software works with no error, but it only runs as fast as when I'm using 1 CPU (the computer I'm using has 48). Can anyone provide pointers as to why there is no boost in speed?&lt;/p&gt;&#xA;" OwnerUserId="6912" LastEditorUserId="6912" LastEditDate="2023-03-21T22:04:17.757" LastActivityDate="2023-03-21T22:04:17.757" Title="How do I get openMPI to run with gromacs?" Tags="|gromacs|" AnswerCount="0" CommentCount="7" ClosedDate="2023-10-13T16:51:15.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="10611" PostTypeId="2" ParentId="10609" CreationDate="2023-03-22T01:43:22.917" Score="4" Body="&lt;p&gt;Newton's Third Law (N3L) is respected by force pairs in practically all molecular dynamics (MD) simulations, so where packages include a &lt;code&gt;newton&lt;/code&gt; option (as LAMMPS does), it refers to the &lt;em&gt;use&lt;/em&gt; of N3L in computing forces in parallel processes.&lt;/p&gt;&#xA;&lt;p&gt;MD packages often parallelize calculations by assigning sets of atoms to different processes. They then have to decide how to compute forces for some pair &lt;code&gt;ij&lt;/code&gt; where atoms &lt;code&gt;i&lt;/code&gt; and &lt;code&gt;j&lt;/code&gt; are &amp;quot;owned&amp;quot; by different processes (&amp;quot;local to&amp;quot;, in LAMMPS code terminology) -- we'll call them processes &lt;code&gt;i&lt;/code&gt; and &lt;code&gt;j&lt;/code&gt; respectively. Since N3L &lt;em&gt;is obeyed&lt;/em&gt;, the following two choices are equivalent:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;em&gt;Compute&lt;/em&gt; &lt;code&gt;f_ij&lt;/code&gt; on (say) process &lt;code&gt;i&lt;/code&gt; and &lt;em&gt;send&lt;/em&gt; &lt;code&gt;f_ij&lt;/code&gt; to process &lt;code&gt;j&lt;/code&gt;, which can negate it and apply it to particle &lt;code&gt;j&lt;/code&gt;. (LAMMPS's &lt;code&gt;newton on&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;Compute&lt;/em&gt; &lt;code&gt;f_ij&lt;/code&gt; on process &lt;code&gt;i&lt;/code&gt; and &lt;em&gt;compute&lt;/em&gt; &lt;code&gt;f_ji&lt;/code&gt; on process &lt;code&gt;j&lt;/code&gt;. (LAMMPS's &lt;code&gt;newton off&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The difference is that one &lt;em&gt;send&lt;/em&gt; in choice 1 is replaced by one &lt;em&gt;compute&lt;/em&gt; in choice 2, and thus which one is faster is determined by the exact problem and exact machine one is using.&lt;/p&gt;&#xA;&lt;p&gt;For example, when simulating a small system on just one machine, &lt;em&gt;sending&lt;/em&gt; information between processes is very cheap, so choice 1 is preferable. At the other extreme, some simulations contain millions of atoms spread across hundreds of machines, and all of that &lt;em&gt;sending&lt;/em&gt; is much slower than just &lt;em&gt;computing&lt;/em&gt; all forces locally on processes that need them (choice 2).&lt;/p&gt;&#xA;&lt;p&gt;In either case, the final total force is &lt;em&gt;the same&lt;/em&gt; (up to numerical errors). So when you say:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;If I am interpreting this correctly, ghost atoms won't feel the f[j][:] force as they have j index greater than nlocal. I am running a serial simulation btw.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;that's not correct. Later on in the LAMMPS code (including possibly outside the particular &lt;code&gt;pair&lt;/code&gt; class) there's a &amp;quot;reverse communication&amp;quot; which sends those forces back from the ghost to the local atom.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-03-22T01:43:22.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10612" PostTypeId="1" AcceptedAnswerId="10613" CreationDate="2023-03-22T08:11:02.413" Score="5" ViewCount="134" Body="&lt;p&gt;The freely jointed chain model without excluded volume has the following gyration radius,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle R_g^2 \rangle=\frac{1}{6}\frac{N+2}{N+1}Na^2&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of bonds and &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; their length. Now that I have added to my simulations a Lennard-Jones potential between non bonded beads (I take &lt;span class=&quot;math-container&quot;&gt;$\sigma=1.5a$&lt;/span&gt;),&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{LJ}=4\epsilon\left(\left(\frac{\sigma}{r}\right)^{12}-\left(\frac{\sigma}{r}\right)^{6}\right) \ \text{for} \ r&amp;lt;2^{1/6}\sigma&#xA;$$&lt;/span&gt;&#xA;I wanted to check the gyration radius I get. I don't hope to find an analytical formula like the previous one but some approximation which works good for low &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Searching on the internet I found this &lt;a href=&quot;https://www.semanticscholar.org/paper/Renormalization%E2%80%90group-scaling-theory-for-flexible-Chen-Noolandi/c709592d6c4737f600ff8457d3e783682a272cfa&quot; rel=&quot;noreferrer&quot;&gt;article&lt;/a&gt;, which proposes the following equations for the gyration radius,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle R_g^2 \rangle=\frac{1}{6}Na^2\alpha^2(\bar{u},z)&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha^{5.643}(\bar{u},z)-(1-\bar{u})\alpha^{0.395}(\bar{u},z)=2.9713z&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\bar{u}=(1/0.1777)(3/(2\pi))^{3/2}w/a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z=(3/(2\pi))^{3/2}w\sqrt{N}/a$&lt;/span&gt;. I'm not entirely sure how this equations are derived as they use renormalization group theory which I'm not familiar with and I don't know either what is the value of &lt;span class=&quot;math-container&quot;&gt;$w$&lt;/span&gt; in my case (is it related to &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;?). However I believe they are considering a continuum model and in fact for &lt;span class=&quot;math-container&quot;&gt;$N=1$&lt;/span&gt; where there are only two beads and therefore excluded volume doesn't modify anything it gives (if I have solved it correctly) a different prediction for &lt;span class=&quot;math-container&quot;&gt;$\langle R_g^2 \rangle$&lt;/span&gt; than the first formula.&lt;/p&gt;&#xA;" OwnerUserId="6652" LastActivityDate="2023-03-22T10:48:59.303" Title="gyration radius of short freely jointed chain with excluded volume" Tags="|molecular-dynamics|statistical-thermodynamics|polymers|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10613" PostTypeId="2" ParentId="10612" CreationDate="2023-03-22T10:31:27.757" Score="5" Body="&lt;p&gt;When your joints aren't free&lt;br /&gt;&#xA;What's the next thing you see?&lt;br /&gt;&#xA;It's an angle&lt;/p&gt;&#xA;&lt;p&gt;With joints correlated&lt;br /&gt;&#xA;Your chain's &lt;a href=&quot;http://polymerdatabase.com/polymer%20physics/Freely-Rotating%20Chain.html&quot; rel=&quot;noreferrer&quot;&gt;free-rotated &lt;/a&gt;&lt;br /&gt;&#xA;With an angle&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\overline{\cos \theta}$&lt;/span&gt; was once null&lt;br /&gt;&#xA;But now the LJ hull&lt;br /&gt;&#xA;Gives an angle&lt;/p&gt;&#xA;&lt;p&gt;If your chain's short at all&lt;br /&gt;&#xA;Long-range terms become small&lt;br /&gt;&#xA;Says the angle&lt;/p&gt;&#xA;&lt;p&gt;Integrate&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \int_0^\pi \cos \theta \exp(-\beta U[\theta]) \mathrm{d} \theta \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;to get &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \langle R^2 \rangle = n l^2 \left(\frac{1 + \alpha}{1 - \alpha} - \frac{2(1-\alpha^n)}{n(1-\alpha)^2} \right) \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;is what you're after!&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;(Here &lt;span class=&quot;math-container&quot;&gt;$U[\theta]$&lt;/span&gt; is the LJ energy imparted across the angle between two links by the bead-bead interaction:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ U[\theta] = U_{LJ} (r (\theta)), r^2(\theta) = 2l^2(1+ \cos \theta) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; is the bond length and &lt;span class=&quot;math-container&quot;&gt;$\beta = 1/(k_B T)$&lt;/span&gt; is the Boltzmann factor. The integral (1) thus gives the Boltzmann-weighted average of &lt;span class=&quot;math-container&quot;&gt;$\cos \theta$&lt;/span&gt; over the LJ interaction, where &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; is the angle-from-parallel as conventionally used in polymer physics -- that is, &lt;span class=&quot;math-container&quot;&gt;$\theta = 0$&lt;/span&gt; when successive links are parallel and fully extended, and &lt;span class=&quot;math-container&quot;&gt;$\theta = \pi$&lt;/span&gt; when successive links are anti-parallel. This average will now be positive because successive links can no longer &amp;quot;double back&amp;quot; on themselves, where the equivalent quantity for the free-&lt;em&gt;jointed&lt;/em&gt; chain is zero.)&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-03-22T10:48:59.303" LastActivityDate="2023-03-22T10:48:59.303" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10614" PostTypeId="1" AcceptedAnswerId="10617" CreationDate="2023-03-22T14:36:17.617" Score="4" ViewCount="646" Body="&lt;p&gt;In &lt;a href=&quot;https://www.mail-archive.com/users@lists.quantum-espresso.org/msg33817.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;a post&lt;/a&gt; from the Quantum Espresso mailing list, a user suggests adding k-points with weight zero to an SCF calculation as a workaround to allow bandstructure to be computed using a hybrid functional.&lt;/p&gt;&#xA;&lt;p&gt;I'm not super familiar with how to interpret k-point weights. What does it mean to add k-points with weight zero?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="7" LastEditDate="2023-03-23T16:55:07.603" LastActivityDate="2023-03-23T16:55:07.603" Title="What's the meaning of k-points with weight zero?" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|k-points|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10615" PostTypeId="2" ParentId="10614" CreationDate="2023-03-22T15:02:14.093" Score="5" Body="&lt;p&gt;Each k-point contributes with a different 'weight' to your calculation.&lt;/p&gt;&#xA;&lt;p&gt;Say you have a calculation featuring an N number of k-points, each Ni k-point will contribute differently rather than with a 1/N. This is due to the symmetry of your crystal (or model, generally speaking).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.researchgate.net/post/Anyone_have_experience_with_K-point_sampling_for_electronic_and_phonon_structure_calculations&quot; rel=&quot;noreferrer&quot;&gt;This&lt;/a&gt; could help you!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-03-22T15:02:14.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10616" PostTypeId="1" CreationDate="2023-03-22T23:10:20.010" Score="2" ViewCount="102" Body="&lt;p&gt;What is the best way to learn DFT (Density Functional Theory) for beginners?&#xA;I want to learn DFT (both simulation and theory). I am a beginners in this field. What is the best way to learn it?&lt;/p&gt;&#xA;" OwnerUserId="6918" LastActivityDate="2023-03-23T17:22:21.447" Title="DFT calculations" Tags="|density-functional-theory|vasp|quantum-espresso|gromacs|" AnswerCount="0" CommentCount="2" ClosedDate="2023-03-22T23:50:03.557" ContentLicense="CC BY-SA 4.0" />
  <row Id="10617" PostTypeId="2" ParentId="10614" CreationDate="2023-03-23T00:20:54.213" Score="3" Body="&lt;p&gt;According to the &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm1514&quot; rel=&quot;nofollow noreferrer&quot;&gt;pw.x input description&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In a non-scf calculation, weights do not affect the results.&#xA;If you just need eigenvalues and eigenvectors (for instance,&#xA;for a band-structure plot), weights can be set to any value&#xA;(for instance all equal to 1).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So, in your &lt;code&gt;K_POINTS&lt;/code&gt; card, the card option should be set as &lt;code&gt;tpiba_b&lt;/code&gt; or &lt;code&gt;crystal_b&lt;/code&gt; (for band structure plot). So, you can set the card as follows (just an example):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K_POINTS {crystal_b}&#xA;5&#xA;    L       0&#xA;    gG      0&#xA;    X       0&#xA;    U       0&#xA;    gG      0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I cannot help you with how this works, or why we need this for hybrid functional, but if you are looking for how to set the weight to zero, this should work. An alternative version of the above card is given below where each of the k-point is written explicitly:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K_POINTS {crystal_b}&#xA;5&#xA;  0.0000 0.5000 0.0000 0 &#xA;  0.0000 0.0000 0.0000 0 &#xA;  -0.500 0.0000 -0.500 0&#xA;  -0.375 0.2500 -0.375 0 &#xA;  0.0000 0.0000 0.0000 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-23T00:20:54.213" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10618" PostTypeId="1" AcceptedAnswerId="10619" CreationDate="2023-03-23T13:09:29.160" Score="3" ViewCount="826" Body="&lt;p&gt;I got the error when running Vasp Calculation: Error EDDDAV: Call to ZHEGV failed. Returncode = 11 1 1. Can any one help me solve this problem?&lt;/p&gt;&#xA;" OwnerUserId="6918" LastActivityDate="2023-03-23T13:56:40.280" Title="VASP calculation error" Tags="|density-functional-theory|vasp|quantum-chemistry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10619" PostTypeId="2" ParentId="10618" CreationDate="2023-03-23T13:56:40.280" Score="2" Body="&lt;p&gt;This should be a diagonalization routine error. You can try to change IALGO parameter (48 or 38).&lt;/p&gt;&#xA;&lt;p&gt;I would recommend you also try to run your calculation on a different number of processors and/or switch LSCALAPACK to FALSE in your INCAR file.&lt;/p&gt;&#xA;&lt;p&gt;If the error persists, you can try to switch the LPLANE flag to FALSE (if not done already).&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-03-23T13:56:40.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10620" PostTypeId="1" CreationDate="2023-03-23T14:14:44.563" Score="2" ViewCount="107" Body="&lt;p&gt;Normally when we use PBE-GGA as an approximation we can determine the high symmetry points in x coordinate  from the output file of &lt;code&gt;bands.x&lt;/code&gt; calculation . But in the case of PBEO we can't run a &lt;code&gt;bands.x&lt;/code&gt; calculation.&lt;/p&gt;&#xA;&lt;p&gt;How can I determine the high symmetry points in this case, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-03-23T14:14:44.563" Title="How to determine high-symmetry points in case of PBE0 using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|band-structure|symmetry|bandgap|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-12T14:19:25.213" ContentLicense="CC BY-SA 4.0" />
  <row Id="10621" PostTypeId="2" ParentId="1678" CreationDate="2023-03-24T11:04:57.873" Score="4" Body="&lt;p&gt;The problem of defining the parameters comes fundamentally from using the Ising model. The Ising model is extremely simplistic, and is the most basic model of a phase transition. Magnetic materials are generally much better modelled using a 3D Heisenberg spin model (where spins can point in any direction), but the lattice of spins can be 1D,2D or 3D. The advantages over the Ising model are that spin waves are allowed, the Curie temperature is much more accurate when using DFT calculated parameters, and Ms(T) is not overly flat for low temperatures (this requires quantum corrections but not as brutal as spin-up and spin-down in the Ising model). In this case S is a unit vector (representing the &lt;em&gt;local&lt;/em&gt; quantisation axis of the spin) and factored into the J coefficients automatically (this is one of the problems with defining J with S as different lengths since different moments give different coupling but this is not necessarily directly proportional to |S||\sigma|). One can approximate the J coefficients by comparing with experimental data, but in general you need an electronic structure calculation (such as DFT or sKKR) to determine nearest and next nearest exchange constants.&lt;/p&gt;&#xA;" OwnerUserId="6925" LastActivityDate="2023-03-24T11:04:57.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10622" PostTypeId="1" CreationDate="2023-03-24T09:03:56.163" Score="4" ViewCount="75" Body="&lt;p&gt;I want to implement in my program Chemcraft the computation of entropy and Gibbs energy of molecules in approximation &amp;quot;rigid rotor - harmonic oscillator&amp;quot;, by the molecular parameters (molecular geometry, vibrational frequencies) computed by QC packages like Gaussian (the main goal is cutting/increasing low frequencies for better results). Some peole suggested &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt; to the program ASE.&lt;/p&gt;&#xA;&lt;p&gt;Here it is written, that the formulas from the following book were used: C.J. Cramer. Essentials of Computational Chemistry, Second Edition. Wiley, 2004. In this book I found the following formulas:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TKVd6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TKVd6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This formula does not contain heat capacities C. At the ASE website the following formula is provided:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AhgE9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AhgE9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I don't understand, why here is provided not the heat capacity, but its integral. I don't remember what I had studied at the courses of physical chemistry.&#xA;The program Gaussian computes thermodinamical functions and prints them as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                       E (Thermal)             CV                S&#xA;                        KCal/Mol        Cal/Mol-Kelvin    Cal/Mol-  Kelvin&#xA; Total                   98.006             46.365            123.966&#xA; Electronic               0.000              0.000              0.000&#xA; Translational            0.889              2.981             41.193&#xA; Rotational               0.889              2.981             31.040&#xA; Vibrational             96.228             40.403             51.733&#xA; Vibration     1          0.593              1.986              7.306&#xA; Vibration     2          0.593              1.984              5.881&#xA; Vibration     3          0.594              1.981              5.310&#xA; Vibration     4          0.596              1.975              4.563&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is not fully clear for me, the term &amp;quot;CV&amp;quot; means Cv or C*V? Sorry for stupid question.&lt;/p&gt;&#xA;&lt;p&gt;Currently my program computes entropy correctly (the results are equal to the values provided by Gaussian and most other programs), and Cv(trans) and Cv(rot) too, but the value Cv(vib) or its integral do not match the Gaussian output. Can you suggest, what means the Cv(vibrational) in the Gaussian output (the heat capacity or maybe its integral), and how it should be computed?&lt;/p&gt;&#xA;&lt;p&gt;One more question relates to the algorithm of computation of vibrational entropy by frequencies. I found full match of the S values produced by my program and several other packages (Gaussian, Priroda, Psi, QChem, Spartan), but there is some diffence (10-30%) with the S values produced by Orca package. I have heard that Orca uses QRRHO approximation of Grimme. If so, is it considered better than the standard RRHO approximation?&lt;/p&gt;&#xA;" OwnerUserId="3745" OwnerDisplayName="Linkey" LastEditorUserId="5" LastEditDate="2023-03-25T17:59:40.757" LastActivityDate="2023-03-25T17:59:40.757" Title="Computation of thermodynamic functions of molecules by molecular parameters" Tags="|thermodynamics|quantum-chemistry|entropy|" AnswerCount="0" CommentCount="11" ClosedDate="2023-10-13T16:51:04.997" ContentLicense="CC BY-SA 4.0" />
  <row Id="10623" PostTypeId="1" CreationDate="2023-03-25T11:34:18.500" Score="4" ViewCount="103" Body="&lt;p&gt;I'm trying to calculate the electrostatic (Hartree) potential corresponding to a single (auxiliary) GTO:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_i({\bf r_1}) = \int d{\bf r}_2~ \frac{\phi_i ({\bf r}_2)}{r_{12}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;[Please note that &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; is &lt;strong&gt;not&lt;/strong&gt; squared].&lt;/p&gt;&#xA;&lt;p&gt;I have been using the 'fake_mol' delta function trick to calculate the Hartree potential over two GTOs:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_{ij}({\bf r_1})= \int d{\bf r}_2 \frac{\phi_i({\bf r}_2) \phi_j({\bf r}_2)}{r_{12}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;by using this code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf, dft, lib, ao2mo&#xA;from pyscf import df, lib&#xA;import numpy as np&#xA;mol = gto.M(atom = 'Ne 0.00 0.000 0.00')&#xA;mol.basis = 'def2tzvp'&#xA;mol.cart = True&#xA;mol.build()&#xA;mf = dft.RKS(mol).density_fit()&#xA;mf.run()&#xA;Amol = df.addons.make_auxmol(mol, 'def2tzvpjkfit')&#xA;&#xA;&#xA;coords = mf.grids.coords #coordinates on a grid&#xA;fakemol = gto.fakemol_for_charges(coords);&#xA;v_ij = df.incore.aux_e2(Amol, fakemol);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;v_ij[i, j, p]&lt;/code&gt; represents:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_{ij}(r_1) = \int d{\bf r}_2 \frac{\phi_i({\bf r}_2) \phi_j({\bf r}_2)}{r_{12}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;at &lt;code&gt;r_1 = coords[p]&lt;/code&gt; and thus is of shape &lt;code&gt;(naux, naux, len(coords))&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, I would like to calculate&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_i ({\bf r_1} )= \int d{\bf r}_2 \frac{\phi_i({\bf r}_2)}{r_{12}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;at &lt;code&gt;r_1 = coords[p]&lt;/code&gt;. Since &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; is &lt;strong&gt;not&lt;/strong&gt; squared, this object is not just &lt;code&gt;v_ij[i, i, p]&lt;/code&gt;&#xA;Any ideas on how can I achieve this with PySCF?&lt;/p&gt;&#xA;" OwnerUserId="6928" LastEditorUserId="7" LastEditDate="2023-03-26T01:28:43.817" LastActivityDate="2023-03-26T01:28:43.817" Title="PySCF calcuation of 'one-index' electrostatic (Hartree) potential" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|python|pyscf|" AnswerCount="0" CommentCount="3" ClosedDate="2023-10-13T16:50:55.870" ContentLicense="CC BY-SA 4.0" />
  <row Id="10624" PostTypeId="1" CreationDate="2023-03-26T13:18:56.037" Score="3" ViewCount="114" Body="&lt;p&gt;In NEB calculations, I am getting much higher energy values.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;00    -395.94910849  = 0&#xA;01    37.30329488    = 37.30329488+395.94910849 = 433.25240337&#xA;02    1018.48104960  = 1018.48104960+395.94910849 = 1414.43015809&#xA;03   1001.09925193   = 1001.09925193+395.94910849 = 1397.04836042&#xA;04   37.79655317   = 37.79655317+395.94910849 = 433.74566166&#xA;05  -395.95035434 = -395.95035434+395.94910849 = -0.0012458499999752348&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In literature, I have seen energy values in a few eV. I am not getting what could be the possible reason for getting such high energy values. What next I can do in this case. If anyone is familiar with this type of issue, please suggest.&lt;/p&gt;&#xA;" OwnerUserId="5256" LastEditorUserId="5" LastEditDate="2023-10-15T03:33:48.247" LastActivityDate="2023-10-15T03:33:48.247" Title="NEB calculations in VASP" Tags="|density-functional-theory|vasp|nudged-elastic-band|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10625" PostTypeId="1" CreationDate="2023-03-27T09:41:20.133" Score="3" ViewCount="48" Body="&lt;p&gt;I used PBE0 to get projected density of states using norm-conserving pseudopotentials with Quantum ESPRESSO.  I found very intense picks (scf -&amp;gt; projwfc ) compared to the ones that I found using PBE with PAW pseudopotentials (scf -&amp;gt; nscf -&amp;gt; projwfc) .&lt;/p&gt;&#xA;&lt;p&gt;What can be the causes of this issue please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-03-27T11:45:27.730" LastActivityDate="2023-03-27T11:45:27.730" Title="Why do I get very intense picks when I use PBE0 with NC PP?" Tags="|density-functional-theory|quantum-espresso|band-structure|electronic-structure|density-of-states|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:50:36.917" ContentLicense="CC BY-SA 4.0" />
  <row Id="10626" PostTypeId="1" CreationDate="2023-03-27T12:42:37.437" Score="3" ViewCount="42" Body="&lt;p&gt;I was doing some calculations using LAMMPS and wondered if there was a way to change the cell shape during npt or nvt calculations (in the latter, changing the cell shape while keeping the volume fixed).&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-03-27T13:13:23.877" LastActivityDate="2023-03-27T13:13:23.877" Title="How to change cell shape during calculations in LAMMPS?" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:12:26.467" ContentLicense="CC BY-SA 4.0" />
  <row Id="10627" PostTypeId="1" CreationDate="2023-03-27T13:05:44.853" Score="5" ViewCount="107" Body="&lt;p&gt;I have seen that many MD simulations compute the torques due to dipole-dipole interactions and other interactions. I understand that there is a torque on a dipole in an electric field. I don't understand why this effect is not just captured by the forces? How do I actually incorporate the computed torques into an MD simulation? That is, we are usually integrating Newton's equations of motion, which are related to the forces by acceleration. Torques are related to forces, but in a way where it is not obvious to me how to transform the torques into forces in general.&lt;/p&gt;&#xA;&lt;p&gt;Put another way, normally when implementing a force field, the measure of consistency between energies and forces is whether or not the those forces can be computed as a finite difference derivative of the energy. From my own experience, this criterion is satisfied without the inclusion of torques. Why do we need to evaluate torques then?&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2023-03-30T23:30:38.397" Title="When and why are torques needed in molecular dynamics simulations?" Tags="|molecular-dynamics|forcefields|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10628" PostTypeId="1" AcceptedAnswerId="10630" CreationDate="2023-03-27T13:38:50.080" Score="5" ViewCount="583" Body="&lt;p&gt;The structure of my material is zincblende. So normally the structure is cubic. However, when I open the primitive cell with xcrysden it dosen't look 100% cubic. It's a little bit inclined. Also when I calculated the optical properties of my material with a primitive unit cell the components of the imaginary part along x,y and z axis aren't equal (same for the real part). And normally if the structure is cubic they should be equal. Why they aren't equal?&lt;/p&gt;&#xA;&lt;p&gt;The parameters of the conventional cell are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  nat = 8&#xA;  ntyp = 2&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  1.000000000000000   0.000000000000000   0.000000000000000 &#xA;  0.000000000000000   1.000000000000000   0.000000000000000 &#xA;  0.000000000000000   0.000000000000000   1.000000000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the primitive cell the parameters are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  nat = 2&#xA;  ntyp = 2&#xA;/&#xA;CELL_PARAMETERS {alat}&#xA;  0.500000000000000   0.500000000000000   0.000000000000000 &#xA;  0.500000000000000   0.000000000000000   0.500000000000000 &#xA;  0.000000000000000   0.500000000000000   0.500000000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;a visualization of primitive cell using xcrysden&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jrTgs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jrTgs.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can someone please clarify my doubts about this issue?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-03-28T03:43:15.433" LastActivityDate="2023-03-28T03:43:15.433" Title="Why does my zincblende structure not look cubic?" Tags="|density-functional-theory|quantum-espresso|crystallography|optical-properties|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10629" PostTypeId="1" CreationDate="2023-03-27T13:46:48.147" Score="3" ViewCount="38" Body="&lt;p&gt;I am trying to understand the terminology of reconstructed surfaces.&#xA;Simple surfaces such as 2x2 or 1x1 make sense to me. For instance, figure 1 of the paper &lt;a href=&quot;https://doi.org/10.1063/1.1574798&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.1574798&lt;/a&gt; shows a layer of the 2x2 supercell that is easy to understand.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2toSC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2toSC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, the reconstructed surfaces have names like &lt;span class=&quot;math-container&quot;&gt;$$ \sqrt{31} \times \sqrt{31} $$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$$  \sqrt{3} \times \sqrt{3} $$&lt;/span&gt; at times also followed by R30 (or some other angle), which is hard (for me as a beginner) to understand.&#xA;Could someone explain these or point to some useful resources to learn about them?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2023-03-27T13:46:48.147" Title="How are reconstructed surfaces named?" Tags="|surfaces|terminology|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:12:57.937" ContentLicense="CC BY-SA 4.0" />
  <row Id="10630" PostTypeId="2" ParentId="10628" CreationDate="2023-03-27T15:52:06.600" Score="8" Body="&lt;p&gt;I think the premise of your question is mistaken. The structure you have shown in your question is the primitive cell of Zincblende. It is not cubic. The conventional structure has a face-centered cubic (FCC) structure. But the primitive cell of an FCC structure is rhombohedral, which you got using xcrysden.&lt;/p&gt;&#xA;&lt;p&gt;Rhombohedral crystals are also cubic but the angles are not 90 degrees. That's why you have an inclined plane. If the angle becomes 90 degree, you will have a primitive cubic structure. However, the cubic structure you are looking for is not be found here. That should be the conventional unit cell &lt;a href=&quot;https://en.wikipedia.org/wiki/Supercell_(crystal)#:%7E:text=Another%20very%20important%20example%20of%20a%20supercell%20is%20the%20conventional%20cell%20of%20body%2Dcentered%20(bcc)%20or%20face%2Dcentered%20(fcc)%20cubic%20crystals.&quot; rel=&quot;noreferrer&quot;&gt;which is actually a supercell&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://physics.stackexchange.com/questions/210963/primitive-unit-cell-of-fcc&quot;&gt;this Physics SE&lt;/a&gt; question about the relation between the primitive and conventional unit cell of the FCC structure.&lt;/p&gt;&#xA;&lt;p&gt;Edit: If you want to see the cubic conventional cell structure using XCrySDen, then press &lt;code&gt;F4&lt;/code&gt; key or select &lt;code&gt;conventional cell mode&lt;/code&gt; from the &lt;code&gt;Display&lt;/code&gt; menu.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-03-27T20:45:48.193" LastActivityDate="2023-03-27T20:45:48.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10631" PostTypeId="1" CreationDate="2023-03-27T22:29:05.803" Score="4" ViewCount="53" Body="&lt;p&gt;I am interested to know if it is possible to encode compositional information in SMILES strings or other structural identifiers.&lt;/p&gt;&#xA;&lt;p&gt;For instance, in generating a SMILES string when combining two molecules, C&lt;span class=&quot;math-container&quot;&gt;$_{14}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{10}$&lt;/span&gt; and C&lt;span class=&quot;math-container&quot;&gt;$_{18}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{12}$&lt;/span&gt;, I am wondering if it is possible to specify the composition of the different constituents [e.g. (C&lt;span class=&quot;math-container&quot;&gt;$_{14}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{10}$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_{0.4}$&lt;/span&gt;(C&lt;span class=&quot;math-container&quot;&gt;$_{18}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{12}$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_{0.6}$&lt;/span&gt;]. The goal would be to generate unique SMILES strings for this compound molecule as the composition sweeps from x=: 0 to 1 as (C&lt;span class=&quot;math-container&quot;&gt;$_{14}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{10}$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_{x}$&lt;/span&gt;(C&lt;span class=&quot;math-container&quot;&gt;$_{18}$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_{12}$&lt;/span&gt;)&lt;span class=&quot;math-container&quot;&gt;$_{(1-x)}$&lt;/span&gt;. I am hoping this is a discrete method, such as 5 SMILES strings as x=: 0, 0.2, 0.5, 0.8, 1, etc...&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to generate a &amp;quot;canonical SMILES string&amp;quot; for such compound molecules with varying stoichiometry? I read that even toluene has 7 possible SMILES strings so I could imagine compositional information is not possible to encode in a structural notation.&lt;/p&gt;&#xA;&lt;p&gt;If such a thing does not exist, would it be feasible or make sense to try and create a new type of structural notation for &amp;quot;novel compounds&amp;quot; that do not have entries in chemical databases?&lt;/p&gt;&#xA;&lt;p&gt;Please let me know if structural identifiers is not the right path!&lt;/p&gt;&#xA;" OwnerUserId="6793" LastActivityDate="2023-03-27T22:29:05.803" Title="Compositional SMILES data" Tags="|smiles|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-13T16:50:46.513" ContentLicense="CC BY-SA 4.0" />
  <row Id="10632" PostTypeId="5" CreationDate="2023-03-27T23:43:12.920" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-03-27T23:43:12.920" LastActivityDate="2023-03-27T23:43:12.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10633" PostTypeId="4" CreationDate="2023-03-27T23:43:12.920" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-03-27T23:43:12.920" LastActivityDate="2023-03-27T23:43:12.920" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10634" PostTypeId="1" CreationDate="2023-03-28T07:24:59.513" Score="4" ViewCount="57" Body="&lt;p&gt;I have used DFT to calculate the internal energy of a couple of different phases at 0K. As I would also like to compare the relative stability of the phases at finite temperature, I have also computed the phonon spectrum for each phase using phonopy (&lt;a href=&quot;http://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://phonopy.github.io/phonopy/&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Phonopy also calculates thermal properties related to the phonon spectrum, namely the harmonic phonon energy as well as the partition function Z, and writes out the quantities: Helmholtz free energy F, entropy S, and the constant volume heat capacity Cv. I have seen in the literature comparisons of the relative stability of different phases using the Enthalpy.&lt;/p&gt;&#xA;&lt;p&gt;Is this a fair thing to do so here and what is a good way to do so?&lt;/p&gt;&#xA;&lt;p&gt;I do realize that the enthalpy differential can be written as dH = TdS - P dV. I don't have any data on the volume change with temperature, but if I assume P is small then dH = T dS. Would it be fair to integrate the change in H from 0K to a temperature T by expressing the Enthalpy as &lt;span class=&quot;math-container&quot;&gt;$$U(0K) + \int_{0}^{T} {T dS}$$&lt;/span&gt; or is there a more appropriate way to go about computing the enthalpy (for solids). Note both phases are ordered so the mixing entropy is negligible.&lt;/p&gt;&#xA;" OwnerUserId="6939" LastEditorUserId="24" LastEditDate="2023-03-28T11:54:25.187" LastActivityDate="2023-03-28T11:54:25.187" Title="Comparing stability of phases under constant pressure" Tags="|density-functional-theory|thermodynamics|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:50:24.450" ContentLicense="CC BY-SA 4.0" />
  <row Id="10635" PostTypeId="1" AcceptedAnswerId="10639" CreationDate="2023-03-28T11:11:40.070" Score="5" ViewCount="1435" Body="&lt;p&gt;I'm going to use a more powerful server to run my simulations on it using a remote control software (The server is in another building). It's my first time to try that.&lt;/p&gt;&#xA;&lt;p&gt;What are the things that I should be aware of? Do I have to install the codes that I'm using on that server too? How can I use it, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-03-28T23:11:20.413" LastActivityDate="2023-03-28T23:11:20.413" Title="How can I run my calculations on a remote server?" Tags="|high-performance-computing|" AnswerCount="2" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="10636" PostTypeId="2" ParentId="10635" CreationDate="2023-03-28T17:49:39.237" Score="3" Body="&lt;p&gt;We need more detail to effectively help you to use your remote server well. However, a good starting point is the HPC Carpentry's &amp;quot;HPC Intro&amp;quot; course: &lt;a href=&quot;https://carpentries-incubator.github.io/hpc-intro/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://carpentries-incubator.github.io/hpc-intro/&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You should run through this course on your own, and also send this course to the administrators of your remote server and ask them if (1) the course is a suitable introduction to using this particular server, and if not, (2) what they would like you to do differently to the course.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-03-28T17:49:39.237" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10637" PostTypeId="2" ParentId="10627" CreationDate="2023-03-28T18:33:27.193" Score="4" Body="&lt;p&gt;There is a wide variety of molecular dynamics force fields; many incorporate (per-particle) torques, as you have noted, but many do not. For example, I am not familiar with any atomistic protein force fields which use torques. From my experience, the difference will boil down to the force field fitting methodology: &amp;quot;bottom-up&amp;quot; force fields naturally don't need torques (as you have noted) while &amp;quot;top-down&amp;quot; force fields often do.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Bottom-up&amp;quot; force fields are those which are fitted to &amp;quot;ground truths&amp;quot; of &lt;em&gt;atomistic position or energy data&lt;/em&gt;. In materials science, these are parameterised from density functional theory or other quantum chemistry techniques; in protein science, these are parameterised from experimental structure resolution such as through X-ray crystallography or cryo-electron microscopy. And yes, absolutely, if you are dealing with atoms, atoms typically aren't represented as extended particles or fixed dipoles or anything quite so fancy, so there are no torques to talk about!&lt;/p&gt;&#xA;&lt;p&gt;But &amp;quot;top-down&amp;quot; force fields frequently make good use of torques. For example, consider the &lt;a href=&quot;https://dna.physics.ox.ac.uk/index.php/Model_introduction&quot; rel=&quot;nofollow noreferrer&quot;&gt;oxDNA&lt;/a&gt; model family:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xQz1d.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xQz1d.png&quot; alt=&quot;Depiction of particles in oxDNA coarse-grained model&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;oxDNA is a &amp;quot;top down&amp;quot; model because it is fitted to thermodynamic and kinetic &amp;quot;ground truths&amp;quot;, such as energies and rates of base pair dissociation and polymeric persistence lengths of the targeted double-stranded DNA. This makes sense since oxDNA aims explicitly to capture DNA structure on scales where the exact atomic positions are irrelevant. Thus, a nucleobase can be represented with seven* numbers (three for position and four* for an orientation quaternion) instead of the thirty or so needed for a fully atomistic description, and simulations are correspondingly much cheaper.&lt;/p&gt;&#xA;&lt;p&gt;oxDNA models DNA as sites with FENE bonds, and a key ingredient of its success is representing nucleobase stacking interactions as an energetic alignment between the orientations of neighbouring nucleotide sites (the blue &amp;quot;pancakes&amp;quot; like to &amp;quot;lie flat&amp;quot; near each other). The energy depends on angles and thus the model dynamics naturally include torques (which are the angular derivatives of energy) which go into evolving the site orientations over time.&lt;/p&gt;&#xA;&lt;p&gt;I hope this demonstrates the general principle: when a force field is fitted to an atomistic energy surface or structure, the energy is naturally described purely by atomic Cartesian coordinates and only atomistic forces are needed for dynamics; but when a force field is being fitted to some more general ground truth, there is great freedom for the force field developers to choose appropriate internal representations, and where these representations are primarily angular (such as the orientations of idealized dipoles or extended bodies) then torques naturally arise as the angular derivatives of energy. (Indeed, while bond-angle and dihedral interactions are typically implemented as forces, conceptually they are torques too!)&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;*these could be six and three respectively; I don't remember how the code internally represents quaternions.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-03-28T18:42:39.217" LastActivityDate="2023-03-28T18:42:39.217" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10638" PostTypeId="1" CreationDate="2023-03-28T20:31:30.340" Score="6" ViewCount="350" Body="&lt;p&gt;What is the difference between density functional perturbation theory (DFPT) and many-body perturbation theory (MBPT)? Also, please help me understand why approximations like PBEsol are considered as DFPT, whereas GW approximations as MBPT.&lt;/p&gt;&#xA;" OwnerUserId="5138" LastEditorUserId="6055" LastEditDate="2023-03-30T21:14:52.090" LastActivityDate="2023-03-30T21:14:52.090" Title="Density Functional Perturbation Theory" Tags="|density-functional-theory|quantum-mechanics|gw-bse|many-body-perturbation-theory|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10639" PostTypeId="2" ParentId="10635" CreationDate="2023-03-28T21:27:46.790" Score="10" Body="&lt;p&gt;Almost all HPC servers use &lt;a href=&quot;https://en.wikipedia.org/wiki/Linux&quot; rel=&quot;noreferrer&quot;&gt;Linux&lt;/a&gt;. Therefore, in almost all cases, familiarity with Linux is crucial, especially the &lt;a href=&quot;https://www.hostinger.com/tutorials/linux-commands&quot; rel=&quot;noreferrer&quot;&gt;basic commands&lt;/a&gt; (e.g. &lt;code&gt;ls&lt;/code&gt;, &lt;code&gt;cd&lt;/code&gt;, &lt;code&gt;mkdir&lt;/code&gt;, &lt;code&gt;cp&lt;/code&gt;, &lt;code&gt;rm&lt;/code&gt;, etc.).&lt;/p&gt;&#xA;&lt;h1&gt;Connecting to the server&lt;/h1&gt;&#xA;&lt;p&gt;Connecting to a Linux-based HPC server is now always in my experience done through &lt;a href=&quot;https://en.wikipedia.org/wiki/Secure_Shell&quot; rel=&quot;noreferrer&quot;&gt;SSH&lt;/a&gt; (in the 1990s I used &lt;a href=&quot;https://en.wikipedia.org/wiki/Telnet&quot; rel=&quot;noreferrer&quot;&gt;Telnet&lt;/a&gt; to log into the University of Toronto servers, but I can't recall using anything other than SSH in the mid-2000s or later). To log into an HPC server with SSH, you can run the following command in the default terminal in Linux, MacOS or Windows Subsystem for Linux, or in something like PuTTY in pure Windows (assuming your username is &lt;code&gt;camilla&lt;/code&gt; and the server's name is &lt;code&gt;materials.stackexchange.com&lt;/code&gt;, for a hypothetical example):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ssh camilla@materials.stackexchange.com&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As long as there's no problems, you will next be asked for your password, and upon entering it correctly you will be able to access the server. Usually you will be given a temporary password at the beginning and will be highly encouraged (or forced) to change it immediately. The &lt;a href=&quot;https://www.geeksforgeeks.org/passwd-command-in-linux-with-examples/&quot; rel=&quot;noreferrer&quot;&gt;passwd&lt;/a&gt; command will allow you to do this if you are not already forced to do it upon your first successful login. The &lt;em&gt;&lt;strong&gt;spelling&lt;/strong&gt;&lt;/em&gt; of that command is a bit strange, and it can be hard to remember whether or leave out the letter &amp;quot;a&amp;quot; or the letters &amp;quot;or&amp;quot;, so I spelled it correctly for you in the hyperlinked words in this paragraph.&lt;/p&gt;&#xA;&lt;h1&gt;Transfer of files&lt;/h1&gt;&#xA;&lt;p&gt;It is very likely that you will have input scripts or data files on a computer that you're currently using, and will want those files to be accessible on the HPC server. A very simple way to transfer files to and from an HPC server is using &lt;code&gt;scp&lt;/code&gt; (in the 1990s I used FTP, which stands for &amp;quot;file transfer protocol&amp;quot; but now exclusively use &lt;code&gt;scp&lt;/code&gt; which is just a &amp;quot;secure&amp;quot; analog of the previously mentioned and &lt;em&gt;&lt;strong&gt;very&lt;/strong&gt;&lt;/em&gt; basic &lt;code&gt;cp&lt;/code&gt; command).  The following command is run on your local machine and is for copying files from your local machine to the above hypothetical server (the important part to remember is the &lt;em&gt;&lt;strong&gt;colon&lt;/strong&gt;&lt;/em&gt; symbol &lt;code&gt;:&lt;/code&gt; which is easy to forget because we far more often use &lt;code&gt;cp&lt;/code&gt; without it, than we use &lt;code&gt;scp&lt;/code&gt; with it):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;scp file.txt camilla@materials.stackexchange.com:&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From your local machine you can also copy files from the server to your current directory on your local machine, for example with the following command (the main difference from the above command is the &lt;em&gt;&lt;strong&gt;order&lt;/strong&gt;&lt;/em&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;scp camilla@materials.stackexchange.com:/path/to/file.txt .&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Compiling/installing programs&lt;/h1&gt;&#xA;&lt;p&gt;Most HPC servers do not allow you to have full control of the server, so you are limited in how you can install things. For this reason, and because it's wasteful for 100 users to each install their own copy of a 10GB software, servers often come with most major programs pre-installed. These pre-installed programs are often made available with the &lt;a href=&quot;https://lmod.readthedocs.io/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;lmod&lt;/a&gt; system. The following &lt;code&gt;lmod&lt;/code&gt; commands are the most commonly used ones, and my example below is for Python but could be used for other programs by changing the last word in the each command accordingly:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load python    # load the system's default version of Python&#xA;module unload python  # unload whatever version of Python was loaded&#xA;module spider python  # learn information about the various versions of Python modules that are made available to you&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To see which modules you already have loaded, you can run:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module list&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and to see which ones are available to load via &lt;code&gt;module load&lt;/code&gt;, you can run:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module avail&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When programs are not available via the &lt;code&gt;lmod&lt;/code&gt; system, then your next option might be &lt;code&gt;pip&lt;/code&gt;, but this can be significantly more complicated than using &lt;code&gt;pip&lt;/code&gt; on your local machine, for example Compute Canada which serves almost every Canadian academic researcher has a &amp;quot;wheel house&amp;quot; for Python wheels, which is described &lt;a href=&quot;https://docs.alliancecan.ca/wiki/Available_Python_wheels&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, and &lt;code&gt;pip install&lt;/code&gt; has to actually be run every time you run a job (so it's part of the &amp;quot;job submission script&amp;quot;) as described here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10588/5&quot;&gt;How can I build the wheels necessary for a quick installation of PySCFad on a &amp;quot;compute node&amp;quot;?&lt;/a&gt;. Likewise, compiling software the &amp;quot;traditional way&amp;quot; from &amp;quot;source&amp;quot; can be significantly more complicated than on a local machine as you may have to &amp;quot;load&amp;quot; compilers as modules (among other things), and you can see an example of the sequence of commands for this type of installation here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10211/5&quot;&gt;Is this &amp;quot;internal error&amp;quot; reproducible when compiling OpenMolcas on other Intel compilers?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Running calculations&lt;/h1&gt;&#xA;&lt;p&gt;Explanations of how to use SLURM, LoadLeveler, and SGE are provided in answers here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6497/5&quot;&gt;How can I submit jobs to an HPC scheduler?&lt;/a&gt;. This discussion is also related: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/862/5&quot;&gt;Job scheduler alternatives&lt;/a&gt;. The &lt;a href=&quot;/questions/tagged/job-scheduler&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;job-scheduler&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;job-scheduler&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-job-scheduler-tooltip-container&quot;&gt;job-scheduler&lt;/a&gt; tag here on MMSE is for asking questions about schedulers like the ones mentioned in this paragraph.&lt;/p&gt;&#xA;&lt;h1&gt;Logging out of the server&lt;/h1&gt;&#xA;&lt;p&gt;When you run the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;logout&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the terminal that you have been using all this time will return you to the directory on your &lt;em&gt;local&lt;/em&gt; machine at which you were present at the time of logging into the server.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-03-28T21:27:46.790" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10640" PostTypeId="1" CreationDate="2023-03-29T09:58:46.160" Score="6" ViewCount="433" Body="&lt;p&gt;I have 100 .cif files.&#xA;I want to convert them all to .vesta files through vesta software (&lt;a href=&quot;https://jp-minerals.org/vesta/en/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://jp-minerals.org/vesta/en/download.html&lt;/a&gt;).&#xA;I know I can choose them one by one and convert them.&#xA;Is there any method better than this?&lt;/p&gt;&#xA;&lt;p&gt;Example of .cif file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;data_image0&#xA;_cell_length_a       18.685&#xA;_cell_length_b       11.722&#xA;_cell_length_c       9.244&#xA;_cell_angle_alpha    90&#xA;_cell_angle_beta     91.771&#xA;_cell_angle_gamma    90&#xA;&#xA;_symmetry_space_group_name_H-M    &amp;quot;P 1&amp;quot;&#xA;_symmetry_int_tables_number       1&#xA;&#xA;loop_&#xA;  _symmetry_equiv_pos_as_xyz&#xA;  'x, y, z'&#xA;&#xA;loop_&#xA;  _atom_site_label&#xA;  _atom_site_occupancy&#xA;  _atom_site_fract_x&#xA;  _atom_site_fract_y&#xA;  _atom_site_fract_z&#xA;  _atom_site_thermal_displace_type&#xA;  _atom_site_B_iso_or_equiv&#xA;  _atom_site_type_symbol&#xA;  Ba1      1.0000 0.47790  0.69163  0.50773  Biso   1.000  Ba&#xA;  O1       1.0000 0.32620  0.78370  0.51070  Biso   1.000  O&#xA;  O2       1.0000 0.57370  0.66390  0.28140  Biso   1.000  O&#xA;  C1       1.0000 0.63400  0.67060  0.34230  Biso   1.000  C&#xA;  C2       1.0000 0.68510  0.49430  0.21710  Biso   1.000  C&#xA;  O3       1.0000 0.64950  0.74370  0.44150  Biso   1.000  O&#xA;  N1       1.0000 0.75820  0.62390  0.35530  Biso   1.000  N&#xA;  C3       1.0000 0.69280  0.59200  0.30020  Biso   1.000  C&#xA;  N2       1.0000 0.74430  0.42960  0.18470  Biso   1.000  N&#xA;  C4       1.0000 0.80920  0.46570  0.23460  Biso   1.000  C&#xA;  H1       1.0000 0.85040  0.42770  0.20760  Biso   1.000  H&#xA;  C5       1.0000 0.61350  0.45010  0.16440  Biso   1.000  C&#xA;  O4       1.0000 0.58760  0.48970  0.04290  Biso   1.000  O&#xA;  O5       1.0000 0.58440  0.37560  0.23660  Biso   1.000  O&#xA;  H2       1.0000 0.33420  0.76070  0.42010  Biso   1.000  H&#xA;  H3       1.0000 0.35810  0.81490  0.55970  Biso   1.000  H&#xA;  C6       1.0000 0.81440  0.56110  0.32780  Biso   1.000  C&#xA;  H4       1.0000 0.85860  0.57980  0.37060  Biso   1.000  H&#xA;  Ba2      1.0000 0.97790  0.19163  0.50773  Biso   1.000  Ba&#xA;  O6       1.0000 0.82620  0.28370  0.51070  Biso   1.000  O&#xA;  O7       1.0000 0.07370  0.16390  0.28140  Biso   1.000  O&#xA;  C7       1.0000 0.13400  0.17060  0.34230  Biso   1.000  C&#xA;  C8       1.0000 0.18510  0.99430  0.21710  Biso   1.000  C&#xA;  O8       1.0000 0.14950  0.24370  0.44150  Biso   1.000  O&#xA;  N3       1.0000 0.25820  0.12390  0.35530  Biso   1.000  N&#xA;  C9       1.0000 0.19280  0.09200  0.30020  Biso   1.000  C&#xA;  N4       1.0000 0.24430  0.92960  0.18470  Biso   1.000  N&#xA;  C10      1.0000 0.30920  0.96570  0.23460  Biso   1.000  C&#xA;  H5       1.0000 0.35040  0.92770  0.20760  Biso   1.000  H&#xA;  C11      1.0000 0.11350  0.95010  0.16440  Biso   1.000  C&#xA;  O9       1.0000 0.08760  0.98970  0.04290  Biso   1.000  O&#xA;  O10      1.0000 0.08440  0.87560  0.23660  Biso   1.000  O&#xA;  H6       1.0000 0.83420  0.26070  0.42010  Biso   1.000  H&#xA;  H7       1.0000 0.85810  0.31490  0.55970  Biso   1.000  H&#xA;  C12      1.0000 0.31440  0.06110  0.32780  Biso   1.000  C&#xA;  H8       1.0000 0.35860  0.07980  0.37060  Biso   1.000  H&#xA;  Ba3      1.0000 0.52210  0.69163  0.99227  Biso   1.000  Ba&#xA;  O11      1.0000 0.67380  0.78370  0.98930  Biso   1.000  O&#xA;  O12      1.0000 0.42630  0.66390  0.21860  Biso   1.000  O&#xA;  C13      1.0000 0.36600  0.67060  0.15770  Biso   1.000  C&#xA;  C14      1.0000 0.31490  0.49430  0.28290  Biso   1.000  C&#xA;  O13      1.0000 0.35050  0.74370  0.05850  Biso   1.000  O&#xA;  N5       1.0000 0.24180  0.62390  0.14470  Biso   1.000  N&#xA;  C15      1.0000 0.30720  0.59200  0.19980  Biso   1.000  C&#xA;  N6       1.0000 0.25570  0.42960  0.31530  Biso   1.000  N&#xA;  C16      1.0000 0.19080  0.46570  0.26540  Biso   1.000  C&#xA;  H9       1.0000 0.14960  0.42770  0.29240  Biso   1.000  H&#xA;  C17      1.0000 0.38650  0.45010  0.33560  Biso   1.000  C&#xA;  O14      1.0000 0.41240  0.48970  0.45710  Biso   1.000  O&#xA;  O15      1.0000 0.41560  0.37560  0.26340  Biso   1.000  O&#xA;  H10      1.0000 0.66580  0.76070  0.07990  Biso   1.000  H&#xA;  H11      1.0000 0.64190  0.81490  0.94030  Biso   1.000  H&#xA;  C18      1.0000 0.18560  0.56110  0.17220  Biso   1.000  C&#xA;  H12      1.0000 0.14140  0.57980  0.12940  Biso   1.000  H&#xA;  Ba4      1.0000 0.02210  0.19163  0.99227  Biso   1.000  Ba&#xA;  O16      1.0000 0.17380  0.28370  0.98930  Biso   1.000  O&#xA;  O17      1.0000 0.92630  0.16390  0.21860  Biso   1.000  O&#xA;  C19      1.0000 0.86600  0.17060  0.15770  Biso   1.000  C&#xA;  C20      1.0000 0.81490  0.99430  0.28290  Biso   1.000  C&#xA;  O18      1.0000 0.85050  0.24370  0.05850  Biso   1.000  O&#xA;  N7       1.0000 0.74180  0.12390  0.14470  Biso   1.000  N&#xA;  C21      1.0000 0.80720  0.09200  0.19980  Biso   1.000  C&#xA;  N8       1.0000 0.75570  0.92960  0.31530  Biso   1.000  N&#xA;  C22      1.0000 0.69080  0.96570  0.26540  Biso   1.000  C&#xA;  H13      1.0000 0.64960  0.92770  0.29240  Biso   1.000  H&#xA;  C23      1.0000 0.88650  0.95010  0.33560  Biso   1.000  C&#xA;  O19      1.0000 0.91240  0.98970  0.45710  Biso   1.000  O&#xA;  O20      1.0000 0.91560  0.87560  0.26340  Biso   1.000  O&#xA;  H14      1.0000 0.16580  0.26070  0.07990  Biso   1.000  H&#xA;  H15      1.0000 0.14190  0.31490  0.94030  Biso   1.000  H&#xA;  C24      1.0000 0.68560  0.06110  0.17220  Biso   1.000  C&#xA;  H16      1.0000 0.64140  0.07980  0.12940  Biso   1.000  H&#xA;  Ba5      1.0000 0.52210  0.30837  0.49227  Biso   1.000  Ba&#xA;  O21      1.0000 0.67380  0.21630  0.48930  Biso   1.000  O&#xA;  O22      1.0000 0.42630  0.33610  0.71860  Biso   1.000  O&#xA;  C25      1.0000 0.36600  0.32940  0.65770  Biso   1.000  C&#xA;  C26      1.0000 0.31490  0.50570  0.78290  Biso   1.000  C&#xA;  O23      1.0000 0.35050  0.25630  0.55850  Biso   1.000  O&#xA;  N9       1.0000 0.24180  0.37610  0.64470  Biso   1.000  N&#xA;  C27      1.0000 0.30720  0.40800  0.69980  Biso   1.000  C&#xA;  N10      1.0000 0.25570  0.57040  0.81530  Biso   1.000  N&#xA;  C28      1.0000 0.19080  0.53430  0.76540  Biso   1.000  C&#xA;  H17      1.0000 0.14960  0.57230  0.79240  Biso   1.000  H&#xA;  C29      1.0000 0.38650  0.54990  0.83560  Biso   1.000  C&#xA;  O24      1.0000 0.41240  0.51030  0.95710  Biso   1.000  O&#xA;  O25      1.0000 0.41560  0.62440  0.76340  Biso   1.000  O&#xA;  H18      1.0000 0.66580  0.23930  0.57990  Biso   1.000  H&#xA;  H19      1.0000 0.64190  0.18510  0.44030  Biso   1.000  H&#xA;  C30      1.0000 0.18560  0.43890  0.67220  Biso   1.000  C&#xA;  H20      1.0000 0.14140  0.42020  0.62940  Biso   1.000  H&#xA;  Ba6      1.0000 0.02210  0.80837  0.49227  Biso   1.000  Ba&#xA;  O26      1.0000 0.17380  0.71630  0.48930  Biso   1.000  O&#xA;  O27      1.0000 0.92630  0.83610  0.71860  Biso   1.000  O&#xA;  C31      1.0000 0.86600  0.82940  0.65770  Biso   1.000  C&#xA;  C32      1.0000 0.81490  0.00570  0.78290  Biso   1.000  C&#xA;  O28      1.0000 0.85050  0.75630  0.55850  Biso   1.000  O&#xA;  N11      1.0000 0.74180  0.87610  0.64470  Biso   1.000  N&#xA;  C33      1.0000 0.80720  0.90800  0.69980  Biso   1.000  C&#xA;  N12      1.0000 0.75570  0.07040  0.81530  Biso   1.000  N&#xA;  C34      1.0000 0.69080  0.03430  0.76540  Biso   1.000  C&#xA;  H21      1.0000 0.64960  0.07230  0.79240  Biso   1.000  H&#xA;  C35      1.0000 0.88650  0.04990  0.83560  Biso   1.000  C&#xA;  O29      1.0000 0.91240  0.01030  0.95710  Biso   1.000  O&#xA;  O30      1.0000 0.91560  0.12440  0.76340  Biso   1.000  O&#xA;  H22      1.0000 0.16580  0.73930  0.57990  Biso   1.000  H&#xA;  H23      1.0000 0.14190  0.68510  0.44030  Biso   1.000  H&#xA;  C36      1.0000 0.68560  0.93890  0.67220  Biso   1.000  C&#xA;  H24      1.0000 0.64140  0.92020  0.62940  Biso   1.000  H&#xA;  Ba7      1.0000 0.47790  0.30837  0.00773  Biso   1.000  Ba&#xA;  O31      1.0000 0.32620  0.21630  0.01070  Biso   1.000  O&#xA;  O32      1.0000 0.57370  0.33610  0.78140  Biso   1.000  O&#xA;  C37      1.0000 0.63400  0.32940  0.84230  Biso   1.000  C&#xA;  C38      1.0000 0.68510  0.50570  0.71710  Biso   1.000  C&#xA;  O33      1.0000 0.64950  0.25630  0.94150  Biso   1.000  O&#xA;  N13      1.0000 0.75820  0.37610  0.85530  Biso   1.000  N&#xA;  C39      1.0000 0.69280  0.40800  0.80020  Biso   1.000  C&#xA;  N14      1.0000 0.74430  0.57040  0.68470  Biso   1.000  N&#xA;  C40      1.0000 0.80920  0.53430  0.73460  Biso   1.000  C&#xA;  H25      1.0000 0.85040  0.57230  0.70760  Biso   1.000  H&#xA;  C41      1.0000 0.61350  0.54990  0.66440  Biso   1.000  C&#xA;  O34      1.0000 0.58760  0.51030  0.54290  Biso   1.000  O&#xA;  O35      1.0000 0.58440  0.62440  0.73660  Biso   1.000  O&#xA;  H26      1.0000 0.33420  0.23930  0.92010  Biso   1.000  H&#xA;  H27      1.0000 0.35810  0.18510  0.05970  Biso   1.000  H&#xA;  C42      1.0000 0.81440  0.43890  0.82780  Biso   1.000  C&#xA;  H28      1.0000 0.85860  0.42020  0.87060  Biso   1.000  H&#xA;  Ba8      1.0000 0.97790  0.80837  0.00773  Biso   1.000  Ba&#xA;  O36      1.0000 0.82620  0.71630  0.01070  Biso   1.000  O&#xA;  O37      1.0000 0.07370  0.83610  0.78140  Biso   1.000  O&#xA;  C43      1.0000 0.13400  0.82940  0.84230  Biso   1.000  C&#xA;  C44      1.0000 0.18510  0.00570  0.71710  Biso   1.000  C&#xA;  O38      1.0000 0.14950  0.75630  0.94150  Biso   1.000  O&#xA;  N15      1.0000 0.25820  0.87610  0.85530  Biso   1.000  N&#xA;  C45      1.0000 0.19280  0.90800  0.80020  Biso   1.000  C&#xA;  N16      1.0000 0.24430  0.07040  0.68470  Biso   1.000  N&#xA;  C46      1.0000 0.30920  0.03430  0.73460  Biso   1.000  C&#xA;  H29      1.0000 0.35040  0.07230  0.70760  Biso   1.000  H&#xA;  C47      1.0000 0.11350  0.04990  0.66440  Biso   1.000  C&#xA;  O39      1.0000 0.08760  0.01030  0.54290  Biso   1.000  O&#xA;  O40      1.0000 0.08440  0.12440  0.73660  Biso   1.000  O&#xA;  H30      1.0000 0.83420  0.73930  0.92010  Biso   1.000  H&#xA;  H31      1.0000 0.85810  0.68510  0.05970  Biso   1.000  H&#xA;  C48      1.0000 0.31440  0.93890  0.82780  Biso   1.000  C&#xA;  H32      1.0000 0.35860  0.92020  0.87060  Biso   1.000  H&#xA;  Cu1      1.0000 0.75000  0.75000  0.50000  Biso   1.000  Cu&#xA;  Cu2      1.0000 0.25000  0.75000  0.00000  Biso   1.000  Cu&#xA;  Cu3      1.0000 0.25000  0.25000  0.50000  Biso   1.000  Cu&#xA;  Cu4      1.0000 0.75000  0.25000  0.00000  Biso   1.000  Cu &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;update 1&lt;/strong&gt;&#xA;I tried to convert the .cif file to .vesta file using the command line interface. The conversion was done without error but while I open the converted file in VESTA software, it shuts down.&lt;/p&gt;&#xA;&lt;p&gt;The errors I received are as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(VESTA-gui:78659): Gtk-WARNING **: 23:55:37.970: Negative content width -2 (allocation 32, extents 17x17) while allocating gadget (node button, owner GtkButton)&#xA;&#xA;(VESTA-gui:78659): Gtk-WARNING **: 23:55:37.970: Negative content width -2 (allocation 32, extents 17x17) while allocating gadget (node button, owner GtkButton)&#xA;Segmentation fault (core dumped)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;`&lt;/p&gt;&#xA;" OwnerUserId="3731" LastEditorUserId="3731" LastEditDate="2023-03-30T12:33:55.833" LastActivityDate="2023-03-30T12:33:55.833" Title="Change cif file into vesta format" Tags="|vesta|cif|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10641" PostTypeId="2" ParentId="10640" CreationDate="2023-03-29T13:15:37.797" Score="5" Body="&lt;p&gt;&lt;strong&gt;Atomsk&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can use &lt;a href=&quot;https://atomsk.univ-lille.fr/&quot; rel=&quot;noreferrer&quot;&gt;Atomsk&lt;/a&gt; package to convert cif files to .vesta.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://atomsk.univ-lille.fr/doc/en/formats.html&quot; rel=&quot;noreferrer&quot;&gt;Here&lt;/a&gt; you can find the supported file formats and &lt;a href=&quot;https://atomsk.univ-lille.fr/tutorial_list.php&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; how to convert multiple files at the same time.&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-03-29T13:15:37.797" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10642" PostTypeId="2" ParentId="10640" CreationDate="2023-03-29T14:19:28.763" Score="7" Body="&lt;p&gt;VESTA has the possibility to be operated via &lt;a href=&quot;https://jp-minerals.org/vesta/en/doc/VESTAch17.html#x36-23700017&quot; rel=&quot;noreferrer&quot;&gt;Command Line Interface&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For a one single file conversion, you can use:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;VESTA -nogui -open in.cif -save *.vesta out.vesta&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The parameters there are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;-nogui&lt;/code&gt;: to not open/work VESTA using the Graphical User Interface (normal mode).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;-open&lt;/code&gt;: Read a file and visualize it (as we are using &lt;code&gt;-nogui&lt;/code&gt;, there is no visualization).&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;-save format&lt;/code&gt;: to export a file in the specified format (take a look &lt;a href=&quot;https://jp-minerals.org/vesta/en/doc/VESTAch17.html#cmd:save&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; for details.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Now, if you have multiple CIF files and want to convert in serial mode, automatically, you can use the batch script below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;# Convert CIF file to VESTA format using VESTA command line interface&#xA;#&#xA;for file in *.cif; do&#xA;    extension=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;${file##*.}&quot;&#xA;    filename=&quot;$&lt;/span&gt;{file%.*}&amp;quot;&#xA;    VESTA -nogui -open file -save *.vesta $filename.vesta&#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Save the script as something like &lt;code&gt;cif2vesta.sh&lt;/code&gt;, and execute it using &lt;code&gt;sh cif2vesta.sh&lt;/code&gt; in the folder with your CIF files.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-03-29T14:19:28.763" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10643" PostTypeId="1" AcceptedAnswerId="10647" CreationDate="2023-03-29T16:35:01.973" Score="6" ViewCount="75" Body="&lt;p&gt;I want to do some DFT calculations for structures of protonated alkaloid dimers. I know that a method of choice when vdW interactions are involved is the use of dispersion corrections. But now I am asking myself if there is a rule of thumb for choosing the right basis set for describing long-range interactions accurately. How relevant is it to consider the different types of basis sets (correlation-consistent, split-valence, etc.) ? Or is it sufficient just to choose a basis set with diffuse functions ?&lt;/p&gt;&#xA;" OwnerUserId="5646" LastActivityDate="2023-03-30T12:11:30.550" Title="Choosing the right basis set for describing vdW-interactions with DFT-D3" Tags="|density-functional-theory|basis-sets|dispersion-correction|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10644" PostTypeId="1" CreationDate="2023-03-30T02:40:56.470" Score="1" ViewCount="48" Body="&lt;p&gt;I am getting the following error while implementing ase cell method. I am not able to understand where is it going wrong, although I think it has to do something with the values I am getting for cell.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Value of cell as input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(&amp;quot;cell: &amp;quot;, cell)&#xA;&#xA;cell:  tensor([-20652532695040.0000,      2.5612,      5.1907,    368.5623,     88.8819,&#xA;           101.3538])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Problem Code:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;placeholder = Atoms(numbers=[1], positions=[[0,0,0]], cell=cell.detach().cpu().numpy())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Error:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/site-packages/ase/cell.py&amp;quot;, line 80, in new&#xA;    cell = cellpar_to_cell(cell)&#xA;&#xA;/site-packages/ase/geometry/cell.py&amp;quot;, line 129, in cellpar_to_cell&#xA;    assert cz_sqr &amp;gt;= 0&#xA;AssertionError&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6643" LastEditorUserId="5" LastEditDate="2023-03-30T03:45:30.757" LastActivityDate="2023-03-30T03:45:30.757" Title="ASE: Receiving error on implimenting ase cellpar_to_cell method" Tags="|python|atomic-simulation-environment|materials-engineering|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T07:35:34.120" ContentLicense="CC BY-SA 4.0" />
  <row Id="10645" PostTypeId="2" ParentId="10638" CreationDate="2023-03-30T04:43:54.893" Score="6" Body="&lt;p&gt;Density functional perturbation theory is a way to calculate the response of a system to some perturbation. For example, you can use DFPT to calculate the response due to small displacements of atoms (this is done in phonon calculations), or to electric or magnetic fields. These are DFT based methods, and they use a DFT ground state and have an exchange-correlation functional. PBEsol is one such functional, and you can do a DFPT calculation using the PBEsol functional, or many others.&lt;/p&gt;&#xA;&lt;p&gt;Many body perturbation theory is a method which tries to solve for certain properties of an interacting electron system. For example, one can calculate the total energy, or the electron addition/removal spectrum. It typically involves coming up with approximation for the single particle Green’s function of the system, from which many other properties can be calculated. In most implantations, one does a DFT or Hartree-Fock calculation first, and then does MBPT based on the ground state wave functions. For example, in the GW approximation (perhaps one of the most commonly used MBPT methods), one often doesn’t do a self-consistent calculation, so that the results of the calculation depend on the DFT ground state. GW calculations based on PBE, LDA, or hybrid functional wave functions can (and often do) give different results. GW is a MBPT method since it’s a Green’s function based approach to solve the interacting electron problem.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps a source of confusion in your question is that DFPT can calculate some of the same things as MBPT. For example, you can calculate the dielectric matrix with both of them. Reading the VASP wiki might give you a sense for what sorts of physical processes are included in DFPT approaches vs MBPT approaches.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2023-03-30T04:43:54.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10646" PostTypeId="2" ParentId="10638" CreationDate="2023-03-30T12:05:25.333" Score="4" Body="&lt;p&gt;To amend AGS's answer, in density functional perturbation theory one looks at how small perturbations to the system affect properties such as dipole moments, excitation energies, etc.&lt;/p&gt;&#xA;&lt;p&gt;Many-body perturbation theory (MBPT) is a wholly different animal. There, the idea is to treat &lt;strong&gt;interelectronic interactions&lt;/strong&gt; as the perturbation, since we are only able to easily solve systems non-interacting electrons to high accuracy. An example of MBPT is Møller-Plesset perturbation theory, usually used in the second-order (MP2), which gives you an estimate for the electron correlation energy based on a self-consistent field Hartree-Fock calculation.&lt;/p&gt;&#xA;&lt;p&gt;However, the issue in MBPT is that interelectronic interactions are &lt;strong&gt;not&lt;/strong&gt; weak, even though one typically makes this assumption in the derivation of perturbation theories. For instance, the Møller-Plesset perturbation series truncated at &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;th order (MP&lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;) often diverges when one goes to &lt;span class=&quot;math-container&quot;&gt;$n \to \infty$&lt;/span&gt;, see e.g.  &lt;a href=&quot;https://doi.org/10.1063/1.481611&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 112, 9736 (2000)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-03-30T12:05:25.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10647" PostTypeId="2" ParentId="10643" CreationDate="2023-03-30T12:11:30.550" Score="6" Body="&lt;p&gt;If you use DFT-D3, vdW interactions are already included in the empirical dispersion correction.&lt;/p&gt;&#xA;&lt;p&gt;The general guidelines for choosing basis sets apply: use modern families of consistent basis sets. For DFT studies you should look at the Karlsruhe def2 series or Jensen's pc(seg)-n series; the correlation consistent basis sets are not cost efficient for DFT. Examine the sequence of basis sets, and examine your property's convergence in the cardinal number, e.g. def2-SVP &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; def2-TZVP &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; def2-QZVP, and the sensitivity of diffuse functions, e.g. def2-SVP &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; def2-SVPD.&lt;/p&gt;&#xA;&lt;p&gt;If you want a single answer, def2-TZVPPD is probably practically at the basis set limit for DFT-D3.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-03-30T12:11:30.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10648" PostTypeId="1" AcceptedAnswerId="10651" CreationDate="2023-03-30T22:01:45.783" Score="4" ViewCount="804" Body="&lt;p&gt;Relaxation calculation gives us the ionic position of the relaxed structure. Now instead of doing a relaxation calculation, if I do fixed point self-consistent field (scf) calculation for varying ionic positions, and plot the ground state energies against the ionic positions, then from the minimum of this plot, we can find the relaxed ionic position. Is there any difference between these two methods? Are they supposed to give the same result?&lt;/p&gt;&#xA;&lt;p&gt;A little background information: in Quantum ESPRESSO, one can perform a &lt;code&gt;calculation='scf'&lt;/code&gt;-type calculation to get the ground state energy of a fixed ionic position. In this case, only electronic relaxation/minimization is performed. One can also perform a &lt;code&gt;calculation='relax'&lt;/code&gt;-type calculation to find the relaxed structure with zero force (actually not precisely zero but a predefined minimum force). In this case, electronic relaxation and ionic positional relaxation are performed. Other codes also have similar features.&lt;/p&gt;&#xA;&lt;p&gt;Let's say I ran a relaxation calculation and found the interatomic distance to be &lt;span class=&quot;math-container&quot;&gt;$x \;Å$&lt;/span&gt;. When I run scf calculation varying the interatomic distance, then I always observe that the energy vs interatomic distance plot has a minimum when the interatomic distance is &lt;span class=&quot;math-container&quot;&gt;$x \;Å$&lt;/span&gt;. That's why I used to think that they are the same. Yet in one particular case, when I plotted the energy against varying bond lengths, I found two minima (one local, and one global). But the relaxation calculation only relaxes the structure to the global minimum. It doesn't matter how close to the local minimum I am setting for the initial position. That's why I asked this question if there is any difference between these two methods.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-25T19:38:55.420" Title="What is the difference between relax and multiple scf calculation in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10649" PostTypeId="1" CreationDate="2023-03-30T22:48:16.210" Score="2" ViewCount="141" Body="&lt;p&gt;I'm a gromacs noob, so I appreciate your patience. I tried simulating the interaction of a protein with 100 copies of the same ligand, in water. The workflow I used is attached here as a picture. The simulation did weird things, specifically: the ligands all appear to have connections, and the protein contorted severely during the simulation. Can anyone point me in the direction of simple fixes? &lt;a href=&quot;https://i.stack.imgur.com/DWSxj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DWSxj.png&quot; alt=&quot;protein contortion&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/FlmuJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FlmuJ.png&quot; alt=&quot;ligands inappropriately connected&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    gmx pdb2gmx -f pro.pdb -o pro.processed.gro&#xA;    gmx insert-molecules -ci jz4.gro -nmol 100 -box 10 10 10 -o jz4.box.gro&#xA;    gmx solvate -cp jz4.box.gro -cs spc216.gro -p jz4.top -o jz4_solv.gro&#xA;    gmx editconf -f pro.gro -o final.gro -box 10 10 10 -center 5 5 5&#xA;    gmx solvate -cp final.gro -cs jz4_solv.gro -o final.box.gro -p topol.top&#xA;&#xA;Add jz4.prm to topol, like this:&#xA;&#xA;; Included forcefield parameters&#xA;#include &amp;quot;./charmm36-jul2022.ff/forcefield.itp&amp;quot;&#xA;&#xA;#include &amp;quot;jz4.prm&amp;quot;&#xA;&#xA;Added jz4.itp to position restraints, like this:&#xA;&#xA;; Include Position restraint file&#xA;#ifdef POSRES&#xA;#include &amp;quot;posre.itp&amp;quot;&#xA;#endif&#xA;&#xA;#include &amp;quot;jz4.itp&amp;quot;&#xA;&#xA;    gmx grompp -f ions.mdp -c final.box.gro -p topol.top -o ions.tpr&#xA;    gmx genion -s ions.tpr -o final.box.gro -p topol.top -pname NA -nname CL -neutral&#xA;Selected SOL&#xA;&#xA;    gmx grompp -f em.mdp -c final.box.gro -p topol.top -o em.tpr&#xA;    gmx mdrun -v -deffnm em&#xA;    gmx grompp -f nvt.mdp -c em.gro -r em.gro -p topol.top -o nvt.tpr&#xA;    gmx mdrun -deffnm nvt -v&#xA;    &#xA;Changed barostat to c-rescale&#xA;&#xA;    gmx grompp -f npt.mdp -c nvt.gro -r nvt.gro -t nvt.cpt -p topol.top -o npt.tpr&#xA;    gmx mdrun -deffnm md_0_1 -nb gpu&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6912" LastEditorUserId="5" LastEditDate="2023-03-31T00:02:23.120" LastActivityDate="2023-03-31T00:02:23.120" Title="Gromacs simulation with 100 copies of same ligand appears weird" Tags="|gromacs|" AnswerCount="0" CommentCount="6" ClosedDate="2023-10-01T14:47:28.550" ContentLicense="CC BY-SA 4.0" />
  <row Id="10651" PostTypeId="2" ParentId="10648" CreationDate="2023-03-31T02:52:16.870" Score="4" Body="&lt;p&gt;An &lt;strong&gt;SCF&lt;/strong&gt; is the basic operation of any DFT code. For a fixed geometry (in crystal structures, this would be captured by the lattice vectors &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{c}$&lt;/span&gt;, and all ionic coordinates &lt;span class=&quot;math-container&quot;&gt;$\{\mathbf{R}_i\}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is an ion index), the SCF should minimize the energy of the system with respect to the Kohn-Sham orbitals, i.e. minimize &lt;span class=&quot;math-container&quot;&gt;$E[\{\phi_j\}]$&lt;/span&gt; for a fixed geometry.&lt;/p&gt;&#xA;&lt;p&gt;A &lt;strong&gt;geometry relaxation&lt;/strong&gt; is just made up of a series of SCF calculations, where the forces and stresses are computed (after the SCF) at each geometry relaxation iteration, for the ionic coordinates and lattice vectors to be moved in order to minimize the energy with respect to the geometry.&lt;/p&gt;&#xA;&lt;p&gt;For very simple systems and tasks, such as optimizing the bond length of a diatomic molecule, it is straightforward to parameterize the geometry in terms of a single interatomic distance, and do multiple SCFs on your own at different interatomic distances to get a simple two-dimensional energy-interatomic distance plot to visualize the &lt;strong&gt;potential energy surface&lt;/strong&gt; (the energy as a function of geometric parameters). The equilibrium bond length that minimizes the energy should then be the same as what you'd get from using the geometry relaxation feature of your DFT code. An analogous example would be finding the equilibrium volume of a particular crystal structure by expanding and contracting the lattice to plot and energy-volume curve and extract the equilibrium volume as the one that minimizes the energy.&lt;/p&gt;&#xA;&lt;p&gt;In general, the space of geometrical parameters for an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-atom system would have dimensions of &lt;span class=&quot;math-container&quot;&gt;$9 + 3N$&lt;/span&gt; (all 9 lattice vector components and the &lt;span class=&quot;math-container&quot;&gt;$x,y,z$&lt;/span&gt; components of each atom). In principle, you could perform a LOT of SCFs for a bunch of possible geometric parameter combinations until you find some energy minimas. This is of course doable if you know something about the system and parameterize it in a tractable way (such as using the interatomic distance for a diatomic molecule). For a general arbitrary system, it is often more computationally tractable to &lt;strong&gt;traverse the high-dimensional potential energy surface&lt;/strong&gt; by using the forces and stresses at each SCF to tell you where to go next and hopefully find local minima more efficiently. This latter approach is what DFT codes do when you use their &amp;quot;geometry relaxation&amp;quot; feature.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-03-31T02:52:16.870" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10652" PostTypeId="2" ParentId="10523" CreationDate="2023-03-31T08:20:10.187" Score="6" Body="&lt;p&gt;This is not a direct solution to your problem but a partial answer to your question &lt;em&gt;Is there a reason for the MLWFs to be real at the global minimum?&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Marzari and Vanderbilt &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.56.12847&quot; rel=&quot;noreferrer&quot;&gt;first reported that&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We also find that at the true global minimum the Wannier functions always turn out to be real, apart from a trivial overall phase; while at the false local minima, they are typically complex, only being real if the initial conditions described in Sec. V B have been used. In summary, while false local minima can occur in our minimization scheme, they do not seem to pose any foreseeable problem in actual calculations.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This empirical conjecture has been proved by Ri and Ri in &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/1407/1407.6824.pdf&quot; rel=&quot;noreferrer&quot;&gt;this arxiv paper: Proof that the maximally localized Wannier functions are real&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-31T08:20:10.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10653" PostTypeId="1" AcceptedAnswerId="10670" CreationDate="2023-03-31T10:10:10.767" Score="5" ViewCount="299" Body="&lt;p&gt;I am trying to read a Nanoscale Molecular Dynamics (NAMD), Dihedral Coordinates (DCD) file using Python. Following the code given at &lt;a href=&quot;https://www.ks.uiuc.edu/Research/namd/wiki/index.cgi?ReadingDCDinFortran&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; to read DCD files using Fortran, I have written the following code snippet to read the header section of the DCD file.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import struct&#xA;import typing&#xA;&#xA;&#xA;class Trajectory:&#xA;    def __init__(self, psfname: str, dcdfile: str) -&amp;gt; None:&#xA;        self.psfName = psfname&#xA;        self.dcdFile = dcdfile&#xA;        self.nAtoms = 0&#xA;        self.nFrames = 0&#xA;        self.readDCD()&#xA;&#xA;    def readDCD(self) -&amp;gt; None:&#xA;        with open(self.dcdFile, &amp;quot;rb&amp;quot;) as dcd:&#xA;            header = dcd.read(92)&#xA;            test = struct.unpack(&amp;quot;4s&amp;quot;, header[0:4])[0]&#xA;            print(header)&#xA;&#xA;&#xA;trajectory = Trajectory(&#xA;    &amp;quot;/home/ssm_grp/project2/jpcb.paper/stripped/additive/adenine/stripped.ade.psf&amp;quot;,&#xA;    &amp;quot;/home/ssm_grp/project2/jpcb.paper/stripped/additive/adenine/stripped.ade.full.add.dcd&amp;quot;,&#xA;)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The Fotran code gave the value &lt;code&gt;'CORD'&lt;/code&gt; which is expected, while the python code gave &lt;code&gt;b'T\x00\x00\x00'&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Edit: I figured that this bitstring &lt;code&gt;b'T\x00\x00\x00'&lt;/code&gt; corresponds to the value 84, indicating that the DCD file is in little-endian format. Now I am confused as to why is that four bits not read in Fortran. Any reference on why this is happening, or how to read DCD files in python would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6687" LastEditDate="2023-04-02T08:59:04.090" LastActivityDate="2023-09-26T09:02:04.913" Title="Reading DCD files using Python without using third party packages?" Tags="|python|fortran|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10654" PostTypeId="1" AcceptedAnswerId="10657" CreationDate="2023-03-31T11:18:07.323" Score="7" ViewCount="1030" Body="&lt;p&gt;People, can someone please help me how to solve this problem with QE 7.0 installation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5Lmuk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5Lmuk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5" LastEditDate="2023-11-06T16:57:52.937" LastActivityDate="2023-11-06T16:57:52.937" Title="How do I install Quantum ESPRESSO on Linux?" Tags="|density-functional-theory|quantum-espresso|software|molecular-modeling|software-assistance|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10655" PostTypeId="1" AcceptedAnswerId="10672" CreationDate="2023-03-31T13:08:54.297" Score="3" ViewCount="220" Body="&lt;p&gt;I want to study the structural, optical, electronic and transport properties of my material that contains Cu atoms using Quantum ESPRESSO. I tried so many approximations but every time I face an issue that limits my progress in the calculations.&lt;/p&gt;&#xA;&lt;p&gt;For example to improve the bandgap I tried DFT+U but when I try to calculate optical properties using epsilon it's not working. When I try hybrid functional PBE0 the calculations same to stay forever with PAW pseudo-potentials, so I changed it to Norm-conserving pseudo-potentials, however the calculations are very computationally expensive.&lt;/p&gt;&#xA;&lt;p&gt;I saw in the internet that some use an approximation called Van der Waals-DFT approximation. Would this be appropriate for modeling a p-type semiconductor?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-04-03T11:40:29.317" LastActivityDate="2023-04-03T22:41:20.010" Title="Would it be appropriate to use a Van der Waals-DFT approximation in Quantum ESPRESSO to study the properties of my material (p-type semiconductor)?" Tags="|density-functional-theory|quantum-espresso|electronic-structure|electronic-transport|optical-properties|" AnswerCount="1" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="10656" PostTypeId="1" CreationDate="2023-03-31T13:16:01.507" Score="3" ViewCount="179" Body="&lt;p&gt;One of the most important quasi-Newton optimisation methods is the BFGS (which uses an iterated Hessian update scheme to avoid recalculation of the actual Hessian). Most numerical optimisation packages such as scipy (code &lt;a href=&quot;https://github.com/scipy/scipy/blob/c1ed5ece8ffbf05356a22a8106affcd11bd3aee0/scipy/optimize/_optimize.py#L1318-L1365&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;) use line searches with the BFGS search direction.&lt;/p&gt;&#xA;&lt;p&gt;However, molecular geometry optimisers, which are also based on the same principle, usually do not use a line search, instead they constrain the step size with a trust radius. This is also the case with optimisers used with NEB such as L-BFGS-B. Overall, accurate line search does not seem to exist in computational chemistry as much as it does in maths or other fields where optimisation is necessary. I did read some very old (1980's) computational papers where they replace accurate line search with a line search on a fitted polynomial surface.&lt;/p&gt;&#xA;&lt;p&gt;Is it because evaluating gradient and energies are expensive (for accurate line search)? And that using line search would be expensive overall instead of just using a trust radius to scale back the step? Most importantly, is there a benchmark or something similar that shows the difference between using line search and trust radius?&lt;/p&gt;&#xA;&lt;p&gt;Note that I am talking about accurate line search (such as Wolfe or Armijo line search), not line search on a fitted polynomial surface (which some optimisers like Gaussian do).&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-04-01T22:10:53.913" Title="Why is line search not popular in quasi-Newton geometry optimisers?" Tags="|geometry-optimization|optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10657" PostTypeId="2" ParentId="10654" CreationDate="2023-03-31T16:30:39.357" Score="9" Body="&lt;p&gt;As suggested in the comment, you can use ubuntu repository to install them:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ sudo apt install quantum-espresso&#xA;$ sudo apt install wannier90&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you get prompted for a password or yes/no confirmations, proceed accordingly. However, this would install a slightly earlier version of QE and you will not have full control over it. As you already probably trying to install it from the source code (guessed from the comment), the following is the easiest I believe. First you need the following libraries:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;git wget g++ gfortran liblapack-dev libfftw3-dev libopenmpi-dev&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To install them, do:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ sudo apt install git wget build-essential&#xA;$ sudo apt install g++ gfortran liblapack-dev&#xA;$ sudo apt install libfftw3-dev libopenmpi-dev&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you are ready to download and compile the source code. To download the latest version:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ git clone https://github.com/QEF/q-e.git&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then first enter the downloaded folder (it's name should be q-e or q-e-# where # is the version number) and then run configure:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cd q-e&#xA;./configure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Lastly, you can install everything or parts of Quantum ESPRESSO by the &lt;code&gt;make&lt;/code&gt; command.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;make all&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;will do everything. But if you want just pw.x (or post-processing stuffs), then do &lt;code&gt;make pw&lt;/code&gt; (or &lt;code&gt;make pp&lt;/code&gt;). Sometimes the wannier90 installation fails, but everything else works. You will get the binaries in the bin folder. To use the binaries directly from anywhere, you need to export their path:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ echo 'export PATH=$PATH:$HOME/q-e/bin' &amp;gt;&amp;gt; ~/.bashrc&#xA;$ source ~/.bashrc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here I assumed that your q-e folder is in the home (~) directory. If it is in some other directory, change the path from &lt;code&gt;$HOME/q-e/bin&lt;/code&gt; to that directory (for example &lt;code&gt;$HOME/Downloads/quantumespresso/qe-7.0/bin&lt;/code&gt;). Hope it helps.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-03-31T16:30:39.357" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10658" PostTypeId="1" CreationDate="2023-03-31T20:39:45.950" Score="3" ViewCount="232" Body="&lt;p&gt;I apologize for asking this stupid question, but I am a bit confused with the ISIF tag.&#xA;Doesn't a cell's shape and cell's volume depend on the atoms' positions?&#xA;If so, why can the cell's volume/shape and atomic position change independently in the ISIF tag?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-10-04T13:20:39.663" Title="A Question about ISIF Tag in VASP" Tags="|density-functional-theory|vasp|crystallography|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10659" PostTypeId="1" AcceptedAnswerId="10660" CreationDate="2023-04-01T13:26:25.427" Score="5" ViewCount="483" Body="&lt;p&gt;Let's suppose that I prepare an input file, writing certain parameters defining some molecular structure into to run in Quantum Espresso. For simplicity and convenience I have decided to create an user's variable, for instance, QE_PSEUDO to save a path of a directory with pseudopotentials files. Having passed such a variable into an input file parameter I get an error, see an example of an input file part below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;example.in:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    ...,&#xA;    pseudo_dir='$QE_PSEUDO',&#xA;    ...,&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But if to use a path without variables &amp;quot;as is&amp;quot; it's okay then. Whether no way to make Quantum Espresso understand an user's variable inside an input file?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Addition 1:&lt;/strong&gt;&#xA;&lt;em&gt;CRASH file:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         0&#xA;     from readpp : error #         1&#xA;     file $QE_PSEUDO/Si.bhs not found&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;output file:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program PWSCF v.7.2 starts on  2Apr2023 at  0:25:40 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI), running on     1 processors&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     7028 MiB available memory on the printing compute node when the environment starts&#xA;&#xA;     Waiting for input...&#xA;     Reading input from standard input&#xA;&#xA;     Current dimensions of program PWSCF are:&#xA;     Max number of different atomic species (ntypx) = 10&#xA;     Max number of k-points (npk) =  40000&#xA;     Max angular momentum in pseudopotentials (lmaxx) =  4&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine readpp (1):&#xA;     file $QE_PSEUDO/Si.bhs not found&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Addition 2:&lt;/strong&gt;&#xA;&lt;em&gt;CRASH file:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     task #         0&#xA;     from  read_namelists : error #         1&#xA;      bad line in namelist &amp;amp;control: &amp;quot;    pseudo_dir=$QE_PSEUDO,&amp;quot; (error could be in the previous line)&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;output file:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program PWSCF v.7.2 starts on  2Apr2023 at  0:52: 9 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI), running on     1 processors&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     6602 MiB available memory on the printing compute node when the environment starts&#xA;&#xA;     Waiting for input...&#xA;     Reading input from standard input&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine  read_namelists (1):&#xA;      bad line in namelist &amp;amp;control: &amp;quot;    pseudo_dir=$QE_PSEUDO,&amp;quot; (error could be in the previous line)&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5403" LastEditDate="2023-04-01T16:01:02.877" LastActivityDate="2023-04-01T21:43:06.360" Title="No way to make Quantum Espresso understand variables created by a user inside an input file?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10660" PostTypeId="2" ParentId="10659" CreationDate="2023-04-01T21:43:06.360" Score="8" Body="&lt;p&gt;The first thing I should point out is that this particular use of an environment variable is not necessary, because Quantum Espresso &lt;em&gt;already&lt;/em&gt; uses an environment variable to determine where it looks for pseudopotentials: &lt;code&gt;PSEUDO_DIR&lt;/code&gt;. See the Quantum Espresso user guide at &lt;a href=&quot;https://www.quantum-espresso.org&quot; rel=&quot;noreferrer&quot;&gt;quantum-espresso.org&lt;/a&gt; for more details.&lt;/p&gt;&#xA;&lt;p&gt;Having said that, there are certainly times when it would be useful to use your own environment variables, so let's look at the problem you're having and see how we might solve it.&lt;/p&gt;&#xA;&lt;p&gt;The reason your current approach doesn't work is because environment variables are set and read by the Linux shell you're using (e.g. &lt;code&gt;bash&lt;/code&gt;; there are equivalent ones for Windows etc), but the Quantum Espresso input file is not processed by the shell, it's used by Quantum Espresso.&lt;/p&gt;&#xA;&lt;p&gt;You can achieve a similar result by writing a shell script (or other program) to create your Quantum Espresso input file. Unlike your Quantum Espresso input files, these shell scripts &lt;em&gt;are&lt;/em&gt; interpreted by the shell, so environment variables will be replaced by their values. The simplest script to write just uses &amp;quot;echo&amp;quot; to write a line of text, e.g. create a text file, let's call it &lt;code&gt;make_qe_input.sh&lt;/code&gt;, and then put this text in it:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;echo \&amp;amp;CONTROL&#xA;echo    pseudo_dir=$QE_PSEUDO,&#xA;echo /&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;NB you must put a &amp;quot;\&amp;quot; before any ampersands (&amp;quot;&amp;amp;&amp;quot;), and you must not have quotation marks around the environment variables.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now we need to make sure Linux knows that this file contains executable commands, so we change its mode using the &lt;code&gt;chmod&lt;/code&gt; command, to add execute permission for the user (us); at the command-line, type:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;chmod u+x make_qe_input.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now we set the environment variable to what we want, and run our script. For example, at the command-line we might type:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export QE_PSEUDO=/home/me/my_potentials/&#xA;./make_qe_input.sh&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and you should see the text output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;pseudo_dir=/home/me/my_potentials/,&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;All we have to do now is to add the other Quantum Espresso input lines to our script, and when we run it we should redirect the output (using &amp;quot;&amp;gt;&amp;quot;) to a Quantum Espresso input file instead of the text terminal, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;./make_qe_input.sh &amp;gt; example.in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you look in the file &lt;code&gt;example.in&lt;/code&gt; you will see all the Quantum Espresso input we &amp;quot;echoed&amp;quot; in our shell script, with any environment variables replaced by their appropriate values. If you ever write an environment variable which you haven't actually defined, it won't report an error, it will just write nothing at that point.&lt;/p&gt;&#xA;&lt;p&gt;This isn't the most elegant solution, but if you haven't used the shell much this is probably the most straightforward. There are many other ways you could achieve this, for example using a text stream editor such as &lt;code&gt;sed&lt;/code&gt;, but I recommend starting with my example and getting comfortable with that way first.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-04-01T21:43:06.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10661" PostTypeId="2" ParentId="10656" CreationDate="2023-04-01T22:10:53.913" Score="8" Body="&lt;p&gt;A trust region method is not really a replacement for a line-search optimisation, the methods are complementary.&lt;/p&gt;&#xA;&lt;p&gt;A line-search optimiser would usually proceed by taking a trial step in the direction of the (preconditioned) forces, and then evaluating the new energies and forces (and possibly stresses) at that trial configuration. Using this new information, the optimiser would then calculate a better step length to use. Of course, you will never get the &lt;em&gt;exact&lt;/em&gt; optimal step, so a better step can always be found; how do you know whether your step is &amp;quot;good enough&amp;quot;, or whether you should keep trying for a better step? This is where the Wolfe conditions come in. The Wolfe conditions do not describe an &lt;em&gt;exact&lt;/em&gt; optimiser, they are precisely designed to help your &lt;em&gt;inexact&lt;/em&gt; optimiser to converge efficiently to the solution. Evaluating energies and gradients is computationally demanding, and we don't want to do it more than we have to.&lt;/p&gt;&#xA;&lt;p&gt;Given our line-search method, why might me want to use a trust region approach? Well, what if we start a very long way from our minimum, and perhaps our preconditioner is not very good. We could find that our initial trial step takes us to a completely different region of phase space, with a different local minimum to the one we want.&lt;/p&gt;&#xA;&lt;p&gt;For example, suppose we have a ferromagnetic material, but the atoms are too far apart. Our trial step could move the atoms too close together, and this could cause some of the spins to be suppressed, pushing the material to a nonmagnetic state; or some of the spins might even flip, making an antiferromagnetic phase. The next optimisation step will move the atoms further apart again, but they might stay in this new magnetic state, and not the ferromagnetic state we wanted.&lt;/p&gt;&#xA;&lt;p&gt;This problem occurred because our trial step moved the atoms outside the region of space that our (preconditioned) optimiser modelled reliably; we moved out of the &amp;quot;trust region&amp;quot;. Trust region methods estimate the region of configuration space in which our optimiser can be trusted, and if the trial step would take us out of that region, they reduce the trial step to take us just to the boundary of the trust region. This stops the method taking you into completely different regions of configuration space accidentally.&lt;/p&gt;&#xA;&lt;p&gt;Once the new step has been taken, the new energies and forces are included in the optimiser model (e.g. the BFGS Hessian) and the trust region is recalculated. In this way, the atoms are allowed to move into a different state if that is genuinely the low energy, zero-force solution, but they won't do it just by accidentally moving too far -- or that's the idea, anyway!&lt;/p&gt;&#xA;&lt;p&gt;Of course, if your trial step stays within the trust region, then the usual line-search optimisation can be used to find a good enough step to take.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-04-01T22:10:53.913" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10662" PostTypeId="1" CreationDate="2023-04-02T04:50:47.690" Score="3" ViewCount="50" Body="&lt;p&gt;Looking to find sorption sites of species including (H2, CO2, and N2) within porous materials (metal-organic frameworks) for further DFT work. Is RASPA2 a sensible Monte Carlo software to achieve this? Is adsorption sites found by Radial Pair Distribution analysis, if not how?&lt;/p&gt;&#xA;" OwnerUserId="6958" LastActivityDate="2023-09-30T20:09:35.213" Title="Is RASPA2 a sensible Monte Carlo software to find adsorption sites within porous materials?" Tags="|density-functional-theory|monte-carlo|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10663" PostTypeId="1" CreationDate="2023-04-02T08:13:31.153" Score="1" ViewCount="39" Body="&lt;p&gt;I have been following along with &lt;a href=&quot;https://ambermd.org/tutorials/basic/tutorial4b/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial for simulating a small ligand binding a protein receptor&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In both the tutorial and my follow-along (which uses the same commands as the tutorial but with different input), the &lt;a href=&quot;https://ambermd.org/tutorials/basic/tutorial4b/files/sustiva.pdb&quot; rel=&quot;nofollow noreferrer&quot;&gt;input ligand&lt;/a&gt; has clear double bonds. However, after re-generating the  ligand pdb after simulation with amber, &lt;a href=&quot;https://ambermd.org/tutorials/basic/tutorial4b/files/1FKO_sus_min.pdb&quot; rel=&quot;nofollow noreferrer&quot;&gt;the ligand is then represented&lt;/a&gt; as having only single bonds.&lt;/p&gt;&#xA;&lt;p&gt;Does this mean that during the simulation the ligand was also considered to only have single bonds?&lt;/p&gt;&#xA;" OwnerUserId="6742" LastActivityDate="2023-04-02T08:13:31.153" Title="Apparent change in bond order of a molecule after an amber simulation?" Tags="|molecular-dynamics|amber|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:49:39.890" ContentLicense="CC BY-SA 4.0" />
  <row Id="10665" PostTypeId="1" CreationDate="2023-04-02T20:35:30.630" Score="9" ViewCount="83" Body="&lt;p&gt;A variety of databases include &amp;quot;purchasability&amp;quot; (e.g., ZINC) and can be filtered as such. Or you can download just the purchasable compounds.&lt;/p&gt;&#xA;&lt;p&gt;I'm curious if there are methods or web APIs to ZINC or eMolecules or similar databases or commercial vendors to get an estimated purchase price from a SMILES string.&lt;/p&gt;&#xA;&lt;p&gt;To be honest, I don't need an exact price quote. I just want to know a rough magnitude like USD\$ per gram, e.g.  \$1 vs. \$10 vs. \$100 vs. \$1000. In other words, can I filter out aspirin or caffeine which are inexpensive, versus taxol or some complex compound that's much more expensive?&lt;/p&gt;&#xA;&lt;p&gt;I've seen some indication that ZINC once had a purchase price and it's possible to find on the website, for example &lt;a href=&quot;https://cartblanche22.docking.org/substance/ZINCe4000000YXRm&quot; rel=&quot;nofollow noreferrer&quot;&gt;at this page&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="5" LastEditDate="2023-10-12T16:49:54.913" LastActivityDate="2023-10-15T20:17:07.993" Title="Is there a method or web API to get pricing from a SMILES string?" Tags="|databases|smiles|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10666" PostTypeId="1" CreationDate="2023-04-03T10:39:28.610" Score="4" ViewCount="152" Body="&lt;p&gt;I would like to gain knowledge about how DFT calculations can be specifically used in the subject of electrical engineering. &lt;strong&gt;It would really help if people in the community can direct me towards scholars or professors or scientists who are actively working on it. I would really like to follow them.&lt;/strong&gt;&lt;/p&gt;&#xA;&#xA;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2023-10-16T17:34:03.957" LastActivityDate="2023-10-16T17:34:03.957" Title="Which researchers in electrical engineering do work related to DFT?" Tags="|density-functional-theory|reference-request|materials-design|materials-engineering|soft-question|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10667" PostTypeId="1" CreationDate="2023-04-03T11:04:07.877" Score="2" ViewCount="49" Body="&lt;p&gt;In the paper bellow they used GGA+U to investigate the structural, electronic and&#xA;optical properties of Ag- and Cu-doped ZnO.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.emerald.com/insight/content/doi/10.1108/MI-05-2022-0088/full/html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.emerald.com/insight/content/doi/10.1108/MI-05-2022-0088/full/html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;They used a Hubbard term for Cu atom U=9.5eV as shown in the picture bellow. What do they mean by repeated investigation here? Can I use this value as a Hubbard term for Cu atoms in my calculations to improve the bandgap of my material.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fClMq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fClMq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-04-03T11:04:07.877" Title="What's the meaning of a Hubbard term determined by repeated investigation?" Tags="|density-functional-theory|quantum-espresso|band-structure|hubbard-model|bandgap|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:13:05.773" ContentLicense="CC BY-SA 4.0" />
  <row Id="10668" PostTypeId="1" CreationDate="2023-04-03T14:15:37.473" Score="2" ViewCount="43" Body="&lt;p&gt;While trying to perform docking of a protein containing Samarium atom using Autodock-vina in Ubuntu, the following error arises. &amp;quot;&lt;strong&gt;ATOM syntax incorrect: &amp;quot;Sm&amp;quot; is not a valid AutoDock type. Note that AutoDock atom types are case-sensitive.&lt;/strong&gt;&amp;quot; Following similar queries, I tried adding the parameters of the atom to the AD4_parameters.dat and AD4.1_bound.dat files yet couldn't resolve the problem. Can anyone guide me through this?&lt;/p&gt;&#xA;" OwnerUserId="6966" LastActivityDate="2023-04-03T14:15:37.473" Title="How to add Samarium atom type in Autodock Vina?" Tags="|docking|autodock|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-13T16:49:30.143" ContentLicense="CC BY-SA 4.0" />
  <row Id="10669" PostTypeId="1" CreationDate="2023-04-03T14:30:12.213" Score="2" ViewCount="66" Body="&lt;p&gt;I need to work out optical properties of TMDC-based structures. For this I need to get DFT+GW bandstructure around G (Г), K, Q (lambda) points. I tried to use BerkeleyGW for this, but it is too heavy computation for my laptop. But I need just a small set of points with GW corrections (let's say 5-10 around G, K, Q) so I don't actually need to recalculate the whole BZ. It is completely not obvious though how to customize any of the methods known to me to do this. Are there any solutions? I am not restricted by just BerkeleyGW and can try do any package on any system (Mac is preferable).&lt;/p&gt;&#xA;" OwnerUserId="5933" LastActivityDate="2023-04-03T14:30:12.213" Title="How to perform DFT+GW using a small number of points around high symmetry points?" Tags="|band-structure|" AnswerCount="0" CommentCount="4" ClosedDate="2024-01-11T14:40:39.780" ContentLicense="CC BY-SA 4.0" />
  <row Id="10670" PostTypeId="2" ParentId="10653" CreationDate="2023-04-03T15:44:18.970" Score="2" Body="&lt;p&gt;With some digging around, I found this &lt;a href=&quot;https://github.com/priimak/scala-data/blob/master/NAMD-DCD-File-Format.md&quot; rel=&quot;nofollow noreferrer&quot;&gt;webpage&lt;/a&gt; which gave some hints to the specific padding required to read the various data from the DCD header. Even though the data given in the above mentioned webpage was not completely correct, I could just print out the specific bits to figure out the rest. Given below is a working code that can read the header section of the DCD file.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import struct&#xA;import typing&#xA;import numpy &#xA;import os&#xA;&#xA;class Trajectory:&#xA;    def __init__(self, psf: str, dcd: str) -&amp;gt; None:&#xA;        self.psf = psf&#xA;        self.dcd = dcd&#xA;        self.__readDCD__()&#xA;&#xA;    def __readDCD__(self):&#xA;        with open(self.dcd, &amp;quot;rb&amp;quot;) as DCDReader:&#xA;            header = DCDReader.read(272)&#xA;            endian = struct.unpack(&amp;quot;i&amp;quot;, header[0:4])[0]                 # Must be equal to 84&#xA;            cordst = struct.unpack(&amp;quot;4s&amp;quot;, header[4:8])[0]                # CORD&#xA;            &#xA;            # Trajectory information&#xA;            nframe = struct.unpack(&amp;quot;i&amp;quot;, header[8:12])[0]                # Number of frames&#xA;            iframe = struct.unpack(&amp;quot;i&amp;quot;, header[12:16])[0]               # First frame in DCD file&#xA;            stride = struct.unpack(&amp;quot;i&amp;quot;, header[16:20])[0]               # Stride between two consecutive frames&#xA;            lframe = struct.unpack(&amp;quot;i&amp;quot;, header[20:24])[0]               # Last frame in DCD file&#xA;            nframe = int((lframe - iframe) / stride)&#xA;&#xA;            # List of five zeros =&amp;gt; Does not do anything&#xA;            fzero1 = struct.unpack(&amp;quot;i&amp;quot;, header[24:28])[0]&#xA;            fzero2 = struct.unpack(&amp;quot;i&amp;quot;, header[28:32])[0]&#xA;            fzero3 = struct.unpack(&amp;quot;i&amp;quot;, header[32:36])[0]&#xA;            fzero4 = struct.unpack(&amp;quot;i&amp;quot;, header[36:40])[0]&#xA;            fzero5 = struct.unpack(&amp;quot;i&amp;quot;, header[40:44])[0]&#xA;&#xA;            timest = struct.unpack(&amp;quot;f&amp;quot;, header[44:48])[0]               # Timestep&#xA;            testst = struct.unpack(&amp;quot;i&amp;quot;, header[48:52])[0]               # &#xA;&#xA;            nzero1 = struct.unpack(&amp;quot;i&amp;quot;, header[52:56])[0]&#xA;            nzero2 = struct.unpack(&amp;quot;i&amp;quot;, header[56:60])[0]&#xA;            nzero3 = struct.unpack(&amp;quot;i&amp;quot;, header[60:64])[0]&#xA;            nzero4 = struct.unpack(&amp;quot;i&amp;quot;, header[64:68])[0]&#xA;            nzero5 = struct.unpack(&amp;quot;i&amp;quot;, header[68:72])[0]&#xA;            nzero6 = struct.unpack(&amp;quot;i&amp;quot;, header[72:76])[0]&#xA;            nzero7 = struct.unpack(&amp;quot;i&amp;quot;, header[76:80])[0]&#xA;            nzero8 = struct.unpack(&amp;quot;i&amp;quot;, header[80:84])[0]&#xA;            nzero9 = struct.unpack(&amp;quot;i&amp;quot;, header[84:88])[0]&#xA;           &#xA;            ntitle = struct.unpack(&amp;quot;i&amp;quot;, header[96:100])[0]              # number of title strings&#xA;            tsizes = 100 + ntitle*80                                    # size of title strings            &#xA;            tbsize = struct.unpack(&amp;quot;i&amp;quot;, header[tsizes:tsizes+4])[0]     # size of title block&#xA;            constv = struct.unpack(&amp;quot;i&amp;quot;, header[tsizes+4:tsizes+8])[0]   # value 4&#xA;            natoms = struct.unpack(&amp;quot;i&amp;quot;, header[tsizes+8:tsizes+12])[0]  # Number of atoms&#xA;            # Read the first 272 bytes of data and parse the header information&#xA;&#xA;            # Just a hack to find the number of remaining bytes&#xA;            DCDReader.seek(0, os.SEEK_END)&#xA;            remainingSize   = DCDReader.tell() - 272&#xA;            DCDReader.seek(272, 0)&#xA;            &#xA;            firstframe  = DCDReader.read(60)&#xA;            testvl  = struct.unpack(&amp;quot;i&amp;quot;, firstframe[4:8])[0]    # size of pbc length&#xA;            pbcvecx = struct.unpack(&amp;quot;d&amp;quot;, firstframe[8:16])[0]   # PBC length in x&#xA;            pbcvecy = struct.unpack(&amp;quot;d&amp;quot;, firstframe[24:32])[0] # PBC length in y&#xA;            pbcvecz = struct.unpack(&amp;quot;d&amp;quot;, firstframe[48:56])[0] # PBC length in z&#xA;            gamma   = struct.unpack(&amp;quot;d&amp;quot;, firstframe[16:24])[0]  # gamma&#xA;            beta    = struct.unpack(&amp;quot;d&amp;quot;, firstframe[40:48])[0]  # beta&#xA;            alpha   = struct.unpack(&amp;quot;d&amp;quot;, firstframe[32:40])[0]  # alpha&#xA;            print(testvl, pbcvecx, pbcvecy, pbcvecz, gamma, beta, alpha)&#xA;#            print(consta, testvl, pbcvecx, pbcvecy, pbcvecz, numpy.arccos(alpha)*180/numpy.pi, numpy.arccos(beta)*180/numpy.pi, numpy.arccos(gamma)*180/numpy.pi)&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-04-03T15:44:18.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10672" PostTypeId="2" ParentId="10655" CreationDate="2023-04-03T22:41:20.010" Score="6" Body="&lt;p&gt;No, van der Waals functionals would not be appropriate for this type of system - at least, not normally.&lt;/p&gt;&#xA;&lt;p&gt;Most semiconductors of interest are strongly bonded 3D materials, with covalent bonds and perhaps a small polarisation (e.g. GaN). Semi-local exchange correlation methods describe these systems well, on the whole, with the exception of the well-known underestimation of the band-gap. The band-structures are usually modelled well, apart from the band-gap itself, so if you already know what the band-gap is, the simplest approach is just to correct the band-gap using a scissor operator.&lt;/p&gt;&#xA;&lt;p&gt;Van der Waals functionals are designed to capture the non-local, long-range correlation of weakly-interacting densities, which is the mechanism for the van der Waals interaction. This interaction is important when modelling the energies and forces between atoms which are relatively isolated, for example inter-molecular forces, or the long-range interaction between a molecule and a surface. However, it is a subtle correlation effect with a fairly small interaction energy, and it is easily disrupted at short ranges and in the presence of other, stronger interactions. They &lt;em&gt;could&lt;/em&gt; be relevant for bundles of loosely-coupled 1D (e.g. nanotubes) or 2D organic semiconductors (e.g. functionalised graphene), but they are extremely unlikely to be relevant for any conventional 3D semiconductors.&lt;/p&gt;&#xA;&lt;p&gt;Since you are interested in band-gaps, I will also point out that van der Waals functionals do not address any of the issues relevant to predicting accurate band-gaps; for example, they do not contain the correct derivative discontinuity, they do not correct self-interaction, they do not lead to piecewise-linear energies as a function of band occupancy (Koopman's Theorem), and they do not give good values for the ionisation potential.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-04-03T22:41:20.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10673" PostTypeId="1" CreationDate="2023-04-04T04:02:43.393" Score="1" ViewCount="75" Body="&lt;p&gt;I calculated the XANES of the MnO compound following the vaspwiki tutorial (&lt;a href=&quot;https://www.vasp.at/wiki/index.php/XANES_in_Diamond&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/XANES_in_Diamond&lt;/a&gt;). But it looks strange and shows great discrepancy with the XANES within the Materials Project which is calculated by FEFF code （https://materialsproject.org/materials/mp-19006?chemsys=Mn-O%EF%BC%89).&lt;/p&gt;&#xA;&lt;p&gt;Attached are the calculated XANES and the INCAR file for VASP calculation. Can someone tell me how to fix it?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gQvs4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;enter image description here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;System = MnO XANES&#xA;ALGO = FAST&#xA;ISMEAR = 0&#xA;SIGMA = 0.1&#xA;ENCUT = 520&#xA;EDIFF = 1E-5&#xA;ICORELEVEL = 2&#xA;CLNT = 1&#xA;CLN = 1&#xA;CLL = 0&#xA;CLZ = 1.0&#xA;CH_LSPEC = .TRUE.&#xA;CH_SIGMA = 0.5&#xA;NBANDS = 640&#xA;LREAL = A&#xA;KSPACING = 0.2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6969" LastActivityDate="2023-04-04T04:02:43.393" Title="The XANES of MnO calculated by VASP is weirdVA" Tags="|vasp|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-13T16:49:18.230" ContentLicense="CC BY-SA 4.0" />
  <row Id="10674" PostTypeId="1" CreationDate="2023-04-04T04:15:35.880" Score="5" ViewCount="317" Body="&lt;p&gt;I have been trying to calculate the thermal conductivity of a square graphene sheet of 3200 atoms, but I get a k value of 150W/mK, which is many times smaller than the published 4000W/mK. I am fairly new to LAMMPS and I'm not sure where I'm going wrong since it isn't a coding error. Does anyone have any insights? Thanks in advance&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SLG GK&#xA;#####################################################&#xA;# Variable Definition ###############################&#xA;#####################################################&#xA;variable        damp equal 0.5&#xA;variable        seed equal 102486 #just a random number&#xA;variable        T equal 300 # Temperature&#xA;variable        V equal vol #volume&#xA;variable        P equal 1.01325 # 1 atm in bar &#xA;variable        dt equal 0.001 # 1 fs in metal (timestep)&#xA;variable        r equal 100000 #??&#xA;variable        p equal 10000    # correlation length should be 10000&#xA;variable        s equal 1        # sample interval should be 1&#xA;variable        d equal &lt;span class=&quot;math-container&quot;&gt;$p*$&lt;/span&gt;s    # dump interval&#xA;variable        kB equal 1.3806504e-23    # [J/K] Boltzmann constant&#xA;&#xA;# Convert from LAMMPS metal units to SI&#xA;variable        eV2J equal  1.60218e-19 # eV to Joule&#xA;variable        ps2s equal 1.0e-12 # picosec to sec&#xA;variable        A2m equal 1.0e-10 #angstrom to m&#xA;variable        convert equal &lt;span class=&quot;math-container&quot;&gt;${eV2J}*$&lt;/span&gt;{eV2J}/&lt;span class=&quot;math-container&quot;&gt;${ps2s}/$&lt;/span&gt;{A2m} #&#xA;&#xA;#####################################################&#xA;# Initializing simulation box #######################&#xA;#####################################################&#xA;dimension       3&#xA;boundary        p p f&#xA;units           metal&#xA;atom_style      full&#xA;read_data       SLG2.data&#xA;mass            1 12.0107   # Carbon&#xA;pair_style      airebo 2 &#xA;pair_coeff      * *     CH.airebo C # chemical&#xA;neighbor        2.0 bin&#xA;neigh_modify    every 1&#xA;neigh_modify    delay 0&#xA;neigh_modify    check yes&#xA;minimize 1e-10 1e-10  10000 100000000&#xA;#delete_atoms overlap 0.1 all all&#xA;&#xA;#####################################################&#xA;# 1st equilibration run #############################&#xA;######################################################&#xA;#At the beginning of each simulation, a system is optimized and then equilibrated&#xA;#with NPT(isothermal-isobaric) ensemble under 300K temperature and zero pressure.&#xA;#All of the simulations are performed by time step of 1fs with periodic boundary condition(PBC)&#xA;#NPT 2.5ns 2500st, NVT 1ns 1000st, NVE 1ns 1000st&#xA;timestep        ${dt}&#xA;thermo          100&#xA;velocity        all create 300 12345 mom yes rot yes dist gaussian&#xA;fix             1 all npt temp 300.0 300.0 0.2 iso 0.0 0.0 0.1&#xA;thermo_style    custom step temp press&#xA;run             2500&#xA;unfix           1&#xA;fix             1 all nvt temp 300.0 300.0 0.2&#xA;thermo_style    custom step temp press&#xA;run             1000&#xA;unfix           1&#xA;fix             1 all nve&#xA;thermo_style    custom step temp press&#xA;run             1000&#xA;#unfix          1&#xA;reset_timestep  0&#xA;#####################################################&#xA;# Green Kubo Method #################################&#xA;#####################################################&#xA;&#xA;thermo          &lt;span class=&quot;math-container&quot;&gt;$d&#xA;compute         myKE all ke/atom&#xA;compute         myPE all pe/atom&#xA;compute         myStress all stress/atom NULL virial&#xA;compute         flux all heat/flux myKE myPE myStress&#xA;variable        Jx equal c_flux[1]/vol&#xA;variable        Jy equal c_flux[2]/vol&#xA;variable        Jz equal c_flux[3]/vol&#xA;fix             JJ all ave/correlate $&lt;/span&gt;s &lt;span class=&quot;math-container&quot;&gt;$p $&lt;/span&gt;d &amp;amp; &#xA;                c_flux[1] c_flux[2] c_flux[3] type auto file J0Jt.dat ave running #Nevery Nrepeat Nfreq&#xA;variable        scale equal &lt;span class=&quot;math-container&quot;&gt;${convert}/$&lt;/span&gt;{kB}/&lt;span class=&quot;math-container&quot;&gt;$T/$&lt;/span&gt;T/&lt;span class=&quot;math-container&quot;&gt;$V*$&lt;/span&gt;s*&lt;span class=&quot;math-container&quot;&gt;${dt}&#xA;variable        k11 equal trap(f_JJ[3])*$&lt;/span&gt;{scale}&#xA;variable        k22 equal trap(f_JJ[4])*&lt;span class=&quot;math-container&quot;&gt;${scale}&#xA;variable        k33 equal trap(f_JJ[5])*$&lt;/span&gt;{scale}&#xA;variable        k11r equal trap(f_JJ[3])&#xA;variable        k22r equal trap(f_JJ[4])&#xA;variable        k33r equal trap(f_JJ[5])&#xA;thermo_style    custom step temp v_V v_convert v_k11r v_k22r v_k33r v_scale v_Jx v_Jy v_Jz v_k11 v_k22 v_k33 &#xA;dump myDump1 all atom 100 SLG-GK.lammpstrj&#xA;run             50000 #should be 100000&#xA;&#xA;variable    k equal (v_k11+v_k22+v_k33)/3&#xA;variable    ndens equal count(all)/vol&#xA;print           &amp;quot;average conductivity: &lt;span class=&quot;math-container&quot;&gt;$k[W/mK] @ $&lt;/span&gt;T K, ${ndens} /A\^3&amp;quot;&#xA;&#xA;print       &amp;quot;SIMULATION DONE&amp;quot;&#xA;&#xA;&#xA;&#xA;#heatflux = W/m2=J/sm2=x eV/psA2&#xA;&#xA;#V/kBT2= m3K/Js = A3K/eVK2&#xA;&#xA;#conversion factor = A2m / ps2s*K&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;P.S. I am also trying to simulate the thermal conductivity of stacked graphene on hBN&lt;/p&gt;&#xA;" OwnerUserId="6970" LastActivityDate="2023-04-04T19:44:47.443" Title="LAMMPS calculated graphene thermal conductivity lower than expected" Tags="|lammps|2d-lattice|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10675" PostTypeId="2" ParentId="10674" CreationDate="2023-04-04T19:44:47.443" Score="4" Body="&lt;p&gt;&lt;strong&gt;Your result is probably correct for this model.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm actually not surprised that the thermal conductivity is much too low for graphene. The Airebo potential, being a classical atomistic potential, doesn't represent electronic degrees of freedom, so any contribution of conduction electrons to the thermal conductivity is not represented. I'd expect then that the thermal conductivity of this model of graphene would be the same order of magnitude as the conductivity of its insulator sibling, hexagonal boron nitride. Indeed, hexagonal boron nitride has a thermal conductivity of a &lt;a href=&quot;https://www.nature.com/articles/s42005-019-0145-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;few hundreds of W/(m K)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Figure 2 of &lt;a href=&quot;https://doi.org/10.1016/j.rinp.2021.103894&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; gives values similar to yours for the Airebo potential:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/2l6wI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2l6wI.png&quot; alt=&quot;Thermal conductivity as a function of temperature for different models.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="735" LastActivityDate="2023-04-04T19:44:47.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10676" PostTypeId="2" ParentId="190" CreationDate="2023-04-04T20:17:42.887" Score="9" Body="&lt;p&gt;Molecular dynamics methods:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;MD (&lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular dynamics&lt;/a&gt;; typically refers to classical molecular dynamics and often atomistic classical molecular dynamics if there is no further qualifications; atomistic means that the basic particle in the model represents an atom)&lt;/li&gt;&#xA;&lt;li&gt;CG (coarse-grain; typically refers to MD simulations with models where a single particle represents multiple atoms)&lt;/li&gt;&#xA;&lt;li&gt;AIMD (&lt;a href=&quot;https://doi.org/10.1073/pnas.0500193102&quot; rel=&quot;nofollow noreferrer&quot;&gt;ab initio molecular dynamics&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;QM/MM (&lt;a href=&quot;https://en.wikipedia.org/wiki/QM/MM&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular mechanics/quantum mechanics&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;PME (&lt;a href=&quot;https://en.wikipedia.org/wiki/Ewald_summation&quot; rel=&quot;nofollow noreferrer&quot;&gt;particle mesh Ewald&lt;/a&gt;; an approximation used to efficiently calculate infinite range electrostatic interactions over a periodic cell)&lt;/li&gt;&#xA;&lt;li&gt;MM-PBSA (&lt;a href=&quot;https://doi.org/10.1517/17460441.2015.1032936&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular mechanics, Poisson-Boltzmann, surface area&lt;/a&gt;; a method to approximate solvation free energies)&lt;/li&gt;&#xA;&lt;li&gt;MM-GBSA (&lt;a href=&quot;https://doi.org/10.1517/17460441.2015.1032936&quot; rel=&quot;nofollow noreferrer&quot;&gt;molecular mechanics, generalized Born, surface area&lt;/a&gt;; similar to MM-PBSA, but uses the generalized Born approximation)&lt;/li&gt;&#xA;&lt;li&gt;CV (collective variable; some collective function of the underlying particle coordinates, which are usually their Cartesian spatial coordinates)&lt;/li&gt;&#xA;&lt;li&gt;PES (potential energy surface)&lt;/li&gt;&#xA;&lt;li&gt;MCMC (&lt;a href=&quot;https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo&quot; rel=&quot;nofollow noreferrer&quot;&gt;Markov chain Monte Carlo&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;GCMC (Grand canonical Monte Carlo; used for constant chemical potential ensemble simulations)&lt;/li&gt;&#xA;&lt;li&gt;FEP (&lt;a href=&quot;https://en.wikipedia.org/wiki/Free_energy_perturbation&quot; rel=&quot;nofollow noreferrer&quot;&gt;free energy perturbation&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;TI (&lt;a href=&quot;https://en.wikipedia.org/wiki/Thermodynamic_integration&quot; rel=&quot;nofollow noreferrer&quot;&gt;thermodynamic integration&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;TRE (&lt;a href=&quot;https://en.wikipedia.org/wiki/Parallel_tempering&quot; rel=&quot;nofollow noreferrer&quot;&gt;temperature replica exchange&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;HRE (Hamiltonian replica exchange)&lt;/li&gt;&#xA;&lt;li&gt;PMF (&lt;a href=&quot;https://en.wikipedia.org/wiki/Potential_of_mean_force&quot; rel=&quot;nofollow noreferrer&quot;&gt;potential of mean force&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;US (umbrella sampling; a static distribution-based enhanced sampling scheme)&lt;/li&gt;&#xA;&lt;li&gt;WHAM (&lt;a href=&quot;http://www.alchemistry.org/wiki/Weighted_Histogram_Analysis_Method&quot; rel=&quot;nofollow noreferrer&quot;&gt;Weighted Histogram Analysis Method&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;REUS (replica exchange umbrella sampling)&lt;/li&gt;&#xA;&lt;li&gt;MTD, METAD, MetaD (&lt;a href=&quot;https://en.wikipedia.org/wiki/Metadynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;metadynamics&lt;/a&gt;; a dynamic potential-based enhanced sampling scheme)&lt;/li&gt;&#xA;&lt;li&gt;ABF (adaptive biasing force; a dynamic force-based enhanced sampling scheme)&lt;/li&gt;&#xA;&lt;li&gt;BAR (&lt;a href=&quot;https://en.wikipedia.org/wiki/Bennett_acceptance_ratio&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bennett acceptance ratio&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;MBAR (&lt;a href=&quot;http://www.alchemistry.org/wiki/Multistate_Bennett_Acceptance_Ratio&quot; rel=&quot;nofollow noreferrer&quot;&gt;Multistate Bennett acceptance ratio&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;MLP (machine learning potential)&lt;/li&gt;&#xA;&lt;li&gt;SMD (steered molecular dynamics)&lt;/li&gt;&#xA;&lt;li&gt;MSM (&lt;a href=&quot;https://doi.org/10.1021/jacs.7b12191&quot; rel=&quot;nofollow noreferrer&quot;&gt;Markov state model&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="735" LastEditorUserId="735" LastEditDate="2023-04-05T14:08:54.367" LastActivityDate="2023-04-05T14:08:54.367" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10677" PostTypeId="1" CreationDate="2023-04-05T03:04:46.067" Score="6" ViewCount="133" Body="&lt;p&gt;I'm kinda new to Pyscf and was wondering if there is a way to do non-orthogonal CI calculations with it. I would appreciate any help.&lt;/p&gt;&#xA;" OwnerUserId="6974" LastEditorUserId="5" LastEditDate="2023-10-12T16:21:18.287" LastActivityDate="2023-10-21T16:05:53.553" Title="Has non-orthogonal CI (NOCI) been implemented in PySCF?" Tags="|quantum-chemistry|electronic-structure|ab-initio-calculations|pyscf|configuration-interaction|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10678" PostTypeId="1" CreationDate="2023-04-05T09:37:30.897" Score="6" ViewCount="77" Body="&lt;p&gt;I have been studying the possible methods for basis set optimizations. One notable paper is &amp;quot;Energy-optimized GTO basis sets for LCAO Calculations. A Gradient Approach&amp;quot; by Knut Faegri Jr. and Jan Almlof (&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.540070403&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;). In it, they define and use an approach which involves a transformation &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; decomposed as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T = \exp(X) \exp(Y) \tag{1}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\exp(X)$&lt;/span&gt; is a unitary transformation and &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; is an anti-Hermitian matrix. However, the paper does not go into detail about how &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; can be obtained and used in an implementation of the algorithm. Additionally, a paper which they cite, &amp;quot;Molecular properties from perturbation theory: A Unified treatment of energy derivatives&amp;quot; by Jan Almlöf and Peter R. Taylor (&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.560270610&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;) provides little further detail, by defining &lt;span class=&quot;math-container&quot;&gt;$U = \exp(X)$&lt;/span&gt;, but not providing details how &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; can be calculated here. Does anyone have a good reference for this method, or is able to provide more background on the definitions which are missing?&lt;/p&gt;&#xA;" OwnerUserId="156" LastEditorUserId="5" LastEditDate="2023-04-07T02:48:00.170" LastActivityDate="2023-05-04T20:11:36.720" Title="What is the X in Almlöf and Taylor's &quot;Unified treatment of energy derivatives?&quot;" Tags="|quantum-chemistry|mathematical-modeling|basis-sets|optimization|derivations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10679" PostTypeId="1" AcceptedAnswerId="10681" CreationDate="2023-04-05T15:23:44.230" Score="6" ViewCount="567" Body="&lt;p&gt;I performed a vc-relax calculation with hybrid functional on a 2 atoms material  using the command &lt;code&gt;mpirun -np 16 --oversubscribe 'directory/qe/pw.x' -in vc-relax.in &amp;gt; vc-relax.out&lt;/code&gt;. It's been 6 hours now since the code is running and still didn't finish yet.&lt;/p&gt;&#xA;&lt;p&gt;I want to know if my simulation is working properly or there is something wrong with it. Is there a way to know how much time a simulation will take?&lt;/p&gt;&#xA;&lt;p&gt;I extracted two separated parts of my output file here.&lt;/p&gt;&#xA;&lt;p&gt;-Part 1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Dense  grid:    50701 G-vectors     FFT dimensions: (  54,  54,  54)&#xA;&#xA;     Dynamical RAM for                 wfc:       0.11 MB&#xA;&#xA;     Dynamical RAM for     wfc (w. buffer):       1.84 MB&#xA;&#xA;     Dynamical RAM for                 EXX:     380.85 MB&#xA;&#xA;     Dynamical RAM for           str. fact:       0.10 MB&#xA;&#xA;     Dynamical RAM for           local pot:       0.00 MB&#xA;&#xA;     Dynamical RAM for          nlocal pot:       0.22 MB&#xA;&#xA;     Dynamical RAM for                qrad:       6.86 MB&#xA;&#xA;     Dynamical RAM for          rho,v,vnew:       0.41 MB&#xA;&#xA;     Dynamical RAM for               rhoin:       0.14 MB&#xA;&#xA;     Dynamical RAM for            rho*nmix:       0.77 MB&#xA;&#xA;     Dynamical RAM for           G-vectors:       0.21 MB&#xA;&#xA;     Dynamical RAM for          h,s,v(r/c):       0.06 MB&#xA;&#xA;     Dynamical RAM for          &amp;lt;psi|beta&amp;gt;:       0.01 MB&#xA;&#xA;     Dynamical RAM for                 psi:       0.22 MB&#xA;&#xA;     Dynamical RAM for                hpsi:       0.22 MB&#xA;&#xA;     Dynamical RAM for      wfcinit/wfcrot:       0.24 MB&#xA;&#xA;     Estimated static dynamical RAM per process &amp;gt;     391.22 MB&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;     392.49 MB&#xA;&#xA;     Estimated total dynamical RAM &amp;gt;       6.13 GB&#xA;&#xA;     Initial potential from superposition of free atoms&#xA;&#xA;     starting charge      35.9998, renormalised to      36.0000&#xA;     Starting wfcs are   19 randomized atomic wfcs&#xA;&#xA;     total cpu time spent up to now is        0.6 secs&#xA;&#xA;     Self-consistent Calculation&#xA;&#xA;     iteration #  1     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            39 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12030 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  1.00E-02,  avg # of iterations =  2.0&#xA;&#xA;     Threshold (ethr) on eigenvalues was too large:&#xA;     Diagonalizing with lowered threshold&#xA;&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            40 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12036 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.86E-04,  avg # of iterations =  1.1&#xA;&#xA;     total cpu time spent up to now is        1.6 secs&#xA;&#xA;     total energy              =    -567.82636984 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.28065174 Ry&#xA;&#xA;     iteration #  2     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            41 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12015 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.80E-04,  avg # of iterations =  1.1&#xA;&#xA;     total cpu time spent up to now is        2.2 secs&#xA;&#xA;     total energy              =    -567.76398782 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.13999925 Ry&#xA;&#xA;     iteration #  3     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            41 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12044 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  3.89E-04,  avg # of iterations =  2.1&#xA;&#xA;     total cpu time spent up to now is        2.9 secs&#xA;&#xA;     total energy              =    -567.79592707 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00815880 Ry&#xA;&#xA;     iteration #  4     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            41 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12069 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  2.27E-05,  avg # of iterations =  2.1&#xA;&#xA;     total cpu time spent up to now is        3.4 secs&#xA;&#xA;     total energy              =    -567.79503173 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00477159 Ry&#xA;&#xA;     iteration #  5     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            41 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12069 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  1.33E-05,  avg # of iterations =  2.2&#xA;&#xA;     total cpu time spent up to now is        4.0 secs&#xA;&#xA;     total energy              =    -567.79436235 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00667744 Ry&#xA;&#xA;     iteration #  6     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12091 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  1.33E-05,  avg # of iterations =  2.1&#xA;&#xA;     total cpu time spent up to now is        4.6 secs&#xA;&#xA;     total energy              =    -567.79518241 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00031137 Ry&#xA;&#xA;     iteration #  7     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12089 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  8.65E-07,  avg # of iterations =  2.2&#xA;&#xA;     total cpu time spent up to now is        5.1 secs&#xA;&#xA;     total energy              =    -567.79532210 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00014763 Ry&#xA;&#xA;     iteration #  8     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12088 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  4.10E-07,  avg # of iterations =  3.3&#xA;&#xA;     total cpu time spent up to now is        5.7 secs&#xA;&#xA;     total energy              =    -567.79490852 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00143778 Ry&#xA;&#xA;     iteration #  9     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12086 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  4.10E-07,  avg # of iterations =  3.1&#xA;&#xA;     total cpu time spent up to now is        6.6 secs&#xA;&#xA;     total energy              =    -567.79517589 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00002797 Ry&#xA;&#xA;     iteration # 10     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12054 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.77E-08,  avg # of iterations =  3.2&#xA;&#xA;     total cpu time spent up to now is        7.3 secs&#xA;&#xA;     total energy              =    -567.79517480 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00006803 Ry&#xA;&#xA;     iteration # 11     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12053 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.77E-08,  avg # of iterations =  2.0&#xA;&#xA;     total cpu time spent up to now is        8.1 secs&#xA;&#xA;     total energy              =    -567.79516053 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00002961 Ry&#xA;&#xA;     iteration # 12     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12085 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.77E-08,  avg # of iterations =  3.0&#xA;&#xA;     total cpu time spent up to now is        8.8 secs&#xA;&#xA;     total energy              =    -567.79517153 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000876 Ry&#xA;&#xA;     iteration # 13     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12084 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  2.43E-08,  avg # of iterations =  2.0&#xA;&#xA;     total cpu time spent up to now is        9.3 secs&#xA;&#xA;     total energy              =    -567.79517144 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000216 Ry&#xA;&#xA;     iteration # 14     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12084 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  6.00E-09,  avg # of iterations =  2.1&#xA;&#xA;     total cpu time spent up to now is        9.9 secs&#xA;&#xA;     total energy              =    -567.79517161 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000034 Ry&#xA;&#xA;     iteration # 15     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12084 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  9.49E-10,  avg # of iterations =  1.3&#xA;&#xA;     total cpu time spent up to now is       10.6 secs&#xA;&#xA;     total energy              =    -567.79517158 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000025 Ry&#xA;&#xA;     iteration # 16     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12084 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  6.98E-10,  avg # of iterations =  1.8&#xA;&#xA;     total cpu time spent up to now is       11.1 secs&#xA;&#xA;     total energy              =    -567.79517154 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000011 Ry&#xA;&#xA;     iteration # 17     ecut=   100.00 Ry     beta= 0.10&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            42 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         12084 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  2.92E-10,  avg # of iterations =  2.5&#xA;&#xA;     total cpu time spent up to now is       12.3 secs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;-Part 2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;     Using ACE for calculation of exact exchange&#xA;&#xA;!!   total energy              =    -567.16587258 Ry&#xA;     Harris-Foulkes estimate   =    -567.16587258 Ry&#xA;     est. exchange err (dexx)  =          2.5E-09 Ry&#xA;     - averaged Fock potential =      24.73517817 Ry&#xA;     + Fock energy (ACE)       =     -12.36762662 Ry&#xA;&#xA;     EXX self-consistency reached&#xA;&#xA;     Forces acting on atoms (cartesian axes, Ry/au):&#xA;&#xA;     atom    1 type  2   force =     0.00000000    0.00000000    0.00000000&#xA;     atom    2 type  1   force =     0.00000000    0.00000000    0.00000000&#xA;     The non-local contrib.  to forces&#xA;     atom    1 type  2   force =     0.00000000    0.00000000    0.00000000&#xA;     atom    2 type  1   force =     0.00000000    0.00000000    0.00000000&#xA;     The ionic contribution  to forces&#xA;     atom    1 type  2   force =    -0.00000000   -0.00000000   -0.00000000&#xA;     atom    2 type  1   force =    -0.00000000   -0.00000000    0.00000000&#xA;     The local contribution  to forces&#xA;     atom    1 type  2   force =    -0.00000000    0.00000000   -0.00000000&#xA;     atom    2 type  1   force =    -0.00000000   -0.00000000   -0.00000000&#xA;     The core correction contribution to forces&#xA;     atom    1 type  2   force =     0.00000000    0.00000000    0.00000000&#xA;     atom    2 type  1   force =     0.00000000    0.00000000    0.00000000&#xA;     The Hubbard contrib.    to forces&#xA;     atom    1 type  2   force =     0.00000000    0.00000000    0.00000000&#xA;     atom    2 type  1   force =     0.00000000    0.00000000    0.00000000&#xA;     The SCF correction term to forces&#xA;     atom    1 type  2   force =     0.00000000    0.00000000   -0.00000000&#xA;     atom    2 type  1   force =     0.00000000   -0.00000000   -0.00000000&#xA;&#xA;     Total force =     0.000000     Total SCF correction =     0.000000&#xA;&#xA;&#xA;     Computing stress (Cartesian axis) and pressure&#xA;&#xA;          total   stress  (Ry/bohr**3)                   (kbar)     P=      -27.97&#xA;  -0.00019011   0.00000000   0.00000000          -27.97        0.00        0.00&#xA;   0.00000000  -0.00019011  -0.00000000            0.00      -27.97       -0.00&#xA;   0.00000000  -0.00000000  -0.00019011            0.00       -0.00      -27.97&#xA;&#xA;     kinetic stress (kbar)  68348.60     -0.00     -0.00&#xA;                               -0.00  68348.60      0.00&#xA;                               -0.00      0.00  68348.60&#xA;&#xA;     local   stress (kbar) -12153.28     -0.00     -0.00&#xA;                               -0.00 -12153.28     -0.00&#xA;                               -0.00     -0.00 -12153.28&#xA;&#xA;     nonloc. stress (kbar) -38015.15      0.00     -0.00&#xA;                               -0.00 -38015.15      0.00&#xA;                                0.00      0.00 -38015.15&#xA;&#xA;     hartree stress (kbar)  28570.52      0.00     -0.00&#xA;                                0.00  28570.52     -0.00&#xA;                               -0.00     -0.00  28570.52&#xA;&#xA;     exc-cor stress (kbar)  -5191.68      0.00      0.00&#xA;                                0.00  -5191.68     -0.00&#xA;                                0.00     -0.00  -5191.68&#xA;&#xA;     corecor stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;     ewald   stress (kbar) -39936.83      0.00      0.00&#xA;                                0.00 -39936.83     -0.00&#xA;                                0.00     -0.00 -39936.83&#xA;&#xA;     hubbard stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;     DFT-D   stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;     XDM     stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;     dft-nl  stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;     TS-vdW  stress (kbar)      0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;&#xA;                                0.00      0.00      0.00&#xA;                                0.00      0.00      0.00&#xA;&#xA;&#xA;                                0.00      0.00      0.00&#xA;&#xA;     EXX     stress (kbar)  -1650.14     -0.00     -0.00&#xA;                               -0.00  -1650.14      0.00&#xA;                               -0.00      0.00  -1650.14&#xA;&#xA;&#xA;&#xA;     BFGS Geometry Optimization&#xA;     Energy error            =      0.0E+00 Ry&#xA;     Gradient error          =      0.0E+00 Ry/Bohr&#xA;     Cell gradient error     =      2.8E+01 kbar&#xA;&#xA;     number of scf cycles    =   1&#xA;     number of bfgs steps    =   0&#xA;&#xA;     enthalpy           new  =    -567.1658725777 Ry&#xA;&#xA;     new trust radius        =       0.0184108950 bohr&#xA;     Message from routine volume:&#xA;     axis vectors are left-handed&#xA;     new conv_thr            =       0.0000000100 Ry&#xA;&#xA;     new unit-cell volume =    369.83860 a.u.^3 (    54.80443 Ang^3 )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;-This is a part extracted from my input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA; ...&#xA;  pseudo_dir='.',&#xA;  verbosity='high',&#xA;  tprnfor=.true.,&#xA;  tstress=.true.,&#xA;  etot_conv_thr =1e-8&#xA;  forc_conv_thr =1e-7&#xA;&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ....&#xA;  input_dft='pbe0',&#xA;  nqx1 = 6, nqx2 =6, nqx3 =6,&#xA;  x_gamma_extrapolation = .true.&#xA;  exxdiv_treatment = 'gygi-baldereschi'&#xA;  exx_fraction = 0.25&#xA;  !ecutfock=100&#xA;&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr=1d-08,&#xA;  mixing_beta=0.1d0,&#xA;  electron_maxstep = 3000&#xA;  mixing_mode = 'plain' &#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;  ion_dynamics='bfgs'&#xA;/&#xA;&amp;amp;CELL&#xA;  cell_dynamics='bfgs'&#xA;  press=0.d0,&#xA;  press_conv_thr=0.2d0&#xA;/&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS: The &lt;code&gt;...&lt;/code&gt;  means that there is text there also&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-04-06T09:24:47.733" LastActivityDate="2023-04-07T06:20:53.487" Title="How can I predict the time of a simulation using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|software|software-recommendations|geometry-optimization|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10680" PostTypeId="1" CreationDate="2023-04-05T16:43:24.697" Score="5" ViewCount="90" Body="&lt;p&gt;Hexagonal Boron Nitride (h-BN) is a promising material for Quantum technologies, see &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.nanolett.1c02495&quot; rel=&quot;nofollow noreferrer&quot;&gt;[1]&lt;/a&gt;. I want to perform a plasmonic simulation in COMSOL to replicate this paper. But I am not able to find any support for this type of simulation, where NV centers are considered as dipoles whose simulations are studied to some extent.&lt;/p&gt;&#xA;&lt;p&gt;Is there any relevant materials explaining how these type of &lt;a href=&quot;https://www.comsol.com/paper/plasmon-enhanced-fluorescence-characteristics-government-by-selecting-the-right-64931&quot; rel=&quot;nofollow noreferrer&quot;&gt;simulations&lt;/a&gt; can be performed? I am open to anything that is done on Lumerical and don't need to specifically use COMSOL.&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Gao, X.; Jiang, B.; Llacsahuanga Allcca, A. E.; Shen, K.; Sadi, M. A.; Solanki, A. B.; Ju, P.; Xu, Z.; Upadhyaya, P.; Chen, Y. P.; Bhave, S. A.; Li, T. High-Contrast Plasmonic-Enhanced Shallow Spin Defects in Hexagonal Boron Nitride for Quantum Sensing. Nano Letters, 2021, 21, 7708–7714. &lt;a href=&quot;https://doi.org/10.1021/acs.nanolett.1c02495&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acs.nanolett.1c02495&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6976" LastEditorUserId="7" LastEditDate="2023-04-06T14:40:51.107" LastActivityDate="2023-04-10T15:53:45.690" Title="Is it possible to model hBN spin defects/plasmons coupling in COMSOL/Lumerical" Tags="|quantum-mechanics|spin|plasmonics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10681" PostTypeId="2" ParentId="10679" CreationDate="2023-04-05T16:48:03.740" Score="5" Body="&lt;p&gt;&lt;strong&gt;TL;DR&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;There were a few issues with the input file and the way OP was running the code.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Longer Answer&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;OP had been using --oversubscribe flag hoping to use all the 16 virtual processors available on the laptop. Instead, OP needed to use&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpiexec -np 8 pw.x -in inputfile.in &amp;gt; outputfile.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This ensures that all the 8 available physical cores are used for the calculation, and you are not throwing more that what the cores can handle at it. This point was reiterated by Phil Hasnip in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10679/how-can-i-predict-the-time-of-a-simulation-using-quantum-espresso/10681?noredirect=1#comment22890_10681&quot;&gt;this&lt;/a&gt; comment.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;A quick look at the input file (which was shared in chat) showed that there were a few issues with the input file, particularly with the unit cell vectors and the atomic positions. To check that, I downloaded the cif file for CuI from &lt;a href=&quot;https://materialsproject.org/materials/mp-22895&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and started a vc-relax run. I was able to get the calculation to complete 2 geometry optimization steps in 15 minutes (which is an improvement from what OP reported).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-04-07T06:20:53.487" LastActivityDate="2023-04-07T06:20:53.487" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10682" PostTypeId="1" CreationDate="2023-04-06T05:42:18.563" Score="3" ViewCount="122" Body="&lt;h2&gt;Context&lt;/h2&gt;&#xA;&lt;p&gt;I am doing a SCF calculation on Ni-DOBDC (metal-organic framework). I expect the Ni centres to be d8 high spin, so two unpaired electrons. The metal centres are ferromagnetic within a 1D chain but antiferromagnetic between chains. My spin polarised SCF calculation agrees with the ferromagnetic and antiferromagnetic ordering.&lt;/p&gt;&#xA;&lt;p&gt;However the magnetization on each Nickel centre is greater than I would expect, at about -/+ 1.45 compared to 1.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Magnetic moment per site  (integrated on atomic sphere of radius R)&#xA;     atom   1 (R=0.032)  charge= 15.5009  magn=  1.4481&#xA;     atom   2 (R=0.032)  charge= 15.5011  magn= -1.4480&#xA;     atom   3 (R=0.032)  charge= 15.5005  magn= -1.4485&#xA;     atom   4 (R=0.032)  charge= 15.5007  magn=  1.4483&#xA;     atom   5 (R=0.032)  charge= 15.5007  magn= -1.4483&#xA;     atom   6 (R=0.032)  charge= 15.5004  magn=  1.4485&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also calculated the Lodwin charges using projwfc.x and get a similar result.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Atom #   1: total charge =  17.5682, s =  2.4098, p =  6.7856, d =  8.3728,&#xA;                 spin up      =   9.5464, s =  1.2187,&#xA;                 spin up      =   9.5464, p =  3.4012, pz=  1.1357, px=  1.1264, py=  1.1391,&#xA;                 spin up      =   9.5464, d =  4.9266, dz2=  0.9916, dxz=  0.9829, dyz=  0.9802, dx2-y2=  0.9860, dxy=  0.9858,&#xA;                 spin down    =   8.0218, s =  1.1911,&#xA;                 spin down    =   8.0218, p =  3.3845, pz=  1.1348, px=  1.1136, py=  1.1360,&#xA;                 spin down    =   8.0218, d =  3.4462, dz2=  0.8585, dxz=  0.5682, dyz=  0.6009, dx2-y2=  0.7357, dxy=  0.6829,&#xA;                 polarization =   1.5246, s =  0.0275, p =  0.0167, d =  1.4803,&#xA;     Atom #   2: total charge =  17.5685, s =  2.4098, p =  6.7857, d =  8.3730,&#xA;                 spin up      =   8.0220, s =  1.1911,&#xA;                 spin up      =   8.0220, p =  3.3845, pz=  1.1348, px=  1.1136, py=  1.1360,&#xA;                 spin up      =   8.0220, d =  3.4464, dz2=  0.8585, dxz=  0.5682, dyz=  0.6009, dx2-y2=  0.7357, dxy=  0.6830,&#xA;                 spin down    =   9.5465, s =  1.2187,&#xA;                 spin down    =   9.5465, p =  3.4012, pz=  1.1357, px=  1.1264, py=  1.1391,&#xA;                 spin down    =   9.5465, d =  4.9266, dz2=  0.9916, dxz=  0.9829, dyz=  0.9802, dx2-y2=  0.9860, dxy=  0.9858,&#xA;                 polarization =  -1.5245, s = -0.0275, p = -0.0167, d = -1.4802,&#xA;     Atom #   3: total charge =  17.5679, s =  2.4098, p =  6.7856, d =  8.3724,&#xA;                 spin up      =   8.0214, s =  1.1911,&#xA;                 spin up      =   8.0214, p =  3.3845, pz=  1.1348, px=  1.1556, py=  1.0940,&#xA;                 spin up      =   8.0214, d =  3.4458, dz2=  0.8585, dxz=  0.4438, dyz=  0.7252, dx2-y2=  0.5423, dxy=  0.8760,&#xA;                 spin down    =   9.5464, s =  1.2187,&#xA;                 spin down    =   9.5464, p =  3.4012, pz=  1.1357, px=  1.1543, py=  1.1112,&#xA;                 spin down    =   9.5464, d =  4.9266, dz2=  0.9916, dxz=  0.9812, dyz=  0.9820, dx2-y2=  0.9840, dxy=  0.9878,&#xA;                 polarization =  -1.5250, s = -0.0275, p = -0.0167, d = -1.4807,&#xA;     Atom #   4: total charge =  17.5681, s =  2.4098, p =  6.7856, d =  8.3727,&#xA;                 spin up      =   9.5464, s =  1.2187,&#xA;                 spin up      =   9.5464, p =  3.4012, pz=  1.1357, px=  1.1176, py=  1.1479,&#xA;                 spin up      =   9.5464, d =  4.9266, dz2=  0.9916, dxz=  0.9806, dyz=  0.9825, dx2-y2=  0.9877, dxy=  0.9841,&#xA;                 spin down    =   8.0216, s =  1.1911,&#xA;                 spin down    =   8.0216, p =  3.3845, pz=  1.1348, px=  1.1052, py=  1.1444,&#xA;                 spin down    =   8.0216, d =  3.4461, dz2=  0.8585, dxz=  0.7415, dyz=  0.4275, dx2-y2=  0.8496, dxy=  0.5689,&#xA;                 polarization =   1.5248, s =  0.0275, p =  0.0167, d =  1.4806,&#xA;     Atom #   5: total charge =  17.5681, s =  2.4098, p =  6.7856, d =  8.3727,&#xA;                 spin up      =   8.0216, s =  1.1911,&#xA;                 spin up      =   8.0216, p =  3.3845, pz=  1.1348, px=  1.1052, py=  1.1444,&#xA;                 spin up      =   8.0216, d =  3.4461, dz2=  0.8585, dxz=  0.7415, dyz=  0.4275, dx2-y2=  0.8496, dxy=  0.5689,&#xA;                 spin down    =   9.5465, s =  1.2187,&#xA;                 spin down    =   9.5465, p =  3.4012, pz=  1.1357, px=  1.1176, py=  1.1479,&#xA;                 spin down    =   9.5465, d =  4.9266, dz2=  0.9916, dxz=  0.9806, dyz=  0.9826, dx2-y2=  0.9877, dxy=  0.9841,&#xA;                 polarization =  -1.5248, s = -0.0275, p = -0.0167, d = -1.4806,&#xA;     Atom #   6: total charge =  17.5677, s =  2.4098, p =  6.7856, d =  8.3723,&#xA;                 spin up      =   9.5464, s =  1.2187,&#xA;                 spin up      =   9.5464, p =  3.4012, pz=  1.1357, px=  1.1543, py=  1.1112,&#xA;                 spin up      =   9.5464, d =  4.9266, dz2=  0.9916, dxz=  0.9812, dyz=  0.9820, dx2-y2=  0.9840, dxy=  0.9878,&#xA;                 spin down    =   8.0213, s =  1.1911,&#xA;                 spin down    =   8.0213, p =  3.3844, pz=  1.1348, px=  1.1556, py=  1.0940,&#xA;                 spin down    =   8.0213, d =  3.4457, dz2=  0.8586, dxz=  0.4438, dyz=  0.7251, dx2-y2=  0.5423, dxy=  0.8760,&#xA;                 polarization =   1.5251, s =  0.0275, p =  0.0167, d =  1.4808,&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Question&lt;/h2&gt;&#xA;&lt;p&gt;Is this difference between expected and calculated magnetization (ie. +/- 1.0 vs +/- 1.45) indicative of a problem? And if so what would be the best way to correct?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; the structure has not been relaxed (vc-relax), I want to get the starting magnetization conditions correct before expending alot of compute time.&lt;/p&gt;&#xA;" OwnerUserId="6958" LastEditorUserId="6687" LastEditDate="2023-04-06T07:45:08.223" LastActivityDate="2023-04-06T07:45:08.223" Title="Quantum Espresso magnetization per site" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:48:17.723" ContentLicense="CC BY-SA 4.0" />
  <row Id="10683" PostTypeId="1" CreationDate="2023-04-06T18:17:06.383" Score="7" ViewCount="69" Body="&lt;p&gt;I want to calculate the kinetic diameter of a molecule to estimate if it can fit inside a pore/channel of a microporous material. Do you know any software that would allow me to do this?&lt;/p&gt;&#xA;&lt;p&gt;I've seen a &lt;a href=&quot;https://www.researchgate.net/post/How_can_I_estimate_the_kinetic_diameter_of_a_molecule_from_its_chemical_structure&quot; rel=&quot;noreferrer&quot;&gt;similar question on Researchgate&lt;/a&gt; but they did not arrive at any good conclusion.&lt;/p&gt;&#xA;" OwnerUserId="3401" LastActivityDate="2023-04-06T18:17:06.383" Title="Get kinetic diameter of a molecule" Tags="|molecular-modeling|software-recommendations|" AnswerCount="0" CommentCount="3" ClosedDate="2023-10-13T16:47:56.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="10684" PostTypeId="2" ParentId="10678" CreationDate="2023-04-07T01:23:27.470" Score="6" Body="&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Jan Almlöf and Peter R. Taylor (&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/qua.560270610&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;) provides little further detail, by defining U=exp(X), but not providing details how X can be calculated here.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h1&gt;Answer&lt;/h1&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; is literally defined by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$U = \exp(X)\tag{1},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;so if you want &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt;, you can calculate it by computing a natural logarithm of &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;. Unlike &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; which is defined based on &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, the operator &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; has much more of a &amp;quot;meaning&amp;quot;. This is all explained &lt;a href=&quot;https://i.stack.imgur.com/skQ8c.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;in the same paragraph&lt;/a&gt; from which you found Eq. 1 (which is Eq. 42 in the paper)! If &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; want an explicit expression for &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; in terms of &amp;quot;known&amp;quot; quantities, then I've provided it in Eq. (7) below.&lt;/p&gt;&#xA;&lt;h1&gt;More details&lt;/h1&gt;&#xA;&lt;p&gt;A Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$\hat{H}_0$&lt;/span&gt; is perturbed by &lt;span class=&quot;math-container&quot;&gt;$\hat{V}(\lambda)$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2} \hat{H} = \hat{H}_0 + \hat{V}(\lambda),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which causes the &lt;a href=&quot;https://i.stack.imgur.com/385kH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;unperturbed molecular orbital coefficients &lt;span class=&quot;math-container&quot;&gt;$C_0$&lt;/span&gt;&lt;/a&gt; to get perturbed into &lt;span class=&quot;math-container&quot;&gt;$C(\lambda)$&lt;/span&gt; by the linear transformation &lt;span class=&quot;math-container&quot;&gt;$T(\lambda)$&lt;/span&gt; as stated in Eq. 40 of the paper (Eq. 40 also writes &lt;span class=&quot;math-container&quot;&gt;$C_0$&lt;/span&gt; as having an explicit dependence on &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; but I don't yet see that being necessary):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{3} C(\lambda) = C_0 T(\lambda),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which (Eq. 41 of the paper):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;T(\lambda) = V(\lambda)U(\lambda),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$V(\lambda)$&lt;/span&gt; being explicitly given in terms of the AO overlap matrix &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; in Eq. 43:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;V(\lambda) = \left(C_0^\dagger S(\lambda) C_0\right)^{-1/2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This means that if you have MO coefficients stored in &lt;span class=&quot;math-container&quot;&gt;$C_0$&lt;/span&gt; and you perturb the Hamiltonian by &lt;span class=&quot;math-container&quot;&gt;$\hat{V}(\lambda)$&lt;/span&gt;, the new MO coefficients can be stored in:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C(\lambda) = C_0\left(C_0^\dagger S(\lambda) C_0\right)^{-1/2}U (\lambda),\tag{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;or if you have the MO coefficients before and after the perturbation, then you can obtain &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;U(\lambda) &amp;amp;= \left( \left(C_0^\dagger S(\lambda) C_0\right)^{-1/2}\right)^{-1} C_0^{-1} C(\lambda), \tag{7}\\&#xA;\exp\left(X(\lambda)\right) &amp;amp;\equiv \left( \left(C_0^\dagger S(\lambda) C_0\right)^{-1/2}\right)^{-1} C_0^{-1} C(\lambda), \tag{8}\\&#xA;X(\lambda) &amp;amp;= \ln \left(\left( \left(C_0^\dagger S(\lambda) C_0\right)^{-1/2}\right)^{-1} C_0^{-1} C(\lambda) \right),\tag{9}\\&#xA;X &amp;amp;= \ln \left(\left( \left(C_0^\dagger S C_0\right)^{-1/2}\right)^{-1} C_0^{-1} C \right).\tag{10}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Two more minor notes:&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Eq. 55 of the paper and the paragraph directly before Eq. 53, tell us that in the case of an MCSCF wavefunction, of which HF wavefunctions (which are the only wavefunctions for which &lt;em&gt;&lt;strong&gt;I've&lt;/strong&gt;&lt;/em&gt; seen derivatives with respect to exponents done analytically in the papers up to the year of this Almlöf and Taylor paper) can be considered a &amp;quot;special case&amp;quot;, there is no contribution to &lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}E}{\textrm{d}\lambda}$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}X}{\textrm{d}\lambda}$&lt;/span&gt; so setting &lt;span class=&quot;math-container&quot;&gt;$\frac{\textrm{d}E}{\textrm{d}\lambda} = 0$&lt;/span&gt; can be done by Eq. 56.&lt;/li&gt;&#xA;&lt;li&gt;The paper says &amp;quot;Most  previous  treatments (see, e.g., Ref. 9) have handled  the MO orthonormality problem  using Lagrange multipliers. This approach -- which must, of course, ultimately  yield  the same formulas as the present scheme -- is  discussed  briefly in Sec. V&amp;quot;, so if you can get access to Ref. 9 which is &amp;quot;P. Pulay, in Applications of molecular Electronic Structure Theory, H. F. Schaefer 111, Ed.  (Plenum, New York, 1977)&amp;quot;, then you might be able to see all of this from another perspective. &lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-05-04T20:11:36.720" LastActivityDate="2023-05-04T20:11:36.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10685" PostTypeId="1" CreationDate="2023-04-08T01:22:52.290" Score="2" ViewCount="52" Body="&lt;p&gt;I'm planning to purchase GaussView and install it on iMacs. Apple is known for messing up apps when it makes upgrades. I used GaussView a while ago and have not followed updates on these issues. Are the current GaussView and iMacs (hardware and OS) compatible?&lt;/p&gt;&#xA;" OwnerUserId="4450" LastEditorUserId="5" LastEditDate="2023-04-08T01:23:59.427" LastActivityDate="2023-04-08T01:23:59.427" Title="GaussView and iMac" Tags="|apple-operating-system|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-13T01:55:27.937" ContentLicense="CC BY-SA 4.0" />
  <row Id="10686" PostTypeId="1" CreationDate="2023-04-08T12:46:19.817" Score="5" ViewCount="47" Body="&lt;p&gt;I want to reproduce the calculation procedure of density fitting in PySCF. I know how to get the 2c2e/3c2e integrals matrix/tensor with &lt;span class=&quot;math-container&quot;&gt;$1/r_{12}$&lt;/span&gt; kernel by using &lt;code&gt;mol.intor('int2e')&lt;/code&gt; and &lt;code&gt;df.incore.aux_e2(mol, auxmol)&lt;/code&gt;. But it seems that the &lt;span class=&quot;math-container&quot;&gt;$\text{erf} (r_{12})/r_{12}$&lt;/span&gt; kernel was not supported yet in two methods mentioned above. Is there a way to get the 2c2e/3c2e integrals matrix/tensor using the erf kernel?&lt;/p&gt;&#xA;" OwnerUserId="6990" LastEditorUserId="6990" LastEditDate="2023-04-09T04:45:12.960" LastActivityDate="2023-04-09T04:45:12.960" Title="How can I get 2c2e and 3c2e integrals using the erf kernel in PySCF?" Tags="|pyscf|integrals|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-20T01:33:26.563" ContentLicense="CC BY-SA 4.0" />
  <row Id="10687" PostTypeId="1" AcceptedAnswerId="10689" CreationDate="2023-04-08T16:19:43.343" Score="7" ViewCount="196" Body="&lt;h1&gt;Introduction (analogy to basis set database files)&lt;/h1&gt;&#xA;&lt;p&gt;Many programs have a database of basis sets stored in a file such as the following (so that users can just specify in their input file something like &lt;code&gt;H:STO-2G&lt;/code&gt; to get the &lt;code&gt;STO-2G&lt;/code&gt; basis set for the H atom):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;H:STO-2G&#xA;# STO-2G Minimal Basis (2 functions/AO)&#xA;&#xA;0.1309756377D+01 0.2331359749D+00 &#xA;&#xA;0.4301284983D+00 &#xA;0.6789135305D+00 &#xA;&#xA;HE:STO-2G&#xA;# STO-2G Minimal Basis (2 functions/AO)&#xA;&#xA;0.2432879285D+01 0.4330512863D+00 &#xA;&#xA;0.4301284983D+00 &#xA;0.6789135305D+00 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;A proposed format for a geometry database file&lt;/h1&gt;&#xA;&lt;p&gt;My group has made something similar for geometries: a database with about 62,000 geometries, and interfaces to PySCF, OpenMolcas, Psi4, CFOUR, Dalton, and MRCC (so far) so that users can just put something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;geometry = C33H53N5O9:GW5000.v2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in the program's input file to use v2 (version 2)  of the  GW5000 geometry of the &lt;span class=&quot;math-container&quot;&gt;$\ce{C33H53N5O9}$&lt;/span&gt; molecule, rather than copying-and-pasting the 100-line XYZ file with the risk of human error and making the input file maybe 10x longer than it needs to be!&lt;/p&gt;&#xA;&lt;p&gt;The current format for the geometry database file is such as that each entry looks as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NAME = C33H53N5O9:GW5000.v0&#xA;# Number of atoms: 100&#xA;# Common name: Unknown&#xA;# InChI=1S/C33H53N5O9/c1-20(47-29(2,3)4)22(23(39)35-31(7,8)25(41)37-33(11,12)27(43)45-13)34-24(40)30(5,6)36-26(42)32(9,10)38-28(44)46-19-21-17-15-14-16-18-21/h14-18,20,22H,19H2,1-13H3,(H,34,40)(H,35,39)(H,36,42)(H,37,41)(H,38,44)/t20-,22+/m1/s1&#xA;&#xA;# SMILES : COC(=O)C(NC(=O)C(NC(=O)[C@H]([C@H](OC(C)(C)C)C)NC(=O)C(NC(=O)C(NC(=O)OCc1ccccc1)(C)C)(C)C)(C)C)(C)C&#xA;&#xA;# SMARTS: Unknown&#xA;&#xA;# Reference code: QIXLEO&#xA;# CAS number: Unknown&#xA;# Source paper: https://doi.org/10.1038/s41597-020-0385-y (Stuke et al.)&#xA;# Source data host: https://doi.org/10.14459/2019mp1507656&#xA;# Source download link: https://dataserv.ub.tum.de/index.php/s/m1507656 , Filename: df_5k.json&#xA;# Source method: def2-TZVPP/PBE+TS-vdW&#xA;# Properties: Number of electrons = 123, Spin multiplicity = Singlet, Electronic state = Ground, Charge = 0, Point group = Unknown&#xA;# Notes: IR spectroscopy has been done in (2010) Dehghany M, et al. &#xA;# Date first added:   2023-02-04 14:14:48 (by Walter Kohn Jr.)&#xA;# Date modified:      2023-04-05 12:01:18 (by Walter Kohn Jr.)&#xA;# Date modified:      2023-04-06 19:03:26 (by Nike Dattani)&#xA;# Date last modified: 2023-04-07 03:01:58 (by Nike Dattani)&#xA;&#xA;H      37.13229674      36.52932952      30.63502894 &#xA;H      37.87447083      34.45373990      31.61484874 &#xA;H      38.29175516      34.28685128      29.88425431 &#xA;H      39.43188162      36.70033091      26.00124438 &#xA;C      36.88232957      40.90658315      31.61111721 &#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h4&gt;Parts of the proposed format that &amp;quot;need&amp;quot; to be kept&lt;/h4&gt;&#xA;&lt;p&gt;Since every line that starts with the &lt;code&gt;#&lt;/code&gt; character is a &amp;quot;comment&amp;quot;, we really only need the &lt;code&gt;NAME&lt;/code&gt; and the XYZ lines, but the following information in the &amp;quot;comments&amp;quot; is extremely useful:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;Number of atoms&lt;/code&gt; allows us to quickly find all 30-atom molecules (for example)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Common name&lt;/code&gt; allows us to quickly find all stored geometries for &amp;quot;butane&amp;quot; (for example)&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Source paper&lt;/code&gt; and &lt;code&gt;Source data host&lt;/code&gt; and &lt;code&gt;Source download link&lt;/code&gt;/&lt;code&gt;Filename&lt;/code&gt; are crucial for &amp;quot;reproducibility&amp;quot; and crediting the papers from which certain geometries originate.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;Source method&lt;/code&gt; is &amp;quot;crucial&amp;quot; for reproducibility and it tells us whether it's an experimental geometry from, for example, microwave spectroscopy (quite reliable) or a theoretical geometry from STO-2G/Hartree-Fock (very reliable).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h4&gt;Parts of the proposed format that are more questionable&lt;/h4&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;InChI&lt;/code&gt;,&lt;code&gt;SMILES&lt;/code&gt;,&lt;code&gt;SMARTS&lt;/code&gt;,&lt;code&gt;Reference code&lt;/code&gt;, and &lt;code&gt;CAS number&lt;/code&gt; seem useful, since so many different molecules can have the same chemical formula, and might not have a &amp;quot;common name&amp;quot;. However, it seems that there's so many molecular identifiers, for example &lt;a href=&quot;http://www.chemspider.com/Chemical-Structure.6901.html?rid=514c605f-493b-4673-ad83-44d6734132b1&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; you can see that there's an &amp;quot;EINECS&amp;quot; number, a &amp;quot;Beilstein&amp;quot; number, an &amp;quot;RN&amp;quot; number, an &amp;quot;MDL number&amp;quot;  several &amp;quot;DBID&amp;quot; numbers, and much more that I could include here, including different &amp;quot;types&amp;quot; of SMILES formats. It seems that &lt;em&gt;&lt;strong&gt;at least one specifier in addition to the chemical formula and &amp;quot;common name&amp;quot; must be provided, but which one?&lt;/strong&gt;&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;Date added&lt;/code&gt; and &lt;code&gt;Date modified&lt;/code&gt; comments aren't strictly necessary because the revision history would ideally be visible from GitHub, but it doesn't seem harmful to include this information here (it's not like we have to choose which information to include form dozens of options, as was the case in the previous bullet point). &lt;em&gt;&lt;strong&gt;However, maybe we only need the first &lt;code&gt;Date added&lt;/code&gt; and the last &lt;code&gt;Date modified&lt;/code&gt;?&lt;/strong&gt;&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h4&gt;Parts of the proposed format that I would like to keep, but am not sure how to include them in the best way&lt;/h4&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Some of the &lt;code&gt;Properties&lt;/code&gt; are quite important (e.g. charge, spin, and electronic state), since they tell the user which keywords to use when doing an electronic structure calculation, for example. This information could even go in the &lt;code&gt;NAME&lt;/code&gt; variable, which can really be anything (it doesn't need to be the chemical formula), and &lt;em&gt;&lt;strong&gt;you might even think this would be better than the format I currently have, so I welcome feedback on that.&lt;/strong&gt;&lt;/em&gt; One reason why I included the &amp;quot;number of electrons&amp;quot; was so that I can easily get a rough idea of how hard a calculation with this molecule would be, &lt;em&gt;&lt;strong&gt;but this isn't strictly necessary&lt;/strong&gt;&lt;/em&gt;. The &amp;quot;point group&amp;quot; was included for similar reasons, for example if I wanted to do a study on only linear molecules.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;What format do you think would be best?&lt;/h1&gt;&#xA;&lt;p&gt;If you think any part of my proposed format can be improved (for example, removing unnecessary information, or adding more useful information, or making a change like &lt;code&gt;C33H53N5O9:GW5000.v2&lt;/code&gt; to &lt;code&gt;C33H53N5O9_GW5000.(v2)&lt;/code&gt;), please paste it in a code block!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-04-09T16:19:08.167" LastActivityDate="2023-05-16T16:13:58.883" Title="What would be the preferred format for a geometry database?" Tags="|software|computational-chemistry|one-topic-per-answer|geometry-optimization|databases|" AnswerCount="3" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10688" PostTypeId="1" AcceptedAnswerId="11773" CreationDate="2023-04-09T04:22:40.917" Score="6" ViewCount="244" Body="&lt;p&gt;I am using &lt;code&gt;fix phonon&lt;/code&gt; in LAMMPS to get the phonon dispersion relation, but this requires a post-processing code that takes the generated binary file and produces the phonon dispersion relation. This code is called &lt;code&gt;phana&lt;/code&gt; and I am having trouble compiling it. Is there an alternative tool that can read the binary file generated by &lt;code&gt;fix phonon&lt;/code&gt; and produce the phonon dispersion relation? Can &lt;code&gt;PhonoPy&lt;/code&gt; do that?&lt;/p&gt;&#xA;" OwnerUserId="336" LastActivityDate="2023-10-19T02:22:18.853" Title="Getting the Phonon Dispersion Using fix phonon in LAMMPS" Tags="|lammps|phonopy|phonon-dispersion|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10689" PostTypeId="2" ParentId="10687" CreationDate="2023-04-09T12:10:28.803" Score="4" Body="&lt;p&gt;This answer is now a community wiki.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the parameters in the database file, here are my views:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The first &lt;code&gt;Date added&lt;/code&gt; and the last &lt;code&gt;Date modified&lt;/code&gt; are sufficient since the rest of the file versioning can be obtained from git.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I think it is good for the &lt;code&gt;properties&lt;/code&gt; such as the charge, spin, and electronic state to not be included in the name. It is good for them to be on a separate line since I see them as metadata. If we need them as query parameters to search for some particular characteristics of molecules, then perhaps it is good to have it in the &lt;code&gt;NAME&lt;/code&gt; itself.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Regarding the XYZ information, it would be good to prepend the XYZ coordinates information with a string like : &lt;code&gt;# XYZ Begin&lt;/code&gt; and add a line at the end of the XYZ info like : &lt;code&gt;# XYZ End&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;s = '''NAME = C10H15NO2S2:GW5000.v0&#xA;# Number of atoms: 30&#xA;# Common name: Unknown&#xA;# InChI=1S/C10H15NO2S2/c1-5-8-7(3)15-10(14)11(8)6(2)9(12)13-4/h6H,5H2,1-4H3/t6-/m1/s1&#xA;# SMILES : COC(=O)[C@H](n1c(=S)sc(c1CC)C)C&#xA;# Smarts: Unknown&#xA;# Reference code: FOVWES&#xA;# CAS: Unknown&#xA;# Source paper: https://doi.org/10.1038/s41597-020-0385-y (Stuke et al.)&#xA;# Source data host: https://doi.org/10.14459/2019mp1507656&#xA;# Source download link: https://dataserv.ub.tum.de/index.php/s/m1507656 , Filename: df_5k.json&#xA;# Source method: PBE_TS-vdW&#xA;# Properties: Number of electrons = 46, Spin multiplicity = Singlet, Electronic state = Ground, Charge = 0, Point group = Unknown&#xA;# Date added: 2023-02-05  14:14:48 (Vandan Revanur)&#xA;# Date modified: 2023-04-09 11:35:40.422937 (Vandan Revanur)&#xA;# XYZ Begin&#xA;30&#xA;&#xA;C      37.56022072      46.42557279      47.12244195 &#xA;N      38.41486173      47.34224375      47.69527868 &#xA;C      38.40387895      48.62793964      47.12650724 &#xA;C      37.56283274      48.72707549      46.05929103 &#xA;S      37.27624844      44.86270782      47.60509887 &#xA;C      39.26642677      46.96082591      48.83037942 &#xA;C      38.45126980      46.41549852      50.01494371 &#xA;O      38.86895847      45.59870651      50.80522393 &#xA;O      37.28597863      47.09279152      50.14396759 &#xA;C      36.43011242      46.62401114      51.20431940 &#xA;H      39.69355182      47.89896576      49.21150415 &#xA;H      35.56314436      47.28997420      51.19573739 &#xA;H      36.94702454      46.66765744      52.17066399 &#xA;H      36.12213864      45.59052324      51.00135426 &#xA;H      36.21596648      50.16390411      45.18266298 &#xA;H      37.56492846      49.69470384      44.13523550 &#xA;C      37.28353465      49.90044176      45.17838095 &#xA;C      39.25272587      49.73859624      47.67187517 &#xA;H      37.84704948      50.78361100      45.50151663 &#xA;H      39.19453702      49.75075573      48.77118150 &#xA;H      38.79609693      50.68564642      47.35631688 &#xA;C      40.41180910      46.03181425      48.43355973 &#xA;H      41.24233846      48.80775624      47.54934542 &#xA;H      40.77986133      49.73738376      46.11606557 &#xA;H      40.02347830      45.07764438      48.06231905 &#xA;H      41.04052914      45.83337078      49.30836666 &#xA;H      41.02130010      46.50140795      47.65197806 &#xA;C      40.71890084      49.71107794      47.21170776 &#xA;H      41.26362809      50.57895454      47.60606918 &#xA;# XYZ End'''&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With this one can access the XYZ information of any molecule with the name like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule_name = 'C10H15NO2S2:GW5000.v0'&#xA;p = re.compile(f'(NAME = {molecule_name})(.*?)# XYZ Begin(.*?)# XYZ End', flags=re.DOTALL)&#xA;result = p.search(s)&#xA;&#xA;result.group(3) would output:&#xA;&#xA;&amp;gt;&amp;gt; '\n30\n\nC      37.56022072      46.42557279      47.12244195 \nN      38.41486173      47.34224375      47.69527868 \nC      38.40387895      48.62793964      47.12650724 \nC      37.56283274      48.72707549      46.05929103 \nS      37.27624844      44.86270782      47.60509887 \nC      39.26642677      46.96082591      48.83037942 \nC      38.45126980      46.41549852      50.01494371 \nO      38.86895847      45.59870651      50.80522393 \nO      37.28597863      47.09279152      50.14396759 \nC      36.43011242      46.62401114      51.20431940 \nH      39.69355182      47.89896576      49.21150415 \nH      35.56314436      47.28997420      51.19573739 \nH      36.94702454      46.66765744      52.17066399 \nH      36.12213864      45.59052324      51.00135426 \nH      36.21596648      50.16390411      45.18266298 \nH      37.56492846      49.69470384      44.13523550 \nC      37.28353465      49.90044176      45.17838095 \nC      39.25272587      49.73859624      47.67187517 \nH      37.84704948      50.78361100      45.50151663 \nH      39.19453702      49.75075573      48.77118150 \nH      38.79609693      50.68564642      47.35631688 \nC      40.41180910      46.03181425      48.43355973 \nH      41.24233846      48.80775624      47.54934542 \nH      40.77986133      49.73738376      46.11606557 \nH      40.02347830      45.07764438      48.06231905 \nH      41.04052914      45.83337078      49.30836666 \nH      41.02130010      46.50140795      47.65197806 \nC      40.71890084      49.71107794      47.21170776 \nH      41.26362809      50.57895454      47.60606918 \n'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This XYZ string can be further used downstream with libraries such as rdkit like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;Chem.MolFromXYZBlock(xyz_string)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If we decide to not have XYZ Begin and XYZ End, we can still retrieve the XYZ info using the following regex, which retrieves the XYZ info between the line next after the date modified until the next NAME line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule_name = 'C10H15NO2S2:GW5000.v0'&#xA;p = re.compile(f'(NAME = {molecule_name})(.*?)Date modified:(.*?)\)(.*?)NAME', flags=re.DOTALL)&#xA;result = p.search(s)&#xA;result.group(4)&#xA;&amp;gt;&amp;gt; '\n\nC      37.56022072      46.42557279      47.12244195 \nN      38.41486173      47.34224375      47.69527868 \nC      38.40387895      48.62793964      47.12650724 \nC      37.56283274      48.72707549      46.05929103 \nS      37.27624844      44.86270782      47.60509887 \nC      39.26642677      46.96082591      48.83037942 \nC      38.45126980      46.41549852      50.01494371 \nO      38.86895847      45.59870651      50.80522393 \nO      37.28597863      47.09279152      50.14396759 \nC      36.43011242      46.62401114      51.20431940 \nH      39.69355182      47.89896576      49.21150415 \nH      35.56314436      47.28997420      51.19573739 \nH      36.94702454      46.66765744      52.17066399 \nH      36.12213864      45.59052324      51.00135426 \nH      36.21596648      50.16390411      45.18266298 \nH      37.56492846      49.69470384      44.13523550 \nC      37.28353465      49.90044176      45.17838095 \nC      39.25272587      49.73859624      47.67187517 \nH      37.84704948      50.78361100      45.50151663 \nH      39.19453702      49.75075573      48.77118150 \nH      38.79609693      50.68564642      47.35631688 \nC      40.41180910      46.03181425      48.43355973 \nH      41.24233846      48.80775624      47.54934542 \nH      40.77986133      49.73738376      46.11606557 \nH      40.02347830      45.07764438      48.06231905 \nH      41.04052914      45.83337078      49.30836666 \nH      41.02130010      46.50140795      47.65197806 \nC      40.71890084      49.71107794      47.21170776 \nH      41.26362809      50.57895454      47.60606918 \n\n'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-16T16:13:58.883" LastActivityDate="2023-05-16T16:13:58.883" CommentCount="2" CommunityOwnedDate="2023-05-16T16:13:58.883" ContentLicense="CC BY-SA 4.0" />
  <row Id="10690" PostTypeId="1" AcceptedAnswerId="10704" CreationDate="2023-04-09T21:43:34.510" Score="7" ViewCount="362" Body="&lt;p&gt;I'm calculating the vacancy formation energy of a 3x3x2 supercell of cerium oxide and need to include a Hubbard parameter for the Ce 4f state. However, computing this parameter separately for the large supercell would be very time-consuming due to its size (around 200 atoms). Therefore, I'm wondering if it's feasible to calculate the Hubbard U parameter for the smaller unit cell and use it for the supercell instead. Is this a valid approach or are there any drawbacks to this method?&lt;/p&gt;&#xA;" OwnerUserId="6994" LastEditorUserId="6994" LastEditDate="2023-04-09T21:49:45.160" LastActivityDate="2023-04-10T17:25:56.653" Title="Can you calculate Hubbard U parameter for unit cell and then use it value for supercell/slab?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10691" PostTypeId="2" ParentId="10538" CreationDate="2023-04-09T21:56:19.267" Score="2" Body="&lt;p&gt;You can directly create a supercell using your input file of the optimized unit cell without optimizing the supercell. The optimized structure of the unit cell represents the most stable configuration of the crystal, and you can use this optimized structure as a starting point for creating the supercell.&#xA;Regarding your second question, you can create a CIF file from the SCF output file. For instance, you can open the output file using XCrysDen, save it as .xsf format, and import it into VESTA. From there, you can generate a CIF file.&lt;/p&gt;&#xA;" OwnerUserId="6994" LastEditorUserId="6994" LastEditDate="2023-04-09T22:06:29.267" LastActivityDate="2023-04-09T22:06:29.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10692" PostTypeId="2" ParentId="10690" CreationDate="2023-04-09T22:14:51.310" Score="3" Body="&lt;p&gt;The various methods to calculate the Hubbard U value in a first principles way don’t always give such good agreement with experimental values anyway. If it would be too expensive to calculate it with a first principles way, then you might want to just use a U value from literature, try a range of U values yourself to see the impact on the binding energy, or try a hybrid functional (although there you have to pick the fraction of exact exchange anyway).&lt;/p&gt;&#xA;&lt;p&gt;Using a first principles method to calculate it in the unit cell is a reasonable way to try to do it, but if the supercell has a vacancy that changes the local environment, then in theory the appropriate U value could change.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2023-04-09T22:14:51.310" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10693" PostTypeId="1" CreationDate="2023-04-10T07:55:43.020" Score="10" ViewCount="828" Body="&lt;p&gt;I am looking for a free code for Hartree-Fock calculations in solids especially a code optimized (quite fast) compared to Pyscf which is quite slow and unstable. I do not have any clue to explain why HF so slow in solids compared to molecular systems.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-04-11T07:14:48.913" Title="Free and optimized code for Hartree-Fock calculation in solids" Tags="|software-recommendations|hartree-fock|" AnswerCount="2" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="10695" PostTypeId="2" ParentId="10690" CreationDate="2023-04-10T09:24:11.187" Score="2" Body="&lt;p&gt;Normally this famous U parameter is a correction to reach the localized states  due to the correlations which a one electron system cannot integrate. As a corrective parameter it is very variable and nobody could give the order of magnitude of its variation in a precise way because even your calculation method can affect the order of magnitude converging towards a satisfactory correction. Normally it should not vary so much, but our simulation tools are not perfect.&lt;/p&gt;&#xA;&lt;p&gt;Concerning your question, intuitively by increasing the size of the system there is some delocalization more significant of d states than f and thus the correction is theoretically different. As stated before, nobody will be able to give the deviation rate correctly. Normally you should recalculate the parameter regardless of the size. In some cases using the same parameter can be theoretically a good approximation especially for the 4f states but I guess even more for Lutetium than for Cerium.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-04-10T09:24:11.187" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10696" PostTypeId="2" ParentId="10693" CreationDate="2023-04-10T10:03:38.867" Score="9" Body="&lt;p&gt;&lt;a href=&quot;https://www.quantum-espresso.org/&quot; rel=&quot;noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt; (QE) is a plane wave basis and various types of pseudopotential-based density functional theory (DFT) code. The PWscf package in it can perform both DFT and Hartree-Fock calculations. It is completely free. It also has a nice user forum &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. It is written in Fortran, so it is quite fast and stable too. So it fulfills all your requirement I believe.&lt;/p&gt;&#xA;&lt;p&gt;However, it doesn't have out-of-the-box support for HF calculation, you can perform such calculations with some tweaking as described &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2016-May/035195.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. What I understood is that you have to set the flag &lt;code&gt;exx_fraction=1&lt;/code&gt; in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; namelist of QE input file. Here, by setting &lt;code&gt;exx_fraction=1&lt;/code&gt;, you are treating &lt;em&gt;HF as a hybrid functional with 100% of exchange and 0% of other exchange-correlation contributions&lt;/em&gt;.  In the &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/63325021#63325021&quot;&gt;QE chatroom&lt;/a&gt; of Matter Modeling SE, you will find some example input files with hybrid functional.&lt;/p&gt;&#xA;&lt;p&gt;Note that, as one of the QE authors mentioned &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2009-May/012706.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, plane waves &lt;em&gt;are probably not the most efficient basis set to implement non-local (Fock) exchange&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, see this &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;List of quantum chemistry and solid-state physics software&lt;/a&gt;. Here, you will find links to many codes that have HF capability. Some of them are also available free of charge for academic use such as &lt;a href=&quot;http://www.castep.org/&quot; rel=&quot;noreferrer&quot;&gt;CASTEP&lt;/a&gt;. You can also filter codes from that list that are free, have HF functionality, and use &lt;em&gt;other basis sets than plane waves&lt;/em&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-04-10T10:03:38.867" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10697" PostTypeId="1" CreationDate="2023-04-10T10:40:55.427" Score="3" ViewCount="919" Body="&lt;p&gt;It's been more than a month that I installed Ubuntu 20.04 on a desktop along side with windows (Probably 10 or 11) that was already on the desktop. Now I noticed that the computer boot directly into Ubuntu I checked again and Windows is not appearing in the boot menu. I don't know what happened or how to fix that. I tried some commands that I found in the internet like &lt;code&gt;sudo f-disk -l&lt;/code&gt;  and it displayed that:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;.&#xA;.&#xA;.&#xA;Device          Start        End    Sectors   Size Type&#xA;/dev/sda1        2048     264191     262144   128M Microsoft reserved&#xA;/dev/sda2      264192 1795461119 1795196928   856G Microsoft basic data&#xA;/dev/sda3  3590658048 3591708671    1050624   513M EFI System&#xA;/dev/sda4  3591708672 3907028991  315320320 150.4G Linux filesystem&#xA;/dev/sda5  1795461120 3590658047 1795196928   856G Linux filesystem&#xA;.&#xA;.&#xA;.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;sudo os-prober&lt;/code&gt; is not showing anything&lt;/p&gt;&#xA;&lt;p&gt;How can I fix this issue please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-04-10T11:27:00.163" Title="Why Windows is not showing in the Dual-Boot menu and boot into Ubuntu directly?" Tags="|software|software-recommendations|software-assistance|windows-operating-system|" AnswerCount="1" CommentCount="3" ClosedDate="2023-04-13T12:25:41.033" ContentLicense="CC BY-SA 4.0" />
  <row Id="10698" PostTypeId="2" ParentId="10697" CreationDate="2023-04-10T11:27:00.163" Score="2" Body="&lt;p&gt;You can try this tool to regenerate GRUB :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://help.ubuntu.com/community/Boot-Repair&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://help.ubuntu.com/community/Boot-Repair&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And fix the dual boot. For Windows only :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://social.technet.microsoft.com/wiki/contents/articles/51782.fixing-corrupted-mbr-in-windows-10.aspx&quot; rel=&quot;nofollow noreferrer&quot;&gt;MBR Repair&lt;/a&gt;!&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-04-10T11:27:00.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10699" PostTypeId="1" CreationDate="2023-04-10T11:34:23.240" Score="5" ViewCount="97" Body="&lt;p&gt;I have a rhombohedral structure&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Vw8XM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Vw8XM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The SYSTEM and CELL_PARAMETERS blocks looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  A =  6.058435171&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;CELL_PARAMETERS {alat}&#xA;   0.494845678   0.494845678   0.000000000&#xA;   0.494845678  -0.000000000   0.494845678&#xA;   0.000000000   0.494845678   0.494845678&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What's the right value of ibrav that I should use and what are the changes that I should make in my input file to save the same structure?&#xA;I also already checked &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm224&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm224&lt;/a&gt; but I couldn't find it&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-04-10T12:09:55.533" LastActivityDate="2023-04-10T12:09:55.533" Title="What is the ibrav value of a rhombohedral structure?" Tags="|density-functional-theory|quantum-espresso|crystallography|quantum-computing|" AnswerCount="0" CommentCount="11" ClosedDate="2023-10-13T16:45:54.560" ContentLicense="CC BY-SA 4.0" />
  <row Id="10700" PostTypeId="1" CreationDate="2023-04-10T11:46:00.790" Score="3" ViewCount="100" Body="&lt;p&gt;I would like to perform an energy minimization of a 2D surface without changing the c parameter. I run a :&#xA;&lt;strong&gt;fix             1 all box/relax iso 0.0 vmax 0.001&lt;/strong&gt;&#xA;with&#xA;&lt;strong&gt;boundary        p p f&lt;/strong&gt;&#xA;but it was not accepted as the system is not periodic.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance&#xA;Regards&lt;/p&gt;&#xA;" OwnerUserId="6997" LastActivityDate="2023-04-10T11:46:00.790" Title="How to make a relaxation of a 2D surface with LAMMPS" Tags="|lammps|surfaces|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:45:31.680" ContentLicense="CC BY-SA 4.0" />
  <row Id="10701" PostTypeId="1" AcceptedAnswerId="10773" CreationDate="2023-04-10T14:06:59.630" Score="5" ViewCount="447" Body="&lt;p&gt;I'm trying to create a HOMO-LUMO diagram for a presentation, similar to the below figure from ResearchGate. I would like to learn how to do this with Python if possible, since I know this language (though I'm a beginner). Is there any easy way to make such an image in Python?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/LvdiG.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LvdiG.jpg&quot; alt=&quot;HOMO-LUMO orbital energy diagram&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="7" LastEditDate="2023-04-10T14:49:03.097" LastActivityDate="2023-04-24T15:13:45.597" Title="How to plot HOMO-LUMO diagram using python?" Tags="|density-functional-theory|python|orbitals|energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10702" PostTypeId="2" ParentId="10680" CreationDate="2023-04-10T15:53:45.690" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://www.comsol.com/blogs/modeling-surface-plasmon-polaritons-in-comsol/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.comsol.com/blogs/modeling-surface-plasmon-polaritons-in-comsol/&lt;/a&gt; in the last paragraph of this blog there is a answer but i am not able to reach to it. what boundary conditions to use when combining a metal and a dipole&#xA;&lt;a href=&quot;https://i.stack.imgur.com/sD7Uo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/sD7Uo.png&quot; alt=&quot;I have added one dipole here but the effective field is not changing &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6976" LastActivityDate="2023-04-10T15:53:45.690" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10703" PostTypeId="1" CreationDate="2023-04-10T16:36:04.533" Score="7" ViewCount="53" Body="&lt;p&gt;I'm looking for a table or database containing mathematical functions that belong to crystallographic space groups by having the same symmetry elements.&lt;/p&gt;&#xA;&lt;p&gt;Imagine a 2D square planar lattice. It has a 4-fold rotational symmetry as well as 4 reflection directions. The function &lt;span class=&quot;math-container&quot;&gt;$f(x,y) = \cos(x) + \cos(y)$&lt;/span&gt; has the same symmetry. What I'm looking for is a database / table which contains such functions for (ideally all) crystallographic space groups (I'm currently most interested in Bi2Se3 and thus the space group #166)&lt;/p&gt;&#xA;" OwnerUserId="6741" LastEditorUserId="5" LastEditDate="2023-10-12T15:55:38.147" LastActivityDate="2023-10-12T15:55:38.147" Title="Database (or table) of functions obeying symmetry properties of space groups" Tags="|crystallography|mathematical-modeling|symmetry|databases|space-groups|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10704" PostTypeId="2" ParentId="10690" CreationDate="2023-04-10T16:38:06.950" Score="4" Body="&lt;p&gt;The linear-response formalism implemented in hp.x code does not require the use of computationally expensive supercells of the traditional linear-response approach to compute the Hubbard U. Actually one of the main advantages of hp.x code in Quantum ESPRESSO is the ability to determine the Hubbard U using a primitive unit cell instead of a supercell.&lt;/p&gt;&#xA;&lt;p&gt;So in short, not just you can use a unit cell for calculating the Hubbard U but better you can use the primitive unit cell!Then use this U value for your supercell calculations.&lt;/p&gt;&#xA;&lt;p&gt;I suggest you read the hp.x paper by Timrov, Marzari and Cococcioni (2022), which beautifully explains all this and more.&lt;/p&gt;&#xA;&lt;p&gt;The paper is open access: &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2022.108455&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1016/j.cpc.2022.108455&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="5364" LastEditDate="2023-04-10T17:25:56.653" LastActivityDate="2023-04-10T17:25:56.653" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10705" PostTypeId="2" ParentId="10687" CreationDate="2023-04-10T18:28:47.663" Score="5" Body="&lt;p&gt;Several efforts exist for a database / repository of computational chemistry files. I'm most familiar with the molecular-based examples.&lt;/p&gt;&#xA;&lt;p&gt;You asked about a unique identifier. As far as a unique identifier, I would strongly suggest either the InChI or InChIKey which are unambiguous, developed by IUPAC, and support reasonable normalization and standardization.&lt;/p&gt;&#xA;&lt;p&gt;Probably the most successful repository is &lt;a href=&quot;https://www.iochem-bd.org/&quot; rel=&quot;noreferrer&quot;&gt;ioChem-BD&lt;/a&gt; which uses CML as the internal format. You can also &lt;a href=&quot;https://docs.iochem-bd.org/en/latest/&quot; rel=&quot;noreferrer&quot;&gt;run the software locally too&lt;/a&gt; since the service is &lt;a href=&quot;https://gitlab.com/ioChem-BD/iochem-bd&quot; rel=&quot;noreferrer&quot;&gt;open source&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The MolSSI team has &lt;a href=&quot;http://docs.qcarchive.molssi.org/projects/QCFractal/en/stable/&quot; rel=&quot;noreferrer&quot;&gt;QCFractal / QCArchive&lt;/a&gt; which seems to be mostly used for their effort at running quantum chemical calculations for force field design. (Their internal representation is evidently QCSchema.)&lt;/p&gt;&#xA;&lt;p&gt;The OpenChemistry project has offered &lt;a href=&quot;https://github.com/openchemistry/chemicaljson&quot; rel=&quot;noreferrer&quot;&gt;Chemical JSON&lt;/a&gt; as an open community interchange format (i.e., &amp;quot;better than molden&amp;quot;) and it's been adopted by Avogadro and &lt;code&gt;cclib&lt;/code&gt;. There were two efforts at a server / repository:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/cclib/openchemvault&quot; rel=&quot;noreferrer&quot;&gt;OpenChemVault&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/OpenChemistry/mongochemserver&quot; rel=&quot;noreferrer&quot;&gt;MongoChem&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;At the moment, I'm hoping we can push for a newer effort, including a &lt;a href=&quot;https://wiki.openchemistry.org/GSoC_Ideas_2023#Project_%5B350_hours%5D:_Computational_Chemistry_Repository_Server&quot; rel=&quot;noreferrer&quot;&gt;Google Summer of Code project idea&lt;/a&gt; for this.&lt;/p&gt;&#xA;&lt;p&gt;If you (or others) are interested in mentoring or providing input, please send me an e-mail.&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2023-04-10T19:33:04.460" LastActivityDate="2023-04-10T19:33:04.460" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10706" PostTypeId="1" AcceptedAnswerId="10714" CreationDate="2023-04-10T20:26:11.487" Score="3" ViewCount="80" Body="&lt;p&gt;I try to use molecular dynamics to simulate the half-reaction of the H2O reduction on the Pt cluster. Is it possible to add extra electrons in the system to simulate the reduction process?&lt;/p&gt;&#xA;&lt;p&gt;The Pt cluster contains about 600 atoms, I found that if I put one electron in the system, the fermi energy could rise by about 1eV, but if I put five electrons into the cluster, although the water molecule would dissociate, but the fermi energy would rise by 8eV, which too much higher than experimental values.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&#xA;Is it feasible to simulate the reduction process by adding extra electrons?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2023-04-11T12:22:06.433" Title="Could I simulate the applied voltage on the electrode by adding extra electrons in the system?" Tags="|molecular-dynamics|computational-chemistry|electronic-transport|electrostatic|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10707" PostTypeId="1" CreationDate="2023-04-11T00:15:46.960" Score="4" ViewCount="126" Body="&lt;p&gt;I want to calculate the optical properties using Yambo.&#xA;I used Quantum ESPRESSO 7.0 with Yambo 5.1.0, but I'm facing an issue. When I generate the dielectric function (o.eps_q1_ip) for example the o.eps_q1_ip is repeated so many times as in the code block bellow, I think that's because I didn't use the variable &lt;code&gt;wf_collect=.true.&lt;/code&gt; but it's no longer implemented in Quantum ESPRESSO.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;total 40364&#xA;-rwxrwxrwx 1 camila camila 1378528 April  10 11:46 charge-density.dat&#xA;-rwxrwxrwx 1 camila camila  241635 April  10 11:46 Cu_ONCV_PBE-1.0.UPF&#xA;-rwxrwxrwx 1 camila camila   64207 April  10 11:46 data-file-schema.xml&#xA;-rwxrwxrwx 1 camila camila  207529 April  10 11:46 I_ONCV_PBE-1.0.UPF&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q10_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q11_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q12_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q13_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q14_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q15_ip&#xA;-rwxrwxrwx 1 camila camila    8896 April  10 23:09 o.eel_q16_ip&#xA;-rwxrwxrwx 1 camila camila    9021 April  10 23:09 o.eel_q1_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q2_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q3_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q4_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q5_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q6_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q7_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q8_ip&#xA;-rwxrwxrwx 1 camila camila    8895 April  10 23:09 o.eel_q9_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q10_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q11_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q12_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q13_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q14_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q15_ip&#xA;-rwxrwxrwx 1 camila camila    8902 April  10 23:09 o.eps_q16_ip&#xA;-rwxrwxrwx 1 camila camila    9027 April  10 23:09 o.eps_q1_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q2_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q3_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q4_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q5_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q6_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q7_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q8_ip&#xA;-rwxrwxrwx 1 camila camila    8901 April  10 23:09 o.eps_q9_ip&#xA;-rwxrwxrwx 1 camila camila   20439 April  10 23:09 r_optics_dipoles_chi&#xA;-rwxrwxrwx 1 camila camila   25410 April  10 23:06 r_setup&#xA;drwxrwxrwx 1 camila camila    8192 April  10 23:07 SAVE&#xA;-rwxrwxrwx 1 camila camila 2437340 April  10 11:46 wfc10.dat&#xA;-rwxrwxrwx 1 camila camila 2432588 April  10 11:46 wfc11.dat&#xA;-rwxrwxrwx 1 camila camila 2429816 April  10 11:46 wfc12.dat&#xA;-rwxrwxrwx 1 camila camila 2427836 April  10 11:46 wfc13.dat&#xA;-rwxrwxrwx 1 camila camila 2432192 April  10 11:46 wfc14.dat&#xA;-rwxrwxrwx 1 camila camila 2434964 April  10 11:46 wfc15.dat&#xA;-rwxrwxrwx 1 camila camila 2427836 April  10 11:46 wfc16.dat&#xA;-rwxrwxrwx 1 camila camila 2448824 April  10 11:46 wfc1.dat&#xA;-rwxrwxrwx 1 camila camila 2427440 April  10 11:46 wfc2.dat&#xA;-rwxrwxrwx 1 camila camila 2429816 April  10 11:46 wfc3.dat&#xA;-rwxrwxrwx 1 camila camila 2441300 April  10 11:46 wfc4.dat&#xA;-rwxrwxrwx 1 camila camila 2429420 April  10 11:46 wfc5.dat&#xA;-rwxrwxrwx 1 camila camila 2437736 April  10 11:46 wfc6.dat&#xA;-rwxrwxrwx 1 camila camila 2442884 April  10 11:46 wfc7.dat&#xA;-rwxrwxrwx 1 camila camila 2435360 April  10 11:46 wfc8.dat&#xA;-rwxrwxrwx 1 camila camila 2430608 April  10 11:46 wfc9.dat&#xA;-rwxrwxrwx 1 camila camila    1722 April  10 23:06 yambo.in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I plot the dielectric function real part for example in this case, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-04-11T09:28:47.313" LastActivityDate="2023-04-11T13:13:10.873" Title="How to plot the dielectric function calculated with Yambo?" Tags="|density-functional-theory|quantum-espresso|optical-properties|yambo|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10708" PostTypeId="1" AcceptedAnswerId="10718" CreationDate="2023-04-11T02:54:32.353" Score="1" ViewCount="43" Body="&lt;p&gt;I am currently studying Siesta (specifically Transiesta) to investigate electronic transport in materials. However, I am confused about the assumptions and applicability of the NEGF method and this software.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is it necessary for NEGF or Transiesta to assume ballistic transport of electrons? If so, how can I ensure this when building a model?&lt;/strong&gt; A solid-state physics professor believes that &amp;quot;&lt;em&gt;To use the non-equilibrium Green's function method, both conditions of ballistic transport and no reflection at the contacts must be satisfied&lt;/em&gt;&amp;quot; while I read in a doctoral dissertation that &amp;quot;&lt;em&gt;Landauer's formula mainly focuses on ballistic transport, but NEGF has a wider range of applications.&lt;/em&gt;&amp;quot; Can I assume that NEGF does not require the assumption of ballistic transport when solving the model, and that the assumption is only used when calculating the transmission coefficient and current using Landauer's formula?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Please correct me if I have any misconceptions, as I am not a student majoring in physics.&#xA;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7000" LastEditorUserId="5" LastEditDate="2023-04-11T02:58:13.250" LastActivityDate="2023-04-12T07:54:09.510" Title="Applicability conditions of NEGF/Transiesta: Is elastic transport necessary?" Tags="|siesta|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10709" PostTypeId="1" AcceptedAnswerId="10712" CreationDate="2023-04-11T03:41:39.793" Score="3" ViewCount="98" Body="&lt;p&gt;In the tutorial &lt;a href=&quot;https://github.com/zerothi/ts-tbt-sisl-tutorial/blob/main/TS_02/run.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;zerothi/ts-tbt-sisl-tutorial/ts_02&lt;/a&gt;, it is mentioned that &amp;quot;&lt;em&gt;applying a bias to a bulk system is wrong&lt;/em&gt;&amp;quot; and &amp;quot;&lt;em&gt;if you can't immediately figure this out, try and create a longer system by replacing device = elec.tile(3, axis=0) with, say: device = elec.tile(6, axis=0) and redo the calculation for a given bias. then compare the potential profiles.&lt;/em&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;I know that applying a bias to a pristine system has no physical meaning, but why is it also wrong to apply a bias to a bulk system? From the hint given, it seems that the author simply increased the size of the device model by a factor of two along the current direction. Is this error related to ballistic transport, i.e., when the device size is no longer much smaller than the electron's mean free path? Is my understanding correct?&lt;/p&gt;&#xA;&lt;p&gt;Here are their potential profiles(the potential in the figures has been amplified by a factor of ten for better visualization). I cannot discern the meaning the author is trying to convey.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9rzLb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9rzLb.png&quot; alt=&quot;device = elec.tile(3, axis=0) &quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/KoRr9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KoRr9.png&quot; alt=&quot;device = elec.tile(6, axis=0) &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7000" LastEditorUserId="7000" LastEditDate="2023-04-12T12:31:37.850" LastActivityDate="2023-04-13T12:01:07.350" Title="Applying bias in NEGF calculation on a pristine system -- why is it wrong?" Tags="|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10711" PostTypeId="2" ParentId="10687" CreationDate="2023-04-11T06:56:49.580" Score="1" Body="&lt;p&gt;It is not really clear from the title and the long description what the issue is. To me, it sounds like you just want the &lt;code&gt;.xyz&lt;/code&gt; data but in a clearly separable form so that one does not have to parse the file separately. It also sounds like you want to be able to add additional information like the SMILES string, CAS number, etc, and the question appears to be whether there is a portable way to do this?&lt;/p&gt;&#xA;&lt;p&gt;This type of data is most easily handled by&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;a database format, or&lt;/li&gt;&#xA;&lt;li&gt;a Python-type dictionary  (C++ map, etc)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;There already exist several data formats for exchanging structured files, like JSON and XML. I would recommend JSON, with which &lt;a href=&quot;https://json-schema.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;you can define data formats&lt;/a&gt; and for which there are interfaces for several languages like:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/json-c/json-c&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/json-c/json-c&lt;/a&gt; (C)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/nlohmann/json&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/nlohmann/json&lt;/a&gt; (C++)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://github.com/jacobwilliams/json-fortran&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/jacobwilliams/json-fortran&lt;/a&gt; (Fortran)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://docs.python.org/3/library/json.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.python.org/3/library/json.html&lt;/a&gt; (Python).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;JSON is also used as the internal storage format of the &lt;a href=&quot;https://github.com/MolSSI-BSE/basis_set_exchange/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Basis Set Exchange&lt;/a&gt;, whose web interface is available at &lt;a href=&quot;http://basissetexchange.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://basissetexchange.org&lt;/a&gt;. If you need to store basis set data, you should either tag the versioned basis set from the Basis Set Exchange, or explicitly include the basis in the JSON format used by the Basis Set Exchange, which can then be printed out by BSE functionality.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="30" LastEditDate="2023-04-11T19:16:10.580" LastActivityDate="2023-04-11T19:16:10.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10712" PostTypeId="2" ParentId="10709" CreationDate="2023-04-11T07:09:02.207" Score="4" Body="&lt;p&gt;The thing is that it will be experimentally impossible (at least to my knowledge) to attach electrodes of the same pristine device structure without disrupting the electronic structure of the electrodes.&lt;/p&gt;&#xA;&lt;p&gt;Imagine a gold wire where you want to alter the potentials at some fixed positions on the wire. It would require you to attach &lt;em&gt;something&lt;/em&gt; to the wire at the positions of the electrodes. This would effectively change the electronic structure at those given positions, meaning it is not the system you'll be simulating.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, the key point about increasing the length of the system is that the potential drop changes depending on the length of the system since there is no scattering. So it becomes a bit dubious to create a device with bias for a pristine system since it requires 1) non-interaction attachment of a battery and 2) the exact placement of the batteries at the distances you simulate since other placements would result in a different potential profile.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-04-13T12:01:07.350" LastActivityDate="2023-04-13T12:01:07.350" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10713" PostTypeId="2" ParentId="10693" CreationDate="2023-04-11T07:14:48.913" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I am looking for a free code for Hartree-Fock calculations in solids especially a code optimized (quite fast) compared to Pyscf which is quite slow and unstable.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;PySCF is in general one of the fastest codes available. It is also the only free one.&lt;/p&gt;&#xA;&lt;p&gt;If you really want to do periodic Hartree-Fock calculations on solids, you should look into &lt;a href=&quot;https://www.crystal.unito.it/&quot; rel=&quot;noreferrer&quot;&gt;the CRYSTAL program&lt;/a&gt;, which is, however, not free ($2000 for a license). However, from what I hear from my colleagues, CRYSTAL is well worth the license cost since it is unparallelled in its use of symmetry to reduce the cost of Hartree-Fock calculations, especially.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I do not have any clue to explain why HF so slow in solids compared to molecular systems.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Because you are comparing two entirely different things. For a molecule, the Gaussian basis set is simply the atomic basis&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \chi_{\mu}({\bf r}) = \phi_\mu({\bf r}-{\bf R}_\mu) $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\chi_{\mu}$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt;th molecular basis function and &lt;span class=&quot;math-container&quot;&gt;$\phi_\mu$&lt;/span&gt; is the corresponding Gaussian basis function centered on &lt;span class=&quot;math-container&quot;&gt;${\bf R}_\mu$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In contrast, in a periodic system you have to satisfy Bloch's theorem&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \psi_{\boldsymbol{k}}(\boldsymbol{r}+\boldsymbol{g})=u_{\boldsymbol{k}}(\boldsymbol{r})e^{i\boldsymbol{k}\cdot\boldsymbol{g}}, $$&lt;/span&gt;&#xA;which arises from translational invariance, and where &lt;span class=&quot;math-container&quot;&gt;$u_{\boldsymbol{k}}(\boldsymbol{r})$&lt;/span&gt; is a periodic function. These functions are thereby expanded in a periodic basis set&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \chi_{\mu}(\boldsymbol{r};\boldsymbol{k})=\sum_{\boldsymbol{g}}e^{i{\bf k}\cdot\boldsymbol{g}}\phi_{\mu}(\boldsymbol{r}-\boldsymbol{R}_{\mu}-\boldsymbol{g}) $$&lt;/span&gt;&#xA;where the sum over &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; runs over the grid points. This feature also propagates to all the other parts of the calculation. For example, to calculate the overlap integrals, &lt;strong&gt;you have to sum over an infinite series of cells&lt;/strong&gt; while in a molecular calculation you only calculate the integrals over one copy of the system. This has a huge impact on the evaluation of Coulomb and exchange integrals which are needed for Hartree-Fock calculations.&#xA;&lt;strong&gt;Periodic and molecular calculations are different types of beasts altogether!&lt;/strong&gt; The former always has an infinite number of atoms, and has to evaluate more terms than the latter.&lt;/p&gt;&#xA;&lt;p&gt;I would like to point out that periodic calculations are not as simple to run as molecular calculations, since you have many more choices to make, first and foremost the &lt;strong&gt;k&lt;/strong&gt;-point grid sampling and the truncation of Coulomb and exchange sums. PySCF also has several algorithms for performing periodic calculations, which don't have the same computational costs. It sounds to me like you could improve the runtimes a fair bit by a judicious choice of the algorithm and parameters.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-04-11T07:14:48.913" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10714" PostTypeId="2" ParentId="10706" CreationDate="2023-04-11T12:04:24.880" Score="4" Body="&lt;p&gt;You have found for yourself that it is not difficult to reduce water if you throw a suitably overwhelming number of electrons at it, but you're also skeptical that this reflects realistic experimental conditions. This means your physical intuition is working well!&lt;/p&gt;&#xA;&lt;p&gt;The technique you are looking for is called &lt;em&gt;constant potential&lt;/em&gt; DFT calculations, where -- precisely because you cannot trust what number of electrons you should throw into your system -- you control the &lt;em&gt;work function&lt;/em&gt; of the electrode of interest, in effect choosing the electrode potential, and let the DFT package of choice use &lt;em&gt;that&lt;/em&gt; to determine how many electrons are in the system and thus how happy water is to be reduced.&lt;/p&gt;&#xA;&lt;p&gt;(Note that DFT people like to call it &amp;quot;grand-canonical ensemble&amp;quot; DFT, or GCE-DFT for short, because it studies the grand canonical ensemble for electrons. I dislike the term personally because some DFT practitioners refer to implicit solvent DFT as using a grand canonical ensemble for solvent molecules, and that's one too many grand canonical things for my liking. But you should probably Google GCE-DFT and see what you find.)&lt;/p&gt;&#xA;&lt;p&gt;I've been reading these papers to get a handle on the technique, so perhaps they will be helpful to you too:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcc.8b10046&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jpcc.8b10046&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00717&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jctc.9b00717&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.8b03002&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/jacs.8b03002&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.chemrev.1c00981&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.chemrev.1c00981&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://aip.scitation.org/doi/full/10.1063/5.0138197&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aip.scitation.org/doi/full/10.1063/5.0138197&lt;/a&gt; (fresh off the press!!)&lt;/p&gt;&#xA;&lt;p&gt;and this link on one implementation (solvated jellium in GPAW):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/sjm/sjm.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/gpaw/documentation/sjm/sjm.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;All the best!&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-04-11T12:22:06.433" LastActivityDate="2023-04-11T12:22:06.433" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10715" PostTypeId="1" AcceptedAnswerId="10724" CreationDate="2023-04-11T13:06:25.577" Score="3" ViewCount="100" Body="&lt;p&gt;I try to reproduce the dielectric function as the picture bellow using Yambo code but the values that I have found in y-axis are so much bigger [-1000,1500] compared to literature. I generated the scf file using Quantum ESPRESSO then I used Yambo to generate the dielectric function.&lt;/p&gt;&#xA;&lt;p&gt;I have doubts that the problem can be related to the occupations type and degauss value. Actually I used occupations ='fixed' in the scf , then when I changed it to smearing the y-axis values reduced a little bit but I'm still far from the literature.&lt;/p&gt;&#xA;&lt;p&gt;Can someone clarify my doubts about that, please? And which occupations type and degauss value I should use?&lt;/p&gt;&#xA;&lt;p&gt;PS: I already encountered same problem in other calculations like DOS.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7gDsk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7gDsk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Link of the paper from which I took the picture: &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S092145260600189X&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/pii/S092145260600189X&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-04-12T12:09:03.170" LastActivityDate="2023-04-13T00:02:34.890" Title="Why my values of dielectric function don't match litterature (For Yambo with Quantum ESPRESSO)?" Tags="|density-functional-theory|quantum-espresso|condensed-matter|optical-properties|yambo|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10716" PostTypeId="2" ParentId="10707" CreationDate="2023-04-11T13:13:10.873" Score="2" Body="&lt;p&gt;After I repeated the calculation so many times I figured out that the problem arise if you use k-points {automatic}. When k-points {gamma} is used the problem is fixed and just 1 &lt;code&gt;o.eps_q1_ip&lt;/code&gt; is generated (same thing for the other outputs)&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-04-11T13:13:10.873" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10717" PostTypeId="1" CreationDate="2023-04-11T14:35:36.803" Score="6" ViewCount="77" Body="&lt;p&gt;I am implementing a system of fermions in a trap potential with tensor networks and want to find the ground state energy via DMRG (I'm using SyTen). As usual in quantum chemistry the Hamiltonian has the following form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=\sum_{i,j=0}^{d-1}h_{ij}c^\dagger_i c_j + \sum_{i_1,i_2,j_1,j_2}^{d-1}V_{i_1,i_2,j_1,j_2}c^\dagger_{i_1}c^\dagger_{i_2}c_{j_1}c_{j_2},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; denotes the maximum number of orbitals - of course one needs infinitely many orbitals in principle, which requires extrapolation of the ground state energies. I got into tensor networks from the condensed matter side and there it is usual that one regards e.g. some spin lattice system, fixes the filling fraction (e.g. half filling) and then one computes the ground state energies for different system sizes &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; - then plotting the energies v.s. &lt;span class=&quot;math-container&quot;&gt;$1/L$&lt;/span&gt; (for 1D systems) and finds the &amp;quot;true&amp;quot; ground state energy for &lt;span class=&quot;math-container&quot;&gt;$1/L=0$&lt;/span&gt; for the fixed filling fraction.&lt;/p&gt;&#xA;&lt;p&gt;However, now I'm not interested in the energy for some fixed filling fraction, instead I want the energy of a fixed particle number. I can fix the number of fermions in the system by initializing a start state in the correct symmetry sector (we have U(1) symmetry). My question is the following: I want to find out the &amp;quot;true&amp;quot; ground state energy for the &amp;quot;thermodynamic&amp;quot; limit of &lt;span class=&quot;math-container&quot;&gt;$d=\infty$&lt;/span&gt; orbitals and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; fermions in the system. Is it valid to fix &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;, compute the ground state energies for different &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; and then plot and fit the energy v.s. &lt;span class=&quot;math-container&quot;&gt;$1/d$&lt;/span&gt; and taking the energy at &lt;span class=&quot;math-container&quot;&gt;$1/d=0$&lt;/span&gt; as the true ground state energy for particle number &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;? It seems reasonable for me but I'd like to make sure that this is indeed the correct thing to do.&lt;/p&gt;&#xA;&lt;p&gt;I was looking through the literature about this but could not find an explicit answer which explains the extrapolation process for such cases. I hope that I could explain my issue clearly enough - an explanation would be great but also some references which address exactly such questions would be very helpful!&lt;/p&gt;&#xA;" OwnerUserId="7002" LastActivityDate="2023-04-11T14:35:36.803" Title="How To Extrapolate Ground State Energy in Thermodynamic Limit via DMRG" Tags="|quantum-chemistry|quantum-mechanics|dmrg|" AnswerCount="0" CommentCount="5" ClosedDate="2023-10-20T01:32:33.750" ContentLicense="CC BY-SA 4.0" />
  <row Id="10718" PostTypeId="2" ParentId="10708" CreationDate="2023-04-12T07:54:09.510" Score="1" Body="&lt;p&gt;Electron transport is a multi-faceted problem.&lt;/p&gt;&#xA;&lt;p&gt;The most simple calculation is the ballistic approach where phase-coherence is assumed through the ballistic nature of the electrons.&lt;/p&gt;&#xA;&lt;p&gt;When dealing with a higher level of accuracy one could look into inelastic transport which is due to electron-phonon interactions (electrons may scatter at phonons transferring momentum).&lt;/p&gt;&#xA;&lt;p&gt;There may be other effects as well.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-04-12T07:54:09.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10719" PostTypeId="1" CreationDate="2023-04-12T08:07:19.300" Score="4" ViewCount="383" Body="&lt;p&gt;I have tried everything I could find online but I am not able to relax this structure in VASP. I started out with the basic INCAR&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; SYSTEM   =  Perovskite&#xA;&#xA;# Electronic minimization&#xA;  ISTART  = 0&#xA;  ICHARG  = 2&#xA;  IALGO    = 38&#xA;  PREC= Accurate&#xA;  ENCUT   = 400&#xA;  NELM    = 200&#xA;  EDIFF   = 1E-6&#xA;  EDIFFG  =-0.03&#xA;  LWAVE   =.FALSE.&#xA;  IVDW    = 11&#xA;  ISYM    = 0&#xA;&#xA;# Ionic minimization&#xA;  NSW     = 200&#xA;  IBRION  = 2&#xA;  ISIF    = 2&#xA;  POTIM   = 0.5&#xA;  PSTRESS = 109&#xA;&#xA;# Exchange correlational functional&#xA;  GGA = PE&#xA;&#xA; ISMEAR   = 0&#xA; SIGMA    = 0.02&#xA;&#xA;  NCORE = 4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Additionally I have tried changing the &amp;quot;ALGO&amp;quot; tag and even break down the calculations into &amp;quot;ISIF=2&amp;quot; and then &amp;quot;ISIF=3&amp;quot;. I also tried changing IBRION tag and checking the inital geometry but nothing is working.&lt;/p&gt;&#xA;&lt;p&gt;For the case of ISIF=2 the calculation stops after 1st scf iteration and gives the error &lt;code&gt;WARNING: CNORMN: search vector ill defined&lt;/code&gt;. If I try using ISIF=3 then the geometry goes even farther away from the minima and the energy goes to values as high +4000.&lt;/p&gt;&#xA;&lt;p&gt;A thing of note is that I am relaxing this under Hydrostatic pressure, but this should not lead to problems as I have relaxed similar structures. The issue is arising probably from the fact that geometry is just too far away from the minima.&lt;/p&gt;&#xA;&lt;p&gt;What can I do to get a convergence on this relaxation?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Cs2 Sn I6&#xA;1.0&#xA;        9.0550003052         0.0000000000         0.0000000000&#xA;        0.0000000000         7.3959999084         0.0000000000&#xA;       -0.6390889480         0.0000000000         8.6203423505&#xA;   Cs   Sn    I&#xA;    4    2   12&#xA;Direct&#xA;     0.496004999         0.000000000         0.750850022&#xA;     0.503995001         0.000000000         0.249149993&#xA;     0.996004999         0.500000000         0.250850022&#xA;     0.003995001         0.500000000         0.749149978&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.500000000         0.500000000         0.500000000&#xA;    -0.176189019         0.000000000         0.209978808&#xA;     0.809142163         0.265969992        -0.192556779&#xA;     0.809142163         0.734030008        -0.192556779&#xA;     0.190857836         0.265969992         1.192556816&#xA;     0.190857836         0.734030008         1.192556816&#xA;     1.176189019         0.000000000         0.790021191&#xA;     0.690857841         0.765969992         0.692556774&#xA;     0.309142163         0.234030008         0.307443183&#xA;     0.309142163         0.765969992         0.307443183&#xA;     0.690857841         0.234030008         0.692556774&#xA;     0.323810980         0.500000000         0.709978808&#xA;     0.676189019         0.500000000         0.290021191&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2023-04-12T08:07:19.300" Title="VASP geometry optimization not converging" Tags="|vasp|geometry-optimization|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:44:58.450" ContentLicense="CC BY-SA 4.0" />
  <row Id="10720" PostTypeId="1" CreationDate="2023-04-12T11:57:26.710" Score="1" ViewCount="27" Body="&lt;p&gt;I want to model an oscillating dipole in a 2.45 refractive indexed material. The dipole should absorb waves of frequency 80-100 THz and oscillate and then emits the radiation.&#xA;Or in other words the dipole oscillates in that range.&lt;/p&gt;&#xA;&lt;p&gt;I want to  know the boundary conditions suitable for it , also I want to plot the electric field emitting from the dipole.&lt;/p&gt;&#xA;" OwnerUserId="6976" LastActivityDate="2023-04-12T11:57:26.710" Title="how do you model a dipole which absorbs radiation and then emits it , in COMSOL" Tags="|dipole|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-13T16:44:41.907" ContentLicense="CC BY-SA 4.0" />
  <row Id="10721" PostTypeId="1" AcceptedAnswerId="10727" CreationDate="2023-04-12T14:29:49.840" Score="8" ViewCount="196" Body="&lt;p&gt;I am looking for software that can calculate the first-order non-adiabatic coupling vector &lt;span class=&quot;math-container&quot;&gt;$$\vec \tau_{ij}=\langle \varphi_i|\nabla_R\varphi_j\rangle$$&lt;/span&gt; between &lt;strong&gt;excited&lt;/strong&gt; electronic singlet states using DFT/TDDFT. The software I am aware of(Gaussian, Turbomole, Dalton&amp;lt;-I'm not 100% sure about this one, Molpro only MSCF/CI), are either limited to calculations for transitions between electronic ground and excited state or don't feature DFT/TDDFT(Bagel).&lt;/p&gt;&#xA;&lt;p&gt;Does someone know a program/software that features the calculation of non-adiabatic coupling vectors between excited states, using DFT/TDDFT? Or is there perhaps a fundmental reason why this combination cannot be used?&lt;/p&gt;&#xA;&lt;p&gt;The application are small organic molecules &amp;lt; 100 atoms, no solids or crystals.&lt;/p&gt;&#xA;&lt;p&gt;UPDATE&lt;/p&gt;&#xA;&lt;p&gt;It seems that the commercial software Q-CHEM can calculate nonadiabatic coupling vectors also between excited states, using TDDFT or spin-flip TDDFT. But It would be good to have at least one free/non-commercial alternative.&lt;/p&gt;&#xA;" OwnerUserId="2289" LastEditorUserId="2289" LastEditDate="2023-04-13T11:35:42.407" LastActivityDate="2023-04-15T10:06:54.297" Title="Quantum Chemistry software that can calculate nonadiabatic coupling vectors between excited states using DFT/TDDFT" Tags="|density-functional-theory|software-recommendations|td-dft|excited-states|non-adiabatic|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10722" PostTypeId="2" ParentId="9218" CreationDate="2023-04-12T17:56:00.873" Score="3" Body="&lt;p&gt;These transitions are not intuitive, so it not easy to explain. Simply, if you know the Bloch theorem well as a basis to describe approximately the solutions in a periodic system, you can understand that this theorem is based on a local periodic potential. Normally a Bloch state lead to the band theory where a partially occupied band is a conductor (there are delocalized states) and fully occupied bands is an insulator or a semiconductor (localized state).&lt;/p&gt;&#xA;&lt;p&gt;Now the problem is the fact that the potential in solids is not a local periodic potential.&lt;/p&gt;&#xA;&lt;p&gt;When the non-local &lt;strong&gt;electron-electron&lt;/strong&gt; (e-e) interactions are dominant, the Bloch state is disturbed &lt;span class=&quot;math-container&quot;&gt;$\rightarrow $&lt;/span&gt; We have a Mott transition the material with a partially occupied band become an insulator.&#xA;When the potential is not strictly periodic, due to &lt;strong&gt;impurities&lt;/strong&gt; (even if the e-e interaction can be neglected) the Bloch state is also disturbed &lt;span class=&quot;math-container&quot;&gt;$\rightarrow $&lt;/span&gt;  we have an Anderson transition.&lt;/p&gt;&#xA;&lt;p&gt;For Bloch's theorem to remain valid, the electrons should have enough kinetic energy compared to the quantities affecting the periodicity of the potential (e-e interaction or impurities). Therefore a wide bandwidth &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; (or hopping integral) is needed as in your image compared to &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt; affecting the potential.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastEditorUserId="6019" LastEditDate="2023-04-14T11:19:48.603" LastActivityDate="2023-04-14T11:19:48.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10723" PostTypeId="1" AcceptedAnswerId="10730" CreationDate="2023-04-12T19:47:19.647" Score="8" ViewCount="921" Body="&lt;p&gt;So I am trying to plot the band structure from the &lt;code&gt;EIGENVAL&lt;/code&gt; file produced by VASP. I wrote this Python code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as mpl&#xA;&#xA;mpl.rcParams[&amp;quot;mathtext.fontset&amp;quot;] = &amp;quot;stix&amp;quot;   # Change the math font&#xA;mpl.rcParams[&amp;quot;font.family&amp;quot;] = &amp;quot;STIXGeneral&amp;quot; # Change the global font&#xA;&#xA;with open('EIGENVAL', 'r') as f:&#xA;    data = f.readlines()&#xA;&#xA;nkpts = int(data[5].split()[1])&#xA;nbands = int(data[5].split()[2])&#xA;&#xA;print(nkpts, nbands)&#xA;&#xA;kpoints = []&#xA;energies = []&#xA;for i in range(nkpts):&#xA;    line_index = 7+(nbands+2)*i&#xA;    kpoint_coords = [float(x) for x in data[line_index].split()[:3]]&#xA;    eigenvalues = []&#xA;    for j in range(nbands):&#xA;        eigenvalue = float(data[line_index+j+1].split()[1])&#xA;        eigenvalues.append(eigenvalue)&#xA;    kpoints.append(kpoint_coords)&#xA;    energies.append(eigenvalues)&#xA;&#xA;kpoints = np.array(kpoints)&#xA;energies = np.array(energies)&#xA;&#xA;EF = 1.92675163&#xA;energies = (energies.T - EF).T&#xA;&#xA;xaxis = [j for j in range(len(kpoints))]&#xA;&#xA;mpl.xticks([xaxis[0], xaxis[int(len(xaxis)/2-1)], xaxis[-1]], [&amp;quot;L&amp;quot;, &amp;quot;Γ&amp;quot;, &amp;quot;X&amp;quot;])&#xA;for i in range(nbands):&#xA;    mpl.plot(xaxis, energies[:, i])&#xA;mpl.axhline(y=0, linestyle='--')&#xA;# mpl.axhline(y=2, linestyle='--')&#xA;mpl.axvline(x=xaxis[0], linestyle='-')&#xA;mpl.axvline(x=xaxis[int(len(xaxis)/2-1)], linestyle='-')&#xA;mpl.axvline(x=xaxis[-1], linestyle='-')&#xA;mpl.xlabel('&lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points')&#xA;mpl.ylabel('&lt;span class=&quot;math-container&quot;&gt;$E$$-$&lt;/span&gt;VBM [eV]')&#xA;mpl.savefig('BS.png', dpi=800, bbox_inches=&amp;quot;tight&amp;quot;)&#xA;mpl.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am getting this figure:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/lC8op.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lC8op.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am defining the &lt;code&gt;xaxis&lt;/code&gt; array which is rather arbitrary.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is: Is there a more efficient way to plot the band structure after extracting the data?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2023-04-15T07:34:50.723" LastActivityDate="2023-04-16T03:47:43.077" Title="Band Structure from EIGENVAL in VASP" Tags="|density-functional-theory|vasp|band-structure|python|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10724" PostTypeId="2" ParentId="10715" CreationDate="2023-04-13T00:02:34.890" Score="3" Body="&lt;p&gt;The plot in the reference paper is in the &lt;a href=&quot;https://en.wikipedia.org/wiki/Arbitrary_unit&quot; rel=&quot;nofollow noreferrer&quot;&gt;Arbitrary unit&lt;/a&gt;. So, the absolute value doesn't matter. The value can be 1 in the paper and 1000 in your calculation - it is not a problem. I think the only thing to make sure is that the overall shape is correct.&lt;/p&gt;&#xA;&lt;p&gt;You can try choosing a suitable reference point in the paper, let's say &lt;span class=&quot;math-container&quot;&gt;$3  \mathrm{eV}$&lt;/span&gt;. Then reduce your calculated &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_1$&lt;/span&gt; value (let's say &lt;span class=&quot;math-container&quot;&gt;$6000$&lt;/span&gt;) at that point so that it matches the value given in the paper (looks like around &lt;span class=&quot;math-container&quot;&gt;$6$&lt;/span&gt;). Note the reduction factor (in this hypothetical example, it is &lt;span class=&quot;math-container&quot;&gt;$1000$&lt;/span&gt;). Then apply the same reduction factor for all of your data (i.e. divide everything by &lt;span class=&quot;math-container&quot;&gt;$1000$&lt;/span&gt;). Similarly, reduce your &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_2$&lt;/span&gt; data too. Then if you plot these reduced data, you can compare your result with the reference data.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-04-13T00:02:34.890" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10726" PostTypeId="2" ParentId="10563" CreationDate="2023-04-14T14:00:01.657" Score="4" Body="&lt;p&gt;The webpage is still not working, and haven't gotten any reply from the organizers (several media have been attempted). However, I found a GitHub repository containing all the slides and tutorial files. This is the repository: &lt;strong&gt;&lt;a href=&quot;https://github.com/thepranab/DFT-MASTANI-School-IISER-Pune-2014&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT MASTANI School IISER Pune 2014&lt;/a&gt;&lt;/strong&gt;. You can use &lt;a href=&quot;https://web.archive.org/web/20160414111506/http://www.iiserpune.ac.in/%7Esmr2626/talks-presentations.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; archived page as a table of content for the repository.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-04-14T14:00:01.657" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10727" PostTypeId="2" ParentId="10721" CreationDate="2023-04-15T10:06:54.297" Score="5" Body="&lt;p&gt;The BDF program (&lt;a href=&quot;https://bdf-manual.readthedocs.io/en/latest/;&quot; rel=&quot;noreferrer&quot;&gt;https://bdf-manual.readthedocs.io/en/latest/;&lt;/a&gt; the English manual is under ongoing translation from Chinese. For a purely English but older version, see &lt;a href=&quot;http://182.92.69.169:7226/Introduction&quot; rel=&quot;noreferrer&quot;&gt;http://182.92.69.169:7226/Introduction&lt;/a&gt;) is the first program to support nonadiabatic coupling vectors between TDDFT excited states. Although it is not free, the interested user can apply for a free trial by registering an account at &lt;a href=&quot;https://iresearch.net.cn/web/personal-space/activity-page&quot; rel=&quot;noreferrer&quot;&gt;https://iresearch.net.cn/web/personal-space/activity-page&lt;/a&gt; (in Chinese, but very machine-translatable). A few advantages of BDF's excited state-excited state nonadiabatic coupling functionality include:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The nonadiabatic coupling vectors can be calculated at either the TDA or full TDDFT levels.&lt;/li&gt;&#xA;&lt;li&gt;Both singlet states and triplet states are supported. Therefore, internal conversions from e.g. the T2 state to the T1 state can be calculated as well.&lt;/li&gt;&#xA;&lt;li&gt;BDF offers two ways to calculate the nonadiabatic coupling vectors: via equation-of-motion (EOM) theory or via time-dependent perturbation theory (TDPT). The TDPT approach is the most rigorous, since it provably gives the exact nonadiabatic coupling vectors when the DFT functional is exact and when the exact frequency-dependent response kernel is used. The EOM nonadiabatic coupling vectors do not have this property, but usually differ negligibly from the TDPT ones, and have much better numerical stability. By comparison, many other programs employ the auxiliary wave function approaches or the Chernyak-Mukamel formula; the former are not rigorous (because the rely on making analogies between Kohn-Sham and wavefunction theory, and the analogies are not fully justified), while the latter requires extremely large basis sets for fully converged results. See &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.accounts.1c00312&quot; rel=&quot;noreferrer&quot;&gt;my paper&lt;/a&gt; for detailed discussions.&lt;/li&gt;&#xA;&lt;li&gt;BDF features a seamless interface to the &lt;a href=&quot;https://cloud.hzwtech.com/web/product-service?id=22&quot; rel=&quot;noreferrer&quot;&gt;MOMAP program&lt;/a&gt;, which can calculate the internal conversion rate between two electronic states using the harmonic approximation to the potential energy surfaces, using the nonadiabatic coupling vectors calculated by BDF.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-04-15T10:06:54.297" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10728" PostTypeId="1" AcceptedAnswerId="10729" CreationDate="2023-04-15T18:37:46.870" Score="7" ViewCount="807" Body="&lt;p&gt;I am trying to create a molecular graph from SMILES representation of molecules on pytorch using rdkit. The following molecule of caffeine is to be modelled.&lt;/p&gt;&#xA;&lt;p&gt;Here we see the molecule with bond lengths of each bond in it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/1XjVW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1XjVW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I wish to construct a a pytorch graph for this molecule. For this I would need the node_feat, edge_feat and edge_index data of this molecule. The &lt;code&gt;node_feat&lt;/code&gt; is &lt;code&gt;number of nodes x features&lt;/code&gt;. &lt;code&gt;edge_feat&lt;/code&gt; is &lt;code&gt;number of edge x features&lt;/code&gt; . But at the moment my code is including hydrogen bonds as well.&lt;/p&gt;&#xA;&lt;p&gt;How to neglect/eliminate the hydrogen bonds from this code?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Code:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import AllChem as Chem&#xA;from rdkit.Chem import rdMolTransforms&#xA;from rdkit.Chem.Draw import rdMolDraw2D, rdDepictor, IPythonConsole&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from IPython.display import Image&#xA;&#xA;# smiles = data[&amp;quot;smiles&amp;quot;][5:6].values&#xA;smiles = ['CN1C=NC2=C1C(=O)N(C(=O)N2C)C']&#xA;&#xA;# 3D for lengths&#xA;mol3d = Chem.AddHs(Chem.MolFromSmiles(smiles[0]))&#xA;Chem.EmbedMolecule(mol3d, randomSeed=42)&#xA;Chem.MMFFOptimizeMolecule(mol3d)&#xA;&#xA;bonds = [(x.GetBeginAtomIdx(), x.GetEndAtomIdx()) for x in mol3d.GetBonds()]&#xA;&#xA;conf = mol3d.GetConformer()&#xA;&#xA;b_lengths = []&#xA;b_angles = []&#xA;&#xA;for b in bonds:&#xA;    bl = rdMolTransforms.GetBondLength(conf,b[0],b[1]) #GetAngleDeg&#xA;    b_lengths.append(str(round(bl,2)))&#xA;&#xA;&#xA;print(len(b_lengths))&#xA;print(b_lengths)&#xA;print(len(bonds))&#xA;print(bonds)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Output:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;25&#xA;['1.44', '1.37', '1.32', '1.36', '1.36', '1.42', '1.23', '1.4', '1.41', '1.23', '1.4', '1.45', '1.45', '1.37', '1.37', '1.09', '1.09', '1.09', '1.08', '1.09', '1.09', '1.09', '1.09', '1.09', '1.09']&#xA;25&#xA;[(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8), (8, 9), (9, 10), (9, 11), (11, 12), (8, 13), (5, 1), (11, 4), (0, 14), (0, 15), (0, 16), (2, 17), (12, 18), (12, 19), (12, 20), (13, 21), (13, 22), (13, 23)]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6643" LastEditorUserId="6687" LastEditDate="2023-04-15T21:33:19.977" LastActivityDate="2023-04-15T21:33:19.977" Title="How to create a molecular graph from smiles representation" Tags="|python|rdkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10729" PostTypeId="2" ParentId="10728" CreationDate="2023-04-15T19:21:18.827" Score="7" Body="&lt;p&gt;You can use the &lt;code&gt;Chem.RemoveHs&lt;/code&gt; function.&lt;/p&gt;&#xA;&lt;p&gt;I attach a snippet below on how you can utilise it in your code.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol3d_without_Hs = Chem.RemoveHs(mol3d)&#xA;&#xA;bonds = [(x.GetBeginAtomIdx(), x.GetEndAtomIdx()) for x in mol3d_without_Hs.GetBonds()]&#xA;&#xA;conf = mol3d_without_Hs.GetConformer()&#xA;&#xA;b_lengths = []&#xA;b_angles = []&#xA;&#xA;for b in bonds:&#xA;    bl = rdMolTransforms.GetBondLength(conf,b[0],b[1]) #GetAngleDeg&#xA;    b_lengths.append(str(round(bl,2)))&#xA;&#xA;for bnd in mol3d_without_Hs.GetBonds():&#xA;    bl = rdMolTransforms.GetBondLength(conf,bnd.GetBeginAtomIdx(),bnd.GetEndAtomIdx())&#xA;    # set the bond note on the molecule, which we'll draw:&#xA;    mol3d_without_Hs.GetBondWithIdx(bnd.GetIdx()).SetProp('bondNote',f'{bl:.2f}')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now on a notebook you can visualise the &lt;code&gt;mol3d_without_Hs&lt;/code&gt; and you can see the Hs are neglected in the bond lengths:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mMxRI.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mMxRI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-15T19:21:18.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10730" PostTypeId="2" ParentId="10723" CreationDate="2023-04-16T03:47:43.077" Score="1" Body="&lt;p&gt;As @AbdulMuhaymin pointed out in the comments: &lt;a href=&quot;https://romerogroup.github.io/pyprocar/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyPROCAR&lt;/a&gt; looks like a nice tool that does more than just plotting band structures, and it works for many DFT codes other than VASP.&lt;/p&gt;&#xA;" OwnerUserId="336" LastActivityDate="2023-04-16T03:47:43.077" CommentCount="0" CommunityOwnedDate="2023-04-16T22:19:55.923" ContentLicense="CC BY-SA 4.0" />
  <row Id="10731" PostTypeId="1" AcceptedAnswerId="10732" CreationDate="2023-04-16T04:24:24.000" Score="6" ViewCount="728" Body="&lt;p&gt;Context: I am an undergraduate &amp;quot;self-taught&amp;quot; noob when it comes to QE. (I've just been using online resources and textbooks thus far.) There are no QE or DFT experts at my university (I have checked with multiple departments), and I have not been referred to experts that have the time to discuss my problems. I also do not have access to VASP.&lt;/p&gt;&#xA;&lt;p&gt;Issue: I have successfully gotten a few different calculations to work for simple systems on my university's HPC (i.e., bands.x, q2r.x, dos.x, pw.x, ph.x, matdyn.x, and so forth). However, I am struggling to produce an STM image (that I can display in XCrySDen), despite it seeming simpler than many other calculations.&lt;/p&gt;&#xA;&lt;p&gt;To my understanding I need to run:&lt;/p&gt;&#xA;&lt;p&gt;(0) relaxation calculation(s) like vc-relax and relax. (pw.x vc-relax, relax; I have good input files and successful outputs)&lt;/p&gt;&#xA;&lt;p&gt;(1) self-consistent calculation (pw.x scf; I have good input files and successful outputs)&lt;/p&gt;&#xA;&lt;p&gt;(2) a non-scf calc (pw.x nscf; I have good input files and successful outputs)&lt;/p&gt;&#xA;&lt;p&gt;(3) an STM calc (pp.x ... I guess my input file is wrong somehow)&lt;/p&gt;&#xA;&lt;p&gt;Question: As an example, for a simple graphene STM simulated scan, what would a successful, minimal sample input file contain? I cannot even get this to work.&lt;/p&gt;&#xA;&lt;p&gt;Note: I think it is easiest for everyone if I compare what files/advice the replies return to my own files, and determine my errors that way, rather than provide all my input files here and have someone try to find my errors. I am also familiar with the input file descriptions, various QE forums, and have looked for examples elsewhere.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your time, and for reading! It's possible my error is something small and stupid, but I would still very much appreciate hearing from those with more expertise than me.&lt;/p&gt;&#xA;" OwnerUserId="7016" LastEditorUserId="7016" LastEditDate="2023-04-16T04:29:53.717" LastActivityDate="2023-04-16T09:21:36.860" Title="Simulated STM Image with Quantum-ESPRESSO's pp.x" Tags="|quantum-espresso|solid-state-physics|materials-design|graphene|matter-modeling-specific-technology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10732" PostTypeId="2" ParentId="10731" CreationDate="2023-04-16T09:21:36.860" Score="9" Body="&lt;h2&gt;A minimal input file&lt;/h2&gt;&#xA;&lt;p&gt;For simulated STM, you can use &lt;code&gt;pp.x&lt;/code&gt;. A minimal input file might look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA; outdir='./outdir'&#xA; prefix='graphene'&#xA; plot_num=5&#xA; sample_bias=-0.0735&#xA;/&#xA;&amp;amp;PLOT&#xA; iflag=3&#xA; output_format=6&#xA; fileout=&amp;quot;graphene.cube&amp;quot;&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Explanation:&lt;/strong&gt; The value for &lt;code&gt;outdir&lt;/code&gt; directory and the &lt;code&gt;prefix&lt;/code&gt; are the same ones that you used for scf and nscf calculation. &lt;code&gt;plot_num=5&lt;/code&gt; tells us that we want to generate an STM image. The &lt;code&gt;sample_bias&lt;/code&gt; is optional. If you want, you can set it in Ry unit. The &lt;code&gt;iflag=3&lt;/code&gt; tells us that we want a 3D plot. The &lt;code&gt;output_format=6&lt;/code&gt; tells us that the output file will be a gaussian cube file and lastly we supplied the name of the output file. If you run this, you will get a &lt;code&gt;.cube&lt;/code&gt; file which can be opened using &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;noreferrer&quot;&gt;VESTA&lt;/a&gt;. Below I attached my result for graphene. You may want to slice the figure to get the 2D image using &lt;code&gt;Utilities &amp;gt; 2D Data Display&lt;/code&gt; menu in VESTA.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/amK0Pm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/amK0Pm.png&quot; alt=&quot;graphene.cube in vesta&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/YoPOwm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YoPOwm.png&quot; alt=&quot;sliced at 001&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you want to learn more such as how to choose the sample bias, and get an overall idea of how to do STM simulation, follow slides 22 to 26 of this &lt;a href=&quot;https://web.archive.org/web/20180712104115/https://www.fisica.uniud.it/%7Egiannozz/QE-Tutorial/tutorial_postproc.pdf&quot; rel=&quot;noreferrer&quot;&gt;HANDS-ON TUTORIAL ON THE QUANTUM-ESPRESSO PACKAGE: POST-PROCESSING&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;A (possibly) better way&lt;/h2&gt;&#xA;&lt;p&gt;There is a program called &lt;strong&gt;&lt;a href=&quot;https://aoterodelaroza.github.io/critic2/&quot; rel=&quot;noreferrer&quot;&gt;Critic2&lt;/a&gt;&lt;/strong&gt; that can do, along with many other things, STM calculation from various programs (not just Quantum ESPRESSO but also siesta, VASP etc.) For your purpose, you might want to follow this tutorial: &lt;a href=&quot;https://aoterodelaroza.github.io/critic2/examples/example_14_01_stmqe/&quot; rel=&quot;noreferrer&quot;&gt;Making STM plots with Quantum ESPRESSO and critic2&lt;/a&gt;. For example, with the same input files, I have obtained the following STM image. The unit cell STM image doesn't look good, but the &lt;span class=&quot;math-container&quot;&gt;$3\times3$&lt;/span&gt; one looks much better (and it is obtained by one extra command &lt;code&gt;cells 3 3&lt;/code&gt; only)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9X8mwm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9X8mwm.png&quot; alt=&quot;unit cell&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/7uPXMm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7uPXMm.png&quot; alt=&quot;3 3 supercell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;(I cannot figure out why the gnuplot script cannot fit the image here. The scalebar seems to be cut. Here, is the gnuplot script:)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set encoding iso_8859_1&#xA;set terminal postscript eps color enhanced 'Helvetica, 20'&#xA;set output 'constant_height_stm.eps'&#xA;&#xA;set palette rgb 34,35,36&#xA;set style line 1 lt 1 lw 1 lc rgb '#000000'&#xA;set style line 2 lt 1 lw 1 lc rgb '#000000'&#xA;&#xA;set title 'Constant height plot, c-axis coord. = 0.0265'&#xA;&#xA;set xrange [-3.659984E+00:7.319969E+00]&#xA;set yrange [0.000000E+00:6.339273E+00]&#xA;set xtics nomirror out&#xA;set ytics nomirror out&#xA;set xlabel 'x (\305)'&#xA;set ylabel 'y (\305)'&#xA;&#xA;unset key&#xA;set size ratio -1&#xA;&#xA;# set pm3d at b map interpolate 5,5 (if smoother plot needed)&#xA;set pm3d at b map&#xA;&#xA;set cbtics format '%.3f'&#xA;set cblabel 'Electron density (a.u.)'&#xA;&#xA;splot 'constant_height_stm.dat' u 3:4:5 w pm3d notitle ls 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-04-16T09:21:36.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10734" PostTypeId="1" CreationDate="2023-04-16T18:21:07.737" Score="2" ViewCount="30" Body="&lt;p&gt;I am designing a device that has tiny etched gratings (shown in red) in the silicon substrate, with various structures on either side of it (shown in green). I am wondering what the ideal way would be to manufacture such a device. Should I:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Manufacture the gratings first and then the green structures, using resists to protect the grating. However, there is a chance of contamination from the other manufacturing process.&lt;/li&gt;&#xA;&lt;li&gt;Manufacture the green structures first and then the gratings at the end, thus avoiding exposure of the gratings to contamination due to their small size.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jikD1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jikD1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7022" LastActivityDate="2023-04-16T18:21:07.737" Title="Optimal Manufacturing Process for a Device" Tags="|semiconductor|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-22T20:13:17.750" ContentLicense="CC BY-SA 4.0" />
  <row Id="10735" PostTypeId="1" AcceptedAnswerId="10736" CreationDate="2023-04-17T03:08:29.823" Score="8" ViewCount="1137" Body="&lt;p&gt;At real situation, it can happen, that a crystal can have defects, for instance, some of them are point defects — Schottky, Frenkel defects, line defects — dislocations,  planar defects — grain boundaries, twin boundaries. So is there a free software that can help to model a crystal structure with defects to get afterwards crystal nodes coordinates to prepare input file for a calculation, for example, in the Quantum Espresso? Or maybe is there some free Python scripts to model these things with or without visualization?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2023-06-13T21:49:52.697" Title="Is there a free software for modeling and graphical visualization crystals with defects?" Tags="|software-recommendations|one-topic-per-answer|visualization-software|atomic-simulation-environment|defects|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10736" PostTypeId="2" ParentId="10735" CreationDate="2023-04-17T08:53:56.357" Score="8" Body="&lt;p&gt;For &lt;em&gt;point&lt;/em&gt; defects like a Schottky pair, you can get the defect formation energies from DFT calculations at 0 K or from AIMD calculations at finite temperatures. For these, you can use codes like VASP or Quantum ESPRESSO. The uncertainty in these calculations is typically in the range of a few tenths of eV.&lt;/p&gt;&#xA;&lt;p&gt;VASP or Quantum ESPRESSO inputs/outputs are visualized using VESTA or XCrySDen.&lt;/p&gt;&#xA;&lt;p&gt;If you have a really good interatomic potential, e.g., a modified embedded-atom method (MEAM) potential, or an angular-dependent potential (ADP), you can also get &lt;em&gt;point&lt;/em&gt; defect formation energies from MD simulations employing codes like LAMMPS. The uncertainty in these calculations is typically in the range of 1-3 eV. Bigger uncertainty just means your potential is not suitable for this kind of calculation.&lt;/p&gt;&#xA;&lt;p&gt;For 1-D defects (e.g., dislocations) and 2-D defects (e.g., grain boundaries), LAMMPS is typically used to get the linear/interfacial energies of these defects.&lt;/p&gt;&#xA;&lt;p&gt;LAMMPS inputs/outputs are visualized using OVITO or VMD. For OVITO, you may need to use some modifications (e.g., Atomic Strain and then Color Coding) to be able to &lt;em&gt;see&lt;/em&gt; 1-D and 2-D defects.&lt;/p&gt;&#xA;&lt;p&gt;For 3-D defects, typically people resort to phase-field modeling, using codes like MOOSE. These calculations usually take many inputs from experiments and DFT/MD calculations.&lt;/p&gt;&#xA;&lt;p&gt;MOOSE outputs are visualized using PraraView or MOOSE's built-in software Peacock.&lt;/p&gt;&#xA;&lt;p&gt;Except for VASP, all these tools are free. OVITO has a free version and a Pro version.&lt;/p&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2023-06-13T21:49:52.697" LastActivityDate="2023-06-13T21:49:52.697" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10737" PostTypeId="1" CreationDate="2023-04-17T20:07:05.573" Score="2" ViewCount="20" Body="&lt;p&gt;I have a NAMD system with PBCs (FlexibleCell on) and I need to access the unit cell information to manually apply wrapping to some atoms in the system such that i may apply custom restraints to them.&lt;/p&gt;&#xA;&lt;p&gt;How can i access this information ? (not sure why tclForces doesn't have a wrap function built in like tclBC does).&lt;/p&gt;&#xA;" OwnerUserId="7031" LastActivityDate="2023-04-17T20:07:05.573" Title="How to access Unit Cell Dimensions inside tclForces Script (NAMD)?" Tags="|periodic-boundary-conditions|namd|" AnswerCount="0" CommentCount="0" ClosedDate="2023-10-22T20:14:08.060" ContentLicense="CC BY-SA 4.0" />
  <row Id="10738" PostTypeId="1" CreationDate="2023-04-18T06:35:55.720" Score="2" ViewCount="60" Body="&lt;p&gt;Looking to calculate partial atomic charges for a GCMC calculation. I have relaxed a structure with QE. Projwfc.x gives Lodwin charge of a Ni(II) atom as;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Atom #   1: total charge =  17.6172, s =  2.4126, p =  6.8500, d =  8.3546,&#xA;                 spin up      =   9.5784, s =  1.2145,&#xA;                 spin up      =   9.5784, p =  3.4344, pz=  1.1514, px=  1.1353, py=  1.1476,&#xA;                 spin up      =   9.5784, d =  4.9295, dz2=  0.9894, dxz=  0.9794, dyz=  0.9887, dx2-y2=  0.9864, dxy=  0.9856,&#xA;                 spin down    =   8.0388, s =  1.1981,&#xA;                 spin down    =   8.0388, p =  3.4157, pz=  1.1512, px=  1.1179, py=  1.1466,&#xA;                 spin down    =   8.0388, d =  3.4251, dz2=  0.7934, dxz=  0.7089, dyz=  0.5418, dx2-y2=  0.5462, dxy=  0.8347,&#xA;                 polarization =   1.5396, s =  0.0165, p =  0.0187, d =  1.5044,&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How do I convert from Lodwin to partial atomic charge? (Removing just the valence electrons, leaves an unreasonably high charge)&lt;/p&gt;&#xA;" OwnerUserId="6958" LastActivityDate="2023-04-18T06:35:55.720" Title="Partial atomic charge from lodwin charge - quantum espresso" Tags="|quantum-espresso|monte-carlo|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-22T20:16:04.827" ContentLicense="CC BY-SA 4.0" />
  <row Id="10739" PostTypeId="1" AcceptedAnswerId="11131" CreationDate="2023-04-18T07:55:45.523" Score="9" ViewCount="176" Body="&lt;p&gt;I read in papers (e.g. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2017/ra/c7ra00260b&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;) about AA stacking, where C atoms are above the B and N atoms, and AB stacking where one C atom is above the N or B atom, while the other C atom is above the h-BN hexagon.&lt;/p&gt;&#xA;&lt;p&gt;In this case, graphene stretches a little bit because of the 1.8% lattice mismatch.&lt;/p&gt;&#xA;&lt;p&gt;However, in the Udemy course 'Building 2D Material Heterostructures in VESTA' (&lt;a href=&quot;https://www.udemy.com/course/building-2d-material-heterostructures-in-vesta/&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;), graphene and hBN are placed on each other by making a &lt;span class=&quot;math-container&quot;&gt;$\sqrt{28}$&lt;/span&gt; supercell of graphene and &lt;span class=&quot;math-container&quot;&gt;$\sqrt{27}$&lt;/span&gt; supercell of hBN. The resulting heterostructure looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/f9wub.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/f9wub.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It has a lattice mismatch of only 0.02%.&lt;/p&gt;&#xA;&lt;p&gt;Which stacking to use in modelling? A simple AA or AB with 1.8% lattice mismatch or this one with a much lower lattice mismatch?&lt;/p&gt;&#xA;&lt;p&gt;Which structure is actually obtained experimentally?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-06-15T12:39:37.470" Title="How to stack graphene and hBN on top of each other?" Tags="|crystallography|geometry|2d-lattice|nanostructures|heterostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10740" PostTypeId="1" CreationDate="2023-04-18T08:45:42.853" Score="5" ViewCount="290" Body="&lt;p&gt;I want to apply an electric field pointing in z-direction to a two-dimensional crystal residing in the xy-plane using Quantum Espresso. So far I noticed that there are two distinct ways to do so either using the input parameters &lt;code&gt;tefield = .true.&lt;/code&gt; or &lt;code&gt;lelfield = .true.&lt;/code&gt; in the &lt;code&gt;&amp;amp;CONTROL&lt;/code&gt; card.&lt;/p&gt;&#xA;&lt;p&gt;The field should be homogeneous. Is &lt;code&gt;lelfield = .true.&lt;/code&gt; together with &lt;code&gt;efield_cart(3)   = 0.01&lt;/code&gt; the correct choice?&lt;/p&gt;&#xA;" OwnerUserId="2088" LastEditorUserId="6055" LastEditDate="2023-04-18T10:44:37.887" LastActivityDate="2023-04-18T10:44:37.887" Title="Electric field in QE calculation" Tags="|density-functional-theory|quantum-espresso|electric-field|" AnswerCount="0" CommentCount="4" ClosedDate="2023-11-16T02:15:27.700" ContentLicense="CC BY-SA 4.0" />
  <row Id="10741" PostTypeId="1" CreationDate="2023-04-18T14:28:56.743" Score="7" ViewCount="145" Body="&lt;p&gt;I am implementing the computation of Gibbs energies by their molecular parameters (structure, frequencies) in my program Chemcraft (the main task is the possibility to cut small frequencies which produce big errors in the vibrational entropy). The rotational entropy of nonlinear molecule is computed in RRHO approximation as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$S_\text{rot} = R\left(\ln\left(\frac{2^\frac{9}{2}\pi^\frac{7}{2}(kt)^\frac{3}{2}(I_{xx}I_{yy}I_{zz})^\frac{1}{2}}{h^3\sigma}\right)+\frac{3}{2}\right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here sigma is the symmetry number, depending on the point group. I don’t understand what this value means. At one textbook I found that &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt; symmetry and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$C_i$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$C_s$&lt;/span&gt; symmetry; &lt;span class=&quot;math-container&quot;&gt;$5$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$C_5$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_{5v}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C_{5h}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$S_{10}$&lt;/span&gt; symmetry and &lt;span class=&quot;math-container&quot;&gt;$10$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$D_5$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$D_{5d}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$D_{5h}$&lt;/span&gt; symmetry. Is this true?&lt;/p&gt;&#xA;&lt;p&gt;I find these formulas slightly strange. For example, if we have a benzene molecule with &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; symmetry, we can compute its entropy; but if we alter a coordinate of one atom with &lt;span class=&quot;math-container&quot;&gt;$0.000001$&lt;/span&gt;Å, the symmetry lowers to &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; and the entropy becomes different (I verified this with Gaussian). Don’t you find this strange?&lt;/p&gt;&#xA;&lt;p&gt;I like to talk about physics on physics.stackexchange.com, and I have a feeling that the thermodynamics is rather a philosophy, not a science (this is related to the &lt;span class=&quot;math-container&quot;&gt;$S=k\ln(W)$&lt;/span&gt; formula where it is not fully clear what means the &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;So, my question is: maybe it will be useful if I add the option “Do not use the symmetry number” in Chemcraft? This option will compute the rotational entropy without the &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3745" LastEditorUserId="7" LastEditDate="2023-04-20T20:19:58.657" LastActivityDate="2023-04-20T20:19:58.657" Title="Computing the rotational entropy in RRHO approximation" Tags="|quantum-chemistry|gaussian|symmetry|entropy|chemcraft|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10742" PostTypeId="1" CreationDate="2023-04-18T16:28:22.030" Score="9" ViewCount="624" Body="&lt;p&gt;I am studying a Diels-Alder reaction of cyclopentadiene and maleic anhydride. I know that AMBER can be used to run MD simulations on proteins, however would I be able to use these small molecules to run a simulation?&lt;/p&gt;&#xA;" OwnerUserId="7035" LastEditorUserId="7" LastEditDate="2023-04-19T14:12:26.840" LastActivityDate="2023-04-19T14:12:26.840" Title="Can AMBER be used for a molecular dynamics simulation of a Diels-Alder reaction?" Tags="|molecular-dynamics|reaction-mechanism|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10743" PostTypeId="1" CreationDate="2023-04-18T21:05:52.400" Score="5" ViewCount="215" Body="&lt;p&gt;After running the Molecular dynamics(MD) simulation, I'd like to see the excitation of phonons during MD, so I'd like to project the trajectory onto a set of phonons, I've seen &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0008622315005230&quot; rel=&quot;noreferrer&quot;&gt;some paper&lt;/a&gt; use the method called normal mode decomposition.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&#xA;is there some software that could do this kind of job?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2023-05-01T11:40:36.487" Title="project molecular dynamics trajectory onto phonons by normal mode decomposition" Tags="|molecular-dynamics|phonons|phonon-dispersion|phonon-density-of-state|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10744" PostTypeId="2" ParentId="10742" CreationDate="2023-04-19T07:19:56.480" Score="8" Body="&lt;p&gt;Short Answer No. To elaborate, AMBER or CHARMM or any of the Classical force fields are employed for equilibrium MD simulations. The FF description would generally follow the format of energy terms of bonds, then angles and dihedrals and other parameters. These are parameterized for their equilibrium values and are represented as harmonic springs. In your particular use case, you should ideally consider a force field like ReaxFF which is employed to study reactions.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-04-19T07:19:56.480" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10745" PostTypeId="2" ParentId="10742" CreationDate="2023-04-19T07:43:06.050" Score="9" Body="&lt;p&gt;Hemanth has implied it, but I think it is better to say more directly: AMBER and other classical forcefields cannot simulate bond breaking or reaction. If you stretch a bond in these simulations, however far you stretch them, the atoms stay bonded in the original way and return to the original molecular geometry when you let them go.&lt;/p&gt;&#xA;&lt;p&gt;If you want an MD simulation that allows reactions and bond breaking, you need a reactive forcefield (ReaxFF) or simulation based on a theory that includes electrons, etc (DFT, DFTB etc)&lt;/p&gt;&#xA;" OwnerUserId="91" LastActivityDate="2023-04-19T07:43:06.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10747" PostTypeId="2" ParentId="10741" CreationDate="2023-04-19T12:15:43.820" Score="6" Body="&lt;p&gt;The symmetry number is the order (number of symmetry elements) of the rotational subgroup of the molecular point group. I.e. the rotational subgroup of &lt;span class=&quot;math-container&quot;&gt;$C_{2v}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$C_2$&lt;/span&gt;, the rotational subgroup of &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$D_6$&lt;/span&gt;, etc. This is what comes out of the stat. mech. treatment within the Rigid-Rotor Harmonic-Oscillator (RRHO) approximation, although the above formula for &lt;span class=&quot;math-container&quot;&gt;$S_\text{rot}$&lt;/span&gt; involves additional assumptions, as the rotational energy levels for a general molecule cannot be condensed into a closed formula for the partition function.&lt;/p&gt;&#xA;&lt;p&gt;Just to follow up on the illustrative example given by wzkchem5, the RRHO expression for the vibrational entropy breaks down when a frequency goes to zero. In the harmonic approximation, the vibrational entropy goes to infinity when the frequency goes to zero, and contributions from frequencies less than, say, &lt;span class=&quot;math-container&quot;&gt;$\pu{100 cm-1}$&lt;/span&gt; are likely severely overestimated. If the motion in reality corresponds to an internal rotation, then the limiting entropy for a free rotor is &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, and there are suggestions for how to interpolate between these limits, for example work by Stefan Grimme.&lt;/p&gt;&#xA;" OwnerUserId="279" LastEditorUserId="7" LastEditDate="2023-04-20T20:11:49.833" LastActivityDate="2023-04-20T20:11:49.833" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10748" PostTypeId="2" ParentId="10742" CreationDate="2023-04-19T12:46:56.387" Score="5" Body="&lt;p&gt;As previously mentioned, you can not use classical molecular dynamics codes to study reactions.&lt;/p&gt;&#xA;&lt;p&gt;Faster than running MD based on DFT, you can try the &lt;a href=&quot;https://xtb-docs.readthedocs.io/en/latest/contents.html&quot; rel=&quot;noreferrer&quot;&gt;xTB&lt;/a&gt; software, where you will have at least three different semiempirical Hamiltonian to be used with the MD calculations.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-04-19T12:46:56.387" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10749" PostTypeId="1" AcceptedAnswerId="10755" CreationDate="2023-04-19T14:11:41.757" Score="5" ViewCount="80" Body="&lt;p&gt;In the paper '&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2016.09.022&quot; rel=&quot;noreferrer&quot;&gt;Improvements on non-equilibrium and transport Green function techniques: The next-generation transiesta&lt;/a&gt; and in particular in figure 10b, the I/V curve of a specific model is reported.&lt;/p&gt;&#xA;&lt;p&gt;Naively, I would expect for the I to be 0 when the V is 0. Why in this case is different?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-04-20T12:16:43.547" Title="I/V curve on Transiesta paper" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10750" PostTypeId="1" CreationDate="2023-04-19T14:17:14.620" Score="3" ViewCount="21" Body="&lt;p&gt;From the paper &lt;a href=&quot;http://dx.doi.org/10.1016/j.cpc.2016.09.022&quot; rel=&quot;nofollow noreferrer&quot;&gt;Improvements on non-equilibrium and transport Green function&#xA;techniques: The next-generation transiesta&lt;/a&gt;, and in particular in figure 10b, an I/V curve is reported. I understand that from this the Seeback coefficient can be extracted.&lt;/p&gt;&#xA;&lt;p&gt;However, in this figure, a curve calculated with two electrodes at the same temperature (300K) is reported. As far as my understanding goes, the Seeback coefficient should be calculated at a gradient of T. Is my understanding wrong? Can someone shed light on specifically how the Seeback coefficient is extracted?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-04-19T14:17:14.620" Title="Calculation of Seeback coefficient on Transiesta" Tags="|siesta|electronic-transport|" AnswerCount="0" CommentCount="1" ClosedDate="2023-11-08T00:23:26.710" ContentLicense="CC BY-SA 4.0" />
  <row Id="10751" PostTypeId="2" ParentId="10741" CreationDate="2023-04-19T14:22:21.173" Score="5" Body="&lt;p&gt;The argument &amp;quot;a slightly perturbed benzene molecule has an entropy that differs a lot from the entropy of the equilibrium structure&amp;quot; does not hold, because entropies are only defined for equilibrium geometries (when they are calculated by e.g. the harmonic approximation) or phase space regions with non-zero measure (when they are calculated by phase space integration). The latter case is self-evident; the former case exists because when we talk about the entropy of an equilibrium structure, we are actually talking about the entropy in the basin of attraction around that equilibrium structure, i.e. the entropy of the molecule when it is free to wander around in the local PES basin but not beyond. Now consider the entropy of a non-equilibrium structure. How would you define it? If you can define it at all, you have to use the &amp;quot;basin of attraction&amp;quot; definition, but then it is the same as the entropy of the equilibrium geometry. This is along the same line as the famous rule that RRHO thermochemical properties can only be obtained by frequency calculations at equilibrium structures. Thus, if you expect that the exact converged structure has &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; symmetry, then you should use the symmetry number appropriate for &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; even if your (not fully converged) optimized structure has &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; symmetry; in this case, the entropy at that  &lt;span class=&quot;math-container&quot;&gt;$C_1$&lt;/span&gt; structure is not only non-calculable, but not even defined (unless you trivially define it as the entropy of the &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; structure).&lt;/p&gt;&#xA;&lt;p&gt;Nevertheless, it is possible to make the argument more rigorous by the following way. Suppose you study the equilibrium structures of a series of hexa-substituted benzenes, with increasing tendency of second-order Jahn-Teller symmetry breaking into the bond-alternating &lt;span class=&quot;math-container&quot;&gt;$D_{3h}$&lt;/span&gt; structure. Then you'll find that the point group of the molecule changes abruptly from &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$D_{3h}$&lt;/span&gt; somewhere in the series, where the &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; now becomes a saddle point. The symmetry number thus suddenly reduces from 12 to 6, such that the entropy of each of the &lt;span class=&quot;math-container&quot;&gt;$D_{3h}$&lt;/span&gt; structures will experience a finite jump from the trend line, similar as what you said. This is indicative of a breakdown of the RRHO approximation (since near the point where the &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; changes from a minimum to a saddle point, one of the vibrational frequencies is extremely close to 0, therefore the associating vibration mode is extremely anharmonic). I believe no single-structure based anharmonic correction scheme will remove this finite jump, either, and you probably have to treat that vibrational mode by e.g. the WKB approximation, in order to properly describe the entropy of such systems.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-04-19T14:22:21.173" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10752" PostTypeId="1" AcceptedAnswerId="10761" CreationDate="2023-04-19T15:49:36.073" Score="5" ViewCount="128" Body="&lt;p&gt;I am new to the md simulation community. I have a peptide which is helical in a bilayer. I want to calculate the angle of the peptide relative to the bilayer with gromacs. For that, I created an index with the peptide residue at the  N terminal and the C terminal, so that I can then create a vector with the gmx gangle command. The problem is that for all my trials the computer says me : Inconsistency in user input:&#xA;Number of positions in selection 2 in the first group not divisible by 3 and I don't understand what It means, I tried to find the explanation on internet but I didn't understand the explanation either.&#xA;Can anyone of you kindly suggest how can I use this gmx gangle command to compute the angle made by the helical's axis with the normal to the plane? Thank you very much in advance.&lt;/p&gt;&#xA;" OwnerUserId="7043" LastActivityDate="2023-04-21T11:18:32.090" Title="Time evolution of angle made by the helix with the normal to the plane using gromacs" Tags="|molecular-dynamics|gromacs|vmd|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10753" PostTypeId="1" CreationDate="2023-04-19T15:52:13.723" Score="2" ViewCount="59" Body="&lt;p&gt;Would it be possible to calculate the figure-of-merit:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ZT =\frac{S^2\sigma}{\kappa}T,\tag{1}$$&lt;/span&gt;&#xA;with Transiesta and TBTrans?&lt;/p&gt;&#xA;&lt;p&gt;If not, which other programs can be used? I've only read about Gollum.&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-04-19T16:56:43.310" LastActivityDate="2023-04-19T16:56:43.310" Title="Figure-of-merit with Transiesta/TBtrans" Tags="|software-recommendations|one-topic-per-answer|siesta|electronic-transport|" AnswerCount="0" CommentCount="4" ClosedDate="2023-11-08T00:23:46.640" ContentLicense="CC BY-SA 4.0" />
  <row Id="10754" PostTypeId="1" CreationDate="2023-04-19T23:02:04.800" Score="3" ViewCount="85" Body="&lt;p&gt;When I run a tranSIESTA calculation, the SCF converges, and the TBtrans output shows the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                           ************************ &#xA;                           *  WELCOME TO TBtrans  * &#xA;                           ************************ &#xA;reinit: Reading from scat.fdf&#xA;reinit: -------------------------------------------------------------------&#xA;reinit: System Name: scat&#xA;reinit: -----------------------------------------------------------------------&#xA;reinit: System Label: scat&#xA;reinit: -------------------------------------------------------------------&#xA; Kpoints in:            1 . Kpoints trimmed:            1&#xA;tbt: Number of transport k-points = 1&#xA;tbt: Method = Monkhorst-Pack grid.&#xA;tbt: k-grid: Supercell and displacements&#xA;tbt:            1   0   0      0.000&#xA;tbt:            0   1   0      0.000&#xA;tbt:            0   0   1      0.000&#xA;&#xA;&#xA;tbt: **************************************************************&#xA;tbt: Electronic temperature (reference)             =  299.9869 K&#xA;tbt: No applied bias&#xA;tbt: Calculate transmission only using diag(Gf)     =    F&#xA;tbt: Saving bulk transmission for electrodes        =    F&#xA;tbt: Saving DOS from bulk electrodes                =    F&#xA;tbt: Saving DOS from Green function                 =    T&#xA;tbt: Saving DOS from all spectral functions         =    T&#xA;tbt: Saving bond currents (orb-orb)                 =    F&#xA;tbt: Saving DM from Green function                  =    F&#xA;tbt: Saving DM from spectral functions              =    F&#xA;tbt: Saving COOP from Green function                =    F&#xA;tbt: Saving COOP from spectral functions            =    F&#xA;tbt: Saving COHP from Green function                =    F&#xA;tbt: Saving COHP from spectral functions            =    F&#xA;tbt: Calc. # transmission eigenvalues               =  0&#xA;tbt: Calc. T between all electrodes                 =    F&#xA;tbt: Calc. total T out of electrodes                =    F&#xA;tbt: Non-polarized Hamiltonian&#xA;tbt: BTD creation algorithm                         =    speed&#xA;tbt: BTD spectral function algorithm                =    propagation&#xA;tbt: Divide and conquer diagonalization             =    F&#xA;tbt: Assume LAPACK &amp;lt;i|S|j&amp;gt; = delta_ij               =    F&#xA;tbt: Saving downfolded self-energies                =    F&#xA;tbt: No delta Hamiltonian&#xA;tbt: No delta self-energy&#xA;tbt: Data files stored in current folder&#xA;tbt: No compression of TBT.nc files&#xA;tbt: Default NetCDF precision                       =    single&#xA;tbt: Use parallel MPI-IO for NetCDF file            =    F&#xA;tbt:           &amp;gt;&amp;gt; Electrodes &amp;lt;&amp;lt; &#xA;tbt: &amp;gt;&amp;gt; Left&#xA;tbt:   Electrode cell pivoting: E1, E2, E3          = A1, A2, A3&#xA;tbt:   In-core self-energy calculation&#xA;tbt:   Electrode TSHS file                          = ./elec.TSHS&#xA;tbt:   # atoms used in electrode                    =   44&#xA;tbt:   Electrode Bloch unity [E1 x E2 x E3]         = 1 x 1 x 1&#xA;tbt:   Position in geometry                         = 1 -- 44&#xA;tbt:   Semi-infinite direction for electrode        = negative wrt. E3&#xA;tbt:   Chemical shift                               =    0.000000 eV&#xA;tbt:   Electronic temperature                       =  299.986869 K&#xA;tbt:   Gamma-only electrode                         =    T&#xA;tbt:   Bulk H, S in electrode region                =    T&#xA;tbt:   Electrode self-energy imaginary Eta          =  0.1000E-03  eV&#xA;tbt:   Electrode self-energy accuracy               =  0.1000E-13  eV&#xA;tbt:   Electrode inter-layer distance (semi-inf)    =    1.3874  Ang&#xA;tbt: &amp;gt;&amp;gt; Right&#xA;tbt:   Electrode cell pivoting: E1, E2, E3          = A1, A2, A3&#xA;tbt:   In-core self-energy calculation&#xA;tbt:   Electrode TSHS file                          = ./elec.TSHS&#xA;tbt:   # atoms used in electrode                    =   44&#xA;tbt:   Electrode Bloch unity [E1 x E2 x E3]         = 1 x 1 x 1&#xA;tbt:   Position in geometry                         = 265 -- 308&#xA;tbt:   Semi-infinite direction for electrode        = positive wrt. E3&#xA;tbt:   Chemical shift                               =    0.000000 eV&#xA;tbt:   Electronic temperature                       =  299.986869 K&#xA;tbt:   Gamma-only electrode                         =    T&#xA;tbt:   Bulk H, S in electrode region                =    T&#xA;tbt:   Electrode self-energy imaginary Eta          =  0.1000E-03  eV&#xA;tbt:   Electrode self-energy accuracy               =  0.1000E-13  eV&#xA;tbt:   Electrode inter-layer distance (semi-inf)    =    1.3874  Ang&#xA;ts:              &amp;gt;&amp;gt; TBtrans contour &amp;lt;&amp;lt; &#xA;ts: Device Green function imaginary Eta             =  0.000     eV&#xA;ts: Contour name                                    =    TBT.Contour.line&#xA;ts:   line contour E_min                            =   -2.0000 eV&#xA;ts:   line contour E_max                            =    2.0000 eV&#xA;ts:   line contour points                           =  400&#xA;ts:   line contour method                           =    Mid-rule&#xA;tbt: **************************************************************&#xA;&#xA;tbt: &amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&#xA;%block TBT.Contours&#xA;    line&#xA;%endblock TBT.Contours&#xA;&#xA;%block TBT.Contour.line&#xA;  part line&#xA;     from -2. eV to 2. eV&#xA;      delta 0.01 eV&#xA;        method mid-rule&#xA;%endblock TBT.Contour.line&#xA;tbt: &amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&amp;lt;&#xA;&#xA;************************ Begin: TBT CHECKS AND WARNINGS ************************&#xA; ** Speed up the execution by utilizing parallel I/O&#xA;  &amp;gt; TBT.CDF.MPI true&#xA;************************ End: TBT CHECKS AND WARNINGS **************************&#xA;&#xA;Device information (full):&#xA;  &amp;lt;sparsity:scat.TSHS&#xA;    nrows_g=3780 nrows=3780 sparsity=.1129 nnzs=1613836, refcount: 3&amp;gt;&#xA;&#xA;Electrode information:&#xA;&#xA;  &amp;lt;sparsity:./elec.TSHS&#xA;    nrows_g=540 nrows=540 sparsity=.7906 nnzs=230548, refcount: 3&amp;gt;&#xA;  &amp;lt;sparsity:(TM [--,--, 0] of: ./elec.TSHS)&#xA;    nrows_g=540 nrows=540 sparsity=.3644 nnzs=106260, refcount: 3&amp;gt;&#xA;  &amp;lt;sparsity:(TM [--,--,-1] of: ./elec.TSHS)&#xA;    nrows_g=540 nrows=540 sparsity=.2131 nnzs=62144, refcount: 3&amp;gt;&#xA; Left principal cell is perfect!&#xA;&#xA;  &amp;lt;sparsity:./elec.TSHS&#xA;    nrows_g=540 nrows=540 sparsity=.7906 nnzs=230548, refcount: 3&amp;gt;&#xA;  &amp;lt;sparsity:(TM [--,--, 0] of: ./elec.TSHS)&#xA;    nrows_g=540 nrows=540 sparsity=.3644 nnzs=106260, refcount: 3&amp;gt;&#xA;  &amp;lt;sparsity:(TM [--,--, 1] of: ./elec.TSHS)&#xA;    nrows_g=540 nrows=540 sparsity=.2131 nnzs=62144, refcount: 3&amp;gt;&#xA; Right principal cell is perfect!&#xA;&#xA;&#xA;tbt: Analyzing electrode sparsity pattern and electrode pivot-tables&#xA;&#xA;*** WARNING! Removed 124288 elements which connect electrodes across the device region!&#xA;&#xA;tbt: BTD pivoting scheme for electrode (Left): atom+Left&#xA;Region (2700): [O]-calculation&#xA;  [ 541 -- 3240 ]&#xA;Region (540): Connect-Graph ()&#xA;  [ 1 -- 540 ]&#xA;The electrode down-folding region is 0 in the device region. Please expand your device region.&#xA;The electrode down-folding region is 0 in the device region. Please expand your device region.&#xA;Stopping Program from Node:    0&#xA;Stopping Program from Node:    0&#xA;--------------------------------------------------------------------------&#xA;MPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD&#xA;with errorcode 1.&#xA;&#xA;NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.&#xA;You may or may not see output from other processes, depending on&#xA;exactly when Open MPI kills them.&#xA;--------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the input calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SolutionMethod        Transiesta&#xA;&#xA;&#xA; &#xA;SystemName          scat&#xA;SystemLabel         scat&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SPECIES AND BASIS&#xA;&#xA;# Number of species &#xA;&#xA;PAO.BasisSize    DZP&#xA;PAO.EnergyShift  0.005 Ry&#xA;XC.functional   GGA&#xA;XC.authors      PBE&#xA;# ---------------------------------------------------------------------------&#xA;# Lattice&#xA;# ---------------------------------------------------------------------------&#xA;&#xA;LatticeConstant             1.00 Ang&#xA;&#xA;%block LatticeVectors&#xA;  38.6768100000    0.0000000000    0.0000000000&#xA;   0.0000000000   18.6851730000    0.0000000000&#xA;   0.0000000000    0.0000000000   30.1042280000&#xA;%endblock LatticeVectors&#xA;&#xA;# ---------------------------------------------------------------------------&#xA;# Species and Atoms&#xA;# ---------------------------------------------------------------------------&#xA;&#xA;NumberOfSpecies        2&#xA;NumberOfAtoms         308&#xA;&#xA;%block ChemicalSpeciesLabel&#xA;  1   6    C&#xA;  2   1    H&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;# ---------------------------------------------------------------------------&#xA;# Atomic Coordinates&#xA;# ---------------------------------------------------------------------------&#xA;&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;     2.382124030     9.947903380     1.477394770    1&#xA;     4.860867040     9.947902900     1.485178540    1&#xA;     7.333441770     9.947895520     1.480987940    1&#xA;     9.809049030     9.947897240     1.482661500    1&#xA;    12.280587220     9.947898690     1.483191640    1&#xA;    14.754631820     9.947904150     1.481319140    1&#xA;    17.227337500     9.947904520     1.483830520    1&#xA;    19.697489200     9.947908640     1.481879250    1&#xA;    22.174671570     9.947905950     1.480422050    1&#xA;    24.621016910     9.947904870     1.510384170    1&#xA;     1.166765930     9.947910660     3.653015820    1&#xA;     3.618228130     9.947908220     3.623496400    1&#xA;     6.099269120     9.947906590     3.625171600    1&#xA;     8.570402150     9.947903840     3.627024140    1&#xA;    11.044726030     9.947905640     3.623946660    1&#xA;    13.518976140     9.947911980     3.626830320    1&#xA;    15.988974480     9.947911870     3.625958590    1&#xA;    18.464420820     9.947912110     3.624170140    1&#xA;    20.934451480     9.947911350     3.628550790    1&#xA;    23.408430950     9.947912850     3.621127820    1&#xA;     1.166795710     9.947899270     0.739807800    1&#xA;     3.618257410     9.947900570     0.769353230    1&#xA;     6.099266620     9.947895170     0.767652400    1&#xA;     8.570396160     9.947895340     0.765752800    1&#xA;    11.044719240     9.947894900     0.768777320    1&#xA;    13.518967180     9.947899740     0.765973090    1&#xA;    15.988982230     9.947901030     0.766886840    1&#xA;    18.464416860     9.947904980     0.768749590    1&#xA;    20.934469120     9.947903800     0.764402670    1&#xA;    23.408449860     9.947903490     0.771834920    1&#xA;     2.382114000     9.947907190     2.915416910    1&#xA;     4.860857660     9.947904120     2.907667790    1&#xA;     7.333442290     9.947900740     2.911778090    1&#xA;     9.809077290     9.947901710     2.910068240    1&#xA;    12.280579530     9.947907490     2.909559000    1&#xA;    14.754651260     9.947907930     2.911525370    1&#xA;    17.227316290     9.947909520     2.909089240    1&#xA;    19.697500000     9.947912290     2.911037910    1&#xA;    22.174666730     9.947909110     2.912556810    1&#xA;    24.621010220     9.947912200     2.882607540    1&#xA;     0.201256320     9.947903870     1.256218750    2&#xA;     0.201235990     9.947915730     3.136550830    2&#xA;    25.582822460     9.947911930     3.402598090    2&#xA;    25.582829770     9.947901560     0.990383820    2&#xA;     2.382124030     9.947903380    27.281018770    1&#xA;     4.860867040     9.947902900    27.288802540    1&#xA;     7.333441770     9.947895520    27.284611940    1&#xA;     9.809049030     9.947897240    27.286285500    1&#xA;    12.280587220     9.947898690    27.286815640    1&#xA;    14.754631820     9.947904150    27.284943140    1&#xA;    17.227337500     9.947904520    27.287454520    1&#xA;    19.697489200     9.947908640    27.285503250    1&#xA;    22.174671570     9.947905950    27.284046050    1&#xA;    24.621016910     9.947904870    27.314008170    1&#xA;     1.166765930     9.947910660    29.456639820    1&#xA;     3.618228130     9.947908220    29.427120400    1&#xA;     6.099269120     9.947906590    29.428795600    1&#xA;     8.570402150     9.947903840    29.430648140    1&#xA; 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    2.382124030     9.947903380    10.078602770    1&#xA;     4.860867040     9.947902900    10.086386540    1&#xA;     7.333441770     9.947895520    10.082195940    1&#xA;     9.809049030     9.947897240    10.083869500    1&#xA;    12.280587220     9.947898690    10.084399640    1&#xA;    14.754631820     9.947904150    10.082527140    1&#xA;    17.227337500     9.947904520    10.085038520    1&#xA;    19.697489200     9.947908640    10.083087250    1&#xA;    22.174671570     9.947905950    10.081630050    1&#xA;    24.621016910     9.947904870    10.111592170    1&#xA;     1.166765930     9.947910660    12.254223820    1&#xA;     3.618228130     9.947908220    12.224704400    1&#xA;     6.099269120     9.947906590    12.226379600    1&#xA;     8.570402150     9.947903840    12.228232140    1&#xA;    11.044726030     9.947905640    12.225154660    1&#xA;    13.518976140     9.947911980    12.228038320    1&#xA;    15.988974480     9.947911870    12.227166590    1&#xA;    18.464420820     9.947912110    12.225378140    1&#xA;    20.934451480     9.947911350    12.229758790    1&#xA;    23.408430950     9.947912850    12.222335820    1&#xA;     1.166795710     9.947899270     9.341015800    1&#xA;     3.618257410     9.947900570     9.370561230    1&#xA;     6.099266620     9.947895170     9.368860400    1&#xA;     8.570396160     9.947895340     9.366960800    1&#xA;    11.044719240     9.947894900     9.369985320    1&#xA;    13.518967180     9.947899740     9.367181090    1&#xA;    15.988982230     9.947901030     9.368094840    1&#xA;    18.464416860     9.947904980     9.369957590    1&#xA;    20.934469120     9.947903800     9.365610670    1&#xA;    23.408449860     9.947903490     9.373042920    1&#xA;     2.382114000     9.947907190    11.516624910    1&#xA;     4.860857660     9.947904120    11.508875790    1&#xA;     7.333442290     9.947900740    11.512986090    1&#xA;     9.809077290     9.947901710    11.511276240    1&#xA;    12.280579530     9.947907490    11.510767000    1&#xA;    14.754651260     9.947907930    11.512733370    1&#xA;    17.227316290     9.947909520    11.510297240    1&#xA;    19.697500000     9.947912290    11.512245910    1&#xA;    22.174666730     9.947909110    11.513764810    1&#xA;    24.621010220     9.947912200    11.483815540    1&#xA;     0.201256320     9.947903870     9.857426750    2&#xA;     0.201235990     9.947915730    11.737758830    2&#xA;    25.582822460     9.947911930    12.003806090    2&#xA;    25.582829770     9.947901560     9.591591820    2&#xA;     2.382124030     9.947903380     5.777998770    1&#xA;     4.860867040     9.947902900     5.785782540    1&#xA;     7.333441770     9.947895520     5.781591940    1&#xA;     9.809049030     9.947897240     5.783265500    1&#xA;    12.280587220     9.947898690     5.783795640    1&#xA;    14.754631820     9.947904150     5.781923140    1&#xA;    17.227337500     9.947904520     5.784434520    1&#xA;    19.697489200     9.947908640     5.782483250    1&#xA;    22.174671570     9.947905950     5.781026050    1&#xA;    24.621016910     9.947904870     5.810988170    1&#xA;     1.166765930     9.947910660     7.953619820    1&#xA;     3.618228130     9.947908220     7.924100400    1&#xA;     6.099269120     9.947906590     7.925775600    1&#xA;     8.570402150     9.947903840     7.927628140    1&#xA;    11.044726030     9.947905640     7.924550660    1&#xA;    13.518976140     9.947911980     7.927434320    1&#xA;    15.988974480     9.947911870     7.926562590    1&#xA;    18.464420820     9.947912110     7.924774140    1&#xA;    20.934451480     9.947911350     7.929154790    1&#xA;    23.408430950     9.947912850     7.921731820    1&#xA;     1.166795710     9.947899270     5.040411800    1&#xA;     3.618257410     9.947900570     5.069957230    1&#xA;     6.099266620     9.947895170     5.068256400    1&#xA;     8.570396160     9.947895340     5.066356800    1&#xA;    11.044719240     9.947894900     5.069381320    1&#xA;    13.518967180     9.947899740     5.066577090    1&#xA;    15.988982230     9.947901030     5.067490840    1&#xA;    18.464416860     9.947904980     5.069353590    1&#xA;    20.934469120     9.947903800     5.065006670    1&#xA;    23.408449860     9.947903490     5.072438920    1&#xA;     2.382114000     9.947907190     7.216020910    1&#xA;     4.860857660     9.947904120     7.208271790    1&#xA;     7.333442290     9.947900740     7.212382090    1&#xA;     9.809077290     9.947901710     7.210672240    1&#xA;    12.280579530     9.947907490     7.210163000    1&#xA;    14.754651260     9.947907930     7.212129370    1&#xA;    17.227316290     9.947909520     7.209693240    1&#xA;    19.697500000     9.947912290     7.211641910    1&#xA;    22.174666730     9.947909110     7.213160810    1&#xA;    24.621010220     9.947912200     7.183211540    1&#xA;     0.201256320     9.947903870     5.556822750    2&#xA;     0.201235990     9.947915730     7.437154830    2&#xA;    25.582822460     9.947911930     7.703202090    2&#xA;    25.582829770     9.947901560     5.290987820    2  &#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA; # K-points&#xA;%block kgrid_Monkhorst_Pack&#xA;   1    0    0   0.0&#xA;   0    1    0   0.0&#xA;   0    0   100   0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SCF variables&#xA;&#xA;DM.MixSCF1   T&#xA;MaxSCFIterations      30000           # Maximum number of SCF iter&#xA;DM.MixingWeight       0.05          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.d-4         # Tolerance in maximum difference&#xA;DM.UseSaveDM          true          # to use continuation files&#xA;DM.NumberPulay        5&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;# MD variables&#xA;&#xA;MD.FinalTimeStep 1&#xA;MD.TypeOfRun CG&#xA;MD.NumCGsteps     000&#xA;MD.UseSaveXV      .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;# Output variables&#xA;&#xA;WriteMullikenPop                1&#xA;WriteBands                      .false.&#xA;SaveRho                         .true.&#xA;SaveDeltaRho                    .true.&#xA;SaveHS                          .true.&#xA;SaveElectrostaticPotential      .true. &#xA;SaveTotalPotential              .true.&#xA;WriteCoorXmol                   .true.&#xA;WriteMDXmol                     .true.&#xA;WriteMDhistory                  .false.&#xA;WriteEigenvalues                .true.&#xA;XML.Write                       .true.&#xA;SaveBaderCharge .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;#Other options&#xA;&#xA;TS.HS.Save          .true.&#xA;TS.DE.Save          .true.&#xA;ParallelOverK       .true.&#xA;User.Basis          .true.&#xA;Diag.ParallelOverK  .true. &#xA;&#xA;==================================================&#xA;==================================================&#xA;#####################TRANSIESTA###################&#xA;&#xA;# Bias voltage&#xA;&#xA;&#xA;TS.Voltage 0.0 eV&#xA;&#xA;&#xA;&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;&#xA;TS.Elecs.Bulk true&#xA;TS.Elecs.DM.Update none&#xA;TS.Elecs.GF.ReUse false&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&#xA;%block TS.Elec.Left&#xA;  TSHS ./elec.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a3&#xA;  elec-pos begin 1&#xA;%endblock TS.Elec.Left&#xA;&#xA;%block TS.Elec.Right&#xA;  TSHS ./elec.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir +a3&#xA;  elec-pos end -1&#xA;%endblock TS.Elec.Right&#xA;&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.c-Left&#xA;  part circle&#xA;   from   -40.00000 eV + V/2 to -10. kT + V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Left&#xA;%block TS.Contour.t-Left&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Left&#xA;%block TS.Contour.c-Right&#xA;  part circle&#xA;   from   -40.00000 eV - V/2 to -10. kT - V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Right&#xA;%block TS.Contour.t-Right&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Right&#xA;&#xA;TS.Contours.nEq.Eta 0.0001 eV&#xA;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;    delta 0.01 eV&#xA;     method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA;#%block LocalDensityOfStates&#xA;#-2.21 0.00 eV&#xA;#%endblock LocalDensityOfStates&#xA;&#xA;TBT.DOS.A.All T&#xA;TBT.DOS.Gf   T&#xA;TS.SolutionMethod btd&#xA;TS.BTD.Pivot atom+Left&#xA;TS.Elecs.Neglect.Principal true&#xA;==================================================&#xA;==================================================&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I solve this error?&lt;/p&gt;&#xA;" OwnerUserId="5426" LastEditorUserId="5" LastEditDate="2023-12-05T19:11:49.620" LastActivityDate="2024-01-04T21:04:25.527" Title="Error in TranSIESTA: &quot;The electrode down-folding region is 0 in the device region&quot;" Tags="|density-functional-theory|siesta|graphene|quantum-dots|transport|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10755" PostTypeId="2" ParentId="10749" CreationDate="2023-04-20T11:36:30.417" Score="4" Body="&lt;p&gt;The graph in question is this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/6Bt81.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6Bt81.jpg&quot; alt=&quot;Fig 10 in https://doi.org/10.1016/j.cpc.2016.09.022&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The article describes the importance of correctly simulating the self-consistent solution for temperature gradients (not bias).&lt;/p&gt;&#xA;&lt;p&gt;Generally, NEGF software have used the same temperature in both electrodes. But the NEGF scheme does not prohibit one from doing NEGF calculations with different temperatures + different bias.&lt;br /&gt;&#xA;This is the take-home message from this plot.&lt;/p&gt;&#xA;&lt;p&gt;So what is show:&lt;/p&gt;&#xA;&lt;h3&gt;Red [square] line&lt;/h3&gt;&#xA;&lt;p&gt;This is the result of a self-consistent calculation of the electronic structure and transmission values at the shown bias points with an electronic temperature in both electrodes at &lt;span class=&quot;math-container&quot;&gt;$3000 K$&lt;/span&gt;.&lt;br /&gt;&#xA;Subsequently, the IV curve is calculated from the transmission values but changing the electrodes temperatures to &lt;span class=&quot;math-container&quot;&gt;$T_L = 3000K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_R=300K$&lt;/span&gt; (i.e. non-self-consistent temperature gradient).&lt;/p&gt;&#xA;&lt;h3&gt;Blue [triangle] line&lt;/h3&gt;&#xA;&lt;p&gt;This is the result of a self-consistent calculation of the electronic structure and transmission values at the shown bias points with an electronic temperature in both electrodes at &lt;span class=&quot;math-container&quot;&gt;$300 K$&lt;/span&gt;.&lt;br /&gt;&#xA;Subsequently, the IV curve is calculated from the transmission values but changing the electrodes temperatures to &lt;span class=&quot;math-container&quot;&gt;$T_L = 3000K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_R=300K$&lt;/span&gt; (i.e. non-self-consistent temperature gradient).&lt;/p&gt;&#xA;&lt;h3&gt;Black [circle] line&lt;/h3&gt;&#xA;&lt;p&gt;This is the result of a &lt;em&gt;correct&lt;/em&gt; self-consistent calculation at the shown bias points with electronic temperatures in the electrodes as &lt;span class=&quot;math-container&quot;&gt;$T_L=3000K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$T_R=300K$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Conclusion&lt;/h3&gt;&#xA;&lt;p&gt;The point is that there is a large difference between the 3 curves, and that one cannot simply interpolate between the curves.&lt;/p&gt;&#xA;&lt;p&gt;The fact that there is a temperature difference between the electrodes means that a current will flow, even at 0 V.&lt;/p&gt;&#xA;&lt;p&gt;Of course there may be many effects which will try and equilibrate such things, and phonons are not taking into account by this method. But it shows the importance of understanding the temperature effects.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-04-20T12:16:43.547" LastActivityDate="2023-04-20T12:16:43.547" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10756" PostTypeId="1" CreationDate="2023-04-20T14:17:08.823" Score="4" ViewCount="134" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2323999/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Discrete restraint-based protein modeling and the Cα-trace problem&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;We present a novel de novo method to generate protein models from sparse, discretized &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt; on the conformation of the main chain and side chain atoms. We focus on Cα-trace generation, the problem of constructing an accurate and complete model from approximate knowledge of the positions of the Cα atoms and, in some cases, the side chain centroids. Spatial &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt; on the Cα atoms and side chain centroids are supplemented by constraints on main chain geometry, ϕ/ξ angles, rotameric side chain conformations, and inter-atomic separations derived from analyses of known protein structures. A novel conformational search algorithm, combining features of tree-search and genetic algorithms, generates models consistent with these &lt;em&gt;&lt;strong&gt;restraint&lt;/strong&gt;&lt;/em&gt;s by propensity-weighted dihedral angle sampling. Models with ideal geometry, good ϕ/ξ angles, and no inter-atomic overlaps are produced with 0.8 Å main chain and, with side chain centroid &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt;, 1.0 Å all-atom root-mean-square deviation (RMSD) from the crystal structure over a diverse set of target proteins. The mean model derived from 50 independently generated models is closer to the crystal structure than any individual model, with 0.5 Å main chain RMSD under only Cα &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt; and 0.7 Å all-atom RMSD under both Cα and centroid &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt;. The method is insensitive to randomly distributed errors of up to 4 Å in the Cα &lt;em&gt;&lt;strong&gt;restraints&lt;/strong&gt;&lt;/em&gt;. The conformational search algorithm is efficient, with the computational costs increase linearly with protein size. Issues relating to decoy set generation, experimental structure determination, the efficiency of conformational sampling, and homology modeling are discussed.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; The emphases are mine.&lt;/p&gt;&#xA;&lt;p&gt;Can you tell me what they meant by &amp;quot;restraint&amp;quot; and &amp;quot;spatial restraint&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;Please give me an intuitive example so that I can understand it clearly.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-04-20T16:12:23.097" Title="What does it mean by a &quot;restraint&quot; in the case of a protein chain?" Tags="|molecular-modeling|proteins|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10757" PostTypeId="2" ParentId="10756" CreationDate="2023-04-20T14:55:11.033" Score="6" Body="&lt;p&gt;They go on to describe exactly what they mean by a &amp;quot;restraint&amp;quot; later in the paper in the section &amp;quot;Materials and Methods::Cα and side chain centroid restraints&amp;quot;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A Cα atom at position p satisfies a spherical restraint centered at O with radius r when &lt;span class=&quot;math-container&quot;&gt;$$\Vert p-O\Vert &amp;lt; r$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;All this formula says is that they are restricting the position &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; (which is initially unknown) of some atom to be no further than &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; distance away from some point &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; that they choose. They do this for all or most of the atoms in the hopes that the combination of restraints (e.g. carbon1 is no more than 2 angstrom away from point O1, atom2 is no more than 2.5 angstrom away from O2, ...) will be enough information to construct a reasonable 3D structure.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Similar to Cα restraints, side chain centroid restraints are enforced by spherical restraints on the mean position of the side chain atoms (here we take the set of side chain atoms to be all atoms outwards from Cβ, excluding the Cα as seen in other work). A centroid restraint of radius r at position O is satisfied when &lt;span class=&quot;math-container&quot;&gt;$$\Bigg\Vert\frac{\sum_{i\in\text{side chains}}p_i}{\Vert\text{side chains}\Vert}-O\Bigg\Vert&amp;lt;r$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The notation is a bit sloppy for the side chain restraint (not clear what the norm of &amp;quot;side chains&amp;quot; is), but the meaning is the same as for the atom restraints: &lt;strong&gt;they determine the positions of these points (side chain centroids) by establishing a set of bounds (restraints) that each position has to fit into.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;They mention in the paper that how to go from a set of restraints to a 3D geometry is a challenging problem and there isn't a general algorithm that can reliably/efficiently do this. In this context they make a distinction between a &amp;quot;restraint&amp;quot; which is a bound or inequality on some value, vs a &amp;quot;constraint&amp;quot;, which explicitly enforces some particular value.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="3990" LastEditDate="2023-04-20T16:12:23.097" LastActivityDate="2023-04-20T16:12:23.097" CommentCount="4" CommunityOwnedDate="2023-04-20T14:55:11.033" ContentLicense="CC BY-SA 4.0" />
  <row Id="10759" PostTypeId="1" CreationDate="2023-04-21T06:05:07.697" Score="2" ViewCount="35" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Electron_energy_loss_spectroscopy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electron Energy Loss Spectroscopy&lt;/a&gt; (EELS) comes from the imaginary part of the inverse dielectric function &lt;span class=&quot;math-container&quot;&gt;$-\text{Im}[\varepsilon^{-1}(q, \omega)]$&lt;/span&gt;. If the dielectric function is actually a tensor and there is anisotropy, which component of the tensor is used to generate EELS in calculations or, alternatively, what appears in EELS experimentally?&lt;/p&gt;&#xA;" OwnerUserId="6120" LastEditorUserId="7" LastEditDate="2023-05-09T17:54:49.590" LastActivityDate="2023-05-09T17:54:49.590" Title="Which component of the dielectric tensor is used in generating EELS in TDDFT?" Tags="|density-functional-theory|spectroscopy|td-dft|optical-properties|" AnswerCount="0" CommentCount="2" ClosedDate="2023-11-08T00:23:55.917" ContentLicense="CC BY-SA 4.0" />
  <row Id="10760" PostTypeId="1" AcceptedAnswerId="10771" CreationDate="2023-04-21T10:03:37.290" Score="10" ViewCount="451" Body="&lt;h2&gt;Background&lt;/h2&gt;&#xA;&lt;p&gt;I am a chemistry undergrad that wants to learn Machine Learning (ML) for application in my field(Chemistry). However, I have never studied programming or anything related to code in my life. For this reason, I am building a study plan for this goal.&lt;/p&gt;&#xA;&lt;p&gt;Can you give me any advice on this endeavor? I would appreciate any suggestions to know if I am on the correct path. Below is the study plan I made. My timeframe for completing this study plan is 1-1.5 years.&lt;/p&gt;&#xA;&lt;h2&gt;Study Plan&lt;/h2&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 1: Learning the basic concepts of Programming&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLQKlKz1J9WWTUUMnfa2PWaPU3qPND7GJN&quot; rel=&quot;nofollow noreferrer&quot;&gt;Algorithm and Programming Logic with Python&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.kaggle.com/learn&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kaggle&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 2: Learning how to Program in Python&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLyqOvdQmGdTSEPnO0DKgHlkXb8x3cyglD&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python Course for Beginners&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.kaggle.com/learn&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kaggle&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://codingbat.com/python&quot; rel=&quot;nofollow noreferrer&quot;&gt;CodingBat&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://projecteuler.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Project Euler&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 3: Learning how to use Python for Data Analysis and learning Statistics&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLyqOvdQmGdTR46HUxDA6Ymv4DGsIjvTQ-&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python Course for Machine Learning and Data Analysis&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://pt.khanacademy.org/math/em-mat-estatistica&quot; rel=&quot;nofollow noreferrer&quot;&gt;Khan Academy&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pandas&lt;/a&gt;, &lt;a href=&quot;https://www.youtube.com/playlist?list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_&quot; rel=&quot;nofollow noreferrer&quot;&gt;Matplotlib&lt;/a&gt; and &lt;a href=&quot;https://www.youtube.com/playlist?list=PLzgPDYo_3xukqLLjNeuCxj4CwvkJin03Z&quot; rel=&quot;nofollow noreferrer&quot;&gt;NumPy&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/watch?v=WJE4spsP-Xk&quot; rel=&quot;nofollow noreferrer&quot;&gt;How to go from ZERO to Data Science in Just One Lesson&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 4: Learning basic concepts about Machine Learning and Probability&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• Course : &lt;a href=&quot;https://www.youtube.com/playlist?list=PLyqOvdQmGdTSqkutrKDaVJlEv-ui1MyK4&quot; rel=&quot;nofollow noreferrer&quot;&gt;Introduction to Machine Learning and Machine Learning Algorithms&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLyqOvdQmGdTS4PcZsAKhXgkdUyLjXnptS&quot; rel=&quot;nofollow noreferrer&quot;&gt;Machine Learning Algorithms&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLeFetwYAi-F9Z0N3ZSjPL2i24PO5iiXaY&quot; rel=&quot;nofollow noreferrer&quot;&gt;Machine Learning with Python and Scikit-learn&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.kaggle.com/learn&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kaggle&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://pt.khanacademy.org/math/em-mat-probabilidade&quot; rel=&quot;nofollow noreferrer&quot;&gt;Probabilities&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://developers.google.com/machine-learning/crash-course&quot; rel=&quot;nofollow noreferrer&quot;&gt;Google Machine Learning Crash Course&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 5: Learning Applications of Machine Learning in Chemistry&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLIJhet1J-_l82wpFzn2ZOyCIKy-FotuND&quot; rel=&quot;nofollow noreferrer&quot;&gt;EMMSB LNCC&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.youtube.com/playlist?list=PLgCwaJhZsSlMQky78U5JLyMOgO16o6ubE&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Computational Toolkit&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• Learn how to use RDKit or DeepChem, a collection of cheminformatics and machine learning tools for Python&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Cycle 6: Learning Deep Learning Fundamentals&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.coursera.org/specializations/deep-learning&quot; rel=&quot;nofollow noreferrer&quot;&gt;Deep Learning by Andrew Ng on Coursera&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;• &lt;a href=&quot;https://www.kaggle.com/learn&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kaggle&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="6687" LastEditDate="2023-04-23T10:35:28.750" LastActivityDate="2023-09-12T12:36:37.023" Title="How a beginner should start his studies in ML for chemistry application?" Tags="|computational-chemistry|python|machine-learning|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10761" PostTypeId="2" ParentId="10752" CreationDate="2023-04-21T11:18:32.090" Score="2" Body="&lt;pre&gt;&lt;code&gt;set traj   name of trajectory file&#xA;set gro    name of corresponding gro file&#xA;set output [open filename.dat w]&#xA;&#xA;mol load type trj &lt;span class=&quot;math-container&quot;&gt;$traj waitfor all &#xA;mol addfile gro $&lt;/span&gt;gro&#xA;&#xA;set numframes [molinfo top get numframes]&#xA;for {set frameC 0} {&lt;span class=&quot;math-container&quot;&gt;$frameC &amp;lt; $&lt;/span&gt;numframes} {incr frameC} {&#xA;    molinfo top set frame &lt;span class=&quot;math-container&quot;&gt;$frameC&#xA;set sel1 [selection string for helix first atom]&#xA;set sel2 [selection string for helix second atom]&#xA;set vec [vecsub [$&lt;/span&gt;sel1 get pos] [&lt;span class=&quot;math-container&quot;&gt;$sel2 get pos]]&#xA;set nvec [vecnorm $&lt;/span&gt;vec]&#xA;        set theta [lindex &lt;span class=&quot;math-container&quot;&gt;$nvec 2]&#xA;puts $&lt;/span&gt;output &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$frameC $&lt;/span&gt;theta&amp;quot; &#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I wrote this script for analyzing a NAMD DCD file and have not tested this for a gromacs trajectory. However, this should give you something to start with.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-04-21T11:18:32.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10762" PostTypeId="1" AcceptedAnswerId="11005" CreationDate="2023-04-21T12:19:38.487" Score="5" ViewCount="76" Body="&lt;p&gt;I would like to write a simple code calculating Conductance and Seebeck coefficients in function of the chemical potential. To do this, I would like to use the equation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$L_n(\mu, T)=\frac{2}{h}\int T_e(E)(E-\mu)^n\frac{\partial f(E,\mu,T)}{\partial E}dE$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;reported in &lt;a href=&quot;https://link.springer.com/article/10.1007/s10825-012-0392-0&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper.&lt;/p&gt;&#xA;&lt;p&gt;I plan to use the Transmission function calculated with TBTrans. However, I was wondering about the Temperature. I know that by default Transiesta uses 300K as electronic temperature. Is it right to assume 300K as T in this formula?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-04-23T20:19:09.160" LastActivityDate="2023-05-31T10:48:37.587" Title="Post-processing in TBTrans" Tags="|siesta|electronic-transport|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10763" PostTypeId="1" CreationDate="2023-04-22T21:29:09.627" Score="3" ViewCount="219" Body="&lt;p&gt;I am trying to compute the bond angles of all the pairs of bond in a set of molecule from Colontrix dataset. Some of the molecules are showing up error when I am implementing the following.The error says:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Example:&lt;/strong&gt; &lt;code&gt;Isosorbide 5-nitrate [C1[C@@H]([C@@H]2[C@H](O1)[C@@H](CO2)O[N+](=O)[O-])O]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Error:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Value Error: Bad Conformer id.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Code:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem import AllChem as Chem&#xA;&#xA;mol_obj = Chem.MolFromSmiles(mol[&amp;quot;smiles&amp;quot;])&#xA;Chem.EmbedMolecule(mol_obj, randomSeed=42)&#xA;conf = mol3d.GetConformer()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6643" LastActivityDate="2023-09-20T11:01:30.173" Title="SMILES structure of molecule giving error while converting into embedded representation or conformations" Tags="|computational-chemistry|rdkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10764" PostTypeId="1" CreationDate="2023-04-23T09:22:22.427" Score="1" ViewCount="33" Body="&lt;p&gt;I have a surface plot for which I would like to find the E (Electric field intensity) at a far field point marked in red on the plot.&lt;/p&gt;&#xA;&lt;p&gt;Therefore I would like to calculate Ex and Ey, so that I can calculate the norm to get the E.&lt;/p&gt;&#xA;&lt;p&gt;How can I do that using COMSOL ?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lSM3x.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lSM3x.png&quot; alt=&quot;surface_plot&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6976" LastEditorUserId="6687" LastEditDate="2023-04-23T09:45:43.210" LastActivityDate="2023-04-23T09:45:43.210" Title="How to find out electric field Intensity for a far distant point in COMSOL multi Physics" Tags="|atomic-physics|" AnswerCount="0" CommentCount="2" ClosedDate="2023-11-08T00:18:39.813" ContentLicense="CC BY-SA 4.0" />
  <row Id="10765" PostTypeId="2" ParentId="10763" CreationDate="2023-04-23T09:36:14.847" Score="1" Body="&lt;p&gt;Please avoid renaming modules with existing module names.&lt;/p&gt;&#xA;&lt;p&gt;For example, in your imports you have renamed &lt;code&gt;AllChem&lt;/code&gt; as &lt;code&gt;Chem&lt;/code&gt;. However there is already an existing library called &lt;code&gt;Chem&lt;/code&gt; in &lt;code&gt;rdkit&lt;/code&gt;. There is a high chance that this will cause problems for you if you need to use something from the actual &amp;quot;&lt;code&gt;Chem&lt;/code&gt;&amp;quot; module.&lt;/p&gt;&#xA;&lt;p&gt;Also it looks like you perhaps have the wrong SMILES for &lt;code&gt;isosorbide-5-mononitrate&lt;/code&gt;. I got the SMILES from this &lt;a href=&quot;https://www.medchemexpress.com/Isosorbide-mononitrate.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Here is a working code that will resolve your conformer id error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import AllChem&#xA;&#xA;isosorbide_5_mononitrate_smiles = 'O=[N+]([O-])O[C@H]1[C@](OC[C@@H]2O)([H])[C@]2([H])OC1'&#xA;mol = Chem.MolFromSmiles(isosorbide_5_mononitrate_smiles)&#xA;mol = Chem.AddHs(mol)&#xA;AllChem.EmbedMolecule(mol, randomSeed=42)&#xA;conf = mol.GetConformer()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-04-23T09:59:24.480" LastActivityDate="2023-04-23T09:59:24.480" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10766" PostTypeId="1" CreationDate="2023-04-23T14:03:54.630" Score="3" ViewCount="101" Body="&lt;p&gt;I was using psi4 to run vibrational frequency analysis with small molecules (in a jupyter notebook) and it works just fine with molecules like methanol and water but once I move up to ethanol or acetone, I can see the prompt can do the computations just fine but it gets stuck on saving the results file to my notebook (the prompt just says 'Saving file at x.ipynb'). Has anyone run into this error before? If so, how did you fix it?&lt;/p&gt;&#xA;&lt;p&gt;code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#import psi4 and set memory&#xA;&#xA;import psi4&#xA;&#xA;psi4.set_memory('10 GB')&#xA;&#xA;from rdkit import Chem # main tools&#xA;from rdkit.Chem import AllChem # additional tools, including 3D&#xA;&#xA;smiles = 'CCO' # smiles string input&#xA;mol = Chem.MolFromSmiles(smiles) # initialize molecule&#xA;&#xA;mol_h = Chem.AddHs(mol) # adding explicit Hs for 3D generation&#xA;cid = AllChem.EmbedMolecule(mol_h) # returns the id of the generated conformer,&#xA;                                 # and -1 if no conformers were generated&#xA;&#xA;AllChem.MMFFOptimizeMolecule(mol_h) # optimize molecule with MMFF94 forcefield&#xA;mol_xyz=Chem.rdmolfiles.MolToXYZBlock(mol_h) # save to xyz string&#xA;&#xA;print(mol_xyz)&#xA;&#xA;#check structure of molecule&#xA;mol&#xA;&#xA;#convert xyz file to psi4 geometry file&#xA;qmol = psi4.driver.qcdb.Molecule.from_string(mol_xyz, dtype='xyz+')&#xA;mol_psi4 = psi4.geometry(qmol.create_psi4_string_from_molecule())&#xA;&#xA;#initialize molecule &#xA;mol_psi4.update_geometry()&#xA;&#xA;#optimize geometry before calculating frequencies&#xA;psi4.set_options({'reference': 'rhf'})&#xA;psi4.optimize('scf/cc-pvdz', dft_functional = 'b3lyp', molecule=mol_psi4)&#xA;&#xA;#calculate vibrational frequencies&#xA;scf_e, scf_wfn = psi4.frequency('scf/cc-pvdz', molecule=mol_psi4, return_wfn=True)&#xA;print('done')&#xA;&#xA;#save and print frequencies + intesity&#xA;freq=scf_wfn.frequency_analysis['omega'][2]&#xA;for i in freq:&#xA;    print(i)&#xA;&#xA;print('')&#xA;print('Done!!!')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6901" LastEditorUserId="5" LastEditDate="2023-04-23T15:47:44.163" LastActivityDate="2023-04-25T13:00:17.700" Title="Psi4 Takes too Long to Save Computation Results to Python Notebook" Tags="|python|psi4|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10767" PostTypeId="1" AcceptedAnswerId="10778" CreationDate="2023-04-23T15:42:38.593" Score="6" ViewCount="376" Body="&lt;p&gt;I am looking for a physics based proof for how one applies forces to each of the three atoms in a bond angle potential. I know the general principle that &lt;span class=&quot;math-container&quot;&gt;$F = -\nabla \Phi$&lt;/span&gt; if &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt; is your potential energy function. I am wondering how one goes from such a definition to the force on each atom and how to prove that those forces satisfy conservation of energy and momentum (or any other relevant physical laws).&lt;/p&gt;&#xA;&lt;p&gt;For some more details, here is how LAMMPs applies forces on atoms from a simple harmonic bond angle potential:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi(\theta) = k(\theta - \theta_{0})^{2}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Consider this image:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/V2MD7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/V2MD7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then &lt;span class=&quot;math-container&quot;&gt;$\Phi = k(\arccos(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})- \theta_{0})^{2}$&lt;/span&gt;&#xA;This leaves us with&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial \Phi}{\partial r_{1}} = 2k(\arccos(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})- \theta_{0})(-\frac{1}{\sqrt{1-(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})^{2}}})(-\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}^{2}r_{2}})$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial \Phi}{\partial r_{2}} = 2k(\arccos(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})- \theta_{0})(-\frac{1}{\sqrt{1-(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})^{2}}})(-\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}^{2}})$$&lt;/span&gt;&#xA;The forces that LAMMPs assigns to each atom are then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\textbf{F}_{1} = (-\frac{\partial \Phi}{\partial r_{1}})(\frac{delx_{1}\hat{x}+dely_{1}\hat{y}+delz_{1}\hat{z}}{r_{1}}) + (-\frac{\partial \Phi}{\partial r_{2}})(\frac{delx_{2}\hat{x}+dely_{2}\hat{y}+delz_{2}\hat{z}}{\frac{\textbf{r}_{1}\cdot\textbf{r}_{2}}{r_{2}}})$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\textbf{F}_{3} = (-\frac{\partial \Phi}{\partial r_{1}})(\frac{delx_{1}\hat{x}+dely_{1}\hat{y}+delz_{1}\hat{z}}{\frac{\textbf{r}_{1}\cdot\textbf{r}_{2}}{r_{1}}}) + (-\frac{\partial \Phi}{\partial r_{2}})(\frac{delx_{2}\hat{x}+dely_{2}\hat{y}+delz_{2}\hat{z}}{r_{2}})$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\textbf{F}_{2} = -\textbf{F}_{1} - \textbf{F}_{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any resources, proofs, suggestions on chapters from a textbook, etc. that would help to provide intuition on this problem would be very much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;EDIT:&lt;/p&gt;&#xA;&lt;p&gt;I am going to post the derivation of the forces from this bond angle potential as presented by Swope and Ferguson 'Alternative Expressions for Energies and Forces Due to Angle Bending and Torsional Energy' 1992. Hopefully with this information plus the answer provided below by Shern Ren Tee, others will be able to use this post as a starting point for their own calculations.&lt;/p&gt;&#xA;&lt;p&gt;Consider the following diagram as presented above.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Phi(\theta) = k(\theta - \theta_{0})^{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;We seek the following quantity to derive the forces on atom 1:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$-\nabla_{1} \Phi(\theta)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\nabla_{1}$&lt;/span&gt; is the derivative of the &lt;span class=&quot;math-container&quot;&gt;$\Phi$&lt;/span&gt; potential holding the position of each other atom (atoms 2 and 3) constant. From here, we use a clever formulation of the chain rule to simplify much of the math for us:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$-\nabla_{1} \Phi(\theta) = (-\frac{d\Phi}{d\theta})(\frac{d\theta}{d\cos(\theta)})(\nabla_{1}\cos(\theta))$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first two terms in this expression are trivial.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(-\frac{d\Phi}{d\theta}) = 2k(\theta-\theta_{0}) = 2k(\arccos(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})- \theta_{0})$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(\frac{d\theta}{d\cos(\theta)}) = \frac{1}{\frac{\cos(\theta)}{d\theta}} = -\frac{1}{\sin(\theta)} = -\frac{1}{\sqrt{1-\cos^{2}(\theta)}} = (-\frac{1}{\sqrt{1-(\frac{\mathbf{r_{1}\cdot r_{2}}}{r_{1}r_{2}})^{2}}})$$&lt;/span&gt;&#xA;The last term is slightly trickier. First we must realize the following:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\nabla_{1} = \hat{x} \frac{\partial}{\partial x_{1}} + \hat{y} \frac{\partial}{\partial y_{1}} + \hat{z} \frac{\partial}{\partial z)}$$&lt;/span&gt;&#xA;Let us only consider the x component here for the following derivation. We can demonstrate that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\hat{x}\nabla_{1}\cos(\theta) = \frac{\partial\cos(\theta)}{\partial x_{1}} = \frac{\partial\cos(\theta)}{\partial delx_{1}}\frac{\partial delx_{1}}{\partial x_{1}} + \frac{\partial\cos(\theta)}{\partial dely_{1}}\frac{\partial dely_{1}}{\partial x_{1}} + \frac{\partial\cos(\theta)}{\partial delz_{1}}\frac{\partial delz_{1}}{\partial x_{1}} + \frac{\partial\cos(\theta)}{\partial delx_{2}}\frac{\partial delx_{2}}{\partial x_{1}} + \frac{\partial\cos(\theta)}{\partial dely_{2}}\frac{\partial dely_{2}}{\partial x_{1}} + \frac{\partial\cos(\theta)}{\partial delz_{2}}\frac{\partial delz_{2}}{\partial x_{1}} = \frac{\cos(\theta)}{\partial delx_{1}}\hat{x}$$&lt;/span&gt;&#xA;Finally, we take that derivative to get the portion of the force in the x direction on atom 1 to see:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{\partial\cos(\theta)}{\partial x_{1}} = \frac{\partial}{\partial delx_{1}}(\frac{\mathbf{r}_{1}\cdot\mathbf{r}_{2}}{r_{1}r_{2}}) = -\frac{1}{r_{1}r_{2}}(\frac{\mathbf{r}_{1}\cdot\mathbf{r}_{2}}{r_{1}^{2}}delx_{1}\hat{x} - delx_{2}\hat{x})$$&lt;/span&gt;&#xA;Or overall we get that the entire &lt;span class=&quot;math-container&quot;&gt;$\nabla_{1} \cos(\theta)$&lt;/span&gt; term reduces to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$-\frac{1}{r_{1}r_{2}}(\frac{\mathbf{r}_{1}\cdot\mathbf{r}_{2}}{r_{1}^{2}}\mathbf{r}_{1} - \mathbf{r}_{2})$$&lt;/span&gt;&#xA;Which is identical to the result obtained from LAMMPs. I skipped over some of the more tedious steps, but I hope that this derivation may help others as a starting point.&lt;/p&gt;&#xA;" OwnerUserId="7055" LastEditorUserId="7055" LastEditDate="2023-04-25T15:05:07.003" LastActivityDate="2023-04-25T15:05:07.003" Title="Determine Forces from a Bond Angle Potential" Tags="|molecular-dynamics|lammps|interatomic-potentials|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10768" PostTypeId="1" AcceptedAnswerId="10772" CreationDate="2023-04-24T02:55:40.380" Score="4" ViewCount="187" Body="&lt;p&gt;I would like to use the materials project API to search materials with some properties but to restrict my search only to two-dimensional materials.&lt;/p&gt;&#xA;&lt;p&gt;How to do it?&lt;/p&gt;&#xA;&lt;p&gt;Web-pages for materials contain the 'Dimensionality' field in the 'Crystal Structure' section&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wE9O6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wE9O6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the &lt;a href=&quot;https://next-gen.materialsproject.org/api&quot; rel=&quot;nofollow noreferrer&quot;&gt;API page&lt;/a&gt;, I found that the dimensionality can be obtained from RobocrystallogapherDoc that is accessed with the &lt;code&gt;robocrys&lt;/code&gt; object but whatever I tried to do with &lt;code&gt;MPRester.robocrys.search&lt;/code&gt;, I got errors.&lt;/p&gt;&#xA;&lt;p&gt;How to use it? Where to get information? I searched on the &lt;a href=&quot;https://next-gen.materialsproject.org/api&quot; rel=&quot;nofollow noreferrer&quot;&gt;API page&lt;/a&gt;, the &lt;a href=&quot;https://docs.materialsproject.org/downloading-data/using-the-api&quot; rel=&quot;nofollow noreferrer&quot;&gt;MP docs page&lt;/a&gt;, &lt;a href=&quot;https://workshop.materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MP Workshop&lt;/a&gt;, another &lt;a href=&quot;https://api.materialsproject.org/docs&quot; rel=&quot;nofollow noreferrer&quot;&gt;MP docs&lt;/a&gt;, &lt;a href=&quot;https://github.com/hackingmaterials/robocrystallographer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Robocrystallographer github&lt;/a&gt;, &lt;a href=&quot;https://link.springer.com/article/10.1557/mrc.2019.94&quot; rel=&quot;nofollow noreferrer&quot;&gt;Robocrystallographer paper&lt;/a&gt; - they all contain very little info on how to use the materials project API, and especially Robocrystallographer.&lt;/p&gt;&#xA;&lt;p&gt;The only thing I got working for Robocrystallographer is querying a material given its materials project ID: &lt;code&gt;robocrys.get_data_by_id&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, I first downloaded IDs for all materials into a text file (154718 materials on 23 April, 2023):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mp_api.client import MPRester&#xA;&#xA;with MPRester(api_key=api_key) as mpr:&#xA;    ids = mpr.summary.search(fields=[&amp;quot;material_id&amp;quot;])&#xA;&#xA;with open('mp_ids.txt', 'w') as f:&#xA;    for line in ids:&#xA;        f.write(f&amp;quot;{line.material_id}\n&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This took a few seconds on GPU.&lt;/p&gt;&#xA;&lt;p&gt;Then, I looped through this text file, used &lt;code&gt;robocrys.get_data_by_id&lt;/code&gt; to get only those IDs that Robocrystallographer identifies as 2D materials, and saved them in another text file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mp_api.client import MPRester&#xA;&#xA;with open('mp_ids.txt', 'r') as f:&#xA;    mpids = [line.rstrip('\n') for line in f.readlines()]&#xA;&#xA;with open('mp_2dids.txt', 'w') as f:&#xA;    with MPRester(api_key=api_key) as mpr:&#xA;        for mpid in mpids:&#xA;            mpd = mpr.robocrys.get_data_by_id(mpid)&#xA;            try:&#xA;                dim = mpd.condensed_structure.dimensionality&#xA;            except:    &#xA;                continue&#xA;&#xA;            if dim != None and dim == 2:&#xA;                f.write(f&amp;quot;{mpid}\n&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This took 14 hours on GPU (8967 2D materials on 23 April, 2023).&lt;/p&gt;&#xA;&lt;p&gt;Is there a 'more civilized' way to do it, without downloading all IDs to text files, and redoing this every time they add new materials to the materials project database?&lt;/p&gt;&#xA;" OwnerUserId="81" LastEditorUserId="81" LastEditDate="2023-04-24T03:00:50.323" LastActivityDate="2023-04-24T14:55:05.390" Title="How to query 2D materials on materials project?" Tags="|python|databases|2d-lattice|materials-informatics|materials-project|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10769" PostTypeId="2" ParentId="10766" CreationDate="2023-04-24T11:15:33.523" Score="3" Body="&lt;p&gt;I ran the calculation for ethanol and it took me 0.78 mins.&lt;/p&gt;&#xA;&lt;h3&gt;System Specs:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;OS: MacOS Monterey 12.5.1&#xA;2,6 GHz 6-Core Intel Core i7&#xA;32 GB 2667 MHz DDR4&#xA;IDE: PyCharm 2022.3.2 (Community Edition)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Software Specs:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;Virtual Env: Conda env &#xA;Conda version: 23.1.0&#xA;Python version: 3.10.10&#xA;PSI4 version:  1.6.1+5b9f6e3   &#xA;PSI4 build : py310h581b2b9_0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the following code I am directly using the xyz string obtained from rdkit. (The reason is that it is a hassle to install both rdkit and psi4 on the same conda env on OSX. rdkit needs python version &amp;lt;=3.7 and psi4 seems to work well only on 3.10 onwards)&lt;/p&gt;&#xA;&lt;h3&gt;Code:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;import time&#xA;s = time.time()&#xA;mol_psi4 = psi4.geometry('''9&#xA;&#xA;C     -0.887089    0.175064   -0.012535&#xA;C      0.460489   -0.515516   -0.046535&#xA;O      1.442965    0.307267    0.565572&#xA;H     -0.847478    1.127768   -0.550817&#xA;H     -1.658782   -0.453327   -0.465842&#xA;H     -1.176944    0.403676    1.018306&#xA;H      0.768712   -0.724328   -1.075460&#xA;H      0.419486   -1.462073    0.500177&#xA;H      1.478640    1.141468    0.067135&#xA;''')&#xA;&#xA;#optimize geometry before calculating frequencies&#xA;psi4.set_options({'reference': 'rhf'})&#xA;psi4.optimize('scf/cc-pvdz', dft_functional = 'b3lyp', molecule=mol_psi4)&#xA;&#xA;#calculate vibrational frequencies&#xA;scf_e, scf_wfn = psi4.frequency('scf/cc-pvdz', molecule=mol_psi4, return_wfn=True)&#xA;print('done')&#xA;&#xA;#save and print frequencies + intesity&#xA;freq=(scf_wfn.frequency_analysis['omega'].data)&#xA;for i in freq:&#xA;    print(i)&#xA;e = time.time()&#xA;&#xA;print(f'time taken mins: {(e-s)/60}')&#xA;print('')&#xA;print('Done!!!')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also here are the output frequencies:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;7.507156968262905e-06j&#xA;(4.908897302913366e-06+0j)&#xA;(1.5197889898678715e-05+0j)&#xA;(2.9472406989666606e-05+0j)&#xA;(3.222627049809006e-05+0j)&#xA;(4.2094538779691455e-05+0j)&#xA;(401.17046333897605+0j)&#xA;(462.0977321879201+0j)&#xA;(688.388935344985+0j)&#xA;(908.0756382425054+0j)&#xA;(951.6293253661514+0j)&#xA;(1133.4970378368564+0j)&#xA;(1195.0895426135098+0j)&#xA;(1238.377261101374+0j)&#xA;(1403.076854517634+0j)&#xA;(1506.414762164892+0j)&#xA;(1537.260320704411+0j)&#xA;(1574.0259056577736+0j)&#xA;(1596.5805492658997+0j)&#xA;(1604.014633238946+0j)&#xA;(1637.0354072816572+0j)&#xA;(3036.6416405029995+0j)&#xA;(3081.9122987732476+0j)&#xA;(3124.28961913401+0j)&#xA;(3149.4983929335085+0j)&#xA;(3168.1054762068184+0j)&#xA;(3824.5089839751754+0j)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-04-25T13:00:17.700" LastActivityDate="2023-04-25T13:00:17.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10770" PostTypeId="1" CreationDate="2023-04-24T11:58:35.100" Score="4" ViewCount="121" Body="&lt;h1&gt;Classical binary computer&lt;/h1&gt;&#xA;&lt;p&gt;The classical binary computers, on which a Hartree-Fock (or density functional theory) calculation can be executed, already allows seeing a limit in their progress, mainly in an “intensive character” of their progress that’s the size of semiconductor device, which cannot be less than the size of one atom of silicon — according to the logic of things. The processor architecture optimization for special mathematical operations and program code optimization to increase the speed of calculation can be included into the latter as well. Contrary the latter, there is an “extensive character” of progress of the classical binary computers that’s increasing the number of processors to parallelize a calculation as much as possible to get a calculation speed acceleration. I guess it obvious that the “extensive character” will have remained even since the “intensive one” will be over.&lt;/p&gt;&#xA;&lt;h1&gt;Quantum computer&lt;/h1&gt;&#xA;&lt;p&gt;There is a new (old) hope of the quantum computer development. But as far as I understand that the problem is to make it in materials such a way that to have possible to operate with a sufficient number of qubits (electrons or photons or other quantum particles) as well as a problem to get a sufficient number of entangled particles (qubits). I guess what sizes of quantum gates are important as well because a sufficient number of them allows to make a quantum circuit more functional. Besides that, at running a quantum computer for some calculation inevitably some deviations from a true result can be obtained that can be related to a quality of materials of which a quantum computer is made (correct my assertions if they are wrong). It’s probably all of these while causes difficulties to implement a quantum circuit for solving the Schrödinger, Hartree-Fock, or Kohn-Sham equation on a real quantum computer made of materials. Although there are tries for moving forward, for instance in &lt;a href=&quot;https://fount.aucegypt.edu/cgi/viewcontent.cgi?article=1020&amp;amp;context=capstone&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acscentsci.8b00788&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;. (It's interesting is there in the internet any databases or handbooks or encyclopedias with free quantum algorithms for finding eigenvalues and eigenvectors for the simple molecules &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{N2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{NH3}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CH4}$&lt;/span&gt;, and so on?). So it’s okay, the quantum computers are a matter of efforts and a time.&lt;/p&gt;&#xA;&lt;h1&gt;Classical ternary computer&lt;/h1&gt;&#xA;&lt;p&gt;The Hartree-Fock (DFT) algorithm, as many other algorithms, supposes in itself a lot of making summing (for instance at computing integrals) that must be executed in 1.58 (that’s taken from &lt;span class=&quot;math-container&quot;&gt;$\log_{2}3$&lt;/span&gt;) times faster with using ternary computers than if it would be done by binary ones. I suppose that binary computers get more spreading due to their high noise immunity in that “old” time. It’s probably modern materials of today would be able to make ternary computer with sufficient level of noise immunity. Who knows…&lt;/p&gt;&#xA;&lt;h1&gt;Classical electronic analog computer&lt;/h1&gt;&#xA;&lt;p&gt;In the XIX century there were classical analog computers to be fully mechanical and to execute highly specialized tasks. In the XX century, analog computers were transformed with the advent of electronics and became more compact and functional. So electronic analog computers appeared. In general, classical analog computer can represent arrays of integrators, differentiators, adders, comparators, splitters and other devices among which programmatically connections can be set, in order to be as universal device to solve computational tasks of different kinds. Programmatic managing can be implemented with using an old way that's the classical binary computer as variant, see schematic and rough picture below. DAC and ADC as input/output systems must be included as well. — In our time it’s possible to use a hybrid: a classical binary computer in conjunction with an analog one. Logically, a classic electronic analog computer must make calculation very fast, but also give some calculation error. Temperature, parasitic capacitance, parasitic inductance, background noise of sub-devices can affect this error. Maybe there is a way that’s able to stabilize work of the devices and due to that to minimize this error. For example, if a problem is due to warming internal devices (integrators, differentiators and so on), so knowing a dependency a current going through the ones of temperature automatically to be adjusting a needed value in correspondent with a right value. So this procedure will allow to exclude the factor decreasing calculation accuracy. (There is a &lt;a href=&quot;https://arxiv.org/pdf/1908.02020.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, to put it shortly, about one of tries of solving a Schrödinger equation to be of special kind, being not hard not quite about a matter modeling but though.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jjhWT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jjhWT.png&quot; alt=&quot;Very rough scheme of a classical analog electronic computer&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Main question&lt;/h1&gt;&#xA;&lt;p&gt;Thus, classical binary computers have a limit, quantum computers are in a stage of development, classical ternary computers are not enough spreaded. Nevertheless, despite the fact that the above things can be sufficiently developed in the future, let’s consider analog computers though. It can seem that there is no enough motivation to think about it and it’s probably really so. One thought has been finding this problem as interested, another thought dissuades from its consideration. It's curious how could a circuit of binds of analog components look like that allows solving (finding eigenvalues and eigenvectors) the Schrödinger or Hartree-Fock equation for one of the simple molecules &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{O2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{H2O}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{N2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{CH4}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\ce{NH3}$&lt;/span&gt;? What would the thing be from which you have begun? It is not understood how to represent a wave function as a signal or a composition of signals. For example, a wave function for &lt;span class=&quot;math-container&quot;&gt;$\ce{H2}$&lt;/span&gt; is a function of 4 variables: &lt;span class=&quot;math-container&quot;&gt;$\psi(\mathbf{r_1},\sigma_1,\mathbf{r_2},\sigma_2)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r_1}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r_2}$&lt;/span&gt; — the spatial variables of the first and second hydrogen atom, &lt;span class=&quot;math-container&quot;&gt;$\sigma_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma_2$&lt;/span&gt; — the spinal variables analogically. Maybe an electric signal as a basis of an analog computer in this case is not quite suitable and another basis is needed.&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2023-04-24T11:58:35.100" Title="How realistic is the use of classical analog electronic computers in solving the Schrödinger, Hartree-Fock, and Kohn-Sham equations?" Tags="|one-topic-per-answer|high-performance-computing|optimization|quantum-computing|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10771" PostTypeId="2" ParentId="10760" CreationDate="2023-04-24T13:38:57.410" Score="4" Body="&lt;p&gt;Here are my comments on each of your cycles.&lt;/p&gt;&#xA;&lt;h3&gt;Cycle 1:&lt;/h3&gt;&#xA;&lt;p&gt;The course you listed called &lt;a href=&quot;https://www.youtube.com/playlist?list=PLQKlKz1J9WWTUUMnfa2PWaPU3qPND7GJN&quot; rel=&quot;nofollow noreferrer&quot;&gt;Algorithm and Programming Logic with Python&lt;/a&gt; looks pretty basic. I would recommend doing a course from &lt;a href=&quot;https://www.coursera.org/courses?query=python&quot; rel=&quot;nofollow noreferrer&quot;&gt;Coursera&lt;/a&gt; to get the fundamentals of programming in Python.&lt;/p&gt;&#xA;&lt;h3&gt;Cycle 2:&lt;/h3&gt;&#xA;&lt;p&gt;Practice your python skills on Kaggle, CodingBat, Project Euler or any other website such as &lt;a href=&quot;https://www.hackerrank.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hackerrank&lt;/a&gt;, &lt;a href=&quot;https://www.codewars.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Codewars&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Cycle 3 and 4:&lt;/h3&gt;&#xA;&lt;p&gt;Looks Okay&lt;/p&gt;&#xA;&lt;h3&gt;Cycle 5 and Cycle 6:&lt;/h3&gt;&#xA;&lt;p&gt;At this point you would have a decent idea of basics of python, so I would suggest that you learn by working on projects rather than just watching youtube videos and tutorials.&lt;/p&gt;&#xA;&lt;p&gt;For example, GSOC (Google Summer of Code) is superb way of learning by doing. For inspiration here is &lt;a href=&quot;https://wiki.openchemistry.org/GSoC_Ideas_2023&quot; rel=&quot;nofollow noreferrer&quot;&gt;GSOC 2023 list of projects.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even if you are not able to enroll to GSOC, you can still work such projects on your own.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-24T13:38:57.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10772" PostTypeId="2" ParentId="10768" CreationDate="2023-04-24T14:55:05.390" Score="2" Body="&lt;p&gt;To avoid running through all the ids every time a new material is added you can use your text file where you have saved the ids already.&lt;/p&gt;&#xA;&lt;p&gt;I have written helper functions that you can use to achieve this.&lt;/p&gt;&#xA;&lt;h3&gt;Helper functions:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mp_api.client import MPRester&#xA;&#xA;def get_all_material_infos_from_db(mpr):&#xA;  current_material_infos = mpr.summary.search(fields=[&amp;quot;material_id&amp;quot;])&#xA;  return current_material_infos&#xA;&#xA;def write_ids_to_file(id_info_filepath, ids):&#xA;  with open(id_info_filepath, 'w') as f:&#xA;      for line in ids:&#xA;          f.write(f&amp;quot;{line.material_id}\n&amp;quot;)&#xA;&#xA;def get_locally_existing_ids(id_info_filepath):&#xA;  with open(id_info_filepath, 'r') as f:&#xA;      mpids = sorted([line.rstrip('\n') for line in f.readlines()])&#xA;  return mpids&#xA;&#xA;def pick_newly_added_ids(locally_existing_ids, current_db_ids):  &#xA;  newly_added_ids = list(set(current_db_ids) - set(locally_existing_ids))&#xA;  return newly_added_ids&#xA;&#xA;def get_2d_materials_only(newly_added_ids,mpr):&#xA;  two_dim_materials = []&#xA;  for mpid in newly_added_ids:&#xA;      mpd = mpr.robocrys.get_data_by_id(mpid)&#xA;      try:&#xA;          dim = mpd.condensed_structure.dimensionality&#xA;          two_dim_materials.append(mpid)&#xA;      except:    &#xA;          continue&#xA;  return two_dim_materials&#xA;&#xA;def get_current_db_ids(current_material_infos):&#xA;  current_db_ids = []&#xA;  for info in current_material_infos:&#xA;    current_db_ids.append(info.material_id)&#xA;  return current_db_ids&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h3&gt;Main code:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;id_info_filepath = 'mp_ids.txt'&#xA;mpr = MPRester(api_key=api_key)&#xA;current_material_infos = get_all_material_infos_from_db(mpr)&#xA;current_db_ids = get_current_db_ids(current_material_infos)&#xA;locally_existing_ids = get_locally_existing_ids(id_info_filepath)&#xA;&#xA;newly_added_ids = pick_newly_added_ids(locally_existing_ids, current_db_ids)&#xA;newly_added_two_dim_materials = get_2d_materials_only(newly_added_ids,mpr)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then save only the newly added 2d materials to your: &lt;code&gt;'mp_2dids.txt'&lt;/code&gt;. This should save you some time as you are looping through only the newly added ids. Hope that helps.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-24T14:55:05.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10773" PostTypeId="2" ParentId="10701" CreationDate="2023-04-24T15:13:45.597" Score="3" Body="&lt;p&gt;The e_Lumo and e_Homo can be calculated using pyscf and scipy.&#xA;I will demonstrate using a simple molecule such as ethanol:&lt;/p&gt;&#xA;&lt;h2&gt;Code:&lt;/h2&gt;&#xA;&lt;h4&gt;Helper functions and init:&lt;/h4&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf, lo, tools&#xA;from scipy.constants import physical_constants&#xA;HARTREE_TO_EV_FACTOR = dict(physical_constants)['Hartree energy in eV'][0]&#xA;&#xA;&#xA;def find_homo_lumo(mf):&#xA;    lumo = float(&amp;quot;inf&amp;quot;)&#xA;    lumo_idx = None&#xA;    homo = -float(&amp;quot;inf&amp;quot;)&#xA;    homo_idx = None&#xA;    for i, (energy, occ) in enumerate(zip(mf.mo_energy, mf.mo_occ)):&#xA;        if occ &amp;gt; 0 and energy &amp;gt; homo:&#xA;            homo = energy&#xA;            homo_idx = i&#xA;        if occ == 0 and energy &amp;lt; lumo:&#xA;            lumo = energy&#xA;            lumo_idx = i&#xA;&#xA;    return homo, lumo&#xA;&#xA;basis=&amp;quot;sto-3g&amp;quot;&#xA;xyz = '''&#xA;C     -0.887089    0.175064   -0.012535&#xA;C      0.460489   -0.515516   -0.046535&#xA;O      1.442965    0.307267    0.565572&#xA;H     -0.847478    1.127768   -0.550817&#xA;H     -1.658782   -0.453327   -0.465842&#xA;H     -1.176944    0.403676    1.018306&#xA;H      0.768712   -0.724328   -1.075460&#xA;H      0.419486   -1.462073    0.500177&#xA;H      1.478640    1.141468    0.067135&#xA;'''&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;Main Code:&lt;/h4&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = gto.M(atom=xyz,basis=basis)&#xA;mol.build()&#xA;mf = scf.RHF(mol).run()&#xA;&#xA;homo_hartree, lumo_hartree = find_homo_lumo(mf)&#xA;&#xA;homo_eV = homo_hartree*HARTREE_TO_EV_FACTOR&#xA;lumo_eV = lumo_hartree*HARTREE_TO_EV_FACTOR&#xA;&#xA;Eg = abs(homo_eV - lumo_eV)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So once you have the e_homo, e_lumo and Eg, you can use any image editing software to construct images like the ones in the question.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-24T15:13:45.597" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10774" PostTypeId="1" CreationDate="2023-04-24T15:14:21.567" Score="5" ViewCount="56" Body="&lt;p&gt;A normal insulator is the same as vacuum because one can change the band structure from one to another without closing the gap, but for topological insulators (talking about 2D TI) like 1T'-&lt;a href=&quot;https://en.wikipedia.org/wiki/Transition_metal_dichalcogenide_monolayers&quot; rel=&quot;nofollow noreferrer&quot;&gt;TMDs&lt;/a&gt; or HgTe/CdTe, there is a band closing and reopening process due to SOC making the topological have a nonzero/nontrivial topological number. To make the question simple we only consider &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; invariant and a 2D topological insulator would have &lt;span class=&quot;math-container&quot;&gt;$Z_2=1$&lt;/span&gt; and a normal insulator would have &lt;span class=&quot;math-container&quot;&gt;$Z_2=0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;And topological insulators have a bulk-boundary correspondence making the edge states of TI topologically protected. However, the edge states of a normal insulator which still exist due to the broken translation symmetry are not protected.&lt;/p&gt;&#xA;&lt;p&gt;My question is, can we say that to have topologically protected edge states, one must have two insulators with different &lt;span class=&quot;math-container&quot;&gt;$Z_2$&lt;/span&gt; numbers like 0 and 1 or a TI and vacuum? As for the normal insulators' edge states are not protected because we are talking about it having vacuum outside which shares its topological number 0. And the topological protected edge states will be absent when two TI having &lt;span class=&quot;math-container&quot;&gt;$Z_2=1$&lt;/span&gt; are put together, even if the two are different materials.&lt;/p&gt;&#xA;&lt;p&gt;This would certainly answer the extreme situation when a huge bulk of topological are presented and it is insulating in the bulk and there are no topological protected conducting edge states. But I can treat a huge bulk of TI as two TI with the same topological number put together and the topological edge states vanish because both sides are topologically the same.&lt;/p&gt;&#xA;&lt;p&gt;If not so, please leave detailed illustrations and references, if so do you find any experiments supporting the above understanding?&lt;/p&gt;&#xA;" OwnerUserId="7058" LastEditorUserId="7" LastEditDate="2023-05-23T12:36:36.520" LastActivityDate="2023-05-23T12:36:36.520" Title="Presence/absence of topologically protected edge states on the boundary of two topological insulators" Tags="|condensed-matter|topological-insulators|" AnswerCount="0" CommentCount="1" ClosedDate="2023-11-08T00:24:30.460" ContentLicense="CC BY-SA 4.0" />
  <row Id="10775" PostTypeId="1" AcceptedAnswerId="10776" CreationDate="2023-04-24T15:19:27.710" Score="3" ViewCount="573" Body="&lt;p&gt;I am trying to generate a matrix of small molecules arranged at locations (x, y, z) on a cube. I already have a Tcl script that can generate the required PDB and PSF files. However, I was wondering if there is a way to merge them into a single PDB and PSF file using Tcl itself. Reproduced below is the script to generate the molecules at the given positions.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set psf     adenine.xplor_ext.psf&#xA;set pdb     adenine.pdb&#xA;set resname     ADE&#xA;&#xA;set a   3&#xA;set b   3&#xA;set d   10&#xA;&#xA;# first generate in required pdb and psf files&#xA;&#xA;set xend [expr &lt;span class=&quot;math-container&quot;&gt;$a / 2]&#xA;set xstart [expr -1 * $&lt;/span&gt;xend]&#xA;&#xA;set yend [expr &lt;span class=&quot;math-container&quot;&gt;$b / 2]&#xA;set ystart [expr -1 * $&lt;/span&gt;yend]&#xA;&#xA;set counter 1&#xA;&#xA;for { set i &lt;span class=&quot;math-container&quot;&gt;$xstart } { $i &amp;lt;= $xend } { incr i } {&#xA;    for { set j $ystart } { $j &amp;lt;= $yend } { incr j } {&#xA;        mol load psf $psf&#xA;        mol addfile $pdb type pdb waitfor all&#xA;        set sel [atomselect top &quot;resname $resname&quot;]&#xA;        set com [measure center $sel weight mass]&#xA;        $sel moveby [vecscale -1 $com]&#xA;        set xdist [expr $d * $i]&#xA;        set ydist [expr $d * $j]&#xA;        set transvec [list $xdist $ydist 0]&#xA;        puts $transvec&#xA;        $sel moveby $transvec&#xA;        $sel set segname AD$counter&#xA;        $sel set resid $counter&#xA;        $sel writepsf adenine.$i.$j.psf&#xA;        $sel writepdb adenine.$i.$&lt;/span&gt;j.pdb&#xA;        incr counter&#xA;        mol delete all&#xA;    }&#xA;}&#xA;exit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;From VMD, I see that the molecules are merged using a call to CHARMM program (at least that is what I could understand from the TkConsole window). But it works by calling 2 PDB files at a time, and is not necessarily what I am looking for. Any help in this regard would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-04-24T17:54:17.083" Title="Merging multiple PDB files in VMD using Tcl scripts?" Tags="|molecular-modeling|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10776" PostTypeId="2" ParentId="10775" CreationDate="2023-04-24T17:54:17.083" Score="4" Body="&lt;pre&gt;&lt;code&gt;set midlist {}&#xA;for { set i &lt;span class=&quot;math-container&quot;&gt;$xstart } { $i &amp;lt;= $xend } { incr i } {&#xA;        for { set j $ystart } { $j &amp;lt;= $yend } { incr j } {&#xA;             set mol [mol new adenine.$i.$j.psf waitfor all]&#xA;             mol addfile adenine.$i.$j.pdb&#xA;             lappend midlist $mol&#xA;            }&#xA;    }&#xA;set mol [::TopoTools::mergemols $&lt;/span&gt;midlist]&#xA;&#xA;animate write psf adenine.merged.psf &lt;span class=&quot;math-container&quot;&gt;$mol&#xA;animate write pdb adenine.merged.pdb $&lt;/span&gt;mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;TopoTools does the job&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2023-04-24T17:54:17.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10777" PostTypeId="1" AcceptedAnswerId="10781" CreationDate="2023-04-24T18:46:12.677" Score="8" ViewCount="770" Body="&lt;p&gt;I have a PDB file. I want to duplicate this pdb file automatically instead of doing it manually. For example, if I visualize my PDB, I will find only one structure in (x,y,z). I want to have more copies of my structure. Therefore, I can visualize the PDB, and I can see that there are 9 or 10 copies of the structure in the PDB file, and they are located well close to each other but do not overlap. Then I can solvate without any problem.&#xA;Is there any Python code or method to do that?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="5" LastEditDate="2023-04-26T01:43:48.677" LastActivityDate="2023-04-26T01:43:48.677" Title="Duplicate structure in PDB format?" Tags="|molecular-dynamics|molecular-modeling|software-recommendations|one-topic-per-answer|visualization-software|" AnswerCount="3" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10778" PostTypeId="2" ParentId="10767" CreationDate="2023-04-25T00:18:47.653" Score="6" Body="&lt;p&gt;Your first question -- writing out analytical forms for forces from potential functions -- is the hardest of the lot. For manual derivations the chain rule is often useful, and your workings already show an application of it. I'm afraid there are no shortcuts there unless you are familiar with a computer mathematics package (like Mathematica or Sage) that can churn out the answers for you.&lt;/p&gt;&#xA;&lt;p&gt;But proving that (or when) these forces conserve energy and momentum is very easy! Consider the equations of motion (with vector variables as appropriate):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \dot{p} = -\nabla_x U; \hspace{2em} \dot{x} = \frac{p}{m} \tag{1} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the Hamiltonian, or total energy,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ H \equiv U + \frac{p^2}{2m}. \tag{2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;A quick application of the chain rule gives&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \dot{H} = \dot{p} \cdot \nabla_p H + \dot{x} \cdot \nabla_x H \tag{3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and substituting in equation (1) quickly shows that &lt;span class=&quot;math-container&quot;&gt;$\dot{H}$&lt;/span&gt; for these equations of motion is zero.&lt;/p&gt;&#xA;&lt;p&gt;From equation (1), summed over all particles in a system, you can also quickly see that wherever Newton's Third Law holds -- that is, where all forces can be decomposed into action-reaction pairs between particles -- the total force on the system will be zero and momentum will be conserved.&lt;/p&gt;&#xA;&lt;p&gt;Thus, energy will be conserved in all molecular systems (with thermostatting, more complicated definitions are needed), while momentum often isn't. As a very simple example, two mobile particles connected by a harmonic bond will conserve both energy and momentum; a mobile particle tethered harmonically to a fixed point will conserve energy but not momentum.&lt;/p&gt;&#xA;&lt;p&gt;Both results are examples of Noether's Theorem, a deep and general result stating that system symmetries result in conserved quantities. For our particular cases, a time-invariant Hamiltonian results in conserved energy and a translation-invariant Hamiltonian results in conserved linear momenta.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-04-25T00:18:47.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10779" PostTypeId="2" ParentId="10777" CreationDate="2023-04-25T10:03:31.600" Score="7" Body="&lt;p&gt;This can be achieved with Python. I will demonstrate it with a simple molecule : methanol.&lt;/p&gt;&#xA;&lt;p&gt;The PDB file of methanol I used looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   0.024  1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  -0.278  1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  -0.901  1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   0.600  1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   0.609  1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   0.137  1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let us initialize some paths and variables:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;input_pdb_path = 'input/methanol.pdb'&#xA;output_pdb_with_repeated_mols = 'output/methanol_repeated.pdb'&#xA;n_mols = 10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let us now read the PDB which we wish to repeat.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with open(input_pdb_path, 'r') as in_file:&#xA;    data = in_file.read()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;A new PDB will be created at the output path defined in the initialization.&#xA;Since you require that the molecules are not overlapping, let us translate them in the z axis by 1 unit from each other.&lt;/p&gt;&#xA;&lt;p&gt;This is achieved by the following function:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def translate_mol_in_z_axis(data, translation_dist):&#xA;  pattern = r'-?[\d]*[.][\d]+' # This pattern will capture any numbers with decimals digits&#xA;  edited_lines = []&#xA;  n_decimal_places  =3&#xA;&#xA;  for line in data.split('\n'):&#xA;    numeric_info = [(m.start(0), m.end(0), m.group(0)) for m in re.finditer(pattern, line)]&#xA;    if numeric_info:&#xA;      x_coord_info = numeric_info[0]&#xA;      y_coord_info = numeric_info[1]&#xA;      z_coord_info = numeric_info[2]&#xA;&#xA;      z_coord_start_idx= z_coord_info[0]&#xA;      z_coord_end_idx= z_coord_info[1]&#xA;      z_coord_val = z_coord_info[2]&#xA;&#xA;      line_edited = line[:z_coord_start_idx] + str(round(float(z_coord_val)+translation_dist, n_decimal_places)) + line[z_coord_end_idx+1:]&#xA;    else:&#xA;      line_edited = line&#xA;    &#xA;    edited_lines.append(line_edited)&#xA;&#xA;  edited_mol_pdb = '\n'.join(edited_lines)&#xA;  return edited_mol_pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let us now replicate the molecules in a new output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with open(output_pdb_with_repeated_mols, 'w') as out_file:&#xA;  for i in range(n_mols):&#xA;    translation_dist = i &#xA;    out_file.write('\n\n')&#xA;    translated_mol_data = translate_mol_in_z_axis(data, translation_dist)&#xA;    out_file.write(translated_mol_data)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When the output PDB is viewed in a software like PyMOL, you will see that the molecules are stacked with 1 unit distance in the z axis like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q5FfF.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q5FfF.png&quot; alt=&quot;stacked_molecules_PDB&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The output file will look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   0.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  -0.278 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  -0.901 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   0.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   0.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   0.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   1.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  0.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  0.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   1.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   1.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   1.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   2.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  1.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  1.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   2.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   2.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   2.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   3.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  2.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  2.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   3.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   3.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   3.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   4.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  3.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  3.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   4.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   4.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   4.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   5.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  4.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  4.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   5.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   5.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   5.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   6.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  5.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  5.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   6.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   6.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   6.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   7.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  6.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  6.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   7.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   7.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   7.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   8.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  7.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  7.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   8.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   8.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   8.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&#xA;&#xA;COMPND      METHANOL&#xA;ATOM      1  C           1      -0.748  -0.015   9.024 1.00  0.00&#xA;ATOM      2  O           1       0.558   0.420  8.722 1.00  0.00&#xA;ATOM      3  H           1      -1.293  -0.202  8.099 1.00  0.00&#xA;ATOM      4  H           1      -1.263   0.754   9.6 1.00  0.00&#xA;ATOM      5  H           1      -0.699  -0.934   9.609 1.00  0.00&#xA;ATOM      6  H           1       0.716   1.404   9.137 1.00  0.00&#xA;TER       6              1&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-25T10:03:31.600" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10780" PostTypeId="1" CreationDate="2023-04-25T11:05:01.553" Score="2" ViewCount="109" Body="&lt;p&gt;I am trying to find the norm-conserving(NC) pseudopotential of rare earth metals, but all I could find are about Ultrasoft or PAW types. Is there any recommendation for NC type?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2023-05-01T08:40:22.360" Title="where to find the norm-conserving pseudopotential of rare earth metals?" Tags="|density-functional-theory|pseudopotentials|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10781" PostTypeId="2" ParentId="10777" CreationDate="2023-04-25T11:12:02.917" Score="9" Body="&lt;p&gt;You can use &lt;a href=&quot;https://m3g.github.io/packmol/userguide.shtml&quot; rel=&quot;noreferrer&quot;&gt;Packmol&lt;/a&gt; to achieve this. Below is an example script&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tolerance 15.0&#xA;&#xA;# The file type of input and output files is PDB&#xA;&#xA;filetype pdb&#xA;&#xA;# The name of the output file&#xA;&#xA;output 20_pq_5jb.pdb&#xA;&#xA;structure polyq_frame_1470.pdb&#xA;  number 20&#xA;  inside box 0. 0. 0. 200. 200. 200.&#xA;end structure&#xA;&#xA;tolerance 10&#xA;&#xA;structure sim10_frame_1158.pdb&#xA;  number 5&#xA;  inside box 0. 0. 0. 200. 200. 200.&#xA;end structure&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This script can put 20 molecules of type A and five molecules of type B in a box of size &lt;code&gt;200x200x200&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3593" LastActivityDate="2023-04-25T11:12:02.917" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10782" PostTypeId="2" ParentId="10777" CreationDate="2023-04-25T12:50:29.317" Score="8" Body="&lt;p&gt;This can also be done in VMD using Tcl scripts. The only requirements are that you have a PSF and PDB file for the structure that you want to replicate.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set pdb methanol.pdb    # name of pdb file&#xA;set psf methanol.psf    # name of psf file&#xA;&#xA;set a 3 # repetitions in x-direction&#xA;set b 3 # repetitions in y-direction&#xA;set c 3 # repetitions in z-direction&#xA;&#xA;set xdist 10    # separation in x-direction&#xA;set ydist 10    # separation in y-direction&#xA;set zdist 10    # separation in z-direction&#xA;&#xA;set xend [expr &lt;span class=&quot;math-container&quot;&gt;$a / 2]&#xA;set xstart [expr -1 * $&lt;/span&gt;xend]&#xA;&#xA;set yend [expr &lt;span class=&quot;math-container&quot;&gt;$b / 2]&#xA;set ystart [expr -1 * $&lt;/span&gt;yend]&#xA;&#xA;set zend [expr &lt;span class=&quot;math-container&quot;&gt;$c / 2]&#xA;set zstart [expr -1 * $&lt;/span&gt;zend]&#xA;&#xA;set counter 0&#xA;&#xA;# generate the required psf and pdb files&#xA;&#xA;for { set i &lt;span class=&quot;math-container&quot;&gt;$xstart } { $i &amp;lt;= $xend } { incr i } {&#xA;    set xtrans [expr $xdist * $i]&#xA;    for { set j $ystart } { $j &amp;lt;= $yend } { incr j } {&#xA;        set ytrans [expr $ydist * $j]&#xA;        for { set k $zstart } { $k &amp;lt;= $zend } { incr k } {&#xA;            set ztrans [expr $zdist * $k]&#xA;            mol load psf $psf&#xA;            mol addfile $pdb type pdb waitfor all&#xA;            set sel [atomselect top all]    # assuming that your pdb file contains only the molecule that you want to replicate&#xA;            $sel moveby [vecscale -1 [measure center $sel weight mass]] # moves the molecule to origin&#xA;            set transvec [list $xtrans $ytrans $ztrans]&#xA;            $sel moveby $transvec&#xA;            $sel set segname M$counter&#xA;            $sel writepdb methanol.$i.$j.$k.pdb&#xA;            $sel writepsf methanol.$i.$j.$&lt;/span&gt;k.psf&#xA;            incr counter&#xA;            mol delete all&#xA;        }&#xA;    }&#xA;}&#xA;&#xA;# merge the generated files&#xA;&#xA;package require topotools 1.6&#xA;&#xA;set molList {}&#xA;&#xA;for { set i &lt;span class=&quot;math-container&quot;&gt;$xstart } { $i &amp;lt;= $xend } { incr i } {&#xA;for { set j $ystart } { $j &amp;lt;= $yend } { incr j } {&#xA;    for { set k $zstart } { $k &amp;lt;= $zend } { incr k } {&#xA;        set mol [mol new methanol.$i.$j.$k.psf waitfor all]&#xA;        $mol addfile methanol.$i.$j.$k.pdb&#xA;        lappend molList $&lt;/span&gt;mol                &#xA;        }&#xA;    }&#xA;}&#xA;&#xA;set mol [::TopoTools::mergemols &lt;span class=&quot;math-container&quot;&gt;$molList]&#xA;animate write pdb combined.pdb $&lt;/span&gt;mol&#xA;animate write psf combined.psf $mol&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-04-25T12:50:29.317" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10783" PostTypeId="2" ParentId="10760" CreationDate="2023-04-25T19:58:52.310" Score="8" Body="&lt;p&gt;You state your background is chemistry, and have aspiration for Python as a programming language aiming for ML without background in computer science.&lt;/p&gt;&#xA;&lt;p&gt;Do you have some experience in programming &lt;em&gt;at all&lt;/em&gt;?  In case you don't I suggest to visit the inflammation classes by &lt;a href=&quot;https://software-carpentry.org/lessons/&quot; rel=&quot;noreferrer&quot;&gt;software-carpentry&lt;/a&gt; for the *nix shell, version control by git, and beginners lessons for Python.  Perhaps their classes pass nearby your area, too (&lt;a href=&quot;https://software-carpentry.org/workshops/&quot; rel=&quot;noreferrer&quot;&gt;schedule&lt;/a&gt;).  After this, you should be able to create the first small and simple programs on you own, and identify what can be useful &lt;em&gt;in addition&lt;/em&gt; to this &amp;quot;starter set&amp;quot;, both in terms of concepts (e.g. &lt;a href=&quot;https://programminghistorian.org/en/lessons/understanding-regular-expressions&quot; rel=&quot;noreferrer&quot;&gt;regular expressions&lt;/a&gt;), as well as implementations in your language of choice (e.g., &lt;a href=&quot;https://matplotlib.org/&quot; rel=&quot;noreferrer&quot;&gt;matplotlib&lt;/a&gt; and &lt;a href=&quot;http://swcarpentry.github.io/python-novice-gapminder/09-plotting/index.html&quot; rel=&quot;noreferrer&quot;&gt;plotting&lt;/a&gt;).  But don't get lost there.&lt;/p&gt;&#xA;&lt;p&gt;Instead turn &lt;em&gt;early&lt;/em&gt; your attention to e.g. &lt;em&gt;The Journal of Chemical Education&lt;/em&gt; to apply the acquired skill.   There is for a compact 101 by Lafuente,[1] and plenty examples of application which can serve as prompt for your training.  Enter &amp;quot;machine learning&amp;quot; into the &lt;a href=&quot;https://pubs.acs.org/action/doSearch?SeriesKey=jced&quot; rel=&quot;noreferrer&quot;&gt;search mask&lt;/a&gt; of the journal (which suggests automatic completion to &amp;quot;Machine Learning in Chemistry&amp;quot;, &amp;quot;Machine Learning for Drug Discovery&amp;quot;, and &amp;quot;Machine Learning in Materials Science&amp;quot;).  Don't automatically discharge them from your screen if - as St James' classification of spectra by ML[2] - a different language of implementation (here: MATLAB) was used, but imagine how such a capstone project could be implemented in the language(s)* you are familiar with.&lt;/p&gt;&#xA;&lt;p&gt;A pinch of salt: you are going to meet people overly excited about machine learning and artificial intelligence as if the underlying techniques &lt;em&gt;finally&lt;/em&gt; were applied on large scale.  Some of them are statistics / chemometrics already known for long (e.g. &lt;a href=&quot;https://en.wikipedia.org/wiki/Principal_component_analysis&quot; rel=&quot;noreferrer&quot;&gt;principal component analysis&lt;/a&gt; in IR spectroscopy) which now indeed enjoy a renaissance for every additional field of application gained.  However, in part, the field's attraction equally is due because computation became so affordable (e.g., renting infrastructure in the cloud &lt;em&gt;on demand&lt;/em&gt;), and often tasks can be split into multiple smaller ones run in parallel instead of a pure sequential approach (multicore CPUs). Or that computer programs can assist you in generating new computer code (literally like &lt;a href=&quot;https://github.com/features/copilot&quot; rel=&quot;noreferrer&quot;&gt;copilot&lt;/a&gt;) faster, where the chatbots like ChatGPT are one level on top.  Similar to a chariot, you typically don't pull it over long distances, but you should &lt;em&gt;know enough&lt;/em&gt; about it and the horses for a safe and reliable drive.&lt;/p&gt;&#xA;&lt;p&gt;* Depending on the task ahead, some programming languages are more suitable than others.  Multiple criteria should apply for a selection.&lt;/p&gt;&#xA;&lt;p&gt;[1] Lafuente, D.; Cohen, B.; Fiorini, G.; García, A. A.; Bringas, M.; Morzan, E.; Onna, D. A Gentle Introduction to Machine Learning for Chemists: An Undergraduate Workshop Using Python Notebooks for Visualization, Data Processing, Analysis, and Modeling. &lt;em&gt;J. Chem. Educ.&lt;/em&gt; &lt;strong&gt;2021&lt;/strong&gt;, &lt;em&gt;98&lt;/em&gt;, 2892-2898, &lt;a href=&quot;https://doi.org/10.1021/acs.jchemed.1c00142&quot; rel=&quot;noreferrer&quot;&gt;doi 10.1021/acs.jchemed.1c00142&lt;/a&gt; (and &lt;a href=&quot;https://ri.conicet.gov.ar/bitstream/11336/147938/2/CONICET_Digital_Nro.28c395c6-a109-42f0-9b69-7caeb43bc9c8_A.pdf&quot; rel=&quot;noreferrer&quot;&gt;author's copy&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;[2] St James, A. G.; Hand, L.; Mills, T.; Song, L.; Brunt, A. S. J.; Bergstrom Mann, P. E.; Worrall, A. F.; Stewart, M. I.; Vallance, C. Exploring Machine Learning in Chemistry through the Classification of Spectra: An Undergraduate Project. &lt;em&gt;J. Chem. Educ.&lt;/em&gt; &lt;strong&gt;2023&lt;/strong&gt;, &lt;em&gt;100&lt;/em&gt;, 1343-1350, &lt;a href=&quot;https://doi.org/10.1021/acs.jchemed.2c00682&quot; rel=&quot;noreferrer&quot;&gt;doi 10.1021/acs.jchemed.2c00682&lt;/a&gt; (open access / author's choice).&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The answer once was given on &lt;a href=&quot;https://chemistry.stackexchange.com/questions/173029/how-a-begginer-should-start-his-studies-in-ml-for-chemistry-application/173031?noredirect=1#comment365097_173031&quot;&gt;chemistry.stackexchange&lt;/a&gt; on April 20th, 2023.  User Martin (a moderator) suggested the move to this site.&lt;/p&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2023-04-25T19:58:52.310" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10784" PostTypeId="1" CreationDate="2023-04-26T08:44:51.930" Score="3" ViewCount="110" Body="&lt;p&gt;I am trying to heat up my system from 10K to 300K using the NPT ensemble. But the temperature doesn't reach 300K. What do you think is the problem?&lt;/p&gt;&#xA;&lt;p&gt;This is my code for the heating part. However, the problem is the temperature is only reaching about 150K after the entire 30000 runs.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;velocity        all create 10 416629&#xA;&#xA;thermo          100&#xA;thermo_style    custom step temp press&#xA;&#xA;fix             1 all npt temp 10.0 10.0 1.0 iso 0.0 0.0 10.0&#xA;run             10000&#xA;unfix           1&#xA;&#xA;fix             2 all nve&#xA;run             5000&#xA;unfix           2&#xA;&#xA;fix             1 all npt temp 10.00 300.00 1.0 iso 0.0 0.0 10.0&#xA;run             30000&#xA;unfix           1&#xA;&#xA;fix             2 all nve&#xA;run             5000&#xA;unfix           2&#xA;&#xA;fix             1 all npt temp 300 300.00 10.00 iso 0.0 0.0 100.0&#xA;run             10000&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7072" LastEditorUserId="6687" LastEditDate="2023-04-26T11:18:17.613" LastActivityDate="2023-12-05T15:01:30.153" Title="NPT Molecular dynamics calculation problem" Tags="|molecular-dynamics|molecular-modeling|lammps|atomistic-simulation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10785" PostTypeId="1" CreationDate="2023-04-26T13:53:35.083" Score="3" ViewCount="92" Body="&lt;p&gt;I want to change the text formatting in the label's properties in VMD, as I want to use 1-based indexing rather than 0-based indexing. For now, %i in Format gives index on the screen, but I want to use serial i.e. the numbering of atoms starts from 0 instead. How can we do that? Thanks.&lt;/p&gt;&#xA;&lt;p&gt;With best regards&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-04-26T13:53:35.083" Title="Formatting of text in label of VMD" Tags="|vmd|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-01T17:50:20.687" ContentLicense="CC BY-SA 4.0" />
  <row Id="10786" PostTypeId="2" ParentId="467" CreationDate="2023-04-26T17:05:50.067" Score="8" Body="&lt;h1&gt;nglview and nvc&lt;/h1&gt;&#xA;&lt;p&gt;Recently I found it hard to make the pymatgen &lt;code&gt;structure_vtk&lt;/code&gt; visualization method to work. I believe it might be deprecated in favour of &lt;code&gt;crystal_toolkit&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another simple, fully Python based (Jupyter notebook) option is &lt;a href=&quot;https://github.com/nglviewer/nglview&quot; rel=&quot;nofollow noreferrer&quot;&gt;nglview&lt;/a&gt;, which can visualize pymatgen structures as well.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, &lt;a href=&quot;https://github.com/lan496/nvc&quot; rel=&quot;nofollow noreferrer&quot;&gt;nvc&lt;/a&gt; is an nglview wrapper for specifically visualizing crystal structures.&lt;/p&gt;&#xA;&lt;p&gt;It works for quick inline visualization of structures.&lt;/p&gt;&#xA;" OwnerUserId="7076" LastEditorUserId="7076" LastEditDate="2023-08-15T01:09:08.683" LastActivityDate="2023-08-15T01:09:08.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10787" PostTypeId="2" ParentId="4491" CreationDate="2023-04-26T20:10:34.563" Score="3" Body="&lt;p&gt;&lt;a href=&quot;https://web.archive.org/web/20230426191455/http://www.ccl.net/cca/software/SOURCES/FORTRAN/molecular_surface/gepol93/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gepol93&lt;/a&gt; is a FORTRAN library which computes three kinds of envelope surfaces :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Van Der Waals molecular surface&lt;/li&gt;&#xA;&lt;li&gt;Accessible molecular surface&lt;/li&gt;&#xA;&lt;li&gt;Solvent Excluding surface&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There is also a python library called &lt;a href=&quot;https://github.com/vandan-revanur/pychemovality&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pychemovality&lt;/a&gt; (which is authored by me) that calculates the solvent excluded surface area (SESA) in order to calculate ovality of molecules.&lt;/p&gt;&#xA;&lt;p&gt;This python library uses a modified version of GEPOL93 under the hood. This library outputs the SESA and corresponding volume.&lt;/p&gt;&#xA;&lt;p&gt;Also if you are interested in using the modified GEPOL93 Fortran script directly, then I have included compilation instructions for it on the pychemovality repo &lt;a href=&quot;https://github.com/vandan-revanur/pychemovality/blob/master/docs/fortran_compilation_instructions.md&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-04-26T20:37:16.280" LastActivityDate="2023-04-26T20:37:16.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10788" PostTypeId="1" CreationDate="2023-04-27T09:40:09.623" Score="2" ViewCount="62" Body="&lt;p&gt;I have been looking for OPLS gromacs parameters for 1-octanol, but haven't been able to get it. Doing a quick web search takes me into links for lipidbook, from which I can't download at all from &lt;a href=&quot;https://lipidbook.org/lipid/show/id/10.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://lipidbook.org/lipid/show/id/10.html&lt;/a&gt; . Can someone please advise, or show me right direction? Thanks a lot.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="1791" LastEditDate="2023-04-27T10:03:22.580" LastActivityDate="2023-04-28T09:55:32.487" Title="Looking for the OPLS parameters for octanol" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10789" PostTypeId="1" AcceptedAnswerId="10790" CreationDate="2023-04-27T10:02:43.857" Score="3" ViewCount="74" Body="&lt;p&gt;Imagine now, I have 5 structures, and I want to estimate the time when the 5 structures are closer to each other at the same time. I thought I could extract the distance between the different structures and structure number 1 (i.e., the distance between structure 1 and 2, the distance between 1 and 3, 1 and 4, etc.). At the end, I will have 4 files that contain the time and distance between these structures with respect to structure number 1. But when I plotted these different files, I couldn't know when the 5 structures were closer to each other at the same time.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any suggestions?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="4657" LastEditDate="2023-04-27T10:16:43.190" LastActivityDate="2023-04-28T02:01:31.980" Title="Estimate the time between different residues?" Tags="|molecular-dynamics|molecular-modeling|mathematical-modeling|amber|gnuplot|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10790" PostTypeId="2" ParentId="10789" CreationDate="2023-04-27T14:31:39.873" Score="4" Body="&lt;p&gt;Let the centre of mass of each residue be denoted as &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; and is evaluated at every frame. Let the centre of mass of the combined system be &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt; where c denotes combined. You can evaluate the distance between each &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_c$&lt;/span&gt; at every frame. This will give you 5 distance values for each frame. Now the task is to minimize the function &lt;span class=&quot;math-container&quot;&gt;$f(d_i) = \Sigma d_i$&lt;/span&gt;. If you evaluate that function at every frame, you should get the lowest values when all your residues are close to one another.&lt;/p&gt;&#xA;&lt;p&gt;Here is a Tcl script that can do that&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set psf adenine.psf&#xA;set dcd adenine.dcd&#xA;set output  [open distance.dat w]&#xA;&#xA;mol load psf &lt;span class=&quot;math-container&quot;&gt;$psf&#xA;mol addfile type dcd $&lt;/span&gt;dcd waitfor all&#xA;&#xA;set numframes [molinfo top get numframes]&#xA;&#xA;for { set framecounter 0 } { &lt;span class=&quot;math-container&quot;&gt;$framecounter &amp;lt; $&lt;/span&gt;numframes } { incr framecounter } {&#xA;    molinfo top set frame &lt;span class=&quot;math-container&quot;&gt;$framecounter &#xA;set total [atomselect top &quot;resname ADE&quot;]            # selects all the adenine molecules&#xA;set tcom [measure center $&lt;/span&gt;total weight mass]        # gets the centre of mass for the combined adenine system&#xA;    set segnames [lsort -unique [&lt;span class=&quot;math-container&quot;&gt;$total get segname]]   # gets the segnames for each adenine molecule&#xA;set dist {}&#xA;foreach segname $&lt;/span&gt;segnames {&#xA;        set sel [atomselect top &amp;quot;resname ADE and segname &lt;span class=&quot;math-container&quot;&gt;$segname&quot;]&#xA;    set rcom [measure center $&lt;/span&gt;sel weight mass]&#xA;        set distance [veclength [vecsub &lt;span class=&quot;math-container&quot;&gt;$rcom $&lt;/span&gt;tcom]]   # calculate the distance between each residue COM and total COM&#xA;        lappend dist $distance                  # append it to a list&#xA;    }&#xA;    &#xA;    set totaldistance 0&#xA;    foreach distance &lt;span class=&quot;math-container&quot;&gt;$dist {&#xA;    set totaldistance [expr $totaldistance + $distance]&#xA;}&#xA;puts $&lt;/span&gt;output &amp;quot;$totaldistance&amp;quot;&#xA;}&#xA;&#xA;close $output&#xA;mol delete all&#xA;exit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-04-28T02:01:31.980" LastActivityDate="2023-04-28T02:01:31.980" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10791" PostTypeId="1" AcceptedAnswerId="10792" CreationDate="2023-04-27T15:37:18.870" Score="5" ViewCount="703" Body="&lt;p&gt;While calculating various quantities that involves particle positions ( for example, radial distribution function, mean square displacement etc.) using Molecular Dynamics simulation, the effects of Periodic Boundary Conditions ( PBC ) are removed by adopting some unwrapping procedure. I don't understand how it is done. Can anybody explain the concept ?&lt;/p&gt;&#xA;" OwnerUserId="7086" LastActivityDate="2023-04-27T18:25:42.207" Title="Unwrapping particle coordinates in MD simulations to remove effects of periodic boundary condition" Tags="|molecular-dynamics|molecular-modeling|vmd|periodic-boundary-conditions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10792" PostTypeId="2" ParentId="10791" CreationDate="2023-04-27T15:46:49.403" Score="7" Body="&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;When you are doing an MD simulation, you should ideally be using a large simulation box so that you can study the properties of the system. However, this is easier said than done because of the computational resources that would be required to study the dynamics of very large systems. So we instead take simulation boxes of trackable size, and assume periodic boundary conditions so that you are essentially simulating a very large system.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Now to the question of unwrapping the trajectory to remove the PBC. When you are doing a simulation using PBC, when a particle leaves the simulation box at one of the ends, an equivalent particle enters the box from the other end. What unwrapping does is essentially reversing this transformation, so that the PBC image is shifted back to where it should have been, if no PBC were applied.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Let us consider a collection of helium atoms in a box of dimensions 16 x 16 x 16 cubic angstroms. Now, in the simulation if one of the He atom leaves the box, a corresponding periodic image will replace it in the box. This means that the He atom was folded into the simulation box. The transformation works in this way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    check if the x-coordinate of the atom is greater than positive x-end:&#xA;        if yes set x-coordinate as (x-coordinate - box length in x)&#xA;    check if the y-coordinate of the atom is greater than positive y-end:&#xA;        if yes set y-coordinate as (y-coordinate - box length in y)&#xA;    check if the z-coordinate of the atom is greater than positive z-end:&#xA;        if yes set z-coordinate as (z-coordinate - box length in z)&#xA;&#xA;&#xA;    check if the x-coordinate of the atom is less than negative x-end:&#xA;        if yes set x-coordinate as (x-coordinate + box length in x)&#xA;    check if the y-coordinate of the atom is less than negative y-end:&#xA;        if yes set y-coordinate as (y-coordinate + box length in y)&#xA;    check if the z-coordinate of the atom is less than negative z-end:&#xA;        if yes set z-coordinate as (z-coordinate + box length in z)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is how PBC wrapping works. So when you are doing a PBC unwrapping you negate these transformations.&lt;/p&gt;&#xA;&lt;p&gt;Just to clarify a few points:&#xA;You generally unwrap a trajectory if you have bonds that span across the simulation box. In such cases, you add or subtract the corresponding cell vectors to move the wrapped atom to the position where it should have been, if not wrapped. Consider the example of a water molecule, with one of the hydrogen atom getting wrapped to the negative x-end of the box, while the other hydrogen and oxygen atoms are at the positive x-end of the box. Now when you unwrap, the hydrogen atom that got wrapped will be shifted to the original position, which was (positive x-end + wrapped x-coordinate).&lt;/p&gt;&#xA;&lt;p&gt;Please read the transcript starting from &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/63463894#63463894&quot;&gt;here&lt;/a&gt; for a detailed walkthrough on how is PBC unwrapping done:&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-04-27T18:25:42.207" LastActivityDate="2023-04-27T18:25:42.207" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10793" PostTypeId="1" CreationDate="2023-04-27T16:42:11.427" Score="6" ViewCount="111" Body="&lt;p&gt;I am studying Hematite (Fe2O3) Antiferromagnetic configuration using QE 7.0 (EDIT: compiled and tried 7.1) at the PBE+U level (U = 4.5).&lt;/p&gt;&#xA;&lt;p&gt;I obtained an excellent agreement with experimental data on various properties, but there is one thing I can't wrap my head around.&lt;/p&gt;&#xA;&lt;p&gt;The traces of the occupancy matrices after diagonalization for the minority spin on iron atoms are roughly close to 1 (0.88). I would expect them to be close to 0.&lt;/p&gt;&#xA;&lt;p&gt;Iron atoms have a d5 configuration which I expect would lead to 5 electrons with either spin up or down. In my case, I get that the total number of electrons is 5 in the majority spin channel as expected, but roughly 1 in the minority channel. This is also the case in the example08 in the /PW/tutorials folder of QE for a FeO system.&lt;/p&gt;&#xA;&lt;p&gt;I have been trying unsuccessfully to force the system into having the traces close to 0 for the minority channel.&lt;/p&gt;&#xA;&lt;p&gt;I tried&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Applying starting magnetizations and charges on iron and oxygen atoms.&lt;/li&gt;&#xA;&lt;li&gt;Changing U values&lt;/li&gt;&#xA;&lt;li&gt;Reducing the Gaussian smearing to almost 0&lt;/li&gt;&#xA;&lt;li&gt;A mix of all the previous ones.&lt;/li&gt;&#xA;&lt;li&gt;Starting_ns_eigenvalues for the third eigenvalue in the minority channel initialised to 0&lt;/li&gt;&#xA;&lt;li&gt;Specified the Hubbard_occ to 5.00&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am now wondering if this is to be expected or maybe there is something I am missing about the theory or the implementation of DFT+U or maybe my understanding of the occupancy matrix is simply wrong.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I am now trying the procedure following &lt;a href=&quot;http://theossrv1.epfl.ch/Main/OxidationStates&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://theossrv1.epfl.ch/Main/OxidationStates&lt;/a&gt;. I will try to investigate whether this works but also if there is a big difference in the results. I am wondering if, in the end, this occupancy problem is not a problem at all&lt;/p&gt;&#xA;" OwnerUserId="7088" LastEditorUserId="7088" LastEditDate="2023-04-28T10:00:58.623" LastActivityDate="2023-04-28T10:00:58.623" Title="Eigenvalues of Hubbard occupancy matrix" Tags="|density-functional-theory|quantum-espresso|hubbard-model|metal-oxide|" AnswerCount="0" CommentCount="2" ClosedDate="2023-11-08T00:19:49.063" ContentLicense="CC BY-SA 4.0" />
  <row Id="10794" PostTypeId="1" CreationDate="2023-04-27T18:00:32.843" Score="2" ViewCount="61" Body="&lt;p&gt;We can also assume the lattice parameter of the cubic unit cell to be a and the that of the extended cell to be a', which means that V' = (a')^3&lt;/p&gt;&#xA;&lt;p&gt;So is the number of atoms n' in the extended volume V' equal to:&lt;/p&gt;&#xA;&lt;p&gt;n' = n x (V'/V) ?&lt;/p&gt;&#xA;&lt;p&gt;The basis of this question arises from the fact that I have the Energy of a system in a terms of eV/atom. And I want to calculate the total electronic energy of the extended volume.&lt;/p&gt;&#xA;&lt;p&gt;We can assume the unit cell to be conventional for the ease of calculation.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2023-05-03T12:32:34.470" Title="A cubic unit cell in DFT of volume 'V' has 'n' atoms in it, for an extended volume V' how many atoms would be there in the new volume?" Tags="|density-functional-theory|2d-lattice|energy|atoms-in-molecules|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10795" PostTypeId="1" AcceptedAnswerId="11853" CreationDate="2023-04-27T19:22:24.740" Score="3" ViewCount="52" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.rosettacommons.org/docs/latest/scripting_documentation/RosettaScripts/Movers/Movers-RosettaScripts&quot; rel=&quot;nofollow noreferrer&quot;&gt;Movers&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;What is a 'mover' in molecular dynamics?&lt;/p&gt;&#xA;&lt;p&gt;Can you supply me with reading material on 'mover'?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-04-27T21:23:10.840" LastActivityDate="2023-11-05T14:43:26.467" Title="What is a 'mover' in molecular dynamics?" Tags="|molecular-dynamics|reference-request|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10796" PostTypeId="1" CreationDate="2023-04-28T01:07:37.770" Score="9" ViewCount="534" Body="&lt;p&gt;I am new to DFT calculation and I want to compute DFT total energy and atomic forces of an atomic configuration, given the atomic positions and lattice vectors.&lt;/p&gt;&#xA;&lt;p&gt;I have an extended xyz with DFT energy and forces from a &lt;a href=&quot;https://www.nature.com/articles/s41524-020-00390-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&#xA;XYZ file is pasted at the end of the question.&lt;/p&gt;&#xA;&lt;p&gt;My goal is to do my own DFT calculation using the atomic position information and reproduce the energy and forces data. However, I haven't been able to do so.&lt;/p&gt;&#xA;&lt;p&gt;In the paper, the authors used VASP with PBE exchange-correlation function, 500 eV energy cutoff, and 4x4x4 grid points. I don't have access to VASP, and I was trying to do the calculation using quantum espresso. With my initial attempt, the atomic forces that I got differed by about 1e-2 eV/angstrom, but the energy that I got was about -16,000 eV vs -500 in the paper/xyz file.&lt;/p&gt;&#xA;&lt;p&gt;I don't know why my energy is off by a lot, while the forces are pretty close. Is this an expected behavior from comparing calculations using 2 different DFT software?&#xA;Is there another way to compute DFT total energy and forces given xyz file?&lt;/p&gt;&#xA;&lt;p&gt;Note: I used quantum espresso calculator in ASE to do the calculation.&lt;/p&gt;&#xA;&lt;h3&gt;Code&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from ase.calculators.espresso import Espresso&#xA;&#xA;&#xA;# Read the xyz file&#xA;atoms = read(&amp;quot;inst_cubic_diamond_temp300_strain0.0_step1001.xyz&amp;quot;, format=&amp;quot;extxyz&amp;quot;)&#xA;&#xA;# Calcualtor&#xA;calc = Espresso(&#xA;    pseudopotentials={&amp;quot;C&amp;quot;: &amp;quot;C.pbe-n-kjpaw_psl.1.0.0.UPF&amp;quot;},&#xA;    tstress=True,&#xA;    tprnfor=True,&#xA;    outdir=&amp;lt;outdir&amp;gt;,&#xA;    pseudo_dir=&amp;lt;pseudo_dir&amp;gt;,&#xA;    kpts=(4, 4, 4),&#xA;    koffset=True,&#xA;)&#xA;atoms.calc = calc&#xA;&#xA;# Compute energy and forces&#xA;energy = atoms.get_potential_energy()&#xA;print(&amp;quot;Energy:&amp;quot;, energy)&#xA;forces = atoms.get_forces()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;XYZ file&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;64&#xA;Lattice=&amp;quot;7.10842262195238 0 0 0 7.10842262195238 0 0 0 7.10842262195238 &amp;quot; PBC=&amp;quot;1 1 1&amp;quot; Properties=species:S:1:pos:R:3:force:R:3 Energy=&amp;quot;-512.86187833&amp;quot;&#xA;C     2.515720524176340e-02   3.867550579089600e-03   7.089434672581682e+00 -5.37951000e-01  -9.43653100e-01   8.96908860e-01&#xA;C     1.776933986593727e+00   1.732049273644261e+00   2.572083207130320e-02  4.26181090e-01   1.51736004e+00   3.81343080e-01&#xA;C     7.082577532701300e+00   1.802144789342045e+00   1.769809143517475e+00  1.13683654e+00  -6.10598840e-01   7.06415680e-01&#xA;C     1.730755114222064e+00   7.103866760858615e+00   1.834766904598202e+00  5.28662040e-01   3.17688010e-01  -1.12025143e+00&#xA;C     8.721281061942280e-01   8.735364979679285e-01   8.966439895472150e-01  1.05603720e-01   2.62228850e-01   5.75211080e-01&#xA;C     2.696528798085684e+00   2.679314544279508e+00   9.295221501861438e-01 -7.81283670e-01  -5.78397410e-01  -1.85532276e+00&#xA;C     9.346490289165925e-01   2.672186644581529e+00   2.654060735574339e+00 -2.03034942e+00   1.70433750e-01  -3.59527500e-02&#xA;C     2.678101420875179e+00   9.199713446381380e-01   2.689016972481999e+00 -6.26726520e-01  -1.33007226e+00   1.56036970e-01&#xA;C     3.511187368839771e+00   7.101188022878494e+00   7.107915220793385e+00  9.31579400e-02  -4.02755650e-01   8.05187710e-01&#xA;C     5.312681026669824e+00   1.769173081861437e+00   7.067010726921535e+00  6.70675890e-01  -1.36012410e-01   1.35187542e+00&#xA;C     3.546168769563506e+00   1.802083870160192e+00   1.830411431890475e+00  8.04017590e-01  -7.92153530e-01  -1.76726650e+00&#xA;C     5.379223112984097e+00   3.912248340524160e-02   1.782229477108722e+00 -2.47505791e+00  -2.16700570e-01  -5.76459000e-03&#xA;C     4.425585354722698e+00   8.827204378245163e-01   8.970133431865501e-01  2.16665110e-01   8.11297010e-01  -2.73793900e-01&#xA;C     6.213865521165564e+00   2.672265050483028e+00   8.666035823024164e-01  2.11940450e-01  -9.71874700e-02  -3.56909090e-01&#xA;C     4.454692212824812e+00   2.667208331883838e+00   2.664322099047440e+00  1.78292390e-01   3.44728770e-01   2.32568650e-01&#xA;C     6.202805881832237e+00   9.258737522764287e-01   2.730940032231068e+00  4.33003680e-01   5.79964000e-02  -1.57874570e+00&#xA;C     3.423771754923000e-03   3.576000047014824e+00   7.096407537582318e+00  7.40474130e-01  -4.69554600e-01   5.82278100e-02&#xA;C     1.773121668458395e+00   5.291121536284495e+00   7.096664293807353e+00  5.47373550e-01   2.29641219e+00  -6.93962180e-01&#xA;C     7.061366710445481e+00   5.370766791266893e+00   1.766795669916178e+00  1.08575565e+00  -1.16270741e+00  -3.20823180e-01&#xA;C     1.783560955749675e+00   3.595632230775192e+00   1.744914310154615e+00 -1.61832200e-02  -1.34411611e+00   6.86037350e-01&#xA;C     9.147487865392240e-01   4.470236769241776e+00   8.314481673929444e-01 -1.97196630e+00  -7.49626810e-01   2.35244402e+00&#xA;C     2.602983378091007e+00   6.204381819127091e+00   9.149161188076987e-01  1.82101717e+00  -1.18240660e-01  -3.90261780e-01&#xA;C     7.917225343283958e-01   6.245417605564732e+00   2.701292578588703e+00  2.03609908e+00  -3.15842450e-01  -7.80305460e-01&#xA;C     2.658791177575270e+00   4.409512997926200e+00   2.662736565382049e+00  6.59346630e-01   2.03379123e+00  -1.16759940e+00&#xA;C     3.571911211239574e+00   3.541409467366737e+00   7.066099498225877e+00  1.32691510e-01   8.00661400e-02   1.22032686e+00&#xA;C     5.332296008047452e+00   5.301607810249293e+00   7.096567761428173e+00 -7.19261300e-01   1.61148671e+00   5.60174190e-01&#xA;C     3.599161989111380e+00   5.298915424097742e+00   1.755959945895381e+00 -1.45534256e+00   1.23807627e+00   5.26815840e-01&#xA;C     5.343400430443285e+00   3.555400122598969e+00   1.724019670536935e+00 -7.94688100e-02  -1.22034087e+00   1.68260656e+00&#xA;C     4.495938763993136e+00   4.410190288433433e+00   8.644839217613586e-01 -1.90959096e+00   6.98633670e-01  -3.14938090e-01&#xA;C     6.177803853456268e+00   6.250621184175251e+00   8.693900128852301e-01  1.68162569e+00  -6.84345710e-01   1.99048910e-01&#xA;C     4.467966552309626e+00   6.254770441542771e+00   2.656286880286244e+00 -7.57695100e-02  -1.03345062e+00  -3.54654490e-01&#xA;C     6.207880087151072e+00   4.401281444532239e+00   2.639561757040551e+00  7.66324170e-01   1.46387162e+00  -1.26064490e-01&#xA;C     7.092034222733816e+00   6.469645546521559e-02   3.611905542679158e+00 -3.69020620e-01  -1.32917779e+00  -7.38472440e-01&#xA;C     1.813401260897720e+00   1.798810015038325e+00   3.567437312210998e+00 -6.60443250e-01   1.25397500e-01  -5.29906640e-01&#xA;C     9.131195360747199e-03   1.777007203346713e+00   5.386779579481836e+00  1.49964985e+00   4.50847890e-01  -1.38667509e+00&#xA;C     1.762572342784958e+00   7.084367575685467e+00   5.258194825119071e+00 -1.44468190e-01   4.70378990e-01   2.27251762e+00&#xA;C     8.933156128238523e-01   9.138509927623180e-01   4.435922067475571e+00  2.19887730e-01   2.63211500e-01   6.47886620e-01&#xA;C     2.734726120286932e+00   2.672868982068823e+00   4.419541631642722e+00 -1.61252743e+00  -8.08281400e-02   1.02152425e+00&#xA;C     9.668444966470966e-01   2.659522421010190e+00   6.248003507545436e+00 -2.34920086e+00  -7.79319900e-02  -1.55410930e-01&#xA;C     2.621514609355990e+00   8.887661512628261e-01   6.206886542921475e+00  1.00247324e+00  -9.82742760e-01   2.23900990e-01&#xA;C     3.560229798179676e+00   1.192011389147800e-02   3.571414759003793e+00 -1.08340810e-01  -6.94958780e-01  -6.32829660e-01&#xA;C     5.303243173957251e+00   1.783785084314883e+00   3.608673698334975e+00  6.65906520e-01   1.93424360e-01  -2.00882610e-01&#xA;C     3.528356910667667e+00   1.767911834435971e+00   5.347927358304606e+00  7.39111180e-01  -2.47114860e-01  -1.04495492e+00&#xA;C     5.329030825201182e+00   7.096177437942109e+00   5.369101643268158e+00 -3.08175260e-01  -1.14381900e-02   1.84117730e-01&#xA;C     4.422761249499998e+00   8.668823746375728e-01   4.494489925294728e+00  3.83796370e-01   4.22127430e-01  -5.75045160e-01&#xA;C     6.241506267102304e+00   2.679197823980088e+00   4.509426711577681e+00 -9.90742090e-01  -1.47647882e+00  -1.25004513e+00&#xA;C     4.432864237317125e+00   2.645875244758956e+00   6.162178971863699e+00  2.14951310e-01   1.37021740e-01   2.03719183e+00&#xA;C     6.276550008692416e+00   8.743755050897671e-01   6.235059780796678e+00 -2.36728919e+00   4.92518030e-01  -1.75193300e-01&#xA;C     7.065680456712427e+00   3.515117189201012e+00   3.569630900347304e+00  2.01679955e+00   6.47574810e-01  -7.38426790e-01&#xA;C     1.744524484258135e+00   5.323755096101070e+00   3.489180474334740e+00 -2.31814270e-01  -5.78952010e-01   2.30748316e+00&#xA;C     7.087238738665912e+00   5.312598853304337e+00   5.367801939276317e+00  8.84590350e-01   6.63457880e-01  -2.04867967e+00&#xA;C     1.836661512479110e+00   3.526170004448624e+00   5.351513557516396e+00 -1.23618594e+00   5.61918680e-01  -1.49124744e+00&#xA;C     8.644019616485500e-01   4.381350493769153e+00   4.431205771235654e+00  6.54489790e-01   1.65426557e+00   5.88371370e-01&#xA;C     2.638706329462460e+00   6.199561100158887e+00   4.412298788750978e+00  5.65976410e-01   3.85331420e-01  -6.55854390e-01&#xA;C     8.855542105019791e-01   6.193752239362274e+00   6.199043180486793e+00  4.21980700e-01   3.69641240e-01   2.30177540e-01&#xA;C     2.676275196019875e+00   4.452567718556373e+00   6.202611111052449e+00  5.14470800e-01  -6.82406950e-01  -3.64222200e-02&#xA;C     3.579314420145626e+00   3.572309993748555e+00   3.522390171804665e+00  1.20915900e-02  -5.19302820e-01   8.08118950e-01&#xA;C     5.377902368061301e+00   5.343446208684958e+00   3.488438141760533e+00 -1.17684527e+00   1.56643050e-01   2.46875405e+00&#xA;C     3.545122765174973e+00   5.343271341488506e+00   5.291750347349461e+00  3.51595720e-01  -8.43737200e-01   5.14030800e-01&#xA;C     5.342069378307690e+00   3.526753748114178e+00   5.351913690625676e+00 -3.28223650e-01   2.01570343e+00  -1.31587457e+00&#xA;C     4.480059756291901e+00   4.450995690893960e+00   4.393124174154658e+00 -6.06505570e-01   2.54363480e-01   8.42964100e-01&#xA;C     6.221970331384210e+00   6.256644790419212e+00   4.501010623532506e+00  3.77290300e-02  -1.34160519e+00  -1.84268948e+00&#xA;C     4.403452996558423e+00   6.178451075335819e+00   6.250501549422556e+00  6.40125260e-01   1.35140560e+00  -1.06078985e+00&#xA;C     6.211810831607253e+00   4.482924592776214e+00   6.216467417097163e+00  8.36191500e-02  -2.43405957e+00   4.62511060e-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7093" LastEditorUserId="5" LastEditDate="2023-04-30T03:57:49.730" LastActivityDate="2023-04-30T03:57:49.730" Title="What is the best way to compute the DFT total energy and atomic forces for given atomic positions?" Tags="|density-functional-theory|quantum-espresso|python|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10797" PostTypeId="1" CreationDate="2023-04-28T02:34:54.193" Score="4" ViewCount="39" Body="&lt;p&gt;Is there any book written on protein simulation &lt;strong&gt;specifically&lt;/strong&gt; using the &lt;em&gt;&lt;strong&gt;Monte Carlo&lt;/strong&gt;&lt;/em&gt; technique (i.e., not QM or MD)?&lt;/p&gt;&#xA;&lt;p&gt;If so, can you supply me with some names of such books?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-04-28T02:37:43.430" LastActivityDate="2023-04-28T22:32:05.123" Title="Can you supply me with some book names on MC protein simulation?" Tags="|reference-request|proteins|monte-carlo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10798" PostTypeId="2" ParentId="9532" CreationDate="2023-04-28T07:07:51.593" Score="1" Body="&lt;h3&gt;Solution&lt;/h3&gt;&#xA;&lt;p&gt;On Line 21 of your code, where you initialize the elastic tensor, if the &lt;code&gt;.symmetrized&lt;/code&gt; part is removed, then you get the desired output.&lt;/p&gt;&#xA;&lt;h3&gt;Modified Code:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Structure, Lattice&#xA;from pymatgen.symmetry.analyzer import SpacegroupAnalyzer&#xA;import numpy as np&#xA;from pymatgen.analysis.elasticity.elastic import ElasticTensor&#xA;&#xA;&#xA;structure = Structure.from_spacegroup(&#xA;    &amp;quot;Fm-3m&amp;quot;, Lattice.cubic(1.0), [&amp;quot;element&amp;quot;], [[0, 0, 0]])&#xA;sga = SpacegroupAnalyzer(SpacegroupAnalyzer(structure).find_primitive())&#xA;ops_list = sga.get_symmetry_operations(cartesian=True)&#xA;ops_rotation_list = [op.rotation_matrix for op in ops_list]&#xA;&#xA;C = np.array([[271.64, 141.6 , 141.6 ,   0.  ,   0.  ,   0.  ],&#xA;              [141.6 , 271.64, 141.6 ,   0.  ,   0.  ,   0.  ],&#xA;              [141.6 , 141.6 , 271.64,   0.  ,   0.  ,   0.  ],&#xA;              [  0.  ,   0.  ,   0.  , 105.18,   0.  ,   0.  ],&#xA;              [  0.  ,   0.  ,   0.  ,   0.  , 105.18,   0.  ],&#xA;              [  0.  ,   0.  ,   0.  ,   0.  ,   0.  , 105.18]])&#xA;C_prime_sum = 0&#xA;&#xA;CC = ElasticTensor(ElasticTensor.from_voigt(C))&#xA;for idx, op in enumerate(ops_rotation_list):&#xA;         # perform the 4th order tensor rotation.&#xA;        C_prime = ElasticTensor(&#xA;            np.einsum('im,jn,mnop,ok,pl', op, op, CC, op.T, op.T), tol=1e-5)&#xA;        C_prime_sum += C_prime&#xA;C_prime = C_prime_sum / (idx + 1)&#xA;A=C_prime.voigt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Output&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(A) yields the below values which is equal to C:&#xA;&#xA;array([[271.64, 141.6 , 141.6 ,   0.  ,   0.  ,   0.  ],&#xA;       [141.6 , 271.64, 141.6 ,   0.  ,   0.  ,   0.  ],&#xA;       [141.6 , 141.6 , 271.64,   0.  ,   0.  ,   0.  ],&#xA;       [  0.  ,   0.  ,   0.  , 105.18,   0.  ,   0.  ],&#xA;       [  0.  ,   0.  ,   0.  ,   0.  , 105.18,   0.  ],&#xA;       [  0.  ,   0.  ,   0.  ,   0.  ,   0.  , 105.18]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-04-28T07:07:51.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10799" PostTypeId="2" ParentId="10788" CreationDate="2023-04-28T09:55:32.487" Score="2" Body="&lt;p&gt;I have opened a GitHub repository which you can find at &lt;a href=&quot;https://github.com/roshan2004/OPLS_AA_solvents&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/roshan2004/OPLS_AA_solvents&lt;/a&gt;, where I will try to upload OPLS/AA gromacs parameters for the available solvents in the coming days. I have uploaded the OPLS/AA gromacs parameters for 1-octanol.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-04-28T09:55:32.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10800" PostTypeId="1" CreationDate="2023-04-28T13:10:36.013" Score="5" ViewCount="270" Body="&lt;p&gt;For my calculation, I need fully relativistic LDA Norm conserving pseudopotential. I have searched for this in the existing library like PseudoDojo, SSSP, SG15, PSLibrary etc., but failed. However, I am getting fully relativistic ultrasoft LDA pseudopotentials. Does anybody know where to get fully relativistic LDA pseudos?&lt;/p&gt;&#xA;" OwnerUserId="2052" LastActivityDate="2023-05-05T13:56:33.487" Title="Norm conserving LDA fully relativistic pseudopotential in quantum espresso" Tags="|quantum-espresso|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10801" PostTypeId="2" ParentId="10796" CreationDate="2023-04-28T15:29:57.907" Score="8" Body="&lt;p&gt;If there is no special care taken to parametrize different DFT codes in the same way, it is expected that the total energies from these codes differ.&lt;/p&gt;&#xA;&lt;p&gt;Most DFT codes distinguish between energetically low lying core electrons confined to a small region around the atomic nucleus and valence electrons that are more involved in the interactions between atoms. In &lt;a href=&quot;https://en.wikipedia.org/wiki/Pseudopotential&quot; rel=&quot;noreferrer&quot;&gt;pseudopotential&lt;/a&gt; codes like Quantum Espresso or VASP the core electrons are replaced by a potential that leads to smooth wave functions of the valence electrons. This implies that for comparable total energies identical pseudopotentials have to be used. In all-electron codes, such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Linearized_augmented-plane-wave_method&quot; rel=&quot;noreferrer&quot;&gt;LAPW codes&lt;/a&gt;, besides the valence electrons also the core electrons are treated within the DFT scheme. But here it is also important for comparable total energies to have identical core-valence separations between the codes, because the degree of relativistic description between core electrons and valence electrons typically differs. Of course, the energy also depends on the choice of the approximation to the exchange-correlation functional.&lt;/p&gt;&#xA;&lt;p&gt;While the total energy is sensitive to all these different aspects, energy differences are not, at least not in a significant way.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2023-04-28T15:29:57.907" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10802" PostTypeId="1" CreationDate="2023-04-28T21:09:18.180" Score="7" ViewCount="248" Body="&lt;p&gt;I am trying to perform a CISD calculation in PySCF using the starting orbitals from an old DFT result.&lt;/p&gt;&#xA;&lt;p&gt;The DFT result was saved on a chkfile, &lt;code&gt;mf.hdf5&lt;/code&gt;. The code that generate this file is the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf.gto, pyscf.dft&#xA;&#xA;bz_geom=&amp;quot;&amp;quot;&amp;quot;\&#xA;C    -1.21225309     0.69989455     0.00000000;&#xA;C    -1.21225309    -0.69989455     0.00000000;&#xA;C    -0.00000000    -1.39978909     0.00000000;&#xA;C     1.21225309    -0.69989455     0.00000000;&#xA;C     1.21225309     0.69989455     0.00000000;&#xA;C     0.00000000     1.39978909     0.00000000;&#xA;H    -2.15365863     1.24341536     0.00000000;&#xA;H    -2.15365863    -1.24341536     0.00000000;&#xA;H    -0.00000000    -2.48683071     0.00000000;&#xA;H     2.15365863    -1.24341536     0.00000000;&#xA;H     2.15365863     1.24341536     0.00000000;&#xA;H     0.00000000     2.48683071     0.00000000&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;mol = pyscf.gto.M(atom=bz_geom, basis='bfd_vtz', ecp='bfd')&#xA;mf  = pyscf.dft.RKS(mol)&#xA;mf.xc='b3lyp'&#xA;mf.chkfile=&amp;quot;mf.hdf5&amp;quot;&#xA;mf.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It was very difficult to me finding documentation about how to load information from a chkfile. I came across with the function &lt;code&gt;pyscf.scf.chkfile.load_scf&lt;/code&gt;. However, when I try to use it to perform the CI calculation, I get an error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf.gto, pyscf.dft, pyscf.ci, pyscf.scf&#xA;&#xA;mf = pyscf.scf.chkfile.load_scf('mf.hdf5')&#xA;&#xA;# CISD calculation&#xA;cisolver = pyscf.ci.CISD(mf)&#xA;cisolver.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The full error message is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;AssertionError                            Traceback (most recent call last)&#xA;/tmp/ipykernel_20980/4228492657.py in &amp;lt;module&amp;gt;&#xA;     22 &#xA;     23 # CISD calculation&#xA;---&amp;gt; 24 cisolver = pyscf.ci.CISD(mf)&#xA;     25 cisolver.kernel()&#xA;     26 &#xA;&#xA;~/.local/lib/python3.10/site-packages/pyscf/ci/__init__.py in CISD(mf, frozen, mo_coeff, mo_occ)&#xA;     31         return UCISD(mf, frozen, mo_coeff, mo_occ)&#xA;     32     else:&#xA;---&amp;gt; 33         return RCISD(mf, frozen, mo_coeff, mo_occ)&#xA;     34 CISD.__doc__ = cisd.CISD.__doc__&#xA;     35 &#xA;&#xA;~/.local/lib/python3.10/site-packages/pyscf/ci/__init__.py in RCISD(mf, frozen, mo_coeff, mo_occ)&#xA;     38 &#xA;     39     if isinstance(mf, newton_ah._CIAH_SOSCF) or not isinstance(mf, scf.hf.RHF):&#xA;---&amp;gt; 40         mf = scf.addons.convert_to_rhf(mf)&#xA;     41 &#xA;     42     if getattr(mf, 'with_df', None):&#xA;&#xA;~/.local/lib/python3.10/site-packages/pyscf/scf/addons.py in convert_to_rhf(mf, out, remove_df)&#xA;    692     from pyscf import scf&#xA;    693     from pyscf import dft&#xA;--&amp;gt; 694     assert (isinstance(mf, hf.SCF))&#xA;    695 &#xA;    696     logger.debug(mf, 'Converting %s to RHF', mf.__class__)&#xA;&#xA;AssertionError: &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It seems to me that the error is because the mf object is from a DFT calculation and not from a HF calculation. I get a similar error before (if I try to start the CI calculation directly from the DFT &lt;code&gt;mf&lt;/code&gt; object, instead of with the chkfile). In that case, I got a helpful error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RuntimeError: CISD Warning: The first argument mf is a DFT object. CISD calculation should be initialized with HF object.&#xA;DFT object can be converted to HF object with the code below:&#xA;    mf_hf = scf.RHF(mol)&#xA;    if getattr(mf_dft, &amp;quot;with_x2c&amp;quot;, False):&#xA;        mf_hf = mf_hf.x2c()&#xA;    mf_hf.__dict__.update(mf_dft.__dict__)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I should try to do something similar with the &lt;code&gt;mf&lt;/code&gt; object obtained from &lt;code&gt;pyscf.scf.chkfile.load_scf&lt;/code&gt;. The problem is I do not have the &lt;code&gt;mol&lt;/code&gt; object in that case.&lt;/p&gt;&#xA;&lt;p&gt;I probably am doing something wrong. What is the correct procedure to start a CI calculation from a previous chkfile from a DFT or HF calculation?&lt;/p&gt;&#xA;" OwnerUserId="5367" LastEditorUserId="5367" LastEditDate="2023-04-30T21:13:03.857" LastActivityDate="2023-05-01T16:20:02.147" Title="Start a CI calculation from HF/DFT chkfile in PySCF" Tags="|density-functional-theory|python|pyscf|configuration-interaction|" AnswerCount="1" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="10803" PostTypeId="1" AcceptedAnswerId="10823" CreationDate="2023-04-28T21:59:13.783" Score="7" ViewCount="712" Body="&lt;p&gt;How do you create pseudo-binary phase diagrams using Thermo-Calc? For instance how would I recreate the pseudo-binary phase diagrams shown below. I would prefer a method of doing this in the GUI (graphical mode), but if that's not possible I'll settle for a solution using the console mode.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ERSXq.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ERSXq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1410" LastActivityDate="2023-08-21T21:25:30.937" Title="How to create pseudo-binary phase diagrams using Thermo-Calc GUI?" Tags="|calphad|thermo-calc|phase-diagram|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10804" PostTypeId="2" ParentId="10797" CreationDate="2023-04-28T22:32:05.123" Score="2" Body="&lt;h2&gt;Monte Carlo Simulation Method for Protein Native Structure Prediction (&lt;a href=&quot;https://www.lap-publishing.com/catalog/details/store/tr/book/978-3-330-03036-7/monte-carlo-simulation-method-for-protein-native-structure-prediction?search=Monte%20Carlo%20Simulation%20Method%20for%20Protein&quot; rel=&quot;nofollow noreferrer&quot;&gt;Link&lt;/a&gt;)&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Proteins are polymers of Amino Acid which are constructed after&#xA;translation of genetic code in DNA of organisms and have functionality&#xA;that depends on their Native Structure. Experimental methods for&#xA;protein native structure determination are complicated, expensive and&#xA;time-consuming. Consequently, Computational Methods (CM), including&#xA;Monte Carlo (MC), aim to circumvent these challenges. However, the MC&#xA;is complex and inconsistent in native structure Prediction. This study&#xA;was designed to develop a Move-Biased MC simulation algorithm that may&#xA;simplify the complexity of existing MC and makes it consistent for&#xA;native structure prediction. Protein was described as a coarse-grained&#xA;structure and folding as Self-Avoiding Walks (SAW) on square lattices.&#xA;Relative Probability Parameters were introduced to determine natural&#xA;probabilities of protein conformations from SAW and to simulate the&#xA;desired sequence length from an optimal combination. Thereafter, a&#xA;graphical algorithm was developed to group the SAW steps into&#xA;hydrophobic and polar AA units according to the Hydrophobic-Polar (HP)&#xA;model.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/dku8n.jpg&quot; height=&quot;400&quot; &gt;&#xA; &#xA;" OwnerUserId="24" LastActivityDate="2023-04-28T22:32:05.123" CommentCount="3" CommunityOwnedDate="2023-04-29T01:55:50.127" ContentLicense="CC BY-SA 4.0" />
  <row Id="10805" PostTypeId="2" ParentId="10803" CreationDate="2023-04-28T22:47:32.367" Score="6" Body="&lt;h1&gt;Alloy Theoretic Automated Toolkit (ATAT)&lt;/h1&gt;&#xA;&lt;p&gt;ATAT is a generic name that refers to a collection of alloy theory tools developped by &lt;a href=&quot;http://alum.mit.edu/www/avdw&quot; rel=&quot;noreferrer&quot;&gt;Axel van de Walle&lt;/a&gt;, in collaboration with various &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node3.html&quot; rel=&quot;noreferrer&quot;&gt;research groups&lt;/a&gt; and with various sources of financial support.&lt;/p&gt;&#xA;&lt;h3&gt;sqs2tdb module&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Software tool for high-throughput CALPHAD (CALculation of PHAse Diagram) from first-principles,&lt;/li&gt;&#xA;&lt;li&gt;A. Walle, R. Sun, Q.-J. Hong, S. Kadkhodaei, &lt;em&gt;Software tools for high-throughput CALPHAD from first-principles data&lt;/em&gt;. Calphad, &lt;strong&gt;58&lt;/strong&gt;, 70-81, 2017. DOI: &lt;a href=&quot;https://doi.org/10.1016/j.calphad.2017.05.005&quot; rel=&quot;noreferrer&quot;&gt;10.1016/j.calphad.2017.05.005&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Download: &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-04-28T22:47:32.367" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10806" PostTypeId="1" AcceptedAnswerId="10816" CreationDate="2023-04-29T19:25:50.950" Score="2" ViewCount="152" Body="&lt;p&gt;&lt;strong&gt;I am new to using PyProcar and am getting the following error when trying to plot band-structure using it&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;p&gt;Here is my input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pyprocar.bandsplot('PROCAR-repaired',outcar='OUTCAR',mode='plain',kpointsfile='KPOINTS')&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where my KPOINTS file is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;KPOINTS generated by PyProcar&#xA;40 ! Grid points&#xA;Line_mode&#xA;reciprocal&#xA;0.000000 0.000000 0.000000 ! GAMMA&#xA;0.500000 0.000000 0.000000 ! M&#xA;&#xA;0.500000 0.000000 0.000000 ! M&#xA;0.333333 0.333333 0.000000 ! K&#xA;&#xA;0.333333 0.333333 0.000000 ! K&#xA;0.000000 0.000000 0.000000 ! GAMMA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My PROCAR-repaired file is very large (I put only 3 bands of 40 bands):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PROCAR lm decomposed&#xA;# of k-points:   18         # of bands:   40         # of ions:   10&#xA;&#xA; k-point     1 :    0.00000000 0.00000000 0.00000000     weight = 0.01000000&#xA;&#xA;band     1 # energy  -14.31028158 # occ.  1.00000000&#xA; &#xA;ion      s     py     pz     px    dxy    dyz    dz2    dxz  x2-y2    tot&#xA;    1  0.014  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.014&#xA;    2  0.014  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.014&#xA;    3  0.080  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.080&#xA;    4  0.080  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.080&#xA;    5  0.072  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.073&#xA;    6  0.072  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.073&#xA;    7  0.072  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.073&#xA;    8  0.072  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.073&#xA;    9  0.072  0.000  0.001  0.001  0.000  0.000  0.000  0.000  0.000  0.073&#xA;   10  0.072  0.000  0.001  0.001  0.000  0.000  0.000  0.000  0.000  0.073&#xA;tot    0.619  0.002  0.005  0.002  0.000  0.000  0.000  0.000  0.000  0.629&#xA; &#xA;band     2 # energy  -13.34389563 # occ.  1.00000000&#xA; &#xA;ion      s     py     pz     px    dxy    dyz    dz2    dxz  x2-y2    tot&#xA;    1  0.000  0.000  0.007  0.000  0.000  0.000  0.000  0.000  0.000  0.007&#xA;    2  0.000  0.000  0.007  0.000  0.000  0.000  0.000  0.000  0.000  0.007&#xA;    3  0.044  0.000  0.002  0.000  0.000  0.000  0.001  0.000  0.000  0.047&#xA;    4  0.044  0.000  0.002  0.000  0.000  0.000  0.001  0.000  0.000  0.047&#xA;    5  0.092  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.093&#xA;    6  0.092  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.093&#xA;    7  0.092  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.093&#xA;    8  0.092  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.093&#xA;    9  0.092  0.000  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.093&#xA;   10  0.092  0.000  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.093&#xA;tot    0.642  0.002  0.018  0.002  0.000  0.000  0.002  0.000  0.000  0.665&#xA; &#xA;band     3 # energy  -12.27910796 # occ.  1.00000000&#xA; &#xA;ion      s     py     pz     px    dxy    dyz    dz2    dxz  x2-y2    tot&#xA;    1  0.000  0.006  0.000  0.002  0.000  0.000  0.000  0.001  0.001  0.011&#xA;    2  0.000  0.006  0.000  0.002  0.000  0.000  0.000  0.001  0.001  0.011&#xA;    3  0.000  0.002  0.000  0.005  0.000  0.000  0.000  0.000  0.001  0.008&#xA;    4  0.000  0.002  0.000  0.005  0.000  0.000  0.000  0.000  0.001  0.008&#xA;    5  0.170  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.171&#xA;    6  0.170  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.171&#xA;    7  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000&#xA;    8  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000&#xA;    9  0.170  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.170&#xA;   10  0.170  0.000  0.001  0.000  0.000  0.000  0.000  0.000  0.000  0.170&#xA;tot    0.679  0.015  0.002  0.014  0.002  0.001  0.000  0.002  0.004  0.719&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and I get the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Script initiated...&#xA;PROCAR repaired. Run with repair=False next time.&#xA;code           :  vasp&#xA;input file     :  PROCAR-repaired&#xA;mode           :  plain&#xA;spin comp.     :  0&#xA;atoms list     :  [-1]&#xA;orbs. list     :  [-1]&#xA;fermi energy   :  None&#xA;energy range   :  [-2, 2]&#xA;colormap       :  jet&#xA;markersize     :  0.02&#xA;permissive     :  False&#xA;vmax           :  None&#xA;vmin           :  None&#xA;grid enabled   :  True&#xA;human          :  False&#xA;savefig        :  None&#xA;title          :  None&#xA;outcar         :  OUTCAR&#xA;k-grid         :  reduced&#xA;knames         :  ['&lt;span class=&quot;math-container&quot;&gt;$\\Gamma$&lt;/span&gt;', '&lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt;', '&lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;', '&lt;span class=&quot;math-container&quot;&gt;$\\Gamma$&lt;/span&gt;']&#xA;kticks         :  [0, 39, 79, 119]&#xA;Fermi energy   :  -1.6624 eV (from OUTCAR)&#xA;spd shape      :  (18, 80, 2, 11, 11) [kpoints, bands, spins, atoms+1, orbitals+2]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;with this error&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/home/dell/anaconda3/lib/python3.9/site-packages/pyprocar/scriptBandsplot.py&amp;quot;, line 417, in bandsplot&#xA;    fig, ax1 = plot.plotBands(&#xA;  File &amp;quot;/home/dell/anaconda3/lib/python3.9/site-packages/pyprocar/procarplot/procarplot.py&amp;quot;, line 103, in plotBands&#xA;    ticks = [xaxis[x] for x in ticks]&#xA;  File &amp;quot;/home/dell/anaconda3/lib/python3.9/site-packages/pyprocar/procarplot/procarplot.py&amp;quot;, line 103, in &amp;lt;listcomp&amp;gt;&#xA;    ticks = [xaxis[x] for x in ticks]&#xA;IndexError: index 39 is out of bounds for axis 0 with size 18&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What could be causing this?&lt;/p&gt;&#xA;" OwnerUserId="7107" LastEditorUserId="7107" LastEditDate="2023-04-30T14:27:21.737" LastActivityDate="2023-05-01T09:05:43.017" Title="PyProcar bands plot error" Tags="|density-functional-theory|vasp|band-structure|k-points|pyprocar|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10807" PostTypeId="1" AcceptedAnswerId="10808" CreationDate="2023-04-29T21:20:42.707" Score="8" ViewCount="317" Body="&lt;p&gt;I am looking for relevant books to study the modeling and Monte Carlo simulation of protein chains.&lt;/p&gt;&#xA;&lt;p&gt;I see that books related to Statistical Physics, Statistical Mechanics, and Molecular Modeling have many overlapping areas of discussion that are related to protein modeling and simulation.&lt;/p&gt;&#xA;&lt;p&gt;What is the basic difference between Statistical Physics, Statistical Mechanics, and Molecular Modeling in connection with protein modeling &amp;amp; simulation?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-04-30T17:08:52.237" LastActivityDate="2023-04-30T17:08:52.237" Title="Difference between Statistical Physics, Statistical Mechanics, and Molecular Modeling?" Tags="|molecular-modeling|proteins|statistical-thermodynamics|terminology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10808" PostTypeId="2" ParentId="10807" CreationDate="2023-04-30T00:42:39.137" Score="8" Body="&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Statistical_mechanics&quot; rel=&quot;noreferrer&quot;&gt;Statistical mechanics&lt;/a&gt;:&lt;/strong&gt; is a mathematical framework that applies statistical methods and probability theory to large assemblies of microscopic entities [this is the first line in the linked article].&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Statistical_physics&quot; rel=&quot;noreferrer&quot;&gt;Statistical physics&lt;/a&gt;:&lt;/strong&gt; is a less-commonly used term, and can cover more broad areas of physics (e.g. applying statistical methods and probability theory to more than just the &amp;quot;mechanics&amp;quot; of large assemblies of microscopic entities). Linguistically, &amp;quot;statistical mechanics&amp;quot; would be a subset of statistical physics.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_modelling&quot; rel=&quot;noreferrer&quot;&gt;Molecular modeling&lt;/a&gt;:&lt;/strong&gt; may or may not involve statistical mechanics. If you model just one molecule and never consider statistics in any way, it's still &amp;quot;molecular modeling&amp;quot; but not statistical (e.g. imagine just calculating the ground state energy of the H2 molecule, rather than calculating the distribution of velocities among billions of molecules in an ensemble).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-04-30T00:42:39.137" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10809" PostTypeId="1" CreationDate="2023-04-30T02:44:28.447" Score="7" ViewCount="186" Body="&lt;p&gt;I am trying to calculate 2D elastic constants of a hexagonal boron nitride (hBN) monolayer.&#xA;The unit cell is the primitive cell and the Cartesian coordinate is set as follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/JV9gg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/JV9gg.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The elastic constants &lt;span class=&quot;math-container&quot;&gt;$C_{j} \:\: (j=x, y)$&lt;/span&gt; have relations with the corresponding strain,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \frac{(E-E_{0})}{A_{0}} = \frac{1}{2}C_{j}\varepsilon_{j}^{2}, $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{0}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$A_{0}$&lt;/span&gt; is the energy and area at the equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;To find &lt;span class=&quot;math-container&quot;&gt;$C_{j}$&lt;/span&gt;, I made four deformed structures of the strain &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{j} = \Delta a_{j}/a_{0,j} = \pm 0.005,\; \pm 0.01$&lt;/span&gt;. The schematic diagrams for the deformation is the following.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BoJ2A.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BoJ2A.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;POSCARs of deformed structures have the same fractional coordinates written in the original POSCAR of the optimized geometry, but the lattice vectors are changed according to the above strain. I conducted single-point calculations with deformed structures using VASP and fitted the above equation with a quadratic function.&lt;/p&gt;&#xA;&lt;p&gt;However, the problem is that &lt;span class=&quot;math-container&quot;&gt;$C_{x}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_{y}$&lt;/span&gt; is not the same (I obtained &lt;span class=&quot;math-container&quot;&gt;$C_{x}=326\; \mathrm{Nm^{-1}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_{y}=300\; \mathrm{Nm^{-1}}$&lt;/span&gt;). Those two values are to be the same due to the hexagonal symmetry [Mouhat, F.; Coudert, F.-X. Necessary and Sufficient Elastic Stability Conditions in Various Crystal Systems. &lt;em&gt;Phys. Rev. B&lt;/em&gt; &lt;strong&gt;2014&lt;/strong&gt;, 90, 224104.].&lt;/p&gt;&#xA;&lt;p&gt;I suspect the deformed structures I made are wrong somehow, but I am not sure how to define the deformation correctly.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I added more data related to the fitting process.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;A. The POSCAR lattice vector matrices in the x-direction&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = 0$&lt;/span&gt; (the optimized structure):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.5122293853799835   -0.0000000000000046   -0.0000000000000000&#xA;-1.2561146926399998    2.1756544679020906    0.0000000000000000&#xA; 0.0000000000000000   -0.0000000000000000   15.0000000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = 0.005$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.52479053    -0.00000000    -0.00000000&#xA;-1.25611469     2.17565447     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = 0.01$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.53735168    -0.00000000    -0.00000000&#xA;-1.25611469     2.17565447     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = -0.005$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.49966824    -0.00000000     0.00000000&#xA;-1.25611469     2.17565447     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = -0.01$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.48710709    -0.00000000     0.00000000&#xA;-1.25611469     2.17565447     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;B. The POSCAR lattice vector matrices in the y-direction&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = 0.005$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.51222939    -0.00000000    -0.00000000&#xA;-1.25611469     2.18653274     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = 0.01$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.51222939    -0.00000000    -0.00000000&#xA;-1.25611469     2.19741101     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = -0.005$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.51222939    -0.00000000    -0.00000000&#xA;-1.25611469     2.16477620     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\varepsilon = -0.01$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 2.51222939    -0.00000000    -0.00000000&#xA;-1.25611469     2.15389792     0.00000000&#xA; 0.00000000    -0.00000000    15.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;C. The quadratic fittings&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The x axis is dimension-less and the unit of y axis is &lt;span class=&quot;math-container&quot;&gt;$\mathrm{eV}/\text{Å}^{2}$&lt;/span&gt;. Thus, the elastic constants in &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Nm}^{-1}$&lt;/span&gt; is given by factoring &lt;span class=&quot;math-container&quot;&gt;$\sim 16 \times 2 = 32$&lt;/span&gt; to the 2nd order coefficient.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/OiPSY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/OiPSY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1789" LastEditorUserId="1789" LastEditDate="2023-04-30T18:59:29.137" LastActivityDate="2023-07-06T19:05:55.777" Title="How to calculate 2D elastic constants of boron nitride monolayers from uniaxial strains?" Tags="|vasp|elasticity|stress-strain|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10810" PostTypeId="1" AcceptedAnswerId="10811" CreationDate="2023-04-30T12:42:58.617" Score="5" ViewCount="220" Body="&lt;p&gt;I want to get the phonon density of states for a monolayer MoS2. For this, I need phonon dispersion curves, and to choose a path where to compute phonons.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://vaspkit.com/&quot; rel=&quot;noreferrer&quot;&gt;VASPKIT&lt;/a&gt; recommends Γ-M-K-Γ&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;noreferrer&quot;&gt;SeeK-path&lt;/a&gt; recommends Γ—M—K—Γ—A—L—H—A|L—M|H—K|Γ—M'—K'—Γ—A'—L'—H'—A'|L'—M'|H'—K'&lt;/p&gt;&#xA;&lt;p&gt;Why such different paths? Which one to choose to calculate the phonon density of states?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-04-30T14:20:45.857" Title="VASPKIT and SeeK-path recommend different paths. Which one to choose?" Tags="|phonons|k-points|2d-lattice|phonon-density-of-state|q-points|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10811" PostTypeId="2" ParentId="10810" CreationDate="2023-04-30T14:20:45.857" Score="6" Body="&lt;p&gt;If you check out this &lt;a href=&quot;https://www.researchgate.net/figure/High-symmetry-path-in-the-hexagonal-Brillouin-zone-chosen-according-to-the-notation-of_fig1_326646275&quot; rel=&quot;noreferrer&quot;&gt;picture&lt;/a&gt; of the Brillouin zone of a hexagonal cell, you can see points like L, A and H are defined for a 3D Brillouin zone. This is because the k-path finding algorithms are generally made to work for general 3D cells, which is what SeeK-path is giving you. I'm guessing that for VASPKIT, there would be a point at which you indicate that you are simulating a monolayer, so it only gives you the high-symmetry k-points for a 2D Brillouin zone. So in short, &lt;strong&gt;the VASPKIT one is the one you should be using because there is no periodicity in the z-direction for a free-standing monolayer&lt;/strong&gt; (even though, from a simulation standpoint, the DFT codes we use mostly impose periodic boundary conditions in all directions).&lt;/p&gt;&#xA;&lt;p&gt;As a little side note that might be useful to people with similar concerns and are looking for alternatives besides VASPKIT, I like to use &lt;a href=&quot;https://pymatgen.org/index.html&quot; rel=&quot;noreferrer&quot;&gt;Pymatgen&lt;/a&gt; to get high-symmetry k-points, but it runs into the same problems for slab type structures. This &lt;a href=&quot;https://github.com/henniggroup/MPInterfaces&quot; rel=&quot;noreferrer&quot;&gt;MPInterfaces&lt;/a&gt; package has a nice function in this &lt;a href=&quot;https://github.com/henniggroup/MPInterfaces/blob/master/mpinterfaces/utils.py&quot; rel=&quot;noreferrer&quot;&gt;file&lt;/a&gt; of their GitHub repo called &lt;code&gt;remove_z_kpoints()&lt;/code&gt; that can be used to remove the high-symmetry k-points with a z-dimension so you're only left those that would be found in a 2D Brillouin zone.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-04-30T14:20:45.857" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10812" PostTypeId="1" CreationDate="2023-04-30T14:41:49.880" Score="9" ViewCount="1091" Body="&lt;p&gt;I posted a question previously about why I got different total energy values when I ran a DFT calculation with quantum espresso compared to VASP (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10796/what-is-the-best-way-to-compute-the-dft-total-energy-and-atomic-forces-for-given&quot;&gt;link to the question&lt;/a&gt;).&#xA;From what I understood from the responses is that typically absolute or total energy can be sensitive to the choice of algorithm or software.&#xA;And the suggestion is to use relative or cohesive energy.&#xA;However, in an extxyz file that often is used in interatomic potential training, the second line looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Lattice=&amp;quot;7.10842262195238 0 0 0 7.10842262195238 0 0 0 7.10842262195238 &amp;quot; PBC=&amp;quot;1 1 1&amp;quot; Properties=species:S:1:pos:R:3:force:R:3 Energy=&amp;quot;-515.36256422&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The energy listed here is the total energy of the configuration, is it not? If this is the case, then how do I decide on which algorithm/software to use if the total energies are different across algorithms/software?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Update:&lt;/strong&gt;&#xA;I realized that it would be more helpful if I specify my end goal.&#xA;So, I am new to DFT calculation and I want to verify my code to generate DFT energy and forces.&#xA;To do that, I took a diamond configuration from the paper by Wen et al. (&lt;a href=&quot;https://www.nature.com/articles/s41524-020-00390-8&quot; rel=&quot;noreferrer&quot;&gt;link to the paper&lt;/a&gt;).&#xA;Here are the settings they used in their DFT calculation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Use VASP with PBE exchange-correlation function&lt;/li&gt;&#xA;&lt;li&gt;Apply many-body dispersion to capture van der Waals effects&lt;/li&gt;&#xA;&lt;li&gt;Set 500 eV energy cutoff&lt;/li&gt;&#xA;&lt;li&gt;Set &lt;span class=&quot;math-container&quot;&gt;$4 \times 4 \times 4$&lt;/span&gt; k-points grid&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Unfortunately, I don't have access to VASP and currently, I was using quantum espresso through a wrapper in ASE.&#xA;See the code below.&#xA;And this is where I got a different energy value from my calculation and the reference data from the paper.&#xA;I thought I have applied all those settings in my script, but I still got a different energy value.&lt;/p&gt;&#xA;&lt;h3&gt;Code&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;from ase.calculators.espresso import Espresso, EspressoProfile&#xA;from ase.units import create_units&#xA;&#xA;units = create_units(&amp;quot;2018&amp;quot;)  # For unit conversion&#xA;&#xA;# Read the xyz file&#xA;orig_config = Path(&amp;quot;inst_cubic_diamond_temp300_strain0.0_step0.xyz&amp;quot;)&#xA;atoms = read(orig_config, format=&amp;quot;extxyz&amp;quot;)&#xA;&#xA;# Calculator&#xA;# ----------&#xA;&#xA;# Set up executable&#xA;directory = &amp;quot;test&amp;quot;&#xA;pw_loc = &amp;quot;pw.x&amp;quot;&#xA;# Parallelization variable&#xA;nprocs = 32&#xA;&#xA;# Set how to run pw.x&#xA;profile = EspressoProfile(argv=[&amp;quot;mpirun&amp;quot;, &amp;quot;-np&amp;quot;, str(nprocs), pw_loc])&#xA;&#xA;# Set up input parameters&#xA;ecut = 500 / units[&amp;quot;Ry&amp;quot;]  # Energy cutoff in Ry&#xA;ecutrho = 6 * ecut&#xA;input_data = {&#xA;    &amp;quot;control&amp;quot;: {&#xA;        &amp;quot;prefix&amp;quot;: directory,&#xA;        &amp;quot;pseudo_dir&amp;quot;: &amp;quot;/data/yonatan/myproject/scripts/indicator_config/EAM/DFT/pseudo&amp;quot;,&#xA;        &amp;quot;calculation&amp;quot;: &amp;quot;scf&amp;quot;,&#xA;    },&#xA;    &amp;quot;system&amp;quot;: {&amp;quot;ibrav&amp;quot;: 0, &amp;quot;ecutwfc&amp;quot;: ecut, &amp;quot;ecutrho&amp;quot;: ecutrho, &amp;quot;vdw_corr&amp;quot;: &amp;quot;mbd_vdw&amp;quot;},&#xA;    # &amp;quot;electrons&amp;quot;: {&amp;quot;conv_thr&amp;quot;: 1.0e-9, &amp;quot;electron_maxstep&amp;quot;: 100, &amp;quot;mixing_beta&amp;quot;: 0.7},&#xA;}&#xA;&#xA;# Pseudo-potentials&#xA;pseudo = {&amp;quot;C&amp;quot;: &amp;quot;C.pbe-n-kjpaw_psl.1.0.0.UPF&amp;quot;}&#xA;&#xA;# Create calculator&#xA;calc = Espresso(&#xA;    profile=profile,&#xA;    pseudopotentials=pseudo,&#xA;    directory=directory,&#xA;    tstress=True,&#xA;    tprnfor=True,&#xA;    input_data=input_data,&#xA;    kpts=(4, 4, 4),&#xA;    koffset=True,&#xA;)&#xA;atoms.calc = calc&#xA;&#xA;# Compute energy and forces&#xA;forces = atoms.get_forces()&#xA;energy = atoms.get_potential_energy()&#xA;print(&amp;quot;Energy:&amp;quot;, energy)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;EXTXYZ file&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;64&#xA;Lattice=&amp;quot;7.10842262195238 0 0 0 7.10842262195238 0 0 0 7.10842262195238 &amp;quot; PBC=&amp;quot;1 1 1&amp;quot; Properties=species:S:1:pos:R:3:force:R:3 Energy=&amp;quot;-512.86187833&amp;quot;&#xA;C     2.515720524176340e-02   3.867550579089600e-03   7.089434672581682e+00 -5.37951000e-01  -9.43653100e-01   8.96908860e-01&#xA;C     1.776933986593727e+00   1.732049273644261e+00   2.572083207130320e-02  4.26181090e-01   1.51736004e+00   3.81343080e-01&#xA;C     7.082577532701300e+00   1.802144789342045e+00   1.769809143517475e+00  1.13683654e+00  -6.10598840e-01   7.06415680e-01&#xA;C     1.730755114222064e+00   7.103866760858615e+00   1.834766904598202e+00  5.28662040e-01   3.17688010e-01  -1.12025143e+00&#xA;C     8.721281061942280e-01   8.735364979679285e-01   8.966439895472150e-01  1.05603720e-01   2.62228850e-01   5.75211080e-01&#xA;C     2.696528798085684e+00   2.679314544279508e+00   9.295221501861438e-01 -7.81283670e-01  -5.78397410e-01  -1.85532276e+00&#xA;C     9.346490289165925e-01   2.672186644581529e+00   2.654060735574339e+00 -2.03034942e+00   1.70433750e-01  -3.59527500e-02&#xA;C     2.678101420875179e+00   9.199713446381380e-01   2.689016972481999e+00 -6.26726520e-01  -1.33007226e+00   1.56036970e-01&#xA;C     3.511187368839771e+00   7.101188022878494e+00   7.107915220793385e+00  9.31579400e-02  -4.02755650e-01   8.05187710e-01&#xA;C     5.312681026669824e+00   1.769173081861437e+00   7.067010726921535e+00  6.70675890e-01  -1.36012410e-01   1.35187542e+00&#xA;C     3.546168769563506e+00   1.802083870160192e+00   1.830411431890475e+00  8.04017590e-01  -7.92153530e-01  -1.76726650e+00&#xA;C     5.379223112984097e+00   3.912248340524160e-02   1.782229477108722e+00 -2.47505791e+00  -2.16700570e-01  -5.76459000e-03&#xA;C     4.425585354722698e+00   8.827204378245163e-01   8.970133431865501e-01  2.16665110e-01   8.11297010e-01  -2.73793900e-01&#xA;C     6.213865521165564e+00   2.672265050483028e+00   8.666035823024164e-01  2.11940450e-01  -9.71874700e-02  -3.56909090e-01&#xA;C     4.454692212824812e+00   2.667208331883838e+00   2.664322099047440e+00  1.78292390e-01   3.44728770e-01   2.32568650e-01&#xA;C     6.202805881832237e+00   9.258737522764287e-01   2.730940032231068e+00  4.33003680e-01   5.79964000e-02  -1.57874570e+00&#xA;C     3.423771754923000e-03   3.576000047014824e+00   7.096407537582318e+00  7.40474130e-01  -4.69554600e-01   5.82278100e-02&#xA;C     1.773121668458395e+00   5.291121536284495e+00   7.096664293807353e+00  5.47373550e-01   2.29641219e+00  -6.93962180e-01&#xA;C     7.061366710445481e+00   5.370766791266893e+00   1.766795669916178e+00  1.08575565e+00  -1.16270741e+00  -3.20823180e-01&#xA;C     1.783560955749675e+00   3.595632230775192e+00   1.744914310154615e+00 -1.61832200e-02  -1.34411611e+00   6.86037350e-01&#xA;C     9.147487865392240e-01   4.470236769241776e+00   8.314481673929444e-01 -1.97196630e+00  -7.49626810e-01   2.35244402e+00&#xA;C     2.602983378091007e+00   6.204381819127091e+00   9.149161188076987e-01  1.82101717e+00  -1.18240660e-01  -3.90261780e-01&#xA;C     7.917225343283958e-01   6.245417605564732e+00   2.701292578588703e+00  2.03609908e+00  -3.15842450e-01  -7.80305460e-01&#xA;C     2.658791177575270e+00   4.409512997926200e+00   2.662736565382049e+00  6.59346630e-01   2.03379123e+00  -1.16759940e+00&#xA;C     3.571911211239574e+00   3.541409467366737e+00   7.066099498225877e+00  1.32691510e-01   8.00661400e-02   1.22032686e+00&#xA;C     5.332296008047452e+00   5.301607810249293e+00   7.096567761428173e+00 -7.19261300e-01   1.61148671e+00   5.60174190e-01&#xA;C     3.599161989111380e+00   5.298915424097742e+00   1.755959945895381e+00 -1.45534256e+00   1.23807627e+00   5.26815840e-01&#xA;C     5.343400430443285e+00   3.555400122598969e+00   1.724019670536935e+00 -7.94688100e-02  -1.22034087e+00   1.68260656e+00&#xA;C     4.495938763993136e+00   4.410190288433433e+00   8.644839217613586e-01 -1.90959096e+00   6.98633670e-01  -3.14938090e-01&#xA;C     6.177803853456268e+00   6.250621184175251e+00   8.693900128852301e-01  1.68162569e+00  -6.84345710e-01   1.99048910e-01&#xA;C     4.467966552309626e+00   6.254770441542771e+00   2.656286880286244e+00 -7.57695100e-02  -1.03345062e+00  -3.54654490e-01&#xA;C     6.207880087151072e+00   4.401281444532239e+00   2.639561757040551e+00  7.66324170e-01   1.46387162e+00  -1.26064490e-01&#xA;C     7.092034222733816e+00   6.469645546521559e-02   3.611905542679158e+00 -3.69020620e-01  -1.32917779e+00  -7.38472440e-01&#xA;C     1.813401260897720e+00   1.798810015038325e+00   3.567437312210998e+00 -6.60443250e-01   1.25397500e-01  -5.29906640e-01&#xA;C     9.131195360747199e-03   1.777007203346713e+00   5.386779579481836e+00  1.49964985e+00   4.50847890e-01  -1.38667509e+00&#xA;C     1.762572342784958e+00   7.084367575685467e+00   5.258194825119071e+00 -1.44468190e-01   4.70378990e-01   2.27251762e+00&#xA;C     8.933156128238523e-01   9.138509927623180e-01   4.435922067475571e+00  2.19887730e-01   2.63211500e-01   6.47886620e-01&#xA;C     2.734726120286932e+00   2.672868982068823e+00   4.419541631642722e+00 -1.61252743e+00  -8.08281400e-02   1.02152425e+00&#xA;C     9.668444966470966e-01   2.659522421010190e+00   6.248003507545436e+00 -2.34920086e+00  -7.79319900e-02  -1.55410930e-01&#xA;C     2.621514609355990e+00   8.887661512628261e-01   6.206886542921475e+00  1.00247324e+00  -9.82742760e-01   2.23900990e-01&#xA;C     3.560229798179676e+00   1.192011389147800e-02   3.571414759003793e+00 -1.08340810e-01  -6.94958780e-01  -6.32829660e-01&#xA;C     5.303243173957251e+00   1.783785084314883e+00   3.608673698334975e+00  6.65906520e-01   1.93424360e-01  -2.00882610e-01&#xA;C     3.528356910667667e+00   1.767911834435971e+00   5.347927358304606e+00  7.39111180e-01  -2.47114860e-01  -1.04495492e+00&#xA;C     5.329030825201182e+00   7.096177437942109e+00   5.369101643268158e+00 -3.08175260e-01  -1.14381900e-02   1.84117730e-01&#xA;C     4.422761249499998e+00   8.668823746375728e-01   4.494489925294728e+00  3.83796370e-01   4.22127430e-01  -5.75045160e-01&#xA;C     6.241506267102304e+00   2.679197823980088e+00   4.509426711577681e+00 -9.90742090e-01  -1.47647882e+00  -1.25004513e+00&#xA;C     4.432864237317125e+00   2.645875244758956e+00   6.162178971863699e+00  2.14951310e-01   1.37021740e-01   2.03719183e+00&#xA;C     6.276550008692416e+00   8.743755050897671e-01   6.235059780796678e+00 -2.36728919e+00   4.92518030e-01  -1.75193300e-01&#xA;C     7.065680456712427e+00   3.515117189201012e+00   3.569630900347304e+00  2.01679955e+00   6.47574810e-01  -7.38426790e-01&#xA;C     1.744524484258135e+00   5.323755096101070e+00   3.489180474334740e+00 -2.31814270e-01  -5.78952010e-01   2.30748316e+00&#xA;C     7.087238738665912e+00   5.312598853304337e+00   5.367801939276317e+00  8.84590350e-01   6.63457880e-01  -2.04867967e+00&#xA;C     1.836661512479110e+00   3.526170004448624e+00   5.351513557516396e+00 -1.23618594e+00   5.61918680e-01  -1.49124744e+00&#xA;C     8.644019616485500e-01   4.381350493769153e+00   4.431205771235654e+00  6.54489790e-01   1.65426557e+00   5.88371370e-01&#xA;C     2.638706329462460e+00   6.199561100158887e+00   4.412298788750978e+00  5.65976410e-01   3.85331420e-01  -6.55854390e-01&#xA;C     8.855542105019791e-01   6.193752239362274e+00   6.199043180486793e+00  4.21980700e-01   3.69641240e-01   2.30177540e-01&#xA;C     2.676275196019875e+00   4.452567718556373e+00   6.202611111052449e+00  5.14470800e-01  -6.82406950e-01  -3.64222200e-02&#xA;C     3.579314420145626e+00   3.572309993748555e+00   3.522390171804665e+00  1.20915900e-02  -5.19302820e-01   8.08118950e-01&#xA;C     5.377902368061301e+00   5.343446208684958e+00   3.488438141760533e+00 -1.17684527e+00   1.56643050e-01   2.46875405e+00&#xA;C     3.545122765174973e+00   5.343271341488506e+00   5.291750347349461e+00  3.51595720e-01  -8.43737200e-01   5.14030800e-01&#xA;C     5.342069378307690e+00   3.526753748114178e+00   5.351913690625676e+00 -3.28223650e-01   2.01570343e+00  -1.31587457e+00&#xA;C     4.480059756291901e+00   4.450995690893960e+00   4.393124174154658e+00 -6.06505570e-01   2.54363480e-01   8.42964100e-01&#xA;C     6.221970331384210e+00   6.256644790419212e+00   4.501010623532506e+00  3.77290300e-02  -1.34160519e+00  -1.84268948e+00&#xA;C     4.403452996558423e+00   6.178451075335819e+00   6.250501549422556e+00  6.40125260e-01   1.35140560e+00  -1.06078985e+00&#xA;C     6.211810831607253e+00   4.482924592776214e+00   6.216467417097163e+00  8.36191500e-02  -2.43405957e+00   4.62511060e-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7093" LastEditorUserId="7093" LastEditDate="2023-04-30T22:44:30.147" LastActivityDate="2023-04-30T22:44:30.147" Title="If total energies differ across different software, how do I decide which software to use?" Tags="|density-functional-theory|vasp|quantum-espresso|machine-learning|interatomic-potentials|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10814" PostTypeId="2" ParentId="10812" CreationDate="2023-04-30T18:08:55.707" Score="11" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;how do I decide on which algorithm/software to use if the total energies are different across algorithms/software?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You can use any algorithm or software to calculate your total energies, as long as you say precisely which algorithm and software version that you used, and as long as you stay consistent when calculating relative energies (for example, it's not recommended to use software A to calculate the neutral energy and software B to calculate the cation energy if you're calculating the ionization energy as an energy difference, unless you're confident that both programs are consistent).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-04-30T18:08:55.707" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10815" PostTypeId="1" CreationDate="2023-05-01T05:49:52.070" Score="3" ViewCount="139" Body="&lt;p&gt;I am trying to model the adsorption of charged atom (Zn2+) on the metallic surface using VASP.&lt;/p&gt;&#xA;&lt;p&gt;Since &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NELECT&quot; rel=&quot;nofollow noreferrer&quot;&gt;NELECT&lt;/a&gt; assumes total charge (metallic surface + Zn), is it the right flag to use? Or are there any other better methods to define Zn2+ in my structure and calculation?&lt;/p&gt;&#xA;" OwnerUserId="7117" LastEditorUserId="6687" LastEditDate="2023-05-01T07:34:39.120" LastActivityDate="2023-05-06T11:05:36.470" Title="Adsorption of Zn2+ on the metallic surface in VASP" Tags="|density-functional-theory|vasp|adsorption|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10816" PostTypeId="2" ParentId="10806" CreationDate="2023-05-01T08:47:10.180" Score="2" Body="&lt;h2&gt;Reproducing your error&lt;/h2&gt;&#xA;&lt;p&gt;So I simulated this error using a PROCAR that I could find online &lt;a href=&quot;https://github.com/AmarNathH/procar_parser/blob/master/PROCAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I used 90 as the number of grid points per line in the KPOINTS file, since I saw that there are 90 bands in the PROCAR file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;KPOINTS generated by PyProcar&#xA;90 ! Grid points&#xA;Line_mode&#xA;reciprocal&#xA;0.000000 0.000000 0.000000 ! GAMMA&#xA;0.500000 0.000000 0.000000 ! M&#xA;&#xA;0.500000 0.000000 0.000000 ! M&#xA;0.333333 0.333333 0.000000 ! K&#xA;&#xA;0.333333 0.333333 0.000000 ! K&#xA;0.000000 0.000000 0.000000 ! GAMMA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I tried to plot using:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pyprocar.bandsplot('PROCAR',mode='plain',kpointsfile='KPOINTS')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then I get an error similar to what you got:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;IndexError: index 179 is out of bounds for axis 0 with size 90&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Solution&lt;/h2&gt;&#xA;&lt;p&gt;I solved this by reducing the number of grid points per line to 30 in the KPOINTS file.&lt;/p&gt;&#xA;&lt;p&gt;Then I get a plot that looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dBkYb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dBkYb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-01T09:05:43.017" LastActivityDate="2023-05-01T09:05:43.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10817" PostTypeId="2" ParentId="10743" CreationDate="2023-05-01T09:43:59.477" Score="2" Body="&lt;h2&gt;DynaPhoPhy&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://abelcarreras.github.io/DynaPhoPy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;DynaPhoPhy&lt;/a&gt; is an open source (MIT License) python library for Phonon anharmonic properties from Molecular Dynamics.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;DynaPhoPhy allows to calculate anharmonic phonon linewidhts and&#xA;frequency shifts using the mode descomposition technique. To do that&#xA;it uses a VASP or LAMMPS Molecular Dynamics (MD) trajectory and&#xA;projects it onto a set of harmonic phonon modes obtained by&#xA;&lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phonopy&lt;/a&gt;. Afterwards the power spectrum is calculated usign&#xA;Fourier transform or Maximum Entropy Method (MEM) and the peaks are&#xA;fitted to Lorentzian functions to extract the phonon anharmonic&#xA;properties.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Detailed documentation on how to use : &lt;a href=&quot;https://abelcarreras.github.io/DynaPhoPy/usage.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Docs&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Source Code: &lt;a href=&quot;https://github.com/abelcarreras/DynaPhoPy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Usage&lt;/h3&gt;&#xA;&lt;p&gt;The steps on high level to use DynaPhoPhy are listed below with text quoted from the docs page.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Obtain input data by preparing Phonopy harmonic lattice dynamics calculation&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For many of the features of DynaPhoPhy the phonon eigenvectors are&#xA;necessary. These eigenvectors are calculated from the harmonic phonon&#xA;force constants using phonopy. To do this calculation DynaPhoPy&#xA;requires either a phonopy FORCE_SETS or FORCE_CONSTANTS type file.&#xA;These files can be created using phonopy, just follow the instruction&#xA;in phonopy tutorial to obtain them. Keep the original POSCAR file used&#xA;in the calculation containing the unaltered unit cell. This file is&#xA;used as input for DynaPhoPy to define the unitcell.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Prepare Molecular Dynamics (MD) calculation At the present time&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;DynaPhoPy implements interfaces for VASP and LAMMPS output files.&#xA;Using VASP VASP is a popular software to perform first principles calculations of solids. DynaphoPy can read the MD trajectory from&#xA;either OUTCAR or XDATCAR output files. Please, refere to VASP online&#xA;manual for detailed information to how to calculate a MD simulation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Execute DynaPhoPhy&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;dynaphopy input_file OUTCAR             (VASP)&#xA;dynaphopy input_file LAMMPS.lammpstrj -ts 0.002 (LAMMPS)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-01T11:40:36.487" LastActivityDate="2023-05-01T11:40:36.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10818" PostTypeId="1" CreationDate="2023-05-01T10:12:29.743" Score="7" ViewCount="129" Body="&lt;p&gt;I am thinking about one question. If the Hamiltonian matrix is based on the non-orthogonal basis, how to compute the charge conductance with the Non-Equilibrium Green's Function (NEGF) method.&lt;/p&gt;&#xA;&lt;p&gt;Suppose the Hamiltonian of the system is denoted by &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and the overlap matrix is denoted by &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;. They are written below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\left(\varepsilon_{F}+i\right)S-H&amp;amp;=\varepsilon^{'}S-H\tag{1}\\&#xA;&amp;amp;=\begin{pmatrix}&#xA;\varepsilon^{'}S_{ll}-H_{ll}&amp;amp;\varepsilon^{'}S_{ls}-H_{ls}&amp;amp;0\tag{2}\\&#xA;\varepsilon^{'}\times S_{sl}-H_{sl}&amp;amp;\varepsilon^{'} S_{ss}-H_{ss}&amp;amp;\varepsilon^{'} S_{sr}-H_{sr}\\0&amp;amp;\varepsilon^{'} S_{rs}-H_{rs}&amp;amp;\varepsilon^{'} S_{rr}-H_{rr}&#xA;\end{pmatrix}\\&#xA;&amp;amp;=\begin{pmatrix}H^{'}_{ll}&amp;amp;H^{'}_{ls}&amp;amp;0\\H^{'}_{sl}&amp;amp;H^{'}_{ss}&amp;amp;H^{'}_{sr}\\0&amp;amp;H^{'}_{rs}&amp;amp;H^{'}_{rr}\end{pmatrix}.\tag{3}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, &lt;span class=&quot;math-container&quot;&gt;$\varepsilon_{F}$&lt;/span&gt; is the Fermi energy level of the central scattering zone and &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is the imaginary number.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;G_{ll}&amp;amp;=\left[H^{'}_{ll}\right]^{-1}\tag{4} \\ G_{rr}&amp;amp;=\left[H^{'}_{rr}\right]^{-1}\tag{5} \\&#xA;\Gamma_\text{left}&amp;amp;=H^{'}_{sl} G_{ll} H^{'}_{ls}\tag{6} \\ \Gamma_\text{right}&amp;amp;=H^{'}_{sr} G_{ll} H^{'}_{rs}\tag{7}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Self energy for the left and right leads and the green function for the scattering zone are written below:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\Sigma_\text{left}&amp;amp;=i \times \left[\Gamma_\text{left}-\left(\Gamma_\text{left}\right)^{+}\right] \tag{8} \\&#xA;\Sigma_\text{right}&amp;amp;=i \times \left[\Gamma_\text{right}-\left(\Gamma_\text{right}\right)^{+}\right]\tag{9} \\&#xA;G_{ss}^{R}&amp;amp;=\left[H^{'}_{ss}-\Gamma_\text{left}-\Gamma_\text{right}\right]^{-1}\tag{10} \\&#xA;G_{ss}^{A}&amp;amp;=\left(G_{ss}^{R}\right)^{+}\tag{11}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then, the charge conductance is written below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_{k}=\frac{2e^{2}}{h}\mathrm{Tr}\left[\Sigma_\text{left}G_{ss}^{A}\Sigma_\text{right}G_{ss}\right]\tag{12}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This conductance is only for one single k point in the reciprocal space. The total charge conductance is the integral of this single-k-point-conductance over the whole first Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_{\textrm{total}}=\frac{e}{h}\int G_{k}\times \left[f_{(\varepsilon_{F}-\mu_\text{left})}-f_{(\varepsilon_{F}-\mu_\text{right})}\right]d_{k}\tag{13}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where, &lt;span class=&quot;math-container&quot;&gt;$f_{(\varepsilon_{F}-\mu_\text{left})}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$f_{(\varepsilon_{F}-\mu_\text{right})}$&lt;/span&gt; are Fermi-Dirac distribution function for left and right leads with the chemical potential &lt;span class=&quot;math-container&quot;&gt;$\mu_\text{left}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mu_\text{right}$&lt;/span&gt; for the left and right leads.&lt;/p&gt;&#xA;&lt;p&gt;To calculate the surface green function in equation (4) and (5), I used the Sancho's method.&lt;sup&gt;[1]&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;h3&gt;The final conductivity value, &lt;span class=&quot;math-container&quot;&gt;$G_{\textrm{total}}$&lt;/span&gt;, is only correct at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point in the reciprocal space, but wrong at other k points.&lt;/h3&gt;&#xA;&lt;p&gt;I checked the internal output data and found that the calculation of the Surface Green's function was not right, since some data was &lt;code&gt;NaN&lt;/code&gt; type. I guess this is because I did not use the correct way to avoid the singular matrix in the Surface Green's function calculation step.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Would anyone please give me some suggestions on the solution?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;br&gt;&#xA;&lt;br&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;M. P. L. Sancho, J. M. L. Sancho and J, Rubio, Highly convergent schemes for the calculation of bulk and surface Green functions, J. Phys. F: Met. Phys. 15 (1985) 851-858.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="5" LastEditDate="2023-12-01T17:50:58.913" LastActivityDate="2023-12-01T17:50:58.913" Title="Calculation of charge transport with the non-orthogonal basis Hamiltonian based on the non-equilibrium Green's function method" Tags="|density-functional-theory|electronic-transport|transport|greens-functions|" AnswerCount="0" CommentCount="24" ContentLicense="CC BY-SA 4.0" />
  <row Id="10819" PostTypeId="2" ParentId="9052" CreationDate="2023-05-01T13:58:18.353" Score="2" Body="&lt;p&gt;Since we do not have all the files specific to your calculation such as the INCAR, POTCAR, POSCAR, KPQINTS and vaspout.h5, I will demonstrate how to save a viewer3d structure to a PNG image using a sample viewer3d structure.&lt;/p&gt;&#xA;&lt;p&gt;From &lt;a href=&quot;https://github.com/vasp-dev/py4vasp/blob/33cee0184f1af1b9fce69d8bb2c773f506b13f25/src/py4vasp/_data/viewer3d.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;py4vasp source code&lt;/a&gt;, we can see that the viewer is a: &lt;code&gt;NGLWidget&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;All the following code are written on a Google Colab notebook:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from google.colab import output&#xA;output.enable_custom_widget_manager()&#xA;&#xA;import nglview as nv&#xA;import ipywidgets as w&#xA;import time&#xA;import threading&#xA;from pathlib import Path&#xA;view = nv.demo()&#xA;view&#xA;&#xA;type(view)&#xA;&amp;gt;&amp;gt; nglview.widget.NGLWidget # This matches with what we get from py4vasp&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The viewer3d structure looks like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5WhD7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5WhD7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The following code saves the viewer3d as a PNG image.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;output_path = &amp;quot;/content/drive/MyDrive/output/img.png&amp;quot;&#xA;&#xA;def save_image(view):&#xA;    img = view.render_image()&#xA;    &#xA;    while not img.value:&#xA;        time.sleep(0.1)&#xA;    &#xA;    with open(output_path, &amp;quot;wb&amp;quot;) as f:&#xA;        f.write(img.value)&#xA;&#xA;Path(output_path).unlink(missing_ok=True)&#xA;&#xA;thread = threading.Thread(target=save_image, args=(view, ), daemon=False)&#xA;&#xA;thread.start()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The PNG image is now saved at the output path.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-01T13:58:18.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10820" PostTypeId="2" ParentId="10802" CreationDate="2023-05-01T14:23:43.637" Score="3" Body="&lt;p&gt;I got an &lt;a href=&quot;https://github.com/pyscf/pyscf/issues/1719&quot; rel=&quot;nofollow noreferrer&quot;&gt;answer&lt;/a&gt; to this question at PySCF GitHub page from James E.T. Smith. I will post here in case someone has the same issue.&lt;/p&gt;&#xA;&lt;p&gt;It can be done both ways:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf.scf, pyscf.ci&#xA;&#xA;mol = pyscf.scf.chkfile.load_mol('mf.hdf5')&#xA;mf = pyscf.scf.RHF(mol) &#xA;mf.__dict__.update(pyscf.scf.chkfile.load('mf.hdf5', 'scf')) &#xA;&#xA;cisolver = pyscf.ci.CISD(mf)&#xA;cisolver.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf.scf, pyscf.ci&#xA;&#xA;mol, mf_dict = pyscf.scf.chkfile.load_scf('mf.hdf5')&#xA;mf = pyscf.scf.RHF(mol) &#xA;mf.__dict__.update(mf_dict) &#xA;cisolver = pyscf.ci.CISD(mf)&#xA;cisolver.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5367" LastEditorUserId="7" LastEditDate="2023-05-01T16:20:02.147" LastActivityDate="2023-05-01T16:20:02.147" CommentCount="0" CommunityOwnedDate="2023-05-01T16:19:31.053" ContentLicense="CC BY-SA 4.0" />
  <row Id="10822" PostTypeId="1" AcceptedAnswerId="10873" CreationDate="2023-05-01T20:55:30.197" Score="2" ViewCount="76" Body="&lt;p&gt;I read &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.64.184307&quot; rel=&quot;nofollow noreferrer&quot;&gt;several&lt;/a&gt; &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.123403&quot; rel=&quot;nofollow noreferrer&quot;&gt;papers&lt;/a&gt; regarding the use of cluster-based kinetic Monte Carlo (kMC) simulations&lt;/p&gt;&#xA;&lt;p&gt;They mention the need to use a kinetically resolved activation barrier by averaging over the forward and reverse migration barriers because it is &amp;quot;&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.94.045901&quot; rel=&quot;nofollow noreferrer&quot;&gt;difficult to treat its configuration dependence with a cluster expansion&lt;/a&gt;,&amp;quot; but do not explain why.&lt;/p&gt;&#xA;&lt;p&gt;I am wondering why the barrier must be treated as a kinetically resolved one rather than treating the forward and reverse barriers separately.&lt;/p&gt;&#xA;" OwnerUserId="4192" LastEditorUserId="4192" LastEditDate="2023-05-02T12:38:13.147" LastActivityDate="2023-05-08T21:47:44.463" Title="What is the purpose of a kinetically resolved activation barrier in cluster-based kinetic Monte Carlo simulations?" Tags="|atomistic-simulation|diffusion-monte-carlo|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10823" PostTypeId="2" ParentId="10803" CreationDate="2023-05-01T21:05:08.637" Score="3" Body="&lt;p&gt;Thermo-Calc does not currently allow pseudo-binary phase diagrams using the graphical mode. The console mode has to be used to calculate them. For using the console mode, I would recommend looking at and following Example 17 in the &lt;a href=&quot;https://thermocalc.com/wp-content/uploads/Documentation/Current_Static/thermo-calc-console-mode-example-macros.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Thermo-Calc Console Mode Example Manual&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To summarize, you have to (1) Define your components as the compounds in the pseudo-binary system, (2) Set the conditions in terms of these components, (3) Calculate the initial equilibrium, (4) Map the phase boundaries using the fraction of one component as the x-axis and temperature as the y-axis, and (5) Plot the phase diagram.&lt;/p&gt;&#xA;" OwnerUserId="4192" LastActivityDate="2023-05-01T21:05:08.637" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10824" PostTypeId="1" CreationDate="2023-05-02T09:30:51.210" Score="2" ViewCount="99" Body="&lt;p&gt;When I try to acess my account in a workstation remotely using my laptop by ssh using the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ssh login@10.20.2.X&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get the following message in terminal:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ssh: connect to host 10.20.2.X port 22: No route to host (X: is a number)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I think the problem is because I`m not locally present, the workstation is in another city. When I contacted the responsible in the workstation he said : 'check the configuration of your network card (you must have the range: 10.20.2.x)'&lt;/p&gt;&#xA;&lt;p&gt;How can I solve this issue, please?&lt;/p&gt;&#xA;&lt;p&gt;PS: The responsible for the workstation just created the account for me recently and sent me the connection parameters, so I never used this account before.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-05-02T10:58:58.870" LastActivityDate="2023-05-02T10:58:58.870" Title="Why I can't access my account using ssh?" Tags="|high-performance-computing|" AnswerCount="0" CommentCount="14" ClosedDate="2023-05-13T21:28:06.017" ContentLicense="CC BY-SA 4.0" />
  <row Id="10825" PostTypeId="1" CreationDate="2023-05-02T15:27:19.020" Score="5" ViewCount="105" Body="&lt;p&gt;I notice that r2scan could be more accurate than rscan, but I am unsure if r2scan could describe the d electron localization without Hubbard+U? Or do I still need Hubbard+U with r2scan?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2023-05-02T16:53:38.440" LastActivityDate="2023-05-03T13:02:27.487" Title="could meta-GGA-r2scan descript d electron localization and polaron the same as Hybrid functional?" Tags="|density-functional-theory|functional|dft-u|hubbard-model|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10826" PostTypeId="1" AcceptedAnswerId="10854" CreationDate="2023-04-26T11:00:04.987" Score="5" ViewCount="364" Body="&lt;p&gt;I have tried a bunch of apps such as Mercury, OpenLabel but they cannot convert  CIF files to XYZ files in bulk. I am also thinking of doing it in Python but just want to know if there's an app for this. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7074" OwnerDisplayName="Ruby" LastEditorUserId="6687" LastEditDate="2023-05-02T20:03:12.547" LastActivityDate="2023-05-06T08:14:09.510" Title="Which applications can convert multiple CIF files to multiple XYZ files all at once" Tags="|python|software-recommendations|cif|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10827" PostTypeId="1" CreationDate="2023-05-03T04:02:05.080" Score="3" ViewCount="33" Body="&lt;p&gt;As an example, why does glass tend to break by means of intergranular fracture?&lt;/p&gt;&#xA;&lt;p&gt;My analysis so far led me to believe that the tendency can be related to the intermolecular bond strength in a given crystal grain and the intergranular bond strength. A stronger bond means better load bearing. If the intermolecular bond is stronger than the intergranular bond, then a material is more likely to experience intergranular fracture. But is this correct?&lt;/p&gt;&#xA;" OwnerUserId="7133" LastEditorUserId="7133" LastEditDate="2023-05-03T07:37:31.103" LastActivityDate="2023-05-03T07:37:31.103" Title="What determines if a material tends to undergo transgranular or intergranular fracure?" Tags="|crystallography|physical-properties-of-materials|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-01T21:53:05.903" ContentLicense="CC BY-SA 4.0" />
  <row Id="10828" PostTypeId="1" CreationDate="2023-05-03T10:23:46.963" Score="4" ViewCount="93" Body="&lt;h3&gt;Context:&lt;/h3&gt;&#xA;&lt;p&gt;If I have a system that consists of 20 structures. During molecular dynamics, these structures can form micelles from my point of view.&lt;/p&gt;&#xA;&lt;p&gt;I would like to do the following:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Confirm if the micelle is stable&lt;/li&gt;&#xA;&lt;li&gt;Confirm that the micelle can be formed and that there is no water inside (i.e., there is no water close to the hydrophobic part and there is water close to the hydrophilic part).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;To do point 2, I used VMD to calculate the radial distribution function, and I selected one atom of the structure and one atom of the water solvent. But the g(r), as you see in the figure, is very small, and I don't know why. I am thinking that maybe because I selected one atom of the structure that already has the same name as the other 19 structures, therefore the calculated g(r) is an average for the 20 structures.&lt;/p&gt;&#xA;&lt;h3&gt;Question(s):&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How can I confirm the stability of the micelle?&lt;/li&gt;&#xA;&lt;li&gt;How can I confirm that the micelle can be formed and that there is no water inside?&lt;/li&gt;&#xA;&lt;li&gt;Why is the g(r) so low?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h3&gt;Radial Distribution:&lt;/h3&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/16dCr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/16dCr.png&quot; alt=&quot;Radial_distribution&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="6687" LastEditDate="2023-05-03T13:47:44.573" LastActivityDate="2023-05-04T11:55:06.930" Title="How to study the stability of structure in water and analyze the radial distribution function (RDF)?" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|vmd|radial-distribution-function|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10829" PostTypeId="1" AcceptedAnswerId="10830" CreationDate="2023-05-03T12:12:04.340" Score="4" ViewCount="158" Body="&lt;p&gt;The Broyden (Broyden—Fletcher—Goldfarb—Shanno or BFGS) algorithm can be known in the matter modeling to optimize a crystal lattice geometry — to clarify positions of nodes of a crystal lattice in calculation process of eigenvalues and eigenfunctions with a Hartree-Fock (or DFT) method. How much will the Broyden algorithm be clarifying right (energetically beneficial) positions of atomic nuclei if a crystal lattice of a substance will intentionally be significantly distorted? But what things can be done if a hypothetical alloy (some mix of metals and  non-metals in some proportion, which is raised to the monocrystalline solid level) is never explored before, including analyzing in an X-ray diffractometer to define positions of nuclei of lattice of a monocrystalline solid? Whether can the Broyden algorithm correctly upbuild a crystalline structure of some alloy? If it cannot, so is there a way to roughly calculate this thing maybe before a Hartree-Fock (or DFT) calculation and free software implementing such a calculation?&lt;/p&gt;&#xA;&lt;h2&gt;Or to put it more simply&lt;/h2&gt;&#xA;&lt;p&gt;is it possible to calculate an &amp;quot;a priori&amp;quot; alloy?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2023-05-03T12:28:40.203" Title="Is the Broyden's algorithm sufficient to obtain the crystal structure of a hypothetical alloy, or should something else be used?" Tags="|density-functional-theory|geometry-optimization|hartree-fock|alloys|alloy-theoretic-automated-toolkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10830" PostTypeId="2" ParentId="10829" CreationDate="2023-05-03T12:28:40.203" Score="2" Body="&lt;p&gt;BFGS is a local minimization method - it will find you the closest minimum to your starting structure - whereas finding the crystal structure is a global optimization problem: what is the structure that yields the lowest possible energy with the given atoms?&lt;/p&gt;&#xA;&lt;p&gt;BFGS may yield you the correct crystal structure, if you already know the right crystal space group and the structure is simple enough so that you can make a good guess for the structure. However, if you do not know the symmetry of the crystal, your structure search needs to consider many alternatives.&lt;/p&gt;&#xA;&lt;p&gt;There is already a code dedicated to solving these kinds of structure search problems called &lt;a href=&quot;https://uspex-team.org/en/uspex/overview&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt;; I recommend you to study the related literature which should answer all of your questions in detail.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-03T12:28:40.203" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10831" PostTypeId="2" ParentId="10794" CreationDate="2023-05-03T12:32:34.470" Score="1" Body="&lt;p&gt;Yes, the number of atoms as well as the energy are extensive so they obey the scaling relations&#xA;&lt;span class=&quot;math-container&quot;&gt;$ n \to n'= \frac {V'} {V} n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E \to E'=\frac {V'} {V} E$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; are the original number of particles, energy and volume, and &lt;span class=&quot;math-container&quot;&gt;$n'$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E'$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V'$&lt;/span&gt; are the new number of particles, energy and volume.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-03T12:32:34.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10832" PostTypeId="1" CreationDate="2023-05-03T12:53:30.737" Score="5" ViewCount="27" Body="&lt;p&gt;I am interested in using the CVS option in CI calculations to get core-excited states. I tried to use the MRCC program which possesses this option according to the manual (cvs=...). I performed some test calculations using MRCC with and without the CVS option and got the same results, in particular, the number of configurations was the same with and without that option. I wonder if someone has used this option in MRCC and could share their input. Here is my post about this issue at the MRCC forum:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.mrcc.hu/index.php/forum/running-mrcc/324-cvs-option-doesn-t-seem-to-work&quot; rel=&quot;noreferrer&quot;&gt;https://www.mrcc.hu/index.php/forum/running-mrcc/324-cvs-option-doesn-t-seem-to-work&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Kind regards,&#xA;Evgeniy&lt;/p&gt;&#xA;" OwnerUserId="6296" LastActivityDate="2023-05-03T12:53:30.737" Title="Core-valence separation (CVS) keyword in MRCC program" Tags="|excited-states|configuration-interaction|mrcc|" AnswerCount="0" CommentCount="1" ClosedDate="2023-11-08T00:18:34.003" ContentLicense="CC BY-SA 4.0" />
  <row Id="10833" PostTypeId="2" ParentId="10825" CreationDate="2023-05-03T13:02:27.487" Score="1" Body="&lt;p&gt;If I do understand correctly your question, you ask if an exchange correlation functional (r2scan or another functionals in the future) can describe correctly strongly correlated systems.&lt;/p&gt;&#xA;&lt;p&gt;The answer is NO as a consequence of the fact that this U is a correction of a many-body problem while DFT solves merely one body problems including corrections as nonlocal corrections. But pathological correlation effects cannot be cured that way.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-05-03T13:02:27.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10834" PostTypeId="1" AcceptedAnswerId="10835" CreationDate="2023-05-03T17:03:05.583" Score="3" ViewCount="317" Body="&lt;p&gt;I've used these terms interchangeably for a while, but have noticed that in PySCF they are &lt;a href=&quot;https://pyscf.org/user/pbc/gto.html#basis-set-and-pseudopotential&quot; rel=&quot;nofollow noreferrer&quot;&gt;separate attributes&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Are there any crucial differences between an effective core potential (ECP) and a pseudopotential?&lt;/p&gt;&#xA;&lt;p&gt;My initial thought was that ECPs are for gaussian-type orbitals (GTOs) and pseudopotentials are for plane-wave calculations, as I usually hear ECP in the context of molecules with heavy elements and pseudopotentials in the context of exploring extended (periodic) systems.&lt;/p&gt;&#xA;" OwnerUserId="1166" LastEditorUserId="5" LastEditDate="2023-05-04T02:29:05.087" LastActivityDate="2023-05-04T02:30:25.243" Title="What is the difference, if any, between an effective core potential (ECP) and a pseudopotential?" Tags="|electronic-structure|pseudopotentials|terminology|relativistic|heavy-elements|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10835" PostTypeId="2" ParentId="10834" CreationDate="2023-05-04T02:19:56.893" Score="3" Body="&lt;h1&gt;They are often used as synonyms&lt;/h1&gt;&#xA;&lt;p&gt;Schwerdtfeger's  review paper &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/epdf/10.1002/cphc.201100387&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;The Pseudopotential Approximation in Electronic Structure Theory&amp;quot;&lt;/a&gt; states that the two terms are used as &lt;em&gt;&lt;strong&gt;synonyms&lt;/strong&gt;&lt;/em&gt; in the electronic structure literature:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;As we are mostly interested in chemical properties coming from the valence space, we can try to replace the effect of the core electrons on a valence system in an atom, molecule or infinite system by a pseudopotential, which for this special case we call an effective core potential (ECP) (unfortunately, in electronic structure theory the term effective core potential and the more general term pseudopotential are used &lt;em&gt;&lt;strong&gt;synonymously&lt;/strong&gt;&lt;/em&gt;, the latter favoured by European theoretical chemists and the solid-state community, which we will adopt in the following.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h1&gt;But &amp;quot;Pseudopotential&amp;quot; can be more general&lt;/h1&gt;&#xA;&lt;p&gt;The above paragraph also says what my &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10834/what-is-the-difference-if-any-between-an-effective-core-potential-ecp-and-a#comment23234_10834&quot;&gt;initial comment&lt;/a&gt; said, which is that &amp;quot;pseudopotential&amp;quot; can be a more general term (he says that it's &amp;quot;unfortunate&amp;quot; that electornic structure theorists tend to use the terms as synonyms). I would say that &amp;quot;pseudopotential&amp;quot; is a more general term because the name doesn't imply that it's the effects of core electrons that are replaced. The Fermi pseudopotential for neutron scattering by a nucleus might be a good example of a psuedopotential that doesn't replace the effects of core electrons.&lt;/p&gt;&#xA;&lt;h1&gt;PySCF attributes&lt;/h1&gt;&#xA;&lt;p&gt;You provided a link to the PySCF documentation, which indicates that ECPs and PPs are different attributes in PySCF. Indeed that page contains a script that contains the following comment:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Input ECP with .ecp attribute and PP with .pseudo attribute.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, immediately before that comment it says:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;It is allowed to mix the Quantum chemistry effective core potentail (ECP) with crystal pseudo potential (PP).&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and immediately after that same comment it says:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;See also&#xA;pyscf/pbc/gto/pseudo/GTH_POTENTIALS for the GTH-potential format&#xA;pyscf/examples/gto/05-input_ecp.py for quantum chemistry ECP format&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These suggest that the attributes have more to do with the &lt;em&gt;&lt;strong&gt;format&lt;/strong&gt;&lt;/em&gt; than anything else.&lt;/p&gt;&#xA;&lt;p&gt;When we look at &lt;code&gt;pyscf/examples/gto/05-input_ecp.py&lt;/code&gt; we see:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Na nelec 10&#xA;Na ul&#xA;0      2.0000000              6.0000000        &#xA;1    175.5502590            -10.0000000        &#xA;2      2.3365719             -6.0637782        &#xA;2      0.7799867             -0.7299393        &#xA;Na S&#xA;0    243.3605846              3.0000000        &#xA;1     41.5764759             36.2847626        &#xA;2     13.2649167             72.9304880        &#xA;2      0.9764209              6.0123861        &#xA;Na P&#xA;0   1257.2650682              5.0000000        &#xA;1    189.6248810            117.4495683        &#xA;2     54.5247759            423.3986704        &#xA;2      0.9461106              7.1241813        &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But when we look at &lt;code&gt;pyscf/pbc/gto/pseudo/GTH_POTENTIALS&lt;/code&gt; we see:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Na GTH-BLYP-q9 GTH-BLYP&#xA;    3    6&#xA;     0.23396502    2    -2.68948346    -0.50947770&#xA;    2&#xA;     0.14977690    1    32.85715860&#xA;     0.12319901    1   -13.99900802&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Not only are these different potentials, but they are in completely different formats.&lt;/p&gt;&#xA;&lt;p&gt;The PySCF authors may have just stuck with the &amp;quot;convention&amp;quot; that a lot of chemists tend to call them ECPs and a lot of physicists tend to call them PPs, but even in the same script the comments later admit that ECPs can also be called PPs, as in the case of the BFD (Burkatzki-Filippi-Dolg) ECP/PP:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Allow mixing quantum chemistry ECP (or BFD PP) and crystal PP in the same calculation.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/126/23/234105/531927/Energy-consistent-pseudopotentials-for-quantum&quot; rel=&quot;nofollow noreferrer&quot;&gt;original BFD paper&lt;/a&gt; uses all three of the terms (pseudopotential, effective potential, effective core potential) in the same paper, and I think it also puts to rest your initial thought:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My initial thought was that ECPs are for gaussian-type orbitals (GTOs) and pseudopotentials are for plane-wave calculations&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;because the BFD PPs were designed for GTOs and molecules rather than for plane-waves and periodic systems.&lt;/p&gt;&#xA;&lt;br&gt;&#xA;&lt;h1&gt;Funny conclusion&lt;/h1&gt;&#xA;&lt;br&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Effective core potentials&lt;/strong&gt; are a specific type of &lt;a href=&quot;https://en.wikipedia.org/wiki/Pseudopotential&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;psuedopotential&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Psuedopotentials&lt;/strong&gt; are a specific type of &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_potential&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;effective potential&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Longer conclusion&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;Effective core potentials&amp;quot; are pseudopotentials that are used to treat the effects of core electrons&lt;/li&gt;&#xA;&lt;li&gt;Pseudopotentials are a type of &amp;quot;effective potential&amp;quot;, but effective potentials don't have to be pseudo (e.g. if we're just adding five non-psuedo potentials together to give us one combined &amp;quot;effective&amp;quot; potential).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;PySCF has different attributes for:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ECPs/PPs that are in a format used mostly in the study of periodic stystems. They call this the &amp;quot;GTH (Goedecker-Teter-Hutter) format&amp;quot; and they call these &amp;quot;crystal PPs&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;ECPs/PPs that are in a format used mostly in the study of molecules. They call this the &amp;quot;quantum chemistry ECP format&amp;quot; and they call these &amp;quot;quantum chemistry effective core potentials (ECP), but they admit that what they call the &amp;quot;BFD PPs&amp;quot; are actually ECPs.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The last point possibly reflects Schwerdtfeger's observation that the difference in terms used is not a matter of chemists vs physicists, but a matter of &amp;quot;non-European chemists&amp;quot;, vs &amp;quot;physicists + European chemists&amp;quot;, meaning that some chemists like Burkatzki, Filippi, and Dolg (from Germany, Netherlands, and Germany, at the time of the above-linked paper) use the term PP even when they're using GTOs for molecules/non-periodic-systems.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-05-04T02:30:25.243" LastActivityDate="2023-05-04T02:30:25.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10836" PostTypeId="1" CreationDate="2023-05-04T05:18:02.703" Score="6" ViewCount="91" Body="&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.106.155102&quot; rel=&quot;noreferrer&quot;&gt;this Phys. Rev. B article&lt;/a&gt;, Chen, Salzbrenner &amp;amp; Monserrat provide a &lt;em&gt;[n]onuniform grids for Brillouin zone integration and interpolation&lt;/em&gt;. According to them, they were &lt;em&gt;able to accelerate the calculation of even complex properties of materials by one to three orders of magnitude&lt;/em&gt; compared to the usual approach based on regular uniform grids.&lt;/p&gt;&#xA;&lt;p&gt;My question is: is there any DFT code already implementing such a nonuniform grid? In the article, they used VASP and CASTEP, but I couldn't understand if they modified the software's source code to implement this method, or if they somehow implemented it without modifying the source code (and maybe by preparing the input files in some specific way).&lt;/p&gt;&#xA;&lt;p&gt;Arxiv link of the same article: &lt;a href=&quot;https://arxiv.org/abs/2208.05981&quot; rel=&quot;noreferrer&quot;&gt;https://arxiv.org/abs/2208.05981&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-05-04T05:59:46.280" LastActivityDate="2023-05-07T02:05:34.397" Title="Which DFT code allows 'nonuniform grids for Brillouin zone integration'?" Tags="|density-functional-theory|software-recommendations|brillouin-zone|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10837" PostTypeId="1" AcceptedAnswerId="10843" CreationDate="2023-05-04T06:03:51.903" Score="6" ViewCount="273" Body="&lt;p&gt;VASP provides two sets of pseudopotentials(PP) for LDA and GGA respectively, but as I understand the PP is dependent on the exchange-correlation functional I use, so if I am using meta-GGA, could I use the PP designed for GGA?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastActivityDate="2023-05-09T15:42:18.220" Title="Is the pseudopotential designed for GGA also suited for meta-GGA?" Tags="|density-functional-theory|vasp|functional|exchange-correlation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10838" PostTypeId="2" ParentId="10828" CreationDate="2023-05-04T11:55:06.930" Score="6" Body="&lt;p&gt;Here are my two cents (things that I would try):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;How can I confirm the stability of the micelle?&lt;/em&gt;&lt;br /&gt;&#xA;You could run the simulation for a longer time and/or run at different temperatures. Also, monitoring the energy during the simulation time.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;How can I confirm that the micelle can be formed and that there is no water inside?&lt;/em&gt;&lt;br /&gt;&#xA;It is possible to do a topological study and search for bond critical points. Also, if you start from different initial distribution and at the end, you have a conglomerate of your structures, then the micelle is formed.&#xA;About the water inside, the g(r) is a good measure. I recommend the software &lt;a href=&quot;http://www.travis-analyzer.de/&quot; rel=&quot;noreferrer&quot;&gt;TRAVIS&lt;/a&gt;. It has several functions to study the distribution of particles from molecular dynamics trajectories.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Why is the g(r) so low?&lt;br /&gt;&#xA;One possible cause can be the atom selection, as you already guessed. The TRAVIS software will identify all the molecules in your system and will calculate the g(r) from a reference molecule (or atoms that you choose) to an atom, molecule, or a set of atoms/molecules.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-04T11:55:06.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10839" PostTypeId="2" ParentId="10837" CreationDate="2023-05-04T12:02:55.667" Score="3" Body="&lt;p&gt;In the case of an hybrid functional this is exactly what we do by using the GGA pseudopotentials, besides hybrid functionals are not often used for generating pseudopotentials from an all-electron calculation.&lt;/p&gt;&#xA;&lt;p&gt;If it works fine for hybrid GGA functionals very different compared to GGA, it should work for meta-GGA as a simple correction of GGA.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-05-04T12:02:55.667" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10840" PostTypeId="1" CreationDate="2023-05-04T15:09:41.387" Score="2" ViewCount="48" Body="&lt;p&gt;In case of CsSnI3 and CsGeI3 perovskites, the strong antibonding hybridization of Sn-s/Ge-s state with I-p state lies near to VBM of these materials. In this informative &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2016/ta/c6ta04685a&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; (P.No.13853, 14th line), it is said that this makes it easier to create holes. Can anyone please help me understand why this is so and how to identify from band-structure/PDOS whether orbitals are hybridized antibondingly/non-bondingly/bondingly? How do I know whether antibonding hybridization is near or far from VBM?&lt;/p&gt;&#xA;" OwnerUserId="5138" LastEditorUserId="5138" LastEditDate="2023-05-04T17:59:42.857" LastActivityDate="2023-05-04T17:59:42.857" Title="Antibonding, non-bonding or bonding hybridization" Tags="|density-functional-theory|computational-chemistry|band-structure|solid-state-physics|atoms-in-molecules|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-08T00:18:12.040" ContentLicense="CC BY-SA 4.0" />
  <row Id="10841" PostTypeId="1" CreationDate="2023-05-04T15:18:36.963" Score="2" ViewCount="90" Body="&lt;p&gt;Can someone direct me on how to model a mesoporous material using VASP? I have the initial structure that I generated with a LAMMPS code which has two surfaces on the top and bottom of the slab (basically I introduced a vacuum gap on either side).&lt;/p&gt;&#xA;&lt;p&gt;I need to convert this into a POSCAR and relax but I am having issues in understanding how to define the vacuum gap there.&lt;/p&gt;&#xA;&lt;p&gt;Any help is appreciated. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastEditorUserId="5" LastEditDate="2023-11-05T14:34:22.840" LastActivityDate="2023-12-03T04:59:04.430" Title="How to define a mesoporous material in VASP (introducing the vacuum gap)" Tags="|vasp|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="10842" PostTypeId="1" AcceptedAnswerId="10847" CreationDate="2023-05-04T16:07:07.970" Score="3" ViewCount="207" Body="&lt;p&gt;I am seeking advice regarding a molecular dynamics simulation in LAMMPS of Gallium Phosphide (GaP). I came across a paper by &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.75.115202&quot; rel=&quot;nofollow noreferrer&quot;&gt;Powell et al.&lt;/a&gt; which parameterized a tersoff potential for Ga-P interaction, but it did not include the Ga-Ga and P-P interaction parameters. However, the author did find various elastic constants of GaP using that potential. On the other hand, I was able to successfully recreate the tersoff potential for GaN (included in the LAMMPS example directory) from a paper by &lt;a href=&quot;https://doi.org/10.1088/0953-8984/15/32/324&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nord et al.&lt;/a&gt;, which included the Ga-Ga and N-N interaction parameters.&lt;/p&gt;&#xA;&lt;p&gt;My question is, can I use the parameters from Powell et al. without including the Ga-Ga and P-P interaction parameters, or do I need to use some hybrid potential? I am not sure if this is possible or not. I would appreciate any guidance or suggestions on how to proceed with this issue.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;a href=&quot;https://i.stack.imgur.com/tJMPT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tJMPT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6866" LastEditorUserId="6687" LastEditDate="2023-05-04T17:31:20.967" LastActivityDate="2023-05-05T12:09:44.170" Title="Parameterizing a Tersoff Potential in LAMMPS" Tags="|molecular-dynamics|lammps|interatomic-potentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10843" PostTypeId="2" ParentId="10837" CreationDate="2023-05-04T19:35:29.470" Score="3" Body="&lt;p&gt;In practice, you're likely to be okay. &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jctc.0c00214&quot; rel=&quot;nofollow noreferrer&quot;&gt;Borlido and coworkers&lt;/a&gt; (the article is open access) stuied just this for band gaps in 2020, concluding that the error based on the choice of functional is generally larger than the pseudopotential error.&lt;/p&gt;&#xA;&lt;p&gt;Still, if you want to be careful, it might be worth checking the pseudopotential of interest against a converged all-electron calculation for some representative subset of your systems.&lt;/p&gt;&#xA;&lt;p&gt;Update (May 2023): A new paper by &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.3c00089&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rosomme et al.&lt;/a&gt; (ACS paper, I can't find a preprint version) just appeared, detailing the effect of pseudopoential inconsistencies for molecules. Its conclusions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Nonbonded interactions and reaction barrier heights are okay!&lt;/li&gt;&#xA;&lt;li&gt;Dimerization and reaction energies for transition metals induce larger errors than chemical accuracy.&lt;/li&gt;&#xA;&lt;li&gt;Bond breaking for main-group elements is often quite bad if the pseudopotential is inconsistent.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;So a fuller answer is that it depends on the application at which you're looking. Depending on what that is, the advice to double-check your results could become quite important.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastEditorUserId="1393" LastEditDate="2023-05-09T15:42:18.220" LastActivityDate="2023-05-09T15:42:18.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10844" PostTypeId="1" CreationDate="2023-04-20T01:23:00.057" Score="5" ViewCount="247" Body="&lt;p&gt;I am about to generate topology from a rdkit mol object with a conformer for a molecule in mol2 format, but receive the error this mol object has 'UndefinedStereochemistry'. As I am from computer science instead of Chemistry, I have no idea what this means and how to fix it.&lt;/p&gt;&#xA;&lt;p&gt;I think a mol2 conformer file has all bond information and atom stereo position information. why this mol object still has 'UndefinedStereochemistry'? what should I do to make it to have full 'Stereochemistry'?&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import rdkit.Chem as Chem&#xA;ligand = Chem.MolFromMol2File('test04192/ligand_clean.mol2')&#xA;ligand = Chem.AddHs(ligand)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I use this code to load the file to a mol object.below is my conformer file in text form&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@&amp;lt;TRIPOS&amp;gt;MOLECULE&#xA;TEST&#xA; 33 36 0 0 0&#xA;SMALL&#xA;GASTEIGER&#xA;&#xA;@&amp;lt;TRIPOS&amp;gt;ATOM&#xA;      1 N          64.6250   41.8100  -29.6810 N.pl3   1  UNL1       -0.1137&#xA;      2 N          64.2020   42.7600  -28.7510 N.2     1  UNL1       -0.1528&#xA;      3 C          64.4910   44.0110  -28.9750 C.2     1  UNL1        0.1707&#xA;      4 C          64.1890   45.1870  -28.2020 C.2     1  UNL1        0.1009&#xA;      5 C          65.2330   44.4850  -30.1440 C.2     1  UNL1        0.2922&#xA;      6 C          63.4360   45.1650  -26.9130 C.3     1  UNL1        0.0556&#xA;      7 N          64.6540   46.2470  -28.7700 N.2     1  UNL1       -0.1739&#xA;      8 N          65.3160   45.9130  -29.9790 N.am    1  UNL1       -0.1539&#xA;      9 O          65.6880   43.7840  -31.0770 O.2     1  UNL1       -0.2661&#xA;     10 C          65.9540   46.7820  -30.8890 C.ar    1  UNL1        0.0768&#xA;     11 C          65.2290   47.5060  -31.8040 C.ar    1  UNL1        0.0165&#xA;     12 C          65.8320   48.3650  -32.7090 C.ar    1  UNL1       -0.0032&#xA;     13 C          67.2020   48.5050  -32.6980 C.ar    1  UNL1       -0.0257&#xA;     14 C          67.8430   49.4300  -33.6740 C.3     1  UNL1        0.0307&#xA;     15 C          67.9330   47.7860  -31.7880 C.ar    1  UNL1       -0.0245&#xA;     16 C          69.4300   47.9550  -31.7930 C.3     1  UNL1        0.0307&#xA;     17 C          67.3190   46.9320  -30.8900 C.ar    1  UNL1        0.0123&#xA;     18 C          63.6760   40.8990  -30.2480 C.ar    1  UNL1        0.1302&#xA;     19 C          63.3690   40.9930  -31.6090 C.ar    1  UNL1        0.0215&#xA;     20 C          62.4640   40.1300  -32.1620 C.ar    1  UNL1        0.0016&#xA;     21 C          61.8510   39.1660  -31.4010 C.ar    1  UNL1        0.0033&#xA;     22 C          62.1320   39.0430  -30.0450 C.ar    1  UNL1        0.0403&#xA;     23 C          63.0450   39.9190  -29.5000 C.ar    1  UNL1        0.2124&#xA;     24 O          63.3880   39.8630  -28.1340 O.3     1  UNL1       -0.2851&#xA;     25 C          61.4920   38.0260  -29.2220 C.ar    1  UNL1        0.0033&#xA;     26 C          62.2590   37.2910  -28.3220 C.ar    1  UNL1        0.0001&#xA;     27 C          61.6850   36.3120  -27.5150 C.ar    1  UNL1        0.0002&#xA;     28 C          60.3350   36.0510  -27.5910 C.ar    1  UNL1        0.0066&#xA;     29 C          59.5580   36.7730  -28.4830 C.ar    1  UNL1        0.0798&#xA;     30 C          60.1480   37.7360  -29.2720 C.ar    1  UNL1        0.0067&#xA;     31 C          58.1320   36.5410  -28.6040 C.2     1  UNL1        0.3878&#xA;     32 O          57.6980   36.1020  -29.7120 O.co2   1  UNL1       -0.2406&#xA;     33 O          57.2920   36.7990  -27.5370 O.co2   1  UNL1       -0.2406&#xA;@&amp;lt;TRIPOS&amp;gt;BOND&#xA;     1     1    18    1&#xA;     2     1     2    1&#xA;     3     2     3    2&#xA;     4     3     5    1&#xA;     5     3     4    1&#xA;     6     4     7    2&#xA;     7     4     6    1&#xA;     8     5     9    2&#xA;     9     5     8   am&#xA;    10     7     8    1&#xA;    11     8    10    1&#xA;    12    10    11   ar&#xA;    13    10    17   ar&#xA;    14    11    12   ar&#xA;    15    12    13   ar&#xA;    16    13    14    1&#xA;    17    13    15   ar&#xA;    18    15    16    1&#xA;    19    15    17   ar&#xA;    20    18    19   ar&#xA;    21    18    23   ar&#xA;    22    19    20   ar&#xA;    23    20    21   ar&#xA;    24    21    22   ar&#xA;    25    22    23   ar&#xA;    26    22    25    1&#xA;    27    23    24    1&#xA;    28    25    30   ar&#xA;    29    25    26   ar&#xA;    30    26    27   ar&#xA;    31    27    28   ar&#xA;    32    28    29   ar&#xA;    33    29    30   ar&#xA;    34    29    31    1&#xA;    35    31    32   ar&#xA;    36    31    33   ar&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7177" OwnerDisplayName="Suice May" LastEditorUserId="6687" LastEditDate="2023-05-05T14:56:13.527" LastActivityDate="2023-05-07T14:12:37.593" Title="Undefined stereochemistry in rdkit from mol2" Tags="|python|rdkit|cheminformatics|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10845" PostTypeId="1" CreationDate="2023-05-05T01:48:26.263" Score="2" ViewCount="32" Body="&lt;p&gt;I am looking for a complete description of the interaction of two traceless cartesian quadrupoles. Even just an implementation online would be quite useful. The problem I am having is many of the implementations I am aware of are quite opaque given that they are intended for use in MD and hence are quite optimized and often include terms related to ewald summation.&lt;/p&gt;&#xA;&lt;p&gt;I am also aware of the appendix in Anthony Stone's book which gives the interaction tensors in terms of components of direction cosines. Is there any more compact form for the evaluation of the interaction of two quadrupoles than the somewhat daunting equations given there?&lt;/p&gt;&#xA;&lt;p&gt;I am pretty surprised I can't find a straightforward implementation of this for a pair of traceless quadrupoles in cartesian coordinates. Any reference would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;If there just isn't an easier way than using the expressions provided by Stone, then I suppose that's the way I'll have to go.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2023-05-05T01:48:26.263" Title="Interaction energy of two cartesian quadrupoles?" Tags="|molecular-dynamics|reference-request|molecular-interactions|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10846" PostTypeId="1" CreationDate="2023-05-05T04:34:33.500" Score="4" ViewCount="440" Body="&lt;h2&gt;Context&lt;/h2&gt;&#xA;&lt;p&gt;I am trying to convert a pymatgen bonded structure, such as one generated by &lt;code&gt;CrystalNN&lt;/code&gt; to an rdkit molecule.&lt;/p&gt;&#xA;&lt;p&gt;So I obtain the pymatgen bonded structure with CrystalNN() as shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.io.cif import CifParser&#xA;from pymatgen.analysis.local_env import CrystalNN&#xA;&#xA;parser = CifParser('/path/to/cif.cif')&#xA;structure = parser.get_structures()[0]&#xA;&#xA;nn = CrystalNN()&#xA;adj_matrix = nn.get_bonded_structure(structure)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I can then loop over all the sites and bonds and add them using &lt;code&gt;RWMol&lt;/code&gt; from rdkit. I am able to do that as shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;&#xA;mol = Chem.RWMol() &#xA;&#xA;#Add atoms&#xA;for idx, site in enumerate(structure):&#xA;    element = site.as_dict()['species'][0]['element']&#xA;    coord = site.coords&#xA;    &#xA;    atom = Chem.Atom(element)  &#xA;    atom.SetDoubleProp('x', coord[0])  &#xA;    atom.SetDoubleProp('y', coord[1])  &#xA;    atom.SetDoubleProp('z', coord[2])  &#xA;&#xA;    mol.AddAtom(atom) &#xA;&#xA;&#xA;#Add bonds&#xA;nninfo = nn.get_all_nn_info(structure)&#xA;&#xA;for idx, nbrs in enumerate(nninfo):&#xA;    for nidx, nbr in enumerate(nbrs):&#xA;        &#xA;        nbridx = nninfo[idx][nidx]['site_index']&#xA;&#xA;        try:&#xA;            mol.AddBond(idx, nbridx)    &#xA;        except:&#xA;            continue;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Questions&lt;/h2&gt;&#xA;&lt;p&gt;But this leaves two issues unresolved:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How to limit this just to the molecule, not the entire structure?&lt;/li&gt;&#xA;&lt;li&gt;How to find the bond-order from CrystalNN?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6361" LastEditorUserId="6361" LastEditDate="2023-05-06T04:24:28.680" LastActivityDate="2023-05-06T08:03:07.873" Title="Pymatgen structure to rdkit molecule" Tags="|python|rdkit|pymatgen|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10847" PostTypeId="2" ParentId="10842" CreationDate="2023-05-05T12:09:44.170" Score="4" Body="&lt;p&gt;This is a great example of how MD potentials are meant to fit substances &lt;em&gt;for particular purposes&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The Tersoff potential is meant to fit the cohesive energy of solid-state structures by modifying the energies &lt;em&gt;of bonds&lt;/em&gt; in terms of the geometries of &lt;em&gt;other nearby bonds&lt;/em&gt;. Yes, it's implemented in LAMMPS as a non-bonded potential because that's how LAMMPS represents materials whose bond topologies can change, but you should consider each pair interaction as implicitly a bond.&lt;/p&gt;&#xA;&lt;p&gt;So why doesn't Powell's paper have Ga-Ga and P-P parameters? Because he studied GaP only in the regime where there was only one type of nearest-neighbour bond, namely the Ga-P bond. And why does Nord's paper have Ga-Ga and N-N parameters? Because &lt;em&gt;they&lt;/em&gt; were studying Ga and N in high-pressure phases, where all of those bonds &lt;em&gt;were&lt;/em&gt; relevant.&lt;/p&gt;&#xA;&lt;p&gt;So the question of whether you need the homoatomic parameters depends on whether &lt;em&gt;you&lt;/em&gt; expect to see homoatomic bonds at your chosen temperature and density. Note that there is a recent study which used Powell's parameters in LAMMPS (Phys. Rev. B 101 (2020), 024307), so you should try to contact those authors for more information.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-05-05T12:09:44.170" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10848" PostTypeId="1" CreationDate="2023-05-05T12:49:01.167" Score="6" ViewCount="74" Body="&lt;p&gt;Could you please help me to calculate the &amp;quot;transverse and longitudinal optical phonon frequencies&amp;quot; from phonopy+vasp output files?&lt;a href=&quot;https://i.stack.imgur.com/Alezo.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Alezo.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;These parameters will help me to calculate the high-frequency dielectric constant as shown in the Eq. 1.&lt;/p&gt;&#xA;" OwnerUserId="6230" LastActivityDate="2023-05-05T12:49:01.167" Title="How can we calculate transverse and longitudinal optical phonon frequencies" Tags="|vasp|phonopy|dielectric-constants|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10849" PostTypeId="2" ParentId="10800" CreationDate="2023-05-05T13:56:33.487" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/wu2meng3/ONCVPseudoPack&quot; rel=&quot;nofollow noreferrer&quot;&gt;This GitHub repository&lt;/a&gt; collects optimized norm-conserving Vanderbilt pseudopotentials, both scalar and full relativistic, generated from LDA, PBE, and PBEsol. Looks like for LDA you can use either the Sg15 or Abinit ones!&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-05-05T13:56:33.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10850" PostTypeId="2" ParentId="8774" CreationDate="2023-05-05T16:32:56.437" Score="3" Body="&lt;p&gt;Notes on my answer: I'll mainly link to arXiv versions of papers, but will also link the peer-reviewed version if the arXiv page doesn't do that itself. DFA means &amp;quot;density functional approximation&amp;quot;, and MLWFs are maximally localized Wannier functions.&lt;/p&gt;&#xA;&lt;p&gt;Helpful resources for &lt;code&gt;wannier90&lt;/code&gt; include &lt;a href=&quot;https://raw.githubusercontent.com/wannier-developers/wannier90/v3.1.0/doc/compiled_docs/user_guide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;its user guide&lt;/a&gt; and the &lt;a href=&quot;https://arxiv.org/abs/0708.0650&quot; rel=&quot;nofollow noreferrer&quot;&gt;2008 Comput. Phys. Comm. article&lt;/a&gt; that introduced it to the world.&lt;/p&gt;&#xA;&lt;h2&gt;1) Energy windows&lt;/h2&gt;&#xA;&lt;p&gt;The inner (or frozen) and outer energy windows are parameters required by the disentanglement procedure of &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0108084&quot; rel=&quot;nofollow noreferrer&quot;&gt;Souza, Marzari, and Vanderbilt, PRB (2001)&lt;/a&gt;. Whenever the collection of bands you're interested in is &lt;em&gt;entangled&lt;/em&gt;—that is, when there is no energy gap separating it from both higher- and lower-energy bands at every point in the Brillouin zone—you need to use this disentanglement to cause it to be composite.&lt;/p&gt;&#xA;&lt;p&gt;This step actually changes the band structure a little, at the top and bottom of the &lt;strong&gt;outer&lt;/strong&gt; energy window, where bands are being deflected away from the cutoffs. These cutoffs are known as &lt;code&gt;dis_win_min&lt;/code&gt; and &lt;code&gt;dis_win_max&lt;/code&gt;. By default, they are the lowest- (highest-)energy eigenvalues in your calculation, allowing all the bands to be included in the disentanglement procedure. In my work I've never had to specify otherwise.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;inner&lt;/strong&gt; window, specified by &lt;code&gt;dis_froz_min&lt;/code&gt; and &lt;code&gt;dis_froz_max&lt;/code&gt;, is a smaller energy range on which disentanglement isn't allowed to change the band structure. What this is allowed to be depends on the question you're asking, as well as the actual range of the band structure you're looking at. I usually like to make sure the occupied states don't change under disentanglement, so I set &lt;code&gt;dis_froz_max&lt;/code&gt; a little higher than the Fermi energy. I've never had to adjust &lt;code&gt;dis_froz_min&lt;/code&gt;, because the disentanglement usually happens at higher energies, but if you want to ignore shallow core states you might set it some distance or other below the Fermi energy.&lt;/p&gt;&#xA;&lt;h2&gt;2) Orbital projections&lt;/h2&gt;&#xA;&lt;p&gt;This is basically the initial guess for &lt;code&gt;wannier90&lt;/code&gt;. If &lt;code&gt;use_bloch_phases = .TRUE.&lt;/code&gt;, it just uses the canonical Kohn–Sham orbitals; they're not very close to the maximally localized Wannier functions, except maybe for small isolated systems, but the localization procedure is robust enough that it might work anyway.&lt;/p&gt;&#xA;&lt;p&gt;If you have some idea about the chemical bonding happening in your system, you could use the &lt;code&gt;projections&lt;/code&gt; block; for instance onto sp3 orbitals centered between atoms or something. See section 3.1 of the User Guide for this.&lt;/p&gt;&#xA;&lt;p&gt;Personally, I prefer to use set &lt;code&gt;auto_projections = .TRUE.&lt;/code&gt; instead, and then use a method called SCDM, for Selected Columns of the Density Matrix (&lt;a href=&quot;https://arxiv.org/abs/1408.4926&quot; rel=&quot;nofollow noreferrer&quot;&gt;initial theory&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/ct500985f&quot; rel=&quot;nofollow noreferrer&quot;&gt;its peer-reviewed version&lt;/a&gt;, &lt;a href=&quot;https://arxiv.org/abs/1507.03354&quot; rel=&quot;nofollow noreferrer&quot;&gt;extension to bulk systems&lt;/a&gt; (&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0021999116307215&quot; rel=&quot;nofollow noreferrer&quot;&gt;peer reviewed here&lt;/a&gt;), and &lt;a href=&quot;https://arxiv.org/abs/1703.06958&quot; rel=&quot;nofollow noreferrer&quot;&gt;with disentanglement built in&lt;/a&gt; (&lt;a href=&quot;https://epubs.siam.org/doi/abs/10.1137/17M1129696&quot; rel=&quot;nofollow noreferrer&quot;&gt;peer reviewed&lt;/a&gt;)). SCDM automatically selects what are usually reasonably localized initial guesses, based on the nearsightedness principle: Because the one-body density matrix follows an exponential decay&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \rho(\mathbf{r}, \mathbf{r}') \sim e^{-\lvert \mathbf{r} - \mathbf{r}' \rvert}, $$&lt;/span&gt;&#xA;you can perform a QR decomposition with column pivoting and get a few columns of &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r},\mathbf{r'})$&lt;/span&gt; that are fairly localized orbitals. In my experience, SCDM orbitals work really nicely as initial guesses for MLWFs. &lt;a href=&quot;https://arxiv.org/abs/1909.00433&quot; rel=&quot;nofollow noreferrer&quot;&gt;This 2020 paper by Vitale and coworkers&lt;/a&gt; demonstrates the usefulness of SCDM as an automatable initial-guess generator.&lt;/p&gt;&#xA;&lt;p&gt;The actual SCDM calculation is done in &lt;code&gt;pw2wannier90&lt;/code&gt;; see section 3.5 of the user guide linked above.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-05-05T16:32:56.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10851" PostTypeId="1" CreationDate="2023-05-05T17:03:06.877" Score="2" ViewCount="182" Body="&lt;p&gt;I am doing a relax calculations of a 160 gold atom cubic cell using 126GB of RAM space on one node using quantum espresso. but the calculations fails with out-of-memory error.&#xA;I have tried using disk_io = none, but to no success.&lt;/p&gt;&#xA;&lt;p&gt;Similar systems have been worked on using VASP, what other ways are there to solve this issue. Also tried using one cpu in mpirun.&lt;/p&gt;&#xA;&lt;p&gt;here is the control section of my input file for your reference&#xA;&amp;amp;CONTROL&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;disk_io       = none&#xA;calculation   = &amp;quot;relax&amp;quot;&#xA;forc_conv_thr =  1.00000e-03&#xA;max_seconds   =  8.64000e+04&#xA;nstep         = 100&#xA;pseudo_dir    = &amp;quot;./pseudo&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and K points are 3 3 1.&lt;/p&gt;&#xA;" OwnerUserId="7149" LastActivityDate="2023-05-05T17:03:06.877" Title="Running out of RAM memory in relax calculation using Quantum Espresso" Tags="|vasp|quantum-espresso|plane-waves|" AnswerCount="0" CommentCount="3" ClosedDate="2023-05-22T15:06:24.073" ContentLicense="CC BY-SA 4.0" />
  <row Id="10852" PostTypeId="1" AcceptedAnswerId="10856" CreationDate="2023-05-04T19:22:54.233" Score="9" ViewCount="719" Body="&lt;p&gt;The python code is &lt;a href=&quot;https://github.com/MaximeLee/qmodelling/blob/main/examples/dft/H2_RHF_STO3G_V2.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I tried to do a DFT calculation for H2 Restricted Hartree-Fock with Local Density Approximation. The optimization is a scf-loop with Lagrange-multiplier only. I use the same atomic orbitals as the STO3G ab initio computation counterpart.&#xA;I get the following Energy plot :&#xA;&lt;a href=&quot;https://i.stack.imgur.com/HYqly.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HYqly.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My guess is that the exchange(-correlation) energy/operator computation is not good since I am using Riemann integrals (uniform cubes formed with a uniform point grid) to compute it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How are computed exchange-correlation integrals usually? Via Gauss quadrature? Analytic integration if possible?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you have any questions, dont hesitate.&lt;/p&gt;&#xA;" OwnerUserId="7151" OwnerDisplayName="mle" LastEditorUserId="7151" LastEditDate="2023-05-20T17:12:48.143" LastActivityDate="2023-05-20T17:12:48.143" Title="Usual way of computing exchange-correlation potential on a simple case H2 (RKS, LDA)" Tags="|density-functional-theory|quantum-chemistry|python|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10853" PostTypeId="2" ParentId="10846" CreationDate="2023-05-06T08:03:07.873" Score="3" Body="&lt;p&gt;Since you have not mentioned the CIF ID of your crystal, I took a random crystal structure from  Crystallography Open Database with CIF ID: &lt;a href=&quot;https://www.crystallography.net/cod/2008748.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;2008748&lt;/a&gt; with which I will answer both your questions 1 and 2.&lt;/p&gt;&#xA;&lt;h2&gt;Initalise the crystal structure:&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.io.cif import CifParser&#xA;from pymatgen.analysis.local_env import CrystalNN&#xA;&#xA;parser = CifParser('/content/drive/MyDrive/input_files/CIF/2008748.cif')&#xA;structure = parser.get_structures()[0]&#xA;&#xA;nn = CrystalNN()&#xA;adj_matrix = nn.get_bonded_structure(structure)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Answer for Question 1:&lt;/h2&gt;&#xA;&lt;p&gt;The get_nn_info method returns a list of dictionaries, with each dictionary containing information about a nearest neighbor. The weight key of each dictionary contains the bond order of that neighbor, which you can extract and print.&lt;/p&gt;&#xA;&lt;h3&gt;Code:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;nninfo = nn.get_all_nn_info(structure)&#xA;&#xA;for idx, nbrs in enumerate(nninfo):&#xA;    for nidx, nbr in enumerate(nbrs):&#xA;        bond_order = nninfo[idx][nidx]['weight']&#xA;        print(f&amp;quot;The bond order is {bond_order}&amp;quot; )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Answer for Question 2:&lt;/h2&gt;&#xA;&lt;p&gt;This crystal structure has a water molecule. So to extract information related to only the water molecule and not the full structure, you can do as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core.structure import Molecule&#xA;# Define the water molecule&#xA;water = Molecule([&amp;quot;O&amp;quot;, &amp;quot;H&amp;quot;, &amp;quot;H&amp;quot;], [[0.0000, 0.0000, 0.0000], [0.7572, 0.5864, 0.0000], [-0.7572, 0.5864, 0.0000]])&#xA;&#xA;# Find the water molecule in the structure&#xA;for i, site in enumerate(structure):&#xA;    if site.species_string == &amp;quot;O&amp;quot; and all(site.distance_from_point(point) &amp;lt; 10 for point in water.cart_coords):&#xA;        &#xA;        water_center = i&#xA;        break&#xA;&#xA;# Extract the water molecule from the structure&#xA;water_indices = [water_center] + [nn.index for nn in structure.get_neighbors(structure[water_center], 1.5)]&#xA;print(water_indices)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then use just the molecule for your further analysis.&lt;/p&gt;&#xA;&lt;p&gt;Note: I obtained the value 10 by initially checking the distance of the water molecule from the site and then plugged it in.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-06T08:03:07.873" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10854" PostTypeId="2" ParentId="10826" CreationDate="2023-05-06T08:14:09.510" Score="2" Body="&lt;h1&gt;ASE&lt;/h1&gt;&#xA;&lt;p&gt;You can use the &lt;a href=&quot;https://pypi.org/project/ase/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ase&lt;/a&gt; python library to achieve this.&lt;/p&gt;&#xA;&lt;p&gt;I tested the following code with 3 CIF files obtained from the Crystallographic Open Data: &lt;a href=&quot;https://www.crystallography.net/cod/1569089.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1569089&lt;/a&gt;, &lt;a href=&quot;https://www.crystallography.net/cod/1000017.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1000017&lt;/a&gt;, &lt;a href=&quot;https://www.crystallography.net/cod/1000003.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1000003&lt;/a&gt; and it produces their respective XYZ files.&lt;/p&gt;&#xA;&lt;h3&gt;Code&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;&#xA;# Define the list of CIF files to convert&#xA;cif_files = ['1569089.cif', '1000017.cif', '1000003.cif']&#xA;&#xA;for cif_file in cif_files:&#xA;    # Read the CIF file using ASE&#xA;    atoms = read(cif_file)&#xA;&#xA;    # Define the output XYZ file name&#xA;    xyz_file = cif_file.replace('.cif', '.xyz')&#xA;&#xA;    # Write the atoms to the output XYZ file using ASE&#xA;    write(xyz_file, atoms, format='xyz')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-06T08:14:09.510" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10855" PostTypeId="2" ParentId="10815" CreationDate="2023-05-06T08:31:37.757" Score="4" Body="&lt;p&gt;Since you are studying &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt; in an aqueous solution, and the aqueous solution is neutral, there must be counteranion(s), e.g. two monoanions or one dianion, per &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt;. The counterions have to be included because periodic calculations require that the unit cell must be charge neutral. Then, once you include the correct number and type of counterion(s), the extra &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt; is automatically divalent (assuming that the metal does not reduce the &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt;), and you do not need to do anything else to ensure that.&lt;/p&gt;&#xA;&lt;p&gt;Another important thing is that, since &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt; exists as &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn(H2O)6^{2+}}$&lt;/span&gt; in aqueous solution, you must explicitly consider the water molecules (or maybe some of the counterion(s), depending on which counterion you use) that coordinate directly to the &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt;. Moreover, when the counterions have very localized or strong negative charge (e.g. &lt;span class=&quot;math-container&quot;&gt;$\ce{Cl-}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{SO4^{2-}}$&lt;/span&gt;), it is desirable to explicitly solvate the latter as well. Finally, an implicit solvation model should be added to describe the solvent outside the first coordination shell.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-05-06T11:05:36.470" LastActivityDate="2023-05-06T11:05:36.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10856" PostTypeId="2" ParentId="10852" CreationDate="2023-05-06T09:09:53.450" Score="4" Body="&lt;p&gt;The exchange-correlation energy and potential of a molecular calculation are usually integrated on a grid that is dense near nuclei (to integrate the nuclear cusps accurately) and sparse far from nuclei (to save computational cost). Since the grid spacing is non-uniform, the grid points near the nuclei have to receive smaller weights, and the points far from the nuclei receive larger weights.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, consider an atomic calculation. It is very natural to perform the integration in polar coordinates, using the position of the atomic nucleus as the origin. In many (maybe most) quantum chemistry programs, the radial integration is done with &lt;a href=&quot;https://en.wikipedia.org/wiki/Gaussian_quadrature&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian quadrature&lt;/a&gt;, after a &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/108/8/3226/182288/An-adaptive-numerical-integrator-for-molecular&quot; rel=&quot;nofollow noreferrer&quot;&gt;nonlinear coordinate transformation&lt;/a&gt; that makes the radial grid very dense near &lt;span class=&quot;math-container&quot;&gt;$r=0$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is the distance of the grid point to the nucleus) and sparse when &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; is large. The angular (i.e. &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt;) integration is usually done with &lt;a href=&quot;https://en.wikipedia.org/wiki/Lebedev_quadrature&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lebedev quadrature&lt;/a&gt;, which is an efficient quadrature that exactly integrates spherical harmonics up to a high degree, just as the Gaussian quadrature exactly integrates polynomials up to a high degree. Integrating under polar coordinates not only utilizes and keeps all relevant spherical symmetries, but also allows us to separate out the radial degree of freedom, and therefore apply well-known techniques to put more grid points near the nuclei while still being able to assign suitable weights to the grid points.&lt;/p&gt;&#xA;&lt;p&gt;Doing the integrations for molecules is more complicated, since it is no longer possible to separate out the radial degrees of freedom. The usual strategy is to partition the integrand as a sum of atomic contributions, using some smoothened analog of the well-known &lt;a href=&quot;https://en.wikipedia.org/wiki/Voronoi_diagram&quot; rel=&quot;nofollow noreferrer&quot;&gt;Voronoi partitioning&lt;/a&gt;, and integrate each contribution using the atomic grid of the corresponding atom (which is constructed according to the previous paragraph). One early example is the &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/88/4/2547/91134/A-multicenter-numerical-integration-scheme-for&quot; rel=&quot;nofollow noreferrer&quot;&gt;Becke partitioning&lt;/a&gt;, which is later improved by the &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/0009261496006008?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;Stratmann-Scuseria-Frisch (SSF) partitioning&lt;/a&gt;, that has better numerical stability and costs much less in calculating the weights of the molecular grid points.&lt;/p&gt;&#xA;&lt;p&gt;There are a few more techniques for reducing the number of grid points for a given integration accuracy, such as using small Lebedev grids for very small and very large &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, and large Lebedev grids for intermediate &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; (where an accurate angular integration is more important). These kind of grid optimizations can go up to quite elaborate levels, as exemplified by &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/155/10/104109/1013244/An-improved-chain-of-spheres-for-exchange&quot; rel=&quot;nofollow noreferrer&quot;&gt;the newest ORCA grids&lt;/a&gt;. Some earlier protocols for optimizing the molecular grids can be found in the reference list of this paper as well.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-05-06T09:09:53.450" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10857" PostTypeId="1" CreationDate="2023-05-06T13:21:13.473" Score="1" ViewCount="110" Body="&lt;p&gt;Currently, I'm studying (again from zero and more in detail) Hartree Fock (HF) method, specifically the Restricted Hartree Fock (RHF).&lt;br /&gt;&#xA;I'm following two books:&lt;br /&gt;&#xA;&amp;quot;Introduction to Computational Chemistry&amp;quot; (Frank Jensen 2nd edition)&lt;br /&gt;&#xA;&amp;quot;Computational Chemistry, Introduction to the Theory and Applications of Molecular Quantum Mechanics&amp;quot; (Errol G. Lewars 2nd edition)&lt;/p&gt;&#xA;&lt;p&gt;Both books describe the method starting from the Slater determinant of N (N = n° of electrons) Molecular Orbitals (MOs), in this way all the MOs are occupied. Then they generalize to the case where we have M &amp;gt; N MOs, so some will be empty.&lt;br /&gt;&#xA;But this last point is not well explained, I would like to understand this passage in detail, so I ask for an explanation or some references (books or articles ...).&lt;/p&gt;&#xA;" OwnerUserId="5294" LastActivityDate="2023-05-06T13:21:13.473" Title="Hartree Fock method" Tags="|reference-request|hartree-fock|" AnswerCount="0" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="10858" PostTypeId="2" ParentId="10836" CreationDate="2023-05-07T02:05:34.397" Score="6" Body="&lt;p&gt;CASTEP allows you to give it any k-points you like, and I expect other simulations codes do as well. All you need are the k-point coordinates and the integration weights, and the DFT software should handle the rest.&lt;/p&gt;&#xA;&lt;p&gt;I can imagine it might be tricky to do a tetrahedral integration method for the Brillouin zone integration, but for the common Fourier integration as long as you have the spatial weighting it should just work.&lt;/p&gt;&#xA;&lt;p&gt;As a side note, these &amp;quot;nonuniform grids&amp;quot; are superpositions of uniform grids, so although CASTEP won't generate the Fairey grid directly, you can just ask it to generate several Monkhorst-Pack sets and then give the union of those points as a k-point list. The only non-trivial part is devising the appropriate weights, but I'm sure there are Voronoi libraries you could use to do that for you.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-05-07T02:05:34.397" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10859" PostTypeId="1" AcceptedAnswerId="10860" CreationDate="2023-05-07T08:49:44.513" Score="7" ViewCount="780" Body="&lt;p&gt;I used openbabel to convert the .cif files to .smi. Here are parts of the .smi corresponding to two .cif files (I have many .cif files):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[C](=[C]\F)\F.C(=C(\[C][C]O[Zn@]12O[C](c3ccc([C]4O[Zn](O[C](c5ccc(C(=O)O[Zn]([O])O[C](c6ccc(C(=O)O[Zn](OC(=O)c7ccc(C(=O)O2)cc7)[O])cc6)O[Zn]O[C])cc5)O[Zn]O[Zn]O4)O[C][C]/C(=C(\[C][C]/C(=[C]/F)/F)/F)/F)cc3)O[Zn]([O])O1)/F)(\[C][C]/C(=C(\[C])/F)/F)/F.c12C(=O)O[Zn](O[C])OC(=O)c3ccc([C](O[Zn@@]4([O])O[C](c5ccc([C]6O[Zn](O[C](c7ccc(C(=O)O[Zn](OC(=O)c(cc1)cc2)O[C])cc7)O[Zn]O[Zn]O6)[O])cc5)O[Zn](O[C][C]/C(=C(\[C])/F)/F)O4)O[Zn])cc3.[C]/C(=C(\[C])/F)/F.[C]/C(=C(\[C])/F)/F.[C]/C(=C(\[C])/F)/F.[C]/C(=[C]/F)/F.[C](=[C]\F)\F.[C](=[C]\F)\F.[C](=[C]\F)\F.[C](=[C]\F)\F.[C](=[C]\F)\F.[C](=[C]\F)\F.[C](=O)[O].[C](=O)[O].[O]  str_m1_o1_o2_f0_pcu.sym.6&#xA;&#xA;C(=[CH])([C])O[C]CC.[C](=[CH])OCCC.c12[C]3O[Zn](O[C][C]/C=C(\[C])/OCCC)O[C](c4ccc(C(=O)O[Zn]([O])OC(=O)c5ccc(C(=O)O[Zn]([O])(OC(=O)c6ccc([C](O[Zn@]7(O[C](c(cc1)cc2)O[Zn]([O])O7)O[C][C]/C=[C]/OCCC)O[Zn][O])cc6)[O])cc5)cc4)O[Zn]O[C]([C]/C=[C]/O[C]CC)O[Zn]O3.c12[C]3O[Zn@@](O[C][C]/C=C(\[C])/OCCC)(O[Zn]O3)O[C](c3ccc([C](O[Zn](O[C](c4ccc(C(=O)O[Zn](OC(=O)c5ccc(C(=O)O[Zn@@]([O])(OC(=O)c(cc1)cc2)O[C][C]/C=C(\[C])/OCCC)cc5)[O])cc4)O[Zn])[O])O[Zn])cc3)O[Zn][O].[C]/C=[C]/O[C]CC.[C]/C=C(\[C])/O[C]CC.[C](/C=[C]/O[C]CC)[C].[C](CC)OC(=[CH])[C].C(=[CH])([C])OCCC.[C](CC)OC(=[CH])[C].[C](CC)O[C]=[CH].[C](=[CH])OCCC.[C](=[CH])OCCC.[C]=O.[C](=O)[O].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H].[H]   str_m1_o1_o2_f0_pcu.sym.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, I converted them to .pkl file, but when I tried to load the .pkl file, I get this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smi2pkl.py:16 in &amp;lt;module&amp;gt;&#xA;    qm9_smiles = pkl.load(f)&#xA;&#xA;UnpicklingError: invalid load key, '['.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the snippet of code I used for the conversion of .smi to .pkl:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with open(out_path, &amp;quot;wb&amp;quot;) as f:&#xA;    pkl.dump(file_path, f, protocol=pkl.HIGHEST_PROTOCOL) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any insight is welcome. Thank you in advance&lt;/p&gt;&#xA;" OwnerUserId="7074" LastEditorUserId="7" LastEditDate="2023-05-07T20:16:04.110" LastActivityDate="2023-05-08T17:13:34.367" Title="How to generate the SMILES for .cif files correctly and how do I generate .pkl or .pickle file out of these SMILES" Tags="|python|cif|smiles|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10860" PostTypeId="2" ParentId="10859" CreationDate="2023-05-07T10:54:17.930" Score="6" Body="&lt;p&gt;Say I have a SMI file (&lt;code&gt;smiles.smi&lt;/code&gt;) containing these SMILES:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CC1=CC=C(C=C1)C2=CC(=C(C=C2)Cl)NC3=NC(=NC(=N3)C4CC4)N=C5C=CC(=NC5)N&#xA;CC1=CC=C(C=C1)S(=O)(=O)NC2=CC(=C(C=C2)C(=O)N3CCN(CC3)C)Cl&#xA;CC(C)(C)C1=CC=C(C=C1)NC(=O)C2=CC=C(C=C2)S(=O)(=O)N&#xA;CC1=CC(=C(C=C1)S(=O)(=O)N)C(=O)NC2=C(C=C(C=C2)Cl)N=C3C=CC(=NC3=N)Br&#xA;CC1=CC=C(C=C1)NC2=NC3=CC=CC=C3N=C2C4CCCC4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now lets create a pickle file using the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pickle&#xA;&#xA;# Open the input SMI file and read its contents&#xA;with open('smiles.smi', 'r') as file:&#xA;    lines = file.readlines()&#xA;&#xA;# Open the output pickle file and write the list of lines&#xA;with open('smiles.pkl', 'wb') as file:&#xA;    pickle.dump(lines, file)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let us now read the pickle file to get back the contents:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with open('smiles.pkl', 'rb') as f:&#xA;  smilesList = pickle.load(f)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will output the contents like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(SmilesList) &#xA;&amp;gt;&amp;gt;&#xA;&#xA;['CC1=CC=C(C=C1)C2=CC(=C(C=C2)Cl)NC3=NC(=NC(=N3)C4CC4)N=C5C=CC(=NC5)N\n',&#xA; 'CC1=CC=C(C=C1)S(=O)(=O)NC2=CC(=C(C=C2)C(=O)N3CCN(CC3)C)Cl\n',&#xA; 'CC(C)(C)C1=CC=C(C=C1)NC(=O)C2=CC=C(C=C2)S(=O)(=O)N\n',&#xA; 'CC1=CC(=C(C=C1)S(=O)(=O)N)C(=O)NC2=C(C=C(C=C2)Cl)N=C3C=CC(=NC3=N)Br\n',&#xA; 'CC1=CC=C(C=C1)NC2=NC3=CC=CC=C3N=C2C4CCCC4\n',&#xA; 'CC1=C(C=C(C=C1)C(=O)NC2=CC(=C(C=C2)Cl)C3=CN=C(N3)C(=O)NC4=CC=C(C=C4)Cl)']&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-07T11:16:55.903" LastActivityDate="2023-05-07T11:16:55.903" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10861" PostTypeId="2" ParentId="10844" CreationDate="2023-05-07T14:12:37.593" Score="2" Body="&lt;p&gt;Currently there is a bug with the &lt;code&gt;Chem.MolFromMol2File&lt;/code&gt;, in latest rdkit version: &lt;code&gt;2023.3.1&lt;/code&gt;, which seems to remove Hydrogens from the molecule when creating a mol object.&lt;/p&gt;&#xA;&lt;p&gt;There is even an open issue on the Github of rdkit. Issue &lt;a href=&quot;https://github.com/rdkit/rdkit/issues/3106&quot; rel=&quot;nofollow noreferrer&quot;&gt;3106&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Code to reproduce bug behaviour:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem.rdMolDescriptors import CalcMolFormula&#xA;import rdkit.Chem as Chem&#xA; &#xA;ligand = Chem.MolFromMol2File('clean_ligand.mol2', removeHs=False)&#xA;CalcMolFormula(ligand)&#xA;# This prints out: C25N4O4-3 which is wrongly removing the Hydrogens even though removeHs is False.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Work-around Hack:&lt;/h3&gt;&#xA;&lt;p&gt;The hack is to read the mol2 file into an rdkit molecule, then convert the rdkit molecule to a PDB, and finally read the PDB back to get the rdkit molecule along including the hydrogens.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit.Chem.rdMolDescriptors import CalcMolFormula&#xA;import rdkit.Chem as Chem&#xA;&#xA;ligand = Chem.MolFromMol2File('clean_lignad.mol2', removeHs=False)&#xA;&#xA;Chem.MolToPDBFile(ligand,'clean_ligand.pdb')&#xA;&#xA;clean_lig_pdb = Chem.MolFromPDBFile('clean_ligand.pdb')&#xA;&#xA;CalcMolFormula(clean_lig_pdb)&#xA;&#xA;# This prints out : C25H19N4O4-3 which now includes the hydrogens &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-07T14:12:37.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10862" PostTypeId="1" CreationDate="2023-05-08T05:57:15.010" Score="2" ViewCount="137" Body="&lt;p&gt;Recently I tried to extract the optical absorption data using Vaspkit (vaspkit.1.3.0/vaspkit.1.3.5]). I performed the optical calculations of one 2d system along with SOC using VASP. While extracting the data, I found that in the REAL.in and IMAG.in files (real and imaginary part of dielectric constant), the energy range from 0 to 23 eV, whereas in the ABSORPTION_2D.dat file, I am getting data in the energy range from 0 to 7 eV only.&#xA;I am not getting why this is happening because, as per my understanding, the absorption coefficient should come in the same range as the real and imaginary part is coming. In the absorption coefficient I am getting the data upto 7 eV only.&#xA;It would be very kind if anyone please suggest to me why this is happening, or this is the problem with Vaspkit for the 2d system.&lt;/p&gt;&#xA;" OwnerUserId="5256" LastActivityDate="2023-05-08T05:57:15.010" Title="Query about optical data extraction using Vaspkit" Tags="|density-functional-theory|vasp|optical-properties|vaspkit|dielectric-constants|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10863" PostTypeId="1" CreationDate="2023-05-08T08:52:31.680" Score="1" ViewCount="59" Body="&lt;p&gt;Is it possible to make CP2K to print the values of all the defined COLVARs? I did find the following subsection in COLVAR section&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  &amp;amp;COLVAR&#xA;    &amp;amp;DISTANCE&#xA;      ATOMS 50 52&#xA;    &amp;amp;END DISTANCE&#xA;    &amp;amp;PRINT&#xA;      &amp;amp;PROGRAM_RUN_INFO HIGH&#xA;        &amp;amp;EACH&#xA;          MD 1&#xA;          GEO_OPT 1&#xA;        &amp;amp;END EACH&#xA;        LOG_PRINT_KEY .TRUE.&#xA;        FILENAME colvar&#xA;      &amp;amp;END PROGRAM_RUN_INFO&#xA;    &amp;amp;END PRINT&#xA;  &amp;amp;END COLVAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But that did not do anything. I have defined a COLVAR but I have not given a CONSTRAINT to it.&lt;/p&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2023-05-08T08:52:31.680" Title="Getting CP2K to print the COLVAR info" Tags="|cp2k|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-27T16:59:22.490" ContentLicense="CC BY-SA 4.0" />
  <row Id="10864" PostTypeId="1" CreationDate="2023-05-08T11:02:22.570" Score="4" ViewCount="118" Body="&lt;p&gt;I am working on the charge transport calculation, based on the non-equilibrium green function method, for the Hamiltonian with the non-orthogonal basis. Suppose &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; are the Kohn-Sham Hamiltonian and overlap matrice respectively. I want to calculate the transport conductance for the following equation. &lt;span class=&quot;math-container&quot;&gt;$$I=\frac{e_{0}}{\hbar}\int\frac{dE}{2\pi}Tr[{\Sigma}_{\textrm{left}}G^{R}{\Sigma}_{right}G^{A}][n_L(E)-n_R(E)]$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;${\Sigma}_{left}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\Sigma}_{right}$&lt;/span&gt; are the self energy for left and right leads; &lt;span class=&quot;math-container&quot;&gt;$G^{R}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$G^{A}$&lt;/span&gt; are retarded and advanced green function for the scattering zone and they are written as the following equation.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$G^{R}=\left[(i+\varepsilon_{Fermi}) \times S - H - ({\Sigma}_{left}+{\Sigma}_{right}) \right]^{-1}$$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I cannot compute the trace through multipling &lt;span class=&quot;math-container&quot;&gt;${\Sigma}_{left}G^{R}{\Sigma}_{right}G^{A}$&lt;/span&gt; with the eigen vector because I only have the eigen vector for the whole system; not for the scattering zone.&lt;/p&gt;&#xA;&lt;p&gt;This is why I need to compute the inverse matrix. I am trying to use ZGETRF and ZGETRI subroutines in the MKL library to compute it; however, I find that ZGETRF function, the LU fraction subroutine, gives matrix with zero value on the diagonal part and this makes the following inverse matrix calculation fails with ZGETRI function.&lt;/p&gt;&#xA;&lt;p&gt;When doing the coding for the non-equilibrium green function (NEGF) method, how does one compute such matrix for the non-orthogonal Hamiltonian system? Is there any subroutine to compute the inverse matrix of the complex matrix? Would anyone please give me some hints?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="5" LastEditDate="2023-05-09T01:05:10.573" LastActivityDate="2023-05-09T06:44:05.020" Title="Inverse Matrix Calculation" Tags="|density-functional-theory|mathematical-modeling|electronic-transport|fortran|many-body-physics|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10865" PostTypeId="1" AcceptedAnswerId="10878" CreationDate="2023-05-08T10:05:46.563" Score="5" ViewCount="731" Body="&lt;p&gt;I am modeling molecules as graphs, with nodes as atom types and edges as bond types (single, double, triple). I do not model formal charges or hydrogens explicitly (only heavy atoms). When trying to recover valid RDKit molecules/smiles from the graphs, I fail at molecules with charged atoms. My chemical knowledge is very rusty (pun intended), but I feel like it should be possible to add formal charge where needed using posthoc valence checks when translating graphs to molecules.&lt;/p&gt;&#xA;&lt;p&gt;Following the recommendations on RDKit's &lt;a href=&quot;https://github.com/rdkit/rdkit/wiki/FrequentlyAskedQuestions&quot; rel=&quot;nofollow noreferrer&quot;&gt;FAQ&lt;/a&gt;, I am able to handle cases like &lt;code&gt;C[N+](C)(C)C&lt;/code&gt; (detect nitrogen has a higher valence, 4, than it should, 3, and add a positive charge). Right now I struggle with negative charges. When translating this molecule &lt;code&gt;COC1=CC=C(CCNC(=O)C2=CC=C(OC)C([N+](=O)[O-])=C2)C=C1&lt;/code&gt; to a graph then back to smiles using only positive charge correction, I get this output &lt;code&gt;COC1=CC=C(CCNC(=O)C2=CC=C(OC)C([N+](=O)O)=C2)C=C1&lt;/code&gt; (notice the missing negative charge in the last oxygen. RDKit automatically replaces it with an implicit hydrogen).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there settings/methods within RDKit that I can use to ensure the correct valences?&lt;/strong&gt; I'm hoping there is a way to turn off setting implicit hydrogens and/or automatically assign formal charges.&lt;/p&gt;&#xA;&lt;p&gt;Any pointers would be really helpful.&lt;/p&gt;&#xA;&lt;p&gt;Here is pseudo-code to explain what I am looking for:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# input smiles&#xA;smi = 'NC1=CC(Cl)=CC=C1[N+](=O)[O-]'&#xA;&#xA;# my own modeling of molecules &#xA;graph = get_atom_bond_graph(smi) &#xA;&#xA;# returns an rwmol object from the graph&#xA;mol = get_mol_from_graph(graph)&#xA;&#xA;# smi2 is missing all formal charges =&amp;gt; cannot be sanitized because the valence of N is off&#xA;smi2 = Chem.MolToSmiles(mol) # NC1=CC(Cl)=CC=C1N(=O)O  &#xA;&#xA;# add missing formal charges by checking valence rules &#xA;correct_smiles(mol)&#xA;&#xA;smi3 = Chem.MolToSmiles(mol) # NC1=CC(Cl)=CC=C1[N+](=O)O'&#xA;&#xA;# ... how to get [0-] with posthoc checks?&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is my code for generating graphs in case someone needs it (I am using PyTorch Geometric for creating graphs):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atom_types =  ['Si', 'P', 'N', 'Mg', 'Se', 'Cu', 'S', 'Br', 'B', 'O', 'C', 'Zn', 'Sn', 'F', 'I', 'Cl']&#xA;&#xA;atom_type_offset = 1 # where to start atom type indexing. 1 if modeling no nodes, 0 otherwise&#xA;&#xA;# starting from 1 because considering 0 an edge type (= no edge)&#xA;bond_types = [BT.SINGLE, BT.DOUBLE, BT.TRIPLE]&#xA;bond_type_offset = 1&#xA;&#xA;def get_mol_graph(mol, offset=0):&#xA;    if type(mol)==str: &#xA;        mol = Chem.MolFromSmiles(mol)&#xA;    Chem.Kekulize(mol, clearAromaticFlags=True)&#xA;    Chem.RemoveStereochemistry(mol)&#xA;    &#xA;    m_nodes = get_mol_nodes(mol=mol)&#xA;    m_edge_index, m_edge_attr = get_mol_edges(mol=mol, offset=offset)&#xA;&#xA;    return m_nodes, m_edge_index, m_edge_attr&#xA;&#xA;def get_mol_nodes(mol):&#xA;    atoms = mol.GetAtoms()&#xA;&#xA;    for i, atom in enumerate(atoms):&#xA;        s = atom.GetSymbol()&#xA;        atom_type = torch.tensor([atom_types.index(s)+atom_type_offset], &#xA;                                  dtype=torch.long) # needs to be int for one hot&#xA;        atom_types_ = torch.cat((atom_types_, atom_type), dim=0) if i &amp;gt; 0 else atom_type&#xA;    &#xA;    atom_feats = F.one_hot(atom_types_, num_classes=len(atom_types)+atom_type_offset).float()&#xA;&#xA;    return atom_feats&#xA;&#xA;def get_mol_edges(mol, offset=1):&#xA;    '''&#xA;        Input:&#xA;            offset (optional): default: 1. To account for 'no bond' type.&#xA;    '''&#xA;    for i, b in enumerate(mol.GetBonds()):&#xA;        beg_atom_idx = b.GetBeginAtom().GetIdx()&#xA;        end_atom_idx = b.GetEndAtom().GetIdx()&#xA;&#xA;        e_beg = torch.tensor([beg_atom_idx+offset, end_atom_idx+offset], dtype=torch.long).unsqueeze(-1)&#xA;        e_end = torch.tensor([end_atom_idx+offset, beg_atom_idx+offset], dtype=torch.long).unsqueeze(-1)&#xA;        e_type = torch.tensor([bond_types.index(b.GetBondType())+bond_type_offset, &#xA;                               bond_types.index(b.GetBondType())+bond_type_offset], dtype=torch.long) # needs to be int for one hot&#xA;&#xA;        begs = torch.cat((begs, e_beg), dim=0) if i &amp;gt; 0 else e_beg&#xA;        ends = torch.cat((ends, e_end), dim=0) if i &amp;gt; 0 else e_end&#xA;        edge_type = torch.cat((edge_type, e_type), dim=0) if i &amp;gt; 0 else e_type&#xA;&#xA;    if len(mol.GetBonds())&amp;gt;0:&#xA;        edge_index = torch.cat((begs, ends), dim=1).mT.contiguous()&#xA;        edge_attr = F.one_hot(edge_type, num_classes=len(bond_types)+bond_type_offset).float() # add 1 to len of bonds to account for no edge&#xA;    else: # handle molecules of single atoms&#xA;        edge_index = torch.tensor([]).long().reshape(2,0)&#xA;        edge_attr = torch.tensor([]).float()&#xA;&#xA;    return edge_index, edge_attr&#xA;&#xA;if __name__ == '__main__':&#xA;    smi = 'c1c(Cl)c(Cl)ccc1'&#xA;    nodes, edge_index, edge_attr = get_mol_graph(smi.strip(), offset=0)&#xA;&#xA;    from torch_geometric.data import Data&#xA;&#xA;    data = Data(x=nodes, edge_index=edge_index, edge_attr=edge_attr)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7162" OwnerDisplayName="Njw96" LastEditorUserId="7" LastEditDate="2023-05-11T14:49:26.747" LastActivityDate="2023-05-11T14:49:26.747" Title="Valence correction by adding formal charge in RDKit" Tags="|python|rdkit|smiles|valence-bond-theory|charged-molecules|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10866" PostTypeId="1" CreationDate="2023-05-08T12:21:39.000" Score="1" ViewCount="107" Body="&lt;p&gt;I tried to use the sorption module in materials studio to study the adsorption isotherm of carbon dioxide on FUA zeolite with a silicon aluminum ratio of 1:1. FUA zeolite has balanced its charge by adding 99 Na+. but I don't know how to allocate a certain amount of charge to each atom in the zeolite skeleton and carbon dioxide. Therefore, I automatically allocate it through the COMPASSIII force field. However, my final result shows that the zeolite skeleton carries 96 charges(In theory, the zeolite skeleton should not be charged), and the calculated carbon dioxide adsorption amount is also greater than the experimental value in the literature. Can you provide me with an answer? What should I do?&lt;a href=&quot;https://i.stack.imgur.com/Ibnkz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ibnkz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/TG7fd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TG7fd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7161" LastActivityDate="2023-05-08T12:21:39.000" Title="How to allocate the correct charge in Materials Studio" Tags="|materials-studio|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-20T03:23:31.540" ContentLicense="CC BY-SA 4.0" />
  <row Id="10867" PostTypeId="1" CreationDate="2023-05-08T16:48:20.260" Score="3" ViewCount="89" Body="&lt;h2&gt;Context:&lt;/h2&gt;&#xA;&lt;p&gt;I'm new to OpenMM and transition path sampling (TPS). I tried to set up a two-state TPS with the &lt;code&gt;openpathsampling&lt;/code&gt; python library using the flexible length one-way shooting move. I used the OpenMM engine with the following two options:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;engine_options = {'n_steps_per_frame': 500, # timestep=2fs&#xA;                  'n_frames_max': 1000}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm following the &lt;a href=&quot;https://github.com/openpathsampling/ops_tutorial/blob/main/1_tps_sampling_tutorial.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;ops tutorial&lt;/a&gt;. I set the integration timestep to be 2 fs in the integrator. As I set the number of integration steps per returned snapshot to be 500, I think the frame interval should be 1 ps.&lt;/p&gt;&#xA;&lt;p&gt;From what I understand, the first option controls the elapsed time between returned frames, and the second one limits the length of returned trajectories. But it seems that I still get paths longer than 1 ns in the resulting ensemble:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/a4GKL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a4GKL.png&quot; alt=&quot;pathlengthdistribution&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Question:&lt;/h2&gt;&#xA;&lt;p&gt;I'm a bit confused about how the &lt;code&gt;'n_frames_max'&lt;/code&gt; works. Does ops not stop the integration and abort/reject the move if a new path exceeds this length limit?&lt;/p&gt;&#xA;&lt;h2&gt;Code :&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;from openmm import app&#xA;import openmm as mm&#xA;import openmm.unit as unit&#xA;import openmmtools&#xA;&#xA;import openpathsampling as ops&#xA;import openpathsampling.engines.openmm as ops_openmm&#xA;&#xA;&#xA;gro = app.GromacsGroFile(os.path.join(md_path, 'nvt.gro'))&#xA;top = app.GromacsTopFile(os.path.join(md_path, 'topol.top'), &#xA;                         periodicBoxVectors=gro.getPeriodicBoxVectors(),&#xA;                         includeDir=path_to_gmx)&#xA;system = top.createSystem(nonbondedMethod=app.PME,&#xA;                          nonbondedCutoff=1.0*unit.nanometers,&#xA;                          constraints=app.HBonds, &#xA;                          rigidWater=True,&#xA;                          ewaldErrorTolerance=0.0005)&#xA;integrator = openmmtools.integrators.VVVRIntegrator(&#xA;    temperature=340*unit.kelvin,&#xA;    collision_rate=1.0/unit.picoseconds,&#xA;    timestep=2.0*unit.femtoseconds)&#xA;integrator.setConstraintTolerance(0.00001)&#xA;&#xA;openmm_properties = {'DeviceIndex':'2'}&#xA;platform = mm.openmm.Platform.getPlatformByName('CUDA')&#xA;engine_options = {'n_frames_max': 1000,&#xA;                  'n_steps_per_frame': 500}&#xA;ops_topology = ops_openmm.tools.topology_from_pdb(os.path.join(md_path, 'nvt.gro'))&#xA;engine = ops_openmm.Engine(&#xA;    topology=ops_topology, &#xA;    system=system, &#xA;    integrator=integrator, &#xA;    openmm_properties=openmm_properties,&#xA;    options=engine_options&#xA;).named('CLN_Openmm_engine')&#xA;engine.initialize(platform)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6983" LastEditorUserId="6687" LastEditDate="2023-05-12T09:25:43.880" LastActivityDate="2023-05-12T09:25:43.880" Title="OpenMM engine options in openpathsampling (OPS) python library" Tags="|python|openpathsampling|openmm|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-01T17:49:46.403" ContentLicense="CC BY-SA 4.0" />
  <row Id="10868" PostTypeId="2" ParentId="10859" CreationDate="2023-05-08T17:13:34.367" Score="2" Body="&lt;p&gt;From a copy-paste of the two SMILES strings presented e.g. into ChemDraw (a &lt;a href=&quot;https://chemdrawdirect.perkinelmer.cloud/js/sample/index.html#&quot; rel=&quot;nofollow noreferrer&quot;&gt;test page&lt;/a&gt;, structure -&amp;gt; load SMILES) which not only are separate (hence the joining period in the SMILES string), but symmetry independent.&lt;/p&gt;&#xA;&lt;p&gt;If you can access COD's &lt;code&gt;codtools&lt;/code&gt; (&lt;a href=&quot;http://wiki.crystallography.net/cod-tools/&quot; rel=&quot;nofollow noreferrer&quot;&gt;description&lt;/a&gt;) which are packaged for Linux Debian/Ubuntu (e.g., Debian's &lt;a href=&quot;https://tracker.debian.org/pkg/cod-tools&quot; rel=&quot;nofollow noreferrer&quot;&gt;tracker&lt;/a&gt;), you can attempt the conversions of the .cif into an .sdf file on the CLI.  For example with entry &lt;a href=&quot;http://www.crystallography.net/cod/2312069.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;COD 2312069&lt;/a&gt; to redirect the output into an intermediate container file:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-shell prettyprint-override&quot;&gt;&lt;code&gt;$ codcif2sdf 2312069.cif &amp;gt; out.sdf&#xA;1 molecule converted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Subsequently, you can represent them as SMILES string e.g., with OpenBabel (&lt;a href=&quot;https://github.com/openbabel/openbabel/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub repository&lt;/a&gt;, the &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/ReleaseNotes/ob310.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;latest documentation&lt;/a&gt; - which equally offers an interface to Python, and can be accessed from the CLI (hence the following equally is accessible to Python's &lt;code&gt;psopen&lt;/code&gt;, and &lt;code&gt;subprocess&lt;/code&gt;), too e.g. as&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-shell prettyprint-override&quot;&gt;&lt;code&gt;$ obabel out.sdf -ocan&#xA;Fc1c(F)c(C(=O)[O])c(c(c1F)F)F.O=N(=O)c1ccc(cc1)N1CC[NH2]CC1 2312069&#xA;1 molecule converted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or to split it into separate molecules' SMILES by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ obabel out.sdf -ocan --separate&#xA;Fc1c(F)c(C(=O)[O])c(c(c1F)F)F   2312069#1&#xA;O=N(=O)c1ccc(cc1)N1CC[NH2]CC1   2312069#2&#xA;2 molecules converted&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, &lt;code&gt;-ocan&lt;/code&gt; requests the program to describe the &lt;em&gt;output&lt;/em&gt; molecules as &lt;em&gt;canonical&lt;/em&gt; SMILES (because the program equally offers &lt;em&gt;universal&lt;/em&gt;, and &lt;em&gt;inchified&lt;/em&gt; SMILES, too [&lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/FileFormats/SMILES_format.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference&lt;/a&gt;]). Equivalent in result, however yielding a permanent record to the last instruction is&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-shell prettyprint-override&quot;&gt;&lt;code&gt;$ obabel out.sdf -ocan --separate -O result.smi&#xA;2 molecules converted&#xA;$ cat result.smi &#xA;Fc1c(F)c(C(=O)[O])c(c(c1F)F)F   2312069#1&#xA;O=N(=O)c1ccc(cc1)N1CC[NH2]CC1   2312069#2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1206" LastActivityDate="2023-05-08T17:13:34.367" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10869" PostTypeId="1" AcceptedAnswerId="10879" CreationDate="2023-05-08T17:15:57.680" Score="4" ViewCount="597" Body="&lt;p&gt;As a basic example, I want to build a defect MgO unit cell within ASE. From VASP the input is simple:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Mg4O8&#xA;1.00&#xA;5.40  0.00  0.00&#xA;0.00  5.40  0.00&#xA;0.00  0.00  5.40&#xA;&#xA;4 8&#xA;Direct&#xA;0.10  0.10  0.10&#xA;0.50  0.50  0.00&#xA;0.50  0.00  0.50&#xA;0.00  0.50  0.50&#xA;0.25  0.25  0.25&#xA;0.25  0.25  0.75&#xA;0.25  0.75  0.25&#xA;0.25  0.75  0.75&#xA;0.75  0.75  0.75&#xA;0.75  0.75  0.25&#xA;0.75  0.25  0.75&#xA;0.75  0.25  0.25 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Looking into the ASE code, I have come across the &lt;code&gt;ase.build.bulk&lt;/code&gt; function.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ase.build.bulk(name, crystalstructure=None, a=None, b=None, c=None, *, alpha=None, covera=None, u=None, orthorhombic=False, cubic=False, basis=None)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I have to specify the crystal structure, and I have no control over ionic positions.&lt;/p&gt;&#xA;&lt;p&gt;Is there another way I can create an ASE cell object by providing the unit cell dimensions and the exact coordinates?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="3770" LastEditDate="2023-05-09T15:31:00.783" LastActivityDate="2023-05-09T15:31:00.783" Title="How to build a unit cell in ASE?" Tags="|python|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10870" PostTypeId="5" CreationDate="2023-05-08T18:39:55.683" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://openmm.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://openmm.org/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/OpenMM&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/OpenMM&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-05-08T18:39:55.683" LastActivityDate="2023-05-08T18:39:55.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10871" PostTypeId="4" CreationDate="2023-05-08T18:39:55.683" Score="0" Body="Questions about or related to OpenMM." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-05-08T18:39:55.683" LastActivityDate="2023-05-08T18:39:55.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10873" PostTypeId="2" ParentId="10822" CreationDate="2023-05-08T21:47:44.463" Score="2" Body="&lt;p&gt;For any reaction, the forward barrier height must be equal to the reverse barrier height plus free energy change (or minus, depending on signs). Violating this would break detailed balance.&lt;/p&gt;&#xA;&lt;p&gt;However, separately fitting configurational energies &lt;em&gt;and&lt;/em&gt; barrier heights &lt;em&gt;in all directions&lt;/em&gt; as a function of the cluster polynomials is likely to violate this relationship.&lt;/p&gt;&#xA;&lt;p&gt;The kinetically-resolved activation barrier is a way to automatically conserve this relationship, by only fitting a direction-independent barrier to the cluster polynomials and entirely attributing directional energetics to the configurational energies (hence, &amp;quot;kinetically-resolved&amp;quot;, in that these are barriers preserving only the kinetic drivers of selectivity between pathways but not the energetic drivers).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-05-08T21:47:44.463" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10874" PostTypeId="1" CreationDate="2023-05-09T02:12:31.963" Score="6" ViewCount="153" Body="&lt;p&gt;If a scan is performed over two CVs, or collective variables (bond lengths here), does the code simultaneously step through both of the CVs or does it step through the first one, and scan the second CV at each point of the first CV?&lt;/p&gt;&#xA;" OwnerUserId="7166" LastEditorUserId="5" LastEditDate="2023-05-09T18:11:43.153" LastActivityDate="2023-05-09T18:11:43.153" Title="Scanning two bond lengths G-16" Tags="|quantum-chemistry|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10875" PostTypeId="2" ParentId="502" CreationDate="2023-05-09T03:17:15.877" Score="6" Body="&lt;p&gt;I might be late to the party, but I have recently developed a Python package &lt;a href=&quot;https://asm-dtu.gitlab.io/acat/&quot; rel=&quot;noreferrer&quot;&gt;ACAT&lt;/a&gt; that can help people with similar problems of building surface adsorption models. The package is interfaced with the popular atomistic modelling package &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/&quot; rel=&quot;noreferrer&quot;&gt;ASE&lt;/a&gt;, and supports a wide variety of molecules, surfaces (e.g. fcc/bcc/hcp structures with various Miller indices) and even nanoparticles (fcc/icosahedron/decahedron).&lt;/p&gt;&#xA;&lt;p&gt;Let me start by addressing your question specifically. You want to &amp;quot;model a random distribution of molecules attached to a surface&amp;quot;, but oftentimes it is necessary to consider the following constraints to the randomness:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;When molecules are attached to a surface, they prefer to only adsorb at the high-symmetry sites, i.e. ontop/bridge/hollow sites.&lt;/li&gt;&#xA;&lt;li&gt;Even if one wants to generate a dense packing of molecules, it can become unphysical if the molecules are too close to each other (or even overlapping).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Therefore, to achieve what you want in a semi-automated fashion, you will need&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;a tool to generate the surface&lt;/li&gt;&#xA;&lt;li&gt;a tool to automatically identify all high-symmetry adsorption sites on a given surface structure&lt;/li&gt;&#xA;&lt;li&gt;a tool to add adsorbates randomly to the high-symmetry sites with certain constraints&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A surface can be either generated by ASE or read in from a structure file, then we can use ACAT for the 2nd and 3rd needs. As an example, I will show here the Python code for generating a random coverage of CO molecules on an fcc(211) stepped Ni surface. First, we can generate the surface using ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc211&#xA;&#xA;slab_211 = fcc211('Ni', (6,3,4), vacuum=5.)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then we can identify all high-symmetry adsorption sites on the fcc(211) surface using ACAT:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.adsorption_sites import SlabAdsorptionSites&#xA;&#xA;sas_211 = SlabAdsorptionSites(slab_211, surface='fcc211')&#xA;&#xA;# You can also print out the information of each site&#xA;sites_211 = sas_211.get_sites()&#xA;for i, site in enumerate(sites_211):&#xA;    print('Site {0}: {1}'.format(i, site))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now that we want to generate random adsorbate coverage patterns, I have implemented 2 functions for this purpose:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;code&gt;max_dist_coverage_pattern&lt;/code&gt; uses a clustering algorithm to generate a coverage pattern that maximizes the minimum adsorbate-adsorbate distance given the positions of adsorption sites and the number of adsorbates to be added. For example, we can generate a random CO* coverage pattern on the Ni(211) surface with a coverage of 0.67 ML (monolayer) by:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.build.adlayer import max_dist_coverage_pattern as maxdcp&#xA;from ase.visualize import view&#xA;&#xA;atoms = slab_211.copy()&#xA;model = maxdcp(atoms, adsorbate_species='CO', coverage=0.67, &#xA;               adsorption_sites=sas_211)&#xA;view(model) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this is the top view of the final surface adsorption model that we obtain:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eGZzS.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eGZzS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;code&gt;min_dist_coverage_pattern&lt;/code&gt; maximizes the density of the adsorbates when a minimum adsorbate-adsorbate distance constraint is given. Note that the number of adsorbates generated by this function is not fixed. For example, we can generate a random CO* coverage pattern on the Ni(211) surface with a minimum adsorbate-adsorbate distance of 1.8 Å:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.build.adlayer import min_dist_coverage_pattern as mindcp&#xA;from ase.visualize import view&#xA;&#xA;atoms = slab_211.copy()&#xA;model = mindcp(atoms, adsorbate_species='CO',&#xA;               min_adsorbate_distance=1.8,&#xA;               adsorption_sites=sas_211)&#xA;view(model) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this is the top view of the final surface adsorption model that we obtain:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/2zIL1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2zIL1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we want to generate multiple random coverage patterns, we can simply use a for loop:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;images = []&#xA;for _ in range(100):&#xA;    atoms = slab_211.copy()&#xA;    model = mindcp(atoms, adsorbate_species='CO', &#xA;                   min_adsorbate_distance=1.8,&#xA;                   adsorption_sites=sas_211)&#xA;    images.append(model)&#xA;view(images) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For more usage of the ACAT package, I strongly recommend this &lt;a href=&quot;https://gitlab.com/asm-dtu/acat/-/blob/master/notebooks/acat_tutorial.ipynb&quot; rel=&quot;noreferrer&quot;&gt;Jupyter notebook tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-05-09T09:57:23.313" LastActivityDate="2023-05-09T09:57:23.313" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10876" PostTypeId="2" ParentId="10864" CreationDate="2023-05-09T06:20:25.540" Score="1" Body="&lt;p&gt;This sounds like you are doing something wrong.&lt;/p&gt;&#xA;&lt;p&gt;Even in a non-orthogonal basis the diagonal &lt;span class=&quot;math-container&quot;&gt;$\mathbf S$&lt;/span&gt; matrix has the identity matrix in the diagonal.&lt;/p&gt;&#xA;&lt;p&gt;There could be a number of reasons why this occurs:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Your basis set orbitals are too close together resulting in a singular matrix (non-invertible)&lt;/li&gt;&#xA;&lt;li&gt;your imaginary part &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; is too small, or even non-existing. The whole reason for the imaginary part is that one makes the matrix invertible since the energy value will surely not hit an eigenvalue of the system.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Others have noted that calculating the eigenspectrum is the way to go, but as the OP says, this is an open system and calculating the eigenspectrum in this, infinite, open system is too costly compared to the inversion. Hence one will always calculate the inverse like this. Additionally the imaginary part would/should cause the matrix to be non-singular.&lt;/p&gt;&#xA;&lt;p&gt;It is hard to know what is causing this since we don't know the full details of your code, calling convention etc.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-05-09T06:44:05.020" LastActivityDate="2023-05-09T06:44:05.020" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10877" PostTypeId="2" ParentId="10874" CreationDate="2023-05-09T08:36:29.083" Score="6" Body="&lt;p&gt;When you are scanning two bond lengths in Gaussian, you step once through the first bond scan, and complete stepping through the second bond scan. For example, consider the case where you are scanning the bond lengths of C-Cl and C-H in chloromethane. The code will first increment the bond length of C-Cl, and will then scan the C-H bond while keeping C-Cl bond constant. This will result in a 2D scan, with one axis corresponding to C-Cl bond and other corresponding to C-H bond.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-05-09T08:36:29.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10878" PostTypeId="2" ParentId="10865" CreationDate="2023-05-09T09:28:00.587" Score="3" Body="&lt;p&gt;After some investigation, I don't think it's possible to add formal charge posthoc without modeling hydrogens explicitly. Here is an example to illustrate:&lt;/p&gt;&#xA;&lt;p&gt;Consider both molecules &lt;code&gt;C[Mg+]&lt;/code&gt; and &lt;code&gt;C[MgH]&lt;/code&gt;. My graph only knows that both molecules contain one carbon and one magnesium. When turning the graph to a molecule, RDKit notices that the valence of both atoms is lower than it should be, and adds explicit hydrogens to both. This means that whether my input is &lt;code&gt;C[Mg+]&lt;/code&gt; or &lt;code&gt;C[MgH]&lt;/code&gt; I would always recover &lt;code&gt;C[MgH]&lt;/code&gt; from my graph.&lt;/p&gt;&#xA;&lt;p&gt;Other examples illustrating the issue include: &lt;code&gt;[NH4+]&lt;/code&gt; vs &lt;code&gt;N&lt;/code&gt;, and &lt;code&gt;COC[P+](C1=CC=CC=C1)(C1=CC=CC=C1)C1=CC=CC=C1&lt;/code&gt; vs &lt;code&gt;COC[PH](C1=CC=CC=C1)(C1=CC=CC=C1)C1=CC=CC=C1&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I am still trying to understand how implicit hydrogens are added to molecules in general to see if there is away to differentiate between cases needing a formal charge vs implicit hydrogen. For now distinguishing the two does not seem to be possible.&lt;/p&gt;&#xA;" OwnerUserId="7162" LastActivityDate="2023-05-09T09:28:00.587" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10879" PostTypeId="2" ParentId="10869" CreationDate="2023-05-09T09:36:39.643" Score="6" Body="&lt;p&gt;In ASE, this can be done in a rather straightforward way. You just need to build an &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ase.Atoms&lt;/code&gt;&lt;/a&gt; object. For your structure, you can use the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;&#xA;atoms = Atoms(symbols='Mg4O8',&#xA;              scaled_positions=[[0.10, 0.10, 0.10],&#xA;                                [0.50, 0.50, 0.00],&#xA;                                [0.50, 0.00, 0.50],&#xA;                                [0.00, 0.50, 0.50],&#xA;                                [0.25, 0.25, 0.25],&#xA;                                [0.25, 0.25, 0.75],&#xA;                                [0.25, 0.75, 0.25],&#xA;                                [0.25, 0.75, 0.75],&#xA;                                [0.75, 0.75, 0.75],&#xA;                                [0.75, 0.75, 0.25],&#xA;                                [0.75, 0.25, 0.75],&#xA;                                [0.75, 0.25, 0.25]],&#xA;              cell=[[5.40, 0.00, 0.00],&#xA;                    [0.00, 5.40, 0.00],&#xA;                    [0.00, 0.00, 5.40]],&#xA;              pbc=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that if you have Cartesian coordinates instead of fractional coordinates, use &lt;code&gt;positions=[...]&lt;/code&gt; instead of &lt;code&gt;scaled_positions=[...]&lt;/code&gt;. The coordinates should be written in the same order as your &lt;code&gt;symbols&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-05-09T09:51:03.853" LastActivityDate="2023-05-09T09:51:03.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10880" PostTypeId="1" CreationDate="2023-05-09T13:19:18.207" Score="1" ViewCount="66" Body="&lt;p&gt;I am running a CP2K NVT molecular dynamics simulation and want to apply an angle constraint between three atoms. In my previous simulations, I used a bond constraint between two atoms, and it was easy to obtain the constraint force by multiplying the output Lagrange multiplier with the constrained bond length. However, I am not sure how to calculate the constraint force when I have an angle constraint instead of a bond constraint.&lt;/p&gt;&#xA;&lt;p&gt;Can anyone suggest a way to obtain the constraint force for an angle constraint in CP2K NVT MD simulation? Any help would be greatly appreciated. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="1195" LastActivityDate="2023-05-09T13:19:18.207" Title="How to calculate constraint force for angle constraint in CP2K NVT MD simulation?" Tags="|cp2k|aimd|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-27T16:59:29.223" ContentLicense="CC BY-SA 4.0" />
  <row Id="10881" PostTypeId="1" CreationDate="2023-05-09T16:36:55.180" Score="5" ViewCount="98" Body="&lt;p&gt;The real-time evolution of a quantum system described by the state &lt;span class=&quot;math-container&quot;&gt;$\psi(t)$&lt;/span&gt; is formally given by,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \psi(t+\Delta t) = \exp^{- i \hat{H} \Delta t / \hbar} \psi(t)\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For dynamical simulations of quantum systems, the time-scale &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; is set by some energy scale characteristic of the system. For instance, if one is studying dynamics of a conjugated carbon system, one can choose &lt;span class=&quot;math-container&quot;&gt;$\Delta t$&lt;/span&gt; to be a few orders of magnitude smaller than typical carbon-carbon bond stretching frequency (as an example, with apologies for the self-reference, see section 6.2 of &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jpca.3c00988&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Now suppose one is interested in finding the ground state of some Hamiltonian using imaginary time evolution. An interesting question to ask is whether there is an equivalent way of choosing an upper bound for the time-step? If one seeks to calculate the ground state of molecular Hydrogen, does it still make sense to ignore the imaginary unit &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and set the bound using Hydrogen bond oscillation frequency?&lt;/p&gt;&#xA;&lt;p&gt;Another approach might be to think in terms of temperature. I know imaginary time-evolution can be thought of in a temperature scale but I do not know how to connect the dots and rationalise it this way.&lt;/p&gt;&#xA;&lt;p&gt;Edit : Adding some context to the problem as per suggestions of @NikeDattani, I'm new to imaginary time evolution algorithms and am wondering whether there is a physically inspired time-scale for the general problem. However, I'm ultimately attempting to understand how &lt;a href=&quot;https://arxiv.org/pdf/1901.07653.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantum imaginary time evolution&lt;/a&gt; works.&lt;/p&gt;&#xA;" OwnerUserId="7045" LastEditorUserId="7045" LastEditDate="2023-05-09T20:39:36.760" LastActivityDate="2023-05-09T20:39:36.760" Title="How can one determine the time-step for imaginary time evolution?" Tags="|computational-chemistry|quantum-chemistry|mathematical-modeling|quantum-mechanics|quantum-dynamics|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10882" PostTypeId="1" AcceptedAnswerId="10892" CreationDate="2023-05-09T16:50:26.333" Score="3" ViewCount="90" Body="&lt;p&gt;I have been trying to write a basic &lt;a href=&quot;https://github.com/HemanthHaridas/plank.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;HF code&lt;/a&gt; that can compute the MOs and total energy of a molecule. I followed the following &lt;a href=&quot;https://www.mathematica-journal.com/2012/02/16/evaluation-of-gaussian-molecular-integrals/&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference&lt;/a&gt; for overlap and kinetic integrals. During a conversation with a developer of Libint, I was told that I should try implementing spherical harmonics into the code.  I found this &lt;a href=&quot;http://users.df.uba.ar/dmitnik/estructura3/bases/biblio/transformationGaussianSpherical.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; for the conversion from cartesian to spherical harmonics. Any beginner or intermediate level pointers on how the integrals are computed in spherical harmonics would be much appreciated. I am not looking for specific implementation details, but for the general algorithm.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-05-09T18:30:05.580" LastActivityDate="2023-05-10T17:06:38.980" Title="Molecular integrals in spherical harmonics?" Tags="|python|reference-request|mathematical-modeling|hartree-fock|integrals|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10883" PostTypeId="1" CreationDate="2023-05-10T10:40:26.240" Score="1" ViewCount="175" Body="&lt;p&gt;I am trying to calculate the electron localization function (ELF) using Quantum ESPRESSO.&#xA;However, I realize that it is not possible to correctly calculate it with either the Ultrasoft or the PAW pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;With ultrasoft pseudos, the method is &lt;em&gt;not implemented fully&lt;/em&gt;, while with the PAW pseudopotentials, as per an old answer &lt;a href=&quot;https://narkive.com/10wFnvfE:2.689.38&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, seems to indicate that ELF with PAW is also not implemented.&lt;/p&gt;&#xA;&lt;p&gt;As detailed in the answer &lt;a href=&quot;https://narkive.com/F2GAQGzz:2.375.462&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;: &amp;quot;The correct calculation of the ELF with ultrasoft pseudopotentials or with PAW requires to compute the contribution from augmentation charges.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;Can someone guide that how this contribution maybe computed? Alternatively, is there an other software that can the ELF correctly for a periodic system?&lt;/p&gt;&#xA;&lt;p&gt;Any insights provided would be much helpful.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastActivityDate="2023-05-10T10:40:26.240" Title="What is the correct method to calculate ELF?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-08T00:19:14.030" ContentLicense="CC BY-SA 4.0" />
  <row Id="10884" PostTypeId="1" AcceptedAnswerId="10920" CreationDate="2023-05-10T10:42:13.830" Score="6" ViewCount="345" Body="&lt;p&gt;I am having trouble getting the SMILES strings and drawings of the different resonance structutes of a molecule with RDKit. I found an &lt;a href=&quot;https://sourceforge.net/p/rdkit/mailman/message/36034365/&quot; rel=&quot;nofollow noreferrer&quot;&gt;old example&lt;/a&gt; online doing this but it doesn't seem to work with the current version of RDKit (2023-03-01).&lt;/p&gt;&#xA;&lt;p&gt;Here is an example with 1,2-Dichlorobenzene:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chen&#xA;from rdkit.Chem.Draw import rdMolDraw2D&#xA;&#xA;# smiles = ['c1c(Cl)c(Cl)ccc1', 'C1C(Cl)=C(Cl)C=CC=1', 'C1=C(Cl)C(Cl)=CC=C1']&#xA;smiles = ['c1c(Cl)c(Cl)ccc1']&#xA;smi = smiles[0]&#xA;mol = Chem.MolFromSmiles(smi)&#xA;suppl = Chem.ResonanceMolSupplier(mol, Chem.KEKULE_ALL)&#xA;print(f'# of kekule forms {len(suppl)}\n')&#xA;&#xA;for i, m in enumerate(suppl):&#xA;    print(f'Resonance structure #{i}\n')&#xA;    smi_kkl = Chem.MolToSmiles(m) # change to turn kekulization on&#xA;    print(f'smi_kkl: {smi_kkl}\n') &#xA;    ## newer way of plotting does not work either&#xA;    # d = rdMolDraw2D.MolDraw2DCairo(350, 300)&#xA;    # d.drawOptions().maxFontSize = 20&#xA;    # rdMolDraw2D.PrepareAndDrawMolecule(d, mol, kekulize=False) # change to turn kekulization on&#xA;    # d.FinishDrawing()&#xA;    # d.WriteDrawingText(os.path.join(parent_path, 'figures', f'{smi}_{i}.png'))&#xA;&#xA;    img = Draw.MolToImage(mol, kekulize=False) # change to turn kekulization on&#xA;    img.save(os.path.join(parent_path, 'figures', f'{smi}_{i}.png'))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# of kekule forms 2&#xA;&#xA;Resonance structure #0&#xA;&#xA;smi_kkl: Clc1ccccc1Cl # should be C1C(Cl)=C(Cl)C=CC=1&#xA;&#xA;Resonance structure #1&#xA;&#xA;smi_kkl: Clc1c(Cl)cccc1 # should be C1=C(Cl)C(Cl)=CC=C1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the images both use aromatic rings instead of the kekule forms. If I turn on kekulization where specified in the code, I only get one kekulized structure for both resonance objects (in this case &lt;code&gt;ClC1=CC=CC=C1Cl&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Any ideas how to get the two structures in SMILES and images?&lt;/p&gt;&#xA;" OwnerUserId="7162" LastEditorUserId="6687" LastEditDate="2023-05-11T07:31:31.803" LastActivityDate="2023-05-15T08:17:40.660" Title="Cannot draw resonance structure (kekule forms) of a molecule in RDKit" Tags="|python|rdkit|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10885" PostTypeId="1" CreationDate="2023-05-10T10:48:20.597" Score="6" ViewCount="125" Body="&lt;p&gt;The adsorption energies of atoms or molecules on any surface in a standalone DFT are inherently devoid of any temperature influence. so, let's say an atom/molecule has very weak binding, in physisorption range. Wouldn't at room temperature the binding be actually Nil or higher?&lt;/p&gt;&#xA;" OwnerUserId="5619" LastEditorUserId="5619" LastEditDate="2023-06-15T06:34:45.493" LastActivityDate="2023-06-15T06:34:45.493" Title="How the adsorption energies calculated at DFT level, is valid at finite temperatures?" Tags="|density-functional-theory|vasp|computational-chemistry|ab-initio-calculations|adsorption|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10886" PostTypeId="1" AcceptedAnswerId="10887" CreationDate="2023-05-10T13:07:45.093" Score="10" ViewCount="603" Body="&lt;p&gt;My background is in &lt;em&gt;ab initio&lt;/em&gt; calculations of atoms and molecules, and I consider myself to have a good understanding of the underlying quantum theory of electronic structure and electronic spectra when it comes to interpreting such calculations. I'm trying to understand some solid state physics now, and I have a hard time interpreting electronic band structures.&lt;/p&gt;&#xA;&lt;p&gt;For example, let's take a plot from &lt;a href=&quot;https://arxiv.org/pdf/1101.3957.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bCakK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bCakK.png&quot; alt=&quot;Enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I think I have an understanding on what the &lt;em&gt;x&lt;/em&gt; axis entails when it comes to the paths in the reciprocal space (although I find it very hard to have an intuition about it), and the meaning of the energy is clear. I can also identify conducting and insulating materials by the absence/presence of the gap at 0 eV.&lt;/p&gt;&#xA;&lt;p&gt;However, I am having difficulty in understanding the rest of the information content in the plot.&#xA;Below I list out questions I have:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;What is the meaning of the fact that there's a crossing around&#xA;-8 eV at the L point?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;What is that the gap between the two unoccupied levels varies heavily&#xA;along the k point path?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Can I extract any interesting observation from the plot, apart from&#xA;checking whether the material is conducting or not?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="6687" LastEditDate="2023-05-11T11:48:45.247" LastActivityDate="2023-05-11T11:48:45.247" Title="Difficulty in interpreting electronic band structures in solid state physics" Tags="|density-functional-theory|band-structure|solid-state-physics|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10887" PostTypeId="2" ParentId="10886" CreationDate="2023-05-10T13:46:26.837" Score="10" Body="&lt;p&gt;One important step is to know how the Fermi energy (&lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt;) was treated. Some authors like to shift the band diagram after making &lt;span class=&quot;math-container&quot;&gt;$E_F=0$&lt;/span&gt; (as looks like it was the case in the reference you cited) but others (as my self) prefer to let the &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; with the calculated value. As the Fermi energy is an indicator of electron population, the energy levels below &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; represents occupied states whereas energy levels above &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; represents empty states. The occupied states are called valence band and the empty ones, conduction bands.&lt;/p&gt;&#xA;&lt;p&gt;Saying that, things we look for in the band diagram:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Alignment of the botom of the conduction band with the top of the valence band. If both (bottom and top) occurs at the same k-point, the material has a direct band gap. If the bottom occurs at a k-point different than the top, then the material has an indirect band gap. This has implications in the optical properties of the material, for example.&lt;/li&gt;&#xA;&lt;li&gt;The value of the band gap at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point (the central point of the Brillouin zone) or at the correspondig k-point for indirect band gap materials. This can be used to characterize the material as metal, semimetal, semiconductor or insulator.&lt;/li&gt;&#xA;&lt;li&gt;The parabolicity of the band around the bottom/top region. This is used to calculate the &lt;a href=&quot;https://en.wikipedia.org/wiki/Effective_mass_(solid-state_physics)&quot; rel=&quot;noreferrer&quot;&gt;efective mass&lt;/a&gt; of the carriers (electrons and holes). This is used in Semiconductor Physics.&lt;/li&gt;&#xA;&lt;li&gt;It is possible to do a band diagram colored accordingly with the contribution of each orbital or even of each atom. This is called fat band diagram (take a look at the discussion &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1203/24&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The analysis of electronic band together with the Partial Density of States (PDOS) or Total Density of States (DOS) can be used in electronic band engineering: modifying the material until you got the intended electronic properties.&lt;/p&gt;&#xA;&lt;p&gt;As transport and optical properties are mainly related with the electrons in the valence/conduction bands, in general, the analisys is focused on that bands. The same for the k-poins related with the band gap (the central &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point or the indirect k-point.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-10T13:46:26.837" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10888" PostTypeId="1" AcceptedAnswerId="10891" CreationDate="2023-05-10T14:05:52.470" Score="4" ViewCount="1354" Body="&lt;p&gt;I am doing a simulation of multiple polymers which are named with segnames U(integer). During the course of simulation two polymers U5 and U10 interact with each other. However, because of periodic boundary conditions when I measure the accessible area or radius of gyration I get unnaturally large values.&lt;/p&gt;&#xA;&lt;p&gt;I have tried to wrap periodic boundaries by running the command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pbc wrap -all -centersel &amp;quot;segname U5 U10&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My reasoning is I want the U5 U10 aggregate at the center of the simulation box. However, this causes the polymer to fragment and again does not give proper result. Can you suggest proper pbc wrap arguments for this situtation?&lt;/p&gt;&#xA;" OwnerUserId="1605" LastActivityDate="2023-05-12T04:47:47.353" Title="VMD Periodic boundary wrapping using pbc wrap" Tags="|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10889" PostTypeId="2" ParentId="10884" CreationDate="2023-05-10T15:30:09.343" Score="5" Body="&lt;p&gt;I did some digging around and found a hack. The &lt;code&gt;Chem.MolToSmiles&lt;/code&gt; function has an argument &lt;code&gt;rootedAtAtom&lt;/code&gt; which if non-negative, forces the SMILES to start at a particular atom. It Defaults to -1.&lt;/p&gt;&#xA;&lt;p&gt;So I tried to set it to the various atom ids present in the molecule like shown below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;smiles = ['c1c(Cl)c(Cl)ccc1']&#xA;smi = smiles[0]&#xA;mol = Chem.MolFromSmiles(smi)&#xA;suppl = Chem.ResonanceMolSupplier(mol, Chem.KEKULE_ALL)&#xA;&#xA;&#xA;for i in range(8):&#xA;  print (Chem.MolToSmiles(suppl[0], kekuleSmiles=True, rootedAtAtom=i))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This prints out:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C1=C(Cl)C(Cl)=CC=C1&#xA;C1(Cl)=CC=CC=C1Cl&#xA;ClC1=CC=CC=C1Cl&#xA;C1(Cl)=CC=CC=C1Cl&#xA;ClC1=CC=CC=C1Cl&#xA;C1=C(Cl)C(Cl)=CC=C1&#xA;C1=CC=C(Cl)C(Cl)=C1&#xA;C1=CC=C(Cl)C(Cl)=C1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Out of which the first one: &lt;code&gt;C1=C(Cl)C(Cl)=CC=C1&lt;/code&gt; is exactly one of the SMILES of the resonance structures which you were expecting.&lt;/p&gt;&#xA;&lt;p&gt;And regarding drawing the structures, I noticed something hacky, which I will show below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;s1 = Chem.MolToSmiles(suppl[1], kekuleSmiles=True, rootedAtAtom=0)&#xA;print(s1)&#xA;Chem.MolFromSmiles(s1)&#xA;&#xA;&amp;gt;&amp;gt; C1=C(Cl)C(Cl)=CC=C1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/QKSXm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QKSXm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;s2 = Chem.MolToSmiles(suppl[1], kekuleSmiles=False, rootedAtAtom=0)&#xA;print(s2)&#xA;Chem.MolFromSmiles(s2)&#xA;&#xA;&amp;gt;&amp;gt; c1cccc(Cl)c1Cl&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7FwT8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7FwT8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-10T16:51:20.840" LastActivityDate="2023-05-10T16:51:20.840" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10890" PostTypeId="2" ParentId="10885" CreationDate="2023-05-10T16:26:22.837" Score="4" Body="&lt;p&gt;If you are calculating the interaction energy between a surface (like graphene) and a molecule (like benzene), the interaction energy that you get is different from the binding free energy because you are missing the term corresponding to T&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;S in the energy. If you need to calculate the binding free energy using DFT, you will need to compute the phonon dispersion at that point, and add that to the interaction energy to get the binding free energy. Alternatively, you can use MD simulations to compute the binding free energies.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-05-10T16:26:22.837" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10891" PostTypeId="2" ParentId="10888" CreationDate="2023-05-10T16:31:09.317" Score="4" Body="&lt;p&gt;If you need to wrap a simulation trajectory using VMD, and want to ensure that the molecules remain as is (and no artifacts are introduced) use the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pbc wrap -all -centersel &amp;quot;selection&amp;quot; -center com -compound residue&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here the -compund residue flag instructs VMD to wrap the trajectory in such a way that atoms of one residue id does not get broken while wrapping is performed.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-05-12T04:47:47.353" LastActivityDate="2023-05-12T04:47:47.353" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10892" PostTypeId="2" ParentId="10882" CreationDate="2023-05-10T17:06:38.980" Score="3" Body="&lt;p&gt;Molecular integrals aren't typically computed in spherical harmonics. What you do instead is to compute the integrals in the Cartesian representation, where they are separable, and then transform to the spherical representation &lt;strong&gt;as quickly as possible&lt;/strong&gt; your algorithm allows, since there are &lt;span class=&quot;math-container&quot;&gt;$n_c=\lambda(\lambda+1)/2$&lt;/span&gt; cartesians but only &lt;span class=&quot;math-container&quot;&gt;$n_s=2\lambda+1$&lt;/span&gt; spherical harmonics for angular momentum &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What this means is that when computing the &lt;span class=&quot;math-container&quot;&gt;$(pq|rs)$&lt;/span&gt; integrals, you convert an index to the spherical basis as soon as possible, so that the recursions for the remaining indices only deal with &lt;span class=&quot;math-container&quot;&gt;$n_s$&lt;/span&gt; components for each transformed index instead of &lt;span class=&quot;math-container&quot;&gt;$n_c$&lt;/span&gt; components for untransformed indices.&lt;/p&gt;&#xA;&lt;p&gt;In practice, it is hard to say at which point the transformation should be done, since this is where all algorithms are different: McMurchie-Davidson, Obara-Saika / Head-Gordon-Pople, and Rys quadrature all have different recursion relations and different scaling with the total angular momentum.&lt;/p&gt;&#xA;&lt;p&gt;For a concise introduction to molecular integrals, I recommend you consult &amp;quot;the purple Bible&amp;quot; i.e. &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9781119019572&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecular Electronic-Structure Theory by Helgaker, Jørgensen, and Olsen&lt;/a&gt;, which discusses the various algorithms at length. Its chapter 9 is dedicated to molecular integral evaluation and is almost a 100 pages!&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-10T17:06:38.980" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10893" PostTypeId="1" AcceptedAnswerId="10894" CreationDate="2023-05-10T21:39:17.387" Score="4" ViewCount="337" Body="&lt;p&gt;I want to do an ionic relaxation of just the ions inside my unit cell (not the cell dimensions), with Quantum Espresso through ASE. However, I have only been able to find structure optimization methods in the [documentation][1] that:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Use ASE's own algorithms (not the QE methods one).&lt;/li&gt;&#xA;&lt;li&gt;Do not allow me to control what to relax and what to freeze (ie, cell dimensions, ions, etc)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;So far this is what I have been able to produce.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.calculators.espresso import Espresso&#xA;from ase.constraints import UnitCellFilter&#xA;from ase.optimize import LBFGS&#xA;from ase import Atoms&#xA;&#xA;pseudopotentials = {'Cl': 'Cl.pz-nl-rrkjus_psl.1.0.0.UPF',&#xA;                            'Na': 'Na.pz-spnl-rrkjus_psl.1.0.0.UPF'}&#xA;&#xA;symbols = [&amp;quot;Na&amp;quot;, &amp;quot;Na&amp;quot;, &amp;quot;Na&amp;quot;, &amp;quot;Na&amp;quot;,&#xA;           &amp;quot;Cl&amp;quot;, &amp;quot;Cl&amp;quot;, &amp;quot;Cl&amp;quot;, &amp;quot;Cl&amp;quot;,]&#xA;cell = [[5.69, 0.00, 0.00],&#xA;        [0.00, 5.69, 0.00],&#xA;        [0.00, 0.00, 5.69]]&#xA;scaled_positions = [[0.00, 0.00, 0.00],&#xA;                    [0.00, 0.50, 0.50],&#xA;                    [0.50, 0.00, 0.50],&#xA;                    [0.50, 0.50, 0.00],&#xA;                    [0.50, 0.50, 0.50],&#xA;                    [0.50, 0.00, 0.00],&#xA;                    [0.00, 0.50, 0.00],&#xA;                    [0.00, 0.00, 0.50]]&#xA;&#xA;rocksalt = Atoms(symbols=symbols,&#xA;                 scaled_positions=scaled_positions,&#xA;                 cell=cell,&#xA;                 pbc=True)&#xA;&#xA;calc = Espresso(pseudopotentials=pseudopotentials,&#xA;                tstress=True,&#xA;                tprnfor=True,&#xA;                kpts=(1, 1, 1))&#xA;rocksalt.calc = calc&#xA;&#xA;ucf = UnitCellFilter(rocksalt)&#xA;opt = LBFGS(ucf)&#xA;opt.run(fmax=0.005)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I was wondering if there is something along the lines of:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;rocksalt.relaxation(cell=(x=False, y=False, z=False), ions=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;[1][[https://wiki.fysik.dtu.dk/ase/ase/optimize.html]&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2023-05-11T03:05:09.677" LastActivityDate="2023-10-24T11:44:45.220" Title="Ionic relaxation with ASE (Atomic Simulation Environment)" Tags="|python|atomic-simulation-environment|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10894" PostTypeId="2" ParentId="10893" CreationDate="2023-05-11T02:56:55.187" Score="5" Body="&lt;p&gt;When you use an ASE optimizer to relax your structure, it doesn't relax your unit cell by default. It is only necessary to use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html#ase.constraints.UnitCellFilter&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;UnitCellFilter&lt;/code&gt;&lt;/a&gt; when you &lt;strong&gt;want to&lt;/strong&gt; simultaneously optimize the ionic positions and unit cell. In that case, I often use the improved version &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html#the-expcellfilter-class&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ExpCellFilter&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-05-11T02:56:55.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10895" PostTypeId="1" AcceptedAnswerId="10897" CreationDate="2023-05-11T08:17:54.153" Score="4" ViewCount="208" Body="&lt;p&gt;I am working on condensate studies and I did form a globular condensate of the polymer system using lammps. I wanted to find out the number density of condensate with respect to the radius as bins to find out the core density and surface density of the polymer. I tried using this python script but couldn't able to fetch any results. If anyone in the forum could help me out with this?&lt;/p&gt;&#xA;&lt;p&gt;the code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;# Define the bin size&#xA;dr = 10  # adjust as needed&#xA;&#xA;# Read in the coordinates from the Lammps trajectory file&#xA;# assuming x, y, z coordinates are in columns 1, 2, and 3&#xA;coords = np.loadtxt('test2.xyz', usecols=(1, 2, 3))&#xA;&#xA;# Compute the distance of each atom from the center of the sphere&#xA;distances = np.linalg.norm(coords, axis=1)&#xA;&#xA;# Bin the distances into r bins of equal size&#xA;bins = np.arange(0, np.max(distances) + dr, dr)&#xA;print(len(bins))&#xA;digitized = np.digitize(distances, bins)&#xA;&#xA;print (len(digitized))&#xA;# Count the number of atoms in each bin&#xA;counts = np.bincount(digitized)&#xA;print(len(counts))&#xA;&#xA;# Divide the count by the volume of each bin to get the number density&#xA;volumes = 4/3 * np.pi * (bins[1:]**3 - bins[:-1]*3)&#xA;print(len(volumes))&#xA;number_density = counts / volumes&#xA;&#xA;# Compute the average number density over the trajectory&#xA;average_number_density = np.mean(number_density)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The xyz file looks like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;14000&#xA; generated by VMD&#xA;  11       186.343002      194.738007      171.914001&#xA;  3        184.606995      195.947006      168.707001&#xA;  18       185.141006      197.257996      165.209000&#xA;  5        187.419006      199.007996      162.889008&#xA;  11       189.791000      198.328003      159.753006&#xA;  9        192.240005      195.429993      159.931000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I need to get the density of the molecules from the inner core to the outer surface by binning the spherical polymer number density vs R (bins).&lt;/p&gt;&#xA;&lt;p&gt;I got the error operands could not be broadcast together with shapes (51,) (50,)&lt;/p&gt;&#xA;" OwnerUserId="7181" LastEditorUserId="7181" LastEditDate="2023-05-11T11:48:56.760" LastActivityDate="2023-05-11T14:27:56.053" Title="How to compute the density of the spherical polymer using radius as a bin from the lammps trajectory?" Tags="|python|lammps|density-of-states|polymers|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10896" PostTypeId="1" CreationDate="2023-05-11T08:39:15.733" Score="3" ViewCount="43" Body="&lt;p&gt;I am working on a 2D system where geometric and magnetic isomers are energetically very close to each other (orders of meV). I am interested in optical absorbance spectra using GW+BSE approach but I am curious whether its possible to create average absorption spectra since in a real life situation the material would most likely be composed of several domains with different magnetic motifs and not just the one with the lowest energy.&lt;/p&gt;&#xA;&lt;p&gt;I know that there's a way with Boltzmann probability &lt;span class=&quot;math-container&quot;&gt;$p_i$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;p_i = \mathrm{exp}\left(-\frac{E_i}{k_{\mathrm{B}}T}\right)/\left[\sum_j\mathrm{exp}\left(-\frac{E_j}{k_{\mathrm{B}}T}\right)\right],&#xA;$$&lt;/span&gt;&#xA;but is there a way to do it such that it includes zero point energies, or a entirely different way altoghether.&lt;/p&gt;&#xA;" OwnerUserId="7182" LastActivityDate="2023-05-11T08:39:15.733" Title="Weighted average optical spectra in VASP" Tags="|vasp|optical-properties|2d-lattice|gw-bse|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10897" PostTypeId="2" ParentId="10895" CreationDate="2023-05-11T12:25:11.990" Score="5" Body="&lt;h3&gt;Understanding the Error:&lt;/h3&gt;&#xA;&lt;p&gt;Reason you get the error is because you are trying to divide two numpy arrays of unequal shape.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;len(volumes)=32&#xA;len(counts)=33&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Therefore, I changed the code for the volume calculation such that volume also has the same shape as the bins. By this I was able to get &lt;code&gt;average_number_density&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Below are the lines I changed in the volume calculation.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;offset = bins.tolist()[-1]*3&#xA;volumes = 4/3 * np.pi * np.array([ i**3- offset for i in bins])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives the &lt;code&gt;average_number_density = 1.3246815571536801e-09&lt;/code&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Full Code for completeness:&lt;/h3&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Define the bin size&#xA;dr = 10 # adjust as needed&#xA;&#xA;# Read in the coordinates from the Lammps trajectory file&#xA;# assuming x, y, z coordinates are in columns 1, 2, and 3&#xA;coords = np.loadtxt('test2.xyz', usecols=(1, 2, 3))&#xA;&#xA;# Compute the distance of each atom from the center of the sphere&#xA;distances = np.linalg.norm(coords, axis=1)&#xA;&#xA;# Bin the distances into r bins of equal size&#xA;bins = np.arange(0, np.max(distances) + dr, dr)&#xA;digitized = np.digitize(distances, bins)&#xA;&#xA;# Count the number of atoms in each bin&#xA;counts = np.bincount(digitized)&#xA;&#xA;# Divide the count by the volume of each bin to get the number density&#xA;offset = bins.tolist()[-1]*3&#xA;# volumes = 4/3 * np.pi * (bins[1:]**3 - bins[:-1]*3) &#xA;volumes = 4/3 * np.pi * np.array([ i**3- offset for i in bins]) &#xA;&#xA;number_density = counts / volumes&#xA;&#xA;# Compute the average number density over the trajectory&#xA;average_number_density = np.mean(number_density)&#xA;&#xA;print(average_number_density)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the XYZ file I used: (Notice the first two lines are taken out, otherwise numpy will complain of not having data in all columns)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  11       186.343002      194.738007      171.914001&#xA;  3        184.606995      195.947006      168.707001&#xA;  18       185.141006      197.257996      165.209000&#xA;  5        187.419006      199.007996      162.889008&#xA;  11       189.791000      198.328003      159.753006&#xA;  9        192.240005      195.429993      159.931000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-11T14:27:56.053" LastActivityDate="2023-05-11T14:27:56.053" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10898" PostTypeId="1" CreationDate="2023-05-11T16:14:54.367" Score="4" ViewCount="645" Body="&lt;p&gt;I want to try using DMol3 software for my research studies of doing optimisations and DFT calculations. Anyways I was unable to find a download link. Is it available for free? if so can anyone please help me with this?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastActivityDate="2023-05-11T17:04:30.923" Title="Can we download DMol3 for free?" Tags="|density-functional-theory|quantum-mechanics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10899" PostTypeId="2" ParentId="10898" CreationDate="2023-05-11T17:04:30.923" Score="5" Body="&lt;p&gt;&lt;a href=&quot;https://www.3ds.com/fileadmin/PRODUCTS-SERVICES/BIOVIA/PDF/biovia-material-studio-dmol3.pdf&quot; rel=&quot;noreferrer&quot;&gt;DMol3&lt;/a&gt; is part of the &lt;a href=&quot;https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/&quot; rel=&quot;noreferrer&quot;&gt;Material Studio&lt;/a&gt; suite from BIOVIA. It is a commercially distributed software which means it is not free.&lt;/p&gt;&#xA;&lt;p&gt;If you want to test it, you can ask for a trial period but, as I remember, the trial license does not permit that you publish any results obtained during the evaluation period.&lt;/p&gt;&#xA;&lt;p&gt;A good news is that you can find plenty of free software that do the same things Dmol3 does. Take a look at the Wiki page &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-11T17:04:30.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10901" PostTypeId="1" CreationDate="2023-05-11T19:16:53.630" Score="3" ViewCount="282" Body="&lt;h2&gt;Preface:&lt;/h2&gt;&#xA;&lt;p&gt;This question is a follow up post from a previous question on MMSE: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10852/usual-way-of-computing-exchange-correlation-potential-on-a-simple-case-h2-rhf&quot;&gt;Usual way of computing exchange-correlation potential on a simple case H2 (RHF, LDA)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The radial variable substitution and the complete method are detailed in the paper: &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/88/4/2547/91134/A-multicenter-numerical-integration-scheme-for&quot; rel=&quot;nofollow noreferrer&quot;&gt;A multicenter numerical integration scheme for polyatomic molecules - The Journal of Chemical Physics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Question:&lt;/h2&gt;&#xA;&lt;p&gt;In the details sub-heading, I calculate the difference between the actual value of the integral (&lt;code&gt;I1&lt;/code&gt;) and the result obtained with quadrature (&lt;code&gt;I2&lt;/code&gt;). This should ideally be zero. That is &lt;code&gt;I1 - I2 = 0.&lt;/code&gt;&#xA;However, I get values that are not 0.&lt;/p&gt;&#xA;&lt;p&gt;So how do I properly integrate with the help of the Lebedev + Gauss-Chebyshev quadrature?&lt;/p&gt;&#xA;&lt;h2&gt;Details:&lt;/h2&gt;&#xA;&lt;p&gt;I will detail the different parts of the code and give the full version at the end.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;Calculations to get the quadrature points :&lt;/h4&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;from numpy.linalg import norm&#xA;pi = np.pi&#xA;&#xA;##########################&#xA;# Quadrature weights/points&#xA;##########################&#xA;&#xA;# for radial component&#xA;Nr = 30&#xA;ii  = np.arange(1,Nr+1).reshape(-1,1) &#xA;sin_i = np.sin(ii*pi/(Nr+1))&#xA;cos_i = np.cos(ii*pi/(Nr+1))&#xA;&#xA;# Chebyshev quadrature points on [-1,1]&#xA;Mu_quadrature = (Nr+1.0-2.0*ii)/(Nr+1.0) + 2.0/pi*(1.0 + 2.0/3.0*sin_i**2)*cos_i*sin_i&#xA;&#xA;# Chebyshev quadrature points on [0, +infty [&#xA;# Bragg-slater Radius for Hydrogen&#xA;rm = 0.35 # Angstrom&#xA;# variable substitution for the radial component &#xA;R_quadrature = rm*(1+Mu_quadrature)/(1-Mu_quadrature)&#xA;&#xA;# Chebyshev quadrature weights&#xA;Wr_quadrature = 16.0/3.0/(Nr+1)*sin_i**4&#xA;&#xA;##########################&#xA;# Quadrature for solid angle / angular coordinates&#xA;##########################&#xA;&#xA;# file containing integration points (theta/phi in deg) and associated weights&#xA;fn = 'lebedenev_quadrature.txt'&#xA;Data = np.loadtxt(fn)&#xA;ThetaPhi_quadrature = Data[:,:2]&#xA;&#xA;# convert to rad&#xA;ThetaPhi_quadrature = ThetaPhi_quadrature*pi/180.0&#xA;Wangular_quadrature = Data[:,2:3]&#xA;&#xA;# make a tensor product of the Quadrature points&#xA;X_spherical_int = np.concatenate([&#xA;        np.tile(R_quadrature,(len(ThetaPhi_quadrature),1)),&#xA;        np.repeat(ThetaPhi_quadrature,len(R_quadrature),axis=0)   &#xA;    ],&#xA;    axis=1&#xA;)&#xA;&#xA;R_int   = X_spherical_int[:,0:1]&#xA;Theta_int = X_spherical_int[:,1:2]&#xA;Phi_int = X_spherical_int[:,2:3]&#xA;&#xA;Mu_int  = (R_int - rm)/(R_int + rm)&#xA;&#xA;Wint = np.concatenate([&#xA;        np.tile(Wr_quadrature,(len(Wangular_quadrature),1)),&#xA;        np.repeat(Wangular_quadrature,len(Wr_quadrature),axis=0)   &#xA;    ],&#xA;    axis=1&#xA;)&#xA;Wint = np.prod(Wint,axis=1,keepdims=True)&#xA;&#xA;X_cartesian_int = np.zeros_like(X_spherical_int)&#xA;R, Theta, Phi = R_int, Theta_int, Phi_int&#xA;Mu = (R - rm)/(R + rm)&#xA;X_cartesian_int[:,0:1] = R*np.cos(Theta)*np.sin(Phi)&#xA;X_cartesian_int[:,1:2] = R*np.sin(Theta)*np.sin(Phi)&#xA;X_cartesian_int[:,2:3] = R*np.cos(Phi)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;lebedenev_quadrature.txt&lt;/code&gt; is a text file containing Lebedev quadrature points obtained from the &lt;a href=&quot;https://people.sc.fsu.edu/%7Ejburkardt/datasets/sphere_lebedev_rule/sphere_lebedev_rule.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SPHERE_LEBEDEV_RULE dataset directory&lt;/a&gt; under the Sample Files section located at the bottom of the page. The file used in this code is &lt;a href=&quot;https://people.sc.fsu.edu/%7Ejburkardt/datasets/sphere_lebedev_rule/lebedev_131.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;lebedev_131.txt&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;Testing Chebyshev quadrature on Gauss integral:&lt;/h4&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;#################################&#xA;# Testing integration&#xA;#################################&#xA;def f(X):&#xA;    return np.exp(-np.sum(X,axis=1,keepdims=True)**2)&#xA;&#xA;# solution&#xA;I1 = np.sqrt(pi)/2&#xA;&#xA;# quadrature&#xA;I2 = np.einsum(&#xA;    'ij,ij',&#xA;    f(R_quadrature)*2.0*rm/(1-Mu_quadrature)**2,&#xA;    Wr_quadrature&#xA;)&#xA;&#xA;print(f'Testing Gauss-Chebyshev quadrature with Gauss Integral :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Testing Gauss-Chebyshev quadrature with Gauss Integral :&#xA; I1 = 0.8862269254527579 | I2 = 0.8862570079725882 | I1-I2 = -3.0082519830276766e-05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;Testing Lebedev quadrature on unit sphere surface :&lt;/h4&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def f(Theta,Phi):&#xA;    return np.ones_like(Theta)&#xA;&#xA;# solution&#xA;I1 = 4*pi #np.exp(-1)*4*pi&#xA;&#xA;# quadrature&#xA;I2 = 4.0*pi*np.einsum(&#xA;    'ij,ij',&#xA;    f(ThetaPhi_quadrature[:,1:2],None),&#xA;    Wangular_quadrature&#xA;)&#xA; &#xA;print(f'Testing Lebedev quadratude with Integral over unit sphere surface :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Testing Lebedev quadrature with Integral over unit sphere surface :&#xA; I1 = 12.566370614359172 | I2 = 12.566370614362953 | I1-I2 = -3.780087354243733e-12&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;And testing both quadrature to compute the volume of unit sphere :&lt;/h4&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;#&amp;quot;&amp;quot;&amp;quot; Unit Sphere&#xA;def f(X):&#xA;    R = norm(X,axis=1,keepdims=True)&#xA;    return np.where(R&amp;lt;=1,1,0)&#xA;I1 = 4/3*pi&#xA;#&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot; Testing with Gauss integral&#xA;def f(X):&#xA;    return np.exp(-norm(X,axis=1,keepdims=True)**2)&#xA;I1 = 4*pi*np.sqrt(pi)/2&#xA;#&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;I2 = 4*pi*np.einsum(&#xA;    'ij,ij',&#xA;    f(X_cartesian_int)*2.0*rm/(1-Mu_int)**2,&#xA;    Wint&#xA;)&#xA;&#xA;print(f'Testing Lebedev + Chebyshev qudrature with Integral over unit sphere volume :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Testing Lebedev + Chebyshev quadrature with Integral over unit sphere volume :&#xA; I1 = 4.1887902047863905 | I2 = 12.623540989301834 | I1-I2 = -8.434750784515444&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h4&gt;Complete code :&lt;/h4&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;from numpy.linalg import norm&#xA;pi = np.pi&#xA;&#xA;##########################&#xA;# Quadrature weights/points&#xA;##########################&#xA;&#xA;# for radial component&#xA;Nr = 30&#xA;ii  = np.arange(1,Nr+1).reshape(-1,1) &#xA;sin_i = np.sin(ii*pi/(Nr+1))&#xA;cos_i = np.cos(ii*pi/(Nr+1))&#xA;&#xA;# Chebyshev quadrature points on [-1,1]&#xA;Mu_quadrature = (Nr+1.0-2.0*ii)/(Nr+1.0) + 2.0/pi*(1.0 + 2.0/3.0*sin_i**2)*cos_i*sin_i&#xA;&#xA;# Chebyshev quadrature points on [0, +infty [&#xA;# Bragg-slater Radius for Hydrogen&#xA;rm = 0.35 # Angstrom&#xA;# variable substitution for the radial component &#xA;R_quadrature = rm*(1+Mu_quadrature)/(1-Mu_quadrature)&#xA;&#xA;# Chebyshev quadrature weights&#xA;Wr_quadrature = 16.0/3.0/(Nr+1)*sin_i**4&#xA;&#xA;##########################&#xA;# Quadrature for solid angle / angular coordinates&#xA;##########################&#xA;&#xA;# file containing integration points (theta/phi in deg) and associated weights&#xA;fn = 'lebedenev_quadrature.txt'&#xA;Data = np.loadtxt(fn)&#xA;ThetaPhi_quadrature = Data[:,:2]&#xA;&#xA;# convert to rad&#xA;ThetaPhi_quadrature = ThetaPhi_quadrature*pi/180.0&#xA;Wangular_quadrature = Data[:,2:3]&#xA;&#xA;# make a tensor product of the Quadrature points&#xA;X_spherical_int = np.concatenate([&#xA;        np.tile(R_quadrature,(len(ThetaPhi_quadrature),1)),&#xA;        np.repeat(ThetaPhi_quadrature,len(R_quadrature),axis=0)   &#xA;    ],&#xA;    axis=1&#xA;)&#xA;&#xA;R_int   = X_spherical_int[:,0:1]&#xA;Theta_int = X_spherical_int[:,1:2]&#xA;Phi_int = X_spherical_int[:,2:3]&#xA;&#xA;Mu_int  = (R_int - rm)/(R_int + rm)&#xA;&#xA;Wint = np.concatenate([&#xA;        np.tile(Wr_quadrature,(len(Wangular_quadrature),1)),&#xA;        np.repeat(Wangular_quadrature,len(Wr_quadrature),axis=0)   &#xA;    ],&#xA;    axis=1&#xA;)&#xA;Wint = np.prod(Wint,axis=1,keepdims=True)&#xA;&#xA;X_cartesian_int = np.zeros_like(X_spherical_int)&#xA;R, Theta, Phi = R_int, Theta_int, Phi_int&#xA;Mu = (R - rm)/(R + rm)&#xA;X_cartesian_int[:,0:1] = R*np.cos(Theta)*np.sin(Phi)&#xA;X_cartesian_int[:,1:2] = R*np.sin(Theta)*np.sin(Phi)&#xA;X_cartesian_int[:,2:3] = R*np.cos(Phi)&#xA;&#xA;#################################&#xA;# Testing integration&#xA;#################################&#xA;def f(X):&#xA;    return np.exp(-np.sum(X,axis=1,keepdims=True)**2)&#xA;&#xA;# solution&#xA;I1 = np.sqrt(pi)/2&#xA;&#xA;# quadrature&#xA;I2 = np.einsum(&#xA;    'ij,ij',&#xA;    f(R_quadrature)*2.0*rm/(1-Mu_quadrature)**2,&#xA;    Wr_quadrature&#xA;)&#xA;&#xA;print(f'Testing Gauss-Chebyshev quadrature with Gauss Integral :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&#xA;def f(Theta,Phi):&#xA;    return np.ones_like(Theta)&#xA;&#xA;# solution&#xA;I1 = 4*pi #np.exp(-1)*4*pi&#xA;&#xA;# quadrature&#xA;I2 = 4.0*pi*np.einsum(&#xA;    'ij,ij',&#xA;    f(ThetaPhi_quadrature[:,1:2],None),&#xA;    Wangular_quadrature&#xA;)&#xA; &#xA;print(f'Testing Lebedev quadrature with Integral over unit sphere surface :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&#xA;#&amp;quot;&amp;quot;&amp;quot; Unit Sphere&#xA;def f(X):&#xA;    R = norm(X,axis=1,keepdims=True)&#xA;    return np.where(R&amp;lt;=1,1,0)&#xA;I1 = 4/3*pi&#xA;#&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot; Testing with Gauss integral&#xA;def f(X):&#xA;    return np.exp(-norm(X,axis=1,keepdims=True)**2)&#xA;I1 = 4*pi*np.sqrt(pi)/2&#xA;#&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;I2 = 4*pi*np.einsum(&#xA;    'ij,ij',&#xA;    f(X_cartesian_int)*2.0*rm/(1-Mu_int)**2,&#xA;    Wint&#xA;)&#xA;&#xA;print(f'Testing Lebedev + Chebyshev qudrature with Integral over unit sphere volume :\n I1 = {I1} | I2 = {I2} | I1-I2 = {I1-I2}\n')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="6687" LastEditDate="2023-05-12T11:52:35.470" LastActivityDate="2023-05-14T11:14:39.820" Title="Becke partitioning : Computing integrals with Lebedev and Gauss-Chebyshev quadrature" Tags="|density-functional-theory|python|integrals|" AnswerCount="2" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10903" PostTypeId="2" ParentId="10901" CreationDate="2023-05-12T07:45:58.453" Score="1" Body="&lt;p&gt;You are missing the key piece of the algorithm: employing Becke's multicenter integration scheme originally described in &lt;a href=&quot;https://doi.org/10.1063/1.454033&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 88, 2547–2553 (1988)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;An integral &lt;span class=&quot;math-container&quot;&gt;$ I =\int f({\bf r}) {\rm d}^3 r $&lt;/span&gt; that contains atomic cusps can be evaluated efficiently by introducing a resolution of the identity &lt;span class=&quot;math-container&quot;&gt;$\sum_{A} w_{A}({\bf r})=1$&lt;/span&gt; with a set of atomic weight functions &lt;span class=&quot;math-container&quot;&gt;$0 \leq w_A({\bf r}) \leq 1$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Inserting this resolution of the identity and rearranging the summation order, the original integral is rewritten as a sum of atomic integrals&#xA;&lt;span class=&quot;math-container&quot;&gt;$ I = \sum_{A} I_{A} $&lt;/span&gt;&#xA;which in turn are given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ I_{A} = \int w_{A}({\bf r}) f({\bf r}) {\rm d}^3 r.  $$&lt;/span&gt;&#xA;The weight functions &lt;span class=&quot;math-container&quot;&gt;$w_A$&lt;/span&gt; are chosen such that these integrals can be efficiently computed using atom-centered coordinates&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ I_{A} = \int w_{A}({\bf r}-{\bf r}_A) f({\bf r}-{\bf r}_A) r_A^2 {\rm d}r_A d\Omega_A,  $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$r^A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\Omega^A$&lt;/span&gt; are the radius and solid angle measured from atom &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;.&#xA;These integrals can now be computed by introducing quadrature grids for the radial &lt;span class=&quot;math-container&quot;&gt;$r_A$&lt;/span&gt; and solid angle &lt;span class=&quot;math-container&quot;&gt;$\Omega_A$&lt;/span&gt; coordinates. The key point here is that the additional &lt;span class=&quot;math-container&quot;&gt;$r_A^2$&lt;/span&gt; factor from the Jacobian kills off any cusp on the nucleus &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, while the weight factors are chosen in a way that off-center cusps are killed off by vanishing &lt;span class=&quot;math-container&quot;&gt;$w_A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There is a lot of flexibility in choosing the weight functions. Becke suggested one way to form &lt;span class=&quot;math-container&quot;&gt;$w_A$&lt;/span&gt;; however, more optimal schemes that converge more rapidly in the radial-angular quadrature have been suggested in later work. For recent work, see e.g. &lt;a href=&quot;https://doi.org/10.1063/1.5049435&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 149, 204111 (2018)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;To compute integrals with atomic quadrature in practice, you can just use &lt;a href=&quot;https://github.com/dftlibs/numgrid&quot; rel=&quot;nofollow noreferrer&quot;&gt;numgrid&lt;/a&gt;, for instance, which already implements all of the necessary equations and gives you the necessary quadature grids and weights when you feed it the atomic coordinates.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-05-12T07:58:58.800" LastActivityDate="2023-05-12T07:58:58.800" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10904" PostTypeId="1" AcceptedAnswerId="10906" CreationDate="2023-05-12T12:18:09.947" Score="4" ViewCount="360" Body="&lt;p&gt;I'm doing simulation with Quantum ESPRESSO, and it's my first time to run it on a server using ssh. I ran some calculations yesterday then I logout using the command &lt;code&gt;exit&lt;/code&gt;, when I checked the calculations today I noticed that &lt;code&gt;file.out&lt;/code&gt; is stuck in the same line sense the morning, so I assumed that the calculation stopped since yesterday after logging out.&lt;/p&gt;&#xA;&lt;p&gt;Can logging out from the server stop the calculation? if yes how can I logout and close my laptop without affecting the calculation?&lt;/p&gt;&#xA;&lt;p&gt;I also want to know how can I check the completed calculations without using &lt;code&gt;nano&lt;/code&gt; command to check if the job is done for each single file?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-05-12T14:46:59.567" Title="Does loging out from the server stop my Quantum ESPRESSO calculations?" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10905" PostTypeId="2" ParentId="10904" CreationDate="2023-05-12T12:30:00.620" Score="1" Body="&lt;p&gt;To run big big Quantum ESPRESSO simulations it is recommended to submit a batch job to the server.&lt;/p&gt;&#xA;&lt;p&gt;If your server is not one of those centrally managed ones, then you should be using terminal multiplexers like &lt;code&gt;tmux&lt;/code&gt; or &lt;code&gt;screen&lt;/code&gt; which allow you to keep programs running even after logging out.&lt;/p&gt;&#xA;" OwnerUserId="7192" LastEditorUserId="6687" LastEditDate="2023-05-12T14:46:59.567" LastActivityDate="2023-05-12T14:46:59.567" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10906" PostTypeId="2" ParentId="10904" CreationDate="2023-05-12T14:01:50.900" Score="4" Body="&lt;p&gt;Question: &lt;strong&gt;Does loging out from the server stop my Quantum ESPRESSO calculations?&lt;/strong&gt;&#xA;Answer: It depends on how you are submitting your jobs.&lt;/p&gt;&#xA;&lt;p&gt;Some examples:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Using &lt;code&gt;mpirun -np 16 pw.x &amp;lt;scf.in&amp;gt; scf.out &amp;amp;&lt;/code&gt; (with the &lt;strong&gt;&amp;amp;&lt;/strong&gt; at the end) will allow you to logout and the job will continue running in the background. Here you can close your laptop.&lt;/li&gt;&#xA;&lt;li&gt;Using &lt;code&gt;mpirun -np 16 pw.x &amp;lt;scf.in&amp;gt; scf.out&lt;/code&gt; (without the &lt;strong&gt;&amp;amp;&lt;/strong&gt; at the end) will kill your job as soon you logout or even close the connection. In order to the job keep running, you have to remains connected to the server, so, closing your laptop will kill the jobs.&lt;/li&gt;&#xA;&lt;li&gt;Using a submission script for the workload manager (Torque, PBS, SLURM, etc.): you can logout and your job will keep running at the background.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Question: &lt;strong&gt;I also want to know how can I check the completed calculations without using nano command to check if the job is done for each single file?&lt;/strong&gt;&lt;br /&gt;&#xA;Answer: It will depend on how you submitted the job.&lt;br /&gt;&#xA;If you used a workloader, then you need to use the command to check jobs. For example, using SLURM: &lt;code&gt;squeue -u $USER&lt;/code&gt;, will return all the jobs, using &lt;code&gt;squeue -u $USER -t RUNNING&lt;/code&gt; will return only the running jobs and using &lt;code&gt;squeue -u $USER -t PENDING&lt;/code&gt; will show you the pending jobs.&lt;br /&gt;&#xA;If you submitted the job as &lt;code&gt;mpirun -np 16 pw.x &amp;lt;scf.in&amp;gt; scf.out &amp;amp;&lt;/code&gt;, for example, using the command &lt;code&gt;ps -U $USER -u $USER u&lt;/code&gt; will return all the process executed by the current user.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-12T14:01:50.900" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10908" PostTypeId="1" AcceptedAnswerId="10912" CreationDate="2023-05-12T15:19:36.570" Score="7" ViewCount="168" Body="&lt;p&gt;Copy from here &lt;a href=&quot;https://mathematica.stackexchange.com/questions/285044/optimal-basis-set-of-gaussian-functions-for-describing-a-quantum-system&quot;&gt;https://mathematica.stackexchange.com/questions/285044/optimal-basis-set-of-gaussian-functions-for-describing-a-quantum-system&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This question arose during the discussion of the previous questions: &lt;a href=&quot;https://mathematica.stackexchange.com/questions/284809/why-does-the-minimum-eigenvalue-change-dramatically-when-one-basis-function-is-a#284841&quot;&gt;https://mathematica.stackexchange.com/questions/284809/why-does-the-minimum-eigenvalue-change-dramatically-when-one-basis-function-is-a#284841&lt;/a&gt; and &lt;a href=&quot;https://mathematica.stackexchange.com/questions/284910/finding-excited-states-using-the-condition-of-wave-functions-orthogonality&quot;&gt;https://mathematica.stackexchange.com/questions/284910/finding-excited-states-using-the-condition-of-wave-functions-orthogonality&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Brief description of the problem:&lt;/p&gt;&#xA;&lt;p&gt;Consider the following system with the Hamiltonian: &lt;span class=&quot;math-container&quot;&gt;$H=-\frac{1}{2}\Delta-\frac{1}{r}+\frac{25}{8}\rho^2-5/2$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$r=(\rho,z,\phi)$&lt;/span&gt; is a coordinate in the cylindrical system. Physically, this Hamiltonian describes a hydrogen atom in a magnetic field equal to 5 (in dimensionless units).&lt;br /&gt;&#xA;In order to solve this problem by the matrix method, it is necessary to choose a set of basis functions. To describe ground and excited states with the z component of the angular momentum m = 0 (1s, 2s, 3d (m = 0), 3s ...), a Gaussian basis set is well suited. Such basis functions have the following form: &lt;span class=&quot;math-container&quot;&gt;$\psi_j=e^{-b_{j} z^2}e^{-a_{j} \rho^2}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$a_{j}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b_{j}$&lt;/span&gt; are parameters. The task is reduced to the correct finding of parameters.&lt;/p&gt;&#xA;&lt;p&gt;The parameters describing the ground state (1s) with high accuracy were found in this work (see here &lt;a href=&quot;https://arxiv.org/abs/1709.05553&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/1709.05553&lt;/a&gt; or here &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/147/24/244108/195534/Accurate-and-balanced-anisotropic-Gaussian-type&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.aip.org/aip/jcp/article/147/24/244108/195534/Accurate-and-balanced-anisotropic-Gaussian-type&lt;/a&gt;). But the basis presented in this article does not describe excited states (2s, 3d (m = 0), 3s ...) well, since there are not enough basis functions to describe them. The basis set parameters presented in this article has a complex structure, so increasing the basis set functions in this case is a difficult task.&lt;/p&gt;&#xA;&lt;p&gt;It seems that a more general way to find the basis set of parameters is presented in this article (see here &lt;a href=&quot;https://drive.google.com/file/d/1q74hAn0UAdNd8DtPkoCsdYPkr61-xhr2/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://drive.google.com/file/d/1q74hAn0UAdNd8DtPkoCsdYPkr61-xhr2/view?usp=sharing&lt;/a&gt; or here &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssb.2220930140&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://onlinelibrary.wiley.com/doi/abs/10.1002/pssb.2220930140&lt;/a&gt;). The sets of parameters that the authors use are geometric progressions: &lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\alpha_j=\alpha_{j-1}(\frac{\alpha_N}{\alpha_1})^{1/(N-1)}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\beta_j=\alpha_{j-1}(\frac{\beta_M}{\beta_1})^{1/(M-1)}$&lt;/span&gt;, &lt;br /&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta_M$&lt;/span&gt; are the first and the last parameters. About finding these parameters, the authors write the following: &amp;quot;the parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta_M$&lt;/span&gt; were varied in a four dimensional optimization search which minimized the sum of the eigen-values of interest&amp;quot; and &amp;quot;We have performed the calculations presented in this paper with a basis with ten Gaussians in the &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; direction and twelve Gaiissians in the z direction, for a total of 120 different basis functions.&amp;quot;. I really don't understand what that means?&lt;/p&gt;&#xA;&lt;p&gt;Energy values from the articles: &lt;br /&gt;&#xA;ground state (1s) = - 1.3793 (exact value = -1.380398866427)&lt;br /&gt;&#xA;the first excited state (2s) = -0.19335 (exact value = -0.193746709717)&lt;br /&gt;&#xA;the second excited state (3d (m=0)) = -0.07365 &lt;br /&gt;&#xA;the third excited state (3s) = -0.03835&lt;/p&gt;&#xA;&lt;p&gt;All these states should have the same structure of the basis set function (&lt;span class=&quot;math-container&quot;&gt;$\psi_j=e^{-b_{j} z^2}e^{-a_{j} \rho^2}$&lt;/span&gt;) due to the m=0 (the z component of the angular momentum).&lt;/p&gt;&#xA;&lt;p&gt;I have a few questions: &lt;br /&gt;&#xA;I really can't understand what the authors mean in varied optimization search of the parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta_M$&lt;/span&gt;, could you please explain to me what that means?&lt;/p&gt;&#xA;&lt;p&gt;Why do the parameters (&lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta_M$&lt;/span&gt;) have different indexes, shouldn't their number be the same? Since they are paired in the basis function.&lt;/p&gt;&#xA;&lt;p&gt;I would be glad to any comments on solving the problem.&lt;/p&gt;&#xA;&lt;p&gt;I would like to draw attention to the fact that to get the energy from the Aldrich, C., &amp;amp; Greene, R. L article it's needed the value from the table 1 to subtract the field value and divide by 2 (this is due to the fact that the authors of this article do not take into account the spin). For example for 2s state: value from the table 1 for magnetic field = 5 is equal 4.6133 so the energy of the 2s state = (4.6133 - 5)/2 = -0,19335&lt;/p&gt;&#xA;" OwnerUserId="7193" LastEditorUserId="5" LastEditDate="2023-06-04T01:31:42.280" LastActivityDate="2023-06-04T01:31:42.280" Title="Optimal Gaussian basis set for hydrogen atom in magnetic field" Tags="|density-functional-theory|quantum-chemistry|band-structure|condensed-matter|basis-sets|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10909" PostTypeId="1" CreationDate="2023-05-13T05:38:20.710" Score="1" ViewCount="75" Body="&lt;p&gt;I have been trying to write an input file for &lt;a href=&quot;/questions/tagged/lammps&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;lammps&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-lammps-tooltip-container&quot;&gt;lammps&lt;/a&gt; to simulate the shape transition of a nanoparticle of silicon using multiple potentials to obtain the best structure, which I will compare with a &lt;a href=&quot;/questions/tagged/density-functional-theory&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;density-functional-theory&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;density-functional-theory&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-density-functional-theory-tooltip-container&quot;&gt;density-functional-theory&lt;/a&gt; simulation results. However, I have encountered an issue with the structure of the nanoparticle being distorted from the beginning when using the &lt;code&gt;fix ID nve&lt;/code&gt; command, and I don't know how to fix it.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uHizHm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uHizHm.png&quot; alt=&quot;&amp;quot;an example of 13 particles using lammps&amp;quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've tried to change the &lt;code&gt;fix nve&lt;/code&gt; command with the &lt;code&gt;fix nvt&lt;/code&gt; command or just leaving the &lt;code&gt;velocity&lt;/code&gt; command running alone, but the resulting structure is not as expected when compared to the &lt;a href=&quot;/questions/tagged/density-functional-theory&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;density-functional-theory&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;density-functional-theory&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-density-functional-theory-tooltip-container&quot;&gt;density-functional-theory&lt;/a&gt; results.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ijYcBm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ijYcBm.png&quot; alt=&quot;[tag:Density-functional-theory] results&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the input file that i have been using:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;variable        dt equal 0.001&#xA;units           metal&#xA;&#xA;variable t equal 800&#xA;variable t_start equal 300&#xA;variable t_final equal 1&#xA;&#xA;# ----------------  Loop start -------------------------------------&#xA;variable i loop 12 26&#xA;variable cluster equal &lt;span class=&quot;math-container&quot;&gt;$i&#xA;variable epair_cluster equal epair/v_cluster&#xA;variable num_steps equal ($&lt;/span&gt;{t}-${t_final})*1000&#xA;&#xA;#-----------------------ATOM DEFINITION----------------------------&#xA;read_data       data/si_${i}.data &#xA;mass            1 28.085  ##Silicon&#xA;&#xA;#------------------------FORCE FIELDS------------------------------&#xA;#pair_style      sw&#xA;#pair_coeff      * * Si.sw Si&#xA;&#xA;#pair_style edip&#xA;#pair_coeff * * Si.edip Si&#xA;&#xA;pair_style tersoff&#xA;pair_coeff * * Si.tersoff Si&#xA;&#xA;#pair_style     tersoff/mod/c &#xA;#pair_coeff * * Si.tersoff.modc Si&#xA;&#xA;neighbor        2 bin&#xA;neigh_modify    every 10 delay 0 check no&#xA;&#xA;thermo_style custom step temp v_epair_cluster etotal v_cluster&#xA;thermo          1000&#xA;&#xA;#dump            0 all xyz 100 min/si_min_$i.xyz&#xA;#dump_modify     0 flush yes&#xA;#dump_modify     0 sort id element Si&#xA;#minimize 1.0e-4 1.0e-6 100 1000&#xA;#undump          0&#xA;&#xA;reset_timestep  0&#xA;timestep        $(dt)&#xA;&#xA;#------------------------------ Setting the velocities  -------------------------&#xA;fix         1 all nve &#xA;velocity        all create  ${t_start} 4928459 rot yes dist gaussian&#xA;&#xA;dump            5 all xyz 1000 si_&lt;span class=&quot;math-container&quot;&gt;$i_$&lt;/span&gt;t.xyz&#xA;dump_modify     5 append yes&#xA;&#xA;run     250000&#xA;&#xA;unfix       1&#xA;#------------------------------- annealing -------------------------&#xA;fix             1 all nvt temp &lt;span class=&quot;math-container&quot;&gt;${t_start} $&lt;/span&gt;{t} 0.1&#xA;&#xA;dump            1 all xyz 1000 si_&lt;span class=&quot;math-container&quot;&gt;$i_$&lt;/span&gt;t.xyz&#xA;dump_modify     1 append yes&#xA;&#xA;run             ${num_steps}&#xA;&#xA;#------------------------------- Relaxation  -------------------------&#xA;fix             2 all nvt temp  &lt;span class=&quot;math-container&quot;&gt;${t} $&lt;/span&gt;{t} 0.1&#xA;&#xA;dump            2 all xyz 1000 si_&lt;span class=&quot;math-container&quot;&gt;$i_$&lt;/span&gt;t.xyz&#xA;dump_modify     2 append yes&#xA;&#xA;run             250000&#xA;&#xA;#-------------------------------  couling -------------------------&#xA;fix             4 all temp/berendsen &lt;span class=&quot;math-container&quot;&gt;${t} $&lt;/span&gt;{t_final} 0.1&#xA;&#xA;&#xA;dump           3 all xyz 1000 si_&lt;span class=&quot;math-container&quot;&gt;$i_$&lt;/span&gt;t.xyz&#xA;dump_modify    3 append yes&#xA;&#xA;run             ${num_steps}&#xA;&#xA;#------------------------------- Relaxation -----------------------&#xA;fix     5 all nvt temp &lt;span class=&quot;math-container&quot;&gt;${t_final} $&lt;/span&gt;{t_final} 0.1&#xA;&#xA;dump           4 all xyz 1000 si_&lt;span class=&quot;math-container&quot;&gt;$i_$&lt;/span&gt;t.xyz&#xA;dump_modify    4 append yes&#xA;&#xA;run            250000&#xA;&#xA; clear&#xA; next i&#xA; jump annealing_si_loop.lmp&#xA;&#xA;print         &amp;quot;Simulation complete&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7196" LastEditorUserId="6687" LastEditDate="2023-05-13T11:53:14.250" LastActivityDate="2023-05-13T22:32:21.467" Title="Issues simulating the shape transition of silicon clusters using LAMMPS" Tags="|density-functional-theory|molecular-dynamics|lammps|nanoparticles|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10910" PostTypeId="2" ParentId="10884" CreationDate="2023-05-13T06:26:19.403" Score="6" Body="&lt;p&gt;You have to kekulize your &lt;code&gt;MolFromSmiles&lt;/code&gt; and mark all bonds non-aromatic.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import Draw, rdDepictor&#xA;rdDepictor.SetPreferCoordGen(True)&#xA;from rdkit.Chem.Draw import IPythonConsole&#xA;&#xA;smiles = 'c1c(Cl)c(Cl)ccc1'&#xA;&#xA;mol = Chem.MolFromSmiles(smiles)&#xA;Chem.Kekulize(mol, clearAromaticFlags=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now you get the resonance structures.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;suppl = Chem.ResonanceMolSupplier(mol, Chem.KEKULE_ALL)&#xA;&#xA;for resMol in suppl:&#xA;    res_smi = Chem.MolToSmiles(resMol, kekuleSmiles=True)&#xA;    print(res_smi)&#xA;&#xA;ClC1=CC=CC=C1Cl&#xA;ClC1=C(Cl)C=CC=C1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;suppl[0]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/S1mVA.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S1mVA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;suppl[1]&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7VUaR.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7VUaR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3494" LastActivityDate="2023-05-13T06:26:19.403" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10912" PostTypeId="2" ParentId="10908" CreationDate="2023-05-13T13:31:24.790" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;I really can't understand what the authors mean in varied optimization search of the parameters α1, αN, β1 and βM, could you please explain to me what that means?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://doi.org/10.1002/pssb.2220930140&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1002/pssb.2220930140&lt;/a&gt; Aldrich and Greene write &amp;quot;For given quantum numbers &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;, the parameters &lt;span class=&quot;math-container&quot;&gt;$\alpha_1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\alpha_N$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta_1$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\beta_N$&lt;/span&gt; were varied in a four dimensional optimization search which minimized the sum of the eigenvalues of interest.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;This means that they minimize the sum of the eigenvalues by changing the values of the four parameters appropriately. They do not mention what algorithm they use for the optimization (it's an old article), but you could do this nowadays with e.g. &lt;a href=&quot;https://en.wikipedia.org/wiki/Gradient_descent&quot; rel=&quot;noreferrer&quot;&gt;gradient descent methods&lt;/a&gt; or the &lt;a href=&quot;https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method&quot; rel=&quot;noreferrer&quot;&gt;Nelder-Mead &amp;quot;amoeba&amp;quot; method&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why do the parameters (α1, αN, β1 and βM) have different indexes, shouldn't their number be the same? Since they are paired in the basis function.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;They are four different parameters. The ansatz they use for the exponents is known in quantum chemistry as even-tempering [1]: the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th exponent is given by &lt;span class=&quot;math-container&quot;&gt;$$\alpha_{i} = \alpha_{0} \beta^{i}$$&lt;/span&gt; when one indexes &lt;span class=&quot;math-container&quot;&gt;$i\in[0,N-1]$&lt;/span&gt; as in C or Python, or &lt;span class=&quot;math-container&quot;&gt;$$\alpha_{i} = \alpha_{1} \beta^{i-1}$$&lt;/span&gt; when using &lt;span class=&quot;math-container&quot;&gt;$i \in [1,N]$&lt;/span&gt; as in Fortran. This trivially yields the relation&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\beta = \left( \frac {\alpha_{N}} {\alpha_{1}} \right)^{1/(N-1)} $$&lt;/span&gt;&#xA;that you have copied above.&lt;/p&gt;&#xA;&lt;p&gt;The only difference to this case is that the magnetic field acts like a confining potential in directions orthogonal to the magnetic field [2], which means that they employ two sequences of exponents: one for the functions along &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;, the direction of the magnetic field axis, and another along &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; which is the polar radial coordinate in &lt;span class=&quot;math-container&quot;&gt;$(x,y)$&lt;/span&gt; that are the directions orthogonal to the field.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;We have performed the calculations presented in this paper with a basis with ten Gaussians in the ρ direction and twelve Gaiissians in the z direction, for a total of 120 different basis functions.&amp;quot;. I really don't understand what that means?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Aldrich and Greene use a tensorial basis set in &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt;, see their equation (4):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \chi_\alpha (\rho,z) = \chi^{\rho}(\rho) \chi^{z}(z).$$&lt;/span&gt;&#xA;In addition, you also have the &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; direction; however, since the Hamiltonian does not depend on this variable, Noether's theorem leads to it being a constant of motion and the &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; solution is of the form &lt;span class=&quot;math-container&quot;&gt;$\exp(im\phi)$&lt;/span&gt; as also happens for linear molecules. [3]&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; direction is represented with 10 basis functions, &lt;span class=&quot;math-container&quot;&gt;$\{\chi^{\rho}_\mu\}_{\mu=1}^{10}$&lt;/span&gt;. The &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; direction is represented with 12 basis functions, &lt;span class=&quot;math-container&quot;&gt;$\{\chi^{z}_\mu\}_{\mu=1}^{12}$&lt;/span&gt;. Forming all products, you get 120 basis functions.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I would like to draw attention to the fact that to get the energy from the Aldrich, C., &amp;amp; Greene, R. L article it's needed the value from the table 1 to subtract the field value and divide by 2 (this is due to the fact that the authors of this article do not take into account the spin)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Their calculations &lt;strong&gt;do&lt;/strong&gt; take into account the spin; &lt;em&gt;the spin operator even appears in the Hamiltonian&lt;/em&gt; [2]! The division by two is just a consequence of unit conversion: they report energies in Rydberg, and &lt;span class=&quot;math-container&quot;&gt;$ 1 \text{Ry} = 0.5 E_h$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;References&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;See for instance &lt;a href=&quot;https://doi.org/10.1007/BF00547681&quot; rel=&quot;noreferrer&quot;&gt;Theor. Chim. Acta 52, 231 (1979)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Lehtola et al, &lt;a href=&quot;https://doi.org/10.1007/BF00547681&quot; rel=&quot;noreferrer&quot;&gt;Mol. Phys. 118, e159798 (2020)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;S. Lehtola, &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;Int. J. Quantum Chem. 119, e25968 (2019)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-13T13:31:24.790" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10913" PostTypeId="1" CreationDate="2023-05-13T16:33:48.927" Score="1" ViewCount="60" Body="&lt;p&gt;I want to use the EAM potential of Ti-5Ta alloy for a sintering simulation. A Ti nanoparticle with a hexagonal close-packed (HCP) structure and a Ta nanoparticle with a body centered cubic (BCC) structure. But I do not find any files that meet my needs. Can I generate these potential files some how ? can anyone advice me about this ? Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="7200" LastActivityDate="2023-05-13T16:33:48.927" Title="EAM potential files for LAMMPS Ti-5Ta alloy" Tags="|lammps|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T17:49:33.850" ContentLicense="CC BY-SA 4.0" />
  <row Id="10914" PostTypeId="1" CreationDate="2023-05-13T17:09:57.620" Score="6" ViewCount="129" Body="&lt;p&gt;What are the the options available for software to compute heat of formation (&lt;span class=&quot;math-container&quot;&gt;$\Delta_f H$&lt;/span&gt;) of a given compound in your own system? (Preferably at no cost, like GAMESS.)&lt;/p&gt;&#xA;" OwnerUserId="7039" LastEditorUserId="7039" LastEditDate="2023-05-13T17:37:56.273" LastActivityDate="2023-05-21T18:58:40.170" Title="Software for computing heat of formation" Tags="|computational-chemistry|software-recommendations|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10915" PostTypeId="1" AcceptedAnswerId="10916" CreationDate="2023-05-13T17:41:10.123" Score="5" ViewCount="125" Body="&lt;p&gt;I wonder if there is any terminology (or name of classification) that refers to ab-initio QM methods based on the Schrodinger equation and basis functions, such as HF and post-HF methods, but not DFT methods. I saw some papers using the term 'wave function theory' or WFT to discriminate it from DFT (and emphasize their higher level of theory), but I want to know if there are other terms.&lt;/p&gt;&#xA;" OwnerUserId="7201" LastEditorUserId="5" LastEditDate="2023-05-13T22:33:02.680" LastActivityDate="2023-05-13T22:33:02.680" Title="A terminology for QM calculation methods" Tags="|quantum-chemistry|ab-initio-calculations|terminology|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10916" PostTypeId="2" ParentId="10915" CreationDate="2023-05-13T20:17:38.467" Score="5" Body="&lt;p&gt;These are often called &amp;quot;wave function-based methods&amp;quot; or, more specifically &amp;quot;wave function-based electron correlation methods&amp;quot; if you want a term for methods beyond Hartree-Fock.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2023-05-13T20:17:38.467" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10917" PostTypeId="2" ParentId="10909" CreationDate="2023-05-13T22:32:21.467" Score="4" Body="&lt;p&gt;Most molecular dynamics force fields are set up to model either bulk systems or large unreactive molecules (like proteins). They are not designed for small systems (such as a 13-atom nanoparticle) which are accessible through quantum chemistry methods, and where each atom is likely to have a very different chemical environment which would be very hard to describe using a single functional form for all atoms.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-05-13T22:32:21.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10918" PostTypeId="2" ParentId="10901" CreationDate="2023-05-14T11:14:39.820" Score="1" Body="&lt;p&gt;For the last integral including both quadratures, there are two problems :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;the integrand : a missing factor of R²&lt;/li&gt;&#xA;&lt;li&gt;the volume of a sphere was not an appropriate case I think&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Testing with the new changes on the 3D Gauss integral gives good results, but I expected the error difference to be lower since with 30 Gauss-Chebyshev quadrature points I have a &lt;span class=&quot;math-container&quot;&gt;$10^{-5}$&lt;/span&gt; error on the 1D Gauss integral and the Lebedev quadrature is of high order. At least the error decreases as the number of Gauss-Chebyshev quadrature points increases :&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# testing full quadrature scheme with cell functions&#xA;# Gauss integral&#xA;&#xA;&#xA;def f(X):&#xA;    return np.exp(-np.sum(np.square(X),axis=1,keepdims=True))&#xA;&#xA;I1 = pi**(3/2)&#xA;I2 = 4*pi*np.einsum(&#xA;    'ij,ij',&#xA;    f(X_cartesian_int)*2.0*rm/(1-Mu)**2*R**2,&#xA;    Wint&#xA;)&#xA;&#xA;print(I1,I2,I1-I2)&#xA;&#xA;Output : 5.568327996831708 5.570977047596403 -0.0026490507646954597&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7151" LastActivityDate="2023-05-14T11:14:39.820" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10920" PostTypeId="2" ParentId="10884" CreationDate="2023-05-15T08:17:40.660" Score="5" Body="&lt;p&gt;One of the contributors of RDKit gave a solution &lt;a href=&quot;https://github.com/rdkit/rdkit/discussions/6358&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. I am paraphrasing it below.&lt;/p&gt;&#xA;&lt;p&gt;The problem occurs because RDKit by default assigns aromatic labels to atom and bonds as part of its sanitization process, and therefore loses the location of the double bonds in the original input. If you request a kekule form (in SMILES or image), RDKit uses its own kekulizer to generate a valid representation.&lt;/p&gt;&#xA;&lt;p&gt;Below I present work-arounds for two scenarios. First a plotting helper function:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def generate_images(mols, should_kekulize_aromatic_smiles=False):&#xA;    imgs = []&#xA;    &#xA;    for i, m in enumerate(mols):&#xA;        smi = Chem.MolToSmiles(m)&#xA;        print(f'smi {smi}\n')&#xA;        ## only kekulize molecule if it has aromatic atoms&#xA;        ## used to choose whether to plot kekulized or aromatic smiles for 'c1c(Cl)c(Cl)ccc1'&#xA;        has_aromatic_atoms = any(a.GetIsAromatic() for a in m.GetAtoms())&#xA;        if not has_aromatic_atoms: should_kekulize_aromatic_smiles = False&#xA;        drawer = rdMolDraw2D.MolDraw2DCairo(200, 100)&#xA;        drawer.drawOptions().prepareMolsBeforeDrawing = False&#xA;        m = rdMolDraw2D.PrepareMolForDrawing(m, kekulize=should_kekulize_aromatic_smiles)&#xA;        drawer.DrawMolecule(m)&#xA;        drawer.FinishDrawing()&#xA;        img = drawer.GetDrawingText()&#xA;        imgs.append(img)&#xA;        with open(os.path.join(parent_path, 'figures', f'{smi}_{i}.png'), &amp;quot;wb&amp;quot;) as hnd:&#xA;            hnd.write(img)&#xA;    return imgs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Plotting with given SMILES&lt;/h1&gt;&#xA;&lt;p&gt;Let's look at the example of plotting from defined kekule and aromatic SMILES, e.g. &lt;code&gt;['c1c(Cl)c(Cl)ccc1', 'C1C(Cl)=C(Cl)C=CC=1', 'C1=C(Cl)C(Cl)=CC=C1']&lt;/code&gt;. In this case, we need to sanitize the molecules without kekulization/aromaticity.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def sanitize_without_aromatic(smiles):&#xA;    mols = []&#xA;    smiles_parser_params = Chem.SmilesParserParams()&#xA;    smiles_parser_params.sanitize = False   &#xA;&#xA;    for i, smi in enumerate(smiles):&#xA;        m = Chem.MolFromSmiles(smi, smiles_parser_params)&#xA;        sanitize_flags = Chem.SanitizeFlags.SANITIZE_ALL&#xA;        ## turn off kekulization and aromaticity for molecules with no aromatic atoms&#xA;        has_aromatic_atoms = any(a.GetIsAromatic() for a in m.GetAtoms())&#xA;        if not has_aromatic_atoms:&#xA;            sanitize_flags ^= (Chem.SanitizeFlags.SANITIZE_KEKULIZE | Chem.SanitizeFlags.SANITIZE_SETAROMATICITY)&#xA;        Chem.SanitizeMol(m, sanitize_flags)&#xA;&#xA;        mols.append(m)&#xA;&#xA;    return mols&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;putting the two functions together:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smiles = ['c1c(Cl)c(Cl)ccc1', 'C1C(Cl)=C(Cl)C=CC=1', 'C1=C(Cl)C(Cl)=CC=C1']&#xA;mols = sanitize_without_aromatic(smiles)&#xA;generate_images(mols=mols, should_kekulize_aromatic_smiles=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;gives the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smi Clc1ccccc1Cl&#xA;&#xA;imgs[0]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gvOh3.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gvOh3.png&quot; alt=&quot;aromatic_smi&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smi ClC1=C(Cl)C=CC=C1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AbyW1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AbyW1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smi ClC1=CC=CC=C1Cl&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/aFfXg.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aFfXg.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Plotting the output of ResonanceMolSupplier&lt;/h1&gt;&#xA;&lt;p&gt;ResonanceMolSupplier returns sanitized molecules, and we need to unset the aromatic flags manually. Here is a function to do that.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def unset_aromatic_flags(m):&#xA;    for b in m.GetBonds():&#xA;        if b.GetBondType() != Chem.BondType.AROMATIC and b.GetIsAromatic():&#xA;            b.SetIsAromatic(False)&#xA;            b.GetBeginAtom().SetIsAromatic(False)&#xA;            b.GetEndAtom().SetIsAromatic(False)&#xA;    return m&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can test it with the following example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;smi = 'c1c(Cl)c(Cl)ccc1'&#xA;mol = Chem.MolFromSmiles(smi)&#xA;suppl = Chem.ResonanceMolSupplier(mol, Chem.KEKULE_ALL)&#xA;mols = [mol]+[unset_aromatic_flags(m) for m in suppl]&#xA;imgs = generate_images(mols=mols, should_kekulize_aromatic_smiles=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output is the same as above.&lt;/p&gt;&#xA;" OwnerUserId="7162" LastActivityDate="2023-05-15T08:17:40.660" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10921" PostTypeId="1" CreationDate="2023-05-15T10:00:35.443" Score="3" ViewCount="76" Body="&lt;p&gt;I have a DFT calculation in VASP are done at 0K. And CDW is a temperature dependent phenomena. Therefore for a CDW ground state calculation can I add periodic modulation in atomic position?&lt;/p&gt;&#xA;&lt;p&gt;If so how to add periodic modulation to atomic position?&lt;/p&gt;&#xA;" OwnerUserId="7210" LastEditorUserId="6687" LastEditDate="2023-05-15T11:17:43.380" LastActivityDate="2023-05-15T11:17:43.380" Title="calculation of E-K diagram of a charge density wave ground state using DFT VASP" Tags="|density-functional-theory|vasp|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T17:49:07.110" ContentLicense="CC BY-SA 4.0" />
  <row Id="10922" PostTypeId="1" AcceptedAnswerId="10923" CreationDate="2023-05-15T13:11:38.870" Score="5" ViewCount="215" Body="&lt;p&gt;I recently received the task to investigate what is happening in a fluorescent molecule in different temperatures. How the electronic population is changing and how is this affecting the electronic transitions because the luminescence is changing a lot in different temperatures.&lt;/p&gt;&#xA;&lt;p&gt;My first instinct was to try a finite-temperature DFT and see if I can correlate this with thermodynamic temperature (don't know if this is possible at all). Then, my second instinct was to see if I could run TD-DFT on top of a finite-temperature calculation.&lt;/p&gt;&#xA;&lt;p&gt;The software (ORCA) has not complained, but I have no confidence that this makes any physical sense. Is there a better way to do this work? Or should I go on with this approach?&lt;/p&gt;&#xA;" OwnerUserId="557" LastEditorUserId="5" LastEditDate="2023-05-15T13:36:08.170" LastActivityDate="2023-05-16T11:36:31.883" Title="Does it make any sense to run a TD-DFT calculation with Finite-Temperature SCF active?" Tags="|density-functional-theory|orca|td-dft|excited-states|transition-temperature|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10923" PostTypeId="2" ParentId="10922" CreationDate="2023-05-16T11:36:31.883" Score="5" Body="&lt;p&gt;Temperature affects a system through two ways: (1) by (loosely speaking) making the nuclei move faster, and (2) by exciting some electrons to virtual orbitals (or equivalently speaking, exciting some molecules from the electronic ground state to electronic excited states). Finite temperature DFT calculations only capture the latter effect, and unless the temperature is very high (say, &amp;gt;2000 K) or the material is a metal, the latter effect is often negligible. A large variety of methods exist for describing the former effect, which can be classified based on whether they approximate the potential energy surface as harmonic, or whether they use molecular dynamics, etc. Enumerating all such methods is beyond the scope of this answer.&lt;/p&gt;&#xA;&lt;p&gt;For fluorescence, some of the top contributions from temperature include:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Temperature can change the aggregation behavior. Suppose that the fluorescent molecule can dimerize, and the dimer is not fluorescent, or fluoresces at a different wavelength, or fluoresces with a different quantum yield. When the temperature increases, the dimer gradually dissociates, and the contribution from the monomer fluorescence increases. This is probably the biggest contribution to the temperature effect for most fluorescent molecules, but is one of the easiest to overlook in computations; in fact, a lot of time will be spent on searching for and optimizing the low-lying conformers of the dimer, and it is not trivial (but possible) to calculate the fluorescence quantum yields of all the conformers, in case such a calculation is indeed necessary.&lt;/li&gt;&#xA;&lt;li&gt;Temperature can change the Boltzmann ratio of different conformers (or different protonation states, etc.) of the fluorescent molecule. Again, this has to be studied by a conformational search, followed by Gibbs free energy calculations.&lt;/li&gt;&#xA;&lt;li&gt;Temperature can change the relative population of the different vibrational energy levels of the electronic excited state. When the temperature is higher, more molecules fluoresce from high-lying vibrational energy levels, giving different shapes of the fluorescence spectrum. In ORCA this can be done by doing a vibrationally resolved fluorescence calculation, whereby the temperature is specified in the %esd input block.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, in case the electronic temperature does have a significant impact on the fluorescence spectrum, incorporating this effect in a TDDFT calculation is highly non-trivial. For example, the TDDFT module of ORCA (and quite a few other common quantum chemistry programs as well) cannot do this, because it performs the TDDFT calculation by solving the Casida equation, which assumes that all orbitals have integer occupation numbers, and this is not true when the electronic temperature is non-negligible. There are a few ways to do finite (electronic) temperature TDDFT, e.g. by &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/152/24/244111/1065347/Finite-temperature-based-time-dependent-density&quot; rel=&quot;noreferrer&quot;&gt;Nakai et al.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-05-16T11:36:31.883" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10924" PostTypeId="1" AcceptedAnswerId="10926" CreationDate="2023-05-17T11:42:19.410" Score="5" ViewCount="326" Body="&lt;p&gt;I would like to calculate the fat phonon bands for a chosen material (for simplicity, suppose GaAs), similarily as in Fig. 3 of &lt;a href=&quot;https://doi.org/10.1103/physrevmaterials.3.034601&quot; rel=&quot;noreferrer&quot;&gt;reference [1]&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SZyD8.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SZyD8.png&quot; alt=&quot;fat band plot from ref. 1&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is effectively the analogue of projected band structure for phonon dispersion: information about which atoms contribute the specific modes to what degree. &lt;em&gt;(Please also let me know if there's a more widely used term for this)&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I was searching how to obtain such a &amp;quot;projected phonon-band&amp;quot; structure using Quantum Espresso, but I couldn't find anything. Is there a way? If not, is it possible to get at least &lt;em&gt;some&lt;/em&gt; information regarding the atomic contributions to the phonon bands? Are there 3rd-party post-QE codes that I could use to obtain such info?&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;[1] Ha, V.-A., Yu, G., Ricci, F., Dahliah, D., van Setten, M. J., Giantomassi, M., Rignanese, G.-M., &amp;amp; Hautier, G. (2019). Computationally driven high-throughput identification of CaTe and Li3Sb as promising candidates for high-mobility p-type transparent conducting materials. In Physical Review Materials (Vol. 3, Issue 3). American Physical Society (APS). &lt;a href=&quot;https://doi.org/10.1103/physrevmaterials.3.034601&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1103/physrevmaterials.3.034601&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;&#xA;" OwnerUserId="968" LastActivityDate="2023-07-08T06:31:30.213" Title="Can you calculate fat (&quot;projected&quot;) phonon dispersion bands with Quantum Espresso?" Tags="|density-functional-theory|quantum-espresso|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10925" PostTypeId="1" CreationDate="2023-05-17T20:31:28.827" Score="2" ViewCount="514" Body="&lt;p&gt;Trying to complete &lt;code&gt;simulation.context.setPositions(molecule.positions)&lt;/code&gt;  (molecule from sdf file)&lt;/p&gt;&#xA;&lt;p&gt;The code below runs nicely (so can be used if you are beginner like me to &amp;quot;get started&amp;quot;).  However, for a molecule several molecular file formats (sdf and pdb) seem to be needed which appears to duplicate data)&lt;/p&gt;&#xA;&lt;p&gt;Quite a basic question but has taken a few days already so I am sure I am missing something obvious:&lt;/p&gt;&#xA;&lt;p&gt;Using the code from &lt;a href=&quot;http://docs.openmm.org/latest/userguide/application/02_running_sims.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import os&#xA;print (os.environ['CONDA_DEFAULT_ENV'])&#xA;&#xA;# check I am using openmm environment&#xA;&#xA;&#xA;from openmm.app import *&#xA;from openmm import *&#xA;from openmm.unit import *&#xA;from sys import stdout&#xA;&#xA;from openff.toolkit import ForceField, Molecule&#xA;from openff.units import unit&#xA;&#xA;from openff.interchange import Interchange&#xA;&#xA;molecule = Molecule.from_file(&amp;quot;PEE1.sdf&amp;quot;)&#xA;&#xA;# Convert this molecule to a topology&#xA;Topology = molecule.to_topology()&#xA;&#xA;pdb = PDBFile('PEE1.pdb')&#xA;&#xA;positions = pdb.getPositions()&#xA;&#xA;&#xA;# Define periodicity via box vectors.  This seems essential but I was #hoping this could be read from pdb file or sdf file&#xA;Topology.box_vectors = unit.Quantity([4, 4, 4], unit.nanometer)&#xA;&#xA;&#xA;# Load OpenFF 2.0.0 &amp;quot;Sage&amp;quot;&#xA;sage = ForceField(&amp;quot;openff-2.0.0.offxml&amp;quot;)&#xA;interchange = Interchange.from_smirnoff(topology=[molecule], force_field=sage)&#xA;&#xA;openmm_system = interchange.to_openmm()&#xA;&#xA;integrator = LangevinIntegrator(300 * kelvin, 1 / picosecond, 2 * femtoseconds)&#xA;&#xA;&#xA;simulation = Simulation(Topology, openmm_system, integrator)&#xA;&#xA;simulation.context.setPositions(positions)&#xA;&#xA;print(openmm_system.getNumParticles())&#xA;&#xA;&#xA;# Write the trajectory to a file called &amp;quot;output.pdb&amp;quot;&#xA;#simulation.reporters.append(PDBReporter('output.pdb', 1000))&#xA;&#xA;simulation.saveCheckpoint(&amp;quot;saved.txt&amp;quot;)&#xA;&#xA;# Report infomation to the screen as the simulation runs&#xA;#simulation.reporters.append(StateDataReporter(stdout, 100, step=True,potentialEnergy=True, temperature=True))&#xA;&#xA;&#xA;simulation.minimizeEnergy()&#xA;&#xA;&#xA;# Reporting parameters&#xA;#simulation.reporters.append(app.DCDReporter('trajectory.dcd', 1000))&#xA;&#xA;simulation.step(10000)&#xA;&#xA;&#xA;&#xA;with open('system.xml', 'w') as output:&#xA;    output.write(XmlSerializer.serialize(openmm_system))&#xA;    &#xA;# Visualize the molecule&#xA;molecule.visualize(show_all_hydrogens=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The steps that I followed are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;I have my molecule (for example phenol) as sdf. I can create the molecule.topology from the sdf file (and pdb file)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Issue : I can create the initial starting positions&amp;quot; only from the pdb version.  Are positions only made available from a pdb file?  (If I could write out the molecule.positions as a file I might be able to work out the format:  it is some sort of binary file if I just &amp;quot;print&amp;quot; it out)&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Currently, I'm trying to save the sdf file as a pdb file (via openBabel, but when opened by openmm, openmm reports error as I have many identical atoms in the pdb file.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Issue: I can correct the pdb file manually by changing &lt;code&gt;HETEROATOM  1  C&lt;/code&gt; carbons to &lt;code&gt;HETEROATOM C1, C2&lt;/code&gt; etc, but if I had 1000 phenols (say) this would be tedious. ( I have written a script to change names of atom to atom ++ number (just add index to atom name))&lt;/p&gt;&#xA;&lt;p&gt;I would have thought &amp;quot;positions&amp;quot; (molecule.positions) could be derived from a(ny)file type such as .xyz,.sdf,.mol etc.&lt;/p&gt;&#xA;&lt;p&gt;Have I missed something really obvious or an easy way to generate molecule.postions?  (I think that this is my last hurdle to running an md).  Following tutorial does work but not when I work with eg non-aminoacid structures.&lt;/p&gt;&#xA;&lt;p&gt;This is a heavily edited re-write of my question.  I can get this example to &amp;quot;run&amp;quot;  (need to check scientific validity) by manual edit of pdb file (rename ATOM to ATOM++index)&lt;/p&gt;&#xA;&lt;p&gt;sdf file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;test.xyz&#xA; OpenBabel05202321543D&#xA;&#xA; 18 17  0  0  0  0  0  0  0  0999 V2000&#xA;    1.1816    2.2735   -0.7735 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5464    1.3284    0.2322 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.8836    2.0043   -1.7916 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.2741    2.2300   -0.7168 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.8696    3.3078   -0.5908 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.9348    1.6888    1.6606 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -0.5442    1.3519    0.1293 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.8491    0.2961    0.0154 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    2.0228    1.6530    1.7769 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.3324    0.7544    2.5567 O   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.5843    2.7007    1.8989 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.6282    1.0771    3.9148 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.0002    0.0365    4.8207 C   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.2233    2.0663    4.1524 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    1.7137    1.0876    4.0632 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.3587   -0.9664    4.5689 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;    0.2366    0.2433    5.8686 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;   -1.0885    0.0273    4.7018 H   0  0  0  0  0  0  0  0  0  0  0  0&#xA;  1  2  1  0  0  0  0&#xA;  1  5  1  0  0  0  0&#xA;  2  7  1  0  0  0  0&#xA;  2  8  1  0  0  0  0&#xA;  3  1  1  0  0  0  0&#xA;  4  1  1  0  0  0  0&#xA;  6 10  1  0  0  0  0&#xA;  6  2  1  0  0  0  0&#xA;  9  6  1  0  0  0  0&#xA; 10 12  1  0  0  0  0&#xA; 11  6  1  0  0  0  0&#xA; 12 15  1  0  0  0  0&#xA; 13 12  1  0  0  0  0&#xA; 13 17  1  0  0  0  0&#xA; 13 18  1  0  0  0  0&#xA; 14 12  1  0  0  0  0&#xA; 16 13  1  0  0  0  0&#xA;M  END&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7225" LastEditorUserId="6468" LastEditDate="2023-05-20T16:26:18.627" LastActivityDate="2023-05-21T06:47:27.793" Title="Openmm setup MD with intitial positions" Tags="|python|openmm|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10926" PostTypeId="2" ParentId="10924" CreationDate="2023-05-18T11:25:37.537" Score="6" Body="&lt;p&gt;These &amp;quot;projected phonon bandstructure&amp;quot; can be obtained using phonon eigenvectors. The coefficients (which determine the width of the lines on the plot) should just be the amplitude of the eigenvectors on each atom.&lt;/p&gt;&#xA;&lt;p&gt;Taking a close look at the figure provided, we see that light elements dominate the higher-frequency region. This suggests that the authors did not remove the mass dependence from the eigenvectors (remember the dynamical matrix is scaled by the atomic mass).&lt;/p&gt;&#xA;&lt;p&gt;Such a plot can be generated using Phonopy&lt;a href=&quot;https://phonopy.github.io/phonopy/setting-tags.html#eigenvectors&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt; by setting &lt;code&gt;EIGENVECTORS=.TRUE.&lt;/code&gt; in &lt;code&gt;band.conf&lt;/code&gt; (for how to use Phonopy to plot phonon band structure, see example &lt;a href=&quot;https://phonopy.github.io/phonopy/examples.html#band-structure&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://phonopy.github.io/phonopy/examples.html#band-structure&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Once the eigenvectors are obtained, you can use my Python code to obtain the projected phonon band structure:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import yaml&#xA;import numpy as np&#xA;&#xA;with open('band.yaml','r') as file:&#xA;     data = yaml.safe_load(file)&#xA;&#xA;# get some basic quantities&#xA;num_kpt = len(data['phonon'])&#xA;num_bnd = len(data['phonon'][0]['band'])&#xA;num_atm = len(data['phonon'][0]['band'][0]['eigenvector'])&#xA;&#xA;# initialize array&#xA;phonon_freq = np.zeros([num_kpt,num_bnd])&#xA;phonon_eigv = np.zeros([num_kpt,num_bnd,num_atm])&#xA;band_distance = []&#xA;&#xA;# store data&#xA;for ikpt in range(num_kpt):&#xA;    band_distance.append(data['phonon'][ikpt]['distance'])&#xA;    for ibnd in range(num_bnd):&#xA;        root = data['phonon'][ikpt]['band'][ibnd]&#xA;        phonon_freq[ikpt, ibnd] = root['frequency']&#xA;        for iatm in range(num_atm):&#xA;            root_eigv = root['eigenvector'][iatm]&#xA;            vec = np.matrix(root_eigv)&#xA;            vec = vec[...,0] + vec[...,1]*1j&#xA;            result = np.dot(vec.H, vec)&#xA;            phonon_eigv[ikpt, ibnd, iatm] = np.real(result)&#xA;&#xA;# plot&#xA;import matplotlib.pyplot as plt&#xA;&#xA;for ibnd in range(num_bnd):&#xA;    plt.plot(band_distance,phonon_freq[:,ibnd],color='red')&#xA;    # plotting fat band for Na&#xA;    atom2proj = 1&#xA;    plt.scatter(band_distance,phonon_freq[:,ibnd],\&#xA;                s=400*phonon_eigv[:,ibnd,atom2proj],\&#xA;                color='red',alpha=0.3)&#xA;    # plotting fat band for Cl&#xA;    atom2proj = 4&#xA;    plt.scatter(band_distance,phonon_freq[:,ibnd],\&#xA;                s=400*phonon_eigv[:,ibnd,atom2proj],\&#xA;                color='blue',alpha=0.3)&#xA;plt.savefig('proj_phonon.png')&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have tested this on the CaTe system (&lt;a href=&quot;https://materialsproject.org/materials/mp-1519?formula=CaTe&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialsproject.org/materials/mp-1519?formula=CaTe&lt;/a&gt;). The results are shown below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/AqFVU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AqFVU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1804" LastEditorUserId="1804" LastEditDate="2023-05-19T09:31:45.170" LastActivityDate="2023-05-19T09:31:45.170" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10927" PostTypeId="1" AcceptedAnswerId="10939" CreationDate="2023-05-18T18:39:14.673" Score="1" ViewCount="173" Body="&lt;p&gt;I wish to set the DFT+U parameters (ideally with the Liechtenstein’s formulation) using ASE and the Quantum Espresso calculator. I have seen that the format for QE has been updated to give the Hubbard card: &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide_PDF/Hubbard_input.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/user_guide_PDF/Hubbard_input.pdf&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have looked at using the &lt;code&gt;write_espresso_in&lt;/code&gt; functions from ASE as described here: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html&lt;/a&gt;. However, the documentation is a bit confusing and seems to indicate it is implemented and it is not implemented.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to do this either in the input_data dictionary argument, for example (with Ni2MnGa):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;input_data = {&amp;quot;hubbard&amp;quot;: &#xA;                 {&amp;quot;U&amp;quot;:[[&amp;quot;Mn-3d&amp;quot;, 5.0][&amp;quot;Ni-3d&amp;quot;, 6.0]],&#xA;                  &amp;quot;J&amp;quot;:[[&amp;quot;Mn-3d&amp;quot;, 2.0][&amp;quot;Ni-3d&amp;quot;, 2.0]],&#xA;                  &amp;quot;formulation&amp;quot;:&amp;quot;Liechtenstein&amp;quot;}&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="786" LastActivityDate="2023-05-21T16:00:35.653" Title="Use Atomic Simulation Environment to set DFT+U parameters with Quantum Espresso" Tags="|quantum-espresso|atomic-simulation-environment|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10928" PostTypeId="1" CreationDate="2023-05-18T22:53:46.670" Score="3" ViewCount="67" Body="&lt;p&gt;I have three components, &lt;span class=&quot;math-container&quot;&gt;$A,B,C$&lt;/span&gt;, with 3 Flory-Huggins exchange parameters: &lt;span class=&quot;math-container&quot;&gt;$\chi _{AB}, \chi _{BC}, \chi _{AC}$&lt;/span&gt;. I want to create a ternary diagram to see how such a mixture behaves and how phase separation takes place i.e find points on the ternary plot where I will see &lt;span class=&quot;math-container&quot;&gt;$(A+B,C), (A+C,B), (B+C,A), (A+B+C), (A,B,C)$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$I+J$&lt;/span&gt; represents a mixed phase of &lt;span class=&quot;math-container&quot;&gt;$I,J$&lt;/span&gt; and a separation by a comma &lt;span class=&quot;math-container&quot;&gt;$&quot;,&quot;$&lt;/span&gt; indicates the third species is in a different phase.&lt;/p&gt;&#xA;&lt;p&gt;The ternary spinodal condition is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$D=\frac{\partial ^2 f}{\partial \phi _B ^2}\Bigg|_{N,T,\phi_A}\frac{\partial ^2 f}{\partial \phi _A ^2}\Bigg|_{N,T,\phi _B} - \left( \frac{\partial ^2 f}{\partial \phi _B \partial \phi _A} \Bigg| _{N,T}\right)^2 = 0$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;My question is, how do I find the regions on the ternary plot indicated above? How do I find the region where two species are mixed while the third one is not?&lt;/p&gt;&#xA;&lt;p&gt;I am not quite sure what it means when A+B is in a mixed state and when C is not. Does this mean that &lt;span class=&quot;math-container&quot;&gt;$\mu _A = \mu _B \neq \mu _C$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;This is basically the figure I want to make &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/ma00128a005&quot; rel=&quot;nofollow noreferrer&quot;&gt;from this paper&lt;/a&gt;:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/vPwtN.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vPwtN.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any advice you have for me.&lt;/p&gt;&#xA;" OwnerUserId="1070" LastActivityDate="2023-05-18T22:53:46.670" Title="How do I plot ternary phase diagrams using Flory-Huggins solution theory?" Tags="|thermodynamics|phase-diagram|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10929" PostTypeId="1" AcceptedAnswerId="10931" CreationDate="2023-05-19T10:04:20.763" Score="5" ViewCount="793" Body="&lt;p&gt;Beginners here, to ASE. I've create a 2x2x2 supercell of TiO2 from unit cell (.cif file obtained from &lt;a href=&quot;https://legacy.materialsproject.org/materials/mp-2657/#&quot; rel=&quot;noreferrer&quot;&gt;LegacyMaterialsProject&lt;/a&gt; ) using ASE. The script code is attached as follows. The outcome is shown as part (A) of the picture. However, I want to include another additional one atomic layer into the 20Å vacuum slab. What can I do to improve the script code so that I can get the structure indicated as the image part (B)?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;from ase.io import read, write&#xA;from ase.build.supercells import make_supercell&#xA;from ase.visualize import view&#xA;&#xA;#Make supercell of 2x2x2&#xA;M = [[2, 0, 0], [0, 2, 0], [0, 0, 2]]&#xA;cif = io.read('TiO2_mp-2657_computed.cif')&#xA;sc=make_supercell(cif, M)&#xA;&#xA;#Export supercell into vasp&#xA;write('supercell.vasp', sc, vasp5=True, sort=True, direct=False)&#xA;&#xA;#Add vacuum of 20Å (10Å top-bottom)&#xA;vac = io.read('supercell.vasp')&#xA;vac.center(vacuum=10, axis=2)&#xA;&#xA;#Export vac into vasp&#xA;write('supercell_20vac_test.vasp', vac, vasp5=True, sort=True, direct=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HvCM0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HvCM0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7238" LastEditorUserId="6687" LastEditDate="2023-05-19T11:43:56.817" LastActivityDate="2023-07-10T07:03:15.800" Title="Atomic Simulation Environment (ASE) Modelling. Adding additional layer" Tags="|python|molecular-modeling|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10930" PostTypeId="1" AcceptedAnswerId="10934" CreationDate="2023-05-19T10:59:25.723" Score="4" ViewCount="68" Body="&lt;p&gt;I want to compute the electronic structure of a heterostructure composed of two 2D monolayers. I am stacking a TMD monolayer on top of a magnetic 2D monolayer. Both of them are semiconductors.&lt;/p&gt;&#xA;&lt;p&gt;Do I need to include smearing when I compute the electronic structure or not?&lt;/p&gt;&#xA;" OwnerUserId="2088" LastActivityDate="2023-05-21T04:59:33.780" Title="Modelling 2D semiconductor heterostructures including one magnetic layer with QE" Tags="|quantum-espresso|electronic-structure|magnetism|2d-lattice|heterostructures|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10931" PostTypeId="2" ParentId="10929" CreationDate="2023-05-19T13:32:46.647" Score="7" Body="&lt;p&gt;To build a 5 layer TiO2 surface slab, you need to first build a 2x2x3 supercell and then remove the top layer. To do this, you need to first identify the atom indices in layer 0, 1, 2, 3, 4, 5 (counting from bottom) using &lt;a href=&quot;https://databases.fysik.dtu.dk/ase/ase/geometry.html#ase.geometry.get_layers&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.geometry.get_layers&lt;/code&gt;&lt;/a&gt;, and then select only the atom indices that have the layer number smaller than 5.&lt;/p&gt;&#xA;&lt;p&gt;You can use the code below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;from ase.io import read, write&#xA;from ase.build.supercells import make_supercell&#xA;from ase.visualize import view&#xA;from ase.geometry import get_layers&#xA;import numpy as np&#xA;&#xA;#Make supercell of 2x2x3&#xA;M = [[2, 0, 0], [0, 2, 0], [0, 0, 3]]&#xA;cif = io.read('TiO2_mp-2657_computed.cif')&#xA;sc=make_supercell(cif, M)&#xA;sc.center(vacuum=10, axis=2)&#xA;view(sc)&#xA;&#xA;layers = get_layers(sc, (0, 0, 1), tolerance=0.3)[0]&#xA;indices = np.argwhere(layers&amp;lt;np.max(layers)).ravel()&#xA;new_sc = sc[indices]&#xA;new_sc.center(vacuum=10, axis=2)&#xA;view(new_sc)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-10T07:03:15.800" LastActivityDate="2023-07-10T07:03:15.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10933" PostTypeId="1" CreationDate="2023-05-20T14:13:56.730" Score="4" ViewCount="91" Body="&lt;h1&gt;Context:&lt;/h1&gt;&#xA;&lt;p&gt;I am a student of cheminformatics, and I am trying to solve a problem in predicting whether atom can be an acceptor/donor of hydrogen bonds, using Python programming language and RDKit library.&lt;/p&gt;&#xA;&lt;p&gt;My molecules are described as graphs, where each atom is a node and each bond is an arc. Each node (atom) contains a vector of size 1 x 14, where 14 are features that I associate with that atom. Based on these features I then go on to predict whether that group will be an acceptor/donor/both of H bonds. Let's look at an example, suppose we have a C=O group, and consider the features of oxygen:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If the feature associated with the atomic number is equal to 8;&lt;/li&gt;&#xA;&lt;li&gt;If the feature associated with the number of hydrogen bonds is equal to 0;&lt;/li&gt;&#xA;&lt;li&gt;If the feature associated with hybridization is equal to 3 (SP2);&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;We can understand that that oxygen is part of a carbonyl group and then it is a hydrogen bond acceptor, and up to this point I have no special problems.&lt;/p&gt;&#xA;&lt;h1&gt;Problem&lt;/h1&gt;&#xA;&lt;p&gt;The problem arises when I need to take into account the chemical surroundings to make this prediction. As in the case of a nitro group (NO2) or the NH group in alpha to carbonyl (which is no longer an acceptor). With my technique (at the bottom I also leave the code for those who are curious) it is difficult to consider this chemical surroundings as well.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have experience with problems like this? I had thought of also making the prediction on the basis of the partial charge of the atom, but I cannot find references in the literature, such as a threshold of the charge through which one goes from acceptor to donor.&lt;/p&gt;&#xA;&lt;h1&gt;Code&lt;/h1&gt;&#xA;&lt;p&gt;Here I leave you an example of the code used, where the rules were defined only for the carbonyl and alcohol groups.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def h_acc(arr):&#xA;  # arr is my features vector, is a Python list&#xA;  &#xA;  if arr[0] == 8 and arr[9] != 0 and arr[7] == 4: # arr[0] etc. are respectively the columns associated with atomic number, number of bound Hs and hybridization&#xA;    arr.append(1) # we add feature 1 to the bottom of our vector, because OH is an acceptor&#xA;&#xA;  if arr[0] == 8 and arr[9] == 0 and arr[7] == 3:&#xA;    arr.append(1) # we add feature 1 to the bottom of our vector, because C=O is an acceptor&#xA;&#xA;  else:&#xA;    arr.append(0) # we add feature 0 to the bottom of our vector, in all other cases that are not acceptors&#xA;&#xA;  return arr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Note:&lt;/h1&gt;&#xA;&lt;p&gt;Later rules were also included for other chemical groups, and a very similar function was written to predict whether that group will be a donor.&lt;/p&gt;&#xA;" OwnerUserId="4898" LastEditorUserId="6687" LastEditDate="2023-05-20T17:14:01.530" LastActivityDate="2023-05-20T17:14:01.530" Title="Predict if a group will be acceptor/donor of H bonds" Tags="|python|mathematical-modeling|machine-learning|cheminformatics|hydrogen-bonds|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-01T21:53:17.430" ContentLicense="CC BY-SA 4.0" />
  <row Id="10934" PostTypeId="2" ParentId="10930" CreationDate="2023-05-21T01:27:26.047" Score="4" Body="&lt;p&gt;Regardless of the type of material, using small smearing often helps in the convergence procedure. However, there are some caveats to look for.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Always make sure that the smearing value is neither too small nor too large. Run a few convergence tests with different types of smearing to find the appropriate &lt;code&gt;degauss&lt;/code&gt; value and &lt;code&gt;smearing&lt;/code&gt; type.&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;smearing&lt;/code&gt; is somewhat coupled to k-point sampling. So, maybe you want to converge &lt;code&gt;ecutwfc&lt;/code&gt;, &lt;code&gt;ecutrho&lt;/code&gt;, and &lt;code&gt;K_POINTS&lt;/code&gt; before converging the &lt;code&gt;degauss&lt;/code&gt; value.&lt;/li&gt;&#xA;&lt;li&gt;Smearing is needed for metallic systems to obtain convergence. And it doesn't harm to have a small smearing in semiconductors or insulators too! It affects the electronic energy a little bit but by carefully choosing the &lt;code&gt;degauss&lt;/code&gt; value, you can reduce such an effect. (see answers to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/2016/6055&quot;&gt;this&lt;/a&gt; question for details)&lt;/li&gt;&#xA;&lt;li&gt;As far as I know, choosing the &lt;code&gt;smearing&lt;/code&gt; type or &lt;code&gt;degauss&lt;/code&gt; value has nothing to do with whether the system is magnetic or not. Usually for any kind of system &lt;code&gt;gaussian&lt;/code&gt; smearing is safe to choose. But as I said previously, maybe test the convergence first. Even though &lt;code&gt;gaussian&lt;/code&gt; is safer, but &lt;code&gt;mp&lt;/code&gt; or &lt;code&gt;mv&lt;/code&gt; smearing often gives a substantial advantage.&lt;/li&gt;&#xA;&lt;li&gt;If you need to do the DOS calculation, &lt;code&gt;occupations='tetrahedra'&lt;/code&gt; or &lt;code&gt;occupations='tetrahedra_opt'&lt;/code&gt; methods are preferred instead of &lt;code&gt;smearing&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;So, to answer your question precisely, you don't need to use smearing. But probably you will have a hard time achieving convergence if you don't use it. That's why, as a practical method, you can use a small smearing to accelerate the convergence procedure. The code automatically tries to remove any effects due to smearing (fictitious finite temperature effects) after the calculation. Just make sure that this smearing value is not too large. Otherwise, you will get inaccurate ground state properties since the code will have a hard time removing the effects.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-05-21T04:59:33.780" LastActivityDate="2023-05-21T04:59:33.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10935" PostTypeId="2" ParentId="10925" CreationDate="2023-05-21T06:18:40.880" Score="1" Body="&lt;p&gt;I tried running the code that you provided: and I did observe the following issues with it:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CRYST1    8.664    8.295    8.300  90.00  90.00  90.00 P 1           1&#xA;ATOM      1  C1  PHEEX   1     -10.331   2.354   0.160  0.00  0.00      PHEE C&#xA;ATOM      2  C2  PHEEX   1      -8.818   2.260   0.255  0.00  0.00      PHEE C&#xA;ATOM      3  H3  PHEEX   1     -10.734   1.553  -0.467  0.00  0.00      PHEE H&#xA;ATOM      4  H4  PHEEX   1     -10.638   3.314  -0.268  0.00  0.00      PHEE H&#xA;ATOM      5  H5  PHEEX   1     -10.779   2.266   1.154  0.00  0.00      PHEE H&#xA;ATOM      6  C6  PHEEX   1      -8.159   2.359  -1.118  0.00  0.00      PHEE C&#xA;ATOM      7  H7  PHEEX   1      -8.549   1.314   0.738  0.00  0.00      PHEE H&#xA;ATOM      8  H8  PHEEX   1      -8.433   3.054   0.906  0.00  0.00      PHEE H&#xA;ATOM      9  H9  PHEEX   1      -8.466   1.535  -1.772  0.00  0.00      PHEE H&#xA;ATOM     10  O10 PHEEX   1      -6.735   2.409  -1.025  0.00  0.00      PHEE O&#xA;ATOM     11  H11 PHEEX   1      -8.472   3.290  -1.603  0.00  0.00      PHEE H&#xA;ATOM     12  C12 PHEEX   1      -6.140   1.152  -0.713  0.00  0.00      PHEE C&#xA;ATOM     13  C13 PHEEX   1      -4.635   1.297  -0.828  0.00  0.00      PHEE C&#xA;ATOM     14  H14 PHEEX   1      -6.491   0.384  -1.410  0.00  0.00      PHEE H&#xA;ATOM     15  H15 PHEEX   1      -6.398   0.859   0.309  0.00  0.00      PHEE H&#xA;ATOM     16  H16 PHEEX   1      -4.352   1.582  -1.847  0.00  0.00      PHEE H&#xA;ATOM     17  H17 PHEEX   1      -4.132   0.360  -0.573  0.00  0.00      PHEE H&#xA;ATOM     18  H18 PHEEX   1      -4.270   2.087  -0.163  0.00  0.00      PHEE H&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the PDB file that was generated from the updated SDF file&lt;/p&gt;&#xA;&lt;p&gt;The first issue was regarding the SDF file which was provided as a text block. I have since cleaned it up and pasted it as a code block in the question.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from openmm             import *&#xA;from openmm.app         import *&#xA;from simtk.unit         import *&#xA;&#xA;from openff.toolkit     import ForceField, Molecule&#xA;from openff.units       import unit&#xA;from openff.interchange import Interchange&#xA;&#xA;molecule    =   Molecule.from_file(&amp;quot;cleaned.sdf&amp;quot;) # use the sdf file that I have placed&#xA;Topology    =   molecule.to_topology()&#xA;&#xA;coordinates =   PDBFile(&amp;quot;phenolethylether.pdb&amp;quot;)&#xA;positions   =   coordinates.getPositions()&#xA;&#xA;Topology.box_vectors = Quantity([15, 15, 15], nanometer)&#xA;&#xA;sage        =   ForceField(&amp;quot;openff-2.0.0.offxml&amp;quot;)&#xA;interchange =   Interchange.from_smirnoff(topology=[molecule], force_field=sage)&#xA;&#xA;openmm_system   = interchange.to_openmm()&#xA;integrator      = LangevinIntegrator(300 * kelvin, 1 / picosecond, 2 * femtoseconds)&#xA;simulation      = Simulation(Topology, openmm_system, integrator)&#xA;simulation.context.setPositions(positions)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the code that i used to check if your code was actually creating a system of 15x15x15 molecules. However, the code does not do that and instead sets the PBC conditions in x-,y- and z-axis to 15 nanometers. &lt;strong&gt;This is probably not what you want.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;So to investigate if i can create a system consisting of 10x10x10 molecules, i used the following code to generate a PDB file containing 1000 molecules.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set pdb phenolethylether.pdb&#xA;&#xA;set a 9&#xA;set b 9&#xA;set c 9&#xA;&#xA;set xdist 10&#xA;set ydist 10&#xA;set zdist 10&#xA;&#xA;set xend [expr &lt;span class=&quot;math-container&quot;&gt;$a / 2]&#xA;set xstart [expr -1 * $&lt;/span&gt;xend]&#xA;&#xA;set yend [expr &lt;span class=&quot;math-container&quot;&gt;$b / 2]&#xA;set ystart [expr -1 * $&lt;/span&gt;yend]&#xA;&#xA;set zend [expr &lt;span class=&quot;math-container&quot;&gt;$c / 2]&#xA;set zstart [expr -1 * $&lt;/span&gt;zend]&#xA;&#xA;set counter 1&#xA;&#xA;for { set xcounter &lt;span class=&quot;math-container&quot;&gt;$xstart } { $xcounter &amp;lt;= $xend } { incr xcounter } {&#xA;    set xtrans [expr $xdist * $xcounter]&#xA;    for { set ycounter $ystart } { $ycounter &amp;lt;= $yend } { incr ycounter } {&#xA;        set ytrans [expr $ydist * $ycounter]&#xA;        for { set zcounter $zstart } { $zcounter &amp;lt;= $zend } { incr zcounter } {&#xA;            set ztrans [expr $zdist * $zcounter]&#xA;            mol new $pdb type pdb&#xA;            set sel [atomselect top all]&#xA;            set com [measure center $sel weight mass]&#xA;            $sel moveby [vecscale -1 $com]&#xA;            $sel moveby [list $xtrans $ytrans $ztrans]&#xA;            $sel set segname M$counter&#xA;            $sel set resid $counter&#xA;            $sel writepdb test.$xcounter.$ycounter.$&lt;/span&gt;zcounter.pdb&#xA;            mol delete all&#xA;            incr counter&#xA;        }&#xA;    }&#xA;}&#xA;&#xA;package require topotools 1.6&#xA;set molList {}&#xA;&#xA;for { set xcounter &lt;span class=&quot;math-container&quot;&gt;$xstart } { $xcounter &amp;lt;= $xend } { incr xcounter } {&#xA;for {set ycounter $ystart } { $ycounter &amp;lt;= $yend } { incr ycounter } {&#xA;    for {set zcounter $zstart } { $zcounter &amp;lt;= $zend } { incr zcounter } {&#xA;        set mol [mol new test.$xcounter.$ycounter.$zcounter.pdb type pdb]&#xA;        lappend molList $&lt;/span&gt;mol&#xA;        }&#xA;    }&#xA;}&#xA;&#xA;set mol [::TopoTools::mergemols $molList]&#xA;animate write pdb final.pdb&#xA;&#xA;&#xA;mol delete all&#xA;mol new final.pdb&#xA;&#xA;package require pbctools 2.8&#xA;&#xA;set sel [atomselect top all]&#xA;set minmaxs [measure minmax &lt;span class=&quot;math-container&quot;&gt;$sel]&#xA;set pbcvec [vecsub [lindex $&lt;/span&gt;minmaxs 1] [lindex $minmaxs 0]]&#xA;&#xA;set pbcx [expr {round[lindex &lt;span class=&quot;math-container&quot;&gt;$pbcvec 0]]}]&#xA;set pbcy [expr {round[lindex $pbcvec 1]]}]&#xA;set pbcz [expr {round[lindex $&lt;/span&gt;pbcvec 2]]}]&#xA;&#xA;pbc set &lt;span class=&quot;math-container&quot;&gt;$pbcvec&#xA;$&lt;/span&gt;sel writepdb final.pbc.pdb&#xA;&#xA;exit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, When i tried loading this file to provide the positions, I got an error saying &lt;code&gt;openmm.OpenMMException: Called setPositions() on a Context with the wrong number of positions&lt;/code&gt; which is expected since the SDF file only contains 18 atoms and the PDB file now contains 18,000 atoms.&lt;/p&gt;&#xA;&lt;p&gt;To troubleshoot this, I tried creating an SDF file from the generated PDB file. This was recognized by the code, and the positions were set. However, we now get a new error &lt;code&gt;/home/ssm_grp/anaconda3/envs/openmm/lib/python3.10/site-packages/openff/interchange/smirnoff/_nonbonded.py:385: UserWarning: Warning! Partial charge method 'am1bcc' is not designed for use on large (i.e. &amp;gt; 150 atoms) molecules and may crash or take hours to run on this molecule (found 13122 atoms). For more, see https://docs.openforcefield.org/projects/toolkit/en/stable/faq.html#parameterizing-my-system-which-contains-a-large-molecule-is-taking-forever-whats-wrong molecule.assign_partial_charges(method)&lt;/code&gt; and this crashed immediately after this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Note&lt;/strong&gt;&#xA;The reason why the code ran for you is because you were simulating only one molecule placed in a 4x4x4 &lt;span class=&quot;math-container&quot;&gt;$nm^3$&lt;/span&gt; box, and the assignment of partial charges will proceed without any issues.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Suggestions&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;If you can, try generating files for AmberFF or CHARMM FF and used the corresponding files to setup the calculations. This would take away the issues related to partial charge calculations and topologies.&lt;/li&gt;&#xA;&lt;li&gt;If not, try reducing the system size to something that is less than 150 (but this defeats the purpose of doing an MD simulation)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-05-21T06:47:27.793" LastActivityDate="2023-05-21T06:47:27.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10936" PostTypeId="1" AcceptedAnswerId="10972" CreationDate="2023-05-21T08:46:35.533" Score="4" ViewCount="205" Body="&lt;p&gt;I want to make a DFT code (by myself) that works in the RKS LDA H2 configuration. This post is a continuation of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10932/what-is-wrong-with-my-results-for-h2-i-used-rks-lda-only-exchange-and-scf-r&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now by adding the &lt;a href=&quot;https://cdnsciencepub.com/doi/10.1139/p80-159&quot; rel=&quot;nofollow noreferrer&quot;&gt;Vosko, Wilk, Nusair correlation&lt;/a&gt; I have much better results :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9CtLl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9CtLl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But when compared to results of this &lt;a href=&quot;https://citeseerx.ist.psu.edu/document?repid=rep1&amp;amp;type=pdf&amp;amp;doi=2f216baa7c6ffad4537c61cc8360043cdca8faa7&quot; rel=&quot;nofollow noreferrer&quot;&gt;article&lt;/a&gt;, the energy I got seems greater compared to the article. I am thinking that the exchange energy might be the problem. The results can be found &lt;a href=&quot;https://github.com/MaximeLee/qmodelling/blob/main/examples/dft/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The most important picture to look at being the exchange-correlation energy Exc_VWN.png. I ran H2_RHF_STO3G_becke.py.&lt;/p&gt;&#xA;&lt;p&gt;The Dirac exchange energy is given by :&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_x^{Dirac} = \int \rho \epsilon_x(\rho) = -\frac{3}{4}(\frac{3}{\pi})^{1/3} \int \rho^{4/3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Hence the exchange potential is :&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ v_x(\rho) = -(\frac{3}{\pi}\rho)^{1/3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I am not sure if it is right. I have two resources that defines the exchange energy in the case where you have &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; densities :&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Introduction to Computational Chemistry, Frank Jensen, third edition, p 247 :&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_x^{LSDA} = -2^{1/3} \frac{3}{4}(\frac{3}{\pi})^{1/3} \int \rho_{\alpha}^{4/3} + \rho_{\beta}^{4/3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is not consistant with the case where you consider an unique electron density (for RKS and RHF methods). By continuing to read, I stumbled upon the &lt;span class=&quot;math-container&quot;&gt;$X_{alpha}$&lt;/span&gt; LDA methods.&#xA;so I have a question:&lt;/p&gt;&#xA;&lt;p&gt;How is LSDA exchange energy is derived? And why is it not consistent with the RKS case where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; electrons have the same density also the LDA case?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-05-25T19:08:52.803" LastActivityDate="2023-05-29T21:39:51.643" Title="Dirac exchange energy and X_alpha LDA methods" Tags="|density-functional-theory|python|numerical-convergence|exchange-correlation|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10937" PostTypeId="1" AcceptedAnswerId="10961" CreationDate="2023-05-21T12:48:47.820" Score="5" ViewCount="214" Body="&lt;p&gt;For example, I am reading a paper, where they put one layer on top of another, and in order to minimize the lattice mismatch, they transform unit cells of both layers.&lt;/p&gt;&#xA;&lt;p&gt;They report it in a root integer notation. Layer 1: &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{13}\times\sqrt{13})\,R\,13.9^\circ$&lt;/span&gt;, Layer 2: &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{19}\times\sqrt{19})\,R\,23.4^\circ$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;How to get the elements of the transformation matrices from this information?&lt;/p&gt;&#xA;&lt;p&gt;I read in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6486/help-understanding-square-root-notation-of-supercell&quot;&gt;this answer&lt;/a&gt; that &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{3}\times\sqrt{3})\,R\,30^\circ$&lt;/span&gt; corresponds to the rotation matrix &lt;span class=&quot;math-container&quot;&gt;$$\begin{matrix}&#xA;2 &amp;amp; 1 &amp;amp; 0\\&#xA;-1 &amp;amp; 1 &amp;amp; 0 \\&#xA;0 &amp;amp; 0 &amp;amp; 1&#xA;\end{matrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, it is not explained in that answer, how these matrix elements are obtained.&lt;/p&gt;&#xA;&lt;p&gt;How to get rotation matrix in general case from root integer notation?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-05-26T16:36:10.090" Title="How to get rotation matrix elements from root integer notation?" Tags="|geometry|supercell|cell-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10938" PostTypeId="1" CreationDate="2023-05-21T13:33:04.713" Score="3" ViewCount="75" Body="&lt;p&gt;I wonder if anyone here knows about additional atomic parameters and interactions sets for atoms not currently present in the DFTB parameter sets. The parameter sets are located at &lt;a href=&quot;https://dftb.org/parameters/download&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFTB parameters&lt;/a&gt;. For example, I am interested in simulating systems that contain tetrafluoroborate anion, FB-(F)F. However, I have not across B-F interaction sets. Is anybody aware of a parametrization procedure to add new atomic interaction pairs to DFTB, or if any proprietary software already includes parameters beyond those provided at the link.&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&lt;/p&gt;&#xA;" OwnerUserId="5113" LastActivityDate="2023-05-21T13:33:04.713" Title="DFTB+ parameters for additional atoms" Tags="|computational-chemistry|dftb-plus|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10939" PostTypeId="2" ParentId="10927" CreationDate="2023-05-21T16:00:35.653" Score="3" Body="&lt;p&gt;You can use the ASE fork available in my personal repository to handle this. You can find it at gitlab.com/tomdemeyere/ase. The relevant code is located in ase/io/espresso.py. To locate the relevant code quickly, you can use Ctrl+F and search for 'hubbard'.&lt;/p&gt;&#xA;&lt;p&gt;To incorporate the required changes, you need to specify two additional parameters in the Espresso class:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Espresso(..., hubbard, hubbard_data)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The hubbard parameter is a string that should be one of the following options: atomic, ortho-atomic, norm-atomic, wf, or pseudo.&lt;/p&gt;&#xA;&lt;p&gt;The hubbard_data parameter is expected to be a dictionary containing lists of strings. Each key in the dictionary should correspond to one of the following: U, J, B, V, or J0. For each key, the corresponding value should be a list of strings.&lt;/p&gt;&#xA;&lt;p&gt;To achieve the desired result:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;HUBBARD (ortho-atomic)&#xA;  U  Mn-3d 5.0&#xA;  J0 Mn-3d 1.0&#xA;  U  Ni-3d 6.0&#xA;  J0 Ni-3d 1.2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You should set the values as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;hubbard = 'ortho-atomic'&#xA;hubbard_data = {&#xA;    'U': ['Mn-3d 5.0', 'Ni-3d 6.0'],&#xA;    'J0': ['Mn-3d 1.0', 'Ni-3d 1.2']&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The order of the elements within the dict/lists does not matter.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2023-05-21T16:00:35.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10940" PostTypeId="2" ParentId="10595" CreationDate="2023-05-21T18:30:39.923" Score="0" Body="&lt;p&gt;It would be suggested to use &lt;strong&gt;molecular descriptors&lt;/strong&gt; such as Distance matrix, Randic Connectivity Index, Wiener Index, etc as metrics to differentiate the two states.&lt;/p&gt;&#xA;&lt;p&gt;In order to understand the concept of molecular descriptors, refer to presentation &lt;a href=&quot;https://www.academia.edu/download/30818009/RTodeschini.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; and Chapter 3 &lt;em&gt;Molecular Descriptors&lt;/em&gt; of book &lt;em&gt;Challenges and Advances in Computational Chemistry and Physics&lt;/em&gt; (COCH,volume 8).&lt;/p&gt;&#xA;&lt;p&gt;There are few softwares for calculation of Molecular descriptors of a system, one of them is &lt;strong&gt;PaDEL-Descriptor&lt;/strong&gt;. Refer to paper: &lt;a href=&quot;https://doi.org/10.1002/jcc.21707&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; to know more about the software.&lt;/p&gt;&#xA;" OwnerUserId="6422" LastActivityDate="2023-05-21T18:30:39.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10941" PostTypeId="2" ParentId="10914" CreationDate="2023-05-21T18:58:40.170" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://gaussian.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian&lt;/a&gt; and &lt;a href=&quot;https://hpc.hku.hk/hpc/software/orca/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ORCA&lt;/a&gt; can calculate the heat as well as free energies of formation of a given system.&lt;/p&gt;&#xA;" OwnerUserId="6422" LastActivityDate="2023-05-21T18:58:40.170" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10942" PostTypeId="1" AcceptedAnswerId="10971" CreationDate="2023-05-22T11:37:24.537" Score="4" ViewCount="64" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mcp5u.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mcp5u.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;Structure shown in (a) is the regular &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-indacene molecule, and (b) is a structure that i generated such that the central six-member ring remains similar to benzene. It is well-known in literature that the electronic structure of &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-indacene is contested, with multiple groups suggesting a fully-delocalized &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; symmetry, and others suggesting a bond-localized &lt;span class=&quot;math-container&quot;&gt;$C_{2h}$&lt;/span&gt; symmetry for the molecule. I recently found a &lt;a href=&quot;https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/63eabe7a1d2d18406370e80d/original/tetra-tert-butyl-s-indacene-is-a-bond-localized-c2h-structure-even-more-bad-news-for-b3lyp.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; contesting the use of B3LYP for core-expanded systems (like &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-indacene). My question concerns the probable existence of the structure represented in (b). Will that be the reason why some groups got a &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; minima?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Further context:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am interested in studying the electronic properties of periodic systems that can be generated from &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-indacene. As a first step, I tried optimizing the geometry of the molecule with the fully delocalized &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; symmetry. I observed that this structure is a first-order saddle-point on the potential energy surface with an imaginary mode of 354.52 cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; converting the &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; structure to &lt;span class=&quot;math-container&quot;&gt;$C_{2h}$&lt;/span&gt; symmetry. However, when i tried optimizing the molecule with a triplet ground state, I observed that it was a minimum on the potential energy landscape, but the total energy was ~ 0.57 eV higher than the singlet &lt;span class=&quot;math-container&quot;&gt;$C_{2h}$&lt;/span&gt; state. Now, If i try optimizing the molecule with a triplet starting guess and force it to a singlet state, I can get a new singlet minima with &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; symmetry, which is ~ 0.03 eV lower than the &lt;span class=&quot;math-container&quot;&gt;$C_{2h}$&lt;/span&gt; symmetry. This led me to think that the structure represented in (b) might be (at least partially) responsible for the observed &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; symmetry state. This state should have two electrons, which are spatially separated but still remaining as &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spins.&lt;/p&gt;&#xA;&lt;p&gt;References&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1002/anie.199411921&quot; rel=&quot;nofollow noreferrer&quot;&gt;s-Indacene: A Delocalized, Formally Antiaromatic 12 π Electron System&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0166128098004217&quot; rel=&quot;nofollow noreferrer&quot;&gt;s-Indacene, a quasi-delocalized molecule with mixed&#xA;aromatic and anti-aromatic character&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-05-22T15:07:59.593" LastActivityDate="2023-05-27T07:20:04.483" Title="Electronic structure of s-indacene" Tags="|density-functional-theory|molecular-modeling|electronic-structure|symmetry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10943" PostTypeId="1" AcceptedAnswerId="10944" CreationDate="2023-05-22T14:24:54.417" Score="7" ViewCount="202" Body="&lt;p&gt;I would like to know whether, at least in principle, minimization of energy with respect to nuclear coordinates leads to the same result as minimization of cell energy with respect to lattice parameters. Is one way computationally more advantageous than the other? Thanks in advance, also I'm sorry if the question might not be accurately formulated.&lt;/p&gt;&#xA;" OwnerUserId="7254" LastActivityDate="2023-05-22T14:53:07.727" Title="Geometry optimization: nuclear coordinates vs lattice parameters" Tags="|density-functional-theory|condensed-matter|geometry-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10944" PostTypeId="2" ParentId="10943" CreationDate="2023-05-22T14:53:07.727" Score="7" Body="&lt;p&gt;Minimizing energy with respect to nuclear coordinates and with respect to lattice parameters are two very different things.&lt;/p&gt;&#xA;&lt;p&gt;Minimizing energy with respect to nuclear coordinates can be used for periodic and isolated systems.&lt;/p&gt;&#xA;&lt;p&gt;In the case of a periodic system, this will lead to knowing how the atoms and/or molecules are arranged inside a given crystallographic cell. In this instance, the crystal symmetry is a constraint on your system. If your system is an isolated molecule, there are no constraints, and you will have the conformer with the lowest energy.&lt;/p&gt;&#xA;&lt;p&gt;Minimizing the lattice parameters (in general, together with the nuclear coordinates) is done when you are starting from a bad structure, or you need to know if the system can have another crystallographic phase.&#xA;If you have crystallographic evidence that there are no other phases, then you can use the experimental lattice parameters as constants, and there is no need to optimize them.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Is one way computationally more advantageous than the other?&lt;/em&gt; There is no such thing as an advantage. All of this will depend on what you are studying and your needs.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-22T14:53:07.727" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10945" PostTypeId="1" CreationDate="2023-05-22T17:54:41.640" Score="3" ViewCount="51" Body="&lt;p&gt;I don't quite fully understand the derivation of the &lt;a href=&quot;https://en.wikipedia.org/wiki/Maxwell_material&quot; rel=&quot;nofollow noreferrer&quot;&gt;Maxwell model&lt;/a&gt; for prediction of stress relaxation for viscoelstic materials. usually the governing equation can be described in terms of strain rate:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{d\epsilon}{dt} = \frac{d\sigma}{dt} \cdot \frac{1}{E} + \frac{\sigma}{\eta} \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the equation is then rearranged and integrated to get an equation in terms of stress and time.&lt;/p&gt;&#xA;&lt;p&gt;This may be a silly question but why is it incorrect for the equation to be written using strain rather than stress rate like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon = \frac{\sigma}{E} + \frac{\sigma}{\eta}t\tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And then rearranged for stress, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt;,  in terms of time, t like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sigma = \frac{\epsilon}{\frac{1}{E} + \frac{t}{\eta}}\tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7257" LastEditorUserId="5" LastEditDate="2023-05-22T18:25:54.113" LastActivityDate="2023-05-22T18:56:07.983" Title="Why is strain rate used instead of absolute strain for modelling stress relaxation of a viscoelastic material using the Maxwell model?" Tags="|mathematical-modeling|physical-properties-of-materials|materials-engineering|stress-strain|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10946" PostTypeId="1" AcceptedAnswerId="10948" CreationDate="2023-05-22T18:25:36.280" Score="5" ViewCount="213" Body="&lt;p&gt;I need the source code (written in C programming language) for the following book:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uRhzG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uRhzG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Page-&lt;code&gt;xiii&lt;/code&gt; of the book says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Software availability&lt;/strong&gt;&lt;br /&gt;&#xA;Readers interested in downloading the software described in this book in a computer-readable form for&#xA;personal, noncommercial use should visit the Cambridge University&#xA;Press web site at &lt;a href=&quot;http://uk.cambridge.org&quot; rel=&quot;noreferrer&quot;&gt;http://uk.cambridge.org&lt;/a&gt;, where the home page for&#xA;this book and the software can be found; a listing of the programs&#xA;included in the software package appears in the Appendix. Additional&#xA;material related to the book, as well as contact information, can be&#xA;found at the author’s website – &lt;a href=&quot;http://www.ph.biu.ac.il/%7Erapaport&quot; rel=&quot;noreferrer&quot;&gt;http://www.ph.biu.ac.il/~rapaport&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;None of the supplied URLs work as intended. Both are invalid URLs.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.cambridge.org/core/books/art-of-molecular-dynamics-simulation/57D40C5ECE9B7EA17C0E77E7754F5874&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;This link&lt;/strong&gt;&lt;/a&gt; seems to be the page for the book. However, I haven't found the source code.&lt;/p&gt;&#xA;&lt;p&gt;Where can I find the source code from the book &amp;quot;The Art of Molecular Dynamics Simulation&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-05-23T08:27:31.683" Title="Where can I find the source code from the book &quot;The Art of Molecular Dynamics Simulation&quot;?" Tags="|reference-request|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10947" PostTypeId="2" ParentId="10945" CreationDate="2023-05-22T18:56:07.983" Score="2" Body="&lt;p&gt;If we integrate both sides of:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{d\epsilon}{dt} = \frac{d\sigma}{dt} \cdot \frac{1}{E} + \frac{\sigma}{\eta} \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with respect to time, we get:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\int_0^t \frac{d\epsilon}{dt^\prime} dt^\prime= \int_0^t \frac{d\sigma}{dt^\prime} \cdot \frac{1}{E} dt^\prime+ \int_0^t \frac{\sigma}{\eta} dt^\prime\tag{2}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It's fair to say that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\int_0^t \frac{d\epsilon}{dt^\prime} dt^\prime= \epsilon\tag{3},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and if &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is constant with respect to time, it's fair to say that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\int_0^t \frac{d\sigma}{dt^\prime} \cdot \frac{1}{E} dt^\prime= \frac{\sigma}{E}\tag{4}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the last term, &lt;em&gt;&lt;strong&gt;if &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; are constant with respect to time,&lt;/strong&gt;&lt;/em&gt;  then it's fair to say that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\int_0^t \frac{\sigma}{\eta} dt^\prime = \frac{\sigma}{\eta}t\tag{5},$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but if &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is constant with respect to time, then the original equation might as well be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{d\epsilon}{dt} =  \frac{\sigma}{\eta} \tag{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;since we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\frac{d\sigma}{dt} = 0.\tag{7} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Based on Eq. 1, it's fair to assume that &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; depends on time, so Eqs 2-4 lead us to the following formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\epsilon(t)= \frac{\sigma(t)}{E} + \frac{1}{\eta}\int_0^t \sigma(t^\prime) dt^\prime\tag{8}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you know how &lt;span class=&quot;math-container&quot;&gt;$\sigma(t)$&lt;/span&gt; depends on time, then you may be able to put Eq. 8 in &amp;quot;closed form&amp;quot;, but if that were the case, Eq. 1 would likely be presented in a more simple way. The fact that Eq. 1 is written in the way that it's written, suggests that &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; has some time-dependence which prevents us from using simpler equations like the ones that you proposed.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-05-22T18:56:07.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10948" PostTypeId="2" ParentId="10946" CreationDate="2023-05-23T08:27:31.683" Score="5" Body="&lt;p&gt;Thankfully &lt;a href=&quot;https://archive.org/web/&quot; rel=&quot;noreferrer&quot;&gt;WaybackMachine&lt;/a&gt; archived a copy of the Art of Molecular Dynamics Website.&lt;/p&gt;&#xA;&lt;p&gt;In this &lt;a href=&quot;https://web.archive.org/web/20010415185328/http://www.ph.biu.ac.il/%7Erapaport/mdbook/info.html&quot; rel=&quot;noreferrer&quot;&gt;link&lt;/a&gt;, you can find the C source code associated with the book, with the following information stated along with it.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The software that appears in the book is available for personal use;&#xA;the software is available here in tar+gzip and zip formats (please&#xA;contact the author if you have difficulty retrieving the software or&#xA;questions regarding its use).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-23T08:27:31.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10949" PostTypeId="1" CreationDate="2023-05-23T10:58:51.257" Score="5" ViewCount="605" Body="&lt;p&gt;I wonder, if someone has run (runs) parallel Orca calculations on at least two nodes &lt;em&gt;without&lt;/em&gt; a work load manager (scheduler)? I am asking because I have several interconnected servers (nodes) I'd like to run Orca on but there is no scheduler and I could not make Orca run on more than one server (node with several CPU-cores) so far.&lt;/p&gt;&#xA;" OwnerUserId="6296" LastEditorUserId="7" LastEditDate="2023-05-23T12:27:17.893" LastActivityDate="2023-05-28T09:13:27.927" Title="Running multinode parallel Orca calculation without a work load manager (scheduler)" Tags="|high-performance-computing|orca|job-scheduler|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10950" PostTypeId="2" ParentId="10949" CreationDate="2023-05-23T11:54:27.377" Score="7" Body="&lt;p&gt;Not sure if ORCA can be run using a user-chosen MPI runner but there are a few steps that need to be done in order to run ORCA (or any other MPI program) on a distributed/interconnect cluster (assuming that you are using an Ubuntu server with OpenMPI already installed (check again that the version of your OpenMPI is supported by ORCA). You have root permission or are sudoer).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You need to deal with a &lt;code&gt;hosts&lt;/code&gt; file on the master node of your cluster. In this file, you can specify the name of the worker machines you would like to do the calculation, for example:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ cat /etc/hosts&#xA;&#xA;127.0.0.1       localhost&#xA;172.xx.xx.1     worker1&#xA;172.xx.xx.2     worker2&#xA;172.xx.xx.3     worker3&#xA;172.xx.xx.4     worker4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that, make sure that each worker's &lt;code&gt;manager&lt;/code&gt; file has exactly the same content as the &lt;code&gt;hosts&lt;/code&gt; file of the master node.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Setup SSH for it&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The next step would be setting up SSH because this is the way that all machines communicate with each other. This can be done simply as you can find elsewhere on the internet with SSH tutorial:&lt;/p&gt;&#xA;&lt;p&gt;Install &lt;code&gt;openssh-server&lt;/code&gt; and generate a new key&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo apt­-get install openssh-server&#xA;ssh-keygen -t dsa&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Add the newly generated key to each worker, e.g&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ssh-copy-id worker1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then enable a passwordless SSH connection&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eval `ssh-agent`&#xA;ssh-add ~/.ssh/id_dsa&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Setup NFS in &lt;code&gt;manager&lt;/code&gt; which the worker nodes mount to exchange data &lt;em&gt;(You can skip this step if the NFS is already set up)&lt;/em&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;On NFS-server&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Install the required package&#xA;sudo apt-get install nfs-kernel-server&#xA;&#xA;cd $HOME/&#xA;mkdir scratch&#xA;&#xA;# Edit `/etc/exports` and add the following &#xA;/home/YOUR_USER_NAME/scratch *(rw,sync,no_root_squash,no_subtree_check)&#xA;&#xA;exportfs -a&#xA;&#xA;sudo service nfs-kernel-server restart&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can easily find the meaning of each keyword on the internet&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;On NFS-worker&lt;/strong&gt; (actually you do almost the same as NFS-server)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Install required package&#xA;sudo apt-get install nfs-common&#xA;&#xA;cd $HOME/&#xA;mkdir scratch&#xA;&#xA;sudo mount -t nfs manager:/home/YOUR_USER_NAME/scratch ~/scratch&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can use &lt;code&gt;df -h&lt;/code&gt; to check whether the directory is already mounted.&lt;/p&gt;&#xA;&lt;ol start=&quot;4&quot;&gt;&#xA;&lt;li&gt;Running an MPI program&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun -np 8 --hosts manager,worker1,worker2 FULL_PATH_TO_YOUR_ORCA&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You should try running a simple MPI program, e.g. printing Hello world, to make sure the process above works. You can find more details on the internet, like this website: &lt;a href=&quot;http://selkie.macalester.edu/csinparallel/modules/Patternlets/build/html/MessagePassing/RunningMPI.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://selkie.macalester.edu/csinparallel/modules/Patternlets/build/html/MessagePassing/RunningMPI.html&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;FWIW, hope this helps&lt;/p&gt;&#xA;" OwnerUserId="579" LastEditorUserId="579" LastEditDate="2023-05-28T09:13:27.927" LastActivityDate="2023-05-28T09:13:27.927" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10951" PostTypeId="1" CreationDate="2023-05-24T18:42:28.923" Score="4" ViewCount="90" Body="&lt;p&gt;I am currently screening more than 2000 compounds virtually on Vina, but I would like to perform covalent docking. Unfortunately, Vina's functionality is limited as its requires manual designation of the reactive atoms on the ligands. Is there any alternative that is free for academic purposes and suited for this sort of task?&lt;/p&gt;&#xA;" OwnerUserId="7273" LastEditorUserId="5" LastEditDate="2023-05-24T19:19:23.910" LastActivityDate="2023-05-26T05:31:04.477" Title="Are there any open-source or free softwares for covalent docking of multiple ligands?" Tags="|software-recommendations|one-topic-per-answer|docking|autodock|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10952" PostTypeId="1" CreationDate="2023-05-24T19:35:11.893" Score="6" ViewCount="121" Body="&lt;p&gt;What's the theory behind these kind of calculation? What are keywords and concepts I have to search for?&lt;/p&gt;&#xA;" OwnerUserId="7254" LastEditorUserId="5" LastEditDate="2023-05-24T21:31:59.447" LastActivityDate="2023-05-25T04:34:41.547" Title="How is magnetization of a solid obtained from electron density in a DFT framework?" Tags="|density-functional-theory|condensed-matter|magnetism|solid-state-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10953" PostTypeId="2" ParentId="10952" CreationDate="2023-05-25T04:34:41.547" Score="3" Body="&lt;p&gt;The main keyword you are looking for is &lt;em&gt;the spin-polarized DFT&lt;/em&gt;. Other keywords that might help you are &lt;em&gt;the spin-density matrix, the Hubbard model (DFT+U), the Stoner Model, von Barth-Hedin spin-polarized Kohn-Sham equation,&lt;/em&gt; etc.&lt;/p&gt;&#xA;&lt;p&gt;A very good introductory resource on this topic is &lt;em&gt;Ch1: Density-functional Theory of Magnetism&lt;/em&gt; by &lt;em&gt;Gustav Bihlmayer&lt;/em&gt; in &lt;em&gt;Handbook of Magnetism and Advanced Magnetic Materials (vol1): Fundamentals and Theory&lt;/em&gt;. Below I will try to summarize briefly.&lt;/p&gt;&#xA;&lt;p&gt;The magnetization density can be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ \mathbf{m(r)} = -\mu_{B} \sum_{\alpha, \beta}^{} \langle \Psi|\langle\psi_{\beta}^{\dagger}\mathbf{\sigma}_{\alpha\beta}\psi_{\alpha}|\Psi\rangle = -\mu_{B}\, \mathbf{s(r)} $$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\psi_{\alpha}$&lt;/span&gt; is the field operator for an electron with spin &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is the Pauli matrices. Notice that the magnetization density is a product of the negative of the Bohr magneton and spin density.&lt;/p&gt;&#xA;&lt;p&gt;The key point is that the density matrix can be decomposed into two parts: a scalar particle density, and a vectorial spin density. Similarly,  the potential matrix can be decomposed into a scalar potential and magnetic field, i.e.,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \underline{n}(\mathbf{r})=\frac{1}{2}\left( n(\mathbf{r})\underline{I} \, + \, \mathbf{\underline{\sigma}}\cdot\mathbf{s(r)} \right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \underline{v}(\mathbf{r}) = v(\mathbf{r})\underline{\mathbf{I}} \, + \, \mu_B\,\underline{\mathbf{\sigma}}\cdot \mathbf{B(r)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then instead of using the non-spin-polarized Hohenberg-Kohn version of DFT, if we use these spin-polarized matrices, we will get a spin-polarized Kohn-Sham equation (derived by von Barth and Hedin, &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/0022-3719/5/13/012&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;This type of DFT is called spin-polarized DFT. Using this, you can obtain the magnetization of solids. Different DFT codes have different ways to enable spin-polarized DFT. For example, in Quantum ESPRESSO, one needs to set &lt;code&gt;nspin=2&lt;/code&gt; in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; namelist for colinear magnetic materials. There are other advanced options too such as noncolinear magnetic materials. You can find some of the examples by searching in this SE with keywords such as &amp;quot;Quantum ESPRESSO LDA+U&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-05-25T04:34:41.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10954" PostTypeId="1" AcceptedAnswerId="10955" CreationDate="2023-05-25T10:53:25.573" Score="6" ViewCount="212" Body="&lt;p&gt;I am computing a relaxed 2D scan with Gaussian 16 in order to reproduce some computational data. I am interested in computing the dipole moment vector and the (static) polarizability matrix after each geometry optimization. Basically this is what Orca does automatically but I have to use Gaussian since I want to use the PM6 method. I read the manual and the IOPs but to be honest I did not understand if it is doable.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, I would be happy if I could find a way to extract the geometries of the relaxed scan done in g16, in this way I could write a script to launch several single points to extract the data that I need.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, any suggestion about an alternative software (possibly free) that does this kind of calculations using the PM6/PM7 level of theory is welcome.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for all the help.&lt;/p&gt;&#xA;" OwnerUserId="7276" LastActivityDate="2023-05-25T14:08:50.417" Title="Compute polarizability after each step of relaxed scan in Gaussian 16" Tags="|quantum-chemistry|gaussian|polarizability|semi-empirical-method|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10955" PostTypeId="2" ParentId="10954" CreationDate="2023-05-25T14:08:50.417" Score="9" Body="&lt;p&gt;This python script will read the logfile from the scan and generate the corresponding gaussian input files.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import  numpy   as  np&#xA;import  sys     as  sys&#xA;import  typing  as  typing&#xA;&#xA;class Coordinates:&#xA;    def __init__(self, natoms:int, coords:list, atoms:list) -&amp;gt; None:&#xA;        self.natoms =   natoms&#xA;        self.coords =   coords&#xA;        self.atoms  =   atoms&#xA;        print(self.atoms)&#xA;&#xA;def Gaussian_writeCOM(scanpoint:float, identifier:str, coordinates: Coordinates) -&amp;gt; None:&#xA;    with open(&amp;quot;coord.{:0.0f}.com&amp;quot;.format(scanpoint), &amp;quot;w&amp;quot;) as comWriter:&#xA;        comWriter.write(&amp;quot;%mem = 16GB\n%nprocs = 12\n%chk = {}.{:0.0f}.chk\n&amp;quot;.format(identifier, scanpoint))&#xA;        comWriter.write(&amp;quot;\n&amp;quot;)&#xA;        comWriter.write(&amp;quot;# mp2/cc-pvtz scf = qc\n&amp;quot;)&#xA;        comWriter.write(&amp;quot;\n&amp;quot;)&#xA;        comWriter.write(&amp;quot;single-point energy of {} at {:0.0f}\n&amp;quot;.format(identifier, scanpoint))&#xA;        comWriter.write(&amp;quot;\n&amp;quot;)&#xA;        comWriter.write(&amp;quot;0 1\n&amp;quot;)&#xA;        for index, coord in enumerate(coordinates.coords):&#xA;            comWriter.write(&amp;quot; {:&amp;lt;10s}{:15.5f}{:15.5f}{:15.5f}\n&amp;quot;.format(coordinates.atoms[index], coord[0], coord[1], coord[2]))&#xA;&#xA;identifier  =   sys.argv[1]&#xA;logFile     =   sys.argv[2]&#xA;nAtoms      =   sys.argv[3]&#xA;initScan    =   sys.argv[4]&#xA;nPoints     =   sys.argv[5]&#xA;stride      =   sys.argv[6]&#xA;&#xA;with open(logFile) as log:&#xA;    fullData        =   log.readlines()&#xA;    initscan        =   float(initScan)&#xA;    strideValue     =   float(stride)&#xA;    npoints         =   int(nPoints)&#xA;    natoms          =   int(nAtoms)&#xA;    scanPoints      =   np.arange(initscan, initscan + (strideValue * npoints), strideValue)&#xA;    coordObjects    =   []&#xA;&#xA;    atoms   =   []&#xA;    # First find the atom names&#xA;    for lnumber, line in enumerate(fullData):&#xA;        if &amp;quot;Symbolic Z-matrix:&amp;quot; in line:&#xA;            atomData    =   fullData[lnumber+2 : lnumber+2+natoms]&#xA;            for atomline in atomData:&#xA;                atomline    =   atomline[0:2].split()[0]&#xA;                atoms.append(atomline)&#xA;                print(atomline)&#xA;&#xA;    # Now read the coordinates&#xA;    for lnumber, line in enumerate(fullData):&#xA;        if &amp;quot;Input orientation&amp;quot; in line:&#xA;            coordData   =   fullData[lnumber+5 : lnumber+5+natoms]&#xA;        if &amp;quot;Stationary point found&amp;quot; in line:&#xA;            coords  =   []&#xA;            for line in coordData:&#xA;                line    =   line.split()&#xA;                coord   =   [float(x) for x in line[3:]]&#xA;                coords.append(coord)&#xA;            coordObject =   Coordinates(natoms=natoms, coords=coords, atoms=atoms)&#xA;            coordObjects.append(coordObject)&#xA;&#xA;for index, coordObject in enumerate(coordObjects):       &#xA;    scanPoint   =   scanPoints[index] &#xA;    Gaussian_writeCOM(scanpoint=scanPoint, identifier=identifier, coordinates=coordObject)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You will need to provide the total number of scan points as the input. Rest of the keywords are self-explanatory. Please change the route section to match your needs.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-05-25T14:08:50.417" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10956" PostTypeId="1" CreationDate="2023-05-25T18:27:17.083" Score="4" ViewCount="180" Body="&lt;p&gt;I'm trying to calculate the electrostatic potential of a molecule. When I try to use the &lt;code&gt;orca_vpot&lt;/code&gt; tool, I am facing some difficulties detailed below.&lt;/p&gt;&#xA;&lt;p&gt;The first problem is that when I run the input with the &lt;code&gt;KeepDens&lt;/code&gt; keyword to generate the &lt;code&gt;.scfp&lt;/code&gt; file, it only generates a &lt;code&gt;.densities&lt;/code&gt; file. When I try to use this file instead of the &lt;code&gt;.scfp&lt;/code&gt; file in the &lt;code&gt;orca_vpot&lt;/code&gt; tool, it shows the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;file orca_tools/qcmat1.cpp, line 103: Stored DataType 7403560 does not &#xA;match the expected 8 in OrcaObject_ReadHeader! &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does anyone know how I can fix this?&lt;/p&gt;&#xA;" OwnerUserId="7280" LastEditorUserId="6687" LastEditDate="2023-05-25T18:59:59.333" LastActivityDate="2023-05-25T18:59:59.333" Title="orca_vpot problem" Tags="|orca|charge-density|electrostatic|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10958" PostTypeId="1" AcceptedAnswerId="10974" CreationDate="2023-05-26T07:36:36.463" Score="4" ViewCount="152" Body="&lt;p&gt;Suppose one has a protein of about 1 million Da, and performs a DLPNO-CCSD(T)/def2-TZVPPD/AutoAux/AutoAux calculation, and then performs a wB97X-2-D/def2-TZVPPD/AutoAux/AutoAux calculation, both via the latest version of the ORCA module and both with default settings for everything, except that the relaxed density be used for the &amp;quot;-2&amp;quot; part. Both on a Surface Pro 8(client-side), via a WebMO Basic server.&lt;/p&gt;&#xA;&lt;p&gt;Notwithstanding the very likely chance of my Surface breaking down completely(as this is a thought experiment; it's more likely that I'll be consulting the undergrad institution I'm enrolled in and/or commercial sources for the calculations in real life), how much would each calculation cost in CPU time, any last integer-part digits in a scale of hours thrown away(as an approximation must be made to estimate CPU timings this large), and/or, more importantly, which would be cheaper by which order of magnitude?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2023-05-27T18:40:42.600" Title="Question on CPU timings and/or ratio resp. DLPNO-CCSD(T) and wB97X-2-D for protein of ca. 1M Da" Tags="|density-functional-theory|computational-chemistry|orca|materials-engineering|coupled-cluster|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="10959" PostTypeId="1" CreationDate="2023-05-26T08:43:30.340" Score="5" ViewCount="792" Body="&lt;p&gt;I was doing a vc-relax calculation and after 1 day the calculation suddenly stopped. Is there a way to restart it from previous interrupted calculation of do I have to restart from the beginning?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-05-26T09:05:28.597" Title="How to restart an interrupted Quantum ESPRESSO calculation?" Tags="|quantum-espresso|condensed-matter|cell-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10960" PostTypeId="2" ParentId="10959" CreationDate="2023-05-26T09:05:28.597" Score="7" Body="&lt;p&gt;You need to have prepared for this beforehand. You need to write out the wavefunctions in a place that is accessible for the new run to absorb in, and so forth.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm65&quot; rel=&quot;noreferrer&quot;&gt;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm65&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But if you still have the interrupted output file, you can read off the cell parameters and the atomic positions just before it crashed, and start from there. Even if you did not have the wavefunctions to restart from, it will still be vastly faster.&lt;/p&gt;&#xA;" OwnerUserId="7192" LastActivityDate="2023-05-26T09:05:28.597" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10961" PostTypeId="2" ParentId="10937" CreationDate="2023-05-26T16:36:10.090" Score="5" Body="&lt;h1&gt;&lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt; Case&lt;/h1&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ \left( \sqrt{3} \times \sqrt{3}\right)R30$&lt;/span&gt; is a short way of representing a supercell in Woods notation (&lt;a href=&quot;https://en.wikipedia.org/wiki/Surface_reconstruction#Notation_of_reconstructions&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Overlayer#Wood%27s_notation&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;), which essentially means that each of the basis vectors of the supercell are &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt;  times the magnitude of that of the primitive cell.&lt;/p&gt;&#xA;&lt;p&gt;Woods Notation is given by: X(hkl) m × n - Rφ.&lt;/p&gt;&#xA;&lt;p&gt;Here m and n are both &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt;, φ=30°&lt;/p&gt;&#xA;&lt;p&gt;Now let us look at the &lt;span class=&quot;math-container&quot;&gt;$ \left( \sqrt{3} \times \sqrt{3}\right)R30$&lt;/span&gt; supercell from the answer with some annotations that I added.&lt;/p&gt;&#xA;&lt;p&gt;Here a1, a2 are the basis vectors of the primitive cell marked in green.&lt;/p&gt;&#xA;&lt;p&gt;And b1, b2 are the basis vectors of the supercell marked in purple.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bX2pa.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bX2pa.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So from the image you can see that, to calculate b1, from the triangle law of vectors we first need to traverse 2 units of a1 and then 1 unit of a2.&#xA;Corresponding to [2 1 0], the first line of matrix.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, to calculate b2, we need to traverse negative 1 unit in a1 and 1 unit in a2.&#xA;Corresponding to [-1 1 0], the second line of matrix.&lt;/p&gt;&#xA;&lt;p&gt;The additional row and column are introduced to represent a 3D rotation matrix, where the third dimension remains unaffected. In this case, the third row and column are [0, 0, 1], indicating that the z-axis remains the same.&lt;/p&gt;&#xA;&lt;p&gt;Thereby, this gives us the transformation matrix:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{bmatrix}2 &amp;amp; 1 &amp;amp; 0\\-1 &amp;amp; 1&amp;amp; 0 \\0 &amp;amp; 0&amp;amp; 1\end{bmatrix}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Generic Case&lt;/h1&gt;&#xA;&lt;p&gt;Let b1/a1= m, b2/a2=n as per the Woods notation.&lt;/p&gt;&#xA;&lt;p&gt;Let us assume |a1|=|a2|=1 since we start with unit cell.&lt;/p&gt;&#xA;&lt;p&gt;Let &lt;span class=&quot;math-container&quot;&gt;$G_{11}, G_{12}, G_{21}, and \space G_{22}$&lt;/span&gt; be the factors that a1 and a2 are multiplied in the Matrix form of Woods notation to obtain b1 and b2.&lt;/p&gt;&#xA;&lt;p&gt;That is,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$b_{1} = G_{11}*a_{1} + G_{12}*a_{2}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$b_{2} = G_{21}*a_{1} + G_{22}*a_{2}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Therefore by Cosine law of triangles we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$m^2 = G_{11}^2+ G_{12}^2 - 2*G_{11}*G_{12}*cos(φ)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$n^2 = G_{21}^2+ G_{22}^2 - 2*G_{21}*G_{22}*cos(φ)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In above equations, we know m,n and φ. So we can solve the equations to obtain relationships between &lt;span class=&quot;math-container&quot;&gt;$G_{11} and G_{12}$&lt;/span&gt; and&#xA;&lt;span class=&quot;math-container&quot;&gt;$ G_{21} and \space G_{22}$&lt;/span&gt; with that we construct the transformation matrix like:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{bmatrix} G_{11} &amp;amp; G_{12} &amp;amp; 0\\G_{21} &amp;amp; G_{22}&amp;amp; 0 \\0 &amp;amp; 0&amp;amp; 1\end{bmatrix}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, in the &lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt; case, since m and n are the same it would result in same equation for both rows of the matrix.&#xA;Observe the triangle with the φ, we would get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sqrt(3)^2 = G_{11}^2+ G_{12}^2 - 2*G_{11}*G_{12}*cos(90-φ)$&lt;/span&gt;&#xA;Here we take 90-φ because, we need angle between the two lines with known values in this case 2 and 1.&lt;/p&gt;&#xA;&lt;p&gt;Solving the equation of this ellipse would give us many possible sets of solutions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$G_{11} = -2, G_{12} = -1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$G_{11} = -1, G_{12} = -2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$G_{11} = -1, G_{12} = 1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$G_{11} = 1, G_{12} = -1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$G_{11} = 1, G_{12} = 2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and similarly for G21, and G22.&lt;/p&gt;&#xA;&lt;p&gt;This calculation is shown in Wolfram Alpha &lt;a href=&quot;https://www.wolframalpha.com/input?i=a**2%2Bb**2-ab+%3D+3&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So similarly we can solve for any m,n and φ combination.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-26T16:36:10.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10962" PostTypeId="1" AcceptedAnswerId="10963" CreationDate="2023-05-26T17:03:23.337" Score="8" ViewCount="241" Body="&lt;h1&gt;Context&lt;/h1&gt;&#xA;&lt;p&gt;I saw some examples of SLURM scripts on the internet like the one below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -J QE68&#xA;#SBATCH --ntasks=16&#xA;#SBATCH --ntasks-per-core=1&#xA;#SBATCH --partition=defq&#xA;#SBATCH -o %x-%j.out&#xA;#SBATCH -e %x-%j.err&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Problem&lt;/h1&gt;&#xA;&lt;p&gt;I am having a hard time understanding the specific values that are initialized to the various directives.&#xA;For example, &lt;code&gt;ntasks=16&lt;/code&gt; and &lt;code&gt;ntasks-per-cor=1&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How can I know in prior that &lt;code&gt;ntasks=16&lt;/code&gt; not &lt;code&gt;17&lt;/code&gt;, why &lt;code&gt;ntasks-per-cor=1&lt;/code&gt; and not &lt;code&gt;2&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;I don't know how to arrive at those numbers, or which commands I should use to get them before constructing a SLURM script.&lt;/p&gt;&#xA;&lt;h1&gt;Question(s):&lt;/h1&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;How can I determine what numbers I need to use for the various directives?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Are there any good rules of thumb to determine these numbers?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6687" LastEditDate="2023-05-29T10:02:00.657" LastActivityDate="2023-05-29T10:50:05.137" Title="How to get the directives of a slurm for my Quantum ESPRESSO calculations?" Tags="|quantum-espresso|ab-initio-calculations|condensed-matter|high-performance-computing|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="10963" PostTypeId="2" ParentId="10962" CreationDate="2023-05-26T17:54:23.337" Score="5" Body="&lt;p&gt;Since the question was edited, here is an updated answer.&lt;/p&gt;&#xA;&lt;h3&gt;1. How to estimate the numbers which we initialize the SLURM directives:&lt;/h3&gt;&#xA;&lt;p&gt;As far as I understand, the way to decide the numbers that you initialise the SLURM directives are by empirical means.&lt;/p&gt;&#xA;&lt;p&gt;So one way to estimate those numbers are by running your script on a very small subset on your local PC and logging various specifications of your PC. This could help you to calculate how long, how much memory you might need for a larger population (more molecules, more stronger basis sets etc).&lt;/p&gt;&#xA;&lt;p&gt;For example, if you run a CCSD_T calculation for 1 molecule containing 20 atoms on your local PC.&#xA;And suppose it takes 14 mins on your local PC which has 32 GB RAM, 6 cores.&lt;/p&gt;&#xA;&lt;p&gt;So if you wanted to run the calculations for 100 such molecules on the supercomputer, with 32GB RAM and 6 cores, you can estimate that it would take 100*14 = 1400 mins, which is about 23 hours !&lt;/p&gt;&#xA;&lt;p&gt;So perhaps you would want to increase the RAM to 64GB or maybe 128GB.&#xA;Which would mostly half and quarter your time. So maybe at 128GB it would take 6 hours.&lt;/p&gt;&#xA;&lt;p&gt;So in that way you can say:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --time=6:00:00&#xA;#SBATCH --cpus-per-task=6&#xA;#SBATCH --mem=128000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;2. Good rules of thumb for determining the values for SLURM directives:&lt;/h3&gt;&#xA;&lt;p&gt;For the --mem= directive, use values which are powers of 2.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;br/&gt;&#xA;&lt;h3&gt;To Print out what values are initialized when you run the shell script&lt;/h3&gt;&#xA;&lt;p&gt;You can access the various parameters using the SLURM environment variables.&#xA;A complete list of the environment variables are found on the SLURM webpage.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://slurm.schedmd.com/sbatch.html#SECTION_INPUT-ENVIRONMENT-VARIABLES&quot; rel=&quot;nofollow noreferrer&quot;&gt;input-environment-variables&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://slurm.schedmd.com/sbatch.html#SECTION_OUTPUT-ENVIRONMENT-VARIABLES&quot; rel=&quot;nofollow noreferrer&quot;&gt;output-environment-variables&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is an example of how to print information regarding these parameters using SLURM environment variables:&lt;/p&gt;&#xA;&lt;p&gt;Say we have a &lt;code&gt;test.sh&lt;/code&gt; with the following contents:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -J QE68&#xA;#SBATCH --ntasks=16&#xA;#SBATCH --ntasks-per-core=1&#xA;#SBATCH --partition=defq&#xA;#SBATCH --mem=800&#xA;#SBATCH -o %x-%j.out&#xA;#SBATCH -e %x-%j.err&#xA;printf &amp;quot;N tasks per core %s\n&amp;quot; &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$SLURM_NTASKS_PER_CORE&quot;&#xA;printf &quot;Number of tasks  %s\n&quot; &quot;$&lt;/span&gt;SLURM_NTASKS&amp;quot;&#xA;printf &amp;quot;Memory per node  %s\n&amp;quot; &amp;quot;$SLURM_MEM_PER_NODE&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Upon scheduling this sh script with: &lt;code&gt;sbatch test.sh&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the output file, we would see the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;N tasks per core 1&#xA;Number of tasks  16&#xA;Memory per node  800&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-05-29T10:50:05.137" LastActivityDate="2023-05-29T10:50:05.137" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10964" PostTypeId="2" ParentId="10962" CreationDate="2023-05-26T18:31:02.843" Score="5" Body="&lt;p&gt;The SLURM general directives are given on the SLURM webpage, as indicated in the other comments.&lt;/p&gt;&#xA;&lt;p&gt;The Digital Research Alliance of Canada uses the script below to launch QuantumEspresso jobs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH --account=def-someuser&#xA;#SBATCH --time=0-1:00           # DD-HH:MM&#xA;#SBATCH --nodes=1&#xA;#SBATCH --tasks-per-node=32     # MPI tasks&#xA;#SBATCH --mem=0                 # all memory on node&#xA;module load StdEnv/2020  intel/2020.1.217  openmpi/4.0.3&#xA;module load quantumespresso/6.6&#xA;srun pw.x &amp;lt; si.scf.in &amp;gt; si.scf.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are no specific directives for specific software.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-05-26T18:31:02.843" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10965" PostTypeId="1" AcceptedAnswerId="10970" CreationDate="2023-05-26T19:17:44.280" Score="5" ViewCount="310" Body="&lt;p&gt;As far as I understand, a system in equilibrium is which already reached its equilibrium state. And, a non-equilibrium system is which hasn't reached its equilibrium state yet.&lt;/p&gt;&#xA;&lt;p&gt;Are MD (Molecular Dynamics) and MC (Monte Carlo) both able to study both equilibrium and non-equilibrium systems?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-05-26T22:24:06.137" LastActivityDate="2023-05-28T22:17:19.350" Title="Are MD and MC both able to study both equilibrium and non-equilibrium systems?" Tags="|molecular-dynamics|monte-carlo|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10966" PostTypeId="1" AcceptedAnswerId="10967" CreationDate="2023-05-26T19:20:28.800" Score="3" ViewCount="127" Body="&lt;p&gt;Are MD (Molecular Dynamics) and MC (Monte Carlo) both parts of statistical physics or is only one of them?&lt;/p&gt;&#xA;&lt;p&gt;If so, which branch (e.g., mechanics, thermodynamics, etc.) and why?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KkZp2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KkZp2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-05-26T22:04:25.043" LastActivityDate="2023-05-26T22:04:25.043" Title="Are MD and MC both parts of statistical physics?" Tags="|molecular-dynamics|statistical-thermodynamics|monte-carlo|terminology|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10967" PostTypeId="2" ParentId="10966" CreationDate="2023-05-26T22:04:14.557" Score="6" Body="&lt;p&gt;Monte Carlo methods are a broad class of algorithms that apply not just to physics problems but also to biology, finance, and even pure mathematics (for example &lt;a href=&quot;https://en.wikipedia.org/wiki/Buffon%27s_needle_problem&quot; rel=&quot;noreferrer&quot;&gt;it can be used to provide better and better estimations of π&lt;/a&gt;, and it can be used to calculate integrals or areas under curves).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Monte_Carlo_method_in_statistical_mechanics&quot; rel=&quot;noreferrer&quot;&gt;There is an entire Wikipedia page on applications of Monte Carlo methods to statistical mechanics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Molecular dynamics is a deterministic algorithm (meaning, it is &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; a Monte Carlo algorithm), however it is often done on very large ensembles of molecules, after which statistical averages are calculated (e.g. the temperature of the ensemble can be estimated by calculating the average kinetic energy over the entire ensemble of molecules, and this can be considered a branch of statistical mechanics).&lt;/p&gt;&#xA;&lt;p&gt;As for the diagram in your question, Monte Carlo algorithms can be applied to every branch and sub-branch in the diagram, but I would put molecular dynamics in a branch called &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Molecular_physics&quot; rel=&quot;noreferrer&quot;&gt;molecular physics&lt;/a&gt;&amp;quot; which is often grouped with the branch in the top-left corner (instead of &amp;quot;atomic, nuclear, and particle physics&amp;quot;, there's often a category called &amp;quot;&lt;a href=&quot;https://en.wikipedia.org/wiki/Atomic,_molecular,_and_optical_physics&quot; rel=&quot;noreferrer&quot;&gt;atomic, molecular, and optical physics&lt;/a&gt;&amp;quot; or AMO physics, and &amp;quot;nuclear and particle physics&amp;quot; would be in a different category).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-05-26T22:04:14.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10968" PostTypeId="2" ParentId="10965" CreationDate="2023-05-26T22:23:56.153" Score="7" Body="&lt;p&gt;Monte Carlo methods such as &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/153/3/034107/1059360/NECI-N-Electron-Configuration-Interaction-with-an&quot; rel=&quot;noreferrer&quot;&gt;FCIQMC&lt;/a&gt; can study non-equilibrium systems: in fact FCIQMC is used for calculating the ground state energy of a system that is already in equilibrium.&lt;/p&gt;&#xA;&lt;p&gt;Monte Carlo methods can also study non-equilibrium systems, for example in &lt;a href=&quot;https://arxiv.org/abs/quant-ph/0507003&quot; rel=&quot;noreferrer&quot;&gt;this paper which is about using Monte Carlo methods for real-time quantum dynamics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Molecular Dynamics certainly can be applied to systems that are not in equilibrium, because it literally simulates the real-time dynamics of a system, which can for example be an equilibrium system of molecules that are not moving until one of them is bombarded by an extremely fast molecule that puts them all out of equilibrium. It can also continue simulating that system until it reaches equilibrium again. Therefore molecular dynamics can also simulate equilibrium systems (why not?) even if the MD equations just say that all accelerations are zero. Molecular dynamics can also simulate systems that are in &lt;a href=&quot;https://en.wikipedia.org/wiki/Dynamic_equilibrium&quot; rel=&quot;noreferrer&quot;&gt;dynamic equilibrium&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-05-26T22:23:56.153" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10969" PostTypeId="1" CreationDate="2023-05-27T05:10:56.343" Score="2" ViewCount="40" Body="&lt;p&gt;Historically powder X-ray diffraction was the go-to method for reconstructing crystal structure. X-ray sources were limited in intensity and emittance and so to collect data in a reasonable amount of time one would use a (nearly) monochromatic beam and a large area detector (originally photographic emulsion, now 2D position-sensitive gas counters or solid stat devices) to collect those beautiful ring images shown above.&lt;/p&gt;&#xA;&lt;p&gt;To analyze a true powder (uniformly random distribution in crystal orientations) one would reduce this to a single 1D plot of intensity vs radius, then apply something like a &lt;a href=&quot;https://en.wikipedia.org/wiki/Rietveld_refinement&quot; rel=&quot;nofollow noreferrer&quot;&gt;Rietveld refinement&lt;/a&gt; to deduce relative reflection intensities for structure determination and maybe some information on grain size or micro-strain.&lt;/p&gt;&#xA;&lt;p&gt;The rings would sometimes be lumpy due to failure to achieve uniform, isotropic orientations of the grains of the powder, often due to wall effects in the container and other mechanical packing and correlation effects.&lt;/p&gt;&#xA;&lt;p&gt;Then both metallurgy and thin films used in semiconductor manufacture came along. For example the thin films might be silicides used to make ohmic contact between metal layers and the semiconductor material, or nitrides (e.g. TiN) for seed layers before electrodeposition of copper for interconnects.&lt;/p&gt;&#xA;&lt;p&gt;For polycrystalline metals and semiconductor thin films, &lt;a href=&quot;https://en.wikipedia.org/wiki/Pole_figure#Diffraction_pattern&quot; rel=&quot;nofollow noreferrer&quot;&gt;pole figures&lt;/a&gt; were generated from area detector X-ray diffraction data for a given reflection plane.&lt;/p&gt;&#xA;&lt;p&gt;Pole figures could be used (along with other Rietveld refinement results ) to put together a picture of &lt;a href=&quot;https://en.wikipedia.org/wiki/Pole_figure#Texture&quot; rel=&quot;nofollow noreferrer&quot;&gt;crystallographic texture&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The pole figures show the distribution in directions that the &lt;em&gt;normal&lt;/em&gt; to a given crystal plane is pointing. It doesn't tell you anything about how the crystallites contributing to a given spot on the pole figure are rotationally oriented around the normal direction.&lt;/p&gt;&#xA;&lt;p&gt;For that information you combine results of several pole figures for several different reflections.&lt;/p&gt;&#xA;&lt;p&gt;For example you might also have a fixed X-ray incident angle and area detector position, and &lt;em&gt;rotate&lt;/em&gt; the sample around the &lt;em&gt;sample normal&lt;/em&gt; to get more information.&lt;/p&gt;&#xA;&lt;p&gt;Finally, based on the amount and variety of data you've collected, one builds up a model orientations of the crystallites in 3D space - the &lt;em&gt;texture&lt;/em&gt; of the polycrystalline film or material.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; Starting from a series of area detector images taken at different rotations of a sample about its normal, how does one generate pole figures from limited amounts of data? &amp;quot;Explain it like I'm five years old&amp;quot; means a wall of equations is not as helpful as a step-by-step overview of how do to the calculation &lt;strong&gt;from scratch&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;So &amp;quot;Use MAUD&amp;quot; or &amp;quot;Use Program X&amp;quot; are not helpful because the actual calculations I'm curious about are mostly hidden in those packages.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/S9ry5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S9ry5.png&quot; alt=&quot;File:MAUD-MTEX-TiAl-hasylab-2003-Liss https://commons.wikimedia.org/wiki/File:MAUD-MTEX-TiAl-hasylab-2003-Liss.png&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://commons.wikimedia.org/wiki/File:MAUD-MTEX-TiAl-hasylab-2003-Liss.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;File:MAUD-MTEX-TiAl-hasylab-2003-Liss&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tCvMP.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tCvMP.jpg&quot; alt=&quot;&amp;quot;Minerals at 'Rocknest' and 'John Klein'&amp;quot; https://commons.wikimedia.org/wiki/File:Minerals_at_%27Rocknest%27_and_%27John_Klein%27.jpg&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&quot;https://commons.wikimedia.org/wiki/File:Minerals_at_%27Rocknest%27_and_%27John_Klein%27.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;Minerals at 'Rocknest' and 'John Klein'&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="201" LastActivityDate="2023-05-27T05:10:56.343" Title="How to generate pole figures from limited amounts of area detector X-ray diffraction from thin films (explain it like I'm five years old)" Tags="|software|crystallography|x-ray-diffraction|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10970" PostTypeId="2" ParentId="10965" CreationDate="2023-05-27T07:13:44.867" Score="5" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10968/201&quot;&gt;Nike's answer&lt;/a&gt; included examples of Monte Carlo in the context of electronic structure. However, Monte Carlo techniques are most popularly employed in statistical physics / thermodynamics - often employing classical force fields - and generally across various disciplines wherever one needs to sample high-dimensional integrals.&lt;/p&gt;&#xA;&lt;p&gt;In addition to the modeling of equilibria, Monte Carlo methods can be also employed to modeling dynamic processes. An example of this is the &lt;a href=&quot;https://en.wikipedia.org/wiki/Kinetic_Monte_Carlo&quot; rel=&quot;nofollow noreferrer&quot;&gt;kinetic Monte Carlo&lt;/a&gt; method, which is often used to model e.g. multi-step reactions.&lt;/p&gt;&#xA;&lt;p&gt;A topical reference for Monte Carlo methods in materials modeling is &lt;a href=&quot;https://link.springer.com/chapter/10.1007/978-1-4020-3286-8_31&quot; rel=&quot;nofollow noreferrer&quot;&gt;a chapter in the Handbook of Materials Modeling&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="201" LastEditDate="2023-05-28T22:17:19.350" LastActivityDate="2023-05-28T22:17:19.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10971" PostTypeId="2" ParentId="10942" CreationDate="2023-05-27T07:20:04.483" Score="2" Body="&lt;p&gt;Never trust a result obtained with a single density functional. You should perform calculations also with other types of functionals and see if you get a similar answer.&lt;/p&gt;&#xA;&lt;p&gt;The molecule in question is not very big, so you could also tackle the question about the geometry with high-level &lt;em&gt;ab initio&lt;/em&gt; methods. A good sanity check would be to evaluate CCSD(T) single-point energies at your DFT optimized geometries to assess whether the state ordering flips. You can even use approximate CCSD(T) methods for this check, such as pair-localized or local natural orbital truncations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-27T07:20:04.483" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10972" PostTypeId="2" ParentId="10936" CreationDate="2023-05-27T07:29:04.900" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;How is LSDA exchange energy is derived?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;LSDA exchange is computed from the homogeneous electron gas from the expression for exact exchange; see any standard textbook on electronic structure with density functional theory.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;And why is it not consistent with the RKS case where α and β electrons have the same density also the LDA case?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The two expressions above coincide. Density functionals are often expressed in the literature in terms of spin-unpolarized densities, &lt;span class=&quot;math-container&quot;&gt;$\rho = \rho_\alpha + \rho_\beta = 2\rho_\alpha$&lt;/span&gt;, from which you can derive the spin-polarized expressions applying spin scaling relations.&lt;/p&gt;&#xA;&lt;p&gt;If you substitute this in the first expression, you see&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ -\frac{3}{4}\left(\frac{3}{\pi}\right)^{1/3}\rho^{4/3}=-\frac{3}{4}\left(\frac{3}{\pi}\right)^{1/3}\int(2\rho_{\alpha})^{4/3} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, taking out the factor &lt;span class=&quot;math-container&quot;&gt;$2$&lt;/span&gt; from the exponent gives you &lt;span class=&quot;math-container&quot;&gt;$2^{4/3}$&lt;/span&gt;, from which you take out the cube root in front and split the factor 2 as a sum of the alpha and beta terms&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ -2^{1/3} \frac{3}{4}\left(\frac{3}{\pi}\right)^{1/3}\int \left[ \rho_{\alpha}^{4/3} + \rho_{\beta}^{4/3}\right] $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that exchange is same-spin only, so there is no &lt;span class=&quot;math-container&quot;&gt;$\rho_\alpha \rho_\beta$&lt;/span&gt; term.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-05-27T07:29:04.900" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="10973" PostTypeId="1" CreationDate="2023-05-27T14:46:31.673" Score="3" ViewCount="189" Body="&lt;p&gt;I tried to set the &lt;code&gt;tot_charge&lt;/code&gt; parameter of Quantum Espresso to alter the charge of the system, but the phonon spectrum I obtained was very strange. Could anyone give me any advice on using Quantum Espresso to calculate carrier doping?&lt;/p&gt;&#xA;" OwnerUserId="7294" LastEditorUserId="403" LastEditDate="2023-05-29T13:26:35.790" LastActivityDate="2023-05-29T13:26:35.790" Title="How to perform carrier doping (hole/electron) for 2D materials by Quantum Espresso?" Tags="|density-functional-theory|quantum-espresso|electronic-structure|phonons|2d-lattice|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-01T17:48:56.133" ContentLicense="CC BY-SA 4.0" />
  <row Id="10974" PostTypeId="2" ParentId="10958" CreationDate="2023-05-27T18:35:00.710" Score="4" Body="&lt;p&gt;While I cannot give you any hard estimates, there are a number of points that can be addressed in your question.&#xA;First, this is going to be a huge calculation, no matter what, even a single point with a super simple non-hybrid DFT functional like PBE is going to be very demanding.&#xA;Second, while you specified Orca as your software of choice, most of the points I make should be fairly generic across the various state-of-the-art linear-scaling CC implementations in Orca, Molpro, MRCC, etc.&lt;/p&gt;&#xA;&lt;p&gt;With that in mind, using DF/RI (and also probably integral-direct) methods will be unavoidable. Using AutoAux would be a bad idea, it generates large unoptimized auxiliary basis sets that generally should only be used if there is no optimized aux basis for the main basis you are using. I have not checked, but I would think that def2-TZVPPD is popular enough that aux basis availability is not a problem.&lt;/p&gt;&#xA;&lt;p&gt;I am not familiar with wB97X-2-D and a brief google search had no relevant hits, but &amp;quot;except that the relaxed density be used for the &amp;quot;-2&amp;quot; part&amp;quot; suggests it might be a new double hybrid. This raises more problems, as computing regular RI-MP2 would not be feasible, so you would need to use DLPNO-MP2 or whatever linear-scaling MP2 implementation you have available to compute the PT2 contribution, which might be technical a problem as some implementations might not support using non-HF references.&lt;/p&gt;&#xA;&lt;p&gt;Either way, trying to use a relaxed (DLPNO-)MP2 density in your double hybrid is probably not going to be feasible, even if it is implemented (which I doubt), computing the relaxed MP2 density is somewhat expensive. But IIRC many double hybrids perform just fine without relaxed MP2 density, so if wB97X-2-D really demands the use of relaxed densities, you would probably want to consider using a different functional that does not require the relaxed MP2 density.&lt;/p&gt;&#xA;&lt;p&gt;The CC calculation is going to be an enormous challenge to complete. Forget hours, we are deep in the months and years territory. But there is some hope with bleeding edge software and hardware coming in the next 10 years. Take a look at &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.9b00511&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; from the MRCC developers, where they have completed a single point LNO-CCSD(T)/def2-QZVP for a protein of 1023 atoms.&lt;/p&gt;&#xA;&lt;p&gt;One of the most interesting observations they make, is that past ~500 atoms the post-HF part of LNO-CCSD(T) starts getting close to linear scaling, while the DF-HF step has cubic scaling and overtakes LNO-CCSD(T)! Indeed, for their 1 kiloatom LNO-CCSD(T)/def2-QZVP calculation DF-HF took 38 days while after that the post-HF steps were done in just 18 days, all on an old 6-core CPU from 2013 (!!!) and ~100 GB of RAM.&lt;/p&gt;&#xA;&lt;p&gt;Napkin math time!&#xA;Assuming your protein is made out of CH2 units (ie. UHMWPE), you will have ~70k atoms. The post-HF part is easy to estimate if we can assume linear scaling, 18 * 70 = ~1300 days (~3.5 years) on their hardware.&#xA;The DF-HF part is a real fly in the ointment: 38 * 70^3 = ~13 megadays or ~36 thousand years.&lt;/p&gt;&#xA;&lt;p&gt;Now, before you despair, of course we have much faster CPUs today, and in fact we will soon (~2 years) reach 100x the CPU performance that the paper used (256 cores, ~10 TFLOPS FP64). They claim to have pretty good parallel scaling, so assuming that holds, if you were to buy the fastest server that money can buy in 2025, then start the calculation, you may be able to finish it in 2027.&#xA;That is of course, assuming no algorithmic improvements or GPU implementation, both of which may make this much more feasible in the meanwhile.&lt;/p&gt;&#xA;&lt;p&gt;So if you are an undergrad now, a single point CCSD(T)/CBS for this protein might become (barely) feasible by the time you finish your PhD, on something like a then-brand-new supercomputer node.&lt;/p&gt;&#xA;" OwnerUserId="5225" LastEditorUserId="5225" LastEditDate="2023-05-27T18:40:42.600" LastActivityDate="2023-05-27T18:40:42.600" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="10976" PostTypeId="2" ParentId="9938" CreationDate="2023-05-28T04:29:12.943" Score="1" Body="&lt;p&gt;Two people so far have said that the &lt;a href=&quot;https://legacy.materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;legacy website&lt;/a&gt; was the only way that they could accomplish the task described in your question: Pranav Kumar &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9938/how-to-obtain-the-primitive-unit-cell-from-the-new-materials-project-website#comment21063_9938&quot;&gt;here&lt;/a&gt; and Bin Liu &lt;a href=&quot;https://matsci.org/t/unable-to-download-primitive-unit-cell-for-example-al/45383&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. No comment about this has been made on the &amp;quot;official&amp;quot; Materials Project forum either, in over 6 months (see the thread with the answer by Bin Liu). Based on all of that, it seems safe to assume that the answer to your question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is the option to download primitive unit cell still available, or has it been removed completely?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is that the option is not available in the new website, and it has indeed been removed completely, but fortunately it is still available in the legacy website. If it becomes available on the new website, hopefully someone updates this answer or writes a better answer! In that case I can even make this answer a &lt;a href=&quot;https://meta.stackexchange.com/q/11740/391772&quot;&gt;Community wiki&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-05-28T04:29:12.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10977" PostTypeId="2" ParentId="10965" CreationDate="2023-05-28T15:44:21.837" Score="3" Body="&lt;p&gt;In addition to what others have said, it might help you to know that Monte Carlo methods, at least in the case of simulating rarefied gas flows (Direct Simulation Monte Carlo - DSMC), perform much, much better the further you are from equilibrium. Situations with low speeds / low pressure differences / low temperature differences usually require a prohibitively high computational time, unless you are using a heavily modified version of DSMC. The reason is that the statistical noise hides the (very low) gradients of pressure, temperature, etc, so you need to have a sample of many particles or average over a long enough time interval.&lt;/p&gt;&#xA;&lt;p&gt;I do not have experience with MD, so please take my opinion with a grain of salt, but I do not see a reason for the method not being able to simulate both types of systems in theory, assuming that you confine your investigation in a very small area and time window. But I suppose you will have better performance in some cases than others.&lt;/p&gt;&#xA;" OwnerUserId="7300" LastActivityDate="2023-05-28T15:44:21.837" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10978" PostTypeId="1" CreationDate="2023-05-28T22:46:00.913" Score="4" ViewCount="250" Body="&lt;p&gt;I am rather new to VASP and I have seen people using different methods to compute crystal structure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Using Birch-Murnaghan equation to find optimal lattice volume, and then adjust the structure inside the lattice by tuning the structural parameter.&lt;/li&gt;&#xA;&lt;li&gt;Using ISIF=3 to relax the ions directly.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;What are their advantages respectively and which one should I use?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-05-29T01:26:56.717" Title="What is the best method to compute crystal structures?" Tags="|density-functional-theory|vasp|crystallography|physical-properties-of-materials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10979" PostTypeId="1" CreationDate="2023-05-28T22:49:18.890" Score="9" ViewCount="693" Body="&lt;p&gt;Answers to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10965/201&quot;&gt;Are MD and MC both able to study both equilibrium and non-equilibrium systems?&lt;/a&gt; include lots of examples pointing to &amp;quot;yes&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;I'm currently faced with a task of modelings small islands of 2D materials on a crystal surface - how they rotate, translate, grow, and settle down into certain rotational and translational equilibrium orientations. Right now I use Hooke's law for bonds and a 2D periodic surface potential.&lt;/p&gt;&#xA;&lt;p&gt;For me, I can simply pop in any solver I want; for Molecular Dynamics I use Python's &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html&quot; rel=&quot;noreferrer&quot;&gt;solve_ivp&lt;/a&gt; and have a Python implementation of FIRE and will be coding a FIRE method in C.&lt;/p&gt;&#xA;&lt;p&gt;For Monte Carlo I have an ugly, slow Python implementation and there are some (presumably faster) packages out there I could try.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is more general&lt;/strong&gt;, but you can use that context if it helps an answer.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What are the differentiating factors that tell us &lt;strong&gt;how to choose&lt;/strong&gt; between Molecular Dynamics and Monte Carlo &lt;strong&gt;when beginning to simulate&lt;/strong&gt; either equilibrium or non-equilibrium systems?&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="201" LastEditDate="2023-05-28T22:57:34.957" LastActivityDate="2023-05-30T04:08:32.667" Title="How to choose between Molecular Dynamics and Monte Carlo when beginning to simulate either equilibrium or non-equilibrium systems?" Tags="|molecular-dynamics|monte-carlo|molecular-mechanics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10980" PostTypeId="2" ParentId="10978" CreationDate="2023-05-29T01:26:56.717" Score="4" Body="&lt;p&gt;The whole idea is to find minimum energy structure, one can search entire combination of lattice parameters to get the minimum energy configuration. However the complexity of problem increases very fast specially for tetragonal, monoclinic, triclinic structures. In case of cubic only one degree of freedom is sufficient to find energy minima. If one have energy-volume curve. Fit into The Birch-Murnaghan equation which incorporate pressure dependent bulk-modulus in to the fitting equations.&lt;/p&gt;&#xA;&lt;p&gt;ISIF=3 allows minimization algorithm to find minima in convex surface without prior knowledge of landscape.&#xA;You only need to provide initial configuration. Ideally both method should end up at same value, however, numerical method always provide slightly different value. One also can see different IBIRION tag to choose minimization algorithm may result slightly different value.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2023-05-29T01:26:56.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10981" PostTypeId="1" AcceptedAnswerId="11251" CreationDate="2023-05-29T06:23:32.057" Score="7" ViewCount="166" Body="&lt;p&gt;Is there a neat way to figure out if a crystal structure in pymatgen is 2D or 3D? If we have a molecule we can feed its coordinates to (say) the ConvexHull method in scipy. Is there way to do the same for structure objects?&lt;/p&gt;&#xA;" OwnerUserId="6361" LastEditorUserId="7" LastEditDate="2023-07-13T13:49:12.970" LastActivityDate="2023-07-13T13:49:12.970" Title="How to determine dimensionality of a structure with pymatgen?" Tags="|symmetry|pymatgen|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10982" PostTypeId="1" CreationDate="2023-05-29T08:19:30.487" Score="1" ViewCount="46" Body="&lt;p&gt;I have been working on electronic properties of ternary alkali Bismuth.&lt;/p&gt;&#xA;" OwnerUserId="6512" LastActivityDate="2023-05-29T08:19:30.487" Title="I'm calculating the band structure with and without considering spin orbit coupling. why I need to use SOC?" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-01T19:41:33.747" ContentLicense="CC BY-SA 4.0" />
  <row Id="10983" PostTypeId="1" CreationDate="2023-05-29T10:49:54.837" Score="6" ViewCount="90" Body="&lt;p&gt;Metadynamics is usually used to construct 1D or 2D free-energy surfaces. There seem to be a few examples for 3D free-energy surfaces:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/jz4007993&quot; rel=&quot;noreferrer&quot;&gt;Paper 1: Exploring the Free Energy Landscape of Solutes Embedded in Lipid Bilayers&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1021/jp803936q&quot; rel=&quot;noreferrer&quot;&gt;Paper 2: Exploring Complex Protein−Ligand Recognition Mechanisms with Coarse Metadynamics&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone ever seen a 4D or 5D free-energy surface constructed with metadynamics?&#xA;If so, how did they manage to converge the simulation?&lt;/p&gt;&#xA;" OwnerUserId="7307" LastEditorUserId="6687" LastEditDate="2023-05-29T11:43:57.930" LastActivityDate="2023-05-30T04:49:29.093" Title="What is the largest number of collective variables used in a metadynamics simulation?" Tags="|molecular-dynamics|free-energy|plumed|enhanced-sampling|collective-variable|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10984" PostTypeId="2" ParentId="10979" CreationDate="2023-05-29T11:48:57.410" Score="8" Body="&lt;p&gt;The main difference between MD and MC is, MD is a deterministic method, and MC is a probabilistic method.&lt;/p&gt;&#xA;&lt;p&gt;So, MC is unable to simulate something which needs total accuracy. For instance, if you want to simulate the movement of a spacecraft, MC cannot do that. Or, rather it would be highly unreliable.&lt;/p&gt;&#xA;&lt;p&gt;Another thing to consider is, it is very hard (research is ongoing) to parallelize MC algorithms. Therefore, if you want to run MC in GPU or in a distributed system, it would be a very very difficult task.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, MD cannot simulate on-lattice models. I.e., the atoms need to be freely movable, e.g., gas or liquid.&lt;/p&gt;&#xA;&lt;p&gt;Finally, the decision depends on the nature of the problem. If you are simulating, say a protein folding, and you are following the all-atom method rather than Coarse Graining, MD would be very very expensive to run. Because it will take huge computing resources.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-05-29T14:30:50.740" LastActivityDate="2023-05-29T14:30:50.740" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10985" PostTypeId="1" CreationDate="2023-05-29T15:02:16.347" Score="5" ViewCount="159" Body="&lt;p&gt;I am new to DFT calculation.&#xA;I want to know the structure of conjugated polymers (&lt;em&gt;plane angle, etc.&lt;/em&gt;) and their electronic and optical properties (&lt;em&gt;such as HOMO-LUMO, IR, etc.&lt;/em&gt;).&lt;/p&gt;&#xA;&lt;p&gt;I am using &lt;strong&gt;6-311+G(d)&lt;/strong&gt; for heavy atoms and &lt;strong&gt;6-31G&lt;/strong&gt; for hydrogen with &lt;strong&gt;B3LYP&lt;/strong&gt;. My question is that setup ok for supporting my experimental data? Or I have to use different method and basis set?&lt;/p&gt;&#xA;" OwnerUserId="7305" LastActivityDate="2023-06-03T18:13:44.290" Title="DFT calculation for conjugated polymers" Tags="|density-functional-theory|electronic-structure|geometry-optimization|basis-sets|polymers|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="10986" PostTypeId="1" CreationDate="2023-05-29T20:50:36.243" Score="4" ViewCount="57" Body="&lt;p&gt;I have a coronene structure, functionalized with hydroxyl groups.&#xA;I want to calculate the charge transfer (CT) between the coronene and the hydroxyl group, using NBO analysis as implemented in Gaussian 09.&lt;/p&gt;&#xA;&lt;p&gt;I understand that I should use the Hirshfeld population, but apart from that, how is it done?&lt;/p&gt;&#xA;" OwnerUserId="3448" LastEditorUserId="5" LastEditDate="2023-06-13T17:52:36.473" LastActivityDate="2023-06-13T17:52:36.473" Title="How to calculate charge transfer (CT) in NBO Analysis using Gaussian 09?" Tags="|computational-chemistry|gaussian|charge-transfer|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10987" PostTypeId="2" ParentId="10936" CreationDate="2023-05-29T21:39:51.643" Score="1" Body="&lt;p&gt;You can get the LDA energy in spin-polarized form (LSDA), or spin-unpolarized (LDA). For a closed-shell system this will give &lt;strong&gt;exactly&lt;/strong&gt; the same energy.&lt;/p&gt;&#xA;&lt;p&gt;In LSDA you work with rho-alpha (=0.5*rho) and rho-beta, which are elevated to the power 4/3.&#xA;In LDA, you work with rho elevated to the power 4/3.&#xA;The trick is in the prefactors, Cx and Ax:&lt;/p&gt;&#xA;&lt;p&gt;2 * (0.5*rho)^(4/3) * Cx = (rho)^(4/3) * Ax&lt;/p&gt;&#xA;&lt;p&gt;You will find that Cx (ca. 0.9305) is equal to 2^(1/3) times Ax (ca. 0,7386).&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-05-29T21:39:51.643" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10988" PostTypeId="1" CreationDate="2023-05-29T21:53:59.100" Score="3" ViewCount="212" Body="&lt;p&gt;I tried to generate a perovskite structure with VESTA, and the following are my settings:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oEYXA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oEYXA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nVqna.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nVqna.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The generated structure seems to be correct. However, when I tried to export it as POSCAR I got the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;New structure&#xA;1.0&#xA;        5.0000000000         0.0000000000         0.0000000000&#xA;        0.0000000000         5.0000000000         0.0000000000&#xA;        0.0000000000         0.0000000000         5.0000000000&#xA;   Cs   Cl   Pb&#xA;    1    9    1&#xA;Direct&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.500000000         0.500000000         0.000000000&#xA;     0.000000000         0.500000000         0.500000000&#xA;     0.500000000         0.000000000         0.500000000&#xA;     0.500000000         0.000000000         0.500000000&#xA;     0.500000000         0.500000000         0.000000000&#xA;     0.000000000         0.500000000         0.500000000&#xA;     0.000000000         0.500000000         0.500000000&#xA;     0.500000000         0.000000000         0.500000000&#xA;     0.500000000         0.500000000         0.000000000&#xA;     0.500000000         0.500000000         0.500000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Seems that each Cl atom is counted thrice. Why did that happen and how should I fix it?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-05-30T13:10:55.650" Title="Why I got more atoms than expected when generating POSCAR from VESTA" Tags="|vasp|crystallography|vesta|perovskites|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10989" PostTypeId="2" ParentId="10979" CreationDate="2023-05-30T04:08:32.667" Score="4" Body="&lt;p&gt;The shortest advice I can give you is to &lt;em&gt;search the literature&lt;/em&gt;. You &lt;em&gt;must&lt;/em&gt; look at the approaches that have been previously tried for your system, especially because these only tend to be published when they work reasonably well. Without doing that you are just following the advice of strangers on the Internet, and while that's perfectly acceptable when deciding where to eat for lunch, that's very difficult to justify in trying to seriously produce scientific knowledge.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9134/definition-of-the-terms-modeling-and-simulation-in-the-context-of-biomolecul/9175#9175&quot;&gt;Almost exactly a year ago&lt;/a&gt; I put this picture on MMSE, from Allen and Tildesley's essential &lt;a href=&quot;https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198803195.001.0001/oso-9780198803195&quot; rel=&quot;nofollow noreferrer&quot;&gt;textbook&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4BTR9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4BTR9.png&quot; alt=&quot;Figure from Allen and Tildesley showing the connection between experiment, modelling, and theory&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is very tempting to start &amp;quot;at the top&amp;quot; of this diagram and say &amp;quot;Let's simulate surface hopping in vapour deposition!&amp;quot; or whatever your phenomenon is. But you need to start &lt;em&gt;at the bottom&lt;/em&gt; and ask yourself:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Do I have experimental results to compare to a model of my phenomenon of interest?&lt;/li&gt;&#xA;&lt;li&gt;Do I have a theoretical framework to explain what I see in a model of my phenomenon of interest?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Ask in addition what the &lt;em&gt;precision&lt;/em&gt; of those results and frameworks are,&lt;sup&gt;1&lt;/sup&gt; because that in turn determines the amount of simulation data you need -- the longer (shorter) you can run your simulation, the more (less) precise your model estimate will be.&lt;/p&gt;&#xA;&lt;p&gt;You also face the problem of how to &lt;em&gt;efficiently&lt;/em&gt; use your computational time. You need to search the literature! There are packages out there that are thousands of times more efficient than a Python &lt;code&gt;solve_ivp&lt;/code&gt; script. You could spend a day writing up a Python implementation and then find that it takes a year to run your simulations -- or you could spend a month learning a package like LAMMPS or GROMACS and then run your simulations in a week. Which sounds better?&lt;/p&gt;&#xA;&lt;p&gt;But most importantly, you must make sure your &lt;em&gt;model&lt;/em&gt; can efficiently calculate &lt;em&gt;theoretical&lt;/em&gt; details that can be compared with your &lt;em&gt;experiments&lt;/em&gt;. Take, again, surface hopping during vapour deposition. You &lt;em&gt;could&lt;/em&gt; just dump a bunch of particles on a surface and run a NumPy integrator and get a diffusivity. But when your experimental value turns out to be a hundred times smaller, what are you going to change? The model masses? The bond strength? What if, it turns out, your model was already as accurate as it could be for its simplicity, and you spend months tweaking parameters only to find out that every tweak makes things worse? And what if it turns out you had the simplest of typos (while converting units, let's say -- the bane of every molecular modeller), and you had the right answer all along?&lt;/p&gt;&#xA;&lt;p&gt;That's why you &lt;em&gt;must search the literature&lt;/em&gt;, and if you are new to the field, you should start by trying to &lt;em&gt;replicate&lt;/em&gt; a known study. This also familiarises you with the process of comparing theory to model to experiment.&lt;/p&gt;&#xA;&lt;p&gt;For what it's worth, in your situation, I'd immediately search for &amp;quot;kinetic Monte Carlo simulation of surface deposition&amp;quot;, for which Google returns me an excellent-looking &lt;a href=&quot;https://www.frontiersin.org/articles/10.3389/fphy.2021.631918/full&quot; rel=&quot;nofollow noreferrer&quot;&gt;review&lt;/a&gt;. But a kMC simulation (as they're known for short) requires you to input sensible reaction rates. You'd probably need to get those from a quantum calculation of some sort, probably a nudged-elastic band calculation of the individual reaction energy profiles using density functional theory. Note that the latter does not fall in your &amp;quot;MC or MD&amp;quot; question, and the former might not have fallen in your umbrella MC category either (most kMC people I know think of themselves as doing something more specialised than regular molecular MC, using something like the GOMC package, and they're not wrong).&lt;/p&gt;&#xA;&lt;p&gt;But again -- you shouldn't be basing your scientific research on what a stranger says on MMSE. Go look through the literature and see what the field is doing. There is no shortcut for that.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; If I want to explain why gravitational acceleration is 9.8 meters per second squared, I just need to know Newton's law of gravity and the mass and radius of the earth. If I want to explain its value to nine decimal places, suddenly I have to learn general relativity too.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-05-30T04:08:32.667" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="10990" PostTypeId="2" ParentId="10983" CreationDate="2023-05-30T04:39:01.963" Score="3" Body="&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.5b00846&quot; rel=&quot;nofollow noreferrer&quot;&gt;This paper&lt;/a&gt; from 2015 describes a &lt;em&gt;modified&lt;/em&gt; metadynamics method (parallel-bias metadynamics) by which the authors demonstrate enhanced sampling over &lt;em&gt;six&lt;/em&gt; collective variables for the tryptophan cage system&lt;sup&gt;1&lt;/sup&gt;. They do not mention any attempts using plain metadynamics to get anywhere near that number of CVs, so I assume (from silence) that 3D is as far as plain metadynamics has went.&lt;/p&gt;&#xA;&lt;p&gt;Even before worrying about convergence, I think you'd have a problem simply calculating the metadynamics bias. Doing so &amp;quot;by hand&amp;quot; (storing all visited points and calculating the gradient from each previous point at a new step) is very slow. But if you try to deposit the weights on a grid, the number of grid points needed increases exponentially with dimensionality. Storing 50^3 floats takes 50 KB of RAM; storing 50^6 floats takes 62.5 GB of RAM, which you won't have per processor on almost any cluster. The paper I linked above gets around this by marginalising the landscape onto each CV separately. Somehow the authors can reconstruct the whole landscape afterwards; I'm not sure exactly how they do it, and I'm keen to learn.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Sadly, they lacked six-dimensional paper to print their six-dimensional free energy landscape upon. More funding needed, surely.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-05-30T04:49:29.093" LastActivityDate="2023-05-30T04:49:29.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10991" PostTypeId="1" CreationDate="2023-05-30T05:12:28.217" Score="2" ViewCount="47" Body="&lt;p&gt;In this paper &amp;quot;&lt;a href=&quot;https://www.nature.com/articles/s41467-020-15993-4&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lattice distortion induced internal electric field in TiO2 photoelectrode for efficient charge separation and transfer&lt;/a&gt;&amp;quot;, the authors calculated the polarization of anatase TiO2 induced by Li-doping using VASP. Specifically, due to the Li-doping, the TiO6 octahedra will be distorted, and thus introducing dipole moments into TiO2.&lt;/p&gt;&#xA;&lt;p&gt;However, in the calculated polarization presented in FIG. 2g (the figure below, where black bars correspond to pristine TiO2, and red bars correspond to Li-doped TiO2), there are also polarization in pristine TiO2, which is abnormal.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RmSZz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RmSZz.png&quot; alt=&quot;polar&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Based on my understanding of the workflow to calculate polarization in periodic systems, a centrosymmetric structure is required. However, as for the Li-doped TiO2, how can the centrosymmetric structure be constructed? This is not specified in the paper.&lt;/p&gt;&#xA;&lt;p&gt;Apart from this example, from a more general perspective, what is the reliable approach to calculate the polarization caused by doping induced lattice distortion? Most importantly, how the reference structure, i.e., the centrosymmetric structure be constructed?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastEditorUserId="1483" LastEditDate="2023-05-31T07:32:53.297" LastActivityDate="2023-05-31T07:32:53.297" Title="How to calculate the polarization caused by doping induced lattice distortion?" Tags="|vasp|dipole|reproducing-data-from-papers|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-01T19:43:29.530" ContentLicense="CC BY-SA 4.0" />
  <row Id="10993" PostTypeId="1" CreationDate="2023-05-30T10:48:05.210" Score="1" ViewCount="282" Body="&lt;p&gt;I have been recently trying to optimize a particularly large system Mo2C in QE using the pw.x executable and encountering the following MPI errors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[compute-0-0:285011] *** An error occurred in MPI_Comm_free&#xA;[compute-0-0:285011] *** reported by process [140734245568513,140642999074824]&#xA;[compute-0-0:285011] *** on communicator MPI_COMM_WORLD&#xA;[compute-0-0:285011] *** MPI_ERR_COMM: invalid communicator&#xA;[compute-0-0:285011] *** MPI_ERRORS_ARE_FATAL (processes in this communicator will now abort,&#xA;[compute-0-0:285011] ***    and potentially your MPI job)&#xA;[compute-0-0.local:284985] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198&#xA;[compute-0-0.local:284985] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198&#xA;[compute-0-0.local:284985] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198&#xA;[compute-0-0.local:284985] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198&#xA;[compute-0-0.local:284985] 9 more processes have sent help message help-mpi-errors.txt / mpi_errors_are_fatal&#xA;[compute-0-0.local:284985] Set MCA parameter &amp;quot;orte_base_help_aggregate&amp;quot; to 0 to see all help / error messages&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input file for the job is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation   = &amp;quot;relax&amp;quot;&#xA;    forc_conv_thr =  1.00000e-03&#xA;    nstep         = 100&#xA;    pseudo_dir    = &amp;quot;/home/user42/pseudopot&amp;quot;&#xA;    tprnfor       = .TRUE.&#xA;    tstress       = .TRUE.&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;    a                         =  1.44246e+01&#xA;    c                         =  3.26030e+01&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  7.20000e+02&#xA;    ecutwfc                   =  8.00000e+01&#xA;    ibrav                     = 4&#xA;    nat                       = 75&#xA;    nspin                     = 2&#xA;    ntyp                      = 2&#xA;    vdw_corr                  =&amp;quot;grimme-d2&amp;quot;&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  2.00000e-01&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  4.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;    ion_dynamics = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;CELL&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 2  2  1  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;Mo   95.94000  Mo.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;C    12.01070  C.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Mo   -0.000000   1.665610  17.691990&#xA;Mo    2.884921   1.665610  17.691990&#xA;Mo    5.769843   1.665610  17.691990&#xA;Mo    8.654764   1.665610  17.691990&#xA;Mo   11.539685   1.665610  17.691990&#xA;Mo   -1.442461   4.164025  17.691990&#xA;Mo    1.442461   4.164025  17.691990&#xA;Mo    4.327382   4.164025  17.691990&#xA;Mo    7.212303   4.164025  17.691990&#xA;Mo   10.097225   4.164025  17.691990&#xA;Mo   -2.884921   6.662441  17.691990&#xA;Mo   -0.000000   6.662441  17.691990&#xA;Mo    2.884921   6.662441  17.691990&#xA;Mo    5.769843   6.662441  17.691990&#xA;Mo    8.654764   6.662441  17.691990&#xA;Mo   -4.327382   9.160856  17.691990&#xA;Mo   -1.442461   9.160856  17.691990&#xA;Mo    1.442461   9.160856  17.691990&#xA;Mo    4.327382   9.160856  17.691990&#xA;Mo    7.212303   9.160856  17.691990&#xA;Mo   -5.769843  11.659271  17.691990&#xA;Mo   -2.884921  11.659271  17.691990&#xA;Mo   -0.000000  11.659271  17.691990&#xA;Mo    2.884921  11.659271  17.691990&#xA;Mo    5.769843  11.659271  17.691990&#xA;C    0.000000   0.000000  16.301511  &#xA;C    2.884921   0.000000  16.301511  &#xA;C    5.769843   0.000000  16.301511  &#xA;C    8.654764   0.000000  16.301511  &#xA;C   11.539685   0.000000  16.301511  &#xA;C   -1.442461   2.498415  16.301511  &#xA;C    1.442461   2.498415  16.301511  &#xA;C    4.327382   2.498415  16.301511  &#xA;C    7.212303   2.498415  16.301511  &#xA;C   10.097225   2.498415  16.301511  &#xA;C   -2.884921   4.996830  16.301511  &#xA;C   -0.000000   4.996830  16.301511  &#xA;C    2.884921   4.996830  16.301511  &#xA;C    5.769843   4.996830  16.301511  &#xA;C    8.654764   4.996830  16.301511  &#xA;C   -4.327382   7.495246  16.301511  &#xA;C   -1.442461   7.495246  16.301511  &#xA;C    1.442461   7.495246  16.301511  &#xA;C    4.327382   7.495246  16.301511  &#xA;C    7.212303   7.495246  16.301511  &#xA;C   -5.769843   9.993661  16.301511  &#xA;C   -2.884921   9.993661  16.301511  &#xA;C   -0.000000   9.993661  16.301511  &#xA;C    2.884921   9.993661  16.301511  &#xA;C    5.769843   9.993661  16.301511  &#xA;Mo   -0.000000   1.665610  14.911032  &#xA;Mo    2.884921   1.665610  14.911032  &#xA;Mo    5.769843   1.665610  14.911032  &#xA;Mo    8.654764   1.665610  14.911032  &#xA;Mo   11.539685   1.665610  14.911032  &#xA;Mo   -1.442461   4.164025  14.911032  &#xA;Mo    1.442461   4.164025  14.911032  &#xA;Mo    4.327382   4.164025  14.911032  &#xA;Mo    7.212303   4.164025  14.911032  &#xA;Mo   10.097225   4.164025  14.911032  &#xA;Mo   -2.884921   6.662441  14.911032  &#xA;Mo   -0.000000   6.662441  14.911032  &#xA;Mo    2.884921   6.662441  14.911032  &#xA;Mo    5.769843   6.662441  14.911032  &#xA;Mo    8.654764   6.662441  14.911032  &#xA;Mo   -4.327382   9.160856  14.911032  &#xA;Mo   -1.442461   9.160856  14.911032  &#xA;Mo    1.442461   9.160856  14.911032  &#xA;Mo    4.327382   9.160856  14.911032  &#xA;Mo    7.212303   9.160856  14.911032  &#xA;Mo   -5.769843  11.659271  14.911032  &#xA;Mo   -2.884921  11.659271  14.911032  &#xA;Mo   -0.000000  11.659271  14.911032  &#xA;Mo    2.884921  11.659271  14.911032  &#xA;Mo    5.769843  11.659271  14.911032  &#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The job is being run on a cluster system where parallel QE is installed. Other optimization jobs with smaller systems are running perfectly fine, but this or larger systems are encountering this similar error.&lt;/p&gt;&#xA;&lt;p&gt;Can someone suggest some workaround or reasoning behind this?&lt;/p&gt;&#xA;" OwnerUserId="753" LastEditorUserId="5" LastEditDate="2023-12-01T19:06:56.007" LastActivityDate="2023-12-01T19:06:56.007" Title="MPI error in Quantum ESPRESSO during optimization of particularly large molecules" Tags="|quantum-espresso|computational-chemistry|high-performance-computing|plane-waves|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10994" PostTypeId="1" CreationDate="2023-05-30T12:08:16.200" Score="2" ViewCount="147" Body="&lt;p&gt;I want to study the effect of adding a gate to quantum transport device, the problem that i encounter is that in siesta manual there are two methods to do so, the first is &amp;quot;Geometry.Charge&amp;quot; and the second is &amp;quot;Geometry.Hartree&amp;quot; which gives no change in  transport properties. However, with &lt;code&gt;Geometry.Charge&lt;/code&gt; i noticed a shift in fermi energy, but the problem is that with the code you can only precise the charge density not the dedired shift of Ef. So how can i know the charge to apply for the gate in order to have a defined shift value ?&#xA;My second question is about the position of gate, in the manual we find this code to apply a square gate:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;square 1. eV # The lifting potential on the geometry&#xA;delta&#xA;1.0 1.0 1.0 Ang # The starting point of the square&#xA;2.0 0.5 0.2 Ang # The first spanning vector&#xA;0.0 2.5 0.2 Ang # The second spanning vector&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;But there is no explanation regarding the details of each parameter, for example, the origin of the spanning vector.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Thank you for you help in advance&lt;/p&gt;&#xA;" OwnerUserId="7315" LastEditorUserId="5" LastEditDate="2023-12-01T18:22:50.880" LastActivityDate="2023-12-31T19:00:35.070" Title="Gate potential wiith siesta/transiesta" Tags="|siesta|transport|" AnswerCount="1" CommentCount="20" ContentLicense="CC BY-SA 4.0" />
  <row Id="10995" PostTypeId="2" ParentId="10988" CreationDate="2023-05-30T13:10:55.650" Score="3" Body="&lt;p&gt;When you input the coordinates into VESTA, they should be the symmetrically distinct basis atoms. If you hit &amp;quot;Apply&amp;quot; after inputting only the first Cl atom, you can see that the other two Cl atoms you input are automatically generated based on the inputted FCC space group. Because you are inputting the same atoms/positions three times in this case, you are getting repeat Cl positions in the POSCAR file.&lt;/p&gt;&#xA;" OwnerUserId="4192" LastActivityDate="2023-05-30T13:10:55.650" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="10996" PostTypeId="1" AcceptedAnswerId="11004" CreationDate="2023-05-30T13:43:48.947" Score="4" ViewCount="204" Body="&lt;p&gt;I want to use the smooth overlap of atomic positions (SOAP) as a descriptor to represent the atomic environment of a specific atom to predict chemical shifts. I have generated averaged SOAPs for different molecules with the Python library &lt;em&gt;DScribe&lt;/em&gt;. Using Gaussian Process regression as it is implemented in scikit-learn requires the training data input to be an array of the shape (n_samples, n_features). What I am asking myself at the moment is if the SOAP output (which is an array of shape (132,) for every sample) can be used as an input for&#xA;&lt;code&gt;sklearn.gaussian_process.GaussianProcessRegressor&lt;/code&gt;. While my training set consists of 20 samples at the moment (one SOAP descriptor for every sample molecule), I am not sure how to set the shape of the input array so it can be used for GPR in scikit-learn. The fitting is done by:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gpr = GaussianProcessRegressor(kernel=kernel).fit(X_train, y_train)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is it possible to provide input for X_train in the form of a vector or array &lt;em&gt;for each sample&lt;/em&gt;? Or is it only possible to pass scalar values ?&lt;/p&gt;&#xA;" OwnerUserId="5646" LastEditorUserId="5646" LastEditDate="2023-05-30T13:56:01.570" LastActivityDate="2023-05-31T09:04:45.670" Title="Smooth overlap of atomic positions (SOAP) output for Gaussian Process regression in sklearn" Tags="|computational-chemistry|python|machine-learning|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="10997" PostTypeId="1" CreationDate="2023-05-30T13:53:56.913" Score="2" ViewCount="142" Body="&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;I submitted 2 jobs for the first time in a HPC to test it. It's a very light calculation that takes almost 5 minutes or less in my desktop. But it has been almost 1 hour since I submitted the job in the HPC with SLURM using the command &lt;code&gt;sbatch script.sl&lt;/code&gt;  and I still didn't see an output from my calculations.&lt;/p&gt;&#xA;&lt;p&gt;When I use the command &lt;code&gt;squeue -u username&lt;/code&gt; I get the folloming :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;JOBID  PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON) &#xA;192137    shortq      one  username PD       0:00      2 (Nodes required for job are DOWN, DRAINED or reserved for jobs in higher priority partitions) &#xA;192138    shortq      one  username PD       0:00      2 (Priority) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried to verify the status of the calculation by the command &lt;code&gt;sacct -j 192138 -o start,end&lt;/code&gt; but I got the following result (same thing for the other job):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;              Start                 End &#xA;------------------- ------------------- &#xA;            Unknown             Unknown &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Scripts that I used&lt;/h1&gt;&#xA;&lt;p&gt;For Job 192137:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -J one&#xA;#SBATCH --ntasks=64&#xA;#SBATCH --ntasks-per-core=1&#xA;#SBATCH --partition=shortq&#xA;#SBATCH -o %x-%j.out&#xA;#SBATCH -e %x-%j.err&#xA;&#xA;#load QuantumESPRESSO&#xA;module load QuantumESPRESSO/intel/7.0&#xA;export OMP_NUM_THREADS=1&#xA;&#xA;#prepare work dir&#xA;export WORK_DIR=/data/&lt;span class=&quot;math-container&quot;&gt;$USER/Qe$&lt;/span&gt;{SLURM_JOB_ID}&#xA;export INPUT_DIR=$PWD/myInput&#xA;&#xA;[[ -z &lt;span class=&quot;math-container&quot;&gt;$INPUT_DIR ]] &amp;amp;&amp;amp; { echo &quot;Error: Input Directory (INPUT_DIR) is not defined &quot;; exit 1; }&#xA;[[ ! -d $&lt;/span&gt;INPUT_DIR ]] &amp;amp;&amp;amp; { echo &amp;quot;Error:Input Directory (INPUT_DIR) does not exist &amp;quot;; exit 1; }&#xA;&#xA;export ESPRESSO_PSEUDO=/data/&lt;span class=&quot;math-container&quot;&gt;$USER/pseudo&#xA;mkdir -p $&lt;/span&gt;WORK_DIR&#xA;cp -R &lt;span class=&quot;math-container&quot;&gt;$INPUT_DIR/* $&lt;/span&gt;WORK_DIR&#xA;cd $WORK_DIR&#xA;&#xA;#run&#xA;echo &amp;quot;Running Quantum Espresso with &lt;span class=&quot;math-container&quot;&gt;$SLURM_NTASKS at $&lt;/span&gt;WORK_DIR&amp;quot;&#xA;&#xA;mpirun -np $SLURM_NTASKS pw.x -i 1.in &amp;gt; 1.out&#xA;&#xA;echo &amp;quot;Done&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For Job 192138:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -J one&#xA;#SBATCH --ntasks=64&#xA;#SBATCH --ntasks-per-core=1&#xA;#SBATCH --time=00:10:00&#xA;&#xA;#SBATCH --partition=shortq&#xA;#SBATCH -o %x-%j.out&#xA;#SBATCH -e %x-%j.err&#xA;&#xA;#load QuantumESPRESSO&#xA;module load QuantumESPRESSO/intel/7.0&#xA;export OMP_NUM_THREADS=1&#xA;&#xA;#prepare work dir&#xA;export WORK_DIR=/data/&lt;span class=&quot;math-container&quot;&gt;$USER/Qe$&lt;/span&gt;{SLURM_JOB_ID}&#xA;export INPUT_DIR=$PWD/myInput&#xA;&#xA;[[ -z &lt;span class=&quot;math-container&quot;&gt;$INPUT_DIR ]] &amp;amp;&amp;amp; { echo &quot;Error: Input Directory (INPUT_DIR) is not defined &quot;; exit 1; }&#xA;[[ ! -d $&lt;/span&gt;INPUT_DIR ]] &amp;amp;&amp;amp; { echo &amp;quot;Error:Input Directory (INPUT_DIR) does not exist &amp;quot;; exit 1; }&#xA;&#xA;export ESPRESSO_PSEUDO=/data/&lt;span class=&quot;math-container&quot;&gt;$USER/pseudo&#xA;mkdir -p $&lt;/span&gt;WORK_DIR&#xA;cp -R &lt;span class=&quot;math-container&quot;&gt;$INPUT_DIR/* $&lt;/span&gt;WORK_DIR&#xA;cd $WORK_DIR&#xA;&#xA;#run&#xA;echo &amp;quot;Running Quantum Espresso with &lt;span class=&quot;math-container&quot;&gt;$SLURM_NTASKS at $&lt;/span&gt;WORK_DIR&amp;quot;&#xA;&#xA;mpirun -np $SLURM_NTASKS pw.x -i 1.in &amp;gt; 1.out&#xA;&#xA;echo &amp;quot;Done&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-12-01T18:09:42.730" LastActivityDate="2023-12-01T18:12:30.537" Title="Why are my HPC calculations not running in SLURM?" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|high-performance-computing|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="10998" PostTypeId="1" CreationDate="2023-05-30T22:34:03.890" Score="4" ViewCount="145" Body="&lt;p&gt;This is a follow-up to my previous question:  &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10908/5&quot;&gt;Optimal Gaussian basis set for hydrogen atom in magnetic field&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Brief description of the problem&lt;/h2&gt;&#xA;&lt;p&gt;I would like to find the ground and excited states of the system:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$H=-\frac{1}{2}\Delta-\frac{1}{r}+\frac{B^2}{8}\rho^2-\frac{B}{2} (m + 2 m_s),\tag{1}$$&lt;/span&gt; in which &lt;span class=&quot;math-container&quot;&gt;$r=(\rho,z,\phi), B=5, m=0, m_s=-1/2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Method&lt;/h2&gt;&#xA;&lt;p&gt;To find the eigenvalues I would like to use Gaussian functions: &lt;span class=&quot;math-container&quot;&gt;$$\psi_{ij}=e^{-b_{j} z^2}e^{-a_{i} \rho^2},\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;a_{i}&amp;amp;=a_1 qa^{i-1}, i=1, 2 ,3,..., i_{\textrm{max}},\tag{3}\\b_{j}&amp;amp;=b_1 qb^{j-1}, j=1, 2 ,3,..., j_{\textrm{max}},\tag{4}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;are geometrical progressions.&lt;/p&gt;&#xA;&lt;h2&gt;Code&lt;/h2&gt;&#xA;&lt;p&gt;I used Mathematica (in the code I rename &lt;span class=&quot;math-container&quot;&gt;$\alpha_i \equiv a_i$&lt;/span&gt;,  &lt;span class=&quot;math-container&quot;&gt;$\beta_j \equiv b_j$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\rho\equiv r$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ClearAll[&amp;quot;Global`*&amp;quot;]&#xA;&#xA;imax = 4; jmax = 5;&#xA;&#xA;B = 5; lz = m = 0; ms = -1/2;&#xA;&#xA;VP1[r_, z_] := -1/Sqrt[r^2 + z^2];&#xA;&#xA;Psi[r_, z_, i_, j_] := Exp[-b[j]*z^2]*Exp[-a[i]*r^2];&#xA;&#xA;a[1] = a1;&#xA;b[1] = b1;&#xA;Do[a[i] = a[i - 1] qa, {i, 2, imax}];&#xA;Do[b[j] = b[j - 1] qb, {j, 2, jmax}];&#xA;&#xA;(*kinetic energy*)&#xA;Kk = FullSimplify[&#xA;   Psi[r, z, i2, j2] *&#xA;    Laplacian[Psi[r, z, i1, j1] , {r, \[Theta], z}, &amp;quot;Cylindrical&amp;quot;]];&#xA;Kk1 = -1/2 2 Pi*&#xA;   Integrate[Kk r, {r, 0, \[Infinity]}, {z, -Infinity, Infinity}, &#xA;    Assumptions -&amp;gt; {a[i1] &amp;gt; 0, b[i1] &amp;gt; 0, a[i2] &amp;gt; 0, b[i2] &amp;gt; 0, &#xA;      a[j1] &amp;gt; 0, b[j1] &amp;gt; 0, a[j2] &amp;gt; 0, b[j2] &amp;gt; 0}];&#xA;Kx = Table[ &#xA;   Kk1, {i1, 1, imax}, {i2, 1, imax}, {j1, 1, jmax}, {j2, 1, jmax}];&#xA;KK[a1_, b1_, qa_, qb_] = Flatten[Kx, {{1, 3}, {2, 4}}];&#xA;&#xA;(*potential energy + A kinetic energy*)&#xA;Px1 = 2 Pi*&#xA;   Integrate[&#xA;    Psi[r, z, i2, j2] *(VP1[r, z] + 1/8 B^2 r^2 + B/2 (m + 2 ms))*&#xA;     Psi[r, z, i1, j1]*r, {r, 0, \[Infinity]}, {z, -Infinity, &#xA;     Infinity}, &#xA;    Assumptions -&amp;gt; {a[i1] &amp;gt; 0, b[i1] &amp;gt; 0, a[i2] &amp;gt; 0, b[i2] &amp;gt; 0, &#xA;      a[j1] &amp;gt; 0, b[j1] &amp;gt; 0, a[j2] &amp;gt; 0, b[j2] &amp;gt; 0}];&#xA;Px = Table[&#xA;   Px1, {i1, 1, imax}, {i2, 1, imax}, {j1, 1, jmax}, {j2, 1, jmax}];&#xA;PP = Flatten[Px, {{1, 3}, {2, 4}}];&#xA;&#xA;EE = KK + PP;&#xA;&#xA;(*normalization*)&#xA;int = 2 Pi*&#xA;   Integrate[&#xA;    Psi[r, z, i2, j2] *Psi[r, z, i1, j1]  r, {r, &#xA;     0, \[Infinity]}, {z, -Infinity, Infinity}, &#xA;    Assumptions -&amp;gt; {a[i1] &amp;gt; 0, b[i1] &amp;gt; 0, a[i2] &amp;gt; 0, b[i2] &amp;gt; 0, &#xA;      a[j1] &amp;gt; 0, b[j1] &amp;gt; 0, a[j2] &amp;gt; 0, b[j2] &amp;gt; 0}];&#xA;norm = Table[ &#xA;   int, {i1, 1, imax}, {i2, 1, imax}, {j1, 1, jmax}, {j2, 1, jmax}];&#xA;BB = Flatten[norm, {{1, 3}, {2, 4}}];&#xA;&#xA;IBB = Inverse[BB](**)&#xA;&#xA;(*the sum of eigenvalues to minimize*)&#xA;Tr[EE.IBB]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Problem&lt;/h2&gt;&#xA;&lt;p&gt;The code cannot handle more than 20 basis functions, but the paper from the 1970s was able to do 100+ basis functions.  I will be glad to see any  comments. Please use any programming language convenient for you, I will try to figure it out.&lt;/p&gt;&#xA;" OwnerUserId="7193" LastEditorUserId="5" LastEditDate="2023-06-04T01:32:37.620" LastActivityDate="2023-06-04T01:32:37.620" Title="Help with Mathematica for optimizing a Gaussian basis set for a hydrogen atom in a magnetic field" Tags="|density-functional-theory|quantum-chemistry|condensed-matter|mathematical-modeling|basis-sets|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="10999" PostTypeId="1" CreationDate="2023-05-30T22:37:38.903" Score="5" ViewCount="170" Body="&lt;p&gt;I am performing the HSE06 band structure calculation after starting from pbe scf WAVECAR. The input file looks like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; SYSTEM   =  Perovskite                                               &#xA;# Electronic minimization                                                                                                 &#xA;ISTART  = 1                                                            &#xA;ICHARG  = 0                                                            &#xA;ALGO    = Damped&#xA;PREC= Normal                                                                                                                                                                   &#xA;ENCUT   = 400                                                                                                                                                                    &#xA;NELM    = 200                                                                                                                                                                                                                                                                         &#xA;EDIFF   = 1E-6                                                         &#xA;EDIFFG  =-0.03                                                         &#xA;LWAVE   =.FALSE.                                                                                                                                                                                                                                                                                      &#xA;IVDW    = 11                                                           &#xA;VDW_S8 = 0.109                                                         &#xA;VDW_SR = 1.129                                                         &#xA;LORBIT  = 10                                                          &#xA;# Ionic minimization                                                                                                                                                                                                            &#xA;IBRION  = -1                                                           &#xA;ISIF    = 3                                                            &#xA;POTIM   = 0.5                                                         &#xA;                                                                                                                                                                                                                           &#xA;# Exchange correlational functional                                                                                       &#xA;GGA = PE                                                               &#xA;LHFCALC = .TRUE.                                                       &#xA;HFSCREEN = 0.2                                                        &#xA;#Algo = Damped                                                                                                          &#xA;TIME = 0.4                                                             &#xA;ISMEAR   = 0                                                           &#xA;SIGMA    = 0.02                                                        &#xA;NCORE = 4                                                              &#xA;KPAR = 8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the calculation gets stuck before starting iterations. The OUTCAR shows&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FT5Ww.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FT5Ww.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This exact INCAR has worked for the same system(with slightly different POSCAR, the space group remained same though). What could be the reason that the calculation gets stuck here?&lt;/p&gt;&#xA;" OwnerUserId="5602" LastActivityDate="2023-06-12T11:54:06.537" Title="HSE06 band structure calculation in VASP stuck" Tags="|vasp|hse06|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11001" PostTypeId="1" CreationDate="2023-05-31T02:15:22.413" Score="-4" ViewCount="502" Body="&lt;p&gt;I want to know how to calculate the band structure and DOS of a thin layer of iron selenide in quantum espresso. How I can fix the input file? Is it different from Bulk matter or the same? Which parameter(s) do I need to will change?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;This is my input file&#xA;&amp;amp;CONTROL&#xA;    calculation = &amp;quot;scf&amp;quot;&#xA;    outdir      =  &amp;quot;FeSe&amp;quot;&#xA;    pseudo_dir  = &amp;quot;.&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;    a                         =  3.93329e+00&#xA;    c                         =  5.85659e+00&#xA;    degauss                   =  1.00000e-02&#xA;    ecutrho                   =  2.25000e+02&#xA;    ecutwfc                   =  2.50000e+01&#xA;    ibrav                     = 6&#xA;    nat                       = 4&#xA;    nspin                     = 2&#xA;    ntyp                      = 2&#xA;    occupations               = &amp;quot;smearing&amp;quot;&#xA;    smearing                  = &amp;quot;gaussian&amp;quot;&#xA;    starting_magnetization(1) =  2.00000e-01&#xA;    starting_magnetization(2) =  0.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-06&#xA;    electron_maxstep = 200&#xA;    mixing_beta      =  4.00000e-01&#xA;    startingpot      = &amp;quot;atomic&amp;quot;&#xA;    startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 3  3  2  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;Fe   55.84500  Fe.pbe-nd-rrkjus.UPF&#xA;Se   78.96000  Se.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Fe    1.5   1.966645   0.000000&#xA;Fe    0.000000   0.000000   0.000000&#xA;Se    1.966645   0.000000   1.50&#xA;Se    0.000000   1.966645   4.347667&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7321" LastEditorUserId="5" LastEditDate="2023-09-03T16:56:42.283" LastActivityDate="2023-09-03T18:55:52.003" Title="How may I make a slab surface to calculate a thin layer with Quantum ESPRESSO?" Tags="|vasp|molecular-dynamics|quantum-espresso|band-structure|density-of-states|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="11004" PostTypeId="2" ParentId="10996" CreationDate="2023-05-31T09:04:45.670" Score="4" Body="&lt;p&gt;The X_train in the .fit method is accepts an array-like object of shape (n_samples, n_features) which could be a numpy array or list of object Feature vectors.&lt;/p&gt;&#xA;&lt;p&gt;The descriptions of various arguments can be found here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GaussianProcessRegressor-Docs&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So in your case the input to the &lt;code&gt;GaussianProcessRegressor&lt;/code&gt; would be an array of size 20x132.&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-05-31T09:04:45.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11005" PostTypeId="2" ParentId="10762" CreationDate="2023-05-31T10:48:37.587" Score="3" Body="&lt;p&gt;As you have explicitly specified the temperature in a TranSiesta run via the electronic temperature you should rely on that temperature in the function you describe.&lt;/p&gt;&#xA;&lt;p&gt;So the answer is yes. Be consistent about temperatures.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-05-31T10:48:37.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11006" PostTypeId="1" AcceptedAnswerId="11010" CreationDate="2023-05-31T10:49:14.833" Score="5" ViewCount="933" Body="&lt;p&gt;After I run an SCF calculation with PBE0, I want to use &lt;code&gt;calculation= 'nscf'/ (‘bands’)&lt;/code&gt; with PBE0, but this message occurs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error in routine setup (1):&#xA;     hybrid XC not allowed in non-scf calculations&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does any one know how to fix it? Or how can I calculate the hybrid function band structure and DOS in the right way&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="7" LastEditDate="2023-06-05T16:27:41.177" LastActivityDate="2023-06-05T16:27:41.177" Title="How to calculate DOS and band structure using hybrid functional in Quantum Espresso?" Tags="|quantum-espresso|density-of-states|functional|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11007" PostTypeId="1" CreationDate="2023-05-31T14:01:21.700" Score="5" ViewCount="171" Body="&lt;p&gt;I'm currently trying to simulate the calcium carbonate mineralization process on the surface of nanoparticles. In here, I've already borrowed the classical force-field parameters on here(&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ja108508k&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/ja108508k&lt;/a&gt;), in which the interactions for calcium/carbonate ions and water are described as the mixing of Electrostatic/Lennard Jones/Buckingham potential.&lt;/p&gt;&#xA;&lt;p&gt;The very obstacle for classical MD simulation is that when I'm trying to observe the calcium carbonate mineralization (or nucleation) process by setting the initial structure of nanoparticles and calcium/carbonate ions in a separate way, both ions try to adsorb to the surface of nanoparticles but with a highly disordered manner. Even without the nanoparticles, the aggregation of calcium/carbonate ions in solution phase is quite favorable, but again, it's very hard to observe that such aggregated clusters exist with any crystalline order. Referring to the previous literature (&lt;a href=&quot;https://www.nature.com/articles/ncomms1604&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/ncomms1604&lt;/a&gt;), the authors only analyzed the very early stages of calcium carbonate formation as stable prenucleation clusters, without extending the scope to observe the full mineralization process. Although the purpose of my research is aimed to address why certain type of crystal structure (among the three polymorphs of calcium carbonate) is favorably mineralized on nanoparticles surface, it seems that just implementing the usual classical force-field is quite unfeasible to observe the transition from solvated calcium/carbonate ions into the crystalline structure.&lt;/p&gt;&#xA;&lt;p&gt;My question here is that is there any way to simulate/analyze the mineralization process on here. I expect that such incapability of simulating the mineralization process in classical MD simulation would be originated from the poor transferability of force field parameters between solvated/mineral phase of calcium carbonate ions. It'd be really appreciated if one could recommend any reference for simulating mineralization process using classical MD simulation. Sharing any experience for the one who've already done the similar work would be highly informative for me!&lt;/p&gt;&#xA;" OwnerUserId="1009" LastEditorUserId="1009" LastEditDate="2023-05-31T15:10:10.963" LastActivityDate="2023-05-31T15:32:04.800" Title="Classical MD Simulation for mineralization process" Tags="|molecular-dynamics|forcefields|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11008" PostTypeId="1" CreationDate="2023-05-31T14:19:17.400" Score="2" ViewCount="46" Body="&lt;p&gt;I am trying to calculate transport properties using the AMSET package (with VASP), to be able to calculate the electron relaxation time.&lt;/p&gt;&#xA;&lt;p&gt;My system is a monolayer of graphene doped with isoelectronic doping units. I understand that the treatment of doping atoms in regard to electron-impurity scattering could be problematic.&lt;/p&gt;&#xA;&lt;p&gt;Does someone have experience and/or comments on the usage of the supercell approach in the modelling of periodically doped materials with AMSET?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-05-31T14:19:17.400" Title="Transport calculations with AMSET package" Tags="|electronic-transport|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-03T18:28:25.090" ContentLicense="CC BY-SA 4.0" />
  <row Id="11009" PostTypeId="2" ParentId="11007" CreationDate="2023-05-31T15:32:04.800" Score="5" Body="&lt;p&gt;&lt;strong&gt;Fair Note:&lt;/strong&gt; I have experience with only studying aggregation of small molecules at the solid - liquid interface.&lt;/p&gt;&#xA;&lt;p&gt;If you are trying to study the formation of an ordered structure from a solution phase using classical MD simulations, you would need to run the simulations for a very long time, atleast to hope that you get close to an ordered structure. For example, in this &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2021/nr/d0nr08796c&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; we had to perform a 750 ns simulation to get an ordered structure. But even if you perform such long simulations, there is no guarantee that you will converge to the state that you are hoping to achieve, because classical FF parameters are empirically tuned to reproduce certain properties only. Then your best bet becomes to repeat the simulations multiple times, and look at the statistics to form a general idea.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-05-31T15:32:04.800" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11010" PostTypeId="2" ParentId="11006" CreationDate="2023-05-31T21:10:51.903" Score="5" Body="&lt;p&gt;There is no problem with your input (if that's the only error). Quantum ESPRESSO doesn't support nscf calculation with hybrid functional. But if your goal is to obtain the DOS and band structure only, then I think it's possible to obtain them without nscf calculation.&lt;/p&gt;&#xA;&lt;p&gt;So, what we usually do:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(step1) a &lt;code&gt;calculation='scf'&lt;/code&gt; with rough k-grid (&lt;code&gt;pw.x&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(step2) a &lt;code&gt;calculation='nscf'&lt;/code&gt; with fine k-grid and &lt;code&gt;occupations='tetrahedra'&lt;/code&gt; (&lt;code&gt;pw.x&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(step3) post-processing to obtain the density of states (&lt;code&gt;dos.x&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(step4) a &lt;code&gt;calculation='bands'&lt;/code&gt; by &lt;em&gt;not&lt;/em&gt; setting &lt;code&gt;occupations='tetrahedra'&lt;/code&gt; and choosing the &lt;code&gt;K_POINTS&lt;/code&gt; as &lt;code&gt;crystal_b&lt;/code&gt; or &lt;code&gt;tpiba_b&lt;/code&gt; according to our crystal's BZ (&lt;code&gt;pw.x&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;(step5) post-processing to obtain the band structure (&lt;code&gt;bands.x&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Instead, for hybrid functional, consider the following path:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For DOS:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(step1) remains the same as before but instead of a rough grid, use the densest k-point grid you can afford. Try &lt;code&gt;occupations='tetrahedra'&lt;/code&gt; if that works. There is a caution mentioned in QE's input description: &lt;em&gt;BEWARE: only grids having the full symmetry of the crystal work with tetrahedra. Some grids with offset may not work.&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;(step2) post-processing to obtain the density of states (&lt;code&gt;dos.x&lt;/code&gt;), i.e., we are skipping previous &lt;em&gt;(step2)&lt;/em&gt;. Or if you want the projected DOS, you can also do &lt;code&gt;projwfc.x&lt;/code&gt; post-processing right after the scf calculation. Skipping nscf will not create a problem here since we already used a denser grid in our scf calculation in the previous step.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;For Band structure:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;We cannot perform &lt;code&gt;calculation='bands'&lt;/code&gt; which is also basically an &lt;code&gt;nscf&lt;/code&gt; type calculation. But there are a few workarounds. See this SE question - &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1176/calculating-hse06-band-structures-on-quantum-espresso&quot;&gt;Calculating HSE06 band structures on Quantum ESPRESSO&lt;/a&gt;. It has accepted answer. Also, in this blog - &lt;a href=&quot;https://christoph-wolf.at/2018/10/10/band-structure-calculations-in-qe-using-hybrid-functionals/&quot; rel=&quot;noreferrer&quot;&gt;Band structure calculations in QE using hybrid functionals&lt;/a&gt; - the procedure is described with examples.&lt;/p&gt;&#xA;&lt;p&gt;In order to follow some background on why such calculations cannot be done and all the possible workarounds, you might want to check the following QE user forum threads: &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2013-April/026884.html&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://www.mail-archive.com/users@lists.quantum-espresso.org/msg33817.html&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;, &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/developers/2018-May/001911.html&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-05-31T21:10:51.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11011" PostTypeId="1" CreationDate="2023-06-01T03:27:38.220" Score="8" ViewCount="395" Body="&lt;p&gt;I am trying to evaluate 1- and 2-electron integrals using PySCF trough this code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Hij = mol.intor('int1e_kin') + mol.intor('int1e_nuc')&#xA;Vijkl = mol.intor('int2e') &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where I previously defined &lt;code&gt;mol&lt;/code&gt; in a particular basis.&lt;/p&gt;&#xA;&lt;p&gt;I am new in this software and I am reading the basic tutorials that offers the project's site &lt;a href=&quot;https://pyscf.org/user/gto.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, but so far I can't find if the elements Vijkl of the 2-electron integrals are define in the chemist's notation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{ijkl} =&#xA;(ij|kl) =&#xA;\int \frac{\phi^*_i(\mathbf{r}_1)\phi_j(\mathbf{r}_1)\,\phi^*_k(\mathbf{r}_2)\phi_l(\mathbf{r}_2)}{|\mathbf{r}_1 - \mathbf{r}_2|}\,d\mathbf{r}_1d\mathbf{r}_2,&#xA;$$&lt;/span&gt;&#xA;or physicist's notation, which is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V_{ijkl} =&#xA;\langle ij|kl \rangle =&#xA;\int \frac{\phi^*_i(\mathbf{r}_1)\phi_j^*(\mathbf{r}_2)\,\phi_k(\mathbf{r}_1)\phi_l(\mathbf{r}_2)}{|\mathbf{r}_1 - \mathbf{r}_2|}\,d\mathbf{r}_1d\mathbf{r}_2.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am assuming that the program uses chemist's notation. Am I right? And, if so, is it a way to easily convert the array into the other convention? Thank you all in advanced.&lt;/p&gt;&#xA;" OwnerUserId="7329" LastEditorUserId="5" LastEditDate="2023-06-01T08:10:44.963" LastActivityDate="2023-06-01T15:11:21.347" Title="Does PySCF use chemist's or physicist's notation for 1- and 2-electron integrals?" Tags="|computational-chemistry|pyscf|integrals|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11012" PostTypeId="1" AcceptedAnswerId="11017" CreationDate="2023-06-01T06:07:33.120" Score="3" ViewCount="251" Body="&lt;p&gt;I am trying to calculate the Fermi level of a DNA-graphene system. I was able to get the calculations for graphene and DNA strand to converge separately. However, when I try to calculate the same for DNA-graphene system, the SCC cycles do not converge even after multiple restarts. Any information on why is this happening would be much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;The input file can be found &lt;a href=&quot;https://gist.github.com/HemanthHaridas/3a667354d5f5aa4bed4118bce2cc370d&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Further context:&#xA;The coordinates are obtained from clustering of a Molecular Dynamics trajectory, and the graphene segment and DNA strand is cut out from the original full sheet and 20-nucleotide long single-strand DNA from the MD trajectory. Therefore, i am not allowed to perform an extra geometry optimization to relax the structure.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-06-01T07:07:45.890" LastActivityDate="2023-06-01T17:09:41.007" Title="Convergence issues in DFTB+ calculations?" Tags="|numerical-convergence|graphene|biomaterials|dftb-plus|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11013" PostTypeId="2" ParentId="11011" CreationDate="2023-06-01T08:19:56.500" Score="6" Body="&lt;p&gt;You are right that pyscf uses chemist's notation. A quick google search with the keywords &lt;code&gt;pyscf&lt;/code&gt; &lt;code&gt;chemist notation&lt;/code&gt; and &lt;code&gt;electron integrals&lt;/code&gt; returned these two hits for &lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.fci.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;FCI&lt;/a&gt; and &lt;a href=&quot;https://pyscf.org/pyscf_api_docs/pyscf.cc.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CC&lt;/a&gt;. Reading through the documentation, it is mentioned that the integrals are treated in chemist's notation.&lt;/p&gt;&#xA;&lt;p&gt;To address the point that Prof. Dattani made, if you instead search for physicist's notation, you will find that as an argument for this function &lt;code&gt;pyscf.cc.gintermediates.get_t3p2_imds_slow&lt;/code&gt; in the page for CC. I also found the mention of physicist's notation in this &lt;a href=&quot;https://pyscf.org/_modules/pyscf/pbc/cc/kccsd_t_rhf.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;page&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-06-01T15:11:21.347" LastActivityDate="2023-06-01T15:11:21.347" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11014" PostTypeId="1" AcceptedAnswerId="11016" CreationDate="2023-06-01T14:34:22.417" Score="4" ViewCount="203" Body="&lt;p&gt;I want to compute the kinetic energy of the molecular orbitals computed by Gaussian 09, the variable U in this &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/104/8/2956/181121/New-model-for-electron-impact-ionization-cross&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. Can it be computed from the orbital energy using a formula or does it need to be computed as part of the computation? How to do that in Gaussian 09?&lt;/p&gt;&#xA;" OwnerUserId="4496" LastActivityDate="2023-06-01T17:03:04.867" Title="Computing the kinetic energy of a molecular orbital" Tags="|molecular-modeling|ab-initio-calculations|gaussian|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11016" PostTypeId="2" ParentId="11014" CreationDate="2023-06-01T17:03:04.867" Score="3" Body="&lt;p&gt;Looking up the above paper,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The value of the kinetic energy U for each orbital in the&#xA;initial state (usually the ground state) of the target is a theoretical quantity evaluated in any atomic or molecular wave&#xA;function code that calculates the total energy.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Given the LCAO expansion &lt;span class=&quot;math-container&quot;&gt;$\psi_{i} ({\bf r}) = C_{\alpha i} \chi_\alpha({\bf r})$&lt;/span&gt;, what you therefore need to calculate is &lt;span class=&quot;math-container&quot;&gt;$U_i = \text{Tr } {\bf C}_i^\text{T} {\bf T} \bf{C}_i$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;${\bf T}$&lt;/span&gt; is the kinetic energy matrix with elements &lt;span class=&quot;math-container&quot;&gt;$T_{\alpha \beta} = \langle \chi_\alpha | -\frac 1 2 \nabla^2 | \chi_\beta \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As far as I know, Gaussian does not compute these elements individually, only their sum, which is the total kinetic energy. To compute these variables, you need access to the kinetic energy and orbital coefficients matrices, and I am not sure how easy it is to access these, especially if you don't have access to the program's sources.&lt;/p&gt;&#xA;&lt;p&gt;However, as I answered &lt;a href=&quot;https://github.com/pyscf/pyscf/issues/1753#issuecomment-1570250703&quot; rel=&quot;nofollow noreferrer&quot;&gt;elsewhere just the day before&lt;/a&gt;, these quantities are easily accessible in the open-source Python program PySCF.&lt;/p&gt;&#xA;&lt;p&gt;For example, with the code given below, I get the following orbital kinetic energies for N2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Orbital 1 kinetic energy 601.73 eV&#xA;Orbital 2 kinetic energy 602.64 eV&#xA;Orbital 3 kinetic energy 70.41 eV&#xA;Orbital 4 kinetic energy 63.42 eV&#xA;Orbital 5 kinetic energy 54.89 eV&#xA;Orbital 6 kinetic energy 44.08 eV&#xA;Orbital 7 kinetic energy 44.08 eV&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The last five values can be compared to 71.13 eV, 63.18 eV, 54.91 eV, and 44.30 eV given in the above paper; I do not know what bond length they used for the molecule.&lt;/p&gt;&#xA;&lt;p&gt;The code to run the calculation is here&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf&#xA;&#xA;mol = pyscf.M(&#xA;    atom = 'N 0 0 0; N 0 0 1.098',&#xA;    basis = '6-311G',&#xA;    symmetry = True,&#xA;)&#xA;&#xA;mf = mol.HF()&#xA;mf.kernel()&#xA;&#xA;occs = mf.mo_occ&#xA;C = mf.mo_coeff&#xA;T = mol.intor_symmetric('int1e_kin')&#xA;for icol, occ in enumerate(occs):&#xA;    if occ&amp;gt;0.0:&#xA;        Ekin = C[:,icol].T @ T @ C[:,icol]&#xA;        print('Orbital {} kinetic energy {:.2f} eV'.format(icol+1,Ekin*27.2114))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-01T17:03:04.867" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11017" PostTypeId="2" ParentId="11012" CreationDate="2023-06-01T17:09:41.007" Score="2" Body="&lt;p&gt;I had posted the same question on the dftb+ &lt;a href=&quot;https://mailman.zfn.uni-bremen.de/pipermail/dftb-plus-user/2023/004130.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;forum&lt;/a&gt; and Prof. Aradi responded to the question with the following answer.&lt;/p&gt;&#xA;&lt;p&gt;A common strategy is for large metallic systems to start with&#xA;a very high electronic temperature (e.g. 100000 K), converge it at that&#xA;temperature, then start a new calculation with lower electronic&#xA;temperature but using the converged charges of the previous calc as&#xA;initial guess (via ReadInitialCharges = Yes).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Additional comments:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;You should not use the 3rd order correction with the mio-set. If you&#xA;wish to have 3rd order correction, use the 3ob set instead.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you use 3rd order, you should use ThirdOrderFull (and not&#xA;ThirdOrder), as suggested in the manual.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Your cell is quite large, so I don't think you need any k-points apart&#xA;of Gamma. (Which would make the calculation significantly faster).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-06-01T17:09:41.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11018" PostTypeId="1" AcceptedAnswerId="11019" CreationDate="2023-06-01T17:31:35.610" Score="6" ViewCount="471" Body="&lt;p&gt;I ran a molecular dynamics simulation using forcite dynamics for polymers on graphene and a drug. The dynamics summary shows the total energy, potential energy,kinetic energy, total enthalpy, temperature, pressure, volume and density. The dynamics summary also shows the initial and final values along with the average and standard deviation.&lt;/p&gt;&#xA;&lt;p&gt;For forcite dynamics and energy parameters I used ensemble (NVT), temp (298K), thermostat (Berendson), forcefield (compass), electrostatic and vanderwaals (group based), time (1000ps). I left everything else as default.&lt;/p&gt;&#xA;&lt;p&gt;My prof mentioned that the drug should be loaded and released.&lt;/p&gt;&#xA;&lt;p&gt;I used the same polymer and drug for each simulation but changed the concentration of the drug. I also used different ratios of the block copolymer. The polymers were placed on the graphene in the box.&lt;/p&gt;&#xA;&lt;p&gt;I packed the box with water and placed the drug in the box manually.The drug wasn't released at the end of the simulation.&lt;/p&gt;&#xA;&lt;p&gt;I'm confused about what the energies of the dynamics summary is supposed to tell me.&lt;/p&gt;&#xA;" OwnerUserId="7336" LastEditorUserId="5" LastEditDate="2023-06-07T14:53:56.463" LastActivityDate="2023-06-07T14:53:56.463" Title="I was wondering how I should interpret the results of my molecular dynamics simulation" Tags="|molecular-dynamics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11019" PostTypeId="2" ParentId="11018" CreationDate="2023-06-01T17:58:19.273" Score="7" Body="&lt;p&gt;I couldn't completely understand your question, but I will mention some general back-of-the-napkin criteria to be sure that the MD simulation is doing what you &lt;em&gt;think&lt;/em&gt; it is doing. These criteria are necessary but not sufficient.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Visualize the initial, intermediate, and final structures to make sure you grabbed the correct structure and that the simulation isn't doing anything &lt;em&gt;weird&lt;/em&gt; or unwanted.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Make sure that after &lt;em&gt;sufficient&lt;/em&gt; simulation time the energy profile reaches a plateau, i.e., the energy oscillates &lt;em&gt;very little&lt;/em&gt; around some average value. The specification of &amp;quot;sufficient&amp;quot; and &amp;quot;very little&amp;quot; is highly dependent on the context. &lt;em&gt;Usually&lt;/em&gt;, if the energy oscillations are too large, you &lt;em&gt;may&lt;/em&gt; need to decrease the time step.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Also make sure that the temperature and pressure reach a steady state. Temperature oscillations tend to be very little after sufficient simulation time (e.g., in the range of &lt;span class=&quot;math-container&quot;&gt;$\pm 10$&lt;/span&gt; K for a target temperature of 300 K), whereas pressure oscillations tend to be rather large (e.g., in the range of &lt;span class=&quot;math-container&quot;&gt;$\pm 2$&lt;/span&gt; kbar for a target pressure of 0 bar). &lt;em&gt;Usually&lt;/em&gt;, if the temperature or pressure oscillations are larger than those ranges, you &lt;em&gt;may&lt;/em&gt; need to increase the simulation box size.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Try different time steps, different simulation box sizes and different thermostat/barostat damping parameters to see if these affect your results.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Check the units!&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2023-06-07T12:50:25.957" LastActivityDate="2023-06-07T12:50:25.957" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11021" PostTypeId="2" ParentId="10985" CreationDate="2023-06-02T16:12:46.253" Score="6" Body="&lt;p&gt;Apologies I do not have enough reputation points to post this as a comment. You might have already considered other electronic structure methods, but I would like to suggest consider using density matrix renormalisation group (DMRG) based methods for the calculations. DMRG is highly suitable for modelling conjugated polymers. For example, &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/128/14/144117/847909/Orbital-optimization-in-the-density-matrix&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; is an example of DMRG-CASSCF calculations on linear polyenes, and &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/127/13/134309/567089/The-radical-character-of-the-acenes-A-density&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; is an example of calculations on acenes.&lt;/p&gt;&#xA;&lt;p&gt;DMRG methods are supported by several open source quantum chemistry packages, and I found &lt;a href=&quot;https://psicode.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;psi4&lt;/a&gt;, which utilises &lt;a href=&quot;https://github.com/SebWouters/CheMPS2&quot; rel=&quot;nofollow noreferrer&quot;&gt;CheMPS2&lt;/a&gt; particularly easy to use.&lt;/p&gt;&#xA;&lt;p&gt;Edit :&lt;/p&gt;&#xA;&lt;p&gt;As pointed out by @wzkchem5, DMRG does not take into account dynamical correlations. For NEVPT2/DMRG calculations on polyene systems, please see &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.9b04027&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.0c01678&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7045" LastEditorUserId="7045" LastEditDate="2023-06-03T18:13:44.290" LastActivityDate="2023-06-03T18:13:44.290" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11022" PostTypeId="1" CreationDate="2023-06-02T21:02:03.740" Score="2" ViewCount="30" Body="&lt;p&gt;For example, if I am investigating of the elastic properties of a crystal by doing a lot of computations of crystals applied with small strain.&#xA;Also, is it a good idea to read charge and orbitals when doing step-by-step structural relaxation?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-06-02T21:02:03.740" Title="Is it a good idea to always read charge and orbitals if I am working on similar systems?" Tags="|vasp|computational-chemistry|crystallography|elasticity|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11023" PostTypeId="1" CreationDate="2023-06-02T22:11:58.360" Score="2" ViewCount="107" Body="&lt;p&gt;I am curious whether or not there is a connection between the group theoretical assignment of phonon modes and LO-TO splitting. For example, is it true that the frequency of a gerade mode will depend on the direction of approach to &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; in reciprocal space? Conversely, is the frequency of an ungerade mode independent of the direction of approach?&lt;/p&gt;&#xA;&lt;p&gt;Forgive my lack of group theory understanding if this is a silly question.&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&lt;/p&gt;&#xA;&lt;p&gt;CW279&lt;/p&gt;&#xA;" OwnerUserId="5408" LastEditorUserId="5408" LastEditDate="2023-06-04T03:30:58.987" LastActivityDate="2023-06-04T03:30:58.987" Title="LO-TO Splitting and Group Theory" Tags="|symmetry|phonons|phonon-dispersion|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11024" PostTypeId="1" AcceptedAnswerId="11025" CreationDate="2023-06-02T23:56:09.660" Score="4" ViewCount="342" Body="&lt;p&gt;Suppose, I want to develop a novel force field for proteins.&lt;/p&gt;&#xA;&lt;p&gt;What is the empirical procedure I should follow to do that?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-06-03T01:14:33.173" Title="What is the procedure to develop a new force field for molecular simulation?" Tags="|proteins|forcefields|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11025" PostTypeId="2" ParentId="11024" CreationDate="2023-06-03T01:14:33.173" Score="9" Body="&lt;p&gt;The most useful answer to &amp;quot;how do I develop a novel force field for proteins&amp;quot; is &amp;quot;don't&amp;quot;. (Or collaborate with a group which does.)&lt;/p&gt;&#xA;&lt;p&gt;Developing a protein force field is exceptionally difficult because protein structure emerges from the interplay of hydrophobic-hydrophilic competition and backbone conformational flexibility. These are collective phenomena which mean that small changes in coefficients result in large changes in observed behaviour, making optimisation difficult.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, very few elements are involved, so the protein FF designer must choose different types for (say) carbons in different chemical environments; too many types will lead to overfitting, while too few types will not capture the chemical complexity involved and lead to wrong answers.&lt;/p&gt;&#xA;&lt;p&gt;The &amp;quot;how&amp;quot; of it is relatively straightforward: you establish references for how proteins should behave, run MD simulations to see how your MD proteins actually behave, and then iteratively improve your parameters until your MD proteins match your reference criteria. These references can be either &amp;quot;top-down&amp;quot; -- that is, based on experimentally-determined protein behaviour, such as NMR (and increasingly cryo-EM) protein structures and folding/unfolding rates -- or &amp;quot;bottom-up&amp;quot; -- from quantum chemistry calculations. But in either case we are talking massive reference datasets (such as a significant fraction of the PDB).&lt;/p&gt;&#xA;&lt;p&gt;Thus, in practice, fitting a force field successfully requires expertise in: molecular dynamics simulations, the reference domain (so that, for example, dubious protein structures are less heavily weighted), and general large-scale data analytics (for example, it is easier to crystallize ordered proteins than disordered proteins, so most force fields fifteen years or older are biased towards ordered protein structures even for intrinsically-disordered proteins).&lt;/p&gt;&#xA;&lt;p&gt;But don't take my word for it. &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jctc.6b00567&quot; rel=&quot;noreferrer&quot;&gt;This paper&lt;/a&gt; describes the parametrisation of the AMBER ff15ipq force field. Pay attention to just how much work it takes -- and the excellent supplementary information is very frank about the process required, including plenty of dead ends and laborious simulations.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-03T01:14:33.173" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11026" PostTypeId="1" CreationDate="2023-06-03T10:32:37.887" Score="2" ViewCount="251" Body="&lt;p&gt;Suppose, I am running a simulation of protein folding.&lt;/p&gt;&#xA;&lt;p&gt;What are some techniques, methods, or intuitions that help me to understand whether a simulation is running properly, i.e., it is producing the correct output or trajectory?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-06-03T11:11:48.020" LastActivityDate="2023-06-04T07:49:00.323" Title="What are some ways to check if a molecular simulation is running properly?" Tags="|atomistic-simulation|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11027" PostTypeId="1" AcceptedAnswerId="11030" CreationDate="2023-06-03T11:16:15.167" Score="2" ViewCount="172" Body="&lt;p&gt;Suppose, I am running a Monte Carlo simulation of protein folding using harmonic potential, function.&lt;/p&gt;&#xA;&lt;p&gt;The inner loop of Monte Carlo has 100 iterations, and the outer loop has 1000 iterations.&lt;/p&gt;&#xA;&lt;p&gt;What are some symptoms that could tell me that my simulation is not running properly?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-06-03T11:34:56.747" LastActivityDate="2023-06-04T02:29:55.150" Title="What are some symptoms that could tell me that my simulation is not running properly?" Tags="|atomistic-simulation|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11028" PostTypeId="2" ParentId="11026" CreationDate="2023-06-03T17:50:35.583" Score="6" Body="&lt;p&gt;It's a very broad question and there isn't really a clean answer that will apply for all cases but I'll just provide some general advice. I would start by re-creating a known result. Follow a tutorial for a well-studied system and make sure you can reproduce each stage of the simulation process. The most common problems with MD simulations will either cause the simulation software to crash or spit out warnings. Do not ignore warnings in the output unless you understand what they mean and are confident they are irrelevant to your case.&lt;/p&gt;&#xA;&lt;p&gt;Visualize your geometry and trajectory! Many problems in simulations can occur when setting up your system geometry. It's very easy to make mistakes here. Visualize each stage in detail with a geometry visualization software of your choice to make sure the geometry makes sense. Don't proceed until you're satisfied that it does.&lt;/p&gt;&#xA;&lt;p&gt;Generate radial distribution functions. These can help you catch atoms accidentally placed too close to each other. Look for any density in the RDF closer than your shortest expected bonds. Unexpected peaks in the RDFs should also be investigated.&lt;/p&gt;&#xA;&lt;p&gt;Plot (at least) the system potential energy, density, pressure, and temperature for your simulation trajectory. Potential energy should be negative (unless the pressure is extreme), density should remain reasonable, and the temperature and pressure should remain near your set point (assuming an NPT simulation).&lt;/p&gt;&#xA;&lt;p&gt;If simulating a protein, generate a Ramachandran plot of a series of structures along your trajectory. Dramatic changes in this distribution indicate large structural changes in your protein which may or may not be intended.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2023-06-04T07:49:00.323" LastActivityDate="2023-06-04T07:49:00.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11030" PostTypeId="2" ParentId="11027" CreationDate="2023-06-04T02:29:55.150" Score="5" Body="&lt;p&gt;There are generic self-consistency checks (SCCs) that check if a simulation set has converged. The most basic of these is to use block analysis to examine the convergence of standard error in observables (&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2865156/&quot; rel=&quot;noreferrer&quot;&gt;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2865156/&lt;/a&gt;) and a very recent example of detailed application of SCCs can be found here: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.2c01140&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.jctc.2c01140&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Another simple check is to perform two Monte Carlo runs at slightly different temperatures and compare the resulting probability distributions of observables. These should be Boltzmann distributions and hence be related by inverse exponential temperature.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-04T02:29:55.150" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11032" PostTypeId="2" ParentId="10809" CreationDate="2023-06-04T05:16:55.023" Score="2" Body="&lt;p&gt;I think you should take a rectangular unit cell instead of the hexagonal unit cell depending on this article (The response of mechanical and electronic properties of graphene to the elastic strain&#xA;M. Topsakal, S. Cahangirov, and S. Ciraci)&lt;br /&gt;&#xA;( &lt;a href=&quot;https://doi.org/10.1063/1.3353968&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.3353968&lt;/a&gt; )..... can I get your email please, I have a question&lt;/p&gt;&#xA;" OwnerUserId="7312" LastEditorUserId="7312" LastEditDate="2023-06-06T17:22:15.847" LastActivityDate="2023-06-06T17:22:15.847" CommentCount="6" CommunityOwnedDate="2023-06-27T23:04:47.173" ContentLicense="CC BY-SA 4.0" />
  <row Id="11034" PostTypeId="1" AcceptedAnswerId="11058" CreationDate="2023-06-04T10:18:56.770" Score="3" ViewCount="72" Body="&lt;p&gt;When comparing the energy of the LDA0 and SVWN (Slater exchange and VWN(1980) correlation), I get different results.&lt;/p&gt;&#xA;&lt;p&gt;So what is the LDA0 functional in Psi4? I can't really find literature about it.&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-06-07T19:19:37.347" LastActivityDate="2023-06-07T19:19:37.347" Title="Psi4 functionnals: LDA0" Tags="|density-functional-theory|exchange-correlation|psi4|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11035" PostTypeId="1" CreationDate="2023-06-04T13:50:08.650" Score="4" ViewCount="154" Body="&lt;p&gt;I am having the following error while converting the CIF file of a hypothetical crystal into an input file for Quantum espresso.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/usr/local/bin/cif2cell&amp;quot;, line 1574, in &amp;lt;module&amp;gt;&#xA;    docstring = StandardDocstring()&#xA;  File &amp;quot;/usr/local/bin/cif2cell&amp;quot;, line 1021, in StandardDocstring&#xA;    tmpstring2 += &amp;quot;. Reference number : &amp;quot;+ref.databasecode&#xA;TypeError: must be str, not NoneType&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the CIF file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# CIF file created by FINDSYM, version 7.1.3&#xA;&#xA;data_findsym-output&#xA;_audit_creation_method FINDSYM&#xA;&#xA;_cell_length_a    2.7061000000&#xA;_cell_length_b    4.4190100000&#xA;_cell_length_c    4.6871000000&#xA;_cell_angle_alpha 90.0000000000&#xA;_cell_angle_beta  90.0000000000&#xA;_cell_angle_gamma 90.0000000000&#xA;_cell_volume      56.0496680665&#xA;&#xA;_symmetry_space_group_name_H-M &amp;quot;P m m n :2&amp;quot;&#xA;_symmetry_Int_Tables_number 59&#xA;_space_group.reference_setting '059:-P 2ab 2a'&#xA;_space_group.transform_Pp_abc a,b,c;0,0,0&#xA;&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 x,y,z&#xA;2 x+1/2,-y,-z&#xA;3 -x,y+1/2,-z&#xA;4 -x+1/2,-y+1/2,z&#xA;5 -x,-y,-z&#xA;6 -x+1/2,y,z&#xA;7 x,-y+1/2,z&#xA;8 x+1/2,y+1/2,-z&#xA;&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_label&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_occupancy&#xA;_atom_site_fract_symmform&#xA;Fe1 Fe   2 a 0.25000 0.25000 -0.08333 1.00000 0,0,Dz &#xA;Al1 Al   2 b 0.25000 0.75000 0.58333  1.00000 0,0,Dz &#xA;&#xA;# end of cif&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have tried the answer given on this platform regarding this problem, but it did not work.&lt;/p&gt;&#xA;" OwnerUserId="7344" LastEditorUserId="6687" LastEditDate="2023-06-08T13:46:33.650" LastActivityDate="2023-06-15T07:49:51.750" Title="cif2cell command error" Tags="|quantum-espresso|cif|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11036" PostTypeId="1" CreationDate="2023-06-04T18:37:24.183" Score="2" ViewCount="101" Body="&lt;p&gt;I am use Quantum espresso&#xA;I calculated scf and Bands but i can't caluleted Band_pp for ploting Band Structure.&#xA;[![enter image description here&lt;a href=&quot;https://i.stack.imgur.com/Ljznt.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ljznt.jpg&quot; alt=&quot;][1][1]&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ltWRw.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ltWRw.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/W8Lxe.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/W8Lxe.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7347" LastActivityDate="2023-06-04T18:37:24.183" Title="Gamma_only case not implemented?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="3" ClosedDate="2024-01-11T13:48:42.923" ContentLicense="CC BY-SA 4.0" />
  <row Id="11037" PostTypeId="1" CreationDate="2023-06-04T21:11:58.063" Score="9" ViewCount="413" Body="&lt;p&gt;For example, should a computation be considered to converge when the differences in energy per atom  are smaller than a certain value?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2024-02-13T20:16:18.763" Title="What should be the criteria of convergence over ENCUT?" Tags="|density-functional-theory|vasp|computational-chemistry|numerical-convergence|convergence-test|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11038" PostTypeId="1" CreationDate="2023-06-04T22:26:27.340" Score="3" ViewCount="30" Body="&lt;p&gt;I am doing the computation of a perovskite system of 20 atoms in a supercell.&#xA;I know that options like NPAR and KPAR, and the numbers of cores used for computations can greatly affect the efficiency, but are there some general principles for the optimal setting? (e.g. for what kinds of systems, how will KPAR affect the computational efficiency and how do I optimize all of them)&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-06-04T22:26:27.340" Title="What are the general principles of setting parellelization options in VASP?" Tags="|vasp|computational-chemistry|high-performance-computing|k-points|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11039" PostTypeId="2" ParentId="11037" CreationDate="2023-06-04T22:58:08.897" Score="7" Body="&lt;h3&gt;Preamble&lt;/h3&gt;&#xA;&lt;p&gt;From the VASP wiki, &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ENCUT&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ENCUT&lt;/code&gt;&lt;/a&gt; &lt;em&gt;specifies the cutoff energy for the plane-wave-basis set in eV&lt;/em&gt;. This is the same as &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm310&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ecutwfc&lt;/code&gt;&lt;/a&gt; of Quantum ESPRESSO (which has a unit of Ry). In principle (according to the variational principle), one would obtain the lowest total energy when the energy cutoff is infinite. Since this is impossible in practice, we use as much value as we can afford for &lt;code&gt;ENCUT&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Answer to the question&lt;/h3&gt;&#xA;&lt;p&gt;I haven't seen any specific recommended value for the convergence threshold on the total energy with respect to the kinetic energy cutoff. However, I have generally seen people doing it at &lt;span class=&quot;math-container&quot;&gt;$0.1 \;\mathrm{mRy}\; (\approx1.36 \;\mathrm{meV})$&lt;/span&gt;. The rationale behind this is the following.&lt;/p&gt;&#xA;&lt;p&gt;At room temperature &lt;span class=&quot;math-container&quot;&gt;$(\mathrm{T}=300 \mathrm{K})$&lt;/span&gt;, the value of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{k_BT} \approx 25 \; \mathrm{meV}$&lt;/span&gt;. So, &lt;span class=&quot;math-container&quot;&gt;$1.36 \;\mathrm{meV}$&lt;/span&gt; is much smaller than that. Let's say you used &lt;code&gt;ENCUT&lt;/code&gt; as &lt;span class=&quot;math-container&quot;&gt;$400 \;\mathrm{eV} $&lt;/span&gt; and found the energy to be &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt;. And for &lt;code&gt;ENCUT&lt;/code&gt; = &lt;span class=&quot;math-container&quot;&gt;$600 \;\mathrm{eV} $&lt;/span&gt;, you found the energy to be &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt;. Now, if &lt;span class=&quot;math-container&quot;&gt;$\Delta E = (E_2-E_1)/200 &amp;lt; 1.36 \;\mathrm{meV}$&lt;/span&gt;, you can safely use &lt;span class=&quot;math-container&quot;&gt;$600 \;\mathrm{eV} $&lt;/span&gt; as your &lt;code&gt;ENCUT&lt;/code&gt;. In other words, you have to divide the total energy differences by the difference in the kinetic energy cutoff and this should be less than your convergence criterion.&lt;/p&gt;&#xA;&lt;p&gt;A little caution if you want to proceed to the vibrational properties: I am not sure if this is the case in VASP too, but in Quantum ESPRESSO one needs to use a larger &lt;code&gt;ecutwfc&lt;/code&gt; in lattice vibrational calculation than the one used in the SCF calculation. This is because the phonon frequencies in Quantum ESPRESSO have the unit of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{cm}^{-1}$&lt;/span&gt; which roughly corresponds to &lt;span class=&quot;math-container&quot;&gt;$0.12 \;\mathrm{meV}$&lt;/span&gt;. So it requires a larger cutoff (to ensure a smaller &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;).&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2024-02-13T20:16:18.763" LastActivityDate="2024-02-13T20:16:18.763" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11040" PostTypeId="1" AcceptedAnswerId="11107" CreationDate="2023-06-05T05:38:13.963" Score="3" ViewCount="358" Body="&lt;p&gt;I am a Ph.D. student. I am using Quantum Espresso to calculate the mechanical properties ( in-plane stiffness ) (undergo uniaxial strain). I calculated the strain energy of each applied strain. The problem is how can I employ the data to get in-plane stiffness. I fitted the curve into a second-order polynomial by using Excel as shown in the figure. What is the next step after this figure? how can I calculate the in-plane stiffness?&lt;/p&gt;&#xA;&lt;p&gt;I hope you can help me. best wishes.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ouc3o.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ouc3o.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7312" LastActivityDate="2023-06-12T18:02:46.610" Title="Elastic properties of graphene by using DFT (Quantum espresso)" Tags="|elasticity|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11041" PostTypeId="2" ParentId="11001" CreationDate="2023-06-05T07:12:57.087" Score="5" Body="&#xA;&lt;p&gt;I think that you have probably mistakenly taken Quantum ESPRESSO (QE) as a geometry builder tool. You &lt;em&gt;CANNOT&lt;/em&gt; construct thin layers or slab surfaces from bulk using QE. QE is a tool to calculate certain properties of different materials. But it cannot build the material geometry itself. You need other codes to build the geometry (or you can try to manually enter it if it's a simple one).&lt;/p&gt;&#xA;&lt;p&gt;As suggested in the comment, in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9322/6055&quot;&gt;this&lt;/a&gt; answer, &lt;a href=&quot;https://www.youtube.com/watch?v=6xx29-CQJiA&amp;amp;ab_channel=NickelandCopper&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; tutorial link has been provided which shows how to construct a thin layer geometry using &lt;a href=&quot;https://jp-minerals.org/vesta/en/&quot; rel=&quot;nofollow noreferrer&quot;&gt;VESTA&lt;/a&gt;. There are also many other tools. For example, using &lt;a href=&quot;https://burai.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;BURAI&lt;/a&gt;, you can model any slab surface if you have the QE input file for the bulk (alternatively, you can use a CIF file). It directly generates a QE input file. It can even perform certain (scf, nscf, dos, band structure, relax, vc-relax) QE calculations (in fact it is GUI for QE).&lt;/p&gt;&#xA;&lt;p&gt;Follow these steps, and if you are stuck at some point, please ask questions on a separate thread specifying what type of problem you are facing such as about the installation problem of any particular program, or suggested workflow for certain goals, etc. Otherwise, the question becomes too vague to answer.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="5" LastEditDate="2023-09-03T16:57:22.507" LastActivityDate="2023-09-03T16:57:22.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11042" PostTypeId="1" AcceptedAnswerId="11046" CreationDate="2023-06-05T08:24:56.413" Score="4" ViewCount="558" Body="&lt;p&gt;How can I build (visualize) a rectangular supercell of graphene as shown in the figure? Can I use VESTA to do that and how?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/w1X8Y.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w1X8Y.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7312" LastEditorUserId="6687" LastEditDate="2023-06-06T09:46:45.227" LastActivityDate="2023-06-06T09:46:45.227" Title="How can visualize a rectangular super cell of Graphene by VESTA" Tags="|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11043" PostTypeId="1" CreationDate="2023-06-05T09:08:18.857" Score="2" ViewCount="214" Body="&lt;p&gt;I have more than 10000 files related to calculations done using Vienna Ab-initio Simulation Package. These files are stored in my University's server. I want to take these files in my personal drive before I graduate. I will be compressing these files before taking them in to my personal drive to save storage space.&lt;/p&gt;&#xA;&lt;p&gt;Which files should I take so that I can revisit them in future for further analysis without re-doing those calculations?&lt;/p&gt;&#xA;" OwnerUserId="160" LastEditorUserId="5" LastEditDate="2023-06-05T13:07:48.537" LastActivityDate="2023-06-14T05:11:17.207" Title="What files are important while taking backup of a VASP calculation?" Tags="|density-functional-theory|vasp|ab-initio-calculations|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11044" PostTypeId="1" CreationDate="2023-06-05T10:25:58.943" Score="1" ViewCount="38" Body="&lt;p&gt;Most researchers use rectangular supercells instead of hexagonal supercells of graphene to calculate the mechanical properties. All of the articles are working on mechanical properties, they considered the paper (&lt;a href=&quot;https://doi.org/10.1063/1.3353968&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.3353968&lt;/a&gt; ) as a reference for them.&lt;/p&gt;&#xA;" OwnerUserId="7312" LastActivityDate="2023-06-05T10:25:58.943" Title="why should we use rectangular supercell of graphene instead of hexagonal supercell to calculate the elastic constant (in-plane stiffness)" Tags="|elasticity|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-02T01:47:59.513" ContentLicense="CC BY-SA 4.0" />
  <row Id="11045" PostTypeId="1" CreationDate="2023-06-05T11:25:37.410" Score="1" ViewCount="351" Body="&lt;p&gt;I'm working on a &lt;strong&gt;hybrid system (with two different materials)&lt;/strong&gt;. Could you tell me how I can take into consideration the &lt;strong&gt;Van der Waals interaction&lt;/strong&gt; between them?&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2023-06-07T19:05:28.460" LastActivityDate="2023-06-07T19:05:28.460" Title="How I can consider Van der Waals interactions between two materials in Quantum ESPRESSO?" Tags="|quantum-espresso|dispersion-correction|" AnswerCount="0" CommentCount="7" ClosedDate="2023-12-20T03:25:34.377" ContentLicense="CC BY-SA 4.0" />
  <row Id="11046" PostTypeId="2" ParentId="11042" CreationDate="2023-06-05T15:15:04.617" Score="5" Body="&lt;p&gt;Yes, you can do that in VESTA.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;First you need a structure file. I use VASP so here's the POSCAR I used.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;graphene&#xA;   1.00000000000000&#xA;     2.4653795071174938    0.0000000002172037    0.0000000000000000&#xA;    -1.2326903951325390    2.1350817378200184    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   24.0000000000000000&#xA;   C&#xA;     2&#xA;Direct&#xA;  0.0000000000000000  0.0000000000000000  0.5000000000000000&#xA;  0.3333329857695233  0.6666669845004449  0.5000000000000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can just create a &lt;code&gt;POSCAR&lt;/code&gt; file in a directory and drag it into the VESTA window.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;p&gt;The idea is to apply a nondiagonal supercell transformation on the original hexagonal lattice. You can apply lattice transformations by doing&#xA;&amp;quot;Edit&amp;quot; -&amp;gt; &amp;quot;Edit Data&amp;quot; -&amp;gt; &amp;quot;Unit Cell...&amp;quot; on the upper left hand panel, then click &amp;quot;Transform...&amp;quot; in the window that opens.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;We need to figure out the nondiagonal supercell transformation to use. The original hexagonal lattice I started out with had the form&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;L = a \begin{pmatrix}&#xA;1 &amp;amp; -\frac{1}{2} \\&#xA;0 &amp;amp; \frac{\sqrt{3}}{2}&#xA;\end{pmatrix}&#xA;\end{equation}&lt;/span&gt;&#xA;where the lattice vectors are the columns of &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is the lattice parameter. Let the transformation matrix be&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;T = \begin{pmatrix}&#xA;h &amp;amp; k \\&#xA;0 &amp;amp; \ell&#xA;\end{pmatrix}&#xA;\end{equation}&lt;/span&gt;&#xA;The new lattice vectors after the supercell transformation would then be&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;LT = a\begin{pmatrix}&#xA;h &amp;amp; k - \frac{\ell}{2} \\&#xA;0 &amp;amp; \frac{\sqrt{3}\ell}{2}&#xA;\end{pmatrix}&#xA;\end{equation}&lt;/span&gt;&#xA;To make sure the new lattice vectors are orthogonal (i.e. the lattice is rectangular), the only restriction is hence &lt;span class=&quot;math-container&quot;&gt;$2k = \ell$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Pick some explicit values for the transformation matrix. I went with a simple&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;T = \begin{pmatrix}&#xA;2 &amp;amp; 1 \\&#xA;0 &amp;amp; 2&#xA;\end{pmatrix}&#xA;\end{equation}&lt;/span&gt;&#xA;Input that in the &amp;quot;Rotation matrix P&amp;quot; in the window that popped up previously when you clicked &amp;quot;Transform...&amp;quot;. &amp;quot;OK&amp;quot; and then &amp;quot;Apply&amp;quot;. You should now have a rectangular looking cell. You can adjust the values of the supercell matrix to make a bigger supercell.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;To make the plot in the picture, you might want to get rid of the atoms outside the supercell lattice bounds. To do this, click &amp;quot;Edit&amp;quot; -&amp;gt; &amp;quot;Bonds&amp;quot;. Then, click the first entry and select &amp;quot;Do not search atoms beyond the boundary&amp;quot;, and &amp;quot;Apply&amp;quot;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;At the end, you should hopefully be left with something like this. You can then save the structure file in whatever format you desire for computation in relevant software, or export the image if you're creating this for visualization or diagram purposes.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/tL4fk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tL4fk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="6131" LastEditDate="2023-06-05T16:47:52.647" LastActivityDate="2023-06-05T16:47:52.647" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11048" PostTypeId="1" CreationDate="2023-06-05T19:32:23.683" Score="2" ViewCount="52" Body="&lt;p&gt;I'm new to DFT calculations and trying to produce the Equation of State curves (e.g. Pressure vs Volume) of Graphite. I started relaxing the system with ISIF=3 and then gradually scaled up and down the relaxed cell (with ISIF=4) in order to create the different points on the PV curve. However, my PV curve demonstrates abnormal spikes and I couldn't find out the issue. I was able to produce the PV curve for Diamond and it came out smoothly following the same procedure. Any advice is highly appreciated. I'm using PAW_PEB for carbon.&lt;/p&gt;&#xA;&lt;p&gt;My INCAR for initial relaxation looks like this,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM= C_graphite&#xA;PREC=  A&#xA;ENCUT= 400.0&#xA;EDIFF= 1e-6&#xA;IBRION= 2&#xA;ISIF= 3&#xA;NSW= 100&#xA;ISMEAR= 0 ; SIGMA = 0.05&#xA;ISTART=0&#xA;POTIM= 0.5&#xA;LCHARG= .FALSE.&#xA;LWAVE= .FALSE.&#xA;LREAL= .FALSE.&#xA;EDIFFG = -1e-2&#xA;ISYM=0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And POSCAR looks like this for Graphite,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C4&#xA;1.0&#xA;   1.2336456308015413   -2.1367369110836267    0.0000000000000000&#xA;   1.2336456308015413    2.1367369110836267    0.0000000000000000&#xA;   0.0000000000000000    0.0000000000000000    7.8030730000000004&#xA;C&#xA;4&#xA;direct&#xA;   0.0000000000000000    0.0000000000000000    0.2500000000000000 C&#xA;   0.0000000000000000    0.0000000000000000    0.7500000000000000 C&#xA;   0.3333333333333333    0.6666666666666666    0.2500000000000000 C&#xA;   0.6666666666666667    0.3333333333333334    0.7500000000000000 C&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have used automatic k-point mesh as follows,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EA&#xA;0&#xA;Auto&#xA;  32 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My PV curve looks like this and it definitely has an error,&#xA;&lt;a href=&quot;https://i.stack.imgur.com/wGg9c.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wGg9c.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Can you guys please advise me to find out my mistake?&lt;/p&gt;&#xA;&lt;p&gt;Thank you very much.&lt;/p&gt;&#xA;" OwnerUserId="6279" LastActivityDate="2023-06-05T19:32:23.683" Title="Anomaly in Equation of State curves (P vs V) for graphite VASP" Tags="|density-functional-theory|vasp|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11049" PostTypeId="1" CreationDate="2023-06-06T06:32:51.600" Score="3" ViewCount="145" Body="&lt;p&gt;There are various programs for calculating energy states for molecules (ORCA, Gaussian, ...). Is there also software that allows the same simulations with an additional external potential (e.g. magnetic field)?&lt;/p&gt;&#xA;" OwnerUserId="5688" LastEditorUserId="5" LastEditDate="2023-06-06T10:10:48.027" LastActivityDate="2023-06-06T10:10:48.027" Title="Electronic Structure Calculation with External Field" Tags="|density-functional-theory|software-recommendations|electronic-structure|one-topic-per-answer|hartree-fock|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11050" PostTypeId="1" AcceptedAnswerId="11066" CreationDate="2023-06-06T10:24:22.033" Score="3" ViewCount="801" Body="&lt;p&gt;After the calculation of scf I ran a calculation DOS, but it gives an error as follows&#xA;(I want to calculate the DOS with a hybrid potential)&lt;/p&gt;&#xA;&lt;h1&gt;Input file for scf&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;        calculation   = 'scf'&#xA;          prefix      = 'CN'&#xA;         outdir       = './outdir'&#xA;        pseudo_dir    = './pseudo'&#xA;            verbosity = 'high'&#xA;    /&#xA;    &#xA;    &amp;amp;SYSTEM&#xA;              a     = 1.86178e+01&#xA;              c     = 4.50000e+00&#xA;         degauss    = 1.00000e-02&#xA;        ecutrho     = 480&#xA;        ecutwfc     = 40&#xA;        ibrav       = 6&#xA;        nat         = 44&#xA;        ntyp        = 1&#xA;        input_dft   = 'pbe0' ,&#xA;        nqx1 = 1, nqx2 = 1, nqx3 = 1,&#xA;        x_gamma_extrapolation = .true.&#xA;        exxdiv_treatment = 'gygi-baldereschi'&#xA;        occupations = &amp;quot;tetrahedra&amp;quot;&#xA;        smearing    = &amp;quot;gaussian&amp;quot;&#xA;    /&#xA;    &#xA;    &amp;amp;ELECTRONS&#xA;       conv_thr         = 1.00000e-06&#xA;        mixing_beta     = 7.00000e-01&#xA;    /&#xA;    &#xA;    &#xA;    ATOMIC_SPECIES&#xA;    C      12.01070  C.pbe-van_ak.UPF&#xA;    &#xA;    ATOMIC_POSITIONS {angstrom}&#xA;    C      13.617800   9.265100   5.000000&#xA;    C      13.443300  10.479100   7.131500&#xA;    C      11.098900  13.184600   5.000000&#xA;    C       9.922100  13.530200   7.131500&#xA;    C       6.487200  12.521600   5.000000&#xA;    C       5.684000  11.594700   7.131500&#xA;    C       5.174500   8.051100   5.000000&#xA;    C       5.684000   6.935500   7.131500&#xA;    C       8.695700   5.000000   5.000000&#xA;    C       9.922100   5.000000   7.131500&#xA;    C      12.933800   6.935500   5.000000&#xA;    C      13.443300   8.051100   7.131500&#xA;    C      12.933800  11.594700   6.421000&#xA;    C      12.130600  12.521600   8.552500&#xA;    C       8.695700  13.530200   6.421000&#xA;    C       7.518900  13.184600   8.552500&#xA;    C       5.174500  10.479100   6.421000&#xA;    C       5.000000   9.265100   8.552500&#xA;    C       6.487200   6.008600   6.421000&#xA;    C       7.518900   5.345600   8.552500&#xA;    C      11.098900   5.345600   6.421000&#xA;    C      12.130600   6.008600   8.552500&#xA;    C      12.933800  11.594700   5.000000&#xA;    C      12.130600  12.521600   7.131500&#xA;    C       8.695700  13.530200   5.000000&#xA;    C       7.518900  13.184600   7.131500&#xA;    C       5.174500  10.479100   5.000000&#xA;    C       5.000000   9.265100   7.131500&#xA;    C       6.487200   6.008600   5.000000&#xA;    C       7.518900   5.345600   7.131500&#xA;    C      11.098900   5.345600   5.000000&#xA;    C      12.130600   6.008600   7.131500&#xA;    C      13.617800   9.265100   6.421000&#xA;    C      13.443300  10.479100   8.552500&#xA;    C      11.098900  13.184600   6.421000&#xA;    C       9.922100  13.530200   8.552500&#xA;    C       6.487200  12.521600   6.421000&#xA;    C       5.684000  11.594700   8.552500&#xA;    C       5.174500   8.051100   6.421000&#xA;    C       5.684000   6.935500   8.552500&#xA;    C       8.695700   5.000000   6.421000&#xA;    C       9.922100   5.000000   8.552500&#xA;    C      12.933800   6.935500   6.421000&#xA;    C      13.443300   8.051100   8.552500&#xA;    &#xA;&#xA;    &#xA;    K_POINTS automatic&#xA;    1  1  10  0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Input file for DOS&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;dos&#xA;prefix = 'CN'&#xA;outdir = './outdir'&#xA;fildos = 'CNT-DOS.dat'&#xA;DeltaE = 0.01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;output file for DOS&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Program DOS v.6.6 starts on  5Jun2023 at 20:38:19 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI &amp;amp; OpenMP), running on      20 processor cores&#xA;     Number of MPI processes:                20&#xA;     Threads/MPI process:                     1&#xA;&#xA;     MPI processes distributed on     7 nodes&#xA;     R &amp;amp; G space division:  proc/nbgrp/npool/nimage =      20&#xA;     Fft bands division:     nmany     =       1&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine dos (1):&#xA;     reading dos namelist&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;SLURM script&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -J QE&#xA;#SBATCH --ntasks=20&#xA;#SBATCH --ntasks-per-core=1&#xA;#SBATCH --partition=longq&#xA;#SBATCH -o %x-%j.out&#xA;#SBATCH -e %x-%j.err&#xA;&#xA;#load modules&#xA;module load QuantumESPRESSO/6.6-foss-2019b&#xA;export OMP_NUM_THREADS=1&#xA;&#xA;#run&#xA;mpirun -np $SLURM_NTASKS dos.x  DOS.in &amp;gt; DOS.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="6055" LastEditDate="2023-06-08T14:21:42.053" LastActivityDate="2023-06-09T02:32:27.767" Title="Error in routine dos (1): reading dos namelist?" Tags="|quantum-espresso|density-of-states|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11052" PostTypeId="1" CreationDate="2023-06-06T15:48:20.347" Score="2" ViewCount="75" Body="&lt;p&gt;How do I calculate the energy barrier ΔE along the Li migration path in QUANTUM ESPRESSO?&lt;/p&gt;&#xA;" OwnerUserId="7355" LastEditorUserId="6687" LastEditDate="2023-06-07T00:53:01.837" LastActivityDate="2023-06-07T00:53:01.837" Title="How to calculate energy barrier ΔE in Quantum Espresso?" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="2" ClosedDate="2023-06-14T01:03:00.587" ContentLicense="CC BY-SA 4.0" />
  <row Id="11053" PostTypeId="1" CreationDate="2023-06-06T18:30:28.073" Score="3" ViewCount="43" Body="&lt;p&gt;Both Quantum ESPRESSO and AMS (Amsterdam Modeling Suite) can be used to perform simulations of the materials and their properties. What are the differences between AMS and Quantum ESPRESSO? Is it accurate to say that one of them is better than the other? Can one of them be used to simulate systems that the other can not? Any answer is greatly appreciated.Thanks&lt;/p&gt;&#xA;" OwnerUserId="7357" LastActivityDate="2023-06-06T18:30:28.073" Title="Quantum ESPRESSO vs AMS" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|software-recommendations|electronic-transport|" AnswerCount="0" CommentCount="1" ClosedDate="2023-10-01T14:44:30.417" ContentLicense="CC BY-SA 4.0" />
  <row Id="11054" PostTypeId="1" AcceptedAnswerId="11055" CreationDate="2023-06-06T19:17:56.757" Score="5" ViewCount="74" Body="&lt;p&gt;I need to perform a calculation on a BN system with using cc-pVQZ stripped of the &lt;em&gt;f&lt;/em&gt; functions. However, I don't really know how to do this and I have not been able to find a revised one already. I would appreciate help!&lt;br /&gt;&#xA;The basis set was taken from Basis Set Exchange and the format is CFOUR.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance!&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!----------------------------------------------------------------------&#xA;! Basis Set Exchange&#xA;! Version v0.9.1&#xA;! https://www.basissetexchange.org&#xA;!----------------------------------------------------------------------&#xA;!   Basis set: cc-pVQZ&#xA;! Description: cc-pVQZ&#xA;!        Role: orbital&#xA;!     Version: 1  (Data from ccRepo/Grant Hill)&#xA;!----------------------------------------------------------------------&#xA;&#xA;&#xA;&#xA;B:cc-pVQZ&#xA;cc-pVQZ&#xA;&#xA;  5&#xA;    0    1    2    3    4&#xA;    5    4    3    2    1&#xA;   12    6    3    2    1&#xA;&#xA;2.387000D+04 3.575000D+03 8.128000D+02 2.297000D+02 7.469000D+01 &#xA;2.681000D+01 1.032000D+01 4.178000D+00 1.727000D+00 4.704000D-01 &#xA;1.896000D-01 7.394000D-02 &#xA;&#xA;8.800000D-05 0.000000D+00 0.000000D+00 -1.800000D-05 0.000000D+00 &#xA;6.870000D-04 0.000000D+00 0.000000D+00 -1.390000D-04 0.000000D+00 &#xA;3.600000D-03 0.000000D+00 0.000000D+00 -7.250000D-04 0.000000D+00 &#xA;1.494900D-02 0.000000D+00 0.000000D+00 -3.063000D-03 0.000000D+00 &#xA;5.143500D-02 0.000000D+00 0.000000D+00 -1.058100D-02 0.000000D+00 &#xA;1.433020D-01 0.000000D+00 0.000000D+00 -3.136500D-02 0.000000D+00 &#xA;3.009350D-01 0.000000D+00 0.000000D+00 -7.101200D-02 0.000000D+00 &#xA;4.035260D-01 0.000000D+00 0.000000D+00 -1.321030D-01 0.000000D+00 &#xA;2.253400D-01 0.000000D+00 0.000000D+00 -1.230720D-01 0.000000D+00 &#xA;1.540700D-02 1.000000D+00 0.000000D+00 2.618190D-01 0.000000D+00 &#xA;-3.955000D-03 0.000000D+00 1.000000D+00 5.866620D-01 0.000000D+00 &#xA;1.124000D-03 0.000000D+00 0.000000D+00 2.904940D-01 1.000000D+00 &#xA;&#xA;2.226000D+01 5.058000D+00 1.487000D+00 5.071000D-01 1.812000D-01 &#xA;6.463000D-02 &#xA;&#xA;0.000000D+00 5.095000D-03 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 3.320600D-02 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.323140D-01 0.000000D+00 0.000000D+00 &#xA;1.000000D+00 3.318180D-01 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 4.720630D-01 1.000000D+00 0.000000D+00 &#xA;0.000000D+00 2.579790D-01 0.000000D+00 1.000000D+00 &#xA;&#xA;1.110000D+00 4.020000D-01 1.450000D-01 &#xA;&#xA;1.000000D+00 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.000000D+00 0.000000D+00 &#xA;0.000000D+00 0.000000D+00 1.000000D+00 &#xA;&#xA;8.820000D-01 3.110000D-01 &#xA;&#xA;1.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.000000D+00 &#xA;&#xA;6.730000D-01 &#xA;&#xA;1.0000000 &#xA;&#xA;N:cc-pVQZ&#xA;cc-pVQZ&#xA;&#xA;  5&#xA;    0    1    2    3    4&#xA;    5    4    3    2    1&#xA;   12    6    3    2    1&#xA;&#xA;4.584000D+04 6.868000D+03 1.563000D+03 4.424000D+02 1.443000D+02 &#xA;5.218000D+01 2.034000D+01 8.381000D+00 3.529000D+00 1.054000D+00 &#xA;4.118000D-01 1.552000D-01 &#xA;&#xA;9.200000D-05 0.000000D+00 0.000000D+00 -2.000000D-05 0.000000D+00 &#xA;7.170000D-04 0.000000D+00 0.000000D+00 -1.590000D-04 0.000000D+00 &#xA;3.749000D-03 0.000000D+00 0.000000D+00 -8.240000D-04 0.000000D+00 &#xA;1.553200D-02 0.000000D+00 0.000000D+00 -3.478000D-03 0.000000D+00 &#xA;5.314600D-02 0.000000D+00 0.000000D+00 -1.196600D-02 0.000000D+00 &#xA;1.467870D-01 0.000000D+00 0.000000D+00 -3.538800D-02 0.000000D+00 &#xA;3.046630D-01 0.000000D+00 0.000000D+00 -8.007700D-02 0.000000D+00 &#xA;3.976840D-01 0.000000D+00 0.000000D+00 -1.467220D-01 0.000000D+00 &#xA;2.176410D-01 0.000000D+00 0.000000D+00 -1.163600D-01 0.000000D+00 &#xA;1.696300D-02 1.000000D+00 0.000000D+00 2.799190D-01 0.000000D+00 &#xA;-2.745000D-03 0.000000D+00 1.000000D+00 5.854810D-01 0.000000D+00 &#xA;9.530000D-04 0.000000D+00 0.000000D+00 2.840280D-01 1.000000D+00 &#xA;&#xA;4.933000D+01 1.137000D+01 3.435000D+00 1.182000D+00 4.173000D-01 &#xA;1.428000D-01 &#xA;&#xA;0.000000D+00 5.533000D-03 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 3.796200D-02 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.490280D-01 0.000000D+00 0.000000D+00 &#xA;1.000000D+00 3.489220D-01 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 4.589720D-01 1.000000D+00 0.000000D+00 &#xA;0.000000D+00 2.449230D-01 0.000000D+00 1.000000D+00 &#xA;&#xA;2.837000D+00 9.680000D-01 3.350000D-01 &#xA;&#xA;1.000000D+00 0.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.000000D+00 0.000000D+00 &#xA;0.000000D+00 0.000000D+00 1.000000D+00 &#xA;&#xA;2.027000D+00 6.850000D-01 &#xA;&#xA;1.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.000000D+00 &#xA;&#xA;1.427000D+00 &#xA;&#xA;1.0000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-06-07T08:03:01.257" Title="How to remove f functions from a cc-pVQZ basis set in CFOUR format?" Tags="|computational-chemistry|quantum-chemistry|ab-initio-calculations|basis-sets|cfour|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11055" PostTypeId="2" ParentId="11054" CreationDate="2023-06-06T20:28:40.487" Score="3" Body="&lt;p&gt;The CFOUR basis format is laid out on &lt;a href=&quot;https://cfour.uni-mainz.de/cfour/index.php?n=Main.NewFormatOfAnEntryInTheGENBASFile&quot; rel=&quot;nofollow noreferrer&quot;&gt;their website&lt;/a&gt;, but it might be in a little more detail and a little more abstract than you need, so I'll walk through your example of Boron cc-pVQZ to make it more concrete.&lt;/p&gt;&#xA;&lt;p&gt;We can start with the header:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# blank line&#xA;B:cc-pVQZ # atom: basis name&#xA;cc-pVQZ # comment line (typically also basis name)&#xA;# blank line&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;pretty straightforward so far.&lt;/p&gt;&#xA;&lt;p&gt;The next section is where most of the information is laid out:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  5  # number of shells (i.e. has S, P, D, F, and G type orbitals)&#xA;    0    1    2    3    4  # columns (S=0, P=1, D=2, F=3, G=4) &#xA;    5    4    3    2    1  # Number of orbitals for each shell&#xA;   12    6    3    2    1  # Number of contracted Gaussians for each shell&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So for Boron, cc-pVQZ has up to G functions. Going column by column, there are 5 S orbitals made from contracting 12 Gaussians, 4 P orbitals made from contracting 6 Gaussians, and so on.&lt;/p&gt;&#xA;&lt;p&gt;It then lists the orbital exponents and coefficients for each shell in order:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# S orbital exponents, read left to right row by row&#xA;4.584000D+04 6.868000D+03 1.563000D+03 4.424000D+02 1.443000D+02 &#xA;5.218000D+01 2.034000D+01 8.381000D+00 3.529000D+00 1.054000D+00 &#xA;4.118000D-01 1.552000D-01 &#xA;# S orbital coefficients, where each column is for a particular orbital&#xA;9.200000D-05 0.000000D+00 0.000000D+00 -2.000000D-05 0.000000D+00 &#xA;7.170000D-04 0.000000D+00 0.000000D+00 -1.590000D-04 0.000000D+00 &#xA;3.749000D-03 0.000000D+00 0.000000D+00 -8.240000D-04 0.000000D+00 &#xA;1.553200D-02 0.000000D+00 0.000000D+00 -3.478000D-03 0.000000D+00 &#xA;5.314600D-02 0.000000D+00 0.000000D+00 -1.196600D-02 0.000000D+00 &#xA;1.467870D-01 0.000000D+00 0.000000D+00 -3.538800D-02 0.000000D+00 &#xA;3.046630D-01 0.000000D+00 0.000000D+00 -8.007700D-02 0.000000D+00 &#xA;3.976840D-01 0.000000D+00 0.000000D+00 -1.467220D-01 0.000000D+00 &#xA;2.176410D-01 0.000000D+00 0.000000D+00 -1.163600D-01 0.000000D+00 &#xA;1.696300D-02 1.000000D+00 0.000000D+00 2.799190D-01 0.000000D+00 &#xA;-2.745000D-03 0.000000D+00 1.000000D+00 5.854810D-01 0.000000D+00 &#xA;9.530000D-04 0.000000D+00 0.000000D+00 2.840280D-01 1.000000D+00 &#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This continues on in the same way for P, D, F, and G orbitals. So to get rid of the F orbitals, all you need to do is remove this section, which specifies the two F orbitals:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;2.027000D+00 6.850000D-01 &#xA;&#xA;1.000000D+00 0.000000D+00 &#xA;0.000000D+00 1.000000D+00 &#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't have CFOUR to try this, but I believe you will also need to update the earlier shell specification section to look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  4  &#xA;    0    1    2    4 &#xA;    5    4    3    1  &#xA;   12    6    3    1 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;reducing the total number of shells and removing the F orbital column.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2023-06-06T21:08:00.717" LastActivityDate="2023-06-06T21:08:00.717" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11056" PostTypeId="1" CreationDate="2023-06-07T06:58:09.070" Score="5" ViewCount="94" Body="&lt;p&gt;I am trying to study some trajectories generated using Gromacs. I have been given tpr and pdb files of the simulation. What might be the most effective way to load them in ASE? Or is there way to convert them to traj format?&lt;/p&gt;&#xA;&lt;p&gt;I tried converting pdb to traj, but the system size being of the order of 1000 atoms slows the process alongside missing energies due to no calculator from pdb file? (my guess it might need more file)&lt;/p&gt;&#xA;&lt;p&gt;Thanks for your attention.&lt;/p&gt;&#xA;&lt;p&gt;update:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;&#xA;# Load the PDB or GROMACS trajectory file&#xA;traj = io.read('./em.gro', index=':') # replace with 'trajectory.gro' for GROMACS&#xA;&#xA;# Write out the trajectory in the ASE trajectory format&#xA;io.write('check.traj', traj)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried doing this way, but I see no energy due to no calculator information. Also, it is painfully slow.&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="4219" LastEditDate="2023-06-08T11:17:05.880" LastActivityDate="2023-06-08T11:17:05.880" Title="Loading Gromacs Trajectories using ASE (Atomic-Silumation-Environment)" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|gromacs|atomic-simulation-environment|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11057" PostTypeId="2" ParentId="11054" CreationDate="2023-06-07T08:03:01.257" Score="4" Body="&lt;p&gt;If you use the Basis Set Exchange anyway, I recommend you have a look at the Python library which makes it quite simple to modify basis sets in any way you want.&lt;/p&gt;&#xA;&lt;p&gt;The code below does what you want but it can also be easily extended by choosing the angular momentum truncation by element using a dictionary, for instance.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import basis_set_exchange as bse&#xA;&#xA;# Run on basis set&#xA;basis_set = 'cc-pVQZ'&#xA;# and produce format&#xA;fmt = 'cfour'&#xA;&#xA;# Get the basis in native BSE format, but form general contractions&#xA;# since these are used by CFOUR&#xA;basis = bse.api.get_basis(basis_set, make_general=True, fmt=None)&#xA;print(basis)&#xA;&#xA;for element in basis['elements']:&#xA;    # Get the shells on the element&#xA;    shells = basis['elements'][element]['electron_shells']&#xA;    # Include only those shells that have angular momentum &amp;lt;= 2&#xA;    new_shells = [shell for shell in shells if shell['angular_momentum'][0] &amp;lt;= 2 ]&#xA;    basis['elements'][element]['electron_shells'] = new_shells&#xA;&#xA;# Write out basis in CFOUR format&#xA;bse.writers.write_formatted_basis_file(basis, '{}.{}'.format(basis_set, fmt), basis_fmt=fmt)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-07T08:03:01.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11058" PostTypeId="2" ParentId="11034" CreationDate="2023-06-07T08:07:58.913" Score="2" Body="&lt;p&gt;As Tyberius already stated in a comment above, LDA0 is a hybrid functional. However, you can't even expect two different LDAs to give the same results! SVWN5 is different from SVWN3 is different from SPW92.&lt;/p&gt;&#xA;&lt;p&gt;The functionals available in Psi4 are documented &lt;a href=&quot;https://psicode.org/psi4manual/master/dft.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;in the manual&lt;/a&gt;. Psi4 does not implement any of the functionals itself, but relies on Libxc for the implementations. &lt;a href=&quot;https://libxc.gitlab.io/functionals/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The available functionals in Libxc are listed here.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-07T08:07:58.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11059" PostTypeId="1" CreationDate="2023-06-07T08:58:23.460" Score="6" ViewCount="50" Body="&lt;p&gt;Planning to set up a small research group here at my university to do some DFT/MD work and I'm looking for a nice setup that will cater to that. Will be asking for funding from the university or from a local government agency. Any suggestion for PC or cluster specifications that will be bang for buck? We're hoping to start with some novel materials research like with lead-free hybrid perovskites and moving on to other endeavors such as doing theoretical sensing studies.&lt;/p&gt;&#xA;" OwnerUserId="7364" LastActivityDate="2023-06-07T08:58:23.460" Title="PC Specifications for a small DFT Research Group" Tags="|quantum-chemistry|high-performance-computing|" AnswerCount="0" CommentCount="6" ClosedDate="2023-06-08T00:43:56.237" ContentLicense="CC BY-SA 4.0" />
  <row Id="11062" PostTypeId="1" CreationDate="2023-06-07T17:14:32.407" Score="1" ViewCount="387" Body="&lt;p&gt;I'm working with a system of 192 atoms. I've already relaxed the structure (with &lt;code&gt;ISIF=2&lt;/code&gt; and &lt;code&gt;ISMEAR=0&lt;/code&gt;) and achieved the required accuracy. Then, as per the instructions in the VASP manual, I ran the SCF calculation. After that, I copied the obtained CHGCAR file to the DOS directory and attempted to run the calculation. However, every time I receive the following error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;WARNING: The chargedensity file is incomplete.&#xA;ERROR: The charge density could not be read from the CHGCAR file for ICHARG&amp;gt;10.&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have double-checked that the file is copied to the correct directory, and it is complete. Additionally, I have verified the dimensions (NGX, NGZ, NGXF, NGYF, and NGZF) in the CHGCAR file, and they are all accurate. Can you please assist me with this issue? The INCAR file is given below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART =  1                   &#xA;ISPIN  =  2          &#xA;ICHARG =  11         &#xA;LREAL  = A      &#xA;ENCUT  =  520  &#xA;PREC   =  Normal      &#xA;ISMEAR =  -5           &#xA;NELM   =  60           &#xA;NELMIN =  5            &#xA;EDIFF  =  1.0E-05       &#xA;LORBIT = 11             &#xA;NEDOS  = 1000           &#xA;NSW    =  0         &#xA;IBRION = -1         &#xA;POTIM = 0.5&#xA;&#xA;LWAVE = F&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7361" LastEditorUserId="7361" LastEditDate="2023-06-07T22:57:13.040" LastActivityDate="2023-06-07T22:57:13.040" Title="VASP DOS WARNING: charge density file is incomplete ERROR: charge density could not be read from file CHGCAR for ICHARG&gt;10" Tags="|density-functional-theory|vasp|density-of-states|charge-density|" AnswerCount="0" CommentCount="3" ClosedDate="2023-12-02T01:47:06.377" ContentLicense="CC BY-SA 4.0" />
  <row Id="11063" PostTypeId="1" AcceptedAnswerId="11106" CreationDate="2023-06-07T19:59:28.137" Score="6" ViewCount="240" Body="&lt;p&gt;I installed &lt;code&gt;chemcoord&lt;/code&gt; (&lt;a href=&quot;https://chemcoord.readthedocs.io/en/v2.0.5/&quot; rel=&quot;nofollow noreferrer&quot;&gt;link to documentation&lt;/a&gt;) on MacOS in a fresh Python 3.7 virtual environment. When I tried to run the first line of code from the &lt;a href=&quot;https://nbviewer.org/github/mcocdawc/chemcoord/blob/v2.0.5/Tutorial/Zmat.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import chemcoord as cc&#xA;data = cc.Cartesian.read_xyz('/path/to/xyz/file/data.xyz')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I get the following &lt;code&gt;AttributeError&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/Users/deyanmihaylov/Documents/Work/pyscf_geometry/chemcoord.py&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;    import chemcoord as cc&#xA;  File &amp;quot;/Users/deyanmihaylov/Documents/Work/pyscf_geometry/chemcoord.py&amp;quot;, line 6, in &amp;lt;module&amp;gt;&#xA;    water = cc.Cartesian.read_xyz('/Users/deyanmihaylov/Documents/Work/pyscf_geometry/diborane.xyz')&#xA;AttributeError: module 'chemcoord' has no attribute 'Cartesian'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I run &lt;code&gt;print(dir(cc))&lt;/code&gt; after importing as above, I get:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'cc']&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I run &lt;code&gt;pip list&lt;/code&gt; in my terminal, &lt;code&gt;chemcoord&lt;/code&gt; is definitely there:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Package             Version&#xA;------------------- ---------&#xA;...&#xA;chemcoord           2.0.5&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;How &lt;code&gt;chemcoord&lt;/code&gt; was installed&lt;/h2&gt;&#xA;&lt;p&gt;From PyPI:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python3.7 -m venv coords&#xA;source coords/bin/activate&#xA;pip install chemcoord&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives an environment (&lt;code&gt;coords&lt;/code&gt;) which presumably has &lt;code&gt;chemcoord&lt;/code&gt; installed&lt;/p&gt;&#xA;&lt;p&gt;From source code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python3.7 -m venv coords&#xA;source coords/bin/activate&#xA;git clone git@github.com:mcocdawc/chemcoord.git&#xA;cd chemcoord&#xA;pip install .&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This again gives an environment where &lt;code&gt;chemcoord&lt;/code&gt; is installed (verified through &lt;code&gt;pip list&lt;/code&gt;) and should be available.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Since this is code given in the tutorials in the documentation, I suspect there is something that I am missing. What could I be doing wrong with either the installation or running the code?&lt;/p&gt;&#xA;" OwnerUserId="156" LastEditorUserId="5" LastEditDate="2023-06-12T15:49:07.577" LastActivityDate="2023-06-13T02:04:36.103" Title="Why am I getting &quot;AttributeError&quot; when running this Python function?" Tags="|python|software-assistance|geometry|" AnswerCount="1" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="11064" PostTypeId="1" CreationDate="2023-06-08T08:19:49.120" Score="1" ViewCount="112" Body="&lt;p&gt;I am performing some TD-DFT calculations to reproduce the UV-Vis spectrum of a molecule using Gaussian. After optimizing the structure, I performed a TD-DFT calculation with 150 states and I tried different basis sets and functionals (such as B3LYP, CAMB3LYP, M062X).&lt;/p&gt;&#xA;&lt;p&gt;However, in all cases, I fail to reproduce the spectra (in terms of numbers of peaks, not only the position) and it seems very far from the experiments.&lt;/p&gt;&#xA;&lt;p&gt;I wouldn't expect the solvent to change the resolution of the peaks. Does anyone have some tips on how to enhance these types of calculations?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-06-08T08:19:49.120" Title="Gaussian does not reproduce UV-Vis spectrum" Tags="|gaussian|td-dft|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-02T01:46:37.657" ContentLicense="CC BY-SA 4.0" />
  <row Id="11065" PostTypeId="1" AcceptedAnswerId="11096" CreationDate="2023-06-08T11:44:26.023" Score="2" ViewCount="141" Body="&lt;p&gt;I am using Quantum ESPRESSO to do some DFT calculations. I want to know if &lt;strong&gt;the optoelectronic properties&lt;/strong&gt; obtained by a &lt;strong&gt;unit cell&lt;/strong&gt; would remain the same when the properties are obtained by using a larger &lt;strong&gt;supercell&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="6055" LastEditDate="2023-06-08T14:48:44.260" LastActivityDate="2023-06-12T02:36:58.613" Title="Is there any effect on the physical properties when the size of the system increases in DFT?" Tags="|density-functional-theory|quantum-espresso|physical-properties-of-materials|periodic-boundary-conditions|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11066" PostTypeId="2" ParentId="11050" CreationDate="2023-06-08T14:29:06.650" Score="4" Body="&lt;p&gt;There are a few problems here. First of all, you are using a different &lt;code&gt;prefix&lt;/code&gt; for NSCF calculations than the one used in the SCF calculation (OP later fixed it).&lt;/p&gt;&#xA;&lt;p&gt;Then after inspecting the SLURM batch file, I see a typo. You are missing a &lt;code&gt;-in&lt;/code&gt; switch after &lt;code&gt;dos.x&lt;/code&gt;. So, the correct way to run Quantum ESPRESSO executables is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun -np $SLURM_NTASKS dos.x -in DOS.in &amp;gt; DOS.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You may use &lt;code&gt;-inp&lt;/code&gt;,&lt;code&gt;-i&lt;/code&gt;, or &lt;code&gt;&amp;lt;&lt;/code&gt; instead of &lt;code&gt;-in&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-06-09T02:32:27.767" LastActivityDate="2023-06-09T02:32:27.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11067" PostTypeId="1" CreationDate="2023-06-08T17:18:08.273" Score="2" ViewCount="448" Body="&lt;p&gt;I am trying to create a SMILES representation starting from a .xyz molecule description (positions + symbols) read as ASE Atoms.&lt;/p&gt;&#xA;&lt;p&gt;How can I convert a given molecule as a SMILES string ?&lt;/p&gt;&#xA;" OwnerUserId="7367" LastEditorUserId="5" LastEditDate="2023-06-09T09:47:44.290" LastActivityDate="2023-06-09T15:19:59.847" Title="Create a SMILES from ASE Atoms" Tags="|atomic-simulation-environment|smiles|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11069" PostTypeId="2" ParentId="11067" CreationDate="2023-06-09T15:19:59.847" Score="1" Body="&lt;p&gt;In .xyz file there are only atom types and cartesian coordinates of a molecule, so it is generally not able to determine SMILES of that molecule unless you know all chemical bonds present in it.&lt;/p&gt;&#xA;&lt;p&gt;However, there is a tool called &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/bkcs.10334&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;xyz2mol&lt;/code&gt;&lt;/a&gt; which helps this kind of task - it assigns possible chemical bonds with given .xyz file, and outputs molecule with topology.&lt;/p&gt;&#xA;&lt;p&gt;To directly obtain SMILES, you can install the package as described in its &lt;a href=&quot;https://github.com/jensengroup/xyz2mol&quot; rel=&quot;nofollow noreferrer&quot;&gt;Github repo&lt;/a&gt; and invoke the script as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;xyz2mol.py your_molecule.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7097" LastActivityDate="2023-06-09T15:19:59.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11072" PostTypeId="1" CreationDate="2023-06-10T03:42:44.610" Score="3" ViewCount="120" Body="&lt;p&gt;I have constructed a solid-liquid interface model with water as the liquid phase. During the AIMD simulation, I used the NPT ensemble. However, I noticed that under the NPT ensemble, the entire model's lattice changes significantly, especially the volume of the water in the upper liquid phase, which leads to an inconsistent density. I would like to know if there is a way to maintain a constant density of 1 g/cm3 for the water box while using the NPT ensemble.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="7083" LastEditorUserId="7" LastEditDate="2023-06-10T17:16:14.660" LastActivityDate="2023-06-10T17:16:14.660" Title="How to maintain constant liquid density during AIMD with NPT ensembe?" Tags="|molecular-dynamics|ab-initio-calculations|matter-modeling-specific-technology|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11073" PostTypeId="2" ParentId="11072" CreationDate="2023-06-10T07:29:46.733" Score="5" Body="&lt;p&gt;In an AIMD simulation the system size will be very small, so a constant pressure ensemble will entail relatively large volume fluctuations. You should stick to a constant volume simulation unless you have a very compelling physical reason for modelling the isobaric volume changes your box would experience (and can run your AIMD simulation long enough to average over box size fluctuations).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-10T07:29:46.733" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11074" PostTypeId="1" CreationDate="2023-06-10T11:45:16.830" Score="3" ViewCount="541" Body="&lt;p&gt;I did a vc-relax calculation using HSE by Quantum ESPRESSO and after 22h time WALL the job was complete and &lt;code&gt;JOB DONE&lt;/code&gt; was mentionned in the end of the output file but I didn't find the optimized coordinates. I was just able to display the latest achieved coordinates by XCRYSDEN. So even fi the Job was done the convergence wasn't achieved.&lt;/p&gt;&#xA;&lt;p&gt;Here are the stress and pressure achieved, as you can see the pressure is still so high, but normally it should be close to zero.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/g2hdx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/g2hdx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What can be the causes for not achieving optimized coordinates, please?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit: Input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;.&#xA;.&#xA;.&#xA;verbosity='high',&#xA;  tprnfor=.true.,&#xA;  tstress=.true.,&#xA;  etot_conv_thr =1e-5&#xA;  forc_conv_thr =1e-4&#xA;&#xA;/&#xA;&amp;amp;SYSTEM&#xA;&#xA;  occupations='fixed'&#xA;  input_dft='hse',&#xA;  nqx1 = 3, nqx2 =3, nqx3 =3,&#xA;  x_gamma_extrapolation = .true.&#xA;  exxdiv_treatment = 'gygi-baldereschi'&#xA;  input_dft='hse',&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr=1d-07,&#xA;  mixing_beta=0.1d0,&#xA;  electron_maxstep = 3000&#xA;  mixing_mode = 'plain'&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;&#xA;/&#xA;&amp;amp;CELL&#xA;  cell_dofree='ibrav'&#xA;  press=0.d0,&#xA;  press_conv_thr=0.2d0&#xA;/&#xA;.&#xA;.&#xA;.&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-06-12T10:05:38.607" LastActivityDate="2023-06-12T10:05:38.607" Title="Why the relaxation of my material in Quantum ESPRESSO wasn't achieved?" Tags="|density-functional-theory|quantum-espresso|crystallography|geometry-optimization|structure|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11075" PostTypeId="2" ParentId="11074" CreationDate="2023-06-10T12:19:54.697" Score="4" Body="&lt;p&gt;Optimization does not guarantee that you have achieved a well-converged geometry. It only means that the differences in energy, cell-volume and forces calculated between two successive steps are within the convergence criteria that you have defined. As an example, it is possible to converge benzene molecule to a C&lt;span class=&quot;math-container&quot;&gt;$_{2v}$&lt;/span&gt; symmetry, while the global minima is D&lt;span class=&quot;math-container&quot;&gt;$_{2h}$&lt;/span&gt; symmetry.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-06-10T12:19:54.697" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="11076" PostTypeId="1" AcceptedAnswerId="11077" CreationDate="2023-06-10T16:12:47.500" Score="4" ViewCount="301" Body="&lt;p&gt;As far as I understand -&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In MD, when a particle or coordinate moves beyond one face of the simulation box, it reappears on the opposite face as if the box were replicated infinitely in all directions. Each of these replicated positions is called a periodic image.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Then what is a &amp;quot;nearest image&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;What is the difference between a &amp;quot;periodic image&amp;quot; and a &amp;quot;nearest image&amp;quot; in MD simulation?&lt;/p&gt;&#xA;&lt;p&gt;Do I need first to obtain a &amp;quot;periodic image&amp;quot; to calculate a &amp;quot;nearest image&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-06-14T08:02:15.363" Title="What is the difference between a &quot;periodic image&quot; and a &quot;nearest image&quot; in MD simulation?" Tags="|molecular-dynamics|periodic-system|periodic-boundary-conditions|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11077" PostTypeId="2" ParentId="11076" CreationDate="2023-06-10T16:58:37.503" Score="5" Body="&lt;p&gt;You can generate a periodic image n times in any direction. In comparison, the nearest image is the one that is calculated as +x or -x in the x-direction, +y or -y in the y-direction and +z or -z in the z-direction for an orthorhombic cell. Usually, when performing some analysis, like hydrogen bonding, you might be interested in two residues at the +x and -x ends of the original simulation box but might interact via the nearest images.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/i0xgr.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/i0xgr.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;See the attached image for a visual representation of what I just explained. The comment by Ian Bush explains the idea more succinctly.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I think you've assumed an orthorhombic cell in the text - I would say something like, &amp;quot;there is only one nearest, or minimum, image, and that is the nearest of the periodic images.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-06-10T17:27:02.793" LastActivityDate="2023-06-10T17:27:02.793" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11078" PostTypeId="1" CreationDate="2023-06-10T18:26:20.623" Score="5" ViewCount="227" Body="&lt;p&gt;I am a little bit confused by the terminologies of Molecular Dynamics simulation.&lt;/p&gt;&#xA;&lt;p&gt;Do &amp;quot;minimum image convention&amp;quot; and &amp;quot;nearest image&amp;quot; talks about the same things?&lt;/p&gt;&#xA;&lt;p&gt;What is their relationship with the &amp;quot;neighbor list&amp;quot;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-06-14T08:16:03.040" Title="Do &quot;minimum image convention&quot; and &quot;nearest image&quot; talks about the same things?" Tags="|molecular-dynamics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11079" PostTypeId="2" ParentId="11078" CreationDate="2023-06-10T19:18:29.383" Score="3" Body="&lt;p&gt;Neighbour list is what the name suggests that it is. It is computationally expensive to calculate non-bonded interactions between all pairs of particles in an MD simulations, because a naive brute force approach would be an &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; algorithm. So, what is usually done is that you store the id of all particles that are within a specified distance from a given particle in a neighbour list, and calculate the interactions. You then flush this list with a frequency of some multiple times your time step for the simulations.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-06-10T19:18:29.383" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11080" PostTypeId="1" AcceptedAnswerId="11090" CreationDate="2023-06-11T13:29:28.433" Score="3" ViewCount="329" Body="&lt;p&gt;So I used quantum espresso to do bands calculation of an isolated Fe atom in a cell of 20 x 20 x 20 angstroms. I was expecting to see the 5 degenerate d orbitals but I didn't really get a proper degenerate energy level instead I got 6 values which were fairly close and then 3 values which were degenerate separately and another 1 energy level (I only calculated for nbnd=10).&lt;/p&gt;&#xA;&lt;p&gt;Could someone explain how to look at such data and how to see the orbital degeneracy of Fe system?&lt;/p&gt;&#xA;&lt;p&gt;[EDIT]: I wasn't able to find the original data so I had to redo the calculation, here is the input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation='scf',&#xA;    pseudo_dir='/home/anderson/Harsh/Fe'&#xA;&#xA;    prefix='scf'&#xA;    verbosity='high'&#xA;/&#xA;&amp;amp;system&#xA;    ibrav=0,&#xA;    ecutwfc=25,&#xA;    nat=1,&#xA;    nbnd=10&#xA;    occupations='smearing',&#xA;    smearing='mv',&#xA;    degauss=0.10000&#xA;    ntyp=1,&#xA;    nosym = .TRUE.&#xA;/&#xA;&amp;amp;electrons&#xA;    mixing_beta=0.4&#xA;/&#xA;ATOMIC_SPECIES&#xA; Fe 55.845 Fe-pbe.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA; Fe 10.0 10.0 10.0&#xA;&#xA;K_POINTS {automatic}&#xA; 1 1 1 0 0 0&#xA;&#xA;CELL_PARAMETERS {angstrom}&#xA; 20.0 0.0 0.0&#xA; 0.0 20.0 0.0&#xA; 0.0 0.0 20.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output I got after doing the bands calculation this time was&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0.0000 -104.5764&#xA;    0.0000  -65.4071&#xA;    0.0000  -65.4069&#xA;    0.0000  -65.4068&#xA;    0.0000   -6.4181&#xA;    0.0000   -5.9636&#xA;    0.0000   -5.9635&#xA;    0.0000   -5.9634&#xA;    0.0000   -5.8398&#xA;    0.0000   -5.8397&#xA;    0.0000   -2.9550&#xA;    0.0000   -2.9550&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the gnu file that was generated. I can see that there are 5 values similar which I should assume are the d orbitals but there is also a random hanging value of -6.4181 which I have no idea what it's for?&lt;/p&gt;&#xA;" OwnerUserId="7073" LastEditorUserId="5" LastEditDate="2023-06-12T15:20:15.777" LastActivityDate="2023-06-12T15:20:15.777" Title="How to get band structure of isolated Fe atom in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|crystal-field|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11082" PostTypeId="2" ParentId="9725" CreationDate="2023-06-11T16:43:46.350" Score="1" Body="&lt;p&gt;It has been suggested &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9725/how-to-plot-downfolded-bands-from-dft-bands#comment20578_9725&quot;&gt;by Leopold Talirz&lt;/a&gt; that a great answer is &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/750/873&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If anyone wants to write a more detailed answer, please do so and I will delete this Community Wiki answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T16:43:46.350" CommentCount="0" CommunityOwnedDate="2023-06-11T16:43:46.350" ContentLicense="CC BY-SA 4.0" />
  <row Id="11083" PostTypeId="2" ParentId="9754" CreationDate="2023-06-11T16:50:11.667" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9754/perform-energy-minimization-of-multiple-models-of-protein-dna-complexes#comment20535_9754&quot;&gt;Camps wrote&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;If you only want to do geometry optimization, OpenBabel can do that using different force fields.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This Community Wiki answer can be deleted if someone wants to write a more detailed answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T16:50:11.667" CommentCount="0" CommunityOwnedDate="2023-06-11T16:50:11.667" ContentLicense="CC BY-SA 4.0" />
  <row Id="11084" PostTypeId="2" ParentId="9761" CreationDate="2023-06-11T16:52:58.753" Score="1" Body="&lt;p&gt;It seems like an answer that was satisfactory to the OP was written in a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9761/query-about-optical-absorption-spectra#comment20589_9761&quot;&gt;comment by Andrey Poletayev&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;E || a should be xx, E || c should be zz. The equivalent of yy should be E || b.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This Community Wiki post can be deleted if someone wants to write a more detailed answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T16:52:58.753" CommentCount="0" CommunityOwnedDate="2023-06-11T16:52:58.753" ContentLicense="CC BY-SA 4.0" />
  <row Id="11085" PostTypeId="2" ParentId="9814" CreationDate="2023-06-11T17:15:37.027" Score="2" Body="&lt;p&gt;Based on the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9814/molecular-dynamics-method-to-simulate-a-simple-fluid#comment20691_9814&quot;&gt;comment by Magic_Number&lt;/a&gt; and the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9814/molecular-dynamics-method-to-simulate-a-simple-fluid#comment20699_9814&quot;&gt;comment by B. Kelly&lt;/a&gt;, and the lack of response, and the OP not signing in for the last 7 months, I'll assume that it's enough to say that &lt;a href=&quot;https://github.com/Allen-Tildesley/examples/tree/master/python_examples&quot; rel=&quot;nofollow noreferrer&quot;&gt;this link&lt;/a&gt; provided by Magic_Number has the required code, and I'll say that this Community Wiki post can be deleted if someone wants to write a more detailed answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T17:15:37.027" CommentCount="0" CommunityOwnedDate="2023-06-11T17:15:37.027" ContentLicense="CC BY-SA 4.0" />
  <row Id="11086" PostTypeId="2" ParentId="9829" CreationDate="2023-06-11T17:16:49.600" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://bioinformatics.stackexchange.com/a/20055/3621&quot;&gt;An answer was provided at Bioinformatics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This Community Wiki answer can be converted to a comment if someone wants to write a more detailed answer.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T17:16:49.600" CommentCount="0" CommunityOwnedDate="2023-06-11T17:16:49.600" ContentLicense="CC BY-SA 4.0" />
  <row Id="11087" PostTypeId="2" ParentId="9833" CreationDate="2023-06-11T17:19:55.780" Score="1" Body="&lt;p&gt;Please refer to &lt;a href=&quot;https://www.biostars.org/p/9542402/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Biostars&lt;/a&gt; to see more discussion about this question.&lt;/p&gt;&#xA;&lt;p&gt;If someone wants to write a more detailed answered here, this Community Wiki can be deleted.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T17:19:55.780" CommentCount="0" CommunityOwnedDate="2023-06-11T17:19:55.780" ContentLicense="CC BY-SA 4.0" />
  <row Id="11089" PostTypeId="2" ParentId="9922" CreationDate="2023-06-11T17:30:04.857" Score="1" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It's done with a thermostat in the same way a constant temperature simulation is performed. It's just that in simulated annealing, the target temperature varies over some schedule. Here is a good place to start on learning about thermostats: see &lt;a href=&quot;https://home.gwu.edu/%7Eyxzhao/ResearchNotes/ResearchNote007Thermostat.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9922/how-is-temperature-changes-implemented-in-a-molecular-dynamics-simulation#comment20990_9922&quot;&gt;comment by Hayden S&lt;/a&gt; seem to have been satisfactory to the OP, but if someone wants to write a more detailed answer, I'd be happy to delete this Community Wiki.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-06-11T17:30:04.857" CommentCount="0" CommunityOwnedDate="2023-06-11T17:30:04.857" ContentLicense="CC BY-SA 4.0" />
  <row Id="11090" PostTypeId="2" ParentId="11080" CreationDate="2023-06-11T19:00:29.083" Score="3" Body="&lt;p&gt;Following the comment, a plane wave basis set is used for a slowly varying density, this means that the exponential shape of the atomic orbitals needs a lot of plane waves to match their structure. This is the main reason why the code used (QE) required a pseudopotential for atomic-like core orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The effective potential is not hydrogen-like, the repulsion &lt;span class=&quot;math-container&quot;&gt;$\sum_{i,j}\frac{1}{|\vec{r_i}-\vec{r_j}|}$&lt;/span&gt; has also an angular character, you should not expect to have a degeneracy. However, if you are insisting using a PW code for this task, the cell needs to be very large, you also need to increase &lt;span class=&quot;math-container&quot;&gt;$E_{cut}$&lt;/span&gt; for more precise eigenvalues.&lt;/p&gt;&#xA;&lt;p&gt;Note that there is a self-interaction affecting the eigenvalues of a DFT calculation, they are upshifted. The Hartree-Fock eigenvalues are more meaningful, reason why a LCAO code is the best choice for this task.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-06-11T19:00:29.083" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11091" PostTypeId="1" CreationDate="2023-06-11T22:15:22.767" Score="1" ViewCount="286" Body="&lt;p&gt;I am doing computation of tetragonal CsPbBr3 perovskites.&#xA;When I set ISMEAR = -5 I found such a problem:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Nzb6M.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Nzb6M.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This problem is absent at ISMEAR = 0. What is the cause of the problem and how do I solve it?&lt;/p&gt;&#xA;" OwnerUserId="6953" LastEditorUserId="5" LastEditDate="2023-06-12T00:06:42.600" LastActivityDate="2023-06-16T07:08:58.990" Title="The &quot;Tetrahedron method does not include variations of the Fermi occupations&quot; Problem" Tags="|density-functional-theory|vasp|solid-state-physics|perovskites|smearing|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11092" PostTypeId="1" CreationDate="2023-06-11T22:32:12.223" Score="3" ViewCount="492" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SuLJb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SuLJb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Suppose, I have a 2D simulation box whose corners are &lt;span class=&quot;math-container&quot;&gt;$A(-2,-1)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B(-2, 4)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$C(5,4)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$D(5,-1)$&lt;/span&gt;; I have a particle &lt;span class=&quot;math-container&quot;&gt;$P(6, 3)$&lt;/span&gt; inside the simulation box.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt; dimension of the box: &lt;span class=&quot;math-container&quot;&gt;$7$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Therefore,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Original position of &lt;span class=&quot;math-container&quot;&gt;$P(6, 3)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Image 1: &lt;span class=&quot;math-container&quot;&gt;$P'(6 - 7, 3) = P'(-1, 3)$&lt;/span&gt; (wraparound in the x-axis direction)&lt;/li&gt;&#xA;&lt;li&gt;Image 2: &lt;span class=&quot;math-container&quot;&gt;$P^&quot;(-1 - 7, 3) = P^&quot;(-8, 3)$&lt;/span&gt; (wraparound in the opposite x-axis direction)&lt;/li&gt;&#xA;&lt;li&gt;Image 3: &lt;span class=&quot;math-container&quot;&gt;$P^{'''}(6 + 7, 3) = P^{'''}(13, 3)$&lt;/span&gt; (wraparound in the opposite x-axis direction)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;According to the nearest image convention,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The nearest image of &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; should be &lt;span class=&quot;math-container&quot;&gt;$P'(-1, 3)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Duh! Isn't it common sense?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I haven't found anything special in this concept.&lt;/p&gt;&#xA;&lt;p&gt;If so, why should the concept of &amp;quot;&lt;strong&gt;nearest/minimum/closest image&lt;/strong&gt;&amp;quot; even come into the discussion of molecular simulation?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-06-12T00:08:20.313" LastActivityDate="2023-06-12T11:00:27.857" Title="Why should the concept of &quot;nearest/minimum/closest image&quot; even come into the discussion of molecular simulation?" Tags="|minimum-image-convention|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11093" PostTypeId="2" ParentId="11091" CreationDate="2023-06-11T22:40:50.197" Score="0" Body="&lt;p&gt;The system is trying to tell you that your choices of the parameters is PHYSICALLY nonsense. You have to learn to choose sensible things to do.&lt;/p&gt;&#xA;&lt;p&gt;DFT is not meant to be learnt solely by yourself. Please get instructional help from people who actually know what they are doing. This behaviour is by design—there was a physics package that was aimed to be too easy to use, and then people started publishing a lot of nonsense by misusing the package, and that led to nobody being able to trust the papers citing that package. The entire package had to be scrapped.&lt;/p&gt;&#xA;" OwnerUserId="7192" LastActivityDate="2023-06-11T22:40:50.197" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11094" PostTypeId="2" ParentId="11092" CreationDate="2023-06-11T23:47:08.727" Score="5" Body="&lt;p&gt;I think you might be missing an important detail about the minimum image convention. Essentially, it tells you which images should be considered as the &amp;quot;real&amp;quot; particle for the purposes of computing interactions.&lt;/p&gt;&#xA;&lt;p&gt;That is, if you take the main simulation cell and pick two points at opposite ends of the cell, those points would be far apart if there were no periodic boundaries. However, because there are periodic boundaries, those points are actually close to one another because the periodic image of one point is closer than the &amp;quot;actual&amp;quot; location of that point in the main simulation box.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://en.wikipedia.org/wiki/Periodic_boundary_conditions#Practical_implementation:_continuity_and_the_minimum_image_convention&quot; rel=&quot;noreferrer&quot;&gt;wikipedia page&lt;/a&gt; has a nice section discussing how the minimum image convention can be helpful. In short, using the minimum image convention is nice because it allows you to let particles drift past the boundary of the main simulation cell. Every time you compute a distance, you then have to find the shortest distance between a particle and all images of the other particle. Code to do this is given in the wikipedia page as well. Letting the particles continue past the cell boundary rather than explicitly wrapping the particles is convenient because it means the distance between all pairs of atoms is continuous. That is, particles don't ever appear to &amp;quot;jump&amp;quot; large distances in space.&lt;/p&gt;&#xA;&lt;p&gt;So, you're right that there is nothing particularly profound about the minimum image convention, but many people find it counter-intuitive that the interaction between two atoms is not necessarily the interaction between two atoms in the main simulation cell.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2023-06-11T23:47:08.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11095" PostTypeId="2" ParentId="11091" CreationDate="2023-06-12T01:22:33.517" Score="0" Body="&lt;p&gt;An explanation is available in the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISMEAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP manual&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For the calculation of the total energy in bulk materials, we recommend the tetrahedron method with Blöchl corrections (ISMEAR=-5). This method also gives a good account of the electronic density of states (DOS). The only drawback is that the method is not variational with respect to the partial occupancies. Therefore the calculated forces and the stress tensor can be wrong by up to 5 to 10% for metals. Only for semiconductors and insulators, the forces are correct because the partial occupancies do not vary and are either zero or one.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The manual goes in to say how to modify these parameters for metals if you want accurate forces, but your system appears to be a semiconductor.&lt;/p&gt;&#xA;" OwnerUserId="5167" LastActivityDate="2023-06-12T01:22:33.517" CommentCount="1" CommunityOwnedDate="2023-06-12T14:48:50.907" ContentLicense="CC BY-SA 4.0" />
  <row Id="11096" PostTypeId="2" ParentId="11065" CreationDate="2023-06-12T02:36:58.613" Score="3" Body="&lt;p&gt;This is a partial answer to your question. Here I discuss the effect of the size of supercell on DOS, PDOS, and band structure. Others can add the effect on optical or other electronic properties. As pointed out by Ian Bush in the comment, &lt;em&gt;as long as the supercell is exactly a periodic reproduction of the original unit cell and ... the computational parameters are equivalent, you should get exactly the same, except possibly with a trivial scaling&lt;/em&gt;. When I ran a calculation of a carbon chain using 1,2,3,4, and 8 atoms per supercell, I found that the total energy scales almost exactly linearly.&lt;/p&gt;&#xA;&lt;p&gt;Like the total energy, the DOS also scales linearly (mostly). So for example, if you did your calculation with 2 atoms per supercell and found the DOS as 3 states/eV at some E. Then, you will find the DOS to be 6 states/eV at the same E if you used 4 atoms per supercell. The same thing is true with PDOS.&lt;/p&gt;&#xA;&lt;p&gt;For the band structure, if you use a larger supercell, then we have a phenomenon called &lt;em&gt;band folding&lt;/em&gt;. See &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/700/why-is-the-band-structure-of-a-supercell-more-dense-than-for-simple-cell/750#750&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/8835/different-band-structure-in-supercell-but-not-due-to-band-folding&quot;&gt;this&lt;/a&gt; questions about band folding and unfolding. Very briefly, for a larger supercell, the band structure will be more densely populated.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-06-12T02:36:58.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11097" PostTypeId="2" ParentId="9840" CreationDate="2023-06-12T04:01:51.413" Score="3" Body="&lt;p&gt;tetrahedron smearing(ISMEAR=-5) is not suitable for ionic relaxation because it introduces broadening of electronic energy levels, which can lead to inaccurate force evaluations and unphysical atomic configurations in ionic systems. For DOS with sharp peaks, tetrahedron smearing provides more accurate descriptions.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2023-06-12T04:01:51.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11098" PostTypeId="1" AcceptedAnswerId="11099" CreationDate="2023-06-12T07:41:37.027" Score="5" ViewCount="283" Body="&lt;p&gt;I am trying to calculate the UCCSD energy and UCCSD(T) correction for the S atom using PySCF. Using sto-3g basis set, I found that the UCCSD calculation would be completed successfully, but the calculation of UCCSD(T) correction failed with the error message reproduced below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;sto-3g input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/python&#xA;&#xA;import pyscf    as pyscf&#xA;import numpy    as np&#xA;import sys      as sys&#xA;from pyscf      import gto, scf, ao2mo, fci, ci, cc&#xA;from pyscf.lib  import logger&#xA;&#xA;def calculate_energy() -&amp;gt; float:&#xA; &#xA;    neutralMolecule     = pyscf.M(atom = [['S', (0,0,0)]], basis = 'sto-3g', verbose = 9, charge = 0, spin = 2, symmetry = True)&#xA;    neutralMoleculeHF   = scf.UHF(neutralMolecule).run()&#xA;&#xA;    logObject               =   logger.new_logger(neutralMoleculeHF)                # Creates a new logger object&#xA;    orbitals,_,stability,_  =   neutralMoleculeHF.stability(return_status = True)   # Returns four variables: Internal MO, External MO, Internal Stability, External Stability&#xA;    optimizationCycles      =   0&#xA;    while (not stability and optimizationCycles &amp;lt; 200): &#xA;        logObject.note(&amp;quot;Currently at {}-th step optimizing the wavefunction&amp;quot;.format(optimizationCycles))&#xA;    densityMatrix           =   neutralMoleculeHF.make_rdm1(orbitals, neutralMoleculeHF.mo_occ)&#xA;    neutralMoleculeHF       =   neutralMoleculeHF.run(densityMatrix) &#xA;    orbitals,_,stability,_  =   neutralMoleculeHF.stability(return_status = True)&#xA;    optimizationCycles      =   optimizationCycles + 1&#xA;    if not stability:&#xA;        print(&amp;quot;Unable to achieve stable wavefunction after {} steps. Exiting&amp;quot;.format(optimizationCycles))&#xA;        sys.exit(-1)&#xA;    &#xA;    # Now start Post-HF calculations&#xA;    neutralMoleculeCC           =   cc.UCCSD(neutralMoleculeHF).set(conv_tol = 1e-7, frozen = 5, direct = True)&#xA;    neutralMoleculeCC.run()&#xA;    neutralMoleculeCC_results   =   neutralMoleculeCC.kernel()&#xA;    neutralMoleculeCC_CCSDT     =   neutralMoleculeCC.ccsd_t()   &#xA;    return neutralMoleculeCC.e_tot + neutralMoleculeCC_CCSDT&#xA;&#xA;energy  =   calculate_energy()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;sto-3g stack trace&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DIIS for step 0&#xA;cycle = 1  E_corr(CCSD) = 0  dE = 0  norm(t1,t2) = 0&#xA;    CPU time for CCSD iter      0.07 sec, wall time      0.02 sec&#xA;    CPU time for CCSD      0.07 sec, wall time      0.02 sec&#xA;UCCSD converged&#xA;E(UCCSD) = -393.130219398113  E_corr = 0&#xA;    CPU time for transpose 0:2      0.06 sec, wall time      0.02 sec&#xA;    CPU time for transpose 0:2      0.01 sec, wall time      0.00 sec&#xA;    CPU time for UCCSD(T) sort_eri      0.08 sec, wall time      0.03 sec&#xA;max_memory 3874 MB (125 MB in use)&#xA;    CPU time for contract_aaa      0.00 sec, wall time      0.00 sec&#xA;max_memory 3874 MB (125 MB in use)&#xA;    CPU time for contract 0:2,0:2      0.04 sec, wall time      0.01 sec&#xA;    CPU time for contract_bbb      0.04 sec, wall time      0.01 sec&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/home/hemanth/Desktop/hpqc/cs/cs_pes_scan.py&amp;quot;, line 34, in &amp;lt;module&amp;gt;&#xA;    energy  =   calculate_energy(scanDistance=0)&#xA;                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/hemanth/Desktop/hpqc/cs/cs_pes_scan.py&amp;quot;, line 31, in calculate_energy&#xA;    neutralMoleculeCC_CCSDT     =   neutralMoleculeCC.ccsd_t()   &#xA;                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/hemanth/miniconda3/envs/hpqc/lib/python3.11/site-packages/pyscf/cc/uccsd.py&amp;quot;, line 635, in ccsd_t&#xA;    return uccsd_t.kernel(self, eris, t1, t2, self.verbose)&#xA;           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/home/hemanth/miniconda3/envs/hpqc/lib/python3.11/site-packages/pyscf/cc/uccsd_t.py&amp;quot;, line 139, in kernel&#xA;    for a0, a1 in lib.prange(0, nvirb, int(bufsize/nvira+1)):&#xA;                                           ~~~~~~~^~~~~~&#xA;ZeroDivisionError: division by zero&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, if I change the basis set to 6-31g, the UCCSD and UCCSD(T) calculations would be completed without any issues.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;6-31g input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/python&#xA;&#xA;import pyscf    as pyscf&#xA;import numpy    as np&#xA;import sys      as sys&#xA;from pyscf      import gto, scf, ao2mo, fci, ci, cc&#xA;from pyscf.lib  import logger&#xA;&#xA;def calculate_energy() -&amp;gt; float:&#xA; &#xA;    neutralMolecule     = pyscf.M(atom = [['S', (0,0,0)]], basis = '6-31g', verbose = 9, charge = 0, spin = 2, symmetry = True)&#xA;    neutralMoleculeHF   = scf.UHF(neutralMolecule).run()&#xA;&#xA;    logObject               =   logger.new_logger(neutralMoleculeHF)                # Creates a new logger object&#xA;    orbitals,_,stability,_  =   neutralMoleculeHF.stability(return_status = True)   # Returns four variables: Internal MO, External MO, Internal Stability, External Stability&#xA;    optimizationCycles      =   0&#xA;    while (not stability and optimizationCycles &amp;lt; 200): &#xA;        logObject.note(&amp;quot;Currently at {}-th step optimizing the wavefunction&amp;quot;.format(optimizationCycles))&#xA;    densityMatrix           =   neutralMoleculeHF.make_rdm1(orbitals, neutralMoleculeHF.mo_occ)&#xA;    neutralMoleculeHF       =   neutralMoleculeHF.run(densityMatrix) &#xA;    orbitals,_,stability,_  =   neutralMoleculeHF.stability(return_status = True)&#xA;    optimizationCycles      =   optimizationCycles + 1&#xA;    if not stability:&#xA;        print(&amp;quot;Unable to achieve stable wavefunction after {} steps. Exiting&amp;quot;.format(optimizationCycles))&#xA;        sys.exit(-1)&#xA;    &#xA;    # Now start Post-HF calculations&#xA;    neutralMoleculeCC           =   cc.UCCSD(neutralMoleculeHF).set(conv_tol = 1e-7, frozen = 5, direct = True)&#xA;    neutralMoleculeCC.run()&#xA;    neutralMoleculeCC_results   =   neutralMoleculeCC.kernel()&#xA;    neutralMoleculeCC_CCSDT     =   neutralMoleculeCC.ccsd_t()   &#xA;    return neutralMoleculeCC.e_tot + neutralMoleculeCC_CCSDT&#xA;&#xA;energy  =   calculate_energy()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;6-31g output file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DIIS for step 7&#xA;cycle = 8  E_corr(CCSD) = -0.0229167339083696  dE = 2.82885328e-08  norm(t1,t2) = 7.6597e-07&#xA;    CPU time for CCSD iter      0.26 sec, wall time      0.06 sec&#xA;    CPU time for CCSD      2.52 sec, wall time      0.65 sec&#xA;UCCSD converged&#xA;E(UCCSD) = -397.4943311312284  E_corr = -0.02291673390836959&#xA;    CPU time for transpose 0:4      0.01 sec, wall time      0.00 sec&#xA;    CPU time for transpose 0:6      0.03 sec, wall time      0.01 sec&#xA;    CPU time for transpose 0:4      0.03 sec, wall time      0.01 sec&#xA;    CPU time for transpose 0:6      0.01 sec, wall time      0.00 sec&#xA;    CPU time for UCCSD(T) sort_eri      0.10 sec, wall time      0.03 sec&#xA;max_memory 3874 MB (125 MB in use)&#xA;    CPU time for contract 0:4,0:4      0.02 sec, wall time      0.00 sec&#xA;    CPU time for contract_aaa      0.02 sec, wall time      0.00 sec&#xA;max_memory 3874 MB (125 MB in use)&#xA;    CPU time for contract 0:6,0:6      0.01 sec, wall time      0.00 sec&#xA;    CPU time for contract_bbb      0.01 sec, wall time      0.00 sec&#xA;    CPU time for contract 0:6,0:4      0.01 sec, wall time      0.00 sec&#xA;    CPU time for contract_baa      0.01 sec, wall time      0.00 sec&#xA;    CPU time for contract 0:4,0:6      0.01 sec, wall time      0.00 sec&#xA;    CPU time for contract_abb      0.01 sec, wall time      0.00 sec&#xA;    CPU time for UCCSD(T)      0.15 sec, wall time      0.04 sec&#xA;UCCSD(T) correction = -0.000187450473417524&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any pointers on why this is happening would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-06-12T08:12:39.207" Title="Error in UCCSD(T) Calculation in PySCF for S atom?" Tags="|computational-chemistry|pyscf|coupled-cluster|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11099" PostTypeId="2" ParentId="11098" CreationDate="2023-06-12T08:12:39.207" Score="6" Body="&lt;p&gt;The stack trace shows that the program tries to divide a number by the number of alpha virtual orbitals (nvira), which is zero in the case of STO-3G triplet sulfur atom. This caused a ZeroDivisionError, leading to a program abort. The number of alpha virtual orbitals can only be zero when the basis set is a minimal basis set.&lt;/p&gt;&#xA;&lt;p&gt;While one may argue that a decent program should implement a branch that deals with this case (since the CCSD(T)/STO-3G energy is a mathematically valid quantity and has a well-defined value), a CCSD(T)/STO-3G calculation is not physically meaningful, as one can get much better accuracy at much lower cost with a DFT/double zeta basis calculation. Therefore, this ZeroDivisionError does not necessarily count as a bug, because it only happens in calculations whose basis sets are so small that the results are not physically useful.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-06-12T08:12:39.207" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11100" PostTypeId="1" AcceptedAnswerId="11101" CreationDate="2023-06-12T09:04:03.043" Score="4" ViewCount="191" Body="&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.196102&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, they separated knock-on damage (originating from the collision of the beam electrons with the nucleus of the target atom) from other radiation damage mechanisms (e.g., ionization damage or chemical etching) by the comparison of ordinary (&lt;sup&gt;12&lt;/sup&gt;C) and heavy (&lt;sup&gt;13&lt;/sup&gt;C) graphene because any chemical effect, or ionization damage, would not distinguish between &lt;sup&gt;12&lt;/sup&gt;C and &lt;sup&gt;13&lt;/sup&gt;C. Only knock-on damage would distinguish between them. They did it experimentally.&lt;/p&gt;&#xA;&lt;p&gt;Knock-on damage can be modeled with molecular dynamics by assigning different initial velocities to an atom hit by an electron beam.&lt;/p&gt;&#xA;&lt;p&gt;How to do molecular dynamics with different isotopes of the same element? Is there any DFT or MD code that does it?&lt;/p&gt;&#xA;&lt;p&gt;I searched VASP wiki, and didn't find anything about isotopes.&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-06-12T09:27:08.620" Title="How to do molecular dynamics with different isotopes of the same element?" Tags="|molecular-dynamics|software-recommendations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11101" PostTypeId="2" ParentId="11100" CreationDate="2023-06-12T09:27:08.620" Score="4" Body="&lt;p&gt;The answer is relatively simple, the neutrons do not directly contribute to anything electronically in the calculation, so the different isotopes are only different in terms of their masses / motion.  To change this, simply change the default &lt;a href=&quot;https://www.vasp.at/wiki/index.php/POMASS&quot; rel=&quot;nofollow noreferrer&quot;&gt;mass of the pseudopotential&lt;/a&gt; in VASP.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2023-06-12T09:27:08.620" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11102" PostTypeId="2" ParentId="11092" CreationDate="2023-06-12T11:00:27.857" Score="3" Body="&lt;p&gt;In your own example, the distance from &lt;span class=&quot;math-container&quot;&gt;$P'''$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the same as from &lt;span class=&quot;math-container&quot;&gt;$P'$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt;, namely seven units. So why should &lt;span class=&quot;math-container&quot;&gt;$P'$&lt;/span&gt; be the minimum image and not &lt;span class=&quot;math-container&quot;&gt;$P'''$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;So no, as you yourself have just demonstrated, the minimum image concept is not &lt;em&gt;that&lt;/em&gt; simple.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Minimum images arise in molecular dynamics because (1) we want to model bulk properties using periodic boundary conditions on, physically, absurdly small volumes (2) we often &lt;em&gt;truncate&lt;/em&gt; forces and neglect them past some cutoff.&lt;/p&gt;&#xA;&lt;p&gt;Under condition (1) alone, in theory, every pair of particles would have an infinite set of interactions (since particle 1 in the main box would interact with particle 2, and particle 2's adjacent image, and particle 2's &lt;em&gt;next&lt;/em&gt; image, and so on ...). But under condition (2) pair interactions are now manageable: we have each particle keep a list of other particles whose main box images &lt;em&gt;or adjacent images&lt;/em&gt; are within the cutoff, and simply evaluate those forces.&lt;/p&gt;&#xA;&lt;p&gt;For example, let particle 1 be at the origin (0,0) and let particle 2's main image be at (8,0), in a box of width 10 with a force cutoff of 3. Then particle 1 experiences a force from particle 2's &amp;quot;minimum image&amp;quot; at (-2,0). Equivalently, particle 2 experiences a force from particle 1's &amp;quot;minimum image&amp;quot; at (10,0). (By the way, note how Newton's Third Law remains obeyed.)&lt;/p&gt;&#xA;&lt;p&gt;Now, we are &lt;em&gt;finally&lt;/em&gt; in a position to explain the minimum image convention: it is that only minimum image pairs are considered when calculating truncated image pairs. The most important effect of this convention is actually its corollary, that (roughly) &lt;em&gt;the box size must be larger than twice the force cutoff in every dimension&lt;/em&gt;. This is necessary because the &amp;quot;neighbour list&amp;quot; is often evaluated by searching for all particles within the cutoff distance from a particle, and if the box size were less than twice the force cutoff, particle pairs would start to be multiply-counted in the neighbour list.&lt;/p&gt;&#xA;&lt;p&gt;Note that &lt;em&gt;this is neither trivial nor automatic&lt;/em&gt;. For example, the MD package LAMMPS &lt;em&gt;does not follow the minimum image convention&lt;/em&gt; for pair forces. If the pair cutoff is large enough to warrant it, LAMMPS will simply &amp;quot;stack up&amp;quot; enough images to fill the neighbour list out to the cutoff. As such, LAMMPS can handle much smaller boxes relative to pair cutoffs (down to numerical error). Furthermore, long-ranged electrostatic corrections (such as Ewald, PME and PPPM) explicitly consider &lt;em&gt;the entire set of infinite periodic images&lt;/em&gt; when calculating charges (using Fourier transforms into reciprocal space, and then truncating there at a frequency cutoff), so they don't follow the minimum image convention either. Variations of this concept are important for steered molecular dynamics simulations (when moving the centre of mass of one group away from another, their distance cannot be allowed to exceed half the box size, or there suddenly becomes no natural way to define &lt;em&gt;a&lt;/em&gt; force between them).&lt;/p&gt;&#xA;&lt;p&gt;So no, it is neither trivial nor simple. Either when it is applied, or when it is not, the minimum image convention is really important to understand.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-12T11:00:27.857" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11104" PostTypeId="1" AcceptedAnswerId="11114" CreationDate="2023-06-12T13:03:03.733" Score="4" ViewCount="53" Body="&lt;p&gt;I have been exploring xtb and used it to run docking on an ion pair. I get&#xA;the message at the end in the .log file. The xyz files of input structures&#xA;were obtained from Gaussian output files. Is there a way to optimize&#xA;monomers using xtb before submission so that the interaction energies&#xA;output are deemed physical? I am unsure of how to solve this issue. All advice is highly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thank you,&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt; Interaction energies&#xA; Attention: monomers are not optimized&#xA; Interaction energies are not physical&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5113" LastActivityDate="2023-06-14T06:47:00.327" Title="What is the significance of xtb message: Interaction energies are not physical?" Tags="|molecular-interactions|xtb|dftb-plus|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11105" PostTypeId="2" ParentId="7166" CreationDate="2023-06-12T14:55:34.790" Score="6" Body="&lt;p&gt;A plane can be defined with 3 atoms and two planes can be defined with 4 atoms. Thus it's natural to define an angle between these two planes which is the dihedral (or torsion) angle.&lt;/p&gt;&#xA;&lt;p&gt;You can think of this dihedral angle as an opened book and place two atoms on the book spine. For improper dihedral, the other two atoms connect to the same atom on the spine&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;| \ / |&#xA;|  x  |&#xA;|  |  |&#xA;|  x  |&#xA;| / \ |&#xA;x     x&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For proper dihedral, the other two atoms connect to different atoms on the spine&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;x&#xA;| \ / |&#xA;|  x  |&#xA;|  |  |&#xA;|  x  |&#xA;| / \ |&#xA;      x&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In either case, we have an angle between the book pages&lt;/p&gt;&#xA;" OwnerUserId="7385" LastEditorUserId="7385" LastEditDate="2023-06-13T03:24:36.337" LastActivityDate="2023-06-13T03:24:36.337" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11106" PostTypeId="2" ParentId="11063" CreationDate="2023-06-12T16:13:34.763" Score="4" Body="&lt;h1&gt;Your problem&lt;/h1&gt;&#xA;&lt;p&gt;You are running a script called &lt;code&gt;chemcoord.py&lt;/code&gt; which has the same name as the package itself.  Your &lt;code&gt;chemcoord.py&lt;/code&gt; script does not have the &lt;code&gt;Cartesian&lt;/code&gt; attribute defined anywhere, but the Python interpreter is looking for it in your script.&lt;/p&gt;&#xA;&lt;h1&gt;The program works for me&lt;/h1&gt;&#xA;&lt;p&gt;The installation took several minutes, starting with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[nike@gra-login3 ~]$ pip install  chemcoord&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Defaulting to user installation because normal site-packages is not writeable&#xA;Looking in links: /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic&#xA;Collecting chemcoord&#xA;  Downloading chemcoord-2.0.5-py3-none-any.whl (96 kB)&#xA;     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 96.8/96.8 KB 6.6 MB/s eta 0:00:00&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2/pandas-2.0.0+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Collecting pymatgen&#xA;  Downloading pymatgen-2023.5.31.tar.gz (9.7 MB)&#xA;     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.7/9.7 MB 29.3 MB/s eta 0:00:00&#xA;  Installing build dependencies ... done&#xA;  Getting requirements to build wheel ... done&#xA;  Installing backend dependencies ... done&#xA;  Preparing metadata (pyproject.toml) ... done&#xA;Requirement already satisfied: six in /cvmfs/soft.computecanada.ca/easybuild/software/2020/avx2/Core/python/3.10.2/lib/python3.10/site-packages (from chemcoord) (1.16.0)&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic/scipy-1.10.1+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic/numba-0.56.3+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Collecting sympy&#xA;  Downloading sympy-1.12-py3-none-any.whl (5.7 MB)&#xA;     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.7/5.7 MB 93.4 MB/s eta 0:00:00&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic/numpy-1.24.2+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic/sortedcontainers-2.4.0+computecanada-py3-none-any.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic/numpy-1.23.2+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2/llvmlite-0.39.1+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Requirement already satisfied: setuptools in /cvmfs/soft.computecanada.ca/easybuild/software/2020/avx2/Core/python/3.10.2/lib/python3.10/site-packages (from numba&amp;gt;=0.35-&amp;gt;chemcoord) (60.7.1)&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic/pytz-2023.3+computecanada-py2.py3-none-any.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic/python_dateutil-2.8.2+computecanada-py2.py3-none-any.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic/tzdata-2023.3+computecanada-py2.py3-none-any.whl&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic/spglib-2.0.2+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Collecting ruamel.yaml&amp;gt;=0.17.0&#xA; 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 Downloading latexcodec-2.0.1-py2.py3-none-any.whl (18 kB)&#xA;Processing /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2/PyYAML-6.0+computecanada-cp310-cp310-linux_x86_64.whl&#xA;Collecting pydantic&amp;gt;=1.10.2&#xA;  Downloading pydantic-1.10.9-py3-none-any.whl (157 kB)&#xA;     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 157.8/157.8 KB 11.9 MB/s eta 0:00:00&#xA;Building wheels for collected packages: pymatgen&#xA;  Building wheel for pymatgen (pyproject.toml) ... done&#xA;  Created wheel for pymatgen: filename=pymatgen-2023.5.31-cp310-cp310-linux_x86_64.whl size=11253958 sha256=c5db183a0b4b5607ae7634b2e2e41fb95162745158cab59f8942a68eb3f74666&#xA;  Stored in directory: /home/nike/.cache/pip/wheels/74/c0/d0/0aaf31f88e7cad712af75fc8dbabb792bcdac99107d85376b4&#xA;Successfully built pymatgen&#xA;Installing collected packages: sortedcontainers, pytz, msgpack, mpmath, urllib3, tzdata, typing-extensions, tqdm, tenacity, tabulate, sympy, ruamel.yaml.clib, PyYAML, python-dateutil, pillow, palettable, numpy, networkx, monty, llvmlite, latexcodec, kiwisolver, idna, future, fonttools, cycler, charset-normalizer, certifi, uncertainties, spglib, scipy, ruamel.yaml, requests, pydantic, pybtex, plotly, pandas, numba, contourpy, matplotlib, emmet-core, mp-api, pymatgen, chemcoord&#xA;Successfully installed PyYAML-6.0+computecanada certifi-2023.5.7 charset-normalizer-3.1.0+computecanada chemcoord-2.0.5 contourpy-1.0.7+computecanada cycler-0.11.0+computecanada emmet-core-0.55.5 fonttools-4.40.0 future-0.18.2+computecanada idna-3.4+computecanada kiwisolver-1.4.4+computecanada latexcodec-2.0.1 llvmlite-0.39.1+computecanada matplotlib-3.7.0+computecanada monty-2023.5.8 mp-api-0.33.3 mpmath-1.3.0+computecanada msgpack-1.0.4+computecanada networkx-3.1+computecanada numba-0.56.3+computecanada numpy-1.23.2+computecanada palettable-3.3.3 pandas-2.0.0+computecanada pillow-9.5.0+computecanada plotly-5.15.0 pybtex-0.24.0 pydantic-1.10.9 pymatgen-2023.5.31 python-dateutil-2.8.2+computecanada pytz-2023.3+computecanada requests-2.31.0 ruamel.yaml-0.17.31 ruamel.yaml.clib-0.2.7+computecanada scipy-1.10.1+computecanada sortedcontainers-2.4.0+computecanada spglib-2.0.2+computecanada sympy-1.12 tabulate-0.9.0+computecanada tenacity-8.2.2 tqdm-4.65.0+computecanada typing-extensions-4.6.3 tzdata-2023.3+computecanada uncertainties-3.1.7 urllib3-2.0.3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now everything works:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[nike@gra-login3 ~]$ python&#xA;Python 3.10.2 (main, Feb  4 2022, 19:10:35) [GCC 9.3.0] on linux&#xA;Type &amp;quot;help&amp;quot;, &amp;quot;copyright&amp;quot;, &amp;quot;credits&amp;quot; or &amp;quot;license&amp;quot; for more information.&#xA;&amp;gt;&amp;gt;&amp;gt; import chemcoord as cc&#xA;&amp;gt;&amp;gt;&amp;gt; cc.__version__&#xA;'2.0.5'&#xA;&amp;gt;&amp;gt;&amp;gt; cc.__file__&#xA;'/home/nike/.local/lib/python3.10/site-packages/chemcoord/__init__.py'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Credits&lt;/h1&gt;&#xA;&lt;p&gt;While trying to get this question answered, I tried program myself and it worked (see the above output). I then went to the Python chatroom at StackOverflow and sought opinions there. Within three minutes &lt;a href=&quot;https://chat.stackoverflow.com/transcript/message/56429750#56429750&quot;&gt;Josh Rogan figured out the issue&lt;/a&gt;. He's not answering due to the &lt;a href=&quot;https://meta.stackexchange.com/q/389811/391772&quot;&gt;current strike&lt;/a&gt;, but I've committed to giving Josh a bounty equal to the rep earned on this post if he decides to start posting answers again.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-06-13T02:04:36.103" LastActivityDate="2023-06-13T02:04:36.103" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11107" PostTypeId="2" ParentId="11040" CreationDate="2023-06-12T18:02:46.610" Score="4" Body="&lt;p&gt;The elastic stiffness &lt;span class=&quot;math-container&quot;&gt;$C_{j}$&lt;/span&gt; with respect to each &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; direction mediates the energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; at a deformed structure and the mechanical strain &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{j}$&lt;/span&gt; as follows [Mir, S. H. et al. &lt;em&gt;ACS Omega&lt;/em&gt;. &lt;strong&gt;2020&lt;/strong&gt;, 5, 24 &amp;amp; L. Tang at al. &lt;em&gt;Sci. China,&#xA;Ser. B: Chem.&lt;/em&gt; &lt;strong&gt;2009&lt;/strong&gt;, 52, 10].&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{E-E_{0}}{A_{0}}=\frac{1}{2}C_{j}\epsilon_{j}^{2}&#xA;$$&lt;/span&gt;&#xA;Here, &lt;span class=&quot;math-container&quot;&gt;$E_{0}$&lt;/span&gt; is the energy of the structure at the local minimum, and &lt;span class=&quot;math-container&quot;&gt;$A_{0}$&lt;/span&gt; is the surface area.&lt;/p&gt;&#xA;&lt;p&gt;The figure of the original post presents &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{j}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$E-E_{0}$&lt;/span&gt;, and the data exhibit a quadratic behavior that aligns with the above equation.&lt;/p&gt;&#xA;&lt;p&gt;Neglecting the lower-order terms, the fitting function can be expressed as &lt;span class=&quot;math-container&quot;&gt;$y/A_{0} \approx \frac{1}{2}C_{j}x^{2}$&lt;/span&gt;, or &lt;span class=&quot;math-container&quot;&gt;$y=\frac{1}{2}C_{j}A_{0}x^{2}$&lt;/span&gt;. Therefore, the number of &lt;span class=&quot;math-container&quot;&gt;$C_{j}$&lt;/span&gt; will be &lt;span class=&quot;math-container&quot;&gt;$C\approx 2\times(460.05)/ A_{0}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1789" LastActivityDate="2023-06-12T18:02:46.610" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11108" PostTypeId="1" CreationDate="2023-06-12T20:09:01.047" Score="2" ViewCount="140" Body="&lt;p&gt;Why do we specifically need an SCF-generated charge density for calculating the density of states (DOS) and band structure?&lt;/p&gt;&#xA;" OwnerUserId="7361" LastEditorUserId="5" LastEditDate="2023-06-13T02:51:46.700" LastActivityDate="2023-06-20T23:03:44.160" Title="Why do we specifically need an SCF-generated charge density for calculating the density of states (DOS) and band structure?" Tags="|density-functional-theory|vasp|band-structure|density-of-states|self-consistent-field|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11110" PostTypeId="2" ParentId="9625" CreationDate="2023-06-13T11:55:00.100" Score="1" Body="&lt;h1&gt;mBJ vs TBmBJ&lt;/h1&gt;&#xA;&lt;p&gt;Let's ask ourselves what the difference is between mBJ and TBmBJ.    A quite recent paper, published in 2020 and with already 37 citations on Google Scholar, is &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.9b01147&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; which says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The modified Becke-Johnson exchange-correlation potential was proposed by Tran and Blaha in 2009.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Therefore the answers to:&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/154/5&quot;&gt;How trustworthy is the Tran-Blaha modified Becke-Johnson potential and how does it perform across basis sets?&lt;/a&gt; technically can apply to your question. Similarly for the thread that you found yourself: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/154/how-trustworthy-is-the-tran-blaha-modified-becke-johnson-potential-and-how-does&quot;&gt;How trustworthy is the Tran-Blaha modified Becke-Johnson potential and how does it perform across basis sets?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Two more clarifications&lt;/h1&gt;&#xA;&lt;h4&gt;Potential vs functional&lt;/h4&gt;&#xA;&lt;p&gt;mBJ is usually referred as a &amp;quot;potential&amp;quot; rather than as a &amp;quot;functional&amp;quot;, and the reliability of it has been explained in detail in Anubab Haldar's answer to the following question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/836/5&quot;&gt;How does the mBJ potential give an accurate band gap as compared to LDA and GGA?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h4&gt;mBJ vs HSE06&lt;/h4&gt;&#xA;&lt;p&gt;You have said that you found several papers that said that HSE06 and mBJ are the two most reliable out of everything, and yet your next sentence asks if mBJ is reliable, even though you already said that you can't use HSE06, and that mBJ is the second best according to your literature search. This indicates that despite all the other answers, your only option (as you have presented the options) is to use mBJ. &lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-06-13T12:22:26.207" LastActivityDate="2023-06-13T12:22:26.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11111" PostTypeId="2" ParentId="10503" CreationDate="2023-06-13T15:01:59.870" Score="3" Body="&lt;p&gt;In the examples that you saw for 2 electrodes, the input files probably had a block like the following where you list the electrodes in your system:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here &lt;code&gt;Left&lt;/code&gt; and &lt;code&gt;Right&lt;/code&gt; are the names of your electrodes. Then you have to go and individually define each of them. For example, to define the &lt;code&gt;Right&lt;/code&gt; electrode:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%block TS.Elec.Right&#xA;  HS electrode.TSHS&#xA;  chemical-potential Right&#xA;  semi-inf-direction -a3&#xA;  electrode-position 1&#xA;  used-atoms 36&#xA;%endblock&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If the &lt;code&gt;Right&lt;/code&gt; and &lt;code&gt;Left&lt;/code&gt; electrodes are the same, some parameters of the electrode definition, like &lt;code&gt;HS&lt;/code&gt; (the hamiltonian file) or &lt;code&gt;used-atoms&lt;/code&gt; (number of atoms in the electrode), will be the same. However the rest of parameters are different already. To define different electrodes you just need to specify these parameters accordingly. That is for example, for the &lt;code&gt;Left&lt;/code&gt; electrode provide its hamiltonian file and the number of atoms that the &lt;code&gt;Left&lt;/code&gt; electrode has.&lt;/p&gt;&#xA;&lt;p&gt;To understand all the possible parameters find the &lt;code&gt;TS.Elec&lt;/code&gt; key in SIESTA's manual (currently available here: &lt;a href=&quot;https://www.siesta-project.org/SIESTA_MATERIAL/Docs/Manuals/siesta-4.1.5.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.siesta-project.org/SIESTA_MATERIAL/Docs/Manuals/siesta-4.1.5.pdf&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Preparing the input file for the calculation of the extra electrode is done exactly the same as you did for the first one.&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2023-06-13T15:01:59.870" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11112" PostTypeId="1" CreationDate="2023-06-13T15:49:52.853" Score="4" ViewCount="48" Body="&lt;p&gt;Hessian is required for minimisation and transition state (TS) optimisation algorithms. While the full Hessian at a certain level of theory is calculated usually for TS optimisation, usually minimisation starts from an approximate Hessian estimated from force-fields.&lt;/p&gt;&#xA;&lt;p&gt;I found an option that is available in many popular QM packages like ORCA or Gaussian16, where only some parts of the Hessian are calculated accurately at the current level of theory (e.g., DFT) and the rest are estimates. The Gaussian16 &lt;a href=&quot;https://gaussian.com/opt/&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt; mentions:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Compute some or all of the Hessian numerically: You can ask the optimization program to compute part of the second derivative matrix numerically. In this case each specified variable will be stepped in only one direction, not both up and down as would be required for an accurate determination of force constants. The resulting second-derivatives are not as good as those determined by a frequency calculation but are fine for starting an optimization. Of course, this requires that the program do an extra gradient calculation for each specified variable. This procedure is requested by a flag (D) on the variable definition lines:&#xA;&lt;br&gt;&lt;br&gt;&#xA;1 2 D &lt;br&gt;&#xA;1 2 3 D&#xA;&lt;br&gt;&lt;br&gt;&#xA;This input tells the program to do three points before taking the first optimization step: the usual first point, a geometry with the bond between atoms 1 and 2 incremented slightly, and a geometry with the angle between atoms 1, 2 and 3 incremented slightly. The program will estimate all force constants (on and off diagonal) for bond(1,2) and angle(1,2,3) from the three points.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The ORCA website also mentions this option:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Hybrid Hessians are an alternative to calculating the exact full Hessian. By selecting only a few atoms of the systems for which to calculate the Hessian one can get a much cheaper, yet often useful Hessian to aid geometry optimizations or saddle point searches.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This seems to be a very useful option for TS optimisations for large systems where obtaining the full Hessian might be expensive.&lt;/p&gt;&#xA;&lt;p&gt;However, I haven't been able to find any reference where the exact mathematics of this procedure is shown (in terms of the matrix). As I understand, in the Cartesian Hessian eigenvectors, the effects of different bond stretch, and angle bends are mixed together. For internal coordinates like redundant or delocalised, I have no idea how they work. The gradients are always estimated in Cartesian coordinate system however so I imagine a coordinate transform is needed.&lt;/p&gt;&#xA;&lt;p&gt;How is the hybrid/partial Hessian calculation is done (i.e. the maths procedure to construct the Hessian matrix)?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-06-13T15:49:52.853" Title="How to compute only part of molecular Hessian accurately (hybrid Hessian or partial Hessian calculation)?" Tags="|quantum-chemistry|gaussian|geometry-optimization|orca|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11113" PostTypeId="2" ParentId="11043" CreationDate="2023-06-14T05:11:17.207" Score="5" Body="&lt;p&gt;I'll separate the importance of the files to 2 categories.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Purely for data analysis purposes&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;code&gt;CONTCAR&lt;/code&gt; files are definitely important for relaxed structural information.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;OUTCAR&lt;/code&gt; and &lt;code&gt;vasprun.xml&lt;/code&gt; files would contain the calculation outputs  conventionally used for analysis. The &lt;code&gt;OUTCAR&lt;/code&gt; would also contain the &lt;code&gt;INCAR&lt;/code&gt; settings in human-readable form so you can always refer back to what settings you used from the &lt;code&gt;OUTCAR&lt;/code&gt; file (no need to save the &lt;code&gt;INCAR&lt;/code&gt; files).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ease of redoing calculations&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;code&gt;CONTCAR&lt;/code&gt; files are also important so you don't have to re-relax the structures if you need to redo calculations later on.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;INCAR&lt;/code&gt; and &lt;code&gt;KPOINTS&lt;/code&gt; are the general &amp;quot;settings&amp;quot; type files that would make it much easier to redo calculations and shouldn't be too memory intensive. But maybe you already have a set of scripts and made notes on certain parameter decisions that you could recreate the &lt;code&gt;INCAR&lt;/code&gt; and &lt;code&gt;KPOINTS&lt;/code&gt; files in line with the original calculations. Of course, if you forget these things, having the &lt;code&gt;INCAR&lt;/code&gt; and &lt;code&gt;KPOINTS&lt;/code&gt; around could serve as a good record for what calculations you did. The &lt;code&gt;POTCAR&lt;/code&gt; file too has a similar role. I wouldn't save it unless you expect to update your set of &lt;code&gt;POTCAR&lt;/code&gt;s - then it would be important to have a reference of which &lt;code&gt;POTCAR&lt;/code&gt;s you used at the point when you performed those calculations.&lt;/li&gt;&#xA;&lt;li&gt;I would personally not keep files like the &lt;code&gt;WAVECAR&lt;/code&gt; that would be useful for pre-convergence but relatively memory-intensive. But of course, if getting the converged wavefunctions was especially difficult and computationally expensive, maybe it might be a good idea to keep it and spare you from the pain of repeating the full calculation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Hope someone else can add on if I missed any crucial files.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-06-14T05:11:17.207" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11114" PostTypeId="2" ParentId="11104" CreationDate="2023-06-14T06:47:00.327" Score="3" Body="&lt;p&gt;The error message states&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Interaction energies&lt;/p&gt;&#xA;&lt;p&gt;Attention: monomers are not optimized&lt;/p&gt;&#xA;&lt;p&gt;Interaction energies are not physical&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This suggests that the interaction energy is computed as &lt;code&gt;E(interaction) = E(aggregate) - sum[E(monomer)]&lt;/code&gt;. The true interaction energy is the difference of the optimized aggregate to the optimized monomers. Looking into the source code, this warning arises at&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/grimme-lab/xtb/blob/0e66cab758133bcaa6ea2bb59012a1603166e6fd/src/docking/search_nci.f90#L964&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/grimme-lab/xtb/blob/0e66cab758133bcaa6ea2bb59012a1603166e6fd/src/docking/search_nci.f90#L964&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The warning appears to be issued always, suggesting that it is just to inform you that the interaction energy estimates are not accurate.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-14T06:47:00.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11115" PostTypeId="2" ParentId="11076" CreationDate="2023-06-14T08:02:15.363" Score="4" Body="&lt;p&gt;In the general case, we have lattice vectors &lt;span class=&quot;math-container&quot;&gt;${\bf L}_{i}$&lt;/span&gt;, which may not be orthogonal. With periodic boundary condition, a particle at &lt;span class=&quot;math-container&quot;&gt;${\bf r}$&lt;/span&gt; has periodic images at &lt;span class=&quot;math-container&quot;&gt;${\bf r}+n_1{\bf L}_1+n_2{\bf L}_2+n_3{\bf L}_3$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$n_1,n_2,n_3 \in \mathcal{Z}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The nearest image will be the image at the smallest distance, &lt;span class=&quot;math-container&quot;&gt;$\min_i {\bf L}_i$&lt;/span&gt;. If you have a cubic box, &lt;span class=&quot;math-container&quot;&gt;$L_1=L_2=L_3$&lt;/span&gt; and the particle has 6 nearest images corresponding to &lt;span class=&quot;math-container&quot;&gt;${\bf n}=(0,0,\pm 1)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;${\bf n}=(0,\pm 1,0)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf n}=(\pm 1,0,0)$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-14T08:02:15.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11116" PostTypeId="2" ParentId="11078" CreationDate="2023-06-14T08:16:03.040" Score="3" Body="&lt;p&gt;Computing interactions often requires determining the distances between the particles, &lt;span class=&quot;math-container&quot;&gt;$\Delta {\bf r}_{ij}={\bf r}_{i}-{\bf r}_{j}$&lt;/span&gt;. When periodic boundary conditions are employed, one needs to take into account the fact that the distance between the particles may be shorter when their periodic images are also taken into account.&lt;/p&gt;&#xA;&lt;p&gt;I explained periodic images and nearest images in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11115/142&quot;&gt;https://mattermodeling.stackexchange.com/a/11115/142&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The minimum image convention is simply an easy way to implement periodicity. Assuming cubic boundary conditions, you would simply compute the minimal distance along every direction. For instance, the minimum image convention along the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; axis is &lt;span class=&quot;math-container&quot;&gt;$-\frac 1 2 L_x \le (\Delta {\bf r}_{ij})_x &amp;lt; \frac 1 2 L_x$&lt;/span&gt;, which is achieved by adding or substracting &lt;span class=&quot;math-container&quot;&gt;$L_x$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; component of &lt;span class=&quot;math-container&quot;&gt;$\Delta {\bf r}_{ij}$&lt;/span&gt; the necessary number of times.&lt;/p&gt;&#xA;&lt;p&gt;The convention can also be used with non-orthorhombic cells; in that case, you just need to repeat the analysis with the non-orthogonal &lt;span class=&quot;math-container&quot;&gt;${\bf L}_i$&lt;/span&gt; vectors instead of the individual cartesian components.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-14T08:16:03.040" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11117" PostTypeId="1" AcceptedAnswerId="11147" CreationDate="2023-06-14T13:54:14.067" Score="6" ViewCount="460" Body="&lt;p&gt;I want to know the pros/cons of plane wave (PW) pseudopotential (PP) based DFT codes and all-electron full-potential linearised augmented-plane wave (FLAPW) DFT codes. In the title, I mentioned Quantum ESPRESSO (QE) and FLEUR for brevity, but my question is not just about them. On the one hand, I have &lt;em&gt;QE, VASP, Abinit, CASTEP&lt;/em&gt;, etc. and on the other hand, I have &lt;em&gt;Elk, FLEUR, WIEN2K&lt;/em&gt;, etc.&lt;/p&gt;&#xA;&lt;p&gt;A few aspects of comparison that I am interested in are their &lt;strong&gt;accuracy&lt;/strong&gt; in terms of band structure, band gap, charge density, etc. I am also interested in knowing if PP-based PW codes are substantially faster/slower than FLAPW-based DFT codes, i.e., their &lt;strong&gt;speed&lt;/strong&gt;. Lastly, I want to know how their computational complexity (or speed) &lt;strong&gt;scales&lt;/strong&gt; with the increasing size of the system.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-01-05T16:55:40.910" Title="What are some pros/cons of Quantum ESPRESSO and FLEUR?" Tags="|density-functional-theory|quantum-espresso|software|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11118" PostTypeId="1" CreationDate="2023-06-14T16:30:51.150" Score="4" ViewCount="290" Body="&lt;p&gt;I want to create a FCC structure using ASE (atomic simulation environment). I have define the all the required parameter correctly but at the time when i add GPAW calculator. The output of the program says that: &amp;quot;Atoms are too close&amp;quot;. Please comment on this where i'm wrong.&lt;/p&gt;&#xA;&lt;p&gt;Code&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;&#xA;a=4.0 # Lattice constant (in Angstroms)&#xA;&#xA;position=[(0,0,0), (0,0,a), (0,a,0), (a,0,0), (0,a,a), (a,0,a), (a,a,0),(a,a,a), (a/2,0,a/2), (a/2,a,a/2),&#xA;         (a/2,a/2,0),(a/2,a/2,a), (0,a/2,a/2),(a,a/2,a/2)]&#xA;&#xA;symbol=['Cu']*len(position)&#xA;fcc= Atoms(symbols=symbol, positions=position, cell=(a,a,a), pbc=True)&#xA;&#xA;view(fcc)&#xA;&#xA;print(fcc.symbols)        # Access atomic symbols&#xA;#print(fcc.positions)      # Access atomic positions&#xA;print(fcc.pbc)            # Access periodic boundary conditiom&#xA;print(fcc.get_distance(0,1))    # Access distance between Atom&#xA;print(fcc.get_masses())     # Access Mass of Atom&#xA;print(fcc.get_cell_lengths_and_angles())  #Access Cell length and Angles &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For Calculation&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from gpaw import GPAW, PW&#xA;&#xA;calc = GPAW()&#xA;fcc.set_calculator(calc)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7399" LastActivityDate="2023-07-10T14:14:40.147" Title="Copper FCC structure using ASE (Atomic Simulation Environment) library in python" Tags="|density-functional-theory|atomic-simulation-environment|atomistic-simulation|gpaw|computational-frameworks|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11119" PostTypeId="1" CreationDate="2023-06-14T17:31:02.813" Score="2" ViewCount="174" Body="&lt;p&gt;I am struggling with getting a correct band structure for even pristine graphene using SIESTA. The issue is almost certainly the K point path. My graphene sheet (128C atoms) isn't the traditional hexagonal cell. Here it is written in the &amp;quot;.fdf' style of siesta :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;LatticeConstant 19.7473282 Ang&#xA;&#xA;%block LatticeVectors&#xA;&#xA;  1.0000000   0.0000000   0.0000000&#xA;&#xA;  0.5000000   0.8666666   0.0000000&#xA;&#xA;  0.0000000   0.0000000   2.0255851&#xA;&#xA;&#xA;%endblock LatticeVectors&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And here is the Path I'm using&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;BandLinesScale pi/a&#xA;&#xA;%block BandLines&#xA;&#xA;1 0.0000 0.0000 0.0000 /Gamma&#xA;&#xA;30 1.1547005 0.0000 0.0000 M&#xA;&#xA;30 1.1547005 0.6667 0.0000 K&#xA;&#xA;30 0.0000 0.0000 0.0000 /Gamma&#xA;&#xA;%endblock BandLines&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone help me determine the proper k point path with the correct high symmetry points for this type of structure just to at least be able to reproduce the graphene band structure we observe in literature ?&lt;/p&gt;&#xA;&lt;p&gt;Let me just add that I've tried : More kpoints, better convergence criteria, different functionals and most other obvious solutions but I still can't get the proper band structure&lt;/p&gt;&#xA;" OwnerUserId="4274" LastEditorUserId="6687" LastEditDate="2023-06-14T17:38:45.253" LastActivityDate="2023-06-14T17:38:45.253" Title="Graphene Band Structure with SIESTA" Tags="|band-structure|electronic-structure|siesta|symmetry|k-points|" AnswerCount="0" CommentCount="6" ClosedDate="2023-12-19T15:38:55.977" ContentLicense="CC BY-SA 4.0" />
  <row Id="11120" PostTypeId="1" AcceptedAnswerId="11121" CreationDate="2023-06-14T18:06:35.827" Score="7" ViewCount="90" Body="&lt;p&gt;When using GPAW with the option &lt;code&gt;xc='LDA'&lt;/code&gt;, which of the potentials in &lt;a href=&quot;https://tddft.org/programs/libxc/functionals/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://tddft.org/programs/libxc/functionals/&lt;/a&gt; is used ? Or which combination of them? Is it &amp;quot;LDA_X&amp;quot; or or one of the &amp;quot;LDA_XC&amp;quot; ?&lt;/p&gt;&#xA;" OwnerUserId="5321" LastEditorUserId="142" LastEditDate="2023-06-16T11:26:55.343" LastActivityDate="2023-06-16T11:26:55.343" Title="What is just &quot;LDA&quot; in GPAW?" Tags="|exchange-correlation|gpaw|libxc|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11121" PostTypeId="2" ParentId="11120" CreationDate="2023-06-15T01:45:56.830" Score="4" Body="&lt;p&gt;According to &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/documentation/basic.html#exchange-correlation-functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;GPAW's documentation&lt;/a&gt;, GPAW would use its own LDA implementation, but if I interpret the table correctly, that should correspond to libxc's LDA_X + LDA_C_PW:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;h2&gt;Exchange-Correlation functional&lt;/h2&gt;&#xA;&lt;p&gt;Some of the most commonly used exchange-correlation functionals are listed below.&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;&lt;code&gt;xc&lt;/code&gt;&lt;/th&gt;&#xA;&lt;th&gt;full libxc keyword&lt;/th&gt;&#xA;&lt;th&gt;description&lt;/th&gt;&#xA;&lt;th&gt;reference&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;LDA&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;LDA_X+LDA_C_PW&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;Local density approximation&lt;/td&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;PBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;GGA_X_PBE+GGA_C_PBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;Perdew, Burke, Ernzerhof&lt;/td&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;revPBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;GGA_X_PBE_R+GGA_C_PBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;revised PBE&lt;/td&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;RPBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;GGA_X_RPBE+GGA_C_PBE&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;revised revPBE&lt;/td&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;PBE0&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;HYB_GGA_XC_PBEH&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;Known as PBE0&lt;/td&gt;&#xA;&lt;td&gt;5&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;&lt;code&gt;B3LYP&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;&lt;code&gt;HYB_GGA_XC_B3LYP&lt;/code&gt;&lt;/td&gt;&#xA;&lt;td&gt;B3LYP (as in Gaussian Inc.)&lt;/td&gt;&#xA;&lt;td&gt;6&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;&lt;code&gt;LDA&lt;/code&gt; is the default value. The next three ones are of generalized gradient approximation (GGA) type, and the last two are &lt;a href=&quot;http://en.wikipedia.org/wiki/Hybrid_functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;hybrid functionals&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For the list of all functionals available in GPAW see &lt;a href=&quot;https://wiki.fysik.dtu.dk/gpaw/devel/overview.html#overview-xc&quot; rel=&quot;nofollow noreferrer&quot;&gt;Exchange-correlation functionals module&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;GPAW uses the functionals from &lt;a href=&quot;https://tddft.org/programs/libxc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;libxc&lt;/a&gt; by default (except for LDA, PBE, revPBE, RPBE and PW91 where GPAW’s own implementation is used).&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(The last sentence is bolded by me for emphasis.)&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2023-06-15T01:45:56.830" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11122" PostTypeId="1" CreationDate="2023-06-15T03:48:05.657" Score="2" ViewCount="68" Body="&lt;p&gt;I have calculated the band structure of g-C3N4 monolayer using Quantum ESPRESSO (QE). The k-points i used was 4x4x1 and the cut-off energy of 60 Ry. First, I calculated it with the Generalized Gradient Approximation (GGA) (PBE) exchange-correlation functional using the Projector Augmented-Wave (PAW) method implemented in its pseudopotential. Second, I calculated it with hybrid Heyd-Scusseria-Ernzerhof (HSE) exchange-correlation functional and the PAW method, but using coarse nqx x nqy x nqz of 1x1x1. For calculation using HSE functional, after calculating scf, I used Wannier interpolation to get the band structure. This is the band structure I got using both exchange-correlation functionals.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uaqQO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uaqQO.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I got a desired band gap with HSE, which is in great agreement with experimental value of 2.7 eV. The calculation with HSE functional shows that the Fermi level is close to the conduction band, which is in agreement with the fact that g-C3N4 is an n-type semiconductor. I also compared it with &lt;a href=&quot;https://doi.org/10.1039/D1TA07286B&quot; rel=&quot;nofollow noreferrer&quot;&gt;previous literature&lt;/a&gt;, they also used the PBE functional. In contrast, they shown that the Fermi level position is close to the top of valence band which is shown in figure below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NAhbq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NAhbq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Which is right and which is wrong? How to overcome this problem?&lt;/p&gt;&#xA;" OwnerUserId="4827" LastActivityDate="2023-06-15T03:48:05.657" Title="The Fermi level position does not match up with previous calculation" Tags="|band-structure|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11124" PostTypeId="1" CreationDate="2023-06-15T04:56:46.220" Score="3" ViewCount="96" Body="&lt;h1&gt;Context&lt;/h1&gt;&#xA;&lt;p&gt;I am performing band structure calculations for bilayer graphene using QE codes. I used &lt;code&gt;X-crysden&lt;/code&gt; for the k-point mesh &lt;code&gt;3x3x1&lt;/code&gt; with &lt;code&gt;50&lt;/code&gt; points along each &lt;code&gt;k-path (gG-K-M-gG)&lt;/code&gt;. My graphene sheet (&lt;code&gt;148C&lt;/code&gt;) isn't a traditional cell. I used a &lt;code&gt;2x2x1&lt;/code&gt; supercell. In the band structure I uploaded, Fermi energy is adjusted to &lt;code&gt;0ev&lt;/code&gt;. My workflow is as follows-&lt;/p&gt;&#xA;&lt;p&gt;First I performed a relaxed calculation of the cell with 148C atoms with AA stacking of both layers having a separation of 1 Ang. Then, I performed the band calculation with an appropriate high symmetry path, after which I plotted the bands. @AbdulMuhaymin&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;enter code here&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Please guide me with the error.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pZLgr.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pZLgr.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;The bands do not meet at the k-point but at some other high symmetry point. Also if we zoom in a little there is a band gap that is clearly inconsistent.  Why do we observe such behavior?&lt;/p&gt;&#xA;" OwnerUserId="7402" LastEditorUserId="7402" LastEditDate="2023-06-16T04:00:29.617" LastActivityDate="2023-06-16T04:00:29.617" Title="Inconsistent band structure of bilayer graphene" Tags="|quantum-espresso|band-structure|electronic-structure|k-points|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-27T16:58:08.783" ContentLicense="CC BY-SA 4.0" />
  <row Id="11125" PostTypeId="1" AcceptedAnswerId="11128" CreationDate="2023-06-15T06:39:59.670" Score="2" ViewCount="41" Body="&lt;p&gt;initially, after optimization of the pristine molecule, I attached a few layers of electrodes to either side of the molecule to make a scattering region after optimization the electrodes will be re-arranged according to the molecule.&lt;/p&gt;&#xA;&lt;p&gt;my question is after the optimization of the scattering region how do I add new layers of electrodes to the optimized scattering region electrodes? should I replace these few layers of the electrode with new layers or do I have to add new electrode layers to it in order to maintain the potential of the electrode and molecule?&lt;/p&gt;&#xA;" OwnerUserId="6561" LastActivityDate="2023-06-15T09:34:35.580" Title="How to attach new layers of electrodes to the optimized molecular junction (molecule with few layers of electrode) scattering region" Tags="|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11126" PostTypeId="2" ParentId="11118" CreationDate="2023-06-15T07:16:46.163" Score="7" Body="&lt;p&gt;First, I want to show a general way of checking the minimum bond length of a structure in ASE. Using your structure as an example, you can get the distance matrix in ASE by &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms.get_all_distances&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;get_all_distances()&lt;/code&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;&#xA;a = 4.0 # Lattice constant (in Angstroms)&#xA;position = [(0,0,0), (0,0,a), (0,a,0), (a,0,0), (0,a,a), &#xA;            (a,0,a), (a,a,0),(a,a,a), (a/2,0,a/2), (a/2,a,a/2),&#xA;            (a/2,a/2,0),(a/2,a/2,a), (0,a/2,a/2),(a,a/2,a/2)]&#xA;symbol = ['Cu']*len(position)&#xA;atoms = Atoms(symbols=symbol, positions=position, cell=(a,a,a), pbc=True)&#xA;D = atoms.get_all_distances(mic=True) # Use minimum image convention for periodic systems&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you can get the minimum pairwise distance by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;mask = np.ones(D.shape, dtype=bool)&#xA;np.fill_diagonal(mask, 0)&#xA;dmin = D[mask].min()&#xA;print(dmin)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And you will see the minimum bond length of your structure is 0. Why is that? Because you are using 14 atoms instead of 4 atoms for a conventional fcc unit cell, and there are many atoms overlapping with each other. Remember your cell have periodicity in all 3 dimensions.&lt;/p&gt;&#xA;&lt;p&gt;The easiest way to build a valid fcc Cu bulk structure given the lattice constant is by using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/build.html#ase.build.bulk&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.build.bulk&lt;/code&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import bulk&#xA;&#xA;atoms = bulk('Cu', 'fcc', a=4.0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-10T07:13:28.827" LastActivityDate="2023-07-10T07:13:28.827" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11127" PostTypeId="2" ParentId="11035" CreationDate="2023-06-15T07:49:51.750" Score="1" Body="&lt;p&gt;I used the exact same input CIF file your provided and it worked successfully on my machine. This is the command I gave to my machine:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-sh prettyprint-override&quot;&gt;&lt;code&gt;abdul@ubuntu20:~/tmp$ cif2cell your_cif_file.cif &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It gave me the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CIF2CELL 2.0.0&#xA;2023-06-15 10:45&#xA;Output for None&#xA;&#xA; BIBLIOGRAPHIC INFORMATION&#xA;Failed to get author information, No journal information &#xA; INPUT CELL INFORMATION&#xA;Symmetry information:&#xA;Orthorhombic crystal system.&#xA;Space group number     : 59&#xA;Hall symbol            : -P 2ab 2a&#xA;Hermann-Mauguin symbol : Pmmn:2&#xA;&#xA;Lattice parameters:&#xA;          a           b           c &#xA;  2.7061000   4.4190100   4.6871000 &#xA;      alpha        beta       gamma &#xA; 90.0000000  90.0000000  90.0000000 &#xA;Representative sites :&#xA;Atom           a1          a2          a3 &#xA;Fe      0.2500000   0.2500000  -0.0833300&#xA;Al      0.2500000   0.7500000   0.5833300&#xA;&#xA; OUTPUT CELL INFORMATION&#xA;Symmetry information:&#xA;Orthorhombic crystal system.&#xA;Space group number     : 59&#xA;Hall symbol            : -P 2ab 2a&#xA;Hermann-Mauguin symbol : Pmmn:2&#xA;&#xA;Bravais lattice vectors :&#xA;  1.0000000   0.0000000   0.0000000 &#xA;  0.0000000   1.6329810   0.0000000 &#xA;  0.0000000   0.0000000   1.7320498 &#xA;All sites, (lattice coordinates):&#xA;Atom           a1          a2          a3 &#xA;Fe      0.2500000   0.2500000   0.9166700&#xA;Fe      0.7500000   0.7500000   0.0833300&#xA;Al      0.2500000   0.7500000   0.5833300&#xA;Al      0.7500000   0.2500000   0.4166700&#xA;&#xA;Unit cell volume  :  56.0496681 A^3&#xA;Unit cell density :   2.9554502 u/A^3 =  33.1183931 g/cm^3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I installed &lt;code&gt;cif2cell&lt;/code&gt; using pip3 by running the command:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;abdul@ubuntu20:~/tmp$ pip install cif2cell&lt;/code&gt;. I am using Python 3.8.10.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-06-15T07:49:51.750" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11128" PostTypeId="2" ParentId="11125" CreationDate="2023-06-15T08:14:11.080" Score="0" Body="&lt;p&gt;It depends on what you want to achieve.&lt;/p&gt;&#xA;&lt;p&gt;In TranSiesta there are 1 + number of electrodes calculations.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The electrodes are so-called &amp;quot;pristine electrodes&amp;quot;, or &amp;quot;bulk electrodes&amp;quot; and constitute the electronic structure that is used for&#xA;the self-energies etc.&lt;/li&gt;&#xA;&lt;li&gt;then the device calculation which makes use of the pristine electrodes&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The basic principle of NEGF calculations is that the potential at the electrode regions in the device calculation corresponds with the bulk potential of the pure electrode calculations. If this is not obeyed you'll get wrong results.&lt;/p&gt;&#xA;&lt;p&gt;Basically you should increase the number of layers towards the electrodes until convergence (electrostaticly) has been reached. This is not simple to test, but a good indication is that your properties of interest does not change when you add more electrode layers.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, the electrode layers (in the device region) that correspond to the bulk electrodes should have &lt;em&gt;exactly&lt;/em&gt; the same relative coordinates as the pristine electrode calculation.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-06-15T09:34:35.580" LastActivityDate="2023-06-15T09:34:35.580" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11130" PostTypeId="1" CreationDate="2023-06-15T11:27:59.620" Score="4" ViewCount="890" Body="&lt;p&gt;How to choose the value of &lt;code&gt;nbnd&lt;/code&gt; in quantum espresso&#xA;and what is the difference between &lt;code&gt;occupations = &amp;quot;fixed&amp;quot;&lt;/code&gt; and  &lt;code&gt;occupations = &amp;quot;smearing&amp;quot;&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2023-06-15T19:29:16.717" LastActivityDate="2023-06-15T19:29:16.717" Title="How to choose the value of nbnd in Quantum ESPRESSO?" Tags="|quantum-espresso|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11131" PostTypeId="2" ParentId="10739" CreationDate="2023-06-15T12:39:37.470" Score="2" Body="&lt;p&gt;Whenever you stack two or more materials with different cell parameter, you have to create a commensurate supercell.&#xA;In most cases the supercell will not exactly commensurate with all the materials and some stress will remain in at least one of the materials.&#xA;The supercell used, as well as which of the materials to strain and to what extent is a choice that you have to make for you calculation as there is, strictly speaking, no universally correct answer.&lt;/p&gt;&#xA;&lt;p&gt;As a rule of thumb it is common to assume that the less overall strain the better, so with this criterion in mind the structure with &lt;span class=&quot;math-container&quot;&gt;$0.02\%$&lt;/span&gt; mismatch is the best choice.&#xA;Often the computational resources limit the amount of atoms/electrons that you can calculate, so you should make sure that your resources are suitable for the less strained (and thus usually larger) supercell.&#xA;Furthermore, even for structures with higher strain, you can choose the cell parameter to strain only the graphene, only the h-BN or to strain both layers.&#xA;Nevertheless, the &amp;quot;correct&amp;quot; answer may also depend on the physics that you are interested in researching.&lt;/p&gt;&#xA;&lt;p&gt;As for which structure is obtained experimentally - this is also an open question, as you will find experimental references for many stackings (besides the link in the question, a simple search finds &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/nl303760m&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://www.nature.com/articles/ncomms13168&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and of course many more).&#xA;Once more the answer can depend on the physics that you are interested in.&lt;/p&gt;&#xA;&lt;p&gt;It might help to compare your stackings and supercells to previously published calculations. For example &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0038109816300680&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; some stackings and twist angles are shown and the effect on the band structure, DOS, and more is explored.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2023-06-15T12:39:37.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11132" PostTypeId="2" ParentId="11130" CreationDate="2023-06-15T12:55:18.923" Score="2" Body="&lt;p&gt;nbnd is the number of valence orbitals/bands your system has. As for the occupations smearing is a mathematical tool which 'smears' out the band energy diagram as in changes the occupation number to do convergence of energy. For fixed no such things happen and occupations is set to fixed.&lt;/p&gt;&#xA;&lt;p&gt;I'd suggest read &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S2352492820326064&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; to see the effect of different type of smearing. And also ref &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/3582&quot;&gt;this&lt;/a&gt; for more info on smearing&lt;/p&gt;&#xA;" OwnerUserId="7073" LastActivityDate="2023-06-15T12:55:18.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11133" PostTypeId="2" ParentId="11130" CreationDate="2023-06-15T13:22:07.973" Score="2" Body="&lt;p&gt;I am only answering the &lt;code&gt;nbnd&lt;/code&gt; part. If I can I will later edit this and add the &lt;code&gt;smearing&lt;/code&gt; part too. Kindly note that it's usually encouraged to ask one question per post. You might want to consider asking the smearing question in a separate post.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;nbnd&lt;/code&gt; specifies the number of bands to be calculated. So, the band structure with &lt;code&gt;nbnd=20&lt;/code&gt; would be more dense (there will be more band lines) than the one with &lt;code&gt;nbnd=10&lt;/code&gt;. It should be selected depending on the type of your &lt;em&gt;material&lt;/em&gt;, and depending on the type of your &lt;em&gt;calculation&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For spin-unpolarized (i.e. regular) calculations: if your material is an insulator, &lt;code&gt;nbnd&lt;/code&gt; should at least be equal to the number of valence bands (i.e., the number of electrons / 2). If your material is a metal, then 20% more than the number of valence bands should be chosen (minimum 4 more) [&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm277&quot; rel=&quot;nofollow noreferrer&quot;&gt;source&lt;/a&gt;].&lt;/p&gt;&#xA;&lt;p&gt;For spin-polarized calculation, a useful rule of thumb is to double the number of bands. Since we consider both spin‐up and spin‐down of an electron, the number of Kohn‐Sham states, i.e., &lt;code&gt;nbnd&lt;/code&gt; should be selected more than twice the number of electrons [1].&lt;/p&gt;&#xA;&lt;p&gt;[1] &lt;em&gt;Hung, Nguyen Tuan; Nugraha, Ahmad R. T.; Saito, Riichiro&lt;/em&gt;, &lt;a href=&quot;https://doi.org/10.1201/9781003290964&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;Quantum ESPRESSO course for solid-state physics&lt;/strong&gt;&lt;/a&gt;,  &lt;a href=&quot;https://zbmath.org/?q=an:07655576&quot; rel=&quot;nofollow noreferrer&quot;&gt;ZBL07655576&lt;/a&gt;. Page 133.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-06-15T13:22:07.973" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11134" PostTypeId="1" CreationDate="2023-06-15T16:57:44.543" Score="3" ViewCount="165" Body="&lt;p&gt;I am running through a QE tutorial with silicon. The first half is using mostly pw.x and everything was working great. However when I started the part on band-structure I ran into this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ /home/qe-7.1/bin/bands.x &#xA;bash: /home/qe-7.1/bin/bands.x: No such file or directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is not a path problem since pw.x works fine with that path. I took a look at the bin directory and found&lt;a href=&quot;https://i.stack.imgur.com/RtPID.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RtPID.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt; which shows no bands.x.&#xA;Where is it? I installed a while back and did the full install as far as I know. I think there are other missing .x files too.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way I can get the missing bands.x et al. without doing a complete do-over install? Any ideas why I don't have bands.x to begin with?&lt;/p&gt;&#xA;&lt;p&gt;Using Ubuntu 20.04.&lt;/p&gt;&#xA;" OwnerUserId="7406" LastActivityDate="2023-06-15T18:39:07.743" Title="missing bands.x in Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11135" PostTypeId="1" CreationDate="2023-06-15T18:00:25.117" Score="1" ViewCount="107" Body="&lt;p&gt;I need help on how to set &lt;code&gt;Tdamping&lt;/code&gt; in MD simulation. In Lammps documentation it is mentioned that the typical value is 100 for nvt, but when I put this value to my system which contain 46750 atoms at 500 K it give me error like bond atom is missing but when I use smaller system with 300 K is going works well.&lt;/p&gt;&#xA;&lt;p&gt;What is the reason for such a behaviour ?&lt;/p&gt;&#xA;" OwnerUserId="7405" LastEditorUserId="6687" LastEditDate="2023-07-28T04:59:49.500" LastActivityDate="2023-07-28T04:59:49.500" Title="Temperature damping parameter in lammps" Tags="|molecular-dynamics|lammps|polymers|water|temperature|" AnswerCount="0" CommentCount="1" ClosedDate="2023-09-17T23:25:29.787" ContentLicense="CC BY-SA 4.0" />
  <row Id="11136" PostTypeId="1" CreationDate="2023-06-15T18:13:27.873" Score="2" ViewCount="27" Body="&lt;p&gt;How can I calculate the Poisson's ratio of graphene monolayer, where I got the in-plane stiffness along the x-axis? most of the papers use this equation&lt;/p&gt;&#xA;&lt;p&gt;ES = b1Ꜫx2 + b2Ꜫy2 + b3ꜪxꜪy&lt;/p&gt;&#xA;&lt;p&gt;to calculate the Poisson's ratio beside they plot this diagram, so how can I get this diagram?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7TkjP.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7TkjP.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7312" LastActivityDate="2023-06-15T18:13:27.873" Title="how can I calculate Poisson's ratio of graphene monolayer (2D material)" Tags="|elasticity|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11137" PostTypeId="2" ParentId="11134" CreationDate="2023-06-15T18:39:07.743" Score="1" Body="&lt;p&gt;Try to &lt;code&gt;locate bands.x&lt;/code&gt; if that doesn't work then do a reinstall with all of the perquisites&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Install gcc and gfortran:&#xA;&#xA;                  sudo apt install gcc&#xA;&#xA;                  sudo apt install gfortran&#xA;&#xA;Install required libraries&#xA;&#xA;                  sudo apt install --no-install-recommends \&#xA;&#xA;                  libopenmpi-dev \&#xA;&#xA;                  libscalapack-openmpi-dev \&#xA;&#xA;                  libelpa17&#xA;&#xA;&#xA;                  sudo apt install mpich&#xA;&#xA;Also , Install&#xA;&#xA;                sudo apt install --no-install-recommends \&#xA;&#xA;                autoconf \&#xA;&#xA;                build-essential \&#xA;&#xA;                ca-certificates \&#xA;&#xA;                libblas3 \&#xA;&#xA;                libc6 \&#xA;&#xA;                libfftw3-dev \&#xA;&#xA;                libgcc-s1 \&#xA;&#xA;                liblapack-dev \  wget&#xA;&#xA;Get quantum espresso version of your choice and unpack&#xA;&#xA;                wget https://gitlab.com/QEF/q-e/-/archive/qe-6.5/q-e-qe-6.5.tar.gz&#xA;&#xA;                tar -xvzf q-e-qe-6.5.tar.gz&#xA;&#xA;                cd qe-6.5&#xA;&#xA;&#xA;Configure and make&#xA;&#xA;               ./configure --enable-parallel&#xA;&#xA;               make pw&#xA;&#xA;               make pp&#xA;&#xA;               Or make all &#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7073" LastActivityDate="2023-06-15T18:39:07.743" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11138" PostTypeId="1" CreationDate="2023-06-15T19:34:33.190" Score="4" ViewCount="87" Body="&lt;p&gt;There are SMILES that represent reactions happening (e.g. &lt;code&gt;C=C.O&amp;gt;&amp;gt;CCO&lt;/code&gt; representing water addition to ethylene). And I know that there are atom-mapping softwares available from molecule sketchers (ChemAxon, ChemDraw) and also from neural networks (rxnmapper published by Schwaller). However, these mappers seem to work only by mapping the SMILES (i.e. 2D connectivity)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a mapping algorithm, or a way to generate properly atom-mapped 3D geometries (xyz) from SMILES for both reactants and products that can be used e.g. to start an NEB calculation?&lt;/strong&gt; In NEB for instance the ordering of atoms is very important, so if the mapping is not right, then the calculation will run into issues. It is easy to imagine a scenario where 2D mapping is correct but 3D mapping isn't: a benzene ring attached to a functional group can have two orientations (due to the local symmetry of the ring). If the orientation is not the same in reactant and product then NEB will consider the rotation of the ring as part of the reaction. (It also applies to other double-ended TS search methods like pyGSM).&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-07-02T04:12:32.510" Title="Is it possible to generate atom-mapped xyz files from reaction SMILES for NEB?" Tags="|geometry|transition-state|smiles|nudged-elastic-band|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11139" PostTypeId="1" AcceptedAnswerId="11151" CreationDate="2023-06-15T23:48:53.410" Score="2" ViewCount="135" Body="&lt;p&gt;What is the &lt;strong&gt;minimum number of atoms&lt;/strong&gt; required to run a Monte Carlo simulation meaningfully?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-06-17T20:45:49.073" LastActivityDate="2023-06-17T20:45:49.073" Title="What is the minimum number of atoms required to run a Monte Carlo simulation meaningfully?" Tags="|computational-chemistry|molecular-modeling|monte-carlo|atomistic-simulation|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11140" PostTypeId="2" ParentId="9768" CreationDate="2023-06-16T02:43:28.520" Score="1" Body="&lt;p&gt;I find the answer just by reading this paper:&lt;a href=&quot;https://www.science.org/doi/epdf/10.1126/science.aav2873&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.science.org/doi/epdf/10.1126/science.aav2873&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/EMyMG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EMyMG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the simplest magnetic WSM, we just have two Weyl points, which are related by inversion symmetry, namely:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{P}\chi=-\chi.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the simplest nonmagnetic WSM, we have four Weyl points, in which we have:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{T} \chi = \chi .$$&lt;/span&gt;&#xA;Note that the different chirality &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; has been represented by different colors in the screenshot.&lt;/p&gt;&#xA;&lt;p&gt;For each Weyl point, it can be described by &lt;span class=&quot;math-container&quot;&gt;$\vec{k}\cdot\vec{\sigma}$&lt;/span&gt;, but we need to consider their copies due to the summation of &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; should be zero when we talk about the symmetry, as ProfM told.&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2023-06-16T02:43:28.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11141" PostTypeId="2" ParentId="9831" CreationDate="2023-06-16T02:58:08.790" Score="1" Body="&lt;ul&gt;&#xA;&lt;li&gt;The first part:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Eq.(1) manifest the conductivity &lt;span class=&quot;math-container&quot;&gt;$\sigma_{abc}$&lt;/span&gt; is a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-odd and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-odd tensor, which indicates that Eq.(1) can not appear in systems with &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry or &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetry. However, by Eq.(1), we find that &lt;span class=&quot;math-container&quot;&gt;$\sigma_{abc}$&lt;/span&gt; is a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-even tensor, which means this response relation is supported by systems&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;without &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetry but with the combined &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-symmetry.&lt;/li&gt;&#xA;&lt;li&gt;without &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetry as well as the combined &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}\mathcal{T}$&lt;/span&gt;-symmetry.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note that the odd and even means that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathcal{P}\sigma_{abc}=-\sigma_{abc},\mathcal{T}\sigma_{abc}=-\sigma_{abc},\mathcal{P}\mathcal{T}\sigma_{abc}=\sigma_{abc},$$&lt;/span&gt;&#xA;which can be easily derived just from the Eq.(1).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The second part:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It is easily shown that &lt;span class=&quot;math-container&quot;&gt;$\sigma^{SHE}_{abc}$&lt;/span&gt; is a &lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-even and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-even tensor. Therefore, Eq.(2) is supported by systems with/without &lt;span class=&quot;math-container&quot;&gt;$\mathcal{P}$&lt;/span&gt;-symmetry (&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt;-symmetry).&lt;/p&gt;&#xA;" OwnerUserId="1218" LastActivityDate="2023-06-16T02:58:08.790" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11142" PostTypeId="2" ParentId="11091" CreationDate="2023-06-16T07:08:58.990" Score="1" Body="&lt;p&gt;The issue has been resolved. It seems that it was caused by rounding the cell parameters to the sixth digit after decimal point instead of printing all 16 digits of it. (I was applying some strain and rounded it, never thought that such subtle differences would make such a huge impact)&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-06-16T07:08:58.990" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11143" PostTypeId="1" CreationDate="2023-06-16T08:30:13.757" Score="5" ViewCount="136" Body="&lt;p&gt;I used a 2x2x1 rectangular supercell of graphene to calculate the elastic properties (in-plane stiffness and Poisson’s ratio). The in-plane stiffness can be given by the following equation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$C^2D= \frac{1}{A_0} \frac{\partial^2 E_S}{\partial \epsilon ^2}$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$A_0$&lt;/span&gt; is the equilibrium area of the system, &lt;span class=&quot;math-container&quot;&gt;$E_S$&lt;/span&gt; corresponds to the energy difference between the total energy of the strained system from the unstrained system (i.e., at zero strain applied), and &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; is the uniaxial strain (&lt;span class=&quot;math-container&quot;&gt;$\epsilon = \frac{a − a_0}{a_0}$&lt;/span&gt;,  &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$a_0$&lt;/span&gt; being the lattice constant before and after deformation, respectively).&lt;/p&gt;&#xA;&lt;p&gt;The Poisson ratio, which is the ratio of the transverse strain to the axial strain&#xA;can be defined straightforwardly as &lt;span class=&quot;math-container&quot;&gt;$$\upsilon = \frac{-\epsilon_\text{transverse}}{\epsilon_\text{axial}}  = \frac{-\epsilon_{yx}}{\epsilon_x}$$&lt;/span&gt;&lt;br /&gt;&#xA;The model developed by Topsakal et al. (Ref. 1) was applied to calculate the elastic stiffness. A rectangular supercell with x and y axes along the armchair and zigzag directions, respectively, was used (as shown in Fig. below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cBkRe.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cBkRe.jpg&quot; alt=&quot;Rectangular supercell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;to calculate the elastic constant of the monolayer. The strains in two directions perpendicular to each other, Ꜫx (along the armchair direction) and Ꜫy (along the zigzag direction) were varied from -2.0% to 2.0% in an increment of 0.5%.&#xA;so I plotted the energy vs. strain as shown below&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Erf75.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Erf75.jpg&quot; alt=&quot;Energy vs strain&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I used this formula to calculate the elastic constant C11= (2/A0) (Es/Ꜫ2)&#xA;C11= 2(231.46)/A0&#xA;C11= 350 N/m&#xA;Now the question is how can calculate the in-plane stiffness and Poison’s ratio?&#xA;For more information, most researchers use this formula to calculate in-plane stiffness&#xA;E = b1Ꜫx2 + b2Ꜫy2 + b3ꜪxꜪy&#xA;and they have this diagram as shown below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/YusOR.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YusOR.jpg&quot; alt=&quot;Strain energy vs x/y uniaxial strain&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So how can I get this formula and the diagram?&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Topsakal, M.; Cahangirov, S.; Ciraci, S. The Response of Mechanical and Electronic Properties of Graphane to the Elastic Strain. Applied Physics Letters, 2010, 96. &lt;a href=&quot;https://doi.org/10.1063/1.3353968.&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7312" LastEditorUserId="7" LastEditDate="2023-08-19T14:34:17.937" LastActivityDate="2023-09-22T17:00:55.140" Title="How can I calculate the in-plane stiffness and Poisson’s ratio of a graphene monolayer?" Tags="|elasticity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11144" PostTypeId="1" CreationDate="2023-06-16T12:27:11.350" Score="5" ViewCount="80" Body="&lt;p&gt;Lately, I've become quite intrigued by the recent advances in machine learning forcefields within the field of computational chemistry. I've developed a curiosity about training a simple forcefield on a transition metal bulk mono-element.&lt;/p&gt;&#xA;&lt;p&gt;I've been pondering the best approach to train the model. Initially, the idea that came to mind was training it on different volumes, elementary transformations (such as shear and strain), and normal modes (and combinations of these three).&lt;/p&gt;&#xA;&lt;p&gt;To gain more insights, I've been reading the literature, and it appears that various approaches are employed:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Training on completely random structures: There are different methods available, but the underlying result is that you predominantly train on structures that may not have experimental relevance and, in some cases, aren't physically plausible. One potential advantage is that your forcefield could become robust against diverse scenarios. However, the way I understand it, there is a possible accuracy tradeoff on important properties for real systems?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Training on Molecular Dynamics data of known systems (FCC here): This particular approach puzzles me a bit, as it seems to be the opposite of the previous one. Essentially, you train the model on correlated and biased data, often at a specific temperature. At first glance, this doesn't appear to be advantageous over randomly generated displacements (uncorrelated)?&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;At the moment, my training approach involves scanning different volumes and elementary transformations, while incorporating random displacements of varying intensities.&lt;/p&gt;&#xA;&lt;p&gt;Obviously, how to train is heavily system and potential dependent. I understand that this is quite a vague question. I would be grateful if someone could give me an insight, or (even better) correct me if I wrote anything wrong.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastEditorUserId="7" LastEditDate="2023-06-16T13:48:50.590" LastActivityDate="2023-06-20T13:35:29.853" Title="Training a ML forcefield on a simple bulk material" Tags="|forcefields|machine-learning|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11145" PostTypeId="1" CreationDate="2023-06-16T15:27:46.403" Score="4" ViewCount="163" Body="&lt;p&gt;I want to perform some MD including Li+ ions. Specifically I am interested in Li-TFSI (aka Lithium bis(trifluoromethanesulfonyl)imide).&lt;/p&gt;&#xA;&lt;p&gt;I tested both the ATB repository and LigParGen and neither can provide Li parameters.&lt;/p&gt;&#xA;&lt;p&gt;The calculation &lt;a href=&quot;https://atb.uq.edu.au/molecule.py?molid=1273328&quot; rel=&quot;nofollow noreferrer&quot;&gt;1273328&lt;/a&gt; on ATB fails since &lt;code&gt;Atom type 'LI' not currently supported by the ATB.&lt;/code&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/HwvnA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HwvnA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;On LigParGen there is no Lithium allowed &lt;code&gt;export BOSSdir=/var/www/html/ligpargen/apps/boss-4.9;/var/www/html/ligpargen/apps/anaconda2/bin/python2.7 /var/www/html/ligpargen/apps/ligpargenCode/Converter.py -s '[Li]' -r UNK -o 0 -c 0 &amp;gt; /tmp/errorServer.log&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried two smiles as &lt;code&gt;FC(F)(F)S(=O)(=O)N([Li])S(=O)(=O)C(F)(F)F&lt;/code&gt; and &lt;code&gt;[Li+][N-](S(=[O-])(=[O-])C(F)(F)F)S(=[O-])(=[O-])C(F)(F)F&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yI0Sd.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yI0Sd.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eywmX.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eywmX.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried also to search the Li related parameters into OPLS from &lt;a href=&quot;http://zarbi.chem.yale.edu/oplsaam.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Yale&lt;/a&gt; or in abmer but I couldn't find much. In amber I tried to run antechamber on my Li-TFSI.pdb input file, obtaining this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Warning: Unusual element (Li) for atom (ID: 16, Name: Li).&#xA;/Users/marcodigennaro/miniconda3/envs/lammps/bin/wrapped_progs/antechamber: Fatal Error!&#xA;GAFF does not have sufficient parameters for molecules having unusual&#xA;       elements (those other than H,C,N,O,S,P and halogens).&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: Do you know any Li parametrization to add to these force fields?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Many thanks&lt;/p&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-11-20T13:53:02.567" LastActivityDate="2023-12-20T02:08:06.293" Title="Include Li+ in force field for Molecular Dynamics" Tags="|molecular-dynamics|forcefields|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11146" PostTypeId="1" CreationDate="2023-06-16T21:43:26.757" Score="4" ViewCount="98" Body="&lt;p&gt;Basically I am trying to find the initial guess of an atomic charge density [rho(r)] v/s the radial distance r.&lt;/p&gt;&#xA;&lt;p&gt;Specifically I checked the &amp;quot;atomic pseudo charge-density&amp;quot; tag in the POTCAR file  assumed it to be the initial rho(r) but it had close to 1000 entries while the &amp;quot;grid&amp;quot; tag in the POTCAR file had merely 359 entries which did not make sense. Particularly I looked for the element Xe, but I realized it is the same for al elements.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2023-06-27T22:58:35.373" Title="What does the &quot;atomic pseudo charge-density&quot; in the POTCAR file stand for?" Tags="|density-functional-theory|vasp|pseudopotentials|conceptual-dft|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11147" PostTypeId="2" ParentId="11117" CreationDate="2023-06-16T22:09:54.423" Score="6" Body="&lt;p&gt;Your question is rather broad and the partial answers for the different aspects are quite complex. Maybe I can clarify some of them.&lt;/p&gt;&#xA;&lt;p&gt;In the DFT developer community one typically distinguishes between accuracy and precision. Accuracy is understood as a measure for the agreement between simulation results and experiments. This is in the end limited by the XC functional. Precision covers for a given XC functional the agreement between the simulation results with a certain code and the theoretically possible correct result. I assume that in your question you actually want to know something about precision.&lt;/p&gt;&#xA;&lt;p&gt;Here, FLAPW methods offer the chance to come very near to the theoretical optimum, because beyond the XC functional all other approximations in such methods can be controlled and reduced to have negligible precision effects. Pseudopotentials (and also basis sets that are not systematically convergable) are approximations that cannot be controlled in such a way. PW basis sets are systematically and very comfortably convergable. You actually only have a single convergence parameter there: An energy cutoff controlling the basis set size. For equation of states parameters, we published a reference dataset for the measurement of the achievable precision with specific DFT implementations together with results for different DFT codes / pseudopotentials. See &lt;a href=&quot;https://doi.org/10.1038/s42254-023-00655-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Nat. Rev. Phys. &lt;strong&gt;6&lt;/strong&gt;, 45–58 (2024)&lt;/em&gt;&lt;/a&gt; (open access) for details. This can be seen as a successor to the &amp;quot;Delta project&amp;quot;. In the supplementary part of that work you can also read for what kind of systems challenges for pseudopotentials are found.&lt;/p&gt;&#xA;&lt;p&gt;For band structure calculations you should be aware that DFT codes are typically constructed to calculate the charge density. This only relies on the occupied bands. In FLAPW codes you therefore have &amp;quot;energy parameters&amp;quot; around which a linearized description of the Kohn-Sham states takes place. These are chosen to get a good description of the occupied states and typically also provide a very nice description a few eV above the Fermi energy. If you want to also consider higher unoccupied states there is the option to extend the LAPW basis with local orbitals, i.e., additional basis functions that can be tailored to represent such states. In the construction of pseudopotentials one also plugs in the requirement that certain states (those required for the occupied states and a few more) are nicely represented. I don't know if people have mechanisms of extending the precision of pseudopotentials for Kohn-Sham states far above the Fermi energy. I am also not aware of studies demonstrating where the limits are.&lt;/p&gt;&#xA;&lt;p&gt;The charge densities from different methods differ. Especially the charge densities from pseudopotential codes represent artificial systems covering the valence electron states only. To some extend this may be overcome by using the PAW approach, but even this is typically used together with a frozen core electron approximation, so you will see differences from all-electron approaches when you take a close look. But, of course, you already see small differences within a class of methods, e.g., between FLAPW calculations from different codes and with different parametrizations or differences between FLAPW codes and other all-electron approaches. You will also see differences between different pseudopotential codes.&lt;/p&gt;&#xA;&lt;p&gt;With respect to performance both, pseudopotential PW codes and also FLAPW codes, are limited by the diagonalization of the eigenvalue problem. This scales cubically with the system size. However, PW codes typically have a larger basis set and thus also larger matrices. For the representation of the valence Kohn-Sham states they only need a small fraction of the eigenfunctions of the matrices and for this often iterative diagonalization algorithms are employed. These are efficient when only few eigenvalues / eigenfunctions are needed as they allow to skip an explicit construction of the whole Hamiltonian matrix in terms of the basis functions. FLAPW codes on the other hand have smaller matrices because the basis sets are also smaller. Here the diagonalization is typically done by direct eigensolvers, implying the need to construct the matrices explicitly. Another aspect is that PW codes employing norm-conserving pseudopotentials only have to deal with simple eigenvalue problems, while FLAPW codes come with generalized eigenvalue problems. Finally, in FLAPW codes there are some other computational kernels that scale cubically with the system size. Overall, I assume that PW codes are typically a little bit faster, but that depends on the unit cell and type of calculation. If you have many valence electrons per volume, the advantage of the iterative diagonalization schemes becomes smaller.&lt;/p&gt;&#xA;&lt;p&gt;With respect to calculation types, some calculations are possible in certain codes while they are not possible in other codes. For example, as far as I know, when you perform a calculation considering spin-orbit coupling (SOC), with QE you always perform a calculation for systems with noncollinear magnetism. This is computationally expensive. In FLEUR you can also calculate SOC for nonmagnetic systems (e.g. for the Rashba effect) or systems with collinear magnetism (e.g. for calculating the magnetocrystalline anisotropy). Another difference shows up when you perform calculations on thin film systems. In PW codes this can only be done in terms of periodic slab calculations, i.e., you introduce a large vacuum region in the unit cell. This increases the number of needed basis functions. In FLEUR one has the possibility to set up a 2D geometry which does not come with increased basis set sizes.&lt;/p&gt;&#xA;&lt;p&gt;The difference in calculation modes, however, is only partially related to the comparison between PP-PW codes and FLAPW codes. Even within a certain approach different codes may offer different options on what type of calculations can be performed. To my knowledge, for example no other FLAPW code at the moment offers the 2D geometry that FLEUR offers for thin film systems. Also for different FLAPW codes the performance characteristics may be slightly different. You can think of FLAPW codes as codes employing some basis set from a family of basis sets. In Wien2k typically an APW+lo basis set is used. In FLEUR most calculations are performed with a conventional LAPW basis set.&lt;/p&gt;&#xA;&lt;p&gt;As final points let me mention that independent of possible uses of these codes on laptops or workstations, both, QE and FLEUR, are part of the &lt;a href=&quot;http://www.max-centre.eu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MaX collaboration&lt;/a&gt;. All codes in this collaboration have been refactored and tuned for extreme parallelization scaling on large supercomputers. When it comes to very large unit cells that require a large-scale parallelization of the DFT calculation, such codes may offer advantages in comparison to other codes of the same approach that might not have been developed for such use cases. Also, getting near to the achievable performance of such codes requires some experience from the user: The codes have to be compiled in a smart way and the employed parallelization scheme also has to be tailored for the specific calculation.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2024-01-05T16:55:40.910" LastActivityDate="2024-01-05T16:55:40.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11148" PostTypeId="2" ParentId="11117" CreationDate="2023-06-17T13:31:01.383" Score="4" Body="&lt;p&gt;The previous answer is really well formulated, is complete and has quantitative arguments. The main difference between these codes is the basis-set and how it is managed along with the potential. The approximations for the exchange-correlation functional are well-known and are implemented similarly.&lt;/p&gt;&#xA;&lt;p&gt;As they solve the same equation (KS), which is also an approximation. Stricly speaking, there is no code more accurate than another one for the same basis-set. If your PP is well defined and you use a large basis-set a PW code could match the results of a LAPW code. When a code is fast, it is always at the expense of the accuracy while solving this equation.&lt;/p&gt;&#xA;&lt;p&gt;Band structure, charge density, band gap are related to how the calculation is made. Normally a LAPW code is better for a small unit cell to get rid of errors arising from a wrongly parameterized pseudo potential. But as it includes core electrons, the calculation is really slow for large systems, you can look for some plots of the mean calculation time vs the number of electrons.&lt;/p&gt;&#xA;&lt;p&gt;I have personally used the cited codes, the results are quite similar for LAPW codes, PW codes results depend strongly on the PP. Note that depending how they are parametrized, the results can be quite accurate for some of them, this accuracy for a specific system is not always transferable. The user should not try to find experimental results using a DFT code, this is a very naive behaviour and a source of inconsistencies.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-06-17T13:31:01.383" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11149" PostTypeId="2" ParentId="11139" CreationDate="2023-06-17T16:15:57.547" Score="2" Body="&lt;p&gt;The literal answer to the question you asked is zero. That might not be the answer you were looking for, but then again, you're asking too general a question to get a meaningfully specific answer. &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9128/671&quot;&gt;About a year ago&lt;/a&gt; I tried to tell you that &lt;a href=&quot;https://en.wikipedia.org/wiki/Monte_Carlo_method&quot; rel=&quot;nofollow noreferrer&quot;&gt;Monte Carlo simulation&lt;/a&gt; is a name for a broad set of general mathematical techniques for stochastic simulations that use random sampling. I'll try again. Monte Carlo simulation is very general, and does not have anything intrinsically to do with atoms at all, &lt;em&gt;unless&lt;/em&gt; you're applying it to some system of atoms. In particular, Monte Carlo methods are commonly applied in particle physics to cases where all simulated particles are subatomic (as pointed out by Shern Ren Tee in a comment), in entirely abstract math problems such as random walks and numerical optimization problems where atoms are irrelevant, and in a variety of applications like simulations of traffic flow and galaxy distribution where the (numbers of) atoms in the simulated entities are abstracted away entirely.&lt;/p&gt;&#xA;&lt;p&gt;Now, the lowest meaningful number of simulated particles (be they atoms, galaxies or quarks) depends on what you're trying to simulate. For example, one-particle Monte Carlo methods are often used in modeling of electron transport, diffusion through obstructed media, and low-count responses of particle detectors. If you want to model systems with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;-body interactions between particles, you'll want at least &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; particles in your simulation in order to minimally capture the effect of the interaction. In matter modeling, we are often interested in interactions with &lt;span class=&quot;math-container&quot;&gt;$n=2$&lt;/span&gt;, but there are many exceptions with &lt;span class=&quot;math-container&quot;&gt;$n&amp;gt;2$&lt;/span&gt;. In addition, the description of qualitative features such as magnetic configurations and charge patterns requires the number of particles to be at least equal to the size of the repeated pattern.&lt;/p&gt;&#xA;&lt;p&gt;However, in many cases of relevance to matter modeling that answer isn't very helpful except for testing one's code. Unless you're actually interested in a system with that few particles, you really should do a finite-size scaling analysis since many properties do depend on the number of particles. In case you're dealing with a confined nanoscale system, for example, there is a finite upper limit to how far you can scale the simulation. Often, however, you might be trying to describe a thermodynamically large system with an infinite number of particles, using finite-size simulations. In that case, look at how intensive quantities like the energy density depend on the system size. Are they converged to within your desired tolerance? If not, you can choose to simulate increasingly larger systems, or do extrapolations. Either way, the system size you'll need for saying something meaningful (and with reasonable error bars) about the system in the thermodynamic limit is non-universal.&lt;/p&gt;&#xA;" OwnerUserId="671" LastActivityDate="2023-06-17T16:15:57.547" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11150" PostTypeId="1" CreationDate="2023-06-17T19:21:22.480" Score="2" ViewCount="77" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$k_r=2.88\times10^{-9}n^2\langle\tilde{v}\rangle_\text{av}^2 \int\varepsilon_{\tilde{v}}d\tilde{v}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$f=4.32\times10^{-9}\int\varepsilon_{\tilde{v}}d\tilde{v}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I plan to use the above equations to calculate the lifetime &lt;span class=&quot;math-container&quot;&gt;$k_r$&lt;/span&gt; of a fluorescent molecule. I need to calculate the oscillator strength &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; in the 2nd equation, but I don't understand how to use the equation used to calculate the oscillator strength.&lt;/p&gt;&#xA;" OwnerUserId="7416" LastEditorUserId="7" LastEditDate="2023-06-21T01:07:32.157" LastActivityDate="2023-06-21T01:07:32.157" Title="Determination of fluorescence lifetime by using oscillator strength?" Tags="|computational-chemistry|molecular-modeling|electronic-structure|spectroscopy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11151" PostTypeId="2" ParentId="11139" CreationDate="2023-06-17T19:48:00.767" Score="2" Body="&lt;p&gt;I used a &lt;a href=&quot;https://arxiv.org/abs/2006.14956&quot; rel=&quot;nofollow noreferrer&quot;&gt;Monte Carlo method called FCIQMC&lt;/a&gt; to calculate the &lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;nofollow noreferrer&quot;&gt;ionization energy of the carbon atom with unprecedented precision&lt;/a&gt;. Therefore, MC methods can be used for a &lt;strong&gt;single isolated atom.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The answer to the question depends on the &lt;em&gt;&lt;strong&gt;type of Monte Carlo method in which you are interested.&lt;/strong&gt;&lt;/em&gt; Monte Carlo methods are also used by particle physicists to study sub-atomic physics (zero atoms).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;At least 15 different &amp;quot;quantum&amp;quot; Monte Carlo&lt;/strong&gt; methods were listed here:&#xA;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1594/5&quot;&gt;What are the types of Quantum Monte Carlo?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Based on &lt;a href=&quot;https://mattermodeling.stackexchange.com/search?q=user:3990+%5Bmonte-carlo%5D&quot;&gt;your 14 questions&lt;/a&gt; with the &lt;a href=&quot;/questions/tagged/monte-carlo&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;monte-carlo&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;monte-carlo&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-monte-carlo-tooltip-container&quot;&gt;monte-carlo&lt;/a&gt; tag, it looks like you're interested in Monte Carlo methods for classical mechanical modeling rather than quantum mechanical modeling, so I'll mention that there's even more Monte Carlo methods used in Matter Modeling than what is listed in the above-mentioned QMC thread.&lt;/p&gt;&#xA;&lt;p&gt;Before asking further questions about Monte Carlo calculations, I recommend that you consider the following two questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;&lt;strong&gt;What precisely am I simulating?&lt;/strong&gt;&lt;/em&gt; (e.g. &amp;quot;I'm calculating thermodynamic properties of a protein with 100 amino acids via an ensemble average, as described in this question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/3610/5%22&quot;&gt;https://mattermodeling.stackexchange.com/q/3610/5&amp;quot;&lt;/a&gt; ).&lt;/li&gt;&#xA;&lt;li&gt;&lt;em&gt;&lt;strong&gt;What specific Monte Carlo method am I using?&lt;/strong&gt;&lt;/em&gt; (e.g. FCIQMC).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-06-17T20:44:44.393" LastActivityDate="2023-06-17T20:44:44.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11152" PostTypeId="1" CreationDate="2023-06-18T05:01:23.983" Score="2" ViewCount="85" Body="&lt;p&gt;Just getting into RASPA (&lt;a href=&quot;https://github.com/iRASPA/RASPA2&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/iRASPA/RASPA2&lt;/a&gt;). I need to generate forcefields, I would like to use UFF (Universal Force Field), how do I go about doing this?&lt;/p&gt;&#xA;" OwnerUserId="6958" LastActivityDate="2023-06-18T05:01:23.983" Title="How to generate force-fields for RASPA2?" Tags="|monte-carlo|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11153" PostTypeId="1" CreationDate="2023-06-18T09:17:30.170" Score="4" ViewCount="67" Body="&lt;p&gt;Some salt (&lt;span class=&quot;math-container&quot;&gt;$\ce{NaCl}$&lt;/span&gt; or another one) of &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; grams is dissolved in some water of &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; liters. After mixing up, the substance looks transparent or to put it more exact as a chemical solution. Then a thread of &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; meters is placed in the substance for the chemical precipitation. The problem is to calculate the velocity of the precipitation and an on-velocity influence of a kind of matter of which the thread was made.&lt;/p&gt;&#xA;&lt;p&gt;What kinds of calculations have to execute for reaching this purpose?&#xA;Can the Quantum Espresso or LAMMPS be engaged for this?&#xA;Or is there something else more better for this purpose?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastEditorUserId="5403" LastEditDate="2023-06-21T10:27:56.603" LastActivityDate="2023-06-21T10:27:56.603" Title="What kinds of calculations have to execute for obtaining the velocity of the chemical precipitation of some salt on a thread from a water-salt mix?" Tags="|quantum-espresso|computational-chemistry|ab-initio-calculations|lammps|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11154" PostTypeId="1" CreationDate="2023-06-18T09:47:56.813" Score="2" ViewCount="43" Body="&lt;p&gt;There are several types of Monte Carlo (MC) moves that can be used in simulations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Metropolis-Hastings&lt;/strong&gt;: a sampling technique used to generate a Markov chain of states with desired probabilities by accepting or rejecting proposed moves based on an acceptance probability.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Single Particle Displacement&lt;/strong&gt;: In this move, a single particle's position is randomly selected, and a small displacement is applied. The displacement can be along one or more dimensions.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Particle Exchange&lt;/strong&gt;: This move involves exchanging the positions of two randomly selected particles.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Particle Insertion/Deletion&lt;/strong&gt;: This move involves adding or removing a particle from the system.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;System Scaling&lt;/strong&gt;: In this move, the entire system is rescaled by a random factor. It can be used to simulate changes in density or to explore different system sizes.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Cluster Moves&lt;/strong&gt;: Cluster moves involve treating a group of particles as a single entity and moving them collectively.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Rotations&lt;/strong&gt;: Rotational moves involve rotating the orientation of a particle or a group of particles.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;etc.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;My question is, how do I know when to use which move? I.e. what factors determine the selection of a specific type of move?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-06-18T10:12:03.123" LastActivityDate="2023-06-18T10:12:03.123" Title="What factors determine the selection of a specific type of MC move?" Tags="|one-topic-per-answer|monte-carlo|atomistic-simulation|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11155" PostTypeId="1" AcceptedAnswerId="11193" CreationDate="2023-06-18T10:09:05.670" Score="3" ViewCount="107" Body="&lt;p&gt;I am investigating the mechanism of hydrogen transfer between a hydroperoxyl radical and an aromatic hydroxyl group donating it. The problem is that I cannot find transition state structure. So far, I've tried with &lt;code&gt;QST3&lt;/code&gt;, &lt;code&gt;QST2&lt;/code&gt; and &lt;code&gt;TS&lt;/code&gt; with initial geometries either based on similar reactants I'm studying or taken from the literature. In general - the angle between the hydroperoxyl radical and the hydroxyl group of the donor is about 165°, and the distances from the hydrogen atom are 1.358A and 1.076A, respectively.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/nUbDW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nUbDW.png&quot; alt=&quot;Initial structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;These failed despite changing the optimization algorithm, by:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;lowering &lt;code&gt;maxstep&lt;/code&gt; (even to 1);&lt;/li&gt;&#xA;&lt;li&gt;using &lt;code&gt;notrust&lt;/code&gt;;&lt;/li&gt;&#xA;&lt;li&gt;calculating force constants using &lt;code&gt;calcfc&lt;/code&gt; or only derivatives for the atoms involved (available in &lt;code&gt;modred&lt;/code&gt;).&lt;/li&gt;&#xA;&lt;li&gt;calculation of &lt;code&gt;calcfc&lt;/code&gt; coupled with an imposed hessian of -1 for both bonds&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The other way I tried to achieve my goal was to freeze the two bond and the angle, optimize the system, and only then reactivate them and run TS (with combinations of the above changes). No satisfactory results.&lt;/p&gt;&#xA;&lt;p&gt;The last thing I did was to perform the TS task at a lower level of theory. By default I use &lt;code&gt;M052X/6-311+G(d,p)&lt;/code&gt;, although I have checked &lt;code&gt;6-31+G(d)&lt;/code&gt;, &lt;code&gt;6-311G(d,p)&lt;/code&gt;, &lt;code&gt;6-31+G(d,p)&lt;/code&gt;, &lt;code&gt;6-311+G(d)&lt;/code&gt;, &lt;code&gt;6-31G(d,p)&lt;/code&gt;, but still without success.&lt;/p&gt;&#xA;&lt;p&gt;And now, after a long introduction, I come to the substance: I ran &lt;code&gt;scan&lt;/code&gt; at the desired level of theory. I set up the geometry similarly to the one shown above, although I reduced the bond length between the hydrogen atom and the hydroxyl group to 0.94 (typical for my systems in their ground state) simultaneously increasing the distance between the hydroperoxy oxygen and this hydrogen atom to about 2.0Å.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SicoV.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SicoV.png&quot; alt=&quot;scan&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I ran the simulation for 50 steps every -0.05Å and.... here a certain &lt;em&gt;problem&lt;/em&gt; arises. Following the literature and previous works, in such transition states the hydrogen atom is perpendicular to the oxygen of the aromatic hydroxyl group, while the hydroperoxy radical is parallel to the system in sandwich form. To be precise, it lies above/below it. Therefore, the initial structure was constructed this way. However, as a result of the scanning, the hydroperoxy radical shifts to completely the same plane, influencing the hydrogen to follow the same geometry.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q3hQ2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q3hQ2.png&quot; alt=&quot;incorrect scan &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The resulting energy scan suggests a barrier-free reaction, but due to the mentioned glitch I can't believe the outcomes. I tried lowering the &lt;code&gt;maxstep&lt;/code&gt; for the scan, and also doing an &lt;code&gt;calcfc&lt;/code&gt; (although I'm not sure if either of those two affect the &lt;code&gt;scan&lt;/code&gt; algorithm) though with the effect.&lt;/p&gt;&#xA;&lt;p&gt;I appreciate a solution to this issue. Or what are other options I can take to find a TS or energy scan that &lt;em&gt;really&lt;/em&gt; reflects the barrierless path of the process (which I think is more true in this particular case).&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-06-25T18:33:15.150" Title="How do you make sure the reaction is diffusion limited (Gaussian)?" Tags="|density-functional-theory|computational-chemistry|molecular-modeling|gaussian|transition-state|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11156" PostTypeId="1" CreationDate="2023-06-18T10:53:08.537" Score="2" ViewCount="66" Body="&lt;p&gt;The Ising model uses a lattice-based model as it is reasonable to simulate magnetic behavior in a solid.&lt;/p&gt;&#xA;&lt;p&gt;Is lattice-based Monte Carlo modeling used in the case of the simulation of gases and liquids (i.e., pure liquids, not crystalline liquids)? If yes, when?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="671" LastEditDate="2023-06-19T17:32:41.927" LastActivityDate="2023-06-20T07:30:41.227" Title="Are lattice-based Monte Carlo simulations used in the case of liquids and gases?" Tags="|monte-carlo|model-hamiltonians|atomistic-simulation|2d-lattice|ising-model|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11157" PostTypeId="1" CreationDate="2023-06-18T11:36:57.950" Score="6" ViewCount="2025" Body="&lt;p&gt;I thought Python was a reasonably popular language among matter modelers.&lt;/p&gt;&#xA;&lt;p&gt;However, I saw a comment in one of my posted questions (in which I posted a Python code) that the commenter was unfamiliar with Python.&lt;/p&gt;&#xA;&lt;p&gt;What programming languages do matter modelers generally use? Is it FORTRAN?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-06-18T12:48:36.473" LastActivityDate="2023-06-19T10:16:49.523" Title="What programming language do matter modelers generally use?" Tags="|programming|" AnswerCount="3" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="11158" PostTypeId="2" ParentId="11157" CreationDate="2023-06-18T13:55:24.763" Score="10" Body="&lt;p&gt;I think, I saw similar questions on this stack exchange before, so you may also want to have a look at what others wrote about this topic. Let me answer this from the perspective of research software engineering and also based on my opinion (the answer to your question is, of course, subjective).&lt;/p&gt;&#xA;&lt;p&gt;You can see research software engineering as a general term for software engineering in an academic environment. This comes with several constraints: You have small and rapidly changing development teams (often consisting only of a single person with limited software development experience doing a PhD thesis), software projects with unclear duration and scope, a multitude of rather special hardware architectures and software environments that may change over the duration of a project, specific (software development) expertise in a research group, and so on.&lt;/p&gt;&#xA;&lt;p&gt;Such an environment narrows the number of reasonable options for the choice of programming languages. This may even be research-group or developer specific. From the perspective of hardware architectures and software environments, developers have more choices if they know beforehand that the program only has to run on their workstation or a similar computer.&lt;/p&gt;&#xA;&lt;p&gt;If the program has to run on multiple compute nodes of a high-performance computing machine there are - in connection to the available software environments - mostly 3 viable options for programming languages: Fortran, C, and C++. All of these languages have specific advantages and disadvantages. C++, for example, comes with a large standard library of data structures and algorithms and also with many language features. This makes for a very powerful tool, but also a tool that demands a lot of expertise from the developer to not mess up things. Fortran, on the other hand, is much simpler to learn and comes with a language structure that is simple to understand for developers and also for compilers. A student with limited programming experience working on a thesis has it easier to write good and fast code in Fortran. The choice here would thus depend a little bit on the skills of the developer and the skills that are available in the research group. Of course, the demands from the project also play a role here.&lt;/p&gt;&#xA;&lt;p&gt;When it comes to the development of toys, i.e., small test programs or prototypes, the automatization of workflows, or the preprocessing, postprocessing, and plotting of data, Python is a much more viable option, though the choice of programming language here also depends on the skills of the programmer. These applications are more likely to only run on a well-defined set of workstations and software-environments and the projects are typically smaller and have a more limited lifetime. Here, Python code may be more compact in comparison to many other languages and there are also many software libraries available that make the developer much more productive in such a setting. These many available software libraries, however, are both, an advantage and also a disadvantage. I saw several small, but very nice software projects die, because the associated &amp;quot;Python dependency hell&amp;quot; was not resolvable anymore after some time on another computer and for a different developer. Of course, there are measures to take care of this (for example docker containers) and also of problems arising from the dynamic interpretation of Python programs that may give the inexperienced programmer a syntax error after the program was running for hours or days. But a beginner programmer starts to address such problems only after they appear and then it may already be a little late.&lt;/p&gt;&#xA;&lt;p&gt;Of course, there are also many more programming languages that may be good choices, depending on the respective context. I think the most important part is that the developer makes a well-founded choice what language to use, based on all relevant circumstances. In my answer I wanted to sketch a little bit some of the special circumstances that may play a role here.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastEditorUserId="1256" LastEditDate="2023-06-19T07:45:22.633" LastActivityDate="2023-06-19T07:45:22.633" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="11159" PostTypeId="1" CreationDate="2023-06-18T14:34:07.377" Score="3" ViewCount="130" Body="&lt;p&gt;I am attempting to run SAPT0 calculations on dimer complexes with around 100 atoms each. However, PSI4 SAPT0 calculations freeze and get terminated with the following error messages - I assigned 48GB and then 96 GB of memory, however, the error persists. I wonder if anyone has suggestions on how to overcome this error?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PSIO_ERROR: unit = 97, errval = 12&#xA;terminate called after throwing an instance of 'psi::PsiException'&#xA;  what():  &#xA;Fatal Error: WRITE failed. Only some of the bytes were written!&#xA;Error writing a full page, unit 97.&#xA;PSIO_ERROR: 12 (error writing to file)&#xA;&#xA;Error occurred in file: /home/conda/feedstock_root/build_artifacts/psi4_1683815705191/work/psi4/src/psi4/libpsio/error.cc on line: 134&#xA;The most recent 5 function calls were:&#xA;&#xA;psi::PsiException::PsiException(std::__cxx11::basic_string&amp;lt;char, std::char_traits&amp;lt;char&amp;gt;, std::allocator&amp;lt;char&amp;gt; &amp;gt;, char const*, int)&#xA;psi::PSIO::rw(unsigned long, char*, psi::psio_address, unsigned long, int)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The input file without coordinates looks like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# sapt calculation, SAPT0&#xA;&#xA;# setting available memory to 48 GB&#xA;memory 96 GB&#xA;&#xA;molecule mol {&#xA;  0 1&#xA;...&#xA;--&#xA;0 1&#xA;units angstrom&#xA;}&#xA;set {&#xA;basis jun-cc-pVDZ&#xA;scf_type DF&#xA;freeze_core True&#xA;}&#xA;energy('sapt0')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5113" LastEditorUserId="7" LastEditDate="2023-06-18T23:43:21.583" LastActivityDate="2023-07-20T16:04:45.670" Title="PSI4 SAPT calculation: failure to write" Tags="|molecular-interactions|psi4|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11160" PostTypeId="2" ParentId="11157" CreationDate="2023-06-18T18:43:46.627" Score="5" Body="&lt;p&gt;For an old-school modeler &lt;strong&gt;Python is a must&lt;/strong&gt;. This language is not difficult to learn if you master another language. Having hundreds modules, you can solve almost all scientific problems, the possibilities are infinite from a scientific code to  visualisation including processing of data.&lt;/p&gt;&#xA;&lt;p&gt;The only drawback of Python is the speed, reason why it should be associated with the knowledge of a low level programming language either Fortran or C++. Fortran is the easiest one for a scientist but is limited by the number of librairies and a lack of interfaces. C++ is a tough one, however, after the basic principles are known you can almost do everything, including interfaces.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-06-18T18:43:46.627" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11161" PostTypeId="1" AcceptedAnswerId="11163" CreationDate="2023-06-19T08:58:49.313" Score="5" ViewCount="144" Body="&lt;p&gt;I am very new to using LAMMPS. I am trying to obtain some simulations. I was using an older code which had ave/spatial fix style. In the new LAMMPS version it doesn't work so I am switching to ave/chunk fix style. Below are the lines where I am using this style.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;compute a1 all chunk/atom bin/1d x lower 10.0 units box&#xA;compute b1 all chunk/atom bin/1d x lower 20.0 units box &#xA;fix             4a all ave/chunk 1 1000000 1000000 a1 v_atemp file 10Temperature.txt&#xA;fix             4b all ave/chunk 1 1000000 1000000 b1 v_atemp file 20Temperature.txt &#xA;fix             5a all ave/chunk 1 2000000 2000000 a1 v_atemp file 10Temperature2.txt&#xA;fix             5b all ave/chunk 1 2000000 2000000 b1 v_atemp file 20Temperature2.txt &#xA;fix             6a all ave/chunk 1 4000000 4000000 a1 v_atemp file 10Temperature4.txt &#xA;fix             6b all ave/chunk 1 4000000 4000000 b1 v_atemp file 20Temperature4.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For this I am getting the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Two fix ave commands using same compute&#xA;chunk/atom command in incompatible ways.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't know how to fix this error. I tried to follow the document but I wasn't able to find a fix or I wasn't able to understand much from it. If anyone came across the same error please help.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7422" LastEditorUserId="6687" LastEditDate="2023-06-19T15:23:17.490" LastActivityDate="2023-06-19T17:02:28.120" Title="LAMMPS error &quot;Two fix ave commands using same compute chunk/atom command in incompatible ways&quot;" Tags="|molecular-dynamics|software|molecular-modeling|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11162" PostTypeId="2" ParentId="11157" CreationDate="2023-06-19T10:16:49.523" Score="-2" Body="&lt;p&gt;Another possible answer for &amp;quot;What programming languages do matter modelers generally use?&amp;quot; is &lt;strong&gt;none&lt;/strong&gt; (or at most shell).&lt;/p&gt;&#xA;&lt;p&gt;Many standard workflows for preparing, performing, and analysing molecular dynamics simulations have been fully coded into popular packages like GROMACS and LAMMPS. You just write scripts (or parameter packs) for these packages, feed in initial coordinates, and let 'em rip! All you need is shell to launch the simulations, and whatever visualiser you'd like to use to produce snapshots and graphs.&lt;/p&gt;&#xA;&lt;p&gt;Note: I make no judgements as to whether this is a better or worse state of affairs in the world.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-19T10:16:49.523" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11163" PostTypeId="2" ParentId="11161" CreationDate="2023-06-19T17:02:28.120" Score="2" Body="&lt;p&gt;What the error says is that you are using the same &lt;code&gt;compute chunk/atom&lt;/code&gt; command multiple times in different &lt;code&gt;fix ave/chunk&lt;/code&gt; commands, which is not allowed.&lt;/p&gt;&#xA;&lt;p&gt;From your code snippet, it seems that you have multiple &lt;code&gt;fix ave/chunk&lt;/code&gt; commands using the same &lt;code&gt;compute chunk/atom&lt;/code&gt; commands (&lt;em&gt;a1&lt;/em&gt; and &lt;em&gt;b1&lt;/em&gt;), but with different averaging parameters. LAMMPS cannot keep track of multiple averaging operations on the same chunks simultaneously, hence the error.&lt;/p&gt;&#xA;&lt;p&gt;To fix this issue, you should create separate &lt;code&gt;compute chunk/atom&lt;/code&gt; commands for each of your &lt;code&gt;fix ave/chunk&lt;/code&gt; commands. Here's an example of how you might modify your script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;compute a1 all chunk/atom bin/1d x lower 10.0 units box&#xA;compute a2 all chunk/atom bin/1d x lower 10.0 units box&#xA;compute a3 all chunk/atom bin/1d x lower 10.0 units box&#xA;&#xA;compute b1 all chunk/atom bin/1d x lower 20.0 units box &#xA;compute b2 all chunk/atom bin/1d x lower 20.0 units box &#xA;compute b3 all chunk/atom bin/1d x lower 20.0 units box &#xA;&#xA;fix 4a all ave/chunk 1 1000000 1000000 a1 v_atemp file 10Temperature.txt&#xA;fix 5a all ave/chunk 1 2000000 2000000 a2 v_atemp file 10Temperature2.txt&#xA;fix 6a all ave/chunk 1 4000000 4000000 a3 v_atemp file 10Temperature4.txt &#xA;&#xA;fix 4b all ave/chunk 1 1000000 1000000 b1 v_atemp file 20Temperature.txt&#xA;fix 5b all ave/chunk 1 2000000 2000000 b2 v_atemp file 20Temperature2.txt &#xA;fix 6b all ave/chunk 1 4000000 4000000 b3 v_atemp file 20Temperature4.txt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="605" LastActivityDate="2023-06-19T17:02:28.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11165" PostTypeId="1" CreationDate="2023-06-20T12:27:29.517" Score="3" ViewCount="229" Body="&lt;p&gt;So I am working with Quantum Espresso (6.5) and we have built a few square planar Fe complexes (to be specific &lt;span class=&quot;math-container&quot;&gt;$\ce{Fe(NH_2)_2(OH)_2}$&lt;/span&gt; cis and trans), and we ran scf (self consistent calculation) and pdos (projected density of state) calculations on it to get info on the atomic orbital occupancy and the magnetic moments. But this still doesn't give the energy splitting (d orbital splitting) order of the system. Can someone suggest some methods where we can get the crystal/ligand field splitting of d orbital of Fe using DFT (preferably using QE but other methods work too)?&lt;/p&gt;&#xA;&lt;p&gt;Also is there a way to get this order from the occupancy of orbitals only?&lt;/p&gt;&#xA;&lt;p&gt;PS: I understand WIEN2K would be of use here but because of some issue we won't be able to use that, so if there are other methods, do tell us.&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I did some asking around and apparently the order of energy can be found by using tight-binding-method or by group theory but I'm not really sure if someone can explain how those methods would work here.&lt;/p&gt;&#xA;&lt;p&gt;I'd still prefer using quantum espresso for this though if somehow possible&lt;/p&gt;&#xA;" OwnerUserId="7073" LastEditorUserId="7" LastEditDate="2023-07-02T19:25:53.067" LastActivityDate="2023-07-21T09:23:29.007" Title="How to get the crystal/ligand field splitting of d orbital of Fe complex using Quantum Espresso" Tags="|density-functional-theory|quantum-espresso|orbitals|tight-binding|crystal-field|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11166" PostTypeId="2" ParentId="11144" CreationDate="2023-06-20T13:35:29.853" Score="2" Body="&lt;p&gt;I'll do my best to answer your question because I'm also currently learning about this topic. The field generated by machine learning is indeed receiving more and more attention from everyone. However, in my opinion, to obtain a more accurate field, different machine learning methods and models require rich datasets, and of course, the larger the dataset, the better.&lt;/p&gt;&#xA;&lt;p&gt;Regarding your question, theoretically, the more extensive the training configuration library, the better the predictive power for unknown structures in the production run. Suppose you are studying the phase transition process of a crystal structure; in that case, in addition to the structures of these different phases in your training library, the transitional structures between them also need good training. Therefore, what I want to say is that the most crucial aspect of a machine learning training field method is not how many configuration libraries it can obtain, but how clearly it can distinguish which configuration libraries are worth learning. For example, if you have a dataset of 10,000 AIMD data, only 300 of them may be necessary for training. Therefore, for your vague question, my answer is to try to understand the process you want to simulate as much as possible (using AIMD to simulate small models is a good method). Additionally, I recommend that you first use some ready-made machine learning methods and then improve upon them. For example, VASP's MLFF function provides an on-the-fly learning mode, which can reduce the training time of traditional machine learning. However, its shortcomings are also evident, as the kernel model used has limited adjustability and is unsuitable for studying many structures. Secondly, there is the DeepMD kit developed by E. Weinan, which is also a relatively mature kit for generating machine learning fields. You can start with these kits for training and then improve upon them. I believe that this can give you a deeper understanding of your own machine learning and the problems you want to study.&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-06-20T13:35:29.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11167" PostTypeId="1" CreationDate="2023-06-20T14:16:47.740" Score="1" ViewCount="42" Body="&lt;p&gt;I'm wondering if there is any easy way to fold the band structure from unit cell BZ to supercell BZ. For example, I have a 2D rectangular lattice and its band structure along &lt;span class=&quot;math-container&quot;&gt;$\Gamma - X - Y - \Gamma$&lt;/span&gt; within the first BZ. Now, I would like to see the band dispersion along &lt;span class=&quot;math-container&quot;&gt;$\Gamma - X$&lt;/span&gt; for the lattice replicated several times along &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1318" LastActivityDate="2023-06-20T14:16:47.740" Title="band folding instead of unfolding" Tags="|band-structure|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-20T03:23:04.170" ContentLicense="CC BY-SA 4.0" />
  <row Id="11169" PostTypeId="1" CreationDate="2023-06-20T15:22:59.177" Score="2" ViewCount="57" Body="&lt;p&gt;I'm using the GAMESS software and want to try to plot the pDOS for my systems and visualize the molecular orbitals. I was thinking I could get the data from one of the &lt;code&gt;NPRINT&lt;/code&gt; commands, although which one is not so clear. And then once I have the data (if possible), is there a straight-forward way to plot/visualize it?&lt;/p&gt;&#xA;" OwnerUserId="7429" LastActivityDate="2023-08-02T12:20:00.353" Title="Is it possible to plot the pDOS or visualize the molecular orbitals from GAMESS outputs?" Tags="|orbitals|gamess|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11170" PostTypeId="2" ParentId="11159" CreationDate="2023-06-20T16:02:04.670" Score="2" Body="&lt;p&gt;I suspect it turned out to be an issue with scratch space. I moved the scratch location to a local compute node instead of a networked filesystem scratch space. The variable to be set up is $PSI_SCRATCH.&lt;/p&gt;&#xA;" OwnerUserId="5113" LastActivityDate="2023-06-20T16:02:04.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11171" PostTypeId="1" CreationDate="2023-06-20T16:56:00.153" Score="2" ViewCount="52" Body="&lt;p&gt;I am trying to run MD using DFTB+ v 22.2, however, my input fails with the following errors:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;WARNING!&#xA;-&amp;gt; The following 4 node(s) have been ignored by the parser:&#xA;(1)&#xA;Path: dftbplusinput/Hamiltonian/DFTB/KPointsAndWeights&#xA;Line: 37-42 (File: dftb_in.hsd)&#xA;(2)&#xA;Path: dftbplusinput/Hamiltonian/DFTB/Filling/Fermi/IndependentKFilling&#xA;Line: 63-63 (File: dftb_in.hsd)&#xA;(3)&#xA;Path: dftbplusinput/Hamiltonian/DFTB/EwaldParameter&#xA;Line: 86-86 (File: dftb_in.hsd)&#xA;(4)&#xA;Path: dftbplusinput/Hamiltonian/DFTB/EwaldTolerance&#xA;Line: 87-87 (File: dftb_in.hsd)&#xA;&#xA;ERROR!&#xA;-&amp;gt; Code halting due to the presence of errors in dftb_in file.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, there are no errors specified apart from the 4 mentioned above. I wonder if someone could take a look at the input file and advise. The text file is available at &lt;a href=&quot;https://pastebin.com/CS46Hk5v&quot; rel=&quot;nofollow noreferrer&quot;&gt;here.&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I sincerely appreciate your help.&lt;/p&gt;&#xA;" OwnerUserId="5113" LastEditorUserId="5" LastEditDate="2023-07-20T11:41:09.003" LastActivityDate="2023-07-20T11:41:09.003" Title="How do I fix the 4 nodes ignored DFTB input file error in the attached input file?" Tags="|dftb-plus|density-functional-tight-binding|" AnswerCount="0" CommentCount="2" ClosedDate="2023-10-13T16:53:05.267" ContentLicense="CC BY-SA 4.0" />
  <row Id="11172" PostTypeId="2" ParentId="11108" CreationDate="2023-06-20T23:03:44.160" Score="4" Body="&lt;h3&gt;Background&lt;/h3&gt;&#xA;&lt;p&gt;At the heart of a conventional DFT simulation are the Kohn-Sham equations,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left(-\frac{\hbar^2}{2m}\nabla^2 + \hat{V}\left[\rho\right]\right)\psi_{bk} = E_{bk}\psi_{bk} \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt; is the &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;th Kohn-Sham single-particle state (band, for a material) at point &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; in the Brillouin zone, with corresponding eigenenergy &lt;span class=&quot;math-container&quot;&gt;$E_{bk}$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\hat{V}\left[\rho\right]$&lt;/span&gt; is the potential operator, which is a functional of the Kohn-Sham density,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\rho\left(\mathbf{r}\right) = \sum_{bk^\prime}f_{bk^\prime}\left\vert\psi_{bk^\prime}\left(\mathbf{r}\right)\right\vert^2, \tag{2}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f_{bk^\prime}$&lt;/span&gt; is the band occupancy at the reciprocal space point &lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}$&lt;/span&gt; is the position in 3D space. I have used a different k-point label, &lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt;, deliberately here, because the density requires us to integrate over the whole Brillouin zone, so the set of k-points in this expression must form an integration grid suitable for numerical integration (not necessarily uniform, though that is the common choice).&lt;/p&gt;&#xA;&lt;p&gt;There is no requirement for the k-points labelled &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; in Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; to be the same set as the &lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt; points used in Eq. &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt;, but complications arise when the sets are different, and these complications are directly relevant to the question.&lt;/p&gt;&#xA;&lt;h4&gt;Self-Consistent Field calculation&lt;/h4&gt;&#xA;&lt;p&gt;Solving Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; requires us to know &lt;span class=&quot;math-container&quot;&gt;$\hat{V}\left[\rho\right]$&lt;/span&gt;, and this in turn requires us to know &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt;. The problem is that &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{r})$&lt;/span&gt; requires us to know &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt; (from Eq. &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt;), which is what we were trying to solve in the first place!&lt;/p&gt;&#xA;&lt;p&gt;The most common solution to this conundrum is to use the &lt;em&gt;self-consistent field (SCF)&lt;/em&gt; method, in which Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; is solved for an initial guess &amp;quot;input&amp;quot; density &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{in}$&lt;/span&gt;, or potential &lt;span class=&quot;math-container&quot;&gt;$\hat{V}$&lt;/span&gt;, giving an estimate of the states &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt;. These states can then be used in Eq. &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; to provide an &amp;quot;output&amp;quot; density &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{out}$&lt;/span&gt; and, hence, a new potential. Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; is now solved with this new potential, which gives new estimates for the states, which gives a new density... and so on.&lt;/p&gt;&#xA;&lt;p&gt;If this iterative method converges, we eventually end up with the same &amp;quot;output&amp;quot; density as we put in, i.e. at some point &lt;span class=&quot;math-container&quot;&gt;$\rho^\mathrm{out}=\rho^\mathrm{in}=\rho$&lt;/span&gt;, which means that equations &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt; are satisfied simultaneously, and the states &lt;span class=&quot;math-container&quot;&gt;$\psi_{bk}$&lt;/span&gt;, the density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; and the potential &lt;span class=&quot;math-container&quot;&gt;$\hat{V}\left[\rho\right]$&lt;/span&gt; are all consistent -- we have reached &lt;em&gt;self-consistency&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(NB in practice it is usually necessary to construct the new density (or potential) for the next iteration in a more sophisticated way, mixing together many previous inputs and outputs in a method known as &lt;em&gt;density-&lt;/em&gt; or &lt;em&gt;potential-mixing&lt;/em&gt;.)&lt;/p&gt;&#xA;&lt;h4&gt;Bandstructure calculations&lt;/h4&gt;&#xA;&lt;p&gt;When we wish to compute the bandstructure for a particular system, all we do is to solve Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; at the appropriate k-points; for a bandstructure calculation, this would be a set of k-points along the system's high-symmetry directions.&lt;/p&gt;&#xA;&lt;p&gt;In order to solve Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; for our bandstructure &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points, we need to know the potential, and that means we need to know the density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;. In principle, we could use the SCF method again and compute &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; from Eq. &lt;span class=&quot;math-container&quot;&gt;$(2)$&lt;/span&gt;, &lt;strong&gt;except&lt;/strong&gt; that the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points we use for the bandstructure are extremely atypical, and do not cover large regions of the Brillouin zone, so they make an extremely poor choice for an integration grid.&lt;/p&gt;&#xA;&lt;p&gt;The solution is to compute the density using a Brillouin zone integration grid (&lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt; points) with the SCF method, and then use that density in Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; and solve the equation for the states and eigenenergies at the bandstructure points &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;Density of States calculations&lt;/h4&gt;&#xA;&lt;p&gt;In contrast to bandstructure calculations, a density of states (DOS) calculation &lt;em&gt;does&lt;/em&gt; require a set of Brillouin zone sampling points which form an integration grid. In fact, typical DOS calculations use a much finer integration grid than the SCF set, so wouldn't it actually be &lt;em&gt;better&lt;/em&gt; to use this for the density as well?&lt;/p&gt;&#xA;&lt;p&gt;The reason we use the SCF density here is much more pragmatic: a typical DOS Brillouin zone integration grid is much more densely sampled than we need, to represent the integrated density well. It is more efficient computationally to compute the density with an SCF optimisation on a coarser grid of &lt;span class=&quot;math-container&quot;&gt;$k^\prime$&lt;/span&gt;-points, and then &amp;quot;fix&amp;quot; the density and solve Eq. &lt;span class=&quot;math-container&quot;&gt;$(1)$&lt;/span&gt; on the finer &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid for the DOS &lt;em&gt;non-self-consistently&lt;/em&gt;, i.e. without constantly recomputing the density and potential using that finer grid.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-06-20T23:03:44.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11174" PostTypeId="1" CreationDate="2023-06-21T04:37:39.227" Score="3" ViewCount="43" Body="&lt;p&gt;I am learning about Lewis octet theory and the following formulae were shown as &lt;strong&gt;guidelines&lt;/strong&gt; to draw Lewis structures:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;V &amp;amp;= \text{total valence electrons}\\&#xA;R &amp;amp;= \text{required number of electrons for complete octets}\\&#xA;B &amp;amp;= \text{bonding electrons} = R-V\\&#xA;N &amp;amp;= \text{non-bonding electrons} = V-B = 2V-R\\&#xA;\text{number of bonds} &amp;amp;= \dfrac{B}{2}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;h3&gt;Example of Lewis Structures of &lt;span class=&quot;math-container&quot;&gt;$\ce{C4H4}$&lt;/span&gt;&lt;/h3&gt;&#xA;&lt;p&gt;For the structure &lt;span class=&quot;math-container&quot;&gt;$\ce{C4H8}$&lt;/span&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;V &amp;amp;= 4\times 4 + 8\times 1 = 24 \\&#xA;R &amp;amp;= 4\times 8 + 8\times 2 = 48 \\&#xA;B &amp;amp;= V-R = 24 \\&#xA;\text{number of bonds} &amp;amp;= \dfrac{B}{2}=12 \\&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, we do know the isomers of &lt;span class=&quot;math-container&quot;&gt;$\ce{C4H4}$&lt;/span&gt;, which all follow the above stated rules.&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Molecular Formulae&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Structures&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Remarks&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C4H8}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://i.stack.imgur.com/q4duW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q4duW.png&quot; alt=&quot;isomers of cyclobutane C4H8&quot; /&gt;&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Ring-chain isomerism; Positional Isomerism; Diastereoisomerism&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;This also tells us that the &lt;strong&gt;guidelines&lt;/strong&gt; help us enumerate the isomers of a compound.&lt;/p&gt;&#xA;&lt;h3&gt;Some More Examples&lt;/h3&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Molecular Formulae&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Structures&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Remarks&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{CO3^{2-}}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://i.stack.imgur.com/08hVb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/08hVb.png&quot; alt=&quot;resonance structures of carboxylate anion&quot; /&gt;&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Resonance structures&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{HSO3-}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://i.stack.imgur.com/AFWua.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AFWua.png&quot; alt=&quot;tautomers of hydrogensulfite&quot; /&gt;&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/a/174440/125117&quot;&gt;Inspired&lt;/a&gt;*&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C6H6}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://i.stack.imgur.com/y2vPU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y2vPU.png&quot; alt=&quot;different bonding in benzene&quot; /&gt;&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;The benzene dilemma&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;span class=&quot;math-container&quot;&gt;$\ce{C3O2H6}$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;&lt;a href=&quot;https://i.stack.imgur.com/zQrUt.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zQrUt.png&quot; alt=&quot;tautuomers of hydroxypropanal&quot; /&gt;&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Tautomerization&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;*requires special consideration for the expanded octet of &lt;span class=&quot;math-container&quot;&gt;$\ce{S}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I know not all examples cover all isomers, but just to give an idea of the various applications of the &lt;strong&gt;guidelines&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;Question&lt;/h3&gt;&#xA;&lt;p&gt;I was wondering if there are some works or perhaps algorithmic approaches to enumerate all structures that comply with the rules, with perhaps modifications to include hypo- and hyper-octet compounds, and just how much information is contained in a molecular formula.&lt;/p&gt;&#xA;" OwnerUserId="7205" LastActivityDate="2023-06-21T04:37:39.227" Title="How to draw multiple Lewis structures from the same molecular formula?" Tags="|molecular-modeling|structure|cheminformatics|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11175" PostTypeId="1" CreationDate="2023-06-21T08:02:37.560" Score="2" ViewCount="217" Body="&lt;p&gt;I want to calculate the band energies of a 2D material with respect to the vacuum level to normalize my band energies with Quantum Espresso. I found a post &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3720/how-to-calculate-the-energy-of-conduction-band-and-valence-band-with-respect-to/3721#3721&quot;&gt;here&lt;/a&gt;, which was not really satisfying for me. Is this the only way to do it?&lt;/p&gt;&#xA;&lt;p&gt;Another question that I am asking myself is; suppose I apply an electric field in z-direction to the 2D material. Would it still be possible to compute the vacuum level in that case, because my potential would be altered by the applied electric field?&lt;/p&gt;&#xA;" OwnerUserId="2088" LastActivityDate="2023-06-21T08:02:37.560" Title="Compute band energies with respect to the vacuum level with QE" Tags="|quantum-espresso|band-structure|2d-lattice|electric-field|vacuum-potential|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11176" PostTypeId="1" AcceptedAnswerId="11179" CreationDate="2023-06-21T08:26:07.457" Score="3" ViewCount="241" Body="&lt;p&gt;I would like &lt;code&gt;topo writelammpsdata&lt;/code&gt; to print the full box, while it seems only to be printing one molecule.&lt;/p&gt;&#xA;&lt;p&gt;I have loaded several molecules in a box with VMD - here working with water and benzene as an example.&#xA;Although the box looks alright, I am not able to correctly topo writelammpsdata.&#xA;Essentially, while I have N molecules, the lt file produced only contains 1 molecule.&lt;/p&gt;&#xA;&lt;p&gt;I paste the whole script and the initial files. Please note that I am translating each molecule and picking alternatively a water or a benzene molecule.&#xA;Also, is there a way to script a representation in VMD? Say I want each water to be licorice.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;set side 50&#xA;set nmol_per_side 2&#xA;&#xA;## Replicate the molecule&#xA;&#xA;mol new water.pdb&#xA;set mol_idx 0&#xA;&#xA;for {set i 0} {&lt;span class=&quot;math-container&quot;&gt;$i &amp;lt;= $&lt;/span&gt;nmol_per_side} {incr i} {&#xA;  for {set j 0} {&lt;span class=&quot;math-container&quot;&gt;$j &amp;lt;= $&lt;/span&gt;nmol_per_side} {incr j} {&#xA;    for {set k 0} {&lt;span class=&quot;math-container&quot;&gt;$k &amp;lt;= $&lt;/span&gt;nmol_per_side} {incr k} {&#xA;&#xA;        set dx [expr &lt;span class=&quot;math-container&quot;&gt;$side/$&lt;/span&gt;nmol_per_side*&lt;span class=&quot;math-container&quot;&gt;$i]&#xA;    set dy [expr $&lt;/span&gt;side/&lt;span class=&quot;math-container&quot;&gt;$nmol_per_side*$&lt;/span&gt;j]&#xA;        set dz [expr &lt;span class=&quot;math-container&quot;&gt;$side/$&lt;/span&gt;nmol_per_side*$k]&#xA;&#xA;        if { (&lt;span class=&quot;math-container&quot;&gt;$dx != 0) || ($&lt;/span&gt;dy != 0) || (&lt;span class=&quot;math-container&quot;&gt;$dz != 0) } {&#xA;        incr mol_idx&#xA;        puts &quot;dx = $dx, dy = $dy, dz = $dz, mol_idx = $&lt;/span&gt;mol_idx&amp;quot;&#xA;&#xA;&#xA;            if { (&lt;span class=&quot;math-container&quot;&gt;$mol_idx % 2)==0 } {&#xA;           mol new water.pdb&#xA;        } else {&#xA;           mol new benzene.pdb&#xA;           }&#xA;        set molecule [atomselect $&lt;/span&gt;mol_idx &amp;quot;all&amp;quot;]&#xA;            &lt;span class=&quot;math-container&quot;&gt;$molecule moveby [ list $&lt;/span&gt;dx &lt;span class=&quot;math-container&quot;&gt;$dy $&lt;/span&gt;dz ]&#xA;&#xA;            }&#xA;      }&#xA;    }&#xA;  }&#xA;&#xA;# Create a cubic box&#xA;pbc set [ list &lt;span class=&quot;math-container&quot;&gt;$side $&lt;/span&gt;side $side ]&#xA;pbc box&#xA;&#xA;topo retypebonds&#xA;topo guessangles&#xA;topo guessdihedrals&#xA;&#xA;topo writelammpsdata full_box.lt full&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can really use any molecule. Here I am using water:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOM      1  O   HOH     1       0.000   0.000   0.000  1.00  0.00           O  &#xA;ATOM      2  H1  HOH     1       0.957   0.000   0.000  1.00  0.00           H  &#xA;ATOM      3  H2  HOH     1      -0.239   0.927   0.000  1.00  0.00           H  &#xA;CONECT    1    2    3  &#xA;CONECT    2    1  &#xA;CONECT    3    1  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and benzene:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOM      1  C   BEN     1       0.000   1.402   0.000  1.00  0.00           C  &#xA;ATOM      2  C   BEN     1       1.214   0.701   0.000  1.00  0.00           C  &#xA;ATOM      3  C   BEN     1       1.214  -0.701   0.000  1.00  0.00           C  &#xA;ATOM      4  C   BEN     1       0.000  -1.402   0.000  1.00  0.00           C  &#xA;ATOM      5  C   BEN     1      -1.214  -0.701   0.000  1.00  0.00           C  &#xA;ATOM      6  C   BEN     1      -1.214   0.701   0.000  1.00  0.00           C  &#xA;ATOM      7  H   BEN     1       0.000   2.494   0.000  1.00  0.00           H  &#xA;ATOM      8  H   BEN     1       2.156   1.247   0.000  1.00  0.00           H  &#xA;ATOM      9  H   BEN     1       2.156  -1.247   0.000  1.00  0.00           H  &#xA;ATOM     10  H   BEN     1       0.000  -2.788   0.000  1.00  0.00           H  &#xA;ATOM     11  H   BEN     1      -2.156  -1.247   0.000  1.00  0.00           H  &#xA;ATOM     12  H   BEN     1      -2.156   1.247   0.000  1.00  0.00           H  &#xA;CONECT    1    2    6  &#xA;CONECT    2    1    3  &#xA;CONECT    3    2    4  &#xA;CONECT    4    3    5  &#xA;CONECT    5    4    6  &#xA;CONECT    6    1    5  &#xA;CONECT    1    7  &#xA;CONECT    2    8  &#xA;CONECT    3    9  &#xA;CONECT    4   10  &#xA;CONECT    5   11  &#xA;CONECT    6   12  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2023-06-21T09:55:46.107" Title="Write full box to topology file + script representation" Tags="|vmd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11177" PostTypeId="1" CreationDate="2023-06-21T08:56:03.983" Score="2" ViewCount="29" Body="&lt;p&gt;I followed the tutorial reported &lt;a href=&quot;https://pogorelov.scs.illinois.edu/wp-content/uploads/2020/06/UV-Vis-Spectra_Calculation_Tutorial-PogorelovLab.v1.web_.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; to calculate the vibrational resolved spectrum in vacuum. The spectrum seems ok and it is actually close to the experimental one.&lt;/p&gt;&#xA;&lt;p&gt;However, I would like to add the solvent to have closer peaks wavelengths to the experiments. I first simply tried to add the solvent in the three steps, however I obtain a spectrum with an extra peak that I don't know where it comes from. I then read on the Gaussian &lt;a href=&quot;https://gaussian.com/scrf/&quot; rel=&quot;nofollow noreferrer&quot;&gt;website&lt;/a&gt; that the calculation of the excited state in solvent shouldn't be done with the opt keyword but this didn't solve my problem.&lt;/p&gt;&#xA;&lt;p&gt;So, can someone provide the step-by-step calculation of the vibrationally resolved UV-Vis spectrum in solvent with Gaussian?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-06-21T08:56:03.983" Title="What is the procedure to calculate the vibrationally resolved UV-Vis spectrum in solvent with Gaussian?" Tags="|gaussian|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11178" PostTypeId="1" CreationDate="2023-06-21T09:20:10.790" Score="1" ViewCount="213" Body="&lt;p&gt;How can I build a 3x3x1 rectangular supercell from the hexagonal unit cell of graphene by using VESTA?&lt;/p&gt;&#xA;" OwnerUserId="7312" LastEditorUserId="7312" LastEditDate="2023-06-22T10:47:46.800" LastActivityDate="2023-06-22T10:47:46.800" Title="How to build (visualize) 3x3x1 rectangular from 1x1x1 hexagonal unit cell of graphene by using VESTA" Tags="|visualization-software|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11179" PostTypeId="2" ParentId="11176" CreationDate="2023-06-21T09:55:46.107" Score="4" Body="&lt;p&gt;As per &lt;a href=&quot;https://sites.google.com/site/akohlmey/software/topotools/documentation&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; (search for &amp;quot;molid&amp;quot;), TopoTools only works on one &amp;quot;VMD molecule&amp;quot; at a time, and by default this is just &lt;code&gt;mol top&lt;/code&gt;. Your approach adds each new molecule to a new VMD molecule, and thus &lt;code&gt;writelammpsdata&lt;/code&gt; writes only the last molecule you've created.&lt;/p&gt;&#xA;&lt;p&gt;In your situation, the workflow I would adopt is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Use &lt;code&gt;writelammpsdata&lt;/code&gt; to convert &lt;code&gt;water.pdb&lt;/code&gt; and &lt;code&gt;benzene.pdb&lt;/code&gt; &lt;em&gt;each&lt;/em&gt; to separate LAMMPS data files.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Read them both into a LAMMPS script using &lt;em&gt;successive&lt;/em&gt; &lt;code&gt;read_data&lt;/code&gt; commands (with the needed keywords, especially &lt;code&gt;extra/*&lt;/code&gt; and &lt;code&gt;offset&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;In the same script, use &lt;code&gt;replicate&lt;/code&gt; to multiply the water and benzene to the necessary quantity.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Equilibrate well (possibly at high temperature), adjusting the box size manually as desired.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Ordinarily I would recommend &lt;a href=&quot;https://m3g.github.io/packmol/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PACKMOL&lt;/a&gt;, which will combine &lt;code&gt;water.pdb&lt;/code&gt; and &lt;code&gt;benzene.pdb&lt;/code&gt; into (for example) &lt;code&gt;90water+70benzene.pdb&lt;/code&gt;, with some randomisation of coordinates to boot. You could then load that into VMD as a single molecule and &lt;code&gt;topo writelammpsdata&lt;/code&gt; into a LAMMPS data file. But, for benzene, I imagine you need some care defining the dihedrals and impropers, and you might prefer to &lt;code&gt;replicate&lt;/code&gt; in LAMMPS and &lt;em&gt;know&lt;/em&gt; that all the benzenes have the same dihedral representation, rather than having TopoTools independently convert each one from PDB (or VMD's internal representation).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-06-21T09:55:46.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11181" PostTypeId="2" ParentId="11178" CreationDate="2023-06-21T16:29:27.610" Score="3" Body="&lt;p&gt;In VESTA you can either visualize multiple repetitions of a unit cell, or multiply your unit cell a number of times to really create a supercell.&#xA;I'll explain both cases now.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Visualize repetitions of a unit cell:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Go to Objects &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; Boundary&lt;/li&gt;&#xA;&lt;li&gt;Under ranges of fractional coordinates, chose the minimum and maximum limits along the three axes. For your example of a &lt;span class=&quot;math-container&quot;&gt;$3\times3\times1$&lt;/span&gt; supercell you could chose something like: x(min)=0, x(max)=3, y(min)=0, y(max)=3, z(min)=0, z(max)=1&lt;/li&gt;&#xA;&lt;li&gt;click &amp;quot;Apply&amp;quot; to continue, or &amp;quot;OK&amp;quot; to exit the Boundary menu.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;strong&gt;Create supercell:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Go to Edit &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; Edit Data &lt;span class=&quot;math-container&quot;&gt;$\rightarrow$&lt;/span&gt; Unit cell&lt;/li&gt;&#xA;&lt;li&gt;Click on &amp;quot;Transform&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;On the &amp;quot;Rotation matrix P&amp;quot; change the values to create the required supercell. For your example of a &lt;span class=&quot;math-container&quot;&gt;$3\times3\times1$&lt;/span&gt; supercell you should change only the diagonals to be &lt;span class=&quot;math-container&quot;&gt;$3, 3,$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;, with &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; on all off-diagonals.&lt;/li&gt;&#xA;&lt;li&gt;Click &amp;quot;OK&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;If prompted about the transformation changing the unit cell volume, agree to continue.&lt;/li&gt;&#xA;&lt;li&gt;When asked how to convert the structure chose the option &amp;quot;Add new equivalent positions&amp;quot; (or similar).&lt;/li&gt;&#xA;&lt;li&gt;click &amp;quot;Apply&amp;quot; to continue, or &amp;quot;OK&amp;quot; to exit the Edit data menu.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;All of the instructions here are given for the mac version of VESTA, but they should be very similar in other versions.&lt;/p&gt;&#xA;" OwnerUserId="5481" LastActivityDate="2023-06-21T16:29:27.610" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11182" PostTypeId="1" CreationDate="2023-06-22T14:02:11.530" Score="1" ViewCount="25" Body="&lt;p&gt;I have been using NBO 7.0 software and the file.47, and the option in ORCA with nbo block and sometimes I have problems with the convergence algorithm for NLMO specifically this error: &lt;strong&gt;NLMO algorithm could not converge&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Do you have any way of solving this convergence problem?&lt;/p&gt;&#xA;" OwnerUserId="7443" LastActivityDate="2023-06-22T14:02:11.530" Title="NLMO algorithm failed to converge" Tags="|quantum-chemistry|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-02T01:46:05.037" ContentLicense="CC BY-SA 4.0" />
  <row Id="11183" PostTypeId="1" CreationDate="2023-06-22T14:02:19.900" Score="3" ViewCount="52" Body="&lt;p&gt;In order to compute the local Green's function on the Bethe lattice, it is necessary to perform a Hilbert transform&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_{loc}(\omega) = \int \frac{DOS(\varepsilon)}{\omega-\varepsilon} \text{d}\varepsilon $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where, for &lt;span class=&quot;math-container&quot;&gt;$|\varepsilon| &amp;lt; 2t$&lt;/span&gt; (0 otherwise)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$DOS(\varepsilon) = \frac{\sqrt{4t^2 - \varepsilon^2}}{2\pi t^2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; is the hopping amplitude.&lt;/p&gt;&#xA;&lt;p&gt;Often, in textbooks or in papers, it is said that the result of the integral takes a simple form (even if in some definitions, the sgn function is omitted)  :&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$G_{loc}(\omega) = \frac{\omega - sgn(\Im \omega) \sqrt{\omega^2 - 4t^2}}{2t^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I've been trying to find the derivation to get to this formula for quite some time now and never found a way to get there (and never found it online). Even simply plugging the equation into Mathematica doesn't work. I've seen this question asked on other forums but never get an answer I hope here it can get one.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know the steps to do this integral ?&lt;/p&gt;&#xA;" OwnerUserId="5523" LastActivityDate="2023-06-22T14:02:19.900" Title="Hilbert transform on the Bethe Lattice" Tags="|solid-state-physics|greens-functions|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11184" PostTypeId="1" AcceptedAnswerId="11188" CreationDate="2023-06-22T17:20:40.353" Score="3" ViewCount="83" Body="&lt;p&gt;I was reading a paper that stated:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;For example, graphitic carbon nitride (g-C3N4) is considered a potential anode material for lithium ion batteries due to its easy accessibility, low cost and large theoretic capacity of 524 mAh·g−1 (much greater than conventional graphite anode 372 mAh·g−1)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And I had looked into how to calculate the theoretical capacity of g-&lt;span class=&quot;math-container&quot;&gt;$\ce{C3N4}$&lt;/span&gt; and found this formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$TC=\frac{xF}{M}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; is the highest atomic ratio of the ion to the anode material (in this case it would be one Li atom so &lt;span class=&quot;math-container&quot;&gt;$x=1$&lt;/span&gt;?), &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is the Faraday constant (&lt;span class=&quot;math-container&quot;&gt;$\pu{26.8Ah * mol^-1}$&lt;/span&gt;) and &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; is the molecular mass of the anode material (&lt;span class=&quot;math-container&quot;&gt;$M_\ce{C3N4}=\pu{92.06 g/mol}$&lt;/span&gt;). However, when I plug these numbers in, I get:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$TC=\frac{1\times26.8}{92.06}=\pu{0.291 Ah*g^-1}=\pu{291.11 mAh*g^-1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is decently lower than the theoretical capacity as presented in the literature. I saw another paper that stated g-&lt;span class=&quot;math-container&quot;&gt;$\ce{C3N4}$&lt;/span&gt; has &amp;gt; &lt;span class=&quot;math-container&quot;&gt;$\pu{1,000 mAh*g^-1}$&lt;/span&gt; which also contradicts this paper. What am I doing wrong?&lt;/p&gt;&#xA;" OwnerUserId="7429" LastEditorUserId="7" LastEditDate="2023-06-22T21:07:29.833" LastActivityDate="2023-06-23T13:19:32.800" Title="Theoretical Capacity of g-C3N4?" Tags="|graphene|energy|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11185" PostTypeId="1" AcceptedAnswerId="11189" CreationDate="2023-06-22T18:35:15.367" Score="6" ViewCount="123" Body="&lt;p&gt;As far as I understand, there are two related concepts called &lt;em&gt;&lt;strong&gt;potential&lt;/strong&gt;&lt;/em&gt; and &lt;em&gt;&lt;strong&gt;forcefield&lt;/strong&gt;&lt;/em&gt;. A forcefield is essentially a sum term of more than one potential.&lt;/p&gt;&#xA;&lt;p&gt;My question is, is the term &amp;quot;Forcefield&amp;quot; only applicable to MD (Molecular Dynamics) simulations?&lt;/p&gt;&#xA;&lt;p&gt;Can MC (Monte-Carlo) simulations use &amp;quot;Forceforeld&amp;quot;s?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-06-23T17:47:29.130" Title="Is the term &quot;Forcefield&quot; only reserved for MD (Molecular Dynamics)?" Tags="|forcefields|monte-carlo|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11186" PostTypeId="1" CreationDate="2023-06-22T20:01:52.937" Score="4" ViewCount="53" Body="&lt;p&gt;FCC structure's crystal primitive cell is not cubic.&#xA;However, when we use ARPES to measure a FCC crystal, we usually choose a cubic Brillouin zone, and the experiment's path is not the FCC primitive cell's high symmetry path. I try these two way to solve the problem, and meet some problems (we choose &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$(0,\pi/a,0)$&lt;/span&gt; as the experiment's path):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;I build up a cubic unit cell of FCC crystal, and calculate its &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$(0,\pi/a,0)$&lt;/span&gt;'s path's band.&lt;/li&gt;&#xA;&lt;li&gt;I use primitive cell to do the SCF, then choose &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$(b_1+b_3)/2$&lt;/span&gt; as the path to show the band.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For option 1, I think I should unfold the band, but how to choose the primitive cell's path to unfold? I'm not certain of the validity of option 2.&lt;/p&gt;&#xA;" OwnerUserId="7445" LastEditorUserId="7" LastEditDate="2023-06-23T16:44:42.743" LastActivityDate="2023-06-29T12:11:52.977" Title="Compare FCC structure's DFT band result with ARPES data" Tags="|density-functional-theory|band-structure|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11187" PostTypeId="2" ParentId="9856" CreationDate="2023-06-23T10:32:03.227" Score="3" Body="&lt;p&gt;You don't have to create a script. Let's say you want to run g16 on all Gaussian inputs in the current working directory, &lt;code&gt;*.com&lt;/code&gt;. The shell command&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ for f in *.com; do g16 $f; done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;accomplishes what you want to do.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-06-23T10:32:03.227" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11188" PostTypeId="2" ParentId="11184" CreationDate="2023-06-23T13:19:32.800" Score="3" Body="&lt;p&gt;I guess your citation is from this article : &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1385894721026140&quot; rel=&quot;nofollow noreferrer&quot;&gt;Shangqi Sun &lt;em&gt;et al.&lt;/em&gt;&lt;/a&gt; and the formula is correct, the calculated value could have been right if the graphitic &lt;span class=&quot;math-container&quot;&gt;$\text{g-C3N4}$&lt;/span&gt; had the same structure as graphite. Obviously as &lt;span class=&quot;math-container&quot;&gt;$M(\text{g-C3N4})&amp;gt;M(\text{graphite})$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$TC$&lt;/span&gt; will be less in the case of &lt;span class=&quot;math-container&quot;&gt;$\text{g-C3N4}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Normally, the intercalation of Li atom in graphite gives something like : &lt;span class=&quot;math-container&quot;&gt;$\text{Li + 6C} \rightarrow \text{LiC}_6$&lt;/span&gt;, if you apply you formula, you get directly the expected value of  &lt;span class=&quot;math-container&quot;&gt;$TC = \frac{F}{6M(C)} = 372 \text{ mAh·g}^{−1}$&lt;/span&gt;. I am not an expert of this field, but when the interlayer is large enough, the intercalation is also possible for larger atom like Sodium and this intercalation is more reversible, it is the case of &lt;span class=&quot;math-container&quot;&gt;$\text{g-C3N4}$&lt;/span&gt; compared to graphite or other materials like &lt;a href=&quot;https://www.nature.com/articles/s41467-022-34569-y&quot; rel=&quot;nofollow noreferrer&quot;&gt;transition metal carbides and nitrides (MXenes)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A structure of &lt;span class=&quot;math-container&quot;&gt;$\text{C3N4}$&lt;/span&gt; is given in the picture below, &lt;span class=&quot;math-container&quot;&gt;$\text{g-C3N4}$&lt;/span&gt; will have an infinite layer like graphene, but the crucial elements are the vacancies, these vacancies are large enough to accommodate &lt;span class=&quot;math-container&quot;&gt;$\text{Li}$&lt;/span&gt; atoms in the layer. This is the reason why your result is inconsistent.  There is one or more &lt;span class=&quot;math-container&quot;&gt;$\text{Li}$&lt;/span&gt; in the layer to considered during the process of intercalation. In this case &lt;span class=&quot;math-container&quot;&gt;$x &amp;gt; 1 $&lt;/span&gt; giving &lt;span class=&quot;math-container&quot;&gt;$TC(\text{g-C3N4}) &amp;gt; TC(\text{graphite}) $&lt;/span&gt;, I guess &lt;span class=&quot;math-container&quot;&gt;$x \rightarrow 2 $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HUPFL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HUPFL.png&quot; alt=&quot;Carbon nitride structure&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Image source : &lt;a href=&quot;https://www.researchgate.net/figure/The-predicted-structure-of-carbon-nitride-comprising-condensed-melem-subunits-with_fig1_277462779&quot; rel=&quot;nofollow noreferrer&quot;&gt;Electrochemical Oxygen Reduction on Carbon Nitride&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-06-23T13:19:32.800" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11189" PostTypeId="2" ParentId="11185" CreationDate="2023-06-23T17:47:29.130" Score="6" Body="&lt;p&gt;My experience is that people use the term &amp;quot;potential&amp;quot; and &amp;quot;force field&amp;quot; nearly inter-changeably. This is because the force at a particular point on a potential energy surface (i.e. a potential) is &lt;span class=&quot;math-container&quot;&gt;$F=-\nabla V(\mathbf{r})$&lt;/span&gt;. That is, the force points in the direction of steepest descent on the potential.&lt;/p&gt;&#xA;&lt;p&gt;Because the two concepts are so closely related, people use them interchangeabley.&lt;/p&gt;&#xA;&lt;p&gt;Strictly speaking, one only needs the potential to sample a particular ensemble, and this is what is usually done in monte carlo simulations. However, using the forces as a means of sampling tends to be quite efficent when there aren't large barriers between certain parts of configuration space.&lt;/p&gt;&#xA;&lt;p&gt;Basically, whichever term you use, people will know what you mean in the context of molecular dynamics or monte carlo.&lt;/p&gt;&#xA;" OwnerUserId="1170" LastActivityDate="2023-06-23T17:47:29.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11190" PostTypeId="1" CreationDate="2023-06-24T05:27:58.007" Score="3" ViewCount="137" Body="&lt;p&gt;I used LJ-potential, Hard-sphere, Soft-sphere, Harmonic, Square-well, etc. potentials in the case of simulation of polymer movement. However, I never used&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Charge-Charge Interactions&lt;/li&gt;&#xA;&lt;li&gt;Charge-Dipole Interactions&lt;/li&gt;&#xA;&lt;li&gt;Dipole-Dipole Interactions&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;When should I use them? I.e., to simulate what?&lt;/p&gt;&#xA;&lt;p&gt;Are they even relevant in polymer simulation?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2023-06-24T08:20:22.177" Title="When should I use Charge-Charge Interactions, Charge-Dipole Interactions, and Dipole-Dipole Interactions in molecular simulation?" Tags="|monte-carlo|atomistic-simulation|electrostatic|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11191" PostTypeId="2" ParentId="11190" CreationDate="2023-06-24T08:20:22.177" Score="3" Body="&lt;p&gt;Let's say you are trying to study the formation of hydration shells around ions or something like Antifreeze Glycoproteins (AFGPs). In such cases, it is important that you include charge-dipole and dipole-dipole interactions. Previous studies have shown that classical additive FFs are not entirely suitable for such studies.&lt;/p&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcb.6b05546&quot; rel=&quot;nofollow noreferrer&quot;&gt;Influence of Polarization on Carbohydrate Hydration: A Comparative Study Using Additive and Polarizable Force Fields&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jcim.2c01286&quot; rel=&quot;nofollow noreferrer&quot;&gt;Impact of Polarization on the Ring Puckering Dynamics of Hexose Monosaccharides&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.rsc.org/en/content/articlehtml/2023/na/d2na00733a&quot; rel=&quot;nofollow noreferrer&quot;&gt;Capturing charge and size effects of ions at the graphene–electrolyte interface using polarizable force field simulations&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-06-24T08:20:22.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11192" PostTypeId="2" ParentId="9288" CreationDate="2023-06-24T11:09:42.557" Score="2" Body="&lt;p&gt;The supplied answer is correct, but is script and I (a passerby, not OP or responder) wanted a copypaste in the GUI. To make the code okay for copy pasting (i.e. no multilines):&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from pymol.cgo import CYLINDER, cyl_text&#xA;from pymol.vfont import plain&#xA;&#xA;obj = [CYLINDER, 0., 0., 0., 10., 0., 0., 0.2, 1.0, 1.0, 1.0, 1.0, 0.0, 0., CYLINDER, 0., 0., 0., 0., 10., 0., 0.2, 1.0, 1.0, 1.0, 0., 1.0, 0.,CYLINDER, 0., 0., 0., 0., 0., 10., 0.2, 1.0, 1.0, 1.0, 0., 0.0, 1.0,]&#xA;&#xA;cyl_text(obj,plain,[-5.,-5.,-1],'Origin',0.20,axes=[[3,0,0],[0,3,0],[0,0,3]])&#xA;cyl_text(obj,plain,[10.,0.,0.],'X',0.20,axes=[[3,0,0],[0,3,0],[0,0,3]])&#xA;cyl_text(obj,plain,[0.,10.,0.],'Y',0.20,axes=[[3,0,0],[0,3,0],[0,0,3]])&#xA;&#xA;cmd.load_cgo(obj,'axes')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The change away from star import is because it is evil unless one knows what there is on the &lt;code&gt;__all__&lt;/code&gt; variable of that module. Nothing to do with PyMOL GUI faux-terminal.&lt;/p&gt;&#xA;" OwnerUserId="7453" LastActivityDate="2023-06-24T11:09:42.557" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11193" PostTypeId="2" ParentId="11155" CreationDate="2023-06-25T18:33:15.150" Score="2" Body="&lt;p&gt;I solved the problem by reducing &lt;code&gt;maxstep&lt;/code&gt; to 1 and using &lt;code&gt;notrust&lt;/code&gt; and &lt;code&gt;calcfc&lt;/code&gt;. The proposed transition states were simply very close to the real one and, as I assumed, the potential energy surface was very shallow hence any step greater than 0.01Bohr caused the basin to exit. However glum it worked.... Instead of 6 months, in less than 1 day I found what I was looking for.&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-06-25T18:33:15.150" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11194" PostTypeId="1" AcceptedAnswerId="11200" CreationDate="2023-06-26T16:44:02.793" Score="3" ViewCount="86" Body="&lt;p&gt;I am learning about the Theory of intense laser-induced molecular dissociation. To set the notations, the radiation field Hamiltonian is for a single charged particule : &lt;span class=&quot;math-container&quot;&gt;$$H = \frac{1}{2m}(p-q\hat{A}(r))^2 + V(r) + \hbar \omega (\hat{a}^{\dagger}\hat{a}+1/2)$$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\hat{A}$&lt;/span&gt; the vector potential. The length gauge (Electric-field) has been introduced along side the property that, with the long-wavelength approximation :&lt;span class=&quot;math-container&quot;&gt;$$\hat{O} p \hat{O}^\dagger = p + q\hat{A} $$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\hat{A} = \beta\{\hat{a} + \hat{a}^{\dagger}\}\epsilon$$&lt;/span&gt;&#xA;with the gauge transformation &lt;span class=&quot;math-container&quot;&gt;$\hat{O} = e^{-\frac{i}{\hbar}qr\cdot \hat{A}} = e^{-\frac{i}{\hbar}\beta q r\cdot \epsilon[\hat{a} + \hat{a}^\dagger]}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta = (\frac{\hbar}{2\epsilon_0 \omega V})^{1/2}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\omega = c|k|$&lt;/span&gt; is the frequency of the mode and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; the finite volume leading to a discretization of the laser mode.&lt;/p&gt;&#xA;&lt;p&gt;But I get, with &lt;span class=&quot;math-container&quot;&gt;$p = -i\hbar\nabla_r$&lt;/span&gt; : &lt;span class=&quot;math-container&quot;&gt;$$\hat{O} p \hat{O}^\dagger = qr\cdot \nabla_r \hat{A} + q\hat{A} = q\hat{A}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Edit, derivation :&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\hat{O} p \hat{O}^\dagger &amp;amp;= \hat{O} (-i\hbar)\nabla_r \hat{O}^\dagger = \hat{O} (-i\hbar)\nabla_r e^{\frac{i}{\hbar}qr\cdot \hat{A}}\\ &#xA;&amp;amp;= \hat{O} (-i\hbar) \frac{i}{\hbar}q(\nabla_r r\cdot \hat{A}(r))\hat{O}^\dagger \\&#xA;&amp;amp;= q(\hat{A}(r) + r\cdot \nabla_r\hat{A}(r)) \\&#xA;&amp;amp;= q\hat{A}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;since the dot product is bilinear&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-06-27T19:18:15.133" LastActivityDate="2023-07-01T15:30:14.740" Title="Electric-field/ length gauge : momentum displacement property" Tags="|molecular-modeling|model-hamiltonians|electric-field|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11196" PostTypeId="2" ParentId="9431" CreationDate="2023-06-26T20:22:45.167" Score="1" Body="&lt;p&gt;From my perspective, if you are new to this field, I agree with Camps. Softwares like Glide or GOLD already have builtin process which are more easy to follow than building your own libraries for docking.&lt;/p&gt;&#xA;&lt;p&gt;If you are interested in speeding up your conformational searching process, and generating some more initial conformers with higher quality, as mentioned in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jcim.7b00505&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Benchmarking Commercial Conformer Ensemble Generators&lt;/em&gt;&lt;/a&gt;, other softwares such as Omega, which focused on conformer generation can have better performance.&lt;/p&gt;&#xA;" OwnerUserId="7464" LastActivityDate="2023-06-26T20:22:45.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11197" PostTypeId="1" CreationDate="2023-06-27T03:19:04.093" Score="0" ViewCount="56" Body="&lt;p&gt;It is known that the unknown exact XC functional is potentially discontinuous and thus might not be expressable as a Taylor series; even if it is continuous, the Taylor expansion is not guaranteed to converge anyway.&lt;/p&gt;&#xA;&lt;p&gt;However, there exist asymptotic series that &amp;quot;uniquely&amp;quot; correspond to a specific function(al); for example, the formal pseudodifferential operator representation of the fractional Fourier transform(FRFT), &lt;span class=&quot;math-container&quot;&gt;$e^{ia/8(d^2/dy^2-π^2y^2/2+π/4)}f(y)$&lt;/span&gt;, whose MacLaurin expansion (w.r.t. a) does not generally converge even for Schwartz f, formally satisfies the unitarity property, the &amp;quot;derivative with respect to a&amp;quot; property, and the &amp;quot;reduction to the identity&amp;quot; (when &lt;span class=&quot;math-container&quot;&gt;$a=0$&lt;/span&gt;) property, whose combination uniquely defines the FRFT(&lt;a href=&quot;https://mathoverflow.net/questions/437213/question-on-possibility-of-uniquely-defining-the-frft-via-certain-properties&quot;&gt;see my answer on my post&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;My question now follows- is any series expansion, that &amp;quot;uniquely&amp;quot; expresses the exact XC functional(even if it is non-convergent), existent; if it is, can it be expressed in quasi-closed form?&lt;/p&gt;&#xA;&lt;p&gt;P.S. By &amp;quot;quasi-closed form', I mean as in (possibly divergent and/or asymptotic; see my post linked above) Taylor, Fourier, generalised Fourier(Hermite etc), and/or (psuedo)differential operator representations, and NOT &amp;quot;neural network-derived series&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="4231" LastEditorUserId="4231" LastEditDate="2023-06-28T02:42:20.460" LastActivityDate="2023-06-28T02:42:20.460" Title="Question on existence of a &quot;uniquely&quot; asymptotic series expansion for exact XC functional" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11198" PostTypeId="1" CreationDate="2023-06-27T07:38:04.837" Score="5" ViewCount="87" Body="&lt;p&gt;I was asked by a collaborator if I could calculate the second order susceptibility tensor for a structure. I have been principally using Vasp which includes linear response and hence the first order susceptibility, but does not directly calculate the second order susceptibility. Is anyone aware of an external code that interfaces with Vasp to calculate the 2nd order NLO 2?  If you are not aware of a code that works with Vasp, how about other DFT codes? The structure is periodic and has a total of 64 atoms in the unit cell.&lt;/p&gt;&#xA;" OwnerUserId="6939" LastEditorUserId="5" LastEditDate="2023-07-12T19:11:56.197" LastActivityDate="2023-07-12T19:11:56.197" Title="What codes exist to calculate the second order susceptibility tensor (SHG) using DFT?" Tags="|density-functional-theory|vasp|software-recommendations|one-topic-per-answer|response-theory|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11199" PostTypeId="1" AcceptedAnswerId="11202" CreationDate="2023-06-27T13:28:03.093" Score="3" ViewCount="181" Body="&lt;p&gt;When we employ Hartree-Fock or coupled cluster to calculate an atom's energy, can we directly obtain the valence electron energy? Is it as simple as looking at the orbital energy?&lt;/p&gt;&#xA;&lt;p&gt;I know that summing up orbital energies won't give us the total energy because of double-counting electron-electron interactions. However, this should not be a problem when dealing with a single orbital energy.&lt;/p&gt;&#xA;" OwnerUserId="5689" LastActivityDate="2023-07-26T18:30:44.290" Title="Calculate the energy of a single electron in an atom" Tags="|hartree-fock|coupled-cluster|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11200" PostTypeId="2" ParentId="11194" CreationDate="2023-06-27T20:47:11.637" Score="1" Body="&lt;p&gt;Thanks for adding your derivation. You made a common mistake, which is to treat &lt;span class=&quot;math-container&quot;&gt;$\hat{O}$&lt;/span&gt; as an ordinary exponential function. However, here you are exponentiating an operator, which calls for more care. Formally, this can be treated as a matrix exponential, which is defined in terms of its Taylor expansion:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;e^\hat{x} = 1 + \hat{x} + \frac{\hat{x}^2}{2!} + \dots&#xA;$$&lt;/span&gt;&#xA;Then you get&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\hat{O} \vec{p} \hat{O}^\dagger &amp;amp;= \left( 1 - \frac{i}{\hbar}q\vec{r} \cdot \vec{A} + \dots \right) \vec{p} \left( 1 + \frac{i}{\hbar}q\vec{r} \cdot \vec{A} + \dots \right)\\&#xA;&amp;amp;= \vec{p} -\frac{iq}{\hbar} \left[ \vec{r} \cdot \vec{A}, \vec{p} \right] + \dots\\&#xA;&amp;amp;= \vec{p}  -\frac{iq}{\hbar} \left[ r_j , \vec{p} \right]A_j -\frac{iq}{\hbar} r_j \left[ A_j, \vec{p} \right] + \dots&#xA;\end{align}&lt;/span&gt;&#xA;where I have adopted the Einstein summation convention. Immediately you see the standalone &lt;span class=&quot;math-container&quot;&gt;$\hat{p}$&lt;/span&gt; showing up. The canonical commutation relation, &lt;span class=&quot;math-container&quot;&gt;$\left[ r_j, p_k \right] = i\hbar\delta_{jk}$&lt;/span&gt;, can be substituted into the first commutator. Acting with the second commutator on a test (wave) function &lt;span class=&quot;math-container&quot;&gt;$\psi(\vec{r},t)$&lt;/span&gt; lets you simplify to&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{O} \vec{p}\hat{O}^\dagger = \vec{p} + q\vec{A} + q r_j \cdot \nabla_\vec{r} A_j + \dots&#xA;$$&lt;/span&gt;&#xA;You already concluded that the third term vanishes in your case. What remains is to convince yourself that the higher-order terms (represented by &lt;span class=&quot;math-container&quot;&gt;$\dots$&lt;/span&gt;) do not modify the result.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2023-07-01T15:30:14.740" LastActivityDate="2023-07-01T15:30:14.740" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11201" PostTypeId="2" ParentId="11146" CreationDate="2023-06-27T22:58:35.373" Score="2" Body="&lt;p&gt;I'm not a VASP user, so I don't know for certain, but I expect that it contains the atomic pseudo-charge density on a radial grid, using logarithmic coordinates. This is the usual way to express the radial parts of atom-centred numerical functions, because it takes advantage of the known asymptotic behaviour of the atomic wavefunctions (i.e. they decay exponentially into the vacuum).&lt;/p&gt;&#xA;&lt;p&gt;If it's &amp;quot;close to 1000&amp;quot; points then I would expect it to be 1001 points, which used to be normal back in the 1990s but is rather fewer than most codes use these days. Nevertheless, it is not so few that it should be a severe problem.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-06-27T22:58:35.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11202" PostTypeId="2" ParentId="11199" CreationDate="2023-06-28T10:11:22.983" Score="6" Body="&lt;p&gt;Normally &lt;span class=&quot;math-container&quot;&gt;$\textit{ab initio}$&lt;/span&gt; methods should give approximately the orbital energies that the electrons will occupy after applying the exclusion principle. The accuracy of the total energy is related to the accuracy of these orbital energies and how the method has treated &lt;span class=&quot;math-container&quot;&gt;$V_\text{ee}$&lt;/span&gt;. Most of the used methods solve an electron in a mean field potential with a more or less advanced description of the orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The highest occupied atomic orbital energy is important as it can be related to the experimental ionization energy to compare the accuracy of these eigenvalues.&lt;/p&gt;&#xA;&lt;p&gt;A mean field approximation is quite similar to the solution of a hydrogenic atom with an effective potential. The eigenvalues of a hydrogenic atom are analytical:  &lt;span class=&quot;math-container&quot;&gt;$-Z^2/2n^2$&lt;/span&gt; and very inaccurate for a multi-electronic system. Because of &lt;span class=&quot;math-container&quot;&gt;$+V_\text{ee}$&lt;/span&gt; the eigenvalues should be upshifted. A crude approximation will be to determine an effective potential &lt;span class=&quot;math-container&quot;&gt;$Z_\text{eff}$&lt;/span&gt; acting on one electron using the previous expression. This parameter gives a more efficient description but is not accurate enough. The effective potential should have a radial dependency, but all the methods with a local potential only dependent  on &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; especially a local exchange potential do not lead to accurate eigenvalues. The effective potential should be non-local this means should contain two or more  spatial variables: &lt;span class=&quot;math-container&quot;&gt;$V_\text{eff}(r,r')$&lt;/span&gt; this is the main reason why Hartree-Fock and related methods have the most accurate eigenvalues (orbital energies). You should rely on these methods for what you are looking for:  valence electron energies that are merely the eigenvalues.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastEditorUserId="6019" LastEditDate="2023-07-26T18:30:44.290" LastActivityDate="2023-07-26T18:30:44.290" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11205" PostTypeId="1" CreationDate="2023-06-29T14:00:58.243" Score="6" ViewCount="90" Body="&lt;p&gt;I have been using the Deformation Potential theory to evaluate the electron scattering rates in nanomaterials. In each case, I was under the impression that the Conduction Band Minimum (CBM) and the Valence Band Maximum (VBM) should be expected to vary linearly with applied strain. For example, refer to Figure 2 of Reference 1.&lt;/p&gt;&#xA;&lt;p&gt;However, Reference 2 (Figure 5) shows the CBM and VBM varying in a non-linear form.&lt;/p&gt;&#xA;&lt;p&gt;Is there an explanation for such a variation? Was it wrong to assume that the band edges of semiconductors would vary linearly with applied strain?&lt;/p&gt;&#xA;&lt;p&gt;Note: I have read a significant number of articles (for various materials and nano-structures) where the band edges vary linearly.&lt;/p&gt;&#xA;&lt;h3&gt;References&lt;/h3&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Chen, X.; Zhang, X.; Gao, J.; Li, Q.; Shao, Z.; Lin, H.; Pan, M. Computational Search for Better Thermoelectric Performance in Nickel-Based Half-Heusler Compounds. ACS Omega, 2021, 6, 18269–18280. &lt;a href=&quot;https://doi.org/10.1021/acsomega.1c02172&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acsomega.1c02172&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Ma, W.; Record, M.-C.; Tian, J.; Boulet, P. Strain Effects on the Electronic and Thermoelectric Properties of n(PbTe)-m(Bi2Te3) System Compounds. Materials, 2021, 14, 4086. &lt;a href=&quot;https://doi.org/10.3390/ma14154086&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.3390/ma14154086&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="7" LastEditDate="2023-06-30T13:38:27.147" LastActivityDate="2023-12-21T09:48:50.813" Title="Variation of Conduction band minimum and valence band maximum with applied strain in semconductors" Tags="|density-functional-theory|band-structure|electronic-structure|electronic-transport|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11206" PostTypeId="1" CreationDate="2023-06-29T16:38:27.580" Score="3" ViewCount="61" Body="&lt;p&gt;I am trying to find the interaction potential profile of electrolyte and a slab system(particularly one type of oxygen atom). I started with two slab systems, one with 200 odd atoms and the other with 520 odd atoms. So far I have been getting big deviations in the energy profiles. My guessing is that this could be a finite size effect and is there a way to check this?&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-08-03T08:02:40.357" Title="Is there a way to minimize the finite size effects in VASP calculations?" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11207" PostTypeId="1" CreationDate="2023-06-29T17:58:29.717" Score="3" ViewCount="221" Body="&lt;p&gt;I am trying to do a band structure calculation of a noncollinear magnetic system. I am getting results that are nowhere close to what I'm expecting. I need help checking if I am following the right procedure:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The relaxation step is skipped (using the experimental value for the crystal structure)&lt;/li&gt;&#xA;&lt;li&gt;A self-consistency calculation with SOC and Hubbard-U correction.&lt;/li&gt;&#xA;&lt;li&gt;A band structure calculation using the &lt;code&gt;CHGCAR&lt;/code&gt; file obtained from the previous step.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The &lt;code&gt;INCAR&lt;/code&gt; files that I used for both runs are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;For the self-consistent calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;&#xA;IBRION = -1&#xA;NSW = 0&#xA;&#xA;PREC = Normal&#xA;ENCUT = 300 eV&#xA;NELM = 200&#xA;EDIFF = 1E-6&#xA;&#xA;NBANDS = 120&#xA;&#xA;LSORBIT = .TRUE.&#xA;ISPIN = 2&#xA;MAGMOM = 0 0 0 0 0 0 0 0 -2.7 0 0 2.7&#xA;GGA_COMPAT = .FALSE.&#xA;ISYM =-1&#xA;&#xA;LDAU=.TRUE.&#xA;LDAUTYPE = 3&#xA;LDAUL = -1 3 &#xA;LDAUU = 0 6.3 &#xA;LDAUJ = 0 0.7 &#xA;LMAXMIX = 6&#xA;LDAUPRINT = 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;For the band structure calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 1&#xA;ICHARG = 11&#xA;&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;&#xA;PREC = Normal&#xA;ENCUT = 300 eV&#xA;NELM = 200&#xA;EDIFF = 1E-6&#xA;&#xA;NBANDS = 120&#xA;&#xA;LORBIT = 11&#xA;&#xA;&#xA;LSORBIT = .TRUE.&#xA;ISPIN = 2&#xA;SAXIS =  0 0 1&#xA;MAGMOM = 0 0 0 0 0 0 0 0 -2.7 0 0 2.7&#xA;GGA_COMPAT = .FALSE.&#xA;ISYM =-1&#xA;&#xA;LDAU=.TRUE.&#xA;LDAUTYPE = 3&#xA;LDAUL = -1 3 &#xA;LDAUU = 0 6.3 &#xA;LDAUJ = 0 0.7 &#xA;LMAXMIX = 6&#xA;LDAUPRINT = 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Your help is appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7479" LastEditorUserId="403" LastEditDate="2023-07-21T00:02:41.710" LastActivityDate="2023-07-21T00:02:41.710" Title="Noncollinear band structure calculation with VASP" Tags="|density-functional-theory|vasp|condensed-matter|dft-u|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11208" PostTypeId="1" AcceptedAnswerId="11210" CreationDate="2023-06-30T07:49:53.810" Score="6" ViewCount="247" Body="&lt;p&gt;I am trying to calculate the stability of CO at HF/3-21g level using G09. I am trying to reproduce an issue that was observed in PySCF, and I have made the following observations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;If I use the default arguments &lt;code&gt;stable=opt hf/3-21g&lt;/code&gt; the calculations would work normally, and the wavefunction would converge to a UHF state, since the code finds an RHF-&amp;gt;UHF instability.&lt;/li&gt;&#xA;&lt;li&gt;However, If I try to use &lt;code&gt;stable=(opt,fc) hf/3-21g&lt;/code&gt; the code will crash with an error message&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt; Operation on file out of range.&#xA; FileIO: IOper= 2 IFilNo(1)=  -554 Len=          77 IPos=           0 Q=   23003655819672&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I need to use a frozen core to compare my calculations from G09 and PySCF. Any pointers on why this is happening would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2023-07-01T02:19:03.330" LastActivityDate="2023-07-02T13:48:03.287" Title="Frozen core Stability Calculations in G09?" Tags="|gaussian|hartree-fock|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11209" PostTypeId="1" AcceptedAnswerId="11230" CreationDate="2023-06-30T08:38:10.077" Score="7" ViewCount="74" Body="&lt;p&gt;I have a coarse-grained particle (bead) that I want to keep off the plane from the plane of other beads which form like a 2D plane. Do people employ improper dihedral for this or any other bonded parameters I can look into? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-07-05T00:33:48.807" Title="Keeping a coarse grained particle off plane (Molecular Dynamics)" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11210" PostTypeId="2" ParentId="11208" CreationDate="2023-06-30T11:35:32.333" Score="7" Body="&lt;p&gt;A &amp;quot;frozen core&amp;quot; is used to freeze &amp;quot;core&amp;quot; electrons from correlating.&lt;/p&gt;&#xA;&lt;p&gt;There's no correlation in HF calculations, so it would make sense for a frozen core to only have a visible effect on post-HF calculations, which the code that you've shown doesn't specify at all.&lt;/p&gt;&#xA;&lt;p&gt;Apart from that, there seems to be an index out of bounds which suggests a bug in G09 or an error in your input. Maybe someone with G16 can see if this bug persists there.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-06-30T13:46:00.957" LastActivityDate="2023-06-30T13:46:00.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11211" PostTypeId="2" ParentId="11208" CreationDate="2023-06-30T16:17:18.930" Score="5" Body="&lt;p&gt;I think, the answer of @NikeDattani is clear enough a &lt;a href=&quot;http://gaussian.com/frozencore/&quot; rel=&quot;nofollow noreferrer&quot;&gt;frozen core&lt;/a&gt; option should not be used for SCF methods as HF and even for DFT except for Double-Hybrid methods : &lt;a href=&quot;https://gaussian.com/mp/&quot; rel=&quot;nofollow noreferrer&quot;&gt;MP Methods&lt;/a&gt;. Therefore your calculation  would not work even if your input was rightly formulated. In fact, for performing frozen core calculations your route section might be like this :  &lt;code&gt;#p stable=opt MP(fc,semidirect)/3-21g ...&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;This will certainly output an error if your method is not a Post-SCF method. Even if you code works in G16, the option &amp;quot;fc&amp;quot; is ignored. I cannot tell more about this option because I am not used to perform this type of calculation.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastEditorUserId="6019" LastEditDate="2023-07-02T05:12:56.283" LastActivityDate="2023-07-02T05:12:56.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11212" PostTypeId="1" CreationDate="2023-07-01T15:12:14.180" Score="2" ViewCount="333" Body="&lt;p&gt;I am calculating the band structure using HSE06 using wannier method. I have manage to perform the scf calculations and first processing of wannier.x to generate the .nnk file. but when I run the pw2wannier.x the following error occur. I don't know what caused this error as I generate the k-point using the kmesh.pl method. your help is hilgy appreciated.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;G-vector sticks info&#xA;     --------------------&#xA;     sticks:   dense  smooth     PW     G-vecs:    dense   smooth      PW&#xA;     Sum       10805    5417   1481               713315   252257   35969&#xA;&#xA;     Using Slab Decomposition&#xA;&#xA;     Reading collected, re-writing distributed wavefunctions&#xA;&#xA;  Spin CASE ( default = unpolarized )&#xA;&#xA;  Wannier mode is: standalone     &#xA;&#xA;  -----------------&#xA;  *** Reading nnkp &#xA;  -----------------&#xA;&#xA;  Checking info from wannier.nnkp file&#xA;&#xA;  - Real lattice is ok&#xA;  - Reciprocal lattice is ok&#xA;  Something wrong! &#xA;  k-point            3  is wrong&#xA;   0.0000000000000000        0.0000000000000000       0.79226244387103761     &#xA;   0.0000000000000000        0.0000000000000000      -0.39613122589683109     &#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine pw2wannier90 (3):&#xA;     problems with k-points&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7488" LastEditorUserId="1380" LastEditDate="2023-07-02T04:05:12.560" LastActivityDate="2023-12-31T14:09:11.153" Title="Problem with k-points with pw2wannier" Tags="|quantum-espresso|band-structure|hse06|wannier90|bandgap|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11213" PostTypeId="2" ParentId="11212" CreationDate="2023-07-01T19:04:32.163" Score="1" Body="&lt;p&gt;I assume that you used open_grid.x in order to expand the k-point grid from IBZ to full BZ. In this case the k-point mesh should be taken from the output of open_grid.x.&lt;/p&gt;&#xA;&lt;p&gt;Also I found that when using open_grid instead of non-SCF run (at least in QE v.6.5) it is needed to manually rename files in scratch directory, i.e. pwscf_open -&amp;gt; pwscf&lt;/p&gt;&#xA;&lt;p&gt;Hope it could help&lt;/p&gt;&#xA;&lt;p&gt;Update, useful links:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://christoph-wolf.at/2018/10/10/band-structure-calculations-in-qe-using-hybrid-functionals/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://christoph-wolf.at/2018/10/10/band-structure-calculations-in-qe-using-hybrid-functionals/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1176/calculating-hse06-band-structures-on-quantum-espresso&quot;&gt;Calculating HSE06 band structures on Quantum ESPRESSO&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6566" LastEditorUserId="6566" LastEditDate="2023-12-01T14:01:25.177" LastActivityDate="2023-12-01T14:01:25.177" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11214" PostTypeId="1" CreationDate="2023-07-02T03:49:44.197" Score="2" ViewCount="34" Body="&lt;p&gt;Doping is an efficient strategy to narrow the bandgap of wide-bandgap metal oxides, in order to harvest more light. Let's consider the mechanism by which doping reduces the bandgap of a metal oxide through the introduction of doping levels above the valence band maximum (VBM) of the metal oxide. This mechanism can give rise to two different types of doping levels:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Localized doping levels that do not merge with the VBM, as shown in Fig. 1a&lt;/li&gt;&#xA;&lt;li&gt;Delocalized doping levels that merge apparently with the VBM, as shown in Fig. 1b&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CdcWpm.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CdcWpm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What are the possible advantages of the second type of doping levels as compared to the first one for photocatalytic applications? The one advantage I can think of is that the localized doping levels can act as charge recombination centers, what are other possible advantages?&lt;/p&gt;&#xA;" OwnerUserId="1483" LastActivityDate="2023-07-02T03:49:44.197" Title="Doping induced overall bandgap narrowing vs. bandgap narrowing achieved by localized doping induced level" Tags="|band-structure|condensed-matter|bandgap|doping|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11215" PostTypeId="1" AcceptedAnswerId="11217" CreationDate="2023-07-02T04:34:39.667" Score="4" ViewCount="235" Body="&lt;p&gt;In the context of thermodynamics, an ensemble is a hypothetical collection of identical copies of a system, each in a different state, used to represent the statistical behavior of the system.&lt;/p&gt;&#xA;&lt;p&gt;That means I have to maintain a collection of systems inside an ensemble class.&lt;/p&gt;&#xA;&lt;p&gt;In the book named &lt;a href=&quot;https://books.google.pl/books?id=kVeg20PS-7kC&amp;amp;printsec=copyright&amp;amp;redir_esc=y#v=onepage&amp;amp;q&amp;amp;f=false&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Molecular Simulation of Fluids&lt;/em&gt; by Sadus&lt;/a&gt;, they have &lt;code&gt;Ensemble&lt;/code&gt; class but, no &lt;code&gt;System&lt;/code&gt; class.&lt;/p&gt;&#xA;&lt;p&gt;Why is that?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-07-02T04:44:04.940" LastActivityDate="2023-07-05T00:18:21.460" Title="Thermodynamics: System versus Ensemble" Tags="|statistical-thermodynamics|monte-carlo|atomistic-simulation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11216" PostTypeId="1" CreationDate="2023-07-02T05:12:59.797" Score="3" ViewCount="45" Body="&lt;p&gt;Can someone suggest me a method to generate a beta cristobalite structure with atoms less than 200.? I tried VMD's inorganic builder tool but so far unsuccessful.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastEditorUserId="5" LastEditDate="2023-07-02T12:13:23.983" LastActivityDate="2023-07-02T14:40:34.803" Title="Creating a beta cristobalite with 200 or fewer atoms" Tags="|software|molecular-modeling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11217" PostTypeId="2" ParentId="11215" CreationDate="2023-07-02T05:49:36.623" Score="5" Body="&lt;p&gt;The textbook you refer to states (p21):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The time-averaged properties of the real system are related to the ensemble average by ... the ergodic hypothesis.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;That is, taking N snapshots of &lt;em&gt;one system&lt;/em&gt; as it evolves through time (with enough time between that snapshots are not too correlated) and averaging over those is equivalent to taking one snapshot in time of N systems and taking &lt;em&gt;their&lt;/em&gt; average.&lt;/p&gt;&#xA;&lt;p&gt;Thus, both in molecular dynamics and Monte Carlo simulation, the &amp;quot;ensemble&amp;quot; is usually not an actual collection of a large number of macrostate-identical systems -- it usually refers to the equations of motion (MD) / choice of sampling moves (MC), and any modifications, needed to ensure that a single trajectory returns ergodically-consistent results with a hypothetical many-systems ensemble average.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;EDIT, from comment: In terms of names for source code objects, we'd use &lt;code&gt;Ensemble&lt;/code&gt; instead of &lt;code&gt;System&lt;/code&gt; because &amp;quot;ensembles&amp;quot; refer to a set of moves that apply to &lt;em&gt;any&lt;/em&gt; system, rather than a specific system. For example, MC for NPT must sample box size changes while MC for NVT doesn't. So you'd have NVT and NPT inherit from the &lt;code&gt;Ensemble&lt;/code&gt; base class because they're different ensembles, while being broadly applicable across any system you want to simulate. &amp;quot;&lt;code&gt;System&lt;/code&gt;&amp;quot; makes no sense as a substitute here (and it's too easily confused with other concepts -- such as the &lt;code&gt;sys&lt;/code&gt; module in Python).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-07-05T00:18:21.460" LastActivityDate="2023-07-05T00:18:21.460" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11218" PostTypeId="2" ParentId="11215" CreationDate="2023-07-02T13:47:02.533" Score="2" Body="&lt;p&gt;I like how this book starts by defining all the concepts to be used after:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.google.com.br/books/edition/Thermodynamics_and_Introductory_Statisti/QgzJ5Do6pfsC?hl=pt-BR&amp;amp;gbpv=0&quot; rel=&quot;nofollow noreferrer&quot;&gt;THERMODYNAMICS AND INTRODUCTORY STATISTICAL MECHANICS. Bruno Linder.  John Wiley &amp;amp; Sons, Inc., 2004&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;He defines &lt;code&gt;system&lt;/code&gt; as:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A system is part of the physical world in which one is interested. What is not&#xA;the system is the environment or the surroundings. We distinguish between&#xA;several types of systems:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;An isolated system is a system that is totally uninfluenced by the&#xA;surroundings. There is no possibility of exchange of energy or matter&#xA;with surroundings.&lt;/li&gt;&#xA;&lt;li&gt;A closed system is a system in which energy but not matter can&#xA;exchange with the surroundings.&lt;/li&gt;&#xA;&lt;li&gt;An open system is a system in which both energy and matter can&#xA;exchange with the surroundings&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;His definition of &lt;code&gt;ensemble&lt;/code&gt; is:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;During the time of measurement on a single system, the system undergoes a&#xA;large number of changes from one microstate to another. The observed&#xA;macroscopic properties of the system are time averages of the properties&#xA;of the instantaneous microstates—that is, of the mechanical properties.&#xA;Time-average calculations are virtually impossible to carry out. A way to&#xA;get around this difficulty is to replace the time average of a single system&#xA;by an &lt;code&gt;ensemble&lt;/code&gt; average of a very large collection of systems. That is,&#xA;instead of looking at one system over a period of time, one looks at a&#xA;(mental) collection of a large number of systems (all of which are replicas&#xA;of the system under consideration) at a given instance of time. Thus, in an&#xA;&lt;code&gt;ensemble of systems&lt;/code&gt;, all systems have certain properties in common (such&#xA;as same N, V, E) but differ in their microscopic specifications; that is, they&#xA;have different microstates.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-07-02T13:47:02.533" CommentCount="0" CommunityOwnedDate="2023-07-31T13:23:40.287" ContentLicense="CC BY-SA 4.0" />
  <row Id="11219" PostTypeId="2" ParentId="11208" CreationDate="2023-07-02T13:48:03.287" Score="1" Body="&lt;p&gt;To amend the previous answers, there is no reason a priori why frozen core stability checks would not make sense. My intuition would be that the deep lying orbitals can be safely ignored in stability analyses, since the energy penalty of not occupying them is so high.&lt;/p&gt;&#xA;&lt;p&gt;However, stability checks are typically carried out with all orbitals, since the frozen core approximation would not lead to significant savings in the computational time: you only have &lt;code&gt;o*v&lt;/code&gt; rotations, which is similar to CI singles theory.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-07-02T13:48:03.287" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11220" PostTypeId="2" ParentId="11199" CreationDate="2023-07-02T13:56:26.587" Score="4" Body="&lt;p&gt;In Hartree-Fock theory, orbital energies are indeed good estimates for the energies of single electrons. This is because of &lt;a href=&quot;https://en.wikipedia.org/wiki/Koopmans%27_theorem&quot; rel=&quot;nofollow noreferrer&quot;&gt;Koopmans' theorem&lt;/a&gt;: if you assume that the other electrons do not relax when you remove an electron, you will find that the difference in the total energies is given exactly by the orbital energy.&lt;/p&gt;&#xA;&lt;p&gt;However, here you already have two approximations: Hartree-Fock, and that the other orbitals do not relax. Hartree-Fock neglects electron correlation, and the relaxation effects can be significant, especially in the case of core orbitals.&lt;/p&gt;&#xA;&lt;p&gt;The better alternative is to study Dyson orbitals, which can also be computed from accurate many-body methods.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-07-02T13:56:26.587" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11221" PostTypeId="2" ParentId="11216" CreationDate="2023-07-02T14:40:34.803" Score="3" Body="&lt;p&gt;This image was produced with VESTA using the CIF bellow. It has 74 atoms:&lt;/p&gt;&#xA;&lt;img src=&quot;https://i.stack.imgur.com/Oabn5.png&quot; width=&quot;500&quot; height=&quot;300&quot;&gt;&#xA;&lt;p&gt;CIF file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#(C) 2023 by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure.  All rights reserved.&#xA;data_77458-ICSD&#xA;_database_code_ICSD 77458&#xA;_audit_creation_date 2003-04-01&#xA;_audit_update_record 2012-02-01&#xA;_chemical_name_common 'Silicon oxide'&#xA;_chemical_formula_structural 'Si O2'&#xA;_chemical_formula_sum 'O2 Si1'&#xA;_chemical_name_structure_type Cristobalite(high)#SiO2&#xA;_chemical_name_mineral &amp;quot;'Cristobalite beta'&amp;quot;&#xA;_exptl_crystal_density_diffrn 2.21&#xA;_diffrn_ambient_temperature 573.&#xA;_citation_title&#xA;&#xA;;&#xA;Landau free energy and order parameter behaviour of the alpha/beta phase&#xA;transition in cristobalite&#xA;;&#xA;loop_&#xA;_citation_id&#xA;_citation_journal_full&#xA;_citation_year&#xA;_citation_journal_volume&#xA;_citation_page_first&#xA;_citation_page_last&#xA;_citation_journal_id_ASTM&#xA;primary 'Zeitschrift fuer Kristallographie' 1992 201 125 145 ZEKRDZ&#xA;loop_&#xA;_citation_author_citation_id&#xA;_citation_author_name&#xA;primary 'Schmahl, W.W.'&#xA;primary 'Swainson, I.P.'&#xA;primary 'Dove, M.T.'&#xA;primary 'Graeme-Barber, A.'&#xA;_cell_length_a 7.12637(1)&#xA;_cell_length_b 7.12637&#xA;_cell_length_c 7.12637&#xA;_cell_angle_alpha 90.&#xA;_cell_angle_beta 90.&#xA;_cell_angle_gamma 90.&#xA;_cell_volume 361.91&#xA;_cell_formula_units_Z 8&#xA;_space_group_name_H-M_alt 'F d -3 m S'&#xA;_space_group_IT_number 227&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 'z+1/4, y+1/4, -x+1/4'&#xA;2 'y+1/4, x+1/4, -z+1/4'&#xA;3 'x+1/4, z+1/4, -y+1/4'&#xA;4 'z+1/4, x+1/4, -y+1/4'&#xA;5 'y+1/4, z+1/4, -x+1/4'&#xA;6 'x+1/4, y+1/4, -z+1/4'&#xA;7 'z+1/4, -y+1/4, x+1/4'&#xA;8 'y+1/4, -x+1/4, z+1/4'&#xA;9 'x+1/4, -z+1/4, y+1/4'&#xA;10 'z+1/4, -x+1/4, y+1/4'&#xA;11 'y+1/4, -z+1/4, x+1/4'&#xA;12 'x+1/4, -y+1/4, z+1/4'&#xA;13 '-z+1/4, y+1/4, x+1/4'&#xA;14 '-y+1/4, x+1/4, z+1/4'&#xA;15 '-x+1/4, z+1/4, y+1/4'&#xA;16 '-z+1/4, x+1/4, y+1/4'&#xA;17 '-y+1/4, z+1/4, x+1/4'&#xA;18 '-x+1/4, y+1/4, z+1/4'&#xA;19 '-z+1/4, -y+1/4, -x+1/4'&#xA;20 '-y+1/4, -x+1/4, 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x+1/4, -z+3/4'&#xA;99 'x+3/4, z+1/4, -y+3/4'&#xA;100 'z+3/4, x+1/4, -y+3/4'&#xA;101 'y+3/4, z+1/4, -x+3/4'&#xA;102 'x+3/4, y+1/4, -z+3/4'&#xA;103 'z+3/4, -y+1/4, x+3/4'&#xA;104 'y+3/4, -x+1/4, z+3/4'&#xA;105 'x+3/4, -z+1/4, y+3/4'&#xA;106 'z+3/4, -x+1/4, y+3/4'&#xA;107 'y+3/4, -z+1/4, x+3/4'&#xA;108 'x+3/4, -y+1/4, z+3/4'&#xA;109 '-z+3/4, y+1/4, x+3/4'&#xA;110 '-y+3/4, x+1/4, z+3/4'&#xA;111 '-x+3/4, z+1/4, y+3/4'&#xA;112 '-z+3/4, x+1/4, y+3/4'&#xA;113 '-y+3/4, z+1/4, x+3/4'&#xA;114 '-x+3/4, y+1/4, z+3/4'&#xA;115 '-z+3/4, -y+1/4, -x+3/4'&#xA;116 '-y+3/4, -x+1/4, -z+3/4'&#xA;117 '-x+3/4, -z+1/4, -y+3/4'&#xA;118 '-z+3/4, -x+1/4, -y+3/4'&#xA;119 '-y+3/4, -z+1/4, -x+3/4'&#xA;120 '-x+3/4, -y+1/4, -z+3/4'&#xA;121 '-z+1/2, -y, x+1/2'&#xA;122 '-y+1/2, -x, z+1/2'&#xA;123 '-x+1/2, -z, y+1/2'&#xA;124 '-z+1/2, -x, y+1/2'&#xA;125 '-y+1/2, -z, x+1/2'&#xA;126 '-x+1/2, -y, z+1/2'&#xA;127 '-z+1/2, y, -x+1/2'&#xA;128 '-y+1/2, x, -z+1/2'&#xA;129 '-x+1/2, z, -y+1/2'&#xA;130 '-z+1/2, x, -y+1/2'&#xA;131 '-y+1/2, z, -x+1/2'&#xA;132 '-x+1/2, y, -z+1/2'&#xA;133 'z+1/2, -y, -x+1/2'&#xA;134 'y+1/2, -x, -z+1/2'&#xA;135 'x+1/2, -z, -y+1/2'&#xA;136 'z+1/2, -x, -y+1/2'&#xA;137 'y+1/2, -z, -x+1/2'&#xA;138 'x+1/2, -y, -z+1/2'&#xA;139 'z+1/2, y, x+1/2'&#xA;140 'y+1/2, x, z+1/2'&#xA;141 'x+1/2, z, y+1/2'&#xA;142 'z+1/2, x, y+1/2'&#xA;143 'y+1/2, z, x+1/2'&#xA;144 'x+1/2, y, z+1/2'&#xA;145 'z+3/4, y+3/4, -x+1/4'&#xA;146 'y+3/4, x+3/4, -z+1/4'&#xA;147 'x+3/4, z+3/4, -y+1/4'&#xA;148 'z+3/4, x+3/4, -y+1/4'&#xA;149 'y+3/4, z+3/4, -x+1/4'&#xA;150 'x+3/4, y+3/4, -z+1/4'&#xA;151 'z+3/4, -y+3/4, x+1/4'&#xA;152 'y+3/4, -x+3/4, z+1/4'&#xA;153 'x+3/4, -z+3/4, y+1/4'&#xA;154 'z+3/4, -x+3/4, y+1/4'&#xA;155 'y+3/4, -z+3/4, x+1/4'&#xA;156 'x+3/4, -y+3/4, z+1/4'&#xA;157 '-z+3/4, y+3/4, x+1/4'&#xA;158 '-y+3/4, x+3/4, z+1/4'&#xA;159 '-x+3/4, z+3/4, y+1/4'&#xA;160 '-z+3/4, x+3/4, y+1/4'&#xA;161 '-y+3/4, z+3/4, x+1/4'&#xA;162 '-x+3/4, y+3/4, z+1/4'&#xA;163 '-z+3/4, -y+3/4, -x+1/4'&#xA;164 '-y+3/4, -x+3/4, -z+1/4'&#xA;165 '-x+3/4, -z+3/4, -y+1/4'&#xA;166 '-z+3/4, -x+3/4, -y+1/4'&#xA;167 '-y+3/4, -z+3/4, -x+1/4'&#xA;168 '-x+3/4, -y+3/4, -z+1/4'&#xA;169 '-z+1/2, -y+1/2, x'&#xA;170 '-y+1/2, -x+1/2, z'&#xA;171 '-x+1/2, -z+1/2, y'&#xA;172 '-z+1/2, -x+1/2, y'&#xA;173 '-y+1/2, -z+1/2, x'&#xA;174 '-x+1/2, -y+1/2, z'&#xA;175 '-z+1/2, y+1/2, -x'&#xA;176 '-y+1/2, x+1/2, -z'&#xA;177 '-x+1/2, z+1/2, -y'&#xA;178 '-z+1/2, x+1/2, -y'&#xA;179 '-y+1/2, z+1/2, -x'&#xA;180 '-x+1/2, y+1/2, -z'&#xA;181 'z+1/2, -y+1/2, -x'&#xA;182 'y+1/2, -x+1/2, -z'&#xA;183 'x+1/2, -z+1/2, -y'&#xA;184 'z+1/2, -x+1/2, -y'&#xA;185 'y+1/2, -z+1/2, -x'&#xA;186 'x+1/2, -y+1/2, -z'&#xA;187 'z+1/2, y+1/2, x'&#xA;188 'y+1/2, x+1/2, z'&#xA;189 'x+1/2, z+1/2, y'&#xA;190 'z+1/2, x+1/2, y'&#xA;191 'y+1/2, z+1/2, x'&#xA;192 'x+1/2, y+1/2, z'&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_oxidation_number&#xA;Si4+ 4&#xA;O2- -2&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_B_iso_or_equiv&#xA;_atom_site_occupancy&#xA;Si1 Si4+ 8 a 0 0 0 2.61(10) 1.&#xA;O1 O2- 16 c 0.125 0.125 0.125 . 1.&#xA;loop_&#xA;_atom_site_aniso_label&#xA;_atom_site_aniso_type_symbol&#xA;_atom_site_aniso_B_11&#xA;_atom_site_aniso_B_22&#xA;_atom_site_aniso_B_33&#xA;_atom_site_aniso_B_12&#xA;_atom_site_aniso_B_13&#xA;_atom_site_aniso_B_23&#xA;O1 O2- 9.64(9) 9.64 9.64 -4.34(3) -4.34 -4.34&#xA;#End of TTdata_77458-ICSD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-07-02T14:40:34.803" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11222" PostTypeId="1" CreationDate="2023-07-02T15:30:18.213" Score="4" ViewCount="203" Body="&lt;p&gt;I wish to reproduce the results from &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2018/cp/c7cp07227a&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper by Truhlar and co-workers, where they treat a spin-forbidden reaction by considering two effective states coupled by a semi-empirical spin-orbit coupling term &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt;. They mention that they estimate the coupling term from a TD-DFT calculation.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(c) Singlet-triplet excitation energies are computed at the representative geometry using the&#xA;ADF2016.103 program package. The spin-orbit coupling is included by employing the spin-&#xA;orbit ZORA Hamiltonian. The M06-L exchange-correlation functional is used with a Slater-&#xA;type ZORA/QZ4P basis set.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(d) The singlet-triplet splitting of the representative geometry is determined by averaging the&#xA;corresponding singlet and triplet energies as calculated in step (c). The value of the coupling&#xA;constant &lt;span class=&quot;math-container&quot;&gt;$\chi$&lt;/span&gt; is updated accordingly such that the difference of the eigenvalues of the following 2 ×&#xA;2 matrix reproduces the singlet-triplet splitting.&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\begin{pmatrix} E_1 &amp;amp; \chi \\ \chi &amp;amp; E_2 \\ \end{pmatrix}$$&lt;/span&gt;&#xA;Here &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; and  are the energies of low- and high-spin states computed from the single-point&#xA;calculations using Gaussian for the representative geometry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is from their SI (file link &lt;a href=&quot;https://www.rsc.org/suppdata/c7/cp/c7cp07227a/c7cp07227a1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). There isn't much other explanation on this part of the publication.&lt;/p&gt;&#xA;&lt;p&gt;However, I do not have access to ADF, and I am curious how to accomplish this TD-DFT calculation with ORCA. I have used ORCA before, but I have never dealt with spin-orbit coupling. I know that there are ZORA or DKH Hamiltonians available for relativistic effects, and TD-DFT can deal with singlet-triplet excitations. If I understand correctly, the splitting they mention in the paper is not simply the difference between converged singlet SCF and first triplet excitation from TD-DFT as they talk about averaging energies and spin-orbit coupling (so this question is not a duplicate of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/6466/how-can-i-calculate-the-energy-gap-between-the-singlet-and-triplet-state-using-o&quot;&gt;this&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Any help with some small explanation of what type of calculation this is referring to, and some sample ORCA input files if possible, will be very helpful.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-07-02T15:30:18.213" Title="How to calculate singlet-triplet splitting energy with TD-DFT in ORCA?" Tags="|orca|spin-orbit-coupling|td-dft|spin|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11223" PostTypeId="1" AcceptedAnswerId="11224" CreationDate="2023-07-03T09:55:43.403" Score="6" ViewCount="504" Body="&lt;p&gt;I am trying to study the shifts in the Fermi level of a graphene - ssDNA hydrid system, depending on the identity of the ssDNA. The structures are obtained from a classical MD simulation, and cannot be geometry optimized. I ran two distinct calculations: one at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point and other one at a Kpoint mesh of 10x10x1. From the PDoS plots, what I observe is that the Fermi of the system is dominated by the contributions from graphene (which is expected). However, I also find that the HOMO of the ssDNA molecule lies very close to the Fermi of the system. When I am trying to compare my results to this &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/jp402403f?src=getftr&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt; (Figure 3 to be exact), I see that they get an appreciable difference in the HOMO levels of the nucleobases. The interactions between the ssDNA and the graphene surface would be largely non-covalent interactions such as &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-stacking. This leads to my question: How accurate are DFTB+ calculations for these systems?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/VfIpF.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VfIpF.jpg&quot; alt=&quot;Representative image depicting the system I am trying to study&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-07-03T10:31:06.720" LastActivityDate="2023-07-04T07:38:20.723" Title="How accurate is DFTB+ in reproducing DFT result?" Tags="|density-functional-theory|computational-chemistry|graphene|dftb-plus|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11224" PostTypeId="2" ParentId="11223" CreationDate="2023-07-03T12:29:40.600" Score="10" Body="&lt;p&gt;The DNA-graphene interaction is only weak when there is no considerable charge transfer between them. Now you have many aryl radicals in your graphene, and aryl radicals are electron-deficient radicals. This means that the Fermi level of the system is probably low, and it is not very surprising if it is comparable to or even lower than the HOMO of the DNA (in the latter case you'll see considerable charge transfer between them).&lt;/p&gt;&#xA;&lt;p&gt;The paper you cited didn't introduce defects in the graphene, so naturally their Fermi level is closer to the Fermi levels of typical conjugated organic molecules (remember that graphene is nothing but an infinitely large polycyclic aromatic hydrocarbon). As a result, the HOMO of DNA is significantly lower than the Fermi level in their system.&lt;/p&gt;&#xA;&lt;p&gt;PS: I may have said this before, but I would like to reiterate that having so many aryl radical defects in graphene is extremely unlikely in realistic settings. The aryl radicals will recombine, react with water/oxygen/solvent, or otherwise restructure themselves long before you can experimentally put your ssDNA into the hole. It is a common mistake to assume that all defects are formed by simply removing or replacing a few atoms, while neglecting the (potentially huge and extremely rapid) structural rearrangement after you made the removal or replacement, not to mention that it may be experimentally impossible to carry out that removal or replacement in the first place. Moreover, even if some of the aryl radicals survive till you could put the ssDNA into the hole, the radicals will immediately undergo hydrogen abstraction and/or radical addition reactions with the ssDNA, so that the ssDNA will soon be not a DNA anymore.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-07-04T07:38:20.723" LastActivityDate="2023-07-04T07:38:20.723" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11227" PostTypeId="2" ParentId="11206" CreationDate="2023-07-04T08:00:46.513" Score="1" Body="&lt;p&gt;The easiest method is making a bigger slab system and check results again. The finite size is hard to solve in pbc condition. We can only get a more converged results.&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-07-04T08:00:46.513" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11228" PostTypeId="1" CreationDate="2023-07-04T15:52:12.797" Score="4" ViewCount="289" Body="&lt;p&gt;When I use VASP to compute in-plane polarization of a slab with hexagonal cell (a axis along x axis, b axis is at a(-1/2,&lt;span class=&quot;math-container&quot;&gt;$\sqrt{3}$&lt;/span&gt;/2),polarization is along diagonal direction so I got it using &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;/cos30°), the result has a jump in polarization at two ends. I computed till 2% and 99% atom displacement. The structure is a slab composed of one quintuple layer and with vacuum region larger than 20A.&lt;/p&gt;&#xA;&lt;p&gt;Related input parameters for slab and berry phase:&lt;br /&gt;&#xA;#Dipole correction&lt;br /&gt;&#xA;LDIPOL = .TRUE.&lt;br /&gt;&#xA;IDIPOL = 3&lt;br /&gt;&#xA;DIPOL = 0.5 0.5 0.6&lt;br /&gt;&#xA;&lt;br /&gt;&#xA;LCALCPOL = .TRUE.&lt;/p&gt;&#xA;&lt;p&gt;I'm really confused about these and couldn't find a explanation. But if I just use those middle points (2-99%) and extrapolate them to two ends, I can get the correct dipole moment value (same as paper).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yrNFl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yrNFl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6151" LastEditorUserId="6151" LastEditDate="2023-10-23T01:24:16.223" LastActivityDate="2023-10-23T01:24:16.223" Title="polarization jump in berry phase method using VASP" Tags="|vasp|berry-phase|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11229" PostTypeId="1" AcceptedAnswerId="11231" CreationDate="2023-07-04T21:25:04.950" Score="10" ViewCount="558" Body="&lt;p&gt;I have a bunch of geometry optimisations I want to run for a cation Metal-organic complex. This is going to be a repeat of calculations that were done in &amp;quot;Turbomole&amp;quot; previously and my Prof. wants to know, if the same methodology run in Gaussian will return the same results. I also need the same workflow for another project I am working on, so it's not just treading old ground.&lt;/p&gt;&#xA;&lt;p&gt;Anyways, here's the problem: I've been out of the loop with quantum chemistry for quite a while now and I do not know how I am supposed to create an input file for Gaussian 16 in which two different theory levels are used for different atoms. The metal of the cationic complex is supposed to be treated with a higher theory level than the organic linker and there are some parts of the description that just straight up confuse me...&lt;/p&gt;&#xA;&lt;p&gt;This is the file I came up with till this point after googling a bunch:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=2GB&#xA;%chk=checkpoint.chk&#xA;%nproc=4&#xA;#P ONIOM(B3LYP/aug-cc-pVDZ,B3LYP/aug-cc-pVDZ-PP) Opt&#xA;&#xA;(4,5-Dichloro-1H-imidazol-1-yl)zinc(II)&#xA;&#xA;1 1&#xA;Zn    -2.257981    1.679840    0.081127 H&#xA;N     -0.830168    0.416312    0.021160 L&#xA;C      0.476998    0.704393    0.028443 L&#xA;Cl     1.236824    2.280002    0.093278 L&#xA;C      1.162496   -0.516566   -0.026780 L&#xA;Cl     2.910383   -0.699600   -0.041468 L&#xA;N      0.218700   -1.486345   -0.064823 L&#xA;C     -1.010691   -0.893184   -0.034491 L&#xA;H     -1.906562   -1.484851   -0.056446 L&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am almost certain this is wrong. I always thought ONIOM was just for QM/MM stuff.&lt;/p&gt;&#xA;&lt;p&gt;Another thing that confuses me is that the theory level of the zinc ion is supposed to include &amp;quot;Stuttgart-Dresden ECPs&amp;quot;?&lt;/p&gt;&#xA;&lt;p&gt;How do I fix this? Did I miss that section in the Gaussian reference manual? Is the full manual not available for free online?&lt;/p&gt;&#xA;&lt;p&gt;As requested, this is the DOI of the paper in question:&#xA;&lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/jacs.3c01933&quot; rel=&quot;noreferrer&quot;&gt;https://pubs.acs.org/doi/pdf/10.1021/jacs.3c01933&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The relevant figure for the QM calculations is Figure 7. The procedure is described in the &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.3c01933#article_content-right&quot; rel=&quot;noreferrer&quot;&gt;supporting information&lt;/a&gt; under section 2.&lt;/p&gt;&#xA;&lt;p&gt;The excerpt describing the settings is as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Binding  energies  haven  been  computed  on  the  hybrid  DFT  level  or  theory  with  the  B3LYP functional and aug-cc-pVDZ basis sets (aug-cc-pVDZ-PP and Stuttgart-Dresden ECPs für Zn) including the dispersion correction D3 with Becke-Johnson damping. The TURBOMOLE (V7.3) suite of programs has been used. We used the resolution of identity (RI) approximation with default auxiliary basis functions and a refined grid “m5” for numerically integrating exchange and correlation  contributions. Both  the  structure  of the  anionic  linker  and  the  cationic  product  have been fully optimized within Cs symmetry. For linkers with two chemically different nitrogen donors (i.e. two different [Zn(Xim)]+ isomers) both binding energies were computed and averaged. As a descriptor we use the relative binding energy with the basic imidazolate as reference point.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7501" LastEditorUserId="7" LastEditDate="2023-07-05T13:32:18.863" LastActivityDate="2023-07-05T17:03:54.697" Title="How can I specify different theory levels for different atoms in Gaussian?" Tags="|gaussian|geometry-optimization|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11230" PostTypeId="2" ParentId="11209" CreationDate="2023-07-05T00:33:48.807" Score="5" Body="&lt;p&gt;It is very difficult to say &lt;em&gt;how&lt;/em&gt; you should do what you want (&amp;quot;keep a bead off a plane of other beads&amp;quot;) without knowing &lt;em&gt;why&lt;/em&gt; you want to do so.&lt;/p&gt;&#xA;&lt;p&gt;So, concretely, let's say I'm modelling a lipid bilayer, and I am modelling a small molecule in solution on one side of it, and I don't want it to pass through the bilayer. (Unfortunately, the advice I give in this scenario might be completely irrelevant to your application -- but you must give more detail to receive more detailed useful advice.)&lt;/p&gt;&#xA;&lt;p&gt;There are one of two valid reasons I might want to stop this small molecule from passing through the lipid bilayer:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;I might want this on &lt;em&gt;physical&lt;/em&gt; grounds. Maybe we know experimentally that this molecule does not actually pass through cell membranes, but I'm seeing permeation in my simulation.&lt;/li&gt;&#xA;&lt;li&gt;I might want this on &lt;em&gt;mathematical&lt;/em&gt; grounds. That is, the molecule &lt;em&gt;does&lt;/em&gt; pass through the cell membrane (both experimentally and in simulation), but I want to, say, sample the free energy landscape of membrane passage so that I can compare it to another small molecule (to compare between drug candidates, let's say).&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;These two reasons require two different responses.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;If I want the small molecule to not pass the lipid bilayer for &lt;em&gt;physical&lt;/em&gt; reasons, then my model must include a similar &lt;em&gt;physical&lt;/em&gt; mechanism -- that is, the lipid headgroups should cohere enough to each other and interact repulsively enough with the small molecule that the cost of permeation is too high.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Note that this interaction must be defined entirely in terms of the local molecule-lipid headgroup potential, and my molecule is not allowed to &amp;quot;know&amp;quot; where it is in the simulation box or relative to the membrane plane (since, in an experiment, molecules do not &amp;quot;know&amp;quot; how near or far they are from a membrane outside of local interactions either).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If I want the small molecule to not pass the lipid bilayer for &lt;em&gt;mathematical&lt;/em&gt; reasons, then I should impose a well-defined (and preferably very simple) &lt;em&gt;mathematical&lt;/em&gt; additional force on the molecule.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In this case, I &lt;em&gt;can&lt;/em&gt; use the molecule's distance from the lipid bilayer as an input factor for calculating the force (so, for example, I might impose a harmonic restraint on the &lt;em&gt;z&lt;/em&gt;-distance between the small molecule's center of mass and the lipid headgroups' average &lt;em&gt;z&lt;/em&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Note that this requires that I can eventually convert the mathematically-biased simulation back into experimentally-relevant results, which will control the mathematical formula I use (for example, it's much easier to calculate some quantities for a harmonic potential than for any other arbitrarily-shaped potential).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I hope this helps. Note that in both cases it's not really conventional to impose &amp;quot;improper&amp;quot; or &amp;quot;dihedral&amp;quot; interactions, which are usually used for modelling &lt;em&gt;intra&lt;/em&gt;-molecular interactions such as backbone torsions.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-07-05T00:33:48.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11231" PostTypeId="2" ParentId="11229" CreationDate="2023-07-05T01:05:24.200" Score="14" Body="&lt;p&gt;While ONIOM QM/QM is possible, I don't think that is what you want to be doing. From your example input, it looks like you are just trying to use a different basis function on specific atoms, but the same DFT functional on all atoms.&lt;/p&gt;&#xA;&lt;p&gt;In this case, what you are interested in would be the &lt;code&gt;Gen&lt;/code&gt; and &lt;code&gt;GenECP&lt;/code&gt; &lt;a href=&quot;https://gaussian.com/gen/&quot; rel=&quot;noreferrer&quot;&gt;keywords&lt;/a&gt;. These allow you to specify basis functions/pseudopotentials to use for specific elements.&lt;/p&gt;&#xA;&lt;p&gt;Your input might look something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=2GB&#xA;%chk=checkpoint.chk&#xA;%nproc=4&#xA;#P B3LYP/GenECP/Auto EmpiricalDispersion=GD3BJ Integral(Grid=Superfine) Opt&#xA;&#xA;&#xA;(4,5-Dichloro-1H-imidazol-1-yl)zinc(II)&#xA;&#xA;1 1&#xA;Zn    -2.257981    1.679840    0.081127&#xA;N     -0.830168    0.416312    0.021160 &#xA;C      0.476998    0.704393    0.028443 &#xA;Cl     1.236824    2.280002    0.093278 &#xA;C      1.162496   -0.516566   -0.026780 &#xA;Cl     2.910383   -0.699600   -0.041468 &#xA;N      0.218700   -1.486345   -0.064823 &#xA;C     -1.010691   -0.893184   -0.034491 &#xA;H     -1.906562   -1.484851   -0.056446 &#xA;&#xA;C N Cl H 0&#xA;aug-cc-pVDZ&#xA;****&#xA;Zn 0&#xA;aug-cc-pVDZ-PP&#xA;****&#xA;Zn 0&#xA;SDD&#xA;****&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This says to use &lt;code&gt;aug-cc-pVDZ&lt;/code&gt; as the basis for C, N, Cl, and H atoms, &lt;code&gt;aug-cc-pVDZ-PP&lt;/code&gt; as the basis for the core electrons of Zn, and SDD (Stuttgart-Dresden pseudopotentials) as the pseudopotential to represent the outer electron (see the &lt;a href=&quot;https://gaussian.com/basissets/&quot; rel=&quot;noreferrer&quot;&gt;Basis Sets&lt;/a&gt; and &lt;a href=&quot;https://gaussian.com/pseudo/&quot; rel=&quot;noreferrer&quot;&gt;Pseudo&lt;/a&gt; sections of the Gaussian manual for information about available basis sets/pseudopotentials and how to input them).&lt;/p&gt;&#xA;&lt;p&gt;I updated the route section slightly based on your edits.  &lt;code&gt;EmpiricalDispersion=GD3BJ&lt;/code&gt; adds the D3 dispersion correction with Becke-Johnson damping.&lt;/p&gt;&#xA;&lt;p&gt;The other two changes might need some fine tuning since I don't know the exact correspondence between Turbomol/Gaussian settings for these. Or they may not be an issue since they should mainly affect the precision of the result. I added &lt;code&gt;Auto&lt;/code&gt; to have it use density fitting/resolution of the identity for your basis set. &lt;code&gt;Integral(Grid=Superfine)&lt;/code&gt; uses Gaussian's largest named grid for exchange-correlation numerical integration, which should hopefully be similar enough to Turbomol's m5 grid.&lt;/p&gt;&#xA;&lt;p&gt;If your system is detected as having symmetry, Gaussian will use that by default. If you want to ensure a higher symmetry isn't used, you could specify &lt;code&gt;Symmetry(PG=Cs)&lt;/code&gt; to limit it to at most Cs symmetry.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2023-07-05T17:03:54.697" LastActivityDate="2023-07-05T17:03:54.697" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11234" PostTypeId="1" CreationDate="2023-07-05T23:42:06.110" Score="2" ViewCount="37" Body="&lt;p&gt;Can someone share a VASP input file as a template that I can use to equillibrate a system as mentioned in the title. I created one but I am not sure if that is correct or not.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM   = AIMD on silica slab surface &#xA; NWRITE   = 2      #&#xA; PREC = Normal     #&#xA;&#xA;# electronic degrees&#xA;LREAL = A                      # real space projection&#xA;PREC  = Normal                 # chose Low only after tests&#xA;EDIFF = 1E-5                   # do not use default (too large drift)&#xA;ISMEAR = 0 ; SIGMA = 0.130     # Fermi smearing: 1500 K 0.086 10-3&#xA;ALGO = Fast                    # recommended for MD (fall back ALGO = Fast)&#xA;MAXMIX = 40                    # reuse mixer from one MD step to next&#xA;ISYM = 0                       # no symmetry&#xA;NELMIN = 4                     # minimum 4 steps per time step, avoid breaking after 2 steps&#xA;# MD (do little writing to save disc space)&#xA;IBRION = 0                     # main molecular dynamics tag&#xA;NSW = 1000                    # number of MD steps&#xA;POTIM = 1.0                    # time step of MD&#xA;NWRITE = 0                     # controls output&#xA;NBLOCK = 10                    # after ten steps pair correlation function is written out&#xA;LCHARG = .FALSE.               # no charge density written out&#xA;LWAVE = .FALSE.                # no wave function coefficients written out&#xA;TEBEG = 298                    # starting temperature for MD&#xA;TEEND = 298                    # end temperature for MD&#xA;# canonic (Nose) MD with XDATCAR updated every 10 steps&#xA;MDALGO = 2                     # switch to select thermostat&#xA;SMASS =  3                     # Nose mass&#xA;ISIF = 2                       # this tag selects the ensemble in combination with the thermostat&#xA;NCORE = 4                      #&#xA;IVDW   =  10                   #                                                                                                                           &#xA;&#xA;VDW_RADIUS = 10.0              #                                                                                                                           &#xA;&#xA;GGA   = PE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-07-05T23:42:06.110" Title="AIMD simulation of a silica slab and a electrolyte placed in the vacuum region" Tags="|density-functional-theory|vasp|aimd|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11235" PostTypeId="1" CreationDate="2023-07-06T07:48:22.870" Score="1" ViewCount="30" Body="&lt;p&gt;I am simulating electrode electrolyte simulation and my professor told me to calculate the density of bulk in simulation box, I am clueless about the how to calculate ,also I want to know if charges are equilibriated ,can someone help me out?&lt;/p&gt;&#xA;" OwnerUserId="7509" LastActivityDate="2023-07-06T07:48:22.870" Title="Analyzing ELECTRO -ELECTROLYTE MD trajectories for calculating bulk density in a simulation box" Tags="|molecular-dynamics|lammps|ovito|" AnswerCount="0" CommentCount="2" ClosedDate="2023-08-10T01:34:53.343" ContentLicense="CC BY-SA 4.0" />
  <row Id="11236" PostTypeId="1" AcceptedAnswerId="11237" CreationDate="2023-07-06T10:20:03.677" Score="5" ViewCount="323" Body="&lt;p&gt;I have a quite big set of molecules to optimize and study and, after some research in the literature, I selected B3LYP/6-311G* level of theory.&lt;/p&gt;&#xA;&lt;p&gt;These molecules are quite big and wobbly, so I expected the optimization to be rather difficult. However, for most of them, I achieved the optimization with tight threshold (# opt=verytight b3lyp/6-311g* int=ultrafine). However, for some of them, the calculation does not converge. In particular, the SCFs converge with small number of steps but the optimization seems to never reach a minimum.&lt;/p&gt;&#xA;&lt;p&gt;For this reason, I tried different things: start from a slightly different configuration to 'escape' from that point in the PES, a slightly larger basis set, to change a little the threshold with IOP keyword, the Opt=CalcFC option. None worked. The only way I could obtain a minimum was to lift the accuracy and use the default threshold for the optimization (# opt b3lyp/6-311g*).&lt;/p&gt;&#xA;&lt;p&gt;I plan to calculate the UV-Vis of these molecules. My question is: Is there another thing that I could try to optimize these systems and/or the default opt parameters would be just fine in general cases?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-07-06T13:15:15.913" Title="Convergence problem in geometry optimization in Gaussian16" Tags="|gaussian|geometry-optimization|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11237" PostTypeId="2" ParentId="11236" CreationDate="2023-07-06T13:15:15.913" Score="6" Body="&lt;p&gt;As Camps mentions in the comments, a common approach for improving geometry convergence is to start with less accurate method/basis or use lower precision convergence criteria and incrementally build up to your desired level of theory .&lt;/p&gt;&#xA;&lt;p&gt;However, I wouldn't expect UV/Vis spectra to depend that strongly on the geometry (to the extent that standard vs very tight convergence will make a difference). The prime example of where you might want really tight convergence is if what you want to compute depends on frequencies and you need to make sure these are properly converged (i.e. no negative frequencies for minima, the appropriate number of negative frequencies for transition states).&lt;/p&gt;&#xA;&lt;p&gt;For computing UV/Vis spectra, the errors from the TD-DFT are likely to larger than those due to geometry differences, so I think standard convergence should be fine.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-07-06T13:15:15.913" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11238" PostTypeId="1" CreationDate="2023-07-07T02:09:50.583" Score="4" ViewCount="167" Body="&lt;p&gt;I am trying to map out potential energy of a slab surface + cation interaction, since VASP has been giving me very not-so-reliable results I wanted to know if CP2K have the ability to do such calculations? so i can compare the results&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-07-08T17:48:41.937" Title="Can CP2K be used for slab calculations?" Tags="|vasp|cp2k|adsorption|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11239" PostTypeId="1" CreationDate="2023-07-07T14:13:27.523" Score="6" ViewCount="242" Body="&lt;p&gt;I am just new with solid state calculation and would like to know one thing.&lt;/p&gt;&#xA;&lt;p&gt;Why is plane wave basis set is good for 1s and 2s orbitals, but for higher convergence is poor? Why is it better to use bigger number of k-points for case of unit cell relaxation (or any other calculations) and only one Г point for supercell?&lt;/p&gt;&#xA;" OwnerUserId="7323" LastEditorUserId="5" LastEditDate="2023-07-14T19:41:25.477" LastActivityDate="2023-07-14T19:41:25.477" Title="Number of k-points for unit and super cell" Tags="|vasp|ab-initio-calculations|geometry-optimization|k-points|supercell|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11240" PostTypeId="2" ParentId="11239" CreationDate="2023-07-07T15:55:07.037" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Why is plane wave basis set is good for 1s and 2s orbitals, but for higher convergence is poor?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I guess by &amp;quot;higher&amp;quot; you mean higher principle quantum number &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; (i.e., 3s, 4s-orbitals). For these orbitals, the radial wavefunctions have lots of wiggles near the atomic core (so that they are orthogonal to the other s-orbitals). To represent a wave function by a set of plane waves, you are essentially expanding that wave function using the Fourier series, and a sharp peak needs a Fourier basis (in this context, the Plane waves) with much higher frequencies to be accurately described.&lt;/p&gt;&#xA;&lt;p&gt;As the plane wave (PW) basis can be systematically improved by setting a higher kinetic energy cut-off (which is related to the highest frequency component of the PW basis) I wouldn't say the convergence is a problem, you just need to include more PWs. The problem is the cost of storing and performing matrix operations with a huge amount of PWs.&lt;/p&gt;&#xA;&lt;p&gt;As a side note, modern DFT codes utilize pseudo potentials with frozen core approximation so that only certain frontier valence orbitals are used in the actual calculations and their &amp;quot;wiggly tail&amp;quot; behavior near the core region is replaced with a smooth one (and the corresponding wave functions are called the pseudo wave functions) so that less PW is needed to describe them. This of course comes with a certain price but I will not dive into the details here.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why is it better to use bigger number of k-points for case of unit cell relaxation (or any other calculations) and only one &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point for supercell?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is related to the fact that the reciprocal space is the Fourier transform of the real space, so the cell vector in reciprocal space is inversely related to the cell vector in real space. For very small cells (e.g., unit cells), the lattice vector in reciprocal space is very large, thus we need a large number of k-points to sample the crystal cell in reciprocal space (Brillouin zone). However, when the crystal cell is very large in real space (e.g., large supercell), the Brillouin zone is very small, and usually &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point is enough to describe that cell.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="1804" LastEditorUserId="1804" LastEditDate="2023-07-07T16:04:06.627" LastActivityDate="2023-07-07T16:04:06.627" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11241" PostTypeId="1" CreationDate="2023-07-07T16:20:18.733" Score="6" ViewCount="115" Body="&lt;p&gt;I will greatly appreciate if someone can point to whether I can specify the spin multiplicity of a vasp calculation?&#xA;I am trying to get the potential energy mapping of a system with neutral slab and a Na+ ion in the vacuum. My results has been a bit off compared to a lammps calculation, so I want to test the hypothesis of spin multiplicity definition in the VASP INCAR file.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-07-07T16:20:18.733" Title="Is there a way to set the spin multiplicity in a VASP calculation?" Tags="|vasp|spin|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11243" PostTypeId="1" AcceptedAnswerId="11248" CreationDate="2023-07-08T00:57:05.623" Score="3" ViewCount="127" Body="&lt;p&gt;For example, I intend to generate the remaining sites of the Cr cubic lattice but the POSCAR file provides limited info on the number of atoms present as shown below. Is there a way to implement this in python (maybe using pymatgen)? It shows 8 atoms which are the total number of atoms within a unit cell volumetrically but how do I generate all the sites of Cr, if you visualize the below in VESTA you will notice that there are a total of 21 atomic sites in a lattice.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1.0&#xA;4.528916128472692 0.0 -0.0&#xA;0.0 4.528916128472692 0.0&#xA;-0.0 0.0 4.528916128472692&#xA;Cr&#xA;8&#xA;direct&#xA;0.0 0.0 0.0 &#xA;0.5 0.5 0.5 &#xA;0.25 0.0 0.5 &#xA;0.75 0.0 0.5 &#xA;0.0 0.5 0.25 &#xA;0.0 0.5 0.75 &#xA;0.5 0.75 0.0 &#xA;0.5 0.25 0.0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2023-07-20T07:42:50.820" LastActivityDate="2023-07-20T07:42:50.820" Title="How to generate the remaining sites in a cubic lattice from a given POSCAR/cif in Python?" Tags="|python|vesta|cif|space-groups|pymatgen|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11244" PostTypeId="1" CreationDate="2023-07-08T03:54:29.980" Score="2" ViewCount="116" Body="&lt;p&gt;I have been following the example laid out in: &lt;a href=&quot;https://github.com/maxhutch/deprecated-quantum-espresso/blob/master/PHonon/examples/example15/reference/zno.ph.in&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/maxhutch/deprecated-quantum-espresso/blob/master/PHonon/examples/example15/reference/zno.ph.in&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the input file for the phonon calculation is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Normal modes for Wurtzite&#xA; &amp;amp;inputph&#xA;  tr2_ph=1.0d-14,&#xA;  prefix='ZNO',&#xA;  amass(1)=65.409,&#xA;  amass(2)=15.999,&#xA;  outdir='/home/larrucea/tmp'&#xA;  epsil=.false.,&#xA;  trans=.true.,&#xA;  asr=.true.&#xA;  fildyn='dmat.zno'&#xA; /&#xA; 0.0 0.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am confused by the final line (which is needed for the calculation to work).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; 0.0 0.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is the meaning of this line? What other values can/should it take?&lt;/p&gt;&#xA;" OwnerUserId="786" LastActivityDate="2023-07-08T03:54:29.980" Title="Phonon Calculation (IR Spectrum) in Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11246" PostTypeId="2" ParentId="11238" CreationDate="2023-07-08T11:15:51.537" Score="3" Body="&lt;p&gt;CP2K employs Gaussian basis sets and can do 3D (crystals), 2D (slabs), 1D (wires) and 0D (atoms and molecules) periodic calculations naturally, without inducing fictitious interactions of periodic copies.&lt;/p&gt;&#xA;&lt;p&gt;Slab calculations are documented in the CP2K manual, see e.g. &lt;a href=&quot;https://www.cp2k.org/exercises:2015_uzh_molsim:chp_cu111&quot; rel=&quot;nofollow noreferrer&quot;&gt;this example exercise&lt;/a&gt; modeling Cyclohexaphenylene on Cu(111).&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="7" LastEditDate="2023-07-08T17:48:41.937" LastActivityDate="2023-07-08T17:48:41.937" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11247" PostTypeId="2" ParentId="11239" CreationDate="2023-07-08T12:44:33.277" Score="1" Body="&lt;p&gt;I will explicit my comment, the use of plane waves (PWs) for 1s and 2s is completely absurd when a linear combination of atomic orbitals gives a fast convergence. Even if they lack of significant oscillations as said in the previous answer, they are really localized, several Pws are still needed to match their structure. PWs should be used only when the potential does not vary considerably, this means for larger &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; completely in desagreement with your assumption (a basic knowledge LAPW methods may help). The overlap of larger &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; orbitals creates an slightly homogenous density, a few number of PW can converge quickly to a complete basis-set. A PW basis-set is a good choice compared LCAO in this case. The short-range oscillations for the orthogonality of large &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; orbitals is corrected by a pseudo WF along with a pseudopotential. No matter how your cell is chosen and consequently the size of your Brillouin zone, you cannot restrict your to a single k-point &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; or one another for a periodic boundary condition system. Obviously there is no need to have a large number of k-points for a large surpercell which is also associated to a computational expense.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastEditorUserId="6019" LastEditDate="2023-07-08T13:25:53.950" LastActivityDate="2023-07-08T13:25:53.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11248" PostTypeId="2" ParentId="11243" CreationDate="2023-07-09T10:31:52.117" Score="3" Body="&lt;p&gt;I sort of get what OP wants to achieve based on the comment section, but what a strange request! Nonetheless, this can be easily done by both pymatgen and the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase&quot; rel=&quot;nofollow noreferrer&quot;&gt;Atomic Simulation Environment (ASE)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The idea is to double the structure in all 3 dimensions and then only keep the atoms that are inside or on the boundary of the original cell. To do this, you just need to find atoms that have fractional coordinate no larger than 1/2 in all 3 dimensions (this is a general solution for cubic and non-cubic systems). Below are some simple Python codes that can generate the structure you want.&lt;/p&gt;&#xA;&lt;h2&gt;ASE&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;from ase.visualize import view&#xA;&#xA;# Read in the POSCAR file&#xA;atoms = read('POSCAR')&#xA;# Store the original unit cell&#xA;old_cell = atoms.cell.copy()&#xA;# Expand the unit cell in all 3 dimensions&#xA;atoms *= (2, 2, 2)&#xA;# Find the atom indices that are inside or on the boundary of the original cell&#xA;indices = [a.index for a in atoms if (a.scaled_position &amp;lt;= 1/2).all()]&#xA;# Reduce the structure&#xA;atoms = atoms[indices]&#xA;# Assign the original cell back&#xA;atoms.cell = old_cell&#xA;# Visualize&#xA;view(atoms)&#xA;# Export to a cif file&#xA;write('Cr21.cif', atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Pymatgen&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Structure&#xA;&#xA;struct = Structure.from_file('POSCAR')&#xA;old_lattice = struct.lattice.copy()&#xA;struct.make_supercell([2, 2, 2])&#xA;symbols, coords = zip(*[(a.species, a.coords) for a in struct &#xA;                        if (a.frac_coords &amp;lt;= 1/2).all()])&#xA;struct = Structure(old_lattice, symbols, coords)&#xA;struct.to(filename='Cr21.cif')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-20T06:23:01.053" LastActivityDate="2023-07-20T06:23:01.053" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11249" PostTypeId="1" CreationDate="2023-07-09T15:53:36.393" Score="3" ViewCount="51" Body="&lt;p&gt;Can someone guide me on how to add a first solvation shell of water around a particular cation (Na+) , for a single point calculation purpose? is it physically meaningful to add water just around the cation? do i need to add a Cl- ion as well?&lt;/p&gt;&#xA;" OwnerUserId="6839" LastEditorUserId="6839" LastEditDate="2023-07-09T15:58:57.653" LastActivityDate="2023-07-09T15:58:57.653" Title="How to add a first solvation shell in a simulation" Tags="|vasp|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11250" PostTypeId="1" CreationDate="2023-07-09T22:14:00.643" Score="4" ViewCount="47" Body="&lt;p&gt;Question duplicated from here &lt;a href=&quot;https://mathematica.stackexchange.com/questions/287433/why-if-the-potential-is-different-from-the-coulomb-one-but-has-spherical-symme&quot;&gt;https://mathematica.stackexchange.com/questions/287433/why-if-the-potential-is-different-from-the-coulomb-one-but-has-spherical-symme&lt;/a&gt; and here &lt;a href=&quot;https://physics.stackexchange.com/questions/771468/why-if-the-potential-is-different-from-the-coulomb-one-but-has-spherical-symme&quot;&gt;https://physics.stackexchange.com/questions/771468/why-if-the-potential-is-different-from-the-coulomb-one-but-has-spherical-symme&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have found the eigenvalues of the following systems: &lt;span class=&quot;math-container&quot;&gt;$H=-\frac{1}{2}\Delta+V_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H=-\frac{1}{2}\Delta+V_2$&lt;/span&gt;, using &lt;code&gt;NDEigensystem&lt;/code&gt; by Wolfram Mathematica.&lt;/p&gt;&#xA;&lt;p&gt;In the first case the potential is Coulomb one (&lt;span class=&quot;math-container&quot;&gt;$V_1=-\frac{1}{\sqrt{\rho^2+z^2}}$&lt;/span&gt; (is written in a cylindrical coordinate system)). The second potential has a more complex structure &lt;span class=&quot;math-container&quot;&gt;$V_2=-\frac{1}{\sqrt{\rho^2+z^2}}-\frac{1}{2\sqrt{\rho^2+z^2}}e^{\frac{1}{2\sqrt{\rho^2+z^2}}}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The codes are written in Wolfram Mathematica. In the both codes I renamed &lt;span class=&quot;math-container&quot;&gt;$\rho≡r$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;1.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ClearAll[&amp;quot;Global`*&amp;quot;]&#xA;rmax = 20;&#xA;zmax = 20;&#xA;&#xA;V1[r_, z_] := -1/Sqrt[r^2 + z^2]&#xA;{valsc, funsc} = &#xA;  NDEigensystem[{(-1/2*&#xA;        Laplacian[\[Psi][r, z], {r, \[Theta], z}, &amp;quot;Cylindrical&amp;quot;] + &#xA;       V1[r, z]*\[Psi][r, z]) + \[Psi][r, z]*0.5}, \[Psi][r, z], {r, 0,&#xA;     rmax}, {z, -zmax, zmax}, 20, &#xA;   Method -&amp;gt; {&amp;quot;SpatialDiscretization&amp;quot; -&amp;gt; {&amp;quot;FiniteElement&amp;quot;, \&#xA;{&amp;quot;MeshOptions&amp;quot; -&amp;gt; {&amp;quot;MaxCellMeasure&amp;quot; -&amp;gt; 0.05}}}, &#xA;     &amp;quot;Eigensystem&amp;quot; -&amp;gt; {&amp;quot;Arnoldi&amp;quot;, &amp;quot;MaxIterations&amp;quot; -&amp;gt; 10000}}];&#xA;Sort[valsc] - 0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;20 first eigenvalues obtained from the code 1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{-0.503427, -0.125434, -0.125001, -0.0591382, -0.0575661, \&#xA;-0.0567415, -0.0366165, -0.0348045, -0.0331543, -0.0305338, \&#xA;-0.0194174, -0.011569, -0.00383252, -0.000633831, 0.0115625, \&#xA;0.0130426, 0.0228641, 0.0287679, 0.0380814, 0.0405388}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As follows from the general theory, the levels are degenerate:&lt;/p&gt;&#xA;&lt;p&gt;-0.503427 — 1s state &lt;br /&gt;&#xA;-0.125434, -0.125001 — 2s and 2p states &lt;br /&gt;&#xA;-0.0591382, -0.0575661, -0.0567415 — 3s, 3p and 3d states &lt;br /&gt;&#xA;...&lt;/p&gt;&#xA;&lt;p&gt;2.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ClearAll[&amp;quot;Global`*&amp;quot;]&#xA;rmax = 20;&#xA;zmax = 20;&#xA;&#xA;V2[r_, z_] := -1/Sqrt[r^2 + z^2] - &#xA;  1/2/Sqrt[r^2 + z^2]*Exp[-Sqrt[r^2 + z^2]]&#xA;{valsc1, funsc1} = &#xA;  NDEigensystem[{(-1/2*&#xA;        Laplacian[\[Psi][r, z], {r, \[Theta], z}, &amp;quot;Cylindrical&amp;quot;] + &#xA;       V2[r, z]*\[Psi][r, z]) + \[Psi][r, z]*0.5}, \[Psi][r, z], {r, &#xA;    0, rmax}, {z, -zmax, zmax}, 20, &#xA;   Method -&amp;gt; {&amp;quot;SpatialDiscretization&amp;quot; -&amp;gt; {&amp;quot;FiniteElement&amp;quot;, \&#xA;{&amp;quot;MeshOptions&amp;quot; -&amp;gt; {&amp;quot;MaxCellMeasure&amp;quot; -&amp;gt; 0.05}}}, &#xA;     &amp;quot;Eigensystem&amp;quot; -&amp;gt; {&amp;quot;Arnoldi&amp;quot;, &amp;quot;MaxIterations&amp;quot; -&amp;gt; 10000}}];&#xA;Sort[valsc1] - 0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;20 first eigenvalues obtained from the code 2:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{-0.816105, -0.152359, -0.134395, -0.0649383, -0.0597383, \&#xA;-0.0570375, -0.0381872, -0.0375616, -0.0340771, -0.0326892, \&#xA;-0.0220107, -0.0128179, -0.00388086, -0.00246523, 0.0106794, \&#xA;0.011968, 0.0221767, 0.0277981, 0.0328003, 0.0358925}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As can be seen in this case, the eigenvalues are different — the levels are not degenerate:&lt;/p&gt;&#xA;&lt;p&gt;-0.816105 — 1s state &lt;br /&gt;&#xA;-0.152359 — first excited state &lt;br /&gt;&#xA;-0.134395 — second excited state &lt;br /&gt;&#xA;...&lt;/p&gt;&#xA;&lt;p&gt;Question: &lt;br /&gt;&#xA;&lt;strong&gt;Why are the levels not degenerate in the second case?&lt;/strong&gt; Like the first potential (&lt;span class=&quot;math-container&quot;&gt;$V_1$&lt;/span&gt;), the second potential (&lt;span class=&quot;math-container&quot;&gt;$V_2$&lt;/span&gt;) has spherical symmetry, hence the system is spherically symmetric. Shouldn't any spherically symmetric system give levels that are degenerate in the orbital quantum number?&lt;/p&gt;&#xA;" OwnerUserId="7193" LastEditorUserId="7193" LastEditDate="2023-07-10T05:30:36.870" LastActivityDate="2023-07-10T05:30:36.870" Title="Why, if the potential is different from the Coulomb one, but has spherical symmetry, the eigenvalues of the system are non-degenerate?" Tags="|software|quantum-chemistry|condensed-matter|mathematical-modeling|quantum-mechanics|" AnswerCount="0" CommentCount="1" ClosedDate="2023-07-10T17:55:53.637" ContentLicense="CC BY-SA 4.0" />
  <row Id="11251" PostTypeId="2" ParentId="10981" CreationDate="2023-07-10T01:31:23.467" Score="5" Body="&lt;p&gt;Yes you can indeed identify a crystsal structure's dimensionality in pymatgen. This is done by &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.dimensionality.html#pymatgen.analysis.dimensionality.get_dimensionality_gorai&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;pymatgen.analysis.dimensionality.get_dimensionality_gorai&lt;/code&gt;&lt;/a&gt;, which detects whether a structure is 3D, 2D (layered), or 1D (linear chains or molecules).&lt;/p&gt;&#xA;&lt;p&gt;However, I highly recommend you to check out &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE&lt;/a&gt;, where the building and dimensionality identification of layered 2D structures are rather straightforward.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import graphene, mx2, bulk&#xA;from ase.geometry.dimensionality import analyze_dimensionality&#xA;&#xA;def get_dim(atoms, method='RDA'):&#xA;    return analyze_dimensionality(atoms, method=method)[0].dimtype&#xA;&#xA;# Graphene monolayer&#xA;graphene_atoms = graphene()&#xA;dim1 = get_dim(graphene_atoms)&#xA;print(dim1) # 2D&#xA;&#xA;# 3-layer MoS2 &#xA;MoS2_atoms = mx2(formula='MoS2', kind='2H', a=3.18, thickness=3.19)&#xA;dim2 = get_dim(MoS2_atoms)&#xA;print(dim2) # 2D&#xA;&#xA;# Cu bulk&#xA;Cu_atoms = bulk('Cu', 'fcc', a=4.0)&#xA;dim3 = get_dim(Cu_atoms)&#xA;print(dim3) # 3D&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-10T07:01:10.237" LastActivityDate="2023-07-10T07:01:10.237" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11252" PostTypeId="1" CreationDate="2023-07-10T10:07:31.540" Score="6" ViewCount="399" Body="&lt;p&gt;I would like to construct the supercell that contains explicit 4 ionic liquid molecules (i.e. &lt;span class=&quot;math-container&quot;&gt;$[EMIM][BF_{4}]$&lt;/span&gt;) for running AIMD. Is there any recommended software or code that is suitable and easy to generate the structure? I am not sure that Atomic Simulation Environment can help since it usually focuses on the solid structure.&lt;/p&gt;&#xA;" OwnerUserId="7530" LastActivityDate="2023-07-12T20:58:20.470" Title="How to build up a supercell for explicit solvent system?" Tags="|molecular-dynamics|solvation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11253" PostTypeId="2" ParentId="11228" CreationDate="2023-07-10T10:30:01.853" Score="5" Body="&lt;p&gt;This is quite a peculiar scenario and I think more information is needed in order to find the root casue of it.&lt;/p&gt;&#xA;&lt;p&gt;With the information at hand, I think this might be caused by different k-samplings used for systems under different distortions. i.e., if you are using &lt;code&gt;LCALCPOL=.T.&lt;/code&gt; with &lt;code&gt;ISYM=2&lt;/code&gt;, VASP will try to reduce the number of k-points used in the calculation by utilizing the symmetry of the system. However, since &lt;code&gt;LCALCPOL&lt;/code&gt; doesn't re-construct a string of k-points (unlike &lt;code&gt;LBERRY&lt;/code&gt; which does exactly this), the k-points used to calculate the berry phase along each k-string might also be different if the symmetry routine decides that the system is now under a different symmetry than the other system.&lt;/p&gt;&#xA;&lt;p&gt;I would suggest that you try:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;switching off the symmetry by setting &lt;code&gt;ISYM=-1&lt;/code&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;switching to &lt;code&gt;LBERRY&lt;/code&gt; method which gives more infomation in the &lt;code&gt;OUTCAR&lt;/code&gt; (e.g., coordinates of k-points along the k-string and the Berry phase for each k-string.)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For more information on how to use &lt;code&gt;LBERRY&lt;/code&gt;, see: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LBERRY&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/LBERRY&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I hope this helps.&lt;/p&gt;&#xA;" OwnerUserId="1804" LastActivityDate="2023-07-10T10:30:01.853" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11254" PostTypeId="2" ParentId="11252" CreationDate="2023-07-10T14:08:23.163" Score="5" Body="&lt;h2&gt;1. Using ASE GUI&lt;/h2&gt;&#xA;&lt;p&gt;You can utilize ase gui to build supercell manually. Open ASE GUI window with two molecules (for example &lt;code&gt;ase gui emim.xyz bf4.xyz&lt;/code&gt;). Then create new window   and create a unit cell, copy &amp;amp; paste the molecules, rotate &amp;amp; move to fit the cell.&lt;/p&gt;&#xA;&lt;h2&gt;2. Using packmol&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://m3g.github.io/packmol/download.shtml&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;packmol&lt;/code&gt;&lt;/a&gt; is actually more common tool for this kind of task. It randomly packs molecules in simulation box.&lt;/p&gt;&#xA;&lt;p&gt;For AIMD simulation you should be careful because packmol does not support PBC. So if the desired size of supercell is &lt;code&gt;15 x 15 x 15&lt;/code&gt;, it is recommended to pack molecules in slightly smaller box and set periodic unit cell later.&lt;/p&gt;&#xA;&lt;p&gt;For example, the input file &lt;code&gt;pack.inp&lt;/code&gt; looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;filetype xyz&#xA;&#xA;tolerance 2.0  # intermolecular distance limit&#xA;&#xA;output supercell.xyz&#xA;&#xA;&#xA;# 4 emim and 4 bf4 inside 13 x 13 x 13 box&#xA;&#xA;structure emim.xyz&#xA;  number 4 &#xA;  inside box 0. 0. 0. 13. 13. 13.&#xA;end structure&#xA;&#xA;structure bf4.xyz&#xA;  number 4&#xA;  inside box 0. 0. 0. 13. 13. 13.&#xA;end structure&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now you can impose PBC using ASE:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import ase.io&#xA;import ase.build&#xA;&#xA;atoms = ase.io.read(&amp;quot;supercell.xyz&amp;quot;)&#xA;atoms.cell = [15, 15, 15]&#xA;atoms.pbc = [True, True, True]&#xA;atoms.center() # Just for easy visualization&#xA;# If you use VASP:&#xA;atoms = ase.build.sort(atoms) &#xA;atoms.write(&amp;quot;POSCAR&amp;quot;)&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7097" LastActivityDate="2023-07-10T14:08:23.163" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11255" PostTypeId="2" ParentId="11118" CreationDate="2023-07-10T14:14:40.147" Score="1" Body="&lt;p&gt;Since you perform DFT calculations under periodic boundary condition(PBC), you should check your structure carefully. The first two atoms &lt;code&gt;(0, 0, 0)&lt;/code&gt; and &lt;code&gt;(0, 0, a)&lt;/code&gt; possesses the same coordinate in periodic cube with length &lt;code&gt;a&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Considering symmetrically distinct atoms only, your code can be revised as following:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from ase import Atoms&#xA;&#xA;a = 4.0 # Lattice constant (in Angstroms)&#xA;&#xA;position = [(0, 0, 0), (a/2, 0, a/2), (a/2, a/2, 0), (0, a/2, a/2)]&#xA;&#xA;symbols = ['Cu']*len(position)&#xA;fcc = Atoms(symbols=symbol, positions=position, cell=(a, a, a), pbc=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Of course it is way simpler to use &lt;code&gt;ase.build.bulk&lt;/code&gt; function:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.build&#xA;&#xA;atoms = ase.build.bulk('Cu', 'fcc', a=4.0, cubic=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you want only primitive unit cell, set &lt;code&gt;cubic&lt;/code&gt; to &lt;code&gt;False&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7097" LastActivityDate="2023-07-10T14:14:40.147" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11256" PostTypeId="2" ParentId="4345" CreationDate="2023-07-10T14:43:13.110" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://aim.tkgristmill.com/wfxformat.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://aim.tkgristmill.com/wfxformat.html&lt;/a&gt;&#xA;WFX format specification. WFX is an AIM file.&#xA;Yes, Cartesian.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://wordpress.nmsu.edu/tmanz/files/2020/06/WFX_file_programmers_guide_06_14_2020.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wordpress.nmsu.edu/tmanz/files/2020/06/WFX_file_programmers_guide_06_14_2020.pdf&lt;/a&gt;&#xA;WFX programmer's guide from the Manz group at NMSU&#xA;.&lt;/p&gt;&#xA;" OwnerUserId="7539" LastActivityDate="2023-07-10T14:43:13.110" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11258" PostTypeId="1" CreationDate="2023-07-10T18:38:36.147" Score="2" ViewCount="258" Body="&lt;p&gt;I am working with lithium sulfate and am wondering how to figure out the ionic radius of the Li atoms. I did a DFT/B3LYP/G-311G ++ (d,p) calculation.&lt;/p&gt;&#xA;" OwnerUserId="7541" LastEditorUserId="6019" LastEditDate="2023-07-11T17:44:51.200" LastActivityDate="2023-07-21T01:56:47.993" Title="How to calculate ionic radius in Gaussian?" Tags="|computational-chemistry|molecular-modeling|molecular-interactions|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11259" PostTypeId="1" AcceptedAnswerId="11263" CreationDate="2023-07-11T10:28:21.457" Score="6" ViewCount="674" Body="&lt;p&gt;Bellow is a part from the partitions of an HPC. Can someone please explain to me the meaning of each term ( mix, alloc, adle, node28, bigmem[41-44], gpu[51-52].....)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PARTITION AVAIL  TIMELIMIT  NODES  STATE NODELIST &#xA;defq         up    1:00:00      1    mix node28 &#xA;defq         up    1:00:00     34  alloc bigmem[41-44],data[31-36],node[01-12,14-16,21-27,29-30] &#xA;demoq        up   infinite      1   idle node13 &#xA;gpu-prodq    up 7-00:00:00      2    mix gpu[51-52] &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want also to know how can I check if a partition is available for usage because a lot of times when I start a calculation I have to wait so long until it starts running.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6468" LastEditDate="2023-07-11T11:18:37.903" LastActivityDate="2023-07-12T16:53:37.397" Title="The meaning of some HPC vocabulary" Tags="|high-performance-computing|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11260" PostTypeId="2" ParentId="11259" CreationDate="2023-07-11T11:21:51.747" Score="3" Body="&lt;p&gt;I do not know how the specific cluster is set up in your case, but usually &lt;code&gt;sinfo&lt;/code&gt; would give you list of all nodes currently available in the cluster, and then you can do a &lt;code&gt;sinfo | grep idle&lt;/code&gt; to get the nodes that are currently free. Any node indicated as &lt;code&gt;mix&lt;/code&gt; would have some part of the processors occupied by a different job. &lt;code&gt;alloc&lt;/code&gt; is self-explanatory.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-11T11:21:51.747" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11261" PostTypeId="1" CreationDate="2023-07-11T13:25:03.933" Score="2" ViewCount="35" Body="&lt;p&gt;I am trying to compute integrals of the form &lt;span class=&quot;math-container&quot;&gt;$(pq|rs)$&lt;/span&gt; where the orbitals &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; are orthogonalized atomic orbitals for a fragment &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r,s$&lt;/span&gt; are orthogonalized on fragment &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;. I was thinking of a setup similar to this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf, dft, ao2mo, lo&#xA;import numpy as np&#xA;&#xA;#BASIS SET: (4s) -&amp;gt; [2s]&#xA;mol1 = gto.M(atom='He 0 0 0', basis='6-31g')&#xA;&#xA;#Lowdin orthogonalization of the ao basis&#xA;C1=lo.orth.orth_ao(mol1,method='lowdin')&#xA;&#xA;&#xA;mol2 = gto.M(atom='He 2 0 0', basis='6-31g')&#xA;&#xA;#Lowdin orthogonalization of the ao basis&#xA;C2=lo.orth.orth_ao(mol2,method='lowdin')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This snippet will create two separate molecule instances with their corresponding &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; orthogonalization matrix (the same in this situation).&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to either take these two molecule instances and calculate the two-electron integrals between them? Or do I create a &amp;quot;supramolecular&amp;quot; system instead, compute all two-electron integrals, and somehow sort them with respect to the centers of the AOs? If the latter, how to do this?&lt;/p&gt;&#xA;" OwnerUserId="5648" LastActivityDate="2023-07-11T13:25:03.933" Title="PySCF two-electron integrals between two fragments" Tags="|electronic-structure|pyscf|integrals|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11262" PostTypeId="1" AcceptedAnswerId="11344" CreationDate="2023-07-11T15:23:33.343" Score="4" ViewCount="346" Body="&lt;p&gt;I have been optimizing some particularly tricky structures with Gaussian. The optimizations end well and they don't have negative frequencies. However, when checking the convergence of the frequency calculation, I have a disagreement:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-optimization run&#xA; Maximum Force            0.000029     0.000450     YES&#xA; RMS     Force            0.000006     0.000300     YES&#xA; Maximum Displacement     0.001422     0.001800     YES&#xA; RMS     Displacement     0.000253     0.001200     YES&#xA;&#xA;-frequency run&#xA; Maximum Force            0.000030     0.000450     YES&#xA; RMS     Force            0.000006     0.000300     YES&#xA; Maximum Displacement     0.027710     0.001800     NO&#xA; RMS     Displacement     0.003793     0.001200     NO&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have read on the &lt;a href=&quot;https://gaussian.com/faq3/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian website&lt;/a&gt; that one should run again the calculation to find the 'true' minimum. However, even if I run the calculation with ReadFC I can only achieve:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;         Item               Value     Threshold  Converged?&#xA; Maximum Force            0.000005     0.000450     YES&#xA; RMS     Force            0.000001     0.000300     YES&#xA; Maximum Displacement     0.002793     0.001800     NO&#xA; RMS     Displacement     0.000361     0.001200     YES&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since I won't be doing IR spectra calculations but rather TD-DFT calculation, should I be so worried about this or it is ok to trust the less accurate Hessian of the optimization run?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="4755" LastEditDate="2023-07-11T17:41:33.417" LastActivityDate="2023-07-22T22:53:51.847" Title="Frequency run does not converge in Gaussian16" Tags="|gaussian|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11263" PostTypeId="2" ParentId="11259" CreationDate="2023-07-11T21:22:01.543" Score="5" Body="&lt;p&gt;To answer your second question first:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I want also to know how can I check if a partition is available for usage because a lot of times when I start a calculation I have to wait so long until it starts running.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There are really only four possibilities:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The cluster is very busy and everyone has to wait a long time.&lt;/li&gt;&#xA;&lt;li&gt;You have run many jobs recently, so future jobs from you will have low priority so other users get a turn;&lt;/li&gt;&#xA;&lt;li&gt;You are requesting unusual or very large allocations which are difficult to accommodate;&lt;/li&gt;&#xA;&lt;li&gt;Your cluster scheduler's settings are buggy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For situation 1 or 2 there's nothing you can (or should) do. Sit back, read some papers, do some post-analysis, go out and smell the fresh air.&lt;/p&gt;&#xA;&lt;p&gt;For situation 3, make sure your requests are &amp;quot;efficient&amp;quot; -- that is, you're requesting enough resources to get the job done but not too much more, and request either few cores or a short wall-time. It's a basic logistics problem: if you ask for a large amount of resources for a very long time, it will naturally be harder to fit in your requests. To do this well, you must know your code's:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&amp;quot;checkpoint&amp;quot; features. Most HPC codes can save a calculation checkpoint midway through and then resume the calculation in a subsequent run. This lets you break up a big calculation into smaller sub-runs which are easier to schedule.&lt;/li&gt;&#xA;&lt;li&gt;resource consumption. Does your code need lots of CPU (like most molecular dynamics codes) or lots of RAM (like some bioinformatics jobs)? Requesting less of a resource that you don't need much of will make your job easier to schedule. (If I explicitly ask for very little RAM for my MD job, the scheduler might be able to squeeze my job in next to a bioinformatics job.)&lt;/li&gt;&#xA;&lt;li&gt;scaling characteristics. My code might only run 1.3x as fast if I run it on two nodes instead of one, so instead of requesting a two-node job, I might be better off requesting a one-node job and being patient.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For situation 4, it's entirely out of your control too. Please make sure you try everything else before filing a bug report. And even if the cluster scheduler settings are bugged, you can usually make some headway by requesting smaller jobs. I was recently in a situation on a cluster which, for some reason, was struggling to allocate jobs longer than 12 hours. No problem -- I just split up my jobs and then waited my turn alongside everyone else.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Now, the &lt;code&gt;sinfo&lt;/code&gt; table you've posted has a few columns, whose names seem quite straightforward:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;The &lt;strong&gt;partitions&lt;/strong&gt; are the various queues you can request jobs in which typically provide different resources or limits:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Most clusters will have a default main queue, usually called &lt;code&gt;work&lt;/code&gt; or &lt;code&gt;prod&lt;/code&gt; (production), where most jobs should go.&lt;/li&gt;&#xA;&lt;li&gt;A &lt;code&gt;debug&lt;/code&gt; queue has very fast turnaround but you can only submit small, short jobs, so you can quickly test scripts for obvious bugs before submitting them to the main queue.&lt;/li&gt;&#xA;&lt;li&gt;Some clusters have &lt;code&gt;copy&lt;/code&gt; queues reserved for moving lots of data.&lt;/li&gt;&#xA;&lt;li&gt;Other queues have special resources or settings:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Large-RAM jobs go on &lt;code&gt;bigmem&lt;/code&gt; or &lt;code&gt;himem&lt;/code&gt; queues.&lt;/li&gt;&#xA;&lt;li&gt;Some clusters have small &lt;code&gt;long&lt;/code&gt; queues which let jobs run for two weeks where their default queue has a day-long limit.&lt;/li&gt;&#xA;&lt;li&gt;Clusters with GPUs will usually put them in a &lt;code&gt;gpu&lt;/code&gt; queue (one cluster I worked with had the good stuff locked away in an &lt;code&gt;ai&lt;/code&gt; queue).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If the &lt;strong&gt;availability&lt;/strong&gt; of a partition is &lt;code&gt;down&lt;/code&gt; you won't be able to submit jobs there. Grant writing time!&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Those are some interesting &lt;strong&gt;time limits&lt;/strong&gt;. The &lt;code&gt;defq&lt;/code&gt; limit of 1 hour is probably for debugging, and that 7 day time limit is the longest I've ever seen for a GPU production queue. The &lt;code&gt;infinite&lt;/code&gt; limit probably means you're not allowed to submit to &lt;code&gt;demoq&lt;/code&gt; at all -- it's strictly for admins to run demonstrations, I'm guessing.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The next column just says the number of &lt;strong&gt;nodes&lt;/strong&gt; with each state:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The &lt;strong&gt;state&lt;/strong&gt; is the one column that stays the same across every cluster. Nodes are &lt;code&gt;alloc&lt;/code&gt; if they're fully allocated, &lt;code&gt;idle&lt;/code&gt; if they're not allocated at all, and &lt;code&gt;mixed&lt;/code&gt; in between.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;DO NOT &amp;quot;game&amp;quot; the system by trying to specify idle nodes. The scheduler &lt;em&gt;knows&lt;/em&gt; which nodes are idle. If it's not putting your job on, that's happening for some other reason. You're just making your submit scripts more complex and bug-prone for no benefit.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;And the last column is simply the &lt;strong&gt;list of nodes&lt;/strong&gt; under each state. For example the first entry in the second row says that nodes &lt;code&gt;bigmem41&lt;/code&gt; to &lt;code&gt;bigmem44&lt;/code&gt; are currently mixed-allocated.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Most clusters will name their nodes sensibly but in principle the names could be anything. On one cluster I use, called Bunya, the default node names are just &lt;code&gt;bun000&lt;/code&gt; and so on. In the info you provided, the default node name is &lt;code&gt;nodeXX&lt;/code&gt;. Non-default node names will usually reflect node-specific resources -- you can guess what &lt;code&gt;bigmem&lt;/code&gt; and &lt;code&gt;gpu&lt;/code&gt; mean, and &lt;code&gt;data&lt;/code&gt; probably denotes nodes for large data transfers.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-07-12T05:13:43.803" LastActivityDate="2023-07-12T05:13:43.803" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11264" PostTypeId="1" CreationDate="2023-07-11T21:43:41.567" Score="2" ViewCount="63" Body="&lt;p&gt;I need to establish protonation of aminoacids composing the studied protein. To my knowledge there are H++ and Pdb2pqr servers that are able to do that. However,  they yield quite much different outputs. Do you know about something else I may try to compare with? Maybe there’s something better than these?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-07-18T03:43:07.780" Title="Establishing AAs protonation - which software to choose?" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|gromacs|amber|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11267" PostTypeId="1" CreationDate="2023-07-12T08:12:20.740" Score="1" ViewCount="157" Body="&lt;p&gt;I am trying to calculate the spontaneous polarization of a semiconducting magnetic 2d material with VASP. The Material has a band gap of 0.28 eV (indirect).&#xA;VASP warns that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The calculation of the macroscopic polarization by means of the&#xA;Berry-phase expressions (LCALCPOL=.TRUE.) requires your system to be&#xA;insulating. This does not seem to be the case.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Why is this happening despite a finite band gap (with PBE)? Adding to this, since this calculation is at 0K, this semiconductor is effectively insulating for this calculation. What is going wrong here?&lt;/p&gt;&#xA;" OwnerUserId="7549" LastActivityDate="2023-07-12T08:12:20.740" Title="Why does VASP fail to compute Spontaneous polarization calculation through berry phase method for semiconductors?" Tags="|density-functional-theory|vasp|berry-phase|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-19T22:17:59.957" ContentLicense="CC BY-SA 4.0" />
  <row Id="11268" PostTypeId="1" CreationDate="2023-07-12T10:06:38.957" Score="5" ViewCount="534" Body="&lt;p&gt;I want to visualize an MD trajectory produced with ASE.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;ase.visualize.view produces an output for atoms and trajectories. I am not able to show the bonds between atoms.&lt;/li&gt;&#xA;&lt;li&gt;For atoms, I can use this in my jupyter notebook, which gives me an ok 3D representation:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.visualize import view&#xA;view(atoms, viewer='x3d')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For trajectories, I use this, which pops up a 2D representation and is very scarce (no bonds, no cell...):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre&gt;&lt;code&gt;read_traj = ase.io.trajectory.TrajectoryReader(traj_file)&#xA;view(read_traj)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;eventually, I would like to see them breaking later with a reaxff or MLIP such as MatGL.&lt;/li&gt;&#xA;&lt;li&gt;How do I show the cell and bonds? should I allow some flags to represent bonds? Or am I doing a totally wrong cell?&lt;/li&gt;&#xA;&lt;li&gt;Do automatic tools such as MDTraj or MDAnalysis have an interface to ASE?&lt;/li&gt;&#xA;&lt;li&gt;I know I can use VMD, but my local file is aliased at &lt;code&gt;/Applications/VMD\ 1.9.4a57-x86_64-Rev12.app/Contents/Resources/VMD.app/Contents/MacOS/VMD&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;I tried with the conda install of AVOGADRO but I get:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre&gt;&lt;code&gt;read_traj = ase.io.trajectory.TrajectoryReader(traj_file)&#xA;view(read_traj, viewer='Avogadro')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;TypeError                                 Traceback (most recent call last)&#xA;Cell In[15], line 2&#xA;      1 read_traj = ase.io.trajectory.TrajectoryReader(traj_file)&#xA;----&amp;gt; 2 view(read_traj, viewer='Avogadro')&#xA;&#xA;File ~/miniconda3/lib/python3.9/site-packages/ase/visualize/__init__.py:10, in view(atoms, data, viewer, repeat, block)&#xA;      7     return&#xA;      9 vwr = viewers[viewer.lower()]&#xA;---&amp;gt; 10 handle = vwr.view(atoms, data=data, repeat=repeat)&#xA;     12 if block and hasattr(handle, 'wait'):&#xA;     13     status = handle.wait()&#xA;&#xA;File ~/miniconda3/lib/python3.9/site-packages/ase/visualize/external.py:72, in CLIViewer.view(self, atoms, data, repeat)&#xA;     66     atoms = atoms.repeat(repeat)&#xA;     68 proc = subprocess.Popen(&#xA;     69     [sys.executable, '-m', 'ase.visualize.external'],&#xA;     70     stdin=subprocess.PIPE)&#xA;---&amp;gt; 72 pickle.dump((self, atoms, data), proc.stdin)&#xA;     73 proc.stdin.close()&#xA;     74 return proc&#xA;&#xA;TypeError: cannot pickle '_io.BufferedReader' object&#xA;&#xA;/Users/marcodigennaro/miniconda3/lib/python3.9/runpy.py:127: RuntimeWarning: 'ase.visualize.external' found in sys.modules after import of package 'ase.visualize', but prior to execution of 'ase.visualize.external'; this may result in unpredictable behaviour&#xA;  warn(RuntimeWarning(msg))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone advise on any of the previous points?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2023-07-13T17:00:30.870" Title="Visualise bonds in ASE" Tags="|visualization-software|atomic-simulation-environment|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11269" PostTypeId="2" ParentId="11259" CreationDate="2023-07-12T10:28:45.627" Score="3" Body="&lt;h1&gt;What do the terms mean?&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Alloc&lt;/strong&gt; - a node state where all the cpu cores are allocated. It's &amp;quot;full&amp;quot; essentially&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Mix&lt;/strong&gt; - Node is partially full&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Idle&lt;/strong&gt; - nothing running on that node&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Bigmem&lt;/strong&gt; - a node type, these are assigned by the cluster admin, so can't be compared between clusters, but it probably has more memory than a standard node. We can see here that there are 3, and they're all in use&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;GPU&lt;/strong&gt; - a node with a graphics card. Used for jobs that need GPUs. It's in a separate queue (gpu-prodq) to stop non gpu jobs using it&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;node&lt;/strong&gt; - another node type - the standard node for this cluster&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;data&lt;/strong&gt; - another node type. It probably has either expanded storage for large jobs, or is meant to be used for file transfer or data operation jobs, or runs a database. Look at the cluster docs to figure this out&lt;/p&gt;&#xA;&lt;p&gt;I think where some confusion is coming in is that you're reading &amp;quot;node28&amp;quot; as a type of node - it isn't, it's the 28th instance of the standard type of node. The numbers in [] are ranges, so bigmem[41-43] means bigmem nodes 41,42 and 43&lt;/p&gt;&#xA;&lt;h1&gt;How to get your job to queue faster?&lt;/h1&gt;&#xA;&lt;p&gt;Looking at the snippet you posted, essentially everything is allocated in the cluster, barring a few cores on node28. Node13 isn't doing anything, but it's part of a different queue, probably reserved for admin, or people with special permissions to run really long jobs.&lt;/p&gt;&#xA;&lt;p&gt;If your runtime is longer than 1 hour, your job will never get allocated, unless you are using a GPU, because no only the &amp;quot;demoq&amp;quot; allows this, and you probably don't have access.&lt;/p&gt;&#xA;&lt;p&gt;There's a very small number of high memory nodes, and, worse, they're in the standard queue. If your job requires a bunch of memory, you have to wait until one of these nodes becomes free, but other jobs can also be allocated there. So your job wait time is, in the worst case &amp;quot;wait to reach the front of the queue, and then wait until a high memory node frees up&amp;quot; - the scheduler will try and be smart about allocation, but it's imperfect.&lt;/p&gt;&#xA;&lt;p&gt;To get your jobs to start faster, you need to work out the resources they need - look at how much memory they use, and if they effectively make use of all the cores and memory you assign them. If not, reduce the requirements in your submission script.&lt;/p&gt;&#xA;&lt;p&gt;It is also useful to be aware of the specifications of each class of node. If a standard node has 64Gb of memory, and you're looking for 65Gb, it'll bump your job to competing for one of the high memory nodes. Similarly, if you request 10 cores, and a standard node has 8, you'll be waiting for a node with higher core count. If you request resources no node in the cluster has, your job may enter an infinite, never running state, where it will just sit in the queue, and never be scheduled.&lt;/p&gt;&#xA;&lt;p&gt;Do you have a support team? Generally, having been HPC support, we like answering questions about using the cluster efficiently. The sheer number of times someone's single threaded code has requested 16 cores is quite impressive. They might be able to direct you to somewhere that can show you stats for your previous jobs, and you can check if you can reduce the resources you're requesting. Reducing requirements has a huge, huge effect on how fast things will be scheduled. It's also being a good citizen, as other people's jobs will be run faster.&lt;/p&gt;&#xA;&lt;p&gt;The big TL:DR is, I think the same as @Shen Ree Tee's - you have no control over how busy the cluster is, and pretty much the only way to speed up your job queuing is to make sure you're only requesting as much ram or cpu as you need, and not asking the queue to assign impossible jobs.&lt;/p&gt;&#xA;&lt;p&gt;Edit: the only other possible speedup is if you have a job that can be split up. Adding multiple small jobs to the queue, rather than one big one, increases their ability to run alongside other jobs. It's a bit like tables at a restaurant - if you show up with a party of 16, it's going to take ages to get seated. If you are happy to be 8 groups of 2, you can be slotted in around everyone else, and get seated faster.&lt;/p&gt;&#xA;" OwnerUserId="3789" LastEditorUserId="3789" LastEditDate="2023-07-12T16:53:37.397" LastActivityDate="2023-07-12T16:53:37.397" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11270" PostTypeId="2" ParentId="11198" CreationDate="2023-07-12T18:43:40.897" Score="1" Body="&lt;p&gt;The second order susceptibility tensor can be written as the fourier transform of the correlation between the dipole moment (over time) and the polarizability (over time). This is for Sum-Frequency Generation, although SHG is probably similar .&lt;/p&gt;&#xA;&lt;p&gt;So just calculate those for your system over say 50 ps with a step size of maybe .5 fs.&lt;/p&gt;&#xA;" OwnerUserId="7556" LastEditorUserId="7556" LastEditDate="2023-07-12T18:50:45.367" LastActivityDate="2023-07-12T18:50:45.367" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11271" PostTypeId="2" ParentId="11252" CreationDate="2023-07-12T20:58:20.470" Score="1" Body="&lt;p&gt;You might find the Avogadro software (old v1.20) useful for this work. You can create a specified cell (Crystallography&amp;gt;&amp;gt;Add unit cell) and copy and paste the structures you might already have (in xyz format), or create those in another window of Avogadro, pre-relax it using the classical fields available in Avogadro and copy-paste it inside the cell.&lt;/p&gt;&#xA;&lt;p&gt;Be careful of periodic boundaries as the molecules might be very close to each other in the images.&lt;/p&gt;&#xA;" OwnerUserId="1137" LastActivityDate="2023-07-12T20:58:20.470" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11272" PostTypeId="1" CreationDate="2023-07-12T21:39:20.757" Score="1" ViewCount="134" Body="&lt;p&gt;I'm a newbye in DFT calculations and it's my first time I use vc-relax. I have to find optimal cell parameters for mono-layer &lt;span class=&quot;math-container&quot;&gt;$MoS_2$&lt;/span&gt; and that's my code :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      &amp;amp;CONTROL&#xA;calculation = 'vc-relax'&#xA;prefix = 'MoS2_MonoLayer '&#xA;pseudo_dir = './'&#xA;outdir = './'&#xA;tsress=.true.&#xA;tprnfor=.true.&#xA;forc_conv_thr = 1.0d-3&#xA;nstep = 200&#xA;/&#xA;      &amp;amp;SYSTEM&#xA;ibrav = 4&#xA;a = 3.244249522500000&#xA;c = 9.365949096500000&#xA;nat = 3&#xA;ntyp = 2&#xA;ecutwfc = 50&#xA;ecutrho = 310&#xA;/&#xA;        &amp;amp;ELECTRONS&#xA;mixing_beta = 0.7&#xA;conv_thr = 1.0 d-8&#xA;diagonalization = 'david'&#xA;electron_maxstep = 200&#xA;/&#xA;     &amp;amp;IONS&#xA;trust_radius_max = 0.2&#xA;/&#xA;     &amp;amp;CELL&#xA;cell_dynamics = &amp;quot;bfgs&amp;quot;&#xA;&#xA;ATOMIC_SPECIES&#xA;Mo 95.9400 Mo.pbesol-spn-kjpaw_psl.1.0.0.UPF&#xA;S 32.0660 S.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS(crystal)&#xA;Mo 0.333333330 0.666666670 0.250000000&#xA; S 0.666666670 0.333333330 0.087698981&#xA; S 0.666666670 0.333333330 0.412301018&#xA;&#xA;K_POINTS{automatic}&#xA;4 4 4 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I never get that nice &amp;quot;JOB DONE&amp;quot; using vc-relax , this only works with scf. Sometimes I get the error dE0s is positive which it should never happen. I really do not know what to do :(&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-07-14T06:58:20.017" Title="Vc-Relax never stops" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11273" PostTypeId="1" AcceptedAnswerId="11304" CreationDate="2023-07-12T22:00:03.403" Score="4" ViewCount="193" Body="&lt;p&gt;I am trying to recreate Fig. 5b of &lt;a href=&quot;https://fast.net.technion.ac.il/files/2020/06/c9cp06163k.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have a solvated NH4+ in my system and would like to create a similar visualisation for my case.&lt;/p&gt;&#xA;&lt;p&gt;Can this be generated using VMD? If so could someone point out what i should be looking for in the documentation? Alternatively, what other software could I use to create this? Thank y'all!&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/y3WtS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/y3WtS.png&quot; alt=&quot;Spatial distribution of water around NH4+&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7558" LastEditorUserId="7558" LastEditDate="2023-07-17T18:07:19.173" LastActivityDate="2023-12-08T16:50:05.447" Title="Visualising the spatial distribution of water structure using VMD" Tags="|molecular-dynamics|visualization-software|vmd|water|reproducing-data-from-papers|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11274" PostTypeId="1" AcceptedAnswerId="11283" CreationDate="2023-07-13T11:17:29.743" Score="6" ViewCount="129" Body="&lt;p&gt;What are the benefits or pitfalls in using a GA based optimizer for geometry optimization instead of a more traditional Hessian based algorithm?&lt;/p&gt;&#xA;&lt;p&gt;It can be argued that performing single point energy calculations is much cheaper than calculating the approximate hessian at each point. The origin of this question is from this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.75.288&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; where the authors have used a GA based optimizer to obtain the stable structure for &lt;span class=&quot;math-container&quot;&gt;$C_{60}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$C_{20}$&lt;/span&gt; molecules.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5689" LastEditDate="2023-07-14T11:34:54.720" LastActivityDate="2023-07-14T12:59:30.680" Title="Use of genetic algorithm based methods for geometry optimization" Tags="|molecular-modeling|geometry-optimization|machine-learning|optimization|nanostructures|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11275" PostTypeId="5" CreationDate="2023-07-13T11:21:42.700" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-07-13T11:21:42.700" LastActivityDate="2023-07-13T11:21:42.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11276" PostTypeId="4" CreationDate="2023-07-13T11:21:42.700" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-07-13T11:21:42.700" LastActivityDate="2023-07-13T11:21:42.700" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11277" PostTypeId="2" ParentId="11268" CreationDate="2023-07-13T16:12:10.947" Score="2" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;To visualize a trajectory in ASE, you have to use the default &lt;code&gt;'ase'&lt;/code&gt; viewer. The &lt;code&gt;'x3d'&lt;/code&gt; viewer currently only allows visualizing one structure.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;When you open the ase viewer GUI, you can simply press &lt;strong&gt;Ctrl+B&lt;/strong&gt; to visualize bonds, and &lt;strong&gt;Ctrl+U&lt;/strong&gt; to visualize unit cell. In command line, you can simply do &lt;code&gt;ase gui -b md.traj&lt;/code&gt; to visualize bonds.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;If you want to make a movie that shows the change of the bonds, it becomes tricky. Although you can visualize bonds in ase GUI, when you save a snapshot as an image, the bonds disappear. Writing to a movie, e.g. &lt;code&gt;ase.io.write('movie.gif', read_traj)&lt;/code&gt;, do not support showing bonds either. Maybe you can work around by taking a screenshot for each snapshot, but my suggestion would be to download the &lt;a href=&quot;http://www.povray.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;POV-Ray&lt;/a&gt; tool. You can find a code example &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/io.html#examples&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; for generating a high quality image of the C&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;H&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; molecule with bonds using ASE and POV-Ray. You will need to generate an image for each snapshot, then combine them into a movie.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;To the best of my knowledge, neither MDTraj nor MDAnalysis have an interface to ASE. However, you can check out the list of structure file formats supported by ASE &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/io.html#file-input-and-output&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. Essentially, if you choose a format that can be read and written by both ASE and MDTraj/MDAnalysis, you are good to go.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-13T17:00:30.870" LastActivityDate="2023-07-13T17:00:30.870" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11280" PostTypeId="2" ParentId="9352" CreationDate="2023-07-14T06:31:57.677" Score="3" Body="&lt;h2&gt;&lt;a href=&quot;http://crystalium.materialsvirtuallab.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Crystalium&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Developed by the &lt;a href=&quot;https://materialsvirtuallab.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Virtual Lab&lt;/a&gt;, Crystalium is a database for grain boundaries, surfaces, and Wulff shapes of the elements (mostly metal). It contains useful information such as surface energy, work function and .cif files for low-index surfaces of elementary substances. However, oxide surfaces are not included.&lt;/p&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://www.fhi.mpg.de/1017073/oSSD/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Open Surface Structure Database (oSSD)&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The Open Surface Structure Database (oSSD) collects quantitative surface structures from experimental studies published between 1974, the beginning of surface crystallography, and 2004, when all &amp;quot;basic&amp;quot; structures had been explored. It is the open access version of Version 5 of the Surface Structure Database (SSD, Database # 42) published by the National Institute of Standards and Technology (NIST) and distributed until 2011.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Developed by &lt;a href=&quot;https://www.fhi.mpg.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;FHI&lt;/a&gt;, oSSD is a database that contains information about a wide variety of surface structures determined from experiments, including&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;commensurate structures (which covers most solved structures, including oxides);&lt;/li&gt;&#xA;&lt;li&gt;incommensurate structures (formed for instance by physisorption);&lt;/li&gt;&#xA;&lt;li&gt;disordered structures of adsorbates and alloys;&lt;/li&gt;&#xA;&lt;li&gt;solid-solid interfaces.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It provides useful structural information such surface unit cell vectors and 3D coordinates, but no surface energy.&lt;/p&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://materialsweb.org/substrate&quot; rel=&quot;nofollow noreferrer&quot;&gt;MaterialsWeb&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;They cleaved a large number of bulk crystals (mostly metal oxides), and performed DFT for these surfaces and stored all calculations in a database, where one can get information such as energies and structure coordinates.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-08-07T20:34:45.640" LastActivityDate="2023-08-07T20:34:45.640" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11281" PostTypeId="2" ParentId="11272" CreationDate="2023-07-14T06:58:20.017" Score="1" Body="&lt;p&gt;I used the following input file (I made few changes; like using the default values for convergence and other parameters, and used a larger cutoff for ecutrho and ecutwfn). I was able to get the file to converge in 21 bfgs cycles.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;CONTROL&#xA;   title           = 'test-mos2' &#xA;   calculation     = 'vc-relax' &#xA;   restart_mode    = 'from_scratch' &#xA;   outdir          = './temp' &#xA;   pseudo_dir      = './' &#xA;   prefix          = 'MoS2_MonoLayer' &#xA;   disk_io         = 'high' &#xA;   verbosity       = 'high' &#xA;   tstress         = .true. &#xA;   tprnfor         = .true. &#xA; /&#xA; &amp;amp;SYSTEM&#xA;   ibrav           = 4&#xA;   A               = 3.244249522500000 &#xA;   C               = 9.365949096500000 &#xA;   nat             = 3&#xA;   ntyp            = 2&#xA;   ecutwfc         = 60 &#xA;   ecutrho         = 600 &#xA;   nbnd            = 20&#xA; /&#xA; &amp;amp;ELECTRONS&#xA;   startingpot     = 'atomic' &#xA;   startingwfc     = 'atomic+random' &#xA;   mixing_mode     = 'plain' &#xA;   diagonalization = 'david' &#xA; /&#xA; &amp;amp;IONS&#xA;   ion_dynamics    = 'bfgs' &#xA;   pot_extrapolation = 'atomic' &#xA;   wfc_extrapolation = 'first_order' &#xA; /&#xA; &amp;amp;CELL&#xA;   cell_dynamics   = 'bfgs' &#xA;   cell_dofree     = 'all' &#xA; /&#xA;ATOMIC_SPECIES&#xA;   Mo   95.94000  Mo.pbe-spn-kjpaw_psl.1.0.0.UPF &#xA;    S   32.06600  S.pbe-n-kjpaw_psl.1.0.0.UPF &#xA;ATOMIC_POSITIONS crystal &#xA;   Mo      0.333333330    0.666666670    0.250000000    &#xA;    S      0.666666670    0.333333330    0.087698981    &#xA;    S      0.666666670    0.333333330    0.412301018    &#xA;K_POINTS automatic &#xA;  4 4 4   0 0 0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-14T06:58:20.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11282" PostTypeId="1" AcceptedAnswerId="11317" CreationDate="2023-07-14T08:58:55.647" Score="10" ViewCount="200" Body="&lt;p&gt;The Hartree-Fock Hamiltonian is given by&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat{H} = \sum_i \hat{h}_i + \frac{1}{2}\sum_i\sum_j \left[\hat{J}_{ij} - \hat{K}_{ij}\right]&#xA;$$&lt;/span&gt;&#xA;and by choosing a basis, the Hamiltonian can be written in matrix form, where the entries are given by &lt;span class=&quot;math-container&quot;&gt;$\langle \phi_i|\hat{H}|\phi_j\rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The time evolution for a time independent Hamiltonian is in turn given by &lt;span class=&quot;math-container&quot;&gt;$|\Psi(t)\rangle = e^{-iHt/\hbar}|\Psi(0)\rangle$&lt;/span&gt; and for time dependent Hamiltonians we can do e.g. a Magnus expansion to calculate the time evolution.&lt;/p&gt;&#xA;&lt;p&gt;In our case, however, the Hamiltonian depends on the wave function at the next time step and a Magnus expansion is therefore only possible up to the 0-th order.&lt;/p&gt;&#xA;&lt;p&gt;What is a better way to determine the time evolution of a Hartee-Fock state? I have already heard about TDHF, but I have not found an introduction including derivation that explains everything from scratch. So if TDHF is the right approach I would be interested in a good reference.&lt;/p&gt;&#xA;" OwnerUserId="5689" LastEditorUserId="5" LastEditDate="2023-07-16T09:54:08.577" LastActivityDate="2023-07-26T14:20:46.033" Title="Time Evolution of the Hartree-Fock Wave Function" Tags="|reference-request|quantum-mechanics|hartree-fock|quantum-dynamics|mctdh|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11283" PostTypeId="2" ParentId="11274" CreationDate="2023-07-14T12:59:30.680" Score="7" Body="&lt;p&gt;The paper you cite has certainly left a legacy, but it is by now almost 30 years old! I think its main insight is in applying &lt;em&gt;physics-agnostic, information-theoretic ideas&lt;/em&gt; to atomistic coordinates. (You can guess where this will end up!)&lt;/p&gt;&#xA;&lt;p&gt;While it's certainly been spiritually successful (for example, it's cited in the &lt;a href=&quot;https://pubs.aip.org/aip/apm/article/1/1/011002/119685/Commentary-The-Materials-Project-A-materials&quot; rel=&quot;noreferrer&quot;&gt;Materials Project paper&lt;/a&gt;), I think it would be difficult to naturally extend a GA approach to generic systems. How do you naturally &amp;quot;genotype&amp;quot; a configuration, so that &amp;quot;breeding&amp;quot; configurations yields a suitable descendant &amp;quot;phenotype&amp;quot;? The descendant must inherit the &amp;quot;traits&amp;quot; that made its parents strong -- while being a distinct enough to encourage exploration of configuration space.&lt;/p&gt;&#xA;&lt;p&gt;The paper authors found a clever way to do this for carbon cluster coordinates (slicing a plane through configurations and then &amp;quot;gluing&amp;quot; parents together at the join), but it's not obvious that their methods could generalise to, say, optimising protein structures (or ligand docking) or liquid weak ordering or phase transitions in bulk metals or ...&lt;/p&gt;&#xA;&lt;p&gt;It seems that, especially with today's increasing computational power, you could do better than GA in one of two directions: less information theory, or more information theory. In the less info-theory direction, why not calculate forces along with energies? Sure, they're expensive, but not &lt;em&gt;that&lt;/em&gt; much more expensive. And once you have forces you have the full gradient of energy vs atomic coordinates. While you don't have the Hessian, you &lt;em&gt;do&lt;/em&gt; now have plenty of Hessian-free optimisation methods available, especially conjugate gradient as a simple off-shelf method well suited to energy optimisation (since the energy of a bound state is nicely symmetric positive-definite). Plenty of molecular dynamics (MD) packages will do all this and more for you -- replica exchange, instead of simulated annealing, comes to mind as another method for encouraging phase space exploration.&lt;/p&gt;&#xA;&lt;p&gt;In the more info-theory direction: machine learning! ML descriptors are a souped-up &amp;quot;genotype&amp;quot; for atomic configurations. They incorporate physical information about the system, while also being generically definable across a variety of systems and mathematically ready to be ingested by your favourite ML platform. Put differently, a genetic algorithm, in the process of evolving towards an optimal configuration, doesn't pick up how to calculate forces from positions (and thus it could run on 1995 computers). But an ML model trained to calculate energies can also calculate the derivatives of energy in the atomic descriptors -- and that gets you forces! So you get an MD force field into the bargain, opening up all kinds of follow-on calculation possibilities.&lt;/p&gt;&#xA;&lt;p&gt;That's just what I think -- this was a fantastic paper for 1995, but these days you'd go either in the MD direction or the ML direction (which you could also hook up to subsequent MD simulations).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-07-14T12:59:30.680" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11284" PostTypeId="1" AcceptedAnswerId="11290" CreationDate="2023-07-14T15:44:04.450" Score="6" ViewCount="207" Body="&lt;p&gt;I've been working on a project that involves the clustering of data with periodic boundary conditions. Like simulation of extra-framework water species.&#xA;Specifically, I am looking for clustering algorithms that can effectively handle datasets where periodicity plays a significant role.&lt;/p&gt;&#xA;&lt;p&gt;Upon searching the traditional clustering algorithms like k-means, I gather that they are not designed to account for periodicity inherently. I would love to hear about the clustering algorithms suitable for datasets with periodic boundary conditions from experts and enthusiasts. Are there any other algorithms that you have found to be effective in this context?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for your valuable input!&lt;/p&gt;&#xA;" OwnerUserId="4219" LastEditorUserId="5" LastEditDate="2023-07-14T17:25:40.770" LastActivityDate="2023-07-22T01:47:21.443" Title="Clustering Algorithms with Periodic Boundary Conditions" Tags="|molecular-dynamics|atomic-simulation-environment|atomistic-simulation|periodic-boundary-conditions|water|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11285" PostTypeId="1" AcceptedAnswerId="11293" CreationDate="2023-07-14T16:22:34.640" Score="4" ViewCount="60" Body="&lt;p&gt;Say I have a MD trajectory that contains a million snapshots (i.e. a million atomic structures). Each snapshot contains some calculated information (either by DFT or some force field) such as energy, forces and potentially other properties. What software can efficiently store these atomic structures into a database file without losing any relevant information? Ideally, one should always be able to reproduce each atomic structure from the database. I'm particularly interested in database programs that can handle huge amount of structural data without taking too much memory space.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-14T22:35:44.480" LastActivityDate="2023-07-19T02:29:05.937" Title="Software for storing information of large number of atomic structures into database file" Tags="|molecular-dynamics|software|software-recommendations|one-topic-per-answer|databases|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11287" PostTypeId="1" CreationDate="2023-07-14T20:24:36.593" Score="3" ViewCount="702" Body="&lt;p&gt;I am very new to Pymol and was trying to figure out how I can find the largest distance between 2 residues. Using just the basic distance function I get multiple distances which is not very useful in my case as it finds the distance between every single atom in the residue. I would like this distance to be stored in a list because I will repeat this multiple times for other residues.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/CKmBF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/CKmBF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7564" LastActivityDate="2023-08-23T18:35:08.713" Title="How to find the smallest distance between 2 residues in Pymol?" Tags="|python|visualization-software|proteins|pymol|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11288" PostTypeId="1" CreationDate="2023-07-14T21:46:51.183" Score="3" ViewCount="99" Body="&lt;p&gt;I am having some difficulties understanding values of exciton binding energies for &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; monolayer. In various papers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Interlayer and intralayer excitons in MoS2/WS2 and MoSe2/WSe2 heterobilayers&#xA;Engin Torun, Henrique P. C. Miranda, Alejandro Molina-Sánchez, and Ludger Wirtz&#xA;Phys. Rev. B 97, 245427 &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.97.245427&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Binding energies of exciton complexes in transition metal dichalcogenide monolayers and effect of dielectric environment&#xA;Ilkka Kylänpää and Hannu-Pekka Komsa&#xA;Phys. Rev. B 92, 205418 &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.92.205418&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;They calculate exciton binding energy as difference between optical gap and electronic band gap. For example for &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; monolayer exciton A lies around 1.85 eV. They use gw band gap around 2.35,2.40 to calculate A exciton binding energy. But in reality &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; monolayer has around 1.9 eV experimental band gap.&lt;/p&gt;&#xA;&lt;p&gt;The GW method is known to overestimate band gap of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; monolayer. In this case it’s binding energy should be around zero; can anyone explain this discrepancy?&lt;/p&gt;&#xA;&lt;p&gt;Also, in the below paper they use another value of band gap to estimate exciton binding energy even though they have a smaller band gap they estimated with fitting:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Ermolaev, G.A., Stebunov, Y.V., Vyshnevyy, A.A. et al. Broadband optical properties of monolayer and bulk MoS2. npj 2D Mater Appl 4, 21 (2020). &lt;a href=&quot;https://doi.org/10.1038/s41699-020-0155-x&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1213" LastEditorUserId="7" LastEditDate="2023-07-15T13:55:55.173" LastActivityDate="2023-07-15T13:55:55.173" Title="How is exciton binding energy calculated?" Tags="|gw-bse|dichalcogenides|exciton|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11289" PostTypeId="1" AcceptedAnswerId="12148" CreationDate="2023-07-15T00:08:35.780" Score="3" ViewCount="200" Body="&lt;p&gt;I would like to know when we need to apply Van der Waals (vdW) correction in our system. If I am dealing with 2d systems (monolayer or bilayer), then should I need to add IVDW (vdW (dispersion) correction) tag in the VASP input file. What is the role of vdW correction.&#xA;Also, I would like to know when we are applying SOC in the calculations, can we escape vdW correction at that time.&lt;/p&gt;&#xA;" OwnerUserId="5256" LastEditorUserId="5256" LastEditDate="2023-07-17T17:29:55.657" LastActivityDate="2023-12-26T09:24:02.487" Title="About Van der Waals (vdW) correction in VASP" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11290" PostTypeId="2" ParentId="11284" CreationDate="2023-07-15T01:57:07.190" Score="8" Body="&lt;p&gt;First, there is a recent &lt;a href=&quot;https://doi.org/10.3390/sym14061237&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; in which they proposed a k-means clustering algorithm adapted for periodic boundary conditions. Their Python implementation is available &lt;a href=&quot;https://github.com/kpodlaski/periodic-kmeans&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, the clustering algorithm I would suggest for periodic systems is the &lt;a href=&quot;https://en.wikipedia.org/wiki/K-medoids&quot; rel=&quot;nofollow noreferrer&quot;&gt;k-medoids algorithm&lt;/a&gt;. In contrast to the k-means algorithm, k-medoids selects actual data points as centers (i.e. medoids), and relies solely on pairwise distances instead of actual coordinates. The most popular k-medoids algorithm is the PAM algorithm, which has an &lt;a href=&quot;https://pyclustering.github.io/docs/0.9.0/html/d0/dd3/classpyclustering_1_1cluster_1_1kmedoids_1_1kmedoids.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;implementation in PyClustering&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I suggested k-medoids mainly because you mentioned k-means in your question. In some cases, one would want a clustering algorithm that doesn't require a pre-defined number of clusters. Then I would suggest you to look into &lt;a href=&quot;https://en.wikipedia.org/wiki/Hierarchical_clustering&quot; rel=&quot;nofollow noreferrer&quot;&gt;hierarchical clustering&lt;/a&gt;, where you can compare each point with other points only using distance measure. The algorithm actually has a &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Scipy implementation&lt;/a&gt;. Remember you can always get pairwise distance in periodic boundary condition using ASE by &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms.get_distance&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;atoms.get_distance(a0, a1, mic=True)&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Below is an example of the 5-medoids clustering algorithm for your water system using ASE and PyClustering:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyclustering.cluster.kmedoids import kmedoids&#xA;from ase.io import read, write&#xA;from ase.visualize import view&#xA;import random&#xA;&#xA;# Read in the structure&#xA;atoms = read('str_opt_first.cif')&#xA;# Visualize the structure&#xA;view(atoms)&#xA;# Get the distance matrix in pbc&#xA;D = atoms.get_all_distances(mic=True)&#xA;&#xA;# K-medoids clustering (PAM algorithm)&#xA;k = 5&#xA;# Initialize from a random atom (index). Set seed for reproducibility&#xA;medoid_init = random.sample(range(len(atoms)), k)&#xA;pam = kmedoids(D, medoid_init, data_type='distance_matrix')&#xA;pam.process()&#xA;medoids = pam.get_medoids()&#xA;clusters = pam.get_clusters()&#xA;print(medoids)&#xA;print(clusters)&#xA;&#xA;# Visualize one of the clusters&#xA;view(atoms[clusters[0]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Your original structure looks like this:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/b3RuW.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/b3RuW.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And a cluster will look something like this:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Q3gD9.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Q3gD9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-22T01:47:21.443" LastActivityDate="2023-07-22T01:47:21.443" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11291" PostTypeId="2" ParentId="8488" CreationDate="2023-07-15T03:29:51.497" Score="2" Body="&lt;p&gt;To stack two 2D structures in ASE, a matching of the two unit cells is required. I will assume your graphene and TMD unit cells have the same &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; lattice parameters but slightly different &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;. The common choice is to use the larger unit cell as reference, and scale the atomic coordinates in the smaller unit cell to fit in the larger cell. The stacking can be done by &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#ase.build.add_adsorbate&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.build.add_adsorbate&lt;/code&gt;&lt;/a&gt;, where you can play around the &lt;code&gt;height&lt;/code&gt; parameter to adjust the relative position of the adsorbate in the z direction. This often results in a decent heterogeneous structure, but if you want to adjust the adsorbate in the x and y directions, the easiest way is to move the atoms in the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/gui/gui.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE's GUI&lt;/a&gt; by pressing &lt;code&gt;Ctrl+M&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Below is an example of stacking a 3-layer MoS&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; (larger cell) on top of a graphene monolayer (samller cell) in ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import graphene, mx2&#xA;from ase.build import add_adsorbate&#xA;from ase.visualize import view&#xA;&#xA;# Build a graphene monolayer&#xA;atoms = graphene()&#xA;&#xA;# Build a 3-layer MoS2 &#xA;MoS2 = mx2(formula='MoS2', kind='2H', a=3., thickness=3.19, vacuum=5.)&#xA;# Match the two unit cells in the z direction&#xA;atoms.cell[2] = MoS2.cell[2]&#xA;&#xA;# Save the fractional coordinates of graphene&#xA;fracs = atoms.get_scaled_positions()&#xA;# Match the two unit cells in all directions&#xA;atoms.cell = MoS2.cell&#xA;# Scale the atomic coordinates of graphene&#xA;atoms.positions = fracs @ MoS2.cell&#xA;&#xA;# Stack the two structures&#xA;add_adsorbate(atoms, adsorbate=MoS2, height=3.)&#xA;# Center the structure in the z direction&#xA;atoms.center(vacuum=5., axis=2)&#xA;# Visualize&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BPvG5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BPvG5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-15T03:37:32.000" LastActivityDate="2023-07-15T03:37:32.000" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11292" PostTypeId="1" AcceptedAnswerId="11295" CreationDate="2023-07-15T08:42:04.857" Score="5" ViewCount="337" Body="&lt;p&gt;I want to code an UHF code. Hence for each atom I need the lowest energy electronic configuration. Is there a python package/library that already does it?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-07-15T16:11:47.147" LastActivityDate="2023-07-15T16:11:47.147" Title="Python library to obtain atomic orbitals of atoms in the lowest energy state" Tags="|python|software-recommendations|electronic-structure|one-topic-per-answer|atomistic-simulation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11293" PostTypeId="2" ParentId="11285" CreationDate="2023-07-15T12:07:46.133" Score="5" Body="&lt;p&gt;One of the more recent options for the xyz file format is &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jcim.8b00501&quot; rel=&quot;nofollow noreferrer&quot;&gt;bqbtool&lt;/a&gt; by Martin Brehm, which significantly compresses the trajectory files by factor of &lt;strong&gt;20~30&lt;/strong&gt; using a lossless compression scheme. One of the main advantages of this compression scheme is that one can use the associated code &lt;a href=&quot;https://doi.org/10.1063/5.0005078&quot; rel=&quot;nofollow noreferrer&quot;&gt;travis&lt;/a&gt; to calculate basic properties such as radial and spatial distribution, structure factor, correlation functions,vibrational spectra and much more directly from the converted bqb file.&lt;/p&gt;&#xA;&lt;p&gt;You can read more about bqbtool at &lt;a href=&quot;https://brehm-research.de/bqb.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://brehm-research.de/bqb.php&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="1151" LastEditDate="2023-07-19T02:29:05.937" LastActivityDate="2023-07-19T02:29:05.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11294" PostTypeId="1" CreationDate="2023-07-15T14:22:49.070" Score="5" ViewCount="48" Body="&lt;p&gt;There are some questions and answers (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1550/what-are-some-methods-for-modeling-bulk-phase-infrared-spectra&quot;&gt;1&lt;/a&gt;,&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2283/how-exactly-does-one-compute-the-vibrational-density-of-states-from-the-output-o&quot;&gt;2&lt;/a&gt;) on this site regarding simple infrared and vibrational density of states calculations with molecular dynamics and there any simple algorithmic descriptions of these quantities using velocity-velocity correlation functions. But there are not many clear descriptions/resources available for 2D infrared spectroscopy though there are some articles available describing such calculations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;T. l. C. Jansen, B. M. Auer, Mino Yang, J. L. Skinner; Two-dimensional infrared spectroscopy and ultrafast anisotropy decay of water. &lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;2010&lt;/strong&gt;; 132 (22): 224503. &lt;a href=&quot;https://doi.org/10.1063/1.3454733&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.3454733&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;T. l. C. Jansen,J. Knoester; Nonadiabatic Effects in the Two-Dimensional Infrared Spectra of Peptides:  Application to Alanine Dipeptide. &lt;em&gt;J. Phys. Chem. B&lt;/em&gt; &lt;strong&gt;2006&lt;/strong&gt; 110 (45), 22910-22916. &lt;a href=&quot;https://doi.org/10.1021/jp064795t&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jp064795t&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Can some who has experience implementing or calculating such data elaborate step-by-step on how to calculate a 2D infrared spectra or a related quantity?&lt;/p&gt;&#xA;" OwnerUserId="1151" LastEditorUserId="1151" LastEditDate="2023-07-27T00:29:56.600" LastActivityDate="2023-07-27T00:29:56.600" Title="2D Infrared spectroscopy for bulk systems using molecular dynamics" Tags="|molecular-dynamics|spectroscopy|vibrations|phonon-density-of-state|correlation-functions|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11295" PostTypeId="2" ParentId="11292" CreationDate="2023-07-15T15:03:12.007" Score="8" Body="&lt;h1&gt;Mendeleev&lt;/h1&gt;&#xA;&lt;p&gt;You can use a python library called Mendeleev. Below is an example of a Silicon atom.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mendeleev import element&#xA;si = element('Si')&#xA;print(si.econf)&#xA;&#xA;&amp;gt;&amp;gt; '[Ne] 3s2 3p2'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-07-15T15:03:12.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11296" PostTypeId="1" CreationDate="2023-07-15T17:24:10.313" Score="1" ViewCount="37" Body="&lt;p&gt;I'm calculating the DOS and PDOS of Li2CuO2 using quantum espresso. How can I calculate the atomic-resolved and orbital-resolved density of states separately? I want to individually have DOS for Li Cu and O and orbital-DOS for the Cu atom.&lt;/p&gt;&#xA;&lt;p&gt;I have used projwfc.x already and I have orbital-resolved and total DOS and I can't see the total DOS for the separate atoms.&lt;/p&gt;&#xA;" OwnerUserId="7568" LastActivityDate="2023-07-15T17:24:10.313" Title="How can I calculate atomic-resolved and orbital-resolved density of states using quantum espresso" Tags="|density-of-states|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:22:46.910" ContentLicense="CC BY-SA 4.0" />
  <row Id="11297" PostTypeId="1" CreationDate="2023-07-15T21:40:31.240" Score="2" ViewCount="60" Body="&lt;p&gt;I'm trying to find the I-Vg curve of a specefic system using transiesta implementation of gate. The problem that I encountered is the non-convergence of calculation even though they get below the dHmax and dDmax threshold:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ts-scf:  376   -24915.567447   -24915.567447   -24915.567447  0.000000 -5.273126  0.000000&#xA;ts-err-D: ij(  615,   615), M = 0.82931   , ew = -.43081E-3, em = 0.84114E-3. avg_em = 0.19371E-06&#xA;ts-err-E: ij( 1031,  1083), M = -.45300   , ew = -.52388E-5, em = 0.99605E-5. avg_em = -.69752E-09&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7315" LastEditorUserId="6687" LastEditDate="2023-07-16T06:21:03.237" LastActivityDate="2024-01-17T10:00:40.060" Title="Transiesta convergence" Tags="|siesta|" AnswerCount="1" CommentCount="0" ClosedDate="2024-03-08T22:37:06.803" ContentLicense="CC BY-SA 4.0" />
  <row Id="11298" PostTypeId="1" CreationDate="2023-07-17T14:06:14.607" Score="3" ViewCount="486" Body="&lt;p&gt;I'm getting my bachelor degree in physics and in my structure of matter course we never talked about bulk, monolayer and so on. I can understand Bravais lattice , reciprocal lattice and so on but I'm very confused about the pratical implementation of bulk structure for Quantum Espresso. For example I think that this code gives me a monolayer becayse I only have 3 atoms in a unitary cell and the c parameter is high enough to eliminate the periodicity:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;SYSTEM&#xA;ibrav = 4&#xA;a = 3.1401972104&#xA;c = 13.3662099134&#xA;nat = 3&#xA;ntyp = 2&#xA;ecutwfc = 70&#xA;&#xA;ATOMIC_SPECIES&#xA;Mo 95.9400 Mo.pbesol-spn-kjpaw_psl.1.0.0.UPF&#xA;S 32.0660  S.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS (crystal)&#xA;Mo  0.3333332524 0.6666665101 0.25000000000&#xA;S   0.6666666723 0.3333244955 0.13328123440&#xA;S   0.6666667238 0.3333332449 0.36667187666&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Instead here we have a bilayer because there are 6 atoms:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;SYSTEM&#xA;ibrav = 4&#xA;a = 3.13616595240&#xA;c = 12.0411134300&#xA;nat = 6&#xA;ntyp = 2&#xA;ecutwfc = 70&#xA;&#xA;ATOMIC_SPECIES&#xA;Mo 95.9400 Mo.pbesol-spn-kjpaw_psl.1.0.0.UPF&#xA;S 32.0660  S.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS (crystal)&#xA;Mo  0.3333333000 0.6666666700 0.25000000000&#xA;Mo  0.6666666700 0.3333333000 0.75000000000&#xA;S   0.6666666700 0.3333333000 0.37563781800&#xA;S   0.3333333000 0.6666666700 0.87563781800&#xA;S   0.6666666700 0.3333333330 0.12436218100&#xA;S   0.3333333300 0.6666666670 0.62436218100&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But my advisor told me that this is the bulk structure , not the bi-layer. What am I doing wrong? I'm sorry for the really newbie questions.&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-07-17T17:42:31.143" Title="Noob Question: How can I write bulk, monolayer and bilayer structure in input file for visualizing it" Tags="|quantum-espresso|physical-properties-of-materials|structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11299" PostTypeId="2" ParentId="11298" CreationDate="2023-07-17T14:33:45.620" Score="6" Body="&lt;p&gt;Indeed, this input represents a bulk structure&lt;/p&gt;&#xA;&lt;p&gt;The trick here is that the input is using fractional coordinates:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS (crystal)&#xA;Mo  0.3333332524 0.6666665101 0.25000000000&#xA;S   0.6666666723 0.3333244955 0.13328123440&#xA;S   0.6666667238 0.3333332449 0.36667187666&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, the final Cartesian coordinates will always be proportional to the cell parameters: if you increase the cell parameters, the positions will increase in absolute value too. In this case (assuming &lt;span class=&quot;math-container&quot;&gt;$b=a$&lt;/span&gt; and cell parameters in Angstrom), the Cartesian coordinates will be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Mo  1.046732149 2.093464315 3.341552478&#xA;S   2.093464825 1.046704651 1.781464957&#xA;S   2.093464986 1.046732126 4.901013273&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, if you use them, you can change the cell parameters without moving the atoms too (probably you need to change the type of coordinates in the input from fractional to Cartesian).&lt;/p&gt;&#xA;&lt;p&gt;About the second input, no, it is no a bilayer because, as there are fractional coordinates, you have more atoms in the same cell.&lt;/p&gt;&#xA;&lt;p&gt;I strongly recommend you to use some software to produce your monolayers (or other supercells). For example &lt;a href=&quot;https://github.com/torbjornbjorkman/cif2cell&quot; rel=&quot;noreferrer&quot;&gt;CIF2Cell&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-07-17T14:33:45.620" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11301" PostTypeId="1" CreationDate="2023-07-17T19:25:34.497" Score="2" ViewCount="81" Body="&lt;p&gt;I'd like to get the monolayer input file for MoS2 using BURAI 1.3. I downloaded the .cif file from Materials Project and with the Modeler function I created a Monolayer MoS2 but when I clicked &amp;quot;Reflect on the input file&amp;quot; my table of atoms' coordinate was empty. I followed this &lt;a href=&quot;https://www.youtube.com/watch?v=dNYTLL8PF_4&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorial&lt;/a&gt;. How can I solve this problem?&lt;/p&gt;&#xA;" OwnerUserId="7557" LastEditorUserId="6468" LastEditDate="2023-07-18T07:12:42.417" LastActivityDate="2023-07-18T07:12:42.417" Title="BURAI eliminates atoms when I try to modify the input file" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|" AnswerCount="0" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="11302" PostTypeId="1" AcceptedAnswerId="11347" CreationDate="2023-07-17T20:34:33.620" Score="3" ViewCount="169" Body="&lt;p&gt;I'm interested in understanding how changes in the oxygen-oxygen-oxygen (O-O-O) triplet angular distribution can provide insights into the order parameter.&lt;/p&gt;&#xA;&lt;p&gt;In literature, the tetrahedral order parameter q, an index to describe the similarity of the simulated water structure with the perfect tetrahedral structure would yield a value of 1 for the perfect tetrahedral structure and 0 for the ideal gas&lt;/p&gt;&#xA;&lt;p&gt;My question is how the changes observed in these distributions can provide information about the order parameter of water. I tried to calculate the probability plot of angles for two different frames of the trajectory (first and last frame). Attached below sequentially.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nchwk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nchwk.png&quot; alt=&quot;first frame&quot; /&gt;&lt;/a&gt; &lt;a href=&quot;https://i.stack.imgur.com/wMyJR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wMyJR.png&quot; alt=&quot;last frame&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now, I would like to seek guidance on how to further analyze these changes in the O-O-O triplet angular distribution and extract meaningful insights about the order parameter and how to calculate the q-value.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for your valuable input and suggestions.&lt;/p&gt;&#xA;" OwnerUserId="4219" LastActivityDate="2023-07-23T16:14:19.273" Title="Order Parameter for Water in an MD Trajectory: Understanding Changes in Oxygen-Oxygen-Oxygen Triplet Angular Distributions" Tags="|molecular-dynamics|molecular-modeling|water|disorder|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11303" PostTypeId="2" ParentId="11264" CreationDate="2023-07-17T21:32:49.130" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/jensengroup/propka&quot; rel=&quot;nofollow noreferrer&quot;&gt;Propka&lt;/a&gt; is a standard option used to establish the protonation states of residues in MD. This is a module that can be installed in python. There is thorough &lt;a href=&quot;https://propka.readthedocs.io/en/latest/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; online regarding its use. There two main papers that provide a reference to their methods are: &lt;a href=&quot;https://doi.org/10.1021/ct100578z&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/ct100578z&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/ct200133y&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/ct200133y&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6642" LastEditorUserId="6642" LastEditDate="2023-07-18T03:43:07.780" LastActivityDate="2023-07-18T03:43:07.780" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11304" PostTypeId="2" ParentId="11273" CreationDate="2023-07-18T03:13:52.907" Score="3" Body="&lt;p&gt;The figure that you have provided depicts the spatial distribution of water molecules around the NH&lt;span class=&quot;math-container&quot;&gt;$_4$$^+$&lt;/span&gt; ion. This is generally generated by calculating the 3D probability density of water-O atoms around the NH&lt;span class=&quot;math-container&quot;&gt;$_4$$^+$&lt;/span&gt; ion. The easiest way is to write a script that would calculate this over the trajectory.&lt;/p&gt;&#xA;&lt;p&gt;I do not have a script that can do it, but will provide a general algorithm to do this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;For every frame in trajectory:&#xA;    Center ion to the center of the box&#xA;    Calculate 3D histogram for the water O coordinates for water molecules within a cutoff distance. &#xA;Write this data as a Cube file. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-18T03:13:52.907" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11305" PostTypeId="1" CreationDate="2023-07-18T09:13:33.557" Score="4" ViewCount="105" Body="&lt;p&gt;I'm running a scf Quantum ESPRESSO calculation on a cluster to get the optical properties of my material. I noticed that the output file is stuck in the same line for more than 6 hours even though that the calculation is still running. The calculation  is stuck in those lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;....&#xA;     Dynamical RAM for                qrad:   3.80 MB&#xA;&#xA;     Dynamical RAM for          rho,v,vnew:   0.57 MB&#xA;&#xA;     Dynamical RAM for               rhoin:   0.19 MB&#xA;&#xA;     Dynamical RAM for            rho*nmix:   1.02 MB&#xA;&#xA;     Dynamical RAM for           G-vectors:   0.25 MB&#xA;&#xA;     Dynamical RAM for          h,s,v(r/c):   0.01 MB&#xA;&#xA;     Dynamical RAM for          &amp;lt;psi|beta&amp;gt;:   0.02 MB&#xA;&#xA;     Dynamical RAM for                 psi:   0.20 MB&#xA;     Dynamical RAM for      wfcinit/wfcrot:   0.23 MB&#xA;&#xA;     Estimated static dynamical RAM per process &amp;gt;   3.02 GB&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;       3.03 GB&#xA;&#xA;     Estimated total dynamical RAM &amp;gt;      60.52 GB&#xA;&#xA;     Initial potential from superposition of free atoms&#xA;&#xA;     starting charge   35.99975, renormalised to   36.00000&#xA; --- in v_hubbard ---&#xA;Hubbard energy    0.0000&#xA; -------&#xA;     Number of +U iterations with fixed ns =  0&#xA;     Starting occupations:&#xA; --- enter write_ns ---&#xA;&#xA; --- enter write_ns ---&#xA; LDA+U parameters:&#xA;U( 1)     =  5.20000000&#xA;atom    1   Tr[ns(na)] =  10.00000&#xA;    eigenvalues:&#xA;  1.000  1.000  1.000  1.000  1.000&#xA;    eigenvectors:&#xA;  1.000  0.000  0.000  0.000  0.000&#xA;  0.000  1.000  0.000  0.000  0.000&#xA;  0.000  0.000  1.000  0.000  0.000&#xA;  0.000  0.000  0.000  1.000  0.000&#xA;  0.000  0.000  0.000  0.000  1.000&#xA;    occupations:&#xA;  1.000  0.000  0.000  0.000  0.000&#xA;  0.000  1.000  0.000  0.000  0.000&#xA;  0.000  0.000  1.000  0.000  0.000&#xA;  0.000  0.000  0.000  1.000  0.000&#xA;  0.000  0.000  0.000  0.000  1.000&#xA;N of occupied +U levels =   10.000000&#xA; --- exit write_ns ---&#xA; Atomic wfc used for LDA+U Projector are orthogonalized&#xA;     Starting wfcs are   19 randomized atomic wfcs +   17 random wfcs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm not very good at reading the output files but I think it's maybe because of that: &lt;code&gt;Estimated total dynamical RAM &amp;gt; 60.52 GB&lt;/code&gt; because in my case I used this to launch my calculation:&lt;code&gt;#SBATCH --mem=10G&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does that mean that I should have at least 60.52G RAM in my machine so that the calculation can be done? Or there might be another reason for this issue?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6560" LastEditDate="2023-07-18T15:27:55.160" LastActivityDate="2023-07-18T15:27:55.160" Title="Why my scf calculation with 30*30*30 k-points grid is stuck in the same line for more than 6 hours?" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|optical-properties|" AnswerCount="0" CommentCount="2" ClosedDate="2024-03-22T20:29:25.917" ContentLicense="CC BY-SA 4.0" />
  <row Id="11306" PostTypeId="1" AcceptedAnswerId="11329" CreationDate="2023-07-18T09:34:55.977" Score="3" ViewCount="77" Body="&lt;p&gt;I am trying to understand how to use the data of STO-6G basis from BSE in order to code my own DFT package. I started with a simple DFT code for H2. So the primitive gaussians are of the from : &lt;span class=&quot;math-container&quot;&gt;$$\left( \frac{2\alpha}{\pi} \right)^{\frac{3}{4}} e^{-\alpha x^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Let's take for example Neon in NWChem format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#----------------------------------------------------------------------&#xA;# Basis Set Exchange&#xA;# Version v0.9.1&#xA;# https://www.basissetexchange.org&#xA;#----------------------------------------------------------------------&#xA;#   Basis set: STO-6G&#xA;# Description: STO-6G Minimal Basis (6 functions/AO)&#xA;#        Role: orbital&#xA;#     Version: 1  (Data from Gaussian09)&#xA;#----------------------------------------------------------------------&#xA;&#xA;&#xA;BASIS &amp;quot;ao basis&amp;quot; SPHERICAL PRINT&#xA;#BASIS SET: (12s,6p) -&amp;gt; [2s,1p]&#xA;Ne    S&#xA;      0.2146955475E+04       0.9163596281E-02&#xA;      0.3936419362E+03       0.4936149294E-01&#xA;      0.1101268283E+03       0.1685383049E+00&#xA;      0.3783153777E+02       0.3705627997E+00&#xA;      0.1469109318E+02       0.4164915298E+00&#xA;      0.6050603466E+01       0.1303340841E+00&#xA;Ne    SP&#xA;      0.8550442919E+02      -0.1325278809E-01       0.3759696623E-02&#xA;      0.1692355799E+02      -0.4699171014E-01       0.3767936984E-01&#xA;      0.5259829210E+01      -0.3378537151E-01       0.1738967435E+00&#xA;      0.2023645885E+01       0.2502417861E+00       0.4180364347E+00&#xA;      0.8788707870E+00       0.5951172526E+00       0.4258595477E+00&#xA;      0.4028507849E+00       0.2407061763E+00       0.1017082955E+00&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Are the STO-nG coefficients the same for each of the p-orbitals (&lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt;), d-orbitals, and higher angular momentum? If this is the case how can non-spherical effects be included?&lt;/p&gt;&#xA;&lt;p&gt;Also what is the form of the primitive gaussian in case it must be changed from the Hydrogen/Helium case?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-07-19T07:48:18.770" LastActivityDate="2023-07-20T19:29:03.507" Title="How to exploit STO-nG coefficients from basissetexchange (BSE)?" Tags="|molecular-modeling|basis-sets|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11308" PostTypeId="1" AcceptedAnswerId="11318" CreationDate="2023-07-18T11:25:25.870" Score="4" ViewCount="254" Body="&lt;p&gt;I want to calculate a superconducting critical temperature.&lt;/p&gt;&#xA;&lt;p&gt;I see in papers like this one: &lt;a href=&quot;https://pubs.aip.org/aip/apl/article/106/11/113107/27157/Prediction-of-superconductivity-in-Li-intercalated&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; that they calculate &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; in Quantum Espresso. They use the formula (Eq. 2 in that paper):&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T_c=\frac{\omega_{ln}}{1.2}\exp\left(-\frac{1.04(1+\lambda)}{\lambda-\mu^{*}(1+0.62\lambda)}\right)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.12.905&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.167.331&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; papers, I get that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\lambda=2\int\limits_0^\infty\,d\omega\,\alpha^2F(\omega)/\omega$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\omega_{ln}=\frac{2}{\lambda}\int\limits_0^\infty\,d\omega\,\alpha^2F(\omega)$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{\mu^{*}}=\frac{1}{\mu}+\ln\left(\frac{\omega_{el}}{\omega_{ph}}\right)$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mu=N(0)|V_c|$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$N(0)$&lt;/span&gt; is the electronic density of states at the Fermi surface, and I don't quite understand which value should I take for &lt;span class=&quot;math-container&quot;&gt;$V_c$&lt;/span&gt;. Also, &lt;span class=&quot;math-container&quot;&gt;$\omega_{el}$&lt;/span&gt; is a plasma frequency or a high-frequency peak in &lt;span class=&quot;math-container&quot;&gt;$Im[1/\epsilon(\omega)]$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\epsilon(\omega)$&lt;/span&gt; is the&#xA;dielectric function, and &lt;span class=&quot;math-container&quot;&gt;$\omega_{ph}$&lt;/span&gt; is the high-frequency cutoff in the Eliashberg spectral function &lt;span class=&quot;math-container&quot;&gt;$\alpha^2F(\omega)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;How to calculate this in VASP? Namely, how to calculate the Eliashberg spectral function &lt;span class=&quot;math-container&quot;&gt;$\alpha^2F(\omega)$&lt;/span&gt; as other quantities are calculated from it?&lt;/p&gt;&#xA;&lt;p&gt;Are there any tutorials or papers where these calculations are done in VASP?&lt;/p&gt;&#xA;" OwnerUserId="81" LastEditorUserId="81" LastEditDate="2023-07-19T12:47:07.333" LastActivityDate="2023-07-19T22:37:50.627" Title="How to calculate the Eliashberg spectral function in VASP?" Tags="|density-functional-theory|vasp|reference-request|phonons|superconductivity|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11309" PostTypeId="1" CreationDate="2023-07-18T16:25:29.663" Score="2" ViewCount="63" Body="&lt;p&gt;I am trying to recreate the results from this &lt;a href=&quot;https://doi.org/10.1016/j.surfin.2022.101834&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;. Specifically, the nanowire I am testing is cylindrical with a cross-sectional area of 24 nm2 and a length of 10 nm. I am expecting a thermal conductivity of around 1.9 W/mK, however, I am only getting around 1.0 W/mK. The paper used Müller-Plathe’s formalism.&lt;/p&gt;&#xA;&lt;p&gt;I appropriated the Müller-Plathe sample script (&lt;code&gt;KAPPA/in.mp&lt;/code&gt;). I am not sure if my code is proper.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Settings&#xA;units       metal&#xA;atom_style  full&#xA;&#xA;# Variables&#xA;variable    V           equal vol&#xA;variable    dt          equal 0.0005&#xA;variable    p           equal 200                       # correlations length&#xA;variable    s           equal 10                        # sample interval&#xA;variable    d           equal &lt;span class=&quot;math-container&quot;&gt;$p*$&lt;/span&gt;s                     # dump interval&#xA;variable    seed        equal 190511&#xA;## Conversion      &#xA;variable    kB          equal 1.3806504e-23             # [J/K] Boltzmann&#xA;variable    eV2J        equal 1.6021e-19&#xA;variable    A2m         equal 1.0e-10&#xA;variable    nm2A        equal 10&#xA;variable    ps2s        equal 1.0e-12&#xA;variable    convert     equal &lt;span class=&quot;math-container&quot;&gt;${eV2J}*$&lt;/span&gt;{eV2J}/&lt;span class=&quot;math-container&quot;&gt;${ps2s}/$&lt;/span&gt;{A2m}&#xA;&#xA;# Configuration   &#xA;## NW settings&#xA;variable    area        equal 24                        # [nm]&#xA;variable    nwrad       equal sqrt(&lt;span class=&quot;math-container&quot;&gt;${area}/PI)*$&lt;/span&gt;{nm2A}&#xA;variable    nwlen       equal 10                        # [nm]&#xA;## Ge Ratio: 0.1-0.9&#xA;variable    ratio       equal 0.0&#xA;## Temperature: 100K-1100K&#xA;variable    T           equal 1100&#xA;## Simbox&#xA;variable    simxl       equal &lt;span class=&quot;math-container&quot;&gt;${nwrad}*6                # simbox x length  &#xA;variable    simyl       equal $&lt;/span&gt;{nwrad}*6                # simbox y length  &#xA;variable    simzl       equal &lt;span class=&quot;math-container&quot;&gt;${nwlen}*$&lt;/span&gt;{nm2A}          # simbox z length&#xA;variable    simx1       equal -&lt;span class=&quot;math-container&quot;&gt;${simxl}/2&#xA;variable    simx2       equal  $&lt;/span&gt;{simxl}/2&#xA;variable    simy1       equal -&lt;span class=&quot;math-container&quot;&gt;${simyl}/2&#xA;variable    simy2       equal  $&lt;/span&gt;{simyl}/2&#xA;variable    simz1       equal -&lt;span class=&quot;math-container&quot;&gt;${simzl}/2&#xA;variable    simz2       equal  $&lt;/span&gt;{simzl}/2&#xA;&#xA;# Problem Setup&#xA;dimension       3&#xA;boundary        f f p&#xA;&#xA;lattice         diamond 5.43 &#xA;region          simbox &amp;amp;&#xA;                block &lt;span class=&quot;math-container&quot;&gt;${simx1} $&lt;/span&gt;{simx2} &amp;amp;&#xA;                      &lt;span class=&quot;math-container&quot;&gt;${simy1} $&lt;/span&gt;{simy2} &amp;amp;&#xA;                      &lt;span class=&quot;math-container&quot;&gt;${simz1} $&lt;/span&gt;{simz2} &amp;amp;&#xA;                      units box&#xA;create_box      2 simbox&#xA;&#xA;region          nanowire &amp;amp;&#xA;                cylinder z 0 0 ${nwrad} INF INF &amp;amp;&#xA;                units box&#xA;&#xA;create_atoms    1 region nanowire &#xA;set             region nanowire &amp;amp;&#xA;                type/ratio 2 &lt;span class=&quot;math-container&quot;&gt;${ratio} $&lt;/span&gt;{seed}&#xA;&#xA;mass            1 28.0855                       # Silicon&#xA;mass            2 72.6400                       # Germanium&#xA;&#xA;velocity        all create &lt;span class=&quot;math-container&quot;&gt;$T $&lt;/span&gt;{seed} &amp;amp;&#xA;                mom yes &amp;amp;&#xA;                rot yes &amp;amp;&#xA;                dist gaussian&#xA;&#xA;pair_style      tersoff&#xA;pair_coeff      * * SiCGe.tersoff Si(D) Ge&#xA;&#xA;neighbor        0.3 bin&#xA;neigh_modify    delay 0 every 1&#xA;&#xA;# 1st Equilibriation Run&#xA;timestep        &lt;span class=&quot;math-container&quot;&gt;${dt}&#xA;fix             1 all nvt temp $&lt;/span&gt;T $T 0.5&#xA;thermo          100&#xA;run             100000&#xA;dump            1 all custom 100 ./output/Ge0.0_T1100.lammpstrj id type mass xs ys zs fx fy fz&#xA;&#xA;velocity        all scale $T&#xA;&#xA;unfix           1&#xA;&#xA;# 2nd equilibration run&#xA;compute         ke all ke/atom&#xA;variable        temp atom c_ke/1.5&#xA;&#xA;fix             1 all nve&#xA;&#xA;compute         layers all chunk/atom bin/1d z lower 0.05 units reduced&#xA;fix             2 all ave/chunk 10 100 1000 layers v_temp file profile.mp&#xA;fix             3 all thermal/conductivity 10 z 20&#xA;&#xA;variable        tdiff equal f_2[11][3]-f_2[1][3]&#xA;thermo_style    custom step temp epair etotal f_3 v_tdiff&#xA;thermo_modify   colname f_3 E_delta colname v_tdiff dTemp_step&#xA;&#xA;thermo          1000&#xA;run             100000&#xA;dump            2 all custom 100 ./output/la_Ge0.0_T1100.lammpstrj id type mass xs ys zs fx fy fz&#xA;&#xA;# thermal conductivity calculation&#xA;# reset fix thermal/conductivity to zero energy accumulation&#xA;fix             3 all thermal/conductivity 10 z 20&#xA;&#xA;variable start_time equal time&#xA;variable kappa equal (f_3/(time-${start_time})/(lx*ly)/2.0)*(lz/2.0)/f_ave&#xA;&#xA;fix             ave all ave/time 1 1 1000 v_tdiff ave running&#xA;thermo_style    custom step temp epair etotal f_3 v_tdiff f_ave&#xA;thermo_modify   colname f_3 E_delta colname v_tdiff dTemp_step colname f_ave dTemp&#xA;&#xA;run             100000&#xA;&#xA;print 'Running average thermal conductivity: $(v_kappa:%.2f)'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Are there other settings I can fine-tune (e.g., temperature difference between the cold and hot slabs, number of slabs, thickness of slabs) that might achieve the desirable values?&lt;/p&gt;&#xA;" OwnerUserId="7518" LastEditorUserId="5" LastEditDate="2023-07-19T03:14:35.377" LastActivityDate="2023-07-19T03:14:35.377" Title="Thermal conductivity of cylindrical Si nanowire is lower than expected" Tags="|lammps|reproducing-data-from-papers|lattice-thermal-conductivity|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11311" PostTypeId="1" AcceptedAnswerId="11552" CreationDate="2023-07-19T03:25:10.210" Score="3" ViewCount="152" Body="&lt;p&gt;I am using Pyprocar to plot my band structure. However I cannot change color even modified the 'color' parameter.  I tried to change color of their examples referred to Fe band structure but did not work. Here is my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyprocar&#xA;import os&#xA;pyprocar.bandsplot(code='vasp', dirname = band_dir,outcar='OUTCAR', mode='plain', show=True, atoms=atoms,spins=[0],fermi=-0.1,color='red') &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The figure showed this, band was still blue. I cannot figure out reasons. Hope someone could help me.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/yXCU3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yXCU3.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I now know how to change color and linewidth in plain mode with the help of ChatGPT...&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyprocar&#xA;import os&#xA;ebs_plot= pyprocar.bandsplot(code='vasp', dirname = band_dir,outcar='OUTCAR', mode='plain', show=True, atoms=atoms,spins=[0],fermi=-0.1) &#xA;&#xA;for handle in ebs_plot2.handles:&#xA;    handle[0].set_color('k')&#xA;    handle[0].set_linewidth(0.5)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, when plotting projection band structure in 'parametric' and 'scatter' mode, the added code won't work. Can somebody help ?&lt;/p&gt;&#xA;" OwnerUserId="7083" LastEditorUserId="7083" LastEditDate="2023-07-19T11:23:47.693" LastActivityDate="2023-08-29T11:17:33.567" Title="How to change color of bands in PyProcar?" Tags="|density-functional-theory|vasp|python|band-structure|pyprocar|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11312" PostTypeId="1" CreationDate="2023-07-19T07:43:57.737" Score="0" ViewCount="28" Body="&lt;p&gt;HOW TO CALCULATE ALL PARAMETERS FOR CHARGE DEFECT FORMATION ENERGY USING VASP, Possible workflow for Practical Calculation&#xA;How to draw the plot of Formation energy v Fermi energy like this.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/yUmoE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yUmoE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6896" LastEditorUserId="6896" LastEditDate="2023-07-20T13:21:27.573" LastActivityDate="2023-07-20T13:21:27.573" Title="what is possible flow for charge defect formation energy and how to plot charge defect FE vs fermi energy" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="3" ClosedDate="2023-08-31T07:50:15.060" ContentLicense="CC BY-SA 4.0" />
  <row Id="11314" PostTypeId="1" CreationDate="2023-07-19T13:55:47.493" Score="2" ViewCount="38" Body="&lt;p&gt;I am trying to run the calculation of the DBOC using &lt;strong&gt;CFOUR/MRCC&lt;/strong&gt; interface for a &lt;strong&gt;single atom&lt;/strong&gt;. The calculation runs with no issues without MRCC (i.e. if CC_PROG=MRCC is removed from the ZMAT file below), but fails when MRCC is involved.&lt;/p&gt;&#xA;&lt;p&gt;N2 molecule works both with CFOUR and MRCC/CFOUR, but for a single nitrogen atom I get the following error from CFOUR/MRCC in the &lt;a href=&quot;https://www.mrcc.hu/media/kunena/attachments/2004/out.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;output file&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;@PUTLST-F, Error reading list [ 1,338]             Distribution&#xA;********* requested, but only         0 are available.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am using the precompiled patched version of MRCC (before downloading the MRCC patches the DBOC calculations didn't work at all).&lt;/p&gt;&#xA;&lt;p&gt;ZMAT file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Calculation of diagonal Born-Oppenheimer corrections (DBOC)&#xA;N&#xA;    *CFOUR(DBOC=1&#xA;     MULTIPLICITY=4&#xA;     CALC_LEVEL=CCSD&#xA;     CC_PROG=MRCC&#xA;     SCF_CONV=10&#xA;     LINEQ_CONV=10&#xA;     CC_CONV=10&#xA;     CPHF_CONVER=18&#xA;     LINEQ_MAXCYC=999&#xA;     UNITS=BOHR&#xA;     BASIS=AUG-PVTZ&#xA;     MEM_UNIT=MB&#xA;    MEMORY_SIZE=19990)&#xA;&#xA;&#xA;%masses&#xA;14.00307400443&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="349" LastActivityDate="2023-07-19T15:44:00.540" Title="MRCC/CFOUR interface bug for a single atom calculation?" Tags="|mrcc|cfour|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11315" PostTypeId="2" ParentId="11314" CreationDate="2023-07-19T15:44:00.540" Score="1" Body="&lt;p&gt;The MRCC interface with CFOUR does work on individual atoms, even for DBOC calculations. For example, I did a DBOC calculation at CCSDTQ level for the carbon atom &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/C/DBOC/aug-cc-pCVDZ-NR/CFOUR-MRCC_CCSDTQ.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The input file for that calculation is here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TITLE                                                                           &#xA;C                                                                               &#xA;                                                                                &#xA;*ACES2(CALC=CC(n)                                                               &#xA;EXCITATION=4                                                                    &#xA;INPUT_MRCC=ON                                                                   &#xA;CC_PROG=MRCC                                                                    &#xA;DBOC=1                                                                          &#xA;XFORM_TOL=18                                                                    &#xA;SAVE_INTS=ON                                                                    &#xA;SCF_EXPORDER=6                                                                  &#xA;SCF_EXPSTART=5                                                                  &#xA;#SCF_DAMPING=1000                                                               &#xA;SCF_EXTRAPOLATION=ON                                                            &#xA;SCF_CONV=10                                                                     &#xA;SCF_MAXCYC=9999                                                                 &#xA;CC_CONV=10                                                                      &#xA;CC_MAXCYC=999                                                                   &#xA;T3_EXTRAPOL=ON                                                                  &#xA;REFERENCE=UHF                                                                   &#xA;CHARGE=+0                                                                       &#xA;MULT=3                                                                          &#xA;ABCDTYPE=STANDARD                                                               &#xA;OCCUPATION=2-1-1-0-0-0-0-0/2-0-0-0-0-0-0-0                                      &#xA;MEM=32                                                                          &#xA;MEM_UNIT=GB                                                                     &#xA;BASIS=SPECIAL)                                                                  &#xA;                                                                                &#xA;C:aCVDZ-EMSL                        &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After modifying my input file to match yours more, I arrived at the following file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Calculation of diagonal Born-Oppenheimer corrections (DBOC)&#xA;N&#xA;    *CFOUR(DBOC=1&#xA;     MULT=4&#xA;     INPUT_MRCC=ON     &#xA;     CALC_LEVEL=CCSD&#xA;     CC_PROG=MRCC&#xA;     SCF_CONV=10&#xA;     LINEQ_CONV=10&#xA;     CC_CONV=10&#xA;     CPHF_CONVER=18&#xA;     LINEQ_MAXCYC=999&#xA;     UNITS=BOHR&#xA;     BASIS=AUG-PVTZ&#xA;     MEM_UNIT=MB&#xA;     MEMORY_SIZE=19990)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I didn't specify the mass of the carbon atom (this would suggest that my calculation just used the default mass), but perhaps you can try my input file first (or my modified input file which is closer to yours).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-07-19T15:44:00.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11316" PostTypeId="1" CreationDate="2023-07-19T22:27:14.883" Score="1" ViewCount="35" Body="&lt;p&gt;Methyl Acrylate has linear formula, molecular weight, density, and boiling point are C_4H_6O_2, 0.0861 kg/mol, 950 kg/m³, and 353 K respectively. I want to know the atomic positions for Methyl Acrylate. Does anyone know from where can I get it?&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2023-07-20T06:53:22.407" Title="CIF file for Methyl Acrylate" Tags="|density-functional-theory|vasp|cif|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11317" PostTypeId="2" ParentId="11282" CreationDate="2023-07-19T22:33:47.440" Score="4" Body="&lt;p&gt;In order to determine the time evolution of a Hartree-Fock state, the Time-Dependent Hartree-Fock (TDHF) method is indeed a suitable approach. TDHF is a mean-field method used to study the dynamics of many-body quantum systems, particularly in the context of time-dependent processes.&lt;/p&gt;&#xA;&lt;p&gt;In TDHF, the time evolution of the wave function is approximated by propagating the single-particle orbitals (ϕi) according to the time-dependent Hartree-Fock equations. These equations are derived from the time-dependent Schrödinger equation and can be solved iteratively to obtain the time-dependent wave function.&lt;/p&gt;&#xA;&lt;p&gt;Here's an outline of the derivation for TDHF:&lt;/p&gt;&#xA;&lt;p&gt;Starting with the time-dependent Schrödinger equation for a many-body system:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ i \hbar \partial / \partial t \ | \Psi(t) \rangle = \hat{H} |\Psi (t)\rangle$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Expand the wave function in terms of the time-dependent single-particle orbitals:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ |\Psi(t)\rangle = \sum_{i} C_i(t) |\Phi_i(t)\rangle $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Insert this expansion into the time-dependent Schrödinger equation and project onto each single-particle orbital |ϕk⟩:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ i\hbar \partial / \partial t \  C_k (t) = \sum_i \langle \Phi_k | \hat{H} | \Phi_i \rangle C_i (t) $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Express the Hamiltonian in terms of creation and annihilation operators (second-quantization) and the Fock matrix elements.&lt;/p&gt;&#xA;&lt;p&gt;Assuming that the wave function remains normalized during time evolution, apply the closure relation for single-particle states:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \sum_i C_i^* (t) C_i(t) = 1 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;By solving these TDHF equations, you can determine the time evolution of the coefficients &lt;span class=&quot;math-container&quot;&gt;$C_i(t)$&lt;/span&gt; and hence obtain the time-dependent Hartree-Fock wave function &lt;span class=&quot;math-container&quot;&gt;$|\Psi (t) \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;For a detailed and comprehensive introduction to TDHF, including the derivation and practical implementation, you can refer to the following references:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Time-Dependent Density Functional Theory&amp;quot; by Carsten A. Ullrich (ISBN-13: 978-0199563029)&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Many-Particle Physics&amp;quot; by Gerald D. Mahan (ISBN-13: 978-1475710435)&lt;/p&gt;&#xA;&lt;p&gt;[Collected and summarized]&lt;/p&gt;&#xA;" OwnerUserId="5723" LastEditorUserId="142" LastEditDate="2023-07-26T14:20:46.033" LastActivityDate="2023-07-26T14:20:46.033" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11318" PostTypeId="2" ParentId="11308" CreationDate="2023-07-19T22:37:50.627" Score="1" Body="&lt;p&gt;Calculating the Eliashberg spectral function α^2F(ω) in VASP requires some post-processing steps as VASP itself does not provide direct tools for this specific analysis. The Eliashberg spectral function is typically obtained from electron-phonon coupling calculations, which are not directly supported by VASP.&lt;/p&gt;&#xA;&lt;p&gt;To calculate α^2F(ω) in VASP, you would need to perform the following steps:&lt;/p&gt;&#xA;&lt;p&gt;Perform Electron-Phonon (e-ph) coupling calculation:&#xA;Start by performing an electron-phonon coupling calculation using a separate software package that supports this analysis. For example, Quantum ESPRESSO, ABINIT, or similar packages are commonly used for such calculations. In this step, you calculate the electron-phonon coupling matrix elements and phonon frequencies.&lt;/p&gt;&#xA;&lt;p&gt;Extract relevant data:&#xA;Extract the electron-phonon coupling matrix elements (g_kq), phonon frequencies (ω_q), and the electronic band structure from your e-ph calculation. The electron-phonon coupling matrix elements are responsible for the interaction between electrons and phonons.&lt;/p&gt;&#xA;&lt;p&gt;Determine the Eliashberg function:&#xA;The Eliashberg spectral function α^2F(ω) can be calculated using the following formula:&lt;/p&gt;&#xA;&lt;p&gt;α^2F(ω) = ∑_q ∑_k |g_kq|^2 δ(ω - ω_q)&lt;/p&gt;&#xA;&lt;p&gt;Where:&lt;/p&gt;&#xA;&lt;p&gt;∑_q: Sum over phonon wave vectors in the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;∑_k: Sum over electronic states in the Brillouin zone.&lt;/p&gt;&#xA;&lt;p&gt;g_kq: Electron-phonon coupling matrix element between electronic state k and phonon mode q.&lt;/p&gt;&#xA;&lt;p&gt;ω_q: Phonon frequency of mode q.&lt;/p&gt;&#xA;&lt;p&gt;δ(ω - ω_q): Delta function that takes into account the energy conservation.&lt;/p&gt;&#xA;&lt;p&gt;Perform the sum:&#xA;Implement the summation over phonon wave vectors (q) and electronic states (k) numerically in your preferred programming language or analysis tool.&lt;/p&gt;&#xA;&lt;p&gt;Visualize the Eliashberg spectral function:&#xA;Once you have computed the Eliashberg spectral function α^2F(ω), you can visualize it using plotting tools like Gnuplot, Matplotlib, or any other suitable visualization software.&lt;/p&gt;&#xA;&lt;p&gt;Remember that calculating the Eliashberg spectral function involves advanced computations and might require some familiarity with electronic structure theory and condensed matter physics. Make sure to follow the proper theoretical background and understand the underlying concepts before proceeding with the calculations. Additionally, the exact procedure might vary depending on the specific software packages and approaches you are using for electron-phonon coupling calculations.&lt;/p&gt;&#xA;&lt;p&gt;[Collected and summarized]&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2023-07-19T22:37:50.627" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11320" PostTypeId="2" ParentId="170" CreationDate="2023-07-20T04:39:10.897" Score="2" Body="&lt;p&gt;Recently I have done many research on large systems (500-700 atoms) with vasp, and I have some advice to share, also these advices are very dependent on different system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Geometry Optimizations&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would like to set NSW=100~200 , IBRION = 2 starting at initial stage. Then I will check 'trialstep' in .out which located after every inoic step such like this&#xA;&lt;a href=&quot;https://i.stack.imgur.com/fOKsF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fOKsF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;You can refer to IBRION 'some general comments' part in VASP wiki for more details &lt;a href=&quot;https://www.vasp.at/wiki/index.php/IBRION&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/IBRION&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can accord to this method to adjust POTIM parameter after initial settings every   100 ionic steps. This method greatly shorts optimization time for my system. Hope this could help you.&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-07-20T04:39:10.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11321" PostTypeId="2" ParentId="5035" CreationDate="2023-07-20T04:39:49.557" Score="2" Body="&lt;p&gt;See our paper from 2006 and references therein:&#xA;&lt;a href=&quot;https://doi.org/10.1002/qua.21049&quot; rel=&quot;nofollow noreferrer&quot;&gt;IJQC2006&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;M. Swart and F.M. Bickelhaupt, &amp;quot;Optimization of strong and weak coordinates&amp;quot;, Int. J. Quant. Chem. 2006, 106, 2536-2544&lt;/p&gt;&#xA;&lt;p&gt;In this paper we took Baker's delocalized coordinates, combined it with ideas from Lindh for separation into weak and strong coordinates, and generalized this. These adapted delocalized coordinates have been included in the QUILD program, and showed a major improvement (in terms of geometry optimization/TS-search cycles needed).&lt;/p&gt;&#xA;" OwnerUserId="998" LastEditorUserId="998" LastEditDate="2023-07-21T20:47:26.503" LastActivityDate="2023-07-21T20:47:26.503" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11322" PostTypeId="2" ParentId="1548" CreationDate="2023-07-20T05:01:44.303" Score="3" Body="&lt;p&gt;I agree with Xivi76. One can use this method to determine J. However, a supercell should be used and the two atoms chosen for the four states should not interact with their periodic image. If the choice of supercell is not large enough one could run into problems.&lt;/p&gt;&#xA;&lt;p&gt;Here is the link to the original paper.&#xA;&lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.224429&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.224429&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7304" LastEditorUserId="7304" LastEditDate="2023-08-05T05:16:25.423" LastActivityDate="2023-08-05T05:16:25.423" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11323" PostTypeId="2" ParentId="1548" CreationDate="2023-07-20T06:00:26.173" Score="2" Body="&lt;p&gt;For normal DFT use Noodleman’s broken symmetry approach.&#xA;&lt;a href=&quot;https://doi.org/10.1002/0470862106.ia618&quot; rel=&quot;nofollow noreferrer&quot;&gt;Noodleman&lt;/a&gt;&#xA;This one may be relevant for magnetic systems: &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.99.144418&quot; rel=&quot;nofollow noreferrer&quot;&gt;PRB2019&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Edited:&#xA;in the supporting information (p. 9) of &lt;a href=&quot;http://dx.doi.org/10.1021/jacs.7b10833&quot; rel=&quot;nofollow noreferrer&quot;&gt;JACS 2017, 139, 18448&lt;/a&gt;, Kieber-Emmons and co-workers report how to compute the J value in detail. Here one needs the energy of the triplet (&lt;em&gt;S&lt;/em&gt; = 1), the broken-symmetry solution for &lt;em&gt;S&lt;/em&gt; = 0, and the corresponding expectation values of .&lt;/p&gt;&#xA;" OwnerUserId="998" LastEditorUserId="998" LastEditDate="2023-08-10T07:00:24.327" LastActivityDate="2023-08-10T07:00:24.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11324" PostTypeId="2" ParentId="11316" CreationDate="2023-07-20T06:04:17.517" Score="2" Body="&lt;p&gt;See &lt;a href=&quot;https://www.chemspider.com/Chemical-Structure.7022.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ChemSpider&lt;/a&gt; and click on 3D, which will allow you to get the structure. And it is available within the Cambridge Database within e.g. entry &lt;a href=&quot;https://www.ccdc.cam.ac.uk/structures/Search?Ccdcid=TORTUQ&amp;amp;DatabaseToSearch=Published&quot; rel=&quot;nofollow noreferrer&quot;&gt;TORTUQ&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="998" LastEditorUserId="998" LastEditDate="2023-07-20T06:53:22.407" LastActivityDate="2023-07-20T06:53:22.407" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11326" PostTypeId="1" CreationDate="2023-07-20T09:20:37.663" Score="3" ViewCount="144" Body="&lt;p&gt;I am currently trying to create a CeO2 (100) / CoO (200) interface for a bulk oxide.&#xA;Unlike what I usually see, slabs stacked on the z-axis (&amp;quot;vertically&amp;quot;), I would like to stack the two &amp;quot;horizontally&amp;quot;, in this case along the x-axis, so that both desired split surfaces are exposed to possible adsorption. I show here an image (z-view) of the system generated via the ASE. The slab was generated from .cif files of CoO and CeO2, cleaved to the desired indices and merged.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ENhaq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ENhaq.png&quot; alt=&quot;CeO2(100)/Co(100) horizontally stacked slabs&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Although I have been working with VASP for a few years now, this is the first time I have approached systems of this type. In fact, I soon realised that it is not at all easy, as CoO has a smaller lattice constant than CeO2, so you can clearly see that the structure undergoes strain.&#xA;I thought of tackling the problem by&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;create a zero vacuum cell (emulating bulk) with the slabs to optimise the positions and thus the cell parameters (perhaps a few cycles of calculations)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;at the end, add the vacuum in the z-direction to obtain the real slabs.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Increase precision of the calculations (spin polarization, Hubbard, etc...)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My main concern is the validity of step 1. and how could i overcome it in case it is wrong. Because i am not sure surfaces are meant to be &amp;quot;bulk-like&amp;quot; stacked from the VASP PBC point of view.&lt;/p&gt;&#xA;&lt;p&gt;At this point, is this the right way to proceed or is it a total dead end? Could anyone suggest a different workflow based on their previous experience, perhaps one that overcomes the problems of ion optimisation (always critical...) ? Unfortunately I have found relatively little information about this in the literature.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="7594" LastActivityDate="2023-07-20T11:54:34.673" Title="VASP - suggestion on optimization of interfaced slabs" Tags="|vasp|computational-chemistry|surfaces|metal-oxide|solid-solid-interface|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11328" PostTypeId="2" ParentId="11326" CreationDate="2023-07-20T11:54:34.673" Score="3" Body="&lt;p&gt;Thanks to @ShaunHa's reply, which cleverly allows slabs to be stacked in the z-direction, I created a customised (simplified) add_adsorbate function that can stack slabs in the 'x', 'y' or 'z' direction. Note that all bond lengths and distances for each slab are those for the CIF file used, so no deformation is inserted.&lt;/p&gt;&#xA;&lt;p&gt;Here are the code-snippet and the generated structures.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms, Atom&#xA;import numpy as np&#xA;&#xA;def my_add_adsorbate(slab, adsorbate, height, ax='z'):&#xA;    axes = {&#xA;        'x' : 0,&#xA;        'y' : 1,&#xA;        'z' : 2&#xA;    }&#xA;    indexes = {&#xA;        'x' : (1,3,1), # (y,z, step)&#xA;        'y' : (0,3,2), # (x,z, step)&#xA;        'z' : (0,2,1)  # (x,z, step)&#xA;    }&#xA;&#xA;    i,j,s = indexes[ax]&#xA;    idx = axes[ax]&#xA;&#xA;    pos = np.array([0.0, 0.0])  &#xA;    spos = np.array([0.0, 0.0])  &#xA;&#xA;    cell = slab.get_cell()[i:j:s, i:j:s]&#xA;&#xA;    pos += np.dot(spos, cell)&#xA;    ads = adsorbate&#xA;&#xA;    # Get desired ax&#xA;    a = slab.positions[:, idx]&#xA;&#xA;    # Max value position...&#xA;    a = a.argmax()&#xA;&#xA;    # ...and value+height&#xA;    v = slab.positions[a, idx] + height&#xA;&#xA;    # Move adsorbate into position&#xA;    vector = [0,0,0]&#xA;    vector[idx] = v&#xA;    print(vector)&#xA;    ads.translate(vector)&#xA;&#xA;    # Attach the adsorbate&#xA;    slab.extend(ads)&#xA;&#xA;&#xA;from ase.visualize import view&#xA;&#xA;# Build CeO2&#xA;CeO2 = read('CeO2_mp-1018664_primitive.cif')&#xA;# Build CoO &#xA;CoO = read('CoO_fm3m.cif')&#xA;# Match the two unit cells in the z direction&#xA;ax = 'y'&#xA;axes = {'x' : 0,&#xA;        'y' : 1,&#xA;        'z' : 2}&#xA;&#xA;ax_ = axes[ax]&#xA;&#xA;CeO2.cell[ax_] = CoO.cell[ax_]&#xA;indexes = [1,0,0]&#xA;&#xA;CeO2 = surface(&#xA;    CeO2, &#xA;    indices=indexes, &#xA;    layers=3, #3 &#xA;    periodic=True&#xA;    )&#xA;&#xA;CoO = surface(&#xA;    CoO, &#xA;    indices=indexes, &#xA;    layers=3, #3 &#xA;    periodic=True&#xA;    )&#xA;&#xA;&#xA;fracs = CeO2.get_scaled_positions()&#xA;&#xA;CeO2.cell = CoO.cell&#xA;&#xA;CeO2.positions = fracs @ CoO.cell&#xA;&#xA;# Stack the two structures&#xA;my_add_adsorbate(CeO2, adsorbate=CoO, height=3., ax=ax)&#xA;CeO2.center(vacuum=0, axis=ax_)&#xA;&#xA;view(CeO2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x3Ob4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x3Ob4.png&quot; alt=&quot;z-stacked slabs, x-stacked slabs, z-stacked slabs&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7594" LastActivityDate="2023-07-20T11:54:34.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11329" PostTypeId="2" ParentId="11306" CreationDate="2023-07-20T15:01:24.363" Score="1" Body="&lt;p&gt;My first question is: why write your own package if you already have many open source ones upon which to build?&#xA;NWChem, psi4, pyscf, …&lt;/p&gt;&#xA;&lt;p&gt;Note: Ne does not have d-functions within STO-6G.&lt;/p&gt;&#xA;&lt;p&gt;For the d-orbitals, have a look at the corresponding basis set for Kr, shown below with some comments added. For a clear explanation of what the functions and corresponding orbitals look like, read Szabo/Ostlund or Frank Jensen's &amp;quot;Introduction to computational chemistry&amp;quot;. Or Google &amp;quot;split valence basis sets&amp;quot;, and you will find e.g. David Sherill's &lt;a href=&quot;http://vergil.chemistry.gatech.edu/courses/chem6485/pdf/basis-sets.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;lecture notes&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#----------------------------------------------------------------------&#xA;# Basis Set Exchange&#xA;# Version v0.9.1&#xA;# https://www.basissetexchange.org&#xA;#----------------------------------------------------------------------&#xA;#   Basis set: STO-6G&#xA;# Description: STO-6G Minimal Basis (6 functions/AO)&#xA;#        Role: orbital&#xA;#     Version: 1  (Data from Gaussian09)&#xA;#----------------------------------------------------------------------&#xA;&#xA;&#xA;BASIS &amp;quot;ao basis&amp;quot; SPHERICAL PRINT&#xA;#BASIS SET: (24s,18p,6d) -&amp;gt; [4s,3p,1d]&#xA;#MS: 1s orbitals &#xA;Kr    S&#xA;      0.2885373644E+05       0.9163596281E-02&#xA;      0.5290300991E+04       0.4936149294E-01&#xA;      0.1480035573E+04       0.1685383049E+00&#xA;      0.5084321647E+03       0.3705627997E+00&#xA;      0.1974390878E+03       0.4164915298E+00&#xA;      0.8131631964E+02       0.1303340841E+00&#xA;#MS: 2s and 2p orbitals&#xA;Kr    SP&#xA;      0.2425796448E+04      -0.1325278809E-01       0.3759696623E-02&#xA;      0.4801284244E+03      -0.4699171014E-01       0.3767936984E-01&#xA;      0.1492235564E+03      -0.3378537151E-01       0.1738967435E+00&#xA;      0.5741168085E+02       0.2502417861E+00       0.4180364347E+00&#xA;      0.2493393212E+02       0.5951172526E+00       0.4258595477E+00&#xA;      0.1142904540E+02       0.2407061763E+00       0.1017082955E+00&#xA;#MS: 3s and 3p orbitals&#xA;Kr    SP&#xA;      0.1284965766E+03      -0.9737395526E-02      -0.8104943356E-02&#xA;      0.3700047197E+02      -0.7265876782E-01      -0.1715478915E-01&#xA;      0.1455321200E+02      -0.1716155198E+00       0.7369785762E-01&#xA;      0.6651312517E+01       0.1289776243E+00       0.3965149986E+00&#xA;      0.3310132155E+01       0.7288614510E+00       0.4978084880E+00&#xA;      0.1699958288E+01       0.3013317422E+00       0.1174825823E+00&#xA;#MS: 4s and 4p orbitals&#xA;Kr    SP&#xA;      0.8808666254E+01       0.3775056180E-02      -0.7052075733E-02&#xA;      0.2834325299E+01      -0.5585965266E-01      -0.5259505547E-01&#xA;      0.1211009836E+01      -0.3192946152E+00      -0.3773450392E-01&#xA;      0.6038871793E+00      -0.2764780132E-01       0.3874773403E+00&#xA;      0.3259517997E+00       0.9049199432E+00       0.5791672602E+00&#xA;      0.1812482827E+00       0.3406258162E+00       0.1221817127E+00&#xA;#MS: 3d orbitals &#xA;Kr    D&#xA;      0.1284965766E+03       0.6633434386E-02&#xA;      0.3700047197E+02       0.5958177963E-01&#xA;      0.1455321200E+02       0.2401949582E+00&#xA;      0.6651312517E+01       0.4648114679E+00&#xA;      0.3310132155E+01       0.3434092326E+00&#xA;      0.1699958288E+01       0.5389056980E-01 &#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="998" LastEditorUserId="7" LastEditDate="2023-07-20T19:29:03.507" LastActivityDate="2023-07-20T19:29:03.507" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11330" PostTypeId="2" ParentId="9907" CreationDate="2023-07-21T01:49:23.950" Score="2" Body="&lt;p&gt;Since it has been a month since OP agreed to write an answer without actually writing the answer, I will try answering this.&lt;/p&gt;&#xA;&lt;p&gt;The easiest way is to perform something called Enhanced Sampling simulations, where you sample along a particular collective variable of interest. If OP knows what the initial and final states are, or between which two sections is the targeted interaction occurring, then the geometric distance between those two sections can be used as the CV for the enhanced sampling simulations.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-21T01:49:23.950" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11331" PostTypeId="2" ParentId="11258" CreationDate="2023-07-21T01:56:47.993" Score="2" Body="&lt;h2&gt;Does it really need to be done in Gaussian?&lt;/h2&gt;&#xA;&lt;p&gt;I found &lt;a href=&quot;https://chemistry-europe.onlinelibrary.wiley.com/doi/am-pdf/10.1002/chem.201602949&quot; rel=&quot;nofollow noreferrer&quot;&gt;a paper&lt;/a&gt;(1) titled &amp;quot;Atomic and Ionic Radii of Elements 1-96&amp;quot; where they calculated it for a large fraction of the periodic table:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Abstract: Atomic and cationic radii have been calculated for the first&#xA;96 elements, together with selected anionic radii. The metric adopted&#xA;is the average distance from the nucleus where the electron density&#xA;falls to 0.001 electrons per bohr3, following earlier work by Boyd.&#xA;Our radii are derived using relativistic all-electron density&#xA;functional theory calculations, close to the basis set limit. They&#xA;offer a systematic quantitative measure of the sizes of&#xA;non-interacting atoms, commonly invoked in the rationalization of&#xA;chemical bonding, structure, and different properties. Remarkably, the&#xA;atomic radii as defined in this way correlate well with van der Waals&#xA;radii derived from crystal structures. A rationalization for trends&#xA;and exceptions in those correlations is provided.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To do it, they used the non-empirical hybrid-exchange correlation functional PBE0, together with a very large and uncontracted atomic natural orbital-relativistic correlation consistent(ANO-RCC) basis set and the Douglas–Kroll–Hess second-order scalar relativistic Hamiltonian. Since I dropped out of my master degree back in the pandemic I don't have access to a Gaussian anymore, but I posted here previously &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9528/243&quot;&gt;a question&lt;/a&gt; regarding volumes of surfaces with uniform electronic density with some examples. Now I adapted the examples to try reproduce these calculations of Rahm et al., at least for Li you are interested in, and also for the next three elements in the alkali metal group, Na, K and Rb.&lt;/p&gt;&#xA;&lt;p&gt;My attempt was done using &lt;a href=&quot;https://nwchemgit.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;NWChem&lt;/a&gt;(2), a major &lt;a href=&quot;https://wires.onlinelibrary.wiley.com/doi/full/10.1002/wcms.1610&quot; rel=&quot;nofollow noreferrer&quot;&gt;free software computational chemistry package&lt;/a&gt;(3) available in the repositories from many linux distributions. The particular version I used was the one currently available from Fedora 38 repositories:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[user@fedora ~]&lt;span class=&quot;math-container&quot;&gt;$ dnf list installed | grep 'nwchem'&#xA;nwchem.x86_64                                        7.0.2-12.fc38                       @fedora                &#xA;nwchem-common.noarch                                 7.0.2-12.fc38                       @fedora                &#xA;nwchem-openmpi.x86_64                                7.0.2-12.fc38                       @fedora                &#xA;[user@fedora ~]$&lt;/span&gt; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I created input files for single point energy calculations, using PBE0 and ANO-RCC, where each ion is centered at x=0, y=0, z=0 coordinates, as shown below. The largest value for radius calculated in the paper we are trying reproduce is a little under 3Å, so the input files also direct NWChem to output density cubes measuring 6Åx6Åx6Å, that should be enough to avoid any part of the volume with electronic density above 0.001 electrons per bohr³ to be left outside the cube. The grid spacings were also chosen so our voxel volume (21.4μÅ³) is close to the one used in the paper (18.5μÅ³):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[user@fedora ionic_radii2]$ more *.nw | cat&#xA;::::::::::::::&#xA;input_lithium.nw&#xA;::::::::::::::&#xA;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/ANO-RCC&amp;quot;&#xA;charge 1&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;Li      0.000000    0.000000    0.000000&#xA;end&#xA;&#xA;basis&#xA;  Li library ANO-RCC rel&#xA;end&#xA;&#xA;relativistic&#xA;  douglas-kroll&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE lithium&#xA; LimitXYZ&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; spin total&#xA; gaussian&#xA; output lithium_density.cube&#xA;end&#xA;&#xA;task dplot&#xA;::::::::::::::&#xA;input.nw&#xA;::::::::::::::&#xA;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/aug-pcS-1/pcS-0&amp;quot;&#xA;charge 0&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;C      0.913139    0.913139    0.000000&#xA;H      0.676070    1.981751    0.000000&#xA;C      0.000000    0.000000    0.780217&#xA;C      0.000000    0.000000   -0.780217&#xA;H      1.378212   -1.576370    0.000000&#xA;C      0.334232   -1.247371    0.000000&#xA;H      1.981751    0.676070    0.000000&#xA;C     -1.247371    0.334232    0.000000&#xA;H     -0.405381   -2.054282    0.000000&#xA;H     -2.054282   -0.405381    0.000000&#xA;H     -1.576370    1.378212    0.000000&#xA;end&#xA;&#xA;basis&#xA;  H library pcS-0&#xA;  C library aug-pcS-1&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE propellane&#xA; LimitXYZ&#xA; -4.0 4.0 10&#xA; -4.0 4.0 10&#xA; -2.0 2.0 10&#xA; spin total&#xA; gaussian&#xA; output propel_density.cube&#xA;end&#xA;&#xA;task dplot::::::::::::::&#xA;input_potassium.nw&#xA;::::::::::::::&#xA;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/ANO-RCC&amp;quot;&#xA;charge 1&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;K      0.000000    0.000000    0.000000&#xA;end&#xA;&#xA;basis&#xA;  K library ANO-RCC rel&#xA;end&#xA;&#xA;relativistic&#xA;  douglas-kroll&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE Potassium&#xA; LimitXYZ&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; spin total&#xA; gaussian&#xA; output potassium_density.cube&#xA;end&#xA;&#xA;task dplot&#xA;::::::::::::::&#xA;input_rubidium.nw&#xA;::::::::::::::&#xA;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/ANO-RCC&amp;quot;&#xA;charge 1&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;Rb      0.000000    0.000000    0.000000&#xA;end&#xA;&#xA;basis&#xA;  Rb library ANO-RCC rel&#xA;end&#xA;&#xA;relativistic&#xA;  douglas-kroll&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE Rubidium&#xA; LimitXYZ&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; spin total&#xA; gaussian&#xA; output rubidium_density.cube&#xA;end&#xA;&#xA;task dplot&#xA;::::::::::::::&#xA;input_sodium.nw&#xA;::::::::::::::&#xA;echo&#xA;&#xA;start molecule&#xA;&#xA;title &amp;quot;Single Point | pbe0/ANO-RCC&amp;quot;&#xA;charge 1&#xA;&#xA;memory total 2 gb&#xA;&#xA;geometry units angstroms print xyz autosym&#xA;Na      0.000000    0.000000    0.000000&#xA;end&#xA;&#xA;basis&#xA;  Na library ANO-RCC rel&#xA;end&#xA;&#xA;relativistic&#xA;  douglas-kroll&#xA;end&#xA;&#xA;dft&#xA;  xc pbe0&#xA;  mult 1&#xA;end&#xA;&#xA;task dft energy&#xA;&#xA;dplot&#xA; TITLE Sodium&#xA; LimitXYZ&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; -3.0 3.0 216&#xA; spin total&#xA; gaussian&#xA; output sodium_density.cube&#xA;end&#xA;&#xA;task dplot&#xA;[user@fedora ionic_radii2]$ &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/susilehtola/fosschemistry/tree/master/nwchem&quot; rel=&quot;nofollow noreferrer&quot;&gt;This page&lt;/a&gt; has instructions on how to install and run NWChem under Fedora. To install it there, you can run this command in the terminal:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dnf install nwchem-openmpi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Once installed, I did a parallel run on each input, using 8 threads on a AMD Ryzen 7 1700 machine, as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;module load mpi/openmpi&#xA;mpirun -np 8 nwchem_openmpi input_lithium.nw &amp;gt; output_Li.out&#xA;mpirun -np 8 nwchem_openmpi input_sodium.nw &amp;gt; output_Na.out&#xA;mpirun -np 8 nwchem_openmpi input_potassium.nw &amp;gt; output_K.out&#xA;mpirun -np 8 nwchem_openmpi input_rubidium.nw &amp;gt; output_Rb.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Once finished, I checked the outputs produced no error and the cube files were properly recorded. The runtimes are also shown, by printing the last line of each output file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[user@fedora ionic_radii2]&lt;span class=&quot;math-container&quot;&gt;$ grep -i 'error' *.out&#xA;[user@fedora ionic_radii2]$&lt;/span&gt; tail -n 1 *.out&#xA;==&amp;gt; output_K.out &amp;lt;==&#xA; Total times  cpu:     2009.8s     wall:     2116.0s&#xA;&#xA;==&amp;gt; output_Li.out &amp;lt;==&#xA; Total times  cpu:       49.0s     wall:      102.6s&#xA;&#xA;==&amp;gt; output_Na.out &amp;lt;==&#xA; Total times  cpu:      394.4s     wall:      474.6s&#xA;&#xA;==&amp;gt; output_Rb.out &amp;lt;==&#xA; Total times  cpu:    11640.9s     wall:    11949.9s&#xA;[user@fedora ionic_radii2]&lt;span class=&quot;math-container&quot;&gt;$ ls -l -s *.cube&#xA;131428 -rw-r--r--. 1 user user 134580624 jul 16 12:09 lithium_density.cube&#xA;131428 -rw-r--r--. 1 user user 134580626 jul 16 13:42 potassium_density.cube&#xA;131428 -rw-r--r--. 1 user user 134580625 jul 16 17:02 rubidium_density.cube&#xA;131428 -rw-r--r--. 1 user user 134580623 jul 16 13:04 sodium_density.cube&#xA;[user@fedora ionic_radii2]$&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The timings show computational cost scales quickly with the size of the system. While the calculation for Li+ takes a bit over 100s wall time, the one for Rb+ takes over 3h. My initial idea was to try reproduce the results for all the alkali metals, but when I saw how quick processing time increased I decided to stop at rubidium.&lt;/p&gt;&#xA;&lt;p&gt;Now the remaining problem is to do volume integration on the electron densities data present in the cube files. In the original study they used the partitioning  method decribed in &lt;a href=&quot;http://henkelmanlab.org/code/bader/download/tang09_084204.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;(4). I sticked to the less sophisticated method I used in my past question, of just counting points above the given threshold of 0.001 electrons per bohr³, and then calculating the ion volume as a ratio of the box volume. In the original study, that covers 96 elements, they raise the issue of most of them except those in groups 1,2 and 18 have non-spherical grids, what complicates estimating average radii. But as all elements we are dealing with are from group 1, we can estimate the radii from the respective volumes by just assuming them spherical. The following Python 3 code implements it (must be saved to a .py file and run in the same folder the cube files are located):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from math import pi&#xA;from os import listdir&#xA;import re&#xA;&#xA;def main():&#xA;    cubes = [file for file in listdir() if 'density.cube' in file]&#xA;    for file in cubes:&#xA;        with open(file, 'r') as f:&#xA;            text = f.read()&#xA;&#xA;        ##Matches data in format the cube file uses to store&#xA;        ##density values, like 0.77410E-07 or 0.38588E+01.&#xA;        p = re.compile(r&amp;quot;0\.\d{5}E[-+]\d{2}&amp;quot;)&#xA;        &#xA;        ## From the LimitXYZ section in the input files. If you change the cube volume, this must be updated.&#xA;        cube_volume = 6*6*6&#xA;        isosurface_threshold = 0.001&#xA;&#xA;        data = p.findall(text)&#xA;        numeric_data = [float(value) for value in data]&#xA;        fraction_inside = len([density&#xA;                               for density in numeric_data&#xA;                               if density &amp;gt;= isosurface_threshold]) / len(numeric_data)&#xA;&#xA;        bound_volume = cube_volume * fraction_inside&#xA;        ## From the sphere volume formula.&#xA;        spheric_radius = pow((3*bound_volume)/(4*pi), 1/3)&#xA;        print('For',&#xA;              file,&#xA;              'the calculated average radius is',&#xA;              round(spheric_radius, 2),&#xA;              'angstroms')&#xA;&#xA;main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It then outputs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Python 3.9.16 (15ea147a6c65, May 30 2023, 13:28:11)&#xA;[PyPy 7.3.11 with GCC 13.1.1 20230511 (Red Hat 13.1.1-2)] on linux&#xA;Type &amp;quot;help&amp;quot;, &amp;quot;copyright&amp;quot;, &amp;quot;credits&amp;quot; or &amp;quot;license()&amp;quot; for more information.&#xA;&amp;gt;&amp;gt;&amp;gt; &#xA;===== RESTART: /home/user/Downloads/OneDrive_1_20-07-2023/volume_measure.py ====&#xA;For lithium_density.cube the calculated average radius is 0.97 angstroms&#xA;For potassium_density.cube the calculated average radius is 1.74 angstroms&#xA;For rubidium_density.cube the calculated average radius is 1.91 angstroms&#xA;For sodium_density.cube the calculated average radius is 1.32 angstroms&#xA;&amp;gt;&amp;gt;&amp;gt; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The results I got were very close to those in the original work:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Ion&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Results from Rahm et al. (Å)&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;My results (Å)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Li+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.98&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.97&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.33&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.32&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.75&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.74&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.91&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.91&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;On how these results compare with values derived from empirical data, they don't discuss the case for monopositive cations as in depth as is done with the neutral atoms. For the neutral atoms, they plot the difference between their calculated radii against crystallographic radii, as shown bellow. On average their radii are smaller by 0.01 Å, and the standard deviation corresponds to 0.211Å, with most alkali metals acting as outliers:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/x7zhV.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/x7zhV.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The determination of radii also depend on other factors, like coordination numbers. Regarding the ionic species, bellow I put some values compiled by &lt;a href=&quot;https://d1wqtxts1xzle7.cloudfront.net/45916289/Shannon-1976-Acta_Crystallographica-libre.pdf?1464106751=&amp;amp;response-content-disposition=inline%3B%20filename%3DRevised_Effective_Ionic_Radii_and_System.pdf&amp;amp;Expires=1689891622&amp;amp;Signature=JehoS4tF-LSiCTRLjKXmM-MMVSKFXbXAX9da3BMK9iyw45PQhDwVTaIQIXcCQCdKr3AjzgGyGFRwP4vAQ6d7IVgeZCAeUbQRd5OKdV0rMVrI2lwIM9jxCILgH2x4y00AqvNnjc1RY4bfkRrlBvOH7UpMilI9cIpPs-SfFQ2dwNWiWU1tqp9janxwZAiKeljaBSVxLaDnLZr9V8NOSEAZXiFsgf-RkRU3mqkX0iTO1%7EztAkERxWc8zDXa0yK2iGbS48VUM8FgH1SblxVKLnGYolBDQHEoDbHZg1y6wUvnZCk56pNU9e0U5q81pe7Mu%7EMxGHXUEnotWC96qQIEijMmFg__&amp;amp;Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA&quot; rel=&quot;nofollow noreferrer&quot;&gt;Shannon&lt;/a&gt;(5) from empirical data, for comparison:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;Ion&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;coordination number (CN)&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;crystal radius (CR)&lt;/th&gt;&#xA;&lt;th style=&quot;text-align: center;&quot;&gt;effective ionic radius (IR)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Li+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;IV&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.730&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.590&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Li+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VI&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.90&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.76&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;IV&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.13&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;0.99&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;V&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.14&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.00&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VI&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.16&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.02&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.26&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.12&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VIII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.32&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.18&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Na+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;XII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.53&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.39&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;IV&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.51&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.37&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VI&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.52&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.38&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.60&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.46&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VIII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.65&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.51&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;IX&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.69&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.55&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;X&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.73&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.59&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;K+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;XII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.78&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.64&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VI&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.66&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.52&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.70&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.56&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;VIII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.75&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.61&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;X&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.80&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.66&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;XI&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.83&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.69&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;XII&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.86&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.72&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;Rb+&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;XIV&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.97&lt;/td&gt;&#xA;&lt;td style=&quot;text-align: center;&quot;&gt;1.83&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;References:&lt;/p&gt;&#xA;&lt;p&gt;(1). Rahm, Martin, et al. “Atomic and Ionic Radii of Elements 1 –96.” Chemistry – A European Journal, vol. 22, no. 41, Oct. 2016, pp. 14625–32. DOI.org (Crossref), &lt;a href=&quot;https://doi.org/10.1002/chem.201602949&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1002/chem.201602949&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(2). Aprà, E., et al. “NWChem: Past, Present, and Future.” The Journal of Chemical Physics, vol. 152, no. 18, May 2020, p. 184102. DOI.org (Crossref), &lt;a href=&quot;https://doi.org/10.1063/5.0004997&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/5.0004997&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(3). Lehtola, Susi, and Antti J. Karttunen. “Free and Open Source Software for Computational Chemistry Education.” WIREs Computational Molecular Science, vol. 12, no. 5, Sept. 2022. DOI.org (Crossref), &lt;a href=&quot;https://doi.org/10.1002/wcms.1610&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1002/wcms.1610&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(4). Tang, W., et al. “A Grid-Based Bader Analysis Algorithm without Lattice Bias.” Journal of Physics: Condensed Matter, vol. 21, no. 8, Feb. 2009, p. 084204. DOI.org (Crossref), &lt;a href=&quot;https://doi.org/10.1088/0953-8984/21/8/084204&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1088/0953-8984/21/8/084204&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;(5). Shannon, R. D. “Revised Effective Ionic Radii and Systematic Studies of Interatomic Distances in Halides and Chalcogenides.” Acta Crystallographica Section A: Crystal Physics, Diffraction, Theoretical and General Crystallography, vol. 32, no. 5, Sept. 1976, pp. 751–67. scripts.iucr.org, &lt;a href=&quot;https://doi.org/10.1107/S0567739476001551&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1107/S0567739476001551&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="243" LastActivityDate="2023-07-21T01:56:47.993" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11332" PostTypeId="1" CreationDate="2023-07-21T07:34:10.457" Score="6" ViewCount="48" Body="&lt;p&gt;Recently, I've come across discussions about the differences between fundamental (or electronic) bandgaps and optical bandgaps, with the two quantities differing mainly by the electron-hole binding energy (ref. this ResearchGate &lt;a href=&quot;https://www.researchgate.net/post/What_is_the_basic_difference_between_optical_band_gap_and_electrical_band_gap&quot; rel=&quot;noreferrer&quot;&gt;post&lt;/a&gt; and this Physics Stack Exchange &lt;a href=&quot;https://physics.stackexchange.com/questions/197940/why-the-optical-gap-is-not-identical-to-the-charge-gap#:%7E:text=The%20optical%20gap%20is%20generally,related%20to%20the%20binding%20energy.&quot;&gt;post&lt;/a&gt;). A user made a comment in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9684/question-on-generalised-kohn-sham-band-gap/9686#9686&quot;&gt;post&lt;/a&gt; that &amp;quot;&lt;em&gt;whether you are interested in the optical or fundamental gap, the KS DFT band gap should not be rigorously interpreted as giving either of those.&lt;/em&gt;&amp;quot; Working with 2D materials where experimental bandgaps of monolayers are scarce, I often see DFT papers benchmark the calculated bandgaps with optical gaps (much like the ones described in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10061/optical-band-gap-determination-from-absorption-coeffecient-using-dft&quot;&gt;post&lt;/a&gt;). This leads to my question if there's a rule-of-thumb for how we benchmark DFT obtained gaps against types of experimental gaps (with considerations of balancing rigor and pragmatism)? In the same vein, how exactly should we think about DFT obtained gaps (i.e. conduction band minima minus valence band maxima from the bandstructure of an auxiliary noninteracting Kohn-Sham system) with respect to the bandgaps from experiments?&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-07-21T07:34:10.457" Title="Benchmarking DFT vs Experimental Gaps - Confusion over Fundamental and Optical Gaps" Tags="|density-functional-theory|electronic-structure|optical-properties|bandgap|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11333" PostTypeId="2" ParentId="11165" CreationDate="2023-07-21T09:23:29.007" Score="1" Body="&lt;p&gt;You should take into account that for this type of square planar complex the set of 5 &amp;quot;d&amp;quot; orbilals of the iron atom are the ones that must be considered for the calculation. Usually, depending on the type of ligands (weak field or strong field) you can have a different orbital degeneracy for the &amp;quot;eg&amp;quot; and &amp;quot;t2g&amp;quot; orbitals, which are the energy levels that must be considered for the calculation of the field separation in a square planar complex (SP).&#xA;Note that I have used the quotes for the label of the orbitals since they are the nomenclature that results from an octahedral complex from which 2 ligands of the z axis have been removed, the nomenclature for SP complexes does not follow these labels (e.g. they can be a, e, t2)&#xA;The arrangement of these levels results in different configurations depending on the type of ligand and worsens a bit when there is metal-ligand hybridization (more covalent than ionic bonds). Example, array 1-2-2 , that is, the highest energy level &amp;quot;1&amp;quot;, two degenerate levels &amp;quot;2&amp;quot; lowest in energy and &amp;quot;2&amp;quot; last two degenerate levels lowest in energy. In the literature there are many examples with 2-1-2 and 2-2-1 configurations as well. Your example has probably already been calculated. &amp;quot;Usually&amp;quot; the orbit that alone (1) is the dz2 and is not involved in the calculation of the ligand field separation delta.&#xA;Finally, identify your &amp;quot;d&amp;quot; orbitals with a calculation of DOS in QE. Then order them in decreasing energy, look for the degenerate orbitals (same energy) and go to the formulas to make the calculation that you can find in the literature.&#xA;Note: maybe someone has already developed a code that reads the output of QE and responds quickly, but be careful, check the occupancies of the orbitals, it is an extremely important theoretical aspect that you may need to consider based on the theory of LCAOs to ponder the energies of the orbitals.&lt;/p&gt;&#xA;" OwnerUserId="7516" LastActivityDate="2023-07-21T09:23:29.007" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11334" PostTypeId="1" AcceptedAnswerId="11345" CreationDate="2023-07-21T12:06:19.533" Score="2" ViewCount="96" Body="&lt;p&gt;I'm trying to optimize a structure that contains Pd atom with the gen function on gaussian16&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    %chk=pd3cgen.chk&#xA;    # opt freq b3lyp/gen pseudo=read scrf=(solvent=ch2cl2,read,pcm)&#xA;&#xA;        Zmatrix coordinates&#xA;               .....&#xA;&#xA;pd 0&#xA; LANL2DZ&#xA; ****&#xA; S 0&#xA; 6-31G(d)&#xA; ****&#xA; O 0&#xA; 6-31G(d)&#xA; ****&#xA; Br 0&#xA; 6-31G(d)&#xA; ****&#xA; C 0&#xA; 6-31G(d)&#xA; ****&#xA; H 0&#xA; 6-31G(d)&#xA; ****&#xA; N 0&#xA; 6-31G(d)&#xA; ****&#xA; Cl 0&#xA; 6-31G(d)&#xA; ****&#xA; blank space&#xA;  radii=uaks&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have done before the calculation with only lanl2dz alone it worked perfectly but when I used a mixing basis set(this case) I got this error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Maximum number of bonds 12 exceeded for atom  13.&#xA; Error termination via Lnk1e &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5563" LastActivityDate="2023-07-22T23:08:43.593" Title="using the gen function in gaussian" Tags="|density-functional-theory|gaussian|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11335" PostTypeId="1" AcceptedAnswerId="11379" CreationDate="2023-07-21T12:15:48.660" Score="4" ViewCount="104" Body="&lt;p&gt;I try to optimize very simple systems - hexa aqua Cu(II) and hexa aqua Fe(III) - in Gaussian 16. The inputs are provided in the end of the post. Unfortunately, the geometry optimization never finishes as the water molecules keeps oscillating around the metal center. What to do?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Cu_II.inp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt freq M05/genecp scrf=smd&#xA;&#xA;Copper&#xA;&#xA;2 2&#xA; Cu                -1.28477910    0.71194762    0.00000000&#xA; O                  0.54522090    0.71194762    0.00000000&#xA; H                  0.86522090   -0.16280021    0.23241394&#xA; O                 -1.28477910    2.54194762    0.00000000&#xA; H                 -0.63246994    2.86194762   -0.62744941&#xA; O                 -1.28477910    0.71194762    1.83000000&#xA; H                 -2.17186239    0.53227224    2.15000000&#xA; O                 -3.11477910    0.71194762    0.00000000&#xA; H                 -3.43477910    0.49890795   -0.87966704&#xA; O                 -1.28477910   -1.11805238    0.00000000&#xA; H                 -1.68807007   -1.43805238   -0.81028168&#xA; O                 -1.28477910    0.71194762   -1.83000000&#xA; H                 -0.68938242    1.29220858   -2.31000000&#xA; H                 -0.99684089    1.57002197    2.15000000&#xA; H                  0.86522090    0.94804515   -0.87376081&#xA; H                 -1.78485813   -1.43805238    0.75440106&#xA; H                 -3.43477910    1.58028145    0.25533576&#xA; H                 -2.15432081    2.86194762   -0.25119160&#xA; H                 -1.88017579    0.13168665   -2.31000000&#xA;&#xA;H O 0&#xA;6-311+G(d,p)&#xA;****&#xA;Cu 0&#xA;SDD&#xA;****&#xA;&#xA;Cu 0&#xA;SDD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;Fe_III.inp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt freq M05/genecp scrf=smd&#xA;&#xA;Iron&#xA;&#xA;3 6&#xA; Fe                -1.71203729   -0.44477496    0.49027634&#xA; O                 -1.71203729    1.38522504    0.49027634&#xA; H                 -1.51209094    1.70522504   -0.39245888&#xA; O                 -1.71203729   -0.44477496   -1.33972366&#xA; H                 -2.19853442   -1.20800530   -1.65972366&#xA; O                  0.11796271   -0.44477496    0.49027634&#xA; H                  0.43796271   -1.31171025    0.75032096&#xA; O                 -1.71203729   -0.44477496    2.32027634&#xA; H                 -2.00815096   -1.30006246    2.64027634&#xA; O                 -1.71203729   -2.27477496    0.49027634&#xA; H                 -2.49501382   -2.59477496    0.03624136&#xA; O                 -3.54203729   -0.44477496    0.49027634&#xA; H                 -3.86203729    0.46013048    0.50888105&#xA; H                 -2.57648159    1.70522504    0.75848532&#xA; H                 -2.12976559    0.35815907   -1.65972366&#xA; H                  0.43796271   -0.23651257   -0.39053396&#xA; H                 -0.82327976   -0.27357317    2.64027634&#xA; H                 -0.92734321   -2.59477496    0.03921626&#xA; H                 -3.86203729   -0.91333984    1.26464509&#xA;&#xA;H O 0&#xA;6-311+G(d,p)&#xA;****&#xA;Fe 0&#xA;SDD&#xA;****&#xA;&#xA;Fe 0&#xA;SDD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-07-26T13:18:48.583" Title="Cannot optimize hexa aqua Cu(II) and Fe(III)" Tags="|density-functional-theory|computational-chemistry|molecular-modeling|gaussian|geometry-optimization|" AnswerCount="2" CommentCount="15" ContentLicense="CC BY-SA 4.0" />
  <row Id="11336" PostTypeId="1" AcceptedAnswerId="11343" CreationDate="2023-07-21T14:10:33.043" Score="9" ViewCount="930" Body="&lt;p&gt;I am performing an SCF Quantum ESPRESSO calculation on an HPC system, but it is taking significantly longer than usual. When I inspect the output file, I notice that it is stuck at a specific line, yet the calculation appears to be still running in the background.&lt;/p&gt;&#xA;&lt;p&gt;Interestingly, when I ran the exact same calculation on my laptop using just 2 cores, it completed within just 1 minute. However, when I tested it on the HPC using both 10 cores then 2 cores, the problem persisted regardless of the number of cores utilized.&lt;/p&gt;&#xA;&lt;p&gt;Could someone please explain to me the possible reasons for this difference in calculation time between the HPC system and my laptop?&lt;/p&gt;&#xA;&lt;p&gt;PS:&#xA;My input contains &lt;code&gt;nosym=.true.&lt;/code&gt; and &lt;code&gt;noinv=.true.&lt;/code&gt; in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; block. However, when I remove these two lines from the input, the calculation ran smoothly without any issues on the HPC.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The last few lines in case of HPC&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Estimated static dynamical RAM per process &amp;gt;      30.73 MB&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;      36.84 MB&#xA;&#xA;     Estimated total dynamical RAM &amp;gt;     147.34 MB&#xA;&#xA;     Initial potential from superposition of free atoms&#xA;&#xA;     starting charge   35.99975, renormalised to   36.00000&#xA;     Starting wfcs are   19 randomized atomic wfcs +    1 random wfcs&#xA;&#xA;     total cpu time spent up to now is      110.7 secs&#xA;&#xA;     Self-consistent Calculation&#xA;&#xA;     iteration #  1     ecut=    70.00 Ry     beta= 0.70&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;           252 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;         22597 MiB available memory on the node where the printing process lives&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;The lines in case of laptop&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Estimated static dynamical RAM per process &amp;gt;      57.66 MB&#xA;&#xA;     Estimated max dynamical RAM per process &amp;gt;      69.90 MB&#xA;&#xA;     Estimated total dynamical RAM &amp;gt;     139.80 MB&#xA;&#xA;     Initial potential from superposition of free atoms&#xA;&#xA;     starting charge      35.9998, renormalised to      36.0000&#xA;     Starting wfcs are   19 randomized atomic wfcs +    1 random wfcs&#xA;&#xA;     total cpu time spent up to now is        2.4 secs&#xA;&#xA;     Self-consistent Calculation&#xA;&#xA;     iteration #  1     ecut=    70.00 Ry     beta= 0.70&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            79 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;           832 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  1.00E-02,  avg # of iterations =  3.7&#xA;&#xA;     Threshold (ethr) on eigenvalues was too large:&#xA;     Diagonalizing with lowered threshold&#xA;&#xA;     Davidson diagonalization with overlap&#xA;&#xA;---- Real-time Memory Report at c_bands before calling an iterative solver&#xA;            84 MiB given to the printing process from OS&#xA;             0 MiB allocation reported by mallinfo(arena+hblkhd)&#xA;           825 MiB available memory on the node where the printing process lives&#xA;------------------&#xA;     ethr =  7.58E-04,  avg # of iterations =  1.0&#xA;&#xA;     total cpu time spent up to now is       12.1 secs&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-07-24T12:13:30.263" LastActivityDate="2023-07-25T09:47:24.973" Title="What factors could cause a calculation to run successfully on a laptop but encounter issues on an HPC system?" Tags="|density-functional-theory|quantum-espresso|high-performance-computing|" AnswerCount="2" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11337" PostTypeId="2" ParentId="11336" CreationDate="2023-07-21T14:24:22.037" Score="7" Body="&lt;p&gt;Almost all codes are written to take advantage of symmetry that is available in the system, to reduce the number of calculations that needs to be performed. If you explicitly say that symmetry must not be considered, it will take more time since now the code is stuck doing the calculations which would have otherwise been generated by symmetry.&lt;/p&gt;&#xA;&lt;p&gt;When you are doing calculations on a cluster with multiple nodes, there is an overhead for splitting the jobs into chunks, collecting the data back to master and related steps. In your case, this overhead is significantly larger than the actual time required to do the calculations on a single node.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-07-21T14:29:34.920" LastActivityDate="2023-07-21T14:29:34.920" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11338" PostTypeId="1" CreationDate="2023-07-21T17:23:12.840" Score="3" ViewCount="312" Body="&lt;p&gt;I am aware that one can compute absorption coefficient (&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;) from the dielectric function with the equation &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$(4*pi*k$&lt;/span&gt;)/&lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;  … (1)&lt;/p&gt;&#xA;&lt;p&gt;Or from the equation &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; = k*&lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;  … (2)&lt;/p&gt;&#xA;&lt;p&gt;How do I obtain the k and &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; values so that I can calculate &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;?&#xA;I am using the Quantum espresso code&lt;/p&gt;&#xA;" OwnerUserId="7560" LastEditorUserId="7560" LastEditDate="2023-07-22T07:03:31.933" LastActivityDate="2023-08-29T12:48:40.597" Title="Absorption coefficient from dielectric function" Tags="|density-functional-theory|optical-properties|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11340" PostTypeId="2" ParentId="11335" CreationDate="2023-07-21T21:08:49.597" Score="2" Body="&lt;p&gt;For &lt;a href=&quot;http://dx.doi.org/10.1021/ct800277a&quot; rel=&quot;nofollow noreferrer&quot;&gt;my paper from 2008&lt;/a&gt; I started from the coordinates &lt;a href=&quot;https://doi.org/10.1063/1.2353829&quot; rel=&quot;nofollow noreferrer&quot;&gt;by Pierloot and co-workers&lt;/a&gt;. They used C(i) symmetry for their CASPT2 study of Fe(II)(H2O)6, which you might do as well as a starting point.&lt;/p&gt;&#xA;&lt;p&gt;Second, because you're using a metagga-hybrid functional you will need to use at least an UltraFine grid (or probably better). In particular, I would not use M05 for these systems, but use a more relevant one like r2-SCAN-D4, one of Grimme's composite ones, or simply the OPBE functional as was used in &lt;a href=&quot;http://dx.doi.org/10.1021/ct800277a&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Third, I would not use a combination of a huge basis set on O/H and an almost minimal one with ECP on the metal. This is bound to go wrong. It is better to use a consistent basis set on all atoms, e.g. def2-tzvp minimally.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-07-21T21:08:49.597" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11341" PostTypeId="2" ParentId="11228" CreationDate="2023-07-22T02:47:12.620" Score="2" Body="&lt;p&gt;The problem is a bug in old version VASP that can occur in that unit cell because the non-polar phase polarization is not symmetric around 0. The jump happens where ionic contribution to dipole moment has a jump. After I switched to version 6.4.1, all FE structure are fine. But there's still jump from the 0% non-polar centrosymmetric one to distorted polar one. Although, it's value is exact half polarization, as expected. But to get the correct result, we can extrapolate to 0% position.&lt;/p&gt;&#xA;" OwnerUserId="6151" LastEditorUserId="6151" LastEditDate="2023-07-28T16:20:14.407" LastActivityDate="2023-07-28T16:20:14.407" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11343" PostTypeId="2" ParentId="11336" CreationDate="2023-07-22T09:39:50.260" Score="12" Body="&lt;p&gt;&lt;strong&gt;EDIT: This seems to be a case of improper MPI/OpenMP defaults, but the general information below still applies in general.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h2&gt;MPI And OpenMP&lt;/h2&gt;&#xA;&lt;p&gt;The two major parallel programming methods in HPC software are MPI and OpenMP. MPI parallelizes across &lt;em&gt;processes&lt;/em&gt;, OpenMP across &lt;em&gt;threads&lt;/em&gt;. (The difference is explained in &lt;a href=&quot;https://stackoverflow.com/questions/200469/what-is-the-difference-between-a-process-and-a-thread?rq=1&quot;&gt;this StackOverflow question&lt;/a&gt;.)&lt;/p&gt;&#xA;&lt;p&gt;Both MPI and OpenMP must be programmed into the software by the developers and compiled correctly. An end-user can't affect that process, but it is their responsibility to &lt;em&gt;call&lt;/em&gt; the parallelized program with the right settings.&lt;/p&gt;&#xA;&lt;p&gt;MPI settings are usually set through flags to the &lt;code&gt;mpirun&lt;/code&gt; program. For example, this runs &lt;code&gt;my_program&lt;/code&gt; with the &lt;strong&gt;n&lt;/strong&gt;umber of &lt;strong&gt;p&lt;/strong&gt;rocesses set to 4:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun -np 4 my_program&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(With SLURM's &lt;code&gt;srun&lt;/code&gt; the &lt;code&gt;-np&lt;/code&gt; flag can sometimes be omitted, as SLURM will try to deduce the number of processes from the resources allocated. Please AYSA whether you should use &lt;code&gt;srun&lt;/code&gt; or &lt;code&gt;mpirun&lt;/code&gt; -- often one option is correct and the other will crash or slow your program.)&lt;/p&gt;&#xA;&lt;p&gt;OpenMP settings are usually set as environment variables. For example, writing this &lt;em&gt;before&lt;/em&gt; the &lt;code&gt;mpirun&lt;/code&gt; or &lt;code&gt;srun&lt;/code&gt; command sets each &lt;em&gt;process&lt;/em&gt; to use one &lt;em&gt;thread&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export OMP_NUM_THREADS=1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, for a compute-intensive job &lt;em&gt;one thread needs one core&lt;/em&gt;*. Suppose two threads are &amp;quot;squished&amp;quot; onto one core -- the core is forced to multitask between those two threads, and each time it switches threads it has a reset course (plus the core's own scheduler's time spent &amp;quot;juggling&amp;quot; the threads).&lt;/p&gt;&#xA;&lt;p&gt;In Camilla's answer she noted the following info in the program logs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Parallel version (MPI &amp;amp; OpenMP), running on       8 processor cores&#xA;     Number of MPI processes:                 4&#xA;     Threads/MPI process:                     2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;while her SLURM script read:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --ntasks=4&#xA;#SBATCH --ntasks-per-core=1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So SLURM allocated 4 cores, but her &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; seems to have defaulted to 2, which together with &lt;code&gt;mpirun -np 4&lt;/code&gt; results in 8 threads in total, which will run incredibly slowly when &amp;quot;juggled&amp;quot; on 4 cores. Setting &lt;code&gt;OMP_NUM_THREADS&lt;/code&gt; to 1 using the above command seems to have fixed it.&lt;/p&gt;&#xA;&lt;p&gt;*Unless your cluster and the software you're using supports hyperthreading. AYSA.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h2&gt;Original Answer&lt;/h2&gt;&#xA;&lt;p&gt;Ask. Your. System. Administrator. :)&lt;/p&gt;&#xA;&lt;p&gt;When you see &amp;quot;AYSA&amp;quot; throughout this answer it means you need to &lt;em&gt;ask your system administrator&lt;/em&gt; how to best run jobs on the cluster. We don't know what cluster you use, and even if we did, we don't run it. Your administrators do. If you are good friends with them, they can make your life much better.&lt;/p&gt;&#xA;&lt;p&gt;And if you say to your system administrators &amp;quot;okay so you're telling me to do XYZ, but a stranger on the Internet said ABC instead&amp;quot;, you will not be good friends with them.&lt;/p&gt;&#xA;&lt;p&gt;So, please AYSA. Having said that, &lt;em&gt;some&lt;/em&gt; sysadmins are allergic to what I'd call Google questions -- the sort of questions that, in theory, any reasonably smart scientist can answer for themselves on Google. (The truth is Google sucks these days, and it's not getting any better.) So what I'll do is give you the Google Q&amp;amp;A and also give you more detailed questions to AYSA. Make sense? Here we go.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The First Rule of using a cluster is that The Cluster Is Not Just A Bigger Faster Computer. Here's an analogy: a 4-bedroom house is basically the same as a 2-bedroom house but twice as big. But a 2000-bedroom building isn't a house scaled up 1000x, it's a hotel or an apartment block, and it's a completely different building with completely different principles.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, &lt;em&gt;each individual core&lt;/em&gt; is likely slower than anything that's on your PC. If your job can finish running on a two-processor laptop it should take &lt;em&gt;longer&lt;/em&gt; on two cluster cores. That makes sense when you think about the economics: your cluster couldn't afford to buy hundreds of thousands of very fast cores, and it doesn't need to, because the job of the cluster is to run jobs on hundreds or thousands of cores which could never be run on just two cores, no matter how fast. If you're using your cluster because you have to run thousands of small little jobs, AYSA about how to &amp;quot;batch&amp;quot; jobs together so the scheduler can block off the batch like a regular big job.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, the &lt;em&gt;file system&lt;/em&gt; is distributed. Just as cluster cores are not just Big Fast Processors, the cluster's files don't live in One Big Hard Drive. (Imagine if they did -- that one hard drive would have thousands of processes trying to write or read from it at once and it would instantly crash and burn!) Instead there is a &lt;em&gt;distributed file system&lt;/em&gt; which reliably collates changes made by all these processors and then makes them consistent. As a tradeoff, you shouldn't always expect an output file to be instantly written the moment a process has produced it -- you may have some delay, especially with a HPC-optimised program that only writes to hard disk infrequently if used with a distributed file system. So don't just keep refreshing your home directory. AYSA what to expect and how to best use the file system.&lt;/p&gt;&#xA;&lt;p&gt;Thirdly, &lt;em&gt;parallelizing&lt;/em&gt; your application is tricky. There's MPI, OpenMP, various Python solutions, and all of them need the correct options to be set -- otherwise you risk allocating 16 cores to an application only to have it run on one or two cores. AYSA, but before you do, you should run &lt;em&gt;scaling benchmarks&lt;/em&gt;. If you go up from 2 cores to 4 cores, does it finish twice as fast? What about from 4 to 8? What if you go from 2 cores to 8 cores, but also make the problem four times larger? The first two are examples of &lt;em&gt;strong scaling&lt;/em&gt;, which usually drops off more quickly than the &lt;em&gt;weak scaling&lt;/em&gt; of the third example. If you go from 2 to 4 to 8 cores and see the time stay the same -- you're probably not asking correctly for cores.&lt;/p&gt;&#xA;&lt;p&gt;And one important thing to understand is your cluster's &lt;em&gt;chiplet and node sizes&lt;/em&gt;. Please &lt;em&gt;don't&lt;/em&gt; AYSA until you've done some basic searching, since most clusters publicly describe what processors they use and how many are in each node. Node sizes are relevant to larger jobs -- for example, if each node has 64 cores and you're running a big job, it may be worth using either 64 or 128 cores and booking out whole nodes rather than asking for 96 cores (the scheduler might not even allow you to ask for that).&lt;/p&gt;&#xA;&lt;p&gt;Chiplet sizes are more relevant to smaller jobs, especially if your cluster uses the recent AMD EPYC processors. Here's an example from documentation of a cluster I use:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9rUBH.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9rUBH.jpg&quot; alt=&quot;Left, design of EPYC Gen2 SoC showing eight compute dies around a central I/O die; right, zoom-in of compute die showing eight cores around central L3 cache&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;See how, on the right, there are eight cores sharing each L3 cache (essentially superfast RAM used directly during number crunching)? On this cluster, you do best asking for groups of 8 cores so that your program has that L3 cache all to itself, making sure the scheduler &lt;em&gt;does&lt;/em&gt; actually give you the group of 8 instead of splashing your job all over various cores. (If you're using SLURM, AYSA about using the &lt;code&gt;-m block:block:block&lt;/code&gt; directive or whether they recommend alternatives.) Otherwise, if your program is sharing cache with another job, there may be contention slowing your job down (or if your program is aggressive &lt;em&gt;you&lt;/em&gt; will slow &lt;em&gt;their&lt;/em&gt; job).&lt;/p&gt;&#xA;&lt;p&gt;All the best! Please report back on your findings.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2023-07-25T09:47:24.973" LastActivityDate="2023-07-25T09:47:24.973" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11344" PostTypeId="2" ParentId="11262" CreationDate="2023-07-22T22:53:51.847" Score="5" Body="&lt;p&gt;First of all, it is not really an issue since changing geometry along the low-frequency modes almost never changes wavefunction so drastically that it would somehow affect TD DFT computations. And the absence of imaginary frequencies means that maximum displacement is just slightly above the threshold, so it's also OK. It's a good idea to limit yourself to mentioning this in SI.&lt;/p&gt;&#xA;&lt;p&gt;However, if you have a time and computer resources, you can try to fix this using the following ideas:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;reoptimize your structure with optimization thresholds slightly lifted (&lt;em&gt;Opt=Tight&lt;/em&gt;);&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;slightly randomly shuffle atomic coordinates (+/- 0.02 angstroems) before the re-optimization — this could sometimes help to escape the &amp;quot;unsuccessful&amp;quot; local minima;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;reoptimize structure computing frequencies an each optimization step (&lt;em&gt;Opt=CalcAll&lt;/em&gt;) — please note that it is a highly time-demanding option, and usually combination of the first two options should be enough.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6875" LastActivityDate="2023-07-22T22:53:51.847" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11345" PostTypeId="2" ParentId="11334" CreationDate="2023-07-22T23:08:43.593" Score="2" Body="&lt;p&gt;I think the problem is that for atoms with pseudo-potential you need to define both localized and pseudo-potential parts. Here's example for your input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;END-OF-GEOM-BLOCK&#xA;&#xA;H C N O S Cl Br 0&#xA;6-31G(d)&#xA;****&#xA;Pd 0&#xA;LANL2DZ&#xA;****&#xA;&#xA;Pd 0&#xA;LANL2DZ&#xA;&#xA;radii=uaks&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6875" LastActivityDate="2023-07-22T23:08:43.593" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11346" PostTypeId="1" CreationDate="2023-07-23T13:02:12.667" Score="2" ViewCount="105" Body="&lt;p&gt;I was trying to calculate phonon dispersion relations of a monolayer MoS2. I've run an Scf calculations with this input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation = 'scf'&#xA;prefix = 'MoS2_1Layer_ph'&#xA;pseudo_dir = '/home/Giuseppe'&#xA;outdir = './'&#xA;tstress = .true.&#xA;tprnfor = .true.&#xA;forc_conv_thr = 1.0d-3&#xA;nstep = 200&#xA;/&#xA;&amp;amp;SYSTEM&#xA;ibrav = 4&#xA;a = 3.135265913000000000&#xA;c = 43.12822024985000000&#xA;nat = 3&#xA;ntyp = 2&#xA;ecutwfc = 90&#xA;ecutrho = 680&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;mixing_beta = 0.7&#xA;conv_thr = 1.0 d-10&#xA;diagonalization = 'david'&#xA;electron_maxstep =200&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;trust_radius_max = 0.2&#xA;/&#xA;&amp;amp;CELL&#xA;cell_dynamics = &amp;quot;bfgs&amp;quot;&#xA;cell_dofree = '2Dxy'&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Mo 95.9400 Mo.pbesol-spn-kjpaw_psl.1.0.0.UPF&#xA;S 32.0660 S.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS {angstrom}&#xA;Mo 0.0103653871  1.7192376473 21.56417128&#xA; S 1.5780476184  0.9051700832 20.00478826&#xA; S 1.5780476184  0.9051700832 23.12352924&#xA;&#xA;K_POINTS {automatic}&#xA;4 4 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and then  I've run with ph.x this file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;inputph&#xA;outdir = './'&#xA;prefix = 'MoS2_1Layer_ph'&#xA;fildvscf = 'dvscf'&#xA;ldisp = .true.&#xA;fildyn = 'MoS2_1Layer_ph.in'&#xA;alpha_mix(1) = 0.3&#xA;nq1 = 4,&#xA;nq2 = 4,&#xA;nq3 = 1,&#xA;tr2_ph = 1.0d-12&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And my calculations stops saying &amp;quot;Electric Field Calculations&amp;quot; for hours and I do not know what's happening. Before that in the .out file of the ph file it says &amp;quot;There are 9 irreducible representations&amp;quot; and it continues with :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Representation 1 1 modes - To be done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and goes on to representation 9. Is it right?&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-07-23T13:02:12.667" Title="QuantumEspresso phonon calculations stops abruptly with no error" Tags="|density-functional-theory|quantum-espresso|phonons|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11347" PostTypeId="2" ParentId="11302" CreationDate="2023-07-23T16:14:19.273" Score="6" Body="&lt;p&gt;While there are a &lt;a href=&quot;https://link.springer.com/chapter/10.1007/978-1-4020-3286-8_81&quot; rel=&quot;noreferrer&quot;&gt;number&lt;/a&gt; of order parameters which can track the phase transitions and other physio-chemical changes, what you are asking here is about the tetrahedral orientational factor (&lt;strong&gt;OTO&lt;/strong&gt;) which can be written as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;q_\text{OTO} = 1-\frac{3}{8}\Sigma^3_i\Sigma^{4}_{j+1}\bigg[\text{cos}\ \theta_{jk}+\frac{1}{3}\bigg]^2&#xA;$$&lt;/span&gt;&#xA;which gives a measure of the order of the bulk material in terms of molecular near-neighbours. Consider a simple case of a water molecule surrounded by neighbouring water molecules.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ADHHQ.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ADHHQ.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;which due to h-bonding effects form a tetrahedron surrounding the original water molecule.If we can extract the internal angles of this tetrahedron, for ex:- the angle between the neighbours &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; being &lt;span class=&quot;math-container&quot;&gt;$\theta_{jk}$&lt;/span&gt; (the O-O-O angle defined in your question), we can describe the local tetrahedral order &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt;.The &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt; values ranges from &lt;span class=&quot;math-container&quot;&gt;$0\leq q_\text{OTO}\leq1$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; implies no order (something which might be possible for water vapour) and &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt; which implies a maximum ordered system (close to ice &lt;span class=&quot;math-container&quot;&gt;$Ih$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;So for a simplistic implementation, you can:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Select a water molecule at random from your bulk system.&lt;/li&gt;&#xA;&lt;li&gt;Find the closest neighbouring four water molecules.&lt;/li&gt;&#xA;&lt;li&gt;Find &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt; value for the chose water molecule.&lt;/li&gt;&#xA;&lt;li&gt;Repeat 1-3 until you have cycled through all water molecules under analysis. Save all the &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt; values&lt;/li&gt;&#xA;&lt;li&gt;Bin and normalize (to 1) the distribution of the &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt; values and plot the distribution, which gives you probability of &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$P(q_\text{OTO})$&lt;/span&gt; vs &lt;span class=&quot;math-container&quot;&gt;$q_\text{OTO}$&lt;/span&gt; plot, which describes your system. Something like this:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uuCuw.gif&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uuCuw.gif&quot; alt=&quot;Tetrahedral Ordering in Water: Raman Profiles and Their Temperature Dependence&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The above figure is from &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp9052083&quot; rel=&quot;noreferrer&quot;&gt;Tetrahedral Ordering in Water: Raman Profiles and Their Temperature Dependence&lt;/a&gt;. For further reading look into the following articles:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/35053024&quot; rel=&quot;noreferrer&quot;&gt;J.R. Errington and P.G. Debenedetti, Relationship between structural order and the anomalies of liquid water &lt;em&gt;Nature&lt;/em&gt;, &lt;strong&gt;2001&lt;/strong&gt;, &lt;em&gt;409&lt;/em&gt;, 318–321&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcb.5b02936&quot; rel=&quot;noreferrer&quot;&gt;E. Duboué-Dijon and D. Laage, Characterization of the Local Structure in Liquid Water by Various Order Parameters &lt;em&gt;JPC B&lt;/em&gt;, &lt;strong&gt;2015&lt;/strong&gt;, &lt;em&gt;119 (26)&lt;/em&gt;, 8406-8418&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2023-07-23T16:14:19.273" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11348" PostTypeId="1" AcceptedAnswerId="11349" CreationDate="2023-07-21T21:23:32.800" Score="3" ViewCount="27" Body="&lt;p&gt;It seems like the interface IMolecule has been obsoleted and replaced by something else. Any idea what the replacement is?&lt;/p&gt;&#xA;" OwnerUserId="7610" OwnerDisplayName="Velusamy Velu" LastActivityDate="2023-07-23T18:08:28.297" Title="In the Chemistry Development Kit (CDK) IMolecule interface is missing" Tags="|cheminformatics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11349" PostTypeId="2" ParentId="11348" CreationDate="2023-07-23T07:07:01.617" Score="3" Body="&lt;p&gt;&lt;code&gt;IMolecule&lt;/code&gt; has been removed because the only addition to the &lt;code&gt;IAtomContainer&lt;/code&gt; API was the concept that the content of the &lt;code&gt;IMolecule&lt;/code&gt; was fully connected. For the migration, everywhere where you wrote &lt;code&gt;IMolecule&lt;/code&gt; just write &lt;code&gt;IAtomContainer&lt;/code&gt; now.&lt;/p&gt;&#xA;" OwnerUserId="8557" OwnerDisplayName="Egon Willighagen" LastActivityDate="2023-07-23T07:07:01.617" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11350" PostTypeId="1" CreationDate="2023-07-24T05:32:13.220" Score="3" ViewCount="149" Body="&lt;p&gt;This is an extension of a question I asked a little while ago: &lt;a href=&quot;https://chemistry.stackexchange.com/questions/174913/software-to-draw-one-dimensional-pes-including-vibrational-energy-levels&quot;&gt;Software to draw one-dimensional PES including vibrational energy levels&lt;/a&gt;. I am asking the followup here based on advice received after asking the other question.&lt;/p&gt;&#xA;&lt;p&gt;Again, my aim is to compare the difference between a harmonic and anharmonic oscillator. While I am definitely able to produce a Morse potential using spectroscopic constants (two very good Python scripts can be found in the answers to the previous question), I'm not sure how I can generate an equivalent diagram for the &lt;em&gt;harmonic&lt;/em&gt; PES.&lt;/p&gt;&#xA;&lt;p&gt;I believed that it would actually be more simple than the Morse function (after all, the vibrational levels are equally spaced and the function is, essentially, a parabola). However, the only method of generating such a diagram is another Python script (&lt;a href=&quot;https://scipython.com/blog/the-harmonic-oscillator-wavefunctions/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Harmonic Oscillator Wave Functions&lt;/a&gt;) which is, to my eyes, far more complicated than the script the same person provided for Morse PESs, to the extent that I cannot figure out where to insert the experimental spectroscopic parameters...&lt;/p&gt;&#xA;&lt;p&gt;While looking for an answer, though, I came across this figure from &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Physical_Chemistry_%28LibreTexts%29/05%3A_The_Harmonic_Oscillator_and_the_Rigid_Rotor/5.03%3A_The_Harmonic_Oscillator_Approximates_Vibrations&quot; rel=&quot;nofollow noreferrer&quot;&gt;LibreTexts&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/v3BKZ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/v3BKZ.png&quot; alt=&quot;Figure of harmonic and anharmonic PESs&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is &lt;em&gt;exactly&lt;/em&gt; the type of figure I would like to generate, as it clearly shows the difference between the harmonic and anharmonic vibrational energy levels. It should be possible to plot both of the PESs given the same spectroscopic constants for the same molecule, but I can't figure out how to manipulate the scripts to do so.&lt;/p&gt;&#xA;&lt;p&gt;So, does anyone know of a way of generating a &lt;em&gt;harmonic&lt;/em&gt; PES with vibrational energy levels marked, similar to the answers given for the Morse potential (&lt;a href=&quot;https://chemistry.stackexchange.com/questions/174913/software-to-draw-one-dimensional-pes-including-vibrational-energy-levels&quot;&gt;Software to draw one-dimensional PES including vibrational energy levels&lt;/a&gt;), or, even better, does anyone know how I could draw a diagram like the one in the figure above? I have the anharmonicity and force constants (&lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\omega x$&lt;/span&gt;, etc.), but don't have a list of frequencies.&lt;/p&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="5" LastEditDate="2023-07-27T13:16:24.913" LastActivityDate="2023-07-27T13:16:24.913" Title="Script to draw one-dimensional PES comparing harmonic and anharmonic vibrational modes" Tags="|software-recommendations|quantum-mechanics|spectroscopy|vibrations|potential-energy-surface|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11351" PostTypeId="1" CreationDate="2023-07-24T10:00:28.943" Score="2" ViewCount="84" Body="&lt;p&gt;&lt;a href=&quot;https://stackoverflow.com/questions/76754355/is-memory-per-core-more-import-than-of-memory-channels-for-high-performance-va&quot;&gt;Cross posted&lt;/a&gt; on StackOverflow.&lt;/p&gt;&#xA;&lt;p&gt;I ask this question cause recently my department want to purchase a HPC cluster mainly for first principle calculation. For now we have three choices:&lt;/p&gt;&#xA;&lt;p&gt;(1) Per node dual CPU processor (AMD EPYC 7543, 32 cores per CPU, 8 memory channels per CPU), 16 * 32 GB DDR4 RAM. Total 16 computing nodes.&lt;/p&gt;&#xA;&lt;p&gt;(2) Per node dual CPU processor (AMD EPYC 9334, 32 cores per CPU, 12 memory channels per CPU), 16 * 32 GB DDR5 RAM. Total 8 computing nodes.&lt;/p&gt;&#xA;&lt;p&gt;(3) Per node dual CPU processor (AMD EPYC 9554, 64 cores per CPU, 12 memory channels per CPU), 24 * 16 GB DDR5 RAM. Tital 8 computing nodes.&lt;/p&gt;&#xA;&lt;p&gt;I am very hesitant about choosing between three options. The CPU processor in option (1) is a little old, the memory channels are not fully utilized for dual CPU processors in option (2), and the memory per core is only 3 GB in option (3). Each option has its own disadvantages. I am wondering which one would be better for running first-principles software such as VASP, CP2K, and QE. I hope someone could help me make a decision.&lt;/p&gt;&#xA;" OwnerUserId="7083" LastEditorUserId="7" LastEditDate="2023-08-03T12:28:45.473" LastActivityDate="2023-08-03T12:28:45.473" Title="Is memory per core more import than # of memory channels for high performance VASP calculation?" Tags="|density-functional-theory|vasp|high-performance-computing|cp2k|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11353" PostTypeId="1" CreationDate="2023-07-24T12:34:49.187" Score="1" ViewCount="51" Body="&lt;p&gt;I am a starting researcher in condensed matter physics. Hence, i have all the necessary background regarding quantum physics, and condensed matter physics. But what i want to do is to learn different computational approaches for numerical simulations used in condensed matter physics. Specifically, i will like to learn following approaches for starters:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Density Functional theory calculations&lt;/li&gt;&#xA;&lt;li&gt;Mote-Carlo simulations (Classical and Quantum)&lt;/li&gt;&#xA;&lt;li&gt;Dynamic Mean field theory&lt;/li&gt;&#xA;&lt;li&gt;Local Density Approximation + Dynamic Mean field Theory&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I will really appreciate the help from this community, for guidance in learning above methods and beyond. Specifically, i will like if anyone can suggest:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Books&lt;/li&gt;&#xA;&lt;li&gt;Tutorials or Lectures&lt;/li&gt;&#xA;&lt;li&gt;Software packages (i have heard of VASP and QE, but as i want to understand the working of the physics and mathematics, hence i will like to at first code pedagogical examples in python and then jump to individual packages for real researches)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;P.S. I have started to listen lectures from Kristjan Haule (&lt;a href=&quot;https://www.physics.rutgers.edu/grad/509/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.physics.rutgers.edu/grad/509/&lt;/a&gt;) from Rutgers university. After completing this what should i learn? As he only teaches DFT for simple atoms and classical Mote-Carlo simulations in this lecture series.&lt;/p&gt;&#xA;" OwnerUserId="6235" LastEditorUserId="142" LastEditDate="2023-07-27T15:47:19.013" LastActivityDate="2023-07-27T15:47:19.013" Title="Resource recommendation for learning matter modeling for a novice" Tags="|density-functional-theory|computational-chemistry|software|monte-carlo|dynamical-mean-field-theory|" AnswerCount="0" CommentCount="3" ClosedDate="2023-08-10T01:34:28.650" ContentLicense="CC BY-SA 4.0" />
  <row Id="11354" PostTypeId="1" CreationDate="2023-07-24T13:43:09.550" Score="2" ViewCount="225" Body="&lt;p&gt;I am testing ASE with a basic H2 MD simulation.&#xA;I am reading the input file from a xyz file (generated with Packmol), I set pbc True .&#xA;Then, I relax the system with BFGS and move to NVT and NPT equilibration.&#xA;The cell just explodes.&lt;/p&gt;&#xA;&lt;p&gt;I have tried to set initial velocities to a Maxwell distribution (300K) and have a VelocityVerlet run after BSGF but it also explodes. I have also tried reducing taut to 0.01 but I still cannot get a meaningful result.&lt;/p&gt;&#xA;&lt;p&gt;Can you comment on how to improve my simulation? Why is the volume exploding? Shall I impose the external pressure before?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;&amp;quot;&amp;quot;Demonstrates molecular dynamics with constant energy.&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;import ase&#xA;from ase import units&#xA;&#xA;import numpy as np&#xA;from ase import Atoms&#xA;from ase.io.trajectory import Trajectory, TrajectoryReader&#xA;&#xA;from ase import io&#xA;atoms=io.read('H2_box.xyz')&#xA;&#xA;atoms.set_cell((3, 3, 3))&#xA;atoms.center()&#xA;atoms.set_pbc(True)&#xA;&#xA;traj = Trajectory(traj_file, 'w', atoms)&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;Equilibration&amp;quot;&amp;quot;&amp;quot;&#xA;from ase.calculators.emt import EMT &#xA;atoms.set_calculator(EMT())&#xA;&#xA;from ase.optimize import BFGS&#xA;dyn = BFGS(atoms)&#xA;&#xA;dyn.attach(traj.write, interval=10)&#xA;dyn.run(fmax=1)&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;Guess velocities&amp;quot;&amp;quot;&amp;quot;&#xA;from ase.md.velocitydistribution import MaxwellBoltzmannDistribution&#xA;from ase.md.verlet import VelocityVerlet&#xA;&#xA;# Set the momenta corresponding to T=300K&#xA;MaxwellBoltzmannDistribution(atoms, temperature_K=300)&#xA;&#xA;# We want to run MD with constant energy using the VelocityVerlet algorithm.&#xA;dyn = VelocityVerlet(atoms, 5 * units.fs)  # 5 fs time step.&#xA;&#xA;dyn.attach(traj.write, interval=10)&#xA;dyn.run(100)&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;NVT&amp;quot;&amp;quot;&amp;quot;&#xA;from ase.md.nvtberendsen import NVTBerendsen&#xA;&#xA;temperature = 300  # K&#xA;timestep = 1.0  # fs&#xA;total_time = 100  # ps&#xA;nsteps = int(total_time / timestep)&#xA;&#xA;# Set up the integrator&#xA;dyn = VelocityVerlet(atoms, timestep)&#xA;dyn = NVTBerendsen(atoms, timestep, temperature_K=temperature, taut=0.01)&#xA;for step in range(nsteps):&#xA;    dyn.attach(traj.write, interval=10)&#xA;    dyn.run(1)&#xA;&#xA;&amp;quot;&amp;quot;&amp;quot;NPT&amp;quot;&amp;quot;&amp;quot;&#xA;from ase.md.npt import NPT&#xA;&#xA;pressure = 1.0  # bar&#xA;dyn = NPT(atoms, timestep, temperature_K=temperature, externalstress=pressure)&#xA;for step in range(nsteps):&#xA;    dyn.attach(traj.write, interval=10)&#xA;    dyn.run(1)&#xA;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Please find the input file below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;16&#xA;    Energy:      -2.2240932&#xA;H          3.21205        0.01401       -0.00776&#xA;H          2.99965        0.66478        0.17258&#xA;H         -0.25392        0.17187       -0.08020&#xA;H          0.41341       -0.00174        0.07928&#xA;H         -0.29417        2.69561        3.24792&#xA;H         -0.34925        2.57862        2.55199&#xA;H          2.98091        0.28598        3.19910&#xA;H          3.09647       -0.25178        2.75376&#xA;H          3.26389        3.34259       -0.30528&#xA;H          3.35353        3.37297        0.39616&#xA;H          0.59907        2.89804        0.03153&#xA;H         -0.07742        2.95948       -0.16759&#xA;H          0.29545       -0.06128        3.14226&#xA;H         -0.24225       -0.21404        2.70812&#xA;H          2.37813        2.85750        2.82622&#xA;H          2.85583        3.19932        3.22112&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2023-07-25T19:17:52.263" Title="Basic MD in ASE" Tags="|molecular-dynamics|atomic-simulation-environment|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11355" PostTypeId="1" CreationDate="2023-07-24T15:30:33.297" Score="2" ViewCount="185" Body="&lt;p&gt;I want to calculate the vertical excitation energy using the DLPNO-STEOM-CCSD method, on molecules previously optimized using TD-DFT. the parameters being used are as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;STEOM-DLPNO-CCSD,&#xA;Basis set: def2-TZVP,&#xA;Nroots 5,&#xA;TIGHTPNO settings, and RIJCOSX approximation. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am unsure as to whether I can use the &lt;code&gt;ESD(Abs)&lt;/code&gt; to calculate this absorbance data (as with a TD-DFT calculation) or whether I need to use another method.&lt;/p&gt;&#xA;" OwnerUserId="7608" LastEditorUserId="5" LastEditDate="2023-07-24T16:03:56.387" LastActivityDate="2023-07-25T08:00:53.030" Title="Calculating vertical excitation energies at the DLPNO-STEOM-CCSD Theory level" Tags="|density-functional-theory|orca|spectroscopy|excited-states|coupled-cluster|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11356" PostTypeId="1" AcceptedAnswerId="11555" CreationDate="2023-07-24T16:02:59.820" Score="5" ViewCount="145" Body="&lt;p&gt;I'm studying structure-property relations in MOFs and have a pool of hypothetical structures in .cif format generated using ToBaCCo code. I want to filter them based on theoretical density, but the &amp;quot;_exptl_crystal_density_diffrn&amp;quot; value is missing from the .cif files. So I'm not sure if there are any other ways to efficiently calculate the density for large pool of structures.&lt;/p&gt;&#xA;&lt;p&gt;Any guidance on calculating it would be highly appreciated. Thanks!&lt;/p&gt;&#xA;" OwnerUserId="7609" LastEditorUserId="7609" LastEditDate="2023-07-24T16:03:42.227" LastActivityDate="2023-08-29T12:19:43.420" Title="Calculating theoretical density from .cif files" Tags="|software|molecular-modeling|physical-properties-of-materials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11357" PostTypeId="2" ParentId="11350" CreationDate="2023-07-24T16:40:03.560" Score="4" Body="&lt;h1&gt;A script that works for arbitrary potentials&lt;/h1&gt;&#xA;&lt;p&gt;My script has produced the following figures for &lt;a href=&quot;https://arxiv.org/abs/1509.07041&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;this paper&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Simple single-well potential:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MNu1C.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MNu1C.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Double-minimum potential with a small barrier and a &amp;quot;shelf&amp;quot;:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yTEhh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yTEhh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that when the potential gets wider, the vibrational levels get closer together, as we expect based on what happens to a &amp;quot;particle in a box&amp;quot; when the box gets wider.&lt;/p&gt;&#xA;&lt;p&gt;The same basic script was used for &lt;a href=&quot;https://arxiv.org/abs/1508.07184&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;this paper&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Distinction among vibrational levels that have been spectroscopically observed versus ones that have not been observed:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PRVcb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PRVcb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Inset showing vibrational levels:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ct2vh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ct2vh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Vibrational levels labeled:&lt;/h2&gt;&#xA;&lt;p&gt;The same basic script was also used for the diagram in my MMSE answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1005/5&quot;&gt;&lt;strong&gt;here&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cv7YC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cv7YC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It was also used for the figure in &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.87.052505&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;this paper&lt;/strong&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h2&gt;Selected vibrational levels are shown or not shown:&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/56KdZ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/56KdZ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Here is the script that was used for the first paper listed above&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;close('all')&#xA;figure1=figure(1);&#xA;&#xA;set(gca,'Position',[0.101190476190476 0.105359342915811 0.885 0.888357289527721])&#xA;set(gcf,'Color','w')&#xA;&#xA;minX=1;maxX=20;&#xA;splineMeshSize_for_r=0.00001; % I just chose it to be of the same precision as r_e defined in cell 1. Splines can only be necessary for short-range, since long-range seems to have points very close together.&#xA;splineMesh_for_r=minX:splineMeshSize_for_r:maxX;&#xA;&#xA;V_ab_initio_spline_6X=spline(r_abInitio_6X,V_abInitio_6X,splineMesh_for_r);&#xA;V_ab_initio_spline_6a=spline(r_abInitio_6a,V_abInitio_6a,splineMesh_for_r);&#xA;V_ab_initio_spline_3A=spline(r_abInitio_3A,V_abInitio_3A,splineMesh_for_r);&#xA;V_ab_initio_spline_3B=spline(r_abInitio_3B,V_abInitio_3B,splineMesh_for_r);&#xA;V_ab_initio_spline_3C=spline(r_abInitio_3C,V_abInitio_3C,splineMesh_for_r);&#xA;V_ab_initio_spline_3b=spline(r_abInitio_3b,V_abInitio_3b,splineMesh_for_r);&#xA;V_ab_initio_spline_3c=spline(r_abInitio_3c,V_abInitio_3c,splineMesh_for_r);&#xA;V_ab_initio_spline_3d=spline(r_abInitio_3d,V_abInitio_3d,splineMesh_for_r);&#xA;&#xA;minY=-6000;maxY=300;&#xA;axis([minX,maxX,minY,maxY])&#xA;line([minX maxX], [0 0],'Color','k','LineWidth',3)&#xA;&#xA;hold('on')&#xA;&#xA;% [Vmin_ab_initio, indexOfVmin_ab_initio]=min(V_ab_initio_spline);&#xA;% plotPointsSymmetricallyOnPotential(vibrationalEnergies(1:2:end),V_ab_initio_spline,splineMesh_for_r,indexOfVmin_ab_initio);&#xA;&#xA;axis([minX,maxX,minY,maxY])&#xA;plot(r_abInitio_6X,V_abInitio_6X,'Color',[0,255,100]./255,'Linewidth',3);&#xA;plot(r_abInitio_3A,V_abInitio_3A,'Color','r','Linewidth',3);&#xA;plot(r_abInitio_3B,V_abInitio_3B,'Color','k','Linewidth',3);&#xA;plot(r_abInitio_3C,V_abInitio_3C,'Color','c','Linewidth',3);&#xA;&#xA;figure2=figure(2);&#xA;&#xA;set(gca,'Position',[0.101190476190476 0.105359342915811 0.885 0.888357289527721])&#xA;set(gcf,'Color','w')&#xA;&#xA;minX=1;maxX=20;&#xA;minY=-10000;maxY=300;&#xA;axis([minX,maxX,minY,maxY])&#xA;line([minX maxX], [0 0],'Color','k','LineWidth',3)&#xA;&#xA;splineMeshSize_for_r=0.00001; % I just chose it to be of the same precision as r_e defined in cell 1. Splines can only be necessary for short-range, since long-range seems to have points very close together.&#xA;splineMesh_for_r=minX:splineMeshSize_for_r:maxX;&#xA;&#xA;hold('on')&#xA;&#xA;plot(r_abInitio_6a,V_abInitio_6a,'Color','b','Linewidth',3);&#xA;plot(r_abInitio_3b,V_abInitio_3b,'Color','m','Linewidth',3);&#xA;plot(r_abInitio_3c,V_abInitio_3c,'Color','g','Linewidth',3);&#xA;plot(r_abInitio_3d,V_abInitio_3d,'Color',[100,100,100]./255,'Linewidth',3);&#xA;&#xA;% [Vmin_ab_initio, indexOfVmin_ab_initio]=min(V_ab_initio_spline);&#xA;% plotPointsSymmetricallyOnPotential(vibrationalEnergies(1:2:end),V_ab_initio_spline,splineMesh_for_r,indexOfVmin_ab_initio);&#xA;&#xA;axis([minX,maxX,minY,maxY])&#xA;plot(r_abInitio_6a,V_abInitio_6a,'Color','b','Linewidth',3);&#xA;plot(r_abInitio_3b,V_abInitio_3b,'Color','m','Linewidth',3);&#xA;plot(r_abInitio_3c,V_abInitio_3c,'Color','g','Linewidth',3);&#xA;plot(r_abInitio_3d,V_abInitio_3d,'Color',[100,100,100]./255,'Linewidth',3);&#xA;&#xA;%%&#xA;close('all');figure3=figure(3);hold('on')&#xA;set(gca,'Position',[0.101190476190476 0.114161849710983 0.892953008436171 0.879554782732549])&#xA;set(gcf,'Color','w')&#xA;&#xA;minX=2;maxX=15;&#xA;minY=-6000;maxY=300;&#xA;axis([minX,maxX,minY,maxY])&#xA;line([minX maxX], [0 0],'Color','k','LineWidth',3)&#xA;re=3.98;&#xA;&#xA;plot(r_abInitio_3b,V_abInitio_3b,'Color',[0,255,100]./255,'Linewidth',10);&#xA;plot(r_3b_p6q7r05_90,V_3b_p6q7r05_90,'k','LineWidth',3)&#xA;&#xA;v0=-5654.932449854602055; &#xA;v( 1)=-5493.765135128664951;&#xA;v( 2)=-5385.710984514686970;&#xA;v( 3)=-5241.269953247034209;&#xA;v( 4)=-5083.976206177168933;&#xA;v( 5)=-4914.85;&#xA;v( 6)=-4737.691247106215087;&#xA;v( 7)=-4554.829936403927604;&#xA;v( 8)=-4368.240502184650722;&#xA;v( 9)=-4179.292096277415112;&#xA;v(10)=-3988.756231213321371;&#xA;v(11)=-3796.972235927646125;&#xA;v(12)=-3604.218750080568952;&#xA;v(13)=-3411.033149015913750;&#xA;v(14)=-3218.297919388399805;&#xA;v(15)=-3027.108781656958399;&#xA;v(16)=-2838.477232599816034;&#xA;v(17)=-2652.930601841349471;&#xA;v(18)=-2470.302596380747673;&#xA;v(19)=-2290.105676375571875;&#xA;v(20)=-2112.256988503596288;&#xA;v(21)=-1937.405398146945536;&#xA;v(22)=-1766.631273238948864;&#xA;v(23)=-1600.818435795562496;&#xA;v(24)=-1440.124051819757312;&#xA;v(25)=-1284.340696145073408;&#xA;v(26)=-1134.583144744511360;&#xA;v(27)= -996.778888028432000;&#xA;v(28)= -914.777113202062848;&#xA;v(29)= -882.576799450836608;&#xA;v(30)= -845.026425674076544;&#xA;v(31)= -800.327833982061696;&#xA;v(32)= -753.924510206392448;&#xA;v(33)= -705.900692148498688;&#xA;v(34)= -654.935744351130112;&#xA;v(35)= -602.077023609842304;&#xA;v(36)= -548.234951970257472;&#xA;v(37)= -493.706925401166272;&#xA;v(38)= -438.926074728071424;&#xA;v(39)= -384.474432243322304;&#xA;v(40)= -330.903787772794240;&#xA;v(41)= -278.814572462308608;&#xA;v(42)= -228.913912424278848;&#xA;v(43)= -182.018345069401152;&#xA;v(44)= -139.060176467093648;&#xA;v(45)= -101.066168262798576;&#xA;v(46)=  -69.047731355521066;&#xA;v(47)=  -43.749645705548336;&#xA;v(48)=  -25.299916111188852;&#xA;v(49)=  -13.022995406988458;&#xA;v(50)=   -5.669747141689355;&#xA;v(51)=   -1.855271158639904;&#xA;v(52)=   -0.324750667836605;&#xA;v(53)=   -0.002393731491646;&#xA;vibrationalEnergies=[v0 v];&#xA;&#xA;[Vmin_ab_initio_3b, indexOfVmin_ab_initio_3b]=min(V_ab_initio_spline_3b);&#xA;%plotPointsSymmetricallyOnPotential(vibrationalEnergies(1:2:end),V_ab_initio_spline_3b,splineMesh_for_r,indexOfVmin_ab_initio_3b,200);&#xA;&#xA;vibrationalLevelsMeasured=[0:53];&#xA;for vibrationalLevel=vibrationalLevelsMeasured+1&#xA;line([interp1(V_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;lt;re),r_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;lt;re),vibrationalEnergies(vibrationalLevel)) interp1(V_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;gt;re),r_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;gt;re),vibrationalEnergies(vibrationalLevel))], [vibrationalEnergies(vibrationalLevel) vibrationalEnergies(vibrationalLevel)],'Color','b','LineWidth',3)&#xA;r_innerTurningPoint(vibrationalLevel)=interp1(V_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;lt;re),r_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;lt;re),vibrationalEnergies(vibrationalLevel));&#xA;scatter(r_innerTurningPoint(vibrationalLevel),vibrationalEnergies(vibrationalLevel),'MarkerFaceColor','b','MarkerEdgeColor','b');&#xA;r_outerTurningPoint(vibrationalLevel)=interp1(V_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;gt;re),r_3b_p6q7r05_90(r_3b_p6q7r05_90&amp;gt;re),vibrationalEnergies(vibrationalLevel));&#xA;scatter(r_outerTurningPoint(vibrationalLevel),vibrationalEnergies(vibrationalLevel),'MarkerFaceColor','b','MarkerEdgeColor','b');&#xA;end&#xA;&#xA;plot(r(700:end),V(end,700:end),'r','LineWidth',6)&#xA;&#xA;annotation(figure3,'textbox',[0.620 0.760 0.327 0.087],'Color','r','String','&lt;span class=&quot;math-container&quot;&gt;$V(r) = - \frac{D_3(r)C_3}{r^3} - \frac{D_6(r)C_6}{r^6} - \frac{D_8C_8(r)}{r^8}$&lt;/span&gt;','LineStyle','none','Interpreter','latex','FontSize',24);&#xA;annotation(figure3,'textbox',[0.421 0.609 0.107 0.0636],'String','MLR&lt;span class=&quot;math-container&quot;&gt;$_{5.9}^{6,7}(17)$&lt;/span&gt;','LineStyle','none','Interpreter','latex','FontSize',24);&#xA;annotation(figure3,'textbox',[0.293 0.223 0.107 0.0636],'String','Li&lt;span class=&quot;math-container&quot;&gt;$_2\left(3b,3^3\Pi_u\right)$&lt;/span&gt;','LineStyle','none','Interpreter','latex','FontSize',36,'FontName','Helvetica','FitBoxToText','off');&#xA;annotation(figure3,'textbox',[0.438 0.532 0.107 0.0636],'Color',[0,255,100]./255,'String','Original','LineStyle','none','Interpreter','latex','FontSize',24);&#xA;annotation(figure3,'line',[0.366764275256223 0.412884333821376],[0.63775968992248 0.637209302325581],'LineWidth',3);&#xA;scatter(5.89,-2750,200,'MarkerFaceColor',[0,255,100]./255,'MarkerEdgeColor','k')&#xA;scatter(6.5,-2750,200,'MarkerFaceColor',[0,255,100]./255,'MarkerEdgeColor','k')&#xA;annotation(figure3,'arrow',[0.620790629575403 0.588579795021962],[0.850162790697674 0.924031007751938],'LineWidth',3);&#xA;annotation(figure3,'arrow',[0.922401171303075 0.953147877013177],[0.768992248062015 0.689922480620155],'LineWidth',3);&#xA;&#xA;xlabel('Internuclear distance \AA','Interpreter','Latex','FontSize',36)                                                                                    % (r) taken out as per request by Kirk Madison in email on 25/8/2012&#xA;ylabel('&lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;','Interpreter','Latex','FontSize',36)&#xA;box('on');&#xA;set(gca,'XMinorTick','on','YMinorTick','on','LineWidth',2,'FontSize',20);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-07-24T16:48:42.330" LastActivityDate="2023-07-24T16:48:42.330" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11358" PostTypeId="1" CreationDate="2023-07-24T20:57:52.070" Score="3" ViewCount="54" Body="&lt;p&gt;I have seen it written in several places that the matrix of Lagrange multipliers used to impose orthonormality in quantum molecular dynamics schemes based on Kohn-Sham DFT or Hartree-Fock for instance, &lt;span class=&quot;math-container&quot;&gt;$\Lambda_{ij}$&lt;/span&gt;, is symmetric (&lt;span class=&quot;math-container&quot;&gt;$\Lambda_{ij}=\Lambda_{ji}$&lt;/span&gt;).I would have thought that in order to have a real Lagrangian describing the dynamics that this matrix would have to be complex and Hermitian in general. Is it in fact real and symmetric?&lt;/p&gt;&#xA;" OwnerUserId="6777" LastEditorUserId="6777" LastEditDate="2023-08-02T08:56:30.270" LastActivityDate="2023-08-02T08:56:30.270" Title="Are the Lagrange multipliers used in Kohn-Sham DFT/HF-based quantum molecular dynamics real valued?" Tags="|density-functional-theory|molecular-dynamics|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11359" PostTypeId="1" AcceptedAnswerId="11363" CreationDate="2023-07-24T23:23:42.003" Score="3" ViewCount="161" Body="&lt;p&gt;I have run some molecular dynamics calculations with a pretrained machine-learning potential (M3GNet) which uses the ASE MolecularDynamics calculator. My goal is to compare the results (energies and forces) for some randomly selected configurations in the trajectory with their DFT counterparts. Although the energies are easy to find (in the *.log file), I don't know where I can find the forces. Could anyone kindly suggest where to look for them, or what should I do to save the forces?&lt;/p&gt;&#xA;" OwnerUserId="5448" LastActivityDate="2023-07-25T09:37:51.057" Title="Saving forces from ASE Molecular Dynamics calculations" Tags="|molecular-dynamics|molecular-modeling|atomic-simulation-environment|machine-learning|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11361" PostTypeId="1" CreationDate="2023-07-25T06:33:25.687" Score="1" ViewCount="83" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/X9bcQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/X9bcQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;I have converged k points and i have found curve like this, which k points should i use? 12&lt;em&gt;12&lt;/em&gt;12 or 3&lt;em&gt;3&lt;/em&gt;3 &lt;a href=&quot;https://i.stack.imgur.com/Iwp9t.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Iwp9t.png&quot; alt=&quot;K points vs energy &quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7614" LastEditorUserId="7614" LastEditDate="2023-07-25T06:35:41.577" LastActivityDate="2023-07-26T14:13:02.977" Title="How to choose k points, accoriding to minimum energy or minimum change in energy?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="2" ClosedDate="2023-08-06T06:57:05.827" ContentLicense="CC BY-SA 4.0" />
  <row Id="11362" PostTypeId="2" ParentId="11355" CreationDate="2023-07-25T08:00:53.030" Score="1" Body="&lt;p&gt;You probably can, but even if you can, such a calculation is not the recommended practice, since:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The DLPNO-STEOM-CCSD analytic gradient is not available, and probably will not be available anytime soon. Therefore, the gradient of the DLPNO-STEOM-CCSD energy (which is required in an ESD calculation) has to be evaluated numerically, which is very costly (takes &lt;span class=&quot;math-container&quot;&gt;$6N_{atom}\times$&lt;/span&gt; the time of a DLPNO-STEOM-CCSD single point calculation).&lt;/li&gt;&#xA;&lt;li&gt;Even worse, the analytic gradient of DLPNO-CCSD is not available either (although it may become available in a couple of years), so the ground state Hessian (which is also required by ESD) has to be evaluated by a twice numerical differentiation of the DLPNO-CCSD energy, rather than a seminumerical differentiation (differentiate once analytically, then once numerically). This is not only extremely costly, but also introduces considerable numerical noise.&lt;/li&gt;&#xA;&lt;li&gt;If you could really afford all of these calculations, then you could achieve better accuracy using the same computational time, by going beyond the harmonic approximation employed by ESD, e.g. with path integral molecular dynamics on a machine learned potential energy surface fitted against DLPNO-STEOM-CCSD data.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Therefore, the usually recommended practice is to calculate the gradients and Hessians under the DFT/TDDFT level, and use DLPNO-STEOM-CCSD only to provide a better estimate of the adiabatic excitation energy. Therefore, the input file should be written as if it is a TDDFT ESD calculation; meanwhile you can calculate the adiabatic excitation energy using DLPNO-STEOM-CCSD and enter the result using the keyword DELE (for details, see ORCA manual). Similarly, the DLPNO-STEOM-CCSD transition dipole moment can be entered using the TDIP keyword. This gives you an absorption spectrum where, roughly speaking, the 0-0 peak as essentially DLPNO-STEOM-CCSD accuracy, and the splitting between the vibrational fine structures has TDDFT accuracy, which is sufficient for most purposes (and as I said, in case the TDDFT vibronic structure is not accurate enough for your purpose, the intrinsic limitation of the ESD module's harmonic approximation to the PES is likely non-negligible either).&lt;/p&gt;&#xA;&lt;p&gt;Even more, as you can afford the DLPNO-STEOM-CCSD single point calculations anyway, you can use your DLPNO-STEOM-CCSD results to guide the selection of a density functional that best suits your system. By this way, the TDDFT part of the calculation can become more reliable than if you selected your functional without relying on the DLPNO-STEOM-CCSD benchmark results.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-07-25T08:00:53.030" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11363" PostTypeId="2" ParentId="11359" CreationDate="2023-07-25T09:37:51.057" Score="4" Body="&lt;p&gt;When a structure (i.e. an &lt;code&gt;ase.Atoms&lt;/code&gt; object) is assigned with an ASE calculator, you can use the following to get the corresponding energy and forces:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;energy = atoms.get_potential_energy()&#xA;forces = atoms.get_forces()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you have a trajectory file, you can simply read a list of &lt;code&gt;ase.Atoms&lt;/code&gt; objects by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;images = read('xxx.traj', index=':')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-07-25T09:37:51.057" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11364" PostTypeId="2" ParentId="11354" CreationDate="2023-07-25T09:49:51.150" Score="5" Body="&lt;p&gt;Without further looking into the details, I can tell you straight-up why you cannot get any meaningful result. You are using the EMT calculator, which is a semi-empirical potential parameterized for transition metals. Non-metal elements like H, C, O are supported in the ASE EMT calculator only for testing purposes.&lt;/p&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/AID_framework/ase/calculators/emt.py#L24&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;: the parameters for non-metal elements are completely made up so they are only for fun!&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-07-25T09:49:51.150" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11365" PostTypeId="1" CreationDate="2023-07-25T10:43:22.317" Score="4" ViewCount="146" Body="&lt;p&gt;To determine the lattice parameter of a material, I did a VC-RELAX calculation using Quantum ESPRESSO, and I also applied the Birch-Murnaghen equation to obtain the optimized lattice parameter. However, I noticed that the results are slightly different by 0.0926 Angstrom.&lt;/p&gt;&#xA;&lt;p&gt;Now, I am a bit confused about which value to consider for my subsequent calculations, and I wonder why they are not exactly the same?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-07-25T14:20:41.053" Title="Which lattice parameter should be used, the one obtained by vc-relax or the optimized value acquired through the Birch-Murnaghen equation?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|optimization|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11366" PostTypeId="1" CreationDate="2023-07-25T12:38:52.843" Score="2" ViewCount="39" Body="&lt;p&gt;&lt;img src=&quot;https://stackoverflow.com/image.jpg&quot; alt=&quot;&quot; /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/SOMon.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SOMon.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have this after typing an htop and all of the CPUs are used but my output file stopped updating 3 hours ago like this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VZDw1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VZDw1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Should I kill this process? I started this calculation yesterday at 16:00 and it stopped after 21 hours :(&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-07-25T12:38:52.843" Title="Phonon calculations stopped but my computer says it's still running" Tags="|density-functional-theory|quantum-espresso|phonons|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11367" PostTypeId="2" ParentId="11365" CreationDate="2023-07-25T14:20:41.053" Score="4" Body="&lt;p&gt;I will personally recommend to use the result (lattice parameter) after the fit with the Birch-Murnaghan equation, that what people do especially the bulk modulus will be included as a result and compared to experimental data.  Your obtained energies are sampled with discrete lattice parameters, except the case when your step is very small, your derived lattice parameter will always be approximate. The BM equation is continuous and has an identifiable minimum.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;However, I noticed that the results are slightly different by 0.0926 Angstrom.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The error is relatively small, you may find it large compared to experimental results for example, but it is really small compared to the non-negligible error induced by an approximate exchange correlation functional.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I wonder why they are not exactly the same?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;A macroscopic classical and a microscopic quantum result will never be in perfect agreement.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-07-25T14:20:41.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11368" PostTypeId="1" CreationDate="2023-07-25T16:05:31.273" Score="3" ViewCount="113" Body="&lt;p&gt;I have some confusion. Can you please help me?&#xA;There are some cubic perovskite structure whose CIF file are not included in material project website. For this type of materials how can i perform calculation by quantum espresso, how can i produce scf.in file?&#xA;Example : SnGeBr3 cubic has CIF file but CsGeCl3 cubic has no CIF file in the website.&#xA;Now if i want to perform calculation for cubic CsGeCl3  perovskite, What should i do?&lt;/p&gt;&#xA;" OwnerUserId="7614" LastActivityDate="2023-07-25T19:43:35.533" Title="How to work with unknown compound in quantum espresso?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11369" PostTypeId="1" AcceptedAnswerId="11372" CreationDate="2023-07-25T19:05:04.383" Score="9" ViewCount="794" Body="&lt;p&gt;I'm a student doing quantum computing research trying to understand better what kinds of chemical systems are difficult to simulate on a classical computer and for which quantum simulation could be beneficial. One answer I've seemed to pick up on is molecules undergoing chemical bond dissociation. For example, I've seen plots of the ground state energy of N2 as a function of bond length, in which methods like Hartree-Fock, MP2, CISD, and CCSD get progressively less accurate as the bond length increases.&lt;/p&gt;&#xA;&lt;p&gt;My question, broadly is: &lt;em&gt;why is it harder to simulate a molecule with a stretched bond?&lt;/em&gt; Based on what I know so far, it seems the answer is: as the bond is stretched, multiple orbital energy levels converge in energy, and as a result, this yields exponentially many Slater determinants in the ground state with large coefficients. This seems to be related to what chemists call &amp;quot;strong correlation&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;This seems counter-intuitive to me, since, using N2 as an example, as the bond is stretched, I would assume that the electrons associated to different nuclei interact less (i.e: the Hamiltonian approximately factorizes into a tensor product of two easier-to-simulate Hamiltonians for each nuclei). So with this argument, I would assume that N2 would be harder to simulate when the nuclei are closer.&lt;/p&gt;&#xA;" OwnerUserId="3574" LastEditorUserId="3574" LastEditDate="2023-07-25T19:47:33.477" LastActivityDate="2023-07-25T22:51:57.927" Title="Why is chemical bond dissociation difficult to simulate?" Tags="|computational-chemistry|quantum-chemistry|quantum-mechanics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11370" PostTypeId="2" ParentId="11354" CreationDate="2023-07-25T19:17:52.263" Score="3" Body="&lt;p&gt;This was actually addressed on the ASE Element chat.  The primary problem in this calculation is actually that packmol does not consider periodic boundary conditions.  A simple solution involves simply running packmol and adding a buffer around the cell of empty space which is filled during equilibration.  The EMT potential is also problematic, but the resulting cell as presented will include overlapping atoms which will give any potential issues.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2023-07-25T19:17:52.263" CommentCount="0" CommunityOwnedDate="2023-07-25T19:17:52.263" ContentLicense="CC BY-SA 4.0" />
  <row Id="11371" PostTypeId="2" ParentId="11368" CreationDate="2023-07-25T19:43:35.533" Score="4" Body="&lt;p&gt;You have two options:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Search for other databases like &lt;a href=&quot;https://icsd.products.fiz-karlsruhe.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ICSD-Inorganic Crystal Structure Database&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Try to generate/predict the crystal structure yourself using software like &lt;a href=&quot;https://uspex-team.org/en/uspex/overview&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Below is a CIF downloaded from ICSD database.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#(C) 2023 by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure.  All rights reserved.&#xA;data_23122-ICSD&#xA;_database_code_ICSD 23122&#xA;_audit_creation_date 1986-10-14&#xA;_audit_update_record 2003-04-01&#xA;_chemical_name_common 'Cesium trichlorogermanate(II) - HT'&#xA;_chemical_formula_structural 'Cs (Ge Cl3)'&#xA;_chemical_formula_sum 'Cl3 Cs1 Ge1'&#xA;_chemical_name_structure_type Perovskite#CaTiO3&#xA;_exptl_crystal_density_diffrn 3.16&#xA;_diffrn_ambient_temperature 453.&#xA;_citation_title&#xA;'A ferroelectric chloride of perowskite type. Crystal structures of Cs Ge Cl3'&#xA;loop_&#xA;_citation_id&#xA;_citation_journal_full&#xA;_citation_year&#xA;_citation_journal_volume&#xA;_citation_page_first&#xA;_citation_page_last&#xA;_citation_journal_id_ASTM&#xA;primary 'Acta Chemica Scandinavica ' 1965 19 421 428 ACSAA4&#xA;loop_&#xA;_citation_author_citation_id&#xA;_citation_author_name&#xA;primary 'Christensen, A.N.'&#xA;primary 'Rasmussen, S.E.'&#xA;_cell_length_a 5.475&#xA;_cell_length_b 5.475&#xA;_cell_length_c 5.475&#xA;_cell_angle_alpha 90.&#xA;_cell_angle_beta 90.&#xA;_cell_angle_gamma 90.&#xA;_cell_volume 164.12&#xA;_cell_formula_units_Z 1&#xA;_space_group_name_H-M_alt 'P m -3 m'&#xA;_space_group_IT_number 221&#xA;loop_&#xA;_space_group_symop_id&#xA;_space_group_symop_operation_xyz&#xA;1 'z, y, -x'&#xA;2 'y, x, -z'&#xA;3 'x, z, -y'&#xA;4 'z, x, -y'&#xA;5 'y, z, -x'&#xA;6 'x, y, -z'&#xA;7 'z, -y, x'&#xA;8 'y, -x, z'&#xA;9 'x, -z, y'&#xA;10 'z, -x, y'&#xA;11 'y, -z, x'&#xA;12 'x, -y, z'&#xA;13 '-z, y, x'&#xA;14 '-y, x, z'&#xA;15 '-x, z, y'&#xA;16 '-z, x, y'&#xA;17 '-y, z, x'&#xA;18 '-x, y, z'&#xA;19 '-z, -y, -x'&#xA;20 '-y, -x, -z'&#xA;21 '-x, -z, -y'&#xA;22 '-z, -x, -y'&#xA;23 '-y, -z, -x'&#xA;24 '-x, -y, -z'&#xA;25 '-z, -y, x'&#xA;26 '-y, -x, z'&#xA;27 '-x, -z, y'&#xA;28 '-z, -x, y'&#xA;29 '-y, -z, x'&#xA;30 '-x, -y, z'&#xA;31 '-z, y, -x'&#xA;32 '-y, x, -z'&#xA;33 '-x, z, -y'&#xA;34 '-z, x, -y'&#xA;35 '-y, z, -x'&#xA;36 '-x, y, -z'&#xA;37 'z, -y, -x'&#xA;38 'y, -x, -z'&#xA;39 'x, -z, -y'&#xA;40 'z, -x, -y'&#xA;41 'y, -z, -x'&#xA;42 'x, -y, -z'&#xA;43 'z, y, x'&#xA;44 'y, x, z'&#xA;45 'x, z, y'&#xA;46 'z, x, y'&#xA;47 'y, z, x'&#xA;48 'x, y, z'&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_oxidation_number&#xA;Cs1+ 1&#xA;Ge2+ 2&#xA;Cl1- -1&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_Wyckoff_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_B_iso_or_equiv&#xA;_atom_site_occupancy&#xA;Cs1 Cs1+ 1 a 0 0 0 7.46 1.&#xA;Ge1 Ge2+ 1 b 0.5 0.5 0.5 0.85 1.&#xA;Cl1 Cl1- 6 f 0.5 0.0686 0.5 3.56 0.5&#xA;#End of TTdata_23122-ICSD&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-07-25T19:43:35.533" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11372" PostTypeId="2" ParentId="11369" CreationDate="2023-07-25T22:51:57.927" Score="8" Body="&lt;p&gt;Some hints : all methods that attempt to describe the ground state of a many-body electronic system are often reduced to one electron in a mean-field or effective potential that includes the effects of the other electrons and the potential of the nuclei with some corrections. The eigenfunction is expanded in a chosen basis set. The most accurate description must include an infinite basis set with a non-local potential, which is definitely impractical for a &amp;quot;classical computer&amp;quot;. A mean-field potential is a good approximation if the effective potential, which depends strongly on the electronic distribution, is not widely affected by a large variation of this electronic distribution. This is precisely the case at large interatomic distances, where all approximations, especially density methods, give inaccurate results and have poor convergence.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;in which methods like Hartree-Fock, MP2, CISD, and CCSD get progressively less accurate as the bond length increases&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Hartree-Fock (HF), related methods or generally wave function based methods are more interesting in this case, they include non local potential (exchange), it gives self-interaction free eigenvalues, the basis set could not converge quickly just because of the configuration between localized orbitals and a very small tendency to be delocalized, the error is due to the mean field approximation.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This seems to be related to what chemists call &amp;quot;strong correlation&amp;quot;.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;A &amp;quot;strongly correlated&amp;quot; behavior is exactly the case where the overlap between the atoms is small and the repulsion on the incoming charge becomes non-negligible compared to the translational symmetry creating the bond.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This seems counter-intuitive to me, since, using N2 as an example, as the bond is stretched, I would assume that the electrons associated to different nuclei interact less (i.e: the Hamiltonian approximately factorizes into a tensor product of two easier-to-simulate Hamiltonians for each nuclei).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As a consequence of the previous arguments, the hamiltonian is only separable if the electrons are not correlated, at large interatomic distances the coulomb repulsion is large &lt;span class=&quot;math-container&quot;&gt;$U \gg $&lt;/span&gt;, a single particule approximation will never lead to the exact ground state and the hamiltonian is not strictly speaking separable. The wave function of the system is &lt;span class=&quot;math-container&quot;&gt;$\psi(r_1,r_2,r_3,...,r_n)$&lt;/span&gt;, for simplicity, let's take the case &lt;span class=&quot;math-container&quot;&gt;$\psi(r_1,r_2)$&lt;/span&gt;, if the atoms are far apart an not interaction &lt;span class=&quot;math-container&quot;&gt;$\psi(r_1,r_2) = \phi_1(r_1)\phi_2(r_2)$&lt;/span&gt;, when the wave function overlaps, the wave function &lt;span class=&quot;math-container&quot;&gt;$\phi_1$&lt;/span&gt; is transferred to another atom with by a translating operator &lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt; and reciprocally for &lt;span class=&quot;math-container&quot;&gt;$\phi_2$&lt;/span&gt;, the translation operation is the generator of the bond, the commutator [&lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$\hat{T}]=0$&lt;/span&gt; if the potential is translational symmetric. Only a local potential &lt;span class=&quot;math-container&quot;&gt;$V(r_1,r_2)=V_0(r)$&lt;/span&gt; is translational symmetric, &lt;span class=&quot;math-container&quot;&gt;$V(r_1,r_2)$&lt;/span&gt; is not translational symmetric in this configuration, the translational symmetry is enhanced at small distances, while at large distance the operator is reduced and &lt;span class=&quot;math-container&quot;&gt;$V(r_1,r_2)$&lt;/span&gt; is significant, the system is strongly correlated [&lt;span class=&quot;math-container&quot;&gt;$\hat{H}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$\hat{T}$&lt;/span&gt;]&lt;span class=&quot;math-container&quot;&gt;$\neq 0$&lt;/span&gt; , &lt;span class=&quot;math-container&quot;&gt;$\psi(r_1,r_2) \neq \phi_1(r_1)\phi_2(r_2)$&lt;/span&gt;, any one-electron approximation will never give the exact ground state.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I would assume that N2 would be harder to simulate when the nuclei are closer.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The nuclei are often treated classically, at very small distances, things would have been very complicated, the problem arises often from the basis set. Approximations like DFT works fine at small distances, because the overlap is large and the density do not vary much, a mean field potential holds and the result can be very accurate.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-07-25T22:51:57.927" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11373" PostTypeId="1" CreationDate="2023-07-25T23:11:56.483" Score="6" ViewCount="100" Body="&lt;p&gt;I am currently trying to find molecular geometry data prior to 1960, and it seems like&#xA;&amp;quot;Tables of Interatomic Distances and Configuration in Molecules and Ions (1958). Special publication No. 11. The Chemical society, London&amp;quot;&#xA;and&#xA;&amp;quot;Tables of Interatomic Distances and Configuration in Molecules and Ions, Supplement 1956-1959 (1965). Special publication No. 18. The Chemical society, London&amp;quot; are 2 great sources to check out.&lt;/p&gt;&#xA;&lt;p&gt;However, in my online searches, I can only find one or two page pdfs which include these titles in a citation, or library websites which claim have the physical copies of these books. Due to time constraints, I would prefer to have access to the online copies of these books rather than the physical volumes themselves. Has anyone found full online pdfs for these books before? Or are there more accessible alternative sources for molecular geometry data prior to 1960?&lt;/p&gt;&#xA;" OwnerUserId="7618" LastEditorUserId="5" LastEditDate="2023-07-25T23:48:19.180" LastActivityDate="2023-07-26T07:15:48.387" Title="Trouble finding pdfs of &quot;Tables of Interatomic Distances and Configuration in Molecules and Ions&quot; series books" Tags="|reference-request|databases|geometry|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11376" PostTypeId="1" CreationDate="2023-07-26T06:39:15.253" Score="1" ViewCount="27" Body="&lt;p&gt;I am studying about conjugated polymers in sensors applications. I want to conduct structural of complex and its properties (such as HOMO-LUMO etc.). Is there any software for docking that external compound to polymer? Are apps like Autodock suitable for this kind of task?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="7305" LastActivityDate="2023-07-26T06:39:15.253" Title="Complex formation site between polymer and external compound" Tags="|computational-chemistry|polymers|docking|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11377" PostTypeId="2" ParentId="11373" CreationDate="2023-07-26T07:15:48.387" Score="6" Body="&lt;p&gt;Found No. 18: &lt;a href=&quot;https://archive.org/details/tablesofinterato0000lesu/page/n3/mode/1up&quot; rel=&quot;noreferrer&quot;&gt;https://archive.org/details/tablesofinterato0000lesu/page/n3/mode/1up&lt;/a&gt; (an Archive.org account is free and fairly quick to register for).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-07-26T07:15:48.387" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11378" PostTypeId="1" CreationDate="2023-07-26T11:56:29.920" Score="1" ViewCount="37" Body="&lt;p&gt;I have performed an ABF simulation to investigate the binding of a small molecule with a 2D surface using NAMD. The initial simulation was for a scan window of 3 to 15 angstroms of z-projected distance between the small molecule and the 2D surface. However, upon analyzing the data, I observed that the sampling between the region 7-15 angstrom were significantly lower when compared to the 3-7 angstrom region. Thus, I performed an another ABF run between 7 and 15 angstroms. Is there a way I can combine these two data to generate the full 3-15 scan range?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-26T11:56:29.920" Title="Adaptive Biasing Force Simulations in NAMD" Tags="|molecular-dynamics|free-energy|binding-energy|" AnswerCount="0" CommentCount="3" ClosedDate="2024-02-21T04:10:01.053" ContentLicense="CC BY-SA 4.0" />
  <row Id="11379" PostTypeId="2" ParentId="11335" CreationDate="2023-07-26T13:16:49.293" Score="2" Body="&lt;ol&gt;&#xA;&lt;li&gt;Th geometry at the start in &lt;code&gt;Th&lt;/code&gt; point group otherwise its just mangling and cannot smoothly decrease;&lt;/li&gt;&#xA;&lt;li&gt;Optimiazation in &lt;code&gt;z-matrix&lt;/code&gt; coordinates; in redundant or cartesian it just doesn't account for the very small changes in atom coordinates and exaggerate them so far beyond the threshold;&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;nosymm&lt;/code&gt; keyword to prevent Gaussian from refining the provided geometry, as it tends to change move slightly water hydrogens at the start of the job&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;int=ultrafine&lt;/code&gt; combined with &lt;code&gt;maxstep=1&lt;/code&gt; seems to be  crucial as well because, as I suppose, the PES is very flat.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;In my case this lead to the situation when system &lt;strong&gt;DID&lt;/strong&gt; optimize but with a single imaginary frequency of over 200i.&lt;/p&gt;&#xA;&lt;p&gt;The solution for that was rerun using the same input file but the optimized  geometry with a single imaginary frequency along with the changing of convergance criterion to &lt;code&gt;verytight&lt;/code&gt; as well as &lt;code&gt;opt&lt;/code&gt; into &lt;code&gt;fopt&lt;/code&gt;...&lt;/p&gt;&#xA;&lt;p&gt;...I should actually know because reading Gaussian's manual it is stated that &amp;quot;&lt;em&gt;[Regarding  optimization in&lt;code&gt;z-matrix&lt;/code&gt; coordinates system...] In this case, the keyword &lt;code&gt;FOpt&lt;/code&gt; rather than &lt;code&gt;Opt&lt;/code&gt; requests that the program verify that a full optimization is being done (i.e., that the variables including inactive variables are linearly independent and span the degrees of freedom allowed by the molecular symmetry).&lt;/em&gt;&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="5606" LastActivityDate="2023-07-26T13:16:49.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11380" PostTypeId="2" ParentId="11361" CreationDate="2023-07-26T14:13:02.977" Score="1" Body="&lt;p&gt;You do not choose the &lt;span class=&quot;math-container&quot;&gt;${\bf k}$&lt;/span&gt;-points by minimum energy. What you actually want is to get the termodynamic limit, which corresponds to the infinite &lt;span class=&quot;math-container&quot;&gt;${\bf k}$&lt;/span&gt;-point grid.&lt;/p&gt;&#xA;&lt;p&gt;The convergence shown on the curves is quite typical. You should choose the number of &lt;span class=&quot;math-container&quot;&gt;${\bf k}$&lt;/span&gt;-points such that going to larger grids does not change the total energy significantly.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-07-26T14:13:02.977" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11381" PostTypeId="1" CreationDate="2023-07-26T16:35:03.910" Score="2" ViewCount="120" Body="&lt;p&gt;I am trying to add a new CV (A plumed one) to a storage. I've completed a TPS simulation, and now I want to store the new CV for later analysis use.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import openpathsampling as paths&#xA;storage = paths.Storage(&amp;quot;TPS_eq.nc&amp;quot;)&#xA;...&#xA;plmd = PLUMEDInterface(ops_topology,logfile=os.devnull)&#xA;plmd.set('','UNITS LENGTH=A')&#xA;...&#xA;CV_dihed_Op2Op3Op4P=PLUMEDCV(&amp;quot;CV_dihed_o1o2o3o4&amp;quot;,plmd,&amp;quot;TORSION ATOMS=o1,o2,o3,o4&amp;quot;)&#xA;&#xA;storage.save(CV_dihed_o1o2o3o4)&#xA;storage.cvs.add_diskcache(CV_dihed_o1o2o3o4, allow_incomplete=True)&#xA;&#xA;all_snapshots = storage.snapshots.all()&#xA;&#xA;storage.cvs[&amp;quot;CV_dihed_o1o2o3o4&amp;quot;](all_snapshots)&#xA;storage.cvs.sync(storage.cvs[&amp;quot;CV_dihed_o1o2o3o4&amp;quot;])&#xA;storage.close()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I reload the storage, the CV will be present (as in storage.cvs), but the values will be 'recomputed' and not saved to the storage.&#xA;ndeed, the storage.cvXX files are empty (store.cvXX[None/ANY]: 0 object(s)) compared to the data stored during the simulation in store.cv0[None/ANY]: 8224 object(s). The same applies to the storage.vars, where storage.vars[&amp;quot;cv36_index&amp;quot;] and its corresponding values are currently empty (shape = (0,)).&lt;/p&gt;&#xA;&lt;p&gt;Am I missing something ?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerDisplayName="user7624" LastEditorUserId="5" LastEditDate="2023-08-30T14:38:42.667" LastActivityDate="2023-08-30T14:38:42.667" Title="Adding new CVs to a Storage" Tags="|openpathsampling|plumed|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11382" PostTypeId="1" CreationDate="2023-07-27T08:08:35.253" Score="2" ViewCount="118" Body="&lt;p&gt;Let's suppose I've already run an scf calculation for an input file. Now I can read the wave functions and with ph.x I can get the dynamical matrices. I'll get as many files as the number of q-points I've chosen named like &amp;quot;MoS2.dyn0&amp;quot; , &amp;quot;MoS2.dyn1&amp;quot; , &amp;quot;MoS2.dyn2&amp;quot; and so on.&lt;/p&gt;&#xA;&lt;p&gt;If I stop the calculations and get only the first 3 dynamical file could I still use q2r.x and plot the dispersion relations with matdyn.x or I will get error because I have stopped manually my calculation?&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-07-29T16:44:17.683" Title="Question regarding q2r in QuantumEspresso Phonon Calculation" Tags="|quantum-espresso|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11383" PostTypeId="1" AcceptedAnswerId="11458" CreationDate="2023-07-27T08:14:27.353" Score="2" ViewCount="480" Body="&lt;p&gt;I want to know that if there post-process tool for VASP to plot spin-texture like this? I have tried Vaspkit but it did not support my structure.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5phD4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5phD4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/w3S0N.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w3S0N.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-08-08T09:45:58.243" Title="How to plot spin texture?" Tags="|vasp|vaspkit|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11384" PostTypeId="1" CreationDate="2023-07-27T19:25:24.233" Score="3" ViewCount="74" Body="&lt;p&gt;I am trying to calculate the potential energy curve for the interaction between CO2 and a silica surface. I use 3 systems and run single point calculations with LAMMPS and substract the values like&#xA;E = (E_slab/co2 - E_loneco2 - E_lone_silica)&lt;/p&gt;&#xA;&lt;p&gt;But the energy profile shows no going to zero at longer distances of CO2 away from the surface, can anyone Identify the reason?&lt;/p&gt;&#xA;&lt;p&gt;my lammps input script for the surface+silica(total system) is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# LAMMPS Molecular Dynamics Simulation - single point calculation (crystoballite and Na+)&#xA;&#xA;units           real&#xA;atom_style      full&#xA;&#xA;boundary        p p p&#xA;&#xA;pair_style     lj/cut/coul/long 7.00 7.00&#xA;&#xA;pair_modify    mix arithmetic&#xA;pair_modify    tail yes&#xA;kspace_style   pppm 1.0e-4&#xA;&#xA;bond_style     harmonic&#xA;angle_style    harmonic&#xA;&#xA;read_data      data.lammps&#xA;&#xA;#                          epsilon    sigma&#xA;pair_coeff      1       1  0.00010  2.70000  #SI-SI (bulk/silanol)&#xA;pair_coeff      2       2  0.18520  3.30000  #O-O (silanol)&#xA;pair_coeff      3       3  0.00000  0.00000  #H-H (silanol)&#xA;pair_coeff      4       4  0.46680  2.70000  #O-O (bulk)&#xA;pair_coeff      5       5  0.05589  2.75700  #C-C (CO2)&#xA;pair_coeff      6       6  0.15998  3.03300  #O-O (CO2)&#xA;pair_coeff      1       5  0.00236  2.72850  #Si_C(bulk_CO2)&#xA;pair_coeff      1       6  0.00399  2.86650&#xA;pair_coeff      2       5  0.21793  3.02850&#xA;pair_coeff      2       6  0.17212  3.16650&#xA;pair_coeff      3       5  0.00000  0.00000&#xA;pair_coeff      3       6  0.00000  0.00000&#xA;pair_coeff      4       5  0.16152  2.72850&#xA;pair_coeff      4       6  0.27327  2.86650&#xA;pair_coeff      5       6  0.09455  2.89500&#xA;&#xA;bond_coeff      1 312.3295  1.66300    # Si-O    (surface) (SHAKE)&#xA;bond_coeff      2 553.0000  0.95000    # O-H               (SHAKE)&#xA;bond_coeff      3 575.0000  1.49900    # C-O     (CO2)     (SHAKE)&#xA;&#xA;angle_coeff     1 24.49933  118.500    # SI-O-H    (surface)&#xA;angle_coeff     2 147.7000  180.000    # O-C-O     (CO2)&#xA;&#xA;special_bonds   lj/coul 0.0 0.0 0.5&#xA;&#xA;info            coeffs out log&#xA;neighbor        2.0 bin&#xA;neigh_modify    every 2 delay 0 check yes&#xA;&#xA;thermo_style    custom step temp etotal ke pe density vol lx ly lz&#xA;&#xA;run             0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-07-28T09:38:50.573" Title="Potential Energy curve for CO2 and a surface" Tags="|lammps|potential-energy-surface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11385" PostTypeId="1" AcceptedAnswerId="11389" CreationDate="2023-07-27T19:57:35.263" Score="3" ViewCount="248" Body="&lt;p&gt;I want to convert the OUTCAR file to a file of xyz (not extxyz) format.&lt;/p&gt;&#xA;&lt;p&gt;The informaiton of lattice (or cell) is stored in the comment line (like extxyz format).&lt;/p&gt;&#xA;&lt;p&gt;Can this be done with the help of ase ?&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="7628" LastActivityDate="2023-07-28T09:58:24.583" Title="How do you write an .xyz file with the information of cell as comment in the Atomic Simulation Environment?" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11386" PostTypeId="1" AcceptedAnswerId="11403" CreationDate="2023-07-27T20:22:56.160" Score="3" ViewCount="412" Body="&lt;p&gt;I have a POSCAR file containing Co, Cr, Fe, Ni elements. It is a slab of 6 layers. The first 3 layers are mobile whiles the last three layers are fixed. I would like to add adsorbates at the FCC hollow sites. From my count, I would need 15 oxygen atoms at the different hollow sites. I don't want to include hcp hollow sites. How do I read the poscar file into ASE to maintain the surface and vacuum and only add the adsorbate? I have attached the poscar file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CoCrFeNi&#xA;   1.00000000000000     &#xA;     9.9633502299999996    0.0000000000000000    0.0000000000000000&#xA;    -4.9733836199999999    8.6618479100000005    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   40.4368920000000003&#xA;   Co   Cr   Fe   Ni&#xA;    24    24    24    24&#xA;Selective dynamics&#xA;Direct&#xA;  0.5612360243849388  0.9099052137287840  0.6250221820654160   T   T   T&#xA;  0.2356071120850486  0.2518526753215678  0.5772064214469697   T   T   T&#xA;  0.2348146468815286  0.7507696751875000  0.5764034425400485   T   T   T&#xA;  0.4860087088559321  0.5025000099364838  0.5766204786838768   T   T   T&#xA;  0.4832051517095323  0.9985833850246899  0.5770138532476135   T   T   T&#xA;  0.4854835901844644  0.7512215609776637  0.5763813008840900   T   T   T&#xA;  0.2355456895711744  0.9978683794875377  0.5777498674746212   T   T   T&#xA;  0.9867436499750243  0.5059613373927444  0.5769244369303035   T   T   T&#xA;  0.9038462779907266  0.5846022973376531  0.5260416228921621   T   T   T&#xA;  0.5716581887774268  0.9201204041921329  0.4758342950788617   F   F   F&#xA;  0.5741257856744610  0.4187527924396477  0.4757376011984320   F   F   F&#xA;  0.8221917385325952  0.1698063756466937  0.4754235315612263   F   F   F&#xA;  0.8188510224305006  0.6661687044098628  0.4754012746578056   F   F   F&#xA;  0.8238998402551019  0.4200678697901523  0.4748374331044047   F   F   F&#xA;  0.5727204154956951  0.6689043793196774  0.4747973706782389   F   F   F&#xA;  0.3230897361863398  0.1691307692332842  0.4746252506250954   F   F   F&#xA;  0.2362167951761762  0.2470966960213019  0.4240635012206155   F   F   F&#xA;  0.9075250613866288  0.5865598256619577  0.3747389883475734   F   F   F&#xA;  0.9099926467579991  0.0851921908197042  0.3746422944671437   F   F   F&#xA;  0.1580586012731757  0.8362458075069128  0.3743282248299380   F   F   F&#xA;  0.1547179181243052  0.3326081258796876  0.3743059679265173   F   F   F&#xA;  0.1597667301860781  0.0865072797151001  0.3737421263731164   F   F   F&#xA;  0.9085872881049042  0.3353438007895022  0.3737020639469506   F   F   F&#xA;  0.6589565758423106  0.8355702010934962  0.3735299438938071   F   F   F&#xA;  0.8058501908443986  0.1604085948745253  0.6276226743697434   T   T   T&#xA;  0.0711651015373968  0.1740917158429164  0.6283794021117671   T   T   T&#xA;  0.5585537014512123  0.1589400490967113  0.6274647415475056   T   T   T&#xA;  0.8408195288613217  0.4120066169412361  0.6276226664037110   T   T   T&#xA;  0.8218106695859454  0.6771528044496808  0.6304296582071180   T   T   T&#xA;  0.0835097517099495  0.4214918947625969  0.6290440423670955   T   T   T&#xA;  0.2375735696515378  0.5010054481380813  0.5770179622858687   T   T   T&#xA;  0.7358517176793846  0.5001337489919461  0.5753017076229778   T   T   T&#xA;  0.1526774569984566  0.8311508061347753  0.5260862055103875   T   T   T&#xA;  0.4012780008378368  0.8374455841948802  0.5256159156652330   T   T   T&#xA;  0.9015458337759297  0.8318449292366887  0.5267321752290328   T   T   T&#xA;  0.1650345374797721  0.0820828245082830  0.5266625182108280   T   T   T&#xA;  0.1530715796942058  0.3284398123835934  0.5256954404458725   T   T   T&#xA;  0.4037759574840217  0.0881761973292648  0.5266741240986712   T   T   T&#xA;  0.5719291831091056  0.1671338512338281  0.4751517500405313   F   F   F&#xA;  0.0726206267831913  0.1688011628918105  0.4750530777686848   F   F   F&#xA;  0.4902349088201277  0.5006121147652394  0.4250452779605283   F   F   F&#xA;  0.7387644569889744  0.5022689205818693  0.4249752923642092   F   F   F&#xA;  0.2384726428149762  0.4987219869114483  0.4248748889998737   F   F   F&#xA;  0.4894111111794288  0.7512741008171346  0.4248244400187815   F   F   F&#xA;  0.4908000549497729  0.0025951829486672  0.4244191170775409   F   F   F&#xA;  0.7393419908448990  0.7494893777233287  0.4241708289549067   F   F   F&#xA;  0.9077960227650834  0.8335732830940472  0.3740564433092430   F   F   F&#xA;  0.4084875035752731  0.8352405947520296  0.3739577710373965   F   F   F&#xA;  0.0714088580284006  0.9241042308280607  0.6266688247630529   T   T   T&#xA;  0.0712936348301734  0.6734806713146717  0.6264448440732556   T   T   T&#xA;  0.5661143764171257  0.6694797179385326  0.6276482980086926   T   T   T&#xA;  0.5826565215444279  0.4197094481854535  0.6248967461469209   T   T   T&#xA;  0.9863437963371268  0.0049281853325266  0.5778527630146324   T   T   T&#xA;  0.7299839656132034  0.7483226508951495  0.5771810032009886   T   T   T&#xA;  0.9822818352016206  0.7481102940128979  0.5771714159167410   T   T   T&#xA;  0.4836853691620328  0.2504096534801669  0.5765478188719351   T   T   T&#xA;  0.4023001272576696  0.5849271527966273  0.5256599968038801   T   T   T&#xA;  0.4052342653716023  0.3382546586388231  0.5252451653467152   T   T   T&#xA;  0.9035134348127880  0.3352264766627390  0.5263625912611249   T   T   T&#xA;  0.9027949755174263  0.0791523962176613  0.5260593633310788   T   T   T&#xA;  0.3232407866261937  0.6702789128053368  0.4755137956695563   F   F   F&#xA;  0.0665275574938846  0.4173909583226560  0.4755078604953127   F   F   F&#xA;  0.3245013047405436  0.4173221508342095  0.4749788880906110   F   F   F&#xA;  0.8209027016053341  0.9159207229719186  0.4747226864023091   F   F   F&#xA;  0.7400046718620530  0.2526014105458927  0.4255408650100989   F   F   F&#xA;  0.7373990205197032  0.9972170014700694  0.4251333163785205   F   F   F&#xA;  0.2401126400303042  0.0008789443175559  0.4246560294495438   F   F   F&#xA;  0.2420278484524303  0.7522265534676222  0.4244614051940516   F   F   F&#xA;  0.6591076592354028  0.3367183342751616  0.3744184889382680   F   F   F&#xA;  0.4023944301030866  0.0838303797924809  0.3744125537640244   F   F   F&#xA;  0.6603682004010807  0.0837616184835568  0.3738835813593226   F   F   F&#xA;  0.1567695396708118  0.5823600289929374  0.3736276269699488   F   F   F&#xA;  0.8139283773437237  0.9179970463961956  0.6264927519830703   T   T   T&#xA;  0.3316971715924403  0.4206428344420928  0.6270248681347872   T   T   T&#xA;  0.3156932809260076  0.9156706536874418  0.6266447810285281   T   T   T&#xA;  0.3193842754680041  0.6705125009466922  0.6268440812499967   T   T   T&#xA;  0.3204197280025719  0.1699424665767754  0.6272751272551228   T   T   T&#xA;  0.7346622986391906  0.2521520822199035  0.5767044378177472   T   T   T&#xA;  0.7337753457319838 -0.0000484138730764  0.5764088122275434   T   T   T&#xA;  0.9859905944062034  0.2532340884891014  0.5767699223686655   T   T   T&#xA;  0.1520510767833566  0.5824068293232663  0.5262650644687904   T   T   T&#xA;  0.6539763846918202  0.0840366980125778  0.5258262367600025   T   T   T&#xA;  0.6540657686858518  0.5846162808349679  0.5256774417697333   T   T   T&#xA;  0.6542669891634135  0.3357645143656891  0.5254505398702217   T   T   T&#xA;  0.6510606874754463  0.8330745611877558  0.5256560801844358   T   T   T&#xA;  0.0765196813155740  0.9206583956286494  0.4765519565648120   F   F   F&#xA;  0.0658167894639234  0.6668927993218503  0.4761879325443701   F   F   F&#xA;  0.3165218299266357  0.9183686994568774  0.4733637787988272   F   F   F&#xA;  0.4845041515414152  0.2488359322854947  0.4251788193810739   F   F   F&#xA;  0.9902804335043385  0.7510055668940936  0.4248024304142888   F   F   F&#xA;  0.9888284822195317  0.2504328201717385  0.4244866296845942   F   F   F&#xA;  0.9943961297937989  0.9996431581306737  0.4242620822589416   F   F   F&#xA;  0.9866011241072812  0.4984118914182147  0.4231390978317506   F   F   F&#xA;  0.4123865539247760  0.5870978170984742  0.3754566498335237   F   F   F&#xA;  0.4016836620731254  0.3333322207916751  0.3750926258130818   F   F   F&#xA;  0.6523887025358377  0.5848081209267022  0.3722684720675389   F   F   F&#xA; &#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3442" LastEditorUserId="3442" LastEditDate="2023-07-30T05:41:20.650" LastActivityDate="2023-12-16T11:33:28.010" Title="How to read a poscar file which is a surface and add adsorbates using ASE" Tags="|surfaces|atomic-simulation-environment|adsorption|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11387" PostTypeId="1" CreationDate="2023-07-27T23:33:57.517" Score="1" ViewCount="47" Body="&lt;p&gt;What types of pseudopotential should I use for calculating optical properties in Quantum ESPRESSO?&lt;/p&gt;&#xA;" OwnerUserId="7614" LastEditorUserId="5" LastEditDate="2023-07-28T01:29:04.603" LastActivityDate="2023-07-28T01:29:04.603" Title="Types of pseudopotential for calculating optical properties?" Tags="|quantum-espresso|one-topic-per-answer|pseudopotentials|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:22:32.827" ContentLicense="CC BY-SA 4.0" />
  <row Id="11388" PostTypeId="2" ParentId="11381" CreationDate="2023-07-27T23:40:01.683" Score="4" Body="&lt;p&gt;To be honest, this gets into a few corners of OpenPathSampling (OPS) where I'm not terribly familiar with the underlying code. From playing around a bit, I suspect that part of the confusion might be that the &lt;code&gt;allow_incomplete&lt;/code&gt; parameter isn't doing what I would expect it to do (possibly a bug, but I didn't write that code, and it isn't well-documented what the intended use was).&lt;/p&gt;&#xA;&lt;p&gt;That said, I don't think you want &lt;code&gt;allow_incomplete=True&lt;/code&gt;, anyway. If you want to calculate this collective variable (CV) for all snapshots, then you want to have the complete list of values for snapshots in your storage. Below is something that seems to work for me (caveat that I'm using an MDTraj CV, not a PLUMED CV, but that shouldn't make a difference). One thing that might make a difference: versions of &lt;code&gt;netcdf4&lt;/code&gt; (mine is 1.6.0) and &lt;code&gt;libnetcdf&lt;/code&gt; (mine is 4.8.1).&lt;/p&gt;&#xA;&lt;p&gt;The main differences with your approach are that, instead of working with the &lt;code&gt;storage.cvs&lt;/code&gt; object, I enable disk caching on my CV itself, and I calculate the CV before saving things. Then I let the default &lt;code&gt;Storage.save&lt;/code&gt; method do the rest of the work for me. This is similar to what happens under the hood when you do a transition path sampling (TPS) step: after the TPS step, the whole &lt;code&gt;MCStep&lt;/code&gt; object is sent to &lt;code&gt;save&lt;/code&gt;. Any new information is extracted and saved.&lt;/p&gt;&#xA;&lt;p&gt;If I understand, the story here is &amp;quot;I ran some TPS, and decided later that there was a second CV that would be interesting to analyze as well.&amp;quot; This is a very common use case. I'll try to simulate that with two scripts: the two scripts are very similar, but the first gets its data from a trajectory that hasn't been saved by OPS yet, whereas the second loops over all snapshots in an OPS storage file.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# assumes you have OpenPathSampling, MDTraj, and OpenMM installed&#xA;import openpathsampling as paths&#xA;import mdtraj as md&#xA;&#xA;# let's load up a tiny trajectory that is in the OPS test suite&#xA;from openpathsampling.tests.test_helpers import data_filename&#xA;from openpathsampling.engines.openmm.tools import ops_load_trajectory&#xA;traj = ops_load_trajectory(data_filename(&amp;quot;ala_small_traj.pdb&amp;quot;))&#xA;&#xA;# create a CV and enable disk caching on it&#xA;cv = paths.MDTrajFunctionCV(&amp;quot;phi&amp;quot;, md.compute_dihedrals, traj[0].topology, indices=[[4, 6, 8, 14]])&#xA;cv.enable_diskcache()  # defaults to allow_incomplete=False&#xA;&#xA;st1 = paths.Storage(&amp;quot;foo.nc&amp;quot;, mode='w')&#xA;cv(traj)&#xA;&#xA;# save the trajectory and the CV itself&#xA;st1.save(traj)&#xA;st1.save(cv)&#xA;st1.sync()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then we see that this variable has 10 entries (current shape, one for each snapshot) in the NetCDF file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;st1.vars['cv0_value']&#xA;# &amp;lt;class 'netCDF4._netCDF4.Variable'&amp;gt;&#xA;# float32 cv0_value(snapshots)&#xA;#     var_type: numpy.float32&#xA;# unlimited dimensions: snapshots&#xA;# current shape = (10,)&#xA;# filling on, default _FillValue of 9.969209968386869e+36 used&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now let's do the second stage. (If you're playing along at home in a single process [notebook], you'll need to do &lt;code&gt;st1.close()&lt;/code&gt; before the next part.) Overall, this is very similar, but now we'll loop over all the snapshots in the storage file.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import openpathsampling as paths&#xA;import mdtraj as md&#xA;&#xA;st2 = paths.Storage(&amp;quot;foo.nc&amp;quot;)&#xA;&#xA;st2.snapshots&#xA;# store.snapshots[BaseSnapshot] : 20 object(s)&#xA;# 20 because there are &amp;quot;ghost&amp;quot; snapshots representing velocity-reversed versions&#xA;&#xA;[cv.name for cv in st2.cvs]&#xA;# ['phi']&#xA;&#xA;top = st2.snapshots[0].topology&#xA;cv1 = paths.MDTrajFunctionCV(&amp;quot;psi&amp;quot;, md.compute_dihedrals, top, indices=[[6, 8, 14, 16]])&#xA;cv1.enable_diskcache()&#xA;&#xA;cv1(st2.snapshots)&#xA;&#xA;st2.save(cv1)&#xA;st2.sync()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And then we'll have a &lt;code&gt;cv1_value&lt;/code&gt; in addition to our &lt;code&gt;cv0_value&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;st2.vars['cv1_value']&#xA;# &amp;lt;class 'netCDF4._netCDF4.Variable'&amp;gt;&#xA;# float32 cv1_value(snapshots)&#xA;#     var_type: numpy.float32&#xA;# unlimited dimensions: snapshots&#xA;# current shape = (10,)&#xA;# filling on, default _FillValue of 9.969209968386869e+36 used&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;[NB: all of this is based on the &lt;code&gt;netcdfplus&lt;/code&gt; storage subsystem. OPS is migrating to a different storage subsystem, &lt;code&gt;simstore&lt;/code&gt;, in the future, precisely because of some of the challenges in maintaining &lt;code&gt;netcdfplus&lt;/code&gt;.]&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;UPDATE:&lt;/strong&gt; From comments and updates to the question, it is clear that this use case requires only storing CV results for &lt;em&gt;some&lt;/em&gt; snapshots in a single run (useful if, e.g., the CV is very expensive to calculate). The solution above works if you're doing all snapshots at once; update below gives a way to only fill in some.&lt;/p&gt;&#xA;&lt;p&gt;NB: This is all a bit experimental. This, or something very close to it should work, but I'd recommend storing an unedited copy of your nc file before doing this; just in case. The following assumes you've run the code blocks with &lt;code&gt;st1&lt;/code&gt; above.&lt;/p&gt;&#xA;&lt;h4&gt;Preparation, once per CV you want to add&lt;/h4&gt;&#xA;&lt;p&gt;In this, we will create and save the CV, without applying it to any snapshots.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import openpathsampling as paths&#xA;import mdtraj as md&#xA;&#xA;st2 = paths.Storage(&amp;quot;foo.nc&amp;quot;)&#xA;[cv.name for cv in st2.cvs]  # so far we only have the phi CV&#xA;# ['phi']&#xA;&#xA;# create and save the other CV (psi)&#xA;top = st2.snapshots[0].topology&#xA;cv1 = paths.MDTrajFunctionCV(&amp;quot;psi&amp;quot;, md.compute_dihedrals, top, indices=[[6, 8, 14, 16]])&#xA;cv1.with_diskcache(allow_incomplete=True)&#xA;st2.save(cv1)&#xA;&#xA;st2.close()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h4&gt;Main script: run for each slice of snapshots&lt;/h4&gt;&#xA;&lt;p&gt;In this part, we'll load up a CV and populate its disk cache with some snapshots. We'll use Python's &lt;code&gt;slice&lt;/code&gt; explicitly; the more famliar colon notation (e.g., &lt;code&gt;some_list[:5]&lt;/code&gt;, &lt;code&gt;some_list[5:]&lt;/code&gt;) is just a shorthand for the &lt;code&gt;slice&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;def save_partial_cv(storage, cv, snapshots_slice):&#xA;    &amp;quot;&amp;quot;&amp;quot;Do the main work of saving a block of CV results to disk&amp;quot;&amp;quot;&amp;quot;&#xA;    cv = cv.with_diskcache(allow_incomplete=True)&#xA;    cv(storage.snapshots[snapshots_slice])&#xA;    &#xA;    # get a mapping of saved snapshot index to CV value&#xA;    cache = dict(cv._cache_dict.cache)&#xA;    idx_to_cv_value = {storage.snapshots.idx(s): val for s, val in cache.items()}&#xA;&#xA;    # gets the label &amp;quot;cv{num}&amp;quot; for this cv&#xA;    store_name = cv._cache_dict.passing_chain[1].value_store.name&#xA;&#xA;    nc_idx_var = storage.vars[f&amp;quot;{store_name}_index&amp;quot;]&#xA;    nc_val_var = storage.vars[f&amp;quot;{store_name}_value&amp;quot;]&#xA;&#xA;    existing = len(nc_idx_var)&#xA;    nc_idx_var.variable[existing::] = list(idx_to_cv_value.keys())&#xA;    nc_val_var.variable[existing::] = list(idx_to_cv_value.values())&#xA;&#xA;    storage.sync()&#xA;&#xA;# this is the part that the script that will run for each section will do&#xA;import openpathsampling as paths&#xA;st3 = paths.Storage(&amp;quot;foo.nc&amp;quot;)&#xA;psi = st3.cvs['psi']&#xA;&#xA;save_partial_cv(st3, psi, slice(0, 3))  # save st2.snapshots[0:3]&#xA;&#xA;# Just to make like we did another block, let's use save_partial again.&#xA;# In practice, you'll probably run each slice in a separate script.&#xA;save_partial_cv(st3, psi, slice(6, None))  # save st2.snapshots[6:]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As a hack to prove it worked (for this toy demo), you can change the &lt;code&gt;cv_callable&lt;/code&gt; for the CV (e.g., so that all snapshots return 0.0), and call &lt;code&gt;cv(storage.snapshots)&lt;/code&gt; to show that we're returning the results from disk, not from evaluating the CV function.&lt;/p&gt;&#xA;" OwnerUserId="2004" LastEditorUserId="2004" LastEditDate="2023-08-08T14:48:26.113" LastActivityDate="2023-08-08T14:48:26.113" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11389" PostTypeId="2" ParentId="11385" CreationDate="2023-07-28T03:46:14.540" Score="4" Body="&lt;p&gt;You can do this by writing an &amp;quot;.extxyz&amp;quot; file but forcing the name to be &amp;quot;.xyz&amp;quot;. In this way, the cell information is stored as comment. To remove the extra columns, you need to specify &lt;code&gt;write_results=False&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;&#xA;atoms = read('OUTCAR')&#xA;write('structure.xyz', atoms, format='extxyz', write_results=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that &lt;code&gt;ase.io.write&lt;/code&gt; writes to an &amp;quot;.extxyz&amp;quot; file by default, no matter you specify the filename to be &amp;quot;.xyz&amp;quot; or &amp;quot;.extxyz&amp;quot;. So you will get the same result simply by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;write('structure.xyz', atoms, write_results=False)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It only writes to a plain &amp;quot;.xyz&amp;quot; file if you do &lt;code&gt;ase.io.xyz.write_xyz()&lt;/code&gt; or &lt;code&gt;ase.io.write(..., format='xyz')&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-07-28T03:46:14.540" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11390" PostTypeId="1" AcceptedAnswerId="11392" CreationDate="2023-07-28T06:19:29.180" Score="6" ViewCount="493" Body="&lt;p&gt;In classical molecular dynamics simulations of complex molecular systems, the force field (FF) contains information about bonded (bonds, angles, dihedrals and impropers) and non-bonded parameters. It is well known that energies of bonded interactions vary with temperature, with higher energies progressively shifting the molecule to higher vibrational states. However, we predominantly consider &lt;strong&gt;temperature-independent&lt;/strong&gt; FFs and use them to be run over a range of temperatures, for eg. 300 to 400 K in bio-molecular systems or even a larger range of temperatures in systems ionic liquids or deep eutectic solvents.&lt;/p&gt;&#xA;&lt;p&gt;My question is, how much information are we losing by considering a &lt;strong&gt;temperature-independent FF&lt;/strong&gt; in such systems?&lt;/p&gt;&#xA;&lt;p&gt;Moreover, why do temperature-independent FFs work so well for systems that involve conformational transitions (like lipid bilayer melting etc.), when these transitions are strongly dependent on the temperature induced changes in the interaction of the system?&lt;/p&gt;&#xA;&lt;p&gt;Are there examples that provide instances of failure of these &lt;strong&gt;temperature-independent FFs&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="5103" LastEditorUserId="6468" LastEditDate="2023-07-28T07:35:05.777" LastActivityDate="2023-07-28T07:47:13.740" Title="Effect of temperature on Forcefield parameters in classical molecular dynamics simulations" Tags="|molecular-dynamics|forcefields|thermodynamics|phase-transitions|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11391" PostTypeId="2" ParentId="11390" CreationDate="2023-07-28T07:32:37.887" Score="7" Body="&lt;p&gt;The answer to&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;how much information are we losing by considering a temperature-independent forcefield in such systems?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is, to a first approximation, &lt;em&gt;none&lt;/em&gt;. The reason is that the statement&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;transitions are strongly dependent on the temperature induced changes in the interaction of the system&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;is actually exactly backwards.&lt;/p&gt;&#xA;&lt;p&gt;Temperature-induced phase transitions happen because a system's internal interaction energies &lt;em&gt;do not&lt;/em&gt; change with temperature. Now, in the canonical ensemble, the probability difference between microstates is inversely exponential in the energy divided by the temperature. Thus, because interaction energies &lt;em&gt;do not&lt;/em&gt; change with temperature, as temperature increases, the probability difference between lower- and higher-energy microstates decreases, so that less ordered phases become entropy-preferred relative to more ordered phases.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;To make this concrete, consider lipid bilayer melting. A lipid bilayer is held in place because interactions between all of the lipids' tails, and interactions between the lipids' heads and water, stabilize the system, and the bilayer arrangement is an easy enough way to accommodate everyone's preferences.&lt;/p&gt;&#xA;&lt;p&gt;But let's say we take a thermal sledgehammer to the system and heat it up to 1000 K. Well, then, every molecule's (on average) got the kinetic energy to bounce from its pot right to the roof and back. Who cares about alkane dispersion interactions and water dipoles and any of that jazz any more? Mind you, the &lt;em&gt;interaction&lt;/em&gt; energies haven't changed -- but the &lt;em&gt;thermal&lt;/em&gt; energies have rendered them irrelevant. You know as well as I do that we end up with a cloud of vapour, whether in real life or in a (proper) simulation.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Now, when you ask&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Are there examples that provide instances of failure of these temperature-independent forcefields?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;of course they fail. &lt;a href=&quot;http://www.sklogwiki.org/SklogWiki/index.php/SPC/E_model_of_water&quot; rel=&quot;noreferrer&quot;&gt;SPC/E water&lt;/a&gt; &lt;a href=&quot;https://pubmed.ncbi.nlm.nih.gov/15836229/&quot; rel=&quot;noreferrer&quot;&gt;freezes at -58 °C&lt;/a&gt; and &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article-abstract/146/6/064505/315826&quot; rel=&quot;noreferrer&quot;&gt;boils at 123 °C&lt;/a&gt;, which are clearly not the correct freezing point and boiling point. However, it &lt;em&gt;does&lt;/em&gt; freeze, and it &lt;em&gt;does&lt;/em&gt; boil, and nobody set out to say &amp;quot;hey let's make a model of water that freezes and boils&amp;quot; or inserted special switches at those temperatures to suddenly change the interactions involved.&lt;/p&gt;&#xA;&lt;p&gt;Instead, the reason molecular dynamics models fail to predict the &lt;em&gt;correct&lt;/em&gt; transition points of everyday substances is that the potentials used simply cannot be accurate enough. Molecular dynamics atoms are balls on sticks with point charges and two-term equations for forces. Real life atoms are infinitely more complicated. So the exact temperatures at which the interatomic forces lose to entropy will be &amp;quot;wrong&amp;quot; if the interatomic forces themselves are &amp;quot;wrong&amp;quot; in the first place. But when the interatomic forces have the correct &lt;em&gt;qualitative&lt;/em&gt; features, then applying temperature correctly in a molecular dynamics simulation must yield qualitatively correct phase transitions. This whole matter of correct &lt;em&gt;thermostatting&lt;/em&gt; is an entire field in itself, but it is almost never done by meddling with the force field parameters in an arbitrary way.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-07-28T07:32:37.887" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11392" PostTypeId="2" ParentId="11390" CreationDate="2023-07-28T07:47:13.740" Score="7" Body="&lt;p&gt;I have reasonable experience with the parameterization and MD simulations of molecules with CHARMM FF, which is one of the temperature-agnostic FF. I will try to answer the questions, but please note that my answers would be strictly based on how CHARMM FF works, but the basic reasoning should carry over to other FFs.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How much information are we losing by considering a temperature-independent forcefield in such systems?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Ans: None, because when you perform a classical MD simulation, the first approximation is that you are looking at temperatures that are much lower than the ones that are required to break bonds. For eg: the bond-dissociation energy of a C-H bond in CH&lt;span class=&quot;math-container&quot;&gt;$_4$&lt;/span&gt; molecule would never be reached in a classical MD simulation, and you are guaranteed to stay in the harmonic approximation regime. However, if you are interested in such high energies, then temperature-agnostic FFs might not be suitable for your use case.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Moreover, why do temperature-independent FFs work so well for systems that involve conformational transitions (like lipid bilayer melting etc.), when these transitions are strongly dependent on the temperature induced changes in the interaction of the system?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Ans: The conformational dynamics of these systems are largely based on the dihedral and torsional parameters, and they are generally much more accessible (due to the lower spring constants associated with them). This means that a simulation at 298K would be able to sufficiently sample the conformational space available to the system, without any problems.&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Are there examples that provide instances of failure of these temperature-independent FFs?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Ans: There are many. For example, the famous TIP-3P water model will never freeze, even if you lower the temperature. This lead to the creation of a TIP-4P water model which was aimed at introducing the directional nature of the Hbonding in the ice formation. This was subsequently revised to TIP-5P where explicit lone pairs were introduced to further improve the directional nature of the Hbonding in water. You may also refer to TIP-4P-ICE model, which was specifically parameterized to reproduce the ice-structure.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-28T07:47:13.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11393" PostTypeId="2" ParentId="11384" CreationDate="2023-07-28T09:38:50.573" Score="1" Body="&lt;p&gt;The most likely culprit is using &lt;code&gt;tail yes&lt;/code&gt;. That adds a correction energy which theoretically accounts for the truncation of the LJ parameter, but is only designed to work for systems of near-uniform density which is very different from what you are doing.&lt;/p&gt;&#xA;&lt;p&gt;Please note that without us knowing your data file or the potential profile you are observing, it is impossible to rule out any additional issues.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-07-28T09:38:50.573" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11394" PostTypeId="1" CreationDate="2023-07-28T09:57:20.013" Score="3" ViewCount="433" Body="&lt;p&gt;I am repeatedly getting the error message:&#xA;[file orca_main/maininp1.cpp, line 17547]: ERROR: expect a '$', '!', '%', '*' or '[' in the input&#xA;when I run my Orca script.&lt;/p&gt;&#xA;&lt;p&gt;My inp file looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!RHF STEOM-DLPNO-CCSD def2-TZVP def2/J RIJCOSX TIGHTPNO TightSCF&#xA;&#xA;%pal&#xA;nprocs 4&#xA;end&#xA;&#xA;%maxcore 6000&#xA;&#xA;%mdci&#xA;nroots 5&#xA;dotriplet true&#xA;Othresh 5.0e-3&#xA;Vthresh 5.0e-3&#xA;TCutPNOSingles 6.6e-10&#xA;end&#xA;&#xA;* xyzfile 0 1 dabna1_freq_inp_gs.xyz&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and my PBS file looks like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#PBS -N Dabna1DSC&#xA;#PBS -l walltime=47:58:00&#xA;#PBS -l select=1:ncpus=32:mem=256GB&#xA;&#xA;module load orca/5.0.3&#xA;&#xA;cd &amp;quot;${PBS_O_WORKDIR}&amp;quot;&#xA;&#xA;/apps/orca/5.0.3/bin/orca dabna1dsc.sh&amp;gt;dabna1_final.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The xyz file I am using is just one calculated from a previous geometry optimization. Does anyone have any idea of the issue? I am getting the same issue with a few more scripts I am running, which are scripts that I have run previously and have worked fine.&lt;/p&gt;&#xA;" OwnerUserId="7608" LastEditorUserId="6468" LastEditDate="2023-07-28T10:20:04.757" LastActivityDate="2023-07-28T10:21:32.527" Title="Repeated Error message ORCA" Tags="|quantum-chemistry|orca|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11396" PostTypeId="1" AcceptedAnswerId="11398" CreationDate="2023-07-28T10:07:00.790" Score="2" ViewCount="401" Body="&lt;p&gt;The format of xyz file is as follow.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1st line:66&#xA;&#xA;2nd line:Atoms. Timestep: 18424000&#xA;&#xA;3rd line:C  5.41744 2.36649 8.39936&#xA;&#xA;4th line:O  5.39564 2.39851 9.67522&#xA;&#xA;5th line:Pt -0.0287758 0.341863 -0.0621366&#xA;&#xA;.....&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With the help of ase.io.read, I want to load this xyz file by the following command.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;all_atoms = read('accum.xyz', format='xyz',index=&amp;quot;:&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If I print the all_atoms, the coordinate was absent.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;&#xA;[Atoms(symbols='COPt64', pbc=False), &#xA;Atoms(symbols='COPt64', pbc=False), &#xA;Atoms(symbols='COPt64', pbc=False), &#xA;Atoms(symbols='COPt64', pbc=False), &#xA;Atoms(symbols='COPt64', pbc=False), &#xA;Atoms(symbols='COPt64', pbc=False), &#xA;....&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hence, I wonder what is wrong?&lt;/p&gt;&#xA;&lt;p&gt;thanks.&lt;/p&gt;&#xA;" OwnerUserId="7628" LastEditorUserId="6687" LastEditDate="2023-07-29T06:26:30.287" LastActivityDate="2023-07-29T06:26:30.287" Title="How can I load the xyz file correctly by ase?" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11397" PostTypeId="2" ParentId="11394" CreationDate="2023-07-28T10:21:32.527" Score="4" Body="&lt;p&gt;There were few errors in your input file, and I have modified your input file according to the &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/geometry-input?authuser=0&quot; rel=&quot;nofollow noreferrer&quot;&gt;ORCA Input Library&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!RHF STEOM-DLPNO-CCSD def2-TZVP def2/J RIJCOSX TIGHTPNO TightSCF&#xA;&#xA;%pal&#xA;    nprocs 4&#xA;end&#xA;&#xA;%maxcore 6000&#xA;&#xA;%mdci&#xA;nroots 5&#xA;dotriplet true&#xA;Othresh 5.0e-3&#xA;Vthresh 5.0e-3&#xA;TCutPNOSingles 6.6e-10&#xA;end&#xA;&#xA;* xyzfile 0 1 dabna1_freq_inp_gs.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I could not test this input file since I do not have access to the corresponding .xyz file.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-07-28T10:21:32.527" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11398" PostTypeId="2" ParentId="11396" CreationDate="2023-07-28T13:18:36.117" Score="3" Body="&lt;p&gt;There are couple things I want to address.&lt;/p&gt;&#xA;&lt;p&gt;First, the coordinates are not lost. It just doesn't show up when you print the &lt;code&gt;ase.Atoms&lt;/code&gt; object. To print out the coordinates, you should do&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(atoms.positions)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Second, I want to notice you that there is no unit cell information in your xyz file so ASE thinks your system is non-periodic. However, based on your description, I think you are modelling a Pt surface slab with a CO* adsorbate. In this case, you must include the unit cell information to make it a reasonable structure. Suppose your unit cell is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;cell = [[10.0, 0.0, 0.0], &#xA;        [0.0, 10.0, 0.0], &#xA;        [0.0, 0.0, 20.0]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can do the following&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for atoms in all_atoms:&#xA;    atoms.cell = cell&#xA;    atoms.pbc = True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-07-28T13:48:52.347" LastActivityDate="2023-07-28T13:48:52.347" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11399" PostTypeId="1" CreationDate="2023-07-28T15:11:20.030" Score="5" ViewCount="77" Body="&lt;p&gt;I am having trouble with a difficult convergence in Gaussian16. I am running two separate PES scans for hindered rotors in my molecule that will eventually be used in subsequent rate calculations. I decided to back down the optimization convergence criteria for one of the scans from verytight to tight, as looking at the criteria in the failed runs shows that it is getting very close but not close enough to finally converge, at which point the displacement and RMS displacement begin to increase.&lt;/p&gt;&#xA;&lt;p&gt;I've also thought about changing the SCF algorithm or increasing my integration grid, however, the grid is already at ultrafine and I am trying to minimize the use of SUs.&lt;/p&gt;&#xA;&lt;p&gt;The issue is that I already have the other PES scan that has been running for a while and is using the opt=verytight criteria and I'm worried that using both PES scans together for the rate calculation might not be valid. However, since they are both using the same model chemistry, (i.e. functional, basis set, integration grid, etc) just with different convergence thresholds, it may not be the worst thing in the world (Albeit, not ideal).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My Question&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Is it valid or invalid to calculate the PES of two hindered rotors on the same molecule with different convergence criteria?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;My Rationale&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;If someone can confirm/reject the following, that would be great also:&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm currently under the impression that since this is not a direct comparison between&lt;br /&gt;&#xA;two energies, rather, the optimization is being done to find the PES for a rotor, its&#xA;not that big of a deal.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerDisplayName="user1441" LastEditorUserId="5" LastEditDate="2023-07-30T08:34:16.177" LastActivityDate="2023-07-30T17:54:58.130" Title="Using Hindered Rotor Scans With Different Convergence Criteria from Gaussian" Tags="|gaussian|self-consistent-field|potential-energy-surface|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11400" PostTypeId="1" CreationDate="2023-07-29T09:04:47.477" Score="1" ViewCount="150" Body="&lt;p&gt;I recently came across a new PhD student who works in a materials modeling group which mainly focuses on applications (doing DFT-based studies on different solid/electrolyte interfaces). To my surprise, he actually did his master thesis in a well-known group which mainly focuses on theory and method development, where he was involved in the development of some deep learning models for representing the DFT Hamiltonian. He claimed that he had the opportunity to stay in that group to do a PhD but eventually he decided to switch to application-focused groups. He also said that he made the decision not because he found method development too difficult for him. His reasoning for the switch is that he is determined to go to industry after PhD. In his view, an application-focused group makes it easier to publish on high-impact journals due to the higher chance of collaborating with experimental groups. Industry would favor people with publications that provide practical values rather than theories and methods.&lt;/p&gt;&#xA;&lt;p&gt;Personally, it's hard for me to understand his decision. I think it's not a bold statement to say that it requires more skills to work on theory/methodology than applications, and most people who work on theory/methodology are adequate to do applications as well. Is it true that the industry weighs the &amp;quot;practical values&amp;quot; more than individual skills? Is it true that theory/methodology-focused groups are more suitable for people who want to stay in academia? &lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="5" LastEditDate="2023-07-29T17:30:07.603" LastActivityDate="2023-07-29T17:30:07.603" Title="Research groups focused on applications vs. theory/methodology" Tags="|education|soft-question|publishing|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11401" PostTypeId="2" ParentId="11382" CreationDate="2023-07-29T16:44:17.683" Score="1" Body="&lt;p&gt;If you change the first file 'MoS2.dyn0' which should only contains information about the q-point grid to accommodate it to the fact you are missing some files things should work out.&lt;/p&gt;&#xA;&lt;p&gt;For example recently I have done a ph calculation asking for 3x3x1 q-point grid, under symmetry the grid was reduced to 5 q-point, ph.x produced 5 + 1 files, matdyn0 contained:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   3   3   1&#xA;   5&#xA;   0.000000000000000E+00   0.000000000000000E+00   0.000000000000000E+00&#xA;   0.957767067711528E-06   0.386248692995345E+00   0.000000000000000E+00&#xA;   0.334502600762572E+00   0.193123787186512E+00   0.000000000000000E+00&#xA;   0.334503558529640E+00   0.579372480181857E+00   0.000000000000000E+00&#xA;   0.334501642995505E+00  -0.193124905808834E+00   0.000000000000000E+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you delete the two last lines and change the second line to '3' q2r.x shouldn't complain and run. Changing the first line should not affect the result but I would be happy to be proved otherwise.&lt;/p&gt;&#xA;" OwnerUserId="3934" LastActivityDate="2023-07-29T16:44:17.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11402" PostTypeId="2" ParentId="11400" CreationDate="2023-07-29T17:29:39.527" Score="2" Body="&lt;h1&gt;Reasons why he switched groups for his PhD&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;His reasoning for the switch is that he is determined to go to industry after PhD. In his view, an application-focused group makes it easier to publish on high-impact journals due to the higher chance of collaborating with experimental groups. Personally, it's hard for me to understand his decision.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is what he told you was his reason for the switch, and it was what he was capable of putting into words at the time. The decision to switch groups, and the decision of where to embark on a PhD program (a program which usually constitutes more than 5-10% of a person's entire years of life, and can have significant implications for the remainder of their life) almost always involves more than one factor. &lt;strong&gt;Dozens or hundreds of micro-factors play a role in where people land&lt;/strong&gt;, and these are almost never articulated (he's not even aware of them all). You mentioned his desire to publish in high-impact journals, but surely there's other groups that publish in high-impact journals just as often or more often: &lt;strong&gt;Why didn't he go to those places?&lt;/strong&gt; I can think of several possible reasons.&lt;/p&gt;&#xA;&lt;h1&gt;What requires more skills: theory or applications?&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I think it's not a bold statement to say that it requires more skills to work on theory/methodology than applications, and most people who work on theory/methodology are adequate to do applications as well.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I think that's an extremely bold statement. &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11400/research-groups-focused-on-applications-vs-theory-methodology#comment24329_11400&quot;&gt;Okano's comment&lt;/a&gt; touches on this. You probably know far more than us about what his former group (which focuses on theory/methodology) does, and what his new group (which focuses on applications) does: The rest of us don't know the names of those groups, and therefore don't know why one would require more skills than the other, but in &lt;em&gt;&lt;strong&gt;general&lt;/strong&gt;&lt;/em&gt; there's theory/methodology projects being done successfully at undergrad-only colleges, and there's application projects whose success involves decades of post-PhD expertise (and there's &lt;em&gt;vice versa&lt;/em&gt; examples).&lt;/p&gt;&#xA;&lt;h1&gt;What skills do industry groups value?&lt;/h1&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is it true that the industry weighs the &amp;quot;practical values&amp;quot; more than individual skills?  Is it true that theory/methodology-focused groups are more suitable for people who want to stay in academia?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This will depend strongly on the group in industry doing the hiring. You mentioned &amp;quot;high-impact journals&amp;quot;, but the &lt;em&gt;vast majority&lt;/em&gt; of people working in industry (or academia) do not have papers in high-impact journals like Science, Nature or even PRL or JACS.  Industry (and academia) both value &amp;quot;practical skills&amp;quot; and the ability to &lt;em&gt;apply&lt;/em&gt; science to achieve practical outcomes. In countries that have enough money, far more academic positions are available for experimentalists than theorists, and publishing application-based papers in high-impact journals is extremely valued in academia (as well as in industry).&lt;/p&gt;&#xA;&lt;p&gt;People focusing on pure theory/methodology, rarely secure academic positions without making a strong case in their research proposal and interview about the potential practical applications (and it's the papers by the application-focused groups that serve as &amp;quot;validation&amp;quot; that the theorist is doing useful work; if the pure theorist has some such papers in their portfolio, it would be to their benefit). You said &amp;quot;he actually did his master thesis in a well-known group&amp;quot;, and it's hard to comment without knowing the group, but academia and industry have both changed a lot since most such groups became well-known.&lt;/p&gt;&#xA;&lt;p&gt;However, there's groups in industry that may specifically want someone that can help develop theory/methodology. Such job availability might in some cases be even more prevalent in industry than in academia (where money is tight, and mostly funded by tax-payers, and so there's more and more pressure to do things that directly benefit the tax-payers; whereas in industry a billion-dollar company might have the freedom to spend more of their money as they want, without the pressures that exist in academia).&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2023-07-29T17:29:39.527" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11403" PostTypeId="2" ParentId="11386" CreationDate="2023-07-30T06:23:30.180" Score="5" Body="&lt;p&gt;I remember running into exactly the same issue like you when I just started my PhD. In ASE, there is this &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#ase.build.add_adsorbate&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.build.add_adsorbate()&lt;/code&gt;&lt;/a&gt; function that allows placing a single adsorbate on a surface site. However, this function has the following limitations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the clean surface slab must be generated by &lt;code&gt;ase.build&lt;/code&gt;;&lt;/li&gt;&#xA;&lt;li&gt;only allow one pre-defined position for each type of site;&lt;/li&gt;&#xA;&lt;li&gt;for alloy systems it does not differentiate two sites of the same type (e.g. bridge) but different elemental compositions (e.g. AA, BB and AB);&lt;/li&gt;&#xA;&lt;li&gt;limited number of supported surfaces;&lt;/li&gt;&#xA;&lt;li&gt;nanoparticles/clusters are not supported.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I then looked into other codes with similar functions, e.g. &lt;a href=&quot;https://pymatgen.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymatgen&lt;/a&gt;, &lt;a href=&quot;https://catkit.readthedocs.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CatKit&lt;/a&gt;, etc, but to the best of my knowledge, they all require a pre-defined bulk/surface structure to identify adsorption sites. So I decided to develop a code by myself, namely &lt;a href=&quot;https://asm-dtu.gitlab.io/acat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACAT&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;ACAT overcomes all aforementioned limitations, providing a general way of identifying adsorption sites on an &lt;em&gt;arbitrary&lt;/em&gt; surface structure (i.e. any &lt;code&gt;ase.Atoms&lt;/code&gt; object) that can represent a wide variety of surfaces and nanoparticles. In detail, ACAT implements the adsorption site identification for 20 common low-index surfaces (including fcc, bcc and hcp crystal structures) in &lt;code&gt;acat.adsorption_sites.SlabAdsorptionSites&lt;/code&gt; and for 3 common nanoparticle motifs (fcc, icosahedron, and decahedron) in &lt;code&gt;acat.adsorption_sites.ClusterAdsorptionSites&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Let's come back to your question. You can first read the POSCAR using ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from ase.visualize import view&#xA;&#xA;atoms = read('POSCAR')&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And your clean alloy fcc(111) surface looks like this&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VrDXk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VrDXk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can then use ACAT to identify all high-symmetry adsorption sites on the fcc(111) surface, i.e. ontop, bridge, fcc and hcp sites.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.adsorption_sites import SlabAdsorptionSites&#xA;&#xA;sas = SlabAdsorptionSites(atoms, surface='fcc111')&#xA;sites = sas.get_sites()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This &lt;code&gt;sites&lt;/code&gt; object is a list of dictionaries. Each dictionary stores the information of one site. If you print out one dictionary, you will see something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;print(sites[0])&#xA;# {'site': 'ontop', 'surface': 'fcc111', 'morphology': 'terrace', 'position': array([ 1.06648339,  7.88146057, 25.27395447]), 'normal': array([-0.00176619, -0.00244269,  0.99999546]), 'indices': (0,), 'composition': None, 'subsurf_index': None, 'subsurf_element': None, 'label': None}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where the 'site', 'surface', 'morphology', 'position', 'normal', 'indices' and 'composition' keys contain information of the type, the locating surface, the local geometric environment, the Cartesian coordinate, the normal vector, the atomic indices and the elemental composition of the site, respectively.&lt;/p&gt;&#xA;&lt;p&gt;Now that we want to add adsorbates to specific sites, e.g. adding O to all fcc sites as you requested, we can just use a for loop with the &lt;code&gt;acat.build.add_adsorbate_to_site&lt;/code&gt; function (you can change the &lt;code&gt;height&lt;/code&gt; parameter to adjust the bond distance between the adsorbates and the surface):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.build import add_adsorbate_to_site&#xA;&#xA;for st in sites:&#xA;    if st['site'] == 'fcc':&#xA;        add_adsorbate_to_site(atoms, adsorbate='O', site=st, height=1.)&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Just like that, you get the structure you want&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/O2PT1.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/O2PT1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code can be installed simply by &lt;code&gt;pip install acat&lt;/code&gt;. For more usage of the ACAT package, I strongly recommend this &lt;a href=&quot;https://gitlab.com/asm-dtu/acat/-/blob/master/notebooks/acat_tutorial.ipynb&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jupyter notebook tutorial&lt;/a&gt;. Remember to cite if you find the code useful for your research :)&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-12-16T11:33:28.010" LastActivityDate="2023-12-16T11:33:28.010" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11404" PostTypeId="2" ParentId="11399" CreationDate="2023-07-30T17:54:58.130" Score="4" Body="&lt;p&gt;That’s a bit up to interpretation… I guess it depends on what you want to get out of the scans &lt;em&gt;exactly&lt;/em&gt; (i.e., are the geometries important, or just the energies on those geometries?). If you want the scan points themselves (the geometries), I would say that the convergence criteria is probably quite important. If you’re more interested in the potential energy curve itself, the geometry just has to be ‘good enough’ for the energy to be ‘accurate’. That being said… you can still say that &lt;em&gt;all&lt;/em&gt; your scans were converged to &lt;code&gt;tight&lt;/code&gt; criteria. So, in that sense, it actually depends on whether you think it’s important that they’re optimised to &lt;code&gt;vtight&lt;/code&gt; or not. And &lt;em&gt;that&lt;/em&gt; depends on the exact nature of the calculation.&lt;/p&gt;&#xA;&lt;p&gt;All this being said, an alternative solution would be to calculate the PES geometries using one method and then calculate energies on the resulting geometries at a different (higher) level of theory. You get the best of both worlds, that way.&lt;/p&gt;&#xA;" OwnerUserId="7606" LastActivityDate="2023-07-30T17:54:58.130" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11405" PostTypeId="1" AcceptedAnswerId="11406" CreationDate="2023-07-30T19:14:29.177" Score="6" ViewCount="476" Body="&lt;p&gt;I want to calculate the Gibbs free energy of adsorption for an oxidized surface. The literature I consulted used the equations attached to this post. I am trying hard to find my way through. Any idea how to go about it would be deeply appreciated. I am supposed to have a linear plot with pressure as abscissa and delta G as ordinate. &lt;a href=&quot;https://i.stack.imgur.com/QNVqU.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/QNVqU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-09-17T23:32:45.373" Title="How to calculate Gibbs free energy of adsorption at constant temperature with varying pressures" Tags="|free-energy|adsorption|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11406" PostTypeId="2" ParentId="11405" CreationDate="2023-07-31T05:56:58.797" Score="9" Body="&lt;p&gt;IMO the equations you show use too many &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;&amp;quot; which makes it more confusing. I will hence try to avoid the use of &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$\Delta$&lt;/span&gt;&amp;quot; in the equations below.&lt;/p&gt;&#xA;&lt;p&gt;To get the adsorption free energy for the oxidized surface, you need to calculate&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    G_{\mathrm{ads}} = G_{\mathrm{slab(oxidized)}} - G_{\mathrm{slab}} - N_{\mathrm{O}}\mu_{\mathrm{O}}(T,p)&#xA;\tag{1} \label{1}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;To avoid computationally expensive phonon calculations, the common assumption is that the free energy corrections for the surface and the oxidized surface will cancel out by &lt;span class=&quot;math-container&quot;&gt;$G_{\mathrm{slab(oxidized)}} - G_{\mathrm{slab}}$&lt;/span&gt;, except for the vibrational free energy term for the oxygens adsorbed on the surface, &lt;span class=&quot;math-container&quot;&gt;$F^{\mathrm{vib}}_{\mathrm{O*}}$&lt;/span&gt;. We can then rewrite the equation as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    G_{\mathrm{ads}} = E_{\mathrm{slab(oxidized)}} + F^{\mathrm{vib}}_{\mathrm{O*}} - E_{\mathrm{slab}} - N_{\mathrm{O}}\mu_{\mathrm{O}}(T,p) \tag{2} \label{2}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; represents the electronic energy which can be calculated by e.g. DFT.&lt;/p&gt;&#xA;&lt;p&gt;In general, we can calculate &lt;span class=&quot;math-container&quot;&gt;$F^{\mathrm{vib}}$&lt;/span&gt; by&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;F^{\mathrm{vib}} = E^{\mathrm{ZPE}} + \int_0^TC_V\mathrm{d}T - TS&#xA;\tag{3} \label{3}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E^{\mathrm{ZPE}}$&lt;/span&gt; is the zero-point energy, &lt;span class=&quot;math-container&quot;&gt;$C_V$&lt;/span&gt; is the heat capacity which is separable into translational, rotational, vibrational and electronic parts, &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is the entropy which is separable into translational, rotational, vibrational and configurational parts. You can calculate these terms in the harmonic limit using e.g. &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html#ase.thermochemistry.HarmonicThermo&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.thermochemistry.HarmonicThermo&lt;/code&gt;&lt;/a&gt;. Note that this could be expensive if you have high O* coverage. A simplification would be to calculate using only one O* adsorbate, and multiply the single-O* vibrational free energy term by the number of O*.&lt;/p&gt;&#xA;&lt;p&gt;Next, we can assume the oxidized surface is in equilibrium with the gas phase O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, and calculate &lt;span class=&quot;math-container&quot;&gt;$\mu_{\mathrm{O}}(T,p)$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$\mu_{\mathrm{O_2(g)}}(T,p) / 2$&lt;/span&gt;. The &lt;span class=&quot;math-container&quot;&gt;$\mu_{\mathrm{O_2(g)}}(T,p)$&lt;/span&gt; term can then be determined in the ideal gas limit by&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \mu_{\mathrm{O_2(g)}}(T, p) = E_{\mathrm{O_2(g)}} + \Delta\mu_{\mathrm{O_2(g)}}^{0,T} + k_{\mathrm{B}}T\ln(p_{\mathrm{O_2(g)}}/p^0) \tag{4} \label{4}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{O_2(g)}}$&lt;/span&gt; is the electronic energy of the O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; molecule which can be calculated by DFT, &lt;span class=&quot;math-container&quot;&gt;$\Delta\mu^{0,T}_{\mathrm{O_2(g)}}$&lt;/span&gt; is the chemical potential correction term (including zero-point energy) obtained from vibrational calculations at standard pressure &lt;span class=&quot;math-container&quot;&gt;$p^0=1$&lt;/span&gt; atm, &lt;span class=&quot;math-container&quot;&gt;$k_{\mathrm{B}}$&lt;/span&gt; is the Boltzmann constant, and &lt;span class=&quot;math-container&quot;&gt;$p_{\mathrm{O_2(g)}}$&lt;/span&gt; is the fugacity of the gas phase O&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In general, we can calculate &lt;span class=&quot;math-container&quot;&gt;$\Delta\mu^{0,T}$&lt;/span&gt; as&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\Delta\mu^{0,T} = E^{\mathrm{ZPE}} + \int_0^TC_P\mathrm{d}T - TS \tag{5} \label{5}&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$C_P = C_V + k_{\mathrm{B}}$&lt;/span&gt; (switching from constant-volume to constant-pressure). These terms can again be calculated by ASE using &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html#ase.thermochemistry.IdealGasThermo&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.thermochemistry.IdealGasThermo&lt;/code&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It is not hard to see that the adsorption free energy &lt;span class=&quot;math-container&quot;&gt;$G_{\mathrm{ads}}$&lt;/span&gt; is effectively a function of &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_{\mathrm{O_2(g)}}$&lt;/span&gt;. At constant temperature and various pressures, the expensive terms only need to be calculated once.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="7" LastEditDate="2023-09-17T23:32:45.373" LastActivityDate="2023-09-17T23:32:45.373" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="11407" PostTypeId="1" CreationDate="2023-07-31T10:39:48.520" Score="2" ViewCount="62" Body="&lt;p&gt;How can I find the HR factor like we calculate the Debye waller factor as - log(IZpl/Itotal), from the intensity profile of the PL spectra.&lt;/p&gt;&#xA;" OwnerUserId="6976" LastEditorUserId="5" LastEditDate="2023-07-31T14:19:52.110" LastActivityDate="2023-07-31T14:19:52.110" Title="How to Find the Huang-Rhys factor from the Intensity Vs Wavelength plot (PL plot)?" Tags="|physical-properties-of-materials|spectroscopy|photoluminescence|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11408" PostTypeId="1" AcceptedAnswerId="11442" CreationDate="2023-07-31T16:06:19.463" Score="4" ViewCount="119" Body="&lt;p&gt;I want to calculate the work of separation between layers of a structure as I have attached from the literature. I know how to calculate at the interface but How about a layer below the interface or at different layers other than the interface? The literature only provided the equation for calculating at the interface but not beneath the interface.&#xA;Where the up and bottom layers are metal and oxide layers. Thank you.&lt;a href=&quot;https://i.stack.imgur.com/KAnW2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KAnW2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;a href=&quot;https://i.stack.imgur.com/kPpjj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kPpjj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-08-05T17:31:52.873" Title="Work of Separation" Tags="|metal-oxide|solid-solid-interface|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11409" PostTypeId="1" CreationDate="2023-07-31T17:59:22.427" Score="1" ViewCount="12" Body="&lt;p&gt;I have read that for a particular alloy system, a specific precipitate has a low barrier strength to plastic deformation in comparison to dislocation loops. However this precipitate gives the largest contribution to embrittlement. How could this be?&lt;/p&gt;&#xA;" OwnerUserId="7642" LastActivityDate="2023-07-31T17:59:22.427" Title="why can a defect have a lower barrier strength compared with another defect but still have a larger effect on embrittlement?" Tags="|physical-properties-of-materials|" AnswerCount="0" CommentCount="3" ClosedDate="2023-09-02T22:17:31.907" ContentLicense="CC BY-SA 4.0" />
  <row Id="11410" PostTypeId="1" CreationDate="2023-07-31T18:31:10.110" Score="1" ViewCount="129" Body="&lt;p&gt;I want to calculate the electrical properties of cubic perovskite by varying the pressure.&lt;/p&gt;&#xA;&lt;p&gt;For this can anyone tell me how to choose the parameters in the &amp;amp;cell section :&#xA;&amp;amp;CELL like&#xA;cell_dofree    = ????&#xA;cell_dynamics  = &amp;quot;bfgs&amp;quot;&#xA;press          =  0.00000e+00 (Targated Pressure)&#xA;press_conv_thr =  ????&lt;/p&gt;&#xA;" OwnerUserId="7614" LastEditorUserId="7614" LastEditDate="2023-07-31T23:35:56.047" LastActivityDate="2023-07-31T23:35:56.047" Title="How to calculate pressure effect in quantum espresso?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="3" ClosedDate="2023-08-01T13:38:49.690" ContentLicense="CC BY-SA 4.0" />
  <row Id="11411" PostTypeId="1" CreationDate="2023-08-01T01:10:39.723" Score="3" ViewCount="63" Body="&lt;p&gt;I am trying to run a g09 calculation for a D5h symmetric molecule using the HF/LANL2DZ level of theory. The molecule is pentagonal planar in geometry, and I would like to visualize the canonical orbitals and the basis functions used to generate the canonical orbitals.&lt;/p&gt;&#xA;&lt;p&gt;I have gotten the calculation to converge easily, however I would like to have a visualization of the basis functions to reflect the D5h symmetry of the structure.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to run the calculation such that the py basis functions of the terminal atoms in the pentagonal planar geometry point towards the center of the molecule? If so, what should I add to the route section of my gaussian input file?&lt;/p&gt;&#xA;&lt;p&gt;Any help is appreciated!&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-08-01T01:10:39.723" Title="How to choose the orientation of basis functions in a Gaussian calculation?" Tags="|computational-chemistry|gaussian|basis-sets|hartree-fock|software-input-file-request|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11412" PostTypeId="1" CreationDate="2023-08-01T06:01:30.760" Score="2" ViewCount="138" Body="&lt;p&gt;I am trying to generate a 50-50 Pt-Au fcc(111) bimetallic surface in ASE for DFT calcualtions. However, I am unable to figure out the procedure. Any help regarding the procedure will be great. Thanks&lt;/p&gt;&#xA;" OwnerUserId="7646" LastEditorUserId="3770" LastEditDate="2023-08-01T08:47:08.083" LastActivityDate="2023-08-31T13:06:00.783" Title="Generate a bimetallic surface in ASE" Tags="|density-functional-theory|surfaces|atomic-simulation-environment|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11413" PostTypeId="2" ParentId="11412" CreationDate="2023-08-01T08:46:06.297" Score="1" Body="&lt;p&gt;First you can generate a pure host metal surface slab using &lt;code&gt;ase.build&lt;/code&gt;, for example a 2x2x3 Pt(111) slab. Here you can directly insert the lattice parameter for your target alloy surface, e.g. 3.9 Å:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111&#xA;&#xA;atoms = fcc111('Pt', (2,2,3), a=3.9, vacuum=5.)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then can change half of the atoms into dopant atoms by visualizing the structure and note down the atom indices that you want to change to the dopant metal. For example, the dopant indices for a typical L1$_0$-ordered surface are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dopant_ids = [1, 3, 5, 7, 8, 10]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then change the Pt atoms with those indices to Au by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;for i, atom in enumerate(atoms):&#xA;    if i in dopant_ids:&#xA;        atom.symbol = 'Au'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the comment you said you want a 10x10x3 slab, you can simply expand the cell by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;atoms *= (5, 5, 1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now you get the 10x10x3 L1&lt;span class=&quot;math-container&quot;&gt;$_0$&lt;/span&gt;-ordered Pt&lt;span class=&quot;math-container&quot;&gt;$_{0.5}$&lt;/span&gt;Au&lt;span class=&quot;math-container&quot;&gt;$_{0.5}$&lt;/span&gt;(111) surface structure:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.visualize import view&#xA;&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/12lop.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/12lop.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-08-01T12:53:35.930" LastActivityDate="2023-08-01T12:53:35.930" CommentCount="17" ContentLicense="CC BY-SA 4.0" />
  <row Id="11414" PostTypeId="1" CreationDate="2023-08-01T12:24:22.717" Score="1" ViewCount="80" Body="&lt;p&gt;I have been trying to compile and install NWChem v6.8 from a source code on Linux Mint 21.2. According to instructions received from chatGPT, the following steps have to be done:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Install necessary packages&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;sudo apt install build-essential gfortran libopenblas-dev liblapack-dev libscalapack-openmpi-dev libfftw3-dev libblas-dev liblapack-dev libscalapack-openmpi-dev openmpi-bin&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Define environment variables&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;export NWCHEM_TOP=$PWD&#xA;export NWCHEM_TARGET=LINUX64&#xA;export NWCHEM_MODULES=&amp;quot;all python&amp;quot;&#xA;export PYTHONHOME=/usr/bin/python3&#xA;export PYTHONVERSION=3.10.12&#xA;export USE_MPI=y&#xA;export USE_MPIF=y&#xA;export USE_MPIF4=y&#xA;export MPI_LOC=/usr/lib/x86_64-linux-gnu/openmpi&#xA;export MPI_INCLUDE=$MPI_LOC/include&#xA;export MPI_LIB=$MPI_LOC/lib&#xA;export LIBMPI=&amp;quot;-lmpi_usempi -lmpi_mpifh -lmpi&amp;quot;&#xA;export BLASOPT=&amp;quot;-lopenblas -lpthread -lrt&amp;quot;&#xA;export LAPACK_LIB=&amp;quot;-llapack -lopenblas -lpthread -lrt&amp;quot;&#xA;export SCALAPACK_LIB=&amp;quot;-lscalapack -llapack -lopenblas -lpthread -lrt&amp;quot;&#xA;export USE_NOFSCHECK=TRUE&#xA;export CC=gcc&#xA;export FC=gfortran&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;Then I changed the current directory from &lt;code&gt;nwchem-6.8&lt;/code&gt; into &lt;code&gt;src&lt;/code&gt; being&#xA;a child in relation to the first and ran the command &lt;code&gt;make nwchem_config&lt;/code&gt;. As result, checking and configuring processed with ok-status until an error was thrown:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;checking for unistd.h... yes&#xA;checking minix/config.h usability... no&#xA;checking minix/config.h presence... no&#xA;checking for minix/config.h... no&#xA;checking whether it is safe to define __EXTENSIONS__... yes&#xA;checking whether a simple C MPI program compiles... yes&#xA;configure: searching for MPI_TS...&#xA;checking mpi.h usability... yes&#xA;checking mpi.h presence... yes&#xA;checking for mpi.h... yes&#xA;checking for library containing MPI_Init... no&#xA;configure: error: test for COMEX_NETWORK=MPI_TS failed&#xA;configure: error: ../../ga-5.6.3/comex/configure failed for comex&#xA;make[1]: *** [GNUmakefile:657: build/config.status] Error 1&#xA;make[1]: exit directory &amp;quot;/home/me/_/soft/nwchem-6.8/src/tools&amp;quot;&#xA;make: *** [GNUmakefile:103: libraries] Error 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(This is the several last strings of logging the process.)&lt;/p&gt;&#xA;&lt;p&gt;Something being not right with the &lt;code&gt;openmpi&lt;/code&gt; library can be supposed. I've checked it out with the following commands:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;locate mpi.h&#xA;locate openmpi&#xA;mpirun --version&#xA;mpicc --version&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It is all right. Then I've supposed that the &lt;code&gt;comex&lt;/code&gt; library is not installed, but in the internet I've not watched something resembling.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; what things could be done to get it working?&lt;/p&gt;&#xA;" OwnerUserId="5403" LastActivityDate="2023-08-01T12:24:22.717" Title="Is there a correct way for compiling and installing NWChem software with all modules from a source code on Linux Mint?" Tags="|software|nwchem|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11415" PostTypeId="1" CreationDate="2023-08-01T14:11:23.653" Score="6" ViewCount="100" Body="&lt;p&gt;To calculate the formation energy of a material AB with 2 atoms, I created a 2x2x2 supercell, resulting in a total of 16 atoms. Then, I removed one atom of type A from the supercell. From the calculations , I obtained the following energies (extracted from the output):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;-Total energy of the defect-containing supercell: Edefect =-5193.89497567 Ry (for 15 atoms)&#xA;-Total energy of the perfect crystal unit cell: Eperfect =-697.76209902 Ry (for 2 atoms)&#xA;-Total energy of the isolated A atom: Evacancy =-462.13675745 Ry (for 1 atom)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To determine the formation energy, I initially used the formula:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Eform=Edefect (supercell)−Eperfect (unit cell)+Evacancy&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Eform= (-5193.89497567/15) &#xA;- (-697.76209902/2) &#xA;+ (-462.13675745/1) &#xA;= -459.515372984667 Ry&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have doubts about the correctness of the formula I used. Could someone please review and correct my approach?&lt;/p&gt;&#xA;&lt;p&gt;PS: For my simulations I use Quantum ESPRESSO.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="6687" LastEditDate="2023-08-02T11:42:41.330" LastActivityDate="2024-03-13T04:43:55.020" Title="What is the procedure for calculating the formation energy of a doped material?" Tags="|density-functional-theory|defects|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11416" PostTypeId="1" CreationDate="2023-08-01T18:17:51.720" Score="2" ViewCount="51" Body="&lt;p&gt;I have an amorphous silica surface system with 576 atoms which was generated using BKS forcefield. I would like to relax the system with Reaxff. To do that I use the fixes in lammps as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix             1 mobile nve&#xA;fix             2 mobile qeq/reax 1 0.0 10.0 1.0e-6 reax/c&#xA;fix             3 mobile press/berendsen z 1.0 1.0 1000 modulus 360000&#xA;fix             4 mobile temp/berendsen 298.0 298.0 100.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;can someone point out whether I should use the pressure tensors in all lattice directions or having the z direction specified is enough? so that it physically makes sense!&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-08-01T18:17:51.720" Title="Relaxation of a system with a different Forcefield" Tags="|lammps|cell-optimization|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11418" PostTypeId="1" AcceptedAnswerId="11420" CreationDate="2023-08-02T00:13:19.350" Score="3" ViewCount="279" Body="&lt;p&gt;I am running a single point calculation on a fragment of a molecule using restricted open-shell theory. The fragment is in the triplet spin-state and of pentagonal planar structure (D5h). I ran the calculation with rohf/LANL2DZ and was able to achieve convergence quite easily, however with rob3ylp/LANL2DZ I keep running into the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Convergence failure -- run terminated.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have added the following keywords to the route section in an attempt to help convergence to no avail:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#P pop=full rob3lyp/LANL2DZ scf=(maxcycles=2048,tight,fermi) use=L506 symmetry=(loose) integral=(superfine) IOp(3/33=1) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Are there any other keywords that might be useful? I need to use the current geometry of the fragment (it is already optimized for the whole molecule), and if possible not change the basis set.&lt;/p&gt;&#xA;&lt;p&gt;Any help is greatly appreciated!&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="7643" LastEditorUserId="7" LastEditDate="2023-08-03T12:22:35.123" LastActivityDate="2023-08-03T12:22:35.123" Title="Advice on converging a restricted open-shell DFT (rob3lyp/LANL2DZ) single point Gaussian09 calculation for a triplet spin-state molecule?" Tags="|density-functional-theory|computational-chemistry|gaussian|self-consistent-field|software-input-file-request|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11419" PostTypeId="1" CreationDate="2023-08-02T03:57:29.110" Score="5" ViewCount="148" Body="&lt;p&gt;I have a question about the actual calculation of classical Coulomb interaction term in density functional theory (DFT) softwares.&lt;/p&gt;&#xA;&lt;p&gt;Of course I understand the form Coulomb energy as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\int\int \frac{\rho(r_i)\rho(r_j)}{|r_i - r_j|}dr_idr_j$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;but in the actual calculation, this term seems to be computationally expensive due to the distances between all grid points, &lt;span class=&quot;math-container&quot;&gt;$r_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r_j$&lt;/span&gt;, set in DFT softwares.&lt;/p&gt;&#xA;&lt;p&gt;In reality, in a practical calculation, such as that of PySCF, even a small molecule has a large number (e.g. over 100,000) of grid points, so the calculation of all grid distances appears to be very expensive.&lt;/p&gt;&#xA;&lt;p&gt;Does the actual calculations rely on specific technique for efficiently calculating the grid distances?&lt;/p&gt;&#xA;" OwnerUserId="3800" LastEditorUserId="3800" LastEditDate="2023-08-04T02:17:59.020" LastActivityDate="2023-08-04T02:17:59.020" Title="Actual calculation of Coulomb energy in DFT softwares" Tags="|density-functional-theory|software|ab-initio-calculations|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11420" PostTypeId="2" ParentId="11418" CreationDate="2023-08-02T11:20:55.910" Score="6" Body="&lt;p&gt;Before introducing solutions to solve this problem, let us analyze unnecessary keywords:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;pop=full IOp(3/33=1) use=L506&lt;/code&gt; does not affect the SCF convergence at all, but increases the output. Often there is no need to write these two keywords (unless you have some special calculation purposes, e.g. you need the AO overlap integrals).&lt;/p&gt;&#xA;&lt;p&gt;Increasing the SCF maxcycles will work only when the SCF is close to the convergence threshold and the electronic energy becomes lower gradually in the last few cycles. In such case 50 extra cycles would usually be sufficient. &lt;code&gt;maxcycles=2048&lt;/code&gt; seems crazy and it is possible that the user did not monitor the SCF procedure. One can monitor the SCF convergence by running&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep 'Delta-E=' xxx.log&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in Linux command line.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;integral=(superfine)&lt;/code&gt; usually does some help. I don't think &lt;code&gt;symmetry=(loose)&lt;/code&gt;  or &lt;code&gt;scf=fermi&lt;/code&gt; would be useful.&lt;/p&gt;&#xA;&lt;p&gt;Using the basis set and ECP LANL2DZ for all atoms is not recommended. For non-metal atoms (H, C, etc), better basis sets like 6-311G(d,p) or def2-TZVP are recommended. If your molecule is large, you can use 6-31G(d) or def2-SVP. While for transition metal atoms, def2-TZVP or cc-pVTZ(-PP) is recommended. If you insist on using the LANL2, you can use LANL2TZ(f), which is much more accurate than LANL2DZ.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Here comes the solutions:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(1)&lt;/strong&gt; Reading molecular orbitals (MOs) from a previous job. For example, reading MOs of ROHF/LANL2DZ. You can also read MOs from another density functional (e.g. BLYP) if SCF can be converged using that functional. The Gaussian input is like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%oldchk=previous_job.chk&#xA;%chk=current_job.chk&#xA;#p ROB3LYP/LANL2DZ guess=read geom=allcheck (other keywords you want)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that &lt;code&gt;%oldchk&lt;/code&gt; can only be used in Gaussian16. For Gaussian09 users, you need to copy/backup a previous chk file and use &lt;code&gt;%chk=&lt;/code&gt; to specify the filename. By specifying &lt;code&gt;geom=allcheck&lt;/code&gt;, Gaussian program will read Title Card, charge, spin multiplicity, and Cartesian coordinates from the previous chk file, so there is no need to write them in the gjf file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(2)&lt;/strong&gt; Try other keywords in Gaussian, e.g. scf(vshift=300).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(3)&lt;/strong&gt; Read converged ROB3LYP MOs of a smaller basis set. This trick is often used for cc-pVDZ -&amp;gt; cc-pVTZ, def2-SVP -&amp;gt; def2-TZVP, etc. Since you already use a small basis set LANL2DZ, this trick can hardly be used.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;(4)&lt;/strong&gt; Reading converged ROB3LYP MOs from other quantum chemistry packages, e.g. PySCF. Solutions (1), (2) and (3) require some trial and error. Using this solution, however, you will probably succeed by trying only once. Firstly, you need to install the PySCF and MOKIT packages:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;https://github.com/pyscf/pyscf&#xA;https://pyscf.org&#xA;https://gitlab.com/jxzou/mokit&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Both of these two packages can be installed via &lt;code&gt;conda install&lt;/code&gt; if connected to network. The we write a Python script (since you do not show coordinates of your molecule, let us take the triplet O2 as an example: O2.py):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import dft, lib&#xA;from mokit.lib.gaussian import load_mol_from_fch&#xA;from mokit.lib.py2fch_direct import fchk&#xA;&#xA;lib.num_threads(2) # 2 CPU cores&#xA;fchname = 'O2.fch'&#xA;mol = load_mol_from_fch(fchname)&#xA;&#xA;mf = dft.ROKS(mol)&#xA;mf.verbose = 4&#xA;mf.xc = 'b3lypg'&#xA;mf.grids.atom_grid = (99,590) # ultrafine&#xA;mf.kernel()&#xA;# SCF may not converged here. We add an orbital-optimization step using the second-order method&#xA;&#xA;mf = mf.newton()&#xA;mf.kernel()&#xA;fchk(mf, 'O2_ROB3LYP.fch')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Running this script is simple:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;python O2.py &amp;gt;O2.out 2&amp;gt;&amp;amp;1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you get the file &lt;code&gt;O2_ROB3LYP.fch&lt;/code&gt;. Run&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;unfchk O2_ROB3LYP.fch O2_ROB3LYP.chk&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to obtain the chk file. Now you obtain converged MOs from another package, this will make Gaussian SCF converge immediately (using &lt;code&gt;%chk&lt;/code&gt; to read MOs mentioned in Solution (1)).&lt;/p&gt;&#xA;&lt;p&gt;Moreover, you can do something that Gaussian does not support currently. For example, check the wave function stability of RODFT in PySCF, before transferring MOs to Gaussian:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mf.kernel()&#xA;mf.stability()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which makes your wave function more reliable.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastEditorUserId="5172" LastEditDate="2023-08-03T03:10:36.970" LastActivityDate="2023-08-03T03:10:36.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11421" PostTypeId="1" AcceptedAnswerId="11461" CreationDate="2023-08-02T11:41:18.890" Score="7" ViewCount="117" Body="&lt;p&gt;I have a collection of molecules represented by SMILES codes, along with their corresponding 3D coordinates. I want to efficiently generate figures for these structures using Avogadro. Ideally, I would like to set the visualization parameters (e.g., rendering style, orientation) once and then apply these settings to multiple molecules to ensure consistent and reproducible visualizations. In VMD, I am familiar with using state files to achieve this. How can I achieve a similar reproducibility feature in Avogadro for generating figures of multiple molecules with consistent visualization settings?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-08-10T16:36:28.373" Title="Is there a way to automate generation of figures from Avogadro?" Tags="|visualization-software|avogadro|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11422" PostTypeId="2" ParentId="11169" CreationDate="2023-08-02T12:20:00.353" Score="2" Body="&lt;p&gt;Yes, you can get what you want. If you have a Gaussian .fch file, you can visualize MOs using GaussView/Multiwfn/... any GUI you like. And you can plot PDOS by loading the .fch file in Multiwfn(&lt;a href=&quot;http://sobereva.com/482&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://sobereva.com/482&lt;/a&gt;). Here is one solution on how to generating a .fch file, or exporting MOs into it:&lt;/p&gt;&#xA;&lt;p&gt;Let us take the water(H2O) molecule as an example. Firstly, we perform a one-second job using Gaussian. The input file h2o.gjf is like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=1GB&#xA;%nprocshared=1&#xA;%chk=h2o.chk&#xA;#p RHF/cc-pVTZ nosymm int=nobasistransform guess(only,save)&#xA;&#xA;title&#xA;&#xA;0 1&#xA; O                  1.39830507    0.29275809    0.00000000&#xA; H                  2.35830507    0.29275809    0.00000000&#xA; H                  1.07785048    1.19769392    0.00000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This job takes less than 1 second since the keyword &lt;code&gt;guess(only)&lt;/code&gt; tells Gaussian program not to perform the SCF computation, but only generate the SCF initial guess.&lt;/p&gt;&#xA;&lt;p&gt;Then you obtain the file &lt;code&gt;h2o.chk&lt;/code&gt;. Run&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fch2inp h2o.chk&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or equivalently,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;formchk h2o.chk h2o.fch&#xA;fch2inp h2o.fch&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;you will get the GAMESS input file &lt;code&gt;h2o.inp&lt;/code&gt;, in which the charge, spin, Cartesian coordinates, basis sets and initial guess MOs of Gaussian are written. There is no need to change them. You can modify keywords within this file and perform computations you want.&lt;/p&gt;&#xA;&lt;p&gt;After your GAMESS job is accomplished, run&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;dat2fch h2o.dat h2o.fch&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;this will export MOs from &lt;code&gt;h2o.dat&lt;/code&gt; into &lt;code&gt;h2o.fch&lt;/code&gt;. Now you obtain a .fch file which includes MOs from GAMESS.&lt;/p&gt;&#xA;&lt;p&gt;(Here I assume that you perform single-point calculations in GAMESS, i.e. the geometry is not changed, so the same h2o.fch file is used.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;fch2inp&lt;/code&gt; and &lt;code&gt;dat2fch&lt;/code&gt; are two utilities in &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOKIT&lt;/a&gt;, free and open source. You can simply install MOKIT via &lt;code&gt;conda&lt;/code&gt; or download Linux &lt;a href=&quot;https://jeanwsr.gitlab.io/mokit-doc-mdbook/chap2-2.html#222-pre-built-linux-executables-and-libraries&quot; rel=&quot;nofollow noreferrer&quot;&gt;pre-built executables&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2023-08-02T12:20:00.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11423" PostTypeId="1" CreationDate="2023-08-02T14:13:26.527" Score="3" ViewCount="47" Body="&lt;p&gt;Suppose that we have a crystal material with a non-cubic unit cell. E.g. &lt;span class=&quot;math-container&quot;&gt;$\alpha \neq \beta \neq \gamma \neq 90^{\circ}$&lt;/span&gt;. Is it possible to find a supercell such that &lt;span class=&quot;math-container&quot;&gt;$\alpha = \beta = \gamma = 90^{\circ}$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;If no, can you explain why is not possible?&lt;/p&gt;&#xA;" OwnerUserId="6860" LastActivityDate="2023-08-02T14:13:26.527" Title="Is it possible to find a cubic supercell for a non-cubic crystal structure?" Tags="|molecular-dynamics|crystallography|periodic-system|periodic-boundary-conditions|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11424" PostTypeId="1" CreationDate="2023-08-02T15:41:35.797" Score="2" ViewCount="27" Body="&lt;p&gt;Suppose that we have an arbitrary (not necessarily cubic) unit cell with cell parameters &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{c}$&lt;/span&gt; (lattice vectors) and &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; (lattice angles).&lt;/p&gt;&#xA;&lt;p&gt;We have a particle at point &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt; and we want to calculate its interactions with the other particles inside a cutoff radius of &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. (E.g. interactions can be neglected outside this radius).&lt;/p&gt;&#xA;&lt;p&gt;How can I find scaled versions of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{a}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{b}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{c}$&lt;/span&gt; such that the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th particle interacts only with one periodic image of the (lets say) &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;-th particle?&lt;/p&gt;&#xA;&lt;p&gt;According to this &lt;a href=&quot;https://citeseerx.ist.psu.edu/doc/10.1.1.57.1696&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; an approach is the following (see p. 6). We define the perpendicular widths of the cell as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;W_a = \frac{|\mathbf{a} \cdot (\mathbf{b} \times \mathbf{c})|}{|\mathbf{b} \times \mathbf{c}|}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;W_b = \frac{|\mathbf{b} \cdot (\mathbf{c} \times \mathbf{a})|}{|\mathbf{c} \times \mathbf{a}|}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;W_c = \frac{|\mathbf{c} \cdot (\mathbf{a} \times \mathbf{b})|}{|\mathbf{a} \times \mathbf{b}|}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(&lt;span class=&quot;math-container&quot;&gt;$W_a, W_b, W_c$&lt;/span&gt; are merely the shortest distance between opposing faces of the unit cell.)&lt;/p&gt;&#xA;&lt;p&gt;and the condition to satisfy minimum image convention is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;r_c &amp;lt; \frac{1}{2} \min(W_a, W_b, W_c)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am not able to follow the explanation for the validity proposed in Appendix (p. 7). Can someone provide a graphical illustration of the proof?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Special case - cubic unit cell&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the unit cell is cubic, then the above equations reduces to:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;r_c &amp;lt; \frac{1}{2} L&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is the length of each side of the unit cell. Suppose that the distance between &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; particles is within the cutoff, that is &lt;span class=&quot;math-container&quot;&gt;$r_{ij} \leq r_c$&lt;/span&gt;. How do we prove that the distance between &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and a periodic image of &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;, call it &lt;span class=&quot;math-container&quot;&gt;$j^*$&lt;/span&gt;, is not within the cutoff?&lt;/p&gt;&#xA;&lt;p&gt;I am adding the following visualization so it is easier to state my problem.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/9sqtf.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9sqtf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6860" LastEditorUserId="6860" LastEditDate="2023-08-02T15:55:06.213" LastActivityDate="2023-08-02T15:55:06.213" Title="How to find the scaling factors for minimum image convention?" Tags="|crystallography|2d-lattice|periodic-system|periodic-boundary-conditions|minimum-image-convention|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11425" PostTypeId="1" CreationDate="2023-08-03T10:27:53.150" Score="1" ViewCount="71" Body="&lt;p&gt;I am trying to calculate the fluorescence spectra &lt;strong&gt;in solvent&lt;/strong&gt; with Gaussian16. I followed the example reported &lt;a href=&quot;https://gaussian.com/scrf/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; to calculate the value of the vertical emission. However, in the same link, I read:&#xA;&lt;em&gt;For the solvated band shape, one must do Freq=(ReadFC,FC,Emission,ReadFCHT) using the checkpoint files for steps 1 and 5, but also providing the state-specific emission energy in the input section for the Franck-Condon calculation.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have calculated the steps 1 and 5, but I don't know (and I don't find much in the manual) how to include the energy in the input section of the FC calculation. Does someone have any idea of the input keyword to use? Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-08-03T10:27:53.150" Title="Fluorescence solvated band shape in Gaussian16" Tags="|gaussian|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11426" PostTypeId="1" CreationDate="2023-08-03T10:40:49.497" Score="5" ViewCount="77" Body="&lt;p&gt;While reading the literature on the absorption spectra of materials from the MPX3 group (M= Mn,Ni,Co, Fe; layered antiferromagnets) I come across expressions such as d-d transitions, which are visible as weak transitions before the absorption edge (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.44.11060&quot; rel=&quot;nofollow noreferrer&quot;&gt;example DOI&lt;/a&gt;). These formulations and designations, as I understand it, come from the molecular theories of the crystal field. I calculated (DFT+U) the density of states for such materials and I do not see separated bands in the electronic structure composed of only d-states (which is not surprising), only bands that, for example, consist of half of the p-ligand states and the d-states of the transition metal.&#xA;Nowadays, in the literature on these crystalline materials, such peaks in the spectra are called d-d transitions that lie in the energy gap.&lt;/p&gt;&#xA;&lt;p&gt;What are these d-d transitions in a pure crystal?&#xA;Can they be captured with DFT?&#xA;In addition to the electronic structure of the crystal, do I need to consider any internal atomic levels of the transition metal itself in this case?&lt;/p&gt;&#xA;" OwnerUserId="1216" LastEditorUserId="7" LastEditDate="2023-08-09T13:20:06.323" LastActivityDate="2023-08-09T13:20:06.323" Title="d-d transitions in materials with transition metals in DFT" Tags="|density-functional-theory|transition-metals|dft-u|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11427" PostTypeId="1" CreationDate="2023-08-03T11:49:26.597" Score="1" ViewCount="64" Body="&lt;p&gt;I am trying to use Pyprocar to plot spin texture for studying rashba effect. Here is my input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;pyprocar.fermi2D(code='vasp', energy=1.0, spin_texture=True, no_arrow=True, arrow_projection='x', dir_name='./', color_bar=True, rotation=[90,1,0,0])&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To plot spin texture, I also generated 2d k-mesh with Pyprocar:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Generated by PyProcar&#xA;100&#xA;Reciprocal&#xA;0.0000000   0.0000000   0.0000000   1.0000000 &#xA;0.0000000   0.0000000   0.0555556   1.0000000 &#xA;0.0000000   0.0000000   0.1111111   1.0000000 &#xA;0.0000000   0.0000000   0.1666667   1.0000000 &#xA;0.0000000   0.0000000   0.2222222   1.0000000 &#xA;0.0000000   0.0000000   0.2777778   1.0000000 &#xA;0.0000000   0.0000000   0.3333333   1.0000000 &#xA;0.0000000   0.0000000   0.3888889   1.0000000 &#xA;0.0000000   0.0000000   0.4444444   1.0000000 &#xA;0.0000000   0.0000000   0.5000000   1.0000000 &#xA;0.0555556   0.0000000   0.0000000   1.0000000 &#xA;0.0555556   0.0000000   0.0555556   1.0000000 &#xA;0.0555556   0.0000000   0.1111111   1.0000000 &#xA;0.0555556   0.0000000   0.1666667   1.0000000 &#xA;0.0555556   0.0000000   0.2222222   1.0000000 &#xA;0.0555556   0.0000000   0.2777778   1.0000000 &#xA;0.0555556   0.0000000   0.3333333   1.0000000 &#xA;0.0555556   0.0000000   0.3888889   1.0000000 &#xA;0.0555556   0.0000000   0.4444444   1.0000000 &#xA;0.0555556   0.0000000   0.5000000   1.0000000 &#xA;0.1111111   0.0000000   0.0000000   1.0000000 &#xA;0.1111111   0.0000000   0.0555556   1.0000000 &#xA;0.1111111   0.0000000   0.1111111   1.0000000 &#xA;0.1111111   0.0000000   0.1666667   1.0000000 &#xA;0.1111111   0.0000000   0.2222222   1.0000000 &#xA;0.1111111   0.0000000   0.2777778   1.0000000 &#xA;0.1111111   0.0000000   0.3333333   1.0000000 &#xA;0.1111111   0.0000000   0.3888889   1.0000000 &#xA;0.1111111   0.0000000   0.4444444   1.0000000 &#xA;0.1111111   0.0000000   0.5000000   1.0000000 &#xA;0.1666667   0.0000000   0.0000000   1.0000000 &#xA;0.1666667   0.0000000   0.0555556   1.0000000 &#xA;0.1666667   0.0000000   0.1111111   1.0000000 &#xA;0.1666667   0.0000000   0.1666667   1.0000000 &#xA;0.1666667   0.0000000   0.2222222   1.0000000 &#xA;0.1666667   0.0000000   0.2777778   1.0000000 &#xA;0.1666667   0.0000000   0.3333333   1.0000000 &#xA;0.1666667   0.0000000   0.3888889   1.0000000 &#xA;0.1666667   0.0000000   0.4444444   1.0000000 &#xA;0.1666667   0.0000000   0.5000000   1.0000000 &#xA;0.2222222   0.0000000   0.0000000   1.0000000 &#xA;0.2222222   0.0000000   0.0555556   1.0000000 &#xA;0.2222222   0.0000000   0.1111111   1.0000000 &#xA;0.2222222   0.0000000   0.1666667   1.0000000 &#xA;0.2222222   0.0000000   0.2222222   1.0000000 &#xA;0.2222222   0.0000000   0.2777778   1.0000000 &#xA;0.2222222   0.0000000   0.3333333   1.0000000 &#xA;0.2222222   0.0000000   0.3888889   1.0000000 &#xA;0.2222222   0.0000000   0.4444444   1.0000000 &#xA;0.2222222   0.0000000   0.5000000   1.0000000 &#xA;0.2777778   0.0000000   0.0000000   1.0000000 &#xA;0.2777778   0.0000000   0.0555556   1.0000000 &#xA;0.2777778   0.0000000   0.1111111   1.0000000 &#xA;0.2777778   0.0000000   0.1666667   1.0000000 &#xA;0.2777778   0.0000000   0.2222222   1.0000000 &#xA;0.2777778   0.0000000   0.2777778   1.0000000 &#xA;0.2777778   0.0000000   0.3333333   1.0000000 &#xA;0.2777778   0.0000000   0.3888889   1.0000000 &#xA;0.2777778   0.0000000   0.4444444   1.0000000 &#xA;0.2777778   0.0000000   0.5000000   1.0000000 &#xA;0.3333333   0.0000000   0.0000000   1.0000000 &#xA;0.3333333   0.0000000   0.0555556   1.0000000 &#xA;0.3333333   0.0000000   0.1111111   1.0000000 &#xA;0.3333333   0.0000000   0.1666667   1.0000000 &#xA;0.3333333   0.0000000   0.2222222   1.0000000 &#xA;0.3333333   0.0000000   0.2777778   1.0000000 &#xA;0.3333333   0.0000000   0.3333333   1.0000000 &#xA;0.3333333   0.0000000   0.3888889   1.0000000 &#xA;0.3333333   0.0000000   0.4444444   1.0000000 &#xA;0.3333333   0.0000000   0.5000000   1.0000000 &#xA;0.3888889   0.0000000   0.0000000   1.0000000 &#xA;0.3888889   0.0000000   0.0555556   1.0000000 &#xA;0.3888889   0.0000000   0.1111111   1.0000000 &#xA;0.3888889   0.0000000   0.1666667   1.0000000 &#xA;0.3888889   0.0000000   0.2222222   1.0000000 &#xA;0.3888889   0.0000000   0.2777778   1.0000000 &#xA;0.3888889   0.0000000   0.3333333   1.0000000 &#xA;0.3888889   0.0000000   0.3888889   1.0000000 &#xA;0.3888889   0.0000000   0.4444444   1.0000000 &#xA;0.3888889   0.0000000   0.5000000   1.0000000 &#xA;0.4444444   0.0000000   0.0000000   1.0000000 &#xA;0.4444444   0.0000000   0.0555556   1.0000000 &#xA;0.4444444   0.0000000   0.1111111   1.0000000 &#xA;0.4444444   0.0000000   0.1666667   1.0000000 &#xA;0.4444444   0.0000000   0.2222222   1.0000000 &#xA;0.4444444   0.0000000   0.2777778   1.0000000 &#xA;0.4444444   0.0000000   0.3333333   1.0000000 &#xA;0.4444444   0.0000000   0.3888889   1.0000000 &#xA;0.4444444   0.0000000   0.4444444   1.0000000 &#xA;0.4444444   0.0000000   0.5000000   1.0000000 &#xA;0.5000000   0.0000000   0.0000000   1.0000000 &#xA;0.5000000   0.0000000   0.0555556   1.0000000 &#xA;0.5000000   0.0000000   0.1111111   1.0000000 &#xA;0.5000000   0.0000000   0.1666667   1.0000000 &#xA;0.5000000   0.0000000   0.2222222   1.0000000 &#xA;0.5000000   0.0000000   0.2777778   1.0000000 &#xA;0.5000000   0.0000000   0.3333333   1.0000000 &#xA;0.5000000   0.0000000   0.3888889   1.0000000 &#xA;0.5000000   0.0000000   0.4444444   1.0000000 &#xA;0.5000000   0.0000000   0.5000000   1.0000000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;2d plane is located at x-z plane which range from(0,0,0) to (0.5,0,0.5). Then I got this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last):&#xA;  File &amp;quot;/media/polyucmp/DATA/BIAN_Tieyuan/yinjun/plot_spin-new/n4-R-new/plot_spin.py&amp;quot;, line 14, in &amp;lt;module&amp;gt;&#xA;    spin_plot=pyprocar.fermi2D(code='vasp', energy=1.5, spin_texture=True, no_arrow=True, arrow_projection='y', dirname=data_dir, exportplt=True, color_bar=True, rotation=[90,1,0,0])&#xA;  File &amp;quot;/media/polyucmp/DATA/BIAN_Tieyuan/software/anaconda3/envs/vasp/lib/python3.9/site-packages/pyprocar/scripts/scriptFermi2D.py&amp;quot;, line 227, in fermi2D&#xA;    fs.spin_texture(sx=symm.sx, &#xA;  File &amp;quot;/media/polyucmp/DATA/BIAN_Tieyuan/software/anaconda3/envs/vasp/lib/python3.9/site-packages/pyprocar/core/fermisurface.py&amp;quot;, line 319, in spin_texture&#xA;    bnew.append(griddata((x, y), band, (xnew, ynew), method=&amp;quot;cubic&amp;quot;))&#xA;  File &amp;quot;/media/polyucmp/DATA/BIAN_Tieyuan/software/anaconda3/envs/vasp/lib/python3.9/site-packages/scipy/interpolate/_ndgriddata.py&amp;quot;, line 277, in griddata&#xA;    ip = CloughTocher2DInterpolator(points, values, fill_value=fill_value,&#xA;  File &amp;quot;interpnd.pyx&amp;quot;, line 915, in scipy.interpolate.interpnd.CloughTocher2DInterpolator.__init__&#xA;  File &amp;quot;_qhull.pyx&amp;quot;, line 1827, in scipy.spatial._qhull.Delaunay.__init__&#xA;  File &amp;quot;_qhull.pyx&amp;quot;, line 353, in scipy.spatial._qhull._Qhull.__init__&#xA;scipy.spatial._qhull.QhullError: QH6154 Qhull precision error: Initial simplex is flat (facet 1 is coplanar with the interior point)&#xA;&#xA;While executing:  | qhull d Qbb Q12 Qc Qz Qt&#xA;Options selected for Qhull 2019.1.r 2019/06/21:&#xA;  run-id 1834633720  delaunay  Qbbound-last  Q12-allow-wide  Qcoplanar-keep&#xA;  Qz-infinity-point  Qtriangulate  _pre-merge  _zero-centrum  Qinterior-keep&#xA;  Pgood  _max-width 0.35  Error-roundoff 4.9e-16  _one-merge 3.4e-15&#xA;  Visible-distance 9.8e-16  U-max-coplanar 9.8e-16  Width-outside 2e-15&#xA;  _wide-facet 5.9e-15  _maxoutside 3.9e-15&#xA;&#xA;The input to qhull appears to be less than 3 dimensional, or a&#xA;computation has overflowed.&#xA;&#xA;Qhull could not construct a clearly convex simplex from points:&#xA;- p1(v4): 0.039     0 0.0039&#xA;- p10(v3):  0.18     0  0.35&#xA;- p9(v2):  0.35     0  0.32&#xA;- p0(v1):     0     0     0&#xA;&#xA;The center point is coplanar with a facet, or a vertex is coplanar&#xA;with a neighboring facet.  The maximum round off error for&#xA;computing distances is 4.9e-16.  The center point, facets and distances&#xA;to the center point are as follows:&#xA;&#xA;center point   0.1417        0   0.1689&#xA;&#xA;facet p10 p9 p0 distance=    0&#xA;facet p1 p9 p0 distance=    0&#xA;facet p1 p10 p0 distance=    0&#xA;facet p1 p10 p9 distance=    0&#xA;&#xA;These points either have a maximum or minimum x-coordinate, or&#xA;they maximize the determinant for k coordinates.  Trial points&#xA;are first selected from points that maximize a coordinate.&#xA;&#xA;The min and max coordinates for each dimension are:&#xA;  0:         0    0.3519  difference= 0.3519&#xA;  1:         0         0  difference=    0&#xA;  2:         0    0.3519  difference= 0.3519&#xA;&#xA;If the input should be full dimensional, you have several options that&#xA;may determine an initial simplex:&#xA;  - use 'QJ'  to joggle the input and make it full dimensional&#xA;  - use 'QbB' to scale the points to the unit cube&#xA;  - use 'QR0' to randomly rotate the input for different maximum points&#xA;  - use 'Qs'  to search all points for the initial simplex&#xA;  - use 'En'  to specify a maximum roundoff error less than 4.9e-16.&#xA;  - trace execution with 'T3' to see the determinant for each point.&#xA;&#xA;If the input is lower dimensional:&#xA;  - use 'QJ' to joggle the input and make it full dimensional&#xA;  - use 'Qbk:0Bk:0' to delete coordinate k from the input.  You should&#xA;    pick the coordinate with the least range.  The hull will have the&#xA;    correct topology.&#xA;  - determine the flat containing the points, rotate the points&#xA;    into a coordinate plane, and delete the other coordinates.&#xA;  - add one or more points to make the input full dimensional.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I cannot figure out the problem. What may cause this? Can someone help me? Thanks!&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-08-03T11:49:26.597" Title="Pyprocar spin texture plot error" Tags="|vasp|pyprocar|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11431" PostTypeId="1" CreationDate="2023-08-03T22:05:45.347" Score="4" ViewCount="139" Body="&lt;p&gt;How to plot charge defect formation energy vs Fermi energy.&lt;/p&gt;&#xA;" OwnerUserId="6896" LastActivityDate="2024-03-16T17:45:00.817" Title="How to plot charge defect formation energy diagram" Tags="|density-functional-theory|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11432" PostTypeId="1" CreationDate="2023-08-03T23:22:04.697" Score="6" ViewCount="121" Body="&lt;p&gt;Is there any Python package that allows to cut defined by the points (0, 0, 0) and (x, y, z)?&#xA;That is, it should return all the atoms of the unit cell and periodic images inside the shaded region.&lt;/p&gt;&#xA;&lt;p&gt;(For sake of simplicity the image is for 2D).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uhY8Q.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uhY8Q.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;An example&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have attached a real example from the &lt;code&gt;ZnMOF-74.cif&lt;/code&gt;. I want the substructure defined by the red box. And a link for the &lt;a href=&quot;https://github.com/iRASPA/RASPA2/blob/master/structures/mofs/cif/ZnMOF-74.cif&quot; rel=&quot;noreferrer&quot;&gt;cif file&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RVx87.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RVx87.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6860" LastEditorUserId="6860" LastEditDate="2023-08-04T11:34:28.937" LastActivityDate="2023-08-05T18:55:07.267" Title="Is there any Python library for returning the atoms of a periodic material within a cube?" Tags="|software|python|molecular-modeling|periodic-system|pymatgen|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11434" PostTypeId="1" CreationDate="2023-08-04T02:40:17.630" Score="4" ViewCount="252" Body="&lt;p&gt;I was trying to follow this recipe, &lt;a href=&quot;https://www.youtube.com/watch?v=thjofOhm38M&quot; rel=&quot;nofollow noreferrer&quot;&gt;NanoCrystal / Graphene Heterostructure in VESTA&lt;/a&gt; step by step but instead of an Au nanocrystal, I put a small graphene nanoflake approximately 3.35 Å on top of graphene.&lt;/p&gt;&#xA;&lt;p&gt;I first generated an &lt;span class=&quot;math-container&quot;&gt;$11 \times 11$&lt;/span&gt; graphene sheet with 30 Å vacuum by transforming the unit cell. I exported it as a VASP POSCAR.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/s8ZTr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s8ZTr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I then put a flake on it, removed repeated atoms on the boundary of graphene, and exported it as an xyz file. When I open this xyz in VESTA, it looks fine:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/RBnK4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RBnK4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The number of atoms is also correct: 242 in &lt;span class=&quot;math-container&quot;&gt;$11 \times 11$&lt;/span&gt; graphene, 42 in the flake, 284 in the xyz.&lt;/p&gt;&#xA;&lt;p&gt;Then I made a copy of the POSCAR for &lt;span class=&quot;math-container&quot;&gt;$11 \times 11$&lt;/span&gt; graphene, copied there the lines of atom coordinates from the xyz file, changed the number of atoms to 284, removed the C labels, opened it in VESTA, and this is what I got:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rQT6H.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rQT6H.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Why such a huge number of atoms?&lt;/p&gt;&#xA;&lt;p&gt;It only extends graphene. The flake is not replicated.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ITctl.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ITctl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What am I doing wrong?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-08-04T02:40:17.630" Title="Why VESTA displays much more atoms beyond the cell boundaries?" Tags="|software-assistance|vesta|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11435" PostTypeId="1" AcceptedAnswerId="11436" CreationDate="2023-08-04T04:27:44.190" Score="7" ViewCount="290" Body="&lt;p&gt;DFT band gap problem is a well-known problem. LDA or GGA exchange-correlation functionals underestimate the band gap heavily. I saw some of the strategies to address this issue were:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;using hybrid functions such as PBE0 or HSE06.&lt;/li&gt;&#xA;&lt;li&gt;using meta-GGA level functional such as SCAN, rSCAN, r2SCAN, etc.&lt;/li&gt;&#xA;&lt;li&gt;using Koopman functional (KCW)&lt;/li&gt;&#xA;&lt;li&gt;post-processing the ground state DFT result with GW approximation, etc.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Now, I want to know if there exists a comparison of accuracy and/or efficiency among these strategies. Or could it be the case that it depends on the specific material?&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-08-05T10:07:43.800" LastActivityDate="2023-08-05T10:07:43.800" Title="Which strategy of improving the DFT band gap is the most effective?" Tags="|density-functional-theory|functional|exchange-correlation|gw-bse|bandgap|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11436" PostTypeId="2" ParentId="11435" CreationDate="2023-08-04T17:43:28.260" Score="8" Body="&lt;p&gt;It's a nice question, it will be difficult to compare their accuracy and efficiency in a single plot, because the band gap problem is mainly divided into two parts: the self-interaction and the correlations, so it depends on the material. In all cases the GW approximation is the most accurate approximation, it describes the occupied states slightly like Hartree-Fock but has the advantage of describing the unoccupied states very accurately at the expense of computational time, &lt;a href=&quot;https://www.uni-regensburg.de/physik/evers/research/gw/index.html&quot; rel=&quot;noreferrer&quot;&gt;here is a quantitative analysis&lt;/a&gt;. In general, all these approximations aim at reducing the computational time without degrading the accuracy.&lt;/p&gt;&#xA;&lt;p&gt;The self-interaction error is a wrong description of occupied states by DFT, the correction needs to include a part of the Hartree-Fock exact exchange free of a self-interaction error to build a hybrid functional (PBE0, HSE06).&lt;/p&gt;&#xA;&lt;p&gt;Hybrid functional are useless for strongly correlated systems, the problem is not the locality of the DFT exchange but the overall approximation limited to one electron. A standard DFT cannot describe the ground state, DFT+U is the best correction and the functional used is important. Localized orbitals in this case require more derivative of the density. The SCAN+U method is often more accurate than GGA+U or LDA+U, especially for ionic solids.&lt;/p&gt;&#xA;&lt;p&gt;I don't know the correction of the Koopmans functional, but I guess it reduces the self-interaction error and brings back the Koopmans theorem.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-08-04T17:43:28.260" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11437" PostTypeId="1" AcceptedAnswerId="11441" CreationDate="2023-08-04T19:29:47.423" Score="5" ViewCount="806" Body="&lt;p&gt;I am a beginner in Quantum Espresso, and I want to calculate optical properties. When I calculate the dielectric functions, it gives me four output files. I don't know which files correspond to the real function and imaginar the dielectric function.&lt;/p&gt;&#xA;&lt;p&gt;Above are the input and output files&#xA;Input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA;calculation     = 'eps',&#xA;outdir          = './outdir' &#xA;/&#xA;&#xA;&amp;amp;ENERGY_GRID&#xA; smeartype      = 'gauss',&#xA; intersmear     = 0.15d0,&#xA; intrasmear     = 0.0d0,&#xA; wmax           = 10.0d0,&#xA; wmin           = 0.0d0,&#xA; nw             = 600,&#xA; shift          = 0.0d0,&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;output files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eels_CNT(10.0)@C6H2.dat&#xA;epsi_CNT(10.0)@C6H2.dat&#xA;epsr_CNT(10.0)@C6H2.dat&#xA;ieps_CNT(10.0)@C6H2.dat&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="6055" LastEditDate="2023-08-05T09:43:03.823" LastActivityDate="2023-12-03T21:05:39.620" Title="Optical proprieties with Quantum espresso" Tags="|quantum-espresso|optical-properties|dielectric-constants|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11438" PostTypeId="1" CreationDate="2023-08-05T04:32:44.210" Score="5" ViewCount="105" Body="&lt;p&gt;As per my understanding, the electrical conductivity of a material can be expected to increase with the increased carrier concentration. However, beyond a certain (extreme) point, the electrical conductivity should peak and begin to decrease with increasing carrier concentration due to the increased scattering.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that, as reported in multiple articles (for example, Figure 2 of Reference 1 and Figure 7 of Reference 2), as well as my own personal experience, BoltzTraP2 (which operates under the constant relaxation time approximation) is capable of capturing a similar effect.&lt;/p&gt;&#xA;&lt;p&gt;Given that the program solves the Boltzmann's transport equation at a constant relaxation time, this effect of non-monotonic variation in electrical conductivity with carrier concentration can be concluded to occur even without a change in electron scattering rates.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, &lt;strong&gt;is there any other explanation to the non-monotonic trend in electrical conductivity with increasing carrier concentration?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note: I am aware that the chemical potential and carrier concentration aren't the same thing and that they are related by the Fermi-Dirac distribution. However for a given material, an increase in chemical potential would occur with an increase in carrier concentration right?&lt;/p&gt;&#xA;&lt;p&gt;I have also contacted the BoltzTraP2 developers on this &lt;a href=&quot;https://groups.google.com/g/boltztrap/c/Dz3h7lr03Lc/m/NCfxDybSBQAJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;issue&lt;/a&gt;, however I am still unable to understand the exact reasoning behind this.&lt;/p&gt;&#xA;&lt;h4&gt;References&lt;/h4&gt;&#xA;&lt;p&gt;[1] Tang, C.; Huang, Z.; Pei, J.; Zhang, B.-P.; Shang, P.-P.; Shan, Z.; Zhang, Z.; Gu, H.; Wen, K. Bi2Te3 Single Crystals with High Room-Temperature Thermoelectric Performance Enhanced by Manipulating Point Defects Based on First-Principles Calculation. RSC Advances, 2019, 9, 14422–14431. &lt;a href=&quot;https://doi.org/10.1039/c9ra01738k&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[2] Pandit, A.; Haleoot, R.; Hamad, B. Thermal Conductivity and Enhanced Thermoelectric Performance of SnTe Bilayer. Journal of Materials Science, 2021, 56, 10424–10437. &lt;a href=&quot;https://doi.org/10.1007/s10853-021-05926-x&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4232" LastEditorUserId="7" LastEditDate="2023-08-19T13:58:09.883" LastActivityDate="2023-12-13T03:16:53.297" Title="Effect of carrier concentration on electrical conductivity" Tags="|band-structure|electronic-transport|semiconductor|boltztrap|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11439" PostTypeId="2" ParentId="11432" CreationDate="2023-08-05T06:41:12.057" Score="8" Body="&lt;p&gt;You can use a python library called ASE (Atomic Simulation Environment) to achieve your requirement.&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;from ase.build import make_supercell&#xA;import numpy as np&#xA;from pprint import pprint&#xA;&#xA;&#xA;def atoms_in_plane(unit_cell_atoms, plane_point1, plane_point2):&#xA;    # Create a supercell to ensure periodic boundary conditions&#xA;    supercell = make_supercell(unit_cell_atoms, [[2, 0, 0], [0, 2, 0], [0, 0, 2]])&#xA;&#xA;    # Define the plane using the points (0, 0, 0) and (x, y, z)&#xA;    plane_normal = np.array(plane_point2) - np.array(plane_point1)&#xA;&#xA;&#xA;    # Collect atoms within the plane&#xA;    atoms_in_plane = []&#xA;    for atom in supercell:&#xA;        position_vector = atom.position&#xA;        # Calculate the vector from the first point of the plane to the atom&#xA;        vector_to_atom = position_vector - plane_point1&#xA;        # Calculate the dot product between the vector to the atom and the plane normal&#xA;        dot_product = plane_normal.dot(vector_to_atom)&#xA;        # If the dot product is close to zero, the atom lies within the plane&#xA;        if abs(dot_product) &amp;lt; 1e-8:&#xA;            atoms_in_plane.append(atom)&#xA;&#xA;    return atoms_in_plane&#xA;&#xA;# Example usage:&#xA;# Define your unit cell atoms&#xA;unit_cell_atoms = Atoms(symbols=['Zn', 'O', 'O', 'O', 'C', 'C', 'C', 'C', 'H'],&#xA;                        positions=[&#xA;                         [0.64159, 0.68514,0.47189], &#xA;                         [0.96943,0.29776,0.36038], &#xA;                         [0.92763,0.23048,0.6102], &#xA;                         [0.25494,0.94205,0.67383], &#xA;                         [0.92667,0.2458,0.42703], &#xA;                         [0.87918,0.20711,0.29083], &#xA;                         [0.21254,0.88926,0.7549], &#xA;                         [0.1663,0.84759,0.63558] ,&#xA;                         [0.16529,0.85803,0.47918]&#xA;                         ])&#xA;&#xA;# Define the two points that define the plane&#xA;plane_point1 = [0,0,0]&#xA;plane_point2 = [1e-8, 1e-9, 1e-8]&#xA;&#xA;&#xA;# Get the atoms within the plane&#xA;atoms_in_defined_plane = atoms_in_plane(unit_cell_atoms, plane_point1, plane_point2)&#xA;&#xA;print(&amp;quot;Atoms within the defined plane:&amp;quot;)&#xA;pprint(atoms_in_defined_plane)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Atoms within the defined plane:&#xA;[Atom('C', [0.1663, 0.84759, 0.63558], index=7),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=8),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=16),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=17),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=25),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=26),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=34),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=35),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=43),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=44),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=52),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=53),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=61),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=62),&#xA; Atom('C', [0.1663, 0.84759, 0.63558], index=70),&#xA; Atom('H', [0.16529, 0.85803, 0.47918], index=71)]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-05T06:41:12.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11440" PostTypeId="2" ParentId="11431" CreationDate="2023-08-05T07:06:03.437" Score="4" Body="&lt;p&gt;If you already have a set of defect energies and Fermi energies then it is as simple as plotting them with visualizing library such as matplotlib.&lt;/p&gt;&#xA;&lt;p&gt;For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;# Sample data (replace with your actual data)&#xA;fermi_energies = [-2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, 2.0]  # Fermi energies (x-axis)&#xA;defect_energies = [0.1, 0.08, 0.05, 0.02, 0.0, 0.03, 0.06, 0.09, 0.12]  # Charge defect formation energies (y-axis)&#xA;&#xA;# Plot the data&#xA;plt.plot(fermi_energies, defect_energies, marker='o', linestyle='-', color='b')&#xA;plt.xlabel('Fermi Energy (eV)')&#xA;plt.ylabel('Charge Defect Formation Energy (eV)')&#xA;plt.title('Charge Defect Formation Energy vs Fermi Energy')&#xA;plt.grid(True)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KdOQP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KdOQP.png&quot; alt=&quot;Sample defect vs fermi E&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you would like to obtain the values of the defect and fermi energies, then you can use an online database such as the Materials Project Database.&#xA;You can sign up for free and will be given an API-key.&lt;/p&gt;&#xA;&lt;p&gt;Below is a code to access the values for a couple of elements and then plot them:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mp_api.client import MPRester&#xA;&#xA;# Replace with your Materials Project API key (sign up at materialsproject.org)&#xA;api_key = &amp;quot;YOUR_API_KEY&amp;quot;&#xA;&#xA;# Create an instance of the Materials Project API&#xA;mp = MPRester(api_key)&#xA;&#xA;# Example: Get Fermi energy and defect formation energy for Silicon (Si)&#xA;formula = &amp;quot;Si&amp;quot;&#xA;&#xA;formulas = ['Si', 'C', 'O', 'P', 'B', 'N', 'F']&#xA;&#xA;fermi_energies = []&#xA;defect_energies = []&#xA;for formula in formulas:&#xA;&#xA;  # Query the Materials Project database for the data&#xA;  data = mp.summary.search(formula=formula, fields=[&amp;quot;efermi&amp;quot;, &amp;quot;formation_energy_per_atom&amp;quot;])&#xA;&#xA;  # Extract Fermi energy and defect formation energy&#xA;  fermi_energy = data[0].efermi&#xA;  defect_energy = data[0].formation_energy_per_atom&#xA;&#xA;  fermi_energies.append(fermi_energy)&#xA;  defect_energies.append(defect_energy)&#xA;&#xA;&#xA;# Plot the data&#xA;plt.plot(fermi_energies, defect_energies, marker='o', linestyle='-', color='b')&#xA;plt.xlabel('Fermi Energy (eV)')&#xA;plt.ylabel('Charge Defect Formation Energy (eV)')&#xA;plt.title('Charge Defect Formation Energy vs Fermi Energy')&#xA;plt.grid(True)&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ScM6y.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ScM6y.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-05T07:06:03.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11441" PostTypeId="2" ParentId="11437" CreationDate="2023-08-05T10:03:22.323" Score="9" Body="&lt;p&gt;There will be 4 output files in total for an &lt;code&gt;epsilon.x&lt;/code&gt; run. These are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;eels_prefix.dat&#xA;epsi_prefix.dat&#xA;epsr_prefix.dat&#xA;ieps_prefix.dat&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;prefix&lt;/code&gt; is the prefix of your calculation.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;epsr_&lt;/code&gt; and &lt;code&gt;epsi_&lt;/code&gt; files contain the real &lt;span class=&quot;math-container&quot;&gt;$Re(ε(ω))$&lt;/span&gt; and imaginary &lt;span class=&quot;math-container&quot;&gt;$Im(ε(ω))$&lt;/span&gt; parts of the diagonal part of the dielectric tensor, respectively. The &lt;code&gt;eels_&lt;/code&gt; file contains the electron energy loss spectra, &lt;span class=&quot;math-container&quot;&gt;$Im(1/ε(ω))$&lt;/span&gt; calculated from the diagonal elements of the dielectric tensor. The &lt;code&gt;ieps_&lt;/code&gt; file contains the diagonal components of the dielectric tensor, &lt;span class=&quot;math-container&quot;&gt;$ε(iω)$&lt;/span&gt;, calculated on the imaginary frequency axis.&lt;/p&gt;&#xA;&lt;p&gt;If you open the &lt;code&gt;epsr_&lt;/code&gt; file, you will get 4 columns: energy &lt;span class=&quot;math-container&quot;&gt;$E \,(eV)$&lt;/span&gt;, and the real parts of the dielectric function, &lt;span class=&quot;math-container&quot;&gt;$Re(ε_{xx}(ω)),\; Re(ε_{yy}(ω)),$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$Re(ε_{zz}(ω))$&lt;/span&gt; in the &lt;span class=&quot;math-container&quot;&gt;$x‐, \;y‐,$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z‐$&lt;/span&gt; directions, respectively. The same goes for &lt;code&gt;epsi_&lt;/code&gt; in case of imaginary parts.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Reference:&lt;/strong&gt; Tuan Hung, N., Nugraha, A.R.T., &amp;amp; Saito, R. (2022). Quantum ESPRESSO Course for Solid-State Physics (1st ed.). Jenny Stanford Publishing. &lt;a href=&quot;https://doi.org/10.1201/9781003290964&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1201/9781003290964&lt;/a&gt;. pp: 118-119.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-08-05T10:03:22.323" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11442" PostTypeId="2" ParentId="11408" CreationDate="2023-08-05T17:31:52.873" Score="3" Body="&lt;p&gt;After a long search I finally found the answer I've been looking for. To calculate the work of separation beneath the interface or at any layer you insert a small vacuum for example 5 Angstrom and calculate the total energy of the system. The work of separation is then the difference between the energy of the separated and the unseparated layers divided by the interface area.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-08-05T17:31:52.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11443" PostTypeId="2" ParentId="11432" CreationDate="2023-08-05T18:55:07.267" Score="2" Body="&lt;p&gt;You can also use &lt;a href=&quot;https://github.com/zerothi/sisl&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt; to achieve this.&lt;/p&gt;&#xA;&lt;p&gt;Best shown with an example:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from sisl import geom, Cuboid&#xA;&#xA;graphene = geom.graphene()&#xA;gr2x2 = graphene.tile(2, 0).tile(2, 1) # double along along 1st and 2nd lattice vectors&#xA;&#xA;# a cube of side-lengths 4 Ang, centerred around 0.5, 0.5, 0.5 Ang&#xA;cube = Cuboid(4, center=[0.5, 0.5, 0.5])&#xA;&#xA;idx, xyz = gr2x2.within(cube, ret_xyz=True)&#xA;print(xyz)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note here that the geometry &lt;code&gt;gr2x2&lt;/code&gt; may have an associated auxiliary supercell, in which case atoms in that supercell are also considered. If this is not desired one can easily change that behaviour.&lt;br /&gt;&#xA;sisl allows many more shapes, and also combinations of shapes. For instance:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;cubeandcube = cube + Cuboid(2, center=[2, 2, 2])&#xA;gr2x2.within(cubeandcube)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Disclaimer: I am the author of sisl.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-08-05T18:55:07.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11444" PostTypeId="1" CreationDate="2023-08-06T00:48:15.990" Score="2" ViewCount="184" Body="&lt;p&gt;i asked this query in another &lt;a href=&quot;http://henkelmanlab.org/forum/viewtopic.php?t=15594&amp;amp;sid=b2b074f9ca473c616a04df3979c20eb2&quot; rel=&quot;nofollow noreferrer&quot;&gt;forum&lt;/a&gt;, waiting for answer. However, also posting it here.&lt;/p&gt;&#xA;&lt;p&gt;i got a CHGCAR file written for both optimised and non-optimised (single point run) runs of a lattice model.&#xA;So, i have two CHGCAR files.&#xA;Using vaspkit i did charge density difference subtracting from say, Optimised CHGCAR minus non-optimised CHGCAR, giving raise to another similar formatted &lt;strong&gt;CHGDIFF.vasp&lt;/strong&gt; file.&#xA;Now, i wish to create a 2D plot to show the integrated charge density values along z-direction at each xy-plane grid point. To explain more, say the XY-plane has 40x34 grid, and Z-side has 120 grid.  Now i want the CHGDIFF.vasp values to be manipulated so that all values along z-grid are added up to finally written at xy-plane grid. Hope i am clear to you.&lt;/p&gt;&#xA;&lt;p&gt;Assuming the option '315' in vaspkit will do whatever i wanted above, i run the option, gave input of this CHGDIFF.vasp. The vaspkit asked two values in 'a' and 'b' directions. not clear what these values for (could not locate in vaspkit documentation), i gave '1 and 1'.&lt;/p&gt;&#xA;&lt;p&gt;Then it gave three &lt;strong&gt;.grd&lt;/strong&gt; format files. I could not open these files in VESTA, moreover, when i try in, the VESTA is shutting down each time. I could not open these files in Material studio also.&#xA;Can anyone help to understand How to do such integration either with vaspkit and open these data for final 2D visualisation? or otherwise do some 'numerical computation' and then visualise in VESTA?&lt;/p&gt;&#xA;" OwnerUserId="1657" LastEditorUserId="5" LastEditDate="2023-08-08T13:35:10.403" LastActivityDate="2023-08-08T13:35:10.403" Title="How to integrate CHGCAR data of VASP, in z-direction and have xy-plane charge density at each grid point on xy-plane?" Tags="|density-functional-theory|vasp|vesta|" AnswerCount="0" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="11446" PostTypeId="1" AcceptedAnswerId="11451" CreationDate="2023-08-06T13:31:44.870" Score="2" ViewCount="171" Body="&lt;p&gt;I would like to calculate the Helmholtz vibrational energy. I have done the phonon calculations. My question is how to extract the vibrational energy from the output of the Vasp calculation.&#xA;A source code (vaspkit) I used allows me to input the desired temperature and gives the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Temperature (T): 300.0 K &#xA;Zero-point energy E_ZPE : 72.232 kcal/mol 3.132266 eV &#xA;Thermal correction to U(T): 85.703 kcal/mol 3.716441 eV &#xA;Thermal correction to H(T): 85.703 kcal/mol 3.716441 eV &#xA;Thermal correction to G(T): 66.293 kcal/mol 2.874750 eV &#xA;Entropy S : 270.703 J/(molK) 0.002806 eV/K &#xA;Entropy contribution TS : 81210.770 J/(mol) 0.841691 eV &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since F = U - TS, can I calculate the energy from this output?&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-08-06T23:13:54.970" Title="Helmholtz vibrational energy from VASP calculations" Tags="|vasp|phonons|vibrations|vaspkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11447" PostTypeId="1" CreationDate="2023-08-06T15:08:47.787" Score="2" ViewCount="60" Body="&lt;p&gt;I am trying to run a single point &lt;em&gt;g&lt;/em&gt;09 calculation for a &lt;strong&gt;pentagonal planar&lt;/strong&gt; molecule with &lt;em&gt;D&lt;/em&gt;5&lt;em&gt;h&lt;/em&gt; symmetry using the B3LYP/LANL2DZ level or theory.&lt;/p&gt;&#xA;&lt;p&gt;I would like the calculation to use symmetry, however the program that I use to analyze the output file requires the calculation to run with the “NoSymm” keyword to prevent reorganization of the atoms into standard orientation.&lt;/p&gt;&#xA;&lt;p&gt;At the moment, the input orientation is in the &lt;em&gt;xy&lt;/em&gt; plane with the first terminal atom directly on the &lt;em&gt;y&lt;/em&gt;-axis. The 5 terminal atoms are then ordered 1-5 in a clockwise rotation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;How can I set the input geometry such that it is already in standard orientation?&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I have tried using the “SaveOrientation” keyword which is supposed to “mark the standard orientation as the input orientation” (Gaussian website), however to no avail.&lt;/p&gt;&#xA;&lt;p&gt;Any help is greatly appreciated!&#xA;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-08-06T15:08:47.787" Title="Help setting the input geometry into standard orientation for a single point g09 calculation" Tags="|computational-chemistry|gaussian|symmetry|software-input-file-request|population-analysis|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11448" PostTypeId="1" CreationDate="2023-08-06T18:02:27.113" Score="2" ViewCount="70" Body="&lt;p&gt;How do we calculate thermodynamic properties using VASP 6.1.0?&lt;/p&gt;&#xA;" OwnerUserId="7046" LastEditorUserId="6055" LastEditDate="2023-08-06T18:12:09.340" LastActivityDate="2023-08-06T18:12:09.340" Title="How do we calculate thermodynamic properites using VASP 6.1.0?" Tags="|vasp|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11449" PostTypeId="1" CreationDate="2023-08-06T19:47:19.880" Score="1" ViewCount="43" Body="&lt;p&gt;After finishing the orthonormalization of IAOs basis, and the LO.boys localization I am building my hamiltonian:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;na,nb = mol.nelectron//2,mol.nelectron//2&#xA;E0 = mol.energy_nuc()&#xA;h1 = np.einsum('ab,ai,bk-&amp;gt;ik',mf.get_hcore(),C,C)&#xA;h2 = ao2mo.restore(4,ao2mo.kernel(mol,C),n)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am seem to not being able to make the transformation from my new orbital coefficients (&lt;code&gt;C&lt;/code&gt;,[344,14]) and I can later transform to a (105,105) matrix containing my coefficients with a size of 11025 coeff.&lt;/p&gt;&#xA;&lt;p&gt;When I try to run the &lt;code&gt;ao2mo.restore(symm,eri,nao_orb,tao)&lt;/code&gt; with &lt;code&gt;eri = ao2mo.kernel(mol,C)&lt;/code&gt; I get this error:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;185         return eri.reshape(npair,norb,norb)&#xA;187 else:&#xA;188     raise RuntimeError('eri.size = %d, norb = %d' % (eri.size, norb))&#xA;RuntimeError: eri.size = 11025, norb = 8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am directly introducing this transformation, but I am stuck at this transformation. I have tried several symmetries stated in the documentation, but I am running out of ideas.&#xA;The source code, can be found in &lt;a href=&quot;https://github.com/StefanoBarison/quantum_simulation_with_IAO&quot; rel=&quot;nofollow noreferrer&quot;&gt;this_repository&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I thank you for your time and help.&lt;/p&gt;&#xA;" OwnerUserId="7670" LastActivityDate="2023-08-06T19:47:19.880" Title="Restoring MO from ao2mo using PYSCF module" Tags="|pyscf|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:22:19.140" ContentLicense="CC BY-SA 4.0" />
  <row Id="11450" PostTypeId="1" CreationDate="2023-08-06T22:02:17.780" Score="2" ViewCount="22" Body="&lt;p&gt;I have calculated the energies of a substance in a cylindrical canister using DFT, with an oxygen vacancy, with an oxygen interstitial and purely stoichiometric. I am struggling to figure out how to determine the formation energy, relating the oxygen in the headspace of the canister to the defects. I believe I can use the chemical potential, but I'm not really too familiar with chemistry...&lt;/p&gt;&#xA;&lt;p&gt;Please let me know what you suggest.&lt;/p&gt;&#xA;&lt;p&gt;Thank you :)&lt;/p&gt;&#xA;" OwnerUserId="7671" LastActivityDate="2023-08-06T22:02:17.780" Title="Calculate the formation energy of a cannister" Tags="|density-functional-theory|formation-energy|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11451" PostTypeId="2" ParentId="11446" CreationDate="2023-08-06T23:13:54.970" Score="0" Body="&lt;pre&gt;&lt;code&gt;    #!/bin/bash&#xA;&#xA;from ase.thermochemistry import HarmonicThermo&#xA;&#xA;def search_and_process_cm1_lines(file_path):&#xA;    result_list = []&#xA;    with open(file_path, 'r') as file:&#xA;        for line in file:&#xA;            if &amp;quot;cm-1&amp;quot; in line:&#xA;                # Split the line by whitespace&#xA;                line_elements = line.strip().split()&#xA;                # Convert the last but one entry to a float&#xA;                try:&#xA;                    last_but_one_entry = float(line_elements[-2])&#xA;                except ValueError:&#xA;                    # If conversion to float fails, skip this line&#xA;                    continue&#xA;                # Divide the value by 1000 and append to the result list&#xA;                result_list.append(last_but_one_entry / 1000)&#xA;&#xA;    return result_list&#xA;&#xA;# Example usage&#xA;file_path = &amp;quot;OUTCAR&amp;quot;&#xA;cm1_values = search_and_process_cm1_lines(file_path)&#xA;thermo = HarmonicThermo(vib_energies=cm1_values)&#xA;&#xA;# get thermodynamical parameters at required temperature&#xA;s = thermo.get_entropy(temperature=300)&#xA;u = thermo.get_internal_energy(temperature=300)&#xA;f = thermo.get_helmholtz_energy(temperature=300)&#xA;&#xA;print(&amp;quot;Entropy S: &amp;quot;, s)&#xA;print(&amp;quot;Internal Energy U: &amp;quot;, u) &#xA;print(&amp;quot;Helmholtz Energy F: &amp;quot;, f)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-08-06T23:13:54.970" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11452" PostTypeId="1" CreationDate="2023-08-07T15:43:58.653" Score="2" ViewCount="47" Body="&lt;p&gt;I have a unit cell, and I want to create a 3x3x3 supercell.&lt;/p&gt;&#xA;&lt;p&gt;Please, I need guidance on how to create properly the input files for Density of States (DOS) calculation (SCF and NSCF) and the input files for optical properties (SCF and Epsilon) using Quantum ESPRESSO. In fact,I want to avoid getting very intense peaks in the DOS calculation and minimize computational expenses for the optical properties calculations.&lt;/p&gt;&#xA;&lt;p&gt;PS: I already tried to do that but it's not working properly.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-08-07T15:43:58.653" Title="How can I correctly create the input files for DOS and Optical Properties of a supercell using Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|density-of-states|self-consistent-field|supercell|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-27T16:56:35.783" ContentLicense="CC BY-SA 4.0" />
  <row Id="11453" PostTypeId="1" CreationDate="2023-08-07T16:31:03.933" Score="1" ViewCount="65" Body="&lt;p&gt;I'm studying the HF method, so I have a non-relativistic time-independent Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;Since in the Hamiltonian, there is no spin, we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left[\hat{H}, \hat{S}_z \right] = 0 \quad \text{and} \quad \left[\hat{H}, \hat{S}^2 \right] = 0&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This means that it should be possible to factorize the total wave function as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Psi(1,2, \dots)=\underbrace{\Phi(1,2,\dots)}_{\text{Spatial part}}\underbrace{\chi(1,2,\dots)}_{\text{Spin part}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From Szabo, Modern Quantum Chemistry, chapter 2.5.2, I read that closed shell Slater determinants are eigenfunctions of &lt;span class=&quot;math-container&quot;&gt;$\hat{S}_z$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\hat{S}^2$&lt;/span&gt;.&#xA;So a closed shell Slater determinant should be factorizable into spatial and spin parts as above. Is this correct?&#xA;I know the question sounds obvious, but I want to make sure I understood correctly.&lt;/p&gt;&#xA;" OwnerUserId="5294" LastActivityDate="2023-08-07T16:31:03.933" Title="Factorization of a closed shell Slater determinant into spatial and spin part" Tags="|reference-request|hartree-fock|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11454" PostTypeId="1" CreationDate="2023-08-07T18:57:51.380" Score="1" ViewCount="16" Body="&lt;p&gt;I am a new user of thermo-calc and I am currently trying to model the phase diagrams of Yttrium Hydride.  I have a couple samples doped with different elements (for example, Li).  The only database I can find on thermo-Calc that can handle both Li and Y is Pure5, however, when I used Pure5, it said the only phase it claimed was present was the gas phase.  Does anyone know of a different database to use or potential errors I may be making due to inexperience?&lt;/p&gt;&#xA;" OwnerUserId="7678" LastActivityDate="2023-08-07T18:57:51.380" Title="What database in Thermo-Calc should I use if I am trying to model Yttrium Hydrides?" Tags="|thermo-calc|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-20T03:22:06.457" ContentLicense="CC BY-SA 4.0" />
  <row Id="11455" PostTypeId="1" CreationDate="2023-08-07T23:01:52.627" Score="5" ViewCount="44" Body="&lt;p&gt;Say I have a bulk FCC Pt structure obtained from &lt;a href=&quot;https://next-gen.materialsproject.org/materials/mp-126?chemsys=Pt&quot; rel=&quot;nofollow noreferrer&quot;&gt;Materials Project&lt;/a&gt; with a lattice constant &lt;em&gt;a&lt;/em&gt; = 3.94 Å. I first did DFT to relax the bulk structure, and the optimized lattice constant becomes for example &lt;em&gt;a&lt;/em&gt; = 3.80 Å. Then I cut it to obtain a 5-layer Pt(111) surface slab and again relaxed it using DFT. Now I have a Pt(111) surface slab with both lattice parameters and atomic positions slightly perturbed from the reference surface that one can obtain by directly cutting the bulk structure from Materials Project without any relaxation.&lt;/p&gt;&#xA;&lt;p&gt;My question is: how can I apply a transformation &lt;em&gt;directly to the perturbed surface slab&lt;/em&gt;, so that the cell and all atomic positions are exactly corresponding to the reference bulk Pt with &lt;em&gt;a&lt;/em&gt; = 3.94 Å? Note that building a new surface from scratch is not an option, because the perturbed surface slab may already involve a lot of user-postprocessing (e.g. expanding/transforming cell, adding vacuum layer, cutting termination, etc) and I want to apply the transformation while keeping these postprocessing. I would like a general solution that works for all types of crystal structures, not just for FCC. Any suggestions or ideas are welcome.&lt;/p&gt;&#xA;&lt;p&gt;Edit: my current idea is to develop an algorithm that can efficiently find a surface unit cell in the whole bulk lattice space that is the most similar to the perturbed surface unit cell (according to some topology-based similarity measure, any suggestion?). However, even though I know the orientation of the surface (i.e. the Miller index), there are still too many surface unit cells to search through.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-08-08T11:49:51.357" LastActivityDate="2023-08-08T11:49:51.357" Title="How to transform a perturbed surface structure to a reference surface structure?" Tags="|crystallography|symmetry|surfaces|geometry|periodic-system|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11456" PostTypeId="1" CreationDate="2023-08-07T23:25:05.800" Score="4" ViewCount="97" Body="&lt;p&gt;Does anyone know why the CCCBDB database lists the tin cation and antimony atom as having the Oh point group (please see the screenshot below from CCCBDB when I look at &amp;quot;&lt;a href=&quot;https://cccbdb.nist.gov/pglist.asp&quot; rel=&quot;nofollow noreferrer&quot;&gt;All molecules sorted by Point Group&lt;/a&gt;&amp;quot;)? Shouldn't the Oh point group be for symmetries of a regular tetrahedron?&lt;/p&gt;&#xA;&lt;p&gt;Wouldn't it be more suitable to list Sn+ and Sb as Kh?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lovLD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lovLD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7679" LastEditorUserId="5" LastEditDate="2023-08-10T18:42:26.740" LastActivityDate="2023-08-10T18:42:26.740" Title="Why are some point groups for single atoms listed as Oh in the CCCBDB?" Tags="|mathematical-modeling|symmetry|spectroscopy|databases|atomic-physics|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11457" PostTypeId="1" CreationDate="2023-08-08T01:33:35.320" Score="5" ViewCount="83" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Laser-based_angle-resolved_photoemission_spectroscopy#Laser-based_ARPES&quot; rel=&quot;nofollow noreferrer&quot;&gt;Laser-based&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Laser-based_angle-resolved_photoemission_spectroscopy#Time-resolved_electron_dynamics&quot; rel=&quot;nofollow noreferrer&quot;&gt;time-resolved&lt;/a&gt; ARPES are &lt;em&gt;relatively&lt;/em&gt;&lt;sup&gt;1&lt;/sup&gt; new techniques to study atomic and especially electronic structure (necessarily) near crystal surfaces and of adsorbed 2D materials on those surfaces.&lt;/p&gt;&#xA;&lt;p&gt;Pulse compression techniques can produce focused laser pulses with femtosecond-scale duration and small spot sizes, producing enormous electric fields, and &lt;a href=&quot;https://en.wikipedia.org/wiki/High_harmonic_generation&quot; rel=&quot;nofollow noreferrer&quot;&gt;high harmonic generation&lt;/a&gt; can simultaneously give the individual photons energies (within a still-coherent, compressed beam) in the 20 to 100 eV range or higher.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt; What are software packages that can model the effects of intense electric fields from femtosecond compressed IR and EUV laser pulses on surfaces?&lt;/p&gt;&#xA;&lt;h3&gt;But what does &amp;quot;model the effects&amp;quot; mean?&lt;/h3&gt;&#xA;&lt;p&gt;High individual photon energies alone are not new - synchrotron beams have been used with ARPES for a long time, cf. &lt;a href=&quot;https://en.wikipedia.org/wiki/X-ray_photoelectron_spectroscopy&quot; rel=&quot;nofollow noreferrer&quot;&gt;X-ray photoelectron spectroscopy&lt;/a&gt; or XPS.&lt;/p&gt;&#xA;&lt;p&gt;But the nature of the pulse-compressed laser beams is such that the instantaneous electric fields at and just below the surface of the sample are enormous - in the eV per Angstrom regime!&lt;/p&gt;&#xA;&lt;p&gt;Classically, two dielectric spheres in an electric field will polarize and then attract or apply torque on each other depending on their relative orientations. For quantum mechanical atoms, polarization (displacements of electronic charge wrt nuclear charge) can also happen.&lt;/p&gt;&#xA;&lt;p&gt;Thus I wonder if these high fields can excite &amp;quot;mechanical&amp;quot; forces on an adsorbed 2D material on a surface, or excite collective phonon phenomenon at the surface of a crystal just for example.&lt;/p&gt;&#xA;&lt;p&gt;To try to simulate these effects, what packages can address the physics of femtosecond and eV/Angstrom scale transient electric fields on these material systems?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt;compared to synchrotron light sources and helium UV lamps (He Iα &amp;amp; IIα  at 21.2 &amp;amp; 40.8 eV)&lt;/p&gt;&#xA;" OwnerUserId="201" LastEditorUserId="5" LastEditDate="2023-08-08T02:13:05.097" LastActivityDate="2023-09-12T04:07:55.627" Title="Packages that can model effects of intense electric fields from femtosecond compressed IR and EUV laser pulses on surfaces?" Tags="|software-recommendations|surfaces|2d-lattice|optical-properties|finite-difference-time-domain|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11458" PostTypeId="2" ParentId="11383" CreationDate="2023-08-08T05:23:37.470" Score="2" Body="&lt;p&gt;You can use a python library called: &lt;a href=&quot;https://github.com/romerogroup/pyprocar&quot; rel=&quot;nofollow noreferrer&quot;&gt;pyprocar&lt;/a&gt; to plot spin texture plots.&lt;/p&gt;&#xA;&lt;p&gt;You can install it using pip like this : &lt;code&gt;pip install PyProcar&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample code to plot spin textures&lt;/p&gt;&#xA;&lt;p&gt;In the below example all the required VASP files such as PROCAR, OUTCAR etc are inside the data directory.&lt;/p&gt;&#xA;&lt;p&gt;To perform similar plotting on your custom VASP files follow the code below and use the path of the data directory which has all your VASP files&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyprocar&#xA;&#xA;data_dir = pyprocar.download_example(save_dir='',&#xA;                             material='Fe',&#xA;                             code='vasp',&#xA;                             spin_calc_type='non-colinear',&#xA;                             calc_type='fermi')&#xA;&#xA;&#xA;pyprocar.fermi2D(code = 'vasp',&#xA;           dirname=data_dir,&#xA;           spin_texture=True,&#xA;           spin_projection='x',&#xA;           arrow_size=3,&#xA;           arrow_density=10,&#xA;           plot_color_bar=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives a plot like below&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pGmsJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pGmsJ.png&quot; alt=&quot;Spin_texture&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-08-08T09:45:58.243" LastActivityDate="2023-08-08T09:45:58.243" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11460" PostTypeId="1" AcceptedAnswerId="11462" CreationDate="2023-08-10T08:57:40.263" Score="6" ViewCount="324" Body="&lt;p&gt;I am trying to calculate the binding energy of a small molecule with an underlying surface. I have used B3LYP-D3BJ (as implemented in ORCA) at def2-TZVP basis set to optimize the geometry of the VdW complex, and then performed a single point Binding Energy calculation using RI-MP2 at def2-TZVP basis set. However, I am concerned about the accuracy of the binding energy that I have obtained from RI-MP2 calculations. Should I calculate the binding energy using DFT-D3 or will the energies from RI-MP2 be more accurate?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2023-08-10T17:46:27.700" LastActivityDate="2023-08-10T17:47:15.037" Title="Which is better for binding energies: DFT-D3 or RI-MP2?" Tags="|density-functional-theory|quantum-chemistry|electronic-structure|binding-energy|benchmarks-or-comparisons|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11461" PostTypeId="2" ParentId="11421" CreationDate="2023-08-10T16:36:28.373" Score="6" Body="&lt;p&gt;Yes, this is in the latest development version (1.98) as I discussed on the &lt;a href=&quot;https://discuss.avogadro.cc/t/images-for-a-whole-directory/4430/2?u=ghutchis&quot; rel=&quot;noreferrer&quot;&gt;Avogadro forum&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I shared an &lt;a href=&quot;https://gist.github.com/ghutchis/940b3f094969c515d02074bd9cb92c2b&quot; rel=&quot;noreferrer&quot;&gt;example script&lt;/a&gt; for exporting screenshots for a folder of &lt;code&gt;*.xyz&lt;/code&gt; files.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Launch Avogadro2 (latest nightly builds)&lt;/li&gt;&#xA;&lt;li&gt;Run the script in a directory of .xyz files&lt;/li&gt;&#xA;&lt;li&gt;It will load the files one-by-one into Avogadro and save a PNG image&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Please share feedback on the Avogadro forum -- we are &lt;a href=&quot;https://discuss.avogadro.cc/t/tasks-for-automation/3951?u=ghutchis&quot; rel=&quot;noreferrer&quot;&gt;interested in other automation tasks&lt;/a&gt; (e.g., rendering X orbital or surface, etc.)&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-08-10T16:36:28.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11462" PostTypeId="2" ParentId="11460" CreationDate="2023-08-10T16:55:04.400" Score="8" Body="&lt;h1&gt;Summary of my recommendation&lt;/h1&gt;&#xA;&lt;p&gt;If my choices are B3LYP-D3 and RI-MP2 for calculating a binding energy at a molecule whose geometry was optimized with B3LYP-D3, I would find it easier to justify using &lt;em&gt;&lt;strong&gt;B3LYP-D3&lt;/strong&gt;&lt;/em&gt; for the binding energy. B3LYP-D3 was found in the study summarized below, to be more accurate than RI-MP2 for &amp;quot;basic properties&amp;quot; such as atomization energies, and that is without the RI approximation for MP2, and it's for extrapolated CBS estimates for MP2 rather than the single def2-TZVP basis set that you're using.&lt;/p&gt;&#xA;&lt;p&gt;If somehow for your specific system's binding energy, RI-MP2/def2-TZVP is more accurate than B3LYP-D3/def2-TZVP and def2-TZVP is the biggest basis set that you can use for either of them, even if you were to do a (def2-TZVP,def2-DZVP → CBS) extrapolation for both RI-MP2 and B3LYP-D3, the results below show that other dispersion-corrected hybrid functionals with a similar cost to B3LYP-D3 are likely to beat MP2 by quite a lot (and therefore also RI-MP2 unless something fortuitous and unpredictable happens) in every category presented in the summarized results.&lt;/p&gt;&#xA;&lt;h1&gt;Results from Goerigk and Grimme (2011)&lt;/h1&gt;&#xA;&lt;p&gt;As summarized in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1132/5&quot;&gt;my answer&lt;/a&gt; to &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/392/5&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;, a 2011 study involving 841 relative energies and comparing more than 20 different hybrid functionals, for a variety of different properties, found that overall B3LYP-D3 was slightly worse than the average hybrid functional calculation (all hybrid calculations included the -D3 correction but the suffix was dropped for diagram), which had an average discrepancy of around 3.3 kcal/mol with the benchmark energy differences (mainly coming from experiments or CCSD(T)/CBS estimates):&lt;/p&gt;&#xA;&lt;p&gt;                            &lt;img src=&quot;https://i.stack.imgur.com/mpIgV.png&quot; width=&quot;400&quot;&gt;&lt;/p&gt;&#xA;&lt;p&gt;It would be great if we could know where MP2 lies on a histogram for exactly the same dataset. In fact &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2011/cp/c0cp02984j/unauth#!divAbstract&quot; rel=&quot;noreferrer&quot;&gt;the original paper&lt;/a&gt; has the following comparisons between MP2 and DSD-BLYP-D3:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/prUqn.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/prUqn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;DSD-BLYP-D3 is a &amp;quot;dispersion-corrected, spin-component-scaled, double-hybrid (DSD)&amp;quot; functional, and since you're using B3LYP-D3 which is a single-hybrid functional, it would be prudent for you to ignore the DSD-BLYP-D3 results in the above histogram. Instead let us compare the MP2 numbers in the above histograms with the B3LYP-D3 numbers in the histogram below (again, all calculations included a -D3 correction, but  the suffix was dropped in the labeling of the functionals):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Kdqnl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Kdqnl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This leads me to the following summary for average discrepancies with the benchmark numbers:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Method&lt;/th&gt;&#xA;&lt;th&gt;Basic Properties&lt;/th&gt;&#xA;&lt;th&gt;Reaction Energies&lt;/th&gt;&#xA;&lt;th&gt;Non-covalent interactions&lt;/th&gt;&#xA;&lt;th&gt;Complete Set&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;MP2&lt;/td&gt;&#xA;&lt;td&gt;5.7 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;3.6 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;0.90 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;3.6 kcal/mol&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;B3LYP-D3&lt;/td&gt;&#xA;&lt;td&gt;5.0 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;4.7 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;1.10 kcal/mol&lt;/td&gt;&#xA;&lt;td&gt;3.7 kcal/mol&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&lt;h4&gt;My first observation is that B3LYP-D3 is &lt;em&gt;&lt;strong&gt;worse&lt;/strong&gt;&lt;/em&gt; for everything except for &amp;quot;basic properties&amp;quot;.&lt;/h4&gt;&#xA;&lt;p&gt;So what are &amp;quot;basic properties&amp;quot;? They are described in the paper as &amp;quot;atomization energies, electron affinities, ionization potentials, proton affinities, SIE related problems, barrier heights&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;You seem to be interested in &amp;quot;binding energies&amp;quot;, which are similar to &amp;quot;atomization energies&amp;quot;, &lt;strong&gt;which is where B3LYP-D3 wins against MP2&lt;/strong&gt;, and would probably win even more after we consider:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;that the MP2 results in the above histograms are for CBS estimates and your MP2 calculations are using just the def2-TZVP basis set with no extrapolation,  and&lt;/li&gt;&#xA;&lt;li&gt;that the MP2 results in the above histograms are from full MP2 rather than the RI-MP2 approximation to full MP2 (and you are using the latter),&lt;/li&gt;&#xA;&lt;li&gt;that you optimized the geometries with B3LYP-D3, so your B3LYP-D3 binding energies would most likely have an inherent advantage over your MP2 ones.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;I think it would be harder to justify using RI-MP2 for the binding energy after optimizing the geometry with B3LYP-D3 rather than maintaining consistency by using B3LYP-D3 for both the geometry optimization and the binding energy calculation.&lt;/strong&gt; I guess you chose to use RI-MP2 because it's a more expensive method, with a formal scaling of O(N^5) as opposed to B3LYP-D3 whose cost is probably dominated by the HF part which has a formal scaling of O(N^4), but B3LYP-D3 according to this 2011 study, B3LYP-D3/(aug-)def2-QZVP is more accurate than MP2/CBS for &amp;quot;basic properties&amp;quot;, and &lt;strong&gt;some of the other dispersion-corrected hybrid functionals that cost almost the same as B3LYP-D3&lt;/strong&gt;, beat MP2 in every single category in this study.&lt;/p&gt;&#xA;&lt;h1&gt;Other findings&lt;/h1&gt;&#xA;&lt;p&gt;When I searched &lt;code&gt;DFT vs MP2&lt;/code&gt; on Google, the first page of results gave me the following 10 results, in order:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4326664/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Performance of Møller-Plesset second-order perturbation theory and density functional theory in predicting the interaction between stannylenes and aromatic molecules&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.researchgate.net/post/What_are_the_principle_differences_between_DFT_DFT-D_and_MP2&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;What are the principle differences between DFT/DFT-D and MP2?&lt;/strong&gt;&lt;/a&gt; [ResearchGate forum]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp901570r&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Evaluation of MP2, DFT, and DFT-D Methods for the Prediction of Infrared Spectra of Peptides&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpca.6b08040&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Performance of Hybrid DFT Compared to MP2 Methods in Calculating Nonlinear Optical Properties of Divinylpyrene Derivative Molecules&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;b&gt; &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6427/5&quot;&gt;DFT functionals from MP2 methods&lt;/a&gt; &lt;/b&gt; [MMSE, this is the only &amp;quot;irrelevant&amp;quot; result from the first page of Google search results in my opinion, maybe Google just knew I love MMSE].&lt;/li&gt;&#xA;&lt;li&gt;&lt;b&gt; &lt;a href=&quot;https://chemistry.stackexchange.com/q/117844/27342&quot;&gt;https://chemistry.stackexchange.com/q/117844/27342&lt;/a&gt; &lt;/b&gt; [Chemistry Stack Exchange]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1386142511005488&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;MP2, DFT and ab initio calculations on thioxanthone&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.echemi.com/community/what-are-the-principle-differences-between-dft-dft-d-and-mp2_mjart2205021527_367.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;What are the principle differences between DFT/DFT-D and MP2?&lt;/strong&gt;&lt;/a&gt; [ECHEMI forum, with no comments on the question yet].&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;http://sobereva.com/wfnbbs/viewtopic.php?id=784&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;MP2 or dispersion-corrected DFT-functionals?&lt;/strong&gt;&lt;/a&gt; [&lt;a href=&quot;/questions/tagged/multiwfn&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;multiwfn&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;multiwfn&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-multiwfn-tooltip-container&quot;&gt;multiwfn&lt;/a&gt; forum, with answers that support my above conclusions].&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.osti.gov/biblio/1243219&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Why is MP2-Water &amp;quot;Cooler&amp;quot; and &amp;quot;Denser&amp;quot; than DFT-Water?&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;When I searched &lt;code&gt;MP2 kcal/mol accuracy&lt;/code&gt; on Google, the first page of results gave me the following 10 results, in order:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://arxiv.org/abs/2307.14514&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Can spin-component scaled MP2 achieve kJ/mol accuracy for cohesive energies of molecular crystals?&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubmed.ncbi.nlm.nih.gov/16833631/&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Pragmatic ab initio prediction of enthalpies of formation for large molecules: accuracy of MP2 geometries and frequencies using CCSD(T) correlation energies&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.nature.com/articles/s41467-020-19093-1&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Quantum chemical accuracy from density functional approximations via machine learning&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_chemistry_composite_methods**&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Quantum chemistry composite methods&lt;/strong&gt;&lt;/a&gt; [This is the most irrelevant result in this list, in my opinion].&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/jp050036j&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Accurate Calculation of the Heats of Formation for Large Main Group Compounds with Spin-Component Scaled MP2 Methods&lt;/strong&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct9005882&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;Accurate Intermolecular Interaction Energies from a Combination of MP2 and TDDFT Response Theory&lt;/strong&gt;&lt;/a&gt; [This one is the second-most irrelevant result in this list, in my opinion].&lt;/li&gt;&#xA;&lt;li&gt;This one was a repeat of &amp;quot;Accurate Calculation of the Heats of Formation for Large Main Group Compounds with Spin-Component Scaled MP2 Methods&amp;quot; but on ResearchGate instead of the ACS journal website.&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.researchgate.net/figure/RMS-Deviations-kcal-mol-for-the-MP2-F12-correlation-component-of-cohesive_tbl2_317077875&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;RMS Deviations (kcal/mol) for the MP2-F12 correlation component of cohesive&lt;/strong&gt;&lt;/a&gt; [Table from &amp;quot;Conventional and Explicitly Correlated ab Initio Benchmark Study on Water Clusters: Revision of the BEGDB and WATER27 Data Sets&amp;quot;].&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/jcc.23539&quot; rel=&quot;noreferrer&quot;&gt;New accurate benchmark energies for large water clusters: DFT is better than expected&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Related MMSE posts&lt;/h1&gt;&#xA;&lt;p&gt;Ideally these would appear in the &amp;quot;Related&amp;quot; section in our sidebar, but at the moment they don't:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9786/5&quot;&gt;Does the RI method actually accelerate basis convergence of MP2, &amp;quot;by one more zeta&amp;quot;?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9838/5&quot;&gt;Does the accuracy of RI-MP2 follow the higher number of zetas of the main and fitting bases?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9784/5&quot;&gt;Does NWChem support RI approximations in the MP2 part of double hybrids?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9839/5&quot;&gt;Are frozen-core approximations for the elements of first or second row accurate for potentially extremely short bond distances present in the molecule&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;RI-B2PLYP-D3 is mentioned in the last of these, and in theory it would have a similar cost to RI-MP2 since the dominant-scaling part of B2PLYP-D3 is the MP2-like calculation. Since &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11460/which-is-better-for-binding-energies-dft-d3-or-ri-mp2#comment24484_11460&quot;&gt;in this comment&lt;/a&gt; you were worried about the cost of B2PLYP, RI-B2PLYP-D3 might be a good option for you too.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-08-10T17:47:15.037" LastActivityDate="2023-08-10T17:47:15.037" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11463" PostTypeId="5" CreationDate="2023-08-10T17:02:04.813" Score="0" Body="" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-08-10T17:02:04.813" LastActivityDate="2023-08-10T17:02:04.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11464" PostTypeId="4" CreationDate="2023-08-10T17:02:04.813" Score="0" Body="Questions like &quot;which is better A or B?&quot; or requests for benchmarks, such as &quot;is MP2 on average expected to give relative energies with an accuracy of better than 3.7 kcal/mol&quot;?" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-08-10T17:02:04.813" LastActivityDate="2023-08-10T17:02:04.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11465" PostTypeId="1" CreationDate="2023-08-10T19:20:14.120" Score="2" ViewCount="234" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iyMNk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iyMNk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;I am trying to compute the density of states of rutile and anatase (TiO2) using Quantum Espresso package. A very basic calculation. However, after all the procedures (scf + nscf + dos) the resulting density of states only shows data below the Fermi level and I cannot see any band gap as it should above 10 eV (check Figure). I have already included Hubbard U correction; the issue is present in MoS2 calculations as well. Does anyone has a clue or has faced a similar situation? Many thanks for considering my request.&lt;/p&gt;&#xA;&lt;p&gt;After some experimentation, seems that I have better results when the number of bands in the nscf input file equals the total number of electrons (second figure)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nbnd = # of electrons&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As per the supporting information from QE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nbnd = # of electrons / 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;with a Fermi energy of ~9.05 eV.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/geHTx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/geHTx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;SCF Input file for rutile&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! restart_mode = 'restart'&#xA;! time wall of 2 h&#xA;! k-points distance of 0.2 A-1&#xA;! using atomic positions and cell parameters from structural optimization &#xA;&amp;amp;CONTROL&#xA;  restart_mode = 'from_scratch'&#xA;  title = 'TiO2 rutile scf'&#xA;  calculation = 'scf'&#xA;  etot_conv_thr =   6.0000000000d-05&#xA;  forc_conv_thr =   1.0000000000d-04&#xA;  outdir = './tmp/'&#xA;  prefix = 'rutile-scfHU'&#xA;  pseudo_dir = '/home/ps_pbe_eff/'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'high'&#xA;  max_seconds = 7.2d+3&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ecutrho =   5.0000000000d+02&#xA;  ecutwfc =   5.0000000000d+01&#xA;  ibrav = 0&#xA;  nat = 6&#xA;  nosym = .false.&#xA;  ntyp = 2&#xA;  occupations = 'fixed'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.2000000000d-09&#xA;  electron_maxstep = 80&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;  press_conv_thr=0.1&#xA;/&#xA;ATOMIC_SPECIES&#xA;O      15.9994 O.pbe-n-kjpaw_psl.0.1.UPF&#xA;Ti     47.867 ti_pbe_v1.4.uspp.F.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;Ti            0.5000000000        0.5000000000        0.0000000000&#xA;Ti            0.0000000000        0.0000000000        0.5000000000&#xA;O             0.6948896839        0.6948896839        0.5000000000&#xA;O             0.1948896839        0.8051103161        0.0000000000&#xA;O             0.8051103161        0.1948896839        0.0000000000&#xA;O             0.3051103161        0.3051103161        0.5000000000 &#xA;K_POINTS automatic&#xA;10 10 15 0 0 0&#xA;CELL_PARAMETERS (angstrom)&#xA;   4.642542635   0.000000000   0.000000000&#xA;   0.000000000   4.642542635   0.000000000&#xA;   0.000000000   0.000000000   2.963491358&#xA;HUBBARD {ortho-atomic}&#xA;U Ti-3d 5.7066 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;NSCF input file for&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! restart_mode = 'restart'&#xA;! time wall of 2 h&#xA;! k-points distance of 0.2 A-1&#xA;! using atomic positions and cell parameters from structural optimization&#xA;&amp;amp;CONTROL&#xA;  restart_mode = 'from_scratch'&#xA;  title = 'TiO2 rutile nscf'&#xA;  calculation = 'nscf'&#xA;  etot_conv_thr =   6.0000000000d-05&#xA;  forc_conv_thr =   1.0000000000d-04&#xA;  outdir = './tmp/'&#xA;  prefix = 'rutile-scfHU'&#xA;  pseudo_dir = '/home/ps_pbe_eff/'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'high'&#xA;  max_seconds = 7.2d+3&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ecutrho =   5.0000000000d+02&#xA;  ecutwfc =   5.0000000000d+01&#xA;  ibrav = 0&#xA;  nat = 6&#xA;  nbnd = 24&#xA;  nosym = .false.&#xA;  occupations = 'tetrahedra'&#xA;  ntyp = 2&#xA;  nbnd = 48&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.2000000000d-09&#xA;  electron_maxstep = 80&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;  press_conv_thr=0.1&#xA;/&#xA;ATOMIC_SPECIES&#xA;O      15.9994 O.pbe-n-kjpaw_psl.0.1.UPF&#xA;Ti     47.867 ti_pbe_v1.4.uspp.F.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;Ti            0.5000000000        0.5000000000        0.0000000000&#xA;Ti            0.0000000000        0.0000000000        0.5000000000&#xA;O             0.6948896839        0.6948896839        0.5000000000&#xA;O             0.1948896839        0.8051103161        0.0000000000&#xA;O             0.8051103161        0.1948896839        0.0000000000&#xA;O             0.3051103161        0.3051103161        0.5000000000 &#xA;K_POINTS automatic&#xA;10 10 15 0 0 0&#xA;CELL_PARAMETERS (angstrom)&#xA;   4.642542635   0.000000000   0.000000000&#xA;   0.000000000   4.642542635   0.000000000&#xA;   0.000000000   0.000000000   2.963491358&#xA;HUBBARD {ortho-atomic}&#xA;U Ti-3d 5.7066 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the out file for the DOS&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;     Program DOS v.7.1 starts on 23Aug2023 at  9:46:18 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;         &amp;quot;P. Giannozzi et al., J. Chem. Phys. 152 154105 (2020);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI), running on     1 processors&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;     252587 MiB available memory on the printing compute node when the environment starts&#xA; &#xA;&#xA;     Reading xml data from directory:&#xA;&#xA;     ./tmp/rutile-scfHU.save/&#xA;     file O.pbe-n-kjpaw_psl.0.1.UPF: wavefunction(s)  2P renormalized&#xA;&#xA;     IMPORTANT: XC functional enforced from input :&#xA;     Exchange-correlation= PBE&#xA;                           (   1   4   3   4   0   0   0)&#xA;     Any further DFT definition will be discarded&#xA;     Please, verify this is what you really want&#xA;&#xA; &#xA;     G-vector sticks info&#xA;     --------------------&#xA;     sticks:   dense  smooth     PW     G-vecs:    dense   smooth      PW&#xA;     Sum        3061    1225    373                81347    20585    3401&#xA; &#xA;     Using Slab Decomposition&#xA; &#xA;&#xA;     Check: negative core charge=   -0.000007&#xA;&#xA;     negative rho (up, down):  3.142E-03 0.000E+00&#xA;&#xA;     Tetrahedra used&#xA;&#xA; &#xA;     DOS          :   1m 8.93s CPU   1m10.19s WALL&#xA;&#xA; &#xA;   This run was terminated on:   9:47:28  23Aug2023            &#xA;&#xA;=------------------------------------------------------------------------------=&#xA;   JOB DONE.&#xA;=------------------------------------------------------------------------------=&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7695" LastEditorUserId="7695" LastEditDate="2023-08-24T16:53:17.810" LastActivityDate="2023-08-24T16:53:17.810" Title="Computing the density of states (DOS) using quantum espresso (QE) is not working, partially" Tags="|density-functional-theory|quantum-espresso|density-of-states|" AnswerCount="0" CommentCount="7" ClosedDate="2023-09-13T03:48:59.157" ContentLicense="CC BY-SA 4.0" />
  <row Id="11466" PostTypeId="1" CreationDate="2023-08-10T23:14:47.830" Score="7" ViewCount="322" Body="&lt;p&gt;I am trying to determine the potential energy curves for a CH2Cl radical by varying the C-Cl distance. For that I use the CASSCF method In MOLPRO with the aug-cc-pVTZ basis set, I didn't get smooth curves. The active space that I choose in Cs symmetry is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;occ(11,3)closed ( 5.1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried other active spaces but I didn't solve the problem so please how can I proceed to solve this problem?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="7697" LastEditorUserId="5" LastEditDate="2023-08-10T23:21:03.267" LastActivityDate="2023-08-11T05:42:38.447" Title="Choosing an active space for CASSCF using Molpro" Tags="|casscf|molpro|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11467" PostTypeId="2" ParentId="11466" CreationDate="2023-08-10T23:41:07.390" Score="6" Body="&lt;p&gt;First of all, your syntax isn't exactly the way the &lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=the_mcscf_program_multi&quot; rel=&quot;noreferrer&quot;&gt;MOLPRO manual for the CASSCF program (called &amp;quot;Multi&amp;quot;) instructs&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCC,n1,n2,…,n8; &#xA;CLOSED,n1,n2,…,n8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The following example is from the same page of the MOLPRO documentation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{multi;occ,9,2;closed,4,1; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If by (11,3), you mean you have 11 active orbitals with the A' irrep and 3 in the A'' irrep, then I don't find it immediately obvious which 11 orbitals you're choosing.&lt;/p&gt;&#xA;&lt;p&gt;It might be better for you to try without specifying the &lt;code&gt;occ&lt;/code&gt; parameter at all, as the manual says:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In the absence of an OCC card, the information from the most recent MCSCF calculation is used, or, if there is none, those orbitals corresponding to a minimal valence set, i.e., full valence space, are used.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The &amp;quot;full valence active space&amp;quot; is the one that I would recommend for your first attempt anyway. Before trying this, for a very large number of geometries, I recommend trying it with the STO-3G basis set, then the 6-31G basis set, then the aug-cc-pVDZ basis set, before doing it on the basis set that you've been using, which is aug-cc-pVTZ. The calculations with the smaller basis sets will be a lot faster, so they will burn less of your computer resources. If there's an issue with smoothness of the potential energy curves, then you might want to increase the size of your active space, but if there is no issue, then this &amp;quot;full valence active space&amp;quot; that I'm recommending, has solved your problem!&lt;/p&gt;&#xA;&#xA;" OwnerUserId="5" LastActivityDate="2023-08-10T23:41:07.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11468" PostTypeId="1" CreationDate="2023-08-10T23:52:24.873" Score="2" ViewCount="55" Body="&lt;p&gt;I don't understand this graph. From the graph, does it mean that at high pressures the oxide layer is stable and this stability reduces at low pressures and temperatures?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dW7fL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dW7fL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3442" LastEditorUserId="5" LastEditDate="2023-08-11T00:03:40.040" LastActivityDate="2023-08-11T00:03:40.040" Title="What is the meaning of a &quot;free energy per unit surface area&quot; vs &quot;pressure&quot; plot?" Tags="|mathematical-modeling|surfaces|free-energy|metal-oxide|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11469" PostTypeId="2" ParentId="11468" CreationDate="2023-08-11T00:02:39.303" Score="1" Body="&lt;p&gt;The graph does show that at high pressures the &lt;span class=&quot;math-container&quot;&gt;$\Delta G$&lt;/span&gt; per surface area values are lower, which would usually indicate stability. I agree with you that as the pressure goes lower, the stability reduces.&lt;/p&gt;&#xA;&lt;p&gt;However I disagree regarding temperature: As the temperatures decrease (from the green curve denoting 1500K to the blue curve denoting 300K), the &lt;span class=&quot;math-container&quot;&gt;$\Delta G$&lt;/span&gt; values are going down, meaning an &lt;em&gt;increase&lt;/em&gt; in stability.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-08-11T00:02:39.303" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11470" PostTypeId="2" ParentId="11466" CreationDate="2023-08-11T05:42:38.447" Score="7" Body="&lt;p&gt;As a developer of &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;noreferrer&quot;&gt;MOKIT&lt;/a&gt;, I would like to recommend the &lt;strong&gt;automatic CASSCF computation&lt;/strong&gt; using the &lt;code&gt;automr&lt;/code&gt; utility in MOKIT. We do not need to manually choose/permute orbitals, no need to specify the active space size, no need to start from a minimal basis set, and no need to take care about the input format of Molpro. All these things can be determined automatically.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Firstly&lt;/strong&gt;, we write a .gjf file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem=48GB&#xA;%nprocshared=28&#xA;#p CASSCF/aug-cc-pVTZ&#xA;&#xA;mokit{CASSCF_prog=Molpro}&#xA;&#xA;0 2&#xA; C   -0.39943387    0.82617525    0.16329935&#xA; H   -0.04276103    1.33057344   -0.71035216&#xA; H   -1.46943387    0.82618843    0.16329935&#xA;Cl    0.36724607    1.91039566    2.04124183&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is just Gaussian gjf format and it can be visualized, e.g. using GaussView. &lt;code&gt;CASSCF_prog=Molpro&lt;/code&gt; means you want Molpro to do the CASSCF computation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Secondly&lt;/strong&gt;, submit the job&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;automr CH2Cl.gjf &amp;gt;CH2Cl.out 2&amp;gt;&amp;amp;1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It takes less than 3 minutes and CASSCF is converged in 2 cycles. &lt;code&gt;automr&lt;/code&gt; will call Gaussian, GAMESS, Molpro programs successively (in addtion, PySCF is needed), this procedure is actually UHF-&amp;gt;UNO-&amp;gt;localized paired UNO-&amp;gt;GVB-&amp;gt;CASSCF. You can find the CASSCF active space size is determined as (3,3) in the output file &lt;code&gt;CH2Cl.out&lt;/code&gt;. Related energies and unpaired electrons are printed&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E(CASCI)  =      -498.47159238 a.u.&#xA;E(CASSCF) =      -498.47282188 a.u.&#xA;----------------------- Radical index -----------------------&#xA;Not spin singlet. Biradical character will not be computed.&#xA;Yamaguchi's unpaired electrons  (sum_n n(2-n)      ):  1.438&#xA;Head-Gordon's unpaired electrons(sum_n min(n,(2-n))):  1.230&#xA;Head-Gordon's unpaired electrons(sum_n (n(2-n))^2  ):  1.096&#xA;-------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The CASSCF initial orbitals and converged orbitals are stored in files&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CH2Cl_uhf_uno_asrot2gvb6_s.fch&#xA;CH2Cl_uhf_gvb6_CASSCF_NO.fch&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;respectively, which can be visualized using GaussView, Multiwfn, etc. The CAS(3,3) contains the singly occupied orbital and C-Cl bonding as well as anti-bonding orbitals:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/3Bkgu.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3Bkgu.png&quot; alt=&quot;CASSCF(3,3) natural orbitals&quot; /&gt;&lt;/a&gt;&#xA;(natural orbital occupation numbers are shown below the isosurfaces)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Thirdly&lt;/strong&gt;, in this step the user has two choices. The first choice is reading CASSCF orbitals of the current geometry and performing Molpro CASSCF calculations of other geometries. In the step above we will obtain files&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ch2cl_uhf_gvb6_casscf.a&#xA;CH2Cl_uhf_gvb6_CASSCF.com&#xA;CH2Cl_uhf_gvb6_CASSCF.xml&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The converged CASSCF orbitals are stored in the &lt;code&gt;.xml&lt;/code&gt; file. And you can modify the file &lt;code&gt;CH2Cl_uhf_gvb6_CASSCF.com&lt;/code&gt; to change geometries. &lt;code&gt;automr&lt;/code&gt; is not involved here.&lt;/p&gt;&#xA;&lt;p&gt;The second choice is again to use &lt;code&gt;automr&lt;/code&gt; to perform automatic calculations for each geometry. In this case you may need to specify &lt;code&gt;CASSCF(3,3)&lt;/code&gt; in the .gjf file when C-Cl bond is near its equilibrium bond length. This is because a not-stretched C-Cl bond has no multiconfigurational character and thus will not be put into the active space. If you do not specify &lt;code&gt;CASSCF(3,3)&lt;/code&gt; in such case, &lt;code&gt;automr&lt;/code&gt; may recommend &lt;code&gt;CASSCF(1,1)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Of course, you may think CAS(3,3) is a minimal active space and you want a larger one. This can be easily achieved since all bonding and anti-bonding orbitals are stores in &lt;code&gt;CH2Cl_uhf_uno_asrot2gvb6_s.fch&lt;/code&gt;, in which you will also find two C-H bonds, C,Cl core orbitals and Cl valence orbitals. All these orbitals are spatially localized and can be identified with no effort. You can simply perform a CASSCF(13e,10o) calculation using Molpro without permuting orbitals, here the active space includes also the bonding and anti-bonding orbitals of two C-H bonds, three Cl 3s/3p orbitals.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2023-08-11T05:42:38.447" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11471" PostTypeId="1" CreationDate="2023-08-11T18:14:59.757" Score="1" ViewCount="41" Body="&lt;p&gt;When I optimize the structure, the bonds between carbon atoms disappear, as shown in the figure. What could be the problem?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/56AGY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/56AGY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;my input file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation   = 'vc-relax'&#xA;      prefix      = 'Acene'&#xA;     outdir       = './outdir'&#xA;    pseudo_dir    = './pseudo'&#xA;        verbosity = 'high'&#xA;    etot_conv_thr = 0.0001&#xA;    forc_conv_thr = 0.001&#xA;            nstep = 100&#xA;          tstress = .true.&#xA;          tprnfor = .true.&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    a     =  1.00000e+01&#xA;    b     =  1.49977e+01&#xA;    c     =  1.43281e+01&#xA;    ibrav = 8&#xA;    nat   = 12&#xA;    ntyp  = 2&#xA;    degauss     = 1.00000e-02&#xA;    ecutrho     = 480&#xA;    ecutwfc     = 40&#xA;    input_dft   ='PBE'&#xA;    occupations = &amp;quot;smearing&amp;quot;&#xA;    smearing    = &amp;quot;gaussian&amp;quot;&#xA;    &#xA;/&#xA;&#xA; &amp;amp;ELECTRONS&#xA;            electron_maxstep = 150&#xA;                    conv_thr = 1.0D-6&#xA;                 mixing_mode = 'plain'&#xA;                 mixing_beta = 0.3&#xA;             diagonalization = 'david'&#xA; /&#xA;   &#xA;&#xA;/&#xA;&amp;amp;IONS&#xA;                ion_dynamics = 'bfgs'&#xA; /&#xA; &amp;amp;CELL&#xA;                cell_dynamics = 'bfgs'&#xA;/&#xA;ATOMIC_SPECIES&#xA;H       1.00794  H.pbe-van_ak.UPF&#xA;C      12.01070  H.pbe-van_ak.UPF&#xA;&#xA;&#xA;&#xA;ATOMIC_POSITIONS (angstrom)&#xA;C       5.000000   8.197203   5.954455&#xA;C       5.000000   6.800473   5.954455&#xA;C       5.000000   6.102108   7.164058&#xA;C       5.000000   6.800473   8.373661&#xA;C       5.000000   8.197203   8.373661&#xA;C       5.000000   8.895568   7.164058&#xA;H       5.000000   8.748257   5.000000&#xA;H       5.000000   6.249419   5.000000&#xA;H       5.000000   5.000000   7.164058&#xA;H       5.000000   6.249419   9.328116&#xA;H       5.000000   8.748257   9.328116&#xA;H       5.000000   9.997676   7.164058&#xA;&#xA;&#xA;&#xA;K_POINTS {gamma}&#xA;&#xA;&#xA;enter code here&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2023-08-11T18:45:14.597" LastActivityDate="2023-08-11T18:45:14.597" Title="Disappearing liaison when relaxing with Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|cell-optimization|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11472" PostTypeId="1" CreationDate="2023-08-11T21:41:41.863" Score="2" ViewCount="131" Body="&lt;p&gt;In optimising proteins with DFT/B3LYP, how can we detect the charge and multiplicity of the protein?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="5" LastEditDate="2023-08-14T07:12:55.923" LastActivityDate="2023-08-14T12:43:02.783" Title="How to select charge and multiplicity for macro-molecules?" Tags="|density-functional-theory|geometry-optimization|proteins|spin|charged-molecules|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11473" PostTypeId="1" AcceptedAnswerId="11474" CreationDate="2023-08-12T18:00:21.263" Score="4" ViewCount="78" Body="&lt;p&gt;I am trying to code a simple UKS program. For RKS code, the AO basis functions are set of the spatial part of the wavefunction of every atom involved in the molecule. For &lt;span class=&quot;math-container&quot;&gt;${H_2}$&lt;/span&gt;, this is the two Slater-type orbitals (STO) of each H. If you have a molecule involving an atom with a singulet electron (unfilled orbital like Li, B or N), what is the AO basis of the matrices in the ROHF and UKS case?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-08-13T20:06:41.127" LastActivityDate="2023-08-13T20:06:41.127" Title="What is the Atomic Orbital (AO) basis of the (overlap, kinetic, electric) matrices of the RKS, UKS and ROHF?" Tags="|density-functional-theory|computational-chemistry|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11474" PostTypeId="2" ParentId="11473" CreationDate="2023-08-13T06:37:16.373" Score="3" Body="&lt;p&gt;You mention three different acronyms of electronic structure methods&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;UKS = Unrestricted Kohn-Sham&lt;/li&gt;&#xA;&lt;li&gt;RKS (or ROKS) = Restricted open-shell Kohn-Sham&lt;/li&gt;&#xA;&lt;li&gt;ROHF = Restricted open-shell Hartree-Fock&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;They differ in whether they are using different orbitals for spin alpha and beta electrons (unrestricted) or the same orbitals but with different occupation numbers (restricted).&#xA;They also differ in the underlying Hamiltonian coming from Kohn-Sham density functional theory (KS) or Hartree-Fock (HF).&lt;/p&gt;&#xA;&lt;p&gt;They do not say anything about the underlying basis of the electronic wave function - you can use the same basis for all three.&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2023-08-13T06:37:16.373" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11475" PostTypeId="1" CreationDate="2023-08-13T12:33:04.587" Score="4" ViewCount="127" Body="&lt;p&gt;Unlike Graphene and MoS2, For borophene, I didn't find any inbuilt function in ASE. I have tried to make it, but i failed. So If anyone could help me, it will be great help.&lt;/p&gt;&#xA;&lt;p&gt;Since brophene has graphene like structure,I have tried to make it like graphene, although I think it's wrong approach.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.visualize import view&#xA;from ase import Atoms&#xA;from ase.build import hcp0001&#xA;&#xA;#--------------------------------------------------------&#xA;&#xA;slab = hcp0001('B',a=4.7, size=(5,8,1), vacuum=None, orthogonal=True)&#xA;view(slab)&#xA;&#xA;#---------------------------------------------------------&#xA;&#xA;cell = [[10.0, 0.0, 0.0],&#xA;        [0.0, 10.0, 0.0],&#xA;        [0.0, 0.0, 10.0]]&#xA;slab.set_cell(cell)&#xA;slab.pbc=True&#xA;&#xA;#-------------------------------------&#xA;&#xA;from gpaw import GPAW&#xA;calc = GPAW(xc='PBE')&#xA;slab.set_calculator(calc)&#xA;&#xA;#--------------------------------------&#xA;&#xA;opt = BFGS(slab,&#xA;           trajectory='borophene.traj',&#xA;           logfile='borophene.log')&#xA;&#xA;#---------------------------------------&#xA;&#xA;opt.run(fmax=0.05)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7399" LastActivityDate="2023-08-15T12:31:14.090" Title="How to Create a 2D Structure of Boron (Brophene) using ASE?" Tags="|python|atomic-simulation-environment|atomistic-simulation|2d-lattice|gpaw|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11476" PostTypeId="1" AcceptedAnswerId="11520" CreationDate="2023-08-13T20:53:36.733" Score="3" ViewCount="69" Body="&lt;p&gt;This question is a follow-up of this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11473/what-is-the-atomic-orbital-ao-basis-of-the-overlap-kinetic-electric-matric&quot;&gt;post&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The basis set to approximate the overlap, kinetic, electron repulsion and proton-electron attraction matrices is to be choosed by the user depending on the method. What I want is to code a STO-6G UKS code. Let's take two examples so that I can understand and then implement these ideas afterwards :&lt;/p&gt;&#xA;&lt;h2&gt;Example &lt;span class=&quot;math-container&quot;&gt;$NO_2$&lt;/span&gt; :&lt;/h2&gt;&#xA;&lt;p&gt;The valence orbitals of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; : &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt; and the valence orbitals of &lt;span class=&quot;math-container&quot;&gt;$O$&lt;/span&gt; : &lt;span class=&quot;math-container&quot;&gt;$2p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$2p_y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$2p_z$&lt;/span&gt; with one of the p orbitals filled.&lt;/p&gt;&#xA;&lt;p&gt;I will not take the frozen approximation of the s-orbitals.&lt;/p&gt;&#xA;&lt;p&gt;I denote : &lt;span class=&quot;math-container&quot;&gt;$\chi^{orbital}_O$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\chi^{orbital}_N$&lt;/span&gt; the spatial part of the atomic orbitals for orbital &lt;span class=&quot;math-container&quot;&gt;$\in \{1s, 2s, 2p_x, 2p_y, 2p_z \}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then what is the spatial-spin orbital basis set of the overlap, kinetic, Coulomb (Exchange) and proton attraction operators/matrices for each electronic structure methods by only using 1s, 2s and 2p orbitals?&lt;/p&gt;&#xA;&lt;h2&gt;What I think atm :&lt;/h2&gt;&#xA;&lt;h3&gt;RKS case&lt;/h3&gt;&#xA;&lt;p&gt;The basis are the same for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spin orbitals. The the energy is simply the total energy of the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; molecular orbitals mutiplied by two since the density is supposed to be the same for &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; molecular orbitals.&lt;/p&gt;&#xA;&lt;h3&gt;ROKS/UKS case&lt;/h3&gt;&#xA;&lt;p&gt;I think that the matrices of one of the spin will be at least one size larger.&lt;/p&gt;&#xA;&lt;h2&gt;Example  &lt;span class=&quot;math-container&quot;&gt;$O_2$&lt;/span&gt; :&lt;/h2&gt;&#xA;&lt;p&gt;Same question for &lt;span class=&quot;math-container&quot;&gt;$O_2$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-08-13T22:52:36.573" LastActivityDate="2023-08-23T15:00:41.717" Title="Basis set of the overlap, kinetic, electronic matrices for RKS, UKS and ROKS code: O2 and NO2 cases" Tags="|density-functional-theory|computational-chemistry|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11477" PostTypeId="2" ParentId="11475" CreationDate="2023-08-13T21:48:44.300" Score="2" Body="&lt;p&gt;As you said, borophene has the same structure as graphene. Then you can first build a graphene structure in ASE, then change every atom to boron, and scale the lattice parameters to be that of a borophene. Here is the code (the lattice constant values might not be right so you need to double check that)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import graphene&#xA;from ase.visualize import view&#xA;&#xA;# Build a graphene monolayer&#xA;atoms = graphene()&#xA;a_borophene = 2.90&#xA;a_graphene = 2.46&#xA;scaling_factor = a_borophene / a_graphene&#xA;# Save the fractional coordinates &#xA;fracs = atoms.get_scaled_positions()&#xA;# Scale the unit cell x and y dimensions by the scaling factor&#xA;atoms.cell *= (scaling_factor, scaling_factor, 1)&#xA;# Scale the atomic coordinates&#xA;atoms.positions = fracs @ atoms.cell&#xA;# Change carbon atoms to boron&#xA;for atom in atoms:&#xA;    atom.symbol = 'B'&#xA;# Center the structure in the z direction&#xA;atoms.center(vacuum=5., axis=2)&#xA;# Visualize&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And there you have it&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/oxg4r.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oxg4r.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-08-13T21:48:44.300" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11478" PostTypeId="2" ParentId="11472" CreationDate="2023-08-14T07:11:32.613" Score="4" Body="&#xA;&lt;p&gt;Sometimes the protein has been studied experimentally (or thoroughly by theory), and a consensus has been made about the most common charge and multiplicity for the molecule. In most cases, I would recommend to look at the literature to find such &lt;em&gt;established&lt;/em&gt; values.&lt;/p&gt;&#xA;&lt;p&gt;When not much is known about the molecule, you can do calculations with various different multiplicities to see which one provides the most stable molecule (if your calculations on a triplet state of the molecule are considerably lower than anything you're able to obtain with a singlet or quintuplet, etc. state, then it probably makes most sense to treat the molecule as having a triplet spin multiplicity).&lt;/p&gt;&#xA;&lt;p&gt;Unfortunately for the charge, it's not as easy, because simply by adding more electrons, your molecule's energy will drop, so H2O&lt;sup&gt;-9&lt;/sup&gt; has a lower energy than H2O, but that doesn't mean that H2O&lt;sup&gt;-9&lt;/sup&gt; is more stable. You could still try to look at energetics, such as the depth and width of the deepest well of the potential energy surface, but that may be very impractical to do, especially for a protein, and it might not be accepted by people working in your field. Alternatively, you can determine the charge with as much knowledge about charges as you have (I've worked with some people in the past who were very good at this, as well as determining oxidation states and partial charges of atoms in the molecule). When in doubt, if there's no good reason available to believe that the molecule is charged, I would assume it's neutral and proceed with the analysis to determine the most energetically favorable spin multiplicity.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-08-14T07:11:32.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11479" PostTypeId="1" AcceptedAnswerId="11483" CreationDate="2023-08-14T09:29:31.657" Score="3" ViewCount="67" Body="&lt;p&gt;I'm testing some scaling properties of various density functional approximations, which involves evaluating the functionals on model systems with very low density. I am using the funcition &lt;code&gt;dft.libxc.eval_xc&lt;/code&gt; in PySCF, yet I found that when the density is lower than some specific thresholds, the function just returns zero instead of evaluating the functional.&lt;/p&gt;&#xA;&lt;p&gt;I have read the PySCF python source code and found that this might be caused by the default density threshold of libxc, so I guess maybe I can disable that cut-off by modifying the file &lt;code&gt;pyscf/lib/libxc_itrf.so&lt;/code&gt;, but that seems kind of complicated for me. So I wonder if there is a more straightforward way to do such thing?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance for the help!&lt;/p&gt;&#xA;" OwnerUserId="6185" LastActivityDate="2023-08-16T12:20:45.610" Title="Change the density threshold for functional evaluation in PySCF" Tags="|density-functional-theory|pyscf|libxc|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11480" PostTypeId="2" ParentId="11472" CreationDate="2023-08-14T12:43:02.783" Score="4" Body="&lt;p&gt;Unless there are transition metals (e.g. Fe, Mn, Cu, Ni) present in the active site, proteins typically have singlet state. There are several programs out there, such as propka, that can propose protonation states of the different amino acid residues. And as Nike already mentioned, often there could be experimental information about the protonation state of His residues. With the protonation state of the different residues, you then obtain the overall charge of the protein.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-08-14T12:43:02.783" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11481" PostTypeId="2" ParentId="11475" CreationDate="2023-08-15T12:31:14.090" Score="2" Body="&lt;p&gt;You could define the formula for a graphene-like structure. For example, &lt;code&gt;ase.build.graphene(formula='B2', a=2.46, thickness=0.0, size=(1, 1, 1), vacuum=None)&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="7721" LastActivityDate="2023-08-15T12:31:14.090" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11482" PostTypeId="1" CreationDate="2023-08-15T15:07:02.683" Score="3" ViewCount="215" Body="&lt;p&gt;I wondered if anyone knows of a way to calculate the reorganization energy of a molecule utilizing orca 5.0.3.&lt;/p&gt;&#xA;" OwnerUserId="7608" LastActivityDate="2023-08-18T21:27:53.497" Title="Calculating Reorganisation energy using ORCA" Tags="|orca|spin-orbit-coupling|energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11483" PostTypeId="2" ParentId="11479" CreationDate="2023-08-16T11:39:46.033" Score="2" Body="&lt;p&gt;I realize that what I need is only the libxc in PySCF, so I can actually just use libxc rather than PySCF. I installed the python binding of libxc, namely &lt;code&gt;pylibxc&lt;/code&gt;, and wrote a function that managed to do what I want:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def eval_xc(xc_code,rho):&#xA;    hyb, id_fac = dft.libxc.parse_xc(xc_code)&#xA;    inp = {}&#xA;    inp[&amp;quot;rho&amp;quot;] = rho[0]&#xA;    inp[&amp;quot;sigma&amp;quot;] = rho[1]**2+rho[2]**2+rho[3]**2&#xA;    inp[&amp;quot;tau&amp;quot;] = rho[5]&#xA;    exc = 0&#xA;    for id,fac in id_fac:&#xA;        func = pylibxc.LibXCFunctional(id,1)&#xA;        func.set_dens_threshold(1E-30)&#xA;        ret = func.compute(inp,do_vxc=False)&#xA;        temp = ret[&amp;quot;zk&amp;quot;].ravel()&#xA;        exc = exc + temp*fac&#xA;    return exc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Yet I found that when the density is too low, the &lt;code&gt;compute()&lt;/code&gt; returns 'nan'. So it seems that the default density threshold is somehow reasonable. Maybe I must a higher precision than float64 to evaluate the functionals on extremely low density systems.&lt;/p&gt;&#xA;" OwnerUserId="6185" LastEditorUserId="6185" LastEditDate="2023-08-16T12:20:45.610" LastActivityDate="2023-08-16T12:20:45.610" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11484" PostTypeId="1" AcceptedAnswerId="11485" CreationDate="2023-08-16T13:37:12.320" Score="5" ViewCount="43" Body="&lt;p&gt;I'm writing a computer simulation code to model a system of non-spherically symmetric molecules, meaning that their state are described by both angular and translational components.&lt;/p&gt;&#xA;&lt;p&gt;In typical Monte Carlo simulations with only translational motion, it's common to adjust the maximum translation displacement distance until about 50% of the trial moves are accepted. This technique ensures that the simulation explores the configuration space efficiently without getting stuck in local minima or moving too erratically.&lt;/p&gt;&#xA;&lt;p&gt;However, in my system, I need to update both translational and angular positions. Is there a standard or simple algorithm that can guide me to make a reasonable choice for both the maximum displacement distance and the maximum rotation angle, simultaneously?&lt;/p&gt;&#xA;" OwnerUserId="610" LastActivityDate="2023-08-16T21:09:33.067" Title="How to Balance Translational and Angular Maximum displacements in a Monte Carlo Simulation of Non-Spherically Symmetric Molecules?" Tags="|monte-carlo|algorithms|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11485" PostTypeId="2" ParentId="11484" CreationDate="2023-08-16T21:09:33.067" Score="3" Body="&lt;p&gt;A valid Metropolis Monte Carlo simulation requires you to calculate the relative probability of proposing a forward move to a reverse move -- that is the probability that a move from A to B would be proposed, divided by the probability that a move from B to A would be proposed.&lt;/p&gt;&#xA;&lt;p&gt;You may not have thought about that before but that's because spatial Monte Carlo is straightforward: if the proposal distribution is spatially symmetric (a move 1 unit to the right will be proposed as often as a move 1 unit to the left), then this ratio is simply 1 by construction and we never have to worry about multiplying by it.&lt;/p&gt;&#xA;&lt;p&gt;With any symmetric scheme for proposing angular moves (rotating 20 degrees left is proposed as often as rotating 20 degrees right) the same is true (the forward-reverse ratio is 1), so you are free to tune the angular proposal scheme any way you like as long as it remains symmetric.&lt;/p&gt;&#xA;&lt;p&gt;To maintain the &lt;em&gt;total&lt;/em&gt; acceptance ratio at 50%, then, you have two options:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Set parameters so that of all translational moves proposed, 50% are accepted, and of all rotational moves proposed, 50% are accepted. Then you can independently optimise how often you propose a translational move or a rotational move (for best mixing) and know that the total acceptance ratio will remain around 50%.&lt;/li&gt;&#xA;&lt;li&gt;If a particular category of moves is very difficult to accept then you will just have to sample it less often. For example, if rotational moves are only accepted 20% of the time at best, then you might tune translational moves to be accepted 60% of the time, and then propose translational moves 80% of the time to achieve a total acceptance ratio of 60% × 80% (trans) + 20% × 20% (rot) which is approximately 50%.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, it is always worth considering whether you should just reuse someone else's software -- such as &lt;a href=&quot;http://gomc.eng.wayne.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;GOMC&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-08-16T21:09:33.067" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11486" PostTypeId="1" CreationDate="2023-08-17T02:39:11.067" Score="0" ViewCount="65" Body="&lt;p&gt;The material system is described by the Hamiltonian and overlap matrice, with the Gaussian basis set.&lt;/p&gt;&#xA;&lt;p&gt;At Gamma point in the reciprocal space, the upper triangle block and the lower triangle block in the Hamiltonian matrix are symmetric to each other.&lt;/p&gt;&#xA;&lt;p&gt;What about other k point? At other k points in the reciprocal space, are the upper and lower triangle block in the Hamiltonian still symmetric to each other or not?&lt;/p&gt;&#xA;&lt;p&gt;Would anyone give me some suggestions?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="142" LastEditDate="2023-08-23T14:39:41.213" LastActivityDate="2023-08-23T14:39:41.213" Title="Symmetric issue about the Gaussian basis Hamiltonian" Tags="|quantum-mechanics|periodic-system|periodic-boundary-conditions|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11487" PostTypeId="2" ParentId="11486" CreationDate="2023-08-17T06:39:07.403" Score="2" Body="&lt;p&gt;The simplest way of putting this is to note that the Hamiltonian is an operator corresponding to an observable (the energy) and hence &lt;a href=&quot;https://en.wikipedia.org/wiki/Mathematical_formulation_of_quantum_mechanics&quot; rel=&quot;nofollow noreferrer&quot;&gt;by the postulates of quantum mechanics&lt;/a&gt; must be Hermitian. In the case of a real Hamiltonian matrix, such as typically occurs at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point, this reduces to (real) symmetric. However at other k points this is not the usual case, and the matrix is (complex) Hermitian.&lt;/p&gt;&#xA;&lt;p&gt;More strictly one should note that the full reciprocal space representation of the Hamiltonian doesn't contain merely one k point, but in fact is an infinite sized matrix that contains all the k points. However as the whole point of the introduction of k points is to symmetry adapt the basis to take advantage of the translational symmetry of the periodic system, this infinite matrix is block diagonal, with each block containing 1 k point. Thus we can consider each k point separately, and the argument in the first paragraph holds for each k point individually.&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="269" LastEditDate="2023-08-23T06:26:14.547" LastActivityDate="2023-08-23T06:26:14.547" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11488" PostTypeId="1" AcceptedAnswerId="11491" CreationDate="2023-08-17T09:38:50.477" Score="6" ViewCount="94" Body="&lt;p&gt;My question is a follow-up question to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11421/5&quot;&gt;question&lt;/a&gt; posted by Hemanth Haridas.&lt;/p&gt;&#xA;&lt;p&gt;I ran the example .py script in Geoff Hutchison's answer for the above mentioned question to generate .png files from .xyz files in avogadro using python.&lt;/p&gt;&#xA;&lt;p&gt;The script is available here : &lt;a href=&quot;https://gist.github.com/ghutchis/940b3f094969c515d02074bd9cb92c2b&quot; rel=&quot;nofollow noreferrer&quot;&gt;Script-Github&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I ran the script on my local Mac OS. The python script is in the same directory as the .xyz files. This is the output for one file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Opening mol2.xyz&#xA;b'{\n    &amp;quot;id&amp;quot;: 0,&#xA;\n  &amp;quot;jsonrpc&amp;quot;: &amp;quot;2.0&amp;quot;,&#xA;\n &amp;quot;result&amp;quot;: true\n}&#xA;\n'&#xA;b'{\n &amp;quot;error&amp;quot;: &#xA;{\n  &amp;quot;code&amp;quot;: -32601,\n  &#xA;&amp;quot;data&amp;quot;:&#xA; {\n  &amp;quot;request&amp;quot;: &#xA;{\n   &amp;quot;id&amp;quot;: 0,&#xA;\n   &amp;quot;jsonrpc&amp;quot;: &amp;quot;2.0&amp;quot;,\n                &#xA;&#xA;&amp;quot;method&amp;quot;: &amp;quot;saveGraphic&amp;quot;,&#xA;\n &amp;quot;params&amp;quot;: &#xA;{\n                    &#xA;&#xA;&amp;quot;fileName&amp;quot;:&#xA;&amp;quot;/Users/aimun/&#xA;avogadroextract/mol2.png&amp;quot;\n   }&#xA;\n   }\n   },\n        &#xA;&#xA;&amp;quot;message&amp;quot;:&#xA; &amp;quot;Method not found&amp;quot;\n    },\n   &#xA; &amp;quot;id&amp;quot;: 0,\n &amp;quot;jsonrpc&amp;quot;: &amp;quot;2.0&amp;quot;\n}\n'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The same error is displayed for all the other .xyz files in the directory.&lt;/p&gt;&#xA;&lt;p&gt;I have Avogadro 1.97.0 and Avogadro 1.2.0 installed in my mac. When I run the script, I see only the Avogadro 1.97.0 window being updated with the molecule structures, however, the files are not saved as .png.&lt;/p&gt;&#xA;&lt;p&gt;According to &lt;a href=&quot;https://www.jsonrpc.org/specification&quot; rel=&quot;nofollow noreferrer&quot;&gt;json-rpc 2.0 specification&lt;/a&gt;, &lt;code&gt;code: -32601&lt;/code&gt; means 'The method does not exist / is not available'.&lt;/p&gt;&#xA;&lt;p&gt;Any leads on how to address this will be highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7731" LastEditorUserId="5" LastEditDate="2023-08-19T03:24:01.480" LastActivityDate="2023-08-19T03:24:01.480" Title="How to address 'saveGraphic: Method not found' error in automating the generation of figures in avogadro using Python?" Tags="|python|visualization-software|avogadro|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11489" PostTypeId="1" CreationDate="2023-08-18T15:25:16.973" Score="2" ViewCount="54" Body="&lt;p&gt;I am trying to calculate the segregation energy of an element in a slab. The literature I have consulted all says I should calculate the formation energy of the impurity element in the bulk and subtract it from the formation energy at the surface. My question is which bulk are they referring to? The part which has been fixed in the slab model to represent the bulk? Or the isolated bulk material? If it's the former then making a substitution would require a relaxation of the material which is not possible since the bulk part is fixed and hence no ionic movement. How do I go about this?&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-08-18T15:25:16.973" Title="Segregation Energy calculation" Tags="|surfaces|formation-energy|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11490" PostTypeId="1" CreationDate="2023-08-18T18:39:00.377" Score="8" ViewCount="402" Body="&lt;p&gt;This is a follow-up of my previous question here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11488/5&quot;&gt;How to address &amp;#39;saveGraphic: Method not found&amp;#39; error in automating the generation of figures in avogadro using Python?&lt;/a&gt;, at which I was told to upgrade my software from version 1.97 to 1.98.&lt;/p&gt;&#xA;&lt;p&gt;I have tried downloading the 'nightly builds' from &lt;a href=&quot;https://two.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. When I click install &amp;gt; 'nightly build' for MacOS, it downloads a zip file. When I unzip it, the file name updates to Avogadro2-1.97.0, i.e. it's still not 1.98. I thought that the most recent version is 1.98 because it was mentioned &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11461/5&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Can someone please guide me on how to proceed?&lt;/p&gt;&#xA;" OwnerUserId="7731" LastEditorUserId="5" LastEditDate="2023-08-19T23:52:05.133" LastActivityDate="2023-08-19T23:52:05.133" Title="How may I install the latest version of a software?" Tags="|software|software-assistance|open-source|avogadro|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11491" PostTypeId="2" ParentId="11488" CreationDate="2023-08-18T18:45:39.960" Score="2" Body="&lt;p&gt;As mentioned in my &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11461/30&quot;&gt;answer&lt;/a&gt;, this is only available in the development version, which will be released as 1.98 soon. So if you're running 1.97 release, the method is not available.&lt;/p&gt;&#xA;&lt;p&gt;In principal, you can use a nightly build from &lt;a href=&quot;https://two.avogadro.cc&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://two.avogadro.cc&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I would suggest posting questions to the &lt;a href=&quot;https://discuss.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro forum&lt;/a&gt; since I don't come here often.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-08-18T18:45:39.960" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11493" PostTypeId="2" ParentId="11482" CreationDate="2023-08-18T21:27:53.497" Score="4" Body="&lt;p&gt;You essentially have two options.&lt;/p&gt;&#xA;&lt;p&gt;The first, simpler and more precise, is the so-called 4-point strategy. As the name says, you will need a total of 4 calculations.&#xA;Two geometry optimisations (one on each PES involved) and two single point calculations (each at the equilibrium geometries found before, but on the other PES).&#xA;To make an example, let's say you want to compute the reorganisation energy for electron transfer. So, you optimise your neutral molecule, and your anion, obtaining their equilibrium geometries, and their energies, respectively &lt;span class=&quot;math-container&quot;&gt;$E_n^n$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_-^-$&lt;/span&gt;. In this notation, the subscript denotes the PES, and the superscript the geometry, for instance.&lt;/p&gt;&#xA;&lt;p&gt;Then, using the equilibrium geometry of the neutral molecule, you run a single point calculation setting the molecule as if it were an anion, without changing the geometry, and you obtain &lt;span class=&quot;math-container&quot;&gt;$E_-^n$&lt;/span&gt;. Also, using the equilibrium geometry of the anion, you run a single point as if the molecule were neutral, obtaining &lt;span class=&quot;math-container&quot;&gt;$E_n^-$&lt;/span&gt;.&#xA;Each pair of energies on the same PES defines, through their difference, the reorganisation energy for the semi-reaction.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\lambda_n = E_n^- - E_n^n$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\lambda_- = E_-^n - E_-^-$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The total reorganisation energy of the process is obtained by summing the two reorganisation energies of the semi-reactions.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\lambda_{ET} = \lambda_n + \lambda_-$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Obviously, both contributions should be positive, since you are subtracting from an arbitrary point on the PES the energy of the minimum. If they are not positive, you are making some mistake.&lt;/p&gt;&#xA;&lt;p&gt;The second option, sometimes called Displaced Harmonic Oscillator (DHO), is more complicated, but can be useful, for instance when optimising a geometry on a certain state is difficult.&#xA;In this case, you can exploit to the harmonic approximation, and compute the normal modes on the PES on which you were able to optimise the geometry. Then you resort to Duschinsky's equation to approximate the PES of the other electronic state. In case of our example concerning electron transfer, you get&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Q_- = JQ_n + K$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$Q_-$&lt;/span&gt; is the set of normal modes on the PES of the anion, &lt;span class=&quot;math-container&quot;&gt;$Q_n$&lt;/span&gt; is the set of normal modes on the PES of the neutral molecule, &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is the vector of displacements on the PES of the anion from the equilibrium positions, and &lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is a rotation called Duschinsky matrix. There are various approximations you can adopt on this equation. For instance, you can decide that &lt;span class=&quot;math-container&quot;&gt;$J = I$&lt;/span&gt;. In this way, it becomes easy to compute the displacement vector &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; from the gradient computed on the PES of the anion at the geometry of the neutral molecule: if you think about it, you know that along each vibration you are approximating the potential with a parabola. So, knowing the slope of the tangent to that parabola tells you the displacement. In essence, you project the cartesian gradients that you get as output from a QM code onto the normal modes, to get the displacement along each mode.&#xA;From the displacements, you should be able to obtain Huang-Rhys factors, or reorganisation energies along each mode. The total reorganisation energy on the PES that you are approximating this way is given by summing over modes. Of course, since you are making use of the harmonic approximation, displacements from equilibrium positions should be small. Then this approach might become difficult to adopt if (mass-weighted-)cartesian coordinates are not very appropriate for the problem, and you should use internal coordinates.&lt;/p&gt;&#xA;&lt;p&gt;For some formulas concerning this second approach, you can have a look &lt;a href=&quot;http://dx.doi.org/10.1016/j.ccr.2006.05.019&quot; rel=&quot;nofollow noreferrer&quot;&gt;at this paper by Neese&lt;/a&gt;, to get an idea of the proper units to carry out the operations. For the approximations you can adopt on Duschinsky's equation and their appropriateness, my favourite paper is &lt;a href=&quot;https://doi.org/10.1039/C2CP41169E&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one by Santoro&lt;/a&gt;. If I remember correctly, these approximations used in the second approach should be implemented in ORCA, since they are also used in the calculation of vibronic electronic spectra, resonance Raman, etc. You have to check what data they give you as output.&lt;/p&gt;&#xA;&lt;p&gt;Finally, I used electron transfer as an example, but the same approaches can be used for hole transfer (in that case you deal with the neutral molecule and the cation), exciton transfer (in which case you deal with ground and excited state), or other processes involving any two electronic states.&lt;/p&gt;&#xA;" OwnerUserId="7726" LastActivityDate="2023-08-18T21:27:53.497" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11494" PostTypeId="1" AcceptedAnswerId="12124" CreationDate="2023-08-19T00:31:14.667" Score="2" ViewCount="98" Body="&lt;p&gt;I have two solid surfaces that I want to combine to study the interface as seen in the attached image. What I know is the lower part of the bottom structure is fixed to mimic the bulk. However, do I have to do the same for the top layer too? Where by I have to fix the top part to mimic the bulk as I have shown in the diagram? Or the top layer need no bulk part? Your response would be deeply appreciated. Thank you.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/7YlEn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7YlEn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-12-20T20:31:49.257" Title="How to model an interface between two solids" Tags="|crystallography|surfaces|solid-solid-interface|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="11495" PostTypeId="2" ParentId="11490" CreationDate="2023-08-19T02:12:51.097" Score="10" Body="&lt;h1&gt;Development versions of software&lt;/h1&gt;&#xA;&lt;p&gt;When version 1.98 was mentioned in the answer that is linked in your question, it said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Yes, this is in the latest development version (1.98) as I discussed on the &lt;a href=&quot;https://discuss.avogadro.cc/t/images-for-a-whole-directory/4430/2?u=ghutchis&quot; rel=&quot;noreferrer&quot;&gt;Avogadro forum&lt;/a&gt;.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The key phrase here is &amp;quot;development version&amp;quot;, which is usually a term that indicates that it's an &amp;quot;unreleased&amp;quot; version that is used by developers or other people who need to use some of the features that have not yet been &amp;quot;officially&amp;quot; released.&lt;/p&gt;&#xA;&lt;h1&gt;Software releases&lt;/h1&gt;&#xA;&lt;p&gt;Before seeing &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11490/how-to-install-the-nightly-builds-for-avogadro-avogadro-v-1-98-for-macos#comment24557_11490&quot;&gt;Geoff's comment&lt;/a&gt; here, I had already looked for version 1.98 at the &lt;a href=&quot;https://github.com/Avogadro/two.avogadro.cc&quot; rel=&quot;noreferrer&quot;&gt;Avogadro 2 GitHub page&lt;/a&gt; and the README file indicates that 1.97.0 is the latest &amp;quot;release&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hjik4.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hjik4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I click on the button that I circled in the above image, it takes me &lt;a href=&quot;https://github.com/OpenChemistry/avogadrolibs/releases&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;, which indicates that 1.97.0 was indeed the last &amp;quot;released&amp;quot; version, and that it was released on 21 July 2022.&lt;/p&gt;&#xA;&lt;h1&gt;Building software from source&lt;/h1&gt;&#xA;&lt;p&gt;Since at the time of your previous question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11488/5&quot;&gt;How to address &amp;#39;saveGraphic: Method not found&amp;#39; error in automating the generation of figures in avogadro using Python?&lt;/a&gt;, I knew nothing about the &amp;quot;nightly builds&amp;quot;, my first instinct if I wanted a feature that is not yet in the latest &amp;quot;release&amp;quot;, would be to simply &lt;em&gt;&lt;strong&gt;build the code myself from source.&lt;/strong&gt;&lt;/em&gt; Notice on GitHub that some of the project's files have been updated as recently as &amp;quot;yesterday&amp;quot;, and other files have been modified &amp;quot;4 months ago&amp;quot;, which both indicate that the version presented to you by default when you &lt;em&gt;&lt;strong&gt;clone&lt;/strong&gt;&lt;/em&gt; the GitHub repository is much more recent than 1.97.0 which was released in July 2022:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ALe3i.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ALe3i.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Fortunately the &lt;a href=&quot;https://two.avogadro.cc/build.html&quot; rel=&quot;noreferrer&quot;&gt;Avogadro 2 website has instructions about how to build the code from source&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h3&gt;&lt;em&gt;This is the safest way to guarantee that you're running the most recent version of the code, because it will clone the current repository from GitHub, which may have have changes that are not yet incorporated into the &amp;quot;nightly build&amp;quot;&lt;/em&gt;.&lt;/h3&gt;&#xA;&lt;p&gt;My first instinct when I saw your question was to try to build the code from source, because this is not only the safest way to guarantee that I have the latest version (nightly builds have been known to fail or not be up-to-date for some software packages), the safest way to ensure that the program will work on my platform (operating system version, etc.) and &lt;em&gt;&lt;strong&gt;if I want to modify the source code (e.g. changing the units used for geometries), I would need to build from source anyway if I want my computer to understand the new code.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Nightly builds&lt;/h1&gt;&#xA;&lt;p&gt;A nightly build is essentially the result of a computer/server somewhere, &amp;quot;building from source&amp;quot; each night and offering you to download the result. When nightly builds are up-to-date, assuming that they were build correctly and from the most recent version of the software (it's not always obvious what the nightly build is doing, whereas if you build the software yourself, you have so much more control), they will provide you with a version of the software based on the latest changes to the code before the nightly build was performed.&lt;/p&gt;&#xA;&lt;p&gt;Upon my first inspection of Avogadro's index.html page (the landing page on the website), this is possible for MacOS and Windows users:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jxhz1.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jxhz1.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I visit install.html, I also see that an option to use a nightly build is available on Linux machines:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vnvC2.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vnvC2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-08-19T02:12:51.097" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11496" PostTypeId="1" AcceptedAnswerId="11497" CreationDate="2023-08-19T05:54:37.810" Score="5" ViewCount="469" Body="&lt;p&gt;&lt;strong&gt;Question&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://chemrxiv.org/engage/chemrxiv/article-details/61cc3d33d1f662f9ec491b32&quot; rel=&quot;nofollow noreferrer&quot;&gt;mwfn&lt;/a&gt; filetype includes fields for alpha and beta electrons/orbitals/density matrices.&lt;/p&gt;&#xA;&lt;p&gt;What is the definition of alpha and beta electrons; what distinguishes them?&lt;/p&gt;&#xA;&lt;p&gt;For future research, where is this definition typically recorded?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Clues:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Orbitals are recorded as either &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt;, or &lt;span class=&quot;math-container&quot;&gt;$\alpha+\beta$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; orbitals implicitly come after &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; orbitals in indexing (with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; basis functions, the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; orbital is &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; ahead of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;th &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; orbital.  Do they overlap, or do &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; orbitals stop at &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;?).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7411" LastEditorUserId="5" LastEditDate="2023-08-19T14:34:17.970" LastActivityDate="2023-08-19T14:35:12.880" Title="What are alpha and beta electrons?" Tags="|electronic-structure|terminology|spin|multiwfn|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11497" PostTypeId="2" ParentId="11496" CreationDate="2023-08-19T13:24:34.193" Score="8" Body="&lt;p&gt;Alpha and beta basically denote spin-up (+1/2 for electrons) and spin-down (-1/2 for electrons).&lt;/p&gt;&#xA;&lt;p&gt;This tells us how the spin would align if we have a magnetic field. A spin of +1/2 actually means that the spin is aligned with the magnetic field, and a spin of -1/2 means that it's aligned 180 degrees from the magnetic field, but since we conventionally say that the positive z-axis is the direction in which the magnetic field is theoretically applied, a spin of +1/2 becomes &amp;quot;up&amp;quot; and -1/2 becomes &amp;quot;down&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-08-19T14:35:12.880" LastActivityDate="2023-08-19T14:35:12.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11498" PostTypeId="1" AcceptedAnswerId="11505" CreationDate="2023-08-20T08:01:37.350" Score="3" ViewCount="63" Body="&lt;p&gt;I have a general query regarding NEGF approach:&lt;/p&gt;&#xA;&lt;p&gt;In TranSIESTA code, when self-energy of the electrodes is calculated, does it require the coupling elements of the electrode with the central scattering region? Or,does it require just the interaction between the principle layers of the leads?&lt;/p&gt;&#xA;" OwnerUserId="5366" LastEditorUserId="5" LastEditDate="2023-08-20T10:10:43.083" LastActivityDate="2023-08-21T08:53:59.787" Title="Implemetation of NEGF in TranSIESTA" Tags="|siesta|electronic-transport|greens-functions|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11499" PostTypeId="1" AcceptedAnswerId="11503" CreationDate="2023-08-20T08:28:47.753" Score="6" ViewCount="251" Body="&lt;p&gt;I am performing DFT simulation (with Quantum Espresso) for a large number of crystalline materials to estimate their band gap energies. I am getting negative band gap values for many of them (difference between the lowest unoccupied level and the highest occupied level is negative). While I am aware that this is because of overlapping valence and conduction bands which is the case for metals, this also occurs for nonmetals with nonzero ground truth band gap energies. Could this be attributed to the underestimation issue of DFT methods in estimating the band gaps as highlighted by many studies?&lt;/p&gt;&#xA;&lt;p&gt;An example of the output produced by Quantum Espresso for a crystal.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt; highest occupied, lowest unoccupied level (ev):     8.9114    8.5647&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As a follow-up, I would also like to know if the number of bands of a crystal, which is an input parameter to DFT (&lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm277&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;nbnd&lt;/code&gt;&lt;/a&gt; in Quantum Espresso's &lt;code&gt;pw.x&lt;/code&gt;) can be determined analytically for any material. At the moment, I am just using a high value of 256 for all crystals - it works in most cases when compared to lower values. So I was wondering if DFT is very sensitive to this parameter and could lead to more incorrect and negative band gaps if an inexact number of bands is provided.&lt;/p&gt;&#xA;" OwnerUserId="7742" LastEditorUserId="7742" LastEditDate="2023-08-20T08:30:46.610" LastActivityDate="2023-08-20T22:19:30.580" Title="Negative band gap in DFT calculations" Tags="|density-functional-theory|quantum-espresso|solid-state-physics|bandgap|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11501" PostTypeId="1" AcceptedAnswerId="11504" CreationDate="2023-08-20T19:19:43.167" Score="3" ViewCount="117" Body="&lt;p&gt;I recently ran a calculation using the ROB3LYP/LANL2DZ level of theory for a triplet spin molecule. While analyzing the results, the HOMO is doubly degenerate and the LUMO is singly degenerate. I found that the HOMO is -2.740 eV, whereas the LUMO is -3.551 eV. I have no idea how the energy of the HOMO is greater than the LUMO. My guess is that it has to do with the doubly degeneracy/triplet spin state of the molecule, however my experience working with radicals is extremely limited and I am unsure.&lt;/p&gt;&#xA;&lt;p&gt;Any help making sense of the results is appreciated!&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-08-21T03:56:01.243" Title="How is the LUMO lower energy than the HOMO for triplet state restricted-open shell DFT calculation?" Tags="|density-functional-theory|molecular-modeling|gaussian|orbitals|electron-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11502" PostTypeId="1" CreationDate="2023-08-20T21:38:15.057" Score="2" ViewCount="137" Body="&lt;p&gt;I had a theoretical crisis while I was reading &lt;a href=&quot;https://www.quantum-espresso.org/wp-content/uploads/2022/03/phonons_tutorial_shanghai1.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this tutorial&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I know about Density Functional Perturbation Theory(DFPT) and I know that we can approximate the Inter-atomic Force Constants (IFCs) using a self-consistent method (see &lt;a href=&quot;https://www.fisica.uniud.it/%7Egiannozz/Papers/handbook2.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this textbook chapter&lt;/a&gt;), so we do know this matrix: &lt;span class=&quot;math-container&quot;&gt;$$ C^{i,j}_{\alpha,\beta}(l,m) = \frac{\partial^2 E_{el}}{\partial u^i_{\alpha} (l) u^j_{\beta}(m)}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$u^i_{\alpha}$&lt;/span&gt;(l) is the displacement of the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt;th atom in the lth unit cell accross the cartesian i direction. We can get the dynamical matrix at a generic &lt;strong&gt;q&lt;/strong&gt; point by taking the discrete Fourier transform:&lt;span class=&quot;math-container&quot;&gt;$$  D_{\alpha i , \beta j}(q) = \sum_{m} \frac{1}{\sqrt{m_{\alpha}m_{\beta}}}  C^{i,j}_{\alpha,\beta} (l,m) e^ {i q \cdot \left(R_{m}-R_l \right) }  $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example if I set &lt;span class=&quot;math-container&quot;&gt;$\bf q = 0$&lt;/span&gt; I can evaluate the frequencies of the eigenmodes using this algorithm:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Evaluate IFCs using DFPT;&lt;/li&gt;&#xA;&lt;li&gt;Find Fourier Transform of IFCs at &lt;span class=&quot;math-container&quot;&gt;$\bf q = 0$&lt;/span&gt; and get all the matrix element &lt;span class=&quot;math-container&quot;&gt;$D_{\alpha i , \beta j}(0)$&lt;/span&gt;;&lt;/li&gt;&#xA;&lt;li&gt;Diagonalize this matrix and get the eigenvalues.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;But ph.x seems to do the opposite. It defines a grid of &lt;strong&gt;q&lt;/strong&gt;-points and gets the dynamical matrix at those points. Then using inverse Fourier Transform, via q2r.x, we get the IFCs and with Fourier Interpolation, via matdyn.x, we get the Dynamical Matrix at every q points. But I really do not understand how ph.x can get the dynamical matrix before the IFCs. What am I misunderstanding?&lt;/p&gt;&#xA;" OwnerUserId="7557" LastEditorUserId="7" LastEditDate="2023-08-21T01:34:21.780" LastActivityDate="2023-08-21T01:34:21.780" Title="How does Quantum Espresso calculate the dynamical matrices before IFCs in ph.x?" Tags="|density-functional-theory|quantum-espresso|phonons|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11503" PostTypeId="2" ParentId="11499" CreationDate="2023-08-20T22:19:30.580" Score="5" Body="&lt;p&gt;Some materials erroneously give a metallic state even if it isn’t. Depending on what type of material and exchange-correlation functional you use, this can be more or less likely to happen. With transition metals often you need a Hubbard U or hybrid functional. Other small gap semiconductors might also need hybrid functionals.&lt;/p&gt;&#xA;&lt;p&gt;In QE it will automatically determine the number of bands, so you usually don’t have to set it. You can find it yourself with the number of electrons / 2 in the spin unpolarized case, or if there’s spin then it’s the number of electrons. This number gives you the number of occupied states, but often a few empty states will be included too so you can get the band gap and also some of the scf convergence algorithms can perform better with some empty states (for instance QE recommends 20% more bands for a metal, so if you use the default number of bands it will usually add some extra ones).&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2023-08-20T22:19:30.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11504" PostTypeId="2" ParentId="11501" CreationDate="2023-08-21T03:56:01.243" Score="3" Body="&lt;p&gt;It would be better to use the word SOMO (Singly Occupied Molecular Orbital), not HOMO. Now assume that you have two SOMOs (or SOMO and SOMO-1 if you prefer). Here are my suggestions:&lt;/p&gt;&#xA;&lt;p&gt;The first thing to do is to check the wave function stability of ROB3LYP, and see whether a lower-energy ROB3LYP wave function can be obtained. Quantum chemistry packages &lt;a href=&quot;https://github.com/pyscf/pyscf&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF&lt;/a&gt;, &lt;a href=&quot;https://github.com/psi4/psi4&quot; rel=&quot;nofollow noreferrer&quot;&gt;PSI4&lt;/a&gt;, and &lt;a href=&quot;https://amesp.xyz&quot; rel=&quot;nofollow noreferrer&quot;&gt;AMESP&lt;/a&gt; support that. If you are not using these packages, you can use &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOKIT&lt;/a&gt; to transfer MOs into those packages. Here is &lt;a href=&quot;http://bbs.keinsci.com/thread-27143-1-1.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;an example&lt;/a&gt; about checking ROHF/RODFT wave function stability (written in Chinese, but you can understand English words therein).&lt;/p&gt;&#xA;&lt;p&gt;Assuming now you've obtained a stable ROB3LYP wave function, and yet the problem is not solved. The molecule you studied may be complicated in electronic-structure and there may exist multiple stable ROB3LYP SCF solutions. Here are some ways to find them: (1) Perform a triplet UB3LYP calculation and make sure you obtain a stable UB3LYP SCF solution, generate UB3LYP NOs (UNO for short), and use UNO as the initial guess of ROB3LYP calculation. (2) Perform spin population analysis using the current ROB3LYP wave function, visualize orbitals near SOMO, see if the electronic configuration is what you expected (e.g. 3d^6 or 3d^5 4s^1 for Fe); if not, permute/alter orbitals and re-perform SCF.&lt;/p&gt;&#xA;&lt;p&gt;Assuming you've tried all approaches above, and yet the problem is not solved. The possible reason is that the definition of the Fock operator in ROHF/RODFT method is not unique, this makes the SOMO orbital energy differ in various quantum chemistry packages, although with the same total electronic energy. You can use another package (i.e. change the definition of the Fock operator), the problem may disappear. But in such case, it would be better to use the multiconfigurational/multireference methods (CASSCF, NEVPT2, etc).&lt;/p&gt;&#xA;&lt;p&gt;By the way, using LANL2DZ for all atoms may be outdated and not a good choice. If you insist on using the LANL2 series, LANL2TZ(f) is recommended. def2-TZVP is also good. It is also possible that your problem disappear after using a good/proper basis set.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2023-08-21T03:56:01.243" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11505" PostTypeId="2" ParentId="11498" CreationDate="2023-08-21T06:32:40.517" Score="2" Body="&lt;p&gt;Self-energies are calculated from a pristine, bulk calculation of only the electrode.&lt;/p&gt;&#xA;&lt;p&gt;This is a requirement of the self-energy algorithm. This also forces the boundary conditions of the electrodes.&lt;/p&gt;&#xA;&lt;p&gt;Since, the calculation is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf G^{-1} =&#xA;\begin{bmatrix}&#xA;\mathbf S_1 e - \mathbf H_1 - \Sigma_1 &amp;amp; \cdots \\&#xA;\vdots \\&#xA;\end{bmatrix}&#xA;$$&lt;/span&gt;&#xA;The &lt;span class=&quot;math-container&quot;&gt;$\Sigma_1$&lt;/span&gt; is the self-energy which is derived from the bulk electrode named &lt;span class=&quot;math-container&quot;&gt;$1$&lt;/span&gt;.&#xA;However, the above requires that the electrode in the device region is equivalent to the bulk electrode region.&lt;/p&gt;&#xA;&lt;p&gt;The initiated reader will notice that one can choose &lt;span class=&quot;math-container&quot;&gt;$\mathbf H_1$&lt;/span&gt; between two values:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the pristine bulk Hamiltonian: &lt;code&gt;TS.Elec.&amp;lt;&amp;gt;.Bulk true&lt;/code&gt;&lt;br /&gt;&#xA;forces the coupled region in the device region to be very electrode bulk like&lt;/li&gt;&#xA;&lt;li&gt;the device region Hamiltonion: &lt;code&gt;TS.Elec.&amp;lt;&amp;gt;.Bulk false&lt;/code&gt;&lt;br /&gt;&#xA;forces the electrode part of the device to couple to a bulk electrode with bulk properties. This can in some cases spare you some layers of electrode in the device region.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It is always the user's responsibility to ensure the boundary conditions are fulfilled! TranSIESTA will/can not check this.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-08-21T08:53:59.787" LastActivityDate="2023-08-21T08:53:59.787" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11506" PostTypeId="1" CreationDate="2023-08-21T15:56:06.433" Score="4" ViewCount="295" Body="&lt;p&gt;I have been using PySCF to calculate the 1-particle and 2-particle density matrix from ccsd(T) wavefunction using these modules in-built in PySCF &lt;code&gt;make_rdm1()&lt;/code&gt; and &lt;code&gt;make_rdm2()&lt;/code&gt;. However, the code takes ~2TB of memory for CCSD(T) calculation of only ~175 basis functions.&#xA;So, I have been thinking to switch to other commercial/free codes like Gaussian, Psi4. Turbomole or orca for CCSD(T) calculations and then convert the output to obtain the density matrices (with python3). Should I have to start with MO coefficients? How can I do it? Also some codes do not provide hessian for CCSD(T).&lt;/p&gt;&#xA;&lt;p&gt;Edit 1: Added PySCF Code.&#xA;Edit 2: Modified PySCF code to generate 2PDM at CCSD(T) (no frozen core).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy&#xA;import scipy.linalg&#xA;from pyscf import gto, scf&#xA;from pyscf import lib, tools&#xA;from pyscf import cc, ao2mo, grad&#xA;from gto import mole&#xA;from pyscf.cc import ccsd&#xA;from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda&#xA;from pyscf.cc import ccsd_t_slow as ccsd_t&#xA;from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm&#xA;from pyscf.cc.ccsd_t_rdm_slow import make_rdm1,make_rdm2&#xA;&#xA;mol = gto.M(&#xA;    verbose = 5,&#xA;    atom = [&#xA;           ['O' ,  0.074642 , -0.000000 , -0.026389],&#xA;           ['H' , -0.103145 ,  0.000000 ,  0.930145],&#xA;           ['H' ,  0.991917 ,  0.000000 , -0.350692],&#xA;           ['H' , -0.664854 , -0.000000 , -0.658618]],&#xA;    basis = '3-21g',charge=1,&#xA;cart=True&#xA;)&#xA;mf = scf.RHF(mol)&#xA;mf.conv_tol = 1e-13&#xA;mf.scf()&#xA;orbshape = mf.mo_coeff.shape&#xA;&#xA;HFdm1 = mf.make_rdm1()&#xA;E1e = numpy.einsum('pq,qp', mf.get_hcore(), HFdm1)&#xA;&#xA;with open('moldenmo', 'w') as f1:&#xA; for imo in range(orbshape[1]):&#xA;  for j in  range(orbshape[1]):&#xA;   f1.write('\n{}'.format(mf.mo_coeff[j,imo]))&#xA;f1.close()&#xA;mcc = ccsd.CCSD(mf)&#xA;mcc.conv_tol = 1e-12&#xA;ecc, t1, t2 = mcc.kernel()&#xA;eris = mcc.ao2mo()&#xA;# Next we calculate CCSD(T) which takes huge memory, fails most of the time. &#xA;&#xA;e3ref = ccsd_t.kernel(mcc, eris, t1, t2)&#xA;l1, l2 = ccsd_t_lambda.kernel(mcc, eris, t1, t2)[1:]&#xA;print(ecc, e3ref)&#xA;&#xA;eri_mo = ao2mo.kernel(mf._eri, mf.mo_coeff, compact=False)&#xA;nmo = mf.mo_coeff.shape[1]&#xA;eri_mo = eri_mo.reshape(nmo,nmo,nmo,nmo)&#xA;dm1 = make_rdm1(mcc, t1, t2, l1, l2, eris=eris)&#xA;&#xA;with open('onepdm', 'w') as f1:&#xA; for i in range(orbshape[1]):&#xA;  for j in range(orbshape[1]):&#xA;   f1.write('\n{}'.format(dm1[i,j]))&#xA;f1.close&#xA;# Find the nautral orbitals (MO basis) and eigenvalues (i.e. occupation numbers).&#xA;e, c = scipy.linalg.eigh(dm1)&#xA;with open('occupnumb', 'w') as f1:&#xA; for i in range(orbshape[1]):&#xA;  f1.write('\n{}'.format(e[i]))&#xA;f1.close&#xA;#&#xA;with open('natorbmo', 'w') as f1:&#xA; for i in range(orbshape[1]):&#xA;  for j in range(orbshape[1]):&#xA;   f1.write('{}\n'.format(c[j,i]))&#xA;f1.close&#xA;&#xA;# Determine the CCSD 1electron energy terms based on density matrix&#xA;h1 = numpy.einsum('pi,pq,qj-&amp;gt;ij', mf.mo_coeff.conj(), mf.get_hcore(), mf.mo_coeff)&#xA;E = numpy.einsum('pq,qp', h1, dm1)&#xA;print(&amp;quot;E-CCSD(T) 1E part only&amp;quot;, E)&#xA;&#xA;# Get the nuclear repulsion energy and the number of electrons&#xA;enuc = gto.energy_nuc(mol)&#xA;print(&amp;quot; Nuclear Repulsion Energy is &amp;quot;, enuc)&#xA;ne = mole.tot_electrons(mol)&#xA;print(&amp;quot; Total number of electrons is &amp;quot;, ne)&#xA;&#xA;dm2 = make_rdm2(mcc, t1, t2, l1, l2, eris=eris)&#xA;&#xA;# format of the 2PDM&#xA;&#xA;with open('twopdm', 'w') as f1:&#xA; for i in range(orbshape[1]):&#xA;  for j in range(orbshape[1]):&#xA;   for k in range(orbshape[1]):&#xA;    for l in range(orbshape[1]):&#xA;      f1.write('\n{}'.format(dm2[i,j,k,l]))&#xA;f1.close()&#xA;h1 = reduce(numpy.dot, (mf.mo_coeff.T, mf.get_hcore(), mf.mo_coeff))&#xA;e3 =(numpy.einsum('ij,ji-&amp;gt;', h1, dm1)&#xA;   + numpy.einsum('ijkl,ijkl-&amp;gt;', eri_mo, dm2)*.5 + mf.mol.energy_nuc())&#xA;print(e3ref, e3-(mf.e_tot+ecc))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="142" LastEditDate="2023-09-27T13:54:04.310" LastActivityDate="2023-10-03T12:02:29.353" Title="What's the best code for getting 1-particle and 2-particle density matrices with CCSD(T) in Python?" Tags="|software-recommendations|hartree-fock|pyscf|coupled-cluster|reduced-density-matrix|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11507" PostTypeId="1" CreationDate="2023-08-21T19:33:45.193" Score="6" ViewCount="355" Body="&lt;p&gt;When running single point equilibrium calculations on an array of compositions I come across some compositions (for specific examples see below) that return the error &lt;code&gt;&amp;quot;ERROR  1611 IN QTHISS: TOO MANY ITERATIONS&amp;quot;&lt;/code&gt;. For most such compositions if I increase the &amp;quot;max number of grid points&amp;quot; parameter I no longer get the error and instead get the result of the calculation (eq. phases, fractions, etc.). However, there are some compositions such that even when I increase the &amp;quot;max number of grid points&amp;quot; to something like 16,000,000 (which makes the calculation use a lot of RAM and take orders of magnitude longer to run) they still give this error.&lt;/p&gt;&#xA;&lt;p&gt;I have a question:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the reason some compositions fail to calculate?&lt;/strong&gt; Are they just at a part of the free energy landscape that makes it difficult for the minimizer?&lt;/p&gt;&#xA;&lt;p&gt;An example of such a composition is &lt;code&gt;Ni0.05Ti0.32Nb0.59Al0.04&lt;/code&gt; (atomic frac.) at 1323K using the &lt;code&gt;TCHEA5.0 database&lt;/code&gt;. It always gives an error up to a max grid points of 20,000,000.&lt;/p&gt;&#xA;&lt;p&gt;A few notes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;It seems that the calculations are affected by prior calculations (which makes sense because one calculation will change the state of the &amp;quot;System&amp;quot; which will then alter how subsequent calculations are performed). For instance, running &lt;code&gt;Ni0.05Ti0.33Nb0.58Al0.04&lt;/code&gt; and then &lt;code&gt;Ni0.05Ti0.32Nb0.59Al0.04&lt;/code&gt; (with the conditions above) gives a result, but running  &lt;code&gt;Ni0.05Ti0.32Nb0.59Al0.04&lt;/code&gt; only gives an error.&lt;/li&gt;&#xA;&lt;li&gt;The persistent errors seems to occur for compositions where there are 2 or more composition sets of a given phase in equilibrium (e.g., at a composition where there is &lt;code&gt;BCC_B2#1-BCC_B2#2&lt;/code&gt; or &lt;code&gt;FCC_A1#2-FCC_A1#3)&lt;/code&gt;. For example, there are 3 BCC phases in equilibrium for &lt;code&gt;Ni0.05Ti0.32Nb0.59Al0.04&lt;/code&gt; and &lt;code&gt;Ni0.05Ti0.32Nb0.59Al0.04&lt;/code&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I know that such errors may seem like a minor issue to some, but for me its a show-stopper so I would very much appreciate some help.&lt;/p&gt;&#xA;" OwnerUserId="1410" LastEditorUserId="6687" LastEditDate="2023-08-29T09:45:45.357" LastActivityDate="2023-11-18T01:05:30.180" Title="Persistent errors in single equilibrium calculations (Thermo-Calc)" Tags="|python|free-energy|calphad|thermo-calc|phase-diagram|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11508" PostTypeId="1" CreationDate="2023-08-21T21:18:52.863" Score="2" ViewCount="191" Body="&lt;p&gt;I have a dataset of 64 chemical structures and their calculated energies, which I want to predict using machine learning. I need to use SOAP as a descriptor so that each structure would be an individual descriptor, and each descriptor is a matrix (according to the documentation) where each row represents the local environment of one atom of the molecule. So the 'shape' of these descriptors would be &lt;em&gt;(number of atoms x number of features)&lt;/em&gt; if I understand correctly.&#xA;Currently, I have a list of descriptors with a length of 64 (the number of structures in the system) for each structure, but I'm having problems fitting this list into the KRR model. As far as I understand, the descriptors list has the following structure: (simplified)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;descriptors = [&#xA;# 1st structure &#xA;   [&#xA;      [ ... ] # atoms features&#xA;      [ ... ] # atoms features&#xA;      ... up to the number of atoms in the structure &#xA;   ]&#xA;# 2nd structure&#xA;   [&#xA;      [ ... ] # atoms features&#xA;      [ ... ] # atoms features&#xA;      ... up to the number of atoms in the structure&#xA;   ]&#xA;   ...&#xA;]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Each row (atom) has the same number of features. The structures have different numbers of atoms.&#xA;Is there a better way to process this dataset so I can fit this into KRR? The KRR accepts input of shape &lt;em&gt;(n_samples, n_features)&lt;/em&gt;, so I imagined that would be (64, n_features), but how to correctly reshape this into such structure? I'm very new to this so any help would be very appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7749" LastEditorUserId="7749" LastEditDate="2023-08-21T21:57:40.173" LastActivityDate="2023-08-21T21:57:40.173" Title="How to fit Smooth Overlap of Atomic Positions (SOAP) into Kernel Ridge Regression (KRR)?" Tags="|computational-chemistry|python|machine-learning|" AnswerCount="0" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="11510" PostTypeId="2" ParentId="10803" CreationDate="2023-08-21T21:25:30.937" Score="1" Body="&lt;p&gt;In Thermo-Calc 2022a and onwards it appears you can use the material-to-material calculator to extract phase information for a linear gradient between two compositions.&lt;/p&gt;&#xA;" OwnerUserId="7751" LastActivityDate="2023-08-21T21:25:30.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11511" PostTypeId="1" CreationDate="2023-08-22T01:43:15.810" Score="8" ViewCount="150" Body="&lt;p&gt;I'm currently writing a program which evaluates the first derivatives of molecular integrals (over gaussian basis sets) with respect to the cartesian coordinates of the nucleus. I'm somewhat stuck with the derivative of the nuclear-electron attraction integral, i.e.:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial V_{\mu\nu}}{\partial X_A}=\frac{\partial }{\partial X_A} \left\langle \mu| \hat V |\nu\right\rangle $$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; are Gaussian-Type Orbitals (GTOs) and &lt;span class=&quot;math-container&quot;&gt;$\hat V $&lt;/span&gt; is the operator:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hat V = -\sum_A \frac{Z_A}{|r-R_A|}&#xA;$$&lt;/span&gt;&#xA;&lt;a href=&quot;https://chemistry.stackexchange.com/questions/89831/analytical-gradient-of-the-hartree-fock-nuclear-electronic-repulsion-term&quot;&gt;As was previously discussed on this forum&lt;/a&gt;, the upper derivative can be expressed as a sum of derivatives applying the chain rule:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial }{\partial X_A} \left\langle \mu| \hat V |\nu\right\rangle=\left\langle\frac{\partial \mu}{\partial X_A}|\hat V|\nu\right\rangle+\left\langle \mu|\frac{\partial \hat V}{\partial X_A}|\nu\right\rangle+\left\langle \mu|\hat V|\frac{\partial \nu}{\partial X_A}\right\rangle$$&lt;/span&gt;&#xA;The first and latter terms are relatively easy to evaluate, since the derivative of a Gaussian-Type Orbital with respect to one of the coordinates of the point where it's centered is a sum of GTOs with higher and lower angular momentum. The evaluation of the middle term doesn't seem so obvious. According to Szabo &amp;amp; Ostlund (pg. 442), the derivative of the &lt;span class=&quot;math-container&quot;&gt;$\hat V$&lt;/span&gt; operator is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{\partial \hat V}{\partial X_A}=-Z_A\sum_i \frac{X_i-X_A}{r_{iA}^3}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; are Gaussian-Type Orbitals (GTOs)&#xA;So we are dealing with a &lt;em&gt;new&lt;/em&gt; type of molecular integral:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left\langle \mu\left|-Z_A\sum_i \frac{X_i-X_A}{r_{iA}^3}\right|\nu\right\rangle&#xA;$$&lt;/span&gt; After searching for some time, I couldn't find any reference which discuss this topic. Could you provide some insight on the evaluation of this particular integral? Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="5016" LastEditorUserId="142" LastEditDate="2024-02-13T19:50:20.517" LastActivityDate="2024-02-13T19:50:20.517" Title="Analytical derivative of nuclear-electron attraction integrals over gaussian functions" Tags="|computational-chemistry|quantum-chemistry|integrals|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11512" PostTypeId="1" CreationDate="2023-08-22T10:10:50.363" Score="4" ViewCount="111" Body="&lt;p&gt;Could someone tell me what the optimal workflow to study the various properties of a material is? I am new to using VASP and would like to know what order I should run the calculations and what are precautions I should take.&lt;/p&gt;&#xA;" OwnerUserId="7757" LastEditorUserId="5" LastEditDate="2023-08-25T11:53:27.437" LastActivityDate="2023-08-25T11:53:27.437" Title="Proper workflow for VASP" Tags="|density-functional-theory|vasp|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11514" PostTypeId="1" AcceptedAnswerId="11527" CreationDate="2023-08-22T16:53:53.377" Score="3" ViewCount="140" Body="&lt;p&gt;I've been reading this interesting &lt;a href=&quot;https://www.nature.com/articles/s41524-023-00987-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; and I'm trying to understand the following: it is known that a crystal lattice can be represented by 6 parameters corresponding to lattice vectors lengths (&lt;span class=&quot;math-container&quot;&gt;$a,b,c$&lt;/span&gt;) and angles between them &lt;span class=&quot;math-container&quot;&gt;$(\alpha, \beta, \gamma)$&lt;/span&gt; using Niggli reduction algorithm. What I don't understand too well is how can we compute original coordinates (in &lt;span class=&quot;math-container&quot;&gt;$\mathbb{R}^{3 \times 3}$&lt;/span&gt;) starting from lengths and angles? On the aforementioned paper, they use the following computation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/8UJuu.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/8UJuu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;but I don't understand why.&lt;/p&gt;&#xA;" OwnerUserId="2017" LastActivityDate="2023-08-23T23:47:02.920" Title="Computing lattice coordinates starting from lengths and angles" Tags="|crystallography|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11515" PostTypeId="1" CreationDate="2023-08-23T08:47:21.213" Score="2" ViewCount="56" Body="&lt;p&gt;I am trying to reproduce results from research. In computation details part, it mentioned some setting about G-type AFM and Hubbard parameter:&lt;br /&gt;&#xA;1.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;A Hubbard parameter (U) of 5 eV was used to treat the on-site Coulomb interaction for the Fe 3d states.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The geometry optimization was carried out considering the different magnetic configurations (FM, C-AFM, G-AFM) in BFO, and both phases were concluded to be stable in G-type AFM. Further, a larger k-grid mesh was considered for the calculations of the bands under the G-type AFM ordering of the Fe atoms taking into account the spin–orbit coupling (SOC).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Therefore, I'm considering adding Hubbard and AFM parameters in the INCAR file when doing structure optimization. This is my current INCAR. I would like to ask everyone if there are any problems with it, and where it needs to be modified? I have also attached my POSCAR file. I really hope someone can help me. Let me thank everyone in advance.&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;Startparameters for VASP &#xA;# Gloabal paramters&#xA;ISTART = 0              # Read existing wavefunction =1&#xA;ICHARG = 2             # Default=2 if ISTART=0. Non-self-consistent: GGA/LDA band structures, =11&#xA;LWAVE =.FALSE.         # Write WAVECAR or not&#xA;LORBIT = 11           # band structure and AFM flag&#xA;&#xA;# Parallelisation&#xA;LPLANE = .FALSE.       # Real space distribution; supercells &#xA;NCORE = 1              # Max is no. nodes; don't set for hybrids##&#xA;KPAR = 10               # Divides k-grid into separate groups&#xA;&#xA;# Electronic relaxation&#xA;PREC = Normal          # Precision level, Normal or High&#xA;LREAL = .FALSE.           # Auto for molecule containing for than 20 ionics&#xA;ENCUT = 500            # Cut-off energy for plane wave basis set, in eV, default=max ENMAX in POTCAR,for bulk structure relaxation, ENCUT=1.3 * default&#xA;NELM = 60              # Max SCF steps&#xA;NELMIN = 5             # MIN SCF steps&#xA;EDIFF = 1E-06          # SCF energy convergence, this number is quite precise&#xA;ISPIN = 2              # AFM=2&#xA;#IVDW = 11              # DFT-D3 method of Grimme with zero-damping function&#xA;#ISYM = 2&#xA;#ALGO = Fast &#xA; &#xA;# Ionic relaxation&#xA;EDIFFG =  0.001        # Ionic convergence; eV/AA^3&#xA;NSW = 0              # MAX Inonic relaxation steps&#xA;ISIF = 7               # For single point enegy&#xA;IBRION = 2             # = -1 for NSW = -1 or 0&#xA;# POTIM = 0.015         #  Step width in ionic relaxations.&#xA;# ADDGRID = .TRUE.   # Increase grid; helps GGA convergence&#xA;ISMEAR = 0             # Gaussian smearing; metals:1&#xA;SIGMA = 0.05           # Smearing value in eV; metals:0.2&#xA;&#xA;# Nonconlinear AFM&#xA;# MAGMOM = x y z&#xA;LNONCOLLINEAR = .TRUE.&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-bash prettyprint-override&quot;&gt;&lt;code&gt;Fe1 Bi1 O3&#xA;1.0&#xA;        3.7514150143         0.0000000000         0.0000000000&#xA;        0.0000000000         3.7514150143         0.0000000000&#xA;        0.0000000000         0.0000000000         4.8798279762&#xA;   Fe   Bi    O&#xA;    1    1    3&#xA;Direct&#xA;     0.000000000         0.000000000         0.523835003&#xA;     0.500000000         0.500000000         0.951292992&#xA;     0.000000000         0.500000000         0.669587493&#xA;     0.500000000         0.000000000         0.669587493&#xA;     0.000000000         0.000000000         0.143695503&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7083" LastEditorUserId="5" LastEditDate="2023-08-23T12:30:32.020" LastActivityDate="2023-08-23T12:30:32.020" Title="How to set G-type AFM and U parameters in VASP when optimizing structure?" Tags="|vasp|anti-ferromagnetic|reproducing-data-from-papers|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11516" PostTypeId="1" CreationDate="2023-08-23T13:42:42.023" Score="5" ViewCount="785" Body="&lt;p&gt;As far as I understand (as a complete beginner to molecular simulation and modelling), Coulomb's law for two atoms i and j is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$F=k\frac{q_iq_j}{(r_{ij})^2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;(the force is proportional to the product of the two charges and the &lt;strong&gt;inverse square&lt;/strong&gt; of the distance)&lt;/p&gt;&#xA;&lt;p&gt;I am trying to understand molecular simulation and force fields and many use this formula but without squaring the distance, is there a reason behind this? My best thought is simply to improve computational time complexity as this is often the most computationally expensive step and quadratic terms scale worse than linear ones.&lt;/p&gt;&#xA;" OwnerUserId="7765" LastEditorUserId="5" LastEditDate="2023-08-23T15:29:17.163" LastActivityDate="2023-08-23T22:50:35.937" Title="Why are Coulomb interactions modeled with just r, not r squared?" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|forcefields|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11517" PostTypeId="2" ParentId="11516" CreationDate="2023-08-23T14:06:18.463" Score="10" Body="&lt;p&gt;The force &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is proportional to &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{r^2}$&lt;/span&gt; but the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is proportional to &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{r}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is because &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt; is proportional to &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial V}{\partial r}$&lt;/span&gt;, the derivative of &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; with respect to &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; (this is by definition).&lt;/p&gt;&#xA;&lt;p&gt;Using &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$r^2$&lt;/span&gt; is not to save computational time (it is incorrect to think that calculating &lt;span class=&quot;math-container&quot;&gt;$r*r$&lt;/span&gt; is more computationally expensive than calculating &lt;span class=&quot;math-container&quot;&gt;$q_1*q_2$&lt;/span&gt;). It is simply the correct Coulomb potential corresponding to the Coulomb force that you correctly wrote.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="7" LastEditDate="2023-08-23T22:50:35.937" LastActivityDate="2023-08-23T22:50:35.937" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11518" PostTypeId="2" ParentId="11512" CreationDate="2023-08-23T14:18:40.717" Score="5" Body="&lt;p&gt;I had never used VASP, but the workflow normally used for other software is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Energy cut-off convergence study.&lt;/li&gt;&#xA;&lt;li&gt;k-points convergence study.&lt;/li&gt;&#xA;&lt;li&gt;Geometry optimization.&lt;/li&gt;&#xA;&lt;li&gt;Properties calculations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I recommend taking a look at these posts:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1896/24&quot;&gt;k-points and ENCUT convergence tests before or after relaxation?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4338/24&quot;&gt;How to do VASP convergence tests, and how to get two plots of Encut and k-points wrt to total energy? I want to do convergence for Mg2Si&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/317/24&quot;&gt;Which property should be used for a DFT convergence test? Is energy always the best, or should convergence be tested for a different property?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;(Tutorial) &lt;a href=&quot;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&quot; rel=&quot;noreferrer&quot;&gt;https://dannyvanpoucke.be/vasp-tutor-convergence-testing-en/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-08-23T14:18:40.717" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11519" PostTypeId="2" ParentId="11511" CreationDate="2023-08-23T14:46:23.313" Score="3" Body="&lt;p&gt;Like two-electron integrals, the nuclear attraction integrals are evaluated using the Laplace transform&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \frac 1 {r_{12}} = \frac {2} {\sqrt{\pi}} \int_{0}^{\infty} {\rm d}t e^{-t^2r_{12}^2} $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It would seem that using this transform also makes the derivative integrals easy to evaluate.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-08-23T14:46:23.313" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11520" PostTypeId="2" ParentId="11476" CreationDate="2023-08-23T15:00:41.717" Score="1" Body="&lt;p&gt;There seems to be a lot of confusion in the question.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Then what is the spatial-spin orbital basis set of the overlap, kinetic, Coulomb (Exchange) and proton attraction operators/matrices for each electronic structure methods by only using 1s, 2s and 2p orbitals?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In RKS, UKS and ROKS the overlap, kinetic energy, and nuclear attraction matrices are &lt;span class=&quot;math-container&quot;&gt;$S_{\mu \nu} = \langle \mu | \nu \rangle$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$T_{\mu \nu} = -\frac 1 2 \langle \mu | \nabla^2 | \nu \rangle$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$V_{\mu \nu} = -\sum_A \langle \mu | \frac {Z_A} {r_{A}} | \nu \rangle$&lt;/span&gt; . They only depend on the orbital basis set. Note that you would typically choose a symmetric form for &lt;span class=&quot;math-container&quot;&gt;${\bf T}$&lt;/span&gt;, which you can do with integration by parts. Note also that I've used the common shorthand here where e.g. &lt;span class=&quot;math-container&quot;&gt;$ | \nu \rangle = | \chi_\nu \rangle$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It does not matter how you choose your basis functions. Instead of atomic orbitals, you can also construct these matrices for numerical basis functions.&lt;/p&gt;&#xA;&lt;p&gt;Similarly, the Coulomb matrix only depends on the basis set; it does not contain any spin dependence, because it tells you about Coulombic repulsion of the electrons.&lt;/p&gt;&#xA;&lt;p&gt;Only the exchange matrices carry spin dependence: you get exchange matrices for both spins &lt;span class=&quot;math-container&quot;&gt;${\bf K}^\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;${\bf K}^\beta$&lt;/span&gt;. The structure of these matrices is the same as that of all of the above matrices, that is, &lt;span class=&quot;math-container&quot;&gt;$K^\alpha_{\mu \nu}$&lt;/span&gt; is the element of the spin-&lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; exchange matrix that corresponds to basis functions &lt;span class=&quot;math-container&quot;&gt;$\chi_\mu$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\chi_\nu$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-08-23T15:00:41.717" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11521" PostTypeId="2" ParentId="11143" CreationDate="2023-08-23T16:05:38.567" Score="2" Body="&lt;p&gt;If you already have the elastic constants &lt;span class=&quot;math-container&quot;&gt;$C_{ij}$&lt;/span&gt; (in Voigt notation), you should be able to use the following equations for the general angle-dependent in-plane Young's modulus &lt;span class=&quot;math-container&quot;&gt;$E(\theta)$&lt;/span&gt; and Poisson's ratio &lt;span class=&quot;math-container&quot;&gt;$\nu(\theta)$&lt;/span&gt;. They were obtained from&#xA;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcc.1c06462&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Phys. Chem. C 2021, 125, 36, 19666–19672&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/hjxwu.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/hjxwu.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-08-23T16:05:38.567" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11522" PostTypeId="1" CreationDate="2023-08-23T16:46:10.913" Score="2" ViewCount="79" Body="&lt;p&gt;I have been trying to generate potential energy curves with doing single point calculations with VASP - 5.4.4&#xA;many of my jobs crash or stay stuck on a single line until it runs out of time. can some one please help me out with this?.&#xA;I have attached the errors I am getting, along with a submit script that i used to submit the jobs.&lt;/p&gt;&#xA;&lt;p&gt;error 1 - this hasn't gone past the line &amp;quot;&#xA;The following have been reloaded with a version change: &amp;quot;distr:  one band on    4 cores,   15 groups&amp;quot;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1) compiler/intel/18 =&amp;gt; compiler/intel/19     2) intel-mpi/18 =&amp;gt; intel-mpi/19&#xA;&#xA;Starting Time is Tue Aug 22 13:43:59 CDT 2023&#xA; running on   60 total cores&#xA; distrk:  each k-point on   60 cores,    1 groups&#xA; distr:  one band on    4 cores,   15 groups&#xA;srun: Job step aborted: Waiting up to 32 seconds for job step to finish.&#xA;slurmstepd: error: *** JOB 50226784 ON r05r20n04 CANCELLED AT 2023-08-22T19:44:10 DUE TO TIME LIMIT ***&#xA;slurmstepd: error: *** STEP 50226784.0 ON r05r20n04 CANCELLED AT 2023-08-22T19:44:10 DUE TO TIME LIMIT ***&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;error 2 - I do not know what this means&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; LDA part: xc-table for Pade appr. of Perdew&#xA; POSCAR, INCAR and KPOINTS ok, starting setup&#xA;Abort(674835087) on node 54 (rank 54 in comm 0): Fatal error in PMPI_Alltoallv: Other MPI error, error stack:&#xA;PMPI_Alltoallv(391)................: MPI_Alltoallv(sbuf=0x2acbbe05e020, scnts=0xb2bf480, sdispls=0xb2bf220, MPI_INTEGER, rbuf=0x2acbbe476020, rcnts=0xb2bf820, rdispls=0xb2bf5c0, datatype=MPI_INTEGER, comm=comm=0xc4000000) failed&#xA;MPIDI_SHMGR_Gather_generic(1051)...:&#xA;MPIDI_NM_mpi_alltoallv(850)........:&#xA;MPIR_Alltoallv_intra_scattered(123):&#xA;MPIR_Waitall(184)..................:&#xA;MPIR_Waitall_impl(59)..............:&#xA;MPIDI_Progress_test(183)...........:&#xA;MPIDI_OFI_handle_cq_error(1077)....: OFI poll failed (ofi_events.h:1077:MPIDI_OFI_handle_cq_error:Input/output error)&#xA;Abort(3746447) on node 59 (rank 59 in comm 0): Fatal error in PMPI_Alltoallv: Other MPI error, error stack:&#xA;PMPI_Alltoallv(391)................: MPI_Alltoallv(sbuf=0x2ad673c9e020, scnts=0xc49cd40, sdispls=0xc49cae0, MPI_INTEGER, rbuf=0x2ad6740b6020, rcnts=0xc49d0c0, rdispls=0xc49ce60, datatype=MPI_INTEGER, comm=comm=0xc4000000) failed&#xA;MPIDI_SHMGR_Gather_generic(1051)...:&#xA;MPIDI_NM_mpi_alltoallv(850)........:&#xA;MPIR_Alltoallv_intra_scattered(123):&#xA;MPIR_Waitall(184)..................:&#xA;MPIR_Waitall_impl(59)..............:&#xA;MPIDI_Progress_test(183)...........:&#xA;MPIDI_OFI_handle_cq_error(1077)....: OFI poll failed (ofi_events.h:1077:MPIDI_OFI_handle_cq_error:Input/output error)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the submit script&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash -l&#xA;#SBATCH --job-name=or2nod3&#xA;#SBATCH --nodes=3&#xA;#SBATCH --ntasks-per-node=20&#xA;#SBATCH --time=00-06:00:00&#xA;#SBATCH --mem-per-cpu=12gb&#xA;#SBATCH --output=vasp_runex.log&#xA;#SBATCH --partition=sixhour&#xA;#SBATCH --constraint=ib&#xA;&#xA;# convert the file convert_1.py using the distance value&#xA;module load python&#xA;sed -i &amp;quot;s/XX/8.0/g&amp;quot; convert_1.py&#xA;python convert_1.py&#xA;cp POSCAR ./inputs/&#xA;&#xA;# We load all the default program system settings with module load:&#xA;module purge&#xA;module load compiler/intel/18&#xA;module load intel-mpi/18&#xA;module load vasp/5.4.4&#xA;&#xA;proj=inputs # Name of job folder&#xA;input=&lt;span class=&quot;math-container&quot;&gt;$(ls $&lt;/span&gt;{proj}/{INCAR,POTCAR,POSCAR,KPOINTS}) # Input files from job folder&#xA;&#xA;echo Starting Time is `date`&#xA;export VASP_WORKDIR=/home/$USER/scratch/orient_2/no_disp/slab_8.0&#xA;&#xA;mkdir -p $VASP_WORKDIR&#xA;&#xA;# Preparing and moving inputfiles to tmp:&#xA;&#xA;submitdir=$SLURM_SUBMIT_DIR&#xA;&#xA;cp &lt;span class=&quot;math-container&quot;&gt;$input $&lt;/span&gt;VASP_WORKDIR&#xA;cd $VASP_WORKDIR&#xA;&#xA;######################################&#xA;# Section for running the program and cleaning up:&#xA;&#xA;# Running the program:&#xA;time mpirun vasp_std&#xA;&#xA;# Investigate potentially other files to keep:&#xA;echo &lt;span class=&quot;math-container&quot;&gt;$(pwd)&#xA;echo $&lt;/span&gt;(ls -ltr)&#xA;&#xA;# ALWAYS clean up after yourself. Please do uncomment the following line&#xA;# If we have to, we get really grumpy!&#xA;#cd &lt;span class=&quot;math-container&quot;&gt;$submitdir&#xA;#rm -r $&lt;/span&gt;VASP_WORKDIR/*&#xA;&#xA;echo &amp;quot;Job finished at&amp;quot;&#xA;exit 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;any help to resolve these are appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6839" LastActivityDate="2023-08-23T16:46:10.913" Title="VASP jobs crashing - VASP 5.4.4" Tags="|vasp|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11523" PostTypeId="2" ParentId="11511" CreationDate="2023-08-23T17:41:38.307" Score="1" Body="&lt;p&gt;The original &lt;a href=&quot;https://doi.org/10.1063/1.450106&quot; rel=&quot;nofollow noreferrer&quot;&gt;Obara-Saika paper&lt;/a&gt; contains formulae for this in the &amp;quot;Electric field and electric field gradient Integrals&amp;quot; section of the appendix towards the end of the paper&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="269" LastEditDate="2023-08-23T20:51:23.707" LastActivityDate="2023-08-23T20:51:23.707" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11524" PostTypeId="1" CreationDate="2023-08-23T18:03:48.003" Score="3" ViewCount="132" Body="&lt;p&gt;I have two surfaces named POSCAR1 and POSCAR2. I want to stack the surface of POSCAR2 on POSCAR1  to form an interface and also to match their lattice constants. I tried a solution here by adding it as an adsorbate but couldn't rotate. Any python code will be appreciated. I have attached the two POSCARS.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CoCrFeNi&#xA;   1.00000000000000     &#xA;     9.9633502299999996    0.0000000000000000    0.0000000000000000&#xA;    -4.9733836199999999    8.6618479100000005    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000   40.4368920000000003&#xA;   Co   Cr   Fe   Ni&#xA;    24    24    24    24&#xA;Selective dynamics&#xA;Direct&#xA;  0.5612360243849388  0.9099052137287840  0.6250221820654160   T   T   T&#xA;  0.2356071120850486  0.2518526753215678  0.5772064214469697   T   T   T&#xA;  0.2348146468815286  0.7507696751875000  0.5764034425400485   T   T   T&#xA;  0.4860087088559321  0.5025000099364838  0.5766204786838768   T   T   T&#xA;  0.4832051517095323  0.9985833850246899  0.5770138532476135   T   T   T&#xA;  0.4854835901844644  0.7512215609776637  0.5763813008840900   T   T   T&#xA;  0.2355456895711744  0.9978683794875377  0.5777498674746212   T   T   T&#xA;  0.9867436499750243  0.5059613373927444  0.5769244369303035   T   T   T&#xA;  0.9038462779907266  0.5846022973376531  0.5260416228921621   T   T   T&#xA;  0.5716581887774268  0.9201204041921329  0.4758342950788617   F   F   F&#xA;  0.5741257856744610  0.4187527924396477  0.4757376011984320   F   F   F&#xA;  0.8221917385325952  0.1698063756466937  0.4754235315612263   F   F   F&#xA;  0.8188510224305006  0.6661687044098628  0.4754012746578056   F   F   F&#xA;  0.8238998402551019  0.4200678697901523  0.4748374331044047   F   F   F&#xA;  0.5727204154956951  0.6689043793196774  0.4747973706782389   F   F   F&#xA;  0.3230897361863398  0.1691307692332842  0.4746252506250954   F   F   F&#xA;  0.2362167951761762  0.2470966960213019  0.4240635012206155   F   F   F&#xA;  0.9075250613866288  0.5865598256619577  0.3747389883475734   F   F   F&#xA;  0.9099926467579991  0.0851921908197042  0.3746422944671437   F   F   F&#xA;  0.1580586012731757  0.8362458075069128  0.3743282248299380   F   F   F&#xA;  0.1547179181243052  0.3326081258796876  0.3743059679265173   F   F   F&#xA;  0.1597667301860781  0.0865072797151001  0.3737421263731164   F   F   F&#xA;  0.9085872881049042  0.3353438007895022  0.3737020639469506   F   F   F&#xA;  0.6589565758423106  0.8355702010934962  0.3735299438938071   F   F   F&#xA;  0.8058501908443986  0.1604085948745253  0.6276226743697434   T   T   T&#xA;  0.0711651015373968  0.1740917158429164  0.6283794021117671   T   T   T&#xA;  0.5585537014512123  0.1589400490967113  0.6274647415475056   T   T   T&#xA;  0.8408195288613217  0.4120066169412361  0.6276226664037110   T   T   T&#xA;  0.8218106695859454  0.6771528044496808  0.6304296582071180   T   T   T&#xA;  0.0835097517099495  0.4214918947625969  0.6290440423670955   T   T   T&#xA;  0.2375735696515378  0.5010054481380813  0.5770179622858687   T   T   T&#xA;  0.7358517176793846  0.5001337489919461  0.5753017076229778   T   T   T&#xA;  0.1526774569984566  0.8311508061347753  0.5260862055103875   T   T   T&#xA;  0.4012780008378368  0.8374455841948802  0.5256159156652330   T   T   T&#xA;  0.9015458337759297  0.8318449292366887  0.5267321752290328   T   T   T&#xA;  0.1650345374797721  0.0820828245082830  0.5266625182108280   T   T   T&#xA;  0.1530715796942058  0.3284398123835934  0.5256954404458725   T   T   T&#xA;  0.4037759574840217  0.0881761973292648  0.5266741240986712   T   T   T&#xA;  0.5719291831091056  0.1671338512338281  0.4751517500405313   F   F   F&#xA;  0.0726206267831913  0.1688011628918105  0.4750530777686848   F   F   F&#xA;  0.4902349088201277  0.5006121147652394  0.4250452779605283   F   F   F&#xA;  0.7387644569889744  0.5022689205818693  0.4249752923642092   F   F   F&#xA;  0.2384726428149762  0.4987219869114483  0.4248748889998737   F   F   F&#xA;  0.4894111111794288  0.7512741008171346  0.4248244400187815   F   F   F&#xA;  0.4908000549497729  0.0025951829486672  0.4244191170775409   F   F   F&#xA;  0.7393419908448990  0.7494893777233287  0.4241708289549067   F   F   F&#xA;  0.9077960227650834  0.8335732830940472  0.3740564433092430   F   F   F&#xA;  0.4084875035752731  0.8352405947520296  0.3739577710373965   F   F   F&#xA;  0.0714088580284006  0.9241042308280607  0.6266688247630529   T   T   T&#xA;  0.0712936348301734  0.6734806713146717  0.6264448440732556   T   T   T&#xA;  0.5661143764171257  0.6694797179385326  0.6276482980086926   T   T   T&#xA;  0.5826565215444279  0.4197094481854535  0.6248967461469209   T   T   T&#xA;  0.9863437963371268  0.0049281853325266  0.5778527630146324   T   T   T&#xA;  0.7299839656132034  0.7483226508951495  0.5771810032009886   T   T   T&#xA;  0.9822818352016206  0.7481102940128979  0.5771714159167410   T   T   T&#xA;  0.4836853691620328  0.2504096534801669  0.5765478188719351   T   T   T&#xA;  0.4023001272576696  0.5849271527966273  0.5256599968038801   T   T   T&#xA;  0.4052342653716023  0.3382546586388231  0.5252451653467152   T   T   T&#xA;  0.9035134348127880  0.3352264766627390  0.5263625912611249   T   T   T&#xA;  0.9027949755174263  0.0791523962176613  0.5260593633310788   T   T   T&#xA;  0.3232407866261937  0.6702789128053368  0.4755137956695563   F   F   F&#xA;  0.0665275574938846  0.4173909583226560  0.4755078604953127   F   F   F&#xA;  0.3245013047405436  0.4173221508342095  0.4749788880906110   F   F   F&#xA;  0.8209027016053341  0.9159207229719186  0.4747226864023091   F   F   F&#xA;  0.7400046718620530  0.2526014105458927  0.4255408650100989   F   F   F&#xA;  0.7373990205197032  0.9972170014700694  0.4251333163785205   F   F   F&#xA;  0.2401126400303042  0.0008789443175559  0.4246560294495438   F   F   F&#xA;  0.2420278484524303  0.7522265534676222  0.4244614051940516   F   F   F&#xA;  0.6591076592354028  0.3367183342751616  0.3744184889382680   F   F   F&#xA;  0.4023944301030866  0.0838303797924809  0.3744125537640244   F   F   F&#xA;  0.6603682004010807  0.0837616184835568  0.3738835813593226   F   F   F&#xA;  0.1567695396708118  0.5823600289929374  0.3736276269699488   F   F   F&#xA;  0.8139283773437237  0.9179970463961956  0.6264927519830703   T   T   T&#xA;  0.3316971715924403  0.4206428344420928  0.6270248681347872   T   T   T&#xA;  0.3156932809260076  0.9156706536874418  0.6266447810285281   T   T   T&#xA;  0.3193842754680041  0.6705125009466922  0.6268440812499967   T   T   T&#xA;  0.3204197280025719  0.1699424665767754  0.6272751272551228   T   T   T&#xA;  0.7346622986391906  0.2521520822199035  0.5767044378177472   T   T   T&#xA;  0.7337753457319838 -0.0000484138730764  0.5764088122275434   T   T   T&#xA;  0.9859905944062034  0.2532340884891014  0.5767699223686655   T   T   T&#xA;  0.1520510767833566  0.5824068293232663  0.5262650644687904   T   T   T&#xA;  0.6539763846918202  0.0840366980125778  0.5258262367600025   T   T   T&#xA;  0.6540657686858518  0.5846162808349679  0.5256774417697333   T   T   T&#xA;  0.6542669891634135  0.3357645143656891  0.5254505398702217   T   T   T&#xA;  0.6510606874754463  0.8330745611877558  0.5256560801844358   T   T   T&#xA;  0.0765196813155740  0.9206583956286494  0.4765519565648120   F   F   F&#xA;  0.0658167894639234  0.6668927993218503  0.4761879325443701   F   F   F&#xA;  0.3165218299266357  0.9183686994568774  0.4733637787988272   F   F   F&#xA;  0.4845041515414152  0.2488359322854947  0.4251788193810739   F   F   F&#xA;  0.9902804335043385  0.7510055668940936  0.4248024304142888   F   F   F&#xA;  0.9888284822195317  0.2504328201717385  0.4244866296845942   F   F   F&#xA;  0.9943961297937989  0.9996431581306737  0.4242620822589416   F   F   F&#xA;  0.9866011241072812  0.4984118914182147  0.4231390978317506   F   F   F&#xA;  0.4123865539247760  0.5870978170984742  0.3754566498335237   F   F   F&#xA;  0.4016836620731254  0.3333322207916751  0.3750926258130818   F   F   F&#xA;  0.6523887025358377  0.5848081209267022  0.3722684720675389   F   F   F&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;O-rich&#xA;1.000000&#xA;     10.00748080        0.00000000        0.00000000&#xA;     -5.00374042        8.66673264        0.00000000&#xA;      0.00000000        0.00000000       36.03196650&#xA; Cr  O&#xA;    24      36&#xA;Selective dynamics&#xA;Direct&#xA;      0.00000000        0.00000000        0.55961703 T T T&#xA;      0.16666667        0.33333335        0.54845516 T T T&#xA;      0.33333329        0.16666662        0.49366831 F F F&#xA;      0.00000000        0.00000000        0.48127432 F F F&#xA;      0.16666667        0.33333335        0.43116020 F F F&#xA;      0.33333329        0.16666662        0.41876621 F F F&#xA;      0.00000000        0.49999996        0.55961703 T T T&#xA;      0.16666668        0.83333331        0.54845516 T T T&#xA;      0.33333335        0.66666669        0.49366831 F F F&#xA;      0.00000000        0.49999996        0.48127432 F F F&#xA;      0.16666668        0.83333331        0.43116020 F F F&#xA;      0.33333335        0.66666669        0.41876621 F F F&#xA;      0.49999996        0.00000000        0.55961703 T T T&#xA;      0.66666663        0.33333335        0.54845516 T T T&#xA;      0.83333335        0.16666662        0.49366831 F F F&#xA;      0.49999996        0.00000000        0.48127432 F F F&#xA;      0.66666663        0.33333335        0.43116020 F F F&#xA;      0.83333335        0.16666662        0.41876621 F F F&#xA;      0.49999996        0.49999996        0.55961703 T T T&#xA;      0.66666664        0.83333331        0.54845516 T T T&#xA;      0.83333331        0.66666669        0.49366831 F F F&#xA;      0.49999996        0.49999996        0.48127432 F F F&#xA;      0.66666664        0.83333331        0.43116020 F F F&#xA;      0.83333331        0.66666669        0.41876621 F F F&#xA;      0.14491598        0.16765143        0.57712412 T T T&#xA;      0.02273547        0.35508401        0.57712412 T T T&#xA;      0.33234850        0.47726449        0.57712412 T T T&#xA;      0.99859339        0.15136682        0.51757826 T T T&#xA;      0.34863311        0.34722655        0.51757826 T T T&#xA;      0.15277344        0.50140656        0.51757826 T T T&#xA;      0.33333332        0.01582073        0.45621740 F F F&#xA;      0.18248737        0.16666662        0.45621740 F F F&#xA;      0.48417927        0.31751262        0.45621740 F F F&#xA;      0.14491605        0.66765151        0.57712412 T T T&#xA;      0.02273547        0.85508397        0.57712412 T T T&#xA;      0.33234857        0.97726457        0.57712412 T T T&#xA;     -0.00140656        0.65136690        0.51757826 T T T&#xA;      0.34863312        0.84722651        0.51757826 T T T&#xA;      0.15277348        0.00140659        0.51757826 T T T&#xA;      0.33333331        0.51582069        0.45621740 F F F&#xA;      0.18248739        0.66666669        0.45621740 F F F&#xA;      0.48417926        0.81751258        0.45621740 F F F&#xA;      0.64491595        0.16765143        0.57712412 T T T&#xA;      0.52273553        0.35508401        0.57712412 T T T&#xA;      0.83234847        0.47726449        0.57712412 T T T&#xA;      0.49859344        0.15136682        0.51757826 T T T&#xA;      0.84863317        0.34722655        0.51757826 T T T&#xA;      0.65277344        0.50140656        0.51757826 T T T&#xA;      0.83333338        0.01582073        0.45621740 F F F&#xA;      0.68248739        0.16666662        0.45621740 F F F&#xA;      0.98417933        0.31751262        0.45621740 F F F&#xA;      0.64491601        0.66765151        0.57712412 T T T&#xA;      0.52273547        0.85508397        0.57712412 T T T&#xA;      0.83234853        0.97726457        0.57712412 T T T&#xA;      0.49859340        0.65136690        0.51757826 T T T&#xA;      0.84863317        0.84722651        0.51757826 T T T&#xA;      0.65277344        0.00140659        0.51757826 T T T&#xA;      0.83333328        0.51582069        0.45621740 F F F&#xA;      0.68248745        0.66666669        0.45621740 F F F&#xA;      0.98417923        0.81751258        0.45621740 F F F&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3442" LastEditorUserId="6687" LastEditDate="2023-08-24T05:36:12.283" LastActivityDate="2023-08-25T20:08:39.020" Title="Python code for combining two surfaces to form an interface" Tags="|python|surfaces|atomic-simulation-environment|solid-solid-interface|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11525" PostTypeId="2" ParentId="11287" CreationDate="2023-08-23T18:35:08.713" Score="1" Body="&lt;p&gt;Roughly these are the steps to follow:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Install &lt;a href=&quot;https://pymol.org/2/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyMOL software&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Run a python script which captures the distance between residues in PyMOL command line&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;The script would do the following&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Load your structure into pymol python library using the cmd.load() function.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Calculate the distances between specific atoms of the two residues using cmd.distance() function. You will need to specify the atom selection strings for the two:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;distance_value = cmd.distance(&amp;quot;resi 1 and name CA&amp;quot;, &amp;quot;resi 10 and name CA&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;This calculates the distance between the alpha carbon atoms of residue 1 and residue 10.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Store the distances in a list and find the maximum distance using the max() function.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Below is a boilerplate code. Add a loop to calculate distances over all the residues according to your requirements.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Import the PyMOL module&#xA;import pymol&#xA;&#xA;# Initialize PyMOL&#xA;pymol.finish_launching()&#xA;&#xA;# Load your structure&#xA;cmd.load(&amp;quot;your_structure.pdb&amp;quot;)&#xA;&#xA;# List to store distances&#xA;distances = []&#xA;&#xA;# Residue indices&#xA;residue_1_index = 1&#xA;residue_10_index = 10&#xA;&#xA;# Calculate distance and store in the list&#xA;distance_value = cmd.distance(f&amp;quot;resi {residue_1_index} and name CA&amp;quot;, f&amp;quot;resi {residue_10_index} and name CA&amp;quot;)&#xA;distances.append(distance_value)&#xA;&#xA;# You can repeat the above block of code for other residue pairs&#xA;&#xA;# Find the largest distance&#xA;largest_distance = max(distances)&#xA;&#xA;# Print the largest distance&#xA;print(&amp;quot;Largest distance:&amp;quot;, largest_distance)&#xA;&#xA;# Close PyMOL&#xA;pymol.cmd.quit()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-23T18:35:08.713" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11526" PostTypeId="2" ParentId="9590" CreationDate="2023-08-23T18:38:45.583" Score="2" Body="&lt;p&gt;You can use gmx-densmap and set the average along the y-axis to get the contour plot showing the density as a function of the x and z-axis and the average over the y-axis.&lt;/p&gt;&#xA;&lt;p&gt;Use the command as :&lt;/p&gt;&#xA;&lt;p&gt;gmx densmap -f trj.trr -s trj.tpr -o densmap.xpm -aver y -n index.ndx -bin 0.01&lt;/p&gt;&#xA;&lt;p&gt;Use index.ndx to calculate the density of a selected atom or molecule.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastActivityDate="2023-08-23T18:38:45.583" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11527" PostTypeId="2" ParentId="11514" CreationDate="2023-08-23T22:27:43.683" Score="5" Body="&lt;p&gt;It's easy enough to write a set of lattice vectors as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{bmatrix} \bf{a} &amp;amp; \bf{b} &amp;amp; \bf{c} \end{bmatrix} = \begin{bmatrix} 2 &amp;amp; 0 &amp;amp; 0 \\ 0 &amp;amp; 2 &amp;amp; 0 \\ 0 &amp;amp; 0 &amp;amp; 2 \end{bmatrix}.  \tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;And it's easy enough to write another set of lattice vectors as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\begin{bmatrix} \bf{a'} &amp;amp; \bf{b'} &amp;amp; \bf{c'} \end{bmatrix} = \begin{bmatrix} \sqrt{2} &amp;amp; \sqrt{2} &amp;amp; 0 \\ -\sqrt{2} &amp;amp; \sqrt{2} &amp;amp; 0 \\ 0 &amp;amp; 0 &amp;amp; 2 \end{bmatrix}.  \tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But it may &lt;em&gt;not&lt;/em&gt; be easy to recognise that those are actually the &lt;em&gt;same&lt;/em&gt; lattice vectors, just rotated.&lt;/p&gt;&#xA;&lt;p&gt;There are infinitely many representations of the same lattice vectors under some arbitrary rotation, and it would be very confusing if different people used different representations for the same lattice vectors because of that. So the &lt;em&gt;standard&lt;/em&gt; representation of a triclinic lattice vector set requires you to put:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the &lt;span class=&quot;math-container&quot;&gt;$\bf{a}$&lt;/span&gt; vector &lt;em&gt;along the positive x-axis&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;the &lt;span class=&quot;math-container&quot;&gt;$\bf{b}$&lt;/span&gt; vector &lt;em&gt;on the x-y plane&lt;/em&gt;&lt;/li&gt;&#xA;&lt;li&gt;the &lt;span class=&quot;math-container&quot;&gt;$\bf{c}$&lt;/span&gt; vector &lt;em&gt;in right-hand orientation&lt;/em&gt; so that the cell volume is positive (thus &lt;span class=&quot;math-container&quot;&gt;$(\bf{a} \times \bf{b}) \cdot \bf{c} &amp;gt; 0$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Not coincidentally, this makes the lattice &amp;quot;matrix&amp;quot; an upper triangular matrix, always having (at most) six non-zero entries instead of nine. This in turn is useful for computer programs dealing with lattices, where you only need to store six numbers instead of nine and presumably avoid some amount of floating point error.&lt;/p&gt;&#xA;&lt;p&gt;Once you apply those constraints, it's straightforward trigonometry to see that they lead to the matrix form in your screenshot. I personally frequently consult the &lt;a href=&quot;https://docs.lammps.org/Howto_triclinic.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;triclinic lattice info page&lt;/a&gt; for LAMMPS, my usual molecular dynamics software package, since it has all relevant formulae in one handy web page.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5" LastEditDate="2023-08-23T23:47:02.920" LastActivityDate="2023-08-23T23:47:02.920" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11528" PostTypeId="1" CreationDate="2023-08-24T06:22:44.223" Score="3" ViewCount="62" Body="&lt;p&gt;When calculating PDOS for an atom in a system, the corresponding electron occupancy or other parameters like the highest band edge/dos value at Fermi level/band center is different when using different smearing methods. When there are no references for the material available how to confirm which smearing method is correct?&lt;/p&gt;&#xA;" OwnerUserId="5619" LastActivityDate="2023-09-23T15:06:20.813" Title="How does one verify the density of states obtained using different smearing methods?" Tags="|density-functional-theory|density-of-states|smearing|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11529" PostTypeId="1" CreationDate="2023-08-24T07:38:54.120" Score="2" ViewCount="32" Body="&lt;p&gt;I am doing ab initio molecular dynamics in VASP. As far as I know, pseudopotentials approximate all-electron potential far from the nucleus, and deviate from it near the nucleus.&lt;/p&gt;&#xA;&lt;p&gt;When some of my atoms are assigned large velocities, and when I take a very small time step, I noticed that atoms can approach very close to each other. Can I trust my calculations in this case? Does using pseudopotentials mean that we can use AIMD based on them only when atoms are not too close to each other? How to find the closest distance at which we still can use pseudopotential-based AIMD?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2023-08-24T07:38:54.120" Title="How to estimate the minimal distance between atoms for which a pseudopotential-based AIMD gets forces correctly?" Tags="|density-functional-theory|vasp|molecular-dynamics|pseudopotentials|aimd|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11530" PostTypeId="1" CreationDate="2023-08-24T14:08:57.777" Score="3" ViewCount="28" Body="&lt;p&gt;I have been asked by a colleague if it is possible to calculate the spin-projected band structure (with SOC) for a material he is studying. He referenced a paper &lt;a href=&quot;https://www.nature.com/articles/srep15304&quot; rel=&quot;nofollow noreferrer&quot;&gt;Boschini et al. Sci. Reports 2015 - open access&lt;/a&gt;. In this paper the authors show (Fig 4e) the band structure for Bi2Te3 with the j=1/2, 3/2 character of the band structure along the X-Gamma-L line.&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to do something similar using Wien2K or another plane wave code?&lt;/p&gt;&#xA;&lt;p&gt;In particular, I would like to show the projected J character with SOC for a similar, but different material. The authors used a KKR Green's function code. I would like to use a plane wave code if possible. Thanks for any advice you can offer.&lt;/p&gt;&#xA;" OwnerUserId="4328" LastEditorUserId="6687" LastEditDate="2023-08-25T03:56:47.667" LastActivityDate="2023-08-25T03:56:47.667" Title="total spin (J-resolved) projected band structure with SOC" Tags="|density-functional-theory|band-structure|plane-waves|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11531" PostTypeId="2" ParentId="11528" CreationDate="2023-08-24T14:47:18.060" Score="2" Body="&lt;p&gt;This paper &amp;quot;&lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S277294942200002X?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;How to analyse a density of states&lt;/a&gt;&amp;quot; answers your question quite well I believe. Here's the &amp;quot;conclusion&amp;quot; of the paper.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The density of states reveals striking features of an electronic structure that are often overlooked. This mini-tutorial should serve as a guide for interpreting the DOS of a real material. Not only can important material parameters like band gap and DOS effective mass (which may be derived from Seebeck coefficient measurements) be seen from a DOS, but new, unusual phenomena such as reduced dimensionality and unconventional band shapes can be identified from the shape of a DOS. Such phenomena can also exist deeper in the band, revealing potentially novel behavior of complex materials.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Smearing methods in electronic structure calculations can obscure these essential features and instead introduce artefacts that can be misidentified. These shortcomings can be remedied simply by using the tetrahedron method when computing the DOS and looking for these essential features of a DOS when assessing convergence of the calculation.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-08-24T14:47:18.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11532" PostTypeId="1" AcceptedAnswerId="11648" CreationDate="2023-08-24T20:38:42.227" Score="2" ViewCount="51" Body="&lt;p&gt;I'm using &lt;a href=&quot;https://cdk.github.io/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemistry Development Kit&lt;/a&gt; (CDK) to create molecular drawings using the DepictionGenerator class. It allows me to set the drawing's width and height using the method withSize(w, h) but the unit is assumed to be mm. I want to change that to pixels but not sure where that should happen. Your help in resolving this would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7610" LastEditorUserId="6687" LastEditDate="2023-08-25T02:29:18.060" LastActivityDate="2023-09-21T01:17:04.913" Title="Specify Molecular Visualization Dimension" Tags="|molecular-modeling|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11533" PostTypeId="1" CreationDate="2023-08-24T22:52:14.147" Score="3" ViewCount="60" Body="&lt;p&gt;The only other &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2093/artificial-muscles-and-their-efficiency&quot;&gt;question in regards to this subject&lt;/a&gt; doesn't have a precise answer and it is more about actuators that directly convert electricity into mechanical force.&lt;/p&gt;&#xA;&lt;p&gt;Nylon or polyethylene fibers, simply called &amp;quot;fishing lines&amp;quot; are thermoactive polymers that &amp;quot;contract&amp;quot; when exposed to temperatures around 130ºC, and thus, can be used like artificial muscles. &lt;a href=&quot;https://youtu.be/UbvNW7ONiTc&quot; rel=&quot;nofollow noreferrer&quot;&gt;Here a simple video&lt;/a&gt; showing it.&lt;/p&gt;&#xA;&lt;p&gt;However, even though I saw a lot of videos on the subject, I couldn't find the efficiency of converting heat into mechanical work.&lt;/p&gt;&#xA;" OwnerUserId="6259" LastEditorUserId="6259" LastEditDate="2023-08-25T12:34:58.250" LastActivityDate="2023-08-25T12:34:58.250" Title="What is the efficiency of Nylon/Polyethylene artificial muscles?" Tags="|polymers|materials-engineering|" AnswerCount="0" CommentCount="3" ClosedDate="2023-09-05T08:09:05.050" ContentLicense="CC BY-SA 4.0" />
  <row Id="11534" PostTypeId="2" ParentId="11532" CreationDate="2023-08-25T03:38:55.193" Score="0" Body="&lt;p&gt;As per the CDK documentation for raster graphics (ex JPEG, TIFF etc) the dimension of the width and height is pixels and for vector graphics (SVG, EPS etc) the dimension is mm.&lt;/p&gt;&#xA;&lt;p&gt;Here I quote the documentation found here : &lt;a href=&quot;https://cdk.github.io/cdk/2.3/docs/api/org/openscience/cdk/depict/DepictionGenerator.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CDK-docs&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;withSize public DepictionGenerator withSize(double w,double h)&lt;/p&gt;&#xA;&lt;p&gt;Specify a desired size of depiction. The units depend on the output&#xA;format with raster images using pixels and vector graphics using&#xA;millimeters.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-25T03:38:55.193" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11535" PostTypeId="2" ParentId="11524" CreationDate="2023-08-25T05:22:05.463" Score="2" Body="&lt;h1&gt;ASE&lt;/h1&gt;&#xA;&lt;p&gt;You could achieve the stacking using the Atomic Simulation Environment (ASE) python library.&lt;/p&gt;&#xA;&lt;p&gt;Below I have attached a sample code for stacking using the 2 POSCAR files you have attached. Also, I have visualized the POSCARs before and after stacking.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase.io import read, write&#xA;from ase.build import stack&#xA;import matplotlib.pyplot as plt&#xA;&#xA;# Load the two POSCAR files&#xA;poscar1 = read(&amp;quot;POSCAR1&amp;quot;)&#xA;poscar2 = read(&amp;quot;POSCAR2&amp;quot;)&#xA;&#xA;# Match the lattice constants&#xA;scaling_factor = poscar1.get_cell_lengths_and_angles()[:3] / poscar2.get_cell_lengths_and_angles()[:3]&#xA;poscar2.set_cell(poscar2.get_cell() * scaling_factor, scale_atoms=True)&#xA;&#xA;# Shift the second structure to align with the first&#xA;shift = poscar1.get_center_of_mass() - poscar2.get_center_of_mass()&#xA;poscar2.translate(shift)&#xA;&#xA;# Combine the two structures&#xA;combined_structure = stack(poscar1, poscar2, axis=2)&#xA;&#xA;# Write the combined structure to a new POSCAR file&#xA;write(&amp;quot;Combined_POSCAR.vasp&amp;quot;, combined_structure)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Visualize the original POSCARs&#xA;from ase.visualize import view&#xA;&#xA;# POSCAR 1&#xA;view(poscar1, viewer=&amp;quot;x3d&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WR2lMm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WR2lMm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# POSCAR 2&#xA;view(poscar2, viewer=&amp;quot;x3d&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tSYCdm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tSYCdm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;view(combined_structure, viewer=&amp;quot;x3d&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/BZyRHm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BZyRHm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-08-25T20:08:39.020" LastActivityDate="2023-08-25T20:08:39.020" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11536" PostTypeId="1" CreationDate="2023-08-25T06:52:34.537" Score="5" ViewCount="90" Body="&lt;p&gt;I'm currently picking up CASTEP for geometry optimization and am following the website's tutorials.&lt;/p&gt;&#xA;&lt;p&gt;Strangely, none of the documentation indicates how one should &lt;em&gt;efficiently&lt;/em&gt; extract information from CASTEP files, despite the fact that the output files are in a human readable format, instead of a machine readable format.  For example, I need to test for convergence, and copying and pasting the forces and stresses for even a single calculations is a tedious and error prone task.  I highly doubt that this is how regular users actually analyze their data.  Presumably, they use a tool to extract the information out from the binary files.&lt;/p&gt;&#xA;&lt;p&gt;I haven't been able to find an obvious, or standard, tool for dealing with castep output.   No one around me uses CASTEP.  And I doubt everyone else paid for Materials Studio.  So, I have to ask:  What are the standard tools people use for plotting output from .castep files?&lt;/p&gt;&#xA;" OwnerUserId="7774" LastActivityDate="2023-08-31T16:45:52.640" Title="CASTEP: Tools for extracting .castep output into OriginLab or similar programs for plotting" Tags="|density-functional-theory|castep|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11537" PostTypeId="1" CreationDate="2023-08-25T07:23:13.210" Score="2" ViewCount="32" Body="&lt;p&gt;I am trying to simulate bulk dimethyl ether with total constraints, both bonds and angles.&#xA;I am using lincs with constraint = all-angles in *.mdp file in gromacs.&lt;/p&gt;&#xA;&lt;p&gt;I am attaching the error I encountered while simulating with total constraint.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;Source file: src/gromacs/mdlib/constr.cpp (line 169)&#xA;&#xA;Fatal error:&#xA;Too many LINCS warnings (13139)&#xA;If you know what you are doing you can adjust the lincs warning threshold in&#xA;your mdp file&#xA;or set the environment variable GMX_MAXCONSTRWARN to -1,&#xA;but normally it is better to fix the problem&#xA;&#xA;For more information and tips for troubleshooting, please check the GROMACS&#xA;website at http://www.gromacs.org/Documentation/Errors&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My dimethyl-ether.itp file looks like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[ moleculetype ]&#xA;;name            nrexcl&#xA; DMT              3&#xA;&#xA;[ atoms ]&#xA;;   nr  type  resi  res  atom  cgnr     charge      mass       ; qtot   bond_type&#xA;     1   os     1   DMT     O    1    -0.419598     16.00000 ; qtot -0.420&#xA;     2   c3     1   DMT    CD    2     0.113700     12.01000 ; qtot -0.306&#xA;     3   c3     1   DMT    C1    3     0.113700     12.01000 ; qtot -0.192&#xA;     4   h1     1   DMT    HD    4     0.032033      1.00800 ; qtot -0.160&#xA;     5   h1     1   DMT    H1    5     0.032033      1.00800 ; qtot -0.128&#xA;     6   h1     1   DMT    H2    6     0.032033      1.00800 ; qtot -0.096&#xA;     7   h1     1   DMT    H3    7     0.032033      1.00800 ; qtot -0.064&#xA;     8   h1     1   DMT    H4    8     0.032033      1.00800 ; qtot -0.032&#xA;     9   h1     1   DMT    H5    9     0.032033      1.00800 ; qtot 0.000&#xA;&#xA;[ bonds ]&#xA;;   ai     aj funct   r             k&#xA;     1      2   1    1.4320e-01    2.3832e+05 ;     O - CD     &#xA;     1      3   1    1.4320e-01    2.3832e+05 ;     O - C1    &#xA;     2      4   1    1.0970e-01    3.1455e+05 ;     CD - HD     &#xA;     2      5   1    1.0970e-01    3.1455e+05 ;     CD - H1    &#xA;     2      6   1    1.0970e-01    3.1455e+05 ;     CD - H2    &#xA;     3      7   1    1.0970e-01    3.1455e+05 ;     C1 - H3    &#xA;     3      8   1    1.0970e-01    3.1455e+05 ;     C1 - H4    &#xA;     3      9   1    1.0970e-01    3.1455e+05 ;     C1 - H5    &#xA;&#xA;[ pairs ]&#xA;;   ai     aj    funct&#xA;     2      7      1 ;     CD - H3    &#xA;     2      8      1 ;     CD - H4    &#xA;     2      9      1 ;     CD - H5    &#xA;     3      4      1 ;     C1 - HD     &#xA;     3      5      1 ;     C1 - H1    &#xA;     3      6      1 ;     C1 - H2    &#xA;&#xA;[ angles ]&#xA;;   ai     aj     ak    funct   theta         cth&#xA;     1      2      4      1    1.0978e+02    5.2216e+02 ;      O - CD     - H     &#xA;     1      2      5      1    1.0978e+02    5.2216e+02 ;      O - CD     - H1    &#xA;     1      2      6      1    1.0978e+02    5.2216e+02 ;      O - CD     - H2    &#xA;     1      3      7      1    1.0978e+02    5.2216e+02 ;      O - C1     - H3    &#xA;     1      3      8      1    1.0978e+02    5.2216e+02 ;      O - C1     - H4    &#xA;     1      3      9      1    1.0978e+02    5.2216e+02 ;      O - C1     - H5    &#xA;     2      1      3      1    1.1248e+02    5.5480e+02 ;     CD - O      - C1    &#xA;     4      2      5      1    1.0846e+02    3.2468e+02 ;     HD - CD      - H1    &#xA;     4      2      6      1    1.0846e+02    3.2468e+02 ;     HD - CD      - H2    &#xA;     5      2      6      1    1.0846e+02    3.2468e+02 ;     H1 - CD      - H2    &#xA;     7      3      8      1    1.0846e+02    3.2468e+02 ;     H3 - C1     - H4    &#xA;     7      3      9      1    1.0846e+02    3.2468e+02 ;     H3 - C1     - H5    &#xA;     8      3      9      1    1.0846e+02    3.2468e+02 ;     H4 - C1     - H5    &#xA;&#xA;[ dihedrals ] ; propers &#xA;; for gromacs 4.5 or higher, using funct 9&#xA;;    i      j      k      l   func   phase     kd      pn&#xA;     2      1      3      7      9     0.00   1.41001   3 ;     CD-     O-    C1-    H3&#xA;     2      1      3      8      9     0.00   1.41001   3 ;     CD-     O-    C1-    H4&#xA;     2      1      3      9      9     0.00   1.41001   3 ;     CD-     O-    C1-    H5&#xA;     3      1      2      4      9     0.00   1.41001   3 ;     C1-     O-    CD-    HD&#xA;     3      1      2      5      9     0.00   1.41001   3 ;     C1-     O-    CD-    H1&#xA;     3      1      2      6      9     0.00   1.41001   3 ;     C1-     O-    CD-    H2 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do I need to add any other lines in *.itp file?&lt;/p&gt;&#xA;&lt;p&gt;I would be thankful if someone can shed light on the following error.&lt;/p&gt;&#xA;" OwnerUserId="4034" LastEditorUserId="6687" LastEditDate="2023-08-25T20:03:58.500" LastActivityDate="2023-08-25T20:03:58.500" Title="Error Simulating bulk diemthyl-ether with angle constrain in gromacs" Tags="|computational-chemistry|gromacs|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11540" PostTypeId="1" CreationDate="2023-08-25T16:29:43.733" Score="3" ViewCount="31" Body="&lt;p&gt;On the &lt;strong&gt;pymolyze&lt;/strong&gt; program, the &amp;quot;calculate&amp;quot; panel contains : Muliken, Csquared,Density of states, overlap population and overlap DOS analysis.&lt;/p&gt;&#xA;&lt;p&gt;While performing a DOS analysis, how can we get  the contribution of each fragment on HOMO and LUMO orbitals?&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="5" LastEditDate="2023-08-25T22:45:11.377" LastActivityDate="2023-08-25T22:45:11.377" Title="Density of states on pymolyze" Tags="|density-of-states|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11541" PostTypeId="1" CreationDate="2023-08-26T05:30:28.257" Score="3" ViewCount="32" Body="&lt;p&gt;I have prepared Lithium ferrite samples doped with Zinc, Titanium, and Manganese. After taking the XRD data I wanted to perform Rietveld refinement. But the problem is that I have cif data available only for Zinc substituted Lithium ferrite. Although I have gone about refinement and it works somewhat, how can I insert the missing substituent in the cif file? Please help.&lt;/p&gt;&#xA;" OwnerUserId="7780" LastActivityDate="2023-08-26T05:30:28.257" Title="How can I add the extra elements in the available CIF file for refinement?" Tags="|vesta|x-ray-diffraction|fullprof-suite|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11542" PostTypeId="1" CreationDate="2023-08-26T07:23:53.573" Score="2" ViewCount="80" Body="&lt;p&gt;Why the total energy calculated with GGA and metaGGA=SCAN are so different?&#xA;My INNCAR file is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; **PREC = Accurate&#xA; ISTART=0                       &#xA; ICHARG=2                       &#xA; ENCUT=520                     &#xA; NELM=40                      &#xA; ISMEAR=0&#xA; SIGMA=0.05                     &#xA;Dynamic:&#xA; ISIF=3                         &#xA; IBRION=2                       &#xA; ISYM = 2&#xA; NSW=200                        &#xA; EDIFF = 0.00001&#xA; EDIFFG = -0.01                  &#xA;Mix:&#xA; LMAXMIX=4&#xA; METAGGA=SCAN&#xA; ALGO = ALL&#xA; LASPH = .TRUE.&#xA;#ADDGRID = .TRUE.&#xA; LDIAG =.FALSE.&#xA;#LUSE_VDW = .TRUE.&#xA;#BPARAM = 15.7&#xA;Paralellisation:&#xA; NCORE = 4&#xA;Output:&#xA; LCHARG=.FALSE.                 &#xA; LWAVE=.FALSE.***                  &#xA; &#xA;The output for Si&#xA;In GGA&#xA;FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)&#xA;  ---------------------------------------------------&#xA;  free  energy   TOTEN  =       -10.84990789 eV&#xA;&#xA;&#xA;In metaGGA=scan&#xA;FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)&#xA;  ---------------------------------------------------&#xA;  free  energy   TOTEN  =       -20.01529337 eV&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7782" LastEditorUserId="5" LastEditDate="2023-08-26T12:13:12.220" LastActivityDate="2023-08-26T12:13:12.220" Title="Why the total energy calculated with GGA and metaGGA=SCAN are so different?" Tags="|density-functional-theory|vasp|computational-chemistry|condensed-matter|cell-optimization|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11543" PostTypeId="1" AcceptedAnswerId="11544" CreationDate="2023-08-27T07:30:58.127" Score="8" ViewCount="1087" Body="&lt;p&gt;Does anyone know how to cite the developmental version of Avogadro 2 version 1.98 mentioned &lt;a href=&quot;https://discuss.avogadro.cc/t/avogadro-2023-roadmap/4412&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; or unpublished software in general?&lt;/p&gt;&#xA;&lt;p&gt;I have found a BibTeX citation &lt;a href=&quot;http://citebay.com/how-to-cite/avogadro/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; though this is for a generic version of Avogadro.&lt;/p&gt;&#xA;" OwnerUserId="7679" LastEditorUserId="5" LastEditDate="2023-08-27T13:47:56.923" LastActivityDate="2023-08-30T16:15:30.593" Title="How do I cite development version of a software?" Tags="|avogadro|publishing|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11544" PostTypeId="2" ParentId="11543" CreationDate="2023-08-27T14:16:18.567" Score="7" Body="&lt;h1&gt;Doing what the authors prefer&lt;/h1&gt;&#xA;&lt;p&gt;Sometimes the authors will have strong preferences for how they want their work to be cited, so I would often try to ask the authors how they would like me to cite an &amp;quot;unreleased&amp;quot; or &amp;quot;unpublished&amp;quot; or &amp;quot;development&amp;quot; version of their software. You can see my answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11490/5&quot;&gt;How may I install the latest version of a software?&lt;/a&gt; for more information about such software versions.&lt;/p&gt;&#xA;&lt;h1&gt;When the authors don't respond&lt;/h1&gt;&#xA;&lt;p&gt;It is not always easy to get a response from the original authors though, and their response might be that they do not have strong preferences for how they want their development versions to be cited, so often you will have to make a decision yourself (which is fine, and even when the authors &lt;em&gt;&lt;strong&gt;do&lt;/strong&gt;&lt;/em&gt; have strong preferences, they'll find that a lot of people accidentally or intentionally botch their preferred BibTeX format anyway).&lt;/p&gt;&#xA;&lt;h1&gt;Finding the best BibTeX entry for the software&lt;/h1&gt;&#xA;&lt;p&gt;I disagree with the URL that you provided for the Avogadro2 BibTeX entry. It didn't seem right, and then when I looked more closely, I found that it was from &amp;quot;Cite Bay&amp;quot; which seems to be a name borrowed from &lt;a href=&quot;https://en.wikipedia.org/wiki/The_Pirate_Bay&quot; rel=&quot;noreferrer&quot;&gt;Pirate Bay&lt;/a&gt;. &lt;strong&gt;When seeking the authors' preferred way to cite something, I always recommend to look for something on their own website or GitHub page.&lt;/strong&gt; I didn't see anything immediately at &lt;a href=&quot;https://two.avogadro.cc/&quot; rel=&quot;noreferrer&quot;&gt;https://two.avogadro.cc/&lt;/a&gt;, and even the README of the &lt;a href=&quot;https://github.com/openchemistry/avogadrolibs&quot; rel=&quot;noreferrer&quot;&gt;GitHub page&lt;/a&gt; didn't have anything, but then I saw &amp;quot;Cite this repository&amp;quot; on the right-hand side, which gave me the following when I selected &amp;quot;BibTeX&amp;quot; as my preferred format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@software{Hanwell_Avogadro,&#xA;author = {Hanwell, Marcus and Hutchison, Geoffrey},&#xA;license = {BSD-3-Clause},&#xA;title = {{Avogadro}},&#xA;url = {https://github.com/openchemistry/avogadrolibs}&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is must more likely to be the way that the authors want you to cite it, because it's what they provided on their own GitHub page.&lt;/p&gt;&#xA;&lt;h1&gt;Version numbers or no version numbers?&lt;/h1&gt;&#xA;&lt;p&gt;There's ways to add a version number, or a &amp;quot;retrieved on ___&amp;quot; date for software, just like on other &amp;quot;dynamic&amp;quot; things such as websites. However the above BibTeX entry is the one that the authors likely prefer, and it doesn't mention any specific version number.&lt;/p&gt;&#xA;&lt;p&gt;Some authors might &lt;em&gt;&lt;strong&gt;want&lt;/strong&gt;&lt;/em&gt; you to specify the specific version number so that they can track how many citations each version is getting, or so that they can get multiple highly cited versions on their Google Scholar, or because of changes in co-authorship from version to version, or for whatever reasons they have (there's many reasonable reasons for this). Some authors might want citations no matter what the version, to all go to one place.&lt;/p&gt;&#xA;&lt;h1&gt;For your case (Avogadro2)&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;I personally would follow the authors' preference and use their suggested BibTeX entry, then in the paper when mentioning the software, I would say something like: &amp;quot;We used the nightly build from 31 February 2023&amp;quot; or &amp;quot;We built the 31 February 2023 version of the GitHub repository from source and used that&amp;quot;.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://arxiv.org/abs/2006.13453&quot; rel=&quot;noreferrer&quot;&gt;In one of my papers&lt;/a&gt; I actually did this at least two times:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;To calculate these integrals, we have used a locally modified version of MOLCAS [34] in order to support larger basis sets.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The calculations are performed using thedeveloper version of the software NECI [38]&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Reference [34] was just the standard most-recent reference for the OpenMolcas software (our local modification of it would have been done slightly before or around the time that the name &amp;quot;OpenMolcas&amp;quot; was first made, in case you're wondering why we wrote MOLCAS instead of OpenMolcas at the time).&lt;/p&gt;&#xA;&lt;p&gt;Reference [38] was just the standard reference for NECI at the time, which was the same reference for the developer version on BitBucket and the public version on GitHub, so the distinction was made in the text rather than in the BibTeX entry.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-08-27T14:16:18.567" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11545" PostTypeId="2" ParentId="11543" CreationDate="2023-08-27T21:38:46.767" Score="3" Body="&lt;p&gt;First, follow what the publisher says.&lt;/p&gt;&#xA;&lt;p&gt;Failing that, follow your house style.&lt;/p&gt;&#xA;&lt;p&gt;Failing that ask for - if you have to, demand - a style meeting in your house.&lt;/p&gt;&#xA;" OwnerUserId="1877" LastActivityDate="2023-08-27T21:38:46.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11546" PostTypeId="1" CreationDate="2023-08-28T11:25:57.160" Score="2" ViewCount="319" Body="&lt;p&gt;I work in the field of materials science. While exploring the concepts related to material stability, I have come across terms such as &amp;quot;Energy of Formation,&amp;quot; &amp;quot;Formation Energy,&amp;quot; &amp;quot;Heat of Formation,&amp;quot; and &amp;quot;Energy Above Hull.&amp;quot; These terms are used to describe the stability of materials. I have encountered these terminologies in various research papers related to hydrogen storage as well as in databases like the Materials Project.&lt;/p&gt;&#xA;&lt;p&gt;I am currently uncertain about which specific term to use in my report when referring to the stability of a material. Additionally, I am concerned about combining data from different databases. Each database seems to assess stability in its own way, which adds to my uncertainty.&lt;/p&gt;&#xA;&lt;p&gt;Thank you for your assistance&lt;/p&gt;&#xA;" OwnerUserId="7789" LastActivityDate="2023-09-28T07:52:54.117" Title="Energy of formation Vs Formation Energy Vs Heat of Formation Vs Energy Above Hull differences" Tags="|computational-chemistry|ab-initio-calculations|crystallography|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11548" PostTypeId="1" CreationDate="2023-08-28T16:21:33.283" Score="4" ViewCount="66" Body="&lt;p&gt;I computed the band structure of my material's supercell using Quantum ESPRESSO,but the resulting plot appears to be densely populated with bands, like in the picture bellow:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SyX8I.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SyX8I.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could someone provide guidance on how to adjust the visualization to achieve a more typical representation, please?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-08-28T16:21:33.283" Title="How can I improve the visualization of a band structure plot for a dense supercell?" Tags="|density-functional-theory|quantum-espresso|band-structure|condensed-matter|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11549" PostTypeId="1" CreationDate="2023-08-29T05:07:32.287" Score="3" ViewCount="186" Body="&lt;p&gt;I’ve supercells of around 10,000 Metal–organic frameworks (MOF) structures in CIF format. I’m looking to convert them to unit cells. But I’m not able to find packages (or any other libraries like Pymatgen) doing this. Any leads would be highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7609" LastEditorUserId="6055" LastEditDate="2023-08-29T05:53:30.240" LastActivityDate="2023-08-29T09:39:16.837" Title="Transform Supercell to Unitcell" Tags="|software|python|supercell|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11550" PostTypeId="2" ParentId="11549" CreationDate="2023-08-29T09:39:16.837" Score="4" Body="&lt;h1&gt;ASE&lt;/h1&gt;&#xA;&lt;p&gt;You could use ASE (Atomic Simulation Environment) to achieve this.&#xA;Here is a sample code.&lt;/p&gt;&#xA;&lt;p&gt;I have tried the below code on three CIF files which can be found on the Crystallography Open Database here:&#xA;&lt;a href=&quot;http://www.crystallography.net/cod/1000017.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1000017&lt;/a&gt;,&#xA;&lt;a href=&quot;http://www.crystallography.net/cod/1000003.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1000003&lt;/a&gt;,&#xA;&lt;a href=&quot;http://www.crystallography.net/cod/1569089.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1569089&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.geometry.analysis import Analysis&#xA;import numpy as np&#xA;import os&#xA;from ase.io import read, write&#xA;&#xA;# Path to the directory containing CIF files&#xA;cif_directory = &amp;quot;path/to/your/cif/files&amp;quot;&#xA;&#xA;# Path to the directory where you want to save the unit cell CIF files&#xA;output_directory = &amp;quot;path/to/output/directory&amp;quot;&#xA;&#xA;&#xA;def find_unit_cell(supercell):&#xA;    # Calculate the inverse of the lattice transformation matrix&#xA;    inv_lattice = np.linalg.inv(supercell.cell.T)&#xA;    &#xA;    # Calculate the fractional positions in the supercell&#xA;    fractional_positions = np.dot(supercell.positions, inv_lattice)&#xA;    &#xA;    # Find unique fractional positions to determine unit cell&#xA;    unique_fractional_positions, indices = np.unique(fractional_positions, axis=0, return_index=True)&#xA;    &#xA;    # Create the unit cell by selecting atoms at unique fractional positions&#xA;    unit_cell = supercell[indices]&#xA;    &#xA;    return unit_cell&#xA;&#xA;# Loop through all CIF files in the directory&#xA;for cif_filename in os.listdir(cif_directory):&#xA;    print(cif_filename)&#xA;    if cif_filename.endswith(&amp;quot;.cif&amp;quot;):&#xA;        cif_path = os.path.join(cif_directory, cif_filename)&#xA;        supercell = read(cif_path)&#xA;        &#xA;&#xA;        # Convert supercell to unit cell&#xA;        unit_cell = find_unit_cell(supercell)&#xA;        &#xA;        # Save the unit cell CIF&#xA;        output_path = os.path.join(output_directory, cif_filename)&#xA;        write(output_path, unit_cell, format=&amp;quot;cif&amp;quot;)&#xA;        &#xA;        print(f&amp;quot;Converted {cif_filename} to unit cell and saved to {output_path}&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-29T09:39:16.837" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11552" PostTypeId="2" ParentId="11311" CreationDate="2023-08-29T10:44:35.353" Score="1" Body="&lt;h1&gt;Changing band color in plain mode&lt;/h1&gt;&#xA;&lt;p&gt;Can be achieved by setting the &lt;code&gt;color&lt;/code&gt; argument in the &lt;code&gt;bandsplot&lt;/code&gt; function&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyprocar&#xA;data_dir = pyprocar.download_example(save_dir='',&#xA;                             material='Fe',&#xA;                             code='vasp',&#xA;                             spin_calc_type='non-spin-polarized',&#xA;                             calc_type='bands')&#xA;pyprocar.bandsplot(code='vasp', dirname = data_dir, mode='plain', &#xA;show=True, atoms=[0],spins=[0],fermi=-0.1,color='red')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This produces a plot with red band lines like below&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/griUB.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/griUB.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Changing band color and line width in parametric and scatter mode&lt;/h1&gt;&#xA;&lt;p&gt;The Pyprocar library doesn't directly support changing the color and linewidth of bands in the projection band structure plots in 'parametric' and 'scatter' modes. However, you can still achieve this by modifying the code of the library or by customizing the plots after they have been generated.&lt;/p&gt;&#xA;&lt;p&gt;Below is the related piece of code which you could tweak.&#xA;So the weights for the color and linewidth are calculated as below.&lt;/p&gt;&#xA;&lt;p&gt;So you could modify the parent function: &lt;code&gt;bandsplot&lt;/code&gt; to have two extra arguments &lt;code&gt;width_weights&lt;/code&gt; and &lt;code&gt;color_weights&lt;/code&gt; and could use them instead of the computed ones.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;weights = ebs_plot.ebs.ebs_sum(atoms=atoms, principal_q_numbers=[-1], orbitals=orbitals, spins=spins)&#xA;        if plot_opt['weighted_color']['value']:&#xA;            color_weights = weights&#xA;        else:&#xA;            color_weights = None&#xA;        if plot_opt['weighted_width']['value']:&#xA;            width_weights = weights&#xA;        else:&#xA;            width_weights = None&#xA;        color_mask = projection_mask&#xA;        width_mask = projection_mask&#xA;        if mode == &amp;quot;parametric&amp;quot;:&#xA;            ebs_plot.plot_parameteric(&#xA;                color_weights=color_weights,&#xA;                width_weights=width_weights,&#xA;                color_mask=color_mask,&#xA;                width_mask=width_mask,&#xA;                spins=spins&#xA;                )&#xA;        elif mode == &amp;quot;scatter&amp;quot;:&#xA;            ebs_plot.plot_scatter(&#xA;                color_weights=color_weights,&#xA;                width_weights=width_weights,&#xA;                color_mask=color_mask,&#xA;                width_mask=width_mask,&#xA;                spins=spins)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastEditorUserId="6687" LastEditDate="2023-08-29T11:17:33.567" LastActivityDate="2023-08-29T11:17:33.567" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11553" PostTypeId="1" CreationDate="2023-08-29T11:26:32.813" Score="10" ViewCount="628" Body="&lt;p&gt;I am trying to reproduce the work done in this paper &lt;a href=&quot;https://doi.org/10.1021/acscatal.7b00588&quot; rel=&quot;noreferrer&quot;&gt;https://doi.org/10.1021/acscatal.7b00588&lt;/a&gt;.&#xA;In this direction, I have been successful in optimizing the unit cells of the zeolites. For further steps, I need to extract rings having 6,8,10 members. Is there any tool available that can extract the atomic positions of these rings?&lt;/p&gt;&#xA;&lt;p&gt;I am aware of the MAZE-sim package that is written over ASE, which is capable of extracting and manipulating &amp;quot;sites&amp;quot; but not rings.&lt;/p&gt;&#xA;&lt;p&gt;Could someone suggest some resource (tool or code snippet) that could be used to extract such rings of different sizes from zeolite?&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2023-08-29T17:29:12.400" LastActivityDate="2023-11-16T21:17:39.437" Title="Tool to extract rings from zeolite structures" Tags="|python|atomic-simulation-environment|pymatgen|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11554" PostTypeId="2" ParentId="11553" CreationDate="2023-08-29T11:44:15.990" Score="6" Body="&lt;p&gt;While there might not be a dedicated tool that directly extracts rings of different sizes from zeolite structures, you can achieve this using graph theory and network analysis libraries that can be helpful in identifying rings in crystal structures. You can consider using tools like NetworkX (Python library) or igraph (available for various programming languages) to help analyze the connectivity of atoms in the zeolite structure.&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample code using python library networkX:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import networkx as nx&#xA;&#xA;def find_rings(graph, size):&#xA;    rings = []&#xA;    for node in graph.nodes():&#xA;        for path in nx.all_simple_paths(graph, source=node, cutoff=size):&#xA;            if len(path) == size + 1 and graph.has_edge(path[-1], path[0]):&#xA;                rings.append(path)&#xA;    return rings&#xA;&#xA;# Load your crystal structure and create a graph&#xA;# Replace this with your actual structure loading code&#xA;# Example: Load a CIF file using ASE&#xA;from ase.io import read&#xA;zeolite_structure = read('zeolite.cif')&#xA;&#xA;# Create a graph using NetworkX&#xA;G = nx.Graph()&#xA;for atom in zeolite_structure:&#xA;    G.add_node(atom.index)&#xA;for bond in zeolite_structure.get_bonds():&#xA;    G.add_edge(bond.index[0], bond.index[1])&#xA;&#xA;# Find rings of specific sizes&#xA;ring_size = 6  # Change this to 8 or 10 for different ring sizes&#xA;rings = find_rings(G, ring_size)&#xA;&#xA;print(f&amp;quot;Found {len(rings)} rings of size {ring_size}&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-29T11:44:15.990" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11555" PostTypeId="2" ParentId="11356" CreationDate="2023-08-29T12:19:43.420" Score="3" Body="&lt;p&gt;Since you have a large pool of hypothetical structures in .cif format and the experimental crystal density information is missing, you can still estimate the theoretical density using various methods. Here are a few approaches you could consider:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Empirical Formulas:&lt;/strong&gt; There are empirical formulas available that can estimate the density of a material based on its chemical composition. These formulas take into account the atomic masses and packing efficiency of the atoms in the crystal lattice. Examples include the &amp;quot;Kissinger-Kirkpatrick&amp;quot; formula and the &amp;quot;Carpenter-Parr&amp;quot; formula. These formulas are relatively simple to apply and could be useful for estimating densities when experimental data is unavailable.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Density Functional Theory (DFT) Calculations:&lt;/strong&gt; Performing DFT calculations on your hypothetical structures can provide accurate estimates of their densities. DFT is a quantum mechanical approach that calculates the electronic structure and properties of materials. Many computational chemistry software packages, such as VASP, Quantum Espresso, and Gaussian, can be used for DFT calculations. While this approach is more computationally intensive, it provides accurate results.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Packing Algorithms:&lt;/strong&gt; There are various packing algorithms that can estimate the density of a crystal lattice based on the arrangement of atoms. These algorithms simulate how atoms are packed together in the crystal structure and can provide reasonable density estimates. Examples include the &amp;quot;Z-method&amp;quot; and the &amp;quot;Voronoi tessellation&amp;quot; method. These methods are computationally less intensive compared to DFT calculations.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Machine Learning Models:&lt;/strong&gt; You can train machine learning models to predict the density of materials based on their crystallographic features. These models can learn patterns from a dataset of known densities and corresponding crystal structures. Features might include lattice parameters, atomic positions, coordination numbers, and more. Once trained, these models can predict the density of your hypothetical structures.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;External Databases:&lt;/strong&gt; Some online databases and tools might be able to provide estimated densities for certain crystal structures. The COD (Crystallography Open Database) and Materials Project are examples of databases that provide various crystallographic information, including density, for a wide range of materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Keep in mind that each method has its own advantages and limitations. The choice of method will depend on factors such as computational resources, accuracy requirements, and the available data. If possible, using a combination of methods might provide a more comprehensive estimate of the theoretical density for your large pool of structures.&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample python code that shows the various methods mentioned above:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Import necessary libraries&#xA;from pymatgen.io.cif import CifParser&#xA;from pymatgen.core.structure import Structure&#xA;import numpy as np&#xA;&#xA;# Load the CIF file using pymatgen&#xA;cif_parser = CifParser(&amp;quot;sample_structure.cif&amp;quot;)&#xA;structure = cif_parser.get_structures()[0]  # Assuming there's only one structure in the CIF&#xA;&#xA;# Method 1: Empirical Formulas&#xA;def estimate_density_empirical(structure):&#xA;    # Example empirical formula for estimation&#xA;    empirical_density = 0.1 * len(structure)  # Just a placeholder formula&#xA;    return empirical_density&#xA;&#xA;# Method 2: Density Functional Theory (DFT) Calculations (using a placeholder)&#xA;def calculate_density_dft(structure):&#xA;    # Example DFT calculation for estimation&#xA;    total_mass = np.sum([site.species.weight for site in structure])&#xA;    volume = structure.volume&#xA;    density = total_mass / volume&#xA;    return density&#xA;&#xA;# Method 3: Packing Algorithm (using a simple algorithm)&#xA;def calculate_density_packing(structure):&#xA;    # Example packing algorithm for estimation&#xA;    volume = structure.volume&#xA;    packing_density = len(structure) / volume&#xA;    density = packing_density * sum([site.species.weight for site in structure])&#xA;    return density&#xA;&#xA;# Method 4: Machine Learning Model (using a simple model)&#xA;# Note: You would need a trained model for this approach&#xA;def predict_density_ml(structure):&#xA;    # Example machine learning model prediction&#xA;    # This is a placeholder and you'd need an actual trained model&#xA;    ml_density = 0.05 * len(structure)  # Placeholder prediction&#xA;    return ml_density&#xA;&#xA;# Method 5: External Database Lookup (using Materials Project API)&#xA;# Note: You need an API key to use the Materials Project API&#xA;from pymatgen.ext.matproj import MPRester&#xA;&#xA;def get_density_from_mp(structure):&#xA;    # Replace 'YOUR_API_KEY' with your actual Materials Project API key&#xA;    api_key = 'YOUR_API_KEY'&#xA;    with MPRester(api_key) as mpr:&#xA;        mp_entry = mpr.get_data(structure.composition.reduced_formula)&#xA;        density = mp_entry[0]['density']&#xA;    return density&#xA;&#xA;# Usage&#xA;empirical_density = estimate_density_empirical(structure)&#xA;dft_density = calculate_density_dft(structure)&#xA;packing_density = calculate_density_packing(structure)&#xA;ml_density = predict_density_ml(structure)&#xA;mp_density = get_density_from_mp(structure)&#xA;&#xA;print(&amp;quot;Empirical Density:&amp;quot;, empirical_density)&#xA;print(&amp;quot;DFT Density:&amp;quot;, dft_density)&#xA;print(&amp;quot;Packing Density:&amp;quot;, packing_density)&#xA;print(&amp;quot;Machine Learning Density:&amp;quot;, ml_density)&#xA;print(&amp;quot;Materials Project Density:&amp;quot;, mp_density)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-29T12:19:43.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11556" PostTypeId="2" ParentId="11338" CreationDate="2023-08-29T12:48:40.597" Score="-1" Body="&lt;p&gt;The imaginary part (k) of the complex dielectric function and the wavelength (λ) are typically obtained from experimental measurements or theoretical calculations. You can find k and λ values from research papers, databases, or materials characterization tools relevant to your specific material or system. Keep in mind that accurate data sources and appropriate methods are crucial for reliable results.&lt;/p&gt;&#xA;&lt;p&gt;Here are some databases where you can find dielectric function data, including the imaginary part (k) and wavelength (λ) values:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Palik's Handbook of Optical Constants&lt;/strong&gt;: This handbook is a comprehensive source for optical constants, including the complex dielectric function, for a wide range of materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Optical Constants of Crystalline and Amorphous Semiconductors&lt;/strong&gt;: This database provides optical constants for various semiconductors, including k and λ values.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Ellipsometry Database&lt;/strong&gt;: Some ellipsometry databases offer complex dielectric function data for different materials. The J.A. Woollam Database is an example.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;NIST Material Data Center&lt;/strong&gt;: The National Institute of Standards and Technology (NIST) provides a collection of material properties, including optical constants, for various materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Materials Project&lt;/strong&gt;: While primarily focused on computational materials data, the Materials Project may also provide some optical properties information.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Online Material Databases of Universities and Research Institutes&lt;/strong&gt;: Many universities and research institutes have online databases that provide optical constants for specific materials or classes of materials.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-08-29T12:48:40.597" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11557" PostTypeId="2" ParentId="11553" CreationDate="2023-08-29T15:22:34.443" Score="6" Body="&lt;h1&gt;R.I.N.G.S. code&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://rings-code.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;RINGS code&lt;/a&gt; can generate a number of ring statistics, including the number of rings (with many supported definitions).&#xA;Among its multiple outputs are the list of atom indices of each ring (in &lt;code&gt;rstat/liste-N&lt;/code&gt;).&#xA;It is thoroughly described on &lt;a href=&quot;https://rings-code.sourceforge.net/&quot; rel=&quot;noreferrer&quot;&gt;its website&lt;/a&gt; and in its &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2010.04.023&quot; rel=&quot;noreferrer&quot;&gt;companion article&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want a python wrapper to get some rings statistics from this software, you can check the &lt;a href=&quot;https://github.com/coudertlab/amof&quot; rel=&quot;noreferrer&quot;&gt;python package &lt;code&gt;aMOF&lt;/code&gt;&lt;/a&gt; (disclaimer: I'm the developer).&lt;/p&gt;&#xA;" OwnerUserId="1609" LastActivityDate="2023-08-29T15:22:34.443" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11558" PostTypeId="1" CreationDate="2023-08-30T06:09:10.513" Score="4" ViewCount="275" Body="&lt;p&gt;I am performing SCF calculations using Quantum Espresso for crystalline materials to determine the band gaps and energies. A sample output for one of the crystals is shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    highest occupied, lowest unoccupied level (ev):     9.2589   13.2824&#xA;&#xA;!    total energy              =    -392.86522200 Ry&#xA;     estimated scf accuracy    &amp;lt;       0.00000034 Ry&#xA;&#xA;     The total energy is the sum of the following terms:&#xA;     one-electron contribution =     -87.58728570 Ry&#xA;     hartree contribution      =      68.54396895 Ry&#xA;     xc contribution           =     -87.05600859 Ry&#xA;     ewald contribution        =    -248.69804485 Ry&#xA;     one-center paw contrib.   =     -38.06785182 Ry&#xA;      -&amp;gt; PAW hartree energy AE =       0.00000000 Ry&#xA;      -&amp;gt; PAW hartree energy PS =       0.00000000 Ry&#xA;      -&amp;gt; PAW xc energy AE      =       0.00000000 Ry&#xA;      -&amp;gt; PAW xc energy PS      =       0.00000000 Ry&#xA;      -&amp;gt; total E_H with PAW    =      68.54396895 Ry&#xA;      -&amp;gt; total E_XC with PAW   =     -87.05600859 Ry&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I would like to know if the total energy here is an absolute or a relative value. Also, does lower total energy always imply more stability, or do I have to divide the energy by the number of atoms to compare the stabilities of different crystals?&lt;/p&gt;&#xA;" OwnerUserId="7742" LastEditorUserId="7742" LastEditDate="2023-08-30T06:21:20.927" LastActivityDate="2023-08-30T06:21:20.927" Title="Interpretation of total energy in SCF calculation using Quantum Espresso" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|bandgap|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-19T17:20:46.537" ContentLicense="CC BY-SA 4.0" />
  <row Id="11559" PostTypeId="2" ParentId="11543" CreationDate="2023-08-30T16:15:30.593" Score="4" Body="&lt;p&gt;GitHub has added support for CITATION files. Unfortunately, GitHub's support isn't great. It suggests the following BibTeX:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@software{Hanwell_Avogadro,&#xA;author = {Hanwell, Marcus and Hutchison, Geoffrey},&#xA;license = {BSD-3-Clause},&#xA;title = {{Avogadro}},&#xA;url = {https://github.com/openchemistry/avogadrolibs}&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The problem is that anything citing Avogadro should also cite the original Avogadro paper.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@article{Hanwell2012,&#xA;  doi = {10.1186/1758-2946-4-17},&#xA;  url = {https://doi.org/10.1186/1758-2946-4-17},&#xA;  year = {2012},&#xA;  month = aug,&#xA;  publisher = {Springer Science and Business Media {LLC}},&#xA;  volume = {4},&#xA;  number = {1},&#xA;  author = {Marcus D Hanwell and Donald E Curtis and David C Lonie and Tim Vandermeersch and Eva Zurek and Geoffrey R Hutchison},&#xA;  title = {Avogadro: an advanced semantic chemical editor,  visualization,  and analysis platform},&#xA;  journal = {Journal of Cheminformatics}&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for Avo2, work on the CML support:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;@article{deJong2013,&#xA;  doi = {10.1186/1758-2946-5-25},&#xA;  url = {https://doi.org/10.1186/1758-2946-5-25},&#xA;  year = {2013},&#xA;  month = may,&#xA;  publisher = {Springer Science and Business Media {LLC}},&#xA;  volume = {5},&#xA;  number = {1},&#xA;  author = {Wibe A de Jong and Andrew M Walker and Marcus D Hanwell},&#xA;  title = {From data to analysis: linking {NWChem} and Avogadro with the syntax and semantics of Chemical Markup Language},&#xA;  journal = {Journal of Cheminformatics}&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;@NikeDattani's answer does a nice job talking about citing particular builds for software in general.&lt;/p&gt;&#xA;&lt;p&gt;Avogadro creates Zenodo DOI for each release, e.g.&#xA;&lt;a href=&quot;https://doi.org/10.5281/zenodo.6877838&quot; rel=&quot;nofollow noreferrer&quot;&gt;Version 1.97&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And upon the release of Avogadro 2.0, we'll certainly have a paper submission for that, and probably also for Chemical JSON.&lt;/p&gt;&#xA;&lt;p&gt;Suffice to say, I need to write up a few things for the README and website.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-08-30T16:15:30.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11560" PostTypeId="1" CreationDate="2023-08-30T16:36:08.013" Score="5" ViewCount="244" Body="&lt;p&gt;Performing SCF calculations for crystal structures using Quantum Espresso sometimes gives me this error.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine electrons (1):&#xA;     charge is wrong: smearing is needed&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I was able to resolve this by setting the value of the parameter &lt;code&gt;nspin&lt;/code&gt; to &lt;code&gt;2&lt;/code&gt; and specifying the &lt;code&gt;tot_magnetization&lt;/code&gt; value obtained from the Materials Project database. If the crystal is metallic, it works if I set the &lt;code&gt;occupation&lt;/code&gt; to &lt;code&gt;smearing&lt;/code&gt; instead of &lt;code&gt;fixed&lt;/code&gt;. In general, for crystals that are entirely unknown/synthetic and not present in any database, is there a way to determine if they have a spin, total magnetization, net charge and whether they are metallic or not? Will using software like &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt; (or any other tools) help in this regard? Just to clarify, I know the structure and composition of the unknown crystals. It is only the properties mentioned above which are not known.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;p&gt;An example of an input file that gives the above &lt;code&gt;charge is wrong&lt;/code&gt; error when I perform SCF calculation. It's the Li₃(NiO₂)₄ crystal (&lt;a href=&quot;https://next-gen.materialsproject.org/materials/mp-755972?material_ids=mp-755972&quot; rel=&quot;nofollow noreferrer&quot;&gt;mp-755972&lt;/a&gt;). The crystal is metallic in this case, but in general, I am not sure if there is a way to determine the metallicity, charge, and total magnetization&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;   calculation      = 'scf'&#xA;   verbosity        = 'high'&#xA;   nstep            = 1&#xA;   tstress          = .false.&#xA;   tprnfor          = .false.&#xA;   outdir           = 'out'&#xA;   prefix           = 'myprefix'&#xA;   pseudo_dir       = 'SSSP'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;   ntyp             = 3&#xA;   nbnd             = 256&#xA;   ecutwfc          = 30&#xA;   ecutrho          = 240&#xA;   occupations      = 'fixed'&#xA;   degauss          = 0.001&#xA;   smearing         = 'gaussian'&#xA;   nspin            = 1&#xA;   nat              = 15&#xA;   ibrav            = 0&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;   electron_maxstep = 1000&#xA;   mixing_mode      = 'plain'&#xA;   mixing_beta      = 0.7&#xA;   diagonalization  = 'david'&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Li 6.94 li_pbe_v1.4.uspp.F.UPF&#xA;Ni 58.6934 ni_pbe_v1.4.uspp.F.UPF&#xA;O 15.999 O.pbe-n-kjpaw_psl.0.1.UPF&#xA;&#xA;K_POINTS automatic&#xA;3 3 3  0 0 0&#xA;&#xA;CELL_PARAMETERS angstrom&#xA;5.61196941000000 0.00000000000000 0.00000000000000&#xA;-2.80568521479842 5.09575857245564 0.00000000000000&#xA;0.00017151044003 -3.27389010244342 4.79031051982104&#xA;&#xA;ATOMIC_POSITIONS angstrom&#xA;Li -1.4027568522 0.9109342350 2.3951552599 &#xA;Li 0.0000857552 -1.6369450512 2.3951552599 &#xA;Li 2.8060704602 -1.6369450512 2.3951552599 &#xA;Ni 0.0001687046 -3.2738817328 4.7903057295 &#xA;Ni 2.8061534096 -3.2738817328 4.7903057295 &#xA;Ni 4.2091268020 2.5478690947 0.0000000000 &#xA;Ni 1.4031477097 2.5478760123 0.0000047903 &#xA;O -1.4025356006 2.5206534950 3.7297501417 &#xA;O 4.2089913062 -0.6987850249 1.0605603782 &#xA;O 4.2089946010 -2.3279785879 3.8047616141 &#xA;O -1.4025332834 4.1498470579 0.9855489057 &#xA;O -0.0249960414 -0.0151120810 3.7377787021 &#xA;O -0.0250827853 1.8368680471 1.0524503824 &#xA;O 2.8315328789 -0.0149995771 3.7378601374 &#xA;O 2.8314517468 1.8369838249 1.0525270274 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7742" LastEditorUserId="7742" LastEditDate="2023-08-31T21:33:11.653" LastActivityDate="2024-01-21T10:18:31.773" Title="SCF calculations for new materials with unknown properties (e.g. charge, spin, magnetization) using Quantum Espresso" Tags="|density-functional-theory|quantum-espresso|self-consistent-field|uspex|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="11562" PostTypeId="1" AcceptedAnswerId="11566" CreationDate="2023-08-31T15:01:36.160" Score="3" ViewCount="205" Body="&lt;p&gt;I am trying to compare the Molecular Orbital coefficients obtained from PySCF and G09 program. Below is the PySCF and Gaussian input and output. I am using 3-21G basis and RHF method for both the packages and the reference system in H3O+.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;PySCF input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf, lib, cc, ao2mo, grad&#xA;from pyscf.gto import mole&#xA;mol = gto.M(&#xA;    verbose = 5,&#xA;    atom = [&#xA;           ['O' ,  0.074642 , -0.000000 , -0.026389],&#xA;           ['H' , -0.103145 ,  0.000000 ,  0.930145],&#xA;           ['H' ,  0.991917 ,  0.000000 , -0.350692],&#xA;           ['H' , -0.664854 , -0.000000 , -0.658618]],&#xA;    basis = '3-21g',charge=1,&#xA;cart=False&#xA;)&#xA;mf = scf.RHF(mol)&#xA;mf.conv_tol = 1e-13&#xA;mf.scf()&#xA;orbshape = mf.mo_coeff.shape&#xA;print('Orbital shape =',orbshape)&#xA;print(&amp;quot;orbshape[1] is &amp;quot;, orbshape[1])&#xA;print(mf.mo_coeff)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;PySCF output&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[ 9.83242599e-01 -2.36723812e-01 -3.60485158e-07  8.26285631e-08&#xA;   8.54201732e-18 -1.39400918e-01 -3.24924379e-07  4.27735532e-08&#xA;   7.40926127e-02 -5.10470621e-07 -2.15882620e-06  2.41476409e-18&#xA;  -5.78614062e-08  4.15554215e-07  7.81241453e-02]&#xA; [ 9.72257975e-02  2.28321145e-01  4.37984919e-07 -3.38123813e-08&#xA;  -2.72406337e-18  7.77816722e-02  1.49262797e-07 -1.03367613e-07&#xA;  -9.97915817e-02  4.31272063e-07  3.64044620e-06 -1.81972141e-17&#xA;   9.28534624e-09 -1.68937209e-06 -1.68161970e+00]&#xA; [-4.06623548e-02  7.36791646e-01  1.20392671e-06 -4.40830696e-07&#xA;  -5.31833825e-17  1.19408932e+00  3.50538923e-06  3.57091405e-07&#xA;  -6.69223322e-02  1.87873763e-06  1.99627276e-06  5.34167834e-17&#xA;   9.67059530e-07  2.32807183e-07  2.12095150e+00]&#xA; [-1.36625076e-08 -3.18711971e-07  3.99875966e-01  1.75087384e-01&#xA;  -3.30919448e-16 -7.74299361e-07  1.65945660e-01 -2.49317047e-01&#xA;  -2.19084201e-06  7.50629546e-02 -1.99510623e-01  2.45189479e-16&#xA;  -3.12498671e-01 -1.00820556e+00  1.30919633e-06]&#xA; [-2.20533621e-19  3.39181393e-18  3.32245076e-16  1.82208797e-16&#xA;   5.40820245e-01 -3.76638923e-17  2.52529300e-16  1.79190184e-16&#xA;  -3.58911407e-17 -1.86188339e-16  1.35022115e-16  1.01914696e+00&#xA;   6.37674753e-16  1.87552354e-16 -6.72338619e-18]&#xA; [ 7.93352318e-09  3.52701876e-07 -1.75087393e-01  3.99876259e-01&#xA;  -1.46708126e-16 -4.71067753e-07  2.49317102e-01  1.65945561e-01&#xA;   2.10332685e-06  1.99503984e-01  7.50645771e-02  5.06756184e-16&#xA;  -1.00820614e+00  3.12498538e-01 -5.27814777e-07]&#xA; [ 3.76724626e-08 -6.16668075e-07  4.07396435e-01  1.78380348e-01&#xA;  -2.65677104e-16 -1.38897953e-06  4.13014501e-01 -6.20514822e-01&#xA;  -9.57009076e-06  1.42830049e-01 -3.79622369e-01 -6.66840066e-16&#xA;   4.50878967e-01  1.45466938e+00 -3.93668672e-06]&#xA; [ 9.64452306e-20  2.60830063e-19  4.13936439e-16  3.10077044e-16&#xA;   6.13588538e-01  6.65585084e-17 -1.99735894e-16 -4.35853887e-18&#xA;   7.78516109e-17  1.63777798e-16 -1.20469219e-16 -9.77065075e-01&#xA;  -5.86277720e-16 -1.23433162e-16  8.04573985e-18]&#xA; [-2.39107820e-08  3.52553118e-07 -1.78380081e-01  4.07396534e-01&#xA;   5.72917657e-17 -1.06848036e-06  6.20513531e-01  4.13014793e-01&#xA;   4.28154714e-06  3.79622597e-01  1.42832608e-01 -6.40250772e-16&#xA;   1.45466023e+00 -4.50882758e-01  2.22748138e-06]&#xA; [ 1.94248591e-03  9.23862276e-02 -1.28310475e-01  1.88977923e-01&#xA;   2.14775999e-16 -1.06720854e-01 -8.55193536e-02 -8.30944140e-02&#xA;   7.70539129e-01 -9.78680219e-01 -5.91504375e-01 -1.39238447e-16&#xA;  -2.47188467e-01  1.30059848e-01 -1.98379128e-01]&#xA; [ 5.62456945e-03 -3.46785210e-04 -5.32958663e-02  7.84956157e-02&#xA;  -4.08253441e-17 -6.24400751e-01 -9.02544457e-01 -8.76971492e-01&#xA;  -4.28270887e-01  6.91196805e-01  4.17745391e-01  3.12184911e-16&#xA;  -5.00615506e-01  2.63385072e-01 -2.95165370e-01]&#xA; [ 1.94245572e-03  9.23861587e-02  2.27814518e-01  1.66309493e-02&#xA;  -1.58478620e-16 -1.06722252e-01 -2.92034169e-02  1.15608088e-01&#xA;   7.70589446e-01 -2.29052135e-02  1.14327999e+00  2.02266614e-17&#xA;   1.09655908e-02 -2.79105624e-01 -1.98375611e-01]&#xA; [ 5.62457575e-03 -3.46710029e-04  9.46264238e-02  6.90793578e-03&#xA;  -4.73459356e-17 -6.24403880e-01 -3.08207951e-01  1.22010974e+00&#xA;  -4.28309655e-01  1.61763449e-02 -8.07445431e-01  4.90902219e-16&#xA;   2.22085951e-02 -5.65236938e-01 -2.95165494e-01]&#xA; [ 1.94248603e-03  9.23858781e-02 -9.95045334e-02 -2.05608780e-01&#xA;   1.65099861e-17 -1.06721571e-01  1.14722404e-01 -3.25123755e-02&#xA;   7.70550564e-01  1.00157189e+00 -5.51838435e-01  2.93965220e-16&#xA;   2.36222936e-01  1.49054040e-01 -1.98378874e-01]&#xA; [ 5.62454904e-03 -3.46679780e-04 -4.13309319e-02 -8.54038412e-02&#xA;   1.17144303e-16 -6.24404361e-01  1.21074784e+00 -3.43140290e-01&#xA;  -4.28281297e-01 -7.07367252e-01  3.89732419e-01 -9.90418101e-16&#xA;   4.78406006e-01  3.01849336e-01 -2.95164069e-01]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Gaussian input&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# rhf/3-21g nosymm output=wfx pop=full&#xA;&#xA;H3O+ run by HF/3-21G&#xA;&#xA;1 1&#xA;O    0.074642   -0.000000   -0.026389&#xA;H   -0.103145    0.000000    0.930145&#xA;H    0.991917    0.000000   -0.350692&#xA;H   -0.664854   -0.000000   -0.658618&#xA;&#xA;h3o+_hf.wfx&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Gaussian output (only showing the Molecular orbital coefficients part)&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Molecular Orbital Coefficients:&#xA;                           1         2         3         4         5&#xA;                           O         O         O         O         O&#xA;     Eigenvalues --   -19.47020  -1.43467  -0.94637  -0.94637  -0.70968&#xA;   1 1   O  1S          0.98228  -0.23712   0.00000   0.00000   0.00000&#xA;   2        2S          0.10399   0.23148   0.00000   0.00000   0.00000&#xA;   3        2PX         0.00000   0.00000   0.40572   0.19088   0.00000&#xA;   4        2PY         0.00000   0.00000   0.00000   0.00000   0.54999&#xA;   5        2PZ         0.00000   0.00000  -0.19088   0.40572   0.00000&#xA;   6        3S         -0.04546   0.72117   0.00000   0.00000   0.00000&#xA;   7        3PX         0.00000   0.00000   0.37306   0.17551   0.00000&#xA;   8        3PY         0.00000   0.00000   0.00000   0.00000   0.60475&#xA;   9        3PZ         0.00000   0.00000  -0.17551   0.37306   0.00000&#xA;  10 2   H  1S          0.00202   0.09741  -0.13924   0.19360   0.00000&#xA;  11        2S          0.00620   0.00349  -0.06611   0.09192   0.00000&#xA;  12 3   H  1S          0.00202   0.09741   0.23729   0.02379   0.00000&#xA;  13        2S          0.00620   0.00349   0.11266   0.01129   0.00000&#xA;  14 4   H  1S          0.00202   0.09741  -0.09804  -0.21739   0.00000&#xA;  15        2S          0.00620   0.00349  -0.04655  -0.10321   0.00000&#xA;                           6         7         8         9        10&#xA;                           V         V         V         V         V&#xA;     Eigenvalues --    -0.24515  -0.13370  -0.13369   0.56303   0.63870&#xA;   1 1   O  1S         -0.14814   0.00000   0.00000   0.06752   0.00000&#xA;   2        2S          0.10957   0.00000   0.00000  -0.09812   0.00000&#xA;   3        2PX         0.00000  -0.09436  -0.35381   0.00000  -0.06009&#xA;   4        2PY         0.00000   0.00000   0.00000   0.00000   0.00000&#xA;   5        2PZ         0.00000  -0.35381   0.09436   0.00000  -0.22535&#xA;   6        3S          1.17146   0.00000  -0.00001   0.00409   0.00000&#xA;   7        3PX         0.00000  -0.18278  -0.68534   0.00000  -0.07354&#xA;   8        3PY         0.00000   0.00000   0.00000   0.00000   0.00000&#xA;   9        3PZ         0.00000  -0.68534   0.18278   0.00000  -0.27579&#xA;  10 2   H  1S         -0.14877   0.17199  -0.08189   0.76216   1.00935&#xA;  11        2S         -0.59347   1.05279  -0.50130  -0.46513  -0.83550&#xA;  12 3   H  1S         -0.14878  -0.01507   0.18990   0.76218  -0.08848&#xA;  13        2S         -0.59345  -0.09225   1.16239  -0.46515   0.07324&#xA;  14 4   H  1S         -0.14878  -0.15692  -0.10800   0.76216  -0.92087&#xA;  15        2S         -0.59346  -0.96054  -0.66108  -0.46513   0.76226&#xA;                          11        12        13        14        15&#xA;                           V         V         V         V         V&#xA;     Eigenvalues --     0.63871   1.00729   1.24182   1.24182   2.41635&#xA;   1 1   O  1S          0.00000   0.00000   0.00000   0.00000   0.07889&#xA;   2        2S          0.00000   0.00000   0.00000   0.00000  -1.67911&#xA;   3        2PX        -0.22535   0.00000  -0.24259  -0.99572   0.00000&#xA;   4        2PY         0.00000   1.01423   0.00000   0.00000   0.00000&#xA;   5        2PZ         0.06010   0.00000  -0.99572   0.24259   0.00000&#xA;   6        3S          0.00000   0.00000   0.00000   0.00000   2.13981&#xA;   7        3PX        -0.27578   0.00000   0.37297   1.53089   0.00000&#xA;   8        3PY         0.00000  -0.98256   0.00000   0.00000   0.00000&#xA;   9        3PZ         0.07355   0.00000   1.53088  -0.37298   0.00000&#xA;  10 2   H  1S         -0.48059   0.00000  -0.30132   0.13556  -0.20131&#xA;  11        2S          0.39781   0.00000  -0.52871   0.23785  -0.30309&#xA;  12 3   H  1S          1.11440   0.00000   0.03327  -0.32874  -0.20130&#xA;  13        2S         -0.92246   0.00000   0.05837  -0.57680  -0.30309&#xA;  14 4   H  1S         -0.63384   0.00000   0.26805   0.19319  -0.20131&#xA;  15        2S          0.52467   0.00000   0.47034   0.33895  -0.30309&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I compared the output for both packages and found that, Gaussian prints the output as atom numbers followed by orbitals as in aufbau principle (probably, not tested for higher order atoms though). So, we obtain O (1S,2S,2P,3S,3P) H(1S,2S) and so on. Whereas PySCF builds them as atom numbers -&amp;gt; 1S,2S,3S etc. Then comes the P orbitals. Such that, O(1S,2S,3S,2P,3P) and then comes H(1S,2S). Right?&#xA;Is there any generic rule for the different conventions (of different QM packages) to print MO coefficients?&lt;/p&gt;&#xA;&lt;p&gt;Actually, I want to load the Molecular Orbitals from Gaussian calculation and reformat them in PySCF format. I want to do that to bypass costly PySCF calculations (I have asked &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11506/how-can-i-calculate-the-1-particle-and-2-particle-density-matrix-from-hf-and-ccs&quot;&gt;this&lt;/a&gt; question on this previously).&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="2194" LastEditDate="2023-08-31T15:54:30.257" LastActivityDate="2023-09-01T08:21:13.477" Title="Comparison between the ordering of Molecular Orbital coefficients between Gaussian and PySCF" Tags="|quantum-chemistry|gaussian|software-assistance|pyscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11563" PostTypeId="1" CreationDate="2023-08-31T16:16:47.920" Score="2" ViewCount="93" Body="&lt;p&gt;Imagine a simple model of a crystal where every atom in the crystal is the same, and the potential energy of the pairwise interaction between atoms is some radial function of distance, U = U(r).  For example this could be the &lt;a href=&quot;https://en.wikipedia.org/wiki/Lennard-Jones_potential#Properties_of_the_Lennard-Jones_solid&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lennard-Jones solid&lt;/a&gt; with hcp packing, U(r) = A/r^12 + B/r^6&lt;/p&gt;&#xA;&lt;p&gt;By calculating the potential energy for different unit cell sizes, we can get the potential energy vs unit cell size curve: this is essentially a volume vs pressure curve at 0K temperature. We can in principle invert this calculation to get the pairwise potential U(r) from the volume vs pressure curve (I believe the inverse problem has a unique solution, although I can't prove that yet).&lt;/p&gt;&#xA;&lt;p&gt;Now, suppose the same solid is simulated at non-zero temperatures.  The equilibrium unit cell size at zero pressure will be larger due to thermal expansion; and also at any cell size the average potential energy will be different from the potential energy at 0K.  We can calculate the pressure using the &lt;a href=&quot;https://en.wikipedia.org/wiki/Virial_stress&quot; rel=&quot;nofollow noreferrer&quot;&gt;virial&lt;/a&gt;, and again get a volume versus pressure curve.  Inverting this in the same way gives a &lt;a href=&quot;https://en.wikipedia.org/wiki/Potential_of_mean_force&quot; rel=&quot;nofollow noreferrer&quot;&gt;potential of mean force&lt;/a&gt; E(r; T) for the pairwise interaction between particles where r is now the mean distance and E is a free energy rather than potential energy.&lt;/p&gt;&#xA;&lt;p&gt;The question is: how can E(r; T) be calculated from U(r)?  If possible, I'm interested in an analytical derivation for simple potentials like Lennard-Jones, but also in methods for getting this from a single trajectory, without running a whole lot of simulations at different unit cell sizes and temperatures.&lt;/p&gt;&#xA;&lt;p&gt;Basically the nature of the problem is this: we know the pairwise potential energy - how do we get the probability distribution of coordinates at nonzero temperatures (in a periodic solid), and how do we get a pairwise free energy?&lt;/p&gt;&#xA;&lt;p&gt;P.S. This is related to the &amp;quot;&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/acs.jpcb.6b06457&quot; rel=&quot;nofollow noreferrer&quot;&gt;Boltzmann inversion method&lt;/a&gt;&amp;quot; used in designing coarse-grained forcefields from atomistic simulations, but is not the same: in Boltzmann inversion the goal is to match the radial density function, here the goal is to match the free energy vs volume curve.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="5" LastEditDate="2023-09-17T13:17:17.760" LastActivityDate="2023-09-17T13:17:17.760" Title="Potential of mean force from potential energy" Tags="|interatomic-potentials|free-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11564" PostTypeId="2" ParentId="11536" CreationDate="2023-08-31T16:45:52.640" Score="3" Body="&lt;p&gt;I have used CASTEP a lot, through the Materials Studio suite though. Initially, I was doing everything manually, but as you mentioned, it is a very tedious task. I ended up writing my own codes to extract the information I needed. Let me give you an example of one I have used to extract the final energy and some other info. I used R. It is for sure not the most efficient nor the most elegant way to do it, but it is a start. In addition, you can check this &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/abs/10.1002/admi.202370038&quot; rel=&quot;nofollow noreferrer&quot;&gt;publication&lt;/a&gt;. All the numerical analysis was done using a simple R code.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#This script imports and reads CASTEP files within a directory for extracting the lattice parameters, final volume, final enthalpy, functional used, and whether long-range dispersion correction was used for the calculations or not.&#xA;&#xA;# the program exports the data into a excel (.xlsx) file. Name is provided by the user. Default location for exporting the file is in the same working directory of the R script&#xA; &#xA;#&#xA;# setting location of the working directory (for the R script)&#xA;#&#xA;setwd(&amp;quot;C:\\Users\\...\\script\\&amp;quot;)&#xA;&#xA;# loading libraries&#xA;&#xA;library(readr)&#xA;library(pracma)&#xA;library(openxlsx) # for writing in excel format&#xA;&#xA;# getting CASTEP files into a list&#xA;&#xA;print(&amp;quot;Introduce the complete route of castep files:&amp;quot;)&#xA;print(&amp;quot;Path must be in the format accepted in R, like 'C:\\Users\\ ...' or 'C:/Users/...' &amp;quot;)&#xA;castep_files_list &amp;lt;- list.files(readline(),all.files = FALSE,full.names = TRUE)&#xA;&#xA;# creating the data structure to store the values that will be extracted&#xA;castep_data &amp;lt;- data.frame(&#xA;  Functional = c(&amp;quot;&amp;quot;),&#xA;  DFTD = c(&amp;quot;On/Off&amp;quot;),&#xA;  Volume = c(&amp;quot;cubic angstrom&amp;quot;),&#xA;  Enthalphy = c(&amp;quot;eV&amp;quot;),&#xA;  a = c(&amp;quot;angstrom&amp;quot;),&#xA;  b = c(&amp;quot;&amp;quot;),&#xA;  c = c(&amp;quot; &amp;quot;),&#xA;  alpha = c(&amp;quot; &amp;quot;),&#xA;  beta = c(&amp;quot; &amp;quot;),&#xA;  gamma = c(&amp;quot; &amp;quot;)&#xA;  &#xA;  )&#xA;&#xA;# we have to iterate through each element of the list to read the file&#xA;# main 'for' loop&#xA;for(i in 1:length(castep_files_list)){&#xA;  # castep_files[i]&#xA;  # storing the file 'castep_files[i]' in &amp;quot;filetxt' variable&#xA;  castep_file &amp;lt;- read.delim(file = castep_files_list[i], header = FALSE, sep = &amp;quot;\n&amp;quot;, quote=&amp;quot;&amp;quot;)&#xA;  &#xA;  # getting the type of functional used&#xA;  for (j in 1:length(row(castep_file))) {&#xA;    if(grepl(&amp;quot;using functional&amp;quot;, castep_file[j,]))&#xA;      functional &amp;lt;- castep_file[j,]&#xA;      #print()&#xA;  }&#xA;  &#xA;  # checking if a long-range dispersion correction was used&#xA;  for (j in 1:length(row(castep_file))) {&#xA;    if(grepl(&amp;quot;dispersion correction&amp;quot;, castep_file[j,]))&#xA;      dftd_correction &amp;lt;- castep_file[j,]&#xA;    #print()dftd_correction&#xA;  }&#xA;  &#xA;  # # extracting the final volume of the structure&#xA;  # for (j in 1:length(row(castep_file))) {&#xA;  #   if(grepl(&amp;quot;Current cell volume&amp;quot;, castep_file[j,]))&#xA;  #      castep_file[j,]&#xA;  #     cell_volume &amp;lt;- castep_file[j,]&#xA;  #     # castep_file[j,]&#xA;  #   # &amp;quot;cell_volume not found&amp;quot; bug. check why the initial values is requiered&#xA;&#xA;      # extracting the value of the final volume after geometry optimization in numeric format, without string or other characters&#xA;      # unit_cell_volume &amp;lt;- as.numeric(unlist(regmatches(cell_volume,gregexpr(&amp;quot;(?&amp;gt;-)*[[:digit:]]+\\.*[[:digit:]]*&amp;quot;,cell_volume, perl=TRUE))))&#xA;      # unit_cell_volume &amp;lt;- unit_cell_volume[1]&#xA;  #}&#xA;  &#xA;  # getting the final lattice constants of the structure (a,b &amp;amp; c)&#xA;  # Lattice parameters(A) and cell angles&#xA;  for (j in 1:length(row(castep_file))) {&#xA;    if(grepl(&amp;quot;Final Configuration&amp;quot;, castep_file[j,])){&#xA;      values_a &amp;lt;- as.numeric(unlist(regmatches(castep_file[j+12,],gregexpr(&amp;quot;(?&amp;gt;-)*[[:digit:]]+\\.*[[:digit:]]*&amp;quot;,castep_file[j+12,], perl=TRUE))))&#xA;      values_b &amp;lt;- as.numeric(unlist(regmatches(castep_file[j+13,],gregexpr(&amp;quot;(?&amp;gt;-)*[[:digit:]]+\\.*[[:digit:]]*&amp;quot;,castep_file[j+13,], perl=TRUE))))&#xA;      values_c &amp;lt;- as.numeric(unlist(regmatches(castep_file[j+14,],gregexpr(&amp;quot;(?&amp;gt;-)*[[:digit:]]+\\.*[[:digit:]]*&amp;quot;,castep_file[j+14,], perl=TRUE))))&#xA;    }&#xA;  } &#xA;  # getting the value of the final enthalpy (as a string)&#xA;  for (j in 1:length(row(castep_file))) {&#xA;    # condition specifically design to read CASTEP files with the exact string&#xA;    if (grepl(&amp;quot;Final Enthalpy&amp;quot;, castep_file[j,])){&#xA;      energy &amp;lt;- castep_file[j,]&#xA;      #extracting the value of the final enthalpy&#xA;      enthalpy_value &amp;lt;- as.numeric(unlist(regmatches(energy,gregexpr(&amp;quot;(?&amp;gt;-)*[[:digit:]]+\\.*[[:digit:]]*&amp;quot;,energy, perl=TRUE))))&#xA;    }}&#xA;  &#xA;  final_enthalpy_value &amp;lt;- enthalpy_value[1]*10^enthalpy_value[2]&#xA;  # in units of eV&#xA;  &#xA;  # calculating the volume of the unit cell&#xA;  unit_cell_volume &amp;lt;- values_a[1]*values_b[1]*values_c[1]&#xA;  # storing the newly extracted values into one temporarily data frame&#xA;  # columns name must be the same, adding the values as lists of one element&#xA;  temp_data &amp;lt;- data.frame(Functional = c(functional),&#xA;                          DFTD = c(dftd_correction),&#xA;                          Volume = c(unit_cell_volume),&#xA;                          Enthalphy = c(final_enthalpy_value),&#xA;                          a = c(values_a[1]),&#xA;                          b = c(values_b[1]),&#xA;                          c = c(values_c[1]),&#xA;                          alpha = c(values_a[2]),&#xA;                          beta = c(values_b[2]),&#xA;                          gamma = c(values_c[2])&#xA;                          )&#xA;  &#xA;  # adding new values to the previously created data frame&#xA;  castep_data &amp;lt;- rbind(castep_data,temp_data)&#xA;  &#xA;}&#xA;&#xA;# exporting the data frame to an excel (.xlsx) file&#xA;# requesting the name of the file to the user&#xA;print(&amp;quot;Insert name of file (e.g., /file_name.xlsx)&amp;quot;)&#xA;name &amp;lt;- readline() #inserting the name of the file in the specified format&#xA;write.xlsx(castep_data, name) #writing the data in a .xlsx file&#xA;print(&amp;quot;file exported successfully :)&amp;quot;)&#xA;print(&amp;quot;file located in:&amp;quot;)&#xA;print(getwd())&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7695" LastActivityDate="2023-08-31T16:45:52.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11565" PostTypeId="1" CreationDate="2023-08-31T18:47:36.760" Score="1" ViewCount="51" Body="&lt;p&gt;I have a graphene system (94 atoms - defective graphene) I was able to converge both right and left electrode runs in just 8 iterations. But the scattering run (transiesta) is not converging even after 10,000 iterations. Can anyone suggest what can be done....&lt;/p&gt;&#xA;&lt;p&gt;Here are the parameters I use for my transiesta run:&lt;/p&gt;&#xA;&lt;h1&gt;General variables&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;MeshCutoff    200.0 Ry&#xA;MaxSCFIterations     100000&#xA;&#xA;DM.MixingWeight       0.05          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.0E-4         # Tolerance in maximum difference&#xA;DM.UseSaveDM          true          # to use continuation files&#xA;DM.NumberPulay         6&#xA;&#xA;PAO.SplitNorm    0.150000&#xA;PAO.EnergyShift    0.005000  Ry&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;MD variables&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;MD.MaxForceTol 0.01 eV/Ang&#xA;MD.TypeOfRun        CG&#xA;MD.VariableCell     false&#xA;MD.NumCGSteps        0&#xA;MD.InitialTimeStep      1&#xA;MD.FinalTimeStep        1&#xA;MD.LengthTimeStep       1 fs&#xA;ElectronicTemperature 300 K&#xA;MD.MaxCGDispl 0.05 Bohr&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7815" LastEditorUserId="5" LastEditDate="2023-12-19T20:15:14.150" LastActivityDate="2023-12-19T20:15:14.150" Title="Transiesta convergence issue" Tags="|siesta|graphene|" AnswerCount="0" CommentCount="1" ClosedDate="2024-03-07T21:14:57.130" ContentLicense="CC BY-SA 4.0" />
  <row Id="11566" PostTypeId="2" ParentId="11562" CreationDate="2023-09-01T08:21:13.477" Score="4" Body="&lt;p&gt;&lt;strong&gt;Answer for basis function conventions:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;What you've concluded is correct, but there are more rules for a general basis set (e.g. def2-TZVP, cc-pVTZ):&lt;/p&gt;&#xA;&lt;p&gt;(1) The order of MO coefficients with angular momentum 5D/7F/9G/11H (and 6D/10F/15G/21H) of basis functions are usually different for different quantum chemistry packages, we need to permute these coefficients.&lt;/p&gt;&#xA;&lt;p&gt;(2) For some MO coefficients, we need to multiply them by a normalized constant like sqrt(2), sqrt(3), etc.&lt;/p&gt;&#xA;&lt;p&gt;(3) Although the basis set name 'cc-pVTZ' are specified in two packages, their primitive Gaussian exponents and contraction coefficients may be not the same. To solve this problem, we need to use exactly the same basis set data in two packages. The best way is to transfer MOs as well as basis set data from one package to another.&lt;/p&gt;&#xA;&lt;p&gt;Conventions of basis functions in various quantum chemistry packages are recorded in the open source package &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOKIT&lt;/a&gt;. For example, conventions of basis functions in PySCF/Gaussian and the related conversion relationship are coded in the file &lt;a href=&quot;https://gitlab.com/jxzou/mokit/-/blob/master/src/fch2py.f90?ref_type=heads&quot; rel=&quot;nofollow noreferrer&quot;&gt;src/fch2py.f90&lt;/a&gt;; its reversed version is coded in the file &lt;a href=&quot;https://gitlab.com/jxzou/mokit/-/blob/master/src/py2fch.f90?ref_type=heads&quot; rel=&quot;nofollow noreferrer&quot;&gt;src/py2fch.f90&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, you can find&lt;br /&gt;&#xA;&lt;code&gt;fch2mkl&lt;/code&gt;/&lt;code&gt;mkl2fch&lt;/code&gt; for Gaussian&amp;lt;-&amp;gt;ORCA;&lt;br /&gt;&#xA;&lt;code&gt;fch2inp&lt;/code&gt;/&lt;code&gt;dat2fch&lt;/code&gt; for Gaussian&amp;lt;-&amp;gt;GAMESS;&lt;br /&gt;&#xA;&lt;code&gt;fch2com&lt;/code&gt;/&lt;code&gt;xml2fch&lt;/code&gt; for Gaussian&amp;lt;-&amp;gt;Molpro;&lt;br /&gt;&#xA;, etc. And &lt;code&gt;py2xxx&lt;/code&gt; modules for &lt;a href=&quot;https://jeanwsr.gitlab.io/mokit-doc-mdbook/chap4-6.html#465-the-py2xxx-modules&quot; rel=&quot;nofollow noreferrer&quot;&gt;PySCF-&amp;gt;other packages&lt;/a&gt;. A lot of quantum chemistry packages are supported. It would be tedious to show all conversions here.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Answer for loading MOs of Gaussian in PySCF:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This can be easily achieved via using MOKIT. Assuming I have a Gaussian .fch(k) file &lt;code&gt;h2o.fch&lt;/code&gt; right now, in which the RHF/cc-pVTZ calculation is performed. Here is a Python script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from mokit.lib.gaussian import load_mol_from_fch, mo_fch2py&#xA;from mokit.lib.py2fch_direct import fchk&#xA;from pyscf import scf, mcscf&#xA;&#xA;# load Cartesian coordinates, basis set data, charge, spin, etc&#xA;fchname = 'h2o.fch'        # converged RHF orbitals&#xA;fchname1 = 'h2o_cas44.fch' # converged CASSCF(4,4) orbitals&#xA;mol = load_mol_from_fch(fchname)&#xA;&#xA;# generate the mf object, make all needed arrays allocated&#xA;mf = scf.RHF(mol)&#xA;mf.init_guess = '1e'&#xA;mf.max_cycle = 1&#xA;mf.verbose = 4&#xA;mf.kernel()&#xA;&#xA;# load MO coefficients (work for RHF/ROHF/UHF-type wfn)&#xA;mf.mo_coeff = mo_fch2py(fchname)&#xA;mf.max_cycle = 10&#xA;dm = mf.make_rdm1() # generate density matrix&#xA;mf.kernel(dm0=dm)&#xA;# here the RHF is converged in 2 cycles with energy change less than 3e-8 a.u.&#xA;&#xA;# if we have converged CASSCF orbitals, we can also perform CASSCF&#xA;mf.mo_coeff = mo_fch2py(fchname1)&#xA;mc = mcscf.CASSCF(mf, 4, 4)&#xA;mc.kernel()&#xA;# here the CASSCF is converged in 1 cycle&#xA;&#xA;# We can also export PySCF MOs to Gaussian .fch file.&#xA;# fchk() will generate a .fch file from scratch.&#xA;mf.mo_coeff = mc.mo_coeff.copy()&#xA;fchk(mf, 'test.fch')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you are working with 1-RDM, you can generate natural orbitals (NOs) using 1-RDM and then transfer NOs among various packages. By the way, the keyword &lt;code&gt;nosymm int=nobasistransform&lt;/code&gt; are recommended to be written in the Gaussian input file for a better transferring of MOs.&lt;/p&gt;&#xA;&lt;p&gt;Hope this will do some help.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2023-09-01T08:21:13.477" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="11567" PostTypeId="2" ParentId="11563" CreationDate="2023-09-01T10:00:25.123" Score="1" Body="&lt;p&gt;Your definition for &amp;quot;a potential of mean force&amp;quot; (or PMF) is not correct. The PMF of a probe from a reference particle is the potential energy change when the probe is moved towards or further from the reference, averaged radially and Boltzmann-averaged over all resulting perturbations of other particles in the ensemble of choice.&lt;/p&gt;&#xA;&lt;p&gt;This is &lt;em&gt;not&lt;/em&gt; the same thing as &lt;em&gt;dilating all particle positions&lt;/em&gt; at once away from the reference particle. As an example, consider the particle-particle PMF of an ideal gas: it does not change with density, but the pressure certainly does.&lt;/p&gt;&#xA;&lt;p&gt;Wikipedia's article for the &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Radial_distribution_function&quot; rel=&quot;nofollow noreferrer&quot;&gt;radial distribution function&lt;/a&gt;, or RDF has many useful equations, including connecting it to the PMF (eq 8) and the pressure equation of state (eq 10).&lt;/p&gt;&#xA;&lt;p&gt;To understand the subsequent quest to derive the RDF from the pair interaction function, historically one starts with understanding the BBGKY hierarchy and subsequently various models for closing it. However, a more modern approach is to study &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ed500049m&quot; rel=&quot;nofollow noreferrer&quot;&gt;classical density functional theory&lt;/a&gt; or cDFT, and ultimately the state of the art is with &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568820/&quot; rel=&quot;nofollow noreferrer&quot;&gt;3D Reference Interaction Site Model&lt;/a&gt; or 3D-RISM theory.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-09-01T10:00:25.123" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11568" PostTypeId="1" CreationDate="2023-09-01T14:38:40.657" Score="4" ViewCount="285" Body="&lt;p&gt;I'm running a PDOS calculation in QE but the file has an output and has an error.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;projwfc&#xA;    prefix='pwscf',&#xA;    outdir='./tmp'&#xA;    filproj='pdoss'&#xA;    deltae  =  1,00000e-02&#xA;    emax    =  5,00000e+01&#xA;    emin    = -5,00000e+01&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Output:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Error in routine do_projwfc (5010):&#xA;     reading projwfc namelist&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="6055" LastEditDate="2023-09-01T15:16:25.640" LastActivityDate="2023-09-01T15:16:25.640" Title="Quantum ESPRESSO &quot;Error in routine do_projwfc (5010): reading projwfc namelist&quot;" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11569" PostTypeId="1" AcceptedAnswerId="11573" CreationDate="2023-09-03T16:19:10.873" Score="4" ViewCount="598" Body="&lt;p&gt;I would like to know some examples too, if you could use them in explaining in the words.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2023-09-04T02:43:28.300" LastActivityDate="2023-09-04T02:43:28.300" Title="What is the difference between computation and simulation?" Tags="|terminology|soft-question|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11570" PostTypeId="1" CreationDate="2023-09-03T17:18:53.183" Score="3" ViewCount="92" Body="&lt;p&gt;Cubic spline interpolation is used in a lot of methods like Nudged Elastic Band (NEB), or String or Growing String Method (GSM) either to reparameterize the path, or to estimate the position of the peak, or to find the path tangent (which is required for the force projection).&lt;/p&gt;&#xA;&lt;p&gt;These splines represent a continuous path through all the images. So it would provide intermediate coordinates and energies for the entire pathway.&lt;/p&gt;&#xA;&lt;p&gt;In most of the papers I have read, the spline interpolation is done with arc-length parameterisation. For example, the simplifiedd string method paper (W. E et al., J. Chem. Phys. 2007, 126, 164103) mentions that the arc lengths are calculated from the current images, and then fitted to a cubic spline. There is also the elastic image method paper (J. Chem. Theory Comput. 2022, 18, 8, 5108–5115) where they mention using a cubic spline on an interpolated path to find the peak, and then using lengths (arc lengths?) to move two images. The growing string paper (J. Chem. Phys. 2004, 120, 7877–7886) also performs cubic interpolation with arc lengths of the path for reparameterisation and growing the string and finding the interpolated (estimated) peak.&lt;/p&gt;&#xA;&lt;p&gt;However, in all of these papers, I haven't found a single description of how the spline fitting and arc length parameterisation is actually performed from a set of Cartesian coordinates. Let's say that I have a series of Cartesian coordinates (&lt;span class=&quot;math-container&quot;&gt;$\vec{x}_A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\vec{x}_B$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\vec{x}_C$&lt;/span&gt;, ...) each with the x, y and z of each atom, and an energy value. &lt;strong&gt;How do I now calculate the arc length to fit the cubic spline, and how do I fit the energies?&lt;/strong&gt; The best I can do is to estimate the Euclidean distances between adjacent points (&lt;span class=&quot;math-container&quot;&gt;$||\vec{x}_A - \vec{x}_B||$&lt;/span&gt;), but that would not be the same as arc length as there is no guarantee that the spline would coincide with the linear path in Euclidean metric (basically norm of the vector subtraction).&lt;/p&gt;&#xA;&lt;p&gt;Once I have the arc-length, it should be possible to fit the cubic spline with scipy's &lt;code&gt;CubicSpline&lt;/code&gt; class, but I am still not sure how to deal with the energies and how to link them with the coordinates.&lt;/p&gt;&#xA;&lt;p&gt;This seems like a such a simple thing that's used in all the methods, but I can't find the actual maths involved in the spline fitting anywhere. Any help with this is appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-09-03T19:39:58.117" LastActivityDate="2023-09-05T08:53:25.197" Title="Cubic spline interpolation through a series of images" Tags="|mathematical-modeling|geometry|nudged-elastic-band|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11571" PostTypeId="1" CreationDate="2023-09-03T21:32:09.437" Score="5" ViewCount="171" Body="&lt;p&gt;For non-covalent systems comprised of small-molecule monomers, folks are usually interested in understanding the interaction and binding energies of small (gas-phase) clusters ... things like &lt;span class=&quot;math-container&quot;&gt;$\ce{X(H2O)_N}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; typically runs from 1-10.&lt;/p&gt;&#xA;&lt;p&gt;For pure water or small molecules in water, I would say the current &amp;quot;benchmark structures&amp;quot; are usually optimized with something like RI-MP2 or DF-MP2. For larger datasets, I would say B3LYP-D3(BJ) is still quite popular, still with &lt;span class=&quot;math-container&quot;&gt;$N\approx$&lt;/span&gt; 10-12.&lt;/p&gt;&#xA;&lt;p&gt;Another approach that is popular, is to perform calculations on structures that were extracted from MD simulations. This makes sense when averaging over many clusters or when &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is large.&lt;/p&gt;&#xA;&lt;p&gt;I'm wondering what you think about something &amp;quot;in between&amp;quot;... like interaction/binding energies using something &amp;quot;high-level&amp;quot; [e.g. DLPNO-CCSD(T)] over 1 set of structures &lt;span class=&quot;math-container&quot;&gt;$\ce{X(H2O)_N}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; = 1 - 20, but were optimized using a semi-empirical method like DFT-3c [e.g. PBEh-3c]&lt;/p&gt;&#xA;&lt;p&gt;In my opinion, this seems like an okay first approximation since the analysis could be refined if needed or complemented by selecting one of the two typical approaches. But on the other hand, since this is somehow in between, should I just pick one of the other approaches?&lt;/p&gt;&#xA;&lt;p&gt;Part of my initial thought is that -3c methods are made to save us time while giving decent structures, so why not? Thoughts?&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2023-09-04T00:45:03.627" LastActivityDate="2023-09-04T01:11:45.270" Title="Is it okay to use semi-empirical methods to optimize structures if I perform high-level energy calculations?" Tags="|density-functional-theory|quantum-chemistry|geometry-optimization|coupled-cluster|intermolecular-forces|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11572" PostTypeId="2" ParentId="11571" CreationDate="2023-09-04T01:11:45.270" Score="5" Body="&lt;p&gt;I generally try to use the most accurate methods that my resources will allow me to use, within a reasonable budget for the desired accuracy.&lt;/p&gt;&#xA;&lt;p&gt;If you're interested in 20 water molecules or 60 atoms (before including your &lt;span class=&quot;math-container&quot;&gt;$\textrm{X}$&lt;/span&gt; atom), then even the cost of DLPNO-CCSD(T) might be quite brutal, so it might as well be done on a decent geometry the first time, so that you don't have to redo the calculation when you later learn that your original geometry was badly flawed.  However, I would certainly not want to use RI-MP2 or DF-MP2 for the geometry optimization for such a large system.&lt;/p&gt;&#xA;&lt;p&gt;This would seem to limit us to the last two options that you mentioned for the geometry optimization: MD and semi-empirical methods. The MD would be quite fast for 60 atoms, so you can obtain the MD structures for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; = 1-20 anyway, with what I think would be negligible cost compared to the DLPNO-CCSD(T) calculations that you're about to do. You could then try optimizing the structures with a semi-empirical method (I would pick one and stick with it, rather than repeating potentially expensive calculations too many times) with N=1,2,3..., checking each time how different the results are compared to the MD calculations. &lt;strong&gt;If the results are mostly unaffected by the optimization method, then there's no need to do heavy calculations all the way up to N=20, since the cheaper calculations are probably just as good and are already available.&lt;/strong&gt; If the results are drastically different, then you have another question to ask: how much more accurate are they? Personally I think that there's already so many more approximations going on than you have even mentioned:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;which basis set are you using?&lt;/li&gt;&#xA;&lt;li&gt;which basis set extrapolation scheme are you using?&lt;/li&gt;&#xA;&lt;li&gt;does the &lt;span class=&quot;math-container&quot;&gt;$\textrm{X}$&lt;/span&gt; atom require a relativistic treatment or does it cause the need for considering multi-reference character that is not amenable to using CCSD(T)?&lt;/li&gt;&#xA;&lt;li&gt;how big is the CCSD(T) error from FCI?&lt;/li&gt;&#xA;&lt;li&gt;how big is the DLPNO-CCSD(T) error from CCSD(T)?&lt;/li&gt;&#xA;&lt;li&gt;how close is the optimized semi-empirical structure from the &lt;em&gt;&lt;strong&gt;real&lt;/strong&gt;&lt;/em&gt; structure or the DLPNO-CCSD(T) structure?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;After considering all of those factors, if you still think a more expensive geometry optimization is worth the computer time and global warming that it causes, and that the delay in publishing the paper is worth it because of a &lt;em&gt;meaningful&lt;/em&gt; gain in accuracy, then by all means do it! If your question is whether or not it's &amp;quot;okay&amp;quot; to do it, I see no reason why it wouldn't be okay! But considering that other errors such as the basis set incompleteness error and the correlation incompleteness error will still be there no matter what, I might just be inclined to stick with the more economical geometry optimization method (although you'll know better about the expected CPU time and value of it once you start doing the actual calculations: maybe I'm worried about nothing and the geometry optimizations will be lightning fast with both options, or maybe you'll see it being prohibitively slow at a small &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; value and your decision will become immediately obvious).&lt;/p&gt;&#xA;&lt;p&gt;You can also just pick a small basis set to test everything (all candidate methods that you're considering) and see how much things matter with the small basis set, where everything is lightning fast (comparatively). This will give you very valuable guidance on what to do for the &amp;quot;real&amp;quot; calculations with the bigger basis sets (if you care about DLPNO-CCSD(T) type accuracy, then you're probably planning to do at least a DZ,TZ-&amp;gt;CBS extrapolation, but you can practice and explore things with things like 6-31G and 3-21G first).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-04T01:11:45.270" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11573" PostTypeId="2" ParentId="11569" CreationDate="2023-09-04T01:32:08.157" Score="4" Body="&lt;p&gt;For the most part, &amp;quot;simulations&amp;quot; are a specific type of &amp;quot;computation&amp;quot;. This agrees with the first lines from the Wikipedia articles for &lt;a href=&quot;https://en.wikipedia.org/wiki/Computation&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;computation&lt;/strong&gt;&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Simulation&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;simulation&lt;/strong&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;A computation is any type of arithmetic or non-arithmetic calculation that is well-defined.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;A simulation is the imitation of the operation of a real-world process or system over time.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You asked for specific examples, so I'll think of specific examples in matter modeling. If I would like to simulate the dynamics of a protein when salt is added to its surrounding aqueous solution, I may enter all atoms of the protein and surrounding water molecules into a computer program, and use &lt;a href=&quot;/questions/tagged/molecular-dynamics&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;molecular-dynamics&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-molecular-dynamics-tooltip-container&quot;&gt;molecular-dynamics&lt;/a&gt; to simulate how the atoms will move when salt is added. Overall, this entire study can be considered a &amp;quot;&lt;strong&gt;simulation&lt;/strong&gt;&amp;quot; but there could be millions of &lt;strong&gt;calculations&lt;/strong&gt; done as part of the simulation process, and since a simulation is a specific type of calculation, the whole simulation can also be called an MD calculation.&lt;/p&gt;&#xA;&lt;p&gt;I'll also go beyond the Wikipedia definition. When it says that a simulation imitates a &amp;quot;real-world process or system over time&amp;quot;, I don't think &lt;em&gt;&lt;strong&gt;needs&lt;/strong&gt;&lt;/em&gt; to be &amp;quot;over time&amp;quot;. You can simulate a static system too. Instead of doing an experiment on a stationary neon atom to find out it's ionization energy, you can simulate it on a computer by entering the number of electrons and protons into an &lt;a href=&quot;/questions/tagged/electronic-structure&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;electronic-structure&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;electronic-structure&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-electronic-structure-tooltip-container&quot;&gt;electronic-structure&lt;/a&gt; program and calculating a numerical solution to the &lt;em&gt;&lt;strong&gt;time-independent&lt;/strong&gt;&lt;/em&gt; Schroedinger equation for the neutral atom and for its cation (the difference in the obtained ground state energies can be considered the ionization energy of our &amp;quot;simulated&amp;quot; atom, even though it remained static the whole time). This simulation, is again a special case of a computation, because we have just computed the solutions to the Schroedinger equation with two different Hamiltonians.&lt;/p&gt;&#xA;&lt;p&gt;Can there be calculations in matter modeling that are not simulations? Yes absolutely! We do calculations all the time (matrix multiplications, root-finding, etc.) that don't need to have any interpretation as a simulation. If we're multiplying a number by &lt;span class=&quot;math-container&quot;&gt;$\hbar$&lt;/span&gt; as a step in a unit conversion, that multiplication is a computation, but are you simulating anything? We can probably find a way to argue that we are, but for the most part it wouldn't be very valuable or important or necessary to think of this as a simulation.&lt;/p&gt;&#xA;&lt;p&gt;Finally, simulations don't have to be computations, which is why my first sentence in this answer starts with &amp;quot;for the most part&amp;quot;. This is sometimes called an &amp;quot;analog simulation&amp;quot;. For example, we might use LEGO to build a structure that closely resembles a certain protein, then we might throw a tennis ball at the structure to see what happens when the protein is bombarded by an extremely high-energy particle. This might not be the most accurate simulation, but it's still a simulation, and it would again not be very valuable or important or necessary to call this a &amp;quot;computation&amp;quot;, even if it's possible to argue that it is one.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-04T01:32:08.157" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11574" PostTypeId="1" CreationDate="2023-09-04T09:36:20.193" Score="4" ViewCount="49" Body="&lt;p&gt;I have a set of molecules that are generated from a regular cyclohexane and have varying amounts of substitutions and double bonds. I need to compute the amount of distortion that each of these changes causes in the molecule. My current method is to calculate the average molecular plane for each molecule and compute the signed z-projected distance of each heavy atom from the molecular plane. Is this a valid way to describe distortion using geometric parameter, or is there any standard tools of descriptors already available for this task?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-09-04T09:36:20.193" Title="How to calculate the distortion of molecule?" Tags="|density-functional-theory|geometry|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11575" PostTypeId="1" AcceptedAnswerId="11586" CreationDate="2023-09-04T12:41:33.247" Score="2" ViewCount="52" Body="&lt;p&gt;During an OO-RI-ωB97X-2-D2 calculation on ORCA, the non-dispersion-corrected OO-DHDF part of the calculation is performed, the D2 dispersion correction energy added to the resulting OO-DHDF energy, and then the properties (including the relaxed MP2 density, and therefore the fully relaxed orbitals) calculated. This means that the fully relaxed orbitals (and their energies) are dependent of the D2 correction iff the relaxed MP2 density depends on the total, OO-DHDF-D2, energy.&lt;/p&gt;&#xA;&lt;p&gt;This was done on a small scale on a model system, namely gas-phase water at the OO-RI-ωB97X-2-D2/aug-pcSseg-2/aug-cc-pwCVQZ(C)/AutoAux(J; ORCA does not support RIJK in OO-RI-MP2) level of theory, the D2 keyword being added separately(ORCA does not support ωB97M(2), which would definitely have &amp;quot;dispersion corrections&amp;quot; in the resulting orbitals in its OO-RI-ωB97M(2) form); the very large molecule I'm actually going to analyse would be likely to have a lot of NCIs and &amp;quot;artificially broken symmetries&amp;quot; in it and hence the OO-RI-ωB97X-2-D4/aug-pcSseg-2/aug-cc-pwCVQZ(C)/AutoAux(J) level of theory would be used(checked the literature; pcSseg-2 already gives at worst chemical accuracy for core-LUMO excitation energies of small molecules at the TD-B97-1 level of theory; no prizes for guessing how small the core-valence correlation errors, mandated as part of OO-RI-MP2 calculations on ORCA, would be, given that B97-1 is actually not good enough for most purposes), the necessary parameters for D4 being taken from those for ωB97X.&lt;/p&gt;&#xA;&lt;p&gt;My main question now follows- would adding D4 to the mix (per my recipe) have meaningful effects on the orbital energies, shapes, the electrostatic potential, NBO populations, and/or other &amp;quot;fully relaxed&amp;quot; properties?&lt;/p&gt;&#xA;" OwnerUserId="4231" LastActivityDate="2023-09-05T15:04:05.043" Title="Does the relaxed density (and therefore the relaxed orbitals) depend on the final energy in OO-DHDF+D calculations?" Tags="|density-functional-theory|molecular-modeling|orbitals|dispersion-correction|many-body-perturbation-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11576" PostTypeId="1" CreationDate="2023-09-04T20:26:38.467" Score="5" ViewCount="369" Body="&lt;p&gt;I have a cell that contains a sphere of organic molecules in a cube of water. What tool and how could I visualize the central cut (slice) of the unit cell? Similar to the one visualized in packmol examples &lt;a href=&quot;https://m3g.github.io/packmol/examples.shtml&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Double layered spherical vesicle with water inside and outside&amp;quot;&lt;/a&gt;. Cannot seem to find the right option in VMD. I use macOS and any other tool recommendations are very much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="184" LastEditorUserId="7" LastEditDate="2023-09-06T00:53:47.453" LastActivityDate="2023-09-06T00:53:47.453" Title="How to visualize a slice of the unit cell?" Tags="|visualization-software|vmd|ovito|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11577" PostTypeId="1" AcceptedAnswerId="11585" CreationDate="2023-09-04T23:38:52.780" Score="3" ViewCount="96" Body="&lt;p&gt;I am doing some high-throughput DFT calculations within Quantum Espresso, and I've noticed that for one system (Germanium-Telluride, in high concentrations of Tellurium) the energy spikes on the first step. I am curious if this behavior is of any concern, or if there is any explanation available!&lt;/p&gt;&#xA;&lt;p&gt;QE input values:&#xA;ecutwfc          = 45,&#xA;ecutrho          = 180,&#xA;occupations      = 'smearing',&#xA;degauss          = 0.005,&#xA;smearing         = 'gaussian',&#xA;kspacing         = ~0.03&lt;/p&gt;&#xA;&lt;p&gt;Pseudos: Te.pbesol-n-kjpaw_psl.1.0.0.UPF, Ge.pbesol-n-kjpaw_psl.1.0.0.UPF&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XdFCD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XdFCD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5433" LastActivityDate="2023-09-10T11:45:52.333" Title="Increase in SCF energy on first step" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11578" PostTypeId="2" ParentId="11576" CreationDate="2023-09-04T23:58:35.603" Score="6" Body="&lt;p&gt;I recently used OVITO for this same visualization. There is an option, &lt;code&gt;Slice&lt;/code&gt;, within the quick command search that is available in the free version. You can use it to select the plane at which you'd like to delete from.&lt;/p&gt;&#xA;&lt;p&gt;If you would like the molecules to still be visible, as in the last packmol example, then after creating the slice open the file again and select &lt;code&gt;Add to scene&lt;/code&gt;. After doing this, use &lt;code&gt;Select type&lt;/code&gt; from the quick command again and select the solvent and delete it with &lt;code&gt;Delete selected&lt;/code&gt;. This should leave you with the sliced box overlayed with the molecules.&lt;/p&gt;&#xA;" OwnerUserId="5433" LastEditorUserId="5433" LastEditDate="2023-09-05T00:29:54.440" LastActivityDate="2023-09-05T00:29:54.440" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11579" PostTypeId="1" CreationDate="2023-09-05T01:03:18.667" Score="5" ViewCount="192" Body="&lt;p&gt;&lt;strong&gt;Motivation for Post&lt;/strong&gt;: I saw a question about how to plot a &lt;code&gt;.cube&lt;/code&gt; file recently on the &lt;em&gt;Mathematica &amp;amp; Wolfram Language&lt;/em&gt; Stack Exchange. It was marked &amp;quot;off-topic,&amp;quot; so I am asking a different (but related) question in the hopes it is on-topic here. Please refer me to the answer if it has already been solved. I have volumetric data I would like to plot in a custom manner (either in Mathematica, but preferably Python). But I have had issues up to this point. I am new to coding, and to Quantum-ESPRESSO (QE) which is how I produced my &lt;code&gt;.cube&lt;/code&gt; file. I am not an expert in anything, merely a student trying to simulate some things.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Goals&lt;/strong&gt;: Either with Python or Mathematica, (1) Generate a 3D plot of my volumetric data.&#xA;(2) Be able to &amp;quot;slice&amp;quot; through that 3D graph with a user-defined plane to view a 2D cross-section.&#xA;I would love to be able to create something inspired by VESTA's ability to do goals (1) and (2), but in a more customizable, flexible way to suit my needs. (I want to customize color mapping especially.)&lt;/p&gt;&#xA;&lt;p&gt;Produced by VESTA:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/cxDa0.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/cxDa0.png&quot; alt=&quot;STMsimScanRepeated&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/bF1Hk.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bF1Hk.png&quot; alt=&quot;sTMsimScanSingle&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Attempts&lt;/strong&gt;: Lots of failed attempts here. I even enlisted the help of a professional programmer who could not discern how the data was meant to be read, plotted, and/or modified.&#xA;In one case, the voxels are not cubic; I would also like to be able to specify the voxel dimensions/spanning vectors. VESTA seems to be able to do this, but I want to do it from scratch so I can map the colors myself for figure-making and whatnot. Here is a failed attempt example. I will not include most here, as I wrote them on another computer.&lt;/p&gt;&#xA;&lt;h2&gt;&lt;a href=&quot;https://i.stack.imgur.com/AQIrz.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AQIrz.jpg&quot; alt=&quot;fail01&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/LIMx6.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/LIMx6.jpg&quot; alt=&quot;fail02&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/wT0U1.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wT0U1.jpg&quot; alt=&quot;fail03&quot; /&gt;&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Knowns:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is how the data is listed: NX = 30, NY= 30, and NZ = 90. The output file has 6 columns (13,500 rows). (See &lt;a href=&quot;https://gaussian.com/cubegen/&quot; rel=&quot;noreferrer&quot;&gt;https://gaussian.com/cubegen/&lt;/a&gt;) And each element corresponds to a 3D pixel (a voxel) and this volumetric data can be plotted in 3D. Then, I eventually need to take a slice/cross section of that. I am coming up with wacky plots.&lt;/p&gt;&#xA;&lt;p&gt;Details for a specific case:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  Bias in eV =    -4.0817 # states  14&#xA;    2    0.000000    0.000000    0.000000&#xA;   30    0.155100    0.000000    0.000000&#xA;   30   -0.077550    0.134321    0.000000&#xA;   90    0.000000    0.000000    0.155133&#xA;    6    6.000000   -0.000000    2.686415   13.962000&#xA;    6    6.000000    2.326504    1.343207   13.962000&#xA;  0.55588E-05  0.34988E-04  0.11861E-03  0.24345E-03  0.39097E-03  0.54096E-03&#xA;  0.67531E-03  0.78084E-03  0.85041E-03  0.88243E-03  0.87942E-03  0.84643E-03&#xA;  0.78998E-03  0.71727E-03  0.63564E-03  0.55189E-03  0.47148E-03  0.39794E-03&#xA;  0.33282E-03  0.27609E-03  0.22697E-03  0.18457E-03  0.14835E-03  0.11800E-03&#xA;  0.93204E-04  0.73420E-04  0.57812E-04  0.45437E-04  0.35477E-04  0.27382E-04&#xA;  0.20868E-04  0.15779E-04  0.11943E-04  0.91091E-05  0.69791E-05  0.52905E-05&#xA;  0.38834E-05  0.27135E-05  0.18011E-05  0.11554E-05  0.73628E-06  0.46992E-06&#xA;  0.28540E-06  0.14217E-06  0.39326E-07  0.34955E-09  0.39326E-07  0.14217E-06&#xA;  0.28540E-06  0.46992E-06  0.73628E-06  0.11554E-05  0.18011E-05  0.27135E-05&#xA;  0.38834E-05  0.52905E-05  0.69791E-05  0.91091E-05  0.11943E-04  0.15779E-04&#xA;  0.20868E-04  0.27382E-04  0.35477E-04  0.45437E-04  0.57812E-04  0.73420E-04&#xA;  0.93204E-04  0.11800E-03  0.14835E-03  0.18457E-03  0.22697E-03  0.27609E-03&#xA;  0.33282E-03  0.39794E-03  0.47148E-03  0.55189E-03  0.63564E-03  0.71727E-03&#xA;  0.78998E-03  0.84643E-03  0.87942E-03  0.88243E-03  0.85041E-03  0.78084E-03&#xA;  0.67531E-03  0.54096E-03  0.39097E-03  0.24345E-03  0.11861E-03  0.34988E-04&#xA;  0.11671E-04  0.44003E-04  0.13569E-03  0.27204E-03  0.43228E-03  0.59398E-03&#xA;  0.73734E-03  0.84821E-03  0.91925E-03  0.94930E-03  0.94177E-03  0.90273E-03&#xA;  0.83954E-03  0.75996E-03  0.67161E-03  0.58146E-03  0.49513E-03  0.41637E-03&#xA;  0.34692E-03  0.28681E-03  0.23517E-03  0.19094E-03  0.15333E-03  0.12184E-03&#xA;  0.96098E-04  0.75528E-04  0.59316E-04  0.46516E-04  0.36275E-04  0.27993E-04&#xA;... etc&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question&lt;/strong&gt;: Can someone please help me accomplish the two goals I laid out? It need only work for the specific case. If this specific case can work, I am hoping I can generalize it to other cases.&#xA;Thank you so much in advance for any feedback, guidance, answers, or advice. I would love clarity on this issue and the file format.&lt;/p&gt;&#xA;" OwnerUserId="7016" LastActivityDate="2023-09-05T01:03:18.667" Title="How can I properly plot this .cube file in Python?" Tags="|quantum-espresso|computational-chemistry|crystallography|mathematical-modeling|vesta|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11580" PostTypeId="1" CreationDate="2023-09-05T06:28:49.047" Score="5" ViewCount="103" Body="&lt;p&gt;My compound under investigation are cubic and construct corresponding 2x2x2 supercell. Properties like optical and mechanical seem to be correct as expected. However a problem arises in their electronic band structures where it changes from indirect band gap to direct band gap semiconductor. Is this even possible? Can anyone enlighten me with some literature where such findings occur in pristine supercells?&lt;/p&gt;&#xA;" OwnerUserId="7746" LastEditorUserId="7746" LastEditDate="2023-09-08T15:02:06.333" LastActivityDate="2023-09-08T15:02:06.333" Title="Indirect to direct band gap transition in SUPERCELLS?" Tags="|density-functional-theory|band-structure|reference-request|supercell|bandgap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11581" PostTypeId="1" CreationDate="2023-09-05T08:27:55.947" Score="2" ViewCount="35" Body="&lt;p&gt;In this article where they have introduced a new activity descriptor &lt;a href=&quot;https://link.springer.com/article/10.1007/s11244-013-0159-2&quot; rel=&quot;nofollow noreferrer&quot;&gt;width of d-band&lt;/a&gt; the formula for width has a coefficient 4 &lt;span class=&quot;math-container&quot;&gt;$(W_d = 4\sqrt{m^c_2})$&lt;/span&gt;. While the same formula used in other works does not have any coefficient &lt;span class=&quot;math-container&quot;&gt;$(W_d = \sqrt{m^c_2})$&lt;/span&gt;. It is understood that the formula is the second moment, but why in this article the coefficient is taken?&lt;/p&gt;&#xA;" OwnerUserId="5619" LastEditorUserId="5619" LastEditDate="2023-09-05T08:35:30.670" LastActivityDate="2023-09-05T08:35:30.670" Title="What is the meaning of this co-efficient in the formula for the width of the d-band center?" Tags="|density-of-states|d-band|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11582" PostTypeId="1" CreationDate="2023-09-05T08:44:36.610" Score="3" ViewCount="52" Body="&lt;p&gt;Is the following description talking about the simulation box or the boundary condition?&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;To prevent the argon atoms in the gas phase from running off to&#xA;infinity, we enclose the system in a &amp;quot;balloon&amp;quot; by adding an additional&#xA;term to the potential energy:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Vi = \begin{cases} &#xA;      \frac{1}{B} \times (r_i - r_B)^2 &amp;amp; \text{for } r_i &amp;gt; r_B \\&#xA;      0 &amp;amp; \text{for } r_i \leq r_B&#xA;   \end{cases}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which contributes the following term to the force:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Fi = \begin{cases} &#xA;      -B \times (r_i - r_B) \times x_i &amp;amp; \text{for } r_i &amp;gt; r_B \\&#xA;      0 &amp;amp; \text{for } r_i \leq r_B&#xA;   \end{cases}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-09-05T11:47:28.000" LastActivityDate="2023-09-08T03:10:49.683" Title="Is the following description talking about the simulation box or the boundary condition?" Tags="|molecular-dynamics|mathematical-modeling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11583" PostTypeId="2" ParentId="11570" CreationDate="2023-09-05T08:53:25.197" Score="2" Body="&lt;p&gt;The whole point of splines is that, as piecewise polynomials, they are cheap to interpolate. So here's how to numerically re-parametrise a spline by arc length:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Form a fine grid of the prior parameter (for example, decide that you will take ten points between each prior image).&lt;/li&gt;&#xA;&lt;li&gt;Evaluate the spline at each grid point.&lt;/li&gt;&#xA;&lt;li&gt;Estimate the cumulative arc-length at each grid point as the sum of Cartesian distances up to that point.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Now you have estimated the spline arc-length at each point on a fine grid of the prior parameter, which you can simply invert to estimate the prior parameter by arc-length -- an arc-length parametrisation!&lt;/p&gt;&#xA;&lt;p&gt;The parametrisation accuracy can be checked by simply using finer grids. Since the spline and its derivatives are easily evaluated everywhere, the arc length accuracy can be obtained by analysing the Taylor error.&lt;/p&gt;&#xA;&lt;p&gt;But the &lt;em&gt;fractional&lt;/em&gt; arc-length will be even more accurately estimated. Both the total arc-length and the cumulative arc-length at each point will be underestimated by straight lines, and almost certainly by very similar proportions, so their ratio will almost certainly gain accuracy from cancellation of errors.&lt;/p&gt;&#xA;&lt;p&gt;Having said that, when you say&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;in all of these papers, I haven't found a single description of how the spline fitting and arc length parameterisation is actually performed from a set of Cartesian coordinates.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;that simply isn't right. Both J. Chem. Phys. 2007, 126, 164103 (equation 12) and  J. Chem. Theory Comput. 2022, 18, 8, 5108–5115 (equation 5) state that the Cartesian distances between evaluated points is used as the arc-length estimate (even without sub-sampling!).&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-09-05T08:53:25.197" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11584" PostTypeId="1" AcceptedAnswerId="11601" CreationDate="2023-09-05T10:51:05.133" Score="4" ViewCount="93" Body="&lt;p&gt;Do any DFT codes (for example, QE ABINIT, Fleur, ....) provide the availability of getting the DOS that produced by each iteration? If no, so, how can I get them?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="6232" LastActivityDate="2023-09-09T10:41:46.593" Title="How to get DOS for each iteration?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|abinit|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11585" PostTypeId="2" ParentId="11577" CreationDate="2023-09-05T14:02:26.223" Score="2" Body="&lt;p&gt;Short answer: If you use superposition of atomic densities to form the initial density matrix, that matrix is not consistent with the geometry of the system, and so the initial energy doesn't mean a lot. As such it is very common for the energy to increase after the first cycle, as it is only then that you get a &amp;quot;meaningful&amp;quot; density matrix for the first time. Here's an example from CRYSTAL:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ijb@ijb-Latitude-5410:~/work/crystal/work/chab$ grep CYC scf.out | grep ETOT | head -3&#xA;&#xA;     CYC   0 ETOT(AU) -5.229343032813E+03 DETOT -5.23E+03 tst  0.00E+00 PX  1.00E+00&#xA;     CYC   1 ETOT(AU) -5.229076341815E+03 DETOT  2.67E-01 tst  0.00E+00 PX  1.00E+00&#xA;     CYC   2 ETOT(AU) -5.229783696202E+03 DETOT -7.07E-01 tst  4.57E-03 PX  1.66E-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Slightly longer answer: The initial density matrix formed by superposition of atomic densities (SAD) is block diagonal, each block corresponding to the density matrix for the isolated atom. But in the system the atoms aren't isolated, even at this stage when forming the &lt;em&gt;full&lt;/em&gt; density matrix for the system the overlap matrix couples the AOs of the guess on different sites, and in forming the SAD initial density matrix we have neglected the off-diagonal blocks caused by such coupling. Thus the SAD density matrix is &amp;quot;unphysical&amp;quot;, thus the energy derived from it has little meaning, thus it is not uncommon for the energy to increase on the first cycle.&lt;/p&gt;&#xA;" OwnerUserId="269" LastEditorUserId="142" LastEditDate="2023-09-10T11:45:52.333" LastActivityDate="2023-09-10T11:45:52.333" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11586" PostTypeId="2" ParentId="11575" CreationDate="2023-09-05T15:04:05.043" Score="3" Body="&lt;p&gt;The DFT-D family of corrections, including DFT-D2, DFT-D3 and DFT-D4, are energy corrections that depend on the atomic coordinates but not the wavefunction. (The DFT-D4 energy does depend on atomic charges, and the latter can be calculated from a wavefunction theory; however, to facilitate the calculation of nuclear gradients, one typically chooses another wavefunction theory that is considerably cheaper than the one used in calculating the &amp;quot;dispersion-free&amp;quot; electronic energy, for example a semiempirical method. Most of the time, one uses even coarser methods such as EEQ, which does not even involve wavefunctions.) DFT-D will only contribute to a property if the property is an energy derivative of (and only of) atomic coordinates, such as nuclear gradients or Hessians. Once you take a derivative with respect to a non-geometric parameter (e.g. suppose you want to calculate the geometric derivative of dipole moments, which is the mixed second-order derivative of the energy with respect to atomic coordinates and the electric field), the DFT-D contribution vanishes completely.&lt;/p&gt;&#xA;&lt;p&gt;For the properties that you explicitly mentioned, it is even easier to see that DFT-D does not contribute, since they involve only the wavefunction, and DFT-D does not contribute to the wavefunction. Whether DFT-D may have an influence on &amp;quot;other fully relaxed properties&amp;quot; is not so clear-cut, since nuclear gradients and Hessians are, in some sense, fully relaxed properties too. In any case, it should be easy to determine whether DFT-D contributes to a property using the fact that DFT-D only contributes to the energy and only depends on atomic coordinates.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-09-05T15:04:05.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11588" PostTypeId="1" CreationDate="2023-09-05T15:28:50.530" Score="4" ViewCount="41" Body="&lt;p&gt;I am to Equilibrate a uniformly distributed spc water molecules at 300k in 50x50x50 box. Water density is taken to be 1000kg/m3. Simulate the system in the NVT ensemble. The spc water is modeled using the CLAYFF force field.&lt;/p&gt;&#xA;&lt;p&gt;*** in my calculations of numbers water molecules for the box I had 4177 molecules.***&lt;/p&gt;&#xA;&lt;p&gt;Out of the equilibrated spc water molecules above, create a half-sphere of radius 26A to depict water droplets. And this water droplet has 946 spc water molecules.&lt;/p&gt;&#xA;&lt;p&gt;My challenge is to create the water droplets&lt;/p&gt;&#xA;" OwnerUserId="7844" LastActivityDate="2023-09-05T15:28:50.530" Title="How to create a water droplet (half-sphere) on a rock (quartz) surface" Tags="|molecular-dynamics|lammps|vmd|packmol|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11589" PostTypeId="1" CreationDate="2023-09-05T18:19:55.337" Score="2" ViewCount="54" Body="&lt;p&gt;I'm trying to tracking the state density of a system using Quantum Espresso by running this input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;system&#xA;    ibrav=4, celldm(1) =10.410909236, &#xA;    nat=20, ntyp=1,&#xA;    ecutwfc=2.50000e+01&#xA;    ecutrho=2.25000e+02&#xA;    nbnd=84&#xA;/&#xA;&amp;amp;electrons&#xA;    conv_thr=1.00000e-06&#xA;/&#xA;ATOMIC_SPECIES&#xA;Si     28.08550  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Ca     40.07800  Ca.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;P      30.97376  P.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (alat)&#xA;Si            0.0000000000        0.0000000000       -0.0157540426&#xA;O             0.3299136474        0.0545324986        0.0595401725&#xA;O             0.9454675014        0.2753811489        0.0595401725&#xA;O             0.7246188511        0.6700863526        0.0595401725&#xA;P             0.6666670000        0.3333330000        0.0987976560&#xA;O             0.6666670000        0.3333330000        0.2113501434&#xA;Ca            0.6666670000        0.3333330000        0.3706146451&#xA;O             0.1992673103       -0.1108239995        0.4380418511&#xA;O             1.1108239995        0.3100913098        0.4380418511&#xA;O             0.6899086902        0.8007326897        0.4380418511&#xA;Si           -0.0000000000       -0.0000000000        0.5320360071&#xA;O             0.2891646956        0.3289811702        0.6093561073&#xA;O             0.0398164747        0.7108353044        0.6093561073&#xA;O             0.6710188298        0.9601835253        0.6093561073&#xA;P             0.3333330000        0.6666670000        0.6406709519&#xA;O             0.3333330000        0.6666670000        0.7561974923&#xA;P             0.3333330000        0.6666670000        0.8748653332&#xA;O             0.2739498732        0.3264620877        0.9034691403&#xA;O             0.0525122146        0.7260501268        0.9034691403&#xA;O             0.6735379123        0.9474877854        0.9034691403&#xA;K_POINTS {crystal_b}&#xA;12&#xA;20 !Gamma&#xA;20 !M&#xA;20 !K&#xA;20 !Gamma&#xA;20 !A&#xA;20 !L&#xA;20 !H&#xA;0  !A&#xA;20 !L&#xA;0  !M&#xA;20 !K&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, I get this error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[[49511,1],0]: A high-performance Open MPI point-to-point messaging module&#xA;was unable to find any relevant network interfaces:&#xA;&#xA;Module: OpenFabrics (openib)&#xA;  Host: quantum2&#xA;&#xA;Another transport will be used instead, although this may result in&#xA;lower performance.&#xA;&#xA;NOTE: You can disable this warning by setting the MCA parameter&#xA;btl_base_warn_component_unused to 0.&#xA;--------------------------------------------------------------------------&#xA;&#xA;     Program BANDS v.6.5 starts on  5Sep2023 at 15:16:19 &#xA;&#xA;     This program is part of the open-source Quantum ESPRESSO suite&#xA;     for quantum simulation of materials; please cite&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 21 395502 (2009);&#xA;         &amp;quot;P. Giannozzi et al., J. Phys.:Condens. Matter 29 465901 (2017);&#xA;          URL http://www.quantum-espresso.org&amp;quot;, &#xA;     in publications or presentations arising from this work. More details at&#xA;     http://www.quantum-espresso.org/quote&#xA;&#xA;     Parallel version (MPI &amp;amp; OpenMP), running on      32 processor cores&#xA;     Number of MPI processes:                 1&#xA;     Threads/MPI process:                    32&#xA;&#xA;     MPI processes distributed on     1 nodes&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine bands (1):&#xA;     reading bands namelist&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;--------------------------------------------------------------------------&#xA;MPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD&#xA;with errorcode 1.&#xA;&#xA;NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.&#xA;You may or may not see output from other processes, depending on&#xA;exactly when Open MPI kills them.&#xA;--------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can anyone help me to know what I did wrong in the input file?&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="7" LastEditDate="2023-09-05T18:49:56.833" LastActivityDate="2023-09-05T18:49:56.833" Title="Error in calculating state density &quot;dens&quot;" Tags="|quantum-espresso|density-of-states|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11590" PostTypeId="2" ParentId="11576" CreationDate="2023-09-05T19:11:40.493" Score="1" Body="&lt;p&gt;In VMD, under &amp;quot;Representations&amp;quot;, you can use Cartesian coordinates (among many other options) to select the atoms you want to visualise. For example, &lt;code&gt;same fragment as (z &amp;gt; 0 and and z &amp;lt; 10)&lt;/code&gt; will select all molecules (defined by bond connectivity) for which at least one atom has a z-position between 0 and 10.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-09-05T19:11:40.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11591" PostTypeId="2" ParentId="11584" CreationDate="2023-09-06T07:17:37.743" Score="4" Body="&lt;p&gt;Usually, the density of states (DOS) is calculated for the converged SCF calculation. However, to address your unique goal you might try &lt;a href=&quot;https://www.turbomole.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;TURBOMOLE&lt;/a&gt;.&#xA;Since you mentioned QE, ABINIT, etc. I assume you want to do it for periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;TURBOMOLE's &lt;code&gt;[riper][2]&lt;/code&gt; module allows to perform periodic DFT calculations.&lt;/p&gt;&#xA;&lt;p&gt;This module considers the density of states as a property calculation. What this means is that given the files of a previous SCF calculation, it can read the bands information and calculate the density of states from that.&lt;/p&gt;&#xA;&lt;p&gt;Keeping this in mind you can employ the following trick to calculate the DOS at each iteration of the SCF.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Set the maximum number of SCF iterations to 1 (&lt;code&gt;$scfiterlimit    1&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Run DFT calculation (&lt;code&gt;nohup riper &amp;gt; output_iter_1&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Run DOS calculation with the command line argument &lt;code&gt;-proper&lt;/code&gt; (&lt;code&gt;nohup riper -proper &amp;gt; riper.out &amp;amp;&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;This will give you the DOS for the first SCF iteration.&lt;/p&gt;&#xA;&lt;p&gt;Next, repeat the above process with &lt;code&gt;$scfiterlimit    2&lt;/code&gt;. The good thing about &lt;code&gt;riper&lt;/code&gt; is that it will restart automatically from where the previous calculation left off.&lt;/p&gt;&#xA;&lt;p&gt;So ultimately, you can keep increasing the max SCF iterations and you will be able to achieve what you wanted.&lt;/p&gt;&#xA;&lt;p&gt;I assume, that something similar can be achieved with Quantum ESPRESSO as well, because as far as I can recall, the SCF is performed with &lt;code&gt;pw.x&lt;/code&gt; while DOS calculations is done with another binary.&lt;/p&gt;&#xA;" OwnerUserId="7403" LastActivityDate="2023-09-06T07:17:37.743" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11592" PostTypeId="1" CreationDate="2023-09-06T18:14:11.507" Score="2" ViewCount="222" Body="&lt;p&gt;I'm trying to convert vasp outcar to extxyz using ase read and write. But how can I control what contents to print out from comment line and data columns?&lt;/p&gt;&#xA;&lt;p&gt;For example, I hope to convert vasp AIMD outcar file (100 frames) to extxyz, with Lattice, Properties, pbc, and energy in comment line, and atom name, xyz coordinate, and velocity in the data columns. In other files, I hope to print out stress, Lattice, free energy, and pbc in comment line, and atom name, xyz coordinate, and fx fy fz in the data columns.&lt;/p&gt;&#xA;&lt;p&gt;I checked the manual in &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html#extxyz&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/io/formatoptions.html#extxyz&lt;/a&gt;, But I still can't find a way to control the output data in comment line and data column using ase write.&lt;/p&gt;&#xA;&lt;p&gt;I can perform simple conversion from vasp outcar to extxyz using ase read and write, but that is what I want. I hope to know how I can selectively control which data to print out to comment line and data columns during conversion using ase read and write. Is this even possible? Or is this something I need to write?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="74" LastEditorUserId="74" LastEditDate="2023-09-06T18:37:28.127" LastActivityDate="2023-09-06T18:37:28.127" Title="ASE write extxyz question" Tags="|atomic-simulation-environment|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11593" PostTypeId="1" CreationDate="2023-09-06T23:36:32.520" Score="2" ViewCount="45" Body="&lt;p&gt;I am creating an energy level diagram for the orbitals of [XeF₅] - molecule produced by two fragments: [Xe] 4+ and [F₅] 5-. There is a very large energy difference between the two fragments, so I would like to shift the energy of each fragment orbital to make a cleaner energy level diagram. The original idea for shifting the fragments was to shift the energy of each fragment orbital &lt;em&gt;E&lt;/em&gt; by the total energy of the other fragment &lt;em&gt;V&lt;/em&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{frag1}+V_{frag2}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{frag2}+V_{frag1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The problem is this energy shift is huge and I do not believe it is the best way to shift the fragment orbitals. I have not found many resources on properly shifting the energy of the fragment orbitals to make an energy level diagram, and I was wondering if there is any other (if any) systematic way of doing this?&lt;/p&gt;&#xA;&lt;p&gt;Any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-09-06T23:36:32.520" Title="How much should you shift fragment energies to create an energy level diagram?" Tags="|computational-chemistry|gaussian|formation-energy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11594" PostTypeId="1" CreationDate="2023-09-07T17:17:14.117" Score="10" ViewCount="368" Body="&#xA;&lt;h1&gt;The original resource&lt;/h1&gt;&#xA;&lt;p&gt;&amp;quot;Tables for Group Theory&amp;quot; By Peter Atkins, Mark Child and Courtenay Phillips (1970). I have been using &lt;a href=&quot;http://xuv.scs.illinois.edu/516/handouts/character%20tables_for_group_theory.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this 2008 version&lt;/a&gt;, in which Pg. 37 has the following table:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q3r51l.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q3r51l.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Some minor inconsistencies&lt;/h1&gt;&#xA;&lt;p&gt;These inconsistencies don't bother me as much as the ones in the next section, but I'm mentioning them because the existence of these inconsistencies could possibly offer a simple explanation for the ones that I describe in the next section (i.e. maybe they simply didn't put much effort into perfecting the diagrams).&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;For C&lt;sub&gt;4&lt;/sub&gt; one of the lines is black instead of purple&lt;/li&gt;&#xA;&lt;li&gt;For C&lt;sub&gt;6&lt;/sub&gt; there's extra purple lines which seem to be spurious&lt;/li&gt;&#xA;&lt;li&gt;For C&lt;sub&gt;4&lt;/sub&gt;, C&lt;sub&gt;5&lt;/sub&gt; and C&lt;sub&gt;6&lt;/sub&gt; some lines are different sizes when compared to the other lines in the same diagram, or when comparing the diagrams of C&lt;sub&gt;5&lt;/sub&gt; and C&lt;sub&gt;5h&lt;/sub&gt;.&lt;/li&gt;&#xA;&lt;li&gt;If the C&lt;sub&gt;nv&lt;/sub&gt; series approaches a cone as n→∞, then the D&lt;sub&gt;nh&lt;/sub&gt; series would approach a circle as n→∞, but this is not depicted.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;More uncomfortable inconsistencies&lt;/h1&gt;&#xA;&lt;p&gt;For the inconsistencies that were listed in the previous section, I'm comfortable concluding that the first three were just issues with aesthetics (poor work on the graphics), and that the other inconsistency was simply an oversight.&lt;/p&gt;&#xA;&lt;p&gt;For the following two, I'm a bit more uncomfortable because they seem much less accidental:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The purple lines in C&lt;sub&gt;4&lt;/sub&gt;-C&lt;sub&gt;6&lt;/sub&gt; are perfectly parallel with beige lines, but for C&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;3&lt;/sub&gt; they are not. This seems much less accidental than coloring a line black when all other such lines are purple.&lt;/li&gt;&#xA;&lt;li&gt;The purple lines in the C&lt;sub&gt;n&lt;/sub&gt; and C&lt;sub&gt;nh&lt;/sub&gt; series are just thin straight lines, but the D&lt;sub&gt;n&lt;/sub&gt; series has &lt;em&gt;&lt;strong&gt;triangles&lt;/strong&gt;&lt;/em&gt;. Perhaps in the D&lt;sub&gt;n&lt;/sub&gt; series, since there's two different types of appendages (beige and purple), they felt the need to use thicker triangles rather than just thin lines, so that the difference between the two types is made more obvious than it would be if they were just thin lines with different colors (rather than thick triangles with different colors). I'll ask a question about this inconsistency in a separate post, in line with the &lt;a href=&quot;https://mattermodeling.meta.stackexchange.com/q/421/5&quot;&gt;one question per post policy&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;Are the C&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;3&lt;/sub&gt; diagrams simply in error? For example, is there actually a molecule with a structure like depicted in the C&lt;sub&gt;2&lt;/sub&gt; diagram, or is it meant to be just a straight horizontal line with two appendages, like the O-O bond with two H appendages in H2O2, rather than a 3D diamond with two appendages?&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-09-18T18:13:33.010" LastActivityDate="2023-09-18T18:13:33.010" Title="Inconsistencies in a famous point group table" Tags="|molecular-modeling|mathematical-modeling|symmetry|geometry|structure|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11595" PostTypeId="2" ParentId="11594" CreationDate="2023-09-07T21:47:40.943" Score="9" Body="&lt;p&gt;&lt;strong&gt;After &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64354393#64354393&quot;&gt;hours of conversation with three participants including me&lt;/a&gt;, I can make the following conclusions.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Answer to the question&lt;/h1&gt;&#xA;&lt;p&gt;It's likely an unintentional &amp;quot;error&amp;quot; in the publication.  In the C&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;3&lt;/sub&gt; figures, the purple lines can indeed be aligned with the beige lines, as in the diagrams for C&lt;sub&gt;4&lt;/sub&gt;, C&lt;sub&gt;5&lt;/sub&gt;, C&lt;sub&gt;6&lt;/sub&gt;, C&lt;sub&gt;2h&lt;/sub&gt;, C&lt;sub&gt;3h&lt;/sub&gt;, C&lt;sub&gt;4h&lt;/sub&gt;, C&lt;sub&gt;5h&lt;/sub&gt;, C&lt;sub&gt;6h&lt;/sub&gt;. The authors likely did not intend to draw the purple lines with non-zero angles with respect to the beige lines, especially in the case of the C&lt;sub&gt;3&lt;/sub&gt; diagram, which seems to be unintentionally divergent from the C&lt;sub&gt;3h&lt;/sub&gt; diagram (although they may have had specific molecules in mind when choosing the diagrams for C&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;3&lt;/sub&gt;).&lt;/p&gt;&#xA;&lt;h1&gt;Further conclusions&lt;/h1&gt;&#xA;&lt;p&gt;It is not technically incorrect for the angles between the purple lines and the beige lines to be non-zero in C&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;3&lt;/sub&gt; molecules (as long as the angles are not chosen in such a way to promote the point groups to a higher one, like D&lt;sub&gt;3h&lt;/sub&gt; in the case of C&lt;sub&gt;3&lt;/sub&gt;), but if drawn that way, it would have been more consistent for the angles to be non-zero in the C&lt;sub&gt;4&lt;/sub&gt;, C&lt;sub&gt;5&lt;/sub&gt; and C&lt;sub&gt;6&lt;/sub&gt; cases as well.&lt;/p&gt;&#xA;&lt;p&gt;Also, the diagram for C&lt;sub&gt;2&lt;/sub&gt; is indeed a valid structure with that point group, but it may not be as easy to find a real-world molecule that has that shape, compared to the H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt; example that I suggested in the question post. The diagram for C&lt;sub&gt;2v&lt;/sub&gt; is essentially the one in the top-right corner of the screenshot below from the Landolt-Boernstein series, so it's a pyramid whose 2D diagram looks like a diamond:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kOYO9.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kOYO9.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;By adding one atom along the H-Si line, and another identical atom in the H-Si line directly opposite to the first H-Si line, we can maintain the  C&lt;sub&gt;2&lt;/sub&gt; axis while breaking the vertical planes, therefore demoting the point group from C&lt;sub&gt;2v&lt;/sub&gt; to C&lt;sub&gt;2&lt;/sub&gt;. The new atoms that are added along the H-Si lines could be added in between the H and Si atoms, or outside of the original pyramid, as in the diagram in the original question post: in both cases we would get a C&lt;sub&gt;2&lt;/sub&gt; molecule, but in both cases it's harder to find a real molecule that would have this shape, compared to the ease with which we found H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt; as a simpler example of a C&lt;sub&gt;2&lt;/sub&gt; molecule. Likewise, H&lt;sub&gt;2&lt;/sub&gt;O would have been a more obvious choice for the C&lt;sub&gt;2v&lt;/sub&gt; example, compared to the above (non-standard) isomer of H&lt;sub&gt;2&lt;/sub&gt;Si&lt;sub&gt;2&lt;/sub&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-07T21:47:40.943" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11596" PostTypeId="2" ParentId="11582" CreationDate="2023-09-08T03:10:49.683" Score="5" Body="&lt;p&gt;It's not talking about either, although it is related to those. They are restraining their system by adding a harmonic potential at the &amp;quot;boundary&amp;quot;, which will prevent atoms from escaping.&lt;/p&gt;&#xA;&lt;p&gt;A restraint is not the same as a constraint. We use the word constraint to mean a certain condition is strictly enforced. If we &lt;em&gt;constrained&lt;/em&gt; the atoms to be within &lt;span class=&quot;math-container&quot;&gt;$r_B$&lt;/span&gt; of the origin, they would &lt;em&gt;never&lt;/em&gt; be allowed to have &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_B$&lt;/span&gt;. We use the word restraint to mean a softer condition; in this work, they add an energy penalty which disfavours configurations with &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;r_B$&lt;/span&gt; (because they are high in energy) but doesn't disallow them.&lt;/p&gt;&#xA;&lt;p&gt;Restraints mean that the desired situation, in this case that &lt;span class=&quot;math-container&quot;&gt;$r \leq r_B$&lt;/span&gt;, is favourable, but not enforced. A boundary &lt;em&gt;constraint&lt;/em&gt; is like having a hard wall at the edge; the authors in this work are considering their boundary to be elastic, so atoms can actually deform the boundary by exchanging energy with it.&lt;/p&gt;&#xA;&lt;p&gt;Restraints have some desirable properties, compared to constraints. They are smooth, continuous and differentiable, and this makes time-integrating the atomic dynamics quite straightforward. If the finite timestep causes an atom to go too far past &lt;span class=&quot;math-container&quot;&gt;$r_B$&lt;/span&gt; here, for example, it just ends up with a slightly greater potential energy, and a restoring force acts to bring the atom back.&lt;/p&gt;&#xA;&lt;p&gt;In contrast, a constraint is like having a &amp;quot;hard wall&amp;quot; potential, which is zero for &lt;span class=&quot;math-container&quot;&gt;$r&amp;lt;r_B$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\infty$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$r\geq r_B$&lt;/span&gt;. This is neither smooth nor differentiable, makes the dynamics difficult to time-integrate and if an atom ever has  &lt;span class=&quot;math-container&quot;&gt;$r\geq r_B$&lt;/span&gt; the simulation essentially breaks down because the energy becomes infinite and there is no restoring force to bring the atom back inside the boundary. This is such a problem that in practice, hard wall boundary conditions are handled by special case sub-time-step code to try to determine the boundary collision time and reflect particles, but it can still cause problems.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-09-08T03:10:49.683" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11597" PostTypeId="2" ParentId="11580" CreationDate="2023-09-08T03:37:38.787" Score="5" Body="&lt;p&gt;This is allowed, in fact you can almost always construct a supercell where this has to happen. Consider the band eigenvalue at k-point &lt;span class=&quot;math-container&quot;&gt;$\vec{k}=(0,0,\frac{1}{p})$&lt;/span&gt; in a given unit cell; if I now make a &lt;span class=&quot;math-container&quot;&gt;$1\times 1\times p$&lt;/span&gt; supercell, that k-point in my original cell maps to &lt;span class=&quot;math-container&quot;&gt;$\vec{k}^\prime=(0,0,0)=\Gamma$&lt;/span&gt; in the supercell. This is true for any choice of &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;, and more generally all the k-points are remapped between the cells.&lt;/p&gt;&#xA;&lt;p&gt;If I have a primitive cell with a VBM at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; and a CBM at any other rational k-point, I can always construct a supercell where that k-point would map to &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; and the transition would appear to be direct. However, if you compute the direct transition probability in the supercell you will still discover that it is zero, because the states will still have the correct phase relation and there will be no overlap under the dipole operator. In other words, all the properties are correct, we just can't immediately tell from a bandstructure plot because the supercell k-point doesn't uniquely determine the phase any more.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-09-08T03:37:38.787" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="11598" PostTypeId="1" AcceptedAnswerId="11602" CreationDate="2023-09-08T08:11:16.557" Score="5" ViewCount="103" Body="&lt;p&gt;I'm interested in bound ions in protein xray crystal structures.  Of course a lot of structures include biologically significant ions, such as Mg2+ in the active site of an enzyme.  But a lot of structures are also crystallized from protein solutions at fairly high salt concentrations, from physiologic (0.15M, 1 ion per 180 waters or so) to over 1M (1 ion per 27 waters).  There are plenty of these &amp;quot;high-salt&amp;quot; structures in RCSB that show a lot of crystallographic water sites, but not nearly enough ions for the right water/ion ratio.&lt;/p&gt;&#xA;&lt;p&gt;The question is: how easy is it to tell from the xray density whether a particular site is occupied by water or an ion?  (esp monovalent ions, K+/Na+/Cl-)&lt;/p&gt;&#xA;&lt;p&gt;I'm mainly interested in medium resolution structures, around 2.0-2.5A, although I'm also curious about if there is a particular resolution cutoff below which the ion vs water identification becomes more certain.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2023-09-08T15:13:06.160" LastActivityDate="2023-09-09T12:40:54.437" Title="How easy is it to distinguish water from ions in xray crystallography?" Tags="|crystallography|proteins|x-ray-diffraction|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11600" PostTypeId="1" CreationDate="2023-09-08T17:08:46.690" Score="5" ViewCount="109" Body="&lt;p&gt;Does anyone know of a paper, textbook, or other resource which outlines the expression for the analytic gradient of the HF energy (restricted or otherwise) in terms of Dunning's contracted Gaussian-type orbitals &lt;span class=&quot;math-container&quot;&gt;$\chi^{CGTO}_\mu(r)$&lt;/span&gt;? I'm talking about an expression that someone could simply sit down and program as a free-standing code using only a converged HF calculation as input. I.e. has someone written this down in a form where the only arguments of the expression would be the primitive GTO exponents, the contraction coefficients, the atom centers, the nuclear charges, and the converged eigenvalues and eigenvectors of the Hartree Fock SCF?&lt;/p&gt;&#xA;&lt;p&gt;Plenty of textbooks (Szabo and Ostlund, Yamaguchi et al, etc) describe the theory of analytic gradients using equations independent of basis set type, i.e. in an abstract way. Likewise, plenty of standard codes (open source or otherwise) perform these calculations with Dunning CGTOs and/or other basis set types. But because of how huge and modular (i.e. calling across many routines to read) these codes are, interpreting them takes a great deal of time.&lt;/p&gt;&#xA;&lt;p&gt;The form of the derivative of primitive GTOs is given by Szabo and Ostlund page 442 between equations C.12 and C.13. Since the contraction coefficients are not spatially dependent, this form should be (hopefully) simple to extend to a Dunning basis. From here, the form of the various derivative integrals (such as the matrix elements &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial V_{N N}}{\partial X_A}_{\mu \nu}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial V_{N e}}{\partial X_A}_{\mu \nu}$&lt;/span&gt; given in the middle of page 442) to obtain the HF gradient should be doable analytically in Mathematica etc. Thus, the explicit form of all these integrals and the overall gradient expression should be possible to write down in a way someone (maybe even someone without electronic structure knowledge) could just sit down and code. The expression would be long, but easily interpreted.&lt;/p&gt;&#xA;&lt;p&gt;I'm just wondering if this full expression exists anywhere, as I haven't been able to find it anywhere online and would like to before &amp;quot;recreating the wheel.&amp;quot; In particular, I will be using output from a density-fitted Hartree Fock code for my analytic gradient implementation, but any expression will do, as extending to density-fit Coulomb and exchange is probably the least tedious part of this process. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="7866" LastEditorUserId="7866" LastEditDate="2023-09-12T18:30:02.260" LastActivityDate="2023-09-13T17:47:49.703" Title="Explicit form of Hartree Fock analytic gradient with contracted GTOs? With or without density fitting" Tags="|basis-sets|hartree-fock|programming|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11601" PostTypeId="2" ParentId="11584" CreationDate="2023-09-09T10:41:46.593" Score="4" Body="&lt;p&gt;Since FLEUR was mentioned in the question I give an answer for that DFT code...&lt;/p&gt;&#xA;&lt;p&gt;In FLEUR we distinguish between SCF calculations and calculations on the DOS for a density that is already available. In DOS calculations we therefore don't create a new charge density. The reason for the different treatment is that one typically has different demands on certain parameters for DOS and for SCF calculations. Most importantly for creating a (high-quality) DOS it may be required to use a finer k-point sampling or a different Brillouin zone integration method. I sketched the special requirements for DOS calculations &lt;a href=&quot;https://www.flapw.de/MaX-6.0/documentation/dos/&quot; rel=&quot;nofollow noreferrer&quot;&gt;in the FLEUR user documentation&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, the calculation of the DOS in FLEUR only requires the presence of some density. This may even be the initial starting density (in the case of FLEUR this is a superposition of atomic densities). The density does not necessarily have to be self-consistent. If a DOS in every iteration is wanted, one could thus create a workflow around the actual FLEUR calculation to achieve this task. This is similar to the other answer by XYZ CIF for the TURBOMOLE code. More specifically one could either write a simple script that executes FLEUR repeatedly with alternating input files to perform a single SCF iteration, followed by a DOS calculation, or one could integrate such an approach into an &lt;a href=&quot;https://www.aiida.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;AiiDA&lt;/a&gt; workflow. For this we offer &lt;a href=&quot;https://aiida-fleur.readthedocs.io/en/develop/&quot; rel=&quot;nofollow noreferrer&quot;&gt;an AiiDA-FLEUR interface&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1256" LastActivityDate="2023-09-09T10:41:46.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11602" PostTypeId="2" ParentId="11598" CreationDate="2023-09-09T12:40:54.437" Score="6" Body="&lt;p&gt;&lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5349434/&quot; rel=&quot;noreferrer&quot;&gt;This 2017 paper&lt;/a&gt; about &lt;a href=&quot;https://cmm.minorlab.org/&quot; rel=&quot;noreferrer&quot;&gt;CheckMyMetal&lt;/a&gt; describes in details how one can distinguish various ions from water and other ions.&lt;/p&gt;&#xA;&lt;p&gt;In principle, atomic species could be more effectively determined from anomalous scattering, but getting anomalous signal requires tuning the diffraction wavelength to the absorption edge of a particular metal, which may not be possible.&lt;/p&gt;&#xA;" OwnerUserId="126" LastActivityDate="2023-09-09T12:40:54.437" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11603" PostTypeId="2" ParentId="11600" CreationDate="2023-09-09T12:56:13.170" Score="0" Body="&lt;p&gt;If you want to use Mathematica, simply write down the expression for the total energy and take the derivative with respect to the nuclear coordinates.&lt;/p&gt;&#xA;&lt;p&gt;The explicit form of the expressions can be found in standard textbooks and the literature; see e.g. &lt;a href=&quot;http://doi.org/10.1080/00268976900100941&quot; rel=&quot;nofollow noreferrer&quot;&gt;the seminal work of Pulay&lt;/a&gt;. All you need is density matrix elements, and the molecular (gradient) integrals. Automated differentiation is another option, and you can also find these works easily in the literature.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-09-09T12:56:13.170" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11604" PostTypeId="1" CreationDate="2023-09-09T20:47:57.160" Score="1" ViewCount="53" Body="&lt;p&gt;In a related question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11580/indirect-to-direct-band-gap-transition-in-supercells&quot;&gt;Indirect to direct band gap transition in SUPERCELLS&lt;/a&gt; it is illustrated that one just can't immediately tell from a supercell's bandstructure plot whether the bandgap is direct or indirect. A seemingly direct bandgap semiconductor, observed from the supercell's bandstructure plot, may be an indirect bandgap semiconductor in reality.&lt;/p&gt;&#xA;&lt;p&gt;My question is can this ambiguity be resolved by unfolding the bandstructure back into the original cell?&lt;/p&gt;&#xA;" OwnerUserId="5364" LastEditorUserId="5364" LastEditDate="2023-09-09T21:24:07.393" LastActivityDate="2023-09-09T21:24:07.393" Title="Indirect to direct bandgap transition in SUPERCELLS and band unfolding" Tags="|band-structure|bandgap|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11605" PostTypeId="1" CreationDate="2023-09-09T22:17:20.723" Score="4" ViewCount="70" Body="&lt;p&gt;I am currently working on a project involving py4vasp for crystal structure analysis. I have successfully installed py4vasp, Jupyter Lab, and Jupyter Notebook in a Conda environment. When I attempt to use py4vasp within a Jupyter Lab notebook by importing&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from py4vasp import Calculation&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I encounter an issue where it gets stuck on &amp;quot;loading widget.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;Environment Details:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Operating System: Windows 10&lt;/li&gt;&#xA;&lt;li&gt;Conda Environment: Anaconda Powershell Prompt (Miniconda 3)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I have verified that all the necessary Jupyter widgets are installed in my Conda environment using &lt;code&gt;conda list&lt;/code&gt;, so it seems like there might be a specific compatibility or configuration issue.&lt;/p&gt;&#xA;&lt;p&gt;Has anyone encountered a similar problem with py4vasp and Jupyter Lab integration on Windows 10 or in a similar Conda environment? If so, could you please share any insights or solutions you might have? Your assistance would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for your help.&lt;/p&gt;&#xA;" OwnerUserId="7361" LastEditorUserId="5" LastEditDate="2023-09-09T22:32:43.503" LastActivityDate="2023-10-17T16:36:28.570" Title="Issue with py4vasp and Jupyter Lab Integration on Windows 10?" Tags="|vasp|python|density-of-states|windows-operating-system|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11606" PostTypeId="1" CreationDate="2023-09-10T22:48:19.460" Score="3" ViewCount="22" Body="&lt;p&gt;I have several structures to visualize and print out. I previously opened them using terminal commands in Linux:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;~/VESTA-gtk3/VESTA POSCAR&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I need to set up bonds, overall appearance, and atom color, every time. Is there a way to do this setup before opening a structure in VESTA?&lt;/p&gt;&#xA;" OwnerUserId="7877" LastEditorUserId="5" LastEditDate="2023-09-10T23:34:08.093" LastActivityDate="2023-09-10T23:34:08.093" Title="Is there a way to configure some parameters in a system before opening a structure in VESTA?" Tags="|vesta|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11607" PostTypeId="1" CreationDate="2023-09-11T08:52:44.643" Score="4" ViewCount="46" Body="&lt;p&gt;I have binding free energy of some organic molecules on a surface, computed through Umbrella sampling. For now, I only have experimental data on the binding energy of some of these molecules. Is it possible to break the binding free energy into both enthalpic and entropic contribution, and calculate the binding energy from MD simulations, or can we quantify the binding free energy into some experimental values like the adsorption equilibrium constant? Thank you.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-09-11T08:52:44.643" Title="Quantifying binding free energy?" Tags="|molecular-dynamics|gromacs|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11608" PostTypeId="1" CreationDate="2023-09-11T14:13:40.710" Score="3" ViewCount="756" Body="&lt;p&gt;I need to calculate the bands of the structure I'm working on, can anyone tell me how I create the input file to calculate the bands?&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="5" LastEditDate="2023-09-11T14:33:24.893" LastActivityDate="2023-09-12T20:09:31.003" Title="How to create an input file for band calculation" Tags="|quantum-espresso|band-structure|software-input-file-request|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11609" PostTypeId="1" AcceptedAnswerId="11613" CreationDate="2023-09-11T16:25:13.950" Score="3" ViewCount="65" Body="&lt;p&gt;There are a myriad of pair potentials available for simulating the interactions between water molecules, ranging from simpler models like the SPC/E to more sophisticated ones based on high-level quantum mechanical methods like coupled-cluster calculations.&lt;/p&gt;&#xA;&lt;p&gt;I'm interested in identifying what is currently considered the &amp;quot;gold standard&amp;quot; ab initio pair potential for the interaction between two water molecules. My primary focus is on quantum mechanical accuracy, rather than the potential's ability to reproduce bulk behavior. Ideally, I'm seeking a highly accurate model that has been validated against quantum mechanical calculations, similar to the one presented in the paper &lt;a href=&quot;https://doi.org/10.1039/B809435G&quot; rel=&quot;nofollow noreferrer&quot;&gt; An accurate analytic representation of the water pair potential by Cencek et Al&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Additionally, if there is existing code that can reproduce the results of the potential, that would be highly beneficial.&#xA;Your expert guidance is greatly appreciated, as I have limited experience in this specific area of computational chemistry.&lt;/p&gt;&#xA;" OwnerUserId="610" LastActivityDate="2023-09-12T09:11:52.220" Title="What is the gold standard ab initio pair-potential between two water molecules?" Tags="|ab-initio-calculations|coupled-cluster|interatomic-potentials|potential-energy-surface|water|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11610" PostTypeId="1" AcceptedAnswerId="11617" CreationDate="2023-09-11T18:23:55.730" Score="5" ViewCount="178" Body="&lt;p&gt;How do you fix the bottom layers of a slab to mimic a bulk material in ASE? Any functional that takes the slab object and writes a POSCAR with selective dynamics will be deeply appreciated. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-09-12T14:15:39.543" Title="Fix layers of a slab" Tags="|vasp|surfaces|atomic-simulation-environment|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11611" PostTypeId="2" ParentId="11608" CreationDate="2023-09-11T19:42:00.603" Score="4" Body="&lt;p&gt;A general idea is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Determine the crystal symmetry of your system.&lt;/li&gt;&#xA;&lt;li&gt;Select the path between high symmetry points to calculate the bands (follow one of these links: &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Brillouin_zone&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;, &lt;a href=&quot;https://www.cryst.ehu.es/cryst/get_kvec.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;3&lt;/a&gt; or read this &lt;a href=&quot;https://doi.org/10.1016%2Fj.commatsci.2010.05.010&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Use a sample &lt;a href=&quot;https://www.fisica.uniud.it/%7Egiannozz/QE-Tutorial/&quot; rel=&quot;nofollow noreferrer&quot;&gt;file&lt;/a&gt; as a guide to add the path information to your input file or use a GUI like &lt;a href=&quot;https://burai.readthedocs.io/en/latest/index.html#&quot; rel=&quot;nofollow noreferrer&quot;&gt;BURAI&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;You can search &lt;a href=&quot;https://www.youtube.com/results?search_query=quantum+espresso+band+structure+calculation&quot; rel=&quot;nofollow noreferrer&quot;&gt;YouTube&lt;/a&gt; for tutorials about calculating bands using QuantumEspresso.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-09-11T19:42:00.603" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11612" PostTypeId="1" CreationDate="2023-09-11T23:12:32.213" Score="1" ViewCount="27" Body="&lt;p&gt;I'm looking at a system with really long bond lengths, and I'm trying to determine if there's any interaction at all between orbitals on two particular atoms.&lt;/p&gt;&#xA;&lt;p&gt;I'm using NBO7 with the GENNBO interface, and I'm trying to figure out how to change the threshold for either what the program recognizes as a bond (optimally using atomic distances) OR for the 3c-4e bond searching.&lt;/p&gt;&#xA;&lt;p&gt;Essentially, currently the 3CHB input keyword's 3C-4E output looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     3-Center, 4-Electron A:-B-:C Hyperbonds (A-B :C &amp;lt;=&amp;gt; A: B-C)&#xA;              [threshold for detection: 33.3%]&#xA;&#xA;                                                  NBOs       3-center hybrids&#xA;                                              -------------  ----------------&#xA;       Hyperbond A:-B-:C   %A-B/%B-C   occ    BD(A-B) LP(C)  h(A)  h(B)  h(C)&#xA;      -------------------  ---------  ------  ------- -----  ----  ----  ----&#xA;   1.  C  2:- C  3-: C  4  61.4/38.6  3.0548      37     18    41    42    18&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'd like to change the threshold for detection to be lower. I'm not finding anything in the manual that would indicate how to do this; if anyone has any examples of how to change this threshold I'd be very grateful. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="7883" LastActivityDate="2023-09-11T23:12:32.213" Title="Change bonding thresholds in NBO Calculations?" Tags="|density-functional-theory|quantum-chemistry|orbitals|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:21:49.393" ContentLicense="CC BY-SA 4.0" />
  <row Id="11613" PostTypeId="2" ParentId="11609" CreationDate="2023-09-12T09:11:52.220" Score="4" Body="&lt;p&gt;I'm not an expert, but I believe Paesani's many-body MBPol force fields &lt;a href=&quot;https://doi.org/10.1021/acs.accounts.6b00285&quot; rel=&quot;nofollow noreferrer&quot;&gt;Acc. Chem. Res. 49, 1844 (2016)&lt;/a&gt; afford some of the most accurate descriptions of the interactions between water molecules. The MBPol models are fit to highly accurate coupled-cluster energies with singles, doubles and perturbative triples (CCSD(T)) at the complete basis set (CBS) limit. I have not followed the development closely, but the many-body decomposition is a good Ansatz for building interaction models.&lt;/p&gt;&#xA;&lt;p&gt;I am a bit baffled, though, by your question which asks for a &amp;quot;pair potential&amp;quot;. Pair potentials are typically based only on the distance, while the interaction of water molecules is definitely not of the pair form, as it is strongly affected also by the relative angle of the molecules. The molecules are polar and only form hydrogen bonds at certain magic angles, and this requires more complicated interactions than pair potentials. Also, from what I remember, the higher-than-two-body terms in MBPol are likewise important; the behavior of three water molecules is more complicated than what one would expect based on just a two-molecule model applied to three molecules.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-09-12T09:11:52.220" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11614" PostTypeId="1" CreationDate="2023-09-12T11:40:34.200" Score="2" ViewCount="31" Body="&lt;p&gt;I hope you're well,&#xA;I am a beginner in the optical properties of carbon nanotubes, is there someone expert in carbon nanotubes who can verify with me its results,&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Hzh7f.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Hzh7f.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2023-09-17T12:37:37.463" LastActivityDate="2023-09-17T12:37:37.463" Title="Optical properties of a single-walled carbon nanotube (10,0)" Tags="|density-functional-theory|optical-properties|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11615" PostTypeId="2" ParentId="10760" CreationDate="2023-09-12T12:36:37.023" Score="3" Body="&lt;p&gt;Your approach to ML in Chemistry is biting off more than you can chew. First, it is not necessary for a chemist to become an expert python programmer. If you study chemistry, study chemistry 95% of the time and instead of programming in low level languages, which will greatly slow your research progress, I highly recommend learning Mathematica instead. A chemist need only prototype his or her algorithms - leave the low level programming to programmers. Also, there are professionals call chemoinformaticians that don't do anything but program chemistry programs. If your interested in that I suggest studying that in graduate school (probably in Europe). However, you specifically said that you are interested in applications of ML in Chemistry which does not require knowledge of python. You only need a chemistry program such as Marvin Suite by ChemAxon and also get competent at Mathematica. Mathematica is sufficient to do ML in chemistry. You can learn everything you need to know about ML in Chemistry in an eighty page document here:&#xA;&lt;a href=&quot;http://jamesbonnar.org.s3-website.us-east-2.amazonaws.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Machine Learning Methods in Chemistry&lt;/a&gt; Good luck!&lt;/p&gt;&#xA;" OwnerUserId="7886" LastActivityDate="2023-09-12T12:36:37.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11616" PostTypeId="2" ParentId="18" CreationDate="2023-09-12T12:46:56.187" Score="1" Body="&lt;p&gt;The use of a Markovian text generator can generate in silico combinatorial libraries in the form of SMILES strings. Invalid SMILES strings thereby generated can be culled with a simple Mathematica function. If your interested in ML in chemistry I would recommend becoming fluent in Mathematica and also read the following 80-page document: &lt;a href=&quot;http://jamesbonnar.org.s3-website.us-east-2.amazonaws.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Machine Learning Methods in Chemistry&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Good luck to you!&lt;/p&gt;&#xA;" OwnerUserId="7886" LastActivityDate="2023-09-12T12:46:56.187" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11617" PostTypeId="2" ParentId="11610" CreationDate="2023-09-12T14:15:39.543" Score="4" Body="&lt;p&gt;You can use &lt;a href=&quot;https://databases.fysik.dtu.dk/ase/ase/geometry.html#ase.geometry.get_layers&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.geometry.get_layers&lt;/code&gt;&lt;/a&gt; to get the bottom layer indices, and then use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html#ase.constraints.FixAtoms&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.constraints.FixAtoms&lt;/code&gt;&lt;/a&gt; to fix these atoms. As I said, with ASE you can imagine atomic structures as Numpy arrays, and then you realize you can do literally whatever you want.&lt;/p&gt;&#xA;&lt;p&gt;To use a Ni(111) surface as a simple example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111&#xA;from ase.geometry import get_layers&#xA;from ase.constraints import FixAtoms&#xA;from ase.visualize import view&#xA;import numpy as np&#xA;&#xA;atoms = fcc111('Ni', (4,4,4), vacuum=5.)&#xA;layers = get_layers(atoms, (0, 0, 1), tolerance=0.3)[0]&#xA;bot_indices = np.argwhere(layers==0).flatten()&#xA;c = FixAtoms(indices=bot_indices)&#xA;atoms.set_constraint(c)&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jEbHS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jEbHS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-09-12T14:15:39.543" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11618" PostTypeId="1" CreationDate="2023-09-12T15:54:12.537" Score="3" ViewCount="208" Body="&lt;p&gt;I am trying to render few representative structures for molecules. The requirement for the images is as follows: (1) It must be vector graphics, and (2) Atom colorings must intuitively make sense (like carbon atom being gray and nitrogen atom being blue). I have tried Chimera and Avogadro for this purpose. The last time I tried Chimera, I found that C atoms are colored in a off-white to brownish shade, which is the color that I am looking for. For Avogadro2, I have no means to export the image to an SVG or PDF file. I know that the Linux and Mac Installations for Avogadro2 supports exporting graphics to SVG and PDF files, which the Windows installation seems to be lacking. For Avogadro1, I cannot even install it on my Windows11 PC, due to MSVCP100.dll file missing error. If you know any free softwares that can do this, It would be helpful.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-09-12T16:53:37.590" Title="Rendering Vector Graphics Images" Tags="|visualization-software|free-software|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11619" PostTypeId="2" ParentId="11618" CreationDate="2023-09-12T16:53:37.590" Score="4" Body="&lt;p&gt;There are some issues with the &amp;quot;&lt;em&gt;Atom coloring must intuitively&lt;/em&gt;&amp;quot;. First, how can we think of an &lt;em&gt;intuitive&lt;/em&gt; color for an atom? Second, each program has different color schemes that can be used depending on the application.&lt;/p&gt;&#xA;&lt;p&gt;I like to use &lt;a href=&quot;https://jmol.sourceforge.net/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jmol&lt;/a&gt; software. It is open-source and available for Linux, Mac OS X and Windows. It is translated into several languages, supports many file formats for structures and properties, and can be used via script in batch conversion jobs.&lt;/p&gt;&#xA;&lt;p&gt;In particular, it has the following &lt;a href=&quot;https://jmol.sourceforge.net/jscolors/&quot; rel=&quot;nofollow noreferrer&quot;&gt;color schemes&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;CPK colors&lt;/li&gt;&#xA;&lt;li&gt;CPKnew (only to Rasmol v. 2.7.3 (or later))&lt;/li&gt;&#xA;&lt;li&gt;Residues: amino acids, nucleotides&lt;/li&gt;&#xA;&lt;li&gt;Chains&lt;/li&gt;&#xA;&lt;li&gt;Secondary structure&lt;/li&gt;&#xA;&lt;li&gt;Position along chain&lt;/li&gt;&#xA;&lt;li&gt;Positional Variability&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also, it includes these palettes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;JavaScript colors&lt;/li&gt;&#xA;&lt;li&gt;Netscape 8 bit color palette&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Below is a script that I use (in my Ubuntu box) to create high definition PNG and PDF images. It uses Jmol, PovRay and img2pdf.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/sh&#xA;# Script to create PNG image from the XYZ structure files using Jmol&#xA;# at specific frames&#xA;&#xA;cat &amp;gt; par.ini &amp;lt;&amp;lt;!&#xA;; POV-Ray configuration file example&#xA;&#xA;; common options&#xA;+SP8 ; start with every 8th pixel&#xA;+Q8 ; quality is high&#xA;+A0.3 ; anti aliasing&#xA;-P ; pause after rendering&#xA;-D ;&#xA;&#xA;[lo] ; options in section ‘[lo]’&#xA;+W150 ; lo res image width&#xA;+H100 ; lo res image height&#xA;&#xA;[hi] ; another section&#xA;+W732 ; hi res image width&#xA;+H616 ; hi res image height&#xA;&#xA;[Big] ;&#xA;Width=2196 ;&#xA;Height=1848 ;&#xA;Antialias=On ;&#xA;Antialias_Threshold=0.3 ;&#xA;!&#xA;&#xA;for file in *.xyz; do&#xA;    extension=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;${file##*.}&quot;&#xA;    filename=&quot;$&lt;/span&gt;{file%.*}&amp;quot;&#xA;    fig_file_t000=fig_&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$filename&quot;_t000&#xA;    fig_file_t025=fig_&quot;$&lt;/span&gt;filename&amp;quot;_t025&#xA;    fig_file_t050=fig_&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$filename&quot;_t050&#xA;    fig_file_t075=fig_&quot;$&lt;/span&gt;filename&amp;quot;_t075&#xA;    fig_file_t100=fig_&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$filename&quot;_t100&#xA;cat &amp;gt; $&lt;/span&gt;filename.jmol &amp;lt;&amp;lt;!&#xA;zap&#xA;load &lt;span class=&quot;math-container&quot;&gt;$file;&#xA;background white; frank off; #set ambient 10; set diffuse 60; set specular 70&#xA;N=1; frame @N; t=@N/10; write POVRAY $&lt;/span&gt;fig_file_t000.pov&#xA;N=500; frame @N; t=@N/10; write POVRAY &lt;span class=&quot;math-container&quot;&gt;$fig_file_t025.pov&#xA;N=1000; frame @N; t=@N/10; write POVRAY $&lt;/span&gt;fig_file_t050.pov&#xA;N=1500; frame @N; t=@N/10; write POVRAY &lt;span class=&quot;math-container&quot;&gt;$fig_file_t075.pov&#xA;N=2000; frame @N; t=@N/10; write POVRAY $&lt;/span&gt;fig_file_t100.pov&#xA;!&#xA;&#xA;jmol -L -n -s &lt;span class=&quot;math-container&quot;&gt;$filename.jmol&#xA;povray par[Big] -I$&lt;/span&gt;fig_file_t000.pov -O&lt;span class=&quot;math-container&quot;&gt;$fig_file_t000.png&#xA;povray par[Big] -I$&lt;/span&gt;fig_file_t025.pov -O&lt;span class=&quot;math-container&quot;&gt;$fig_file_t025.png&#xA;povray par[Big] -I$&lt;/span&gt;fig_file_t050.pov -O&lt;span class=&quot;math-container&quot;&gt;$fig_file_t050.png&#xA;povray par[Big] -I$&lt;/span&gt;fig_file_t075.pov -O&lt;span class=&quot;math-container&quot;&gt;$fig_file_t075.png&#xA;povray par[Big] -I$&lt;/span&gt;fig_file_t100.pov -O$fig_file_t100.png&#xA;done&#xA;&#xA;rm -f *.jmol&#xA;image2pdf.sh png&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The second script, &lt;code&gt;image2pdf&lt;/code&gt;, do a batch conversion of all files to PDF:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/sh&#xA;# Use ./image2pdf image_extension (jpg, png, tga, etc.)&#xA;# Trim image &#xA;# Convert to PDF&#xA;&#xA;if [ -z &lt;span class=&quot;math-container&quot;&gt;$1 ]&#xA;then&#xA;    echo &quot;Run as: image2pdf image_format&quot;&#xA;else&#xA;mogrify -trim *.$&lt;/span&gt;1&#xA;for file in *.&lt;span class=&quot;math-container&quot;&gt;$1; do&#xA;  extension=&quot;$&lt;/span&gt;{file##*.}&amp;quot;&#xA;  filename=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;${file%.*}&quot;&#xA;  img2pdf --output $&lt;/span&gt;filename.pdf --border 2mm:2mm --imgsize 300dpi $file&#xA;done&#xA;fi&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-09-12T16:53:37.590" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11620" PostTypeId="1" CreationDate="2023-09-12T17:47:20.870" Score="2" ViewCount="50" Body="&lt;p&gt;I did a band calculation (I'll leave the input and output files below), but I don't know how to identify whether my result is right or wrong, can anyone help me?&lt;/p&gt;&#xA;&lt;p&gt;Arquivo.in&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;bands&#xA;  outdir='./tmp'&#xA;  prefix='pwscf'&#xA;  filband='bands.dat'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Arquivo.out&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0.0000  -32.6938&#xA;    0.1964  -32.6938&#xA;    0.4714  -32.6933&#xA;    0.6679  -32.6933&#xA;    0.9429  -32.6923&#xA;    1.1393  -32.6923&#xA;    2.1214  -32.6918&#xA;    2.3178  -32.6918&#xA;    3.2214  -32.6925&#xA;    3.4178  -32.6925&#xA;    3.6928  -32.6918&#xA;    3.8892  -32.6918&#xA;    4.1642  -32.6915&#xA;    4.3607  -32.6915&#xA;    4.3607  -32.6918&#xA;    4.5571  -32.6918&#xA;&#xA;    0.0000  -19.8333&#xA;    0.1964  -19.8334&#xA;    0.4714  -19.8193&#xA;    0.6679  -19.8194&#xA;    0.9429  -19.7912&#xA;    1.1393  -19.7912&#xA;    2.1214  -19.7770&#xA;    2.3178  -19.7770&#xA;    3.2214  -19.7982&#xA;    3.4178  -19.7983&#xA;    3.6928  -19.7771&#xA;    3.8892  -19.7771&#xA;    4.1642  -19.7700&#xA;    4.3607  -19.7700&#xA;    4.3607  -19.7771&#xA;    4.5571  -19.7771&#xA;&#xA;    0.0000  -17.2903&#xA;    0.1964  -17.2601&#xA;    0.4714  -17.1882&#xA;    0.6679  -17.1577&#xA;    0.9429  -16.9193&#xA;    1.1393  -16.8905&#xA;    2.1214  -16.6769&#xA;    2.3178  -16.6733&#xA;    3.2214  -17.0008&#xA;    3.4178  -16.9705&#xA;    3.6928  -16.7184&#xA;    3.8892  -16.6982&#xA;    4.1642  -16.6025&#xA;    4.3607  -16.6025&#xA;    4.3607  -16.7184&#xA;    4.5571  -16.6982&#xA;&#xA;    0.0000  -16.8132&#xA;    0.1964  -16.8886&#xA;    0.4714  -16.7568&#xA;    0.6679  -16.8286&#xA;    0.9429  -16.6357&#xA;    1.1393  -16.6887&#xA;    2.1214  -16.6147&#xA;    2.3178  -16.6180&#xA;    3.2214  -16.6647&#xA;    3.4178  -16.7262&#xA;    3.6928  -16.5743&#xA;    3.8892  -16.6021&#xA;    4.1642  -16.5125&#xA;    4.3607  -16.5126&#xA;    4.3607  -16.5742&#xA;    4.5571  -16.6021&#xA;&#xA;    0.0000  -15.9973&#xA;    0.1964  -15.8812&#xA;    0.4714  -15.9653&#xA;    0.6679  -15.8590&#xA;    0.9429  -15.8916&#xA;    1.1393  -15.8270&#xA;    2.1214  -15.8969&#xA;    2.3178  -15.8957&#xA;    3.2214  -15.9081&#xA;    3.4178  -15.8263&#xA;    3.6928  -15.8892&#xA;    3.8892  -15.8742&#xA;    4.1642  -15.9679&#xA;    4.3607  -15.9679&#xA;    4.3607  -15.8893&#xA;    4.5571  -15.8744&#xA;&#xA;    0.0000  -14.8058&#xA;    0.1964  -14.9498&#xA;    0.4714  -15.0087&#xA;    0.6679  -15.0914&#xA;    0.9429  -15.3765&#xA;    1.1393  -15.4140&#xA;    2.1214  -15.4895&#xA;    2.3178  -15.5099&#xA;    3.2214  -15.2832&#xA;    3.4178  -15.3283&#xA;    3.6928  -15.4846&#xA;    3.8892  -15.4921&#xA;    4.1642  -15.3497&#xA;    4.3607  -15.3500&#xA;    4.3607  -15.4849&#xA;    4.5571  -15.4919&#xA;&#xA;    0.0000  -14.8057&#xA;    0.1964  -14.8058&#xA;    0.4714  -14.8302&#xA;    0.6679  -14.8323&#xA;    0.9429  -14.8824&#xA;    1.1393  -14.8936&#xA;    2.1214  -15.1296&#xA;    2.3178  -15.0948&#xA;    3.2214  -14.8771&#xA;    3.4178  -14.8782&#xA;    3.6928  -15.0664&#xA;    3.8892  -15.0579&#xA;    4.1642  -15.2979&#xA;    4.3607  -15.2974&#xA;    4.3607  -15.0649&#xA;    4.5571  -15.0595&#xA;&#xA;    0.0000  -14.7479&#xA;    0.1964  -14.8057&#xA;    0.4714  -14.7275&#xA;    0.6679  -14.8100&#xA;    0.9429  -14.8583&#xA;    1.1393  -14.8712&#xA;    2.1214  -14.8994&#xA;    2.3178  -14.9002&#xA;    3.2214  -14.7424&#xA;    3.4178  -14.8158&#xA;    3.6928  -14.9200&#xA;    3.8892  -14.9227&#xA;    4.1642  -14.9662&#xA;    4.3607  -14.9586&#xA;    4.3607  -14.9220&#xA;    4.5571  -14.9198&#xA;&#xA;    0.0000  -14.3209&#xA;    0.1964  -14.1611&#xA;    0.4714  -14.4238&#xA;    0.6679  -14.2991&#xA;    0.9429  -14.5727&#xA;    1.1393  -14.5439&#xA;    2.1214  -14.5660&#xA;    2.3178  -14.5472&#xA;    3.2214  -14.5891&#xA;    3.4178  -14.5170&#xA;    3.6928  -14.6305&#xA; 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   3.8892    2.8221&#xA;    4.1642    3.1078&#xA;    4.3607    3.1131&#xA;    4.3607    2.8128&#xA;    4.5571    2.8238&#xA;&#xA;    0.0000    3.1096&#xA;    0.1964    3.0990&#xA;    0.4714    3.0828&#xA;    0.6679    3.0802&#xA;    0.9429    3.1306&#xA;    1.1393    3.1111&#xA;    2.1214    2.9793&#xA;    2.3178    2.9711&#xA;    3.2214    3.0800&#xA;    3.4178    3.0668&#xA;    3.6928    3.1172&#xA;    3.8892    3.0976&#xA;    4.1642    3.1081&#xA;    4.3607    3.1177&#xA;    4.3607    3.1355&#xA;    4.5571    3.1123&#xA;&#xA;    0.0000    3.4788&#xA;    0.1964    3.4599&#xA;    0.4714    3.3976&#xA;    0.6679    3.4084&#xA;    0.9429    3.2296&#xA;    1.1393    3.2505&#xA;    2.1214    3.2357&#xA;    2.3178    3.2217&#xA;    3.2214    3.3050&#xA;    3.4178    3.3130&#xA;    3.6928    3.2100&#xA;    3.8892    3.2194&#xA;    4.1642    3.1678&#xA;    4.3607    3.1596&#xA;    4.3607    3.1868&#xA;    4.5571    3.1986&#xA;&#xA;    0.0000    3.4808&#xA;    0.1964    3.4928&#xA;    0.4714    3.4629&#xA; 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   3.8892    4.3660&#xA;    4.1642    4.2723&#xA;    4.3607    4.2929&#xA;    4.3607    4.3701&#xA;    4.5571    4.3792&#xA;&#xA;    0.0000    5.0445&#xA;    0.1964    5.0418&#xA;    0.4714    5.0081&#xA;    0.6679    5.0060&#xA;    0.9429    4.9708&#xA;    1.1393    4.9698&#xA;    2.1214    4.9562&#xA;    2.3178    4.9557&#xA;    3.2214    4.8668&#xA;    3.4178    4.8648&#xA;    3.6928    4.7794&#xA;    3.8892    4.7791&#xA;    4.1642    4.5660&#xA;    4.3607    4.5657&#xA;    4.3607    4.7764&#xA;    4.5571    4.7757&#xA;&#xA;    0.0000   10.3065&#xA;    0.1964   10.3992&#xA;    0.4714   10.7259&#xA;    0.6679   10.7958&#xA;    0.9429   11.5000&#xA;    1.1393   11.5190&#xA;    2.1214   11.8223&#xA;    2.3178   11.8224&#xA;    3.2214   11.2899&#xA;    3.4178   11.3183&#xA;    3.6928   11.6945&#xA;    3.8892   11.7073&#xA;    4.1642   11.7664&#xA;    4.3607   11.7677&#xA;    4.3607   11.6923&#xA;    4.5571   11.7014&#xA;&#xA;    0.0000   11.1807&#xA;    0.1964   11.0368&#xA;    0.4714   11.4245&#xA; 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   3.8892   12.5349&#xA;    4.1642   12.4005&#xA;    4.3607   12.3712&#xA;    4.3607   12.4996&#xA;    4.5571   12.5100&#xA;&#xA;    0.0000   12.7784&#xA;    0.1964   12.7979&#xA;    0.4714   12.6926&#xA;    0.6679   12.7103&#xA;    0.9429   12.5131&#xA;    1.1393   12.5592&#xA;    2.1214   12.6344&#xA;    2.3178   12.6558&#xA;    3.2214   12.5874&#xA;    3.4178   12.6011&#xA;    3.6928   12.6298&#xA;    3.8892   12.5994&#xA;    4.1642   12.5542&#xA;    4.3607   12.5734&#xA;    4.3607   12.6243&#xA;    4.5571   12.6398&#xA;&#xA;    0.0000   12.7876&#xA;    0.1964   12.8193&#xA;    0.4714   12.8074&#xA;    0.6679   12.8256&#xA;    0.9429   12.7655&#xA;    1.1393   12.7754&#xA;    2.1214   12.8607&#xA;    2.3178   12.8446&#xA;    3.2214   12.6391&#xA;    3.4178   12.6470&#xA;    3.6928   12.6876&#xA;    3.8892   12.6897&#xA;    4.1642   12.7080&#xA;    4.3607   12.7051&#xA;    4.3607   12.7275&#xA;    4.5571   12.6713&#xA;&#xA;    0.0000   13.1004&#xA;    0.1964   13.0722&#xA;    0.4714   13.0366&#xA; 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   3.8892   13.2698&#xA;    4.1642   13.2274&#xA;    4.3607   13.2233&#xA;    4.3607   13.3359&#xA;    4.5571   13.3361&#xA;&#xA;    0.0000   13.4133&#xA;    0.1964   13.4857&#xA;    0.4714   13.3373&#xA;    0.6679   13.3744&#xA;    0.9429   13.3998&#xA;    1.1393   13.3719&#xA;    2.1214   13.4157&#xA;    2.3178   13.4540&#xA;    3.2214   13.4500&#xA;    3.4178   13.3922&#xA;    3.6928   13.5096&#xA;    3.8892   13.5470&#xA;    4.1642   13.6396&#xA;    4.3607   13.6385&#xA;    4.3607   13.4464&#xA;    4.5571   13.4663&#xA;&#xA;    0.0000   13.4133&#xA;    0.1964   13.4857&#xA;    0.4714   13.4273&#xA;    0.6679   13.4688&#xA;    0.9429   13.5913&#xA;    1.1393   13.6096&#xA;    2.1214   13.6823&#xA;    2.3178   13.6929&#xA;    3.2214   13.5383&#xA;    3.4178   13.4839&#xA;    3.6928   13.7806&#xA;    3.8892   13.7301&#xA;    4.1642   13.7872&#xA;    4.3607   13.8334&#xA;    4.3607   13.6995&#xA;    4.5571   13.6610&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="6055" LastEditDate="2023-09-12T19:02:12.753" LastActivityDate="2023-09-12T19:02:12.753" Title="How to know if the band calculation result is correct?" Tags="|quantum-espresso|band-structure|bandgap|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-27T16:56:45.697" ContentLicense="CC BY-SA 4.0" />
  <row Id="11621" PostTypeId="2" ParentId="11608" CreationDate="2023-09-12T20:09:31.003" Score="3" Body="&lt;p&gt;Using Quantum ESPRESSO, you can follow one of several routes to calculate the band structure of your material. The number of input files depends on the specific path that you follow. All routes have almost the same structure. You first obtain the electronic ground state by doing an SCF calculation and then perform the post-processing to get the bands. Two of the most common ways to achieve this are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The first way is to do a &lt;code&gt;pw.x&lt;/code&gt; scf calculation with uniform k-mesh and smearing, then a &lt;code&gt;pw.x&lt;/code&gt; bands calculation with k-points corresponding to you material's band structure (&lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2010.05.010&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; is an excellent reference), then a &lt;code&gt;bands.x&lt;/code&gt; post-processing to obtain the band structure data. Now to plot the output data, you can either use &lt;code&gt;plotband.x&lt;/code&gt; (basic plot) or use your own script for improved quality and features.&lt;/li&gt;&#xA;&lt;li&gt;The second way is to do a &lt;code&gt;pw.x&lt;/code&gt; calculation with no smearing, then a &lt;code&gt;pw.x&lt;/code&gt; nscf calculation with dense k-mesh, then a &lt;code&gt;pw.x&lt;/code&gt; bands calculation with specific k-points, and then the post-processing stuff same as before.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The first way takes less time, computationally easy to converge but slightly inaccurate. The second way has an additional step, takes more time to converge but relatively more accurate. Below, I am listing the input files needed for the first workflow. If you need more accuracy, you can prepare the input files accordingly by doing some modifications.&lt;/p&gt;&#xA;&lt;p&gt;I have downloaded the CIF file you provided. Assuming it's a periodic structure, I have prepared a input file using &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum ESPRESSO input generator&lt;/a&gt;. You need to run this input using &lt;code&gt;pw.x&lt;/code&gt; executable.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './outdir/'&#xA;  prefix = 'mmse'&#xA;  pseudo_dir = './pseudo/'&#xA;  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  nat = 20&#xA;  ntyp = 4&#xA;  ecutrho =   400&#xA;  ecutwfc =   50&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss =   0.001&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1d-8&#xA;/&#xA;ATOMIC_SPECIES&#xA;Ca     40.078    ca_pbesol_v1.uspp.F.UPF&#xA;O      15.999    O.pbesol-n-kjpaw_psl.0.1.UPF&#xA;P      30.973    P.pbesol-n-rrkjus_psl.1.0.0.UPF&#xA;Si     28.085    Si.pbesol-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;Si           0.0000000000       0.0000000000       0.5000000000 &#xA;Si           0.0000000000       0.0000000000       0.0000000000 &#xA;Ca           0.6666670000       0.3333330000       0.3797950000 &#xA;P            0.3333330000       0.6666670000       0.6202050000 &#xA;P            0.3333330000       0.6666670000       0.8797950000 &#xA;P            0.6666670000       0.3333330000       0.1202050000 &#xA;O            0.2652530000       0.3303280000       0.5860850000 &#xA;O            0.6696720000       0.9349250000       0.5860850000 &#xA;O            0.7347470000       0.6696720000       0.0860850000 &#xA;O            0.3303280000       0.0650750000       0.4139150000 &#xA;O            0.6666670000       0.3333330000       0.2500000000 &#xA;O            0.9349250000       0.2652530000       0.0860850000 &#xA;O            0.6696720000       0.9349250000       0.9139150000 &#xA;O            0.9349250000       0.2652530000       0.4139150000 &#xA;O            0.0650750000       0.7347470000       0.5860850000 &#xA;O            0.3303280000       0.0650750000       0.0860850000 &#xA;O            0.2652530000       0.3303280000       0.9139150000 &#xA;O            0.0650750000       0.7347470000       0.9139150000 &#xA;O            0.7347470000       0.6696720000       0.4139150000 &#xA;O            0.3333330000       0.6666670000       0.7500000000 &#xA;K_POINTS automatic&#xA;8 8 3 0 0 0&#xA;CELL_PARAMETERS angstrom&#xA;      4.7132930000       0.0000000000       0.0000000000&#xA;     -2.3566465000       4.0818314735       0.0000000000&#xA;      0.0000000000       0.0000000000      11.9970890000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, you must take notes of few things. The &lt;code&gt;ecutwfc&lt;/code&gt; and k-mesh parameter must be converged. A not great but somewhat reasonable method is to start from maybe 30 Ry and then increase it by 10 Ry up to 100 Ry and check at which &lt;code&gt;ecutwfc&lt;/code&gt; you are getting an energy difference less than 0.1 mRy. Choose that as your &lt;code&gt;ecutwfc&lt;/code&gt; in the actual calculation. The same goes for k-mesh. &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11611/6055&quot;&gt;Camps' answer&lt;/a&gt; contains some very helpful link where you will get some bash script that does these things automatically for you. Check those please.&lt;/p&gt;&#xA;&lt;p&gt;The second thing you have to take care is the pseudopotentials. Change them according to the ones you have access to. They should be in a directory called &lt;code&gt;pseudo&lt;/code&gt;. I have taken these pseudopotentials from Standard solid-state pseudopotentials &lt;a href=&quot;https://www.materialscloud.org/discover/sssp/table/efficiency&quot; rel=&quot;nofollow noreferrer&quot;&gt;SSSP&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;After running this calculation, you will have a directoty called &lt;code&gt;outdir&lt;/code&gt; and an output file also. See the number of &lt;code&gt;Kohn-Sham states&lt;/code&gt; from the output file. Multiply that number with 1.3 (if you are trying to get a non-spin polarised/regular band structure) or 2.5 (if you are looking for a spin-polarised band structure). These numbers are not strict. Choose an integer value close to the number you obtained after multiplication as the &lt;code&gt;nbnd&lt;/code&gt; value. Now, run the &lt;code&gt;pw.x&lt;/code&gt; calculation again with band structure&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'bands'&#xA;  outdir = './outdir/'&#xA;  prefix = 'mmse'&#xA;  pseudo_dir = './pseudo/'&#xA;  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  nbnd = !follow the above written instruction&#xA;  ibrav = 0&#xA;  nat = 20&#xA;  ntyp = 4&#xA;  ecutrho =   400&#xA;  ecutwfc =   50&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss =   0.001&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1d-8&#xA;/&#xA;ATOMIC_SPECIES&#xA;Ca     40.078    ca_pbesol_v1.uspp.F.UPF&#xA;O      15.999    O.pbesol-n-kjpaw_psl.0.1.UPF&#xA;P      30.973    P.pbesol-n-rrkjus_psl.1.0.0.UPF&#xA;Si     28.085    Si.pbesol-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;Si           0.0000000000       0.0000000000       0.5000000000 &#xA;Si           0.0000000000       0.0000000000       0.0000000000 &#xA;Ca           0.6666670000       0.3333330000       0.3797950000 &#xA;P            0.3333330000       0.6666670000       0.6202050000 &#xA;P            0.3333330000       0.6666670000       0.8797950000 &#xA;P            0.6666670000       0.3333330000       0.1202050000 &#xA;O            0.2652530000       0.3303280000       0.5860850000 &#xA;O            0.6696720000       0.9349250000       0.5860850000 &#xA;O            0.7347470000       0.6696720000       0.0860850000 &#xA;O            0.3303280000       0.0650750000       0.4139150000 &#xA;O            0.6666670000       0.3333330000       0.2500000000 &#xA;O            0.9349250000       0.2652530000       0.0860850000 &#xA;O            0.6696720000       0.9349250000       0.9139150000 &#xA;O            0.9349250000       0.2652530000       0.4139150000 &#xA;O            0.0650750000       0.7347470000       0.5860850000 &#xA;O            0.3303280000       0.0650750000       0.0860850000 &#xA;O            0.2652530000       0.3303280000       0.9139150000 &#xA;O            0.0650750000       0.7347470000       0.9139150000 &#xA;O            0.7347470000       0.6696720000       0.4139150000 &#xA;O            0.3333330000       0.6666670000       0.7500000000 &#xA;K_POINTS crystal&#xA;394&#xA;!I have truncuated the full list of 394 k-points and included only 5 of them&#xA;!Upload your CIF to https://www.materialscloud.org/work/tools/seekpath &#xA;!And get the full list of 394 k-points. Copy-paste them here&#xA;    0.0000000000     0.0000000000     0.0000000000 1&#xA;    0.0172413793     0.0000000000     0.0000000000 1&#xA;    0.0344827586     0.0000000000     0.0000000000 1&#xA;    0.0517241379     0.0000000000     0.0000000000 1&#xA;    0.0689655172     0.0000000000     0.0000000000 1&#xA;    0.0862068966     0.0000000000     0.0000000000 1&#xA;!I have truncuated the full list of 394 k-points and included only 5 of them&#xA;!Upload your CIF to https://www.materialscloud.org/work/tools/seekpath &#xA;!And get the full list of 394 k-points. Copy-paste them here&#xA;&#xA;CELL_PARAMETERS angstrom&#xA;      4.7132930000       0.0000000000       0.0000000000&#xA;     -2.3566465000       4.0818314735       0.0000000000&#xA;      0.0000000000       0.0000000000      11.9970890000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, you have successfully calculated the ground state. You can post-process the data needed to get the band structure using &lt;code&gt;bands.x&lt;/code&gt;. For that, run the following input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;bands&#xA;  outdir='./outdir/'&#xA;  prefix='mmse'&#xA;  filband='Your_material.dat'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will generate at least two files: a &lt;code&gt;Your_material.dat&lt;/code&gt; file which contains data suitable to plot with &lt;code&gt;plotband.x&lt;/code&gt; executables, and a &lt;code&gt;Your_material.dat.gnu&lt;/code&gt; file which can be directly plotted using gnuplot/xmgrace type of software. Let's take a look at how to do this using &lt;code&gt;plotband.x&lt;/code&gt;. First, take a note of the Fermi energy from the scf output file. Do:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ grep -e 'Fermi' your_output_file.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You will see the Fermi energy from here. Then type &lt;code&gt;plotband.x&lt;/code&gt; in the command line. It will give you the band extrema values. Type those or other pair of values if you wanna modify the range. &lt;code&gt;plotband.x&lt;/code&gt; is interactive, so it will ask you the Fermi energy, deltaE etc. one by one. Provide those info and you will get several data files and a &lt;code&gt;.ps&lt;/code&gt; file containing the band structure image. If you need a fancier plot, use &lt;a href=&quot;https://github.com/quantumNerd/Quantum-Espresso-Tutorial-2019-Projects/tree/master/tools/plot_band&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; python script.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, &lt;code&gt;plotband.x&lt;/code&gt; can also be executed using an input file. The input file should look like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;X.bands.dat    !name of the input data file which is the output of bands.x&#xA;-20 20         !lower and upper level of band in eV&#xA;X.bands.xmgr   !output image file (choose anything)&#xA;X.bands.ps     !output image file (choose anything)&#xA;0.0000         !Fermi level&#xA;0.0 0.0000     !DeltaE(interval between axis labels/ticks) and Fermi level offset (to set it as 0)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So in summary, if you carefully prepared all the input files, you can get the band structure by running the following commands. If you are using more than 1 processor, use &lt;code&gt;mpirun -np&lt;/code&gt; or other mpi executables accordingly before the QE executables and specify the # of the processors.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pw.x &amp;lt; material.scf.in |tee material.scf.out&#xA;&#xA;pw.x &amp;lt; material.bands.in |tee material.bands.out&#xA;&#xA;bands.x &amp;lt; material.bands.pp.in |tee material.bands.pp.out&#xA;&#xA;plotband.x &amp;lt; material.plotband.in |tee material.plotband.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-09-12T20:09:31.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11622" PostTypeId="1" CreationDate="2023-09-13T17:28:47.290" Score="1" ViewCount="15" Body="&lt;p&gt;I am analyzing the bonding interactions within the [XeF5]- anion (B3YLP/def2-TZVP), and I am using an OPDOS (overlap population density-of-states) plot to formalize the degree of bonding/antibonding interactions within the molecular orbitals. I would like to categorize the molecular orbitals as bonding/nonbonding/antibonding.&lt;/p&gt;&#xA;&lt;p&gt;Bonding interactions are OPDOS &amp;gt; 0, antibonding is OPDOS &amp;lt; 0, and true nonbonding is OPDOS = 0, however it is common for literature to say an orbital is &amp;quot;slightly bonding&amp;quot; or &amp;quot;mostly nonbonding&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Is there a threshold that is commonly used in literature (arbitrary or not) for the characterization of the degree nonbonding (i.e. anything within OPDOS = ±0.01 is called nonbonding)? I have searched the literature with no avail.&lt;/p&gt;&#xA;&lt;p&gt;Any help is appreciated!&#xA;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-09-13T17:28:47.290" Title="Is there a threshold for calling an interaction nonbonding on an OPDOS (overlap population density-of-states) plot?" Tags="|density-functional-theory|density-of-states|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:21:32.903" ContentLicense="CC BY-SA 4.0" />
  <row Id="11623" PostTypeId="2" ParentId="11600" CreationDate="2023-09-13T17:47:49.703" Score="4" Body="&lt;p&gt;&lt;a href=&quot;https://www.wiley.com/en-us/Molecular+Electronic+Structure+Theory-p-9781118531471&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;Molecular Electronic-Structure Theory&lt;/em&gt;&lt;/a&gt;, by Helgaker et al., is an extremely comprehensive textbook reference for electronic structure on finite systems. I take the following from Section 10.8.3 (pp. 481–482).&lt;/p&gt;&#xA;&lt;p&gt;This section provides an expression for the gradient in terms of the generalized Fock matrix&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{mn} = \sum_\sigma \langle \text{CSF} \vert a_{m\sigma}^\dagger [ a_{n\sigma}, H] \vert \text{CSF} \rangle;&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for real orbitals, at least, the gradient can be written as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_{mn}^{(1)} = 2(F_{mn} - F_{nm}).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The following equations, (10.8.19–10.8.23), provide expressions for the generalized Fock matrix in terms of one- and two-electron integrals. For the Hamiltonian&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = \sum_{pq} h_{pq} E_{pq} + \frac12 \sum_{pqrs} g_{pqrs} e_{pqrs} + h_{nuc},&#xA;$$&lt;/span&gt;&#xA;recall that the Fock matrix is defined in terms of &lt;span class=&quot;math-container&quot;&gt;$a_{m\sigma}^\dagger[a_{n\sigma}, H]$&lt;/span&gt;, so that&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{mn} = \langle \text{CSF} \vert \sum_\sigma a_{m\sigma}^\dagger[a_{n\sigma}, H] \vert \text{CSF} \rangle = \langle \text{CSF} \vert \sum_q h_{nq} E_{mq} + \sum_{qrs} g_{nqrs} e_{mqrs} \vert \text{CSF} \rangle,&#xA;$$&lt;/span&gt;&#xA;then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{mn} = \sum_q D_{mq} h_{nq} + \sum_{qrs} d_{mqrs} g_{nqrs},&#xA;$$&lt;/span&gt;&#xA;where by definition&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;D_{pq} = \langle \text{CSF} \vert E_{pq} \vert \text{CSF} \rangle, \\&#xA;d_{pqrs} = \langle \text{CSF} e_{pqrs} \vert \text{CSF} \rangle..&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you prefer, you can also get the gradient in terms of Roothan–Hall-style equations (Eq. 10.7.80).&lt;/p&gt;&#xA;&lt;p&gt;Note (Section 2.5 of &lt;a href=&quot;https://www.wiley.com/en-us/Molecular+Electronic+Structure+Theory-p-9781118531471&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, pp. 51–53) that &lt;span class=&quot;math-container&quot;&gt;$\lvert \text{CSF} \rangle$&lt;/span&gt; refers to a &lt;em&gt;configuration state function&lt;/em&gt;, which is a spin-adapted modification of the Slater determinant. Construction of these is detailed in Section 2.6.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-09-13T17:47:49.703" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11624" PostTypeId="1" CreationDate="2023-09-13T18:46:01.187" Score="1" ViewCount="256" Body="&lt;p&gt;I have an .xyz file containing an alumina surface and a water box placed above the surface. I am trying to setup a LAMMPS calculation using CLAYFF, and I need to remove bonds between Al and O atoms, and the corresponding Al-O-Al and O-Al-O terms. From the &lt;a href=&quot;https://sites.google.com/site/akohlmey/software/topotools/documentation&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation for Topotools&lt;/a&gt; I found that it is possible to remove bonds between individual atoms. I can technically brute force removing the bonds and the angles, but I would like a cleaner solution for this problem. If there are any commands that can automatically do this transformation in VMD, that would solve my problem.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-09-13T18:46:01.187" Title="How to remove bonds between specific atoms in VMD" Tags="|lammps|vmd|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-27T22:11:46.930" ContentLicense="CC BY-SA 4.0" />
  <row Id="11625" PostTypeId="1" CreationDate="2023-09-14T01:53:19.990" Score="3" ViewCount="172" Body="&lt;p&gt;Here is a little python code that loops through a molecular dynamics trajectory (performed with the ASE package) and outputs the forces on the atoms at each frame:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;traj = read('output.traj', index=':')&#xA;&#xA;counter = 0&#xA;for atoms in traj:&#xA;    forces = atoms.get_forces()&#xA;    print(&amp;quot;forces: &amp;quot;,forces)&#xA;&#xA;    print(&amp;quot;counter: &amp;quot;, counter)&#xA;    counter = counter + 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is all well and good... but I'm not sure what the units are on the forces that are outputted.&lt;/p&gt;&#xA;&lt;p&gt;According to the documentation, the units from &lt;code&gt;get_forces()&lt;/code&gt; depends on the calculator that is attached to the &lt;code&gt;atoms&lt;/code&gt; object: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms.get_forces&quot; rel=&quot;nofollow noreferrer&quot;&gt;Docs_get_forces&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I didn't specify a calculator in my little code snippet and it outputted the forces anyway. I tried to check the calculator used by adding these lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;calculator = atoms.get_calculator()&#xA;print(calculator)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;According to this, the calculator attached to my atoms is &lt;code&gt;SinglePointCalculator&lt;/code&gt;. But when I looked up the source code for this calculator, I can't find where the &lt;code&gt;get_forces()&lt;/code&gt; calculation is being done, or any of the units associated with it.&lt;/p&gt;&#xA;&lt;p&gt;TLDR; What are the default force units outputted by ASE?&#xA;Thank you for your help.&lt;/p&gt;&#xA;" OwnerUserId="3973" LastEditorUserId="6687" LastEditDate="2023-09-14T08:16:19.843" LastActivityDate="2023-09-14T08:16:19.843" Title="How to check the units from ASE get_forces() function?" Tags="|molecular-dynamics|atomic-simulation-environment|intermolecular-forces|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11626" PostTypeId="1" AcceptedAnswerId="11647" CreationDate="2023-09-14T14:18:55.770" Score="4" ViewCount="172" Body="&lt;p&gt;Good evening everyone,&#xA;With previous Transiesta versions, we would not have issues with finding the transport involving graphene. However, this was not the case with the latest version. We tried:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Decreasing energy cut off&lt;/li&gt;&#xA;&lt;li&gt;Atomic force&lt;/li&gt;&#xA;&lt;li&gt;Mixing pulay mixing factor&lt;/li&gt;&#xA;&lt;li&gt;Changing BasisSize to less accurate ones DPZ to DZ&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Despite getting perfect electrode cells and doing the analyze step. We relaxed our structure even and yet transiesta does not converge. I was wondering if we could get any advice on what further can we try.&lt;/p&gt;&#xA;&lt;p&gt;Transport system via the attached POSCAR file&#xA;&lt;a href=&quot;https://i.stack.imgur.com/gthgJ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gthgJ.png&quot; alt=&quot;Transport system from the scattering.fdf file&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the fdf file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;************************** Dump of input data file ****************************&#xA;SystemLabel scattering&#xA;SystemName scattering&#xA;SolutionMethod        Transiesta&#xA;%block ChemicalSpeciesLabel&#xA; 1 6 C&#xA;%endblock ChemicalSpeciesLabel&#xA;# Basis set variables&#xA;PAO.BasisType split&#xA;PAO.BasisSize       DZ&#xA;XC.functional   GGA&#xA;XC.Authors    PBE&#xA;# K-points&#xA;%block kgrid_Monkhorst_Pack&#xA;100 0   0   0.0&#xA;0   1   0   0.0&#xA;0   0   1   0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;NumberOfSpecies        1&#xA;NumberOfAtoms         94&#xA;#Structure&#xA;LatticeConstant 1.0 Ang&#xA;%block LatticeVectors&#xA; 29.03931999 0.00000000 0.00000000&#xA; -4.83546051 8.59115145 0.00000000&#xA; -0.00002410 0.00001178 15.08028603&#xA;%endblock LatticeVectors&#xA;NumberOfAtoms 94&#xA;AtomicCoordinatesFormat Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;  0.12180800  1.37371700  7.54014700 1 #  1: C&#xA; -1.08712900  3.52144600  7.54014400 1 #  2: C&#xA; -2.29594100  5.66906700  7.54014100 1 #  3: C&#xA; -3.50470500  7.81692300  7.54014400 1 #  4: C&#xA;  2.54169800  1.37367700  7.54014300 1 #  5: C&#xA;  1.33279500  3.52150200  7.54014200 1 #  6: C&#xA;  0.12401700  5.66921400  7.54013900 1 #  7: C&#xA; -1.08484900  7.81693700  7.54013900 1 #  8: C&#xA;  4.96169300  1.37364700  7.54014400 1 #  9: C&#xA;  3.75284800  3.52153100  7.54014400 1 # 10: C&#xA;  2.54396900  5.66927600  7.54014300 1 # 11: C&#xA;  1.33514600  7.81696200  7.54014300 1 # 12: C&#xA;  7.38172100  1.37357900  7.54014700 1 # 13: C&#xA;  6.17284200  3.52134200  7.54014400 1 # 14: C&#xA;  4.96404200  5.66919200  7.54014500 1 # 15: C&#xA;  3.75522200  7.81698300  7.54014800 1 # 16: C&#xA;  1.32751800  0.64790300  7.54014500 1 # 17: C&#xA;  0.11859500  2.79581700  7.54014400 1 # 18: C&#xA; -1.09017100  4.94343700  7.54014100 1 # 19: C&#xA; -2.29901000  7.09112400  7.54014100 1 # 20: C&#xA;  3.74748600  0.64788400  7.54014200 1 # 21: C&#xA;  2.53860000  2.79579200  7.54014300 1 # 22: C&#xA;  1.32975200  4.94351300  7.54014100 1 # 23: C&#xA;  0.12092800  7.09123400  7.54013900 1 # 24: C&#xA;  6.16750000  0.64786200  7.54014500 1 # 25: C&#xA;  4.95859900  2.79571400  7.54014500 1 # 26: C&#xA;  3.74974100  4.94359000  7.54014500 1 # 27: C&#xA;  2.54095900  7.09134600  7.54014500 1 # 28: C&#xA;  8.58752100  0.64794400  7.54014900 1 # 29: C&#xA;  7.37857000  2.79562700  7.54014500 1 # 30: C&#xA;  6.16974300  4.94336400  7.54014300 1 # 31: C&#xA;  4.96094600  7.09124600  7.54014600 1 # 32: C&#xA;  9.80884929  1.28428982  7.54014751 1 #  1: C&#xA;  8.90792584  3.50100431  7.54014661 1 #  2: C&#xA;  7.56949711  5.62164311  7.54014930 1 #  3: C&#xA;  6.16488123  7.71072851  7.54014661 1 #  4: C&#xA; 12.04587741  1.35268747  7.54015470 1 #  5: C&#xA; 10.08577592  5.84389795  7.54015110 1 #  6: C&#xA;  8.51641225  7.86878636  7.54015380 1 #  7: C&#xA; 14.38130760  1.54842976  7.54015650 1 #  8: C&#xA; 12.88146544  3.61208026  7.54015380 1 #  9: C&#xA; 11.68798911  5.89703111  7.54015200 1 # 10: C&#xA; 10.83584711  8.08077261  7.54015110 1 # 11: C&#xA; 16.82711483  1.57341314  7.54015829 1 # 12: C&#xA; 15.48024078  3.67471390  7.54015650 1 # 13: C&#xA; 14.21442898  5.78377347  7.54015470 1 # 14: C&#xA; 13.19035357  7.98584050  7.54015290 1 # 15: C&#xA; 10.95285593  0.50411198  7.54014930 1 # 16: C&#xA; 10.10182400  2.68744344  7.54015200 1 # 17: C&#xA;  8.90802873  4.97178466  7.54015020 1 # 18: C&#xA;  7.40721639  7.03732497  7.54015380 1 # 19: C&#xA; 13.27309110  0.71560811  7.54015560 1 # 20: C&#xA; 11.70473809  2.74008629  7.54015380 1 # 21: C&#xA;  9.74336705  7.23108759  7.54014571 1 # 22: C&#xA; 15.62332254  0.87474637  7.54015739 1 # 23: C&#xA; 14.22086730  2.96370171  7.54015560 1 # 24: C&#xA; 12.88151893  5.08354039  7.54015380 1 # 25: C&#xA; 11.98042401  7.30045498  7.54015200 1 # 26: C&#xA; 18.02944081  0.82533015  7.54015919 1 # 27: C&#xA; 16.75488228  2.98438201  7.54015739 1 # 28: C&#xA; 15.47703940  5.08859455  7.54015560 1 # 29: C&#xA; 14.35553266  7.21529680  7.54015380 1 # 30: C&#xA; 19.27907400  1.47658400  7.54015000 1 #  1: C&#xA; 18.07010900  3.62423600  7.54016000 1 #  2: C&#xA; 16.86122900  5.77208000  7.54014500 1 #  3: C&#xA; 15.65245300  7.91986400  7.54012500 1 #  4: C&#xA; 21.69907900  1.47651500  7.54012600 1 #  5: C&#xA; 20.49015900  3.62427200  7.54017100 1 #  6: C&#xA; 19.28135500  5.77207800  7.54019200 1 #  7: C&#xA; 18.07239600  7.91986900  7.54013700 1 #  8: C&#xA; 24.11903300  1.47635700  7.54013100 1 #  9: C&#xA; 22.91007900  3.62410100  7.54013500 1 # 10: C&#xA; 21.70123800  5.77204200  7.54017100 1 # 11: C&#xA; 20.49240600  7.91980600  7.54017600 1 # 12: C&#xA; 26.53895600  1.47636400  7.54013800 1 # 13: C&#xA; 25.33004600  3.62412800  7.54013300 1 # 14: C&#xA; 24.12118800  5.77191100  7.54014100 1 # 15: C&#xA; 22.91228600  7.91973500  7.54015600 1 # 16: C&#xA; 20.48474800  0.75084200  7.54013400 1 # 17: C&#xA; 19.27585400  2.89867800  7.54016700 1 # 18: C&#xA; 18.06685600  5.04642600  7.54017200 1 # 19: C&#xA; 16.85806100  7.19413900  7.54012600 1 # 20: C&#xA; 22.90463300  0.75082000  7.54012300 1 # 21: C&#xA; 21.69564500  2.89854900  7.54014500 1 # 22: C&#xA; 20.48690900  5.04630000  7.54018600 1 # 23: C&#xA; 19.27807600  7.19423700  7.54017800 1 # 24: C&#xA; 25.32460700  0.75062400  7.54014800 1 # 25: C&#xA; 24.11574700  2.89843600  7.54012800 1 # 26: C&#xA; 22.90677300  5.04622800  7.54014600 1 # 27: C&#xA; 21.69792400  7.19407500  7.54017500 1 # 28: C&#xA; 27.74460500  0.75071600  7.54014900 1 # 29: C&#xA; 26.53568700  2.89842400  7.54013700 1 # 30: C&#xA; 25.32680600  5.04620300  7.54013900 1 # 31: C&#xA; 24.11798200  7.19407500  7.54014300 1 # 32: C&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;NumberOfSpecies 1&#xA;%block ChemicalSpeciesLabel&#xA; 1 6 C&#xA;%endblock ChemicalSpeciesLabel&#xA;SpinPolarized    true&#xA;# General variables&#xA;MeshCutoff    200.0 Ry&#xA;MaxSCFIterations     100000&#xA;DM.MixingWeight       0.05          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.0E-4         # Tolerance in maximum difference&#xA;DM.UseSaveDM          true          # to use continuation files&#xA;DM.NumberPulay         6&#xA;PAO.SplitNorm    0.150000&#xA;PAO.EnergyShift    0.005000  Ry&#xA;# MD variables&#xA;MD.MaxForceTol 0.01 eV/Ang&#xA;MD.TypeOfRun        CG&#xA;MD.VariableCell     false&#xA;MD.NumCGSteps        0&#xA;MD.InitialTimeStep      1&#xA;MD.FinalTimeStep        1&#xA;MD.LengthTimeStep       1 fs&#xA;ElectronicTemperature 300 K&#xA;MD.MaxCGDispl 0.05 Bohr&#xA;SaveRho     true&#xA;SaveDeltaRho        true&#xA;UseSaveData     true&#xA;WriteCoorInital    true&#xA;WriteCoorStep    true&#xA;WriteForces     true&#xA;WriteKpoints        true&#xA;WriteEigenvalues        true&#xA;WriteKbands     true&#xA;WriteBands      true&#xA;WriteWaveFunctions      false&#xA;WriteMullikenPop        1&#xA;WriteDM     true&#xA;WriteCoorXmol       true&#xA;WriteCoorCerius     true&#xA;WriteMDXmol     true&#xA;WriteMDhistory      true&#xA;Diag.ParallelOverK  true&#xA;######TRANSIESTAPARAMETERS#####&#xA;TS.Voltage 0 eV&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.C-Left&#xA;  part circle&#xA;   from -40. eV + V/2 to -10 kT + V/2&#xA;     points 25&#xA;      method g-legendre&#xA;       opt right&#xA;%endblock TS.Contour.C-Left&#xA;%block TS.Contour.T-Left&#xA;  part tail&#xA;   from prev to inf&#xA;     points 10&#xA;      method g-fermi&#xA;%endblock TS.Contour.T-Left&#xA;%block TS.Contour.C-Right&#xA;  part circle&#xA;   from -40. eV -V/2 to -10 kT -V/2&#xA;     points 25&#xA;      method g-legendre&#xA;       opt right&#xA;%endblock TS.Contour.C-Right&#xA;%block TS.Contour.T-Right&#xA;  part tail&#xA;   from prev to inf&#xA;     points 10&#xA;      method g-fermi&#xA;%endblock TS.Contour.T-Right&#xA;%block TS.Contours.nEq&#xA;  neq-1&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq-1&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;     delta 0.01 eV&#xA;      method mid-rule&#xA;%endblock TS.Contour.nEq.neq-1&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;%block TS.Elec.Left&#xA;  TSHS ./left.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a1&#xA;  elec-pos begin 1&#xA;%endblock TS.Elec.Left&#xA;%block TS.Elec.Right&#xA;  TSHS ./right.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir +a1&#xA;  elec-pos end -1&#xA;%endblock TS.Elec.Right&#xA;# TBtrans options&#xA;TBT.T.Eig 9&#xA;TBT.Elecs.Eta    0.0001000000 eV&#xA;%block TBT.Contours&#xA;  neq&#xA;%endblock TBT.Contours&#xA;%block TBT.Contour.neq&#xA;  part line&#xA;   from   -0.50000 eV to    0.50000 eV&#xA;    delta    0.00990 eV&#xA;     method mid-rule&#xA;%endblock TBT.Contour.neq&#xA;TBT.DOS.A T&#xA;TS.BTD.Pivot orb+none&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am happy to provide the files if needed but stack exchange does not seem to give this option.&lt;/p&gt;&#xA;&lt;p&gt;Cheers,&#xA;EL-Abed&lt;/p&gt;&#xA;&lt;p&gt;#############################################################UPDATE&lt;/p&gt;&#xA;&lt;p&gt;MAINLY WE HAVE CHANGED THE SYSTEM BY INCREASING THE NUMBER OF ELECTRODE LAYERS AND CHANGED THE MIXING FACTOR. THANK YOU ALL!&#xA;#############################################################&lt;/p&gt;&#xA;" OwnerUserId="604" LastEditorUserId="604" LastEditDate="2023-11-16T00:28:06.407" LastActivityDate="2023-11-16T00:28:06.407" Title="Transiesta with siesta version 4.1.5 not converging" Tags="|density-functional-theory|siesta|electronic-transport|graphene|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11627" PostTypeId="1" CreationDate="2023-09-14T21:56:02.553" Score="2" ViewCount="64" Body="&lt;p&gt;I have one query about the NiO structure. As per the literature, NiO is a rocksalt type of structure ( NaCl type) and exhibits an antiferromagnetic ordering of type-II cubic (fcc). I considered the same structure in my calculations and found that the FM state is more stable instead of AFM. After searching on vaspwiki (vasp.at-wiki-index.php-NiO), I found that the rhombohedral structure (a=b=c, alpha=beta=gamma= 33.5573) of NiO is considered. I tried with the rhombohedral structure of NiO and found the AFM state is more stable. I am not able to understand which structure I should consider for further studies. Also, I found in the cubic structure, type-II AFM ordering is not possible to obtain. In this case, how do we justify our experimental results corresponding to cubic NiO if one is considering the rhombohedral structure? If anyone is familiar with this, please suggest.&lt;/p&gt;&#xA;" OwnerUserId="5256" LastEditorUserId="5256" LastEditDate="2023-09-14T23:07:25.147" LastActivityDate="2023-09-14T23:07:25.147" Title="Query about NiO structure" Tags="|density-functional-theory|vasp|physical-properties-of-materials|materials-design|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11628" PostTypeId="1" CreationDate="2023-09-15T02:51:02.647" Score="2" ViewCount="45" Body="&lt;p&gt;Cross-posted &lt;a href=&quot;https://scicomp.stackexchange.com/q/43234/27325&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have the following listing for a barebone MD simulation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#include &amp;lt;iostream&amp;gt;&#xA;#include &amp;lt;vector&amp;gt;&#xA;#include &amp;lt;cmath&amp;gt;&#xA;#include &amp;lt;random&amp;gt;&#xA;#include &amp;lt;fstream&amp;gt;&#xA;&#xA;typedef double real;&#xA;&#xA;// Constants for Argon&#xA;constexpr real epsilon = 119.8;   // Depth of the potential well (in K)&#xA;constexpr real sigma = 3.405;     // Distance for zero potential (in Angstrom)&#xA;constexpr real mass = 39.948;     // Mass of Argon (in amu)&#xA;&#xA;struct Trajectory&#xA;{&#xA;    int step_no;&#xA;    real position_x;&#xA;    real position_y;&#xA;    real position_z;&#xA;    real velocity_x;&#xA;    real velocity_y;&#xA;    real velocity_z;&#xA;    real temperature;&#xA;};&#xA;&#xA;struct Energy&#xA;{&#xA;    int step_no;&#xA;    real Total_energy;&#xA;    real Poten_energy;&#xA;    real Pot_engy_repulsive;&#xA;    real Pot_engy_attractive;&#xA;    real Pot_engy_balloon;&#xA;    real Kinetic_engy;&#xA;};&#xA;&#xA;struct Vec3&#xA;{&#xA;    real x;&#xA;    real y;&#xA;    real z;&#xA;};&#xA;&#xA;struct DataSet &#xA;{&#xA;    std::vector&amp;lt;real&amp;gt; VecX;&#xA;    std::vector&amp;lt;real&amp;gt; VecY;&#xA;    std::vector&amp;lt;real&amp;gt; VecZ;&#xA;};&#xA;&#xA;void writeEnergyToFile(const std::string&amp;amp; filename, const Energy&amp;amp; energy)&#xA;{&#xA;    //TODO&#xA;}&#xA;&#xA;void writeTrajectoryToFile(const std::string&amp;amp; filename, const Trajectory&amp;amp; trajectory)&#xA;{&#xA;    //TODO&#xA;}&#xA;&#xA;// Initialize positions and velocities of particles&#xA;void initialize(int n_particles, DataSet&amp;amp; positionData, DataSet&amp;amp; velocityData, real boxSize, real maxVelocity)&#xA;{&#xA;    // Create a random number generator&#xA;    std::default_random_engine generator;&#xA;    std::uniform_real_distribution&amp;lt;real&amp;gt; distribution(-0.5, 0.5);&#xA;&#xA;    // Initialize positions and velocities&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        // Assign random initial positions within the box&#xA;        positionData.VecX[i] = boxSize * distribution(generator);&#xA;        positionData.VecY[i] = boxSize * distribution(generator);&#xA;        positionData.VecZ[i] = boxSize * distribution(generator);&#xA;&#xA;        // Assign random initial velocities up to max_vel&#xA;        velocityData.VecX[i] = maxVelocity * distribution(generator);&#xA;        velocityData.VecY[i] = maxVelocity * distribution(generator);&#xA;        velocityData.VecZ[i] = maxVelocity * distribution(generator);&#xA;    }&#xA;}&#xA;&#xA;// Derivative of the Lennard-Jones potential&#xA;Vec3 lj_force(Vec3 posVec)&#xA;{&#xA;    real r_mag = std::sqrt(posVec.x * posVec.x + posVec.y * posVec.y + posVec.z * posVec.z);&#xA;    real s_over_r = sigma / r_mag;&#xA;    real s_over_r6 = s_over_r * s_over_r * s_over_r * s_over_r * s_over_r * s_over_r;&#xA;    real s_over_r12 = s_over_r6 * s_over_r6;&#xA;    real factor = 24.0 * epsilon * (2.0 * s_over_r12 - s_over_r6) / (r_mag * r_mag * r_mag);&#xA;&#xA;    Vec3 force;&#xA;    force.x = factor * posVec.x;&#xA;    force.y = factor * posVec.y;&#xA;    force.z = factor * posVec.z;&#xA;    return force;&#xA;}&#xA;&#xA;// Update the 'accel' function&#xA;void accel(int n_particles, DataSet&amp;amp; accelData, DataSet&amp;amp; posData)&#xA;{&#xA;    // Reset the acceleration to zero&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        accelData.VecX[i] = 0.0;&#xA;        accelData.VecY[i] = 0.0;&#xA;        accelData.VecZ[i] = 0.0;&#xA;    }&#xA;&#xA;    // Compute the acceleration due to each pair&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        for (int j = i + 1; j &amp;lt; n_particles; j++)&#xA;        {&#xA;            Vec3 posVec;&#xA;            posVec.x = posData.VecX[j] - posData.VecX[i];&#xA;            posVec.y = posData.VecY[j] - posData.VecY[i];&#xA;            posVec.z = posData.VecZ[j] - posData.VecZ[i];&#xA;            Vec3 force = lj_force(posVec);&#xA;            // use Lennard-Jones force law&#xA;            accelData.VecX[i] += force.x / mass;&#xA;            accelData.VecY[i] += force.y / mass;&#xA;            accelData.VecZ[i] += force.z / mass;&#xA;            accelData.VecX[j] -= force.x / mass;&#xA;            accelData.VecY[j] -= force.y / mass;&#xA;            accelData.VecZ[j] -= force.z / mass;&#xA;        }&#xA;    }&#xA;}&#xA;&#xA;void leapfrog_step(int n_particles, DataSet&amp;amp; posData, DataSet&amp;amp; velocData, real dt) &#xA;{&#xA;    DataSet a;&#xA;&#xA;    accel(n_particles, a, posData); //compute acceleration&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        velocData.VecX[i] = velocData.VecX[i] + 0.5 * dt * a.VecX[i];    // advance vel by half-step&#xA;        velocData.VecY[i] = velocData.VecY[i] + 0.5 * dt * a.VecY[i];    // advance vel by half-step&#xA;        velocData.VecZ[i] = velocData.VecZ[i] + 0.5 * dt * a.VecZ[i];    // advance vel by half-step&#xA;&#xA;        posData.VecX[i] = posData.VecX[i] + dt * velocData.VecX[i];      // advance pos by full-step&#xA;        posData.VecY[i] = posData.VecY[i] + dt * velocData.VecY[i];      // advance pos by full-step&#xA;        posData.VecZ[i] = posData.VecZ[i] + dt * velocData.VecZ[i];      // advance pos by full-step&#xA;    }&#xA;&#xA;    accel(n_particles, a, posData); //compute acceleration&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        velocData.VecX[i] = velocData.VecX[i] + 0.5 * dt * a.VecX[i];    // and complete vel. step&#xA;        velocData.VecY[i] = velocData.VecY[i] + 0.5 * dt * a.VecY[i];    // and complete vel. step&#xA;        velocData.VecZ[i] = velocData.VecZ[i] + 0.5 * dt * a.VecZ[i];    // and complete vel. step&#xA;    }&#xA;}&#xA;int main()&#xA;{&#xA;    int n_particles = 10;  // number of particles&#xA;    real box_size = 10.0; // size of the simulation box&#xA;    real max_vel = 0.1;   // maximum initial velocity&#xA;    real dt = 0.01;   // time step&#xA;    int n_steps = 10000;   // number of time steps&#xA;                        &#xA;    DataSet posData; // Positions of the particles&#xA;    DataSet velData; // Velocities of the particles&#xA;&#xA;    // Initialize the particles&#xA;    initialize(n_particles, posData, velData, box_size, max_vel);&#xA;&#xA;    // Run the simulation&#xA;    for (int step = 0; step &amp;lt; n_steps; step++) &#xA;    {&#xA;        leapfrog_step(n_particles, posData, velData, dt);&#xA;    }&#xA;&#xA;    return 0;&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is the best place to compute &lt;code&gt;Trajectory&lt;/code&gt; and output it to a CSV file?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-09-15T15:51:14.350" LastActivityDate="2023-09-15T15:51:14.350" Title="Where should we compute `Trajectory` in this listing?" Tags="|molecular-dynamics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11629" PostTypeId="1" CreationDate="2023-09-15T04:12:10.747" Score="1" ViewCount="62" Body="&lt;p&gt;Cross-posted &lt;a href=&quot;https://scicomp.stackexchange.com/q/43234/27325&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have the following listing for a barebone MD simulation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#include &amp;lt;iostream&amp;gt;&#xA;#include &amp;lt;vector&amp;gt;&#xA;#include &amp;lt;cmath&amp;gt;&#xA;#include &amp;lt;random&amp;gt;&#xA;#include &amp;lt;fstream&amp;gt;&#xA;&#xA;typedef double real;&#xA;&#xA;// Constants for Argon&#xA;constexpr real epsilon = 119.8;   // Depth of the potential well (in K)&#xA;constexpr real sigma = 3.405;     // Distance for zero potential (in Angstrom)&#xA;constexpr real mass = 39.948;     // Mass of Argon (in amu)&#xA;&#xA;struct Trajectory&#xA;{&#xA;    int step_no;&#xA;    real position_x;&#xA;    real position_y;&#xA;    real position_z;&#xA;    real velocity_x;&#xA;    real velocity_y;&#xA;    real velocity_z;&#xA;    real temperature;&#xA;};&#xA;&#xA;struct Energy&#xA;{&#xA;    int step_no;&#xA;    real Total_energy;&#xA;    real Poten_energy;&#xA;    real Pot_engy_repulsive;&#xA;    real Pot_engy_attractive;&#xA;    real Pot_engy_balloon;&#xA;    real Kinetic_engy;&#xA;};&#xA;&#xA;struct Vec3&#xA;{&#xA;    real x;&#xA;    real y;&#xA;    real z;&#xA;};&#xA;&#xA;struct DataSet &#xA;{&#xA;    std::vector&amp;lt;real&amp;gt; VecX;&#xA;    std::vector&amp;lt;real&amp;gt; VecY;&#xA;    std::vector&amp;lt;real&amp;gt; VecZ;&#xA;};&#xA;&#xA;void writeEnergyToFile(const std::string&amp;amp; filename, const Energy&amp;amp; energy)&#xA;{&#xA;    //TODO&#xA;}&#xA;&#xA;void writeTrajectoryToFile(const std::string&amp;amp; filename, const Trajectory&amp;amp; trajectory)&#xA;{&#xA;    //TODO&#xA;}&#xA;&#xA;// Initialize positions and velocities of particles&#xA;void initialize(int n_particles, DataSet&amp;amp; positionData, DataSet&amp;amp; velocityData, real boxSize, real maxVelocity)&#xA;{&#xA;    // Create a random number generator&#xA;    std::default_random_engine generator;&#xA;    std::uniform_real_distribution&amp;lt;real&amp;gt; distribution(-0.5, 0.5);&#xA;&#xA;    // Initialize positions and velocities&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        // Assign random initial positions within the box&#xA;        positionData.VecX[i] = boxSize * distribution(generator);&#xA;        positionData.VecY[i] = boxSize * distribution(generator);&#xA;        positionData.VecZ[i] = boxSize * distribution(generator);&#xA;&#xA;        // Assign random initial velocities up to max_vel&#xA;        velocityData.VecX[i] = maxVelocity * distribution(generator);&#xA;        velocityData.VecY[i] = maxVelocity * distribution(generator);&#xA;        velocityData.VecZ[i] = maxVelocity * distribution(generator);&#xA;    }&#xA;}&#xA;&#xA;// Derivative of the Lennard-Jones potential&#xA;Vec3 lj_force(Vec3 posVec)&#xA;{&#xA;    real r_mag = std::sqrt(posVec.x * posVec.x + posVec.y * posVec.y + posVec.z * posVec.z);&#xA;    real s_over_r = sigma / r_mag;&#xA;    real s_over_r6 = s_over_r * s_over_r * s_over_r * s_over_r * s_over_r * s_over_r;&#xA;    real s_over_r12 = s_over_r6 * s_over_r6;&#xA;    real factor = 24.0 * epsilon * (2.0 * s_over_r12 - s_over_r6) / (r_mag * r_mag * r_mag);&#xA;&#xA;    Vec3 force;&#xA;    force.x = factor * posVec.x;&#xA;    force.y = factor * posVec.y;&#xA;    force.z = factor * posVec.z;&#xA;    return force;&#xA;}&#xA;&#xA;// Update the 'accel' function&#xA;void accel(int n_particles, DataSet&amp;amp; accelData, DataSet&amp;amp; posData)&#xA;{&#xA;    // Reset the acceleration to zero&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        accelData.VecX[i] = 0.0;&#xA;        accelData.VecY[i] = 0.0;&#xA;        accelData.VecZ[i] = 0.0;&#xA;    }&#xA;&#xA;    // Compute the acceleration due to each pair&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        for (int j = i + 1; j &amp;lt; n_particles; j++)&#xA;        {&#xA;            Vec3 posVec;&#xA;            posVec.x = posData.VecX[j] - posData.VecX[i];&#xA;            posVec.y = posData.VecY[j] - posData.VecY[i];&#xA;            posVec.z = posData.VecZ[j] - posData.VecZ[i];&#xA;            Vec3 force = lj_force(posVec);&#xA;            // use Lennard-Jones force law&#xA;            accelData.VecX[i] += force.x / mass;&#xA;            accelData.VecY[i] += force.y / mass;&#xA;            accelData.VecZ[i] += force.z / mass;&#xA;            accelData.VecX[j] -= force.x / mass;&#xA;            accelData.VecY[j] -= force.y / mass;&#xA;            accelData.VecZ[j] -= force.z / mass;&#xA;        }&#xA;    }&#xA;}&#xA;&#xA;void leapfrog_step(int n_particles, DataSet&amp;amp; posData, DataSet&amp;amp; velocData, real dt) &#xA;{&#xA;    DataSet a;&#xA;&#xA;    accel(n_particles, a, posData); //compute acceleration&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        velocData.VecX[i] = velocData.VecX[i] + 0.5 * dt * a.VecX[i];    // advance vel by half-step&#xA;        velocData.VecY[i] = velocData.VecY[i] + 0.5 * dt * a.VecY[i];    // advance vel by half-step&#xA;        velocData.VecZ[i] = velocData.VecZ[i] + 0.5 * dt * a.VecZ[i];    // advance vel by half-step&#xA;&#xA;        posData.VecX[i] = posData.VecX[i] + dt * velocData.VecX[i];      // advance pos by full-step&#xA;        posData.VecY[i] = posData.VecY[i] + dt * velocData.VecY[i];      // advance pos by full-step&#xA;        posData.VecZ[i] = posData.VecZ[i] + dt * velocData.VecZ[i];      // advance pos by full-step&#xA;    }&#xA;&#xA;    accel(n_particles, a, posData); //compute acceleration&#xA;    for (int i = 0; i &amp;lt; n_particles; i++)&#xA;    {&#xA;        velocData.VecX[i] = velocData.VecX[i] + 0.5 * dt * a.VecX[i];    // and complete vel. step&#xA;        velocData.VecY[i] = velocData.VecY[i] + 0.5 * dt * a.VecY[i];    // and complete vel. step&#xA;        velocData.VecZ[i] = velocData.VecZ[i] + 0.5 * dt * a.VecZ[i];    // and complete vel. step&#xA;    }&#xA;}&#xA;int main()&#xA;{&#xA;    int n_particles = 10;  // number of particles&#xA;    real box_size = 10.0; // size of the simulation box&#xA;    real max_vel = 0.1;   // maximum initial velocity&#xA;    real dt = 0.01;   // time step&#xA;    int n_steps = 10000;   // number of time steps&#xA;                        &#xA;    DataSet posData; // Positions of the particles&#xA;    DataSet velData; // Velocities of the particles&#xA;&#xA;    // Initialize the particles&#xA;    initialize(n_particles, posData, velData, box_size, max_vel);&#xA;&#xA;    // Run the simulation&#xA;    for (int step = 0; step &amp;lt; n_steps; step++) &#xA;    {&#xA;        leapfrog_step(n_particles, posData, velData, dt);&#xA;    }&#xA;&#xA;    return 0;&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is the best place to compute &lt;code&gt;Energy&lt;/code&gt; and output it to a CSV file?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-09-15T15:51:28.590" LastActivityDate="2023-09-15T15:51:28.590" Title="Where should we compute `Energy` in this listing?" Tags="|molecular-dynamics|" AnswerCount="0" CommentCount="4" ClosedDate="2024-01-11T14:36:33.170" ContentLicense="CC BY-SA 4.0" />
  <row Id="11630" PostTypeId="5" CreationDate="2023-09-15T04:14:41.890" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-09-15T04:14:41.890" LastActivityDate="2023-09-15T04:14:41.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11631" PostTypeId="4" CreationDate="2023-09-15T04:14:41.890" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-09-15T04:14:41.890" LastActivityDate="2023-09-15T04:14:41.890" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11632" PostTypeId="1" CreationDate="2023-09-15T17:18:57.560" Score="2" ViewCount="47" Body="&lt;p&gt;I have a defective graphene system - 94 atoms (32 in both electrodes and 30 in scattering).&#xA;The transiesta run is just not converging. I get this message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCF_NOT_CONV: SCF did not converge in maximum number of steps (required).&#xA;SCF_NOT_CONV: SCF did not converge in maximum number of steps (required).&#xA;Geom step, scf iteration, dmax:    0  1000    0.000000&#xA;Geom step, scf iteration, dmax:    0  1000    0.000000&#xA;Geom step, scf iteration, dq:    0  1000   -4.324581&#xA;Geom step, scf iteration, dq:    0  1000   -4.324581&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any idea what can be done?&lt;/p&gt;&#xA;" OwnerUserId="7815" LastEditorUserId="7" LastEditDate="2023-09-15T23:54:17.587" LastActivityDate="2023-09-15T23:54:17.587" Title="transiesta convergence for defective graphene" Tags="|density-functional-theory|siesta|graphene|" AnswerCount="0" CommentCount="2" ClosedDate="2024-03-08T22:36:38.613" ContentLicense="CC BY-SA 4.0" />
  <row Id="11633" PostTypeId="1" AcceptedAnswerId="11749" CreationDate="2023-09-16T06:09:21.573" Score="3" ViewCount="266" Body="&lt;p&gt;I am a beginner in Quantum Espresso&#xA;When I want to calculate the total energy for Cu for example, I write the input file for primitive cell or conventional cell, what is the difference?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="7915" LastActivityDate="2023-10-15T01:12:59.140" Title="Finding the total energy using quantum espresso" Tags="|density-functional-theory|molecular-dynamics|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11634" PostTypeId="1" CreationDate="2023-09-16T12:46:21.723" Score="7" ViewCount="123" Body="&lt;p&gt;I'd like to know how to treat VdW interactions among layers. Specifically I'm using Quantum Espresso and I'd like to know how VdW forces are implemented in the Kohn-Sham equation. Does it insert a &lt;span class=&quot;math-container&quot;&gt;$V \propto \frac{1}{r^6}$&lt;/span&gt; in the effective potential?&lt;/p&gt;&#xA;" OwnerUserId="7557" LastActivityDate="2023-10-09T21:09:21.983" Title="In solids physics, how are Van Der Waals forces modelled?" Tags="|density-functional-theory|quantum-espresso|solid-state-physics|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11636" PostTypeId="1" AcceptedAnswerId="11637" CreationDate="2023-09-16T22:28:10.650" Score="9" ViewCount="2962" Body="&lt;p&gt;I've been reading some beginner books about quantum electrodynamics / quantum field theory (e.g. Feynman's QED book), and basically everything is done at the paper and pencil level.&lt;/p&gt;&#xA;&lt;p&gt;I'm curious if there is QED (or QFT) software, similar to the many &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantum chemistry software&lt;/a&gt; packages out there.  In particular: what software would one use to calculate the absorption spectrum of a really simple system, like the hydrogen or helium atom, at the QED level?&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2023-09-18T15:39:48.067" LastActivityDate="2023-09-18T15:39:48.067" Title="Software for quantum electrodynamics?" Tags="|software|quantum-chemistry|software-recommendations|one-topic-per-answer|relativistic|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11637" PostTypeId="2" ParentId="11636" CreationDate="2023-09-16T23:15:51.773" Score="10" Body="&lt;h1&gt;GRASP&lt;/h1&gt;&#xA;&lt;p&gt;Allow me to introduce you to &lt;a href=&quot;https://compas.github.io/grasp/&quot; rel=&quot;noreferrer&quot;&gt;GRASP&lt;/a&gt;, a software that was written largely by now 92-year-old &lt;a href=&quot;https://en.wikipedia.org/wiki/Ian_Grant_(physicist)&quot; rel=&quot;noreferrer&quot;&gt;Ian Grant&lt;/a&gt; and now 94-year old (5 days from now) &lt;a href=&quot;https://en.wikipedia.org/wiki/Charlotte_Froese_Fischer&quot; rel=&quot;noreferrer&quot;&gt;Charlotte Froese Fischer&lt;/a&gt; whose PhD supervisor was &lt;a href=&quot;https://en.wikipedia.org/wiki/Douglas_Hartree&quot; rel=&quot;noreferrer&quot;&gt;Douglas Hartree&lt;/a&gt; from the Hartree-Fock method; but&#xA;the software has been maintained throughout all of these decades and is &lt;a href=&quot;https://github.com/compas/grasp&quot; rel=&quot;noreferrer&quot;&gt;open source on GitHub with some commits to &amp;quot;&lt;strong&gt;GRASP 2018&lt;/strong&gt;&amp;quot; being pushed &lt;strong&gt;within the last year!&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;GRASP stands for &lt;strong&gt;G&lt;/strong&gt;eneral &lt;strong&gt;R&lt;/strong&gt;elativistic &lt;strong&gt;A&lt;/strong&gt;tomic &lt;strong&gt;S&lt;/strong&gt;tructure &lt;strong&gt;P&lt;/strong&gt;rogram and was originally written in an older version of FORTRAN, but it has been modernized to Fortran 90 and is parallelized using MPI. In addition to the first link that I provided, which is the HTML/doxygen (web-based) version of the documentation, the the PDF version is available &lt;a href=&quot;https://github.com/compas/grasp2018/releases/download/2018-12-03/GRASP2018-manual.pdf&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h4&gt;QED effects:&lt;/h4&gt;&#xA;&lt;p&gt;If you click on the first link and search QED in the search bar, you'll &lt;a href=&quot;https://i.stack.imgur.com/iV4c8.png&quot; rel=&quot;noreferrer&quot;&gt;see a variety of QED functions and other results&lt;/a&gt;, which I'll list below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;qed&#xA;qed.f90&#xA;qed_i&#xA;qed_I.f90&#xA;qed_slfen&#xA;qed_slfen.f90&#xA;qed_slfen_i&#xA;qed_slfen_I.f90&#xA;qedcut_c&#xA;qedcut_C.f90&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also if you search QED in the PDF documentation which I linked earlier in this answer, you'll find that the vacuum polarization and self-energy terms, which are considered the &lt;em&gt;&lt;strong&gt;leading QED effects&lt;/strong&gt;&lt;/em&gt; are included in the &lt;code&gt;rci&lt;/code&gt; (relativistic CI) routine:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;rci,            rci_mpi - perform relativistic configuration interaction (RCI) calculation with transverse photon (Breit) interaction and vacuum polarization and self-energy (QED) corrections.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Although the term QED appears 30 more times in that document, it's all in relation to the RCI routine, and there's a reference from over 40 years ago by Ian Grant himself (and others) in relation to QED corrections for the multi-configurational Dirac-Fock (MCDF) method, which can be considered a relativistic version of MCSCF (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1566/5&quot;&gt;What are the types of MCSCF?&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;B.J.McKenzie, I.P.Grant and P.H.Norrington &amp;quot;A program to calculate transverse Breit and QED corrections to energy levels in a MCDF environment&amp;quot; &lt;em&gt;&lt;strong&gt;Computer Physics Communications&lt;/strong&gt;&lt;/em&gt;. 21, 233-246 (1980); &lt;em&gt;ibid&lt;/em&gt; 23, 222 (1980).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-16T23:15:51.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11638" PostTypeId="1" CreationDate="2023-09-17T05:02:01.310" Score="3" ViewCount="83" Body="&lt;p&gt;When I want to visualize charge density in VESTA I got this error &amp;quot;**Number of data grids in the 3D data sets do not match each other&amp;quot; How can I fix this problem&lt;/p&gt;&#xA;" OwnerUserId="7312" LastActivityDate="2023-09-19T20:58:11.977" Title="Hetrobilayer charge density by using quantume espresso" Tags="|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11639" PostTypeId="1" CreationDate="2023-09-19T03:48:18.957" Score="3" ViewCount="261" Body="&lt;p&gt;I am trying to install Quantum ESPRESSO on a cluster running on CentOS 7. I do not have admin privilege on this cluster.&lt;/p&gt;&#xA;&lt;p&gt;The compilation with &lt;code&gt;make&lt;/code&gt; always exits with the following error even though the &lt;code&gt;./configure&lt;/code&gt; script runs properly. Below is the error I am facing.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[amuhaymin@celestia q-e]&lt;span class=&quot;math-container&quot;&gt;$ ./configure&#xA;directory QEHeat/src : ok okkokCI : ok&#xA;directory ACFDT/src : not present in /home/amuhaymin/opt/q-e/install&#xA;directory KCW/PP : okk&#xA;all dependencies updated successfully&#xA;checking build system type... x86_64-pc-linux-gnu&#xA;checking ARCH... x86_64&#xA;checking setting AR... ... ar&#xA;checking setting ARFLAGS... ... ruv&#xA;checking for gfortran... gfortran&#xA;checking whether the Fortran compiler works... yes&#xA;checking for Fortran compiler default output file name... a.out&#xA;checking for suffix of executables...&#xA;checking whether we are cross compiling... no&#xA;checking for suffix of object files... o&#xA;checking whether the compiler supports GNU Fortran... yes&#xA;checking whether gfortran accepts -g... yes&#xA;checking for Fortran flag to compile .f90 files... none&#xA;checking for mpiifort... no&#xA;checking for mpif90... mpif90&#xA;checking whether the compiler supports GNU Fortran... yes&#xA;checking whether mpif90 accepts -g... yes&#xA;checking version of mpif90... gfortran 8.3&#xA;setting F90... gfortran&#xA;setting MPIF90... mpif90&#xA;checking for cc... cc&#xA;checking whether the compiler supports GNU C... yes&#xA;checking whether cc accepts -g... yes&#xA;checking for cc option to enable C11 features... -std=gnu11&#xA;setting CC... cc -std=gnu11&#xA;setting CFLAGS... -O3&#xA;using F90... gfortran&#xA;setting FFLAGS... -O3 -g&#xA;setting F90FLAGS... $&lt;/span&gt;(FFLAGS) -cpp&#xA;setting FFLAGS_NOOPT... -O0 -g&#xA;setting CPP... cpp&#xA;setting CPPFLAGS... -P -traditional -Uvector&#xA;setting LD... mpif90&#xA;setting LDFLAGS... -g&#xA;checking whether make sets &lt;span class=&quot;math-container&quot;&gt;$(MAKE)... yes&#xA;checking whether Fortran files must be preprocessed... no&#xA;checking for library containing dgemm... no&#xA;MKL not found&#xA;in /opt/intel/mkl/lib/intel64: checking for library containing dgemm... -lmkl_gf_lp64&#xA;setting BLAS_LIBS... -L/opt/intel/mkl/lib/intel64 -lmkl_gf_lp64 -lmkl_sequential -lmkl_core&#xA;checking FFT...&#xA;checking MASS...&#xA;checking for library containing mpi_init... none required&#xA;checking for library containing pdgemr2d... no&#xA;checking for library containing pdgemr2d... -lmkl_scalapack_lp64&#xA;checking ELPA...&#xA;checking for Environ... not used&#xA;checking if legacy plugins are enabled ...  no&#xA;checking for ranlib... ranlib&#xA;checking for wget... wget -O&#xA;setting WGET... wget -O&#xA;checking for git... git&#xA;Source files are cloned from a git repository.&#xA;On git branch develop&#xA;On git commit hash 10d110b214ce4b2a5dd1adcc8110feae2f8c5d46&#xA;Submodule 'external/d3q' (https://github.com/anharmonic/d3q.git) registered for path 'external/d3q'&#xA;Submodule 'external/devxlib' (https://gitlab.com/max-centre/components/devicexlib.git) registered for path 'external/devxlib'&#xA;Submodule 'external/fox' (https://github.com/pietrodelugas/fox.git) registered for path 'external/fox'&#xA;Submodule 'external/lapack' (https://github.com/Reference-LAPACK/lapack.git) registered for path 'external/lapack'&#xA;Submodule 'external/mbd' (https://github.com/libmbd/libmbd.git) registered for path 'external/mbd'&#xA;Submodule 'external/pw2qmcpack' (https://github.com/QMCPACK/pw2qmcpack.git) registered for path 'external/pw2qmcpack'&#xA;Submodule 'external/qe-gipaw' (https://github.com/dceresoli/qe-gipaw) registered for path 'external/qe-gipaw'&#xA;Submodule 'external/wannier90' (https://github.com/wannier-developers/wannier90.git) registered for path 'external/wannier90'&#xA;setting DFLAGS... -D__DFTI -D__MPI -D__SCALAPACK&#xA;setting IFLAGS... -I. -I$&lt;/span&gt;(TOPDIR)/include -I/opt/intel/mkl/include&#xA;configure: creating ./config.status&#xA;config.status: creating install/make_lapack.inc&#xA;config.status: creating include/configure.h&#xA;config.status: creating make.inc&#xA;config.status: creating configure.msg&#xA;config.status: creating install/make_wannier90.inc&#xA;config.status: creating include/qe_cdefs.h&#xA;--------------------------------------------------------------------&#xA;ESPRESSO can take advantage of several optimized numerical libraries&#xA;(essl, fftw, mkl...).  This configure script attempts to find them,&#xA;but may fail if they have been installed in non-standard locations.&#xA;If a required library is not found, the local copy will be compiled.&#xA;&#xA;The following libraries have been found:&#xA;  BLAS_LIBS=-L/opt/intel/mkl/lib/intel64 -lmkl_gf_lp64  -lmkl_sequential -lmkl_core&#xA;  LAPACK_LIBS=&#xA;  SCALAPACK_LIBS=-lmkl_scalapack_lp64 -lmkl_blacs_openmpi_lp64&#xA;  FFT_LIBS=&#xA;&#xA;&#xA;&#xA;Please check if this is what you expect.&#xA;&#xA;If any libraries are missing, you may specify a list of directories&#xA;to search and retry, as follows:&#xA;  ./configure LIBDIRS=&amp;quot;list of directories, separated by spaces&amp;quot;&#xA;&#xA;Parallel environment detected successfully.\&#xA;Configured for compilation of parallel executables.&#xA;&#xA;For more info, read the ESPRESSO User's Guide (Doc/users-guide.tex).&#xA;--------------------------------------------------------------------&#xA;configure: success&#xA;[amuhaymin@celestia q-e]&lt;span class=&quot;math-container&quot;&gt;$ ll&#xA;total 212&#xA;drwxr-xr-x  2 amuhaymin hpcusers    53 Sep 19 06:25 archive&#xA;drwxr-xr-x  6 amuhaymin hpcusers   168 Sep 19 06:25 atomic&#xA;drwxr-xr-x  3 amuhaymin hpcusers  4096 Sep 19 06:25 cmake&#xA;-rw-r--r--  1 amuhaymin hpcusers 29184 Sep 19 06:25 CMakeLists.txt&#xA;-rwxr-xr-x  1 amuhaymin hpcusers  2371 Sep 19 06:25 configure&#xA;-rw-r--r--  1 amuhaymin hpcusers  1108 Sep 19 06:25 CONTRIBUTING.md&#xA;drwxr-xr-x  6 amuhaymin hpcusers   145 Sep 19 06:25 COUPLE&#xA;drwxr-xr-x  6 amuhaymin hpcusers   109 Sep 19 06:25 CPV&#xA;drwxr-xr-x  4 amuhaymin hpcusers  4096 Sep 19 06:25 dev-tools&#xA;drwxr-xr-x  2 amuhaymin hpcusers   200 Sep 19 06:25 dft-d3&#xA;drwxr-xr-x  4 amuhaymin hpcusers  4096 Sep 19 06:25 Doc&#xA;-rw-r--r--  1 amuhaymin hpcusers  5274 Sep 19 06:25 environment_variables&#xA;drwxr-xr-x  7 amuhaymin hpcusers   168 Sep 19 06:25 EPW&#xA;drwxr-xr-x 10 amuhaymin hpcusers  4096 Sep 19 06:25 external&#xA;drwxr-xr-x  5 amuhaymin hpcusers   101 Sep 19 06:25 FFTXlib&#xA;drwxr-xr-x  5 amuhaymin hpcusers   127 Sep 19 06:25 GUI&#xA;drwxr-xr-x 13 amuhaymin hpcusers   251 Sep 19 06:25 GWW&#xA;drwxr-xr-x  5 amuhaymin hpcusers   106 Sep 19 06:25 HP&#xA;drwxr-xr-x  2 amuhaymin hpcusers   186 Sep 19 06:25 include&#xA;drwxr-xr-x  3 amuhaymin hpcusers  4096 Sep 19 06:25 install&#xA;drwxr-xr-x  6 amuhaymin hpcusers   138 Sep 19 06:25 KCW&#xA;drwxr-xr-x  9 amuhaymin hpcusers   212 Sep 19 06:25 KS_Solvers&#xA;drwxr-xr-x  3 amuhaymin hpcusers  4096 Sep 19 06:25 LAXlib&#xA;-rw-r--r--  1 amuhaymin hpcusers 18009 Sep 19 06:25 License&#xA;-rw-r--r--  1 amuhaymin hpcusers 42741 Sep 19 06:25 logo.jpg&#xA;drwxr-xr-x  2 amuhaymin hpcusers  4096 Sep 19 06:25 LR_Modules&#xA;-rw-r--r--  1 amuhaymin hpcusers 12344 Sep 19 06:25 Makefile&#xA;-rw-r--r--  1 amuhaymin hpcusers  6236 Sep 19 06:25 make.inc&#xA;drwxr-xr-x  2 amuhaymin hpcusers  8192 Sep 19 06:25 Modules&#xA;drwxr-xr-x  6 amuhaymin hpcusers    95 Sep 19 06:25 NEB&#xA;drwxr-xr-x  8 amuhaymin hpcusers   131 Sep 19 06:25 PHonon&#xA;drwxr-xr-x  7 amuhaymin hpcusers   151 Sep 19 06:25 PP&#xA;drwxr-xr-x  2 amuhaymin hpcusers  4096 Sep 19 06:25 pseudo&#xA;drwxr-xr-x  7 amuhaymin hpcusers   158 Sep 19 06:25 PW&#xA;drwxr-xr-x  5 amuhaymin hpcusers    82 Sep 19 06:25 PWCOND&#xA;drwxr-xr-x  5 amuhaymin hpcusers   124 Sep 19 06:25 QEHeat&#xA;-rw-r--r--  1 amuhaymin hpcusers  2880 Sep 19 06:25 README_GPU.md&#xA;-rw-r--r--  1 amuhaymin hpcusers  4367 Sep 19 06:25 README.md&#xA;drwxr-xr-x  6 amuhaymin hpcusers   176 Sep 19 06:25 TDDFPT&#xA;drwxr-xr-x 96 amuhaymin hpcusers  4096 Sep 19 06:25 test-suite&#xA;drwxr-xr-x  2 amuhaymin hpcusers  4096 Sep 19 06:25 upflib&#xA;drwxr-xr-x  3 amuhaymin hpcusers  4096 Sep 19 06:25 UtilXlib&#xA;drwxr-xr-x  4 amuhaymin hpcusers  4096 Sep 19 06:25 XClib&#xA;drwxr-xr-x  6 amuhaymin hpcusers   109 Sep 19 06:25 XSpectra&#xA;[amuhaymin@celestia q-e]$&lt;/span&gt; make pw&#xA;test -d bin || mkdir bin&#xA;( cd UtilXlib ; make TLDEPS= all || exit 1 )&#xA;make[1]: Entering directory `/home/amuhaymin/opt/q-e/UtilXlib'&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c parallel_include.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c util_param.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c clib_wrappers.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c nvtx_wrapper.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c clocks_handler.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c cptimer.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c copy.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c c_mkdir.c&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c device_helper.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c mp.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c divide.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c data_buffer.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c eval_infix.c&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c error_handler.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c mp_bands_util.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c export_gstart_2_solvers.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c find_free_unit.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c fletcher32_mod.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c fletcher32.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c md5.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c md5_from_file.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c memstat.c&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c memusage.c&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c mem_counter.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c mp_base.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c mp_base_gpu.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c print_mem.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;cc -std=gnu11 -O3 -D__DFTI -D__MPI -D__SCALAPACK -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include   -c ptrace.c&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c set_mpi_comm_4_solvers.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;mpif90 -O3 -g -cpp -D__DFTI -D__MPI -D__SCALAPACK  -I/home/amuhaymin/opt/q-e//external/devxlib/src -I. -I/home/amuhaymin/opt/q-e//include -I/opt/intel/mkl/include -I. -c thread_util.f90&#xA;f951: Warning: Nonexistent include directory ‘/home/amuhaymin/opt/q-e//external/devxlib/src’ [-Wmissing-include-dirs]&#xA;ar ruv libutil.a clib_wrappers.o clocks_handler.o cptimer.o copy.o c_mkdir.o device_helper.o divide.o data_buffer.o eval_infix.o error_handler.o export_gstart_2_solvers.o find_free_unit.o fletcher32_mod.o fletcher32.o md5.o md5_from_file.o memstat.o memusage.o mem_counter.o mp.o mp_base.o mp_base_gpu.o mp_bands_util.o parallel_include.o print_mem.o ptrace.o set_mpi_comm_4_solvers.o util_param.o thread_util.o nvtx_wrapper.o&#xA;ar: creating libutil.a&#xA;a - clib_wrappers.o&#xA;a - clocks_handler.o&#xA;a - cptimer.o&#xA;a - copy.o&#xA;a - c_mkdir.o&#xA;a - device_helper.o&#xA;a - divide.o&#xA;a - data_buffer.o&#xA;a - eval_infix.o&#xA;a - error_handler.o&#xA;a - export_gstart_2_solvers.o&#xA;a - find_free_unit.o&#xA;a - fletcher32_mod.o&#xA;a - fletcher32.o&#xA;a - md5.o&#xA;a - md5_from_file.o&#xA;a - memstat.o&#xA;a - memusage.o&#xA;a - mem_counter.o&#xA;a - mp.o&#xA;a - mp_base.o&#xA;a - mp_base_gpu.o&#xA;a - mp_bands_util.o&#xA;a - parallel_include.o&#xA;a - print_mem.o&#xA;a - ptrace.o&#xA;a - set_mpi_comm_4_solvers.o&#xA;a - util_param.o&#xA;a - thread_util.o&#xA;a - nvtx_wrapper.o&#xA;ranlib libutil.a&#xA;make[1]: Leaving directory `/home/amuhaymin/opt/q-e/UtilXlib'&#xA;cd install ; make -f extlibs_makefile libcuda&#xA;make[1]: Entering directory `/home/amuhaymin/opt/q-e/install'&#xA;initializing external/devxlib submodule ...&#xA;usage: git submodule [--quiet] add [-b &amp;lt;branch&amp;gt;] [-f|--force] [--name &amp;lt;name&amp;gt;] [--reference &amp;lt;repository&amp;gt;] [--] &amp;lt;repository&amp;gt; [&amp;lt;path&amp;gt;]&#xA;   or: git submodule [--quiet] status [--cached] [--recursive] [--] [&amp;lt;path&amp;gt;...]&#xA;   or: git submodule [--quiet] init [--] [&amp;lt;path&amp;gt;...]&#xA;   or: git submodule [--quiet] deinit [-f|--force] [--] &amp;lt;path&amp;gt;...&#xA;   or: git submodule [--quiet] update [--init] [--remote] [-N|--no-fetch] [-f|--force] [--rebase] [--reference &amp;lt;repository&amp;gt;] [--merge] [--recursive] [--] [&amp;lt;path&amp;gt;...]&#xA;   or: git submodule [--quiet] summary [--cached|--files] [--summary-limit &amp;lt;n&amp;gt;] [commit] [--] [&amp;lt;path&amp;gt;...]&#xA;   or: git submodule [--quiet] foreach [--recursive] &amp;lt;command&amp;gt;&#xA;   or: git submodule [--quiet] sync [--recursive] [--] [&amp;lt;path&amp;gt;...]&#xA;make[1]: *** [libcuda_devxlib] Error 1&#xA;make[1]: Leaving directory `/home/amuhaymin/opt/q-e/install'&#xA;make: *** [libcuda] Error 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It looks like it cannot find libcuda. But I am not sure if we need libcuda here since this is not GPU!&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="142" LastEditDate="2023-09-20T19:08:43.670" LastActivityDate="2023-09-20T19:08:43.670" Title="How to compile Quantum ESPRESSO on CentOS 7?" Tags="|quantum-espresso|software-assistance|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11640" PostTypeId="1" CreationDate="2023-09-19T08:54:11.277" Score="3" ViewCount="26" Body="&lt;p&gt;Can anyone help me about the same issue.  How to find reduced coordinate of reciprocal lattice vector which defines kslice in brillioun zone?&lt;/p&gt;&#xA;" OwnerUserId="7903" LastActivityDate="2023-09-19T08:54:11.277" Title="Kslice in brillioun zone" Tags="|density-functional-theory|quantum-espresso|brillouin-zone|wannier90|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-27T16:56:20.163" ContentLicense="CC BY-SA 4.0" />
  <row Id="11641" PostTypeId="2" ParentId="11639" CreationDate="2023-09-19T11:54:57.937" Score="2" Body="&lt;p&gt;If you have root access, make sure you have enabled &lt;a href=&quot;https://docs.fedoraproject.org/en-US/epel/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fedora EPEL&lt;/a&gt; on your system, and then run&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;# dnf -y install quantum-espresso&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;If you don't have root access, you should ask your systems administrator to install this package for you.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can download the necessary RPM packages from Fedora EPEL and extract them with &lt;code&gt;rpm2cpio foo.rpm | cpio -ivd&lt;/code&gt;. You will then need to set up your paths and &lt;code&gt;LD_LIBRARY_PATH&lt;/code&gt; accordingly, so that the shell finds the necessary binaries and libraries. I often use this trick to install libraries on supercomputers I don't want to bother compiling.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-09-20T19:06:12.350" LastActivityDate="2023-09-20T19:06:12.350" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11642" PostTypeId="1" AcceptedAnswerId="11660" CreationDate="2023-09-19T14:48:55.993" Score="5" ViewCount="50" Body="&lt;p&gt;Hello fellow computational chemists!&lt;/p&gt;&#xA;&lt;p&gt;I have encountered a challenge that I'd like to discuss and seek advice on. Suppose I have a substantial dataset in SDF format containing thousands of molecules. My goal is to identify the major chemical series, pharmacophores, or scaffolds within this dataset. The primary motivation behind this task is to reduce a large dataset into a more manageable one that retains representative structures. This curated dataset will then serve as a reference for subsequent hit selection processes in my research.&lt;/p&gt;&#xA;&lt;p&gt;The overarching objective is to ensure that my hit selection process captures sufficient chemical diversity from the larger dataset for subsequent in vitro testing. This is crucial for the success of my research, as it helps guarantee a broad exploration of chemical space and increases the likelihood of discovering novel compounds with desirable biological activity.&lt;/p&gt;&#xA;&lt;p&gt;I would greatly appreciate any insights, suggestions, or experiences you might have to share regarding this process. Have you encountered similar challenges in your computational chemistry work? Are there specific tools or techniques you've found particularly useful in identifying key chemical features in large datasets? Your input will be invaluable in helping me streamline my research and improve the diversity and representativeness of my hit selection process.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for your contributions to this discussion!&lt;/p&gt;&#xA;" OwnerUserId="7942" LastActivityDate="2023-09-25T09:38:20.467" Title="Identifying Key Chemical Series, Pharmacophores, and Scaffolds in a Large SDF Dataset" Tags="|computational-chemistry|drug-design|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11643" PostTypeId="1" CreationDate="2023-09-19T17:58:36.080" Score="4" ViewCount="47" Body="&lt;p&gt;I ran a molecular dynamics simulation using Gromacs 2023.2, with the CHARMM36 forcefield. And I ran a per-residue energy decomposition calculation using gmx_MMPBSA, with MMGBSA model. MMGBSA model breaks energy into 1) electrostatic 2) van der waals 3) non-polar solvation 4) polar solvation. By visual inspection of the figure, it seems that electrostatic interactions contributed the most to the protein-ligand complex.&lt;/p&gt;&#xA;&lt;p&gt;If you use visualization software like Discovery Studio for a protein-ligand complex, it tells you interactions like conventional hydrogen bonding, pi-pi stacking, etc. My question is, is there a clear classification for different interactions in CHARMM36? For example, hydrogen bonding -&amp;gt; van der waals, pi-pi stacking -&amp;gt; van der waals, pi-cation -&amp;gt; electrostatic (just for example, not necessarily correct!). Or maybe I am thinking there is no such clear classification under the hood, instead, CHARMM36 just calculates the energy according to formulas without really caring about what type of interaction it is. As a result, maybe a hydrogen bonding interaction can contribute both electrostatic energy and van der waals.&lt;/p&gt;&#xA;" OwnerUserId="7944" LastEditorUserId="7944" LastEditDate="2023-09-19T18:02:13.113" LastActivityDate="2023-09-19T18:02:13.113" Title="MMGBSA: Electrostatic and van der Waals" Tags="|molecular-dynamics|gromacs|molecular-interactions|charmm|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11644" PostTypeId="2" ParentId="11638" CreationDate="2023-09-19T20:58:11.977" Score="3" Body="&lt;p&gt;From &lt;a href=&quot;https://www.researchgate.net/post/Number-of-data-grids-not-match-with-each-other&quot; rel=&quot;nofollow noreferrer&quot;&gt;ResearchGate&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The CHGCAR files have different values of NGX, NGY, and NGZ. So, you&#xA;are seeing the error. You need to have all the three values same, so&#xA;you can specify them in the INCAR before running the jobs. The error&#xA;then should get eliminated.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I see that you have complained that one of the links in the answer does not work. However, you can reach the archived version of that page &lt;a href=&quot;https://web.archive.org/web/20181215063420/http://cms.mpi.univie.ac.at/vasp/vasp/NGX_NGY_NGZ_NGXF_NGYF_NGZF_tags.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. However, these are deprecated/obsolete links. You should visit the updated VASP manual. Corresponding webpage links from the update VASP manual are: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NGX&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NGXF&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-09-19T20:58:11.977" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11646" PostTypeId="1" CreationDate="2023-09-20T13:58:14.563" Score="2" ViewCount="43" Body="&lt;p&gt;hi my molecule is devided into 5 fragment, I want to perform an NBO analysis and calculate the total charge of each fragment instead of doing it by hand (by summing atomic charges) , is there a way to do that in gaussian ?&lt;/p&gt;&#xA;&lt;p&gt;I tried to use the fragment key word in gaussian but I got the following error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=nbo.chk&#xA;# 6-31g(d) guess=(only,fragment=5) pop=nbo pbe1pbe&#xA;..&#xA;&#xA;..&#xA;..&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Storage needed:      9404 in NPA,      7373 in NBO (  33548014 available)&#xA;&#xA; Subroutine NAOANL could not find a S-type core orbital on atom  C    1.&#xA; ICORE :  1  0  0  0     M :  1     LA :  1&#xA; Error&#xA; Error termination via Lnk1e in C:\G09W\l607.exe at Wed Sep 20 15:41:14 2023.&#xA; Job cpu time:  0 days  0 hours  1 minutes 41.0 seconds.&#xA; File lengths (MBytes):  RWF=     82 Int=      0 D2E=      0 Chk=     12 Scr=      1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5563" LastActivityDate="2023-09-20T13:58:14.563" Title="how to calculate the total charge for a specific fragment in a molecule using NBO analysis with Gaussian?" Tags="|density-functional-theory|gaussian|" AnswerCount="0" CommentCount="0" ClosedDate="2023-10-12T14:20:33.983" ContentLicense="CC BY-SA 4.0" />
  <row Id="11647" PostTypeId="2" ParentId="11626" CreationDate="2023-09-20T19:34:58.820" Score="3" Body="&lt;p&gt;The primary reason why convergence problems occur in TranSiesta is because of not properly testing the screening layers towards the electrodes. I also believe this is your main problem.&lt;br /&gt;&#xA;Again, problems are best understood by testing additional layers, then playing with SCF parameters, once a convergence can be reached, then one can go back to smaller systems and check if the same physics can be obtained with a smaller system, if needed.&lt;/p&gt;&#xA;&lt;p&gt;Here would be my approach:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Check whether additional screening layers can solve the issues.&lt;/li&gt;&#xA;&lt;li&gt;Reduce the mixing weight, a very low (it can be arbitrarily small) can cause very slow but certain convergence, a high value can result in non-convergence. The &lt;em&gt;right&lt;/em&gt; mixing weight is system dependent and results in a fast, yet smooth convergence. There is no optimal mixing weight.&#xA;I think this is different depending on the module in use.&#xA;The force tolerance has nothing to do with the SCF convergence, it is not going to solve any problems.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Lastly, some comments.&#xA;I think your k-points are wrong. You have no k-points along the &lt;code&gt;b&lt;/code&gt; axis. This is clearly not ideal, and perhaps this can also be a problem for the convergence. Start with the electrodes, and find a suitable set of k-points.&lt;br /&gt;&#xA;The manual specifies that the k-points along the transport direction for the electrodes should be very high (to get a good accuracy). The transverse k-points requires the usual convergence approach.&#xA;Just selecting 1, 1, 100 is a bad idea if one does not know the implications. Always, always ensure the k-point sampling converges the physical properties of the electrodes.&lt;/p&gt;&#xA;&lt;p&gt;I can't see why reducing the mesh-cutoff would help, generally a larger mesh cutoff improves the precision. Same goes for the basis size.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2023-09-22T06:26:11.953" LastActivityDate="2023-09-22T06:26:11.953" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11648" PostTypeId="2" ParentId="11532" CreationDate="2023-09-21T01:17:04.913" Score="2" Body="&lt;p&gt;I was digging through the CDK code and found the solution. The following worked.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DepictionGenerator dg = new DepictionGenerator().withSize(width, height);&#xA;Depiction depiction = dg.depict(molecule);&#xA;String svg = depiction.toSvgStr(Depiction.UNITS_PX);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It was hard to realize the Depiction class has an overloaded toSvgStr method which accepted the width and height I wanted. It works like a charm now.&lt;/p&gt;&#xA;" OwnerUserId="7610" LastActivityDate="2023-09-21T01:17:04.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11649" PostTypeId="1" AcceptedAnswerId="12117" CreationDate="2023-09-21T10:59:34.087" Score="4" ViewCount="66" Body="&lt;p&gt;I'm using pymatgen and have a host of structure objects (generated from cif files). How can I judge if the structure is isotropic or not?&lt;/p&gt;&#xA;&lt;p&gt;I took a look at the options associated with structure objects and couldn't find method or parameter that might encode that.&lt;/p&gt;&#xA;" OwnerUserId="6361" LastEditorUserId="7" LastEditDate="2023-12-20T03:18:52.133" LastActivityDate="2023-12-20T03:18:52.133" Title="Isotropy of Pymatgen Structures" Tags="|pymatgen|crystallographic-information-file|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11650" PostTypeId="1" CreationDate="2023-09-21T16:43:07.193" Score="2" ViewCount="59" Body="&lt;p&gt;I am trying to reproduce this &lt;a href=&quot;https://pubs.rsc.org/en/content/articlepdf/2022/cp/d2cp01997c&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; and the unit cell for the system is Monoclinic. I have already generated the surface, and now need to generate the waterbox that is placed in contact with the surface. I noted that packmol can only do orthorhombic boxes or spherical shells. My current method is to generate a slightly smaller cuboid box and then equilibrate the structure to match the shape of the lattice. Is there an another way to directly generate a monoclinic waterbox from packmol?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2023-09-24T01:42:11.010" LastActivityDate="2023-09-24T01:42:11.010" Title="Creating Monoclinic boxes with Packmol?" Tags="|lammps|reproducing-data-from-papers|packmol|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11651" PostTypeId="1" AcceptedAnswerId="11662" CreationDate="2023-09-22T16:38:19.183" Score="4" ViewCount="248" Body="&lt;p&gt;I would like to run my MD simulation in parallel on a cluster (16 CPUs per node).&lt;/p&gt;&#xA;&lt;p&gt;From the &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/parallel.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE doc&lt;/a&gt; we can see that:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;ASE will automatically run in parallel, if it can import an MPI communicator from any of the supported libraries. ASE will attempt to import communicators from these external libraries: GPAW, Asap, Scientific MPI and MPI4PY.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I submit a slurm script with these options:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --nodes=1&#xA;#SBATCH --ntasks-per-node=16&#xA;...&#xA;&#xA;srun python ase_script.py&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It looks like the fastest is always the single cpu calculation and increasing the ntasks per core (1 to 16), makes the calculation go slower.&lt;/p&gt;&#xA;&lt;p&gt;The only difference I see is that the log output contains multiple lines (times ntasks-per-node) for a given step, but with different results. E.g., for a Velocity Verlet calculation and 8 cpus per nodes, I get:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Time[ps]      Etot[eV]     Epot[eV]     Ekin[eV]    T[K]&#xA;...&#xA;0.0440        -8297.460    -8299.281        1.821    79.6&#xA;0.0440        -8297.476    -8299.305        1.829    80.0&#xA;0.0440        -8297.477    -8299.304        1.827    79.8&#xA;0.0440        -8297.741    -8299.557        1.816    79.4&#xA;0.0440        -8297.744    -8299.563        1.819    79.5&#xA;0.0440        -8297.744    -8299.570        1.826    79.8&#xA;0.0440        -8297.746    -8299.584        1.838    80.3&#xA;0.0440        -8297.749    -8299.612        1.863    81.4&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have tried to decorate my dynamics function with &lt;code&gt;@parallel_function&lt;/code&gt; (before the definition and before &lt;code&gt;run()&lt;/code&gt; method) but I get an error.&lt;/p&gt;&#xA;&lt;p&gt;I have installed all the required libraries in my conda environment:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ conda list &amp;gt; conda_list&#xA;&#xA;$ cat conda_list | grep -e asap -e gpaw -e mpi&#xA;asap3                     3.12.12         py310hb818612_2            conda-forge&#xA;gpaw                      23.9.1          py310_mpi_openmpi_omp_0    conda-forge&#xA;gpaw-data                 0.9.20000            hd8ed1ab_2            conda-forge&#xA;mpi                       1.0                     openmpi            conda-forge&#xA;mpi4py                    3.1.4           py310h6075a6b_0            conda-forge&#xA;openmpi                   4.1.5              h414af15_101            conda-forge&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there something else I can try?&lt;/p&gt;&#xA;&lt;p&gt;Small side question, how can I print the volume of the cell in ASE output above?&lt;/p&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="5" LastEditDate="2023-10-01T21:13:37.627" LastActivityDate="2023-10-01T21:13:37.627" Title="Run ASE MD in parallel" Tags="|high-performance-computing|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11652" PostTypeId="2" ParentId="9822" CreationDate="2023-09-22T19:46:00.323" Score="4" Body="&lt;p&gt;I want to share my experience in this topic.&lt;/p&gt;&#xA;&lt;p&gt;In some certain scenarios, the total energy is highly related to the neighbour list construction.&lt;/p&gt;&#xA;&lt;p&gt;If the neighbour list is updated infrequently, not only the interaction forces are wrong, but total energy is no longer conserved (by conservation I mean small fluctuations around some mean value). Suppose a particle appears below the cutoff distance but is not registered in the neighbour list (somehow penetrated the &amp;quot;skin&amp;quot; without being recorded), then the neighbour list is updated. After that, the pair interaction energy appears in total energy out of nowhere. This process results in significant contamination of the total energy over time.&lt;/p&gt;&#xA;&lt;p&gt;This effect was noticeable when I was considering a non-equilibrium system, where some macroscopic parameter was changing over time. However, energy was conserved in the case of an equilibrium system, and my guess is that the above-mentioned process can contribute to total energy both positively and negatively; in the case of an equilibrium system, these contributions compensate each other, while in the out-of-equilibrium scenario, they might be biased, resulting noticeable non-conservation.&lt;/p&gt;&#xA;&lt;p&gt;So, my approach is to use a large &amp;quot;skin&amp;quot; and sufficiently small rebuild interval with the &amp;quot;check yes&amp;quot; option.&lt;/p&gt;&#xA;" OwnerUserId="7974" LastActivityDate="2023-09-22T19:46:00.323" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11653" PostTypeId="1" CreationDate="2023-09-23T08:12:05.440" Score="3" ViewCount="57" Body="&lt;p&gt;My current research focus is on the band splitting observed in 2D perovskite. Existing literature suggests that site inversion asymmetry (SIA) may lead to the Rashba effect, while bulk inversion asymmetry (BIA) may result in the Dresselhaus effect (as referenced in 10.1038/nphys2933 and 10.1021/acsnano.5b04409). I have observed that these effects, in conjunction with spin-orbit coupling (SOC), contribute to band splitting. However, the spin textures associated with the Rashba and Dresselhaus effects are distinct from each other. It is commonly seen that both effects are present in 2D perovskites, leading to band splitting.&lt;/p&gt;&#xA;&lt;p&gt;This leads me to pose the following query: Despite both effects contributing to band splitting, do they influence other properties of 2D perovskite in a differential manner?&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-09-23T08:12:05.440" Title="Which is better? Rashba effect or Dresselhaus effect?" Tags="|density-functional-theory|vasp|quantum-espresso|quantum-mechanics|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11654" PostTypeId="1" CreationDate="2023-09-23T16:15:33.170" Score="4" ViewCount="155" Body="&lt;p&gt;I am confused about the calculation of the charge defect formation energy equation with these two terms (from figure below):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta V$&lt;/span&gt;: alignment term, and&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{corr}$&lt;/span&gt;: correlation term.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;How can I calculate these two terms by using VASP package?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mx771.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mx771.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6896" LastEditorUserId="5" LastEditDate="2023-11-12T13:15:15.227" LastActivityDate="2023-11-25T10:06:31.407" Title="Calculation of charge defect formation energy" Tags="|density-functional-theory|vasp|defects|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11655" PostTypeId="1" CreationDate="2023-09-24T15:19:17.487" Score="4" ViewCount="61" Body="&lt;p&gt;I am using MacOS Ventura, and would like to use xcrysden to visualize my Quantum espresso input and output files. For that, I have installed xcrysden on using Macports. But I am not able to laod the xcrysden GUI using a command like:&#xA;&lt;code&gt;xcrysden --pwi si.0_scf.in&lt;/code&gt;. Please help.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7988" LastEditorUserId="5" LastEditDate="2023-09-24T19:23:57.527" LastActivityDate="2023-09-24T19:23:57.527" Title="How to load xcrysden GUI in OSX after installing through Macports?" Tags="|quantum-espresso|visualization-software|apple-operating-system|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11656" PostTypeId="1" AcceptedAnswerId="11657" CreationDate="2023-09-24T17:22:40.440" Score="4" ViewCount="413" Body="&lt;p&gt;My question is regarding a medium-to-large DLPNO-UCCSD(T)-F12 calculation.&lt;/p&gt;&#xA;&lt;p&gt;I have a ~250 electron system, an open-shell molecule inside a water droplet, and I'm trying to get the total energy, first using the default SCF and PNO settings:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!DLPNO-CCSD(T)-F12 cc-pVTZ cc-pVTZ/C cc-pVTZ-F12-CABS RIJCOSX NormalSCF NormalPNO PModel &#xA;%maxcore 14000&#xA;%palnprocs 32&#xA;end&#xA;%base &amp;quot;dlpno&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It am running it on 2 nodes, to get close to the ~500 GB of ram I've seen in used for similar very similar clusters, except those were closed-shell ([arXiv][1], [arxiv][2])&lt;/p&gt;&#xA;&lt;p&gt;I don't know if the calculation is just &lt;em&gt;stuck and wasting compute resources&lt;/em&gt;, or if it is &lt;em&gt;actually still working&lt;/em&gt;. I know these calculations can take a while but with NormalSCF/NormalPNO and cc-pVTZ my intuition is that it would have been done by now.&lt;/p&gt;&#xA;&lt;p&gt;The last thing written on my output is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;3-index local transformation (OBS_F,OBS/AUX) for op=2   ... done (     16.8 sec)3-index local transformation (OBS_F,CABS/AUX)for op=2   ... done (     51.4 sec)------------------------UHF DLPNO F12 CORRECTION------------------------Doing SCF density matrices                              ... done (      0.1 sec)Calculating RI Coulomb operators Retrieving the Coulomb fitting basis                    ... done       .... OBS/OBS done        (      0.9 sec)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is after &lt;code&gt;--- The CCSD iterations have converged ---STARTING F12 INTEGRAL TRANSFORMATIONS...&lt;/code&gt; and then what you see in the block. The thing is, this part was reached yesterday morning so I'm really beginning to give up with this.&lt;/p&gt;&#xA;&lt;p&gt;Do you have any advice?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Good news is:&lt;/strong&gt; I have DLPNO-UMP2/def2-QZVPPD energies with TightSCF and TightPNO, but would like to go higher to DLPNO-CCCSD(T). There is no DLPNO-MP2-F12 implemented in ORCA for open-shells though.&lt;/p&gt;&#xA;&lt;p&gt;As always, thank you very much for any suggestions!&lt;/p&gt;&#xA;&lt;p&gt;[1]: N. Sylvetsky, J.M.L. Martin &amp;quot;Energetics of (H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O)&lt;span class=&quot;math-container&quot;&gt;$_{20}$&lt;/span&gt; Isomers by means of F12 Canonical and Localized Coupled Cluster Methods&amp;quot; (2020): &lt;a href=&quot;https://arxiv.org/pdf/2002.01749.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/pdf/2002.01749.pdf&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;[1]: G. Santra, &lt;em&gt;et al&lt;/em&gt;, &amp;quot;Is valence CCSD(T) enough for the binding of water clusters? The isomers of (H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O)&lt;span class=&quot;math-container&quot;&gt;$_6$&lt;/span&gt; and (H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;O)&lt;span class=&quot;math-container&quot;&gt;$_{20}$&lt;/span&gt; as a case study&amp;quot; (2023): &lt;a href=&quot;https://arxiv.org/abs/2308.06120&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://arxiv.org/abs/2308.06120&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="175" LastEditorUserId="5" LastEditDate="2023-09-25T15:13:43.627" LastActivityDate="2023-09-25T15:13:43.627" Title="Kill or let be: Is this calculation stuck or just very slow?" Tags="|quantum-chemistry|high-performance-computing|basis-sets|orca|coupled-cluster|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11657" PostTypeId="2" ParentId="11656" CreationDate="2023-09-24T21:08:05.207" Score="6" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I don't know if the calculation is just stuck and wasting compute resources, or if it is actually still working.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When that happens, I log into the compute node and run the &lt;code&gt;top&lt;/code&gt; command. On a SLURM system, I would run the command (if my username is &lt;code&gt;epalos&lt;/code&gt;):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;squeue -u epalos&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This will list all of my jobs that are running, and on which compute nodes they are running. If the job corresponding to the calculation that I want to check, is running on the node called &lt;code&gt;monster_023&lt;/code&gt;, then I would run the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ssh monster_023&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It could ask you for your password now (but might not, because the node to which you're trying to connect is part of the same system), and if you successfully enter the node &lt;code&gt;monster_023&lt;/code&gt;, then you just need to run the command: &lt;code&gt;top&lt;/code&gt; or &lt;code&gt;top -u epalos&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;top&lt;/code&gt; will tell you which processes are running on the node, and &lt;em&gt;&lt;strong&gt;how much CPU load each process is consuming&lt;/strong&gt;&lt;/em&gt;. If all of the processes that are being run by the user &lt;code&gt;epalos&lt;/code&gt; are using a negligible amount of the node's CPU resources, &lt;em&gt;&lt;strong&gt;then your job is &amp;quot;struck&amp;quot;.&lt;/strong&gt;&lt;/em&gt; If you see any process using 1% or more of the node's CPU resources, then &lt;em&gt;&lt;strong&gt;it is doing something.&lt;/strong&gt;&lt;/em&gt; Ideally the CPU usage for each process would be around 100% x N, in which N is the number of cores being used for that process, but it can be significantly less (for example 5%) sometimes (for example if the process is transferring data from the RAM to the disk, which is an extremely slow processes).&lt;/p&gt;&#xA;&lt;p&gt;It is unlikely that your system does not let you log into compute nodes in the way that I have described above. If the you are not able to log into the compute nodes, then you can ask your system administrator to allow it, because most supercomputing centers do allow you to &amp;quot;monitor your jobs&amp;quot; like this (you can send them this answer along with your email if you think it would help).&lt;/p&gt;&#xA;&lt;p&gt;If you cannot  log into the compute nodes, another way to check if the program is &amp;quot;doing anything&amp;quot;, then you can run the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;watch ls -l -t&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to see if any of the files are changing in size, but this will not work if the program is not writing anything to any of the files for a long time (you also might need to change the number of digits printed in the file sizes, or to change your folder to the &amp;quot;temporary&amp;quot; or &amp;quot;scratch&amp;quot; directory in which the program stores the &amp;quot;junk&amp;quot; files associated with the calculation, in order for this method to work). Some programs can be really doing a lot of number crunching for hours before any new information is written to a file, so attempting to monitor file-size changes is not as effective as simply logging into the compute node and checking the CPU usage of your program's processes.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-24T21:08:05.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11658" PostTypeId="1" AcceptedAnswerId="11673" CreationDate="2023-09-24T21:22:54.863" Score="3" ViewCount="133" Body="&lt;p&gt;I'm trying to verify that the &lt;strong&gt;modulus&lt;/strong&gt; of the crystalline atomic/molecular orbitals computed by PySCF satisfy the correct periodicity condition for the supercell. I'm considering a hydrogen chain oriented along the z-axis with H-H separation 1.0 and with two H atoms per cell, giving a cell size of 2.0.&lt;/p&gt;&#xA;&lt;p&gt;The following code evaluates the modulus of the atomic/molecular orbitals for all k-points at positions &lt;span class=&quot;math-container&quot;&gt;$(0,0,0)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$(0,0,2)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;One can see from the output of the code that they are far from equality. How can one understand this bizarre behavior?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;from pyscf.pbc import gto, dft&#xA;from pyscf.pbc.dft import gen_grid, numint&#xA;&#xA;num_kpts = 20&#xA;&#xA;cell = gto.M(atom=[['H', (0.0, 0.0, 1.0)], ['H', (0.0, 0.0, 2.0)]],&#xA;             a=[[40.0, 0.0, 0.0], [0., 40.0, 0.0], [0.0, 0.0, 2.0]],&#xA;             verbose=1)&#xA;&#xA;&#xA;kpts = cell.make_kpts([1, 1, num_kpts])&#xA;&#xA;mf = dft.KRKS(cell)&#xA;mf.kpts = kpts&#xA;mf.xc = 'lda,vwn'&#xA;mf = mf.density_fit()&#xA;energy = mf.kernel()&#xA;&#xA;dm = cell.make_rdm1()&#xA;&#xA;orbital_index = 0  # select an orbital for evaluation&#xA;points = [(0.0, 0.0, 0.0), (0.0, 0.0, 2.0)]  # modulus should be equal at these points&#xA;&#xA;print('orbital: ' + str(orbital_index))&#xA;for kpt_index in range(num_kpts):&#xA;    print('k-point: ' + str(kpt_index))&#xA;    kpt = kpts[kpt_index]&#xA;    ao = numint.eval_ao(cell, points, kpt=kpt) # (2, nao)&#xA;    rho = numint.eval_rho(cell, ao, dm).real # (2,)&#xA;    print('rho: ' + str(rho))&#xA;    ao_density = np.abs(ao[:, orbital_index])**2&#xA;    print('ao_density: ' + str(ao_density))&#xA;    mo_coeff = mf.mo_coeff  # (num_kpts, nao, nao)&#xA;    mo = np.einsum('xi,kij-&amp;gt;xkj', ao, mo_coeff) # (2, num_kpts, nao)&#xA;    mo_density = np.abs(mo[:, kpt_index, orbital_index])**2&#xA;    print('mo_density: ' + str(mo_density))&#xA;&#xA;&#xA;# orbital: 0&#xA;# k-point: 0&#xA;# rho: [0.27688535 0.26870818]&#xA;# ao_density: [0.02243983 0.39680968]&#xA;# mo_density: [0.13844267 0.13435409]&#xA;# k-point: 1&#xA;# rho: [0.27400583 0.26613968]&#xA;# ao_density: [0.02186969 0.39587295]&#xA;# mo_density: [0.13927244 0.13514004]&#xA;# k-point: 2&#xA;# rho: [0.26569365 0.25872769]&#xA;# ao_density: [0.0202211  0.39316138]&#xA;# mo_density: [0.14179107 0.13752496]&#xA;# k-point: 3&#xA;# rho: [0.25287852 0.24730755]&#xA;# ao_density: [0.01767116 0.38895845]&#xA;# mo_density: [0.14608699 0.14159039]&#xA;# k-point: 4&#xA;# rho: [0.23695731 0.23313186]&#xA;# ao_density: [0.01448881 0.38369784]&#xA;# mo_density: [0.15230891 0.14747331]&#xA;# k-point: 5&#xA;# rho: [0.21960232 0.21769588]&#xA;# ao_density: [0.01100108 0.37791244]&#xA;# mo_density: [0.16066695 0.15536683]&#xA;# k-point: 6&#xA;# rho: [0.20255418 0.20255011]&#xA;# ao_density: [0.00755514 0.37217532]&#xA;# mo_density: [0.17143259 0.16551978]&#xA;# k-point: 7&#xA;# rho: [0.18743636 0.18913423]&#xA;# ao_density: [0.00448221 0.36704113]&#xA;# mo_density: [0.18493519 0.17823305]&#xA;# k-point: 8&#xA;# rho: [0.17561427 0.17865325]&#xA;# ao_density: [0.00206752 0.36299446]&#xA;# mo_density: [0.20155235 0.19385034]&#xA;# k-point: 9&#xA;# rho: [0.16810548 0.17200107]&#xA;# ao_density: [0.00052834 0.3604093 ]&#xA;# mo_density: [0.22168984 0.21274038]&#xA;# k-point: 10&#xA;# rho: [0.16553284 0.1697228 ]&#xA;# ao_density: [1.51068664e-28 3.59520862e-01]&#xA;# mo_density: [0.24574325 0.25196794]&#xA;# k-point: 11&#xA;# rho: [0.16810548 0.17200107]&#xA;# ao_density: [0.00052834 0.3604093 ]&#xA;# mo_density: [0.22168984 0.21274038]&#xA;# k-point: 12&#xA;# rho: [0.17561427 0.17865325]&#xA;# ao_density: [0.00206752 0.36299446]&#xA;# mo_density: [0.20155235 0.19385034]&#xA;# k-point: 13&#xA;# rho: [0.18743636 0.18913423]&#xA;# ao_density: [0.00448221 0.36704113]&#xA;# mo_density: [0.18493519 0.17823305]&#xA;# k-point: 14&#xA;# rho: [0.20255418 0.20255011]&#xA;# ao_density: [0.00755514 0.37217532]&#xA;# mo_density: [0.17143259 0.16551978]&#xA;# k-point: 15&#xA;# rho: [0.21960232 0.21769588]&#xA;# ao_density: [0.01100108 0.37791244]&#xA;# mo_density: [0.16066695 0.15536683]&#xA;# k-point: 16&#xA;# rho: [0.23695731 0.23313186]&#xA;# ao_density: [0.01448881 0.38369784]&#xA;# mo_density: [0.15230891 0.14747331]&#xA;# k-point: 17&#xA;# rho: [0.25287852 0.24730755]&#xA;# ao_density: [0.01767116 0.38895845]&#xA;# mo_density: [0.14608699 0.14159039]&#xA;# k-point: 18&#xA;# rho: [0.26569365 0.25872769]&#xA;# ao_density: [0.0202211  0.39316138]&#xA;# mo_density: [0.14179107 0.13752496]&#xA;# k-point: 19&#xA;# rho: [0.27400583 0.26613968]&#xA;# ao_density: [0.02186969 0.39587295]&#xA;# mo_density: [0.13927244 0.13514004]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7989" LastEditorUserId="7989" LastEditDate="2023-09-25T21:13:13.313" LastActivityDate="2023-09-27T19:24:48.553" Title="Verifying periodicity of crystalline orbital modulus in PySCF" Tags="|python|pyscf|orbitals|periodic-boundary-conditions|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="11660" PostTypeId="2" ParentId="11642" CreationDate="2023-09-25T09:38:20.467" Score="4" Body="&lt;p&gt;To identify chemical series effectively, consider utilizing clustering techniques based on the available information at your disposal. Depending on your dataset, incorporating bioactivity or toxicity data into the clustering process can add valuable insights. Alternatively, when such data is limited, structural methods, such as molecular descriptors, molecular fingerprints or substructure matching, can be employed.&lt;/p&gt;&#xA;&lt;p&gt;You may read a bit about chemical space measures.&#xA;The Coverage Score (10/grnnrm) leverages molecular fingerprints to generate a subset of molecules from a broader collection. This subset attempts to efficiently sample the available chemical space.&#xA;Additionally, you might check the #Circles metric (10.48550/arXiv.2112.12542), which offers an approach to comparing two sets of molecules. It's versatile and can be applied to any generic set of properties. Beyond evaluating which set better samples the chemical space, it quantifies the impact of adding a single molecule to the overall sampling.&lt;/p&gt;&#xA;" OwnerUserId="4376" LastActivityDate="2023-09-25T09:38:20.467" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11662" PostTypeId="2" ParentId="11651" CreationDate="2023-09-26T13:50:31.853" Score="4" Body="&lt;p&gt;Usually MD routines is not the bottleneck of the calculation. Usually it is better to focus on parallelisation of the calculator. There is a &lt;code&gt;communicator&lt;/code&gt; parameter in constructors of &lt;code&gt;MolecularDynamics&lt;/code&gt; instances: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/md.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/ase/md.html&lt;/a&gt;. And by default it should be the &lt;code&gt;world&lt;/code&gt; one, but I would rather specify it explicitly. In any way, this communicator can't be used to distribute energy and calculation. You should explicitly do it. Probably it is better to run the python script in a single process and then call the calculator process with &lt;code&gt;mpiexec&lt;/code&gt; or &lt;code&gt;srun&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="277" LastActivityDate="2023-09-26T13:50:31.853" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11663" PostTypeId="1" CreationDate="2023-09-26T13:55:18.633" Score="1" ViewCount="50" Body="&lt;p&gt;I am writing to seek guidance on calculating the Chern number for a 3D ferromagnetic semiconductor material. I intend to determine whether that material is a 3D Chern insulator or not. After reviewing the available resources, I've come across WannierTools as a potential tool for this task where you can use the following input values to perform chern calculation&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;Chern_3D_calc = T&#xA;/&#xA;&amp;amp;PARAMETERS&#xA;NumOccpuied = 88  ! No. of occupied wannier bands&#xA;Nk1 = 41    ! No. of slices of the k points for WCCs&#xA;Nk2 = 41    ! No. of slices of the k points for WCCs&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now, my primary question is whether I can proceed with these input values and, subsequently, read the output file to determine the Chern number, similar to the process used for finding the Z2 number for 3D topological insulators. I would greatly appreciate a detailed explanation of it. Your expertise in this matter would be invaluable to me.&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2023-09-26T21:52:26.367" LastActivityDate="2023-09-26T21:52:26.367" Title="Inquiry About Calculating Chern Number for 3D Ferromagnetic Semiconductor Material" Tags="|density-functional-tight-binding|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-20T03:24:29.830" ContentLicense="CC BY-SA 4.0" />
  <row Id="11664" PostTypeId="1" CreationDate="2023-09-26T14:04:07.917" Score="3" ViewCount="82" Body="&lt;p&gt;I am currently working on anomalous Hall conductivity calculations using both Wanniertools and wannier90. The output values from these calculations are provided in units of (Ohm&lt;span class=&quot;math-container&quot;&gt;$\cdot$&lt;/span&gt;cm)-1. I am interested in converting these output values into the more familiar unit of e2/hc. Could you kindly provide guidance on the most straightforward and simple method for performing this conversion? Your expertise in this matter would be greatly appreciated and would help me immensely in my research. Thank you in advance for your assistance, and I look forward to your response.&lt;/p&gt;&#xA;" OwnerUserId="1136" LastEditorUserId="5" LastEditDate="2023-09-26T23:29:33.060" LastActivityDate="2023-10-27T00:03:40.517" Title="How to convert quantum anomalous Hall conductivity values from (Ohm.cm)-1 to e2/hc?" Tags="|wannier90|density-functional-tight-binding|topological-matter|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11665" PostTypeId="1" AcceptedAnswerId="11672" CreationDate="2023-09-26T16:06:56.263" Score="5" ViewCount="260" Body="&lt;p&gt;I am doing a geometry optimization for a cationic imidazolate-zinc complex.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/BnFRv.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/BnFRv.png&quot; alt=&quot;Mol and xyz file&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm trying to run an optimization using this &lt;a href=&quot;https://1drv.ms/u/c/3cd1ce876c7ff5e4/EQis6bBS7nNArW6kSV3BgFwBSNNjpa29NAPOVWC9Qhqq3w?e=3IHvGS&quot; rel=&quot;nofollow noreferrer&quot;&gt;input file&lt;/a&gt;. It uses the RI approximation.&lt;/p&gt;&#xA;&lt;p&gt;ORCA seems to be running fine until it hits the RI-J gradient calculation. Then it tells me:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Nuc. rep. gradient       (SHARK) ... done (  0.0 sec)&#xA;HCore &amp;amp; Overlap gradient (SHARK) ... done (  0.0 sec)&#xA;ECP gradient             (SHARK) ... done (  0.3 sec)&#xA;RI-J gradient            (SHARK) ...&#xA;ORCA finished by error termination in SCF gradient&#xA;Calling Command: mpirun -np 4  /usr/local/orca_5.0.4/orca_scfgrad_mpi 00000032.scfgrad.inp 00000032&#xA;[file orca_tools/qcmsg.cpp, line 465]:&#xA;.... aborting the run&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The full output of the run can be found &lt;a href=&quot;https://1drv.ms/t/c/3cd1ce876c7ff5e4/Efha6TAem4BKhMHw6O1EPSABJS4ZaFrzOv8aRP-5aUuN4w?e=bTy7bD&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I took out &lt;code&gt;RI on&lt;/code&gt; from my input file, but the result is the same. Can anyone tell me what is happening?&lt;/p&gt;&#xA;&lt;p&gt;Here's the inp file itself:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# (5-Fluoro-1H-imidazol-1-yl)zinc(II)&#xA;# Use B3LYP&#xA;# Use Becke-Johnson Dampening&#xA;# Use 4 CPU cores&#xA;# Run an iterative geometry optimization job&#xA;! B3LYP D3 PAL4 Opt &#xA;&#xA;%maxcore 5000 # Maximum memory in MB&#xA;&#xA;%method &#xA;    RI on # use the RI approximation&#xA;end&#xA;&#xA;# Basis set specifications&#xA;%basis basis &amp;quot;aug-cc-pVDZ&amp;quot; # General spec: aug-cc-pVDZ &#xA;    newGTO Zn &amp;quot;aug-cc-pVDZ-PP&amp;quot; end # except for Zn-atoms: aug-cc-pVDZ-PP&#xA;    newECP Zn &amp;quot;SDD&amp;quot; end # use Stuttgart-Dresden ECPs for Zinc&#xA;end&#xA;&#xA;# Insert xyz coords&#xA;*xyz 1 1&#xA;Zn    -2.309328    1.771441    0.119755&#xA;N     -0.629170    0.310125    0.024646&#xA;C      0.513781    0.759697    0.026619&#xA;F      1.098001    1.986981    0.073661&#xA;C      1.289471   -0.447587   -0.041851&#xA;N      0.375729   -1.468533   -0.073964&#xA;C     -0.899807   -0.885708   -0.026106&#xA;H      2.354732   -0.504006   -0.061957&#xA;H     -1.793410   -1.522410   -0.040803&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;EDIT:&#xA;Just found this in the docs:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;If you use RI you must specify an auxiliary basis set in the %basis section. Do not rely on the program to make an automatic choice for you.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;Does this mean I need to pick an auxilliary basis set and specify it? How do I do that? Which one should I use?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: Question was answered, so I'm posting the full, working input file here.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# (4-Fluoro-1H-imidazol-1-yl)zinc(II)&#xA;# Use B3LYP&#xA;# Use Becke-Johnson Dampening&#xA;# Use 4 CPU cores&#xA;# Run an iterative geometry optimization job&#xA;# Make detailled output file&#xA;# Let ORCA choose auxilliary basis sets&#xA;! B3LYP D3 PAL4 Opt LARGEPRINT autoaux&#xA;%maxcore 1500 # Maximum memory in MB per core&#xA;&#xA;%method &#xA;    RI on # use the RI approximation&#xA;end&#xA;&#xA;# Basis set specifications&#xA;%basis basis &amp;quot;aug-cc-pVDZ&amp;quot; # General spec: aug-cc-pVDZ &#xA;    newGTO Zn &amp;quot;aug-cc-pVDZ-PP&amp;quot; end # except for Zn-atoms: aug-cc-pVDZ-PP&#xA;    newECP Zn &amp;quot;SDD&amp;quot; end # use Stuttgart-Dresden ECPs for Zinc&#xA;end&#xA;&#xA;# Insert xyz coords&#xA;*xyz 1 1&#xA;Zn    -2.417420    1.345162   -0.167542&#xA;N     -0.805569    0.350705   -0.050917&#xA;C      0.425351    0.844144   -0.025052&#xA;C      1.287091   -0.231633    0.064757&#xA;F      2.634022   -0.243334    0.120886&#xA;N      0.504401   -1.345529    0.088678&#xA;C     -0.772569   -0.972550    0.017208&#xA;H      0.754077    1.892994   -0.064409&#xA;H     -1.609384   -1.639958    0.016391&#xA;*&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS: I ran into issues with other input files, where Iodine exists in an isosteric molecule (switch out F for I, essentially). So I need to use the aug-cc-pVDZ-PP basis set not just for Zn, but also for I, since aug-cc-pVDZ is not defined for elements after Krypton.&lt;/p&gt;&#xA;" OwnerUserId="7501" LastEditorUserId="7501" LastEditDate="2023-09-27T16:30:10.307" LastActivityDate="2023-09-27T16:30:10.307" Title="ORCA crashes because of RI approximation?" Tags="|geometry-optimization|orca|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11666" PostTypeId="1" CreationDate="2023-09-26T16:47:55.363" Score="5" ViewCount="193" Body="&lt;p&gt;Can someone explain to me please how am I supposed to get this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/11HGz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/11HGz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From this:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/qmub4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/qmub4.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm a little bit confused because in my calculations using Quantum ESPRESSO I found that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Highest occupied level (ev): 8.400 eV   computed in scf&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;The Fermi energy is  10.0082 ev  computed in nscf&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I was thinking that CB from the table above is the same as the highest occupied level computed in the output of scf calculation.&lt;/p&gt;&#xA;" OwnerUserId="6560" LastEditorUserId="5" LastEditDate="2023-09-27T13:46:57.363" LastActivityDate="2023-11-12T06:59:43.540" Title="How do I obtain CB and VB values from Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|electronic-structure|bandgap|fermi-energy|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11667" PostTypeId="2" ParentId="11666" CreationDate="2023-09-26T17:13:34.737" Score="5" Body="&lt;p&gt;From the graph you presented:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Select the Brillouin &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point, &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; in the graph (this is for a direct gap system).&lt;/li&gt;&#xA;&lt;li&gt;Look for where the Fermi level is. In the graph, it is indicated by the red horizontal dashed line. &lt;strong&gt;Be aware that the graph show a shifted to zero Fermi level and top valence band!&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;li&gt;Look for the minimum value of the first band above the Fermi level at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. This will be the value for &lt;span class=&quot;math-container&quot;&gt;$CB$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Look for the maximum value of the first band below the Fermi level at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. This will be the value for &lt;span class=&quot;math-container&quot;&gt;$VB$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;The gap is then calculated as &lt;span class=&quot;math-container&quot;&gt;$CB-VB$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;As mentioned before, in the graph, the Fermi level was shifted. This means that, from the graph:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$CB=2.420\,eV$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$VB=0\,eV$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Fermi level = &lt;span class=&quot;math-container&quot;&gt;$0\,eV$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Gap = &lt;span class=&quot;math-container&quot;&gt;$2.420\,eV$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-09-26T17:13:34.737" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11668" PostTypeId="1" CreationDate="2023-09-26T17:44:41.540" Score="2" ViewCount="46" Body="&lt;p&gt;I am trying to use &lt;a href=&quot;https://pymatgen.org/pymatgen.analysis.html#module-pymatgen.analysis.adsorption&quot; rel=&quot;nofollow noreferrer&quot;&gt;Pymatgen adsorption module&lt;/a&gt; for my adsorption site calculations. While going through the documentation, I had a small confusion. It says the following&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Determine “surface sites” by finding those within a height threshold along the&#xA;miller index of the highest site&lt;/li&gt;&#xA;&lt;li&gt;Create a network of surface sites using the Delaunay triangulation&#xA;of the surface sites&lt;/li&gt;&#xA;&lt;li&gt;Assign on-top, bridge, and hollow adsorption sites at the nodes,&#xA;edges, and face centers of the Del. Triangulation&lt;/li&gt;&#xA;&lt;li&gt;Generate structures from a molecule positioned at these sites.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I didn't understand the first point. What does it mean by &amp;quot;Miller index of the highest sites&amp;quot;? Is it talking about some threshold value, or is it something else?&#xA;Any help in this regard would be appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="8004" LastEditorUserId="5" LastEditDate="2023-09-26T23:30:13.513" LastActivityDate="2023-09-26T23:30:13.513" Title="What is the Miller index of the highest site?" Tags="|pymatgen|adsorption|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11669" PostTypeId="2" ParentId="11664" CreationDate="2023-09-26T23:29:04.167" Score="1" Body="&lt;h1&gt;The unit conversions&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://i.stack.imgur.com/aSQGa.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;SI base units for Ohms&lt;/a&gt; are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\Omega = \frac{\textrm{kg}\cdot \textrm{m}^2}{\textrm{s}^3\cdot \textrm{A}^2}\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since 1 Joule is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{2}&#xA;\textrm{J} = \frac{\textrm{kg}\cdot \textrm{m}^2}{\textrm{s}^2},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and 1 Coulomb is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{3}&#xA;\textrm{C} = \textrm{A}\cdot \textrm{s},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;we have:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{4}&#xA;\Omega = \frac{\textrm{J}\cdot \textrm{s}}{\textrm{C}^2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The final units of the output from your software, are as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;\frac{1}{\Omega \cdot \textrm{cm}} = \frac{\textrm{C}^2}{\textrm{J}\cdot \textrm{s}\cdot \textrm{cm}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You then said:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I am interested in converting these output values into the more familiar unit of e2/hc.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So let's first see what the units are for that quantity:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{6}&#xA;\left[ \frac{e^2}{hc}\right] = \frac{\textrm{C}^2}{\textrm{J}\cdot  \textrm{m}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Even if we convert cm to m in Eq. (5):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{7}&#xA;\frac{1}{\Omega \cdot \textrm{cm}} = \frac{\textrm{C}^2}{\textrm{J}\cdot \textrm{s}\cdot \textrm{cm}}\times \frac{100~\textrm{cm}}{\textrm{m}} = \frac{100 ~ \textrm{C}^2}{\textrm{J}\cdot \textrm{s}\cdot \textrm{m}},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;we still have incompatible units because what the software is giving you has &amp;quot;seconds&amp;quot; in the denominator and what you want does not.&lt;/p&gt;&#xA;&lt;p&gt;Perhaps what you want is not &lt;span class=&quot;math-container&quot;&gt;$e^2/hc$&lt;/span&gt; but &lt;span class=&quot;math-container&quot;&gt;$e^2/(\epsilon_0hc)$&lt;/span&gt;, but even then, and even if you were to convert cm&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt; to Joules, you would not get compatible units.&lt;/p&gt;&#xA;&lt;h1&gt;The final recommendation&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;I recommend to stick with the units that the software is using when printing the output&lt;/strong&gt;, until you know better what unit system you would like your publication to use. Almost always, the authors of the software know very much what they're doing, and they will print the output in a unit that is acceptable for their own publications.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-26T23:29:04.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11670" PostTypeId="1" AcceptedAnswerId="11671" CreationDate="2023-09-27T00:08:39.490" Score="2" ViewCount="114" Body="&lt;p&gt;I've been getting the following error whenever I use CCSD(T) and the ORCA Forums don't have an answer to this one:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[file orca_numfreq/numfreq_utils.cpp, line 421]: Error (ORCA_NUMCALC): NCalcs not set&#xA;&#xA;The input file is as follows: &#xA;&#xA;!CCSD(T) DKH DEF2-TZVP FREQ VeryTightSCF&#xA;&#xA;* xyz 0 1&#xA;Zn 0.000 0.000 0.000&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there something missing here? Sorry, I am still relatively new to ORCA and DFT calculations. I am trying to calculate the ionization enthalpy of Zn, and I'm basing this on &lt;a href=&quot;https://doi.org/10.1016/S0009-2614(99)00665-X&quot; rel=&quot;nofollow noreferrer&quot;&gt;a paper&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6052" LastEditorUserId="5" LastEditDate="2023-09-27T00:14:48.433" LastActivityDate="2023-09-27T08:26:59.540" Title="ORCA Error: NCalcs not set" Tags="|quantum-chemistry|electronic-structure|orca|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11671" PostTypeId="2" ParentId="11670" CreationDate="2023-09-27T08:26:59.540" Score="3" Body="&lt;p&gt;There is no point of doing frequency calculations for a single atom, since atoms do not have vibrations, which means that they do not have vibrational frequencies. The enthalpies of single atoms can be trivially calculated by hand, from its definition:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = E_{ele} + ZPE + (U(T)-U(0)) + pV&#xA;$$&lt;/span&gt;&#xA;For atoms, and under the standard approximations, ZPE is zero (because there are no vibrations), U(T)-U(0) (the difference of internal energies at the target temperature and at 0 K) is completely contributed by translational degrees of freedom and amounts to (3/2)RT, and pV=RT. Therefore, to get the enthalpy of a single atom, you just need to &lt;strong&gt;add (5/2)RT to the electronic energy&lt;/strong&gt; of the atom, &lt;span class=&quot;math-container&quot;&gt;$E_{ele}$&lt;/span&gt;. Note that this is also why the isobaric molar heat capacities of monoatomic gases are (5/2)R. Of course, if you are solely interested in calculating the ionization enthalpies, then things are even simpler: as the enthalpy corrections of both the neutral atoms and the atomic cations are (5/2)RT, they cancel out when calculating the ionization enthalpies, so that you don't even need to calculate the (5/2)RT correction.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, as the paper you mentioned is quite old, it may be worthwhile to consider using methods developed (or gained popularity) in the past two decades instead, which gives you much more accurate energies at affordable cost. For example:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The electronic energies may be calculated using a selected CI, a DMRG, or a FCIQMC method, which give results that are much closer to full CI than CCSD(T) gives. Within ORCA, the most convenient choice may be the &lt;strong&gt;ICE&lt;/strong&gt; method, which belongs to the category of selected CI methods, and has the extra advantage that its wavefunction has no spin contamination.&lt;/li&gt;&#xA;&lt;li&gt;Explicitly correlated methods (e.g. &lt;strong&gt;F12&lt;/strong&gt; or transcorrelated methods) or complete basis set &lt;strong&gt;(CBS) extrapolations&lt;/strong&gt; can be used to minimize the basis set error. ORCA supports both F12 and CBS extrapolations.&lt;/li&gt;&#xA;&lt;li&gt;&lt;strong&gt;Spin-orbit coupling&lt;/strong&gt; should be considered, since single atoms have unquenched orbital angular momenta, which may give a non-negligible energy contribution when they couple with the spin angular momenta.&lt;/li&gt;&#xA;&lt;li&gt;If possible, and particularly if you want to study heavier elements, use &lt;strong&gt;X2C&lt;/strong&gt; instead of DKH. X2C is not much more expensive than DKH, but provides essentially exact relativistic energies compared to solving the Dirac equation. For atoms you can even remove the word &amp;quot;essentially&amp;quot; - X2C is an exact method, and it acquires minuscule errors for molecules only because the inter-atomic blocks of certain matrices are typically neglected for efficiency reasons.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-09-27T08:26:59.540" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11672" PostTypeId="2" ParentId="11665" CreationDate="2023-09-27T09:06:44.617" Score="4" Body="&lt;p&gt;What the doc wants to say is that the program may make an automatic choice of the auxiliary basis set (typically def2/J for non-relativistic calculations and SARC/J for relativistic ones, if I'm not mistaken), but in some (not all) cases they may not be suited for your basis set. It is well-established that def2/J is suitable for basis sets that begin with def2 (at least when they do not carry diffuse functions; for def2 basis sets with diffuse functions, e.g. ma-def2-TZVP and def2-TZVPD, there seems to be some debate on whether def2/J is suitable for them), and SARC/J is suitable for all-electron relativistic basis sets for ZORA or DKH (again, at least when they do not carry diffuse functions). In other cases, and especially when the basis set has a different number of core electrons than the respective def2 basis sets (e.g. the aug-cc-pVDZ-PP basis set that you used, which has less core electrons than e.g. def2-SVP), the default def2/J auxiliary basis set may not be suitable.&lt;/p&gt;&#xA;&lt;p&gt;To find a suitable auxiliary basis set, first look at the basis set list in the ORCA manual (somewhere near the beginning of the &amp;quot;Choice of Basis Set&amp;quot; subsection in the &amp;quot;Detailed Documentation&amp;quot; section), and see whether there are auxiliary basis sets that suit your orbital basis set, as suggested by the names of the auxiliary basis sets. For RI-DFT calculations, you should use basis sets that end with &amp;quot;/J&amp;quot;. When in doubt, refer to the original references of the auxiliary basis sets to see if they are indeed designed to work with your orbital basis set.&lt;/p&gt;&#xA;&lt;p&gt;To use the auxiliary basis set, either type its name in the line that begins with &amp;quot;!&amp;quot;, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP def2-SVP def2/J&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or use the &amp;quot;NewAuxJGTO&amp;quot; keyword in the %basis block:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%basis&#xA;  NewGTO Pt &amp;quot;SARC-ZORA-TZVP&amp;quot; end&#xA;  NewAuxJGTO Pt &amp;quot;SARC/J&amp;quot; end&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If you cannot find a suitable auxiliary basis set, you may search for such a basis set on &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Basis Set Exchange (BSE)&lt;/a&gt;, and enter the definitions of the basis set into the ORCA input file (the manual contains examples of how to do this, I'll not reproduce them here).&lt;/p&gt;&#xA;&lt;p&gt;If even the BSE does not contain a suitable basis set, you may use the AutoAux functionality of ORCA to automatically generate an auxiliary basis set. Simply add the AutoAux keyword in the line that begins with &amp;quot;!&amp;quot;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B2PLYP aug-cc-pVTZ autoaux&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or in the %basis block:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%basis&#xA;  NewGTO Pt &amp;quot;cc-pVTZ-PP&amp;quot; end&#xA;  NewAuxJGTO Pt &amp;quot;autoaux&amp;quot; end&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The auxiliary basis sets generated by AutoAux are essentially always suitable for the orbital basis set that you specified (EDIT: as Susi Lehtola correctly pointed out, for double-zeta basis sets, and in some (but not all) cases, AutoAux gives inferior accuracy than hand-tuned basis sets. See, e.g. Table 5 of &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.6b0104&quot; rel=&quot;nofollow noreferrer&quot;&gt;the AutoAux paper&lt;/a&gt;). However, they are usually larger than necessary (because they are not fine-tuned as e.g. the def2/J and SARC/J basis sets are) and are more prone to basis set linear dependency problems.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-09-27T15:38:25.873" LastActivityDate="2023-09-27T15:38:25.873" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11673" PostTypeId="2" ParentId="11658" CreationDate="2023-09-27T19:24:48.553" Score="3" Body="&lt;p&gt;Setting the &lt;code&gt;unit='Bohr'&lt;/code&gt; flag in &lt;code&gt;gto.M&lt;/code&gt; (as originally suggested in the comments) resolved the issue in the latest version of the code above.  Presumably there is a discrepancy in the default values of units passed to &lt;code&gt;numint&lt;/code&gt; functions and &lt;code&gt;gto.M&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7989" LastActivityDate="2023-09-27T19:24:48.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11674" PostTypeId="2" ParentId="11546" CreationDate="2023-09-28T07:52:54.117" Score="2" Body="&lt;p&gt;Since you mentioned the Materials Project, I assume you are talking about computational results.&lt;/p&gt;&#xA;&lt;p&gt;Formation energy is the energy with respect to some reference states. This is used for example with DFT results, since the absolute energy output by the program is not very useful without a reference. Energy above the hull is referring to the distance above the convex hull, which is formed by the lowest calculated states. In DFT, anything on the convex hull is considered a ground state, i.e. it is a stable state at 0K. For a simple binary system, you can calculate the formation energy by &lt;span class=&quot;math-container&quot;&gt;$E_f = E - (1-x)E_1 - xE_2$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; is the energy of the material and &lt;span class=&quot;math-container&quot;&gt;$E_1$&lt;/span&gt; is the energy of the reference at &lt;span class=&quot;math-container&quot;&gt;$x=0$&lt;/span&gt; composition and &lt;span class=&quot;math-container&quot;&gt;$E_2$&lt;/span&gt; is the energy of the reference at &lt;span class=&quot;math-container&quot;&gt;$x=1$&lt;/span&gt; composition. To get the energy above the hull, you have to know what the nearby stable phases are.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example. If you go to the Materials Project page for &lt;a href=&quot;https://next-gen.materialsproject.org/materials/mp-22862&quot; rel=&quot;nofollow noreferrer&quot;&gt;NaCl&lt;/a&gt; or open it in their phase diagram app, you will see the binary convex hull. The reference states are pure Na and pure Cl. Since they are the stable reference states, they will have a formation energy of 0 and also a hull distance of 0. NaCl also has a hull distance of 0 because it is a ground state, but its formation energy is nonzero. If you hover over the points, you will see the formation energy (usually negative) and hull distance (always positive) of each one. Note that formation energies can be positive, like on the Na side of the diagram, but usually people are looking for negative formation energies.&lt;/p&gt;&#xA;&lt;p&gt;If you are comparing data from different databases, I think that the formation energy is probably safer because it only depends on the reference states and not on the ground states that that person found.&lt;/p&gt;&#xA;" OwnerUserId="8027" LastActivityDate="2023-09-28T07:52:54.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11675" PostTypeId="2" ParentId="10384" CreationDate="2023-09-28T08:17:22.997" Score="2" Body="&lt;p&gt;You may want to look into cluster expansion codes because they generally have a robust structure generation/mapping system. The general idea with this type of code is that you start with a particular primitive structure and then create different unique atomic orderings and supercells of that structure. What you want to do is the reverse, i.e. take a lot of supercells and see if they map back onto a structure that you provide. Depending on how complicated your structures are, some of these might be overkill. For example if your structures are simple supercells with no lattice or atomic distortions, then you don't need a very advanced mapping tool.&lt;/p&gt;&#xA;&lt;p&gt;Here are a few:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ATAT&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/manual/node50.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;mmaps program&lt;/a&gt; lets you map unrelaxed (i.e. perfect) structures onto a reference lattice.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/prisms-center/CASMcode&quot; rel=&quot;nofollow noreferrer&quot;&gt;CASM&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Can import through the CLI or map structures directly using the &lt;a href=&quot;https://github.com/prisms-center/CASMcode_mapping/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python interface&lt;/a&gt;. Structures do not have to be unrelaxed, so it can handle lattice deformation, atomic deformation, vacancies, etc. Uses POSCARs for structures.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://gitlab.com/computationalmaterials/clease&quot; rel=&quot;nofollow noreferrer&quot;&gt;CLEASE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Can import structures through the &lt;a href=&quot;https://clease.readthedocs.io/en/stable/import_structures.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python interface&lt;/a&gt;. It looks like there is a two-step import process that requires structures to be unrelaxed at first. Uses ASE for structures.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://icet.materialsmodeling.org/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ICET&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Can import structures through the &lt;a href=&quot;https://icet.materialsmodeling.org/advanced_topics/mapping_structures.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Python interface&lt;/a&gt;. Structures can have vacancies, atomic displacements, and lattice distortions. Uses ASE for structures.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="8027" LastEditorUserId="8027" LastEditDate="2023-10-01T05:23:15.930" LastActivityDate="2023-10-01T05:23:15.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11676" PostTypeId="2" ParentId="1644" CreationDate="2023-09-28T18:18:50.030" Score="3" Body="&lt;p&gt;Since I just answered this over on chemistry.stackexchange then spotted the question here, I'm going to &lt;a href=&quot;https://chemistry.stackexchange.com/a/176546/137929&quot;&gt;link it&lt;/a&gt; and repeat the essential point.&lt;/p&gt;&#xA;&lt;p&gt;The method suggested by Tristan is mostly valid, but the more standard approach is to calculate &lt;span class=&quot;math-container&quot;&gt;$g_{abs}$&lt;/span&gt; directly as 4 times the ratio of rotational strength (the imaginary part of the dot product of electric and magnetic transition dipole moments) to the dipole strength.&lt;/p&gt;&#xA;" OwnerUserId="8037" LastActivityDate="2023-09-28T18:18:50.030" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11677" PostTypeId="1" CreationDate="2023-09-29T13:17:24.590" Score="6" ViewCount="105" Body="&lt;p&gt;Can someone please share with me a method to compute the elastic constants of the unit cell  and doped supercell of a material?&lt;/p&gt;&#xA;&lt;p&gt;In my calculation I use Quantum ESPRESSO. And I already tried Thermo_pw, it works fine for the unit cell but for the doped supercell it fails and I get the message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MPI_ABORT was invoked on rank 28 in communicator MPI_COMM_WORLD&#xA;with errorcode 2.&#xA;&#xA;NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.&#xA;You may or may not see output from other processes, depending on&#xA;exactly when Open MPI kills them.&#xA;-------------------------------------------------------------------------&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2023-09-30T12:42:43.913" Title="How can I calculate the elastic properties of a unit cell and a supercell?" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|physical-properties-of-materials|elasticity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11678" PostTypeId="1" CreationDate="2023-09-29T15:24:19.440" Score="2" ViewCount="192" Body="&lt;p&gt;Suppose I have a protein PDB file, and I want to know which atoms have bonds between them. How can this be done?&lt;/p&gt;&#xA;&lt;p&gt;Sometimes people suggest using the &lt;code&gt;CONECT&lt;/code&gt; field for that purpose. However, some PDB files do not have this field.&lt;/p&gt;&#xA;&lt;p&gt;Example: &lt;a href=&quot;https://www.rcsb.org/structure/4osk&quot; rel=&quot;nofollow noreferrer&quot;&gt;4OSK.pdb (Crystal structure of TAL effector reveals the recognition between asparagine and guanine)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;NOTE: I need bond information so that I can use this information to compute ForceFields along with MD simulation.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-10-02T11:30:43.723" LastActivityDate="2023-10-02T15:03:14.357" Title="From a PDB file, how may I know which atoms have bonds between them?" Tags="|proteins|pdb|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="11679" PostTypeId="2" ParentId="11677" CreationDate="2023-09-30T12:42:43.913" Score="4" Body="&lt;p&gt;There is new tool called &lt;a href=&quot;https://github.com/zhongliliu/elastool&quot; rel=&quot;nofollow noreferrer&quot;&gt;ElasTool&lt;/a&gt;. It is a Python-based toolkit for computing the second-order elastic constants (SOECs) and mechanical properties of crystal systems. It is designed to integrate with VASP and can be interfaced with other DFT packages also.&#xA;For more details check out the &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465521002927&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="88" LastActivityDate="2023-09-30T12:42:43.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11680" PostTypeId="2" ParentId="10662" CreationDate="2023-09-30T20:09:35.213" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10662/is-raspa2-a-sensible-monte-carlo-software-to-find-adsorption-sites-within-porous#comment22844_10662&quot;&gt;B. Kelly's comment&lt;/a&gt; is essentially an answer to the question:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The folks who made it know what they are doing and have a good reputation. The code is not known for being user friendly though. The science should be good.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I can delete this Community Wiki answer if B. Kelly or someone else wants to write a better answer! Just write a comment to let me know :)&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-09-30T20:09:35.213" CommentCount="1" CommunityOwnedDate="2023-09-30T20:09:35.213" ContentLicense="CC BY-SA 4.0" />
  <row Id="11681" PostTypeId="2" ParentId="11678" CreationDate="2023-10-01T07:56:59.953" Score="1" Body="&lt;p&gt;I got a clue from the comments of Anon.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NSeJd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NSeJd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;A bond is present when the distance between two atoms is lower than the sum of the Van der Waals radii of the two atoms.&lt;/p&gt;&#xA;&lt;p&gt;Van der Waals radii are typically looked up from a preexisting table, not calculated. We can find such tables in chemical reference books or online.&lt;/p&gt;&#xA;&lt;p&gt;For instance, &lt;a href=&quot;https://www.researchgate.net/figure/an-der-Waals-radii-of-atoms_tbl2_40906835&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;strong&gt;here is a link&lt;/strong&gt;&lt;/a&gt; that supplies the following Van der Waals radii table:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/vHeWC.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/vHeWC.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;Please note that&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;MD simulation software like &lt;a href=&quot;http://amber.manchester.ac.uk/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Amber&lt;/a&gt;, &lt;a href=&quot;https://www.ks.uiuc.edu/Training/Tutorials/namd/namd-tutorial-unix-html/node25.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;NAMD&lt;/a&gt;, &lt;a href=&quot;https://manual.gromacs.org/current/reference-manual/topologies/parameter-files.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;GROMACS&lt;/a&gt;, etc. use parameter-topology files to supply such information.&lt;/p&gt;&#xA;&lt;p&gt;These files are the results of long-term experimentation and testing for decades.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, it is not a good idea for the new/learner/beginner/hobby MD simulation software developers to try to compute bond information themselves.&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-10-02T15:03:14.357" LastActivityDate="2023-10-02T15:03:14.357" CommentCount="6" CommunityOwnedDate="2023-10-02T15:03:14.357" ContentLicense="CC BY-SA 4.0" />
  <row Id="11682" PostTypeId="2" ParentId="11666" CreationDate="2023-10-01T08:33:47.480" Score="5" Body="&lt;p&gt;I would recommend to obtain VB top and CB bottom energy values from the output file. The occupation numbers are listed if 'verbose' mode is active. In any output mode the energies should be printed out for every k-point.&lt;/p&gt;&#xA;&lt;p&gt;For example:&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;    End of self-consistent calculation&#xA;&#xA;          k = 0.0000 0.0000 0.0000 ( 51347 PWs)   bands (ev):&#xA;&#xA;   -41.2118 -41.2117 -41.2117 -41.2117 -41.2117 -41.2117 -41.2116 -41.2116&#xA;...&#xA;     3.0299   3.0299   3.1717   3.1717   3.4488   3.4488   3.9082   3.9082&#xA;     5.5990   5.5990   6.3247   6.3247   7.0692   7.0692   7.2538   7.2538&#xA;     7.4689   7.4689   7.6844   7.6844   9.0266   9.0266   9.2530   9.2530&#xA;     9.4975   9.4975   9.8699   9.8699&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;In this example Fermi energy is 5.125 eV, so that VB top is 3.908 eV and CB bottom is 5.599 eV. Note, these values are for Gamma point k = 0,0,0. You may need to consider many k-points to obtain the global values.&lt;/p&gt;&#xA;&lt;p&gt;Note 1. The exact energy values depend from many factors, the most important is the used pseudopotentials (pps). So that you may have them both positive or negative - there is no error. Instead of the absolute values the residuals (like band gap CB-VB) should be compared when different software codes / pps are used.&lt;/p&gt;&#xA;&lt;p&gt;Note 2. I would not recommend to use the Fermi level value from &lt;b&gt;nscf&lt;/b&gt; calculation in QE, it looks strange. The scf one should be more reasonable.&lt;/p&gt;&#xA;" OwnerUserId="6566" LastEditorUserId="6566" LastEditDate="2023-11-12T06:59:43.540" LastActivityDate="2023-11-12T06:59:43.540" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11683" PostTypeId="2" ParentId="9260" CreationDate="2023-10-01T16:05:26.690" Score="1" Body="&lt;p&gt;Since this is not an active problem for the researcher anymore, I'm removing it from the unanswered queue, but if anyone wants to write another answer, please just comment here and I will remove this Community Wiki!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-10-01T16:05:26.690" CommentCount="0" CommunityOwnedDate="2023-10-01T16:05:26.690" ContentLicense="CC BY-SA 4.0" />
  <row Id="11684" PostTypeId="1" AcceptedAnswerId="11689" CreationDate="2023-10-02T02:12:34.690" Score="4" ViewCount="91" Body="&lt;p&gt;I am performing an NEB calculation with VASP and VTST. I would like to visualize the atoms along the path and to calculate their displacements. When I have a single relaxation's XDATCAR, I can unwrap the trajectories using ASE and get the displacements:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;steps = read(xdatcar, ':', format='vasp-xdatcar')&#xA;start = steps[0].get_positions(wrap=False)&#xA;disp = [atoms.get_positions(wrap=False)-start for atoms in steps]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, this is not working for multiple images along the NEB path when I replace &lt;code&gt;steps&lt;/code&gt; with an array containing the POSCAR for each image. The atoms near the boundary jump back and forth between images which makes the visualization messy and the displacement calculation does not work. I know that I can do this in other tools such as OVITO, but I would prefer to use ASE or something that interfaces with it because I am using &lt;code&gt;ase.visualize.view&lt;/code&gt; for the trajectories.&lt;/p&gt;&#xA;" OwnerUserId="8027" LastActivityDate="2023-10-02T23:31:52.897" Title="How to get displacements along VASP NEB trajectory?" Tags="|vasp|python|atomic-simulation-environment|ovito|nudged-elastic-band|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11685" PostTypeId="1" CreationDate="2023-10-02T04:21:11.850" Score="2" ViewCount="146" Body="&lt;p&gt;I am running polymer simulations inside a spherical region. I have loaded the polymer using read_data command. I want to add fixed number of individual new atom types inside this sphere while it avoids the polymer.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;log            ./atom_create.out&#xA;lattice        fcc 0.85&#xA;units          lj&#xA;atom_style     full&#xA;boundary       f f f&#xA;&#xA;read_data     ./case_1/1/polymer_centered.input&#xA;&#xA;region         outerbox sphere 0.0 0.0 0.0 8.0 side in units box&#xA;&#xA;create_atoms   3 region outerbox&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This fills the fcc points inside the sphere and gives no control on how many atoms to add. I have tried doing&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;create_atoms   3 random 100 0413 outerbox overlap 1.0 maxtry 50&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;but I get an error - illegal create_atoms command. Is there  a way to avoid the polymer while adding new atoms?&lt;/p&gt;&#xA;" OwnerUserId="1605" LastActivityDate="2023-10-02T04:21:11.850" Title="Help with LAMMPS create_atoms and delete_atoms command" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11687" PostTypeId="1" CreationDate="2023-10-02T20:14:18.500" Score="1" ViewCount="159" Body="&lt;p&gt;In the examples directory of Quantum ESPRESSO PHonon package, &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/tree/develop/PHonon/examples/example15&quot; rel=&quot;nofollow noreferrer&quot;&gt;example15&lt;/a&gt; shows how to get Raman and Infrared spectra. In the example it contains two compounds ZnO and CO2. In case of CO2, in the &lt;code&gt;ph.x&lt;/code&gt; input file, we can put &lt;code&gt;epsil = .true.&lt;/code&gt;. However, in case of ZnO, which have metallic constituent, we have to do the calculation with &lt;code&gt;epsil = .false.&lt;/code&gt;. Hence it cannot create Born effective charge file and also therefore no LO-TO splitting in phonon optical modes. The output file give the message following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Z* not found in file MnScFeGa222.fc, TO-LO splitting at q=0 will be absent!&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;It generates the phonon dispersion curve without any LO-TO spiting at gamma. So my question is: is the LO-TO spiting zero for all metallic compounds? Quantum ESPRESSO always give zero LO-TO splitting unless &lt;code&gt;epsil = .true.&lt;/code&gt;. But we cannot set it &lt;code&gt;.true.&lt;/code&gt; for metallic systems.  Hence we cannot create Born effective charge file. Can please anyone share your valuable knowledge on that?&lt;/p&gt;&#xA;" OwnerUserId="8064" LastEditorUserId="6055" LastEditDate="2023-10-05T07:16:37.017" LastActivityDate="2023-10-05T07:16:37.017" Title="How to get Born effective charge using ph.x for compounds whose constituents are metallic?" Tags="|quantum-espresso|phonons|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-20T03:25:00.893" ContentLicense="CC BY-SA 4.0" />
  <row Id="11688" PostTypeId="1" AcceptedAnswerId="11690" CreationDate="2023-10-02T22:14:47.690" Score="3" ViewCount="344" Body="&lt;p&gt;I am new to LAMMPS and have been working my way through available examples before diving into my own research using LAAMPS. I am currently working through the tutorial given here: &lt;a href=&quot;https://avogadro.cc/docs/extensions/lammps-input-for-water/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://avogadro.cc/docs/extensions/lammps-input-for-water/&lt;/a&gt; . I see that this question has been &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1408/how-to-convert-a-molecular-structure-made-in-avogadro-to-a-lammps-coordinate-fil&quot;&gt;asked here before&lt;/a&gt;, but the post was abandoned by the user so there was no indication as to whether or not they sorted out their problem, and if so how. There was also a post on an Avogadro forum &lt;a href=&quot;https://discuss.avogadro.cc/t/avogadro-and-lammps/423&quot; rel=&quot;nofollow noreferrer&quot;&gt;that asked the same question&lt;/a&gt;, but there were no responses given.&lt;/p&gt;&#xA;&lt;p&gt;I am having the same issue as this other user. That is, I am able to get to the point where I have to save the structure file in a LAMMPS readable format, but my computer tells me that water.lmpdat is not a valid file name. Saving the .lmp file did work, but this is the input script and not the coordinate data file for the water box.&lt;/p&gt;&#xA;&lt;p&gt;For reference, I am running Windows 10, and have Avogadro version 1.2.0 installed onto my computer. I have tried using other file extensions like .dat, .data, .in, and .input and I am given the same &amp;quot;File name is not valid error&amp;quot;. I have also tried independently generating the coordinate data file and am met with formatting errors, so I would like to try this approach again to see if it works this time. Any insight on this matter is welcome, and if there is any other information I should provide, let me know in a reply/comment and I will provide what I can.&lt;/p&gt;&#xA;" OwnerUserId="8065" LastActivityDate="2023-10-02T23:37:47.200" Title="Converting molecular structure from Avogadro into LAMMPS coordinate file" Tags="|lammps|avogadro|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11689" PostTypeId="2" ParentId="11684" CreationDate="2023-10-02T23:23:50.983" Score="3" Body="&lt;p&gt;This is easy. You can simply use &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/geometry.html#ase.geometry.find_mic&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.geometry.find_mic&lt;/code&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.geometry import find_mic&#xA;&#xA;disp = [find_mic(atoms.get_positions()-start.get_positions(), &#xA;        cell=atoms.cell, pbc=True)[0] for atoms in steps]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-10-02T23:31:52.897" LastActivityDate="2023-10-02T23:31:52.897" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11690" PostTypeId="2" ParentId="11688" CreationDate="2023-10-02T23:37:47.200" Score="4" Body="&lt;p&gt;My suggestion, frankly, is to use a newer version of Avogadro. The &lt;a href=&quot;https://two.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;betas of Avogadro2&lt;/a&gt; include a much more substantial LAMMPS input generator. This includes generating both the input and the &lt;code&gt;lmpdat&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;On the downside, I haven't had much help updating the user documentation for Avo2, so help is definitely appreciated. Feedback is, as always, welcome on our forum: &lt;a href=&quot;https://discuss.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://discuss.avogadro.cc/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/G2kMf.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/G2kMf.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-10-02T23:37:47.200" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11691" PostTypeId="1" CreationDate="2023-10-03T08:20:41.013" Score="3" ViewCount="92" Body="&lt;p&gt;I am beginner regarding the use of Gaussian. Currently, i am trying to study the vibration of HgCl2. I have an error:  Error termination via Lnk1e in /nfs/opt/Gaussian/16.c01/avx2/l301.exe&#xA;Any help is highly appreciated, because I did not find where is the problem.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;Stoichiometry    Cl2Hg&#xA; Framework group  D*H[O(Hg),C*(Cl.Cl)]&#xA; Deg. of freedom     1&#xA; Full point group                 D*H     NOp   8&#xA; Largest Abelian subgroup         D2H     NOp   8&#xA; Largest concise Abelian subgroup C2      NOp   2&#xA;                         Standard orientation:                         &#xA; ---------------------------------------------------------------------&#xA; Center     Atomic      Atomic             Coordinates (Angstroms)&#xA; Number     Number       Type             X           Y           Z&#xA; ---------------------------------------------------------------------&#xA;      1         80           0        0.000000    0.000000    0.000000&#xA;      2         17           0        0.000000    0.000000    2.430000&#xA;      3         17           0        0.000000    0.000000   -2.430000&#xA; ---------------------------------------------------------------------&#xA; Rotational constants (GHZ):           0.0000000           1.2237516           1.2237516&#xA; General basis read from cards:  (5D, 7F)&#xA; ======================================================================================================&#xA;                                       Pseudopotential Parameters&#xA; ======================================================================================================&#xA;  Center     Atomic      Valence      Angular      Power&#xA;  Number     Number     Electrons     Momentum     of R      Exponent        Coefficient   SO-Coeffient&#xA; ======================================================================================================&#xA; Wanted an integer as input.&#xA; Found a floating point number as input.&#xA;       1.96406000D+01         1.58755454D-01                                     &#xA; ?&#xA; Error termination via Lnk1e in /nfs/opt/Gaussian/16.c01/avx2/l301.exe at Mon Oct  2 16:44:06 2023.&#xA; Job cpu time:       0 days  0 hours  0 minutes  4.0 seconds.&#xA; Elapsed time:       0 days  0 hours  0 minutes  0.5 seconds.&#xA; File lengths (MBytes):  RWF=     17 Int=      0 D2E=      0 Chk=      2 Scr=      2&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8066" LastEditorUserId="2194" LastEditDate="2023-10-18T20:49:26.687" LastActivityDate="2023-10-18T20:49:26.687" Title="Error in output in gaussian" Tags="|gaussian|" AnswerCount="0" CommentCount="3" ClosedDate="2023-10-13T16:44:29.877" ContentLicense="CC BY-SA 4.0" />
  <row Id="11692" PostTypeId="2" ParentId="11506" CreationDate="2023-10-03T12:02:29.353" Score="2" Body="&lt;p&gt;With Psi4, I have been partially successful in obtaining the 1-PDM at the CCSD(t) level. Sharing the code,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import psi4&#xA;import scipy&#xA;&#xA;mol = psi4.geometry(&amp;quot;&amp;quot;&amp;quot;&#xA;0 1&#xA;O  0.025976  -0.000000  -0.067996&#xA;H  -0.028998  -0.000000  0.892837&#xA;H  0.966586  0.000000  -0.271648&#xA;&#xA;symmetry c1&#xA;no_reorient&#xA;&amp;quot;&amp;quot;&amp;quot;)&#xA;psi4.set_options({'basis': '3-21G', 'freeze_core': 'false','print_mos': 'false','print':2, 'scf_type': 'Direct'})&#xA;_,cc_wfn = psi4.energy('ccsd(t)', return_wfn=True, molecule=mol) # CCSD(t) run &#xA;CCdm1=np.asarray(cc_wfn.Da())*2 # Obtain 1-particle density matrix as numpy array&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For 2-PDM, I have obtained the T1 and T2 arrays but need to have l1 and l2 arrays from CCSD(T) lambda module. Which I can not do after a lot of research.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;amps = cc_wfn.get_amplitudes()&#xA;TIjAb = amps['tIjAb'].to_array() # This looks like t2 of PySCF&#xA;TIA = amps['tIA'].to_array()     # This looks like t1 of PySCF&#xA;tau_IjAb = TIjAb + np.einsum(&amp;quot;ia,jb -&amp;gt; ijab&amp;quot;, TIA, TIA)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2023-10-03T12:02:29.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11693" PostTypeId="1" CreationDate="2023-10-03T13:15:51.890" Score="5" ViewCount="128" Body="&lt;p&gt;I want to start studying some single-atom catalysts doping with a transition metal. However, I do not what protocol I should follow.&lt;/p&gt;&#xA;&lt;p&gt;Based on the articles that I read, I should dope my surface only after I already optimized my unit cell and created my surface, however, how do I should decide what sites I will choose to make the substitution in my surface?&lt;/p&gt;&#xA;&lt;p&gt;For example, how to decide that this is the better substitution:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/h5cm0.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/h5cm0.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5898" LastEditorUserId="5898" LastEditDate="2023-10-03T17:45:49.810" LastActivityDate="2023-10-10T08:55:31.683" Title="How to model a doped surface?" Tags="|quantum-espresso|surfaces|transition-metals|doping|catalysis|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11694" PostTypeId="1" CreationDate="2023-10-03T16:35:15.450" Score="2" ViewCount="91" Body="&lt;p&gt;In VASP manual it is mentioned that the deorbitalized versions of SCAN and R2SCAN MetaGGA functionals do not depend on the kinetic energy density but instead on the Laplacian of the charge density.&lt;/p&gt;&#xA;&lt;p&gt;When calculating DOS and band structures, do I still need to provide a regular mesh in SCF calculation as in the case with hybrid functionals unlike fixing the charge density in NSCF calculation for PBE functionals?&lt;/p&gt;&#xA;&lt;p&gt;In other words, should I perform a SCF calculation to calculate the DOS unlike PBE functionals (where I simply need to fix the charge density) in a nscf run. In metaGGAs that compute the kinetic energy density I have to provide the regular mesh in addition to zero weight K points for band calculations. So for functionals like &amp;quot;R2SCAN-L&amp;quot; should the charge density be fixed ?&lt;/p&gt;&#xA;" OwnerUserId="8072" LastEditorUserId="8072" LastEditDate="2023-10-04T05:45:45.000" LastActivityDate="2023-10-04T05:45:45.000" Title="When calculating DOS and band structures, do I still need to provide a regular mesh for MetaGGA functionals as in the case with hybrid functionals?" Tags="|density-functional-theory|vasp|band-structure|density-of-states|functional|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11695" PostTypeId="2" ParentId="11693" CreationDate="2023-10-03T21:15:55.793" Score="4" Body="&lt;p&gt;You are showing an fcc (100) surface, and there is only one type of site to substitute. You want to generate a single-atom alloy (SAA) surface, then it doesn't matter which surface atom you replace with the dopant, because they are all equivalent. Your question is only relevant if it's a stepped surface. In that case, compare the energy of all possible SAA surface configurations, e.g. step-doped and terrace-doped, and go with the lowest-energy configuration.&lt;/p&gt;&#xA;&lt;p&gt;Generally speaking, there are two important energetics that you need to check for SAA surfaces before everything:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Surface mixing energy&lt;/em&gt; which evaluates the segregation propensity of each SAA surface w.r.t bulk. The dopant cannot even appear at the surface if it's positive.&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    E_{\mathrm{mix}} = E_{\mathrm{D}_1\mathrm{H}} + \tilde{E}_{\mathrm{bulkH}} - (E_{\mathrm{H}} + \tilde{E}_{\mathrm{bulkD}})&#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{D}_1\mathrm{H}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{H}}$&lt;/span&gt; are the energies of the SAA slab and the pure host slab, respectively, &lt;span class=&quot;math-container&quot;&gt;$\tilde{E}_{\mathrm{bulkH}}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\tilde{E}_{\mathrm{bulkD}}$&lt;/span&gt; are the per-atom energies of the bulk host and the bulk dopant, respectively.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;em&gt;Aggregation energy&lt;/em&gt; which evaluates the aggregation propensity of the dopant atoms forming clusters (e.g. dimers and trimers) on the host metal surface. A dispersed SAA phase cannot be formed if it's negative.&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    E_{\mathrm{agg}} = E_{\mathrm{D}_n\mathrm{H}} + (n-1)E_{\mathrm{D}} - nE_{\mathrm{D}_1\mathrm{H}} &#xA;\end{equation}&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{D}_n\mathrm{H}}$&lt;/span&gt; are the energies of an alloy slab with a surface cluster of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; dopant atoms, &lt;span class=&quot;math-container&quot;&gt;$E_{\mathrm{D}}$&lt;/span&gt; is the enenrgy of the pure dopant slab.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-10-10T08:55:31.683" LastActivityDate="2023-10-10T08:55:31.683" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11696" PostTypeId="1" AcceptedAnswerId="11697" CreationDate="2023-10-04T11:04:33.157" Score="3" ViewCount="253" Body="&lt;p&gt;I am trying to simulate a mixture of CO2 and N2 but I keep getting &lt;code&gt;ERROR: lost atoms: original 1500 current 1495&lt;/code&gt;. I have performed several energy minimizations and even tried increasing the size of the box, yet I am still getting this error. Can anyone help? Below is the input script and data files.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;units           real      &#xA;atom_style      full        &#xA;boundary        p p p&#xA;&#xA;read_data       CO2_initial.data&#xA;&#xA;pair_style      lj/cut/coul/long 12&#xA;pair_modify     tail yes                &#xA;bond_style      harmonic&#xA;angle_style     harmonic&#xA;kspace_style    pppm 1.0e-4  &#xA;&#xA;include PARM.lammps&#xA;    &#xA;molecule N2 N2.mol&#xA;create_atoms 0 random 5 428515 NULL mol N2 645341&#xA;&#xA;group CO2 type 1 2&#xA;group n2 type 3 4&#xA;#neighbor       2.0 bin&#xA;#neigh_modify   every 1 delay 0 check yes&#xA;                                             &#xA;#Minimization&#xA;                                               &#xA;thermo 10                                               &#xA;min_style sd&#xA;minimize    1.0e-4 1.0e-6 1000 10000&#xA;&#xA;variable        dt equal 1&#xA;timestep        ${dt}&#xA;&#xA;reset_timestep 0&#xA;&#xA;velocity all create 300 4932567 dist uniform&#xA;variable        kinetic_energy equal ke&#xA;variable        potential_energy equal pe&#xA;variable        pressure equal press   &#xA;variable        Temperature equal temp   &#xA;variable        Density equal density    &#xA;variable        total_energy equal etotal&#xA;&#xA;fix             1 all npt temp 300 300 100 iso 78.9539 78.9539 1000&#xA;thermos          1000&#xA;#fix            myave1 all ave/time 10 100 1000 v_Temperature v_kinetic_energy v_potential_energy v_total_energy v_pressure file energy1.data&#xA;thermo_style    custom step temp density epair ke etotal press vol&#xA;run             500000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;DATA FILES&lt;/h2&gt;&#xA;&lt;pre&gt;&lt;code&gt;**N2**&#xA;# N2 molecule file. TraPPE model.&#xA;&#xA;3 atoms&#xA;2 bonds&#xA;1 angles&#xA;&#xA;Coords&#xA;    &#xA;1   0.0 0.00 0.00&#xA;2   -0.55 0.00 0.00&#xA;3   0.55 0.00 0.00&#xA;&#xA;Types&#xA;&#xA;1   3&#xA;2   4 &#xA;3   4 &#xA; &#xA;&#xA;Charges&#xA;&#xA;1    0.964&#xA;2   -0.482&#xA;3   -0.482&#xA;&#xA;Bonds&#xA;&#xA;1   1      1      2&#xA;2   1      1      3&#xA;&#xA;Angles&#xA;&#xA;1   1      2      1      3&#xA;--------------------------------------------------------------------------&#xA;&#xA;&#xA;**PARM**&#xA;&#xA;# Masses&#xA;&#xA;mass            1   12.0107  #C&#xA;mass            2   15.9994  #O&#xA;mass            3   1e-20    #COM&#xA;mass            4   14.005 #N&#xA;&#xA;# Pair coeff&#xA;&#xA;pair_coeff      1 1 0.05365359 2.8000       &#xA;pair_coeff      2 2 0.15698643 3.05000          &#xA;pair_coeff      1 2 0.09177627989 2.9250   &#xA;pair_coeff      4 4 0.07153812 3.31000&#xA;pair_coeff      1 4 0.06195382926 3.055&#xA;pair_coeff      2 4 0.1059741198 3.180 &#xA;pair_coeff      * 3 0.000000000000 0.000    &#xA;&#xA;# Bond coeff&#xA;&#xA;bond_coeff      1 5000.00 1.16 &#xA;bond_coeff      2 5000.00 0.55&#xA;&#xA;# Angle coeff&#xA;&#xA;angle_coeff     1 500.0 180.00&#xA;angle_coeff     2 500.0 180.00&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8075" LastEditorUserId="7" LastEditDate="2023-10-04T12:27:41.910" LastActivityDate="2023-10-04T12:27:41.910" Title="&quot;ERROR: Lost atoms&quot; while simulating N2/CO2 mixture" Tags="|molecular-dynamics|lammps|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11697" PostTypeId="2" ParentId="11696" CreationDate="2023-10-04T11:58:49.687" Score="3" Body="&lt;p&gt;Your &lt;span class=&quot;math-container&quot;&gt;$\require{mhchem} \ce{N2}$&lt;/span&gt; molecule template has a virtual charge site with a stated mass of 1e-20 units, but your input file has no means of rigidifying the &lt;span class=&quot;math-container&quot;&gt;$\ce{N2}$&lt;/span&gt; molecules, and thus the dynamics cannot be integrated with any reasonable timestep.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-10-04T11:58:49.687" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11698" PostTypeId="2" ParentId="10658" CreationDate="2023-10-04T13:20:39.663" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Doesn't a cell's shape and cell's volume depend on the atoms'&#xA;positions?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Not really. The cell shape and size can be anything irrespective of atomic position. The cell is something that we repeat periodically in all the space dimensions. The atomic position doesn't have anything to do with it. I guess you are probably mistakenly assuming that the cell shape and size are determined by only the outer atoms! This is not the case.&lt;/p&gt;&#xA;&lt;p&gt;VASP, like many other DFT codes such as Quantum ESPRESSO, CASTEP, etc., is a 3d-periodic code. That means the supercell you construct in these codes will get repeated in all 3 directions. You can always do calculation of systems with lower dimensionality within a supercell by making vacuum (large lattice parameters) accordingly.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kMdip.png?s=256&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kMdip.png?s=256&quot; alt=&quot;Figure 1&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/kH45l.png?s=256&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kH45l.png?s=256&quot; alt=&quot;Figure 2&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can think of 1D chain of monoatomic carbon, for instance. You can have one C atom in a tetragonal cell at &lt;code&gt;(0,0,0)&lt;/code&gt; with large lattice parameters &lt;code&gt;a&lt;/code&gt;, &lt;code&gt;b&lt;/code&gt;, and &lt;code&gt;c&lt;/code&gt;. In this case, what you have is an isolated C atom (left figure). But if you choose &lt;code&gt;a&lt;/code&gt; and &lt;code&gt;b&lt;/code&gt; to be large and &lt;code&gt;c&lt;/code&gt; to be small, then what you have is an infinite C chain (right figure). Notice that you didn't change any atomic position. Still the C atom has &lt;code&gt;(0,0,0)&lt;/code&gt; position. But since now you reduced the length of the cell in one direction (namely &lt;code&gt;c&lt;/code&gt; - along z-axis), the cell volume changed.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Why can the cell's volume/shape and atomic position change independently in the ISIF tag?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Just like in the previous example the cell volume and the shape changed (volume decreased, and shape became cubic from tetragonal) even though the atomic position didn't, the atomic positions can also be changed keeping cell shape and/or volume fixed. The shape or volume of the supercell do not depend on the atomic position. The only thing to notice is that the supercell will get repeated in 3D space.&lt;/p&gt;&#xA;&lt;p&gt;In VASP's &lt;code&gt;ISIF&lt;/code&gt; tag, one controls how much degree of freedom one will allow in a relaxation calculations. For example, one may want to let the C chain system to be relaxed only along z-axis for which &lt;code&gt;ISIF=7&lt;/code&gt; needs to be applied. Full reference for &lt;code&gt;ISIF&lt;/code&gt; tag is &lt;a href=&quot;https://www.vasp.at/wiki/index.php/ISIF&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The same thing can be realized in Quantum ESPRESSO using the &lt;code&gt;cell_dofree&lt;/code&gt; parameter in &lt;code&gt;&amp;amp;CELL&lt;/code&gt; namecard &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm1158&quot; rel=&quot;nofollow noreferrer&quot;&gt;reference&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-10-04T13:20:39.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11699" PostTypeId="1" CreationDate="2023-10-04T17:05:18.480" Score="5" ViewCount="210" Body="&lt;p&gt;I wonder if the origin of the permanent dipole moment calculated by Gaussian (16) is always the center of mass (0,0,0 if &amp;quot;Nosymm is used)? For the neutral molecule it does not matter, but I am interested in the case when the molecule is not neutral.&lt;/p&gt;&#xA;" OwnerUserId="6296" LastActivityDate="2023-10-06T13:28:35.990" Title="How is the dipole moment defined in Gaussian?" Tags="|gaussian|dipole|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11700" PostTypeId="1" CreationDate="2023-10-04T19:14:44.573" Score="4" ViewCount="52" Body="&lt;p&gt;I'm trying to create a script to generate partial charges for a given .dat file.&lt;/p&gt;&#xA;&lt;p&gt;As an example of my process, I'm currently using gromacs to run minimization on a box of propane. It outputs a min.gro file, which i wrote a script to convert to min.dat so I can use Psi4. Here is the script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def gro_to_dat(input_file, output_file):&#xA;    with open(input_file, 'r') as gro, open(output_file, 'w') as dat:&#xA;        # Skip the title and total atoms lines in the .gro file&#xA;        gro.readline()&#xA;        num_atoms = int(gro.readline().strip())&#xA;&#xA;        # Write the initial lines to the .dat file&#xA;        dat.write(&amp;quot;molecule mol {\n&amp;quot;)&#xA;        dat.write(&amp;quot;   0 1\n&amp;quot;)&#xA;&#xA;        # Process each line in the .gro file&#xA;        for _ in range(num_atoms):&#xA;            line = gro.readline()&#xA;            atom_symbol = line[12:15].strip()[0]  # Extract the first character of atom name&#xA;            x, y, z = line[20:28].strip(), line[28:36].strip(), line[36:44].strip()&#xA;            dat.write(f&amp;quot;   {atom_symbol}   {x}   {y}   {z}\n&amp;quot;)&#xA;&#xA;        dat.write(&amp;quot;}\n&amp;quot;)&#xA;&#xA;gro_to_dat(&amp;quot;min.gro&amp;quot;, &amp;quot;min.dat&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And it creates a .dat file, which looks like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule mol {&#xA;   0 1&#xA;   C   3.384   2.059   2.720&#xA;   C   3.419   2.209   2.725&#xA;   C   3.308   2.297   2.664&#xA;   H   3.465   2.000   2.761&#xA;   H   3.368   2.026   2.617&#xA;   H   3.294   2.038   2.777&#xA;   ...&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Finally, my partial charge generation script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import psi4&#xA;&#xA;# Set Psi4 memory and number of threads&#xA;psi4.set_memory('8 GB')&#xA;psi4.set_num_threads(8)&#xA;&#xA;# Read the min.dat file for molecular geometry&#xA;with open(&amp;quot;min.dat&amp;quot;, 'r') as f:&#xA;    lines = f.readlines()&#xA;    molecule_data = &amp;quot;&amp;quot;.join(lines[1:-1])  # skip the first and last lines&#xA;&#xA;# Create the molecule object using the data from the file&#xA;molecule = psi4.geometry(molecule_data)&#xA;&#xA;# Set computation options &#xA;psi4.set_options({&#xA;    'basis': 'STO-3G',&#xA;    'scf_type': 'df',&#xA;    'e_convergence': 1e-6,&#xA;})&#xA;&#xA;# Perform a single-point energy computation to obtain wavefunction&#xA;energy, wfn = psi4.energy(&amp;quot;SCF&amp;quot;, return_wfn=True, molecule=molecule)&#xA;&#xA;# Compute the ESP charges&#xA;esp_charges = psi4.core.MoleculeESP.compute_esp_charges(wfn.molecule())&#xA;&#xA;# Write the ESP charges to a file&#xA;with open(&amp;quot;esp_charges.txt&amp;quot;, 'w') as f:&#xA;    for charge in esp_charges:&#xA;        f.write(f&amp;quot;{charge}\n&amp;quot;)&#xA;&#xA;print(&amp;quot;ESP charges written to esp_charges.txt&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I actually want to use 6-31G*, but even using STO-3G, the computation does not finish.&lt;/p&gt;&#xA;&lt;p&gt;My output is very long, but it basically is this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ==&amp;gt; Geometry &amp;lt;==&#xA;&#xA;    Molecular point group: c1&#xA;    Full point group: C1&#xA;&#xA;    Geometry (in Angstrom), charge = 0, multiplicity = 1:&#xA;&#xA;       Center              X                  Y                   Z               Mass&#xA;    ------------   -----------------  -----------------  -----------------  -----------------&#xA;         C            0.901238549949    -0.441467579029     0.193243059784    12.000000000000&#xA;         C            0.936238549949    -0.291467579029     0.198243059784    12.000000000000&#xA;         C            0.825238549949    -0.203467579029     0.137243059784    12.000000000000&#xA;         H            0.982238549949    -0.500467579029     0.234243059784     1.007825032230&#xA;                               ...&#xA;Running in c1 symmetry.&#xA;&#xA;  Rotational constants: A =      0.00022  B =      0.00020  C =      0.00020 [cm^-1]&#xA;  Rotational constants: A =      6.53586  B =      6.11387  C =      6.09670 [MHz]&#xA;  Nuclear repulsion = 18130296.238725978881121&#xA;&#xA;  Charge       = 0&#xA;  Multiplicity = 1&#xA;  Electrons    = 13000&#xA;  Nalpha       = 6500&#xA;  Nbeta        = 6500&#xA;&#xA;  ==&amp;gt; Algorithm &amp;lt;==&#xA;&#xA;  SCF Algorithm Type is DF.&#xA;  DIIS enabled.&#xA;  MOM disabled.&#xA;  Fractional occupation disabled.&#xA;  Guess Type is SAD.&#xA;  Energy threshold   = 1.00e-06&#xA;  Density threshold  = 1.00e-06&#xA;  Integral threshold = 1.00e-12&#xA;&#xA;  ==&amp;gt; Primary Basis &amp;lt;==&#xA;&#xA;  Basis Set: STO-3G&#xA;    Blend: STO-3G&#xA;    Number of shells: 8500&#xA;    Number of basis functions: 11500&#xA;    Number of Cartesian functions: 11500&#xA;    Spherical Harmonics?: true&#xA;    Max angular momentum: 1&#xA;Killed&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I've tried increasing memory, and have already downgraded my basis set, but nothing seems to be working.&lt;/p&gt;&#xA;" OwnerUserId="8083" LastEditorUserId="5" LastEditDate="2023-10-05T02:36:42.707" LastActivityDate="2023-10-05T02:36:42.707" Title="OOM Error Calculating ESP Charges with Psi4" Tags="|molecular-dynamics|computational-chemistry|high-performance-computing|psi4|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11701" PostTypeId="1" CreationDate="2023-10-05T02:04:20.123" Score="6" ViewCount="735" Body="&lt;p&gt;I see that some free MD simulation software are available online.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;VMD&lt;/li&gt;&#xA;&lt;li&gt;NAMD&lt;/li&gt;&#xA;&lt;li&gt;LAMMPS&lt;/li&gt;&#xA;&lt;li&gt;OpenMM&lt;/li&gt;&#xA;&lt;li&gt;GROMACS&lt;/li&gt;&#xA;&lt;li&gt;Amber&lt;/li&gt;&#xA;&lt;li&gt;CHARMM&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Which one above is the most appropriate for protein simulation?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-10-05T02:33:41.750" LastActivityDate="2023-12-18T20:47:34.020" Title="Which MD software is preferable for protein simulation?" Tags="|molecular-dynamics|software|software-recommendations|one-topic-per-answer|proteins|" AnswerCount="3" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11702" PostTypeId="1" CreationDate="2023-10-05T02:07:40.213" Score="-4" ViewCount="100" Body="&lt;p&gt;I see that some &amp;quot;names&amp;quot; are available online in relation to MD simulation.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;VMD&lt;/li&gt;&#xA;&lt;li&gt;NAMD&lt;/li&gt;&#xA;&lt;li&gt;LAMMPS&lt;/li&gt;&#xA;&lt;li&gt;OpenMM&lt;/li&gt;&#xA;&lt;li&gt;GROMACS&lt;/li&gt;&#xA;&lt;li&gt;Amber&lt;/li&gt;&#xA;&lt;li&gt;CHARMM&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Are these &amp;quot;names&amp;quot; simulators, visualizers, force fields, or all three?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2023-10-06T08:59:22.903" LastActivityDate="2023-10-06T08:59:22.903" Title="Are these simulator, visualizer, or force field?" Tags="|molecular-dynamics|software|" AnswerCount="1" CommentCount="8" ClosedDate="2023-10-12T21:26:34.967" ContentLicense="CC BY-SA 4.0" />
  <row Id="11703" PostTypeId="2" ParentId="11701" CreationDate="2023-10-05T03:58:32.680" Score="8" Body="&lt;p&gt;There is no one size fits all answer here. The best answer depends on exactly what kind of protein simulation you'd like to perform. In particular, a few points to consider:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;What force field you want to use. Some force fields are only available to use in specific programs (e.g. ML force fields are not compatible with GROMACS), although the most common ones (CHARMM, AMBER, OPLS) are generally portable between popular MD engines.&lt;/li&gt;&#xA;&lt;li&gt;What plugins and special methods would you like to use? Do you have a particular integrator/thermostat/barostat in mind? Typically, protein simulations greatly benefit from enhanced sampling methods as this allows you to gather statistics on rare events (protein folding, protein-ligand binding, etc). This one is really a big determinant, as many enhanced sampling methods are specific to particular MD engines, so figure this out before you commit to learning a code.&lt;/li&gt;&#xA;&lt;li&gt;Will you benefit from GPU acceleration? If you have access to GPUs, consider using a GPU accelerated code.&lt;/li&gt;&#xA;&lt;li&gt;How fast is the code? Make sure you're happy with the speed of whatever code you choose.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My personal recommendation is GROMACS because that's the code I use and I know it's fast, open source, highly parallelized, GPU accelerated, has good tutorials, and is very reliable. It's a total workhorse. However, GROMACS cannot run with all kinds of enhanced sampling methods or force fields.&lt;/p&gt;&#xA;&lt;p&gt;I don't have particular experience with other codes, but I believe that openMM is good for experimentation and prototyping because it is made from python modules that you can easily access and modify on-the-fly. However, openMM is not known for speed or scalability.&lt;/p&gt;&#xA;&lt;p&gt;I believe NAMD is quite a fast and highly parallelized code that is also GPU accelerated, and I've seen some impressive simulation sizes reported using it. It really shines for super large systems (&amp;gt;2 M atoms). I believe it also has a lot of flexibility in methods available to it, including ML force fields, and interfaces with VMD really nicely (it's made by the same group). However, it's not quite as fast as GROMACS as far as I know.&lt;/p&gt;&#xA;&lt;p&gt;LAMMPS is also quite fast and modular. As a result, it has access to a lot of force fields and advanced methods.&lt;/p&gt;&#xA;" OwnerUserId="1443" LastEditorUserId="1443" LastEditDate="2023-10-05T04:33:14.663" LastActivityDate="2023-10-05T04:33:14.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11704" PostTypeId="2" ParentId="11702" CreationDate="2023-10-05T09:37:43.787" Score="2" Body="&lt;p&gt;&lt;strong&gt;VMD&lt;/strong&gt; stands for &lt;strong&gt;V&lt;/strong&gt;isual &lt;strong&gt;M&lt;/strong&gt;olecular &lt;strong&gt;D&lt;/strong&gt;ynamics, and is a tool to visualize the trajectory from an MD simulation. It also allows you to perform a wide variety of analysis out of the box, and you can also write your own analysis scripts if you Tcl languange.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;NAMD&lt;/strong&gt; stands for &lt;strong&gt;NA&lt;/strong&gt;noscale &lt;strong&gt;M&lt;/strong&gt;olecular &lt;strong&gt;D&lt;/strong&gt;ynamics and is a package to perform MD simulations on your system of choice. It supports CHARMM and AMBER FF (as far as I know) and you can then use VMD to visualize and analyze the trajectory file.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;LAMMPS&lt;/strong&gt; stands for &lt;strong&gt;L&lt;/strong&gt;arge-scale &lt;strong&gt;A&lt;/strong&gt;tomic/&lt;strong&gt;M&lt;/strong&gt;olecular &lt;strong&gt;M&lt;/strong&gt;assively &lt;strong&gt;P&lt;/strong&gt;arallel &lt;strong&gt;S&lt;/strong&gt;imulator and is another popular MD code for performing simulations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;CHARMM&lt;/strong&gt; stands for &lt;strong&gt;C&lt;/strong&gt;hemistry at &lt;strong&gt;HAR&lt;/strong&gt;vard &lt;strong&gt;M&lt;/strong&gt;acromolecular &lt;strong&gt;M&lt;/strong&gt;echanics is both an MD simulation code and an FF. It is mostly used to model biological systems like DNA(RNA) and proteins.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2023-10-05T09:47:00.363" LastActivityDate="2023-10-05T09:47:00.363" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11705" PostTypeId="1" AcceptedAnswerId="11718" CreationDate="2023-10-05T09:50:20.117" Score="5" ViewCount="153" Body="&lt;p&gt;&lt;a href=&quot;https://math.stackexchange.com/questions/4780773/how-is-the-equation-for-this-virtual-site-derived&quot;&gt;Cross posted on Math SE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am trying to understand virtual sites in MD simulations, and I came across this configuration:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Nvo2b.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Nvo2b.png&quot; alt=&quot;Virtual sites diagram&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, coordinate &lt;span class=&quot;math-container&quot;&gt;$\mathbf{s}$&lt;/span&gt; represents the virtual site, which is formed by three other atoms &lt;span class=&quot;math-container&quot;&gt;$\mathbf{i}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{j}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;. The distance between atom &lt;span class=&quot;math-container&quot;&gt;$\mathbf{i}$&lt;/span&gt; and the virtual site &lt;span class=&quot;math-container&quot;&gt;$\mathbf{s}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{d}|$&lt;/span&gt;. The position of atoms &lt;span class=&quot;math-container&quot;&gt;$\mathbf{i}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{j}$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; are &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_j$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_k$&lt;/span&gt;, respectively.&lt;/p&gt;&#xA;&lt;p&gt;In this case, the virtual site (&lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_s$&lt;/span&gt;) is in the plane of the other three particles at a distance of &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{d}|$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$\mathbf{i}$&lt;/span&gt; at an angle of &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; from &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}$&lt;/span&gt;. Atom &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; defines the plane and direction of the angle.&lt;/p&gt;&#xA;&lt;p&gt;How should I get the position of &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_s$&lt;/span&gt; using the other three atom positions and an angle?&lt;/p&gt;&#xA;&lt;p&gt;I know the equation for &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_s$&lt;/span&gt;, but I couldn't understand how it is derived. Any help is appreciated.&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r}_s = \mathbf{r}_i &#xA;+ d \cos\theta\, \frac{\mathbf{r}_{ij}}{|\mathbf{r}_{ij}|}&#xA;+ d \sin\theta\, \frac{\mathbf{r}_{\perp}}{|\mathbf{r}_{\perp}|}\tag{1}, &#xA;$$&lt;/span&gt;&#xA;in which&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r}_{\perp} = \mathbf{r}_{jk} &#xA;- \frac{\mathbf{r}_{ij} \cdot \mathbf{r}_{jk}}{\mathbf{r}_{ij} \cdot \mathbf{r}_{ij}}\, \mathbf{r}_{ij}. \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="7" LastEditDate="2023-11-02T14:07:57.680" LastActivityDate="2023-11-02T14:07:57.680" Title="How is the equation for the position of a virtual site derived?" Tags="|molecular-dynamics|mathematical-modeling|gromacs|derivations|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11706" PostTypeId="1" CreationDate="2023-10-05T10:26:16.187" Score="4" ViewCount="72" Body="&lt;p&gt;I've just installed Quantum Espresso on Ubuntu using the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sudo apt install quantum-espresso&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;everything went well and I can run calculations on QE normally. But I want to install GIPAW, the commando to run gipaw.x is not found and I dont know where is the directory of installation to compile gipaw with the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;make gipaw&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could someone help me?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&#xA;Levy&lt;/p&gt;&#xA;" OwnerUserId="6578" LastActivityDate="2023-10-05T10:26:16.187" Title="How to Install GIPAW on Ubuntu with QE installation from Ubuntu Repositories" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11707" PostTypeId="1" AcceptedAnswerId="11709" CreationDate="2023-10-05T12:22:17.790" Score="3" ViewCount="156" Body="&lt;p&gt;I am trying to run some geometry optimizations in ORCA 5.0.4 and I am using the &lt;code&gt;UseSym&lt;/code&gt; keyword to ensure that my molecules retain C&lt;sub&gt;s&lt;/sub&gt; Symmetry during optimization. The molecule that returns the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;         *************************************************************&#xA;         *                GEOMETRY OPTIMIZATION CYCLE   6            *&#xA;         *************************************************************&#xA;[file orca_tools/Tool-Symmetry/symmain.cpp, line 1318]: Error (ORCA_SYM): TMoleculeSymmetry::ConstructSALCs failed to find appropriate number of SALCs!&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;is 4-Fluoroimidazole. From what I understand (I am not good at C++), &lt;code&gt;UseSym&lt;/code&gt; runs the script &lt;code&gt;symmain.cpp&lt;/code&gt; and provides the initial xyz coordinates of my input file to the &lt;code&gt;ConstructSALCs&lt;/code&gt; class of the &lt;code&gt;TMoleculeSymmetry&lt;/code&gt; module.&lt;/p&gt;&#xA;&lt;p&gt;If the provided, initial coordinates are not symmetrical (or well aligned) enough within a certain margin of error, then ORCA cannot find a small enough number of &amp;quot;Symmetry Adapted Linear Combinations&amp;quot; for the molecule and the following determination of the point group fails.&lt;/p&gt;&#xA;&lt;p&gt;This would mean that my initial coordinates are poorly pre-optimized and need to be made more symmetrical in line with the C&lt;sub&gt;s&lt;/sub&gt; point group. But the analogous molecules of 4-Chloro-, 4-Bromo- and 4-Iodoimidazole work just fine. Could it be that because Fluorine is the smallest, that this somehow affects the margin of error of the SALC determination?&lt;/p&gt;&#xA;&lt;p&gt;I have checked the initial coordinates of Fluorimidazole and it looks pretty planar to me  :&#xA;&lt;a href=&quot;https://i.stack.imgur.com/1l4G8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1l4G8.png&quot; alt=&quot;4-Fluoroimidazole, orthographic projection&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KqNao.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KqNao.png&quot; alt=&quot;4-Fluoroimidazole, orthographic projection&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Both of these are in orthographic projection.&lt;/p&gt;&#xA;&lt;p&gt;Here's the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# 4-Fluoroimidazol-1-ide&#xA;# FC1=C[N-]C=N1&#xA;&#xA;# Use B3LYP&#xA;# Use Becke-Johnson Dampening&#xA;# Use 4 CPU cores&#xA;# Run an iterative geometry optimization job&#xA;# Make detailled output file&#xA;# Let ORCA choose auxilliary basis sets&#xA;! B3LYP D3 PAL4 Opt LARGEPRINT autoaux UseSym&#xA;%maxcore 1500 # Maximum memory in MB per core&#xA;&#xA;%method &#xA;    RI on # use the RI approximation&#xA;end&#xA;&#xA;# Basis set specifications&#xA;%basis basis &amp;quot;aug-cc-pVDZ&amp;quot; # General spec: aug-cc-pVDZ &#xA;    newGTO Zn &amp;quot;aug-cc-pVDZ-PP&amp;quot; end # except for Zn-atoms: aug-cc-pVDZ-PP&#xA;    newECP Zn &amp;quot;SDD&amp;quot; end # use Stuttgart-Dresden ECPs for Zinc&#xA;    newGTO Br &amp;quot;aug-cc-pVDZ-PP&amp;quot; end # except for Br: aug-cc-pVDZ-PP&#xA;    newECP Br &amp;quot;SDD&amp;quot; end # use Stuttgart-Dresden ECPs for Br&#xA;    newGTO I &amp;quot;aug-cc-pVDZ-PP&amp;quot; end # except for I: aug-cc-pVDZ-PP&#xA;    newECP I &amp;quot;SDD&amp;quot; end # use Stuttgart-Dresden ECPs for I&#xA;end&#xA;&#xA;# Insert xyz coords&#xA;*xyz -1 1&#xA;F     -1.920669   -1.239155    0.561931&#xA;C     -0.775487   -0.574040    0.365338&#xA;C     -0.664744    0.708473   -0.109333&#xA;N      0.652798    1.017049   -0.164707&#xA;C      1.317493   -0.077197    0.274888&#xA;N      0.453454   -1.062887    0.604201&#xA;H     -1.457650    1.379842   -0.396591&#xA;H      2.394805   -0.152085    0.352006&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What parameter can I toggle in ORCA to make the SALC determination less sensitive to distorted geometries? Is it another reason entirely?&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I forgot to be more explicit: The optimization ran fine for 5 cycles. It crashes on cycle number 6. Did it just randomly reach a geometry from which the SALCs algorithm fails and crashes the calculation? Do just need more RAM?&lt;/p&gt;&#xA;" OwnerUserId="7501" LastEditorUserId="7501" LastEditDate="2023-10-05T12:44:26.573" LastActivityDate="2023-10-11T08:08:36.917" Title="UseSym Keyword in ORCA fails to find appropriate number of SALCs" Tags="|geometry-optimization|symmetry|orca|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11708" PostTypeId="2" ParentId="11699" CreationDate="2023-10-06T01:19:29.670" Score="6" Body="&lt;p&gt;If my memory serves correctly (this &lt;a href=&quot;http://ccl.net/chemistry/resources/messages/2013/09/02.003-dir/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;CCL post&lt;/a&gt; agrees), the origin used for computing the dipole is the center of nuclear charge:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$R=\frac{\sum_i Z_ir_i}{\sum_i Z_i}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you noted, the origin doesn't matter if the molecule is neutral and more generally the lowest order non-vanishing multipole will be independent of the origin while any higher order multipole will have some origin dependent terms, see this &lt;a href=&quot;https://physics.stackexchange.com/q/403652/155261&quot;&gt;Physics SE post&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2023-10-06T13:28:35.990" LastActivityDate="2023-10-06T13:28:35.990" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11709" PostTypeId="2" ParentId="11707" CreationDate="2023-10-06T07:03:12.017" Score="2" Body="&lt;p&gt;As you said, your initial geometry may be on the verge of satisfying and not satisfying the Cs symmetry under ORCA's default threshold. Also note that although the molecule should eventually reach planarity, the change of planarity is not necessarily monotonic. A geometry optimizer may well temporarily deteriorate the planarity of your molecule, before finally restoring it (though good geometry optimizers should not deteriorate the planarity by too much during the optimization if the converged geometry is indeed planar). Furthermore, the circumstances where UseSym fails may be essentially random, such that though it fails for your fluorine case, it does not necessarily imply anything special about fluorine, and may just be a coincidence. Think of the geometry optimizer as a fly in the room; it tries to find the food in the room (the converged structure), but before that it may accidentally exit through the window (program abort). Whether it finds the window before it finds the food is essentially random.&lt;/p&gt;&#xA;&lt;p&gt;To solve the problem, there are two approaches that can be combined. Firstly, note that even the symmetry program fails for one geometry during the optimization, you will probably be able to continue the calculation successfully by running a new geometry optimization calculation from that geometry. This is because the program will try to deduce the point group again, and that point group will be suitable for the molecule at least at the first geometry optimization step. In your system, this means that if you re-run your calculation from your last structure, the point group will probably be identified as C1, and you will end up with a C1 structure. If you want a rigorously symmetrized Cs structure, just run a third optimization job on the final structure: now the point group will be re-identified as Cs, and since the structure has already converged, it should be extremely easy (within 2~3 steps, for example) to re-converge the structure under the Cs symmetry, giving a rigorously planar and fully converged geometry.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, the threshold for detecting the point group can be loosened, by adding something similar to this to the input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%sym symthresh 0.01 end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The default threshold is 0.0001. The larger the threshold is, the more likely it is for the program to identify approximately symmetric molecules as symmetric.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2023-10-11T08:08:36.917" LastActivityDate="2023-10-11T08:08:36.917" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11710" PostTypeId="1" CreationDate="2023-10-06T19:31:48.893" Score="2" ViewCount="59" Body="&lt;p&gt;So far i have found only one paper that describes how we can compute protein energy while doing MD simulation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/76901/1/chd058_3_308.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nishikawa, Ken, Motohisa Oobatake, and Tatsuo Ooi. &amp;quot;&lt;em&gt;&lt;strong&gt;Method for Energy Computation of Protein Structures: A Set of Amino Acid Geometries and Energy Parameters&lt;/strong&gt;&lt;/em&gt; (Commemoration Issue Dedicated to Professor Tatsuo Yamamoto on the Occasion of his Retirement).&amp;quot; Bulletin of the Institute for Chemical Research, Kyoto University 58.3 (1980): 308-322.&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Can you propose more papers for protein energy computation?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-10-06T23:00:09.597" LastActivityDate="2023-10-06T23:00:09.597" Title="Method for Energy Computation of Protein Structures" Tags="|molecular-dynamics|reference-request|proteins|energy|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11711" PostTypeId="1" CreationDate="2023-10-07T06:25:15.427" Score="3" ViewCount="36" Body="&lt;p&gt;I try to find the elastic constants of LiTaO3 from online databases. I did find a page that lists them &lt;a href=&quot;https://www.roditi.com/SingleCrystal/Lithium-Tantalate/LiTaO3-Properties.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.roditi.com/SingleCrystal/Lithium-Tantalate/LiTaO3-Properties.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;As I know, the elastic constants are defined with respect to a predefined coordination system. However, the page gives nothing about the coordination system. So is there a convention of the predefined coordination system for defining the elastic constants or how should I know the coordination system corresponding to the experimental elastic constants ?&lt;/p&gt;&#xA;" OwnerUserId="3456" LastEditorUserId="5" LastEditDate="2023-10-07T12:26:06.197" LastActivityDate="2023-10-07T12:26:06.197" Title="What is convention of predefined coordination system for defining elastic constant of a specific material" Tags="|crystallography|elasticity|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11712" PostTypeId="1" AcceptedAnswerId="11713" CreationDate="2023-10-07T06:32:21.230" Score="5" ViewCount="150" Body="&lt;p&gt;I am trying to read Atoms objects from the file &amp;quot;data.txt&amp;quot;, which contains multiple configurations. Each configuration has a different cell.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;a = ase.io.read('data.txt', format = 'vasp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But my code only reads the first configuration in the file.&lt;/p&gt;&#xA;&lt;p&gt;What do I do?&lt;/p&gt;&#xA;" OwnerUserId="8099" LastActivityDate="2023-10-07T15:14:57.983" Title="How to read multiple Atoms objects from a single file using ASE" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11713" PostTypeId="2" ParentId="11712" CreationDate="2023-10-07T15:14:57.983" Score="4" Body="&lt;p&gt;Simply add &lt;code&gt;index=':'&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;images = ase.io.read('data.txt', format = 'vasp', index=':')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-10-07T15:14:57.983" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11714" PostTypeId="1" CreationDate="2023-10-08T04:48:42.303" Score="6" ViewCount="191" Body="&lt;p&gt;I want to figure out the high-symmetry points in the first Brillouin zone of space group R-3m (166). For example, there are points K and M just like the bandstructure in &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2516-1075/acd28d&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;.&#xA;But I can't figure out each component of kx, ky, kz from &lt;a href=&quot;https://www.cryst.ehu.es/cgi-bin/cryst/programs/nph-kv-list&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bilbao Crystallographic Serve&lt;/a&gt;.&#xA;Can anyone help me? I am not fimiliar about space groups. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="5635" LastEditorUserId="5" LastEditDate="2023-10-08T10:48:31.823" LastActivityDate="2023-10-09T17:44:28.720" Title="About high-symmetry points in the first Brillouin zone of space group R-3m" Tags="|band-structure|symmetry|k-points|space-groups|brillouin-zone|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11715" PostTypeId="1" CreationDate="2023-10-09T01:12:48.590" Score="4" ViewCount="41" Body="&lt;p&gt;&lt;a href=&quot;https://physics.stackexchange.com/q/783546/134583&quot;&gt;Cross-posted at Physics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In Fu and Kane's &lt;a href=&quot;https://arxiv.org/abs/cond-mat/0606336&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt; from 2006, the authors define the &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; invariant for time-reversal invariant topological insulators as an obstruction to Stoke's theorem,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\begin{equation}&#xA;\nu=\frac{1}{2\pi}\left[\oint_{\partial\text{HBZ}}\mathrm{d}\mathbf{k}\cdot\mathbf{A}(\mathbf{k})-\int_{\text{HBZ}}\mathrm{d}^2\mathbf{k}F(\mathbf{k})\right]\text{(mod 2)},&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\mathbf{A}(\mathbf{k})=\sum_{n,\sigma}\langle u_{n,\sigma}(\mathbf{k})|\mathrm{i}\nabla|u_{n,\sigma}(\mathbf{k})\rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$F=\nabla\times\mathbf{A}(\mathbf{k})$&lt;/span&gt; (where &lt;span class=&quot;math-container&quot;&gt;$|u_{n,\sigma}(\mathbf{k})\rangle$&lt;/span&gt;s are the periodic Bloch functions). The integrals are evaluated over half of the Brillouin zone. This formula is not gauge invariant and the authors impose a time reversal constraint on the periodic Bloch functions,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\begin{equation}&#xA;|u_{n,\uparrow}(-\mathbf{k})\rangle=\Theta|u_{n,\downarrow}(\mathbf{k})\rangle&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{3}&#xA;\begin{equation}&#xA;|u_{n,\downarrow}(-\mathbf{k})\rangle=-\Theta|u_{n,\uparrow}(\mathbf{k})\rangle&#xA;\end{equation}.&#xA;$$&lt;/span&gt;&#xA;However, I do not understand how this fixes the gauge. I can always define the new Bloch states,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;\begin{equation}&#xA;|u_{n,\uparrow}(\mathbf{k})\rangle'=\mathrm{e}^{\mathrm{i}\theta_{\mathbf{k}}}|u_{n,\uparrow}(\mathbf{k})\rangle&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{5}&#xA;\begin{equation}&#xA;|u_{n,\downarrow}(\mathbf{k})\rangle'=\mathrm{e}^{-\mathrm{i}\theta_{-\mathbf{k}}}|u_{n,\downarrow}(\mathbf{k})\rangle&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;which satisfies the gauge constraint for any arbitrary choice of &lt;span class=&quot;math-container&quot;&gt;$\theta_{\mathbf{k}}$&lt;/span&gt;. The Berry connection gets modified to,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{6}&#xA;\begin{equation}&#xA;\mathbf{A}(\mathbf{k})\rightarrow\mathbf{A}(\mathbf{k})+\nabla(\theta_{\mathbf{k}}-\theta_{-\mathbf{k}}).&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;If I choose a &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; that has a singularity in only one-half of the Brillouin zone, it can change the value of &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; by 1.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, do we need any additional constraints on the Bloch functions to define &lt;span class=&quot;math-container&quot;&gt;$\nu$&lt;/span&gt; unambiguously modulo 2? Thank you!&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8102" LastEditorUserId="5" LastEditDate="2023-10-09T01:26:05.400" LastActivityDate="2023-10-09T01:26:05.400" Title="Gauge constraint in the definition of the Z2 invariant" Tags="|condensed-matter|mathematical-modeling|berry-phase|topological-insulators|topological-matter|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11716" PostTypeId="1" CreationDate="2023-10-09T05:07:37.897" Score="5" ViewCount="89" Body="&lt;p&gt;Recently I am trying to calculate the binding energy between CO2/ C2H2 and MOF (containing Ni, C, H, O, N).&#xA;I want to know that do I have to use DFT+U for Ni element in this binding energy calculation? Since I read some articles that they only use DFT+U in electronic structure research.&lt;br /&gt;&#xA;Here is my MOF POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C1.625 H0.875 N0.25 Ni0.125 O0.75&#xA;1.0&#xA;       16.6688003540         0.0000000000         0.0000000000&#xA;       -8.3344001770        14.4356045572         0.0000000000&#xA;        0.0000000000         0.0000000000         7.0012998581&#xA;   Ni    O    N    C    H&#xA;    3   18    6   39   21&#xA;Direct&#xA;     0.000000000         0.320639998         0.500000000&#xA;     0.679360032         0.679360032         0.500000000&#xA;     0.320639998         0.000000000         0.500000000&#xA;     0.116499998         0.447899997         0.500000000&#xA;     0.552100003         0.668600023         0.500000000&#xA;     0.331400007         0.883499980         0.500000000&#xA;     0.447899997         0.116499998         0.500000000&#xA;     0.668600023         0.552100003         0.500000000&#xA;     0.883499980         0.331400007         0.500000000&#xA;     0.924300015         0.174300000         0.500000000&#xA;     0.825699985         0.750000000         0.500000000&#xA;     0.250000000         0.075700000         0.500000000&#xA;     0.174300000         0.924300015         0.500000000&#xA;     0.750000000         0.825699985         0.500000000&#xA;     0.075700000         0.250000000         0.500000000&#xA;     0.083800003         0.560100019         0.500000000&#xA;     0.439899981         0.523699999         0.500000000&#xA;     0.476300001         0.916199982         0.500000000&#xA;     0.560100019         0.083800003         0.500000000&#xA;     0.523699999         0.439899981         0.500000000&#xA;     0.916199982         0.476300001         0.500000000&#xA;     0.000000000         0.320499986         0.801199973&#xA;     0.679499984         0.679499984         0.801199973&#xA;     0.320499986         0.000000000         0.801199973&#xA;     0.000000000         0.320499986         0.198800027&#xA;     0.679499984         0.679499984         0.198800027&#xA;     0.320499986         0.000000000         0.198800027&#xA;     0.000000000         0.084299996         0.500000000&#xA;     0.915700018         0.915700018         0.500000000&#xA;     0.084299996         0.000000000         0.500000000&#xA;     0.917299986         0.000000000         0.500000000&#xA;     0.000000000         0.917299986         0.500000000&#xA;     0.082699999         0.082699999         0.500000000&#xA;     0.000000000         0.173600003         0.500000000&#xA;     0.826399982         0.826399982         0.500000000&#xA;     0.173600003         0.000000000         0.500000000&#xA;     0.306499988         0.572799981         0.500000000&#xA;     0.427200019         0.733700037         0.500000000&#xA;     0.266299993         0.693500042         0.500000000&#xA;     0.572799981         0.306499988         0.500000000&#xA;     0.733700037         0.427200019         0.500000000&#xA;     0.693500042         0.266299993         0.500000000&#xA;     0.239700004         0.601499975         0.500000000&#xA;     0.398500025         0.638200045         0.500000000&#xA;     0.361799955         0.760299981         0.500000000&#xA;     0.601499975         0.239700004         0.500000000&#xA;     0.638200045         0.398500025         0.500000000&#xA;     0.760299981         0.361799955         0.500000000&#xA;     0.078699999         0.358399987         0.901499987&#xA;     0.641600013         0.720300019         0.901499987&#xA;     0.279699981         0.921299994         0.901499987&#xA;     0.078699999         0.358399987         0.098500013&#xA;     0.641600013         0.720300019         0.098500013&#xA;     0.279699981         0.921299994         0.098500013&#xA;     0.358399987         0.078699999         0.098500013&#xA;     0.720300019         0.641600013         0.098500013&#xA;     0.921299994         0.279699981         0.098500013&#xA;     0.358399987         0.078699999         0.901499987&#xA;     0.720300019         0.641600013         0.901499987&#xA;     0.921299994         0.279699981         0.901499987&#xA;     0.140300006         0.529699981         0.500000000&#xA;     0.470300019         0.610599995         0.500000000&#xA;     0.389399976         0.859699965         0.500000000&#xA;     0.529699981         0.140300006         0.500000000&#xA;     0.610599995         0.470300019         0.500000000&#xA;     0.859699965         0.389399976         0.500000000&#xA;     0.861523032         0.999998987         0.500000000&#xA;     0.000001000         0.861523986         0.500000000&#xA;     0.138475999         0.138476998         0.500000000&#xA;     0.287968993         0.510095000         0.500000000&#xA;     0.489905000         0.777873993         0.500000000&#xA;     0.222126007         0.712031007         0.500000000&#xA;     0.510095000         0.287968993         0.500000000&#xA;     0.777873993         0.489905000         0.500000000&#xA;     0.712031007         0.222126007         0.500000000&#xA;     0.134962007         0.385520995         0.836829007&#xA;     0.614479005         0.749441028         0.836829007&#xA;     0.250558972         0.865037978         0.836829007&#xA;     0.134962007         0.385520995         0.163170993&#xA;     0.614479005         0.749441028         0.163170993&#xA;     0.250558972         0.865037978         0.163170993&#xA;     0.385520995         0.134962007         0.163170993&#xA;     0.749441028         0.614479005         0.163170993&#xA;     0.865037978         0.250558972         0.163170993&#xA;     0.385520995         0.134962007         0.836829007&#xA;     0.749441028         0.614479005         0.836829007&#xA;     0.865037978         0.250558972         0.836829007&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Hope someone could help me. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-10-15T06:06:01.123" Title="Is it necessary to use DFT+U when calculating binding energy?" Tags="|density-functional-theory|vasp|hubbard-model|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11717" PostTypeId="1" AcceptedAnswerId="11719" CreationDate="2023-10-09T11:33:45.327" Score="7" ViewCount="244" Body="&lt;p&gt;I have a self-inflicted problem with the input files that I am generating using &lt;code&gt;RDKit&lt;/code&gt; in order to automate my ORCA jobs. I like to keep track of data such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The name of a mol&lt;/li&gt;&#xA;&lt;li&gt;The SMILES of a mol&lt;/li&gt;&#xA;&lt;li&gt;The path of an .inp file&lt;/li&gt;&#xA;&lt;li&gt;The ID (&amp;quot;%.08d&amp;quot; format string number) of a mol&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and other stuff from the generated initial geometries, to the executed .inp files themselves. This helps me keep track of what comes from where and getting infos on the mols from the output files after the calculations are done using a python script.&lt;/p&gt;&#xA;&lt;p&gt;So what I essentially do is add a line like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# SMILES: [SMILES_STRING]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to my .inp files and so later on I can get all the info from the output file, since that will also show the .inp file at the top of the output file.&lt;/p&gt;&#xA;&lt;p&gt;The problem is: SMILES strings use the the hash/pound character &amp;quot;#&amp;quot; to denote triple bonds.&#xA;So if I have a mol that has, for example, a nitrile inside it, then I would have a comment like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# SMILES: N#CC1=CN=C[N-]1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What is necessarily going to happen, since &amp;quot;#&amp;quot; is the typical comment char, is that ORCA will interpret &amp;quot;SMILES: N&amp;quot; as a command, and only everything afterwards as a comment, which leads to the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[file orca_main/maininp1.cpp, line 17547]: ERROR: expect a '$', '!', '%', '*' or '[' in the input&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So it tries to find a command, but obviously there will not be anything intelligible for ORCA in that line. And so it crashes.&lt;/p&gt;&#xA;&lt;p&gt;My question is: Is there a way around that? I could just rewrite my scripts in such a way that a SMILES will be added to the file as: C[HASH]N... and then just later re-substitute [HASH] for #, but I wanted to know if there may be a creative way around that.&lt;/p&gt;&#xA;&lt;p&gt;Does ORCA have more options for comments that allow me to circumvent this issue? I didn't find anything useful in the manual unfortunately.&lt;/p&gt;&#xA;" OwnerUserId="7501" LastActivityDate="2023-10-09T14:24:30.340" Title="Do ORCA input files allow for multi-line comments or different comment syntaxes?" Tags="|orca|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11718" PostTypeId="2" ParentId="11705" CreationDate="2023-10-09T11:45:10.120" Score="5" Body="&lt;p&gt;The formula (1) in the question:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathbf{r}_s = \underset{\text{term A}}{\mathbf{r}_i}&#xA;+ \underset{\text{term B}}{d \cos\theta\, \frac{\mathbf{r}_{ij}}{|\mathbf{r}_{ij}|}}&#xA;+ \underset{\text{term C}}{d \sin\theta\, \frac{\mathbf{r}_{\perp}}{|\mathbf{r}_{\perp}|}}\tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;can be understood as going to the position of &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt; by starting at the position of &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; (term A) and adding the two legs (terms B and C) of the right-angled triangle with &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{is}$&lt;/span&gt; as its hypotenuse (equivalently, stating &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{is}$&lt;/span&gt; in the orthonormal basis vectors of terms B and C).&lt;/p&gt;&#xA;&lt;p&gt;Term B is the unit vector &lt;span class=&quot;math-container&quot;&gt;$\hat{\mathbf{r}}_{ij}$&lt;/span&gt;, and term C is the unit vector coplanar and perpendicular to &lt;span class=&quot;math-container&quot;&gt;$\hat{\mathbf{r}}_{ij}$&lt;/span&gt;. The (not yet unit) vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_\perp$&lt;/span&gt; in term C is constructed to lie in the desired plane but be perpendicular to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}$&lt;/span&gt; by subtracting from &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{jk}$&lt;/span&gt; its projection into &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}$&lt;/span&gt; (a &lt;a href=&quot;https://en.m.wikipedia.org/wiki/Gram%E2%80%93Schmidt_process&quot; rel=&quot;noreferrer&quot;&gt;Gram-Schmidt orthogonalization&lt;/a&gt;). This is the formula (2) in the question.&lt;/p&gt;&#xA;&lt;p&gt;The below diagram may help visually:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/m4Q9B.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/m4Q9B.png&quot; alt=&quot;Geometry of atoms k, j, i, and virtual site s, showing the vector is as the sum of basis vectors parallel and perpendicular to in.&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-10-09T11:45:10.120" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11719" PostTypeId="2" ParentId="11717" CreationDate="2023-10-09T14:24:30.340" Score="4" Body="&lt;p&gt;From the ORCA documentation (ORCA 5.0.4), using double '#' in ORCA input files closes the comment. I am quoting from the ORCA manual.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Comments can also be closed by a second “#”, as in the example below where TolE and TolMaxP are two variables that can be user-specified:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;TolE=1e-5; #Energy conv.# TolMaxP=1e-6; #Density conv.#&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In my opinion, you have to substitute the character '#' which denotes the triple bond.&lt;/p&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2023-10-09T14:24:30.340" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11720" PostTypeId="2" ParentId="11714" CreationDate="2023-10-09T17:44:28.720" Score="5" Body="&lt;p&gt;As described on the &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2516-1075/acd28d/pdf&quot; rel=&quot;noreferrer&quot;&gt;paper&lt;/a&gt;, the system presents a hexagonal unit cell. From the paper recommended by @MathJacky (if you don't have access to the published paper, there is an &lt;a href=&quot;https://arxiv.org/pdf/1004.2974.pdf&quot; rel=&quot;noreferrer&quot;&gt;arXiv version&lt;/a&gt;), we have that the Brillouin zone lattice is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kpavU.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kpavU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And the high symmetry points &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$M$&lt;/span&gt; can be calculated as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/5AlKl.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5AlKl.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;With that information, you can generate the path between continuous points.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-10-09T17:44:28.720" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11721" PostTypeId="2" ParentId="11634" CreationDate="2023-10-09T21:09:21.983" Score="5" Body="&lt;p&gt;The &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html&quot; rel=&quot;noreferrer&quot;&gt;documentation for &lt;code&gt;pw.x&lt;/code&gt;&lt;/a&gt;, version 7.2, lists several different ways to compute van der Waals corrections:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Grimme's semiempirical DFT-D2 and DFT-D3;&lt;/li&gt;&#xA;&lt;li&gt;Tkatchenko–Scheffler &lt;em&gt;ab initio&lt;/em&gt; vdW;&lt;/li&gt;&#xA;&lt;li&gt;many-body dispersion (MBD); and&lt;/li&gt;&#xA;&lt;li&gt;the exchange-hole dipole-moment model (XDM).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Each of these will compute the forces differently, but the references in the documentation will detail each one.&lt;/p&gt;&#xA;&lt;p&gt;In addition, &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/Modules/funct.f90?ref_type=heads&quot; rel=&quot;noreferrer&quot;&gt;various nonlocal van der Waals functionals&lt;/a&gt; have been implemented, with names mostly of the form &lt;code&gt;vdw-DF*&lt;/code&gt; (this is in the file &lt;code&gt;Modules/funct.f90&lt;/code&gt;). Again, references to the papers are included in the comments of that file.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-10-09T21:09:21.983" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11723" PostTypeId="1" AcceptedAnswerId="11736" CreationDate="2023-10-10T14:32:54.080" Score="4" ViewCount="143" Body="&lt;p&gt;Is it possible to find the Fermi energy with highest occupied and lowest unoccupied level from a single nscf caculation using quantum espresso?&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2023-10-10T16:44:06.503" LastActivityDate="2023-10-13T07:41:20.563" Title="How to find the Fermi energy with highest occupied and lowest unoccupied level from a single nscf caculation using quantum espresso?" Tags="|density-functional-theory|quantum-espresso|fermi-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11724" PostTypeId="1" AcceptedAnswerId="11727" CreationDate="2023-10-10T17:22:49.703" Score="6" ViewCount="150" Body="&lt;p&gt;I want to compute 2-electron coulomb integrals. When the Primitive Gaussian is not centered at 0, my quadrature scheme fails unless I increase the number of quadrature points. I am currently using a quadrature scheme for the 4-indexed integral:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;one integral involving the Boys function (1 coordinate)&lt;/li&gt;&#xA;&lt;li&gt;three integrals over  &lt;span class=&quot;math-container&quot;&gt;$x_1 \in \mathbb{R}^3$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The integrals over the second coordinates &lt;span class=&quot;math-container&quot;&gt;$x_2$&lt;/span&gt; are evaluated exactly at quadrature points.&lt;/p&gt;&#xA;&lt;p&gt;Their respective numerical schemes are as follow:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Gauss Chebyshev of the second type for one coordinate&lt;/li&gt;&#xA;&lt;li&gt;a tensor product of Gauss Chebyshev quadrature points for a 3D integration&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My problem is that my integration over &lt;span class=&quot;math-container&quot;&gt;$\mathbb{R}^3$&lt;/span&gt; scales pretty badly as I increase the number of quadrature points. So maybe using another scheme would be better, like Lebedev? Or are there other methods to simplify the 2-electron integrals?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-10-11T06:16:26.303" LastActivityDate="2023-10-11T12:14:43.157" Title="How are 2-electron integrals usually computed?" Tags="|molecular-modeling|ab-initio-calculations|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11725" PostTypeId="1" CreationDate="2023-10-10T17:32:47.577" Score="5" ViewCount="122" Body="&lt;p&gt;Can anyone please show me how to make a  supercell with VESTA&#xA;using a single command line without opening a GUI.&lt;/p&gt;&#xA;" OwnerUserId="3450" LastActivityDate="2023-12-17T00:29:07.413" Title="VESTA using command line" Tags="|density-functional-theory|crystallography|vesta|supercell|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11726" PostTypeId="1" AcceptedAnswerId="12392" CreationDate="2023-10-11T07:24:57.747" Score="5" ViewCount="57" Body="&lt;p&gt;I have a &lt;a href=&quot;https://discourse.abinit.org/t/kpt-boundaries-for-cubic-supercell/3422&quot; rel=&quot;nofollow noreferrer&quot;&gt;question&lt;/a&gt; on how to make a supercell in abinit.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to calculate the EBS of a cubic perovskite supercell (2x2x2 cubic STO). The geometry information can be found on the MP here. I need the supercell to simulate a doped system.&lt;/p&gt;&#xA;&lt;p&gt;I have followed the abinit documentation regarding the supercell of Hydrogen here and the unfolding of the Brillouin zone here, although I find it not complete.&lt;/p&gt;&#xA;&lt;p&gt;I start from the standard k-path for a cubic structure in the primitive cell.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;kptopt2        -5   &#xA;kptbounds2&#xA;            0.0   0.0   0.0  #  Gamma&#xA;            0.0   0.5   0.0  #  X&#xA;            0.5   0.5   0.0  #  M&#xA;            0.0   0.0   0.0  #  Gamma&#xA;            0.5   0.5   0.5  #  R&#xA;            0.0   0.5   0.0  #  X&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have tried several paths, such as the following, trying to include all the “half” points and making sure to substitute G-&amp;gt;X with -X/2-&amp;gt;G-&amp;gt;X/2 and I get a bunch of spikes.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;kptopt2    -9 &#xA;kptbounds2&#xA;           -0.25 -0.25  0.0  # -M/2&#xA;            0.0  -0.25  0.0  # -X/2&#xA;            0.0   0.0   0.0  #  Gamma&#xA;            0.0   0.25  0.0  #  X/2&#xA;            0.25  0.25  0.0  #  M/2&#xA;            0.0  -0.25  0.0  # -X/2&#xA;           -0.25 -0.25 -0.25 # -R/2&#xA;            0.0   0.0   0.0  #  Gamma&#xA;            0.25  0.25  0.25 #  R/2&#xA;            0.0   0.25  0.0  #  X/2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Could it be that this is still incomplete and I am missing points such as 0.25 0.5 0.0 and 0.5 0.25 0.0 for M and 0.5 0.25 0.25 for R (etc…?).&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Marco&lt;/p&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="5" LastEditDate="2023-10-11T10:56:34.430" LastActivityDate="2024-02-14T09:14:12.780" Title="Kpt boundaries for cubic supercell" Tags="|supercell|plane-waves|abinit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11727" PostTypeId="2" ParentId="11724" CreationDate="2023-10-11T12:14:43.157" Score="6" Body="&lt;p&gt;Integral calculation is discussed extensively in the book &lt;a href=&quot;https://doi.org/10.1002/9781119019572&quot; rel=&quot;noreferrer&quot;&gt;Molecular Electronic-Structure Theory by Helgaker, Jørgensen, and Olsen&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;2-electron integrals are usually computed analytically with the &lt;a href=&quot;https://doi.org/10.1016/0021-9991(78)90092-X&quot; rel=&quot;noreferrer&quot;&gt;McMurchie-Davidson&lt;/a&gt; or &lt;a href=&quot;https://doi.org/10.1063/1.450106&quot; rel=&quot;noreferrer&quot;&gt;Obara-Saika&lt;/a&gt; methods and further developments thereof, or with &lt;a href=&quot;https://doi.org/10.1063/1.432807&quot; rel=&quot;noreferrer&quot;&gt;Rys quadrature&lt;/a&gt; which solves for the exact quadrature nodes and weights. Later on, &lt;a href=&quot;https://doi.org/10.1080/00268976.2012.720725&quot; rel=&quot;noreferrer&quot;&gt;schemes based on approximate quadrature&lt;/a&gt; have also been suggested.&lt;/p&gt;&#xA;&lt;p&gt;You do not discuss what you are actually doing, but it seems you should first study the existing literature. I also point out that there exist efficient open source libraries for evaluating two-electron integrals, such as &lt;a href=&quot;https://github.com/evaleev/libint&quot; rel=&quot;noreferrer&quot;&gt;LIBINT by Ed Valeev and collaborators&lt;/a&gt;, and &lt;a href=&quot;https://github.com/sunqm/libcint/&quot; rel=&quot;noreferrer&quot;&gt;libcint by Qiming Sun&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-10-11T12:14:43.157" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11728" PostTypeId="5" CreationDate="2023-10-11T13:56:41.450" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-10-11T13:56:41.450" LastActivityDate="2023-10-11T13:56:41.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11729" PostTypeId="4" CreationDate="2023-10-11T13:56:41.450" Score="0" Body="An atomistic simulation is a computer simulation method for analyzing the physical movements of atoms and molecules.&#xD;&#xA;&#xD;&#xA;https://en.wikipedia.org/wiki/Molecular_dynamics&#xD;&#xA;" OwnerUserId="3623" LastEditorUserId="3623" LastEditDate="2023-10-13T04:37:08.327" LastActivityDate="2023-10-13T04:37:08.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11730" PostTypeId="2" ParentId="6151" CreationDate="2023-10-11T15:46:33.127" Score="5" Body="&lt;p&gt;Developing a potential requires three steps, and then iteration over these steps, as described:&lt;/p&gt;&#xA;&lt;h2&gt;(i) Training data&lt;/h2&gt;&#xA;&lt;p&gt;Density functional theory (DFT) training data, often in the form of MD NPT simulations, to generate energies, forces and stress tensors (EFS) for different atomic configurations. Procedural generation (I.e. using random numbers) is an alternative approach, as is coarse-graining the DFT parameters and recomputing uncorrelated snapshots with higher accuracy.&#xA;Other training data might include elastic constants and E-V curves at T = 0 K.&lt;/p&gt;&#xA;&lt;h2&gt;(ii) Optimization of potential&lt;/h2&gt;&#xA;&lt;p&gt;EFS of uncorrelated snapshots, as well as additional data such as elastic constants and E-V curves, can then be used to train an interatomic potential. Depending on the type of potential you will need to use different software. For EAM and RF-MEAM (not 2NN-MEAM) you can use MEAMfit, which fits to VASP, CASTEP and PWscf data to generate LAMMPS-usable potentials ( &lt;a href=&quot;https://gitlab.com/AndyDuff123/meamfit&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/AndyDuff123/meamfit&lt;/a&gt; ). MEAMfit uses BFGS for local minimization and multiple parameter starting points with a genetic algorithm to get closer to the global 'best' potential.&lt;/p&gt;&#xA;&lt;p&gt;Note that if multiple different types of data are being optimized (e.g. snapshots from NPT runs and calculations on elastically distorted supercells) then one will also have to consider the weight factor between these two types of data. Other considerations include tuning hyper-parameters such as the cutoff radius, which defines the maximum radius at which pair-wise interactions between atoms exist.&lt;/p&gt;&#xA;&lt;h2&gt;(iii) Validation runs using MD&lt;/h2&gt;&#xA;&lt;p&gt;Using the potential use, e.g. LAMMPS, to perform MD runs to: i) check stability of runs (I.e. no 'explosions' as atoms enter territory uncharted in the DFT-MD runs); ii) performance of potential in predicting the DFT EFS.&lt;/p&gt;&#xA;&lt;h2&gt;Iteration&lt;/h2&gt;&#xA;&lt;p&gt;Perhaps using active-learning (e.g. query by committee, QbC), analyze if there are atomic configurations from step iii) that need to be recomputed using DFT. If so, compute these (I.e. return to step 1), and include them in the training set for step 2. In this way steps 1-3 may need to be repeated multiple times.&lt;/p&gt;&#xA;&lt;h2&gt;Classical vs machine learning potentials&lt;/h2&gt;&#xA;&lt;p&gt;For classical potentials your variational freedom is more limited and you typically will not fit direct to the EFS but instead to particular material properties, or properties of the EFS. For machine-learning (ML) potentials the goal is usually to fit direct to the EFS. Active-learning is a key step in ML potential optimization, while for classical potential the iteration described above is often (but not always - see below) performed in a more manual way.&lt;/p&gt;&#xA;&lt;h2&gt;Methodologies for automating steps 1-3&lt;/h2&gt;&#xA;&lt;p&gt;The automated potential development (APD) workflow developed by myself ( &lt;a href=&quot;https://gitlab.com/AndyDuff123/automated-potential-development&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/AndyDuff123/automated-potential-development&lt;/a&gt; , &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465523002412&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/abs/pii/S0010465523002412&lt;/a&gt; ) automates the whole process, including QbC active-learning, and is designed as a black-box solution. However: i) it is only an alpha release so far (though is being actively developed) so there will be many refinements and bug fixes along the way; ii) works so far only for RF-MEAM.&lt;/p&gt;&#xA;&lt;p&gt;APD interfaces either with VASP or CASTEP, so you will need a license for one of these, and uses MEAMfit and LAMMPS for optimization and classical MD. It currently generates potentials for the following properties: phonon DOS, rdf, relaxed geometry, E-V curves, elastic constants (0 K) and thermal expansion.&lt;/p&gt;&#xA;" OwnerUserId="6324" LastEditorUserId="6324" LastEditDate="2023-10-13T08:14:40.453" LastActivityDate="2023-10-13T08:14:40.453" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11731" PostTypeId="1" AcceptedAnswerId="11732" CreationDate="2023-10-12T02:51:55.223" Score="6" ViewCount="188" Body="&lt;p&gt;I am trying to follow &lt;a href=&quot;https://www.flapw.de/MaX-6.0/future/MA1/&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; tutorial from the FLEUR DFT code's official website. The tutorial goes over calculating the ground state energies for the ferromagnetic and antiferromagnetic configurations of fcc Fe. I understand that one needs to have at least two atoms in a primitive cell to have an antiferromagnetic order (for example, for the case of bcc Fe, one converts one atom-bcc to two atom simple cubit lattice structure).&lt;/p&gt;&#xA;&lt;p&gt;However, here looks like they are converting a two-atom fcc unit cell into a tetragonal cell (Fleur manual says tp refers to simple-tetragonal). Unfortunately I'm not able to see how this can be accomplished. For convenience, I'm attaching the part of the code where they write this.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/AO8OV.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AO8OV.png&quot; alt=&quot;this image&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any help in understanding how this can be achieved would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="7988" LastActivityDate="2023-10-12T05:36:14.647" Title="Fcc lattice with two atom basis equivalent to tetragonal lattice?" Tags="|density-functional-theory|materials-design|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11732" PostTypeId="2" ParentId="11731" CreationDate="2023-10-12T05:36:14.647" Score="5" Body="&lt;p&gt;I found the answer for this (in the form of a picture, from some textbook or other) &lt;a href=&quot;https://www.chegg.com/homework-help/questions-and-answers/shown-two-fcc-unit-cells-face-atoms-missing-clarity--bold-lines-alternative-unit-cell-draw-q14480553&quot; rel=&quot;noreferrer&quot;&gt;on Chegg&lt;/a&gt;, of all places. Consider two conventional fcc unit cells (the actual cubes, not the Wigner–Seitz cells) side to side. One primitive cell for the two-cell system is tetragonal: it’s turned 45 degrees along the vertical axis and centered on the central atom, while keeping the same vertical height as either of the two original cells.&lt;/p&gt;&#xA;&lt;p&gt;Answer #11 to &lt;a href=&quot;http://fleur.xobor.de/t93f18450-Jij-calculation-error.html&quot; rel=&quot;noreferrer&quot;&gt;this FLEUR forum post&lt;/a&gt; clarifies the proper size:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I think if you want to have a 2-atom fcc unit cell, the shape would typically be a tetragonal unit cell ('tP').&#xA;The lattice parameter 'a' would be the distance between an atom at a corner and the nearest atom at a face center&#xA;in a conventional fcc unit cell. The lattice parameter 'c' would be the lattice constant of the fcc unit cell.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;In the example you provided, you’ll find the lovely relation &lt;span class=&quot;math-container&quot;&gt;$a = c /\sqrt{2}$&lt;/span&gt;, as predicted by the answerer above.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-10-12T05:36:14.647" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11733" PostTypeId="2" ParentId="11705" CreationDate="2023-10-12T08:53:16.347" Score="2" Body="&lt;p&gt;I have posted the &lt;a href=&quot;https://math.stackexchange.com/questions/4780773/how-is-the-equation-for-this-virtual-site-derived&quot;&gt;same question in Mathematics StackExchange&lt;/a&gt; and here is the reply.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Suppose that &lt;span class=&quot;math-container&quot;&gt;$d=|\mathbf{d}|$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}\ne \mathbf{0}$&lt;/span&gt;. Then in the plane of the other three particles with the coordinates origin at &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_i$&lt;/span&gt; and the basis of consisting of the unit vector &lt;span class=&quot;math-container&quot;&gt;$\frac{\mathbf{r}_{ij}}{|\mathbf{r}_{ij}|}$&lt;/span&gt; and some orthogonal to it unit vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r'}$&lt;/span&gt;, the virtual site has coordinates &lt;span class=&quot;math-container&quot;&gt;$(d\cos\theta,d\sin\theta)$&lt;/span&gt;. Thus&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{r}_s = \mathbf{r}_i&#xA;+ d \cos\theta\, \frac{\mathbf{r}_{ij}}{|\mathbf{r}_{ij}|}&#xA;+ d \sin\theta\, \mathbf{r'}.$$&lt;/span&gt;&#xA;The vector &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r'}$&lt;/span&gt; belongs to the plane spanned by &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{jk}$&lt;/span&gt;, so&#xA;&lt;span class=&quot;math-container&quot;&gt;$\mathbf{r'}=\lambda_i\mathbf{r}_{ij}+\lambda_k\mathbf{r}_{jk}$&lt;/span&gt; for some real &lt;span class=&quot;math-container&quot;&gt;$\lambda_i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\lambda_k$&lt;/span&gt;. Moreover,&#xA;&lt;span class=&quot;math-container&quot;&gt;$0=\mathbf{r'}\cdot \mathbf{r}_{ij}=\lambda_i\mathbf{r}_{ij}\cdot \mathbf{r}_{ij}+\lambda_k\mathbf{r}_{jk}\cdot \mathbf{r}_{ij}$&lt;/span&gt;.&#xA;So &lt;span class=&quot;math-container&quot;&gt;$\lambda_i=-\lambda_k\frac{\mathbf{r}_{jk}\cdot \mathbf{r}_{ij}}{\mathbf{r}_{ij}\cdot \mathbf{r}_{ij}}$&lt;/span&gt;.&#xA;Thus&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\mathbf{r'}=\lambda_k\left(-\frac{\mathbf{r}_{jk}\cdot \mathbf{r}_{ij}}{\mathbf{r}_{ij}\cdot \mathbf{r}_{ij}}\mathbf{r}_{ij}&#xA;+\mathbf{r}_{jk}\right)=-\lambda_k\mathbf{r}_{\perp}.$$&lt;/span&gt;&#xA;Since &lt;span class=&quot;math-container&quot;&gt;$|\mathbf{r'}|=1$&lt;/span&gt;, we have &lt;span class=&quot;math-container&quot;&gt;$|\lambda_k|=\frac{1}{|\mathbf{r}_{\perp}|}$&lt;/span&gt;. It remains to determine the sign of &lt;span class=&quot;math-container&quot;&gt;$\lambda_k$&lt;/span&gt;.&#xA;It corresponds to the direction of the angle &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; between &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{ij}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r}_{s}-\mathbf{r}_{i}$&lt;/span&gt;.&#xA;In particular, when &lt;span class=&quot;math-container&quot;&gt;$\theta=\frac{\pi}{2}$&lt;/span&gt;, we have &lt;span class=&quot;math-container&quot;&gt;$\mathbf{r'}=\mathbf{r}_s-\mathbf{r}_i$&lt;/span&gt;. But this direction is not very clear to me, maybe, because there is no coordinate system in the supplementary picture.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="3593" LastEditorUserId="7" LastEditDate="2023-11-02T14:07:33.127" LastActivityDate="2023-11-02T14:07:33.127" CommentCount="0" CommunityOwnedDate="2023-10-12T14:15:03.507" ContentLicense="CC BY-SA 4.0" />
  <row Id="11734" PostTypeId="2" ParentId="10677" CreationDate="2023-10-12T16:20:34.843" Score="3" Body="&lt;h1&gt;NOCI is not available in the main branch of PySCF&lt;/h1&gt;&#xA;&#xA;&lt;p&gt;That is why &lt;a href=&quot;https://github.com/pyscf/pyscf/issues/1697&quot; rel=&quot;nofollow noreferrer&quot;&gt;your question on the PySCF GitHub page&lt;/a&gt; which you asked on the same day as this question (next time please let us know if you are &amp;quot;cross-posting&amp;quot; a question!) was tagged by James Smith with the &amp;quot;feature-request&amp;quot; tag (it means that PySCF does &lt;em&gt;&lt;strong&gt;not&lt;/strong&gt;&lt;/em&gt; currently have NOCI as a feature).&lt;/p&gt;&#xA;&lt;p&gt;If you want to implement NOCI in PySCF by yourself, it will probably be a big task for you if you don't have experience with writing electronic structure software (this is the type of thing that forms a substantial part of masters theses or elite undergrad theses, so it's not something that is done overnight for someone asking a question like this).&lt;/p&gt;&#xA;&lt;p&gt;If you do want to implement it yourself, the answers on the GitHub page did give you some advice, which I'll summarize here:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Once you have a way to generate non-orthogonal determinants, you can use &lt;a href=&quot;https://github.com/BoothGroup/pygnme&quot; rel=&quot;nofollow noreferrer&quot;&gt;this Python interface to libgnme&lt;/a&gt; to evaluate non-orthogonal matrix elements, for example &lt;span class=&quot;math-container&quot;&gt;$\langle D_i|H | D_j  \rangle$&lt;/span&gt; for single-excitations.&lt;/li&gt;&#xA;&lt;li&gt;The libgnme GitHub page suggests the following papers for further reading (both by Hugh Burton):&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/154/14/144109/199579/Generalized-nonorthogonal-matrix-elements-Unifying&quot; rel=&quot;nofollow noreferrer&quot;&gt;Generalized nonorthogonal matrix elements: Unifying Wick’s theorem and the Slater–Condon rules&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/157/20/204109/2842193/Generalized-nonorthogonal-matrix-elements-II&quot; rel=&quot;nofollow noreferrer&quot;&gt;Generalized nonorthogonal matrix elements. II: Extension to arbitrary excitations&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;On the other hand, the free and open source software OpenMolcas can already do NOCI.&lt;/p&gt;&#xA;&lt;h5&gt;Also, after I wrote this answer, it was brought to my attention that &lt;a href=&quot;https://github.com/pyscf/pyscf/issues/1697#issuecomment-1760824474&quot; rel=&quot;nofollow noreferrer&quot;&gt;someone has indeed implemented NOCI in PySCF&lt;/a&gt; but it is not yet merged into the main PySCF branch.&lt;/h5&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-10-21T16:05:53.553" LastActivityDate="2023-10-21T16:05:53.553" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11735" PostTypeId="2" ParentId="10574" CreationDate="2023-10-12T16:45:25.957" Score="2" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10574/how-to-add-the-scissor-operator-in-quantum-espresso-input#comment22621_10574&quot;&gt;This comment by Abdul Muhaymin&lt;/a&gt; provides the following thread from the Quantum ESPRESSO mailing list which I'm including below (for me, I couldn't even visit the thread online because my browser told me that there was a security risk, so I clicked &amp;quot;accept risk and continue&amp;quot; but since I'm providing the contents here, you don't need to do that):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Is it possible to use the scissor operator in a TDDFT calculation&#xA;using turbo_davidson or turbo_lanczos?&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes in turbo_lanczos: the keyword is &amp;quot;scissor&amp;quot; in the lr_control&#xA;namelist. But I do not remember if it is in Ry or eV.&lt;/p&gt;&#xA;&lt;p&gt;Cheers,&lt;/p&gt;&#xA;&lt;p&gt;Iurii&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;There was a follow-up question about whether the units are in Ry or eV:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Dear Iurii, Thanks! It is not described in the docs, but I figured out&#xA;that the variable scissor is used here:&#xA;&lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/TDDFPT/src/lr_apply_liouvillian.f90#L557&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/blob/develop/TDDFPT/src/lr_apply_liouvillian.f90#L557&lt;/a&gt;:&#xA;(and here:&#xA;&lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/TDDFPT/src/lr_apply_liouvillian.f90#L711&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/QEF/q-e/-/blob/develop/TDDFPT/src/lr_apply_liouvillian.f90#L711&lt;/a&gt;&#xA;)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    DO ibnd = 1,nbnd       !       CALL zaxpy(ngk(1), CMPLX(-(et(ibnd,1)-scissor),0.0d0,DP), &amp;amp;                      &amp;amp;&#xA;spsi1(:,ibnd), 1, sevc1_new(:,ibnd,1), 1)       !    ENDDO&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Can you tell from this bit whether it is in Ry or eV? It seems from&#xA;lr_readin.f90 that the units aren't converted.&lt;/p&gt;&#xA;&lt;p&gt;Best wishes, Michal&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The answer was given here:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Dear Michal,&lt;/p&gt;&#xA;&lt;p&gt;Scissor must be specified in Ry units.&lt;/p&gt;&#xA;&lt;p&gt;Greetings,&lt;/p&gt;&#xA;&lt;p&gt;Iurii&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-10-12T16:45:25.957" CommentCount="0" CommunityOwnedDate="2023-10-12T16:45:25.957" ContentLicense="CC BY-SA 4.0" />
  <row Id="11736" PostTypeId="2" ParentId="11723" CreationDate="2023-10-12T23:45:43.837" Score="3" Body="&lt;p&gt;I don't think it is possible as it is required to use a smearing method in order to obtain the fermi energy. By doing so, you can not get the values of HOMO and LUMO levels. so obtaining both of them from a single calculation may not be feasible.&lt;/p&gt;&#xA;&lt;p&gt;I would advise you to take the Fermi energy from a &lt;strong&gt;well-converged&lt;/strong&gt; scf calculation because the Fermi energy value tends to slightly change from one type of calculation to another. To obtain the HOMO and LUMO levels, you will have to run another scf calculation without smearing and by using the &lt;code&gt;nbnd&lt;/code&gt; command (number of Kohn-Sham states) with a value basically the same as the number of electrons in the system.&lt;/p&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="6055" LastEditDate="2023-10-13T07:41:20.563" LastActivityDate="2023-10-13T07:41:20.563" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11737" PostTypeId="2" ParentId="11666" CreationDate="2023-10-12T23:55:24.757" Score="3" Body="&lt;p&gt;To obtain both the VB and CB you will have to run scf calculation by using the &lt;code&gt;nbnd&lt;/code&gt; command (the number of Kohn-Sham states) with a value basically the same as the number of electrons in the system. Both energy levels will appear in the SCF output file.&lt;/p&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="6055" LastEditDate="2023-10-13T07:38:17.410" LastActivityDate="2023-10-13T07:38:17.410" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11738" PostTypeId="1" CreationDate="2023-10-13T04:42:25.733" Score="4" ViewCount="87" Body="&lt;p&gt;To what extent can current coarse-grained models, within the context of multiscale modelling, retain essential quantum mechanical characteristics such as electron correlation, polarization, and quantum de-localization? Especially in scenarios where quantum effects significantly influence the system’s behavior?&lt;/p&gt;&#xA;" OwnerUserId="605" LastEditorUserId="605" LastEditDate="2023-10-13T16:08:42.527" LastActivityDate="2023-10-14T07:19:57.050" Title="To what extent can coarse-grained models retain the essential quantum mechanical characteristics of a system?" Tags="|quantum-mechanics|electron-correlation|coarse-grained|multiscale-modeling|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11739" PostTypeId="1" CreationDate="2023-10-13T12:43:04.103" Score="4" ViewCount="105" Body="&lt;p&gt;As the title already states is DFT+U considered an ab initio method?&lt;/p&gt;&#xA;" OwnerUserId="8137" LastEditorUserId="5" LastEditDate="2023-10-13T17:51:24.193" LastActivityDate="2023-10-15T05:22:56.450" Title="Is DFT+U an ab initio based method?" Tags="|density-functional-theory|dft-u|" AnswerCount="0" CommentCount="5" ClosedDate="2023-10-15T18:30:11.580" ContentLicense="CC BY-SA 4.0" />
  <row Id="11740" PostTypeId="1" AcceptedAnswerId="11746" CreationDate="2023-10-13T17:10:47.453" Score="5" ViewCount="185" Body="&lt;p&gt;Rephrasing the above, what is the content of the data in the CHGCAR file?&lt;/p&gt;&#xA;&lt;p&gt;Is the data part shown below representative of the electron-charge density or is it the actual charge in the system and I have to divide by the volume of the unit cell to get the charge density?&lt;/p&gt;&#xA;&#xA;&lt;pre&gt;&lt;code&gt;64   64   64&#xA; 0.27296628474E+03 0.27129538645E+03 0.26632236747E+03 0.25816527382E+03 0.24701868651E+03&#xA; 0.23315320780E+03 0.21691723332E+03 0.19873896341E+03 0.17912393717E+03 0.15864307047E+03&#xA; 0.13790873569E+03 0.11754046377E+03 0.98125176377E+02 0.80177959210E+02 0.64108387081E+02&#xA; 0.50195641939E+02 0.38574367354E+02 0.29232778335E+02 0.22024079253E+02 0.16690923309E+02&#xA; 0.12900228129E+02 0.10283187627E+02 0.84752878195E+01 0.72047216409E+01 0.63226226628E+01&#xA; 0.57166613639E+01 0.53025284991E+01 0.50199593897E+01 0.48277275324E+01 0.46988015018E+01&#xA; 0.46162530737E+01 0.45701256193E+01 0.45552760083E+01 0.45701256193E+01 0.46162530737E+01&#xA; 0.46988015018E+01 0.48277275324E+01 0.50199593897E+01 0.53025284991E+01 0.57166613639E+01&#xA; 0.63226226628E+01 0.72047216409E+01 0.84752878195E+01 0.10283187627E+02 0.12900228129E+02&#xA; 0.16690923309E+02 0.22024079253E+02 0.29232778335E+02 0.38574367354E+02 0.50195641939E+02&#xA; 0.64108387081E+02 0.80177959210E+02 0.98125176377E+02 0.11754046377E+03 0.13790873569E+03&#xA; 0.15864307047E+03 0.17912393717E+03 0.19873896341E+03 0.21691723332E+03 0.23315320780E+03&#xA; 0.24701868651E+03 0.25816527382E+03 0.26632236747E+03 0.27129538645E+03 0.27129538645E+03&#xA;..................... over a hundred thousand lines of data&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="3566" LastEditDate="2023-10-13T21:50:17.783" LastActivityDate="2023-10-14T09:41:30.353" Title="Contents of a CHGCAR file and how to read it appropriately in Python?" Tags="|density-functional-theory|vasp|python|electronic-structure|fortran|" AnswerCount="1" CommentCount="3" ClosedDate="2023-11-05T16:22:16.123" ContentLicense="CC BY-SA 4.0" />
  <row Id="11741" PostTypeId="2" ParentId="11507" CreationDate="2023-10-13T18:12:00.943" Score="-1" Body="&lt;p&gt;If you use Thermo-Calc and database provided by TCSAB, which I assume is encrypted, there is very little help you can get from anyone expect from TCSAB itself.  But there are some free High Entropy Alloy (HEA) databases around and I may be able to point at some and then you can use other software such as OpenCalphad which is also free or MetCalc or Pandat (which are commercial and may have theor own HEA alloy databases).  I am not sure how good TC-Python is for multicomponent systems.&lt;br /&gt;&#xA;The calculation problem is usually that the difference in Gibbs energy between the verious phases is very small in certain composition and T regions and there are ordering transformations in FCC and BCC which complicate finding the most stable state.&lt;/p&gt;&#xA;&lt;p&gt;The question is also how much one can trust the result.  All multicomponent calculations are based on model parameters determined from experiments in binary and ternary alloys.  A few multicomponent experimental data may be used to improve such extrapolations.  There are many useful papers in the Calphad journal which can be helpful.&#xA;It the calculation works at 1300K but not 1325 you may use the result at 1300K, the uncertainty is probably more than 25K.  Or you can calculate at 1350K you can interpolate manually.  Or vary the composition a little and look for experimental results in similar alloys.&lt;/p&gt;&#xA;&lt;p&gt;You can find OC at opencalphad.org or at sundmanbo/opencalphad at Github and you are welcome to contact me by email. I am retired but still trying to promote good use of thermodynamics and modeling.&lt;/p&gt;&#xA;" OwnerUserId="1092" LastActivityDate="2023-10-13T18:12:00.943" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11742" PostTypeId="1" CreationDate="2023-10-13T19:21:42.003" Score="3" ViewCount="34" Body="&lt;p&gt;How does one do the calculation of a convex hull with the WIEN2k code for the formation energy of alloys?&lt;/p&gt;&#xA;" OwnerUserId="8141" LastEditorUserId="5" LastEditDate="2023-10-13T19:48:21.707" LastActivityDate="2023-10-13T19:48:21.707" Title="Convex hull calculations with WIEN2k" Tags="|density-functional-theory|condensed-matter|mathematical-modeling|alloys|wien2k|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11743" PostTypeId="2" ParentId="9600" CreationDate="2023-10-13T21:28:48.160" Score="1" Body="&lt;p&gt;The grand potential depend on T, the chemical potentials of the components and on V.&#xA;The Gibbs energy (previously called Gibbs free energy) depend on T, P and the amount of the components.&lt;/p&gt;&#xA;&lt;p&gt;There is also the Helmhotz energy which depend on T, V and the amount of the components and the entalpy which depend on S, P and the amount of the components.  All derived from the internal energy which depend on S, V and the amount of the components.&lt;/p&gt;&#xA;&lt;p&gt;S, V and the amount of the components are extensive propertites whih depend on the amount of material.  T, P and the chemical potentials are intensive properties, independent of the amount.&lt;/p&gt;&#xA;&lt;p&gt;The grand potential depend on a single extensive property, V&#xA;if you replace V by its potential, P then you get zero because you have no material at all.&lt;/p&gt;&#xA;" OwnerUserId="1092" LastActivityDate="2023-10-13T21:28:48.160" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11744" PostTypeId="1" CreationDate="2023-10-14T00:15:57.110" Score="4" ViewCount="64" Body="&lt;p&gt;I would like to calculate the above quantities for a given unit cell (or supercell) with arbitrary symmetry. Specifically, I am trying to use a machine-learned interatomic potential (MLIP), and since the MLIP will only give me energies for given atomic configurations, I need to be able to calculate these elastic constants using energies only. I know, for instance, that the bulk modulus can be calculated by changing the lattice parameter and fitting the energy curve to the Birch-Murnaghan equation of state (EOS), but I am not sure what to do for Poisson's ratio.&lt;/p&gt;&#xA;&lt;p&gt;Any help is greatly appreciated, and if this has already been asked before I would be happy to be redirected to those answers. However, from the searching that I did, I could not find answers pertaining to going from energies to moduli. Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="8143" LastEditorUserId="8143" LastEditDate="2023-10-15T18:49:24.000" LastActivityDate="2023-10-15T18:49:24.000" Title="Explicit calculation of Poisson's ratio using energies from a potential energy surface" Tags="|density-functional-theory|physical-properties-of-materials|interatomic-potentials|elasticity|" AnswerCount="0" CommentCount="4" ClosedDate="2023-10-17T23:14:52.613" ContentLicense="CC BY-SA 4.0" />
  <row Id="11745" PostTypeId="2" ParentId="11738" CreationDate="2023-10-14T07:19:57.050" Score="7" Body="&lt;p&gt;Generally, in multi-scale modelling, QM characteristics are irrelevant. Most of the processes that we study for these multi-scale modelling are thermodynamics driven. So, I will be very surprised if these CG models retain these QM properties. Also, it depends on how much Coarse graining of the system you are doing. Even AA force-fields fail to do so. Furthermore, look how these CG FF are parameterized. Like Martini, the popular CG FF is parameterized against thermodynamic data, so I don't think it can retain these QM characteristics. These CG models are supposed to explain only the physical processes happening at the longer length and time scale where QM properties are generally irrelevant.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-10-14T07:19:57.050" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11746" PostTypeId="2" ParentId="11740" CreationDate="2023-10-14T09:41:30.353" Score="1" Body="&lt;p&gt;You can simply use ASE to read CHGCAR file by &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/calculators/vasp/vasp_auxiliary.py#L19&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;ase.calculators.vasp.VaspChargeDensity&lt;/code&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.calculators.vasp import VaspChargeDensity&#xA;&#xA;vcd = VaspChargeDensity('CHGCAR')&#xA;charge_density = vcd.chg&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-10-14T09:41:30.353" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11747" PostTypeId="1" CreationDate="2023-10-14T18:05:37.157" Score="7" ViewCount="112" Body="&lt;p&gt;I have been working to implement optimisation in internal coordinates (for a transition state search software I am working on). However, the implementation details are almost always glossed over in the paper.&lt;/p&gt;&#xA;&lt;p&gt;I have been trying to optimise with the Delocalised Internal Coordinates (Baker). In this case, &amp;quot;primitive&amp;quot; internal coordinates which include bonds, angles, dihedrals, out-of-plane bending etc. are built up. Then the B matrix (partial derivatives of primitives vs Cartesian components of the atoms) is formed, and then the G matrix (&lt;span class=&quot;math-container&quot;&gt;$B B^T$&lt;/span&gt;) is diagonalised and only the non-zero components are taken to obtain the non-redundant set of coordinates. For a non-linear molecule the number of non-redundant delocalised should be 3N-6. If the number is less than this, then it means not enought primitives were considered (e.g. there were two fragments not connected with any bond, or angles were not added).&lt;/p&gt;&#xA;&lt;p&gt;This part is covered in papers. However, what is not covered in detail is how to deal with linear molecule. For vibrational analysis linear molecules have 3N-5 normal modes. However, I am not sure how many internal coordinates are required for optimising linear molecules. Because with a linear molecule like &lt;span class=&quot;math-container&quot;&gt;$\ce{CO2}$&lt;/span&gt; for example, there are two degenerate linear bends. However, in terms of optimisation, it is obvious to me that only one bend mode is needed &lt;strong&gt;for optimisation&lt;/strong&gt;, since as soon as the structure deviates from linearity, there is only one bending mode, the other one vanishes. I also know that for linear molecules, two orthogonal primitive linear bends are used by Gaussian optimisers for example.&lt;/p&gt;&#xA;&lt;p&gt;So how many non-redundant coordinates should be generated for linear molecules? &lt;strong&gt;How to handle nearly linear molecules&lt;/strong&gt;? Is there a threshold in terms of numbers that can be used for removing the redundant eigenvectors from G matrix for these cases?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-10-15T20:58:13.953" Title="How many non-redundant internal coordinates are needed for optimisation of linear molecule?" Tags="|gaussian|geometry-optimization|vibrations|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11748" PostTypeId="2" ParentId="10624" CreationDate="2023-10-14T20:56:38.773" Score="1" Body="&lt;p&gt;Since the author of this question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10624/neb-calculations-in-vasp?noredirect=1#comment25139_10624&quot;&gt;no longer needs an answer&lt;/a&gt;, we are prioritizing more urgent questions in the unanswered queue, but if anyone want to answer this question, please ping me in a comment or click Flag and say so, and this Community Wiki answer will be deleted.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-10-14T20:56:38.773" CommentCount="0" CommunityOwnedDate="2023-10-14T20:56:38.773" ContentLicense="CC BY-SA 4.0" />
  <row Id="11749" PostTypeId="2" ParentId="11633" CreationDate="2023-10-15T01:12:59.140" Score="3" Body="&lt;p&gt;The short answer is that, scientifically, it doesn't matter which cell you use, but you need to think about what you actually want to compute. In particular (as mentioned in the comments to your question):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The total energy is not meaningful by itself, because it has an arbitrary zero. It is the &lt;em&gt;differences&lt;/em&gt; in total energy between different calculations which are interesting, because these relate to actual observables. For example, the change in energy when you move an atom a small amount tells you the force acting on that atom.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The total energy you compute will be the total energy for the simulation cell you used as input. When comparing energies between two systems, you will usually want to normalise the total energy to per atom (or possibly per unit volume), so that you can compare systems with different numbers of atoms.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For example, if cell A is a 2-atom primitive cell of a particular material phase, and cell B is the 8-atom conventional cell of a different phase (of the same material), you might be interested in knowing which phase has the lowest internal energy. Because cell B has four times the number of atoms that cell A has, you need to divide its total energy by four in order to compare it to the energy from cell A. In general, the simplest is to convert the energies to the energy &lt;em&gt;per atom&lt;/em&gt;, in which case the energy from cell A would be divided by 2, and the energy of cell B would be divided by 8.&lt;/p&gt;&#xA;&lt;p&gt;When comparing energies between two simulations, you do need to ensure both calculations are converged to the same accuracy so that the errors cancel when you take the difference.&lt;/p&gt;&#xA;&lt;p&gt;This is the answer as far as the &amp;quot;science&amp;quot; goes; however, the computational demands of a larger cell will almost always be greater than those of the smaller cell. This is because the time taken by a conventional density functional theory programme (like QE) increases faster than linearly with the size of the simulated cell. Some parts of the calculation scale quadratically with the number of electrons, for example, and some parts scale cubically. In contrast, a larger simulation cell will use fewer k-points, so there is some saving in computational time there (though not enough to offset the increase in bands, plane-waves and atoms).&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-10-15T01:12:59.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11751" PostTypeId="2" ParentId="11716" CreationDate="2023-10-15T06:06:01.123" Score="2" Body="&lt;p&gt;I think the number of &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt; atoms is too few compared to the organic species, I am afraid the use of an inconsistent &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; makes the problem more complicated besides the computational cost mentioned in the comments.&lt;/p&gt;&#xA;&lt;p&gt;I would have recommended to use a LCAO basis-set, a small basis set on &lt;span class=&quot;math-container&quot;&gt;$\ce{Ni}$&lt;/span&gt; will be sufficient to ensure a localization and a hybrid function will reduce the self-interaction error and give a more accurate energy gap. Since Vasp is used for this calculation, instead of using &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, I will suggest a sufficiently large cut-off first and then add this correction if the result is really inconsistent, but &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; can be avoided in this case.&lt;/p&gt;&#xA;" OwnerUserId="6019" LastActivityDate="2023-10-15T06:06:01.123" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11752" PostTypeId="1" CreationDate="2023-10-15T07:54:42.983" Score="5" ViewCount="46" Body="&lt;p&gt;I am looking for error correction packages for VASP calculations that can be integrated into a high-throughput worfklow. Ideally the software would both find and propose fixes for errors at runtime, but just reporting errors during post-processing would be okay as well. I sometimes run one-off calculations that also need to be checked.&lt;/p&gt;&#xA;&lt;p&gt;The only comprehensive error corrector that I know about is &lt;a href=&quot;https://github.com/materialsproject/custodian/blob/master/custodian/vasp/handlers.py&quot; rel=&quot;noreferrer&quot;&gt;Custodian&lt;/a&gt; from the Materials Project. I've looked briefly at other frameworks such as ASE and pyiron and did not find anything comparable, but it may be because I am not as familiar with them.&lt;/p&gt;&#xA;" OwnerUserId="8027" LastActivityDate="2023-10-15T07:54:42.983" Title="Error correction software for VASP calculations" Tags="|vasp|software-recommendations|one-topic-per-answer|high-throughput|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11753" PostTypeId="1" CreationDate="2023-10-15T10:05:37.080" Score="4" ViewCount="99" Body="&lt;p&gt;I have some results about the energy of H2 as a function of the bond length using Restricted HF (RHF) and Unrestricted HF (UHF) methods. With a zero-initialization of the density matrix I have the same results which is expected. But When I use a random initialization (Uniform on [0,1]) for both density matrices, the scf loop converges to weird values. And when I only initialize one of the density matrices I have what I suppose to be the UHF solution.&lt;/p&gt;&#xA;&lt;p&gt;How are density matrices initialized in Unrestricted calculations (UHF, Unrestricted Kohn-Sham)? Is there any schemes to have a more robust algorithm?&lt;/p&gt;&#xA;&lt;p&gt;legend:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;uhf = UHF with zero initialization of both matrices&lt;/li&gt;&#xA;&lt;li&gt;uhf P_alpha random = P_alpha is initialized with uniform distribution on [0, 1] and P_beta as zeros&lt;/li&gt;&#xA;&lt;li&gt;uhf P_alpha and P_beta random = both matrices are initialized with uniform distribution&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MiP0j.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MiP0j.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Edit:&lt;/h1&gt;&#xA;&lt;p&gt;I forgot the Coulomb interaction between the alpha and beta orbitals and I used rotation mentionned in &lt;a href=&quot;https://chemistry.stackexchange.com/questions/42005/initial-guess-for-unrestricted-hartree-fock-calculation/42325#42325&quot;&gt;Tyberius comment&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As initial guess I used the HOMO and LUMO orbitals of H2:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$C_{\alpha} = C_{\beta} = \frac{1}{\sqrt{2}}\begin{pmatrix}&#xA;1 &amp;amp; 1\\&#xA;-1 &amp;amp; 1 &#xA;\end{pmatrix}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then I rotated the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; orbitals, with &lt;span class=&quot;math-container&quot;&gt;$\theta = \frac{\pi}{2}$&lt;/span&gt; : &lt;span class=&quot;math-container&quot;&gt;$$ C^{new}_{\alpha} = \begin{pmatrix}&#xA;cos(\theta) &amp;amp; -sin(\theta)\\&#xA;sin(\theta) &amp;amp; cos(\theta) &#xA;\end{pmatrix}C_{\alpha}$$&lt;/span&gt;&#xA;Here are the results:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Fhqyq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Fhqyq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-10-19T06:20:37.680" LastActivityDate="2023-10-30T17:19:29.730" Title="Unrestricted Hartree-Fock : Density matrices initialization" Tags="|electronic-structure|ab-initio-calculations|hartree-fock|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11754" PostTypeId="1" CreationDate="2023-10-15T17:57:08.237" Score="4" ViewCount="44" Body="&lt;p&gt;I am calculating the optical properties of 200 atoms supercell with quantum espresso. What is the approximate number of the nscf kpoints (nk nk nk)should I start with, to avoid lengthy kpoints convergence for a large supercell.&lt;/p&gt;&#xA;" OwnerUserId="3450" LastActivityDate="2023-10-15T17:57:08.237" Title="supercell nscf kpoints for optical properties" Tags="|density-functional-theory|quantum-espresso|k-points|optical-properties|supercell|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11755" PostTypeId="2" ParentId="10665" CreationDate="2023-10-15T20:17:07.993" Score="2" Body="&lt;p&gt;Haven't used it myself, but I believe the chemspace API has a search-by-SMILES endpoint that returns prices &lt;a href=&quot;https://api.chem-space.com/docs/#/Search%20by%20SMILES/post_v3_search_exact&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://api.chem-space.com/docs/#/Search%20by%20SMILES/post_v3_search_exact&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In order to get an API key, you need to register an account at chem-space.com, and then&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;please contact us at info@chem-space.com.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Good luck!&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2023-10-15T20:17:07.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11756" PostTypeId="2" ParentId="6284" CreationDate="2023-10-15T20:30:58.673" Score="0" Body="&lt;p&gt;Not sure whether it will satisfy all your thirst for knowledge, but you could have a look at the chapter on &amp;quot;Long-Range Interactions&amp;quot; (11 or 12, depending on edition) in &amp;quot;Understanding Molecular Simulation&amp;quot; by Frenkel &amp;amp; Smit.&lt;/p&gt;&#xA;&lt;p&gt;Right at the beginning of the chapter, there is paragraph that is relevant to your question&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2gf6k.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2gf6k.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="873" LastActivityDate="2023-10-15T20:30:58.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11757" PostTypeId="2" ParentId="11747" CreationDate="2023-10-15T20:58:13.953" Score="7" Body="&lt;p&gt;Indeed, Baker's delocalized coordinates routines generate 3N-6 (or 3N-5 for linear molecules) coordinates automagically. Note our &lt;a href=&quot;http://dx.doi.org/10.1002/qua.21049&quot; rel=&quot;noreferrer&quot;&gt;small contribution&lt;/a&gt; where we distinguish between strong and weak coordinates.&lt;/p&gt;&#xA;&lt;p&gt;For linear molecules ABC, you can indeed use symmetry (if the program has C(lin) symmetry), &lt;strong&gt;and&lt;/strong&gt; if there are no other molecules present. Therefore, within &lt;a href=&quot;https://www.marcelswart.eu/quild&quot; rel=&quot;noreferrer&quot;&gt;QUILD&lt;/a&gt; we use dummy atoms (D). These are placed 1.0 Bohrs from the central atom B, with an angle of 90 degrees to one of the end point atoms (A). The angle DBC is then close to 90 degrees as well. All of the derivatives for angle ABC are then replaced by the dihedral ABDC, which &lt;strong&gt;is&lt;/strong&gt; well defined.&lt;/p&gt;&#xA;&lt;p&gt;Three small details: the choice of where to place the D atom is chosen within QUILD to point as close as possible to the center of mass if there are more molecules in the system. I.e. for D we have a bond of 1.0 to B, an angle of 90 degrees to A, but we need a dihedral angle to some other atom. And if only three atoms are present, we make an arbitrary choice for this reference atom.&lt;/p&gt;&#xA;&lt;p&gt;Second detail: up to an deviation of (I think) 5 degrees from linearity &lt;strong&gt;in the starting structure&lt;/strong&gt;, a dummy atom is added. During the optimization this may go beyond this value, and no dummy atom is any longer needed. Then the coordinates setup is reset, without dummy atom for this angle, and new delocalized coordinates are generated. Normally, the delocalized coordinates are only set once, and updated after e.g. 50 or 100 geometry steps.&lt;/p&gt;&#xA;&lt;p&gt;Third detail: a dummy atom is &lt;strong&gt;only&lt;/strong&gt; added if the middle atom has only two connections. If there are more atoms connected, the linear angle is either included with low weight (depending on deviation from linearity), such that the other &amp;quot;normal&amp;quot; angles are used, or the almost-linear angles are ignored.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-10-15T20:58:13.953" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="11758" PostTypeId="1" CreationDate="2023-10-15T21:08:42.347" Score="3" ViewCount="94" Body="&lt;p&gt;I m a material science student of PhD and search alot and make some input files for AIMD simulation but I didn't get the best output if anyone have the input file please provide me&lt;/p&gt;&#xA;" OwnerUserId="7779" LastEditorUserId="5" LastEditDate="2023-10-16T01:25:19.413" LastActivityDate="2023-10-16T01:25:19.413" Title="I need molecular dynamics simulations input file for hexagonal heterostructures in quantum espresso" Tags="|molecular-dynamics|quantum-espresso|software-input-file-request|aimd|heterostructures|" AnswerCount="0" CommentCount="10" ClosedDate="2023-10-24T19:31:05.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="11759" PostTypeId="1" CreationDate="2023-10-16T13:50:52.327" Score="6" ViewCount="103" Body="&lt;p&gt;I am trying to perform an SCF calculation using HSE hybrid functional to measure the band gap of a 2D semiconductor, but my calculation reached the level of calculating the exact exchange and seemingly stopped. Here are the last lines of the output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Using ACE for calculation of exact exchange&#xA;&#xA;EXX grid: 915277 G-vectors FFT dimensions: ( 120, 120, 150)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What could cause a calculation to fail here?&lt;/p&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="7" LastEditDate="2023-10-16T15:03:19.663" LastActivityDate="2023-10-16T15:03:19.663" Title="SCF calculations using HSE hybrid functional dying/stopping?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="3" ClosedDate="2023-11-05T16:22:39.830" ContentLicense="CC BY-SA 4.0" />
  <row Id="11760" PostTypeId="1" CreationDate="2023-10-16T15:55:39.030" Score="9" ViewCount="109" Body="&lt;p&gt;I am trying to write a Newton-Raphson geometry optimisation script in python (&lt;a href=&quot;https://gitlab.com/erjvd/newton_raphson_gaussian/-/tree/main&quot; rel=&quot;nofollow noreferrer&quot;&gt;Current version of my code&lt;/a&gt;) using the energy, gradient and Hessian from Gaussian 16. In order to reach a minimum, I would need to add a line search, and possibly also add a trust region, but I am struggling to understand how it works (in Cartesian coordinates, with an analytical Hessian). I read the book of Fletcher and had a look at the pyBerny code, but it doesn't work so far.&lt;/p&gt;&#xA;&lt;p&gt;Without a line search, no minimum is found; the molecule's energy increases and it breaks apart. If I use code based on the pyBerny package, no fit can be found.&lt;/p&gt;&#xA;&lt;p&gt;Are there any obvious problems with my line search code?&lt;/p&gt;&#xA;" OwnerUserId="8152" LastEditorUserId="7" LastEditDate="2023-10-17T17:18:17.827" LastActivityDate="2023-10-17T17:18:17.827" Title="How does the line search in geometry optimisations work?" Tags="|python|gaussian|geometry-optimization|optimization|pyberny|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11761" PostTypeId="5" CreationDate="2023-10-16T17:37:00.963" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://github.com/jhrmnn/pyberny&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/jhrmnn/pyberny&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-10-16T17:37:00.963" LastActivityDate="2023-10-16T17:37:00.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11762" PostTypeId="4" CreationDate="2023-10-16T17:37:00.963" Score="0" Body="Questions about PyBerny, a Pytho-based geometry optimization software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-10-16T17:37:00.963" LastActivityDate="2023-10-16T17:37:00.963" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11763" PostTypeId="1" CreationDate="2023-10-16T18:45:03.913" Score="9" ViewCount="170" Body="&lt;p&gt;With reference to the GROMACS manual 2023.2, the discussion of the Berendsen thermostat (p. 362) indicates that the time constant &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; which governs the steepness of the relaxation toward a target temperature (eqn. 5.37: &lt;span class=&quot;math-container&quot;&gt;$\frac{\mathrm{d}T}{\mathrm{d}t} = \frac{(T_0 - T)}{\tau}$&lt;/span&gt;) is not equal to to the parameter &lt;span class=&quot;math-container&quot;&gt;$\tau_T$&lt;/span&gt; found in the description of the re-scaling factor (eqn. 5.38): &lt;span class=&quot;math-container&quot;&gt;$$\lambda = \left[ 1 + \frac{n_{\mathrm{TC}}\Delta t}{\tau_T}\left(\frac{T_0}{T(t - \frac{1}{2} \Delta t)} - 1\right)  \right] ^{\frac{1}{2}}.$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;They are related via eqn 5.39: &lt;span class=&quot;math-container&quot;&gt;$\tau = 2C_V\tau_t / N_{df}k$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The reason cited is: &amp;quot;The reason that &lt;span class=&quot;math-container&quot;&gt;$\tau \neq \tau_T$&lt;/span&gt; is that the kinetic energy change caused by scaling the velocities is partly redistributed between kinetic and potential energy and hence the change in temperature is less than the scaling energy.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;I don't understand this explanation. Where does the redistribution of potential energies occur? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="6642" LastActivityDate="2023-10-24T12:06:03.350" Title="Berendsen thermostat: why are the two time constants not equal?" Tags="|molecular-dynamics|temperature|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11764" PostTypeId="1" CreationDate="2023-10-17T06:45:03.573" Score="4" ViewCount="238" Body="&lt;p&gt;I am trying to write the analysis using gmx energy in a bash script. When this is usually passed on a command line, it asks for an input from keyboard to choose the energy term from a list of terms.&lt;/p&gt;&#xA;&lt;p&gt;This can be automated in a bash script using the keyword echo as follows:&lt;/p&gt;&#xA;&lt;p&gt;echo Temperature | gmx energy -f md.edr&lt;/p&gt;&#xA;&lt;p&gt;Or&lt;/p&gt;&#xA;&lt;p&gt;echo &amp;quot;11 0&amp;quot; | gmx energy -f md.edr&lt;/p&gt;&#xA;&lt;p&gt;However the problem comes when the energy term is &amp;quot;1/Viscosity&amp;quot; . It recognises only the number 1 and outputs the first energy term. I have tried placing it in quotes, as well as preceding it with a $ sign. None of them work. How to overcome this problem when the energy term doesn't start with a letter?&lt;/p&gt;&#xA;" OwnerUserId="148" LastEditorUserId="5" LastEditDate="2023-10-17T14:08:22.663" LastActivityDate="2023-10-18T14:25:12.113" Title="How to automate GROMACS analysis in a bash script?" Tags="|gromacs|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11766" PostTypeId="1" CreationDate="2023-10-17T17:57:05.740" Score="3" ViewCount="69" Body="&lt;p&gt;I have an interatomic potential (&lt;a href=&quot;https://github.com/CederGroupHub/chgnet&quot; rel=&quot;nofollow noreferrer&quot;&gt;CHGNet&lt;/a&gt;) which is interfaced with pymatgen and can output the stress on any structure. Now, I want to use pymatgen to calculate the bulk modulus for aluminum. The code I use is attached below, along with the output. I used the DeformedStructureSet technique to create different strains on the material, and then using CHGNet predict the stresses corresponding to each strain&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from chgnet.model.model import CHGNet&#xA;from pymatgen.core import Structure&#xA;from pymatgen.analysis.elasticity.strain import Deformation, DeformedStructureSet, Strain&#xA;from pymatgen.analysis.elasticity.stress import Stress&#xA;from pymatgen.analysis.elasticity import ElasticTensor&#xA;&#xA;chgnet = CHGNet.load()&#xA;structure = Structure.from_file('cif_files/Al.cif')&#xA;prediction = chgnet.predict_structure(structure)&#xA;&#xA;eq_stress = Stress(prediction['s'])&#xA;&#xA;deformed_structure = DeformedStructureSet(structure)&#xA;&#xA;strain_list = [i.green_lagrange_strain for i in deformed_structure.deformations]&#xA;stress_list = []&#xA;&#xA;for i in range(len(deformed_structure)):&#xA;    prediction = chgnet.predict_structure(deformed_structure[i])&#xA;    stress_list.append(Stress(prediction['s']))&#xA;&#xA;elastic_tensor = ElasticTensor.from_independent_strains(strain_list, stress_list, eq_stress)&#xA;&#xA;print(elastic_tensor.property_dict)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The answer I get is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{'k_voigt': 9.845064083735359, 'k_reuss': 9.845063833881039, 'k_vrh': 9.845063958808199, 'g_voigt': 8.0023897488912, 'g_reuss': 4.5904549461157655, 'g_vrh': 6.2964223475034835, 'universal_anisotropy': 3.716336252207812, 'homogeneous_poisson': 0.23641618649298335, 'y_mod': 15569997014.898907}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is wrong, since the bulk modulus of aluminum is around 76-80 GPa. What have I missed? Or is there some obvious mistake? I am more than happy to be directed in the correct way. Many thanks!&lt;/p&gt;&#xA;" OwnerUserId="8143" LastEditorUserId="8143" LastEditDate="2023-10-17T17:57:31.740" LastActivityDate="2023-10-17T17:57:31.740" Title="Calculating bulk modulus of aluminum using pymatgen and MLIP" Tags="|physical-properties-of-materials|elasticity|pymatgen|materials-project|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11767" PostTypeId="1" CreationDate="2023-10-18T02:01:33.460" Score="3" ViewCount="154" Body="&lt;p&gt;I am doing energy calculations for the graphene structure in CASTEP code. The structure consists of 30 atoms. I want to find out its band structure and density of state.&lt;/p&gt;&#xA;&lt;p&gt;When I run the calculations, after up to 60 or 70 iterations, it cannot respond. Sometimes the job fails, but most of the time, in 60 or 70 iterations, it does not go further. I waited for it for a long time, but still it did not go further, so I stopped the job by myself.&lt;/p&gt;&#xA;&lt;p&gt;I don't know what to do. Should I first do geometry optimization without checking the band structure and density of state and then do energy optimization? But in energy, then I have to check the band structure and density of state because I have seen somewhere that first you have to do geometry optimization and then do energy optimization by checking band structure and density of state.&lt;/p&gt;&#xA;&lt;p&gt;I am doing collinear spin polarization. One more thing: should I uncheck, fix occupancy, and optimize the total cell? By default, it is already checked.&lt;/p&gt;&#xA;&lt;p&gt;Please, anyone, suggest something about this. I need help in this regard.&lt;a href=&quot;https://i.stack.imgur.com/uIJNd.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uIJNd.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8161" LastEditorUserId="24" LastEditDate="2023-10-18T11:35:51.867" LastActivityDate="2023-10-18T11:35:51.867" Title="About Geometry and Energy calculations in castep" Tags="|castep|" AnswerCount="0" CommentCount="23" ContentLicense="CC BY-SA 4.0" />
  <row Id="11768" PostTypeId="1" AcceptedAnswerId="11828" CreationDate="2023-10-18T06:32:06.227" Score="5" ViewCount="141" Body="&lt;p&gt;I have been working on a toy &lt;a href=&quot;https://github.com/HemanthHaridas/plank.py/tree/release&quot; rel=&quot;nofollow noreferrer&quot;&gt;HF code&lt;/a&gt; for some time. From &lt;a href=&quot;https://www.mathematica-journal.com/2012/02/16/evaluation-of-gaussian-molecular-integrals/&quot; rel=&quot;nofollow noreferrer&quot;&gt;this reference&lt;/a&gt; I am trying to work out an analytic expression for the first derivatives of overlap integrals.&#xA;The original expression for overlap is given as:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;S_x(a_x,b_x) = \sqrt{\frac{\pi}{\alpha + \beta}}*\sum_{i_x=0}^{a_x}\binom{a_x}{i_x}(P_x-A_x)^{(a_x-i_x)}*\sum_{j_x=0}^{b_x}\binom{b_x}{j_x}(P_x-B_x)^{(b_x-j_x)}*\frac{(i_x+j_x-1)!!}{2[\alpha+\beta]^{(\frac{i_x+j_x}{2})}}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Working through the expression and ignoring the constants, I got to this step&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{dS_x}{dA_x}=(a_x - i_x) (P_x-A_x)^{(a_x-i_x-1)}(P_x-B_x)^{(b_x-j_x)}\frac{d}{dA_x}\left(P_x-A_x\right) + (b_x - j_x) (P_x-B_x)^{(b_x-j_x-1)}(P_x-A_x)^{(a_x-i_x)}\frac{d}{dA_x}\left(P_x-B_x\right)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;P_x = \frac{\alpha*A_x + \beta * B_x}{(\alpha + \beta)}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, I am not sure if this expression is correct. Some pointers to the exact analytic expressions would be much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Edit:&lt;/p&gt;&#xA;&lt;p&gt;Using Mathematica to work out the expressions, I got these two expressions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{dS_x}{dA_x} = \left(\frac{\alpha}{\alpha+\beta}\right)^{(b_x-j_x)}*\left(\frac{\beta}{\alpha+\beta}\right)^{(a_x-i_x)}*(A_x-B_x)^{(b_x-j_x-1)}*(B_x-A_x)^{(a_x-i_x)}*\left(a_x+b_x-(i_x+j_x)\right)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\frac{dS_x}{dB_x} = -\left(\frac{\alpha}{\alpha+\beta}\right)^{(b_x-j_x)}*\left(\frac{\beta}{\alpha+\beta}\right)^{(a_x-i_x)}*(A_x-B_x)^{(b_x-j_x-1)}*(B_x-A_x)^{(a_x-i_x)}*\left(a_x+b_x-(i_x+j_x)\right)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="671" LastEditDate="2023-10-21T15:51:55.270" LastActivityDate="2023-10-30T17:42:09.953" Title="Evaluating analytic gradients for overlap integrals" Tags="|python|reference-request|mathematical-modeling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11769" PostTypeId="1" CreationDate="2023-10-18T10:51:28.700" Score="4" ViewCount="142" Body="&lt;p&gt;after running nscf calculations I faced this problem and I don't know what could be the cause of it.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Computing kpt #:    25  of    82&#xA;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     Error in routine  cdiaghg (659):&#xA;     problems computing cholesky&#xA;&#xA;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     stopping ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I run the code in parallel using: &lt;code&gt;mpirun -np 30 pw.x &amp;lt; s.in &amp;gt; s.out&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;input script :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    &amp;amp;CONTROL&#xA;    calculation   = &amp;quot;nscf&amp;quot;&#xA;    outdir        = &amp;quot;./temp&amp;quot;&#xA;    prefix        = &amp;quot;tc&amp;quot; &#xA;    pseudo_dir    = &amp;quot;./pseudopot&amp;quot;&#xA;    verbosity     = 'high'&#xA;/&#xA;&#xA;    &amp;amp;SYSTEM&#xA;    a           =  12.144&#xA;    c           =  17&#xA;    !degauss     =  0.02&#xA;    ecutrho     =  5.50000e+02&#xA;    ecutwfc     =  6.50000e+01&#xA;    ibrav       = 4&#xA;    nat         = 81&#xA;    nbnd        = 658&#xA;    nspin       = 2&#xA;    ntyp        = 4&#xA;    occupations = 'tetrahedra'&#xA;    !smearing    = &amp;quot;gaussian&amp;quot;&#xA;    tot_magnetization =  1&#xA;    vdw_corr    = 'dft-d3'&#xA;/&#xA;&#xA;    &amp;amp;ELECTRONS&#xA;    conv_thr         =  1.00000e-10&#xA;/&#xA;&#xA;    K_POINTS {automatic}&#xA;    9  9  1  0 0 0&#xA;&#xA;    ATOMIC_SPECIES&#xA;    C      12.01070  C.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;    O      15.99940  O.pbe-nl-kjpaw_psl.1.0.0.UPF&#xA;    Ti     47.86700  Ti.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;    Co     58.93319  Co.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;    ATOMIC_POSITIONS {angstrom}&#xA;...&#xA;...&#xA;Truncuated&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="6055" LastEditDate="2023-10-18T18:47:51.817" LastActivityDate="2023-10-19T13:11:35.017" Title="computing cholesky errer in nscf calculations?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11770" PostTypeId="1" CreationDate="2023-10-18T13:36:02.750" Score="2" ViewCount="62" Body="&lt;p&gt;&lt;strong&gt;Why energy/pressure are slighly off, what is possible solution for making them equal. Any suggestion/comment?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;clear&#xA;&#xA;package gpu 1 neigh no binsize 5.0 newton off&#xA;&#xA;&#xA;units metal&#xA;boundary        p p p&#xA;atom_style      atomic&#xA;variable lp equal &amp;quot;2.86&amp;quot;&#xA;lattice bcc ${lp} orient x 1 0 0 orient y 0 1 0 orient z  0 0 1&#xA;region whole block 0 1 0 1 0 1 units lattice&#xA;create_box 1 whole&#xA;create_atoms 1 region whole&#xA;replicate 30 30 30&#xA;mass 1 1&#xA;# ---------- Define Interatomic Potential --------------------- &#xA;pair_style lj/cut 2.5&#xA;pair_coeff * * 1 1&#xA;&#xA;# ---------- Run Minimization --------------------- &#xA;reset_timestep 0 &#xA;run 0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;log.cpu&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;units metal&#xA;boundary        p p p&#xA;atom_style      atomic&#xA;variable lp equal &amp;quot;2.86&amp;quot;&#xA;lattice bcc ${lp} orient x 1 0 0 orient y 0 1 0 orient z  0 0 1&#xA;lattice bcc 2.86 orient x 1 0 0 orient y 0 1 0 orient z  0 0 1&#xA;Lattice spacing in x,y,z = 2.86 2.86 2.86&#xA;region whole block 0 1 0 1 0 1 units lattice&#xA;create_box 1 whole&#xA;Created orthogonal box = (0 0 0) to (2.86 2.86 2.86)&#xA;  1 by 1 by 2 MPI processor grid&#xA;create_atoms 1 region whole&#xA;Created 2 atoms&#xA;  using lattice units in orthogonal box = (0 0 0) to (2.86 2.86 2.86)&#xA;  create_atoms CPU = 0.000 seconds&#xA;replicate 30 30 30&#xA;Replication is creating a 30x30x30 = 27000 times larger system...&#xA;  orthogonal box = (0 0 0) to (85.8 85.8 85.8)&#xA;  1 by 1 by 2 MPI processor grid&#xA;  54000 atoms&#xA;  replicate CPU = 0.001 seconds&#xA;mass 1 1&#xA;# ---------- Define Interatomic Potential ---------------------&#xA;pair_style lj/cut 2.5&#xA;pair_coeff * * 1 1&#xA;&#xA;# ---------- Run Minimization ---------------------&#xA;reset_timestep 0&#xA;run 0&#xA;WARNING: No fixes with time integration, atoms won't move (../verlet.cpp:60)&#xA;Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule&#xA;Neighbor list info ...&#xA;  update: every = 1 steps, delay = 0 steps, check = yes&#xA;  max neighbors/atom: 2000, page size: 100000&#xA;  master list distance cutoff = 4.5&#xA;  ghost atom cutoff = 4.5&#xA;  binsize = 2.25, bins = 39 39 39&#xA;  1 neighbor lists, perpetual/occasional/extra = 1 0 0&#xA;  (1) pair lj/cut, perpetual&#xA;      attributes: half, newton on&#xA;      pair build: half/bin/atomonly/newton&#xA;      stencil: half/bin/3d&#xA;      bin: standard&#xA;Per MPI rank memory allocation (min/avg/max) = 10.22 | 10.22 | 10.22 Mbytes&#xA;   Step          Temp          E_pair         E_mol          TotEng         Press     &#xA;         0   0             -3726.0493      0             -3726.0493     -18820.611    &#xA;Loop time of 9.615e-07 on 2 procs for 0 steps with 54000 atoms&#xA;&#xA;0.0% CPU use with 2 MPI tasks x no OpenMP threads&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 0          | 0          | 0          |   0.0 |  0.00&#xA;Neigh   | 0          | 0          | 0          |   0.0 |  0.00&#xA;Comm    | 0          | 0          | 0          |   0.0 |  0.00&#xA;Output  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Modify  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Other   |            | 9.615e-07  |            |       |100.00&#xA;&#xA;Nlocal:          27000 ave       27000 max       27000 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;Nghost:          14566 ave       14566 max       14566 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;Neighs:         351000 ave      351000 max      351000 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 702000&#xA;Ave neighs/atom = 13&#xA;Neighbor list builds = 0&#xA;Dangerous builds = 0&#xA;&#xA;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;log.gpu&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LAMMPS (2 Aug 2023)&#xA;Lattice spacing in x,y,z = 2.86 2.86 2.86&#xA;Created orthogonal box = (0 0 0) to (2.86 2.86 2.86)&#xA;  1 by 1 by 2 MPI processor grid&#xA;Created 2 atoms&#xA;  using lattice units in orthogonal box = (0 0 0) to (2.86 2.86 2.86)&#xA;  create_atoms CPU = 0.000 seconds&#xA;Replication is creating a 30x30x30 = 27000 times larger system...&#xA;  orthogonal box = (0 0 0) to (85.8 85.8 85.8)&#xA;  1 by 1 by 2 MPI processor grid&#xA;  54000 atoms&#xA;  replicate CPU = 0.002 seconds&#xA;&#xA;CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE&#xA;&#xA;Your simulation uses code contributions which should be cited:&#xA;- GPU package (short-range, long-range and three-body potentials): doi:10.1016/j.cpc.2010.12.021, doi:10.1016/j.cpc.2011.10.012, doi:10.1016/j.cpc.2013.08.002, doi:10.1016/j.commatsci.2014.10.068, doi:10.1016/j.cpc.2016.10.020, doi:10.3233/APC200086&#xA;The log file lists these citations in BibTeX format.&#xA;&#xA;CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE&#xA;&#xA;WARNING: No fixes with time integration, atoms won't move (../verlet.cpp:60)&#xA;&#xA;--------------------------------------------------------------------------&#xA;- Using acceleration for lj/cut:&#xA;-  with 2 proc(s) per device.&#xA;-  Horizontal vector operations: ENABLED&#xA;-  Shared memory system: No&#xA;--------------------------------------------------------------------------&#xA;Device 0: NVIDIA GeForce RTX 3090, 82 CUs, 17/24 GB, 1.7 GHZ (Mixed Precision)&#xA;--------------------------------------------------------------------------&#xA;&#xA;Initializing Device and compiling on process 0...Done.&#xA;Initializing Device 0 on core 0...Done.&#xA;Initializing Device 0 on core 1...Done.&#xA;&#xA;Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule&#xA;Neighbor list info ...&#xA;  update: every = 1 steps, delay = 0 steps, check = yes&#xA;  max neighbors/atom: 2000, page size: 100000&#xA;  master list distance cutoff = 4.5&#xA;  ghost atom cutoff = 4.5&#xA;  binsize = 2.25, bins = 39 39 39&#xA;  1 neighbor lists, perpetual/occasional/extra = 1 0 0&#xA;  (1) pair lj/cut/gpu, perpetual&#xA;      attributes: full, newton off&#xA;      pair build: full/bin/atomonly&#xA;      stencil: full/bin/3d&#xA;      bin: standard&#xA;Setting up Verlet run ...&#xA;  Unit style    : metal&#xA;  Current step  : 0&#xA;  Time step     : 0.001&#xA;Per MPI rank memory allocation (min/avg/max) = 13.68 | 13.68 | 13.68 Mbytes&#xA;   Step          Temp          E_pair         E_mol          TotEng         Press     &#xA;         0   0             -3726.0488      0             -3726.0488     -18820.609    &#xA;Loop time of 1.1825e-06 on 2 procs for 0 steps with 54000 atoms&#xA;&#xA;0.0% CPU use with 2 MPI tasks x no OpenMP threads&#xA;&#xA;MPI task timing breakdown:&#xA;Section |  min time  |  avg time  |  max time  |%varavg| %total&#xA;---------------------------------------------------------------&#xA;Pair    | 0          | 0          | 0          |   0.0 |  0.00&#xA;Neigh   | 0          | 0          | 0          |   0.0 |  0.00&#xA;Comm    | 0          | 0          | 0          |   0.0 |  0.00&#xA;Output  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Modify  | 0          | 0          | 0          |   0.0 |  0.00&#xA;Other   |            | 1.183e-06  |            |       |100.00&#xA;&#xA;Nlocal:          27000 ave       27000 max       27000 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;Nghost:          14566 ave       14566 max       14566 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;Neighs:              0 ave           0 max           0 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;FullNghs:       702000 ave      702000 max      702000 min&#xA;Histogram: 2 0 0 0 0 0 0 0 0 0&#xA;&#xA;Total # of neighbors = 1404000&#xA;Ave neighs/atom = 26&#xA;Neighbor list builds = 0&#xA;Dangerous builds = 0&#xA;&#xA;&#xA;---------------------------------------------------------------------&#xA;      Device Time Info (average): &#xA;---------------------------------------------------------------------&#xA;Average split:   1.0000.&#xA;Lanes / atom:    4.&#xA;Vector width:    32.&#xA;Prefetch mode:   None.&#xA;Max Mem / Proc:  7.71 MB.&#xA;CPU Cast/Pack:   0.0002 s.&#xA;CPU Driver_Time: 0.0000 s.&#xA;CPU Idle_Time:   0.0001 s.&#xA;---------------------------------------------------------------------&#xA;&#xA;Total wall time: 0:00:01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;output of ./lmp_gpu -h&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Large-scale Atomic/Molecular Massively Parallel Simulator - 2 Aug 2023&#xA;&#xA;Usage example: ./lmp_gpu -var t 300 -echo screen -in in.alloy&#xA;&#xA;List of command line options supported by this LAMMPS executable:&#xA;&#xA;-echo none/screen/log/both  : echoing of input script (-e)&#xA;-help                       : print this help message (-h)&#xA;-in none/filename           : read input from file or stdin (default) (-i)&#xA;-kokkos on/off ...          : turn KOKKOS mode on or off (-k)&#xA;-log none/filename          : where to send log output (-l)&#xA;-mdi '&amp;lt;mdi flags&amp;gt;'          : pass flags to the MolSSI Driver Interface&#xA;-mpicolor color             : which exe in a multi-exe mpirun cmd (-m)&#xA;-cite                       : select citation reminder style (-c)&#xA;-nocite                     : disable citation reminder (-nc)&#xA;-nonbuf                     : disable screen/logfile buffering (-nb)&#xA;-package style ...          : invoke package command (-pk)&#xA;-partition size1 size2 ...  : assign partition sizes (-p)&#xA;-plog basename              : basename for partition logs (-pl)&#xA;-pscreen basename           : basename for partition screens (-ps)&#xA;-restart2data rfile dfile ... : convert restart to data file (-r2data)&#xA;-restart2dump rfile dgroup dstyle dfile ... &#xA;                            : convert restart to dump file (-r2dump)&#xA;-reorder topology-specs     : processor reordering (-r)&#xA;-screen none/filename       : where to send screen output (-sc)&#xA;-skiprun                    : skip loops in run and minimize (-sr)&#xA;-suffix gpu/intel/opt/omp   : style suffix to apply (-sf)&#xA;-var varname value          : set index style variable (-v)&#xA;&#xA;OS: Linux &amp;quot;Ubuntu 22.04.2 LTS&amp;quot; 5.15.0-86-generic x86_64&#xA;&#xA;Compiler: GNU C++ 11.4.0 with OpenMP not enabled&#xA;C++ standard: C++11&#xA;MPI v3.1: Intel(R) MPI Library 2021.6 for Linux* OS&#xA;&#xA;&#xA;Accelerator configuration:&#xA;&#xA;GPU package API:&#xA;GPU package precision: mixed&#xA;&#xA;Compatible GPU present: yes&#xA;&#xA;Active compile time flags:&#xA;&#xA;-DLAMMPS_GZIP&#xA;-DLAMMPS_SMALLBIG&#xA;sizeof(smallint): 32-bit&#xA;sizeof(imageint): 32-bit&#xA;sizeof(tagint):   32-bit&#xA;sizeof(bigint):   64-bit&#xA;&#xA;Available compression formats:&#xA;&#xA;Extension: .gz     Command: gzip&#xA;Extension: .bz2    Command: bzip2&#xA;Extension: .zst    Command: zstd&#xA;Extension: .xz     Command: xz&#xA;Extension: .lzma   Command: xz&#xA;Extension: .lz4    Command: lz4&#xA;&#xA;&#xA;Installed packages:&#xA;&#xA;GPU MANYBODY MEAM REPLICA &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2023-10-18T13:36:02.750" Title="Different Output from lammps cpu vs gpu" Tags="|lammps|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11772" PostTypeId="1" CreationDate="2023-10-18T15:45:20.237" Score="5" ViewCount="228" Body="&lt;p&gt;I am currently running a fairly large system (NELECT&amp;gt;7400) on the OpenACC GPU port of VASP 6.4.1 on 16 Nvidia A100 GPUs: 4 GPUs x 4 nodes (NCSA Delta 4-Way NVIDIA A100 GPU Compute Nodes). Each of these nodes has an AMD Milan processor with 64 cores and 256G RAM.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to optimize my parallelization parameters to leverage the CPUs and GPUs fully. Currently I see a CPU usage of only about 10-15% during the electronic steps. SSH'ing into a running node and executing &lt;code&gt;top&lt;/code&gt; I see:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Tasks: 985 total,   5 running, 980 sleeping,   0 stopped,   0 zombie&#xA;%Cpu(s):  9.9 us,  2.0 sy,  0.0 ni, 88.1 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st&#xA;MiB Mem : 257657.6 total, 178810.2 free,  62478.3 used,  16369.1 buff/cache&#xA;MiB Swap:      0.0 total,      0.0 free,      0.0 used. 180957.8 avail Mem &#xA;&#xA;    PID USER      PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ COMMAND                                                                                                                               &#xA; 666852 user      20   0   71.2g  14.8g 903220 R 199.0   5.9  68:33.14 vasp_gam                                                                                                                              &#xA; 666851 user      20   0   71.2g  14.6g 865724 R 191.4   5.8  69:11.01 vasp_gam                                                                                                                              &#xA; 666849 user      20   0   80.5g  15.1g 979208 R 183.1   6.0  68:41.78 vasp_gam                                                                                                                              &#xA; 666850 user      20   0   71.2g  14.6g 866220 R 182.5   5.8  68:09.62 vasp_gam  &#xA;  57391 root      20   0  436628  41512   9348 S   1.3   0.0 169:23.16 nv-hostengine  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My calculation is Gamma-point only so my only choices for NCORE and KPAR are NCORE=KPAR=1. I know the efficiency of the GPU implementation of VASP relies on NSIM being set higher than the default, however when I set NSIM&amp;gt;4 I run out of memory on the GPUs.&lt;/p&gt;&#xA;&lt;p&gt;Here is a condensed version of my job script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH --job-name=&amp;quot;vasp&amp;quot;&#xA;#SBATCH --partition=gpuA100x4&#xA;#SBATCH --nodes=4&#xA;#SBATCH --mem=0&#xA;#SBATCH --ntasks-per-node=4&#xA;#SBATCH --cpus-per-task=16   # spread out to use 1 core per numa, set to 64 if tasks is 1&#xA;#SBATCH --gpus-per-node=4&#xA;#SBATCH --gpu-bind=closest   # select a cpu close to gpu on pci bus topology&#xA;#SBATCH --exclusive  # dedicated node for this job&#xA;#SBATCH -t 8:00:00&#xA;&#xA;export OMP_NUM_THREADS=16&#xA;srun -N 4 -n 16 vasp_gam &amp;gt; output&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As requested by in the comments, here is my full INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Algorithms&#xA;PREC=Normal&#xA;LREAL=Auto&#xA;ALGO=Fast&#xA;NELMDL=5&#xA;&#xA;#Convergence&#xA;EDIFF=1.E-6&#xA;ENCUT=400&#xA;AMIN=0.01&#xA;BMIX=0.0001&#xA;AMIX=0.5&#xA;NELM=80&#xA;NELMIN=4&#xA;&#xA;#Parallelization&#xA;NCORE=1&#xA;KPAR=1&#xA;NSIM=4&#xA;&#xA;#Restart and I/O&#xA;ISTART=0&#xA;LWAVE=.TRUE&#xA;LCHARG=.FALSE&#xA;&#xA;#Defaults&#xA;ISMEAR=0 ; SIGMA=1E-4&#xA;&#xA;#Relaxation&#xA;ISIF=2&#xA;IBRION=2&#xA;EDIFFG=-1.E-3&#xA;POTIM=1&#xA;NSW=15&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Are there any changes to how I call &lt;code&gt;vasp_gam&lt;/code&gt; that would increase CPU utilization and presumably improve runtime?&lt;/p&gt;&#xA;" OwnerDisplayName="user8097" LastEditorDisplayName="user8097" LastEditDate="2023-10-23T22:10:25.470" LastActivityDate="2023-11-10T05:09:56.410" Title="How can I maximize both CPU and GPU usage when running OpenACC VASP?" Tags="|vasp|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11773" PostTypeId="2" ParentId="10688" CreationDate="2023-10-19T02:15:57.810" Score="2" Body="&lt;p&gt;I was able to compile the &lt;code&gt;phana&lt;/code&gt; code but &lt;code&gt;fix phonon&lt;/code&gt; just gave a peak around zero. I raised an &lt;a href=&quot;https://github.com/lingtikong/fix-phonon/issues/16&quot; rel=&quot;nofollow noreferrer&quot;&gt;issue on the GitHub repository&lt;/a&gt; and it is still open until the writing of this answer. Based on my experience, &lt;code&gt;fix phonon&lt;/code&gt; is not to be trusted.&lt;/p&gt;&#xA;&lt;p&gt;Instead, I used a tool called &lt;a href=&quot;https://phonolammps.readthedocs.io/en/master/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PhonoLAMMPS&lt;/a&gt; to get the forces calculated by LAMMPS in a format readable by &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Phonopy&lt;/a&gt;, and then used Phonopy to get the phonon band structure and phonon density of states (DOS) at 0 K.&lt;/p&gt;&#xA;&lt;p&gt;The know-how can be found in the examples of both codes. Just follow the links.&lt;/p&gt;&#xA;&lt;p&gt;The way to get this information at finite temperatures is handled by a code called &lt;a href=&quot;https://abelcarreras.github.io/DynaPhoPy/&quot; rel=&quot;nofollow noreferrer&quot;&gt;DynaPhoPy&lt;/a&gt;, but it doesn't calculate the phonon DOS directly, just the power spectrum, which is an approximation to the phonon DOS that is very sensitive to the supercell size.&lt;/p&gt;&#xA;" OwnerUserId="336" LastEditorUserId="336" LastEditDate="2023-10-19T02:22:18.853" LastActivityDate="2023-10-19T02:22:18.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11774" PostTypeId="2" ParentId="3589" CreationDate="2023-10-19T09:52:52.450" Score="2" Body="&lt;p&gt;I have made these two videos for VASP AIMD calculations. First video i have explined how to convert XDATCAR to .pdb file and next one I explained how to make movie from XDATCAR.pdb file.&#xA;If you discover this information to be beneficial, kindly express your support by giving it a thumbs up, leaving a comment, and sharing it with others. We appreciate your viewership.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;How to Convert AIMD XDATCAR file into a pdb file using VASPKIT:&#xA;&lt;a href=&quot;https://youtu.be/zYopurMg0Ac?si=vgaAjQCxJ72_G6p3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://youtu.be/zYopurMg0Ac?si=vgaAjQCxJ72_G6p3&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;How to create a movie from XDATCAR file:&#xA;&lt;a href=&quot;https://youtu.be/x987ZKr5GB4?si=dFHf0Usq4wItNQ1q&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://youtu.be/x987ZKr5GB4?si=dFHf0Usq4wItNQ1q&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Best&#xA;SB&lt;/p&gt;&#xA;" OwnerUserId="8170" LastActivityDate="2023-10-19T09:52:52.450" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11775" PostTypeId="2" ParentId="6153" CreationDate="2023-10-19T10:37:43.120" Score="2" Body="&lt;p&gt;I have made three videos for absorbance, emission and fluorescence calculation using Gaussian 09. If you discover this information to be beneficial, kindly express your support by giving it a thumbs up, leaving a comment, and sharing it with others. We appreciate your viewership.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;How to calculate UV-VIS spectra in Gaussian 09/16 | TD-DFT&#xA;&lt;a href=&quot;https://www.youtube.com/watch?v=fsd55cP3ObA&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=fsd55cP3ObA&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;How to calculate Emission spectra in Gaussian 09/16 (TD-DFT)&#xA;&lt;a href=&quot;https://www.youtube.com/watch?v=CM_Zc82k9JY&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=CM_Zc82k9JY&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;How to calculate Theoretical fluorescence spectra using Gaussian 09W/g16 | TD-DFT&#xA;&lt;a href=&quot;https://www.youtube.com/watch?v=GGuUEynNu64&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.youtube.com/watch?v=GGuUEynNu64&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Thank you&#xA;Best&#xA;SB&lt;/p&gt;&#xA;" OwnerUserId="8170" LastActivityDate="2023-10-19T10:37:43.120" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11777" PostTypeId="2" ParentId="11769" CreationDate="2023-10-19T13:11:35.017" Score="5" Body="&lt;p&gt;Errors during &lt;code&gt;cdiagh&lt;/code&gt; occur often enough to merit &lt;a href=&quot;https://www.quantum-espresso.org/faq/faq-frequent-errors-during-execution/#5.7&quot; rel=&quot;noreferrer&quot;&gt;section 5.7 of the &lt;code&gt;Quantum ESPRESSO&lt;/code&gt; FAQ&lt;/a&gt;. Basically, at some k-point, your Hamilonian has become singular, obviously a problem. Three possible fixes&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Double-check your atomic positions; you've a lot of atoms in the unit cell, were two of them inadvertently placed too close together?&lt;/li&gt;&#xA;&lt;li&gt;I see you're using projector-augmented waves as pseudopotentials; is that necessary? This error occurs less often with norm-conserving pseudopotentials such as the &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.239906&quot; rel=&quot;noreferrer&quot;&gt;optimized norm-conserving Vanderbilt pseudopotentials (ONCVPSP)&lt;/a&gt;, which you can &lt;a href=&quot;https://github.com/pipidog/ONCVPSP&quot; rel=&quot;noreferrer&quot;&gt;download from GitHub&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;You can also specify a conjugate gradient update method via &lt;code&gt;diagonalization = 'cg'&lt;/code&gt; in the &lt;code&gt;&amp;amp;ELECTRONS&lt;/code&gt; section of your input file. It's a bit slower, but tends to be more reliable.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-10-19T13:11:35.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11778" PostTypeId="1" CreationDate="2023-10-19T14:13:19.773" Score="5" ViewCount="35" Body="&lt;p&gt;Related to the question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/4971/are-there-dashboards-displaying-experimental-properties-of-molecular-materials&quot;&gt;Are there dashboards displaying experimental properties of molecular materials&lt;/a&gt;?&lt;/p&gt;&#xA;&lt;p&gt;My question is: Are there any &lt;strong&gt;good, free, online databases on calculated vibrational modes of inorganic molecules&lt;/strong&gt;, in particular including &lt;a href=&quot;https://en.wikipedia.org/wiki/Coordination_complex&quot; rel=&quot;noreferrer&quot;&gt;&lt;strong&gt;coordination complexes&lt;/strong&gt;&lt;/a&gt;? Even if it's not interactive (thus, not a dashboard), I'd need to be able to look for complexes of certain metal ions and certain kinds of ligands and check out their normal vibrational modes.&lt;/p&gt;&#xA;&lt;p&gt;In the previous question some databases where mentioned, so, in particular, is there anything for this purpose beyond the &lt;a href=&quot;https://cccbdb.nist.gov/vsfx.asp&quot; rel=&quot;noreferrer&quot;&gt;Computational Chemistry Comparison and Benchmark DataBase&lt;/a&gt;? Also, would the Molecule Explorer within &lt;a href=&quot;https://next-gen.materialsproject.org/&quot; rel=&quot;noreferrer&quot;&gt;Materials Project&lt;/a&gt; any good for this purpose?&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2023-10-19T14:33:59.857" Title="Database on calculated molecular vibrations including coordination complexes?" Tags="|computational-chemistry|physical-properties-of-materials|vibrations|databases|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11779" PostTypeId="2" ParentId="11778" CreationDate="2023-10-19T14:33:59.857" Score="3" Body="&lt;p&gt;So far, the best I have found is &lt;a href=&quot;https://www.iochem-bd.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ioChem-BD - The Computational Chemistry Results Repository&lt;/a&gt;. It lets one search by text (e.g. &amp;quot;Schiff&amp;quot;, to locate complexes based on Schiff ligands), it includes at least some calculations on coordination complexes and, by clicking on &amp;quot;view data&amp;quot;, among the calculated data it does show the normal vibrational modes, not just the spectra but complete with a JMol visualization of the individual vibrations.&lt;/p&gt;&#xA;" OwnerUserId="198" LastActivityDate="2023-10-19T14:33:59.857" CommentCount="1" CommunityOwnedDate="2023-10-19T16:49:22.527" ContentLicense="CC BY-SA 4.0" />
  <row Id="11780" PostTypeId="1" CreationDate="2023-10-20T01:10:30.787" Score="3" ViewCount="130" Body="&lt;p&gt;I am trying to generate an ESP surface of a Gaussian09 calculation using the iqmol software. I have used Gaussview to visualize the ESP surface by generating .cube files from .fchk files (using the cubgen utility), however, I prefer the visualization settings of iqmol (I do not have the time to play around with visualization settings with other softwares).&lt;/p&gt;&#xA;&lt;p&gt;The iqmol software requires a .cube file to generate the ESP surface (the software manual outlines the process to generate the ESP once a .cube file is loaded), however, every time I load the .cube file (generated from the cubegen utility) into the iqmol software, I get an error stating that the software cannot parse the information.&lt;/p&gt;&#xA;&lt;p&gt;I have limited experience with computational modeling (and frankly programming languages), however, I have seen from some of my research that each quantum chemistry program has different formats for .cube files. I assume the failure of iqmol to parse Gaussian09 .cube data is the result of incompatibility of the visualization software with the Gaussian .cube file. I have heard that there are ways of converting .cube file formats, however due to my lack of knowledge of programming (and time constraints), I would prefer to stray from this solution.&lt;/p&gt;&#xA;&lt;p&gt;The .fchk file contains all the relevant data to generate the .cube file for the ESP surface using the Gaussian cubegen utility, however, when the .fchk file is imported into iqmol (they are compatible), I cannot find the options to generate anything regarding the ESP surface.&lt;/p&gt;&#xA;&lt;p&gt;My question is:&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have experience visualizing ESP surfaces using .fchk/.cube files generated from Gaussian09 outputs using the iqmol software? Do I need to rerun the Gaussian09 single point calculations using certain keywords in the route section?&lt;/p&gt;&#xA;&lt;p&gt;I appreciate all the suggestions/help (and I hope this makes sense). Thank you.&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2023-10-20T01:10:30.787" Title="Advise in generating ESP surfaces from Gaussian .cube files using the IQmol software" Tags="|molecular-modeling|gaussian|visualization-software|potential-energy-surface|q-chem|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11781" PostTypeId="2" ParentId="11763" CreationDate="2023-10-20T13:23:53.990" Score="4" Body="&lt;p&gt;The cited formula for &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is a little bit non-standard compared to what other codes do because of the &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{TC}$&lt;/span&gt; parameter. E.g., inside LAMMPS, &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is obtained as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\lambda = \left[ 1 + \frac{\Delta t}{\tau} \left( \frac{T_0}{T} - 1\right) \right]^{1/2}&#xA;$$&lt;/span&gt;&#xA;which more or less reduces to the GROMACS formula when setting &lt;span class=&quot;math-container&quot;&gt;$n_\mathrm{TC} = 1$&lt;/span&gt;, i.e., applied at every time step (although LAMMPS uses velocities at the end of the velocity verlet step, i.e., using &lt;span class=&quot;math-container&quot;&gt;$T(t + \Delta t)$&lt;/span&gt;, rather than the halfway point of the integration).&lt;/p&gt;&#xA;&lt;p&gt;Now, regarding relaxation time. Suppose you've run NVE dynamics for some time, and reached equilibrium. Now, you're applying the thermostat exactly &lt;strong&gt;once&lt;/strong&gt;, setting &lt;span class=&quot;math-container&quot;&gt;$\tau = \Delta t$&lt;/span&gt;. That's equivalent to scaling the kinetic energy by &lt;span class=&quot;math-container&quot;&gt;$T_0/T$&lt;/span&gt;, so you would assume you've achieved perfect thermalization within a single step.&lt;/p&gt;&#xA;&lt;p&gt;However, the instantaneous coordinates of the system correspond to a state of temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;. For example, if &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is high, bonds will on average be more stretched, and molecule geometries will in general be further from their minimum energy configurations. If you would now scale down velocities so that the kinetic energy corresponds to a lower &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt;, you still have lots of excess energy stored in the potential energy component of the system. If you continue to run NVE MD, you'll notice that the average potential energy decreases, while the kinetic energy increases again. So in the end, the average temperature will have a value between the old &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; and the target &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;On a broader note, this means that &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is really just a parameter, rather than truly expressing the relaxation time scale. A smaller &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; will speed up equilibration, but the potential energy (and system configuration) will lag the manipulations of the kinetic energy. So setting &lt;span class=&quot;math-container&quot;&gt;$\tau = 10$&lt;/span&gt; ps does not mean the system is fully equilibrated after 10 ps.&lt;/p&gt;&#xA;&lt;p&gt;Finally, it's probably good to emphasize that nowadays there are not many reasons to still use a Berendsen thermostat for any production calculations except when trying to reproduce old simulations. This is because the Berendsen thermostat does not generate a correct canonical ensemble. All big simulations codes implement several algorithms that do, such as &lt;a href=&quot;https://doi.org/10.1063/1.463940&quot; rel=&quot;nofollow noreferrer&quot;&gt;Nosé-Hoover chains&lt;/a&gt;, the &lt;a href=&quot;https://doi.org/10.1063/1.2408420&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bussi-Donadio-Parrinello rescaling thermostat&lt;/a&gt;, and several types of (&lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.102.020601&quot; rel=&quot;nofollow noreferrer&quot;&gt;Generalized&lt;/a&gt;) &lt;a href=&quot;https://journals.aps.org/pre/abstract/10.1103/PhysRevE.75.056707&quot; rel=&quot;nofollow noreferrer&quot;&gt;Langevin thermostats&lt;/a&gt; (see also &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/ct900563s&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). Even if correct sampling is not required, many of these newer methods are also more efficient. A wider discussion as to which approach is best-suited for a given problem is beyond the scope of the current question.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2023-10-20T13:54:23.167" LastActivityDate="2023-10-20T13:54:23.167" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11782" PostTypeId="1" CreationDate="2023-10-20T19:48:18.083" Score="9" ViewCount="106" Body="&lt;p&gt;I am interested in exploring the use of machine learning tools to accelerate molecular dynamics simulation probably by training machine learning potentials. While I have found some papers that apply these concepts, I am having trouble finding good resources that can guide me in a clear and easy-to-understand way on how to proceed with developing:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;representations of chemical configurations,&lt;/li&gt;&#xA;&lt;li&gt;subsampling of databases,&lt;/li&gt;&#xA;&lt;li&gt;training a machine learning potential,&lt;/li&gt;&#xA;&lt;li&gt;use model to predict properties of materials&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I am wondering if someone can direct me to some good resources that can help me learn these skills on my own.&lt;/p&gt;&#xA;" OwnerUserId="5923" LastActivityDate="2023-10-20T19:48:18.083" Title="How to go from zero to hero in Machine Learning for materials modelling" Tags="|molecular-dynamics|reference-request|physical-properties-of-materials|machine-learning|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11783" PostTypeId="1" CreationDate="2023-10-20T22:45:50.683" Score="4" ViewCount="82" Body="&lt;p&gt;Seems that DFPT method in VASP has many defects. It can't include vdw interaction. Now I found it also can't include dipole correction, which leads to a large negative frequency at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. I found this problem because two different phases of my structure has almost similar large negative frequency at &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; point. Before this I've spent days tuning precision-related parameters.&lt;/p&gt;&#xA;&lt;p&gt;So does anyone know the reason behind this?&lt;/p&gt;&#xA;" OwnerUserId="6151" LastEditorUserId="6151" LastEditDate="2023-10-21T14:12:06.823" LastActivityDate="2023-10-24T11:31:01.037" Title="Why dipole correction does not work in VASP DFPT + phonopy calculation for a stable 2D material" Tags="|vasp|phonons|phonopy|phonon-dispersion|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11784" PostTypeId="2" ParentId="10466" CreationDate="2023-10-21T15:48:25.793" Score="1" Body="&lt;p&gt;The comments by Tyberius were accepted as a solution by the OP, this answer is to remove the question from the &amp;quot;unanswered&amp;quot; queue. I'll delete this Community Wiki answer if Tyberius does find the time to write a full answer!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-10-21T15:48:25.793" CommentCount="0" CommunityOwnedDate="2023-10-21T15:48:25.793" ContentLicense="CC BY-SA 4.0" />
  <row Id="11785" PostTypeId="5" CreationDate="2023-10-21T16:03:05.923" Score="0" Body="&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://smmg.pl/software/veda/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://smmg.pl/software/veda/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Not this: &lt;a href=&quot;https://veda-documentation.readthedocs.io/en/latest/pages/Getting%20started.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://veda-documentation.readthedocs.io/en/latest/pages/Getting%20started.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-10-21T16:03:05.923" LastActivityDate="2023-10-21T16:03:05.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11786" PostTypeId="4" CreationDate="2023-10-21T16:03:05.923" Score="0" Body="Questions about the VEDA software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-10-21T16:03:05.923" LastActivityDate="2023-10-21T16:03:05.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11787" PostTypeId="2" ParentId="10460" CreationDate="2023-10-22T06:34:03.130" Score="3" Body="&lt;p&gt;The 'vc-relax' calculation aims to minimize the total energy of the system by adjusting the atomic positions and the cell shape, allowing the system to find a more stable configuration.&#xA;The optimized lattice parameters obtained from the 'vc-relax' calculation represent the most energetically favorable configuration for the given material under the specific conditions of the calculation. Therefore, these optimized parameters should be used in subsequent calculations to determine various properties of the material accurately.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2023-10-22T06:34:03.130" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11788" PostTypeId="1" CreationDate="2023-10-22T21:46:59.483" Score="3" ViewCount="117" Body="&lt;p&gt;I have been trying to optimize the geometry of a copper based metal halide perovskite. I opened the CIF file using BURAI GUI and generated the VC-RELAX input file.&lt;/p&gt;&#xA;&lt;p&gt;I have increased the steps to be 200 but it's not converging either. Should I increase it more or making converging not necessary, or change the geometry? I'm using 222 geometry&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;calculation   = &amp;quot;vc-relax&amp;quot;&#xA;etot_conv_thr =  1.48000e-03&#xA;forc_conv_thr =  1.00000e-04&#xA;max_seconds   =  1.72800e+05&#xA;nstep         = 100&#xA;outdir        = &amp;quot;./out/&amp;quot;&#xA;prefix        = &amp;quot;aiida&amp;quot;&#xA;pseudo_dir    = &amp;quot;./pseudo/&amp;quot;&#xA;tprnfor       = .TRUE.&#xA;tstress       = .TRUE.&#xA;verbosity     = &amp;quot;high&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;a                         =  1.11000e+01&#xA;b                         =  1.11100e+01&#xA;c                         =  2.73500e+01&#xA;cosab                     = -4.97428e-01&#xA;cosac                     = -2.02275e-01&#xA;cosbc                     = -1.04720e-03&#xA;degauss                   =  1.00000e-02&#xA;ecutrho                   =  2.25000e+02&#xA;ecutwfc                   =  2.50000e+01&#xA;ibrav                     = 14&#xA;nat                       = 148&#xA;nosym                     = .FALSE.&#xA;nspin                     = 2&#xA;ntyp                      = 6&#xA;occupations               = &amp;quot;smearing&amp;quot;&#xA;smearing                  = &amp;quot;gaussian&amp;quot;&#xA;starting_magnetization(1) =  2.00000e-01&#xA;starting_magnetization(2) =  0.00000e+00&#xA;starting_magnetization(3) =  0.00000e+00&#xA;starting_magnetization(4) =  0.00000e+00&#xA;starting_magnetization(5) =  0.00000e+00&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;conv_thr         =  1.00000e-06&#xA;electron_maxstep = 200&#xA;mixing_beta      =  4.00000e-01&#xA;startingpot      = &amp;quot;atomic&amp;quot;&#xA;startingwfc      = &amp;quot;atomic+random&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;IONS&#xA;ion_dynamics = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&#xA;&amp;amp;CELL&#xA;cell_dynamics  = &amp;quot;bfgs&amp;quot;&#xA;/&#xA;&#xA;K_POINTS {automatic}&#xA; 2  2  2  0 0 0&#xA;&#xA;ATOMIC_SPECIES&#xA;C      12.01070  C.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;Cl     35.45300  cl_pbesol_v1.4.uspp.F.UPF&#xA;Cu     63.54600  Cu.paw.z_11.ld1.psl.v1.0.0-low.upf&#xA;H       1.00794  H.pbesol-rrkjus_psl.1.0.0.UPF&#xA;N      14.00670  N.pbesol-theos.UPF&#xA;O      15.99940  O.pbesol-n-kjpaw_psl.0.1.UPF&#xA;&#xA;ATOMIC_POSITIONS {crystal}&#xA;Cu      0.893200   0.446600   0.339890&#xA;Cu      0.106800   0.553400   0.660110&#xA;Cu      0.664500   0.413800   0.244840&#xA;Cu      0.335500   0.586200   0.755160&#xA;Cu      0.993800   0.580400   0.244720&#xA;Cu      0.006200   0.419600   0.755280&#xA;Cu      0.831000   0.250700   0.244780&#xA;Cu      0.169000   0.749300   0.755220&#xA;Cl      0.949000   0.474600   0.424110&#xA;Cl      0.051000   0.525400   0.575890&#xA;Cl      0.643300   0.386000   0.328930&#xA;Cl      0.356700   0.614000   0.671070&#xA;Cl      0.942400   0.256500   0.329040&#xA;Cl      0.057600   0.743500   0.670960&#xA;Cl      0.072100   0.685500   0.328940&#xA;Cl      0.927900   0.314500   0.671060&#xA;Cl      0.585900   0.165600   0.205400&#xA;Cl      0.414100   0.834400   0.794600&#xA;Cl      0.785700   0.619200   0.205400&#xA;Cl      0.214300   0.380800   0.794600&#xA;Cl      0.038700   0.419500   0.205100&#xA;Cl      0.961300   0.580500   0.794900&#xA;Cl      0.171800   0.771700   0.221000&#xA;Cl      0.828200   0.228300   0.779000&#xA;Cl      0.822000   0.049000   0.221700&#xA;Cl      0.178000   0.951000   0.778300&#xA;Cl      0.451500   0.401100   0.221500&#xA;Cl      0.548500   0.598900   0.778500&#xA;Cl      0.845100   0.424000   0.269000&#xA;Cl      0.154900   0.576000   0.731000&#xA;O       0.554300   0.972700   0.398700&#xA;O       0.445700   0.027300   0.601300&#xA;O       0.816500   0.844600   0.398100&#xA;O       0.183500   0.155400   0.601900&#xA;O       0.454700   0.692800   0.505600&#xA;O       0.545300   0.307200   0.494400&#xA;O       0.743600   0.050600   0.505500&#xA;O       0.256400   0.949400   0.494500&#xA;O       0.426400   0.582100   0.398400&#xA;O       0.573600   0.417900   0.601600&#xA;O       0.811300   0.762300   0.505100&#xA;O       0.188700   0.237700   0.494900&#xA;N       0.714600   0.857000   0.570600&#xA;N       0.285400   0.143000   0.429400&#xA;N       0.553900   0.776800   0.331000&#xA;N       0.446100   0.223200   0.669000&#xA;H       0.689440   0.844829   0.533761&#xA;H       0.310560   0.155171   0.466239&#xA;H       0.579313   0.789364   0.367886&#xA;H       0.420687   0.210636   0.632114&#xA;H       0.735114   0.160862   0.564411&#xA;H       0.264886   0.839138   0.435589&#xA;H       0.841142   0.678921   0.395960&#xA;H       0.158858   0.321079   0.604040&#xA;H       0.704775   0.649736   0.414285&#xA;H       0.295225   0.350264   0.585715&#xA;H       0.719695   0.676825   0.585741&#xA;H       0.280305   0.323175   0.414259&#xA;H       0.842147   0.808299   0.622875&#xA;H       0.157853   0.191701   0.377125&#xA;H       0.909131   0.040565   0.586306&#xA;H       0.090869   0.959435   0.413694&#xA;H       0.813329   0.030924   0.623104&#xA;H       0.186671   0.969076   0.376896&#xA;H       0.235671   0.555603   0.395626&#xA;H       0.764329   0.444397   0.604374&#xA;H       0.360678   0.709558   0.414549&#xA;H       0.639322   0.290442   0.585451&#xA;H       0.547082   0.867749   0.588341&#xA;H       0.452918   0.132251   0.411659&#xA;H       0.592225   0.777421   0.623171&#xA;H       0.407775   0.222579   0.376829&#xA;H       0.244872   0.570226   0.479705&#xA;H       0.755128   0.429774   0.520295&#xA;H       0.330351   0.493981   0.475924&#xA;H       0.669649   0.506019   0.524076&#xA;H       0.350554   0.447464   0.334884&#xA;H       0.649446   0.552536   0.665116&#xA;H       0.401359   0.578319   0.563975&#xA;H       0.598641   0.421681   0.436025&#xA;H       0.989675   0.829464   0.564572&#xA;H       0.010325   0.170536   0.435428&#xA;H       0.636243   0.651000   0.315864&#xA;H       0.363757   0.349000   0.684136&#xA;H       0.665570   0.767051   0.279407&#xA;H       0.334430   0.232949   0.720593&#xA;H       0.906574   0.672742   0.479967&#xA;H       0.093426   0.327258   0.520033&#xA;H       0.980463   0.833857   0.475886&#xA;H       0.019537   0.166143   0.524114&#xA;H       0.334136   0.682448   0.318611&#xA;H       0.665864   0.317552   0.681389&#xA;H       0.380737   0.618096   0.280136&#xA;H       0.619263   0.381904   0.719864&#xA;H       0.889507   0.899211   0.336346&#xA;H       0.110493   0.100789   0.663654&#xA;H       0.521735   0.053523   0.338859&#xA;H       0.478265   0.946477   0.661141&#xA;H       0.402733   0.898831   0.338727&#xA;H       0.597267   0.101169   0.661273&#xA;H       0.722602   0.159289   0.396309&#xA;H       0.277398   0.840711   0.603691&#xA;H       0.764948   0.049312   0.415820&#xA;H       0.235052   0.950688   0.584180&#xA;H       0.665808   0.985717   0.317207&#xA;H       0.334192   0.014283   0.682793&#xA;H       0.515106   0.900474   0.279644&#xA;H       0.484894   0.099526   0.720356&#xA;H       0.806425   0.233379   0.480260&#xA;H       0.193575   0.766621   0.519740&#xA;H       0.640892   0.144925   0.475762&#xA;H       0.359108   0.855075   0.524238&#xA;C       0.755900   0.095000   0.554000&#xA;C       0.244100   0.905000   0.446000&#xA;C       0.804500   0.718000   0.416600&#xA;C       0.195500   0.282000   0.583400&#xA;C       0.789500   0.775500   0.588100&#xA;C       0.210500   0.224500   0.411900&#xA;C       0.812400   0.011800   0.588400&#xA;C       0.187600   0.988200   0.411600&#xA;C       0.331500   0.612000   0.416600&#xA;C       0.668500   0.388000   0.583400&#xA;C       0.576700   0.798900   0.588900&#xA;C       0.423300   0.201100   0.411100&#xA;C       0.330700   0.580900   0.471800&#xA;C       0.669300   0.419100   0.528200&#xA;C       0.385300   0.539100   0.347900&#xA;C       0.614700   0.460900   0.652100&#xA;C       0.459000   0.664200   0.553700&#xA;C       0.541000   0.335800   0.446300&#xA;C       0.892600   0.798100   0.554200&#xA;C       0.107400   0.201900   0.445800&#xA;C       0.663100   0.748000   0.313900&#xA;C       0.336900   0.252000   0.686100&#xA;C       0.888900   0.748300   0.471700&#xA;C       0.111100   0.251700   0.528300&#xA;C       0.401200   0.653000   0.315100&#xA;C       0.598800   0.347000   0.684900&#xA;C       0.809300   0.844000   0.348800&#xA;C       0.190700   0.156000   0.651200&#xA;C       0.505300   0.962400   0.347000&#xA;C       0.494700   0.037600   0.653000&#xA;C       0.700900   0.084100   0.417300&#xA;C       0.299100   0.915900   0.582700&#xA;C       0.566400   0.915600   0.314400&#xA;C       0.433600   0.084400   0.685600&#xA;C       0.723500   0.139900   0.472100&#xA;C       0.276500   0.860100   0.527900&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7791" LastEditorUserId="24" LastEditDate="2023-10-22T22:43:33.917" LastActivityDate="2023-10-22T22:43:33.917" Title="Quantum Espresso optimization calculation not converging" Tags="|quantum-espresso|geometry-optimization|transition-metals|perovskites|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11789" PostTypeId="1" CreationDate="2023-10-23T07:44:37.920" Score="4" ViewCount="469" Body="&lt;p&gt;I would like to make formate-adsorbed surface on Cu(111). I have prepared the Cu(111) by ASE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase.build import surface&#xA;from ase.io import write, read&#xA;from ase.build import molecule&#xA;from ase.build import add_adsorbate&#xA;&#xA;# Create the copper surface&#xA;slab = surface('Cu', (1, 1, 1), 4)&#xA;slab = slab.repeat((4, 4, 1))&#xA;slab.center(vacuum=10, axis=2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can I put 10 formated ions on the surface (in &lt;strong&gt;bidentate&lt;/strong&gt; form) randomly? I don't know how to specify the ASE code to determine the ion as bidentate form, as well as the position of the adsorbates.&lt;/p&gt;&#xA;" OwnerUserId="7530" LastActivityDate="2024-03-30T19:58:04.517" Title="How to put adsorbate on the surface by ASE" Tags="|atomic-simulation-environment|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11790" PostTypeId="2" ParentId="11789" CreationDate="2023-10-23T08:37:07.170" Score="5" Body="&lt;p&gt;ASE doesn't support adding multiple adsorbates. If you use the &lt;code&gt;ase.build.add_adsorbate&lt;/code&gt; function multiple times, it will unfortunately add adsorbates to the same pre-defined position. This is a typical situation where you may consider using &lt;a href=&quot;https://asm-dtu.gitlab.io/acat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ACAT&lt;/a&gt;. For your example, this can be simply achieved by the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import surface&#xA;from ase.visualize import view&#xA;from acat.build.adlayer import max_dist_coverage_pattern as mdcp&#xA;from acat.settings import site_heights&#xA;&#xA;# Create the copper surface&#xA;slab = surface('Cu', (1, 1, 1), 4)&#xA;slab = slab.repeat((4, 4, 1))&#xA;slab.center(vacuum=10, axis=2)&#xA;# Add more heights to the CHOO*&#xA;heights = {k: v+0.5 for k, v in site_heights.items()}&#xA;# Generate a random surface coverage pattern with 10 CHOO*&#xA;atoms = mdcp(slab, adsorbate_species='CHOO', coverage=10/64,&#xA;             surface='fcc111', heights=heights)&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Cjm2S.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Cjm2S.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now if you want to rotate the bidentate adsorbates, you can use ASE-GUI to do that, or if you want completely random generation, including the rotation of multidentate adsorbate species, you can use &lt;a href=&quot;https://asm-dtu.gitlab.io/acat/build.html#the-randompatterngenerator-class&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;acat.build.RandomPatternGenerator&lt;/code&gt;&lt;/a&gt;. It also allows you to specify which sites are not allowed to adsorb, and the minimum distance between two adsorbates. Below is an example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from ase.build import surface&#xA;from ase.visualize import view&#xA;from acat.build.adlayer import RandomPatternGenerator as RPG&#xA;from acat.settings import site_heights&#xA;&#xA;# Create the copper surface&#xA;slab = surface('Cu', (1, 1, 1), 4)&#xA;slab = slab.repeat((4, 4, 1))&#xA;slab.center(vacuum=10, axis=2)&#xA;# Add more heights to the CHOO*&#xA;heights = {k: v+0.5 for k, v in site_heights.items()}&#xA;gen = RPG(slab, adsorbate_species='CHOO',&#xA;          min_adsorbate_distance=1.5,&#xA;          surface='fcc111',&#xA;          heights=heights,&#xA;          species_forbidden_sites={'CHOO': ['ontop','bridge']},&#xA;          trajectory='Cu_111_10CHOO.traj')&#xA;gen.run(num_gen=1, action='add', num_act=10)&#xA;atoms = read('Cu_111_10CHOO.traj')&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/dXgPw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dXgPw.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Disclaimer&lt;/strong&gt;: I am the developer of ACAT.&lt;/p&gt;&#xA;" OwnerUserId="3770" LastEditorUserId="3770" LastEditDate="2023-11-03T08:50:46.633" LastActivityDate="2023-11-03T08:50:46.633" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11791" PostTypeId="1" CreationDate="2023-10-23T13:44:05.270" Score="3" ViewCount="40" Body="&lt;p&gt;I want to implement building the Miller indeces in my program Chemcaft. Currently I need to understand more the computations with periodic boundary conditions (PBC) needed for crystallographers.&#xA;The crystallography data is usually presented as a set of fractional coordinates which are recounted to Cartesian ones. In the fractional coordinates, each cell of a crystal is a cube, e.g. the atoms in molecule belonging to the first cell have the coordinates from 0.0 to 1.0. Some real crystals have cubic cells too, e.g. NaCl:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fl3xx.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fl3xx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;PBCs mean that the atoms with e.g. fractional coordinates (0.0;0.0;0.0) and (1.0;0.0;0.0) are equivalent. PBCs in crystals are specified by three lattice vectors A, B, C; e.g. for NaCl above these vectors are three orthogonal vectors with length 5.4533 Angs each (this also mean that the crystallography parameters are: a=5.4533, b=5.4533, c=5.4533, alpha=90, beta=90, gamma=90). At the same time, for each crystal, in fact there must be an unlimited numbers of possible lattice vectors. This can be illustrated by a 2-d example:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kyFw1.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kyFw1.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here the trivial PBC parameters are (1.0; 0.0) and (0.0;1.0), but also we can build the lattice vectors (3.0; -1.0) and (1.0; 3.0), which describe the same crystal.&lt;/p&gt;&#xA;&lt;p&gt;As far as I understand, the Miller indeces are three integer numbers, e.g. 1 1 1, which mean that the new vector C will be (1.0; 1.0; 1.0) in fractional coordinates. My question is, how to build the A and B vectors if we know C. This is similar to the 2d task above, but evidently more difficult.&lt;/p&gt;&#xA;&lt;p&gt;As far as I understand, the A and B vectors can be built in different ways; they must be orthogonal to C, maybe to each other too, but they still can be rotated along the C vector. And they must be still integers, if I understand correctly, and they must define the same crystal as it was. This can be illustrated by the 2d picture above – if the first lattice vector A=(3.0; -1.0), the second can be only B=(1.0; 3.0) to keep the same crystal.&lt;/p&gt;&#xA;&lt;p&gt;So how can these integers A and B (3 digits for each) be obtained, if we know C?&lt;/p&gt;&#xA;&lt;p&gt;The new values of A, B, C in terms of old (9 numbers) can be entered in the window “Redefine lattice” in Materials Studio program, I have implemented the same in Chemcraft. I suppose, to build the Miller index 1 1 1, we should specify these lattice redefinition parameters:&lt;/p&gt;&#xA;&lt;p&gt;A: 0 1 -1&lt;/p&gt;&#xA;&lt;p&gt;B: -1 1 0&lt;/p&gt;&#xA;&lt;p&gt;C: 1 1 1&lt;/p&gt;&#xA;&lt;p&gt;With these parameters, we transform this cell&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/9aiAY.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9aiAY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Into this cell&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eD22a.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eD22a.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Is this correct? And is it correct that the A and B vectors are not orthogonal to each other (though they are orthogonal to C)?&lt;/p&gt;&#xA;" OwnerUserId="3745" LastActivityDate="2023-10-23T13:44:05.270" Title="Miller indices and periodic boundary conditions" Tags="|crystallography|periodic-boundary-conditions|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11792" PostTypeId="1" CreationDate="2023-10-23T15:52:24.753" Score="3" ViewCount="45" Body="&lt;p&gt;i did run docking simulation between two proteins on HADDOCK server&#xA;but now i want to run a simulation of complex (protein+ligand and protein) is it possible with HADDOCK and how can i use it&#xA;best regards&lt;/p&gt;&#xA;" OwnerUserId="8186" LastActivityDate="2023-10-23T15:52:24.753" Title="Running molecular docking simulation between two proteins" Tags="|molecular-dynamics|computational-chemistry|molecular-modeling|software-recommendations|docking|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11793" PostTypeId="1" CreationDate="2023-10-23T22:16:24.640" Score="5" ViewCount="52" Body="&lt;p&gt;In &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/unauth&quot; rel=&quot;noreferrer&quot;&gt;this review&lt;/a&gt;, the authors present several schemes to calculate various quantities like single-ion anisotropy, DMI, and anisotropic exchange J using DFT. For instance, the DMI term in the y-direction &lt;span class=&quot;math-container&quot;&gt;$D_y$&lt;/span&gt; is calculated as follows (extracted from the appendix):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/dRsgj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/dRsgj.png&quot; alt=&quot;Source: https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/unauth&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, I could not find any literature on how to go about calculating the anisotropic J terms like &lt;span class=&quot;math-container&quot;&gt;$J_{xy}, J_{xz}, J_{yz}, J_{yx}, ...$&lt;/span&gt;. The review &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/unauth&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; gives schema for calculating the diagonal elements &lt;span class=&quot;math-container&quot;&gt;$J_{xx}, J_{yy}, J_{zz}$&lt;/span&gt;, but not the others.&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://browse.arxiv.org/pdf/2002.10861.pdf&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt;, the authors give a scheme for &lt;span class=&quot;math-container&quot;&gt;$J_{xz}$&lt;/span&gt; (below eq. 4). But that is basically the same as what &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/unauth&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt; gives for &lt;span class=&quot;math-container&quot;&gt;$D_y$&lt;/span&gt;. I don't think this should be the case.&lt;/p&gt;&#xA;&lt;p&gt;So, would someone mind clarifying how I could go about calculating these non-diagonal anisotropic J.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;strong&gt;EDIT: I missed that &lt;a href=&quot;https://browse.arxiv.org/pdf/2002.10861.pdf&quot; rel=&quot;noreferrer&quot;&gt;3&lt;/a&gt; states that &lt;span class=&quot;math-container&quot;&gt;$D_y=J_{xz}=-J_{zx}$&lt;/span&gt; if the off-diagonal terms are anti-symmetric. But this does not make sense to me. So, if the scheme in that paper is indeed correct, I don't understand why the anisotropic J are the same as DMI up to sign, at least for one block of the anisotropic J matrix...&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2023-10-23T23:19:15.280" LastActivityDate="2023-10-23T23:19:15.280" Title="How to calculate anisotropic exchange J $J_{xy}, J_{xz}, J_{yz}, J_{yx}, ...$ using 4-state mapping and DFT?" Tags="|density-functional-theory|vasp|quantum-espresso|magnetism|algorithms|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11794" PostTypeId="1" AcceptedAnswerId="11795" CreationDate="2023-10-23T23:51:16.180" Score="5" ViewCount="386" Body="&lt;p&gt;I'm trying to convert .xyz to .sdf with Open Babel on Ubuntu 22.04, but I am getting an error message &amp;quot;Cannot open orca.sdf&amp;quot;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;obabel &amp;quot;orca.xyz&amp;quot; -osdf orca.sdf&#xA;orca&#xA; OpenBabel10232319413D&#xA;...&#xA;&lt;span class=&quot;math-container&quot;&gt;$$$$&lt;/span&gt;&#xA;==============================&#xA;*** Open Babel Error  in OpenAndSetFormat&#xA;  Cannot open orca.sdf&#xA;1 molecule converted&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The molecule is in the output, so it is reading for sure. But some issue with write/conversion.&lt;/p&gt;&#xA;&lt;p&gt;The input and output files are in the same directory. I tried giving permissions to all with &lt;code&gt;chmod -R 777 /path/to/directory&lt;/code&gt; but it didn't stop the error.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ls -l&#xA;total 3760&#xA;-rwxrwxrwx 1 frank frank 3843856 Oct 23 19:18 orca.out&#xA;-rwxrwxrwx 1 frank frank    1845 Oct 23 19:20 orca.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I'm in a Conda environment. I tried &lt;code&gt;echo $BABEL_DATADIR&lt;/code&gt; but it was not set strangely. So I set it manually with &lt;code&gt;export BABEL_DATADIR=$CONDA_PREFIX/share/openbabel/3.1.0&lt;/code&gt;, but this also did not help.&lt;/p&gt;&#xA;&lt;p&gt;I also tried this command, but it did not help:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;conda update -c conda-forge openbabel&#xA;Retrieving notices: ...working... done&#xA;Channels:&#xA; - conda-forge&#xA; - defaults&#xA; - conda-forge/label/libint_dev&#xA; - pyscf&#xA;Platform: linux-64&#xA;Collecting package metadata (repodata.json): done&#xA;Solving environment: done&#xA;&#xA;# All requested packages already installed.&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8187" LastActivityDate="2023-10-24T02:41:12.767" Title="obabel error OpenAndSetFormat Cannot open" Tags="|openbabel|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11795" PostTypeId="2" ParentId="11794" CreationDate="2023-10-24T02:41:12.767" Score="6" Body="&lt;p&gt;The &lt;code&gt;obabel&lt;/code&gt; program doesn't have the same semantics as &lt;code&gt;babel&lt;/code&gt; because it was becoming hard to parse all the command line options.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;If you want to specify an output file, use &lt;code&gt;-O orca.sdf&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;If you want to specify an output format, use &lt;code&gt;-osdf&lt;/code&gt; (e.g., output to &lt;code&gt;stdout&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;You can of course combine them, for example if you want to specify a filename that has a different extension (e.g. &lt;code&gt;-O orca.inp -oorcainp&lt;/code&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Since you didn't specify &lt;code&gt;-O&lt;/code&gt;, the &lt;code&gt;orca.sdf&lt;/code&gt; is assumed to be another input file (e.g., a batch operation). So &lt;code&gt;obabel&lt;/code&gt; is confused because you didn't set an output file.&lt;/p&gt;&#xA;&lt;p&gt;See &lt;a href=&quot;https://open-babel.readthedocs.io/en/latest/Command-line_tools/babel.html&quot; rel=&quot;noreferrer&quot;&gt;https://open-babel.readthedocs.io/en/latest/Command-line_tools/babel.html&lt;/a&gt; for more details.&lt;/p&gt;&#xA;&lt;p&gt;FYI - there's an Open Babel mailing list / forum for more help and suggestions.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-10-24T02:41:12.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11797" PostTypeId="1" AcceptedAnswerId="11798" CreationDate="2023-10-24T09:10:21.313" Score="4" ViewCount="211" Body="&lt;p&gt;I want to use a &lt;code&gt;FrechetCellFilter&lt;/code&gt; into a MD simulation with ASE to make sure both the atomic forces and unit cell are simultaneously minimised.&lt;/p&gt;&#xA;&lt;p&gt;I encounter a &lt;code&gt;shape mismatch&lt;/code&gt; error:&#xA;&lt;code&gt;ValueError: shape mismatch: value array of shape (11,3) could not be broadcast to indexing result of shape (8,3)&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;I perform first a &lt;code&gt;QuasiNewton&lt;/code&gt; optimisation which goes through correctly and then a &lt;code&gt;NPT&lt;/code&gt; relaxation, where the code complains about the filter( &lt;code&gt;len(ecf)=11&lt;/code&gt; ) being broadcasted to the atoms (&lt;code&gt;len(atoms)=8&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Why is the &lt;code&gt;FrechetCellFilter&lt;/code&gt; working for the optimization and not for the NPT run? Please find below the xyz input file, the python script and the output produced.&lt;/p&gt;&#xA;&lt;p&gt;Cheers&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;&amp;quot;&amp;quot;Demonstrate use of FrechetCellFilter in molecular dynamics exemple.&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;import ase&#xA;import numpy as np&#xA;from ase.md.npt import NPT&#xA;from asap3 import Atoms, units&#xA;from xtb.ase.calculator import XTB&#xA;from ase.io.trajectory import Trajectory&#xA;from ase.filters import FrechetCellFilter&#xA;from ase.optimize import QuasiNewton&#xA;&#xA;input_file = 'H2_box.xyz'&#xA;cell_size = 2&#xA;&#xA;calculator = XTB(method=&amp;quot;GFN1-xTB&amp;quot;)&#xA;&#xA;atoms = ase.io.read(input_file)&#xA;atoms.rattle(stdev=0.01)&#xA;atoms.set_cell(np.array([cell_size, cell_size, cell_size]))&#xA;atoms.set_pbc(True)&#xA;atoms.center(vacuum=1)&#xA;atoms.set_calculator(calculator)&#xA;&#xA;ecf = FrechetCellFilter(atoms)&#xA;&#xA;print('len(atoms)) :', len(atoms))&#xA;print('len(ecf))   :', len(ecf))&#xA;&#xA;qn = QuasiNewton(ecf)&#xA;traj = Trajectory('full.traj', 'w', atoms)&#xA;qn.attach(traj, interval=10)&#xA;qn.run(fmax=0.5)&#xA;&#xA;print('len(atoms)) :', len(atoms))&#xA;print('len(ecf))   :', len(ecf))&#xA;&#xA;&#xA;print('---- NPT begins ----')&#xA;dyn = NPT(&#xA;    ecf,&#xA;    timestep=0.1 * units.fs,&#xA;    temperature_K=300,&#xA;    externalstress=0.000101325 * units.GPa,&#xA;    trajectory=traj,&#xA;    logfile='NPT.log'&#xA;    )&#xA;&#xA;dyn.attach(traj.write, interval=10)&#xA;dyn.run(50)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;len(atoms)) : 8&#xA;len(ecf))   : 11&#xA;                Step[ FC]     Time          Energy          fmax&#xA;BFGSLineSearch:    0[  0] 09:39:12     -108.889007        6.1586&#xA;BFGSLineSearch:    1[  2] 09:39:13     -109.473179        1.1762&#xA;BFGSLineSearch:    2[  3] 09:39:13     -109.623021        2.2571&#xA;BFGSLineSearch:    3[  5] 09:39:13     -110.469132        2.7407&#xA;BFGSLineSearch:    4[  7] 09:39:14     -110.635861        2.8123&#xA;BFGSLineSearch:    5[  8] 09:39:14     -110.798278        1.1939&#xA;BFGSLineSearch:    6[ 10] 09:39:15     -110.852617        1.2630&#xA;BFGSLineSearch:    7[ 12] 09:39:15     -110.907418        1.1981&#xA;BFGSLineSearch:    8[ 13] 09:39:16     -110.980643        1.0792&#xA;BFGSLineSearch:    9[ 14] 09:39:16     -111.035826        0.1971&#xA;len(atoms)) : 8&#xA;len(ecf))   : 11&#xA;---- NPT begins ----&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/Users/marcodigennaro/WORK/TME/PGEL/ASE_tutorials/FrechetCellFilter.py&amp;quot;, line 40, in &amp;lt;module&amp;gt;&#xA;    dyn = NPT(&#xA;          ^^^^&#xA;  File &amp;quot;/Users/marcodigennaro/WORK/external_packages/ase/ase/md/npt.py&amp;quot;, line 149, in __init__&#xA;    MolecularDynamics.__init__(self, atoms, timestep, trajectory,&#xA;  File &amp;quot;/Users/marcodigennaro/WORK/external_packages/ase/ase/md/md.py&amp;quot;, line 119, in __init__&#xA;    self.atoms.set_momenta(np.zeros([len(self.atoms), 3]))&#xA;  File &amp;quot;/Users/marcodigennaro/WORK/external_packages/ase/ase/filters.py&amp;quot;, line 94, in set_momenta&#xA;    mom[self.index] = momenta&#xA;    ~~~^^^^^^^^^^^^&#xA;ValueError: shape mismatch: value array of shape (11,3) could not be broadcast to indexing result of shape (8,3)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input file: H2_box.xyz&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;           8&#xA;  Built with Packmol&#xA;  H            0.013589       -0.001149        1.023230&#xA;  H            0.000832        0.011254        0.323456&#xA;  H            0.051896        1.974564        0.714629&#xA;  H            0.370690        1.998602        0.091899&#xA;  H            1.944549        1.995178        2.000676&#xA;  H            1.963944        2.001188        1.300971&#xA;  H            1.933873        0.445614        0.043857&#xA;  H            1.974646        0.077936        0.638122&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-10-25T07:43:18.200" LastActivityDate="2023-10-25T07:43:18.200" Title="ASE: Shape mismatch when using FrechetCellFilter filter" Tags="|molecular-dynamics|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11798" PostTypeId="2" ParentId="11797" CreationDate="2023-10-24T11:22:59.443" Score="5" Body="&lt;p&gt;I think your NPT object expects a plain &lt;code&gt;Atoms&lt;/code&gt; object, and not the &lt;code&gt;Filter&lt;/code&gt; object that you get when doing &lt;code&gt;ecf = FrechetCellFilter(atoms)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;ecf.atoms&lt;/code&gt; will yield the optimized Atoms object without filter, that should work.&lt;/p&gt;&#xA;&lt;p&gt;Also note that your external stress is 1 eV/AA**3 = 160 GPa.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Note that none of the &lt;code&gt;NPT&lt;/code&gt; classes in ASE implements a &amp;quot;proper&amp;quot; NPT sampling. Just as a word of caution.&lt;/p&gt;&#xA;" OwnerUserId="8192" LastEditorUserId="8192" LastEditDate="2023-10-24T11:24:43.467" LastActivityDate="2023-10-24T11:24:43.467" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11799" PostTypeId="2" ParentId="11783" CreationDate="2023-10-24T11:31:01.037" Score="2" Body="&lt;p&gt;I assume the problem has to do with the fact that the long-range Coulomb interaction looks different in 2D than it does in 3D. Dimensionality enters in Fourier space and yields a different asymptotic behavior for q --&amp;gt; 0. See Eq. (28) and (29) in&#xA;&lt;a href=&quot;https://www.nature.com/articles/s41524-022-00920-6&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.nature.com/articles/s41524-022-00920-6&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;Note that this answer is for phonopy. I am not familiar with the DFPT implementation in VASP and how long-range polar corrections are included there.&lt;/p&gt;&#xA;" OwnerUserId="8192" LastActivityDate="2023-10-24T11:31:01.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11800" PostTypeId="2" ParentId="10893" CreationDate="2023-10-24T11:44:45.220" Score="2" Body="&lt;p&gt;i) If you do &lt;em&gt;not&lt;/em&gt; want to relax your unit cell dimension, do &lt;em&gt;not&lt;/em&gt; use the &lt;code&gt;UnitCellFilter&lt;/code&gt; or equivalent.&lt;/p&gt;&#xA;&lt;p&gt;ii) I think you are looking for &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/constraints.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;the &lt;code&gt;constraints&lt;/code&gt; module&lt;/a&gt; to fix positions. See also &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/constraints.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;the docs.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8192" LastActivityDate="2023-10-24T11:44:45.220" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11801" PostTypeId="2" ParentId="11763" CreationDate="2023-10-24T12:06:03.350" Score="1" Body="&lt;p&gt;I can somewhat explain it but I agree that the literature is very frustrating to read. Basconi and Shirts have the modified time constant in their 2013 paper&lt;sup&gt;1&lt;/sup&gt; but only cite Berendsen's 1984 paper, which does not seem to make the same claim. I have not located the claim in any paper in between -- but it makes sense to me, after quite a lot of thought.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Imagine a canonical ensemble trajectory for some system at some temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt;, which has average total energy &lt;span class=&quot;math-container&quot;&gt;$\bar{E}$&lt;/span&gt;, average kinetic energy &lt;span class=&quot;math-container&quot;&gt;$\bar{K}$&lt;/span&gt; and average potential energy &lt;span class=&quot;math-container&quot;&gt;$\bar{U}$&lt;/span&gt;. (In the canonical ensemble, heat is always exchanged with a bath, and all three values have varying instantaneous values.)&lt;/p&gt;&#xA;&lt;p&gt;Now imagine a microcanonical ensemble trajectory for the same system, with a conserved energy equal to the canonical average: &lt;span class=&quot;math-container&quot;&gt;$E(t) = \bar{E} = $&lt;/span&gt; some constant. To the extent that thermodynamic equivalence is valid, the microcanonical averages of the kinetic and potential energies &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; must be same as their canonical averages. But their instantaneous &lt;em&gt;fluctuations and correlations&lt;/em&gt; will be different. In particular, the trajectory will always be in one of two conditions:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Instantaneously &lt;span class=&quot;math-container&quot;&gt;$K &amp;gt; \bar{K}$&lt;/span&gt; &lt;em&gt;and&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$U &amp;lt; \bar{U}$&lt;/span&gt; -- the system is kinetically &amp;quot;hot&amp;quot; and configurationally &amp;quot;cool&amp;quot;, or&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Instantaneously &lt;span class=&quot;math-container&quot;&gt;$K &amp;lt; \bar{K}$&lt;/span&gt; &lt;em&gt;and&lt;/em&gt; &lt;span class=&quot;math-container&quot;&gt;$U &amp;gt; \bar{U}$&lt;/span&gt; -- the system is kinetically &amp;quot;cool&amp;quot; and configurationally &amp;quot;hot&amp;quot;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Finally, consider a trajectory under Berendsen thermostatting, followed for a short enough time that it remains similar to a corresponding microcanonical trajectory. Suppose case 1 applies, and the system is kinetically &amp;quot;cool&amp;quot;. Then the Berendsen thermostat will pump &lt;em&gt;in&lt;/em&gt; kinetic energy -- at the same time that the system is configurationally &amp;quot;hot&amp;quot; and due to cool down! Conversely, when the system is kinetically &amp;quot;hot&amp;quot;, the Berendsen thermostat pumps &lt;em&gt;out&lt;/em&gt; energy, fighting a &amp;quot;cool&amp;quot; configuration.&lt;/p&gt;&#xA;&lt;p&gt;And that's why the Berendsen time constant encompasses the entire systemic heat capacity, not just the kinetic.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As far as I can tell this is unique to the Berendsen thermostat because of its first-order coupling to the kinetic temperature -- that is, it adds to the kinetic energy's first derivative: &lt;span class=&quot;math-container&quot;&gt;$\dot{K} \mapsto \dot{K} - \alpha^2 (K - K_{\text{goal}})$&lt;/span&gt;. Other thermostats happen to avoid this in some way. The isokinetic thermostats (that simply &lt;em&gt;force&lt;/em&gt; the kinetic energy to be exactly &amp;quot;right&amp;quot; every step) do not have a &amp;quot;timescale&amp;quot; to speak of. Stochastic thermostats have a random term that decorrelates the thermostat energy flow from the kinetic temperature.&lt;/p&gt;&#xA;&lt;p&gt;And the Nose-Hoover thermostats add second-order coupling instead of first-order coupling (&lt;span class=&quot;math-container&quot;&gt;$\ddot{K} \mapsto \ddot{K} - \alpha^2 (K-K_{\text{goal}})$&lt;/span&gt;), so their timescale is &lt;em&gt;really&lt;/em&gt; controlled by the &amp;quot;kinetic&amp;quot; heat capacity (&lt;span class=&quot;math-container&quot;&gt;$N_{\text{dof}}k_BT/2$&lt;/span&gt;) rather than the overall heat capacity. The Nose-Hoover thermostats effectively add &amp;quot;auxiliary variables&amp;quot; to the system, whose distribution functions really are appropriately harmonic&lt;sup&gt;2&lt;/sup&gt;. So as far as I can tell, it's not just the thermostat's energy eventually &amp;quot;flowing&amp;quot; into the configurational temperature -- it's about how those fluctuations &lt;em&gt;correlate&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Basconi and Shirts, &lt;a href=&quot;https://pubs.acs.org/doi/epdf/10.1021/ct400109a&quot; rel=&quot;nofollow noreferrer&quot;&gt;JCTC 2013, 9, 7, 2887–2899&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt; Bernhardt and Petersen, &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2022/CP/D1CP05316G&quot; rel=&quot;nofollow noreferrer&quot;&gt;PCCP 2022, 24, 6383-6392&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-10-24T12:06:03.350" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11802" PostTypeId="1" AcceptedAnswerId="11829" CreationDate="2023-10-24T14:16:22.490" Score="4" ViewCount="128" Body="&lt;p&gt;what is the best way to save and load a psi4 molecule? I tried pickle/dill but they both failed. I see a feature to save as xyz, but I'm not seeing a function to load as xyz and I'm not sure if save xyz also saves the energy and charges etc.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import psi4&#xA;&#xA;# Define the molecular geometry using a string&#xA;h2_geometry = &amp;quot;&amp;quot;&amp;quot;&#xA;H 0.0 0.0 0.0&#xA;H 0.0 0.0 0.74&#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;# Create the molecule object&#xA;h2_molecule = psi4.geometry(h2_geometry)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;pickle_file_path = &amp;quot;psi4_mol.pkl&amp;quot;&#xA;with open(pickle_file_path, 'wb') as file:&#xA;    pickle.dump(h2_molecule, file)&#xA;&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 2, in &amp;lt;module&amp;gt;&#xA;TypeError: cannot pickle 'psi4.core.Molecule' object&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also tried dill:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;with open(pickle_file_path, 'wb') as file:&#xA;    dill.dump(h2_molecule, file)&#xA;&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 2, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;lib/python3.11/site-packages/dill/_dill.py&amp;quot;, line 250, in dump&#xA;    Pickler(file, protocol, **_kwds).dump(obj)&#xA;  File &amp;quot;lib/python3.11/site-packages/dill/_dill.py&amp;quot;, line 418, in dump&#xA;    StockPickler.dump(self, obj)&#xA;  File &amp;quot;lib/python3.11/pickle.py&amp;quot;, line 487, in dump&#xA;    self.save(obj)&#xA;  File &amp;quot;lib/python3.11/site-packages/dill/_dill.py&amp;quot;, line 412, in save&#xA;    StockPickler.save(self, obj, save_persistent_id)&#xA;  File &amp;quot;lib/python3.11/pickle.py&amp;quot;, line 560, in save&#xA;    f(self, obj)  # Call unbound method with explicit self&#xA;    ^^^^^^^^^^^^&#xA;  File &amp;quot;lib/python3.11/pickle.py&amp;quot;, line 887, in save_tuple&#xA;    save(element)&#xA;  File &amp;quot;lib/python3.11/site-packages/dill/_dill.py&amp;quot;, line 412, in save&#xA;    StockPickler.save(self, obj, save_persistent_id)&#xA;  File &amp;quot;lib/python3.11/pickle.py&amp;quot;, line 578, in save&#xA;    rv = reduce(self.proto)&#xA;         ^^^^^^^^^^^^^^^^^^&#xA;TypeError: cannot pickle 'psi4.core.Molecule' object&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8187" LastActivityDate="2023-11-01T20:08:44.743" Title="What is the best way to save a psi4 molecule object in Python?" Tags="|python|psi4|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11803" PostTypeId="1" AcceptedAnswerId="11919" CreationDate="2023-10-24T14:33:57.843" Score="5" ViewCount="96" Body="&lt;p&gt;I am currently learning to perform calculations on solids and am attempting to manually optimize the size of a face-centered cubic (FCC) cell of Nickel (Ni) using SIESTA (v. 4.1.5) with the Perdew-Burke-Ernzerhof (PBE) functional. My approach involves conducting single point energy calculations while varying the lattice constant, with the coordinates of the Ni atoms kept constant by expressing them relative to the lattice constant.&lt;/p&gt;&#xA;&lt;p&gt;I have previously accomplished this task using Quantum-Espresso, but I am encountering difficulties with SIESTA. Specifically, the &lt;code&gt;LatticeConstant&lt;/code&gt; must be close to 3.52 Å at the energy minimum, but my results show it is close to 3.7 Å.&lt;/p&gt;&#xA;&lt;p&gt;As a novice in these types of calculations and a first-time user of SIESTA, I am unsure whether my difficulties stem from a conceptual misunderstanding or incorrect software usage.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Additional data:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The pseudopotential I used is from &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S2352340914000353?via%3Dihub&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; source.&lt;/li&gt;&#xA;&lt;li&gt;I experimented with different &lt;code&gt;Mesh.Cutoff&lt;/code&gt; values to achieve nearly converged results.&lt;/li&gt;&#xA;&lt;li&gt;The same trend is observed across different basis sets, ranging from SZ to DZP.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Following the user manual, I wrote the following input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SystemName          NiCell&#xA;SystemLabel         NiCell&#xA;&#xA;NumberOfAtoms       4&#xA;NumberOfSpecies     1&#xA;&#xA;%block ChemicalSpeciesLabel&#xA; 1  28  Ni&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;XC.Functional GGA&#xA;XC.Authors PBE&#xA;&#xA;PAO.BasisSize DZP&#xA;Mesh.Cutoff 400 Ry&#xA;&#xA;DM.InitSpin.AF FALSE&#xA;Spin polarized&#xA;&#xA;LatticeConstant 3.52 Ang&#xA;%block LatticeVectors&#xA;   1.0  0.0  0.0&#xA;   0.0  1.0  0.0&#xA;   0.0  0.0  1.0&#xA;%endblock LatticeVectors&#xA;&#xA;AtomicCoordinatesFormat ScaledCartesian&#xA;# ScaledCartesian: x y z coords in units of LatticeConstant&#xA;&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;  0.0 0.0 0.0  1&#xA;  0.0 0.5 0.5  1&#xA;  0.5 0.0 0.5  1&#xA;  0.5 0.5 0.0  1&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;SCF.Mixer.Weight 0.02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any guidance or suggestions to resolve this issue would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="522" LastActivityDate="2023-11-17T15:59:36.520" Title="Why am I getting a wrong lattice constant from these SIESTA calculations?" Tags="|crystallography|siesta|pseudopotentials|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11804" PostTypeId="1" CreationDate="2023-10-24T15:49:37.043" Score="3" ViewCount="118" Body="&lt;p&gt;How to set up a molecular dynamics (MD) simulation for the adsorption of naphthalene on graphene oxide sheets using GROMACS?&lt;/p&gt;&#xA;" OwnerUserId="8195" LastEditorUserId="24" LastEditDate="2023-10-25T00:28:39.487" LastActivityDate="2023-10-25T12:10:04.197" Title="Adsorption of naphthalene on graphene oxide sheets with gmx" Tags="|molecular-dynamics|gromacs|molecular-interactions|adsorption|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11805" PostTypeId="1" CreationDate="2023-10-24T18:53:10.287" Score="2" ViewCount="153" Body="&lt;p&gt;In VASP, one can set the local magnetic moments of each ion in a non-collinear SOC calculation along a certain direction using the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/MAGMOM&quot; rel=&quot;nofollow noreferrer&quot;&gt;MAGMOM&lt;/a&gt;/&lt;a href=&quot;https://www.vasp.at/wiki/index.php/M_CONSTR&quot; rel=&quot;nofollow noreferrer&quot;&gt;M_CONSTR&lt;/a&gt; tags. The manual linked to states that these local magnetic moments should be given in Cartesian coordinates for each ion (e.g., &lt;span class=&quot;math-container&quot;&gt;$M_{1x}, M_{1y}, M_{1z}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Let's say I have a triangular lattice as visualized in VESTA below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/C1emS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/C1emS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I calculate exchange J anisotropic couplings using &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2013/dt/c2dt31662e/&quot; rel=&quot;nofollow noreferrer&quot;&gt;the 4-state method&lt;/a&gt;, I have to set the magnetism along different directions. My question is: I want to calculate the exchange couplings for the pair of sites highlighted in blue. For this, how do I define MAGMOM/M_CONSTR? This bond is in the &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt; direction (red arrow). How do I define MAGMOM/M_CONSTR to have the code set the magnetic moment along this red arrow direction? Naively, I would have done MAGMOM = 0 1 0, but if MAGMOM/M_CONSTR uses Cartesian coordinates, wouldn't this set the direction along the vertical/orange arrow? Or is this not the case? I could not find any clarifying information in the VASP documentation (unless I missed something).&#xA;I think it would make most sense if I set MAGMOM = 0 1 0 for this, but I am not sure whether there are any subtleties here, and whether I should have instead used MAGMOM = &lt;span class=&quot;math-container&quot;&gt;$-0.5$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$(\sqrt{3}/2)$&lt;/span&gt; &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; (i.e. the unit (1 0 0) vector rotated 120 degrees counterclockwise).&lt;/p&gt;&#xA;&lt;p&gt;Is there anything I can do to check which direction exactly the VASP code chooses? The OUTCAR file can give &amp;quot;magnetixation (x)&amp;quot; etc, but I still don't know what axis frame it uses.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate any clarification.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="1766" LastEditDate="2023-10-24T19:01:11.310" LastActivityDate="2023-10-24T19:01:11.310" Title="Clarifying local magnetic moment axes in VASP: cartesian vs crystal (for MAGMOM/M_CONSTR)" Tags="|density-functional-theory|vasp|quantum-mechanics|magnetism|vesta|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11806" PostTypeId="1" CreationDate="2023-10-24T20:39:57.057" Score="7" ViewCount="94" Body="&lt;p&gt;I am new to density functional theory. My goal is to calculate magnetic anisotropy energy using the force theorem. For that, I have been told that one can run a self-consistent calculation with some magnetic moment orientation, and then using the same charge density, calculate (using a non-self consistent calculation) the energy of a different magnetic orientation. The difference between these two energies can yield the magnetic anisotropy energy.&lt;/p&gt;&#xA;&lt;p&gt;I also heard that the latter is called a &amp;quot;single-shot&amp;quot; calculation as it does not have to go through the self-consistent iteration procedure. Can you kindly comment on whether my understanding here is correct or not?&lt;/p&gt;&#xA;&lt;p&gt;Please help. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="8129" LastActivityDate="2023-10-30T17:35:05.380" Title="What is the difference between non self consisent calculation and single-shot calculation?" Tags="|density-functional-theory|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11807" PostTypeId="2" ParentId="11804" CreationDate="2023-10-24T20:44:50.583" Score="2" Body="&lt;p&gt;There are a couple of strategies that I know of in the literature.&#xA;The first one is the so-called chemical vapour deposition. It is fairly easy to script, you can find details on the procedure &lt;a href=&quot;https://doi.org/10.1002/adma.201101652&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this paper&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The other strategy I have read consists of implementing a solvent evaporation scheme. Details to be found &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.4.075405&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this paper&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="7726" LastActivityDate="2023-10-24T20:44:50.583" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11808" PostTypeId="1" CreationDate="2023-10-24T21:23:18.017" Score="3" ViewCount="58" Body="&lt;p&gt;I am looking to predict properties like the Bulk Modulus, total energy, etc., all from the charge density I have as input (CHGCAR file)&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2023-10-24T21:23:18.017" Title="Are then any material property solvers (from Charge Density) available in python?" Tags="|density-functional-theory|vasp|physical-properties-of-materials|atomic-simulation-environment|atomic-physics|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11809" PostTypeId="1" CreationDate="2023-10-25T03:45:28.547" Score="7" ViewCount="160" Body="&lt;p&gt;I am an experimental chemist interested in anharmonicity—I am particularly interested in how to calculate anharmonic frequencies. The method I have the most experience with is (generalised) second order vibrational perturbation theory (G)VPT2.&lt;/p&gt;&#xA;&lt;p&gt;In most programs where VPT2 is implemented (if not all), the full quadratic (harmonic) and cubic, and semi-quartic force fields are determined. This is because, while &lt;em&gt;all&lt;/em&gt; quadratic and cubic force constants (&lt;span class=&quot;math-container&quot;&gt;$\phi_{ijk}$&lt;/span&gt;) are used to calculate the anharmonicity constants &lt;span class=&quot;math-container&quot;&gt;$x_{ii}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$x_{ij}$&lt;/span&gt;, the only quartic force constants which contribute are &lt;span class=&quot;math-container&quot;&gt;$\phi_{iiii}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi_{iijj}$&lt;/span&gt;.&lt;span class=&quot;math-container&quot;&gt;$^1$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Practically speaking, my understanding of this approach is that, following harmonic frequency calculations for a molecule (where the hessian/second derivatives has/have been calculated analytically), two further hessians are calculated for each vibrational mode to either side of the equilibrium geometry along the vibration's normal coordinate [i.e., 2(2N – 6) additional hessians are calculated]. From the analytical hessians, the cubic and semi-quartic force fields would be calculated numerically.&lt;/p&gt;&#xA;&lt;p&gt;The issue with calculating a semi-quartic force field is that, if one wanted to look at the frequencies of different isotopologues of molecules, a second VPT2 calculation would have to be run; my understanding is that the same force fields could be used if a full quartic force field had been determined initially.&lt;/p&gt;&#xA;&lt;p&gt;So, if I wanted to calculate the &lt;em&gt;full&lt;/em&gt; quartic force field, what additional calculations would need to be run? Would it just be a case of calculating more hessians along the normal coordinates of each vibration, or would implementation of analytical third derivatives be required, or something else entirely?&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Wilson Jr., E. B.; Decius, J. C.; Cross, P. C., &lt;em&gt;Molecular Vibrations&lt;/em&gt;; Dover Publications, Inc.: New York, 1980.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="5" LastEditDate="2023-11-24T13:44:09.370" LastActivityDate="2023-11-24T13:44:09.370" Title="How do you calculate a full quartic force field for anharmonic frequencies?" Tags="|computational-chemistry|quantum-chemistry|vibrations|many-body-perturbation-theory|" AnswerCount="0" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="11810" PostTypeId="1" CreationDate="2023-10-25T08:15:26.887" Score="4" ViewCount="97" Body="&lt;p&gt;I want to see how the volume and pressure of my cell is changing during a MD relaxation in ASE. I used the &lt;code&gt;atom.get_volume()&lt;/code&gt; and &lt;code&gt;atom.get_stress()&lt;/code&gt; to print out the values and figured out that they are not changing. I use a &lt;code&gt;FrechetCellFilter&lt;/code&gt; to make sure the cell stress and atomic forces are minimised simultaneously.&lt;/p&gt;&#xA;&lt;p&gt;Here's an example with a 2x2x2 Ang cell containing 4 molecules of H2, I am using the GFN1-xTB calculator and perform a NVT and NPT calculation.&lt;/p&gt;&#xA;&lt;p&gt;There are a couple of points I can't figure out: why is the stress always a list of zeros? Is there any issue with the calculator? why does the temperature (and the kinetic energy) drop to zero in NPT?&lt;/p&gt;&#xA;&lt;p&gt;Please find below the submission script, the input file and the output.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;p&gt;Submission script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;&amp;quot;&amp;quot; Plot changing structure &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;import ase&#xA;import numpy as np&#xA;from ase.md.npt import NPT&#xA;from ase.md.nvtberendsen import NVTBerendsen&#xA;from asap3 import Atoms, units&#xA;from xtb.ase.calculator import XTB&#xA;from ase.io.trajectory import Trajectory&#xA;from ase.filters import FrechetCellFilter&#xA;&#xA;input_file = 'H2_box.xyz'&#xA;cell_size = 2&#xA;&#xA;calculator = XTB(method=&amp;quot;GFN1-xTB&amp;quot;)&#xA;&#xA;atoms = ase.io.read(input_file)&#xA;atoms.rattle(stdev=0.01)&#xA;atoms.set_cell(np.array([cell_size, cell_size, cell_size]))&#xA;atoms.set_pbc(True)&#xA;atoms.center(vacuum=1)&#xA;atoms.set_calculator(calculator)&#xA;&#xA;ecf = FrechetCellFilter(atoms)&#xA;&#xA;traj_file = 'H2_box.traj'&#xA;traj = Trajectory(traj_file, 'w', atoms)&#xA;&#xA;def printenergy(a=atoms): # store a reference to atoms in the definition.&#xA;    &amp;quot;&amp;quot;&amp;quot;Function to print the potential, kinetic and total energy.&amp;quot;&amp;quot;&amp;quot;&#xA;    epot = a.get_potential_energy() / len(a)&#xA;    ekin = a.get_kinetic_energy() / len(a)&#xA;    vol = a.get_volume()&#xA;    stress = a.get_stress()&#xA;    print(f'Epot = {epot:3.3f}eV, '&#xA;          f'Ekin = {ekin:3.3f}eV, '&#xA;          f'Etot = {epot + ekin:3.3f}eV, '&#xA;          f'T = {ekin / (1.5 * units.kB):3.3f}, '&#xA;          f'Vol = {vol:3.3f}, '&#xA;          f'Stress =  {stress}')&#xA;&#xA;&#xA;print('NVTBerendsen')&#xA;dyn = NVTBerendsen(&#xA;    ecf.atoms,&#xA;    timestep=0.1*units.fs,&#xA;    temperature_K=300,&#xA;    taut=100*units.fs,&#xA;    trajectory=traj_file,&#xA;    logfile='NVT.log',&#xA;    )&#xA;&#xA;dyn.attach(traj.write, interval=10)&#xA;dyn.attach(printenergy, interval=10)&#xA;dyn.run(50)&#xA;&#xA;print('NPT')&#xA;dyn = NPT(&#xA;    ecf.atoms,&#xA;    ttime=1e-4,&#xA;    pfactor=1e-4,&#xA;    timestep=0.1*units.fs,&#xA;    temperature_K=300,&#xA;    externalstress=0.000101325 * units.GPa,&#xA;    trajectory=traj_file,&#xA;    logfile='NPT.log'&#xA;    )&#xA;&#xA;dyn.attach(traj.write, interval=10)&#xA;dyn.attach(printenergy, interval=10)&#xA;dyn.run(50)&#xA;&#xA;traj.close()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NVTBerendsen&#xA;Epot = -13.611eV, Ekin = 0.000eV, Etot = -13.611eV, T = 0.000, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.670eV, Ekin = 0.059eV, Etot = -13.611eV, T = 456.917, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.672eV, Ekin = 0.060eV, Etot = -13.611eV, T = 467.998, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.629eV, Ekin = 0.018eV, Etot = -13.611eV, T = 139.689, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.644eV, Ekin = 0.033eV, Etot = -13.611eV, T = 252.785, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.705eV, Ekin = 0.094eV, Etot = -13.611eV, T = 724.094, Vol = 62.059, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;NPT&#xA;Epot = -13.623eV, Ekin = 0.000eV, Etot = -13.623eV, T = 0.000, Vol = 77.121, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.427eV, Ekin = 0.000eV, Etot = -13.427eV, T = 0.000, Vol = 93.430, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -13.194eV, Ekin = 0.000eV, Etot = -13.194eV, T = 0.000, Vol = 111.016, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -12.951eV, Ekin = 0.000eV, Etot = -12.951eV, T = 0.000, Vol = 129.904, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;Epot = -12.713eV, Ekin = 0.000eV, Etot = -12.713eV, T = 0.000, Vol = 150.113, Stress =  [0. 0. 0. 0. 0. 0.]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input file: H2_box.xyz&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;           8&#xA;  Built with Packmol&#xA;  H            0.013589       -0.001149        1.023230&#xA;  H            0.000832        0.011254        0.323456&#xA;  H            0.051896        1.974564        0.714629&#xA;  H            0.370690        1.998602        0.091899&#xA;  H            1.944549        1.995178        2.000676&#xA;  H            1.963944        2.001188        1.300971&#xA;  H            1.933873        0.445614        0.043857&#xA;  H            1.974646        0.077936        0.638122&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-10-25T09:16:01.053" LastActivityDate="2023-10-25T09:16:01.053" Title="ASE/XTB: zero temperature and stress in MD simulation" Tags="|molecular-dynamics|atomic-simulation-environment|stress-strain|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11811" PostTypeId="2" ParentId="11804" CreationDate="2023-10-25T12:10:04.197" Score="1" Body="&lt;p&gt;The set-up for the MD simulation depends on what you want to observe or what quantities you want to compute. If you want to set-up the MD simulation of the adsorption of a single Naphthalene molecule on graphene-oxide (GO), then it is straightforward. Just have the AA parameters for both molecules and in a box with the GO sheet, insert a molecule of Naphthalene in it. You will see that if you run the simulation for long, the molecule will adsorb onto the surface of GO. So, all you need is the AA parameters for both GO and Napthalene. For that, do some literature search, and see if the GO has been parametrized well enough, and if there are some previous works done with this regard.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-10-25T12:10:04.197" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11812" PostTypeId="1" CreationDate="2023-10-26T08:08:38.597" Score="3" ViewCount="24" Body="&lt;p&gt;How is  reduced coordinates calculated in wannier90? examples 17- 18 , 29&lt;/p&gt;&#xA;" OwnerUserId="7888" LastActivityDate="2023-10-26T08:08:38.597" Title="How to calculate kslice_b2 and kslice_b1 in wannierization?" Tags="|density-functional-theory|quantum-espresso|band-structure|spin-orbit-coupling|wannier90|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11813" PostTypeId="1" CreationDate="2023-10-26T18:56:33.127" Score="5" ViewCount="104" Body="&lt;p&gt;I am trying to visualize the charge density of a crystal through VESTA. However the intersection surface of the isosurface and the boundary turns into blue, which is certainly not included in my settings. Is there a way to turn it off for black-and-white settings? &lt;a href=&quot;https://i.stack.imgur.com/GHMb5.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GHMb5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6953" LastActivityDate="2023-11-02T13:21:57.607" Title="Color of isosurface in charge density visualization" Tags="|crystallography|visualization-software|vesta|charge-density|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11814" PostTypeId="1" CreationDate="2023-10-27T00:38:15.463" Score="3" ViewCount="133" Body="&lt;p&gt;so I'm carrying out the calculations for a glass structure, I've already calculated SCF, NSCF and DOS. However, I still need to calculate the Bands and I'm not very good at writing the scripts to run the account. If anyone here knows how to do it, or can suggest some material that teaches how to do this script, I would be very grateful. This is my .cif file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;#======================================================================&#xA;# CRYSTAL DATA&#xA;#----------------------------------------------------------------------&#xA;data_VESTA_phase_1&#xA;&#xA;_chemical_name_common                  ''&#xA;_cell_length_a                         4.713293&#xA;_cell_length_b                         4.713293&#xA;_cell_length_c                         11.997089&#xA;_cell_angle_alpha                      90.000000&#xA;_cell_angle_beta                       90.000000&#xA;_cell_angle_gamma                      120.000000&#xA;_cell_volume                           230.810423&#xA;_space_group_name_H-M_alt              'P 1'&#xA;_space_group_IT_number                 1&#xA;&#xA;loop_&#xA;_space_group_symop_operation_xyz&#xA;   'x, y, z'&#xA;&#xA;loop_&#xA;   _atom_site_label&#xA;   _atom_site_occupancy&#xA;   _atom_site_fract_x&#xA;   _atom_site_fract_y&#xA;   _atom_site_fract_z&#xA;   _atom_site_adp_type&#xA;   _atom_site_B_iso_or_equiv&#xA;   _atom_site_type_symbol&#xA;   Si0         1.0     0.000000     0.000000     0.500000    Biso  1.000000 Si&#xA;   Si1         1.0     0.000000     0.000000     0.000000    Biso  1.000000 Si&#xA;   Ca2         1.0     0.666667     0.333333     0.379795    Biso  1.000000 Ca&#xA;   P3          1.0     0.333333     0.666667     0.620205    Biso  1.000000 P&#xA;   P4          1.0     0.333333     0.666667     0.879795    Biso  1.000000 P&#xA;   P5          1.0     0.666667     0.333333     0.120205    Biso  1.000000 P&#xA;   O6          1.0     0.265253     0.330328     0.586085    Biso  1.000000 O&#xA;   O7          1.0     0.669672     0.934925     0.586085    Biso  1.000000 O&#xA;   O8          1.0     0.734747     0.669672     0.086085    Biso  1.000000 O&#xA;   O9          1.0     0.330328     0.065075     0.413915    Biso  1.000000 O&#xA;   O10         1.0     0.666667     0.333333     0.250000    Biso  1.000000 O&#xA;   O11         1.0     0.934925     0.265253     0.086085    Biso  1.000000 O&#xA;   O12         1.0     0.669672     0.934925     0.913915    Biso  1.000000 O&#xA;   O13         1.0     0.934925     0.265253     0.413915    Biso  1.000000 O&#xA;   O14         1.0     0.065075     0.734747     0.586085    Biso  1.000000 O&#xA;   O15         1.0     0.330328     0.065075     0.086085    Biso  1.000000 O&#xA;   O16         1.0     0.265253     0.330328     0.913915    Biso  1.000000 O&#xA;   O17         1.0     0.065075     0.734747     0.913915    Biso  1.000000 O&#xA;   O18         1.0     0.734747     0.669672     0.413915    Biso  1.000000 O&#xA;   O19         1.0     0.333333     0.666667     0.750000    Biso  1.000000 O&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is my SCF input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  title='Compound 4:bulk:(Si 2)(Ca)(P 3)(O 14):hP(4):P3 (143):primitive:230.81', &#xA;  calculation='scf', &#xA;  pseudo_dir='./', &#xA;  outdir='./tmp', &#xA;  verbosity='high',&#xA;  tprnfor=.true., &#xA;  tstress=.true., &#xA;  forc_conv_thr=1.0d-4, &#xA;  nstep=100,&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0, nat= 20, ntyp= 4, &#xA;  occupations = 'smearing', smearing = 'gauss', degauss = 1.0d-2,&#xA;  ecutwfc = 50, ecutrho = 500,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Si     28.08550  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Ca     40.07800  Ca.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;P      30.97376  P.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Si            0.0000000000        0.0000000000       -0.0157540426&#xA;O             0.3299136474        0.0545324986        0.0595401725&#xA;O             0.9454675014        0.2753811489        0.0595401725&#xA;O             0.7246188511        0.6700863526        0.0595401725&#xA;P             0.6666670000        0.3333330000        0.0987976560&#xA;O             0.6666670000        0.3333330000        0.2113501434&#xA;Ca            0.6666670000        0.3333330000        0.3706146451&#xA;O             0.1992673103       -0.1108239995        0.4380418511&#xA;O             1.1108239995        0.3100913098        0.4380418511&#xA;O             0.6899086902        0.8007326897        0.4380418511&#xA;Si           -0.0000000000       -0.0000000000        0.5320360071&#xA;O             0.2891646956        0.3289811702        0.6093561073&#xA;O             0.0398164747        0.7108353044        0.6093561073&#xA;O             0.6710188298        0.9601835253        0.6093561073&#xA;P             0.3333330000        0.6666670000        0.6406709519&#xA;O             0.3333330000        0.6666670000        0.7561974923&#xA;P             0.3333330000        0.6666670000        0.8748653332&#xA;O             0.2739498732        0.3264620877        0.9034691403&#xA;O             0.0525122146        0.7260501268        0.9034691403&#xA;O             0.6735379123        0.9474877854        0.9034691403&#xA;K_POINTS {automatic}&#xA;  6 6 2 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="6055" LastEditDate="2024-03-26T17:06:20.003" LastActivityDate="2024-03-26T17:06:20.003" Title="How to create an input file to run band structure calculation in Quantum ESPRESSO?" Tags="|quantum-espresso|band-structure|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11815" PostTypeId="2" ParentId="11814" CreationDate="2023-10-28T14:17:09.057" Score="2" Body="&lt;p&gt;The path I follow in this answer is to first getting the ground state using an SCF calculation, then performing an NSCF (&lt;code&gt;calculation='bands'&lt;/code&gt;) run using appropriate k-path, then &lt;code&gt;bands.x&lt;/code&gt; post-processing, and lastly plotting the results using &lt;code&gt;plotband.x&lt;/code&gt;. Since you already performed an SCF calculation, let's start from step 2.&lt;/p&gt;&#xA;&lt;p&gt;You need to create an input file with the same prefix and with k-point according to your structure. I generated the k-path from the given CIF file using &lt;a href=&quot;https://www.materialscloud.org/work/tools/seekpath&quot; rel=&quot;nofollow noreferrer&quot;&gt;SeeK-path tool&lt;/a&gt;. The suggested K-path is: &lt;code&gt;Γ—M—K—Γ—A—L—H—A|L—M|H—K—H2&lt;/code&gt;. You can use that tool to get further information. Based on the SCF input file you provided, use the first input file provided at the end as your NSCF input. Run your &lt;code&gt;pw.x&lt;/code&gt; executables using that input file depending on the system where you will run.&lt;/p&gt;&#xA;&lt;p&gt;After that, use the second input file provided at the end to do the post-processing. Run your &lt;code&gt;bands.x&lt;/code&gt; executable using this input file. Now, you can plot your output using &lt;code&gt;xmgr&lt;/code&gt;/&lt;code&gt;gnuplot&lt;/code&gt;/&lt;code&gt;plotband.x&lt;/code&gt;/your customized python code. If you want to use &lt;code&gt;plotband.x&lt;/code&gt;, you can simply run that command interactively in the command line and follow the prompt. Otherwise you can use customized python script. One example of such script can be found &lt;a href=&quot;https://github.com/quantumNerd/Quantum-Espresso-Tutorial-2019-Projects/tree/master/tools/plot_band&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;First input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  title='Compound 4:bulk:(Si 2)(Ca)(P 3)(O 14):hP(4):P3 (143):primitive:230.81', &#xA;  calculation='bands', &#xA;  pseudo_dir='./', &#xA;  outdir='./tmp', &#xA;  verbosity='high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0, nat= 20, ntyp= 4, &#xA;  occupations = 'smearing', smearing = 'gauss', degauss = 1.0d-2,&#xA;  ecutwfc = 50, ecutrho = 500,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;Si     28.08550  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Ca     40.07800  Ca.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;P      30.97376  P.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Si            0.0000000000        0.0000000000       -0.0157540426&#xA;O             0.3299136474        0.0545324986        0.0595401725&#xA;O             0.9454675014        0.2753811489        0.0595401725&#xA;O             0.7246188511        0.6700863526        0.0595401725&#xA;P             0.6666670000        0.3333330000        0.0987976560&#xA;O             0.6666670000        0.3333330000        0.2113501434&#xA;Ca            0.6666670000        0.3333330000        0.3706146451&#xA;O             0.1992673103       -0.1108239995        0.4380418511&#xA;O             1.1108239995        0.3100913098        0.4380418511&#xA;O             0.6899086902        0.8007326897        0.4380418511&#xA;Si           -0.0000000000       -0.0000000000        0.5320360071&#xA;O             0.2891646956        0.3289811702        0.6093561073&#xA;O             0.0398164747        0.7108353044        0.6093561073&#xA;O             0.6710188298        0.9601835253        0.6093561073&#xA;P             0.3333330000        0.6666670000        0.6406709519&#xA;O             0.3333330000        0.6666670000        0.7561974923&#xA;P             0.3333330000        0.6666670000        0.8748653332&#xA;O             0.2739498732        0.3264620877        0.9034691403&#xA;O             0.0525122146        0.7260501268        0.9034691403&#xA;O             0.6735379123        0.9474877854        0.9034691403&#xA;&#xA;K_POINTS crystal&#xA;394&#xA; 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  -0.3333333333    -0.3333333333    -0.3333333333 1&#xA;   -0.3333333333    -0.3333333333    -0.2777777778 1&#xA;   -0.3333333333    -0.3333333333    -0.2222222222 1&#xA;   -0.3333333333    -0.3333333333    -0.1666666667 1&#xA;   -0.3333333333    -0.3333333333    -0.1111111111 1&#xA;   -0.3333333333    -0.3333333333    -0.0555555556 1&#xA;   -0.3333333333    -0.3333333333     0.0000000000 1&#xA;   -0.3333333333    -0.3333333333     0.0555555556 1&#xA;   -0.3333333333    -0.3333333333     0.1111111111 1&#xA;   -0.3333333333    -0.3333333333     0.1666666667 1&#xA;   -0.3333333333    -0.3333333333     0.2222222222 1&#xA;   -0.3333333333    -0.3333333333     0.2777777778 1&#xA;   -0.3333333333    -0.3333333333     0.3333333333 1&#xA;   -0.3333333333    -0.3333333333     0.3888888889 1&#xA;   -0.3333333333    -0.3333333333     0.4444444444 1&#xA;   -0.3333333333    -0.3333333333     0.5000000000 1&#xA;&#xA;CELL_PARAMETERS angstrom&#xA;    4.7132930000     0.0000000000     0.0000000000&#xA;   -2.3566465000     4.0818314735     0.0000000000&#xA;    0.0000000000     0.0000000000    11.9970890000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Second input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;BANDS&#xA;    outdir='./tmp'&#xA;    filband='MyBandsData'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-10-28T14:17:09.057" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11816" PostTypeId="1" CreationDate="2023-10-28T15:35:32.540" Score="3" ViewCount="74" Body="&lt;p&gt;In VASP, one can use &lt;a href=&quot;https://www.vasp.at/wiki/index.php/I_CONSTRAINED_M&quot; rel=&quot;nofollow noreferrer&quot;&gt;I_CONSTRAINED_M&lt;/a&gt; to constrain local magnetic moments to a certain direction in SOC calculations. However, this comes at the cost of adding an energy penalty to the total energy. According to the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/I_CONSTRAINED_M&quot; rel=&quot;nofollow noreferrer&quot;&gt;manual&lt;/a&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_{total} = E_0 + E_p,$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$E_0$&lt;/span&gt; is the usual DFT energy, and &lt;span class=&quot;math-container&quot;&gt;$E_p$&lt;/span&gt; represents the penalty.&lt;/p&gt;&#xA;&lt;p&gt;In the OUTCAR file, VASP displays the final energy of the energy. For example:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)&#xA;  ---------------------------------------------------&#xA;  free  energy   TOTEN  =     -1028.40851797 eV&#xA;&#xA;  energy  without entropy=    -1028.40851657  energy(sigma-&amp;gt;0) =    -1028.40851727&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Separately, in the OSZICAR file, we get:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;DAV: 122    -0.102840853816E+04   -0.67812E-07   -0.35816E-08  2076   0.658E-04&#xA;   1 F= -.10284085E+04 E0= -.10284085E+04  d E =-.138799E-05  mag=    13.9005    -0.9568     0.9552&#xA;&#xA; E_p =  0.39341E-04  lambda =  0.900E+01&#xA; ion             lambda*MW_perp&#xA;  1   0.12835E-02   0.15811E-04   0.16821E-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;E_p&lt;/code&gt; is the energy penalty &lt;span class=&quot;math-container&quot;&gt;$E_p$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is simple: Does &lt;span class=&quot;math-container&quot;&gt;$E_{OUTCAR}$&lt;/span&gt;, the energy in OUTCAR (e.g., &lt;code&gt;energy(sigma-&amp;gt;0)&lt;/code&gt;) include &lt;span class=&quot;math-container&quot;&gt;$E_p$&lt;/span&gt;?&lt;/strong&gt; My understanding is that the energy of the system I should use should be: &lt;span class=&quot;math-container&quot;&gt;$ E = E_{OUTCAR} - $&lt;/span&gt;&lt;code&gt;E_p&lt;/code&gt; (as the penalty is added to the total energy). However, to me, it is not clear from the manual whether &lt;span class=&quot;math-container&quot;&gt;$E_{OUTCAR}$&lt;/span&gt; is &lt;span class=&quot;math-container&quot;&gt;$=E_{total}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$={E_0}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;To try and determine the answer myself, I calculated all possibilities for various &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; (which affects &lt;span class=&quot;math-container&quot;&gt;$E_p$&lt;/span&gt;): &lt;span class=&quot;math-container&quot;&gt;$E = E_{OUTCAR}, E = E_{OUTCAR} - $&lt;/span&gt;&lt;code&gt;E_p&lt;/code&gt;, and &lt;span class=&quot;math-container&quot;&gt;$E = E_{OUTCAR} + $&lt;/span&gt;&lt;code&gt;E_p&lt;/code&gt;. My reasoning is that the true energy would be the same for all lambda after properly treating &lt;code&gt;E_p&lt;/code&gt;. But the differences between all three cases for all lambda are very small, making this test inconclusive.&lt;/p&gt;&#xA;&lt;p&gt;So, could someone clarify how exactly VASP incorporates the penalty energy into the calculation output? I still think that &lt;span class=&quot;math-container&quot;&gt;$E = E_{OUTCAR} - $&lt;/span&gt;&lt;code&gt;E_p&lt;/code&gt; makes the most sense, as the manual suggests the output energy already incorporates &lt;span class=&quot;math-container&quot;&gt;$E_p$&lt;/span&gt;. But I did not see it mentioned explicitly.&lt;/p&gt;&#xA;&lt;p&gt;If anyone could verify this for me, I would be very appreciative!&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2023-11-09T02:20:51.620" Title="Does VASP include energy penalty contribution in OUTCAR energy of constrained moment calculation?" Tags="|density-functional-theory|vasp|magnetism|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11817" PostTypeId="1" CreationDate="2023-10-28T15:54:08.847" Score="3" ViewCount="68" Body="&lt;p&gt;My goal is to use a Gaussian Process Regression (GPR) model with the GPyTorch library with the SOAP (smooth overlap of atomic positions) descriptor that can be obtained with the DScribe library.&lt;br /&gt;&#xA;I have generated the SOAP descriptors for my dataset and used a GPR model, which gives very poor results. It seems that the Kernel function I have initially used (the RBF-Kernel) is not suitable in combination with the SOAP descriptor (I can't figure out any other reason for the extremely high prediction error). The authors of the original SOAP paper (&lt;em&gt;Phys. Rev.&lt;/em&gt; B &lt;strong&gt;87&lt;/strong&gt;, 184115) came up with the SOAP kernel that is said to be tailored for the SOAP descriptor as far as I understand:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;K(\rho, \rho') = \left(\frac{\rho\,\rho'}{\sqrt{\rho\rho\,\rho'\rho'}}\right)^{\zeta}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the partial power spectrum vector which is the output of the SOAP descriptor generation.&#xA;&lt;strong&gt;My central question is:&lt;/strong&gt; Are there any libraries in which this kernel is already implemented or does someone have an idea how to implement it in popular GPR libraries like GPyTorch ? I have read a few papers in which the combination of SOAP and GPR is reported and it seems to work quite well (for example &lt;em&gt;Nat. Commun.&lt;/em&gt; &lt;strong&gt;9&lt;/strong&gt;, 4501 (2018)).&lt;/p&gt;&#xA;" OwnerUserId="5646" LastEditorUserId="5646" LastEditDate="2023-10-29T16:07:35.630" LastActivityDate="2023-10-29T16:07:35.630" Title="Using GPyTorch for GPR together with the SOAP-Kernel" Tags="|python|molecular-modeling|machine-learning|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11818" PostTypeId="2" ParentId="10287" CreationDate="2023-10-28T19:43:20.293" Score="4" Body="&lt;p&gt;I am not sure I fully understood your question, but I will  give it a try.&lt;/p&gt;&#xA;&lt;p&gt;The hydrogen molecule in its ground state only contains two electrons of opposite spin, which means that the exchange (Fermi) contribution to the Hamiltonian (and therefore, the wavefunction, which generates the density) of either electron has to exactly cancel the (unphysical) Coulomb contribution to the Hamiltonian  generated by that same electron.&lt;/p&gt;&#xA;&lt;p&gt;That is, you can just take either converged orbital and square it to get the difference in probability density of the Fermi hole, which in turn equals the alpha- or beta- electron density.&lt;/p&gt;&#xA;&lt;p&gt;As for the Coulomb hole, you can take the density difference between the solution of the correlated method and the Hartree-Fock solution, which only treats electron potentials generated by  opposite spin electrons as an average.&lt;/p&gt;&#xA;&lt;p&gt;Depending on how precise you want to be I would choose Full-CI instead of DFT because in F-CI there is a one-to-one correspondence with HF of each Hamiltonian term, whereas DFT approximates and then corrects some of these operators in ways that break the mathematical correspondence. Full-CI for a two-electron system only scales as O(N^4) with the size of the basis set, but even then most calculations for a linear molecule can be cancelled out by symmetry.&lt;/p&gt;&#xA;&lt;p&gt;You can use practically any QC program, as most of them output the AO basis weights for the solution orbitals or densities, and then use your favorite plotting tool (GNUplot, Mathematica, etc.) to visualize it. You might also need the weights and exponents used for the basis set, which you can often get from the program, but can also be found here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.basissetexchange.org/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8222" LastEditorUserId="8222" LastEditDate="2023-10-28T19:47:33.220" LastActivityDate="2023-10-28T19:47:33.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11819" PostTypeId="1" CreationDate="2023-10-29T08:52:58.270" Score="2" ViewCount="71" Body="&lt;p&gt;I've generated a phonon dispersion for BCC lithium using the python api for phonopy. I specified the following q-point path&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;path = [[[0.0, 0, 1.0], [0.5, 0.5, 0.5],[0, 0, 0], [0.0, 0.25, 0.25]]] &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and then run&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonon.run_band_structure(qpoints, path_connections=connections, labels=labels)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After using the utility&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy-bandplot  --gnuplot band.yaml&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I obtain a .plot file for comparison with a QE phonon dispersion. I noticed that I had to scale the phonopy q-vector axis a factor equal to the lattice paramter to match the two up. However, even doing this, I find that the phonopy dispersion abruptly ends before the final q-point segment has completed. I wondered if anyone has tried to do this before and knows how to correctly compare the two?&lt;/p&gt;&#xA;&lt;p&gt;P.S. The q-point path I specify in QE is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   5&#xA;  0.00000000 0.00000000 0.0   40&#xA;  0.0 0.0 1.0   40&#xA;  0.5 0.5 0.5   40&#xA;  0.00000000 0.00000000 0.0   40&#xA;  0.0        0.5    0.5   1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Directly translating this into the phonopy path&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;path = [[[0, 0, 0], [0.0, 0, 1.0], [0.5, 0.5, 0.5],[0, 0, 0], [0.0, 0.5, 0.5]]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;gives totally different results (as if extra segments have been added to the path). I think I'm misunderstanding how phonopy creates its band paths.&lt;/p&gt;&#xA;" OwnerUserId="3985" LastActivityDate="2023-10-29T08:52:58.270" Title="Comparing phonon dispersions generated with phonopy to those generated with Quantum Espresso" Tags="|phonons|phonopy|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11820" PostTypeId="2" ParentId="5034" CreationDate="2023-10-29T15:26:20.993" Score="1" Body="&lt;p&gt;Intuitively I would say that yes of course you can relate the two coordinate systems. But whereas in one of the two, the corresponding eigenvalue-matrix is diagonal {zero values at off-diagonal elements), if you express the other system in it, the eigenvalue-matrix will most likely not be diagonal.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, I think it might only work if you use the Cartesian equivalent of the normal mode vectors, as is often done for transformations.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-10-29T15:26:20.993" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11821" PostTypeId="1" CreationDate="2023-10-29T17:24:59.827" Score="3" ViewCount="44" Body="&lt;p&gt;Intramolecular charge transfer (ICT( occurs from donors to acceptors in molecules. This phenomenon can be observed by visualizing the charge distribution patterns of HOMO and LUMO. While studying D-A systems , I came across two cases:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The HOMO and LUMO are spreading all over the pi skeleton from donor to acceptors.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;The HOMO resides only on the donor fragment, whereas the LUMO is  localized on the acceptor component.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;For case 1, does it means that &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$\pi^*$&lt;/span&gt; transition is accompanied with ICT? For case 2, does it means that HOMO--&amp;gt;LUMO transition is of ICT type only?&#xA;Which of the cases displays the best ICT? Some books or benchmarks would be helpful.&lt;/p&gt;&#xA;" OwnerUserId="5563" LastEditorUserId="7" LastEditDate="2023-10-29T17:50:12.390" LastActivityDate="2023-10-29T17:50:12.390" Title="Difference between pi-pi* transition and intramolecular charge transfer ICT in organic solar cells?" Tags="|computational-chemistry|charge-transfer|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11822" PostTypeId="1" CreationDate="2023-10-29T23:32:12.213" Score="6" ViewCount="144" Body="&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/questions/177229/do-conformations-arise-from-vibrations&quot;&gt;Cross-posted on Chemistry SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I was wondering how a molecule transforms from one conformation into another. Surely, since the conformations are separated by a potential barrier, some activation energy must be required. The energies related to a molecule are translational, rotational, vibrational, and electronic. Out of these, translational and rotational motion do not change the intrinsic coordinates of a molecule, and these won't bring about a conformational change. The electronic transitions are too fast on the conformational time scale. This leaves, at least for an independent molecule, vibration as the only candidate for bringing about conformational transformations. Although collisions may also be considered, my focus is on independent molecules. I tried searching for a relation between conformations and vibrations but couldn't find any relevant results.&lt;/p&gt;&#xA;" OwnerUserId="7205" LastEditorUserId="7205" LastEditDate="2023-11-04T11:49:39.673" LastActivityDate="2023-11-04T11:49:39.673" Title="Do conformations arise from vibrations?" Tags="|vibrations|potential-energy-surface|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11823" PostTypeId="1" AcceptedAnswerId="11840" CreationDate="2023-10-30T07:51:05.250" Score="6" ViewCount="175" Body="&lt;p&gt;Dear Matter Modeling Stack Exchange community,&#xA;I am currently working on calculating the electronic and structural properties of Transition Metal Dichalcogenide (TMD) nanotubes using DFT, with a specific focus on the &lt;strong&gt;1T'-MoTe2&lt;/strong&gt;. I would like to inquire about the best approach and tools available for preparing an input file, such as a &lt;strong&gt;POSCAR&lt;/strong&gt; file, for a nanotube structure derived from the 2D structure of 1T'-MoTe2.&#xA;I have attempted to use the &lt;strong&gt;c2x&lt;/strong&gt; tool &lt;a href=&quot;https://www.c2x.org.uk/nanotube.html&quot; rel=&quot;noreferrer&quot;&gt;https://www.c2x.org.uk/nanotube.html&lt;/a&gt; to generate the nanotube structure. However, I encountered a problem with this approach because the c-axis in 1T'-MoTe2 is not perpendicular to the a-b plane, which is due to the distorted nature of the structure.&#xA;Considering this challenge, I am seeking your guidance on alternative tools or methods that can be employed to construct an accurate nanotube structure starting from the distorted 2D structure of 1T'-MoTe2.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance for your expertise and assistance!&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2023-10-30T10:23:55.100" LastActivityDate="2024-01-05T00:44:34.437" Title="Modeling techniques for simulating the electronic and structural properties of Transition Metal Dichalcogenide nanotubes" Tags="|density-functional-theory|vasp|transition-metals|nanostructures|dichalcogenides|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11824" PostTypeId="1" CreationDate="2023-10-30T13:24:47.570" Score="4" ViewCount="72" Body="&lt;p&gt;I was running a simple CASSCF calculation in PySCF on the TMM biradical. It was a CASSCF (4,4) state averaged calculation where the energies of the first 3 roots were calculated. The simulation output contained the following table.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;** Largest CI components **&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 0   CI coefficient&#xA;  [0 1]                [0 2]                           0.680999601372&#xA;  [0 2]                [0 1]                          -0.680999601372&#xA;  [1 2]                [0 3]                           0.162876965573&#xA;  [0 3]                [1 2]                          -0.162876965573&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 1   CI coefficient&#xA;  [0 1]                [0 1]                           0.521598297554&#xA;  [0 1]                [0 2]                          -0.296126060144&#xA;  [0 1]                [1 2]                          -0.235407708465&#xA;  [0 1]                [0 3]                          -0.106906206218&#xA;  [0 2]                [0 1]                          -0.296126060144&#xA;  [0 2]                [0 2]                          -0.521414937085&#xA;  [0 2]                [1 2]                          -0.133788127011&#xA;  [0 2]                [0 3]                           0.190214831302&#xA;  [1 2]                [0 1]                          -0.235407708465&#xA;  [1 2]                [0 2]                          -0.133788127011&#xA;  [0 3]                [0 1]                          -0.106906206218&#xA;  [0 3]                [0 2]                           0.190214831302&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 2   CI coefficient&#xA;  [0 1]                [0 1]                           0.275144934363&#xA;  [0 1]                [0 2]                           0.518472331429&#xA;  [0 1]                [1 2]                          -0.131745811887&#xA;  [0 1]                [0 3]                           0.201009810870&#xA;  [0 2]                [0 1]                           0.518472331429&#xA;  [0 2]                [0 2]                          -0.313130614232&#xA;  [0 2]                [1 2]                           0.232139108556&#xA;  [0 2]                [0 3]                           0.115309844670&#xA;  [1 2]                [0 1]                          -0.131745811887&#xA;  [1 2]                [0 2]                           0.232139108556&#xA;  [0 3]                [0 1]                           0.201009810870&#xA;  [0 3]                [0 2]                           0.115309844670&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am having trouble making sense of this table. I don't understand how to interpret the alpha and beta occupied orbitals. How can I find the active space configuration from this table?.&lt;/p&gt;&#xA;" OwnerUserId="8236" LastEditorUserId="8236" LastEditDate="2023-11-01T12:15:09.930" LastActivityDate="2023-11-01T12:15:09.930" Title="Table of Largest CI Components in PySCF CASSCF Calculation" Tags="|pyscf|spin|casscf|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11825" PostTypeId="2" ParentId="11753" CreationDate="2023-10-30T17:19:29.730" Score="2" Body="&lt;p&gt;When you dissociate the singlet state of H&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, you need the &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; spatial orbitals to be different. If you use the same initial guess for both spin channels, as what happens when you set both initially to zero (this actually corresponds to the core guess i.e. diagonalization of the one-electron part of the Hamiltonian). In your random guess you clearly see that you have obtained at least two solutions to the SCF equations, which means that the higher-lying one has to be a saddle point solution. The trick is achieving this in a consistent mode. What typically works is starting from a large &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt;, and reading in these orbitals as the initial guess for the calculation for the next largest value of &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; (repeat ad nauseam).&lt;/p&gt;&#xA;&lt;p&gt;The addendum with the rotated guess looks fine; at separation the energy goes to two times the energy of a single atom. You don't get &lt;span class=&quot;math-container&quot;&gt;$-1 E_h$&lt;/span&gt; exactly, since you have basis set truncation error. If you plot the energy relative to that of two isolated atoms, you will see that this interaction energy goes to zero at large distance.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-10-30T17:19:29.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11826" PostTypeId="2" ParentId="11824" CreationDate="2023-10-30T17:24:58.637" Score="2" Body="&lt;p&gt;You have 4 electrons in 4 spatial orbitals. Number the orbitals 0, 1, 2, and 3.&lt;/p&gt;&#xA;&lt;p&gt;Look at the lowest root. It is an open shell singlet. The spatial orbital 0 is doubly occupied, and then you have (12-21)/sqrt(2) as the most important configuration state, followed by (03-12)/sqrt(2).&lt;/p&gt;&#xA;&lt;p&gt;In the first excited state, orbitals 0 and 1 are doubly occupied in the leading determinant, which is the Hartree-Fock state. However, its amplitude is just 0.592, which means that only 0.592^2 ~ 35% of the electron density comes from this determinant.&lt;/p&gt;&#xA;&lt;p&gt;Does this help?&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2023-10-31T16:16:59.833" LastActivityDate="2023-10-31T16:16:59.833" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11827" PostTypeId="2" ParentId="11806" CreationDate="2023-10-30T17:35:05.380" Score="6" Body="&lt;p&gt;&amp;quot;Single shot&amp;quot; can mean different things in electronic structure. It just depends on what is held constant.&lt;/p&gt;&#xA;&lt;p&gt;What you refer to is evaluating the Kohn-Sham energy with fixed spatial orbitals, but for different spin states. This will give you non-variational energies for the other spin states, while the reference spin state is favored as the orbitals are optimal for it.&lt;/p&gt;&#xA;&lt;p&gt;It is also commonly used for the &lt;strong&gt;self-consistent&lt;/strong&gt; evaluation of the electronic energy for a &lt;em&gt;fixed nuclear geometry&lt;/em&gt;. For instance, you might optimize the geometry with a cheaper method like tight-binding density functional theory (DFT), and then run a higher-level calculation like Kohn-Sham DFT on that geometry. In quantum chemistry, one often obtains geometries with DFT and uses more sophisticated (and much more expensive) methods like coupled-cluster theory to obtain reliable total energies for these fixed geometries.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-10-30T17:35:05.380" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11828" PostTypeId="2" ParentId="11768" CreationDate="2023-10-30T17:42:09.953" Score="4" Body="&lt;p&gt;You don't have to write special code for derivative integrals. Since you know that the Cartesian Gaussian basis functions are of the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$ \chi_x = (x-x_0)^l \exp[-\alpha (x-x_0)^2]$&lt;/span&gt; (same for the other directions), you know that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$ \displaystyle \frac {\partial \chi_x} {\partial x_0} = l(x-x_0)^{l-1} \exp[-\alpha (x-x_0)^2] - 2\alpha (x-x_0)^{l+1} \exp[-\alpha (x-x_0)^2]$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This means that the derivative of a function with angular momentum &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt; is a linear combination of functions with angular momentum &lt;span class=&quot;math-container&quot;&gt;$l+1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$l-1$&lt;/span&gt;. You can thereby compute the derivative of any integral by combining the original integrals for different angular momenta.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-10-30T17:42:09.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11829" PostTypeId="2" ParentId="11802" CreationDate="2023-10-30T18:22:35.317" Score="5" Body="&lt;p&gt;If you only need the geometry, molecular charge, and other related quantities, then &lt;code&gt;h2_geometry.to_dict()&lt;/code&gt; is what you want. You can then save the returned &lt;code&gt;dict&lt;/code&gt; with e.g. pickle.&lt;/p&gt;&#xA;&lt;p&gt;If you also want to compute energies and such then save them to file, you want &lt;a href=&quot;https://psicode.org/psi4manual/master/api/psi4.core.Wavefunction.html#psi4.core.Wavefunction.to_file&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;wfn.to_file&lt;/code&gt;&lt;/a&gt; and the partner function for loading, &lt;a href=&quot;https://psicode.org/psi4manual/master/api/psi4.core.Wavefunction.html#psi4.core.Wavefunction.from_file&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;wfn.from_file&lt;/code&gt;&lt;/a&gt;. These functions also generate (and read) &lt;code&gt;dict&lt;/code&gt;s, which are serialized forms of the entire wavefunction. You may also pass an optional filename, which will save the wavefunction object as a &lt;code&gt;numpy&lt;/code&gt; file.&lt;/p&gt;&#xA;&lt;p&gt;You can get the wavefunction as a return from a calculation or building it yourself, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import psi4&#xA;&#xA;mol = psi4.geometry(&amp;quot;&amp;quot;&amp;quot;&#xA;H 0.0 0.0 0.0&#xA;H 0.0 0.0 0.74&amp;quot;&amp;quot;&amp;quot;)&#xA;&#xA;# build wfn yourself&#xA;bas = psi4.core.BasisSet.build(mol,&amp;quot;ORBITAL&amp;quot;,&amp;quot;sto-3g&amp;quot;,quiet=True)&#xA;wfn = psi4.core.Wavefunction(mol,bas)&#xA;&#xA;# get wfn as a return&#xA;psi4.set_options({&amp;quot;basis&amp;quot;:&amp;quot;sto-3g&amp;quot;})&#xA;e,wfn = psi4.energy('scf',return_wfn=True)&#xA;&#xA;# either way, save to file&#xA;wfn.to_file('wfn.npy')&#xA;&#xA;# load it back up as a new wfn and print the variables inside&#xA;new_wfn = psi4.core.Wavefunction.from_file('wfn.npy')&#xA;print(new_wfn.variables())&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8237" LastEditorUserId="8237" LastEditDate="2023-11-01T20:08:44.743" LastActivityDate="2023-11-01T20:08:44.743" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11830" PostTypeId="2" ParentId="11553" CreationDate="2023-10-31T15:38:55.517" Score="1" Body="&lt;h1&gt;RingsStatisticsMatter.jl&lt;/h1&gt;&#xA;&lt;p&gt;If you prefer your rings to be returned as a python list to do further analysis with, there's code available at &lt;a href=&quot;https://github.com/MorrowChem/RingsStatisticsMatter.jl&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/MorrowChem/RingsStatisticsMatter.jl&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;With a couple of lines of python (and installing Julia), you can get the nodes of the rings in your structure, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ats = read('structures/POSCAR-SiO2-a-quartz', '-1')&#xA;&#xA;rs, rings = ring_statistics(ats, cutoff=1.63, maxlvl=20)&#xA;&#xA;print(rings[11])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Nodes for 12-membered rings&#xA;[array([0, 6, 2, 7, 1, 8, 0, 3, 1, 4, 2, 5], dtype=int64),&#xA;  array([0, 8, 1, 3, 0, 5, 2, 4, 1, 7, 2, 6], dtype=int64),&#xA;  array([0, 8, 1, 7, 2, 4, 1, 3, 0, 5, 2, 6], dtype=int64)])&#xA;&#xA;&#xA;Ring statistics:&#xA;Ring Size |            Count &#xA;----------|------------------&#xA;        1 |             0.0&#xA;        2 |             0.0&#xA;        3 |             0.0&#xA;        4 |             0.0&#xA;        5 |             0.0&#xA;        6 |             0.0&#xA;        7 |             0.0&#xA;        8 |             0.0&#xA;        9 |             0.0&#xA;       10 |             0.0&#xA;       11 |             0.0&#xA;       12 |             3.0&#xA;       13 |             0.0&#xA;       14 |             0.0&#xA;       15 |             0.0&#xA;       16 |            15.0&#xA;       17 |             0.0&#xA;       18 |             0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8245" LastEditorUserId="8245" LastEditDate="2023-11-16T21:17:39.437" LastActivityDate="2023-11-16T21:17:39.437" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11831" PostTypeId="2" ParentId="11772" CreationDate="2023-11-01T06:21:50.023" Score="-1" Body="&lt;p&gt;There is a conference paper from NERSC that has benchmarks for different VASP settings on Perlmutter using NVIDIA A100 GPUs and AMD Milan CPUs.&lt;/p&gt;&#xA;&lt;p&gt;In the paper, they mention that running VASP on a GPU node leaves many CPUs idle. Here is their conclusion:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;One can see that enabling OpenMP threads significantly slows down the HSE workloads, especially when using fewer threads per task (see blue bars for Si256 hse and B.hR105 hse). However, OpenMP threads benefit other workloads, although not significantly, especially for one-node runs (up to 6%). In practice, enabling eight or 16 threads per task to utilize otherwise idling CPU resources for non-HSE&#xA;workloads can get a small additional speedup. The significant slowdown from using OpenMP threads for HSE workloads can be fixed when setting NBLOCK_FOCK= NBANDS/Total_number_of_MPI_processes in the INCAR file. NBLOCK_FOCK, the blocking factor in the Fock-exchange operator (an undocumented INCAR tag), is set to 2*OMP_NUM_THREADS internally in VASP. Apparently, it benefits from a larger NBLOCK_FOCK than 2*OMP_NUM_THREADS, especially for smaller OMP_NUM_THREADS values, to achieve optimal performance. When a proper NBLOCK_FOCK is used for HSE, the OpenMP threads also benefit the VASP performance similar to the rest of the workloads.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So it seems that increasing CPU usage does not significantly affect VASP performance on GPUs. There are other benchmarks in the paper as well. The best things to do are to set KPAR = # of GPUs, which I think will not work for a gamma point calculation, and to use all the GPU memory which you are already doing.&lt;/p&gt;&#xA;&lt;p&gt;Here is a &lt;a href=&quot;https://drive.google.com/file/d/1kPFNc-y0ezn_ANatYDpE04x603U-gxlL/view&quot; rel=&quot;nofollow noreferrer&quot;&gt;direct link&lt;/a&gt; to the paper, it may also be available on the &lt;a href=&quot;https://cug.org/digital-library/&quot; rel=&quot;nofollow noreferrer&quot;&gt;conference website&lt;/a&gt; at some point as well.&lt;/p&gt;&#xA;" OwnerUserId="8027" LastEditorUserId="8027" LastEditDate="2023-11-10T05:09:56.410" LastActivityDate="2023-11-10T05:09:56.410" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11832" PostTypeId="1" CreationDate="2023-11-01T10:17:56.737" Score="2" ViewCount="49" Body="&lt;p&gt;I am trying to calculate the Pauli limit for a superconducting material with Hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H_0$&lt;/span&gt; and an external magnetic field contribution &lt;span class=&quot;math-container&quot;&gt;$H_p$&lt;/span&gt;. I find the matsubara greens function as &lt;span class=&quot;math-container&quot;&gt;$\hat{G} = [i\omega_n - H_0 - H_p]^{-1}$&lt;/span&gt; and then to solve the gap equation for &lt;span class=&quot;math-container&quot;&gt;$T_c$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H_{c2}$&lt;/span&gt; I calculate the susceptibility as &lt;span class=&quot;math-container&quot;&gt;$\chi = \frac{1}{N\beta}\sum_{k,\omega_n} G_{\uparrow\uparrow}(k,i\omega_n)G_{\downarrow\downarrow}(-k,-i\omega_n) - G_{\downarrow\uparrow}(k,i\omega_n)G_{\downarrow\uparrow}(-k,-i\omega_n)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I see people here are using specific software and libraries . But I am just using plain python. I generate points in a square BZ with a simple for loop and my problem is the following. When I change the number of points in the grid even slightly the result changes dramatically. How do I properly generate the points in the BZ ? And to perform the summation over k do I need some kind of density of states weighting when I generate the points ?  Also the way I am defining the matsubara greens functions the susceptibility is positive. Does this also have to do with the super simple way of generating the points or is my formula incorrect ?&lt;/p&gt;&#xA;" OwnerUserId="8247" LastEditorUserId="8247" LastEditDate="2023-11-01T12:28:16.707" LastActivityDate="2023-11-01T12:28:16.707" Title="BZ grid and susceptibility for numerical Pauli limit calculation" Tags="|k-points|brillouin-zone|superconductivity|greens-functions|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11833" PostTypeId="1" CreationDate="2023-11-01T14:25:04.983" Score="1" ViewCount="81" Body="&lt;p&gt;I was running a state averaged CASSCF (4,4) calculation for the first 3 roots of the TMM biradical in PySCF. I wanted to get the spin configuration of the active space but the only information I could find in the simulation output is the following table.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;** Largest CI components **&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 0   CI coefficient&#xA;  [0 1]                [0 2]                           0.680999601372&#xA;  [0 2]                [0 1]                          -0.680999601372&#xA;  [1 2]                [0 3]                           0.162876965573&#xA;  [0 3]                [1 2]                          -0.162876965573&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 1   CI coefficient&#xA;  [0 1]                [0 1]                           0.521598297554&#xA;  [0 1]                [0 2]                          -0.296126060144&#xA;  [0 1]                [1 2]                          -0.235407708465&#xA;  [0 1]                [0 3]                          -0.106906206218&#xA;  [0 2]                [0 1]                          -0.296126060144&#xA;  [0 2]                [0 2]                          -0.521414937085&#xA;  [0 2]                [1 2]                          -0.133788127011&#xA;  [0 2]                [0 3]                           0.190214831302&#xA;  [1 2]                [0 1]                          -0.235407708465&#xA;  [1 2]                [0 2]                          -0.133788127011&#xA;  [0 3]                [0 1]                          -0.106906206218&#xA;  [0 3]                [0 2]                           0.190214831302&#xA;  [alpha occ-orbitals] [beta occ-orbitals]  state 2   CI coefficient&#xA;  [0 1]                [0 1]                           0.275144934363&#xA;  [0 1]                [0 2]                           0.518472331429&#xA;  [0 1]                [1 2]                          -0.131745811887&#xA;  [0 1]                [0 3]                           0.201009810870&#xA;  [0 2]                [0 1]                           0.518472331429&#xA;  [0 2]                [0 2]                          -0.313130614232&#xA;  [0 2]                [1 2]                           0.232139108556&#xA;  [0 2]                [0 3]                           0.115309844670&#xA;  [1 2]                [0 1]                          -0.131745811887&#xA;  [1 2]                [0 2]                           0.232139108556&#xA;  [0 3]                [0 1]                           0.201009810870&#xA;  [0 3]                [0 2]                           0.115309844670&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I had previously posted a question on the interpretation of this table at &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11824/table-of-largest-ci-components-in-pyscf-casscf-calculation&quot;&gt;Table of Largest CI Components in PySCF CASSCF Calculation&lt;/a&gt; where I came to know that the ground state (state 0) in the table represents an open-shell singlet state. But according to the &amp;lt;S**2&amp;gt; value provided in the output, the ground state is supposed to be a triplet state&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CASSCF energy = -154.937807129837&#xA;CASCI E = -154.937807129837  E(CI) = -3.22262432727504  S^2 = 0.6666667&#xA;CASCI state-averaged energy = -154.937807129837&#xA;CASCI energy for each state&#xA;  State 0 weight 0.333333  E = -154.964945548567 S^2 = 2.0000000&#xA;  State 1 weight 0.333333  E = -154.924749463197 S^2 = 0.0000000&#xA;  State 2 weight 0.333333  E = -154.923726377748 S^2 = 0.0000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why is there a disagreement in the result? Is there an alternative approach to obtaining the spin configuration of the active space in PySCF?&#xA;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="8236" LastEditorUserId="5" LastEditDate="2023-11-01T18:03:29.990" LastActivityDate="2023-11-01T18:03:29.990" Title="Spin Configuration of Active Space in PySCF" Tags="|pyscf|spin|casscf|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11834" PostTypeId="2" ParentId="11833" CreationDate="2023-11-01T15:48:03.493" Score="1" Body="&lt;p&gt;PySCF works in a determinant basis. This means that you can only set the value of &lt;span class=&quot;math-container&quot;&gt;$S_z$&lt;/span&gt;, the &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; projection of the total spin.&lt;/p&gt;&#xA;&lt;p&gt;If you have a state with total spin &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;, it will have &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; projections of &lt;span class=&quot;math-container&quot;&gt;$-S$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$-S+1$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\dots$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$S-1$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt;. This means that if you try to target a singlet state by setting &lt;span class=&quot;math-container&quot;&gt;$S_z=0$&lt;/span&gt;, you may also find that the lowest root is a higher spin state, such as a triplet, quintet, heptet, etc.&lt;/p&gt;&#xA;&lt;p&gt;The energy ordering of the states depends on many factors. The used orbitals are one important factor. The size of the active space and dynamical correlation is another: going to a larger active space or including dynamic correlation can change or flip the ordering of the various spin states. This is likely what you are also seeing.&lt;/p&gt;&#xA;&lt;p&gt;Furthermore, in this case, you have a small active space and you are not optimizing the orbitals for the ground state, but rather for a state average. The orbitals may simply be better for the excited triplet state than for the ground singlet state, which results in the incorrect ordering.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-11-01T15:48:03.493" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11835" PostTypeId="1" AcceptedAnswerId="11836" CreationDate="2023-11-02T11:17:55.537" Score="4" ViewCount="241" Body="&lt;p&gt;I have run into a particular problem while trying to automate my input file generation for ORCA calculations. Apparently, I either do not fully understand how SMILES strings work, or I am demanding more than they can really deliver. What I generally do is to use a python script to generate xyz files from SMILES strings to get the initial coordinates of my molecules. This usually works just fine, but metal-organic complexes seem to pose a particular challenge.&lt;/p&gt;&#xA;&lt;p&gt;As an example, I will show you the SMILES &lt;code&gt;[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1&lt;/code&gt;, which corresponds to the following molecule:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wWXtD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wWXtD.png&quot; alt=&quot;initial coords xyz from RDKit EmbedMolecule&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Right off the bat: There is something weird about the SMILES. I wasn't able to generate the right molecule with the SMILES &lt;code&gt;[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1&lt;/code&gt;, which would show the correct distribution of charges and numbers of hydrogens on the ammonia ligands. So the only way to get it to work is to use cationic &amp;quot;ammonium&amp;quot; side groups/ligands and compensate their overall charge using negative charges on the Zinc atom.&lt;/p&gt;&#xA;&lt;p&gt;I've looked for SMILES other metal-organic complexes, which I could use as a reference, to construct a proper SMILES for my mols, but it seems that I am not the only one facing this issue. Take a look at the page for &lt;a href=&quot;https://pubchem.ncbi.nlm.nih.gov/compound/Tetraamminecopper_2_-sulfate&quot; rel=&quot;nofollow noreferrer&quot;&gt;Tetraamminecopper(2+) sulfate&lt;/a&gt; on pubchem. The SMILES on there is incorrect and no geometry can be generated on the website. This indicates to me that SMILES strings are, at least regular SMILES strings, not well adapted to depict metal-organic complexes.&lt;/p&gt;&#xA;&lt;p&gt;This isn't that much of an issue in itself, since I have found a workaround to generate my initial coordinates using RDKit anyways. The real problem arises when I try to do an initial MMFF94 Energy Minimization of the initial coordinates: How is MMFF94 supposed to know which atom types to assign to this molecule and perform it's energy minimization? Short answer: It obviously can't and so the energy minimization isn't performed.&lt;/p&gt;&#xA;&lt;p&gt;What I have discovered though is that Avogadro can indeed perform an energy minimization using UFF if you load in the xyz file of the initial coordinates. So it seems that Avogadro has some kind of fancy way to assign atom types based on xyz file info alone and perform a proper energy minimization using UFF:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rYRpo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rYRpo.png&quot; alt=&quot;Optimized coords using UFF in Avogadro&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now here is where I got excited: So there is a way to properly preoptimize my mols using UFF and guess what? You can use UFF preoptimization in &lt;code&gt;RDKit&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;from rdkit import Chem&#xA;from rdkit.Chem import AllChem&#xA;&#xA;# Load SMILES as mol obj&#xA;mol = Chem.MolFromSmiles('[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1')  &#xA;mol = AllChem.AddHs(mol) # make sure to add explicit hydrogens&#xA;&#xA;# Generate 3D coordinates&#xA;AllChem.EmbedMolecule(mol)&#xA;xyz = Chem.AllChem.MolToXYZBlock(mol) # initial coords&#xA;&#xA;with open('unoptimized.xyz','w') as outf:&#xA;    outf.write(xyz)&#xA;&#xA;# Perform UFF optimization&#xA;ff = AllChem.UFFGetMoleculeForceField(mol)&#xA;ff.Initialize()&#xA;ff.Minimize(energyTol=1e-7,maxIts=100000)&#xA;&#xA;xyz = Chem.AllChem.MolToXYZBlock(mol)&#xA;with open('B.xyz','w') as outf:&#xA;    outf.write(xyz)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the problem though: I am still using a fundamentally incorrect SMILES. And while the xyz information does not remember the incorrect charges of the Zinc and the Nitrogens, the RDKit mol object certainly does. And so I cannot use that mol object to preoptimize my mols.&lt;/p&gt;&#xA;&lt;p&gt;But there could be a way out if I just create a new mol object only from the xyz information from the initial coords and then perform the minimization. It worked in Avogadro, so why not in RDKit, right? Well, unfortunately no...&lt;/p&gt;&#xA;&lt;p&gt;I added this code fragment to my code after the initial coords generation:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;mol = Chem.MolFromXYZBlock(xyz)&#xA;Chem.SanitizeMol(mol)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which overwrites the mol object with one only generated from xyz information. But when I run the UFF minimization on that mol, the UFF typer of RDKit doesn't let me.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;UFFTYPER: Unrecognized charge state for atom: 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Keep in mind: The charges are no longer provided by the incorrect SMILES, but &lt;em&gt;must&lt;/em&gt; be dynamically assigned by RDKit's UFF typer. And since the charge of the Zinc atom is not recognized by the Universal Force Field, the geometry optimization doesn't do anything.&lt;/p&gt;&#xA;&lt;p&gt;So it would seem that while the RDKit UFF typer is incapable of assigning any meaningful atom types for my mol, the UFF typer of Avogadro can perform some kind of eldritch magic and get it done regardless. Which means &lt;em&gt;a lot&lt;/em&gt; of manual optimization for me.&lt;/p&gt;&#xA;&lt;p&gt;I have tried to switch out the Zinc for other elements (Sn, Si, Pb bc tetragonal) so that the UFF typer would at least do some of the work for me, but no luck.&lt;/p&gt;&#xA;&lt;p&gt;So my question is this: Is there a way to get RDKit to recognize such mols and preoptimize them anyway? It is clearly possible with Avogadro and it is almost certainly a UFF Typer assignment issue. Maybe there is a better SMILES that I can use? Perhaps the charges of the Zinc can be edited manually somehow? I have some ideas of what I can try, but not how to test them...&lt;/p&gt;&#xA;&lt;p&gt;EDIT: I messed up the SMILES in the pics. The correct SMILES is:&#xA;&lt;code&gt;[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="7501" LastEditorUserId="5" LastEditDate="2023-11-03T00:59:44.437" LastActivityDate="2023-11-03T00:59:44.437" Title="How to pre-optimize metal-organic complexes in RDKit using UFF?" Tags="|geometry-optimization|forcefields|rdkit|avogadro|metals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11836" PostTypeId="2" ParentId="11835" CreationDate="2023-11-02T12:48:56.597" Score="3" Body="&lt;p&gt;Okay, there's a bunch to answer here, but I'll do my best.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Take a look at the page for Tetraamminecopper(2+) sulfate on pubchem. The SMILES on there is incorrect and no geometry can be generated on the website.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, that's because PubChem uses &lt;a href=&quot;https://chemistry.stackexchange.com/a/125591/5017&quot;&gt;MMFF94 to generate 3D geometries&lt;/a&gt; so not all molecules on PubChem have them.&lt;/p&gt;&#xA;&lt;p&gt;You ask about MMFF94 minimization - not all force fields support metals. MMFF94 supports a few types of isolated ions, but not in molecules.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;So it seems that Avogadro has some kind of fancy way to assign atom types based on xyz file info alone and perform a proper energy minimization using UFF:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Avogadro uses Open Babel's implementation for UFF, which I wrote. It's intended to be very forgiving of weird charges and coordination environments. A strict UFF implementation (e.g., RDKit) will insist the &lt;code&gt;Zn3+2&lt;/code&gt; parameters only apply to &lt;span class=&quot;math-container&quot;&gt;$\ce{Zn^{2+}}$&lt;/span&gt; ions.&lt;/p&gt;&#xA;&lt;p&gt;I'm less familiar with feeding metals to RDKit's UFF implementation - your better bet is to ask there.&lt;/p&gt;&#xA;&lt;p&gt;But you can feed whatever you want into Open Babel as well:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;obabel -:'[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1' -O zn.xyz --gen3d&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Or in Python:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from openbabel import pybel&#xA;&#xA;# assuming a list of SMILES&#xA;smiles_list = [ '[Zn--]([NH3+])([NH3+])([NH3+])N1C=C(Cl)N=C1' ]&#xA;&#xA;for smiles in smiles_list:&#xA;&#xA;    mol = pybel.readstring(&amp;quot;smi&amp;quot;, smiles)&#xA;&#xA;    # make it 3D&#xA;    pybel._builder.Build(mol.OBMol)&#xA;    mol.addh()&#xA;&#xA;    # if possible (e.g., a ligand) use MMFF94&#xA;    #  .. otherwise UFF&#xA;    ff = pybel._forcefields[&amp;quot;mmff94&amp;quot;]&#xA;    success = ff.Setup(mol.OBMol)&#xA;    if not success:&#xA;        ff = pybel._forcefields[&amp;quot;uff&amp;quot;]&#xA;        success = ff.Setup(mol.OBMol)&#xA;        if not success:&#xA;           sys.exit(&amp;quot;Cannot set up forcefield&amp;quot;)&#xA;&#xA;    # optimize a bit and do a quick conformer search&#xA;    ff.ConjugateGradients(100, 1.0e-3)&#xA;    ff.WeightedRotorSearch(100, 25)&#xA;    ff.ConjugateGradients(250, 1.0e-4)&#xA;&#xA;    # update the coordinates&#xA;    ff.GetCoordinates(mol.OBMol)&#xA;&#xA;    # pick your favorite format&#xA;    # here, I'm suggesting SDF &#xA;    # if you want to retain formal charges&#xA;    mol.write(&amp;quot;sdf&amp;quot;, &amp;quot;test.sdf&amp;quot;, overwrite=True)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-11-02T12:48:56.597" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11838" PostTypeId="1" CreationDate="2023-11-02T14:14:39.650" Score="4" ViewCount="58" Body="&lt;p&gt;I used a python code to extract &lt;a href=&quot;https://handwiki.org/wiki/Physics:Lindemann_index&quot; rel=&quot;nofollow noreferrer&quot;&gt;Lindemann index&lt;/a&gt; from dump files. But the problem is the code works fine with dump files with little amount of data and atoms. When I use large files if shows overflow for python data types. Is there any alternative way to extract Lindemann Index ?&lt;/p&gt;&#xA;" OwnerUserId="7200" LastEditorUserId="1206" LastEditDate="2023-11-02T16:26:18.377" LastActivityDate="2023-11-02T16:26:18.377" Title="How to extract Lindemann Index from LAMMPS dump files?" Tags="|molecular-dynamics|lammps|ovito|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11839" PostTypeId="1" CreationDate="2023-11-02T17:02:26.667" Score="3" ViewCount="54" Body="&lt;p&gt;INCAR, POSCAR, and KPOINTS are the same but for the same calculation, the bandgap is changing.&#xA;First, I relaxed the structure then did the self-consistent calculation, and bandstructure calculation. Obviously, for this, I changed my POSCAR, INCAR and KPOINTS accordingly. I am trying to reproduce the results of this paper.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://link.aps.org/pdf/10.1103/PhysRevMaterials.6.035402&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://link.aps.org/pdf/10.1103/PhysRevMaterials.6.035402&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here are my INCAR File Parameters for the calculation of the Band structure&#xA;System = X&#xA;PREC = Accurate&#xA;ISTART = 1&#xA;ICHARG = 11&#xA;NBANDS = 63&#xA;ISPIN = 1&#xA;ENCUT = 550&#xA;NELM = 100&#xA;NELMIN = 5&#xA;EDIFF = 1E-6&#xA;LREAL = Auto&#xA;ALG0 = Normal&#xA;NSW = 0&#xA;IBRION = -1&#xA;ISIF = 2&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;LWAVE = .TRUE.&#xA;LCHARG = .TRUE.&#xA;NCORE =4&lt;/p&gt;&#xA;" OwnerUserId="6602" LastEditorUserId="6602" LastEditDate="2023-11-03T14:00:42.050" LastActivityDate="2023-11-03T14:00:42.050" Title="My INCAR file, POSCAR, and KPOINTS are same for GGA, however after the PBE calculation, I found that the bandgap is Changing. Why is that happened?" Tags="|density-functional-theory|vasp|bandgap|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11840" PostTypeId="2" ParentId="11823" CreationDate="2023-11-02T18:56:58.777" Score="3" Body="&lt;p&gt;I'd recommend ChiralTube: &lt;a href=&quot;http://chiraltube.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://chiraltube.com&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code (and simulations) were covered in a recent publication:&#xA;&lt;a href=&quot;https://doi.org/10.1039/D3NA00301A&quot; rel=&quot;nofollow noreferrer&quot;&gt;&amp;quot;Chiraltube, rolling 2D materials into chiral nanotubes&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code is also available on GitHub: &lt;a href=&quot;https://github.com/Chema-dac/chiraltube&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/Chema-dac/chiraltube&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The paper covers, carbon nanotubes, phosphorene, but also &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\ce{Ti3C2}$&lt;/span&gt;. I haven't had much time to explore it, but the &lt;code&gt;UnitCellExamples&lt;/code&gt; include QuantumEspresso input, &amp;quot;special XYZ&amp;quot;, and VASP.&lt;/p&gt;&#xA;&lt;p&gt;Here's &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; in &amp;quot;special xyz&amp;quot; format:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;3&#xA;####comment####&#xA;S 1.5905260315876495465 0.9182342920325894154  6.565586833&#xA;S 1.5905260315876495465 0.9182342920325894154  3.434413167&#xA;Mo 0.0000142401699290626 1.8365313040729291692 5.000000000000&#xA;alat&#xA;1.0&#xA;mass S 28.09&#xA;mass Mo 95.95&#xA;supercell&#xA; 3.181079696    0.000000000   0.000000000&#xA;-1.590540237    2.754889038   0.000000000&#xA; 0.000000000    0.000000000  10.000000000&#xA;cartesian coordinates&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The website writes the &amp;quot;special xyz&amp;quot; by default, but you can use VASP input and output from the Python script:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;python chiraltube.py &amp;lt;inputfile&amp;gt; -indexn5m10 -VASPin -VASPout&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;It also gives help with:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;python chiraltube.py -h&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;For example, a supercell of &lt;span class=&quot;math-container&quot;&gt;$\ce{MoS2}$&lt;/span&gt; 5,5 nanotube in POSCAR rendered by Avogadro:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mgKrK.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mgKrK.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-11-02T18:56:58.777" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11841" PostTypeId="2" ParentId="11822" CreationDate="2023-11-02T22:25:54.140" Score="5" Body="&lt;p&gt;Yes, you can think of conformations as arising from vibrational modes, typically low-energy ones. In fact, some conformational search methods use low-energy dynamics or projection to find new conformers.&lt;/p&gt;&#xA;&lt;p&gt;I think Paul Hawkins still has the best review:&#xA;&lt;a href=&quot;https://doi.org/10.1021/acs.jcim.7b00221&quot; rel=&quot;noreferrer&quot;&gt;&amp;quot;Conformation Generation: The State of the Art&amp;quot; (2017)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Stochastic methods based on Monte Carlo-simulated annealing (23) (MC) are often faster than MD methods. (24, 25) Methods based on low-mode or normal-mode searching attempt to retain the sound physics of MD while requiring still less computation time. (26-29) However, all these methods can still require many CPU minutes to produce conformations for a single molecule and are therefore unsuitable for processing even a few thousand molecules. Additionally, for MD and MC approaches (but, to a lesser degree, low-mode MD methods), the input conformation, which is required in all these methods, can bias the sampling, requiring the use of either multiple input conformations or longer sampling time.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Thus, many conformer search techniques either drive torsional angles or use distance-geometry (e.g. RDKit / ETKDG) as ways to stochastically project new conformer minima without needing MD or biasing the search.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-11-02T22:25:54.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11842" PostTypeId="1" CreationDate="2023-11-03T00:22:44.217" Score="4" ViewCount="407" Body="&lt;p&gt;I have a periodic structure with an aromatic group that can interact via hydrogen bonding to another species. I would like to conduct a potential energy scan to determine the energy barrier to rotation with respect to the aromatics angle.&lt;/p&gt;&#xA;&lt;p&gt;I think I need to run a SCF calculation for each step (ie. 10 degrees) of rotation to then plot my energy barrier.&lt;/p&gt;&#xA;&lt;p&gt;I am unsure if there is a function in Quantum Espresso or if input files need to be individually prepared. If it is the latter how do I go about changing the rotation of the aromatic species when starting with a CIF?&lt;/p&gt;&#xA;" OwnerUserId="6958" LastActivityDate="2023-11-03T06:40:18.573" Title="Potential energy scan in quantum espresso rotating an aromatic group" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11843" PostTypeId="1" CreationDate="2023-11-03T02:48:13.830" Score="4" ViewCount="214" Body="&lt;p&gt;I am trying to calculate the d orbital energy of the Cu single atom, like &lt;a href=&quot;http://www.graylark.com/eve/orbital-energies-table.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this page&lt;/a&gt;, I have tried to use the Eigenband energies minus the vacuum energy level(about 0.007eV).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA; k-point     1 :       0.0000    0.0000    0.0000&#xA;  band No.  band energies     occupation &#xA;      1      -6.8877      1.00000&#xA;      2      -6.8877      1.00000&#xA;      3      -6.8872      1.00000&#xA;      4      -6.8863      1.00000&#xA;      5      -6.8863      1.00000&#xA;      6      -5.9796      1.00000&#xA;      7      -0.9533      0.00000&#xA;      8      -0.8847      0.00000&#xA;      9      -0.5722      0.00000&#xA;     10      -0.1787      0.00000&#xA; Fermi energy:        -5.7513822398&#xA;&#xA; spin component 2&#xA;&#xA; k-point     1 :       0.0000    0.0000    0.0000&#xA;  band No.  band energies     occupation &#xA;      1      -6.6023      1.00000&#xA;      2      -6.6010      1.00000&#xA;      3      -6.6010      1.00000&#xA;      4      -6.6010      1.00000&#xA;      5      -6.6010      1.00000&#xA;      6      -5.2707      0.00000&#xA;      7      -0.4024      0.00000&#xA;      8      -0.2912      0.00000&#xA;      9       0.0570      0.00000&#xA;     10       0.0751      0.00000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The result is far from the experient result.&#xA;My question is : how should I calculate the d orbital energy using VASP?&lt;/p&gt;&#xA;" OwnerUserId="1788" LastEditorUserId="5" LastEditDate="2023-11-03T11:32:19.863" LastActivityDate="2023-11-03T11:32:19.863" Title="How may I calculate atomic orbital energies using VASP?" Tags="|density-functional-theory|vasp|orbitals|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11844" PostTypeId="2" ParentId="11842" CreationDate="2023-11-03T06:40:18.573" Score="4" Body="&lt;p&gt;I do not think Quantum Espresso has a direct pathway towards such a calculation. However, You can use PLUMED along with Quantum Espresso to achieve the same goal. The advantage of this approach is that you can also generate the free-energy surface from PLUMED itself. The only downside is that you will most probably need to recompile Quantum Espresso and patch it with PLUMED if you decide to go this way.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2023-11-03T06:40:18.573" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11845" PostTypeId="2" ParentId="11843" CreationDate="2023-11-03T08:00:02.530" Score="1" Body="&lt;p&gt;I will suppose that you have done the following as your approach looks correct, you shoud have performed an (SCF) calculation and include a sufficient number of bands to accurately capture the d orbital energies. Make sure to converge the calculation properly, including the k-point sampling. Once the SCF calculation is complete, you can analyze the band structure output. This output usually includes the energy levels and occupations for each band at different k-points in the Brillouin zone. Identify the d orbital bands: Look for the bands associated with the d orbitals of the Cu atom. I think in your provided output, the d orbital bands are not visible due to the incomplete band structure. Typically, the d orbitals appear at higher energies, so you may need to examine bands beyond the ones shown. Determine the d orbital energy: Once you have identified the d orbital bands, you can calculate their energies. The energy of a band is given relative to the Fermi energy. In your case, subtracting the vacuum energy level (0.007 eV) from the band energies should give you an approximation of the d orbital energies. Keep in mind that the accuracy of your calculation may depend on various factors, such as the exchange-correlation functional used, the basis set, and the convergence criteria. It's important to ensure that your VASP calculation is appropriately converged and includes all relevant factors for an accurate determination of the d orbital energies.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-03T08:00:02.530" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11846" PostTypeId="1" CreationDate="2023-11-03T08:54:16.453" Score="3" ViewCount="32" Body="&lt;p&gt;I have run a few AIMD calculations of some impurities trapped in a solid using &lt;a href=&quot;https://www.cp2k.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;CP2K&lt;/a&gt; and &lt;a href=&quot;http://www.travis-analyzer.de&quot; rel=&quot;nofollow noreferrer&quot;&gt;TRAVIS&lt;/a&gt; to simulate the resulting infrared spectrum. While the infrared spectrum was simulated well, there is no indication as to what vibrations each peak corresponds to, so I cannot make the comparison between bulk phase AIMD and gas phase ab initio calculations.&lt;/p&gt;&#xA;&lt;p&gt;One of the other features TRAVIS has, though, is a normal coordinate analysis (I assume) specifically for a situation like this. I attempted to run the normal coordinate analysis; however, one of the questions TRAVIS asks is to input a reference geometry.&lt;/p&gt;&#xA;&lt;p&gt;The problem is that I have no idea what kind of reference geometry TRAVIS might want. For example, would it want an &lt;code&gt;.xyz&lt;/code&gt; file (i.e., first line is number of atoms, second line is a comment line, and the cartesian coordinates follow), or simply a file with cartesian coordinates only? Should I take a random frame from the AIMD trajectory and use them as my reference geometry, or should I provide an optimised structure?&lt;/p&gt;&#xA;&lt;p&gt;I have tried optimising one of the molecules in CP2K and using that as my reference structure (as was done in &lt;a href=&quot;https://doi.org/10.1063/1.4887082&quot; rel=&quot;nofollow noreferrer&quot;&gt;this article&lt;/a&gt;), but, using a simple file with the cartesian coordinates of the impurity as input produced an error, saying:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Some atoms are not connected to the molecule&#xA;&#xA;Molecule recognition failed&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To my knowledge, there is currently no manual for TRAVIS, and the only tutorials I could find were about how to generate the IR spectra. I have reached out to the lead developer but not gotten a reply.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any experience doing this, or have any idea how to run this type of analysis in TRAVIS? Any help would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="7606" LastEditDate="2023-11-03T11:04:05.727" LastActivityDate="2023-11-03T11:04:05.727" Title="Normal coordinate analysis in TRAVIS" Tags="|spectroscopy|cp2k|aimd|travis|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11847" PostTypeId="5" CreationDate="2023-11-03T11:06:49.793" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-11-03T11:06:49.793" LastActivityDate="2023-11-03T11:06:49.793" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11848" PostTypeId="4" CreationDate="2023-11-03T11:06:49.793" Score="0" Body="Questions related to the program TRAVIS (Trajectory Analyzer and Visualizer)." OwnerUserId="7606" LastEditorUserId="5" LastEditDate="2023-11-03T11:29:25.690" LastActivityDate="2023-11-03T11:29:25.690" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11849" PostTypeId="1" CreationDate="2023-11-03T20:55:44.580" Score="5" ViewCount="127" Body="&lt;p&gt;I am confused as to whether integrating over the charge density gets us the number of valence electrons in the material system or the total number of valence electrons in the material system.&lt;/p&gt;&#xA;&lt;p&gt;Let's take an example: say I have the charge density of Al2O3, which contains exactly 2 atoms of Aluminim and 3 atoms of Oxygen. Now we all know that Al has 3 valence electrons and O has 2 valence electrons. So this charge density has a total of 2*3 + 3*2 = 12 valence electrons right? So if I integrate over the charge density should I get 12 as the result?&lt;/p&gt;&#xA;&lt;p&gt;It would help all of us understand this better, if one would write out the formula to obtain the valence electrons from the charge density array (rho).&lt;/p&gt;&#xA;&lt;p&gt;Is &lt;code&gt;no. of valence electrons = round(vol*np.sum(rho)/rho.size)&lt;/code&gt; in python?&lt;/p&gt;&#xA;&lt;p&gt;Please provide suitable references to your answer.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2023-11-03T21:49:08.670" LastActivityDate="2023-11-05T07:59:42.013" Title="What do we get by integrating over the charge density data of a material system calculated with DFT?" Tags="|density-functional-theory|vasp|electronic-structure|electron-density|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11851" PostTypeId="2" ParentId="11849" CreationDate="2023-11-04T08:18:04.270" Score="4" Body="&lt;p&gt;The integration of the charge density over the entire system gives you the total charge of the system. This value should be equal to the total number of electrons in the system, accounting for both the occupied and unoccupied states. Integrating over the charge density of Al2O3 will not directly give you the number of valence electrons in the system. The charge density represents the distribution of electron density in space, but it does not provide a direct count of the number of valence electrons.&#xA;The formula you provided in Python calculates an estimate of the number of valence electrons. Here's a breakdown of each component of the formula:&#xA;np.sum(rho),this calculates the sum of all the elements in the charge density array. It sums up the electron density values across all grid points in the system. vol, this represents the volume of the system. rho.size, this returns the total number of elements in the charge density array. It represents the total number of grid points or voxels used to discretize the system. np.sum(rho)/rho.size,this calculates the average electron density by dividing the sum of the electron density values by the total number of grid points. It gives you an estimate of the average electron density in the system. vol * np.sum(rho)/rho.size, this multiplies the average electron density by the volume of the system. The result is an estimate of the total number of electrons in the system.&#xA;round(vol * np.sum(rho)/rho.size), is the round function applied to round the calculated estimate of the total number of electrons to the nearest whole number. This is done because the number of valence electrons must be an integer value. By multiplying the average charge density by the volume of the system and rounding the result to the nearest whole number, you obtain an estimate of the total number of electrons in the system. In the context of valence electrons, this estimate assumes that the charge density represents the electron density associated with the valence electrons.  However, it's important to note that this formula provides an estimate and assumes a uniform charge density distribution throughout the system. It may not accurately capture the precise number of valence electrons, especially in more complex or non-uniform systems. The actual determination of valence electrons typically involves considering the electronic configuration of the individual atoms in the material or performing population analysis methods.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-04T08:18:04.270" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11852" PostTypeId="1" CreationDate="2023-11-05T14:01:57.720" Score="3" ViewCount="60" Body="&lt;p&gt;The situation is as follows: I did the DOS and PDOS calculations. However, in the PDOS results, several output files were generated, for example (O 1s, O 2p, etc.), so I saw that I needed to obtain the sum of these atoms to be able to generate the graph, does anyone know how to do this procedure? Or is there any material that teaches you?&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="5" LastEditDate="2023-11-05T14:32:29.117" LastActivityDate="2023-12-25T11:25:19.280" Title="Doubts about how to add the atoms of the PDOS output files" Tags="|quantum-espresso|density-of-states|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11853" PostTypeId="2" ParentId="10795" CreationDate="2023-11-05T14:43:26.467" Score="1" Body="&lt;p&gt;The &lt;a href=&quot;https://www.rosettacommons.org/docs/latest/rosetta_basics/structural_concepts/Mover&quot; rel=&quot;nofollow noreferrer&quot;&gt;link provided by Tyberius&lt;/a&gt; in a comment explains what a mover is.&lt;/p&gt;&#xA;&lt;p&gt;If someone would like to explain it here, I can delete this Community Wiki answer (you can just ask me in a comment on this answer, or click &amp;quot;flag&amp;quot; and &amp;quot;In need of moderator intervention&amp;quot; and explain yourself).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T14:43:26.467" CommentCount="0" CommunityOwnedDate="2023-11-05T14:43:26.467" ContentLicense="CC BY-SA 4.0" />
  <row Id="11854" PostTypeId="2" ParentId="10784" CreationDate="2023-11-05T14:46:21.000" Score="1" Body="&lt;p&gt;The OP found an answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Ah I found the solution. I changed the Tdamp to $(100*dt) and it worked. Although, I don’t understand exactly what is happening.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If someone would like to write an answer, I can delete this Community Wiki answer (you can just ask me in a comment on this answer, or click &amp;quot;flag&amp;quot; and &amp;quot;In need of moderator intervention&amp;quot; and explain yourself).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T14:46:21.000" CommentCount="0" CommunityOwnedDate="2023-11-05T14:46:21.000" ContentLicense="CC BY-SA 4.0" />
  <row Id="11855" PostTypeId="2" ParentId="10303" CreationDate="2023-11-05T15:26:47.960" Score="1" Body="&lt;p&gt;&lt;a href=&quot;https://orcaforum.kofo.mpg.de/viewtopic.php?f=8&amp;amp;t=9710&amp;amp;p=41039&amp;amp;hilit=mpi+memory#p41039&quot; rel=&quot;nofollow noreferrer&quot;&gt;This workaround&lt;/a&gt; solved the problem for the OP.&lt;/p&gt;&#xA;&lt;p&gt;If someone would like to write an answer, I can delete this Community Wiki answer (you can just ask me in a comment on this answer, or click &amp;quot;flag&amp;quot; and &amp;quot;In need of moderator intervention&amp;quot; and explain yourself).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T15:26:47.960" CommentCount="0" CommunityOwnedDate="2023-11-05T15:26:47.960" ContentLicense="CC BY-SA 4.0" />
  <row Id="11856" PostTypeId="2" ParentId="10453" CreationDate="2023-11-05T15:41:55.297" Score="1" Body="&lt;p&gt;To prioritize other people's questions in search results for unanswered questions, I'm taking this out of the unanswered queue.&lt;/p&gt;&#xA;&lt;p&gt;If have also &lt;a href=&quot;https://mattermodeling.meta.stackexchange.com/a/433/5&quot;&gt;promised to put a bounty on this question if someone does answer it and warns me in advance&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;If you want to answer this question, let me know and I'll remove this Community Wiki answer!&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T15:41:55.297" CommentCount="0" CommunityOwnedDate="2023-11-05T15:41:55.297" ContentLicense="CC BY-SA 4.0" />
  <row Id="11857" PostTypeId="2" ParentId="10406" CreationDate="2023-11-05T15:46:41.180" Score="2" Body="&lt;p&gt;jheindel's comment points to an answer:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Here is a question and answer that explains how to do this if you have the full set of distances. In general though, it may not be possible to reconstruct the full 3-D geometry from just the bond lengths. For instance, in methane, there will only be four bond lengths in your weighted adjacency matrix, which is insufficient to get the 9 degrees of freedom necessary to embed the molecule in 3-D space. &lt;a href=&quot;https://math.stackexchange.com/q/156161/202425%22&quot;&gt;https://math.stackexchange.com/q/156161/202425&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If someone would like to write an answer, I can delete this Community Wiki answer (you can just ask me in a comment on this answer, or click &amp;quot;flag&amp;quot; and &amp;quot;In need of moderator intervention&amp;quot; and explain yourself).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-05T15:46:41.180" CommentCount="0" CommunityOwnedDate="2023-11-05T15:46:41.180" ContentLicense="CC BY-SA 4.0" />
  <row Id="11858" PostTypeId="1" CreationDate="2023-11-05T23:32:35.843" Score="6" ViewCount="64" Body="&lt;p&gt;I really like Frank Jensen's &amp;quot;Introduction to Computational Chemistry&amp;quot; because it provides a broad perspective, starting from first principles and extending to surveys of current methods for Monte Carlo, molecular dynamics, etc. However, this book is from 2017, and many new directions are not covered (for example, machine learning driven methods, quantum computing related methods, and computational methods to address chemical synthesis). Is there a recommendation for recent books, book chapters, review articles, etc., that cover the important new directions in a way that is accessible for non-experts, especially in applications related to drug discovery and medicinal chemistry?&lt;/p&gt;&#xA;" OwnerUserId="8277" LastEditorUserId="5" LastEditDate="2023-11-05T23:58:49.247" LastActivityDate="2023-11-05T23:58:49.247" Title="Updated book/chapter or review article with broad perspective on computational chemistry" Tags="|computational-chemistry|molecular-modeling|reference-request|drug-design|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11860" PostTypeId="1" CreationDate="2023-11-06T16:46:33.713" Score="5" ViewCount="152" Body="&lt;p&gt;&lt;a href=&quot;https://www.linkedin.com/posts/kamran-elyas-916109142_struggling-to-install-quantum-espresso-on-activity-7127327350236585984-e6YP?utm_source=share&amp;amp;utm_medium=member_desktop&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cross posted on LinkedIn&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Struggling to install Quantum Espresso on Windows 10 for vital DFT calculations due to missing GitHub libraries. Seeking assistance from the LinkedIn community. If you have expertise or resources to help, please reach out. Your support is greatly appreciated in advancing our research.&lt;/p&gt;&#xA;" OwnerUserId="8281" LastEditorUserId="7" LastEditDate="2023-11-06T19:04:07.947" LastActivityDate="2023-11-06T19:04:07.947" Title="How do I install Quantum ESPRESSO on Windows 10?" Tags="|quantum-espresso|software|software-assistance|windows-operating-system|" AnswerCount="0" CommentCount="1" ClosedDate="2024-03-22T20:28:54.040" ContentLicense="CC BY-SA 4.0" />
  <row Id="11861" PostTypeId="1" AcceptedAnswerId="11868" CreationDate="2023-11-06T21:37:58.187" Score="4" ViewCount="85" Body="&lt;p&gt;I've recently started with VESTA and am having some trouble building the β-Tellurene structure (monoclinic, space group nº 12). I know that the lattice vectors are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\vec {a} = a\hat x \\ \vec {b} = b\hat y \\ \vec c =c\cos{\beta}\hat x+ c\sin{\beta}\hat z$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where, &lt;span class=&quot;math-container&quot;&gt;$a= 7.51 \mathring{A},\, b= 4.15\mathring{A},\, c\approx  10 \mathring{A}\quad \text{and} \quad \alpha =\gamma =90^\circ,\, \beta=141^\circ $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried to place the atoms at the midpoints of the vectors to change the unit cell, but without success. The closest I got was in the &amp;quot;armchair&amp;quot; part of the structure. The &amp;quot;zigzag&amp;quot; on the side I couldn't reproduce without breaking the symmetry:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/mtlOQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/mtlOQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm trying to get as close to the structure below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TKHPS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TKHPS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Bozhao Wu et al 2017 Mater. Res. Express 4 095902&lt;/p&gt;&#xA;" OwnerUserId="8250" LastEditorUserId="8250" LastEditDate="2023-11-07T06:20:05.070" LastActivityDate="2023-11-07T16:16:43.590" Title="Having difficulty creating the β-tellurene structure in VESTA" Tags="|crystallography|vesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11862" PostTypeId="2" ParentId="136" CreationDate="2023-11-07T01:50:12.853" Score="2" Body="&lt;p&gt;The cross-pollination and exchange of ideas between the operations research and physics communities in the context of Ising optimization methods can be traced back to several key papers and conferences. While it is difficult to pinpoint a single paper or conference that facilitated this exchange, there were significant developments during the period you mentioned (between circa 1961 and 1986) that contributed to the mutual understanding and adoption of techniques.&lt;/p&gt;&#xA;&lt;p&gt;One important milestone in this regard was the 1970 paper titled &amp;quot;Optimization by Simulated Annealing&amp;quot; by Scott Kirkpatrick, C. Daniel Gelatt, and Mario P. Vecchi. This paper introduced the simulated annealing algorithm, which is a stochastic optimization method inspired by the annealing process in metallurgy and physics. Simulated annealing was initially developed for solving optimization problems in physics, particularly Ising models, but it quickly gained attention in the operations research community due to its effectiveness in finding near-optimal solutions for complex combinatorial problems. Another influential work was the 1983 paper &amp;quot;Optimization by Simulated Annealing: Quantitative Studies&amp;quot; by S. Kirkpatrick, C. D. Gelatt, Jr., and M. P. Vecchi. This paper provided further analysis and empirical results demonstrating the effectiveness of simulated annealing as an optimization method. It helped solidify the understanding of simulated annealing as a powerful technique for solving a wide range of optimization problems, leading to its adoption and exploration by researchers in both operations research and physics.&lt;/p&gt;&#xA;&lt;p&gt;In terms of conferences, the colloquium on &amp;quot;Spin Glasses, Optimization and Neural Networks&amp;quot; held in 1986 at the University of Rome &amp;quot;La Sapienza&amp;quot; played a crucial role in bringing together researchers from different disciplines. This event provided a platform for discussions and presentations on spin glasses, optimization, and neural networks, fostering interdisciplinary collaboration and knowledge exchange. The proceedings of this colloquium, which you mentioned, contain valuable contributions from both the operations research and physics communities and further contributed to the cross-fertilization of ideas. It is worth noting that during this period, researchers from both communities were actively exploring optimization techniques, and the exchange of ideas happened gradually through various channels such as publications, conferences, and collaborations. The introduction of simulated annealing and its subsequent success in solving optimization problems played a significant role in drawing attention to the potential benefits of adopting methods from physics in the operations research domain. While it is challenging to attribute the entire cross-pollination process to a single paper or conference, the works and events mentioned here were instrumental in facilitating the exchange of ideas between the operations research and physics communities, leading to the mutual adoption of Ising optimization methods and the development of novel techniques in both fields.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-07T01:50:12.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11863" PostTypeId="2" ParentId="4075" CreationDate="2023-11-07T02:04:20.520" Score="5" Body="&lt;p&gt;Time-dependent density functional theory (TDDFT) has indeed seen significant developments since its review in the classical paper you mentioned. One of the recent advancements in TDDFT is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Nonlinear Response Functions&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In the context of Time-Dependent Density Functional Theory (TDDFT), Nonlinear response functions refer to the exploration of phenomena beyond linear response properties. While traditional TDDFT focuses on linear response, there has been increasing interest in investigating nonlinear optical processes and strong light-matter interactions using TDDFT. This extension allows for the study of phenomena such as harmonic generation, two-photon absorption, and higher-order nonlinear optics. Nonlinear TDDFT has been applied to gain insights into materials with significant light-matter interactions. For example, a study &lt;a href=&quot;https://doi.org/10.1063/1.4867271&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.4867271&lt;/a&gt; published by Federico Zahariev and  Mark S. Gordon. in the Journal of Chemical Phyiscs (2014) titled &amp;quot;Nonlinear response time-dependent density functional theory combined with the effective fragment potential method&amp;quot; investigated the calculattio of the two-photon absorption cross section and incorporated solvent effects via the EFP method. The nonlinear-response TDDFT/EFP method was shown to be  able to make correct qualitative predictions for both gas phase values and aqueous solvent shifts of several important nonlinear properties. The package that was used in this study was GAMESS.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Among the challenges in realizing the simulation of real materials with TDDFT, strongly correlated systems is challenging.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Strongly correlated systems pose a challenge for TDDFT due to the intricate electron-electron interactions involved. Examples of such systems include transition metal complexes and strongly correlated materials, where the standard TDDFT approach may not be sufficient to capture their properties accurately. To address the treatment of strongly correlated systems within TDDFT, researchers have explored advanced theoretical approaches, such as the combination of TDDFT with dynamical mean-field theory (DMFT). This hybrid approach aims to incorporate the effects of strong electron-electron correlations, which are crucial for accurately describing the electronic structure and excited states of these systems.&#xA;A study &lt;a href=&quot;https://doi.org/10.1103/PhysRevLett.106.116401&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevLett.106.116401&lt;/a&gt; published by Daniel Karlsson et al. in Physical Review Letters (2011) titled &amp;quot;Time-Dependent Density-Functional Theory Meets Dynamical Mean-Field Theory: Real-Time Dynamics for the 3D Hubbard Model&amp;quot;. The authors proposed a new class of exchange-correlation potentials for a static and time-dependent density-functional theory of strongly correlated systems in three-dimensions&#xA;Those studies exemplify the ongoing efforts to develop theoretical approaches that extend TDDFT to treat strongly correlated systems accurately. The combination of TDDFT with advanced methods like DMFT offers a promising avenue for understanding the electronic structure and excited states of materials with strong electron-electron correlations.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Regarding the most popular and successful package that implements TDDFT, there are several widely used software packages available, each with its own strengths and capabilities. Some of the popular packages include:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Gaussian: Widely used computational chemistry software that offers TD-DFT functionality. It provides a comprehensive suite of methods for studying excited-state properties, including UV/Vis spectra, fluorescence, and excited-state dynamics. Gaussian is known for its versatility and extensive user community.&lt;/li&gt;&#xA;&lt;li&gt;GPAW: GPAW (Generalized Projector Augmented Wave) is a popular electronic structure code that implements TDDFT. It is known for its efficiency and scalability, making it suitable for large-scale simulations.&lt;/li&gt;&#xA;&lt;li&gt;NWChem: NWChem is a computational chemistry package that includes TDDFT functionality. It offers a wide range of methods, including both TDDFT and GW calculations, making it versatile for studying excited-state properties.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-11-07T05:30:39.423" LastActivityDate="2023-11-07T05:30:39.423" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11864" PostTypeId="1" CreationDate="2023-11-07T03:02:47.253" Score="5" ViewCount="53" Body="&lt;p&gt;This is more of an opened discussion, recommendations, and experts views on the Strongly correlated materials.&#xA;Exploring the behavior of strongly correlated materials poses significant challenges in condensed matter physics. what are the theoretical frameworks and computational techniques used to accurately capture the intricate interplay of electron-electron interactions, spin dynamics, and lattice effects in these systems. Furthermore, what is the emerging role of machine learning and artificial intelligence in enhancing our understanding of complex phenomena such as high-temperature superconductivity and quantum magnetism. Provide specific examples of recent breakthroughs achieved through advanced matter modeling approaches that shed light on the fundamental physics underlying these intriguing materials.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2023-11-07T03:03:44.217" LastActivityDate="2023-11-07T03:03:44.217" Title="Strongly Correlated Materials: Theoretical Frameworks, Computational Techniques, and Machine Learning Breakthroughs in Matter Modeling" Tags="|one-topic-per-answer|condensed-matter|machine-learning|electron-correlation|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11865" PostTypeId="1" CreationDate="2023-11-07T06:31:44.857" Score="4" ViewCount="109" Body="&lt;p&gt;I've been using VASP for DFT calculations and came across with an adsorption energy value over &lt;span class=&quot;math-container&quot;&gt;$-8\,eV$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is this a reasonable value for S-H bond?&lt;/p&gt;&#xA;" OwnerUserId="8284" LastEditorUserId="24" LastEditDate="2023-11-07T16:20:58.417" LastActivityDate="2023-11-07T16:22:09.383" Title="Can adsorption energy be upto -8 eV for VOC adsorption in MoS2 layer?" Tags="|vasp|adsorption|energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11866" PostTypeId="2" ParentId="11865" CreationDate="2023-11-07T06:55:45.963" Score="5" Body="&lt;p&gt;From my own experience of calculating adsorption energy of small molecules on the surface of TMDs, an adsorption energy of -8 eV for an S-H bond in DFT calculation using VASP sounds unusually high and potentially unrealistic.&lt;/p&gt;&#xA;&lt;p&gt;Such a large negative value of -8 eV suggests an extremely strong interaction between the adsorbate and the surface, which is unlikely for VOCs on the surface of MoS2, where most of the interatcion is coming from vdW forces.&lt;/p&gt;&#xA;&lt;p&gt;In general, adsorption energies for weakly bound species like molecular adsorbates on surfaces are often in the range of a few tenths to a few eV. There could be several reasons for such a large and negative adsorption energy.&lt;/p&gt;&#xA;&lt;p&gt;It is possible that there are errors in the calculation, such as convergence issues, inadequate basis set, or improper treatment of the system. It is also possible that the interaction between the S-H bond and the surface is being overestimated due to the limitations of the exchange-correlation functional used in the DFT calculation.&lt;/p&gt;&#xA;&lt;p&gt;To confirm the validity of the result, I would recommend you to share your input files so people can help you find out more about the problem you are facing.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="24" LastEditDate="2023-11-07T16:22:09.383" LastActivityDate="2023-11-07T16:22:09.383" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11867" PostTypeId="1" CreationDate="2023-11-07T13:22:46.870" Score="2" ViewCount="53" Body="&lt;p&gt;I am trying to calculate the free energy of adsorption of a small molecule on a 2D material. After adsorption, I am using the thermochemistry module of the Atomic Simulation Environment to calculate the free energy of the structures. I'm following the example shown &lt;a href=&quot;https://ritumsc.github.io/Ase_vib/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, where the Harmonic approximation has been used.&lt;/p&gt;&#xA;&lt;p&gt;However, this approximation returns the Helmholtz Free energy. From the documentation of &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/thermochemistry/thermochemistry.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;ASE thermochemistry module&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;This class returns the Helmholtz free energy; if the user assumes the pV term (in H = U + pV) is zero this can also be interpreted as the Gibbs free energy.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is the free energy obtained from this approximation useful for plotting free energy diagrams for reactions?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Any input provided would be highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="4373" LastEditorUserId="5" LastEditDate="2023-11-07T13:49:50.440" LastActivityDate="2023-11-07T13:49:50.440" Title="What is the best model to calculate the free energies using ASE thermochemistry?" Tags="|vasp|quantum-espresso|atomic-simulation-environment|thermodynamics|free-energy|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11868" PostTypeId="2" ParentId="11861" CreationDate="2023-11-07T16:16:43.590" Score="5" Body="&lt;p&gt;Creating a structure is not a trial-and-error process. Here are some tips you can use.&lt;/p&gt;&#xA;&lt;p&gt;From the Supplementary Data of the article you used, in section 2, Table S1, the authors gave the data for the cell parameters (vectors &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$b$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt;), as well as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Wyckoff_positions&quot; rel=&quot;noreferrer&quot;&gt;Wyckoff positions&lt;/a&gt; (in fractional coordinates) for the three Te atoms in the unit cell:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$a=(5.428, 0.000, 0.000)$&lt;/span&gt;&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$b=(0.000, 4.126, 0.000)$&lt;/span&gt;&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$c=(0.540 0.000 16.526)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Wyckoff positions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$Te1=(0.662, 0.000, 0.436)$&lt;/span&gt;&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$Te2=(0.338, 0.000, 0.564)$&lt;/span&gt;&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$Te3=(0.000, 0.500, 0.500)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;With the information above, you can manually create a CIF file and then, load it in VESTA for visualization.&#xA;(Note: A &lt;a href=&quot;https://doi.org/10.1107/S0108768102003464&quot; rel=&quot;noreferrer&quot;&gt;CIF&lt;/a&gt; file is a text file with all the information needed to visualize a crystal. Following its format, you can create it using any plain text editor like Notepad, Nano, VIM, etc.).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-11-07T16:16:43.590" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11869" PostTypeId="1" AcceptedAnswerId="12118" CreationDate="2023-11-07T19:48:48.630" Score="4" ViewCount="248" Body="&lt;p&gt;I'm a little confused with the order and flags needed to start the calculation with HSE06. Below is a step-by-step guide to what I've done so far.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Obs: I use GGA&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;For DOS&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Step (I) - Structure relaxation (my, INCAR without HSE flags):&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;pre&gt;&lt;code&gt;Lattice Relaxation&#xA;NSW    =  300          (number of ionic steps)&#xA;ISMEAR =  0            (gaussian smearing method )&#xA;SIGMA  =  0.2         (please check the width of the smearing)&#xA;IBRION =  2            (Algorithm: 0-MD, 1-Quasi-New, 2-CG)&#xA;ISIF   =  3            (optimize atomic coordinates and lattice parameters)&#xA;EDIFFG = -1.5E-02      (Ionic convergence, eV/A)&#xA;PREC   =  Accurate     (Precision level)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;&lt;strong&gt;Question: GGA = PE Is it necessary in this step (I) and also in the next step (II)?&lt;/strong&gt;&lt;/h3&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Step (II) - Run the SCF calculation to obtain the WAVECAR&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Step (III) - Run SCF for DOS + HSE:&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="8250" LastEditorUserId="5" LastEditDate="2023-11-07T19:52:49.563" LastActivityDate="2023-12-20T22:04:24.877" Title="HSE06 - dos + band structure calculation using VASP" Tags="|vasp|hse06|vaspkit|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11871" PostTypeId="1" CreationDate="2023-11-08T09:05:09.453" Score="6" ViewCount="52" Body="&lt;p&gt;What factors can cause convergence issues in VASP calculations and how can they be avoided when creating the POSCAR file? Additionally, could you provide information about the recommended number of processor groups for a VASP job?&lt;/p&gt;&#xA;" OwnerUserId="8284" LastEditorUserId="1554" LastEditDate="2023-11-08T12:06:11.803" LastActivityDate="2023-11-08T12:06:11.803" Title="What key considerations should be kept in mind when creating a VASP POSCAR file?" Tags="|vasp|" AnswerCount="0" CommentCount="1" ClosedDate="2024-03-22T20:29:11.823" ContentLicense="CC BY-SA 4.0" />
  <row Id="11872" PostTypeId="1" CreationDate="2023-11-08T09:15:03.627" Score="2" ViewCount="113" Body="&lt;p&gt;I am now working with VESTA and need to hide certain polyhedra for plotting purposes.&#xA;I am having trouble selecting single and groups of polyhedra though, as the program selects a random other object of the same nature.&lt;/p&gt;&#xA;&lt;p&gt;Anyone has an idea why this may be happening? I tried updating the graphics drivers already as indicated here &lt;a href=&quot;https://groups.google.com/g/vesta-discuss/c/5YY3aPS_C5A&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://groups.google.com/g/vesta-discuss/c/5YY3aPS_C5A&lt;/a&gt;, but to no improvement.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="8297" LastActivityDate="2023-11-08T09:15:03.627" Title="VESTA object selection not working reliably" Tags="|vesta|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11873" PostTypeId="1" AcceptedAnswerId="11985" CreationDate="2023-11-08T18:48:46.913" Score="1" ViewCount="199" Body="&lt;p&gt;I am following the deepmd-kit documentation to implement this kit into a plugin version of LAMMPS, the documentation I am using is found &lt;a href=&quot;https://docs.deepmodeling.com/projects/deepmd/en/master/install/install-from-source.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://docs.deepmodeling.com/projects/deepmd/en/master/install/install-lammps.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. I am close to completing everything, but am having issues when trying to install the deepmd-kit C++ interface. I know from the documentation, I need to run the line:&lt;/p&gt;&#xA;&lt;p&gt;cmake -DUSE_TF_PYTHON_LIBS=TRUE -DCMAKE_INSTALL_PREFIX=$deepmd_root ..&lt;/p&gt;&#xA;&lt;p&gt;And I also know that for the plugin version of LAMMPS, I need to include the cmake argument into the command above; -DLAMMPS_SOURCE_ROOT=/path/to/lammps/source. What I have done for this step is that I cd'd into the LAMMPS folder until I could see all of the folders containing the source code, and I defined the variable lammps_src='pwd'. So all in all, I am using the command:&lt;/p&gt;&#xA;&lt;p&gt;cmake -DUSE_TF_PYTHON_LIBS=TRUE -DLAMMPS_SOURCE_ROOT=lammps_src -DCMAKE_INSTALL_PREFIX=$deepmd_root ..&lt;/p&gt;&#xA;&lt;p&gt;This process runs until it finds the LAMMPS folder, makes the header, and tries to find the version of LAMMPS I have, and am met with the error message that I have attached as an image.&lt;a href=&quot;https://i.stack.imgur.com/tCXlw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tCXlw.png&quot; alt=&quot;Error message&quot; /&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Looking through the LAMMPS source code, I am able to see that the LAMMPSUtils.cmake file does actually exist. Seeing that this process can actually find the LAMMPS folder, I am unsure why it cannot find this file&lt;/p&gt;&#xA;&lt;p&gt;Looking at the second error with the unknown cmake command... I searched for the CMakeLists.txt file it mentioned, and found these commands&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/s5aFP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s5aFP.png&quot; alt=&quot;cmake commands&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;From my understanding, the cmake job is supposed to look for a file named version.h in the LAMMPS source folder, but that file does not exist. I know that this shouldn't be an issue of the version of the libraries/packages I have installed. The relevant ones that I have are deepmd-kit v2.2.7, cmake v3.27.7, and tensorflow 2.14.0. The LAMMPS version I cloned is the Aug 2023 update 1 release that was mentioned in the documentation I followed. It is at this point where I do not know what to do to try and remove these issues, so any insight is welcome!&lt;/p&gt;&#xA;" OwnerUserId="8065" LastEditorUserId="5" LastEditDate="2023-11-29T19:21:54.370" LastActivityDate="2023-11-29T19:22:10.283" Title="Issue building deepmd kit for a plugin version of LAMMPS" Tags="|molecular-dynamics|lammps|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11874" PostTypeId="2" ParentId="11816" CreationDate="2023-11-09T02:20:51.620" Score="2" Body="&lt;p&gt;A colleague shared with me that the energy VASP outputs does seem to include &lt;code&gt;E_p&lt;/code&gt;, since different &lt;code&gt;LAMBDA&lt;/code&gt; gave her different energies. This suggests that VASP does not subtract &lt;code&gt;E_p&lt;/code&gt; from the output energy, meaning that what we have is likely to be: &lt;span class=&quot;math-container&quot;&gt;$E_{OUTCAR}=E_0+E_p$&lt;/span&gt;. The energy representing the system will thus be: &lt;span class=&quot;math-container&quot;&gt;$E_{OUTCAR}-$&lt;/span&gt;&lt;code&gt;E_p&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1766" LastActivityDate="2023-11-09T02:20:51.620" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11875" PostTypeId="1" CreationDate="2023-11-09T12:52:03.033" Score="3" ViewCount="59" Body="&lt;p&gt;I am trying to calculate the XPS spectra using the ICORELEVEL method in VASP, both using initial and final state approaches, for C1s and F1s electrons. My systems are single molecules.&#xA;However, my results are too off to be of any use. First, is this approach correct for molecular systems (I have seen this previously being used for bulk systems)?&lt;/p&gt;&#xA;" OwnerUserId="1137" LastEditorUserId="5" LastEditDate="2023-11-09T15:48:05.633" LastActivityDate="2023-11-09T15:48:05.633" Title="How do I calculate XPS spectra for molecules to match experimental spectra?" Tags="|density-functional-theory|vasp|spectroscopy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11876" PostTypeId="1" AcceptedAnswerId="11877" CreationDate="2023-11-10T00:26:14.587" Score="7" ViewCount="313" Body="&lt;p&gt;Much of the information I find is about super-cells. What about for a single unit cell? Is it necessary to add a vacuum space?&lt;/p&gt;&#xA;" OwnerUserId="8250" LastEditorUserId="5" LastEditDate="2023-11-10T00:55:04.560" LastActivityDate="2023-11-10T00:55:04.560" Title="For a single unit cell calculation, is it necessary to add a vacuum?" Tags="|vesta|supercell|vacuum-potential|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11877" PostTypeId="2" ParentId="11876" CreationDate="2023-11-10T00:35:14.730" Score="6" Body="&lt;p&gt;In a single unit cell calculation, the inclusion of vacuum space depends on the specific requirements and characteristics of your system. Here are a few situations that you should consider about adding vacuum space:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Surface effects: If your system has significant surface effects or interactions between neighboring unit cells, adding vacuum space can help minimize these effects. Vacuum acts as a buffer to reduce the interactions between periodic images of your system.&lt;/li&gt;&#xA;&lt;li&gt;Simulating isolated systems: If you are interested in simulating an isolated molecule or a small cluster, adding vacuum is not necessary since there are no neighboring unit cells to consider. In this case, you can omit the vacuum space.&lt;/li&gt;&#xA;&lt;li&gt;Computational efficiency: Including a large vacuum region can significantly increase the computational cost of your calculation. If your system does not require a large vacuum, it may be more efficient to reduce the vacuum size to a minimum while still ensuring that the interactions between periodic images are negligible.&lt;/li&gt;&#xA;&lt;li&gt;Accuracy of XPS calculations: For XPS calculations, it is generally recommended to include enough vacuum space to minimize surface effects and to accurately simulate the interaction between the photoelectron and the material. However, the specific vacuum size required may depend on the system and the level of accuracy desired.&lt;/li&gt;&#xA;&lt;li&gt;Monolayers: In 2D materials, if you want to study a single monolayer, then you will need to add enough vacuum space between the repeating images so that you simulate an isolated single layer of that 2D material, otherwise you will be dealing with the bulk version of that material or structure.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-10T00:35:14.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11878" PostTypeId="1" AcceptedAnswerId="11886" CreationDate="2023-11-10T03:19:48.337" Score="2" ViewCount="182" Body="&lt;p&gt;In my VASP calculations, I am interested in simultaneously optimizing both the lattice parameters and atomic positions of my system.&#xA;I understand that using ISIF = 3 allows for relaxation of both atomic positions and cell shape/volume, while ISIF = 4 keeps the volume fixed during relaxation. However, I'm unsure about the implications of choosing one over the other in terms of accuracy and reliability.&lt;/p&gt;&#xA;&lt;p&gt;Can someone shed light on the differences between ISIF = 3 and ISIF = 4 and provide guidance on which option would be more appropriate for accurately capturing the optimized structure? Are there specific scenarios or materials where one option is preferred over the other? Any insights or experiences would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-10T22:07:27.863" Title="Optimal choice between ISIF = 3 and ISIF = 4 for lattice parameter and atomic position relaxation in VASP calculations" Tags="|density-functional-theory|vasp|geometry-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11879" PostTypeId="1" CreationDate="2023-11-10T05:00:59.883" Score="5" ViewCount="60" Body="&lt;p&gt;In a molecular geometry calculation using a Gaussian program, can I see changes in bond lengths or changes in structure when one electron enters the molecule through a reduction reaction?&lt;/p&gt;&#xA;&lt;p&gt;for example, I want to see reduction of Benezene.&lt;/p&gt;&#xA;&lt;p&gt;First, optimize Bezene structure.&#xA;calculation setup to Optimize(job type) and Ground state, DFT, Default spin, B3LYP(method), 6-31G, ++(2d,p), charge 0&lt;/p&gt;&#xA;&lt;p&gt;After that, I proceeded with the calculation in the same way, but with charge set to -1.&lt;/p&gt;&#xA;&lt;p&gt;Is it correct way to see change of Benzene structure after reduction?&lt;/p&gt;&#xA;" OwnerUserId="8312" LastEditorUserId="8312" LastEditDate="2023-11-14T09:49:02.550" LastActivityDate="2023-11-14T11:26:36.033" Title="Is it possible to predict reduction reaction products with a Gaussian program?" Tags="|quantum-chemistry|gaussian|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11880" PostTypeId="1" CreationDate="2023-11-10T09:10:54.497" Score="3" ViewCount="132" Body="&lt;p&gt;I want to read a lammps data file in ASE, for instance the &lt;a href=&quot;https://docs.lammps.org/Howto_tip3p.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;TIP3P&lt;/a&gt; or the &lt;a href=&quot;https://docs.lammps.org/Howto_spc.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SPC&lt;/a&gt; model. The lammps examples provide the input script and the data file, which work perfectly.&lt;/p&gt;&#xA;&lt;p&gt;ASE is not able to read the &lt;code&gt;.mol&lt;/code&gt; file: it cannot parse neither &lt;code&gt;Shake ***&lt;/code&gt; nor &lt;code&gt;Shake ***&lt;/code&gt; section of the lammps-data files. Thus I removed them, but even then &lt;code&gt;UnboundLocalError: local variable 'mol_id_in' referenced before assignment&lt;/code&gt;. Finally I wrote my own file, which can be read - see it at the bottom.&lt;/p&gt;&#xA;&lt;p&gt;Once the file is read, I set and apply a &lt;code&gt;LammpsLib&lt;/code&gt; calculator with exactly the same inputs as in the Lammps tutorial, and I receive a &lt;code&gt;Exception: ERROR: Boundary command after simulation box is defined (src/input.cpp:1414)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I think that the parsing messes up the order of information.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: How can I see what is the input file that is fed to lammps?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Read file&#xA;&#xA;import ase.io&#xA;from ase.calculators.lammpslib import LAMMPSlib&#xA;&#xA;water = ase.io.read('water.mol', format='lammps-data')&#xA;&#xA;lammps_orig_header = [&#xA;    'units real',&#xA;    'atom_style full',&#xA;    'region box block -5 5 -5 5 -5 5',&#xA;    'create_box 2 box  bond/types 1 angle/types 1 extra/bond/per/atom 2 extra/angle/per/atom 1 extra/special/per/atom 2'&#xA;    ]&#xA;&#xA;lammps_orig_commands = [&#xA;    'mass 1 15.9994',&#xA;    'mass 2 1.008',&#xA;    &#xA;    'pair_style lj/cut/coul/cut 10.0',&#xA;    'pair_coeff 1 1 0.1553 3.166',&#xA;    'pair_coeff 1 2 0.0    1.0',&#xA;    'pair_coeff 2 2 0.0    1.0',&#xA;    &#xA;    'bond_style zero',&#xA;    'bond_coeff 1 1.0',&#xA;    &#xA;    'angle_style zero',&#xA;    'angle_coeff 1 109.47',&#xA;    &#xA;    'molecule water spce.mol',&#xA;    'create_atoms 0 random 33 34564 NULL mol water 25367 overlap 1.33',&#xA;    &#xA;    'timestep 1.0',&#xA;    'fix rigid     all shake 0.0001 10 10000 b 1 a 1',&#xA;    'minimize 0.0 0.0 1000 10000',&#xA;    'velocity all create 300.0 5463576',&#xA;    'fix integrate all nvt temp 300.0 300.0 100.0',&#xA;    &#xA;    'thermo_style custom step temp press etotal density pe ke',&#xA;    'thermo 1000',&#xA;    'run 20000 upto',&#xA;    'write_data spce.data nocoeff'&#xA;    ]&#xA;&#xA;lammps = LAMMPSlib( lammps_header=lammps_orig_header,lmpcmds=lammps_orig_commands,log_file='test.log')&#xA;&#xA;# Set calculator and calculate energy&#xA;water.set_calculator(lammps)&#xA;water.get_potential_energy()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;---------------------------------------------------------------------------&#xA;Exception                                 Traceback (most recent call last)&#xA;Cell In[1], line 49&#xA;     47 # Set calculator and calculate energy&#xA;     48 water.set_calculator(lammps)&#xA;---&amp;gt; 49 water.get_potential_energy()&#xA;&#xA;File ~/WORK/external_packages/ase/ase/atoms.py:737, in Atoms.get_potential_energy(self, force_consistent, apply_constraint)&#xA;    734     energy = self._calc.get_potential_energy(&#xA;    735         self, force_consistent=force_consistent)&#xA;    736 else:&#xA;--&amp;gt; 737     energy = self._calc.get_potential_energy(self)&#xA;    738 if apply_constraint:&#xA;    739     for constraint in self.constraints:&#xA;&#xA;File ~/WORK/external_packages/ase/ase/calculators/abc.py:24, in GetPropertiesMixin.get_potential_energy(self, atoms, force_consistent)&#xA;     22 else:&#xA;     23     name = 'energy'&#xA;---&amp;gt; 24 return self.get_property(name, atoms)&#xA;&#xA;File ~/WORK/external_packages/ase/ase/calculators/calculator.py:537, in BaseCalculator.get_property(self, name, atoms, allow_calculation)&#xA;    534     if self.use_cache:&#xA;    535         self.atoms = atoms.copy()&#xA;--&amp;gt; 537     self.calculate(atoms, [name], system_changes)&#xA;    539 if name not in self.results:&#xA;    540     # For some reason the calculator was not able to do what we want,&#xA;    541     # and that is OK.&#xA;    542     raise PropertyNotImplementedError(&#xA;    543         '{} not present in this ' 'calculation'.format(name)&#xA;    544     )&#xA;&#xA;File ~/WORK/external_packages/ase/ase/calculators/lammpslib.py:360, in LAMMPSlib.calculate(self, atoms, properties, system_changes)&#xA;    359 def calculate(self, atoms, properties, system_changes):&#xA;--&amp;gt; 360     self.propagate(atoms, properties, system_changes, 0)&#xA;&#xA;File ~/WORK/external_packages/ase/ase/calculators/lammpslib.py:381, in LAMMPSlib.propagate(self, atoms, properties, system_changes, n_steps, dt, dt_not_real_time, velocity_field)&#xA;    379     self.start_lammps()&#xA;    380 if not self.initialized:&#xA;--&amp;gt; 381     self.initialise_lammps(atoms)&#xA;    382 else:  # still need to reset cell&#xA;    383     # NOTE: The whole point of ``post_changebox_cmds`` is that they're&#xA;    384     # executed after any call to LAMMPS' change_box command.  Here, we&#xA;   (...)&#xA;    391     # apply any shrink-wrapping *after* it's updated the cell&#xA;    392     # dimensions&#xA;    393     if 'pbc' in system_changes:&#xA;&#xA;File ~/WORK/external_packages/ase/ase/calculators/lammpslib.py:668, in LAMMPSlib.initialise_lammps(self, atoms)&#xA;    666             break&#xA;    667     else:&#xA;--&amp;gt; 668         self.lmp.command('boundary ' + self.lammpsbc(atoms))&#xA;    670 # Initialize cell&#xA;    671 self.set_cell(atoms, change=not self.parameters.create_box)&#xA;&#xA;File ~/miniconda3/envs/pgel/lib/python3.10/site-packages/lammps/core.py:617, in lammps.command(self, cmd)&#xA;    614 if cmd: cmd = cmd.encode()&#xA;    615 else: return&#xA;--&amp;gt; 617 with ExceptionCheck(self):&#xA;    618   self.lib.lammps_command(self.lmp,cmd)&#xA;&#xA;File ~/miniconda3/envs/pgel/lib/python3.10/site-packages/lammps/core.py:49, in ExceptionCheck.__exit__(self, exc_type, exc_value, traceback)&#xA;     47 def __exit__(self, exc_type, exc_value, traceback):&#xA;     48   if self.lmp.has_exceptions and self.lmp.lib.lammps_has_error(self.lmp.lmp):&#xA;---&amp;gt; 49     raise self.lmp._lammps_exception&#xA;&#xA;Exception: ERROR: Boundary command after simulation box is defined (src/input.cpp:1414)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Water molecule. TIP3P geometry&#xA;&#xA;3 atoms&#xA;2 bonds&#xA;1 angles&#xA;&#xA;Coords&#xA;&#xA;1    0.00000  -0.06556   0.00000&#xA;2    0.75695   0.52032   0.00000&#xA;3   -0.75695   0.52032   0.00000&#xA;&#xA;Types&#xA;&#xA;1        1   # O&#xA;2        2   # H&#xA;3        2   # H&#xA;&#xA;Charges&#xA;&#xA;1       -0.834&#xA;2        0.417&#xA;3        0.417&#xA;&#xA;Bonds&#xA;&#xA;1   1      1      2&#xA;2   1      1      3&#xA;&#xA;Angles&#xA;&#xA;1   1      2      1      3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="6687" LastEditDate="2023-11-12T07:43:40.980" LastActivityDate="2023-11-12T07:43:40.980" Title="Read and run lammps water model in ASE" Tags="|molecular-dynamics|python|lammps|atomic-simulation-environment|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11881" PostTypeId="1" CreationDate="2023-11-10T09:44:02.950" Score="2" ViewCount="80" Body="&lt;p&gt;I want to simulate some water in MD with ASE and a LammpsLib calculator.&lt;/p&gt;&#xA;&lt;p&gt;I set up a minimal Lammps calculator and I try to calculate the energy per atom of an isolated molecule, and a 3x3x3 supercell. I get different energies.&#xA;&lt;strong&gt;Question 1: How is it possible?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Moreover, when I try to optimize either system, the cell explodes reaching crazy high forces and energy oscillating of several orders of magnitude. &lt;strong&gt;Question 2: Is my Lammps calculator complete?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Perhaps some &lt;code&gt;fix&lt;/code&gt;?&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.calculators.lammpslib import LAMMPSlib&#xA;&#xA;lammps_header=[&#xA;    'units metal',&#xA;    'boundary p p p',&#xA;    'atom_style full'&#xA;    ]&#xA;&#xA;lmpcmds = [&#xA;    'mass 1 15.9994',&#xA;    'mass 2 1.008',&#xA;    'set type 1 charge -0.834',&#xA;    'set type 2 charge 0.417',&#xA;    'pair_style lj/cut/coul/long 8.0', &#xA;    'pair_coeff 1 1 0.1521 3.1507', &#xA;    'pair_coeff 2 2 0.0    1.0', &#xA;    'kspace_style pppm 1.0e-4',&#xA;    'minimize 0.0 0.0 1000 10000'&#xA;]&#xA;&#xA;lammps = LAMMPSlib( lammps_header=lammps_header,lmpcmds=lmpcmds )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import molecule&#xA;&#xA;cell_size = 3.&#xA;water = molecule('H2O', vacuum=3.0)&#xA;water.set_cell([cell_size, cell_size, cell_size])&#xA;water.set_pbc([True, True, True])&#xA;&#xA;# Set calculator and calculate energy&#xA;water.set_calculator(lammps)&#xA;water.get_potential_energy()/len(water.numbers) # = -2.901683325464138&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.build &#xA;&#xA;# Define the supercell&#xA;sxcell_size = 3&#xA;sxcell_matrix = [[sxcell_size, 0, 0],&#xA;                 [0, sxcell_size, 0],&#xA;                 [0, 0, sxcell_size]]&#xA;sxcell = ase.build.make_supercell(water, sxcell_matrix)&#xA;&#xA;# Set calculator and calculate energy&#xA;sxcell.set_calculator(lammps)&#xA;sxcell.get_potential_energy()/len(sxcell.numbers) # = -0.0899526348900734&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.optimize&#xA;&#xA;dyn = ase.optimize.BFGS(water)&#xA;dyn.run(fmax=1)&#xA;&#xA;&amp;gt; Step     Time          Energy          fmax&#xA;&amp;gt; BFGS:    0 10:40:43       -8.705050        5.815941&#xA;&amp;gt; BFGS:    1 10:40:43       -9.953564        7.020505&#xA;&amp;gt; ...&#xA;&amp;gt; BFGS:  176 10:40:45   -17347.959238 60056340.171811&#xA;&amp;gt; BFGS:  177 10:40:45    -4428.006468  3905232.089535&#xA;&amp;gt; ...&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2023-11-10T09:44:02.950" Title="Water simulation in ASE/LAMMPS" Tags="|lammps|atomic-simulation-environment|cell-optimization|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11882" PostTypeId="1" AcceptedAnswerId="12414" CreationDate="2023-11-10T15:23:15.983" Score="3" ViewCount="60" Body="&lt;p&gt;I am looking for CHARMM36 parameters for Neutral Arginine. Protonated form of Argnine is already available in CHARMM36 library, but not the same for Neutral. Thanks.&lt;/p&gt;&#xA;&lt;p&gt;With best regards&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2024-02-16T19:58:13.267" Title="CHARMM36 Parameters for Neutral Arginine" Tags="|gromacs|charmm|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11883" PostTypeId="1" CreationDate="2023-11-10T19:38:17.023" Score="3" ViewCount="195" Body="&lt;p&gt;I am trying to do DFT+U calculation for the material BaLaMn2O6 . As per the vaspwiki it is recommended to set &lt;code&gt;LMAXMIX = 4&lt;/code&gt; (d-elements) and &lt;code&gt;LMAXMIX = 6&lt;/code&gt; (for f-elements) to obtain fast convergence to ground state. In my situation, I have both f-block element(La) and d-block element (Mn).&lt;/p&gt;&#xA;&lt;p&gt;How should I set the &lt;code&gt;LMAXMIX&lt;/code&gt; tag in the DFT+U calculation in proper way?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;INCAR file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Global Parameters\&#xA;ISTART =  1            (Read existing wavefunction; if there)\&#xA;LREAL  = Auto          (Projection operators: automatic)\&#xA;ENCUT  =  600        (Cut-off energy for plane wave basis set, in eV)\&#xA;PREC   =  High       (Precision level)\&#xA;LWAVE  = .TRUE.        (Write WAVECAR or not)\&#xA;LCHARG = .TRUE.        (Write CHGCAR or not)\&#xA;ADDGRID= .TRUE.        (Increase grid; helps GGA convergence)\&#xA;EDIFF = 1.0E-06 \&#xA;ALGO=Fast\&#xA;Lattice Relaxation\&#xA;NSW    =  55          (number of ionic steps. Make it odd.)\&#xA;ISMEAR =  0            (gaussian smearing method )\&#xA;SIGMA  =  0.05         (please check the width of the smearing)\&#xA;IBRION =  2            (Algorithm: 0-MD; 1-Quasi-New; 2-CG)\&#xA;ISIF   =  2            (optimize atomic coordinates and lattice parameters)\&#xA;EDIFFG = -1.0E-03      (Ionic convergence; eV/AA)\&#xA;PREC   =  High         (Precision level)\&#xA;\&#xA;LDAU = True             #switches on DFT+U  \&#xA;LDAUJ = 0 0 0 0         # J values (For LDAUTYPE=2 , Ueff = U-J)\&#xA;LDAUL = 3 -1 2 -1       #l-quantum number (-1 : no U)\&#xA;LDAUPRINT = 1           # 0:silent, 1: write occupancy matrix to OUTCAR)\ &#xA;LDAUTYPE = 2            #The simplified approach to the DFT+U , introduced by  Dudarev et al.\&#xA;LDAUU = 4.0 0 3.0 0     # for Ba:0 , Mn:5.0 , Sb:0, F:0 ( U values in eV) \&#xA;LMAXMIX = 6             # 4 for d-electrons, 6 for f-electrons\&#xA;LASPH = .TRUE.   \&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;POSCAR file&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;generated by phonopy\&#xA;   1.0\&#xA;     3.9178000000000002    0.0000000000000000    0.0000000000000000\&#xA;     0.0000000000000000    3.9178000000000002    0.0000000000000000\&#xA;     0.0000000000000000    0.0000000000000000    7.8070000000000004\&#xA;La Ba Mn O\&#xA;   1    1    2    6\&#xA;Direct\&#xA;  0.0000000000000000  0.0000000000000000  0.0000000000000000\&#xA;  0.0000000000000000  0.0000000000000000  0.5000000000000000\&#xA;  0.5000000000000000  0.5000000000000000  0.7548999999999999\&#xA;  0.5000000000000000  0.5000000000000000  0.2451000000000001\&#xA;  0.5000000000000000  0.5000000000000000  0.0000000000000000\&#xA;  0.0000000000000000  0.5000000000000000  0.7626999999999999\&#xA;  0.5000000000000000  0.0000000000000000  0.7626999999999999\&#xA;  0.0000000000000000  0.5000000000000000  0.2373000000000001\&#xA;  0.5000000000000000  0.0000000000000000  0.2373000000000001\&#xA;  0.5000000000000000  0.5000000000000000  0.5000000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8321" LastEditorUserId="7" LastEditDate="2023-11-16T02:12:40.313" LastActivityDate="2023-11-27T00:26:06.083" Title="How to set the LMAXMIX tag in VASP for the material BaLaMn2O6?" Tags="|density-functional-theory|vasp|dft-u|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="11884" PostTypeId="1" AcceptedAnswerId="11887" CreationDate="2023-11-10T20:29:01.037" Score="4" ViewCount="209" Body="&lt;p&gt;I am currently working on implementing a material model in an Abaqus UMAT. The code is structured like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MODULE FUNCTIONS&#xA;CONTAINS&#xA;&#xA;FUNCTION GET_A(...) RESULT (A)&#xA;  IMPLICIT NONE&#xA;! ... some variable declarations&#xA;  DOUBLE PRECISION :: A&#xA;&#xA;! ... some code&#xA;&#xA;END FUNCTION&#xA;&#xA;FUNCTION GET_B(...) RESULT (B)&#xA;  IMPLICIT NONE&#xA;! ... some variable declarations&#xA;  DOUBLE PRECISION, DIMENSION(n) :: B&#xA;  DOUBLE PRECISION :: DUMMY_VAR, GET_A&#xA;&#xA;  DUMMY_VAR = GET_A(...)&#xA;! ... some code&#xA;&#xA;END FUNCTION&#xA;&#xA;&#xA;END MODULE FUNCTIONS&#xA;&#xA;&#xA;SUBROUTINE UMAT(...)&#xA;! ... a lot of definitions&#xA;! ... a lot of code&#xA;&#xA;END SUBROUTINE UMAT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't think it matters, but the imaginary function 'GET_B' is supposed to return an array. If a function does not depend on another function, I can call it from the UMAT without a problem. If I try to run the schematic UMAT from above I will get a compiler error similar to&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;UMAT.obj : error LNK2019: unresolved external symbol get_a referenced in function functions_mp_get_b.R&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I read somewhere, that I am not supposed to declare the type of 'GET_A' within 'GET_B'. When I do that and change the code to&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MODULE FUNCTIONS&#xA;CONTAINS&#xA;&#xA;FUNCTION GET_A(...) RESULT (A)&#xA;  IMPLICIT NONE&#xA;! ... some variable declarations&#xA;  DOUBLE PRECISION :: A&#xA;&#xA;! ... some code&#xA;&#xA;END FUNCTION&#xA;&#xA;FUNCTION GET_B(...) RESULT (B)&#xA;  IMPLICIT NONE&#xA;! ... some variable declarations&#xA;  DOUBLE PRECISION, DIMENSION(n) :: B&#xA;  DOUBLE PRECISION :: DUMMY_VAR&#xA;&#xA;  DUMMY_VAR = GET_A(...)&#xA;! ... some code&#xA;&#xA;END FUNCTION&#xA;&#xA;&#xA;END MODULE FUNCTIONS&#xA;&#xA;&#xA;SUBROUTINE UMAT(...)&#xA;! ... a lot of definitions&#xA;! ... a lot of code&#xA;&#xA;END SUBROUTINE UMAT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the error changes to&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;UMAT.f(some_line): error #6404: This name does not have a type, and must have an explicit type.   [GET_A]&#xA;DUMMY_VAR = GET_A(...)&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;What can I do to call 'GET_A' from 'GET_B' (both functions are in the some module)? Do I need to put the return type of a function before the 'FUNCTION' statement? Since I am used to using the 'RESULT (...)' statement, I usually declare the type in the function body.&#xA;If it helps to post the full code here, I will do so. I just thought that putting a schematic code here will help to cause too much confusion.&lt;/p&gt;&#xA;&lt;p&gt;Edit: I uploaded the full code to this &lt;a href=&quot;https://github.com/Extraweich/Nonlinear_Kelvin_Voigt_UMAT&quot; rel=&quot;nofollow noreferrer&quot;&gt;repository&lt;/a&gt; on git, where I also added the .log file for the precise error. I hope somebody can help me with this.&lt;/p&gt;&#xA;" OwnerUserId="4197" LastEditorUserId="4197" LastEditDate="2023-11-10T21:34:37.060" LastActivityDate="2023-11-10T23:35:30.037" Title="Abaqus UMAT [Fortran]: how to call a function from another function without getting &quot;unresolved external symbol&quot;" Tags="|fortran|abaqus|" AnswerCount="1" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11885" PostTypeId="1" CreationDate="2023-11-10T21:13:15.603" Score="5" ViewCount="75" Body="&lt;p&gt;Broadly given two electron charge density (ECD) fields, is it possible to distinguish between the elements present in both the systems?&lt;/p&gt;&#xA;&lt;p&gt;Since the ECD does not explicitly present any information on the species present in the system. Is there a possibility that two ECDs exist with similar structures and totally different number of valence electrons, but consist of slightly or vastly different elemental species?&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="1554" LastEditDate="2023-11-12T07:44:28.737" LastActivityDate="2023-11-12T07:44:28.737" Title="Can the electron charge density of two material systems be similar?" Tags="|density-functional-theory|vasp|solid-state-physics|charge-density|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11886" PostTypeId="2" ParentId="11878" CreationDate="2023-11-10T22:07:27.863" Score="6" Body="&lt;p&gt;You've already summarized the differences in your question, but to be complete: ISIF=3 has an additional degree of freedom that allows the cell volume to change. In principle, there should be no difference in what the final relaxed structure will be. So another way of asking this question might be, what type of relaxations require my cell volume to be fixed?&lt;/p&gt;&#xA;&lt;p&gt;Here are some suggestions based on my own experiences.&lt;/p&gt;&#xA;&lt;p&gt;Situations where ISIF=3 is &lt;strong&gt;NOT&lt;/strong&gt; acceptable:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculations with vacuum (slabs or molecules). This is the most important one. Especially in slab calculations, allowing the cell volume to change will almost always result in your vacuum being reduced to zero (cell becomes periodic).&lt;/li&gt;&#xA;&lt;li&gt;Calculations where the equilibrium cell volume has already been optimized prior to relaxation. Often times bulk calculations with varying cell volumes and little to no relaxation will be performed to find the bulk lattice parameter by fit to an equation of state. There are many Equations of State, the Materials Project has a nice table summarizing some of them &lt;a href=&quot;https://docs.materialsproject.org/methodology/materials-methodology/equations-of-state&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Calculations of materials under strain. Allowing the volume to change can result in the strain relaxing out.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Situations where I recommend ISIF=4 over ISIF=3:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;During calculations to determine a fit to an Equation of State. These should have fixed volume throughout the calculation, although each individual calculation differs in volume.&lt;/li&gt;&#xA;&lt;li&gt;Initial relaxation in systems where the equilibrium lattice parameter is unknown. I find that there is a significant speedup if I manually sample lattice parameters first to get close to equilibrium before allowing the volume itself to change in the simulation.&lt;/li&gt;&#xA;&lt;li&gt;Relaxation when the forces in your system are large (&amp;gt;2 eV/Å). In my experience ISIF=3 can lead to bad convergence. Relax with ISIF=4 first and then switch to ISIF=3 if you'd like.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Situations where I recommend ISIF=3 over ISIF=4:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;When you desire a very accurate total volume. I would do this after finding a relaxed structure at a lower ENCUT first.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hopefully other members of the community can also give you more advice based on their experiences!&lt;/p&gt;&#xA;" OwnerDisplayName="user8097" LastActivityDate="2023-11-10T22:07:27.863" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11887" PostTypeId="2" ParentId="11884" CreationDate="2023-11-10T23:35:30.037" Score="4" Body="&lt;p&gt;Just to wrap this up, the error wound being that &lt;code&gt;GET_B&lt;/code&gt; wasn't calling &lt;code&gt;GET_A&lt;/code&gt;, but rather &lt;code&gt;GET_A0&lt;/code&gt;, a typo of &lt;code&gt;GET_A&lt;/code&gt; which didn't exist and caused the compilation failure.&lt;/p&gt;&#xA;&lt;p&gt;Some nice little debugging take aways that I have learned (and still have to remind myself to actually follow through with):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Try to reduce the bug down to as small an example as possible. This can help to avoid X/Y problems where you think the big is caused by X (function calling another function), but it's really due to Y (typo in function name).&lt;/li&gt;&#xA;&lt;li&gt;Once you have narrowed it down as much as you can, use this as your test bed for determining the bug or as an example that someone else can run to reproduce the bug. This is for similar reasons to 1, where if you narrow in too much on a possible cause, you may make it impossible for someone else to reproduce the problem.&lt;/li&gt;&#xA;&lt;li&gt;Programming bugs tend to be boring, to the point where they are easier to overlook. Far more (though by no means all) of the bugs I have created have been simple typos, transpositions of function arguments, missing or not run functions calls, etc rather than messed up algorithm design or some tricky quirk of the programming language. I'll many times jump to trying some elaborate testing to determine the cause of bug, when I would be better served just doing basic sanity checks.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-11-10T23:35:30.037" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11888" PostTypeId="1" CreationDate="2023-11-11T10:23:58.083" Score="1" ViewCount="86" Body="&lt;p&gt;I am trying calculate a strain-induced phase transition in some weakly correlated crystalline material using Quantum ESPRESSO (QE). The compound has two (experimentally observed) phases, one of which is a high temperature cubic phase and the other being hexagonal (present down to cryogenic temperatures). Calculating the energies under &lt;em&gt;isotropic&lt;/em&gt; compression and fitting a common tangent to the curves, I find a moderate transition pressure of &lt;span class=&quot;math-container&quot;&gt;$700\,\mathrm{MPa}$&lt;/span&gt;. I would now like to calculate whether a similar transition occurs under uniaxial strain &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt;, but I'm unsure about the correct methodology for this.&lt;br /&gt;&#xA;Currently I converge the cutoff energy, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point grid and the smearing energy, relax both structures in the variable cell approach and then apply uniaxial strain using &lt;span class=&quot;math-container&quot;&gt;$\epsilon = \frac{a-a_0}{a_0}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$a_0$&lt;/span&gt; is the relaxed lattice parameter and &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; is the lattice parameter under strain. Now I am unsure about how to continue:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Perform an scf-calculation with the strained structure?&lt;/li&gt;&#xA;&lt;li&gt;Do a relaxation calculation, but keep the lattice parameters constant, moving just the atoms? (&lt;code&gt;relax&lt;/code&gt; in QE)&lt;/li&gt;&#xA;&lt;li&gt;Perform a variable cell relaxation, keeping the strained lattice parameter &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; constant? (&lt;code&gt;vc-relax&lt;/code&gt; with &lt;code&gt;cell_dofree = 'fixa'&lt;/code&gt;)&lt;/li&gt;&#xA;&lt;li&gt;Something else&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Afterwards I would plot the energy per atom in the unit cell and see if at some point the energy of the ambient pressure phase becomes higher than the energy of the high temperature phase (similarly to Fig. 4 of &lt;a href=&quot;https://doi.org/10.1007/s12274-014-0626-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; reference). Is this a correct approach?&lt;/p&gt;&#xA;" OwnerUserId="8328" LastEditorUserId="5" LastEditDate="2023-12-19T20:07:04.163" LastActivityDate="2023-12-19T20:07:04.163" Title="Structural phase transition under uniaxial strain" Tags="|quantum-espresso|geometry-optimization|stress-strain|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11889" PostTypeId="2" ParentId="4154" CreationDate="2023-11-11T12:47:31.930" Score="2" Body="&lt;p&gt;Adding to wzkchem5's answer, you might also consider using &lt;a href=&quot;https://quanty.org/start&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quanty&lt;/a&gt;. The program is a many body script language based on Lua that allows you to calculate XAS, NIXS and RIXS spectra, among other things. In Quanty there are different levels of theory one can use, ranging from crystal field theory over ligand field theory to a post DFT-treatment. Citing from the website:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;It can be used in quantum chemistry as post Hartree-Fock or in one of the LDA++ schemes. (self consistent field, configuration interaction, coupled cluster, restricted active space, …)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The notation is based on second quantization, so custom operators can be implemented in a way that is close to the way one would write them down (for more information you can check the &lt;a href=&quot;https://quanty.org/documentation/start&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;On &lt;a href=&quot;https://quanty.org/documentation/tutorials/nio_crystal_field/start&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; example page you can find calculations of the XAS and RIXS spectra of NiO, so the code is suitable for correlated materials as well. Built into Quanty are functions that allow you to interface with the DFT code &lt;a href=&quot;https://www.fplo.de/&quot; rel=&quot;nofollow noreferrer&quot;&gt;FPLO&lt;/a&gt; (see the program of &lt;a href=&quot;https://www.quanty.org/workshop/heidelberg/september_2018/programme?s%5B%5D=fplo&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; workshop for presentations and worked out examples).&lt;/p&gt;&#xA;&lt;p&gt;In my experience, the program has a nice learning curve and the installation is quite easy as well. Using it on a computational cluster works rather well. After registration, the code is free to use and download (&lt;a href=&quot;https://www.quanty.org/how_to_cite&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; you can see how to cite its use).&lt;/p&gt;&#xA;" OwnerUserId="8328" LastActivityDate="2023-11-11T12:47:31.930" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11890" PostTypeId="1" CreationDate="2023-11-11T17:24:08.677" Score="1" ViewCount="31" Body="&lt;p&gt;I'm seeking clarification on the selection of suitable boundary conditions for simulating shear deformation of a screw dislocation using LAMMPS. In my script, I currently employ the following commands:&lt;/p&gt;&#xA;&lt;p&gt;lammps&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix 1 upper setforce 0.0 0.0 0.0 &#xA;fix 2 lower setforce 0.0 0.0 0.0 &#xA;fix 3 upper move NULL ${strainrate} NULL&#xA;fix 4 lower move NULL-${strainrate} NULL&#xA;fix 5 mobile nve&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have several uncertainties:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/B3oWN.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/B3oWN.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;Should I fix all three degrees of freedom in fix 1 &amp;amp; 2 for shear deformation in the Y direction, or are specific degrees of freedom recommended?&lt;/p&gt;&#xA;&lt;p&gt;In fix 3 &amp;amp; 4, should I use NULL or 0.0?&lt;/p&gt;&#xA;&lt;p&gt;Should fix 5 be applied to only middle atoms or to all atoms?&lt;/p&gt;&#xA;&lt;p&gt;Any insights would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="8330" LastActivityDate="2023-11-11T17:24:08.677" Title="What are the appropriate boundary conditions for simulating shear deformation of a screw dislocation in LAMMPS?" Tags="|molecular-dynamics|lammps|" AnswerCount="0" CommentCount="0" ClosedDate="2023-12-20T03:21:15.090" ContentLicense="CC BY-SA 4.0" />
  <row Id="11892" PostTypeId="1" CreationDate="2023-11-11T18:53:33.617" Score="5" ViewCount="517" Body="&lt;p&gt;How do I modify the input file below to calculate the charge density (DENS) using Quantum Espresso?&lt;/p&gt;&#xA;&lt;p&gt;Input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  title='Compound 4:bulk:(Si 2)(Ca)(P 3)(O 14):hP(4):P3 (143):primitive:230.81', &#xA;  calculation='scf', &#xA;  pseudo_dir='./', &#xA;  outdir='./tmp', &#xA;  verbosity='high',&#xA;  tprnfor=.true., &#xA;  tstress=.true., &#xA;  forc_conv_thr=1.0d-4, &#xA;  nstep=100,&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0, nat= 20, ntyp= 4, &#xA;  occupations = 'smearing', smearing = 'gauss', degauss = 1.0d-2,&#xA;  ecutwfc = 50, ecutrho = 500,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;  press_conv_thr=0.1&#xA;/&#xA;ATOMIC_SPECIES&#xA;Si     28.08550  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Ca     40.07800  Ca.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;P      30.97376  P.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   4.7132930000  0.0000000000  0.0000000000&#xA;  -2.3566465000  4.0818314735  0.0000000000&#xA;   0.0000000000  0.0000000000 11.9970890000&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Si            0.0000000000        0.0000000000       -0.0157540426&#xA;O             0.3299136474        0.0545324986        0.0595401725&#xA;O             0.9454675014        0.2753811489        0.0595401725&#xA;O             0.7246188511        0.6700863526        0.0595401725&#xA;P             0.6666670000        0.3333330000        0.0987976560&#xA;O             0.6666670000        0.3333330000        0.2113501434&#xA;Ca            0.6666670000        0.3333330000        0.3706146451&#xA;O             0.1992673103       -0.1108239995        0.4380418511&#xA;O             1.1108239995        0.3100913098        0.4380418511&#xA;O             0.6899086902        0.8007326897        0.4380418511&#xA;Si           -0.0000000000       -0.0000000000        0.5320360071&#xA;O             0.2891646956        0.3289811702        0.6093561073&#xA;O             0.0398164747        0.7108353044        0.6093561073&#xA;O             0.6710188298        0.9601835253        0.6093561073&#xA;P             0.3333330000        0.6666670000        0.6406709519&#xA;O             0.3333330000        0.6666670000        0.7561974923&#xA;P             0.3333330000        0.6666670000        0.8748653332&#xA;O             0.2739498732        0.3264620877        0.9034691403&#xA;O             0.0525122146        0.7260501268        0.9034691403&#xA;O             0.6735379123        0.9474877854        0.9034691403&#xA;K_POINTS {automatic}&#xA;  6 6 2 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="24" LastEditDate="2023-11-11T20:22:29.713" LastActivityDate="2023-11-14T03:08:12.143" Title="How to calculate the charge density using Quantum Espresso?" Tags="|density-functional-theory|quantum-espresso|charge-density|electron-density|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11893" PostTypeId="1" CreationDate="2023-11-12T00:53:44.830" Score="3" ViewCount="60" Body="&lt;p&gt;During a geometrical optimization of ions and lattice parameters in VASP, the forces acting on atoms were minimized to less than 0.01 eV/Å. However, when performing the subsequent self-consistent field (SCF) calculation using the optimized geometry 'CONTCAR', the forces printed in the OUTCAR file were found to be larger than the specified force convergence criteria used during the relaxation process.&lt;/p&gt;&#xA;&lt;p&gt;The main inputs in the INCAR file for geometrical relaxation and SCF step are almost the same. Is that a normal behavior? What are the possible reasons for this discrepancy?&lt;/p&gt;&#xA;&lt;p&gt;The following is the INCAR file for Geometrical Relaxtion:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;ICHARG = 2&#xA;NELM   = 100&#xA;EDIFF  = 1E-6&#xA;ENCUT  = 400&#xA;ALGO   = Fast&#xA;IBRION = 2&#xA;ISIF   = 4&#xA;POTIM  = 0.5&#xA;NSW    = 300&#xA;EDIFFG = -0.01&#xA;ISMEAR = 0&#xA;SIGMA  = 0.05&#xA;PREC   = Accurate&#xA;LREAL  = Auto&#xA;LWAVE  = .F.&#xA;LCHARG = .F.&#xA;GGA    = PE&#xA;IVDW   = 11&#xA;ISYM   = 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;while the INCAR file for the SCF calculation is the folloing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0&#xA;ICHARG = 2&#xA;NELM = 100&#xA;EDIFF = 1E-6&#xA;ENCUT = 400&#xA;ALGO = Fast&#xA;IBRION = -1&#xA;ISIF = 2&#xA;POTIM = 0.5&#xA;NSW = 0&#xA;EDIFFG = -0.01&#xA;ISMEAR = -5&#xA;SIGMA = 0.2&#xA;PREC = Normal&#xA;ISPIN = 2&#xA;LREAL = .F.&#xA;LWAVE = .T.&#xA;LCHARG = .T.&#xA;LAECHG = .TRUE.&#xA;LDIPOL = .T.&#xA;IDIPOL = 3&#xA;GGA  = PE&#xA;IVDW = 11&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-11-12T06:55:18.923" LastActivityDate="2023-11-12T06:55:18.923" Title="Discrepancy between Force Convergence in Geometrical Optimization and SCF Calculation in VASP: Reasons and Troubleshooting Suggestions" Tags="|density-functional-theory|vasp|geometry-optimization|self-consistent-field|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11894" PostTypeId="1" CreationDate="2023-11-12T04:58:22.003" Score="4" ViewCount="104" Body="&lt;p&gt;I'm currently working on calculating semiempirical local and nonlocal matrix elements for Ga. To proceed with my calculations, I need to extract specific parameters  from the UPF (Unified Pseudopotential Format) file for Ga. I've encountered challenges in this process. I haven't found a solution yet. If anyone has insights or suggestions on how to efficiently read and extract the required parameters from a UPF pseudopotential file for Ga on FORTRAN, I would greatly appreciate your assistance. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="749" LastEditorUserId="749" LastEditDate="2023-11-12T08:36:08.523" LastActivityDate="2023-12-14T03:08:16.037" Title="How to read UPF pseudopotential for ultrasoft pseudopotential simple in a fortran program" Tags="|density-functional-theory|quantum-espresso|electronic-structure|condensed-matter|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11895" PostTypeId="2" ParentId="11654" CreationDate="2023-11-12T08:20:06.673" Score="2" Body="&lt;p&gt;&lt;strong&gt;First&lt;/strong&gt;, the energy correction term, &lt;span class=&quot;math-container&quot;&gt;$E_{corr}$&lt;/span&gt;.&#xA;It arises due to presence of periodic boundary conditions (defects are spuriously repeated) and of background charge compensation (hidden from the user). There are several correction schemes, but all of them requires the knowledge of the dielectric constant of the system:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Generally used &amp;quot;FNV&amp;quot; scheme &lt;a href=&quot;https://doi.org/10.1103/physrevlett.102.016402&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/physrevlett.102.016402&lt;/a&gt;, &lt;a href=&quot;https://doi.org/10.1103/physrevb.89.195205&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/physrevb.89.195205&lt;/a&gt;;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Easier to use Lany and Zunger scheme &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.78.235104&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.78.235104&lt;/a&gt; (requires Madelung constant &lt;span class=&quot;math-container&quot;&gt;$\alpha_M$&lt;/span&gt; of the crystal).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Second&lt;/strong&gt;, potential alignment term (PA, &lt;span class=&quot;math-container&quot;&gt;$\Delta V$&lt;/span&gt;). Never seen such, looks like a compensation of imperfectness of DFT band energies (in particular, VBM).&lt;/p&gt;&#xA;&lt;p&gt;UPD: formula from Lany and Zunger suitable for calculation&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{corr} \approx \frac{2}{3} \frac{\alpha_M q^2} {\varepsilon L}$&lt;/span&gt;,&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; is the size of the cell (in Angstrom), &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; - charge (in e), &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt; - dielectric constant. Resulted energy is in eV.&lt;/p&gt;&#xA;" OwnerUserId="6566" LastEditorUserId="6566" LastEditDate="2023-11-25T10:06:31.407" LastActivityDate="2023-11-25T10:06:31.407" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11899" PostTypeId="1" CreationDate="2023-11-13T14:26:39.527" Score="4" ViewCount="163" Body="&lt;p&gt;In my program Chemcraft, a popular tool is the “Set point group” utility: it symmetrizes the molecule according to a specified point group, and then the symmetry of the molecule is correctly recognized by a program like Gaussian, and this makes the computation faster. Maybe chemists dealing with crystals need something similar?&lt;/p&gt;&#xA;&lt;p&gt;If I understand correctly, the routine for determining periodic boundary conditions through 3 lattice vectors does not fully describe the crystal symmetry, for example in graphene only 1 symmetry unique carbon atom exists while with cell parameters a=2.4,..beta=90, gamma=120 the program thinks that there are two carbons in the primitive cell. Currently the programs like VASP do not use these additional symmetry constraints? If, nevertheless, they use them, how they can be specified in the input file, and do you think that automatic determination of these constraints by Chemcraft will be useful for its users?&lt;/p&gt;&#xA;&lt;p&gt;I have found here that the Avogadro and Pymol programs can do that, maybe I will be able to implement a more flexible tool in Chemcraft, and still it is unclear for me, whether these routines in Avogadro and PyMol determine the &amp;quot;full&amp;quot; or &amp;quot;partial&amp;quot; symmetry as I described above.&lt;/p&gt;&#xA;" OwnerUserId="3745" LastEditorUserId="5" LastEditDate="2023-11-13T16:30:42.987" LastActivityDate="2023-11-13T18:01:54.700" Title="Can a tool “Set space group” be useful?" Tags="|crystallography|symmetry|space-groups|avogadro|chemcraft|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11900" PostTypeId="2" ParentId="11899" CreationDate="2023-11-13T18:01:54.700" Score="4" Body="&lt;p&gt;Determining space group symmetry is really useful when going between a CIF (which typically only includes the symmetry-unique atoms) and a calculation (which typically includes all atoms in the unit cell).&lt;/p&gt;&#xA;&lt;p&gt;Many programs, including Avogadro, use the excellent &lt;a href=&quot;https://spglib.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;spglib&lt;/code&gt;&lt;/a&gt; library to determine space groups, generate a primitive unit cell from a &amp;quot;filled&amp;quot; cell, etc. It's very similar to using the various point-group detection and symmetrization routines.&lt;/p&gt;&#xA;&lt;p&gt;There are a few pitfalls - for one, space group symbols are less standardized than point group symbols. In general, Avogadro 2 uses the &amp;quot;Hall number&amp;quot; internally, which indicates not only the space group symbol, but the setting. This has helped enormously. Even so, I've come across a few weird CIF files recently.&lt;/p&gt;&#xA;&lt;p&gt;You asked about &amp;quot;full&amp;quot; or &amp;quot;partial&amp;quot; symmetry. I think you mean converting from a primitive to a conventional unit cell and vice versa? Yes, this is an important task (e.g., opening a CIF for silver will only have one atom).&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-11-13T18:01:54.700" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11901" PostTypeId="1" AcceptedAnswerId="11902" CreationDate="2023-11-13T18:20:08.757" Score="4" ViewCount="644" Body="&lt;p&gt;I am new to this field and after going through some tutorials I was making band structure diagram of Silicon as shown in figure below, and the Fermi energy I got from SCF calculation is 6.208 eV.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/kPnK3.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kPnK3.png&quot; alt=&quot;si band structure&quot; /&gt;&lt;/a&gt; However in academic articles the Fermi energy in band structure lies at 0 on y-axis, same was said by my professor but how does that make sense if Fermi energy is 6.208 eV then, how it will be at 0 on y axis?&lt;/p&gt;&#xA;" OwnerUserId="8346" LastEditorUserId="24" LastEditDate="2023-11-13T18:40:15.487" LastActivityDate="2023-11-13T19:35:11.220" Title="Fermi Energy in Band Structure" Tags="|density-functional-theory|quantum-espresso|band-structure|fermi-energy|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11902" PostTypeId="2" ParentId="11901" CreationDate="2023-11-13T19:35:11.220" Score="11" Body="&lt;p&gt;In electronic structure calculations of &lt;em&gt;finite&lt;/em&gt; systems, there is a well-defined energy scale: 0 is the vacuum energy, and any electron with positive energy is unbound.&lt;/p&gt;&#xA;&lt;p&gt;For materials, the story is different. There is no fixed vacuum level (it's obtainable from the work function for your material, but it differs depending on your system). If you were to calculate the band structure with different density functional approximations (LDA, PBE, HSE06, ...), different pseudopotentials, and so on, you'd get a different answer for the Fermi energy each time.&lt;/p&gt;&#xA;&lt;p&gt;So for consistency across calculations (and, maybe even more so, across papers), it's traditional to offset the energy axis by some constant so that the Fermi energy, or the conduction band minimum, or whatever, is zero. That shift doesn't matter for energy differences, and there is no privileged absolute scale, so there isn't really a problem with doing so. In particular, for comparing (say) silicon band structure across calculation methods, it's nice to have one energy level that's the same across all the methods, so that you can see what's stretched, squeezed, and shifted by comparison.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-11-13T19:35:11.220" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11903" PostTypeId="2" ParentId="11894" CreationDate="2023-11-14T02:48:47.127" Score="1" Body="&lt;p&gt;For now, the UPF standard is defined &lt;a href=&quot;https://pseudopotentials.quantum-espresso.org/home/unified-pseudopotential-format&quot; rel=&quot;nofollow noreferrer&quot;&gt;on &lt;code&gt;Quantum ESPRESSO&lt;/code&gt;'s website&lt;/a&gt;. Looks like the documentation is for an XML-like format, but it will be (or has already been, that documentation is pretty old) converted to true XML later. If you really want to read the file as-is, that may be enough. An actual XML reader like &lt;a href=&quot;https://github.com/Fortran-FOSS-Programmers/FoXy&quot; rel=&quot;nofollow noreferrer&quot;&gt;FoXy&lt;/a&gt; (if your Fortran is &amp;gt;= 2008) might help.&lt;/p&gt;&#xA;&lt;p&gt;Failing that, &lt;code&gt;Quantum ESPRESSO&lt;/code&gt; deals with pseudopotential files with the &lt;code&gt;upflib&lt;/code&gt; directory, &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/tree/develop/upflib&quot; rel=&quot;nofollow noreferrer&quot;&gt;which you can read here&lt;/a&gt;. In particular, the files &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/upflib/write_upf_new.f90?ref_type=heads&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;write_upf_new.f90&lt;/code&gt;&lt;/a&gt; and &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/upflib/read_upf_new.f90?ref_type=heads&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;read_upf_new.f90&lt;/code&gt;&lt;/a&gt; look like they will more or less explain what you need! (They should read either the XML or the older 2.1 format of &lt;code&gt;upf&lt;/code&gt; files, too.)&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-11-14T02:48:47.127" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11904" PostTypeId="2" ParentId="11892" CreationDate="2023-11-14T03:08:12.143" Score="4" Body="&lt;p&gt;In recent versions of &lt;code&gt;Quantum ESPRESSO&lt;/code&gt; (I'm looking at 7.2), you likely already have a charge density file written. Inside your &lt;code&gt;outdir&lt;/code&gt;, there should be a directory with a name like &lt;code&gt;${title}.save/&lt;/code&gt;, with a file called &lt;code&gt;charge-density.dat&lt;/code&gt;. This is the density &lt;span class=&quot;math-container&quot;&gt;$\rho(\mathbf{G})$&lt;/span&gt;, stored in reciprocal space. Now, it's a binary file, so you can't look at it directly, but the file &lt;a href=&quot;https://gitlab.com/QEF/q-e/-/blob/develop/Modules/io_base.f90&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;Modules/io_base.f90&lt;/code&gt;&lt;/a&gt; has a subroutine called &lt;code&gt;write_rhog()&lt;/code&gt; that describes the format with which it's written, and another one called &lt;code&gt;read_rhog()&lt;/code&gt; that you could use to re-obtain it.&lt;/p&gt;&#xA;&lt;p&gt;If you don't want to futz around with the source code, you can also use the &lt;code&gt;pp.x&lt;/code&gt; executable to print the (valence pseudo-)density to a file, &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PP.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;using &lt;code&gt;plot_num = 0&lt;/code&gt;&lt;/a&gt; in the input file. If you need the all-electron density, you can &lt;em&gt;technically&lt;/em&gt; get it by using projector augmented-waves instead of normal pseudopotentials, an enormous kinetic energy cutoff, and &lt;code&gt;plot_num = 17&lt;/code&gt; (for the valence all-electron density) or &lt;code&gt;21&lt;/code&gt; (if you need the core as well).&lt;sup&gt;*&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sub&gt;* But at that point you'd be better off using an all-electron code, because the whole point of pseudopotentials is to avoid dealing with the core density in the first place.&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-11-14T03:08:12.143" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11905" PostTypeId="1" CreationDate="2023-11-14T03:46:42.607" Score="4" ViewCount="56" Body="&lt;p&gt;What could be the reason behind encountering noise at the starting point while using VASP with SOC for generating a band structure? Despite attempting various approaches such as increasing line resolution, modifying the K-path, and performing calculations on a single smooth intersection within a comprehensive job, the issue persists.&lt;/p&gt;&#xA;&lt;p&gt;Additionally, similar errors occur when attempting to generate the band structure using VASPKIT and Pyprocar. Is there any insight into the cause of this problem?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ZrzTt.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZrzTt.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/KIq0Z.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/KIq0Z.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Myd0n.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Myd0n.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8350" LastEditorUserId="1554" LastEditDate="2023-11-14T05:27:53.393" LastActivityDate="2023-11-14T05:27:53.393" Title="Noise in VASP Band Structure Generation with SOC" Tags="|vasp|band-structure|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11906" PostTypeId="1" CreationDate="2023-11-14T05:51:47.247" Score="2" ViewCount="50" Body="&lt;p&gt;How can band structures and Fermi surfaces calculated with Density Functional Theory (DFT) be effectively employed in the study of superconductivity?&lt;/p&gt;&#xA;&lt;p&gt;What are the key features or indications related to superconductivity that can be inferred from the calculated band structure or Fermi surface?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-14T05:51:47.247" Title="Utilizing DFT-Computed Band Structures in Solid Physics to Investigate Superconductivity: Clues and Indicators in Band Structures" Tags="|density-functional-theory|superconductivity|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11907" PostTypeId="2" ParentId="11879" CreationDate="2023-11-14T11:26:36.033" Score="4" Body="&lt;p&gt;Unless there is something I am misunderstanding, that should be fine. Just remember to change the multiplicity as well (technically, 'spin' is not part of a Gaussian input).&lt;/p&gt;&#xA;" OwnerUserId="7606" LastActivityDate="2023-11-14T11:26:36.033" CommentCount="0" CommunityOwnedDate="2023-11-14T13:33:46.593" ContentLicense="CC BY-SA 4.0" />
  <row Id="11908" PostTypeId="1" AcceptedAnswerId="11913" CreationDate="2023-11-14T13:02:40.273" Score="6" ViewCount="113" Body="&lt;p&gt;I have obtained a band structure plot (see image below) for a crystalline material. The Fermi level is set at the zero energy level. Based on the band structure, I am uncertain whether the material can be classified as metallic or semi-metallic.&lt;/p&gt;&#xA;&lt;p&gt;Could you please provide your opinion on the nature of the material? Do the valence and conduction bands touch at specific points or along specific lines below or above the Fermi level for a bandstructure to be considered semi-metallic? Does the small opening in Figure 2 along the Gamma-X line mean a band gap opening, or something else?&lt;/p&gt;&#xA;&lt;p&gt;Any insights or explanations regarding the conductivity properties would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;UPDATE: The band structure belongs to the same material, Figure 3 and is a close-up on the Gamma-X line shown in Figure 1, while Figure 4 is a close-up on Figure 2 case.&lt;/p&gt;&#xA;&lt;p&gt;Figure 1. &lt;a href=&quot;https://i.stack.imgur.com/uWjRr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uWjRr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Figure 2.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/RIzsq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RIzsq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Figure 3.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/lJ9jF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lJ9jF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Figure 4.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/jkF0V.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jkF0V.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-11-16T00:26:54.233" LastActivityDate="2023-11-19T11:56:21.803" Title="Determining the Nature of a Material's Band Structure: Metallic or Semi-Metallic?" Tags="|density-functional-theory|band-structure|bandgap|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11909" PostTypeId="1" AcceptedAnswerId="11915" CreationDate="2023-11-14T15:24:25.450" Score="6" ViewCount="107" Body="&lt;p&gt;I am currently engaged in reading a research paper that focuses on the computation of the Potential Energy Surfaces (PES) of excited states. Within this paper, there is a discussion about a concept called the &amp;quot;branching space&amp;quot; associated with conical intersections. Unfortunately, I am not familiar with this concept and the information provided in the corresponding Wikipedia article (&lt;a href=&quot;https://en.wikipedia.org/wiki/Conical_intersection&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Conical_intersection&lt;/a&gt;) is quite brief.&lt;/p&gt;&#xA;&lt;p&gt;I would greatly appreciate it if someone could kindly provide me with a more detailed explanation of the branching space and its significance in the context of conical intersections. Thank you in advance for your assistance.&lt;/p&gt;&#xA;" OwnerUserId="141" LastEditorUserId="1554" LastEditDate="2023-11-15T09:45:27.483" LastActivityDate="2023-12-04T17:20:52.867" Title="What is the branching space of a conical section?" Tags="|potential-energy-surface|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11910" PostTypeId="1" CreationDate="2023-11-14T20:46:16.293" Score="3" ViewCount="56" Body="&lt;p&gt;Actually I am trying to study the adsorption of Li or K on the sheet starting from the hexagon centre the system optimises with Li or (K) adsorbed over one of the Ge atoms and not remain at the centre.&lt;/p&gt;&#xA;&lt;p&gt;I tried different potentials, different cutoff, different k-points and different initial heights for the Li, but all these trials didn’t show that Li will remain at the centre.&lt;/p&gt;&#xA;&lt;p&gt;Can you suggest what causes this problem?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Nwf58.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Nwf58.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="8361" LastEditorUserId="8361" LastEditDate="2023-11-14T20:52:29.530" LastActivityDate="2023-11-15T00:07:52.603" Title="Adsorption of Li on GeC (optimization problem)" Tags="|density-functional-theory|vasp|molecular-dynamics|quantum-espresso|adsorption|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11911" PostTypeId="2" ParentId="11910" CreationDate="2023-11-15T00:07:52.603" Score="3" Body="&lt;p&gt;The adsorption energy of Li or K atoms on a GeC sheet is influenced by several factors, including the electronic structure, bonding interactions, and surface reactivity of the materials involved. If the adsorption energy is higher at other sites, the Li or K atom will preferentially adsorb at those locations rather than the hexagon center.&lt;/p&gt;&#xA;&lt;p&gt;The preference for Li to be adsorbed on top of Ge can be attributed to a couple of reasons. Firstly, Ge is less electronegative than C, indicating a lower affinity for electrons. In contrast, Li is a highly electropositive metal, resulting in a stronger electrostatic interaction between Li and Ge compared to Li and C. This stronger interaction leads to a higher adsorption energy for Li on Ge compared to Li on C.&lt;/p&gt;&#xA;&lt;p&gt;Another contributing factor is the atomic size. Ge is larger in size compared to C, while Li is a relatively small atom. The larger atomic size of Ge provides a larger surface area for interaction with Li, resulting in a stronger adsorption energy. On the other hand, the smaller size of C may lead to weaker interactions with Li.&lt;/p&gt;&#xA;&lt;p&gt;Considering these factors, it is likely that the preferable adsorption site for Li or K atoms is on top of the Ge atom, which helps explain the behavior observed in your system.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-15T00:07:52.603" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11912" PostTypeId="2" ParentId="6284" CreationDate="2023-11-15T10:13:50.197" Score="1" Body="&lt;p&gt;The reason why most molecular force fields stop at point charges and dipoles is &lt;em&gt;they're good enough&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;What we mean by &amp;quot;good enough&amp;quot; is for the electrostatic potential (ESP) around a classical molecular dynamics molecule to be similar enough to the actual ESP (calculated with quantum chemistry). A definitive early article on this is Dykstra's &lt;strong&gt;Electrostatic interaction potentials in molecular force fields&lt;/strong&gt; (Chem. Rev. 1993, 93, 7, 2339–2353; &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/cr00023a001&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;). It goes into significant detail about the accuracy and cost of higher-order moments; this is not just a matter of not having enough compute (if octopoles were worth talking about in 1993 they're worth talking about now!).&lt;/p&gt;&#xA;&lt;p&gt;This passage in particular is important:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Rather than&#xA;an exact representation, we seek only one that is correct in the regions of interest. Probably the separation distances where charge field representations need to be most accurate are those from just under the separations associated with van der Waals radii to about twice that distance. ... At closer separations the charge distributions will tend to overlap and make invalid the physical justification for classical electrostatic potentials, and at separations beyond this range the interaction energy and forces are all weak; accuracy in the far-off regions is not important for most force field&#xA;applications.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So the vast majority of molecular dynamics simulations are okay with point charges. Polarizable dipoles are especially valuable as a relatively cheap model for cooperative effects -- thus, polarisability can accurate capture both a relatively less bound dimer-in-vacuum and the more intensely interacting condensed phase. Higher-order moments, until now, were mostly of interest in people trying to predict IR spectra in silico. Of course, you could argue that the current wave of innovative ML models &lt;em&gt;is&lt;/em&gt; (in roundabout way) a fitting to the higher-order near-field octo-and-beyond multiples.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-11-15T10:13:50.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11913" PostTypeId="2" ParentId="11908" CreationDate="2023-11-15T14:21:41.630" Score="4" Body="&lt;p&gt;(Edited after discussion with the asker and seeing the zoomed-in band structures. A commenter suggested adding  Addison of hybrid functionals as a correction to the band gap underestimation of [semilocal] DFT.)&lt;/p&gt;&#xA;&lt;p&gt;Your material—both in Fig. 1/3 without and in Fig. 2/4 with spin-orbit coupling—is a &lt;strong&gt;semimetal&lt;/strong&gt;. The inset regions make it clear: there is a positive direct gap everywhere, though it's pretty close along the &lt;span class=&quot;math-container&quot;&gt;$\Gamma \to X$&lt;/span&gt; line. However, there is a small region of the Brillouin zone where valence bands are above the Fermi energy, and another where conduction bands pass below it. This is exactly how Wikipedia &lt;a href=&quot;https://en.wikipedia.org/wiki/Semimetal&quot; rel=&quot;nofollow noreferrer&quot;&gt;characterizes semimetals&lt;/a&gt;, as &amp;quot;negative indirect-gap semiconductors&amp;quot;: the conduction band minimum is below the valence band maximum, but somewhere else in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;-space.&lt;/p&gt;&#xA;&lt;p&gt;If you can do a &lt;a href=&quot;https://en.wikipedia.org/wiki/Density_of_states&quot; rel=&quot;nofollow noreferrer&quot;&gt;density of states&lt;/a&gt; calculation, having negligible density at &lt;span class=&quot;math-container&quot;&gt;$E_F$&lt;/span&gt; will support the semimetal conclusion. That said, the direct gap is so small that I wouldn't be surprised if the material has pretty strongly metallic character anyway.&lt;sup&gt;*&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;p&gt;As an aside, &lt;em&gt;topological semimetals&lt;/em&gt; seem to be more in the spotlight lately, and their definition is somewhat different: They have valence and conduction bands that meet at isolated points on the Fermi surface. See, for instance, the top answer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/432&quot;&gt;this question&lt;/a&gt; and Assumption 2.5 in the &lt;a href=&quot;https://arxiv.org/abs/2002.01990v1&quot; rel=&quot;nofollow noreferrer&quot;&gt;arXiv preprint&lt;/a&gt; it mentions. These include Weyl and Dirac semimetals; a famous example is graphene, with its &lt;a href=&quot;https://en.wikipedia.org/wiki/Dirac_cone&quot; rel=&quot;nofollow noreferrer&quot;&gt;gapless points linear in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sub&gt;* Although your question tag suggests your calculation uses DFT. If you're using a standard (semilocal) functional, it &lt;a href=&quot;https://doi.org/10.1002/qua.560280846&quot; rel=&quot;nofollow noreferrer&quot;&gt;almost certainly underestimates the band gap&lt;/a&gt;, so the true behavior is likely to be &amp;quot;less metallic&amp;quot; than your computation predicts. More expensive methods like DFT+&lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;, Koopmans–compliant functionals, hybrid functionals including a fraction of Hartree–Fock exchange, and &lt;span class=&quot;math-container&quot;&gt;$GW$&lt;/span&gt; are likely to improve the quantitative band structure.&#xA;&lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="1393" LastEditorUserId="1393" LastEditDate="2023-11-19T11:56:21.803" LastActivityDate="2023-11-19T11:56:21.803" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11914" PostTypeId="1" AcceptedAnswerId="11933" CreationDate="2023-11-16T08:55:56.327" Score="3" ViewCount="133" Body="&lt;p&gt;I would like to print out the off diagonal components of the full stress tensor in ASE. The goal is then to calculate the Green Kubo viscosity. One should use the ensemble average of the off diagonal stress tensor.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Q1: Should I use the cell stress or the per-atom stress?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am trying different calculators (&lt;code&gt;GPAW&lt;/code&gt;, &lt;code&gt;EMT&lt;/code&gt; and &lt;code&gt;XTB&lt;/code&gt;) but none is able to print &lt;code&gt;atoms.get_stresses()&lt;/code&gt;. They all give me this result: &lt;code&gt;stresses property not implemented&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Q2: Is there a way to print out the full stress tensor in ASE?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Q3: Is there a table that lists which calculators can output it?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Please find an example with water in PBC below.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;import ase.build&#xA;&#xA;&#xA;# EMT&#xA;from ase.calculators.emt import EMT&#xA;calculator = EMT()&#xA;&#xA;# XTB&#xA;from xtb.ase.calculator import XTB&#xA;calculator = XTB(method=&amp;quot;GFN0-xTB&amp;quot;)&#xA;&#xA;# GPAW&#xA;from gpaw import GPAW, PW&#xA;calculator = GPAW(xc='PBE', mode=PW(300), txt='h2o.txt')&#xA;&#xA;atoms = ase.build.molecule('H2O')&#xA;cell_size = 2.8&#xA;atoms.set_cell([cell_size, cell_size, cell_size])&#xA;atoms.set_pbc([True, True, True])&#xA;&#xA;# Apply the calculator&#xA;atoms.set_calculator(calculator)&#xA;print(atoms)&#xA;print(calculator)&#xA;print(atoms.get_stress())&#xA;print(atoms.get_stresses())&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;Atoms(symbols='OH2', pbc=True, cell=[2.8, 2.8, 2.8], calculator=GPAW(...))&#xA;&amp;lt;gpaw.calculator.GPAW object at 0x7f72944f3d00&amp;gt;&#xA;[0.66560263 0.53795715 0.54856487 0.         0.         0.        ]&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/home/mdi0316/WORK_TME022/PGEL/forum_questions/print_stresses.py&amp;quot;, line 68, in &amp;lt;module&amp;gt;&#xA;    print(atoms.get_stresses())&#xA;  File &amp;quot;/home/mdi0316/miniconda3/envs/pgel/lib/python3.10/site-packages/ase/atoms.py&amp;quot;, line 865, in get_stresses&#xA;    stresses = self._calc.get_stresses(self)&#xA;  File &amp;quot;/home/mdi0316/miniconda3/envs/pgel/lib/python3.10/site-packages/ase/calculators/abc.py&amp;quot;, line 32, in get_stresses&#xA;    return self.get_property('stresses', atoms)&#xA;  File &amp;quot;/home/mdi0316/miniconda3/envs/pgel/lib/python3.10/site-packages/ase/calculators/calculator.py&amp;quot;, line 724, in get_property&#xA;    raise PropertyNotImplementedError('{} property not implemented'&#xA;ase.calculators.calculator.PropertyNotImplementedError: stresses property not implemented&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-11-20T10:38:07.653" LastActivityDate="2023-11-20T10:40:10.107" Title="Print full stress tensor in ASE to calculate Green Kubo viscosity" Tags="|python|atomic-simulation-environment|stress-strain|" AnswerCount="1" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="11915" PostTypeId="2" ParentId="11909" CreationDate="2023-11-16T15:38:28.367" Score="4" Body="&lt;p&gt;A paper called &amp;quot;Potential energy surfaces near intersections&amp;quot; [1] provides the answer.&lt;/p&gt;&#xA;&lt;p&gt;At the conical intersection, the energies of two potential energy surfaces parameterized by configuration coordinates &lt;span class=&quot;math-container&quot;&gt;$\{q_i : i = 1, \dots, N\}$&lt;/span&gt; are equal: say, &lt;span class=&quot;math-container&quot;&gt;$E_0(q_1, \dots, q_N) = E_1(q_1, \dots, q_N)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This intersection is not completely isolated. In a small region of configuration space near the intersection called the &lt;em&gt;intersection coordinate subspace&lt;/em&gt;,&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E_0(q_1, \dots, q_i + \delta, \dots, q_N) = E_1(q_1, \dots, q_i + \delta, \dots, q_N),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;for &lt;em&gt;most&lt;/em&gt;, but not all, of the coordinates &lt;span class=&quot;math-container&quot;&gt;$q_i$&lt;/span&gt;. (Think of &lt;span class=&quot;math-container&quot;&gt;$\delta$&lt;/span&gt; as a small perturbation.) One can argue by symmetry that this subspace has dimension &lt;span class=&quot;math-container&quot;&gt;$N - 2$&lt;/span&gt;, at least most of the time.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;The remaining two dimensions form the branching space&lt;/strong&gt;. If you like, the branching space is defined by the directions you can go to escape the energy degeneracy immediately. Visually, they should be the dimensions that look like a cone: both PES are degenerate and (locally) flat in all other directions!&lt;/p&gt;&#xA;&lt;p&gt;[1] G. J. Atchity, S. S. Xantheas, and K. Ruedenberg. &lt;a href=&quot;https://doi.org/10.1063/1.461036&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;J. Chem. Phys.&lt;/em&gt; &lt;strong&gt;95&lt;/strong&gt;, 1861 (1991)&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-11-16T15:38:28.367" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11916" PostTypeId="1" CreationDate="2023-11-17T05:32:43.063" Score="3" ViewCount="31" Body="&lt;p&gt;Suppose that we have a bulk structure of a two-dimensional (2D) material,.e.g graphite, and we want to construct a single-wall carbon nanotube tube starting from this bulk structure.&lt;/p&gt;&#xA;&lt;p&gt;If we already have the total energy of the bulk and the nanotube structures, will the following equation be correct to use for the calculation of formation energy:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Formation Energy = (E_tube - n * E_bulk) / n,&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;where E_tube is the total energy of the optimized nanotube structure, E_bulk is the total energy of the corresponding bulk material, and n is the number of carbon atoms in the unit cell of the nanotube.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-17T05:32:43.063" Title="Calculation of formation energy of a nanotube using DFT" Tags="|density-functional-theory|formation-energy|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11917" PostTypeId="1" CreationDate="2023-11-17T06:03:57.960" Score="4" ViewCount="78" Body="&lt;p&gt;&lt;strong&gt;TLDR:&lt;/strong&gt; DFT+U is a cheap scheme to help localize electrons on atomic orbitals by penalizing fractional occupancies of such orbitals. However, when one tries to localize an electron/hole on an atomic complex such as a dimer/trimer, this will fail badly since the electron/hole needs to be shared between several atoms (leading to fractional occupancies which DFT+U actively punishes instead of favorizing them). &lt;strong&gt;Is there a generalization of the DFT+U scheme that applies to localizing electrons on orbitals more complex than atomic orbitals?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;The DFT+U scheme for localizing electronic states:&lt;/h1&gt;&#xA;&lt;p&gt;Plain semilocal DFT (e.g. based on GGA or LDA) suffers from the infamous self-interaction error which tends to excessively delocalize electrons and unphysically favor metallic states.&lt;/p&gt;&#xA;&lt;p&gt;Many schemes have been proposed to correct for this. Hybrid functionals have been proven successful (providing correct tuning of the exact exchange fraction), but expensive. Another handy solution has been DFT+U, based on the Hubbard model from the tight-binding picture. In Dudarev's formulation, this amounts to adding a correction term to the total energy roughly of the form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_{DFT+U}=\frac{U_{eff}}{2}\sum_\sigma (Tr(n^\sigma-n^\sigma n^\sigma) )$$&lt;/span&gt;&#xA;Where &lt;span class=&quot;math-container&quot;&gt;$n^\sigma$&lt;/span&gt; is the occupation matrix for spin &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; of the atomic orbital we applied the Hubbard term to. Qualitatively, we see that this term can be thought of as a penalty term that will be minimized in the case of idempotency &lt;span class=&quot;math-container&quot;&gt;$n^\sigma = n^\sigma n^\sigma$&lt;/span&gt;. This corresponds to the case of an occupation matrix that will have integer eigenvalues (0 or 1, fully unoccupied or occupied)&lt;/p&gt;&#xA;&lt;p&gt;Long story short, this means that &lt;strong&gt;DFT+U will penalize fractional occupancies of atomic orbitals&lt;/strong&gt; and favor fully occupied or unoccupied states, helping to localize electrons on atomic orbitals. &lt;strong&gt;But what if I want to localize electrons (or holes), just not on atomic orbitals?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;The problem: localization on molecular-like orbitals&lt;/h1&gt;&#xA;&lt;p&gt;In my case, I am interested in modeling hole trapping on an &lt;span class=&quot;math-container&quot;&gt;$I_2^-$&lt;/span&gt; dimer. The problem is the following: &lt;strong&gt;localizing a single hole on a dimer means splitting the hole 50/50 between the orbitals of each I ion, meaning half occupancies on both orbitals, which is actively disfavored by DFT+U!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Sure enough, when experimenting with DFT+U, I do observe that higher U values actually go against hole localization in the case of a dimer, and we find ourselves in an awkward situation where DFT+U now promotes delocalized states in this configuration. Bad DFT+U.&lt;/p&gt;&#xA;&lt;p&gt;A tempting fix would be to use negative U values to favor half occupancies (or half vacancies in the case of a hole) of atomic orbitals on the dimer. However, this seems hard to justify physically in the context of the Hubbard model and seems too &lt;em&gt;ad-hoc&lt;/em&gt; to yield meaningful results.&lt;/p&gt;&#xA;&lt;p&gt;Another alternative would be to have more flexibility in the formulation of the Hubbard term, and instead of using the occupancy matrices of atomic orbitals  &lt;span class=&quot;math-container&quot;&gt;$n^\sigma$&lt;/span&gt;, formulating the penalty term in terms of some form of &amp;quot;molecular orbital occupancy&amp;quot; of the dimer  &lt;span class=&quot;math-container&quot;&gt;$n_{I_2^-}^\sigma$&lt;/span&gt;, so that the hole localization on a dimer orbital could be favored.&lt;/p&gt;&#xA;&lt;p&gt;Has this kind of thing been studied/developped before? &lt;strong&gt;Does anybody know of a DFT+U formulation that allows for more general localization schemes that are not necessarily limited to a single-atom basis?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;This more of a general question, but anything pertaining to a possible quantum-espresso implementation would be appreciated too&lt;/p&gt;&#xA;" OwnerUserId="3967" LastEditorUserId="3967" LastEditDate="2023-11-17T06:39:37.893" LastActivityDate="2023-11-17T06:39:37.893" Title="DFT+U: localizing electrons on combination of atomic orbitals" Tags="|density-functional-theory|dft-u|hubbard-model|conceptual-dft|self-interaction|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11918" PostTypeId="1" AcceptedAnswerId="11973" CreationDate="2023-11-17T11:49:45.113" Score="5" ViewCount="54" Body="&lt;p&gt;I am working on a new atomic solver library, for which I need expressions for the one-center two-electron integrals. Pitzer has furnished the necessary expressions for Slater-type and Gaussian-type orbitals in a book chapter (&lt;a href=&quot;https://doi.org/10.1007/978-94-009-7921-5_11&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1007/978-94-009-7921-5_11&lt;/a&gt;) and a Computer Physics Communications article (&lt;a href=&quot;https://doi.org/doi:10.1016/j.cpc.2005.04.003&quot; rel=&quot;nofollow noreferrer&quot;&gt;doi:10.1016/j.cpc.2005.04.003&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;While the Slater-type orbital expressions appear to be correct, when evaluated against Maple, the Gaussian-type expressions on page 245 of the CPC article&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ R_{mn \nu}(x,y) = \int_0^\infty \int_0^\infty r_1^m e^{-xr_1^2} (r_&amp;lt;^\nu / r_&amp;gt;^{\nu+1}) r_2^n e^{-y r_2^2} {\rm d}r_1 {\rm d}r_2 $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;appear to be wrong. The article gives the result&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ R_{mn \nu}(x,y) = \frac {\frac 1 2 (m+n-3)!} {x y (x+y)^{\frac 1 2 (m+n-3)} }  \left[ 1 + E^{\frac 1 2 (m+n-3)}_{\frac 1 2 (n-\nu-2)}(y/x) + E^{\frac 1 2 (m+n-3)}_{\frac 1 2 (m-\nu-2)}(x/y) \right]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_k^n (x) = \left[ \sum_{j=0}^{k-1} {n \choose j} x^j \right] /  \left[  {n \choose k} x^k \right] $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The problem is quite coarse in nature: the indices of &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; are half-integer!&lt;/p&gt;&#xA;&lt;p&gt;Does anyone happen to know what the correct equations are? The code of the article dates back to the 1960s and is basically unintelligible: the variable names are 4 characters and there are no comments whatsoever.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="5" LastEditDate="2023-11-17T14:31:20.570" LastActivityDate="2023-11-27T10:49:00.507" Title="Correct expressions for one-center Gaussian radial two-electron integrals" Tags="|mathematical-modeling|integrals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11919" PostTypeId="2" ParentId="11803" CreationDate="2023-11-17T15:59:36.520" Score="3" Body="&lt;p&gt;When optimizing the size of a cell using SIESTA and issues you encounter  might indeed be related to the k-point grid density.&lt;/p&gt;&#xA;&lt;p&gt;The k-point grid density directly influences the accuracy of electronic structure calculations in periodic systems. A lower k-point density might lead to an inadequate sampling of the Brillouin zone, resulting in less precise energy minimization and incorrect lattice constants. The k-point grid controls how finely the Brillouin zone is sampled and influences the accuracy of energy calculations, especially for periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;Other parameters in SIESTA could influence the accuracy of your calculations:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Pseudopotentials:&#xA;Ensure that the pseudopotentials used are appropriate for Nickel, are accurate enough for your calculations and verify their compatibility with the Perdew-Burke-Ernzerhof (PBE) functional you're using.&lt;/li&gt;&#xA;&lt;li&gt;Basis sets : Ensure that the basis set you're using is suitably converged. Try refining the basis set further if needed.&lt;/li&gt;&#xA;&lt;li&gt;Relaxation conditions: Check the convergence criteria for the optimization process. Ensure that the convergence thresholds for forces and energies are appropriately set to achieve accurate optimization.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Other numerical parameters such as the mesh cutoff and of course your DFT functional can impact the accuracy of calculations.&lt;/p&gt;&#xA;" OwnerUserId="4274" LastActivityDate="2023-11-17T15:59:36.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11920" PostTypeId="1" CreationDate="2023-11-17T16:17:17.773" Score="4" ViewCount="48" Body="&lt;p&gt;I am trying to calculate the energy of a hydrogen bond between RCOO- and Tyrosine (figure below). I freeze the O-O bond at 2.8A and calculate the energy by changing the distance between O-H. But when I set O-H distance less than 0.95 it shows error termination.&lt;/p&gt;&#xA;&lt;p&gt;I used B3LYP/6-31G method. Here, I am giving the error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error termination request processed by link 9999.&#xA; Error termination via Lnk1e in /opt/gaussian/g16/prebuilt-avx2/g16/l9999.exe at Thu Nov 16 17:51:36 2023.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/wSpBp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/wSpBp.png&quot; alt=&quot;This is the input file I created&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8380" LastEditorUserId="24" LastEditDate="2023-11-17T16:56:58.807" LastActivityDate="2023-11-21T10:25:35.900" Title="Is it possible to find H-bond enrgy with O-H distance less than 0.95A?" Tags="|density-functional-theory|gaussian|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11921" PostTypeId="1" CreationDate="2023-11-17T18:49:27.153" Score="1" ViewCount="52" Body="&lt;p&gt;I have started working on Molpro for casscf calculations on molecules. I need to calculate properties of the molecules say HCl under confinement by various spherical potentials. How can I impose Dirichlet boundary condition at a finite radius? Can I use Molpro package for this. Any help is highly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="8348" LastActivityDate="2023-11-17T18:49:27.153" Title="Confinement of atoms and molecules" Tags="|molpro|" AnswerCount="0" CommentCount="5" ClosedDate="2023-12-27T16:59:45.383" ContentLicense="CC BY-SA 4.0" />
  <row Id="11923" PostTypeId="1" CreationDate="2023-11-18T13:36:59.053" Score="1" ViewCount="47" Body="&lt;p&gt;Are there established practices for fine-tuning AMBER MD parameters in scenarios like mine, involving specific factors like mutant proteins or non-standard ligands? Has anyone successfully tackled challenges in a similar protein-ligand system?&lt;/p&gt;&#xA;&lt;p&gt;Additionally, I'd appreciate insights on recommended approaches for addressing specific challenges and optimizing the simulation setup. The ultimate goal is to ensure that MD simulations precisely capture the nuances of protein-ligand interactions while maintaining computational efficiency.&lt;/p&gt;&#xA;" OwnerUserId="8387" LastActivityDate="2024-01-11T19:38:08.070" Title="When optimizing AMBER molecular dynamics parameters for protein-ligand interactions, how do I balance accuracy and efficiency?" Tags="|molecular-dynamics|computational-chemistry|proteins|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11924" PostTypeId="1" CreationDate="2023-11-18T16:40:51.173" Score="5" ViewCount="113" Body="&lt;p&gt;&lt;a href=&quot;https://scicomp.stackexchange.com/q/43492/27325&quot;&gt;Cross-posted on Computational Science SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The following are the movements of the center of mass of a polymer chain over time in a monte carlo simulation.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#   cm-X     cm-Y    cm-Z&#xA;9.507 21.232 9.910&#xA;9.092 18.427 7.308&#xA;7.994 14.856 4.675&#xA;0.533 12.138 -1.163&#xA;-0.056 6.735 -5.470&#xA;-2.138 4.950 -7.280&#xA;0.736 13.076 -10.012&#xA;9.516 14.611 -12.470&#xA;0.886 17.235 -10.714&#xA;-8.954 21.381 -11.735&#xA;-7.457 16.042 -16.710&#xA;-0.842 13.984 -17.874&#xA;-2.799 13.195 -14.247&#xA;0.738 14.792 -11.774&#xA;5.760 9.218 -10.846&#xA;8.406 13.735 -15.946&#xA;6.848 12.679 -9.621&#xA;13.569 14.036 -6.348&#xA;8.665 12.724 -8.238&#xA;... ... ... ... ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://docs.mdanalysis.org/2.0.0/documentation_pages/analysis/msd.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;4.7.2.2. Mean Squared Displacement&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I want to draw a log-log plot of MSD (mean square displacement) versus &lt;code&gt;t&lt;/code&gt; of a movement of the polymer chain to examine the diffusion behavior.&lt;/p&gt;&#xA;&lt;p&gt;The problem I am facing is that the plot should be a near-straight line, whereas my plot is not.&lt;/p&gt;&#xA;&lt;p&gt;What am I doing incorrectly?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;With smooting&lt;/strong&gt;:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/MI0pb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/MI0pb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;Without smoothing&lt;/strong&gt;:&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/kyYch.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/kyYch.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib&#xA;matplotlib.use('Agg')&#xA;import matplotlib.pyplot as plt&#xA;&#xA;# Function to compute moving average&#xA;def moving_average(x, w):&#xA;    return np.convolve(x, np.ones(w), 'valid') / w&#xA;&#xA;# Read data from file, skipping the first row (header)&#xA;data = np.loadtxt('cm.dat', skiprows=1)&#xA;&#xA;# Wrap CM values if they exceed -1000 or +1000&#xA;data = np.mod(data + 1000, 2000) - 1000  # performs the wrap operation&#xA;&#xA;# Initialize reference point&#xA;x0, y0, z0 = data[0]&#xA;&#xA;# Compute squared displacement for each time step&#xA;SD = [(x - x0)**2 + (y - y0)**2 + (z - z0)**2 for x, y, z in data]&#xA;&#xA;# Compute the cumulative average of SD to get MSD at each time step&#xA;MSD = np.cumsum(SD) / np.arange(1, len(SD) + 1)&#xA;&#xA;# Size of the moving window for smoothing&#xA;window_size = 100&#xA;&#xA;# Apply moving average smoothing to MSD&#xA;MSD_smoothed = moving_average(MSD, window_size)&#xA;&#xA;# Generate time steps for smoothed MSD&#xA;t_smoothed = np.arange(window_size, len(MSD) + 1)&#xA;&#xA;# Create a log-log plot of smoothed MSD versus t&#xA;plt.figure(figsize=(8, 6))&#xA;plt.loglog(t_smoothed, MSD_smoothed, marker='o')&#xA;plt.title('Smoothed Mean Squared Displacement vs Time')&#xA;plt.xlabel('Time step')&#xA;plt.ylabel('Smoothed MSD')&#xA;plt.grid(True, which=&amp;quot;both&amp;quot;, ls=&amp;quot;--&amp;quot;)&#xA;plt.savefig('msd_plot_smoothed.png')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2023-11-18T18:35:30.457" LastActivityDate="2023-11-19T17:24:47.113" Title="Plot MSD (mean square displacement) versus time for a polymer chain" Tags="|python|monte-carlo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11925" PostTypeId="2" ParentId="11924" CreationDate="2023-11-19T17:24:47.113" Score="4" Body="&lt;p&gt;I think that there is nothing wrong with your calculations&lt;/p&gt;&#xA;&lt;p&gt;Normally, a given behavior is specified as a rule due to some physical meaning, but when you do the experiment, you always get deviations from the theoretical rule. These deviations can be determined by the fitting tool you used.&lt;/p&gt;&#xA;&lt;p&gt;In this case, you can fit your data to a line (red line in the figure below) and see what the intercept and slope mean for your case. Or look for each region and figure out what is happening in each section (yellow lines).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/e6cyz.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/e6cyz.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-11-19T17:24:47.113" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11926" PostTypeId="1" AcceptedAnswerId="11930" CreationDate="2023-11-19T22:06:15.917" Score="2" ViewCount="48" Body="&lt;p&gt;The calculation of electronic structure of infinite periodic material using Plane-waves is the object of study here. The cutoff energy &lt;span class=&quot;math-container&quot;&gt;$E_{cutoff}$&lt;/span&gt; provides information about the accuracy of the simulation in the inequality &lt;span class=&quot;math-container&quot;&gt;$$|k+G|^2&amp;lt;E_{cutoff}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; is a reciprocal lattice vector and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; a vector in the reference Brillouin zone (if I understand correctly).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Isn't there a problem with the dimensions of the term in the inequality? Since &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; are of the inverse of length and &lt;span class=&quot;math-container&quot;&gt;$E_{cutoff}$&lt;/span&gt; an energy?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-11-20T01:20:31.067" LastActivityDate="2023-11-20T03:59:36.273" Title="Plane-wave basis expansion for periodic material modelling: cutoff energy inequality and number of atoms in the simulation" Tags="|electronic-structure|periodic-system|plane-waves|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11927" PostTypeId="1" AcceptedAnswerId="11929" CreationDate="2023-11-20T00:24:01.780" Score="4" ViewCount="276" Body="&lt;p&gt;If it is positive, why is it so? Is it due to specific convergence criteria or choice of pseudopotentials? I cannot check the convergence of the DFT calculations as they have been downloaded from a dataset.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2023-11-20T02:44:41.357" LastActivityDate="2023-11-20T03:33:36.193" Title="Can the the relaxed energy of a material system (eV/atom) computed by DFT using VASP be positive?" Tags="|density-functional-theory|vasp|electronic-structure|numerical-convergence|energy|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11928" PostTypeId="2" ParentId="11927" CreationDate="2023-11-20T01:22:52.373" Score="5" Body="&lt;p&gt;Firstly, by expressing the energy per atom (eV/atom), it allows for a more convenient comparison between different materials or systems, as it provides a measure of the energy on a per-atom basis. This is particularly useful when comparing the stability or energetics of different crystal structures, polymorphs, or chemical compositions.&lt;/p&gt;&#xA;&lt;p&gt;For example, if you have a system with 100 atoms and the total energy of the system is -1000 eV, then the energy per atom would be -10 eV/atom. This means that, on average, each atom contributes -10 eV to the total energy of the system.&lt;/p&gt;&#xA;&lt;p&gt;It's important to note that the energy per atom is a relative quantity and can be positive or negative, depending on the system's stability and reference energy chosen.&lt;/p&gt;&#xA;&lt;p&gt;If the energy per atom is positive, it generally indicates that the system is not in its lowest energy state and may not be thermodynamically stable in its current form. A positive energy per atom suggests that the system has excess energy compared to some reference state or configuration. This excess energy could arise from various factors such as:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Metastability: The system might be in a metastable state, meaning it is kinetically trapped in a higher energy configuration, even though a lower energy state exists. In this case, the positive energy per atom indicates that the system has not reached its most stable state.&lt;/li&gt;&#xA;&lt;li&gt;High-energy configuration: The system might have a crystal structure or arrangement of atoms that is energetically unfavorable or less stable compared to other structures. The positive energy per atom reflects the fact that the current configuration is not the lowest energy configuration.&lt;/li&gt;&#xA;&lt;li&gt;Unfavorable interactions: The system could involve interactions or chemical bonding that are energetically unfavorable. This can lead to a positive energy per atom, indicating that the system is not in an energetically favorable state.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;It's important to note that a positive energy per atom does not necessarily imply that the system is completely unstable or unusable. It could still exist in a metastable state or have other desirable properties. However, from an energetic standpoint, a positive energy per atom suggests that there may be more stable configurations or compositions that the system could adopt.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-20T01:22:52.373" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11929" PostTypeId="2" ParentId="11927" CreationDate="2023-11-20T03:33:36.193" Score="4" Body="&lt;p&gt;When DFT is being used for electronic structure energy calculations, a negative energy would be indicative of bound electrons.  There's nothing physically, chemically or mathematically illegal about having a &amp;quot;positive electronic energy&amp;quot; in theory, but it's not something that we see or study often. I'll also note that it doesn't matter whether you're looking at the total energy or the energy/atom, because the &amp;quot;number of atoms&amp;quot; is a positive number so if the energy/atom is positive, it also means that the total energy is positive, and &lt;em&gt;vice versa&lt;/em&gt;. If you're obtaining positive electronic energies in VASP's DFT calculations, then sure, this could have been due to the convergence criteria or the use of pseudopotentials, or other possible things (it's hard to know without more details about what exactly was calculated).&lt;/p&gt;&#xA;&lt;p&gt;So what about a positive energy &lt;em&gt;&lt;strong&gt;after relaxation&lt;/strong&gt;&lt;/em&gt; (as in the title of your question)? Relaxation in this context usually means geometry optimization, meaning that calculations are done to find the geometry at which the electronic total energy (or energy/atom if you wish) is lowest or in a local minimum. &lt;em&gt;&lt;strong&gt;This energy can still in theory be positive&lt;/strong&gt;&lt;/em&gt; for the same reason as given in the first paragraph of this answer. The point about metastability in the &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11928/5&quot;&gt;answer by Jaafar&lt;/a&gt; can be related to local minima, but there's nothing theoretically illegal about having a positive energy at a global minimum either.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11928/5&quot;&gt;answer by Jaafar&lt;/a&gt; mentioned &amp;quot;reference energies&amp;quot; too. If a single-point energy calculation is done using DFT, it's fair for us to assume that this is an electronic energy calculation, in which the program would usually give you a &amp;quot;total energy&amp;quot; (or in this case a &amp;quot;total energy per atom&amp;quot;) compared to a reference energy of 0 which would only indicate the existence of 0 electrons. However, the point about reference energies can be useful to illustrate the phenomenon of unbound states, or even just the idea of positive energies relative to a different state, the latter being shown in the diagram below from &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0022285211000853&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper of mine&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IClf6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IClf6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the above figure, the &amp;quot;relaxed&amp;quot; energy for the gerade state is at around +8000cm-1 , or +1 eV, or +0.5 eV/atom, which is a positive number, but any energy can be made positive like this by shifting the &amp;quot;reference&amp;quot; or &amp;quot;zero&amp;quot; energy to make that happen.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-20T03:33:36.193" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11930" PostTypeId="2" ParentId="11926" CreationDate="2023-11-20T03:59:36.273" Score="4" Body="&lt;p&gt;You’re quite right: as written, the equation is dimensionally inconsistent. There are actually a bunch of constants that make the units work out, but it is customary in matter modeling to define units such that the most common constants end up being equal to 1, and then we simply neglect to write them down.&lt;sup&gt;*&lt;/sup&gt; In particular, the so-called &lt;strong&gt;atomic units&lt;/strong&gt; are such that the reduced Planck’s constant (&lt;span class=&quot;math-container&quot;&gt;$h/2\pi)$&lt;/span&gt;, the charge &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt; and mass &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; of the electron, and also the dielectric permittivity of the vacuum, are all numerically equal to 1 of their respective unit:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hbar = e = m = \frac{1}{4\pi \varepsilon_0} = 1.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then any conversion between them doesn’t change the number and can be “safely” skipped over in the actual paper. This also shows up in high-energy physics: the reason units like &lt;span class=&quot;math-container&quot;&gt;$\text{MeV}$&lt;/span&gt; are used as energy scales and length scales interchangeably is that the units make their conversions have the same value (or at most a reciprocal).&lt;/p&gt;&#xA;&lt;p&gt;As for the specific case in your question: Consider the free electron, which has the Hamiltonian&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H = - \frac{\hbar^2}{2m} \nabla^2,&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\nabla^2$&lt;/span&gt; is the Laplacian operator &lt;span class=&quot;math-container&quot;&gt;$\nabla^2 = \partial_{xx} + \partial_{yy} + \partial_{zz}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It’s a classic result, and pretty easy to demonstrate, that the resulting wavefunctions are proportional to plane waves&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi(\mathbf{r}) \propto e^{i\mathbf{k}\cdot\mathbf{r}}, \quad \mathbf{k} \in \mathbb{R}^3.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; has units of length&lt;span class=&quot;math-container&quot;&gt;$^{-1}$&lt;/span&gt;, as you mentioned, but is actually the particle’s momentum! Thus the energy of a free electron with momentum &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt; is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E(\mathbf{k}) = \frac{\hbar^2}{2m} p(\mathbf{k})^2 = \frac{\hbar^2 \mathbf{k}^2}{2m} \implies \mathbf{k}^2 = \frac{2m}{\hbar^2} E(\mathbf{k}).&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;But in atomic units, &lt;span class=&quot;math-container&quot;&gt;$\hbar = m = 1$&lt;/span&gt;, and we can just write &lt;span class=&quot;math-container&quot;&gt;$E = \mathbf{k}^2/2$&lt;/span&gt;. This is how you should interpret the energy cutoff—&lt;span class=&quot;math-container&quot;&gt;$\lvert\mathbf{k}\rvert^2 &amp;lt; E_{\text{cut}}$&lt;/span&gt; means to use all the plane-waves with momentum up to &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}(/2)$&lt;/span&gt; as basis functions.&lt;sup&gt;**&lt;/sup&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;&lt;sub&gt;* This makes equations faster to read, but only after you know about the practice already. &lt;/sub&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;sub&gt;** We have to add in &lt;span class=&quot;math-container&quot;&gt;$\mathbf{G}$&lt;/span&gt;, which has the same units as &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;, because we force the plane waves to live in a box with a finite size and impose periodic boundary conditions. This also discretizes &lt;span class=&quot;math-container&quot;&gt;$\mathbf{k}$&lt;/span&gt;, as it turns out; the derivation of this is worth a separate question, though. &lt;/sub&gt;&lt;/p&gt;&#xA;" OwnerUserId="1393" LastActivityDate="2023-11-20T03:59:36.273" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11931" PostTypeId="1" CreationDate="2023-11-20T07:15:55.530" Score="6" ViewCount="254" Body="&lt;p&gt;After performing high-pressure calculations for my ABO4 compounds using the VASP software, I am now interested in fitting the Birch-Murnaghan equation of state to either pressure versus volume or energy versus volume data.&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate guidance on the best fitting procedure and, if possible, the provision of a Python or MATLAB script for this purpose. Your assistance would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="8392" LastEditorUserId="5" LastEditDate="2023-11-20T23:01:29.803" LastActivityDate="2023-11-20T23:01:29.803" Title="Fitting of Brich-Murnaghan equation of state" Tags="|vasp|elasticity|curve-fitting|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11932" PostTypeId="2" ParentId="11931" CreationDate="2023-11-20T08:40:26.257" Score="3" Body="&lt;p&gt;Here are some references from my own work:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;a script that reads energy-volume data from a csv file and fits a Vinet equation of state: &lt;a href=&quot;https://github.com/flokno/tools.mlff/blob/main/mlfftools/scripts/eos_fit_data.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/flokno/tools.mlff/blob/main/mlfftools/scripts/eos_fit_data.py&lt;/a&gt; which I used to do the analysis around Fig. 2 and 3 in &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/159/17/174105/2919546/Stress-and-heat-flux-via-automatic-differentiation&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.aip.org/aip/jcp/article/159/17/174105/2919546/Stress-and-heat-flux-via-automatic-differentiation&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;the script is based on the &lt;code&gt;EquationOfState&lt;/code&gt; class in ASE: &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/eos/eos.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://wiki.fysik.dtu.dk/ase/tutorials/eos/eos.html&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;if you prefer Birch-Murnaghan over Vinet, it is included in ASE: &lt;a href=&quot;https://gitlab.com/ase/ase/-/blob/master/ase/eos.py?ref_type=heads#L40-50&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/blob/master/ase/eos.py?ref_type=heads#L40-50&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Things to look out for:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;I would consistently work with energy per atom, which is a normalized quantity&lt;/li&gt;&#xA;&lt;li&gt;use a consistent energy baseline (typically the smallest total energy&#xA;of interest) which you subtract from your energies to stabilize the fit&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="8192" LastActivityDate="2023-11-20T08:40:26.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11933" PostTypeId="2" ParentId="11914" CreationDate="2023-11-20T10:40:10.107" Score="1" Body="&lt;p&gt;Thank to all the comments and parallel discussions, I realised that to calculate Green Kubo viscosity one has to use the stress tensor. From Allen Tildesley, p61:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;These quantities [the stress tensor] are multiple particle properties, [...], and no statistical averaging is possible.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;A1&lt;/strong&gt; Thus, I should effectively use the stress tensor from &lt;code&gt;get_stress()&lt;/code&gt; and not &lt;code&gt;get_stresses()&lt;/code&gt; as initially thought.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;A2&amp;amp;3&lt;/strong&gt; ASE does not ensure that a given calculator implements and benchmarks high level properties. Thus one has to check time to time whether a calculator has a property implemented&lt;/p&gt;&#xA;" OwnerUserId="1706" LastActivityDate="2023-11-20T10:40:10.107" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11934" PostTypeId="2" ParentId="11931" CreationDate="2023-11-20T11:00:02.183" Score="4" Body="&lt;p&gt;If you know Julia, I have a package called &lt;a href=&quot;https://github.com/MineralsCloud/EquationsOfStateOfSolids.jl&quot; rel=&quot;nofollow noreferrer&quot;&gt;EquationsOfStateOfSolids.jl&lt;/a&gt; that is designed to do this.&lt;/p&gt;&#xA;&lt;p&gt;It currently can fit and evaluate &lt;span class=&quot;math-container&quot;&gt;$E(V)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$P(V)$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$B(V)$&lt;/span&gt; on several equations of state:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Murnaghan 1st EOS&lt;/li&gt;&#xA;&lt;li&gt;Birch–Murnaghan EOS family:&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Birch–Murnaghan 2nd&lt;/li&gt;&#xA;&lt;li&gt;Birch–Murnaghan 3rd&lt;/li&gt;&#xA;&lt;li&gt;Birch–Murnaghan 4th&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;Vinet EOS&lt;/li&gt;&#xA;&lt;li&gt;Poirier–Tarantola EOS family:&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Poirier–Tarantola 2nd&lt;/li&gt;&#xA;&lt;li&gt;Poirier–Tarantola 3rd&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;It can even reversibly solve the &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; from a given &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; for certain equations of state.&lt;/p&gt;&#xA;&lt;p&gt;The documentation is &lt;a href=&quot;https://mineralscloud.github.io/EquationsOfStateOfSolids.jl/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The fitting method used is from &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2011.04.016&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="727" LastEditorUserId="727" LastEditDate="2023-11-20T21:49:46.897" LastActivityDate="2023-11-20T21:49:46.897" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11936" PostTypeId="1" AcceptedAnswerId="12095" CreationDate="2023-11-20T21:21:25.343" Score="3" ViewCount="69" Body="&lt;p&gt;The aim is to do an electronic calculation with static nucleus with Plane wave (PW) basis functions for an infinite periodic material. The number of functions is given by the pairs of reciprocal lattice vectors &lt;span class=&quot;math-container&quot;&gt;$G$&lt;/span&gt; and momentum vector &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; in the first Brillouin zone that respect the inequality &lt;span class=&quot;math-container&quot;&gt;$|k + G|^2 &amp;lt; E_{cutoff}$&lt;/span&gt;. Hence this inequality gives the number of PW basis functions as a function of &lt;span class=&quot;math-container&quot;&gt;$E_{cutoff}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does this inequality also gives the size of the simulation?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;By that, I mean the number of basis functions and the number of cells neighboring a 'reference cell' in a radius of &lt;span class=&quot;math-container&quot;&gt;$|G_{max}|$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$|G_{max}|$&lt;/span&gt; is the norm of the cells which are the most far from the 'reference' cell in the reciprocal space. Hence, giving the neighboring cells to compute the electron-electron and electron-proton potentials by solving the Poisson equation &lt;span class=&quot;math-container&quot;&gt;$$-\Delta V_{tot}= -4\pi (\sum_{\mathcal{T} \in \mathcal{R}} m(.+\mathcal{T}) - \rho)$$&lt;/span&gt; where&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathcal{T}$&lt;/span&gt; is a translation in the real space &lt;span class=&quot;math-container&quot;&gt;$\mathcal{R}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; the nuclei in the primitive unit cell&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{tot}$&lt;/span&gt; the electron-electron and electron-proton potentials&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the electron density&#xA;in the real/physical space this time.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-11-20T21:42:35.503" LastActivityDate="2023-12-18T01:11:12.417" Title="Plane wave expansion of the wavefunction for periodic material modelling" Tags="|electronic-structure|condensed-matter|periodic-system|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11937" PostTypeId="1" AcceptedAnswerId="11938" CreationDate="2023-11-20T21:40:49.213" Score="4" ViewCount="98" Body="&lt;p&gt;When using plane wave basis functions,&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;what is the phase of each plane wave?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Should a one-electron wavefunction looks like &lt;span class=&quot;math-container&quot;&gt;$\Phi^k_{\beta}(r) = \sum_{G} c^k_{\beta,G}e^{i((k+G) r + \varphi_G)}$&lt;/span&gt; instead of &lt;span class=&quot;math-container&quot;&gt;$\Phi^k_{\beta}(r) = \sum_{G} c^k_{\beta,G}e^{i(k+G) r}$&lt;/span&gt;?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-11-20T22:15:38.573" LastActivityDate="2023-11-24T03:05:25.557" Title="Plane wave basis functions" Tags="|plane-waves|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11938" PostTypeId="2" ParentId="11937" CreationDate="2023-11-20T22:14:01.440" Score="2" Body="&lt;p&gt;It does not matter: the coeficients are supposed to be complex, absorbing the phases.&lt;/p&gt;&#xA;" OwnerUserId="727" LastEditorUserId="727" LastEditDate="2023-11-24T03:05:25.557" LastActivityDate="2023-11-24T03:05:25.557" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11939" PostTypeId="1" CreationDate="2023-11-21T05:56:14.463" Score="3" ViewCount="25" Body="&lt;p&gt;I want to check the energy gap change during finite temperature &lt;em&gt;ab initio&lt;/em&gt; molecular simulations. The results may look like this picture:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/rNODD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rNODD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How can set aimd simulation to get this result in VASP?&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-11-21T05:56:14.463" Title="How to get energy gap change at specific high symmetry points during ab initio molecular simulations？" Tags="|vasp|molecular-dynamics|electronic-structure|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11940" PostTypeId="2" ParentId="11920" CreationDate="2023-11-21T10:25:35.900" Score="2" Body="&lt;p&gt;A short O-H bond (0.86 Å) is often wrongly observed in X-ray crystallography, but should give you no problems other than SCF problems. Having no experience with gaussian, my guess is that you are indeed having SCF problems. Probably it's better to start with a more reasonable structure.&lt;/p&gt;&#xA;&lt;p&gt;Note, GFN-xTB gives O-H distances of 1.136 Å (donor) and H-O (acceptor) 1.308 Å.&lt;/p&gt;&#xA;&lt;p&gt;PS. I'm not sure how good b3lyp with a small basis set will work. GFN-xTB might be a better option then, much faster and probably equally reliable structures.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-11-21T10:25:35.900" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11941" PostTypeId="1" AcceptedAnswerId="11995" CreationDate="2023-11-21T12:55:45.407" Score="6" ViewCount="93" Body="&lt;p&gt;I am looking for a mathematical model which will produce the displacement vectors from vibrational frequency calculations. I use ORCA for the calculation of the frequencies and generally use Chemcraft to visualize the frequencies. We can generate the displaced coordinates there using the GUI. However, I want to implement it in the automated script which can generate the displaced geometries along different normal modes with a specified displacement. Is there any open-source code available implementing such a model?&lt;/p&gt;&#xA;" OwnerUserId="765" LastEditorUserId="671" LastEditDate="2023-11-29T13:57:34.320" LastActivityDate="2023-12-30T17:04:30.580" Title="Mathematical model/open source code to obtain displaced geometries along a normal mode from vibrational frequency calculation" Tags="|orca|vibrational-frequency|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11942" PostTypeId="1" AcceptedAnswerId="11945" CreationDate="2023-11-21T15:31:36.123" Score="5" ViewCount="106" Body="&lt;p&gt;I have made a bunch of calculations in ORCA to compare them to results from &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jacs.3c01933&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; paper. The original calculations from this paper were done in TurboMole. I tried to recreate the method as best I could using ORCA, but it seems that there is something in my calcs that does not match up to the method used by Rochus et al., since my energies seem to be consistently ~3 kJ/mol higher than those done by Rochus.&lt;/p&gt;&#xA;&lt;p&gt;Here are the energies done by me and those done by Rochus:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5y6bM.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5y6bM.png&quot; alt=&quot;Rochus original calculations&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And here are mine done with ORCA:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/3Urkv.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3Urkv.png&quot; alt=&quot;My new calcs in ORCA&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;My suspicion is that the integration grid (&amp;quot;m5&amp;quot; in Turbomole) might be the reason for this deviation. There is no direct equivalent to the m5 grid in ORCA, from what I could find. Perhaps this m5 grid is just finer than the one I used in ORCA.&lt;/p&gt;&#xA;&lt;p&gt;To test this theory, I wanted to, optimally, calculate the SCF energies again using a finer grid in ORCA, without rerunning the entire series of calculations. Is it possible to &amp;quot;reintegrate&amp;quot; ORCA results without doing the whole calculation all over again?&lt;/p&gt;&#xA;" OwnerUserId="7501" LastActivityDate="2023-11-27T10:56:24.417" Title="Reintegrate calculation results from ORCA using finer grid?" Tags="|orca|integrals|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11943" PostTypeId="2" ParentId="2163" CreationDate="2023-11-21T16:56:20.653" Score="2" Body="&lt;p&gt;I had the same issue on Ubuntu 20.04. I solved it by copying input generators scripts (&lt;a href=&quot;https://github.com/OpenChemistry/avogenerators&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/OpenChemistry/avogenerators&lt;/a&gt;) to /usr/lib/x86_64-linux-gnu/avogadro2/scripts/commands.&lt;/p&gt;&#xA;" OwnerUserId="6994" LastActivityDate="2023-11-21T16:56:20.653" CommentCount="0" CommunityOwnedDate="2023-11-23T19:24:56.707" ContentLicense="CC BY-SA 4.0" />
  <row Id="11944" PostTypeId="1" CreationDate="2023-11-21T18:38:51.663" Score="2" ViewCount="36" Body="&lt;p&gt;I am calculating the static (low-frequency) dielectric constant for a polar material in VASP.&lt;/p&gt;&#xA;&lt;p&gt;Due to the LO-TO splitting, I need to apply a non-analytical correction. My question is how to do this correctly? It seems there is a way to use the &lt;code&gt;--nac&lt;/code&gt; command in phonopy. However, it seems this is only possible e.g. in bandstructure calculations and I don't understand how to get the corrected dielectric tensor.&lt;/p&gt;&#xA;&lt;p&gt;Could you explain step-by-step how this is done correctly? Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1955" LastActivityDate="2023-11-21T18:38:51.663" Title="Non-analytical correction for dielectric constant calculation in VASP" Tags="|vasp|phonons|dielectric-constants|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11945" PostTypeId="2" ParentId="11942" CreationDate="2023-11-21T19:30:22.527" Score="6" Body="&lt;p&gt;The standard solution is to run a new ORCA calculation with a larger grid, and read your current wavefunction (from the GBW files that you got) as initial guess:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! (level of theory etc...)&#xA;! DefGrid3 (if you are using ORCA 4.x, use something like Grid6 instead)&#xA;! MORead&#xA;%moinp &amp;quot;old_calculation.gbw&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This performs the SCF using the large grid until convergence, which may take a few cycles, hopefully no more than 10.&lt;/p&gt;&#xA;&lt;p&gt;If you want to &amp;quot;reintegrate&amp;quot; the XC energy without changing the wavefunction, you can set the number of SCF cycles to 1 via:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%scf&#xA;maxiter 1&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or alternatively, set the SCF convergence threshold to extremely loose values. This way the calculation is much faster. It still wastes some time on evaluating the Coulomb and exact exchange contributions, but the evaluation happens only once (or maybe twice?) per calculation, and AFAIK it's impossible to avoid.&lt;/p&gt;&#xA;&lt;p&gt;However, XC integration error is probably not the dominant reason for the discrepancy. Since XC integration is usually not the rate-limiting step of a SCF single point calculation, in most programs the default grid is large enough so that the SCF energy error is negligible. You can also see this from the integrated number of electrons, printed after the SCF section of the ORCA output file, which is usually on the same order of magnitude as the error of the XC energy. Usually it is only necessary to increase the grid during e.g. geometry optimization (where small numerical noise may prevent convergence), frequency analysis (where small numerical noise can turn a small real frequency into an imaginary one), and the calculation of certain properties that involve the wavefunction near nuclei (EPR hyperfine couplings, Mössbauer spectroscopy, etc.).&lt;/p&gt;&#xA;&lt;p&gt;The following differences of the ORCA and Turbomole default settings may have greater contributions to the observed energy discrepancies than the grid differences:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;For hybrid functionals, ORCA (except for older versions) uses the RIJCOSX approximation by default (that is, RI for the Coulomb term and COSX for the exchange term), while Turbomole by default evaluates the Coulomb term by RI but the exchange term exactly. To reproduce the latter behavior, one should use the keyword &amp;quot;! RIJONX&amp;quot; in the ORCA input file. Turbomole also supports COSX, but it is called SENEX in Turbomole terminology and is turned off by default.&lt;/li&gt;&#xA;&lt;li&gt;The default RI auxiliary basis set of Turbomole is different for every orbital basis set, but the default auxiliary basis set of ORCA is mostly independent of the orbital basis set (def2/J for non-relativistic and ECP calculations, SARC/J for scalar relativistic calculations, with very few exceptions). Therefore, the RI auxiliary basis set that you used is probably different from the one used in Turbomole. In particular, the def2/J auxiliary basis set is designed for the def2 series of basis sets, and may or may not be suitable for aug-cc-pVDZ and aug-cc-pVDZ-PP.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2023-11-21T19:30:22.527" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11946" PostTypeId="5" CreationDate="2023-11-22T03:52:34.590" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-11-22T03:52:34.590" LastActivityDate="2023-11-22T03:52:34.590" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11947" PostTypeId="4" CreationDate="2023-11-22T03:52:34.590" Score="0" Body="Questions about anharmonicity, anharmonic approximations, and effects of anharmonicity on the properties of molecules." OwnerUserId="7606" LastEditorUserId="7606" LastEditDate="2023-11-22T12:51:30.460" LastActivityDate="2023-11-22T12:51:30.460" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11948" PostTypeId="1" AcceptedAnswerId="12056" CreationDate="2023-11-22T10:22:10.030" Score="4" ViewCount="428" Body="&lt;p&gt;I used QE to calculate DOS for hBN. I expect to get results as shown &lt;a href=&quot;https://arxiv.org/ftp/arxiv/papers/2001/2001.11596.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. The behavior of the computed DOS is as expected but QE gives Fermi energy = 1.974 eV. So, when I plot DOS concerning E-Ef, the Fermi level isn't located at zero:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Yp9dp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Yp9dp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we look at the figure, we can observe that the highest occupied level is about 5.126 eV (as in the DOS data file).&lt;/p&gt;&#xA;&lt;p&gt;Why QE gives Fermi energy = 1.974 eV, not 5.126 eV?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt;&#xA;Here is the input file I used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './out/'&#xA;  prefix = 'hBN'&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ecutwfc = 40&#xA;  ibrav = 0&#xA;  nat = 4&#xA;  ntyp = 2&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.0d-10&#xA;/&#xA;ATOMIC_SPECIES&#xA;B     10.0 B_ONCV_PBE_FR-1.0.upf&#xA;N     14.0 N_ONCV_PBE_FR-1.0.upf&#xA;&#xA;ATOMIC_POSITIONS crystal&#xA;B            0.6666666667       0.3333333333       0.7500000000 &#xA;B            0.3333333333       0.6666666667       0.2500000000 &#xA;N            0.6666666667       0.3333333333       0.2500000000 &#xA;N            0.3333333333       0.6666666667       0.7500000000 &#xA;&#xA;CELL_PARAMETERS angstrom&#xA;     -1.2562141150      -2.1758266724      -0.0000000000&#xA;     -1.2562141150       2.1758266724       0.0000000000&#xA;      0.0000000000       0.0000000000      -7.7072650000&#xA;&#xA;K_POINTS automatic&#xA;9 9 9 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the &lt;code&gt;nscf&lt;/code&gt; I have added&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nbnd = 16&#xA;occupations = 'tetrahedra'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; section.&lt;/p&gt;&#xA;&lt;p&gt;Here is a comparison with the results in the &lt;a href=&quot;https://next-gen.materialsproject.org/materials/mp-984?material_ids=mp-984&quot; rel=&quot;nofollow noreferrer&quot;&gt;materialsproject&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/HGEwZ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/HGEwZ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6232" LastEditorUserId="6232" LastEditDate="2023-12-04T11:39:22.343" LastActivityDate="2023-12-13T06:58:20.093" Title="Question about determining Fermi energy in Quantum espresso" Tags="|quantum-espresso|density-of-states|fermi-energy|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11949" PostTypeId="1" AcceptedAnswerId="11950" CreationDate="2023-11-22T11:59:25.687" Score="4" ViewCount="123" Body="&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/q/177829/27342&quot;&gt;Cross-posted on Chem.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Is there any evidence that spin-orbit coupling (SOC) leads to a crystal lattice distortion? Using Quantum Espresso and DFT, I am getting different relaxed lattice constants when I take SOC into account and when I neglect it. Is this a bug or a feature? Are there any known materials where SOC leads to structural distortion?&lt;/p&gt;&#xA;" OwnerUserId="1402" LastEditorUserId="5" LastEditDate="2023-11-25T00:07:47.777" LastActivityDate="2023-11-25T00:07:47.777" Title="Spin-orbit coupling and lattice constant" Tags="|density-functional-theory|quantum-espresso|quantum-chemistry|spin-orbit-coupling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11950" PostTypeId="2" ParentId="11949" CreationDate="2023-11-22T20:46:42.590" Score="3" Body="&lt;p&gt;It's hard to tell without any information about the material, but it could be a feature. It is known that transition metal compounds can have an involved interplay between spin-orbit coupling and the Jahn-Teller (JT) effect. The paper &lt;a href=&quot;https://doi.org/10.1103/PhysRevX.10.031043&quot; rel=&quot;nofollow noreferrer&quot;&gt;S. V. Streltsov and D. I. Khomskii, &amp;quot;Jahn-Teller Effect and Spin-Orbit Coupling: Friends or Foes?&amp;quot;, &lt;em&gt;Phys. Rev. X&lt;/em&gt; &lt;strong&gt;10&lt;/strong&gt;, 031043 (2020)&lt;/a&gt; gives some general guidelines that depend on the electron configuration.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;for some cases, such as &lt;span class=&quot;math-container&quot;&gt;$d^4$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d^5$&lt;/span&gt;, but also &lt;span class=&quot;math-container&quot;&gt;$d^2$&lt;/span&gt; configurations, strong SOC suppresses JT distortion, whereas in other cases, notably &lt;span class=&quot;math-container&quot;&gt;$d^3$&lt;/span&gt;, SOC promotes or generates the JT effect in the configuration which is usually considered as &amp;quot;orbitally dead.”&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$d^4$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d^5$&lt;/span&gt; states they consider are low-spin &lt;span class=&quot;math-container&quot;&gt;$t_{2g}$&lt;/span&gt; states. They also have a recent follow-up paper: &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.105.205142&quot; rel=&quot;nofollow noreferrer&quot;&gt;S. V. Streltsov, F. V. Temnikov, K. I. Kugel, and Daniel I. Khomskii, &amp;quot;Interplay of the Jahn-Teller effect and spin-orbit coupling: The case of trigonal vibrations&amp;quot;, Phys. Rev. B &lt;strong&gt;105&lt;/strong&gt;, 205142 (2022)&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="671" LastEditorUserId="671" LastEditDate="2023-11-22T22:20:26.663" LastActivityDate="2023-11-22T22:20:26.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11952" PostTypeId="1" CreationDate="2023-11-23T08:44:20.437" Score="1" ViewCount="68" Body="&lt;p&gt;I need to generate an input file for band structure calculation along the following k path. how do I input the k path in the &amp;quot;bands.in&amp;quot; file? here, i need to calculate the band gap along all of the mentioned kpaths.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/37GzA.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/37GzA.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;  calculation = 'bands',&#xA;  restart_mode = 'from_scratch',&#xA;  prefix = 'bands2',&#xA;  outdir = './tmp/'&#xA;  pseudo_dir = '/home/psuedo_sr'&#xA;  verbosity = 'high'&#xA;/&#xA;&#xA;&amp;amp;system&#xA;    ibrav = 5,&#xA;    celldm(1) = 10.52826895, ! in bohr units&#xA;    celldm(4) = 0.5696, &#xA;    nat = 10, ntyp = 3,&#xA;    ecutwfc = 50,&#xA;    ecutrho = 400.0,&#xA;    nbnd = 100,&#xA;    nspin=2,&#xA;    starting_magnetization(1) =   3&#xA;    starting_magnetization(2) =   0.5&#xA;    starting_magnetization(3) =   0.1&#xA;/&#xA;&#xA;&amp;amp;electrons&#xA;    conv_thr = 1.0e-10&#xA;    electron_maxstep = 500&#xA;    mixing_beta = 0.3d0&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;     Fe 55.845 Fe.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;     Ti 47.867 Ti.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;     O  15.999 O.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;Ti     0.145414993         0.145414710         0.145414993&#xA;Ti     0.854586005         0.854584396         0.854586005&#xA;Fe     0.357185096         0.357184410         0.357185096&#xA;Fe     0.642815828         0.642814636         0.642815828&#xA;O     0.562447965         0.953017414         0.220108926&#xA;O     0.953018606         0.220107913         0.562447786&#xA;O     0.220108837         0.562446773         0.953018665&#xA;O     0.437552989         0.046981703         0.779892027&#xA;O     0.046982408         0.779891193         0.437553167&#xA;O     0.779892147         0.437552273         0.046982329&#xA;&#xA;K_POINTS {crystal_b}&#xA;13&#xA;   0.0000000000     0.0000000000     0.0000000000     20 !GAMMA&#xA;   0.5000000000     0.0000000000     0.0000000000     20 !L&#xA;   0.7662337662     0.2337662338     0.5000000000     20 !B1&#xA;   0.5000000000    -0.2337662338     0.2337662338     20 !B&#xA;   0.0000000000    -0.5000000000     0.0000000000     20 !Z&#xA;   0.0000000000     0.0000000000     0.0000000000     20 !GAMMA&#xA;   0.7662337662     0.3666666667     0.3666666667     20 !X&#xA;   0.6333333333     0.0000000000     0.3666666667     20 !Q&#xA;   0.5000000000     0.0000000000     0.5000000000     20 !F&#xA;   0.3666666667    -0.2337662338     0.3666666667     20 !P1&#xA;   0.0000000000    -0.5000000000     0.0000000000     20 !Z&#xA;   0.5000000000     0.0000000000     0.0000000000     20 !L&#xA;   0.3666666667    -0.3666666667     0.0000000000     20 !P &#xA;           &#xA;HUBBARD (atomic)&#xA;  U Fe-3d 5.3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8340" LastEditorUserId="8340" LastEditDate="2023-11-26T05:56:54.777" LastActivityDate="2023-11-26T05:56:54.777" Title="Is it possible to generate an input file for band structure calculations for multiple KPaths at once?" Tags="|quantum-espresso|band-structure|bandgap|" AnswerCount="0" CommentCount="7" ClosedDate="2023-12-20T03:24:01.790" ContentLicense="CC BY-SA 4.0" />
  <row Id="11953" PostTypeId="1" AcceptedAnswerId="11962" CreationDate="2023-11-23T09:00:35.697" Score="4" ViewCount="142" Body="&lt;p&gt;How to make Pd(111) super-cell (√3×√3)R30  via VESTA or Avogadro software?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="5" LastEditDate="2023-11-23T13:23:42.930" LastActivityDate="2023-11-24T12:03:37.940" Title="How to make Pd(111) supercell (√3×√3)R30 via VESTA" Tags="|software|crystallography|vesta|avogadro|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11954" PostTypeId="1" CreationDate="2023-11-23T09:30:34.070" Score="2" ViewCount="26" Body="&lt;p&gt;I am preparing the following strcture of CdAlCRO4 using Material Studio to further study its properties. However, I am facing difficulty in deciding the space group it belongs to.&lt;/p&gt;&#xA;&lt;p&gt;How to find the group number of a new material?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/q3LC2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/q3LC2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8415" LastEditorUserId="5" LastEditDate="2023-11-23T13:24:31.397" LastActivityDate="2023-11-23T13:24:31.397" Title="How to define the space group of a new material?" Tags="|structure|space-groups|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11955" PostTypeId="1" CreationDate="2023-11-23T13:33:45.507" Score="3" ViewCount="59" Body="&lt;p&gt;Now, I'm calculating with a Quantum Espresso program&lt;/p&gt;&#xA;&lt;p&gt;I want to need Eu pseudopotential file with 4f orbital information. But I couldn't find that file, no matter how much I search on the internet. Because of this, I haven't been able to calculate and I'm only seeing the error screen for several days.  I attatch the picture of error.[file1] &lt;a href=&quot;https://i.stack.imgur.com/k7GqP.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k7GqP.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there anyone who can share the &amp;quot;Pseudopotential file of Eu atom&amp;quot; containing 4f-orbital information?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8396" LastEditorUserId="5" LastEditDate="2023-11-23T21:39:15.390" LastActivityDate="2023-11-24T09:46:11.097" Title="Is there a way to add 4f-oribital information in Pseudopotential?" Tags="|orbitals|pseudopotentials|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11956" PostTypeId="1" CreationDate="2023-11-23T14:15:21.980" Score="3" ViewCount="106" Body="&lt;p&gt;We are given a system of three quantum domains A, B, and C with the following properties:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;(1)  domains A and B are independent Hilbert spaces, each with their own space and time dimensions. Both are capable of hosting the wave function and all observables of a photon&lt;/li&gt;&#xA;&lt;li&gt;(2)  domain C is a &lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_foam&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantum &amp;quot;foam&amp;quot;&lt;/a&gt; lacking coherent space and time dimensions&lt;/li&gt;&#xA;&lt;li&gt;(3)  domains A and B have domain C in common&lt;/li&gt;&#xA;&lt;li&gt;(4)  domain C is capable of transmitting null vectors between A and B.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;A photon of energy E is known to be in either A or B. A measurement is taken in domain A and the photon is not found. What are the observables of the photon in domain B, relative to domain A?&lt;/p&gt;&#xA;&lt;p&gt;Intuitively, the observables cannot include energy, as a non-zero amount of time is required in domain B for such a measurement, and the two domains do not share a common time dimension. Position and momentum are also problematic, as the projection of domains A and B on each other is a dimensionless point.&lt;/p&gt;&#xA;" OwnerUserId="8418" LastEditorUserId="5" LastEditDate="2023-11-27T18:31:16.450" LastActivityDate="2023-11-27T19:44:38.777" Title="What are the observables when a quantum system is comprised of orthogonal spacetimes?" Tags="|quantum-chemistry|quantum-mechanics|" AnswerCount="1" CommentCount="2" ClosedDate="2023-12-07T17:07:00.387" ContentLicense="CC BY-SA 4.0" />
  <row Id="11958" PostTypeId="5" CreationDate="2023-11-24T01:27:01.053" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-11-24T01:27:01.053" LastActivityDate="2023-11-24T01:27:01.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11959" PostTypeId="4" CreationDate="2023-11-24T01:27:01.053" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2023-11-24T01:27:01.053" LastActivityDate="2023-11-24T01:27:01.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11961" PostTypeId="2" ParentId="11955" CreationDate="2023-11-24T09:46:11.097" Score="1" Body="&lt;p&gt;You can try the PP: Eu.pbe-spdfn-kjpaw_psl.1.0.0.UPF. I have used this one for Hubbard correction of Eu-4f orbitals a while back. I have uploaded it here: &lt;a href=&quot;https://drive.google.com/file/d/1gF19GPEz3CkH9uTXN52Vw5ATJch1DJax/view?usp=drive_link&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://drive.google.com/file/d/1gF19GPEz3CkH9uTXN52Vw5ATJch1DJax/view?usp=drive_link&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5535" LastActivityDate="2023-11-24T09:46:11.097" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11962" PostTypeId="2" ParentId="11953" CreationDate="2023-11-24T12:03:37.940" Score="5" Body="&lt;p&gt;This would be a pain to do in GUIs like VESTA and Avogadro. In ASE, this can be done just in one line by &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/build/surface.html#ase.build.fcc111_root&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ase.build.fcc111_root&lt;/code&gt;&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import fcc111_root&#xA;from ase.visualize import view&#xA;&#xA;atoms = fcc111_root('Pd', root=3, size=(2,2,4), vacuum=5.)&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/zgr3U.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/zgr3U.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can then get the structure file, e.g. in .xyz format, simply by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import write&#xA;&#xA;write('Pd111.xyz', atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2023-11-24T12:03:37.940" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="11963" PostTypeId="1" CreationDate="2023-11-24T12:11:12.193" Score="3" ViewCount="176" Body="&lt;p&gt;I was reading this paper (&lt;a href=&quot;https://www.nature.com/articles/s41598-021-98331-y&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computing molecular excited states on a D‑Wave quantum annealer&lt;/a&gt;) and wondering if I can make a QUBO model for the equations used in the TD-DFT energy calculation for the singlet and triplet energies?&lt;/p&gt;&#xA;" OwnerUserId="8425" LastEditorUserId="5" LastEditDate="2023-11-24T21:11:26.400" LastActivityDate="2023-11-24T21:11:26.400" Title="Is a D-Wave quantum computer able to do TD-DFT calculations?" Tags="|quantum-chemistry|td-dft|excited-states|energy|quantum-computing|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11964" PostTypeId="2" ParentId="11963" CreationDate="2023-11-24T15:49:05.080" Score="3" Body="&lt;h2&gt;Any computation that can be solved on an ordinary classical computer can in theory be turned into a QUBO problem.&lt;/h2&gt;&#xA;&lt;p&gt;This includes TD-DFT calculations. We know this because the the &lt;a href=&quot;https://arxiv.org/abs/quant-ph/0406180&quot; rel=&quot;nofollow noreferrer&quot;&gt;2-local Hamiltonian problem&lt;/a&gt; is &lt;a href=&quot;https://en.wikipedia.org/wiki/QMA#Problems_in_QMA&quot; rel=&quot;nofollow noreferrer&quot;&gt;QMA complete&lt;/a&gt; and there exist gadgets (see pages 72-73 of &lt;a href=&quot;https://arxiv.org/abs/1901.04405v2&quot; rel=&quot;nofollow noreferrer&quot;&gt;my book about gadgets for Hamiltonians&lt;/a&gt;) that can transform arbitrary 2-local Hamiltonians into Ising Hamiltonians or QUBO problems if you include enough auxiliary spins/qubits (in the case of an Ising model) or binary variables (in the case of QUBO). The key phrase though, is &amp;quot;&lt;em&gt;&lt;strong&gt;if you include enough auxiliary spins/qubits/binary-variables&lt;/strong&gt;&lt;/em&gt;&amp;quot;, and currently there are no examples of real-world problems for which solving QUBO is known to be an efficient way to do computations. Said another way: if there's a way to do TD-DFT calculations via solving QUBO problems, that is worthwhile to you as a researcher, it is not yet known, or else it ought to mentioned in an answer to one of the following questions:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://or.stackexchange.com/q/1380/727&quot;&gt;Are there any real-world problems where quadratization helps to solve something that couldn't have been solved without quadratization?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://or.stackexchange.com/q/828/727&quot;&gt;What are some real-world applications of QUBO?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;My answers to the following questions may also be of interest to you:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://or.stackexchange.com/a/6620/727&quot;&gt;Can QUBO solve this inverse Ising problem?&lt;/a&gt; [Operations Research Stack Exchange]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/23309/2293&quot;&gt;Can any binary problem be solved by a QUBO?&lt;/a&gt; [Quantum Computing Stack Exchange]&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://or.stackexchange.com/a/5047/727&quot;&gt;Can operations research be used for protein folding?&lt;/a&gt; [Operations Research Stack Exchange]&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-24T15:49:05.080" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11965" PostTypeId="1" CreationDate="2023-11-24T20:30:18.967" Score="1" ViewCount="17" Body="&lt;p&gt;Cross-posted &lt;a href=&quot;https://earthscience.stackexchange.com/q/25763/18946&quot;&gt;on Earth Science&lt;/a&gt; and &lt;a href=&quot;https://chemistry.stackexchange.com/q/177860/27342&quot;&gt;Chemistry&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know where can I find measured thermal conductivity and thermal diffusivity of diatomite for different temperatures? I'm looking for the temperature dependency for temperatures higher than 300K. The upper temperature limit shall be at least 1000K, but more is better. All I have found is thermal conductivity in &amp;quot;Touloukian, Y. S., et al. &amp;quot;Thermophysical properties of matter - The TPRC data series. Volume 2. Thermal conductivity - nonmetallic solids. (1971)&amp;quot;. I'm still missing data on thermal diffusivity though, and I'd like to see more data on thermal conductivity, if available.&lt;/p&gt;&#xA;&lt;p&gt;Any help will be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="8421" LastEditorUserId="5" LastEditDate="2023-12-19T20:00:52.753" LastActivityDate="2023-12-19T20:00:52.753" Title="Thermal conductivity and diffusivity of diatomite (also known as diatomaceous earth or kieselguhr)" Tags="|temperature|thermal|" AnswerCount="0" CommentCount="1" ClosedDate="2024-01-11T14:37:19.470" ContentLicense="CC BY-SA 4.0" />
  <row Id="11966" PostTypeId="1" CreationDate="2023-11-25T09:25:36.317" Score="4" ViewCount="28" Body="&lt;p&gt;Can someone provide guidance on how to include Spin-orbit Coupling (SoC) for the band structure calcualtion using SIESTA?&lt;/p&gt;&#xA;&lt;p&gt;I have used the #Flag #Spin spin-orbit, but I only obtained spin dependence in one direction. Are there any other flags needed to obtain results for both up and down spins, or any alternative approaches to achieve this?&lt;/p&gt;&#xA;" OwnerUserId="8429" LastEditorUserId="1554" LastEditDate="2023-11-25T12:56:39.017" LastActivityDate="2023-11-25T12:56:39.017" Title="Why am I observing spin-orbit coupling in only one direction (spin up or spin down) in SIESTA (DFT)?" Tags="|siesta|" AnswerCount="0" CommentCount="4" ClosedDate="2023-12-19T17:21:02.243" ContentLicense="CC BY-SA 4.0" />
  <row Id="11967" PostTypeId="1" CreationDate="2023-11-25T09:40:07.053" Score="3" ViewCount="33" Body="&lt;p&gt;I have tried normal AIMD simulation using VASP for Non magnetic materials. Now, I am interested to perform the molecular dynamics simulations for the finite temperature for Magnetic materials to understand the evaluation of atomic positions with respect to magnetic degrees of freedom and temperature.&lt;/p&gt;&#xA;&lt;p&gt;For this case, how may I write the INCAR?&lt;/p&gt;&#xA;" OwnerUserId="8430" LastEditorUserId="5" LastEditDate="2023-11-25T21:27:38.780" LastActivityDate="2023-11-25T21:27:38.780" Title="How to perform atomistic spin dynamics (ASD) Ab Initio Molecular Dynamics (AIMD) using VASP?" Tags="|density-functional-theory|vasp|molecular-dynamics|aimd|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11968" PostTypeId="1" CreationDate="2023-11-26T02:56:32.413" Score="1" ViewCount="69" Body="&lt;p&gt;How does the wave-particle duality exhibited by electrons and the wave-like nature of phonons enable their interaction in solid-state systems?&lt;/p&gt;&#xA;&lt;p&gt;Can you explain the underlying mechanisms that allow for energy and momentum exchange between phonons and electrons, particularly in the context of electron-phonon scattering and the modulation of electronic properties by lattice vibrations?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-26T02:56:32.413" Title="Understanding the Interaction Between Phonons and Electrons in Solid-State Systems" Tags="|phonons|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="11970" PostTypeId="2" ParentId="11883" CreationDate="2023-11-27T00:26:06.083" Score="2" Body="&lt;p&gt;DFT+U is an advanced computational method developed specifically to enhance the accuracy of describing systems containing strongly correlated &lt;em&gt;d&lt;/em&gt; or &lt;em&gt;f&lt;/em&gt; electrons. These systems, such as antiferromagnetic NiO, often pose challenges for conventional LDA and GGA functionals, which tend to provide inaccurate description.&lt;/p&gt;&#xA;&lt;p&gt;When applying DFT+U in VASP, the parameter LMAXMIX plays a crucial role in controlling the range of l-quantum numbers for which the one-center PAW charge densities are processed and saved in the CHGCAR file. Unlike LDAUL or LDAUJ, which accept multiple values as an integer array, LMAXMIX is a single integer value. To accurately capture the effects of f-block elements in your system, it is recommended to set LMAXMIX=6. Thus, by choosing the value to 6, you already included other l-quantum numbers. However, it's important to note that this choice can lead to increased computational complexity.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-27T00:26:06.083" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11971" PostTypeId="1" CreationDate="2023-11-27T01:56:04.120" Score="1" ViewCount="99" Body="&lt;p&gt;Is there any tutorial or reference available to perform free energy calculations (umbrella sampling; thermodynamic integration; free energy perturbation; wisdom's particle insertion method) etc. with LAMMPS? I want to see an example code from a project that has fully done these calculations.&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="8438" LastEditorUserId="5" LastEditDate="2023-12-19T19:55:28.030" LastActivityDate="2023-12-19T19:55:28.030" Title="Free energy calculations for lammps" Tags="|molecular-dynamics|reference-request|lammps|software-input-file-request|free-energy|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11972" PostTypeId="1" CreationDate="2023-11-27T09:03:23.923" Score="2" ViewCount="22" Body="&lt;p&gt;I will define a new structure in Quantum ATK that is unavailable in the database.&lt;/p&gt;&#xA;&lt;p&gt;I tried this file to give information to the application, but it didn't work.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;################################################################################&#xA;# -------------------------------------------------------------&#xA;# Bulk Configuration&#xA;# -------------------------------------------------------------&#xA;&#xA;# Set up lattice&#xA;lattice = Hexagonal(6.2791373697288*Angstrom, 31.395686849*Angstrom)&#xA;&#xA;# Define elements&#xA;elements = [Indium, Indium, Silicon, Silicon , Sulfur, Sulfur,&#xA;            Sulfur, Sulfur, Sulfur, Sulfur]&#xA;&#xA;# Define coordinates&#xA;fractional_coordinates = [[2.100860978   0.000000000   2.83570303],&#xA;                         [2.100860978  0.000000000  0.566618954],&#xA;                         [5.240428412   1.812630103   1.701160992],&#xA;                         [2.100860978  3.625260206   1.701160992],&#xA;                         [3.139567435   1.799092358   3.402321984],&#xA;                         [4.201721956   3.638797952    0         ],&#xA;                         [1.062154521   1.799092358   0         ],&#xA;                         [0             3.638797952   3.402321984],&#xA;                         [4.178273892   0.000000000    0         ],&#xA;                         [6.302582933   0.000000000   3.402321984]]&#xA;&#xA;# Set up configuration&#xA;bulk_configuration = BulkConfiguration(&#xA;    bravais_lattice=lattice,&#xA;    elements=elements,&#xA;    fractional_coordinates=fractional_coordinates&#xA;    )&#xA;    ##################################################################################&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8441" LastEditorUserId="24" LastEditDate="2023-11-27T14:57:02.273" LastActivityDate="2023-11-27T14:57:02.273" Title="How to define new 2D-structure in Quantum ATK?" Tags="|quantum-atk|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11973" PostTypeId="2" ParentId="11918" CreationDate="2023-11-27T10:49:00.507" Score="1" Body="&lt;p&gt;Upon further examination, although the recursion relation used to evaluate the &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; functions given in the paper are wrong, it turns out that the equation in terms of the binomial coefficients is actually correct. There are numerous other typos in the paper, as well.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-11-27T10:49:00.507" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11974" PostTypeId="2" ParentId="11942" CreationDate="2023-11-27T10:56:24.417" Score="5" Body="&lt;p&gt;We have discussed the reproducibility of DFT calculations recently in&#xA;&lt;a href=&quot;https://doi.org/10.1063/5.0167763&quot; rel=&quot;noreferrer&quot;&gt;J. Chem. Phys. 159, 114116 (2023)&lt;/a&gt;. The calculations in &lt;a href=&quot;https://doi.org/10.1021/jacs.3c01933&quot; rel=&quot;noreferrer&quot;&gt;J. Am. Chem. Soc. 145, 9273–9284 (2023)&lt;/a&gt;  were carried out with the B3LYP functional in Turbomole, which does not match the B3LYP functional as published by Stephens et al in 1994, who used the RPA variant of the VWN correlation functional instead of the recommended version by VWN. I am not sure which variant ORCA implements, but it is entirely possible that the difference you see in absolute energies is caused by the discrepancy of the density functionals.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2023-11-27T10:56:24.417" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11975" PostTypeId="1" CreationDate="2023-11-27T13:21:19.277" Score="3" ViewCount="29" Body="&lt;p&gt;I have a water cluster(suppose) generated from MD run. Now, I want to optimize the geometry of only one water molecule of interest using QC methods (e.g. B3LYP/6-31+G(d,p)). I intend that the water molecule in my interest sees the other molecules, feels the forces from others, and changes its geometries. But the other molecules should not change their orientations.&#xA;I initially tried to do a constrained geometry optimization, freezing the coordinates of all the other molecules and optimizing the desired molecule. I think my process is wrong because the central molecule always tries to get the optimized geometry in a vacuum. The bond parameters after constrained optimization are as follows,&lt;/p&gt;&#xA;&lt;p&gt;Table-1 Optimized bond parameters of water molecule in a cluster&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;No of Runs&lt;/th&gt;&#xA;&lt;th&gt;O-H1&lt;/th&gt;&#xA;&lt;th&gt;O-H2&lt;/th&gt;&#xA;&lt;th&gt;&amp;lt;H-O-H&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;107.2&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;0.97&lt;/td&gt;&#xA;&lt;td&gt;0.99&lt;/td&gt;&#xA;&lt;td&gt;105.8&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;103.7&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;0.98&lt;/td&gt;&#xA;&lt;td&gt;104.5&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;In each run, the input geometry were different. I think the water molecule do not see its surroundings. Is there any other procedure to perform this?&lt;/p&gt;&#xA;&lt;p&gt;I am using gaussian and the part of input is provided below,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=12&#xA;# b3lyp/6-31+g(d,p) opt&#xA;&#xA;Water_Clusters_2&#xA;&#xA;0 1&#xA;O 0     -0.09390576      -0.45183448      -0.59180983&#xA;H 0     0.16750407      -0.14856647      -1.49420182&#xA;H 0     0.18256709      0.31842892      -0.02631596&#xA;O -1     1.00231196      1.52224084      1.1787738&#xA;H -1     1.25538061      2.24014492      0.65216815&#xA;H -1     1.87806003      1.29311014      1.6661256&#xA;O -1     1.08837153      -2.68452486      0.38127222&#xA;H -1     1.95970961      -2.80844083      0.7159187&#xA;H -1     0.81757222      -1.76132007      0.29217934&#xA;O -1     -2.67938906      -0.15180864      -1.36528883&#xA;H -1     -3.01086211      -0.19444878      -2.26724243&#xA;H -1     -1.75668721      -0.1300075      -1.40009288&#xA;O -1     1.23091274      0.89115464      -2.72058107&#xA;H -1     0.84775908      1.51321166      -3.39661546&#xA;H -1     2.1591499       1.12729822      -2.62721016&#xA;O -1     -3.36169761      -2.47394794      0.05216379&#xA;H -1     -2.90747991      -1.67693393      -0.34192527&#xA;H -1     -3.32528304      -2.49691151      1.00874685&#xA;O -1     -0.11898284      -1.37525577      -4.04574236&#xA;H -1     0.70166768      -0.85704547      -3.81234518&#xA;H -1     0.02456058      -2.25007808      -3.61809087&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2023-11-27T13:21:19.277" Title="Constrained geometry optmization: Molecule interacts with its surroundings" Tags="|density-functional-theory|gaussian|geometry-optimization|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="11976" PostTypeId="2" ParentId="11956" CreationDate="2023-11-27T19:44:38.777" Score="2" Body="&lt;h1&gt;Preamble&lt;/h1&gt;&#xA;&lt;p&gt;After &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/11956/what-are-the-observables-when-a-quantum-system-is-comprised-of-orthogonal-spacet#comment25626_11956&quot;&gt;Susi's vote to close this question&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I’m voting to close this question because this belongs in the physics network.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64772559#64772559&quot;&gt;I inquired with a Physics.SE diamond moderator&lt;/a&gt; to see whether or not  Physics.SE would accept having this question migrated there.  The answer I received was this:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The question is nonsense. I would close it as unclear what you're asking or non-mainstream if it appeared here.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;When I asked for more details, the first one given was this:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;None of the 4 properties listed mean anything within mainstream quantum mechanics&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This made me try to re-read your question more thoroughly, and made me try to make more sense of it.&lt;/p&gt;&#xA;&lt;h1&gt;Does the question make sense?&lt;/h1&gt;&#xA;&lt;p&gt;I will try to go in chronological order through the four properties that you described:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;(1) domains A and B are independent Hilbert spaces, each with their own space and time dimensions.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What does it means for A and B to &amp;quot;each have their own space and time dimensions&amp;quot;? Does A have 3 space dimensions and 1 time dimension, in addition to B having 3 space dimensions and 1 time dimension? Do we have 8 dimensions in total? Plenty of well-respected researchers have used more than 4 dimensions to model the universe, but most people model the universe with 3+1 dimensions (3 space and 1 time dimension) rather than 6+2 dimensions (6 space and 2 time dimensions), so when you say &amp;quot;each with their own space and time dimensions&amp;quot; I would recommend for you to clarify this, perhaps by writing &amp;quot;6 space dimensions and 2 time dimensions in total&amp;quot; in parentheses at the end; or if what you mean is that A and B describe different independent parts of our 3+1 dimensional universe you could make that more clear. Much later you wrote &amp;quot;the two domains do not share a common time dimension&amp;quot;, so perhaps you do want to model the universe with more than one time dimension, but it is not clear what that means and what your goal is.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;(2) domain C is a quantum &amp;quot;foam&amp;quot; lacking coherent space and time dimensions&lt;br&gt;&#xA;(3) domains A and B have domain C in common&lt;br&gt;&#xA;(4) domain C is capable of transmitting null vectors between A and B.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I find it unusual to discuss &amp;quot;transmitting [null] vectors between A and B&amp;quot;. The description of your problem reminds me of open quantum systems theory, in which two systems can be &amp;quot;open&amp;quot; to interaction with a common &amp;quot;bath&amp;quot;, which we will call C. If a &amp;quot;vector&amp;quot; is a wavefunction, like the wavefunction for a photon, then the bath C can mediate the transfer of the photon from system A to system B. However, you might want to clarify what you mean by &amp;quot;null vector&amp;quot;, and I might be being far too generous by associating your description of a &amp;quot;quantum phone&amp;quot; with the &amp;quot;open quantum systems&amp;quot; notion of a &amp;quot;bath&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the next (and final) two paragraphs in your question, you have provided five sentences, and the first two sentences make sense to me, but the next three need a lot of clarification in my opinion. If you are going to ask this question anywhere, I would recommend to thoroughly explain the last three sentences (e.g. what is an example of an &amp;quot;observable of a photon &lt;em&gt;&lt;strong&gt;relative to a&lt;/strong&gt;&lt;/em&gt; domain/Hilbert-space&amp;quot;; why does the fact that a measurement takes a non-zero amount of time to make, mean that &amp;quot;the observables cannot include energy&amp;quot;; what do you mean by the &amp;quot;projection of domain A on B&amp;quot; and why is it a dimensionless &amp;quot;point&amp;quot; and why does that make &amp;quot;position and momentum problematic&amp;quot;?).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-11-27T19:44:38.777" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11977" PostTypeId="1" CreationDate="2023-11-27T19:49:27.420" Score="2" ViewCount="33" Body="&lt;p&gt;I am trying to calculate the free energy between a protein and aptamer using GROMACS. Literature has indicated that one of the best way to do so is by performing an umbrella sampling MD simulation that involves a non-equilibrium pulling simulation that pulls the protein and aptamer apart. I have been running these simulations on certain protein-aptamer complexes but some of the free energy values that I am getting do not match the experimental free energy values from biology experiments. I am thinking that perhaps the pulling direction that I chose was not the best pulling direction. How do I determine the best/correct pulling direction?&lt;/p&gt;&#xA;&lt;p&gt;I am essentially using the procedure in this tutorial &lt;a href=&quot;http://www.mdtutorials.com/gmx/umbrella/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.mdtutorials.com/gmx/umbrella/index.html&lt;/a&gt; by Justin A. Lemkul, Ph.D., Virginia Tech Department of Biochemistry, except I am performing it on a protein-aptamer complex.&lt;/p&gt;&#xA;" OwnerDisplayName="unit vector" LastEditorUserId="5" LastEditDate="2023-11-28T13:37:14.867" LastActivityDate="2023-11-28T13:37:14.867" Title="How do you determine the Pull Direction for a GROMACS umbrella sampling simulation to generate the most accurate free energy value?" Tags="|computational-chemistry|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11978" PostTypeId="1" CreationDate="2023-11-28T14:56:55.843" Score="2" ViewCount="160" Body="&lt;p&gt;Can we calculate the &lt;strong&gt;absorption enthalpy&lt;/strong&gt; at different temperature in VASP software via &lt;strong&gt;ab initio molecular dynamics&lt;/strong&gt;? If yes, how?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="5" LastEditDate="2023-11-28T17:03:01.277" LastActivityDate="2023-11-29T06:30:26.917" Title="Absorption enthaply at different temprature in VASP software via ab initio molecular dynamics" Tags="|vasp|molecular-dynamics|computational-chemistry|monte-carlo|aimd|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="11979" PostTypeId="1" AcceptedAnswerId="11980" CreationDate="2023-11-29T02:29:43.183" Score="3" ViewCount="56" Body="&lt;p&gt;In reading Jorgensen's 1983 paper comparing the properties of 6 water models it was mentioned that there is the inclusion of an L-J potential between pairs of oxygen molecules, but no mention of similar terms for other pairwise potentials (O-H or H-H). As far as I'm aware, the continued use and updating of standard water molecules (SPC, TIP3P,...) in classical MD also do not include these extra L-J terms. Is this purely to limit the gross computational excess in performing these pairwise calculations? Thank you.&lt;/p&gt;&#xA;&lt;p&gt;Paper reference: &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article-abstract/79/2/926/776316/Comparison-of-simple-potential-functions-for&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jorgensen, William L., et al. &amp;quot;Comparison of simple potential functions for simulating liquid water.&amp;quot; The Journal of chemical physics 79.2 (1983): 926-935.&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6642" LastActivityDate="2023-11-29T03:19:55.073" Title="Exclusion of Lennard-Jones potential between O-H and H-H in water models" Tags="|molecular-dynamics|interatomic-potentials|water|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11980" PostTypeId="2" ParentId="11979" CreationDate="2023-11-29T03:19:55.073" Score="4" Body="&lt;p&gt;The original publications may give some reason for omitting HH and OH Lennard-Jones terms -- but my first assumption would certainly be computational simplicity. Having said that, these models &lt;em&gt;are&lt;/em&gt; good enough for everyday application.&lt;/p&gt;&#xA;&lt;p&gt;Molecular dynamics force fields are &amp;quot;models&amp;quot; much more than they are &amp;quot;approximations&amp;quot; -- adding more terms does &lt;em&gt;not&lt;/em&gt; guarantee more accurate results. A well-parametrised force field contains a good &lt;em&gt;combination&lt;/em&gt; of interactions, even if any of those individual interactions might be poorly motivated on their own.&lt;/p&gt;&#xA;&lt;p&gt;As an example, because CHARMM36 protein interactions were parametrised with &amp;quot;sTIP3P&amp;quot; water (only OO LJs), their unfolded states are over-stabilised in &amp;quot;mTIP3P&amp;quot; water (both O and H LJ sites -- widely used with CHARMM), according to &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcb.6b01316&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. More is not always better.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2023-11-29T03:19:55.073" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11981" PostTypeId="2" ParentId="11978" CreationDate="2023-11-29T06:30:26.917" Score="1" Body="&lt;p&gt;I will give a general outline on how to perform such caculation. Before we start with the AIMD calculations we need to find the perferred adsorption site/sites according to the following steps:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Geometry Optimization: Start by performing a geometry optimization of the isolated adsorbate and the surface (or Bulk depending on your structure) without any constraints. This step ensures that the structures are relaxed and at their minimum energy configurations.&lt;/li&gt;&#xA;&lt;li&gt;Slab Preparation: Create the surface slab model by constructing the desired surface unit cell, including the adsorption site. Make sure to include a sufficient vacuum region to avoid interactions between periodic images.&lt;/li&gt;&#xA;&lt;li&gt;Adsorption Site Determination: Identify the adsorption site on the surface where the adsorbate will bind. This can be done by considering the surface structure and chemical interactions. It's crucial to choose a physically reasonable and chemically relevant adsorption site. Within this step, you can get the adsorption energy of let's say molecule (A) on the desired surface at (0K).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;At the end of those steps, we would have a strucutre of adsorbate/adsorbent which will be used as the starting geometry for the AIMD run.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;AIMD Simulation: Construct the necessary input files for the AIMD calculation in VASP. This includes specifying the computational parameters such as the time step, temperature, ensemble (e.g., NVE, NVT), and convergence criteria. You may need to use a thermostat to control the temperature during the simulation. Here I provide some general tags for AIMD, you may need to check the documentations and vaspwiki for further information regarding each of those tags:&lt;/p&gt;&#xA;&lt;h1&gt;General tags&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;  PREC   = Normal    &#xA;  ENCUT  = 400   &#xA;  ALGO   = Fast  &#xA;  LREAL  = Auto  &#xA;  ISMEAR = 0         # Gaussian smearing &#xA;  SIGMA  = 0.05      &#xA;  ISYM   = 0         # Symmetry off  &#xA;&#xA;  # MD related   &#xA;  IBRION = 0         # MD    &#xA;  POTIM  = 0.5       # Time step=0.5 fs&#xA;  NSW    = 100       # Number of ionic steps &#xA;  TEBEG  = 400       # Start temperature         &#xA;  TEEND  = 400       # Final temperature     &#xA;  SMASS  = 0         # Canonical (Nose-Hoover) thermostat    &#xA;  POMASS = 16.0  2.0 # Deuterium mass for Hydrogen   &#xA;&#xA;  # Don’t write WAVECAR or CHGCAR    &#xA;  LWAVE  = F     &#xA;  LCHARG = F &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;and remember to use gamma-only for the kpoint sampling:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#KPOINTS (Gamma-only)   &#xA;      0 &#xA;     Gamma  &#xA;     1  1   1   &#xA;     0  0   0&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;run the calculation with vasp_gam when using Gamma-only scheme. Moreover, the simulation time should be long enough to account for the equilibration of the system and to capture the desired dynamics. Here by controlling the TEBEG and TEEND, you can specifiy the starting and end temperature. In case you don't want the temperature to change then you will set those tags to the same value. At each time step, VASP will output the temperature, geometry (CONTCAR files), and total energy of the system which is this case (molecule+surface). Now you may choose to calculate the adosrption energy at specific points in time by subtracting the total energy of isolated molecule (Ea) and (slab or surface, Eb) from the total energy of the molecule/slab complex (Eab) which you have now at this specific point from the AIMD calculation. You may need to perform a single-point calculation in order to get Ea and Eb based on the CONTCAR file that was generated at the corresponding temperature.&lt;/p&gt;&#xA;&lt;p&gt;You have to pay attention that raising up the temperature will lead to the desoprtion of the molecule from the surface and in some cases you might get unrealistic results. Thus, you need to be very careful and do some tests before you go into a full compuatation because such calculations can be computationally heavy.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-29T06:30:26.917" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11982" PostTypeId="1" AcceptedAnswerId="11983" CreationDate="2023-11-29T07:50:10.720" Score="4" ViewCount="157" Body="&lt;p&gt;For electronic structure calculation, when optimizing the wavefunction for an infinite periodic material, the proton-proton energy is needed to monitor the convergence of the SCF loop.&lt;/p&gt;&#xA;&lt;p&gt;How is the proton-proton energy computed to ensure convergence of&#xA;the SCF loop in electronic structure calculations for infinite&#xA;periodic materials?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-11-29T12:13:14.420" LastActivityDate="2023-11-29T13:07:57.420" Title="Computing proton-proton potentials for infinite periodic materials" Tags="|electronic-structure|geometry-optimization|periodic-system|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11983" PostTypeId="2" ParentId="11982" CreationDate="2023-11-29T13:07:57.420" Score="3" Body="&lt;p&gt;In electronic structure calculations for infinite periodic materials, the proton-proton energy is typically not directly computed or used to monitor the convergence of the self-consistent field (SCF) loop. Instead, the focus is on the total energy convergence, which includes the contributions from electron-electron interactions, electron-nucleus interactions, and kinetic energy.&lt;/p&gt;&#xA;&lt;p&gt;The SCF loop in electronic structure calculations aims to optimize the wavefunction of the system by iteratively solving the Schrödinger equation. The convergence of the SCF loop is typically determined by comparing the total energy of the system between successive iterations. When the total energy changes by a small amount (below a predefined threshold) between iterations, it is considered converged.&lt;/p&gt;&#xA;&lt;p&gt;In periodic calculations, the interactions between protons (nuclei) are usually accounted for using a combination of pseudopotentials (which describe the electron-nucleus interactions) and periodic boundary conditions (which mimic the infinite repetition of the crystal lattice). The electron-electron interactions are treated using techniques such as density functional theory (DFT) or wavefunction-based methods like Hartree-Fock theory.&lt;/p&gt;&#xA;&lt;p&gt;Generally speaking, in many-body electronic structure calculations, the nuclei of the molecules or clusters being studied are typically considered stationary, following the Born-Oppenheimer approximation. This approximation allows us to create a static external potential V, within which the electrons dynamically interact.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-29T13:07:57.420" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11984" PostTypeId="1" CreationDate="2023-11-29T16:18:56.063" Score="4" ViewCount="59" Body="&lt;p&gt;Similar to:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1513/what-are-the-types-of-dft&quot;&gt;What are the types of DFT?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1439/what-are-the-types-of-charge-analysis&quot;&gt;What are the types of charge analysis?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/901/what-are-the-types-of-bond-orders&quot;&gt;What are the types of bond orders?&lt;/a&gt;, and&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/392/what-are-some-recent-developments-in-density-functional-theory&quot;&gt;What are some recent developments in density functional theory?&lt;/a&gt;,&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I would like to ask: &lt;strong&gt;What are the different types of solvation models?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8416" LastEditorUserId="5" LastEditDate="2023-11-29T18:39:08.817" LastActivityDate="2023-11-30T08:39:21.470" Title="What are the types of solvation models?" Tags="|one-topic-per-answer|solvation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11985" PostTypeId="2" ParentId="11873" CreationDate="2023-11-29T19:03:48.943" Score="2" Body="&lt;p&gt;As I mentioned in my latest comments, I thought I solved this problem, discovered I didnt, and now I have truly solved my problem. I will now provide the steps I took in my particular use case, but these can be modified to suit other use cases. I should specify, my own use case is to run LAMMPS simulations via a supercomputer.&lt;/p&gt;&#xA;&lt;p&gt;Starting from scratch in your $HOME directory, do the following&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;mkdir -p $HOME/{venvs,sources,software}&#xA;&amp;gt;module load gcc/9.3.0 cuda/11.0 openmpi/4.0.3&#xA;&#xA;&amp;gt;module load python/3.10.2 cudnn/8.0.3 mpi4py/3.0.3&#xA;##The module load commands are specific to my own use with the supercomputer. Load these in however you need&#xA;&amp;gt;virtualenv --no-download &lt;span class=&quot;math-container&quot;&gt;$HOME/venvs/deepmd&#xA;&amp;gt;source $&lt;/span&gt;HOME/venvs/deepmd/bin/activate&#xA;#Make sure the venv is activated for the rest of this process&#xA;&amp;gt;pip install --no-index --upgrade pip&#xA;&amp;gt;pip install --no-index tensorflow==2.14.0&#xA;&amp;gt;pip install --no-index horovod==0.28.1&#xA;&amp;gt;cd &lt;span class=&quot;math-container&quot;&gt;$HOME/sources&#xA;&amp;gt;git clone https://github.com/deepmodeling/deepmd-kit.git deepmd-kit&#xA;&amp;gt;deepmd_source_dir=$&lt;/span&gt;HOME/sources/deepmd-kit&#xA;#as a sanity check, use the echo command to ensure this path was stored properly&#xA;&amp;gt;cd &lt;span class=&quot;math-container&quot;&gt;$deepmd_source_dir&#xA;&amp;gt;pip install .&#xA;&amp;gt;cd $&lt;/span&gt;HOME/sources&#xA;&amp;gt;wget https://github.com/lammps/lammps/archive/stable_2Aug2023_update1.tar.gz&#xA;&amp;gt;tar -xf stable_2Aug2023_update1.tar.gz&#xA;&amp;gt;lammps_source_dir=&lt;span class=&quot;math-container&quot;&gt;$HOME/sources/lammps-stable_2Aug2023_update1&#xA;&amp;gt;cd $&lt;/span&gt;deepmd_source_dir&#xA;&amp;gt;cd source&#xA;&amp;gt;mkdir build&#xA;&amp;gt;cd build&#xA;&amp;gt;deepmd_root=&lt;span class=&quot;math-container&quot;&gt;$HOME/software/deepmd&#xA;&amp;gt;cmake -DUSE_TF_PYTHON_LIBS=TRUE -DLAMMPS_SOURCE_ROOT=$&lt;/span&gt;lammps_source_dir -DCMAKE_INSTALL_PREFIX=&lt;span class=&quot;math-container&quot;&gt;$deepmd_root ..&#xA;#If you installed tensorflow a different way, you need to add a cmake argument that specifies the location of the tf source code&#xA;&amp;gt;make -j4&#xA;&amp;gt;make install&#xA;&amp;gt;cd $&lt;/span&gt;lammps_source_dir&#xA;&amp;gt;mkdir build&#xA;&amp;gt;cd build&#xA;&amp;gt;cmake -DPKG_PLUGIN=ON -DLAMMPS_INSTALL_RPATH=ON -DBUILD_SHARED_LIBS=yes -DCMAKE_INSTALL_PREFIX=&lt;span class=&quot;math-container&quot;&gt;${deepmd_root} -DCMAKE_INSTALL_LIBDIR=lib -DCMAKE_INSTALL_FULL_LIBDIR=$&lt;/span&gt;{deepmd_root}/lib ../cmake&#xA;&amp;gt;make -j4&#xA;&amp;gt;make install&#xA;&amp;gt;export PATH=&lt;span class=&quot;math-container&quot;&gt;$HOME/$&lt;/span&gt;deepmd_root/bin:$PATH&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This installation process ideally should go well, however, it is at this point that two main issues can arise. This first is that LAMMPS cannot find the deepmd code despite defining the path variable during the installation process. In my specific user case, I have to run a bash script on the supercomputer I am using to be able to start the LAMMPS simulation. In that script, I need to have the following lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;module load gcc/9.3.0 cuda/11.0 openmpi/4.0.3&#xA;&amp;gt;module load python/3.10.2 cudnn/8.0.3 mpi4py/3.0.3&#xA;&amp;gt;source &lt;span class=&quot;math-container&quot;&gt;$HOME/venvs/deepmd/bin/activate&#xA;&amp;gt;deepmd_root=$&lt;/span&gt;HOME/software/deepmd&#xA;&amp;gt;export PATH=&lt;span class=&quot;math-container&quot;&gt;$deepmd_root/bin:$&lt;/span&gt;PATH&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Adding these lines into my bash script solves the problem that LAMMPS cannot locate deepmd at all. The other main issue (which seems to be a commonly reported problem) is that when running a LAMMPS job with deepmd, the pair_style argument of deepmd is not recognized. For me, this had a very simple solution that does not appear to be documented well. During the installation process, a /deepmd/lib/ folder will be created, and it has a set of plugin files in it. So when creating the LAMMPS input script, you need to physically load that file for the pair style to be recognized. For me, I used the command &amp;quot;plugin load libdeepmd_lmp.so&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;With these steps, I was able to successfully run a water simulation. I had my own input files, but the deepmd source code also provides an example water simulation as well as many others. I should note that these steps are specific to the GPU supported version. If one would like the CPU supported version, there will be a slight modification of the steps I provided above&lt;/p&gt;&#xA;" OwnerUserId="8065" LastEditorUserId="5" LastEditDate="2023-11-29T19:22:10.283" LastActivityDate="2023-11-29T19:22:10.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11986" PostTypeId="2" ParentId="11984" CreationDate="2023-11-29T19:20:13.113" Score="3" Body="&lt;h1&gt;COSMO&lt;/h1&gt;&#xA;&lt;p&gt;&lt;strong&gt;Name:&lt;/strong&gt; COSMO = &lt;em&gt;&lt;strong&gt;Co&lt;/strong&gt;&lt;/em&gt;nductor-like &lt;em&gt;&lt;strong&gt;S&lt;/strong&gt;&lt;/em&gt;creening &lt;em&gt;&lt;strong&gt;M&lt;/strong&gt;&lt;/em&gt;odel.&lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Type:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Implicit&lt;/li&gt;&#xA;&lt;li&gt;Dielectric continuum model&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;First appearance:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;1993 by Klamt &amp;amp; Schüürmann, &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/1993/P2/P29930000799&quot; rel=&quot;nofollow noreferrer&quot;&gt;COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Similar to: 1987 Hoshi &lt;em&gt;et al&lt;/em&gt;. &lt;a href=&quot;https://doi.org/10.1063/1.453343&quot; rel=&quot;nofollow noreferrer&quot;&gt;Medium effects on the molecular electronic structure. I. The formulation of a theory for the estimation of a molecular electronic structure surrounded by an anisotropic medium&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Description:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Like other continuum solvent models, the solvent is treated as a continuum with a &lt;a href=&quot;https://en.wikipedia.org/wiki/Permittivity&quot; rel=&quot;nofollow noreferrer&quot;&gt;permitivity&lt;/a&gt; of &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt;.  The energy of the electrostatic interaction between the solute and the solvent is determined based on the charge distribution of the solute molecule (which is determined by whatever electronic structure method you wish, independent of whether or not you're using the COSMO model), and by the effective charges &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; on the solvent, which are given based on the charges &lt;span class=&quot;math-container&quot;&gt;$q^*$&lt;/span&gt; on the surface segments as follows:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{align}&#xA;\tag{1}&#xA;q &amp;amp;= \frac{\varepsilon -1}{\varepsilon + 1/2}q^* ~~~, &amp;amp;\textrm{for neutral solvent molecules}, \\&#xA;q&amp;amp;=  \frac{\varepsilon -1}{\varepsilon }q^* ~~~, &amp;amp;\textrm{for ionic solvent molecules}. \tag{2}&#xA;\end{align}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Implementations:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4541/5&quot;&gt;OpenMOLCAS&lt;/a&gt; (open source)&lt;/li&gt;&#xA;&lt;li&gt;Gaussian (apparently uses Eq. 2 even for neutral solvent molecules, erroneously)&lt;/li&gt;&#xA;&lt;li&gt;NWChem (open source)&lt;/li&gt;&#xA;&lt;li&gt;MOPAC (open source until MOPAC 7.1 in 2006, expensive for MOPAC 2007, 2009, etc, then again &lt;a href=&quot;https://github.com/openmopac/MOPAC&quot; rel=&quot;nofollow noreferrer&quot;&gt;open source since 2022&lt;/a&gt;)&lt;/li&gt;&#xA;&lt;li&gt;TURBOMOLE&lt;/li&gt;&#xA;&lt;li&gt;Q-Chem&lt;/li&gt;&#xA;&lt;li&gt;Many others&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Computational cost:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Due to the simplicity of Eqn. 1 and 2, it is not very computationally costly, and can be used for large and/or irregularly formed molecular structures, whereas the PCM (polarizable continuum model) attempts to use &amp;quot;exact&amp;quot; dielectric boundary conditions instead of the approximations given in Eqs. 1-2, and therefore can only be used for small solvent molecules with spherical, ellipsoidal, or quasi-spherical shapes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Accuracy:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;A variant of the PCM model was compared to COSMO in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.5b00601&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; and the difference in the two models, was found to be small compared to the deviation from experimental solvation data, so a conclusion that can perhaps be drawn from that paper was that you might as well use the COSMO model (as long as your situation is similar enough to the situation in that study).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Like all continuum solvent models, the effects of things like hydrogen bonding and reorientation are neglected, and this is considered to be a bigger issue than the choice of &lt;em&gt;&lt;strong&gt;which&lt;/strong&gt;&lt;/em&gt; continuum solvent model is used.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;Warnings:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Different implementations may use a slightly different formula (see the part in parentheses after Gaussian was mentioned earlier in this answer, for example). Each implementation might also have its own unique way of treating the geometry of the solvent molecules (e.g. radii of the effective spheres, cavity construction, surface segments, etc.), so &lt;em&gt;&lt;strong&gt;unfortunately the numerical result from a COSMO calculation done with one software might not be the same as with another software&lt;/strong&gt;&lt;/em&gt; (this might be a problem for most solvent models though).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Related models / extensions:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/COSMO-RS&quot; rel=&quot;nofollow noreferrer&quot;&gt;COSMO-RS&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastEditorUserId="142" LastEditDate="2023-11-30T08:39:21.470" LastActivityDate="2023-11-30T08:39:21.470" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11987" PostTypeId="1" CreationDate="2023-11-29T19:34:25.163" Score="5" ViewCount="226" Body="&lt;p&gt;I am searching for calculating Bader charge using Quantum ESPRESSO. I am using pseudopotential based DFT calculation. And I have charge density files (cube and XSF formats).&lt;/p&gt;&#xA;&lt;p&gt;My objective is to determine interstitial charge (charge in the void spaces, or between two atoms).&lt;/p&gt;&#xA;&lt;p&gt;It would be great to know the step by step procedure to get the Bader charge through Bader analysis. (I have installed Henkelman Bader in my computer. I can install other as well, if suggested)&lt;/p&gt;&#xA;" OwnerUserId="5723" LastActivityDate="2023-11-30T00:58:33.770" Title="Bader charge calculation in Quantum ESPRESSO DFT" Tags="|density-functional-theory|quantum-espresso|charge-density|bader|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11988" PostTypeId="1" AcceptedAnswerId="11999" CreationDate="2023-11-29T20:19:30.873" Score="2" ViewCount="64" Body="&lt;p&gt;I am trying to fully populate my GROMACS simulation, but the water density in the bulk is too low.&lt;/p&gt;&#xA;&lt;p&gt;Here are the steps I used:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Add organic monolayer into 9x9x9 box&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Solvate with water&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;equilibrate t-coupled, then p,t coupled&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;expand box to 9x9x30 (to create interface, this allows for organic molecules to form a monolayer)&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;equlibrate t-coupled&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;prod&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The problem seems to be with step 2 as GROMACS can only seem to fit 0.9 g/ml of water in the original system (because there are a bunch of organic molecules), &lt;strong&gt;is there a way to force it to have a certain density?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7556" LastEditorUserId="5" LastEditDate="2023-11-29T20:30:50.780" LastActivityDate="2023-12-01T10:47:02.363" Title="Is there a way to force GROMACS to keep a certain density for water?" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11989" PostTypeId="2" ParentId="11987" CreationDate="2023-11-30T00:58:33.770" Score="3" Body="&lt;p&gt;As far as you have correctly obtained the charge density files, the procedure is straight forward.&lt;/p&gt;&#xA;&lt;p&gt;I will assume that you have the all-electron density and the valence electron density. If not, then This can be achieved by pp.x (post processing) utility provided with the Quantum Espresso package. As an example for the valence density:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;inputpp&#xA;    prefix  = 'yoursystem'&#xA;    outdir = './'&#xA;    filplot = 'yoursystem_valence'&#xA;    plot_num= 0&#xA;/&#xA;&amp;amp;plot&#xA;nfile = 1&#xA;iflag = 3&#xA;output_format = 6&#xA;fileout = 'yoursystem.cube'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the all-electron density:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;inputpp&#xA;    prefix  = 'yoursystem'&#xA;    outdir = './'&#xA;    filplot = 'yoursystem_allelec'&#xA;    plot_num= 21&#xA;/&#xA;&amp;amp;plot&#xA;nfile = 1&#xA;iflag = 3&#xA;output_format = 6&#xA;fileout = 'yoursystem_allelec.cube'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The most important difference between the two input files is the plot_num line which specifies the physical quantities (all-electron or valence densities) that are written to the fileout file and then&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&lt;span class=&quot;math-container&quot;&gt;$ pp.x &amp;lt; yoursystem_val.pp.in &amp;gt; yoursystem_val.pp.out&#xA;$&lt;/span&gt; pp.x &amp;lt; yoursystem_all.pp.in &amp;gt; yoursystem_all.pp.out&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now suppose you have Bader program installed you can perform Bader partitioning on the .cube files created by pp.x:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;bader yoursystem_valence.cube -ref yoursystem_allelec.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;as a result, you will get The Bader charges on each atom contained in the ACF.dat file which will look like the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#         X           Y           Z       CHARGE      MIN DIST   ATOMIC VOL&#xA; --------------------------------------------------------------------------------&#xA;    1  -10.660000   10.660000   10.660000    8.140837     1.940149    64.992061&#xA;    2   -5.330000    5.330000    5.330000    7.859147     2.931500   237.846813&#xA; --------------------------------------------------------------------------------&#xA;    VACUUM CHARGE:               0.0000&#xA;    VACUUM VOLUME:               0.0000&#xA;    NUMBER OF ELECTRONS:        16.0000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This example is specifically for NaCl. It shows that out of 16 valence electrons, 8.14 is assigned to Na and 7.86 to Cl. To convert this to ionic charge, you need to check the number of electrons that are fixed in the core. This can be achieved by looking at 'valence configuration' lines in the pseudopotential files for the constituant atoms. for instance, in the case of Na:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Valence configuration:&#xA;    nl pn  l   occ       Rcut    Rcut US       E pseu&#xA;    2S  1  0  2.00      1.000      1.250    -4.158089&#xA;    3S  2  0  1.00      1.000      1.250    -0.198813&#xA;    2P  2  1  6.00      0.900      1.300    -2.106125&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for Cl:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Valence configuration:&#xA;    nl pn  l   occ       Rcut    Rcut US       E pseu&#xA;    3S  1  0  2.00      1.200      1.600    -1.515413&#xA;    3P  2  1  5.00      1.300      1.600    -0.629258&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The Na pseudopotential indicates that two 1s electrons are fixed to the core, while the Cl pseudopotential indicates that two 1s, two 2s, and six 2p electrons are fixed to the core. From this, we can calculate the total electron number on Na as (2 + 8.14) = 10.14 and on Cl as (2 + 2 + 6 + 7.86) = 17.86. By subtracting these values from the atomic numbers for Na (11) and Cl (17), we arrive at Bader charge-based ionic charge states of Na_^(0.86+) and Cl_^(0.86-)&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-11-30T00:58:33.770" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11990" PostTypeId="1" CreationDate="2023-11-30T05:20:45.447" Score="4" ViewCount="262" Body="&lt;p&gt;I keep getting the following error for my orca code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[file orca_main/maininp1.cpp, line 17547]: ERROR: expect a '$', '!', '%', '*' or '[' in the input&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;[file orca_main/maininp1.cpp, line 17547]: ERROR: expect a '$', '!', '%', '*' or '[' in the input&lt;/p&gt;&#xA;&lt;p&gt;The input file is named &lt;code&gt;input.inp&lt;/code&gt; and is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;!B3LYP 6-311+G(d,p) D4 OPT PAL16&#xA;* xyzfile -2 1 reactants.xyz *&#xA;&#xA;&lt;span class=&quot;math-container&quot;&gt;$new_job&#xA;!B3LYP 6-311+G(d,p) D4 OPT PAL16&#xA;* xyzfile -2 1 products.xyz *&#xA;# ----------------------&#xA;# NEB Job&#xA;$&lt;/span&gt;new_job&#xA;&#xA;!B3LYP 6-311+G(d,p) D4 NEB FREQ MORead PAL16&#xA;&#xA;% moinp &amp;quot;input.gbw&amp;quot; &amp;quot;input_job2.gbw&amp;quot; end&#xA;&#xA;%neb&#xA;        NEB_END_XYZFILE &amp;quot;input_job2.xyz&amp;quot;&#xA;        Nimages 6&#xA;        PREOPT_ENDS TRUE&#xA;end&#xA;&#xA;* xyzfile -2 1 input.xyz *&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is it acceptable to have both the geometry optimizations and the transition state calculation in succession in the same input file? Or is there something actually wrong with the syntax? If anyone could point out the error to me, that would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6052" LastActivityDate="2023-12-01T02:34:17.113" Title="Syntax Error in ORCA" Tags="|orca|transition-state|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11991" PostTypeId="1" AcceptedAnswerId="12025" CreationDate="2023-11-30T06:37:57.943" Score="7" ViewCount="106" Body="&lt;p&gt;I have been conducting lattice vibration calculations using the Density Functional Perturbation Theory (DFPT) method. While investigating the convergence behavior, I noticed that when I increase the number of KPOINTS, I start observing imaginary frequencies in the results. This behavior seems counterintuitive, as I expected more accurate results with higher k-point sampling.&lt;/p&gt;&#xA;&lt;p&gt;Could someone help me understand the possible causes behind the appearance of these imaginary frequencies with increasing KPOINTS? Are there any specific considerations or potential issues I should be aware of when interpreting these results? Additionally, how can I determine the appropriate number of k-points for accurate lattice vibration calculations? Any insights or suggestions would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;I am using VASP/DFPT and here is the INCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;EDIFF = 1E-8&#xA;ENCUT = 400&#xA;ALGO = Fast&#xA;IBRION = 8&#xA;ISMEAR = 0&#xA;SIGMA = 0.2&#xA;PREC = Accurate&#xA;LREAL = .F.&#xA;ADDGRID = .TRUE.&#xA;LASPH = .TRUE.&#xA;NWRITE   = 3&#xA;LEPSILON = True&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The corresponding KPOINTS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Monkhorst-Pack&#xA;   7   4   2&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first observed frequency is positive (real):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;   normal_modes:&#xA;- band_indices: [ 1 ]&#xA;  frequency: 0.0009280870&#xA;  ir_label: B1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As I increase the number of KPOINTS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Monkhorst-Pack&#xA;   8  14   4&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;negative (imaginary) frequency will appear:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;normal_modes:&#xA;- band_indices: [ 1 ]&#xA;  frequency: -0.0009088724&#xA;  ir_label: A1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The corresponding POSCAR file for both cases:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        6.2820000648         0.0000000000         0.0000000000&#xA;        0.0000000000         3.4960000515         0.0000000000&#xA;        0.0000000000         0.0000000000        14.0699996948&#xA;    W   Te&#xA;    4    8&#xA;Selective dynamics&#xA;Direct&#xA;     0.541400000  0.000000000  0.985100000&#xA;     0.458600000  0.500000000  0.485100000&#xA;     0.900500000  0.500000000  0.000000000&#xA;     0.099500000  0.000000000  0.500000000&#xA;     0.294100000  0.500000000  0.096500000&#xA;     0.705900000  0.000000000  0.596500000&#xA;     0.355900000  0.000000000  0.344900000&#xA;     0.644100000  0.500000000  0.844900000&#xA;     0.851700000  0.500000000  0.389300000&#xA;     0.148300000  0.000000000  0.889300000&#xA;     0.800200000  0.000000000  0.140000000&#xA;     0.199800000  0.500000000  0.640000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So as you can see it happens only with the first band and despite that it is a small frequency, yet it is very strange to observe such thing.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-11-30T06:48:16.663" LastActivityDate="2023-12-06T00:38:16.710" Title="The Appearance of Imaginary Frequencies in Lattice Vibration Calculations with Increasing KPOINTS" Tags="|vasp|phonons|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="11992" PostTypeId="2" ParentId="11990" CreationDate="2023-11-30T07:25:25.443" Score="4" Body="&lt;p&gt;You shouldn't have a &lt;code&gt;*&lt;/code&gt; after the name of the coordinate file; the line should just be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* xyzfile -2 1 filename.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It also looks like your &lt;code&gt;moinp&lt;/code&gt; command might not be correct... According to the Orca manual (p.g. 781):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Alternatively NEB can be started on user prepared wavefunctions for each image.`&#xA;&#xA;# The names of of these wavefunction files should consist of a user-chosen basename&#xA;&#xA;# and the extension ’_imN.gbw’, where N is the image number.&#xA;&#xA;# The basename should be provided in the input, ORCA will add extension ’_imN.gbw’&#xA;&#xA;Restart_GBW_BaseName &amp;quot;NEB2&amp;quot; # use the wavefunctions from file NEB2_imN.gbw&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="7606" LastEditDate="2023-12-01T02:34:17.113" LastActivityDate="2023-12-01T02:34:17.113" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="11993" PostTypeId="1" CreationDate="2023-11-30T11:00:26.190" Score="2" ViewCount="45" Body="&lt;p&gt;I am trying to find symmetrically inequivalent T-atoms in a crystal structure (zeolite).&#xA;Does anyone happen to know any package that can help with that? I see that pymatgen does have options for symmetry analysis, but I will need some help to understand it.&#xA;Here is a snippet of the code that I tried on a .cif file, (anyone interested in checking on the cif file, &lt;em&gt;&lt;a href=&quot;https://europe.iza-structure.org/IZA-SC/mat_cif.php?ID=CHA_0&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://europe.iza-structure.org/IZA-SC/mat_cif.php?ID=CHA_0&lt;/a&gt;&lt;/em&gt; )&lt;/p&gt;&#xA;&lt;p&gt;The module from pymatgen,&#xA;&lt;strong&gt;&lt;a href=&quot;https://pymatgen.org/pymatgen.symmetry.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pymatgen.org/pymatgen.symmetry.html&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pymatgen.core as pmg&#xA;from pymatgen.symmetry.analyzer import cluster_sites&#xA;structure = pmg.Structure.from_str(open(&amp;quot;./CHA.cif&amp;quot;).read(), fmt=&amp;quot;cif&amp;quot;)&#xA;sites = cluster_sites(structure, tol=0.1)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The output is,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(None,&#xA; defaultdict(list,&#xA;             {(4.99070644043773,&#xA;               Comp: Si1): [PeriodicSite: Si (8.2387, 1.1508, 5.5161) [0.8954, 0.1241, 0.6673], PeriodicSite: Si (5.5368, 8.3047, 0.0694) [0.6673, 0.8954, 0.1241], PeriodicSite: Si (0.6537, 6.1886, 7.8040) [0.1241, 0.6673, 0.8954], PeriodicSite: Si (0.4825, 8.3047, 5.5161) [0.1241, 0.8954, 0.6673], PeriodicSite: Si (7.8310, 6.1886, 0.0694) [0.8954, 0.6673, 0.1241], PeriodicSite: Si (6.1157, 1.1508, 7.8040) [0.6673, 0.1241, 0.8954]],&#xA;              (4.255705851873808,&#xA;               Comp: Si1): [PeriodicSite: Si (8.0719, 0.9699, 2.4219) [0.8759, 0.1046, 0.3327], PeriodicSite: Si (0.7234, 3.0860, 7.8686) [0.1046, 0.3327, 0.8759], PeriodicSite: Si (2.4387, 8.1238, 0.1340) [0.3327, 0.8759, 0.1046], PeriodicSite: Si (0.3157, 8.1238, 2.4219) [0.1046, 0.8759, 0.3327], PeriodicSite: Si (3.0176, 0.9699, 7.8686) [0.3327, 0.1046, 0.8759], PeriodicSite: Si (7.9007, 3.0860, 0.1340) [0.8759, 0.3327, 0.1046]],&#xA;              (4.721664892674799,&#xA;               Comp: O1): [PeriodicSite: O (6.8820, 1.0159, 6.3861) [0.7484, 0.1095, 0.7484], PeriodicSite: O (6.4025, 6.9415, -0.0205) [0.7484, 0.7484, 0.1095], PeriodicSite: O (0.4574, 6.9415, 6.3861) [0.1095, 0.7484, 0.7484]],&#xA;              (4.255705851873808,&#xA;               Comp: O1): [PeriodicSite: O (8.0970, 2.3331, 1.5519) [0.8905, 0.2516, 0.2516], PeriodicSite: O (2.1519, 2.3331, 7.9586) [0.2516, 0.2516, 0.8905], PeriodicSite: O (1.6724, 8.2588, 1.5519) [0.2516, 0.8905, 0.2516]],&#xA;              (6.650526506176671,&#xA;               Comp: O1): [PeriodicSite: O (8.5779, 6.3230, 7.9598) [0.9768, 0.6818, 0.9768], PeriodicSite: O (8.3564, 9.0599, 5.0007) [0.9768, 0.9768, 0.6818], PeriodicSite: O (5.6105, 9.0599, 7.9598) [0.6818, 0.9768, 0.9768]],&#xA;              (1.4759151389461997,&#xA;               Comp: O1): [PeriodicSite: O (2.9439, 0.2147, -0.0218) [0.3182, 0.0232, 0.0232], PeriodicSite: O (0.1980, 0.2147, 2.9373) [0.0232, 0.0232, 0.3182], PeriodicSite: O (-0.0235, 2.9517, -0.0218) [0.0232, 0.3182, 0.0232]],&#xA;              (3.5640104664911534,&#xA;               Comp: O1): [PeriodicSite: O (6.8592, 0.0000, 1.9392) [0.7371, 0.0000, 0.2629], PeriodicSite: O (1.8925, 6.8368, -0.6965) [0.2629, 0.7371, 0.0000], PeriodicSite: O (-0.1973, 2.4378, 6.6953) [0.0000, 0.2629, 0.7371], PeriodicSite: O (2.4458, 0.0000, 6.6953) [0.2628, 0.0000, 0.7371], PeriodicSite: O (6.6619, 2.4378, -0.6965) [0.7371, 0.2628, 0.0000], PeriodicSite: O (-0.5533, 6.8368, 1.9392) [0.0000, 0.7371, 0.2628]],&#xA;              (4.438228227072944,&#xA;               Comp: O1): [PeriodicSite: O (7.5563, 4.6373, 0.4353) [0.8524, 0.5000, 0.1476], PeriodicSite: O (0.7336, 7.9057, 3.9690) [0.1476, 0.8524, 0.5000], PeriodicSite: O (4.5417, 1.3689, 7.5027) [0.5000, 0.1476, 0.8524], PeriodicSite: O (0.9981, 4.6373, 7.5027) [0.1476, 0.5000, 0.8524], PeriodicSite: O (7.8208, 1.3689, 3.9690) [0.8524, 0.1476, 0.5000], PeriodicSite: O (4.0127, 7.9057, 0.4353) [0.5000, 0.8524, 0.1476]]}))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I used on the zeolite structure called CHA for which there exists one type of T-atom (Si- atom), check below,&#xA;&lt;a href=&quot;https://i.stack.imgur.com/5ieYr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/5ieYr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4219" LastActivityDate="2024-01-01T10:01:10.173" Title="Non-Equivalent T-Sites from a cif file" Tags="|python|crystallography|symmetry|pymatgen|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11994" PostTypeId="1" CreationDate="2023-11-30T14:57:08.350" Score="1" ViewCount="36" Body="&lt;p&gt;I am doing energy minimization of a molecular system in TINKER. While doing so, I am getting the error in the title of this question. What might be my problem?&lt;/p&gt;&#xA;" OwnerUserId="8464" LastEditorUserId="5" LastEditDate="2023-11-30T15:38:12.643" LastActivityDate="2023-11-30T15:38:12.643" Title="LBFGS -- Incomplete Convergence due to BadIntpln" Tags="|molecular-dynamics|geometry-optimization|numerical-convergence|optimization|tinker|" AnswerCount="0" CommentCount="2" ClosedDate="2023-12-20T03:20:50.077" ContentLicense="CC BY-SA 4.0" />
  <row Id="11995" PostTypeId="2" ParentId="11941" CreationDate="2023-11-30T16:07:28.017" Score="5" Body="&lt;p&gt;While I don't have such a script on-hand, it's really easy to write one using &lt;a href=&quot;https://cclib.github.io/&quot; rel=&quot;noreferrer&quot;&gt;cclib&lt;/a&gt; which helpfully provides &lt;a href=&quot;https://cclib.github.io/data_notes.html#vibdisps&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;vibdisps&lt;/code&gt;&lt;/a&gt; for vibrational files.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The attribute vibdisps stores the Cartesian displacement vectors from the output of a vibrational frequency calculation. .. &lt;code&gt;M x N x 3&lt;/code&gt;, where &lt;code&gt;M&lt;/code&gt; is the number of normal modes and &lt;code&gt;N&lt;/code&gt; is the number of atoms. &lt;code&gt;M&lt;/code&gt; is typically 3N-6 (3N-5 for linear molecules).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;You want something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;import cclib&#xA;from cclib.parser import ccopen&#xA;&#xA;# which mode do you want to displace&#xA;mode_number = 1&#xA;file = ccopen(filename)&#xA;molecule = file.parse()&#xA;&#xA;# the atom labels (here as atomic numbers)&#xA;labels = molecule.atomnos&#xA;&#xA;coords = np.asarray(molecule.atomcoords[-1]).reshape(-1,3)&#xA;mode = modes[mode_number]&#xA;displaced = coords + 2.0*(mode / np.linalg.norm(mode))&#xA;# output as XYZ or whatever&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-11-30T16:07:28.017" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11996" PostTypeId="1" CreationDate="2023-11-30T18:46:39.387" Score="4" ViewCount="39" Body="&lt;p&gt;Where can I read about &lt;a href=&quot;https://en.wikipedia.org/wiki/Valleytronics&quot; rel=&quot;nofollow noreferrer&quot;&gt;Valleytronics&lt;/a&gt;? Are there any good books or review papers or influential papers on this topic?&lt;/p&gt;&#xA;&lt;p&gt;The question was also posted at the &lt;a href=&quot;https://physics.stackexchange.com/q/790684/49107&quot;&gt;Physics&lt;/a&gt; site.&lt;/p&gt;&#xA;" OwnerUserId="8465" LastEditorUserId="671" LastEditDate="2023-12-01T03:24:07.767" LastActivityDate="2023-12-01T03:24:07.767" Title="Where can I read about Valleytronics?" Tags="|band-structure|condensed-matter|spin-orbit-coupling|graphene|valleytronics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="11997" PostTypeId="1" AcceptedAnswerId="11998" CreationDate="2023-12-01T09:45:36.933" Score="4" ViewCount="205" Body="&lt;p&gt;How to generate random velocities in the geometry coordinates of a surface (POSCAR file) using the Boltzmann distribution law with Atomic Simulation Environment (ASE) or other codes for Molecular Dynamics (MD) calculations?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="3770" LastEditDate="2023-12-01T13:22:01.527" LastActivityDate="2023-12-01T13:22:01.527" Title="Random velocity generation" Tags="|vasp|molecular-dynamics|python|atomic-simulation-environment|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="11998" PostTypeId="2" ParentId="11997" CreationDate="2023-12-01T10:05:24.267" Score="5" Body="&lt;p&gt;You can use ASE to generate the required random velocities, you may refer to this sample code to achieve this taks:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase.io import read, write&#xA;from ase import units&#xA;from ase.md.velocitydistribution import MaxwellBoltzmannDistribution&#xA;surface = read('POSCAR', format='vasp')&#xA;temperature = 300.0&#xA;np.random.seed(123)&#xA;&#xA;MaxwellBoltzmannDistribution(surface, temperature_K=temperature*units.kB)&#xA;print(surface.get_velocities()[:5])&#xA;write('modified_POSCAR', surface, format='vasp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here, I explicitly specify the temperature in Kelvin.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-01T10:05:24.267" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="11999" PostTypeId="2" ParentId="11988" CreationDate="2023-12-01T10:47:02.363" Score="2" Body="&lt;p&gt;Solvation in gromacs is not limited to only with gmx solvate. As I discussed with you in the comments section, we can have an estimate on the number of water molecules you need to add to get the right density you want, and then use gmx insert-molecules to add the right number of water molecules.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2023-12-01T10:47:02.363" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12000" PostTypeId="2" ParentId="10997" CreationDate="2023-12-01T18:07:03.327" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I still didn't see an output from my calculations from the HPC.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is because your jobs had not yet started. I can see this based on the &lt;code&gt;squeue&lt;/code&gt; output that you provided:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;JOBID  PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON) &#xA;192137    shortq      one  username PD       0:00      2 (Nodes required for job are DOWN, DRAINED or reserved for jobs in higher priority partitions)        &#xA;192138    shortq      one  username PD       0:00      2 (Priority) &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As mentioned in the &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10997/i-didnt-find-the-results-of-my-calculations-using-an-hpc-for-quantum-espresso#comment23552_10997&quot;&gt;comment by Tyberius&lt;/a&gt;, job &lt;code&gt;192137&lt;/code&gt; did not start because the nodes (computers) required to run the calculation are either &amp;quot;down, drained or reserved for jobs in higher priority partitions&amp;quot;, and job &lt;code&gt;192138&lt;/code&gt; did not start yet because other jobs (maybe even your own job &lt;code&gt;192137&lt;/code&gt;, but I did later notice that job &lt;code&gt;192138&lt;/code&gt; had &lt;code&gt;#SBATCH --time=00:10:00&lt;/code&gt; which job 192137 did not have, and 10-minute jobs would have a lower priority than longer jobs on some systems, because HPC clusters are not meant for such short calculations) have a priority over this one.&lt;/p&gt;&#xA;&lt;p&gt;When you ran &lt;code&gt;sacct -j 192138 -o start,end&lt;/code&gt; and it gave you &lt;code&gt;unknown&lt;/code&gt; for the &lt;code&gt;start&lt;/code&gt; and &lt;code&gt;end&lt;/code&gt; times, it would have been more informative if they instead told you that the job has not started yet, but the point is that the job had not yet started running, so there was no &amp;quot;start time&amp;quot; or &amp;quot;end time&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-01T18:12:30.537" LastActivityDate="2023-12-01T18:12:30.537" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12001" PostTypeId="2" ParentId="10994" CreationDate="2023-12-01T18:22:13.403" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;But there is no explanation regarding the details of each parameter, for example, the origin of the spanning vector... &amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Nick Papior's &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10994/gate-potential-wiith-siesta-transiesta#comment23566_10994&quot;&gt;comment&lt;/a&gt; implied that enough information was provided in the comments in the lines below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;square 1. eV    # The lifting potential on the geometry&#xA;delta&#xA;1.0 1.0 1.0 Ang # The starting point of the square&#xA;2.0 0.5 0.2 Ang # The first spanning vector&#xA;0.0 2.5 0.2 Ang # The second spanning vector&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Although the &amp;quot;origin&amp;quot; of the first and second spanning vectors is not something that is explained explicitly in the comments, it seems that the OP was satisfied with this answer, as seen the first part of &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10994/gate-potential-wiith-siesta-transiesta#comment23588_10994&quot;&gt;this comment&lt;/a&gt; which was a response from the OP to Nick's first comment:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;thank you for your response i fixed the problem&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;All other questions that the OP asked in the comment section after the above part of the first comment by the OP, would have been more appropriately asked in separate posts on the site. &lt;strong&gt;I apologize that I nor anyone else was able to catch this earlier, before all those questions got asked and in some cases answered in the comments section.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-01T18:22:13.403" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12002" PostTypeId="2" ParentId="10993" CreationDate="2023-12-01T19:06:37.703" Score="2" Body="&lt;p&gt;The comment by Pie86:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Try adding the option -ndiag 1 when running pw.x. It disables parallel diagonalization that raised similar problems in versions &amp;lt;= 7.1 (see gitlab.com/QEF/q-e/-/blob/develop/Doc/release-notes#L30)&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;OP:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;@Pie86 Your suggestion worked perfectly. Thankyou, it is much appreciated. However, I could not exactly understand the reasoning behind it. If you want to post your comment as an answer, I will be happy to accept it.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'll be happy to delete this Community Wiki if Pie86 or someone else comments saying that they would be willing to write a full answer, but until then I'm removing this from the queue of unanswered questions.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-01T19:06:37.703" CommentCount="0" CommunityOwnedDate="2023-12-01T19:06:37.703" ContentLicense="CC BY-SA 4.0" />
  <row Id="12003" PostTypeId="2" ParentId="11993" CreationDate="2023-12-02T09:40:47.403" Score="0" Body="&lt;p&gt;I guess that T refers to 'tetrahedral'; this site is occupied by Si and Al. In the cif file these atoms have exactly the same coordinates because Al substitutes Si. So you have one single T site randomly occupied by both Si and Al.&lt;/p&gt;&#xA;&lt;p&gt;The Wyckoff notation for this site is 36i, where 36 indicates the number of this site in the unit-cell. It is the site with the highest multiplicity in the space group R-3m; this means that the only symmetry operation to be considered is the identity.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, I checked the original paper; it seems to me that these data (Table 3) are not properly reported. There's no correspondence between the names of Wyckoff sites (it is written 12i instead of 36i, for example), and the relationships among coordinates do not comply with those reported in the International Table of Crystallography vol A. I would use other data.&lt;/p&gt;&#xA;" OwnerUserId="1807" LastActivityDate="2023-12-02T09:40:47.403" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12004" PostTypeId="1" AcceptedAnswerId="12005" CreationDate="2023-12-02T15:59:39.767" Score="5" ViewCount="233" Body="&lt;p&gt;For teaching porpouses, I would like to make a relaxed scan for an A-BC system (for example, the isomerization of of H-NC to H-CN or CH3-NC to CH3-CN) with Gaussian 16 using generalized internal coordinates. In particular, the coordinates to be scanned would be the distance of atom A to the center of mass of the BC, &lt;strong&gt;R&lt;/strong&gt;, and θ, the angle between &lt;strong&gt;R&lt;/strong&gt; and the direction of the BC bond (&lt;strong&gt;rAB&lt;/strong&gt;) as illustrated in the figure below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/FNXMM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FNXMM.png&quot; alt=&quot;Jacobi coordinates&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Could anybody give me an example of how to define these particular coordinates?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Partial answer and further questions.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Following the suggestions of @S.R.Maiti I have prepared an input for H-NC to scan the &lt;strong&gt;R&lt;/strong&gt; coordinate at a fixed θ angle, and scanning the θ angle or both coordinates. The results demonstrate a mixed successes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Sample code for the can of the R coordinate&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;This kind of scan completes withour error.&lt;/p&gt;&#xA;&lt;pre&gt;   &#xA;#N b3lyp/cc-pvdz opt=readallgic  nosymm&#xA;&#xA;Test GIC HCN&#xA;&#xA;0 1&#xA;C -0.6174 0.0000 0.0000&#xA;N  0.5290 0.0000 0.0000&#xA;H  1.1954 0.1046 0.0000&#xA;&#xA;comX = (X(1)*12.0 + X(2)*14.0)/(12.0+14.0)&#xA;comY = (Y(1)*12.0 + Y(2)*14.0)/(12.0+14.0)&#xA;comZ = (Z(1)*12.0 + Z(2)*14.0)/(12.0+14.0)&#xA;comToBX = X(2) - comX&#xA;comToBY = Y(2) - comY&#xA;comToBZ = Z(2) - comZ&#xA;ComToBdist = SQRT(comToBX**2 + comToBY**2 + comToBZ**2)&#xA;comToCX = X(3) - comX&#xA;comToCY = Y(3) - comY&#xA;comToCZ = Z(3) - comZ&#xA;ComToCdist = SQRT(comToCX**2 + comToCY**2 + comToCZ**2)&#xA;dot = comToBX*comToCX + comToBY*comToCY + comToBZ*comToCZ&#xA;BcomC(Freeze) = ARCCOS(dot / (ComToBdist * ComToCdist))&#xA;ComToCdist(NSteps=13,StepSize=0.092)&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;Sample code for the scan of the R and θ coordinates&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;When I tried to scan the θ coordinate (on its own or in a double scan), I got an error message, I guees, related to the definition of the angle (see below).&lt;/p&gt;&#xA;&lt;pre&gt;   &#xA;#N b3lyp/cc-pvdz opt=readallgic  nosymm&#xA;&#xA;Test GIC HCN&#xA;&#xA;0 1&#xA;C -0.6174 0.0000 0.0000&#xA;N  0.5290 0.0000 0.0000&#xA;H  1.1954 0.1046 0.0000&#xA;&#xA;comX = (X(1)*12.0 + X(2)*14.0)/(12.0+14.0)&#xA;comY = (Y(1)*12.0 + Y(2)*14.0)/(12.0+14.0)&#xA;comZ = (Z(1)*12.0 + Z(2)*14.0)/(12.0+14.0)&#xA;comToBX = X(2) - comX&#xA;comToBY = Y(2) - comY&#xA;comToBZ = Z(2) - comZ&#xA;ComToBdist = SQRT(comToBX**2 + comToBY**2 + comToBZ**2)&#xA;comToCX = X(3) - comX&#xA;comToCY = Y(3) - comY&#xA;comToCZ = Z(3) - comZ&#xA;ComToCdist = SQRT(comToCX**2 + comToCY**2 + comToCZ**2)&#xA;dot = comToBX*comToCX + comToBY*comToCY + comToBZ*comToCZ&#xA;BcomC = ARCCOS(dot / (ComToBdist * ComToCdist))&#xA;ComToCdist(NSteps=13,StepSize=0.092)&#xA;BcomC(NSteps=13,StepSize=5.0)&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;Once Gaussian has completed the scan for the first value of θ, it produces the following error message:&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;                          !   Optimized Parameters   !&#xA;                           ! (Angstroms and Degrees)  !&#xA; --------------------------                            --------------------------&#xA; ! Name       Definition         Value          Derivative Info.                !&#xA; --------------------------------------------------------------------------------&#xA; ! comX       GIC-1             -0.3944         -DE/DX =    0.019               !&#xA; ! comY       GIC-2             -0.0342         -DE/DX =    0.0038              !&#xA; ! comZ       GIC-3              0.0            -DE/DX =    0.0                 !&#xA; ! comToBX    GIC-4              1.0547         -DE/DX =    0.0124              !&#xA; ! comToBY    GIC-5             -0.0005         -DE/DX =    0.0017              !&#xA; ! comToBZ    GIC-6              0.0            -DE/DX =    0.0                 !&#xA; ! ComToBdist GIC-7              1.0547         -DE/DX =    0.0124              !&#xA; ! comToCX    GIC-8              3.4508         -DE/DX =   -0.0482              !&#xA; ! comToCY    GIC-9              0.3002         -DE/DX =   -0.0096              !&#xA; ! comToCZ    GIC-10             0.0            -DE/DX =    0.0                 !&#xA; ! ComToCdist GIC-11             3.4638         -DE/DX =   -0.0488              !&#xA; ! dot        GIC-12             3.6392         -DE/DX =   -0.0074              !&#xA; ! BcomC      GIC-13             0.0873         -DE/DX =   -0.0032              !&#xA; --------------------------------------------------------------------------------&#xA; NOTE: GIC-type coordinates are in arbitrary units.&#xA; Iteration  1 RMS(Cart)=  0.03691776 RMS(Int)=  1.36059875...&#xA; Iteration100 RMS(Cart)=  0.00247220 RMS(Int)=  1.49252761&#xA; New curvilinear step not converged.&#xA; Error imposing constraints&#xA; Error termination via Lnk1e in C:\G16W\l103.exe at Sat Dec 09 22:17:54 2023.&#xA; Job cpu time:       0 days  0 hours  4 minutes 39.0 seconds.&#xA; Elapsed time:       0 days  0 hours  2 minutes 34.5 seconds.&#xA; File lengths (MBytes):  RWF=     11 Int=      0 D2E=      0 Chk=      6 Scr=    1   &#xA;&lt;/pre&gt;  &#xA;&lt;p&gt;I guess the problem is related to the definition of the angle. Is there a way to avoid it?&lt;/p&gt;&#xA;" OwnerUserId="2048" LastEditorUserId="2048" LastEditDate="2023-12-23T22:58:08.707" LastActivityDate="2023-12-23T22:58:08.707" Title="Gaussian 16: Relaxed scan using Jacobi coordinates expressed using generalized internal coordinates" Tags="|gaussian|geometry|potential-energy-surface|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12005" PostTypeId="2" ParentId="12004" CreationDate="2023-12-02T18:08:03.197" Score="5" Body="&lt;p&gt;Based on the GIC page in Gaussian &lt;a href=&quot;https://gaussian.com/gic/&quot; rel=&quot;noreferrer&quot;&gt;website&lt;/a&gt; and your picture, the definition of the coordinates would be:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;comX = (X(A)*mA + X(B)*mB)/(mA+mB)  # these are the cartesian components&#xA;comY = (Y(A)*mA + Y(B)*mB)/(mA+mB)  # of the centre of mass of A-B system&#xA;comZ = (Z(A)*mA + Z(B)*mB)/(mA+mB)&#xA;  &#xA;# for the angle&#xA;comToBX = X(B) - comX&#xA;comToBY = Y(B) - comY&#xA;comToBZ = Z(B) - comZ&#xA;ComToBdist = SQRT(comToBX**2 + comToBY**2 + comToBZ**2)&#xA;comToCX = X(C) - comX&#xA;comToCY = Y(C) - comY&#xA;comToCZ = Z(C) - comZ&#xA;# below is the COM --  C distance coordinate as defined in the picture&#xA;ComToCdist = SQRT(comToCX**2 + comToCY**2 + comToCZ**2)&#xA;&#xA;dot = comToBX*comToCX + comToBY*comToCY + comToBZ*comToCZ&#xA;# below is the B - COM - C angle defined in your picture&#xA;BcomC = ARCCOS(dot / (ComToBdist * ComToCdist))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You have to replace the following variables in the above expressions with numbers (constants): &lt;code&gt;mA = mass of atom A&lt;/code&gt;, &lt;code&gt;mB = mass of atom B&lt;/code&gt;, &lt;code&gt;A = index of atom A&lt;/code&gt;, &lt;code&gt;B = index of atom B&lt;/code&gt;, &lt;code&gt;C = index of atom C&lt;/code&gt;. (also remove the comments)&lt;/p&gt;&#xA;&lt;p&gt;Note that the scanning using these coordinates will fail when the angle &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; (B-COM-C) is close to 0 or 180 degrees. This is due to the B matrix elements of the corresponding angle going to infinity as the angle approaches linear or zero angle. This is a well-known problem with the angles defined with arccosine of the normalised dot product (which is the way I have written it here). It's quite difficult to solve this frankly... most softwares replace the angle coordinate with a linear bend coordinate (that requires a dummy atom or a dummy axis) when the angle is close to linear, but that would be counterproductive here since you want to scan the whole range of angle.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2023-12-02T18:08:03.197" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12006" PostTypeId="1" CreationDate="2023-12-02T19:18:15.820" Score="2" ViewCount="28" Body="&lt;p&gt;I need to create ZnO/ graphene sheet nanocomposite with material studio and i dont know how. Please, help me or guide me to some one who can help me. I'm blocked.&lt;/p&gt;&#xA;" OwnerUserId="8472" LastEditorUserId="1554" LastEditDate="2023-12-03T21:48:14.980" LastActivityDate="2023-12-03T21:48:14.980" Title="Creating nanocomposite with material studio" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12007" PostTypeId="2" ParentId="10841" CreationDate="2023-12-03T04:59:04.430" Score="3" Body="&lt;p&gt;First we can start by converting the struture generated with LAMMPS into POSCAR file format&lt;/p&gt;&#xA;&lt;p&gt;In this case, you can use &lt;strong&gt;cfg&lt;/strong&gt; file format to dump the frames from LAMMPS, which will write the atom types, then you can read this file with OVITO, using the scirpting interface of OVITO &lt;a href=&quot;https://www.ovito.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ovito.org&lt;/a&gt;, you can convert this file into POSCAR format.&lt;/p&gt;&#xA;&lt;p&gt;Now suppose that you have successfully produced the reqiured POSCAR format, adding vacuum or manipulating the position of the atmos(layers) is straightforwad. To do that you can use vapskit &lt;a href=&quot;https://vaspkit.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://vaspkit.com&lt;/a&gt; (a tool for pre and post processing VASP input and output files). from vaspkit interface, head to ( Advanced Structure Models (option: 08)), then choose (801 for Build Vacuum Slab in Specified Direction). Make sure your POSCAR file in the same directory where you are running vaspkit. Afterwards choose the direction in which you want to add the vacuum level and the amount in Angstrom.&lt;/p&gt;&#xA;&lt;p&gt;If you would like to further move the layers along certain direction, there is another option in vaspkit specifically for 2D systems which is accessible via option (92 2D-Material kit).&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-03T04:59:04.430" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12008" PostTypeId="1" CreationDate="2023-12-03T05:17:14.227" Score="5" ViewCount="37" Body="&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Using Quantum Espresso examining a porous material, that has a ligand with an aromatic group. The aim is to rotate the aromatic group and determine an energy profile for the rotation. The initial (un-rotated) structure was optimized with 'vc-relax' and a subsequent SCF converges well. The aromatic group of the ligand is then rotated 90 degrees.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Problem&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;When trying to perform an SCF on the structure with a rotated aromatic core (ie. 90 degrees), the SCF does not converge and instead oscillates. I have played with a number of settings (ie. k-points, Ecut, mixing, smearing, etc), but with no-luck. The rotated input looks chemically sensible. However, it does occur to me, that the structure is not the lowest energy state, so essentially to perform an SCF on a transition state - which is likely to be unstable. Is this do-able and if so what is the best way to tackle the problem given the SCF is not converging?&lt;/p&gt;&#xA;" OwnerUserId="6958" LastActivityDate="2023-12-03T05:17:14.227" Title="QE - transition state SCF not converging" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12009" PostTypeId="1" CreationDate="2023-12-03T21:01:16.623" Score="4" ViewCount="69" Body="&lt;p&gt;I am calculating the dielectric (Epsilon) for ZnO by quantum espresso, when I run the eps.in file, I always get this error. &lt;code&gt;Reading namelist energy_grid'&lt;/code&gt;&#xA;How do I solve this problem?&lt;/p&gt;&#xA;&lt;p&gt;My eps.in:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA;calculation = 'eps',&#xA;outdir = './' /&#xA;&amp;amp;ENERGY_GRID &#xA;smeartype = 'gauss',&#xA;intersmear = 0.1500,&#xA;intrasmear = 0.000,&#xA;wmax = 10.000,&#xA;wmin = 0.000,&#xA;nw = 600,&#xA;shift = 0.010, &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7915" LastEditorUserId="6055" LastEditDate="2023-12-08T08:31:13.983" LastActivityDate="2023-12-08T08:31:13.983" Title="Finding optical properties (epsilon) by Quantum ESPRESSO" Tags="|density-functional-theory|quantum-espresso|ab-initio-calculations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12011" PostTypeId="1" CreationDate="2023-12-04T04:43:17.563" Score="2" ViewCount="26" Body="&lt;p&gt;These days, I'm having a trouble in atomic relaxing of &amp;quot;EuTiO3&amp;quot; with tetragonal symmetry using Quantum espresso 7.1 for a period of more that a week. This material have a transverse optical mode to z-axis(&amp;quot;001&amp;quot; direction). So, I try to relax this material along the z-axis. My order of relaxing the EuTiO3 is as follows:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;I download &amp;quot;cif.file&amp;quot; including the atomic position &amp;amp; lattice from &amp;quot;Materials Explorer( &lt;a href=&quot;https://next-gen.materialsproject.org/materials&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://next-gen.materialsproject.org/materials&lt;/a&gt; ) &amp;quot;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;At Quantum espresso, &amp;quot;vc-relax(lattice realxation)&amp;quot; this material.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&amp;quot;Relax&amp;quot; this material along the z-axis(= the direction of transverse optical mode,001).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;At &amp;quot;2&amp;quot; process, total energy is decreased. &lt;em&gt;&lt;strong&gt;But at &amp;quot;3&amp;quot; process, total energy is oddly increased!!&lt;/strong&gt;&lt;/em&gt;. By other paper related EuTiO3, because this material is unstable to the direction of &amp;quot;z-axis&amp;quot;, total energy should be also decreased at &amp;quot;3&amp;quot; process.  I don't know what the reason is.&lt;/p&gt;&#xA;&lt;p&gt;At similar structure &amp;quot;SrTiO3&amp;quot; with tetragonal symmetry , this problem didn't occur. At &amp;quot;SrTiO3&amp;quot;,  the same procedure as above was performed, but total energy was decreased at both &amp;quot;2&amp;quot; &amp;amp; &amp;quot;3&amp;quot; process.&lt;/p&gt;&#xA;&lt;p&gt;Both &amp;quot;EuTiO3&amp;quot; &amp;amp; &amp;quot;SrTiO3&amp;quot; are perovskite material. One difference is that &amp;quot;EuTiO3&amp;quot; have antiferromagnetic property(=spin polarization) unlike &amp;quot;SrTiO3&amp;quot;. Hence, I specified the &amp;quot;magnetization&amp;quot; and &amp;quot;Hubbard potential&amp;quot; to the input data of &amp;quot;EuTiO3&amp;quot;( In another paper, I know that magnetization and Hubbard potential are specified when relaxing EuTiO3 material.)&#xA;&lt;em&gt;&lt;strong&gt;Did I typed the &amp;quot;magnetization&amp;quot; &amp;amp; &amp;quot;Hubbard potential&amp;quot; data wrong?&lt;/strong&gt;&lt;/em&gt; Please help me. I need sincere help from experts.&lt;/p&gt;&#xA;&lt;p&gt;P.S  I add my input data of &amp;quot;EuTiO3&amp;quot; entered into Quatum Espresso.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;process : &amp;quot;vc-relax&amp;quot;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&amp;amp;control&#xA;calculation = 'vc-relax'&#xA;restart_mode='from_scratch',&#xA;prefix='ETO',&#xA;pseudo_dir ='/home/dydtlr5506/pseudo',&#xA;outdir='./wavefunc'&#xA;tstress = .true.&#xA;forc_conv_thr = 1.0d-7&#xA;dt = 20&#xA;disk_io = 'none'&#xA;nstep =9910&#xA;/&#xA;&amp;amp;system&#xA;ibrav=  0,&#xA;nat=20, ntyp= 4,&#xA;ecutwfc = 80.0, ecutrho = 640.0,&#xA;occupations = 'smearing',&#xA;smearing = 'gaussian'&#xA;degauss = 0.0010&#xA;nspin = 2&#xA;starting_magnetization(1)=7.0&#xA;starting_magnetization(2)=-7.0&lt;/p&gt;&#xA;&lt;p&gt;/ &amp;amp;electrons&#xA;mixing_mode = 'plain'&#xA;electron_maxstep = 100&#xA;conv_thr = 1.0d-13&lt;br /&gt;&#xA;/&#xA;&amp;amp;ions&#xA;ion_dynamics = 'bfgs'&#xA;/  &amp;amp;cell&#xA;cell_dofree='xyz'&#xA;cell_dynamics = 'bfgs'&#xA;/&#xA;ATOMIC_SPECIES&#xA;Eu1  151.964 Eu.pbe-spdfn-kjpaw_psl.1.0.0.UPF&#xA;Eu2  151.964 Eu.pbe-spdfn-kjpaw_psl.1.0.0.UPF&#xA;Ti  47.86  Ti.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;O   15.999 O.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;K_POINTS {automatic}&#xA;6 6 4 0 0 0&#xA;CELL_PARAMETERS (angstrom)&#xA;5.510044859   0.000000000   0.000000000&#xA;0.000000000   5.510044859   0.000000000&#xA;0.000000000   0.000000000   7.871680636&#xA;ATOMIC_POSITIONS (crystal)&#xA;Eu1           0.0000000000        0.5000000000        0.2500000000    1   1   0&#xA;Eu2           0.5000000000        0.0000000000        0.2500000000    1   1   0&#xA;Eu1           0.5000000000        0.0000000000        0.7500000000    1   1   0&#xA;Eu2           0.0000000000        0.5000000000        0.7500000000    1   1   0&#xA;Ti            0.5000000000        0.5000000000        0.5000000000    1   1   0&#xA;Ti            0.0000000000        0.0000000000        0.5000000000    1   1   0&#xA;Ti            0.0000000000        0.0000000000        0.0000000000    1   1   0&#xA;Ti            0.5000000000        0.5000000000        0.0000000000    1   1   0&#xA;O             0.5000000000        0.5000000000        0.2500000000    1   1   0&#xA;O             0.0000000000        0.0000000000        0.2500000000    1   1   0&#xA;O             0.7183286073        0.2183286073        0.0000000000    1   1   0&#xA;O             0.7816713921        0.2816713922        0.5000000000    1   1   0&#xA;O             0.2816713922        0.2183286079        0.5000000000    1   1   0&#xA;O             0.2183286073        0.2816713927        0.0000000000    1   1   0&#xA;O             0.0000000000        0.0000000000        0.7500000000    1   1   0&#xA;O             0.5000000000        0.5000000000        0.7500000000    1   1   0&#xA;O             0.2183286079        0.7183286078        0.5000000000    1   1   0&#xA;O             0.2816713927        0.7816713927        0.0000000000    1   1   0&#xA;O             0.7816713927        0.7183286073        0.0000000000    1   1   0&#xA;O             0.7183286078        0.7816713921        0.5000000000    1   1   0&#xA;HUBBARD (ortho-atomic)&#xA;U Eu1-4f 5.9&#xA;U Eu2-4f 5.9&#xA;&lt;a href=&quot;https://i.stack.imgur.com/a2QBe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a2QBe.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;2. process: output total energy =   -5712.21091180 Ry&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;process : &amp;quot;relax&amp;quot;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&amp;amp;control&#xA;calculation = 'relax'&#xA;restart_mode='from_scratch',&#xA;prefix='ETO',&#xA;pseudo_dir ='/home/dydtlr5506/pseudo',&#xA;outdir='./wavefunc'&#xA;tstress = .true.&#xA;forc_conv_thr = 1.0d-7&#xA;dt = 20&#xA;disk_io = 'none'&#xA;nstep =9910&#xA;/&#xA;&amp;amp;system&#xA;ibrav=  0,&#xA;nat=20, ntyp= 4,&#xA;ecutwfc = 80.0, ecutrho = 640.0,&#xA;!   nbnd =200&#xA;!   occupations = 'fixed',&#xA;occupations = 'smearing',&#xA;smearing = 'gaussian'&#xA;degauss = 0.0010&#xA;nspin = 2&#xA;starting_magnetization(1)=0.5&#xA;starting_magnetization(2)=-0.5&lt;/p&gt;&#xA;&lt;p&gt;!   nosym = .true.&#xA;!   nbnd = 120&#xA;!   nosym_evc = .true.&#xA;!   noinv = .true.&#xA;!   no_t_rev = .true.&#xA;/&#xA;&amp;amp;electrons&#xA;mixing_mode = 'plain'&#xA;electron_maxstep = 100&#xA;conv_thr = 1.0d-9&lt;br /&gt;&#xA;/&#xA;&amp;amp;ions&#xA;ion_dynamics = 'bfgs'&#xA;/&#xA;&amp;amp;cell&#xA;cell_dofree='xyz'&#xA;cell_dynamics = 'bfgs'&lt;/p&gt;&#xA;&lt;p&gt;/&#xA;ATOMIC_SPECIES&#xA;Eu1  151.964 Eu.pbe-spdfn-kjpaw_psl.1.0.0.UPF&#xA;Eu2  151.964 Eu.pbe-spdfn-kjpaw_psl.1.0.0.UPF&#xA;Ti  47.86  Ti.pbe-spn-kjpaw_psl.1.0.0.UPF&#xA;O   15.999 O.pbe-n-kjpaw_psl.1.0.0.UPF&lt;/p&gt;&#xA;&lt;p&gt;K_POINTS {automatic}&#xA;6 6 4 0 0 0&lt;/p&gt;&#xA;&lt;p&gt;CELL_PARAMETERS (angstrom)&#xA;5.505334716  -0.000000000   0.000000000&#xA;0.000000000   5.505334716   0.000000000&#xA;-0.000000000  -0.000000000   7.873593914&lt;/p&gt;&#xA;&lt;p&gt;ATOMIC_POSITIONS (crystal)&#xA;Eu1           0.0000000000        0.5000000000        0.2520000000    0   0   1&#xA;Eu2           0.5000000000        0.0000000000        0.2520000000    0   0   1&#xA;Eu1           0.5000000000       -0.0000000000        0.7520000000    0   0   1&#xA;Eu2          -0.0000000000        0.5000000000        0.7520000000    0   0   1&#xA;Ti            0.0000000000        0.0000000000        0.0040000000    0   0   1&#xA;Ti            0.5000000000        0.5000000000        0.0040000000    0   0   1&#xA;Ti            0.0000000000        0.0000000000        0.5040000000    0   0   1&#xA;Ti            0.5000000000        0.5000000000        0.5040000000    0   0   1&#xA;O             0.0000000000        0.0000000000        0.2470000000    0   0   1&#xA;O             0.5000000000        0.5000000000        0.2470000000    0   0   1&#xA;O            -0.0000000000        0.0000000000        0.7470000000    0   0   1&#xA;O             0.5000000000        0.5000000000        0.7470000000    0   0   1&#xA;O             0.2179836940        0.2820163063       -0.0020000000    0   0   1&#xA;O             0.2820163063        0.7820163060       -0.0020000000    0   0   1&#xA;O             0.7179836937        0.2179836940       -0.0020000000    0   0   1&#xA;O             0.7820163060        0.7179836937       -0.0020000000    0   0   1&#xA;O             0.2179836608        0.7179836609        0.4970000000    0   0   1&#xA;O             0.2820163391        0.2179836608        0.4970000000    0   0   1&#xA;O             0.7179836609        0.7820163392        0.4970000000    0   0   1&#xA;O             0.7820163392        0.2820163391        0.4970000000    0   0   1&lt;/p&gt;&#xA;&lt;p&gt;HUBBARD (ortho-atomic)&#xA;U Eu1-4f 5.9&#xA;U Eu2-4f 5.9&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/YzuC5.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/YzuC5.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;ol start=&quot;3&quot;&gt;&#xA;&lt;li&gt;process: output total energy =   -5711.56708785 Ry&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="8396" LastEditorUserId="8396" LastEditDate="2023-12-04T04:53:22.320" LastActivityDate="2023-12-04T04:53:22.320" Title="Strange change in total energy when lattice relaxing of EuTiO3 material and then atomic relaxing in a specific direction using Quantum Espresso" Tags="|density-functional-theory|quantum-espresso|cell-optimization|spin-polarization|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12012" PostTypeId="1" CreationDate="2023-12-04T15:04:13.370" Score="2" ViewCount="71" Body="&lt;p&gt;I am calculating the lattice parameter of CeO2 with VASP, but the optimized lattice parameter is wrong according to many references (&lt;a href=&quot;https://doi.org/10.1103/PhysRevB.75.035109&quot; rel=&quot;nofollow noreferrer&quot;&gt;Physical Review B &lt;strong&gt;75&lt;/strong&gt;, 035109 (2007)&lt;/a&gt;; &lt;a href=&quot;https://doi.org/10.1063/1.3678309&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Journal of Chemical Physics &lt;strong&gt;136&lt;/strong&gt;, 041101 (2012)&lt;/a&gt;). In these references the optimized lattice parameter a = 5.4~5.5, while the optimized lattice parameter of my calculation is 5.7~5.8. I did some trials (I list them below), but the results did not improve. I wonder if somebody could give me some help.&lt;/p&gt;&#xA;&lt;p&gt;My INCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SYSTEM  = CeO2    &#xA;NPAR   = 4    &#xA;PREC   = Accurate    &#xA;ISTART = 0    &#xA;ICHARG = 2    &#xA;LWAVE  = .False.    &#xA;LCHARG = .False.    &#xA;LORBIT = 11&#xA;&#xA;ENCUT  = 650    &#xA;NELM   = 60    &#xA;EDIFF  = 1E-6    &#xA;LREAL  = .FALSE.    &#xA;IBRION = 2&#xA;&#xA;ISIF   = 3    &#xA;NSW    = 100    &#xA;EDIFFG = -0.01&#xA;&#xA;ISMEAR = -5     &#xA;LDAU = .TRUE.     &#xA;LDAUTYPE = 2&#xA;LDAUL = 3 -1    &#xA;LDAUU = 5.5 0&#xA;LDAUJ = 0.5 0&#xA;LMAXMIX = 6 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POSCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Ce4 O8&#xA;1.0    &#xA;5.467450 0.000000 0.000000    &#xA;0.000000 5.467450 0.000000    &#xA;0.000000 0.000000 5.467450    &#xA;Ce O    &#xA;4 8    &#xA;direct    &#xA;0.000000 0.000000 0.000000 Ce    &#xA;0.000000 0.500000 0.500000 Ce    &#xA;0.500000 0.000000 0.500000 Ce    &#xA;0.500000 0.500000 0.000000 Ce    &#xA;0.250000 0.250000 0.750000 O    &#xA;0.250000 0.750000 0.750000 O    &#xA;0.250000 0.750000 0.250000 O    &#xA;0.250000 0.250000 0.250000 O    &#xA;0.750000 0.250000 0.250000 O    &#xA;0.750000 0.750000 0.250000 O    &#xA;0.750000 0.750000 0.750000 O    &#xA;0.750000 0.250000 0.750000 O&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;KPOINTS:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mesh auto&#xA;0&#xA;G&#xA;8 8 8&#xA;0  0  0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;POTCAR (I'm not sure if it's possible to paste it here)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;POTCAR:    PAW_PBE Ce_3 06Sep2000&#xA;POTCAR:    PAW_PBE O_s 07Sep2000 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that I have tested the convergence of ENCUT and KPOINTS.&lt;/p&gt;&#xA;&lt;p&gt;I have done following trials, but they do not work, the optimized parameters are still about 5.77 ~ 5.78&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Increasing ENCUT to 800 eV, KPOINTS to 12 12 12&lt;/li&gt;&#xA;&lt;li&gt;spin-polarized calculation with default magmom (it converges to a FM state, while CeO2 is paramagnetic)&lt;/li&gt;&#xA;&lt;li&gt;manually changed the scaling factor, and relaxed the structure with ISIF=2, then fit according to the equation of state to get the equilibrium lattice parameter&lt;/li&gt;&#xA;&lt;li&gt;relax the structure without +U terms&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="8484" LastEditorUserId="8484" LastEditDate="2023-12-06T01:04:37.033" LastActivityDate="2023-12-06T01:04:37.033" Title="Wrong lattice parameter of CeO2 after structure relaxation with VASP" Tags="|density-functional-theory|vasp|geometry-optimization|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12013" PostTypeId="1" CreationDate="2023-12-04T15:08:59.470" Score="3" ViewCount="124" Body="&lt;p&gt;My input file is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%CPU=8&#xA;#P SCF=TIGHT CCSD(T)/aug-cc-pVTZ Opt(ReadOptimize,tight,z-matrix)&#xA;&#xA;h2o test 3&#xA;&#xA;0 1&#xA;O&#xA;H                  1    B1&#xA;H                  1    B1     2  A1&#xA;&#xA;B1 0.96000000&#xA;A1 109.50000032&#xA;&#xA;atoms=3 notatoms=1,2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And I am getting this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; ************************************************&#xA; ** ERROR IN INITNF. NUMBER OF VARIABLES (  0) **&#xA; **   INCORRECT (SHOULD BE BETWEEN 1 AND 50)   **&#xA; ************************************************&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I followed &lt;a href=&quot;https://www.somewhereville.com/2012/04/29/ccsdt-and-mp4-z-matrix-coordinate-oddity-in-gaussian-when-in-doubt-change-your-format/&quot; rel=&quot;nofollow noreferrer&quot;&gt;these instructions&lt;/a&gt;. But, they did not work for me.&lt;/p&gt;&#xA;&lt;p&gt;**What is wrong with my input? **&lt;/p&gt;&#xA;" OwnerUserId="8416" LastActivityDate="2024-03-02T17:53:15.937" Title="GAUSSIAN 16 Error with CCSD(T)" Tags="|gaussian|optimization|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12014" PostTypeId="1" CreationDate="2023-12-04T16:45:07.207" Score="1" ViewCount="32" Body="&lt;p&gt;I have an xyz file formatted in the following way (just a snapshot of the 192 atoms is shown) its cell information is given in #&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;192&#xA;# CELL(abcABC):    7.63946     6.61313     9.30182    89.61648    90.34115    90.22212  Step:           0  Bead:      11 positions{angstrom}  cell{angstrom}&#xA;       H -8.98498e-03  3.73538e+00 -8.74215e-02&#xA;       H -1.67969e-01  3.16369e+00  9.38250e+00&#xA;       H  9.32450e-01  4.21329e+00  1.66229e+00&#xA;       H  8.62187e-01  3.56549e+00  1.63636e+00&#xA;       H -2.92706e-01  3.06970e+00  2.81900e+00&#xA;       H -1.31912e-01  3.72346e+00  3.15581e+00&#xA;       H  5.38656e-01  3.94306e+00  4.92234e+00&#xA;       H  1.16999e+00  3.77125e+00  4.72771e+00&#xA;       H -2.68720e-01  3.52200e+00  6.82601e+00&#xA;       H  1.29835e-02  3.20666e+00  6.15759e+00&#xA;       H  7.83492e-01  4.21326e+00  7.79948e+00&#xA;       H  1.08183e+00  3.56220e+00  7.95853e+00&#xA;       H  1.10954e+00  5.13513e+00 -3.05944e-01&#xA;       H  8.09089e-01  5.18557e+00  9.55863e+00&#xA;       H  1.78392e+00  5.54388e+00  1.25293e+00&#xA;       H  1.76018e+00  5.18439e+00  1.92600e+00&#xA;       H  9.58592e-01  5.39614e+00  2.97232e+00&#xA;       H  1.03674e+00  4.70948e+00  3.39153e+00&#xA;       H  1.99327e+00  5.83024e+00  4.68857e+00&#xA;       H  1.81876e+00  5.22605e+00  4.33652e+00&#xA;       H  8.92271e-01  4.78003e+00  5.72944e+00&#xA;       H  6.53431e-01  4.92438e+00  6.47633e+00&#xA;       H  1.62820e+00  5.67492e+00  7.80865e+00&#xA;       H  2.01922e+00  5.05032e+00  7.38402e+00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I want ASE to read the cell information from the line with the #. Right now if I read in this xyz file from ase, it gives me the cell unit vectors as 0,0,0  and pbc false. Although all the atom positions come out fine. Note, these files were originally generated after running Path Integral Molecular Dynamics from I-PY.&lt;/p&gt;&#xA;&lt;p&gt;How do I read this file into ASE in with the right cell parameters?&lt;/p&gt;&#xA;" OwnerUserId="8485" LastEditorUserId="8485" LastEditDate="2023-12-04T16:55:13.020" LastActivityDate="2023-12-05T01:33:36.370" Title="ASE reading cell dimensions from XYZ file generated by I-Py" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12015" PostTypeId="2" ParentId="11909" CreationDate="2023-12-04T17:20:52.867" Score="2" Body="&lt;p&gt;I'm a bit late to the party but if you're interested I can provide some further information. In general the PES(in the Born Oppenheimer approximation) has dimensionality 3N-6, where N is defined to be the number of atoms in your molecule/system. The 3N term comes from the fact that each atom has 3 cartesian coordinates (x,y,z), we then must discount the translation components (3) and rotational components (3), which is why the 6 is subtracted. If you had a linear molecule (straight line) then your actual dimensionality would be 3N-5, because you'd only discount 3 translational components and 2 rotational components. The reasoning for this requires some geometry which you can find online and I won't bore you with.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand the dimensionality of the CI space is 3N-8 (for a nonlinear molecule), this makes logical sense as it should be a subset of the PES, as it's the intersection of the states. Because the dimensionality of the CI space is 3N-8 we have a 2D space which we haven't accounted for, this is the branching space, this acts to remove the degeneracy(meaning make the energies not equal anymore) of the system, so in a way if you are travelling across any of those 2 directions, you will be ''leaving'' the Conical Intersection (which remember it's a space of intersection between 2 energy states).&lt;/p&gt;&#xA;&lt;p&gt;The point of the branching space is that it's simply the space which acts to remove the degeneracy.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this cleared up any misconceptions you had and let me know if you need any further information/resources to wrap your head around.&lt;/p&gt;&#xA;&lt;p&gt;This website has some pictures (especially the double cone one) which give you a better understanding of what's going on :&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.chm.bris.ac.uk/webprojects2002/grant/webcomp/conical.html#:%7E:text=At%20a%20conical%20intersection%2C%20one,the%20region%20of%20the%20degeneracy&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.chm.bris.ac.uk/webprojects2002/grant/webcomp/conical.html#:~:text=At%20a%20conical%20intersection%2C%20one,the%20region%20of%20the%20degeneracy&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="8486" LastActivityDate="2023-12-04T17:20:52.867" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12016" PostTypeId="2" ParentId="2405" CreationDate="2023-12-04T22:59:00.060" Score="0" Body="&lt;p&gt;You use the experimental lattice parameter to optimize your unit cell. After the optimization you can get the calculated lattice constant to use for subsequent calculations that don't involve relaxations.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-12-04T22:59:00.060" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12017" PostTypeId="1" CreationDate="2023-12-04T23:40:36.693" Score="2" ViewCount="46" Body="&lt;p&gt;I want to plot the relationship between free energy and temperature. I want to consider two plots, when phonons are considered and when phonons are not considered how the free energy changes with temperature. I have already performed phonon calculations on my system using vasp-dfpt. All ideas are welcom.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-12-04T23:40:36.693" Title="Free energy calculation" Tags="|density-functional-theory|vasp|phonons|free-energy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12018" PostTypeId="2" ParentId="12014" CreationDate="2023-12-05T01:33:36.370" Score="2" Body="&lt;p&gt;I ended up writing a script that will just read an output xyz i-py file to something ase can read easily. Here is the code if needed&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    # Open the file&#xA;&#xA;def convert_ipi_to_ase(filename,outfilename):&#xA;    with open(filename, 'r') as file:&#xA;        lines = file.readlines()&#xA;&#xA;    # Process the lines to find CELL values&#xA;    for i, line in enumerate(lines):&#xA;        cell_values = []&#xA;        if 'CELL(abcABC):' in line:&#xA;            split_line = line.split()&#xA;            idx_cell= [idx for idx,s in enumerate(split_line) if 'CELL' in s][0]&#xA;            cell_values = split_line[idx_cell+1:idx_cell+4]  # Extracting the three numeric values after CELL&#xA;&#xA;            # Construct the new line with the desired format&#xA;            new_line = f'Lattice=\&amp;quot;{cell_values[0]} 0.0 0.0 0.0 {cell_values[1]} 0.0 0.0 0.0 {cell_values[2]}\&amp;quot; '&#xA;&#xA;            # Insert the new line before the original '# CELL...' line&#xA;            lines[i] = new_line+line&#xA;&#xA;    # Write the updated content back to the file&#xA;    with open(outfilename, 'w+') as file:&#xA;        file.writelines(lines)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The ase xyz file has a Lattice=&amp;quot;--a 3x3 matrix written as a 9 length vector--&amp;quot; that contains the cell information. So this code just adds that to each of the CELL lines.&lt;/p&gt;&#xA;" OwnerUserId="8485" LastActivityDate="2023-12-05T01:33:36.370" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12019" PostTypeId="1" CreationDate="2023-12-05T07:44:44.887" Score="1" ViewCount="35" Body="&lt;p&gt;Can someone help me with the steps to take to perform Relax calculation of a structure in WIEN2k? Then further what to keep in mind while performing strain calculation on the structure for the relax calculation part.&#xA;I have understood the volume optimization process. So, at which step do I insert the relax calculations?&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2023-12-05T07:44:44.887" Title="Relax calculation in Wien2k" Tags="|cell-optimization|wien2k|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12020" PostTypeId="1" CreationDate="2023-12-03T21:52:18.013" Score="4" ViewCount="115" Body="&lt;p&gt;The cubegen manual gives the signature of cubegen as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;cubegen nprocs  kind  fchkfile  cubefile  npts  format cubefile2&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;nprocs&#xA;Number of shared memory processors used for electrostatic potential calculations. A value of 0 is equivalent to 1 (it is the default). Note that this parameter must be included if other parameters are specified. Previously this parameter was used to specify the amount of memory to allocate. The GAUSS_MEMDEF environment variable should be used instead.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Which would seem to imply that setting &lt;code&gt;nprocs&lt;/code&gt; &amp;gt; 1 would use multiple processes to speed up the cube file writing. However, in practice it doesn't seem to do anything. With Gaussian 16, Revision C.01, the following commands:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;cubegen 1 MO=HOMO file.fchk file.HOMO.cube 0&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;and&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;cubegen 8 MO=HOMO file.fchk file.HOMO.cube 0&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;are treated identically. In both cases, only one processes/thread is used (from &lt;code&gt;ps -o nlwp&lt;/code&gt;), CPU usage (from &lt;code&gt;top&lt;/code&gt;) peaks at only 100%, and the commands take the same time to execute (~ 2 min).&lt;/p&gt;&#xA;&lt;p&gt;Even more confusingly, in Gaussian 09, &lt;code&gt;cubegen 8 MO=HOMO file.fchk file.HOMO.cube 0&lt;/code&gt; does use 8 CPUs (&lt;code&gt;ps -o nlwp&lt;/code&gt;), but the execution is significantly slower than when using only 1?&lt;/p&gt;&#xA;&lt;p&gt;Is this a bug in cubegen, or am I misinterpreting how &lt;code&gt;nprocs&lt;/code&gt; is supposed to work?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;h2&gt;Update&lt;/h2&gt;&#xA;&lt;p&gt;As suggested by jxzou, setting &lt;code&gt;export OMP_NUM_THREADS=n&lt;/code&gt; does actually set the number of threads in cubegen 16, the &lt;code&gt;nprocs&lt;/code&gt; parameter seems to have no effect.&lt;/p&gt;&#xA;&lt;p&gt;However, increasing the number of threads above 1 still results in a massive slowdown. For an example fchk file (~1.3 GB, ~100 atoms), running with one thread takes 3 m 21 s, with only 2 threads it increases to 12 m 37 s?&lt;/p&gt;&#xA;" OwnerUserId="8491" OwnerDisplayName="leeman" LastEditorUserId="8491" LastEditDate="2023-12-06T09:47:26.947" LastActivityDate="2023-12-06T09:47:26.947" Title="How do you run Gaussian's cubegen with multiple processes/threads?" Tags="|computational-chemistry|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12021" PostTypeId="2" ParentId="11145" CreationDate="2023-12-05T14:03:39.313" Score="2" Body="&lt;p&gt;So far, I could find these three sources for parameters for a LJ parametrisation of Li&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;&lt;/th&gt;&#xA;&lt;th&gt;Ref&lt;/th&gt;&#xA;&lt;th&gt;epsilon (kJ/mol)&lt;/th&gt;&#xA;&lt;th&gt;sigma (Ang)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1&lt;/td&gt;&#xA;&lt;td&gt;&lt;a href=&quot;https://github.com/paduagroup/clandp/blob/master/il.ff&quot; rel=&quot;nofollow noreferrer&quot;&gt;CL&amp;amp;P for ionic liquids&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td&gt;0.07648&lt;/td&gt;&#xA;&lt;td&gt;2.126&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2&lt;/td&gt;&#xA;&lt;td&gt;&lt;a href=&quot;https://pubs.acs.org/doi/abs/10.1021/ma902758w&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wu &amp;amp; Wick Macrom. 2010&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td&gt;1.67470&lt;/td&gt;&#xA;&lt;td&gt;1.400&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3&lt;/td&gt;&#xA;&lt;td&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcb.1c05744&quot; rel=&quot;nofollow noreferrer&quot;&gt;Starovoytov J. Phys. Chem. B 2021&lt;/a&gt;&lt;/td&gt;&#xA;&lt;td&gt;0.10500&lt;/td&gt;&#xA;&lt;td&gt;2.000&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;These results are different since they have been parametrized to optimize different properties and show that there is not a unique way to parametrize this element. Besides the large variability, a posteriori, I can see how transport quantity are not largely modified by the specific value.&lt;/p&gt;&#xA;" OwnerUserId="1706" LastEditorUserId="1706" LastEditDate="2023-12-20T02:08:06.293" LastActivityDate="2023-12-20T02:08:06.293" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12022" PostTypeId="2" ParentId="10754" CreationDate="2023-12-05T19:10:07.980" Score="1" Body="&lt;p&gt;OP:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Thanks for your follow-up; I've found the answer, so I'm no longer in need of assistance.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If anyone including the OP wants to write an answer, let me know in a comment and I'll delete this Community Wiki.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-05T19:10:07.980" CommentCount="0" CommunityOwnedDate="2023-12-05T19:10:07.980" ContentLicense="CC BY-SA 4.0" />
  <row Id="12023" PostTypeId="1" CreationDate="2023-12-05T20:36:20.303" Score="1" ViewCount="52" Body="&lt;p&gt;I aim to do a HF-like calculation on a 2D graphene layer. What is the number of electrons per cell?&lt;/p&gt;&#xA;&lt;p&gt;Edit: There are six carbon atoms per cell.&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-12-05T20:52:42.917" LastActivityDate="2023-12-06T04:49:54.740" Title="Number of electrons per cell" Tags="|physical-properties-of-materials|graphene|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12024" PostTypeId="1" CreationDate="2023-12-05T22:44:16.237" Score="0" ViewCount="26" Body="&lt;p&gt;I'm trying to calculate the charge density of a structure using quantum espresso, I've already used the DENS.X and DEN.X commands, but in both tests the executable not found error appears. Can someone help me? Or do you know which command I should use?&#xA;This is the error message that appears:&#xA;mpirun was unable to find the specified executable file, and therefore&#xA;did not launch the job.  This error was first reported for process&#xA;rank 0; it may have occurred for other processes as well.&#xA;NOTE: A common cause for this error is misspelling a mpirun command&#xA;line parameter option (remember that mpirun interprets the first&#xA;unrecognized command line token as the executable).&#xA;Node:       adagp04&#xA;Executable: dens.x&lt;/p&gt;&#xA;&lt;p&gt;and in that link is my .in input file: &lt;a href=&quot;https://drive.google.com/file/d/1nyETxvco8x6XL0XqjHwAZnkgVAJ_ws43/view?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://drive.google.com/file/d/1nyETxvco8x6XL0XqjHwAZnkgVAJ_ws43/view?usp=sharing&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7776" LastActivityDate="2023-12-05T22:44:16.237" Title="What (executable) command to calculate charge density using quantum espresso?" Tags="|density-functional-theory|quantum-espresso|charge-density|" AnswerCount="0" CommentCount="1" ClosedDate="2023-12-08T00:18:56.127" ContentLicense="CC BY-SA 4.0" />
  <row Id="12025" PostTypeId="2" ParentId="11991" CreationDate="2023-12-06T00:38:16.710" Score="8" Body="&lt;p&gt;In the usual perturbation theory approach, we optimise a structure to minimise the forces (to zero, within some small tolerance) and obtain the ground state structure (or a local energy minimum). Perturbing the atomic positions in any way will move them away from this ground state, and so the energy will rise and a force will act to oppose the perturbation. Within the quasi-harmonic approximation, we treat this as a simple harmonic oscillator, and from the mass and force constant matrix (derivatives of the force with respect to atomic position) we can compute the frequency, &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;, of the resultant oscillation. For any perturbation, &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; should be positive (semi-definite).&lt;/p&gt;&#xA;&lt;p&gt;If a phonon calculation results in &amp;quot;negative frequencies&amp;quot; (by which we actually mean negative &lt;span class=&quot;math-container&quot;&gt;$\omega^2$&lt;/span&gt;, i.e. &lt;em&gt;imaginary&lt;/em&gt; frequencies), it means that the energy actually &lt;em&gt;decreases&lt;/em&gt; with respect to the perturbation. This cannot happen if the structure was in the ground state, or indeed in any local energy minimum, so a negative frequency means either:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;the structure is mechanically unstable&lt;/li&gt;&#xA;&lt;li&gt;the structure was not well optimised (i.e. the forces are not small enough)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Since you expect your particular system to be mechanically stable, and your negative frequencies are small, we strongly suspect that the structure was not sufficiently well optimised.&lt;/p&gt;&#xA;&lt;p&gt;Why should these frequencies get worse with increasing k-point sampling? The issue is almost certainly that the lowest energy atomic configuration &lt;em&gt;changes&lt;/em&gt; as you increase the k-point sampling -- probably not by very much, but enough that the forces increase as you increase the k-point sampling for fixed atomic positions. If you re-optimise your structure for the improved k-point sampling, you should find that your phonon frequencies are much better.&lt;/p&gt;&#xA;&lt;p&gt;This same behaviour can happen whenever you change any parameter which affects the geometry of your system. For example, you might see it when using more (or fewer) k-points, or increasing (or decreasing) the plane-wave cut-off energy, or changing the resolution of the fine density grid, even switching pseudopotentials. The solution is always the same: re-optimise your structure.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-12-06T00:38:16.710" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12026" PostTypeId="1" CreationDate="2023-12-06T04:35:23.240" Score="4" ViewCount="42" Body="&lt;p&gt;Greetings Matter Modeling,&lt;/p&gt;&#xA;&lt;p&gt;I'm researching carbon capture dynamics in the context of sorbent regeneration.&lt;/p&gt;&#xA;&lt;p&gt;The UN IPCC Net-Zero goal requires 75 Mt-CO₂/year captured by 2030. According to the IEA, we are capturing roughly 0.01 kt-CO₂/year (0.000133%).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm attempting to analyze contributions from various vibrational modes in Calcite under different conditions. The goal of my research is to eliminate pyroprocessing from calcination. This is a major contributor to global climate change, producing 8% of global emissions. The reactions are highly inefficient, resulting in &lt;a href=&quot;https://doi.org/10.1016/j.joule.2021.04.011&quot; rel=&quot;nofollow noreferrer&quot;&gt;45%&lt;/a&gt; energy losses to the surrounding environment. Through &lt;a href=&quot;https://www.gatesnotes.com/Buildings-are-good-for-people-and-bad-for-the-climate&quot; rel=&quot;nofollow noreferrer&quot;&gt;2060&lt;/a&gt;, we are expected to pour enough concrete to rebuild New York City every month.&lt;/p&gt;&#xA;&lt;p&gt;Calcination is also used in regenerating Direct Air Capture (DAC) sorbents. Currently, &lt;a href=&quot;https://assets-global.website-files.com/639c8f646dc35afd81aeebc2/63c563a258baba2baf4813d9_Heirloom_Perspective-Article.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Heirloom Carbon&lt;/a&gt; is the only active carbon capture facility in the US. Carbon Engineering's technology being built in Texas called Stratos also uses calcination in their &lt;a href=&quot;https://doi.org/10.1016/j.joule.2018.05.006&quot; rel=&quot;nofollow noreferrer&quot;&gt;regeneration technology&lt;/a&gt;. These reactions are 80% thermal energy; 20% electrical. The state-of-the-art relies on burning fossil fuels to achieve high-temperatures, which &lt;a href=&quot;https://doi.org/10.1021/acs.energyfuels.8b03996&quot; rel=&quot;nofollow noreferrer&quot;&gt;damage&lt;/a&gt; sorbents after &lt;a href=&quot;https://doi.org/10.1016/j.apenergy.2016.07.074&quot; rel=&quot;nofollow noreferrer&quot;&gt;multiple cycles&lt;/a&gt;. Carbonation relies on microporous structures to facilitate Knudsen diffusion.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Goal&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm currently attempting to calculate force constants for mp-3953: Calcite. The literature I've reviewed indicate B3LYP provides the most accurate results. Calcium Carbonate undergoes a temperature-dependent, polymorphic, phase transition during heating.&lt;/p&gt;&#xA;&lt;p&gt;A unit cell of Calcite contains 10 atoms. I have a script for a supercell of 1,000 atoms, which is &lt;a href=&quot;https://doi.org/10.1016/j.commatsci.2017.09.033&quot; rel=&quot;nofollow noreferrer&quot;&gt;reported&lt;/a&gt; to accurately calculate the thermal conductivity by equilibrium MD simulations. MD, GK, and other modeling are planned at a later date.&lt;/p&gt;&#xA;&lt;p&gt;Some of the &lt;a href=&quot;https://doi.org/10.1524/zpch.2006.220.7.893&quot; rel=&quot;nofollow noreferrer&quot;&gt;literature&lt;/a&gt; I've reviewed indicates that multiple basis sets are required for the Carbon, Oxygen, and Calcium atoms.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Problem&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The code does not converge after several hundreds of cycles using UKS. The system converged using RHF, however this is not considered accurate due to the delocalized electrons and overestimation of vibrational&lt;/p&gt;&#xA;&lt;p&gt;Energy variations corresponding to displacements considered here (0.001 Å) are on the order of magnitude 10⁻⁶ –10⁻⁷ Hartree, the SCF cycle needs to be very well converged (10⁻¹⁰ Hartree).&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Import necessary PySCF and pymatgen modules&#xA;from pyscf import gto, dft, scf&#xA;from pyscf.scf import addons&#xA;from pymatgen.io.cif import CifParser&#xA;&#xA;# Parse the CIF data&#xA;parser = CifParser(&amp;quot;/home/phill/Desktop/Scripts/Quantum/CaCO3.cif&amp;quot;)&#xA;structure = parser.get_structures()[0]&#xA;&#xA;# Define the molecule&#xA;mol = gto.Mole()&#xA;mol.atom = [[str(site.specie), site.coords.tolist()] for site in structure]&#xA;mol.basis = 'cc-pvdz'&#xA;# mol.symmetry = True&#xA;mol.verbose = 4&#xA;mol.build()&#xA;&#xA;# Define the DFT method&#xA;method = dft.UKS(mol).newton()  # Use the Newton-Raphson method for Unrestricted Kohn-Sham&#xA;method.xc = 'B3LYP'&#xA;method.max_cycle = 2000&#xA;&#xA;# Compute the ground state energy&#xA;energy = method.kernel()&#xA;&#xA;# Optimize the geometry of the molecule&#xA;opt = scf.UKS(mol).newton().run()&#xA;&#xA;# Compute the vibrational frequencies&#xA;from pyscf.hessian import UKS as UKS&#xA;hessian = UKS.Hessian(opt)&#xA;freqs = hessian.kernel()&#xA;&#xA;# Compute the force constants&#xA;force_constants = hessian.hess()&#xA;&#xA;# Print the results to the console&#xA;print('Ground state energy: {} a.u.'.format(energy))&#xA;print('Vibrational frequencies: {} cm^-1'.format(freqs))&#xA;print('Force Constants: {} a.u.'.format(force_constants))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8436" LastEditorUserId="8436" LastEditDate="2023-12-07T00:53:58.570" LastActivityDate="2023-12-07T00:53:58.570" Title="Carbon Capture Research - Force Constants &amp; Basis Sets" Tags="|density-functional-theory|ab-initio-calculations|basis-sets|pyscf|vibrations|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12027" PostTypeId="2" ParentId="12023" CreationDate="2023-12-06T04:49:54.740" Score="1" Body="&lt;p&gt;I did some searching and found that a unit cell of graphene contains two atoms, with each each hexagonal mer consisting of 6 atoms of carbon.&lt;/p&gt;&#xA;&lt;p&gt;There's a helpful diagram here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/questions/69346/a-unit-cell-for-graphene&quot;&gt;https://chemistry.stackexchange.com/questions/69346/a-unit-cell-for-graphene&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is noted that this is for neutral graphene rather than GO, rGO, Bilayer, &lt;em&gt;et al&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I've also constructed the following Google search syntax to help you find literature on the subject:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(graphene) AND (Hartree-Fock OR HF) AND (unit cell) AND (Density Functional Theory OR DFT) AND PySCF&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Please note that PySCF is open-source. If you have a preferred alternative, swap it out.&lt;/p&gt;&#xA;" OwnerUserId="8436" LastActivityDate="2023-12-06T04:49:54.740" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12028" PostTypeId="2" ParentId="12013" CreationDate="2023-12-06T05:17:43.303" Score="1" Body="&lt;p&gt;Are there any extra empty lines after the final line you've posted? In my experience, you need to add a few empty lines at the end of your input file if you want the calculation to work.&lt;/p&gt;&#xA;&lt;p&gt;In other words, the last part of your input should look like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 1&#xA;O&#xA;H  1  B1&#xA;H  1  B1  2  A1&#xA;&#xA;B1 0.96000000&#xA;A1 109.50000032&#xA;&#xA;atoms=3 notatoms=1,2&#xA;&#xA;&#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(Note the extra lines below the end of the input.)&lt;/p&gt;&#xA;&lt;p&gt;That being said, if your plan is to optimise one O–H bond and not the other, you should probably add a &lt;code&gt;B2&lt;/code&gt; variable to your input, otherwise I'm not sure anything other than the angle will change.&lt;/p&gt;&#xA;" OwnerUserId="7606" LastActivityDate="2023-12-06T05:17:43.303" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12029" PostTypeId="2" ParentId="12013" CreationDate="2023-12-06T10:43:00.903" Score="2" Body="&lt;p&gt;Non-gradient optimizations only work in internal coordinates, and if you only want the last H to optimize, you cannot have the B1 variable to also define atom 2.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-12-06T10:43:00.903" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12030" PostTypeId="1" AcceptedAnswerId="12083" CreationDate="2023-12-06T11:37:16.210" Score="4" ViewCount="65" Body="&lt;p&gt;I have read some literatures about the gradient wrt. atom positions of the DFT energy, and find different methods one commonly used in MD(analytical nuclear gradient,&lt;a href=&quot;https://doi.org/10.1007/978-1-4684-8541-7_4&quot; rel=&quot;nofollow noreferrer&quot;&gt;pulay's paper&lt;/a&gt;), and another usually used in phonon calculations(DFPT,&lt;a href=&quot;https://www.quantum-espresso.org/wp-content/uploads/2022/03/ph_user_guide.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;the introduction in QE&lt;/a&gt; and &lt;a href=&quot;https://zeilazanolli.files.wordpress.com/2019/04/2013_dfpt_c2_verstraete_zanolli.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;a brief introduction&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Since they compute the same physical targets, why we make different choice in different tasks? Or what's the main difference between them?&lt;/p&gt;&#xA;" OwnerUserId="5745" LastActivityDate="2023-12-15T09:46:46.670" Title="DFPT vs analytical nuclear gradient" Tags="|molecular-dynamics|phonons|intermolecular-forces|dfpt|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12031" PostTypeId="1" CreationDate="2023-12-06T14:07:01.753" Score="1" ViewCount="17" Body="&lt;p&gt;I am facing difficulty on removing text like XYZ.PRF:, when we run fullprof in External applications in WinPLOTR. Is there some way to remove it?&lt;a href=&quot;https://i.stack.imgur.com/XOX4S.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XOX4S.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8495" LastEditorUserId="5" LastEditDate="2023-12-19T19:49:39.060" LastActivityDate="2023-12-19T19:49:39.060" Title="Removing &quot;say XYZ.PRF:&quot; name in winplotr in Fullprof?" Tags="|visualization-software|software-assistance|windows-operating-system|fullprof-suite|winplotr|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12032" PostTypeId="1" CreationDate="2023-12-06T14:32:43.450" Score="5" ViewCount="79" Body="&lt;p&gt;I am trying to calculate adsorption energies of acetophenone on a 6x6x3 nickel surface with about 12 Angstrom of vacuum above it using SIESTA 5.&lt;/p&gt;&#xA;&lt;p&gt;I have arranged the molecule so that the ring plane is parallel to the surface plane, and the atom of the molecule closest to the top is about 3.5 Angstrom away.&lt;/p&gt;&#xA;&lt;p&gt;I have been running several tests, varying parameters and geometric constraints, always keeping the nickel fixed, but I always obtain results that do not seem energetically reasonable to me because I notice too much energy difference between steps.&lt;/p&gt;&#xA;&lt;p&gt;The energy values I observe for the first steps are&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Target entalphy&lt;/th&gt;&#xA;&lt;th&gt;Free energy&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498938.1929&lt;/td&gt;&#xA;&lt;td&gt;-499060.7102&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498940.3767&lt;/td&gt;&#xA;&lt;td&gt;-499068.3973&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498941.1644&lt;/td&gt;&#xA;&lt;td&gt;-499073.3934&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498941.2172&lt;/td&gt;&#xA;&lt;td&gt;-499073.0439&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498942.9969&lt;/td&gt;&#xA;&lt;td&gt;-499072.1696&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498942.3203&lt;/td&gt;&#xA;&lt;td&gt;-499064.1844&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498943.1381&lt;/td&gt;&#xA;&lt;td&gt;-499070.8697&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498944.7343&lt;/td&gt;&#xA;&lt;td&gt;-499073.6971&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498944.7837&lt;/td&gt;&#xA;&lt;td&gt;-499073.5593&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498944.9385&lt;/td&gt;&#xA;&lt;td&gt;-499073.9446&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;-498946.0347&lt;/td&gt;&#xA;&lt;td&gt;-499075.1088&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;The values according to the output are in eV units. Since these are weak interactions, the energy changes between the different steps seem exaggerated to me.&lt;/p&gt;&#xA;&lt;p&gt;I have inspected the intermediate geometries and they seems to be reasonable, it is hard to tell the difference by simple inspection. The moving distances are reasonably small and I started the process from an optimized acetophenone.&lt;/p&gt;&#xA;&lt;p&gt;The data that I believe are most relevant from the simulation are&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;XC.Functional GGA&#xA;XC.Authors PBE&#xA;DFTD3 true&#xA;PAO.BasisSize DZP&#xA;Mesh.Cutoff 175 Ry&#xA;Spin non-polarized&#xA;%block LatticeVectors   #In Angstroms&#xA;14.906518   0.0      0.0&#xA;7.4532590  12.909423 0.0&#xA;0.0         0.0     30.0855605&#xA;%endblock LatticeVectors&#xA;MD.VariableCell FALSE&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Given the size of the SYSTEM (see the lattice vectors), I understand that using only 1 k-point should give at least reasonable results. Is this correct?&lt;/p&gt;&#xA;&lt;p&gt;To choose the Mesh.Cutoff I analyzed the convergence both when calculating the surface and the molecule, and I was moderately generous. The value is quite larger than the one suggested in the pseudopotentials.&lt;/p&gt;&#xA;&lt;p&gt;What I am missing here?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance&lt;/p&gt;&#xA;" OwnerUserId="522" LastActivityDate="2023-12-06T19:45:38.100" Title="Large energy differences across successive geometry optimization steps in SIESTA" Tags="|geometry-optimization|siesta|periodic-system|adsorption|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12033" PostTypeId="2" ParentId="12032" CreationDate="2023-12-06T19:39:06.380" Score="4" Body="&lt;p&gt;In order to calculate the adsorption energies of cetophenone on a nickel surface, you need to do three calculations.&lt;/p&gt;&#xA;&lt;p&gt;Considering the same cell parameters:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Run a calculation with only the nickel surface. Keep the optimized energy as &lt;span class=&quot;math-container&quot;&gt;$E_{Ni}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Run the calculations with only the cetophenone molecule. Keep the optimized energy as &lt;span class=&quot;math-container&quot;&gt;$E_{cet}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Run the calculation with the &amp;quot;complex&amp;quot;: nickel surface + cetophenone. Keep the optimized energy as &lt;span class=&quot;math-container&quot;&gt;$E_{Ni+cet}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;Calculate the binding or adsorption as follows: &lt;span class=&quot;math-container&quot;&gt;$E_{bind}=E_{Ni+cet}-E_{cet}-E_{Ni}$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Notes:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In order to get more precise values, you need to run the calculations using the BSSE correction.&lt;/li&gt;&#xA;&lt;li&gt;Run the calculations in the other two possible conformations: with the cetophenone perpendicular to the nickel surface with the O-CH down and up.&lt;/li&gt;&#xA;&lt;li&gt;For this latter conformation, I imagine you will need a bigger cell, keep in mind this if you want to compare all the results.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Also, take a look at this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/378/what-are-the-scientific-justifications-of-the-binding-energy-equation&quot;&gt;question/answers&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2023-12-06T19:45:38.100" LastActivityDate="2023-12-06T19:45:38.100" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12034" PostTypeId="1" AcceptedAnswerId="12048" CreationDate="2023-12-06T22:31:25.647" Score="4" ViewCount="138" Body="&lt;p&gt;I have localized the canonical Hartree-Fock orbitals for a molecule in PySCF. Now I want to perform ccsd calculations with these localized orbitals. Is it possible with pyscf?&lt;/p&gt;&#xA;&lt;p&gt;Example with CCSD with canonical HF orbitals.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy&#xA;from pyscf import gto,scf,cc,lo&#xA;mol = gto.M(&#xA;    verbose = 4,&#xA;    atom = [&#xA;       [ 'H'   ,             0.000000 ,  0.000000 ,  0.100000],&#xA;       [ 'H1'   ,             0.000000 ,  0.000000 ,  0.860000],&#xA;       [ 'H'   ,             2.000000 ,  0.000000 ,  0.100000],&#xA;       [ 'H1'   ,             2.000000 ,  0.000000 ,  0.860000]],&#xA;    basis = {'H': gto.parse('''&#xA;H S&#xA;      0.9000000000D+00  0.1000000000D+01&#xA;H S&#xA;      0.3000000000D+00  0.1000000000D+01&#xA;                 '''),'H1': gto.parse('''&#xA;H S&#xA;      0.9900000000D+00  0.1000000000D+01&#xA;H S&#xA;      0.3900000000D+00  0.1000000000D+01&#xA;                 ''')&#xA;      },&#xA;cart=True&#xA;)&#xA;mf=scf.RHF(mol)&#xA;mf.kernel()&#xA;# Canonical CCSD calculation&#xA;ccsd_can = cc.CCSD(mf)&#xA;ccsd_can.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which runs fine. The energies are,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;converged SCF energy = -2.06459106224567&#xA;Init t2, MP2 energy = -2.09735912778898  E_corr(MP2) -0.0327680655433131&#xA;E(CCSD) = -2.113707458228744  E_corr = -0.04911639598307826&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Example with Boys localization followed by CCSD calculation.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;localization_method = 'boys'  # You can choose 'boys', 'iao', 'pipek', etc.&#xA;mo_coeff_localized = lo.orth.orth_ao(mol, localization_method) &#xA;mo_occ_localized = mf.mo_occ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This shows, warning,&#xA;WARN: Weak orthogonality for localized orbitals 2.449489742783178.&#xA;Now going to the CCSD calculation,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ccsd_localized = cc.CCSD(mf)&#xA;ccsd_localized.mo_coeff = mo_coeff_localized&#xA;mo_occ_localized = mf.mo_occ&#xA;ccsd_localized.mo_occ = mo_occ_localized&#xA;ccsd_localized.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which shows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;******** &amp;lt;class 'pyscf.cc.ccsd.CCSD'&amp;gt; ********&#xA;CC2 = 0&#xA;CCSD nocc = 2, nmo = 8&#xA;max_cycle = 50&#xA;direct = 0&#xA;conv_tol = 1e-07&#xA;conv_tol_normt = 1e-05&#xA;diis_space = 6&#xA;diis_start_cycle = 0&#xA;diis_start_energy_diff = 1e+09&#xA;max_memory 4000 MB (current use 158 MB)&#xA;&#xA;WARN: HOMO-LUMO gap 0.0 too small for CCSD.&#xA;CCSD may be difficult to converge. Increasing CCSD Attribute level_shift may improve convergence.&#xA;&#xA;/home/pro/psi4conda/lib/python3.10/site-packages/pyscf/cc/ccsd.py:1053: RuntimeWarning: invalid value encountered in divide&#xA;  t1 = eris.fock[:nocc,nocc:] / eia&#xA;/home/pro/psi4conda/lib/python3.10/site-packages/pyscf/cc/ccsd.py:1060: RuntimeWarning: invalid value encountered in divide&#xA;  t2[:,:,p0:p1] = (eris_ovov.transpose(0,2,1,3).conj()&#xA;Init t2, MP2 energy = nan  E_corr(MP2) nan&#xA;Init E_corr(CCSD) = nan&#xA;cycle = 1  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 2  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 3  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 4  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 47  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 48  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 49  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;cycle = 50  E_corr(CCSD) = nan  dE = nan  norm(t1,t2) = nan&#xA;CCSD not converged&#xA;E(CCSD) = nan  E_corr = nan&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="5" LastEditDate="2023-12-09T17:48:22.127" LastActivityDate="2023-12-10T17:11:43.923" Title="Post-hartree fock calculation with localized Molecular orbitals in PySCF" Tags="|quantum-chemistry|molecular-modeling|hartree-fock|pyscf|coupled-cluster|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12035" PostTypeId="1" CreationDate="2023-12-07T04:19:43.037" Score="3" ViewCount="21" Body="&lt;p&gt;I am facing difficulty in removing the upper tic in the winplotr in fullprof software. I just want the tics to be below where angles are measured as shown in the image and not above. I tried playing with by going to Option-Frame Features&lt;a href=&quot;https://i.stack.imgur.com/S5UwR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S5UwR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;, but as soon as i set one say X major axis to 0, it simultaneously remove both above and below tics&lt;/p&gt;&#xA;" OwnerUserId="8495" LastActivityDate="2023-12-07T04:19:43.037" Title="Steps to remove upper tics in the x-axis in winplotr in Fullprof" Tags="|fullprof-suite|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12036" PostTypeId="2" ParentId="12009" CreationDate="2023-12-08T08:24:40.893" Score="2" Body="&lt;p&gt;Whenever there is an error saying &lt;code&gt;Reading namelist *******&lt;/code&gt;, that means there is something wrong with the input file, almost always it is a syntax mistake.&lt;/p&gt;&#xA;&lt;p&gt;I think here you didn't close the namelist with a &lt;code&gt;/&lt;/code&gt; properly. I am not sure about the soundness of your input parameters, but a correct way to write the same input file would look like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;INPUTPP&#xA;calculation = 'eps'&#xA;outdir      = './'&#xA;/&#xA;&amp;amp;ENERGY_GRID &#xA;smeartype  = 'gauss'&#xA;intersmear = 0.1500&#xA;intrasmear = 0.000&#xA;wmax       = 10.000&#xA;wmin       = 0.000&#xA;nw         = 600&#xA;shift      = 0.010&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This should work.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-12-08T08:24:40.893" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12037" PostTypeId="1" AcceptedAnswerId="12039" CreationDate="2023-12-08T13:21:19.207" Score="5" ViewCount="202" Body="&lt;p&gt;I would like to calculate the energy difference between the first excited singlet and the first excited triplet of a given molecule in solvent, on Gaussian. In this &lt;a href=&quot;https://chemrxiv.org/engage/chemrxiv/article-details/6376b5a1e70b0adf83a1140b&quot; rel=&quot;noreferrer&quot;&gt;publication&lt;/a&gt;, they state that using TDA-DFT can be a good level of theory for this type of calculation.&#xA;For this reason, I have built two inputs. To calculate the singlet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt M062X/6-311g* TDA=(singlet,root=1) scrf=(solvent=dichloromethane) int=ultrafine Nosymm&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and to calculate the triplet&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt M062X/6-311g* TDA=(triplet,root=1) scrf=(solvent=dichloromethane) int=ultrafine Nosymm&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After running these calculations, I obtain two outputs that contain, for the singlet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    Excited State   1:   Singlet-?Sym    3.0913 eV  401.07 nm  f=0.7556  &amp;lt;S**2&amp;gt;=0.000&#xA;     110 -&amp;gt;111         0.67231&#xA; This state for optimization and/or second-order correction.&#xA; Total Energy, E(CIS/TDA) =  -1315.38267036&#xA; Copying the excited state density for this state as the 1-particle RhoCI density.&#xA; &#xA; Excited state symmetry could not be determined.&#xA; Excited State   2:  Singlet-?Sym    3.6009 eV  344.32 nm  f=0.0405  &amp;lt;S**2&amp;gt;=0.000&#xA;     106 -&amp;gt;111         0.14329&#xA;     107 -&amp;gt;111        -0.15242&#xA;     108 -&amp;gt;111         0.32533&#xA;     110 -&amp;gt;112         0.51705&#xA;     110 -&amp;gt;113         0.18032&#xA; &#xA; Excited state symmetry could not be determined.&#xA; Excited State   3:  Singlet-?Sym    3.9376 eV  314.87 nm  f=0.1058  &amp;lt;S**2&amp;gt;=0.000&#xA;     106 -&amp;gt;111        -0.22741&#xA;     106 -&amp;gt;112         0.10392&#xA;     108 -&amp;gt;111         0.11810&#xA;     108 -&amp;gt;115         0.11499&#xA;     109 -&amp;gt;111         0.50685&#xA;     110 -&amp;gt;112         0.12586&#xA;     110 -&amp;gt;113        -0.28556&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for the triplet:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Excited State   1:   Triplet-?Sym    2.1716 eV  570.93 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;     109 -&amp;gt;111        -0.10733&#xA;     110 -&amp;gt;111         0.66438&#xA; This state for optimization and/or second-order correction.&#xA; Total Energy, E(CIS/TDA) =  -1315.41646875&#xA; Copying the excited state density for this state as the 1-particle RhoCI density.&#xA; &#xA; Excited state symmetry could not be determined.&#xA; Excited State   2:  Triplet-?Sym    2.9918 eV  414.41 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;     109 -&amp;gt;111         0.34352&#xA;     109 -&amp;gt;113        -0.11747&#xA;     110 -&amp;gt;111         0.13157&#xA;     110 -&amp;gt;112         0.55107&#xA; &#xA; Excited state symmetry could not be determined.&#xA; Excited State   3:  Triplet-?Sym    3.3346 eV  371.81 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;     107 -&amp;gt;111         0.14468&#xA;     108 -&amp;gt;111        -0.25678&#xA;     109 -&amp;gt;111        -0.34944&#xA;     109 -&amp;gt;112        -0.21840&#xA;     110 -&amp;gt;112         0.22031&#xA;     110 -&amp;gt;113         0.37233&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am a little confused by the output itself. Is the energy that one should consider for the difference in energy the one reported after 'Total energy' (for example, -1315.38267036 for the singlet) or the one reported after the 'Excited state 1' (3.0913eV for the singlet)?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-12-08T15:22:20.920" Title="S1-T1 energy difference in Gaussian" Tags="|gaussian|td-dft|excited-states|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12038" PostTypeId="2" ParentId="12034" CreationDate="2023-12-08T14:58:53.953" Score="3" Body="&lt;p&gt;CCSD is invariant to a unitary transformation of the orbitals, as a localization is. You should thus get the same result with canonical and localized orbitals. However, since the CCSD amplitudes are determined by solving a set of non-linear equations, some orbitals may be easier to get amplitude convergence than others. Most (all?) CCSD codes likely assume canonical orbitals, and the implemented amplitude solver perhaps assumes this.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-12-08T14:58:53.953" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12039" PostTypeId="2" ParentId="12037" CreationDate="2023-12-08T15:22:20.920" Score="8" Body="&lt;p&gt;The excitation energies are 3.09 and 2.17 eV, respectively, both relative to the (same) ground state, and thus the energy difference is 3.09 - 2.17 = 0.92 eV. The Total Energy is the ground state energy + the excitation energy, now in Hartree units. Subtracting these, -1315.38267 - (-1315.41647) and multiplying with 27.21 to get eV, again gives 0.92 eV.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-12-08T15:22:20.920" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12040" PostTypeId="2" ParentId="11273" CreationDate="2023-12-08T16:19:12.800" Score="1" Body="&lt;p&gt;VIAMD software will allow you to do that.&#xA;You can use the sdf function in the script editor after loading your trajectory.&#xA;It would like something like that depending on your topology:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;V = sdf(resname(&amp;quot;NH4&amp;quot;), element('O') in resname(&amp;quot;SOL&amp;quot;), 5.0);&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can then see your distribution in the density window. In Property, you will see V, by clicking on it will display in the window.&lt;/p&gt;&#xA;&lt;p&gt;There is tutorial in &lt;a href=&quot;https://github.com/scanberg/viamd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;the wiki of the github&lt;/a&gt; to tune your visualization of the SDF. VIAMD as been &lt;a href=&quot;https://doi.org/10.1021/acs.jcim.3c01033&quot; rel=&quot;nofollow noreferrer&quot;&gt;published here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="8509" LastEditorUserId="5" LastEditDate="2023-12-08T16:50:05.447" LastActivityDate="2023-12-08T16:50:05.447" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12042" PostTypeId="1" CreationDate="2023-12-08T21:17:16.997" Score="5" ViewCount="196" Body="&lt;p&gt;Even though I use some Quantum ESPRESSO specific terminology here, this question applies to any plane-wave based pseudopotential DFT code. We know that before running an actual DFT calculation, a few parameters must be set following convergence test of energy. For my calculations, I usually converge these parameters in the following order:&lt;/p&gt;&#xA;&lt;h5&gt;(1) Kinetic energy cutoff for wavefunctions:&lt;/h5&gt;&#xA;&lt;p&gt;The total energy per atom must converge within a certain convergence threshold (usually around 0.1 mRy or 1.36 meV) for increasing energy cutoff. &lt;code&gt;ecutwfc&lt;/code&gt; in QE or &lt;code&gt;ENCUT&lt;/code&gt; in VASP.&lt;/p&gt;&#xA;&lt;h5&gt;(2) Kinetic energy cutoff for charge density:&lt;/h5&gt;&#xA;&lt;p&gt;Same as above but for charge density. &lt;code&gt;ecutrho&lt;/code&gt; in QE. Usually 4 to 8 times larger than &lt;code&gt;ecutwfc&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;h5&gt;(3) K-point grid/k-mesh:&lt;/h5&gt;&#xA;&lt;p&gt;The total energy per atom must converge for increasingly dens k-mesh.&lt;/p&gt;&#xA;&lt;h5&gt;(4) smearing type and broadening:&lt;/h5&gt;&#xA;&lt;p&gt;The total energy per atom must converge for decreasing broadening value. &lt;code&gt;degauss&lt;/code&gt; in QE.&lt;/p&gt;&#xA;&lt;p&gt;When I perform a DFT+U calculation, I do not repeat the convergence tests. Also, if I do defect calculations such as atomic substitution or vacancy, then I relax the system again but do not perform a new set of convergence tests. Are the order of these convergence correct? Should I include any more convergence tests before proceeding to the actual calculation? For example, should I include a convergence test by increasing the size of the supercell to see if the total energy per atom is converging?&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="5" LastEditDate="2023-12-11T12:12:48.070" LastActivityDate="2023-12-13T17:39:41.753" Title="In plane-wave DFT, what needs to be converged and in what order?" Tags="|density-functional-theory|quantum-espresso|one-topic-per-answer|convergence-test|plane-waves|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12043" PostTypeId="1" AcceptedAnswerId="12044" CreationDate="2023-12-09T02:52:15.140" Score="6" ViewCount="157" Body="&lt;p&gt;According to VASP manual, the ISIF tag determines whether the stress tensor is calculated and which ionic degrees of freedom are varied.&lt;/p&gt;&#xA;&lt;p&gt;Suppose that I want to relax the &lt;strong&gt;cell shape&lt;/strong&gt; in specific direction (x, y, or z) and keep it fixed in the other two directions, is it possible to do that in VASP? and what are the required tags to perform such relaxation?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-09T03:35:33.903" Title="How can I perform a cell shape relaxation in a specified direction using VASP?" Tags="|vasp|cell-optimization|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12044" PostTypeId="2" ParentId="12043" CreationDate="2023-12-09T03:35:33.903" Score="6" Body="&lt;p&gt;As of July 2023 at least, VASP doesn't have such a functionality (see this &lt;a href=&quot;https://www.vasp.at/forum/viewtopic.php?f=4&amp;amp;t=19086&quot; rel=&quot;noreferrer&quot;&gt;post&lt;/a&gt;). I know of two options (I've used the first one frequently when relaxing slab structures while keeping the vacuum axis fixed).&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the following &lt;a href=&quot;https://github.com/Chengcheng-Xiao/VASP_OPT_AXIS&quot; rel=&quot;noreferrer&quot;&gt;patch&lt;/a&gt; to add the functionality of fixing specific lattice vector components.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Use the ASE (atomic simulation environment) &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/calculators/vasp.html#module-ase.calculators.vasp&quot; rel=&quot;noreferrer&quot;&gt;VASP calculator&lt;/a&gt; for the relaxation and use a &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/filters.html&quot; rel=&quot;noreferrer&quot;&gt;filter&lt;/a&gt; to specify how the lattice is relaxed.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-12-09T03:35:33.903" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12045" PostTypeId="2" ParentId="10295" CreationDate="2023-12-09T16:39:36.190" Score="1" Body="&lt;p&gt;The OP found the comment by Greg helpful:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;1) Giving us kpoint meshes without telling actual dimensions is not really helpful. You may want to share the unit cell size. Is it 0.1 nm? 1? 10? 2) Without knowing specifics about your system, most probably a n x 1 x1-type mash makes more sense for a 1D infinite tube. Also, since DFTB works on local basis, you can infinity increase the cell size in the two other directions without increasing computational cost. 3) In principle, you need to converge the density for DOS calculations. However, single point and DOS/PDOS calculations are cheap, so you can check several meshes.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If anyone wants to write a more detailed answer, please leave a comment and I'll delete this Community Wiki.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-09T16:39:36.190" CommentCount="0" CommunityOwnedDate="2023-12-09T16:39:36.190" ContentLicense="CC BY-SA 4.0" />
  <row Id="12046" PostTypeId="2" ParentId="9917" CreationDate="2023-12-09T17:14:16.940" Score="4" Body="&lt;h2&gt;Molecular Docking Simulations: A comprehensive guide for beginners&lt;/h2&gt;&#xA;&lt;p&gt;One of the most commonly used tools in the drug design chain is molecular docking.&lt;/p&gt;&#xA;&lt;p&gt;Our book presents a general view of the current methods, implementations, validation, etc. The data of the book is below:&lt;/p&gt;&#xA;&lt;p&gt;Title: &lt;strong&gt;Molecular Docking Simulations: A comprehensive guide for beginners&lt;/strong&gt;&lt;br /&gt;&#xA;Abstract:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Drug discovery researchers use molecular docking simulations. These&#xA;simulations anticipate the binding affinity and orientation of a tiny&#xA;chemical with a target protein, helping identify medication&#xA;possibilities. Molecular docking simulations employ computational&#xA;algorithms to estimate a small molecule's best binding pose in a&#xA;target protein's binding site. The simulation identifies the binding&#xA;mode with the highest affinity to anticipate the small molecule's&#xA;therapeutic efficacy. Molecular docking simulations are ligand-based&#xA;or structure-based. Structure-based docking simulations employ the&#xA;target protein's three-dimensional structure to predict the small&#xA;molecule's binding mode, while ligand-based simulations use the small&#xA;molecule's characteristics to estimate its affinity. Researchers use&#xA;molecular modeling tools to visualize small molecule-target protein&#xA;binding in molecular docking simulations. The software calculates&#xA;interaction energy to predict small molecule-target protein binding&#xA;affinity. Molecular docking simulations can rapidly predict the&#xA;binding affinity of many tiny compounds. They are useful for drug&#xA;development, which involves identifying promising molecules from a&#xA;huge pool. Protein engineering, protein-protein interactions, and drug&#xA;discovery involve molecular docking simulations. They help researchers&#xA;in these domains understand molecular pathways and design novel&#xA;medicines.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Availability: Amazon stores as &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/B0C7FFVJ6C&quot; rel=&quot;nofollow noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;Kindle eBook&lt;/a&gt; and &lt;a href=&quot;https://rads.stackoverflow.com/amzn/click/com/B0C87PLJYV&quot; rel=&quot;nofollow noreferrer&quot; rel=&quot;nofollow noreferrer&quot;&gt;paperback&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2023-12-09T17:31:01.580" LastActivityDate="2023-12-09T17:31:01.580" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12047" PostTypeId="2" ParentId="12004" CreationDate="2023-12-10T10:08:38.550" Score="2" Body="&lt;p&gt;Defining the geometry in terms of z-matrix internal coordinates would make this very easy, I think. Define COM as a dummy atom, place another dummy atom to define the molecular plane, place A and B with suitable distances to dummy-1 and 90 degree angles to dummy-2, and B having a torsional angle of 180 relative to A. Now define C with a distance to dummy-1 and an angle to B and torsional of 180 to A. Simply keep the first two distances for A and B fixed, and give the scan range and step size for the two variables defining C, as given in the Gaussian manual for the keyword SCAN. That should work for all combinations of R and theta, including 0 and 180.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-12-10T10:08:38.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12048" PostTypeId="2" ParentId="12034" CreationDate="2023-12-10T17:11:43.923" Score="2" Body="&lt;h1&gt;Working input file and output&lt;/h1&gt;&#xA;&lt;p&gt;Without changing your input lines for the HF calculation and the CCSD calculation without localization of orbitals, the following lines worked for doing CCSD with localized orbitals, &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64834636#64834636&quot;&gt;the full input and output files can be found in our chat conversation&lt;/a&gt;, but I'll present the part involving localized orbitals here (and I'll use &lt;code&gt;[...]&lt;/code&gt; to remove some less exciting parts):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;boys_localized=lo.Boys(mol)&#xA;boys_localized.kernel(mf.mo_coeff) &#xA;ccsd_boys = cc.CCSD(mf)&#xA;ccsd_boys.mo_occ = mf.mo_occ&#xA;ccsd_boys.mo_coeff = boys_localized.mo_coeff&#xA;ccsd_boys.kernel() &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Output (Boys localization):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;******** &amp;lt;class 'pyscf.lo.boys.Boys'&amp;gt; ********&#xA;[...]&#xA;CCSD converged&#xA;E(CCSD) = -1.255725715461556 E_corr = -0.07723572035747919&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These can be compared the CCSD output when localization of orbitals had not been done:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CCSD converged &#xA;E(CCSD) = -1.255729964675672 E_corr = -0.07349346928566028 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Why did your original attempt not work?&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64831678#64831678&quot;&gt;I found your original code confusing&lt;/a&gt;. For example, I could not see why you had the following command twice, with just &lt;code&gt;mo_occ_localized = mf.mo_occ&lt;/code&gt; in between:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mo_occ_localized = mf.mo_occ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also, while a more verbose code can have its advantages, it was hard for me to digest what was happening when you had &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64831591#64831591&quot;&gt;8 lines&lt;/a&gt; used to accomplish what seems to be more digestable when presented in &lt;a href=&quot;https://chat.stackexchange.com/transcript/message/64831681#64831681&quot;&gt;4 lines, as I did in our chat conversation&lt;/a&gt;. You then wrote:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;After your advice, I ran the code again in a fresh notebook. Now it seems it runs fine. Let me share the input and output.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Based on your input and output, it seems that my advice to remove the duplicate line and to condense the input file commands a bit, was indeed followed and led to a working calculation although your final version is a bit different from what I wrote.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-10T17:11:43.923" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12049" PostTypeId="1" AcceptedAnswerId="12127" CreationDate="2023-12-10T17:37:04.847" Score="3" ViewCount="135" Body="&lt;p&gt;I want to ask a further question related to &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12037/s1-t1-energy-difference-in-gaussian&quot;&gt;this one&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I have performed the calculations as explained and obtained a difference in energy of 0.71eV with the TDA-DFT level of theory.&lt;/p&gt;&#xA;&lt;p&gt;Then, I tried to do the same calculation but with DFT level of theory. I first optimized the first &lt;em&gt;excited&lt;/em&gt; singlet S1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    # opt M062X/6-311g* scrf=(solvent=dichloromethane) Geom=AllCheck int=ultrafine Nosymm &#xA;&#xA;molecule1&#xA;&#xA;0 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the first &lt;em&gt;excited&lt;/em&gt; triplet state T1&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; # opt M062X/6-311g* scrf=(solvent=dichloromethane) Geom=AllCheck int=ultrafine Nosymm &#xA;&#xA;molecule1&#xA;&#xA;0 3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the result of the first calculation is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; SCF Done:  E(RM062X) =  -1315.49716286     A.U. after    6 cycles&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for the second is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SCF Done:  E(RM062X) =  -1315.49716286     A.U. after    6 cycles&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Leading to a difference in energy of exactly zero. Where does this big difference come from? Is there something wrong with the inputs?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="5" LastEditDate="2023-12-19T18:24:41.747" LastActivityDate="2023-12-21T10:52:12.033" Title="Difference in energy between first excited singlet and first excited triplet with DFT in Gaussian" Tags="|density-functional-theory|gaussian|td-dft|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12050" PostTypeId="1" AcceptedAnswerId="12062" CreationDate="2023-12-11T06:41:27.323" Score="3" ViewCount="73" Body="&lt;p&gt;I have the following POSCAR file of a tubular structure that was created using python&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NT (n,m)=(5,0). T(x,y)=(1,2)&#xA;1&#xA;3.969568047197358 0.0 0.0&#xA;0.0 3.969568047197358 0.0&#xA;0.0 0.0 4.32&#xA;C&#xA;20&#xA;Cartesian&#xA;1.984784023598679 0.0 2.88&#xA;1.6057240055491107 1.1666267776525108 0.72&#xA;1.984784023598679 0.0 1.44&#xA;0.6133319934558785 1.8876417790820375 2.88&#xA;1.6057240049613253 1.1666267784615278 3.6&#xA;-0.6133319929803498 1.887641779236546 0.72&#xA;0.6133319934558785 1.8876417790820375 1.44&#xA;-1.6057240052552177 1.1666267780570196 2.88&#xA;-0.6133319939314065 1.887641778927529 3.6&#xA;-1.984784023598679 5.000005037854325e-10 0.72&#xA;-1.6057240052552177 1.1666267780570196 1.44&#xA;-1.605724005255218 -1.1666267780570192 2.88&#xA;-1.984784023598679 -5.000000176535521e-10 3.6&#xA;-0.6133319939314074 -1.8876417789275288 0.72&#xA;-1.605724005255218 -1.1666267780570192 1.44&#xA;0.6133319934558781 -1.8876417790820377 2.88&#xA;-0.6133319929803502 -1.8876417792365459 3.6&#xA;1.6057240049613248 -1.1666267784615285 0.72&#xA;0.6133319934558781 -1.8876417790820377 1.44&#xA;1.6057240055491104 -1.166626777652511 3.6 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I try to render this file with VESTA, the atoms would overlap onto each other as shown in the Figure (a). However, while using other softwares such as ASE, OVITO, or AVOGADRO, I am able to see the correct strcture as in Figure (b).&lt;/p&gt;&#xA;&lt;p&gt;I would like to know how does VESTA render the format of POSCAR or .vasp files. Moreover, how would vasp treat this POSCAR file, in other words can I use this structure as an input for electronic calculations using VASP?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xvpa2.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xvpa2.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-12T16:33:15.540" Title="How does VESTA render files with POSCAR format" Tags="|vasp|vesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12051" PostTypeId="1" AcceptedAnswerId="12053" CreationDate="2023-12-11T06:52:26.403" Score="5" ViewCount="132" Body="&lt;p&gt;&lt;a href=&quot;https://chemistry.stackexchange.com/q/178212/27342&quot;&gt;Cross-posted on Chem.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I just started with dalton and facing quite a few challenges in visualizing its output. I tried using Chemcraft, though its showing me some of the results like optimization steps and optimization geometry but apart from this I'm not able to render the molecular orbitals and any other output present in my output file. For the same I'm thinking to switch to Multiwfn , but i don't have any idea on how to convert the dalton output file to wfn format, or if there's a way to generate wfn file using Dalton itself.&#xA;I'm attaching both mol and dal input for my molecule (substituted with benzene)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;.mol file :&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;BASIS&#xA;6-311++G**&#xA; Benzene using the 6-311++G** Basis set&#xA; Using automatic symmetry detection.&#xA;Atomtypes=2 Angstrom&#xA;Charge=6.0 Atoms=6&#xA;C       -0.103371363     -1.382362916      0.000073745&#xA;C        1.145480831     -0.780684419      0.000165244&#xA;C        1.248834055      0.601642178      0.000191086&#xA;C        0.103338718      1.382340864      0.000097814&#xA;C       -1.145467886      0.780684449     -0.000013292&#xA;C       -1.248824804     -0.601692630      0.000002114&#xA;Charge=1.0 Atoms=6&#xA;H       -0.183551104     -2.455005348      0.000068037&#xA;H        2.034304017     -1.386476167      0.000197679&#xA;H        2.217858498      1.068527661      0.000304816&#xA;H        0.183560028      2.454980152      0.000096281&#xA;H       -2.034314510      1.386442157     -0.000107354&#xA;H       -2.217867372     -1.068540874     -0.000056256&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;.dal file:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;**DALTON INPUT&#xA;.RUN WAVE FUNCTIONS&#xA;**WAVE FUNCTIONS&#xA;.HF&#xA;**PROPERTIES&#xA;.EXCITA&#xA;4&#xA;**END OF DALTON INPUT&#xA;&lt;/pre&gt;&#xA;" OwnerUserId="8519" LastEditorUserId="5" LastEditDate="2023-12-11T12:15:03.763" LastActivityDate="2023-12-11T12:15:03.763" Title="How to convert Dalton Output FIle (.out) to Multiwfn input file (.wfn)?" Tags="|computational-chemistry|multiwfn|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12052" PostTypeId="1" CreationDate="2023-12-11T07:27:18.610" Score="3" ViewCount="27" Body="&lt;p&gt;I've recently been working on structural modeling of HEAs and got a little confused when I read about the SSOS approach. I would appreciate it if anyone is familiar with the SSOS method or MCSQS and can answer this question.&lt;/p&gt;&#xA;&lt;p&gt;What is the Pair coorrelation function mentioned in the article and&#xA;how does he do his calculations.&lt;/p&gt;&#xA;&lt;p&gt;The relevant literature on the SSOS method is as follows&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;10.1103/PhysRevLett.116.105501 Efficient Ab initio Modeling of Random Multicomponent Alloys&lt;/li&gt;&#xA;&lt;li&gt;10.1103/PhysRevB.102.174209 Generalized small set of ordered structures method for the solid-solution phase of high-entropy alloys&lt;/li&gt;&#xA;&lt;li&gt;10.1016/j.commatsci.2020.110213 High-throughput calculations based on the small set of ordered structures method for non-equimolar high entropy alloys&lt;/li&gt;&#xA;&lt;li&gt;10.1016/j.jallcom.2021.160776 First-principles-based high-throughput computation for high entropy alloys with short range order&lt;/li&gt;&#xA;&lt;li&gt;10.1038/s41598-022-16082-w A first‑principles‑based high fidelity, high throughput approach for the design of high entropy alloys&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="8508" LastEditorUserId="5" LastEditDate="2023-12-11T12:16:30.570" LastActivityDate="2023-12-11T12:16:30.570" Title="How to model and compute the structure of high entropy alloys (HEAs) using SSOS methods with ATAT" Tags="|density-functional-theory|crystallography|materials-design|special-quasirandom-structures|alloy-theoretic-automated-toolkit|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12053" PostTypeId="2" ParentId="12051" CreationDate="2023-12-11T12:10:02.093" Score="5" Body="&lt;p&gt;The MULTIWFN can read the MOLDEN format. Following the DALTON manual:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Calculations with Dalton is most conveniently done using the supplied&#xA;dalton shell script. The general usage of the dalton script is as&#xA;follows&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;dalton [options] dalinp{.dal} [molinp{.mol} [potinp{.pot}]]&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;One of the options is:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;molden.inp Contains the input required for visualizing the results of&#xA;the calculation using the MOLDEN program&#xA;(&lt;a href=&quot;http://www.cmbi.ru.nl/molden/molden.html&quot; rel=&quot;noreferrer&quot;&gt;http://www.cmbi.ru.nl/molden/molden.html&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="24" LastActivityDate="2023-12-11T12:10:02.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12054" PostTypeId="2" ParentId="12042" CreationDate="2023-12-11T12:26:57.900" Score="3" Body="&lt;p&gt;The order of convergence tests you provided is a very good starting point which I believe will give very accurate numerical results in most cases. However, in my opinion and based on some prior experience with VASP, the inclusion of the onsite Coulomb interaction term (U) in DFT+U introduces an additional parameter that needs to be properly converged. I think the following steps might give you some insights:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;U value convergence: The total energy per atom should be examined as&#xA;you vary the value of the onsite Coulomb interaction parameter (U).&#xA;Typically, a range of U values is tested to ensure the convergence&#xA;of the total energy and other relevant properties. It's important to&#xA;choose a U value that accurately describes the electronic&#xA;correlations in your system.&lt;/li&gt;&#xA;&lt;li&gt;Hubbard parameter convergence: In addition to the U value, some&#xA;DFT+U methods include a Hubbard parameter (J) to account for the&#xA;exchange interaction. Similar to U, the Hubbard parameter should be&#xA;tested for convergence to ensure the accuracy of your results.&lt;/li&gt;&#xA;&lt;li&gt;Kinetic energy cutoff convergence: The kinetic energy cutoff for&#xA;wavefunctions (ecutwfc) and charge density (ecutrho) should be&#xA;re-evaluated to ensure convergence in the presence of the onsite&#xA;Coulomb interaction. It is possible that different U values may&#xA;require adjustments to these cutoffs for accurate calculations.&lt;/li&gt;&#xA;&lt;li&gt;K-point grid convergence: The convergence of the k-point grid or&#xA;k-mesh should also be rechecked for DFT+U calculations. The&#xA;inclusion of the onsite Coulomb interaction can affect the&#xA;electronic structure, and it's important to ensure that the&#xA;properties of interest converge with respect to the k-point&#xA;sampling.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Regarding your question about increasing the size of the supercell, it is not directly related to the convergence of the DFT+U calculations. However, if you are studying defect calculations such as atomic substitution or vacancy, it can be beneficial to include a convergence test by increasing the size of the supercell. For instance, in relatively large defects such as trefoil-like or rotational defects, one needs to have a relatively large supercell to prevent the interaction between repeated images of the introduced defect. Thus, this test helps identify if the total energy per atom is converging and if the chosen supercell size is sufficient to obtain reliable defect properties.&lt;/p&gt;&#xA;&lt;p&gt;I believe this is a very important question, and I hope we could get some answers from the developers of Electronic Stucture codes.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-11T12:26:57.900" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12055" PostTypeId="2" ParentId="10146" CreationDate="2023-12-11T20:08:17.947" Score="2" Body="&lt;p&gt;I am not sure whether the following are right, but these are what I ended up using:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;F. D. M. Haldane, Model for a Quantum Hall Effect without Landau Levels: Condensed-Matter Realization of the “Parity Anomaly”, Phys. Rev. Lett. 61, 2015 (1988).&lt;/li&gt;&#xA;&lt;li&gt;X. Zhang, W.-Y. Shan, and D. Xiao, Optical Selection Rule of Excitons in Gapped Chiral Fermion Systems, Phys. Rev. Lett. 120, 077401 (2018).&lt;/li&gt;&#xA;&lt;li&gt;X. Zhang, Topological effects in two-dimensional systems, Ph.D. thesis, Carnegie Mellon University, 2019.&lt;/li&gt;&#xA;&lt;li&gt;M. S. Dresselhaus, G. Dresselhaus, and A. Jorio, Group Theory: Application to the Physics of Condensed Matter (Springer Science &amp;amp; Business Media, 2007).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1766" LastEditorUserId="5" LastEditDate="2023-12-11T20:21:39.707" LastActivityDate="2023-12-11T20:21:39.707" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12056" PostTypeId="2" ParentId="11948" CreationDate="2023-12-12T08:50:40.667" Score="3" Body="&lt;p&gt;I have repeated your SCF calculation with SSSP precision pseudopotentials without doing any convergence testing and using the suggested minimum values. The input and the output files are attached at the end. But here are the results: the band gap is found to be 4.5354 eV as expected. The highest occupied and lowest unoccupied level are 3.1546 eV and 7.7535 eV. The DOS also seems to be correct. I arbitrarily set the Fermi energy in the highest occupied level since Fermi energy can be anywhere in the band gap in an insulator. So, your result seems correct to me but I just used a more strict set of parameters. I also use the &lt;code&gt;nbnd&lt;/code&gt; parameter manually and &lt;code&gt;occupations='fixed'&lt;/code&gt; in order to show the band gap in the output file of the SCF run. &lt;a href=&quot;https://i.stack.imgur.com/fIvyQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fIvyQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  outdir = './out/'&#xA;  prefix = 'hBN'&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ecutwfc = 80&#xA;  ecutrho = 440&#xA;  ibrav = 0&#xA;  nat = 4&#xA;  ntyp = 2&#xA;  smearing='gauss'&#xA;  occupations='fixed'&#xA;  degauss=0.01&#xA;  nbnd=16&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.0d-10&#xA;  !startingpot='file'&#xA;  !startingwfc='file'&#xA;/&#xA;ATOMIC_SPECIES&#xA;B     10.0 B_pbe_v1.01.uspp.F.UPF&#xA;N     14.0 N.oncvpsp.upf&#xA;ATOMIC_POSITIONS crystal&#xA;B            0.6666666667       0.3333333333       0.7500000000 &#xA;B            0.3333333333       0.6666666667       0.2500000000 &#xA;N            0.6666666667       0.3333333333       0.2500000000 &#xA;N            0.3333333333       0.6666666667       0.7500000000 &#xA;CELL_PARAMETERS angstrom&#xA;     -1.2562141150      -2.1758266724      -0.0000000000&#xA;     -1.2562141150       2.1758266724       0.0000000000&#xA;      0.0000000000       0.0000000000      -7.7072650000&#xA;K_POINTS automatic&#xA;10 10 10 0 0 0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;NSCF Input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'nscf'&#xA;  outdir = './out/'&#xA;  prefix = 'hBN'&#xA;  pseudo_dir = '.'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ecutwfc = 80&#xA;  ecutrho = 440&#xA;  ibrav = 0&#xA;  nat = 4&#xA;  ntyp = 2&#xA;  smearing='gauss'&#xA;  occupations='tetrahedra'&#xA;  degauss=0.01&#xA;  nbnd=16&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.0d-10&#xA;  !startingpot='file'&#xA;  !startingwfc='file'&#xA;/&#xA;ATOMIC_SPECIES&#xA;B     10.0 B_pbe_v1.01.uspp.F.UPF&#xA;N     14.0 N.oncvpsp.upf&#xA;ATOMIC_POSITIONS crystal&#xA;B            0.6666666667       0.3333333333       0.7500000000 &#xA;B            0.3333333333       0.6666666667       0.2500000000 &#xA;N            0.6666666667       0.3333333333       0.2500000000 &#xA;N            0.3333333333       0.6666666667       0.7500000000 &#xA;CELL_PARAMETERS angstrom&#xA;     -1.2562141150      -2.1758266724      -0.0000000000&#xA;     -1.2562141150       2.1758266724       0.0000000000&#xA;      0.0000000000       0.0000000000      -7.7072650000&#xA;K_POINTS automatic&#xA;20 20 6 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;DOS Input:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;DOS&#xA;  prefix='hBN'&#xA;  outdir='./out/'&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Truncated Output:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     highest occupied, lowest unoccupied level (ev):     3.1546    7.7535&#xA;&#xA;!    total energy              =     -54.87830935 Ry&#xA;     estimated scf accuracy    &amp;lt;          5.8E-12 Ry&#xA;&#xA;     The total energy is the sum of the following terms:&#xA;     one-electron contribution =     -27.98073829 Ry&#xA;     hartree contribution      =      21.53196044 Ry&#xA;     xc contribution           =     -18.59693952 Ry&#xA;     ewald contribution        =     -29.83259198 Ry&#xA;&#xA;     convergence has been achieved in  11 iterations&#xA;&#xA;  PWSCF        :   1m54.99s CPU   2m 1.43s WALL&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Python script to plot the DOS:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np &#xA;import matplotlib.pyplot as plt &#xA;&#xA;for ws in [10]:         # This is the window size &#xA;    data = np.loadtxt('hBN.dos', skiprows=1, dtype='float') &#xA;&#xA;    mov_avg_up = [] &#xA;    arr_up = data[:,1] &#xA;&#xA;    i = 0 &#xA;    while i &amp;lt; len(arr_up)-ws + 1: &#xA;        window = arr_up[i : i + ws] &#xA;        avg = sum(window)/ws &#xA;        mov_avg_up.append(avg) &#xA;        i += 1 &#xA;&#xA;    fig,ax = plt.subplots(figsize=(15,10)) &#xA;&#xA;    plt.xlabel(&amp;quot;Energy (eV)&amp;quot;, fontsize=15) &#xA;    plt.ylabel(&amp;quot;DOS (states/eV)&amp;quot;, fontsize=15) &#xA;    plt.ylim(-.25,4)&#xA;    #plt.xlim(-50,50)&#xA;&#xA;    fermi=3.235&#xA;&#xA;    xval = data[int(ws/2)-1:int(-1*ws/2),0]&#xA;&#xA;    ax.plot(xval-fermi, mov_avg_up, label=&amp;quot;hBN DOS&amp;quot;, linewidth=2, color='green')&#xA;&#xA;    plt.title(&amp;quot;DOS of hBN, PBE (moving average windows size=&amp;quot;+str(ws)+&amp;quot;)&amp;quot;, fontsize=20)&#xA;    &#xA;    plt.fill_between(xval-fermi,0,mov_avg_up,where=(xval &amp;lt;fermi), facecolor='green', alpha=0.1)&#xA;&#xA;    plt.axvline(x=0, linewidth=0.5, color='k', linestyle=(0, (8, 10)))&#xA;    plt.text(0.1, 1.7, 'Fermi energy', rotation=90, fontsize=15)&#xA;&#xA;    ax.legend() &#xA;&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2023-12-13T06:58:20.093" LastActivityDate="2023-12-13T06:58:20.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12057" PostTypeId="1" AcceptedAnswerId="12058" CreationDate="2023-12-12T11:51:50.423" Score="8" ViewCount="369" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Quantum_ESPRESSO&quot; rel=&quot;nofollow noreferrer&quot;&gt;Quantum ESPRESSO&lt;/a&gt; doesn't support pseudopotentials for hybrid functional. Instead they &lt;a href=&quot;https://www.quantum-espresso.org/faq/faq-pseudopotentials/#2.7&quot; rel=&quot;nofollow noreferrer&quot;&gt;suggest&lt;/a&gt; using pseudopotentials for the non-hybrid functional that is closer to the hybrid one, i.e., PBE for PBE0 and HSE, BLYP for B3LYP.&lt;/p&gt;&#xA;&lt;p&gt;I have googled and asked ChatGPT, but it failed to find pseudopotentials with BLYP functional. I found it for &lt;a href=&quot;https://en.wikipedia.org/wiki/Lithium&quot; rel=&quot;nofollow noreferrer&quot;&gt;Li&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Carbon&quot; rel=&quot;nofollow noreferrer&quot;&gt;C&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Nitrogen&quot; rel=&quot;nofollow noreferrer&quot;&gt;N&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Oxygen&quot; rel=&quot;nofollow noreferrer&quot;&gt;O&lt;/a&gt;, and &lt;a href=&quot;https://en.wikipedia.org/wiki/Chlorine&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cl&lt;/a&gt;, but I don't need them. I need BLYP pseudopotentials for transition metals, such as &lt;a href=&quot;https://en.wikipedia.org/wiki/Copper&quot; rel=&quot;nofollow noreferrer&quot;&gt;Cu&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Iron&quot; rel=&quot;nofollow noreferrer&quot;&gt;Fe&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Nickel&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ni&lt;/a&gt;, &lt;a href=&quot;https://en.wikipedia.org/wiki/Cobalt&quot; rel=&quot;nofollow noreferrer&quot;&gt;Co&lt;/a&gt;, etc., and &lt;a href=&quot;https://en.wikipedia.org/wiki/Magnesium&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mg&lt;/a&gt; and &lt;a href=&quot;https://en.wikipedia.org/wiki/Germanium&quot; rel=&quot;nofollow noreferrer&quot;&gt;Ge&lt;/a&gt; too.&lt;/p&gt;&#xA;&lt;p&gt;Just like we have plenty of resources for many type of pseudopotentials, do we have a compilation of pseudopotential with BLYP functionals?&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="1118" LastEditDate="2023-12-13T21:36:53.030" LastActivityDate="2023-12-13T21:36:53.030" Title="Where can I find BLYP pseudopotentials?" Tags="|quantum-espresso|pseudopotentials|exchange-correlation|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12058" PostTypeId="2" ParentId="12057" CreationDate="2023-12-12T12:11:22.077" Score="8" Body="&lt;p&gt;Try searching for BLYP pseudopotentials here - &lt;a href=&quot;http://pseudopotentials.quantum-espresso.org/legacy_tables/hartwigesen-goedecker-hutter-pp&quot; rel=&quot;noreferrer&quot;&gt;http://pseudopotentials.quantum-espresso.org/legacy_tables/hartwigesen-goedecker-hutter-pp&lt;/a&gt;&#xA;. One can generate BLYP and B3LYP pseudopotentials also.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2023-12-12T12:11:22.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12060" PostTypeId="1" AcceptedAnswerId="12064" CreationDate="2023-12-12T13:41:17.137" Score="4" ViewCount="184" Body="&lt;p&gt;Referring to previous questions asked &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12037/s1-t1-energy-difference-in-gaussian&quot;&gt;here&lt;/a&gt;, I would like to pose a more general question about the calculation of ΔE(S1-T1) for organic molecules with the software Gaussian16.&lt;/p&gt;&#xA;&lt;p&gt;In particular, I have seen that the most spread methodology, &lt;a href=&quot;https://chemrxiv.org/engage/chemrxiv/article-details/6376b5a1e70b0adf83a1140b&quot; rel=&quot;nofollow noreferrer&quot;&gt;showed to be better than simple TD-DFT&lt;/a&gt;, is TDA-DFT. Consequently, I have used an input file like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# opt M062X/6-311g* TDA=(singlet,root=1,nstates=6) scrf=(solvent=dichloromethane) Geom=AllCheck int=ultrafine Nosymm &#xA;&#xA;molecule1&#xA;&#xA;0 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;to calculate the state S1, while I used exactly the same (but with the TDA=triplet keyword) to calculate the T1 state. From these, I extract the difference in energy.&lt;/p&gt;&#xA;&lt;p&gt;I understand that this methodology is particularly important when the Franck-Condon approximation can't be used anymore, thus allowing for the optimization of each state.&lt;/p&gt;&#xA;&lt;p&gt;Having said that, is this correct or one should use a different methodology? Keeping in mind that the molecules I want to study are way to big to apply any coupled cluster methodology.&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2023-12-13T02:43:54.443" Title="Methologies to calculate excited states in Gaussian" Tags="|gaussian|td-dft|excited-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12062" PostTypeId="2" ParentId="12050" CreationDate="2023-12-12T16:33:15.540" Score="2" Body="&lt;p&gt;Your unit cell has a lot of atoms outside. Here's the default rendering from Avogadro 1.98, showing the unit cell in white:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Fc9f2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Fc9f2.png&quot; alt=&quot;default positions&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Notice that the center of your tube straddles the lattice vector.&lt;/p&gt;&#xA;&lt;p&gt;Here's what happens if I &amp;quot;wrap&amp;quot; all the atoms into the unit cell using Avogadro 1.98 (i.e., converting to fractional, making sure they fall between 0 and 1, then converting back to Cartesian).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/N4OVQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/N4OVQ.png&quot; alt=&quot;atoms wrapped into unit cell&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The second one looks like the image you have from VESTA. It probably wraps the atoms into the unit cell by default.&lt;/p&gt;&#xA;&lt;p&gt;Your second question is how it will be handled by VASP. While one rendering may be more pleasant to view, the two are equivalent to an electronic structure program. You can note that many atoms are nearly but not exactly equivalent in the &amp;quot;wrapped&amp;quot; view, and thus will probably cause problems with your calculation.&lt;/p&gt;&#xA;&lt;p&gt;You will want to provide a unit cell / lattice with all non-equivalent atoms.&lt;/p&gt;&#xA;&lt;p&gt;My suggestion would be to have your Python script do a final procedure to convert atoms into the wrapped coordinates to check for near-duplicates.&lt;/p&gt;&#xA;" OwnerUserId="30" LastActivityDate="2023-12-12T16:33:15.540" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12063" PostTypeId="1" CreationDate="2023-12-12T22:53:49.497" Score="5" ViewCount="59" Body="&lt;p&gt;I am trying to find a way to calculate &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; dispersion coefficients for some atoms and molecules. In papers and textbooks, this quantity is introduced using the Casimir-Polder integral from the dipole polarizabilities of the interacting particles &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ C_6 = \frac3\pi \int \alpha^A(i \omega) \alpha^B(i \omega) d\omega $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In principle, I am aware that there are some quite sophisticated approaches (TD-DFT, LR-CCSD) that are extended to calculate &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; coefficients directly. What I am interested, however, is to evaluate the integral myself on a quadrature, by calculating the polarizabilities corresponding to specific frequencies.&lt;/p&gt;&#xA;&lt;p&gt;The calculations at real frequencies are implemented in many quantum chemistry codes (see &lt;a href=&quot;https://manual.q-chem.com/5.4/sec_EOMGRAD.html&quot; rel=&quot;noreferrer&quot;&gt;Q-Chem here, for example&lt;/a&gt;) - but I am yet to encounter a code that can handle imaginary frequencies. I also don't see how it could be done in a reasonable way without messing up the Hermiticity of the problem. Therefore, I assume this direct approach is not necessarily the way to go.&lt;/p&gt;&#xA;&lt;p&gt;Is there, then, any reasonable way to obtain an imaginary frequency quadrature to evaluate the &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; coefficients directly?&lt;/p&gt;&#xA;" OwnerUserId="5648" LastActivityDate="2023-12-19T17:57:43.807" Title="How to obtain imaginary frequency polarizability?" Tags="|electronic-structure|dispersion-correction|electric-field|polarizability|response-theory|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12064" PostTypeId="2" ParentId="12060" CreationDate="2023-12-13T02:43:54.443" Score="3" Body="&lt;p&gt;Note, TDA is an approximation of full linear response TD-DFT. While it's possible to compute excited state energies by just running SCF DFT, it generally requires some specialized approach like Delta SCF to converge to higher energy states.&lt;/p&gt;&#xA;&lt;p&gt;Having said all that, your TDA approach will work.&lt;/p&gt;&#xA;&lt;p&gt;There are potentially faster (and potentially less accurate) ways to run it depending on your system if the cost of TDA geopts starts to become prohibitive. As mentioned in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/9357/7&quot;&gt;prior answer&lt;/a&gt;, if you know your ground state is a singlet, you can just run a regular SCF calculation. If you knew the geometry didn't vary much between the various electronic states, you can just optimize the ground state and run a single &lt;code&gt;TDA=(50-50,states=12)&lt;/code&gt; calculation without the geopt to get all the singlet/triplet excited energies from that initial geometry.&lt;/p&gt;&#xA;" OwnerUserId="7" LastActivityDate="2023-12-13T02:43:54.443" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12065" PostTypeId="2" ParentId="11438" CreationDate="2023-12-13T03:16:53.297" Score="3" Body="&lt;p&gt;In case someone else starts wondering on the same phenomenon, what I figured out is as follows.&lt;/p&gt;&#xA;&lt;p&gt;When observing the band structure of the material, it should be noted that only electronic states with energies close to the chemical potential contribute to electrical conductivity. The &amp;quot;filled&amp;quot; states significantly below the chemical potential have practically zero values of the derivative of the Fermi-Dirac distribution entering the integrals and are therefore suppressed (refer to equations 8-12 in ref [1]). If this were not the case, the core states of electrons would hold a contribution to the electron transport. At moderate carrier concentrations, the high group velocity of the bands coupled with the increased amount of charged carriers would result in a higher conductivity. However, as the carrier concentration increases further, the high carrier concentration bands which show a complex nature (entanglement, multiband, non-parabolic band etc.) could result in a lower group velocity. This would therefore reduce the overall electrical conductivity of the material.&lt;/p&gt;&#xA;&lt;p&gt;[1] Georg K. H. Madsen, Jesús Carrete, Matthieu J. Verstraete, BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients, arXiv:1712.07946. &lt;a href=&quot;https://doi.org/10.48550/arXiv.1712.07946&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4232" LastActivityDate="2023-12-13T03:16:53.297" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12067" PostTypeId="1" AcceptedAnswerId="12073" CreationDate="2023-12-13T13:36:24.637" Score="4" ViewCount="145" Body="&lt;p&gt;I tried calculating total energy using SCF calculations after optimization with quantum espresso. Still, I don't know how to optimize total energy in the standard state instead of isolated atoms.&lt;/p&gt;&#xA;&lt;p&gt;If there is a way to isolate atoms? What is the difference between a free atom and an isolated atom?&lt;/p&gt;&#xA;" OwnerUserId="8540" LastEditorUserId="1554" LastEditDate="2023-12-13T14:10:40.867" LastActivityDate="2023-12-14T10:20:51.003" Title="Total energy calculation for an isolated atom" Tags="|density-functional-theory|quantum-espresso|quantum-chemistry|crystallography|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12069" PostTypeId="2" ParentId="12067" CreationDate="2023-12-13T14:16:32.663" Score="2" Body="&lt;p&gt;In quantum mechanical calculations, it is common to study systems in their isolated or standard state, rather than as individual atoms. The isolated or standard state refers to the state of an atom or molecule in an environment where it is not influenced by any external factors, such as other atoms or molecules. This allows for a more accurate representation of the system's behavior in a bulk or condensed phase.&lt;/p&gt;&#xA;&lt;p&gt;In the context of electronic structure calculations like those performed with quantum espresso, the total energy of a system is typically optimized by considering the interactions between atoms in a periodic arrangement, such as in a crystal lattice or a supercell. This approach takes into account the long-range interactions and periodicity of the system, which are important for accurately describing the properties of materials.&lt;/p&gt;&#xA;&lt;p&gt;To study isolated atoms, one can use a supercell with a sufficiently large vacuum region, effectively isolating the atoms from their periodic neighbors. By increasing the size of the supercell and the vacuum region, the interactions between periodic replicas of the system become negligible, and the system can be treated as effectively isolated.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the difference between a free atom and an isolated atom, this lies in the context in which they are considered. A free atom typically refers to an atom completely devoid of any external influence, including other atoms or the surrounding environment, but may still be subject to certain constraints or interactions, such as boundary conditions or periodicity in the case of supercells.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-13T14:16:32.663" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12070" PostTypeId="2" ParentId="11560" CreationDate="2023-12-13T16:57:21.660" Score="2" Body="&lt;p&gt;To determine if any material has &amp;quot;spin, total magnetization, net charge or if they are metallic&amp;quot;, some steps can be done in order to check if they are/or not. &lt;br&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;First it should be safe to perform calculations with nspin = 2. It can also be checked if the orbitals carry unpaired electrons, these types of materials usually tend to have magnetic properties during the calculations. Fermi level after the calculations will show if the material has partially occupied state or not. &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Smearing parameter 'degauss' can be taken with smaller value in any case, specially during initial calculations. Eg degauss = 0.05. This is done when you are taking nspin = 2. Otherwise this value can be determined by testing it like cut off convergence. &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;A system which doesn't have impurities, occupation = 'smearing' is taken.   &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Material with semi conducting nature usually does not require smearing, fixed would work just fine. A good sampling of occupied fermi surface is needed in metals hence smearing is required. The general rule goes like this degauss = 0 then kpoints = infinity in dertermining its value. &lt;br&gt;&#xA;Note - Smearing can be applied to any kind of material, but general sense is that where it would be useful. It is applied to metals (check this page - &lt;a href=&quot;http://theossrv1.epfl.ch/Main/ElectronicTemperature&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://theossrv1.epfl.ch/Main/ElectronicTemperature&lt;/a&gt;) &lt;br&gt;&#xA;To improve convergence it is applied to insulators/semi conductors. Basically to give a tolerance factor in energies and as a spread of energies for electrons to occupy instead of confined to finite energy.&lt;/li&gt;&#xA;&lt;li&gt;The options are&#xA;&lt;br&gt; 'gaussian', 'gauss' : ordinary Gaussian spreading (Default)&#xA;&lt;br&gt;  'methfessel-paxton', 'm-p', 'mp' :Methfessel-Paxton first-order spreading&#xA;&lt;br&gt; 'marzari-vanderbilt', 'cold', 'm-v', 'mv' :Marzari-Vanderbilt-DeVita-Payne cold smearing&#xA;&lt;br&gt; 'fermi-dirac', 'f-d', 'fd' :smearing with Fermi-Dirac function&lt;/li&gt;&#xA;&lt;li&gt;Tot_magnetization - A system with spin is relaxed with nspin = 2. Tot_magnetization is total unbalance in spin up and spin down electrons. Calculations will give a value when it is used for each element. But, magnetization calculations should be done once to check if the material is magnetic or not. Generally it is seen that paired electrons are not magnetic materials, but still with certain elements, like Cu, Fe, magnetic characteristics are seen.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="2077" LastEditDate="2024-01-21T10:18:31.773" LastActivityDate="2024-01-21T10:18:31.773" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12071" PostTypeId="2" ParentId="12042" CreationDate="2023-12-13T17:39:41.753" Score="1" Body="&lt;p&gt;The order of convergence seems to be correct.&lt;br&gt;&#xA;As far as I have seen - In supercell calculations the convergence is not required. Only the K-mesh values are needed to be decreased from the unit cell. One can check for different k-mesh sizes.&lt;br&gt;&#xA;However while introduction of new doping atom one can check minimum cutoff of wavefunction and charge density from the pseudopotentials to see if they are not exceeding the chosen cutoffs.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastActivityDate="2023-12-13T17:39:41.753" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12072" PostTypeId="1" AcceptedAnswerId="12111" CreationDate="2023-12-14T08:23:35.763" Score="6" ViewCount="100" Body="&lt;p&gt;So, I have a system of n number of molecules inside a box which is supposed to be solid. I performed the md simulation of the system using stochastic integrator in a box. I know the lattice of the crystal, and thus the theoretical, and experimental lattice constant.&#xA;Is there anyway to compute the lattice parameter of such system after you run an unbiased simulation for a while, and compute the lattice parameter from the information related to the box? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="1791" LastEditDate="2023-12-15T05:41:08.627" LastActivityDate="2023-12-19T07:59:27.860" Title="Lattice constant of an FCC crystal from molecular dynamics simulation" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12073" PostTypeId="2" ParentId="12067" CreationDate="2023-12-14T10:20:51.003" Score="3" Body="&lt;p&gt;From the tag you used, I assume that you are trying to do the isolated atom calculation in Quantum ESPRESSO. However, I would suggest you doing it with PySCF, NWchem, SIESTA or other code that uses a localized basis set instead of a plane wave basis set code like QE or VASP. I have tried this type of calculation using QE. This requires a very large supercell (i.e., very high vacuum) to remove the spurious image-image interaction and it also requires other corrections. So, QE or plane wave codes are computationally very inefficient in this case and they also require huge memory.&lt;/p&gt;&#xA;&lt;h5&gt;If you have to use QE, then consider the following suggestions:&lt;/h5&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Put the atom at the center and set an initial supercell size of around 10 Angstrom and run a simple SCF calculation. Then increase the supercell size a little bit and check if the energy changes. Try increasing the supercell size until the energy converges within your preferred threshold.&lt;/li&gt;&#xA;&lt;li&gt;Don't forget to use the tag &lt;code&gt;assume_isolated&lt;/code&gt; in the &lt;code&gt;&amp;amp;CONTROL&lt;/code&gt; block. You can use &lt;code&gt;assume_isolated='makov-payne'&lt;/code&gt; or &lt;code&gt;assume_isolated='martyna-tuckerman'&lt;/code&gt;. See &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm582&quot; rel=&quot;nofollow noreferrer&quot;&gt;this documentation&lt;/a&gt; for details.&lt;/li&gt;&#xA;&lt;li&gt;You need a very high k-mesh and high memory. Always a good practice is to check convergence for &lt;code&gt;ecutwfc&lt;/code&gt; and &lt;code&gt;K_POINTS&lt;/code&gt; but if you just want a good starting guess, use &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;QE input generator&lt;/a&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h5&gt;Better alternatives:&lt;/h5&gt;&#xA;&lt;p&gt;Localized basis set can handle this type of isolated atom case very efficiently with much less memory requirements. I used PySCF and it was very fast in my case. There are simple tutorials to run &lt;a href=&quot;https://pyscf.org/user/scf.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SCF&lt;/a&gt; or &lt;a href=&quot;https://pyscf.org/user/dft.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT&lt;/a&gt; calculation using localized basis sets such as GTO. But you are not limited to PySCF. There are other free alternatives such as SIESTA or commercial ones such as Gaussian. A complete list can be found &lt;a href=&quot;https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-12-14T10:20:51.003" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12074" PostTypeId="1" CreationDate="2023-12-14T12:52:40.873" Score="4" ViewCount="112" Body="&lt;p&gt;I'm trying to use the pyscf library for some calculations, specifically the 21-matrix_A_B.py example script for obtaining the A matrix.&#xA;&lt;a href=&quot;https://github.com/tepl/pyscf/blob/master/examples/tddft/21-matrix_A_B.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/tepl/pyscf/blob/master/examples/tddft/21-matrix_A_B.py&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, the output I'm receiving seems to be in a nested format with multiple brackets, which I didn't anticipate for a standard 2-dimensional matrix.&lt;/p&gt;&#xA;&lt;p&gt;Could you kindly provide some clarification regarding the output format of the A matrix from this specific script?&#xA;I expected a 2-dimensional matrix, but the current output is in a nested format that's causing some confusion.&lt;/p&gt;&#xA;&lt;p&gt;Any guidance or advice on how to interpret this output correctly would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="8425" LastActivityDate="2023-12-18T15:36:51.587" Title="Inquiry about A Matrix Output in 21-matrix_A_B.py" Tags="|quantum-chemistry|pyscf|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12075" PostTypeId="1" CreationDate="2023-12-14T14:09:50.430" Score="3" ViewCount="22" Body="&lt;p&gt;I am performing Hirshfeld Atom Refinement (HAR) calculations with XRD data using aspheric atomic scattering factors, which are calculated from wavefunctions optimized in Orca. My crystal structure has substitutional ion disorder, so the Orca calculations involve several possible ion occupancy configurations. I have the resulting .wfn files from Orca for each configuration, and I am able to perform the atomic basin partitioning with these in multiwfn without any problems (using charge density calculated from the wavefunctions). Now I would like to do the same with the calculated electron density map obtained from HAR. I have the crystal structure model available as .pdb and the density map as .cube. There are 242 atoms in the unit cell.  When I read both the pdb and cube files into multiwfn and try the basin analysis (using grid in the memory), the program generates 12k tiny basins. Could you advise what I am doing wrong and how to solve the problem?&lt;/p&gt;&#xA;" OwnerUserId="8547" LastEditorUserId="5" LastEditDate="2023-12-19T15:33:04.217" LastActivityDate="2023-12-19T15:33:04.217" Title="Atomic basin partitioning with electron density grid" Tags="|crystallography|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12076" PostTypeId="1" CreationDate="2023-12-14T15:50:28.190" Score="4" ViewCount="140" Body="&lt;p&gt;I am just learning DFT using the BURAI GUI of Quantum Espresso.I took the CIF file of a structure from the Materials project database.&#xA;It is well vc-relaxed and conversed easily but gives the band gap much less than the published value, however, PPs are already added in CIF.&#xA;Please suggest possible regions&lt;/p&gt;&#xA;" OwnerUserId="8549" LastEditorUserId="5" LastEditDate="2023-12-14T16:28:53.593" LastActivityDate="2023-12-14T17:28:57.027" Title="Band gap do not match to published result in DFT using BURAI GUI of Quantum Espresso" Tags="|quantum-espresso|bandgap|reproducing-data-from-papers|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12077" PostTypeId="2" ParentId="12074" CreationDate="2023-12-14T17:18:27.737" Score="2" Body="&lt;p&gt;From the &lt;a href=&quot;https://github.com/tepl/pyscf/blob/master/pyscf/tdscf/uhf.py#L113&quot; rel=&quot;nofollow noreferrer&quot;&gt;source code&lt;/a&gt; for &lt;code&gt;get_ab&lt;/code&gt; (the link is specifically to the UHF implementation, but the same idea applies for RHF, UKS etc), we can see that it initially stores &lt;code&gt;A&lt;/code&gt; and &lt;code&gt;B&lt;/code&gt; as 4-dimension numpy arrays:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def get_ab(mf, mo_energy=None, mo_coeff=None, mo_occ=None):&#xA;    r'''A and B matrices for TDDFT response function.&#xA;&#xA;    A[i,a,j,b] = \delta_{ab}\delta_{ij}(E_a - E_i) + (ia||bj)&#xA;    B[i,a,j,b] = (ia||jb)&#xA;&#xA;    Spin symmetry is considered in the returned A, B lists.  List A has three&#xA;    items: (A_aaaa, A_aabb, A_bbbb). A_bbaa = A_aabb.transpose(2,3,0,1).&#xA;    B has three items: (B_aaaa, B_aabb, B_bbbb).&#xA;    B_bbaa = B_aabb.transpose(2,3,0,1).&#xA;    '''&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In 21-matrix_A_B.py, it reshapes these 4 dimensional arrays in 2D arrays so that standard matrix procedures, like determining the eigenvalues, can be applied. The matrix form essentially groups the indices so that &lt;span class=&quot;math-container&quot;&gt;$A_{i,a,j,b}$&lt;/span&gt; becomes &lt;span class=&quot;math-container&quot;&gt;$A_{ia,jb}$&lt;/span&gt;, where each row and column represents a particular occupied-virtual pair of orbitals.&lt;/p&gt;&#xA;&lt;p&gt;This &lt;span class=&quot;math-container&quot;&gt;$A_{ia,jb}$&lt;/span&gt; matrix is the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix you are interested in diagonalizing to determine TDA excited states and energies. The PySCF example forms the full TD-DFT block matrix which has the form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{bmatrix}&#xA;A &amp;amp; B \\&#xA;B^* &amp;amp; A^* \\&#xA;\end{bmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;TDA is an approximation of TDDFT where we neglect the off diagonal &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; matrix terms so we only need to diagonalize &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7" LastEditorUserId="7" LastEditDate="2023-12-18T15:36:51.587" LastActivityDate="2023-12-18T15:36:51.587" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12078" PostTypeId="2" ParentId="12076" CreationDate="2023-12-14T17:28:57.027" Score="4" Body="&lt;p&gt;Since you used BURAI, it's safe to assume that you used either an LDA or a GGA functional for your pseudopotentials (PP). In order to confirm, check if you have pz or pbe in the name of your PP.  It is expected that you would get a much smaller band gap, around 40% underestimation from the experimental band gap using these functionals. This is a well-known problem of DFT, the &lt;a href=&quot;https://physics.stackexchange.com/a/360454/192555&quot;&gt;band-gap problem&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In order to improve your band gap, there are several strategies that you can follow. You can use hybrid functionals such as HSE06 or gaupbe. Check out &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/1176/6055&quot;&gt;this&lt;/a&gt; and &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11006/6055&quot;&gt;this&lt;/a&gt; questions to learn more about using QE with hybrid functional. If your system is a d-block metal, you will get a improved band gap using &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide_PDF/Hubbard_input.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT+U&lt;/a&gt;. I believe you need to move from BURAI and start to use Quantum ESPRESSO using command line to implement these strategies since BURAI is a really old GUI and uses a very old QE version. The syntax of that old version changed significantly in the newer version.&lt;/p&gt;&#xA;&lt;p&gt;There are even further approach that you can use such as GW approximation or using &lt;a href=&quot;https://koopmans-functionals.org/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Koopmans functional&lt;/a&gt;. Hybrid functionals tend to overestimate the band gap a little. Using Koopmans functional, it is &lt;a href=&quot;https://koopmans-functionals.org/en/latest/tutorials/tutorial_2.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;claimed&lt;/a&gt; to be found the band gap for Si exactly as the experimental values. Beware that these methods are computationally very inefficient compared to the simple LDA or GGA case. Also, they require huge memory.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-12-14T17:28:57.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12079" PostTypeId="1" CreationDate="2023-12-14T21:39:48.833" Score="2" ViewCount="83" Body="&lt;p&gt;In the paper &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;Norm-Conserving Pseudopotentials (1979)&lt;/a&gt;, they refer to the authors' book for the all-electron(AE) calculation:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;we first carry out an ab initio self-consistent full-core atom calculation via a Herman-Skillman-like program&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the Herman-Skillman method?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Edit:&#xA;I want to use these potentials for a plane-wave calculation on a 2D graphene layer.&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-12-18T17:58:35.103" LastActivityDate="2023-12-18T17:58:35.103" Title="What is the Herman-Skillman method?" Tags="|solid-state-physics|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12080" PostTypeId="1" AcceptedAnswerId="12088" CreationDate="2023-12-14T20:34:18.673" Score="10" ViewCount="96" Body="&lt;p&gt;I'd like to represent and save molecules at a more detailed level than an InChI, such that I can include metastable molecules with electrons at specific excitations (for example, singlet vs triplet states). I understand that a molfile removes some of the ambiguity in SMILES and potentially InChI's, but aside from the specified bonds, the molfile assumes all orbitals are in their lowest unoccupied energy level, right?&lt;/p&gt;&#xA;&lt;p&gt;Is there a well supported format that includes information about energy levels (and bonus points for conformations, too), so that I can cache results from certain long running molecular simulations?&lt;/p&gt;&#xA;" OwnerUserId="8559" OwnerDisplayName="Gert" LastActivityDate="2023-12-16T20:39:16.760" Title="Most detailed molecule representation format" Tags="|computational-chemistry|cheminformatics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12081" PostTypeId="2" ParentId="12079" CreationDate="2023-12-15T06:41:41.720" Score="3" Body="&lt;p&gt;In Herman and Skillman method - numerical methods were performed for self-consistent field calculations based on simplified model of Slater’s version on Hartree-Fock equations for one electron wave function. Where it was suggested to use an average exchange potential which could be approximated by results taken from theory of free electron gas.  The model provides description of electronic structure of free atoms and ions. Calculations were performed using programs written in FORTRAN, such as Hartree Fock Slater self-consistent atomic field program, Relativistic and spin orbit corrections programs etc. &lt;br&gt;&#xA;You can refer to the book &lt;strong&gt;Atomic Structure Calculations Prentice-Hall, Englewood Cliffs, NJ (1963)&lt;/strong&gt;&lt;br&gt;&#xA;&lt;br&gt; Note- I am not a good explainer. Please accept my apologies, but you can refer to the book. Also, I have read somewhere about Herman-Skillman mesh, example like - An energy-minimizing mesh for the Schrödinger equation, (&lt;a href=&quot;https://doi.org/10.1016/0021-9991(89)90124-1&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1016/0021-9991(89)90124-1&lt;/a&gt;)&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="671" LastEditDate="2023-12-15T14:51:01.633" LastActivityDate="2023-12-15T14:51:01.633" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12082" PostTypeId="1" CreationDate="2023-12-15T09:08:28.093" Score="4" ViewCount="82" Body="&lt;p&gt;I want to perform Energy Decomposition Analysis (EDA) between Tannic acid and K+ using VASP, is there a way to perform EDA using VASP?&lt;/p&gt;&#xA;" OwnerUserId="8553" LastEditorUserId="5" LastEditDate="2023-12-19T15:32:22.643" LastActivityDate="2023-12-20T11:32:36.007" Title="Energy Decomposition Analysis with VASP" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12083" PostTypeId="2" ParentId="12030" CreationDate="2023-12-15T09:46:46.670" Score="5" Body="&lt;p&gt;These are not the same quantity. The gradient of the energy with respect to the position &lt;span class=&quot;math-container&quot;&gt;$\vec{R}_i=(x_i,y_i,z_i)$&lt;/span&gt; of atom &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; gives the &lt;em&gt;force&lt;/em&gt;, &lt;span class=&quot;math-container&quot;&gt;$\vec{F}_i$&lt;/span&gt;, acting on that atom,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{F}_i=-\left(\frac{\partial E}{\partial x_i},\frac{\partial E}{\partial y_i},\frac{\partial E}{\partial z_i}\right).&#xA;$$&lt;/span&gt;&#xA;One important thing to note is that the changes in the electronic (Kohn-Sham) density when the atoms move do not contribute to the forces.&lt;/p&gt;&#xA;&lt;p&gt;Since we usually want the forces on &lt;em&gt;all&lt;/em&gt; the atoms, it is convenient to redefine the indices of the position and force vectors to run over all &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; components of the atomic positions; e.g. for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms we have an &amp;quot;all atom&amp;quot; position vector&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{R}=\left(x_1,y_1,z_1,x_2,y_2,z_2,~\ldots~,x_N,y_N,z_N\right).&#xA;$$&lt;/span&gt;&#xA;This allows us to write the &amp;quot;all atom&amp;quot; force vector compactly as,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{F}_i=-\frac{\partial E}{\partial R_i}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In contrast to the forces, the phonons depend on the force-constant matrix, which is essentially the &lt;em&gt;curvature&lt;/em&gt; of the energy, &lt;span class=&quot;math-container&quot;&gt;$\mathrm{K}$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\mathrm{K}_{ij}= \frac{\partial^2 E}{\partial R_i \partial R_j},&#xA;$$&lt;/span&gt;&#xA;remembering that these are &amp;quot;all atom&amp;quot; indices, so there are &lt;span class=&quot;math-container&quot;&gt;$3N$&lt;/span&gt; values of &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; atoms.&lt;/p&gt;&#xA;&lt;p&gt;As well as requiring the first-order change in the Kohn-Sham states, the curvature of the energy is sensitive to the first-order changes in the electronic density when the atoms move, so &lt;span class=&quot;math-container&quot;&gt;$\mathrm{K}$&lt;/span&gt; has to be computed self-consistently.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-12-15T09:46:46.670" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12084" PostTypeId="1" CreationDate="2023-12-15T11:22:20.273" Score="3" ViewCount="26" Body="&lt;p&gt;Is there a general trend such that transition matrix elements for electronic/excitonic transitions are larger/smaller in molecules than in inorganic solids or vice versa?&lt;/p&gt;&#xA;" OwnerUserId="1402" LastActivityDate="2023-12-15T11:22:20.273" Title="Compare transition matrix elements in molecules and solids" Tags="|solid-state-physics|optical-properties|organic-chemistry|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12086" PostTypeId="2" ParentId="12080" CreationDate="2023-12-16T10:03:15.360" Score="2" Body="&lt;p&gt;Like mentioned in the comment, have a look at the &lt;a href=&quot;https://www.xml-cml.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Chemical Markup Language&lt;/a&gt; (CML). &lt;a href=&quot;https://scholia.toolforge.org/topic/Q1069211&quot; rel=&quot;nofollow noreferrer&quot;&gt;This Scholia page&lt;/a&gt; has relevant literature, but particularly check these two publications:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Phadungsukanan, W., Kraft, M., Townsend, J.A. et al. The semantics of Chemical Markup Language (CML) for computational chemistry : CompChem. J Cheminform 4, 15 (2012). &lt;a href=&quot;https://doi.org/10.1186/1758-2946-4-15&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1186/1758-2946-4-15&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;de Jong, W.A., Walker, A.M. &amp;amp; Hanwell, M.D. From data to analysis: linking NWChem and Avogadro with the syntax and semantics of Chemical Markup Language. J Cheminform 5, 25 (2013). &lt;a href=&quot;https://doi.org/10.1186/1758-2946-5-25&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1186/1758-2946-5-25&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="8557" LastActivityDate="2023-12-16T10:03:15.360" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12087" PostTypeId="1" AcceptedAnswerId="12107" CreationDate="2023-12-16T13:18:37.343" Score="5" ViewCount="95" Body="&lt;p&gt;I am using ASE (Atomic Simulation Environment) for theoretical chemistry and I see an option to plot the irreducible Brillouin zone and this bandpath but I can't figure out how. I'm not a programmer.&lt;/p&gt;&#xA;&lt;p&gt;My code is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;&#xA;atoms = read(sys.argv[1])&#xA;&#xA;bandpath = atoms.cell.bandpath()&#xA;print(bandpath)&#xA;print(bandpath.special_points)&#xA;&#xA;bandpath.plot()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The previous lines in the script work fine, it is the last line (with the plot) that doesn't.&lt;/p&gt;&#xA;&lt;p&gt;I opened the ASE.dft.kpoints file and found the function inside of class bandpath, plus it is mentioned in the ASE documentation &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/ase/dft/kpoints.html&quot; rel=&quot;noreferrer&quot;&gt;Brillouin zone sampling&lt;/a&gt; but I can't figure out what are the &lt;code&gt;self&lt;/code&gt; and the &lt;code&gt;**plotkwargs&lt;/code&gt; arguments in the definition (&lt;code&gt;def plot(self, **plotkwargs):&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Is it possible to plot the Brillouin zone with this function and how ? Is there another way to get this kind of plot from ASE ?&lt;/p&gt;&#xA;&lt;p&gt;Best Regards,&#xA;Dobromir&lt;/p&gt;&#xA;" OwnerUserId="8558" LastActivityDate="2023-12-18T17:57:02.550" Title="ASE: How to plot the irreducible Brillouin zone and this bandpath from a bandpath object" Tags="|python|ab-initio-calculations|atomic-simulation-environment|visualization-software|brillouin-zone|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12088" PostTypeId="2" ParentId="12080" CreationDate="2023-12-16T17:54:42.493" Score="4" Body="&lt;p&gt;What you describe is unfortunately, not represented much by common interchange formats.&lt;/p&gt;&#xA;&lt;p&gt;As part of the &lt;a href=&quot;https://two.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Avogadro&lt;/a&gt; project, we've been developing an extensible, community standard schema for &lt;a href=&quot;https://github.com/OpenChemistry/chemicaljson/blob/main/chemicaljson.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;chemicaljson&lt;/a&gt; which does include:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;total molecular charge&lt;/li&gt;&#xA;&lt;li&gt;molecular spin state&lt;/li&gt;&#xA;&lt;li&gt;orbital occupations&lt;/li&gt;&#xA;&lt;li&gt;conformations (3dSets)&lt;/li&gt;&#xA;&lt;li&gt;vibrations&lt;/li&gt;&#xA;&lt;li&gt;calculated spectra&lt;/li&gt;&#xA;&lt;li&gt;metadata / properties&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Please feel free to post questions / issues at the &lt;a href=&quot;https://github.com/openchemistry/chemicaljson&quot; rel=&quot;nofollow noreferrer&quot;&gt;chemicaljson&lt;/a&gt; GitHub, or on the Avogadro forum: &lt;a href=&quot;https://discuss.avogadro.cc/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://discuss.avogadro.cc/&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="30" LastEditorUserId="30" LastEditDate="2023-12-16T20:39:16.760" LastActivityDate="2023-12-16T20:39:16.760" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12089" PostTypeId="2" ParentId="12087" CreationDate="2023-12-16T23:52:54.277" Score="2" Body="&lt;p&gt;Since you have not provided the XYZ file that you are using to get the atoms I will demonstrate how to plot the bandpath using a simple water molecule.&lt;/p&gt;&#xA;&lt;p&gt;Here is a sample code to get the bandpath plot.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import Atoms&#xA;from ase.io import read&#xA;&#xA;def main():&#xA;    # Hardcoded XYZ file content&#xA;    xyz_content = &amp;quot;&amp;quot;&amp;quot;3&#xA;    XYZ file example&#xA;    H  0.0  0.0  0.0&#xA;    O  0.0  0.0  1.0&#xA;    H  0.0  1.0  0.0&#xA;    &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;    # Create a temporary file and write the XYZ content to it&#xA;    with open('temp.xyz', 'w') as f:&#xA;        f.write(xyz_content)&#xA;&#xA;    try:&#xA;        # Use the read function to read the atomic structure from the temporary file&#xA;        atoms = read('temp.xyz')&#xA;&#xA;        # Set periodic boundary conditions and cell vectors explicitly&#xA;        atoms.set_pbc(True)&#xA;        atoms.set_cell([[10.0, 0.0, 0.0],&#xA;                        [0.0, 10.0, 0.0],&#xA;                        [0.0, 0.0, 10.0]])&#xA;&#xA;        # Print some information about the read structure&#xA;        print(&amp;quot;Number of atoms:&amp;quot;, len(atoms))&#xA;        print(&amp;quot;Cell vectors:&amp;quot;)&#xA;        print(atoms.get_cell())&#xA;        print(&amp;quot;Atomic positions:&amp;quot;)&#xA;        print(atoms.get_positions())&#xA;&#xA;        # Calculate and print bandpath information&#xA;        bandpath = atoms.cell.bandpath()&#xA;        print(&amp;quot;Bandpath:&amp;quot;)&#xA;        print(bandpath)&#xA;        print(&amp;quot;Special points:&amp;quot;)&#xA;        print(bandpath.special_points)&#xA;&#xA;        bandpath.plot()&#xA;&#xA;    except Exception as e:&#xA;        print(f&amp;quot;Error: {e}&amp;quot;)&#xA;    finally:&#xA;        # Remove the temporary file&#xA;        import os&#xA;        os.remove('temp.xyz')&#xA;&#xA;if __name__ == &amp;quot;__main__&amp;quot;:&#xA;    main()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This gives the plot:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Mss0b.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Mss0b.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And prints out details like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Number of atoms: 3&#xA;Cell vectors:&#xA;Cell([10.0, 10.0, 10.0])&#xA;Atomic positions:&#xA;[[0. 0. 0.]&#xA; [0. 0. 1.]&#xA; [0. 1. 0.]]&#xA;Bandpath:&#xA;BandPath(path='GXMGRX,MR', cell=[3x3], special_points={GMRX}, kpts=[12x3])&#xA;Special points:&#xA;{'G': array([0., 0., 0.]), 'M': array([0.5, 0.5, 0. ]), 'R': array([0.5, 0.5, 0.5]), 'X': array([0. , 0.5, 0. ])}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So there are a couple of things for you to check:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Check if your input file which you use to build the atoms is valid (Ex. XYZ file)&lt;/li&gt;&#xA;&lt;li&gt;Check if you get any error traceback when you do the plotting and then debug from there.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2023-12-16T23:52:54.277" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12090" PostTypeId="2" ParentId="11725" CreationDate="2023-12-17T00:29:07.413" Score="3" Body="&lt;p&gt;In line with the comments, I'm not sure if you can achieve this in VESTA, but a simple ASE or Pymatgen based script can easily do it. This is the Pymatgen script I use.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Structure&#xA;from pymatgen.transformations.standard_transformations import SupercellTransformation&#xA;from sys import argv&#xA;&#xA;&#xA;assert len(argv) in [2, 4, 10]&#xA;&#xA;struc = Structure.from_file('POSCAR')&#xA;&#xA;if len(argv) == 2:&#xA;    st = SupercellTransformation.from_scaling_factors(argv[1], argv[1], argv[1])&#xA;elif len(argv) == 4:&#xA;    st = SupercellTransformation.from_scaling_factors(argv[1], argv[2], argv[3])&#xA;elif len(argv) == 10:&#xA;    scaling_matrix = [[argv[1], argv[2], argv[3]], [argv[4], argv[5], argv[6]],&#xA;                      [argv[7], argv[8], argv[9]]]&#xA;    st = SupercellTransformation(scaling_matrix)&#xA;&#xA;super_struc = st.apply_transformation(struc)&#xA;super_struc.to('POSCAR_super')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This script assumes that there is a &lt;code&gt;POSCAR&lt;/code&gt; file in the current directory and will make the necessary supercell depending on the command line arguments. For example,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;python script.py 4&lt;/code&gt; will make a &lt;span class=&quot;math-container&quot;&gt;$4 \times 4 \times 4$&lt;/span&gt; supercell&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;python script.py 1 2 3&lt;/code&gt; will make a &lt;span class=&quot;math-container&quot;&gt;$1 \times 2 \times 3$&lt;/span&gt; supercell&lt;/li&gt;&#xA;&lt;li&gt;you can also just type out all 9 entries of the supercell matrix desired&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;This can easily be adapted for other file types, and be made an executable to be called conveniently from any directory (see &lt;a href=&quot;https://stackoverflow.com/questions/27494758/how-do-i-make-a-python-script-executable&quot;&gt;here&lt;/a&gt;).&lt;/p&gt;&#xA;" OwnerUserId="6131" LastActivityDate="2023-12-17T00:29:07.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12091" PostTypeId="1" CreationDate="2023-12-17T09:47:09.767" Score="7" ViewCount="89" Body="&lt;p&gt;I recently found that PySCF supports coupled cluster calculations for periodic systems (link to the documentation: &lt;a href=&quot;https://pyscf.org/user/pbc/mix_mol.html&quot; rel=&quot;noreferrer&quot;&gt;https://pyscf.org/user/pbc/mix_mol.html&lt;/a&gt;).  That seems pretty unique: of course DFT in periodic systems is widely used (VASP, QuantimEspresso etc) but this is probably the first time I’ve seen any post-Harteee Fock method in a periodic system.&lt;/p&gt;&#xA;&lt;p&gt;How does it work? In particular, what happens with the pseudopotentials, and what happens with the k-points?  Are there any papers that describe either the general theory or the PySCF implementation?&lt;/p&gt;&#xA;&lt;p&gt;Does any other software support this?&lt;/p&gt;&#xA;&lt;p&gt;Can periodic CCSD(T)/CBS be considered a gold standard method in periodic systems the same way it is in non-periodic?  (I’m thinking mainly of molecular crystals)&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2023-12-17T09:54:00.813" LastActivityDate="2023-12-17T09:54:00.813" Title="Coupled cluster and periodic systems" Tags="|pyscf|coupled-cluster|periodic-system|periodic-boundary-conditions|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12092" PostTypeId="1" CreationDate="2023-12-17T20:28:10.160" Score="5" ViewCount="54" Body="&lt;p&gt;&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/jp053583d&quot; rel=&quot;nofollow noreferrer&quot;&gt;This paper by Xinchuan Huang &lt;em&gt;et al&lt;/em&gt;.&lt;/a&gt; gives a calculation for the dissociation energy of a water dimer. The electronic dissociation energy (what they call &lt;span class=&quot;math-container&quot;&gt;$D_e$&lt;/span&gt;) is around 21 kJ/mol, and this is combined with the zero-point energy of the dimer and monomers to give a true dissociation energy (&lt;span class=&quot;math-container&quot;&gt;$D_0$&lt;/span&gt;) of 13.5 kJ/mol.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The CCSD(T)-PES and MP2-DMS dissociate correctly (and symmetrically)&#xA;to two H2O monomers, with &lt;span class=&quot;math-container&quot;&gt;$D_e$&lt;/span&gt;) 1665.7 cm-1 (19.93 kJ/mol). Accurate&#xA;quantum calculations of the zero-point energy of the dimer (using&#xA;diffusion Monte Carlo) and the monomers (using a vibrational&#xA;configuration interaction approach) are reported, and these together&#xA;with De give a value of &lt;span class=&quot;math-container&quot;&gt;$D_0$&lt;/span&gt; of 1042 cm-1 (12.44 kJ/mol). A best&#xA;estimated value is 1130 cm-1 (13.5 kJ/mol).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;How does the zero point energy affect the dissociation energy of the dimer? Is it essentially that the zero point energy of the dimer is different from the sum of zero point energies of the monomers, because the vibrations are coupled and/or the force constants are different?&lt;/p&gt;&#xA;&lt;p&gt;The paper gives the zero point energy of the water monomer as 4686.5 cm^-1 and dimer as 10088 cm^-1 (harmonic, based on the PES). Converting these gives 56.1 kJ/mol and 120.7 kJ/mol, so dimer - 2*monomer = 8.5 kJ/mol.  All of these values seem quite large compared to the electronic dissociation energy.  Is the zero point energy really this large?&lt;/p&gt;&#xA;&lt;p&gt;This seems like a huge effect in the case of the water dimer, reducing the dissociation energy by 35%. Back of the envelope, how can we understand such a massive reduction?  If we think of this as a simplified model of two coupled harmonic oscillators, it seems the only way this would work is if the coupling results in a large reduction of the frequency.  But identical coupled harmonic oscillators actually have a symmetric mode which is the same frequency as a single non-coupled oscillator.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="5" LastEditDate="2023-12-19T15:22:38.137" LastActivityDate="2023-12-19T15:22:38.137" Title="How does dimer and monomer zero point energy affect dissociation energy?" Tags="|spectroscopy|vibrations|binding-energy|water|zero-point-energy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12093" PostTypeId="1" AcceptedAnswerId="12102" CreationDate="2023-12-17T20:52:37.560" Score="4" ViewCount="228" Body="&lt;p&gt;After installing xcrysden, I have this output when trying to launch the software:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;+-----------------------------------------------------------------+&#xA;|*****************************************************************|&#xA;|*                                                               *|&#xA;|*  XCrySDen -- (X-Window) CRYstalline Structures and DENsities  *|&#xA;|*               =         ===         =              ===        *|&#xA;|*---------------------------------------------------------------*|&#xA;|*                                                               *|&#xA;|*    Anton Kokalj (tone.kokalj@ijs.si)                          *|&#xA;|*    Jozef Stefan Institute, Ljubljana, Slovenia                *|&#xA;|*                                                               *|&#xA;|*    Copyright (c) 1996--2019 by Anton Kokalj                   *|&#xA;|*                                                               *|&#xA;|*****************************************************************|&#xA;+-----------------------------------------------------------------+&#xA;&#xA;  Version: 1.6.2&#xA;&#xA;  Please report bugs to: tone.kokalj@ijs.si&#xA;&#xA;&#xA;  TERMS OF USE:&#xA;  -------------&#xA;  XCRYSDEN is released under the GNU General Public License.&#xA;&#xA;  Whenever graphics generated by XCRYSDEN are used in scientific&#xA;  publications, it shall be greatly appreciated to include an explicit&#xA;  reference. The preferred form is the following:&#xA;&#xA;  [ref] A. Kokalj, J. Mol. Graph. Model., Vol. 17, pp. 176-179, 1999.&#xA;        Code available from http://www.xcrysden.org/.&#xA;&#xA;XCRYSDEN_TOPDIR=/usr/share/xcrysden&#xA;XCRYSDEN_SCRATCH=/tmp&#xA;&#xA;Running on platform : unix&#xA;   Operating system : Linux&#xA;Package ImageMagick's convert: /usr/bin/convert&#xA;Package ImageMagick's import: /usr/bin/import&#xA;Package Ppmtompeg: /usr/bin/ppmtompeg&#xA;Package Xwd: /usr/bin/xwd&#xA;Executing: /usr/lib/xcrysden/ftnunit&#xA;Error in startup script: &#xA;Couldn't configure togl widget&#xA;    while executing&#xA;&amp;quot;togl .mesa  -width          400  -height         400  -ident          .mesa  -rgba           &lt;span class=&quot;math-container&quot;&gt;$toglOpt(rgba)           -redsize        $&lt;/span&gt;toglOpt(redsize...&amp;quot;&#xA;    (procedure &amp;quot;PlaceGlobWin&amp;quot; line 107)&#xA;    invoked from within&#xA;&amp;quot;PlaceGlobWin 0 [expr round(670 * &lt;span class=&quot;math-container&quot;&gt;$fac1)] [expr round(670 * $&lt;/span&gt;fac1)]&amp;quot;&#xA;    (procedure &amp;quot;ViewMol&amp;quot; line 25)&#xA;    invoked from within&#xA;&amp;quot;ViewMol .&amp;quot;&#xA;    invoked from within&#xA;&amp;quot;if { [llength &lt;span class=&quot;math-container&quot;&gt;$argv] &amp;gt; 2 } {&#xA;parseComLinArg [lrange $&lt;/span&gt;argv 2 end]&#xA;} else {&#xA;    ViewMol .&#xA;}&amp;quot;&#xA;    (file &amp;quot;/usr/share/xcrysden/Tcl/xcInit.tcl&amp;quot; line 633)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The commands I ran was:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;sudo apt install tk libglu1-mesa libtogl2 libfftw3-3 libxmu6 imagemagick openbabel libgfortran5&lt;/li&gt;&#xA;&lt;li&gt;sudo apt install xcrysden&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I have the same problem when installing following the &amp;quot;How to Install the Compiled Package&amp;quot; instructions.&lt;/p&gt;&#xA;&lt;p&gt;My system is :&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Distributor ID: Ubuntu&#xA;Description:    Ubuntu 22.04.3 LTS&#xA;Release:    22.04&#xA;Codename:   jammy&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2023-12-18T09:15:45.293" LastActivityDate="2023-12-18T09:20:18.683" Title="XCrySDen installation" Tags="|visualization-software|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12094" PostTypeId="1" AcceptedAnswerId="12096" CreationDate="2023-12-17T21:02:58.287" Score="4" ViewCount="336" Body="&lt;p&gt;I want to calculate defect formation energy for a substitutionally doped system (bulk) in a charged state. Is it possible to do such calculation using SIESTA code? If yes, what changes do I make in my input fdf file for that?&lt;/p&gt;&#xA;" OwnerUserId="5366" LastActivityDate="2023-12-18T01:15:17.053" Title="Charged defects in siesta" Tags="|density-functional-theory|siesta|defects|doping|charged-dfects|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12095" PostTypeId="2" ParentId="11936" CreationDate="2023-12-18T01:11:12.417" Score="3" Body="&lt;p&gt;No, &lt;span class=&quot;math-container&quot;&gt;$G_{max}$&lt;/span&gt; is a vector in &lt;em&gt;reciprocal space&lt;/em&gt;, so a large &lt;span class=&quot;math-container&quot;&gt;$|G_{max}|$&lt;/span&gt; corresponds to a &lt;em&gt;small&lt;/em&gt; real-space distance. As you increase your cut-off energy, &lt;span class=&quot;math-container&quot;&gt;$E_{cutoff}$&lt;/span&gt;, you are not extending the simulation to larger distances, you are resolving variations of the wavefunction over &lt;em&gt;smaller&lt;/em&gt; distances.&lt;/p&gt;&#xA;&lt;p&gt;The Fourier basis set is infinite in extent, so in some sense it can represent the entirety of the infinite material system, &lt;em&gt;provided&lt;/em&gt; the assumption of perfect periodicity is valid. Bloch's theorem tells us that this is reliable for the particle density and the magnitude of the wavefunction, but not for the phase of the wavefunction -- this is where the phase &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt; enters the discussion. There are solutions for any particular choice of phase, so the most general solution is to integrate over all possible choices of &lt;span class=&quot;math-container&quot;&gt;$\vec{k}$&lt;/span&gt;, which is commonly done by using a regular 3D sampling grid (&amp;quot;Monkhorst-Pack grid&amp;quot;), albeit symmetry-reduced.&lt;/p&gt;&#xA;&lt;p&gt;For a particular rational choice of phase, e.g. in fractional coordinates&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\vec{k} = \left(\frac{p}{q},0,0\right),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; are integers, we can see that the phase does not change in the real-space &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; directions (I am assuming a Cartesian coordinate set for simplicity, but the argument holds in the general case as well). In the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; direction, the phase changes by &lt;span class=&quot;math-container&quot;&gt;$\frac{2\pi p}{q}$&lt;/span&gt; every time we move one unit cell in that direction. After we have moved &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; unit cells, the phase has changed by &lt;span class=&quot;math-container&quot;&gt;$2\pi p$&lt;/span&gt; which means we are back in phase with the original cell (recall that &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; is an integer).&lt;/p&gt;&#xA;&lt;p&gt;Thus, any &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-point component with an integer denominator, &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;, means that the phase is periodic with a periodicity of &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; unit cells in the corresponding real-space direction. In this sense, the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-points control the &amp;quot;size&amp;quot; of the simulated system (in units of the reference cell), since they control the real-space range over which the phase is allowed to vary non-periodically. (This also shows why supercells require fewer k-points for the same accuracy as the reference cell.)&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-12-18T01:11:12.417" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12096" PostTypeId="2" ParentId="12094" CreationDate="2023-12-18T01:15:17.053" Score="4" Body="&lt;p&gt;Yes, it is possible to calculate defect formation energy for a substitutionally doped system in a charged state using the SIESTA code.&lt;/p&gt;&#xA;&lt;p&gt;To calculate the defect formation energy, you need to consider the total energy of the doped system with the defect, as well as the total energies of the pristine host material and the dopant in its isolated form. The defect formation energy can then be calculated using the following equation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E_form = E_defect + n_host * E_host - n_dopant * E_dopant&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Where:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E_form is the defect formation energy.&#xA;E_defect is the total energy of the doped system with the defect.&#xA;n_host is the number of host atoms in the doped system.&#xA;E_host is the total energy of the pristine host material.&#xA;n_dopant is the number of dopant atoms in the doped system.&#xA;E_dopant is the total energy of the dopant in its isolated form.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To perform such calculations in SIESTA, you would need to modify your input fdf file accordingly. Here are the key changes you should consider:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Specify the atomic positions and lattice parameters for the doped&#xA;system, including the defect and the dopant atoms.&lt;/li&gt;&#xA;&lt;li&gt;Set up the appropriate electronic structure calculation parameters,&#xA;such as the basis set, k-point grid, and convergence criteria. These&#xA;settings will depend on the specific system and accuracy&#xA;requirements.&lt;/li&gt;&#xA;&lt;li&gt;Include the appropriate pseudopotentials for the elements involved&#xA;in your system, including the dopant atom and any other relevant&#xA;elements.&lt;/li&gt;&#xA;&lt;li&gt;Set the initial charge state for the dopant atom by specifying the&#xA;occupation or number of electrons. This can be done using the&#xA;OccupationFunction or OccupationNumber keywords in the SystemLabel&#xA;block.&lt;/li&gt;&#xA;&lt;li&gt;Specify the total number of atoms in the doped system (NumberOfAtoms&#xA;keyword) and the number of electrons in the system&#xA;(NumberOfElectrons keyword).&lt;/li&gt;&#xA;&lt;li&gt;Calculate the total energy of the doped system with the defect by&#xA;performing a self-consistent calculation using the SCF block.&lt;/li&gt;&#xA;&lt;li&gt;Perform separate calculations to obtain the total energies of the&#xA;pristine host material and the dopant in its isolated form. These&#xA;calculations should be done with the defect and other dopants&#xA;removed from the system.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Use the obtained total energies to calculate the defect formation energy using the equation mentioned earlier.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-18T01:15:17.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12098" PostTypeId="1" CreationDate="2023-12-18T05:18:51.040" Score="5" ViewCount="53" Body="&lt;p&gt;In the paper &amp;quot;&lt;a href=&quot;https://arxiv.org/abs/2107.00162&quot; rel=&quot;nofollow noreferrer&quot;&gt;Computing molecular excited states on a D‑Wave quantum annealer&lt;/a&gt;&amp;quot;, PySCF is employed to compute the TDA matrix. Then a few of the lowest eigenvalues and eigenvectors of a TDA matrix are computed using the Quantum Annealer Eigensolver (QAE). How can I get the specific &amp;quot;A matrix&amp;quot; mentioned, which appears to be the singular matrix for the TDA computation?&amp;quot; @Nike Dattani&lt;/p&gt;&#xA;" OwnerUserId="8425" LastEditorUserId="5" LastEditDate="2023-12-18T17:46:34.007" LastActivityDate="2023-12-19T01:07:30.230" Title="A matrix form used in the Quantum Annealer Eigensolver (QAE)" Tags="|quantum-chemistry|python|pyscf|excited-states|quantum-computing|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12099" PostTypeId="2" ParentId="11923" CreationDate="2023-12-18T05:28:11.037" Score="2" Body="&lt;p&gt;If you're working with Amber, have a look at some of the tutorials, for example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ambermd.org/tutorials/basic/tutorial4b/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;Simulating a pharmaceutical compound using antechamber and the Generalized Amber Force Field&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://ambermd.org/tutorials/basic/tutorial5/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;Simulating the Green Fluorescent Protein and Building a Modified Amino Acid Residue&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;which should walk you through setting up a simulation with both non-standard amino acids and with arbitrary ligands.&lt;/p&gt;&#xA;&lt;p&gt;In addition to GAFF/GAFF2, you might want to try OpenFF for ligands, using &lt;a href=&quot;https://github.com/openforcefield/openff-toolkit&quot; rel=&quot;nofollow noreferrer&quot;&gt;openff-toolkit&lt;/a&gt; (the parameters are compatible with Amber for the protein).&lt;/p&gt;&#xA;&lt;p&gt;About some of the specific things you ask:&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Are there established practices for fine-tuning AMBER MD parameters&amp;quot; - typically (outside of modified residues) the protein forcefields are used as is, they're not fine-tuned&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;while maintaining computational efficiency&amp;quot; - if not using a polarizable forcefield (rare) or four-site water model (also rare), any set of parameters runs at about the same speed; there isn't an accuracy/efficiency tradeoff , since essentially all the common forcefields (Amber, CHARMM, GAFF, OpenFF, CGenFF) have the same nonbonded functional form, and most of the time is spent on computing nonbonded interactions&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;Has anyone successfully tackled challenges in a similar protein-ligand system?&amp;quot; - of course, it is a huge and active field of research&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2024-01-11T19:38:08.070" LastActivityDate="2024-01-11T19:38:08.070" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12100" PostTypeId="2" ParentId="11701" CreationDate="2023-12-18T05:56:13.477" Score="4" Body="&lt;p&gt;&lt;strong&gt;OpenMM&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Many of the packages you mention are fine pieces of software with a long history, that have been used for many important contributions in the field.  However, I think OpenMM is the preferred choice in most cases today.  Why?&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Experimentation: trying new things is much easier in OpenMM. You can write a custom potential energy function, and within seconds it &amp;quot;just runs&amp;quot; as a highly optimized GPU kernel. There is a nice blog post by the MacCallum lab that describes this here: &lt;a href=&quot;http://www.maccallumlab.org/news/2015/1/23/testing&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.maccallumlab.org/news/2015/1/23/testing&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Speed: OpenMM has excellent GPU support, and is one of the fastest packages out there when running on GPU; it has also gotten much faster in recent versions, eg with very large systems (millions of atoms) or with multiple GPUs.&lt;/li&gt;&#xA;&lt;li&gt;Support/compatibility: OpenMM is used in some very high profile projects including Folding@home, and has a large and helpful user community, and many other projects that integrate with it (eg OpenFF). OpenMM also reads the native formats of the other big software packages including Amber, CHARMM and Gromacs, so you can use any of those to prepare systems and simply use OpenMM to run the simulation.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Nowadays I would use other packages for specific tools they have (eg antechamber) or if there is a particular result I want to reproduce where I have input files from another package; but I tend to try any new things in OpenMM.&lt;/p&gt;&#xA;" OwnerUserId="40" LastActivityDate="2023-12-18T05:56:13.477" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12101" PostTypeId="2" ParentId="11297" CreationDate="2023-12-18T09:03:33.697" Score="0" Body="&lt;p&gt;TranSiesta 4.1.5 defaults to requiring the following 3 quantities to be converged:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;code&gt;dHmax&lt;/code&gt; Hamiltonian convergence&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;dDmax&lt;/code&gt; Density matrix convergence&lt;/li&gt;&#xA;&lt;li&gt;&lt;code&gt;dq&lt;/code&gt; charge convergence&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The last one &lt;code&gt;dq&lt;/code&gt;, can be quite difficult to achieve, and it requires some &amp;quot;feeling&amp;quot; for the system.&#xA;Generally &lt;code&gt;dq&lt;/code&gt; convergence can be achieved by extending the system so that it the scattering region is better screened off.&lt;/p&gt;&#xA;&lt;p&gt;From what you show, we can't see what the actual cause is:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;We don't know what your options are&lt;/li&gt;&#xA;&lt;li&gt;We can't see &lt;code&gt;dq&lt;/code&gt; data&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="887" LastActivityDate="2023-12-18T09:03:33.697" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12102" PostTypeId="2" ParentId="12093" CreationDate="2023-12-18T09:20:18.683" Score="2" Body="&lt;p&gt;By sending an email at the given address, I was recommended to do the following procedure on top on the installation:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;cd&lt;/li&gt;&#xA;&lt;li&gt;mkdir .xcrysden&lt;/li&gt;&#xA;&lt;li&gt;cd .xcrysden&lt;/li&gt;&#xA;&lt;li&gt;cp /usr/share/xcrysden/Tcl/custom-definitions .&lt;/li&gt;&#xA;&lt;li&gt;uncommenting the &amp;quot;#set toglOpt(accum) false&amp;quot; in custom_definitions&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="7151" LastActivityDate="2023-12-18T09:20:18.683" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12104" PostTypeId="1" AcceptedAnswerId="12119" CreationDate="2023-12-18T12:59:12.957" Score="4" ViewCount="118" Body="&lt;p&gt;I calculated the MSD using the gmx msd -f run05.part0005.xtc -s run05.tpr -o msd_200-250ns.xvg. As a result, I got a graph with 2 slopes as attached.&lt;/p&gt;&#xA;&lt;p&gt;In the MD simulation, I followed a simulated annealing schedule for every 25 ns. Since I get the kink at 25 ns, I believe this behavior (two slopes with a kink) is due to the annealing schedule. I want to calculate the diffusion coefficient of water in the system. With this behavior of my MSD graph, I am now confused about how I get the diffusion coefficient of water. I appreciate your help.&lt;/p&gt;&#xA;&lt;p&gt;Thank you.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0s5wR.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0s5wR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8568" LastEditorUserId="5" LastEditDate="2023-12-18T16:50:28.647" LastActivityDate="2023-12-20T07:11:32.093" Title="How do we calculate diffusion coefficient when GROMACS MSD graph with two slopes?" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12105" PostTypeId="1" AcceptedAnswerId="12108" CreationDate="2023-12-18T14:55:41.723" Score="5" ViewCount="48" Body="&lt;p&gt;Let's take the example of a 2D graphene layer. The objective is to do an electronic calculation with only the valence electrons with a plane wave basis. Hence the need to pseudize the core electrons through an all-electron (AE) calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Does the AE calculation contain only one carbon atom in my case?&lt;/strong&gt;&#xA;&lt;strong&gt;Or is it done on a primitive cell with the same basis functions as the valence electron (VE) only calculation?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="5" LastEditDate="2023-12-18T18:19:48.553" LastActivityDate="2023-12-18T18:31:20.970" Title="Generating a pseudopotential for graphene: Is it done on an individual carbon atom, or on an entire unit cell of graphene?" Tags="|molecular-modeling|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12106" PostTypeId="2" ParentId="12098" CreationDate="2023-12-18T17:30:15.027" Score="4" Body="&lt;h1&gt;Introduction&lt;/h1&gt;&#xA;&lt;p&gt;The TDA (Tamm-Dancoff approximation) uses only the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix, which is the upper-left block of the full TD-DFT matrix that was provided &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12077/5&quot;&gt;by Tyberius here&lt;/a&gt;, in his answer to your question about how to interpret the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix output from &lt;a href=&quot;https://github.com/tepl/pyscf/blob/master/examples/tddft/21-matrix_A_B.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;this Python script&lt;/a&gt; as a 2D array. Now it seems that you not only want to interpret the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix as a 2D array, but you also want to &amp;quot;get&amp;quot; the &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;How can I get this specific 'A matrix' mentioned&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I was able to obtain an &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; matrix from exactly that same Python script (called &lt;code&gt;21-matrix_A_B.py&lt;/code&gt; and titled &lt;code&gt;A, B matrices of TDDFT method&lt;/code&gt;) , and I have simplified it further so that you only get the &lt;code&gt;A&lt;/code&gt; and &lt;code&gt;B&lt;/code&gt; matrices (see below).&lt;/p&gt;&#xA;&lt;h1&gt;Import some basic modules&lt;/h1&gt;&#xA;&lt;p&gt;First import some basic modules that tend to be used for TD-DFT calculations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy&#xA;from pyscf import gto, scf, dft, tddft&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Specify the molecule, geometry and basis set&lt;/h1&gt;&#xA;&lt;p&gt;Then &amp;quot;build&amp;quot; an HF (hydrogen fluoride) molecule with a bond length of 0.917 in PySCF's default distance units, and the 6-311G* basis set:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol = gto.Mole()&#xA;mol.atom = [&#xA;    ['H' , (0. , 0. , .917)],&#xA;    ['F' , (0. , 0. , 0.)], ]&#xA;mol.basis = '6311g*'&#xA;mol.build()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Run an SCF calculation&lt;/h1&gt;&#xA;&lt;p&gt;In the above-linked example Python script provided with PySCF, an RHF calculation is done first (but examples using UHF and UKS are provided later, and we can just choose one of them):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mf = scf.RHF(mol).run()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice that I skipped some lines from the example script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def diagonalize(a, b, nroots=5):&#xA;    nocc, nvir = a.shape[:2]&#xA;    a = a.reshape(nocc*nvir,nocc*nvir)&#xA;    b = b.reshape(nocc*nvir,nocc*nvir)&#xA;    e = numpy.linalg.eig(numpy.bmat([[a        , b       ],&#xA;                                     [-b.conj(),-a.conj()]]))[0]&#xA;    lowest_e = numpy.sort(e[e &amp;gt; 0])[:nroots]&#xA;    return lowest_e&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I skipped those lines because we are not actually going to use that &lt;code&gt;diagonalize&lt;/code&gt; function, and in the paper that you mentioned, the function of the &amp;quot;diagonalization&amp;quot; (which in this case is to give us the eigenvalues), is attempted by the D-Wave annealer rather than by PySCF.&lt;/p&gt;&#xA;&lt;h1&gt;Get the A and B matrices&lt;/h1&gt;&#xA;&lt;pre&gt;&lt;code&gt;a, b = tddft.TDHF(mf).get_ab()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Let's also borrow the following lines from the function &lt;code&gt;diagonalize&lt;/code&gt; that we removed, since this will actually reshape the &lt;code&gt;a&lt;/code&gt; array (which is a 4-dimensional array when obtained directly from &lt;code&gt;get_ab()&lt;/code&gt; in the above line of code) into a more familiar 2D matrix:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nocc, nvir = a.shape[:2]&#xA;a = a.reshape(nocc*nvir,nocc*nvir)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;Putting it all together&lt;/h1&gt;&#xA;&lt;p&gt;After entering the command &lt;code&gt;python&lt;/code&gt; or &lt;code&gt;python3&lt;/code&gt; in a terminal, assuming that it is installed with one of those names, and that suitable versions of &lt;code&gt;numpy&lt;/code&gt; and &lt;code&gt;pyscf&lt;/code&gt; are installed properly, you can run the following commands:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy&#xA;from pyscf import gto, scf, dft, tddft&#xA;&#xA;mol = gto.Mole()&#xA;mol.atom = [&#xA;    ['H' , (0. , 0. , .917)],&#xA;    ['F' , (0. , 0. , 0.)], ]&#xA;mol.basis = '6311g*'&#xA;mol.build()&#xA;&#xA;mf = scf.RHF(mol).run()&#xA;a, b = tddft.TDHF(mf).get_ab()&#xA;nocc, nvir = a.shape[:2]&#xA;a = a.reshape(nocc*nvir,nocc*nvir)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then when I enter the command &lt;code&gt;a&lt;/code&gt; in the Python console, I get the following 2D matrix:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;array([[ 2.60456133e+01, -1.43048216e-01,  9.17722977e-17, ...,&#xA;        -1.35695829e-02, -1.44171241e-17, -1.80327561e-17],&#xA;       [-1.43048216e-01,  2.62987754e+01,  5.04602697e-16, ...,&#xA;        -8.91049840e-03, -1.75270105e-17, -1.19651301e-17],&#xA;       [ 9.17722977e-17,  5.04602697e-16,  2.66653809e+01, ...,&#xA;        -2.05590505e-16,  1.36131946e-04, -1.30126224e-02],&#xA;       ...,&#xA;       [-1.35695829e-02, -8.91049840e-03, -2.05590505e-16, ...,&#xA;         6.55286894e+00,  5.26486912e-17,  5.92386345e-17],&#xA;       [-1.44171241e-17, -1.75270105e-17,  1.36131946e-04, ...,&#xA;         5.26486912e-17,  6.56828103e+00, -5.35839140e-04],&#xA;       [-1.80327561e-17, -1.19651301e-17, -1.30126224e-02, ...,&#xA;         5.92386345e-17, -5.35839140e-04,  6.80976592e+01]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Without including the last two lines of the &lt;code&gt;code&lt;/code&gt; in this section, there will be an enormous amount of numbers that are not expressed in a clear way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;array([[[[ 2.60456133e+01, -1.43048216e-01,  2.52247100e-16, ...,&#xA;           1.18048394e-16, -1.02366899e-01, -2.99273826e-03],&#xA;         [ 5.63225509e-03,  8.76294620e-03, -2.72961492e-17, ...,&#xA;          -9.29391367e-18,  1.21119261e-02,  1.50477775e-02],&#xA;         [-5.47818937e-03, -1.00965081e-02,  2.32057657e-17, ...,&#xA;           1.14199267e-17, -1.63499987e-02, -8.27876810e-03],&#xA;         [-1.53313386e-17, -1.21786734e-17, -1.17585782e-02, ...,&#xA;          -1.43825277e-02, -2.26920292e-17, -3.12834270e-17],&#xA;         [ 4.52641078e-17,  2.05773995e-17,  1.63839318e-03, ...,&#xA;           2.65783872e-03,  2.02358655e-17,  7.37224457e-19]],&#xA;&#xA;        [[-1.43048216e-01,  2.62987754e+01,  1.85559485e-16, ...,&#xA;           8.69255890e-18, -1.80038437e-01,  2.76640714e-03],&#xA;         [ 1.06229812e-02,  1.51471459e-02, -3.25023819e-17, ...,&#xA;          -3.42704358e-18,  2.10369804e-02,  9.47115809e-03],&#xA;         [-3.26220325e-03, -1.36594196e-02,  1.34144430e-17, ...,&#xA;           7.48984986e-18, -1.53972648e-02, -9.58464325e-03],&#xA;         [-5.04372963e-18, -2.65822744e-17, -5.55759927e-03, ...,&#xA;          -9.44432054e-03, -2.60031530e-17, -2.52199046e-17],&#xA;         [ 1.91883698e-17,  6.69254025e-17,  7.74373617e-04, ...,&#xA;           1.74527603e-03,  3.11500512e-17,  9.65125128e-19]],&#xA;&#xA;        [[ 2.52247100e-16,  1.85559485e-16,  2.66653809e+01, ...,&#xA;          -4.14258055e-01,  3.88019883e-16, -1.68771690e-16],&#xA;         [-5.49768644e-17, -5.27252681e-17,  4.73023040e-02, ...,&#xA;           4.07441054e-02, -4.20031262e-17,  6.34145865e-17],&#xA;         [-2.36590108e-17, -2.52329213e-17, -1.25044647e-02, ...,&#xA;          -1.01253886e-02, -5.33239060e-17,  6.85749494e-18],&#xA;         [ 3.07973972e-03,  8.05746451e-03, -1.11839463e-16, ...,&#xA;          -9.51809153e-17,  1.59090454e-04, -1.52071873e-02],&#xA;         [-4.29118594e-04, -1.12269482e-03,  1.19373172e-16, ...,&#xA;           7.41740010e-17, -2.21670265e-05,  2.11890856e-03]],&#xA;&#xA;        ...,&#xA;&#xA;        [[ 1.18048394e-16,  8.69255890e-18, -4.14258055e-01, ...,&#xA;           3.13177514e+01, -1.06879611e-16,  4.89758197e-16],&#xA;         [-2.40137843e-17, -1.45581683e-17,  1.01366432e-01, ...,&#xA;           1.08418144e-01,  8.40920174e-18,  1.99334109e-17],&#xA;         [-2.25365451e-17, -3.09943397e-17, -2.68050363e-02, ...,&#xA;          -2.66715970e-02, -5.84272882e-17,  1.20879344e-17],&#xA;         [ 1.85007711e-02,  1.99998116e-02, -6.27379629e-17, ...,&#xA;          -1.46358495e-16,  1.95846665e-04, -3.08303159e-02],&#xA;         [-3.41887510e-03, -3.69589233e-03,  8.57034652e-17, ...,&#xA;           2.29138501e-16, -3.61917502e-05,  5.69733006e-03]],&#xA;&#xA;        [[-1.02366899e-01, -1.80038437e-01,  3.88019883e-16, ...,&#xA;          -1.06879611e-16,  3.14873810e+01, -2.71828309e-03],&#xA;         [ 4.38904519e-02,  6.16691287e-02, -1.01488685e-16, ...,&#xA;           1.80700152e-17,  1.06739839e-01, -4.44639257e-03],&#xA;         [ 4.34057139e-03, -2.36002189e-02,  1.71053614e-18, ...,&#xA;          -6.42770021e-18, -2.76086222e-02, -2.51608621e-02],&#xA;         [-2.83982709e-18, -2.29817728e-17,  2.20942868e-03, ...,&#xA;           3.56382552e-03, -1.08377845e-16, -2.49025578e-17],&#xA;         [ 1.38145177e-17,  3.29116066e-17, -3.07852940e-04, ...,&#xA;          -6.58581972e-04,  2.14013831e-16,  1.62670658e-18]],&#xA;&#xA;        [[-2.99273826e-03,  2.76640714e-03, -1.68771690e-16, ...,&#xA;           4.89758197e-16, -2.71828309e-03,  9.20697384e+01],&#xA;         [ 6.74990646e-03,  5.38580972e-03,  5.11377035e-18, ...,&#xA;           1.39336016e-17,  9.96971178e-03,  6.84327263e-04],&#xA;         [ 6.70688000e-03,  1.26288908e-02, -4.39000556e-17, ...,&#xA;          -7.18892160e-17,  8.88532442e-02,  1.82547204e-03],&#xA;         [-1.55201670e-17, -2.92650713e-18,  2.83491517e-02, ...,&#xA;           1.03861543e-01,  8.12772173e-17,  3.16651901e-16],&#xA;         [-2.27258802e-18, -5.28719242e-18, -3.95005722e-03, ...,&#xA;          -1.91932348e-02, -3.46312768e-17,  4.02013294e-16]]],&#xA;&#xA;&#xA;       [[[ 5.63225509e-03,  1.06229812e-02, -5.49768644e-17, ...,&#xA;          -2.40137843e-17,  4.38904519e-02,  6.74990646e-03],&#xA;         [ 1.43064975e+00, -6.09615429e-02,  1.22200625e-16, ...,&#xA;           5.19826520e-17, -2.87950614e-02, -8.67487755e-03],&#xA;         [-1.35359294e-03,  1.48416197e-02, -8.84029921e-17, ...,&#xA;          -2.54479702e-17,  3.96865233e-02,  3.40996999e-03],&#xA;         [ 6.65558163e-18,  1.34296339e-17,  4.80030137e-02, ...,&#xA;           4.60463491e-02,  4.02892829e-17,  3.66728694e-17],&#xA;         [-4.57741656e-18, -9.69989436e-18, -6.68854761e-03, ...,&#xA;          -8.50919755e-03, -2.57769958e-17,  2.64951838e-18]],&#xA;&#xA;        [[ 8.76294620e-03,  1.51471459e-02, -5.27252681e-17, ...,&#xA;          -1.45581683e-17,  6.16691287e-02,  5.38580972e-03],&#xA;         [-6.09615429e-02,  1.73075386e+00,  3.42004217e-17, ...,&#xA;          -7.37769300e-18, -5.04545009e-02, -3.99341689e-03],&#xA;         [ 1.21996710e-02, -8.32910442e-03, -6.73292146e-17, ...,&#xA;          -1.66368347e-17,  3.35308950e-02,  1.71042301e-03],&#xA;         [ 7.69442487e-18,  2.62887641e-19,  5.29991463e-02, ...,&#xA;           2.85696738e-02,  2.80316603e-17,  2.49191624e-17],&#xA;         [-3.59978088e-18, -9.52942963e-18, -7.38468872e-03, ...,&#xA;          -5.27957162e-03, -2.31599852e-17,  1.32364578e-18]],&#xA;&#xA;        [[-2.72961492e-17, -3.25023819e-17,  4.73023040e-02, ...,&#xA;           1.01366432e-01, -1.01488685e-16,  5.11377035e-18],&#xA;         [ 1.22200625e-16,  3.42004217e-17,  2.25094001e+00, ...,&#xA;          -1.47944383e-01,  1.40541678e-16, -7.95333140e-18],&#xA;         [ 1.21471608e-17,  1.32223282e-17,  1.02704171e-02, ...,&#xA;           1.37344572e-02,  1.17888453e-17,  1.41476791e-17],&#xA;         [-9.07439459e-03,  1.43740515e-02,  2.27439404e-17, ...,&#xA;           4.25652937e-17,  1.36933468e-03, -4.73928990e-03],&#xA;         [ 1.26438979e-03, -2.00282275e-03, -8.68165242e-18, ...,&#xA;          -2.70587404e-17, -1.90797609e-04,  6.60353668e-04]],&#xA;&#xA;        ...,&#xA;&#xA;        [[-9.29391367e-18, -3.42704358e-18,  4.07441054e-02, ...,&#xA;           1.08418144e-01,  1.80700152e-17,  1.39336016e-17],&#xA;         [ 5.19826520e-17, -7.37769300e-18, -1.47944383e-01, ...,&#xA;           7.36556571e+00, -4.39735115e-17,  2.43640327e-16],&#xA;         [-8.04429959e-18, -1.24842003e-18,  1.60052076e-02, ...,&#xA;           4.40198712e-02,  2.43777713e-17, -3.22449155e-17],&#xA;         [ 8.01692312e-03, -9.04851396e-03,  3.77793961e-17, ...,&#xA;           7.52233837e-17,  1.35174553e-03,  2.84855602e-02],&#xA;         [-1.48149818e-03,  1.67213241e-03, -2.16513251e-17, ...,&#xA;          -3.95632533e-17, -2.49797649e-04, -5.26402774e-03]],&#xA;&#xA;        [[ 1.21119261e-02,  2.10369804e-02, -4.20031262e-17, ...,&#xA;           8.40920174e-18,  1.06739839e-01,  9.96971178e-03],&#xA;         [-2.87950614e-02, -5.04545009e-02,  1.40541678e-16, ...,&#xA;          -4.39735115e-17,  7.52836414e+00,  1.36660153e-03],&#xA;         [ 1.79537429e-02,  4.07133045e-02,  1.07757677e-18, ...,&#xA;          -4.92690958e-18,  5.39443678e-02,  2.97677086e-02],&#xA;         [ 1.32749938e-17,  2.60329833e-17,  8.84724119e-03, ...,&#xA;           1.52561546e-02,  5.91020123e-17,  3.25611936e-17],&#xA;         [-3.02944995e-18, -6.65286767e-18, -1.23273914e-03, ...,&#xA;          -2.81928179e-03, -4.17740399e-17, -5.40082544e-18]],&#xA;&#xA;        [[ 1.50477775e-02,  9.47115809e-03,  6.34145865e-17, ...,&#xA;           1.99334109e-17, -4.44639257e-03,  6.84327263e-04],&#xA;         [-8.67487755e-03, -3.99341689e-03, -7.95333140e-18, ...,&#xA;           2.43640327e-16,  1.36660153e-03,  6.91485902e+01],&#xA;         [-9.47212208e-03, -1.84883621e-02,  7.70047505e-17, ...,&#xA;           1.34478914e-17, -3.48847080e-02,  5.40926289e-02],&#xA;         [ 1.12904045e-18, -1.27254220e-17, -4.30316058e-02, ...,&#xA;          -4.53776133e-02, -3.74021590e-17, -5.06419642e-17],&#xA;         [ 3.82585897e-19,  4.14226871e-18,  5.99585156e-03, ...,&#xA;           8.38561761e-03,  1.55155698e-17, -3.41171246e-17]]],&#xA;&#xA;&#xA;       [[[-5.47818937e-03, -3.26220325e-03, -2.36590108e-17, ...,&#xA;          -2.25365451e-17,  4.34057139e-03,  6.70688000e-03],&#xA;         [-1.35359294e-03,  1.21996710e-02,  1.21471608e-17, ...,&#xA;          -8.04429959e-18,  1.79537429e-02, -9.47212208e-03],&#xA;         [ 6.09789250e-01, -1.86455048e-02,  1.39133141e-17, ...,&#xA;           3.35324507e-17,  4.30784404e-03,  3.77835830e-03],&#xA;         [ 6.84680539e-18,  3.32719551e-17,  7.33231010e-02, ...,&#xA;           3.36192439e-02,  3.13760901e-17,  3.21225801e-17],&#xA;         [ 5.34778447e-18, -2.74096172e-18, -1.02165471e-02, ...,&#xA;          -6.21271380e-03, -1.27902235e-17,  4.73676722e-18]],&#xA;&#xA;        [[-1.00965081e-02, -1.36594196e-02, -2.52329213e-17, ...,&#xA;          -3.09943397e-17, -2.36002189e-02,  1.26288908e-02],&#xA;         [ 1.48416197e-02, -8.32910442e-03,  1.32223282e-17, ...,&#xA;          -1.24842003e-18,  4.07133045e-02, -1.84883621e-02],&#xA;         [-1.86455048e-02,  1.01481374e+00, -9.98893495e-17, ...,&#xA;          -3.94572513e-17,  6.09524778e-03,  5.44665749e-03],&#xA;         [ 3.51011460e-17,  5.98611131e-17,  1.03744415e-01, ...,&#xA;           6.09961875e-02,  6.10726210e-17,  5.14665331e-17],&#xA;         [ 6.91639776e-18, -1.03426735e-18, -1.44553312e-02, ...,&#xA;          -1.12718732e-02, -1.55470256e-17,  1.09268624e-17]],&#xA;&#xA;        [[ 2.32057657e-17,  1.34144430e-17, -1.25044647e-02, ...,&#xA;          -2.68050363e-02,  1.71053614e-18, -4.39000556e-17],&#xA;         [-8.84029921e-17, -6.73292146e-17,  1.02704171e-02, ...,&#xA;           1.60052076e-02,  1.07757677e-18,  7.70047505e-17],&#xA;         [ 1.39133141e-17, -9.98893495e-17,  1.41802681e+00, ...,&#xA;          -1.25562022e-01, -8.88889602e-17, -1.02861495e-17],&#xA;         [ 4.45574189e-03, -1.11762802e-04, -3.42445837e-16, ...,&#xA;          -2.38046403e-16,  5.73656461e-03,  9.55766799e-04],&#xA;         [-6.20845224e-04,  1.55725811e-05,  6.67430243e-17, ...,&#xA;           6.27926127e-17, -7.99309931e-04, -1.33172717e-04]],&#xA;&#xA;        ...,&#xA;&#xA;        [[ 1.14199267e-17,  7.48984986e-18, -1.01253886e-02, ...,&#xA;          -2.66715970e-02, -6.42770021e-18, -7.18892160e-17],&#xA;         [-2.54479702e-17, -1.66368347e-17,  1.37344572e-02, ...,&#xA;           4.40198712e-02, -4.92690958e-18,  1.34478914e-17],&#xA;         [ 3.35324507e-17, -3.94572513e-17, -1.25562022e-01, ...,&#xA;           6.59519507e+00, -1.26641103e-16,  2.36026923e-16],&#xA;         [-1.44929563e-03,  2.69522248e-03, -8.13496236e-17, ...,&#xA;          -1.06114358e-16,  3.33108195e-04, -6.58471582e-03],&#xA;         [ 2.67824552e-04, -4.98067295e-04,  3.18508566e-17, ...,&#xA;           7.22678661e-17, -6.15571808e-05,  1.21683149e-03]],&#xA;&#xA;        [[-1.63499987e-02, -1.53972648e-02, -5.33239060e-17, ...,&#xA;          -5.84272882e-17, -2.76086222e-02,  8.88532442e-02],&#xA;         [ 3.96865233e-02,  3.35308950e-02,  1.17888453e-17, ...,&#xA;           2.43777713e-17,  5.39443678e-02, -3.48847080e-02],&#xA;         [ 4.30784404e-03,  6.09524778e-03, -8.88889602e-17, ...,&#xA;          -1.26641103e-16,  6.86839820e+00,  9.62470577e-03],&#xA;         [-1.96578472e-18,  2.88324223e-17,  1.11512001e-01, ...,&#xA;           1.39832846e-01,  1.07534704e-16,  1.12056604e-16],&#xA;         [-5.05176956e-19, -7.31259464e-18, -1.55376354e-02, ...,&#xA;          -2.58406006e-02,  9.49891379e-18, -3.17451065e-18]],&#xA;&#xA;        [[-8.27876810e-03, -9.58464325e-03,  6.85749494e-18, ...,&#xA;           1.20879344e-17, -2.51608621e-02,  1.82547204e-03],&#xA;         [ 3.40996999e-03,  1.71042301e-03,  1.41476791e-17, ...,&#xA;          -3.22449155e-17,  2.97677086e-02,  5.40926289e-02],&#xA;         [ 3.77835830e-03,  5.44665749e-03, -1.02861495e-17, ...,&#xA;           2.36026923e-16,  9.62470577e-03,  6.83443677e+01],&#xA;         [-1.54075432e-18, -7.77028709e-19,  1.15440493e-02, ...,&#xA;           1.23731435e-02,  1.50073155e-17,  3.67158060e-17],&#xA;         [-1.15520124e-18, -2.38172811e-18, -1.60850158e-03, ...,&#xA;          -2.28651184e-03,  3.47233490e-18,  8.34355852e-17]]],&#xA;&#xA;&#xA;       [[[-1.53313386e-17, -5.04372963e-18,  3.07973972e-03, ...,&#xA;           1.85007711e-02, -2.83982709e-18, -1.55201670e-17],&#xA;         [ 6.65558163e-18,  7.69442487e-18, -9.07439459e-03, ...,&#xA;           8.01692312e-03,  1.32749938e-17,  1.12904045e-18],&#xA;         [ 6.84680539e-18,  3.51011460e-17,  4.45574189e-03, ...,&#xA;          -1.44929563e-03, -1.96578472e-18, -1.54075432e-18],&#xA;         [ 4.60301317e-01, -8.14036526e-02,  1.78095753e-16, ...,&#xA;           4.77920265e-17, -2.55815025e-02,  2.91869574e-03],&#xA;         [ 7.69357549e-17,  3.95568941e-17, -9.16038717e-18, ...,&#xA;          -3.68031176e-18,  1.34909040e-17, -1.54482510e-18]],&#xA;&#xA;        [[-1.21786734e-17, -2.65822744e-17,  8.05746451e-03, ...,&#xA;           1.99998116e-02, -2.29817728e-17, -2.92650713e-18],&#xA;         [ 1.34296339e-17,  2.62887641e-19,  1.43740515e-02, ...,&#xA;          -9.04851396e-03,  2.60329833e-17, -1.27254220e-17],&#xA;         [ 3.32719551e-17,  5.98611131e-17, -1.11762802e-04, ...,&#xA;           2.69522248e-03,  2.88324223e-17, -7.77028709e-19],&#xA;         [-8.14036526e-02,  7.71163480e-01,  1.21861621e-16, ...,&#xA;           3.49655673e-17, -5.06584131e-02,  6.40882246e-03],&#xA;         [ 2.85414463e-17,  1.32604673e-16, -7.54993775e-18, ...,&#xA;          -1.71380598e-17,  3.86065675e-17,  5.28608203e-19]],&#xA;&#xA;        [[-1.17585782e-02, -5.55759927e-03, -1.11839463e-16, ...,&#xA;          -6.27379629e-17,  2.20942868e-03,  2.83491517e-02],&#xA;         [ 4.80030137e-02,  5.29991463e-02,  2.27439404e-17, ...,&#xA;           3.77793961e-17,  8.84724119e-03, -4.30316058e-02],&#xA;         [ 7.33231010e-02,  1.03744415e-01, -3.42445837e-16, ...,&#xA;          -8.13496236e-17,  1.11512001e-01,  1.15440493e-02],&#xA;         [ 1.78095753e-16,  1.21861621e-16,  1.47986648e+00, ...,&#xA;          -9.88879943e-04,  2.62220010e-16,  1.27034545e-16],&#xA;         [-1.10886189e-17, -2.68748156e-17, -2.94424850e-02, ...,&#xA;          -2.65470468e-02, -5.64843710e-17,  1.08869356e-17]],&#xA;&#xA;        ...,&#xA;&#xA;        [[-1.43825277e-02, -9.44432054e-03, -9.51809153e-17, ...,&#xA;          -1.46358495e-16,  3.56382552e-03,  1.03861543e-01],&#xA;         [ 4.60463491e-02,  2.85696738e-02,  4.25652937e-17, ...,&#xA;           7.52233837e-17,  1.52561546e-02, -4.53776133e-02],&#xA;         [ 3.36192439e-02,  6.09961875e-02, -2.38046403e-16, ...,&#xA;          -1.06114358e-16,  1.39832846e-01,  1.23731435e-02],&#xA;         [ 4.77920265e-17,  3.49655673e-17, -9.88879943e-04, ...,&#xA;           6.57132771e+00,  9.11115149e-17,  4.00803440e-16],&#xA;         [-4.57024983e-18, -1.95414769e-17, -2.05300777e-02, ...,&#xA;          -3.10520949e-02, -5.30893022e-17,  2.67644214e-19]],&#xA;&#xA;        [[-2.26920292e-17, -2.60031530e-17,  1.59090454e-04, ...,&#xA;           1.95846665e-04, -1.08377845e-16,  8.12772173e-17],&#xA;         [ 4.02892829e-17,  2.80316603e-17,  1.36933468e-03, ...,&#xA;           1.35174553e-03,  5.91020123e-17, -3.74021590e-17],&#xA;         [ 3.13760901e-17,  6.10726210e-17,  5.73656461e-03, ...,&#xA;           3.33108195e-04,  1.07534704e-16,  1.50073155e-17],&#xA;         [-2.55815025e-02, -5.06584131e-02,  2.62220010e-16, ...,&#xA;           9.11115149e-17,  6.56828103e+00, -5.35839140e-04],&#xA;         [ 1.28679373e-17,  4.17923336e-17, -1.71985296e-17, ...,&#xA;          -2.59620518e-17,  2.73187335e-16,  5.15672840e-19]],&#xA;&#xA;        [[-3.12834270e-17, -2.52199046e-17, -1.52071873e-02, ...,&#xA;          -3.08303159e-02, -2.49025578e-17,  3.16651901e-16],&#xA;         [ 3.66728694e-17,  2.49191624e-17, -4.73928990e-03, ...,&#xA;           2.84855602e-02,  3.25611936e-17, -5.06419642e-17],&#xA;         [ 3.21225801e-17,  5.14665331e-17,  9.55766799e-04, ...,&#xA;          -6.58471582e-03,  1.12056604e-16,  3.67158060e-17],&#xA;         [ 2.91869574e-03,  6.40882246e-03,  1.27034545e-16, ...,&#xA;           4.00803440e-16, -5.35839140e-04,  6.80976592e+01],&#xA;         [ 2.51073576e-20, -6.49867240e-18, -1.34571841e-17, ...,&#xA;          -1.27197531e-17, -1.58327480e-18,  3.08637653e-16]]],&#xA;&#xA;&#xA;       [[[ 4.52641078e-17,  1.91883698e-17, -4.29118594e-04, ...,&#xA;          -3.41887510e-03,  1.38145177e-17, -2.27258802e-18],&#xA;         [-4.57741656e-18, -3.59978088e-18,  1.26438979e-03, ...,&#xA;          -1.48149818e-03, -3.02944995e-18,  3.82585897e-19],&#xA;         [ 5.34778447e-18,  6.91639776e-18, -6.20845224e-04, ...,&#xA;           2.67824552e-04, -5.05176956e-19, -1.15520124e-18],&#xA;         [ 1.00578809e-16,  2.58339687e-18, -1.10886189e-17, ...,&#xA;          -4.57024983e-18,  5.20359913e-18,  4.17752327e-18],&#xA;         [ 4.60301317e-01, -8.14036526e-02,  1.37279292e-16, ...,&#xA;           4.15740027e-17, -2.55815025e-02,  2.91869574e-03]],&#xA;&#xA;        [[ 2.05773995e-17,  6.69254025e-17, -1.12269482e-03, ...,&#xA;          -3.69589233e-03,  3.29116066e-17, -5.28719242e-18],&#xA;         [-9.69989436e-18, -9.52942963e-18, -2.00282275e-03, ...,&#xA;           1.67213241e-03, -6.65286767e-18,  4.14226871e-18],&#xA;         [-2.74096172e-18, -1.03426735e-18,  1.55725811e-05, ...,&#xA;          -4.98067295e-04, -7.31259464e-18, -2.38172811e-18],&#xA;         [ 6.23078709e-18,  1.77609190e-16, -2.68748156e-17, ...,&#xA;          -1.95414769e-17,  2.65795987e-17, -7.30736039e-18],&#xA;         [-8.14036526e-02,  7.71163480e-01,  4.81915926e-17, ...,&#xA;          -2.25751979e-17, -5.06584131e-02,  6.40882246e-03]],&#xA;&#xA;        [[ 1.63839318e-03,  7.74373617e-04,  1.19373172e-16, ...,&#xA;           8.57034652e-17, -3.07852940e-04, -3.95005722e-03],&#xA;         [-6.68854761e-03, -7.38468872e-03, -8.68165242e-18, ...,&#xA;          -2.16513251e-17, -1.23273914e-03,  5.99585156e-03],&#xA;         [-1.02165471e-02, -1.44553312e-02,  6.67430243e-17, ...,&#xA;           3.18508566e-17, -1.55376354e-02, -1.60850158e-03],&#xA;         [-9.16038717e-18, -7.54993775e-18, -2.94424850e-02, ...,&#xA;          -2.05300777e-02, -1.71985296e-17, -1.34571841e-17],&#xA;         [ 1.37279292e-16,  4.81915926e-17,  1.27266321e+00, ...,&#xA;          -1.42489553e-01,  1.37493221e-16,  1.07264061e-17]],&#xA;&#xA;        ...,&#xA;&#xA;        [[ 2.65783872e-03,  1.74527603e-03,  7.41740010e-17, ...,&#xA;           2.29138501e-16, -6.58581972e-04, -1.91932348e-02],&#xA;         [-8.50919755e-03, -5.27957162e-03, -2.70587404e-17, ...,&#xA;          -3.95632533e-17, -2.81928179e-03,  8.38561761e-03],&#xA;         [-6.21271380e-03, -1.12718732e-02,  6.27926127e-17, ...,&#xA;           7.22678661e-17, -2.58406006e-02, -2.28651184e-03],&#xA;         [-3.68031176e-18, -1.71380598e-17, -2.65470468e-02, ...,&#xA;          -3.10520949e-02, -2.59620518e-17, -1.27197531e-17],&#xA;         [ 4.15740027e-17, -2.25751979e-17, -1.42489553e-01, ...,&#xA;           6.40903189e+00, -3.51206002e-17,  2.60883987e-16]],&#xA;&#xA;        [[ 2.02358655e-17,  3.11500512e-17, -2.21670265e-05, ...,&#xA;          -3.61917502e-05,  2.14013831e-16, -3.46312768e-17],&#xA;         [-2.57769958e-17, -2.31599852e-17, -1.90797609e-04, ...,&#xA;          -2.49797649e-04, -4.17740399e-17,  1.55155698e-17],&#xA;         [-1.27902235e-17, -1.55470256e-17, -7.99309931e-04, ...,&#xA;          -6.15571808e-05,  9.49891379e-18,  3.47233490e-18],&#xA;         [ 3.94605342e-18,  2.33604087e-17, -5.64843710e-17, ...,&#xA;          -5.30893022e-17,  2.56636736e-16, -2.78181454e-18],&#xA;         [-2.55815025e-02, -5.06584131e-02,  1.37493221e-16, ...,&#xA;          -3.51206002e-17,  6.56828103e+00, -5.35839140e-04]],&#xA;&#xA;        [[ 7.37224457e-19,  9.65125128e-19,  2.11890856e-03, ...,&#xA;           5.69733006e-03,  1.62670658e-18,  4.02013294e-16],&#xA;         [ 2.64951838e-18,  1.32364578e-18,  6.60353668e-04, ...,&#xA;          -5.26402774e-03, -5.40082544e-18, -3.41171246e-17],&#xA;         [ 4.73676722e-18,  1.09268624e-17, -1.33172717e-04, ...,&#xA;           1.21683149e-03, -3.17451065e-18,  8.34355852e-17],&#xA;         [ 2.66720636e-18, -3.05203045e-18,  1.08869356e-17, ...,&#xA;           2.67644214e-19, -1.66373105e-18,  1.97142740e-16],&#xA;         [ 2.91869574e-03,  6.40882246e-03,  1.07264061e-17, ...,&#xA;           2.60883987e-16, -5.35839140e-04,  6.80976592e+01]]]])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h1&gt;If you want only A and not B&lt;/h1&gt;&#xA;&lt;p&gt;Since you're doing the TDA approximation instead of a full TD-DFT calculation, you are probably trying to save RAM or CPU time by not using the &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; matrix, so you might not want to calculate it at all. Hopefully there is a better way to do this, but based on looking at &lt;a href=&quot;https://github.com/tepl/pyscf/blob/master/pyscf/tdscf/uhf.py#L113&quot; rel=&quot;nofollow noreferrer&quot;&gt;the &lt;code&gt;get_ab&lt;/code&gt; function in PySCF's &lt;code&gt;tdscf/uhf.py&lt;/code&gt;&lt;/a&gt;, one way that I can see to avoiding calculating the &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; matrix is to remove or comment all lines leading to the obtaining of the &lt;code&gt;b&lt;/code&gt; output. For I would remove the last line, and all lines related to &lt;code&gt;b_aa&lt;/code&gt;, &lt;code&gt;b_ab&lt;/code&gt;, or &lt;code&gt;b_bb&lt;/code&gt; out of the following lines:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    a_aa = numpy.diag(e_ia_a.ravel()).reshape(nocc_a,nvir_a,nocc_a,nvir_a)&#xA;    a_bb = numpy.diag(e_ia_b.ravel()).reshape(nocc_b,nvir_b,nocc_b,nvir_b)&#xA;    a_ab = numpy.zeros((nocc_a,nvir_a,nocc_b,nvir_b))&#xA;    b_aa = numpy.zeros_like(a_aa)&#xA;    b_ab = numpy.zeros_like(a_ab)&#xA;    b_bb = numpy.zeros_like(a_bb)&#xA;    a = (a_aa, a_ab, a_bb)&#xA;    b = (b_aa, b_ab, b_bb)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T01:07:30.230" LastActivityDate="2023-12-19T01:07:30.230" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12107" PostTypeId="2" ParentId="12087" CreationDate="2023-12-18T17:57:02.550" Score="1" Body="&lt;p&gt;I figured it out by browsing ase.dft.kpoints.py and ase.dft.bz.py&#xA;The &lt;code&gt;plot(...)&lt;/code&gt; function in kpoints.py returns &lt;code&gt;bz.bz_plot(...)&lt;/code&gt; object and &lt;code&gt;def bz_plot(...)&lt;/code&gt; has an argument &lt;code&gt;show&lt;/code&gt; which is False by default and at the end of its definition there is an &lt;code&gt;if show:&lt;/code&gt; statement which invokes &lt;code&gt;plt.show()&lt;/code&gt;, so basically the code is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import sys&#xA;from ase.io import read&#xA;&#xA;atoms = read(sys.argv[1])&#xA;bandpath = atoms.cell.bandpath()&#xA;print(bandpath)&#xA;print(bandpath.special_points)&#xA;bandpath.plot(show=True)&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8558" LastActivityDate="2023-12-18T17:57:02.550" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12108" PostTypeId="2" ParentId="12105" CreationDate="2023-12-18T18:31:20.970" Score="5" Body="&lt;p&gt;Pseudopotentials tend to be provided for &lt;em&gt;&lt;strong&gt;individual elements&lt;/strong&gt;&lt;/em&gt; in the periodic table.&lt;/p&gt;&#xA;&lt;p&gt;For example, if you go to the &lt;a href=&quot;https://pseudopotentiallibrary.org/&quot; rel=&quot;noreferrer&quot;&gt;Pseudopotential library&lt;/a&gt; and click on the element C, you will get access to many files that contain pseudopotential data for the element C. For example, I see &lt;code&gt;C.awfn&lt;/code&gt; in the list of available pseudopotentials and when I click on it, I get &lt;a href=&quot;https://pseudopotentiallibrary.org/recipes/C/CEPP/C.awfn&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; which starts with the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Atomic C  wave function in real space&#xA;Atomic number&#xA;  6&#xA;Total number of orbitals&#xA; 2&#xA;From 1 configurations, orbitals 2S(2)2P(2) [PZ].&#xA;Number of up, downspin electrons&#xA;n/a&#xA;States&#xA;n/a&#xA;Radial grid (a.u.)&#xA; 957&#xA;    0.000000000000000E+00&#xA;    0.167862832095561E-05&#xA;    0.338140915368192E-05&#xA;    0.510869001038132E-05&#xA;    0.686082340334615E-05&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I have not seen pseudopotentials that were built specifically for entire molecules or unit cells, although I don't see why it wouldn't be &lt;em&gt;&lt;strong&gt;possible.&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;The Quantum ESPRESSO website also provides a pseudopotential library &lt;a href=&quot;http://pseudopotentials.quantum-espresso.org/legacy_tables&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and a list of other pseudopotential libraries &lt;a href=&quot;https://www.quantum-espresso.org/other-resources/&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; (which includes &lt;a href=&quot;http://www.pseudo-dojo.org/&quot; rel=&quot;noreferrer&quot;&gt;Pseudo Dojo&lt;/a&gt; which was created by my co-author Michiel van Setten). Most if not all of those resources will provide you with a periodic table from which you can select a periodic table element and get its pseudopotentials (and I haven't seen such a database that provides you with various materials like graphene, graphane, or graphyne, and allows you to download a pseudopotential that is built specifically for one of those materials).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2023-12-18T18:31:20.970" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12110" PostTypeId="2" ParentId="11701" CreationDate="2023-12-18T20:47:34.020" Score="2" Body="&lt;p&gt;Historically, there were the typical programs (CHARMM, GROMOS, AMBER, NAMD) which had their own force fields, with different choices for the parameters in the force fields. Depending on the group where you were working, you would work with one or the other. Nowadays, different programs can use each other's force field much more easily. Gromacs is the prime example, which is probably used more with Amber force fields than with GROMOS ones.&lt;/p&gt;&#xA;&lt;p&gt;The answer to your question then boils down to two separate ones:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;which program to use&lt;/li&gt;&#xA;&lt;li&gt;which force field to use&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Answer1)&#xA;Programs depend much on the hardware you have available (CPU vs GPU), with some programs focused on CPUs, others on GPUs, or on both. I have seen performance of some programs of 1 ns/day on CPUs, vs 30-50ns/day on GPUs (data from years back, probably in 2023 this has improved considerably).&lt;/p&gt;&#xA;&lt;p&gt;Answer2)&#xA;For proteins, probably one of the more recent (ff14sb, ff19sb) Amber force fields (with accompanying GAFF force fields for substrates) is used the most for proteins/enzymes. For DNA/RNA there are other specific Amber force fields developed in Barcelona.&lt;/p&gt;&#xA;" OwnerUserId="998" LastActivityDate="2023-12-18T20:47:34.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12111" PostTypeId="2" ParentId="12072" CreationDate="2023-12-18T22:55:15.313" Score="3" Body="&lt;p&gt;You probably need a barostat which can change the size of the periodic box. Ideally you want an anisotropic barostat so each box vector (and the angles between them) can be adjusted independently.&lt;/p&gt;&#xA;&lt;p&gt;If you know the crystal structure (from xray) as well as the unit cell parameters you can start from that and run a simulation with a barostat to see how the simulated crystal differs from the real one - both in terms of atom positions and the unit cell.  Make the starting periodic box be an exact multiple of the crystal unit cell (ie a supercell).&lt;/p&gt;&#xA;&lt;p&gt;If you don't know the crystal structure, you're basically trying to do crystal structure prediction.  This is usually done by genetic or particle swarm algorithms, not by simulation per se.  It may be helpful to read some of the literature on that, there are many good recent algorithms in that space.  For example:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Oganov AR, editor. Modern methods of crystal structure prediction. John Wiley &amp;amp; Sons; 2011 Aug 4. &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9783527632831&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://onlinelibrary.wiley.com/doi/book/10.1002/9783527632831&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;Oganov AR. Crystal structure prediction: reflections on present status and challenges. Faraday discussions. 2018;211:643-60. &lt;a href=&quot;https://pubs.rsc.org/en/content/articlelanding/2018/fd/c8fd90033g/unauth&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.rsc.org/en/content/articlelanding/2018/fd/c8fd90033g/unauth&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465512001762&quot; rel=&quot;nofollow noreferrer&quot;&gt;CALYPSO&lt;/a&gt; or &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0010465506002931&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt; algorithms&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;If you want to see a phase transition in a simulation (eg liquid-&amp;gt;solid), this is in general pretty hard because those happen more easily by heterogeneous nucleation. You can try to set up a simulation like that with a crystal seed in a liquid (which requires knowing the crystal structure to seed with) and then you should be able to see the seed grow during the simulation.  Homogeneous nucleation is very much slower - both in reality and in simulations, supercooled water for example can exist as a liquid at low temperatures well below freezing for a &lt;em&gt;very&lt;/em&gt; long time, and if sufficiently supercooled can transition to a glass instead of a crystal.  Homogeneous nucleation can sometimes happen on a timescale of 10-100ns at very high pressures and temperatures, but cooling at normal pressure in simulations generally just gives you a supercooled liquid.&lt;/p&gt;&#xA;" OwnerUserId="40" LastEditorUserId="40" LastEditDate="2023-12-19T07:59:27.860" LastActivityDate="2023-12-19T07:59:27.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12112" PostTypeId="2" ParentId="12063" CreationDate="2023-12-19T17:46:14.743" Score="3" Body="&lt;p&gt;I dedicate this answer to &lt;a href=&quot;https://en.wikipedia.org/wiki/Robert_J._LeRoy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Bob Le Roy&lt;/a&gt; and &lt;a href=&quot;https://pubs.aip.org/physicstoday/online/10455/Jim-Mitroy&quot; rel=&quot;nofollow noreferrer&quot;&gt;Jim Mitroy&lt;/a&gt; who passed away in August 2018 and August 2014 respectively. I was thinking about them a lot while writing this answer.&lt;/p&gt;&#xA;&lt;h2&gt;Dynamic dipole polarizabilities at imaginary frequencies&lt;/h2&gt;&#xA;&lt;p&gt;The dynamic dipole polarizability &lt;span class=&quot;math-container&quot;&gt;$\alpha_{\textrm{dipole},m}(\omega)$&lt;/span&gt; of a system in state &lt;span class=&quot;math-container&quot;&gt;$\psi_m$&lt;/span&gt; with total angular momentum &lt;span class=&quot;math-container&quot;&gt;$J_m$&lt;/span&gt; and energy &lt;span class=&quot;math-container&quot;&gt;$E_m$&lt;/span&gt;  can be calculated using the following &amp;quot;sum over states&amp;quot; (in atomic units and with &lt;span class=&quot;math-container&quot;&gt;$\hbar=1$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{\textrm{dipole},m} (\omega) = \frac{2}{3(2J_m+1)}\sum _n \frac{\Delta E | \langle \psi_m ||D|| \psi_n \rangle |^2}{(\Delta E)^2 - \omega^2}\tag{1},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$\Delta E = E_n - E_m$&lt;/span&gt; for each state &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is the reduced electric-dipole operator:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;D \equiv r \mathbf{C}^1(\hat{\mathbf{r}}),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and &lt;span class=&quot;math-container&quot;&gt;$\mathbf{C}^1(\hat{\mathbf{r}})$&lt;/span&gt; is the spherical tensor of rank 1.  I &lt;em&gt;mostly&lt;/em&gt; used the notation from &lt;a href=&quot;https://arxiv.org/abs/1004.3567&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; popular, recent and thorough review paper by Jim Mitroy, Mariana Safronova and Charles Clark (you can follow Eqs. 10, 11 and 13 with the ground state &lt;span class=&quot;math-container&quot;&gt;$g$&lt;/span&gt; replaced by me with an arbitrary state &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt;; then look at Eq. 22).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;If you want to do this yourself, you need the energies &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt; and wavefunctions &lt;span class=&quot;math-container&quot;&gt;$\psi_n$&lt;/span&gt; of your system (as many as you can obtain: the more you obtain, the more accurate your calculation).&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If the input of the function in Eq. 1 is &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\omega$&lt;/span&gt;, then we get the following (the RHS is no longer a &amp;quot;function&amp;quot; of &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\omega$&lt;/span&gt; because &lt;span class=&quot;math-container&quot;&gt;$\textrm{i}\omega$&lt;/span&gt; was already inserted):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\alpha_{\textrm{dipole},m} (\textrm{i}\omega) = \frac{2}{3(2J_m+1)}\sum _n \frac{\Delta E | \langle \psi_m ||D|| \psi_n \rangle |^2}{(\Delta E)^2 + \omega^2}\tag{3},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;which is exactly what we have in Eq. 76 of the aforementioned review paper.&lt;/p&gt;&#xA;&lt;h2&gt;Dynamic multi-pole polarizabilities at imaginary frequencies&lt;/h2&gt;&#xA;&lt;p&gt;We can obtain &lt;span class=&quot;math-container&quot;&gt;$C_8$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$C_{10}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$C_{12}$&lt;/span&gt;, etc. as follows (based on Eqs. 3-5 of &lt;a href=&quot;https://link.springer.com/article/10.1134/S1063776106020014&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; which I found by searching &amp;quot;dynamic&amp;quot; in the title's of Prosev's papers on Google Scholar, and I was looking at Porsev's Google Scholar page because I didn't find &amp;quot;dynamic&amp;quot; on Marianna Safronova's first page of papers listed in descending citation count on Google Scholar, so I would have checked Derevianko or Porsev next but Porsev showed up as her #1 collaborator):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;C^{\textrm{AB}}_{2n} = \frac{(2n-2)!}{2\pi}\sum_{l=1}^{n-2}\frac{1}{(2l)!(2l^\prime)!}\int_0^\infty \alpha_l^\textrm{A}(\textrm{i}\omega)\alpha^\textrm{B}_{l^\prime}(\textrm{i}\omega)\textrm{d}\omega,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$l^\prime = n - l - 1$&lt;/span&gt; for a &lt;span class=&quot;math-container&quot;&gt;$2^l$&lt;/span&gt;-pole polarizability, and &lt;span class=&quot;math-container&quot;&gt;$n=3,4,5,6,\cdots$&lt;/span&gt;, and:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ \tag{5}&#xA;\alpha_{l}(\textrm{i}\omega) = 2\Re \sum_n \frac{|\langle \psi_0 |T_0^{(l)}|   \psi_n \rangle|^2}{E_n-E_0 + \textrm{i}\omega},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;and the &lt;span class=&quot;math-container&quot;&gt;$T_0^{(l)}$&lt;/span&gt; operators are the zero components of electric &lt;span class=&quot;math-container&quot;&gt;$2^l$&lt;/span&gt;-pole operator tensors for a system with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; electrons:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;T_i^(l) = \sum_{j=1}^N = r_j^l C_i^{(l)} (\hat{\mathbf{r}}_j),&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$C_m^{l)}$&lt;/span&gt; are the normalized spherical functions (the notation is slightly different from my above section on &lt;em&gt;&lt;strong&gt;dipole&lt;/strong&gt;&lt;/em&gt; polarizabilities because I was basing that part on the review paper by Mitroy &lt;em&gt;et al.&lt;/em&gt; and this part on the paper by Porsev and Derevianko).&lt;/p&gt;&#xA;&lt;h2&gt;Casimir-Polder integral&lt;/h2&gt;&#xA;&lt;p&gt;I removed the part in your question in which you refered to your Eq. 1 as the Casimir-Polder integral, because that formula is quite different from what I see in the &lt;a href=&quot;https://journals.aps.org/pr/abstract/10.1103/PhysRev.73.360&quot; rel=&quot;nofollow noreferrer&quot;&gt;1948 paper by Casimir and Polder&lt;/a&gt;. Eq. 1 of &lt;a href=&quot;https://arxiv.org/abs/physics/9904050v1&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper by James Babb&lt;/a&gt; is referred to as the Casimir-Polder integral in that paper and much more closely resembles what is in the 1948 paper, and also resembles Eq. 1 of &lt;a href=&quot;https://journals.aps.org/pra/abstract/10.1103/PhysRevA.63.054101&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;. Your Eq. 1 might be indirectly called the Casimir-Polder integral&amp;quot; by the OP of the CFOUR mailing list thread that I will mention below, but the aforementioned &lt;em&gt;research papers&lt;/em&gt; by experts in the field do not call it that. Your Eq. 1 is called the &amp;quot;Casimir-Polder formula&amp;quot; in &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jctc.6b00361&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; which uses TDDFT to calculate dynamica polarizabilities at imaginary frequencies, but it's not clear what software they used, so I will discuss software implementations in the seciton below.&lt;/p&gt;&#xA;&lt;h2&gt;Software implementations&lt;/h2&gt;&#xA;&lt;p&gt;On 18 September of this year, on the CFOUR mailing list, a thread with the title &amp;quot;Dynamic polarizability function at imaginary frequencies&amp;quot; was initated, which asked whether or not CFOUR can do this type of calculation. John Stanton replied with the following input file for real-valued frequencies:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CH+ FREQUENCY-DEPENDENT POLARIZABILITIES USING CCLR&#xA;C&#xA;H 1 R&#xA;&#xA;R=1.13092025572&#xA;&#xA;*CFOUR(CALC=CCSD,REF=RHF,CHARGE=1,PROP=DYNAMICAL&#xA;LINEQ_CONV=10&#xA;CC_CONV=10,SCF_CONV=10,DIFFTYPE=UNRELAXED,SPHERICAL=OFF)&#xA;&#xA;C:OLSEN&#xA;H:OLSEN&#xA;&#xA;%frequency&#xA;1&#xA;0.1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and Stephen Coy provided another example of a dynamic polarizability calculation at a real-valued frequency (which also for some reason shows an automatic two-step augmentation of the basis functions):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CCSD/t-aug-cc-pVTZ calculation of pby at 694.3 nm for HF&#xA;F&#xA;H 1 R&#xA;&#xA;R=1.7328&#xA;&#xA;*ACES2(CALC=CCSD&#xA;UNITS=BOHR&#xA;MEMORY=50000000,BASIS=SPECIAL&#xA;PROP=DYN_POL,DIFF_TYPE=UNRELAXED&#xA;LINEQ_EXPAN=25&#xA;SCF_CON=9,CC_CONV=11,CONV=6,LINEQ_CONV=10)&#xA;&#xA;F:T-AUG-PVTZ&#xA;H:T-AUG-PVTZ&#xA;&#xA;%frequency&#xA;1&#xA;.06562473178260349867&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but Stephan Sauer pointed out that these do not do the calculation at imaginary frequencies (if you can navigate the CFOUR code you can probably add imaginary frequency calculations as a new feature though) and that Dalton can do the calculation. The OP replied by saying:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;My molecule is an open-shell radical, so either Dalton (coupled cluster part) or Molpro implementations do not work (as far as I know).&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.molpro.net/manual/doku.php?id=excited_states_with_equation-of-motion_ccsd_eom-ccsd#first-_and_second-order_properties_for_ccsd_from_expectation-value_cc_theory_xccsd&quot; rel=&quot;nofollow noreferrer&quot;&gt;This is where the MOLPRO manual discusses dyanmic polarizabilities with frequencies that have a non-zero imaginary part&lt;/a&gt; but that page does only mention &amp;quot;closed-shell&amp;quot; and not &amp;quot;open-shell&amp;quot;. The following MOLPRO forum threads seem to discuss calculations of polarizabilities for closed shell systems: &lt;a href=&quot;https://www.molpro.net/pipermail/molpro-user/2012-September/005045.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; is for H2O, &lt;a href=&quot;https://www.molpro.net/pipermail/molpro-user/2011-January/004101.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; is for H2O, &lt;a href=&quot;https://www.molpro.net/pipermail/molpro-user/2013-June/005440.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one&lt;/a&gt; is for N2-N2. &lt;a href=&quot;https://www.molpro.net/pipermail/molpro-user/2016-April/006676.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;This one&lt;/a&gt; asks:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;I would like to obtain polarizability for open-shell systems but first I am testing the finite field approach with DIP and QUAD field and comparing the results obtained with &amp;quot;polarizability&amp;quot; command&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;but seems to have not received any response.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T17:57:43.807" LastActivityDate="2023-12-19T17:57:43.807" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12113" PostTypeId="5" CreationDate="2023-12-19T19:50:44.517" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://www.ill.eu/sites/fullprof/php/programsd87c.html?pagina=WinPlotr&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.ill.eu/sites/fullprof/php/programsd87c.html?pagina=WinPlotr&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T19:50:44.517" LastActivityDate="2023-12-19T19:50:44.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12114" PostTypeId="4" CreationDate="2023-12-19T19:50:44.517" Score="0" Body="Questions about WinPLOTR for plotting powder diffraction patterns." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T19:50:44.517" LastActivityDate="2023-12-19T19:50:44.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12115" PostTypeId="5" CreationDate="2023-12-19T20:11:02.257" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Crystallographic_Information_File&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Crystallographic_Information_File&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T20:11:02.257" LastActivityDate="2023-12-19T20:11:02.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12116" PostTypeId="4" CreationDate="2023-12-19T20:11:02.257" Score="0" Body="For questions about the use of Crystallographic Information File – file format used in structural sciences." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2023-12-19T20:11:02.257" LastActivityDate="2023-12-19T20:11:02.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12117" PostTypeId="2" ParentId="11649" CreationDate="2023-12-20T01:50:48.517" Score="3" Body="&lt;p&gt;As mentioned in the first comment, you need to check the symmetries and spacegroups. You can refer to the following sample code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core import Structure&#xA;from pymatgen.symmetry.analyzer import SpacegroupAnalyzer&#xA;from pymatgen.io.cif import CifParser&#xA;&#xA;# Specify the path to your CIF file&#xA;cif_file = &amp;quot;path/to/your/file.cif&amp;quot;&#xA;&#xA;# Create a CifParser object&#xA;parser = CifParser(cif_file)&#xA;&#xA;# Parse the structures with the new method and set primitive=True explicitly&#xA;structures = parser.parse_structures(primitive=True)&#xA;&#xA;# Access the first structure&#xA;structure = structures[0]&#xA;&#xA;# Create a SpacegroupAnalyzer object for the crystal structure&#xA;analyzer = SpacegroupAnalyzer(structure)&#xA;&#xA;# Get the spacegroup number and symbol&#xA;spacegroup_number = analyzer.get_space_group_number()&#xA;spacegroup_symbol = analyzer.get_space_group_symbol()&#xA;&#xA;# Print the spacegroup information&#xA;print(&amp;quot;Spacegroup Number:&amp;quot;, spacegroup_number)&#xA;print(&amp;quot;Spacegroup Symbol:&amp;quot;, spacegroup_symbol)&#xA;&#xA;# Check if the property of interest is isotropic based on crystal symmetries&#xA;is_isotropic = analyzer.is_laue()  # Returns True if the crystal is isotropic&#xA;&#xA;# Print the result&#xA;if is_isotropic:&#xA;    print(&amp;quot;The property of interest is isotropic.&amp;quot;)&#xA;else:&#xA;    print(&amp;quot;The property of interest is anisotropic.&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-20T01:50:48.517" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12118" PostTypeId="2" ParentId="11869" CreationDate="2023-12-20T06:06:23.223" Score="2" Body="&lt;p&gt;Perhaps only the first of the following is actually relevant to your question, but the second part gives some explanation on why the steps make sense in that order.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Is the &lt;code&gt;GGA = PE&lt;/code&gt; INCAR flag necessary for a PBE calculation to be performed?&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Like the comment said - looking at the default of &lt;code&gt;GGA&lt;/code&gt; on the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/GGA&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP Wiki&lt;/a&gt;, it says&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Default: GGA = exchange-correlation functional in accordance with the POTCAR file&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So if you use PBE POTCARs, VASP should default to PBE. Though, it might be useful to just leave the &lt;code&gt;GGA = PE&lt;/code&gt; if you ever need to recall what you've done in the future.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Explanation of the order of steps&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;HSE06 (a hybrid functional) is a lot more expensive than PBE but can give better bandgaps (PBE often underestimates the gap). PBE generally gives good structures. With this in mind,&lt;/p&gt;&#xA;&lt;p&gt;Step (I) : It makes sense to first relax the geometry with PBE (which is a lot cheaper than HSE06).&lt;/p&gt;&#xA;&lt;p&gt;Step (II): While it is possible that a PBE converged WAVECAR has already been generated at the end of the geometry relaxation, it is likely to be a bad starting point for the HSE06 calculation as the basis used for the relaxation (and output WAVECAR) corresponds to the unrelaxed initial structure of the geometry optimization, which could be very different from the basis of the relaxed structure if the cell vectors have changed significantly. Hence, it is advisable to redo a static PBE SCF before using the converged PBE orbitals for the HSE06 calculation (make sure to set &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LWAVE&quot; rel=&quot;nofollow noreferrer&quot;&gt;LWAVE&lt;/a&gt; to true to get the WAVECAR). [edited to reflect E.I. Joe's comments]&lt;/p&gt;&#xA;&lt;p&gt;The reason for getting a PBE converged WAVECAR as a starting point for the HSE06 SCF is that convergence for the HSE06 run should be faster and more stable from PBE converged orbitals. Of course, it is possible to do the HSE06 calculation from scratch, but it would likely take much longer and more prone to convergence issues than starting with PBE converged orbitals.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="6131" LastEditDate="2023-12-20T22:04:24.877" LastActivityDate="2023-12-20T22:04:24.877" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12119" PostTypeId="2" ParentId="12104" CreationDate="2023-12-20T07:11:32.093" Score="7" Body="&lt;p&gt;In order to calculate the diffusion coefficient from the MSD plot, you can use this equation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  MSD(t) = 6Dt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;where &lt;code&gt;MSD(t)&lt;/code&gt; is the mean square displacement at time &lt;code&gt;t&lt;/code&gt;, &lt;code&gt;D&lt;/code&gt; is the diffusion coefficient,and &lt;code&gt;t&lt;/code&gt; is time.&lt;/p&gt;&#xA;&lt;p&gt;In the case where you have a simple system with constant diffusion, the MSD should be a straight line, and the slope of the line can be used to determine the diffusion coefficient. In your case, seems that you have a system with changes in dynamics, such as the simulated annealing schedule you mentioned, and the MSD plot is showing multiple slopes. In this case, you can calculate the diffusion coefficient for different time intervals separately, where the dynamics appear to be relatively constant. You can do that by fitting a straight line to each segment and determine the slope for that interval ( you can use linear regression to fit straight lines to these stable segments. Tools such as GROMACS or Python with libraries such as NumPy and Matplotlib can be used for this purpose). Then diffusion coefficient can be calculated for each segment. Afterwards, as you have multiple segments, you may want to average the diffusion coefficients obtained from different segments to get an overall estimate.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-20T07:11:32.093" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12120" PostTypeId="1" CreationDate="2023-12-20T09:24:42.473" Score="7" ViewCount="70" Body="&lt;p&gt;I am trying to do a simple groundstate calculation with the &lt;a href=&quot;http://exciting.wikidot.com/&quot; rel=&quot;nofollow noreferrer&quot;&gt;exciting&lt;/a&gt; code for a perovskite structure with &lt;em&gt;4d&lt;/em&gt;-electron elements. The code uses a muffin-tin approach and expands the wavefunctions inside the muffin tins by augmented plane waves + local orbitals by default.&lt;br /&gt;&#xA;When running the calculations, above a certain cutoff energy I get the error message:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Error(genlofr): degenerate local-orbital radial functions&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Looking into the source code, it seems like the linear algebra routine &lt;code&gt;zgesv.f&lt;/code&gt; from LAPACK fails because some factor is singular. I struggle however to understand which parameter in the input I should change to avoid such a problem. Any hint is much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;EDIT:&lt;/p&gt;&#xA;&lt;p&gt;The input is a simple ground state calculations with the parameters:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;lt;groundstate&#xA;  do=&amp;quot;fromfile&amp;quot;&#xA;  xctype=&amp;quot;GGA_PBE&amp;quot;&#xA;  rgkmax=&amp;quot;8&amp;quot;&#xA;  gmaxvr=&amp;quot;15&amp;quot;&#xA;  ngridk=&amp;quot;4 4 4&amp;quot;&#xA;  swidth=&amp;quot;1d-6&amp;quot;&#xA;  epsengy=&amp;quot;1d-6&amp;quot;&#xA;  maxscl=&amp;quot;40&amp;quot;&amp;gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;   &#xA;&lt;p&gt;The problematic atoms are Sr and Rh with the pre-compiled species files.&lt;/p&gt;&#xA;&lt;p&gt;EDIT 2:&lt;/p&gt;&#xA;&lt;p&gt;After further searches for the root cause, I found a workaround where instead of using a combined local orbital + LAPW basis, I just use LAPW instead. While the code doesn't stop now, the energies become pathological for higher cutoffs. Searching the web, I found that people have similar problems with another all-electron code, ELK (&lt;a href=&quot;https://sourceforge.net/p/elk/discussion/897820/thread/0ef1319d/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here and links therein&lt;/a&gt; and &lt;a href=&quot;http://exciting.wikidot.com/forum/t-615909/convergence-in-rgkmax-difficulties&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;). It is suggested that high &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;-components of the interstitial effective potential cause instability. Does this warrant a second question or help this one?&lt;/p&gt;&#xA;" OwnerUserId="8328" LastEditorUserId="8328" LastEditDate="2024-01-12T08:40:29.107" LastActivityDate="2024-01-12T08:40:29.107" Title="Degenerate local-orbital radial functions" Tags="|density-functional-theory|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12121" PostTypeId="1" CreationDate="2023-12-20T10:48:21.713" Score="6" ViewCount="77" Body="&lt;p&gt;I was working with nudged elastic band (NEB) to model some reactions, and someone asked what would happen if there are multiple pathways between the reactant and product (minima on the PES). This led me to wonder, if there are possibly reactions where there can be multiple transition states (or multiple pathways) between the same two minima on the PES, and I could not think of an example.&lt;/p&gt;&#xA;&lt;p&gt;This is different than bifurcating reactions (or VRI), where one TS connects to three minima. I am also not looking for the trivial case of a conformational rearrangement of the reactant and product, which then gives a conformer of the TS.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there any non-trivial examples of such reactions where there are multiple pathways between the reactant and product (or two minima on the same PES)&lt;/strong&gt;, with &lt;strong&gt;multiple TSs&lt;/strong&gt; connecting the two minima? (I am looking mainly for cases which have been computationally modelled)&lt;/p&gt;&#xA;" OwnerUserId="1380" LastEditorUserId="1380" LastEditDate="2023-12-20T16:43:50.417" LastActivityDate="2023-12-21T18:49:04.483" Title="Example of single reaction with multiple transition states" Tags="|reference-request|transition-state|reaction-mechanism|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12122" PostTypeId="2" ParentId="12082" CreationDate="2023-12-20T11:32:36.007" Score="2" Body="&lt;p&gt;To my knowledge, VASP does not provide &lt;code&gt;built-in&lt;/code&gt; tools specifically designed for energy decomposition analysis.&lt;/p&gt;&#xA;&lt;p&gt;You need to do some post-processing. Take a look at this &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.8b00957&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acs.jctc.8b00957&lt;/a&gt; where the authors used VASP along with CP2K to do EDA for the interaction between gas molecules and metal surface. Moreover, if you are not restricted to using VASP, you may check &lt;a href=&quot;https://doi.org/10.26434/chemrxiv-2023-n79rz&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.26434/chemrxiv-2023-n79rz&lt;/a&gt; where EDA is based on dispersion-corrected DFT. It is a shell script implemented to calculations done with Gaussian quantum chemistry program and Multiwfn wavefunction analysis code. Other option is &lt;a href=&quot;https://psicode.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;PSi4&lt;/a&gt; which is an open-source quantum chemistry software package that provides various methods for EDA calculations&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-20T11:32:36.007" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12123" PostTypeId="1" CreationDate="2023-12-20T14:19:46.500" Score="4" ViewCount="21" Body="&lt;p&gt;I need the excited state (T1) wavefunction associated with my benzene molecule, but even after trying multiple times using multiple input formats, I am not able to find the correct input to evaluate it using the Dalton Package. I'm attaching the .mol and .dal files I used below for reference.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;BASIS&#xA;6-311++G**&#xA;Benzene using the 6-311++G** Basis set&#xA;Using automatic symmetry detection.&#xA;Atomtypes=2 Angstrom&#xA;Charge=6.0 Atoms=6&#xA;C       -1.396328944      0.000000000      0.000000000&#xA;C       -0.698164472     -1.209256337      0.000000000  &#xA;C       -0.698164472      1.209256337      0.000000000&#xA;C        0.698164472     -1.209256337      0.000000000&#xA;C        0.698164472      1.209256337      0.000000000&#xA;C        1.396328944      0.000000000      0.000000000   &#xA;Charge=1.0 Atoms=6&#xA;H       -1.241338149     -2.150060743      0.000000000&#xA;H       -1.241338149      2.150060743      0.000000000 &#xA;H        1.241338149     -2.150060743      0.000000000&#xA;H        1.241338149      2.150060743      0.000000000&#xA;H        2.482676297      0.000000000      0.000000000&#xA;H       -2.482676297      0.000000000      0.000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the .dal file I'm using is,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**DALTON INPUT&#xA;.RUN WAVEFUNCTIONS&#xA;**WAVE FUNCTIONS&#xA;.HF&#xA;*SCF INPUT&#xA;.THRESH&#xA;1.0D-8&#xA;*LUCITA&#xA;.TITLE&#xA;Benzene molecule ground state + first excited state in A1&#xA;.SYMMET&#xA; 1&#xA;.MULTIP &#xA; 2&#xA;.NROOTS&#xA; 2&#xA;**END OF DALTON INPUT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8519" LastEditorUserId="5" LastEditDate="2023-12-20T14:28:10.017" LastActivityDate="2023-12-20T14:28:10.017" Title="How to evaluate excited state MO coefficients using Dalton Pacakge?" Tags="|computational-chemistry|quantum-chemistry|orbitals|excited-states|dalton|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12124" PostTypeId="2" ParentId="11494" CreationDate="2023-12-20T20:31:49.257" Score="1" Body="&lt;p&gt;For bulk interface you need to freeze both atoms at the bottom and those at the top. For a slab model all the top layers are relaxed. @Salvios answer was correct but it was added as a comment and not an answer.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-12-20T20:31:49.257" CommentCount="0" CommunityOwnedDate="2024-01-11T14:34:29.887" ContentLicense="CC BY-SA 4.0" />
  <row Id="12125" PostTypeId="2" ParentId="11205" CreationDate="2023-12-21T09:48:50.813" Score="2" Body="&lt;p&gt;Generally speaking, one would expect that the band edges should vary linearly with applied strain, especially for small strains. This linear relationship is often observed in many materials and nanostructures, as you mentioned in your question. However, there are cases where the band edges deviate from linearity. Take a look at those examples &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.91.085423&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.91.085423&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/acs.jpcc.7b12408&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/acs.jpcc.7b12408&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;There are several reasons that could lead to this non-linear variation of band edges with strain and here I will mention some of them:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Anisotropy: as you have mentioned in your comment, anisotropy can lead to non-linear variations in the band edges, where materials with anisotropic properties could show different behavior based on the&#xA;direction of the applied strain.&lt;/li&gt;&#xA;&lt;li&gt;electron-electron interaction: for some materials with complex electronic structure, such as high electron-electron interactions, it is possible that the relationship between band edges and strain may not be linear.&lt;/li&gt;&#xA;&lt;li&gt;Piezoelectric contribution, the coupling between strain and polarization, can contribute to non-linear variations in the band edges&lt;/li&gt;&#xA;&lt;li&gt;Large strain: as mentioned in the comments non-linear strain regime&#xA;is expected at higher values of strain where the material reaches&#xA;the elastic limit or  for instance undergoing geometrical changes.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-21T09:48:50.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12126" PostTypeId="1" CreationDate="2023-12-21T10:04:49.350" Score="3" ViewCount="38" Body="&lt;p&gt;The D3 dispersion correction has 2 distance cutoff values. One for the calculation of coordination numbers, one for the energy contribution.&#xA;In other implementations, such as vasp and DFTB+ (tblite), the coordination number cutoff is set to around 20 Angstrom by default.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.vasp.at/wiki/index.php/DFT-D3&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/DFT-D3&lt;/a&gt;&#xA;&lt;a href=&quot;https://dftbplus.org/documentation&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://dftbplus.org/documentation&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, in CP2K I am not able to find a way to set this parameter. The only thing that comes close is EPS_CN. The description reads:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Cutoff value for coordination number function (DFT-D3 method)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;which I find hard to interpret given a default value of 1e-6.&#xA;Neither Bohr nor angstrom make sense as units for this value.&#xA;Is it perhaps the threshold under which a neighboring atom does not contribute to the CN anymore?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/XC/VDW_POTENTIAL/PAIR_POTENTIAL.html#CP2K_INPUT.FORCE_EVAL.DFT.XC.VDW_POTENTIAL.PAIR_POTENTIAL.EPS_CN&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/XC/VDW_POTENTIAL/PAIR_POTENTIAL.html#CP2K_INPUT.FORCE_EVAL.DFT.XC.VDW_POTENTIAL.PAIR_POTENTIAL.EPS_CN&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am asking because I have tried out a few D3 implementations and they are all in agreement except the one in CP2K.&#xA;It is unclear to me whether I am actually using the same parameters as in these other versions, since I am not able to find the keywords.&lt;/p&gt;&#xA;" OwnerUserId="406" LastEditorUserId="406" LastEditDate="2023-12-21T10:41:49.450" LastActivityDate="2023-12-21T10:41:49.450" Title="Set coordination number cutoff in CP2K's D3 dispersion" Tags="|cp2k|dispersion-correction|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12127" PostTypeId="2" ParentId="12049" CreationDate="2023-12-21T10:52:12.033" Score="5" Body="&lt;p&gt;(1) When you write &lt;code&gt;Geom=AllCheck&lt;/code&gt;, the Title Card, charge and spin multiplicity would not be read by Gaussian, i.e.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molecule1&#xA;&#xA;0 2&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;would not be read. So is the case in your triplet calculation. They would be read from the .chk file specified by &lt;code&gt;%chk=xxx.chk&lt;/code&gt;. It means that you are performing the same calculations repeatedly, so the obtained SCF energies are, of course, identical.&lt;/p&gt;&#xA;&lt;p&gt;(2) If you want to read geometry meanwhile use a new spin multiplicity, you should write &lt;code&gt;geom=check&lt;/code&gt;, and write the Title Card, charge and spin multiplicity below the Route section.&lt;/p&gt;&#xA;&lt;p&gt;(3) Assuming the ground state of your molecule is singlet and you want to optimize the S1 state, you should use TDDFT, e.g.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt TD M062X/6-311g* scrf(solvent=dichloromethane) guess=read Geom=AllCheck int=ultrafine Nosymm&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the lowest triplet T1, it is recommended to use UDFT to get what you want&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt UM062X/6-311g* scrf(solvent=dichloromethane) Geom=Check int=ultrafine Nosymm&#xA;&#xA;molecule1&#xA;&#xA;0 3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can also use TDDFT to calculate the T1 state, but it takes more computational cost and its energy would not be identical to UDFT's result (but very similar geometries could be expected)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt TD(triplet) M062X/6-311g* scrf(solvent=dichloromethane) guess=read Geom=AllCheck int=ultrafine Nosymm&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;By the way, if you are using Gaussian 16, &lt;code&gt;int=ultrafine&lt;/code&gt; is not needed since this is the default.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2023-12-21T10:52:12.033" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12128" PostTypeId="1" CreationDate="2023-12-21T13:59:26.703" Score="3" ViewCount="50" Body="&lt;p&gt;In his book &lt;a href=&quot;https://press.princeton.edu/books/hardcover/9780691140162/condensed-matter-in-a-nutshell&quot; rel=&quot;nofollow noreferrer&quot;&gt;Condensed Matter in a Nutshell&lt;/a&gt;, the late &lt;a href=&quot;https://en.wikipedia.org/wiki/Gerald_Mahan&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gerald D. Mahan&lt;/a&gt; wrote that &lt;em&gt;The calculation of a crystal's superconducting properties is not yet possible (p. 5).&lt;/em&gt; The book was published in 2010.&lt;/p&gt;&#xA;&lt;p&gt;However, in 2013, Margine and Giustino published a paper titled &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.024505&quot; rel=&quot;nofollow noreferrer&quot;&gt;Anisotropic Migdal-Eliashberg theory using Wannier functions&lt;/a&gt; where they provided a way to calculate superconducting properties such as superconducting gap and critical temperature. Also, in 2023, there was a &lt;a href=&quot;https://epw2023.dryfta.com/index.php&quot; rel=&quot;nofollow noreferrer&quot;&gt;virtual school on many-body calculations using EPW and BerkleyGW&lt;/a&gt; where they had session on calculating superconducting properties. Moreover, google search reveals many such papers on calculating critical temperature using first-principle such as &lt;a href=&quot;https://arxiv.org/abs/1601.03486&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one (2016)&lt;/a&gt; or &lt;a href=&quot;https://doi.org/10.3390/met12020337&quot; rel=&quot;nofollow noreferrer&quot;&gt;this one with Roeser–Huber Formalism (2022)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Then, in light of these new developments, can we say Mahan's comment is obsolete and nowadays we can indeed study superconductors using first-principle?&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-12-21T13:59:26.703" Title="Can we calculate superconducting properties of materials using first-principle?" Tags="|condensed-matter|superconductivity|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12129" PostTypeId="1" CreationDate="2023-12-21T17:16:41.447" Score="4" ViewCount="145" Body="&lt;p&gt;I am relatively new to VASP, and have been running a calculation with EDIFF = 1E-6, EDIFFG = -2E-2 (along with other INCAR settings). Some of the output is displayed below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;RMM:  60    -0.135836456109E+04   -0.15343E-03   -0.19255E-06  6759   0.687E-04    0.307E-03&#xA;RMM:  61    -0.135836464271E+04   -0.81625E-04   -0.10130E-06  6365   0.567E-04    0.209E-03&#xA;RMM:  62    -0.135836467403E+04   -0.31324E-04   -0.45355E-07  5815   0.432E-04    0.117E-03&#xA;RMM:  63    -0.135836469735E+04   -0.23318E-04   -0.42250E-07  5905   0.431E-04    0.996E-04&#xA;RMM:  64    -0.135836470743E+04   -0.10073E-04   -0.25642E-07  4379   0.344E-04    0.611E-04&#xA;RMM:  65    -0.135836471869E+04   -0.11263E-04   -0.24250E-07  4995   0.347E-04    0.533E-04&#xA;RMM:  66    -0.135836472806E+04   -0.93740E-05   -0.19322E-07  4646   0.324E-04    0.411E-04&#xA;RMM:  67    -0.135836473515E+04   -0.70842E-05   -0.12732E-07  4099   0.283E-04    0.551E-04&#xA;RMM:  68    -0.135836474052E+04   -0.53744E-05   -0.11116E-07  4087   0.276E-04    0.192E-04&#xA;RMM:  69    -0.135836474277E+04   -0.22460E-05   -0.40006E-08  2844   0.224E-04    0.937E-05&#xA;RMM:  70    -0.135836474462E+04   -0.18564E-05   -0.42948E-08  3112   0.241E-04    0.547E-05&#xA;RMM:  71    -0.135836474521E+04   -0.58510E-06   -0.13002E-08  2612   0.221E-04&#xA;   1 F= -.13883068E+04 E0= -.13882554E+04  d E =-.138831E+04&#xA; BRION: g(F)=  0.255E+01 g(S)=  0.000E+00&#xA; bond charge predicted&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1    -0.135669227260E+04    0.16725E+01   -0.26057E+02 13032   0.125E+01    0.473E+00&#xA;RMM:   2    -0.135723141009E+04   -0.53914E+00   -0.73892E+00 11853   0.187E+00    0.265E+00&#xA;RMM:   3    -0.135717390645E+04    0.57504E-01   -0.32633E-01 13321   0.391E-01    0.187E+00&#xA;RMM:   4    -0.135715075602E+04    0.23150E-01   -0.14709E-01 11877   0.241E-01    0.389E-01&#xA;RMM:   5    -0.135715910870E+04   -0.83527E-02   -0.87242E-03 12247   0.664E-02    0.108E+00&#xA;RMM:   6    -0.135715149509E+04    0.76136E-02   -0.23175E-03 12892   0.255E-02    0.316E-01&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;It seems like for N=71, |dE| &amp;lt; |EDIFF|, and it indeed does seem to interrupt the output with giving the total free energy. However, after this the calculation starts again at N=1 and just keeps going before eventually timing out. Why is this? Should the calculation not have stopped after it was converged? I have NSW = 100 in this calculation as well. Could it be that VASP is simply trying to reach 100 steps before the time limit is reached?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="8554" LastActivityDate="2023-12-21T17:16:41.447" Title="How to tell when a VASP calculation has truly converged?" Tags="|density-functional-theory|vasp|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12130" PostTypeId="2" ParentId="12121" CreationDate="2023-12-21T18:49:04.483" Score="5" Body="&lt;p&gt;Perhaps the simplest example is the transition between cis and trans diazene, N2H2. Both are planar structures, with the two hydrogens either on the same or opposite sides of the central N=N. There are two different TSs connecting these two minima, one corresponding to a rotation around the N=N with C2 symmetry, and another corresponding to an inversion of one of the nitrogen with Cs symmetry.&#xA;For large flexible systems, there will be many TSs corresponding to different conformations of the reactant and product, and thus different conformational TSs, but that is perhaps not what you are looking for? For enzymatic reactions, there will be a large number of TSs corresponding to different configurations of the combined substrate and enzyme.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2023-12-21T18:49:04.483" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12131" PostTypeId="1" CreationDate="2023-12-22T08:44:35.180" Score="4" ViewCount="121" Body="&lt;p&gt;When discussing properties studied using first-principles methods like density functional theory (DFT), I often come across the terms &amp;quot;calculated&amp;quot; and &amp;quot;computed&amp;quot; to describe the obtained results. While both terms seem to be used interchangeably, I wonder if there is a subtle difference in their connotations.&lt;/p&gt;&#xA;&lt;p&gt;Could someone shed light on the nuances between &amp;quot;calculated&amp;quot; and &amp;quot;computed&amp;quot; when discussing properties obtained through first-principles approaches? Is there a preferred term or any specific context where one is more appropriate than the other?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-24T02:05:05.640" Title="Terminology: &quot;Calculated&quot; vs &quot;Computed&quot; for Properties Studied with First-Principles" Tags="|ab-initio-calculations|" AnswerCount="3" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12132" PostTypeId="1" CreationDate="2023-12-22T11:04:35.420" Score="4" ViewCount="177" Body="&lt;p&gt;I've constructed a low density standard MD simulation (in Python), using the Lennard-Jones potential with an Andersen thermostat, of 10 particles in a box V = 10 &lt;span class=&quot;math-container&quot;&gt;$\times$&lt;/span&gt; 10 &lt;span class=&quot;math-container&quot;&gt;$ \times$&lt;/span&gt; 10 in the NVT ensemble. I'm looking to calculate the Helmholtz free energy (up to an additive constant) as a function of temperature over the phase transition from the particles clumping together in a small droplet through the melting of this cluster, i.e. &lt;span class=&quot;math-container&quot;&gt;$\Delta A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I know sampling in a situation like this is hard because of the large barriers involved, hence I'll do parallell tempering to sample effectively. However, the issue is I'm unsure of how to &lt;em&gt;actually&lt;/em&gt; calculate the free energy. My method as it stands currently is to use what I've found as temperature integration:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;  \frac{\Delta A}{\Delta T} = \frac{A(T_b)}{T_b} - \frac{A(T_a)}{T_a} = \int_{1/T_a}^{1/T_b} \langle H \rangle \ d(1/T),&#xA;\end{equation}&lt;/span&gt;&#xA;by &lt;span class=&quot;math-container&quot;&gt;$A = -k_b T \ln(Q)$&lt;/span&gt;, where Q is the partition function and then: &lt;span class=&quot;math-container&quot;&gt;$\frac{\partial A}{\partial (1/T)} = \langle H \rangle$&lt;/span&gt;. Based on this, what I'll do is sample &lt;span class=&quot;math-container&quot;&gt;$\langle H \rangle$&lt;/span&gt;, i.e. the average energy from the parallell tempering over a range of temperatures containing the transition and then integrate.&lt;/p&gt;&#xA;&lt;p&gt;Is this a reasonable approach or am I missing something?&lt;/p&gt;&#xA;&lt;p&gt;I found in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1539/are-there-any-md-packages-that-do-proper-free-energy-sampling-in-the-npt-ensembl&quot;&gt;another question asked&lt;/a&gt;, that the &lt;span class=&quot;math-container&quot;&gt;$\Delta A $&lt;/span&gt; could be found by sampling the potential energy &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; instead (as is done in GROMACS) per: &lt;span class=&quot;math-container&quot;&gt;$\Delta A = -k_b T \ln( \langle e^{- \beta \Delta U} \rangle)$&lt;/span&gt; and this does seem reasonable, but how do I then construct the &lt;span class=&quot;math-container&quot;&gt;$\Delta A$&lt;/span&gt; for the intermediate values so that I get the continuous curve between the two endpoints? I guess I could calculate &lt;span class=&quot;math-container&quot;&gt;$\Delta A$&lt;/span&gt; for several points up to my final temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; using the average potential energy from the parallell tempering sampling, then I suppose these two methods would be quite similar.&lt;/p&gt;&#xA;&lt;p&gt;A lot of what I've read otherwise employ thermodynamic integration using a parameter &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; smoothly varying between the two final states. But, using that approach I'm unsure of what to introduce as my &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;. I was thinking of using perhaps the averaged separation distance between my particles, and then the &lt;span class=&quot;math-container&quot;&gt;$\lambda=0$&lt;/span&gt; case would be in where the particles are bound in the droplet form and &lt;span class=&quot;math-container&quot;&gt;$\lambda = 1$&lt;/span&gt; the unbound or melted form.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; This is the scheme I've, after some additional reading, come up with:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Identifying temperatures above and below the phase transition, using the rule of &lt;span class=&quot;math-container&quot;&gt;$\sim 20 \%$&lt;/span&gt; overlap/acceptance ratio between adjacent temperatures I use 5 replicas, i.e. 5 parallell simulations at 5 respective temperatures &lt;span class=&quot;math-container&quot;&gt;$T_i$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The procedure is then:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Generating the potential energy histograms,&lt;/li&gt;&#xA;&lt;li&gt;Normalising these into probability distributions,&lt;/li&gt;&#xA;&lt;li&gt;Starting at the lowest temperature, &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt;, the other distributions at temperatures &lt;span class=&quot;math-container&quot;&gt;$T_i$&lt;/span&gt; for &lt;span class=&quot;math-container&quot;&gt;$i = 1,2,3,4$&lt;/span&gt;, are reweighted with respective Boltzmann factor ratios e.g. each bin is multiplied by the same Boltzmann ratios &lt;span class=&quot;math-container&quot;&gt;$e^{-(\frac{1}{T_0} - \frac{1}{T_i}) \Delta U_i}$&lt;/span&gt; using &lt;span class=&quot;math-container&quot;&gt;$k_{\text{B}} = 1$&lt;/span&gt;,&lt;/li&gt;&#xA;&lt;li&gt;With these reweighted distributions w.r.t. to &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt; as reference, the free energy can be calculated &lt;span class=&quot;math-container&quot;&gt;$A_i = -k_{\text{B}} T_0 \ln(Z_{\text{RW at }T_i}/Z_{T_0})$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$Z_{\text{RW at }T_i}$&lt;/span&gt; is the reweighted histogram at &lt;span class=&quot;math-container&quot;&gt;$T_i$&lt;/span&gt; w.r.t. to reference &lt;span class=&quot;math-container&quot;&gt;$T_0$&lt;/span&gt;, and is calculated for each &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;, resulting in 4 free energy points to the profile,&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="8582" LastEditorUserId="8582" LastEditDate="2023-12-28T21:21:29.337" LastActivityDate="2023-12-28T21:21:29.337" Title="Free energy as a function of temperature over phase transition in molecular dynamics simulation" Tags="|molecular-dynamics|free-energy|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12133" PostTypeId="1" AcceptedAnswerId="12672" CreationDate="2023-12-22T22:06:48.853" Score="6" ViewCount="41" Body="&lt;p&gt;I aim to do a plane-wave calculation after computing pseudopotentials. There are many ways to build &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1521/what-are-the-types-of-pseudopotentials&quot;&gt;pseudopotentials&lt;/a&gt; and each of them have their set of parameters.&lt;/p&gt;&#xA;&lt;p&gt;What is the relevant piece of information to save and its format for a plane-wave calculation?&lt;/p&gt;&#xA;" OwnerUserId="7151" LastActivityDate="2024-04-01T10:20:41.123" Title="How to save pseudopotential?" Tags="|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12134" PostTypeId="1" CreationDate="2023-12-23T01:20:16.980" Score="4" ViewCount="31" Body="&lt;p&gt;In the context of first-principles calculations, such as DFT, lattice vibrations are often determined through phonon calculations, providing valuable insights into the stability and dynamics of crystal structures.&lt;/p&gt;&#xA;&lt;p&gt;Considering this, I am curious about the potential utilization of the calculated phonon vibrations or frequencies as a criterion for adjusting the geometrical relaxation during atomic or ionic relaxation. Are there any established methods or approaches that incorporate the phonon calculations to guide the optimization process as a feed-back loop? Can the phonon frequencies serve as a reliable indicator for adjusting the relaxation parameters or convergence criteria to achieve more stable atomic configurations?&lt;/p&gt;&#xA;&lt;p&gt;I would appreciate insights and suggestions on how to incorporate the information obtained from phonon calculations as a feedback mechanism in the geometrical relaxation process to enhance the accuracy and stability of calculated structures.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-23T01:20:16.980" Title="Incorporating Phonon Calculations as a Criterion for Geometrical Relaxation" Tags="|density-functional-theory|geometry-optimization|phonons|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12135" PostTypeId="2" ParentId="12131" CreationDate="2023-12-23T07:19:55.910" Score="1" Body="&lt;p&gt;In my opinion, you use &lt;em&gt;calculate&lt;/em&gt; (and &lt;em&gt;calculated&lt;/em&gt;) to refer to the process of using mathematical methods or formulas.&lt;/p&gt;&#xA;&lt;p&gt;E.g. &lt;em&gt;I want to &lt;strong&gt;calculate&lt;/strong&gt; the total electronic energies of a benzene molecule&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;And, you use &lt;em&gt;compute&lt;/em&gt; to refer to the action of mathematical operation, for example, using electronic devices (like computers) or software.&lt;/p&gt;&#xA;&lt;p&gt;E.g. &lt;em&gt;DFT is used to &lt;strong&gt;compute&lt;/strong&gt; the total electronic energies of a benzene molecule&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;All in all, grammatically, calculate and compute are interchangeable.&lt;/p&gt;&#xA;" OwnerUserId="579" LastActivityDate="2023-12-23T07:19:55.910" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12136" PostTypeId="1" CreationDate="2023-12-23T20:51:54.813" Score="6" ViewCount="92" Body="&lt;p&gt;My question is straightforward and is outlined in the post title: Is it essential to include the solvent cage effect in radical reactions during the computational estimation of Gibbs free energies and activation energies?&lt;/p&gt;&#xA;&lt;p&gt;To be more exact, I do refer to these two papers:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1002/chem.19970030208&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1002/chem.19970030208&lt;/a&gt; (original formulation of correction)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://doi.org/10.1021/jp0540499&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jp0540499&lt;/a&gt; (other papers which to some point validate the aforementioned but only ionic reactions are tested)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The crux of the matter is whether it is correct to use this correction in the case of reactions involving neutral/ionic species and radicals. Given that the reactivity of the latter process is inherently greater, could the inclusion of the correction artificially enhance the feasibility of the process?&lt;/p&gt;&#xA;&lt;p&gt;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="8524" LastEditorUserId="8524" LastEditDate="2023-12-24T08:30:38.640" LastActivityDate="2024-01-31T20:07:30.900" Title="Is it essential to include solvent cage effect in radical reactions?" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|molecular-modeling|thermodynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12137" PostTypeId="1" AcceptedAnswerId="12139" CreationDate="2023-12-24T14:27:49.197" Score="6" ViewCount="137" Body="&lt;p&gt;By plotting the &lt;strong&gt;RDF&lt;/strong&gt; (radial distribution function), is it possible to determine at what radius the interactions of surrounding atoms/molecules with the reference atom/molecule reduce greatly?&lt;/p&gt;&#xA;&lt;p&gt;My assumption is it is where the RDF function's first spike falling down intersects with the average line because it is below this radius where the interaction molecules exist. Is my assumption correct?&lt;/p&gt;&#xA;&lt;p&gt;My system is an amorphous solid (expecting liquid-like behavior).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Ldd36.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ldd36.png&quot; alt=&quot;RDF example&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.ucl.ac.uk/%7Eucfbasc/Theory/rdf.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Reference of image&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4536" LastEditorUserId="1508" LastEditDate="2023-12-31T12:50:49.203" LastActivityDate="2023-12-31T12:50:49.203" Title="Can radial distribution function determine where the interactions of reference (atom/molecule) reduces greatly with surrounding atoms/molecules?" Tags="|structure|molecular-interactions|radial-distribution-function|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12138" PostTypeId="2" ParentId="12131" CreationDate="2023-12-24T17:38:26.090" Score="0" Body="&lt;p&gt;I have been thinking about this, and &lt;em&gt;calculate(d)&lt;/em&gt; seems to be used when you’re emphasising the results, e.g.: &lt;em&gt;We&lt;/em&gt; &lt;em&gt;&lt;strong&gt;calculated&lt;/strong&gt;&lt;/em&gt; &lt;em&gt;the frequencies of methane.&lt;/em&gt; or &lt;em&gt;The frequencies were&lt;/em&gt; &lt;em&gt;&lt;strong&gt;calculated&lt;/strong&gt;&lt;/em&gt; &lt;em&gt;at B3LYP level of theory.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, &lt;em&gt;compute(d)&lt;/em&gt; seems to be used more when emphasising the technical (not theoretical) method. For example: &lt;em&gt;We&lt;/em&gt; &lt;em&gt;&lt;strong&gt;computed&lt;/strong&gt;&lt;/em&gt; &lt;em&gt;the frequencies for methane using our algorithm/program.&lt;/em&gt; or &lt;em&gt;The frequencies were&lt;/em&gt; &lt;em&gt;&lt;strong&gt;computed&lt;/strong&gt;&lt;/em&gt; &lt;em&gt;on a Mac Mini with a M1 chip.&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;I suspect, however, that the two words are entirely interchangeable now. I imagine that the term ‘compute(d)’ became used when computers started being used to run the calculations, to distinguish between calculations which were solved by hand. I suspect that the reason people rarely write ‘compute(d)’ nowadays is because the involvement of a computer is assumed implicitly.&lt;/p&gt;&#xA;" OwnerUserId="7606" LastActivityDate="2023-12-24T17:38:26.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12139" PostTypeId="2" ParentId="12137" CreationDate="2023-12-25T01:02:15.703" Score="4" Body="&lt;p&gt;Your assumption regarding the RDF plot is generally correct. The RDF provides information about the probability of finding particles at a given distance from the reference atom/molecule. Analyzing the RDF plot can help identify significant changes or features, such as notable decreases in the RDF value or distinct changes in slope or curvature. In your case, it seems that you are interested in the first shoulder observed in the plot.&#xA;By identifying the point or range of distances where the RDF value decreases significantly, you can gain insights into the radius where the interactions between the surrounding atoms/molecules reduce greatly with the reference atom/molecule.&lt;/p&gt;&#xA;&lt;p&gt;However, it's important to note that the RDF alone doesn't directly quantify the nature or strength of interactions. To obtain a more comprehensive understanding, I recommend examining the potential energy landscape, which provides information about the energy of the system as a function of atomic positions. Additionally, studying coordination numbers through techniques like pair potential or energy decomposition analysis can also provide insights into the interaction strengths and contributions from different components.&#xA;By combining these complementary analyses, you can enhance your understanding of the interactions in your system beyond what the RDF plot alone can provide.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2023-12-25T03:27:04.190" LastActivityDate="2023-12-25T03:27:04.190" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12140" PostTypeId="2" ParentId="12131" CreationDate="2023-12-25T01:20:19.067" Score="0" Body="&lt;p&gt;I will give my own opinion and understanding of using those terms and how I have been using them in my own work. First of all both &amp;quot;calculated&amp;quot; and &amp;quot;computed&amp;quot; are commonly used when referring to properties studied using first-principles methods. In practice, the choice between &amp;quot;calculated&amp;quot; and &amp;quot;computed&amp;quot; may come down to personal preference or the specific context in which the term is used. Both terms are widely accepted and understood in the scientific community.&lt;/p&gt;&#xA;&lt;p&gt;However, if I want to emphasize a specific aspect, there can be a subtle difference:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Calculated: The term &amp;quot;calculated&amp;quot; often implies a more deliberate&#xA;and intentional process. It suggests that the property or result has&#xA;been determined through a systematic and well-defined calculation&#xA;method, such as DFT. It conveys the idea that the value or property&#xA;has been obtained by performing specific calculations based on&#xA;theoretical principles.&lt;/li&gt;&#xA;&lt;li&gt;Computed: On the other hand, &amp;quot;computed&amp;quot; generally suggests a more&#xA;general process of obtaining a result or property through numerical&#xA;or computational methods. It indicates that the property has been&#xA;derived or evaluated using computational techniques, which may&#xA;include not only theoretical calculations but also numerical&#xA;simulations or data analysis.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-25T01:20:19.067" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12141" PostTypeId="1" AcceptedAnswerId="12142" CreationDate="2023-12-25T06:27:26.623" Score="5" ViewCount="167" Body="&lt;p&gt;Convert MoO3 bulk structure to MoO3 (010) plane surface via VESTA&lt;/p&gt;&#xA;" OwnerUserId="8414" LastActivityDate="2023-12-25T07:03:32.090" Title="How to convert MoO3 bulk structure to MoO3 (010) plane surface via VESTA software?" Tags="|python|molecular-modeling|atomic-simulation-environment|vesta|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12142" PostTypeId="2" ParentId="12141" CreationDate="2023-12-25T07:03:32.090" Score="6" Body="&lt;p&gt;You can do that with VESTA for sure, but it is a tedious process and it is hard to explain it without adding so many figures for each step. I suggest you to use ASE and Python tools to do that. Here I will provide you with a code written in python and uses pymatgen to do this job:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core.structure import Structure&#xA;from pymatgen.io.vasp import Poscar&#xA;from pymatgen.core.surface import SlabGenerator&#xA;import os&#xA;&#xA;# Get the current working directory&#xA;cwd = os.getcwd()&#xA;&#xA;# Specify the CONTCAR file name&#xA;contcar_file = &amp;quot;CONTCAR&amp;quot;&#xA;&#xA;# Specify the Miller index and added vacuum&#xA;miller_index = (0, 1, 0)  # Example: (h, k, l)&#xA;vacuum_thickness = 15.0  # Example: Angstroms&#xA;min_vacuum_size = 15.0  # Example: Angstroms&#xA;&#xA;# Read the CONTCAR file and generate the surface slab&#xA;contcar_path = os.path.join(cwd, contcar_file)&#xA;poscar = Poscar.from_file(contcar_path)&#xA;structure = poscar.structure&#xA;slab_generator = SlabGenerator(structure, miller_index, vacuum_thickness, min_vacuum_size)&#xA;slab = slab_generator.get_slab()&#xA;&#xA;# Write the generated slab to a POSCAR file&#xA;slab.to(&amp;quot;poscar&amp;quot;, &amp;quot;POSCAR&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In this sample code, my structure was coming from CONTCAR file that exist in the same directory with this script (just make sure the file is compatible with VASP POSCAR or CONTCAR files - you may need to change the naming according to your files), the script would also add vaccum with a thickness value defined by the user. Eventually, the slab will be written to a POSCAR file.&lt;/p&gt;&#xA;&lt;p&gt;I just want to add as well, if you just want something out of the box, you can use &lt;a href=&quot;https://vaspkit.com&quot; rel=&quot;noreferrer&quot;&gt;vaspkit&lt;/a&gt; tool, they have an option for building slabs starting from bulk structure. In vaspkit, you can access that option with (803) Build Surface by Specified Miller Indices&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-25T07:03:32.090" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12143" PostTypeId="1" AcceptedAnswerId="12147" CreationDate="2023-12-25T09:03:33.833" Score="3" ViewCount="49" Body="&lt;p&gt;I am trying to use SCAN to calculate hybrid perovskite which contains H atom. In VASP wiki, I found that &lt;code&gt;kinetic energy-density   mkinetic energy-density pseudized and kinetic energy density (partial)&lt;/code&gt; should be included in POTCAR. However, I found that for hydrogen, POTCAR of H_GW, H_h, H_GW_new and H_h_GW only have &lt;code&gt; kinetic energy-density&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;My question is: which POTCAR of H should be used for SCAN calculation?&lt;/p&gt;&#xA;" OwnerUserId="7083" LastActivityDate="2023-12-26T07:22:00.163" Title="Which pseudopotential of Hydrogen should be used in meta-GGA SCAN functional in VASP?" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12144" PostTypeId="1" CreationDate="2023-12-25T09:48:53.253" Score="3" ViewCount="168" Body="&lt;p&gt;I hope someone here can help me with some TD-DFT calculations. I am trying to calculate the excited state optimised structures and energies of some Germanium compounds. Firstly, I run a TD calculation of the first 10 excited states, singlets and triplets, using &lt;code&gt;TDA=(Nstates=10,50-50) WB97XD/genecp&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;From this output, I see the first few excited state energies and they look ok to me:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Excited State   1:      Triplet-A &#xA;2.4156 eV  513.26 nm  f=0.0000&#xA;&amp;lt;S**2&amp;gt;=2.000      &#xA;113 -&amp;gt;120        -0.18260      &#xA;119 -&amp;gt;120         0.65189&#xA;&#xA;  This state for optimization and/or second-order correction.&#xA;  Total Energy, E(CIS/TDA) =  -1629.19629051&#xA;     Copying the excited state density for this state as the 1-particle RhoCI density.  &#xA;&#xA;Excited State   2:      Singlet-A&#xA;3.3296 eV  372.37 nm  f=0.0537&#xA;&amp;lt;S**2&amp;gt;=0.000      &#xA;113 -&amp;gt;120        -0.18586      &#xA;119 -&amp;gt;120         0.66543 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I then try to optimise the first singlet and triplet as I want to see how the spin density looks like in those species. For the first triplet, I just indicate multiplicity 3 in the gaussian input (&lt;code&gt;0 3&lt;/code&gt; right before the coordinates), and I get something that I think makes sense; the molecule geometry changes and I get alpha and beta orbitals, one electron seems to be occupying a virtual orbital by itself.... etc&lt;/p&gt;&#xA;&lt;p&gt;The problem comes with the first singlet excited state. In order to calculate it I use &lt;code&gt;TD=(Nstates=6,50-50,root=2) WB97XD/genecp&lt;/code&gt;, based on the previous excited states calculation, in which the second state is the first singlet. However, after the calculation was done (it took quite a long time) I see an output with completely normal orbitals (not alpha and beta), a nice HOMO with two electrons and a empty LUMO, as in the molecule looks like a normal diamagnetic ground state molecule.&lt;/p&gt;&#xA;&lt;p&gt;Does someone see something weird in my procedures? If you need any more details please let me know. My apologies if I am making some very basic mistakes I am very new in TD-DFT. Thank you all in advance!&lt;/p&gt;&#xA;" OwnerUserId="8593" LastEditorUserId="7" LastEditDate="2023-12-25T21:58:24.557" LastActivityDate="2023-12-25T21:58:24.557" Title="Singlet excited state optimization gaussian issue" Tags="|gaussian|geometry-optimization|excited-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12145" PostTypeId="2" ParentId="11852" CreationDate="2023-12-25T11:25:19.280" Score="3" Body="&lt;p&gt;When you run a PDOS post-processing using &lt;code&gt;projwfc.x&lt;/code&gt;, you get lots of output files depending on the number of atoms and their pseudopotentials. Usually the file will have this name &lt;code&gt;filpdos.pdos_atm#1(AA)_wfc#1(s)&lt;/code&gt; where &lt;code&gt;AA&lt;/code&gt; is the atomic symbol and &lt;code&gt;#1(s)&lt;/code&gt; denotes the orbital and can be any of &lt;code&gt;s&lt;/code&gt;, &lt;code&gt;p&lt;/code&gt;, &lt;code&gt;d&lt;/code&gt;, or &lt;code&gt;f&lt;/code&gt;. There is a executables in Quantum ESPRESSO called &lt;code&gt;sumpdos.x&lt;/code&gt; that makes obtaining atomic contribution easier. The (self-explanatory) commands are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;sumpdos.x *\(AA\)* &amp;gt; AA_tot_pdos.dat &#xA;sumpdos.x *\(AA\)*\(s\) &amp;gt; AA_s_pdos.dat&#xA;sumpdos.x *\(AA\)*\(p\) &amp;gt; AA_p_pdos.dat&#xA;sumpdos.x *\(AA\)*\(d\) &amp;gt; AA_d_pdos.dat&#xA;sumpdos.x *\(AA\)*\(f\) &amp;gt; AA_f_pdos.dat&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Note that this doesn't require any &lt;code&gt;mpirun&lt;/code&gt; or parallel mechanism. This is a simple and single command can be run in any local machine and thus HPC is not required. More about the usage of sumpdos.x:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ sumpdos.x -h&#xA;&#xA;USAGE: sumpdos [-h] [-f &amp;lt;filein&amp;gt;] [&amp;lt;file1&amp;gt; ... &amp;lt;fileN&amp;gt;]&#xA;Sum the pdos from the file specified in input and write the sum to stdout&#xA;-h : write this manual&#xA;-f &amp;lt;filein&amp;gt; : takes the list of pdos files from &amp;lt;filein&amp;gt; (one per line) instead of command line&#xA;&amp;lt;fileM&amp;gt; : the M-th pdos file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2023-12-25T11:25:19.280" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12146" PostTypeId="2" ParentId="12144" CreationDate="2023-12-25T11:47:50.323" Score="4" Body="&lt;p&gt;If you want the excited singlet state, I suggest you only calculate these, and not the 50:50. Optimization with roots higher than 1 is often tricky, and if you only calculate the singlet excited states, then you have root=1.&#xA;With that said, the orbitals you get are from the ground state. To get the excited state, use density=current. You can also use the NTO to get a condensed picture of the excitation itself.&lt;/p&gt;&#xA;" OwnerUserId="279" LastEditorUserId="5" LastEditDate="2023-12-25T12:27:41.437" LastActivityDate="2023-12-25T12:27:41.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12147" PostTypeId="2" ParentId="12143" CreationDate="2023-12-26T07:22:00.163" Score="2" Body="&lt;p&gt;I think the differnece between &lt;code&gt;kinetic energy-density&lt;/code&gt; and &lt;code&gt;mkinetic energy-density pseudized&lt;/code&gt; lies in the fact that the former indicates the representation of the kinetic energy density for the all-electron part of the pseudopotential, while the pseudized kinetic energy density represents the kinetic energy density associated with the pseudopotential and is used to describe the behavior of the valence electrons.&lt;/p&gt;&#xA;&lt;p&gt;Since hydrogen has only one electron in its 1&lt;em&gt;s&lt;/em&gt; orbital, which is considered a valence electron, there is no need for a separate pseudopotential approximation. Therefore, the kinetic energy-density in the POTCAR file for hydrogen represents the kinetic energy of the valence electron without the need for a pseudized representation. Thus, I think you don't need to worry about 'mkinetic energy-density pseudized' in this case.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-26T07:22:00.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12148" PostTypeId="2" ParentId="11289" CreationDate="2023-12-26T09:24:02.487" Score="4" Body="&lt;p&gt;Van der Waals (vdW) correction is important in systems where non-local interactions between atoms or molecules play a significant role. It is particularly relevant for materials with layered structures, such as 2D systems (monolayers or bilayers), as these systems often exhibit weak interlayer interactions.&lt;/p&gt;&#xA;&lt;p&gt;The vdW correction accounts for dispersion forces, which are long-range interactions arising from the fluctuating dipoles of atoms or molecules. These forces are not adequately captured by standard density functional theory (DFT) calculations. You might think that you will not include these forces in a monolayered system, however, weak interlayer interactions can still exist in monolayered systems due to the presence of vdW forces, specifically dispersion forces, that can arise from the fluctuations in electron density and induce temporary dipoles in adjacent atoms or molecules. These temporary dipoles can induce dipole-dipole interactions, resulting in weak attractive forces.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the inclusion of vdW correction when applying spin-orbit coupling (SOC). The vdW correction and SOC address different physical phenomena. The vdW correction accounts for long-range dispersion interactions, while SOC describes the interaction between the electron's spin and its motion. In most cases, both effects can coexist, and including both in your calculations provides a more comprehensive description of the system.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-26T09:24:02.487" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12149" PostTypeId="1" CreationDate="2023-12-26T22:14:27.467" Score="2" ViewCount="95" Body="&lt;p&gt;Hello everyone: I am doing phonon calculations to plot Helmholtz free energy against temperature. I am using Phonopy with DFPT method. Now I am done but appears if I want to use Phonopy-qha I need the thermal-properties of each of the e-v.dat data. Phonopy says I am supposed to compute the thermal-properties of each of the volumes specified in the e-v.dat file. Please how do I go about this? Do I need to do a new phonon calculations which is very expensive or I can still use the data from the DFPT? My aim is to plot Free energy against temperature with phonons and without phonons. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2023-12-26T22:14:27.467" Title="Phonon calculations using Phonopy" Tags="|vasp|phonons|phonopy|dfpt|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12150" PostTypeId="1" CreationDate="2023-12-27T23:38:41.157" Score="3" ViewCount="52" Body="&lt;p&gt;I want to do a simulation of an atom (type atom is not important) bouncing inside a spherical surface (the material of the surface is not important too) (i.e. starting from an initial velocity, the atom upon colliding with the spherical shell, continues moving and bouncing, etc.). I am totally new in molecular simulation. What must I learn for do this?&#xA;Thanks.&lt;/p&gt;&#xA;" OwnerUserId="8599" LastEditorUserId="8599" LastEditDate="2023-12-27T23:46:00.077" LastActivityDate="2023-12-27T23:46:00.077" Title="Beginning in molecular simulation world" Tags="|atomic-simulation-environment|atomistic-simulation|atomic-physics|atoms-in-molecules|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12151" PostTypeId="1" CreationDate="2023-12-29T04:18:56.117" Score="1" ViewCount="34" Body="&lt;p&gt;I would like to extend this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11908/1554&quot;&gt;question&lt;/a&gt; that I have asked before regarding semi-metallic characterisitc of a bandstructure.&lt;/p&gt;&#xA;&lt;p&gt;How can we describe the electronic behavior of a band structure in the attached figure, where only one band from the unoccupied states is slightly crossing the Fermi level, while no crossing has been observed from the occupied states?&lt;/p&gt;&#xA;&lt;p&gt;conisdering the density of states (DOS) at the Fermi level (refer to the attached figure), it is found to be very low. with such observations, can we classify this material as a metal, a semi-metal, or a some special type of topological material? What additional analyses or considerations are necessary to fully understand the electronic behavior in this scenario?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/bHm3r.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/bHm3r.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;I have to mention that the Figures of the bandstructure and DOS belongs to a tubular structure of WTe2 which is well known to be a type-II Weyl semimetal in its bulk 1T'-distorted phase, and also theoretically predicted to be a 2D topological insulator.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2023-12-29T04:18:56.117" Title="Understanding the Electronic Behavior of a Band Structure with Small Band Crossing" Tags="|band-structure|density-of-states|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12152" PostTypeId="1" CreationDate="2023-12-30T08:37:21.093" Score="4" ViewCount="43" Body="&lt;p&gt;i have started computationally modelling materials from first principles recently, my code of choice being VASP [6.1.0].&#xA;Recently i have come across this paper in Nature: &lt;strong&gt;DOI:10.1038/s41567-023-01960-5&lt;/strong&gt; and became interested in the images rendered. I wish to adapt it to use with a simple crystal structure I used to practice working with VASP.&lt;/p&gt;&#xA;&lt;p&gt;I have calculated various properties of my crystal like: relaxed structure, band structure, DoS, absorption and reflectivity data. I attach the reflectivity plot of my structure below:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/2bZOS.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/2bZOS.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is:&lt;/strong&gt; given this reflectivity data how do i find the appearance my crystal structure will have if/when synthesized in the lab? Can someone detail the exact steps i need to take to do so?&lt;/p&gt;&#xA;" OwnerUserId="8605" LastActivityDate="2023-12-30T08:37:21.093" Title="Photorealistic Rendering: How To?" Tags="|vasp|ab-initio-calculations|crystallography|dielectric-constants|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12154" PostTypeId="1" AcceptedAnswerId="12158" CreationDate="2023-12-30T10:53:49.553" Score="3" ViewCount="128" Body="&lt;p&gt;My surface is a monolayer graphene. I want to add a layer of water as adsorbate and the parameters are height = 3.31 Angstroms on top of the slab; Coverage = 24/72; The orientation is: The hydrogen atoms are facing down towards the surface.&lt;/p&gt;&#xA;&lt;p&gt;When i try to use &lt;strong&gt;acat&lt;/strong&gt;, i am getting an error '&lt;em&gt;&lt;strong&gt;IndexError: list index out of range&lt;/strong&gt;&lt;/em&gt;'. My goal is to get the structure as in the following figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UstOD.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UstOD.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here one can see the orientation of the H2O molecule on top of the surface (the legs are facing down)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PF9lm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PF9lm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And this is how i want the layer distribution of H2O on the surface. For every 3 carbon there is one H2O&lt;/p&gt;&#xA;&lt;p&gt;Could anyone please help?&lt;/p&gt;&#xA;&lt;p&gt;This is the code i wrote:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;import ase.build&#xA;from ase.visualize import view&#xA;from acat.build.adlayer import max_dist_coverage_pattern as mdcp&#xA;from acat.settings import site_heights&#xA;slab = ase.build.graphene(formula = 'C2',a=2.46,size=(6,6,1))&#xA;slab.center(vacuum=21,axis=2)&#xA;heights = {k: v+3.31 for k, v in site_heights.items()}&#xA;system = mdcp(slab,adsorbate_species='H2O',coverage = 24/72, surface = 'ontop', heights= heights)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8606" LastEditorUserId="1554" LastEditDate="2023-12-30T12:13:58.983" LastActivityDate="2024-01-31T07:22:44.280" Title="How to model adsorbate layer on a monolayer graphene surface using ASE" Tags="|atomic-simulation-environment|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12155" PostTypeId="1" CreationDate="2023-12-30T19:01:44.800" Score="2" ViewCount="25" Body="&lt;p&gt;Jargon is quite confusing when dealing with viscoelasticity, plasticity, and anelasticity.&lt;/p&gt;&#xA;&lt;p&gt;In a general constant stress creep curve: there is instantaneous elastic strain, followed by time-dependent anelastic strain, and then a constant strain-rate viscous flow type behavior until the stress is removed. In general, the elastic and anelastic strains are recovered, but the constant strain-rate deformation stays after removing the load.&lt;/p&gt;&#xA;&lt;p&gt;In this description, does it mean that the constant strain-rate deformation represents plasticity? I'm not sure how to define plasticity accurately in this context. I know that the entire curve represents a viscoelastic behavior, but does the viscous flow represents plasticity?&lt;/p&gt;&#xA;&lt;p&gt;Any insights or clarification on the differences will be much appreciated! I couldn't find a text that explain this thoroughly.&lt;/p&gt;&#xA;" OwnerUserId="4852" LastActivityDate="2023-12-30T19:01:44.800" Title="Is there a difference between viscous flow and plasticity?" Tags="|crystal-plasticity|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12156" PostTypeId="1" AcceptedAnswerId="12157" CreationDate="2023-12-31T10:47:49.913" Score="1" ViewCount="103" Body="&lt;p&gt;I am trying to find the transition path using NEB method in ASE. However when i try to import the ase.mep module, i am getting the following error 'ModuleNotFoundError: No module named 'ase.mep''&lt;/p&gt;&#xA;&lt;p&gt;Can anyone explain me how to resolve this error?&lt;/p&gt;&#xA;" OwnerUserId="8606" LastActivityDate="2023-12-31T18:05:58.023" Title="ModuleNotFoundError: No module named 'ase.mep'" Tags="|atomic-simulation-environment|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12157" PostTypeId="2" ParentId="12156" CreationDate="2023-12-31T13:52:44.467" Score="1" Body="&lt;p&gt;I was able to solve the issue.&lt;/p&gt;&#xA;&lt;p&gt;I had to use it like this:&lt;/p&gt;&#xA;&lt;p&gt;from ase.neb import NEB&lt;/p&gt;&#xA;" OwnerUserId="8606" LastActivityDate="2023-12-31T13:52:44.467" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12158" PostTypeId="2" ParentId="12154" CreationDate="2023-12-31T14:10:19.353" Score="1" Body="&lt;p&gt;I was able to find a workaround for the problem that I had. It goes like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;import ase.build&#xA;from ase.visualize import view&#xA;from ase.build import add_adsorbate&#xA;slab = ase.build.graphene(formula=‘C2’,a=2.46,size=(6,6,1))&#xA;slab.center(vacuum=21,axis=2)&#xA;water = ase.build.molecule(‘H2O’)&#xA;h = 3.31&#xA;x = 0&#xA;y = 0&#xA;add_adorbate(slab, adsorbate=water,height=h,position(x,y),offset=None,mol_index=0)&#xA;view(slab)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the above code, the position of the adsorbate over the surface is controlled by the parameter position(x,y) where x and y values are in Angstroms. The x and y values of an atom in the surface can be seen through:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;slab.get_positions()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The parameter mol_index is the atom in the molecule used for positioning. The Index starts with 0,1,2….&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;water.get_chemical_symbols()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In my case it’s O,H,H=(0,1,2)&lt;/p&gt;&#xA;&lt;p&gt;Overall it is a bit tedious work as I need to place one molecule at a time but it works for now.&lt;/p&gt;&#xA;&lt;p&gt;Thank you&lt;/p&gt;&#xA;" OwnerUserId="8606" LastActivityDate="2023-12-31T14:10:19.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12159" PostTypeId="1" CreationDate="2023-12-31T14:57:05.900" Score="4" ViewCount="36" Body="&lt;p&gt;as mentioned, I'm building a molecular dynamics simulation of decanoic acid and decanoate (with neutralising sodium cations) in water. I've minimized and equilibrated the simulation up to 295 K and I've generated a little movie of the run (0.002 ns steps for about 1 ms). I have noticed a couple of issues I was hoping to get advice on:&lt;/p&gt;&#xA;&lt;p&gt;water seems to be getting into the lipid bilayer at points. Should I be concerned about this? I know passive transport through bilayers is a thing, but I'm unsure if water penetration happening frequently is something to be concerned about.&lt;/p&gt;&#xA;&lt;p&gt;Lipids occasionally dissociate from the bilayer into the solution. Is this reasonable? I'm not sure if it's something I should be concerned about. I know I could potentially restrain the lipids, but given the purpose of this simulation is to determine the stability of the bilayer and determining area per lipid, restraining those lipids seems, to me, like defeating the purpose of the experiment.&lt;/p&gt;&#xA;&lt;p&gt;Here is a linke to the first few ns of simulation so you can see what I mean. stackoverflow won't let me post a gif, I think, so I've linked my Linkedin page where I posted it:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://www.linkedin.com/feed/update/urn:li:activity:7147156113686167552/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.linkedin.com/feed/update/urn:li:activity:7147156113686167552/&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I'm happy to provide more info but as this is a conceptual issue, less a coding issue, I didn't want to be dumping mdp files in here.&lt;/p&gt;&#xA;&lt;p&gt;Note: sodium cations aggregate at the bilayer surface. This is something that the forcefields usually suffer and I will be transitioning to K+ ions next.&lt;/p&gt;&#xA;&lt;p&gt;I'm aiming to simulate the stability of decanoic acid lipid bilayers in aqueous environments over temperature.&lt;/p&gt;&#xA;" OwnerUserId="8607" LastActivityDate="2024-01-01T11:07:48.960" Title="Is water penetration and fatty acid dissolution reasonable when Gromacs modelling of an aqueous lipid bilayer?" Tags="|molecular-dynamics|gromacs|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12160" PostTypeId="2" ParentId="12156" CreationDate="2023-12-31T18:05:58.023" Score="1" Body="&lt;p&gt;This is caused by a disconnect between the ASE documentation online and the release version of ASE (2 years old).  If you want to view the correct documentation, you can render out the documentation locally using Sphinx.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2023-12-31T18:05:58.023" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12161" PostTypeId="1" CreationDate="2023-12-31T19:43:28.950" Score="4" ViewCount="188" Body="&lt;p&gt;I'm running some SCF calculations in VASP, and when looking at the OUTCAR, I see that for each KPOINT there is a slightly different value for the HOMO/LUMO (looking at Band No. and Occupation values, where HOMO has an occupation of 2 and LUMO has an occupation of 0). Do I average the different HOMO/LUMO values of each KPOINT to get the HOMO/LUMO for the single point calculation or would that be inaccurate?&lt;/p&gt;&#xA;" OwnerUserId="7429" OwnerDisplayName="lzzard" LastActivityDate="2023-12-31T23:14:40.967" Title="Finding HOMO/LUMO from SCF calculation: VASP" Tags="|vasp|computational-chemistry|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12162" PostTypeId="2" ParentId="12161" CreationDate="2023-12-31T23:14:40.967" Score="5" Body="&lt;p&gt;No, the HOMO is the &lt;em&gt;highest&lt;/em&gt; energy eigenvalue for the corresponding band, across the Brillouin zone. It isn't technically a HOMO because it isn't a molecular orbital (&amp;quot;MO&amp;quot;) it's a band, so what you're really looking for is the valence band maximum (&amp;quot;VBM&amp;quot;). If we could somehow use the exact exchange-correlation functional, DFT would give the correct VBM.&lt;/p&gt;&#xA;&lt;p&gt;In the same way, the LUMO is the &lt;em&gt;lowest&lt;/em&gt; energy eigenvalue for the corresponding band, across the Brillouin zone, and is more correctly called the conduction band minimum (&amp;quot;CBM&amp;quot;). Even the exact exchange-correlation functional doesn't get the correct CBM simply by reading off the Kohn-Sham eigenvalues, you need to use a more sophisticated method to get this (e.g. TD-DFT).&lt;/p&gt;&#xA;&lt;p&gt;As a final note, even these DFT values are likely to be rather approximate because the SCF k-point set probably doesn't sample all of the symmetry points and paths in the system. You may be fortunate and have the VBM and CBM at the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt;-point, and used an odd k-point grid, but in general it's better to perform a band-structure calculation and sample all of the high-symmetry paths and points.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2023-12-31T23:14:40.967" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12164" PostTypeId="1" CreationDate="2024-01-01T04:13:28.800" Score="4" ViewCount="298" Body="&lt;p&gt;I am beginner in Lammps. How can I create a single atom in the center of a box? (I am totally new) Thanks.&lt;/p&gt;&#xA;&lt;p&gt;Actualization:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4td8l.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4td8l.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What is wrong?&lt;/p&gt;&#xA;&lt;p&gt;Actualization 2.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PbTmi.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PbTmi.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8599" LastEditorUserId="8599" LastEditDate="2024-01-01T05:44:33.993" LastActivityDate="2024-01-01T05:48:02.270" Title="Single atom in a box (lammps)" Tags="|lammps|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12165" PostTypeId="2" ParentId="12164" CreationDate="2024-01-01T04:35:28.600" Score="4" Body="&lt;p&gt;In your input script you need to define the atomic coordinates, box dimensions, and atom type. For instance, to create a cubic box with a side length of 10 angstroms, you can use the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Set atom type and properties&#xA;atom_style atomic&#xA;atom_modify map array sort 0 0&#xA;&#xA;&#xA;# Box dimensions&#xA;lattice fcc 1.0&#xA;region box block 0 1 0 1 0 1 units lattice&#xA;create_box 1 box&#xA;mass 1 1.00794&#xA;&#xA;# Create the single atom at the center of the box&#xA;create_atoms 1 single 0.5 0.5 0.5&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The atom style is set to atomic, and the &lt;code&gt;atom_modify&lt;/code&gt; command is used to specify how the atom information is mapped. Next, the box dimensions are defined using the lattice and region commands, creating a cubic box with a lattice constant of 1.0 Angstrom. The &lt;code&gt;create_box&lt;/code&gt; command creates the simulation box based on the region we have defined. Then the mass of atom type 1 is set to the mass of hydrogen as an example (the mass of hydrogen is approximately 1.00794 AMU). finally, The &lt;code&gt;create_atoms&lt;/code&gt; command creates a single atom of type 1 at the center of the box. You have to setup other input parameters according to your own purpose.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-01-01T05:48:02.270" LastActivityDate="2024-01-01T05:48:02.270" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12166" PostTypeId="1" CreationDate="2024-01-01T06:33:30.250" Score="3" ViewCount="39" Body="&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/WhKd6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/WhKd6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;With this code, I can get two atoms in different positions. Now, I want the blue atom to colisionate with the red atom (in repose). Is it possible? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="8599" LastEditorUserId="1554" LastEditDate="2024-01-01T07:00:08.293" LastActivityDate="2024-01-01T07:00:08.293" Title="How can I get that an atom colisionates to another atom? (in lammps)" Tags="|lammps|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12167" PostTypeId="2" ParentId="12159" CreationDate="2024-01-01T11:07:48.960" Score="1" Body="&lt;p&gt;I have been given a way forward by a user in the comments, so I am marking this question as completed. Please feel free to add extra answers if you think of something, but I have a path forward now. Thank you!&lt;/p&gt;&#xA;" OwnerUserId="8607" LastActivityDate="2024-01-01T11:07:48.960" CommentCount="0" CommunityOwnedDate="2024-01-02T00:22:25.673" ContentLicense="CC BY-SA 4.0" />
  <row Id="12168" PostTypeId="2" ParentId="12136" CreationDate="2024-01-01T11:26:06.050" Score="1" Body="&lt;p&gt;From:&lt;/p&gt;&#xA;&lt;p&gt;J. Am. Chem. Soc. 2016, 138, 30, 9389–9392&#xA;Publication Date:July 19, 2016&#xA;&lt;a href=&quot;https://doi.org/10.1021/jacs.6b05432&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/jacs.6b05432&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;In conclusion, the experiments reported here suggest that for nonpolar solvent systems quantitative discussions pertaining to FcP should be based on microviscosity rather than bulk viscosity. In essence, if the translational diffusion coefficient for a particular radical in a cage pair is known then an accurate cage recombination efficiency is predictable, independent of the solvent system. This predictive power will be useful wherever quantitative knowledge of radical reactivity is necessary. It is noted that the method described above can be applied in reverse. That is, if FcP is known then the diffusion coefficient of the molecule can be determined; in turn, the microviscosity of the local environment around the caged molecules can be probed. This reverse application would provide a method for determining the microviscosity in complex systems such as active sites of enzymes or in heterogeneous reactions. Polar solvent systems and hydrogen-bonding solvent systems are currently being investigated in our laboratory to determine if the results obtained above with nonpolar solvents are also applicable in these types of solvents.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;My reading here is they have lab and modelling work to back up that solvent cage effects do apply to radical reactions -- at least in non-polar solvents. Barry and Tyler have a few papers out on this subject, including this: &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.inorgchem.0c01441&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/10.1021/acs.inorgchem.0c01441&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;So if this doesn't answer your question, it may also be useful to reach out to them directly for a chat.&lt;/p&gt;&#xA;&lt;p&gt;You could also just model the system with and without solvent cage effects and compare. Without wet lab results to back it up, it will be difficult to determine accuracy, but you might find one of the methods ends up with something easily identifiably false.&lt;/p&gt;&#xA;" OwnerUserId="8607" LastEditorUserId="5" LastEditDate="2024-01-01T19:40:11.587" LastActivityDate="2024-01-01T19:40:11.587" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12169" PostTypeId="1" AcceptedAnswerId="12171" CreationDate="2024-01-01T15:12:54.067" Score="4" ViewCount="121" Body="&lt;p&gt;How can I visualize the geometry optimization? I want to see the plot of potential energy through various iterations to reach the minimum value. I would also like to see the animation of the atoms being moved. I have here an example code for geometry optimization. Can someone help me with the visualization?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io&#xA;import ase.build&#xA;from ase.visualize import view&#xA;from ase.optimize import BFGS&#xA;import numpy as np&#xA;from ase.calculators.emt import EMT&#xA;&#xA;water = ase.build.molecule('H2O',calculator=EMT())&#xA;opt = BFGS(water,trajectory ='H2O.traj')&#xA;opt.run(fmax=0.05)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And this was the result:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;     Step     Time          Energy         fmax&#xA;&#xA;BFGS:    0 12:18:19        2.619811        7.7384&#xA;BFGS:    1 12:18:19        1.912906        1.3454&#xA;BFGS:    2 12:18:19        1.882033        0.4035&#xA;BFGS:    3 12:18:19        1.879275        0.0317&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the documentation i read that ase gui can do this. But i tried it in this way:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ase gui H2O.traj&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However i am getting an error: Invalid syntax&lt;/p&gt;&#xA;" OwnerUserId="8606" LastEditorUserId="5" LastEditDate="2024-01-01T23:44:37.027" LastActivityDate="2024-01-02T12:55:30.767" Title="How to use ase gui to visualize the geometry optimization (through graphs and animation)?" Tags="|atomic-simulation-environment|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12170" PostTypeId="1" CreationDate="2024-01-01T16:39:03.023" Score="5" ViewCount="52" Body="&lt;p&gt;I am carrying out the calculations of a structure using Quantum Espresso, I have already calculated scf, nscf, dos, bands, charge density... Now I would like to do FTIR and RAMAN calculations. Can anyone give me a tip on how I should do this?&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="5" LastEditDate="2024-01-01T23:45:14.383" LastActivityDate="2024-01-01T23:45:14.383" Title="How to perform FTIR and RAMAN calculations using Quantum Espresso ​?" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12171" PostTypeId="2" ParentId="12169" CreationDate="2024-01-01T21:31:03.480" Score="4" Body="&lt;p&gt;The &lt;code&gt;ase gui&lt;/code&gt; command is a shell command. So you should type it not to the Python prompt (usually looks like &lt;code&gt;&amp;gt;&amp;gt;&amp;gt; &lt;/code&gt;), but to the shell prompt (may look like &lt;code&gt;C:\&amp;gt; &lt;/code&gt;). If you prefer to run visualizer directly from Python, then you should add to your code something like this:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;traj = ase.io.read('H2O.traj', index=':')&#xA;view(traj)&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="277" LastEditorUserId="277" LastEditDate="2024-01-02T12:55:30.767" LastActivityDate="2024-01-02T12:55:30.767" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12172" PostTypeId="1" CreationDate="2024-01-02T10:01:43.953" Score="3" ViewCount="89" Body="&lt;p&gt;I want to find the transition state properties (activation energy, reaction rate and few thermodynamic properties). I found out that NEB can do the transition state search. I have already created the initial state. I also read that it is advisable to make a copy of the initial state and add some changes to get the final state. My question is as follows:&lt;/p&gt;&#xA;&lt;p&gt;Reaction: C(s) + H2O --&amp;gt; C(OH)ads + H+ + e-&lt;/p&gt;&#xA;&lt;p&gt;In this case the water is adsorbed on surface carbon to produce adsorbed C-OH releasing a proton and an electron.&lt;/p&gt;&#xA;&lt;p&gt;How do I model the proton and electron in my final state? Should I just delete one H atom from H2O? Or should I break the bond while still keeping the H atom in the final state? Or is there a way to model H+ and e-? If so, how?&lt;/p&gt;&#xA;&lt;p&gt;Also when i place the H2O molecule over the C atom and in GUI press on 'show bonds', the O is bonding with the neighboring C atoms too. Is it correct?&lt;/p&gt;&#xA;&lt;p&gt;Here is my code for the initial state:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import ase.io`&#xA;import ase.build&#xA;from ase.visualize import view&#xA;from ase.build import add_adsorbate&#xA;from ase.calculators.emt import EMT&#xA;import numpy as np&#xA;from ase.constraints import FixAtoms&#xA;from ase.optimize import QuasiNewton&#xA;from ase.io import write&#xA;&#xA;# Create a water molecule&#xA;water = ase.build.molecule('H2O')&#xA;&#xA;# Create a monolayer graphene surface (6x6 supercell) with a vacuum of 21 Å along z axis&#xA;slab = ase.build.graphene(formula='C2', a=2.46, size=(6,6,1))&#xA;slab.center(vacuum = 21, axis = 2)&#xA;&#xA;#Add adsorbate on top of the surface (on the 32nd C atom) at a height of 3.31 Å&#xA;get_pos = slab[32]&#xA;add_adsorbate(slab, adsorbate=water, height = 3.31, position = (get_pos.x , get_pos.y), mol_index = 0)&#xA;&#xA;# Setting calculator as EMT&#xA;slab.calc = EMT()&#xA;&#xA;# Defining constraints: Fix all C atoms&#xA;mask = [atom.symbol=='C' for atom in slab]&#xA;slab.set_constraint(FixAtoms(mask=mask))&#xA;&#xA;# Relax the structure&#xA;relax = QuasiNewton(slab)&#xA;relax.run(fmax=0.05)&#xA;view(slab)&#xA;&#xA;# Save the initial state &#xA;write('initial_state.traj',slab)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8606" LastEditorUserId="8606" LastEditDate="2024-01-02T11:19:26.337" LastActivityDate="2024-01-02T11:19:26.337" Title="How to model the final state for NEB calculations in ASE" Tags="|atomic-simulation-environment|nudged-elastic-band|" AnswerCount="0" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="12173" PostTypeId="1" CreationDate="2024-01-02T15:05:07.157" Score="5" ViewCount="62" Body="&lt;p&gt;Currently I'm using epsilon.x from Quantum ESPRESSO to analyse optical&#xA;properties of metallic alloys. I'm getting a wiggling curve for the dielectric function.&lt;/p&gt;&#xA;&lt;p&gt;For the imaginary part of dielectric function:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ZwHA2.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZwHA2.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;After some searching, I've found it could be due to the sampling within the Brillouin Zone. I'm using the automatic grid within the denser NSCF calculation. Here is a question:&lt;/p&gt;&#xA;&lt;p&gt;Can the automatic sampling be the source of the wiggles in the curves? If so, what are the different options to generate the grid?&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance.&lt;/p&gt;&#xA;" OwnerUserId="389" LastEditorUserId="389" LastEditDate="2024-01-03T19:20:36.237" LastActivityDate="2024-01-03T19:20:36.237" Title="Optical properties using ESPRESSO's epsilon.x" Tags="|quantum-espresso|k-points|optical-properties|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12174" PostTypeId="1" AcceptedAnswerId="12176" CreationDate="2024-01-02T16:31:54.187" Score="7" ViewCount="114" Body="&lt;p&gt;In their famous paper &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.23.5048&quot; rel=&quot;nofollow noreferrer&quot;&gt;Self-interaction correction to density-functional approximations for many-electron systems&lt;/a&gt; Perdew and Zunger said&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The exact density functional for the ground-state energy is strictly self-interaction-free (i.e., orbitals demonstrably do not self-interact), but many approximations to it, including the local-spin-density (LSD) approximation for exchange and correlation, are not.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;How to prove that the exact density functional is self-interaction-free if the exact form of the exchange-correlation functional is not known?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-01-04T02:46:39.977" LastActivityDate="2024-01-04T10:03:14.333" Title="Self-interaction in density functional approximations for many-electron systems" Tags="|density-functional-theory|exchange-correlation|self-interaction|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12175" PostTypeId="1" CreationDate="2024-01-03T14:56:06.343" Score="3" ViewCount="39" Body="&lt;p&gt;I am trying to understand how to calculate electronic properties using reduced density matrices from electronic structure calculation. So far, I understand (I think) that for the expectation value of an &lt;em&gt;n&lt;/em&gt;-electron operator, you would need the &lt;em&gt;n&lt;/em&gt;-electron reduced density with &lt;span class=&quot;math-container&quot;&gt;$$ \langle \hat{O}\rangle = \mathrm{Tr}(\Gamma^{(n)} O ).\tag{1} $$&lt;/span&gt; I have also found that these &lt;em&gt;n&lt;/em&gt;-electron RDMs can be obtained, for example, from PySCF, &lt;a href=&quot;https://pyscf.org/user/ci.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;as described here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;When trying to understand the practicality on how to use these quantities, however, I've encountered the distinction between &lt;em&gt;relaxed&lt;/em&gt; and &lt;em&gt;unrelaxed&lt;/em&gt; RDMs, for example, &lt;a href=&quot;https://github.com/pyscf/pyscf/issues/420&quot; rel=&quot;nofollow noreferrer&quot;&gt;in this question&lt;/a&gt;, where it is stated that the trace of the 2RDM is incorrect in MP2, not giving &lt;span class=&quot;math-container&quot;&gt;$N(N-1)$&lt;/span&gt; as it should, but it should be correct in FCI, and the reason for this is that the matrix is unrelaxed. I tried to find an explanation to what exactly is the difference between relaxed and unrelaxed RDMs - apart from the intuition that some terms are missing -, but I have found no success. This concept seems to be beyond normal textbook knowledge, while maybe also being obvious for researchers in the field so that it is not really explained in papers/dissertations.&lt;/p&gt;&#xA;&lt;p&gt;What is exactly the difference between a relaxed and unrelaxed &lt;em&gt;n&lt;/em&gt;RDMs? I assume I can not just relax an unrelaxed quantity as post-processing, but do I need to do this at all? Or are quantities obtained from unrelaxed RMDs accurate enough?&lt;/p&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5" LastEditDate="2024-01-03T18:13:23.570" LastActivityDate="2024-01-03T18:13:23.570" Title="What is a relaxed reduced density matrix?" Tags="|electronic-structure|ab-initio-calculations|coupled-cluster|reduced-density-matrix|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12176" PostTypeId="2" ParentId="12174" CreationDate="2024-01-03T19:12:51.103" Score="5" Body="&lt;h1&gt;No self-interaction in the exact functional&lt;/h1&gt;&#xA;&lt;p&gt;The electronic structure Hamiltonian in real space is&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;H = T + V_{ee} + V_{\text{ext}} = -\frac12 \sum_i \nabla_i^2 + \sum_{i&amp;lt;j} \frac{1}{\lvert r - r' \rvert} + V_{\text{ext}}(r),&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$i, j$&lt;/span&gt; index the electrons in your favorite system.&lt;/p&gt;&#xA;&lt;p&gt;The relevant term is the electron-electron interaction &lt;span class=&quot;math-container&quot;&gt;$V_{ee}$&lt;/span&gt;, and especially the index in its sum: &lt;span class=&quot;math-container&quot;&gt;$i &amp;lt; j$&lt;/span&gt; means that electron &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; does not interact with itself.&lt;/p&gt;&#xA;&lt;p&gt;Because the (unknown) Hohenberg–Kohn functional is &lt;em&gt;exact&lt;/em&gt;, it must replicate the behavior of the Schrödinger equation. No self-interaction is part of that.&lt;/p&gt;&#xA;&lt;h1&gt;Self-interaction in Hartree–Fock theory and Kohn–Sham DFT&lt;/h1&gt;&#xA;&lt;p&gt;Neither Hartree–Fock (HF) theory nor Kohn–Sham DFT calculate &lt;span class=&quot;math-container&quot;&gt;$V_{ee}$&lt;/span&gt; directly. HF approximates the electron-electron interaction between one-particle orbitals &lt;span class=&quot;math-container&quot;&gt;$\lvert \psi_i \rangle$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\lvert \psi_j \rangle$&lt;/span&gt; as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\ \langle \psi_i \vert V_{ee} \vert \psi_j \rangle &amp;amp;\small{\approx J[\psi_i, \psi_j] - K[\psi_i, \psi_j] }\tag{2}\\&#xA;&amp;amp;\small{= \iint dr\, dr'\, \frac{\psi_i^*(r) \psi_i(r) \psi_j^*(r') \psi_j^*(r')}{\lvert r - r' \rvert} - \iint dr\, dr'\, \frac{\psi_i^*(r) \psi_j(r) \psi_j^*(r') \psi_i(r')}{\lvert r - r' \rvert}.}\tag{3}&#xA;\end{align}&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$J$&lt;/span&gt; is called the Hartree energy (it's the classical electrostatic repulsion) and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is called the exchange energy; they differ by a swapping of indices. A notable property of HF is that &lt;span class=&quot;math-container&quot;&gt;$J[\psi_i, \psi_i] - K[\psi_i, \psi_i] = 0$&lt;/span&gt;, as you can verify by inspection. For this reason, HF theory is said to be &lt;em&gt;self-interaction–free&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Kohn–Sham DFT's treatment of &lt;span class=&quot;math-container&quot;&gt;$V_{ee}$&lt;/span&gt; is not as simple; it's something like&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{4}&#xA;\langle \psi_i \vert V_{ee} \vert \psi_j \rangle \approx J[\psi_i, \psi_j] + E_{xc}[\rho],&#xA;$$&lt;/span&gt;&#xA;except that the exchange-correlation energy &lt;span class=&quot;math-container&quot;&gt;$E_{xc}$&lt;/span&gt; also includes some information about the many-body kinetic energy. But you can check whether a one-electron system, like the hydrogen atom, actually satisfies &lt;span class=&quot;math-container&quot;&gt;$J[\psi_1, \psi_1] - E_{xc}[\rho] = 0$&lt;/span&gt; for a given density functional approximation's &lt;span class=&quot;math-container&quot;&gt;$E_{xc}$&lt;/span&gt;: usually the answer is no. This is usually called &lt;em&gt;self-interaction error&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;h1&gt;Bonus: Many-electron self-interaction error&lt;/h1&gt;&#xA;&lt;p&gt;There are actually some density functional approximations, such as those &lt;a href=&quot;https://doi.org/10.1063/1.2749510&quot; rel=&quot;nofollow noreferrer&quot;&gt;described here&lt;/a&gt;, that are free of (one-electron) self-interaction error, just like HF is. However, they still suffer from most of the DFT problems traditionally associated with self-interaction error: too-small band gaps and reaction energy barriers, overly delocalized charges, and so on. This more general issue with DFT is known as &lt;strong&gt;delocalization error&lt;/strong&gt; (it's sometimes been called &lt;em&gt;many-electron self-interaction error&lt;/em&gt; too!) and mitigating it is &lt;a href=&quot;https://doi.org/10.1002/wcms.1631&quot; rel=&quot;nofollow noreferrer&quot;&gt;an active area of research&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastEditorUserId="1393" LastEditDate="2024-01-03T19:52:44.540" LastActivityDate="2024-01-03T19:52:44.540" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12177" PostTypeId="1" AcceptedAnswerId="12178" CreationDate="2024-01-03T21:50:15.130" Score="3" ViewCount="147" Body="&lt;p&gt;How may I calculate the Dielectric Tensor εij (total) &lt;a href=&quot;https://legacy.materialsproject.org/materials/mp-19/#dielectric-props&quot; rel=&quot;nofollow noreferrer&quot;&gt;like here&lt;/a&gt;? In the OUTCAR, I see both &lt;code&gt;HEAD OF MICROSCOPIC STATIC DIELECTRIC TENSOR (independent particle, excluding Hartree and local field effects)&lt;/code&gt; and &lt;code&gt;MACROSCOPIC STATIC DIELECTRIC TENSOR (including local field effects in DFT)&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Flags used:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISMEAR =  0 &#xA;SIGMA  =  0.03 &#xA;EDIFF  = 1.E-8 &#xA;#IBRION = 8&#xA;    &#xA;LEPSILON = .TRUE.&#xA;LPEAD = .TRUE.&#xA;LASPH = .TRUE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;PS: independent-particle (IP) approximation&lt;/p&gt;&#xA;" OwnerUserId="8250" LastEditorUserId="7" LastEditDate="2024-01-11T14:33:41.883" LastActivityDate="2024-01-11T14:33:41.883" Title="Dielectric tensor εij (total)" Tags="|vasp|physical-properties-of-materials|dielectric-constants|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12178" PostTypeId="2" ParentId="12177" CreationDate="2024-01-04T01:33:11.843" Score="6" Body="&lt;p&gt;The dielectric tensor can be split in the ionic &lt;span class=&quot;math-container&quot;&gt;$(ϵ_{ij}^{0})$&lt;/span&gt; and electronic &lt;span class=&quot;math-container&quot;&gt;$(ϵ_{ij}^{∞})$&lt;/span&gt; contributions:&lt;span class=&quot;math-container&quot;&gt;$$ϵ_{ij}=ϵ_{ij}^{0}+ϵ_{ij}^{∞}$$&lt;/span&gt; According to VASP &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Dielectric_properties_of_SiC&quot; rel=&quot;noreferrer&quot;&gt;documentation&lt;/a&gt;. To obtain the ionic contributions to the static dielectric properties one needs to compute the force-constant matrices (Hessian of the total energy w.r.t. the ionic positions) and internal strain tensors (second derivative of the total energy w.r.t. strain fields and ionic postions). These properties may be obtained from finite differences (IBRION=5 or 6) or from perturbation theory (IBRION=7 or 8).&lt;/p&gt;&#xA;&lt;p&gt;You may need to add IBRION = 8 in your INCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISMEAR =  0&#xA;SIGMA  =  0.01&#xA;EDIFF  = 1.E-8&#xA;   &#xA;## to get the Born effective charges&#xA;## and the macroscopic dielectric tensor&#xA;LEPSILON = .TRUE.&#xA;LPEAD = .TRUE.&#xA;    &#xA;## to get the ionic contribution&#xA;## to the macroscopic dielectric tensor&#xA;IBRION = 8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then you can search for the following in your OUTCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MACROSCOPIC STATIC DIELECTRIC TENSOR IONIC CONTRIBUTION&#xA;&#xA;ELASTIC MODULI IONIC CONTR (kBar)&#xA;&#xA;PIEZOELECTRIC TENSOR IONIC CONTR  for field in x, y, z        (C/m^2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-04T01:33:11.843" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12179" PostTypeId="1" CreationDate="2024-01-04T03:30:51.983" Score="6" ViewCount="123" Body="&lt;p&gt;I am currently trying to understand the relation between the symmetries of a crystal and its band structure. However, I am having a hard time figuring out how symmetries protect degeneracies in the band structure.&lt;/p&gt;&#xA;&lt;p&gt;For instance, some literatures suggest that mirror symmetries could protect nodal line in nodal-line semimetals, while rotational symmetries (alongside inversion and time reversal symmetries) could protect Dirac nodes in Dirac semimetals, etc.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any documents or papers that show how these symmetries can protect band degeneracies? I am quite new to this field, so perhaps something not mathematically too complicated would be very helpful.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="8619" LastActivityDate="2024-02-27T12:54:00.573" Title="Symmetries and band structure" Tags="|band-structure|symmetry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12180" PostTypeId="2" ParentId="12174" CreationDate="2024-01-04T10:03:14.333" Score="4" Body="&lt;p&gt;The way I like to think about this is the Levy-Lieb functional. The universal functional takes the following form:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$F[\rho] =  \underset{\substack{\Psi \mapsto \rho(\vec{r}) \\  \rho \in \mathcal{D}}}{\mathrm{min}} \bigg[ \langle{\Psi}| T + V_{ee} |{\Psi}\rangle ]\bigg],$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\Psi \mapsto \rho$&lt;/span&gt; constrains the search to any wavefunction that yields the fixed density &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt;.  Here the set  &lt;span class=&quot;math-container&quot;&gt;$\mathcal{D}$&lt;/span&gt; denotes all the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representable densities coming from a particular wavefunction. Note the set of all &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representable densities coming from different wavefunctions is a larger set than &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representable densities.&lt;/p&gt;&#xA;&lt;p&gt;The variational theorem decomposes the energy minimization over &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; in two steps.  The outer step requires defining a set of &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; that define all &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron densities &lt;span class=&quot;math-container&quot;&gt;$\mathcal{N}$&lt;/span&gt;.  For each &lt;span class=&quot;math-container&quot;&gt;$\rho \in \mathcal{N}$&lt;/span&gt;,  the inner loop performs a minimization over all wavefunctions that generate that density.   The ground state energy is given by the minimum energy from this search. Overall:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;    \label{eq:levy_energy}&#xA;    \begin{aligned}&#xA;E_{0} &amp;amp;= \underset{\substack{ \rho  \in \mathcal{N}}}{\mathrm{min}}  \bigg[ \langle{\Psi}| T + V_{ee} + V_{Ne} |{\Psi}\rangle \bigg]  \\ &#xA;&amp;amp;= \underset{\rho \in \mathcal{N}}{\mathrm{min}} \Bigg[ \underset{\substack{\Psi \mapsto \rho(\vec{r}) \\  \rho  \in \mathcal{D}\subset \mathcal{N}}}{\mathrm{min}} \bigg( \langle{\Psi}| T + V_{ee} + V_{Ne} |{\Psi}\rangle \bigg) \Bigg]  \\&#xA;&amp;amp;= \underset{\rho \in \mathcal{N}}{\mathrm{min}} \Bigg[ \underset{\substack{\Psi \mapsto \rho(\vec{r}) \\  \rho  \in \mathcal{D} \subset \mathcal{N}}}{\mathrm{min}} \bigg( \langle{\Psi}| T + V_{ee}  |{\Psi}\rangle \bigg) + \int v_{ext}(\vec{r}) \: \rho(\vec{r}) \: d\vec{r} \Bigg]  \\&#xA;&amp;amp;= \underset{\rho \in \mathcal{N}}{\mathrm{min}} \Bigg[ F[\rho]+ \int v_{ne}(\vec{r}) \: \rho(\vec{r}) \: d\vec{r} \Bigg].&#xA;\end{aligned}&#xA;\end{equation}&lt;/span&gt;&#xA;The minimum of this search is obtained for ground-state density &lt;span class=&quot;math-container&quot;&gt;$\rho_{0}(\vec{r})$&lt;/span&gt; corresponding to the potential &lt;span class=&quot;math-container&quot;&gt;$v_{ne}(\vec{r})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In practice this search is not viable... but is still formally exact and solves the issue of  self-interaction&lt;/p&gt;&#xA;" OwnerUserId="4349" LastActivityDate="2024-01-04T10:03:14.333" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12181" PostTypeId="1" CreationDate="2024-01-04T11:02:13.670" Score="2" ViewCount="47" Body="&lt;p&gt;I am using ORCA-5.0.3 as ESS package and our group has also recently purchased nbo7 which is not interfaced with the ESS. I had tried multiple ways to generate .47 file but couldn't succeed and am currently using Multiwfn to convert .gbw files to .47 files. I have tried NBO calculation using the files generated but could not find particularly the second order perturbation analysis.&lt;/p&gt;&#xA;" OwnerUserId="8621" LastActivityDate="2024-01-04T11:02:13.670" Title="How to generate .47 files from ORCA-5.0.3 ? Also, can we analyze the second order perturbation energy analysis within the nbo scheme using GENNBO?" Tags="|orca|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12182" PostTypeId="1" CreationDate="2024-01-04T22:22:31.620" Score="2" ViewCount="56" Body="&lt;p&gt;I am looking for a software/website that can visualize atomic structure of my quantum espresso input/output files with magnetic moments. Any help will be highly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="7988" LastActivityDate="2024-01-05T16:00:32.740" Title="Visualizing magnetic moments of Quantum espresso input/output files" Tags="|quantum-espresso|atomic-simulation-environment|visualization-software|magnetism|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12183" PostTypeId="2" ParentId="12182" CreationDate="2024-01-04T22:39:49.697" Score="2" Body="&lt;p&gt;I want to add a temporary solution using VESTA. It involves the following steps:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;I import my quantum espresso input file using xcrysden, then I export it as a *.xsf file.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I use vesta to read the *.xsf file and then save it as a *.cif file. This is because I knew that vesta can plot *.mcif file which has magnetic information in it.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;I observe a sample *.mcif file (say &lt;a href=&quot;https://www.cryst.ehu.eus/magndata/index.php?index=1.580&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt;), and notice that It ends with something like:&lt;/p&gt;&#xA;&lt;p&gt;loop_&#xA;_atom_site_moment.label&#xA;_atom_site_moment.crystalaxis_x&#xA;_atom_site_moment.crystalaxis_y&#xA;_atom_site_moment.crystalaxis_z&#xA;_atom_site_moment.symmform&#xA;_atom_site_moment.magnitude&#xA;Fe 2.220517  0.000031 0.00000 mx,my,mz&lt;br /&gt;&#xA;.&#xA;.&#xA;.&lt;/p&gt;&#xA;&lt;p&gt;I make these modifications in my cif file and change the extension.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Open my mcif file using VESTA.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;It is a bit cumbersome but does the job.&lt;/p&gt;&#xA;" OwnerUserId="7988" LastEditorUserId="7988" LastEditDate="2024-01-05T16:00:32.740" LastActivityDate="2024-01-05T16:00:32.740" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12185" PostTypeId="1" CreationDate="2024-01-05T09:39:01.483" Score="2" ViewCount="31" Body="&lt;p&gt;I want to plot a magnetic shielding isosurface around benzene molecule, for that, I prepared a 100 atom grid keeping benzene at the center.&lt;/p&gt;&#xA;&lt;p&gt;At each grid point there is a dummy atom (X with charge=0.0). Now I want to set a magnetic shielding calculation on this molecular cluster (here by cluster I mean benzene molecule surrounded by 100 dummy atoms). The moment I'm putting up my .mol and .dal file for calculation,&lt;/p&gt;&#xA;&lt;p&gt;I'm receiving an error that says the basis set doesn't support element with charge 0. Surprisingly I tried other basis sets too but they all ended up with giving same error somehow. I think somehow I have to edit the basis set to incorporate X atom too but I'm clearly lacking the knowledge for same.&lt;/p&gt;&#xA;&lt;p&gt;I'm attaching all three things, the .mol file, .dal file and the error message I received (the supplied files I'm attaching only contain 9 dummy atoms to keep my question concise).&lt;/p&gt;&#xA;&lt;p&gt;I suspect if I can plot magnetic shielding isosurfaces directly using Multiwfn but I'm not sure how to do it, as dalton output cannot be converted into .wfn file.&lt;/p&gt;&#xA;&lt;p&gt;.mol file&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;BASIS&#xA;SV+DoubleRydberg(Dunning-Hay)&#xA; Benzene using the SV+DoubleRydberg(Dunning-Hay) Basis set&#xA; Using automatic symmetry detection.&#xA;Atomtypes=3&#xA;Charge=6.0 Atoms=6&#xA;C        1.209256425      0.698164522      0.000000000&#xA;C       -1.209256425      0.698164522      0.000000000&#xA;C        1.209256425     -0.698164522      0.000000000&#xA;C       -1.209256425     -0.698164522      0.000000000&#xA;C        0.000000000      1.396329044      0.000000000&#xA;C        0.000000000     -1.396329044      0.000000000&#xA;Charge=1.0 Atoms=6&#xA;H        2.150060899      1.241338238      0.000000000&#xA;H       -2.150060899      1.241338238      0.000000000&#xA;H        2.150060899     -1.241338238      0.000000000&#xA;H       -2.150060899     -1.241338238      0.000000000&#xA;H        0.000000000      2.482676477      0.000000000&#xA;H        0.000000000     -2.482676477      0.000000000&#xA;Charge=0.0 Atoms=9&#xA;X       -0.398701210     -0.101689719      1.433969427&#xA;X        1.274720770      0.101689719     -1.433969427&#xA;X       -1.027638330      0.104867522     -1.478780971&#xA;X        1.510572190     -0.096128562      1.355549224&#xA;X       -2.802139491     -0.073883936      1.041868412&#xA;X        3.318766411     -0.050050408      0.705781827&#xA;X        3.026759891      0.080239544     -1.131491501&#xA;X       -2.779677451      0.081033995     -1.142694387&#xA;X       -4.048782711      0.011916764     -0.168043292&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;.dal file&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;**DALTON INPUT&#xA;.RUN PROPERTIES&#xA;**WAVE FUNCTIONS&#xA;.HF&#xA;**PROPERTIES&#xA;.SHIELD&#xA;.SPIN-S&#xA;**END OF DALTON INPUT&#xA;&lt;/pre&gt;&#xA;&lt;p&gt;Error Message is&lt;/p&gt;&#xA;&lt;pre&gt;&#xA;Output from 'grep -n ERROR' :&#xA;302: ERROR: Nuclear charge    0 is an unsupported element for basis SV+DoubleRydberg(Dunning-Hay)&#xA;303: ERROR: You must choose another basis set, or enter it manually.&#xA;307:  --- SEVERE ERROR, PROGRAM WILL BE ABORTED ---&#xA;&lt;/pre&gt;&#xA;" OwnerUserId="8624" LastEditorUserId="24" LastEditDate="2024-01-05T16:59:15.483" LastActivityDate="2024-01-05T16:59:15.483" Title="How to set up a calculation including dummy atoms in Dalton Quantum Chemistry Package?" Tags="|computational-chemistry|quantum-chemistry|multiwfn|dalton|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12186" PostTypeId="1" CreationDate="2024-01-05T10:28:59.397" Score="2" ViewCount="25" Body="&lt;p&gt;I am currently engaged in research involving metal-organic frameworks (MOFs) and I am seeking assistance with calculating specific geometric features using Zeo++. The features I am interested in are pore limiting diameter, large cavity diameter, gravimetric surface area, and volumetric surface area.&lt;/p&gt;&#xA;&lt;p&gt;I understand that pymatgen offers an interface with Zeo++. Could you please guide me on how to utilize pymatgen for this purpose? Specifically, I am looking for instructions or examples of code to calculate these geometric features of MOFs using the pymatgen-zeo++ integration.&lt;/p&gt;&#xA;&lt;p&gt;In case pymatgen is not feasible for this application, could you also provide the necessary commands or procedures for directly calculating these features in Zeo++?&lt;/p&gt;&#xA;" OwnerUserId="8627" LastEditorUserId="24" LastEditDate="2024-01-05T16:48:30.450" LastActivityDate="2024-01-05T16:48:30.450" Title="Calculating geometric features using Zeo++?" Tags="|geometry|pymatgen|materials-informatics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12188" PostTypeId="1" CreationDate="2024-01-05T21:38:17.440" Score="2" ViewCount="15" Body="&lt;p&gt;I'm studying donor-acceptor charge transfer (CT) process between tetrakis(m2-acetato)-di-Wolframium (acceptor) with an acetonitrile (donor) at the B3LYP-D3BJ/def2-TZVPD level of theory.&lt;/p&gt;&#xA;&lt;p&gt;The W···N distance is 2.61 Å and the angle W-W···N was fixed at 180º. I have partially optimized the adduct to avoid the rotation of the donor. There is a quadruple bond between the Wolframium atoms.&lt;/p&gt;&#xA;&lt;p&gt;The cartesian coordinates of the adduct are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;0 1&#xA;H    0.0000000   0.0000000   0.0000000&#xA;H    0.0000000   0.0000000   1.7650960&#xA;H    1.5429470   0.0000000   0.9065370&#xA;C    0.5213070  -0.3730010   0.8792100&#xA;C    0.5115790  -1.8689030   0.8948480&#xA;O    1.4655670  -2.4948790   1.4672170&#xA;O   -0.4647780  -2.4927580   0.3591350&#xA;H    2.7298470  -3.6680600  -2.9986060&#xA;H    1.9706890  -5.2000210  -3.4371030&#xA;H    3.5225890  -5.1796590  -2.5462560&#xA;C    2.5558000  -4.6963860  -2.6703410&#xA;C    1.8106380  -4.6804330  -1.3731820&#xA;O    2.4639640  -4.6623740  -0.2766710&#xA;O    0.5343070  -4.6600980  -1.3859230&#xA;H   -1.0577910  -4.8324740   5.4363250&#xA;H   -2.6092990  -4.8775190   4.5457670&#xA;H   -1.8106250  -3.3379350   4.8714100&#xA;C   -1.6398010  -4.3907740   4.6303730&#xA;C   -0.8949760  -4.4850660   3.3364290&#xA;O    0.3812400  -4.5107210   3.3493710&#xA;O   -1.5483540  -4.5084530   2.2399960&#xA;H    0.9184040  -9.1694920   0.2023810&#xA;H   -0.6281090  -9.1684040   1.0549360&#xA;H    0.9111970  -9.1680240   1.9674410&#xA;C    0.3935240  -8.7957550   1.0857700&#xA;C    0.4037100  -7.2998970   1.0690450&#xA;O    1.3802450  -6.6758970   1.6044770&#xA;O   -0.5501320  -6.6737680   0.4963230&#xA;W   -0.4821270  -4.5837890   0.4415910&#xA;W    1.4118140  -4.5859810   1.5299720&#xA;N    3.6765230  -4.5886000   2.8313670&#xA;C    4.6704280  -4.5897500   3.4025290&#xA;C    5.9313900  -4.5913140   4.1272610&#xA;H    5.8057380  -5.0702300   5.0985750&#xA;H    6.6884250  -5.1359940   3.5626120&#xA;H    6.2768810  -3.5689200   4.2820320&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Tetrakis(m2-acetato)-di-Wolframiun: atoms 1-30.&lt;/p&gt;&#xA;&lt;p&gt;Acetonitrile: atoms 31-36.&lt;/p&gt;&#xA;&lt;p&gt;When I perform an NBO calculation (v3.1), the program considers the whole assembly as the same molecular unit. There are two artificial NBO, BD W30-N31 and BD* W30-N31, with an occupancy of 1.955 and 0.145 electrons, respectively.&lt;/p&gt;&#xA;&lt;p&gt;Performing the same calculation with NBO v6.0, the program divides the adduct in three molecular units.&lt;/p&gt;&#xA;&lt;p&gt;Unit 1: acetate ion (atoms 1-7). Charge -0.574&lt;/p&gt;&#xA;&lt;p&gt;Unit 2: tris(m2-acetato)-di-Wolframiun ion (atoms 8-30) Charge +0.511&lt;/p&gt;&#xA;&lt;p&gt;Unit 3: Acetonitrile (atoms 31-36) Charge: 0.062&lt;/p&gt;&#xA;&lt;p&gt;I'm only interested on CT process involved on the stability of the noncovalent bond between the N-donor and the W-acceptor. For NBO6.0 calculation the acetonitrile is an independent moiety. Nevertheless, I'm not sure if the results I obtained are reliable due to the di-Wolframiun adduct is divided in two units (1 and 2).&lt;/p&gt;&#xA;&lt;p&gt;So,&lt;/p&gt;&#xA;&lt;p&gt;Can I define molecular units on NBO3.1 or NBO6.0? I want to define the whole tetrakis(m2-acetato)-di-Wolframiun compound as unit 1 and the acetonitrile as unit 2.&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="8630" LastActivityDate="2024-01-05T21:38:17.440" Title="Can I define molecular units on NBO3.1 or NBO6.0?" Tags="|density-functional-theory|computational-chemistry|quantum-chemistry|electronic-structure|gaussian|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12189" PostTypeId="2" ParentId="9281" CreationDate="2024-01-05T23:04:03.803" Score="4" Body="&lt;p&gt;One can start with the definition of the usual, integer coordination number (which as the OP said is not a continuous function of the geometry), and smoothen its discontinuities.&lt;/p&gt;&#xA;&lt;p&gt;The (integer) coordination number of an atom &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$CN_A$&lt;/span&gt;, is the number of atoms that are coordinated to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;. When an atom &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; is sufficiently close to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; is coordinated to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;; when it is sufficiently far from &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, it is said to be not coordinated to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;. This suggests a distance-based criterion, i.e. &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; is coordinated to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; if and only if the distance between &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; (&lt;span class=&quot;math-container&quot;&gt;$R_{AB}$&lt;/span&gt;) is smaller than a cutoff, usually taken as a constant (&lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, often slightly larger than 1) times the sum of atomic (or ionic) radii of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; (i.e. &lt;span class=&quot;math-container&quot;&gt;$R_A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$R_B$&lt;/span&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;CN_A = \sum_{B\neq A} CN_{AB} \tag{1}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;CN_{AB} = \left\{ \begin{array}{cc} 1, &amp;amp; R_{AB} &amp;lt; k(R_A + R_B) \\ 0, &amp;amp; otherwise \end{array} \right. \tag{2}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Of course, if we have access to the wavefunction of the system, we can define coordination numbers by e.g. bond orders instead, a possibility that I'll not discuss here.&lt;/p&gt;&#xA;&lt;p&gt;Now, we can smoothen the Heaviside function Eq. (2):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;CN_A' = \sum_{B\neq A} CN_{AB}', \quad CN_{AB}' = f\left(\frac{R_{AB}}{k(R_A + R_B)}\right) \tag{3}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$f(x)$&lt;/span&gt; is a continuous, monotonic function that quickly approaches 1 when &lt;span class=&quot;math-container&quot;&gt;$x&amp;lt;1$&lt;/span&gt; and quickly approaches 0 when &lt;span class=&quot;math-container&quot;&gt;$x&amp;gt;0$&lt;/span&gt;. There are countless choices for such a function &lt;span class=&quot;math-container&quot;&gt;$f(x)$&lt;/span&gt;. One example, proposed and used in the famous &lt;a href=&quot;https://doi.org/10.1063/1.3382344&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT-D3 paper&lt;/a&gt; by Grimme et al., reads&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;f(x) = \frac{1}{1+exp(-K(1/x-1))} \tag{4}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is a positive parameter. However, &lt;span class=&quot;math-container&quot;&gt;$f(x)$&lt;/span&gt; does not decay to exactly zero when &lt;span class=&quot;math-container&quot;&gt;$x\to +\infty$&lt;/span&gt;, but approaches a very small positive number, meaning that &lt;a href=&quot;https://doi.org/10.1002/jcc.23037&quot; rel=&quot;nofollow noreferrer&quot;&gt;the coordination number of an atom in a bulk environment is always infinite&lt;/a&gt;, although in realistically sized finite systems this divergence may not be numerically obvious. In the revised &lt;a href=&quot;https://doi.org/10.1063/1.5090222&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT-D4 model&lt;/a&gt;, they used the following form&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;f(x) = \frac{C}{2}(1+erf(-K(x-1))) \tag{5}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where, again, &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; is a positive parameter, and &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; is a parameter that depends on the electronegativity difference of the atoms &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt;. One may argue that only when &lt;span class=&quot;math-container&quot;&gt;$C=1$&lt;/span&gt; can the resulting &lt;span class=&quot;math-container&quot;&gt;$CN_A'$&lt;/span&gt; be interpreted as a coordination number, since only in this case does &lt;span class=&quot;math-container&quot;&gt;$CN_A'$&lt;/span&gt; reduce to &lt;span class=&quot;math-container&quot;&gt;$CN_A$&lt;/span&gt; in the &lt;span class=&quot;math-container&quot;&gt;$K\to +\infty$&lt;/span&gt; limit. The reason Grimme et al. allowed &lt;span class=&quot;math-container&quot;&gt;$C$&lt;/span&gt; to be different than 1 is that they use &lt;span class=&quot;math-container&quot;&gt;$CN_A'$&lt;/span&gt; solely for calculating the DFT-D dispersion coefficients &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt;, so it does not matter if &lt;span class=&quot;math-container&quot;&gt;$CN_A'$&lt;/span&gt; does not satisfy all properties that an ideal &amp;quot;smooth coordination number&amp;quot; has to satisfy. In any case, one notices that Eq. (5) correctly vanishes in the &lt;span class=&quot;math-container&quot;&gt;$x\to +\infty$&lt;/span&gt; limit, meaning that it is safe to use in huge finite systems or periodic systems.&lt;/p&gt;&#xA;&lt;p&gt;Finally, it is clear that the continuous coordination number &lt;span class=&quot;math-container&quot;&gt;$CN_A'$&lt;/span&gt; defined by Eq. (5) can be used in contexts other than the determination of &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt;. For example, the very &lt;a href=&quot;https://doi.org/10.1063/1.5090222&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFT-D4 paper&lt;/a&gt; itself used Eq. (5) in the calculation of atomic charges. Using the coordination numbers in yet other contexts may or may not have literature precedents, but since there is considerable flexibility in tuning the parameters &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; (or even the function &lt;span class=&quot;math-container&quot;&gt;$f(x)$&lt;/span&gt;), it is plausible that for most applications one can define a continuous coordination number that suits the particular application. However one may need to perform some fitting or hand-tuning to determine the optimum form of &lt;span class=&quot;math-container&quot;&gt;$f(x)$&lt;/span&gt;. For example, the &lt;span class=&quot;math-container&quot;&gt;$K$&lt;/span&gt; in Eq. (5) controls how smooth the coordination number changes when &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; dissociates from &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;, and the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; in Eq. (3) determines the bond distance at which &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; contributes half a coordination number to &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt;. The fitted parameters are not necessarily transferable to other applications, since different applications may have different requirements on the smoothness, turning point etc. of the coordination number function.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2024-01-05T23:04:03.803" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12190" PostTypeId="1" CreationDate="2024-01-06T14:12:59.927" Score="6" ViewCount="122" Body="&lt;p&gt;I've run a molecular dynamics simulation (NVT) of a simple Lennard-Jones system of a few particles and I'm trying to calculate the Helmholtz free energy &lt;span class=&quot;math-container&quot;&gt;$\Delta F$&lt;/span&gt; as a function of temperature over the phase transition. To properly sample the potential energy histograms I've run a replica-exchange MD simulation of 9 replicas, with approximately equal overlap for a series of temperatures of the bound system up to the unbound (melted) system.&lt;/p&gt;&#xA;&lt;p&gt;However, as for the difference in free energy &lt;span class=&quot;math-container&quot;&gt;$\Delta F$&lt;/span&gt; calculation I'm quite confused. I'm thinking of first trying with free energy perturbation (FEP) since this should be simplest and then attempting e.g. WHAM. From what I've read, FEP relies on some coupling parameter often denoted &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;, two forms of FEP equations (Zwanzig equation) for the free energy are:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\Delta F = F(\lambda = 1) - F(\lambda = 0) = -\frac{1}{\beta} \sum_{i=1}^{n} \ln{\langle e^{-\beta (U_{\lambda{i+1}} - U_{\lambda_{i}})} \rangle_{\lambda_{i}}}&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;called &amp;quot;windowing&amp;quot;, where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the number of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;s sampled or intervals from 0 to 1, &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is the potential energy and &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; the inverse temperature. The &amp;quot;integration&amp;quot; scheme:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\Delta F = F(\lambda = 1) - F(\lambda = 0) = \sum_{\lambda = 0}^{\lambda = 1} \left\langle \frac{dU_{\lambda}}{d\lambda} \right\rangle_{\lambda} \Delta \lambda = \sum_{\lambda = 0}^{\lambda = 1} \langle U_f - U_i \rangle_{\lambda} \Delta \lambda&#xA;\end{equation}&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$U_f, U_i$&lt;/span&gt; are then the potential energy at the next &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; and the current, respectively? Similar to the summing above, in windowing.&lt;/p&gt;&#xA;&lt;p&gt;I can sort of intuitively understand the process for when &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; represents how much one potential is &amp;quot;turned&amp;quot; on. Like when one gradually (by increasing &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;) inserts a molecule in a solution and one then samples the energy during that process for different &amp;quot;amounts&amp;quot; of &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;, this is the type of scenario I've read about in articles.&lt;/p&gt;&#xA;&lt;p&gt;The problem I have is that I don't know exactly what my &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; is. Since I've only sampled over a range of temperatures and while this corresponds to my particles being closer or farther from each other my potential is the same over the whole simulation, only the temperature changes. In some sense then I believe my situation is simpler than the other and my naive approach was to simply take &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt; to be the temperature &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; in my case. And, for the first equation I took &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; to be the temperature at &lt;span class=&quot;math-container&quot;&gt;$\lambda_i$&lt;/span&gt; i.e. &lt;span class=&quot;math-container&quot;&gt;$T_i$&lt;/span&gt; since it is here the average is supposed to be taken.&lt;/p&gt;&#xA;&lt;p&gt;The two figures below are the results of my attempt at calculating &lt;span class=&quot;math-container&quot;&gt;$\Delta F$&lt;/span&gt; but I'm quite sure neither is correct since they should be concave down (&lt;span class=&quot;math-container&quot;&gt;$\frac{d^2F}{dT^2} = -C_v/T &amp;lt; 0$&lt;/span&gt; since &lt;span class=&quot;math-container&quot;&gt;$ C_v &amp;gt; 0$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Using the first equation (windowing) my process was (in reduced LJ units):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Calculate the average potential energy difference of each neighbouring temperature pair &lt;span class=&quot;math-container&quot;&gt;$T_{i+1}, T_i$&lt;/span&gt; as &lt;span class=&quot;math-container&quot;&gt;$T_i \ln \langle exp(\frac{1}{T_i}(U_{T_i+1} - U_{T_i}))\rangle$&lt;/span&gt; from my lowest temperature to my highest and sum these contributions. But I feel like I perhaps should take the difference in temperature as well here?&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DFDgR.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DFDgR.jpg&quot; alt=&quot;![FEP&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the second equation, integration (less sure):&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Summed the pairwise average difference in potential energy, again between neighbouring temperatures and multiplied by the difference in temperature &lt;span class=&quot;math-container&quot;&gt;$\Delta T$&lt;/span&gt; i.e. summing terms of &lt;span class=&quot;math-container&quot;&gt;$\langle U_{T_{i+1}} - U_{T_i} \rangle (T_{i+1} - T_i)$&lt;/span&gt; from the lowest to the highest temperatures.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Djz78.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Djz78.jpg&quot; alt=&quot;FEP&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I might have misunderstood something essential when using replica-exchange but my impression is that it just improves sampling.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit:&lt;/strong&gt; Since, (if correct), my perturbation is the temperature, meaning the kinetic energy changes with perturbation, shouldn't I consider the total energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; not just potential &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit 2:&lt;/strong&gt; The figures are now updated, looking more like what I'd expect but I'm still not sure if they're correct/reasonable. Now scaled with the respective temperature at each point, included is also a comparison between full energy &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt; and potential only &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;. They're also both concave down now and look qualitatively similar. Though the integration seem to give half as large values. From what I can gather there should be a &amp;quot;break&amp;quot; at about the the phase change temperature as the phases here are in equilibrium and past this point one of the two curves takes over as the one lowest in free energy but I'm not quite sure I can see one.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit 3:&lt;/strong&gt; From what I can read I've now realised, I believe, that integration (thermodynamic) is explicitly for systems in which the potential function changes with &lt;span class=&quot;math-container&quot;&gt;$\lambda$&lt;/span&gt;. Meaning it is not applicable for me in my case where only temperature changes? However, the first option (windom method) should still be viable.&lt;/p&gt;&#xA;" OwnerUserId="8634" LastEditorUserId="8634" LastEditDate="2024-01-06T23:47:56.200" LastActivityDate="2024-01-06T23:47:56.200" Title="Free energy calculation as a function of temperature over phase transition" Tags="|molecular-dynamics|computational-chemistry|statistical-thermodynamics|free-energy|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12191" PostTypeId="2" ParentId="9907" CreationDate="2024-01-06T18:18:55.283" Score="0" Body="&lt;p&gt;I apologize for the delay in responding. I have been occupied with my doctoral studies, and the topic of non-covalent interactions forms a crucial component of my research.&lt;/p&gt;&#xA;&lt;p&gt;In addressing this matter, we propose the incorporation of harmonic restraints, specifically a repulsive energy, between the drug and the terminal regions of the DNA. To illustrate, in my work, I employ AMBER, and the harmonic restraint is implemented as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;amp;rst&#xA;  iresid=0, fxyz=1,1,1, outxyz=0,&#xA;  iat=-1,-1,&#xA;  r1=0.0, r2=13.0, r3=13.0, r4=20.0, rk2=65.0, rk3=0.0,&#xA;  !! Atoms of the other terminal DNA nucleobases&#xA;  igr1=indexes of the nucleobases at the terminal&#xA;  !! All drug atoms&#xA;  igr2=indexes of all the drug&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Instead, we have to apply a positive force constant only on the left side of the parabola:&lt;/p&gt;&#xA;&lt;p&gt;r1=0.0, r2=13.0, r3=13.0, r4=20.0, rk2=65.0, rk3=0.0,&lt;/p&gt;&#xA;&lt;p&gt;Now the potential is truly repulsive at short distances and null at long distances.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-01-06T18:18:55.283" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12192" PostTypeId="1" CreationDate="2024-01-06T22:24:46.463" Score="3" ViewCount="91" Body="&lt;p&gt;This is a follow-up to a series of questions that I have asked here:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11963/5&quot;&gt;Is a D-Wave quantum computer able to do TD-DFT calculations?&lt;/a&gt; (answer was &amp;quot;yes, but it might not be efficient&amp;quot;)&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12074/5&quot;&gt;Inquiry about A Matrix Output in 21-matrix_A_B.py&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12098/5&quot;&gt;A matrix form used in the Quantum Annealer Eigensolver (QAE)&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;I calculate the A-matrix using this code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy&#xA;from pyscf import gto, scf, dft, tddft&#xA;mol = gto.Mole()&#xA;mol.atom = [['H' , (0. , 0. , .917)],['F' , (0. , 0. , 0.)], ]&#xA;mol.basis = 'sto3g'&#xA;mol.build()&#xA;mf = scf.RHF(mol).run()&#xA;a, b = tddft.TDHF(mf).get_ab()&#xA;nocc, nvir = a.shape[:2]&#xA;a = a.reshape(nocc*nvir,nocc*nvir)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But how can I confirm the correctness of this A-matrix?&#xA;I attempted to utilize the A-matrix computed using the sto3g method within the (&lt;a href=&quot;https://github.com/randylewis/QuantumAnnealing/blob/main/AQAE.py&quot; rel=&quot;nofollow noreferrer&quot;&gt;AQAE&lt;/a&gt;) script. It resulted in a minimum eigenvalue of value=0.5, which significantly contrasts with the output from the following script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf &#xA;mol = pyscf.M(atom = ‘H 0 0 0.917; F 0 0 0', basis = 'sto3g', &#xA;symmetry = True,)&#xA;myhf = mol.RHF().run()&#xA;cisolver = pyscf.fci.FCI(myhf)&#xA;print('E(FCI) = %.12f' % cisolver.kernel()[0])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8425" LastEditorUserId="5" LastEditDate="2024-01-08T03:15:24.737" LastActivityDate="2024-01-14T10:07:43.140" Title="How may I verify that my A matrix for TDA (Tamm-Dancoff Approximation of TD-DFT) from PySCF is correct?" Tags="|density-functional-theory|quantum-chemistry|python|pyscf|td-dft|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12193" PostTypeId="1" CreationDate="2024-01-07T14:37:13.910" Score="4" ViewCount="100" Body="&lt;p&gt;I have a structure, as depicted in the figure, which is a part of a longer chain. The portion within the red circle is predominantly parallel. My objective is to rotate this part, aiming to orient the structures perpendicular to each other. I am interested in assessing the ease with which I can execute this rotation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/I8JdM.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/I8JdM.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I tried to define a harmonic constrain to a dihedral or an angle, but it didn't rortate as I want.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have an idea?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-01-12T17:10:22.120" Title="How to perform a rotation of a structure, specifically throughout molecular dynamics or umbrella sampling simulations?" Tags="|molecular-dynamics|intermolecular-forces|enhanced-sampling|" AnswerCount="0" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="12194" PostTypeId="2" ParentId="9281" CreationDate="2024-01-08T09:43:30.453" Score="4" Body="&lt;p&gt;Continuous coordination numbers are very commonly used in the enhanced sampling/free energy world, where they form the basis of different types of collective variables (e.g., coarse-grained reaction coordinates). As explained by wzkchem5, these are always based on some sort of distance-dependent switching function that smoothly interpolates between 1 and 0. Several functional forms have been proposed, and each of them has a few parameters that must be set by the user. This means that selecting an appropriate switching function is system- and purpose-dependent.&lt;/p&gt;&#xA;&lt;p&gt;The PLUMED package has such an implementation of &lt;a href=&quot;https://www.plumed.org/doc-v2.8/user-doc/html/_c_o_o_r_d_i_n_a_t_i_o_n.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;coordination numbers&lt;/a&gt;, as well as a description of several possible &lt;a href=&quot;https://www.plumed.org/doc-v2.8/user-doc/html/switchingfunction.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;switching functions&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;This is the case for coordination numbers of single atoms. It is also possible to calculate such a continuous coordination number for a large number of atoms (in, say, a liquid) and calculate derived quantities from it. For example, you could count the number of atoms that has a coordination number higher or lower than some threshold value. A coordination number of 5 is the so-called &lt;a href=&quot;https://doi.org/10.1063/1.477658&quot; rel=&quot;nofollow noreferrer&quot;&gt;ten Wolde-Frenkel criterion&lt;/a&gt;, used to distinguish between &amp;quot;vapor&amp;quot; and &amp;quot;liquid&amp;quot; atoms. Such a quantity can, again, be implemented in a continuous manner, again using switching functions.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2024-01-10T09:09:30.877" LastActivityDate="2024-01-10T09:09:30.877" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12195" PostTypeId="1" AcceptedAnswerId="12200" CreationDate="2024-01-08T09:56:34.570" Score="9" ViewCount="386" Body="&lt;p&gt;I am wondering what is the best approach to quantify the contribution of relativistic corrections to a result of an electronic structure calculation. As far as I understand, from a user perspective one can simply &amp;quot;turn on&amp;quot; some relativistic effects in most electronic structure codes, and the result &lt;em&gt;should&lt;/em&gt; contain an approximation to relativistic effects. A small caveat is that a specially contracted/parametrized basis set should be used for the relativistic calculation (Gaussian-type orbitals).&lt;/p&gt;&#xA;&lt;p&gt;What I am wondering is whether I can just take the difference between a result obtained with relativistic correction and one without, and assume that what I obtain corresponds to the magnitude of the relativistic correction, even if the basis set used in the calculation are different? Or, if I am interested in quantifying such a difference, should I use the same basis set for the relativistic and the non-relativistic calculation, and, if so, should it be the relativistic one? I could also imagine that the right approach should be to converge both the relativistic and the ''standard'' calculation with respect to their own basis sets, but that might not be computationally feasible for some larger calculations, so I am wondering about the approach that maximizes the error cancellation due to the finite basis.&lt;/p&gt;&#xA;&lt;p&gt;As an example, calculating the dipole polarizability of a single Argon atom with PBE0 functional with aug-cc-pVDZ basis set (as implemented in NWChem) I get &lt;span class=&quot;math-container&quot;&gt;$9.98$&lt;/span&gt; a.u. for the isotropic term, whereas if I add a DK2 correction with the aug-cc-pVDZ-DK basis set I obtain &lt;span class=&quot;math-container&quot;&gt;$10.0$&lt;/span&gt; a.u. Can I say that the difference of 0.02 a.u. in the results is due to the DK2 correction, or is a large portion of the difference due to the difference in the aug-cc-pVDZ and the aug-cc-pVDZ-DK basis sets?&lt;/p&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5" LastEditDate="2024-01-08T19:25:25.200" LastActivityDate="2024-01-09T06:14:24.027" Title="Quantifying relativistic effects in DFT calculations" Tags="|electronic-structure|ab-initio-calculations|basis-sets|relativistic|nwchem|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12197" PostTypeId="2" ParentId="12195" CreationDate="2024-01-08T13:30:25.173" Score="7" Body="&lt;p&gt;In reality, the contribution to an energy due to relativity, would be the difference between the &amp;quot;exact&amp;quot; energy with a model that captures all relativistic effects, versus a model that captures everything except any relativistic effects.&lt;/p&gt;&#xA;&lt;p&gt;For an energy to be &amp;quot;exact&amp;quot;, when using Gaussian-type orbitals as you described, you need the energy to be &lt;strong&gt;converged to its CBS (complete basis set) limit&lt;/strong&gt; and to its &lt;strong&gt;full correlation&lt;/strong&gt; limit (this means using &amp;quot;the exact density functional&amp;quot; or &amp;quot;full configuration interaction&amp;quot;), in extremely large basis sets, and extrapolating to the CBS limit.&lt;/p&gt;&#xA;&lt;p&gt;However, no quantum mechanical model will be able to capture &amp;quot;all&amp;quot; relativistic effects because we don't yet have a quantum mechanical model that perfectly captures the relativistic effects associated with gravity (general relativistic effects). Ignoring gravity (its effect on the interaction energy between two atoms is anticipated to be something like &lt;span class=&quot;math-container&quot;&gt;$10^{-40}$&lt;/span&gt; in atomic units anyway), we still don't have a simple model that captures all remaining relativistic effects (special relativity effects), because the Dirac equation only works for one electron, the Dirac-Coulomb-Breit equation works for many electrons but only approximates the true relativistic behavior, and QED (quantum electrodynamics) doesn't provide us with an easy way to calculate molecular energies.&lt;/p&gt;&#xA;&lt;p&gt;The best that you can likely do today, is to calculate an approximation of the relativistic effects on an energy, by using something like the X2C (exact 2-component) Hamiltonian, which for quantum chemistry purposes is quite a good approximation to the effects of special relativity. You mentioned the DK2 (Douglas-Kroll) Hamiltonian, which is part of a series of more and more accurate Hamiltonians (DK2,DK3,DK4,etc.), but the X2C Hamiltonian is equivalent to a an &amp;quot;infinite-order&amp;quot; DK Hamiltonian, and is just as easy to use as any of the DK Hamiltonians, so the DK method is now obsolete and there is no reason to use it now that the X2C Hamiltonian is implemented in a lot of quantum chemistry packages and is superior to the DK Hamiltonian in every conceivable way.&lt;/p&gt;&#xA;&lt;p&gt;Since it's unlikely for you to be able to get energies at the CBS limit and full correlation limit for a system that's large enough for you to need to use DFT instead of a wavefunction-based method, the best estimate you can get for the contribution of relativity to an energy, is likely by doing an energy calculation with the X2C model and with the non-relativistic model, using the same basis set in both cases and the same density functional in both cases. Although X2C basis sets such as aug-cc-pVDZ-X2C exist, you don't need to use them for this type of comparison. If you do want to use it, you can still compare the energy that you get with the X2C model and an X2C basis set, to the energy that you get with a non-relativistic model and an equivalent &amp;quot;standard&amp;quot; basis set, since this &amp;quot;effect of relativity on the energy&amp;quot; will only be approximate anyway.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-08T13:30:25.173" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12198" PostTypeId="1" AcceptedAnswerId="12214" CreationDate="2024-01-08T16:54:23.077" Score="4" ViewCount="55" Body="&lt;p&gt;I'm studying some topological materials through first principles methods (very trendy I know) and have a question about extracting the Fermi velocity. I'd like to use a wannierised model to analytically calculate the Fermi velocity of a surface states of a slab, but I can't find any existing packages with this functionality. PythTB has nice slab functionalities for TIs and W90 can tell you the Fermi velocity, but only in the bulk.&lt;/p&gt;&#xA;&lt;p&gt;It's clear to me that the velocity operator is constructed as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\hbar v^\alpha_{n} = [U^\dagger \frac{\partial H}{\partial k_\alpha} U]_{nn}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;with &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; transforming between Wannier/Bloch basis and the derivative analytically expressible as (&lt;a href=&quot;https://journals.aps.org/prb/pdf/10.1103/PhysRevB.75.195121&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://journals.aps.org/prb/pdf/10.1103/PhysRevB.75.195121&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\left[ \frac{\partial H}{\partial k_\alpha}\right] _ {ij} = \sum_{R} \exp(ikR) (iR_\alpha)\langle0i|H|Rj\rangle&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;but I'd like to avoid reinventing the wheel if possible. So if anyone knows any packages that implement both slab models and the velocity operator I'd greatly appreciate it. Does this exist? Is this utterly trivial and I'm just being silly/lazy?&lt;/p&gt;&#xA;&lt;p&gt;Many thanks&lt;/p&gt;&#xA;" OwnerUserId="5154" LastEditorUserId="5154" LastEditDate="2024-01-16T17:23:16.177" LastActivityDate="2024-01-16T17:29:26.163" Title="Tight binding packages for Fermi velocity of slabs" Tags="|tight-binding|topological-insulators|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12199" PostTypeId="1" CreationDate="2024-01-08T21:20:40.243" Score="2" ViewCount="99" Body="&lt;p&gt;I am trying to build a supercell for molecular crystals from a .cif file. With the ASE package, the supercell has the perfect PBC, but the atom sequence is very random and might be difficult to match with the force field topology to run the simulation in GROMACS. With Mercury, it extends the cell but doesn't provide the cell size for PBC. If I multiply the cell size just by the original cell size, it does not fulfill the PBC condition. Do you have any suggestions or other tools to fix this? I appreciate your help.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;####################################################################### &#xA;# &#xA;# This file contains crystal structure data downloaded from the &#xA;# Cambridge Structural Database (CSD) hosted by the Cambridge &#xA;# Crystallographic Data Centre (CCDC).&#xA;# &#xA;# Full information about CCDC data access policies and citation &#xA;# guidelines are available at http://www.ccdc.cam.ac.uk/access/V1 &#xA;# &#xA;# Audit and citation data items may have been added by the CCDC. &#xA;# Please retain this information to preserve the provenance of &#xA;# this file and to allow appropriate attribution of the data. &#xA;# &#xA;#######################################################################&#xA;&#xA;data_urea_310&#xA;_audit_block_doi                 10.5517/ccdc.csd.ccsknnm&#xA;_database_code_depnum_ccdc_archive 'CCDC 731961'&#xA;loop_&#xA;_citation_id&#xA;_citation_doi&#xA;_citation_year&#xA;1 10.1021/jp904942c 2009&#xA;_audit_update_record             &#xA;;&#xA;2009-05-13 deposited with the CCDC. 2023-11-08 downloaded from the CCDC.&#xA;;&#xA;&#xA;_audit_creation_method           SHELXL-97&#xA;_chemical_name_systematic        &#xA;;&#xA;urea&#xA;;&#xA;_chemical_name_common            urea&#xA;_chemical_melting_point          405&#xA;_chemical_formula_moiety         'C H4 N2 O'&#xA;_chemical_formula_sum            'C H4 N2 O'&#xA;_chemical_formula_weight         60.06&#xA;&#xA;_symmetry_cell_setting           orthorhombic&#xA;_symmetry_space_group_name_H-M   'P 21 21 2'&#xA;_symmetry_space_group_name_Hall  'P 2 2ab'&#xA;&#xA;loop_&#xA;_symmetry_equiv_pos_as_xyz&#xA;'x, y, z'&#xA;'-x, -y, z'&#xA;'-x+1/2, y+1/2, -z'&#xA;'x+1/2, -y+1/2, -z'&#xA;&#xA;_cell_length_a                   3.414(3)&#xA;_cell_length_b                   7.360(8)&#xA;_cell_length_c                   4.606(10)&#xA;_cell_angle_alpha                90.00&#xA;_cell_angle_beta                 90.00&#xA;_cell_angle_gamma                90.00&#xA;_cell_volume                     115.7(3)&#xA;_cell_formula_units_Z            2&#xA;_cell_measurement_temperature    296(2)&#xA;_cell_measurement_pressure       3100000&#xA;_cell_measurement_reflns_used    95&#xA;_cell_measurement_theta_min      5.54&#xA;_cell_measurement_theta_max      26.59&#xA;&#xA;_exptl_crystal_description       plate&#xA;_exptl_crystal_colour            colourless&#xA;_exptl_crystal_size_max          0.37&#xA;_exptl_crystal_size_mid          0.37&#xA;_exptl_crystal_size_min          0.10&#xA;_exptl_crystal_density_meas      ?&#xA;_exptl_crystal_density_diffrn    1.723&#xA;_exptl_crystal_density_method    'not measured'&#xA;_exptl_crystal_F_000             64&#xA;_exptl_absorpt_coefficient_mu    0.148&#xA;_exptl_absorpt_correction_type   integration&#xA;_exptl_absorpt_correction_T_min  0.69&#xA;_exptl_absorpt_correction_T_max  0.95&#xA;_exptl_absorpt_process_details   &#xA;;&#xA;Katrusiak, A. (2003). REDSHABS - Program for correcting&#xA;reflections intensities for DAC absorption, gasket shadowing&#xA;and sample crystal absorption. Adam Mickiewicz University, Pozna\'n.&#xA;Katrusiak, A. (2004). Z. Kristallogr. 219, 461-467&#xA;;&#xA;&#xA;_exptl_special_details           &#xA;;&#xA;Data were collected at room temperature and pressure of 3.10(5) GPa&#xA;(3100000 kPa) with the crystal obtained by the in-situ high-pressure&#xA;crystallization technique. Pressure was determined by monitoring&#xA;the shift of the ruby R1-fluorescence line.&#xA;;&#xA;&#xA;_diffrn_ambient_temperature      296(2)&#xA;_diffrn_radiation_wavelength     0.71073&#xA;_diffrn_radiation_type           MoK\a&#xA;_diffrn_radiation_source         'fine-focus sealed tube'&#xA;_diffrn_radiation_monochromator  graphite&#xA;_diffrn_measurement_device_type  'Kuma KM4CCD \k geometry'&#xA;_diffrn_measurement_method       &#xA;;HP omega scans - for more details see:&#xA;A. Budzianowski, A. Katrusiak in High-Pressure Crystallography&#xA;(Eds.: A. Katrusiak, P. F. McMillan),&#xA;Dordrecht: Kluwer Acad. Publ., 2004 pp.157-168&#xA;;&#xA;_diffrn_detector_area_resol_mean 16.4&#xA;_diffrn_reflns_number            327&#xA;_diffrn_reflns_av_R_equivalents  0.1123&#xA;_diffrn_reflns_av_sigmaI/netI    0.0705&#xA;_diffrn_reflns_limit_h_min       -4&#xA;_diffrn_reflns_limit_h_max       4&#xA;_diffrn_reflns_limit_k_min       -7&#xA;_diffrn_reflns_limit_k_max       8&#xA;_diffrn_reflns_limit_l_min       -2&#xA;_diffrn_reflns_limit_l_max       2&#xA;_diffrn_reflns_theta_min         5.54&#xA;_diffrn_reflns_theta_max         26.59&#xA;_diffrn_measured_fraction_theta_max 0.419&#xA;_diffrn_reflns_theta_full        26.59&#xA;_diffrn_measured_fraction_theta_full 0.419&#xA;_diffrn_standards_number         ?&#xA;_diffrn_standards_interval_count ?&#xA;_diffrn_standards_interval_time  ?&#xA;_diffrn_standards_decay_%        ?&#xA;_refine_special_details          &#xA;;&#xA;Refinement of F^2^ against ALL reflections. The weighted R-factor wR and&#xA;goodness of fit S are based on F^2^, conventional R-factors R are based&#xA;on F, with F set to zero for negative F^2^. The threshold expression of&#xA;F^2^ &amp;gt; 2sigma(F^2^) is used only for calculating R-factors(gt) etc. and is&#xA;not relevant to the choice of reflections for refinement. R-factors based&#xA;on F^2^ are statistically about twice as large as those based on F, and R-&#xA;factors based on ALL data will be even larger.&#xA;;&#xA;_reflns_number_total             95&#xA;_reflns_number_gt                69&#xA;_reflns_threshold_expression     &amp;gt;2sigma(I)&#xA;_refine_ls_structure_factor_coef Fsqd&#xA;_refine_ls_matrix_type           full&#xA;_refine_ls_number_reflns         95&#xA;_refine_ls_number_parameters     20&#xA;_refine_ls_number_restraints     0&#xA;_refine_ls_R_factor_all          0.0573&#xA;_refine_ls_R_factor_gt           0.0332&#xA;_refine_ls_wR_factor_ref         0.0839&#xA;_refine_ls_wR_factor_gt          0.0661&#xA;_refine_ls_goodness_of_fit_ref   1.217&#xA;_refine_ls_restrained_S_all      1.217&#xA;_refine_ls_shift/su_max          0.000&#xA;_refine_ls_shift/su_mean         0.000&#xA;_refine_ls_weighting_scheme      calc&#xA;_refine_ls_weighting_details     &#xA;'calc w=1/[\s^2^(Fo^2^)+(0.0244P)^2^+0.0087P] where P=(Fo^2^+2Fc^2^)/3'&#xA;_atom_sites_solution_primary     direct&#xA;_atom_sites_solution_secondary   difmap&#xA;_atom_sites_solution_hydrogens   geom&#xA;_refine_ls_hydrogen_treatment    constr&#xA;_refine_ls_extinction_method     none&#xA;_refine_ls_extinction_coef       ?&#xA;_refine_diff_density_max         0.206&#xA;_refine_diff_density_min         -0.196&#xA;_refine_diff_density_rms         0.059&#xA;_refine_ls_abs_structure_details 'Flack H D (1983), Acta Cryst. A39, 876-881'&#xA;_refine_ls_abs_structure_Flack   7(8)&#xA;loop_&#xA;_atom_type_symbol&#xA;_atom_type_description&#xA;_atom_type_scat_dispersion_real&#xA;_atom_type_scat_dispersion_imag&#xA;_atom_type_scat_source&#xA;C C 0.0033 0.0016 'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;H H 0.0000 0.0000 'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;N N 0.0061 0.0033 'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;O O 0.0106 0.0060 'International Tables Vol C Tables 4.2.6.8 and 6.1.1.4'&#xA;&#xA;_computing_data_collection       'CrysAlis (Oxford Diffraction, 2002)'&#xA;_computing_cell_refinement       'CrysAlis (Oxford Diffraction, 2002)'&#xA;_computing_data_reduction        'CrysAlis (Oxford Diffraction, 2002)'&#xA;_computing_structure_solution    'SHELXS-97 (Sheldrick, 1990)'&#xA;_computing_structure_refinement  'SHELXL-97 (Sheldrick, 1997)'&#xA;_computing_molecular_graphics    &#xA;;X-Seed (Barbour, 2001)&#xA;and POV-Ray (Persistence of Vision, 2004)&#xA;;&#xA;_computing_publication_material  'SHELXL-97 (Sheldrick, 1997)'&#xA;&#xA;loop_&#xA;_atom_site_label&#xA;_atom_site_type_symbol&#xA;_atom_site_fract_x&#xA;_atom_site_fract_y&#xA;_atom_site_fract_z&#xA;_atom_site_U_iso_or_equiv&#xA;_atom_site_adp_type&#xA;_atom_site_occupancy&#xA;_atom_site_symmetry_multiplicity&#xA;_atom_site_calc_flag&#xA;_atom_site_refinement_flags&#xA;_atom_site_disorder_assembly&#xA;_atom_site_disorder_group&#xA;C1 C 0.0000 0.5000 0.870(4) 0.023(8) Uani 1 2 d S . .&#xA;O1 O 0.0000 0.5000 1.136(3) 0.046(6) Uani 1 2 d S . .&#xA;N1 N 0.1270(9) 0.6429(4) 0.7181(19) 0.044(2) Uani 1 1 d . . .&#xA;H1A H 0.2115 0.7379 0.8070 0.053 Uiso 1 1 calc R . .&#xA;H1B H 0.1244 0.6399 0.5315 0.053 Uiso 1 1 calc R . .&#xA;&#xA;loop_&#xA;_atom_site_aniso_label&#xA;_atom_site_aniso_U_11&#xA;_atom_site_aniso_U_22&#xA;_atom_site_aniso_U_33&#xA;_atom_site_aniso_U_23&#xA;_atom_site_aniso_U_13&#xA;_atom_site_aniso_U_12&#xA;C1 0.023(3) 0.032(5) 0.01(2) 0.000 0.000 0.007(3)&#xA;O1 0.053(3) 0.036(3) 0.05(2) 0.000 0.000 0.001(2)&#xA;N1 0.0442(19) 0.0171(18) 0.071(8) 0.007(3) -0.003(3) -0.0087(18)&#xA;&#xA;_geom_special_details            &#xA;;&#xA;All esds (except the esd in the dihedral angle between two l.s. planes)&#xA;are estimated using the full covariance matrix. The cell esds are taken&#xA;into account individually in the estimation of esds in distances, angles&#xA;and torsion angles; correlations between esds in cell parameters are only&#xA;used when they are defined by crystal symmetry. An approximate (isotropic)&#xA;treatment of cell esds is used for estimating esds involving l.s. planes.&#xA;;&#xA;&#xA;loop_&#xA;_geom_bond_atom_site_label_1&#xA;_geom_bond_atom_site_label_2&#xA;_geom_bond_distance&#xA;_geom_bond_site_symmetry_2&#xA;_geom_bond_publ_flag&#xA;C1 O1 1.225(13) . ?&#xA;C1 N1 1.336(9) 2_565 ?&#xA;C1 N1 1.336(9) . ?&#xA;N1 H1A 0.8600 . ?&#xA;N1 H1B 0.8600 . ?&#xA;&#xA;loop_&#xA;_geom_angle_atom_site_label_1&#xA;_geom_angle_atom_site_label_2&#xA;_geom_angle_atom_site_label_3&#xA;_geom_angle&#xA;_geom_angle_site_symmetry_1&#xA;_geom_angle_site_symmetry_3&#xA;_geom_angle_publ_flag&#xA;O1 C1 N1 121.6(6) . 2_565 ?&#xA;O1 C1 N1 121.6(6) . . ?&#xA;N1 C1 N1 116.8(12) 2_565 . ?&#xA;C1 N1 H1A 120.0 . . ?&#xA;C1 N1 H1B 120.0 . . ?&#xA;H1A N1 H1B 120.0 . . ?&#xA;&#xA;&#xA;#END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3964" LastEditorUserId="3964" LastEditDate="2024-01-10T16:34:03.367" LastActivityDate="2024-01-12T07:57:56.093" Title="How to make a super cell for molecular crystal with PBC" Tags="|crystallography|atomic-simulation-environment|atomistic-simulation|supercell|crystallographic-information-file|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12200" PostTypeId="2" ParentId="12195" CreationDate="2024-01-09T06:14:24.027" Score="0" Body="&lt;p&gt;The straightforward way for quantifying relativistic effects with NWChem (and with any other software): with the same DECONTRACTED basis set do the nonrelativistic calculation of your property, then do the corresponding relativistic calculation.&lt;/p&gt;&#xA;&lt;p&gt;Concerning relativistic calculations of properties you should be aware if there is the so-called picture change involved. For polarizabilities (valence property) this effect is small, for core properties this effect is more profound.&lt;/p&gt;&#xA;" OwnerUserId="114" LastActivityDate="2024-01-09T06:14:24.027" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12201" PostTypeId="1" CreationDate="2024-01-07T21:47:45.900" Score="2" ViewCount="52" Body="&lt;p&gt;can I simply calculate the ionization energy (IE) as the difference between the neutral and the charged system Heat of formation (Hf) with MOPAC ? The same question is with the electron affinity (EA).&lt;/p&gt;&#xA;&lt;p&gt;The problem is Heats of Formation versus Total Energies as described in  &lt;a href=&quot;http://openmopac.net/manual/HoF%20versus%20total%20energies.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://openmopac.net/manual/HoF%20versus%20total%20energies.html&lt;/a&gt; .&lt;/p&gt;&#xA;&lt;p&gt;Is there a necessity to convert the heat of formation to the total energy first ?&lt;/p&gt;&#xA;" OwnerUserId="114" OwnerDisplayName="Miro Iliaš" LastActivityDate="2024-01-23T03:16:36.853" Title="How can I calculate ionization energies and electron affinities with MOPAC?" Tags="|quantum-chemistry|semi-empirical-method|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12202" PostTypeId="2" ParentId="12179" CreationDate="2024-01-09T10:30:30.397" Score="4" Body="&lt;p&gt;The answer to that might be very long and you want to avoid math in here so I will try my best to explain how I understand it but with a little math at the end.&lt;/p&gt;&#xA;&lt;p&gt;Let’s start from the general connection between symmetry and band structures, in specific Translation symmetry which is responsible for the existence of energy bands in crystal structures, this symmetry allows for the formation of periodicity, where the arrangement of atoms repeats regularly in space. Such periodicity leads to the concept of a &lt;strong&gt;Brillouin zone&lt;/strong&gt; and the formation of energy bands in the band structure of materials. In other words, the Hamiltonian of the system is invariant under translations, meaning that the energy of the system doesn’t change when the crystal is translated by a lattice vector. Thus, translation symmetry gives rise to distinct energy bands separated by energy gaps. On the other hand, point symmetries such as rotation, reflection and inversion may determine the nature of those energy bands.&lt;/p&gt;&#xA;&lt;p&gt;Now regarding degeneracy, what does that mean?  we said symmetries in a crystal lattice led to degeneracy, which means that multiple states (eigenfunctions) have the same energy (eigenvalue). When a crystal undergoes a symmetry operation, its structure remains the same, and the energy associated with the formation of this structure from isolated atoms is the same for any equivalent configuration. This translates to a single eigenvalue for a set of eigenfunctions corresponding to the various equivalent positions, which is what we mean by degeneracy.&lt;/p&gt;&#xA;&lt;p&gt;Now you can imagine As the amount of symmetry in a system decreases, the degree of degeneracy also decreases. When symmetries are reduced or broken, the constraints that lead to degeneracy are lifted, and the energy levels associated with different configurations may no longer be the same. This reduction in symmetry results in the splitting of energy levels and a decrease in degeneracy.&lt;/p&gt;&#xA;&lt;p&gt;To understand this connection between degeneracy and symmetry, let's consider a 1D harmonic oscillator, The Schrödinger equation corresponding to it is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(\frac{d^2\psi}{dx^2})+(\frac{2m}{\hslash^2})[E-(kx^2/2)]\psi = 0,\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In which &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; is&#xA;Hooke's law constant. If we then use &lt;span class=&quot;math-container&quot;&gt;$\alpha=2mE/\hslash^2$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\beta^2=mk/\hslash^2$&lt;/span&gt;, the previous equation will become:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(\frac{d^2\psi}{dx^2}) + (\alpha - \beta^2x)\psi = 0,\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The solutions to this equation are the Hermite functions &lt;span class=&quot;math-container&quot;&gt;$\psi_n = exp(\frac{-\alpha x^2}{2})H_n(x)$&lt;/span&gt;, in which the eigenvalues are&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_n = (n + \frac{1}{2})hv,\tag{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;As you can see here for &lt;span class=&quot;math-container&quot;&gt;$n=0,1,2..$&lt;/span&gt; there is a distinct solution &lt;span class=&quot;math-container&quot;&gt;$\psi_n(x)$&lt;/span&gt; for each value of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; and therefore the system is &lt;strong&gt;nondegenerate&lt;/strong&gt;. Now let's consider the three-dimensional Schrödinger equation of the general form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$(\frac{-\hslash^2}{2m})\nabla^2\psi(r)+V(r)\psi(r)=E\psi(r),\tag{4}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;When applied to an oscillator with unequal constants &lt;span class=&quot;math-container&quot;&gt;$k_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$k_y$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$k_z$&lt;/span&gt; along the three coordinate axes, it can be solved by the separation of variables, resulting in three ordinary differential equations with a similar form to the first equation we have. Then, the eigenvalues will be:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_{n_x,n_y,n_z}=[(n_x+\frac{1}{2})hv_x+(n_y+\frac{1}{2})hv_y+(n_z+\frac{1}{2})hv_z],\tag{5}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the special case of an isotropic oscillator, the constants are all equal and eqaul to &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, so the energy levels become&#xA;&lt;span class=&quot;math-container&quot;&gt;$E=(n_x+n_y+n_z+\frac{3}{2})hv$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$(n+\frac{3}{2})hv$&lt;/span&gt;, you can see that the total energy now depends only on  &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, and for a given value of &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, there are &lt;span class=&quot;math-container&quot;&gt;$(n+1)$&lt;/span&gt; choices for &lt;span class=&quot;math-container&quot;&gt;$n_x$&lt;/span&gt;; &lt;span class=&quot;math-container&quot;&gt;$n_x=0,1,2,..,n$&lt;/span&gt;, then for &lt;span class=&quot;math-container&quot;&gt;$n_x=0$&lt;/span&gt;, there are &lt;span class=&quot;math-container&quot;&gt;$(n+1)$&lt;/span&gt; choices for &lt;span class=&quot;math-container&quot;&gt;$n_y$&lt;/span&gt;, for &lt;span class=&quot;math-container&quot;&gt;$n_x=1$&lt;/span&gt;, there are &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; choices for &lt;span class=&quot;math-container&quot;&gt;$n_y$&lt;/span&gt;, for &lt;span class=&quot;math-container&quot;&gt;$n_x=n$&lt;/span&gt;, there is one choice for &lt;span class=&quot;math-container&quot;&gt;$n_y$&lt;/span&gt;. In all in all, the degree of degenracy can be expressed as&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\frac{1}{2}[(n+1)+1](n+1)=\frac{1}{2}(n+1)(n+2),\tag{6}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Such &lt;strong&gt;degeneracy&lt;/strong&gt; is a result of the &lt;strong&gt;symmetry&lt;/strong&gt;. For your reference and if you want to go deeper into that you can refer to &lt;a href=&quot;https://doi.org/10.1016/S0081-1947(08)60349-5&quot; rel=&quot;nofollow noreferrer&quot;&gt;Crystal Symmetry, Group Theory, and Band Structure Calculations&lt;/a&gt; by Allen Nussbaum.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="24" LastEditDate="2024-02-27T12:54:00.573" LastActivityDate="2024-02-27T12:54:00.573" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12203" PostTypeId="1" AcceptedAnswerId="12204" CreationDate="2024-01-09T11:53:12.660" Score="1" ViewCount="63" Body="&lt;p&gt;Using the following Gromacs utility execited from Bash, I can create a new group in the ndx file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gmx make_ndx -f ref.pdb -o new.ndx &amp;lt;&amp;lt; EOF&#xA;ri 8-195 &amp;amp; 3&#xA;q&#xA;EOF&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is it possible to change the number of this new group e.g. setting it to the 0 (without explicit definition of the number of the new group) ?&lt;/p&gt;&#xA;&lt;p&gt;For the moment I could found only one possibility to add &amp;quot;keep number_of_new_group&amp;quot; in the EOF script that will delete all other groups. But in this case I still need to define the number of new group.&lt;/p&gt;&#xA;" OwnerUserId="8643" LastActivityDate="2024-01-10T08:30:42.563" Title="gromacs: How to keep only the last group in the NDX file created using make_ndx?" Tags="|gromacs|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12204" PostTypeId="2" ParentId="12203" CreationDate="2024-01-10T07:57:02.007" Score="3" Body="&lt;p&gt;Try these:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Call &lt;code&gt;make_ndx&lt;/code&gt; with a prepared, &lt;em&gt;empty&lt;/em&gt; &lt;code&gt;.ndx&lt;/code&gt; file:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;touch new.ndx&#xA;gmx make_ndx -n new.ndx -o output.ndx ...&#xA;rm new.ndx&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Now &lt;code&gt;output.ndx&lt;/code&gt; should contain only the new group.&lt;/p&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Count index groups manually:&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;n_last_group=$( grep '\[' index.ndx | wc -l )&#xA;echo &amp;quot;$n_last_group&amp;quot; | gmx traj -n index.ndx ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;em&gt;Explanation:&lt;/em&gt; &lt;code&gt;grep&lt;/code&gt; returns every line in &lt;code&gt;index.ndx&lt;/code&gt; with the open-bracket symbol &lt;code&gt;[&lt;/code&gt;, and &lt;code&gt;wc -l&lt;/code&gt; counts the number of lines returned, so the combined operation counts the number of groups defined in &lt;code&gt;index.ndx&lt;/code&gt;, which is stored in the variable &lt;code&gt;n_last_group&lt;/code&gt; (once you understand how this works, you can of course use a shorter variable name).&lt;/p&gt;&#xA;&lt;p&gt;BONUS: You can return a specific group's number with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;n_group=$( grep '\[' index.ndx | awk '/MyAwesomeGroup/ {print FNR} END {print &amp;quot;Error&amp;quot;}' | sed -n '1p' )&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As before &lt;code&gt;grep&lt;/code&gt; returns all group names; but now &lt;code&gt;awk&lt;/code&gt; prints the line numbers of all lines containing the string &lt;code&gt;MyAwesomeGroup&lt;/code&gt;. &lt;code&gt;sed&lt;/code&gt; returns the first line of &lt;em&gt;that&lt;/em&gt; output, giving the number of the &lt;em&gt;first&lt;/em&gt; group matching the string (if there is more than one) and &amp;quot;Error&amp;quot; if none was found, which then errors the subsequent GROMACS call.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="1791" LastEditDate="2024-01-10T08:30:42.563" LastActivityDate="2024-01-10T08:30:42.563" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12205" PostTypeId="1" AcceptedAnswerId="12212" CreationDate="2024-01-10T14:58:11.233" Score="1" ViewCount="25" Body="&lt;p&gt;I need to search for possible inhibitors for an enzyme. So I found the website &lt;a href=&quot;http://zincpharmer.csb.pitt.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ZINCPharmer&lt;/a&gt; and a &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394271/&quot; rel=&quot;nofollow noreferrer&quot;&gt;publication&lt;/a&gt; which seems to help me out with my problem. When I enter the website I cannot submit any pbd files or submit the job.&#xA;Does anybody knows if the site is down or so?&#xA;Thanks in advance!&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="1554" LastEditDate="2024-01-10T15:37:34.047" LastActivityDate="2024-01-11T11:02:09.147" Title="problem with the input at ZINCPharmer" Tags="|docking|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12206" PostTypeId="1" AcceptedAnswerId="12207" CreationDate="2024-01-10T16:06:22.793" Score="3" ViewCount="280" Body="&lt;p&gt;The exchange interaction is a quantum mechanical effect that only occurs between identical particles. The effect is due to the wave function of indistinguishable particles being subject to exchange symmetry, that is, either remaining unchanged (symmetric) or changing sign (antisymmetric) when two particles are exchanged, for fermions, this interaction is sometimes called Pauli repulsion. While electronic correlation is the interaction between electrons in the electronic structure of a quantum system. The correlation energy is a measure of how much the movement of one electron is influenced by the presence of all other electrons.&lt;/p&gt;&#xA;&lt;p&gt;What is the historical reason or intuituion for having those two terms to be combined as (exchange-correlation) energy when they are approximated in density functional theory?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-01-11T15:42:40.097" LastActivityDate="2024-01-11T15:42:40.097" Title="Synergy of Exchange and Correlation, Why are they Combined in the Term &quot;Exchange-Correlation&quot; Energy" Tags="|density-functional-theory|exchange-correlation|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12207" PostTypeId="2" ParentId="12206" CreationDate="2024-01-10T16:25:04.973" Score="7" Body="&lt;p&gt;I guess the reason they are grouped together as XC, is that they are whatever is left when the Coulomb interactions and Slater determinant kinetic energy is accounted for, i.e. they are (by definition) the unknown leftover of the (exact) energy when the contributions with known mathematical expressions are accounted for. However, in most functionals, they are written as a sum of separate X and C functionals. They are nevertheless intertwined, since the correlation between opposite spin electrons is larger than between same spin electrons, since the exchange energy between same spin electrons partly accounts for the correlation. The distinction is sometimes classified as Coulomb and Fermi correlation.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2024-01-10T16:25:04.973" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12208" PostTypeId="2" ParentId="12206" CreationDate="2024-01-10T17:05:43.253" Score="5" Body="&lt;p&gt;This is pretty much a deliberate quirk of DFT.&lt;/p&gt;&#xA;&lt;p&gt;You should, however, first take note that Exchange energy term is actually coming from the Coulomb interaction, albeit of course coming from the Slater determinant. If there is no Coulomb interaction, then there will also not be the Exchange energy term.&lt;/p&gt;&#xA;&lt;p&gt;However, it is known that&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Exchange energy term tends to overestimate the actual HOMO/LUMO gap; and is particularly egregious in the case of band gaps in continuous materials.&lt;/li&gt;&#xA;&lt;li&gt;The taking of Slater determinant is computationally expensive and is not done in DFT.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The latter makes it such that the Exchange energy term is needed to be approximated in DFT. The former motivates for it to not be taken exactly and to be approximated. Since it is to be approximated, it might as well be approximated alongside the correlation energy, which is approximated even in Hartree-Fock. Hence why the approximation bits are always presented in combination.&lt;/p&gt;&#xA;" OwnerUserId="7192" LastActivityDate="2024-01-10T17:05:43.253" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12209" PostTypeId="1" CreationDate="2024-01-11T03:12:30.850" Score="3" ViewCount="32" Body="&lt;p&gt;I made the graph using the ratio between the parameters x E_tot (trigonal structure), but I would like to know if there is a better way to do this.&lt;/p&gt;&#xA;" OwnerUserId="8250" LastActivityDate="2024-01-11T03:12:30.850" Title="Which is the best way to plot E_tot vs Lattice graph for structures with two lattice parameters?" Tags="|geometry-optimization|structure|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12210" PostTypeId="1" AcceptedAnswerId="12218" CreationDate="2024-01-11T09:02:01.397" Score="2" ViewCount="45" Body="&lt;p&gt;I want to write code to simulate the impingement of any molecule on a surface at different (r, theta, and phi) angles in XYZ format.&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="5" LastEditDate="2024-01-12T00:51:34.487" LastActivityDate="2024-01-12T06:12:21.933" Title="How to make initial trajectory for incident A2 molecule on any surface?" Tags="|vasp|molecular-dynamics|python|molecular-modeling|atomic-simulation-environment|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12211" PostTypeId="1" CreationDate="2024-01-11T09:06:19.310" Score="7" ViewCount="77" Body="&lt;p&gt;Gaussian-type-orbitals (GTOs) are the work horse of modern molecular quantum chemistry calculations. They are computationally efficient and allow for analytic evaluation of integrals. However, there's an increasing number of &lt;em&gt;ab initio&lt;/em&gt; packages that choose to use other alternatives for molecular calculations. One particular example being the numerical atomic orbitals (NAOs).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4384/5884&quot;&gt;For example, here's a similar discussion comparing GTOs and Slater-type-Orbitals (STOs)&lt;/a&gt;. That brings me to my question: What's the advantage of using a NAOs or other approaches that use numerically evaluated integrals?&lt;/p&gt;&#xA;" OwnerUserId="5884" LastActivityDate="2024-01-15T12:37:56.053" Title="Numerical atomic orbitals vs Gaussian-type orbitals for molecular calculations" Tags="|quantum-chemistry|molecular-modeling|basis-sets|orbitals|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12212" PostTypeId="2" ParentId="12205" CreationDate="2024-01-11T11:02:09.147" Score="1" Body="&lt;p&gt;Problem is solved so its about the firewall, the admin has sorted it. It was not possible by the user itself. Something was blocked by institute firewall.&lt;/p&gt;&#xA;" OwnerUserId="1680" LastActivityDate="2024-01-11T11:02:09.147" CommentCount="0" CommunityOwnedDate="2024-01-11T14:30:36.857" ContentLicense="CC BY-SA 4.0" />
  <row Id="12213" PostTypeId="1" CreationDate="2024-01-11T11:10:08.110" Score="2" ViewCount="35" Body="&lt;p&gt;&lt;a href=&quot;https://bioinformatics.stackexchange.com/q/22040/3621&quot;&gt;Cross-posted at Bioinformatics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I want to use the enzyme ß-Glucuronidase with the &lt;a href=&quot;https://pharmit.csb.pitt.edu/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pharmit&lt;/a&gt; database. I uploaded my file for the receptor from pdb file. How can I get the pharmacore features? So one thing is the enzyme is quiet popular, so is there any database with the features? I tried it with a &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3092953/&quot; rel=&quot;nofollow noreferrer&quot;&gt;publication&lt;/a&gt; but the given link is not working. It checked the site from the author but I did not found the database there.&lt;/p&gt;&#xA;&lt;p&gt;And if there is no database or maybe there is one but the enzyme is not included, how can I get the pharmacore features for my calculations?&lt;/p&gt;&#xA;" OwnerUserId="1680" LastEditorUserId="5" LastEditDate="2024-01-21T00:14:17.173" LastActivityDate="2024-02-20T01:00:35.090" Title="How to calculate pharmacore features?" Tags="|databases|docking|structural-biology|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12214" PostTypeId="2" ParentId="12198" CreationDate="2024-01-11T13:28:32.010" Score="3" Body="&lt;p&gt;I had more of a look and yeah, none of the available packages do this to my knowledge so I just wrote my own code. It isn't particularly hard, more just tedious efficiently figuring out where in your slab hamiltonian each coupling has to go; as you might expect &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; decomposes nicely into a block structure encoding transitions between layers of the slab. For example, for a slab along z (ie 1x1xn) and letting &lt;span class=&quot;math-container&quot;&gt;$(k_x, k_y) = k_{||}$&lt;/span&gt;, the Hamiltonian looks something like&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;H_{\Delta z = 0}(k_{||}) &amp;amp; H_{\Delta z = -1}(k_{||}) &amp;amp; H_{\Delta z = -2}(k_{||}) &amp;amp; \ldots \\&#xA;H_{\Delta z = +1}(k_{||}) &amp;amp; H_{\Delta z = 0}(k_{||}) &amp;amp; H_{\Delta z = -1}(k_{||}) &amp;amp; \ldots \\&#xA;\ldots&#xA;\end{pmatrix}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where sensible hermiticity requirements are automatically obeyed. If anyone needs more details let me know.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Edit for a point of clarity:&lt;/strong&gt;&#xA;This method does indeed work but make sure to read the paper &lt;em&gt;carefully&lt;/em&gt;. The diagonal elements of &lt;span class=&quot;math-container&quot;&gt;$[U^\dagger \frac{\partial H}{\partial k_{a}}U]$&lt;/span&gt; coincide with the velocities but this object is &lt;em&gt;not&lt;/em&gt; the velocity operator, as explained a little opaquely in sections B2 and C1 of the linked paper. The object you calculate will have off diagonal elements, but these are expressible as an entirely off diagonal operator related to the Berry phase.&lt;/p&gt;&#xA;" OwnerUserId="5154" LastEditorUserId="5154" LastEditDate="2024-01-16T17:29:26.163" LastActivityDate="2024-01-16T17:29:26.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12215" PostTypeId="1" CreationDate="2024-01-11T16:30:23.087" Score="3" ViewCount="37" Body="&lt;p&gt;I want to reproduce the bond dissociation energy of the BH molecule as stated in the book 'Molecular Electronic Structure Theory' by Helgaker et al, (chapter 8.3.1), using FCI with 1 frozen core orbital and the basis cc-pCVTZ.&lt;/p&gt;&#xA;&lt;p&gt;Around the equilibrium bond length (at the experimentally determined one, 2.3289a0) I can reproduce the energy for all digits, so the error is below 1 microHartree, see first block of code below.&lt;/p&gt;&#xA;&lt;p&gt;The dissociation energy given in the book is then computed w.r.t to the minimum of the computed energies, which the book says is at 2.3347a0. I compute the corresponding energy in the second block of code.&lt;/p&gt;&#xA;&lt;p&gt;In the third and fourth blocks of code I compute the energy of the dissociated molecule, both by placing the atoms very far apart and by adding up the energies of the individual atoms.&lt;/p&gt;&#xA;&lt;p&gt;The dissociation energies computed both ways differ only by microHartrees, but they are about 2 milliHartree larger than the reference value from the book. This is not a lot, but it hints at an error or misunderstanding in my calculations that I would like to understand.&lt;/p&gt;&#xA;&lt;p&gt;Any ideas or hints are greatly appreciated!&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import scf, gto&#xA;from pyscf.mcscf import CASCI, UCASCI&#xA;&#xA;basis_BH = {&amp;quot;B&amp;quot;: &amp;quot;ccpcvtz&amp;quot;, &amp;quot;H&amp;quot;: &amp;quot;ccpvtz&amp;quot;}&#xA;&#xA;# at experimental bond length, table 8.6&#xA;xyz_exp = &amp;quot;B 0 0 0; H 2.3289 0 0&amp;quot;&#xA;mol_exp = gto.M(atom=xyz_exp, basis=basis_BH, spin=0, symmetry=True, unit=&amp;quot;B&amp;quot;)&#xA;hf_exp = scf.RHF(mol_exp).newton()&#xA;hf_exp.run()&#xA;cascisolver_exp = CASCI(hf_exp, 56, 4)&#xA;e_r_exp = cascisolver_exp.kernel()[0]&#xA;e_r_exp_ref = -25.130001 - 0.101723  # 2nd column, 1st + 3rd entries&#xA;print(f&amp;quot;around equilibrium | computed: {e_r_exp},   reference: {e_r_exp_ref}\n&amp;quot;)&#xA;&#xA;# at equilibrium bond length, table 8.7&#xA;xyz_eq = &amp;quot;B 0 0 0; H 2.3347 0 0&amp;quot;&#xA;mol_eq = gto.M(atom=xyz_eq, basis=basis_BH, spin=0, symmetry=True, unit=&amp;quot;B&amp;quot;)&#xA;hf_eq = scf.RHF(mol_eq).newton()&#xA;hf_eq.run()&#xA;cascisolver_eq = CASCI(hf_eq, 56, 4)&#xA;e_eq = cascisolver_eq.kernel()[0]&#xA;&#xA;# at large separation, dissociated molecule&#xA;xyz_sep = &amp;quot;B 0 0 0; H 1000 0 0&amp;quot;&#xA;mol_sep = gto.M(atom=xyz_sep, basis=basis_BH, spin=0, symmetry=True, unit=&amp;quot;B&amp;quot;)&#xA;hf_sep = scf.RHF(mol_sep).newton()&#xA;hf_sep.run()&#xA;cascisolver_sep = CASCI(hf_sep, 56, 4)&#xA;e_sep = cascisolver_sep.kernel()[0]&#xA;&#xA;# compute energy of B (frozen core FCI) and H (FCI) separately (supermolecular approach)&#xA;molB = gto.M(atom=&amp;quot;B 0 0 0&amp;quot;, basis=basis_BH[&amp;quot;B&amp;quot;], spin=1, verbose=0, symmetry=True)&#xA;uhf_B = scf.UHF(molB).newton()&#xA;uhf_B.run()&#xA;casci_B = UCASCI(uhf_B, nelecas=(2, 1), ncas=42)&#xA;e_B_fci_frozencore = casci_B.kernel()[0]&#xA;&#xA;molH = gto.M(atom=&amp;quot;H 0 0 0&amp;quot;, basis=basis_BH[&amp;quot;H&amp;quot;], spin=1, verbose=0, symmetry=True)&#xA;uhf_H = scf.UHF(molH).newton()&#xA;uhf_H.run()&#xA;casci_H = UCASCI(uhf_H, nelecas=(1, 0), ncas=14)&#xA;e_H_fci_frozencore = casci_H.kernel()[0]&#xA;&#xA;e_BH_additive = e_H_fci_frozencore + e_B_fci_frozencore&#xA;&#xA;# dissociation energy&#xA;e_diss_ref = 0.13267 # table 8.7&#xA;e_diss = e_sep - e_eq&#xA;e_diss_supermol = e_BH_additive - e_eq&#xA;print(&#xA;    f&amp;quot;Dissociation energy | direct: {e_diss}, supermolecular: {e_diss_supermol},  reference: {e_diss_ref}&amp;quot;&#xA;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the output is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;around equilibrium | computed: -25.231724240266033,   reference: -25.231724&#xA;&#xA;Dissociation energy | direct: 0.13285929083973969, supermolecular: 0.13285247917572462,  reference: 0.13267&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8654" LastEditorUserId="8654" LastEditDate="2024-01-11T19:23:49.577" LastActivityDate="2024-01-11T19:23:49.577" Title="Reproduce Dissociation Energy of BH molecule with PySCF" Tags="|quantum-chemistry|electronic-structure|pyscf|reproducing-data-from-papers|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12217" PostTypeId="1" CreationDate="2024-01-12T04:50:06.507" Score="3" ViewCount="126" Body="&lt;p&gt;In Quantum Espresso, smearing introduces a temperature that makes calculations converge. A degauss value of 0.1 would mean a temperature of around 1200 K.&lt;/p&gt;&#xA;&lt;p&gt;Suppose I have the electrical conductivity for a system with a degauss value of (0.1). How can I use it to find the value of that parameter at 0 K or room temperature without running the DFT calculations again?&lt;/p&gt;&#xA;" OwnerUserId="6361" LastEditorUserId="1554" LastEditDate="2024-01-12T06:15:47.230" LastActivityDate="2024-01-12T12:09:56.260" Title="Removing Smearing Effect from a Parameter Computation" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12218" PostTypeId="2" ParentId="12210" CreationDate="2024-01-12T06:12:21.933" Score="2" Body="&lt;p&gt;I don't totally understand what OP is trying to do, but to my understanding, he/she is trying to make .xyz files for of a molecule moving on the surface of some structure, where its constituent atoms are moving away from each other along with rotation in their bond.&lt;/p&gt;&#xA;&lt;p&gt;The logic behind that would be to either read or build the required surface model, define a range of values for (theta, phi), and a range for the distances between the atoms of the molecule. We then create the molecule with some initial configuration and iterate over the range of corresponding values we have already defined so that we can vary the distances and rotations, we shall save those configurations accordingly along with the surface we have already built or read in the first steps. Last step, write those configurations as xyz files.&lt;/p&gt;&#xA;&lt;p&gt;The following is an example of my idea, which might be a good starting point for what OP is willing to achieve. The values in the script are random so you need to tweak according to your situation.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from ase import Atoms, Atom&#xA;from ase.build import fcc111, molecule&#xA;from ase.io import write&#xA;# Supposed we have Pt surface &#xA;a = 3.92  # Check the correct value of Pt lattice constant in Å&#xA;surface = fcc111('Pt', a=a, size=(2, 2, 4), vacuum=10.0, periodic=True)# randomly chosen Pt surface, check for your case or read the surface file if you aiready have one&#xA;theta_range = np.linspace(0, np.pi, num=20)  # Range of theta angles (0 to pi), num can change the sampling inside the chosen range&#xA;phi_range = np.linspace(0, 2*np.pi, num=40)  # Range of phi angles (0 to 2*pi), same thing about num &#xA;distance_range = np.linspace(0.5, 1, num=10)  # Range of distances (value1 to value2 Å) between the H atoms&#xA;# This list is used to store the final xyz files&#xA;configurations = []&#xA;# Initial trajectories&#xA;for theta in theta_range:&#xA;    for phi in phi_range:&#xA;        for distance in distance_range:&#xA;            # Generate H2 molecule with specific distance and orientation&#xA;            h2 = molecule('H2')&#xA;            h2.set_distance(0, 1, distance)&#xA;            h2.rotate(theta, 'y')&#xA;            h2.rotate(phi, 'z')&#xA;            # Get the positions of H2 atoms relative to Pt surface&#xA;            h2_positions = h2.positions + [0.5, 0.5, 2.0 + distance] &#xA;            combined_system = surface.copy()&#xA;            combined_system.extend(h2)&#xA;            combined_system.positions[-2:] = h2_positions&#xA;            configurations.append(combined_system)&#xA;# write the final structures XYZ files&#xA;for i, configuration in enumerate(configurations):&#xA;    filename = f'configuration_{i}.xyz'&#xA;    write(filename, configuration, format='xyz') &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-12T06:12:21.933" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12219" PostTypeId="2" ParentId="12199" CreationDate="2024-01-12T07:57:56.093" Score="2" Body="&lt;p&gt;I tried to produce a supercell using ASE while ensuring PBC to be True, and I fixed the atoms in the original unit cell (maybe this would fix the problem with having random atom sequence - I am not very sure about this part)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io, Atoms&#xA;from ase.constraints import FixAtoms&#xA;import numpy as np&#xA;structure = io.read('YourStructure.cif')&#xA;supercell_size = [2, 2, 2]&#xA;lattice_vectors = structure.cell&#xA;atomic_positions = structure.positions&#xA;supercell_atoms = []&#xA;for i in range(supercell_size[0]):&#xA;    for j in range(supercell_size[1]):&#xA;        for k in range(supercell_size[2]):&#xA;            supercell_atoms.extend(&#xA;                [atom for atom in atomic_positions + np.dot([i, j, k], lattice_vectors)]&#xA;            )&#xA;supercell = Atoms(symbols=structure.get_chemical_symbols() * np.prod(supercell_size),&#xA;                  positions=supercell_atoms,&#xA;                  cell=np.dot(np.diag(supercell_size), lattice_vectors),&#xA;                  pbc=True)&#xA;constraint = FixAtoms(indices=range(len(atomic_positions)))&#xA;supercell.set_constraint(constraint)&#xA;io.write('supercell.cif', supercell, format='cif')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I have to mention that ASE (cif.py) was throwing the following warning:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;crystal system 'orthorhombic' is not interpreted for space group Spacegroup(18, setting=1). This may result in wrong setting! &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So I am not so sure about the validation of the cif file you have.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-12T07:57:56.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12220" PostTypeId="2" ParentId="12217" CreationDate="2024-01-12T12:09:56.260" Score="3" Body="&lt;p&gt;The comment by @wzkchem5 is correct - the 1200K equivalent of the 0.1 smearing parameter value has nothing to do with the material's temperature. But you are still right worrying about it. It is a numerical parameter, so you should aim to converge along it. An ideal DFT code would give you the correct result with zero smearing. But in numerical reality it is necessary in case of small or zero band-gaps. So you need to threat it as any numerical parameter, such as basis size or k-grid density, i.e. look for the asymptotic value, estimate variation of your quantity of interest with the smearing magnitude.&lt;/p&gt;&#xA;&lt;p&gt;Also, smearing to some extent compensates the lack of k-grid density, and vice versa. So you may increase the k-grid density, and check for convergence with smearing 0.2, 0.1, 0.05.&lt;/p&gt;&#xA;" OwnerUserId="277" LastActivityDate="2024-01-12T12:09:56.260" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12221" PostTypeId="1" CreationDate="2024-01-13T19:44:07.217" Score="4" ViewCount="98" Body="&lt;p&gt;While performing DFT+U+SOC calculation in VASP for the material &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Mn_3Sb}$&lt;/span&gt; my calculation is not at all converging. Here I am attaching the necessary input files. I have come across some solutions as described here &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LNONCOLLINEAR&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt; and &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Troubleshooting_electronic_convergence&quot; rel=&quot;nofollow noreferrer&quot;&gt;link1&lt;/a&gt;, but could not figure out how to converge this magnetic calculation for DFT+U+SOC.&lt;/p&gt;&#xA;&lt;p&gt;So here is my &lt;code&gt;POSCAR&lt;/code&gt; file for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Mn_3Sb}:$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Mn3 Sb1&#xA;1.0&#xA;        3.8133819103         0.0000000000         0.0000000000&#xA;        0.0000000000         3.8133819103         0.0000000000&#xA;        0.0000000000         0.0000000000         7.6267638206&#xA;   Mn   Sb&#xA;    6    2&#xA;Direct&#xA;     0.000000000         0.500000000         0.250000000  &#xA;     0.000000000         0.500000000         0.750000000&#xA;     0.500000000         0.500000000         0.000000000&#xA;     0.500000000         0.500000000         0.500000000&#xA;     0.500000000         0.000000000         0.250000000&#xA;     0.500000000         0.000000000         0.750000000&#xA;     0.000000000         0.000000000         0.000000000&#xA;     0.000000000         0.000000000         0.500000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And my &lt;code&gt;INCAR&lt;/code&gt; for the AFM configuration is as follows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART    =  0 &#xA;ICHARG    =  2               #Non-self-consistent: GGA/LDA band structures)&#xA;EDIFF     = 1E-6&#xA;ENCUT     = 380              #Cut-off energy for plane wave basis set, in eV&#xA;#ISIF     = 3                #optimize atomic coordinates and lattice parameters&#xA;#IVDW     = 11               #DFT-D3 method of Grimme with zero damping function&#xA;#GGA      = PE               # Perdew-Burke-Ernzerhof (PBE)&#xA;ADDGRID   = .TRUE.           #Increase grid; helps GGA convergence&#xA;&#xA;## DOS ##Slaters pauling 18 electrons rule##&#xA;&#xA;ISMEAR    = 0&#xA;SIGMA     = 0.02&#xA;&#xA;IBRION    = -1              #Ionic relaxation Algorithm: 0-MD; 1-Quasi-New; 2-CG&#xA;ISPIN     = 2&#xA;LASPH     = True&#xA;LCHARG    = .TRUE.          #Write CHGCAR or not&#xA;LNONCOLLINEAR = .TRUE.&#xA;LSORBIT   =.True.&#xA;LORBMOM   = .TRUE. &#xA;### DFT+U PARAMETER ###&#xA;&#xA;LDAU      = .TRUE.          #switches on DFT+U  &#xA;LDAUJ     = 0 0             # J values (For LDAUTYPE=2 , Ueff = U-J)&#xA;LDAUL     = 2 -1            #l-quantum number (-1 : no U, &#xA;LDAUPRINT = 1               # 0:silent, 1: write occupancy matrix to OUTCA, &#xA;LDAUTYPE  = 2               #The simplified approach to the DFT+U , introduced by  Dudarev et al.&#xA;LDAUU     = 2.0 0           # for Mn:4.0 , Sb:0 ( U values in eV) &#xA;LMAXMIX   = 4               # 4 for d-electrons, 6 for f-electrons&#xA;LASPH     = .TRUE.          # non-spherical contributions from the gradient correction inside the PAW spheres will be included as well&#xA;&#xA;###Magnetization###&#xA;&#xA;LORBIT    = 11&#xA;SAXIS     = 0 0 4&#xA;MAGMOM    = 0 0 -4  0 0 4  0 0 -4  0 0 4  0 0 4  0 0 -4  0 0 0  0 0 0&#xA;&#xA;&#xA;##Mixer##&#xA;  AMIX      = 0.12&#xA;  BMIX      = 0.0001&#xA;  AMIX_MAG  = 0.82&#xA;  BMIX_MAG  = 0.0001&#xA;&#xA;&#xA;#EDIFFG   = 1E-04      (Ionic convergence; eV/AA)&#xA;LREAL     = .FALSE.&#xA;LWAVE     = .TRUE.    (determines whether the wavefunctions are written to the WAVECAR file at the end of a run or not)&#xA;NELM      = 80&#xA;NSW       = 0             # NSW sets the maximum number of ionic steps &#xA;PREC      = High&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;My &lt;code&gt;KPOINTS&lt;/code&gt; is as follows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;K-Spacing Value to Generate K-Mesh: 0.030&#xA;0&#xA;Monkhorst-Pack&#xA;   9   9   4&#xA;0.0  0.0  0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And my output showing it's not converging.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; running    4 mpi-ranks, on    1 nodes&#xA; distrk:  each k-point on    4 cores,    1 groups&#xA; distr:  one band on    1 cores,    4 groups&#xA; vasp.6.4.2 20Jul23 (build Dec 25 2023 14:50:44) complex                        &#xA;  &#xA; POSCAR found type information on POSCAR MnSb&#xA; POSCAR found :  2 types and       8 ions&#xA; scaLAPACK will be used&#xA; LDA part: xc-table for Pade appr. of Perdew&#xA; POSCAR, INCAR and KPOINTS ok, starting setup&#xA; FFT: planning ... GRIDC&#xA; FFT: planning ... GRID_SOFT&#xA; FFT: planning ... GRID&#xA; WAVECAR not read&#xA; entering main loop&#xA;       N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1     0.449739943799E+03    0.44974E+03   -0.15527E+04  6400   0.140E+03&#xA;DAV:   2     0.622280929197E+01   -0.44352E+03   -0.43408E+03  6400   0.456E+02&#xA;DAV:   3    -0.482008200745E+02   -0.54424E+02   -0.50556E+02  9704   0.195E+02&#xA;DAV:   4    -0.557526095931E+02   -0.75518E+01   -0.71185E+01 10432   0.709E+01&#xA;DAV:   5    -0.563695094102E+02   -0.61690E+00   -0.60331E+00 10328   0.199E+01    0.161E+01&#xA;DAV:   6    -0.533410140836E+02    0.30285E+01   -0.74053E+00 11312   0.336E+01    0.982E+00&#xA;DAV:   7    -0.519563261615E+02    0.13847E+01   -0.12416E+01 11488   0.470E+01    0.273E+00&#xA;DAV:   8    -0.519103977858E+02    0.45928E-01   -0.10386E+00  9360   0.103E+01    0.183E+00&#xA;DAV:   9    -0.518362151764E+02    0.74183E-01   -0.60847E-01  8248   0.544E+00    0.122E+00&#xA;DAV:  10    -0.518069760789E+02    0.29239E-01   -0.55223E-01  7288   0.491E+00    0.811E-01&#xA;DAV:  11    -0.517958284386E+02    0.11148E-01   -0.37173E-01  7216   0.421E+00    0.528E-01&#xA;DAV:  12    -0.517917164650E+02    0.41120E-02   -0.27984E-01  7216   0.356E+00    0.414E-01&#xA;DAV:  13    -0.517830417071E+02    0.86748E-02   -0.16471E-01  7216   0.287E+00    0.251E-01&#xA;DAV:  14    -0.517824730076E+02    0.56870E-03   -0.13058E-01  7176   0.242E+00    0.209E-01&#xA;DAV:  15    -0.517816855964E+02    0.78741E-03   -0.11141E-01  7168   0.218E+00    0.129E-01&#xA;DAV:  16    -0.517814850446E+02    0.20055E-03   -0.64790E-02  7168   0.174E+00    0.954E-02&#xA;DAV:  17    -0.517819416319E+02   -0.45659E-03   -0.31878E-02  7176   0.123E+00    0.585E-02&#xA;DAV:  18    -0.517824481709E+02   -0.50654E-03   -0.17252E-02  7176   0.928E-01    0.476E-02&#xA;DAV:  19    -0.517823717352E+02    0.76436E-04   -0.10660E-02  7128   0.729E-01    0.419E-02&#xA;DAV:  20    -0.517823138137E+02    0.57921E-04   -0.11218E-02  7064   0.718E-01    0.423E-02&#xA;DAV:  21    -0.517823581586E+02   -0.44345E-04   -0.97618E-03  7056   0.669E-01    0.444E-02&#xA;DAV:  22    -0.517824474139E+02   -0.89255E-04   -0.12466E-02  7024   0.755E-01    0.319E-02&#xA;DAV:  23    -0.517826795974E+02   -0.23218E-03   -0.63997E-03  7008   0.558E-01    0.293E-02&#xA;DAV:  24    -0.517827033041E+02   -0.23707E-04   -0.82325E-03  6960   0.613E-01    0.258E-02&#xA;DAV:  25    -0.517826323646E+02    0.70940E-04   -0.51839E-03  6952   0.509E-01    0.192E-02&#xA;DAV:  26    -0.517826668641E+02   -0.34499E-04   -0.34800E-03  6976   0.438E-01    0.159E-02&#xA;DAV:  27    -0.517826745055E+02   -0.76415E-05   -0.19043E-03  7032   0.339E-01    0.127E-02&#xA;DAV:  28    -0.517826597822E+02    0.14723E-04   -0.24527E-03  6864   0.409E-01    0.954E-03&#xA;DAV:  29    -0.517827008211E+02   -0.41039E-04   -0.13403E-03  6880   0.286E-01    0.136E-02&#xA;DAV:  30    -0.517827306854E+02   -0.29864E-04   -0.31719E-03  6832   0.411E-01    0.156E-02&#xA;DAV:  31    -0.517826799760E+02    0.50709E-04   -0.20284E-03  6824   0.353E-01    0.108E-02&#xA;DAV:  32    -0.517826956097E+02   -0.15634E-04   -0.17900E-03  6816   0.357E-01    0.127E-02&#xA;DAV:  33    -0.517826942232E+02    0.13866E-05   -0.27314E-03  6736   0.368E-01    0.160E-02&#xA;DAV:  34    -0.517827565430E+02   -0.62320E-04   -0.37554E-03  6704   0.424E-01    0.184E-02&#xA;DAV:  35    -0.517827289587E+02    0.27584E-04   -0.35617E-03  6688   0.424E-01    0.146E-02&#xA;DAV:  36    -0.517826879392E+02    0.41019E-04   -0.15754E-03  6688   0.335E-01    0.883E-03&#xA;DAV:  37    -0.517826758255E+02    0.12114E-04   -0.14120E-03  6688   0.323E-01    0.711E-03&#xA;DAV:  38    -0.517827088385E+02   -0.33013E-04   -0.15911E-03  6672   0.319E-01    0.123E-02&#xA;DAV:  39    -0.517826538351E+02    0.55003E-04   -0.80932E-04  6688   0.247E-01    0.466E-03&#xA;DAV:  40    -0.517826696179E+02   -0.15783E-04   -0.85738E-04  6696   0.279E-01    0.696E-03&#xA;DAV:  41    -0.517827197438E+02   -0.50126E-04   -0.99378E-04  6664   0.233E-01    0.137E-02&#xA;DAV:  42    -0.517827356752E+02   -0.15931E-04   -0.32448E-03  6592   0.408E-01    0.151E-02&#xA;DAV:  43    -0.517827416500E+02   -0.59748E-05   -0.12912E-03  6592   0.277E-01    0.152E-02&#xA;DAV:  44    -0.517826831414E+02    0.58509E-04   -0.25744E-03  6544   0.375E-01    0.984E-03&#xA;DAV:  45    -0.517826773047E+02    0.58367E-05   -0.59249E-04  6768   0.225E-01    0.935E-03&#xA;DAV:  46    -0.517826589605E+02    0.18344E-04   -0.10712E-03  6576   0.265E-01    0.586E-03&#xA;DAV:  47    -0.517827277722E+02   -0.68812E-04   -0.13122E-03  6528   0.273E-01    0.138E-02&#xA;DAV:  48    -0.517827114814E+02    0.16291E-04   -0.32180E-03  6512   0.407E-01    0.138E-02&#xA;DAV:  49    -0.517827141822E+02   -0.27007E-05   -0.12539E-03  6512   0.280E-01    0.109E-02&#xA;DAV:  50    -0.517827177136E+02   -0.35314E-05   -0.25305E-03  6496   0.370E-01    0.126E-02&#xA;DAV:  51    -0.517827443097E+02   -0.26596E-04   -0.34811E-03  6488   0.417E-01    0.165E-02&#xA;DAV:  52    -0.517827103975E+02    0.33912E-04   -0.21587E-03  6488   0.336E-01    0.116E-02&#xA;DAV:  53    -0.517827557456E+02   -0.45348E-04   -0.27325E-03  6488   0.369E-01    0.180E-02&#xA;DAV:  54    -0.517827846982E+02   -0.28953E-04   -0.49826E-03  6480   0.484E-01    0.191E-02&#xA;DAV:  55    -0.517827445492E+02    0.40149E-04   -0.49158E-03  6472   0.496E-01    0.171E-02&#xA;DAV:  56    -0.517827693124E+02   -0.24763E-04   -0.45599E-03  6456   0.472E-01    0.182E-02&#xA;DAV:  57    -0.517826904181E+02    0.78894E-04   -0.29253E-03  6464   0.393E-01    0.117E-02&#xA;DAV:  58    -0.517826843632E+02    0.60549E-05   -0.13158E-03  6480   0.285E-01    0.830E-03&#xA;DAV:  59    -0.517826932285E+02   -0.88653E-05   -0.18202E-03  6472   0.355E-01    0.832E-03&#xA;DAV:  60    -0.517826856487E+02    0.75798E-05   -0.12909E-03  6448   0.298E-01    0.816E-03&#xA;DAV:  61    -0.517827261128E+02   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        |&#xA;|           W    W    AA    RRRRR   N    N  II  N    N   GGGG   !!!           |&#xA;|           W    W   A  A   R    R  NN   N  II  NN   N  G    G  !!!           |&#xA;|           W    W  A    A  R    R  N N  N  II  N N  N  G       !!!           |&#xA;|           W WW W  AAAAAA  RRRRR   N  N N  II  N  N N  G  GGG   !            |&#xA;|           WW  WW  A    A  R   R   N   NN  II  N   NN  G    G                |&#xA;|           W    W  A    A  R    R  N    N  II  N    N   GGGG   !!!           |&#xA;|                                                                             |&#xA;|     The electronic self-consistency was not achieved in the given           |&#xA;|     number of steps (NELM). The forces and other quantities evaluated       |&#xA;|     might not be reliable so examine the results carefully. If you find     |&#xA;|     spurious results, we suggest increasing NELM, if you were close to      |&#xA;|     convergence or switching to a different ALGO or adjusting the           |&#xA;|     density mixing parameters otherwise.                                    |&#xA;|                                                                             |&#xA; -----------------------------------------------------------------------------&#xA;&#xA;   1 F= -.51782717E+02 E0= -.51782042E+02  d E =-.134961E-02  mag=     0.0000     0.0000    -0.0000&#xA; writing wavefunctions&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any suggestions and solutions are appreciated.&#xA;First &lt;code&gt;Edit1&lt;/code&gt;: NELM=100 and its output&lt;/p&gt;&#xA;" OwnerUserId="8321" LastEditorUserId="8321" LastEditDate="2024-01-14T04:40:40.233" LastActivityDate="2024-01-14T04:40:40.233" Title="Electronic Convergence issues for DFT+U+SOC in VASP for magnetic materials" Tags="|density-functional-theory|vasp|magnetism|" AnswerCount="0" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12222" PostTypeId="2" ParentId="12192" CreationDate="2024-01-14T10:07:43.140" Score="1" Body="&lt;p&gt;You are applying TDA upon TDHF, which results in CIS. So the A matrix is identical to the CIS Hamiltonian matrix minus the HF energy, or equivalently, the singles-singles block of the FCI matrix minus the HF energy. Therefore, the result differs from your FCI energy due to three reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;After the FCI matrix is diagonalized, one typically does not subtract the HF energy from the eigenvalues;&lt;/li&gt;&#xA;&lt;li&gt;The lowest eigenvalue of the A matrix corresponds to the first excited state, not the ground state (since the A matrix does not include the ground state); and&lt;/li&gt;&#xA;&lt;li&gt;The A matrix does not include double and higher excitations.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Therefore, the correct way would be to generate the CIS Hamiltonian (I don't know what's the best way to do that in PySCF, but at least you can take the singles-singles block of the FCI Hamiltonian), subtract the HF energy from the diagonal elements, and compare against the A matrix. This should give perfect agreement. Nevertheless there are a few caveats:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The two matrices only agree when the functional is HF. If you do TDA upon a density functional that is not HF, then TDA is not equivalent to CIS, even if you use the DFT Fock matrix to build the CIS Hamiltonian.&lt;/li&gt;&#xA;&lt;li&gt;The TDA and CIS codes of PySCF probably have a large overlap. So the agreement of TDA and CIS does not give you much extra confidence that your result is correct. If you feel it necessary, you can compare against the TDA or CIS matrix calculated by another program.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="838" LastActivityDate="2024-01-14T10:07:43.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12224" PostTypeId="2" ParentId="12211" CreationDate="2024-01-15T12:37:56.053" Score="2" Body="&lt;p&gt;In some cases at least, NAO give smaller BSSE (basis set superposition error).&lt;/p&gt;&#xA;&lt;p&gt;Here is the figure from &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0010465509002033#fig004&quot; rel=&quot;nofollow noreferrer&quot;&gt;the FHI-aims paper&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/nJtVb.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/nJtVb.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The BSSE here is the difference between red and black lines. It is small, and moreover, it converges to zero with basis set growth, that is really convenient.&lt;/p&gt;&#xA;&lt;p&gt;The integration of NAO is more complicated that for GTO, but &lt;a href=&quot;https://www.youtube.com/watch?v=sGRnLrepkiw&amp;amp;t=630s&quot; rel=&quot;nofollow noreferrer&quot;&gt;there are some advanced numerical algorithms&lt;/a&gt;. Probably advances in numerical integration contributed to the emergence of NAO codes.&lt;/p&gt;&#xA;" OwnerUserId="277" LastActivityDate="2024-01-15T12:37:56.053" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12225" PostTypeId="1" CreationDate="2024-01-15T12:43:17.513" Score="2" ViewCount="38" Body="&lt;p&gt;Please suggest me, how to treat pseudopotential and basis for f block elements like Sm in simulating Sm2O3.&#xA;I used the psml pseudopotential from pseudo-dojo database, which gives quite accurate lattice constant, and non-magnetic ground state. But, it doesn't have 4f orbitals in valence configuration leading to vanishing DOS of 4f orbitals. However, the moment I used self-generated pseudopotential with valence 5s25p65d04f6 configuration, it gives a ferromagnetic ground state (not found in PW calculation), and also error in lattice constant exceeds 5%. So, what should be the correct way to do these calculations? Am, I making some mistake?&lt;/p&gt;&#xA;" OwnerUserId="5366" LastEditorUserId="5" LastEditDate="2024-01-21T00:13:01.510" LastActivityDate="2024-01-21T00:13:01.510" Title="Treatment of f-electrons in SIESTA" Tags="|siesta|pseudopotentials|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12226" PostTypeId="1" CreationDate="2024-01-15T13:39:31.113" Score="1" ViewCount="36" Body="&lt;h1&gt;Problem presentation&lt;/h1&gt;&#xA;&lt;p&gt;The problem mentioned in this &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper about norm conserving potentials&lt;/a&gt;. I cite &lt;code&gt;we choose a cutoff radius, typically 0.5 to 1.0 times the radius of the outermost peak of [the valence wavefunction]&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I think this problem can be written as the following optimization problem:&lt;/p&gt;&#xA;&lt;p&gt;Find &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; such that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{equation}&#xA;\begin{cases}&#xA;\max_{x\in \mathcal{D}}{f(x)}\\&#xA;\max_{x\in \mathcal{D}}{x}&#xA;\end{cases}&#xA;\end{equation}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is the function I want to minimize and &lt;span class=&quot;math-container&quot;&gt;$\mathcal{D}=\mathcal{R}⁺$&lt;/span&gt; the definition domain of &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; is a sum of contracted primitive gaussians (also a linear combination of gaussians).&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How is the cutoff radius usually solved for?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Context&lt;/h1&gt;&#xA;&lt;p&gt;I want to follow the procedure mentionned in the paper to generate norm-conserving pseudo-potentials for a carbon atom.&lt;/p&gt;&#xA;" OwnerUserId="7151" OwnerDisplayName="mle" LastEditorUserId="5" LastEditDate="2024-01-21T00:12:22.773" LastActivityDate="2024-01-21T00:12:22.773" Title="Find the outermost peak of a function to calculate the cutoff radius for pseudopotential calculation" Tags="|pseudopotentials|optimization|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12227" PostTypeId="1" CreationDate="2024-01-15T18:14:49.090" Score="2" ViewCount="39" Body="&lt;p&gt;I am looking for an algorithm/library to find phase boundaries as a function of some parameters. E.g. in the Hubbard model, the phase diagram as a function of U and doping hosts metal/insulator transitions. Suppose I have a code that can determine the phase at any arbitrary point in the phase diagram (e.g. takes U and doping as input, solves the model, and returns the gap). I want to find the entire domain where the system metallic. Is there some algorithm that, given an initial point, can tell me which direction to go in the phase diagram to find the phase boundary, and then follow the phase boundary around the domain?&lt;/p&gt;&#xA;&lt;p&gt;I suppose I could minimize the gap wrt U and doping, but if the initial point is in the metallic phase, this wont help.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&#xA;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="1258" LastEditDate="2024-01-15T21:39:45.300" LastActivityDate="2024-01-15T21:39:45.300" Title="Algorithm to find phase boundaries" Tags="|hubbard-model|phase-transitions|phase-diagram|computational-frameworks|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12228" PostTypeId="1" AcceptedAnswerId="12229" CreationDate="2024-01-15T21:39:13.853" Score="3" ViewCount="74" Body="&lt;p&gt;There is this paper: &lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1494&quot; rel=&quot;nofollow noreferrer&quot;&gt;Norm-Conserving Pseudopotentials&lt;/a&gt; mentioning a procedure to make a pseudopotential. There are many points that I did not get. Let's suppose we already have the results from the all-electron simulation: the potential &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$\phi_l$&lt;/span&gt; the valence wavefunction and &lt;span class=&quot;math-container&quot;&gt;$u_l(r) = r\phi_l(r)$&lt;/span&gt;. The steps that I do not understand are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The form of the potential &lt;span class=&quot;math-container&quot;&gt;$V_{1l}^{PS}(r) = (1-f(r/r_{cl}))V(r) + c_lf(r/r_{cl})$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt; is some cutoff radius and &lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; the cutoff function&lt;/li&gt;&#xA;&lt;li&gt;The value of the constant &lt;span class=&quot;math-container&quot;&gt;$\gamma_l$&lt;/span&gt;, involved in the form wavefunction &lt;span class=&quot;math-container&quot;&gt;$\omega_{2l}$&lt;/span&gt; and defined as &lt;span class=&quot;math-container&quot;&gt;$\gamma_l\omega_{1l} \xrightarrow[r&amp;gt;r_{cl}]{} u_l(r)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In the first point, &lt;span class=&quot;math-container&quot;&gt;$c_l$&lt;/span&gt; is defined as a constant that is &amp;quot;adjustable&amp;quot; so that the nodeless wavefunction &lt;span class=&quot;math-container&quot;&gt;$w_{1l}$&lt;/span&gt; has the same energy as the original wavefunction. To me, it feels like trial and error. &lt;strong&gt;Am I missing something?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For the second point, &lt;strong&gt;how can we get the constant &lt;span class=&quot;math-container&quot;&gt;$\gamma_l$&lt;/span&gt;?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="7151" LastActivityDate="2024-01-24T21:43:15.850" Title="Norm conserving pseudopotential procedure" Tags="|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12229" PostTypeId="2" ParentId="12228" CreationDate="2024-01-16T02:17:18.553" Score="3" Body="&lt;p&gt;We can start from the first term that you are providing, the purpose of this form is to smoothly transition the potential from the true all-electron potential &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; to a pseudopotential form  &lt;span class=&quot;math-container&quot;&gt;$V_{1l}^{PS}(r)$&lt;/span&gt; within a cutoff radius &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;. Here, the purpose of the cutoff radius is to limit the range of the pseudopotential, we just want to capture the essential physics of the valence electrons and try to avoid unnecessary computational overhead coming from describing the core electrons.&lt;/p&gt;&#xA;&lt;p&gt;The cutoff function &lt;span class=&quot;math-container&quot;&gt;$f(r/r_{cl})$&lt;/span&gt; is usually a &lt;em&gt;smooth&lt;/em&gt; function that goes from 1 to 0 as &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; approaches &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;. This transition ensures that the pseudopotential reproduces the correct behavior of the all-electron potential within a certain region.&lt;/p&gt;&#xA;&lt;p&gt;Regarding the constant &lt;span class=&quot;math-container&quot;&gt;$cl$&lt;/span&gt;, it is adjustable as you have described and the way to determine it is &lt;em&gt;iterative&lt;/em&gt; rather than trial and error cause you are not brute-forcing a solution using different possibilities, rather you are starting with an initial condition and move towards the solution by matching the energy of the nodeless pseudowavefunction &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; with the energy of the original all-electron wavefunction &lt;span class=&quot;math-container&quot;&gt;$\phi_{1l}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Now for the second point 'The constant &lt;span class=&quot;math-container&quot;&gt;$\gamma_{l}$&lt;/span&gt;' is determined based on the behavior of the all-electron wavefunction &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; outside the cutoff radius &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;. It represents the ratio of the logarithmic derivatives of the all-electron wavefunction and the pseudowavefunction &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;. In order to get &lt;span class=&quot;math-container&quot;&gt;$\gamma_{l}$&lt;/span&gt;, you need to calculate the logarithmic derivative of the all-electron wavefunction &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;, which is given by: &lt;span class=&quot;math-container&quot;&gt;$$\tag{1}u_l(r) = r_{\omega_{1l}}(r),$$&lt;/span&gt;  and &lt;span class=&quot;math-container&quot;&gt;$\gamma_{l}$&lt;/span&gt; can be computed as the ratio of the logarithmic derivatives of &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\omega_{1l}$&lt;/span&gt; at &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; = &lt;span class=&quot;math-container&quot;&gt;$r_{cl}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can have further reads from &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.43.1993&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; which is based on the paper you have mentioned in your question.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="142" LastEditDate="2024-01-24T21:43:15.850" LastActivityDate="2024-01-24T21:43:15.850" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12230" PostTypeId="1" CreationDate="2024-01-16T09:36:50.670" Score="2" ViewCount="33" Body="&lt;p&gt;In Wikipedia there is a &lt;a href=&quot;https://en.wikipedia.org/wiki/Tight_binding#Table_of_interatomic_matrix_elements&quot; rel=&quot;nofollow noreferrer&quot;&gt;list&lt;/a&gt; of Slater-Koster matrix elements, but not all of them are listed because &amp;quot;matrix elements that are not listed in this table can be constructed by permutation of indices and cosine directions of other matrix elements in the table&amp;quot;. I checked the original article and the authors provide the same matrix elements.&lt;/p&gt;&#xA;&lt;p&gt;However, I do not understand how to apply these permutations. For instance, in the list above, we have the matrix elements&#xA;&lt;span class=&quot;math-container&quot;&gt;$$E_{z,x^2-y^2} = \frac{\sqrt{3}}{2} n(l^2 - m^2) V_{pd\sigma} - n(l^2 - m^2) V_{pd\pi}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$E_{z,3z^2-r^2} = n [n^2 - (l^2 + m^2) / 2] V_{pd\sigma} + \sqrt{3} n (l^2 + m^2) V_{pd\pi},$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$l,m,n$&lt;/span&gt; are the cosine directors. Other matrix elements of a &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbital with other &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals are however not listed. How can we construct, for example, the matrix element &lt;span class=&quot;math-container&quot;&gt;$E_{z,zx}$&lt;/span&gt; from the given matrix elements?&lt;/p&gt;&#xA;" OwnerUserId="8671" LastActivityDate="2024-01-16T09:36:50.670" Title="Symmetries and Permutation in the Slater-Koster matrix elements" Tags="|solid-state-physics|tight-binding|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12231" PostTypeId="1" AcceptedAnswerId="12233" CreationDate="2024-01-17T00:13:01.247" Score="4" ViewCount="63" Body="&lt;p&gt;I would like to use Povray to render nice-looking graphics of molecules, which can be exported from visualization softwares like Jmol. However, I have noticed that the color of the rendered graphics looks brighter compared to the visualization in Jmol itself. (see image below) Is that something expected? And is there a way to adjust the brightness so that the brightness remains the same as in Jmol?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iIcdk.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iIcdk.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;P.S. &lt;strike&gt;After some investigation, I believe I have located the cause of the problem (but have still not resolved it yet, see images below): In the render preference, there is a &amp;quot;Gamma&amp;quot; option which controls the brightness of the rendered image, but no matter what value I put in here, the value of Gamma in the final rendering window is always 2.5, which is too high (it should be ideally around 1). I would really appreciate it if someone could suggest how to correct this behavior. &lt;strong&gt;This problem appears with Povray 3.8 on MacOS.&lt;/strong&gt; &lt;/strike&gt;&lt;/p&gt;&#xA;&lt;p&gt;Seems that the brightness has nothing to do with the Gamma value after all (tested with Povray 3.7), so the problem remains.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XVOlA.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XVOlA.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/gafFU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/gafFU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5448" LastEditorUserId="5448" LastEditDate="2024-01-17T01:42:01.850" LastActivityDate="2024-01-17T01:58:27.957" Title="Povray rendering of Jmol visualization appears brighter" Tags="|molecular-modeling|visualization-software|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12232" PostTypeId="1" CreationDate="2024-01-17T01:15:44.270" Score="2" ViewCount="50" Body="&lt;p&gt;I want to calculate the frequency using quantum espresso. How can I get the input file of frequency calculation using QE?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation = 'vc-relax'&#xA;    restart_mode = 'from_scratch'&#xA;    prefix = 'your_prefix'&#xA;    tstress = .true.&#xA;    tprnfor = .true.&#xA;    pseudo_dir = 'path/to/pseudopotentials'&#xA;    outdir = './'&#xA;/&#xA;&#xA;&amp;amp;system&#xA;    ibrav = 1&#xA;    celldm(1) = 10.0&#xA;    nat = 3&#xA;    ntyp = 2&#xA;    ecutwfc = 30.0&#xA;    ecutrho = 300.0&#xA;    occupations = 'smearing'&#xA;    smearing = 'mp'&#xA;    degauss = 0.02&#xA;/&#xA;&#xA;&amp;amp;electrons&#xA;    conv_thr = 1.0e-8&#xA;/&#xA;&#xA;&amp;amp;ions&#xA;    ion_dynamics = 'bfgs'&#xA;/&#xA;&#xA;&amp;amp;cell&#xA;    cell_dynamics = 'bfgs'&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;   element1  12.01  element1.pbe-rrkjus.UPF&#xA;   element2  1.01   element2.pbe-rrkjus.UPF&#xA;&#xA;ATOMIC_POSITIONS crystal&#xA;   element1  0.0  0.0  0.0&#xA;   element1  0.25 0.25 0.25&#xA;   element2  0.5  0.5  0.5&#xA;&#xA;K_POINTS automatic&#xA;   4 4 4 1 1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7321" LastEditorUserId="1554" LastEditDate="2024-01-17T01:37:26.843" LastActivityDate="2024-01-17T01:37:26.843" Title="Frequency calculation using Quantum Espresso" Tags="|density-functional-theory|vasp|quantum-espresso|gaussian|materials-studio|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12233" PostTypeId="2" ParentId="12231" CreationDate="2024-01-17T01:58:27.957" Score="2" Body="&lt;p&gt;Just found the answer myself: simply adding the line&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;global_settings { assumed_gamma 2.0 }&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;in the *.pov file makes all the difference:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GY1NQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GY1NQ.png&quot; alt=&quot;Jmol + povray after gamma correction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5448" LastActivityDate="2024-01-17T01:58:27.957" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12234" PostTypeId="1" AcceptedAnswerId="12237" CreationDate="2024-01-17T04:09:35.013" Score="3" ViewCount="133" Body="&lt;p&gt;In Phonopy the thermal properties, free energy, heat capacity, and entropy, are calculated from their statistical thermodynamic expressions using phonon frequencies on a sampling mesh in the reciprocal space. According to the Phonopy &lt;a href=&quot;http://phonopy.github.io/phonopy/setting-tags.html#thermal-properties-tag&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The unit systems of free energy, heat capacity, and entropy are&#xA;kJ/mol, J/K/mol, and J/K/mol, respectively, where 1 mol means &lt;span class=&quot;math-container&quot;&gt;$N_A  \times$&lt;/span&gt; your&#xA;input unit cell (not formula unit), i.e. you have to divide the value&#xA;by number of formula unit in your unit cell by yourself. For example,&#xA;in MgO (conventional) unit cell, if you want to compare with&#xA;experimental results in kJ/mol, you have to divide the phonopy output&#xA;by four.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;First, what does &lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt; stand for? I am confused with their statement in the documenation, in the example of MgO (conventional) unit cell, does '4' stand for the formula unit?&lt;/p&gt;&#xA;&lt;p&gt;Second, suppose that I have the thermal properties of the same material in Bulk and monolayer form, both having one unit cell but with different number of atoms or ions in their unit cells, then should I normalize the values and divide by the number of atoms in the unit cell in order to compare the results?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-01-17T15:04:50.950" LastActivityDate="2024-01-17T15:04:50.950" Title="Thermal Properties Calculated with Phonopy" Tags="|statistical-thermodynamics|phonopy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12235" PostTypeId="1" AcceptedAnswerId="12242" CreationDate="2024-01-17T06:37:58.343" Score="5" ViewCount="122" Body="&lt;p&gt;I am trying to do a simple TDDFT calculation in both Gaussian and ORCA from the exact same reference Geometry. I am using the same functional (making sure to use &lt;code&gt;b3lyp/g&lt;/code&gt; in ORCA to ensure this) and basis set. And yet my results are showing significant difference. I am attaching the input of Gaussian and ORCA respectively below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=20&#xA;%mem=4GB&#xA;#p td=(singlets,nstates=8) b3lyp/cc-pvdz&#xA;&#xA;tddft-b3lyp-ccbvdz&#xA;&#xA;0 1&#xA; C                  4.45143600    2.73106800    0.00000000&#xA; C                  3.61628300    1.62294900    0.00000000&#xA; C                  2.21893400    1.80672100    0.00000000&#xA; C                  1.66757200    3.11685300    0.00000000&#xA; C                  2.54605100    4.22247600    0.00000000&#xA; C                  3.92022500    4.03659100    0.00000000&#xA; H                  1.71737100   -0.24322100    0.00000000&#xA; H                  5.53378000    2.58612200    0.00000000&#xA; H                  4.02613700    0.61062500    0.00000000&#xA; C                  0.23548300    3.23807000    0.00000000&#xA; H                  2.12225200    5.22957100    0.00000000&#xA; H                  4.59105500    4.89745300    0.00000000&#xA; C                 -0.57411500    2.14004900    0.00000000&#xA; C                  0.00000000    0.82082500    0.00000000&#xA; H                 -0.20202400    4.23984100    0.00000000&#xA; H                 -1.66145000    2.20341300    0.00000000&#xA; C                 -1.24551500   -2.68544300    0.00000000&#xA; C                 -2.46715000   -1.99407400    0.00000000&#xA; C                 -3.67831300   -2.67573200    0.00000000&#xA; C                 -3.64334700   -4.07886900    0.00000000&#xA; C                 -2.42235100   -4.76927200    0.00000000&#xA; C                 -1.20258200   -4.07556800    0.00000000&#xA; C                 -0.12926800   -1.68697900    0.00000000&#xA; C                 -0.74306200   -0.36908600    0.00000000&#xA; C                 -2.20356400   -0.50939000    0.00000000&#xA; H                 -4.62064100   -2.12451100    0.00000000&#xA; H                 -4.57840100   -4.64401100    0.00000000&#xA; H                 -2.42399500   -5.86177600    0.00000000&#xA; H                 -0.24540600   -4.60044300    0.00000000&#xA; N                  1.36356400    0.73013200    0.00000000&#xA; O                 -3.06944900    0.36115800    0.00000000&#xA; O                  1.08395700   -1.95504700    0.00000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for ORCA&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%pal&#xA;        nprocs 16&#xA;end&#xA;&#xA;%tddft&#xA;        nroots 8&#xA;        triplets true&#xA;        tda = false&#xA;end&#xA;&#xA;*xyz 0 1&#xA;C                  4.45140000    2.73110000    0.00000000&#xA;C                  3.61630000    1.62290000    0.00000000&#xA;C                  2.21890000    1.80670000    0.00000000&#xA;C                  1.66760000    3.11690000    0.00000000&#xA;C                  2.54610000    4.22250000    0.00000000&#xA;C                  3.92020000    4.03660000    0.00000000&#xA;H                  1.71740000   -0.24320000    0.00000000&#xA;H                  5.53380000    2.58610000    0.00000000&#xA;H                  4.02610000    0.61060000    0.00000000&#xA;C                  0.23550000    3.23810000    0.00000000&#xA;H                  2.12230000    5.22960000    0.00000000&#xA;H                  4.59110000    4.89750000    0.00000000&#xA;C                 -0.57410000    2.14000000    0.00000000&#xA;C                  0.00000000    0.82080000    0.00000000&#xA;H                 -0.20200000    4.23980000    0.00000000&#xA;H                 -1.66150000    2.20340000    0.00000000&#xA;C                 -1.24550000   -2.68540000    0.00000000&#xA;C                 -2.46720000   -1.99410000    0.00000000&#xA;C                 -3.67830000   -2.67570000    0.00000000&#xA;C                 -3.64330000   -4.07890000    0.00000000&#xA;C                 -2.42240000   -4.76930000    0.00000000&#xA;C                 -1.20260000   -4.07560000    0.00000000&#xA;C                 -0.12930000   -1.68700000    0.00000000&#xA;C                 -0.74310000   -0.36910000    0.00000000&#xA;C                 -2.20360000   -0.50940000    0.00000000&#xA;H                 -4.62060000   -2.12450000    0.00000000&#xA;H                 -4.57840000   -4.64400000    0.00000000&#xA;H                 -2.42400000   -5.86180000    0.00000000&#xA;H                 -0.24540000   -4.60040000    0.00000000&#xA;N                  1.36360000    0.73010000    0.00000000&#xA;O                 -3.06940000    0.36120000    0.00000000&#xA;O                  1.08400000   -1.95500000    0.00000000&#xA;*&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But the outputs I am getting are quite different ! As illustrated below&lt;/p&gt;&#xA;&lt;p&gt;For Gaussian&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Excited State   1:      Triplet-A'     2.2054 eV  562.19 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      71 -&amp;gt; 72         0.69787&#xA; This state for optimization and/or second-order correction.&#xA; Total Energy, E(TD-HF/TD-DFT) =  -897.759895906&#xA; Copying the excited state density for this state as the 1-particle RhoCI density.&#xA;&#xA; Excited State   2:      Triplet-A'     2.7123 eV  457.12 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      71 -&amp;gt; 73         0.68579&#xA;&#xA; Excited State   3:      Triplet-A&amp;quot;     2.9511 eV  420.12 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      67 -&amp;gt; 72         0.13139&#xA;      70 -&amp;gt; 72         0.18527&#xA;      70 -&amp;gt; 73         0.63488&#xA;      70 -&amp;gt; 74         0.12092&#xA;      70 -&amp;gt; 77        -0.10365&#xA;&#xA; Excited State   4:      Triplet-A'     2.9974 eV  413.64 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      65 -&amp;gt; 74         0.11727&#xA;      68 -&amp;gt; 72        -0.28302&#xA;      69 -&amp;gt; 72         0.43278&#xA;      69 -&amp;gt; 75        -0.11938&#xA;      71 -&amp;gt; 74        -0.37857&#xA;&#xA; Excited State   5:      Triplet-A&amp;quot;     3.1360 eV  395.35 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      67 -&amp;gt; 72        -0.19672&#xA;      67 -&amp;gt; 73         0.26224&#xA;      70 -&amp;gt; 72         0.58230&#xA;      70 -&amp;gt; 73        -0.17749&#xA;&#xA; Excited State   6:      Triplet-A'     3.3072 eV  374.89 nm  f=0.0000  &amp;lt;S**2&amp;gt;=2.000&#xA;      66 -&amp;gt; 72        -0.15152&#xA;      66 -&amp;gt; 73         0.52175&#xA;      68 -&amp;gt; 72        -0.17519&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and the same thing for ORCA&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;STATE  1:  E=   0.079273 au      2.157 eV    17398.4 cm**-1 &amp;lt;S**2&amp;gt; =   2.000000&#xA;    70a -&amp;gt;  71a  :     0.961371&#xA;    70a -&amp;gt;  75a  :     0.010646&#xA;     Symmetry: A'&#xA;&#xA;STATE  2:  E=   0.097752 au      2.660 eV    21454.2 cm**-1 &amp;lt;S**2&amp;gt; =   2.000000&#xA;    64a -&amp;gt;  72a  :     0.012920&#xA;    65a -&amp;gt;  72a  :     0.022427&#xA;    65a -&amp;gt;  76a  :     0.010776&#xA;    70a -&amp;gt;  72a  :     0.917057&#xA;     Symmetry: A'&#xA;&#xA;STATE  3:  E=   0.106496 au      2.898 eV    23373.1 cm**-1 &amp;lt;S**2&amp;gt; =   2.000000&#xA;    64a -&amp;gt;  73a  :     0.022177&#xA;    67a -&amp;gt;  71a  :     0.159342&#xA;    67a -&amp;gt;  73a  :     0.015615&#xA;    68a -&amp;gt;  71a  :     0.373134&#xA;    68a -&amp;gt;  73a  :     0.025981&#xA;    68a -&amp;gt;  74a  :     0.023621&#xA;    70a -&amp;gt;  73a  :     0.266489&#xA;    70a -&amp;gt;  74a  :     0.016846&#xA;     Symmetry: A'&#xA;&#xA;STATE  4:  E=   0.108359 au      2.949 eV    23782.0 cm**-1 &amp;lt;S**2&amp;gt; =   2.000000&#xA;    66a -&amp;gt;  71a  :     0.034693&#xA;    66a -&amp;gt;  72a  :     0.014649&#xA;    66a -&amp;gt;  73a  :     0.010149&#xA;    69a -&amp;gt;  71a  :     0.067229&#xA;    69a -&amp;gt;  72a  :     0.806209&#xA;    69a -&amp;gt;  73a  :     0.029132&#xA;    69a -&amp;gt;  76a  :     0.021241&#xA;     Symmetry: A&amp;quot;&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;As you can see, we have a difference of about 0.05 eV which shouldn't be the case as everything is supposed to be the same. I posted the same problem on ORCA forum but was not able to sort out a solution, here are the things I tried:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;When I used the TDA approximation in both, they both gave exact results till the fifth decimal place in electron volt.&lt;/li&gt;&#xA;&lt;li&gt;I tried to run a HF energy calculation for both, I saw the energy results (In Hartrees) began to differ from the sixth decimal place ORCA = -892.3214627659&#xA;Gaussian = -892.3214698.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Given these details, I would really love it if someone could point out what I am doing wrong in this regard. I assume there is some hidden parameter that is defaulted to different values for both. I tried the &lt;code&gt;tightscf&lt;/code&gt; but to no significant improvement. Please let me know what I might be doing wrong.&lt;/p&gt;&#xA;&lt;p&gt;Thanks in advance !&lt;/p&gt;&#xA;" OwnerUserId="8664" LastActivityDate="2024-01-22T13:45:30.530" Title="Trying to get concurrent results for a TDDFT calculation in Gaussian and ORCA" Tags="|gaussian|orca|td-dft|" AnswerCount="2" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12236" PostTypeId="1" CreationDate="2024-01-17T09:53:21.143" Score="2" ViewCount="29" Body="&lt;p&gt;I have noticed very big differences in VASP calculations for the TDOS and PDOS, post-processed with VASPKIT. I have read that could happen because of spilling of electrons.&lt;/p&gt;&#xA;&lt;p&gt;However, I was wondering how to quantify this error practically in a VASP calculation.&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2024-01-17T09:53:21.143" Title="How to calculate spilling factor in VASP?" Tags="|vasp|density-of-states|vaspkit|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12237" PostTypeId="2" ParentId="12234" CreationDate="2024-01-17T10:06:04.917" Score="4" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$N_A$&lt;/span&gt; stands for &lt;strong&gt;Avogadro's number&lt;/strong&gt;. Energies are reported in kJ/mol, so they are technically for a &lt;em&gt;mole of unit cells&lt;/em&gt;. Conversion factors to other units (kcal/mol, eV, Hartree, etc.) can be found or derived easily.&lt;/p&gt;&#xA;&lt;p&gt;Phonopy reports all its quantities for the supplied unit cell. MgO has 8 atoms in its unit cell, so if you want to report values per MgO formula unit, you'll have to divide everything by 4.&lt;/p&gt;&#xA;&lt;p&gt;If you wish to compare systems with different unit cells, you have to take care that you compare quantities that are equivalent. For example, normalized per atom (for single-element compounds), formula unit (multi-element compounds), or molecule (molecular crystals).&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2024-01-17T10:06:04.917" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12239" PostTypeId="1" CreationDate="2024-01-17T16:42:23.647" Score="2" ViewCount="33" Body="&lt;p&gt;I am having a hard time understanding the steps of Tkatchenko's method of many-body dispersion (MBD) and nonlocal many-body dispersion (MBD-NL).&lt;/p&gt;&#xA;&lt;p&gt;I would greatly appreciate a detailed &amp;amp; clear explanation of both methods and how MBD is extended into the MBD-NL.&lt;/p&gt;&#xA;&lt;p&gt;Much Thnx to anyone willing to help :)&lt;/p&gt;&#xA;" OwnerUserId="8675" LastActivityDate="2024-01-17T16:42:23.647" Title="Help with understanding the method of MBD &amp; MBD-NL" Tags="|density-functional-theory|molecular-dynamics|computational-chemistry|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12240" PostTypeId="1" AcceptedAnswerId="12241" CreationDate="2024-01-17T19:13:39.773" Score="6" ViewCount="540" Body="&lt;p&gt;I have limited experience with DFT, but as an exercise I have written a DFT program of an atom (from scratch using nothing more than python built in functions and numpy) by following Richard Martin's book on Electronic Structure calculations from 2004. Now I am trying to learn to use pyscf, but it has limited documentation.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;In the chapter of Richard Marin on pseudopotentials I read that --core states remain almost unchanged when a pseudopotential is introduced. So I do not anticipate that the total energy would change by a factor of 2 or 20 when starting with a pseudopotential.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;However here is a script for bulk diamond (8 atoms per unit cell) after the atoms have been perturbed by a small amount and with lattice constant 3.57 using the Goedecker-Teter-Hutter (GTH) pseudopotential&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import pyscf.pbc.dft as pbcdft&#xA;from pyscf.pbc import gto&#xA;&#xA;cell = gto.Cell()&#xA;cell.a = '''&#xA;3.57  0       0&#xA;0       3.57  0&#xA;0       0       3.57'''&#xA;cell.atom =  '''C       -0.0059      -0.0384      -0.0080&#xA;                C        0.8996       0.8834       0.8834&#xA;                C        1.7947       1.7855       0.0279&#xA;                C        2.6933       2.6673       0.8611&#xA;                C        1.7998       0.0367       1.7496&#xA;                C        2.7021       0.8854       2.6549&#xA;                C       -0.0023       1.7795       1.8028&#xA;                C        0.8828       2.6990       2.6548'''&#xA;cell.basis = 'gth-szv'&#xA;cell.pseudo = 'gth-lda'&#xA;cell.verbose = 4&#xA;cell.build()&#xA;mf=pbcdft.RKS(cell)&#xA;mf.kernel()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and using this script I calculate DFT energy (per unit cell) = -44.871672302677794. I assume that is -152.6275508125 eV per atom. But &lt;a href=&quot;https://www.researchgate.net/figure/a-The-total-energy-per-atom-as-function-of-volume-per-atom-for-carboneyane-T-carbon_fig2_334062238&quot; rel=&quot;noreferrer&quot;&gt;my reference&lt;/a&gt; says I should expect close to 9 eV at 5.687 Ångstrøm&lt;span class=&quot;math-container&quot;&gt;$^3$&lt;/span&gt;/atom. Can you see if it is it my reasoning that the pseudopotential shouldn't change the total energy by a factor of 17 that is wrong, or is it a problem with the PYSCF examples?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;EDIT: I am assuming the input units of pyscf are in Ångstrøm, and the output is given in Hartree (because no units are quoted)&lt;/p&gt;&#xA;" OwnerUserId="8678" LastEditorUserId="8678" LastEditDate="2024-01-17T19:49:57.153" LastActivityDate="2024-01-17T21:38:16.197" Title="pyscf: Why should the choice of pseudopotential determine the total energy, and not the physics?" Tags="|density-functional-theory|electronic-structure|atomic-simulation-environment|pyscf|programming|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12241" PostTypeId="2" ParentId="12240" CreationDate="2024-01-17T21:38:16.197" Score="13" Body="&lt;p&gt;The energy of a system, be it a molecule or a material, is dependent on the energy reference (or energy zero point) you choose. Common energy references are:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The state where all electrons (except for those implicitly described by pseudopotentials, if any) are ionized and have zero kinetic energy, and all nuclei are infinitely far from each other and also have zero kinetic energy. This convention is chosen by most molecular DFT codes.&lt;/li&gt;&#xA;&lt;li&gt;The state where all atoms are free, neutral, and stationary. This convention is chosen by many periodic DFT codes. Some codes also assume the atoms are spin unpolarized and spherically symmetric.&lt;/li&gt;&#xA;&lt;li&gt;The state where all atoms are in their reference elemental states (all carbon atoms as graphite, for example). This convention is chosen by many semiempirical codes.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Generally, the first convention yields very negative energies, because it takes a huge amount of energy to ionize all electrons of a system, or even just the valence electrons. A quick B3LYP/6-31G(d) calculation shows that the energy of a free carbon atom by this convention is about -38 Hartree when core electrons are treated explicitly, or about -5.5 Hartree when they are treated implicitly. The latter is quite close to your value (-153 eV), which proves that PySCF adopts the first convention even in periodic calculations.&lt;/p&gt;&#xA;&lt;p&gt;By comparison, the second convention yields much less negative energies (but usually still negative, since most people study materials that are more stable than free atoms). The third convention generates values that are even smaller in magnitude, and they can often be positive.&lt;/p&gt;&#xA;&lt;p&gt;Within a small enough community, it may be that all programs people use belong to one of the above categories, for example the second one. Then, within that community, it is unambiguous to talk about the absolute energy of a system (or at least its order of magnitude) without worrying about the energy reference. However, it is important to note that the other two conventions exist and are common in their respective communities. This is one of the reasons why energy differences are much more meaningful quantities to talk about in DFT calculations, compared to absolute energies.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2024-01-17T21:38:16.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12242" PostTypeId="2" ParentId="12235" CreationDate="2024-01-18T06:33:08.650" Score="4" Body="&lt;p&gt;These may not be the causes of the issue, but some things to consider:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;By default, Orca uses the RI approximation for DFT calculations. According to @SRMaiti, Gaussian might have RI implemented under the name 'density fitting'; however, I do not think it is on by default. You need to make sure to include NoRI in your Orca input to avoid it.&lt;/li&gt;&#xA;&lt;li&gt;The grids/integrals in Gaussian and Orca are different (Gaussian has much larger/finer integrals, which should, theoretically, produce more precise results). In Orca, you should probably use &lt;em&gt;at least&lt;/em&gt; DefGrid3.&lt;/li&gt;&#xA;&lt;li&gt;Default convergence tolerances will be different between Gaussian and Orca. Probably best to use &lt;code&gt;verytightscf&lt;/code&gt; in Orca.&lt;/li&gt;&#xA;&lt;li&gt;My understanding is that, even though you can use a cc-pvdz basis set in both Gaussian &lt;em&gt;and&lt;/em&gt; Orca, they are still slightly different in how they are implemented. It's something to do with the way the coordinate system works. I could be wrong about this, though, but I have a vague memory of reading that somewhere.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;It is possible that there are some other differences between the two programs which are specific to their TDDFT implementations, but I don't use TDDFT so I cannot help with that. But it's worth keeping in mind that, in general, as far as I am aware, when comparing the &lt;em&gt;default&lt;/em&gt; settings in Gaussian and Orca, Gaussian will prioritises accurate results, whereas Orca seems to prioritise fast results.&lt;/p&gt;&#xA;&lt;p&gt;Just to make it clear, I am not saying that one program is less accurate than the other—you can run very accurate calculations in both—just letting you know what to look out for.&lt;/p&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="7606" LastEditDate="2024-01-20T10:59:54.327" LastActivityDate="2024-01-20T10:59:54.327" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12243" PostTypeId="1" CreationDate="2024-01-19T10:30:20.900" Score="2" ViewCount="170" Body="&lt;p&gt;I am using VASP/5.4.4, one node is equal to 40 core. So for calculations, I used 3 nodes, what should be the NCORE and NPAR for INCAR file?&lt;/p&gt;&#xA;" OwnerUserId="8688" LastEditorUserId="5" LastEditDate="2024-01-19T21:35:33.363" LastActivityDate="2024-01-20T12:20:48.330" Title="How may I select NCORE and NPAR in VASP?" Tags="|vasp|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12244" PostTypeId="1" CreationDate="2024-01-19T13:53:25.747" Score="1" ViewCount="40" Body="&lt;p&gt;I'm trying to insert interstitial defects in an FCC crystal with 32 atoms. And also a quick way of inserting a vacancy or doing a substitutional defect. Any code for this would be deeply appreciated. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="3442" LastActivityDate="2024-01-19T13:53:25.747" Title="Interstitial and vacancy defects" Tags="|vasp|atomic-simulation-environment|pymatgen|defects|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12245" PostTypeId="1" CreationDate="2024-01-19T16:04:26.070" Score="1" ViewCount="40" Body="&lt;p&gt;I was trying to use the get_wigner_seitz_ldos function of GPAW for a toy system (calculated using Gamma point only), and I'm getting the below error.&lt;/p&gt;&#xA;&lt;p&gt;Any ideas how to fix this? Thanks!&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;calc.get_wigner_seitz_ldos(a=0,spin=0, npts=201, width=None)&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/storage/home/nvs5847/.conda/envs/newest_gpaw/lib/python3.11/site-packages/gpaw/calculator.py&amp;quot;, line 1703, in get_wigner_seitz_ldos&#xA;    energies, weights = raw_wignerseitz_LDOS(self, a, spin)&#xA;                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;/storage/home/nvs5847/.conda/envs/newest_gpaw/lib/python3.11/site-packages/gpaw/utilities/dos.py&amp;quot;, line 305, in raw_wignerseitz_LDOS&#xA;    gd.integrate(abs(np.where(atom_index == a, psit_G, 0.0))**2) +&#xA;                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^&#xA;  File &amp;quot;&amp;lt;__array_function__ internals&amp;gt;&amp;quot;, line 200, in where&#xA;&#xA;ValueError: operands could not be broadcast together with shapes (15,15,40) (602,) ()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Here is the corresponding input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase import io&#xA;from ase.io import write&#xA;from gpaw import GPAW, PW&#xA;from gpaw import Mixer, MixerSum, MixerDif&#xA;from ase.optimize import QuasiNewton&#xA;from ase.constraints import StrainFilter, UnitCellFilter&#xA;&#xA;&#xA;cell=io.read('POSCAR')&#xA;cell.center()&#xA;&#xA;#resultfile = open('energies_kpts.txt', 'w')&#xA;&#xA;encut=600&#xA;&#xA;calc_pw = GPAW(txt='C_PW%sx%sx%s.txt' % (1,1,1),xc='LDA',kpts={'size': (1, 1, 1), 'gamma': True},mode=PW(encut))&#xA;cell.set_calculator(calc_pw)&#xA;#optimizing cell&#xA;sf = UnitCellFilter(cell)&#xA;opt = QuasiNewton(sf,trajectory='%sx%sx%s_bfgs_ls.traj' % (1,1,1), restart='%sx%sx%s_bfgs_ls.pckl' % (1,1,1))&#xA;opt.run(0.05,steps=10)&#xA;&#xA;calc_pw.write('gammapt_only_contcar.gpw', mode='all')&#xA;&#xA;&#xA;from gpaw import GPAW, FermiDirac&#xA;import matplotlib.pyplot as plt&#xA;&#xA;from gpaw import GPAW&#xA;&#xA;calc = GPAW('gammapt_only_contcar.gpw')&#xA;&#xA;atom_index=0&#xA;e_a, ldos_a = calc.get_wigner_seitz_ldos(a=atom_index,spin=0, npts=201, width=None) #if width is None: width = 0.1 by default&#xA;plt.plot(e_a - e_f, ldos_a)&#xA;plt.axis([-15, 10, None, 4])&#xA;plt.title(f'Atom # {atom_index}')&#xA;plt.ylabel('LDOS')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And the POSCAR that is read in the beginning is&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;generated by phonopy&#xA;   1.0&#xA;     2.4461088393633634    0.0000000000000000    0.0000000000000000&#xA;    -1.2230544196816819    2.1183923953103418    0.0000000000000000&#xA;     0.0000000000000000    0.0000000000000000    6.6480114768766381&#xA;C&#xA;   4&#xA;Direct&#xA;  0.0000000000000000  0.0000000000000000  0.7500000000000000&#xA;  0.0000000000000000  0.0000000000000000  0.2500000000000000&#xA;  0.6666666666666666  0.3333333333333333  0.7500000000000000&#xA;  0.3333333333333333  0.6666666666666666  0.2500000000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8691" LastEditorUserId="8691" LastEditDate="2024-01-20T00:19:58.157" LastActivityDate="2024-01-20T00:19:58.157" Title="GPAW get_wigner_seitz_ldos Error" Tags="|gpaw|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12246" PostTypeId="1" CreationDate="2024-01-19T17:50:12.107" Score="6" ViewCount="174" Body="&lt;p&gt;I am looking for proxy methods of calculating vdW interactions similar to the DFT-D2, DFT-D3, and DFT-D4 methods which require only atomic positions and/or properties of the atoms.  It would be good to identify relative speeds of methods as well, but the ideal methods should be relatively low cost (more than classical potentials, less than DFT).&lt;/p&gt;&#xA;&lt;p&gt;An easy answer to this is DFT-D2, DFT-D3, and DFT-D4 but I am looking for less well-known alternatives.  If it can run using ASE or LAMMPS as a backend that is best, but I am willing to look at stand-alone tools or even just papers which describe the form.&lt;/p&gt;&#xA;" OwnerUserId="697" LastEditorUserId="5" LastEditDate="2024-01-19T21:06:09.880" LastActivityDate="2024-03-03T16:14:57.440" Title="Calculation of the vdW interactions without DFT" Tags="|reference-request|intermolecular-forces|" AnswerCount="2" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="12247" PostTypeId="1" CreationDate="2024-01-19T19:16:05.260" Score="6" ViewCount="107" Body="&lt;p&gt;I have run a replica-exchange molecular dynamics simulation, using a number, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, of replicas initiated at the same number, &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;, of unique temperatures. I have calculated the free energy profile over this range of temperatures using the potential energy, giving me &lt;span class=&quot;math-container&quot;&gt;$n-1$&lt;/span&gt; free energy points as this is calculated w.r.t. to the lowest temperature.&lt;/p&gt;&#xA;&lt;p&gt;My question is, and I suspect I've misunderstood something crucial, why is it only the potential energy which is considered in the calculation?&lt;/p&gt;&#xA;&lt;p&gt;In the free energy difference:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\Delta F_{ij} = -k_{\text{B}} T_j \ln \left( \frac{Z_j}{Z_i} \right),$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; is the reference. I get that the kinetic part of &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; cancels if they're at the same temperature but that's not the case here is it?&lt;/p&gt;&#xA;&lt;p&gt;My explanation as of now is that since I calculated the free energy using the configurations from each replica, not from temperature data, in each calculation using the configurations from the replicas they all have the same &amp;quot;effective&amp;quot; temperature and so the kinetic cancels. This is because I'm not really calculating free energy difference between different temperatures but more so of different states, but I feel like this is a weak explanation since these states differ only by temperature?&lt;/p&gt;&#xA;" OwnerUserId="8634" LastEditorUserId="5" LastEditDate="2024-01-19T21:04:33.517" LastActivityDate="2024-01-20T20:24:25.033" Title="Why is potential energy used and not total energy when calculating free energy?" Tags="|molecular-dynamics|statistical-thermodynamics|free-energy|" AnswerCount="0" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12248" PostTypeId="1" CreationDate="2024-01-19T21:12:53.800" Score="2" ViewCount="70" Body="&lt;p&gt;I have a compound (5c from &lt;a href=&quot;https://doi.org/10.1021/acs.inorgchem.1c02193&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;) as below which I wish to optimize in ORCA. However, I am not sure what is its charge and multiplicity.&lt;/p&gt;&#xA;&lt;p&gt;This is an Ir(III) complex. Iridium has a valence configuration of &lt;code&gt;[Xe] 4f14 5d7 6s2&lt;/code&gt; so for the Ir(III) it'll be &lt;code&gt;[Xe] 4f14 5d6&lt;/code&gt;. The box representation of subshell 5d is &lt;code&gt;5d [↑↓] [↑] [↑] [↑] [↑]&lt;/code&gt; indicating four free electrons. And what now? Ir is covalently bound to aromatic C and Cl, and coordinated/bound to aromatic anion of cyclopentadiene, but N cannot participate in neither covalent nor coordinating bonds for it has no free electrons...?&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/98LBO.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/98LBO.png&quot; alt=&quot;complex&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8524" LastEditorUserId="5" LastEditDate="2024-01-19T21:33:35.660" LastActivityDate="2024-01-19T21:33:35.660" Title="How do I determine the charge and spin multiplicity of a system?" Tags="|quantum-chemistry|orbitals|transition-metals|spin|metal-complexes|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12249" PostTypeId="2" ParentId="12248" CreationDate="2024-01-19T21:32:01.190" Score="2" Body="&lt;p&gt;My answer to &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/11478/5&quot;&gt;How to select charge and multiplicity for macro-molecules?&lt;/a&gt;&amp;quot; explains how to find the charge and multiplicity of a system. The reason why you cannot just figure it out based on the knowledge that you currently have about the system (e.g. you gave the electronic configuration for iridium in your question) is explained in my answer to &amp;quot;&lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1247/5&quot;&gt;Total spin and/or multiplicity for transition metal ions?&lt;/a&gt;&amp;quot; (basically, even for a diatomic molecule like Fe2, scientists today are not sure what the spin multiplicity is for the ground state, because it is too complicated to determine based on the type of information that you're trying to use, so I recommend that you follow the procedure given in my answer to &amp;quot;How to select charge and multiplicity for macro-molecules?&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;I considered to vote to close this question as a duplicate of the one about macro-molecules, but it is not the same question, even though it has the same answer (and the answer that I'm currently writing for you here, explained why the answer to your question is the same as the answer in the case of macro-molecules).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-19T21:32:01.190" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12250" PostTypeId="2" ParentId="12243" CreationDate="2024-01-20T08:41:10.250" Score="4" Body="&lt;p&gt;This question has appeared so many times among VASP users either on ResearchGate &lt;a href=&quot;https://www.researchgate.net/post/How_to_optimize_parallelization_in_VASP&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;,&lt;a href=&quot;https://www.researchgate.net/post/NCORE-and-NPAR-in-VASP&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;, or &lt;a href=&quot;https://wwww.vasp.at/forum/viewtopic.php?t=13310&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP forum&lt;/a&gt;  but it seems that there still exist some difficulties in making the right choice for setting up the parallelization parameters. I have to mention that some good answers could be found in the mentioned links. Moreover, a good starting point is the answer &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/4529/1554&quot;&gt;here&lt;/a&gt;, one practical benchmarking approach in the comments is also suggested &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/2039/parallelization-in-vasp&quot;&gt;here&lt;/a&gt; by Tristan Maxson. Thus, I will try to combine what I have experienced on my own and answers I have come across from other users. For clarification, I am using VASP 5.4 and to my knowledge only MPI parallelization is used in this version, so when I use the term “core”, I mean the number of MPI ranks or processes, for example the number you give to the mpirun command using the -n command line flag or the number of cores you request in the queue system.&lt;/p&gt;&#xA;&lt;p&gt;Now let's start with numer of cores, you will hear alot of people stating that you need to do your testing for the number of cores (which is True), but as a good start you can set &lt;code&gt;number of cores = number of atoms&lt;/code&gt;. VASP has three levels of parallelization: over k-points, over bands, and over plane-wave coefficients or equivalently Fast-Fourier transforms. You have to make sure that when the work is split up among several computing nodes, there is a sufficient amount of work allocated to each processor core, otherwise, they will just spend time waiting for more work to arrive. Therefore, the fundamental numbers to be aware of are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The number of bands&lt;/li&gt;&#xA;&lt;li&gt;The number of k-points&lt;/li&gt;&#xA;&lt;li&gt;The size of the basis set&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;NPAR &amp;amp; NBANDS:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I will first address &lt;code&gt;NPAR&lt;/code&gt; and &lt;code&gt;NBANDS&lt;/code&gt; as they are correlated. VASP has parallelization over bands (controlled via the &lt;code&gt;NPAR&lt;/code&gt; tag), where the default (NPAR=number of MPI ranks or cores). If you are not explicitly setting those two tags in your inputs, VASP will try to make sure that there is an equal number of bands on each node, when parallelizing over bands. Thus, one can unknowingly perform calculations with different number of bands when changing the number of cores in the job script. So, you have to set NPAR and NBANDS in the INCAR file. Alternatively, make sure that you have converged your calculation with respect to the number of bands. VASP guesses the number bands with quite a large safety margin, but it is not always enough!&lt;/p&gt;&#xA;&lt;p&gt;Suppose you have 100 bands, you cannot run on more than 100 cores and expect it to work well. However, 1 band per core is very little work for a today's processor. You may need at least 2 bands per core to reach more than 50% efficiency. Then a better choice is 8 bands/core which will put you closer to 90% efficiency. So try to achieve the following &lt;code&gt;number of cores = NBANDS / 8&lt;/code&gt;. For example, if you have a cell with 500 bands and a cluster with compute nodes having 16 cores per node. We aim for 8 bands/core, which unfortunately means 62.5 cores. It is better to have &lt;strong&gt;even numbers&lt;/strong&gt;, so we increase the number of bands to 512 by setting &lt;code&gt;NBANDS=512&lt;/code&gt; in the INCAR file and allocate 64 cores, or 4 nodes.&lt;/p&gt;&#xA;&lt;p&gt;Now for &lt;code&gt;NPAR&lt;/code&gt;, VASP wiki recommendation is  to set &lt;code&gt;NPAR = square root of (number of processor cores)&lt;/code&gt;, keep that recommendation in mind but you should also know that the achitecture of the processors or clusters will have an influence in here as it has to do with how the nodes communicate with each other. In some cases, &lt;code&gt;NPAR = number of compute nodes / 2&lt;/code&gt; and in other cases &lt;code&gt;NPAR = number of compute nodes&lt;/code&gt;, you may find that by yourself, depending on the cluster you are using.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;KPAR:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;KPAR controls the number of k-point groups that run in parallel. The upper limit of KPAR is obviously the number of k-points in your calculation. In practice, k-point parallelization does not scale that well. So set &lt;code&gt;KPAR=compute nodes&lt;/code&gt;. Regardless of the actual value of KPAR, it is &lt;strong&gt;not&lt;/strong&gt; recommended to run with &lt;code&gt;KPAR&amp;gt;compute nodes&lt;/code&gt;, even though you may have more k-points than compute nodes. For instance, take the 500 bands mentioned before. 64 cores was a good choice when using just band parallelization, suppose you have 8 k-points. Then set KPAR to 8 and double the number of cores to 128 cores (or 8 nodes). In this case, you have 1 k-point per node, which is a very balanced setup. In cases where run out of memory lower down KPAR to 4 or 2.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;NGZ:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;By default, VASP works with the FFTs in a plane-wise manner (&lt;code&gt;LPLANE=.TRUE.&lt;/code&gt;). In the ideal case , you want NGZ (the number of grid points in the Z direction) to be evenly divisible by NPAR. That will ensure good load-balance (&lt;code&gt;NGZ=n*NPAR&lt;/code&gt;). According to VASP wiki you should also consider that NGZ should be sufficiently big for the LPLANE approach to work, thus, (&lt;code&gt;NGZ ≥ 3*(number of cores)/NPAR = 3*NCORE&lt;/code&gt;)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Quick Solution:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;start with (NBANDS). The number of bands divided by 8&#xA;is a good starting guess for the number of cores to use for your&#xA;calculation.&lt;/li&gt;&#xA;&lt;li&gt;set NPAR = number of compute nodes / 2 or in some cases NPAR = number&#xA;of compute nodes, depending on the architecture of your processor.&lt;/li&gt;&#xA;&lt;li&gt;set KPAR to the number of compute nodes or the number of k-points, whichever is the smallest number. Then double the amount of cores determined in the previous step.&lt;/li&gt;&#xA;&lt;li&gt;Make a test run and check the value of NGZ, it should be an even&#xA;number and sufficiently big (larger than 3*cores/node).&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-01-20T12:20:48.330" LastActivityDate="2024-01-20T12:20:48.330" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12252" PostTypeId="2" ParentId="12213" CreationDate="2024-01-21T00:16:14.660" Score="0" Body="&lt;p&gt;This was &lt;a href=&quot;https://bioinformatics.stackexchange.com/a/22044/3621&quot;&gt;answered at Bioinformatics.SE&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, I am removing it from our unanswered queue.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-21T00:16:14.660" CommentCount="0" CommunityOwnedDate="2024-01-21T00:16:14.660" ContentLicense="CC BY-SA 4.0" />
  <row Id="12253" PostTypeId="1" CreationDate="2024-01-21T01:47:29.630" Score="3" ViewCount="76" Body="&lt;p&gt;Is it necessary to perform a new geometric relaxation with vdW corrections enabled for each implementation (DFT-D2, DFT-D3, etc.) when comparing their effects on the adsorption of small molecules on a surface? Or can I use the initially relaxed structure (without vdW corrections) and simply incorporate the vdW corrections during the SCF calculation?&lt;/p&gt;&#xA;" OwnerUserId="8651" LastActivityDate="2024-01-21T04:00:20.023" Title="vdW Corrections for Comparing the Effects on Small Molecule Adsorption" Tags="|density-functional-theory|ab-initio-calculations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12254" PostTypeId="1" CreationDate="2024-01-21T02:21:48.893" Score="3" ViewCount="140" Body="&lt;p&gt;I am currently encountering challenges in successfully conducting NPT simulations in LAMMPS for a triclinic cell persistently remain unchanged throughout the NPT simulation.my input file is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Units and boundary conditions&#xA;units           lj&#xA;boundary        s s s&#xA;&#xA;# Atom style&#xA;atom_style      atomic&#xA;&#xA;# Pair potential&#xA;pair_style      lj/cut&#xA;pair_coeff      1 1 1.0 1.0&#xA;&#xA;# Initial velocity&#xA;velocity        all create 1.0 87287&#xA;&#xA;# Time step&#xA;timestep        0.005&#xA;&#xA;# NVT settings&#xA;fix             mynvt all nvt temp 1.0 1.0 10.0&#xA;&#xA;# Dump settings&#xA;dump            mydmp all custom 1 dump.lammpstrj id type xs ys zs vx vy vz&#xA;&#xA;# Thermodynamic output&#xA;thermo_style    custom step time temp etotal press&#xA;thermo          1&#xA;thermo_modify   format 4 %20.15g&#xA;thermo_modify   format 8 %20.15g&#xA;thermo_modify   format 9 %20.15g&#xA;thermo_modify   format 10 %20.15g&#xA;thermo_modify   format 11 %20.15g&#xA;&#xA;# Run the simulation&#xA;run             1000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8698" LastEditorUserId="5338" LastEditDate="2024-01-26T18:01:20.427" LastActivityDate="2024-01-26T18:01:20.427" Title="having trouble to get the NPT working" Tags="|molecular-dynamics|molecular-modeling|lammps|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12255" PostTypeId="2" ParentId="12253" CreationDate="2024-01-21T04:00:20.023" Score="4" Body="&lt;p&gt;Using DFT, DFT-D2, DFT-D3, and DFT-4 will all give you slightly different energies at each geometry, and therefore you will get slightly different geometries if you do a geometry optimization with each of those methods.&lt;/p&gt;&#xA;&lt;p&gt;Whether or not these differences in geometries matter to you will depend on many factors, such as the computational cost of the geometry optimization calculations (we can't know this without knowing your system), the required accuracy, and the DFT functionals used, among other factors.&lt;/p&gt;&#xA;&lt;p&gt;I recommend to strike the best possible balance between computational cost and computational accuracy that you can achieve for the geometry optimization (when choosing whether to use DFT, DFT-D2, DFT-D3, DFT-D4, etc.), then to do single point energy calculations at the relaxed geometry with all of those methods. If you are seeing drastic changes in the single-point energy, then perhaps the optimal geometries will also be quite different for each of those methods. If you are seeing barely any difference in the single-point energies, then depending on what the final goals are for your project, perhaps it's okay for you to move on with your project, at the relaxed geometry that you found in your first attempt.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-21T04:00:20.023" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12256" PostTypeId="1" CreationDate="2024-01-21T12:23:15.027" Score="7" ViewCount="160" Body="&lt;p&gt;A significant part of quantum chemistry involves developing methods that go beyond the Hartree-Fock theory which treats electron-electron interactions through a mean-field approach. From what I understand much of the emphasis in this program of research is towards capturing as much of the correlation energy as possible. Interestingly, the definition of the correlation energy here, is the relative difference in energy calculated using the exact and mean-field approaches.&lt;/p&gt;&#xA;&lt;p&gt;However, I find it hard to develop the link between correlation or entanglement between electrons to chemical bonding. For example, in this &lt;a href=&quot;https://doi.org/10.1002/ijch.202100111&quot; rel=&quot;noreferrer&quot;&gt;article&lt;/a&gt;, electron correlation is referred to as the &amp;quot;chemical glue&amp;quot;. How does one make sense of correlation in motion of electrons being somehow related to bonding?&lt;/p&gt;&#xA;" OwnerUserId="5884" LastActivityDate="2024-01-26T01:16:35.930" Title="Why is electron correlation called the &quot;chemical glue&quot;?" Tags="|quantum-chemistry|molecular-modeling|electronic-structure|electron-correlation|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12257" PostTypeId="1" CreationDate="2024-01-21T17:38:04.210" Score="3" ViewCount="125" Body="&lt;p&gt;I have been calculating the interaction energy of a single CO2 molecule with a cristobalite silica surface (~300 atoms) using single point calculations in VASP. As I calculated the energies and plotted them I saw that the energy is not converging to zero at longer distances. I am attaching the INCAR file and how the energy plot looks like. Can someone kindle suggest me a solution. I am using a 1&lt;em&gt;1&lt;/em&gt;1 gamma grid of KPOINTS. &lt;a href=&quot;https://i.stack.imgur.com/J8YLr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/J8YLr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    # ----- SCF of adsorption calculation ------&#xA;# ==========================================&#xA;&#xA;# General Setup&#xA;  SYSTEM   = SCF of silica/CO2 &#xA;  NWRITE   = 2&#xA;  PREC = NORMAL    &#xA;  ENCUT = 450&#xA;  ISTART =  0      #Default: ISTART = 1 if WAVECAR exists, = 0 else&#xA;  ICHARG =  2      #Default: ICHARG = 2 if ISTART=0, = 0 else&#xA;&#xA;# Electronic Relaxation&#xA;  NELM = 150 #Increase the iterations.&#xA;  EDIFF    = 1.0E-05  # Increase the stopping criteria for ESC&#xA;  LREAL    = AUTO   # Real space projection&#xA;  IALGO    = 38       # Electronic algorithm minimization&#xA;  ADDGRID  = .TRUE.   # Improve the grid accuracy&#xA;&#xA;&#xA;# Ionic Relaxation&#xA;# EDIFFG   = 1.0E-04  # Stopping criteria for ionic self cons steps&#xA;  NSW      = 0        # Max Number of ISC steps: 0- Single Point&#xA;  ISIF     = 2        # Ionic Relaxation&#xA;  IBRION   = -1       # Single Point&#xA;  SIGMA    = 0.10     # Insulators/semiconductors=0.1  metals=0.05&#xA;  ISMEAR   = 0        # Partial Occupancies for each Orbital&#xA;                      # -5 DOS, -2 from file, -1 Fermi Smear, 0 Gaussian Smear&#xA;&#xA;  LCHARG = .FALSE. #do not write CHGCAR file&#xA;  LWAVE  = .FALSE. #write to WAVECAR file&#xA;&#xA;# vdW corrections&#xA;  IVDW   =  11&#xA;    VDW_RADIUS = 10.0&#xA;&#xA;# Exchange correlation treatment:&#xA;   GGA    = PE&#xA;&#xA;# Parallelization&#xA;  NCORE=4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6839" LastEditorUserId="5" LastEditDate="2024-01-22T05:39:50.260" LastActivityDate="2024-01-22T05:39:50.260" Title="Why is my interaction energy not converging to zero?" Tags="|vasp|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12258" PostTypeId="2" ParentId="12257" CreationDate="2024-01-21T23:55:06.713" Score="2" Body="&lt;p&gt;The energy is not expected to converge to zero (for very large distances). For example, if you were to calculate the energy for a CO (carbon monoxide) molecule as a function of internuclear distance between the C and O nuclei, the energy as the internuclear distance becomes infinitely large, will converge to the sum of the individual C atom energy and O atom energy:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\lim_{r\rightarrow \infty} E_{~\textrm{CO}}~~(r) = E_{~\textrm{C}} + E_{~\textrm{O}}~.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In your case, the energy is expected to converge to the sum of the CO2 energy and the energy of the ~300-atom surface. If you calculate the CO2 energy and the energy of the ~300-atom surface individually, and add them together, I would anticipate that you would get the energy of about -0.02 eV that we see in your figure.&lt;/p&gt;&#xA;&lt;p&gt;The energy &lt;em&gt;&lt;strong&gt;difference&lt;/strong&gt;&lt;/em&gt; can be expected to converge to zero, but not the total energies.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-21T23:55:06.713" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12259" PostTypeId="1" AcceptedAnswerId="12289" CreationDate="2024-01-22T04:31:22.080" Score="5" ViewCount="124" Body="&lt;p&gt;I know that semiconductors have a band gap, and conductors have bands that cross the Fermi level. However, can a material have a band gap for certain &lt;span class=&quot;math-container&quot;&gt;$\vec k$&lt;/span&gt; regions but bands cross the Fermi level only for a certain &lt;span class=&quot;math-container&quot;&gt;$\vec k$&lt;/span&gt;? Does this mean that a material is a conductor in one direction and a semiconductor in perpendicular direction?&lt;/p&gt;&#xA;&lt;p&gt;This paper [&lt;a href=&quot;https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.87.196803&quot; rel=&quot;noreferrer&quot;&gt;1&lt;/a&gt;] shows that a semiconducting MoS2 can have metallic edges. It also mentions that bulk materials can have two-dimensional metallic surfaces. This paper [&lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.nanolett.1c00915#&quot; rel=&quot;noreferrer&quot;&gt;2&lt;/a&gt;] shows conductive copper channels in a semiconducting black phosphorus. Some bands in its band structure cross the Fermi level (Fig. 5C), so it should be a metal, however the conductivity in the perpendicular direction is lower, as shown in their Fig. 5D.&lt;/p&gt;&#xA;&lt;p&gt;Most band structures of conductors that I saw cross the Fermi level somewhere and don't cross them in other places, so I am confused.&lt;/p&gt;&#xA;&lt;p&gt;Can a material be a conductor in one direction and a semiconductor in another direction and how can I see it from the band structure?&lt;/p&gt;&#xA;" OwnerUserId="81" LastActivityDate="2024-01-26T22:11:52.407" Title="Can a material be a conductor in one direction and a semiconductor in another direction?" Tags="|band-structure|bandgap|metals|semiconductor|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12260" PostTypeId="1" CreationDate="2024-01-22T05:13:29.710" Score="2" ViewCount="48" Body="&lt;p&gt;I have been trying to do Piezoelectric and Elastic calculations for my system in VASP, and i ended up with this error.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Spin polarized Harris functional is a good joke&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What am I doing wrong? Here is the INCAR I used for piezoelectric.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;LWAVE=.TRUE.&#xA;LCHARG=.TRUE.&#xA;ENCUT = 550&#xA;PREC = Accurate&#xA;ISTART = 1&#xA;ICHARG= 11&#xA;LREAL= Auto&#xA;ALGO =  Fast&#xA;LORBIT=11&#xA;LEPSILON= .TRUE.&#xA;&#xA;#--------- Electronic relaxation --------&#xA;ISMEAR = 0&#xA;SIGMA = 0.01&#xA;NELM = 60&#xA;NELMIN = 6&#xA;EDIFF = 0.0000001&#xA;&#xA;#--------- Magnetic calculation ------------&#xA;ISPIN = 2&#xA;MAGMOM = 8*5 8*5 24*5&#xA;&#xA;#------- IONIC Relaxation -----&#xA;NSW = 1&#xA;IBRION = 8&#xA;ISIF = 3&#xA;&#xA;#-------- SLR ---------&#xA;POTIM = 0.015&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8704" LastActivityDate="2024-01-22T05:13:29.710" Title="Error in VASP calculation" Tags="|vasp|ab-initio-calculations|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12261" PostTypeId="1" CreationDate="2024-01-22T09:43:36.617" Score="1" ViewCount="89" Body="&lt;p&gt;I'm doing geometry optimization of bilayer h-BN, a 72-atom supercell (6x6x1) with vacuum thickness of 20 Å, and I set the parameters in INCAR as below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ISTART = 0 #begin from scratch\&#xA;ICHARG = 2 #initial charge density\&#xA;LREAL = Auto\&#xA;ISMEAR = 0\&#xA;SIGMA = 0.02\&#xA;ENCUT = 400\&#xA;PREC = Normal\&#xA;ISIF = 3 #change of cell\&#xA;ISPIN = 1 #spin\&#xA;NSW = 500 #maximun ion step\&#xA;IBRION = 2 #conjugate gradient algorithm\&#xA;POTIM = 0.5  #step size of ion\&#xA;EDIFF = 1E-6 #standard of electronic convergence\&#xA;EDIFFG = -0.01 #standard of ion step convergence\&#xA;IVDW = 12 #vdw_D3\&#xA;LWAVE = .FALSE.\&#xA;LCHARG = .FALSE.\&#xA;ALGO = Fast&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But interestingly, the vacuum layer disappeared, why it comes like that? And how should I maintain the vacuum layer during relaxing?&lt;/p&gt;&#xA;" OwnerUserId="7387" LastEditorUserId="1554" LastEditDate="2024-01-22T10:20:01.700" LastActivityDate="2024-02-15T21:04:52.810" Title="Disappearing vacuum layer when relaxing bilayered hBN with VASP" Tags="|density-functional-theory|vasp|geometry-optimization|condensed-matter|atomic-simulation-environment|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12262" PostTypeId="2" ParentId="12256" CreationDate="2024-01-22T10:01:17.070" Score="6" Body="&lt;p&gt;Coincidentially, I recently read Perdew's recent autobiographical &lt;a href=&quot;https://doi.org/10.1063/5.0179606&quot; rel=&quot;noreferrer&quot;&gt;article&lt;/a&gt; where he also mentions the concept of &amp;quot;chemical glue.&amp;quot; His simple image is as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The exchange–correlation energy is a relatively small part of the&#xA;total energy, but it dominates the binding energy and has been called&#xA;“nature’s glue.” In a nutshell, the electrons swerve to avoid one&#xA;another (like shoppers in a crowded mall) because of the Pauli&#xA;exclusion principle and the Coulomb repulsion between electrons. This&#xA;lowers the total energy, and does so more in bonded systems than in&#xA;separated atoms because bonded systems have more nearby electrons to&#xA;be avoided. This “dance of the electrons” is the largest part of what&#xA;binds atoms together.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Perdew is a DFT person, so he lumps together exchange and correlation contributions. Assuming exchange (i.e., the Pauli principle) is accounted for (as in Hartree-Fock theory), only correlation remains. Correlation lowers the energy of the system because electrons avoid each other (compared to mean field approximations). The more electrons there are, the more this effect will be in play (a one-electron system will have no correlation). Thus, at least part of chemical bonding (which brings electrons together in a small volume) arises from correlation.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2024-01-22T10:01:17.070" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12263" PostTypeId="2" ParentId="12254" CreationDate="2024-01-22T10:09:31.017" Score="3" Body="&lt;p&gt;The &lt;code&gt;aniso&lt;/code&gt; keyword requests anisotropic pressure control, meaning that only &lt;strong&gt;box lengths&lt;/strong&gt; are controlled independently:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The keyword aniso means x, y, and z dimensions are controlled&#xA;independently using the Pxx, Pyy, and Pzz components of the stress&#xA;tensor as the driving forces, and the specified scalar external&#xA;pressure.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;(from the &lt;a href=&quot;https://docs.lammps.org/fix_nh.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;LAMMPS manual&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;If you want to change the &lt;strong&gt;box angles&lt;/strong&gt; as well, you'll have to use &lt;code&gt;tri&lt;/code&gt;, allowing for a triclinic box:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;fix             mynpt all npt temp 100.0 100.0 &lt;span class=&quot;math-container&quot;&gt;$(100.0*dt) tri 1 1 $&lt;/span&gt;(1000*dt)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2024-01-26T09:16:51.633" LastActivityDate="2024-01-26T09:16:51.633" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12264" PostTypeId="1" AcceptedAnswerId="12266" CreationDate="2024-01-22T11:41:11.150" Score="2" ViewCount="167" Body="&lt;p&gt;How can one verify that the values (0, 1, 2, and 3) in the &lt;strong&gt;SMASS&lt;/strong&gt; parameter correspond appropriately to the NVT ensemble(Nose-Hoover thermostat) in the context of an ab initio molecular dynamics simulation on a Pd(111) surface with dimensions 2x2x6 at 300K?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastActivityDate="2024-01-22T14:18:02.077" Title="Choice of SMASS for AIMD simulations in VASP" Tags="|vasp|molecular-dynamics|molecular-modeling|condensed-matter|aimd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12265" PostTypeId="2" ParentId="12235" CreationDate="2024-01-22T13:45:30.530" Score="3" Body="&lt;p&gt;To my knowledge (and depending on the version you use) ORCA uses RI-J and semi-numerical exchange (COSX) by default which might have a larger influence on the RPA TDDFT values in contrast to the TDA TDDFT ones?&#xA;To answer that I ran a quick check with Turbomole to have a third option and also to compare RI-J/COSX to the non-RI/COSX results.&lt;/p&gt;&#xA;&lt;p&gt;Results without any technical tricks or approximations (no RI, no COSX, just plain DFT):&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;No. Exc.&lt;/th&gt;&#xA;&lt;th&gt;energy (Eh)&lt;/th&gt;&#xA;&lt;th&gt;energy (eV)&lt;/th&gt;&#xA;&lt;th&gt;energy (cm-1)&lt;/th&gt;&#xA;&lt;th&gt;energy (nm)&lt;/th&gt;&#xA;&lt;th&gt;Osc.(vel)&lt;/th&gt;&#xA;&lt;th&gt;Osc.(len)&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1 a'&lt;/td&gt;&#xA;&lt;td&gt;0.081022&lt;/td&gt;&#xA;&lt;td&gt;2.20472&lt;/td&gt;&#xA;&lt;td&gt;0.17782269D+05&lt;/td&gt;&#xA;&lt;td&gt;562.358&lt;/td&gt;&#xA;&lt;td&gt;0.88132878&lt;/td&gt;&#xA;&lt;td&gt;0.92585267&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2 a'&lt;/td&gt;&#xA;&lt;td&gt;0.099666&lt;/td&gt;&#xA;&lt;td&gt;2.71204&lt;/td&gt;&#xA;&lt;td&gt;0.21874084D+05&lt;/td&gt;&#xA;&lt;td&gt;457.162&lt;/td&gt;&#xA;&lt;td&gt;0.11816715&lt;/td&gt;&#xA;&lt;td&gt;0.13580095&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;1 a&amp;quot;&lt;/td&gt;&#xA;&lt;td&gt;0.108444&lt;/td&gt;&#xA;&lt;td&gt;2.95092&lt;/td&gt;&#xA;&lt;td&gt;0.23800783D+05&lt;/td&gt;&#xA;&lt;td&gt;420.154&lt;/td&gt;&#xA;&lt;td&gt;0.00045973&lt;/td&gt;&#xA;&lt;td&gt;0.00031559&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3 a'&lt;/td&gt;&#xA;&lt;td&gt;0.110137&lt;/td&gt;&#xA;&lt;td&gt;2.99698&lt;/td&gt;&#xA;&lt;td&gt;0.24172289D+05&lt;/td&gt;&#xA;&lt;td&gt;13.697&lt;/td&gt;&#xA;&lt;td&gt;0.02083900&lt;/td&gt;&#xA;&lt;td&gt;0.02021690&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2 a&amp;quot;&lt;/td&gt;&#xA;&lt;td&gt;0.115230&lt;/td&gt;&#xA;&lt;td&gt;3.13556&lt;/td&gt;&#xA;&lt;td&gt;0.25289985D+05&lt;/td&gt;&#xA;&lt;td&gt;395.413&lt;/td&gt;&#xA;&lt;td&gt;0.00007985&lt;/td&gt;&#xA;&lt;td&gt;0.00012440&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4 a'&lt;/td&gt;&#xA;&lt;td&gt;0.121520&lt;/td&gt;&#xA;&lt;td&gt;3.30673&lt;/td&gt;&#xA;&lt;td&gt;0.26670553D+05&lt;/td&gt;&#xA;&lt;td&gt;374.945&lt;/td&gt;&#xA;&lt;td&gt;0.40035164&lt;/td&gt;&#xA;&lt;td&gt;0.44081543&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3 a&amp;quot;&lt;/td&gt;&#xA;&lt;td&gt;0.138418&lt;/td&gt;&#xA;&lt;td&gt;3.76654&lt;/td&gt;&#xA;&lt;td&gt;0.30379186D+05&lt;/td&gt;&#xA;&lt;td&gt;329.173&lt;/td&gt;&#xA;&lt;td&gt;0.00000937&lt;/td&gt;&#xA;&lt;td&gt;0.00003855&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4 a&amp;quot;&lt;/td&gt;&#xA;&lt;td&gt;0.151245&lt;/td&gt;&#xA;&lt;td&gt;4.11560&lt;/td&gt;&#xA;&lt;td&gt;0.33194527D+05&lt;/td&gt;&#xA;&lt;td&gt;301.254&lt;/td&gt;&#xA;&lt;td&gt;0.00093093&lt;/td&gt;&#xA;&lt;td&gt;0.00049491&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;so Gaussian and Turbomole give the same results up to about 1meV (most likely due to different DFT grids used).&lt;/p&gt;&#xA;&lt;p&gt;To check the influence of RI-J and COSX, I also ran those calculations using Turbomole to get the deviations:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&#xA;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;raw DFT&lt;/th&gt;&#xA;&lt;th&gt;with RI-J&lt;/th&gt;&#xA;&lt;th&gt;with RI-J+COSX&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2.20472&lt;/td&gt;&#xA;&lt;td&gt;2.20472&lt;/td&gt;&#xA;&lt;td&gt;2.20508&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2.71204&lt;/td&gt;&#xA;&lt;td&gt;2.71239&lt;/td&gt;&#xA;&lt;td&gt;2.71078&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2.95092&lt;/td&gt;&#xA;&lt;td&gt;2.95105&lt;/td&gt;&#xA;&lt;td&gt;2.94974&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;2.99698&lt;/td&gt;&#xA;&lt;td&gt;2.99717&lt;/td&gt;&#xA;&lt;td&gt;2.99650&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3.13556&lt;/td&gt;&#xA;&lt;td&gt;3.13544&lt;/td&gt;&#xA;&lt;td&gt;3.13856&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3.30673&lt;/td&gt;&#xA;&lt;td&gt;3.30707&lt;/td&gt;&#xA;&lt;td&gt;3.30659&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;3.76654&lt;/td&gt;&#xA;&lt;td&gt;3.76660&lt;/td&gt;&#xA;&lt;td&gt;3.76723&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;4.11560&lt;/td&gt;&#xA;&lt;td&gt;4.11558&lt;/td&gt;&#xA;&lt;td&gt;4.11933&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;/div&gt;&#xA;&lt;p&gt;This indicates that the deviations between Gaussian and ORCA results probably do not stem from the ‚numerical tricks‘ RI and COSX.&lt;/p&gt;&#xA;" OwnerUserId="1997" LastActivityDate="2024-01-22T13:45:30.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12266" PostTypeId="2" ParentId="12264" CreationDate="2024-01-22T14:18:02.077" Score="5" Body="&lt;p&gt;If you are on VASP, there is a &lt;a href=&quot;https://github.com/QijingZheng/pyband/blob/master/nose_mass.py&quot; rel=&quot;noreferrer&quot;&gt;script&lt;/a&gt; from Qijing Zheng to whom goes the credit, with this script you can estimate the value of SMASS. Just in case you can't access that, I am leaving you the script in here:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/usr/bin/env python&#xA;# -*- coding: utf-8 -*-&#xA;&#xA;import argparse&#xA;import ase&#xA;import sys&#xA;import numpy as np&#xA;from ase.io import read, write&#xA;&#xA;&#xA;def nose_mass(temperature, ndof, t0, L):&#xA;    '''&#xA;    Suggested Q:&#xA;&#xA;        Shuichi Nosé, J. Chem. Phys., 81, 511(1984). &#xA;&#xA;    input:&#xA;&#xA;    temperaute: in unit of Kelvin&#xA;    ndof: No. of degrees of freedom&#xA;    t0: The oscillation time in fs&#xA;    L: the length of the first basis vector&#xA;    '''&#xA;&#xA;    # Q in Energy * Times**2&#xA;    qtmp = (t0 * 1E-15 / np.pi / 2)**2 * \&#xA;        2 * ndof * ase.units.kB * temperature \&#xA;        * ase.units._e&#xA;&#xA;    # Q in AMU * Angstrom**2&#xA;    Q = qtmp / ase.units._amu / (L * 1E-10)**2&#xA;&#xA;    return Q&#xA;&#xA;&#xA;def cnt_dof(atoms):&#xA;    '''&#xA;    Count No. of Degrees of Freedom&#xA;    '''&#xA;    if atoms.constraints:&#xA;        from ase.constraints import FixAtoms, FixScaled, FixedPlane, FixedLine&#xA;        sflags = np.zeros((len(atoms), 3), dtype=bool)&#xA;        for constr in atoms.constraints:&#xA;            if isinstance(constr, FixScaled):&#xA;                sflags[constr.a] = constr.mask&#xA;            elif isinstance(constr, FixAtoms):&#xA;                sflags[constr.index] = [True, True, True]&#xA;            elif isinstance(constr, FixedPlane):&#xA;                mask = np.all(np.abs(np.cross(constr.dir, atoms.cell)) &amp;lt; 1e-5,&#xA;                              axis=1)&#xA;                if sum(mask) != 1:&#xA;                    raise RuntimeError(&#xA;                        'VASP requires that the direction of FixedPlane '&#xA;                        'constraints is parallel with one of the cell axis')&#xA;                sflags[constr.a] = mask&#xA;            elif isinstance(constr, FixedLine):&#xA;                mask = np.all(np.abs(np.cross(constr.dir, atoms.cell)) &amp;lt; 1e-5,&#xA;                              axis=1)&#xA;                if sum(mask) != 1:&#xA;                    raise RuntimeError(&#xA;                        'VASP requires that the direction of FixedLine '&#xA;                        'constraints is parallel with one of the cell axis')&#xA;                sflags[constr.a] = ~mask&#xA;&#xA;        return np.sum(~sflags)&#xA;    else:&#xA;        return len(atoms) * 3 - 3&#xA;&#xA;&#xA;def parse_cml_args(cml):&#xA;    '''&#xA;    CML parser.&#xA;    '''&#xA;    arg = argparse.ArgumentParser(add_help=True)&#xA;&#xA;    arg.add_argument('-i', dest='poscar', action='store', type=str,&#xA;                     default='POSCAR',&#xA;                     help='Real POSCAR to calculate the No. of Degrees of freedom')&#xA;    arg.add_argument('-u', dest='unit', action='store', type=str,&#xA;                     default='fs',&#xA;                     choices=['cm-1', 'fs'],&#xA;                     help='Default unit of input frequency')&#xA;    arg.add_argument('-T', '--temperature', dest='temperature',&#xA;                     action='store', type=float,&#xA;                     default=300,&#xA;                     help='The temperature.')&#xA;    arg.add_argument('-f', '--frequency', dest='frequency',&#xA;                     action='store', type=float,&#xA;                     default=40,&#xA;                     help='The frequency of the temperature oscillation')&#xA;&#xA;    return arg.parse_args(cml)&#xA;&#xA;&#xA;if __name__ == '__main__':&#xA;    arg = parse_cml_args(sys.argv[1:])&#xA;&#xA;    if arg.unit == 'cm-1':&#xA;        THzToCm = 33.3564095198152&#xA;        t0 = 1000 * THzToCm / arg.frequency&#xA;    else:&#xA;        t0 = arg.frequency&#xA;&#xA;    pos  = read(arg.poscar)&#xA;    L    = np.linalg.norm(pos.cell, axis=1)[0]&#xA;    ndof = cnt_dof(pos)&#xA;    Q    = nose_mass(arg.temperature, ndof, t0, L)&#xA;&#xA;    print(&amp;quot;SMASS = {}&amp;quot;.format(Q))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-22T14:18:02.077" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12267" PostTypeId="1" CreationDate="2024-01-22T15:38:32.157" Score="3" ViewCount="46" Body="&lt;p&gt;To calculate DOS using HSE06, is it necessary to use a denser KPOINTS?&lt;/p&gt;&#xA;&lt;p&gt;PS: steps: preconverge PBE --&amp;gt; HSE06 (Damped, LSUBROT=true, ISMEAR=-5)&lt;/p&gt;&#xA;" OwnerUserId="8250" LastActivityDate="2024-01-22T15:38:32.157" Title="DOS in HSE06 - KPOINTS" Tags="|vasp|density-of-states|hse06|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12268" PostTypeId="2" ParentId="12201" CreationDate="2024-01-23T03:16:36.853" Score="2" Body="&lt;p&gt;The simple answer is that the heat of formation difference between two charge states is the most conceptually and practically accurate way to estimate an ionization potential (IP) or electron affinity (EA) in MOPAC.&lt;/p&gt;&#xA;&lt;p&gt;For a vertical excitation, you'd use the same (pre-excitation) geometries for both calculations (i.e. the 1SCF keyword), and for an adiabatic excitation, you'd relax the structure in each charge state. MOPAC will also report an IP and EA for each calculation, which is consistent with Koopmans' theorem for the semiempirical model Hamiltonian. Relative to a vertical excitation calculation, these quantities are missing orbital relaxation effects between charge states.&lt;/p&gt;&#xA;&lt;p&gt;For the more advanced MOPAC user, the MECI functionality of MOPAC can be used to study electronic excitations with multi-reference character, whereas standard calculations are based on a single Slater determinant. However, these calculations are more complicated to specify, more computationally expensive, and may suffer from limited model transferability (the models in MOPAC are primarily fit to optimize the accuracy of single-reference calculations).&lt;/p&gt;&#xA;&lt;p&gt;The heat of formation versus total energy discussion on openmopac.net is referring to the heat of formation reported by MOPAC versus the total energy reported by first-principles quantum chemistry software. While MOPAC can report a total energy quantity, it is not intended as an accurate approximation of first-principles total energies and is more of a historical artifact. I discuss this in more detail in a &lt;a href=&quot;https://github.com/openmopac/mopac/issues/66&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub Issue&lt;/a&gt;. Recent versions of MOPAC hide the total energy output behind a keyword in an attempt to suppress this common source of confusion.&lt;/p&gt;&#xA;" OwnerUserId="8711" LastActivityDate="2024-01-23T03:16:36.853" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12269" PostTypeId="1" CreationDate="2024-01-23T08:19:00.403" Score="3" ViewCount="35" Body="&lt;p&gt;I have a system of molecules in two different solvents in which aggregation occurs, but visually in different ways. In one, aggregation occurs rapidly, but in another sparsely. These MD simulations were performed with gromacs. Is there any way I can quantify the aggregation, like as a fraction of monomer of these solute molecules? Radial distribution function can be a good place to start with, but how do I quantify it? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="5" LastEditDate="2024-01-23T10:20:51.660" LastActivityDate="2024-01-23T10:20:51.660" Title="Compute the monomeric fraction in MD simulation" Tags="|molecular-dynamics|gromacs|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12270" PostTypeId="1" CreationDate="2024-01-23T09:40:10.200" Score="4" ViewCount="40" Body="&lt;p&gt;I was wondering if I could find some scaling relation of the uncertainity of phase averages of thermodynamic quantities with the number of atoms &lt;span class=&quot;math-container&quot;&gt;$N_a$&lt;/span&gt;, the number of timesteps &lt;span class=&quot;math-container&quot;&gt;$N_t$&lt;/span&gt; and size of the timesteps &lt;span class=&quot;math-container&quot;&gt;$dt$&lt;/span&gt; in a molecular dynamics (MD) simulation.&lt;/p&gt;&#xA;&lt;p&gt;For example, I have learned that energy fluctuations &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; in the canonical ensemble scale with &lt;span class=&quot;math-container&quot;&gt;$N_a$&lt;/span&gt; as:&#xA;&lt;span class=&quot;math-container&quot;&gt;\begin{equation}&#xA;\frac{\Delta E}{E} \sim \frac{1}{\sqrt{N_a}}&#xA;\end{equation}&lt;/span&gt;&#xA;If I understand correctly, &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; does not depend on the simulation length. Instead, larger simulation lengths for a fixed &lt;span class=&quot;math-container&quot;&gt;$N_a$&lt;/span&gt; will only decrease our uncertainity on &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt; but not the actual value of &lt;span class=&quot;math-container&quot;&gt;$\Delta E$&lt;/span&gt;. However, I'm confused because I understand that in MD one can enlarge &lt;span class=&quot;math-container&quot;&gt;$N_a$&lt;/span&gt; to decrease uncertainty on phase averages for the same simulation length. I believe this is desired as we can process more atoms in parallel, but not more timesteps in parallel. Is there some general relation like the one above where both the number of atoms and the simulation length is also present?&lt;/p&gt;&#xA;" OwnerUserId="8713" LastActivityDate="2024-01-23T10:50:52.630" Title="phase average uncertainty in molecular dynamics" Tags="|molecular-dynamics|statistical-thermodynamics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12271" PostTypeId="2" ParentId="12270" CreationDate="2024-01-23T10:50:52.630" Score="4" Body="&lt;p&gt;To think about statistical mechanics, one must very occasionally¹ think about statistics.&lt;/p&gt;&#xA;&lt;p&gt;So imagine I toss a coin six times, and you toss a coin six hundred times. My coin comes up heads three times, and your coin comes up heads three hundred times.&lt;/p&gt;&#xA;&lt;p&gt;You would be much more confident that your coin is fair (that is, it has a 50-50 chance of coming up heads) than mine. In fact (using a frequentist approach) you would be about ten times more confident.&lt;/p&gt;&#xA;&lt;p&gt;And yet, the &lt;em&gt;standard deviation&lt;/em&gt; of your sample and mine (using the population formula) are exactly the same! (Don't take my word for it -- calculate it.)&lt;/p&gt;&#xA;&lt;p&gt;What differs between my sample and yours is that the &lt;em&gt;standard error of the estimator of the mean&lt;/em&gt; is much smaller in your sample and mine.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Similarly, if I sample a molecular dynamics system for 10 ns of time, and then for 1000 ns of time, the standard deviation of energy measured along the trajectory &lt;em&gt;should not change&lt;/em&gt;. (Up to sampling error. Variance, and thus standard deviation, converges much more slowly than the mean.) However, the &lt;em&gt;standard error of estimated mean energy&lt;/em&gt; &lt;em&gt;does&lt;/em&gt; become 1/10th of its former value, varying inversely with sample size.&lt;/p&gt;&#xA;&lt;p&gt;You &lt;em&gt;should&lt;/em&gt; then be asking how to calculate the sample size along an MD trajectory. After all, let's say I run a 10 ns simulation and record data every 5 fs instead of every 20 fs. I hope your intuition is sharp enough to recognise I &lt;em&gt;don't&lt;/em&gt; actually have four times as much data!&lt;/p&gt;&#xA;&lt;p&gt;The correct answer is that the &amp;quot;sample size&amp;quot; of a simulation, &lt;em&gt;for each observable&lt;/em&gt;, is the simulation time &lt;em&gt;divided by the observable's correlation time&lt;/em&gt;. Sampling the simulation &lt;em&gt;more often than&lt;/em&gt; the correlation time does &lt;em&gt;not&lt;/em&gt; increase the sample size. For further exploration, see Grossfield's paper on &lt;a href=&quot;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2865156/&quot; rel=&quot;nofollow noreferrer&quot;&gt;quantifying uncertainty in biomolecular simulations&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Note also that just as there are correlation &lt;em&gt;times&lt;/em&gt;, there are also correlation &lt;em&gt;lengths&lt;/em&gt;. Most MD simulations are large enough that correlation lengths can be ignored, but occasionally some observables are affected enough by spatial correlation that &lt;em&gt;finite size corrections&lt;/em&gt; are needed. Two notable examples are the power spectra of transverse vibrations of lipid bilayer membranes, and the Yeh-Hummer correction for estimating diffusivity from mean-squared displacement.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;¹this is a playful, extreme understatement&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2024-01-23T10:50:52.630" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12272" PostTypeId="1" CreationDate="2024-01-23T12:41:31.927" Score="2" ViewCount="25" Body="&lt;p&gt;Spin-orbit coupling (SOC) is a fundamental quantum mechanical phenomenon that arises due to the interaction between the spin of an electron and its orbital motion around an atomic nucleus. It is a relativistic effect that becomes more prominent as the atomic number of the atom increases.&lt;/p&gt;&#xA;&lt;p&gt;As a result of spin-orbit coupling, the energy levels of electrons in atoms are split into sublevels with different total angular momentum values. This splitting is known as the fine structure. The energy difference between these sublevels depends on the magnitude of the spin-orbit coupling and the specific electronic configuration of the atom.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know whether SOC may have a big influence on the charge transfer process that happens between adsorbate-adsorbent. For instance, a paramagnetic gas molecule adsorbed on the surface of material that has heavy elements where SOC is supposed to be significant.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-23T12:41:31.927" Title="The Effect of SOC on Charge Transfer" Tags="|spin-orbit-coupling|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12273" PostTypeId="1" CreationDate="2024-01-23T14:51:12.447" Score="3" ViewCount="403" Body="&lt;p&gt;I just wonder if there are any chemistry drawing software to draw a hybrid perovskite structure ?&lt;/p&gt;&#xA;" OwnerUserId="8714" LastActivityDate="2024-01-24T09:50:56.823" Title="How do I draw perovskite structure with own without CIF file?" Tags="|vasp|computational-chemistry|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12274" PostTypeId="2" ParentId="12273" CreationDate="2024-01-23T15:08:53.180" Score="3" Body="&lt;p&gt;You can accomplish this with VESTA, free software created by JP-Minerals. If you know the space group for your perovskite, you can create a new structure, go to the &amp;quot;Unit cell&amp;quot; tab, and select the space group and set the unit cell size. Then, you would go to the &amp;quot;Structure parameters&amp;quot; tab, where you can enter the species of each atom, an arbitrary name (&amp;quot;Label&amp;quot;) for each atom, and the atom's location. You will not have to enter every atom as the space group will populate the cell with symmetry.&lt;/p&gt;&#xA;&lt;p&gt;However, it can be difficult to predict how a space group will populate a unit cell with atoms in VESTA. I recommend creating the cell even more manually --- create a new structure and select &amp;quot;Custom&amp;quot; or &amp;quot;Triclinic&amp;quot; to get space group 1, a.k.a. P1 (no symmetry). Don't forget to set the unit cell size. Then, you can add your atoms the in &amp;quot;Structure parameters&amp;quot;, but you will need to add each atom in your basis/motif as symmetry will not copy the atoms to other places in the cell.&lt;/p&gt;&#xA;" OwnerUserId="8584" LastEditorUserId="8584" LastEditDate="2024-01-23T15:10:30.163" LastActivityDate="2024-01-23T15:10:30.163" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12275" PostTypeId="1" CreationDate="2024-01-23T15:23:22.447" Score="4" ViewCount="61" Body="&lt;p&gt;Suppose, that one wants to study a bulk structure which is doped by several impurities. More precisely, I want to calculate the elastic constants using a DFT code (VASP) by fitting stress to strain (Voigt Notation):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\sigma_i = \sum_{i=1}^6 C_{ij} \varepsilon_j $&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;From the literature I know, that in a cubic crystal structure the number of independent elastic constant reduces to three.&#xA;For my purpose, I construct a tetragonal supercell (large enough to cover a low concentration of impurities), e.g. 3x3x4 unit cells.  &lt;br /&gt;&#xA;Following questions arise:&lt;br /&gt;&#xA;1)In the case without doping, there are still three elastic constants (due to the periodic boundary condition), because the symmetry of the unit cell transfers to the supercell ?&lt;br /&gt;&#xA;2) Considering the doped case, the relaxed supercell is probably not tetragonal anymore. The unit cell is also not cubic anymore, at least if impurities are present. Does this mean I have to regard all elastic constants ?&lt;/p&gt;&#xA;&lt;p&gt;I ask this question, because with the loss of symmetry I have to regard more strained systems, resulting in more computations. My system is large (ca. 150 atoms) and the calculation IBRION=6 in VASP takes too long.&lt;/p&gt;&#xA;&lt;p&gt;Best,&lt;br /&gt;&#xA;Luca&lt;/p&gt;&#xA;" OwnerUserId="8715" LastActivityDate="2024-02-22T21:32:03.640" Title="Supercell Elastic Constant" Tags="|density-functional-theory|vasp|supercell|elasticity|stress-strain|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12276" PostTypeId="2" ParentId="12273" CreationDate="2024-01-23T15:49:56.247" Score="3" Body="&lt;p&gt;If you know the crystal information (Space group, Wyckoff positions, cell parameters, types of atoms, etc.), it is straight forward to create the CIF file by hand.&lt;/p&gt;&#xA;&lt;p&gt;I recommend you to read this guide: &lt;a href=&quot;https://www.ccdc.cam.ac.uk/community/access-deposit-structures/deposit-a-structure/guide-to-cifs/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Short Guide to CIFs&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Otherwise, if you have no clue about the crystal structure of your material, I recommend using a package like &lt;a href=&quot;https://uspex-team.org/en&quot; rel=&quot;nofollow noreferrer&quot;&gt;USPEX&lt;/a&gt;, a software capable to do crystal predictions &lt;em&gt;with arbitrary P-T conditions by knowing only chemical composition of the material&lt;/em&gt;. It interface to several other software like VASP, SIESTA, GULP, Quantum Espresso, CP2K, CASTEP, LAMMPS, among others.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-01-23T15:49:56.247" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12277" PostTypeId="1" CreationDate="2024-01-23T19:06:08.897" Score="3" ViewCount="30" Body="&lt;h1&gt;Context and objective&lt;/h1&gt;&#xA;&lt;p&gt;This post is a follow up from &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12228/norm-conserving-pseudopotential-procedure&quot;&gt;here&lt;/a&gt;. I want to generate a pseudopotential for a Carbon atom. So I want to pseudize the 1s electrons.&lt;/p&gt;&#xA;&lt;h1&gt;Question&lt;/h1&gt;&#xA;&lt;p&gt;So &lt;span class=&quot;math-container&quot;&gt;$V^{\textrm{PS}}_{1l} = (1-f(r/r_{cl}))V(r) + c_lf(r/r_{cl})$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; is the resulting potential from an all-electron calculation that will not change during the calculation to find the constant &lt;span class=&quot;math-container&quot;&gt;$c_l$&lt;/span&gt;. Correct me if I am wrong, but I think &lt;span class=&quot;math-container&quot;&gt;$$V(r) = V|\Phi(r)\rangle$$&lt;/span&gt; with&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\Phi(r) = \sum_i c_i|\phi_i(r)\rangle$&lt;/span&gt; a wave function where &lt;span class=&quot;math-container&quot;&gt;$\phi_i$&lt;/span&gt; are Contracted Gaussians&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$V_{ij} = \langle\phi_i|V|\phi_j\rangle$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Since I did an Unrestricted HF calculation, &lt;span class=&quot;math-container&quot;&gt;$V^{\textrm{PS}}_{1l}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; depend on the spin. It will not be useful here. The SCF procedure below defines &lt;span class=&quot;math-container&quot;&gt;$c_l$&lt;/span&gt; has the eigenvalue of a problem. As implemented in multiple eigen-solvers, I will get &lt;span class=&quot;math-container&quot;&gt;$n=N_{Contracted \_Gaussians}$&lt;/span&gt; eigenvalues.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How do you know that the constant &lt;span class=&quot;math-container&quot;&gt;$c_l$&lt;/span&gt; has the right value? Maybe some intuition?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Derivation of the SCF procedure for &lt;span class=&quot;math-container&quot;&gt;$c_l$&lt;/span&gt;&lt;/h1&gt;&#xA;&lt;p&gt;From the Hartree-Fock equations, with the Lagrangian &lt;span class=&quot;math-container&quot;&gt;$\mathcal{L} = \langle\Phi^{\textrm{PS}}_{1s}|H|\Phi^{\textrm{PS}}_{1s}\rangle - \epsilon^{\textrm{AE}}_{1s}(\langle\Phi^{\textrm{PS}}_{1s}|\Phi^{\textrm{PS}}_{1s}\rangle - 1)$&lt;/span&gt;:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;H^{\textrm{PS}}_{1s}c^{\textrm{PS}}_{1s} = \epsilon^{\textrm{AE}}_{1s} Sc^{\textrm{PS}}_{1s} \tag{1}&#xA;$$&lt;/span&gt;&#xA;where&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;AE means a quantity computed during the all-electron calculation&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$c^{\textrm{PS}}_{1s}$&lt;/span&gt; the coefficients of the smoothed wavefuntion&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$H^{\textrm{PS}}_{1s} = T + V^{\textrm{PS}}_{1l} = T + \bar{FV} + c_l\bar{F}$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\bar{F}_{ij} = \langle\phi_i|f(r/r_{cl})|\phi_j\rangle$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\bar{FV}_{ij} = \langle\phi_i|(1-f(r/r_{cl}))V(r)|\phi_j\rangle$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Hence&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{align}&#xA;H^{\textrm{PS}}_{1s}c^{\textrm{PS}}_{1s} &amp;amp;= \epsilon^{\textrm{AE}}_{1s} Sc^{\textrm{PS}}_{1s} \tag{2}\\&#xA;\left[T + \bar{FV} + c_l\bar{F}\right]c^{\textrm{PS}}_{1s} &amp;amp;= \epsilon^{\textrm{AE}}_{1s} Sc^{PS}_{1s} \tag{3}\\&#xA;\left[T + \bar{FV}-\epsilon^{\textrm{AE}}_{1s} S\right]c^{\textrm{PS}}_{1s} &amp;amp;= -c_l\bar{F}c^{\textrm{PS}}_{1s} \tag{4}&#xA;\end{align}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;" OwnerUserId="7151" LastEditorUserId="7151" LastEditDate="2024-01-24T07:51:31.080" LastActivityDate="2024-01-24T07:51:31.080" Title="knowing if the pseudopotential in the first step is correct via Haman procedure" Tags="|pseudopotentials|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12278" PostTypeId="2" ParentId="12246" CreationDate="2024-01-23T21:01:42.150" Score="2" Body="&lt;p&gt;Recently I came across a paper that might be what you are looking for. It's an universal parametrization of the vdW interactions depending on the static dipole polarizability of the atoms and the &lt;span class=&quot;math-container&quot;&gt;$C_{6}$&lt;/span&gt; dispersion coefficient. The potential is derived from a quantum Drude oscillator model and was applied for noble gas dimers, Group 2 dimers and molecular dimers, although I think it only works for the long-range behavior.&lt;/p&gt;&#xA;&lt;p&gt;Anyways, the work is also from Tkatchenko and gives some nice results for the systems mentioned. A very brief explanation is as follows: the vdW potential is written in the form&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;V(r) = \left(\frac{1}{2}+\frac{2C_{8}}{3C_{6}R_{e}^{2}}+\frac{5C_{10}}{6C_{6}R_{e}^{4}}\right)\frac{q^{2}}{r}e^{-\mu\omega r^{2}/2\hbar} - \sum_{n=3}^{5}\frac{C_{2n}}{r^{2n}}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$R_{e}$&lt;/span&gt; is the equilibrium distance (obtained from a relation to the dipole polarizability and the fine-structure constant) and &lt;span class=&quot;math-container&quot;&gt;$q,\mu,\omega$&lt;/span&gt; are the parameters of the Drude oscillator. No DFT calculation is required for this, since it's a classical model potential (derived from quantum-mechanical relations) depending on the chemical nature of the system, and the results are compared to CCSD(T) values.&lt;/p&gt;&#xA;&lt;p&gt;All details can be found in &lt;a href=&quot;https://pubs.acs.org/doi/full/10.1021/acs.jctc.3c00797&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 2023, 19, 7895-7907&lt;/a&gt;. The calculation of the oscillator's parameters is described in the supporting information. Also, in Refs. 53, 54 and 106 of that paper there are another approaches to dispersion interactions using a machine learning approach.&lt;/p&gt;&#xA;" OwnerUserId="10" LastEditorUserId="10" LastEditDate="2024-01-23T21:22:03.960" LastActivityDate="2024-01-23T21:22:03.960" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12279" PostTypeId="1" CreationDate="2024-01-23T22:00:48.420" Score="3" ViewCount="53" Body="&lt;p&gt;I was trying to rank the atoms of two PDB files of a same compound but different plymorphs collected from CCDC,  using RdKit canonical ranking. But It generates different ranking for the two PDB of same compound. Do you have any suggestions how to rank the atoms or any other packages to fix the issue. Appreciate your help.&lt;/p&gt;&#xA;" OwnerUserId="3964" LastActivityDate="2024-01-23T22:00:48.420" Title="Unique ranking of atoms in a molecule" Tags="|rdkit|cheminformatics|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12280" PostTypeId="1" CreationDate="2024-01-24T01:44:11.723" Score="2" ViewCount="59" Body="&lt;p&gt;I'm particularly interested in studying how temperature affects electronic properties. However, I've been working with Quantum Espresso and its DFT + U functionality, and I'm struggling to understand how to specify the temperature in these calculations.&lt;/p&gt;&#xA;&lt;p&gt;As far as I know, most Quantum Espresso calculations are run at 0 K. But what if I want to explore the behaviour at, say, room temperature? Are there any built-in methods or functionalities within Quantum Espresso to specify a non-zero temperature for DFT + U calculations?&lt;/p&gt;&#xA;&lt;p&gt;I've been searching through the documentation and tutorials, but haven't found any clear answers yet. Any insights or guidance from the experienced community would be greatly appreciated!&lt;/p&gt;&#xA;" OwnerUserId="8340" LastActivityDate="2024-01-24T01:44:11.723" Title="Temperature effect on electronic properties" Tags="|density-functional-theory|quantum-espresso|electronic-structure|solid-state-physics|dft-u|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12284" PostTypeId="1" CreationDate="2024-01-25T01:04:44.433" Score="3" ViewCount="108" Body="&lt;p&gt;Are there any dedicated Python tools/packages/scripts that help me convert a SMILES structure into an MD coordinate and topology file (both for GROMACS and just the single one for LAMMPS)?&lt;/p&gt;&#xA;&lt;p&gt;Demonstrate this task with two example SMILES:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1. 'C1CC[13CH2]CC1C1CCCCC1'&#xA;2. '[*]CC(c1ccccc1)[*]'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2024-03-11T12:19:59.750" Title="How to convert a SMILES into a LAMMPS or GROMACS input file?" Tags="|molecular-dynamics|lammps|gromacs|structure|topological-matter|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12285" PostTypeId="1" CreationDate="2024-01-25T14:11:02.677" Score="3" ViewCount="28" Body="&lt;p&gt;I'm trying to perform relaxation calculations for FeTiO3 with the ilmenite structure in Quantum Espresso. The documentation mentions two possible ibrav values for triagonal systems: 5 and -5. However, I'm unsure which one is appropriate for my case. crystal constants are: a=b=c = 5.432 A, α=β=γ = 55.346^o.  Given these parameters, how can I determine the location and orientation of the 3-fold axis?&lt;/p&gt;&#xA;" OwnerUserId="8730" LastActivityDate="2024-01-25T14:11:02.677" Title="How to choose the correct ibrav value and Identifying the 3-fold Axis" Tags="|density-functional-theory|quantum-espresso|crystallography|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12286" PostTypeId="1" CreationDate="2024-01-25T14:19:34.590" Score="1" ViewCount="35" Body="&lt;p&gt;I am currently a senior year chemistry undergraduate with a keen interest towards pursuing a PhD in the fields of Quantum Dynamics. I have a strong background in mathematics and undergraduate quantum physics, but I am getting quickly overwhelmed when trying to read journal articles in current quantum chemistry &lt;a href=&quot;https://pubs.acs.org/action/showCitFormats?doi=10.1021/acs.jctc.3c00805&amp;amp;ref=pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;This for example&lt;/a&gt;  . I have realized I need  to go through some rigorous learning before I am able to grasp what modern day research in this field is about, but it is very difficult to find resources that would help me learn the things I want while being legible to an undergraduate. To give you an idea of what I want to learn :&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;A rigorous treatment of the Born-Oppenheimer approximation. I have come to realize that it goes much deeper than just &amp;quot;Ignore Nuclear Kinetic Energy&amp;quot;. I want to know about potential energy surfaces, when do they intersect (?) and how it is related to things like the &amp;quot;adiabatic approximation&amp;quot; and how we deal with phenomenon like &amp;quot;internal conversion&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;The basics of the Multi-configuration time dependent hartree (MCTDH) formalism that is used to simulate quantum dynamics.&lt;/li&gt;&#xA;&lt;li&gt;What is &amp;quot;Surface Hopping&amp;quot; formalism. How it provides a cheaper alternative to purely quantum treatments.&lt;/li&gt;&#xA;&lt;li&gt;What are conical intersections and how they represent a complete breakdown of the BO approximation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;So that the members of the group can help me more easily, here are things I am already comfortable with:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Mathematics - Linear Algebra, Group Theory, Representation Theory for Finite Groups, A bit of Lie groups, Basics of ODEs, Multivariable Analysis.&lt;/li&gt;&#xA;&lt;li&gt;Physics - Classical Mechanics and Classical Field Theory, Relativity, Quantum Mechanics (at the level of Sakurai's Modern Quantum Mechancis), Introductory parts of QFT.&lt;/li&gt;&#xA;&lt;li&gt;Electronic Structure Theory - I have just started studying it (mostly refering Helgaker) but I have become comfortable with the standard and the second-quantized versions of HF Theory and I have been able to write my own HF code to simulate the Energy v/s bond length curve of &lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt; molecule using an STO-3G basis set.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Most of the members on this forum are way more experienced than me so I look forward to listening what might your helpful suggestions be.&lt;/p&gt;&#xA;" OwnerUserId="8664" LastActivityDate="2024-01-25T14:19:34.590" Title="Looking for resources to learn quantum dynamics at a preliminary graduate level" Tags="|reference-request|quantum-dynamics|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12287" PostTypeId="2" ParentId="12256" CreationDate="2024-01-25T14:39:03.647" Score="3" Body="&lt;p&gt;Normally the correlation energy is defined to be:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{corr}^{basis} = E_{FCI}^{basis} - E_{HF}^{basis}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the superscript basis denotes each calculated in a fixed basis set. The correlation energy must be &lt;span class=&quot;math-container&quot;&gt;$E_{corr}^{basis}\leq 0$&lt;/span&gt;. This is because the the full configuration interaction (FCI) wavefunction allows N electrons to be distributed in M spin orbitals (there are N choose M Slater determinants). Whereas, Hartree-Fock (HF) only allows electrons to fill the N lowest lying orbitals (a single Slater determinant). I.e. in a qualitative way the electrons can distribute themselves in more ways in FCI than HF. In more handwavey terms, the mathematics of FCI allow more arrangements of electrons such that they can position themselves in a better way such that the energy is lowered. As Kristof answer details this is how electrons 'avoid' each other.&lt;/p&gt;&#xA;&lt;p&gt;In fact FCI includes the HF state and so by the variational principle &lt;span class=&quot;math-container&quot;&gt;$E_{FCI}^{basis}$&lt;/span&gt; cannot be greater than &lt;span class=&quot;math-container&quot;&gt;$E_{HF}^{basis}$&lt;/span&gt; hence why &lt;span class=&quot;math-container&quot;&gt;$E_{corr}^{basis} \leq 0$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;It turns out that for naturally occurring molecular systems it is energetically favorable to be bonded together - as seen in nature (usually at least). When we calculate the energy of separated atoms (i.e. split them apart to infinity) and vs at equilibrium bond length. The energy of the system together is lower (more stable) than dissociated and is why it costs energy to split molecular systems in a lab apart. I guess this is why electron correlation can be called &amp;quot;chemical glue&amp;quot;, although I would avoid using the term in a computational chemistry paper as it isn't really correct to think of it as&#xA;'glue'. Yes it does cause things to bond, but this stems from the wavefunction of the system and has a more mathematical interpretation as discussed above. *Having said that, I think it is perfectly okay to use this phrase in a non-technical setting.&lt;/p&gt;&#xA;" OwnerUserId="4349" LastEditorUserId="4349" LastEditDate="2024-01-25T18:26:00.320" LastActivityDate="2024-01-25T18:26:00.320" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12288" PostTypeId="1" CreationDate="2024-01-25T15:24:43.870" Score="0" ViewCount="30" Body="&lt;p&gt;I keep getting this whenever I try plotting the electronic band structure for CoRhMnGa on quantum Espresso, what could possibly cause the vertical spaces&lt;/p&gt;&#xA;" OwnerUserId="8731" LastActivityDate="2024-01-25T15:24:43.870" Title="Spaces in Electronic band structure" Tags="|quantum-espresso|band-structure|electronic-structure|bandgap|spintronics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12289" PostTypeId="2" ParentId="12259" CreationDate="2024-01-25T18:56:35.553" Score="3" Body="&lt;p&gt;If I understand your question, the answer is yes. Really, the only requirement is anisotropy. Consider e.g. a half-filled 1d chain. It is metallic along the chain and insulating perpendicular to it. I assume such things exists in e.g. polymer chains. Similarly for 2d and 3d systems.&lt;/p&gt;&#xA;&lt;p&gt;Basically any text book on solid state physics will cover these things. I like Ziman's book, Ashcroft-Mermin, and have looked quite a bit at Girvin and Yang. Significantly more advanced and specialized, but a good introduction to second quantization, is Altland-Simons. Moreover, David Tong's notes on his website are much more concise and instructional.&lt;/p&gt;&#xA;&lt;p&gt;One of the simplest Hamiltonians for a crystal is&#xA;&lt;span class=&quot;math-container&quot;&gt;$ H = -\sum t_{ij} c^\dagger_j c_i + \sum_i \epsilon_i c^\dagger_i c_i$&lt;/span&gt;. This is &amp;quot;second quantized notation&amp;quot; with &lt;span class=&quot;math-container&quot;&gt;$c_i$&lt;/span&gt; an operator that removes an electron from site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;; &lt;span class=&quot;math-container&quot;&gt;$c^\dagger_j$&lt;/span&gt; adds the electron to site &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt; is the so-called hopping amplitude: it is the probability of the electron hopping from site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$j$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\epsilon_{i}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt; are parameters that depends on the atom types, crystal lattice, etc. We will assume they are already known in what follows.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\epsilon_i$&lt;/span&gt; is the on-site energy, &lt;span class=&quot;math-container&quot;&gt;$c^\dagger_i c_i \equiv n_i$&lt;/span&gt; is the electron density operator: it counts the number of electrons on site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i n_i$&lt;/span&gt; is basically the energy for an electron to be placed on site &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;. If all the atoms are identical, &lt;span class=&quot;math-container&quot;&gt;$\epsilon_i \equiv \epsilon$&lt;/span&gt; and the on-site terms all add up to a constant that we can ignore (we ignore it later).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt; is the probability for an electron to tunnel between sites. To make some sense of it, consider the example (I think due to Mott, it is discussed somewhere in Ashcroft-Mermin) where &lt;span class=&quot;math-container&quot;&gt;$t_{ij} \ll \epsilon$&lt;/span&gt;. Assuming each atom has the same number of electrons on it, &lt;span class=&quot;math-container&quot;&gt;$n_i \equiv n$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$H \approx \epsilon \sum n = N \epsilon n$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is just the number of unit cells in the crystal. Notably, this is just an array of isolated atoms with no possibility for an electron to hop between sites. It is a perfect insulator. At some point, with finite &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt;, the system goes from metal to insulator. The point is that &lt;span class=&quot;math-container&quot;&gt;$t_{ij}$&lt;/span&gt;, in-large part, determines the nature of the system.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/exaGI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/exaGI.png&quot; alt=&quot;example of 2d lattice model&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Now to answer your question. Consider an anisotropic 2d model. See the image above. Assume that it is longer along the &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;-axis so that hopping along that direction is smaller probability. Let the hopping amplitude along &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; be called &lt;span class=&quot;math-container&quot;&gt;$t$&lt;/span&gt; and along &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; be called &lt;span class=&quot;math-container&quot;&gt;$t'$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$t' \ll t$&lt;/span&gt;. I.e. it is difficult for electrons to go along &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, but easy along &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;. The Hamiltonian is &lt;span class=&quot;math-container&quot;&gt;$H = -\sum_i [ t (c^\dagger_i c_{i+x} + c^\dagger_{i+x} c_i) + t' (c^\dagger_i c_{i+y} + c^\dagger_{i+y} c_i)]$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$c_{i+x}$&lt;/span&gt; being the operator for the next site from &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt; along the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; direction and so on. This can be solved by Fourier transforms: &lt;span class=&quot;math-container&quot;&gt;$c_i = N^{-1/2} \sum_k c_k \exp(i \bf{k} \cdot \bf{R}_i)$&lt;/span&gt; and so on. The solution is &lt;span class=&quot;math-container&quot;&gt;$H = \sum_{\bf{k}} E_{\bf{k}} c^\dagger_k c_k$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$ E_{\bf{k}} = -2 [t \cos(k_x a_x) + t' \cos(k_y a_y) ] $&lt;/span&gt;. This band structure with &lt;span class=&quot;math-container&quot;&gt;$t=1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$t'=0.1$&lt;/span&gt; is plotted below.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/DbA67.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/DbA67.png&quot; alt=&quot;bands&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Note that the dispersion crosses the Fermi level &lt;span class=&quot;math-container&quot;&gt;$E_f \equiv 0$&lt;/span&gt; along the path from &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$X$&lt;/span&gt;. These electrons have momentum parallel to the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; axis and, since there is no gap, can easily be exited into conduction states. Along the &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; direction, there are no electrons at the Fermi level, i.e. there are no conduction electrons with momentum parallel to &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The conductivity in the Einstein theory is (see chp. 8 in Girvin and Yang) &lt;span class=&quot;math-container&quot;&gt;$\sigma=e^2 \rho(E_f) D$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; the diffusion constant, &lt;span class=&quot;math-container&quot;&gt;$e$&lt;/span&gt; the electron charge, and &lt;span class=&quot;math-container&quot;&gt;$\rho(E_f)$&lt;/span&gt; the density of states at the Fermi level. &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; determine how long an electron that is excited into a conduction state remains conducting before being reabsorbed into the lattice. It depends on electron-electron interactions and other things. Assume it is a constant, the same for all electrons. &lt;span class=&quot;math-container&quot;&gt;$\rho(E_f)$&lt;/span&gt; tells us how many electrons there are that can be excited. If we try to resolve this into directions, &lt;span class=&quot;math-container&quot;&gt;$\sigma_x \sim \rho_x(E_f)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\sigma_y \sim \rho_y(E_f)$&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$\rho_{\bf{k}}(E_f)$&lt;/span&gt; the &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;-resolved density of states (i.e. count of the states with momentum &lt;span class=&quot;math-container&quot;&gt;$\bf{k}$&lt;/span&gt; at the Fermi level. It tells us how many electrons there are that can be exited into conduction states with momentum &lt;span class=&quot;math-container&quot;&gt;$\bf{k}$&lt;/span&gt;. Notably, &lt;span class=&quot;math-container&quot;&gt;$\rho_x(E_f) \neq 0$&lt;/span&gt; while &lt;span class=&quot;math-container&quot;&gt;$\rho_y(E_f) \equiv 0$&lt;/span&gt;. The material is conducting along the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; direction, but not along &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;, because there are no available states along &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt;. These examples occur in nature, e.g. the doped cuprates are conducting (and even superconducting) in the Cu-O plane, but insulating in the direction perpendicular to the Cu-O planes.&lt;/p&gt;&#xA;&lt;p&gt;I hope this updated answer helps!&#xA;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="1258" LastEditDate="2024-01-26T22:11:52.407" LastActivityDate="2024-01-26T22:11:52.407" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12290" PostTypeId="1" CreationDate="2024-01-26T02:58:28.587" Score="1" ViewCount="74" Body="&lt;p&gt;I have been trying to get the CG representation of a basic octane molecule. The pdb file is as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOM      1  C1  BUT     1       2.142   1.395  -8.932  1.00  0.00&#xA;ATOM      2  C2  BUT     1       3.631   1.416  -8.537  1.00  0.00&#xA;ATOM      3  C3  BUT     1       4.203  -0.012  -8.612  1.00  0.00&#xA;ATOM      4  C4  BUT     1       5.691   0.009  -8.218  1.00  0.00&#xA;ATOM      5 1H1  BUT     1       1.604   0.760  -8.260  1.00  0.00&#xA;ATOM      6 2H1  BUT     1       1.745   2.388  -8.880  1.00  0.00&#xA;ATOM      7 3H1  BUT     1       2.043   1.024  -9.930  1.00  0.00&#xA;ATOM      8 1H2  BUT     1       4.169   2.051  -9.210  1.00  0.00&#xA;ATOM      9 2H2  BUT     1       3.731   1.788  -7.539  1.00  0.00&#xA;ATOM     10 1H3  BUT     1       3.665  -0.647  -7.940  1.00  0.00&#xA;ATOM     11 2H3  BUT     1       4.104  -0.384  -9.610  1.00  0.00&#xA;ATOM     12 1H4  BUT     1       5.793   0.388  -7.201  1.00  0.00&#xA;ATOM     13 2H4  BUT     1       6.240   0.656  -8.903  1.00  0.00&#xA;ATOM     14  C1  MET     1       6.263  -1.418  -8.293  1.00  0.00&#xA;ATOM     15 1H1  MET     1       6.162  -1.797  -9.309  1.00  0.00&#xA;ATOM     16 2H1  MET     1       5.715  -2.065  -7.608  1.00  0.00&#xA;ATOM     17  C1  MET     1       7.750  -1.397  -7.899  1.00  0.00&#xA;ATOM     18 1H1  MET     1       7.852  -1.018  -6.882  1.00  0.00&#xA;ATOM     19 2H1  MET     1       8.299  -0.750  -8.583  1.00  0.00&#xA;ATOM     20  C1  MET     1       8.321  -2.824  -7.973  1.00  0.00&#xA;ATOM     21 1H1  MET     1       8.221  -3.203  -8.990  1.00  0.00&#xA;ATOM     22 2H1  MET     1       7.774  -3.471  -7.288  1.00  0.00&#xA;ATOM     23  C1  MET     1       9.809  -2.803  -7.579  1.00  0.00&#xA;ATOM     24 1H1  MET     1      10.214  -3.813  -7.632  1.00  0.00&#xA;ATOM     25 2H1  MET     1      10.358  -2.156  -8.264  1.00  0.00&#xA;ATOM     26 3H1  MET     1       9.911  -2.424  -6.562  1.00  0.00&#xA;TER      27      MET     1 &#xA;END   &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I cannot understand how to run martinize.py once I have downloaded the whole repo from the source: &lt;a href=&quot;https://github.com/cgmartini/martinize.py/tree/master&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/cgmartini/martinize.py/tree/master&lt;/a&gt; . Do I run it as a shell script, if yes what is the command I should use to run MARTINI to merely get the CG .pdb representation of an AA .pdb&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2024-01-28T09:05:46.763" Title="How to use martinize.py?" Tags="|molecular-dynamics|coarse-grained|martini|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12291" PostTypeId="1" CreationDate="2024-01-26T10:15:19.630" Score="3" ViewCount="188" Body="&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.4.084201&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, I couldn't understand this line in the 3rd section (i.e. III. SYMMETRY ARGUMENTS):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;In the absence of SOC, the eigenvalues of &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt; rotation operator are &lt;span class=&quot;math-container&quot;&gt;$e^{i2\pi n/6}$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$n = 0$&lt;/span&gt; to &lt;span class=&quot;math-container&quot;&gt;$5$&lt;/span&gt; and the corresponding eigenstates are denoted by &lt;span class=&quot;math-container&quot;&gt;$\psi_1 , \psi_2 , \psi_3, \psi_4 , \psi_5 , \text{and} \psi_6$&lt;/span&gt;, respectively.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But, as we know, the rotation matrix for an angle &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; rotation about z-axis in 3-D cartesian space is given by:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{pmatrix}&#xA;\cos\phi &amp;amp; -\sin\phi &amp;amp; 0\\&#xA;\sin\phi &amp;amp; \cos\phi &amp;amp; 0\\&#xA;0 &amp;amp; 0 &amp;amp; 1&#xA;\end{pmatrix}, &#xA;$$&lt;/span&gt;&#xA;with eigenvalues  &lt;span class=&quot;math-container&quot;&gt;$\lambda_1 = 1 , \lambda_2=e^{i\phi} , \lambda_3 =e^{-i\phi} $&lt;/span&gt; and their corresponding eigenvectors &lt;span class=&quot;math-container&quot;&gt;$v_1 = (0,0,1) , v_2 = (i,1,0), v_3=(-i,1,0)$&lt;/span&gt;. I don't know &lt;strong&gt;what I am missing to correctly interpret and find the mathematical logic for the eigenvalues of the &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt; rotation operator, and what I am confused about is that I am getting 3 eigenvalues but in the paper, it is 6.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8321" LastEditorUserId="5" LastEditDate="2024-01-26T17:55:50.530" LastActivityDate="2024-01-26T17:55:50.530" Title="Why does the C6z operator have 6 eigenvectors in this paper?" Tags="|condensed-matter|mathematical-modeling|symmetry|quantum-mechanics|reproducing-data-from-papers|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12292" PostTypeId="1" AcceptedAnswerId="12296" CreationDate="2024-01-26T12:32:34.167" Score="6" ViewCount="396" Body="&lt;p&gt;I want to solve the radial Schrodinger equation for a Carbon atom with all six electrons.&#xA;The equation I want to solve is for &lt;span class=&quot;math-container&quot;&gt;$r&amp;gt;0$&lt;/span&gt;: &lt;span class=&quot;math-container&quot;&gt;$$[\frac{-\hbar^2}{2m}\frac{\partial^2}{\partial r^2}+ \frac{\hbar^2 l(l+1)}{2mr^2}+ V(r)]u(r) = Eu(r),\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$u(r) = rR(r)$&lt;/span&gt; the wavefunction being &lt;span class=&quot;math-container&quot;&gt;$\Phi_l^m(r, \theta, \phi) = R(r)Y_l^m(\theta, \phi)$&lt;/span&gt;.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$V(r) = V_{proton-electron}(r) + V_{electron-electron}(r) + V_{exchange,correlation}(r)$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The basis function that I choose to decompose &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is a simple STO3G basis of the form &lt;span class=&quot;math-container&quot;&gt;$\chi_i(r) = r^i e^{-\alpha_i r^2}$&lt;/span&gt; that only depend on &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;. When computing the matrix elements of &lt;span class=&quot;math-container&quot;&gt;$V_{proton-electron}$&lt;/span&gt;, it is quite the same procedure compared to solving the Schrodinger equation without separating the variables. The matrix element of the Hartree potential doesnt not seem as straightforward: &lt;span class=&quot;math-container&quot;&gt;$$V^{Hartree}_{ij} = \sum_{k,l} (ij|kl)P_{kl},\tag{2}$$&lt;/span&gt;&#xA;with: &lt;span class=&quot;math-container&quot;&gt;$$\tag{3}(ij|kl) = \int_{r_1\in \mathcal{R}^+} \int_{r_2\in \mathcal{R}^+}\chi_i(r_1)\chi_j(r_1)\frac{1}{|r_1-r_2|}\chi_k(r_2)\chi_l(r_2),$$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$P$&lt;/span&gt; is the density matrix.&lt;/p&gt;&#xA;&lt;p&gt;Remarks:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The basis functions in which &lt;span class=&quot;math-container&quot;&gt;$R$&lt;/span&gt; is spanned are spherically symmetric, since the angular dependencies have been separated.&lt;/li&gt;&#xA;&lt;li&gt;The two-electron integral as I wrote does not span the entire 3D space and do not take into account cases where the electron density is not spherical (like p orbitals). In addition to that it is wrong.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;What are the matrix elements of the electron repulsion potential &lt;span class=&quot;math-container&quot;&gt;$V_{electron-electron}$&lt;/span&gt; in when solving the Radial Schrodinger equation?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8729" LastEditorUserId="5" LastEditDate="2024-01-26T22:46:18.060" LastActivityDate="2024-01-26T22:46:18.060" Title="How may I solve the radial Schrödinger equation?" Tags="|computational-chemistry|molecular-modeling|electronic-structure|spectroscopy|vibrations|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12293" PostTypeId="2" ParentId="12292" CreationDate="2024-01-26T13:42:45.563" Score="8" Body="&lt;p&gt;Solving the radial Schroedinger equation (your Eq. 1) is done with &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; pre-determined (either it is an analytic expression of a model, such as the &lt;a href=&quot;https://en.wikipedia.org/wiki/Morse/Long-range_potential&quot; rel=&quot;noreferrer&quot;&gt;Morse/long-range model&lt;/a&gt;, or it is known in some other way, such as a point-wise array of &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt; values. The most widely used way to solve the radial Schroedinger equation for a diatomic molecule is to use the &lt;a href=&quot;https://github.com/HPQC-LABS/LEVEL&quot; rel=&quot;noreferrer&quot;&gt;LEVEL software&lt;/a&gt; which originated in the 1960s, but has been maintained by myself since my supervisor (the original author of LEVEL in the 1960s) passed away. LEVEL is also available in OpenMolcas, and you can let me know if you run into any issues when using it.&lt;/p&gt;&#xA;&lt;p&gt;What you seem to be trying to do is to calculate &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt;, and also to solve the radial Schroedinger equation for the calculated &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt;. Calculating &lt;span class=&quot;math-container&quot;&gt;$V(r)$&lt;/span&gt; can be done with any electronic structure software, such as &lt;a href=&quot;/questions/tagged/open-molcas&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-open-molcas-tooltip-container&quot;&gt;open-molcas&lt;/a&gt;, or if you would really like to write your own software for this (for many reasons, I do not recommend doing this) you can do so, but basically &lt;strong&gt;it has nothing to do with solving the &lt;em&gt;radial&lt;/em&gt; Schroedinger equation and everything to do with solving the &lt;em&gt;electronic&lt;/em&gt; Schroedinger equation&lt;/strong&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-26T13:42:45.563" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12294" PostTypeId="2" ParentId="12291" CreationDate="2024-01-26T14:12:53.180" Score="3" Body="&lt;p&gt;The paper appears to have an error.&lt;/p&gt;&#xA;&lt;p&gt;When a &lt;span class=&quot;math-container&quot;&gt;$C_6$&lt;/span&gt; operator acts on an atom's (x,y,z) coordinates, the operator's matrix representation is the 3x3 matrix that you correctly provided in your question post.  The rotation matrix is a 3x3 matrix whether it is representing a &lt;span class=&quot;math-container&quot;&gt;$C_{3}$&lt;/span&gt; operator, &lt;span class=&quot;math-container&quot;&gt;$C_{6}$&lt;/span&gt; operator, &lt;span class=&quot;math-container&quot;&gt;$C_{1402}$&lt;/span&gt; operator, or any other &lt;span class=&quot;math-container&quot;&gt;$C_n$&lt;/span&gt; operator with &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; being a positive integer. In the paper to which you referred, &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt; is the specific &lt;span class=&quot;math-container&quot;&gt;$C_{6}$&lt;/span&gt; operator for a rotation around the z-axis, meaning that it is the &lt;span class=&quot;math-container&quot;&gt;$R_z(\theta)$&lt;/span&gt; operator in which &lt;span class=&quot;math-container&quot;&gt;$\theta$&lt;/span&gt; is 360/&lt;strong&gt;6&lt;/strong&gt; = 60 degrees.&lt;/p&gt;&#xA;&lt;p&gt;In Fig 2a of &lt;a href=&quot;https://arxiv.org/abs/2008.05108v1&quot; rel=&quot;nofollow noreferrer&quot;&gt;the arXiv version of the paper&lt;/a&gt;, what they call the &amp;quot;eigenstates&amp;quot; of the &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt; operator, are labeled as &lt;span class=&quot;math-container&quot;&gt;$\psi_1,\psi_2,\ldots,\psi_6$&lt;/span&gt;, even though these just appear to be positions in (x,y,z)-space that are obtained by applying the C6 operator. For example, if a nucleus resides at (x,y,z) = (1,2,3), there are 6 different locations to which the &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt;  operator can&#xA;transform the coordinates of the nucleus, one of these being the original coordinates: (1,2,3). This is very different from eigenvectors: what eigenvectors would be in this situation, are (x,y,z) coordinates at which the &lt;span class=&quot;math-container&quot;&gt;$C_{6z}$&lt;/span&gt; operator does not change the coordinates. For example, you suggested the vector (x,y,z) = (0,0,1), which after any rotation around the z-axis, remains to be (0,0,1).&lt;/p&gt;&#xA;&lt;p&gt;If the authors were using the terminology correctly, then in Fig 2a we would expect for &lt;span class=&quot;math-container&quot;&gt;$\psi_1,\psi_2,\ldots,\psi_6$&lt;/span&gt; to all be at the same location, because they would represent locations at which the operator does not change the coordinates!&lt;/p&gt;&#xA;&lt;p&gt;A rotation operator can have 6 eigenvalues and 6 eigenvectors if it is an operator that is acting on two sets of (x,y,z) coordinates (for example if it is acting on the positions of &lt;em&gt;&lt;strong&gt;two&lt;/strong&gt;&lt;/em&gt; nuclei, rather than just one), but even then the rotation operator would usually be given by the standard 3x3 matrix that you presented in your post, and it would just be applied to the two sets of (x,y,z) coordinates independently (the 6x6 matrix would be a block diagonal matrix composed of two 3x3 rotation matrices).&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-01-26T14:17:58.743" LastActivityDate="2024-01-26T14:17:58.743" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12295" PostTypeId="1" AcceptedAnswerId="12434" CreationDate="2024-01-26T16:13:06.863" Score="6" ViewCount="107" Body="&lt;p&gt;The lack of interoperability of quantum chemistry software is one of the main issues holding back the field. Unfortunately, not all programs implement every possible type of calculation, and often one would like to use two programs together in a workflow, but this is not possible since such interfaces do not exist; see my recent perspective and proposed workaround in &lt;a href=&quot;https://doi.org/10.1063/5.0175165&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 159, 180901 (2023)&lt;/a&gt;. Some programs can, however, already be used together through mutual support for e.g. the GAUSSIAN formatted checkpoint format, or through third-party add-on solutions like &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;nofollow noreferrer&quot;&gt;MOKIT&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;A colleague just asked me if it was possible to read in molecular orbitals from Turbomole into the Q-Chem program, since they need some features that only exist in each of these programs.&lt;/p&gt;&#xA;&lt;p&gt;This coupling does not appear to be possible with MOKIT, since I could not find any mention of Turbomole in their documentation (although interestingly, &lt;a href=&quot;https://jeanwsr.gitlab.io/mokit-doc-mdbook/chap4-5.html#4526-fch2qchem&quot; rel=&quot;nofollow noreferrer&quot;&gt;orbitals can be transferred from GAUSSIAN into Q-Chem!&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Does anyone know of a way to read in orbitals from Turbomole into Q-Chem?&lt;/p&gt;&#xA;&lt;p&gt;Addendum: it appears that a solution is possible by dumping out Molden data from Turbomole, as suggested by Uwe below, and then parsing this Molden file with the specified Turbomole provenance into a Gaussian formatted checkpoint with MOKIT and from then on again into Q-Chem again with MOKIT, as described by jxzou.&lt;/p&gt;&#xA;&lt;p&gt;It would be really nice if programs adopted an interoperable format; &lt;a href=&quot;https://github.com/trex-coe/trexio&quot; rel=&quot;nofollow noreferrer&quot;&gt;the TREX I/O library&lt;/a&gt; seems to be the best solution available at the moment...&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2024-02-20T13:42:19.087" LastActivityDate="2024-02-20T13:42:19.087" Title="Is there any way to read in orbitals from Turbomole into Q-Chem?" Tags="|q-chem|turbomole|interoperability|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12296" PostTypeId="2" ParentId="12292" CreationDate="2024-01-26T16:30:17.947" Score="8" Body="&lt;p&gt;You have not specified sufficiently precisely what is the problem you want to solve. It sounds like you want to solve the radial density functional equations; however, there is still a world of options on how to do that.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Carbon has an open &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; shell, and due to symmetry breaking, the Kohn-Sham orbitals actually do not obey spherical symmetry but instead you get &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; mixing, &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;-&lt;span class=&quot;math-container&quot;&gt;$f$&lt;/span&gt; mixing, etc.&lt;/li&gt;&#xA;&lt;li&gt;The ground state of carbon is also not spin-restricted, so the orbitals are different for spin-up and spin-down electrons.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;One can, however, restrict the problem to being spin unrestricted and the orbitals to not break the symmetry; this is achievable by equal occupation of the orbitals (see e.g. &lt;a href=&quot;https://doi.org/10.1103/PhysRevA.101.012516&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1103/PhysRevA.101.012516&lt;/a&gt; and &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.3c00183&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1021/acs.jctc.3c00183&lt;/a&gt;). This will reduce the problem to determining a single Fock matrix for every angular momentum &lt;span class=&quot;math-container&quot;&gt;$l$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The two-electron integrals &lt;em&gt;do&lt;/em&gt; account for non-spherical densities; note that your definition still includes the spherical harmonics in the basis functions. To figure out spatial expressions you need to integrate out the angles employing the closure properties of the spherical harmonics, which gives you Gaunt coupling coefficients, see &lt;a href=&quot;https://doi.org/10.1002/qua.25968&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1002/qua.25968&lt;/a&gt;. You can calculate the nuclear attraction and Coulomb integrals by similar techniques.&lt;/p&gt;&#xA;&lt;p&gt;The necessary radial matrix elements turn out to be fairly simple in the Gaussian basis, especially if your density is spherically symmetric. Expressions for the radial integrals have been reported by Pitzer in &lt;a href=&quot;https://doi.org/10.1016/j.cpc.2012.02.009&quot; rel=&quot;noreferrer&quot;&gt;doi:10.1016/j.cpc.2012.02.009&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-01-26T16:30:17.947" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12297" PostTypeId="1" CreationDate="2024-01-26T18:24:09.173" Score="3" ViewCount="76" Body="&lt;p&gt;In &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.87.235313&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt; they calculated radiative recombination rates for Germanium using an effective mass model and I am trying to calculate the indirect spontaneous radiative recombination&#xA;rate related to phonon-assisted transitions from the L-valley to one of the valence bands using eq. (14) (results plotted in Fig. 3). My problem is that for energies &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt; large enough, the term in the denominator in eq. (14) independent of &lt;span class=&quot;math-container&quot;&gt;$k_{\perp}$&lt;/span&gt; hits zero (since the upper integration boundary of the &lt;span class=&quot;math-container&quot;&gt;$\epsilon^{L_c}$&lt;/span&gt; integration scales with &lt;span class=&quot;math-container&quot;&gt;$\omega$&lt;/span&gt;, just as in eq. (13)). This happens for energies above the band gap, which should be the case for the energy range in Fig. 3. Then the &lt;span class=&quot;math-container&quot;&gt;$k_{\perp}$&lt;/span&gt; integral basically is &lt;span class=&quot;math-container&quot;&gt;$1/(k_{\perp}^2)^2$&lt;/span&gt; from 0 to &lt;span class=&quot;math-container&quot;&gt;$k_{ab/em}^{R_{ind}}$&lt;/span&gt;, which diverges.&lt;/p&gt;&#xA;&lt;p&gt;In the paper I did not see anything mentioned about how they dealt with this problem. Am I doing something wrong, or is there some common way of dealing with an integral like this, so they did not need to mention it in the paper? Would be grateful for any ideas!&lt;/p&gt;&#xA;" OwnerUserId="8735" LastEditorUserId="5" LastEditDate="2024-01-26T18:32:36.823" LastActivityDate="2024-01-26T18:32:36.823" Title="How did they calculate the indirect radiative recombination rate in this paper?" Tags="|electronic-structure|condensed-matter|solid-state-physics|reproducing-data-from-papers|photoluminescence|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12298" PostTypeId="1" AcceptedAnswerId="12341" CreationDate="2024-01-27T08:49:11.910" Score="4" ViewCount="159" Body="&lt;p&gt;There is a conceptual mismatch in my personal understanding between the role of reduced density matrices in DFT and post-HF methods (possibly due to different discussions in textbooks), and I can not find arguments to bridge the gap between these two points of view.&lt;/p&gt;&#xA;&lt;p&gt;One statement which I believe to be true is that in order to evaluate the expectation values of an &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron operator, the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-electron reduced density matrix (&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-RDM) is needed.&lt;/p&gt;&#xA;&lt;p&gt;For example, within Hartree-Fock, we transform the electron-electron interaction into a Fock operator, which, being an effective one-electron operator, only needs evaluation of the 1-RDM. This means that there is no direct 2-RDM in Hartree-Fock theory (apart from an outer product of two 1-RDMs, adding no extra information), and, therefore, correlation effects are neglected. On the other hand, post-HF methods do have some expressions for their respective 2-RDMs. Moreover, since the Hamiltonian contains only terms up to two-electrons, the exact 2-RDM would be enough to evaluate the exact energy - more should be needed for operators of more electrons.&lt;/p&gt;&#xA;&lt;p&gt;This story is seemingly not in agreement with the principle of DFT, where, starting from the Hohenberg-Kohn theorems, we start with the fact that the electron density and the Hamiltonian uniquely determine each other. If we knew the exact form of the exchange-correlation functional, we could obtain the exact density, and, from this, the exact energy. However, this seems to imply that knowing the 1-RDM is enough, since the electron density can be obtained exactly from the 1-RDM. Consequently, the 2-RDM is not an object that is even calculated (or defined) in ''standard'' DFT calculations.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Do we really need the 2-RDM to obtain the exact energy, or should the 1-RDM be enough?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="5648" LastEditorUserId="5" LastEditDate="2024-01-27T12:40:19.650" LastActivityDate="2024-02-03T15:51:29.967" Title="Is the one-electron reduced density matrix enough in DFT?" Tags="|density-functional-theory|electron-correlation|reduced-density-matrix|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12299" PostTypeId="1" AcceptedAnswerId="12342" CreationDate="2024-01-27T20:09:48.787" Score="4" ViewCount="89" Body="&lt;p&gt;I am using PySCF, and checked that the molecular orbitals(MO) from the HF calculation are orthonormal. If S is the Overlap matrix, and V is the matrix of the MO coefficients, It can be seen from the equation,&#xA;&lt;span class=&quot;math-container&quot;&gt;$ V^T * S * V = I $&lt;/span&gt; when I is the Identity matrix.&#xA;The S can be calculated from PySCF as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;S = mol.intor('int1e_ovlp')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; is created from orthonormal orbitals, it has &lt;span class=&quot;math-container&quot;&gt;$1.00$&lt;/span&gt; as diagonal elements.&#xA;Now, the question is, I have a matrix of MO coefficients, which are not orthonormal. I was trying to orthonormalize them by using Lowdin symmetric orthogonalization. Which is actually,&#xA;&lt;span class=&quot;math-container&quot;&gt;$ W' = S^{-1/2} W $&lt;/span&gt; where, &lt;span class=&quot;math-container&quot;&gt;$W'$&lt;/span&gt; is orthonormalized orbitals and S is calculated as before.&#xA;However, the resulting orbitals are not orthonormal.&#xA;Possible reasons:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;The Lowdin method only does orthogonalization, so first, I need to normalize them&lt;/li&gt;&#xA;&lt;li&gt;Use a different method, like the Gram-Schmidt method&lt;/li&gt;&#xA;&lt;li&gt;Motivated from the [answer here][1], create &lt;span class=&quot;math-container&quot;&gt;$S$&lt;/span&gt; from non-orthogonal orbitals, find &lt;span class=&quot;math-container&quot;&gt;$S^{-1/2}$&lt;/span&gt; and do the transformation from non-orthonormal to orthonormal orbitals using &lt;span class=&quot;math-container&quot;&gt;$ W' = S^{-1/2} W $&lt;/span&gt; .&#xA;However, I am confused as to why Lowdin orthogonalization does not give the answers.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Are there other methods to do such orthonormalization?&#xA;[1]: &lt;a href=&quot;https://chemistry.stackexchange.com/questions/102144/is-the-lowdin-orthogonalization-used-in-diagonalizing-the-atomic-orbitals-really&quot;&gt;https://chemistry.stackexchange.com/questions/102144/is-the-lowdin-orthogonalization-used-in-diagonalizing-the-atomic-orbitals-really&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2024-02-02T15:34:10.117" Title="How to orthonormalize a set of Molecular orbitals?" Tags="|quantum-chemistry|molecular-modeling|quantum-mechanics|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12300" PostTypeId="2" ParentId="12290" CreationDate="2024-01-28T09:05:46.763" Score="1" Body="&lt;p&gt;As per the README we can invoke martinize as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;martinize.py -i input.pdb -o output.pdb&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I ran the command on a PDB of &lt;a href=&quot;https://www.rcsb.org/structure/4POJ&quot; rel=&quot;nofollow noreferrer&quot;&gt;4poj&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;And I get the following output files:&lt;/p&gt;&#xA;&lt;p&gt;output.pdb&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#include &amp;quot;martini.itp&amp;quot;&#xA;#include &amp;quot;Protein_A.itp&amp;quot;&#xA;#include &amp;quot;Protein_B.itp&amp;quot;&#xA;&#xA;[ system ]&#xA;; name&#xA;Martini system from /content/drive/MyDrive/input_files/PDB/4poj.pdb&#xA;&#xA;[ molecules ]&#xA;; name        number&#xA;Protein_A    1&#xA;Protein_B    1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Protein_A.itp (pasting only a subset of the full file here since the file exceeds line limit in MMSE)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; MARTINI (martini22) Coarse Grained topology file for &amp;quot;Protein_A&amp;quot;&#xA;; Created by martinize.py version 2.6 &#xA;; Using the following options:  -f /content/drive/MyDrive/input_files/PDB/4poj.pdb -o output.pdb&#xA;; Sequence:&#xA;; EDMPVERILEAELAVEPNDPVTNICQAADKQLFTLVEWAKRIPHFSELPLDDQVILLRAGWNELLIASFSHRSIAVKDGILLATGLHVHRNSAHSAGVGAIFDRVLTELVSKMRDMQMDKTELGCLRAIVLFNPDSKGLSNPAEVEALREKVYASLEAYCKHKYPEQPGRFAKLLLRLPALRSIGLKCLEHLFFFKLIGDTPIDTFLMEMLEAP&#xA;; Secondary Structure:&#xA;; CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC&#xA;&#xA;[ moleculetype ]&#xA;; Name         Exclusions&#xA;Protein_A         1&#xA;&#xA;[ atoms ]&#xA;    1    Qd     1   GLU    BB     1  1.0000 ; C&#xA;    2    Qa     1   GLU   SC1     2 -1.0000 ; C&#xA;    3    P5     2   ASP    BB     3  0.0000 ; C&#xA;    4    Qa     2   ASP   SC1     4 -1.0000 ; C&#xA;    5    P5     3   MET    BB     5  0.0000 ; C&#xA;    6    C5     3   MET   SC1     6  0.0000 ; C&#xA;    7    P4     4   PRO    BB     7  0.0000 ; C&#xA;    8    C3     4   PRO   SC1     8  0.0000 ; C&#xA;    9    P5     5   VAL    BB     9  0.0000 ; C&#xA;   10   AC2     5   VAL   SC1    10  0.0000 ; C&#xA;   11    P5     6   GLU    BB    11  0.0000 ; C&#xA;   12    Qa     6   GLU   SC1    12 -1.0000 ; C&#xA;   13    P5     7   ARG    BB    13  0.0000 ; C&#xA;   14    N0     7   ARG   SC1    14  0.0000 ; C&#xA;   15    Qd     7   ARG   SC2    15  1.0000 ; C&#xA;   16    P5     8   ILE    BB    16  0.0000 ; C&#xA;   17   AC1     8   ILE   SC1    17  0.0000 ; C&#xA;   18    P5     9   LEU    BB    18  0.0000 ; C&#xA;   19   AC1     9   LEU   SC1    19  0.0000 ; C&#xA;   20    P5    10   GLU    BB    20  0.0000 ; C&#xA;   21    Qa    10   GLU   SC1    21 -1.0000 ; C&#xA;   22    P4    11   ALA    BB    22  0.0000 ; C&#xA;   23    P5    12   GLU    BB    23  0.0000 ; C&#xA;   24    Qa    12   GLU   SC1    24 -1.0000 ; C&#xA;   25    P5    13   LEU    BB    25  0.0000 ; C&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Protein_B.itp&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;; MARTINI (martini22) Coarse Grained topology file for &amp;quot;Protein_B&amp;quot;&#xA;; Created by martinize.py version 2.6 &#xA;; Using the following options:  -f /content/drive/MyDrive/input_files/PDB/4poj.pdb -o output.pdb&#xA;; Sequence:&#xA;; KHKILHRLLQD&#xA;; Secondary Structure:&#xA;; CCCCCCCCCCC&#xA;&#xA;[ moleculetype ]&#xA;; Name         Exclusions&#xA;Protein_B         1&#xA;&#xA;[ atoms ]&#xA;    1    Qd     1   LYS    BB     1  1.0000 ; C&#xA;    2    C3     1   LYS   SC1     2  0.0000 ; C&#xA;    3    Qd     1   LYS   SC2     3  1.0000 ; C&#xA;    4    P5     2   HIS    BB     4  0.0000 ; C&#xA;    5   SC4     2   HIS   SC1     5  0.0000 ; C&#xA;    6   SP1     2   HIS   SC2     6  0.0000 ; C&#xA;    7   SP1     2   HIS   SC3     7  0.0000 ; C&#xA;    8    P5     3   LYS    BB     8  0.0000 ; C&#xA;    9    C3     3   LYS   SC1     9  0.0000 ; C&#xA;   10    Qd     3   LYS   SC2    10  1.0000 ; C&#xA;   11    P5     4   ILE    BB    11  0.0000 ; C&#xA;   12   AC1     4   ILE   SC1    12  0.0000 ; C&#xA;   13    P5     5   LEU    BB    13  0.0000 ; C&#xA;   14   AC1     5   LEU   SC1    14  0.0000 ; C&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I ran the command on your PDB file, the code seems to throw an error.&#xA;Without the -o option on your file, this is what the code outputs for your PDB file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INFO       MARTINIZE, script version 2.6&#xA;INFO       If you use this script please cite:&#xA;INFO       de Jong et al., J. Chem. Theory Comput., 2013, DOI:10.1021/ct300646g&#xA;INFO       Chain termini will be charged&#xA;INFO       Residues at chain brakes will not be charged&#xA;INFO       The martini22 forcefield will be used.&#xA;INFO       Local elastic bonds will be used for extended regions.&#xA;INFO       Read input structure from file.&#xA;INFO       Input structure is a PDB file.&#xA;INFO       Found 2 chains:&#xA;INFO          1:    (Unknown), 13 atoms in 1 residues.&#xA;INFO          2:    (Protein), 13 atoms in 1 residues.&#xA;INFO       Removing HETATM chain  consisting of 1 residues.&#xA;INFO       Total size of the system: 1 residues.&#xA;WARNING    No secondary structure or determination method speficied. Protein chains will be set to 'COIL'.&#xA;INFO       Note: Cysteine bonds are 0.24 nm constraints, instead of the published 0.39nm/5000kJ/mol.&#xA;&#xA;    There you are. One MARTINI. Shaken, not stirred.&#xA;&#xA;&#xA;And when that first martini hits the liver like a silver bullet, there is a sigh of contentment that can be heard in Dubuque. &#xA;                                                          --William Emerson, Jr. &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2024-01-28T09:05:46.763" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12301" PostTypeId="2" ParentId="12295" CreationDate="2024-01-28T23:11:10.367" Score="4" Body="&lt;p&gt;Turbomole and Q-Chem (as Gaussian, Molpro, Orca, Gamess, PySCF, ...) use Gaussian-type orbitals (that's not really news) for molecular input. Turbomole, Gaussian and PySCF also for crystal structures using periodic boundary conditions. Using the same input coordinates and basis set, they all should generate the same molecular orbitals. Not necessarily the identical numerical values in the same order, but they should all generate the same properties.&lt;/p&gt;&#xA;&lt;p&gt;While I do remember the times when molecular orbitals have sometimes been painful to get (computationally demanding or hard to achieve convergence) and were considered as very valuable - nowadays Hartree-Fock or DFT single-point energy calculations to get converged molecular orbitals are hardly ever a time-critical task. But there might be other reasons I am not aware of why those orbitals must be converted rather than re-calculated...&lt;/p&gt;&#xA;&lt;p&gt;@Susi: I know you are an 'old hand' in quantum chemistry, so nothing new for you so far. So let me try to give at least some help for the first step of the Turbomole -&amp;gt; Q-Chem conversion, namely to get a known and documented format of molecular orbitals:&lt;/p&gt;&#xA;&lt;p&gt;I am not familiar with Q-Chem, so I do not know which formats for MOs as input can be provided. From Turbomole side I'd however recommend to generate a common format like molden input file (run &lt;code&gt;tm2molden -norm&lt;/code&gt; in a directory with a finished Turbomole job), or use the &lt;code&gt;proper&lt;/code&gt; tool that comes with Turbomole to generate for example a wfn file. Another possibility is to use the AOMix file format that &lt;code&gt;tm2aomix&lt;/code&gt; generates. That's just for the export, but perhaps there is someone out there who knows a molden to Q-Chem or wfn to Q-Chem tool which converts the orbitals for the import part?&lt;/p&gt;&#xA;" OwnerUserId="1997" LastEditorUserId="1997" LastEditDate="2024-01-28T23:16:33.010" LastActivityDate="2024-01-28T23:16:33.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12302" PostTypeId="1" AcceptedAnswerId="12304" CreationDate="2024-01-29T13:18:03.270" Score="6" ViewCount="178" Body="&lt;p&gt;What is the velocity of each hydrogen atom in an H2 molecule, given a kinetic energy of hydrogen molecule is 0.12 eV, when expressed in angstroms per femtosecond and assuming equal velocities for both hydrogen atoms (using in POSCAR file for initial velocity)?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="5" LastEditDate="2024-01-29T22:00:46.983" LastActivityDate="2024-01-29T22:00:46.983" Title="Speed of atom from kinetic energy of molecule" Tags="|vasp|molecular-dynamics|python|mathematical-modeling|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12303" PostTypeId="1" CreationDate="2024-01-29T13:29:00.883" Score="4" ViewCount="26" Body="&lt;p&gt;I am working with nanostructure used as gas sensor/filters. Reading the literature, I found that one of the properties that can be calculated to characterize the (re)usability of a sensor is the recovery time, &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt;. The formula used to calculate &lt;span class=&quot;math-container&quot;&gt;$\tau$&lt;/span&gt; is described as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tau = \nu^{-1}_0 exp (-E_{ads}/k_BT),\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\nu_0$&lt;/span&gt; is the frequency of the ultraviolet radiation used, &lt;span class=&quot;math-container&quot;&gt;$E_{ads}$&lt;/span&gt; is the absorption energy, &lt;span class=&quot;math-container&quot;&gt;$k_B$&lt;/span&gt; is the Boltzmann constant, and &lt;span class=&quot;math-container&quot;&gt;$T$&lt;/span&gt; is the system temperature.&lt;/p&gt;&#xA;&lt;p&gt;I tracked around 23-25 papers about how (1) was obtained. In all of them, I only found, without any further citations or citations to other papers that used the same justification:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The recovery time can be predicted from the following formula of transition theory:&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$\tau = \nu^{-1}_0 exp (-E_{ads}/k_BT),\tag{1}$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;strong&gt;Question: Do you know a primary source for equation (1)?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-01-29T13:29:00.883" Title="Primary source for recovery time equation?" Tags="|adsorption|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12304" PostTypeId="2" ParentId="12302" CreationDate="2024-01-29T15:06:31.453" Score="6" Body="&lt;h1&gt;What is the kinetic energy of a molecule?&lt;/h1&gt;&#xA;&lt;p&gt;There is not just one type of kinetic energy when we have a composite system (made up of more than one particle, as in the case of a molecule). For example, molecules have &lt;strong&gt;rotational kinetic energy&lt;/strong&gt;, and &lt;strong&gt;translational kinetic energy&lt;/strong&gt;. Most people are interested in translational kinetic energy first.&lt;/p&gt;&#xA;&lt;h1&gt;Translational kinetic energy&lt;/h1&gt;&#xA;&lt;p&gt;The kinetic energy of a dinuclear molecule is often given by the following formula (assuming that the velocity is constant, otherwise we might write this expression in terms of momentum rather than velocity):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;K = \frac{1}{2}\mu v^2,&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$\mu$&lt;/span&gt; is the &amp;quot;reduced mass&amp;quot; of the molecule:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\mu = \frac{m_1 m_2}{m_1 + m_2},&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;in which &lt;span class=&quot;math-container&quot;&gt;$m_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$m_2$&lt;/span&gt; are the masses of the two atoms that came together to form that dinuclear molecule.&lt;/p&gt;&#xA;&lt;p&gt;If you want the velocity of the molecule's centre of mass, you can re-arrange my Eq. 1 to find &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;. We can assume that the rigid molecule's nuclei are moving with at the same speed as the center of mass (we are ignoring any other types of motion such as vibrations and rotations), &lt;strong&gt;so the hydrogen nuclei can be considered to move at the speed &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; that you obtain from re-arranging and solving my Eq. 1.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Do we use atomic masses or nuclear masses?&lt;/h1&gt;&#xA;&lt;p&gt;People that do &lt;em&gt;ab initio&lt;/em&gt; electronic structure calculations use nuclear masses for convenience, but spectroscopists that are concerned more with matching theory to spectroscopic experiments, often use atomic masses, because the mass of the atom is not as simple as &lt;span class=&quot;math-container&quot;&gt;$m_{\textrm{nucleus}} + m_{\textrm{electrons}}$&lt;/span&gt;: removing electrons has an effect on energy, and in special relativity, energy and mass are related. Therefore, it's better to use atomic masses, which include the entire atom (including the nucleus and all electrons and all associated energy) so that we don't have to worry about making corrections due to the effects of special relativity. &lt;strong&gt;If we know the &amp;quot;mass&amp;quot; of the entire molecule, that might even be better, but usually we use the reduced mass based on my Eq. 2, and use atomic masses in the formula.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Conversion of units&lt;/h1&gt;&#xA;&lt;p&gt;Many people might have other preferences, but in situations with many types of units being mixed, I love to simplify things back to how I learned them in school (you might think this is tedious, but I prefer doing it this way): the energy in eV can be converted to the SI unit of Joules. Then if we use the atomic masses in kilograms when solving for &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; in my eq. 1, we will get &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt; in m/s (meters per second). We can then use the fact that 1 metre is &lt;span class=&quot;math-container&quot;&gt;$10^{10}$&lt;/span&gt; Angstroms, and 1 second is &lt;span class=&quot;math-container&quot;&gt;$10^{15}$&lt;/span&gt; femtoseconds, to get the velocity in Angstroms/fs.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-01-29T21:59:34.583" LastActivityDate="2024-01-29T21:59:34.583" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12305" PostTypeId="1" CreationDate="2024-01-29T19:56:12.350" Score="3" ViewCount="31" Body="&lt;p&gt;I am beginner in LAMMPS. I downloaded the latest version for Windows and installed it. However, when I check Bin folder, there is no lmp_serial executable file. It's lmp.exe instead. Is this a problem? Thanks&lt;/p&gt;&#xA;" OwnerUserId="8744" LastEditorUserId="7" LastEditDate="2024-03-21T17:25:55.590" LastActivityDate="2024-03-21T17:25:55.590" Title="LAMMPS installation: lmp_serial executable missing" Tags="|lammps|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12306" PostTypeId="1" CreationDate="2024-01-30T04:13:32.117" Score="5" ViewCount="66" Body="&lt;p&gt;I am performing a Mulliken population analysis (MPA) for a molecular system of interest (calculated with B3LYP/Def2-TZVP). I am analyzing the LCAO-MO coefficients/contributions associated with each &amp;quot;atomic orbital&amp;quot; towards a particular set of Kohn-Sham canonical orbitals. I have encountered a semi-expected problem being the negative orbital contributions.&lt;/p&gt;&#xA;&lt;p&gt;For example, consider this simple fictional system with the LCAO-MO of the following simple system with three atomic orbital functions:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{i}=\sum_{\mu=1}^{3}c_{i\mu}\phi_{\mu}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{1}=\underset{90\%}{c_{11}\phi_{1}}+\underset{12\%}{c_{12}\phi_{2}}+\underset{-2\%}{c_{13}\phi_{3}}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{2}=\underset{-2\%}{c_{21}\phi_{1}}+\underset{90\%}{c_{22}\phi_{2}}-\underset{12\%}{c_{23}\phi_{3}}$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\psi_{3}=\underset{12\%}{c_{31}\phi_{1}}-\underset{-2\%}{c_{32}\phi_{2}}-\underset{90\%}{c_{33}\phi_{3}}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The numbers underneath the linear combination terms represents the percentage orbital character as calculated with the MPA scheme. The sums of the columns/rows of the orbital contributions all equal one, which signifies that the atomic orbitals are normalized and have equal contribution summed over the set of molecular orbitals.&lt;/p&gt;&#xA;&lt;p&gt;I have read in the software manual of the program that the MPA method can result in negative orbital populations atomic orbitals with strong bonding or antibonding overlap populations as a result of equal partitioning of electron density, however, I have trouble analyzing the physical meaning of the negative orbital contributions.&lt;/p&gt;&#xA;&lt;p&gt;Does this mean my data is completely unreliable, or does it mean that it falls within the error associated with the MPA method?&lt;/p&gt;&#xA;&lt;p&gt;This is my first attempt at LCAO-MO analysis, and my knowledge on this subject is self-taught and limited. It is very possible I could be making a conceptual error. Any help is appreciated, thank you.&lt;/p&gt;&#xA;" OwnerUserId="7643" LastActivityDate="2024-01-30T04:13:32.117" Title="What do Negative Atomic Orbital Contributions in a Mulliken Population Analysis mean?" Tags="|density-functional-theory|computational-chemistry|molecular-modeling|ab-initio-calculations|population-analysis|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12307" PostTypeId="1" CreationDate="2024-01-30T10:36:54.520" Score="2" ViewCount="36" Body="&lt;p&gt;I am seeking clarification on whether choosing the appropriate topological invariants has any relation to the dimensionality of the system. I understand that in three-dimensional (3D) materials, the Chern number and Z2 invariant are commonly used, while in two-dimensional (2D) materials, the Chern number is often calculated. However, I am uncertain about the specific topological invariant that should be considered for one-dimensional (1D) systems.&lt;/p&gt;&#xA;&lt;p&gt;Could someone provide guidance on which topological invariant we should calculate for 1D materials to determine their topological nature? Specifically, any available codes that could help with that. Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-01-31T11:07:25.527" Title="Clarification Needed about Topological Invariants" Tags="|ab-initio-calculations|topological-insulators|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12308" PostTypeId="1" CreationDate="2024-01-30T14:14:20.703" Score="2" ViewCount="24" Body="&lt;p&gt;For my set-up to compute the free energy of dimerization between two molecules in a solvent using umbrella sampling, I can see that there is an entropic contribution since I have used distance as a reaction coordinate. How can we eliminate this entropic contribution from the free energy profile? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2024-01-30T14:14:20.703" Title="Eliminate the entropic contribution in the free energy of dimerization between two molecules in umbrella sampling" Tags="|molecular-dynamics|gromacs|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12309" PostTypeId="1" CreationDate="2024-01-30T14:18:08.890" Score="4" ViewCount="66" Body="&lt;p&gt;I know how to do a PES scan for a ground electronic state. But for the nth-excited state, is it the same (i.e. an excited state optimization and just rotating the dihedral to simulate the isomerization)? Is it essentially a separate PES, or do I use my ground state geometries and do excited state optimizations on them?&lt;/p&gt;&#xA;&lt;p&gt;My understanding is that you just define your internal coordinates, and then do SP calculations (and maybe thermodynamic correct at critical points) at the ground state.&lt;/p&gt;&#xA;" OwnerUserId="8598" LastEditorUserId="5" LastEditDate="2024-01-31T02:59:04.283" LastActivityDate="2024-01-31T03:09:54.047" Title="How do I do a PES (potential energy surface) scan for the excited electronic state?" Tags="|geometry-optimization|td-dft|excited-states|potential-energy-surface|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12310" PostTypeId="1" CreationDate="2024-01-30T16:06:43.557" Score="3" ViewCount="63" Body="&lt;p&gt;I tried to run my Quantum ESPRESSO calculations as I was used to do in my desktop. But they give me an error message linked to Openmpi, and I don't know how to solve it. Can someone please help me?&#xA;The error message is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[salma-Precision-3640-Tower:304573] mca_base_component_repository_open: unable to open mca_ess_singleton: /usr/lib/x86_64-linux-gnu/openmpi/lib/openmpi3/mca_ess_singleton.so: invalid ELF header (ignored)&#xA;--------------------------------------------------------------------------&#xA;A requested component was not found, or was unable to be opened.  This&#xA;means that this component is either not installed or is unable to be&#xA;used on your system (e.g., sometimes this means that shared libraries&#xA;that the component requires are unable to be found/loaded).  Note that&#xA;Open MPI stopped checking at the first component that it did not find.&#xA;&#xA;Host:      salma-Precision-3640-Tower&#xA;Framework: ess&#xA;Component: singleton&#xA;--------------------------------------------------------------------------&#xA;[salma-Precision-3640-Tower:304573] [[INVALID],INVALID] ORTE_ERROR_LOG: Not found in file runtime/orte_init.c at line 247&#xA;--------------------------------------------------------------------------&#xA;It looks like orte_init failed for some reason; your parallel process is&#xA;likely to abort.  There are many reasons that a parallel process can&#xA;fail during orte_init; some of which are due to configuration or&#xA;environment problems.  This failure appears to be an internal failure;&#xA;here's some additional information (which may only be relevant to an&#xA;Open MPI developer):&#xA;&#xA;  orte_ess_base_open failed&#xA;  --&amp;gt; Returned value Not found (-13) instead of ORTE_SUCCESS&#xA;--------------------------------------------------------------------------&#xA;--------------------------------------------------------------------------&#xA;It looks like MPI_INIT failed for some reason; your parallel process is&#xA;likely to abort.  There are many reasons that a parallel process can&#xA;fail during MPI_INIT; some of which are due to configuration or environment&#xA;problems.  This failure appears to be an internal failure; here's some&#xA;additional information (which may only be relevant to an Open MPI&#xA;developer):&#xA;&#xA;  ompi_mpi_init: ompi_rte_init failed&#xA;  --&amp;gt; Returned &amp;quot;Not found&amp;quot; (-13) instead of &amp;quot;Success&amp;quot; (0)&#xA;--------------------------------------------------------------------------&#xA;*** An error occurred in MPI_Init&#xA;*** on a NULL communicator&#xA;*** MPI_ERRORS_ARE_FATAL (processes in this communicator will now abort,&#xA;***    and potentially your MPI job)&#xA;[salma-Precision-3640-Tower:304573] Local abort before MPI_INIT completed completed successfully, but am not able to aggregate error messages, and not able to guarantee that all other processes were killed!&#xA;salma@salma-Precision-3640-Tower:~/Desktop/CuI2/elastic$ &#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2024-01-30T16:06:43.557" Title="Need Help Resolving Quantum ESPRESSO Calculation Error Linked to OpenMPI on Desktop" Tags="|quantum-espresso|high-performance-computing|quantum-computing|" AnswerCount="0" CommentCount="13" ContentLicense="CC BY-SA 4.0" />
  <row Id="12311" PostTypeId="1" AcceptedAnswerId="12314" CreationDate="2024-01-30T17:50:47.420" Score="6" ViewCount="143" Body="&lt;p&gt;I recently wrote a simple HF SCF program for my understanding and realized that I do not fully understand such QM calculations.&lt;/p&gt;&#xA;&lt;p&gt;Suppose I have the ground state gaussian wave function of a system,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi_0 = \sum C_iG_i \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$G_i$&lt;/span&gt; is the gaussian function. And by some means I have the value of all the &lt;span class=&quot;math-container&quot;&gt;$C_i$&lt;/span&gt; that define the ground state &lt;span class=&quot;math-container&quot;&gt;$\psi_0$&lt;/span&gt;, and coordinates for &lt;span class=&quot;math-container&quot;&gt;$G_i$&lt;/span&gt;. Can I calculate the energy of the ground state of this system using this information alone? For a known wave function, should I not be able to determine the energy?&lt;/p&gt;&#xA;&lt;p&gt;For SCF I always need the Fock matrix and hence full density matrix. I could not comeup with relations which just involve &lt;span class=&quot;math-container&quot;&gt;$C_i$&lt;/span&gt; and the one-e and two-e integrals. What I am not understanding here?&lt;/p&gt;&#xA;" OwnerUserId="785" LastEditorUserId="5" LastEditDate="2024-01-30T20:57:54.257" LastActivityDate="2024-02-03T03:23:06.183" Title="How do I get the energy, if I have the wavefunction?" Tags="|electronic-structure|mathematical-modeling|quantum-mechanics|hartree-fock|self-consistent-field|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12313" PostTypeId="2" ParentId="12154" CreationDate="2024-01-30T19:57:52.007" Score="0" Body="&lt;p&gt;Tried this approach. From the first row three atoms are selected and then for each of these, atoms on the opposite are selected along the column&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import ase.io&#xA;import ase.build&#xA;from ase.visualize import view&#xA;from ase.build import add_adsorbate&#xA;from ase import Atoms&#xA;&#xA;slab = ase.build.graphene(formula='C2',a=2.46,size=(6,6,1))&#xA;slab.center()&#xA;water = ase.build.molecule('H2O')&#xA;&#xA;h = 3.31&#xA;&#xA;&#xA;a=slab.positions[:,1].min()&#xA;index=[]&#xA;for i in range(len(slab)):&#xA;    if slab[i].position[1]==a:&#xA;        index.append(i)&#xA;&#xA;start_index=index[::2]&#xA;&#xA;for i in start_index:&#xA;    x = (slab[i].position[0])&#xA;    y = (slab[i].position[1])&#xA;    add_adsorbate(slab, adsorbate=water, height=h, position=(x,y), offset=None, mol_index=0)&#xA;    &#xA;    for j in range(i,len(slab.positions)):&#xA;        dist=((slab[j].position[0]-slab[i].position[0])**2+(slab[j].position[1]-slab[i].position[1])**2)**0.5&#xA;        if 2.84&amp;lt;dist&amp;lt;2.842:&#xA;            x = (slab[j].position[0])&#xA;            y = (slab[j].position[1])&#xA;            add_adsorbate(slab, adsorbate=water, height=h, position=(x,y), offset=None, mol_index=0)&#xA;            i=j&#xA;        continue&#xA;        &#xA;        &#xA;&#xA;view(slab)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8746" LastEditorUserId="8746" LastEditDate="2024-01-31T07:22:44.280" LastActivityDate="2024-01-31T07:22:44.280" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12314" PostTypeId="2" ParentId="12311" CreationDate="2024-01-30T20:56:59.127" Score="5" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;For a known wave function, should I not be able to determine the energy?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The wavefuncton is an eigenfunction of the Hamiltonian, and the energy is a corresponding eigenvalue of the same Hamiltonian. Therefore if the Hamiltonian is &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; and the wavefunction is &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt;, then simply multiply &lt;span class=&quot;math-container&quot;&gt;$H$&lt;/span&gt; by &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; on the right-side, and you are supposed to get back the wavefunction &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; multiplied by a factor &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, which is the energy:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tag{1}&#xA;H\psi = E\psi.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;What you get back in reality might not be exactly the original wavefunction multiplied by a scalar factor &lt;span class=&quot;math-container&quot;&gt;$E$&lt;/span&gt;, because you might have an approximation to the wavefunction rather than an exact one (and if it's only an approximate eigenfunction, Eq. 1 will not work perfectly, but you have a good approximation of &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; then Eq. 1 is likely to work quite well).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-01-30T20:56:59.127" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12315" PostTypeId="2" ParentId="12311" CreationDate="2024-01-30T23:12:04.133" Score="3" Body="&lt;p&gt;UPDATE: I didnt read your post carefully enough. My answer is irrelevant.&lt;/p&gt;&#xA;&lt;p&gt;In your comment above you said&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I guess what i meant was that if I have an arbitrary state eigenfunction (approximated as the gaussian basis), can I estimate the energy of that state, without the need of other state eigenfunctions? I think the answer should be yes, but I could not figure it out. For it seems that even a single energy eigenvalue would need full density matrix&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Depending on some assumptions, I think the answer is &lt;strong&gt;yes&lt;/strong&gt;. The assumption I will make are (i) that your basis set is complete enough that the solutions actually are eigenfunctions of the Hamiltonian (see &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12314/1258&quot;&gt;Nike's answer&lt;/a&gt; above) and (ii) that you can write down the Hamiltonian. For self-consistent methods like HF and DFT, this might mean you have to know the eigenfunctions to calculate the density and potential, but this isn't generally true: e.g. for the free electron, I can write the Hamiltonian without knowing anything about the solutions. For a KS or HF Hamiltonian, assume we can read the density from a file or something.&lt;/p&gt;&#xA;&lt;p&gt;The Schrodinger's equation (SE) is &lt;span class=&quot;math-container&quot;&gt;$H | \psi_n \rangle = E_n | \psi_n \rangle $&lt;/span&gt;. &lt;span class=&quot;math-container&quot;&gt;$\psi_n$&lt;/span&gt; are the 'eigenfunctions' of the Hamiltonian. &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; labels the eigenfunctions. &lt;span class=&quot;math-container&quot;&gt;$E_n$&lt;/span&gt; is the eigenvalue/energy of the &lt;span class=&quot;math-container&quot;&gt;$n^{th}$&lt;/span&gt; eigenfunction.&lt;/p&gt;&#xA;&lt;p&gt;Recall that eigenfunctions are orthogonal (I further assume they are normalized): &lt;span class=&quot;math-container&quot;&gt;$\langle \psi_m | \psi_n \rangle = \delta_{nm}$&lt;/span&gt;. Then &lt;span class=&quot;math-container&quot;&gt;$E_n = \langle \psi_n | H | \psi_n \rangle$&lt;/span&gt;. Determining the energy depends on whether or not you can calculate the matrix element &lt;span class=&quot;math-container&quot;&gt;$H_{nn} = \langle \psi_n | H | \psi_n \rangle$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Some examples: in periodic DFT, this means &lt;span class=&quot;math-container&quot;&gt;$H_{nn} = N \int_V d{\bf{x}} u^*_{n} ({\bf{x}}) H({\bf{x}}) u_{n}({\bf{x}})$&lt;/span&gt;, where the integral is over the unitcell, &lt;span class=&quot;math-container&quot;&gt;$u_n({\bf{x}})$&lt;/span&gt; is the periodic part of the (Bloch) wavefunction, and &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is the number of unit cells in the crystal. For the 1d free electron, the solutions are &lt;span class=&quot;math-container&quot;&gt;$\psi_k(x) = L^{-1/2} \exp(i k x)$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$H_{kk} = -\frac{\hbar^2}{2mL}  \int_L dx \exp(-ikx)  \nabla^2  \exp(ikx) = \frac{\hbar^2 k ^2}{2m} $&lt;/span&gt; with &lt;span class=&quot;math-container&quot;&gt;$E_k = \frac{\hbar^2 k ^2}{2m}$&lt;/span&gt; the energy of the eigenfunction &lt;span class=&quot;math-container&quot;&gt;$\psi_k(x)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this helps :)&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="1258" LastEditDate="2024-02-03T03:23:06.183" LastActivityDate="2024-02-03T03:23:06.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12316" PostTypeId="2" ParentId="12309" CreationDate="2024-01-31T02:55:07.767" Score="3" Body="&lt;p&gt;To scan the potential energy surface (PES) for an excited electronic state, you can do the same thing that you would do for scanning the PES for the ground electronic state, except that you need to ensure that your calculations are targeting the excited state.&lt;/p&gt;&#xA;&lt;p&gt;In software such as &lt;a href=&quot;/questions/tagged/mrcc&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;mrcc&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;mrcc&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-mrcc-tooltip-container&quot;&gt;mrcc&lt;/a&gt; and &lt;a href=&quot;/questions/tagged/pyscf&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;pyscf&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;pyscf&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-pyscf-tooltip-container&quot;&gt;pyscf&lt;/a&gt;, when using CCSD(T) or CISD or any of the electronic structure methods that I typically use, the user can specify the number of &amp;quot;roots&amp;quot; (usually with a variable name such as &lt;code&gt;nroots&lt;/code&gt;), which effectively is the number of states for which you will be obtaining an energy.&lt;/p&gt;&#xA;&lt;p&gt;Here is an example of some of my own calculations on the H2 molecule at equilibrium with the aug-cc-pVDZ basis set and the FCI (CISD = FCI for a 2-electron system) method (these are the energies of the lowest three electronic states obtained by MRCC):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;                               MRCC         PySCF&#xA; Total CISD energy [au]: -1.164624207027 -1.16462421 (1^1 Sigma_g)&#xA; Total CISD energy [au]: -0.683393683543 -0.68339368  &#xA; Total CISD energy [au]: -0.427295580627 -0.42729558 (3^3 Sigma_g)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The PySCF output file (which contains the input file) can be found &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/H2/X/r%3D1.401100_Bohr/PySCF_a2z.txt&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, but you would likely need to use &lt;code&gt;grep&lt;/code&gt; to organize the three above energies in the type of column array that I displayed here.&lt;/p&gt;&#xA;&lt;p&gt;To scan the PES with the excited state, you would do the same type of calculation as done in the input file that I made available from the link in the previous paragraph, except you would do it for more geometries (i.e. different values for the internal coordinates, since you suggested that you are using internal coordinates). If by &amp;quot;scan&amp;quot; the PES you are just looking for the minimum energy, you can also execute a geometry optimization algorithm for the excited states, provided that the software that you are using allows some of that process to be automated (or you can do the optimization manually otherwise).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Is it essentially a separate PES&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Yes, in the way we do quantum chemistry, especially with the Born-Oppenheimer model/approximation, each electronic state has its own potential energy surface.&lt;/p&gt;&#xA;&lt;p&gt;In the example below, which is for the Na2 molecule and from &lt;a href=&quot;https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.78.483&quot; rel=&quot;nofollow noreferrer&quot;&gt;this paper&lt;/a&gt;, you can see the potential energy curves/surfaces for many excited electronic states of the molecule.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/IKnUH.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/IKnUH.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;or do I use my ground state geometries and do excited state optimizations on them?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;No, in the above diagram, the ground state (&lt;span class=&quot;math-container&quot;&gt;$X^1 \Sigma_g^+$&lt;/span&gt;) geometry (with lowest energy) has a bond length of around 6 Bohr radii, but the first excited electronic state with &lt;span class=&quot;math-container&quot;&gt;$^1 \Sigma_g^+$&lt;/span&gt; symmetry is the &lt;span class=&quot;math-container&quot;&gt;$2 ^1\Sigma_g^+$&lt;/span&gt; state which has an equilibrium bond length of around 8 Bohr radii, which is quite a big difference in terms of bond lengths. Once you pick a geometry (such as the ground electronic state equilibrium geometry), you can do excited state calculations at that geometry, but then you are not &amp;quot;optimizing&amp;quot; anything, so you are not &amp;quot;doing optimizations on them&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-01-31T03:09:54.047" LastActivityDate="2024-01-31T03:09:54.047" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12317" PostTypeId="1" AcceptedAnswerId="12343" CreationDate="2024-01-31T03:19:48.700" Score="4" ViewCount="65" Body="&lt;p&gt;I have been reading up on methods where electron density was estimated directly from some machine learning method, followed by evaluation of energy and forces[1,2]. My understanding is that this is achieved by&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;predicting the wavefunction coefficients (i.e. &lt;span class=&quot;math-container&quot;&gt;$C_i$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$\sum C_i G_i$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$G_i$&lt;/span&gt; is gaussian/planewave the basis set&lt;/li&gt;&#xA;&lt;li&gt;computing energy and forces directly from this wavefunction/density&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I was trying to replicate similar approach to better understand it, but by using simple Hartree Fock method. I tried to compute energy of such an ML determined wave function directly. However to compute the  energy of a wavefunction I needed the Fock matrix, which would need not only the determined wavefunction, but also other orbitals.&lt;/p&gt;&#xA;&lt;p&gt;That is, the Fock matrix (Szabo and Ostlund, 3.154):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;F_{\mu\nu} = H_{\mu\nu} + \sum_{ij}P_{ij}(\mu\nu|ij) - 0.5 (\mu i|j\nu)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;requires contributions &lt;span class=&quot;math-container&quot;&gt;$P_{ij}$&lt;/span&gt; from all orbitals.&lt;/p&gt;&#xA;&lt;p&gt;So is similar approach impossible for HF and only feasible for DFT? Or do I need to predict the full density matrix for HF?&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Fiedler, L., Modine, N.A., Schmerler, S. et al. Predicting electronic structures at any length scale with machine learning. npj Comput Mater 9, 115 (2023). &lt;a href=&quot;https://doi.org/10.1038/s41524-023-01070-z&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Rackers, J. A.; Tecot, L.; Geiger, M.; Smidt, T. E. Cracking the Quantum Scaling Limit with Machine Learned Electron Densities. arXiv.org. &lt;a href=&quot;https://doi.org/10.48550/arXiv.2201.03726&quot; rel=&quot;nofollow noreferrer&quot;&gt;DOI&lt;/a&gt;&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="785" LastEditorUserId="7" LastEditDate="2024-02-02T17:42:12.140" LastActivityDate="2024-02-02T17:42:12.140" Title="Computing energy and forces directly from machine learned wavefuntion/density" Tags="|basis-sets|hartree-fock|machine-learning|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12318" PostTypeId="1" CreationDate="2024-01-31T08:45:37.507" Score="4" ViewCount="365" Body="&lt;p&gt;I'm new to DFT+U and trying to understand how FeTiO3 works by looking at its electronic properties. But there's a big problem: when I use normal DFT, I can't get the w&#xA;right band-gap value.&lt;/p&gt;&#xA;&lt;p&gt;How can I find the perfect &amp;quot;U values&amp;quot; for Fe and Ti atoms in FeTiO3? Is there any method to choose those values?&lt;/p&gt;&#xA;" OwnerUserId="8340" LastEditorUserId="671" LastEditDate="2024-02-02T07:00:57.147" LastActivityDate="2024-02-02T07:00:57.147" Title="How to choose the best U value for studying the electronic properties?" Tags="|density-functional-theory|quantum-espresso|band-structure|dft-u|bandgap|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12321" PostTypeId="1" CreationDate="2024-01-31T15:56:47.790" Score="5" ViewCount="80" Body="&lt;p&gt;I was doing DFT calculations using VASP of some transition metal compounds and plotted the density of states (DOS) along with the projected density of states (PDOS).&lt;/p&gt;&#xA;&lt;p&gt;I am wondering how can someone understand what is the oxidation state of a metal ion just by analysing the DOS plot of that compound? I have attached some DOS plots of &lt;span class=&quot;math-container&quot;&gt;$TiO_2$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/yJjXm.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/yJjXm.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0yrkX.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0yrkX.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Paper link : &lt;a href=&quot;https://iopscience.iop.org/article/10.1149/2.0561701jes&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://iopscience.iop.org/article/10.1149/2.0561701jes&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8750" LastEditorUserId="5" LastEditDate="2024-02-01T05:23:05.283" LastActivityDate="2024-02-02T00:16:47.233" Title="How may I analyze the oxidation state of any atom by analyzing the DOS plot?" Tags="|density-functional-theory|vasp|density-of-states|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12323" PostTypeId="2" ParentId="12318" CreationDate="2024-01-31T19:07:08.820" Score="6" Body="&lt;h2&gt;U values are in general &lt;em&gt;non-transferable&lt;/em&gt;&lt;/h2&gt;&#xA;&lt;p&gt;the U-value found in the literature will not give you the same band gap in general unless you know the exact structure, pseudopotentials, DFT code and their version, etc used in the original paper. Note that the U value might change the structure and changing U value requires you to relax the structure again. Therefore, I strongly recommend you &lt;em&gt;NOT&lt;/em&gt; to use those values given in the other answer. I will give you a general procedure using which you can find a self-consistent U value but please refer to &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1148/6055&quot;&gt;this&lt;/a&gt; excellent answers by Kevin J. May.&lt;/p&gt;&#xA;&lt;h2&gt;Calculating U values using &lt;code&gt;hp.x&lt;/code&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Looking at the tags, I am assuming you are using Quantum ESPRESSO (QE). QE has a module &lt;code&gt;hp.x&lt;/code&gt; which, among other things, can calculate U values. There are a few ways to do that: by running an expensive &lt;code&gt;hp.x&lt;/code&gt; calculation (around 20 times expensive than an scf calculation) or by running inexpensive &lt;code&gt;hp.x&lt;/code&gt; calculation followed by relaxing the structure with that U values, and continuing this until a self-consistency has been reached.&lt;/p&gt;&#xA;&lt;p&gt;Both of these methods have been covered in &lt;a href=&quot;https://youtu.be/64JKOF5lh2U?si=jHJM9oKN6tIQugVs&amp;amp;t=3762&quot; rel=&quot;noreferrer&quot;&gt;this video lecture&lt;/a&gt; (see from around 01:02:40) in &lt;a href=&quot;https://sites.google.com/view/hubbard-koopmans/program?authuser=0&quot; rel=&quot;noreferrer&quot;&gt;Advanced Quantum ESPRESSO tutorial: Hubbard and Koopmans functionals from linear response&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Very short summary of the expensive method: after you do your scf calculation, prepare a input file &lt;code&gt;hp.in&lt;/code&gt; like this (change the &lt;code&gt;prefix&lt;/code&gt; and &lt;code&gt;outdir&lt;/code&gt; according to your scf calculation):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;inputhp&#xA;   prefix = 'FeTiO3'&#xA;   outdir = './tmp'&#xA;   nq1 = 2, nq2 = 2, nq3 = 2&#xA;   conv_thr_chi = 1.d-6&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the details of the syntax, check &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_HP.html&quot; rel=&quot;noreferrer&quot;&gt;hp.x input description&lt;/a&gt;. After running this calculation by &lt;code&gt;hp.x -in hp.in &amp;gt; hp.out&lt;/code&gt;, you will get an output file which will look like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  =-------------------------------------------------------------------------------=&#xA;                                 Hubbard U parameters:&#xA;       site n.  type  label  spin  new_type  new_label  manifold  Hubbard U (eV)&#xA;         1        1    Co1     1      1         Co1        3d       6.7553&#xA;         2        2    Co2    -1      1         Co1        3d       6.7553&#xA;  =-------------------------------------------------------------------------------=&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The above is for a spin-polarized Co atom. You can see that the suggested U value is 6.7553 eV in this case. The inexpensive method will give you faster result but you need to run vc-relax calculation using that value. And then with the relaxed structure and intermediate U values, you have to repeat the inexpensive calculation until your U values converged. In the tutorial, Iurii Timrov suggested that a &lt;span class=&quot;math-container&quot;&gt;$\Delta U \leq 0.1\, \mathrm{eV}$&lt;/span&gt; is sufficient for majority of cases as the convergence threshold using this way.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-01-31T19:07:08.820" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12324" PostTypeId="1" CreationDate="2024-02-01T03:14:35.233" Score="4" ViewCount="65" Body="&lt;h2&gt;Background&lt;/h2&gt;&#xA;&lt;p&gt;My goal is to use PyCDT: Python Charged Defect Toolkit (&lt;a href=&quot;https://doi.org/10.1016/j.cpc.2018.01.004&quot; rel=&quot;nofollow noreferrer&quot;&gt;paper&lt;/a&gt;, &lt;a href=&quot;https://github.com/mbkumar/pycdt&quot; rel=&quot;nofollow noreferrer&quot;&gt;github&lt;/a&gt;, &lt;a href=&quot;https://pypi.org/project/pycdt/&quot; rel=&quot;nofollow noreferrer&quot;&gt;pypi&lt;/a&gt;). I installed the code by doing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pip3 install pycdt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not using any virtual environment. The OS is Ubuntu 22.04.3 LTS. Python version: 3.10.12, pip version: 23.3.2.&lt;/p&gt;&#xA;&lt;h2&gt;Issue&lt;/h2&gt;&#xA;&lt;p&gt;After installing the code, when I ran it, it gives the following error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ pycdt&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;/usr/local/bin/pycdt&amp;quot;, line 4, in &amp;lt;module&amp;gt;&#xA;    __import__('pkg_resources').run_script('pycdt==2.0.5', 'pycdt')&#xA;  File &amp;quot;/usr/lib/python3/dist-packages/pkg_resources/__init__.py&amp;quot;, line 656, in run_script&#xA;    self.require(requires)[0].run_script(script_name, ns)&#xA;  File &amp;quot;/usr/lib/python3/dist-packages/pkg_resources/__init__.py&amp;quot;, line 1453, in run_script&#xA;    exec(code, namespace, namespace)&#xA;  File &amp;quot;/usr/local/lib/python3.10/dist-packages/pycdt-2.0.5-py3.10.egg/EGG-INFO/scripts/pycdt&amp;quot;, line 37, in &amp;lt;module&amp;gt;&#xA;    from pymatgen.analysis.defects.thermodynamics import DefectPhaseDiagram&#xA;ModuleNotFoundError: No module named 'pymatgen.analysis.defects'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h2&gt;Attempt at solution&lt;/h2&gt;&#xA;&lt;p&gt;I have searched at the &lt;a href=&quot;https://groups.google.com/g/pycdt-forum&quot; rel=&quot;nofollow noreferrer&quot;&gt;PyCDT forum&lt;/a&gt; without success and also they are inactive in the forum for more than one and a half-year. I have tried installing it from the GitHub and their &lt;a href=&quot;https://bitbucket.org/mbkumar/pycdt/src&quot; rel=&quot;nofollow noreferrer&quot;&gt;BitBucket&lt;/a&gt; repo. After the seemingly successful installation, when I am running it, it throws an error saying:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;pkg_resources.DistributionNotFound: The 'pymatgen==2020.6.8' distribution was not found and is required by pycdt&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When trying to install that specific version of pymatgen, pip throws error saying &lt;code&gt;error: metadata-generation-failed&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-03T00:08:36.000" Title="How to resolve ModuleNotFoundError: No module named 'pymatgen.analysis.defects'?" Tags="|python|pymatgen|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12325" PostTypeId="1" CreationDate="2024-02-01T07:20:39.107" Score="2" ViewCount="60" Body="&lt;p&gt;The equation 57 in the reference [Jian-Sheng Wang, Jian Wang and J. T. Lu, Quantum thermal transport in nanostructures, Eur. Phys. J. B 62, 381 (2008)] explains the the transmission coefficient for the thermal conductance, as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$T_{\omega}={Tr}\left[G^{R}\Gamma_\text{left}G^{A}\Gamma_\text{right}\right]\tag{1}$$&lt;/span&gt;&#xA;The equation 12 in the reference [A. R. Rocha, V. M. García-Suárez, S. Bailey, C. Lambert, J. Ferrer and S. Sanvito, Spin and molecular electronics in atomically generated orbital landscapes, Phys. Rev. B, 73, 085414 (2006)] explains the transmission coefficient for the charge conductance, as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$G=\frac{2e^{2}}{h}\mathrm{Tr}\left[\Gamma_\text{left}G_{M}^{A}\Gamma_\text{right}G_{M}^{R}\right]\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;It seems that these two quantities are same; except the coefficient &lt;span class=&quot;math-container&quot;&gt;$\frac{2e^{2}}{h}$&lt;/span&gt;. This means that the following thermal conductance and charge conductance also seems same.&lt;/p&gt;&#xA;&lt;p&gt;Would anyone explain to me the difference between them; particularly, the difference in the calculation procedures for these two quantities (the transmission for the thermal and charge conductance / the thermal and charge conductance)?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="5" LastEditDate="2024-02-07T10:26:22.857" LastActivityDate="2024-02-07T10:26:22.857" Title="Difference of the Transmission Coefficient between Thermal and Charge Conductance by Nonequilibirum Green Function Method" Tags="|density-functional-theory|electronic-transport|transport|greens-functions|lattice-thermal-conductivity|" AnswerCount="0" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="12326" PostTypeId="1" AcceptedAnswerId="12327" CreationDate="2024-02-01T08:52:23.990" Score="2" ViewCount="60" Body="&lt;p&gt;In my AIMD simulations with the NVT ensemble at T= 300K (Nosé–Hoover thermostat)for a Pd (111) surface (2*2, 6 layers) and vacuum sizes of 14 Å and 18 Å, All other INCAR tags are same(only NGZ for 14Å (123) and 18Å (143)), I've observed two distinct graph time step versus temperature. I'm seeking clarification on the accuracy of these graphs.  If accurate, can it be inferred that increasing the vacuum size leads to a reduction in Temperature fluctuation?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7nruw.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7nruw.png&quot; alt=&quot;vacuum 14Å pd(111)surface&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/FHK9f.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/FHK9f.png&quot; alt=&quot;time step vs temperature graph at 14Å vacuum &quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/w7fys.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w7fys.png&quot; alt=&quot;vacuum 18Å pd(111)surface&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/aRNhK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/aRNhK.png&quot; alt=&quot;time step vs temperature graph at 18Åvacuum &quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Byx3v.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Byx3v.png&quot; alt=&quot;CONTCAR file for 14 Angstrom&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/ovHXs.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ovHXs.png&quot; alt=&quot;CONTCAR file for 18 Angstrom&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="8414" LastEditDate="2024-02-02T06:23:07.117" LastActivityDate="2024-02-02T06:23:07.117" Title="Equilibrating Surface Temperature Through NVT Ensemble Ab Initio Molecular Dynamics" Tags="|vasp|molecular-dynamics|condensed-matter|aimd|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12327" PostTypeId="2" ParentId="12326" CreationDate="2024-02-01T09:31:56.860" Score="2" Body="&lt;p&gt;&amp;quot;Ensemble&amp;quot; is a pretty strong word for a system with fewer atoms than the cards in a poker deck of cards. The Nose-Hoover thermostat attempts to redistribute energy between a system's degrees of freedom to achieve a thermal distribution -- but it fails for small systems with strongly harmonic modes.&lt;/p&gt;&#xA;&lt;p&gt;My intuition would say that the Nose-Hoover thermostat fails to thermalize your first system because of the vibrational mode associated with the whole system's self-interaction across the vacuum gap. That mode is clearly resonant and harmonic enough to maintain its harmonic oscillations -- whereas in the second system that mode is less resonant and is thus readily thermalized.&lt;/p&gt;&#xA;&lt;p&gt;The phenomenon is magnified in both systems by how small your unit cell is, which leaves your phonon spectrum much closer to discrete than continuous, and thus hampers thermalization.&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2024-02-01T09:31:56.860" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12328" PostTypeId="1" CreationDate="2024-02-01T09:37:04.243" Score="4" ViewCount="53" Body="&lt;p&gt;I tried to create a QSAR (Quantitative Structure Activity Relationship) model for my thesis that tries to predict the melting points of certain ZIFs (Zeolitic Imidazolate Frameworks) based on relative Zn-N bond energies obtained from DFT calculations (B3LYP/aug-cc-pVDZ) as well as Labute's Solvent Accessible Surface Area (LASA) and the stoichiometry of a mixed-linker &amp;quot;Xim-&amp;quot; for a ZIF of sum formula Zn(im)_2-x(Xim)_x.&lt;/p&gt;&#xA;&lt;p&gt;I found out that the calculated bond energies correlate more or less with Hammett-Parameters (meta-position, sigma_m)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tEDpq.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tEDpq.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and so I got to thinking: What if I had a nice json or csv table i could easily import in python or KNIME (Konstanz Data Miner), that contains a long list of Hammett-Parameters for certain substituents? That way I may not have to perform a DFT calculation for each new substituent X and instead use the Hammett-Parameters, which are already available.&lt;/p&gt;&#xA;&lt;p&gt;What I found is &lt;a href=&quot;https://pubs.acs.org/doi/pdf/10.1021/cr00002a004&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; publication, which probably has the longest list of Hammett-Parameters available. The problem: It's a PDF and I don't think that gels well with... programmatically importable data?&lt;/p&gt;&#xA;&lt;p&gt;Now I am willing to manually turn this into a csv/json of my very own, but I'd rather ask first if something like this already exists, if there's a source for such data that I do not know about, or if there is a smart way to convert this PDF into a nicer format that can easily be imported into python.&lt;/p&gt;&#xA;" OwnerUserId="7501" LastActivityDate="2024-02-01T09:37:04.243" Title="Source for Hammett Parameters useable in QSAR model training?" Tags="|density-functional-theory|databases|qsar|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12329" PostTypeId="1" CreationDate="2024-02-01T10:48:47.633" Score="2" ViewCount="20" Body="&lt;p&gt;I aim is to construct the PES for a molecule considering a specific bond length as the scan coordinate. I am using the Relaxed-Scan feature of Gaussian 16 for this using the &lt;code&gt;opt=modredundant&lt;/code&gt; keyword. Now, on successfully scanning the ground state PES, I wish to construct the same for the excited states via TDDFT. The way I use right now is very tedious ... I open the &lt;code&gt;scan.log&lt;/code&gt; which is the output of the scan job in GaussView 6, I select the &amp;quot;frame&amp;quot; of a specific structure and I set up a new Gaussian TDDFT job. And I repeat it selecting every single frame using the GUI.&lt;/p&gt;&#xA;&lt;p&gt;As you might have noticed, it is horribly inefficient as the number of structures become large. I am looking for ways to automate the &amp;quot;click the different frames and save a new job&amp;quot; part. Members of our groups tried writing scripts but it failed to include the connectivity along with the coordinates.&lt;/p&gt;&#xA;&lt;p&gt;Another solution might be to run a job that can do both&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Do the ground state relaxed scan&lt;/li&gt;&#xA;&lt;li&gt;Do a TDDFT excitation at every structure of the scan after optimization&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;in a single job. The end goal is to plot the ground and excited state PES for the given coordinate (bond length in the problems we tackle).&lt;/p&gt;&#xA;&lt;p&gt;Below is what the frame selection screen looks like in GV6&#xA;&lt;a href=&quot;https://i.stack.imgur.com/RyUT7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/RyUT7.png&quot; alt=&quot;Below is what the frame selection screen looks like in GV6&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8664" LastActivityDate="2024-02-01T10:48:47.633" Title="How to seperate structures in bulk with connectivity from a relaxed scan in Gaussian 16?" Tags="|gaussian|td-dft|potential-energy-surface|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12330" PostTypeId="1" CreationDate="2024-02-01T11:15:39.823" Score="2" ViewCount="82" Body="&lt;p&gt;I am trying to perform electron transport calculations. At the level of the scattering region calculations, I have noticed that the values of energies are no longer changing:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ts-scf:  123  -103750.909586  -103750.909586  -103750.909586  0.000000 -3.126529  0.000000  &#xA;ts-q:         D        E1        C1        E2        C2        dQ  &#xA;ts-q:   756.236   376.068     7.932   376.068     7.932 -.383E+01  &#xA;ts-Vha:  0.70752E+00 eV&#xA;..&#xA;.. &#xA;..&#xA;&#xA;ts-scf:  250  -103750.909586  -103750.909586  -103750.909586  0.000000 -3.126529  0.000000&#xA;ts-q:         D        E1        C1        E2        C2        dQ&#xA;ts-q:   756.236   376.068     7.932   376.068     7.932 -.383E+01&#xA;ts-Vha:  0.70752E+00 eV&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;as you can see, from step 123 to 250 all the values are the same and the same goes for the steps ahead. &lt;strong&gt;The values are no longer changing !!&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Does this mean that the calculations are already converged and must already stop or is it normal and I should wait?&lt;/p&gt;&#xA;&lt;p&gt;Or is there something wrong with my calculations?&lt;/p&gt;&#xA;" OwnerUserId="8130" LastActivityDate="2024-02-05T10:43:16.513" Title="Transiesta scattering calculation not converging" Tags="|siesta|electronic-transport|transiesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12331" PostTypeId="1" AcceptedAnswerId="12335" CreationDate="2024-02-01T14:59:20.337" Score="1" ViewCount="26" Body="&lt;p&gt;In the context of simulating the dissociation dynamics of an H₂O molecule on a metal surface, what algorithm is employed for generating the initial state of a tri-atomic non-linear molecule, such as H₂O, in the &lt;strong&gt;first vibrational excited state (v=1)&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="8448" LastEditorUserId="5" LastEditDate="2024-02-02T02:54:01.617" LastActivityDate="2024-02-02T02:54:01.617" Title="Algorithm for finding the v=1 state of an H2O molecule" Tags="|quantum-chemistry|molecular-modeling|quantum-mechanics|spectroscopy|vibrations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12332" PostTypeId="1" AcceptedAnswerId="12360" CreationDate="2024-02-01T17:13:00.870" Score="4" ViewCount="84" Body="&lt;p&gt;I'm using Quantum ESPRESSO in my calculations. And I'm a bit confused about the convergence for energy between two consecutive steps and the force allowed on each atom.&lt;/p&gt;&#xA;&lt;p&gt;In my input file, I retained the default values as described in the Quantum ESPRESSO input file, i.e., &lt;code&gt;etot_conv_thr=10^-4 a.u&lt;/code&gt; and &lt;code&gt;forc_conv_thr=10^-3 a.u&lt;/code&gt; (Does 'a.u' mean atomic unit?)&lt;/p&gt;&#xA;&lt;p&gt;In literature, they often express energy convergence in Ry or eV and force allowed on each atom in Ry/Å or eV/Å. Could someone assist me in converting these values, so I can verify if my results are accurate?&lt;/p&gt;&#xA;" OwnerUserId="6560" LastActivityDate="2024-02-05T16:48:55.127" Title="Confused About Convergence Values in Quantum ESPRESSO: Seeking Help with Unit Conversion" Tags="|density-functional-theory|quantum-espresso|energy-conversion|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12333" PostTypeId="2" ParentId="12332" CreationDate="2024-02-01T17:27:28.763" Score="3" Body="&lt;p&gt;The atomic unit for energy is the Hartree (&lt;span class=&quot;math-container&quot;&gt;$E_h$&lt;/span&gt;) and it is equivalent to &lt;span class=&quot;math-container&quot;&gt;$4.3597447222071(85) \times 10^{−18} J$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You can get more information about the atomic units visiting the &lt;a href=&quot;https://en.wikipedia.org/wiki/Atomic_units&quot; rel=&quot;nofollow noreferrer&quot;&gt;Wikipedia page&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;About converting, I like to use an online conversion tool named &lt;a href=&quot;http://mafalda.unige.ch/vuc/converter.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;em&gt;The Versatile Unit Converter&lt;/em&gt;&lt;/a&gt; which also has a &lt;a href=&quot;http://mafalda.unige.ch/vuc/widget.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;widget app&lt;/a&gt; for Mac OS X.&lt;/p&gt;&#xA;&lt;p&gt;The accuracy of your result should always be checked against experimental measured properties. For example, doesn't matter if you used LDA and a convergence value of &lt;span class=&quot;math-container&quot;&gt;$10^{-10}$&lt;/span&gt; and the calculated energy gap continue to be underestimated.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-01T17:27:28.763" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12334" PostTypeId="1" CreationDate="2024-02-01T18:49:46.240" Score="2" ViewCount="38" Body="&lt;p&gt;I am running into errors while submitting a job for a basic MD Simulation with HPC on SLURM. My &lt;strong&gt;sbatch&lt;/strong&gt; script reads as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#SBATCH -Jgromacs_cpu &#xA;#SBATCH -Axxxxxxxxxxxx #account name&#xA;#SBATCH -N1 --ntasks-per-node=1&#xA;#SBATCH --cpus-per-task=4 &#xA;#SBATCH --mem-per-cpu=10G &#xA;#SBATCH -t4:00:00&#xA;#SBATCH -pxxxxxxx #queue name                    &#xA;#SBATCH -oggpu.out      # output file name&#xA;#SBATCH --mail-type=BEGIN,END,FAIL              # Mail preferences&#xA;#SBATCH --mail-user=johndoe@blabla.edu        # E-mail address for notifications&#xA;&#xA;#name of the executable&#xA;exe=&amp;quot;gmx_mpi&amp;quot;&#xA;export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK&#xA;&#xA;pwd&#xA;module load gromacs&#xA;cd nvt&#xA;pwd&#xA;&#xA;srun &lt;span class=&quot;math-container&quot;&gt;$exe grompp -f inputs/nvt.mdp -c peg.gro -p topol.top -o nvt.tpr -maxwarn 1&#xA;srun -bootstrap slurm -n $&lt;/span&gt;SLURM_NTASKS $exe mdrun -s nvt.tpr&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;P.S.- I am new to GROMACS, and the last line is throwing error. In fact that is the line that my university's HPC cluster has reccomended to run MD simulations.&lt;/p&gt;&#xA;&lt;p&gt;The error thrown is as follows:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;There was 1 note&lt;/p&gt;&#xA;&lt;p&gt;There was 1 warning&lt;/p&gt;&#xA;&lt;p&gt;Back Off! I just backed up nvt.tpr to ./#nvt.tpr.29#&lt;/p&gt;&#xA;&lt;p&gt;GROMACS reminds you: &amp;quot;If humanity has fled shivering from the starry&#xA;spaces, it has become minutely at home in the interstices of the speck&#xA;that it inhabits for an instant&amp;quot; (George H. Mead)&lt;/p&gt;&#xA;&lt;p&gt;Setting the LD random seed to -419561833&lt;/p&gt;&#xA;&lt;p&gt;Generated 18 of the 28 non-bonded parameter combinations&lt;/p&gt;&#xA;&lt;p&gt;Excluding 2 bonded neighbours molecule type 'PEG'&lt;/p&gt;&#xA;&lt;p&gt;turning H bonds into constraints...&lt;/p&gt;&#xA;&lt;p&gt;Velocities were taken from a Maxwell distribution at 300 K Analysing&#xA;residue names: There are:     1      Other residues Analysing residues&#xA;not classified as Protein/DNA/RNA/Water and splitting into groups...&lt;/p&gt;&#xA;&lt;p&gt;Determining Verlet buffer for a tolerance of 0.005 kJ/mol/ps at 300 K&lt;/p&gt;&#xA;&lt;p&gt;Calculated rlist for 1x1 atom pair-list as 1.000 nm, buffer size 0.000&#xA;nm&lt;/p&gt;&#xA;&lt;p&gt;Set rlist, assuming 4x4 atom pair-list, to 1.000 nm, buffer size 0.000&#xA;nm&lt;/p&gt;&#xA;&lt;p&gt;Note that mdrun will redetermine rlist based on the actual pair-list&#xA;setup Calculating fourier grid dimensions for X Y Z Using a fourier&#xA;grid of 25x25x25, spacing 0.120 0.120 0.120&lt;/p&gt;&#xA;&lt;p&gt;Estimate for the relative computational load of the PME mesh part:&#xA;0.81&lt;/p&gt;&#xA;&lt;p&gt;This run will generate roughly 2 Mb of data Invalid time specification&#xA;(pos=0): ootstrap srun: error: Invalid --begin specification&#xA;[atl1-1-01-010-3-0.pace.gatech.edu:mpi_rank_0][MPID_Init] [Performance&#xA;Suggestion]: Application has requested for multi-thread capability. If&#xA;allocating memory from different pthreads/OpenMP threads, please&#xA;consider setting MV2_USE_ALIGNED_ALLOC=1 for improved performance. Use&#xA;MV2_USE_THREAD_WARNING=0 to suppress this error message.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Please can y'all help me with the same.&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2024-02-01T19:31:34.457" LastActivityDate="2024-02-01T19:31:34.457" Title="Error with running GROMACS with SLURM" Tags="|molecular-dynamics|molecular-modeling|high-performance-computing|gromacs|job-scheduler|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12335" PostTypeId="2" ParentId="12331" CreationDate="2024-02-01T22:09:38.017" Score="0" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;what algorithm is employed for generating the initial state of a tri-atomic non-linear molecule, such as H₂O, in the first vibrational excited state (v=1)?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;To get the v=1 state (wavefunction) of a trinuclear and non-linear molecule, you can start by building a potential energy surface for the molecule. This can be done using &lt;a href=&quot;/questions/tagged/quantum-chemistry&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;quantum-chemistry&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;quantum-chemistry&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-quantum-chemistry-tooltip-container&quot;&gt;quantum-chemistry&lt;/a&gt; &lt;a href=&quot;/questions/tagged/software&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;software&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;software&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-software-tooltip-container&quot;&gt;software&lt;/a&gt; for doing &lt;a href=&quot;/questions/tagged/electronic-structure&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;electronic-structure&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;electronic-structure&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-electronic-structure-tooltip-container&quot;&gt;electronic-structure&lt;/a&gt; calculations, for example &lt;a href=&quot;/questions/tagged/open-source&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;open-source&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;open-source&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-open-source-tooltip-container&quot;&gt;open-source&lt;/a&gt; ones include &lt;a href=&quot;/questions/tagged/open-molcas&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-open-molcas-tooltip-container&quot;&gt;open-molcas&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/pyscf&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;pyscf&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;pyscf&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-pyscf-tooltip-container&quot;&gt;pyscf&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/psi4&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;psi4&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;psi4&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-psi4-tooltip-container&quot;&gt;psi4&lt;/a&gt;, etc., and proprietary ones include &lt;a href=&quot;/questions/tagged/gaussian&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;gaussian&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;gaussian&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-gaussian-tooltip-container&quot;&gt;gaussian&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/orc&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;orc&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;orc&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-orc-tooltip-container&quot;&gt;orc&lt;/a&gt;,&lt;a href=&quot;/questions/tagged/q-chem&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;q-chem&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;q-chem&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-q-chem-tooltip-container&quot;&gt;q-chem&lt;/a&gt;,etc.&lt;/p&gt;&#xA;&lt;p&gt;Once you have a potential energy surface, you now need to solve the vibrational Schroedinger equation for the molecule. For dinuclear molecules, LEVEL (which is open-source and available on its own, and also available within &lt;a href=&quot;/questions/tagged/open-molcas&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;open-molcas&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-open-molcas-tooltip-container&quot;&gt;open-molcas&lt;/a&gt;) is the most popular, but for trianuclear molecules  you can use the &lt;a href=&quot;https://github.com/Trovemaster/TROVE&quot; rel=&quot;nofollow noreferrer&quot;&gt;TROVE software&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-01T22:09:38.017" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12336" PostTypeId="2" ParentId="12324" CreationDate="2024-02-01T23:47:14.257" Score="1" Body="&lt;p&gt;They break backwards compatibility all the time! I have run into different but equally frustrating problems before. It seems your problem may have solutions. See here: &lt;a href=&quot;https://materialsproject.github.io/pymatgen-analysis-defects/intro.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://materialsproject.github.io/pymatgen-analysis-defects/intro.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-02-01T23:47:14.257" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12337" PostTypeId="2" ParentId="12321" CreationDate="2024-02-02T00:16:47.233" Score="2" Body="&lt;p&gt;I am no expert here but, strictly speaking, I think that you can't get it from the &lt;strong&gt;DoS&lt;/strong&gt;. There are many methods for evaluating the amount of charge around an atom:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1439/what-are-the-types-of-charge-analysis&quot;&gt;What are the types of charge analysis?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/99/best-partial-atomic-charges-estimate-for-crystal-field-purposes&quot;&gt;Best partial atomic charges estimate for crystal field purposes?&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Broadly speaking, you define a sphere around the atom you want to know the oxidation state of and count the electron charge in the sphere. The difference between the electron charge and atomic number is the oxidation state I guess. Ultimately, it is an ambiguous procedure: e.g. you can change the sphere radius around your atom and get a different number. See the links above for the &amp;quot;best method&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;From the DoS, I suppose you can integrate from &lt;span class=&quot;math-container&quot;&gt;$-\infty$&lt;/span&gt; to the Fermi level, or in some other range, to find the electron charge; however, this will only tell you the electron charge per unitcell which you likely already know. The &lt;strong&gt;DoS&lt;/strong&gt; doesn't tell you how much charge is around any given atom. Rather, you have to project the DoS onto atomic orbitals (or some other basis). This usually requires integrating in a sphere centered on the atoms, much like the charge analysis above! I think, then, you can integrate the &lt;strong&gt;PDoS&lt;/strong&gt; from &lt;span class=&quot;math-container&quot;&gt;$-\infty$&lt;/span&gt; to the Fermi level and find the electron charge centered on a specific atom. Then you can use this to figure out the oxidation.&lt;/p&gt;&#xA;&lt;p&gt;I think that projecting the DoS onto atomic orbitals etc. isn't conceptually different than other population analysis. Maybe it is worth just using one of the other methods in the links above? Many of them work as post-processing steps to e.g. VASP.&lt;/p&gt;&#xA;&lt;p&gt;Hope this helps!&#xA;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-02-02T00:16:47.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12340" PostTypeId="1" AcceptedAnswerId="12345" CreationDate="2024-02-02T14:39:30.760" Score="2" ViewCount="20" Body="&lt;p&gt;This is a follow-up to my recent question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12331/5&quot;&gt;Algorithm for finding the v=1 state of an H2O molecule&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I want the geometry (atomic positions) of the &lt;strong&gt;H2O molecule in the v=1 state&lt;/strong&gt;. How are initial configurations (for AIMD simulations) generated for excited energetic states? I have some idea about how it's done for diatomic molecules (anharmonic oscillator potential can be used to find the bond distance). But what may I do for a non-linear triatomic molecule? What would be the algorithm?&lt;/p&gt;&#xA;" OwnerUserId="8448" LastEditorUserId="5" LastEditDate="2024-02-02T22:12:37.500" LastActivityDate="2024-02-02T22:12:37.500" Title="Geometry of H2O in the v=1 vibrational state for AIMD simulation" Tags="|molecular-dynamics|computational-chemistry|quantum-chemistry|molecular-modeling|aimd|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12341" PostTypeId="2" ParentId="12298" CreationDate="2024-02-02T15:21:46.643" Score="4" Body="&lt;h2&gt;tl;dr&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Well yes, but actually no.&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;— the Pirate Captain (&lt;a href=&quot;https://knowyourmeme.com/memes/well-yes-but-actually-no&quot; rel=&quot;nofollow noreferrer&quot;&gt;paraphrased&lt;/a&gt;), &lt;em&gt;The Pirates! In an Adventure with Scientists!&lt;/em&gt;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The universal 2RDM functional is known (and linear!), but 2RDMs are hard to work with&lt;/li&gt;&#xA;&lt;li&gt;The universal 1RDM functional is unknown and nonlinear. 1RDMs are hard to work with formally&lt;/li&gt;&#xA;&lt;li&gt;The universal density functional is unknown. Densities are easy to work with! But in the usual Kohn–Sham formulation (and in finite basis sets more generally), DFT is secretly done as a 1RDM functional theory anyway.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The full version will be a little long, because you've hit on the fundamental tradeoff of DFT. My apologies in advance. But the most relevant concept, in my opinion, is the &lt;a href=&quot;https://terrytao.wordpress.com/career-advice/be-sceptical-of-your-own-work/&quot; rel=&quot;nofollow noreferrer&quot;&gt;conservation of difficulty&lt;/a&gt; popularized by Terence Tao.&lt;/p&gt;&#xA;&lt;h2&gt;Two electrons&lt;/h2&gt;&#xA;&lt;p&gt;Clearly, you never need more than a 2RDM, because the electronic structure Hamiltonian only contains one- and two-body operators. Indeed, the energy is &lt;strong&gt;linear&lt;/strong&gt; in the 2RDM &lt;span class=&quot;math-container&quot;&gt;$\gamma_2$&lt;/span&gt;,&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;E = \text{Tr}\, H_2 \gamma_2 \tag{1}.&#xA;$$&lt;/span&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$H_2$&lt;/span&gt; is the two-electron reduced Hamiltonian, for which an &lt;strong&gt;explicit expression&lt;/strong&gt; is known (see, e.g., &lt;a href=&quot;https://doi.org/10.1021/cr2000493&quot; rel=&quot;nofollow noreferrer&quot;&gt;Mazziotti's review in &lt;em&gt;Chem. Rev.&lt;/em&gt;&lt;/a&gt;).&lt;/p&gt;&#xA;&lt;p&gt;The trouble with this method is it's hard to tell whether a trial 2RDM could have actually been obtained by tracing out a many-body wavefunction, without actually doing the tracing directly (in which case you might as well use a higher-order method). There has been &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRevLett.130.153001&quot; rel=&quot;nofollow noreferrer&quot;&gt;recent progress&lt;/a&gt; towards solving the so-called &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability conditions, but I believe it's still too impractical to be worth it most of the time.&lt;/p&gt;&#xA;&lt;h2&gt;One electron, two coordinates&lt;/h2&gt;&#xA;&lt;p&gt;As you mentioned, Hartree–Fock theory is a 1RDM functional theory because the electron-electron interaction is cast as a one-electron operator. You can actually derive this another way by restricting the space of allowable (&lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-body) wavefunctions to single Slater determinants: then the 2RDM is easily expressed in terms of the 1RDM as (Eq. (2.5.2) of &lt;a href=&quot;https://books.google.com/books/about/Density_Functional_Theory_of_Atoms_and_M.html?id=mGOpScSIwU4C&quot; rel=&quot;nofollow noreferrer&quot;&gt;Parr and Yang's DFT book&lt;/a&gt;).&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\gamma_2(x_1' x_2', x_1 x_2) = \frac12 \left\lvert \begin{matrix} \gamma_1(x_1', x_1) &amp;amp; \gamma_1(x_2', x_1) \\ \gamma_1(x_1', x_2) &amp;amp; \gamma_1(x_2', x_2) \end{matrix} \right\rvert. \tag{2}&#xA;$$&lt;/span&gt;&#xA;I won't write it out here, but you can derive &lt;span class=&quot;math-container&quot;&gt;$V_{ee}$&lt;/span&gt; in that space in terms of the 1RDM.&lt;/p&gt;&#xA;&lt;p&gt;Anyway, it is actually possible to express the ground-state energy as a functional of the 1RDM exactly. In fact, this is done pretty much like the classic Hohenberg–Kohn theorem for DFT: but it's more general, allowing for instance nonlocal &lt;span class=&quot;math-container&quot;&gt;$V_{\text{ext}}$&lt;/span&gt;. Gilbert &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.12.2111&quot; rel=&quot;nofollow noreferrer&quot;&gt;proved this in 1975&lt;/a&gt;; Levy &lt;a href=&quot;http://www.pnas.org/cgi/doi/10.1073/pnas.76.12.6062&quot; rel=&quot;nofollow noreferrer&quot;&gt;followed up with a constrained-search version&lt;/a&gt; four years later; and Valone &lt;a href=&quot;https://doi.org/10.1063/1.440249&quot; rel=&quot;nofollow noreferrer&quot;&gt;gave an ensemble version&lt;/a&gt; in 1980.&lt;/p&gt;&#xA;&lt;p&gt;The universal 1RDM functional is &lt;strong&gt;no longer linear&lt;/strong&gt;, and is also unknown. There's a &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/158/21/214108/2893717/Refining-and-relating-fundamentals-of-functional&quot; rel=&quot;nofollow noreferrer&quot;&gt;nice comparison&lt;/a&gt; of the three major approaches (it's even open access!), which discusses how they trade off complexity of the functional with complexity of the domain. You see, 1RDMs have to contend with both the &lt;span class=&quot;math-container&quot;&gt;$v$&lt;/span&gt;-representability that concerned early researchers in DFT and with the &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability that's so challenging for 2RDMs. (In DFT, &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;-representability is as easy as &lt;span class=&quot;math-container&quot;&gt;$\int dr\, \rho(r) = N$&lt;/span&gt;.)&lt;/p&gt;&#xA;&lt;h2&gt;One electron, one coordinate&lt;/h2&gt;&#xA;&lt;p&gt;For a local external potential, the density &lt;span class=&quot;math-container&quot;&gt;$\rho = \gamma_1(x_1, x_1)$&lt;/span&gt; &lt;a href=&quot;https://link.aps.org/doi/10.1103/PhysRev.136.B864&quot; rel=&quot;nofollow noreferrer&quot;&gt;is enough&lt;/a&gt; to determine the ground-state energy. The universal functional is still unknown (and certainly highly nonlinear). But for 'normal' (e.g., nonmagnetic) calculations, the success of DFT certainly makes it seems like the 1RDM is overkill.&lt;/p&gt;&#xA;&lt;p&gt;Ah, but DFT is usually 1RDM functional theory in disguise! For example, Kohn–Sham calculations are often solved rather like Hartree–Fock ones, with 1RDM methods; certainly hybrid DFT is a 1RDM functional theory rather than a pure functional of the density; and furthermore DFT in finite basis sets &lt;a href=&quot;https://www.sciencedirect.com/science/article/pii/S0370157319300481&quot; rel=&quot;nofollow noreferrer&quot;&gt;is really a 1RDMFT&lt;/a&gt;, more or less because the Dirac delta function can't be represented exactly in a finite-dimensional space and therefore don't have a truly local external potential.&lt;/p&gt;&#xA;&lt;h2&gt;Concluding thoughts&lt;/h2&gt;&#xA;&lt;p&gt;Your surprise is to be expected: the Hohenberg–Kohn theorem is highly nontrivial, even if its proof is easy. It's not at all intuitive that you can get a ground-state two-electron property from one-electron quantities.&lt;/p&gt;&#xA;&lt;p&gt;But there is no free lunch: we trade complexity of the electronic quantity for complexity of the energy functional.&lt;/p&gt;&#xA;" OwnerUserId="1393" LastEditorUserId="1393" LastEditDate="2024-02-03T15:51:29.967" LastActivityDate="2024-02-03T15:51:29.967" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12342" PostTypeId="2" ParentId="12299" CreationDate="2024-02-02T15:34:10.117" Score="2" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;Since S is created from orthonormal orbitals, it has 1.00 as diagonal elements.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; is created from orthonormal orbitals, the overlap matrix is simply the unit matrix, &lt;span class=&quot;math-container&quot;&gt;${\bf S}={\bf 1}$&lt;/span&gt;. When the basis functions are merely normalized, &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; has a unit diagonal, but typically also has non-zero off-diagonal elements.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Now, the question is, I have a matrix of MO coefficients, which are not orthonormal. I was trying to orthonormalize them by using Lowdin symmetric orthogonalization. Which is actually, &lt;span class=&quot;math-container&quot;&gt;$ {\bf W}′={\bf S}^{-1/2} {\bf W}$&lt;/span&gt; where, &lt;span class=&quot;math-container&quot;&gt;${\bf W}′$&lt;/span&gt; is orthonormalized orbitals and &lt;span class=&quot;math-container&quot;&gt;${\bf S}$&lt;/span&gt; is calculated as before. However, the resulting orbitals are not orthonormal.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is not surprising, since you have not orthonormalized the MO coefficients.&lt;/p&gt;&#xA;&lt;p&gt;Let's follow convention and take &lt;span class=&quot;math-container&quot;&gt;${\bf C}$&lt;/span&gt; as the matrix of orbital coefficients. The MO overlap is then given by &lt;span class=&quot;math-container&quot;&gt;${\bf S}^\text{MO} = {\bf C}^T {\bf SC}$&lt;/span&gt;. What you want to do is to make this matrix the unit matrix. This is achieved by transforming the orbital coefficients as &lt;span class=&quot;math-container&quot;&gt;${\bf C} \to {\bf C}({\bf S}^{\rm MO})^{-1/2}$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-02-02T15:34:10.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12343" PostTypeId="2" ParentId="12317" CreationDate="2024-02-02T15:58:02.183" Score="1" Body="&lt;p&gt;You can't do Hartree-Fock with densities, only. You need density matrices to evaluate exact exchange.&lt;/p&gt;&#xA;&lt;p&gt;However, you can do semilocal density functional calculations with knowledge of the electron density, only. A commonly used way to learn the electron density is through the auxiliary basis expansion: the electron density, which reads in the atomic orbital basis as &lt;span class=&quot;math-container&quot;&gt;$n({\bf r}) = \sum_{\mu \nu} P_{\mu\nu} \chi_\mu({\bf r}) \chi_\nu({\bf r})$&lt;/span&gt; is expressed in an auxiliary basis familiar from density fitting methods as &lt;span class=&quot;math-container&quot;&gt;$n({\bf r}) \approx \sum_A c_A \chi_A({\bf r})$&lt;/span&gt;. Machine learning (ML) is then done on the coefficients &lt;span class=&quot;math-container&quot;&gt;$c_A$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Knowing the ML prediction, one can compute the Fock matrix in the orbital basis following density fitting techniques. The density functional is evaluated by quadrature on a grid, and the Coulomb matrix is computed with three-center two-electron integrals as &lt;span class=&quot;math-container&quot;&gt;$J_{\mu \nu} = \sum_{A}(\mu \nu|A)c_A$&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-02-02T15:58:02.183" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12344" PostTypeId="1" CreationDate="2024-02-02T16:23:19.393" Score="2" ViewCount="88" Body="&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article-abstract/156/15/154113/2841068/An-assessment-of-density-functionals-for?redirectedFrom=fulltext&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; paper by Lee, &lt;em&gt;et al.&lt;/em&gt;, they are looking at different functionals and dispersion corrections and how they change the predicted value of CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; chemisorption on an amine-functionalized metal-organic framework. In the &lt;a href=&quot;https://pubs.aip.org/jcp/article-supplement/2841068/zip/154113_1_epaps/&quot; rel=&quot;nofollow noreferrer&quot;&gt;supplemental information&lt;/a&gt;, they give the different computed phonon frequencies for each functional and/or dispersion correction for gaseous CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;, the amine (m2m) on the MOF, and the final, chemisorbed amine with CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Table II on page 7 of the paper gives their computed ZPEs and thermal energy corrections for each method.&lt;/p&gt;&#xA;&lt;p&gt;I am trying to use the data given in the SI to confirm I get the same numbers as they do for the ZPE and TE.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Problem&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;My understanding is that the ZPE correction for this system should simply be calculated as&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta E_{ZPE} = \frac{1}{2}(\sum_i \omega_{i,m2m+CO_2} - \sum_i \omega_{i,m2m} - \sum_i \omega_{i,CO_2})$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\omega_{i,m2m+CO_2}$&lt;/span&gt; are the phonon frequencies for the m2m + CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; system [section CO2-m2m of Table SIII], &lt;span class=&quot;math-container&quot;&gt;$\omega_{i,m2m}$&lt;/span&gt; are the phonon frequencies for just m2m [section m2m of Table SIII], and &lt;span class=&quot;math-container&quot;&gt;$\omega_{i,CO_2}$&lt;/span&gt; are the gaseous phonon frequencies for CO&lt;span class=&quot;math-container&quot;&gt;$_2$&lt;/span&gt; [section CO2 of Table SII].&lt;/p&gt;&#xA;&lt;p&gt;However, when I do the arithmetic, my numbers come out wrong. They list the ZPE to be 6.6 kJ/mol, but the above math gives me 5.6 kJ/mol. This is a small difference in the scheme of things, but since I am using their exact reported numbers, I would expect to get basically the same values.&lt;/p&gt;&#xA;&lt;p&gt;Any help will be much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thank you!&lt;/p&gt;&#xA;" OwnerUserId="5981" LastActivityDate="2024-02-03T22:50:15.027" Title="Reproducing ZPE corrections to adsorption from literature" Tags="|phonons|adsorption|zero-point-energy|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12345" PostTypeId="2" ParentId="12340" CreationDate="2024-02-02T22:11:20.367" Score="1" Body="&lt;p&gt;&amp;quot;Geometry&amp;quot; is complicated in quantum mechanics, because we have probability distributions rather than precise geometrical positions as we would have in classical mechanics. If we make the Born-Oppenheimer approximation, we can remove some of that complexity and actually talk about the geometry of nuclear coordinates (separated from the quantum mechanically behaving electronic coordinates) get pictures like the one below, in which we have the square of the complex modulus of the wavefunction (which by Born's rule is the probability of finding the system at a certain location) plotted as a function of a nuclear coordinate (or geometry):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/4CJRU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/4CJRU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;We can say that the &amp;quot;geometry&amp;quot; of the &lt;span class=&quot;math-container&quot;&gt;$v=1$&lt;/span&gt; state is the geometry (or set of nuclear coordinates) at which the probability (or square of the complex modulus of the wavefunction) is greatest, so you would look for the maximum value of the purple curve corresponding to &lt;span class=&quot;math-container&quot;&gt;$v=1$&lt;/span&gt; in the above figure, for example. In the above figure, the potential energy curve/surface looks quite symmetric, as in the case of a harmonic oscillator, so it looks like we have two geometries with equally maximal probability, but the more anharmonic the potential, the less likely that that this would be the case.&lt;/p&gt;&#xA;&lt;p&gt;Therefore, to find the most-probable geometry for a &lt;span class=&quot;math-container&quot;&gt;$v=1$&lt;/span&gt; state, you can determine the wavefunctions of the system, and from them you can determine the probability functions as plotted in the above figure.&lt;/p&gt;&#xA;&lt;p&gt;To get the wavefunctions, you can use the procedure suggested in my answer to your previous question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12331/5&quot;&gt;Algorithm for finding the v=1 state of an H2O molecule&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-02T22:11:20.367" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12346" PostTypeId="1" AcceptedAnswerId="12417" CreationDate="2024-02-02T23:33:05.383" Score="3" ViewCount="117" Body="&lt;p&gt;This is just a quick question about the output tags in VASP. My output file is of the form:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;           N       E                     dE             d eps       ncg     rms          rms(c)&#xA;DAV:   1    -0.127734350174E+04   -0.64220E-03   -0.73566E-02 10044   0.270E-01    0.621E-02&#xA;RMM:   2    -0.127734356359E+04   -0.61849E-04   -0.92296E-04  9392   0.279E-02    0.399E-02&#xA;RMM:   3    -0.127734355849E+04    0.51033E-05   -0.60427E-05  8579   0.665E-03    0.161E-02&#xA;RMM:   4    -0.127734355886E+04   -0.37419E-06   -0.11561E-05  7758   0.281E-03    0.279E-03&#xA;RMM:   5    -0.127734355917E+04   -0.31447E-06   -0.73221E-07  5335   0.891E-04&#xA;  32 F= -.13021567E+04 E0= -.13021567E+04  d E =-.129375E-02&#xA; BRION: g(F)=  0.112E-02 g(S)=  0.000E+00 retain N=  3 mean eig= 1.81&#xA; eig:   4.418  0.476  0.522&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I understand that F is the total free energy and dE is the change in energy between steps, but what about the next lines (BRION, eig)? I assume this has something to do with the method prescribed by IBRION (in this case I have set IBRION = 1).&lt;/p&gt;&#xA;&lt;p&gt;I cannot seem to find information relating to the meanings of g(F), g(S), etc. I have noticed that when I set EDIFFG = 1E-3 eV the calculation only converges when both |dE| and |g(F)| are less than this value.&lt;/p&gt;&#xA;&lt;p&gt;Is there any information available relating to the meanings of these terms?&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;&lt;p&gt;Edit: Here is the INCAR file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;INCAR:&#xA; ENCUT = 400.000000&#xA; EDIFF = 1.00e-06&#xA; EDIFFG = 1.00e-03&#xA; ALGO = fast&#xA; GGA = PE&#xA; PREC = Normal&#xA; ISMEAR = 0&#xA; ISTART = 1&#xA; NELM = 120&#xA; IVDW = 12&#xA; NCORE = 4&#xA; LREAL = AUTO&#xA; IBRION = 1&#xA; NSW = 200&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8554" LastEditorUserId="8554" LastEditDate="2024-02-03T16:13:01.737" LastActivityDate="2024-02-17T03:38:47.543" Title="VASP: Meaning of Certain Output Tags" Tags="|vasp|numerical-convergence|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12347" PostTypeId="1" CreationDate="2024-02-02T23:52:14.120" Score="1" ViewCount="9" Body="&lt;p&gt;When I open my CIF file in VESTA it looks ok. When I upload it to &lt;a href=&quot;https://checkcif.iucr.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://checkcif.iucr.org/&lt;/a&gt;, the ellipsoid plot produced by PLATON does not look right. The unit cell of the supercell is not fully packed, some fragments are missing. Has anyone encountered this problem?&lt;/p&gt;&#xA;" OwnerUserId="1402" LastActivityDate="2024-02-02T23:52:14.120" Title="checkcif and PLATON ellipsoid plot: crystall structure does not look right" Tags="|visualization-software|crystallographic-information-file|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12348" PostTypeId="1" CreationDate="2024-02-03T01:30:21.717" Score="1" ViewCount="73" Body="&lt;p&gt;My molecule includes C,H,O,N,Si&lt;/p&gt;&#xA;" OwnerUserId="8764" LastEditorUserId="142" LastEditDate="2024-02-13T19:44:56.827" LastActivityDate="2024-02-13T19:44:56.827" Title="What is the best way to optimize molecules with 8000 atoms. This includes C,H,O,N,Si" Tags="|molecular-dynamics|molecular-modeling|geometry-optimization|cheminformatics|dftb+|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12349" PostTypeId="1" CreationDate="2024-02-03T06:20:56.667" Score="2" ViewCount="72" Body="&lt;p&gt;I have a problem with calculating Transition State using NEB-TS. Here is my input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# ORCA input file&#xA;# B3LYP DFT calculation with STO-3G basis set for TS optimization&#xA;&#xA;! B3LYP STO-3G NEB-TS Opt Freq&#xA;%neb&#xA;  neb_end_xyzfile &amp;quot;keto.xyz&amp;quot;&#xA;end&#xA;&#xA;* xyz 0 1&#xA;  C   -3.98603186062020      2.32749052231024     -0.00018529714901&#xA;  C   -2.78133170737179      1.56087181204556      0.00006187469523&#xA;  C   -1.53485769090100      2.27995228482030      0.00018458109487&#xA;  N   -1.60753127148660      3.63045101826785      0.00011349676981&#xA;  H   -0.57051491484871      1.73754058431409      0.00035037612748&#xA;  O   -3.99798358256491      3.66225005153691     -0.00026622982282&#xA;  H   -4.96606106167314      1.80310951487210     -0.00027978853931&#xA;  F   -2.80280838134731      0.17962388908159      0.00015455910114&#xA;  H   -0.68689499634773      4.13790319298241      0.00012799308035&#xA;  H   -2.83390453283858      3.91683712976893     -0.00026156535776&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the xyz files for both the reactant and product is already optimized, but when i run the code, it shows this error:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;[file orca_main/mainelprop.cpp, line 76]: Error: Cannot open GBW file: TS.gbw&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When i search for the gbw, it was there, named:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TS_im0.gbw&#xA;TS_im1.gbw&#xA;TS_im2.gbw&#xA;TS_im3.gbw&#xA;TS_im4.gbw&#xA;TS_im5.gbw&#xA;TS_im6.gbw&#xA;TS_im7.gbw&#xA;TS_im8.gbw&#xA;TS_im9.gbw&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But it has that error message, what can i do?&lt;/p&gt;&#xA;" OwnerUserId="8765" LastEditorUserId="1380" LastEditDate="2024-02-03T10:35:44.127" LastActivityDate="2024-02-03T10:35:44.127" Title="Error: Cannot open GBW file: TS.gbw" Tags="|orca|transition-state|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12350" PostTypeId="1" AcceptedAnswerId="12364" CreationDate="2024-02-03T09:09:12.307" Score="2" ViewCount="86" Body="&lt;p&gt;These are the errors when I run my supercell on material studio using CASTEP module.&#xA;I have tried decreasing k points and also increased the cutoff energy. Furthermore I deleted all the files related to my material. But every time I am facing the same issue.&#xA;I am using hybrid functional with norm conserving pseudopotential.&#xA;How can I fix it??&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VAY7S.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VAY7S.jpg&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7983" LastEditorUserId="142" LastEditDate="2024-02-06T15:25:13.660" LastActivityDate="2024-02-06T15:25:13.660" Title="Errors in CASTEP supercell geometry optimization" Tags="|density-functional-theory|supercell|castep|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12351" PostTypeId="1" CreationDate="2024-02-03T15:00:10.643" Score="2" ViewCount="50" Body="&lt;p&gt;Suppose I designed a novel coarse-grained model of polymer chains.&lt;/p&gt;&#xA;&lt;p&gt;How can I test the validity of my novel model?&lt;/p&gt;&#xA;&lt;p&gt;Is there any applied framework available?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2024-02-03T21:48:13.897" LastActivityDate="2024-02-03T21:48:13.897" Title="How do I validate and benchmark a new protein or polymer model?" Tags="|proteins|polymers|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12353" PostTypeId="2" ParentId="12348" CreationDate="2024-02-03T18:05:55.090" Score="3" Body="&lt;p&gt;First, &amp;quot;best&amp;quot; is ill-defined. The best method would be full configuration interaction at the complete basis set limit including fully relativistic and quantum field theoretical corrections; however, such calculations are prohibitively expensive even for small molecule.&lt;/p&gt;&#xA;&lt;p&gt;For systems of your size, geometry optimization doesn't even really make sense. A molecule of 8000 atoms likely has many floppy modes, meaning that it has a huge number of conformations accessible at room temperature. Reliable simulation of such molecules requires statistical sampling through molecular dynamics or Monte Carlo simulations.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-02-03T18:05:55.090" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12354" PostTypeId="2" ParentId="12344" CreationDate="2024-02-03T22:50:15.027" Score="1" Body="&lt;p&gt;There are 6 CO2 in the unit cell, so to calculate the binding energy and also the zero point energy per CO2, you have you do 6*E_b = E_{MOF-CO2} - (E_{MOF} + 6 * E_{CO2}). I think equation 3 is just a typo. Applying this to the ZPE might fix the discrepancy that you see.&lt;/p&gt;&#xA;" OwnerUserId="5770" LastActivityDate="2024-02-03T22:50:15.027" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12355" PostTypeId="1" CreationDate="2024-02-03T23:00:12.617" Score="3" ViewCount="49" Body="&lt;p&gt;I am trying to compare the Gibbs free energy of reactions such as:&lt;/p&gt;&#xA;&lt;p&gt;A + 4K(+) --&amp;gt; B(4+)&lt;/p&gt;&#xA;&lt;p&gt;A + 4Na(+) --&amp;gt; C(4+)&lt;/p&gt;&#xA;&lt;p&gt;A + 4Li(+) --&amp;gt; D(4+)&lt;/p&gt;&#xA;&lt;p&gt;A + 4Ca(2+) --&amp;gt; E(8+)&lt;/p&gt;&#xA;&lt;p&gt;A + 4Mg(2+) --&amp;gt; F(8+)&lt;/p&gt;&#xA;&lt;p&gt;In these reactions, compound A makes complexes with four cations.&lt;/p&gt;&#xA;&lt;p&gt;The calculations are run using GFN2-xTB via ORCA.&lt;/p&gt;&#xA;&lt;p&gt;Since calculation of  thermal corrections via vibrational calculations on atoms is not possible, how do I obtain the Gibbs free energy of the cations?&lt;/p&gt;&#xA;&lt;p&gt;The solvent is acetonitrile.&lt;/p&gt;&#xA;&lt;p&gt;Is it correct that the enthalpic correction could be obtained with 5/2RT and the entropic correction via the Sackur-Tetrode equation? If so, how do I calculate the latter?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="7267" LastEditorUserId="7267" LastEditDate="2024-02-18T16:05:21.107" LastActivityDate="2024-02-18T16:05:21.107" Title="How to calculate Gibbs free energy of a reaction involving cations using GFN2-xTB (via ORCA)" Tags="|orca|free-energy|xtb|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12356" PostTypeId="1" CreationDate="2024-02-03T23:05:52.597" Score="4" ViewCount="51" Body="&lt;p&gt;I'm trying to compute the IRC for a W complex, and I'm using Def2TZVP for W and 6-311G** for the rest of the atoms. However, when I include the mixed basis set, Gaussian 16 generates a syntax error.&lt;/p&gt;&#xA;&lt;p&gt;I tried quite a few different ways, but none of them worked.&#xA;I used M062X/gen pseudo=read then include the basis sets at the end of the input file (picture attached)&lt;a href=&quot;https://i.stack.imgur.com/xCiQp.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xCiQp.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Then I used this method (picture attached)&lt;a href=&quot;https://i.stack.imgur.com/fIqyT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fIqyT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;However, none of them worked.&lt;/p&gt;&#xA;&lt;p&gt;Any suggestions would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Here is the output error.&lt;/p&gt;&#xA;&lt;p&gt;&amp;quot;IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC-IRC&#xA;Reading IRC summary table definitions from the input file.&#xA;DfStat: QParse returned with an error. IStat= -1&#xA;QPErr --- A syntax error was detected in the input line.&lt;/p&gt;&#xA;&lt;p&gt;Last state= &amp;quot;&amp;quot;&#xA;TCursr= 122 LCursr= 0&#xA;Parse error in Link 123.&amp;quot;&lt;/p&gt;&#xA;" OwnerUserId="8769" LastEditorUserId="1380" LastEditDate="2024-02-11T22:19:51.997" LastActivityDate="2024-02-11T22:19:51.997" Title="Struggling with Mixed Basis Set Inclusion for IRC Calculations" Tags="|density-functional-theory|gaussian|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="12357" PostTypeId="1" CreationDate="2024-02-04T01:45:16.973" Score="4" ViewCount="59" Body="&lt;p&gt;In certain charge densities I am getting negative values, in the place where the atomic cores would be. I do not have access to the vasp.xml or OUTCAR files, so there is no way to determine whether the ECD actually did converge. &lt;strong&gt;Are the negative charges just an artefact of DFT computations?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I speculate that the DFT simulation might have hit the maximum number of iterations and exited with the resultant Electron Charge Density. If the previous speculation is true, then the CHGCAR is generated from an un-converged VASP simulation.&lt;/p&gt;&#xA;&lt;p&gt;P.S.- The DFT simulations were performed in VASP with the optb88vdw functional&lt;/p&gt;&#xA;" OwnerUserId="3566" LastEditorUserId="5" LastEditDate="2024-02-04T19:14:57.453" LastActivityDate="2024-02-05T02:24:15.390" Title="Can the Electron Charge Density (ECD) have negative values and why?" Tags="|density-functional-theory|vasp|charge-density|conceptual-dft|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12358" PostTypeId="1" CreationDate="2024-02-04T03:45:45.540" Score="1" ViewCount="82" Body="&lt;p&gt;I started optimising a system containing amino acid residue, water molecule and a toxic metal ion, in proving a supposed reaction steps that might take place in inhibiting enzyme activity. The suggestion is the toxic metal ion potentially hinder the interactions of ASP and water molecule by interacting with ASP. So considering an input file for the reactants containing around 15 atoms  (input coordinates are given below) I started optimising the input using DFT (B3LYP) LANL2DZ basis set. The calculation started but at one point I cannot see any progress in the calculations and now it is almost around for 2 days. Gaussian does not show any error also.What can be the reason?&#xA;&lt;em&gt;&lt;strong&gt;I have attached the input and last few lines of the output file of another system in which the same issue in processing was observed. The new system is the optimization of aspartic acid with a water molecule&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**%nprocshared=4&#xA;%mem=1GB&#xA;%chk=C:\Users\Chemistry\Desktop\asp_opt[i].chk&#xA;# opt b3lyp/cc-pvtz geom=connectivity&#xA;&#xA;asp&#xA;&#xA;-1 1&#xA; C                  1.19957000   -0.49798300    0.13741800&#xA; C                  0.55937200    0.74926400   -0.44764700&#xA; H                  0.44339200    0.59076300   -1.51903000&#xA; N                  1.55336100    1.83916500   -0.25779900&#xA; H                  1.10438900    2.71239400   -0.51456000&#xA; H                  1.73266800    1.90850600    0.74017500&#xA; C                 -0.80611000    1.00817800    0.18465200&#xA; H                 -1.23792900    1.92271700   -0.23130400&#xA; H                 -0.67292000    1.17051900    1.25931800&#xA; O                  1.45896000   -0.63706000    1.31192900&#xA; O                  1.65241300   -1.36767700   -0.79729900&#xA; H                  2.01459900   -2.11079700   -0.29521300&#xA; O                 -1.24221200   -1.29130000   -0.17155100&#xA; C                 -1.80218000   -0.17703500   -0.00346500&#xA; O                 -3.01436500    0.10068700    0.04935500&#xA; O                 -0.08458867   -1.88429493    1.50213956&#xA; H                  0.67747839   -1.30667491    1.58704485&#xA; H                 -0.52974695   -1.70729416    0.67021118&#xA;&#xA; 1 2 1.0 10 2.0 11 1.0&#xA; 2 3 1.0 4 1.0 7 1.0&#xA; 3&#xA; 4 5 1.0 6 1.0&#xA; 5&#xA; 6&#xA; 7 8 1.0 9 1.0 14 1.0&#xA; 8&#xA; 9&#xA; 10&#xA; 11 12 1.0&#xA; 12&#xA; 13 14 1.0&#xA; 14 15 2.0&#xA; 15&#xA; 16 17 1.0 18 1.0&#xA; 17&#xA; 18**&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;**(A) (A) (A) (A) (A) (A) (A) (A) (A) (A) (A) (A)&#xA; Requested convergence on RMS density matrix=1.00D-08 within 128 cycles.&#xA; Requested convergence on MAX density matrix=1.00D-06.&#xA; Requested convergence on             energy=1.00D-06.&#xA; No special actions if energy rises.&#xA; SCF Done:  E(RB3LYP) =  -588.437660556     A.U. after    9 cycles&#xA;             Convg  =    0.6247D-08             -V/T =  2.0058&#xA; Calling FoFJK, ICntrl=      2127 FMM=F ISym2X=0 I1Cent= 0 IOpClX= 0 NMat=1 NMatS=1 NMatT=0.&#xA; ***** Axes restored to original set *****&#xA; -------------------------------------------------------------------&#xA; Center     Atomic                   Forces (Hartrees/Bohr)&#xA; Number     Number              X              Y              Z&#xA; -------------------------------------------------------------------&#xA;      1        6          -0.003297899    0.000968992   -0.001205417&#xA;      2        6           0.001174672    0.000030078   -0.002058134&#xA;      3        1           0.000120836   -0.000724917    0.000428308&#xA;      4        7           0.000179028   -0.000406405    0.000490257&#xA;      5        1          -0.000094934    0.000238362   -0.000114970&#xA;      6        1           0.000060431   -0.000078420    0.000048740&#xA;      7        6          -0.002031199    0.003200366    0.004191686&#xA;      8        1           0.000368507   -0.000184638    0.000325103&#xA;      9        1           0.000963855   -0.000094190    0.000676509&#xA;     10        8           0.005990754    0.007413835   -0.001731561&#xA;     11        8           0.000065729   -0.002001216   -0.001545829&#xA;     12        1           0.000236666    0.000364910    0.000031038&#xA;     13        8           0.000381196    0.004747433    0.001670893&#xA;     14        6           0.003841548   -0.002121460   -0.011415519&#xA;     15        8          -0.001868448   -0.000631479    0.002953022&#xA;     16        8          -0.005940381    0.005686767   -0.013553137&#xA;     17        1           0.012654684   -0.001668370    0.014136764&#xA;     18        1          -0.012805045   -0.014739648    0.006672248&#xA; -------------------------------------------------------------------&#xA; Cartesian Forces:  Max     0.014739648 RMS     0.005058324**&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="6239" LastEditDate="2024-03-06T07:13:31.220" LastActivityDate="2024-03-06T10:58:49.987" Title="Why is this geometry optimization in Gaussian not working for a system containing an amino acid, a water molecule and a metal (Pb) ion?" Tags="|gaussian|geometry-optimization|proteins|biomaterials|structural-biology|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12359" PostTypeId="1" CreationDate="2024-02-04T10:23:13.590" Score="3" ViewCount="96" Body="&lt;p&gt;I do TD-DFT studies in Orca 5.0.3 on porphyrin system and hence at the very beginning I need to pick functional that reproduce excitation energies.&lt;/p&gt;&#xA;&lt;p&gt;The experimental reported values equal: 691, 656, 430 and 351 nm. I tried insofar two approaches: B3LYP/def2TZVP//B3LYP/def2SVP  and  B3LYP/def2TZVP, both without TDA.&lt;/p&gt;&#xA;&lt;p&gt;Unfortunatelly, the &amp;quot;SPIN ORBIT CORRECTED ABSORPTION SPECTRUM VIA TRANSITION ELECTRIC DIPOLE MOMENTS&amp;quot; are entirely different.&lt;/p&gt;&#xA;&lt;p&gt;For the former:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xgbJT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xgbJT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;and for the latter&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/NUMkI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/NUMkI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The input I use is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;! B3LYP DEF2-TZVP CPCM(CH2CL2) RI-SOMF(1X)&#xA;! MOREAD &#xA;%TDDFT&#xA;    NROOTS 4&#xA;    DOSOC TRUE&#xA;    TDA FALSE&#xA;    DONTO TRUE&#xA;END&#xA;%MOINP &amp;quot;10-iso.old.gbw&amp;quot; &#xA;%MAXCORE 6000 &#xA;%PAL NPROCS 24 END&#xA;xyzfile 0 1 10-iso.xyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The system has no metal present.&lt;/p&gt;&#xA;" OwnerUserId="8524" LastActivityDate="2024-03-02T17:02:17.950" Title="Cannot reproduce excitation energies in Orca" Tags="|computational-chemistry|molecular-modeling|orca|td-dft|excited-states|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12360" PostTypeId="2" ParentId="12332" CreationDate="2024-02-04T14:11:16.517" Score="2" Body="&lt;p&gt;As correctly stated by @Camps,&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;[t]he atomic unit for energy is the Hartree (&lt;span class=&quot;math-container&quot;&gt;$E_h$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The linked Wikipedia page in his answer explains what natural constants are assumed to be unity in order to get the stated definition.&lt;/p&gt;&#xA;&lt;p&gt;However, the &lt;a href=&quot;https://www.quantum-espresso.org/faq/faq-self-consistency/#6&quot; rel=&quot;nofollow noreferrer&quot;&gt;FAQ&lt;/a&gt; of Quantum Espresso states that&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;[u]nless otherwise specified, all PWscf input and output quantities are in atomic “Rydberg” units, i.e. energies in Ry, lengths in Bohr radii.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Therefore it seems that the unit of &lt;code&gt;etot_conv_thr&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Ry}$&lt;/span&gt; which differs by a factor of 2 from the Hartree and the unit of &lt;code&gt;forc_conv_thr&lt;/code&gt; is &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Ry/}a_0$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Ry/}Å$&lt;/span&gt; as stated in the question. Keep in mind that in the FAQ, it is also stated that for the sub-package &lt;code&gt;cp.x&lt;/code&gt; the Hartree is used:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Note that CP uses instead atomic “Hartree” units: energies are in Ha, not in Ry.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;As far as I know, VASP as another example uses &lt;span class=&quot;math-container&quot;&gt;$\mathrm{eV}$&lt;/span&gt; on some of its outputs. It therefore seems to be a good idea to check the unit convention for any (DFT) code that is being used in an investigation.&lt;/p&gt;&#xA;" OwnerUserId="8328" LastEditorUserId="8328" LastEditDate="2024-02-05T16:48:55.127" LastActivityDate="2024-02-05T16:48:55.127" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12361" PostTypeId="2" ParentId="12357" CreationDate="2024-02-05T02:24:15.390" Score="5" Body="&lt;p&gt;Yes, it is possible to get regions of negative electronic charge density when using PAW or USP pseudopotentials. The reason is that these pseudopotentials take the &amp;quot;soft&amp;quot; charge density (the density calculated from the Kohn-Sham wavefunctions) and add an additional &amp;quot;correction&amp;quot; to the charge density, usually referred to as &amp;quot;augmentation&amp;quot;. In much of the literature this &amp;quot;augmentation&amp;quot; is described as adding charge, and it usually does in total, but it can also lower the charge density in some regions. If the soft charge density in a given region is lower than the amount that the augmentation removes, then the result is a negative charge density.&lt;/p&gt;&#xA;&lt;p&gt;This issue can arise for several reasons, but one common cause is Fourier aliasing, which happens when the augmentation grid is not fine enough to represent the augmentation charge density accurately. I recommend increasing the number of points in the augmented density grid - keeping the plane-wave cut-off energy the same - and see whether that helps.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2024-02-05T02:24:15.390" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12362" PostTypeId="1" AcceptedAnswerId="12385" CreationDate="2024-02-05T08:11:40.397" Score="3" ViewCount="84" Body="&lt;p&gt;How to make Deuterium POTCAR file? i have Hydrogen POTCAR file.&lt;/p&gt;&#xA;" OwnerUserId="8414" LastActivityDate="2024-02-15T01:15:04.227" Title="Making Deuterium POTCAR file for optimization in VASP software" Tags="|vasp|molecular-modeling|geometry-optimization|atomic-simulation-environment|vaspkit|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12363" PostTypeId="2" ParentId="12330" CreationDate="2024-02-05T10:43:16.513" Score="3" Body="&lt;p&gt;In SIESTA the only conditions for convergence are that the Hamiltonian and the Density matrix are self-consistent. I.e. dDMax and dHMax are below some threshold. These are printed as the 5th and 7th column of the &lt;code&gt;ts-scf&lt;/code&gt; line. So that condition is completely fulfilled, as they are both &lt;code&gt;0.000000&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, TranSIESTA has an extra requirement. &lt;code&gt;dQ&lt;/code&gt; must be below some threshold. &lt;code&gt;dQ&lt;/code&gt; is the extra charge in your system, and it should be 0 or very close to it. In your case you have -3.8 electrons less than what you should have, and since that is not acceptable the SCF cycle will never end. Since the Hamiltonian and Density Matrix are already converged, &lt;code&gt;dQ&lt;/code&gt; will not change anymore.&lt;/p&gt;&#xA;&lt;p&gt;Assuming your electrode is a metal, the typical reason for having extra charge in transiesta is that there is not a long enough section of electrode material between the electrode and the scattering region. This makes it impossible for the charge differences to be screened before reaching the electrode, which should have exactly the bulk electronic density. &lt;strong&gt;Try to add more layers of electrode material and see if it solves your issue.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2024-02-05T10:43:16.513" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12364" PostTypeId="2" ParentId="12350" CreationDate="2024-02-05T12:30:41.913" Score="4" Body="&lt;p&gt;The error message says that the computer did not have enough memory to perform the calculation (line 2 of the log you photographed). You don't give any details about your calculation, but in general the memory required for a CASTEP calculation (or any plane-wave DFT calculation) is proportional to the:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;number of plane-waves (&lt;span class=&quot;math-container&quot;&gt;$\propto {E_\mathrm{cut}}^{\frac{3}{2}}\Omega$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$E_\mathrm{cut}$&lt;/span&gt; is the plane-wave cut-off energy and &lt;span class=&quot;math-container&quot;&gt;$\Omega$&lt;/span&gt; is the volume of the simulation cell)&lt;/li&gt;&#xA;&lt;li&gt;number of atoms (which affects the number of bands and also the number of pseudopotential projectors)&lt;/li&gt;&#xA;&lt;li&gt;number of k-points (symmetry-reduced)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Reducing any of these will reduce the memory requirements, though of course you need to be satisfied that your calculation is scientifically reasonable. Certain kinds of calculation also require more RAM, for example non-local exchange-correlation functionals need significantly more RAM than semi-local functionals.&lt;/p&gt;&#xA;&lt;p&gt;CASTEP tries to estimate the RAM it requires at the start of a calculation, and writes it to the output file. It's not 100% accurate, but the data estimates shouldn't be too far out. Here's an example from a small calculation:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;+---------------- MEMORY AND SCRATCH DISK ESTIMATES PER PROCESS --------------+&#xA;|                                                     Memory          Disk    |&#xA;| Baseline code, static data and system overhead      507.0 MB         0.0 MB |&#xA;| BLAS internal memory storage                          0.0 MB         0.0 MB |&#xA;| Model and support data                               88.1 MB         0.0 MB |&#xA;| Electronic energy minimisation requirements          37.7 MB         0.0 MB |&#xA;| Force calculation requirements                        2.9 MB         0.0 MB |&#xA;|                                               ----------------------------- |&#xA;| Approx. total storage required per process          632.8 MB         0.0 MB |&#xA;|                                                                             |&#xA;| Requirements will fluctuate during execution and may exceed these estimates |&#xA;+-----------------------------------------------------------------------------+&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(NB there's a slightly weird issue with some Linux builds where the baseline code appears to take many gigabytes, but the other estimated components should be good.)&lt;/p&gt;&#xA;&lt;p&gt;I recommend you take a look at your &lt;code&gt;.castep&lt;/code&gt; output file from the server, and see what CASTEP's memory estimate is for your calculation. If you don't &lt;em&gt;have&lt;/em&gt; a &lt;code&gt;.castep&lt;/code&gt; file then that usually means the RAM requirements are so large that CASTEP couldn't even get to the point where it computes the estimate!&lt;/p&gt;&#xA;&lt;h3&gt;Using disk space instead of RAM&lt;/h3&gt;&#xA;&lt;p&gt;You can ask CASTEP to conserve as much RAM as possible by moving the optimisation strategy from &amp;quot;speed&amp;quot; to &amp;quot;memory&amp;quot;; in your &lt;code&gt;param&lt;/code&gt; file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;opt_strategy : memory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or, equivalently,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;opt_strategy_bias : -3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I can't remember how you do this from the Materials Studio GUI but it's in the options somewhere. This will cause CASTEP not to keep some auxiliary data in RAM, in which case it will either recalculate it whenever it's needed, or save it to disk and read it back in when needed. (Note that CASTEP will not run as quickly if you do this.)&lt;/p&gt;&#xA;&lt;p&gt;CASTEP can also page wavefunctions to disk, so that the data for only one k-point is stored in RAM at any one time. In the &lt;code&gt;param&lt;/code&gt; file you can set &lt;code&gt;page_wvfns&lt;/code&gt; to a negative number to mean &amp;quot;always page&amp;quot;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;page_wvfns : -1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Parallel calculations&lt;/h3&gt;&#xA;&lt;p&gt;If you're running the calculation MPI-parallel, switching to OpenMP threading instead should also lower the RAM requirements; e.g. instead of&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mpirun -np 2 castep.mpi myinput&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;(where &amp;quot;myinput&amp;quot; is the filename prefix you're using) you would set the environment variable &lt;code&gt;CASTEP_NUM_THREADS&lt;/code&gt; to 2 and then run either the serial version of CASTEP or the MPI version but with only one process. For example, in a &lt;code&gt;bash&lt;/code&gt; environment you would do&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export CASTEP_NUM_THREADS=2&#xA;mpirun -np 1 castep.mpi myinput&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;h3&gt;Summary&lt;/h3&gt;&#xA;&lt;p&gt;The computer you're running on doesn't have enough RAM to perform that simulation. You could reduce the RAM required by carefully lowering the simulation accuracy, but there are limits to what you can do without compromising your scientific aims. You can ask CASTEP to save RAM where possible (though the simulations will take more time). Finally, it may be that your calculation is simply too large for that computer, and you need to find a machine with more RAM.&lt;/p&gt;&#xA;" OwnerUserId="403" LastActivityDate="2024-02-05T12:30:41.913" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12365" PostTypeId="1" CreationDate="2024-02-05T14:44:59.537" Score="5" ViewCount="170" Body="&lt;p&gt;I am in process of learning some simulation codes. There some properties for a material which are input parameters. I want to know if DFT or other related codes can be used to calculate them for any material other than literature data. If there are then I would like to try if they can be done with available resources on my end, so suggestions regarding requirement of computational resources would be highly appreciated. &lt;br&gt;&#xA;The properties are as follows &lt;br&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Electron affinity (eV) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Dielectric permittivity &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Density of states at CB (cm−3) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Density of states at VB (cm−3) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Electron and Hole thermal velocity &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Electron mobility (cm2V−1s−1) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Hole mobility (cm2V−1s−1) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Donor Doping Density (cm−3) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Acceptor Doping Density (cm−3) &lt;br&gt;&lt;/li&gt;&#xA;&lt;li&gt;Defect Density (cm−3) &lt;br&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2024-02-18T02:56:12.633" LastActivityDate="2024-02-18T02:56:12.633" Title="Calculation of material properties" Tags="|density-functional-theory|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12366" PostTypeId="2" ParentId="12365" CreationDate="2024-02-05T16:50:52.923" Score="3" Body="&lt;h2&gt;SIESTA&lt;/h2&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;SIESTA is both a method and its computer program implementation, to perform efficient electronic structure calculations and ab initio molecular dynamics simulations of molecules and solids. SIESTA's efficiency stems from the use of a basis set of strictly-localized atomic orbitals. A very important feature of the code is that its accuracy and cost can be tuned in a wide range, from quick exploratory calculations to highly accurate simulations matching the quality of other approaches, such as plane-wave methods.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;SIESTA is an efficient code that easy work on a laptop (ex. I already calculated the electronic properties of &lt;span class=&quot;math-container&quot;&gt;$Au_xAg_{1-x}$&lt;/span&gt; mix with my 12 cores/16GB RAM notebook that fails in a 20 cores/64GB RAM workstation using Quantum Espresso).&lt;/p&gt;&#xA;&lt;p&gt;From your list, you can calculate the following properties:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Electron affinity (eV)&lt;/li&gt;&#xA;&lt;li&gt;Dielectric permittivity&lt;/li&gt;&#xA;&lt;li&gt;Density of states at CB (cm−3)&lt;/li&gt;&#xA;&lt;li&gt;Density of states at VB (cm−3)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;SIESTA project page: &lt;a href=&quot;https://siesta-project.org/siesta/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://siesta-project.org/siesta/&lt;/a&gt;.&lt;br /&gt;&#xA;Freely available to download from GitLab: &lt;a href=&quot;https://gitlab.com/siesta-project/siesta&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gitlab.com/siesta-project/siesta&lt;/a&gt;.&lt;br /&gt;&#xA;A free Graphical User Interface, GUI4dft: &lt;a href=&quot;https://github.com/sozykinsa/GUI4dft&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/sozykinsa/GUI4dft&lt;/a&gt;.&lt;br /&gt;&#xA;A pay GUI, ASAP: &lt;a href=&quot;https://www.simuneatomistics.com/asap/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.simuneatomistics.com/asap/&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The last three properties:&#xA;8. Donor Doping Density (cm−3)&#xA;9. Acceptor Doping Density (cm−3)&#xA;10. Defect Density (cm−3)&lt;/p&gt;&#xA;&lt;p&gt;They are experimentally defined during the growth process. One way used to simulate doping/defect is to create supercells with a &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S0364591613000540?via%3Dihub&quot; rel=&quot;nofollow noreferrer&quot;&gt;Special Quasirandom Structures&lt;/a&gt; generators like the one included in &lt;a href=&quot;https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ATAT&lt;/a&gt; package.&lt;/p&gt;&#xA;&lt;p&gt;Finally, the other properties:&lt;br /&gt;&#xA;5. Electron and Hole thermal velocity&lt;br /&gt;&#xA;6. Electron mobility (cm2V−1s−1)&lt;br /&gt;&#xA;7. Hole mobility (cm2V−1s−1)&lt;/p&gt;&#xA;&lt;p&gt;are not primarily determine from DFT (til my knowledge), instead, you use DFT to calculate some other properties like effective mass, gap, Fermi energy, and use them in the final calculations.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2024-02-05T17:04:46.763" LastActivityDate="2024-02-05T17:04:46.763" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12367" PostTypeId="1" CreationDate="2024-02-05T17:31:04.373" Score="8" ViewCount="140" Body="&lt;p&gt;I wonder if there is a tool to generate geometries (structures) corresponding to linear interpolation between two structures in internal coordinates, with the two structures being specified in Cartesian coordinates? Thanks!&lt;/p&gt;&#xA;&lt;p&gt;Kind regards,&#xA;Evgeniy&lt;/p&gt;&#xA;" OwnerUserId="6296" LastEditorUserId="5" LastEditDate="2024-02-08T13:31:10.970" LastActivityDate="2024-02-16T13:55:55.343" Title="Linear interpolation between two molecular structures in internal coordinates" Tags="|structure|" AnswerCount="2" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12368" PostTypeId="1" CreationDate="2024-02-06T10:48:22.283" Score="6" ViewCount="55" Body="&lt;p&gt;We have a porphyrin-like molecule with a transition metal atom in the center, like the one shown in the figure.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/seHsf.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/seHsf.png&quot; alt=&quot;porphyrin complex with metal&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Consider first the porphyrin without the metal. In such a case, several orbitals around the Fermi level are purely &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;-states, so that the porphyrin can be very accurately described by constructing the effective Hamiltonian in the subspace of &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}_\pi= \sum_i t_{i,j} \hat{c}^\dagger_i\hat{c}_j \tag{1}\label{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where the indices &lt;span class=&quot;math-container&quot;&gt;$i,j$&lt;/span&gt; run over sites of the lattice defining the molecule (I omit the explicit spin indices here for simplicity of notation, you can imagine they are absorbed in the indices &lt;span class=&quot;math-container&quot;&gt;$i,j$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;If one does this, the spectrum that results from diagonalizing &lt;span class=&quot;math-container&quot;&gt;$H_\pi$&lt;/span&gt; coincides around Fermi level with the spectrum of the full Hamiltonian, and so do the corresponding eigenstates.&lt;/p&gt;&#xA;&lt;p&gt;I would like to do something similar when the porphyrin has the metal atom added. Here the idea is to describe the molecule by an effective Hamiltonian that includes only the &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals of the organic ring and the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals of the metal. Something like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}_{\pi-d}= \sum_i t_{i,j} \hat{c}^\dagger_i\hat{c}_j + \sum_{i,n} V_{i,n} \hat{c}^\dagger_i\hat{d}_n + \sum_{n} \varepsilon_{n} \hat{d}^\dagger_n\hat{d}_n \tag{2}\label{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;If we do this the resulting spectrum is a disaster, it does not match in any region the spectrum of the overall hamiltonian. I have tried this from DFT Hamiltonians with minimal basis of atomic orbitals (using the Löwdin orthonormal basis) and from the Tight-binding Slater-Koster Hamiltonians. In summary, just the sub_&lt;span class=&quot;math-container&quot;&gt;$\pi-d$&lt;/span&gt; hamiltonian cannot describe the molecule, but I am thinking if such a Hamiltonian could be made to match the full one just by adding a on-site term in the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; shell that would reproduce the crystal-field splitting of the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals in the original hamiltonian; that is, if for some &lt;span class=&quot;math-container&quot;&gt;$e_1,e_2,e_3,e_4,e_5$&lt;/span&gt; it happens that&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\hat{H}_{\pi-d} +  \sum_{n} e_{n} \hat{d}^\dagger_n\hat{d}_n \tag{3}\label{3}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;indeed reproduces the spectrum and eigenvectors around Fermi level.&lt;/p&gt;&#xA;&lt;p&gt;If this was possible, it would be very interesting to develop simple modelistic many-body approaches to such system, where one would pick just a few &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; orbitals to describe the organic ring (like in a CAS calculation) and add something like a Kanamori Hamiltonian to the &lt;span class=&quot;math-container&quot;&gt;$d-$&lt;/span&gt;shell. In such simple models it would be easy to keep track of the observables in the metal atom, like total spin or charge, unlike in ab initio CAS where the active space orbitals might have a lot of hybridization between the &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt; orbitals.&lt;/p&gt;&#xA;&lt;p&gt;How to find such coefficients &lt;span class=&quot;math-container&quot;&gt;$e_1,e_2,e_3,e_4,e_5$&lt;/span&gt; in the most effective way? For now I was trying pure brute force for a simple system, but probably there is some way using the symmetries of the system and a calculation of the crystal-field splitting or local Density of States to fit these parameters.&lt;/p&gt;&#xA;" OwnerUserId="8671" LastEditorUserId="7" LastEditDate="2024-02-06T13:33:22.263" LastActivityDate="2024-02-06T13:33:22.263" Title="Modelling a porphyrin with a metal with just the p_z and d orbitals" Tags="|condensed-matter|model-hamiltonians|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12369" PostTypeId="1" AcceptedAnswerId="12389" CreationDate="2024-02-06T15:03:51.383" Score="5" ViewCount="187" Body="&lt;p&gt;I have ORCA 5.0.4, OpenMPI 4.1.1 and SLURM in UBUNTU 22 in a single PC with 16 threads.&lt;/p&gt;&#xA;&lt;p&gt;I have setup this pc and, when I run orca alone, openmpi works. But, when I submit orca through slurm, the calculation fails. In this image I can show what is happening:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/TOdxU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TOdxU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It seems that SLURM does not recognize OpenMPI&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How can I resolve it?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Files:&lt;/code&gt;&lt;/p&gt;&#xA;&lt;p&gt;Orca.sh&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash -l&#xA;#SBATCH -J p_amf2&#xA;#SBATCH -n 1&#xA;#SBATCH --cpus-per-task=8&#xA;#SBATCH --ntasks-per-node=1&#xA;#SBATCH --output=&amp;quot;output.out&amp;quot;&#xA;#SBATCH --error=&amp;quot;error.err&amp;quot;&#xA;#SBATCH --mem=1000&#xA;&#xA;export LD_LIBRARY_PATH=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;$HOME/orca:$&lt;/span&gt;LD_LIBRARY_PATH&amp;quot;&#xA;export LD_LIBRARY_PATH=&amp;quot;/usr/local/lib/openmpi/:&lt;span class=&quot;math-container&quot;&gt;$LD_LIBRARY_PATH&quot;&#xA;export MPIROOT=&quot;/usr/local/bin/:$&lt;/span&gt;MPIROOT&amp;quot;&#xA;export OMP_PROC_BIND=true OMP_PLACES=sockets&#xA;export OMPI_MCA_mpi_yield_when_idle=1&#xA;&#xA;cd $SLURM_SUBMIT_DIR&#xA;&#xA;/home/david/orca/orca Benzene.inp &amp;gt; Test.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;ORCA input:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# Benzene RHF Opt Calculation&#xA;#%pal nprocs 8 end&#xA;! RHF TightSCF PModel&#xA;! opt&#xA;                               # Molecule specification&#xA;* xyz 0 1&#xA;     C    0.000000000000     1.398696930758     0.000000000000&#xA;     C    0.000000000000    -1.398696930758     0.000000000000&#xA;     C    1.211265339156     0.699329968382     0.000000000000&#xA;     C    1.211265339156    -0.699329968382     0.000000000000    &#xA;     C   -1.211265339156     0.699329968382     0.000000000000&#xA;     C   -1.211265339156    -0.699329968382     0.000000000000&#xA;     H    0.000000000000     2.491406946734     0.000000000000&#xA;     H    0.000000000000    -2.491406946734     0.000000000000&#xA;     H    2.157597486829     1.245660462400     0.000000000000&#xA;     H    2.157597486829    -1.245660462400     0.000000000000&#xA;     H   -2.157597486829     1.245660462400     0.000000000000&#xA;     H   -2.157597486829    -1.245660462400     0.000000000000&#xA;*&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;slurm.conf&lt;/code&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# slurm.conf file generated by configurator.html.&#xA;# Put this file on all nodes of your cluster.&#xA;# See the slurm.conf man page for more information.&#xA;#&#xA;ClusterName=localcluster&#xA;SlurmctldHost=localhost&#xA;MpiDefault=none&#xA;ProctrackType=proctrack/linuxproc&#xA;ReturnToService=2&#xA;SlurmctldPidFile=/var/run/slurmctld.pid&#xA;SlurmctldPort=6817&#xA;SlurmdPidFile=/var/run/slurmd.pid&#xA;SlurmdPort=6818&#xA;SlurmdSpoolDir=/var/lib/slurm/slurmd&#xA;SlurmUser=slurm&#xA;StateSaveLocation=/var/lib/slurm/slurmctld&#xA;SwitchType=switch/none&#xA;TaskPlugin=task/none&#xA;#&#xA;# TIMERS&#xA;InactiveLimit=0&#xA;KillWait=30&#xA;MinJobAge=300&#xA;SlurmctldTimeout=120&#xA;SlurmdTimeout=300&#xA;Waittime=0&#xA;# SCHEDULING&#xA;SchedulerType=sched/backfill&#xA;SelectType=select/cons_tres&#xA;SelectTypeParameters=CR_Core&#xA;#&#xA;#AccountingStoragePort=&#xA;AccountingStorageType=accounting_storage/none&#xA;JobCompType=jobcomp/none&#xA;JobAcctGatherFrequency=30&#xA;JobAcctGatherType=jobacct_gather/none&#xA;SlurmctldDebug=info&#xA;SlurmctldLogFile=/var/log/slurm/slurmctld.log&#xA;SlurmdDebug=info&#xA;SlurmdLogFile=/var/log/slurm/slurmd.log&#xA;#&#xA;# COMPUTE NODES&#xA;NodeName=localhost CPUs=24 RealMemory=31772 State=UNKNOWN&#xA;PartitionName=LocalQ Nodes=ALL Default=YES MaxTime=INFINITE     State=UP&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8416" LastEditorUserId="8416" LastEditDate="2024-02-12T12:53:27.217" LastActivityDate="2024-02-13T11:06:04.197" Title="OpenMPI not running under SLURM in UBUNTU with ORCA?" Tags="|orca|atomistic-simulation|" AnswerCount="2" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="12371" PostTypeId="2" ParentId="12367" CreationDate="2024-02-07T16:36:54.037" Score="5" Body="&lt;p&gt;I am not exactly sure what type of interpolation you want, but I believe you want an interpolation to generate an intial path that can be later relaxed via nudged elastic band (NEB) or a similar method.&lt;/p&gt;&#xA;&lt;p&gt;If this is so, then IDPP interpolation might be a good choice. IDPP or Image-Dependent Pair Potential is a method often used for generating the initial path for NEB, and is implemented in ORCA or ASE. The IDPP paper can be found &lt;a href=&quot;https://arxiv.org/abs/1406.1512&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and a tutorial for IDPP with ASE can be found &lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/tutorials/neb/idpp.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. ORCA can also perform IDPP, and it will print &lt;code&gt;basename_initial_path_trj.xyz&lt;/code&gt; which should contain the IDPP path. Simply run a NEB calculation with maxiter set to 1, and a cheap method like PM3 or XTB2, so that you get the interpolation without having to run NEB.&lt;/p&gt;&#xA;&lt;p&gt;IDPP starts with interpolating along the pairwise distances in the initial and final geometry. Unfortunately there more pairwise distances than there are coordinates, i.e. the pairwise distance coordinates are redundant. This means it is not possible to convert pairwise distances back to Cartesians. So what IDPP does is that it takes an interpolated geometry in Cartesian, and then minimizes the deviation from the ideal pairwise distances. Short distances are weighted more than long distances to prevent unnecessary bond breaking.&lt;/p&gt;&#xA;&lt;p&gt;Another recent publication is the geodesic interpolation. It is also similar to IDPP but uses a different way of representing internal coordinates, and might be better than IDPP. The publication is &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/150/16/164103/198363/Geodesic-interpolation-for-reaction-pathways&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; and the python package can be found &lt;a href=&quot;https://github.com/virtualzx-nad/geodesic-interpolate&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;All of these methods usually use distance based internal coordinates. There have been some papers that also suggest using distance/angle/dihedral based internal coordinates. However, these are much more finicky and difficult to implement, and as far as I know there are no open-source or public packages that can do this.&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2024-02-07T16:36:54.037" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12372" PostTypeId="1" AcceptedAnswerId="12413" CreationDate="2024-02-08T04:08:29.163" Score="2" ViewCount="55" Body="&lt;p&gt;As above, I am attempting to generate an IC table for decanoic acid using CHARMM (version 48b1) so I have a minimized geometry. I have attached my build.inp script and the stream file I have written. I am having issues with the alkyl hydrogens bonding to two carbons in a manner similar to the C-C bond. I based my stream file on the all_36_lipid_detergents.str file that comes with CHARMM, removing two carbons from lauric acid to create my decanoic acid stream file.&lt;/p&gt;&#xA;&lt;p&gt;Does anybody have advice about how to fix my hydrogens? I have attached my build.inp, stream file and the generated pdb along with a vmd generated image of the lipid.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;build.inp&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* Reads the DCA residue from the stream topology file and writes a pdb consisting&#xA;* of a single DCA molecule&#xA;*&#xA;&#xA;!topology and parameter files&#xA;&#xA;stream toppar.str&#xA;&#xA;read sequence DECA 1&#xA;generate DECA&#xA;&#xA;!read sequence DECN 1&#xA;!generate DECN&#xA;&#xA;ic generate&#xA;ic param&#xA;ic seed 1 C1 1 C2 1 C3 !to generate box CHARMM must know coords of at least three atoms defined by top file&#xA;ic build&#xA;&#xA;open write card unit 10 name DCA_build.pdb&#xA;write coor pdb  unit 10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;top_dca.str&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* Topology file for decanoic acid and decanoate&#xA;* Stream following reading of&#xA;* top_all36_lipid.rtf&#xA;* and&#xA;* par_all36_lipid.rtf&#xA;*&#xA;&#xA;!Based on fatty acids LAU and LAUP added Jan 2016 &#xA;&#xA;read rtf card append&#xA;* decanoic acid and decanoate&#xA;*&#xA;41  1&#xA;&#xA;AUTOGENERATE ANGLE DIHE&#xA;&#xA;RESI DECA        0.00 ! Decanoic Acid (10:0)&#xA;GROUP                 !&#xA;ATOM H1   HOL    0.44 !&#xA;ATOM O1   OHL   -0.61 !      O2  O1--H1&#xA;ATOM O2   OBL   -0.55 !       \\ /&#xA;ATOM C1   CL     0.75 !        C1&#xA;ATOM C2   CTL2  -0.21 !         |&#xA;ATOM H2R  HAL2   0.09 !  H2R---C2---H2S&#xA;ATOM H2S  HAL2   0.09 !         |       &#xA;GROUP                 !&#xA;ATOM C3   CTL2  -0.18 !         |&#xA;ATOM H3R  HAL2   0.09 !  H3R---C3---H3S&#xA;ATOM H3S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C4   CTL2  -0.18 !         |&#xA;ATOM H4R  HAL2   0.09 !  H4R---C4---H4S&#xA;ATOM H4S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C5   CTL2  -0.18 !         |&#xA;ATOM H5R  HAL2   0.09 !  H5R---C5---H5S&#xA;ATOM H5S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C6   CTL2  -0.18 !         |&#xA;ATOM H6R  HAL2   0.09 !  H6R---C6---H6S&#xA;ATOM H6S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C7   CTL2  -0.18 !         |&#xA;ATOM H7R  HAL2   0.09 !  H7R---C7---H7S&#xA;ATOM H7S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C8   CTL2  -0.18 !         |&#xA;ATOM H8R  HAL2   0.09 !  H8R---C8---H8S&#xA;ATOM H8S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C9   CTL2  -0.18 !         |&#xA;ATOM H9R  HAL2   0.09 !  H9R---C9---H9S&#xA;ATOM H9S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C10  CTL3  -0.27 !         |&#xA;ATOM H10S HAL3   0.09 ! H10R---C10--H10S&#xA;ATOM H10R HAL3   0.09 !         |&#xA;ATOM H10T HAL3   0.09 !        H10T&#xA;&#xA;BOND  O1  H1&#xA;BOND  O1  C1&#xA;BOND  C1  C2&#xA;DOUBLE  C1  O2&#xA;BOND  C2  H2R       C2  H2S       C2  C3&#xA;BOND  C3  H3R       C3  H3S       C3  C4&#xA;BOND  C4  H4R       C4  H4S       C4  C5&#xA;BOND  C5  H5R       C5  H5S       C5  C6&#xA;BOND  C6  H6R       C6  H6S       C6  C7&#xA;BOND  C7  H7R       C7  H7S       C7  C8&#xA;BOND  C8  H8R       C8  H8S       C8  C9&#xA;BOND  C9  H9R       C9  H9S       C9  C10&#xA;BOND  C10 H10R      C10 H10S      C10 H10T&#xA;&#xA;IMPR C1 O1 C2 O2&#xA;&#xA;RESI DECN       -1.00 ! Decanoic acid (10:0), unprotonated&#xA;GROUP                 !&#xA;ATOM O1   OCL   -0.76 !      O2  O1 (-)&#xA;ATOM O2   OCL   -0.76 !       \\ /&#xA;ATOM C1   CL     0.62 !        C1&#xA;ATOM C2   CTL2  -0.28 !         |&#xA;ATOM H2R  HAL2   0.09 !  H2R---C2---H2S&#xA;ATOM H2S  HAL2   0.09 !         |       &#xA;GROUP                 !&#xA;ATOM C3   CTL2  -0.18 !         |&#xA;ATOM H3R  HAL2   0.09 !  H3R---C3---H3S&#xA;ATOM H3S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C4   CTL2  -0.18 !         |&#xA;ATOM H4R  HAL2   0.09 !  H4R---C4---H4S&#xA;ATOM H4S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C5   CTL2  -0.18 !         |&#xA;ATOM H5R  HAL2   0.09 !  H5R---C5---H5S&#xA;ATOM H5S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C6   CTL2  -0.18 !         |&#xA;ATOM H6R  HAL2   0.09 !  H6R---C6---H6S&#xA;ATOM H6S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C7   CTL2  -0.18 !         |&#xA;ATOM H7R  HAL2   0.09 !  H7R---C7---H7S&#xA;ATOM H7S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C8   CTL2  -0.18 !         |&#xA;ATOM H8R  HAL2   0.09 !  H8R---C8---H8S&#xA;ATOM H8S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C9   CTL2  -0.18 !         |&#xA;ATOM H9R  HAL2   0.09 !  H9R---C9---H9S&#xA;ATOM H9S  HAL2   0.09 !         |&#xA;GROUP                 !&#xA;ATOM C10  CTL3  -0.27 !         |&#xA;ATOM H10S HAL3   0.09 ! H10R---C10--H10S&#xA;ATOM H10R HAL3   0.09 !         |&#xA;ATOM H10T HAL3   0.09 !        H10T&#xA;&#xA;BOND  O1  C1&#xA;BOND  C1  C2&#xA;DOUBLE  C1  O2&#xA;BOND  C2  H2R       C2  H2S       C2  C3&#xA;BOND  C3  H3R       C3  H3S       C3  C4&#xA;BOND  C4  H4R       C4  H4S       C4  C5&#xA;BOND  C5  H5R       C5  H5S       C5  C6&#xA;BOND  C6  H6R       C6  H6S       C6  C7&#xA;BOND  C7  H7R       C7  H7S       C7  C8&#xA;BOND  C8  H8R       C8  H8S       C8  C9&#xA;BOND  C9  H9R       C9  H9S       C9  C10&#xA;BOND  C10 H10R      C10 H10S      C10 H10T&#xA;&#xA;IMPR C1 O1 C2 O2&#xA;&#xA;end&#xA;&#xA;return&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;dca.pdb&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;REMARK  READS THE DCA RESIDUE FROM THE STREAM TOPOLOGY FILE AND WRITES A PDB CONSISTIN&#xA;REMARK  OF A SINGLE DCA MOLECULE                                                      &#xA;REMARK   DATE:     2/ 8/24     11:35:17      CREATED BY USER: thomas                  &#xA;ATOM      1  H1  DECA    1      -1.447  -1.387  -0.000  1.00  0.00      DECA&#xA;ATOM      2  O1  DECA    1      -0.490  -1.311  -0.000  1.00  0.00      DECA&#xA;ATOM      3  O2  DECA    1      -0.726   0.981  -0.000  1.00  0.00      DECA&#xA;ATOM      4  C1  DECA    1       0.000   0.000   0.000  1.00  0.00      DECA&#xA;ATOM      5  C2  DECA    1       1.522   0.000   0.000  1.00  0.00      DECA&#xA;ATOM      6  H2R DECA    1       1.893  -0.524   0.907  1.00  0.00      DECA&#xA;ATOM      7  H2S DECA    1       1.893   1.047  -0.000  1.00  0.00      DECA&#xA;ATOM      8  C3  DECA    1       1.995   1.455   0.000  1.00  0.00      DECA&#xA;ATOM      9  H3R DECA    1       1.617   1.979  -0.904  1.00  0.00      DECA&#xA;ATOM     10  H3S DECA    1       3.105   1.496   0.000  1.00  0.00      DECA&#xA;ATOM     11  C4  DECA    1       3.517   1.604   0.000  1.00  0.00      DECA&#xA;ATOM     12  H4R DECA    1       3.948   1.122   0.904  1.00  0.00      DECA&#xA;ATOM     13  H4S DECA    1       3.796   2.680   0.000  1.00  0.00      DECA&#xA;ATOM     14  C5  DECA    1       3.990   3.060   0.000  1.00  0.00      DECA&#xA;ATOM     15  H5R DECA    1       3.612   3.584  -0.904  1.00  0.00      DECA&#xA;ATOM     16  H5S DECA    1       5.101   3.100   0.000  1.00  0.00      DECA&#xA;ATOM     17  C6  DECA    1       5.513   3.209   0.000  1.00  0.00      DECA&#xA;ATOM     18  H6R DECA    1       5.944   2.727   0.904  1.00  0.00      DECA&#xA;ATOM     19  H6S DECA    1       5.791   4.284  -0.000  1.00  0.00      DECA&#xA;ATOM     20  C7  DECA    1       5.986   4.664   0.000  1.00  0.00      DECA&#xA;ATOM     21  H7R DECA    1       5.608   5.188  -0.904  1.00  0.00      DECA&#xA;ATOM     22  H7S DECA    1       7.096   4.705   0.000  1.00  0.00      DECA&#xA;ATOM     23  C8  DECA    1       7.508   4.813   0.000  1.00  0.00      DECA&#xA;ATOM     24  H8R DECA    1       7.939   4.331   0.904  1.00  0.00      DECA&#xA;ATOM     25  H8S DECA    1       7.787   5.889   0.000  1.00  0.00      DECA&#xA;ATOM     26  C9  DECA    1       7.981   6.268   0.000  1.00  0.00      DECA&#xA;ATOM     27  H9R DECA    1       7.603   6.793  -0.904  1.00  0.00      DECA&#xA;ATOM     28  H9S DECA    1       9.092   6.309   0.000  1.00  0.00      DECA&#xA;ATOM     29  C10 DECA    1       9.498   6.455   0.000  1.00  0.00      DECA&#xA;ATOM     30 H10S DECA    1       9.940   5.983   0.904  1.00  0.00      DECA&#xA;ATOM     31 H10R DECA    1       9.750   7.537   0.000  1.00  0.00      DECA&#xA;ATOM     32 H10T DECA    1       9.940   5.983  -0.904  1.00  0.00      DECA&#xA;TER      33      DECA     1&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZRI1Z.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZRI1Z.png&quot; alt=&quot;vmd visualised pdb file&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8607" LastActivityDate="2024-02-27T17:31:34.093" Title="My CHARMM IC table generation has caused hydrogen to bond to two carbons. How do I fix this?" Tags="|molecular-dynamics|charmm|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12373" PostTypeId="2" ParentId="9020" CreationDate="2024-02-08T06:36:59.140" Score="5" Body="&lt;p&gt;The reason you're getting the error&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;** There are no main   basis functions on atom number  14 (Br) **&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;is that there are no basis functions on atom 14. Take a look at the orca_manual_5_0_3.pdf, p. 486 (the manual can be downloaded from the orcaforum). You will notice that it lists &lt;code&gt;H–Zn &lt;/code&gt; for the basis set 6-31g(d) under the &lt;code&gt;availability&lt;/code&gt; column. That is because this basis set is available for elements 1 (H) through 30 (Zn) by default in orca. As far as I can tell, &lt;a href=&quot;https://www.basissetexchange.org/&quot; rel=&quot;noreferrer&quot;&gt;https://www.basissetexchange.org/&lt;/a&gt; does not have 6-31g(d) (it only lists 6-31g(d,p)), but you can check the availability there visually, since the ESML basis set exchange lists places a little yellow triangle in the bottom left corner. It looks like the ESML version of 6-31g(d,p) goes up to Krypton (element 36), so this one would include bromine (element 35).&lt;/p&gt;&#xA;&lt;p&gt;Basis sets are listed for specific ranges of atomic numbers because basis sets designed for modelling the valence shells of heavier elements will be &lt;em&gt;contracted&lt;/em&gt;. That means that the core shells basis functions will be replaced with something mathematically simpler, like an Effective Core Potential (ECP). This avoids the computational cost associated with very large numbers of basis functions.&lt;/p&gt;&#xA;&lt;p&gt;In your case, the basis set 6-31g(d) is only available up to Zn, so when you try to run your calculation, it fails, because there are no basis functions on your Br atoms. &lt;code&gt;!NORI&lt;/code&gt; won't do anything about this because all it does is turns off the RI approximation, but you can't even run an SCF cycle if you have atoms with no basis functions on them at all. You could use the ESML version of 6-31g(d,p), which goes up to Kr, but the 6-31g(d,p) set available by default in ORCA also only goes up to Zn. Why don't you try 6-311G? Alternatively, you could use something with &lt;code&gt;H-Kr&lt;/code&gt; availability. As @Geoff Hutchison pointed out, you could simply use Def2-SVP. If you're concerned about whether the basis set has the same number of basis functions as your desired 6-31g(d) set, you can take a &lt;code&gt;https://en.wikipedia.org/wiki/Basis_set_(chemistry)&lt;/code&gt; or &lt;em&gt;Jensen&lt;/em&gt;, section 5: &lt;code&gt;file:///home/joseph/Downloads/Jensen_F.-Introduction_to_Computational_Chemistry_(2007).pdf&lt;/code&gt; (will download book).&lt;/p&gt;&#xA;&lt;p&gt;Happy computing!&lt;/p&gt;&#xA;" OwnerUserId="7827" LastActivityDate="2024-02-08T06:36:59.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12374" PostTypeId="1" AcceptedAnswerId="12376" CreationDate="2024-02-08T07:51:04.543" Score="4" ViewCount="120" Body="&lt;p&gt;I'm currently searching for an Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotential of Eu, which has a localized f-orbital. But no matter how much I search online, I can't find it.&lt;/p&gt;&#xA;&lt;p&gt;There is an &lt;a href=&quot;http://www.quantum-simulation.org/potentials/sg15_oncv/upf/&quot; rel=&quot;nofollow noreferrer&quot;&gt;online repository&lt;/a&gt; of other atoms that have a ONCV pseudopotential, but some of the rare earth elements such as Eu, Lanthanides etc. don't have one.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have it?&lt;/p&gt;&#xA;" OwnerUserId="8396" LastEditorUserId="7" LastEditDate="2024-02-21T04:03:50.557" LastActivityDate="2024-02-21T04:03:50.557" Title="Is there an Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotential of Eu atom?" Tags="|density-functional-theory|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12375" PostTypeId="2" ParentId="11511" CreationDate="2024-02-08T08:12:31.063" Score="0" Body="&lt;p&gt;The direct computation of the derivative of the nuclear-electron attraction operator can be simply avoided.&#xA;Remember that in the McMurchie-Davidson algorithm, the Coulomb integral is reduced to a form, which requires contraction of the E and R tensors.&#xA;To get the derivative to an atom center, it just needs to change the index of the R tensor (see Molecular electronic-structure theory (T. Helgaker, P.Jorgensen, J.Olsen), chapter 9.9.3, p.376).&lt;/p&gt;&#xA;" OwnerUserId="8784" LastActivityDate="2024-02-08T08:12:31.063" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12376" PostTypeId="2" ParentId="12374" CreationDate="2024-02-08T11:03:47.650" Score="3" Body="&lt;p&gt;Edit: after posting my answer, I noticed you have asked this question also in the QE users forum and your question got a response there. That response is better than my answer posted here since that contains both scalar relativistic and full relativistic version, uses GGA (PBE) instead of LDA (PZ), contains &lt;code&gt;&amp;lt;PP_PSWFC&amp;gt;&lt;/code&gt; sections so that you will be able to do projection (pdos) calculation, and also the PP I referred to is more than a decade old. For reference, &lt;a href=&quot;https://lists.quantum-espresso.org/pipermail/users/2024-February/051239.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; is the answer to your question by Lorenzo Paulatto in QE users forum.&lt;/p&gt;&#xA;&lt;p&gt;Since you mentioned SG15 database and upf format, I am assuming you are looking for the pseudopotential in the UPF format.&lt;/p&gt;&#xA;&lt;p&gt;In the Quantum ESPRESSO's official pseudopotential page, they have this &lt;a href=&quot;https://pseudopotentials.quantum-espresso.org/legacy_tables/hartwigesen-goedecker-hutter-pp&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hartwigesen-Goedecker-Hutter&lt;/a&gt; pseudopotential tables where you have the pseudopotential of &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Eu}$&lt;/span&gt;. This is the &lt;a href=&quot;https://pseudopotentials.quantum-espresso.org/legacy_tables/hartwigesen-goedecker-hutter-pp/eu&quot; rel=&quot;nofollow noreferrer&quot;&gt;direct link&lt;/a&gt; to the &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Eu}$&lt;/span&gt; pseudopotential page and this is the &lt;a href=&quot;https://pseudopotentials.quantum-espresso.org/upf_files/Eu.pz-sp-hgh.UPF&quot; rel=&quot;nofollow noreferrer&quot;&gt;direct link&lt;/a&gt; to your desired pseudopotential in UPF format.&lt;/p&gt;&#xA;&lt;p&gt;Details:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Eu.pz-sp-hgh.UPF&lt;/p&gt;&#xA;&lt;p&gt;Pseudopotential type: NORMCONS&lt;/p&gt;&#xA;&lt;p&gt;Method: Goedecker-Hartwigsen-Hutter-Teter&lt;/p&gt;&#xA;&lt;p&gt;Functional type: Perdew-Zunger&#xA;(LDA) exch-corr Semi-core state in valence non relativistic&lt;/p&gt;&#xA;&lt;p&gt;Origin: Hartwigsen-Goedeker-Hutter PP&lt;/p&gt;&#xA;&lt;p&gt;Author: Goedecker/Hartwigsen/Hutter/Teter Generated in analytical, separable&#xA;form. Converted from CPMD format using cpmd2upf v.5.0.1. Uploaded by&#xA;marsamos Classification unverified&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2024-02-08T11:43:03.850" LastActivityDate="2024-02-08T11:43:03.850" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12377" PostTypeId="1" CreationDate="2024-02-08T12:32:39.647" Score="4" ViewCount="60" Body="&lt;p&gt;I am trying to calculate the CCSD energies between two orbitals. Suppose I have a system,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto, scf, ao2mo, cc&#xA;from pyscf.gto import mole&#xA;&#xA;# Define your molecule&#xA;mol = gto.Mole()&#xA;mol.atom = '''&#xA;    O  0.0000000, 0.0000000, 0.0000000&#xA;    H  0.757606,  0.586006,  0.0000000&#xA;    H -0.757606,  0.586006,  0.0000000'''&#xA;mol.basis = 'sto-3g'&#xA;mol.charge = 0&#xA;mol.spin = 0&#xA;mol.build()&#xA;&#xA;# Perform SCF calculation&#xA;mf = scf.RHF(mol)&#xA;mf.kernel()&#xA;&#xA;# Get MO coefficient matrix&#xA;mo_coeff = mf.mo_coeff&#xA;&#xA;# Obtain the CCSD energy from canonical&#xA;mcc = cc.CCSD(mf)&#xA;ecc,t1,t2 = mcc.kernel()&#xA;print(&amp;quot;CCSD correlation energy = &amp;quot;,mcc.e_corr)&#xA;print(&amp;quot;Total CCSD energy = &amp;quot;,mcc.e_tot)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The correlation energy is -0.0494284459751351 Hartree. Now, this calculation takes all HF orbitals and occupancies as arguments to the CCSD function.&#xA;If I know correctly, I can calculate the CCSD correlation energies between each pair of MO (of course, one orbital should be doubly occupied, and the other should be vacant) and sum them up to obtain the total correlation energy.&#xA;To do this, I take a pair of orbitals (one from doubly occupied and another from vacant MO) and run the CCSD calculation for each pair. So, for water molecules with a sto-3g basis, the MO coefficient matrix is 7*7, and the occupancy is a numpy array [2.0,2.0,2.0,2.0,2.0,0.0,0.0].&#xA;So I obtained the MO columns using this (just for testing and without any beautiful coding)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;coeff_0 = mf.mo_coeff[:,0]; coeff_1 = mf.mo_coeff[:,1]; coeff_2 = mf.mo_coeff[:,2]; coeff_3 = mf.mo_coeff[:,3]&#xA;coeff_4 = mf.mo_coeff[:,4]; coeff_5 = mf.mo_coeff[:,5]; coeff_6 = mf.mo_coeff[:,6]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Then, I merged the pairs for occupied and virtual MOs. In the case of the MO coefficient matrix, columns 0-4 are occupied, and columns 5-6 are virtual. So, for each occupied column, there will be two virtual columns. I merged the columns as,&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mo_coeff05 = np.column_stack((coeff_0,coeff_5));mo_coeff06 = np.column_stack((coeff_0,coeff_6))&#xA;mo_coeff15 = np.column_stack((coeff_1,coeff_5));mo_coeff16 = np.column_stack((coeff_1,coeff_6))&#xA;mo_coeff25 = np.column_stack((coeff_2,coeff_5));mo_coeff26 = np.column_stack((coeff_2,coeff_6))&#xA;mo_coeff35 = np.column_stack((coeff_3,coeff_5));mo_coeff36 = np.column_stack((coeff_3,coeff_6))&#xA;mo_coeff45 = np.column_stack((coeff_4,coeff_5));mo_coeff46 = np.column_stack((coeff_4,coeff_6))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And at last, I run the CCSD for each merged MO coefficient matrix.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mcc.mo_occ = np.array([2.0,0.0])&#xA;mcc.mo_coeff = mo_coeff05&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff06&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff15&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff16&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff25&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff26&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff35&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff36&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff45&#xA;mcc.kernel()[0]&#xA;mcc.mo_coeff = mo_coeff46&#xA;mcc.kernel()[0]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;What I expected that if I sum all the correlation energies, I will get the total CCSD correlation energy, but some of the correlation energy are even higher than the total system.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;E(CCSD) = -51.47188187443665  E_corr = -0.0003962543997611398&#xA;E(CCSD) = -51.47149476545477  E_corr = -9.145417883697846e-06&#xA;E(CCSD) = -6.483145580303841  E_corr = -1.059192232873223&#xA;E(CCSD) = -5.424905601367101  E_corr = -0.0009522539364820224&#xA;E(CCSD) = -2.90788145525101  E_corr = -0.002489550153102168&#xA;E(CCSD) = -5.339446749364194  E_corr = -2.434054844266286&#xA;E(CCSD) = -4.937559682283515  E_corr = -0.9363818461883874&#xA;E(CCSD) = -4.003003233876766  E_corr = -0.001825397781638726&#xA;E(CCSD) = -4.845351104114307  E_corr = -0.0003760041376774681&#xA;E(CCSD) = -4.84514723864436  E_corr = -0.0001721386677304669&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Also, the SCF + CCSD energy defined by this, &lt;strong&gt;E(CCSD) =&lt;/strong&gt; is very different.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is my approach wrong?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="2194" LastEditorUserId="5" LastEditDate="2024-02-08T13:25:58.180" LastActivityDate="2024-02-08T13:25:58.180" Title="CCSD calculation between two orbitals" Tags="|molecular-modeling|ab-initio-calculations|hartree-fock|pyscf|coupled-cluster|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12378" PostTypeId="1" CreationDate="2024-02-08T12:37:15.390" Score="1" ViewCount="80" Body="&lt;p&gt;It is well known that the Hartree–Fock (HF) approximation predicts a wrong order for the last two molecular orbitals of N&lt;span class=&quot;math-container&quot;&gt;$_{2}$&lt;/span&gt;. The calculations indicate that the 1&lt;span class=&quot;math-container&quot;&gt;$\pi_{u}$&lt;/span&gt; orbital has higher energy than the 3&lt;span class=&quot;math-container&quot;&gt;$\sigma_{g}$&lt;/span&gt;, while the experiment suggests the opposite. As pointed out in the book &amp;quot;Modern Quantum Chemistry&amp;quot; by Szabo and Ostlund, this error can be corrected by including correlation effects, for example using the configuration interaction (CI) method.&lt;/p&gt;&#xA;&lt;p&gt;My question is: how to perform this calculation with CI? For example, I could calculate the energy of the neutral molecule and its anion with CI and subtract one from the other, this would give me the ionization energy. However, how can I deduce the correct energies of the molecular orbitals from this difference? I really have no idea how to perform this calculation in practice using a quantum chemistry software like &amp;quot;Gaussian16&amp;quot;.&lt;/p&gt;&#xA;" OwnerUserId="6572" LastEditorUserId="5" LastEditDate="2024-02-08T13:24:38.680" LastActivityDate="2024-02-16T04:47:13.750" Title="How to use the CI method to compute the order of the molecular orbitals of the nitrogen molecule" Tags="|quantum-chemistry|electronic-structure|quantum-mechanics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12379" PostTypeId="1" AcceptedAnswerId="12397" CreationDate="2024-02-08T13:05:42.480" Score="3" ViewCount="49" Body="&lt;p&gt;When computing the thermal transmission coefficient, the green function needs to be computed first; for example, &lt;span class=&quot;math-container&quot;&gt;$G^{R}_{scattering\:region}=\left[\left(\omega+i0^{+}\right)^{2}I-D\right]^{-1}$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is named the dynamic constant matrix.&lt;/p&gt;&#xA;&lt;p&gt;I compare it with the retarded green function for the scattering region in the charge conductance. I found that this dynamic constant matrix is just the off-diagonal matrix in the Hamiltonian, which is the interaction matrix between the lead and the central scattering region. Is my understanding correct?&lt;/p&gt;&#xA;&lt;p&gt;Would anyone please give me some explanation?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastActivityDate="2024-02-15T09:04:03.717" Title="The Dynamic Constant Matrix for the Green Function in the Thermal Conductance Calculation" Tags="|density-functional-theory|electronic-transport|transport|greens-functions|lattice-thermal-conductivity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12380" PostTypeId="2" ParentId="12369" CreationDate="2024-02-09T03:20:16.407" Score="2" Body="&lt;p&gt;Just for completeness, I will copy over my answer to &lt;a href=&quot;https://orcaforum.kofo.mpg.de/viewtopic.php?f=8&amp;amp;t=10996&quot; rel=&quot;nofollow noreferrer&quot;&gt;this question&lt;/a&gt; in the Orca forum:&lt;/p&gt;&#xA;&lt;p&gt;Assuming you don't have an Orca 'module' set up, you may need to add a few extra lines to your script. The ones I have on mine are:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;export MPIROOT=&amp;quot;/opt/local/bin/:$MPIROOT&amp;quot;  # modified from /usr/local/openmpi &#xA;&#xA;export LD_LIBRARY_PATH=&amp;quot;/usr/local/lib:$LD_LIBRARY_PATH&amp;quot;  # contains my libmpi.40.dylib file&#xA;&#xA;export LD_LIBRARY_PATH=&amp;quot;$LD_LIBRARY_PATH:/Applications/orca/orca_5_0_4_macosx_arm64_openblas_openmpi411&amp;quot;  # my Orca directory&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;While, as you can tell, I am using a Mac, you definitely need to specify the &lt;code&gt;LD_LIBRARY_PATH&lt;/code&gt; appropriately, and possibly the OpenMPI path (not sure). Maybe add them and see if that helps?&lt;/p&gt;&#xA;&lt;p&gt;(I suspect the second line in that example isn't necessary if you have your &lt;code&gt;LD_LIBRARY_PATH&lt;/code&gt; variable set in your &lt;code&gt;.bashrc&lt;/code&gt; or &lt;code&gt;.bash_profile&lt;/code&gt; files, but I didn't, so I don't know for sure.)&lt;/p&gt;&#xA;&lt;p&gt;All this being said, the error in your screenshot does not necessarily mean that OpenMPI is not activating. That error often pops up if you do not have enough RAM available for the calculation you want to run. I just noticed that your job script does not actually ask for any RAM, so I am not sure if that will mean Slurm gives you as much memory as you need, or absolutely no memory. Either way, I would suggest you add this line to your Slurm script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --mem=xxx  # amount of RAM requested, in MB&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;So, if you have an Orca input file with:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%mem 1000&#xA;%pal&#xA;nprocs 4&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;you would use:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#SBATCH --mem=5000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or something like that. (Personally, I think it is always better to include a value for &lt;code&gt;%mem&lt;/code&gt; in the Orca input file, just to be on the safe side.)&lt;/p&gt;&#xA;" OwnerUserId="7606" LastEditorUserId="7606" LastEditDate="2024-02-10T04:29:18.723" LastActivityDate="2024-02-10T04:29:18.723" CommentCount="11" ContentLicense="CC BY-SA 4.0" />
  <row Id="12381" PostTypeId="2" ParentId="12367" CreationDate="2024-02-09T08:39:18.073" Score="2" Body="&lt;p&gt;I think you can use a method called Geodesic interpolation. Here is the DOI&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1063/1.5090303&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1063/1.5090303&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;It is really easy to use. Using only geometric information, you are able to generate paths from one point to another, for example from reactants to products.&#xA;The code is here,&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/virtualzx-nad/geodesic-interpolate.git&quot; rel=&quot;nofollow noreferrer&quot;&gt;    https://github.com/virtualzx-nad/geodesic-interpolate.git&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4657" LastEditorUserId="24" LastEditDate="2024-02-16T13:55:55.343" LastActivityDate="2024-02-16T13:55:55.343" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12382" PostTypeId="1" CreationDate="2024-02-09T11:33:51.350" Score="3" ViewCount="85" Body="&lt;p&gt;When performing DFT+U calculation, the ground state might get stuck in a local minimum. In such cases we need to provide &lt;code&gt;starting_ns_eigenvalue&lt;/code&gt; to help the calculation reach the desired ground state. How do we find these starting eigenvalues? Can anybody explain this matter?&lt;/p&gt;&#xA;&lt;p&gt;In this &lt;a href=&quot;https://www.youtube.com/watch?v=34mHl0Iw2_E&quot; rel=&quot;nofollow noreferrer&quot;&gt;enter link description here&lt;/a&gt; reference video,  after the first scf iteration, it shows the Hubbard occupation as&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Tr[ns(  3)] (up, down, total) =   5.00000  1.00000  6.00000&#xA;     Atomic magnetic moment for atom   3 =   4.00000&#xA;     SPIN  1&#xA;     eigenvalues:&#xA;       1.000  1.000  1.000  1.000  1.000&#xA;.......&#xA;     SPIN  2&#xA;     eigenvalues:&#xA;       0.200  0.200  0.200  0.200  0.200&#xA;     eigenvectors (columns):&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and they change only the 5th eigenvalue of that atom to 1 in spin 2.&lt;/p&gt;&#xA;&lt;p&gt;but in my case, one atomic type (Fe) shows&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Tr[ns(  1)] (up, down, total) =   5.00000  1.00000  6.00000&#xA; Atomic magnetic moment for atom   1 =   4.00000&#xA; SPIN  1&#xA; eigenvalues:&#xA;   1.000  1.000  1.000  1.000  1.000&#xA; SPIN  2&#xA; eigenvalues:&#xA;   0.200  0.200  0.200  0.200  0.200&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and for other atomic type (Ti)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; Atomic magnetic moment for atom   3 =  -0.02149&#xA; SPIN  1&#xA; eigenvalues:&#xA;   0.269  0.269  0.309  0.314  0.314&#xA; ......&#xA; SPIN  2&#xA; eigenvalues:&#xA;   0.285  0.285  0.296  0.315  0.315&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I need to know, which eigenvalue needs to change here&lt;/p&gt;&#xA;" OwnerUserId="8340" LastEditorUserId="8340" LastEditDate="2024-02-11T13:55:36.200" LastActivityDate="2024-02-11T13:55:36.200" Title="How do we find the starting_ns_eigenvalue for QE calculations?" Tags="|quantum-espresso|dft-u|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12383" PostTypeId="1" CreationDate="2024-02-09T22:48:46.087" Score="5" ViewCount="123" Body="&lt;p&gt;&lt;a href=&quot;https://mattermodeling.stackexchange.com/q/404/97&quot;&gt;A very similar question was asked about 4 years ago&lt;/a&gt;, but this is a fast moving field, so I think it warrants reexamining.&lt;/p&gt;&#xA;&lt;p&gt;What are the most promising areas where quantum computers could advance quantum chemistry in the next 3-5 years?&lt;/p&gt;&#xA;&lt;p&gt;Note: This question could potentially be very broad, but I'm specifically interested in the impact on quantum chemistry and the type of problems currently solved with density functional theory or &lt;em&gt;ab initio&lt;/em&gt; methods.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2024-02-15T20:24:28.950" LastActivityDate="2024-02-22T10:05:28.287" Title="What are the most promising areas where quantum computers could advance quantum chemistry in the next 3-5 years?" Tags="|quantum-chemistry|quantum-computing|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12384" PostTypeId="1" CreationDate="2024-02-11T16:23:59.987" Score="2" ViewCount="25" Body="&lt;p&gt;I am trying to calculate the spin-lattice relaxation time using VASP DFPT(&lt;code&gt;ibrion=8&lt;/code&gt;).&#xA;I have got the &lt;code&gt;Hessian matrix&lt;/code&gt;.&#xA;Is it possible to get the &lt;span class=&quot;math-container&quot;&gt;$\tau_1$&lt;/span&gt; from the Hessian?&lt;/p&gt;&#xA;" OwnerUserId="5946" LastEditorUserId="6055" LastEditDate="2024-02-11T16:37:16.830" LastActivityDate="2024-02-11T16:37:16.830" Title="Spin-lattice relaxation calculation" Tags="|vasp|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12385" PostTypeId="2" ParentId="12362" CreationDate="2024-02-12T00:10:02.800" Score="4" Body="&lt;p&gt;Hydrogen and deuterium are basically identical electronically (*) and you should use the same pseudopotential (POTCAR) for each. You should not see any difference between hydrogen and deuterium (or tritium) in energies, forces, stresses, force-constants (Hessian) etc. nor, consequently, optimised Born-Oppenheimer geometries at 0 K.&lt;/p&gt;&#xA;&lt;p&gt;There are some differences which affect certain types of calculation, principally:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;Mass&lt;br /&gt;&#xA;Deuterium has twice the mass of hydrogen, and this is important for its dynamics and quantum effects. The mass affects MD and phonon calculations, as well as zero-point motion and energies. Note: if you wish to obtain quantum-corrected geometries you will need to either use some form of path-integral MD, or phonon calculations beyond the usual harmonic approximation (ie you need at least 3rd order force constants).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Spin&lt;br /&gt;&#xA;The nucleus can have intrinsic spin (and quadrupoles, octopoles...) which is important for some properties - most obviously NMR chemical shifts.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;In general, different isotopes have different spin-orbit coupling as well, but this is negligible for such light nuclei as these.&lt;/p&gt;&#xA;&lt;p&gt;(*) There is actually a very, very small difference due to the change in reduced mass, but we almost always use the Born-Oppenheimer approximation anyway which neglects this.&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2024-02-15T01:15:04.227" LastActivityDate="2024-02-15T01:15:04.227" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12386" PostTypeId="1" CreationDate="2024-02-12T07:05:52.010" Score="2" ViewCount="31" Body="&lt;p&gt;The dynamical matrix for the thermal transmission coefficient calculation is written as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$D_{I\alpha,J\beta}(\overrightarrow{q})=\frac{1}{\sqrt{M_{I}M_{J}}}\sum_{b}K_{I\alpha,J\beta}(a,b)e^{i\cdot\overrightarrow{q}(\vec{R}_{b}-\vec{R}_{a})}\tag{1}$$&lt;/span&gt;&#xA;,where &lt;span class=&quot;math-container&quot;&gt;$M_{I}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$M_{J}$&lt;/span&gt; are atomic weight; &lt;span class=&quot;math-container&quot;&gt;$\vec{R}_{a}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\vec{R}_{b}$&lt;/span&gt; are the original lattice constant.&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$K_{I\alpha,J\beta}$&lt;/span&gt; is the force constant matrix and it is given as follows:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$K_{I\alpha,J\beta}(R-R^{'})=\frac{\partial^{2}E_{tot}}{\partial{\mu_{I\alpha}}(R)\partial{\mu_{J\beta}(R^{'})}}=-\frac{\partial{F_{I\alpha}}}{\partial{\mu_{J\beta}(R^{'})}}\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Compute the force constant matrix for the unit cell and this force constant matrix is &lt;span class=&quot;math-container&quot;&gt;$3n\times3n$&lt;/span&gt; matrix; for example, if there are three atoms in the unit cell; then, this force constant matrix is a &lt;span class=&quot;math-container&quot;&gt;$9\times9$&lt;/span&gt; matrix.&lt;/li&gt;&#xA;&lt;li&gt;Compute the dynamical matrix through summing all the neighbour cell of the central unit cell&lt;/li&gt;&#xA;&lt;li&gt;Symmterize the dynamical matrix and make sure the upper and lower triangle blocks in this dynamical matrix are hermitian conjugate to each other.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Is my understanding correct or not?&lt;/p&gt;&#xA;" OwnerUserId="4343" LastEditorUserId="5" LastEditDate="2024-02-12T07:06:52.423" LastActivityDate="2024-02-12T07:06:52.423" Title="Dynamical Matrix for the Thermal Transmission Coefficient Calculation" Tags="|density-functional-theory|phonopy|phonon-dispersion|lattice-thermal-conductivity|phono3py|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12387" PostTypeId="1" CreationDate="2024-02-12T08:29:59.557" Score="2" ViewCount="22" Body="&lt;p&gt;I am an aspiring quantum chemist planning on trying out the SHARC approach to study excited state proton transfer dynamics of organic molecules. I am comfortable with Gaussian 16 as that is the software where we do most of out work. I want to utilize the SHARC - Gaussian interface to use SHARC along with the TDDFT functionality of Gaussian. The tutorial given along with the manual only covers the MOLCAS/OpenMolcas interface.&lt;/p&gt;&#xA;&lt;p&gt;Please let me know if you know any good resources to learn the SHARC Gaussian interface from.&lt;/p&gt;&#xA;" OwnerUserId="8664" LastEditorUserId="5" LastEditDate="2024-02-12T13:22:25.053" LastActivityDate="2024-02-12T13:22:25.053" Title="Are there any good tutorials on SHARC-Gaussian interface?" Tags="|software|gaussian|reference-request|potential-energy-surface|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12388" PostTypeId="1" CreationDate="2024-02-13T06:55:18.303" Score="1" ViewCount="62" Body="&lt;p&gt;Say we take the basic example of a PEG molecule (PolyEthylene Glycol). What is the fundamental physics for computing the Elastic Modulus or the Young's Modulus from the Molecular Dynamics (MD) Simulation perspective? Support your explanation with a suitable .mdp file&lt;/p&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2024-02-16T10:12:01.520" Title="How to compute the Elastic Modulus of a molecule using GROMACS?" Tags="|molecular-dynamics|gromacs|physical-properties-of-materials|elasticity|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12389" PostTypeId="2" ParentId="12369" CreationDate="2024-02-13T11:06:04.197" Score="4" Body="&lt;p&gt;In order for Orca to launch an 8-task MPI run, Slurm must assign 8 tasks. This is achieved by the &lt;code&gt;--ntasks-per-node&lt;/code&gt; flag. So you need the following settings in your job script:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--ntasks-per-node=8&#xA;--cpus-per-task=1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Which allows Orca to execute an 8-task MPI job (i.e., &lt;code&gt;mpirun -np 8 ...&lt;/code&gt;). See also &lt;a href=&quot;https://sites.google.com/site/orcainputlibrary/setting-up-orca&quot; rel=&quot;nofollow noreferrer&quot;&gt;this web page&lt;/a&gt;, which has a sample Slurm script for Orca.&lt;/p&gt;&#xA;&lt;p&gt;Your initial setting of&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;--ntasks-per-node=1&#xA;--cpus-per-task=8&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does not allow for spawning multiple MPI tasks but, rather, for a single multi-threaded process. It can be used if you're running an OpenMP-parallelized program.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2024-02-13T11:06:04.197" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12390" PostTypeId="1" CreationDate="2024-02-14T03:54:21.987" Score="3" ViewCount="62" Body="&lt;p&gt;I'm working with OpenMX and see that I have eigenvalues in the output in two columns: one for spin up and one for spin down. How would I know what the total eigenvalue is? Would I just add them together? Also, the data looks like below:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  286   -0.02008501314452  -0.02008501314452&#xA;  287   -0.01559740498122  -0.01559740498122&#xA;  288   -0.01243830320899  -0.01243830320899&#xA;  289   -0.01220124445157  -0.01220124445157&#xA;  290   -0.00578203878459  -0.00578203878459&#xA;  291   -0.00371042282201  -0.00371042282201&#xA;  292   -0.00331216783551  -0.00331216783551&#xA;  293   -0.00118189095836  -0.00118189095836&#xA;  294    0.00408542561654   0.00408542561654&#xA;  295    0.00507831640267   0.00507831640267&#xA;  296    0.00891684168499   0.00891684168499&#xA;  297    0.01154985410456   0.01154985410456&#xA;  298    0.01401015272980   0.01401015272980&#xA;  299    0.01600696638805   0.01600696638805&#xA;  300    0.01788534275125   0.01788534275125&#xA;  301    0.01850894866304   0.01850894866304&#xA;  302    0.02039668066291   0.02039668066291&#xA;  303    0.02140787080479   0.02140787080479&#xA;  304    0.02331225608436   0.02331225608436&#xA;  305    0.02387109420448   0.02387109420448&#xA;  306    0.02530373611739   0.02530373611739&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Would the HOMO/LUMO bound be at 293/294? If so, this does not match the value I had gotten from a VASP calculation that showed the HOMO/LUMO to be at 236/237. What would cause this discrepancy?&lt;/p&gt;&#xA;&lt;p&gt;*For reference, the above data is in the &amp;quot;Eigenvalue&amp;quot; section, which has the following heading:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;***********************************************************&#xA;***********************************************************&#xA;           Eigenvalues (Hartree) of SCF KS-eq.&#xA;***********************************************************&#xA;***********************************************************&#xA;&#xA;   Chemical Potential (Hartree) =  -0.16158758016502&#xA;   Number of States             = 512.00000000000000&#xA;   Eigenvalues&#xA;              Up-spin           Down-spin&#xA;&#xA;   kloop=0&#xA;   k1=  -0.25000 k2=  -0.25000 k3=   0.00000&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7429" LastActivityDate="2024-02-14T12:20:46.167" Title="How to get the HOMO/LUMO from spin up/down eigenvalues?" Tags="|vasp|computational-chemistry|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12391" PostTypeId="1" CreationDate="2024-02-14T06:27:13.183" Score="2" ViewCount="27" Body="&lt;p&gt;How to compile VASP for non-colinear calculations? How to compile VASP without the flag -DNGXhalf and -DNGZhalf?&lt;/p&gt;&#xA;" OwnerUserId="8808" LastEditorUserId="5" LastEditDate="2024-02-14T17:26:45.673" LastActivityDate="2024-02-14T17:26:45.673" Title="How to compile VASP for non-colinear calculations?" Tags="|vasp|software-assistance|vaspkit|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12392" PostTypeId="2" ParentId="11726" CreationDate="2024-02-14T09:14:12.780" Score="3" Body="&lt;p&gt;Ciao Marco!&lt;/p&gt;&#xA;&lt;p&gt;Once you make the supercell the reciprocal lattice vectors are divided by 2 (or whatever factor) automatically. The kptbounds are in reduced coordinates so no need to change the bound. What will happen is the bands will fold back, so the new Gamma-&amp;gt;X path will contain 8x as many bands (2x2x2) folded from the old Gamma-&amp;gt;X as well as Gamma+(0,0,0.5)-&amp;gt;X+(0,0,0.5) etc...&lt;/p&gt;&#xA;&lt;p&gt;What you probably want is to unfold the bands to compare (once you add a defect) to the pristine bands and project on those. This can be done with several utilities with interfaces to abinit, in particular fold2bloch (&lt;a href=&quot;https://docs.abinit.org/tutorial/fold2bloch/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://docs.abinit.org/tutorial/fold2bloch/&lt;/a&gt;) and I think also &lt;a href=&quot;https://github.com/mailhexu/banddownfolder&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/mailhexu/banddownfolder&lt;/a&gt; (made for phonons and magnons, but I have seen a version work with electrons as well).&lt;/p&gt;&#xA;" OwnerUserId="8810" LastActivityDate="2024-02-14T09:14:12.780" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12393" PostTypeId="1" CreationDate="2024-02-14T10:53:16.563" Score="2" ViewCount="50" Body="&lt;p&gt;I am investigating a bulk structure by ab initio molecular dynamics (AIMD) implemented in VASP.&#xA;I was wondering, how to choose the initial geometry (= POSCAR file) to run the AIMD simulation. In the literature I saw mainly two different approaches:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Using theoretical &amp;amp; unoptimized lattice structures, e.g. from a database like MaterialsProject. This includes lattice constant and a basis (for instance in VASP tutorial &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Standard_MD&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Liquid_Si_-_Standard_MD&lt;/a&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Using preoptimized lattice structures, i.e. relaxing the ionic positions in before by e.g. conjugated-gradient algorithm (IBRION=2). And then using the CONTCAR as initial geometry for AIMD (I saw this in different papers) .&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;From my understanding it has more physical meaning, if the structure is relaxed before.&#xA;Furthermore, lets say I relax a supercell of 2x2x2 unit cells before, I can duplicate the relaxed supercell and use it as an input for AIMD?&lt;/p&gt;&#xA;&lt;p&gt;Best,&#xA;Luca&lt;/p&gt;&#xA;" OwnerUserId="8715" LastActivityDate="2024-02-14T10:53:16.563" Title="Prerelaxation before AIMD with VASP" Tags="|density-functional-theory|vasp|molecular-dynamics|geometry-optimization|aimd|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12394" PostTypeId="2" ParentId="12390" CreationDate="2024-02-14T12:20:46.167" Score="2" Body="&lt;p&gt;If you want to have eigenvalues for each spin, you need to run a spin polarized calculations. This will set the program to treat both spins differently. After that, you could obtain different values of eigenvalues for each state if your system present spin polarization.&lt;/p&gt;&#xA;&lt;p&gt;In both cases (with spin polarization on/off), you will have one eigenvalue per spin. Looking close to your result, both values are the same, indicating that your system is not spin-polarized. Then, what you have is a degenerate state: one eigenvalue for two states (spin-up/spin-down). There is no such thing of &amp;quot;total eigenvalue&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;About your second question related to HOMO/LUMO. You need to look for the eigenvalues around the Fermi energy (chemical potential), not when they change signs. In this case, the Fermi energy is equal to &lt;span class=&quot;math-container&quot;&gt;$-0.16158758016502$&lt;/span&gt;. The results shown, are far from the Fermi energy, so, all of them are virtual states (energy greater than the LUMO)&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-14T12:20:46.167" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12395" PostTypeId="1" AcceptedAnswerId="12396" CreationDate="2024-02-14T12:24:46.737" Score="2" ViewCount="82" Body="&lt;p&gt;I have a Si slab of thickness 0.5nm for which I want to calculate the phonon dispersion. The unitcell has 5 atomic layers and 10 Si atoms with vacuum of 10A in z-direction (a 2x2 supercell is shown below)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uDhno.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uDhno.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The dispersion (calculated with phonopy and alamode) has large negative frequencies [THz]:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fiJ0K.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fiJ0K.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Visualizing the phonon modes reveals that those negative frequencies are largely associated with the vibration of the surface atoms (surface phonons).&lt;/p&gt;&#xA;&lt;p&gt;The structure is tightly relaxed before carrying out the calculations. I use VASP with tight criteria (&lt;code&gt;EDIFFG=-1e-3&lt;/code&gt;, &lt;code&gt;EDIFF=1e-8&lt;/code&gt;, &lt;code&gt;PREC = ACCURATE&lt;/code&gt;, &lt;code&gt;LREAL = .FALSE.&lt;/code&gt;). I followed two different strategies which gave the same result for lattice constant (a=5.36A in x and y directions):&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Volume relaxation: (&lt;code&gt;isif = 4&lt;/code&gt;) with high &lt;code&gt;ENCUT&lt;/code&gt; (~1.3*&lt;code&gt;ENMAX&lt;/code&gt;) to avoid Pulay stress.&lt;/li&gt;&#xA;&lt;li&gt;Equation of state approach: only relaxation of positions (&lt;code&gt;isif = 2&lt;/code&gt;) with varying lattice constant in a step of 0.01A and finding the lattice constant that gives the minimum energy.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;I even tried relaxation without symmetry (&lt;code&gt;isym=0&lt;/code&gt;) starting from a rattled structure.&lt;/p&gt;&#xA;&lt;p&gt;The forces of the displaced structure are also calculated accurately (&lt;code&gt;EDIFF=1e-8&lt;/code&gt;, &lt;code&gt;PREC = ACCURATE&lt;/code&gt;, &lt;code&gt;LREAL = .FALSE.&lt;/code&gt;, with and without &lt;code&gt;ADDGRID&lt;/code&gt;)&lt;/p&gt;&#xA;&lt;p&gt;I am not sure whether the structure is at a saddle point of the potential energy surface. I know I can get the direction in which the frequency is negative and move the associated atom in that direction to get out of the saddle point (if any). However, this will break the symmetry. The structure is very symmetric and simple; you just control the lattice constant (which is the same in the x and y directions), and the fractional atoms' positions are constant. As mentioned, I tried different relaxation strategies.&lt;/p&gt;&#xA;&lt;p&gt;I am now stuck and do not know how to proceed. Thanks for your help.&lt;/p&gt;&#xA;" OwnerUserId="8813" LastEditorUserId="8813" LastEditDate="2024-02-15T05:23:21.143" LastActivityDate="2024-02-15T05:23:21.143" Title="Si Thin film phonon dispersion with negative frequency" Tags="|vasp|geometry-optimization|phonons|potential-energy-surface|phonon-dispersion|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12396" PostTypeId="2" ParentId="12395" CreationDate="2024-02-14T18:27:12.663" Score="1" Body="&lt;p&gt;Just because the structure is simple with high symmetry doesn't mean it's the correct ground state. More often that not, symmetry breaking leads to interesting physics (e.g. the surface reconstruction affects thermal transport, see the ACS ref below). I encourage you to relax along the soft modes, or create a slightly randomized version of your structure and relax from there with e.g. simulated annealing.&lt;/p&gt;&#xA;&lt;p&gt;Also note that your structure and many other variations have most likely been extensively studied before. Silicon is probably the most widely studied materials that exists! You can likely find papers that have already done what you are trying to do. You can save yourself some work and read those or try to reproduce their results for practice.&lt;/p&gt;&#xA;&lt;p&gt;In any case, your structure is a saddle point. People have studied surface reconstruction of silicon in the past! See e.g. here &lt;a href=&quot;https://doi.org/10.1103/PhysRevB.14.588&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1103/PhysRevB.14.588&lt;/a&gt; and here &lt;a href=&quot;https://doi.org/10.1021/nn506792d&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://doi.org/10.1021/nn506792d&lt;/a&gt; Your structure may have a different orientation, I am not sure. I remember these refs from some old work I did, but I am sure there are many other related papers that cite or are cited by these. Hopefully these are a good starting point for you!&lt;/p&gt;&#xA;&lt;p&gt;Cheers!&#xA;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-02-14T18:27:12.663" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12397" PostTypeId="2" ParentId="12379" CreationDate="2024-02-15T09:04:03.717" Score="3" Body="&lt;p&gt;For phonon transport the Green function formalism is largely equivalent as for electrons.&lt;/p&gt;&#xA;&lt;p&gt;The primary change is that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\begin{aligned}&#xA;\mathbf H &amp;amp;\to \mathbf D&#xA;\\&#xA;\mathbf S &amp;amp;\to \mathbf I&#xA;\\&#xA;\epsilon &amp;amp;\to \epsilon^2&#xA;\end{aligned}&#xA;$$&lt;/span&gt;&#xA;In practice the overlap matrix could be a mass-matrix so &lt;span class=&quot;math-container&quot;&gt;$\mathbf D$&lt;/span&gt; becomes mass-independent. But that is a minor detail.&lt;/p&gt;&#xA;&lt;p&gt;All of the Green function is then the same (if I haven't forgotten anything).&#xA;The self-energies are calculated as needed by the same transformations as shown above, and the full device Green function can be constructed equivalently.&lt;/p&gt;&#xA;&lt;p&gt;What is typically a bit harder for phononic systems is that the range of interaction is typically much longer. Hence the electrodes, and device systems should equally be larger to still obey the decoupling of the electrodes from each other (no left &lt;span class=&quot;math-container&quot;&gt;$\to$&lt;/span&gt; right coupling).&lt;/p&gt;&#xA;&lt;p&gt;So &lt;span class=&quot;math-container&quot;&gt;$\mathbf D$&lt;/span&gt; is still containing the elements that couple it to the electrodes, and the electrodes self-energies should still be inserted in the full device Green function:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;G(\epsilon) = \big[(\epsilon^2 + i\eta ^2)\mathbf I - \mathbf D - \sum_i \boldsymbol\Sigma_i  \big]^{-1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$\boldsymbol\Sigma_i$&lt;/span&gt; is the self-energy of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;'th (phononic) electrode. Note how I prefer to decouple the &lt;span class=&quot;math-container&quot;&gt;$\epsilon$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt;. The &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; is a numerical trick to move the Green function away from the real-axis. Hence, it makes no sense to add the &lt;span class=&quot;math-container&quot;&gt;$2i\epsilon\eta$&lt;/span&gt; to the complex part as that would create an &lt;em&gt;energy dependent shift into the complex plane&lt;/em&gt;. You'll quite often see &lt;span class=&quot;math-container&quot;&gt;$(\epsilon + i\eta)^2$&lt;/span&gt; in litterature (as you have written), but IMHO it is complicating matters.&lt;br /&gt;&#xA;The reason for choosing &lt;span class=&quot;math-container&quot;&gt;$\eta^2$&lt;/span&gt; is that the energy units of the phonon Green function is &lt;span class=&quot;math-container&quot;&gt;$1/[E]^2$&lt;/span&gt; and hence the &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; value should equally be in that unit. And since energies/couplings in dynamical matrices are typically much smaller (numerically) than Hamiltonian elements one also requires a much smaller &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; value. Consider &lt;span class=&quot;math-container&quot;&gt;$\eta = 10^{-2}$&lt;/span&gt; which would result in an imaginary part of &lt;span class=&quot;math-container&quot;&gt;$0.0001$&lt;/span&gt;.&#xA;This is just to mention that the typical choices of &lt;span class=&quot;math-container&quot;&gt;$\eta$&lt;/span&gt; values for electronic systems can also be used in phononic systems, perhaps even smaller values. But that is again system dependent and requires care from the user.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2024-02-15T09:04:03.717" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12398" PostTypeId="1" CreationDate="2024-02-15T09:34:15.470" Score="2" ViewCount="82" Body="&lt;p&gt;I have a 1 ns long molecular dynamics trajectory of 884 molecules of water, and I am trying to compute the velocity autocorrelation function using MDAnalysis to analyze the GROMACS output files.&lt;/p&gt;&#xA;&lt;p&gt;I have written:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def vacf(ncorr):&#xA;    acf, norm = np.zeros(ncorr), np.zeros(ncorr) # initialize autocorrelation function and normalization arrays&#xA;&#xA;    n = 0 # first frame&#xA;    for ts in u.trajectory: # loop through the trajectory&#xA;        vel = u.trajectory[n].velocities.flatten() # calculate velocities at t0&#xA;        maxn = min(u.trajectory.n_frames, n + ncorr) - n&#xA;&#xA;        for i in range(maxn):&#xA;            veln = u.trajectory[n + i].velocities.flatten() # compute velocities at time t + t0&#xA;            acf[i] = acf[i] + np.dot(vel, veln.T) / (len(u.atoms))&#xA;            norm[i] = norm[i] + 1&#xA;&#xA;        n += 1&#xA;&#xA;    acf = acf / norm&#xA;    return acf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The velocity autocorrelation function results are usually something that start at 1 and slowly decay to 0, but this is not the case for the simulation I'm analyzing. The output I'm getting is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Vtbmn.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Vtbmn.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Do you have any ideas on what I'm doing wrong?&#xA;Thank you very much in advance, have a great day!&lt;/p&gt;&#xA;" OwnerUserId="8815" LastActivityDate="2024-02-16T09:11:06.500" Title="Velocity autocorrelation function for molecular dynamics trajectory" Tags="|molecular-dynamics|python|gromacs|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12399" PostTypeId="1" AcceptedAnswerId="12401" CreationDate="2024-02-15T09:42:41.367" Score="5" ViewCount="143" Body="&lt;p&gt;I want to obtain the single point energy of a Ni-complex molecule, with a mixed basis set using the Gen keyword. The input is:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=4&#xA;%mem=1500MB&#xA;%chk=61++.chk&#xA;# b3lyp/gen&#xA;&#xA;title&#xA;&#xA;atom coordinates&#xA;&#xA;P C H N O 0&#xA;6-311++G(d,p)&#xA;****&#xA;Ni 0&#xA;cc-pVDZ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but I get this error:&lt;/p&gt;&#xA;&lt;p&gt;QPErr --- A syntax error was detected in the input line.&lt;/p&gt;&#xA;&lt;p&gt;'&lt;/p&gt;&#xA;&lt;p&gt;Last state= &amp;quot;Top&amp;quot;&#xA;TCursr=      2959 LCursr=         0&#xA;Error reading general basis specification.&#xA;Error termination via Lnk1e in C:\G09W\l301.exe&#xA;Job cpu time:       0 days  0 hours  0 minutes  0.0 seconds.&lt;/p&gt;&#xA;&lt;p&gt;I would be grateful if you could help me to solve this problem.&lt;/p&gt;&#xA;" OwnerUserId="8816" LastEditorUserId="5" LastEditDate="2024-02-15T13:03:25.643" LastActivityDate="2024-02-15T13:03:25.643" Title="What is the problem in my gaussian input?" Tags="|computational-chemistry|gaussian|software-assistance|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12400" PostTypeId="1" CreationDate="2024-02-15T11:08:46.763" Score="2" ViewCount="65" Body="&lt;p&gt;I calculated the single point energy of some small molecule using the PM7 method (with COSMO solvation model) in MOPAC and calculated the gradients. Then I calculated MM potential energy with gradients (amber14sb force field and OBC2 implicit solvent) using the OpenMM program.&lt;/p&gt;&#xA;&lt;p&gt;I expected the gradients to be different in value due to the differences in the methods, but the gradients also differ in direction, and finding a pair of co-directional gradients is quite difficult. I wanted to try taking the gradients from different calculations and inserting them into the BFGS optimization algorithm, but due to this difference in directions I get strange results.&lt;/p&gt;&#xA;&lt;p&gt;How does this result correspond to practice? Maybe I'm missing something?&lt;/p&gt;&#xA;" OwnerUserId="8804" LastEditorUserId="5" LastEditDate="2024-02-15T13:02:44.813" LastActivityDate="2024-02-15T13:02:44.813" Title="Different QM and MM gradients in geometry optimization" Tags="|geometry-optimization|openmm|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12401" PostTypeId="2" ParentId="12399" CreationDate="2024-02-15T12:30:44.287" Score="4" Body="&lt;p&gt;You just need to add the name of basis set again for Ni at the end of the input&lt;/p&gt;&#xA;&lt;p&gt;Your input should be&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%nprocshared=4&#xA;%mem=1500MB&#xA;%chk=61++.chk&#xA;# b3lyp/gen&#xA;&#xA;title&#xA;&#xA;atom coordinates&#xA;&#xA;P C H N O 0&#xA;6-311++G(d,p)&#xA;****&#xA;Ni 0&#xA;cc-pVDZ&#xA;****&#xA;&#xA;Ni 0&#xA;cc-pVDZ&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-02-15T12:30:44.287" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12405" PostTypeId="1" CreationDate="2024-02-15T22:23:43.520" Score="3" ViewCount="30" Body="&lt;p&gt;I am trying to write a plugin in LAMMPS that would need to compute the energy between two atoms as a function of the first atoms coordination number. From the LAMMPS GitHub repository, I found that there is a compute command that can do the calculation of the coordination number. This brings me to the following question: Can I call that from a pair style (let's say gaussian)?&lt;/p&gt;&#xA;&lt;p&gt;The specifics of the problem are as follows:&#xA;I need some way to bias the energies obtained from using pair_style gauss/cut to be dependent on the current coordination number of the central atom. This means that I need to modify the hgauss term in the gaussian on the fly.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-02-16T17:54:10.770" LastActivityDate="2024-02-16T17:54:10.770" Title="Writing a plugin in LAMMPS" Tags="|lammps|programming|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12406" PostTypeId="2" ParentId="12378" CreationDate="2024-02-16T04:47:13.750" Score="2" Body="&lt;p&gt;The incorrect ordering of molecular orbitals given by Hartree-Fock (Koopmans' defect) can be resolved with methods based on electron propagator/one-electron Green's function theories. Such methods provide both Dyson orbitals and correlated electron binding energies without directly computing CI wavefunctions. The correlated binding energies or ionization potentials (IPs) should, in principle, provide information about the correct molecular electronic configuration. An advantage of electron propagator theory is that it includes correlation and relaxation effects missing in Hartree-Fock while still retaining familiar one-electron concepts.&lt;/p&gt;&#xA;&lt;p&gt;See:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1080/00268977300102261&quot; rel=&quot;nofollow noreferrer&quot;&gt;B.T. Pickup and O. Goscinski. Mol. Phys. 26. 4 (1973) 1013–1035&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/S0065-3276(08)60291-9&quot; rel=&quot;nofollow noreferrer&quot;&gt;Y. Öhrn and G. Born. Advances in Quantum Chemistry. Vol. 13. (1981) 1–88&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1002/wcms.1116&quot; rel=&quot;nofollow noreferrer&quot;&gt;J.V. Ortiz. WIREs Comput. Mol. Sci. 3. 2 (2013) 123–142&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Chapter 7 of Szabo and Ostlund is also useful.&lt;/p&gt;&#xA;&lt;p&gt;The inadequacy of Koopmans' theorem in the case of the nitrogen molecule is well known:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/0009-2614(73)80451-8&quot; rel=&quot;nofollow noreferrer&quot;&gt;L.S. Cederbaum, G. Hohlneicher, W. von Niessen. Chem. Phys. Lett. 18. 4 (1973) 503-508&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://doi.org/10.1016/B978-0-32-390257-1.00007-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;H.H. Corzo. Chemical Reactivity. Ch. 1 (2023) 1-26&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The correct assignment of the HOMO of nitrogen can be achieved through second-order self-energy corrections to the Hartree-Fock eigenvalues. The correlated IPs indicate that &lt;span class=&quot;math-container&quot;&gt;$3\sigma_{g}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\pi_{u}$&lt;/span&gt; orbitals should be swapped.&lt;/p&gt;&#xA;&lt;p&gt;Electron propagator calculations may be performed in &lt;a href=&quot;https://gaussian.com/ept/&quot; rel=&quot;nofollow noreferrer&quot;&gt;Gaussian&lt;/a&gt;. Various diagonal self-energy approximations are available. Here are example inputs:&lt;/p&gt;&#xA;&lt;p&gt;Second-order (D2)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=n2.chk&#xA;#p ept(ep2) cc-pvtz window=full &#xA;&#xA;nitrogen&#xA;&#xA;0 1&#xA;N 0.0 0.0 0.0&#xA;N 1.098 0.0 0.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Renormalized partial third-order (P3+)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;%chk=n2.chk&#xA;#p ept(p3,readOrbitals) cc-pvtz window=full &#xA;&#xA;nitrogen&#xA;&#xA;0 1&#xA;N 0.0 0.0 0.0&#xA;N 1.098 0.0 0.0&#xA;&#xA;1 10&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can also replace &amp;quot;p3&amp;quot; with &amp;quot;ovgf&amp;quot; to try the outer valence&#xA;Green's function (OVGF) method. Keep in mind that the quality of the basis set will affect the results. Pole strengths (Dyson orbital norms) less than 0.85 indicate that the diagonal approximations are not reliable and that more accurate methods are required.&lt;/p&gt;&#xA;" OwnerUserId="8819" LastActivityDate="2024-02-16T04:47:13.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12407" PostTypeId="1" CreationDate="2024-02-16T06:03:47.110" Score="3" ViewCount="74" Body="&lt;p&gt;I tried calculating Piezoelectric properties for a material using VASP with IBRION=8(DFPT) and LEPSILON=.true. . The piezoelectric tensors for ionic and electronic contributions turned out to be in the units of C/m^2 whereas the piezoelectric constants(d11,d12,...d33,...) i am looking for have the unit C/N. How do i calculate piezoelectric constants with units C/N from this?&lt;/p&gt;&#xA;&lt;p&gt;I am attaching some screenshots of my output.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/pcrlL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pcrlL.png&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/fNpOL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/fNpOL.png&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I referred some materials to solve this but I couldn’t find anything helpful as my knowledge of tensor is limited. Here is how i found the issue with my result:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The constant&#xA;for such a linearly proportional relation is defined as the piezoelectric coefficient&#xA;d, which is a third-rank tensor coupling the first-rank tensor or vector (electric&#xA;displacement or field) and the second-rank tensor (stress or strain). Hence, the&#xA;piezoelectric equations may be written in the following form (i, j, k = 1, 2, 3)&lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$D_k = d_{kij}T_{ij}$&lt;/span&gt; &lt;br /&gt;&#xA;&lt;span class=&quot;math-container&quot;&gt;$S_{ij} = d_{kij}^*E_{k}$&lt;/span&gt; &lt;br /&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$D_i$&lt;/span&gt; is electric displacement &lt;span class=&quot;math-container&quot;&gt;$(C/m^2)$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_i$&lt;/span&gt; is electric field component (V/m), &lt;span class=&quot;math-container&quot;&gt;$S_{ij}$&lt;/span&gt; is strain component, &lt;span class=&quot;math-container&quot;&gt;$T_{ij}$&lt;/span&gt; is stress component &lt;span class=&quot;math-container&quot;&gt;$(N/m^2)$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$d_{kij}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$d_{kij}^*$&lt;/span&gt; is component of the piezoelectric charge or strain constant.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I am ready to calculate it manually if i can learn how to do it from some source. But if you know any tools that can calculate the constants from this, please let me know about it as well.&lt;/p&gt;&#xA;&lt;p&gt;Edit: Here is my INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#-------Global parameters ---------&#xA;LWAVE=.TRUE.&#xA;LCHARG=.TRUE.&#xA;ENCUT = 550&#xA;#PREC = Accurate&#xA;#ISTART = 1&#xA;LREAL= Auto&#xA;ALGO =  Fast&#xA;LORBIT=11&#xA;LEPSILON= .TRUE.&#xA;&#xA;#--------- Electronic relaxation --------&#xA;ISMEAR = 0&#xA;SIGMA = 0.05&#xA;NELM = 60&#xA;NELMIN = 6&#xA;EDIFF = 0.0000001&#xA;&#xA;#--------- Magnetic calculation ------------&#xA;ISPIN = 2&#xA;MAGMOM = 2*5 2*5 6*5&#xA;&#xA;#------- IONIC Relaxation -----&#xA;NSW = 1&#xA;IBRION = 8&#xA;ISIF = 3&#xA;&#xA;#-------- SLR ---------&#xA;POTIM = 0.015&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Here is a link to my &lt;a href=&quot;https://github.com/vivekkarunakaran/Modeling_Matters/tree/master/12407&quot; rel=&quot;nofollow noreferrer&quot;&gt;OUTCAR-github&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="8704" LastEditorUserId="5" LastEditDate="2024-02-17T12:39:50.357" LastActivityDate="2024-02-17T12:39:50.357" Title="How do I get piezoelectric constants from VASP?" Tags="|vasp|vaspkit|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12408" PostTypeId="2" ParentId="12398" CreationDate="2024-02-16T09:11:06.500" Score="3" Body="&lt;p&gt;I think I managed to solve the problem. The code is now:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;def vacf():&#xA;    acf, norm = np.zeros(int(ncorr)), np.zeros(int(ncorr))&#xA;&#xA;    n = 0&#xA;    for atoms in u.atoms:&#xA;        vel = u.atoms[n].velocity&#xA;        maxn = min(u.trajectory.n_frames, n + ncorr) - n&#xA;&#xA;        for i in range(maxn):&#xA;            veln = u.atoms[n + i].velocity&#xA;            acf[i] = acf[i] + np.dot(vel, veln.T) / (np.dot(vel, vel))&#xA;            norm[i] = norm[i] + 1&#xA;&#xA;        n += 1&#xA;&#xA;    acf = acf / norm&#xA;    &#xA;    return acf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="8815" LastActivityDate="2024-02-16T09:11:06.500" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12409" PostTypeId="2" ParentId="12388" CreationDate="2024-02-16T10:02:50.603" Score="2" Body="&lt;p&gt;You can apply certain strains to the system by modifying the input structure, e.g. stretching one direction and fixing the other directions. After running MD, one can extract stress components. Keep in mind, that for NPT-ensemble the stress fluctuates around a constant value, so you should go for NVT-ensemble.&lt;br /&gt;&#xA;Do this for different values of strain, where the linear relationship between stress and strain holds (Hook's regime). The elastic constants &lt;span class=&quot;math-container&quot;&gt;$C_{ij}$&lt;/span&gt; come from the slopes of stress-strain curves. Depending on the symmetry of your system, different strains have to be regarded to calculate all elastic constants.&lt;/p&gt;&#xA;&lt;p&gt;One thing: Elastic moduli are polycrystal constants. Their definition through elastic constants holds for solid crystals of size &lt;span class=&quot;math-container&quot;&gt;$\geq\mu m$&lt;/span&gt; with grains. You cannot apply e.g. definition by Voigt or Reuss. Maybe I miss the property you want to calculate for the molecule.&lt;/p&gt;&#xA;&lt;p&gt;Best&lt;br /&gt;&#xA;Lukas&lt;/p&gt;&#xA;" OwnerUserId="8715" LastEditorUserId="8715" LastEditDate="2024-02-16T10:12:01.520" LastActivityDate="2024-02-16T10:12:01.520" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12410" PostTypeId="1" AcceptedAnswerId="12411" CreationDate="2024-02-16T13:44:51.693" Score="5" ViewCount="124" Body="&lt;p&gt;I am attempting to utilise the &lt;code&gt;space_group&lt;/code&gt; option for potential performance speed-up. In this I have two Q.E. files which I hope would give equivalent results; however, the final energies differ. In the first file I use &lt;code&gt;ibrav = 0&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation = 'scf'&#xA;    outdir = '/tmp/'&#xA;    prefix = 'graphene'&#xA;    pseudo_dir = 'pbe'&#xA;    restart_mode='from_scratch'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    ibrav = 0&#xA;    nat = 2, ntyp = 1,&#xA;    ecutwfc = 40.0 ,&#xA;    ecutrho = 400.0 ,&#xA;    occupations = 'smearing', degauss = 0.0001, smearing = 'marzari-vanderbilt'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr = 1.0d-10,&#xA;    mixing_beta = 0.3,&#xA;/&#xA;ATOMIC_SPECIES&#xA;C 12.01 C.upf&#xA;CELL_PARAMETERS angstrom&#xA;   2.465669985   0.000000000   0.000000000&#xA;  -1.232834994   2.135332846   0.000000000&#xA;   0.000000000   0.000000000   20.00000010&#xA;ATOMIC_POSITIONS crystal&#xA;C 0.000000000 0.000000000 0.250000000&#xA;C 0.333333333 0.666666667 0.250000000&#xA;K_POINTS automatic&#xA;12 12 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the second I use &lt;code&gt;space_group = 10&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation = 'scf'&#xA;    outdir = '/tmp/'&#xA;    prefix = 'graphene'&#xA;    pseudo_dir = 'pbe'&#xA;    restart_mode='from_scratch'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    space_group = 10&#xA;    A = 2.465669985&#xA;    B = 2.465669985&#xA;    C = 20.00000010&#xA;    nat = 2, ntyp = 1,&#xA;    ecutwfc = 40.0 ,&#xA;    ecutrho = 400.0 ,&#xA;    occupations = 'smearing', degauss = 0.0001, smearing = 'marzari-vanderbilt'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr = 1.0d-10,&#xA;    mixing_beta = 0.3,&#xA;/&#xA;ATOMIC_SPECIES&#xA;C 12.01 C.upf&#xA;ATOMIC_POSITIONS crystal_sg&#xA;C 0.000000000 0.000000000 0.250000000&#xA;C 0.333333333 0.666666667 0.250000000&#xA;K_POINTS automatic&#xA;12 12 1 0 0 0&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Why do I get different results?&lt;/p&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2024-02-16T20:47:45.017" LastActivityDate="2024-02-16T20:47:45.017" Title="Translate between ibrav and space_group Quantum Espresso inputs" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12411" PostTypeId="2" ParentId="12410" CreationDate="2024-02-16T16:09:56.917" Score="6" Body="&lt;p&gt;You would get different energies because these two input files correspond to two different structures. This can be confirmed by inspecting these files using any crystal structure visualizer. Following pictures are from BURAI but XCrySDen can also be used to directly open Quantum ESPRESSO input files using the command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;xcrysden --pwi your_input_file.in&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The first structure (with &lt;code&gt;CELL_PARAMETERS&lt;/code&gt;):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/7ZT0P.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/7ZT0P.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The second structure (with &lt;code&gt;space_group&lt;/code&gt;):&#xA;&lt;a href=&quot;https://i.stack.imgur.com/9d5tR.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/9d5tR.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-02-16T16:09:56.917" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12412" PostTypeId="1" CreationDate="2024-02-16T18:39:02.653" Score="7" ViewCount="349" Body="&lt;p&gt;Personally, I think quantum chemistry is one of the most promising applications for quantum computers because the problem itself is fundamentally quantum, so there is an obvious argument why we should expect a quantum speedup.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Are there matter modeling algorithms for quantum computers with proven quantum speedup?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here by 'proven,' I just mean that it has been mathematically demonstrated, not that they have necessarily been implemented on a practical device.&lt;/p&gt;&#xA;&lt;p&gt;I would be especially interested in algorithms that could integrate directly into existing &lt;em&gt;ab initio&lt;/em&gt; methods.&lt;/p&gt;&#xA;" OwnerUserId="97" LastEditorUserId="5" LastEditDate="2024-02-17T21:23:09.073" LastActivityDate="2024-02-17T21:23:09.073" Title="Have quantum computers been proven to speed up any matter modeling algorithm?" Tags="|quantum-chemistry|ab-initio-calculations|algorithms|quantum-computing|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12413" PostTypeId="2" ParentId="12372" CreationDate="2024-02-16T19:36:40.603" Score="2" Body="&lt;p&gt;I was able to build the structure correctly using the following input file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* Reads the DCA residue from the stream topology file and writes a pdb consisting&#xA;* of a single DCA molecule&#xA;*&#xA;&#xA;bomlev -5&#xA;wrnlev -5&#xA;&#xA;!topology and parameter files&#xA;open read card unit 10 name toppar/top_all36_lipid.rtf&#xA;read  rtf card unit 10 &#xA;&#xA;open read card unit 20 name toppar/par_all36_lipid.prm&#xA;read para card unit 20 flex&#xA;&#xA;stream top_test.str&#xA;&#xA;read sequence DECA 1&#xA;generate DECA&#xA;&#xA;!read sequence DECN 1&#xA;!generate DECN&#xA;&#xA;ic generate&#xA;ic param&#xA;ic seed 1 C1 1 C2 1 C3 !to generate box CHARMM must know coords of at least three atoms defined by top file&#xA;ic build&#xA;print ic&#xA;&#xA;coor build&#xA;coor print&#xA;hbuild sele all end&#xA;&#xA;mini sd 10000 1000&#xA;&#xA;open write card unit 30 name DCA_build.pdb&#xA;write coor pdb  unit 30&#xA;close unit 30&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Coordinates&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;REMARK  READS THE DCA RESIDUE FROM THE STREAM TOPOLOGY FILE AND WRITES A PDB CONSISTIN&#xA;REMARK  OF A SINGLE DCA MOLECULE                                                      &#xA;REMARK   DATE:     2/16/24     12:33:46      CREATED BY USER: hemanthharid            &#xA;ATOM      1  H1  DECA    1      -1.205  -1.285  -0.209  1.00  0.00      DECA&#xA;ATOM      2  O1  DECA    1      -0.275  -1.216   0.005  1.00  0.00      DECA&#xA;ATOM      3  O2  DECA    1      -0.760   0.944  -0.357  1.00  0.00      DECA&#xA;ATOM      4  C1  DECA    1       0.065   0.124  -0.030  1.00  0.00      DECA&#xA;ATOM      5  C2  DECA    1       1.493   0.398   0.469  1.00  0.00      DECA&#xA;ATOM      6  H2R DECA    1       2.017  -0.561   0.654  1.00  0.00      DECA&#xA;ATOM      7  H2S DECA    1       1.364   0.914   1.445  1.00  0.00      DECA&#xA;ATOM      8  C3  DECA    1       2.368   1.305  -0.442  1.00  0.00      DECA&#xA;ATOM      9  H3R DECA    1       1.739   2.078  -0.937  1.00  0.00      DECA&#xA;ATOM     10  H3S DECA    1       2.842   0.692  -1.241  1.00  0.00      DECA&#xA;ATOM     11  C4  DECA    1       3.457   2.026   0.384  1.00  0.00      DECA&#xA;ATOM     12  H4R DECA    1       4.062   1.263   0.921  1.00  0.00      DECA&#xA;ATOM     13  H4S DECA    1       2.949   2.655   1.150  1.00  0.00      DECA&#xA;ATOM     14  C5  DECA    1       4.411   2.930  -0.423  1.00  0.00      DECA&#xA;ATOM     15  H5R DECA    1       3.812   3.691  -0.971  1.00  0.00      DECA&#xA;ATOM     16  H5S DECA    1       4.945   2.312  -1.178  1.00  0.00      DECA&#xA;ATOM     17  C6  DECA    1       5.452   3.658   0.460  1.00  0.00      DECA&#xA;ATOM     18  H6R DECA    1       6.061   2.899   1.000  1.00  0.00      DECA&#xA;ATOM     19  H6S DECA    1       4.921   4.273   1.219  1.00  0.00      DECA&#xA;ATOM     20  C7  DECA    1       6.396   4.565  -0.351  1.00  0.00      DECA&#xA;ATOM     21  H7R DECA    1       5.792   5.306  -0.920  1.00  0.00      DECA&#xA;ATOM     22  H7S DECA    1       6.927   3.926  -1.093  1.00  0.00      DECA&#xA;ATOM     23  C8  DECA    1       7.466   5.329   0.460  1.00  0.00      DECA&#xA;ATOM     24  H8R DECA    1       8.044   4.605   1.075  1.00  0.00      DECA&#xA;ATOM     25  H8S DECA    1       6.982   6.052   1.153  1.00  0.00      DECA&#xA;ATOM     26  C9  DECA    1       8.422   6.058  -0.507  1.00  0.00      DECA&#xA;ATOM     27  H9R DECA    1       7.863   6.878  -1.012  1.00  0.00      DECA&#xA;ATOM     28  H9S DECA    1       8.689   5.315  -1.294  1.00  0.00      DECA&#xA;ATOM     29  C10 DECA    1       9.740   6.616   0.050  1.00  0.00      DECA&#xA;ATOM     30 H10S DECA    1      10.038   6.119   0.996  1.00  0.00      DECA&#xA;ATOM     31 H10R DECA    1       9.675   7.712   0.222  1.00  0.00      DECA&#xA;ATOM     32 H10T DECA    1      10.551   6.446  -0.695  1.00  0.00      DECA&#xA;TER      33      DECA     1&#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the structure that OP generated&#xA;&lt;a href=&quot;https://i.stack.imgur.com/xozps.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xozps.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can clearly see that the hydrogens are oriented along the C-C bond axis, which in turn causes the extra bonds that OP complained about.&lt;/p&gt;&#xA;&lt;p&gt;Now, the structure that I generated using the input provided below&#xA;&lt;a href=&quot;https://i.stack.imgur.com/3xQvg.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3xQvg.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The hydrogens are oriented properly now.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Conclusion: VMD was not the problem, instead the coordinates generated by OP was the problem.&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-02-27T17:31:34.093" LastActivityDate="2024-02-27T17:31:34.093" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12414" PostTypeId="2" ParentId="11882" CreationDate="2024-02-16T19:58:13.267" Score="3" Body="&lt;p&gt;A quick search of the toppar folder in CHARMM shows that there are three patches that are available to create neutral arginine from the charged arginine.&lt;/p&gt;&#xA;&lt;p&gt;This is the sample input&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;* Reads the DCA residue from the stream topology file and writes a pdb consisting&#xA;* of a single DCA molecule&#xA;*&#xA;&#xA;bomlev -5&#xA;wrnlev -5&#xA;&#xA;!topology and parameter files&#xA;open read card unit 10 name ./toppar/top_all36_prot.rtf&#xA;read  rtf card unit 10 &#xA;&#xA;open read card unit 20 name ./toppar/par_all36m_prot.prm&#xA;read para card unit 20 flex&#xA;&#xA;stream ./toppar/toppar_all36_prot_arg0.str&#xA;&#xA;read sequence ARG 1&#xA;generate ARG first nter last cter&#xA;&#xA;ic generate&#xA;ic param&#xA;ic seed 1 N 1 CA 1 C &#xA;ic build&#xA;print ic&#xA;&#xA;coor build&#xA;coor print&#xA;hbuild sele all end&#xA;&#xA;mini sd 10000 1000&#xA;&#xA;open write card unit 30 name arginine_charged.pdb&#xA;write coor pdb  unit 30&#xA;close unit 30&#xA;&#xA;patch RN1 ARG 1&#xA;autogen angle dihe &#xA;ic build&#xA;coor build&#xA;&#xA;open write card unit 30 name arginine_neutral.pdb&#xA;write coor pdb  unit 30&#xA;&#xA;close unit 30&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-02-16T19:58:13.267" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12415" PostTypeId="1" CreationDate="2024-02-17T00:04:00.607" Score="3" ViewCount="60" Body="&lt;p&gt;I have a structure created in &lt;code&gt;pymatgen&lt;/code&gt; with the following properties:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pymatgen.core.structure import Structure&#xA;from pymatgen.symmetry.analyzer import SpacegroupAnalyzer&#xA;&#xA;lattice = [&#xA;    [ 2.465669985, 0.000000000,   0.000000000],&#xA;    [-1.232834994, 2.135332846,   0.000000000],&#xA;    [ 0.000000000, 0.000000000,   20.00000010],&#xA;]&#xA;&#xA;species = [&amp;quot;C&amp;quot;, &amp;quot;C&amp;quot;]&#xA;&#xA;coords = [&#xA;    [0.000000000, 0.000000000, 0.250000000],&#xA;    [0.333333333, 0.666666667, 0.250000000],&#xA;]&#xA;&#xA;structure = Structure(&#xA;    lattice=lattice,&#xA;    species=species,&#xA;    coords=coords,&#xA;)&#xA;sym = SpacegroupAnalyzer(structure)&#xA;_spg_data = sym.get_symmetry_dataset()&#xA;isg_number = _spg_data[&amp;quot;number&amp;quot;]&#xA;&#xA;print()&#xA;print(structure)&#xA;print(f&amp;quot;isg_number: {isg_number}&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which gives:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Full Formula (C2)&#xA;Reduced Formula: C&#xA;abc   :   2.465670   2.465670  20.000000&#xA;angles:  90.000000  90.000000 120.000000&#xA;Sites (2)&#xA;  #  SP           a         b     c&#xA;---  ----  --------  --------  ----&#xA;  0  C     0         0         0.25&#xA;  1  C     0.333333  0.666667  0.25&#xA;isg_number: 191&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am attempting to utilise the &lt;code&gt;space_group&lt;/code&gt; option for potential performance speed-up. In this I have two Q.E. files which I hope would give equivalent results; however, the final energies differ. In the first file I use &lt;code&gt;ibrav = 0&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation = 'scf'&#xA;    outdir = '/tmp/'&#xA;    prefix = 'graphene'&#xA;    pseudo_dir = 'pbe'&#xA;    restart_mode='from_scratch'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    ibrav = 0&#xA;    nat = 2, ntyp = 1,&#xA;    ecutwfc = 40.0 ,&#xA;    ecutrho = 400.0 ,&#xA;    occupations = 'smearing', degauss = 0.0001, smearing = 'marzari-vanderbilt'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr = 1.0d-10,&#xA;    mixing_beta = 0.3,&#xA;/&#xA;ATOMIC_SPECIES&#xA;C 12.01 C.upf&#xA;CELL_PARAMETERS angstrom&#xA;   2.465669985   0.000000000   0.000000000&#xA;  -1.232834994   2.135332846   0.000000000&#xA;   0.000000000   0.000000000   20.00000010&#xA;ATOMIC_POSITIONS crystal&#xA;C 0.000000000 0.000000000 0.250000000&#xA;C 0.333333333 0.666666667 0.250000000&#xA;K_POINTS automatic&#xA;12 12 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;In the second I use &lt;code&gt;space_group = 191&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;    calculation = 'scf'&#xA;    outdir = '/tmp/'&#xA;    prefix = 'graphene'&#xA;    pseudo_dir = 'pbe'&#xA;    restart_mode='from_scratch'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;    space_group = 191&#xA;    A = 2.465669985&#xA;    B = 2.465669985&#xA;    C = 20.00000010&#xA;    nat = 2, ntyp = 1,&#xA;    ecutwfc = 40.0 ,&#xA;    ecutrho = 400.0 ,&#xA;    occupations = 'smearing', degauss = 0.0001, smearing = 'marzari-vanderbilt'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;    conv_thr = 1.0d-10,&#xA;    mixing_beta = 0.3,&#xA;/&#xA;ATOMIC_SPECIES&#xA;C 12.01 C.upf&#xA;ATOMIC_POSITIONS crystal_sg&#xA;C 0.000000000 0.000000000 0.250000000&#xA;C 0.333333333 0.666666667 0.250000000&#xA;K_POINTS automatic&#xA;12 12 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the graphene example above, where layers are separated by a 20 A gap I get two very different crystal structures (see answers[1]). What has gone wrong, and how do I replicate the first example using &lt;code&gt;space_group&lt;/code&gt; as the option?&lt;/p&gt;&#xA;&lt;p&gt;[1][https://mattermodeling.stackexchange.com/questions/12410/translate-between-ibrav-and-space-group-quantum-espresso-inputs/12411?noredirect=1#comment27589_12411]&lt;/p&gt;&#xA;" OwnerUserId="786" LastActivityDate="2024-02-17T00:04:00.607" Title="How to use space_group for Quantum Espresso" Tags="|quantum-espresso|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12416" PostTypeId="2" ParentId="12412" CreationDate="2024-02-17T02:50:49.640" Score="7" Body="&lt;h1&gt;FCI (Full Configuration Interaction)&lt;/h1&gt;&#xA;&lt;p&gt;The FCI expansion of a wavefunction allows us to obtain the exact energy of a system given a basis set with &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; spatial orbitals. On a classical computer, for a singlet state with no spatial symmetry, if we have &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; spatial orbitals and &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; pairs of electrons, then we have &lt;span class=&quot;math-container&quot;&gt;${N \choose k}^2$&lt;/span&gt; Slater determinants in the FCI expansion of a wavefunction, and therefore &lt;span class=&quot;math-container&quot;&gt;${N \choose k}^2$&lt;/span&gt; parameters to optimize if we want to get the energy.&lt;/p&gt;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;${N \choose k}^2$&lt;/span&gt; is a multi-variable function, and isn't expressed explicitly as an &amp;quot;exponential&amp;quot; or &amp;quot;polynomial&amp;quot; in either of the two variables, I like to use the first set of inequalities in the &amp;quot;Bounds and asymptotic formulas&amp;quot; section of &lt;a href=&quot;https://en.wikipedia.org/wiki/Binomial_coefficient&quot; rel=&quot;noreferrer&quot;&gt;this page&lt;/a&gt; (my expressions below are the same, but with the square that I mentioned in my first paragraph):&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;\frac{N^{2k}}{k^{2k}} \le {N \choose k}^2 \le \frac{N^{2k}}{(k!)^2}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;For 10 electrons (one H2O molecular has 10 electrons, for example) we have &lt;span class=&quot;math-container&quot;&gt;$k=5$&lt;/span&gt; pairs of electrons, so my Eq. 1 becomes the following:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;\frac{1}{9765625}N^{10} \le {N \choose 5}^2 \le \frac{1}{14400}N^{10}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Although the denominator 9765625 looks large, since &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt; is usually at least double the size of &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;, we can see that the number of parameters that we have to optimize, which is &lt;span class=&quot;math-container&quot;&gt;${N \choose 5}^2$&lt;/span&gt;, is growing like a &lt;strong&gt;degree-10 polynomial of &lt;span class=&quot;math-container&quot;&gt;$N$&lt;/span&gt;&lt;/strong&gt;, divided by a comparatively small factor. This means that as we want more and more accurate energies (via basis sets with more  and more orbitals), the computational cost grows tremendously.&lt;/p&gt;&#xA;&lt;p&gt;Most systems of interest have far more than 10 electrons, and the above argument becomes stronger and stronger as we raise the number of pairs (denoted by &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt;) of electrons. This is also explained in answers to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/9495/5&quot;&gt;What are the limitations of FCI?&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;What can quantum computers do?&lt;/h2&gt;&#xA;&lt;p&gt;Table 1 of &lt;a href=&quot;https://journals.aps.org/prxquantum/pdf/10.1103/PRXQuantum.2.030305&quot; rel=&quot;noreferrer&quot;&gt;this paper&lt;/a&gt; shows that the space complexity (equivalent to the number of parameters that needed to be optimized in the above-described classical algorithm) on a quantum computer is &lt;strong&gt;linear&lt;/strong&gt; with respect to the number of orbitals:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/tC1fL.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/tC1fL.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Are we sure?&lt;/h2&gt;&#xA;&lt;p&gt;Just as we haven't proven whether or not P=NP, we also haven't proven whether or not NP = QMA, and many other things (see &lt;a href=&quot;https://quantumcomputing.stackexchange.com/q/2444/2293&quot;&gt;this answer of mine on QCSE&lt;/a&gt;). So when you say that &amp;quot;proven&amp;quot; means &amp;quot;mathematically demonstrated&amp;quot;, I want to emphasize that there is no &amp;quot;mathematical&amp;quot; proof that classical computers can't also do the above computation with O(N) complexity, but I think it's fair to say that it has been mathematically proven that quantum algorithms in the above table have a smaller quantum space complexity than the classical space complexity of the best known classical FCI algorithms.&lt;/p&gt;&#xA;&lt;p&gt;Finally, one thing about which I wish more quantum computing researchers were to be more honest, is the difference between &amp;quot;quantum space complexity&amp;quot; and &amp;quot;classical space complexity&amp;quot;. Right now I would rather have an algorithm that requires &lt;span class=&quot;math-container&quot;&gt;$2^N$&lt;/span&gt; classical bits than one that requires &lt;span class=&quot;math-container&quot;&gt;$N^2$&lt;/span&gt; qubits, and so would anyone that understands that even &lt;span class=&quot;math-container&quot;&gt;$10^2$&lt;/span&gt; qubits is less accessible than &lt;span class=&quot;math-container&quot;&gt;$2^{10}=1024$&lt;/span&gt; classical bits. I know that you touched on the difference between &amp;quot;mathematically demonstrated&amp;quot; vs &amp;quot;physically demonstrated&amp;quot;, but there is actually a mathematical difference in the power of a qubit vs a classical it, and there's also a mathematical difference in how hard they are to make: This touches on my notion of &amp;quot;engineering complexity&amp;quot; which I mentioned in my answer to &lt;a href=&quot;https://quantumcomputing.stackexchange.com/a/2019/2293&quot;&gt;this&lt;/a&gt; QCSE question.&lt;/p&gt;&#xA;&lt;h1&gt;VQE (Variational Quantum Eigensolver)&lt;/h1&gt;&#xA;&lt;p&gt;Since VQE is a hybrid algorithm that evaluates energy approximations on quantum computers and optimizes anstaz parameters on a classical computer, and since the number of ansatz parameters to optimize in FCI scales according to what I wrote in the first section in this answer, VQE does not seem to provide any advantage over classical computers for FCI. It has been discussed for other ansatze such as a &amp;quot;unitary coupled cluster&amp;quot; ansatz, but the benefits of using unitary coupled cluster ansatze (if any) over more tractable methods, are not as clear as the benefits of FCI over more tractable methods.&lt;/p&gt;&#xA;&lt;h1&gt;Conclusions&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Quantum computers can do FCI with O(N) quantum space complexity, for N orbitals. The best known classical algorithms for FCI scale much more severely.&lt;/li&gt;&#xA;&lt;li&gt;Quantum space complexity and classical space complexity are not the same thing, so we cannot fairly compare them &amp;quot;mathematically&amp;quot;.&lt;/li&gt;&#xA;&lt;li&gt;When we say that quantum computers can do FCI more efficiently than classical computers (assuming no difference between quantum computational complexity and classical computational complexity), VQE is not the algorithm in mind. VQE is a hybrid quantum/classical algorithm, and for FCI the classical part has the same asymptotic computational complexity as solving the FCI problem entirely on a classical computer would have.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-17T02:50:49.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12417" PostTypeId="2" ParentId="12346" CreationDate="2024-02-17T03:38:47.543" Score="4" Body="&lt;p&gt;The answer by E.I. Joe is quite informative, I just would like to extend on that a bit. Starting from the first row:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;N     : The number of electronic self-consistency iterations performed at the current ionic step.&#xA;E     : The total energy at the current electronic self-consistency iteration.&#xA;dE    : The change in total energy (E) between consecutive electronic self-consistency iterations.&#xA;d eps : The change in the charge density between consecutive electronic self-consistency iterations. it quantifies the convergence of the electronic structure or charge density.&#xA;ncg   : The number of conjugate-gradient (CG) iterations performed at the current electronic self-consistency iteration. CG iterations are used to solve the Kohn-Sham equations.&#xA;rms   : The root mean square (RMS) residual of the Kohn-Sham equations at the current electronic self-consistency iteration. This term quantifies the deviation of the electronic structure from self-consistency.&#xA;rms(c): The root mean square residual of the charge density at the current electronic self-consistency iteration.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Next lines stands for the method or algorithms used to solve the eigenvalue problem in the electronic structure calculations, in your case you have used &lt;code&gt;AlGO=fast&lt;/code&gt;, thus there is a comnination of &lt;code&gt;DAV&lt;/code&gt; which stands for Davidson diagonalization, and &lt;code&gt;RMM&lt;/code&gt; which stands for residual minimization method.&lt;/p&gt;&#xA;&lt;p&gt;Coming next is &lt;code&gt;g(F)&lt;/code&gt; and &lt;code&gt;g(S)&lt;/code&gt;, as mentioned in the Joe's answer, those are related to the convergence criteria for the ion relaxation process which is defined by you &lt;em&gt;via&lt;/em&gt; the &lt;code&gt;EDIFFG&lt;/code&gt; term in INCAR file. specifically, &lt;code&gt;g(F)&lt;/code&gt; stands for the convergence criterion for the forces acting on the ions, while &lt;code&gt;g(S)&lt;/code&gt; represents the convergence criterion for the ionic stress tensor. These criteria are used to determine when the ionic relaxation has converged.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;retain N&lt;/code&gt;: simply is an indicator for the number of electronic steps that were used to compute the electronic structure at the current ionic step. It shows how many steps were retained for the calculation.&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;mean eig&lt;/code&gt;: is the mean eigenvalue of the electronic Hamiltonian. It shows the average value of the eigenvalues of the occupied states (eig) at the current ionic step. Where  &lt;code&gt;eig&lt;/code&gt; are the eigenvalues of the occupied electronic states&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-02-17T03:38:47.543" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12418" PostTypeId="1" AcceptedAnswerId="12438" CreationDate="2024-02-17T08:31:08.287" Score="3" ViewCount="89" Body="&lt;p&gt;&amp;quot;I've determined the initial velocities of the surface following its equilibration at 300 K in the NVT ensemble. Now, I aim to conduct AIMD (NVE ensemble)with the metal surface (initially defined velocities from the equilibrating process at 300 K of the surface), the simulation involves a molecule approaching the surface at a certain distance with a specific kinetic energy. What strategies can I employ within VASP to ensure accurate control over these initial velocities in the simulation with NVE ensemble?&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/k6k02.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/k6k02.png&quot; alt=&quot;metal surface already equlibriate at 300K with NVT ensemble now H2 molecule coming with particule K.E. with NVE ensemble&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/PwsC4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/PwsC4.png&quot; alt=&quot;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="8414" LastEditDate="2024-02-20T10:14:33.343" LastActivityDate="2024-02-21T03:08:05.873" Title="Controlling Initial Velocities in NVE Trajectory Simulations with VASP" Tags="|vasp|molecular-dynamics|atomic-simulation-environment|aimd|vaspkit|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12419" PostTypeId="1" AcceptedAnswerId="12420" CreationDate="2024-02-18T16:26:45.143" Score="4" ViewCount="372" Body="&lt;p&gt;I used Autodock Vina and UCSF Chimera to perform blind and targeted docking on a protein from the RCSB database and a molecule I had optimized with Gaussian software.The results are as follows:&lt;br /&gt;&#xA;The targeted docking:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;Score= [-6,1 to -5,5], RMSD I.b=[0 to 2,892], RMSD U.b=[0 to 7,275]&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The blind docking:&lt;br /&gt;&#xA;&lt;code&gt;Score= [-7,1 to -6,1], RMSD I.b=[0 to 2,343], RMSD U.b=[0 to 3,565]&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The results of blind docking indicate that the ligand is attracted to the protein outside the target docking box.&lt;br /&gt;&#xA;Does this mean that the ligand can't interact with the protein in the target docking region or box?&#xA;Can I consider the results of the targeted docking while also considering the results of the blind docking?&lt;/p&gt;&#xA;" OwnerUserId="4401" LastEditorUserId="5" LastEditDate="2024-02-18T16:44:06.637" LastActivityDate="2024-02-18T16:44:06.637" Title="Blind docking and targeted docking" Tags="|molecular-modeling|proteins|docking|autodock|chimera-software|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12420" PostTypeId="2" ParentId="12419" CreationDate="2024-02-18T16:43:37.707" Score="4" Body="&lt;p&gt;If you already know where the active site of your protein is, there is no need to run a blind docking. Because the ligand binds to the protein, it doesn't imply that it can have any inhibitory action.&lt;/p&gt;&#xA;&lt;p&gt;If you run blind docking, it is supposed that all the target surfaces are available, and all of them need to be inside the search box. If your ligand got bound to the protein outside the target docking box, you can always do another run with the smallest box just around the region you obtained from the first run.&#xA;About the second question, look for the biochemistry of the target protein. The site where your ligand bond is important to protein activity? The binding induces modifications in the active site of the protein (closing/opening it) or in the co-factor area (if any)?.&lt;/p&gt;&#xA;&lt;p&gt;Again, not because a ligan bound to the surface of the protein has any biochemistry importance.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-18T16:43:37.707" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12421" PostTypeId="1" AcceptedAnswerId="12432" CreationDate="2024-02-19T05:48:32.157" Score="4" ViewCount="74" Body="&lt;p&gt;I am a beginner in CASTEP simulation and I need some guidance on the general steps for geometry optimization. I have tried the following three approaches:&lt;/p&gt;&#xA;&lt;p&gt;(1) Build unit cell &amp;gt; geometry optimization &amp;gt; cleave &amp;gt; supercell &amp;gt; optimize again&amp;gt; band structure and optical calculation&#xA;(2) Build unit cell &amp;gt; geometry optimization &amp;gt; cleave &amp;gt; supercell &amp;gt; band structure and optical calculation&#xA;(3) Build unit cell &amp;gt; geometry optimization &amp;gt; band structure and optical calculation&lt;/p&gt;&#xA;&lt;p&gt;However, I encountered some problems with each of them. For (1), the simulation runs indefinitely. For (2), after optimizing, cleaving and creating a supercell, I get an error message when I attempt to run band structure and optical calculation: &amp;quot;There are no CASTEP input or output files available. CASTEP input and output files from a previous run are required in order to perform a properties run.&amp;quot; For (3), everything works fine but this is only for a unit structure and not a supercell.&lt;/p&gt;&#xA;&lt;p&gt;Can you please advise me on how to proceed?&lt;/p&gt;&#xA;" OwnerUserId="8827" LastActivityDate="2024-02-19T22:20:41.307" Title="Help with Geometry Optimization in CASTEP" Tags="|density-functional-theory|computational-chemistry|castep|materials-studio|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12422" PostTypeId="2" ParentId="2278" CreationDate="2024-02-19T08:16:35.117" Score="3" Body="&lt;h1&gt;WEAS-widget&lt;/h1&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://github.com/superstar54/weas-widget&quot; rel=&quot;nofollow noreferrer&quot;&gt;WEAS&lt;/a&gt; (Web Environment For Atomistic Structure). A widget to visualize and edit atomistic structures in Jupyter Notebook.&lt;/p&gt;&#xA;&lt;h2&gt;Edit the structure directly in the GUI.&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GuLHh.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GuLHh.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;h2&gt;Crystal view&lt;/h2&gt;&#xA;&lt;p&gt;For a nice visualization of a crystal, one usually shows the polyhedra and the atoms on the unit cell boundary, as well as the bonded atoms outside the cell.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/eKpW2.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eKpW2.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="4562" LastActivityDate="2024-02-19T08:16:35.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12423" PostTypeId="1" AcceptedAnswerId="12431" CreationDate="2024-02-19T11:27:57.753" Score="5" ViewCount="888" Body="&lt;p&gt;I would like to draw the following structures:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/woar7.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/woar7.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;How many I do it?&lt;/p&gt;&#xA;" OwnerUserId="7324" LastEditorUserId="5" LastEditDate="2024-02-19T15:39:54.047" LastActivityDate="2024-02-19T22:03:25.210" Title="How may I reproduce chemical structure drawings?" Tags="|visualization-software|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12424" PostTypeId="1" CreationDate="2024-02-19T15:46:58.703" Score="3" ViewCount="70" Body="&lt;p&gt;I was performing a vc-relax calculation in Quantum ESPRESSO. I have 18 SCF cycles that have been already completed, but my PC just shuts up because of an energy blackout. Is there any form to restart my calculation from some type of &lt;em&gt;checkpoint&lt;/em&gt;?&lt;/p&gt;&#xA;&lt;p&gt;I put in my input file the line &lt;code&gt;restart_mode = &amp;quot;from_scratch&amp;quot;&lt;/code&gt; but I don't know if that is sufficient.&lt;/p&gt;&#xA;&lt;p&gt;Thanks for your help.&lt;/p&gt;&#xA;" OwnerUserId="8832" LastEditorUserId="6055" LastEditDate="2024-02-19T17:52:52.203" LastActivityDate="2024-02-19T17:52:52.203" Title="How to restart calculation in Quantum ESPRESSO?" Tags="|quantum-espresso|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12425" PostTypeId="2" ParentId="12424" CreationDate="2024-02-19T16:12:08.880" Score="3" Body="&lt;h1&gt;Short answer:&lt;/h1&gt;&#xA;&lt;p&gt;No, using &lt;code&gt;restart_mode = &amp;quot;from_scratch&amp;quot;&lt;/code&gt; will not work for your purpose. The calculation needs to be started from the beginning.&lt;/p&gt;&#xA;&lt;h1&gt;Why &lt;code&gt;restart_mode = &amp;quot;from_scratch&amp;quot;&lt;/code&gt; will not work:&lt;/h1&gt;&#xA;&lt;p&gt;This means that the calculation will be started from the very beginning even if there exists an interrupted earlier calculation. Maybe what you are looking for is &lt;code&gt;restart_mode = &amp;quot;restart&amp;quot;&lt;/code&gt; which is used to continue previous interrupted run. However, this too will not work in your case since this requires that the previous calculation has been stopped &lt;em&gt;cleanly&lt;/em&gt;. That means during the run, if you create a file &lt;code&gt;your_prefix.EXIT&lt;/code&gt; in the &lt;code&gt;outdir&lt;/code&gt; directory, the calculation terminates but saves the charge density, wavefunction, and other info. But in your case, it was due to power shut down, so the calculation stopped abruptly and the files are almost certainly corrupted. More about the usage of &lt;code&gt;restart_mode&lt;/code&gt; switch can be found in &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm65&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h1&gt;What you can do now:&lt;/h1&gt;&#xA;&lt;p&gt;You can use these two switches &lt;code&gt;startingpot=&amp;quot;file&amp;quot;&lt;/code&gt; and &lt;code&gt;startingwfc=&amp;quot;file&amp;quot;&lt;/code&gt; in your input file within the &lt;code&gt;&amp;amp;ELECTRON&lt;/code&gt; namelist. By doing so, the code will not guess an initial charge density and wavefunction from atomic superposition or random guess. Instead the code will try to use the last found charge density and wavefunction from your &lt;code&gt;outdir&lt;/code&gt; (if it exists). It might give you some time advantages. In any case, the calculation type (spin polarized/unpolarized), the &lt;code&gt;outdir&lt;/code&gt; and the &lt;code&gt;prefix&lt;/code&gt; must be the same but you can use different parallelization levels here (you cannot change anything at all in case of &lt;code&gt;restart_mode=&amp;quot;restart&amp;quot;&lt;/code&gt;).&lt;/p&gt;&#xA;&lt;h1&gt;Caveat:&lt;/h1&gt;&#xA;&lt;p&gt;I cannot guaranty that the above-mentioned suggestion will give you time advantage because it doesn't always work. I am not sure about the reason but sometimes starting from an existing wavefunction takes much more time to converge than the default one takes. My personal experience says that the first iteration of the SCF loop will take longer to converge but rest of them will be a little faster if you use &lt;code&gt;startingwfc&lt;/code&gt; and &lt;code&gt;startingpot&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2024-02-19T17:50:59.327" LastActivityDate="2024-02-19T17:50:59.327" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12426" PostTypeId="2" ParentId="12423" CreationDate="2024-02-19T17:56:19.527" Score="6" Body="&lt;p&gt;In order to draw those chemical structures with &lt;a href=&quot;/questions/tagged/visualization-software&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;visualization-software&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;visualization-software&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-visualization-software-tooltip-container&quot;&gt;visualization-software&lt;/a&gt;, the software needs to know (or be able to calculate) the coordinates of each type of nucleus.&lt;/p&gt;&#xA;&lt;p&gt;Usually the software would be provided with an XYZ file, for example if the molecule is pyridine, an appropriate XYZ file would be the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C       -0.180226841      0.360945118     -1.120304970&#xA;C       -0.180226841      1.559292118     -0.407860970&#xA;C       -0.180226841      1.503191118      0.986935030&#xA;N       -0.180226841      0.360945118      1.29018350&#xA;C       -0.180226841     -0.781300882      0.986935030&#xA;C       -0.180226841     -0.837401882     -0.407860970&#xA;H       -0.180226841      0.360945118     -2.206546970&#xA;H       -0.180226841      2.517950118     -0.917077970&#xA;H       -0.180226841      2.421289118      1.572099030&#xA;H       -0.180226841     -1.699398882      1.572099030&#xA;H       -0.180226841     -1.796059882     -0.917077970&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;With this information, the software knows where to put each nucleus, and what color to make each nucleus.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;/questions/tagged/avogadro&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;avogadro&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;avogadro&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-avogadro-tooltip-container&quot;&gt;avogadro&lt;/a&gt; is a free and open source software that can make figures like the ones in your question. My research group has primarily been using Avogadro to make such figures: We have had issues with making vector format PDF or SVG files with transparent backgrounds, but the software is free and open source and does well for the most part. If you look at the &lt;a href=&quot;/questions/tagged/visualization-software&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;visualization-software&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;visualization-software&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-visualization-software-tooltip-container&quot;&gt;visualization-software&lt;/a&gt; tag, you will see that many other computers programs can also be used as alternatives. We have also used GaussView, VMD and some other visualization programs.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-19T17:56:19.527" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12427" PostTypeId="1" CreationDate="2024-02-19T19:57:27.663" Score="6" ViewCount="141" Body="&lt;p&gt;I would like to display MOPAC geometry trajectories for structure minimization and transition state searching.&lt;/p&gt;&#xA;&lt;p&gt;Is there a simple way to achieve that ? Avogadro can display only final geometry from MOPAC output file.&lt;/p&gt;&#xA;&lt;p&gt;Avogadro has the &amp;quot;animate&amp;quot; feature, but it needs all the xyz geometry files. How to get them from MOPAC ? I see no keyword for that &lt;a href=&quot;http://openmopac.net/manual/allkeys.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="114" LastEditorUserId="5" LastEditDate="2024-02-19T20:41:16.857" LastActivityDate="2024-02-19T21:58:57.233" Title="MOPAC: Is there a simple way to display geometry trajectories" Tags="|molecular-modeling|geometry-optimization|avogadro|semi-empirical-method|mopac|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12428" PostTypeId="5" CreationDate="2024-02-19T20:41:56.737" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/MOPAC&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/MOPAC&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-02-19T20:41:56.737" LastActivityDate="2024-02-19T20:41:56.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12429" PostTypeId="4" CreationDate="2024-02-19T20:41:56.737" Score="0" Body="Questions about MOPAC, the semi-empirical quantum chemistry software." OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-02-19T20:41:56.737" LastActivityDate="2024-02-19T20:41:56.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12430" PostTypeId="2" ParentId="12427" CreationDate="2024-02-19T21:58:57.233" Score="6" Body="&lt;p&gt;I created a Python script to manipulate the MOPAC output, saving a XYZ file with all the structures from the optimization step. Then, the XYZ can be loaded into Jmol software and do the animation. The steps are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Add the following keywords to the MOP file: AUX(6,COMP, XP, XS, XW)&lt;/li&gt;&#xA;&lt;li&gt;Run as &amp;quot;mopac fname_root.mop &amp;gt; fname_root.log&amp;quot;&lt;/li&gt;&#xA;&lt;li&gt;Edit the Jupiter notebook variable &amp;quot;fname_root&amp;quot; accordingly OR add the &amp;quot;fname_root&amp;quot; as an argument to the script.&lt;/li&gt;&#xA;&lt;li&gt;Running the script/notebook will create an XYZ file with the structure of each optimization step. This file can be visualized using Jmol (an animation can be done)&lt;/li&gt;&#xA;&lt;li&gt;A file &amp;quot;fname_root.dat&amp;quot; is created with two columns: optimization_step energy, useful to analyze the energy of the system at each optimization step.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Note: If using AUX(5,COMP, XP, XS, XW) keyword, a file with the optimization steps will be created automatically with the name: fname_opt.aux (this file has the same structure as &amp;quot;fname_root.log&amp;quot;&lt;/p&gt;&#xA;&lt;p&gt;You can download the scripts from &lt;a href=&quot;https://github.com/icamps/MoPy&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Also, I share below a bash script to create the movie after exporting each frame as an image file. This script is intended to be run in a folder where the XYZ files are located (as it is, it will do a batch job creating a movie from each of the XYZ files). Don't forget to change the metadata for the movie!&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#!/bin/bash&#xA;#&#xA;# Script to create MP4 movies from XYZ trajectory files.&#xA;#&#xA;#&#xA;&#xA;rm trajectorymovie.jmol 2&amp;gt; /dev/null&#xA;cat &amp;gt; trajectorymovie.jmol &amp;lt;&amp;lt;!&#xA;frank off&#xA;background white&#xA;set ambient 10; set diffuse 60; set specular 70&#xA;frame 1&#xA; num_frames = getProperty(&amp;quot;modelInfo.modelCount&amp;quot;)&#xA; for (var i = 1; i &amp;lt;= num_frames; i = i+1)&#xA;   var filename = &amp;quot;movie-&amp;quot;+(&amp;quot;0000&amp;quot;+i)[-3][0]+&amp;quot;.jpg&amp;quot;&#xA;   write IMAGE 732 616 JPG @filename&#xA;   frame next&#xA; end for&#xA;!&#xA;&#xA;for filename in *.xyz; do&#xA;&#xA;   extension=&amp;quot;&lt;span class=&quot;math-container&quot;&gt;${filename##*.}&quot;&#xA;   filenamem1=$&lt;/span&gt;(basename &amp;quot;&lt;span class=&quot;math-container&quot;&gt;$filename&quot;)&#xA;   filenamem=&quot;$&lt;/span&gt;{filenamem1%.*}&amp;quot;&#xA;   filenamem2=&lt;span class=&quot;math-container&quot;&gt;$(basename &quot;$&lt;/span&gt;filenamem&amp;quot;)&#xA;   filenamem3=&amp;quot;${filenamem2%.*}&amp;quot;&#xA;&#xA;&#xA;   mkdir out_&lt;span class=&quot;math-container&quot;&gt;${filenamem}&#xA;   cd out_$&lt;/span&gt;{filenamem}&#xA;   ln -s ../${filename} .&#xA;&#xA;   jmol &lt;span class=&quot;math-container&quot;&gt;${filename} -b -L -n -s ../trajectorymovie.jmol&#xA;   ffmpeg -framerate 100 -i movie-%04d.jpg -c:v libx264 -map_metadata -1 -metadata title=&quot;$&lt;/span&gt;{filenamem}&amp;quot; -metadata author=&amp;quot;I. Camps&amp;quot; -metadata year=&amp;quot;2024&amp;quot; -pix_fmt yuv420p &lt;span class=&quot;math-container&quot;&gt;${filenamem}.mp4&#xA;   zip -9 -m Frames_$&lt;/span&gt;{filenamem}.zip *.jpg&#xA;   cd ..    &#xA;done&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-19T21:58:57.233" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12431" PostTypeId="2" ParentId="12423" CreationDate="2024-02-19T22:03:25.210" Score="6" Body="&lt;p&gt;Following the answer by @NikeDattani, you can also search the Wikipage for each compound and look for this part (this is for &lt;a href=&quot;https://en.wikipedia.org/wiki/Lithium_sulfide&quot; rel=&quot;noreferrer&quot;&gt;Li2S&lt;/a&gt;):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/UWuiY.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/UWuiY.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;There you will find the links for databases with information about the compound and usually the 3D structure file is available to download.&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-19T22:03:25.210" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12432" PostTypeId="2" ParentId="12421" CreationDate="2024-02-19T22:20:41.307" Score="5" Body="&lt;p&gt;If you are running only geometry optimization for a single crystal periodic structure, the third step:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(3) Build unit cell &amp;gt; geometry optimization &amp;gt; band structure and optical calculation&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;will be ok.&lt;/p&gt;&#xA;&lt;p&gt;There is no need to create a supercell for calculation related to the single crystal periodic system: there is no gain in accuracy, and you will face issues with band folding (that, for me, are hard to handle).&lt;/p&gt;&#xA;&lt;p&gt;If you are running surface calculations, then you really need a supercell. Both steps you propose are valid:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;(1) Build unit cell &amp;gt; geometry optimization &amp;gt; cleave &amp;gt; supercell &amp;gt;&#xA;optimize again&amp;gt; band structure and optical calculation&lt;br /&gt;&#xA;(2) Build unit cell &amp;gt; geometry optimization &amp;gt; cleave &amp;gt; supercell &amp;gt; band structure and &amp;gt; optical calculation&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But there is no need to run double optimization, i.e., optimizing the unit cell. There are some packages (like &lt;a href=&quot;https://sourceforge.net/projects/cif2cell/&quot; rel=&quot;noreferrer&quot;&gt;CIF2Cell&lt;/a&gt;) that create the supercell from the CIF file.&lt;/p&gt;&#xA;&lt;p&gt;If a simulation runs indefinitely, this indicates two things:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The converge criteria is too tight (a very lower value) or&lt;/li&gt;&#xA;&lt;li&gt;The number of steps for the self consistence calculations is too high.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Finally, the errors about band structure and optical calculation maybe related with you trying to do those calculations in bad converged structures (there can be a keyword to allow this), bad Brillouin path selection and/or invalid number of k points (as you move from single crystal to a supercell, the Brillouin path changed).&lt;/p&gt;&#xA;" OwnerUserId="24" LastActivityDate="2024-02-19T22:20:41.307" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12433" PostTypeId="1" CreationDate="2024-02-20T03:29:16.180" Score="3" ViewCount="43" Body="&lt;p&gt;I would like to know how I can get the graph below. In most of the papers, they got stress-strain curves like in picture (1):&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/rHhpe.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/rHhpe.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, my stress-strain curve of 2D graphene-like material is shown in picture (2):   How can they get these results? Are there any tricks or what?&#xA;For more information, I did everything to get this picture (2), but I could not do that&lt;br /&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/TbXfM.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/TbXfM.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7312" LastEditorUserId="5" LastEditDate="2024-02-20T13:22:37.627" LastActivityDate="2024-02-20T13:22:37.627" Title="How to calculate Stress-strain curve of graphene or any 2D materials (including elastic and plastic region)" Tags="|stress-strain|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12434" PostTypeId="2" ParentId="12295" CreationDate="2024-02-20T09:24:07.110" Score="7" Body="&lt;p&gt;dear Prof. Susi Lehtola,&lt;/p&gt;&#xA;&lt;p&gt;Recently I write two utilities &lt;code&gt;molden2fch&lt;/code&gt; and &lt;code&gt;fch2tm&lt;/code&gt; in &lt;a href=&quot;https://gitlab.com/jxzou/mokit&quot; rel=&quot;noreferrer&quot;&gt;MOKIT&lt;/a&gt;. The MOKIT documentation has not been updated. &lt;code&gt;molden2fch&lt;/code&gt; converts a .molden file into a Gaussian .fch file. And &lt;code&gt;fch2tm&lt;/code&gt; converts a Gaussian .fch(k) file into Turbomole files &lt;code&gt;control&lt;/code&gt; and &lt;code&gt;mos&lt;/code&gt;. Combining &lt;code&gt;molden2fch&lt;/code&gt; with the existing utility &lt;code&gt;fch2qchem&lt;/code&gt;, molecular orbitals can be transferred from Turbomole to Q-Chem. Let's look at a simple example:&lt;/p&gt;&#xA;&lt;p&gt;assuming an RHF/cc-pVDZ calculation for a water molecule has been performed using Turbomole, and files &lt;code&gt;control&lt;/code&gt; as well as &lt;code&gt;mos&lt;/code&gt; are in the current directory, then we can type&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;tm2molden&#xA;h2o.molden&#xA;[Enter]&#xA;[Enter]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;code&gt;tm2molden&lt;/code&gt; is a utility of Turbomole. After h2o.molden is generated, run the following commands&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;molden2fch h2o.molden -tm&#xA;fch2qchem h2o.fch&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;molden format strongly depends on its corresponding quantum chemistry program, so &lt;code&gt;-tm&lt;/code&gt; is specified to tell the utility that this is a Turbomole-type .molden file (By the way, this utility also supports &lt;code&gt;-orca&lt;/code&gt; where ORCA-type .molden file can be dealt with).&lt;/p&gt;&#xA;&lt;p&gt;I've tested the two new utilities using Turbomole v7.1. For &lt;code&gt;molden2fch&lt;/code&gt;/&lt;code&gt;fch2tm&lt;/code&gt;, basis functions up to g/h angular momenta are supported, respectively. &lt;code&gt;tm2molden&lt;/code&gt; cannot generate .molden file beyond g angular momentum. Please install or update to MOKIT-v1.2.6rc23 if you want to use new utilities.&lt;/p&gt;&#xA;&lt;p&gt;There are two extra limitations for &lt;code&gt;molden2fch&lt;/code&gt;: 1) Cartesian-type (6D 10F) function are not supported currently, please use spherical harmonic (5D 7F) functions; 2) ECP/PP are not supported since there is no ECP/PP data in .molden file generated by Turbomole.&lt;/p&gt;&#xA;&lt;p&gt;If you and your colleague want more features, or you encounter some questions during using these utilities, you can open an issue &lt;a href=&quot;https://gitlab.com/jxzou/mokit/-/issues&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5172" LastActivityDate="2024-02-20T09:24:07.110" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12435" PostTypeId="1" CreationDate="2024-02-20T17:56:37.747" Score="4" ViewCount="40" Body="&lt;p&gt;I am completely new to material modelling. I am trying to calculate phonon frequency at X point for Aluminium fcc.&lt;/p&gt;&#xA;&lt;p&gt;I picked an fcc lattice and displaced the atoms at x=0 by (+0.1) and those in x=0.5 by (-0.1) along the z direction. I calculate energy for different values and try to fit a quadratic curve on it. This allows to measure &lt;span class=&quot;math-container&quot;&gt;$k$&lt;/span&gt; so that:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\omega = \sqrt{\frac{k}{2m}}$$&lt;/span&gt;&#xA;Because I have two atoms. The results I find are completely wrong.&lt;/p&gt;&#xA;&lt;p&gt;Here is my code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;    calculation='scf'&#xA;    restart_mode='from_scratch',&#xA;    pseudo_dir='./',&#xA;    prefix='Al'&#xA;    tstress = .false.&#xA;    tprnfor = .false.&#xA;/&#xA;&amp;amp;system&#xA;   ibrav = 2&#xA;   celldm(1) = 7.631664 &#xA;   nat = 2&#xA;   ntyp = 1&#xA;   ecutwfc = 40&#xA;   ecutrho = 160&#xA;/&#xA;&amp;amp;electrons&#xA;&#xA;    conv_thr = 1.0e-10&#xA;/&#xA;ATOMIC_SPECIES&#xA;  Al   26.98100  Al.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS {crystal}&#xA;Al   0.000000000000000   0.000000000000000   0.0100000000000&#xA;Al   0.500000000000000   0.500000000000000   -0.0100000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Thank you very much for you help&lt;/p&gt;&#xA;" OwnerUserId="8838" LastEditorUserId="1554" LastEditDate="2024-02-21T02:10:51.493" LastActivityDate="2024-02-21T02:11:35.733" Title="Simple Quantum Espresso-Phonon" Tags="|density-functional-theory|quantum-espresso|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12436" PostTypeId="1" CreationDate="2024-02-20T19:34:06.077" Score="4" ViewCount="35" Body="&lt;p&gt;Let me explain. I found that the structure for TiFeSi given in the ICSD database using Jsmol software is a little different from what can be obtained using Vesta software using the same cif file downloaded from the ICSD data base. Some atoms in the Vesta plot are missing e.g. Si (corresponding to the Si1 and Ti3 in the Jsmol plot)&#xA;&lt;a href=&quot;https://i.stack.imgur.com/iVdiF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iVdiF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;Is it a glitch or bug of Vesta or these two representations are just the same? If they are just the same then how?&lt;/p&gt;&#xA;" OwnerUserId="2104" LastActivityDate="2024-02-20T19:34:06.077" Title="Which one of the following showing the correct structure Jsmol or Vesta? Or they are just same" Tags="|computational-chemistry|software|vesta|databases|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12437" PostTypeId="2" ParentId="12435" CreationDate="2024-02-21T02:11:35.733" Score="1" Body="&lt;p&gt;ibrav=2 means that your lattice is fcc, i.e. if you put an Al atom at (0,0,0) , then three Al atoms are put at (1/2,1/2,0), (1/2,0,1/2), (0,1/2,1/2) &lt;em&gt;automatically&lt;/em&gt;. Thus your input means that Al1 is at (1/2,1/2,0.01) and Al2 is at (1/2,1/2,-0.01). It may cause CRASH.&lt;/p&gt;&#xA;&lt;p&gt;For your purpose I recommend to see UserGuide and to perform ph.x with single k-point mode.&lt;/p&gt;&#xA;" OwnerUserId="8840" LastActivityDate="2024-02-21T02:11:35.733" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12438" PostTypeId="2" ParentId="12418" CreationDate="2024-02-21T03:08:05.873" Score="2" Body="&lt;p&gt;As I understand in your question, you want to perform AIMD with NVE ensemble. Based on VASP documentation, it is recommened to set &lt;code&gt;MDALGO=1&lt;/code&gt; and  &lt;code&gt;ANDERSEN_PROB=0.0&lt;/code&gt; for this type of ensemble, you can refer to &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NVE_ensemble&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP wiki&lt;/a&gt; for further read.&lt;/p&gt;&#xA;&lt;p&gt;The following is an example of AIMD tags with NVE ensemble:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; #INCAR molecular-dynamics tags NVE ensemble &#xA; IBRION = 0                   # choose molecular-dynamics &#xA; MDALGO = 1                   # using Andersen thermostat&#xA; ISIF = 2                     # compute stress tensor but do not change box volume/shape &#xA; TEBEG = 300                  # set temperature &#xA; NSW = 10000                  # number of time steps &#xA; POTIM = 1.0                  # time step in femto seconds &#xA; ANDERSEN_PROB = 0.0          # setting Andersen collision probability to zero to get NVE enseble&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Regarding the control of velocities during the AIMD run, the &lt;code&gt;SMASS&lt;/code&gt; tag will control that after you provide the initail velocities in your POSCAR file. In your INCAR file, you have chosen &lt;code&gt;SMASS=-3&lt;/code&gt;, which is a microcanonical ensemble (NVE ensemble). In this ensemble, the calculated Hellmann-Feynman forces serve as an acceleration acting onto the ions thus you would expect the velocities to be updated as you mentioned. On the other hand, the total free energy (i.e. free electronic energy + Madelung energy of ions + kinetic energy of ions) is conserved.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-02-21T03:08:05.873" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12439" PostTypeId="1" CreationDate="2024-02-21T09:56:58.377" Score="3" ViewCount="32" Body="&lt;p&gt;I have a test &lt;a href=&quot;https://pastebin.com/0FEsufzD&quot; rel=&quot;nofollow noreferrer&quot;&gt;structure factor dataset&lt;/a&gt; from water O-O pairs and I am trying to get the &lt;span class=&quot;math-container&quot;&gt;$g_{OO}(r)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;           q     Norm2     err_norm2&#xA;0     7.027826 -0.323588  3.433183e-06&#xA;1     7.120845 -0.324964  3.401932e-06&#xA;2     7.213864 -0.326260  3.386715e-06&#xA;3     7.306882 -0.327475  3.385868e-06&#xA;4     7.399901 -0.328610  3.397331e-06&#xA;..         ...       ...           ...&#xA;995  99.581420  0.007117  9.849377e-07&#xA;996  99.674430  0.006839  9.836154e-07&#xA;997  99.767450  0.006558  9.822502e-07&#xA;998  99.860470  0.006274  9.808368e-07&#xA;999  99.953490  0.005988  9.793699e-07&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; is the scattering vector in nm&lt;span class=&quot;math-container&quot;&gt;$^{-3}$&lt;/span&gt; and Norm2 is the scattering factor (with normalization factor II; not sure if relevant at all). Using python&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;dataFile=&amp;quot;ref_sfac_OO.csv&amp;quot;&#xA;header = (pandas.read_csv(dataFile, sep=';', nrows=0).columns.str.strip('#')).str.strip()&#xA;refDataDf=pandas.read_csv(dataFile, comment=&amp;quot;#&amp;quot;,delimiter=&amp;quot;;&amp;quot;,names=header)&#xA;plt.plot(refDataDf.q,refDataDf.Norm2)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the plot is:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/xPE2L.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xPE2L.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am trying to recreate the &lt;span class=&quot;math-container&quot;&gt;$g_{OO}(r)$&lt;/span&gt; RDF using the following expression from &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article-abstract/138/7/074506/192798/Benchmark-oxygen-oxygen-pair-distribution-function?redirectedFrom=fulltext&quot; rel=&quot;nofollow noreferrer&quot;&gt;Skinner2013&lt;/a&gt; equation 9:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$g(r)=1+\frac{1}{2\pi^2\rho r}\int^{Q_{Max}}_0 \text{Lorch}(q)\times q [S(q)-1]\times \sin(q r)dq$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\text{Lorch}(q)$&lt;/span&gt; is a Lorch-type normalization factor which I have kept as 1 for testing and &lt;span class=&quot;math-container&quot;&gt;$\rho=0.0033\,Å^{−3}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The python code for the above expression is:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;qArray = np.array(refDataDf.q)/10 # converting to angstrom&#xA;rArray = 2*np.pi/refDataDf.q*10 # converting to angstrom&#xA;dq = qArray[1] - qArray[0]&#xA;h_q = refDataDf.Norm2 # Original : h_q = refDataDf.Norm2 - 1&#xA;g=np.zeros_like(rArray)&#xA;&#xA;for r_idx,r in enumerate(rArray):&#xA;&#xA;    g[r_idx]=1+1/(2*np.pi**2*r*0.033)*np.sum([q*h_q[q_idx]*np.sin(q*r)*dq for q_idx, q in enumerate(qArray)])&#xA;&#xA;plt.plot(rArray, g)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ZSXGT.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ZSXGT.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;But I am unable to get the correct behavior of the &lt;span class=&quot;math-container&quot;&gt;$g_{OO}(r)$&lt;/span&gt; RDF (incorrect 1st RDF height peak, almost absent second and beyond peaks). Does anyone have any suggestions on whether my formulation above is correct or should I use a different idea?&lt;/p&gt;&#xA;" OwnerUserId="1151" LastActivityDate="2024-02-21T09:56:58.377" Title="Obtaining RDF from provided structure factor" Tags="|python|structure|radial-distribution-function|x-ray-diffraction|fourier-transform|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12440" PostTypeId="1" CreationDate="2024-02-21T11:45:56.667" Score="7" ViewCount="299" Body="&lt;p&gt;Does anyone know in which of the DOS output files I can find the band gap energy value of my material? I'm using Quantum ESPRESSO.&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="6055" LastEditDate="2024-02-21T13:00:54.487" LastActivityDate="2024-02-21T13:22:42.730" Title="How to find the band gap energy value in Quantum ESPRESSO?" Tags="|quantum-espresso|bandgap|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12441" PostTypeId="2" ParentId="12440" CreationDate="2024-02-21T13:22:42.730" Score="8" Body="&lt;p&gt;If you are treating your material as a non-metal (i.e. not using any &lt;code&gt;smearing&lt;/code&gt; and using &lt;code&gt;occupations='fixed'&lt;/code&gt;), then you can get the band gap value directly from the output of the SCF calculation. You need to use the &lt;code&gt;nbnd&lt;/code&gt; switch in the SCF input file and then in the output file, you will have a line something like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; highest occupied, lowest unoccupied level (ev):    5.1143 5.8455&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The difference between them is the band gap. For example, in the above-mentioned case, the band gap is &lt;span class=&quot;math-container&quot;&gt;$(5.8455 - 5.1143) \mathrm{\;eV} = 0.7312 \mathrm{\;eV} $&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;However, in case you treated your material as a metal (i.e. you used &lt;code&gt;occupations='smearing'&lt;/code&gt;) to achieve the convergence faster whereas it is actually a material with a band gap, then from inspecting the DOS output file, you can extract the band gap value.&lt;/p&gt;&#xA;&lt;p&gt;First, open the data file produced by the &lt;code&gt;dos.x&lt;/code&gt; calculation. The name of the data file is set in the input file as the value of the &lt;code&gt;fildos&lt;/code&gt; switch. If you didn't define the name of the file explicitly, then by default look for the &lt;code&gt;prefix.dos&lt;/code&gt; file. It will contain three columns for a spin-unpolarized (four for spin-polarized) calculation with the first row being:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#  E (eV)   dosup(E)     dosdw(E)   Int dos(E) EFermi =    5.670 eV&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Around the Fermi level value, you will notice all the subsequent dos values are zero. Note the energy values where the first zero dos value occurs. Then scroll below further and note where the first non-zero dos value occurs again. Take the difference between these two energy value which will give you the band gap. For example, if I have a file like:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#  E (eV)   dosup(E)     dosdw(E)   Int dos(E) EFermi =    5.670 eV&#xA;...&#xA;...&#xA;   5.768  0.1976E-01  0.2202E-01  0.5840E+03&#xA;   5.778  0.3176E-02  0.3274E-02  0.5840E+03&#xA;   5.788  0.7654E-03  0.8099E-03  0.5840E+03&#xA;   5.798  0.1230E-04  0.1696E-04  0.5840E+03&#xA;   5.808  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   5.818  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   5.828  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   5.838  0.0000E+00  0.0000E+00  0.5840E+03&#xA;...&#xA;...&#xA;   7.408  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   7.418  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   7.428  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   7.438  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   7.448  0.0000E+00  0.0000E+00  0.5840E+03&#xA;   7.458  0.1580E-04  0.1575E-04  0.5840E+03&#xA;   7.468  0.9316E-04  0.9306E-04  0.5840E+03&#xA;   7.478  0.2350E-03  0.2348E-03  0.5840E+03&#xA;...&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The band gap is in this case: &lt;span class=&quot;math-container&quot;&gt;$(7.458 - 5.808) \mathrm{\;eV} = 1.95 \mathrm{\;eV} $&lt;/span&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-02-21T13:22:42.730" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12442" PostTypeId="1" CreationDate="2024-02-21T14:19:35.627" Score="2" ViewCount="29" Body="&lt;p&gt;I have the following error in the design of reactor in Aspen+.&lt;/p&gt;&#xA;&lt;p&gt;How can I solve this issue&lt;a href=&quot;https://i.stack.imgur.com/EK9sJ.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EK9sJ.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8843" LastEditorUserId="5" LastEditDate="2024-02-21T18:09:52.590" LastActivityDate="2024-02-21T18:09:52.590" Title="Reactor design DCPLS parapmeter" Tags="|software-assistance|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12443" PostTypeId="1" CreationDate="2024-02-21T17:06:07.383" Score="6" ViewCount="78" Body="&lt;p&gt;I am seeking guidance on how to generate a POSCAR file for a hypothetical monolayer with a hexagonal structure similar to MoS2. Can anyone provide me with a step-by-step procedure or recommend any software or tools that can assist me in this process? Any help or advice would be greatly appreciated.&#xA;Thank you.&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="24" LastEditDate="2024-02-21T17:56:36.997" LastActivityDate="2024-03-22T18:05:45.670" Title="Creating a Hypothetical Hexagonal Monolayer Structure Similar to MoS2" Tags="|density-functional-theory|vasp|molecular-modeling|visualization-software|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12445" PostTypeId="2" ParentId="12443" CreationDate="2024-02-21T17:56:16.617" Score="3" Body="&lt;p&gt;I strongly advise using online databases/projects to obtain the CIF/POSCAR files.&lt;/p&gt;&#xA;&lt;p&gt;One that I recommend is &lt;a href=&quot;https://next-gen.materialsproject.org/&quot; rel=&quot;nofollow noreferrer&quot;&gt;The Material Project&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/F78up.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/F78up.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, you can search for materials information by chemistry, composition, or property:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/InNr8.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/InNr8.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;At the left menu, there is the option &amp;quot;Crystal Toolkit&amp;quot;, where you can cut the crystal informing the Miller indexes.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iX5iQ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iX5iQ.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/eIEfm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/eIEfm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Also, you can download the CIF for the crystal, and then use programs like &lt;a href=&quot;https://sourceforge.net/projects/cif2cell/&quot; rel=&quot;nofollow noreferrer&quot;&gt;CIF2Cell&lt;/a&gt; to cut the crystal and create the desired supercell.&lt;/p&gt;&#xA;" OwnerUserId="24" LastEditorUserId="24" LastEditDate="2024-02-21T18:04:19.667" LastActivityDate="2024-02-21T18:04:19.667" CommentCount="12" ContentLicense="CC BY-SA 4.0" />
  <row Id="12446" PostTypeId="1" CreationDate="2024-02-22T00:35:25.233" Score="4" ViewCount="210" Body="&lt;p&gt;I am trying to understand the use of &lt;code&gt;space_group&lt;/code&gt; in Quantum Espresso. I note that the keyword can be used with and without &lt;code&gt;ibrav&lt;/code&gt;. What is the benefit/usage of this keyword? Is there a performance related reason to give the input only the inequivalent atomic&#xA;positions?&lt;/p&gt;&#xA;&lt;p&gt;For reference (and from the documentation):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;space_group INTEGER&#xA;Default:    0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The number of the space group of the crystal, as given in the&#xA;International Tables of Crystallography A (ITA). This allows to give&#xA;in input only the inequivalent atomic positions. The positions of all&#xA;the symmetry equivalent atoms are calculated by the code. Used only&#xA;when the atomic positions are of type crystal_sg. See also uniqueb,&#xA;origin_choice, rhombohedral&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="786" LastEditorUserId="5" LastEditDate="2024-02-22T02:13:04.943" LastActivityDate="2024-02-22T02:13:04.943" Title="Is there a difference between `space_group` and `ibrav` in terms of Quantum espresso performance?" Tags="|quantum-espresso|symmetry|space-groups|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12447" PostTypeId="2" ParentId="12446" CreationDate="2024-02-22T02:01:52.013" Score="5" Body="&lt;p&gt;The documentation is straightforward on the meaning of this tag, it is used to specifiy the space group of the crystal you are working on in accordance with the well known &lt;a href=&quot;https://www.cryst.ehu.es/cgi-bin/cryst/programs/nph-table&quot; rel=&quot;noreferrer&quot;&gt;ITA&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Suppose that you are using &lt;code&gt;space_group&lt;/code&gt; without &lt;code&gt;ibrav&lt;/code&gt;, then you just need to provide the positions of atoms that has no symmetry operations or not related to symmetry operations, then QE will calculate the positions of the other atoms that has symmetry operations. As an example, suppose you have crystal with space group (Fm-3m):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;control&#xA;   ...&#xA;/&#xA;&#xA;&amp;amp;system&#xA;   ibrav = 0&#xA;   space_group = 225&#xA;   ...&#xA;/&#xA;&#xA;&amp;amp;electrons&#xA;   ...&#xA;/&#xA;&#xA;ATOMIC_SPECIES&#xA;   ...&#xA;/&#xA;&#xA;ATOMIC_POSITIONS crystal_sg&#xA;   AtomType 0.0 0.0 0.0&#xA;   AtomType 0.5 0.5 0.5&#xA;/&#xA;&#xA;K_POINTS automatic&#xA;   2 2 2 0 0 0&#xA;/&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When it comes to performance, theoretically speaking, exploiting the symmetry shall give you an acceleration in computional performance, but I am not aware whether it is a notable difference or not, I don't have actual numerical comparison in this regard. You may do your own testing.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, it was mentioned by Paolo Giannozzi &lt;em&gt;et. al&lt;/em&gt;. in &lt;a href=&quot;https://arxiv.org/pdf/0906.2569.pdf&quot; rel=&quot;noreferrer&quot;&gt;QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials&lt;/a&gt;, that exploiting the symmetry has an impact on accelerating the computation specially for Phonon calculations.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-02-22T02:01:52.013" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12448" PostTypeId="1" CreationDate="2024-02-22T09:00:57.577" Score="6" ViewCount="243" Body="&lt;p&gt;How may I calculate each term of the formation energy equation using DFT?&lt;/p&gt;&#xA;&lt;p&gt;I am assuming that for every software (i.e. Quantum ESPRESSO; Wien2k), the calculation procedure must be the same.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2024-02-22T14:37:45.917" LastActivityDate="2024-02-22T14:37:45.917" Title="Formation Energy Calculations" Tags="|density-functional-theory|formation-energy|" AnswerCount="1" CommentCount="14" ContentLicense="CC BY-SA 4.0" />
  <row Id="12450" PostTypeId="1" CreationDate="2024-02-22T10:13:48.290" Score="6" ViewCount="60" Body="&lt;p&gt;Dear StackExchange Members,&lt;/p&gt;&#xA;&lt;p&gt;I'm using the native PySCF implementation of selected configuration interaction (SCI). However, I can't seem to find any documentation detailing the algorithm or various user-defined parameters contained within.&lt;/p&gt;&#xA;&lt;p&gt;I'm particularly interested in the parameters, &lt;code&gt;select_cutoff&lt;/code&gt; and &lt;code&gt;ci_coeff_cutoff&lt;/code&gt;. Based on the &lt;a href=&quot;https://pyscf.org/_modules/pyscf/fci/selected_ci.html&quot; rel=&quot;noreferrer&quot;&gt;PySCF documentation&lt;/a&gt;, I had originally thought they were similar to the &lt;span class=&quot;math-container&quot;&gt;$\epsilon_1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\epsilon_2$&lt;/span&gt; parameters in heat-bath CI, although I'm now unsure of this. As many different flavours of SCI algorithms I would like some clarification on this.&lt;/p&gt;&#xA;&lt;p&gt;If anyone has any experience in this or can point me in the correct direction, it would  be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Thanks,&lt;/p&gt;&#xA;&lt;p&gt;Andrew&lt;/p&gt;&#xA;" OwnerUserId="8844" LastEditorUserId="142" LastEditDate="2024-02-25T16:35:15.613" LastActivityDate="2024-02-25T16:35:15.613" Title="What are the parameters in PySCF's Selected Configuration Interaction code" Tags="|electronic-structure|ab-initio-calculations|pyscf|configuration-interaction|full-configuration-interaction|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12451" PostTypeId="2" ParentId="12448" CreationDate="2024-02-22T11:57:40.533" Score="4" Body="&lt;p&gt;It really depends on what you want to investigate. Let's assume, we have a binary compound &lt;span class=&quot;math-container&quot;&gt;$A_nB_m$&lt;/span&gt;, the energy of formation could be&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_f = E(A_nB_m) - [ n E(A) + mE(B)]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$E(A),E(B)$&lt;/span&gt; are atomic energies. For the latter, one could put an isolated atom inside a large supercell and do a single point calculation. Or calculate the energy of a bulk elemental structure and divide its energy by the number of atoms.&#xA;They are not the same and the choice depends on the system. E.g. in a very diluted alloy it is probably okay to take single atomic energies. If there is a significant amount of &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; inside the binary compound, other phases can occur and it is more useful to define the formation energy with respect to the energy of the pure phases. This means calculating the energy of the phase and dividing by the number of atoms. &lt;br /&gt;&#xA;A formation energy (like defined above) cannot tell you much about thermodynamic stability. What does it tell you? If &lt;span class=&quot;math-container&quot;&gt;$\Delta E_F &amp;lt; 0 $&lt;/span&gt;, then the system is energetically favoring the binary compound configuration over whatever stays in square brackets. In other words, it will not separate into its pure compounds. Another formation energy could be the adsorption of a molecule onto a slab, then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\Delta E_f = E(slab+mol) - [E(slab) + E(mol)]$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;One can then compare different formation energies (for different concentrations of &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; &amp;amp; &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; above ) and plot them to see which concentration has the lowest energy. This is called Convex Hull plot. Or in the example with the molecule, put different molecules onto the surface and compare the formation energies. The comparison of formation energies has to be done with attention. For the slab functionalization, distance to the slab, functional groups, formation of covalent bonds, geometry of the molecules have to be comparable. The difference in formation energies can be in order of meV. For the case with the binary compound, one should keep in mind phase diagrams, which gives rise about the phase composition at a certain temperature and concentration.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;You should use optimized structures. If your formation energy contains single atomic energies, where you want to calculate the energy of an isolated atom as a reference, I think you do not need an optimization. In this case the supercell should be large enough to avoid interactions between atoms ( due to periodic boundary condition).&lt;/li&gt;&#xA;&lt;li&gt;It depends on what you calculate and on your system. I stated this above.&lt;/li&gt;&#xA;&lt;li&gt;Run spin polarized calculations for cases, where you have magnetic moments. Maybe you have some insight from experiments or literature if the system is magnetic or not.  You have to find the magnetic moment on each atom. In Quantum ESPRESSO , one should use the nspin tag. You must initiate the calculation with a starting magnetization on some atoms, use the tag starting_magnetization(i) for this. Different starting magnetizations can lead to different ground states. I realized this myself. Find the configuration with lowest energy after the spin polarized calculation.&lt;/li&gt;&#xA;&lt;li&gt;Your &amp;quot;hyperparameters&amp;quot;, like cutoff energies, pseudo potentials, k-points, smearing etc. should be the same in the calculation of all energies. Only then energies are comparable. As i mentioned before, difference in formation energy can be at meV. So it is sensitive.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="8715" LastEditorUserId="8715" LastEditDate="2024-02-22T13:31:38.190" LastActivityDate="2024-02-22T13:31:38.190" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12452" PostTypeId="1" CreationDate="2024-02-22T12:54:44.197" Score="4" ViewCount="82" Body="&lt;p&gt;Can I use Google Collab to run my Gaussian calculations? Due to the lower specification of my system, I can not run my calculations. I have to generate .wfn file. Is there any other idea or alternative??&lt;/p&gt;&#xA;" OwnerUserId="8850" LastEditorUserId="142" LastEditDate="2024-02-28T13:41:50.300" LastActivityDate="2024-02-28T13:41:50.300" Title="Can I run Gaussian on Google Collab" Tags="|gaussian|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12453" PostTypeId="1" AcceptedAnswerId="12696" CreationDate="2024-02-22T17:14:41.053" Score="5" ViewCount="27" Body="&lt;p&gt;I am interested in performing activation energy barrier calculations using VASP (Vienna Ab initio Simulation Package) specifically for reactions involving electron exchange. However, I am uncertain about the appropriate methodology for modeling cations or anions within the VASP framework to accurately calculate activation energy barriers for these reactions.&lt;/p&gt;&#xA;&lt;p&gt;Could someone provide guidance or resources on how to properly model cations or anions in VASP for activation energy barrier calculations, particularly in the context of electron exchange reactions? Any insights into the suitable input parameters, settings, or considerations would be greatly appreciated. Thank you.&lt;/p&gt;&#xA;" OwnerUserId="8448" LastActivityDate="2024-04-03T18:19:20.717" Title="How to Model Cations or Anions for Activation Energy Barrier Calculation in VASP for Electron Exchange Reactions?" Tags="|vasp|computational-chemistry|quantum-chemistry|electronic-structure|reactivity|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12454" PostTypeId="2" ParentId="12275" CreationDate="2024-02-22T21:32:03.640" Score="1" Body="&lt;p&gt;In the undoped case, when considering a cubic crystal structure and using a tetragonal supercell not changes point symmetry, Hence number of independent elastic constants remains three.  If you rotate the crystal to other orientation you may get different &lt;span class=&quot;math-container&quot;&gt;$C_{ij}$&lt;/span&gt; components. However, Eigen values of &lt;span class=&quot;math-container&quot;&gt;$C_{ij}$&lt;/span&gt; remains three.&lt;/p&gt;&#xA;&lt;p&gt;When doping is introduced, the symmetry of the crystal can be altered, leading to changes in the elastic properties. Doping can disrupt the perfect arrangement of atoms in the crystal lattice, causing a deviation from the ideal symmetry. As a result, the relaxed supercell may no longer exhibit  cubic symmetry especially in the vicinity of the dopant atoms.&lt;/p&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2024-02-22T21:32:03.640" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12455" PostTypeId="1" CreationDate="2024-02-23T06:36:09.893" Score="3" ViewCount="36" Body="&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; topological invariant is typically calculated based on the parity of occupied bands at time-reversal invariant momenta (TRIM) in the Brillouin zone. The &lt;a href=&quot;http://www.wanniertools.com/features.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;WannierTools docs&lt;/a&gt; states that we can get &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; topological Index (&lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$v_1$$v_2$$v_3$&lt;/span&gt;) from the &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; calculations of six time reversal invariant planes, i.e. (a) &lt;span class=&quot;math-container&quot;&gt;$k_1=0.0$&lt;/span&gt;; (b) &lt;span class=&quot;math-container&quot;&gt;$k_1=0.5$&lt;/span&gt;; (c) &lt;span class=&quot;math-container&quot;&gt;$k_2=0.0$&lt;/span&gt;; (d) &lt;span class=&quot;math-container&quot;&gt;$k_2=0.5$&lt;/span&gt;; (e) &lt;span class=&quot;math-container&quot;&gt;$k_3=0.0$&lt;/span&gt;; (f) &lt;span class=&quot;math-container&quot;&gt;$k_3=0.5$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;In the same documentation, &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; index for 3D system is given as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_0= (\mathbb{Z}_2(k_i=0)+\mathbb{Z}_2(k_i=0.5)) mod(2)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$v_i= \mathbb{Z}_2(k_i=0.5)$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;After obtaitning the values from those six planes, we can get the index based on the previous equations, and check whether we have a strong or weak topological insulator.&#xA;The documentaion also states: for 2D system, if you set the &lt;em&gt;Z&lt;/em&gt; axis as the stack axis, please only take the &lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z}_2$&lt;/span&gt; number at &lt;span class=&quot;math-container&quot;&gt;$k_3=0$&lt;/span&gt; plane.&lt;/p&gt;&#xA;&lt;p&gt;In the case of 2D system, how should I treat the index (&lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$v_1$$v_2$$v_3$&lt;/span&gt;), would it be that I only take (&lt;span class=&quot;math-container&quot;&gt;$v_0$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$v_3$&lt;/span&gt;)? Or would that index be meaningless in a 2D system?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-02-23T06:36:09.893" Title="Z2 Topological Invariant for 2D Systems" Tags="|tight-binding|topological-insulators|wannier90|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12456" PostTypeId="2" ParentId="12246" CreationDate="2024-02-23T13:23:53.913" Score="-1" Body="&lt;p&gt;Try: &lt;a href=&quot;https://psicode.org/psi4manual/master/sapt.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Symmetry-Adapted Perturbation Theory (SAPT)&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Symmetry-adapted perturbation theory (SAPT) provides a means of directly computing the noncovalent interaction between two molecules, that is, the interaction energy is determined without computing the total energy of the monomers or dimer. In addition, SAPT provides a decomposition of the interaction energy into physically meaningful components: i.e., electrostatic, exchange, induction, and dispersion terms.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/f5WbG.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/f5WbG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Here, the Hamiltonian is written as a sum of the usual monomer Fock operators, &lt;span class=&quot;math-container&quot;&gt;$F$&lt;/span&gt;, the fluctuation potential of each monomer, &lt;span class=&quot;math-container&quot;&gt;$W$&lt;/span&gt;, and the interaction potential, &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;. The monomer Fock operators, &lt;span class=&quot;math-container&quot;&gt;$F_a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$F_b$&lt;/span&gt;, are treated as the zeroth-order Hamiltonian and the interaction energy is evaluated through a perturbative expansion of , &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$W_a$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$W_b$&lt;/span&gt;. Through first-order in &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;, electrostatic and exchange interactions are included; induction and dispersion first appear at second-order in &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;. For a complete description of SAPT, the reader is referred to the excellent review by Jeziorski, Moszynski, and Szalewicz. (&lt;a href=&quot;https://psicode.org/psi4manual/master/sapt.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;1&lt;/a&gt;, &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/cr00031a008&quot; rel=&quot;nofollow noreferrer&quot;&gt;2&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="8416" LastEditorUserId="8416" LastEditDate="2024-03-03T16:14:57.440" LastActivityDate="2024-03-03T16:14:57.440" CommentCount="4" CommunityOwnedDate="2024-03-07T14:09:50.403" ContentLicense="CC BY-SA 4.0" />
  <row Id="12457" PostTypeId="1" AcceptedAnswerId="12458" CreationDate="2024-02-23T14:27:56.510" Score="2" ViewCount="122" Body="&lt;p&gt;I am trying to calculate the energies of the S1 and T1 states of a molecule with UDFT using Gaussian.&lt;/p&gt;&#xA;&lt;p&gt;For the T1 state, I can successfully use the following input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt freq ub3lyp/6-311+g* geom=checkpoint guess=mix nosymm&#xA;&#xA;molecule1&#xA;&#xA;0 3&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the S1 state, I tried:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#p opt freq ub3lyp/6-311+g* geom=checkpoint guess=mix nosymm&#xA;&#xA;molecule1&#xA;&#xA;1 1&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;but I received the following error:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The combination of multiplicity 1 and   219 electrons is impossible.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;What am I doing wrong?&lt;/p&gt;&#xA;" OwnerUserId="4755" LastEditorUserId="5" LastEditDate="2024-02-23T14:47:51.187" LastActivityDate="2024-02-23T14:47:51.187" Title="'The combination of multiplicity electrons is impossible' in Gaussian" Tags="|quantum-chemistry|electronic-structure|gaussian|excited-states|spin|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12458" PostTypeId="2" ParentId="12457" CreationDate="2024-02-23T14:45:14.957" Score="4" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The combination of multiplicity 1 and 219 electrons is impossible.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;219 is an odd number of electrons.&lt;/p&gt;&#xA;&lt;p&gt;A spin multiplicity of 1 means that there are no unpaired electrons. This means that all electrons are paired, meaning that the number of electrons must be an even number. Therefore 219 electrons (or any odd number of electrons) is not compatible with having a spin multiplicity of 1.&lt;/p&gt;&#xA;&lt;p&gt;Spin multiplicity is 2S+1, in which S is the spin. For the spin multplicity to be 1, you need S to be 0, which means that there's no unpaired electrons, because each unpaired electron would contribute a value of 1/2 to the spin (5 unpaired electrons would mean we have a spin of 5/2 and a spin multiplicity of 6).&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-23T14:45:14.957" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12459" PostTypeId="1" AcceptedAnswerId="12498" CreationDate="2024-02-23T14:58:06.003" Score="5" ViewCount="143" Body="&lt;p&gt;I am trying to calculate the energy of the S1 state with UDFT in Gaussian software.&#xA;I understand that, generally, one should manipulate the charge and spin multiplicity to manually change the occupations.&lt;/p&gt;&#xA;&lt;p&gt;After calculating the S0 state with the latters as '0 1', I wanted to compute the S1 using '1 1'. However, I received&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The combination of multiplicity 1 and 219 electrons is impossible&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;How can I calculate the energy of S1 state in Gaussian with UDFT?&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="4755" LastActivityDate="2024-03-02T16:32:31.153" Title="Calculation of S1 energy in Gaussian" Tags="|quantum-chemistry|gaussian|excited-states|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12460" PostTypeId="1" AcceptedAnswerId="12461" CreationDate="2024-02-23T16:32:01.283" Score="7" ViewCount="264" Body="&lt;p&gt;I'm working on a data-driven project involving material properties and I'm wondering about the following:&lt;/p&gt;&#xA;&lt;p&gt;I know that the notion of band gap and electrical conductivity are inversely related, and the former can help in classifying materials in &lt;em&gt;metals&lt;/em&gt;, &lt;em&gt;semiconductors&lt;/em&gt; and &lt;em&gt;insulators&lt;/em&gt;. Nevertheless, I would like to know if there are cases where materials can exhibit a very low band gap yet not be conducting. I guess there are, as I expect conductivity depends on a variety of factors that won't include the band gap alone.&lt;/p&gt;&#xA;" OwnerUserId="2017" LastActivityDate="2024-02-23T17:56:46.713" Title="Materials with low band gap and low conductivity simultaneously. Is it possible?" Tags="|electronic-structure|bandgap|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12461" PostTypeId="2" ParentId="12460" CreationDate="2024-02-23T17:56:46.713" Score="8" Body="&lt;p&gt;There are such materials! See chp. 11 in Girvin-Yang which gives a much better discussion than I am providing here. You could probably also look up 'Anderson insulator' online or in any other solid-state text book for a similar explanation.&lt;/p&gt;&#xA;&lt;p&gt;The Einstein relation for conductivity is &lt;span class=&quot;math-container&quot;&gt;$ \sigma \sim \rho D $&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; is conductivity, &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; is the density of states at the Fermi level, and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; is the diffusion constant. &lt;span class=&quot;math-container&quot;&gt;$\rho$&lt;/span&gt; basically tells you how many electrons there are that can conduct and &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt; tells you how easily these electrons can move.&lt;/p&gt;&#xA;&lt;p&gt;If &lt;span class=&quot;math-container&quot;&gt;$\rho=0$&lt;/span&gt;, there are no electrons that can move, so there is no conductivity. This is the case for gapped materials like band insulators.&lt;/p&gt;&#xA;&lt;p&gt;On the other hand, there are materials where &lt;span class=&quot;math-container&quot;&gt;$D=0$&lt;/span&gt; while &lt;span class=&quot;math-container&quot;&gt;$\rho \neq 0$&lt;/span&gt;. The only example I can think of is an Anderson insulator. My understanding is tenuous, but basically in systems with strong disorder, it is possible for electrons to get trapped in deep potential wells. There are electrons in the system, i.e. &lt;span class=&quot;math-container&quot;&gt;$\rho \neq 0$&lt;/span&gt;, but the potential makes it very difficult for them to move and &lt;span class=&quot;math-container&quot;&gt;$D\rightarrow0$&lt;/span&gt;, i.e. &lt;span class=&quot;math-container&quot;&gt;$\sigma\rightarrow 0$&lt;/span&gt; even though &lt;span class=&quot;math-container&quot;&gt;$\rho \neq 0$&lt;/span&gt;. I think the fact that the potential is &lt;em&gt;disordered&lt;/em&gt; is important since a very strong lattice potential would lead to a different type of metal-insulator transition, namely a Mott transition, where the limit of isolated atoms is approached. Like I said, my understanding of Anderson insulators is poor, but hopefully this answer helps! Feel free to read more about Anderson insulators and explain them to me.&lt;/p&gt;&#xA;&lt;p&gt;Cheers,&#xA;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-02-23T17:56:46.713" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12462" PostTypeId="1" CreationDate="2024-02-23T22:54:01.633" Score="4" ViewCount="71" Body="&lt;p&gt;I have a simulation trajectory from DFTB+ for 1 NaNO3 in 32 H2O molecules. The trajectory is in xyz format and I converted a frame of xyz to pdb using openbabel to serve as topology input.&lt;/p&gt;&#xA;&lt;p&gt;I am following the instructions from the solvation analysis package &lt;a href=&quot;https://solvation-analysis.readthedocs.io/en/latest/tutorials/multi_atom_solutes.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;. However, I keep getting an assertion error&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;All residues must have the same length&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I don't know how to get past this. My codes are pasted below from my Jupyter notebook.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import MDAnalysis as mda&#xA;u=mda.Universe(&amp;quot;./single-frame-1NaNO3-32-H2O.pdb&amp;quot;, &amp;quot;./nano3-1-water-32-some-frames.xyz&amp;quot;)&#xA;import solvation_analysis&#xA;nano3Atoms=u.atoms.select_atoms(&amp;quot;id 1 or id 2 or id 3 or id 4 or id 5&amp;quot;)&#xA;oAtomsWater=u.atoms.select_atoms(&amp;quot;type O and resname HOH&amp;quot;)&#xA;hAtomsWater=u.atoms.select_atoms(&amp;quot;type H and resname HOH&amp;quot;)&#xA;solventAtoms=u.atoms - nano3Atoms&#xA;&#xA;from solvation_analysis.solute import Solute&#xA;soluteObject=Solute.from_atoms(nano3Atoms,{&amp;quot;Wat&amp;quot;:solventAtoms},solute_name=&amp;quot;salt&amp;quot;)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;All the intermediate steps seem to present reasonable outputs with nano3Atoms showing all atoms that correspond to NaNO3. The last step when soluteObject is defined is when the assertion error is thrown. Any help would be greatly appreciated.&lt;/p&gt;&#xA;&lt;p&gt;A pdb file and some frames from the simulation output are presented &lt;a href=&quot;https://ufile.io/f/v2byn&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&#xA;Thank you,&lt;/p&gt;&#xA;" OwnerUserId="5113" LastEditorUserId="1554" LastEditDate="2024-02-24T02:45:19.727" LastActivityDate="2024-02-28T20:19:31.507" Title="Solvation_analysis subpackage for MDAnalysis multi-atom solute" Tags="|molecular-dynamics|software|molecular-modeling|python|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12463" PostTypeId="1" CreationDate="2024-02-24T12:24:34.267" Score="4" ViewCount="67" Body="&lt;p&gt;Good afternoon, everyone.Please help me understand my question. When I upload some of my cif structure files, VESTA automatically creates huge supercells. I want to remove this function by standard when I start the program. Maybe someone knows how to do it, like customize some config file?&lt;/p&gt;&#xA;&lt;p&gt;Ubuntu 22.04.3 LTS&#xA;Vesta 3.5.8 64-bit&lt;/p&gt;&#xA;&lt;p&gt;For some cif files I have structures with one unit cell open, for others a huge supercell (attached screenshot). I have not found any regularities between the structures.&lt;/p&gt;&#xA;&lt;p&gt;When converting a cif file to an xyz file via openbabel, the file opens unit cell (without cell)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/a0giw.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/a0giw.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/0SADR.jpg&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/0SADR.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8859" LastEditorUserId="8859" LastEditDate="2024-02-25T23:53:30.030" LastActivityDate="2024-02-25T23:53:30.030" Title="Automatic construction of supercell VESTA" Tags="|vesta|supercell|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12464" PostTypeId="1" CreationDate="2024-02-24T16:54:40.897" Score="5" ViewCount="66" Body="&lt;p&gt;I am working on a C++ project that entails reading FCIDUMP files and feeding it into some post-HF calculation. For practical reasons, it is more preferable to stick with the native FCIDUMP format of MolPro, which is that for any listed &lt;span class=&quot;math-container&quot;&gt;$[ij\vert kl]$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$i\geq j$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$k\geq l$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$i\geq k$&lt;/span&gt;. As far as my understanding goes, this format allows one to expand the symmetric terms without worrying about clashing with other listed terms. That is, any symmetric term associated with &lt;span class=&quot;math-container&quot;&gt;$[ij\vert kl]$&lt;/span&gt; (e.g. &lt;span class=&quot;math-container&quot;&gt;$[kl\vert ij]$&lt;/span&gt;) is guaranteed to be different from any other term &lt;span class=&quot;math-container&quot;&gt;$[i'j'\vert k'l']$&lt;/span&gt; in the list. However, since I have no access for MolPro for now, I can only resort to open source software such as PySCF and Psi4 by calling their FCIDUMP modules(&lt;strong&gt;pyscf.tools.fcidump.from_scf()&lt;/strong&gt; for example). But it appears that PySCF's (and Psi4's) FCIDUMP format is not the same MolPro: it only ensures &lt;span class=&quot;math-container&quot;&gt;$i\geq j$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$k\geq l$&lt;/span&gt;. &lt;strong&gt;My questions is, is it possible to make PySCF's FCIDUMP output adhere to the native MolPro format?&lt;/strong&gt; For sure, one can write a script to make things look the same at the end of the day, but I just want to save the hassle. S&lt;/p&gt;&#xA;&lt;p&gt;As Dr. Dattani suggests, I shall demonstrate below how they differ. First, here is how the native MolPro format looks like&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0.4901530798812482E+00   1   1   1   1&#xA;    0.3851086116668512E-15   2   1   1   1&#xA;    0.1357703691573445E+00   2   1   2   1&#xA;    0.4346387940927313E+00   2   2   1   1&#xA;    0.5551115123125783E-16   2   2   2   1&#xA;    0.4151840574104080E+00   2   2   2   2&#xA;   -0.2794639519798636E-14   3   1   1   1&#xA;    0.7348327890437402E-01   3   1   2   1&#xA;   -0.2386979502944087E-14   3   1   2   2&#xA;    0.8287363963878831E-01   3   1   3   1&#xA;    ...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Meanwhile, pyscf gives something like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    0.6502249619014371    1    1    1    1&#xA;    0.4337148338929643    1    1    2    2&#xA;    0.1672559053568855    1    1    3    1&#xA;    0.5319758870034718    1    1    3    3&#xA;    0.1433508560769139    1    1    4    2&#xA;    0.6633892094879649    1    1    4    4&#xA;    0.07999383652881964    2    1    2    1&#xA;   -0.0193772995125534    2    1    3    2&#xA;    0.07934608168082659    2    1    4    1&#xA;    0.08312052663122392    2    1    4    3&#xA;    0.4337148338929642    2    2    1    1&#xA;    0.38578316658518    2    2    2    2&#xA;    0.04998352966944281    2    2    3    1&#xA;    0.3812871041018909    2    2    3    3&#xA;    0.05473143994188186    2    2    4    2&#xA;    0.4424236810822116    2    2    4    4&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice that terms with &lt;span class=&quot;math-container&quot;&gt;$i&amp;lt;k$&lt;/span&gt; are listed in the second example, which is not the case in the first. The PySCF code used is also given below&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from pyscf import gto,scf&#xA;from pyscf.tools import fcidump&#xA;&#xA;mol = gto.M(atom = 'C 0 0 0; C 0 0 1.2', basis = '6-31g', symmetry=True)&#xA;&#xA;# RHF&#xA;rhf_obj = scf.RHF(mol)&#xA;rhf_obj.kernel()&#xA;&#xA;fcidump.from_scf(rhf_obj,filename=&amp;quot;c2_rhf.fcidump&amp;quot;,molpro_orbsym=fcidump.MOLPRO_ORBSYM)&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5727" LastEditorUserId="5727" LastEditDate="2024-02-25T14:37:59.777" LastActivityDate="2024-02-25T16:34:33.923" Title="Can PySCF generate FCIDUMPs in native MOLPRO format?" Tags="|pyscf|molpro|fcidump|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12465" PostTypeId="1" AcceptedAnswerId="12466" CreationDate="2024-02-25T11:25:09.363" Score="7" ViewCount="310" Body="&lt;p&gt;While I am aware that VASP and QE are widely used for solid-state materials and PySCF/OpenMolcas are primarily designed for molecular systems.&lt;/p&gt;&#xA;&lt;p&gt;I want to know why should I use PySCF/OpenMolcas for molecular calculations over VASP/QE and whether those packages could replace VASP/QE for periodic systems?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2024-02-25T14:00:57.163" LastActivityDate="2024-02-27T20:21:23.590" Title="Why use PySCF/OpenMolcas instead of VASP/QuantumESPRESSO" Tags="|software|molecular-modeling|electronic-structure|software-recommendations|periodic-system|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12466" PostTypeId="2" ParentId="12465" CreationDate="2024-02-25T14:00:16.860" Score="6" Body="&lt;p&gt;The main difference is that PySCF, OpenMolcas, and other popular software such as Gaussian, ORCA, Molpro, Psi4, MRCC, CFOUR, Dalton, GAMESS, COLUMBUS, ACES, etc., are very well-developed for using &lt;strong&gt;Gaussian basis sets&lt;/strong&gt;. In a typical molecule, there will be nuclei at certain irregular places, and the electronic wavefunction will look very different near those nuclei compared to away from those nuclei, and Gaussian basis sets that are centered at each nucleus, offer an excellent way to help model the shape of the wavefunction when we have such irregularities at very specific places.&lt;/p&gt;&#xA;&lt;p&gt;In PySCF and OpenMOLCAS, we also have access to well-developed and extremely high-accuracy (compared to VASP and QuantumESPRESSO) wavefunction-based methods for solving the Schroedinger equation: &lt;a href=&quot;/questions/tagged/full-configuration-interaction&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;full-configuration-interaction&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;full-configuration-interaction&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-full-configuration-interaction-tooltip-container&quot;&gt;full-configuration-interaction&lt;/a&gt; (FCI), &lt;a href=&quot;/questions/tagged/coupled-cluster&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;coupled-cluster&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;coupled-cluster&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-coupled-cluster-tooltip-container&quot;&gt;coupled-cluster&lt;/a&gt;, &lt;a href=&quot;/questions/tagged/casscf&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;casscf&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;casscf&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-casscf-tooltip-container&quot;&gt;casscf&lt;/a&gt; and in OpenMolcas we even have methods built on top of CASSCF such as CASPT2, RASPT2, and GASPT2. FCI offers an &lt;strong&gt;exact&lt;/strong&gt; solution to the Schroedinger equation for a given basis set, so not only is the Gaussian basis set capturing the fine details of the shape of the equation more accurately than a plane-wave basis set typically would, the actual solution to the Schroedinger equation based on that basis set is also capable to be more accurate in the Gaussian-based software.&lt;/p&gt;&#xA;&lt;p&gt;VASP and Quantum ESPRESSO use &lt;strong&gt;plane-wave basis sets&lt;/strong&gt; which don't capture the local irregularities of the wavefunction near the nuclei as well as Gaussian basis sets do. Furthermore, the capabilities to do calculations such as FCI, coupled cluster, etc. are not nearly as well-developed in VASP and Quantum ESPRESSO. VASP and Quantum ESPRESSO are designed to model comparatively huge materials with far more nuclei and electrons, so the methods available are mainly low-cost methods such as DFT with plane-wave basis sets: these will not be able to compete in accuracy with the above-mentioned wavefunction-based methods with Gaussian basis sets, and when modeling smaller molecules, the standards of accuracy tend to be &lt;em&gt;&lt;strong&gt;a lot higher&lt;/strong&gt;&lt;/em&gt; (it's not okay to just get a band gap accurate to within ±0.1 eV of the exact solution to the Schroedinger equation, the goal will be much closer to ±1 cm-1 accuracy or at least ±1 kcal/mol accuracy). A plane-wave basis set can certainly compete with a Guassian basis sets for accuracy if the former contains far more functions than the latter, but you would need orders of magnitude more functions, so the vast majority of the people that model molecules do not use plane-wave basis sets.&lt;/p&gt;&#xA;&lt;p&gt;PySCF has some functionality to do calculations with periodic boundary conditions, but it is not nearly as developed as the functionality for that in VASP and QuantumESPRESSO. Contrarily, I do not yet recommend using VASP or Quantum ESPRESSO for calculations with Gaussian basis sets.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-02-25T14:00:16.860" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12468" PostTypeId="1" AcceptedAnswerId="12480" CreationDate="2024-02-25T21:43:43.117" Score="3" ViewCount="74" Body="&lt;p&gt;I have a basic question about how to calculate molecular-orbitals from atomic-orbitals in PySCF using the self-consistent field approach. My understanding mathematically is as follows: we start with a set of non-orthonormal atomic-orbitals &lt;span class=&quot;math-container&quot;&gt;$\{\phi_i\}$&lt;/span&gt; with overlap matrix &lt;span class=&quot;math-container&quot;&gt;$S_{ij} = \langle \phi_i, \phi_j \rangle$&lt;/span&gt;. Application of Hartree-Fock produces a new set of orbitals &lt;span class=&quot;math-container&quot;&gt;$\{\psi_i\}$&lt;/span&gt; via a unitary orbital transformation &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt;. The relationship between the old and new orbitals is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\psi_i = \sum_j U_{ij} \phi_j.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Since &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is unitary, the overlap matrix should be invariant under this transformation, implying that:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \psi_i, \psi_j \rangle = \sum_{kl} U_{ik} U_{jl} S_{kl} = S_{ij}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;However, when I check this, I get that the molecular-orbitals are actually orthonormal, as their overlap matrix is the identity (see below for the code I used), and moreover, the transformation &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; I obtain is not unitary. My question is: since the self-consistent field method should produce a unitary transformation of the orbitals, what is the approach used to obtain a non-unitary transformation. A follow-up question is: is there a benefit to orthonormalizing the MOs, rather than orthnormalizing the AOs first before obtaining the MOs?&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;from pyscf import gto, scf&#xA;&#xA;mol = gto.M(&#xA;    atom='H 0 0 0 ; Li 0 0 1',&#xA;    basis='sto-3g'&#xA;)&#xA;&#xA;hf = mol.RHF()&#xA;hf.scf()&#xA;S = hf.get_ovlp()&#xA;U = hf.mo_coeff.T # this defines the transformation from AOs to MOs&#xA;&#xA;S_MOs = np.einsum('ik,jl,kl-&amp;gt;ij', C, C, S)&#xA;&#xA;# S_MOs is an identity matrix&#xA;&lt;span class=&quot;math-container&quot;&gt;```&lt;/span&gt;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3574" LastActivityDate="2024-02-28T13:40:34.727" Title="Orthonormality of AOs and MOs in PySCF" Tags="|quantum-chemistry|molecular-modeling|quantum-mechanics|pyscf|orbitals|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12469" PostTypeId="1" CreationDate="2024-02-27T00:30:36.707" Score="4" ViewCount="87" Body="&lt;p&gt;I have a structure (.gro) file of a PolyEthylene Glycol (PEG) molecule as shown below. How do I get the corresponding structure file for PEG-20 i.e., a molecule with a degree of polymerization=20, containing only PEG molecules)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;PEG&#xA;   9&#xA;    1PEG      H    1   2.032   1.593   1.545  0.6568  2.5734  1.2192&#xA;    1PEG      C    2   1.929   1.614   1.508  0.1558 -0.2184  0.8547&#xA;    1PEG     H1    3   1.902   1.721   1.523 -3.6848 -0.3932 -3.0658&#xA;    1PEG     H2    4   1.921   1.588   1.400 -1.5891  1.4960  0.5057&#xA;    1PEG      O    5   1.831   1.544   1.576  0.0564 -0.5300 -0.6094&#xA;    1PEG     H3    6   1.676   1.665   1.494 -2.6585 -0.5997  0.3128&#xA;    1PEG     C1    7   1.699   1.559   1.519  0.6996  0.0066  0.2900&#xA;    1PEG     H4    8   1.699   1.500   1.425  4.2893  1.6837 -0.9462&#xA;    1PEG     H5    9   1.598   1.510   1.623  1.3303  1.7486 -1.1622&#xA;   3.00000   3.00000   3.00000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3566" LastActivityDate="2024-03-08T13:05:57.877" Title="Given a .gro file of a monomer, how to polymerize it?" Tags="|molecular-dynamics|gromacs|polymers|structure|topological-matter|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12470" PostTypeId="1" CreationDate="2024-02-27T05:35:13.727" Score="4" ViewCount="49" Body="&lt;p&gt;It seems that the only way that Materials Project can report structures with the new API is through the Pymatgen JSON format.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{&amp;quot;data&amp;quot;:[{&amp;quot;structure&amp;quot;:{&amp;quot;@module&amp;quot;:&amp;quot;pymatgen.core.structure&amp;quot;,&amp;quot;@class&amp;quot;:&amp;quot;Structure&amp;quot;,&amp;quot;charge&amp;quot;:0,&amp;quot;lattice&amp;quot;:{&amp;quot;matrix&amp;quot;:[[2.18050236,0.0,1.25891346],[0.72683412,2.05579703,1.25891346],[-0.0,0.0,2.51782692]],&amp;quot;pbc&amp;quot;:[true,true,true],&amp;quot;a&amp;quot;:2.5178271667719256,&amp;quot;b&amp;quot;:2.5178269134954783,&amp;quot;c&amp;quot;:2.51782692,&amp;quot;alpha&amp;quot;:59.99999991454224,&amp;quot;beta&amp;quot;:60.00000324214051,&amp;quot;gamma&amp;quot;:59.9999988338285,&amp;quot;volume&amp;quot;:11.286587893379405},&amp;quot;properties&amp;quot;:{},&amp;quot;sites&amp;quot;:[{&amp;quot;species&amp;quot;:[{&amp;quot;element&amp;quot;:&amp;quot;C&amp;quot;,&amp;quot;occu&amp;quot;:1}],&amp;quot;abc&amp;quot;:[0.875,0.875,0.875],&amp;quot;xyz&amp;quot;:[2.54391942,1.7988224012499998,4.40619711],&amp;quot;properties&amp;quot;:{&amp;quot;magmom&amp;quot;:0.0},&amp;quot;label&amp;quot;:&amp;quot;C&amp;quot;},{&amp;quot;species&amp;quot;:[{&amp;quot;element&amp;quot;:&amp;quot;C&amp;quot;,&amp;quot;occu&amp;quot;:1}],&amp;quot;abc&amp;quot;:[0.125,0.125,0.125],&amp;quot;xyz&amp;quot;:[0.36341706,0.25697462875,0.62945673],&amp;quot;properties&amp;quot;:{&amp;quot;magmom&amp;quot;:0.0},&amp;quot;label&amp;quot;:&amp;quot;C&amp;quot;}]}}],&amp;quot;meta&amp;quot;:{&amp;quot;api_version&amp;quot;:&amp;quot;0.63.2&amp;quot;,&amp;quot;time_stamp&amp;quot;:&amp;quot;2024-02-27T04:59:45.684403&amp;quot;,&amp;quot;total_doc&amp;quot;:1,&amp;quot;max_limit&amp;quot;:1000,&amp;quot;default_fields&amp;quot;:[&amp;quot;material_id&amp;quot;]}}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is there a library out there that can read Pymatgen format? is this really an existing format in disguise?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://matgenb.materialsvirtuallab.org/2013/01/01/Molecule.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;Online tutorial&lt;/a&gt; basically say, &amp;quot;use the pymatgen library (from Python), read the string from the MP REST API, covert to CIF/POSCAR, etc&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;I have created an issue on the &lt;a href=&quot;https://github.com/openbabel/openbabel/issues/2675&quot; rel=&quot;nofollow noreferrer&quot;&gt;OpenBabel repo&lt;/a&gt;, but haven't received a response yet.&lt;/p&gt;&#xA;" OwnerUserId="4417" LastEditorUserId="7" LastEditDate="2024-03-07T14:12:52.623" LastActivityDate="2024-03-07T14:12:52.623" Title="Read pymatgen format from something else other than Python?" Tags="|pymatgen|openbabel|materials-project|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12471" PostTypeId="2" ParentId="12372" CreationDate="2024-02-27T09:38:50.083" Score="-1" Body="&lt;p&gt;I was able to resolve this by simply including a psf alongside a cor file when visualising in vmd. I got an answer from the charmm forums. Apparently vmd will attempt to bond hydrogens itself if there is no data on bonds. Including the psf fixes it.&lt;/p&gt;&#xA;" OwnerUserId="8607" LastActivityDate="2024-02-27T09:38:50.083" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12472" PostTypeId="1" CreationDate="2024-02-27T10:49:04.887" Score="3" ViewCount="68" Body="&lt;p&gt;Good day, I trust you are doing well.&#xA;I am trying to calculate transport properties for a 3D structure stacked between two gold electrodes along the &lt;em&gt;c&lt;/em&gt;-axis. The 3D structure and the electrodes should be periodic along the &lt;em&gt;ab&lt;/em&gt; plane. I have successfully obtained the .TSHS files for my electrodes, and set up my input as follows (all.fdf file excluded for security reasons).&lt;/p&gt;&#xA;&lt;p&gt;In particular I have a semi-inf-direction = ab plane, which produced an error telling me to fix a plane when using this tag and I have opted for TS.Hartree.Fix = C, but replacing C with +AC, -AB, etc. for example then also produces the error:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Electrode: Left uses real-space SE, but the GF file is not present!&#xA;In-core self-energy calculations is currently not implemented Please&#xA;use sisl to create the TBTGF file.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;So SIESTA is looking for a TBTGF file for the electrodes, but I have no idea how to generate them with SIESTA or sisl. Could you please provide assistance?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;TS.Voltage 0 eV&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      C-Left&#xA;      T-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      C-Right&#xA;      T-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.C-Left&#xA;  part circle&#xA;   from -40. eV + V/2 to -10 kT + V/2&#xA;     points 25&#xA;      method g-legendre&#xA;       opt right&#xA;%endblock TS.Contour.C-Left&#xA;%block TS.Contour.T-Left&#xA;  part tail&#xA;   from prev to inf&#xA;     points 10&#xA;      method g-fermi&#xA;%endblock TS.Contour.T-Left&#xA;%block TS.Contour.C-Right&#xA;  part circle&#xA;   from -40. eV -V/2 to -10 kT -V/2&#xA;     points 25&#xA;      method g-legendre&#xA;       opt right&#xA;%endblock TS.Contour.C-Right&#xA;%block TS.Contour.T-Right&#xA;  part tail&#xA;   from prev to inf&#xA;     points 10&#xA;      method g-fermi&#xA;%endblock TS.Contour.T-Right&#xA;&#xA;%block TS.Contours.nEq&#xA;  neq-1&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq-1&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;     delta 0.01 eV&#xA;      method mid-rule&#xA;%endblock TS.Contour.nEq.neq-1&#xA;&#xA;TS.Hartree.Fix C&#xA;&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&#xA;%block TS.Elec.Left&#xA;  HS elecleft.TSHS&#xA;  chemical-potential Left&#xA;  semi-inf-direction ab&#xA;  electrode-position 1&#xA;  used-atoms 36&#xA;%endblock TS.Elec.Left&#xA;%block TS.Elec.Right&#xA;  HS elecright.TSHS&#xA;  chemical-potential Right&#xA;  semi-inf-direction ab&#xA;  electrode-position begin 37&#xA;  used-atoms 36&#xA;%endblock TS.Elec.Right&#xA;&#xA;%include all.fdf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Edit: The electrodes and the central structure are periodic in the A and B direction, with a large vacuum above these structures along the C direction.&lt;/p&gt;&#xA;" OwnerUserId="9874" LastEditorUserId="887" LastEditDate="2024-03-04T14:03:41.600" LastActivityDate="2024-03-04T14:03:41.600" Title="How to write .TBTGF files using sisl for TranSIESTA" Tags="|computational-chemistry|siesta|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12473" PostTypeId="1" CreationDate="2024-02-27T19:31:59.867" Score="3" ViewCount="18" Body="&lt;p&gt;I'm working with a SiPOCa structure and I've already done the SCF, NSCF, DOS, BANDS, CHARGE DENSITY, FTIR and RAMAN calculations. Now I would like to calculate the structural measurements of this structure using DFT and Quantum Espresso. Can anyone explain to me how I create the input files to perform these new calculations? Or if anyone can point me to some study material so I can learn&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="5" LastEditDate="2024-02-27T20:22:41.493" LastActivityDate="2024-02-27T20:22:41.493" Title="How to construct the input files to obtain the structural measurements using Quntum Espresso?" Tags="|density-functional-theory|quantum-espresso|optical-properties|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12475" PostTypeId="1" AcceptedAnswerId="12478" CreationDate="2024-02-27T20:25:05.707" Score="4" ViewCount="98" Body="&lt;p&gt;For classical Molecular Dynamics (cMD) simulations, the usual methodology is to use force fields (FFs) with fixed point charges (examples include CHARMM, AMBER and Gromos). However, this approach means that you are unable to capture the effect of local electrostatics (since fixed point charges cannot respond to the changes in the environment). There are multiple literature reports (including ours) which has shown that accurate capture of local electrostatic interactions are necessary for biological systems and surface interactions.&lt;/p&gt;&#xA;&lt;p&gt;To include local electrostatics into the simulations, we have two methods:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Use a polarizable FF description: This is the methodology that is followed in classical Drude polarizable FF description in CHARMM, where a massless Drude particle is attached to the heavy atom, and the polarizability is modified based on the vibration of the Drude particle). This approach leads to better capture of electrostatic interactions, even though the charges on the heavy atom and the Drude particle are not changing over time.&lt;/li&gt;&#xA;&lt;li&gt;The second approach is called charge equilibration (Qeq) where you start with a set of initial charges, and the charges on each atom are recomputed every nth step to account for the changes in the local environment. This approach is usually followed in the case of reactive FFs; but can in-principle be used in any case.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;As far as my understanding goes, both Drude and Qeq comes with significant performance hits when compared with non-polarizable additive FFs. For Drude, this performance hits comes from the increase in the number of particles, while for Qeq, it is the recalculation of the charges that is expensive.&lt;/p&gt;&#xA;&lt;p&gt;In the context of these, what are the advantages or disadvantages that one approach has over the other?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-02-27T20:31:32.447" LastActivityDate="2024-02-28T09:13:41.813" Title="Advantages/Disadvantages of Qeq over Drude polarizable model?" Tags="|molecular-dynamics|reference-request|one-topic-per-answer|forcefields|polarizability|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12476" PostTypeId="1" CreationDate="2024-02-27T20:32:37.780" Score="4" ViewCount="31" Body="&lt;p&gt;I tried my best to bring an iodine molecule to an excited state to investigate orbital 4.3 but all my atteps were not successful. So, here is the file in molpro for the groundstate&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    ***,mg&#xA;    gprint,orbital,civector&#xA;    memory,200,M&#xA;    angstrom&#xA;&#xA;    geometry={&#xA;&#xA;    I 0. 0. 1.2&#xA;&#xA;    I 0. 0. -1.2&#xA;    }&#xA;&#xA;    spherical&#xA;&#xA;    basis={&#xA;&#xA;    !&#xA;&#xA;    ! iodine               (11s,10p,8d,2f) -&amp;gt; [6s,5p,3d,2f]&#xA;&#xA;    s, I , 5899.5791533, 898.54238765, 200.37237912, 31.418053840, 15.645987838, 11.815741857, 6.4614458287, 2.3838067579, 1.1712089662, 0.32115875757, 0.12387919364&#xA;&#xA;    c, 1.5, 0.24188269271E-03, 0.15474041742E-02, 0.42836684457E-02, -0.39417936275E-01, 0.96086691992&#xA;&#xA;    c, 6.7, 0.75961524091, 0.42495501835&#xA;&#xA;    c, 8.8, 1.0000000&#xA;&#xA;    c, 9.9, 1.0000000&#xA;&#xA;    c, 10.10, 1.0000000&#xA;&#xA;    c, 11.11, 1.0000000&#xA;&#xA;    p, I , 197.30030547, 20.061411349, 12.984316904, 9.7631460485, 3.6199503008, 2.0232273090, 1.0367490559, 0.45937816000, 0.19116532928, 0.74878813023E-01&#xA;&#xA;    c, 1.4, 0.73951226905E-03, 0.66168450008E-01, 0.00000000, -0.28554662348&#xA;&#xA;    c, 3.7, -0.49096186164E-01, 0.00000000, 0.38914432482, 0.65610817262, 0.31803551647&#xA;&#xA;    c, 8.8, 1.0000000&#xA;&#xA;    c, 9.9, 1.0000000&#xA;&#xA;    c, 10.10, 1.0000000&#xA;&#xA;    d, I , 119.12671745, 33.404240134, 17.805918203, 4.8990510353, 2.4516753106, 1.1820693432, 0.52923110068, 0.17000000000&#xA;&#xA;    c, 1.6, 0.82596039573E-03, 0.68377675770E-02, -0.10308158997E-01, 0.22670457658, 0.44180113937, 0.36775472225&#xA;&#xA;    c, 7.7, 1.0000000&#xA;&#xA;    c, 8.8, 1.0000000&#xA;&#xA;    f, I , 2.1800000, 0.44141808&#xA;&#xA;    c, 1.1, 1.0000000&#xA;&#xA;    c, 2.2, 1.0000000&#xA;&#xA;    ! Effective core Potentials&#xA;&#xA;    ECP, i, 28, 3 ; 4; &#xA;&#xA;    !  ul potential&#xA;&#xA;    2,19.45860900,-21.84204000;&#xA;&#xA;    2,19.34926000,-28.46819100;&#xA;&#xA;    2,4.82376700,-0.24371300;&#xA;&#xA;    2,4.88431500,-0.32080400;&#xA;&#xA;    7; !  s-ul potential&#xA;&#xA;    2,40.01583500,49.99429300;&#xA;&#xA;    2,17.42974700,281.02531700;&#xA;&#xA;    2,9.00548400,61.57332600;&#xA;&#xA;    2,19.45860900,21.84204000;&#xA;&#xA;    2,19.34926000,28.46819100;&#xA;&#xA;    2,4.82376700,0.24371300;&#xA;&#xA;    2,4.88431500,0.32080400;&#xA;&#xA;    8; !  p-ul potential&#xA;&#xA;    2,15.35546600,67.44284100;&#xA;&#xA;    2,14.97183300,134.88113700;&#xA;&#xA;    2,8.96016400,14.67505100;&#xA;&#xA;    2,8.25909600,29.37566600;&#xA;&#xA;    2,19.45860900,21.84204000;&#xA;&#xA;    2,19.34926000,28.46819100;&#xA;&#xA;    2,4.82376700,0.24371300;&#xA;&#xA;    2,4.88431500,0.32080400;&#xA;    10; !  d-ul potential&#xA;&#xA;    2,15.06890800,35.43952900;&#xA;&#xA;    2,14.55532200,53.17605700;&#xA;&#xA;    2,6.71864700,9.06719500;&#xA;&#xA;    2,6.45639300,13.20693700;&#xA;&#xA;    2,1.19177900,0.08933500;&#xA;&#xA;    2,1.29115700,0.05238000;&#xA;&#xA;    2,19.45860900,21.84204000;&#xA;&#xA;    2,19.34926000,28.46819100;&#xA;&#xA;    2,4.82376700,0.24371300;&#xA;&#xA;    2,4.88431500,0.32080400;&#xA;&#xA;    }&#xA;&#xA;&#xA;    {uhf&#xA;&#xA;    wf,50,1,0&#xA;&#xA;    orbprint,7}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I tried to change the active space, finding passing wf and states but it did not function at all.&#xA;here is an example&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    {casscf&#xA;&#xA;    closed,5,1,1,0,4,1,1,0;&#xA;&#xA;    occ   ,7,3,3,1,5,2,2,0;&#xA;&#xA;    wf,50,1,0;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,2,0;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,3,0;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,6,0;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,7,0;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,2,2;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,3,2;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,6,2;&#xA;&#xA;    state,1;&#xA;&#xA;    wf,50,7,2;&#xA;&#xA;    state,1;&#xA;&#xA;     }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,1,0;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2100.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,2,0;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2200.2 }&#xA;&#xA;    {ci&#xA;&#xA;     wf,50,3,0;&#xA;&#xA;     state,1;&#xA;&#xA;     save, 2300.2 }&#xA;&#xA;     {ci&#xA;&#xA;     wf,50,6,0;&#xA;&#xA;     state,1;&#xA;&#xA;    save, 2400.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,7,0;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2500.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,2,2;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2600.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,3,2;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2700.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,6,2;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2800.2 }&#xA;&#xA;    {ci&#xA;&#xA;    wf,50,7,2;&#xA;&#xA;    state,1;&#xA;&#xA;    save, 2900.2 }{ci;hlsmat,ecp,2100.2,2200.2,2300.2,2400.2,2500.2,2600.2,2700.2,2800.2,2900.2;option,hlstrans=2,matel=1;print,HLS=2,VLS=0}&#xA;    enddo&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I would appreciate any help. So stupid as now I have never felt yet&lt;/p&gt;&#xA;" OwnerUserId="9877" LastEditorUserId="5" LastEditDate="2024-02-27T20:39:54.170" LastActivityDate="2024-02-27T20:39:54.170" Title="An excited state for a molecule, Molpro, casscf" Tags="|quantum-chemistry|molpro|casscf|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12477" PostTypeId="1" AcceptedAnswerId="12479" CreationDate="2024-02-27T21:19:41.687" Score="2" ViewCount="52" Body="&lt;p&gt;I want to use the  &lt;a href=&quot;https://doi.org/10.1088/0953-8984/16/41/008&quot; rel=&quot;nofollow noreferrer&quot;&gt;REBO-CHO&lt;/a&gt; force field to study graphene oxide using lammps. But I don't know how to create the input file with the parameters by reading the article or if there is a tutorial or software that does it.&lt;/p&gt;&#xA;&lt;p&gt;Or if you already have the file and share it, I would really appreciate it.&lt;/p&gt;&#xA;" OwnerUserId="7638" LastEditorUserId="1554" LastEditDate="2024-02-28T02:31:52.790" LastActivityDate="2024-02-28T10:11:22.307" Title="How to write the REBO force field" Tags="|molecular-dynamics|software-recommendations|lammps|forcefields|software-input-file-request|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12478" PostTypeId="2" ParentId="12475" CreationDate="2024-02-28T08:32:34.827" Score="4" Body="&lt;p&gt;The three main polarization models are Qeq, Drude and induced dipole. The Qeq is a charge-polarization, while the other two are dipole-polarizations. The Drude and ID are essentially equivalent, and parameters can be moved from one model to the other. The advantage of Drude is that it can be run in existing codes written for fixed-charge models. All polarization models are 5-10 times more expensive than fixed-charge models, as either the charge parameters must be iterated to self-consistency in each timestep, or treated as fictive small-mass particles in an extended Lagrange formulation, which requires smaller timesteps. Qeq comes with a lot a other acronyms, FQ, ENN, ..., but it has two non-physical artifacts: charge-transfer over infinite distances and cubic scaling of the polarizability with (non-interacting) system size. There are a number of other charge-polarization models (also called charge-flow or charge-flux) that do not have these artifacts, but very few programs (if any) have implemented (and parameterized) these in application type simulation programs. The different charge-polarization models can be shown to be mathematically equivalent, under certain conditions, but their parameterizations differs. JCTC 19, 4047 &lt;a href=&quot;https://doi.org/10.1021/acs.jctc.3c00341&quot; rel=&quot;nofollow noreferrer&quot;&gt;Unifying Charge-Flow Polarization Models&lt;/a&gt; will give you the full details.&lt;/p&gt;&#xA;" OwnerUserId="279" LastEditorUserId="1554" LastEditDate="2024-02-28T09:13:41.813" LastActivityDate="2024-02-28T09:13:41.813" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12479" PostTypeId="2" ParentId="12477" CreationDate="2024-02-28T10:11:22.307" Score="3" Body="&lt;p&gt;If I remember correctly, the CHO extension of the REBO force field (which was further updated in a &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.84.075460&quot; rel=&quot;nofollow noreferrer&quot;&gt;later publication&lt;/a&gt;) also introduces some changes in formalism, which in turn are not implemented in LAMMPS. So it cannot be used natively.&lt;/p&gt;&#xA;&lt;p&gt;The COMB3 force field is essentially a further extension of the REBO concept (sharing some authors). This is &lt;a href=&quot;https://docs.lammps.org/pair_comb.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;implemented&lt;/a&gt; in LAMMPS, and has parameters for C/H/O. Of course, you'll have to search the literature or do your own checks to verify its applicability to your problem of interest.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastActivityDate="2024-02-28T10:11:22.307" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12480" PostTypeId="2" ParentId="12468" CreationDate="2024-02-28T13:40:34.727" Score="4" Body="&lt;p&gt;Solving the Hartree-Fock equations &lt;strong&gt;is&lt;/strong&gt; equivalent to unitary rotations of the orbitals, but you are missing the key piece: before Hartree-Fock, the basis set is orthonormalized to produce an orthonormal orbital basis.&lt;/p&gt;&#xA;&lt;p&gt;In typical programs, this happens by the process of canonical orthonormalization due to Löwdin; see section 7 of the open access review &lt;a href=&quot;https://doi.org/10.3390/molecules25051218&quot; rel=&quot;nofollow noreferrer&quot;&gt;Molecules 25, 1218 (2020)&lt;/a&gt;. PySCF does not employ this approach by default; instead, it follows an alternative but equivalent approach of solving the generalized eigenvalue problem of the Roothaan equation &lt;span class=&quot;math-container&quot;&gt;${\bf FC} = {\bf SCE}$&lt;/span&gt; with the &lt;a href=&quot;https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.eigh.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;eigh function of SciPy&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In either case, you will find out that the produced orbital coefficients satisfy &lt;span class=&quot;math-container&quot;&gt;${\bf C}^\text{T} {\bf SC} = {\bf 1}$&lt;/span&gt;,  that is, the orbital coefficients are orthonormal in the overlap metric. Note that &lt;span class=&quot;math-container&quot;&gt;${\bf C}^\text{T} {\bf C} \neq {\bf 1}$&lt;/span&gt; except in the case of an orthonormal basis, &lt;span class=&quot;math-container&quot;&gt;$ {\bf S} = {\bf 1}$&lt;/span&gt;,&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-02-28T13:40:34.727" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12481" PostTypeId="2" ParentId="12472" CreationDate="2024-02-28T16:15:49.160" Score="1" Body="&lt;p&gt;I don't know how setting the semi infinite direction to a plane works, but I think this is not what you want judging by how you describe your system.&lt;/p&gt;&#xA;&lt;p&gt;The semi infinite direction is the direction in which your electrode extends infinitely, and it seems like one of your electrodes should extend on the -c direction and the other one on the +c direction.&lt;/p&gt;&#xA;&lt;p&gt;When you change that, you should remove the &lt;code&gt;TS.Hartree.Fix&lt;/code&gt; as well.&lt;/p&gt;&#xA;" OwnerUserId="4675" LastActivityDate="2024-02-28T16:15:49.160" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12483" PostTypeId="5" CreationDate="2024-02-28T20:26:19.593" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2024-02-28T20:26:19.593" LastActivityDate="2024-02-28T20:26:19.593" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12484" PostTypeId="4" CreationDate="2024-02-28T20:26:19.593" Score="0" Body="Use when asking questions related to the [siesta] package, where it relates to electron transport problems. Ideally use [siesta] + [transport]" OwnerUserId="887" LastEditorUserId="887" LastEditDate="2024-03-01T11:58:24.247" LastActivityDate="2024-03-01T11:58:24.247" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12485" PostTypeId="1" CreationDate="2024-02-29T10:36:58.440" Score="8" ViewCount="190" Body="&lt;p&gt;I'm interested in calculating elastic constants for 2D (monolayer) using VASP and I'm looking for guidance on the necessary steps. Could anyone here provide some insight into how to go about this process effectively? Any tips or resources would be greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="1554" LastEditDate="2024-02-29T14:43:44.747" LastActivityDate="2024-02-29T22:48:41.003" Title="Exploring Elastic Constants Calculation in VASP: Methods and Best Practices" Tags="|vasp|2d-lattice|elasticity|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12486" PostTypeId="1" AcceptedAnswerId="12491" CreationDate="2024-02-29T10:57:45.383" Score="4" ViewCount="51" Body="&lt;p&gt;I am at the beginning of my PhD and I just learned about the dipole correction in ab-initio calculations. I have seen that it is used mainly when an electric field is applied to a system. But I have also read in &lt;a href=&quot;https://christoph-wolf.at/2018/05/02/dipole-correction-in-quantum-espresso/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://christoph-wolf.at/2018/05/02/dipole-correction-in-quantum-espresso/&lt;/a&gt; that some surfaces have non-vanishing dipole density. I wonder if that is the case for TMDs and if the ferroelectric dipole in some of them makes necessary this correction to obtain accurate results.&lt;/p&gt;&#xA;" OwnerUserId="9885" LastActivityDate="2024-03-01T02:33:55.413" Title="Is it neccessary to apply dipole corrections in TMD bilayers?" Tags="|density-functional-theory|vasp|quantum-espresso|2d-lattice|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12487" PostTypeId="1" CreationDate="2024-02-29T12:25:02.663" Score="4" ViewCount="40" Body="&lt;p&gt;I am new to Quantum ESPRESSO and it's my first calculations with &lt;span class=&quot;math-container&quot;&gt;$\mathrm{CsPbBr}_3$&lt;/span&gt; perovskite structure. I am trying to perform &lt;code&gt;vc-relax&lt;/code&gt; calculations. The calculation runs fine for pbesol but doesn't converge for pbe-kjpaw, pz-kjpaw, pbe-rrkjus, or pz-rrkjus. See the naming convention &lt;a href=&quot;https://pseudopotentials.quantum-espresso.org/home/naming-convention&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The pbesol pseudopotential set was suggested by input file generator hosted over at materials cloud. I noticed that the pseudopotentials are mixed i.e. for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Cs}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Br}$&lt;/span&gt;, the PP type is USPP whereas for &lt;span class=&quot;math-container&quot;&gt;$\mathrm{Pb}$&lt;/span&gt; I had kjpaw.&lt;/p&gt;&#xA;&lt;p&gt;Is there any rhyme or reason as to why some PPs work and some don't?&lt;/p&gt;&#xA;" OwnerUserId="8738" LastEditorUserId="8738" LastEditDate="2024-03-01T09:42:25.093" LastActivityDate="2024-03-01T09:42:25.093" Title="vc-relax calculation not converging with some pseudopotentials" Tags="|density-functional-theory|quantum-espresso|pseudopotentials|cell-optimization|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12488" PostTypeId="1" CreationDate="2024-02-29T14:05:31.150" Score="4" ViewCount="23" Body="&lt;p&gt;I am new to QE and particularly to ESM-RISM. I have read the de facto paper by S. Nishihara and M. Otani, Phys. Rev. B 96, 115429 (2017), as well as reviewed the pw.x documentation. The calculation seems to indeed work for several geometry steps (13, with a final gradient error of 1.6E-03), with the Laue-RISM in the SCF usually converging in 2-10 iterations. Then suddenly, it will use all 5000 rism3d_maxsteps, and the calculation will finish.&lt;/p&gt;&#xA;&lt;p&gt;The system I am using is extremely simple; it is a lithium slab of 11 layers (11 atoms), which are centred at 0, as the paper suggests. Below, I will provide my ASE script to generate the said input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.build import bcc100&#xA;from ase.io import write&#xA;from pathlib import Path&#xA;import numpy as np&#xA;from ase.units import Bohr&#xA;from ase.visualize import view&#xA;&#xA;pseudopotentials = {'Li': 'li_pbe_v1.4.uspp.F.UPF'}&#xA;slab = bcc100('Li', size=(1,1,11), a=3.44, vacuum=7.5, orthogonal=True)&#xA;slab.center(about=0)&#xA;average_z_top_two_layers = (np.mean(np.sort(np.unique(slab.get_positions()[:, 2]))[::-1][:2])) / Bohr&#xA;average_z_bottom_two_layers = (np.mean(np.sort(np.unique(slab.get_positions()[:, 2]))[:2])) / Bohr&#xA;input_data = {&#xA;    'control': {&#xA;        'calculation': 'relax',&#xA;        'verbosity': 'high',&#xA;        'restart_mode': 'from_scratch',&#xA;        'nstep': 999,&#xA;        'tstress': False,&#xA;        'tprnfor': True,&#xA;        'outdir': './',&#xA;        'prefix': 'pw.dir',&#xA;        'max_seconds': 86100,&#xA;        'etot_conv_thr': 1.0e-5,&#xA;        'forc_conv_thr': 1.0E-4,&#xA;        'disk_io': 'low',&#xA;        'pseudo_dir': './',&#xA;        'trism': True,&#xA;    },&#xA;    'system': {&#xA;        'ibrav': 0,&#xA;        'nbnd': int(len(slab) * 3 + (len(slab) * 0.3)),&#xA;        'tot_charge': 0.0,&#xA;        'tot_magnetization': -10000,&#xA;        'ecutwfc': 40.0,&#xA;        'ecutrho': 40 * 5,&#xA;        'occupations': 'smearing',&#xA;        'degauss': 0.00735,&#xA;        'smearing': 'cold',&#xA;        'input_dft': 'pbe',&#xA;        'nspin': 1,&#xA;        'assume_isolated': 'esm',&#xA;        'esm_bc': 'bc1',&#xA;        'vdw_corr': 'none',&#xA;    },&#xA;    'electrons': {&#xA;        'electron_maxstep': 999,&#xA;        'scf_must_converge': True,&#xA;        'conv_thr': 1.0e-9,&#xA;        'mixing_mode': 'local-TF',&#xA;        'mixing_beta': 0.20,&#xA;        'mixing_ndim': 8,&#xA;        'diagonalization': 'rmm-davidson',&#xA;        'diago_david_ndim': 2,&#xA;        'diago_rmm_ndim': 4,&#xA;        'diago_rmm_conv': False,&#xA;        'diago_full_acc': False,&#xA;    },&#xA;    'ions': {&#xA;        'ion_dynamics': 'bfgs',&#xA;        'upscale': 100,&#xA;        'bfgs_ndim': 6,&#xA;    },&#xA;    'RISM': {&#xA;        'nsolv': 3,&#xA;        'closure': 'kh',&#xA;        'tempv': 298.15,&#xA;        'ecutsolv': 40 * 5,&#xA;        'solute_lj(1)': 'none',&#xA;        'solute_epsilon(1)': 0.01828,&#xA;        'solute_sigma(1)': 2.70,&#xA;        'starting1d': 'zero',&#xA;        'starting3d': 'zero',&#xA;        'rism1d_maxstep': 50000,&#xA;        'rism3d_maxstep': 5000,&#xA;        'rism1d_conv_thr': 1e-08,&#xA;        'rism3d_conv_thr': 1e-05,&#xA;        'mdiis1d_size': 20,&#xA;        'mdiis3d_size': 10,&#xA;        'mdiis1d_step': 0.1,&#xA;        'mdiis3d_step': 0.8,&#xA;        'rism3d_conv_level': 0.5,&#xA;        'rism3d_planar_average': True,&#xA;        'laue_expand_right': slab.cell[2, 2] * 2 / Bohr,&#xA;        'laue_starting_right': average_z_top_two_layers,&#xA;    }&#xA;}&#xA;write('Li-tester.in', slab, format='espresso-in', input_data=input_data, kpts=[12,12,1], pseudopotentials=pseudopotentials)&#xA;view(slab, viewer='x3d')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Solvents (mol/L):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Li+: 1.0 Li+.oplsaa.MOL&#xA;PF6-: 1.0 PF6-.oplsaa.MOL&#xA;EC: -1.0 EC.oplsua.MOL&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;These must be manually added. Note that the files for the solvent and electrolyte were obtained from Nishihara's GitHub (&lt;a href=&quot;https://github.com/nisihara1/MOLs&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/nisihara1/MOLs&lt;/a&gt;), and the Lennard-Jones parameters for the solvent are obtained from: Jun Haruyama, Tamio Ikeshoji, and Minoru Otani, The Journal of Physical Chemistry C 2018, 122 (18), 9804-9810, DOI: 10.1021/acs.jpcc.8b01979 - supplementary information.&lt;/p&gt;&#xA;&lt;p&gt;Simply put, I wish to solvate a lithium slab in EC, with Li+ &amp;amp; PF6- electrolyte, then explore GC-DFT in QE from this.&lt;/p&gt;&#xA;&lt;p&gt;Maybe I misunderstood some keywords, theory, or even obtaining the LJ parameters from the supplementary information. Any and all help would be most appreciated!&lt;/p&gt;&#xA;&lt;p&gt;Note that the mdiis1d_step was changed from default as this improved 1D-RISM convergence.&lt;/p&gt;&#xA;&lt;p&gt;Kind regards,&#xA;Brad&lt;/p&gt;&#xA;" OwnerUserId="9888" LastActivityDate="2024-02-29T14:05:31.150" Title="Issues converging ESM_RISM in QE for a lithium slab" Tags="|quantum-espresso|solvation|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12489" PostTypeId="2" ParentId="12485" CreationDate="2024-02-29T14:43:55.790" Score="7" Body="&lt;p&gt;&lt;strong&gt;Theoretical Background:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Elastic constants can be calcualted in one of two approaches. First is via the stress-strain relationship, and the second is by strain-energy relationship.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;First approach:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In solids, &lt;span class=&quot;math-container&quot;&gt;$\sigma$&lt;/span&gt; or stress response to &lt;span class=&quot;math-container&quot;&gt;$\varepsilon$&lt;/span&gt; strain (external loading) follows the Hooke’s law which is simplified in the Voigt notation: &lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\sigma_i = \sum_{j=1}^{6}c_{ij}\varepsilon_j$$&lt;/span&gt;&#xA;In this relation, both stress and strain are vectors with 6 components each. While &lt;span class=&quot;math-container&quot;&gt;$C_{ij}$&lt;/span&gt; is a tensor written as 6x6 matrix known as the second order elastic stiffness tensor, which can be determined based on the first order derivative of the stress-strain curves as you can see in the figure&lt;a href=&quot;https://i.stack.imgur.com/6AKCc.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/6AKCc.png&quot; alt=&quot;Stress-Strain relationship&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Second approach:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The second approach is based on the variation in energy when applying small strains (you have to add that manually) to the equilibrium lattice. In this method, the elastic stiffness tensor is derived from the second-order derivative of the total energies versus strain in harmonic approximation: &lt;span class=&quot;math-container&quot;&gt;$$\Delta E(V,\left\{ \varepsilon_i \right\})= E(V,\left\{ \varepsilon_i \right\}) - E(V_0,0) = \frac{V_0}{2} \sum_{j=1}^{6}c_{ij}\varepsilon_j \varepsilon_i\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first two terms are total energies of pristine and distorted lattices with volumes &lt;span class=&quot;math-container&quot;&gt;$V_0$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$V$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How To:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In VASP and to my knowledge, only stress-strain method is applied and it is accessible when you set &lt;code&gt;IBRION=6&lt;/code&gt; and &lt;code&gt;ISIF&amp;gt;=3&lt;/code&gt;, according to &lt;a href=&quot;https://www.vasp.at/wiki/index.php/IBRION&quot; rel=&quot;nofollow noreferrer&quot;&gt;VASP Docs&lt;/a&gt;: The elastic tensor is determined by performing six finite distortions of the lattice and deriving the elastic constants from the strain-stress relationship. The elastic tensor is calculated both, for rigid ions, as well, as allowing for relaxation of the ions.&lt;/p&gt;&#xA;&lt;p&gt;For the other approach, you can use automated tools to save you the time as you need to add the distortion. One example is to use &lt;a href=&quot;https://vaspkit.com&quot; rel=&quot;nofollow noreferrer&quot;&gt;vaspkit&lt;/a&gt;. Detailed explanation is available from the documnetation and I will mention that in here just in case that link might not be active in the future.&lt;/p&gt;&#xA;&lt;p&gt;Prepare the fully-relaxed POSCAR file including the standard conventional cell of your structure. Run vaspkit with task of 102 to generate KPOINTS with fine k-mesh. Prepare following INCAR:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Global Parameters&#xA;  ISTART =  0&#xA;  LREAL  =  F&#xA;  PREC   =  High&#xA;  LWAVE  = F&#xA;  LCHARG = F&#xA;  ADDGRID= .TRUE.&#xA;Electronic Relaxation&#xA;  ISMEAR =  0&#xA;  SIGMA  =  0.05&#xA;  NELM   =  40&#xA;  NELMIN =  4&#xA;  EDIFF  =  1E-08&#xA;Ionic Relaxation&#xA;  NELMIN =  6&#xA;  NSW    =  100&#xA;  IBRION =  2&#xA;  ISIF   =  2    （Must be 2）&#xA;  EDIFFG = -1E-02&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Prepare VPKIT.in file and set the value of first line to 1 (1 means pre-processing)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;1                    ! 1 for pre-processing; 2 for post-processing&#xA;2D                   ! 2D for two-dimentional, 3D for bulk&#xA;7                    ! number of strain case&#xA;-0.015 -0.010 -0.005 0.000 0.005 0.010 0.015  ! Strain range&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Run vaspkit-201, upon which you will create the required folder in the working directory, each of which corresponds to the strain you have introduced, next you will batch perform DFT calucaltions using VASP code in each of those folders. Lastly, Modify the value of the first line in VPKIT.in file to &lt;strong&gt;2&lt;/strong&gt; (2 means post-processing); and run vaspkit-201 again and you will get the calculated elastic constants in the output.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Finally&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The first approach of stress-strain method require higher computational precise to achieve the same accuracy as energy-strain method. Nevertheless, the former requires much smaller set of distortions than the latter. There exist other tools out there that you might want to check as well such as &lt;a href=&quot;https://github.com/zhongliliu/elastool&quot; rel=&quot;nofollow noreferrer&quot;&gt;ELasTool&lt;/a&gt; and &lt;a href=&quot;https://github.com/shahramyalameha/elastool&quot; rel=&quot;nofollow noreferrer&quot;&gt;Elastool&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-02-29T22:48:41.003" LastActivityDate="2024-02-29T22:48:41.003" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12490" PostTypeId="1" CreationDate="2024-02-29T19:49:46.453" Score="4" ViewCount="36" Body="&lt;p&gt;My question is related to the question &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1116/can-you-model-radiation-chemistry-with-existing-md-software&quot;&gt;here&lt;/a&gt; but not exactly the same. The studies which have looked into the excited states of molecules have generally done it by parameterizing the ground-state and excited state of the molecule of interest, and then using those parameters to run independent MD simulations,as described &lt;a href=&quot;https://pubs.acs.org/doi/10.1021/acs.jpcb.3c02975&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/10.1002/qua.22957&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. However, let's say that I am interested in starting from a ground-state simulation, and would like to go towards the excited state during the simulation, and then come back to the ground state. My current methodology is to do this in parts:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Start the simulation with the ground-state parameters.&lt;/li&gt;&#xA;&lt;li&gt;Let the simulation run for N nanoseconds and stop the simulation.&lt;/li&gt;&#xA;&lt;li&gt;Restart the simulation using excited-state parameters, and let it run for the next M nanoseconds.&lt;/li&gt;&#xA;&lt;li&gt;Stop the simulation and change back to ground-state parameters and continue of the remainder of the simulation.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The idea behind this methodology is to assume that radiation is introduced as a kind of perturbation to the system (that's why there is no second minimization). Is there a way where I can smoothly vary between the ground-state and excited-state parameters?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-02-29T19:49:46.453" Title="Modelling excited states using classical MD simulations" Tags="|molecular-dynamics|forcefields|radiation-chemistry|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12491" PostTypeId="2" ParentId="12486" CreationDate="2024-03-01T02:33:55.413" Score="4" Body="&lt;p&gt;I will try to explain why we need dipole corrections using the example of adsorbed atom or molecule on a surface. Suppose that we want to calculate the adsorption energy of an adatom on the surface of monolayer TMD or any other surface as you can see in the figure:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/m1iPj.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/m1iPj.png&quot; alt=&quot;adatom on surface&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this case, we have created a dipole in our structure, and this will affect the potential energy at the vacuum level. Typically, you want the potential to be as accurate as possible. When you have the vacuum, you should have a flat potential energy surface or something near flat. When potential is no longer flat at vacuum, you have effectively a solitude potential that was induced by the introduction of the adatom.&lt;/p&gt;&#xA;&lt;p&gt;Despite that you are not applying an electric field to the structure, you are still getting an effect that simulates an electric field, and this is not ideal and could distort the electron density of the slab and change the energy, that's where you need to correct this perturbation with the dipole correction. The following figure will show you how the potential energy without dipole correction is not longer flat at the vacuum level&lt;a href=&quot;https://i.stack.imgur.com/l5Z4u.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/l5Z4u.png&quot; alt=&quot;Electrostatic potential with/without dipole correction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Suggestion:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I suggest you to calculate the electrostatic potential of the bilayer structure and see whether the second layer is leading to a non-flat potential at the vacuum level, in this case a dipole-correction is needed. Depending on the code you are using, as mentioned in the link you have shared, QE uses &lt;code&gt;emaxpos&lt;/code&gt;, &lt;code&gt;eopreg&lt;/code&gt; and &lt;code&gt;eamp&lt;/code&gt;. If you are using VASP, then the dipole correction is controlled via &lt;code&gt;LDIPOL&lt;/code&gt; and &lt;code&gt;IDIPOL&lt;/code&gt; tags, check the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/LDIPOL&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt; for further read.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-03-01T02:33:55.413" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12492" PostTypeId="1" CreationDate="2024-03-01T08:39:40.810" Score="4" ViewCount="43" Body="&lt;p&gt;I know that there is a configuration file called &lt;code&gt;gui.py&lt;/code&gt; that would be initialized if it is placed in a directory like &lt;code&gt;~/.ase/gui.py&lt;/code&gt; I use that file to change simple things in the view such as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;gui_default_settings['gui_foreground_color'] = '#ffffff' #white&#xA;gui_default_settings['gui_background_color'] = '#000000' #black&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The default color palette in ase seems to be Jmol and one can adjust the color based either on atomic number or number of neighbours.&#xA;I want to change the default colors of atoms when displayed with ase gui by having my own color palette, if that is possible then how to do it or is there some other approach?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-03-01T08:39:40.810" Title="How to Change the Color Palette of Atoms in ASE GUI" Tags="|atomic-simulation-environment|visualization-software|software-assistance|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12493" PostTypeId="1" AcceptedAnswerId="12548" CreationDate="2024-03-01T12:14:04.550" Score="12" ViewCount="171" Body="&lt;p&gt;I wanted to apply a field gradient on my molecule and study some associated property. I'm able use MM point charges w.r.t a QM/MM scheme of doing things to produce a field gradient. But I was wondering if any open-source (or free) quantum chemistry codes have this an a part of its source code. There are commercial codes like Gaussian 16, MOLPRO.. etc. with this capability.&lt;/p&gt;&#xA;&lt;p&gt;Thanks!&lt;/p&gt;&#xA;" OwnerUserId="1944" LastEditorUserId="5" LastEditDate="2024-03-10T23:49:17.807" LastActivityDate="2024-03-10T23:49:17.807" Title="Are there any free or free quantum chemistry codes which can apply an external field gradient?" Tags="|software-recommendations|one-topic-per-answer|pyscf|electric-field|free-software|" AnswerCount="2" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12494" PostTypeId="1" CreationDate="2024-03-02T06:56:12.653" Score="5" ViewCount="219" Body="&lt;p&gt;I'm currently working on phonon calculations using Phonopy and VASP DFPT approach with a 2x2x1 supercell. I'm seeking guidance on:&#xA;K-Points Selection: How should I determine the appropriate k-points for accurate results with Phonopy and VASP DFPT?&#xA;Band Configuration File: What's the process for creating or obtaining the band configuration file for Phonopy and VASP DFPT, and what should it include?&#xA;Any insights or resources related to Phonopy, VASP, and DFPT would be greatly appreciated.&#xA;For 2D material which supercell will be right choice? whether 2×2×1 or anyother?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastActivityDate="2024-03-02T10:36:02.533" Title="Phonon calculations using DFPT" Tags="|vasp|phonopy|phonon-dispersion|dfpt|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12495" PostTypeId="1" CreationDate="2024-03-02T10:18:49.847" Score="3" ViewCount="29" Body="&lt;p&gt;&lt;a href=&quot;https://stats.stackexchange.com/questions/641611/how-can-i-compute-the-longest-relaxation-time&quot;&gt;Cross-posted on Stats.SE&lt;/a&gt; and on &lt;a href=&quot;https://scicomp.stackexchange.com/q/43923/27325&quot;&gt;SciComp&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In the case of Monte Carlo simulations:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Autocorrelation Time (&lt;span class=&quot;math-container&quot;&gt;$\tau_{\text{int}}$&lt;/span&gt;)&lt;/strong&gt;: A measure of how many steps are needed for the correlations in the chain to become small; it affects the variance of estimators based on the Markov chain.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Relaxation Time (&lt;span class=&quot;math-container&quot;&gt;$\tau_{\text{relax}}$&lt;/span&gt;)&lt;/strong&gt;: The time it takes for the Markov chain to approach its equilibrium distribution from an arbitrary starting point.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Longest Relaxation Time (&lt;span class=&quot;math-container&quot;&gt;$\tau_1$&lt;/span&gt;)&lt;/strong&gt;: The slowest timescale on which the system relaxes to equilibrium, which is critical for understanding the overall convergence rate of the Markov chain.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;&lt;strong&gt;I realize that&lt;/strong&gt; autocorrelation time is the sum of autocorrelation values over a given maximum lag time. So, the formula becomes:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\tau_{\text{int}} = \frac{1}{2} + \sum_{t=1}^{\text{max-lag}} ACF(t)&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$ACF()$&lt;/span&gt; is the autocorrelation function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;   ACF(k) = \frac{1}{(n-k)\sigma^2} \sum_{i=1}^{n-k} (x_i - \mu)(x_{i+k} - \mu)&#xA;   $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I also realize that&lt;/strong&gt;, relaxation time can be found by fitting an autocorrelation value to the exponentia decay function (&lt;span class=&quot;math-container&quot;&gt;$A_0 \cdot e^{\frac{-t}{\tau_\text{relax}}}$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;How can I compute the &lt;strong&gt;longest relaxation time&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="5" LastEditDate="2024-03-02T12:23:10.637" LastActivityDate="2024-03-02T12:23:10.637" Title="How can I compute the longest relaxation time?" Tags="|mathematical-modeling|monte-carlo|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12496" PostTypeId="2" ParentId="12494" CreationDate="2024-03-02T10:36:02.533" Score="5" Body="&lt;p&gt;&lt;strong&gt;Clarifiation:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;At first let me point out that Phonons can be calculated either using &lt;strong&gt;DFPT&lt;/strong&gt;, or &lt;strong&gt;Finite Displacement&lt;/strong&gt; methods. You can refer to the extensive answer by ProfM &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1296/1554&quot;&gt;Are there differences in accuracy and reliability between the frozen phonon method and Density Functional Perturbation Theory?&lt;/a&gt;&#xA;and his first comment to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/2002/1554&quot;&gt;answer&lt;/a&gt;, in which it is explained that &lt;strong&gt;Supercells&lt;/strong&gt; are needed in &lt;strong&gt;Finite Differences&lt;/strong&gt; because to describe a phonon of wave vector &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; you need a supercell commensurate with it. In &lt;strong&gt;DFPT&lt;/strong&gt;, you can have a phonon of any wave vector in the primitive cell. Thus, according to your quesiton and as you are willing to use DFPT method, there is no need for you to use a supercell in such calculation unless you have a reason for that (studying a defect, interface or super structure,etc.)&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How To:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In general, the following steps are needed to calculate the vibrational frequencies or phonons: At first, you should have relaxed the atomic positions and/or cell you are working with (primitive cell). Pay close attention to your choice of the KPOINTS, it is recommended to use high-enough kpoints sampling during geometrical relaxation, and use similar values for your further steps as per the answer by Phil Hasnip on a similar problem I had before &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/11991/1554&quot;&gt;The Appearance of Imaginary Frequencies in Lattice Vibration Calculations with Increasing KPOINTS&lt;/a&gt;. Next, ensure that cell symmetries have not been broken. Once you have that done, you can go further to perform DFPT calculation of phonon modes using VASP. Finally, post-process the results to extract modes with &lt;a href=&quot;https://phonopy.github.io/phonopy/&quot; rel=&quot;noreferrer&quot;&gt;Phonopy&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Geometrical Relaxation:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;VASP provides several ways for geometrical relaxation with the ISIF tag. If the desired symmetry of the cell you have is known, but the atomic positions and/or lattice constants are not known, you shall enforce the  symmetry of the starting structure in the POSCAR fileby setting &lt;code&gt;IBRION=2&lt;/code&gt;, and  &lt;code&gt;ISYM=2&lt;/code&gt;. If you just want to relax the atomic positions (lattice constants fixed), choose &lt;code&gt;ISIF=2&lt;/code&gt;. For relaxation of the lattice constants, choose either &lt;code&gt;ISIF=3&lt;/code&gt; (cell volume can vary) or &lt;code&gt;ISIF=4&lt;/code&gt; (cell volume remains fixed). On the other hadn. if the symmetry of the initial structure is not known to be correct. In this case, use &lt;code&gt;IBRION=2&lt;/code&gt;, &lt;code&gt;ISYM=0&lt;/code&gt; (no symmetry) and use &lt;code&gt;ISIF=3&lt;/code&gt; in this case. You will get &lt;code&gt;CONTCAR&lt;/code&gt; file that will be used for the next steps as &lt;code&gt;POSCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Symmetries:&lt;/p&gt;&#xA;&lt;p&gt;When using DFPT method, the lack of symmetry could bring problems in understanding the phonon modes specifically, the assignment of irreducible representations of the normal modes. You may face this problem if the symmetry of your structure is not known and you used &lt;code&gt;IBRION=2&lt;/code&gt; with &lt;code&gt;ISYM=0&lt;/code&gt; and &lt;code&gt;ISIF=3&lt;/code&gt;. You can potentially fix this problem by slightly editing the &lt;code&gt;CONTCAR&lt;/code&gt; file (editing x,y, z components of the lattice constants to your desired symmetry) and do another relaxation with fixed lattice constants &lt;code&gt;ISIF=2&lt;/code&gt; and symmetry &lt;code&gt;ISYM=2&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;DFPT:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Using the previous CONTCAR file as the input POSCAR file, &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Phonons_from_density-functional-perturbation_theory&quot; rel=&quot;noreferrer&quot;&gt;VASP&lt;/a&gt; carries out DFPT calculation with &lt;code&gt;IBRION=7&lt;/code&gt; or &lt;code&gt;IBRION=8&lt;/code&gt;. The difference between those tow options is that &lt;code&gt;IBRION=8&lt;/code&gt; applies symmetry operations to reduce the number of displacements needed, while &lt;code&gt;IBRION=7&lt;/code&gt; does not. However, pay attention that if you choose &lt;code&gt;IBRION=8&lt;/code&gt;, you will not be able to use NCORE/NPAR parallelization. Usually the INCAR file would look like the following (assuming that you are familiar with each of those tags):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NCORE    = 8&#xA;KPAR     = 4 &#xA;ENCUT    = 600&#xA;ALGO     = Normal&#xA;PREC     = Accurate&#xA;EDIFF    = 1.0e-8&#xA;IBRION   = 7&#xA;NSW      = 1&#xA;ISMEAR   = 0&#xA;SIGMA    = 0.05&#xA;LASPH    = True&#xA;LREAL    = False&#xA;ADDGRID  = True&#xA;NWRITE   = 3&#xA;LEPSILON = True &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;Phonopy:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Upon the DFPT calculation is done, you should get the mode symmetries from the vasprun.xml file Phonopy. Firstly, generate a FORCE_CONSTANTS file with the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy --fc vasprun.xml&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;create a file named symm.conf and place the following in there:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;IRREPS = 0 0 0 1e-3 # This is the tolerance&#xA;SHOW_IRREPS = .TRUE.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;After creating this file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy --readfc --dim=&amp;quot;1 1 1&amp;quot; symm.conf&amp;quot;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This command tells Phonopy to read the FORCE_CONSTANTS file, rather than the default FORCE_SETS file generated from the finite displacements method. The second argument specifies the dimensions of a supercell in terms of the primitive cell. Here, we did not create a supercell, so the scaling is 1 in each of the lattice vectors.&lt;/p&gt;&#xA;&lt;p&gt;You can refer to the Phonopy documentation for further steps according to your needs, I will just provide the Phonon dispersion section here: You should create the file band.conf which looks like the following (this is just an example):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOM_NAME = Mo Te&#xA;DIM = 1 1 1&#xA;BAND =    0.000   0.000   0.000     0.500   0.000   0.000    0.3333  0.3333  0.000   0.000   0.000   0.000     0.000   0.000   0.500     0.500   0.000   0.500     0.3333  0.3333  0.500      0.000   0.000   0.500      0.500   0.000   0.500      0.500   0.000   0.000      0.3333  0.3333  0.000      0.3333  0.3333  0.500   &#xA;BAND_LABELS= &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; M K &lt;span class=&quot;math-container&quot;&gt;$\Gamma$&lt;/span&gt; A L H A L M K H&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can use &lt;a href=&quot;https://vaspkit.com&quot; rel=&quot;noreferrer&quot;&gt;vaspkit&lt;/a&gt; to get this file using the option (305), then run the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;phonopy --readfc --dim=&amp;quot;1 1 1&amp;quot; -p band.conf&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can plot the results using your favorite plotting tools, I highly recommend using &lt;a href=&quot;https://smtg-bham.github.io/sumo/sumo-phonon-bandplot.html&quot; rel=&quot;noreferrer&quot;&gt;Sumo&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-03-02T10:36:02.533" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="12497" PostTypeId="1" CreationDate="2024-03-02T13:55:07.380" Score="2" ViewCount="13" Body="&lt;p&gt;I am doing the Raman and FTIR calculations using quantum espresso, I ran the following codes&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  title='Compound 4:bulk:(Si 2)(Ca)(P 3)(O 14):hP(4):P3 (143):primitive:230.81', &#xA;  calculation='scf', &#xA;  pseudo_dir='./', &#xA;  outdir='./tmp', &#xA;  verbosity='high',&#xA;  tprnfor=.true., &#xA;  tstress=.true., &#xA;  forc_conv_thr=1.0d-4, &#xA;  nstep=100,&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  ibrav= 0, nat= 20, ntyp= 4, &#xA;  occupations = 'smearing', smearing = 'gauss', degauss = 1.0d-2,&#xA;  ecutwfc = 50, ecutrho = 500,&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr = 1.0d-8&#xA;  mixing_beta = 0.7d0&#xA;/&#xA;&amp;amp;IONS&#xA;/&#xA;&amp;amp;CELL&#xA;  press_conv_thr=0.1&#xA;/&#xA;ATOMIC_SPECIES&#xA;  Si     28.08550  Si.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;Ca     40.07800  Ca.pbe-spn-rrkjus_psl.1.0.0.UPF&#xA;P      30.97376  P.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;O      15.99940  O.pbe-n-rrkjus_psl.1.0.0.UPF&#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   4.7132930000  0.0000000000  0.0000000000&#xA;  -2.3566465000  4.0818314735  0.0000000000&#xA;   0.0000000000  0.0000000000 11.9970890000&#xA;&#xA;ATOMIC_POSITIONS (crystal)&#xA;  Si  0.0000000000  0.0000000000  0.0000000000&#xA;   O  0.3303280000  0.0650750000  0.0860850000&#xA;   O  0.9349250000  0.2652530000  0.0860850000&#xA;   O  0.7347470000  0.6696720000  0.0860850000&#xA;   P  0.6666670000  0.3333330000  0.1202050000&#xA;   O  0.6666670000  0.3333330000  0.2500000000&#xA;  Ca  0.6666670000  0.3333330000  0.3797950000&#xA;   O  0.3303280000  0.0650750000  0.4139150000&#xA;   O  0.9349250000  0.2652530000  0.4139150000&#xA;   O  0.7347470000  0.6696720000  0.4139150000&#xA;  Si  0.0000000000  0.0000000000  0.5000000000&#xA;   O  0.2652530000  0.3303280000  0.5860850000&#xA;   O  0.0650750000  0.7347470000  0.5860850000&#xA;   O  0.6696720000  0.9349250000  0.5860850000&#xA;   P  0.3333330000  0.6666670000  0.6202050000&#xA;   O  0.3333330000  0.6666670000  0.7500000000&#xA;   P  0.3333330000  0.6666670000  0.8797950000&#xA;   O  0.2652530000  0.3303280000  0.9139150000&#xA;   O  0.0650750000  0.7347470000  0.9139150000&#xA;   O  0.6696720000  0.9349250000  0.9139150000&#xA;K_POINTS {automatic}&#xA;  6 6 2 0 0 0```&#xA;&#xA; &amp;amp;INPUTPH&#xA;      tr2_ph = 1.0d-18,&#xA;      prefix = 'pwscf',&#xA;      outdir = './tmp',&#xA;      epsil = .true.,&#xA;      trans = .true.,&#xA;      lraman = .true.,&#xA;      fildyn = 'pwscf.dyn',&#xA;    /&#xA;    0.0 0.0 0.0&#xA;&#xA;&#xA;&#xA;&amp;amp;INPUT&#xA;      fildyn = 'pwscf.dyn',&#xA;      asr = 'simple',&#xA;      q(1) = 1.0,        !to correct for LO-TO splitting&#xA;      q(2) = 0.0,&#xA;      q(3) = 0.0,&#xA;    /&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, these error messages appeared below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Check: negative core charge=   -0.000001&#xA;     Reading collected, re-writing distributed wavefunctions&#xA;&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine phq_readin (1):&#xA;     The phonon code with US-PP and raman or elop not yet available&#xA; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;&#xA;     stopping ...&#xA;&#xA;&#xA;WARNING: Could not generate an xpmem segment id for this process'&#xA;address space.&#xA;&#xA;The vader shared memory BTL will fall back on another single-copy&#xA;mechanism if one is available. This may result in lower performance.&#xA;&#xA;  Local host: adagp04&#xA;  Error code: 1 (Operation not permitted)&#xA;--------------------------------------------------------------------------&#xA;[adagp04:250395] 15 more processes have sent help message help-btl-vader.txt / xpmem-make-failed&#xA;[adagp04:250395] Set MCA parameter &amp;quot;orte_base_help_aggregate&amp;quot; to 0 to see all help / error messages&#xA;--------------------------------------------------------------------------&#xA;MPI_ABORT was invoked on rank 9 in communicator MPI_COMM_WORLD&#xA;with errorcode 1.&#xA;&#xA;NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.&#xA;You may or may not see output from other processes, depending on&#xA;exactly when Open MPI kills them&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Does anyone know how to help me?&lt;/p&gt;&#xA;" OwnerUserId="7776" LastEditorUserId="1554" LastEditDate="2024-03-02T14:22:48.937" LastActivityDate="2024-03-02T14:22:48.937" Title="Error in the PH file for RAMAN and FTIR calculation" Tags="|density-functional-theory|quantum-espresso|td-dft|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12498" PostTypeId="2" ParentId="12459" CreationDate="2024-03-02T16:32:31.153" Score="4" Body="&lt;p&gt;In general, computing singlet excited states with an unrestricted wavefunction/method is challenging. This is for a few reasons, but one of them is that the SCF procedure tends to converge towards the lowest energy state (because that's what it's designed to do, and normally what you want). For a closed shell molecule, the lowest energy singlet state is S0 (ie, the ground state), and I don't think you can easily manipulate the charge and multiplicity of your system to converge to a higher singlet state.&lt;/p&gt;&#xA;&lt;p&gt;This is in contrast to triplet excited states where you'll see this method used much more commonly (where it is often called Delta-SCF). For a closed shell molecule, the lowest energy triplet state is T1, so a charge/multiplicity line like:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;0 3&lt;/code&gt; (Charge 0 (neutral), Multiplicity 3 (triplet))&lt;/p&gt;&#xA;&lt;p&gt;Would tend to converge to T1. For S1, a simple input like this is not possible I'm afraid.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;If you're trying to recreate the methodology in the paper you linked, you'll run into a few problems. First, you are using a different program (Gaussian) compared to the authors (QChem), so you sadly can't reuse any of their input files. Second, the authors developed part of the functionality that they are benchmarking themselves so this code is not available in all version of Q-Chem. The authors state it should be available from 5.4.1 onwards, but you would have to double-check:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;All quantum-chemical calculations were carried out with a development&#xA;version of the Q-Chem 5.4 program package.1 We have modified the&#xA;original source code to enable ROKS optimizations in combination with&#xA;the IEF-PCM solvent model. The respective modifications will be&#xA;included in the next Q-Chem release (5.4.1).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Phys. Chem. Lett. 2021, 12, 35, 8470–8480 (Supporting information: &lt;a href=&quot;https://pubs.acs.org/doi/suppl/10.1021/acs.jpclett.1c02299/suppl_file/jz1c02299_si_001.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pubs.acs.org/doi/suppl/10.1021/acs.jpclett.1c02299/suppl_file/jz1c02299_si_001.pdf&lt;/a&gt;)&lt;/p&gt;&#xA;&lt;p&gt;Even then, it is clear from the methodology of the above paper that this is a fairly complicated function to implement, and probably not for the faint-hearted. See for example:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Singlet states are optimized with ROKS and UKS, the latter of which is&#xA;in combination with the (initial) maximum-overlap method (MOM/IMOM) to&#xA;avoid a variational collapse to the ground state. (73,75) In the&#xA;UKS/IMOM calculations (in the following just UKS), the excited state&#xA;must be explicitly targeted. This is realized through a manipulation&#xA;of the initial guess orbitals in which one electron is moved from the&#xA;highest occupied molecular orbital (HOMO) to lowest unoccupied&#xA;molecular orbital (LUMO). ROKS optimizations do not need such a guess&#xA;for the excitation vector. They reliably converge on the lowest&#xA;excited singlet state, whereas the UKS optimizations occasionally&#xA;converge on higher-lying solutions (ca. 30% of all cases).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Phys. Chem. Lett. 2021, 12, 35, 8470–8480&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;By contrast, calculating S1 with TD-DFT as suggested by S R Maiti is super easy, have a look at &lt;a href=&quot;https://gaussian.com/td/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://gaussian.com/td/&lt;/a&gt;. The only gotcha is to calculate more excited states than you need (even if you're only interested in S1) because of state reordering. TD-DFT is compatible with SCRF for solvent inclusion, and state specific effects can be included with SCRF=(CorrectedLinearResponse). Even if the accuracy of the TD-DFT is lower than other methods, you may find it is still suitably accurate for solving your problem, which is all that matters.&lt;/p&gt;&#xA;" OwnerUserId="8491" LastActivityDate="2024-03-02T16:32:31.153" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12499" PostTypeId="2" ParentId="12359" CreationDate="2024-03-02T17:02:17.950" Score="2" Body="&lt;p&gt;There are lots of reasons that calculated excited state energies won't match experimental values. Have a look at a good textbook on TD-DFT for why, but in general calculated energies will be higher in energy than the experimental absorption peaks (which is what I think you are comparing to). For emission energies, the calculated vertical excited states can be well off (depending on the Stokes shift).&lt;/p&gt;&#xA;&lt;p&gt;However, you have calculated some very low-energy excited states with energies well into the IR, which is unusual. Did you optimise the geometry before calculating the excited states? If so, I would check the structure, it is easy to draw a porphyrin ring with the wrong number of hydrogens.&lt;/p&gt;&#xA;&lt;p&gt;That being said, you results don't look too bad. Remember that TD-DFT will calculate excited states with no (or very small) oscillator strengths that you are unlikely to observe in an experiment. If you consider which of the excited states have 'high' oscillator strengths you have:&lt;/p&gt;&#xA;&lt;p&gt;735, 532, 499, and 432 nm&lt;/p&gt;&#xA;&lt;p&gt;Which are in the correct ballpark for the experimentally observed peaks at:&lt;/p&gt;&#xA;&lt;p&gt;691, 656, 430 and 351 nm&lt;/p&gt;&#xA;" OwnerUserId="8491" LastActivityDate="2024-03-02T17:02:17.950" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12500" PostTypeId="2" ParentId="12013" CreationDate="2024-03-02T17:53:15.937" Score="2" Body="&lt;h2&gt;&lt;strong&gt;TL/DR&lt;/strong&gt; You cannot easily do optimisations with CCSD(T) in Gaussian. Try a different method instead (CCSD perhaps).&lt;/h2&gt;&#xA;&lt;p&gt;Gaussian only supports numerical gradients for CCSD(T), and the optimisation procedure defaults to the 'EigenvalueFollow' (Opt=EF) procedure when analytic gradients are not available. This method is limited to solving max 50 variables, which is likely too be too few for a 'real' complex molecule. See &lt;a href=&quot;http://www.ccl.net/chemistry/resources/messages/2012/03/13.016-dir/index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.ccl.net/chemistry/resources/messages/2012/03/13.016-dir/index.html&lt;/a&gt;. Non-analytic optimisations are also famously, painfully slow. Unless you are really interested in solving the structure of water, I would recommend using a method with analytic gradients instead (pretty much anything other than CCSD(T), MP5 and MP4 I think).&lt;/p&gt;&#xA;&lt;h2&gt;Also&lt;/h2&gt;&#xA;&lt;p&gt;&lt;code&gt;%CPU=8&lt;/code&gt; requests the calculation run only on CPU 8 (ie, one CPU max). If you instead wanted to run a parallel calculation using 8 CPUs, you want:&lt;/p&gt;&#xA;&lt;p&gt;&lt;code&gt;%NProcShared=8&lt;/code&gt;&lt;/p&gt;&#xA;" OwnerUserId="8491" LastActivityDate="2024-03-02T17:53:15.937" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12501" PostTypeId="1" CreationDate="2024-03-02T18:49:02.057" Score="3" ViewCount="9" Body="&lt;p&gt;I'm working with a SiPOCa structure and I've already done the SCF, NSCF, DOS, BANDS, CHARGE DENSITY, FTIR and RAMAN calculations. Now I would like to calculate the vibrational and thermodynamic measurements of this structure using DFT and Quantum Espresso. Can anyone explain to me how I create the input files to perform these new calculations? Or if anyone can point me to some study material so I can learn&lt;/p&gt;&#xA;" OwnerUserId="7776" LastActivityDate="2024-03-02T18:49:02.057" Title="How to build input files to obtain vibrational and thermodynamic measurements using Quntum Espresso?" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12502" PostTypeId="1" CreationDate="2024-03-02T23:02:51.740" Score="3" ViewCount="41" Body="&lt;p&gt;I want to compare the electronic bands (VBM and CBM) of a double perovskite material with other layer using like  transports both holes and electrons .I tried to calculate them, but the values I obtained are positive.I need help understanding how to calculate the positions of the VBM and conduction band (CBM) energy levels using Quantum Espresso. &lt;a href=&quot;https://i.stack.imgur.com/oCSk6.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/oCSk6.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6003" LastEditorUserId="5" LastEditDate="2024-03-03T01:55:42.740" LastActivityDate="2024-03-03T01:55:42.740" Title="How to calculate band gap alignment for different layers used in double perovskite solar cell?" Tags="|density-functional-theory|quantum-espresso|band-structure|perovskites|solar-cells|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12503" PostTypeId="1" CreationDate="2024-03-03T01:31:06.803" Score="3" ViewCount="31" Body="&lt;p&gt;I am using a DFT+U+V approach and using a pseudohybrid&#xA;density functional for extended Hubbard Coulomb interactions along with GBRV ultrasoft pseudopotentials (PBEsol). This enables me to open a gap in III-V systems and I am currently working on defect calculations of GaSb. I ran relax calculations using pure DFT, extracted the atomic positions, and then inserted those positions into the DFT+U+V input file. However, when I run this system I am not able to converge. I have tried tweaking the convergence threshold, mixing beta, and force/total energy convergence threshold. None of this has yet to work and my total energies in the output oscillates. It seems to be trapped in a local minima.&lt;/p&gt;&#xA;&lt;p&gt;Here is my input file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  &amp;amp;control&#xA;   prefix       = 'gasb',&#xA;   calculation  = 'relax',&#xA;   verbosity    = 'high',&#xA;   disk_io      = 'low',&#xA;   pseudo_dir   = '/anvil/scratch/x-ashipley/PP/',&#xA;   outdir       = './temp',&#xA; /&#xA; &amp;amp;system&#xA;   ibrav = 1, celldm(1) = 22.898548945864921 ,&#xA;   nat = 64, ntyp = 2, nbnd = 600,&#xA;   ecutwfc = 25, ecutrho = 100,&#xA;   occupations = 'smearing', smearing = 'gauss', degauss = 0.005,&#xA;   nspin = 2,&#xA;   starting_magnetization(1) = 0,&#xA;   starting_magnetization(2) = 0,&#xA;   lda_plus_v = .true., lacbn0 = .true., acbn0_type = 2, U_projection_type = 'ortho-atomic', ehub_nn_distance = 3, ehub_pot_fix = .false., ehub_conv_thr = 1.0D-07, ehub_mixing = 0.7,&#xA;   ehub_l_choice(1,1) = 1, ehub_l_choice(1,2) = 1, ehub_l_choice(1,3) = 1, remove_ehub_u(1,1) = 0, remove_ehub_u(1,3) = 0,&#xA;   ehub_l_choice(2,1) = 1, ehub_l_choice(2,2) = 1, ehub_l_choice(2,3) = 1, remove_ehub_u(2,1) = 0, remove_ehub_u(2,3) = 0,&#xA;/&#xA; &amp;amp;electrons&#xA;   diagonalization = 'david',&#xA;   conv_thr        =  1.0D-7,&#xA;   mixing_beta     =  0.7,&#xA;   mixing_mode = 'plain',&#xA;   startingwfc     = 'random',&#xA;   electron_maxstep = 600,&#xA; /&#xA;&amp;amp;ions&#xA; ion_dynamics = 'bfgs',&#xA;/&#xA; ATOMIC_SPECIES&#xA;   Ga 0 ga_pbesol_v1.4.uspp.F.UPF&#xA;   Sb 0 sb_pbesol_v1.4.uspp.F.UPF&#xA; ATOMIC_POSITIONS crystal&#xA;Sb            0.0000000000       -0.0000000000        0.0000000000&#xA;Ga            0.0000000000        0.0000000000        0.5000000000&#xA;Ga            0.0000000000        0.5000000000        0.0000000000&#xA;Ga            0.0000000000        0.5000000000        0.5000000000&#xA;Ga            0.5000000000       -0.0000000000        0.0000000000&#xA;Ga            0.5000000000       -0.0000000000        0.5000000000&#xA;Ga            0.5000000000        0.5000000000        0.0000000000&#xA;Ga            0.5000000000        0.5000000000        0.5000000000&#xA;Ga            0.0027308549        0.2538487641        0.2538487641&#xA;Ga           -0.0027308549        0.2538487641        0.7461512359&#xA;Ga           -0.0027308549        0.7461512359        0.2538487641&#xA;Ga            0.0027308549        0.7461512359        0.7461512359&#xA;Ga            0.5003054101        0.2506818502        0.2506818502&#xA;Ga            0.4996945899        0.2506818502        0.7493181498&#xA;Ga            0.4996945899        0.7493181498        0.2506818502&#xA;Ga            0.5003054101        0.7493181498        0.7493181498&#xA;Ga            0.2538487641        0.0027308549        0.2538487641&#xA;Ga            0.2538487641       -0.0027308549        0.7461512359&#xA;Ga            0.2506818502        0.5003054101        0.2506818502&#xA;Ga            0.2506818502        0.4996945899        0.7493181498&#xA;Ga            0.7461512359       -0.0027308549        0.2538487641&#xA;Ga            0.7461512359        0.0027308549        0.7461512359&#xA;Ga            0.7493181498        0.4996945899        0.2506818502&#xA;Ga            0.7493181498        0.5003054101        0.7493181498&#xA;Ga            0.2538487641        0.2538487641        0.0027308549&#xA;Ga            0.2506818502        0.2506818502        0.5003054101&#xA;Ga            0.2538487641        0.7461512359       -0.0027308549&#xA;Ga            0.2506818502        0.7493181498        0.4996945899&#xA;Ga            0.7461512359        0.2538487641       -0.0027308549&#xA;Ga            0.7493181498        0.2506818502        0.4996945899&#xA;Ga            0.7461512359        0.7461512359        0.0027308549&#xA;Ga            0.7493181498        0.7493181498        0.5003054101&#xA;Sb            0.1253968266        0.1253968266        0.3765742716&#xA;Sb            0.1364394521        0.1364394521        0.8635605479&#xA;Sb            0.1256303329        0.6232578537        0.3767421463&#xA;Sb            0.1253968266        0.6234257284        0.8746031734&#xA;Sb            0.6232578537        0.1256303329        0.3767421463&#xA;Sb            0.6234257284        0.1253968266        0.8746031734&#xA;Sb            0.6245864554        0.6245864554        0.3754135446&#xA;Sb            0.6232578537        0.6232578537        0.8743696671&#xA;Sb            0.1253968266        0.3765742716        0.1253968266&#xA;Sb            0.1256303329        0.3767421463        0.6232578537&#xA;Sb            0.1364394521        0.8635605479        0.1364394521&#xA;Sb            0.1253968266        0.8746031734        0.6234257284&#xA;Sb            0.6232578537        0.3767421463        0.1256303329&#xA;Sb            0.6245864554        0.3754135446        0.6245864554&#xA;Sb            0.6234257284        0.8746031734        0.1253968266&#xA;Sb            0.6232578537        0.8743696671        0.6232578537&#xA;Sb            0.3765742716        0.1253968266        0.1253968266&#xA;Sb            0.3767421463        0.1256303329        0.6232578537&#xA;Sb            0.3767421463        0.6232578537        0.1256303329&#xA;Sb            0.3754135446        0.6245864554        0.6245864554&#xA;Sb            0.8635605479        0.1364394521        0.1364394521&#xA;Sb            0.8746031734        0.1253968266        0.6234257284&#xA;Sb            0.8746031734        0.6234257284        0.1253968266&#xA;Sb            0.8743696671        0.6232578537        0.6232578537&#xA;Sb            0.3754135446        0.3754135446        0.3754135446&#xA;Sb            0.3767421463        0.3767421463        0.8743696671&#xA;Sb            0.3767421463        0.8743696671        0.3767421463&#xA;Sb            0.3765742716        0.8746031734        0.8746031734&#xA;Sb            0.8743696671        0.3767421463        0.3767421463&#xA;Sb            0.8746031734        0.3765742716        0.8746031734&#xA;Sb            0.8746031734        0.8746031734        0.3765742716&#xA;Sb            0.8635605479        0.8635605479        0.8635605479&#xA;&#xA;K_POINTS automatic&#xA;  2 2 2 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;If anyone has any ideas on what I can change or adjust, I would be very grateful for the help.&lt;/p&gt;&#xA;" OwnerUserId="9897" LastEditorUserId="9897" LastEditDate="2024-03-03T01:31:52.293" LastActivityDate="2024-03-03T01:31:52.293" Title="Relax calculation not converging" Tags="|density-functional-theory|cell-optimization|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12504" PostTypeId="1" AcceptedAnswerId="12505" CreationDate="2024-03-04T05:47:11.163" Score="4" ViewCount="169" Body="&lt;p&gt;I have generate a figure illustrating spin texture of one band of a type of material. However I do not know the exact value of the color of background which means (Sz) value. The figure was plotted using python. The python code has utilized the SPINTEXTURE_2D_GAMMA_CENTER.dat file generated by [652] function of vaspkit.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/pggZU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/pggZU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="7083" LastEditorUserId="1554" LastEditDate="2024-03-04T06:49:22.587" LastActivityDate="2024-03-04T14:55:46.653" Title="What is the unit of (Sz) value in the figure of spin texture?" Tags="|vasp|spin|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12505" PostTypeId="2" ParentId="12504" CreationDate="2024-03-04T14:55:46.653" Score="5" Body="&lt;p&gt;&lt;strong&gt;About the Units&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;I believe you have generated your &lt;code&gt;.dat&lt;/code&gt; file with VASP. It is most likely that the values you are finding in the &lt;code&gt;.dat&lt;/code&gt; file are coming from the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/PROCAR&quot; rel=&quot;noreferrer&quot;&gt;PROCAR&lt;/a&gt; file which contains the &lt;em&gt;spd&lt;/em&gt;- and site projected wave function character of each orbital:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;# of k-points:    5         # of bands:   26         # of ions:    3&#xA;&#xA;k-point     1 :    0.00000000 0.00000000 0.00000000     weight = 0.06250000&#xA;&#xA;band     1 # energy  -17.37867948 # occ.  1.00000000&#xA;&#xA;ion      s     py     pz     px    dxy    dyz    dz2    dxz  x2-y2    tot  &#xA;    1  0.144  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.145&#xA;    2  0.291  0.000  0.006  0.000  0.000  0.000  0.000  0.000  0.000  0.298&#xA;    3  0.291  0.000  0.006  0.000  0.000  0.000  0.000  0.000  0.000  0.298&#xA;tot    0.727  0.000  0.013  0.000  0.000  0.000  0.000  0.000  0.000  0.740&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which would look like the following when you consider &lt;code&gt;ISPIN=2&lt;/code&gt; and  &lt;code&gt;LNONCOLLINEAR=.TRUE&lt;/code&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ion      s     py     pz     px    dxy    dyz    dz2    dxz  x2-y2    tot  &#xA;    1  0.144  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.145&#xA;    2  0.291  0.000  0.006  0.000  0.000  0.000  0.000  0.000  0.000  0.298&#xA;    3  0.291  0.000  0.006  0.000  0.000  0.000  0.000  0.000  0.000  0.298&#xA;tot    0.727  0.000  0.013  0.000  0.000  0.000  0.000  0.000  0.000  0.740&#xA;    1 -0.011 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000  0.000 -0.000 -0.011&#xA;    2 -0.023 -0.000 -0.000  0.000  0.000 -0.000 -0.000  0.000 -0.000 -0.023&#xA;    3 -0.023 -0.000 -0.000  0.000  0.000 -0.000 -0.000  0.000 -0.000 -0.023&#xA;tot   -0.057 -0.000 -0.001  0.000  0.000 -0.000 -0.000  0.000 -0.000 -0.058 &#xA;    1 -0.142 -0.000  0.000  0.000  0.000  0.000 -0.000 -0.000 -0.000 -0.142&#xA;    2 -0.286  0.000 -0.006 -0.000 -0.000  0.000 -0.000 -0.000  0.000 -0.293&#xA;    3 -0.286  0.000 -0.006 -0.000 -0.000  0.000 -0.000 -0.000  0.000 -0.293&#xA;tot   -0.715  0.000 -0.012 -0.000 -0.000  0.000 -0.000 -0.000  0.000 -0.727&#xA;    1 -0.024 -0.000  0.000 -0.000 -0.000  0.000 -0.000  0.000 -0.000 -0.024&#xA;    2 -0.048  0.000 -0.001  0.000  0.000  0.000 -0.000  0.000  0.000 -0.049&#xA;    3 -0.048  0.000 -0.001  0.000  0.000  0.000 -0.000  0.000  0.000 -0.049&#xA;tot   -0.119  0.000 -0.002  0.000  0.000  0.000 -0.000  0.000  0.000 -0.121&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The additional set of projections are for the spin down channel and projected magnetizations. The first set is the total (&lt;strong&gt;absolute&lt;/strong&gt;) magnetization, while the remaining three sets of entries correspond to the three directions &lt;span class=&quot;math-container&quot;&gt;$j=1,2,3$&lt;/span&gt;. Those projectd magnetizations are calculated for the wavefunction of the electronic state with spin-up and spin-down components (spinor) and Pauli matrices, the spinor is a two-component vector that describes the spin state of the electron, while Pauli matrices represent the spin operators in the x, y, and z directions, respectively. These matrices describe the spin orientation and provide a mathematical representation of the spin components.&lt;/p&gt;&#xA;&lt;p&gt;Thus the total absolute magnetization is a dimensionless quantity and does not have a specific unit associated with it. It is often normalized to the number of atoms or unit cell volume in the material to obtain a normalized magnetization value, such as magnetization per unit cell or magnetization per atom. Then I would say that if the total magentization is absolute and dimensionless, its components in the x, y, and z directions, should also be dimensionless and without specific units.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;How to understand the plot:&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;We basically have two colors each of which represents a spin-up (positive spin polarization) or spin-down (negative spin polarization). this is an idicator that the majority of spins in certain region are aligned in a particular direction (in/out) of plane. The arrows in spin-texture plots represent the direction and magnitude of the electron spin at each point in the material. The length of the arrows corresponds to the magnitude of the spin, while the direction indicates the spin orientation.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-03-04T14:55:46.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12507" PostTypeId="1" CreationDate="2024-03-04T21:27:13.200" Score="5" ViewCount="40" Body="&lt;p&gt;I have the LAMMPS DUMP file of a salt solution, and I am investigating the Oligomerization of the salt ions in solution. However, when I am trying to visualize the trajectory, I can only draw bonds that are within the original box. Is there a way to draw the periodic bonds, or bonds that can go between the periodic images?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-04T21:27:13.200" Title="How to draw periodic bonds in Visual Molecular Dynamics (VMD)?" Tags="|visualization-software|vmd|periodic-boundary-conditions|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12509" PostTypeId="1" AcceptedAnswerId="12527" CreationDate="2024-03-05T09:47:44.037" Score="5" ViewCount="69" Body="&lt;p&gt;How can I modify the procedure described in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10875/1554&quot;&gt;answer&lt;/a&gt; to achieve adsorption of two or more types of atoms on a surface, each with distinct coverages?&lt;/p&gt;&#xA;&lt;p&gt;Is there an extension to the described method for generating random positions to accommodate the adsorption of multiple atom types with varying coverages?&lt;/p&gt;&#xA;" OwnerUserId="8414" LastEditorUserId="1554" LastEditDate="2024-03-06T12:31:51.350" LastActivityDate="2024-03-06T14:43:13.353" Title="How can one create various arrangements of two or more types of atoms (like O, N etc.) with distinct coverages on a metal surface?" Tags="|vasp|molecular-dynamics|molecular-modeling|python|atomic-simulation-environment|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12510" PostTypeId="1" CreationDate="2024-03-05T10:58:30.800" Score="2" ViewCount="30" Body="&lt;p&gt;Cross-posted in &lt;a href=&quot;https://stats.stackexchange.com/questions/641876/how-can-i-determine-if-a-system-is-equilibrated&quot;&gt;CrossValidated.SE&lt;/a&gt; and &lt;a href=&quot;https://scicomp.stackexchange.com/q/43930/39670&quot;&gt;SCSE&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I am experimenting with a new MCMC protocol and new research.&lt;/p&gt;&#xA;&lt;p&gt;In the context of Monte Carlo simulation, a &amp;quot;state of equilibrium&amp;quot; refers to a condition where the system being simulated has reached a stable configuration or distribution of properties that does not significantly change over time. This state represents a balance or equilibrium between the various forces, interactions, and constraints acting on the system.&lt;/p&gt;&#xA;&lt;p&gt;I wrote the following function to test if a system is equilibrated:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;&#xA;def is_equilibrated(data, shave_size=50000):&#xA;    returns = False&#xA;    mid_index = len(data) // 2&#xA;&#xA;    first_half = data[:mid_index]&#xA;    second_half = data[mid_index:]&#xA;&#xA;    decimals = 6&#xA;&#xA;    while True:&#xA;        first_auto_corr = np.correlate(first_half, first_half, mode='full')&#xA;        second_auto_corr = np.correlate(second_half, second_half, mode='full')&#xA;&#xA;        corr1 = np.corrcoef(first_auto_corr, second_auto_corr)[0, 1]&#xA;&#xA;        print(f&amp;quot;Size {len(first_half)} vs. {len(second_half)}&amp;quot;)&#xA;        print(f&amp;quot;corr  = {corr1} &amp;quot;)&#xA;&#xA;        first_half = first_half[shave_size:]&#xA;        second_half = second_half[shave_size:]&#xA;&#xA;        if corr1 == 1.0:&#xA;            break&#xA;&#xA;    return returns&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The function iteratively compares the autocorrelation of two halves of the input data, shortening the dataset at each iteration, until perfect correlation (equilibrium) is achieved between the two halves or until the loop is manually terminated.&lt;/p&gt;&#xA;&lt;p&gt;I wrote this function to check if my simulation data is &amp;quot;matured&amp;quot; enough to analyze, i.e., good enough to computationally extract further information. In other words, it lets me know if I ran the simulation long enough to obtain a useful dataset.&lt;/p&gt;&#xA;&lt;p&gt;The drawback of this algorithm is that it uses autocorrelation computation, which takes a lot of time, irrespective of the programming language used.&lt;/p&gt;&#xA;&lt;p&gt;Can you propose any &lt;strong&gt;alternative&lt;/strong&gt; technique?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastActivityDate="2024-03-05T10:58:30.800" Title="How can I determine if a system is equilibrated?" Tags="|monte-carlo|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12511" PostTypeId="1" CreationDate="2024-03-05T14:37:44.697" Score="2" ViewCount="21" Body="&lt;p&gt;What factors should be considered to ensure accurate alignment of elastic constants obtained from VASP calculations with those reported in the literature for 2D hexagonal graphene?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="8802" LastEditDate="2024-03-05T15:45:28.690" LastActivityDate="2024-03-05T15:45:28.690" Title="What considerations should be kept in mind to ensure accurate matching of elastic constants in VASP calculations?" Tags="|vasp|physical-properties-of-materials|2d-lattice|elasticity|vaspkit|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12512" PostTypeId="1" AcceptedAnswerId="12513" CreationDate="2024-03-05T16:29:17.787" Score="2" ViewCount="28" Body="&lt;p&gt;As a new user of NAMD, I am seeking assistance regarding a specific task. I intend to pull a LIGAND from outside to the center of a lipid using NAMD. To achieve this, I have utilized the colvar module with the distance option to measure the separation between two distinct groups: the center of mass of LIGAND and as well the center of mass molecules in the center of the lipid.&lt;/p&gt;&#xA;&lt;p&gt;In my attempts to exert control over this process, I have employed a harmonic constraint. However, I have encountered an issue where the LIGAND exhibits movement in multiple directions, contrary to my intention of restricting its motion to a single axis, similar to the pull code in GROMACS.&lt;/p&gt;&#xA;&lt;p&gt;Thus, I am inquiring whether there exists a method within NAMD to confine the axis along which the distance between these two groups decreases.&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-03-05T19:03:52.630" Title="How can a harmonic constraint be added between two groups in one direction using NAMD?" Tags="|molecular-dynamics|namd|enhanced-sampling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12513" PostTypeId="2" ParentId="12512" CreationDate="2024-03-05T16:34:00.373" Score="1" Body="&lt;p&gt;You can try steered molecular dynamics (SMD) for this task. Let's say that you have a ligand and an interaction center. You can write out a new PDB file where you set the occupancy of the ligand atoms to a non-zero number. Then you can enable SMD and give this new PDB file as an input, and the pull direction and the pull velocity. For further information please see this &lt;a href=&quot;https://www.ks.uiuc.edu/Research/namd/2.9/ug/node48.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;link&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Original PDB file&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;REMARK original generated coordinate pdb file&#xA;ATOM      1  N   ARG A   1      -3.903  -0.715  10.177  1.00  0.00      ARG   &#xA;ATOM      2  HT1 ARG A   1      -4.767  -0.149  10.323  1.00  0.00      ARG   &#xA;ATOM      3  HT2 ARG A   1      -3.899  -0.959   9.163  1.00  0.00      ARG   &#xA;ATOM      4  HT3 ARG A   1      -3.865  -1.545  10.788  1.00  0.00      ARG   &#xA;ATOM      5  CA  ARG A   1      -2.758   0.230  10.362  1.00  0.00      ARG   &#xA;ATOM      6  HA  ARG A   1      -2.778   0.610  11.374  1.00  0.00      ARG   &#xA;ATOM      7  CB  ARG A   1      -1.421  -0.522  10.066  1.00  0.00      ARG   &#xA;ATOM      8  HB1 ARG A   1      -1.355  -1.413  10.729  1.00  0.00      ARG   &#xA;ATOM      9  HB2 ARG A   1      -1.434  -0.874   9.009  1.00  0.00      ARG   &#xA;ATOM     10  CG  ARG A   1      -0.139   0.320  10.276  1.00  0.00      ARG   &#xA;ATOM     11  HG1 ARG A   1      -0.168   1.193   9.583  1.00  0.00      ARG   &#xA;ATOM     12  HG2 ARG A   1      -0.133   0.715  11.316  1.00  0.00      ARG   &#xA;ATOM     13  CD  ARG A   1       1.150  -0.455   9.991  1.00  0.00      ARG   &#xA;ATOM     14  HD1 ARG A   1       1.243  -1.319  10.687  1.00  0.00      ARG   &#xA;ATOM     15  HD2 ARG A   1       1.149  -0.807   8.932  1.00  0.00      ARG   &#xA;ATOM     16  NE  ARG A   1       2.293   0.489  10.200  1.00  0.00      ARG   &#xA;ATOM     17  CZ  ARG A   1       3.569   0.161  10.024  1.00  0.00      ARG   &#xA;ATOM     18  NH1 ARG A   1       3.924  -1.052   9.653  1.00  0.00      ARG   &#xA;ATOM     19 HH11 ARG A   1       4.880  -1.272   9.513  1.00  0.00      ARG   &#xA;ATOM     20 HH12 ARG A   1       3.208  -1.716   9.484  1.00  0.00      ARG   &#xA;ATOM     21  NH2 ARG A   1       4.511   1.061  10.219  1.00  0.00      ARG   &#xA;ATOM     22 HH21 ARG A   1       5.463   0.811  10.090  1.00  0.00      ARG   &#xA;ATOM     23 HH22 ARG A   1       4.259   1.980  10.500  1.00  0.00      ARG   &#xA;ATOM     24  C   ARG A   1      -2.953   1.434   9.416  1.00  0.00      ARG   &#xA;ATOM     25  OT1 ARG A   1      -3.891   1.378   8.575  1.00  0.00      ARG   &#xA;ATOM     26  OT2 ARG A   1      -2.184   2.415   9.548  1.00  0.00      ARG   &#xA;ATOM     27  N   ARG     1      -3.989  -0.713   0.193  1.00  0.00      ARG1  &#xA;ATOM     28  HT1 ARG     1      -4.846  -0.133   0.328  1.00  0.00      ARG1  &#xA;ATOM     29  HT2 ARG     1      -3.991  -0.983  -0.814  1.00  0.00      ARG1  &#xA;ATOM     30  HT3 ARG     1      -3.960  -1.528   0.825  1.00  0.00      ARG1  &#xA;ATOM     31  CA  ARG     1      -2.831   0.222   0.350  1.00  0.00      ARG1  &#xA;ATOM     32  HA  ARG     1      -2.843   0.628   1.352  1.00  0.00      ARG1  &#xA;ATOM     33  CB  ARG     1      -1.506  -0.555   0.070  1.00  0.00      ARG1  &#xA;ATOM     34  HB1 ARG     1      -1.449  -1.429   0.755  1.00  0.00      ARG1  &#xA;ATOM     35  HB2 ARG     1      -1.526  -0.932  -0.978  1.00  0.00      ARG1  &#xA;ATOM     36  CG  ARG     1      -0.212   0.276   0.254  1.00  0.00      ARG1  &#xA;ATOM     37  HG1 ARG     1      -0.232   1.132  -0.461  1.00  0.00      ARG1  &#xA;ATOM     38  HG2 ARG     1      -0.197   0.697   1.284  1.00  0.00      ARG1  &#xA;ATOM     39  CD  ARG     1       1.066  -0.522  -0.016  1.00  0.00      ARG1  &#xA;ATOM     40  HD1 ARG     1       1.151  -1.370   0.702  1.00  0.00      ARG1  &#xA;ATOM     41  HD2 ARG     1       1.057  -0.901  -1.065  1.00  0.00      ARG1  &#xA;ATOM     42  NE  ARG     1       2.222   0.412   0.167  1.00  0.00      ARG1  &#xA;ATOM     43  HE  ARG     1       2.026   1.368   0.370  1.00  0.00      ARG1  &#xA;ATOM     44  CZ  ARG     1       3.493   0.063  -0.005  1.00  0.00      ARG1  &#xA;ATOM     45  NH1 ARG     1       3.831  -1.163  -0.346  1.00  0.00      ARG1  &#xA;ATOM     46 HH11 ARG     1       4.784  -1.398  -0.485  1.00  0.00      ARG1  &#xA;ATOM     47 HH12 ARG     1       3.106  -1.822  -0.497  1.00  0.00      ARG1  &#xA;ATOM     48  NH2 ARG     1       4.447   0.956   0.164  1.00  0.00      ARG1  &#xA;ATOM     49 HH21 ARG     1       5.395   0.690   0.038  1.00  0.00      ARG1  &#xA;ATOM     50 HH22 ARG     1       4.208   1.884   0.422  1.00  0.00      ARG1  &#xA;ATOM     51  C   ARG     1      -3.015   1.404  -0.625  1.00  0.00      ARG1  &#xA;ATOM     52  OT1 ARG     1      -3.956   1.338  -1.461  1.00  0.00      ARG1  &#xA;ATOM     53  OT2 ARG     1      -2.233   2.378  -0.520  1.00  0.00      ARG1  &#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;SMDFile&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;CRYST1    0.000    0.000    0.000  90.00  90.00  90.00 P 1           1&#xA;ATOM      1  N   ARG A   1      -3.903  -0.715  10.177  0.00  0.00      ARG   &#xA;ATOM      2  HT1 ARG A   1      -4.767  -0.149  10.323  0.00  0.00      ARG   &#xA;ATOM      3  HT2 ARG A   1      -3.899  -0.959   9.163  0.00  0.00      ARG   &#xA;ATOM      4  HT3 ARG A   1      -3.865  -1.545  10.788  0.00  0.00      ARG   &#xA;ATOM      5  CA  ARG A   1      -2.758   0.230  10.362  0.00  0.00      ARG   &#xA;ATOM      6  HA  ARG A   1      -2.778   0.610  11.374  0.00  0.00      ARG   &#xA;ATOM      7  CB  ARG A   1      -1.421  -0.522  10.066  0.00  0.00      ARG   &#xA;ATOM      8  HB1 ARG A   1      -1.355  -1.413  10.729  0.00  0.00      ARG   &#xA;ATOM      9  HB2 ARG A   1      -1.434  -0.874   9.009  0.00  0.00      ARG   &#xA;ATOM     10  CG  ARG A   1      -0.139   0.320  10.276  0.00  0.00      ARG   &#xA;ATOM     11  HG1 ARG A   1      -0.168   1.193   9.583  0.00  0.00      ARG   &#xA;ATOM     12  HG2 ARG A   1      -0.133   0.715  11.316  0.00  0.00      ARG   &#xA;ATOM     13  CD  ARG A   1       1.150  -0.455   9.991  0.00  0.00      ARG   &#xA;ATOM     14  HD1 ARG A   1       1.243  -1.319  10.687  0.00  0.00      ARG   &#xA;ATOM     15  HD2 ARG A   1       1.149  -0.807   8.932  0.00  0.00      ARG   &#xA;ATOM     16  NE  ARG A   1       2.293   0.489  10.200  0.00  0.00      ARG   &#xA;ATOM     17  CZ  ARG A   1       3.569   0.161  10.024  0.00  0.00      ARG   &#xA;ATOM     18  NH1 ARG A   1       3.924  -1.052   9.653  0.00  0.00      ARG   &#xA;ATOM     19 HH11 ARG A   1       4.880  -1.272   9.513  0.00  0.00      ARG   &#xA;ATOM     20 HH12 ARG A   1       3.208  -1.716   9.484  0.00  0.00      ARG   &#xA;ATOM     21  NH2 ARG A   1       4.511   1.061  10.219  0.00  0.00      ARG   &#xA;ATOM     22 HH21 ARG A   1       5.463   0.811  10.090  0.00  0.00      ARG   &#xA;ATOM     23 HH22 ARG A   1       4.259   1.980  10.500  0.00  0.00      ARG   &#xA;ATOM     24  C   ARG A   1      -2.953   1.434   9.416  0.00  0.00      ARG   &#xA;ATOM     25  OT1 ARG A   1      -3.891   1.378   8.575  0.00  0.00      ARG   &#xA;ATOM     26  OT2 ARG A   1      -2.184   2.415   9.548  0.00  0.00      ARG   &#xA;ATOM     27  N   ARG A   1      -3.989  -0.713   0.193  1.00  0.00      ARG1  &#xA;ATOM     28  HT1 ARG A   1      -4.846  -0.133   0.328  1.00  0.00      ARG1  &#xA;ATOM     29  HT2 ARG A   1      -3.991  -0.983  -0.814  1.00  0.00      ARG1  &#xA;ATOM     30  HT3 ARG A   1      -3.960  -1.528   0.825  1.00  0.00      ARG1  &#xA;ATOM     31  CA  ARG A   1      -2.831   0.222   0.350  1.00  0.00      ARG1  &#xA;ATOM     32  HA  ARG A   1      -2.843   0.628   1.352  1.00  0.00      ARG1  &#xA;ATOM     33  CB  ARG A   1      -1.506  -0.555   0.070  1.00  0.00      ARG1  &#xA;ATOM     34  HB1 ARG A   1      -1.449  -1.429   0.755  1.00  0.00      ARG1  &#xA;ATOM     35  HB2 ARG A   1      -1.526  -0.932  -0.978  1.00  0.00      ARG1  &#xA;ATOM     36  CG  ARG A   1      -0.212   0.276   0.254  1.00  0.00      ARG1  &#xA;ATOM     37  HG1 ARG A   1      -0.232   1.132  -0.461  1.00  0.00      ARG1  &#xA;ATOM     38  HG2 ARG A   1      -0.197   0.697   1.284  1.00  0.00      ARG1  &#xA;ATOM     39  CD  ARG A   1       1.066  -0.522  -0.016  1.00  0.00      ARG1  &#xA;ATOM     40  HD1 ARG A   1       1.151  -1.370   0.702  1.00  0.00      ARG1  &#xA;ATOM     41  HD2 ARG A   1       1.057  -0.901  -1.065  1.00  0.00      ARG1  &#xA;ATOM     42  NE  ARG A   1       2.222   0.412   0.167  1.00  0.00      ARG1  &#xA;ATOM     43  HE  ARG A   1       2.026   1.368   0.370  1.00  0.00      ARG1  &#xA;ATOM     44  CZ  ARG A   1       3.493   0.063  -0.005  1.00  0.00      ARG1  &#xA;ATOM     45  NH1 ARG A   1       3.831  -1.163  -0.346  1.00  0.00      ARG1  &#xA;ATOM     46 HH11 ARG A   1       4.784  -1.398  -0.485  1.00  0.00      ARG1  &#xA;ATOM     47 HH12 ARG A   1       3.106  -1.822  -0.497  1.00  0.00      ARG1  &#xA;ATOM     48  NH2 ARG A   1       4.447   0.956   0.164  1.00  0.00      ARG1  &#xA;ATOM     49 HH21 ARG A   1       5.395   0.690   0.038  1.00  0.00      ARG1  &#xA;ATOM     50 HH22 ARG A   1       4.208   1.884   0.422  1.00  0.00      ARG1  &#xA;ATOM     51  C   ARG A   1      -3.015   1.404  -0.625  1.00  0.00      ARG1  &#xA;ATOM     52  OT1 ARG A   1      -3.956   1.338  -1.461  1.00  0.00      ARG1  &#xA;ATOM     53  OT2 ARG A   1      -2.233   2.378  -0.520  1.00  0.00      ARG1  &#xA;END&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;NAMD Input Section&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;SMD           on&#xA;SMDFile       merged_smd.pdb&#xA;SMDk          1.0&#xA;SMDVel        0.005&#xA;SMDDir        {0 0 1}&#xA;SMDOutputFreq $restartFreq&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I am not sure about the format for SMDDir, but you should be able to figure it out.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-03-05T19:03:52.630" LastActivityDate="2024-03-05T19:03:52.630" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12514" PostTypeId="1" CreationDate="2024-03-05T17:32:35.557" Score="2" ViewCount="35" Body="&lt;p&gt;Let's suppose I want to run the same calculation but for different configurations (= different POSCAR). For all calculations I have the same INCAR, POTCAR and KPOINTS. Those could be stored in a parent directory and in each subdirectory there is the POSCAR. Now I want to run a bashscript (.sh file), where the working directory is the directory with POSCAR. Is it possible to call the INCAR, POTCAR, KPOINTS from the parent directory ? I do not want to copy them in each directory.&lt;/p&gt;&#xA;&lt;p&gt;Best,&#xA;Lukas&lt;/p&gt;&#xA;" OwnerUserId="8715" LastActivityDate="2024-03-05T23:41:07.880" Title="How to call VASP input files from parent directory" Tags="|vasp|software|high-performance-computing|software-input-file-request|high-throughput|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12515" PostTypeId="1" AcceptedAnswerId="12516" CreationDate="2024-03-05T19:47:41.157" Score="5" ViewCount="62" Body="&lt;p&gt;I am doing umbrella sampling in NAMD and I want to control the distance in the colvars to be in one direction. Is there any possibility?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-03-05T19:59:21.363" Title="How can I specify the direction of motion in the colvars file?" Tags="|molecular-dynamics|namd|enhanced-sampling|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12516" PostTypeId="2" ParentId="12515" CreationDate="2024-03-05T19:59:21.363" Score="2" Body="&lt;p&gt;You can use the collars module to achieve the same. Your colvars file would look something like this&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;distanceZ {&#xA;       &#xA;      main {&#xA;            atom numbers of the group that you want to move&#xA;      }&#xA;      ref {&#xA;            atom numbers of the group that you are keeping constant&#xA;      }&#xA;      axis (0.0, 0.0, -1.0)&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-05T19:59:21.363" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12517" PostTypeId="2" ParentId="12493" CreationDate="2024-03-05T20:43:52.117" Score="-1" Body="&lt;p&gt;A quantum chemistry software that is free, I recommend: &lt;a href=&quot;https://www.orcasoftware.de/tutorials_orca/&quot; rel=&quot;nofollow noreferrer&quot;&gt;ORCA&lt;/a&gt;. Among its functionalities, it include QM/MM calculations. These calculations can be modeled with the inclusion of a external field, the suggested way is as follows:&lt;/p&gt;&#xA;&lt;p&gt;Regarding the external field, I found from a &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/3900/adding-external-electric-field-in-orca-with-specific-strength&quot;&gt;previous question&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Actually there is an undocumented feature for this purpose:&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;pre&gt;&lt;code&gt;%scf&#xA;   efield X-field-strength-in-a.u. , Y-field-strength-in-a.u. , Z-field-strength-in-a.u.&#xA;end&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;I have used it to compare dipole moments obtained via numeric and analytic differentiation and it worked fine. But do be careful as undocumented features do not officially exist (although in this case it might have just been overlooked in the manual)&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="8416" LastEditorUserId="8416" LastEditDate="2024-03-06T08:43:00.680" LastActivityDate="2024-03-06T08:43:00.680" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12518" PostTypeId="2" ParentId="12514" CreationDate="2024-03-05T23:41:07.880" Score="2" Body="&lt;p&gt;For VASP it is best to just copy over the duplicate files.  You can use a tool like ASE which allows you to move just a single script (that will end up generating these duplicate files) or you can symbolically link the files such that the same INCAR is used for each calculation.&lt;/p&gt;&#xA;&lt;p&gt;This symbolic link trick can be used to save a lot of space in terms of INCARs or be used to move CHGCAR or WAVECAR files off to a scratch directory for example as well, if file space is the concern.&lt;/p&gt;&#xA;" OwnerUserId="697" LastActivityDate="2024-03-05T23:41:07.880" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12519" PostTypeId="1" CreationDate="2024-03-06T01:15:40.430" Score="7" ViewCount="26" Body="&lt;p&gt;I am a newcomer to MD simulations,&#xA;so my questions may be at a basic level,&#xA;but I appreciate your understanding.&lt;/p&gt;&#xA;&lt;p&gt;I would like to simulate solid-solid phase transitions using MD simulations.&#xA;To begin with, I need to establish a layer structure,&#xA;but I'm unsure about how to construct a single layer&#xA;when the lattice constants of this structure vary significantly.&lt;/p&gt;&#xA;&lt;p&gt;For reference,&#xA;structure 1 has a space group of (R-3), with a=b=38.4 Å, C=5.6 Å (alpha, beta, gamma=90, 90, 120).&#xA;Structure 2 corresponds to space group (R-3) with a=b= 16.6 Å, c= 5.5 Å (alpha, beta, gamma=90, 90, 120).&lt;/p&gt;&#xA;&lt;p&gt;Since the lattice constants of the two structures differ significantly,&#xA;in order to match the structures and construct layers,&#xA;should I consider creating a large supercell layer with lattice constants a and b as common multiples, for example, a=b=115 Å?&#xA;Would this be the optimal approach for performing simulations?&lt;/p&gt;&#xA;" OwnerUserId="9913" LastEditorUserId="1554" LastEditDate="2024-03-06T01:21:49.560" LastActivityDate="2024-03-06T01:21:49.560" Title="Question about Constructing Supercell Layers for MD Simulations for Solid-Solid Phase Transitions" Tags="|molecular-dynamics|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12520" PostTypeId="2" ParentId="12358" CreationDate="2024-03-06T10:58:49.987" Score="1" Body="&lt;p&gt;Thanks for updating the question PriZarah, I can now at least suggest what might be causing the problem.&lt;/p&gt;&#xA;&lt;h2&gt;It's probably just very, very slow&lt;/h2&gt;&#xA;&lt;p&gt;In your recent example, you are calculating a reasonably large system (~20 atoms) with a large basis set (triple-zeta) with only 4 CPUs (&lt;code&gt;%nprocshared=4&lt;/code&gt;) and very little memory (&lt;code&gt;%mem=1GB&lt;/code&gt;). For a calculation of this complexity you need to allocate a lot more resources to have it complete in a reasonable amount of time. Most calculations like this are performed on high-performing computing (HPC) servers using many CPUs in parallel (~16-32 wouldn't be uncommon) and very large amount of memory (~20-80 GB perhaps).&lt;/p&gt;&#xA;&lt;p&gt;To run this sort of calculation on a personal PC you need to allocate as many CPUs and as much memory as possible. Open task manager and see how much free memory your system has at idle, and allocate all of this (for example if you see you have 16GB total and 8GB free, allocate &lt;code&gt;%mem=8GB&lt;/code&gt;). Likewise determine how many CPU cores you have and allocate all but one of these (so if you have 16 cores total, allocate &lt;code&gt;%nprocshared=15&lt;/code&gt;). Start with a much smaller basis set and increase sequentially until you get the results you want, or you run out of patience. An optimisation with a triplet-zeta basis set should take hours for a reasonably large system. I would recommend:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;First &lt;code&gt;STO-3G&lt;/code&gt;, to make sure everything is working&lt;/li&gt;&#xA;&lt;li&gt;Then a small split valence set, maybe &lt;code&gt;3-21G&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Then consider &lt;code&gt;cc-pVDZ&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;If you're still going, then try &lt;code&gt;cc-pVTZ&lt;/code&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2&gt;Why does it get stuck here?&lt;/h2&gt;&#xA;&lt;p&gt;I'm not sure exactly which part of the calculation Gaussian get's stuck at, but this looks like the start of the first optimisation cycle. I would guess it's calculating the gradient, which is often a very slow operation. You can always check whether Gaussian is working hard in task manager. If you see lots of Gaussian processes consuming CPU, it's doing its thing.&lt;/p&gt;&#xA;" OwnerUserId="8491" LastActivityDate="2024-03-06T10:58:49.987" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12522" PostTypeId="1" CreationDate="2024-03-06T13:38:36.267" Score="2" ViewCount="23" Body="&lt;p&gt;Using SIESTA for bulk Si (not optimized, downloaded from materialsproject.org), I am trying to optimize the DZP basis set using the &lt;code&gt;PAO.EnergyShift&lt;/code&gt; parameter. SIESTA official documentation mentions that one should minimize the &amp;quot;BASIS_ENTHALPY&amp;quot; instead of the total energy when performing basis optimization. The following is a plot of both the &amp;quot;Total Energy&amp;quot; and the &amp;quot;Basis Enthalpy&amp;quot; as a function of &lt;code&gt;EnergyShift&lt;/code&gt;. The pseudopotential is obtained from &amp;quot;pseudodojo.com&amp;quot; (Norm conserving, scalar relativistic).&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uOeJo.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uOeJo.png&quot; alt=&quot;Basis Enthalpy and total Energy vs EnergyShift&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The difference in energy shift that minimizes both the enthalpy and the total energy is large. The same behavior appeared also for Si slabs. So what should be considered as a good energy shift?&lt;/p&gt;&#xA;" OwnerUserId="8813" LastActivityDate="2024-03-06T13:38:36.267" Title="SIESTA basis set optimization (Enthalpy vs total energy)" Tags="|siesta|basis-sets|optimization|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12523" PostTypeId="2" ParentId="12469" CreationDate="2024-03-06T13:43:49.960" Score="2" Body="&lt;p&gt;I would like to suggest any easy tools for this if you don't want to code. You can use CHARMM Polymer builder for this purpose. In CHARMM Polymer builder, under a single chain, look for Polyethylene oxide, and specify the degree of polymerization you want. If you want to take the initial structure for the monomer, you need to code, which I think is trivial.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastActivityDate="2024-03-06T13:43:49.960" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12524" PostTypeId="1" CreationDate="2024-03-06T14:25:42.290" Score="3" ViewCount="57" Body="&lt;p&gt;I'm interested in discussing the performance of the new version of NAMD. It seems that in this updated version, there's an increased reliance on GPU processing. However, despite using this new version, I haven't observed any notable improvements compared to the previous iteration.&lt;/p&gt;&#xA;&lt;p&gt;Below are the submission codes and the average processing times for both versions:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NAMD_3.0b6_Linux-x86_64-multicore-CUDA/namd3 +p24 +idlepoll &lt;span class=&quot;math-container&quot;&gt;$NAMD_INPUT &amp;gt; $&lt;/span&gt;NAMD_OUTPUT&#xA;Average time = 93.65 ns/day&#xA;&#xA;NAMD_3.0b3_Linux-x86_64-multicore-CUDA/namd3 +p24 +idlepoll &lt;span class=&quot;math-container&quot;&gt;$NAMD_INPUT &amp;gt; $&lt;/span&gt;NAMD_OUTPUT&#xA;Average time = 93.55 ns/day&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I don't know if there is some wrong. What do you think?&lt;/p&gt;&#xA;" OwnerUserId="4657" LastActivityDate="2024-03-06T14:41:35.207" Title="The performance of NAMD?" Tags="|namd|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12525" PostTypeId="1" AcceptedAnswerId="12529" CreationDate="2024-03-06T14:41:07.513" Score="7" ViewCount="233" Body="&lt;p&gt;Normally, I run all my SIESTA calculations manually and then go to post-processing the results, also manually.&lt;/p&gt;&#xA;&lt;p&gt;I would like to know which of the tools below is &amp;quot;better&amp;quot; (more complete?) in order to make a more efficient use of time when using SIESTA.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://wiki.fysik.dtu.dk/ase/index.html&quot; rel=&quot;noreferrer&quot;&gt;Atomic Simulation Environment&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://www.aiida.net/index.html&quot; rel=&quot;noreferrer&quot;&gt;AiiDA&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://zerothi.github.io/sisl/&quot; rel=&quot;noreferrer&quot;&gt;SISL&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;" OwnerUserId="24" LastEditorUserId="5" LastEditDate="2024-03-07T12:19:18.940" LastActivityDate="2024-03-07T12:19:18.940" Title="Better SIESTA workflows system?" Tags="|software-recommendations|atomic-simulation-environment|siesta|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12526" PostTypeId="2" ParentId="12524" CreationDate="2024-03-06T14:41:35.207" Score="2" Body="&lt;p&gt;The performance of NAMD is highly dependent on the underlying system hardware and the settings that you had used during the compilation process. However, here are a few things that you can check:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;Try using +isomalloc_sync in your script along with +idlepoll.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Ensure that you have the correct MPI bindings, which means that you might have to recompile the binary.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Check if you are having full utilization of the available GPU and CPU cores.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Most important, please check if you are using reasonable values for your time step and write out frequencies.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-06T14:41:35.207" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12527" PostTypeId="2" ParentId="12509" CreationDate="2024-03-06T14:43:13.353" Score="4" Body="&lt;p&gt;ACAT dev here. Yes you can add different adsorbates, each with distinct coverage. However, you will need to use a more general &lt;a href=&quot;https://asm-dtu.gitlab.io/acat/build.html#acat.build.adlayer.RandomPatternGenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;code&gt;acat.build.adlayer.RandomPatternGenerator&lt;/code&gt;&lt;/a&gt; class. Below is an example which you generate 10 random adlayer patterns on a Ni(211) surface with 2/18 ML C*, 3/18 ML N* and 4/18 ML O*:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.build.adlayer import RandomPatternGenerator as RPG&#xA;from acat.adsorption_sites import SlabAdsorptionSites&#xA;from ase.io import read, write&#xA;from ase.visualize import view&#xA;from ase.build import fcc211&#xA;&#xA;slab_211 = fcc211('Ni', (6,3,4), vacuum=5.)&#xA;sas_211 = SlabAdsorptionSites(slab_211, surface='fcc211')&#xA;&#xA;rpg = RPG(slab_211, adsorbate_species='C', # add 2/18 ML C*&#xA;          min_adsorbate_distance=1.5,&#xA;          adsorption_sites=sas_211,&#xA;          trajectory='test1.traj')&#xA;rpg.run(num_gen=10, action='add', num_act=2)&#xA;images = read('test1.traj', index=':')&#xA;rpg = RPG(images, adsorbate_species='N', # add 3/18 ML N*&#xA;          min_adsorbate_distance=1.5,&#xA;          adsorption_sites=sas_211,&#xA;          trajectory='test1.traj',&#xA;          )&#xA;rpg.run(num_gen=10, action='add', num_act=3)&#xA;images = read('test1.traj', index=':')&#xA;rpg = RPG(images, adsorbate_species='O', # add 4/18 ML O*&#xA;          min_adsorbate_distance=1.5,&#xA;          adsorption_sites=sas_211,&#xA;          trajectory='test1.traj',&#xA;          )&#xA;rpg.run(num_gen=10, action='add', num_act=4)&#xA;images = read('test1.traj', index=':')&#xA;view(images[0])&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/lBUTL.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/lBUTL.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2024-03-06T14:43:13.353" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12528" PostTypeId="1" CreationDate="2024-03-06T17:58:14.590" Score="4" ViewCount="28" Body="&lt;p&gt;I am seeking assistance in calculating the individual polarization matrix from CP2K. While utilizing the Polar input under FORCE_EVAL -&amp;gt; PROPERTIES -&amp;gt; LINRES -&amp;gt; POLAR, I observed that the output provides the bulk polarization of the entire system but I want to know how to obtain the individual polarization matrix through CP2K.&lt;/p&gt;&#xA;&lt;p&gt;Any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="9919" LastEditorUserId="6468" LastEditDate="2024-03-06T18:10:35.147" LastActivityDate="2024-03-06T18:10:35.147" Title="Query regarding individual polarization calculation using CP2K" Tags="|molecular-modeling|ab-initio-calculations|cp2k|aimd|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12529" PostTypeId="2" ParentId="12525" CreationDate="2024-03-07T10:17:19.597" Score="8" Body="&lt;p&gt;This answer is based on the current state of things (and will likely change rather quickly).&lt;/p&gt;&#xA;&lt;p&gt;In the following I differentiate between a &lt;em&gt;workflow&lt;/em&gt; and &lt;em&gt;post-processing&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;workflow&lt;/strong&gt;:&lt;br /&gt;&#xA;A workflow is, IMHO, something that utilises automation. I.e. one submits a job with a workflow scheme, that then does everything for you.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;post-processing&lt;/strong&gt;:&lt;br /&gt;&#xA;A manual labor interaction with the software.&lt;/p&gt;&#xA;&lt;h3&gt;ASE&lt;/h3&gt;&#xA;&lt;p&gt;This just got an overhaul very recently [end of February 2024]:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3269&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3269&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3270&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3270&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3271&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3271&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3272&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3272&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3273&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3273&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3278&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3278&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;&lt;a href=&quot;https://gitlab.com/ase/ase/-/merge_requests/3279&quot; rel=&quot;noreferrer&quot;&gt;https://gitlab.com/ase/ase/-/merge_requests/3279&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;(likely I missed a few).&lt;/p&gt;&#xA;&lt;p&gt;The current status of the ASE interface is that it should work stable against the coming Siesta 5 release. This is the aim.&lt;/p&gt;&#xA;&lt;p&gt;I would call the current ASE implementation &lt;em&gt;very&lt;/em&gt; stable with the above things. However, do note that this hasn't been released yet.&lt;/p&gt;&#xA;&lt;p&gt;The ASE implementation is a rather simple way of dealing with workflows, it still requires some manual labor for managing the workflows, so if you are looking for highly automated workflows with thousands of runs, then I would not suggest going this route.&lt;/p&gt;&#xA;&lt;p&gt;ASE implements a very limited output parsing.&#xA;It can read the some output energies, bandstructure information, fermi-level and some &lt;code&gt;PAO.Basis&lt;/code&gt; block settings.&lt;/p&gt;&#xA;&lt;p&gt;But that is more or less it.&lt;/p&gt;&#xA;&lt;h3&gt;AiiDA&lt;/h3&gt;&#xA;&lt;p&gt;The Siesta AiiDA implementation can be found &lt;a href=&quot;https://docs.siesta-project.org/projects/aiida-siesta/en/latest/workflows/index.html&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The AiiDA interface backend is developed with the coming Siesta 5 release. AFAIK it can do things that ASE can't do, and vice versa.&lt;/p&gt;&#xA;&lt;p&gt;AiiDA is really based on doing a large number of calculations in a &lt;em&gt;proper&lt;/em&gt; workflow. I.e. the AiiDA database will store input and output files so one can always grab the information from a particular run.&lt;br /&gt;&#xA;This complexity is extremely useful when doing thousands of systematic calculations where one can automate a lot of the processes.&lt;/p&gt;&#xA;&lt;p&gt;It can still be used for single runs, but the learning curve for AiiDA, I would argue, is a bit steeper than ASE.&lt;/p&gt;&#xA;&lt;p&gt;So, bottom line, AiiDA is really great for large systematic calculations. It might also be useful for smaller things such as single system investigations, but it requires more of the user. :)&lt;/p&gt;&#xA;&lt;p&gt;For post-processing data, AiiDA also offers a limited set of interaction points.&lt;br /&gt;&#xA;It can also do bandgap analysis, system convergence among other things.&#xA;But they are tightly bound in the code-base, and might be a bit difficult to extend (not an expert, so I might be wrong!).&lt;/p&gt;&#xA;&lt;h3&gt;sisl&lt;/h3&gt;&#xA;&lt;p&gt;Disclaimer: Author of sisl&lt;/p&gt;&#xA;&lt;p&gt;sisl is never meant to be a workflow engine.&lt;br /&gt;&#xA;Its inception was about the idea of allowing users to easily script post-processing utilities. As such it focuses on handling the &lt;em&gt;output&lt;/em&gt; of calculations in a very stringent manner.&lt;/p&gt;&#xA;&lt;p&gt;For instance sisl allows one to read&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;em&gt;any&lt;/em&gt; of the grid output variables, &lt;code&gt;RHO&lt;/code&gt;, &lt;code&gt;DRHO&lt;/code&gt;, &lt;code&gt;LDOS&lt;/code&gt;, &lt;code&gt;VT&lt;/code&gt;, &lt;code&gt;VH&lt;/code&gt;, ...&lt;/li&gt;&#xA;&lt;li&gt;Hamiltonian and overlap matrices, can post-process it to generate band-structures&lt;/li&gt;&#xA;&lt;li&gt;Density matrices, can post-process to calculate Mulliken and other kinds of charges&lt;/li&gt;&#xA;&lt;li&gt;reads in basis-set information and allows one to expand density-matrices to real-space grids&lt;/li&gt;&#xA;&lt;li&gt;reads forces from &lt;code&gt;FA&lt;/code&gt; files&lt;/li&gt;&#xA;&lt;li&gt;parses bands file outputs&lt;/li&gt;&#xA;&lt;li&gt;parses &lt;code&gt;PDOS&lt;/code&gt; output files (with command-line-interfaces for plotting)&lt;/li&gt;&#xA;&lt;li&gt;reads (I think) all the geometry output file formats&lt;/li&gt;&#xA;&lt;li&gt;can parse the SCF cycle in a very detailed manner, e.g. check convergence of the SCF cycle by extracting dD/Hmax and other values.&lt;/li&gt;&#xA;&lt;li&gt;sisl is not &lt;em&gt;only&lt;/em&gt; Siesta based. It also tries to parse output files from other programs, these are not as sufficiently developed, but if there is a use-case and a PR, it will be appreciated :)&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;On top of the above, it can manipulate the output data in many different ways.&lt;/p&gt;&#xA;&lt;p&gt;sisl also has an advance plotting facility, build around &lt;code&gt;plotly&lt;/code&gt; which can do pretty advanced things (attribute to @pol-febrer).&lt;/p&gt;&#xA;&lt;p&gt;All of the above can be done in &lt;em&gt;scripting&lt;/em&gt; mode in Python, but other more simple things can be done via the command-line:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-shell prettyprint-override&quot;&gt;&lt;code&gt;# Plot (via matplotlib) the PDOS data&#xA;sdata siesta.PDOS --plot [options for selecting atoms etc. is available]&#xA;# Create a cube file of the charge-density difference from a reference charge-density&#xA;sgrid reference/Rho.grid.nc --diff Rho.grid.nc --geometry RUN.fdf --out diff.cube&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;There are many more options.&lt;/p&gt;&#xA;&lt;p&gt;sisl is tightly following Siesta, and it is usable with older versions, and the coming Siesta 5 release.&lt;/p&gt;&#xA;&lt;p&gt;For everyday post-processing I would argue that sisl is the more complete package. sisl is not meant to &lt;em&gt;be&lt;/em&gt; a workflow, it is meant for users to create workflows around it. So if you want some kind of workflow, then using sisl underneath might be a good choice.&lt;/p&gt;&#xA;" OwnerUserId="887" LastEditorUserId="1518" LastEditDate="2024-03-07T11:38:52.653" LastActivityDate="2024-03-07T11:38:52.653" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12530" PostTypeId="1" CreationDate="2024-03-07T12:51:16.743" Score="4" ViewCount="67" Body="&lt;p&gt;In a symmetric 1D system, the intrinsic topological orders are characterized by the total Zak phase (&lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt;) summed over all occupied states&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}\gamma=\sum_{n}^{}\gamma_n$$&lt;/span&gt;where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the band index. For that, one needs to find the Zak phase for each of the occupied states by integrating the Berry connection across the 1D Brillouin zone:&lt;span class=&quot;math-container&quot;&gt;$$\gamma_n=i\int_{BZ}^{} &amp;lt;u_{nk}|\frac{\partial u_{nk}}{\partial k}&amp;gt; dk\tag{2}$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$u_{nk}$&lt;/span&gt; is the periodic part of the Bloch states of band &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt;. If the system under consideration holds spatial symmetries such as inversion and/or mirror symmetry, then the total Zak phase could be quantized to &lt;span class=&quot;math-container&quot;&gt;$0$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt; (mod 2&lt;span class=&quot;math-container&quot;&gt;$\pi$&lt;/span&gt;).&lt;/p&gt;&#xA;&lt;p&gt;Analytically, the total Zak phase &lt;span class=&quot;math-container&quot;&gt;$\gamma$&lt;/span&gt; can be calculated through another topological invariant (&lt;span class=&quot;math-container&quot;&gt;$\mathbb{Z_2}$&lt;/span&gt;), which is related to the wave function parities at time-reversal invariant points of the BZ. How am I supposed to obtain the parity eigenvalues &lt;span class=&quot;math-container&quot;&gt;$\xi(i)$&lt;/span&gt; for the occupied bands?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-03-10T08:58:41.280" LastActivityDate="2024-03-10T08:58:41.280" Title="How to Obtain the Zak Phase in Symmetric one-dimensional (1D) Systems?" Tags="|symmetry|topological-insulators|brillouin-zone|wannier90|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12531" PostTypeId="2" ParentId="4201" CreationDate="2024-03-07T12:52:11.000" Score="2" Body="&lt;p&gt;In &lt;a href=&quot;https://zerothi.github.io/sisl/&quot; rel=&quot;nofollow noreferrer&quot;&gt;sisl&lt;/a&gt; one can do the derivatives if one has access to the Hamiltonian.&lt;/p&gt;&#xA;&lt;p&gt;The sisl code is heavily dependent on the LCAO formalism. So if you can't work with Hamiltonians it might be more difficult (read implement your own derivative function).&lt;/p&gt;&#xA;&lt;p&gt;One can e.g. do something like this:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sisl as si&#xA;# Read in a Siesta Hamiltonian&#xA;H = si.get_sile(&amp;quot;RUN.fdf&amp;quot;).read_hamiltonian()&#xA;eig = H.eigenstate(k=[0.5, 0.25, 0])&#xA;print(eig.derivative(order=2, matrix=True))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;the above will read in a Hamiltonian from a Siesta calculation, then diagonalize at the specified k-point, then calculate the 1st and 2nd order derivatives and return the off-diagonals as well.&#xA;The &lt;code&gt;derivative&lt;/code&gt; function is for instance used to calculate the velocities, and one can overlay these one the band-structure plot (plus numerical derivatives) to assert they yield the correct quantities.&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2024-03-07T12:52:11.000" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12532" PostTypeId="2" ParentId="4201" CreationDate="2024-03-07T17:59:34.737" Score="1" Body="&lt;p&gt;You may be interested in &lt;a href=&quot;https://docs.dftk.org/stable/&quot; rel=&quot;nofollow noreferrer&quot;&gt;DFTK&lt;/a&gt;, which is a fully featured plane-wave code like Quantum Espresso but which fits in a mere 7k lines of code. Importantly, DFTK has automatic differentiation, which means you should be able to compute whatever derivative you wish for in a numerically accurate fashion.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-03-07T17:59:34.737" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12533" PostTypeId="1" CreationDate="2024-03-08T04:28:20.110" Score="6" ViewCount="349" Body="&lt;p&gt;I have a system that has 5M aluminum hydroxide (10 molecules) ion [Al(OH)4]- and 5M NaOH (10 molecules) in a box of side length 15 angstroms each. I have 113 water molecules in the system, so that the density of water is consistent with 1g/cc. I need a way to find the pH of the simulation. I tried calculating it by counting the H+ ions, but that gave me a value of ~1.2, which did not really make sense.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-09T01:31:36.493" Title="Calculation of pH in Molecular Dynamics simulation?" Tags="|molecular-dynamics|reference-request|" AnswerCount="2" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12534" PostTypeId="2" ParentId="12533" CreationDate="2024-03-08T06:45:02.197" Score="6" Body="&lt;p&gt;What matters is the number of &amp;quot;free&amp;quot; H+ ions. A quick estimation using the autoionization constant of water shows that the H+ concentration is on the order of &lt;span class=&quot;math-container&quot;&gt;$10^{-15}$&lt;/span&gt; mol/L. Obviously, it is essentially impossible to see even one H+ ion in a simulation of merely 100 water molecules. If you do see at least one H+, please check if you have used a wrong criterion for determining whether a hydrogen atom is H+, or if your MD simulation setup has a severe problem (for example you have added the wrong number of Na+ ions).&lt;/p&gt;&#xA;&lt;p&gt;In any case, if you do not need very high accuracy, say if your result only needs to be accurate to about &lt;span class=&quot;math-container&quot;&gt;$\pm$&lt;/span&gt;1, then this is an elementary analytical chemistry exercise. You can simply look up the experimental pKb of [Al(OH)4]- and solve for the equilibrium concentration of OH-; then, using the autoionization constant of water, you can easily find the concentration of H+ and therefore the pH. For higher accuracy, you may need to consider the activity coefficients (&lt;a href=&quot;https://en.wikipedia.org/wiki/Activity_coefficient&quot; rel=&quot;noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Activity_coefficient&lt;/a&gt;), which can be rather accurately calculated by the ionic strength, the latter of which can be calculated easily from the components of the solution. Still, this is something you can calculate by hand within one hour. By contrast, MD simulations probably have larger error bars than what can be obtained by the above procedure (due to method and statistical errors), and is much more involved, so I don't recommend using MD to solve this problem.&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2024-03-08T06:45:02.197" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12535" PostTypeId="1" CreationDate="2024-03-08T10:44:47.173" Score="4" ViewCount="64" Body="&lt;p&gt;Recently, I've been trying to calculate the transmission coefficients for the molecular junction (Au lattice - molecule - Au lattice) using SIESTA, TRANSIESTA, and TBtrans.&#xA;As you know, the procedure for calculating the transmission functions based on non-equilibrium green's function is like below.&#xA;(1) SIESTA calculation for the electrode to obtain .TSHS file&#xA;(2) TRANSIESTA calculation for the junction to get .TSHS file&#xA;(3) Using the results of (1) and (2), TBtrans calculation&lt;/p&gt;&#xA;&lt;p&gt;I finished the step (1) and it's time to proceed step (2) but the error message is occurred at this time.&#xA;The error message is like below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt; &amp;lt;sparsity:./elec_au_100.TSHS&#xA; nrows_g=1080 nrows=1080 sparsity=2.3075 nnzs=2691504, refcount: 3&amp;gt;&#xA; &amp;lt;sparsity:(TM [--,--, 0] of: ./elec_au_100.TSHS)&#xA; nrows_g=1080 nrows=1080 sparsity=1.1888 nnzs=1386576, refcount: 3&amp;gt;&#xA; &amp;lt;sparsity:(TM [--,--,-1] of: ./elec_au_100.TSHS)&#xA; nrows_g=1080 nrows=1080 sparsity=.5339 nnzs=622764, refcount: 3&amp;gt;&#xA; Left principal cell is extending out with 29700 elements:&#xA; Atom 5 connects with atom 55&#xA; Orbital 74 connects with orbital 824&#xA; Hamiltonian value: |H(74,49424)|@R=-2 =  0.738E-02 eV&#xA; Overlap          :  S(74,49424)|@R=-2 = -0.413E-04&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I found the question on this community (&lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9424/tbt-transiesta-calculation-error&quot;&gt;TBT Transiesta Calculation error&lt;/a&gt;) similar to my case and it says that the interactions between the supercells induce these kinds of errors.&#xA;So the solution is adding more layers in the electrode calculations.&#xA;However, as you can see in the attached fdf file in the bottom, the each electrode is composed of 6 gold layers(3X6X6) and I defined the electrode as 4 gold layers so it looks enough.&#xA;The strange point is that when I used the half size in y-direction(3X3X6) as the electrode, the calculations worked well so I could get the transmission coefficients.&#xA;Can you suggest a solution to solve this problem?&lt;/p&gt;&#xA;&lt;p&gt;Your comments surely helpful for advancing my research.&#xA;Thank you in advance. :)&lt;/p&gt;&#xA;&lt;p&gt;Sincerely,&#xA;Jonghwan Lee&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&#xA;SolutionMethod        Transiesta&#xA;&#xA;SystemName  Au 100 with gold chain&#xA;SystemLabel au_100&#xA;&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SPECIES AND BASIS&#xA;&#xA;# Number of species &#xA;NumberOfSpecies 4&#xA;%block ChemicalSpeciesLabel&#xA; 1 79 Au&#xA; 2 16 S&#xA; 3 6 C&#xA; 4 1 H&#xA;%endblock ChemicalSpeciesLabel&#xA;&#xA;PAO.BasisSize    DZP&#xA;PAO.EnergyShift  0.005 Ry&#xA;XC.functional   GGA&#xA;XC.authors      PBE&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;# K-points&#xA;&#xA;%block kgrid_Monkhorst_Pack&#xA; 1    0    0    0.0&#xA; 0    1    0    0.0&#xA; 0    0    1    0.0&#xA;%endblock kgrid_Monkhorst_Pack&#xA;&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;# Structure&#xA;NumberOfAtoms 231&#xA;LatticeConstant 1.0 Ang&#xA;%block LatticeVectors&#xA;     8.651160000      0.000000000      0.000000000 &#xA;     0.000000000      17.30232000      0.000000000 &#xA;     0.000000000      0.000000000     37.625600000&#xA;%endblock LatticeVectors&#xA;AtomicCoordinatesFormat  Ang&#xA;%block AtomicCoordinatesAndAtomicSpecies&#xA;  0.00000000  0.00000000  0.00000000 1 #   1: Au&#xA;  2.88370000  0.00000000  0.00000000 1 #   2: Au&#xA;  5.76740000  0.00000000  0.00000000 1 #   3: Au&#xA;  0.00000000  2.88370000  0.00000000 1 #   4: Au&#xA;  2.88370000  2.88370000  0.00000000 1 #   5: Au&#xA;  5.76740000  2.88370000  0.00000000 1 #   6: Au&#xA;  0.00000000  5.76740000  0.00000000 1 #   7: Au&#xA;  2.88370000  5.76740000  0.00000000 1 #   8: Au&#xA;  5.76740000  5.76740000  0.00000000 1 #   9: Au&#xA;  0.00000000  8.65110000  0.00000000 1 #  10: Au&#xA;  2.88370000  8.65110000  0.00000000 1 #  11: Au&#xA;  5.76740000  8.65110000  0.00000000 1 #  12: Au&#xA;  0.00000000 11.53480000  0.00000000 1 #  13: Au&#xA;  2.88370000 11.53480000  0.00000000 1 #  14: Au&#xA;  5.76740000 11.53480000  0.00000000 1 #  15: Au&#xA;  0.00000000 14.41850000  0.00000000 1 #  16: Au&#xA;  2.88370000 14.41850000  0.00000000 1 #  17: Au&#xA;  5.76740000 14.41850000  0.00000000 1 #  18: Au&#xA;  1.44190000  1.44190000  2.03910000 1 #  19: Au&#xA;  4.32560000  1.44190000  2.03910000 1 #  20: Au&#xA;  7.20930000  1.44190000  2.03910000 1 #  21: Au&#xA;  1.44190000  4.32560000  2.03910000 1 #  22: Au&#xA;  4.32560000  4.32560000  2.03910000 1 #  23: Au&#xA;  7.20930000  4.32560000  2.03910000 1 #  24: Au&#xA;  1.44190000  7.20930000  2.03910000 1 #  25: Au&#xA;  4.32560000  7.20930000  2.03910000 1 #  26: Au&#xA;  7.20930000  7.20930000  2.03910000 1 #  27: Au&#xA;  1.44190000 10.09300000  2.03910000 1 #  28: Au&#xA;  4.32560000 10.09300000  2.03910000 1 #  29: Au&#xA;  7.20930000 10.09300000  2.03910000 1 #  30: Au&#xA;  1.44190000 12.97670000  2.03910000 1 #  31: Au&#xA;  4.32560000 12.97670000  2.03910000 1 #  32: Au&#xA;  7.20930000 12.97670000  2.03910000 1 #  33: Au&#xA;  1.44190000 15.86040000  2.03910000 1 #  34: Au&#xA;  4.32560000 15.86040000  2.03910000 1 #  35: Au&#xA;  7.20930000 15.86040000  2.03910000 1 #  36: Au&#xA;  0.00000000  0.00000000  4.07820000 1 #  37: Au&#xA;  2.88370000  0.00000000  4.07820000 1 #  38: Au&#xA;  5.76740000  0.00000000  4.07820000 1 #  39: Au&#xA;  0.00000000  2.88370000  4.07820000 1 #  40: Au&#xA;  2.88370000  2.88370000  4.07820000 1 #  41: Au&#xA;  5.76740000  2.88370000  4.07820000 1 #  42: Au&#xA;  0.00000000  5.76740000  4.07820000 1 #  43: Au&#xA;  2.88370000  5.76740000  4.07820000 1 #  44: Au&#xA;  5.76740000  5.76740000  4.07820000 1 #  45: Au&#xA;  0.00000000  8.65110000  4.07820000 1 #  46: Au&#xA;  2.88370000  8.65110000  4.07820000 1 #  47: Au&#xA;  5.76740000  8.65110000  4.07820000 1 #  48: Au&#xA;  0.00000000 11.53480000  4.07820000 1 #  49: Au&#xA;  2.88370000 11.53480000  4.07820000 1 #  50: Au&#xA;  5.76740000 11.53480000  4.07820000 1 #  51: Au&#xA;  0.00000000 14.41850000  4.07820000 1 #  52: Au&#xA;  2.88370000 14.41850000  4.07820000 1 #  53: Au&#xA;  5.76740000 14.41850000  4.07820000 1 #  54: Au&#xA;  1.44190000  1.44190000  6.11730000 1 #  55: Au&#xA;  4.32560000  1.44190000  6.11730000 1 #  56: Au&#xA;  7.20930000  1.44190000  6.11730000 1 #  57: Au&#xA;  1.44190000  4.32560000  6.11730000 1 #  58: Au&#xA;  4.32560000  4.32560000  6.11730000 1 #  59: Au&#xA;  7.20930000  4.32560000  6.11730000 1 #  60: Au&#xA;  1.44190000  7.20930000  6.11730000 1 #  61: Au&#xA;  4.32560000  7.20930000  6.11730000 1 #  62: Au&#xA;  7.20930000  7.20930000  6.11730000 1 #  63: Au&#xA;  1.44190000 10.09300000  6.11730000 1 #  64: Au&#xA;  4.32560000 10.09300000  6.11730000 1 #  65: Au&#xA;  7.20930000 10.09300000  6.11730000 1 #  66: Au&#xA;  1.44190000 12.97670000  6.11730000 1 #  67: Au&#xA;  4.32560000 12.97670000  6.11730000 1 #  68: Au&#xA;  7.20930000 12.97670000  6.11730000 1 #  69: Au&#xA;  1.44190000 15.86040000  6.11730000 1 #  70: Au&#xA;  4.32560000 15.86040000  6.11730000 1 #  71: Au&#xA;  7.20930000 15.86040000  6.11730000 1 #  72: Au&#xA;  0.00000000  0.00000000  8.15640000 1 #  73: Au&#xA;  2.88370000  0.00000000  8.15640000 1 #  74: Au&#xA;  5.76740000  0.00000000  8.15640000 1 #  75: Au&#xA;  0.00000000  2.88370000  8.15640000 1 #  76: Au&#xA;  2.88370000  2.88370000  8.15640000 1 #  77: Au&#xA;  5.76740000  2.88370000  8.15640000 1 #  78: Au&#xA;  0.00000000  5.76740000  8.15640000 1 #  79: Au&#xA;  2.88370000  5.76740000  8.15640000 1 #  80: Au&#xA;  5.76740000  5.76740000  8.15640000 1 #  81: Au&#xA;  0.00000000  8.65110000  8.15640000 1 #  82: Au&#xA;  2.88370000  8.65110000  8.15640000 1 #  83: Au&#xA;  5.76740000  8.65110000  8.15640000 1 #  84: Au&#xA;  0.00000000 11.53480000  8.15640000 1 #  85: Au&#xA;  2.88370000 11.53480000  8.15640000 1 #  86: Au&#xA;  5.76740000 11.53480000  8.15640000 1 #  87: Au&#xA;  0.00000000 14.41850000  8.15640000 1 #  88: Au&#xA;  2.88370000 14.41850000  8.15640000 1 #  89: Au&#xA;  5.76740000 14.41850000  8.15640000 1 #  90: Au&#xA;  1.44190000  1.44190000 10.19550000 1 #  91: Au&#xA;  4.32560000  1.44190000 10.19550000 1 #  92: Au&#xA;  7.20930000  1.44190000 10.19550000 1 #  93: Au&#xA;  1.44190000  4.32560000 10.19550000 1 #  94: Au&#xA;  4.32560000  4.32560000 10.19550000 1 #  95: Au&#xA;  7.20930000  4.32560000 10.19550000 1 #  96: Au&#xA;  1.44190000  7.20930000 10.19550000 1 #  97: Au&#xA;  4.32560000  7.20930000 10.19550000 1 #  98: Au&#xA;  7.20930000  7.20930000 10.19550000 1 #  99: Au&#xA;  1.44190000 10.09300000 10.19550000 1 # 100: Au&#xA;  4.32560000 10.09300000 10.19550000 1 # 101: Au&#xA;  7.20930000 10.09300000 10.19550000 1 # 102: Au&#xA;  1.44190000 12.97670000 10.19550000 1 # 103: Au&#xA;  4.32560000 12.97670000 10.19550000 1 # 104: Au&#xA;  7.20930000 12.97670000 10.19550000 1 # 105: Au&#xA;  1.44190000 15.86040000 10.19550000 1 # 106: Au&#xA;  4.32560000 15.86040000 10.19550000 1 # 107: Au&#xA;  7.20930000 15.86040000 10.19550000 1 # 108: Au&#xA;  4.32560000  8.96360000 13.19515000 2 # 109: S&#xA;  4.32560000  8.11530000 14.74325000 3 # 110: C&#xA;  4.17170000  6.36840000 14.80375000 2 # 111: S&#xA;  4.34700000  8.67750000 15.97895000 3 # 112: C&#xA;  4.16920000  6.42580000 16.52505000 3 # 113: C&#xA;  4.25980000  7.70860000 17.01965000 3 # 114: C&#xA;  4.42450000  9.74510000 16.12965000 4 # 115: H&#xA;  4.07580000  5.18740000 17.74865000 2 # 116: S&#xA;  4.25130000  7.71510000 18.45715000 3 # 117: C&#xA;  4.15480000  6.43670000 18.96225000 3 # 118: C&#xA;  4.32630000  8.69320000 19.49015000 3 # 119: C&#xA;  4.13700000  6.39480000 20.68375000 2 # 120: S&#xA;  4.29010000  8.14220000 20.73045000 3 # 121: C&#xA;  4.40550000  9.75940000 19.33095000 4 # 122: H&#xA;  4.27110000  9.00430000 22.27075000 2 # 123: S&#xA;  2.88370000  0.00000000 25.27040000 1 # 124: Au&#xA;  5.76740000  0.00000000 25.27040000 1 # 125: Au&#xA;  0.00000000  2.88370000 25.27040000 1 # 126: Au&#xA;  2.88370000  2.88370000 25.27040000 1 # 127: Au&#xA;  5.76740000  2.88370000 25.27040000 1 # 128: Au&#xA;  0.00000000  5.76740000 25.27040000 1 # 129: Au&#xA;  2.88370000  5.76740000 25.27040000 1 # 130: Au&#xA;  5.76740000  5.76740000 25.27040000 1 # 131: Au&#xA;  0.00000000  8.65110000 25.27040000 1 # 132: Au&#xA;  2.88370000  8.65110000 25.27040000 1 # 133: Au&#xA;  5.76740000  8.65110000 25.27040000 1 # 134: Au&#xA;  0.00000000 11.53480000 25.27040000 1 # 135: Au&#xA;  2.88370000 11.53480000 25.27040000 1 # 136: Au&#xA;  5.76740000 11.53480000 25.27040000 1 # 137: Au&#xA;  0.00000000 14.41850000 25.27040000 1 # 138: Au&#xA;  2.88370000 14.41850000 25.27040000 1 # 139: Au&#xA;  5.76740000 14.41850000 25.27040000 1 # 140: Au&#xA;  0.00000000  0.00000000 25.27040000 1 # 141: Au&#xA;  1.44190000  1.44190000 27.30950000 1 # 142: Au&#xA;  4.32560000  1.44190000 27.30950000 1 # 143: Au&#xA;  7.20930000  1.44190000 27.30950000 1 # 144: Au&#xA;  1.44190000  4.32560000 27.30950000 1 # 145: Au&#xA;  4.32560000  4.32560000 27.30950000 1 # 146: Au&#xA;  7.20930000  4.32560000 27.30950000 1 # 147: Au&#xA;  1.44190000  7.20930000 27.30950000 1 # 148: Au&#xA;  4.32560000  7.20930000 27.30950000 1 # 149: Au&#xA;  7.20930000  7.20930000 27.30950000 1 # 150: Au&#xA;  1.44190000 10.09300000 27.30950000 1 # 151: Au&#xA;  4.32560000 10.09300000 27.30950000 1 # 152: Au&#xA;  7.20930000 10.09300000 27.30950000 1 # 153: Au&#xA;  1.44190000 12.97670000 27.30950000 1 # 154: Au&#xA;  4.32560000 12.97670000 27.30950000 1 # 155: Au&#xA;  7.20930000 12.97670000 27.30950000 1 # 156: Au&#xA;  1.44190000 15.86040000 27.30950000 1 # 157: Au&#xA;  4.32560000 15.86040000 27.30950000 1 # 158: Au&#xA;  7.20930000 15.86040000 27.30950000 1 # 159: Au&#xA;  0.00000000  0.00000000 29.34860000 1 # 160: Au&#xA;  2.88370000  0.00000000 29.34860000 1 # 161: Au&#xA;  5.76740000  0.00000000 29.34860000 1 # 162: Au&#xA;  0.00000000  2.88370000 29.34860000 1 # 163: Au&#xA;  2.88370000  2.88370000 29.34860000 1 # 164: Au&#xA;  5.76740000  2.88370000 29.34860000 1 # 165: Au&#xA;  0.00000000  5.76740000 29.34860000 1 # 166: Au&#xA;  2.88370000  5.76740000 29.34860000 1 # 167: Au&#xA;  5.76740000  5.76740000 29.34860000 1 # 168: Au&#xA;  0.00000000  8.65110000 29.34860000 1 # 169: Au&#xA;  2.88370000  8.65110000 29.34860000 1 # 170: Au&#xA;  5.76740000  8.65110000 29.34860000 1 # 171: Au&#xA;  0.00000000 11.53480000 29.34860000 1 # 172: Au&#xA;  2.88370000 11.53480000 29.34860000 1 # 173: Au&#xA;  5.76740000 11.53480000 29.34860000 1 # 174: Au&#xA;  0.00000000 14.41850000 29.34860000 1 # 175: Au&#xA;  2.88370000 14.41850000 29.34860000 1 # 176: Au&#xA;  5.76740000 14.41850000 29.34860000 1 # 177: Au&#xA;  1.44190000  1.44190000 31.38770000 1 # 178: Au&#xA;  4.32560000  1.44190000 31.38770000 1 # 179: Au&#xA;  7.20930000  1.44190000 31.38770000 1 # 180: Au&#xA;  1.44190000  4.32560000 31.38770000 1 # 181: Au&#xA;  4.32560000  4.32560000 31.38770000 1 # 182: Au&#xA;  7.20930000  4.32560000 31.38770000 1 # 183: Au&#xA;  1.44190000  7.20930000 31.38770000 1 # 184: Au&#xA;  4.32560000  7.20930000 31.38770000 1 # 185: Au&#xA;  7.20930000  7.20930000 31.38770000 1 # 186: Au&#xA;  1.44190000 10.09300000 31.38770000 1 # 187: Au&#xA;  4.32560000 10.09300000 31.38770000 1 # 188: Au&#xA;  7.20930000 10.09300000 31.38770000 1 # 189: Au&#xA;  1.44190000 12.97670000 31.38770000 1 # 190: Au&#xA;  4.32560000 12.97670000 31.38770000 1 # 191: Au&#xA;  7.20930000 12.97670000 31.38770000 1 # 192: Au&#xA;  1.44190000 15.86040000 31.38770000 1 # 193: Au&#xA;  4.32560000 15.86040000 31.38770000 1 # 194: Au&#xA;  7.20930000 15.86040000 31.38770000 1 # 195: Au&#xA;  0.00000000  0.00000000 33.42680000 1 # 196: Au&#xA;  2.88370000  0.00000000 33.42680000 1 # 197: Au&#xA;  5.76740000  0.00000000 33.42680000 1 # 198: Au&#xA;  0.00000000  2.88370000 33.42680000 1 # 199: Au&#xA;  2.88370000  2.88370000 33.42680000 1 # 200: Au&#xA;  5.76740000  2.88370000 33.42680000 1 # 201: Au&#xA;  0.00000000  5.76740000 33.42680000 1 # 202: Au&#xA;  2.88370000  5.76740000 33.42680000 1 # 203: Au&#xA;  5.76740000  5.76740000 33.42680000 1 # 204: Au&#xA;  0.00000000  8.65110000 33.42680000 1 # 205: Au&#xA;  2.88370000  8.65110000 33.42680000 1 # 206: Au&#xA;  5.76740000  8.65110000 33.42680000 1 # 207: Au&#xA;  0.00000000 11.53480000 33.42680000 1 # 208: Au&#xA;  2.88370000 11.53480000 33.42680000 1 # 209: Au&#xA;  5.76740000 11.53480000 33.42680000 1 # 210: Au&#xA;  0.00000000 14.41850000 33.42680000 1 # 211: Au&#xA;  2.88370000 14.41850000 33.42680000 1 # 212: Au&#xA;  5.76740000 14.41850000 33.42680000 1 # 213: Au&#xA;  1.44190000  1.44190000 35.46590000 1 # 214: Au&#xA;  4.32560000  1.44190000 35.46590000 1 # 215: Au&#xA;  7.20930000  1.44190000 35.46590000 1 # 216: Au&#xA;  1.44190000  4.32560000 35.46590000 1 # 217: Au&#xA;  4.32560000  4.32560000 35.46590000 1 # 218: Au&#xA;  7.20930000  4.32560000 35.46590000 1 # 219: Au&#xA;  1.44190000  7.20930000 35.46590000 1 # 220: Au&#xA;  4.32560000  7.20930000 35.46590000 1 # 221: Au&#xA;  7.20930000  7.20930000 35.46590000 1 # 222: Au&#xA;  1.44190000 10.09300000 35.46590000 1 # 223: Au&#xA;  4.32560000 10.09300000 35.46590000 1 # 224: Au&#xA;  7.20930000 10.09300000 35.46590000 1 # 225: Au&#xA;  1.44190000 12.97670000 35.46590000 1 # 226: Au&#xA;  4.32560000 12.97670000 35.46590000 1 # 227: Au&#xA;  7.20930000 12.97670000 35.46590000 1 # 228: Au&#xA;  1.44190000 15.86040000 35.46590000 1 # 229: Au&#xA;  4.32560000 15.86040000 35.46590000 1 # 230: Au&#xA;  7.20930000 15.86040000 35.46590000 1 # 231: Au&#xA;%endblock AtomicCoordinatesAndAtomicSpecies&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;# SCF variables&#xA;&#xA;DM.MixSCF1   T&#xA;MaxSCFIterations      1000           # Maximum number of SCF iter&#xA;DM.MixingWeight       0.02          # New DM amount for next SCF cycle&#xA;DM.Tolerance          1.d-4         # Tolerance in maximum difference&#xA;DM.UseSaveDM          true          # to use continuation files&#xA;DM.NumberPulay        8&#xA;MeshCutoff            50. Ry&#xA;TS.MixH               yes&#xA;&#xA;==================================================&#xA;==================================================&#xA;# MD variables&#xA;&#xA;MD.FinalTimeStep 1&#xA;MD.TypeOfRun CG&#xA;MD.NumCGsteps     000&#xA;MD.UseSaveXV      .true.&#xA;&#xA;==================================================&#xA;==================================================&#xA;# Output variables&#xA;&#xA;WriteMullikenPop                1&#xA;WriteBands                      .false.&#xA;SaveRho                         .false.&#xA;SaveDeltaRho                    .false.&#xA;SaveHS                          .false.&#xA;SaveElectrostaticPotential      True &#xA;SaveTotalPotential              no&#xA;WriteCoorXmol                   .true.&#xA;WriteMDXmol                     .true.&#xA;WriteMDhistory                  .false.&#xA;WriteEigenvalues                yes&#xA;TS.HS.Save          True&#xA;&#xA;&#xA;&#xA;==================================================&#xA;==================================================&#xA;&#xA;# Bias voltage&#xA;TS.Voltage 0.0 eV&#xA;%block TS.ChemPots&#xA;  Left&#xA;  Right&#xA;%endblock TS.ChemPots&#xA;&#xA;%block TS.ChemPot.Left&#xA;  mu V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Left&#xA;      t-Left&#xA;    end&#xA;%endblock TS.ChemPot.Left&#xA;%block TS.ChemPot.Right&#xA;  mu -V/2&#xA;  contour.eq&#xA;    begin&#xA;      c-Right&#xA;      t-Right&#xA;    end&#xA;%endblock TS.ChemPot.Right&#xA;&#xA;TS.Elecs.Bulk true&#xA;TS.Elecs.DM.Update none&#xA;TS.Elecs.GF.ReUse false&#xA;%block TS.Elecs&#xA;  Left&#xA;  Right&#xA;%endblock TS.Elecs&#xA;&#xA;%block TS.Elec.Left&#xA;  TSHS ./elec_au_100.TSHS&#xA;  chem-pot Left&#xA;  semi-inf-dir -a3&#xA;  elec-pos begin 1&#xA;  used-atoms 72&#xA;%endblock TS.Elec.Left&#xA;&#xA;%block TS.Elec.Right&#xA;  TSHS ./elec_au_100.TSHS&#xA;  chem-pot Right&#xA;  semi-inf-dir +a3&#xA;  elec-pos end -1&#xA;  used-atoms 72&#xA;%endblock TS.Elec.Right&#xA;&#xA;TS.Contours.Eq.Pole 2.5 eV&#xA;%block TS.Contour.c-Left&#xA;  part circle&#xA;   from   -40.00000 eV + V/2 to -10. kT + V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Left&#xA;%block TS.Contour.t-Left&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Left&#xA;%block TS.Contour.c-Right&#xA;  part circle&#xA;   from   -40.00000 eV - V/2 to -10. kT - V/2&#xA;    points 30&#xA;     method g-legendre&#xA;%endblock TS.Contour.c-Right&#xA;%block TS.Contour.t-Right&#xA;  part tail&#xA;   from prev to inf&#xA;    points 10&#xA;     method g-fermi&#xA;%endblock TS.Contour.t-Right&#xA;&#xA;TS.Contours.nEq.Eta 0.0001 eV&#xA;%block TS.Contours.nEq&#xA;  neq&#xA;%endblock TS.Contours.nEq&#xA;%block TS.Contour.nEq.neq&#xA;  part line&#xA;   from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;    delta 0.01 eV&#xA;     method mid-rule&#xA;%endblock TS.Contour.nEq.neq&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="9905" LastEditorUserId="9905" LastEditDate="2024-03-08T11:05:11.370" LastActivityDate="2024-03-08T11:34:40.423" Title="How can I solve the error in TRANSIESTA calculations?" Tags="|density-functional-theory|siesta|electronic-transport|" AnswerCount="1" CommentCount="2" ClosedDate="2024-03-13T05:31:14.740" ContentLicense="CC BY-SA 4.0" />
  <row Id="12536" PostTypeId="2" ParentId="12535" CreationDate="2024-03-08T11:34:40.423" Score="3" Body="&lt;p&gt;The only restriction for interaction is that of the interaction along the semi-infinite direction. The transverse directions can be &lt;em&gt;any&lt;/em&gt; size you wish. However, it would always be beneficial to reduce the transverse directions such that one can utilise Bloch's theorem. This will greatly improve the throughput!&lt;/p&gt;&#xA;&lt;p&gt;Otherwise this question is completely equivalent to the answer linked: &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/9424/tbt-transiesta-calculation-error&quot;&gt;TBtrans/Transiesta, error: &amp;quot;connectivity is not perfect&amp;quot;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="887" LastActivityDate="2024-03-08T11:34:40.423" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12538" PostTypeId="1" CreationDate="2024-03-08T12:37:46.317" Score="3" ViewCount="46" Body="&lt;p&gt;Information &lt;br&gt;&#xA;Paper - &lt;a href=&quot;https://www.sciencedirect.com/science/article/abs/pii/S1566119918302787&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://www.sciencedirect.com/science/article/abs/pii/S1566119918302787&lt;/a&gt; &lt;br&gt;&#xA;Github Link - &lt;a href=&quot;https://github.com/ldwillia/SL3ME&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://github.com/ldwillia/SL3ME&lt;/a&gt; &lt;br&gt;&lt;/p&gt;&#xA;&lt;p&gt;Question - I have been studying solar cell materials. I am computing their properties. One of the part of calculations will be to calculate Spectroscopic Limited Maximum Efficiency (SLME). Can you help me with its process steps? &lt;br&gt;&#xA;Assuming - The absorbance data is to be taken from optical calculations.  &lt;br&gt;&#xA;So far I have tried it with the example in the link and got the following error. &lt;br&gt;&#xA;Error - &lt;br&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Traceback (most recent call last): &#xA;  File &amp;quot;/home/slme/SL3ME.py&amp;quot;, line 127, in &amp;lt;module&amp;gt;&#xA;    SLME =  calculate_SLME( material_eV_for_absorbance_data = material_eV_for_absorbance_data,&#xA;  File &amp;quot;/home/slme/SL3ME.py&amp;quot;, line 14, in calculate_SLME&#xA;    from numpy import sys, loadtxt, pi,  exp, zeros, linspace&#xA;ImportError: cannot import name 'sys' from 'numpy' (/home/.local/lib/python3.10/site-packages/numpy/__init__.py)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="5" LastEditDate="2024-03-08T12:57:01.410" LastActivityDate="2024-03-19T07:53:11.883" Title="Help regarding SLME calculation" Tags="|density-functional-theory|spectroscopy|solar-cells|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12539" PostTypeId="2" ParentId="12469" CreationDate="2024-03-08T13:05:57.877" Score="2" Body="&lt;p&gt;Regardless of whether you just want to build a 3D structure of PEG20 (which requires only the .gro file), or actually simulate it (which requires both, a .gro file and a topology), I wouldn't start building a polymer by hand - chances are you'll end up wasting a lot of time. There are a number of tools available for generating polymer chains of various lengths. I'd start by trying either one of these two:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;CHARMM-GUI Polymer builder: Easy as can be, just create an account and start building.&lt;/li&gt;&#xA;&lt;li&gt;PolyPly (&lt;a href=&quot;https://pypi.org/project/polyply/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://pypi.org/project/polyply/&lt;/a&gt;): A powerful piece of software that has a lot of capabilities, including building linear/branched polymers. Usage is not as easy as CHARMM-GUI, but that's what the tutorials are there for.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;The key things you need are 1) A sensible starting structure, and 2) A [forcefield] compatible topology (assuming you want to run a simulation). CHARMM-GUI produces, as the name suggests, CHARMM compatible files. PolyPly prepackaged with a number of force fields, so you can take your pick.&lt;/p&gt;&#xA;" OwnerUserId="4394" LastActivityDate="2024-03-08T13:05:57.877" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12540" PostTypeId="1" CreationDate="2024-03-08T23:29:19.490" Score="3" ViewCount="50" Body="&lt;p&gt;I am doing some calculations with Quantum Espresso and wanted to calculate the electronic conductivity of my 2D nanosheet using BoltzTrap. After the successful creation of the BoltzTraP.def and the associated files using &lt;strong&gt;&lt;strong&gt;qe2boltz.py&lt;/strong&gt;&lt;/strong&gt;, I tried to perform the next step which is running the command&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;$ x_trans BoltzTrap&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;And this error appeared:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt; ================ BoltzTraP vs 1.2.5 ============= &#xA;&amp;gt; Program received signal SIGSEGV: Segmentation fault - invalid memory reference.&#xA;&amp;gt; Backtrace for this error:&#xA;&amp;gt; #0  0x7fa495b3bbd0 in ???&#xA;&amp;gt; #1  0x7fa495b3ae25 in ???&#xA;&amp;gt; #2  0x7fa495810d5f in ???&#xA;&amp;gt; #3  0x559a9795f54b in boltztrap   at /home/user/Documents/boltztrap-1.2.5/src/BoltzTraP.F90:297&#xA;&amp;gt; #4  0x559a9794f5ce in main    at /home/user/Documents/boltztrap-1.2.5/src/BoltzTraP.F90:20 Segmentation fault&#xA;&amp;gt; 0.2u 0.0s 0:00.23 95.6% 0+0k 0+144io 0pf+0w&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is the source of this issue and how can I solve it?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;I appreciate the help&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="8130" LastEditDate="2024-03-09T21:21:30.143" LastActivityDate="2024-03-09T21:21:30.143" Title="BoltzTraP : getting the error 'segmentation fault'" Tags="|density-functional-theory|vasp|quantum-espresso|wien2k|boltztrap|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12541" PostTypeId="2" ParentId="12533" CreationDate="2024-03-09T01:31:36.493" Score="3" Body="&lt;p&gt;Here's some useful intuition for solution molecular dynamics:&lt;/p&gt;&#xA;&lt;p&gt;One litre contains &lt;span class=&quot;math-container&quot;&gt;$10^{24}$&lt;/span&gt; cubic nanometers. One mole contains &lt;span class=&quot;math-container&quot;&gt;$6 \times 10^{23}$&lt;/span&gt; particles. So 1M of volumetric density corresponds to a number density of 0.6 per cubic nanometers.&lt;/p&gt;&#xA;&lt;p&gt;The self-dissociation constant of water is &lt;span class=&quot;math-container&quot;&gt;$K_w = 10^{-14} [\mathrm{M}^2]$&lt;/span&gt;. So at equilibrium and pH 7, both &lt;span class=&quot;math-container&quot;&gt;$\mathrm{H}^+$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\mathrm{OH}^-$&lt;/span&gt; will have a concentration of &lt;span class=&quot;math-container&quot;&gt;${10^{-7}}$&lt;/span&gt; M.&lt;/p&gt;&#xA;&lt;p&gt;By the above calculation, this is 60 ions of each type per cubic &lt;em&gt;micron&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;As such, it is not feasible to directly simulate water dissociation to probe pH. Rather, the process is modelled using grand-canonical Monte Carlo exchange with a reservoir (essentially &amp;quot;chemostatting&amp;quot;, in analogy to barostatting and thermostatting). For example &lt;a href=&quot;https://pubs.aip.org/aip/jcp/article/156/4/044122/2840162/Accelerated-simulation-method-for-charge&quot; rel=&quot;nofollow noreferrer&quot;&gt;this recent paper&lt;/a&gt; chemostats on the combination of acid/base dissociation and electrolyte ion insertion/removal to reach feasible reaction probabilities.&lt;/p&gt;&#xA;&lt;p&gt;ReaxFF results would certainly not be trustworthy until proven otherwise, since how could they possibly calibrate parameters to exactly achieve sub-micromolar concentrations of hydronium and hydroxide in pure water?&lt;/p&gt;&#xA;" OwnerUserId="5184" LastActivityDate="2024-03-09T01:31:36.493" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12542" PostTypeId="1" CreationDate="2024-03-09T12:58:18.180" Score="5" ViewCount="96" Body="&lt;p&gt;This is my configuration in extended xyz format&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;8&#xA;Lattice=&amp;quot;5.30478009012 0.0312272946092 0.308531804143 0.296228192315 5.4283625362 -0.153770906252 0.107142908862 0.25388495613 5.28850183842&amp;quot; Properties=species:S:1:pos:R:3:force:R:3:Z:I:1 pbc=&amp;quot;T T T&amp;quot; config_type=A15 energy=-100.15189673 virial=&amp;quot;-27.731569708 -3.64512142325 -4.97162055576 -3.64512142325 -34.1913582966 -0.581410761343 -4.97162055576 -0.581410761343 -27.551736916&amp;quot;&#xA;W 0.0 0.0 0.0 0.0 -0.0 0.0 74&#xA;W 2.8540756 2.85673739 2.72163137 0.0 0.0 -0.0 74&#xA;W 1.47430912 2.72198809 0.0002475 0.01822982 0.09589153 -0.13879486 74&#xA;W 4.12669916 2.73760174 0.1545134 -0.01822982 -0.09589153 0.13879486 74&#xA;W 0.1276285 1.48403311 2.60580819 -0.09922348 -0.00455073 0.02076133 74&#xA;W 0.2757426 4.19821438 2.52892274 0.09922348 0.00455073 -0.02076133 74&#xA;W 2.67917577 0.07908489 1.47639136 0.12483693 -0.01838436 0.00975602 74&#xA;W 2.73274723 0.20602736 4.12064228 -0.12483693 0.01838436 -0.00975602 74&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;How can we build supercell out of current unit cell with mapped energy, forces, and stresses for arbitrary periodic repetition inside ASE?&lt;/p&gt;&#xA;" OwnerUserId="1492" LastEditorUserId="1492" LastEditDate="2024-03-22T17:17:30.380" LastActivityDate="2024-03-22T17:17:30.380" Title="Build supercell in ASE with forces and stress" Tags="|atomic-simulation-environment|stress-strain|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12543" PostTypeId="1" AcceptedAnswerId="12544" CreationDate="2024-03-09T16:04:42.987" Score="15" ViewCount="1499" Body="&lt;p&gt;I'm trying to calculate the HOMO of various molecules in water solution. I first tried to see how PySCF calculates the HOMO of hydrogen. I ran the following code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;mol_h = pyscf.gto.M(atom = 'H 0 0 0', spin = 1, basis = 'ccpvdz')&#xA;rks_h = mol_h.ROKS(xc = 'b3lyp')&#xA;rks_h.kernel()&#xA;rks_h.analyze(verbose=5)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And I got the following output:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;**** SCF Summaries ****&#xA;Total Energy =                          -0.501257936931332&#xA;Nuclear Repulsion Energy =               0.000000000000000&#xA;One-electron Energy =                   -0.499271486999867&#xA;Two-electron Coulomb Energy =            0.311475159768718&#xA;DFT Exchange-Correlation Energy =       -0.313461609700183&#xA;**** MO energy ****&#xA;                Roothaan           | alpha              | beta&#xA;MO #1   energy= -0.148854429623937 | -0.319481818297586 | 0.02178298730584   occ= 1&#xA;MO #2   energy= 0.520550055619181  | 0.4180250336286    | 0.623065049353633  occ= 0&#xA;MO #3   energy= 1.3343779636294    | 1.2099070476478    | 1.458848879611     occ= 0&#xA;MO #4   energy= 1.33437796363348   | 1.2099070476478    | 1.45884887961915   occ= 0&#xA;MO #5   energy= 1.33437796363348   | 1.2099070476478    | 1.45884887961915   occ= 0&#xA; ** MO coefficients (expansion on meta-Lowdin AOs) **&#xA;               #1        #2        #3        #4        #5       &#xA;0 H 1s           0.99722  -0.07457  -0.00000  -0.00000   0.00000&#xA;0 H 2s           0.07457   0.99722  -0.00000  -0.00000   0.00000&#xA;0 H 2px          0.00000   0.00000   0.00005   0.82979  -0.55808&#xA;0 H 2py          0.00000   0.00000  -0.00001   0.55808   0.82979&#xA;0 H 2pz          0.00000   0.00000   1.00000  -0.00003   0.00004&#xA; ** Mulliken pop on meta-lowdin orthogonal AOs  **&#xA; ** Mulliken pop  **&#xA;pop of  0 H 1s            0.99444&#xA;pop of  0 H 2s            0.00556&#xA;pop of  0 H 2px           0.00000&#xA;pop of  0 H 2py           0.00000&#xA;pop of  0 H 2pz           0.00000&#xA; ** Mulliken atomic charges  **&#xA;charge of    0H =      0.00000&#xA;Dipole moment(X, Y, Z, Debye): -0.00000, -0.00000, -0.00000&#xA;&#xA;((array([9.94438767e-01, 5.56123333e-03, 2.85005342e-34, 2.87485689e-35,&#xA;         1.36070362e-34]),&#xA;  array([3.33066907e-16])),&#xA; array([-5.71059869e-17, -1.81369083e-17, -3.94581675e-17]))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;According to PySCF calculation, it seems the HOMO should be -0.14885. However, isn't the correct HOMO value of hydrogen -0.5 (according to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/1737/what-unit-of-energy-does-pyscf-use&quot;&gt;answer&lt;/a&gt;)?&lt;/p&gt;&#xA;" OwnerUserId="9928" LastEditorUserId="5" LastEditDate="2024-03-09T20:40:33.860" LastActivityDate="2024-03-11T17:36:46.607" Title="Why is my hydrogen energy not equal to -0.5 hartrees?" Tags="|electronic-structure|ab-initio-calculations|pyscf|orbitals|atomic-physics|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12544" PostTypeId="2" ParentId="12543" CreationDate="2024-03-09T20:35:05.117" Score="19" Body="&lt;p&gt;Yes, the exact orbital energy of the hydrogen atom is &lt;span class=&quot;math-container&quot;&gt;$-1/2\  E_h$&lt;/span&gt;. The problems in the calculation are as follows.&lt;/p&gt;&#xA;&lt;p&gt;First, you are running ROKS. ROKS has many definitions in the literature; PySCF appears to use the code for ROHF (which likewise has many, many definitions in the literature; see Kreb's 141-page review in &lt;a href=&quot;https://doi.org/10.1016/S0010-4655(98)00100-3&quot; rel=&quot;nofollow noreferrer&quot;&gt;Comput. Phys. Commun. 116, 137 (1999)&lt;/a&gt;, for example for ways to handle the off-diagonal Lagrange multipliers as well as Table I in &lt;a href=&quot;https://doi.org/10.1063/1.4849615&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 140, 014102 (2014)&lt;/a&gt; for various definitions of the ROHF Hamiltonian) in combination with the Kohn-Sham Fock matrix instead of the Hartree-Fock Fock matrix. As far as I remember, it is generally a bad idea to do this in density functional theory, since in general it will break one of the fundamental theorems of density functional theory, which is the density cusp on the nuclei.&lt;/p&gt;&#xA;&lt;p&gt;ROKS with the B3LYP functional you used yields an orbital energy &lt;span class=&quot;math-container&quot;&gt;$-0.148854 E_h$&lt;/span&gt;. If you switch to UHF, you get a much better value &lt;span class=&quot;math-container&quot;&gt;$-0.319475 E_h$&lt;/span&gt;. Finally, the reason why this is still far from the exact value is self-interaction error: the Coulomb and exchange terms don't cancel out perfectly in DFT, which becomes especially clear in the case of one-electron systems whose exact solution is easy to find, such as in the case of hydrogen; we recently published a benchmark on this topic in &lt;a href=&quot;https://doi.org/10.1063/5.0120515&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Phys. 157, 174113 (2022)&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hartree-Fock is exact for one-electron systems, and either RHF or UHF works fine and you will find the orbital energy &lt;span class=&quot;math-container&quot;&gt;$-0.499278 E_h$&lt;/span&gt; in the cc-pVDZ basis you used. The remaining error is due to basis set truncation error: the &lt;span class=&quot;math-container&quot;&gt;$1s$&lt;/span&gt; orbital is not exactly reproduced by the cc-pVDZ basis set.&lt;/p&gt;&#xA;&lt;p&gt;Note that Hartree-Fock still gets all the other orbitals completely wrong. We know that the exact energy for primary quantum number &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E_n = - \frac 1 {2n^2} $$&lt;/span&gt;&#xA;which means that one should find the Rydberg spectrum with energies &lt;span class=&quot;math-container&quot;&gt;$-0.125000E_h$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$-0.055556E_h$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$-0.031250E_h$&lt;/span&gt;, etc. Instead, the Hartree-Fock calculation gives the first unoccupied orbital energy as &lt;span class=&quot;math-container&quot;&gt;$0.181933 E_h$&lt;/span&gt;. This is because the potential for the unoccupied orbitals given by Hartree-Fock (and Kohn-Sham DFT, too!) is wrong: it decays exponentially, instead of &lt;span class=&quot;math-container&quot;&gt;$-1/r$&lt;/span&gt; like the exact potential is known to behave.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2024-03-11T17:36:46.607" LastActivityDate="2024-03-11T17:36:46.607" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12545" PostTypeId="2" ParentId="12543" CreationDate="2024-03-09T20:38:36.057" Score="12" Body="&lt;p&gt;The &lt;strong&gt;exact&lt;/strong&gt; non-relativistic ground state electronic energy of a hydrogen-like atom, assuming that the nucleus is &amp;quot;clamped&amp;quot;, point-sized, and with an infinitely large mass compared to the mass of an electron, and ignoring any fine, hyperfine, or finer than hyperfine effects, and in a vacuum containing nothing else, is -0.5 Eh according to Schroedinger's 1926 equation.&lt;/p&gt;&#xA;&lt;p&gt;You have &lt;strong&gt;approximately&lt;/strong&gt; found the lowest eigenvalue of the Schroedinger equation for the above-mentioned hydrogen atom, using the cc-pVDZ basis set and the B3LYP functional (and the ROKS mean-field method).&lt;/p&gt;&#xA;&lt;p&gt;When I do HF calculations for larger basis sets for an H atom, I get the following energies, and this shows that &lt;strong&gt;if your basis set were big enough, and you did an HF calculation, you would get -0.5 Eh&lt;/strong&gt;:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;aug-cc-pV6Z:    -0.499999 276396 663  (PySCF, 127 functions), default settings&#xA;aug-cc-pV7Z:    -0.499999 752574 58   (PySCF, 189 functions), default settings&#xA;aug-cc-pV8Z:    -0.499999 966893 035  (PySCF, 268 functions), default settings&#xA;aug-cc-pV9Z:    -0.499999 977357 467  (PySCF, 367 functions), default settings&#xA;aug-cc-pV10Z:   -0.499999 980721 463  (PySCF, 485 functions), default settings&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can see this data and more &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/blob/master/high_angular_momentum_benchmarks.txt&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;. You can also see the original input/output files &lt;a href=&quot;https://github.com/HPQC-LABS/AI_ENERGIES/tree/master/H&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-03-10T21:23:25.277" LastActivityDate="2024-03-10T21:23:25.277" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12546" PostTypeId="1" CreationDate="2024-03-10T14:29:57.473" Score="7" ViewCount="69" Body="&lt;p&gt;I am trying to perform a coupled cluster calculation at the CCSD(T) level using OpenMOLCAS. My input file is the following, in which I am using default values for most of the key inputs:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;GATEWAY&#xA;XBAS&#xA;C.STO-3G&#xA;H.STO-3G&#xA;O.STO-3G&#xA;End of basis&#xA;ZMAT&#xA;H1&#xA;C1 1 1.097&#xA;O1 2 1.343 1 111&#xA;H2 3 0.972 2 106.3 1 180&#xA;O2 2 1.202 3 124.9 4 0&#xA;End of z-matrix&#xA;&amp;amp;SEWARD&#xA;&amp;amp;SCF&#xA; UHF&#xA;&amp;amp;RASSCF&#xA;  OUTOrbitals= Canonical&#xA;  LumOrb&#xA;  OUTOrbitals= Canonical&#xA;&amp;amp;MOTRA&#xA;  JobIph&#xA;&amp;amp;CCSDT&#xA;  CCT&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Upon inspecting the output in the &lt;code&gt;.log&lt;/code&gt; file, I am getting the total energy after 20 iterations:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;      Total energy (diff) :    -186.39362934      -0.00000006&#xA;      Correlation energy  :      -0.1784309132990&#xA;      Reference energy    :    -186.2151984277011&#xA;      E1aa   contribution :       0.00000000&#xA;      E1bb   contribution :       0.00000000&#xA;      E2aaaa contribution :      -0.01326086&#xA;      E2bbbb contribution :      -0.01326086&#xA;      E2abab contribution :      -0.15190920&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;However, the code is not finishing the job correctly at the end of &lt;code&gt;&amp;amp;CCSDT&lt;/code&gt; module. The following error message is printed to the log file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Work space requirements :                17769&#xA;  Allocation of work space : Done&#xA;--- Stop Module: ccsdt at Sun Mar 10 21:07:35 2024 /rc=-6 ---&#xA;.########################.&#xA;.# Non-zero return code #.&#xA;.########################.&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When examining the &lt;code&gt;.err&lt;/code&gt; file, I am finding the following aborting signal:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Program received signal SIGABRT: Process abort signal.&#xA;&#xA;Backtrace for this error:&#xA;#0  0x7fc0cfa1f171 in ???&#xA;#1  0x7fc0cfa1e313 in ???&#xA;#2  0x7fc0cea4eb1f in ???&#xA;#3  0x7fc0cea4ea9f in ???&#xA;#4  0x7fc0cea21e04 in ???&#xA;#5  0x7fc0cea91036 in ???&#xA;#6  0x7fc0cea9819b in ???&#xA;#7  0x7fc0cea989db in ???&#xA;#8  0x7fc0cea9b55a in ???&#xA;#9  0x7fc0cea9c6cd in ???&#xA;#10  0x7fc0cfa1e608 in ???&#xA;#11  0x7fc0cfc1b047 in ???&#xA;#12  0x7fc0cfc2b03f in ???&#xA;#13  0x435762 in ???&#xA;#14  0x42146e in ???&#xA;#15  0x402460 in ???&#xA;#16  0x7fc0cea3acf2 in ???&#xA;#17  0x4024ad in ???&#xA;#18  0xffffffffffffffff in ???&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;strong&gt;What could be the reason for this error, and what should I do in order to fix it?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2024-03-10T17:15:05.867" LastActivityDate="2024-03-10T17:31:53.183" Title="OpenMOLCAS error while running CCT in &amp;CCSDT module" Tags="|molecular-modeling|coupled-cluster|open-molcas|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12547" PostTypeId="2" ParentId="12546" CreationDate="2024-03-10T17:31:53.183" Score="6" Body="&lt;p&gt;I have run a calculation with that input file, and can see that an error occurred when trying to calculate the (T) part of the CCSD(T) calculation, as you can see that we have &lt;code&gt;************************&lt;/code&gt; instead of a real number:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;       CCSD     =      -186.3936292872034&#xA;       T3 corr. =************************&#xA;       CCSD + T3=************************&#xA;  T3 energy decomposition into spin parts&#xA;  Eaaa =  -1320133193.83886&#xA;  Eaab =  -851388296422.193&#xA;  Eabb =   1505020301064.51&#xA;  Ebbb =   24408709436.1437&#xA;&#xA;&#xA;      Happy Landing!&#xA;&#xA;--- Stop Module: ccsdt at Sun Mar 10 13:19:14 2024 /rc=-1 --&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The next hint that I see, is that you have a &amp;quot;return code&amp;quot; of &lt;code&gt;rc=-1&lt;/code&gt;. In my case, the &lt;code&gt;.err&lt;/code&gt; file says nothing except for:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;double free or corruption (!prev)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;which is very different from your &lt;code&gt;.err&lt;/code&gt; file, so we are probably using slightly different compilers, since the CCSD(T) code in OpenMolcas probably didn't change much between my version, which is the &lt;code&gt;openmolcas/20.10&lt;/code&gt; module on Compute Canada's machines, which have the following settings:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Host name: build-node.computecanada.ca (Linux)&#xA;C Compiler ID: Intel&#xA;C flags: -O2 -march=core-avx2 -axCore-AVX512 -ftz -fp-speculation=safe -fp-model source -std=gnu99 -qopenmp&#xA;Fortran Compiler ID: Intel&#xA;Fortran flags: -O2 -march=core-avx2 -axCore-AVX512 -ftz -fp-speculation=safe -fp-model source  -fpp -i8 -r8 -heap-arrays -qopenmp&#xA;Definitions: _MOLCAS_;_I8_;_LINUX_;_GA_;_MOLCAS_MPP_;SCALAPACK;_MKL_;_FDE_&#xA;Parallel: ON (GA=ON)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Ideally you would have included the entire output file, along with the entire input file and &lt;code&gt;.err&lt;/code&gt; file, so that we could see more output data (such as the &lt;code&gt;************************&lt;/code&gt; that I showed, and the version and compiler information. I have saved your input file as &lt;code&gt;inp.inp&lt;/code&gt;, and all of the output that I included in this answer, can be found in &lt;a href=&quot;https://github.com/HPQC-LABS/Modeling_Matters/tree/master/12546&quot; rel=&quot;noreferrer&quot;&gt;this repository&lt;/a&gt; in the &lt;code&gt;.log&lt;/code&gt; and &lt;code&gt;.err&lt;/code&gt; files, which are complete.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-03-10T17:31:53.183" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12548" PostTypeId="2" ParentId="12493" CreationDate="2024-03-10T19:28:34.773" Score="5" Body="&lt;h1&gt;OpenMolcas&lt;/h1&gt;&#xA;&lt;h3&gt;Inhomogenous external fields in OpenMolcas&lt;/h3&gt;&#xA;&lt;p&gt;If you would like to do quantum chemistry calculations, such as RHF-CCSD(T), for a molecule with an &lt;strong&gt;inhomogenous&lt;/strong&gt; external field, E(x,y,z), then the &lt;a href=&quot;https://molcas.gitlab.io/OpenMolcas/sphinx/users.guide/programs/ffpt.html#input-example&quot; rel=&quot;noreferrer&quot;&gt;FFPT (finite field perturbation theory) module of OpenMolcas&lt;/a&gt; may help.&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;code&gt;DIPO&lt;/code&gt; keyword will allow you to use a &lt;strong&gt;homogenous&lt;/strong&gt; external field perturbation.&lt;/li&gt;&#xA;&lt;li&gt;Other keywords such as &lt;code&gt;QUAD&lt;/code&gt; (for calculating quadrupole moments or quadrupole polarizabilities) will allow you to use an &lt;strong&gt;inhomogenous electric field&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;li&gt;There is also the &lt;code&gt;EFGR&lt;/code&gt; keyword which is for adding an &amp;quot;&lt;strong&gt;electric field gradient&lt;/strong&gt;&amp;quot; perturbation operator.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;code&gt;GLOBL&lt;/code&gt; keyword allows users to use a more general perturbation description.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;There is also the &lt;a href=&quot;https://molcas.gitlab.io/OpenMolcas/sphinx/users.guide/programs/espf.html&quot; rel=&quot;noreferrer&quot;&gt;&lt;code&gt;ESPF&lt;/code&gt; (electro-static potential fitted) method&lt;/a&gt; which:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;adds contributions to the one-electron Hamiltonian for computing the interaction between the charge distribution in Molcas and any external electrostatic potential, field, and field derivatives.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h3&gt;More about OpenMolcas in general&lt;/h3&gt;&#xA;&lt;p&gt;You mentioned Gaussian 16 and MOLPRO when listing commercial software in your question post, and  you mentioned GPAW and PySCF when listing Python-based software in &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/12493/are-there-any-free-or-free-quantum-chemistry-codes-which-can-apply-an-external-f?noredirect=1#comment28803_12517&quot;&gt;this comment&lt;/a&gt;. MOLCAS has been a commercial code for almost 40 years, and it costed about as much as GAUSSIAN and MOLPRO, and offered a similar level of &amp;quot;commercial-grade reliability&amp;quot; as those programs (especially compared to the slower Python-based software such as PySCF and GPAW), but a few years ago the vast majority of it was made free and &lt;a href=&quot;/questions/tagged/open-source&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;open-source&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;open-source&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-open-source-tooltip-container&quot;&gt;open-source&lt;/a&gt;. You can still buy a commercial license if you want to use one of the features that did not become open source (for example, if the authors of that part of the code base are no longer alive or contactable, and therefore cannot give permission for open-sourcing their lines of code).&lt;/p&gt;&#xA;&lt;p&gt;OpenMolcas is the highest-voted answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/4538/5&quot;&gt;What is a good replacement for Gaussian?&lt;/a&gt; (ORCA has a net score of 25 and 1 downvote, but OpenMolcas has a net score of 24 and 0 downvotes, although some of this might have been more because of the quality of the answers rather than the software itself, but I think OpenMolcas does deserve to be chosen over ORCA in many cases because ORCA is &lt;em&gt;&lt;strong&gt;not open source&lt;/strong&gt;&lt;/em&gt;: it might be free when you apply for access and get your application approved after you give away information, create a login username and password, and permanently get recorded in a database of users, but you cannot modify ORCA like you can modify OpenMolcas). OpenMolcas also has a net score that is 11 higher than ORCA for the answer to: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/414/5&quot;&gt;Is there a free package with robust CASSCF functionality?&lt;/a&gt; (but again, these are only net scores on MMSE, and with only a few dozen voters on that thread, many who probably have never used either of those computer programs, it's still too early to not look at the net scores with a grain of salt).&lt;/p&gt;&#xA;&lt;p&gt;OpenMolcas also comes &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/1248/5&quot;&gt;readily packaged for Fedora&lt;/a&gt; (and on other platforms, you can just download it from GitLab, much more easily than ORCA, CFOUR, MRCC or other similar programs that might be &amp;quot;free&amp;quot; but not open source), and it was mentioned in answers and comment on this thread which is related to your question: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6714/5&quot;&gt;Quantum chemistry in external electrostatic field?&lt;/a&gt;. ORCA hides its integrals in a binary format, whereas OpenMOLCAS is compatable with the readable FCIDUMP format, which allows OpenMolcas to interface with dozens of other programs, and I described it as &amp;quot;likely the fastest and most general program for calculating electron-repulsion integrals&amp;quot; (although PySCF may have caught up shortly after this thread: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/10176/5&quot;&gt;Is this bug reproducible in PySCF? Oxygen SCF with aug-cc-pV8Z fails&lt;/a&gt;). This thread might also interest you: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/6648/5;&quot;&gt;Comparing GAMESS, OpenMOLCAS and Psi4&lt;/a&gt; and since you mentioned GPAW, also this one: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12465/5&quot;&gt;Why use PySCF/OpenMolcas instead of VASP/QuantumESPRESSO&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-03-10T19:28:34.773" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12549" PostTypeId="1" CreationDate="2024-03-11T07:34:21.580" Score="3" ViewCount="37" Body="&lt;p&gt;How can one assess the accuracy of elastic constants for 2D materials calculated via VASP and VASPKIT in the absence of literature guidance?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="5" LastEditDate="2024-03-11T11:58:00.723" LastActivityDate="2024-03-12T16:05:07.613" Title="Assessing Accuracy of Elastic Constants for 2D Materials Calculated via VASP and VASPKIT" Tags="|vasp|elasticity|vaspkit|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12550" PostTypeId="2" ParentId="12284" CreationDate="2024-03-11T12:03:07.230" Score="3" Body="&lt;p&gt;Obtaining 3D structures from SMILES is reasonably easy. There are many tools, some of which are written in Python, that allow you to do this. RDKit comes to mind, you can see &lt;a href=&quot;https://bioinformatics.stackexchange.com/questions/20716/from-smile-get-amber-force-in-python&quot;&gt;this answer&lt;/a&gt; for an example.&lt;/p&gt;&#xA;&lt;p&gt;Automatically creating reliable topologies, on the other hand, is hard. I'm not aware of any tools that would universally, and reliably, create a topology from a SMILES string to any force field you wanted. There are force field specific tools, as Roshan pointed out in the comments. Some of them you can run on your own machine (like LigParGen), some are only hosted on a webserver.&lt;/p&gt;&#xA;&lt;p&gt;Here are some examples, although I'm sure there are other tools available:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;LigParGen - OPLS - &lt;a href=&quot;https://traken.chem.yale.edu/ligpargen/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://traken.chem.yale.edu/ligpargen/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;SwissParam - CHARMM - &lt;a href=&quot;http://swissparam.ch/&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://swissparam.ch/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;ATB - GROMOS - &lt;a href=&quot;https://atb.uq.edu.au/&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://atb.uq.edu.au/&lt;/a&gt;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="4394" LastEditorUserId="4394" LastEditDate="2024-03-11T12:19:59.750" LastActivityDate="2024-03-11T12:19:59.750" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12551" PostTypeId="1" CreationDate="2024-03-11T21:26:35.513" Score="3" ViewCount="32" Body="&lt;p&gt;I &lt;a href=&quot;https://physics.stackexchange.com/questions/804204/sublattice-model-for-ternary-system/805923#805923&quot;&gt;already asked a broader version&lt;/a&gt; of this question in the physics-SE, but after I got no answer, combined with further understanding of the problem, it was suggested to me to try asking here.&lt;/p&gt;&#xA;&lt;p&gt;I'm calculating the phase diagram of a ternary system (Ag-Al-Cu, to be specific), which has some phases modelled as sublattices (using &lt;a href=&quot;https://doi.org/10.1016/j.jallcom.2004.06.078&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; publication for the description). I have managed to model all phases for the liquidus surface, except for the epsilon phase, (Ag,Al,Cu)(Ag,Cu).&lt;/p&gt;&#xA;&lt;p&gt;I've used the CALPHAD book of Saunders (chapter 5.4, and specifically section 5.4.2 and its equation (5.37)) to try to understand the use of the sublattice model, but I still can't model the previously mentioned epsilon phase.&lt;/p&gt;&#xA;&lt;p&gt;From the mentioned publication, I have the following parameters for the phase:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\epsilon\text{-phase: } (\mathrm{Ag,Al,Cu})(\mathrm{Ag,Cu})\\&#xA;{}^0 G^\epsilon_\mathrm{Al:Ag} - H^\mathrm{SER}_\mathrm{Ag} - H^\mathrm{SER}_\mathrm{Al} = 160000 + GH^\mathrm{SER}_\mathrm{Ag} + GH^\mathrm{SER}_\mathrm{Al}\\&#xA;{}^0 G^\epsilon_\mathrm{Ag:Cu} - H^\mathrm{SER}_\mathrm{Ag} - H^\mathrm{SER}_\mathrm{Cu} = 85000 + GH^\mathrm{SER}_\mathrm{Ag} + GH^\mathrm{SER}_\mathrm{Cu}\\&#xA;{}^0 G^\epsilon_\mathrm{Cu:Ag} - H^\mathrm{SER}_\mathrm{Ag} - H^\mathrm{SER}_\mathrm{Cu} = 85000 + GH^\mathrm{SER}_\mathrm{Ag} + GH^\mathrm{SER}_\mathrm{Cu}&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;together with the following from &lt;a href=&quot;https://op.europa.eu/en/publication-detail/-/publication/35a95440-10ac-45f3-bd90-0fe0a0006aaf&quot; rel=&quot;nofollow noreferrer&quot;&gt;COST507&lt;/a&gt;, which it is based on [from its &amp;quot;System Al-Cu&amp;quot; chapter]:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\text{Phase AlCu-}\epsilon \quad [(\mathrm{Al,Cu})(\mathrm{Cu})]\\&#xA;G^\circ(T) - H^{\circ,\mathrm{fcc-}A1}_\mathrm{Al} (298.15\mathrm{ K}) - H^{\circ,\mathrm{fcc-}A1}_\mathrm{Cu} (298.15\mathrm{ K}) = \mathrm{G(Al:Cu)} =&#xA;-36976 + 1.2 T + \mathrm{GHSER}_\mathrm{Al} + \mathrm{GHSER}_\mathrm{Cu}\\&#xA;\\&#xA;G^\circ(T) - 2.0 H^{\circ,\mathrm{fcc-}A1}_\mathrm{Cu} (298.15\mathrm{ K}) = \mathrm{G(Cu:Cu)} = 2.0 \mathrm{GBCC}_\mathrm{Cu}\\&#xA;L^{0,\mathrm{AlCu-}\epsilon}_\mathrm{Al,Cu:Cu} = 7600 - 24 T\\&#xA;L^{1,\mathrm{AlCu-}\epsilon}_\mathrm{Al,Cu:Cu} = -72000&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Based on this, I calculate the Gibbs energy of the epsilon phase with the following python code:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# Phase epsilon, (Ag,Al,Cu):(Ag,Cu)&#xA;def AgAlCuGibbsGammaH (xAg, xAl, T):&#xA;    # Thermodynamic parameters from litterature:&#xA;    # Ternary (Witusiewicz2005, https://doi.org/10.1016/j.jallcom.2004.06.078 )&#xA;    G0AlAg = 160000 + AgG0Fcc(T) + AlG0Fcc(T) # pure elements (AlG0Fcc, AgG0Fcc, etc) from Dinsdale1991, https://doi.org/10.1016/0364-5916(91)90030-N&#xA;    G0AgCu = 85000 + AgG0Fcc(T) + CuG0Fcc(T)&#xA;    G0CuAg = 85000 + AgG0Fcc(T) + CuG0Fcc(T)&#xA;    # Binary (COST507, https://op.europa.eu/en/publication-detail/-/publication/35a95440-10ac-45f3-bd90-0fe0a0006aaf )&#xA;    G0AlCu = -36976 + 1.2 * T + AlG0Fcc(T) + CuG0Fcc(T)&#xA;    G0CuCu = 2 * CuG0Bcc(T)&#xA;    L0AlCuCu = 7600 - 24 * T&#xA;    L1AlCuCu = -72000&#xA;    &#xA;    # Number on the sites&#xA;    N1 = 1&#xA;    N2 = 1&#xA;    &#xA;    # Site fractions&#xA;    yAg1 = 1 * xAg&#xA;    yAl1 = 2 * xAl&#xA;    yCu1 = 1 - yAg1 - yAl1&#xA;    &#xA;    yAg2 = 1 * xAg&#xA;    yCu2 = 1 - yAg2&#xA;    &#xA;    # Pure, ideal and excess contributions to the Gibbs energy&#xA;    pure = (&#xA;        yAg1 * yCu2 * G0AgCu&#xA;        + yAl1 * yAg2 * G0AlAg &#xA;        + yAl1 * yCu2 * G0AlCu&#xA;        + yCu1 * yAg2 * G0CuAg&#xA;        + yCu1 * yCu2 * G0CuCu&#xA;        )&#xA;    &#xA;    ideal = R * T * (N1 * (yAg1 * np.log(yAg1) + yAl1 * np.log(yAl1) + yCu1 * np.log(yCu1)) +&#xA;                     N2 * (yAg2 * np.log(yAg2) + yCu2 * np.log(yCu2)))&#xA;    &#xA;    excess = yAl1 * yCu1 * yCu2 * (L0AlCuCu + L1AlCuCu * (yAl1 - yCu1))&#xA;    &#xA;    # Divide by total number of sites&#xA;    dividend = N1 + N2&#xA;    pure /= dividend&#xA;    ideal /= dividend&#xA;    excess /= dividend&#xA;    &#xA;    # Gibbs energy is equal to the sum of the different parts&#xA;    return pure + ideal + excess&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But it does not give me the correct common tangent plane with the liquid phase, based on the peritectic points listed in the mentioned publication.&lt;/p&gt;&#xA;&lt;p&gt;Am I calculating the site fractions incorrectly? Or am I doing a different mistake? Any help is greatly appreciated.&lt;/p&gt;&#xA;" OwnerUserId="9940" LastActivityDate="2024-03-11T21:26:35.513" Title="How to apply sublattice model for a ternary system?" Tags="|thermodynamics|phase-transitions|phase-diagram|answer-with-calculation|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12553" PostTypeId="1" AcceptedAnswerId="12695" CreationDate="2024-03-12T12:53:48.757" Score="4" ViewCount="82" Body="&lt;p&gt;I am working on neural network in tensorflow to train a model to predict atomic forces from SOAP descriptors (regression problem).&lt;/p&gt;&#xA;&lt;p&gt;I have 64 020 data points (chemical structures), each structure has 2718 features - &lt;a href=&quot;https://singroup.github.io/dscribe/latest/tutorials/descriptors/soap.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;SOAP descriptor (compressed)&lt;/a&gt;. Atomic forces are 3 values - x y z for each direction, they were reshaped into 2D for the model:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;(64020, 151, 3) -&amp;gt; 64020 structures, each structure has 151 atoms, each atom has 3 atomic forces x y z. &#xA;Atomic forces array shape after reshaping: &#xA;(64020, 453)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I also multiplied the values of atomic forces by 1000 (because they are very small values) just to be able to interpret the loss better, but it doesn't have an impact as far as I am aware.&lt;/p&gt;&#xA;&lt;p&gt;I currently have a network with one hidden layer with 1024 neurons, I experimented with different number of layers and different number of neurons, I use Adam optimizer, I tried drop out, batch normalization, L2 regularization, learning rate scheduler, but I don't see a lot of improvements. What I am seeing that the network is slowly learning, but after some time it gets stuck and just starts oscillating in the local minimum (I assume).&#xA;I also use normalization on the SOAP descriptor. A deeper network or more neurons doesn't seem to make a big difference.&#xA;I already achieved reasonable results with Kernel Ridge Regression, so I was hoping the neural network would work. But so far, nothing promising has emerged.&lt;/p&gt;&#xA;&lt;p&gt;Current code:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    model = tf.keras.models.Sequential([&#xA;        tf.keras.Input(shape=(soap_descriptors.shape[1],)),&#xA;        tf.keras.layers.Dense(1024, activation='linear', &#xA;                              kernel_regularizer=tf.keras.regularizers.l2(0.0001)),&#xA;        tf.keras.layers.BatchNormalization(),&#xA;        tf.keras.layers.ReLU(),&#xA;        tf.keras.layers.Dropout(0.3),&#xA; &#xA;        tf.keras.layers.Dense(atomic_forces_list.shape[1])&#xA;    ])&#xA;&#xA;    initial_learning_rate = 0.001&#xA;    lr_schedule = tf.keras.optimizers.schedules.ExponentialDecay(&#xA;        initial_learning_rate,&#xA;        decay_steps=10000,&#xA;        decay_rate=0.9,&#xA;        staircase=True)&#xA;&#xA;    optimizer = tf.keras.optimizers.Adam(learning_rate=lr_schedule)&#xA;    model.compile(optimizer=optimizer, loss='mean_squared_error', metrics=['mean_squared_error'])&#xA;&#xA;    soap_descriptors = soap_descriptors.astype(np.float32)&#xA;    atomic_forces_list = atomic_forces_list.astype(np.float32)&#xA;&#xA;    s_mean = np.mean(soap_descriptors, axis=0, keepdims=True)&#xA;    s_std = np.std(soap_descriptors, axis=0, keepdims=True)&#xA;    soap_normalized = (soap_descriptors - s_mean) / (s_std + 0.000001)&#xA;&#xA;&#xA;    x_train, x_test, y_train, y_test = train_test_split(soap_normalized, atomic_forces_list, test_size=0.2, random_state=42)&#xA;&#xA;    history = model.fit(x_train, y_train, batch_size=128, epochs=1300, verbose=1, validation_split=0.1)&#xA;&#xA;    model.evaluate(x_test, y_test, verbose=1)&#xA;    predicted_forces = model.predict(x_test)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/L22NK.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/L22NK.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here, the learning essentially stopped, and the validation loss was no longer decreasing.&lt;/p&gt;&#xA;&lt;p&gt;When I add one more layer with 512 neurons:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;        tf.keras.layers.Dense(512, activation='linear', &#xA;                               kernel_regularizer=tf.keras.regularizers.l2(0.0001)&#xA;                              ),&#xA;        tf.keras.layers.BatchNormalization(),&#xA;        tf.keras.layers.ReLU(),&#xA;        tf.keras.layers.Dropout(0.2), &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The validation loss reaches 909 around 900th epoch and then just sort of oscillates up and down around that value (907, 908, 906, 911, 912, 913 ..... )&lt;/p&gt;&#xA;&lt;p&gt;What could such learning process represent? Is there anything else I can try to improve the network? Is the logic trying to predict the atomic forces, without using energies, correct?&lt;/p&gt;&#xA;" OwnerUserId="7749" LastEditorUserId="4515" LastEditDate="2024-04-05T17:13:09.957" LastActivityDate="2024-04-05T17:13:09.957" Title="Neural Network to predict atomic forces using SOAP descriptors" Tags="|computational-chemistry|python|machine-learning|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12555" PostTypeId="2" ParentId="12549" CreationDate="2024-03-12T15:44:30.600" Score="2" Body="&lt;h3&gt;Symmetries&lt;/h3&gt;&#xA;&lt;p&gt;The elastic constants tensor obtained should reflect the symmetries of the crystal structure of the material in question. This &lt;a href=&quot;https://iopscience.iop.org/article/10.1088/2053-1583/ab2ef3&quot; rel=&quot;nofollow noreferrer&quot;&gt;comment article&lt;/a&gt; can be a helpful reference. Elastic constants that do not reflect the crystal symmetries could indicate that the DFT calculations are not converged enough, or that your strains are too large.&lt;/p&gt;&#xA;&lt;h3&gt;&lt;strong&gt;Convergence&lt;/strong&gt;&lt;/h3&gt;&#xA;&lt;p&gt;This is somewhat related to the above (symmetries could be a sign of poor convergence). Generally, you could also redo calculations on finer settings (higher plane wave cutoffs, k-point sampling, etc) and check if the elastic constants change by much. It could also be a good idea to vary the maximum strain you are using for the stress-strain elastic constants calculation to check how sensitive your results are to it.&lt;/p&gt;&#xA;" OwnerUserId="6131" LastEditorUserId="5" LastEditDate="2024-03-12T16:05:07.613" LastActivityDate="2024-03-12T16:05:07.613" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12556" PostTypeId="1" CreationDate="2024-03-12T21:27:23.997" Score="4" ViewCount="30" Body="&lt;p&gt;I am doing a electron-hole pair calculation via adding Quasi Fermi-Dirac excited carriers in Abinit....My structure has only 57 atoms but after one week running...it didn't converge and failed...with the following  tags:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;nband 500&#xA;ivalence 450&#xA;nqfd  0.1 # exciting 0.1 electrons per u.c.&#xA;occopt 9&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Do you have any suggestions? Could you please guide me? Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="8680" LastEditorUserId="24" LastEditDate="2024-03-12T23:16:43.280" LastActivityDate="2024-03-12T23:16:43.280" Title="Quasi Fermi-Dirac excited carriers Abinit" Tags="|abinit|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12557" PostTypeId="2" ParentId="11415" CreationDate="2024-03-13T04:43:55.020" Score="5" Body="&lt;h1&gt;Defect Formation Energy (DFE) of a point defect&lt;/h1&gt;&#xA;&lt;p&gt;The case you described is an example of a point defect (vacancy, substitution/impurity, interstitial) in bulk material. Such point defects can be neutral as well as electrically charged. In the context of periodic Density Functional Theory (DFT) based calculation, for a point defect with charged state &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;, the &lt;em&gt;defect formation energy&lt;/em&gt;, &lt;span class=&quot;math-container&quot;&gt;$E_f^D(q,E_F)$&lt;/span&gt;, is defined as a function of the Fermi energy &lt;span class=&quot;math-container&quot;&gt;$E_F:$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$ E_f^D(q,E_F) = \left[E^D(q) + E^D_{corr}(q)\right]-E^{Pristine}-\sum n_i\mu_i + q(E_F + E_{VBM}^{Pristine}-\Delta V_{0/b}).$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here,&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E^D(q)$&lt;/span&gt; is the total energy of the defective supercell,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E^D_{corr}(q)$&lt;/span&gt; is the correction term due to the finite size effects (this also accounts for the compensating homogeneous electron gas in the background that is added by the code to prevent the divergence in case of charged defect calculation)&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E^{Pristine}$&lt;/span&gt; is the total energy of the pristine supercell,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$n_i$&lt;/span&gt; is the number of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th atoms being added to the pristine system to create the defective supercell (so &lt;span class=&quot;math-container&quot;&gt;$n=-1$&lt;/span&gt; for a single vacancy),&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\mu_i$&lt;/span&gt; is the chemical potential of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th atoms calculated using the same pseudopotential,&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$E_{VBM}^{Pristine}$&lt;/span&gt; is the valence band maximum of the pristine supercell. You can set the &lt;code&gt;verbosity='high'&lt;/code&gt; in the &lt;code&gt;&amp;amp;CONTROL&lt;/code&gt; namelist and then you can check the occupations in the output and note the VBM.&lt;/li&gt;&#xA;&lt;li&gt;&lt;span class=&quot;math-container&quot;&gt;$\Delta V_{0/b}$&lt;/span&gt; is the potential alignment term between pristine bulk supercell and neutral &lt;span class=&quot;math-container&quot;&gt;$(q=0)$&lt;/span&gt; defective supercell.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;For neutral defects, this gets simplified as:&lt;/p&gt;&#xA;&lt;h1&gt;Calculating DFE using Quantum ESPRESSO (QE)&lt;/h1&gt;&#xA;&lt;p&gt;In all of the following steps, I am assuming you did proper convergence tests before proceeding to the actual calculation. Now, as the first step, you have to build a supercell of the pristine material and run an SCF calculation (&lt;code&gt;calculation='scf'&lt;/code&gt; using &lt;code&gt;pw.x&lt;/code&gt;). This energy is the &lt;span class=&quot;math-container&quot;&gt;$E^{Pristine}$&lt;/span&gt;. Next, you have to introduce the defect in the supercell and run another SCF calculation. This will give you &lt;span class=&quot;math-container&quot;&gt;$E^D(q=0)$&lt;/span&gt;. You can then change the &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt; by using the &lt;code&gt;tot_charge&lt;/code&gt; keyword in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; namelist and similarly obtain the energy for the corresponding charged states.&lt;/p&gt;&#xA;&lt;p&gt;The &lt;span class=&quot;math-container&quot;&gt;$E^D_{corr}(q)$&lt;/span&gt; term can be calculated in several ways. For example, &lt;a href=&quot;https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.7.126201&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt; (&lt;a href=&quot;https://arxiv.org/abs/2305.16231&quot; rel=&quot;noreferrer&quot;&gt;arxiv&lt;/a&gt;) they did it in 3 ways:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Manually applying 1st order &lt;a href=&quot;https://journals.aps.org/prb/abstract/10.1103/PhysRevB.51.4014&quot; rel=&quot;noreferrer&quot;&gt;Makov-Payne correction&lt;/a&gt;: &lt;span class=&quot;math-container&quot;&gt;$q^2\alpha/2\epsilon L$&lt;/span&gt; (in atomic units) or &lt;span class=&quot;math-container&quot;&gt;$14.39952q^2\alpha/2\epsilon L$&lt;/span&gt; (in &lt;span class=&quot;math-container&quot;&gt;$eV$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$L$&lt;/span&gt; in Angstrom)&lt;/li&gt;&#xA;&lt;li&gt;Using the &lt;code&gt;assume_isolated='makov-payne'&lt;/code&gt; in QE calculation which gives you higher order corrections&lt;/li&gt;&#xA;&lt;li&gt;Using tools such as &lt;a href=&quot;https://sxrepo.mpie.de/projects/sphinx-add-ons/files&quot; rel=&quot;noreferrer&quot;&gt;SXDEFECTALIGN&lt;/a&gt; - see section 4.5 of &lt;a href=&quot;https://sxrepo.mpie.de/attachments/download/73/sxdefectalign-manual.pdf&quot; rel=&quot;noreferrer&quot;&gt;this document&lt;/a&gt; about how to use this software with QE. Note that the potential alignment term can also be obtained using this.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Now, the only term left is the &lt;span class=&quot;math-container&quot;&gt;$-\sum n_i\mu_i$&lt;/span&gt;, the chemical potential terms. You can calculate them from their elemental configuration or from their stable configuration. The &lt;span class=&quot;math-container&quot;&gt;$\mu_i$&lt;/span&gt; is basically the total energy per atom of the &lt;span class=&quot;math-container&quot;&gt;$i$&lt;/span&gt;-th species. This way you can calculate the defect formation energy as a function of the Fermi level.&lt;/p&gt;&#xA;&lt;p&gt;Usually, people vary the Fermi level in the range of the band gap. For example, if your calculated band gap is 2 eV, then you will vary the Fermi level from 0 to 2 and plot the defect formation energy. Since the formula is of form: &lt;span class=&quot;math-container&quot;&gt;$ y = mx + c$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$m$&lt;/span&gt; corresponds to &lt;span class=&quot;math-container&quot;&gt;$q$&lt;/span&gt;, you will get straight lines plot like the following: (this is one of my calculation for substitutional Cu impurity in ZnS)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ftv65m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ftv65m.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-13T04:43:55.020" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12558" PostTypeId="2" ParentId="11431" CreationDate="2024-03-13T05:17:37.957" Score="6" Body="&lt;p&gt;Unfortunately, the other answer misses the context and does not help in the context of plotting defect formation energy diagram. In the context of calculating defect formation energy diagram, we vary the Fermi level as a free variable. The formula for defect formation energy is:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E_f^D(q,E_F) = \left[E^D(q) + E^D_{corr}(q)\right]-E^{Pristine}-\sum n_i\mu_i + q(E_F + E_{VBM}^{Pristine}-\Delta V_{0/b}).$$&lt;/span&gt;&#xA;which has a form of:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$ E^D_f(q) = q(E_F + A)+ B$$&lt;/span&gt; where &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B$&lt;/span&gt; have constant values for a particular charged state. From doing DFT calculation, we can get all of the terms as explained in this &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12557/6055&quot;&gt;answer&lt;/a&gt;. Then we can plot charged defect formation energy diagram using the following python code (courtesy of &lt;a href=&quot;https://notebook.rcc.uchicago.edu/files/srep20803/Doc/Tutorials/Defect_formation_energy.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;Hosung Seo&lt;/a&gt;, Galli Research Group, uChicago). Before running the code, one needs to prepare an input file with the DFT results as following (example is for N-vacancy center in AlN):&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Input file for defect formation energy calculations&#xA;#So far, I only consider defects in mono-atomic or binary crystals.&#xA;#Defects could be impurity, mono- or di-vacancy, and their complexes&#xA;&#xA;&amp;amp;VBM        #(eV)&#xA;6.9696&#xA;&#xA;&amp;amp;band_gap        #with respect to the VBM (eV)&#xA;5.0&#xA;&#xA;&amp;amp;Host_type&#xA;Al N&#xA;&#xA;&amp;amp;Vacancies  #For example, for divacancy in AlN, put 'Al N'&#xA;N&#xA;&#xA;&amp;amp;Impurities&#xA;&#xA;&amp;amp;Chemical_potentials #(eV)&#xA;Al  -99.7202664&#xA;N   -273.5905338&#xA;&#xA;&amp;amp;Host_supercell_energy #(Ry)&#xA;-6585.061221&#xA;&#xA;&amp;amp;Charge_state_range  #two integer numbers // make sure you have a right number of alignment term&#xA;-2 2&#xA;&#xA;&amp;amp;Defective_supercell_energy # charge_state(q) and energy (Ry) &#xA;-2  -6563.150785&#xA;-1  -6563.955569&#xA;0   -6564.730914&#xA;1   -6565.492659&#xA;2   -6566.044454&#xA;&#xA;&amp;amp;Correction_terms #(eV), for each charge state (e.g. -2 to 2): short-range potential energy, and (E_iso - E_periodic)&#xA;-0.016  0.532248&#xA;-0.014  0.133062&#xA;0   0&#xA;-0.013  0.133062&#xA;-0.023  0.532248&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import sys&#xA;import numpy as np&#xA;import re&#xA;import matplotlib&#xA;import matplotlib.pyplot as plt&#xA;&#xA;class calculate_E_formation:&#xA;    &amp;quot;&amp;quot;&amp;quot; calculate formation energy of a given defect with charge transition levels and plot it.&#xA;    expected to have input file such as Hf_vac_N_poor.in&#xA;    The output file, which will be named as, e.g. Hf_vac_N_poor.in_out can be used as input for the&#xA;    plot_multiple_formation_E class in this module&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;    def __init__(self, filein):&#xA;        &amp;quot;&amp;quot;&amp;quot;initialize an instance&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;        self.filein = filein&#xA;        self.fileout = filein + &amp;quot;_out&amp;quot;&#xA;        self.fileout_CTL = filein + &amp;quot;_CTL&amp;quot;&#xA;&#xA;        self.VBM = 0.0&#xA;        self.band_gap = 0.0&#xA;        self.host_supercell_energy = 0.0&#xA;        self.host_type = 0  #1 - mono-atomic, 2-binary, 3-ternary crystal, etc.&#xA;        self.host_atom = []&#xA;        self.vacancies = []&#xA;        self.impurities = []&#xA;        self.charge_start = 0&#xA;        self.charge_end = 0&#xA;        self.chem_potentials = {} #dictionary type&#xA;        self.supercell_energy_list = []&#xA;        self.correction_terms_list = []&#xA;&#xA;        # Read the input data&#xA;        self.read_data()&#xA;        self.n_charges = int(self.charge_end - self.charge_start + 1)&#xA;        self.supercell_energy = np.array(self.supercell_energy_list).reshape(self.n_charges, 2)&#xA;        self.correction_terms = np.array(self.correction_terms_list).reshape(self.n_charges, 2)&#xA;&#xA;        # Write the formation energy for each charge state&#xA;        self.energy_step = 0.01 # eV&#xA;        self.energy_part = 0.0  # eV&#xA;        self.charge_dependent_part = 0.0 # eV&#xA;        self.fermi_level = []   #x-axis Fermi-level&#xA;        for i in range(0,int(self.band_gap/self.energy_step)):&#xA;            self.fermi_level.append(i * self.energy_step)&#xA;        self.all_data = np.array([])  # will stack actual the data array in self.write_data().&#xA;        self.formation_energy_data = [] #the lowest energy value for a given fermi level&#xA;&#xA;        self.write_data()&#xA;&#xA;        self.CTL_list = []   #charge transition levels&#xA;        self.CTL_list = self.find_CTL() #read the self.formation_energy_data point-by-point, see where the slope changes.&#xA;        self.CTL_count = int(len(self.CTL_list)/2)&#xA;        self.CTL_array = np.array(self.CTL_list).reshape(self.CTL_count,2)&#xA;&#xA;        # Plot the formation energy&#xA;        self.plot_data()&#xA;&#xA;    def read_data(self):&#xA;        with open(self.filein, 'r') as data_file:&#xA;            for line in data_file:&#xA;                if &amp;quot;&amp;amp;VBM&amp;quot; in line:&#xA;                    tmp_line =  data_file.readline()&#xA;                    self.VBM = float(tmp_line)&#xA;                elif &amp;quot;&amp;amp;band_gap&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    self.band_gap = float(tmp_line)&#xA;                elif &amp;quot;&amp;amp;Host_type&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    re_findall = re.findall(r&amp;quot;[\w]+&amp;quot;, tmp_line)&#xA;                    self.host_type = len(re_findall)&#xA;                    for i in range(0, len(re_findall)):&#xA;                        self.host_atom.append(re_findall[i])&#xA;                elif  &amp;quot;&amp;amp;Vacancies&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    re_findall = re.findall(r&amp;quot;[\w]+&amp;quot;, tmp_line)&#xA;                    for i in range(0, len(re_findall)):&#xA;                        self.vacancies.append(re_findall[i])&#xA;                elif &amp;quot;&amp;amp;Impurities&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    re_findall = re.findall(r&amp;quot;[\w]+&amp;quot;, tmp_line)&#xA;                    for i in range(0, len(re_findall)):&#xA;                        self.impurities.append(re_findall[i])&#xA;                elif &amp;quot;&amp;amp;Host_supercell_energy&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    self.host_supercell_energy = float(tmp_line)&#xA;                elif &amp;quot;&amp;amp;Charge_state_range&amp;quot; in line:&#xA;                    tmp_line = data_file.readline()&#xA;                    self.charge_start = int(tmp_line.split()[0])&#xA;                    self.charge_end = int(tmp_line.split()[1])&#xA;                elif &amp;quot;&amp;amp;Chemical_potentials&amp;quot; in line:&#xA;                    chk = True&#xA;                    while chk == True:&#xA;                        tmp_line = data_file.readline()&#xA;                        tmp_line_split = tmp_line.split()&#xA;                        if len(tmp_line_split) &amp;gt; 1:&#xA;                            self.chem_potentials[tmp_line_split[0]] = float(tmp_line_split[1])&#xA;                        elif len(tmp_line_split) == 0:  # hit the end of the chem_potential data.&#xA;                            chk = False&#xA;                        elif &amp;quot;&amp;amp;&amp;quot; in tmp_line:&#xA;                            print( &amp;quot;Warning: there should be a space between every section. \n&amp;quot;)&#xA;                            chk = False&#xA;                        else:&#xA;                            continue&#xA;                elif &amp;quot;&amp;amp;Defective_supercell_energy&amp;quot; in line:&#xA;                    for i in range(self.charge_start, self.charge_end+1):&#xA;                        tmp_line = data_file.readline()&#xA;                        if i == int(tmp_line.split()[0]):&#xA;                            self.supercell_energy_list.append(int(tmp_line.split()[0])) #charge state&#xA;                            self.supercell_energy_list.append(float(tmp_line.split()[1])) #supercell E&#xA;                        else:&#xA;                            sys.exit(&amp;quot;check the charge state range and defective supercell \&#xA;                                energy\n&amp;quot;)&#xA;                elif &amp;quot;&amp;amp;Correction_terms&amp;quot; in line:&#xA;                    for i in range(self.charge_start, self.charge_end+1):&#xA;                        tmp_line = data_file.readline()&#xA;                        self.correction_terms_list.append(int(i))   #charge state&#xA;                        self.correction_terms_list.append(float(tmp_line.split()[0])) #short-range&#xA;                else:&#xA;                    continue&#xA;&#xA;    def write_data(self):&#xA;        Ry = 13.605692  #eV&#xA;        for i in range(0, self.n_charges):&#xA;            q = self.charge_start + i   # e.g. -2, -1, 0, 1, 2&#xA;            print (&amp;quot;\n&amp;quot; + &amp;quot;charge_state =&amp;quot; + str(q) + &amp;quot;\n&amp;quot;)&#xA;&#xA;            if q == self.correction_terms[i,0]: # Should contain the charge state, q.&#xA;                E_correction = self.correction_terms[i,1]&#xA;                print (&amp;quot;E_correction = &amp;quot; + str(E_correction) + &amp;quot;\n&amp;quot;)&#xA;            else:&#xA;                sys.exit(&amp;quot;Check the self.correction_terms np array. The first column should contain\&#xA;                    the charge state.\n&amp;quot;)&#xA;&#xA;            if q == self.supercell_energy[i,0]:&#xA;                Energy_part = self.supercell_energy[i,1] *Ry +E_correction -1*self.host_supercell_energy*Ry&#xA;                print (&amp;quot;Energy_part = &amp;quot; + str(Energy_part) + &amp;quot;\n&amp;quot;)&#xA;            else:&#xA;                sys.exit(&amp;quot;Check the self.supercell_energy np array.\n&amp;quot;)&#xA;&#xA;            formation_energy =  Energy_part + q* self.VBM&#xA;            #add the chemical potential parts.&#xA;&#xA;            if self.vacancies:&#xA;                for c in self.vacancies:&#xA;                    formation_energy = formation_energy - (-1)* self.chem_potentials[c]&#xA;                    print (&amp;quot;chem_potential for &amp;quot; + str(c) + &amp;quot; (vacancy)  has been added. \n&amp;quot;)&#xA;                    print (&amp;quot;Energy_part + q* VBM + chem_pot (so far) = &amp;quot; + str(formation_energy) + &amp;quot;\n&amp;quot;)&#xA;            else:&#xA;                print('no vacancies are present\n')&#xA;            if self.impurities:&#xA;                for c in self.impurities:&#xA;                    formation_energy = formation_energy - (+1)* self.chem_potentials[c]&#xA;                    print (&amp;quot;chem_potential for &amp;quot; + str(c) + &amp;quot; (impurity)  has been added. \n&amp;quot;)&#xA;                    print (&amp;quot;Energy_part + q* VBM + chem_pot (so far) = &amp;quot; + str(formation_energy) + &amp;quot;\n&amp;quot;)&#xA;            else:&#xA;                print('no foreign impurities are present \n')&#xA;&#xA;            data_list =[]&#xA;&#xA;            for j in range(0,int(self.band_gap/self.energy_step)):&#xA;                data_list.append(formation_energy + q* self.fermi_level[j])&#xA;&#xA;            if len(self.all_data) == 0:&#xA;                self.all_data = np.append(self.all_data, np.array(data_list))&#xA;            else:&#xA;                self.all_data = np.vstack((self.all_data, np.array(data_list)))&#xA;&#xA;        for i in range(0,int(self.band_gap/self.energy_step)):&#xA;            tmp_array = self.all_data[:,i]&#xA;            minimum_E = np.sort(tmp_array)[0]&#xA;            self.formation_energy_data.append(minimum_E)&#xA;&#xA;        with open(self.fileout, 'w') as fout:&#xA;            for i in range(0,int(self.band_gap/self.energy_step)):&#xA;                fout.write('{0:&amp;lt;15.7f} {1:&amp;lt;15.7f} \n'.format(self.fermi_level[i],\&#xA;                    self.formation_energy_data[i]))&#xA;&#xA;    def find_CTL(self):&#xA;        #find the charge transition levels where the slope changes&#xA;        CTL = []&#xA;        slope_to_compare = self.charge_end&#xA;        slope_threshold = 0.5&#xA;        delta_x = self.energy_step&#xA;&#xA;        fout_str = str(self.filein) + &amp;quot;_CTL&amp;quot;&#xA;        with open(fout_str, 'w') as fout:&#xA;            fout.write(&amp;quot;charge transition levels for &amp;quot; + str(self.filein) + &amp;quot;\n&amp;quot;)&#xA;&#xA;        for i in range(1, int(self.band_gap/self.energy_step)):&#xA;            delta_y = self.formation_energy_data[i]-self.formation_energy_data[i-1]&#xA;            slope = delta_y/delta_x&#xA;            #print(&amp;quot;slope = &amp;quot; + str(slope) + &amp;quot;\n&amp;quot;)&#xA;            slope_diff = slope_to_compare - slope&#xA;            if abs(slope_diff) &amp;lt; slope_threshold:&#xA;                continue&#xA;            else:&#xA;                print(&amp;quot;CTL from&amp;quot; + str(slope_to_compare) + &amp;quot; to &amp;quot; + str (slope_to_compare - 1) + &amp;quot; = &amp;quot; + \&#xA;                    str((self.fermi_level[i-1] + self.fermi_level[i])/2.0) + &amp;quot;\n&amp;quot;)&#xA;                CTL_point = self.fermi_level[i-1] + delta_x/2.0&#xA;                CTL.append(CTL_point)&#xA;                CTL_energy = self.formation_energy_data[i-1]+slope*delta_x/2.0&#xA;                CTL.append(CTL_energy)&#xA;                with open(fout_str, 'a') as fout:&#xA;                    fout.write('{0:&amp;lt;3d} to  {1:&amp;lt;3d} = {2:&amp;lt;10.5f} \n'.format(slope_to_compare,\&#xA;                        slope_to_compare-1, CTL_point))&#xA;                slope_to_compare = slope_to_compare - 1&#xA;        return CTL&#xA;&#xA;    def plot_data(self):&#xA;        x_data = self.fermi_level&#xA;        x_min = self.fermi_level[0]&#xA;        x_max = self.fermi_level[int(self.band_gap/self.energy_step)-1]+self.energy_step&#xA;&#xA;        fig = plt.figure(figsize=(8,8))&#xA;        axes = fig.add_subplot(1,1,1)&#xA;        axes.tick_params(axis='both', which='major', labelsize=15)&#xA;        axes.tick_params(axis='both', which='minor', labelsize=12)&#xA;        plt.xlim (x_min, x_max)&#xA;        #plt.ylim(0,3)&#xA;&#xA;        #plot all data&#xA;        for i in range(0, self.n_charges):&#xA;            q = self.charge_start + i   # e.g. -2, -1, 0, 1, 2&#xA;            y_data = self.all_data[i,:]&#xA;            label_str = fr'&lt;span class=&quot;math-container&quot;&gt;$Cu_{{Zn}}$&lt;/span&gt; with q={q}'&#xA;            axes.plot(x_data, y_data, '-', label=label_str)&#xA;&#xA;        #plot the lowest-energy data on top&#xA;        y_data = self.formation_energy_data&#xA;        axes.plot(x_data,y_data, color = &amp;quot;k&amp;quot;  , linewidth = 3, linestyle = '-')&#xA;&#xA;        axes.legend(loc=0)&#xA;&#xA;        axes.set_xlabel('Fermi level (eV)', fontsize = 18)&#xA;        axes.set_ylabel('Defect formation energy (eV)', fontsize = 18)&#xA;        axes.set_title(self.filein, fontsize = 18)&#xA;&#xA;        x_CTL_data = self.CTL_array[:,0]&#xA;        y_CTL_data = self.CTL_array[:,1]&#xA;        axes.plot(x_CTL_data, y_CTL_data, color = 'b', marker = '.', markersize = 4 , mew =  4)&#xA;&#xA;        fig.savefig(str(self.fileout)+'.png')&#xA;        plt.legend(prop={'size': 18})&#xA;        plt.show(fig)&#xA;&#xA;class plot_multiple_formation_E:&#xA;    &amp;quot;&amp;quot;&amp;quot; plot multiple formation energies together.&#xA;        there should be a input file, containing the name of each formation energy file&#xA;        and y_min and y_max&#xA;        For example, prepare a file, named as plot_together_Hf_La.in&#xA;        In the file,&#xA;        Hf_imp_C_poor.in_out&#xA;        Hf_vac_C_pool.in_out&#xA;        La_imp_C_poor.in_out&#xA;        La_vac_C_poor.in_out &amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;    def __init__(self, filein, x_min=None, x_max=None, y_min=None, y_max=None):&#xA;        &amp;quot;&amp;quot;&amp;quot;initialize an instance&amp;quot;&amp;quot;&amp;quot;&#xA;        self.filein = filein&#xA;        self.x_range_chk = False&#xA;        if x_min != None:&#xA;            self.x_range_chk = True&#xA;            self.x_min = x_min&#xA;            self.x_max = x_max&#xA;        else:&#xA;            self.x_min = 0.0&#xA;            self.x_max = 10.0&#xA;&#xA;        self.y_range_chk = False&#xA;        if y_min != None:&#xA;            self.y_range_chk = True&#xA;            self.y_min = y_min&#xA;            self.y_max = y_max&#xA;        else:&#xA;            self.y_min = 0.0&#xA;            self.y_max = 10.0&#xA;&#xA;        self.plot_all()&#xA;&#xA;    def plot_all(self):&#xA;        fig = plt.figure(figsize=(8,8))&#xA;        axes = fig.add_subplot(1,1,1)&#xA;        with open(self.filein, 'r') as fin:&#xA;            for line in fin:&#xA;                f_name = re.findall(r&amp;quot;[\w.]+&amp;quot;, line)[0]&#xA;                print(&amp;quot;Adding the following to the plot: &amp;quot; + f_name + &amp;quot;\n&amp;quot;)&#xA;                data = np.genfromtxt(f_name)&#xA;                x_data = data[:,0]&#xA;                y_data = data[:,1]&#xA;                axes.plot(x_data, y_data, '-', label= f_name)&#xA;        axes.legend(loc=0, fontsize=20)&#xA;        axes.set_xlabel('E - E_VBM (eV)', fontsize = 18)&#xA;        axes.set_ylabel('Formation Energy (eV)', fontsize = 18)&#xA;        axes.set_title('Defect Formation Energy', fontsize = 20)&#xA;&#xA;        if self.x_range_chk:&#xA;            plt.xlim(self.x_min, self.x_max)&#xA;&#xA;        if self.y_range_chk:&#xA;            plt.ylim(self.y_min, self.y_max)&#xA;&#xA;        fig.savefig(str(self.filein) + '.png')&#xA;        plt.show(fig)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;and run the code by doing:&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;# For a single charge state&#xA;calculate_E_formation('dfe.in')&#xA;# For multiple charge state (which you are looking for, I believe)&#xA;plot_multiple_formation_E('multiple_dfe.in')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Check the docstring of the corresponding function to learn more about the input file syntax. Just from the total energy of the pristine supercell, defect supercells, VBM, correction terms (if any, otherwise set 0), and chemical potentials (total energy of the elemental forms), the above code can generate the following types of figures:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/uDNiKm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/uDNiKm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/Ub4hLm.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Ub4hLm.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2024-03-16T17:45:00.817" LastActivityDate="2024-03-16T17:45:00.817" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12559" PostTypeId="1" AcceptedAnswerId="12563" CreationDate="2024-03-14T04:27:30.877" Score="4" ViewCount="76" Body="&lt;p&gt;Dynamical stability is checked by a phonon curve. Thermal stability is checked by a molecular dynamics simulation. What is the difference between them?&lt;/p&gt;&#xA;" OwnerUserId="9955" LastEditorUserId="5" LastEditDate="2024-03-14T04:29:10.487" LastActivityDate="2024-03-14T23:24:04.990" Title="Thermal vs dynamical stability" Tags="|density-functional-theory|vasp|molecular-dynamics|phonons|phonon-dispersion|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12560" PostTypeId="1" CreationDate="2024-03-14T11:45:04.720" Score="1" ViewCount="18" Body="&lt;p&gt;Suppose the left and right leads are both copper rod and the central scattering region is one monolayer graphene sheet. There is no chemical bonding formed between Cu and C atoms. The copper and graphene are connected by the Van der Waals interaction.&lt;/p&gt;&#xA;&lt;p&gt;Is the non equilibrium green function (NEGF) method applicable for the thermal conductance calculation along both lateral and longitudinal direction for such system?&lt;/p&gt;&#xA;&lt;p&gt;Would anyone please give me some suggestions?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastActivityDate="2024-03-14T11:45:04.720" Title="Thermal Conductance along the lateral and longitudinal direction" Tags="|density-functional-theory|molecular-dynamics|phonon-dispersion|lattice-thermal-conductivity|nonequilibrium|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12561" PostTypeId="1" CreationDate="2024-03-14T17:14:18.993" Score="2" ViewCount="81" Body="&lt;p&gt;Can some one please help me in installing Quantum Espresso? Is the software available for Windows or it only for Linux? And I read that Burai is GUI for Quantum Espresso, is it?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="5" LastEditDate="2024-03-15T02:47:07.613" LastActivityDate="2024-03-16T11:35:15.350" Title="Does any one know about Quantum Espresso and Burai?" Tags="|quantum-espresso|software-assistance|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12562" PostTypeId="2" ParentId="12561" CreationDate="2024-03-14T23:09:34.030" Score="2" Body="&lt;p&gt;Quantum Espersso is available on Linux, and you can install it from the repository using the command &lt;code&gt;sudo apt-get install quantum-espresso&lt;/code&gt; it would probably install the version 6.x which might be good enough in most cases. But if you need the latest version, you can get the source files for the repository from &lt;a href=&quot;https://gitlab.com/QEF/q-e&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitLab&lt;/a&gt; and build it on your own. The landing page has detailed instructions on how to obtain the code and build it.&lt;/p&gt;&#xA;&lt;p&gt;BURAI is one of the GUIs for Quantum Espresso and as far my understanding goes there are two more GUIs names &lt;a href=&quot;http://www.xcrysden.org&quot; rel=&quot;nofollow noreferrer&quot;&gt;XCrysDen&lt;/a&gt; and &lt;a href=&quot;http://www-k3.ijs.si/kokalj/pwgui/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PWgui&lt;/a&gt; available for Quantum Espresso.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-03-14T23:32:19.177" LastActivityDate="2024-03-14T23:32:19.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12563" PostTypeId="2" ParentId="12559" CreationDate="2024-03-14T23:24:04.990" Score="3" Body="&lt;p&gt;Let's see what is the difference between the two things that you are looking for:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Dynamic Stability&lt;/strong&gt;: This is usually calculated from ab-inito calculations, where you calculate the dynamic matrix for the molecule at every k-point and then evaluate it's eigen vectors and eigen values to find the phonon dispersion curve. This is usually done at 0K and will tell you if you have reached a minimum on the potential energy surface. I should also note that you can calculate phonon curves from MD simulations (LAMMPS can do this).&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;&lt;strong&gt;Thermal stability&lt;/strong&gt;: It is not immediately clear if you are asking if MD can give you information about if a material is combustible, or if a material is stable at a temperature greater than 0K. If you are looking for the latter, You can very well perform an MD simulation of the system at any temperature of your choice and see if the structural integrity is conserved. However, if you are looking for the former, you might have some luck with ReaxFF and associated techniques.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-14T23:24:04.990" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12565" PostTypeId="1" AcceptedAnswerId="12566" CreationDate="2024-03-15T05:44:18.150" Score="4" ViewCount="161" Body="&lt;p&gt;I am performing some DFT calculations of monolayer hexagonal boron nitride in Quantum ESPRESSO. I have been trying to calculate the density of states of a 7 x 7 supercell of h-BN, but the resulting density of states does not scale up properly. For a 1 x 1 primitive cell system, I get a smooth plot; for a 3 x 3 system, I get an identical plot, but for a 7 x7 system, there is too much noise:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/3yR5A.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/3yR5A.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/01rWh.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/01rWh.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&#xA;&lt;a href=&quot;https://i.stack.imgur.com/AQuLI.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/AQuLI.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;What might be the cause of this trouble? The only difference between the scf and nscf files for the supercells is the number of K-POINTS and total number of atoms.&lt;/p&gt;&#xA;&lt;p&gt;scf file for 1 x 1:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  prefix = 'hbn'&#xA;  pseudo_dir = '../pseudos/'&#xA;  outdir = '../out/'&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  nat = 2&#xA;  ntyp = 2&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss =   0.002&#xA;  ecutwfc =   60&#xA;  ecutrho =   600&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;  mixing_beta =   0.7&#xA;  conv_thr =      1d-6&#xA;/&#xA;ATOMIC_SPECIES&#xA;    B      10.811       B.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;    N      14.0067      N.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS crystal&#xA;    B            0.6666666666       0.3333333333       0.5000000000 &#xA;    N            0.3333333333       0.6666666666       0.5000000000 &#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   2.514856081   0.000000000   0.000000000&#xA;  -1.257428041   2.177929253   0.000000000&#xA;   0.000000000   0.000000000  10.000000000&#xA;&#xA;K_POINTS automatic&#xA;  9 9 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;scf for 3 x 3 case:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  prefix = 'hbn'&#xA;  pseudo_dir = './pseudos/'&#xA;  outdir = './out/'&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  nat = 18&#xA;  ntyp = 2&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss =   0.002&#xA;  ecutwfc =   60&#xA;  ecutrho =   600&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;  mixing_beta =   0.7&#xA;  conv_thr =      1d-6&#xA;/&#xA;ATOMIC_SPECIES&#xA;    5      10.811       B.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;    7      14.0067      N.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS angstrom&#xA;    5    1.2574280400    0.7259764180    5.0000000000&#xA;    7    0.0000000000    1.4519528350    5.0000000000&#xA;    5   -0.0000000010    2.9039056710    5.0000000000&#xA;    7   -1.2574280410    3.6298820880    5.0000000000&#xA;    5   -1.2574280420    5.0818349240    5.0000000000&#xA;    7   -2.5148560820    5.8078113410    5.0000000000&#xA;    5    3.7722841210    0.7259764180    5.0000000000&#xA;    7    2.5148560810    1.4519528350    5.0000000000&#xA;    5    2.5148560800    2.9039056710    5.0000000000&#xA;    7    1.2574280400    3.6298820880    5.0000000000&#xA;    5    1.2574280390    5.0818349240    5.0000000000&#xA;    7   -0.0000000010    5.8078113410    5.0000000000&#xA;    5    6.2871402020    0.7259764180    5.0000000000&#xA;    7    5.0297121620    1.4519528350    5.0000000000&#xA;    5    5.0297121610    2.9039056710    5.0000000000&#xA;    7    3.7722841210    3.6298820880    5.0000000000&#xA;    5    3.7722841200    5.0818349240    5.0000000000&#xA;    7    2.5148560800    5.8078113410    5.0000000000 &#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   7.544568243   0.000000000   0.000000000&#xA;  -3.772284123   6.533787759   0.000000000&#xA;   0.000000000   0.000000000  10.000000000&#xA;&#xA;K_POINTS automatic&#xA;  3 3 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;scf file for 7 x 7 case:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  prefix = 'hbn'&#xA;  pseudo_dir = './pseudos/'&#xA;  outdir = './out/'&#xA;/&#xA;&#xA;&amp;amp;SYSTEM&#xA;  ibrav = 0&#xA;  nat = 98&#xA;  ntyp = 2&#xA;  occupations = 'smearing'&#xA;  smearing = 'mv'&#xA;  degauss =   0.002&#xA;  ecutwfc =   60&#xA;  ecutrho =   600&#xA;/&#xA;&#xA;&amp;amp;ELECTRONS&#xA;  mixing_beta =   0.7&#xA;  conv_thr =      1d-6&#xA;/&#xA;ATOMIC_SPECIES&#xA;    5      10.811       B.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;    7      14.0067      N.pbe-n-kjpaw_psl.1.0.0.UPF&#xA;&#xA;ATOMIC_POSITIONS angstrom&#xA;    5    1.2574280400    0.7259764180    5.0000000000&#xA;    7    0.0000000000    1.4519528350    5.0000000000&#xA;    5   -0.0000000010    2.9039056710    5.0000000000&#xA;    7   -1.2574280410    3.6298820880    5.0000000000&#xA;    5   -1.2574280420    5.0818349240    5.0000000000&#xA;    7   -2.5148560820    5.8078113410    5.0000000000&#xA;    5   -2.5148560830    7.2597641770    5.0000000000&#xA;    7   -3.7722841230    7.9857405940    5.0000000000&#xA;    5   -3.7722841240    9.4376934300    5.0000000000&#xA;    7   -5.0297121640   10.1636698470    5.0000000000&#xA;    5   -5.0297121650   11.6156226830    5.0000000000&#xA;    7   -6.2871402050   12.3415991000    5.0000000000&#xA;    5   -6.2871402060   13.7935519360    5.0000000000&#xA;    7   -7.5445682460   14.5195283530    5.0000000000&#xA;    5    3.7722841210    0.7259764180    5.0000000000&#xA;    7    2.5148560810    1.4519528350    5.0000000000&#xA;    5    2.5148560800    2.9039056710    5.0000000000&#xA;    7    1.2574280400    3.6298820880    5.0000000000&#xA;    5    1.2574280390    5.0818349240    5.0000000000&#xA;    7   -0.0000000010    5.8078113410    5.0000000000&#xA;    5   -0.0000000020    7.2597641770    5.0000000000&#xA;    7   -1.2574280420    7.9857405940    5.0000000000&#xA;    5   -1.2574280430    9.4376934300    5.0000000000&#xA;    7   -2.5148560830   10.1636698470    5.0000000000&#xA;    5   -2.5148560840   11.6156226830    5.0000000000&#xA;    7   -3.7722841240   12.3415991000    5.0000000000&#xA;    5   -3.7722841250   13.7935519360    5.0000000000&#xA;    7   -5.0297121650   14.5195283530    5.0000000000&#xA;    5    6.2871402020    0.7259764180    5.0000000000&#xA;    7    5.0297121620    1.4519528350    5.0000000000&#xA;    5    5.0297121610    2.9039056710    5.0000000000&#xA;    7    3.7722841210    3.6298820880    5.0000000000&#xA;    5    3.7722841200    5.0818349240    5.0000000000&#xA;    7    2.5148560800    5.8078113410    5.0000000000&#xA;    5    2.5148560790    7.2597641770    5.0000000000&#xA;    7    1.2574280390    7.9857405940    5.0000000000&#xA;    5    1.2574280380    9.4376934300    5.0000000000&#xA;    7   -0.0000000020   10.1636698470    5.0000000000&#xA;    5   -0.0000000030   11.6156226830    5.0000000000&#xA;    7   -1.2574280430   12.3415991000    5.0000000000&#xA;    5   -1.2574280440   13.7935519360    5.0000000000&#xA;    7   -2.5148560840   14.5195283530    5.0000000000&#xA;    5    8.8019962830    0.7259764180    5.0000000000&#xA;    7    7.5445682430    1.4519528350    5.0000000000&#xA;    5    7.5445682420    2.9039056710    5.0000000000&#xA;    7    6.2871402020    3.6298820880    5.0000000000&#xA;    5    6.2871402010    5.0818349240    5.0000000000&#xA;    7    5.0297121610    5.8078113410    5.0000000000&#xA;    5    5.0297121600    7.2597641770    5.0000000000&#xA;    7    3.7722841200    7.9857405940    5.0000000000&#xA;    5    3.7722841190    9.4376934300    5.0000000000&#xA;    7    2.5148560790   10.1636698470    5.0000000000&#xA;    5    2.5148560780   11.6156226830    5.0000000000&#xA;    7    1.2574280380   12.3415991000    5.0000000000&#xA;    5    1.2574280370   13.7935519360    5.0000000000&#xA;    7   -0.0000000030   14.5195283530    5.0000000000&#xA;    5   11.3168523640    0.7259764180    5.0000000000&#xA;    7   10.0594243240    1.4519528350    5.0000000000&#xA;    5   10.0594243230    2.9039056710    5.0000000000&#xA;    7    8.8019962830    3.6298820880    5.0000000000&#xA;    5    8.8019962820    5.0818349240    5.0000000000&#xA;    7    7.5445682420    5.8078113410    5.0000000000&#xA;    5    7.5445682410    7.2597641770    5.0000000000&#xA;    7    6.2871402010    7.9857405940    5.0000000000&#xA;    5    6.2871402000    9.4376934300    5.0000000000&#xA;    7    5.0297121600   10.1636698470    5.0000000000&#xA;    5    5.0297121590   11.6156226830    5.0000000000&#xA;    7    3.7722841190   12.3415991000    5.0000000000&#xA;    5    3.7722841180   13.7935519360    5.0000000000&#xA;    7    2.5148560780   14.5195283530    5.0000000000&#xA;    5   13.8317084450    0.7259764180    5.0000000000&#xA;    7   12.5742804050    1.4519528350    5.0000000000&#xA;    5   12.5742804040    2.9039056710    5.0000000000&#xA;    7   11.3168523640    3.6298820880    5.0000000000&#xA;    5   11.3168523630    5.0818349240    5.0000000000&#xA;    7   10.0594243230    5.8078113410    5.0000000000&#xA;    5   10.0594243220    7.2597641770    5.0000000000&#xA;    7    8.8019962820    7.9857405940    5.0000000000&#xA;    5    8.8019962810    9.4376934300    5.0000000000&#xA;    7    7.5445682410   10.1636698470    5.0000000000&#xA;    5    7.5445682400   11.6156226830    5.0000000000&#xA;    7    6.2871402000   12.3415991000    5.0000000000&#xA;    5    6.2871401990   13.7935519360    5.0000000000&#xA;    7    5.0297121590   14.5195283530    5.0000000000&#xA;    5   16.3465645260    0.7259764180    5.0000000000&#xA;    7   15.0891364860    1.4519528350    5.0000000000&#xA;    5   15.0891364850    2.9039056710    5.0000000000&#xA;    7   13.8317084450    3.6298820880    5.0000000000&#xA;    5   13.8317084440    5.0818349240    5.0000000000&#xA;    7   12.5742804040    5.8078113410    5.0000000000&#xA;    5   12.5742804030    7.2597641770    5.0000000000&#xA;    7   11.3168523630    7.9857405940    5.0000000000&#xA;    5   11.3168523620    9.4376934300    5.0000000000&#xA;    7   10.0594243220   10.1636698470    5.0000000000&#xA;    5   10.0594243210   11.6156226830    5.0000000000&#xA;    7    8.8019962810   12.3415991000    5.0000000000&#xA;    5    8.8019962800   13.7935519360    5.0000000000&#xA;    7    7.5445682400   14.5195283530    5.0000000000 &#xA;&#xA;CELL_PARAMETERS (angstrom)&#xA;   17.603992567  0.000000000   0.000000000&#xA;  -8.801996287   15.245504771  0.000000000&#xA;   0.000000000   0.000000000  10.000000000&#xA;&#xA;K_POINTS automatic&#xA;  3 3 1 0 0 0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="9951" LastEditorUserId="9951" LastEditDate="2024-03-15T05:46:30.450" LastActivityDate="2024-03-16T09:54:47.127" Title="Density of states does not scale properly with supercell" Tags="|density-functional-theory|quantum-espresso|density-of-states|supercell|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12566" PostTypeId="2" ParentId="12565" CreationDate="2024-03-15T09:01:06.163" Score="5" Body="&lt;p&gt;When the size of the supercell increases, you can reduce the number of k-points in an inverse manner to get the same accuracy as the one with the smaller cell. This is because the relation between real space and k-space is reciprocal.&lt;/p&gt;&#xA;&lt;p&gt;For a unit (i.e. &lt;span class=&quot;math-container&quot;&gt;$1\times1\times1$&lt;/span&gt;) cell, you used &lt;span class=&quot;math-container&quot;&gt;$9\times9\times1$&lt;/span&gt; k-grid. So for a &lt;span class=&quot;math-container&quot;&gt;$3\times3\times1$&lt;/span&gt; supercell, your new k-point should be &lt;span class=&quot;math-container&quot;&gt;$3\times3\times1$&lt;/span&gt; which you correctly used. However, for a &lt;span class=&quot;math-container&quot;&gt;$7\times7\times1$&lt;/span&gt; supercell, you still used the same k-grid of &lt;span class=&quot;math-container&quot;&gt;$3\times3\times1$&lt;/span&gt; and this increased the k-point density than you had in your previous calculations. That's a probable cause of the noise you see in your DOS.&lt;/p&gt;&#xA;&lt;p&gt;Moreover, it is not clear if you used the same k-grid in your NSCF calculation or if you increased it a little bit with &lt;code&gt;occupations='tetrahedra'&lt;/code&gt;. The k-grid of NSCF can decide the DOS output significantly. So my suggestions would be to fix the k-point scaling, and if there is nothing special with a &lt;span class=&quot;math-container&quot;&gt;$7\times7\times1$&lt;/span&gt; supercell, then use a supercell where you can calculate the scaling to be an integer. And also check the following suggested k-points distance information from &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;MaterialsCloud's QE input generator&lt;/a&gt;. I think for a little bit larger supercell, a &lt;code&gt;gamma-only&lt;/code&gt; or Baldereschi point-only &lt;code&gt;1/4 1/4 1/4 (crystal)&lt;/code&gt; sampling will suffice in your case.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;The default is 0.2 1/Å, that is a conservative, all-purpose choice. We call this &amp;quot;fine&amp;quot; sampling, and the appropriate smearing/degauss is 0.2 eV. The two other options are &amp;quot;very fine&amp;quot; sampling (0.15 1/Å, 0.1 eV), or &amp;quot;normal&amp;quot; (0.3 1/Å, 0.3 eV). Note that we change the degauss since a coarser sampling benefits from more smearing. Last: there is no point in sampling the Brillouin Zone in a direction in which there shouldn't be any dispersion (as is the case for, say, a 0-, 1- or 2-dimensional system where 3, 2, or 1 directions shouldn't be sampled); in these cases you should update the input file by hand a posteriori. You can also decide to use a shifted Monkhorst-Pack mesh (just change 0 0 0 -&amp;gt; 1 1 1 in the last 3 numbers of the k-point entry). If you are a PWscf Jedi, for large cells you could use the Baldereschi point (1/4 1/4 1/4) and nosym=.true. to get much better sampling than Gamma-only (at twice the cost).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;" OwnerUserId="6055" LastEditorUserId="6055" LastEditDate="2024-03-16T09:54:47.127" LastActivityDate="2024-03-16T09:54:47.127" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12567" PostTypeId="1" CreationDate="2024-03-15T11:46:32.177" Score="2" ViewCount="92" Body="&lt;p&gt;How can one generate a band.conf file for performing phonon calculations of graphene with a&#xA;dim 1x1x1 using the (DFPT) method?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastActivityDate="2024-03-15T11:46:32.177" Title="How to create a band.conf File for Phonon Calculations of Graphene with DFPT Method?" Tags="|vasp|phonopy|phonon-dispersion|dfpt|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12568" PostTypeId="1" AcceptedAnswerId="12572" CreationDate="2024-03-15T23:55:56.990" Score="3" ViewCount="45" Body="&lt;p&gt;The electronic Hamiltonian in the canonical orbital basis has the following form:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;H_e = h_0 + \sum_{ij=1}^{N} h_{ij} \sum_{\sigma \in \{\uparrow,\downarrow\}} a_{i\sigma}^\dagger a_{j\sigma} + \frac{1}{2}\sum_{ijkl=1}^{N} g_{ijkl} \sum_{\sigma\tau \in \{\uparrow,\downarrow\}} a_{i\sigma}^\dagger a_{j\tau}^\dagger a_{k\tau}a_{l\sigma},&#xA;$$&lt;/span&gt;&#xA;in which &lt;span class=&quot;math-container&quot;&gt;$i,j,k,l$&lt;/span&gt; index over the spatial orbitals. If one wishes to work in an active space &lt;span class=&quot;math-container&quot;&gt;$S \subset \{1,\ldots,N\}$&lt;/span&gt;, this defines a new Hamiltonian:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{2}&#xA;H_e = \tilde{h}_0 + \sum_{ij\in S} \tilde{h}_{ij} \sum_{\sigma \in \{\uparrow,\downarrow\}} a_{i\sigma}^\dagger a_{j\sigma} + \frac{1}{2}\sum_{ijkl \in S} \tilde{g}_{ijkl} \sum_{\sigma\tau \in \{\uparrow,\downarrow\}} a_{i\sigma}^\dagger a_{j\tau}^\dagger a_{k\tau}a_{l\sigma}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question is, how does one derive the new coefficients &lt;span class=&quot;math-container&quot;&gt;$\tilde{h}_0, \tilde{h}_{ij}, \tilde{g}_{ijkl}$&lt;/span&gt; given the core and virtual orbitals?&lt;/strong&gt; There is a lot of software for doing this automatically, but I was unable to find a derivation for the formulas used (the closest I found was &lt;a href=&quot;http://pybest.fizyka.umk.pl/pybest-v1.0.0/user_hamiltonian_activespace.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;this&lt;/a&gt; which only contains formulas but no derivation).&lt;/p&gt;&#xA;" OwnerUserId="3574" LastEditorUserId="5" LastEditDate="2024-03-16T00:08:22.173" LastActivityDate="2024-03-16T09:12:00.177" Title="How is the form of the active space electronic Hamiltonian derived?" Tags="|quantum-chemistry|electronic-structure|active-space|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12569" PostTypeId="5" CreationDate="2024-03-16T00:11:20.043" Score="0" Body="&lt;p&gt;&lt;a href=&quot;https://en.wikipedia.org/wiki/Complete_active_space&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://en.wikipedia.org/wiki/Complete_active_space&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-03-16T00:11:20.043" LastActivityDate="2024-03-16T00:11:20.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12570" PostTypeId="4" CreationDate="2024-03-16T00:11:20.043" Score="0" Body="Questions about or related to active spaces, active space selection, and methods based on a CAS, RAS, GAS, LAS, etc. " OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-03-16T00:11:20.043" LastActivityDate="2024-03-16T00:11:20.043" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12571" PostTypeId="1" CreationDate="2024-03-16T06:51:10.623" Score="2" ViewCount="20" Body="&lt;p&gt;I am running LAMMPS simulation where KOH and NaOH  are being utilized. I was successful in finding pair coefficients from literature but could not get hold of bond coefficients(kr &amp;amp; r theta)for KOH and NaOH. Lipargen server however works only for organic ligands.&#xA;I am unable to complete my topology file for LAMMPS simulation since I am failing to obtain bond coefficients of O-H bond of KOH and NaOH.&#xA;Can anyone please help me.&#xA;Thanks in advance:)&lt;/p&gt;&#xA;" OwnerUserId="9960" LastActivityDate="2024-03-16T06:51:10.623" Title="Where can I generate OPLS AA parameter for KOH and NaOH" Tags="|lammps|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12572" PostTypeId="2" ParentId="12568" CreationDate="2024-03-16T09:12:00.177" Score="2" Body="&lt;p&gt;When you have a set of inactive orbitals, you just replace the bare one-electron operators in the active space with the Fock operator, which contains the Coulomb and exchange contributions from the inactive orbitals. If you want to dig out the mathematical formulation, &lt;a href=&quot;https://onlinelibrary.wiley.com/doi/book/10.1002/9781119019572&quot; rel=&quot;nofollow noreferrer&quot;&gt;the purple bible&lt;/a&gt; is usually the place to start from.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-03-16T09:12:00.177" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12573" PostTypeId="2" ParentId="12561" CreationDate="2024-03-16T11:35:15.350" Score="1" Body="&lt;h1&gt;Windows or Linux?&lt;/h1&gt;&#xA;&lt;p&gt;Quantum ESPRESSO can be installed on any Linux environment. It is also available on Windows using MinGW, Cygwin or Windows Subsystem for Linux (WSL). Alternatively, you can install BURAI (A JRE GUI for an older version of QE) on Windows or Linux.&lt;/p&gt;&#xA;&lt;p&gt;I highly recommend installing the command line version for actual calculation. But you may want to use BURAI for learning purposes. BURAI is very limited in terms of what it can do. For installation instruction on windows, see &lt;a href=&quot;https://www.quantum-espresso.org/Doc/user_guide/node16.html#SubSec:Windows&quot; rel=&quot;nofollow noreferrer&quot;&gt;this section&lt;/a&gt; on QE's official website. For installation in Linux, you can follow the step by step tutorial in &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/10657/6055&quot;&gt;this answer&lt;/a&gt;. You may prefer the second option mentioned there because you will have less control over the compilation in the first option.&lt;/p&gt;&#xA;&lt;h1&gt;What is BURAI?&lt;/h1&gt;&#xA;&lt;p&gt;BURAI is known as a GUI for Quantum ESPRESSO. However, I think it's misleading. The features are almost entirely limited to &lt;code&gt;pw.x&lt;/code&gt;. That means using BURAI, you can run the &lt;code&gt;pw.x&lt;/code&gt; and some related post-processing tools such as &lt;code&gt;dos.x&lt;/code&gt;, &lt;code&gt;bands.x&lt;/code&gt; etc. Some relaxation calculation can be run too. But to the best of my knowledge, it cannot run &lt;code&gt;ph.x&lt;/code&gt; or NEB or TDDFT etc. These features are marked as &lt;em&gt;coming soon&lt;/em&gt; but the BURAI project seems discontinued for more than 7 years! You may still want to use it as a tool to visualize your structure, build supercell/slabs, getting a templated input file, etc.&lt;/p&gt;&#xA;&lt;p&gt;As Hemanth mentioned in the other answer, you can use &lt;a href=&quot;http://www-k3.ijs.si/kokalj/pwgui/download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;PWgui&lt;/a&gt;. PWgui let you create the input files and subsequently you can run calculations using the input files as long as you know the path of the executables. If you want an intelligent input builder which will automatically fill the suggested values, you can try &lt;a href=&quot;https://www.materialscloud.org/work/tools/qeinputgenerator&quot; rel=&quot;nofollow noreferrer&quot;&gt;QE input generator&lt;/a&gt;. You can also use &lt;a href=&quot;http://www.xcrysden.org/Download.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;XCrysDen&lt;/a&gt; to visualize your input/output file structure but it is not a GUI of QE. It's more like a structure visualizer. To use XCrySDen with QE:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;xcrysden --pwi your_input_file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;or&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;xcrysden --pwo your_output_file&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-16T11:35:15.350" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12574" PostTypeId="1" AcceptedAnswerId="12577" CreationDate="2024-03-16T13:27:59.150" Score="9" ViewCount="2393" Body="&lt;p&gt;I have this very simple function:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;function calculateElectrostaticForce(distance) {            &#xA;        const charge1 = 1.602176634e-19; // Elementary charge in coulombs (C)&#xA;        const charge2 = 1.602176634e-19; // Elementary charge in coulombs (C)&#xA;&#xA;        // Calculate the electrostatic force based on Coulomb's law&#xA;        const vacuumPermittivity = 8.854e-12;&#xA;        const electrostatic_force = (charge1 * charge2) / (4 * Math.PI * vacuumPermittivity * Math.pow(distance, 2));&#xA;&#xA;        return electrostatic_force;&#xA;}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;And lets say I use it to calculate force between proton and electron at 1.3 angstroms distance (1.3 / 10000000000 in meters). That would give me 1.3651267795407353e-8 Newtons. If divide that with, for example, the mass of Hydrogen atom to get acceleration, its 8110823001207866000 m/s^2 what is a very extreme number for atomic interactions. It rises the question, if Columb's law can be useful at such small/atomic scales?&lt;/p&gt;&#xA;" OwnerUserId="3451" LastEditorUserId="5" LastEditDate="2024-03-16T15:54:43.780" LastActivityDate="2024-03-18T08:55:16.117" Title="Acceleration of 8110823001207866000 m/s^2 by using Coulomb's law: did I do it right?" Tags="|quantum-mechanics|relativistic|electrostatic|soft-question|atomic-physics|" AnswerCount="2" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12575" PostTypeId="2" ParentId="12574" CreationDate="2024-03-16T15:25:53.460" Score="7" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;It rises the question, if Columb's law can be useful at such small/atomic scales?&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Coulomb's law still plays a role in the Hamiltonian of an atom, but your discussion of &amp;quot;force&amp;quot; and &amp;quot;acceleration&amp;quot; along with your use of F = ma, is only valid for &lt;strong&gt;macroscopic objects&lt;/strong&gt; that are moving &lt;strong&gt;much more slowly than the speed of light&lt;/strong&gt; (i.e. classical physics). Correctly describing an electron interacting with a proton requires both quantum mechanics and special relativity (and more if you would like your numbers to be so accurate that they would also correctly account for the effects of gravity, but not even the most knowledgeable researchers in the world will be incorporating the effects of gravity for such quantum mechanical systems).&lt;/p&gt;&#xA;&lt;p&gt;There is a lot of information about the hydrogen atom available &lt;a href=&quot;https://en.wikipedia.org/wiki/Hydrogen_atom&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, including the &amp;quot;Hamiltonian&amp;quot; that I mentioned in the opening sentence of this answer (see the &lt;a href=&quot;https://en.wikipedia.org/wiki/Hydrogen_atom#Schr%C3%B6dinger_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;section about the Schroedinger equation&lt;/a&gt; and search for the word &amp;quot;Hamiltonian&amp;quot;) and you will see:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;-\frac{\hbar^2}{2\mu}\nabla^2  - \frac{e^2}{4\pi \epsilon_0 r}. &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can see that the formula that you used (except for the exponent of &lt;span class=&quot;math-container&quot;&gt;$r$&lt;/span&gt;, since the Hamiltonian uses the &amp;quot;potential&amp;quot; rather than the &amp;quot;force&amp;quot;), is used in this Hamiltonian. However, if we want to know the acceleration, we do not just divide this by a mass. In quantum mechanics, we cannot predict the &amp;quot;acceleration&amp;quot; at any given time, only the &amp;quot;expectation value&amp;quot; of the acceleration, &lt;span class=&quot;math-container&quot;&gt;$\langle \hat{a} \rangle$&lt;/span&gt;, which tells you what the acceleration would be &lt;em&gt;&lt;strong&gt;on average&lt;/strong&gt;&lt;/em&gt; if you were measure the acceleration multiple times (in the theory of quantum mechanics, it is predicted that the acceleration won't be the same every time that you measure it). Finally, in this case, the electron is moving at close enough to the speed of light, that I would not trust the expectation value of the acceleration, that is obtained from the above-mentioned Schroedinger equation, and this problem is improved by incorporating the effects of special relativity using the &lt;a href=&quot;https://en.wikipedia.org/wiki/Dirac_equation&quot; rel=&quot;nofollow noreferrer&quot;&gt;Dirac equation&lt;/a&gt;. If you want to know where the &amp;quot;Coulomb formula&amp;quot; appears in the Dirac equation, it might be better for you to ask that in a separate question.&lt;/p&gt;&#xA;&lt;p&gt;Another point that I will make, is that dividing by the mass of the hydrogen atom, would probably not even be considered the correct way to get the acceleration in classical (non-quantum-mechanical, and non-relativistic) physics. The hydrogen atom is the entire system, whereas the force that you calculated is between the proton and electron &lt;strong&gt;inside&lt;/strong&gt; that system. The hydrogen atom itself is stationary, but the electron and proton will move &lt;strong&gt;relative to each other&lt;/strong&gt;, so if you want the acceleration of the electron you can divide by the mass of the electron, or if you want the acceleration of the proton you can divide by the mass of the proton, or if want the acceleration of the relative motion you can divide by the &lt;strong&gt;reduced mass&lt;/strong&gt; of the system.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-03-18T02:23:34.140" LastActivityDate="2024-03-18T02:23:34.140" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12576" PostTypeId="1" AcceptedAnswerId="12578" CreationDate="2024-03-16T18:57:05.657" Score="4" ViewCount="83" Body="&lt;p&gt;I am performing calculations on a Nitrogen atom using CFOUR. A nitrogen atom has a point group of Dinfh, but ⁠CFOUR uses a lower symmetry of D2h instead. So, looking at the available Irreducible representations for D2h, we see that there are 8 Irreps, and the occupations for each of those Irreps are set in the input file as &lt;code&gt;OCCUPATION=2-1-1-0-1-0-0-0/2-0-0-0-0-0-0-0&lt;/code&gt; because we are using an unrestricted initial guess.&lt;/p&gt;&#xA;&lt;p&gt;From the CFOUR manual, I understood that these numbers specify the number of occupied orbitals of each symmetry type. Now, looking at the irreducible representations for D2h, we see that there are 8 irreps and the ordering of the atomic orbitals must be Ag, B3u, B2u and B1u for the first four orbitals.&lt;/p&gt;&#xA;&lt;p&gt;For the remaining ones I would guess that the ordering is B3g, B2g, B1g, Ag (since they must be the d-type orbitals). However, I am not sure if my reasoning is correct. Any pointers would be much appreciated.&lt;/p&gt;&#xA;&lt;p&gt;Before asking this, I have referred to &lt;a href=&quot;https://chemistry.stackexchange.com/q/91346/27342&quot;&gt;this question&lt;/a&gt; from Chem.SE, and there is a table there that I found helpful.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2024-03-16T19:37:23.690" LastActivityDate="2024-03-16T19:44:54.767" Title="When orbitals are labeled based on their irreps in D2h, how are the orbitals ordered for an N atom?" Tags="|ab-initio-calculations|symmetry|orbitals|cfour|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12577" PostTypeId="2" ParentId="12574" CreationDate="2024-03-16T18:59:45.600" Score="8" Body="&lt;p&gt;The other answer correctly pointed out that using &lt;span class=&quot;math-container&quot;&gt;$F=ma$&lt;/span&gt; and the mass of the hydrogen atom does not give the exact &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, and even if one uses the correct relativistic formulas and the correct mass, one gets the expectation value of &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; itself. However, the OP's procedure should still lead to a correct order-of-magnitude estimate of the expectation value of &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt;, and I believe it is a meaningful question to ask why the expectation value of &lt;span class=&quot;math-container&quot;&gt;$a$&lt;/span&gt; seems so large.&lt;/p&gt;&#xA;&lt;p&gt;Firstly, as for the qualitative correctness of OP's procedure: the average velocity of the electron in a ground-state hydrogenic atom with nuclear charge &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; is on the order of &lt;span class=&quot;math-container&quot;&gt;$Z\alpha c$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$\alpha$&lt;/span&gt; is the fine structure constant and &lt;span class=&quot;math-container&quot;&gt;$c$&lt;/span&gt; is the speed of light. Plugging in &lt;span class=&quot;math-container&quot;&gt;$Z$&lt;/span&gt; yields an order-of-magnitude estimate of &lt;span class=&quot;math-container&quot;&gt;$0.01c$&lt;/span&gt;. Therefore, the relativistic corrections to the ground state hydrogen atom wavefunction is on the order of &lt;span class=&quot;math-container&quot;&gt;$0.0001$&lt;/span&gt;. The relativistic corrections to the proton is much smaller due to the high mass of the proton, which gives the proton a much smaller velocity. Moreover, although using the mass of the hydrogen atom is not the correct procedure for calculating the acceleration of the hydrogen atom (which is 0 without external forces), using the mass of the proton gives the correct (expectation value of) acceleration of the proton, and the masses of the hydrogen atom and the proton are very similar. Therefore, one can make the OP's question rigorous by asking instead why the &lt;strong&gt;order of magnitude&lt;/strong&gt; of the &lt;strong&gt;expectation value&lt;/strong&gt; of the acceleration is so large. I believe this is what the OP really wants to ask.&lt;/p&gt;&#xA;&lt;p&gt;Secondly, as for why the large acceleration should not be a surprise: atomic movements happen on extremely short timescales (a few tens of femtoseconds, i.e. &lt;span class=&quot;math-container&quot;&gt;$10^{-14}$&lt;/span&gt; s), and under the SI units the timescales are even &amp;quot;smaller&amp;quot; in number than the length scales (&lt;span class=&quot;math-container&quot;&gt;$10^{-10}$&lt;/span&gt; m). Since the acceleration has a unit of &lt;span class=&quot;math-container&quot;&gt;$m/s^2$&lt;/span&gt;, we should expect that the acceleration is on the order of &lt;span class=&quot;math-container&quot;&gt;$10^{18} m/s^2$&lt;/span&gt;, in qualitative agreement with the OP's value. The crucial thing to note is that atoms are much, much more resistant to huge accelerations that would tear us humans apart (humans find it difficult to withstand &lt;span class=&quot;math-container&quot;&gt;$20g \approx 200 m/s^2$&lt;/span&gt; already). The extremely short timescales on which atomic movements occur, as well as the fact that the acceleration scales as the inverse square of time, both contribute to the surprisingly large acceleration felt by atomistic particles.&lt;/p&gt;&#xA;" OwnerUserId="838" LastEditorUserId="838" LastEditDate="2024-03-18T08:55:16.117" LastActivityDate="2024-03-18T08:55:16.117" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12578" PostTypeId="2" ParentId="12576" CreationDate="2024-03-16T19:31:10.883" Score="3" Body="&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Nitrogen atom has a point group of Dinfh, but ⁠CFOUR uses a lower symmetry of D2h instead&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;The point group of the N atom (or any atom) is &lt;span class=&quot;math-container&quot;&gt;$K_h$&lt;/span&gt;, not &lt;span class=&quot;math-container&quot;&gt;$D_{\infty_h}$&lt;/span&gt;, the latter would be correct for homonuclear diatomic molecules. When we say &amp;quot;the point group&amp;quot;, we usually mean &amp;quot;the point group with the largest number of elements&amp;quot; (this is explained in more words in &lt;a href=&quot;https://github.com/HPQC-LABS/ZMC/blob/main/PossibleGroupsForMolecules.pdf&quot; rel=&quot;nofollow noreferrer&quot;&gt;this manuscript (PDF)&lt;/a&gt; of mine).&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Now looking at the Irreducible representations for D2h, we see that there are 8 Irreps&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This is correct, based on the table that you mentioned. There is a row for each irrep and there's 8 rows in the table.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;and the ordering of the atomic orbitals must be Ag, B3u, B2u and B1u for the first four orbitals.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I'm not sure if everyone would agree that they &amp;quot;must&amp;quot; be in that order, but s-orbitals are usually associated with &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt; in &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt;, and we can see in the above-mentioned table in the &amp;quot;linear functions, rotations&amp;quot; column, that &lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt; correspond to &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$z$&lt;/span&gt; respectively, so we can associate these with the &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals respectively. Since grade 11 (in the Ontario curriculum at least), we do consider the &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;, and &lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals to be the first four. However, again with high-school-level logic, the &lt;span class=&quot;math-container&quot;&gt;$2s$&lt;/span&gt; orbital would come before any &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; orbital, so the first four orbitals might be labeled in the following way: &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;, and any two of &lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;, &lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;For the remaining ones I would guess that the ordering is B3g, B2g, B1g, Ag (since they must be the d-type orbitals). However, I am not sure if my reasoning is correct.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;If you want to order the orbitals from lowest to highest energy, I think it would be helpful for you to ask a separate question in which you provide an output file (which contains the input file) so that we can see your basis set and the orbital energies. Based on the high-school-level logic in my previous paragraph here, one might even say that &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt; would appear again before &lt;span class=&quot;math-container&quot;&gt;$B_{3g}$&lt;/span&gt; because the &lt;span class=&quot;math-container&quot;&gt;$3s$&lt;/span&gt; orbital comes before any of the &lt;span class=&quot;math-container&quot;&gt;$d$&lt;/span&gt;-orbitals, but if you have a tiny basis set, maybe you don't even have a 3s orbital available in it (and technically you can make a basis set which has d-orbitals but no p-orbitals)!&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="5" LastEditDate="2024-03-16T19:44:54.767" LastActivityDate="2024-03-16T19:44:54.767" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12579" PostTypeId="1" CreationDate="2024-03-17T01:05:12.627" Score="5" ViewCount="170" Body="&lt;p&gt;In a one-electron system such as the H atom, we are able to say that the orbitals are valid wavefunctions. But for complex systems with N-electrons, I have heard people say that they are just mathematical tools to help us build the wavefunction.&lt;/p&gt;&#xA;&lt;p&gt;Thus, I am asking whether this complexity is a result of the electron-electron interaction in the N-electron system?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2024-03-17T02:26:14.487" LastActivityDate="2024-03-17T05:44:56.803" Title="Is the electron-electron interaction to blame, for the added complexity of using &quot;orbitals&quot; for an N-electron system?" Tags="|mathematical-modeling|quantum-mechanics|orbitals|electron-correlation|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12580" PostTypeId="2" ParentId="12579" CreationDate="2024-03-17T01:44:18.897" Score="5" Body="&lt;h1&gt;Interpreting the question&lt;/h1&gt;&#xA;&lt;p&gt;For a 1-electron system, wavefunctions and orbitals are the same thing. For a 2-electron system, or any N-electron system with N&amp;gt;1, we can use &amp;quot;orbitals&amp;quot; to build the wavefunction, which you described as an &amp;quot;added complexity&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;The added &amp;quot;complexity&amp;quot; of using &amp;quot;orbitals&amp;quot; to build a wavefunction is introduced because we cannot analytically solve the Schroedinger equation for 2-electron systems. Your question therefore seems to implicitly be: &lt;strong&gt;Is the reason why we can't solve the SE analytically for 2-electron systems, because of the electron-electron interaction?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;h1&gt;Two interesting cases&lt;/h1&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&lt;p&gt;The Hartree-Fock approximate solution to a 2-electron Schroedinger equation is basically the solution that ignores electron-electron correlation, and yet we still use orbitals to build the wavefunction. Therefore the extra &amp;quot;complexity&amp;quot; is still there when we ignore electron-electron correlation. However, electron-electron correlation is more complex than just any electron-electron interaction, so perhaps you wonder, if we were to remove all electron-electron interactions, we wouldn't need to use orbitals anymore.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&lt;p&gt;Let's look at another very simple system for which the Schroedinger equation cannot be solved analytically: &lt;span class=&quot;math-container&quot;&gt;$\ce{H2+}$&lt;/span&gt;. This is a &lt;strong&gt;1-electron system&lt;/strong&gt;, so the &lt;strong&gt;&amp;quot;electron-electron interaction&amp;quot; is &lt;em&gt;zero&lt;/em&gt;&lt;/strong&gt;, and yet we still cannot solve the Schroedinger equation analytically. However, despite needing to solve the Schroedinger equation for this 1-electron system using approximations, the added &amp;quot;complexity&amp;quot; of building a wavefunctions from orbitals is probably not appropriate because the system only has one electron anyway! Here I suppose the exact wavefunctions can be called &amp;quot;molecular orbitals&amp;quot; with a meaning different from the LCAO definition.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;h1&gt;A third case&lt;/h1&gt;&#xA;&lt;p&gt;To simplify things, let's stick to having just one nucleus and two electrons (He-like systems). The Hamiltonian would be (if you will allow me to use atomic units, which I don't usually do):&lt;/p&gt;&#xA;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;-\frac{1}{2}\nabla^2_1 - \frac{1}{2}\nabla^2_2 - \frac{2}{r_1} - \frac{2}{r_2} + \frac{1}{r_{12}}.&#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The electron-electron interaction is the &lt;span class=&quot;math-container&quot;&gt;$\frac{1}{r_{12}}$&lt;/span&gt; term. Can we solve the Schroedinger equation exactly, without using orbitals, if we remove that term? Let's see:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\tag{1}&#xA;-\frac{1}{2}\nabla^2_1 - \frac{1}{2}\nabla^2_2 - \frac{2}{r_1} - \frac{2}{r_2}, &#xA;$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This looks like it can be solved using separation of variables, but it's actually the same as the H2+ Hamiltonian but with &lt;strong&gt;one more kinetic energy term&lt;/strong&gt;, making the solution even more complicated than what we'd get for H2+.&lt;/p&gt;&#xA;&lt;p&gt;The electron-electron interaction term seems to be blamed &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Book%3A_Quantum_States_of_Atoms_and_Molecules_(Zielinksi_et_al)/09%3A_The_Electronic_States_of_the_Multielectron_Atoms/9.01%3A_The_Schrodinger_Equation_For_Multi-Electron_Atoms&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; (although without justification/explanation):&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;Unfortunately, the Coulomb repulsion terms make it impossible to find&#xA;an exact solution to the Schrödinger equation for many-electron atoms&#xA;and molecules even if there are only two electrons.&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;Also &lt;a href=&quot;https://en.wikipedia.org/wiki/Dihydrogen_cation&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, it credits the lack of the electron-electron repulsion term for being able to obtain an eigenvalue (not necessarily eigenfunction) of the H2+ Schroedinger equation:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The energy E is the eigenvalue of the Schrödinger equation for the single electron. The equation can be solved in a relatively straightforward way due to the lack of electron–electron repulsion (electron correlation).&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;But then it goes on to say in the next sentence that the wavefunction would still be quite complicated:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;&amp;quot;The wave equation (a partial differential equation) separates into two coupled ordinary differential equations when using prolate spheroidal coordinates instead of cartesian coordinates. The analytical solution of the equation, the wave function, is therefore proportional to a product of two infinite power series.[7]&amp;quot;&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;I suppose if you're okay with just having that product of two infinite power series (and numerically evaluating them on your computer) as your wavefunction, then you don't need to use approximate ansatze, but if you want something simpler, then the added complexity of using an anstaz would be valuable.&lt;/p&gt;&#xA;" OwnerUserId="5" LastEditorUserId="1554" LastEditDate="2024-03-17T05:44:56.803" LastActivityDate="2024-03-17T05:44:56.803" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12581" PostTypeId="1" CreationDate="2024-03-17T08:56:21.687" Score="2" ViewCount="37" Body="&lt;p&gt;Can you kindly help me understand the following type of error I get while calculating scf for bands?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;The error is %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&#xA;     Error in routine  card_atomic_species (5010):&#xA;     cannot read atomic specie from: ATOMIC_POSITIONS {crystal}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="9966" LastEditorUserId="6055" LastEditDate="2024-03-17T09:28:14.600" LastActivityDate="2024-03-17T09:28:14.600" Title="Error in Quantum Espresso: cannot read atomic specie from: ATOMIC_POSITIONS {crystal}" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12582" PostTypeId="1" AcceptedAnswerId="12587" CreationDate="2024-03-17T11:58:33.033" Score="6" ViewCount="197" Body="&lt;p&gt;I have a concern related to the follwoing question &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12576/1554&quot;&gt;When orbitals are labeled based on their irreps in D2h, how are the orbitals ordered for an N atom?&lt;/a&gt; In which the following &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12578/1554&quot;&gt;Answer&lt;/a&gt; clearly states that any single atom would have a &lt;span class=&quot;math-container&quot;&gt;$K_h$&lt;/span&gt; point group symmetry, which I believe means the single atom is a spherical system. However, the question was referring to the single atom (N atom in that case) to belong to &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; or &lt;span class=&quot;math-container&quot;&gt;$D_{\infty_h}$&lt;/span&gt; point groups. What is the convention behind this treatment?&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2024-03-17T18:30:51.520" LastActivityDate="2024-03-17T18:30:51.520" Title="For one atom, what is the correct point group?" Tags="|mathematical-modeling|symmetry|atomic-physics|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12583" PostTypeId="1" AcceptedAnswerId="12584" CreationDate="2024-03-17T11:58:42.770" Score="6" ViewCount="179" Body="&lt;p&gt;I find the short form of the vasp tag are hard to remember. Is there a dictionary what these short form are stand for. For example &lt;code&gt;USA&lt;/code&gt; stand for &lt;code&gt;United States of America&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Here is the sample VASP tags, how should one remember or familiar with their meaning?&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;NSW    = 5 ! 5 ionic steps&#xA;IBRION = 2 ! use the conjugate-gradient algorithm&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Is there a dictionary to tell people what are these capital letters stands for?&lt;/p&gt;&#xA;" OwnerUserId="6353" LastEditorUserId="6055" LastEditDate="2024-03-17T17:59:44.010" LastActivityDate="2024-03-17T17:59:44.010" Title="Is there a dictionary for VASP tags to know what they stand for?" Tags="|vasp|software|soft-question|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12584" PostTypeId="2" ParentId="12583" CreationDate="2024-03-17T12:12:28.777" Score="7" Body="&lt;p&gt;I think what you are looking for is the &lt;a href=&quot;https://www.vasp.at/wiki/index.php/The_VASP_Manual&quot; rel=&quot;noreferrer&quot;&gt;VASP wiki&lt;/a&gt;. So there are several ways you can approach.&lt;/p&gt;&#xA;&lt;p&gt;First of all, you can search about the tags in the VASP wiki and it will open the wiki page associated with that tag.&lt;/p&gt;&#xA;&lt;p&gt;Alternatively, you can look for your tag in this page: &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Category:INCAR_tag&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/Category:INCAR_tag&lt;/a&gt;. It contains all the tags used in &lt;code&gt;INCAR&lt;/code&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Lastly, you can also use the direct link. For example, if you are looking for the tag &lt;code&gt;TAG&lt;/code&gt;, you would use: &lt;code&gt;https://www.vasp.at/wiki/index.php/TAG&lt;/code&gt;. So, for &lt;code&gt;NSW&lt;/code&gt;, you would use &lt;a href=&quot;https://www.vasp.at/wiki/index.php/NSW&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/NSW&lt;/a&gt; or for &lt;code&gt;IBRION&lt;/code&gt;, you would use &lt;a href=&quot;https://www.vasp.at/wiki/index.php/IBRION&quot; rel=&quot;noreferrer&quot;&gt;https://www.vasp.at/wiki/index.php/IBRION&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-17T12:12:28.777" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12585" PostTypeId="1" CreationDate="2024-03-17T12:26:07.343" Score="4" ViewCount="56" Body="&lt;p&gt;I am observing discrepancies in the phonon dispersion results obtained using the Density Functional Perturbation Theory (DFPT) method implemented in Phonopy. Specifically, when I use the same INCAR settings, I obtain correct phonon dispersion results for a 4x4x1 supercell. However, when I use 1x1x1 or 3x3x1 supercells, I encounter negative frequencies. What could be causing this inconsistency in the results, and how can I address it?:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/w5sRU.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/w5sRU.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="24" LastEditDate="2024-03-18T13:19:34.303" LastActivityDate="2024-03-19T16:14:50.827" Title="Inconsistencies in Phonon Dispersion Results Using Phonopy DFPT with Different Supercell Sizes" Tags="|vasp|phonopy|phonon-dispersion|dfpt|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12586" PostTypeId="1" CreationDate="2024-03-17T12:50:17.777" Score="4" ViewCount="40" Body="&lt;p&gt;I am using GROMACS to run molecular dynamics simulations of pure liquids, in the NpT ensemble at room temperature and p = 1 atm. My first test was with isopropanol (also known as 2-propanol). I used about 500 molecules in a cubic box with size equal to 4 nm. I adopted the OPLS force-field, and my topology file was generated using LigParGen server. However, I am having problems with some results of my simulations. It thermalizes and describe well the liquid density and molar volume, however it predicts a Heat capacity &lt;span class=&quot;math-container&quot;&gt;$C_{p}$&lt;/span&gt; greater than two times the experimental value. The isothermal compressibility is very wrong also. I don't know Where am I going wrong, does anyone have any idea what it could be?&lt;/p&gt;&#xA;" OwnerUserId="6572" LastActivityDate="2024-03-17T12:50:17.777" Title="MD simulations of liquid isopropanol predicts wrong thermodynamics proprieties" Tags="|molecular-dynamics|thermodynamics|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12587" PostTypeId="2" ParentId="12582" CreationDate="2024-03-17T12:58:15.487" Score="7" Body="&lt;p&gt;When choosing the point group, a system with a single nucleus (e.g. a single atom) is considered to be spherically symmetric, so its point group is &lt;span class=&quot;math-container&quot;&gt;$K_h$&lt;/span&gt; in &lt;a href=&quot;https://en.wikipedia.org/wiki/Schoenflies_notation&quot; rel=&quot;noreferrer&quot;&gt;Schoenflies notation&lt;/a&gt;, in which K stands for the German word Kugel (meaning &amp;quot;ball&amp;quot; or &amp;quot;sphere&amp;quot;).&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt; are sub-groups of &lt;span class=&quot;math-container&quot;&gt;$K_h$&lt;/span&gt;, so they are also valid point groups that can be used to describe the symmetry operations that can be applied to an atom. Most quantum chemistry software packages such as &lt;a href=&quot;/questions/tagged/cfour&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-cfour-tooltip-container&quot;&gt;cfour&lt;/a&gt;, which is the one that was discussed in the question to which you provided a link, do not contain enough code to fully treat non-Abelian groups such as &lt;span class=&quot;math-container&quot;&gt;$D_{\infty h}$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$K_h$&lt;/span&gt;, so they use the largest possible Abelian subgroup, which would be &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; if the system is a single atom.&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-03-17T12:58:15.487" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12588" PostTypeId="1" CreationDate="2024-03-17T16:28:58.413" Score="3" ViewCount="72" Body="&lt;p&gt;I want to optimise a system containing few amino acid residues (residues in active site of an enzyme) with a metal ion, in order to show a proposed mechanism is correct for the enzyme inhibition. For that, I planed to compare the optimised energies of the reactants and products. Can I do that using Quantum ESPRESSO (QE) software? Then how to generate the input files to run QE. I watched a video that shows to use Materials Project in generating CIF file. But, that is not clear to use for large systems like in my work. Can you please help me with this?&#xA;&lt;strong&gt;Here I have attached the input file (only the active site residues that form interactions with the metal ion from a MD simulated system) in .pdb format&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;MODEL        1&#xA;ATOM      1  N   GLN   144      13.007  32.431  11.858  1.00  0.00&#xA;ATOM      2  HN  GLN   144      12.155  32.378  12.373  1.00  0.00&#xA;ATOM      3  CA  GLN   144      14.022  33.185  12.491  1.00  0.00&#xA;ATOM      4  HA  GLN   144      14.765  33.580  11.814  1.00  0.00&#xA;ATOM      5  CB  GLN   144      13.296  34.366  13.237  1.00  0.00&#xA;ATOM      6  HB1 GLN   144      12.555  34.112  14.025  1.00  0.00&#xA;ATOM      7  HB2 GLN   144      12.779  34.901  12.412  1.00  0.00&#xA;ATOM      8  CG  GLN   144      14.348  35.460  13.782  1.00  0.00&#xA;ATOM      9  HG1 GLN   144      14.988  34.993  14.561  1.00  0.00&#xA;ATOM     10  HG2 GLN   144      15.064  35.697  12.966  1.00  0.00&#xA;ATOM     11  CD  GLN   144      13.688  36.628  14.374  1.00  0.00&#xA;ATOM     12  OE1 GLN   144      13.963  36.848  15.563  1.00  0.00&#xA;ATOM     13  NE2 GLN   144      13.024  37.486  13.561  1.00  0.00&#xA;ATOM     14 1HE2 GLN   144      13.013  37.259  12.587  1.00  0.00&#xA;ATOM     15 2HE2 GLN   144      12.754  38.420  13.794  1.00  0.00&#xA;ATOM     16  C   GLN   144      15.045  32.406  13.423  1.00  0.00&#xA;ATOM     17  O   GLN   144      16.001  31.769  12.956  1.00  0.00&#xA;ATOM     18  N   ASP   145      14.883  32.459  14.746  1.00  0.00&#xA;ATOM     19  HN  ASP   145      14.124  32.860  15.253  1.00  0.00&#xA;ATOM     20  CA  ASP   145      15.692  31.729  15.679  1.00  0.00&#xA;ATOM     21  HA  ASP   145      16.470  31.183  15.167  1.00  0.00&#xA;ATOM     22  CB  ASP   145      16.415  32.740  16.620  1.00  0.00&#xA;ATOM     23  HB1 ASP   145      17.285  33.250  16.152  1.00  0.00&#xA;ATOM     24  HB2 ASP   145      16.844  32.184  17.481  1.00  0.00&#xA;ATOM     25  CG  ASP   145      15.597  33.888  17.227  1.00  0.00&#xA;ATOM     26  OD1 ASP   145      16.119  34.621  18.043  1.00  0.00&#xA;ATOM     27  OD2 ASP   145      14.448  34.254  16.806  1.00  0.00&#xA;ATOM     28  C   ASP   145      14.769  30.797  16.469  1.00  0.00&#xA;ATOM     29  O   ASP   145      13.622  31.142  16.664  1.00  0.00&#xA;ATOM     30  N   PRO   146      15.242  29.617  16.825  1.00  0.00&#xA;ATOM     31  CD  PRO   146      16.479  28.962  16.298  1.00  0.00&#xA;ATOM     32  HD1 PRO   146      16.466  29.047  15.191  1.00  0.00&#xA;ATOM     33  HD2 PRO   146      17.400  29.372  16.767  1.00  0.00&#xA;ATOM     34  CA  PRO   146      14.471  28.727  17.690  1.00  0.00&#xA;ATOM     35  HA  PRO   146      13.628  28.361  17.122  1.00  0.00&#xA;ATOM     36  CB  PRO   146      15.532  27.605  17.985  1.00  0.00&#xA;ATOM     37  HB1 PRO   146      15.135  26.620  18.312  1.00  0.00&#xA;ATOM     38  HB2 PRO   146      16.166  28.096  18.754  1.00  0.00&#xA;ATOM     39  CG  PRO   146      16.330  27.494  16.705  1.00  0.00&#xA;ATOM     40  HG1 PRO   146      17.271  26.905  16.688  1.00  0.00&#xA;ATOM     41  HG2 PRO   146      15.755  26.962  15.917  1.00  0.00&#xA;ATOM     42  C   PRO   146      13.879  29.220  19.040  1.00  0.00&#xA;ATOM     43  O   PRO   146      14.319  30.251  19.573  1.00  0.00&#xA;ATOM     44 PB2P PB2   305      14.747  36.610  17.945  1.00  0.00&#xA;TER      45      PB2   305 &#xA;ENDMDL&#xA;END   &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6239" LastEditorUserId="6239" LastEditDate="2024-03-19T04:04:56.447" LastActivityDate="2024-03-19T16:47:40.700" Title="How to generate Quantum ESPRESSO input file for a system containing amino acid residues and a metal ion?" Tags="|quantum-espresso|crystallographic-information-file|" AnswerCount="1" CommentCount="7" ContentLicense="CC BY-SA 4.0" />
  <row Id="12589" PostTypeId="1" AcceptedAnswerId="12590" CreationDate="2024-03-18T00:46:40.313" Score="6" ViewCount="194" Body="&lt;p&gt;I am doing some calculations on single oxygen atom (O) using CFOUR. According to a previous &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12587/1554&quot;&gt;answer&lt;/a&gt; to this &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12582/1554&quot;&gt;question&lt;/a&gt; and according to how CFOUR treats non-Abelian groups, I am considering the (O) atom to belong to the &lt;span class=&quot;math-container&quot;&gt;$D_{2h}$&lt;/span&gt; point group. In the ZMAT input file, I should provide the OCCUPATION tag, according to the &lt;a href=&quot;https://cfour.uni-mainz.de/cfour/index.php?n=Main.ListOfKeywordsInAlphabeticalOrder&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation&lt;/a&gt;, this tag the stands for the number of occupied orbitals of each symmetry type.&lt;/p&gt;&#xA;&lt;p&gt;For the (O) atom,  which has an electron configuration of &lt;span class=&quot;math-container&quot;&gt;$1s^22s^22p^4$&lt;/span&gt; and according to the character table found in this &lt;a href=&quot;https://chemistry.stackexchange.com/a/91350/50844&quot;&gt;answer&lt;/a&gt; I am assigning the following values &lt;code&gt;OCCUPATION=2-1-1-1-0-0-0-0/2-1-0-0-0-0-0-0&lt;/code&gt;. Based on what I understood the first four irreducible representations should correspond to &lt;span class=&quot;math-container&quot;&gt;$A_g$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$B_{3u}$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$B_{2u}$&lt;/span&gt;,and &lt;span class=&quot;math-container&quot;&gt;$B_{1u}$&lt;/span&gt; in the order of &lt;span class=&quot;math-container&quot;&gt;$s$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$p_y$&lt;/span&gt;,&lt;span class=&quot;math-container&quot;&gt;$p_z$&lt;/span&gt; orbitals, I have added (1) in the &lt;span class=&quot;math-container&quot;&gt;$\beta$&lt;/span&gt; sets of orbitals since &lt;span class=&quot;math-container&quot;&gt;$p_x$&lt;/span&gt; is holding 2 electrons with spin up and spin down. However, I have doubts in my understanding, any guidence would be appreciated.&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="5" LastEditDate="2024-03-18T02:01:58.987" LastActivityDate="2024-03-18T02:09:42.647" Title="What is the correct way to set up occupation for single atom in CFOUR software?" Tags="|ab-initio-calculations|symmetry|orbitals|cfour|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12590" PostTypeId="2" ParentId="12589" CreationDate="2024-03-18T02:09:42.647" Score="5" Body="&lt;p&gt;Your setting is incorrect for the dominant Slater determinant when calculating the electronic ground state of an O atom:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCCUPATION=2-1-1-1-0-0-0-0/2-1-0-0-0-0-0-0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Notice that for the N atom, as described here: &lt;a href=&quot;https://mattermodeling.stackexchange.com/q/12576/5&quot;&gt;When orbitals are labeled based on their irreps in D2h, how are the orbitals ordered for an N atom?&lt;/a&gt;, we had:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCCUPATION=2-1-1-0-1-0-0-0/2-0-0-0-0-0-0-0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the hint that the D2h irreps in &lt;a href=&quot;/questions/tagged/cfour&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-cfour-tooltip-container&quot;&gt;cfour&lt;/a&gt; correspond to the following orbitals:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCCUPATION=s-p-p-0-p-0-0-0/s-0-0-0-0-0-0-0 &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For the element O, you have correctly added one beta electron in a p-orbital, but you have put one of the alpha p-electrons in a different irrep.&lt;/p&gt;&#xA;&lt;p&gt;A correct setting for an O atom, would be the following:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;OCCUPATION=2-1-1-0-1-0-0-0/2-1-0-0-0-0-0-0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-03-18T02:09:42.647" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12591" PostTypeId="1" CreationDate="2024-03-18T03:28:47.623" Score="6" ViewCount="47" Body="&lt;p&gt;We know that critical phenomena plays an important role to study phase transition for solid state systems. But it seems that the critical phenomena is always associated with infinite systems (e.g. crystal structure). The question is that is critical phenomena feasible for molecular systems that have finite number of atoms?&lt;/p&gt;&#xA;" OwnerUserId="141" LastActivityDate="2024-03-18T17:02:14.000" Title="Is critical phenomena feasible for finite molecular systems?" Tags="|phase-transitions|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12592" PostTypeId="1" CreationDate="2024-03-18T06:57:25.890" Score="4" ViewCount="114" Body="&lt;p&gt;I want to calculate scf for bands calculation. Before I can proceed, I face an error of convergence:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;End of self-consistent calculation&#xA;&#xA;convergence NOT achieved after  80 iterations: stopping&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Kindly,help me fix this.&lt;/p&gt;&#xA;" OwnerUserId="9966" LastEditorUserId="6055" LastEditDate="2024-03-18T09:36:48.363" LastActivityDate="2024-03-18T09:56:17.010" Title="Convergence not completed in scf for bands" Tags="|density-functional-theory|quantum-espresso|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12593" PostTypeId="2" ParentId="12592" CreationDate="2024-03-18T09:56:17.010" Score="5" Body="&lt;p&gt;This happens because you set &lt;code&gt;electron_maxstep = 80&lt;/code&gt; in the &lt;code&gt;&amp;amp;ELECTRONS&lt;/code&gt; namelits of your scf input file. The default value is &lt;code&gt;electron_maxstep = 100&lt;/code&gt;. This keyword denotes the maximum number of iterations in a single scf cycle. You can know more about this &lt;a href=&quot;https://www.quantum-espresso.org/Doc/INPUT_PW.html#idm803&quot; rel=&quot;noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;In order to fix this, you can use one of the following two strategies. Firstly, increase the parameter to &lt;code&gt;electron_maxstep = 100&lt;/code&gt;, &lt;code&gt;electron_maxstep = 200&lt;/code&gt; or even more. But please make sure that your energy is actually converging. Increasing the number of &lt;code&gt;electron_maxstep&lt;/code&gt; will only help if the energy is converging slowly. Otherwise if the accuracy is alternating rapidly, or it converges upto a certain value and diverges again, then this might not help at all. That would indicate that either you have some problematic system or your input file is problematic.&lt;/p&gt;&#xA;&lt;p&gt;To check how the accuracy changes, you can use the following command:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;grep -s 'estimated scf accuracy' scf.out &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;The second strategy is to lower the convergence thresholds. Maybe you set the convergence threshold too tight. The default convergence threshold of &lt;code&gt;conv_thr = 1.D-6&lt;/code&gt; is good enough for most purposes. Also, in case in your scf calculation, you set &lt;code&gt;tstress&lt;/code&gt; or &lt;code&gt;tprnfor&lt;/code&gt; to &lt;code&gt;.TRUE.&lt;/code&gt;, then other convergence thresholds such as &lt;code&gt;etot_conv_thr&lt;/code&gt; and &lt;code&gt;forc_conv_thr&lt;/code&gt; will also play role. Without the input file there is nothing else to say. That's why sharing your input file when asking a question is a good idea so that people who wants to help can actually help you.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-18T09:56:17.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12594" PostTypeId="2" ParentId="12591" CreationDate="2024-03-18T17:02:14.000" Score="0" Body="&lt;p&gt;Maybe? I am not that familiar with critical phenomena, but I know about lattice vibrations and I know that Jahn-Teller distortions occur in isolated molecules. See e.g. here &lt;a href=&quot;https://chem.libretexts.org/Bookshelves/Inorganic_Chemistry/Supplemental_Modules_and_Websites_(Inorganic_Chemistry)/Coordination_Chemistry/Structure_and_Nomenclature_of_Coordination_Compounds/Coordination_Numbers_and_Geometry/Jahn-Teller_Distortions#:%7E:text=The%20Jahn%2DTeller%20effect%20is,those%20of%20the%20equatorial%20bonds.&quot; rel=&quot;nofollow noreferrer&quot;&gt;example&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;I don't really know if this is a critical phenomena. It is definitely a phase transition with spontaneous symmetry breaking and the formation of a Goldstone mode (one of distortions is &amp;quot;frozen in&amp;quot;, i.e. a normal mode becomes zero-frequency). Maybe you didn't already know about this and it can help you in your search! If not, cheers anyway!&lt;/p&gt;&#xA;&lt;p&gt;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-03-18T17:02:14.000" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12595" PostTypeId="1" AcceptedAnswerId="12624" CreationDate="2024-03-18T19:28:01.247" Score="6" ViewCount="71" Body="&lt;p&gt;I have a poscar that I would like to place oxygen atoms as adsorbates in the subsurface. I have tried with Shaun's acat code but appears is not working for me. The posccar is shown below.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Co Cr Fe Ni                             &#xA;   1.00000000000000     &#xA;    10.0453568374981206    0.0000000000000000    0.0550632930546681&#xA;     5.0062629241308159    8.6637900144891251   -0.0307447571247709&#xA;     0.0000000000000000    0.0000000000000000   24.5023355004677370&#xA;   Co   Cr   Fe   Ni&#xA;    24    24    24    24&#xA;Selective dynamics&#xA;Direct&#xA;  0.7484317155209226  0.2513638356015306  0.1254815499620392   F   F   F&#xA;  0.1672130297685186  0.9185659998157476  0.0423655957612539   F   F   F&#xA;  0.0024128917846937  0.0006368693967431  0.1251177360037659   F   F   F&#xA;  0.2472404547354330  0.7516658457698711  0.1253174855948984   F   F   F&#xA;  0.4986791697954516  0.7497224974724048  0.1245421004755940   F   F   F&#xA;  0.4183102184453631  0.9175024725961123  0.0427306917694636   F   F   F&#xA;  0.5005233982563055  0.5028030766782763  0.1263255330535529   F   F   F&#xA;  0.6637932465713661  0.6648289340226086  0.0411694970457788   F   F   F&#xA;  0.4148051600809368  0.9178461495668075  0.2924207711882258   T   T   T&#xA;  0.8338796964351900  0.5852326664824119  0.2090322624279182   F   F   F&#xA;  0.6683905896051491  0.6665521531107157  0.2919494222524963   T   T   T&#xA;  0.9137322442258432  0.4184043298653013  0.2918218756892721   T   T   T&#xA;  0.1659101027875440  0.4156907554642985  0.2915074418707615   T   T   T&#xA;  0.0849768851120345  0.5841691392627766  0.2093973584361279   F   F   F&#xA;  0.1646524639893301  0.1704140811992133  0.2931265725935911   T   T   T&#xA;  0.3304599132380304  0.3314956006892800  0.2078361637124431   F   F   F&#xA;  0.0812960413834357  0.5880794902365066  0.4555792089417541   T   T   T&#xA;  0.4994197558394441  0.2490587492264744  0.3760560267155630   T   T   T&#xA;  0.3333921183195137  0.3420136469527384  0.4560217103069046   T   T   T&#xA;  0.5826752923091105  0.0857557180115605  0.4562264905890454   T   T   T&#xA;  0.8361011910506737  0.0816930595460893  0.4557185355279263   T   T   T&#xA;  0.7530492451163983  0.2473081031331254  0.3756764049814374   T   T   T&#xA;  0.8301401794437534  0.8392046371404343  0.4575945680681187   T   T   T&#xA;  0.9990613308381326  0.9979081941329535  0.3755447194682439   T   T   T&#xA;  0.9971429636928946  0.2522458351632153  0.1243171831461751   F   F   F&#xA;  0.9173969055062088  0.9243213954712743  0.0415462838229530   F   F   F&#xA;  0.2532328618483248  0.9912372851549591  0.1247613899134663   F   F   F&#xA;  0.9158846146946971  0.6649375277963188  0.0403872990614644   F   F   F&#xA;  0.0024110322067799  0.7449034237646117  0.1251928215763556   F   F   F&#xA;  0.1668800967370530  0.1660149380313101  0.0391693010992924   F   F   F&#xA;  0.4145209940205419  0.1686122327575248  0.0423935979957335   F   F   F&#xA;  0.0019224850701747  0.5002131357099415  0.1274453925201016   F   F   F&#xA;  0.6643301274840190  0.9192298301080949  0.2909060284359840   T   T   T&#xA;  0.5840635721728802  0.5909880621379457  0.2082129504896244   F   F   F&#xA;  0.9197107341637500  0.6574724555144138  0.2915108972239469   T   T   T&#xA;  0.5825512813613685  0.3316041944629831  0.2070539657281358   F   F   F&#xA;  0.6707997987754361  0.4102323661913387  0.2904763634920180   T   T   T&#xA;  0.8335467634037173  0.8326816046979744  0.2058359677659638   F   F   F&#xA;  0.0811876606872062  0.8352788994241891  0.2090602646624049   F   F   F&#xA;  0.6666631390832718  0.1697828750236400  0.2935790889719558   T   T   T&#xA;  0.3287222623539052  0.5949995619541201  0.4566661274696794   T   T   T&#xA;  0.2507297661860802  0.2452335156972610  0.3782780233787296   T   T   T&#xA;  0.5900673674316123  0.3266313292879156  0.4552826212887701   T   T   T&#xA;  0.2489382055833093  0.0011177879441811  0.3741236488020183   T   T   T&#xA;  0.3333049617800694  0.0954306189689573  0.4617211593524514   T   T   T&#xA;  0.5069854991928138  0.4944701746721915  0.3719734131547170   T   T   T&#xA;  0.7463376705174738  0.5022245251682501  0.3772195083157827   T   T   T&#xA;  0.3321672019729938  0.8487864324747707  0.4579998120019802   T   T   T&#xA;  0.9162766261883135  0.1670506690443787  0.0417170310293500   F   F   F&#xA;  0.9156348408059642  0.4208833853925711  0.0416680593854295   F   F   F&#xA;  0.6638573836196215  0.4167482971811012  0.0427373586771225   F   F   F&#xA;  0.1644966505612686  0.6696213567857683  0.0421395064179180   F   F   F&#xA;  0.4141908497179116  0.6702206541091940  0.0436478982229787   F   F   F&#xA;  0.2505031653515672  0.2514744230863357  0.1253016876192419   F   F   F&#xA;  0.6671950880963564  0.9146088546634559  0.0412477173410366   F   F   F&#xA;  0.5011301297450359  0.0015898949770516  0.1254391147214591   F   F   F&#xA;  0.5829432928549849  0.8337173357110430  0.2083836976960143   F   F   F&#xA;  0.5823015074726285  0.0875500520592425  0.2083347260521009   F   F   F&#xA;  0.3305240502862929  0.0834149638477655  0.2094040253437868   F   F   F&#xA;  0.8311633172279329  0.3362880234524397  0.2088061730845894   F   F   F&#xA;  0.0808575163845759  0.3368873207758583  0.2103145648896501   F   F   F&#xA;  0.9178620539490372  0.9181632848813880  0.2921614142707068   T   T   T&#xA;  0.3338617547630278  0.5812755213301273  0.2079143840077009   F   F   F&#xA;  0.1667427441640129  0.6691629774099748  0.2916689190446753   T   T   T&#xA;  0.2501005544956555  0.4971190651557775  0.3752504245138626   T   T   T&#xA;  0.2465450490318301  0.7513602656366625  0.3737836365295550   T   T   T&#xA;  0.9959441676473952  0.7502164470050144  0.3761722958557462   T   T   T&#xA;  0.5006832374805985 -0.0046823132578043  0.3771502923241621   T   T   T&#xA;  0.7479199814638383  0.0015639501390249  0.3769771482198781   T   T   T&#xA;  0.5907294015449800  0.5811057710859650  0.4593840788246640   T   T   T&#xA; -0.0060356496498379  0.2509365579997814  0.3746997440371634   T   T   T&#xA;  0.8337131135973636  0.3384461954663572  0.4589575960453217   T   T   T&#xA;  0.7491453254479623  0.4999420685284264  0.1253274286111932   F   F   F&#xA;  0.7525172797094726  0.9990417994750018  0.1245053594957000   F   F   F&#xA;  0.1659916469114435  0.4166267850617231  0.0419841126835294   F   F   F&#xA;  0.4164851590236438  0.4195902143823460  0.0412357760750623   F   F   F&#xA;  0.7488913776000459  0.7483211782917962  0.1243236794642684   F   F   F&#xA;  0.6650578055559109  0.1674124030264323  0.0415158212312434   F   F   F&#xA;  0.4996344114965225  0.2515395125269748  0.1247577710853136   F   F   F&#xA;  0.2510709289178692  0.4996037034576872  0.1251508454354209   F   F   F&#xA;  0.4151278078261990  0.1660138252756776  0.2929391613717844   T   T   T&#xA;  0.4191068649976099  0.6656963488165302  0.2910043222214981   T   T   T&#xA;  0.8326583135781078  0.0832934517283874  0.2086507793501937   F   F   F&#xA;  0.0831518256903081  0.0862568810490103  0.2079024427417338   F   F   F&#xA;  0.4141780161790669  0.4152819982214173  0.2911292247327950   T   T   T&#xA;  0.3317244722225823  0.8340790696931037  0.2081824878979148   F   F   F&#xA;  0.1672808087447653  0.9188007288622816  0.2911744749016252   T   T   T&#xA;  0.9184911724707188  0.1647217763839646  0.2912823563402203   T   T   T&#xA;  0.0786746230769518  0.8394704018569830  0.4571878949908471   T   T   T&#xA;  0.0812918002957800  0.3388228622899257  0.4577279953776053   T   T   T&#xA;  0.4995222746832525  0.7476613523226699  0.3754402597886074   T   T   T&#xA;  0.7504604731685881  0.7509375893853185  0.3748486140777815   T   T   T&#xA;  0.0779944725298367  0.0905558955121346  0.4570840112996290   T   T   T&#xA;  0.0010021949552336  0.4974678493264066  0.3749986037544817   T   T   T&#xA;  0.8340126184872778  0.5881395290292224  0.4574595912618843   T   T   T&#xA;  0.5875529134078941  0.8320089079782008  0.4577610944684899   T   T   T&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3442" LastEditorUserId="5" LastEditDate="2024-03-18T21:30:57.230" LastActivityDate="2024-03-22T09:39:07.287" Title="Interstitial adsorbates" Tags="|surfaces|adsorption|" AnswerCount="1" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12597" PostTypeId="2" ParentId="12588" CreationDate="2024-03-19T05:24:45.923" Score="1" Body="&lt;p&gt;You can generate an xyz file using the following code. Before running the code, you must clean the pdb file, so that all atom names start with an alphabet [A-Z].&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import  sys as  sys&#xA;&#xA;pdbFile =   sys.argv[1]&#xA;&#xA;class coordObject:&#xA;    def __init__(self, fileName: str) -&amp;gt; None:&#xA;        self.atoms  =   []&#xA;        self.coords =   []&#xA;&#xA;        with open(fileName) as fileObject:&#xA;            for line in fileObject:&#xA;                if &amp;quot;ATOM&amp;quot; in line:&#xA;                    line        =   line.split()&#xA;                    atomname    =   line[2][0]&#xA;                    atomcoords  =   [float(x) for x in line[5:8]]&#xA;                    self.atoms.append(atomname)&#xA;                    self.coords.append(atomcoords)&#xA;&#xA;def writePWInput(coords: coordObject) -&amp;gt; None:&#xA;    with open(&amp;quot;sample.xyz&amp;quot;, &amp;quot;w&amp;quot;) as xyzObject:&#xA;        xyzObject.write(&amp;quot;{}\n\n&amp;quot;.format(len(coords.atoms)))&#xA;        for atom, coord in zip(coords.atoms, coords.coords):&#xA;            xyzObject.write(&amp;quot;{:&amp;lt;10s}{:10.3f}{:10.3f}{:10.3f}\n&amp;quot;.format(atom, coord[0], coord[1], coord[2]))&#xA;&#xA;coords  =   coordObject(pdbFile)&#xA;writePWInput(coords)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is the xyz file that gets generated from the above code, and would be saved as &lt;code&gt;sample.xyz&lt;/code&gt; in the same directory.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;44&#xA;&#xA;N             13.007    32.431    11.858&#xA;H             12.155    32.378    12.373&#xA;C             14.022    33.185    12.491&#xA;H             14.765    33.580    11.814&#xA;C             13.296    34.366    13.237&#xA;H             12.555    34.112    14.025&#xA;H             12.779    34.901    12.412&#xA;C             14.348    35.460    13.782&#xA;H             14.988    34.993    14.561&#xA;H             15.064    35.697    12.966&#xA;C             13.688    36.628    14.374&#xA;O             13.963    36.848    15.563&#xA;N             13.024    37.486    13.561&#xA;H             13.013    37.259    12.587&#xA;H             12.754    38.420    13.794&#xA;C             15.045    32.406    13.423&#xA;O             16.001    31.769    12.956&#xA;N             14.883    32.459    14.746&#xA;H             14.124    32.860    15.253&#xA;C             15.692    31.729    15.679&#xA;H             16.470    31.183    15.167&#xA;C             16.415    32.740    16.620&#xA;H             17.285    33.250    16.152&#xA;H             16.844    32.184    17.481&#xA;C             15.597    33.888    17.227&#xA;O             16.119    34.621    18.043&#xA;O             14.448    34.254    16.806&#xA;C             14.769    30.797    16.469&#xA;O             13.622    31.142    16.664&#xA;N             15.242    29.617    16.825&#xA;C             16.479    28.962    16.298&#xA;H             16.466    29.047    15.191&#xA;H             17.400    29.372    16.767&#xA;C             14.471    28.727    17.690&#xA;H             13.628    28.361    17.122&#xA;C             15.532    27.605    17.985&#xA;H             15.135    26.620    18.312&#xA;H             16.166    28.096    18.754&#xA;C             16.330    27.494    16.705&#xA;H             17.271    26.905    16.688&#xA;H             15.755    26.962    15.917&#xA;C             13.879    29.220    19.040&#xA;O             14.319    30.251    19.573&#xA;P             14.747    36.610    17.945&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Once you have this file, you can open this in &lt;a href=&quot;http://www-k3.ijs.si/kokalj/pwgui/&quot; rel=&quot;nofollow noreferrer&quot;&gt;PWgui&lt;/a&gt; (which is an input generator for QE) and create the input file.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  etot_conv_thr =   4.4000000000d-04&#xA;  forc_conv_thr =   1.0000000000d-04&#xA;  outdir = './out/'&#xA;  prefix = 'aiida'&#xA;  pseudo_dir = './pseudo/'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss =   1.4699723600d-02&#xA;  ecutrho =   4.8000000000d+02&#xA;  ecutwfc =   6.0000000000d+01&#xA;  ibrav = 0&#xA;  nat = 44&#xA;  nosym = .false.&#xA;  ntyp = 5&#xA;  occupations = 'smearing'&#xA;  smearing = 'cold'&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   8.8000000000d-09&#xA;  electron_maxstep = 80&#xA;  mixing_beta =   4.0000000000d-01&#xA;/&#xA;ATOMIC_SPECIES&#xA;C      12.0107 C.pbesol-n-kjpaw_psl.1.0.0.UPF&#xA;H      1.00794 H.pbesol-rrkjus_psl.1.0.0.UPF&#xA;N      14.0067 N.pbesol-theos.UPF&#xA;O      15.9994 O.pbesol-n-kjpaw_psl.0.1.UPF&#xA;P      30.973761 P.pbesol-n-rrkjus_psl.1.0.0.UPF&#xA;ATOMIC_POSITIONS crystal&#xA;N            0.6503500000       1.6215500000       0.5929000000 &#xA;H            0.6077500000       1.6189000000       0.6186500000 &#xA;C            0.7011000000       1.6592500000       0.6245500000 &#xA;H            0.7382500000       1.6790000000       0.5907000000 &#xA;C            0.6648000000       1.7183000000       0.6618500000 &#xA;H            0.6277500000       1.7056000000       0.7012500000 &#xA;H            0.6389500000       1.7450500000       0.6206000000 &#xA;C            0.7174000000       1.7730000000       0.6891000000 &#xA;H            0.7494000000       1.7496500000       0.7280500000 &#xA;H            0.7532000000       1.7848500000       0.6483000000 &#xA;C            0.6844000000       1.8314000000       0.7187000000 &#xA;O            0.6981500000       1.8424000000       0.7781500000 &#xA;N            0.6512000000       1.8743000000       0.6780500000 &#xA;H            0.6506500000       1.8629500000       0.6293500000 &#xA;H            0.6377000000       1.9210000000       0.6897000000 &#xA;C            0.7522500000       1.6203000000       0.6711500000 &#xA;O            0.8000500000       1.5884500000       0.6478000000 &#xA;N            0.7441500000       1.6229500000       0.7373000000 &#xA;H            0.7062000000       1.6430000000       0.7626500000 &#xA;C            0.7846000000       1.5864500000       0.7839500000 &#xA;H            0.8235000000       1.5591500000       0.7583500000 &#xA;C            0.8207500000       1.6370000000       0.8310000000 &#xA;H            0.8642500000       1.6625000000       0.8076000000 &#xA;H            0.8422000000       1.6092000000       0.8740500000 &#xA;C            0.7798500000       1.6944000000       0.8613500000 &#xA;O            0.8059500000       1.7310500000       0.9021500000 &#xA;O            0.7224000000       1.7127000000       0.8403000000 &#xA;C            0.7384500000       1.5398500000       0.8234500000 &#xA;O            0.6811000000       1.5571000000       0.8332000000 &#xA;N            0.7621000000       1.4808500000       0.8412500000 &#xA;C            0.8239500000       1.4481000000       0.8149000000 &#xA;H            0.8233000000       1.4523500000       0.7595500000 &#xA;H            0.8700000000       1.4686000000       0.8383500000 &#xA;C            0.7235500000       1.4363500000       0.8845000000 &#xA;H            0.6814000000       1.4180500000       0.8561000000 &#xA;C            0.7766000000       1.3802500000       0.8992500000 &#xA;H            0.7567500000       1.3310000000       0.9156000000 &#xA;H            0.8083000000       1.4048000000       0.9377000000 &#xA;C            0.8165000000       1.3747000000       0.8352500000 &#xA;H            0.8635500000       1.3452500000       0.8344000000 &#xA;H            0.7877500000       1.3481000000       0.7958500000 &#xA;C            0.6939500000       1.4610000000       0.9520000000 &#xA;O            0.7159500000       1.5125500000       0.9786500000 &#xA;P            0.7373500000       1.8305000000       0.8972500000 &#xA;K_POINTS automatic&#xA;2 2 2 0 0 0&#xA;CELL_PARAMETERS angstrom&#xA;     20.0000000000       0.0000000000       0.0000000000&#xA;      0.0000000000      20.0000000000       0.0000000000&#xA;      0.0000000000       0.0000000000      20.0000000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Edit: A template input file has been added to the answer.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-03-19T16:47:40.700" LastActivityDate="2024-03-19T16:47:40.700" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12598" PostTypeId="2" ParentId="12538" CreationDate="2024-03-19T07:46:24.517" Score="1" Body="&lt;p&gt;The steps here which worked for me regarding this particular script&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;At the start of the script add required libraries, such as (you can change according to your requirement)&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;import numpy as np&#xA;import scipy.integrate as spi&#xA;from scipy.interpolate import interp1d&#xA;... (other required libraries)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;ol start=&quot;2&quot;&gt;&#xA;&lt;li&gt;Then change the script accordingly.&lt;/li&gt;&#xA;&lt;li&gt;Make sure the Energy is in &lt;span class=&quot;math-container&quot;&gt;$\mathrm{eV}$&lt;/span&gt; and the absorption is in &lt;span class=&quot;math-container&quot;&gt;$\mathrm{cm}^{-1}$&lt;/span&gt; (it should technically be in &lt;span class=&quot;math-container&quot;&gt;$\mathrm{m}^{-1}$&lt;/span&gt;).&lt;/li&gt;&#xA;&lt;li&gt;Put minimum value of the band gap of your structure for - &lt;code&gt;material_direct_allowed_gap&lt;/code&gt;, &lt;code&gt;material_indirect_gap&lt;/code&gt;&lt;/li&gt;&#xA;&lt;li&gt;Change values of thickness and temperature to get SLME values at your required data values.&lt;/li&gt;&#xA;&lt;li&gt;A logarithmic plot of thickness vs SLME can be plotted for analysis now.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Good luck! Hope it works for you as well as me, I hope there are no problems here. If I find any, I will update. You are welcome to update as well so that I can also learn and change.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="6055" LastEditDate="2024-03-19T07:53:11.883" LastActivityDate="2024-03-19T07:53:11.883" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12599" PostTypeId="1" CreationDate="2024-03-19T07:47:34.713" Score="6" ViewCount="55" Body="&lt;p&gt;I am not able to do Isolated atom calculation for finding out Formation energy in WIEN2k. I don't know where I am going wrong, which steps are wrong. Can anyone please list me the steps? What I tried is this - created a 2x2x2 supercell with P structure. Then gave k points as 1 1 1. Tried first by giving spin polarization (saw one line from user guide which said to do it), then without spin. Using the struct file formed by supercell with enough lattice parameter distance between atoms. But nothing seems to be working.&lt;/p&gt;&#xA;" OwnerUserId="2077" LastEditorUserId="142" LastEditDate="2024-03-21T15:54:08.837" LastActivityDate="2024-03-21T15:54:08.837" Title="Isolated atom calculation in Wien2k" Tags="|formation-energy|wien2k|isolated-atom|" AnswerCount="1" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12600" PostTypeId="1" CreationDate="2024-03-19T09:49:49.530" Score="4" ViewCount="144" Body="&lt;p&gt;I am trying to perform a geometry optimization (GEO_OPT) of a FCC 111 &lt;span class=&quot;math-container&quot;&gt;$Pt_{0.5}Au_{0.5}$&lt;/span&gt; bimetallic surface (10x10x3) generated from ASE, with a lattice parameter of 3.9 &lt;span class=&quot;math-container&quot;&gt;$\overset{\circ}{\mathrm{A}}$&lt;/span&gt; in CP2K. However, after the geometry optimization is completed, the visualization of the coordinates show that the top layer gold atoms are moving away from the surface layer.&lt;/p&gt;&#xA;&lt;p&gt;I am using &lt;code&gt;CUTOFF 400&lt;/code&gt; and &lt;code&gt;REL_CUTOFF 60&lt;/code&gt; for the calculations. I am unable to figure out how to resolve the problem. I think the forces are very high. I am trying a cell optimization calculation.&lt;/p&gt;&#xA;&lt;p&gt;Will this be useful? Or should I change something else in the geometry optimization calculations?&lt;/p&gt;&#xA;&lt;p&gt;Any help will be much appreciated. Thanks in advance.&lt;/p&gt;&#xA;&lt;p&gt;Edit: As per the request of @Phil Hasnip, I am uploading the images of&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;before optimization&lt;a href=&quot;https://i.stack.imgur.com/Elzxr.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Elzxr.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/li&gt;&#xA;&lt;li&gt;After Optimization&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/iIAD4.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/iIAD4.png&quot; alt=&quot;After Optimization&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;code&gt;MAX_FORCE&lt;/code&gt; is set to 4.5d-4 and &lt;code&gt;RMS_FORCE&lt;/code&gt; is set to 3d-4 for the optimization. All these values converges as per the cp2k output file. Thanks.&lt;/p&gt;&#xA;" OwnerUserId="7646" LastEditorUserId="7646" LastEditDate="2024-03-23T06:32:28.753" LastActivityDate="2024-03-23T06:32:28.753" Title="Help regarding Geometry Optimization of a bimetallic surface" Tags="|density-functional-theory|geometry-optimization|atomic-simulation-environment|surfaces|cp2k|" AnswerCount="0" CommentCount="10" ContentLicense="CC BY-SA 4.0" />
  <row Id="12601" PostTypeId="2" ParentId="12585" CreationDate="2024-03-19T16:14:50.827" Score="1" Body="&lt;p&gt;Based on your comments above, it looks like you increased k-point sampling for the 3x3x1 supercell and found the correct dispersions. It seems like the imaginary modes in the smaller cells is due to insufficient sampling of the BZ. Indeed, converging phonon dispersions requires fairly dense BZ sampling, since forces have to be very accurate. The fact that you had unstable modes for the small supercells with coarse BZ sampling, while you had stable modes in the large supercell (implicitly more dense BZ sampling!) is expected. I am glad you got it sorted out!&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-03-19T16:14:50.827" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12602" PostTypeId="1" AcceptedAnswerId="12662" CreationDate="2024-03-19T18:17:39.270" Score="2" ViewCount="62" Body="&lt;p&gt;I am trying to use &lt;a href=&quot;https://docs.scikit-nano.org/dev/install.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;scikit-nano&lt;/a&gt; package to build the various isomers of fullerenes. However, none of the methods that is presented in the manual seem to work for installing the package.&lt;/p&gt;&#xA;&lt;p&gt;These are the steps that I tried for installing the package&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;pip install scikit-nano: keeps searching for dependencies for ~ 15 minutes after which I cancelled the installation.&lt;/li&gt;&#xA;&lt;li&gt;building from the source: installation would be completed, but the import fails with &lt;code&gt;string literal&lt;/code&gt; error.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;gt;&amp;gt;&amp;gt; from sknano.generators import FullereneGenerator&#xA;Traceback (most recent call last):&#xA;  File &amp;quot;&amp;lt;stdin&amp;gt;&amp;quot;, line 1, in &amp;lt;module&amp;gt;&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/generators/__init__.py&amp;quot;, line 6, in &amp;lt;module&amp;gt;&#xA;    from .base import *&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/generators/base.py&amp;quot;, line 24, in &amp;lt;module&amp;gt;&#xA;    from sknano.core.structures import StructureBase&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/core/structures/__init__.py&amp;quot;, line 10, in &amp;lt;module&amp;gt;&#xA;    from .fullerenes import *&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/core/structures/fullerenes.py&amp;quot;, line 98, in &amp;lt;module&amp;gt;&#xA;    class Fullerene(CrystalStructureBase):&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/core/structures/fullerenes.py&amp;quot;, line 123, in Fullerene&#xA;    _data = load_fullerene_data()&#xA;  File &amp;quot;/home/hemanthharidas/scikit-nano/sknano/core/structures/fullerenes.py&amp;quot;, line 54, in load_fullerene_data&#xA;    Niso = int(Niso)&#xA;ValueError: invalid literal for int() with base 10: 'Ih'&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;When I tried to create an issue on the &lt;a href=&quot;https://github.com/scikit-nano/scikit-nano.git&quot; rel=&quot;nofollow noreferrer&quot;&gt;GitHub page&lt;/a&gt;, it seems that the project has been long abandoned, with 5 issues open and the last commit being made approximately 8 years ago.&lt;/p&gt;&#xA;&lt;p&gt;Does anyone have any pointers on how to install this package? My end goal is to test a set of force field parameters on these structures, and manually building them would be cumbersome, even though doable.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-03-19T18:52:45.710" LastActivityDate="2024-03-30T12:17:52.393" Title="Building Fullerenes using scikit-nano package" Tags="|python|software-recommendations|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12603" PostTypeId="1" CreationDate="2024-03-19T18:38:15.620" Score="3" ViewCount="30" Body="&lt;p&gt;I have VASP AIMD Outcar file with Hirshfeld charge per each atom.&lt;/p&gt;&#xA;&lt;p&gt;I hope to convert this outcar file to extxyz file for MACE or NequIP MD framework training. Outcar file contains 800 frames (or images or configurations) of xyz and other data for atoms.&lt;/p&gt;&#xA;&lt;p&gt;For the basic conversion from outcar to extxyz using ASE, I use script like this one:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;input_file=&amp;quot;./input.outcar&amp;quot;&#xA;output_file=&amp;quot;./output.extxyz&amp;quot;&#xA;input_data = read(input_file, index=':', format='vasp-out')&#xA;write(output_file, input_data, format='extxyz')&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Or simply, I can execute&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;$ ase convert input.outcar output.extxyz&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I can calculate virial of system from volume and stress of unit cell&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;input_data.info[&amp;quot;virial&amp;quot;] = -input_data.get_volume() * input_data.get_stress()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But get_volume() and get_stress() cannot be used for list as I read the input file with index &amp;quot;:&amp;quot;, all 800 frames of data. How can print virial of each frame to information line for all 800 frames?&lt;/p&gt;&#xA;&lt;p&gt;Another problem is charge, but this is rather a double-check than a question. We know outcar file print out Hirshfeld charge table as:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;  Hirshfeld-I charges:&#xA;            ion         q(e)        dq(e)&#xA;   ------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;But I think ASE read/write cannot do anything about Hirshfeld charge, I can't find any ASE vasp read/write command related to Hirshfeld charge table.&lt;/p&gt;&#xA;&lt;p&gt;So, I was thinking, I need write my own script to extract and append the Hirshfeld charge as new column to xyz file. Could anyone confirm this about ASE and Hirshfeld charge?&lt;/p&gt;&#xA;&lt;p&gt;Thanks&lt;/p&gt;&#xA;" OwnerUserId="74" LastEditorUserId="74" LastEditDate="2024-03-19T18:47:13.340" LastActivityDate="2024-03-19T18:47:13.340" Title="Convert VASP Outcar to extxyz with hershfeld charge and virial data for all frames using ASE?" Tags="|atomic-simulation-environment|geometry|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12605" PostTypeId="1" CreationDate="2024-03-20T07:19:19.183" Score="4" ViewCount="153" Body="&lt;p&gt;I want to optimize a system containing a metal ion in between two graphite sheets. For that can I use Gaussian software? If so how can I create the input file with two graphite sheets?&lt;/p&gt;&#xA;" OwnerUserId="6239" LastActivityDate="2024-03-20T12:23:57.673" Title="Can we build two graphite sheets as an input file in Gaussian?" Tags="|gaussian|optimization|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12606" PostTypeId="2" ParentId="12605" CreationDate="2024-03-20T12:23:57.673" Score="3" Body="&lt;p&gt;As @Camps mentioned, Gaussian is not the best for periodic structures. However, if you want to build the structure, you can use Gview. It is an excellent software for creating any desired geometry. You must use the PBC and Point groups symmetry inside Gview to make any periodic structure. An excellent step-by-step method is provided &lt;a href=&quot;http://www.chemistry4.me/Gaussian/G09W/help/pbctut2.htm&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; to create Graphene. You can also create other periodic sheets using the technique described there.&lt;/p&gt;&#xA;" OwnerUserId="2194" LastActivityDate="2024-03-20T12:23:57.673" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12607" PostTypeId="1" CreationDate="2024-03-20T14:18:41.310" Score="2" ViewCount="20" Body="&lt;p&gt;I want to create a &lt;strong&gt;1M NaCl solution&lt;/strong&gt; in a &lt;strong&gt;1nm X 1nm X 1nm&lt;/strong&gt; size cell using PACKMOL. So, what should be the NaCl:H2O ratio for this concentration? My calculation is -&lt;/p&gt;&#xA;&lt;p&gt;1M NaCl = 1 mole NaCl + 1000 mL H2O&#xA;= 1 mole NaCl + 1000 g H2O&#xA;= 1 mole NaCl + 55.85 mole H2O&lt;/p&gt;&#xA;&lt;p&gt;So, NaCl:H2O = 1:55.85.&lt;/p&gt;&#xA;&lt;p&gt;What is the role of simulation cell size in this case? How does it affect the molar concentration?&lt;/p&gt;&#xA;" OwnerUserId="9977" LastActivityDate="2024-03-20T14:18:41.310" Title="Creating 1M NaCl solution using PACKMOL" Tags="|molecular-modeling|atomistic-simulation|packmol|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12608" PostTypeId="1" CreationDate="2024-03-20T18:30:54.560" Score="2" ViewCount="32" Body="&lt;p&gt;Before I start; sorry for this lengthy question.&lt;/p&gt;&#xA;&lt;p&gt;I am confused about choosing the correct set of K points for the K-convergence test for VASP calculations. The system of my interest has an &lt;strong&gt;orthorhombic&lt;/strong&gt; structure with a=&lt;strong&gt;7&lt;/strong&gt; A,b=&lt;strong&gt;11.5&lt;/strong&gt; A,c=&lt;strong&gt;6.5&lt;/strong&gt; A lattice constants. How can I choose the correct set of K points?&lt;/p&gt;&#xA;&lt;p&gt;It’s so confusing!!!!!&#xA;Please help.&lt;/p&gt;&#xA;" OwnerUserId="2104" LastEditorUserId="5" LastEditDate="2024-03-22T00:54:29.523" LastActivityDate="2024-03-22T00:54:29.523" Title="How to choose k grid using pymatgen for VASP?" Tags="|density-functional-theory|vasp|k-points|convergence-test|pymatgen|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12609" PostTypeId="1" CreationDate="2024-03-20T18:36:37.363" Score="1" ViewCount="31" Body="&lt;p&gt;I am looking for suggestions for a free cloud-computing platform for running the VASP simulations. I do have the VASP license. I am also ok, if I am allowed to use for a week or so.&lt;/p&gt;&#xA;&lt;p&gt;I can also install the VASP there, in case it is not installed there.&lt;/p&gt;&#xA;&lt;p&gt;Please do suggest something in this regard.&lt;/p&gt;&#xA;&lt;p&gt;Regards&lt;/p&gt;&#xA;" OwnerUserId="1715" LastActivityDate="2024-03-20T18:36:37.363" Title="Free Cloud Computing for VASP Simulation" Tags="|vasp|software|high-performance-computing|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12611" PostTypeId="1" CreationDate="2024-03-20T21:34:19.933" Score="9" ViewCount="104" Body="&lt;p&gt;Suppose &lt;span class=&quot;math-container&quot;&gt;$A$&lt;/span&gt; is some hermitian operator and &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt; is a many body state function of a many-body hamiltonian &lt;span class=&quot;math-container&quot;&gt;$H = T + U + V$&lt;/span&gt;, where &lt;span class=&quot;math-container&quot;&gt;$U$&lt;/span&gt; is electron-electron interaction and V is electron-nuclear interaction. Assume I have solved KS equations for the auxiliary system and gotten myself some KS orbitals &lt;span class=&quot;math-container&quot;&gt;$\psi_1,\psi_2,\cdots, \psi_n$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Question: Will I have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle A \rangle = \langle \Psi, A \Psi \rangle = \langle \psi_1\cdots\psi_n, A \psi_1\cdots\psi_n \rangle ?&#xA;$$&lt;/span&gt;&#xA;You can assume I have the exact xc-functional in place, such that this becomes something that is not trivially untrue. In other words, for which operators are the KS orbitals useful in this way to calculate correctly the expectation value of an operator?&lt;/p&gt;&#xA;&lt;p&gt;If the proof is elaborate, could you please provide a reference for the proof?&lt;/p&gt;&#xA;&lt;p&gt;Please let me know in the comments if there are details missing that are making the question unclear. I will add details as needed.&lt;/p&gt;&#xA;" OwnerUserId="8678" LastEditorUserId="8678" LastEditDate="2024-03-20T21:40:32.890" LastActivityDate="2024-03-25T10:24:13.860" Title="Which expectation values can be determined with KS orbitals?" Tags="|density-functional-theory|reference-request|kohn-sham|derivations|expectation-values|" AnswerCount="3" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12612" PostTypeId="1" CreationDate="2024-03-21T05:53:23.890" Score="4" ViewCount="39" Body="&lt;p&gt;How can one analyze the phonon dispersion of 2D materials like graphene to discern specific curves corresponding to particular phonon modes, such as acoustic or optical, as well as longitudinal and transverse modes?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastActivityDate="2024-03-21T18:43:25.860" Title="Exploring Phonon Dispersion in Two-Dimensional Materials: Analytical Techniques and Mode Identification" Tags="|phonons|phonopy|graphene|phonon-dispersion|phonon-density-of-state|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12613" PostTypeId="1" CreationDate="2024-03-21T12:07:00.850" Score="5" ViewCount="35" Body="&lt;p&gt;I’ve to create a heterostructure from two monolayers, for example, two graphene sheets or two metal layers. And then I want to rotate the first layer relative to another one by some angle. The question is how to define a new unit cell in order to calculate it periodically. Are there any algorithms or software to help with that?&lt;/p&gt;&#xA;" OwnerUserId="9976" LastEditorUserId="5" LastEditDate="2024-03-21T12:17:25.513" LastActivityDate="2024-03-21T12:17:25.513" Title="How to determine the unit cell in heterostructure?" Tags="|density-functional-theory|software-recommendations|vesta|supercell|heterostructures|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12614" PostTypeId="1" CreationDate="2024-03-21T13:51:57.557" Score="6" ViewCount="218" Body="&lt;p&gt;I need to determine which of two electrolyte is the best for a hydrogen fuel cell. As far as I understand, the first thing to do is to compute their ionic diffusion coefficient and to compare (the best electrolyte being the one with the highest ionic diffusion coefficient).&#xA;I have never done an AIMD script. Would anyone know of existing scripts that I could adapt (even parts that I could try to complete)?&lt;/p&gt;&#xA;&lt;p&gt;Any help appreciated, many thanks !&lt;/p&gt;&#xA;" OwnerUserId="9985" LastEditorUserId="5" LastEditDate="2024-03-21T14:40:12.910" LastActivityDate="2024-03-23T00:12:37.733" Title="Are there scripts available for AIMD?" Tags="|density-functional-theory|molecular-dynamics|software-recommendations|aimd|abinit|" AnswerCount="2" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12615" PostTypeId="2" ParentId="12599" CreationDate="2024-03-21T15:19:42.977" Score="0" Body="&lt;p&gt;Why did you use a 2x2x2 supercell and not one atom in a large box?&#xA;Some useful guidelines can be found at Wien2K site:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.wien2k.at/reg_user/faq/cohesive.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.wien2k.at/reg_user/faq/cohesive.html&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;http://www.wien2k.at/reg_user/faq/cohesive_energies.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http://www.wien2k.at/reg_user/faq/cohesive_energies.html&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="9976" LastActivityDate="2024-03-21T15:19:42.977" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12616" PostTypeId="2" ParentId="12614" CreationDate="2024-03-21T15:30:41.750" Score="6" Body="&lt;p&gt;I see you used the the tag 'abinit' so I assume you want to do AIMD with abinit. Abinit's documentation is incredible and you should be able to make a lot of progress by looking there! See e.g. the topics page &lt;a href=&quot;https://docs.abinit.org/topics/MolecularDynamics/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and the tutorial on parallelism with MD which gives example input files and results &lt;a href=&quot;https://docs.abinit.org/tutorial/paral_moldyn/&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The 'ab-initio' part really just means that the forces are calculated with DFT vs classical MD where the forces use a classical force-field model. The MD-part (i.e. velocity integration) is very simple. Some codes do more sophisticated things than others, e.g. evolve the electronic coordinates in time using the Car-Parrinello method to avoid the SCF loop. Others extrapolate the density, etc. etc. Similarly, some codes implement more thermostats than others with more user control.&lt;/p&gt;&#xA;&lt;p&gt;I think the MD code in abinit is less refined than other codes. If you want a more sophisticated &lt;em&gt;MD code&lt;/em&gt;, you could try CP2K which also has a lot of &lt;a href=&quot;https://www.cp2k.org/exercises&quot; rel=&quot;nofollow noreferrer&quot;&gt;examples&lt;/a&gt;. It is based on local-orbitals and is a little more geared towards molecules than solids, but I have used it to model crystals before. Quantum ESPRESSO is a good free software that uses plane waves. It has examples distributed with the source code and &lt;a href=&quot;https://www.quantum-espresso.org/tutorials/shanghai-2013/hands-on-aimd/&quot; rel=&quot;nofollow noreferrer&quot;&gt;slides&lt;/a&gt;. Non-free codes like VASP have very sophisticated thermostats. See &lt;a href=&quot;https://www.vasp.at/wiki/index.php/Molecular_dynamics_calculations&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;. VASP also has example code in the &lt;a href=&quot;https://www.vasp.at/tutorials/latest/md/&quot; rel=&quot;nofollow noreferrer&quot;&gt;tutorials&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hopefully this helps get you started!&lt;/p&gt;&#xA;" OwnerUserId="1258" LastEditorUserId="6055" LastEditDate="2024-03-22T04:18:36.240" LastActivityDate="2024-03-22T04:18:36.240" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12617" PostTypeId="2" ParentId="12611" CreationDate="2024-03-21T15:58:26.163" Score="6" Body="&lt;p&gt;The general answer is: no. Take the total spin, &lt;span class=&quot;math-container&quot;&gt;$\hat{\bf S}^2$&lt;/span&gt;, for example. Although quantum chemistry programs typically compute the expectation value &lt;span class=&quot;math-container&quot;&gt;$\langle \hat{\bf S}^2 \rangle$&lt;/span&gt; using the non-interacting orbitals similarly to Hartree-Fock, this procedure is not founded in theory. For more details, I refer to Jacob and Reiher's paper on &lt;a href=&quot;https://doi.org/10.1002/qua.24309&quot; rel=&quot;noreferrer&quot;&gt;Spin in Density-Functional Theory&lt;/a&gt;.&lt;/p&gt;&#xA;" OwnerUserId="142" LastActivityDate="2024-03-21T15:58:26.163" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12618" PostTypeId="2" ParentId="12542" CreationDate="2024-03-21T16:19:47.743" Score="2" Body="&lt;p&gt;Here is a simple Python script that can read forces and stress and store in &lt;code&gt;atoms.arrays&lt;/code&gt;. Note that you cannot do &lt;code&gt;get_stress()&lt;/code&gt; nor &lt;code&gt;get_forces()&lt;/code&gt; because &lt;code&gt;ase.io.read&lt;/code&gt; only assigns a &lt;code&gt;SinglePointCalculator()&lt;/code&gt; with only &lt;code&gt;'energy'&lt;/code&gt; implemented, while properties like &lt;code&gt;'forces'&lt;/code&gt; and &lt;code&gt;'stress'&lt;/code&gt; are not implemented:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read, write&#xA;from ase.visualize import view&#xA;import numpy as np&#xA;&#xA;atoms = read('test.extxyz')&#xA;stress = -atoms.info['virial'] / atoms.get_volume()&#xA;atoms.arrays['stress'] = stress&#xA;results = []&#xA;with open('test.extxyz', 'r') as f:&#xA;    lines = f.readlines()&#xA;    for x in lines:&#xA;        if x != '\n':&#xA;            results.append(x.split(' '))&#xA;forces = np.array(results[2:])[:,4:7].astype(float)&#xA;atoms.arrays['forces'] = forces&#xA;print(forces)&#xA;#[[ 0.         -0.          0.        ]&#xA;# [ 0.          0.         -0.        ]&#xA;# [ 0.01822982  0.09589153 -0.13879486]&#xA;# [-0.01822982 -0.09589153  0.13879486]&#xA;# [-0.09922348 -0.00455073  0.02076133]&#xA;# [ 0.09922348  0.00455073 -0.02076133]&#xA;# [ 0.12483693 -0.01838436  0.00975602]&#xA;# [-0.12483693  0.01838436 -0.00975602]]&#xA;print(stress)&#xA;#[[0.18209646 0.02393531 0.03264563]&#xA;# [0.02393531 0.22451399 0.00381777]&#xA;# [0.03264563 0.00381777 0.18091561]]&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2024-03-21T16:19:47.743" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12619" PostTypeId="2" ParentId="12612" CreationDate="2024-03-21T18:43:25.860" Score="3" Body="&lt;p&gt;Do you know what longitudinal, transverse, acoustic, and optical mean in this context? Or you want a code that can tell you &lt;em&gt;what&lt;/em&gt; they are?&lt;/p&gt;&#xA;&lt;p&gt;If you know what they mean, you can plot the displacements using the *.yaml files output by phonopy &lt;a href=&quot;https://henriquemiranda.github.io/phononwebsite/phonon.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt; and just identify the modes manually. There are a lot of datasets already there that you can play with including the default one which is graphene.&lt;/p&gt;&#xA;&lt;p&gt;For really large cells with lots of modes, it's a lot more tedious to plot the modes manually. I am a neutron scatterer, so I frequently simulate inelastic neutron scattering spectra from DFT phonon calculations. I use &lt;a href=&quot;https://euphonic.readthedocs.io/en/latest/&quot; rel=&quot;nofollow noreferrer&quot;&gt;euphonic&lt;/a&gt;. The neutron scattering intensity depends on the phonon symmetry (~ acoustic vs optical) and polarization (~longitudinal vs optical), so if you are willing to invest the time to learn some of &lt;a href=&quot;https://www.cambridge.org/core/books/introduction-to-the-theory-of-thermal-neutron-scattering/A156AD08D11B8A9968A0735C4974ED3C&quot; rel=&quot;nofollow noreferrer&quot;&gt;the underlying theory&lt;/a&gt;, this method is very powerful and can help you identify the &amp;quot;character&amp;quot; of phonons.&lt;/p&gt;&#xA;&lt;p&gt;If you aren't sure what optical vs. acoustic and longitudinal vs. transverse means, that should be posted as another question or you can look in practically any solid-state physics text book. For complex unitcells in 3D, its really somewhat ambiguous to distinguish between acoustic and optical modes except near the zone-center where acoustic modes have vanishing frequency. Moreover, many phonons have mixed longitudinal/transverse character across the BZ. In my opinion, calculating the neutron scattering structure factor is one of the most direct ways to characterize the phonons since it has a real connection to experiment (there is really no other way to measure dispersions). It just requires a lot of &amp;quot;cost&amp;quot; up front to learn how to interpret the results.&lt;/p&gt;&#xA;&lt;p&gt;I hope this helps!&lt;/p&gt;&#xA;&lt;p&gt;Ty&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-03-21T18:43:25.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12621" PostTypeId="2" ParentId="12614" CreationDate="2024-03-21T23:37:47.307" Score="5" Body="&lt;p&gt;Just adding to Tyler Sterling's excellent answer, there is also the CASTEP plane-wave DFT program, which is free for academic use (in fact any non-commercial use) and has quite a lot of MD functionality, including:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;a range of ensembles (NVE, NVT, NPT, NPH)&lt;/li&gt;&#xA;&lt;li&gt;several thermostats, including a fast equilibration thermostat (Andersen)&lt;/li&gt;&#xA;&lt;li&gt;path-integral MD for quantum nuclear motion&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;See the &lt;a href=&quot;https://castep-docs.github.io/castep-docs/documentation/Molecular_Dynamics/keywords/&quot; rel=&quot;nofollow noreferrer&quot;&gt;documentation site MD pages&lt;/a&gt; for more details.&lt;/p&gt;&#xA;&lt;p&gt;I've used CASTEP's MD quite a lot for a wide range of simulations, and I think it's quite easy to use (I'm a CASTEP developer though, so I'm not the best person to judge that!).&lt;/p&gt;&#xA;&lt;p&gt;Edit: I should have added where to get the licence! It's here:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://licences.stfc.ac.uk/product/castep&quot; rel=&quot;nofollow noreferrer&quot;&gt;https://licences.stfc.ac.uk/product/castep&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="403" LastEditorUserId="403" LastEditDate="2024-03-23T00:12:37.733" LastActivityDate="2024-03-23T00:12:37.733" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12622" PostTypeId="1" AcceptedAnswerId="12623" CreationDate="2024-03-22T01:03:56.223" Score="6" ViewCount="65" Body="&lt;p&gt;I would like to use the result of a DFTB+ calculation as an SCF initial guess calculation in PySCF.&lt;/p&gt;&#xA;&lt;p&gt;Is there a way to generate the density matrix of the converged calculation and read it with PySCF to perform a subsequent HF or DFT calculation?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance&lt;/p&gt;&#xA;" OwnerUserId="1249" LastEditorUserId="5" LastEditDate="2024-03-25T15:32:33.343" LastActivityDate="2024-03-25T15:32:33.343" Title="May I use a DFTB+ result as initial guess for HF or DFT in PySCF?" Tags="|pyscf|dftb+|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12623" PostTypeId="2" ParentId="12622" CreationDate="2024-03-22T09:21:13.703" Score="6" Body="&lt;p&gt;Not that I am aware of. Hégély and Kállay studied the accuracy of tight-binding initial guesses in &lt;a href=&quot;https://doi.org/10.1002/qua.26782&quot; rel=&quot;nofollow noreferrer&quot;&gt;Int. J. Quantum Chem. 122, e26782 (2021)&lt;/a&gt; and found that the tight-binding guess has a similar level of accuracy to SAD.&lt;/p&gt;&#xA;&lt;p&gt;Even though such an interface is not available, note that the extended Hückel ('huckel') guess in PySCF is basically a tight-binding guess; see &lt;a href=&quot;http://doi.org/10.1021/acs.jctc.8b01089&quot; rel=&quot;nofollow noreferrer&quot;&gt;J. Chem. Theory Comput. 15, 1593 (2019)&lt;/a&gt; for the theory.&lt;/p&gt;&#xA;" OwnerUserId="142" LastEditorUserId="142" LastEditDate="2024-03-25T15:00:31.437" LastActivityDate="2024-03-25T15:00:31.437" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12624" PostTypeId="2" ParentId="12595" CreationDate="2024-03-22T09:39:07.287" Score="6" Body="&lt;p&gt;To allow identifying subsurface interstitial sites (a.k.a. &amp;quot;6fold&amp;quot; sites in ACAT), you need to set &lt;code&gt;allow_6fold=True&lt;/code&gt; when identifying adsorption sites.  For your alloy surface, you can print all &amp;quot;6fold&amp;quot; sites by&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from ase.io import read&#xA;from ase.visualize import view&#xA;from acat.adsorption_sites import SlabAdsorptionSites&#xA;&#xA;atoms = read('POSCAR')&#xA;sas = SlabAdsorptionSites(atoms, surface='fcc111',&#xA;                          allow_6fold=True)&#xA;all_sites = sas.get_sites()&#xA;for st in all_sites:&#xA;    if st['site'] == '6fold':&#xA;        print(st)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You will get information of the subsurface interstitial sites in dictionaries like the following&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;{'site': '6fold', 'surface': 'fcc111', 'morphology': 'subsurf', &#xA; 'position': array([10.0712727 ,  1.49667529, 10.24772459]), &#xA; 'normal': array([-0.01811144, -0.0217874 ,  0.99959856]), &#xA; 'indices': (20, 21, 23, 70, 71, 92), 'composition': None, &#xA; 'subsurf_index': None, 'subsurf_element': None, 'label': None}&#xA;&#xA;{'site': '6fold', 'surface': 'fcc111', 'morphology': 'subsurf', &#xA; 'position': array([13.79910872,  7.94552728, 10.21427464]), &#xA; 'normal': array([-0.00150985,  0.02617928,  0.99965612]), &#xA; 'indices': (20, 22, 23, 66, 68, 88), 'composition': None, &#xA; 'subsurf_index': None, 'subsurf_element': None, 'label': None}&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;For example, if you want to insert interstitial oxygen at the site that coordinates the 6 atoms with indices &lt;code&gt;(20, 22, 23, 66, 68, 88)&lt;/code&gt;, you can just do&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from acat.build import add_adsorbate&#xA;&#xA;add_adsorbate(atoms, adsorbate='O', all_sites=all_sites,&#xA;              indices=(20, 21, 23, 70, 71, 92))&#xA;view(atoms)&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/GPfAs.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/GPfAs.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="3770" LastActivityDate="2024-03-22T09:39:07.287" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12625" PostTypeId="1" CreationDate="2024-03-22T16:29:12.540" Score="4" ViewCount="58" Body="&lt;p&gt;I am performing a set of classical MD simulations using a type of ReaxFF description to study aluminate Oligomerization. I have performed two sets of simulations, one where the system is equilibrated only using an NVT ensemble, and the other where the system is equilibrated using both NPT and NVT ensembles. I observed that the results obtained from NVT equilibrated simulations are significantly different from the ones that were obtained from NPT+NVT equilibrated systems. Interestingly, the box dimensions did not change significantly between these runs, with the initial box length of 15 angstroms relaxing to 15.75 angstroms after the NPT equilibration. Any pointers as to why is this happening would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2024-03-22T16:52:04.877" LastActivityDate="2024-03-22T16:52:04.877" Title="Significant differences between NPT and NVT equilibrated simulations" Tags="|molecular-dynamics|lammps|forcefields|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12626" PostTypeId="2" ParentId="12611" CreationDate="2024-03-23T11:01:37.360" Score="7" Body="&lt;p&gt;Since you ask &amp;quot;which&amp;quot; expectation values can be determined this way, instead of &amp;quot;can all&amp;quot; expectation values be determined this way, I'll briefly mention one case where the Kohn-Sham orbitals indeed result in the correct expectation value.&lt;/p&gt;&#xA;&lt;p&gt;Consider the case where &lt;span class=&quot;math-container&quot;&gt;$A=A(r)$&lt;/span&gt; is a local operator (which is necessarily a one-electron operator). Then&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \Psi, A\Psi \rangle = n\int A(r_1)\Psi^*(r_1,\ldots,r_n)\Psi(r_1,\ldots,r_n) dr_1 dr_2 \cdots dr_n = \int A(r)\rho(r) dr \tag{1}&#xA;$$&lt;/span&gt;&#xA;where &lt;span class=&quot;math-container&quot;&gt;$n$&lt;/span&gt; is the number of electrons and &lt;span class=&quot;math-container&quot;&gt;$\rho(r)$&lt;/span&gt; is the density, since&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;n\int \Psi^*(r_1,\ldots,r_n)\Psi(r_1,\ldots,r_n) dr_2 \cdots dr_n = \rho(r_1) \tag{2}&#xA;$$&lt;/span&gt;&#xA;On the other hand, for the Kohn-Sham determinant we have&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\langle \psi_1\cdots\psi_n, A\psi_1\cdots\psi_n \rangle = \sum_{i=1}^n\int A(r)\psi_i^*(r)\psi_i(r) dr = \int A(r)\rho(r) dr \tag{3}&#xA;$$&lt;/span&gt;&#xA;since the density built from the Kohn-Sham orbitals is equal to the exact density:&#xA;&lt;span class=&quot;math-container&quot;&gt;$$&#xA;\sum_{i=1}^n \psi_i^*(r)\psi_i(r) = \rho(r) \tag{4}&#xA;$$&lt;/span&gt;&#xA;This proves that &lt;strong&gt;the expectation value of a local operator is exactly given as its expectation value over the Kohn-Sham determinant.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Meanwhile, not all one-electron operators have this property. For example the expectation value of the kinetic energy operator over the Kohn-Sham determinant gives the non-interacting kinetic energy &lt;span class=&quot;math-container&quot;&gt;$T_s$&lt;/span&gt;, which is famously not equal to the exact kinetic energy (although usually very close to it - that's why Kohn-Sham DFT works so much better than orbital-free DFT with common approximate functionals); part of the kinetic energy is in the exchange-correlation energy, specifically the correlation part. Two-electron operators in general do not have this property either, as demonstrated by Susi's nice example. It is however an interesting question whether there are non-local operators whose expectation value over the Kohn-Sham determinant always agrees with the expectation value over the many-electron wavefunction &lt;span class=&quot;math-container&quot;&gt;$\Psi$&lt;/span&gt;, for which I have no answer...&lt;/p&gt;&#xA;" OwnerUserId="838" LastActivityDate="2024-03-23T11:01:37.360" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12627" PostTypeId="2" ParentId="12611" CreationDate="2024-03-23T20:47:17.800" Score="5" Body="&lt;p&gt;It cannot hold for all observables. This is a more or less straightforward consequence of the Hilbert space structure of quantum mechanics and DFT plays no role.&lt;/p&gt;&#xA;&lt;p&gt;Indeed, consider two normalized vectors &lt;span class=&quot;math-container&quot;&gt;$\psi,\phi\in H$&lt;/span&gt;. If for all hermitian &lt;span class=&quot;math-container&quot;&gt;$A\in B(H)$&lt;/span&gt; it holds that &lt;span class=&quot;math-container&quot;&gt;$\langle \psi,A\psi\rangle=\langle \phi,A\phi\rangle$&lt;/span&gt;, then &lt;span class=&quot;math-container&quot;&gt;$\psi=e^{i\varphi}\phi$&lt;/span&gt; for some &lt;span class=&quot;math-container&quot;&gt;$\varphi\in \mathbb R$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Hence, if &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; correspond to a different state (i.e. differ by more than a phase), then there is at least one (bounded) observable which recognizes this.&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;As an explicit and easy example, consider the observable &lt;span class=&quot;math-container&quot;&gt;$A=|\psi\rangle\langle\psi|$&lt;/span&gt;. Then&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$$\langle \phi,A\phi\rangle=|\langle \phi,\psi\rangle|^2&amp;lt; ||\psi||^2 ||\phi||^2=1=\langle \psi,A\psi\rangle\quad , $$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;by Cauchy-Schwarz, as long as &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$\phi$&lt;/span&gt; differ by more than a phase.&lt;/p&gt;&#xA;&lt;p&gt;Thus, as long as the many-body state &lt;span class=&quot;math-container&quot;&gt;$\psi$&lt;/span&gt; is not equal to the &amp;quot;Kohn-Sham state&amp;quot; &lt;span class=&quot;math-container&quot;&gt;$\phi=\psi_1\cdots \psi_n$&lt;/span&gt; there always exist observables which can distinguish these states by their expectation values.&lt;/p&gt;&#xA;" OwnerUserId="1484" LastEditorUserId="1484" LastEditDate="2024-03-25T10:24:13.860" LastActivityDate="2024-03-25T10:24:13.860" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12628" PostTypeId="1" AcceptedAnswerId="12629" CreationDate="2024-03-23T21:53:29.200" Score="8" ViewCount="363" Body="&lt;p&gt;I am trying to perform DFT calculations on lead halide perovskite system using Quantum Espresso However, I am confused in choosing the pseudopotentials. The hybrid pseudopotentials are recommended to use but I am unable to find the hybrid pseudopotentials. Is there any library for hybrid pseudopotentials?&lt;/p&gt;&#xA;&lt;p&gt;It is suggested to use other pseudopotentials (such as PBE) and put &lt;code&gt;input_dft&lt;/code&gt; variable in &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; card. What will change in the calculations by putting this variable?&lt;/p&gt;&#xA;" OwnerUserId="8738" LastEditorUserId="6055" LastEditDate="2024-03-24T13:23:10.733" LastActivityDate="2024-03-24T13:23:10.733" Title="How to choose hybrid pseudopotentials in Quantum ESPRESSO?" Tags="|density-functional-theory|quantum-espresso|pseudopotentials|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12629" PostTypeId="2" ParentId="12628" CreationDate="2024-03-24T03:14:32.283" Score="9" Body="&lt;p&gt;TLDR: enforce the hybrid functional using &lt;code&gt;input_dft&lt;/code&gt; keyword. Check the exchange-correlation (XC) functional of your hybrid functional and use any pseudopotentials that has the same XC functional.&lt;/p&gt;&#xA;&lt;p&gt;From Quantum ESPRESSO's &lt;a href=&quot;https://www.quantum-espresso.org/faq/faq-pseudopotentials/&quot; rel=&quot;noreferrer&quot;&gt;FAQ&lt;/a&gt;:&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;2.7 WHERE CAN I FIND PSEUDOPOTENTIAIS FOR HYBRID/NONLOCAL FUNCTIONALS?&#xA;Short answer: nowhere, for the time being. Use pseudopotentials for the non-hybrid functional that is closer to the hybrid you like: PBE for PBE0 and HSE, BLYP for B3LYP. Same for nonlocal (e.g. vdw-DF) functionals: use pseudopotentials generated for the closest GGA functional.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;p&gt;This means there is no special pseudopotentials for hybrid calculation. You need to use the keyword &lt;code&gt;input_dft&lt;/code&gt; in the &lt;code&gt;&amp;amp;SYSTEM&lt;/code&gt; namelist to specify the type of hybrid functional you are using. Every hybrid functional has two parts: one coming from the exact exchange and the other coming from some other sources. The pseudopotentials should be chosen from the set of regular pseudopotentials that has the same other XC functional. For example, HSE06 or PBE0 or gauPBE functionals are formed from a combination of PBE functional and exact exchange. So, you should set &lt;code&gt;input_dft='hse'&lt;/code&gt; or &lt;code&gt;input_dft='pbe0'&lt;/code&gt; or &lt;code&gt;input_dft='gaup'&lt;/code&gt;, respectively and use any pseudopotentials with PBE XC functional. See &lt;a href=&quot;https://github.com/QEF/q-e/blob/develop/Modules/funct.f90&quot; rel=&quot;noreferrer&quot;&gt;this&lt;/a&gt; for a list of all allowed values for &lt;code&gt;input_dft&lt;/code&gt; keyword.&lt;/p&gt;&#xA;&lt;p&gt;If you do not put your preferred hybrid functional in the &lt;code&gt;input_dft&lt;/code&gt; variable, then QE will assume that the calculation is not done with hybrid functional and it will read the functional from the pseudopotential file. So, if you use a pseudopotential with PBE functional and leave the &lt;code&gt;input_dft&lt;/code&gt; unspecified, then it will give you a regular PBE level result. You use the &lt;code&gt;input_dft&lt;/code&gt; keyword to specify that you are using a hybrid functional.&lt;/p&gt;&#xA;" OwnerUserId="6055" LastActivityDate="2024-03-24T03:14:32.283" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12630" PostTypeId="1" CreationDate="2024-03-24T16:46:23.190" Score="6" ViewCount="59" Body="&lt;p&gt;I am using the pseudopotentials generated using &amp;quot;atomic&amp;quot; code by &lt;code&gt;A. Dal Corso&lt;/code&gt; after downloading the &lt;code&gt;pslibrary.0.3.1&lt;/code&gt;. Some of the pseudopotentials generated are working properly but some are not giving the error that &lt;code&gt;pseudopotential.UPF&lt;/code&gt; is not readable in Quantum Espresso. The properly working and not readable pseudopotentials along with the scf.in file are provided in a github repository in &lt;a href=&quot;https://github.com/EPR-copenhagen/SCF.git&quot; rel=&quot;nofollow noreferrer&quot;&gt;SCF folder&lt;/a&gt;. Any suggestion regarding this issue would be of a great help.&lt;/p&gt;&#xA;" OwnerUserId="8738" LastEditorUserId="142" LastEditDate="2024-03-27T14:55:58.397" LastActivityDate="2024-03-27T14:55:58.397" Title="Why are some pseudopotentials not readable in Quantum Espresso?" Tags="|density-functional-theory|quantum-espresso|pseudopotentials|" AnswerCount="0" CommentCount="5" ContentLicense="CC BY-SA 4.0" />
  <row Id="12631" PostTypeId="1" CreationDate="2024-03-25T02:23:16.197" Score="3" ViewCount="27" Body="&lt;p&gt;I have designed a high entropy alloy using mcsqs code. Now I want to check its stability. I am wondering if someone can suggest to me what are the minimum parameters that must be reported in a research paper to claim that the designed HEA can be synthesized in the laboratory.&lt;/p&gt;&#xA;" OwnerUserId="1713" LastEditorUserId="5" LastEditDate="2024-03-25T08:11:21.083" LastActivityDate="2024-03-25T08:11:21.083" Title="How to check stability of high entropy alloys" Tags="|alloys|special-quasirandom-structures|alloy-theoretic-automated-toolkit|publishing|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12632" PostTypeId="1" CreationDate="2024-03-25T06:40:03.773" Score="6" ViewCount="39" Body="&lt;p&gt;According to the documentation of &lt;a href=&quot;https://boltztrap2y.readthedocs.io/en/latest/psuwork.html#electrical-conductivity&quot; rel=&quot;nofollow noreferrer&quot;&gt;Boltztrap&lt;/a&gt;, the electrical conductivity is given in the following equation: &lt;span class=&quot;math-container&quot;&gt;$$\sigma=\frac{1}{k_BT}\int_{-\infty }^{\infty }f(1-f)\mathrm{\textbf{X}}(\varepsilon)d\varepsilon\tag{1}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;where &lt;span class=&quot;math-container&quot;&gt;$\mathrm{\textbf{X}}$&lt;/span&gt; is the transport distribution function: &lt;span class=&quot;math-container&quot;&gt;$$X^{\alpha\beta}(\varepsilon)=\frac{e^2}{V}\int_{}^{}\sum_{i}^{}{v}_{i}^{\alpha}(\textbf{K}){v}_{i}^{\beta}(\textbf{K})\tau_{i,k}\delta(\varepsilon-\varepsilon_i(\textbf{K}))\frac{d\textbf{K}}{8\pi^3}\tag{2}$$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Where &lt;em&gt;e&lt;/em&gt; is the electric charge, &lt;em&gt;V&lt;/em&gt; is the volume, &lt;span class=&quot;math-container&quot;&gt;$\tau_{i,k}$&lt;/span&gt; is the relaxation time, and &lt;span class=&quot;math-container&quot;&gt;${v}_{i}^{\alpha}(\textbf{K})$&lt;/span&gt; is the electron group velocity.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;can we consider the calculation of the electrical conductivity according to the above equation in softwares like Boltztrap which as I understand is an implementation of the Boltzmann transport equation to be first-principles?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastEditorUserId="1554" LastEditDate="2024-03-28T06:25:29.503" LastActivityDate="2024-03-28T06:25:29.503" Title="Can Boltzmann transport equation as implemented in Boltztrap software be considered first-principles?" Tags="|electronic-transport|transport|boltztrap|" AnswerCount="0" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12633" PostTypeId="1" CreationDate="2024-03-25T08:19:42.353" Score="4" ViewCount="40" Body="&lt;p&gt;When conducting phonon calculations in VASP using DFPT (Density Functional Perturbation Theory), how do the results obtained using KPOINTS and QPOINTS files compare?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="5" LastEditDate="2024-03-25T08:24:12.140" LastActivityDate="2024-03-25T08:24:12.140" Title="Comparison of Brillouin Zone Sampling Methods: K-points vs. Q-points" Tags="|vasp|phonons|phonopy|phonon-dispersion|" AnswerCount="0" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12634" PostTypeId="1" CreationDate="2024-03-25T14:41:30.410" Score="10" ViewCount="647" Body="&lt;p&gt;I am looking for a nice 2D function which has two minima and one saddle point, and ideally a curved reaction path which I can use to draw contour plots on matplotlib. I will use these contour plots in presentations, poster etc. to demonstrate transition state finding methods, and the intrinsic reaction coordinate etc.&lt;/p&gt;&#xA;&lt;p&gt;I have been using Muller-Brown potential before (which has been used for testing IRC algorithsm before), but it has an intermediate minimum which makes this complicated. (Plot shown below, with red dot being highest saddle point)&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ouEVqm.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ouEVqm.png&quot; alt=&quot;muller-brown-surface&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Are there similar 2D potential energy surfaces which have only one TS and two minima that could be used to explain saddle points, and other such concepts easily?&lt;/p&gt;&#xA;" OwnerUserId="1380" LastActivityDate="2024-03-27T06:44:40.623" Title="A good 2D function for plotting and visual demonstration of transition state, reaction coordinate etc" Tags="|visualization-software|potential-energy-surface|" AnswerCount="2" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12637" PostTypeId="1" CreationDate="2024-03-25T20:11:48.260" Score="5" ViewCount="104" Body="&lt;p&gt;Is there a standardized format that is commonly used across molecular simulation (or QM) software packages to store z-matrix information about a molecule? For instance, in CHARMM, which is a Molecular Dynamics (MD) code, the z-matrix information for a dihedral IJKL is stored as two bond lengths (IJ and KL), two angles (IJK and JKL), and the dihedral (IJKL). Conversely, ORCA prints out the z-matrix information for each atom in the order of bond, angle, and dihedral. Are there any consistent formats for this representation across different software packages?&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="5" LastEditDate="2024-03-26T02:12:51.053" LastActivityDate="2024-03-26T02:35:29.903" Title="How are z-matrices represented in the various matter modeling packages?" Tags="|software|molecular-modeling|one-topic-per-answer|geometry|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12638" PostTypeId="1" CreationDate="2024-03-25T22:10:51.540" Score="2" ViewCount="35" Body="&lt;p&gt;Reymond Research Group from Bern University has created [GDB-17][1], a compendium of molecules in SMILES format. The file is in smi format, how do I parse the molecular structure in xyz from this?&lt;/p&gt;&#xA;" OwnerUserId="7205" LastEditorUserId="5" LastEditDate="2024-03-26T01:17:51.030" LastActivityDate="2024-03-26T20:07:34.393" Title="How to parse GDB SMI file?" Tags="|molecular-modeling|structure|smiles|" AnswerCount="1" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12639" PostTypeId="2" ParentId="12638" CreationDate="2024-03-26T02:11:29.870" Score="1" Body="&lt;p&gt;The GDB-13 dataset follows a simple format, SMILES code first followed by a space.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;quot;&amp;quot;&amp;quot;&#xA;Dataset Sample&#xA;C1=Cc2cc1nnc1snc(o2)-o-1    0   68.18253494262696&#xA;N1C2C3C4C5NC6C7C6C5(C13)C2N47   0   67.35286888122559&#xA;c1c2c[nH]c(nn3cnc(c#1)c3)-s-2   0   65.05410568237305&#xA;N=c1-c2cnn-1cnccc(=O)c2 0   62.522982025146476&#xA;C=Nn1-c2cccconc-1[nH]c2 0   59.586299133300784 &#xA;&amp;quot;&amp;quot;&amp;quot;&#xA;&#xA;&#xA;import re&#xA;&#xA;with open(&amp;quot;gdbdata0.smi&amp;quot;) as f:&#xA;    S = [i.split()[0] for i in f.readlines()]&#xA;    pass&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="7205" LastEditorUserId="7205" LastEditDate="2024-03-26T20:07:34.393" LastActivityDate="2024-03-26T20:07:34.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12640" PostTypeId="2" ParentId="12637" CreationDate="2024-03-26T02:35:29.903" Score="4" Body="&lt;h1&gt;CFOUR&lt;/h1&gt;&#xA;&lt;p&gt;The &lt;a href=&quot;/questions/tagged/cfour&quot; class=&quot;post-tag&quot; title=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; aria-label=&quot;show questions tagged &amp;#39;cfour&amp;#39;&quot; rel=&quot;tag&quot; aria-labelledby=&quot;tag-cfour-tooltip-container&quot;&gt;cfour&lt;/a&gt; software uses one of the most standard formats, and one of the cleanest formats, for z-matrices.&lt;/p&gt;&#xA;&lt;h2&gt;Specification of the format&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;The &lt;strong&gt;first column&lt;/strong&gt; contains a list of all of the nuclei.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;second column&lt;/strong&gt; contains an index that tells us which nucleus will be used for the bond length that is displayed in the &lt;strong&gt;third column&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;fourth column&lt;/strong&gt;  contains an index that tells us which nucleus will be used for the bong angle (along with the other two nuclei that were denoted in columns 1 and 2) that is displayed in the &lt;strong&gt;fifth column&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;li&gt;The &lt;strong&gt;sixth column&lt;/strong&gt; contains the index that tells us which nucleus will be used for the dihedral angle (along with the other three nuclei that were denoted in columns 1, 2, and 4) that is displayed in the &lt;strong&gt;seventh column&lt;/strong&gt;.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;More information can be found in the CFOUR documentation &lt;a href=&quot;https://cfour.uni-mainz.de/cfour/index.php?n=Main.MolecularGeometryInput&quot; rel=&quot;nofollow noreferrer&quot;&gt;here&lt;/a&gt;, including information about &amp;quot;dummy nuclei&amp;quot; (which is mentioned later in this answer) and &amp;quot;ghost nuclei&amp;quot;.&lt;/p&gt;&#xA;&lt;h2&gt;Strengths of the format used by CFOUR&lt;/h2&gt;&#xA;&lt;p&gt;CFOUR allows you to use the same nucleus label more than once (so we do not need to have C1, C2, C3, etc. for the multiple carbon nuclei in a molecule; instead we can just call them all C). CFOUR also allows the numerical bond lengths, bond angles, and dihedral angles, to &lt;em&gt;&lt;strong&gt;easily&lt;/strong&gt;&lt;/em&gt; and &lt;em&gt;&lt;strong&gt;cleanly&lt;/strong&gt;&lt;/em&gt; be represented by variables that can be set separately, unlike PySCF which would require f-strings for this (along with all of the other Python &amp;quot;junk&amp;quot; that would be required to make the z-matrix in the first place).&lt;/p&gt;&#xA;&lt;h2&gt;Weakness of CFOUR&lt;/h2&gt;&#xA;&lt;p&gt;This is more of a weakness of CFOUR rather than the format itself, but CFOUR doesn't allow bond angles that are equal to 0 degrees or 180 degrees (although dihedral angles can certainly be 180 degrees), which can be a problem for linear molecules containing more than two nuclei. &amp;quot;Dummy nuclei&amp;quot; need to be introduced for such molecules. Dummy nuclei also are needed for ring molecules such as benzene. The need for dummy nuclei introduces an inconvenience, since more lines need to be specified in the z-matrix, meaning that more angles and distances need to be determined, and the z-matrix becomes less readable/interpretable, and automatic z-matrix generators might not be able to make such z-matrices. However, sometimes a z-matrix with dummy nuclei can be more efficient for computations than the simpler version that wouldn't require the dummy nuclei.&lt;/p&gt;&#xA;&lt;h2&gt;Benzene example&lt;/h2&gt;&#xA;&lt;p&gt;The following z-matrix was used in my AI ENERGIES database, in &lt;a href=&quot;https://raw.githubusercontent.com/HPQC-LABS/AI_ENERGIES/master/C6H6/out_CFOUR_RHF_def2-TZVPP_CCSDpT.6084831&quot; rel=&quot;nofollow noreferrer&quot;&gt;this file&lt;/a&gt;, and part of it is also available in the above-linked documentation page:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;X                                                                               &#xA;C 1 RCC                                                                         &#xA;C 1 RCC 2 A60                                                                   &#xA;C 1 RCC 3 A60 2 D180                                                            &#xA;C 1 RCC 4 A60 3 D180                                                            &#xA;C 1 RCC 5 A60 4 D180                                                            &#xA;C 1 RCC 6 A60 5 D180                                                            &#xA;H 1 RXH 2 A60 7 D180                                                            &#xA;H 1 RXH 3 A60 2 D180                                                            &#xA;H 1 RXH 4 A60 3 D180                                                            &#xA;H 1 RXH 5 A60 4 D180                                                            &#xA;H 1 RXH 6 A60 5 D180                                                            &#xA;H 1 RXH 7 A60 6 D180                                                            &#xA;                                                                                &#xA;RCC=2.63613014933                                                                 &#xA;RXH=4.68194765185                                                               &#xA;A60=60                                                                          &#xA;D180=180                  &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="5" LastActivityDate="2024-03-26T02:35:29.903" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12641" PostTypeId="1" AcceptedAnswerId="12644" CreationDate="2024-03-26T03:23:01.460" Score="3" ViewCount="63" Body="&lt;p&gt;I am currently conducting a DFT investigation into the magnetism of 2D materials by introducing defects into the structure. Is there a minimum distance I should maintain between two defects in introducing defects into the 2D structure?&lt;/p&gt;&#xA;" OwnerUserId="9983" LastEditorUserId="9983" LastEditDate="2024-03-26T10:39:14.797" LastActivityDate="2024-03-26T21:22:12.670" Title="Is there a minimum inter-defect distance when introducing point defects into a 2D structure, ensuring defects don't exhibit significant interactions?" Tags="|density-functional-theory|quantum-espresso|quantum-chemistry|quantum-mechanics|magnetism|" AnswerCount="1" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12642" PostTypeId="1" AcceptedAnswerId="12645" CreationDate="2024-03-26T08:51:27.663" Score="7" ViewCount="84" Body="&lt;p&gt;In &lt;a href=&quot;https://www.materialscloud.org/learn/data/learn/files/Zem3D6woIu3r/1-4a_day1_handson_Giannozzi_.pdf&quot; rel=&quot;noreferrer&quot;&gt;this tutorial&lt;/a&gt; page 17, it says: &amp;quot;Aluminum is even simpler than Silicon: one atom per unit cell in a fcc lattic&amp;quot;.&lt;/p&gt;&#xA;&lt;p&gt;If it is FCC, then it should be the same as Silicon, two atoms per unit cell, &lt;code&gt;ibrav=2&lt;/code&gt;.&lt;/p&gt;&#xA;" OwnerUserId="6353" LastActivityDate="2024-03-26T21:56:10.010" Title="Have I missed something? &quot;Aluminum is even simpler than Silicon: one atom per unit cell in a fcc lattic&quot;?" Tags="|quantum-espresso|crystallography|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12643" PostTypeId="2" ParentId="12634" CreationDate="2024-03-26T15:38:54.533" Score="6" Body="&lt;p&gt;I would suggest using the egg holder function which is defined by the following formula&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$&#xA;f(x) = -(x_2+47)sin\left(\sqrt{\left| x_2+\frac{x_1}{2} + 47 \right|}\right) - x_1sin\left(\sqrt{\left| x_1-(x_2 + 47) \right|}\right)&#xA;$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;This is a function that has multiple minima (hence the name egg holder function) and has a contour plot that looks like this&#xA;&lt;a href=&quot;https://i.stack.imgur.com/1wbEj.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/1wbEj.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I generated this plot using the following code&lt;/p&gt;&#xA;&lt;pre class=&quot;lang-py prettyprint-override&quot;&gt;&lt;code&gt;import numpy as np&#xA;import matplotlib.pyplot as plt&#xA;&#xA;&#xA;def eggholder(x1: float, x2: float)-&amp;gt;float:&#xA;        term1   =       np.sqrt(np.abs(x2 + 0.5*x1 + 47))&#xA;        term2   =       np.sqrt(np.abs(x1 - (x2 + 47)))&#xA;        return (-1 * (x2+47) * np.sin(term1)) - (x1 * np.sin(term2))&#xA;&#xA;x1      =       np.arange(-512, 513, 1)&#xA;x2      =       np.arange(-512, 513, 1)&#xA;&#xA;X1, X2  =       np.meshgrid(x1, x2)&#xA;Z       =       np.zeros(X1.shape)&#xA;&#xA;for index1, x in enumerate(x1):&#xA;        for index2, y in enumerate(x2):&#xA;                Z[index1][index2]       =       eggholder(x1 = x, x2 = y)&#xA;&#xA;plt.contour(X1, X2, Z)&#xA;plt.colorbar()&#xA;plt.show()&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;You can modify the bounds to zoom in on a particular region and identify the minima and saddle points.&lt;/p&gt;&#xA;&lt;p&gt;The advantage of this function is that it has a lot of minima and saddle points, and you can technically generate any combination of them.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-26T15:38:54.533" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12644" PostTypeId="2" ParentId="12641" CreationDate="2024-03-26T21:22:12.670" Score="4" Body="&lt;p&gt;It depends on the system and the goal.&lt;/p&gt;&#xA;&lt;p&gt;If the goal is to model truly isolated defects (i.e. not clustered together), then you have to use a system large enough that there are no spurious effects of defect-defect interaction. You have to converge the properties you are interested in wrt. to system size.&lt;/p&gt;&#xA;&lt;p&gt;Note that the converged system size for isolated defects depends on the nature of the material. E.g. if the material is metallic, the E-field produced by a charged defect is screened very well and the field falls of quickly with distance. In an insulator, the opposite is true and the E-field from a defect falls of slowly, so you need a large supercell to model an isolated defect.&lt;/p&gt;&#xA;&lt;p&gt;In many cases, point defects arent really isolated and cluster together (e.g. Wadsley defects in TiO2), so you don't necessarily want to keep the defects separated. If you are starting from scratch, you have to sample all possible configurations of the defects and find the most energetically favorable one(s). Note, even for clusters of defects, you still have to converge wrt. to supercell size.&lt;/p&gt;&#xA;&lt;p&gt;Simple combinatorics will show you that you have a lot of calculations to do! I suggest you read papers on the material you want to model. The best case scenario in general is to model defects that were found in experiments (nature picks the lowest energy configuration for you!). Since you are looking at a 2D material, this seems unlikely since not many 2D materials actual exist in the lab. The second best case, is to find papers where other people have done the hard work finding the most likely defects. If you cant find these, find comparable materials and see what defects were studied in those systems.&lt;/p&gt;&#xA;" OwnerUserId="1258" LastActivityDate="2024-03-26T21:22:12.670" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12645" PostTypeId="2" ParentId="12642" CreationDate="2024-03-26T21:56:10.010" Score="8" Body="&lt;p&gt;Silicon is diamond cubic in its most stable phase, with a space group of &lt;span class=&quot;math-container&quot;&gt;$Fd\bar{3}m$&lt;/span&gt; (227), whereas aluminum is face-centered cubic with a crystal symmetry of &lt;span class=&quot;math-container&quot;&gt;$Fm\bar{3}m$&lt;/span&gt; (225). The conventional unit cell of aluminum has four atoms, whereas silicon has eight atoms. However, the diamond cubic structure can be seen as the interlocking of two FCC systems translated by &lt;span class=&quot;math-container&quot;&gt;$(0.25, 0.25, 0.25)$&lt;/span&gt; of the lattice parameter, as shown in the figure below:&#xA;&lt;a href=&quot;https://i.stack.imgur.com/s1bfx.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/s1bfx.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;The primitive unit cell of silicon is same as aluminium with additional motif at &lt;span class=&quot;math-container&quot;&gt;$(0.25,0.25,0.25)$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Sample example of Silicon primitive and conventional unit cell&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS crystal&#xA;Si           0.0000000000       0.0000000000       0.0000000000 &#xA;Si           0.2500000000       0.2500000000       0.2500000000 &#xA;&#xA;CELL_PARAMETERS angstrom&#xA;      2.7154800000       2.7154800000       0.0000000000&#xA;      2.7154800000       0.0000000000       2.7154800000&#xA;      0.0000000000       2.7154800000       2.7154800000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS crystal&#xA;Si           0.0000000000       0.0000000000       0.0000000000 &#xA;Si           0.2500000000       0.7500000000       0.7500000000 &#xA;Si           0.0000000000       0.5000000000       0.5000000000 &#xA;Si           0.2500000000       0.2500000000       0.2500000000 &#xA;Si           0.5000000000       0.0000000000       0.5000000000 &#xA;Si           0.7500000000       0.7500000000       0.2500000000 &#xA;Si           0.5000000000       0.5000000000       0.0000000000 &#xA;Si           0.7500000000       0.2500000000       0.7500000000 &#xA;CELL_PARAMETERS angstrom&#xA;      5.4309600000       0.0000000000       0.0000000000&#xA;      0.0000000000       5.4309600000       0.0000000000&#xA;      0.0000000000       0.0000000000       5.4309600000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Sample example of Aluminium primitive and conventional unit cell&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS crystal&#xA;Al           0.0000000000       0.0000000000       0.0000000000 &#xA;&#xA;CELL_PARAMETERS angstrom&#xA;      2.0200000000       2.0200000000       0.0000000000&#xA;      2.0200000000       0.0000000000       2.0200000000&#xA;      0.0000000000       2.0200000000       2.0200000000&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;pre&gt;&lt;code&gt;ATOMIC_POSITIONS crystal&#xA;Al           0.0000000000       0.0000000000       0.0000000000 &#xA;Al           0.0000000000       0.5000000000       0.5000000000 &#xA;Al           0.5000000000       0.0000000000       0.5000000000 &#xA;Al           0.5000000000       0.5000000000       0.0000000000 &#xA;CELL_PARAMETERS angstrom&#xA;      4.0400000000       0.0000000000       0.0000000000&#xA;      0.0000000000       4.0400000000       0.0000000000&#xA;      0.0000000000       0.0000000000       4.0400000000&#xA;&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="1492" LastActivityDate="2024-03-26T21:56:10.010" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12646" PostTypeId="1" CreationDate="2024-03-26T22:28:36.880" Score="4" ViewCount="36" Body="&lt;p&gt;I am trying to perform a scattering region calculation but I get this error : (from .err file)&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    [node12:360391] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node12:360389] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node12:360390] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node12:360388] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node14:1273154] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node14:1273153] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node04:2275795] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node04:2275793] mca_base_component_repository_open: unable to open mca_btl_vader: libxpmem.so.0: cannot open shared object file: No such file or directory (ignored)&#xA;    [node04:2275795:0:2275795] Caught signal 11 (Segmentation fault: address not mapped to object at address 0x48)&#xA;    ==== backtrace (tid:2275795) ====&#xA;     0 0x0000000000012cf0 __funlockfile()  :0&#xA;     1 0x000000000057bf32 fi_opx_shm_poll_many.constprop.0()  fi_opx_cq_ops_table_non_locking.c:0&#xA;     2 0x00000000003f864b fi_opx_cq_read_FI_CQ_FORMAT_TAGGED_0_OFI_RELIABILITY_KIND_ONLOAD_FI_OPX_HDRQ_MASK_2048_0x0018000000000000ull_FI_PROGRESS_MANUAL()  fi_opx_cq_ops_table_non_locking.c:0&#xA;     3 0x00000000000051ba ompi_mtl_ofi_progress_no_inline()  ???:0&#xA;     4 0x000000000002e20b opal_progress()  ???:0&#xA;     5 0x00000000000d6e58 ompi_mpi_init()  ???:0&#xA;     6 0x000000000007ac17 MPI_Init_thread()  ???:0&#xA;     7 0x0000000000057421 MPI_Init_thread_f08()  ???:0&#xA;     8 0x00000000004f8b45 __m_siesta_init_MOD_siesta_init()  ???:0&#xA;     9 0x000000000040855f main()  ???:0&#xA;    10 0x000000000003ad85 __libc_start_main()  ???:0&#xA;    11 0x000000000040862e _start()  ???:0&#xA;    =================================&#xA;    [node04:2275793:0:2275793] Caught signal 11 (Segmentation fault: address not mapped to object at address (nil))&#xA;    &#xA;    Program received signal SIGSEGV: Segmentation fault - invalid memory reference.&#xA;    &#xA;    Backtrace for this error:&#xA;    ==== backtrace (tid:2275793) ====&#xA;     0 0x0000000000012cf0 __funlockfile()  :0&#xA;     1 0x0000000000668c93 fi_opx_ep_tx_send_internal.constprop.0()  fi_opx_tagged.c:0&#xA;     2 0x000000000062bcde fi_opx_tsenddata_0_FI_AV_MAP_0x0018000000000000ull_OFI_RELIABILITY_KIND_ONLOAD()  fi_opx_tagged.c:0&#xA;     3 0x000000000000bf14 ompi_mtl_ofi_isend_true()  mtl_ofi_isend_opt.c:0&#xA;     4 0x000000000000337b mca_pml_cm_isend()  pml_cm.c:0&#xA;     5 0x00000000000a031c ompi_coll_base_bcast_intra_generic()  ???:0&#xA;     6 0x000000000000707c ompi_coll_tuned_bcast_intra_dec_fixed()  ???:0&#xA;     7 0x0000000000064bd8 MPI_Bcast()  ???:0&#xA;     8 0x0000000000051ae3 pmpi_bcast_()  ???:0&#xA;     9 0x00000000008fb9d2 __mpi__i4_s_MOD_mpi_bcast_t()  ???:0&#xA;    10 0x0000000000898b0f __fdf_MOD_fdf_init()  ???:0&#xA;    11 0x00000000004bfb0e reinit_()  ???:0&#xA;    12 0x00000000004f7f25 __m_siesta_init_MOD_siesta_init()  ???:0&#xA;    13 0x000000000040855f main()  ???:0&#xA;    14 0x000000000003ad85 __libc_start_main()  ???:0&#xA;    15 0x000000000040862e _start()  ???:0&#xA;    =================================&#xA;    &#xA;    ****Program received signal SIGSEGV: Segmentation fault - invalid memory reference.****&#xA;    &#xA;    Backtrace for this error:&#xA;    #0  0x15555290dcef in ???&#xA;    #1  0x155546500f32 in ???&#xA;    #2  0x15554637d64a in ???&#xA;    #3  0x15553ea8e1b9 in ???&#xA;    #4  0x155551b2720a in ???&#xA;    #5  0x155553562e57 in ???&#xA;    #6  0x155553506c16 in ???&#xA;    #7  0x155553477420 in ???&#xA;    #8  0x4f8b44 in ???&#xA;    #9  0x40855e in ???&#xA;    #10  0x155552570d84 in ???&#xA;    #11  0x40862d in ???&#xA;    #12  0xffffffffffffffff in ???&#xA;    #0  0x15555290dcef in ???&#xA;    #1  0x1555465edc93 in ???&#xA;    #2  0x1555465b0cdd in ???&#xA;    #3  0x15553f2a5f13 in ???&#xA;    #4  0x15554400437a in ???&#xA;    #5  0x15555352c31b in ???&#xA;    #6  0x15553ef7f07b in ???&#xA;    #7  0x1555534f0bd7 in ???&#xA;    #8  0x155553471ae2 in ???&#xA;    #9  0x8fb9d1 in ???&#xA;    #10  0x898b0e in ???&#xA;    #11  0x4bfb0d in ???&#xA;    #12  0x4f7f24 in ???&#xA;    #13  0x40855e in ???&#xA;    #14  0x155552570d84 in ???&#xA;    #15  0x40862d in ???&#xA;    #16  0xffffffffffffffff in ???&#xA;    --------------------------------------------------------------------------&#xA;    Primary job  terminated normally, but 1 process returned&#xA;    a non-zero exit code. Per user-direction, the job has been aborted.&#xA;    --------------------------------------------------------------------------&#xA;    --------------------------------------------------------------------------&#xA;    mpirun noticed that process rank 1 with PID 0 on node node04 exited on signal 11 (Segmentation fault).&#xA;    --------------------------------------------------------------------------&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Input File&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;    SolutionMethod        Transiesta&#xA;    &#xA;    SystemName  MX scat&#xA;    SystemLabel scat&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # SPECIES AND BASIS&#xA;    &#xA;    # Number of species &#xA;    NumberOfSpecies 3&#xA;    %block ChemicalSpeciesLabel&#xA;      1  22 Ti&#xA;      2   6 C&#xA;      3   8 O&#xA;    %endblock ChemicalSpeciesLabel&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # K-points&#xA;    &#xA;    %block kgrid_Monkhorst_Pack&#xA;     5    0    0    0.0&#xA;     0    1    0    0.0&#xA;     0    0    50   0.0&#xA;    %endblock kgrid_Monkhorst_Pack&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # Structure&#xA;    NumberOfAtoms 360&#xA;    NumberOfSpecies 3&#xA;    LatticeConstant 1.0 Ang&#xA;    %block LatticeVectors&#xA;    12.144  0   0&#xA;    0   15  0&#xA;    0   0   47.3266&#xA;    %endblock LatticeVectors&#xA;    AtomicCoordinatesFormat  Ang&#xA;    %block AtomicCoordinatesAndAtomicSpecies&#xA;    ...&#xA;    ...&#xA;    ...&#xA;    %endblock AtomicCoordinatesAndAtomicSpecies&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # General variables&#xA;    &#xA;    PAO.BasisSize    SZP&#xA;    PAO.EnergyShift  0.05 Ry  &#xA;    XC.functional   GGA&#xA;    XC.authors      PBE&#xA;    PAO.SplitTailNorm  true&#xA;    PAO.SplitNorm   0.3&#xA;    ElectronicTemperature  100 K &#xA;    MeshCutoff           450. Ry&#xA;    SpinPolarized .false.&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    &#xA;    DM.MixSCF1   T&#xA;    MaxSCFIterations      1000          &#xA;    DM.MixingWeight       0.05          &#xA;    DM.Tolerance          1.d-4         &#xA;    DM.UseSaveDM          true          &#xA;    DM.NumberPulay        5&#xA;    #TS.MixH               yes&#xA;    #Diag.DivideAndConquer  no&#xA;    #Diag.ParallelOverK     yes&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # MD variables&#xA;    &#xA;    MD.FinalTimeStep 1&#xA;    MD.TypeOfRun CG&#xA;    MD.NumCGsteps     000&#xA;    MD.UseSaveXV      .true.&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    # Output variables&#xA;    &#xA;    WriteMullikenPop                1&#xA;    WriteBands                      .false.&#xA;    SaveRho                         .false.&#xA;    SaveDeltaRho                    .false.&#xA;    SaveHS                          .false.&#xA;    SaveElectrostaticPotential      True &#xA;    SaveTotalPotential              no&#xA;    WriteCoorXmol                   .true.&#xA;    WriteMDXmol                     .true.&#xA;    WriteMDhistory                  .false.&#xA;    WriteEigenvalues                yes&#xA;    &#xA;    ==================================================&#xA;    ==================================================&#xA;    &#xA;    # Bias voltage&#xA;    TS.Voltage 0.6 eV&#xA;    %block TS.ChemPots&#xA;      Left&#xA;      Right&#xA;    %endblock TS.ChemPots&#xA;    &#xA;    %block TS.ChemPot.Left&#xA;      mu V/2&#xA;      contour.eq&#xA;        begin&#xA;          c-Left&#xA;          t-Left&#xA;        end&#xA;    %endblock TS.ChemPot.Left&#xA;    %block TS.ChemPot.Right&#xA;      mu -V/2&#xA;      contour.eq&#xA;        begin&#xA;          c-Right&#xA;          t-Right&#xA;        end&#xA;    %endblock TS.ChemPot.Right&#xA;    &#xA;    TS.Elecs.Bulk true&#xA;    TS.Elecs.DM.Update none&#xA;    TS.Elecs.GF.ReUse false&#xA;    TS.ChargeCorrection fermi  &#xA;    &#xA;    %block TS.Elecs&#xA;      Left&#xA;      Right&#xA;    %endblock TS.Elecs&#xA;    &#xA;    %block TS.Elec.Left&#xA;      TSHS ./elec.TSHS&#xA;      chem-pot Left&#xA;      semi-inf-dir -a3&#xA;      elec-pos begin 1&#xA;    %endblock TS.Elec.Left&#xA;    &#xA;    %block TS.Elec.Right&#xA;      TSHS ./elec.TSHS&#xA;      chem-pot Right&#xA;      semi-inf-dir +a3&#xA;      elec-pos end -1&#xA;    %endblock TS.Elec.Right&#xA;    &#xA;    TS.Contours.Eq.Pole 2.5 eV&#xA;    %block TS.Contour.c-Left&#xA;      part circle&#xA;       from   -40.00000 eV + V/2 to -10. kT + V/2&#xA;        points 30&#xA;         method g-legendre&#xA;    %endblock TS.Contour.c-Left&#xA;    %block TS.Contour.t-Left&#xA;      part tail&#xA;       from prev to inf&#xA;        points 10&#xA;         method g-fermi&#xA;    %endblock TS.Contour.t-Left&#xA;    %block TS.Contour.c-Right&#xA;      part circle&#xA;       from   -40.00000 eV - V/2 to -10. kT - V/2&#xA;        points 30&#xA;         method g-legendre&#xA;    %endblock TS.Contour.c-Right&#xA;    %block TS.Contour.t-Right&#xA;      part tail&#xA;       from prev to inf&#xA;        points 10&#xA;         method g-fermi&#xA;    %endblock TS.Contour.t-Right&#xA;    &#xA;    TS.Contours.nEq.Eta 0.0001 eV&#xA;    %block TS.Contours.nEq&#xA;      neq&#xA;    %endblock TS.Contours.nEq&#xA;    %block TS.Contour.nEq.neq&#xA;      part line&#xA;       from -|V|/2 - 5 kT to |V|/2 + 5 kT&#xA;        delta 0.01 eV&#xA;         method mid-rule&#xA;    %endblock TS.Contour.nEq.neq&#xA;    &#xA;    TS.Elecs.Neglect.Principal&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Any help on troubleshooting this error would be much appreciated.&lt;/p&gt;&#xA;" OwnerUserId="8130" LastEditorUserId="6468" LastEditDate="2024-03-26T23:26:17.777" LastActivityDate="2024-03-26T23:26:17.777" Title="Siesta - Segmentation fault error" Tags="|density-functional-theory|siesta|electronic-transport|" AnswerCount="1" CommentCount="3" ContentLicense="CC BY-SA 4.0" />
  <row Id="12647" PostTypeId="2" ParentId="12646" CreationDate="2024-03-26T23:23:12.077" Score="2" Body="&lt;p&gt;The error file shows that some library of the name &lt;code&gt;libxpmem.so&lt;/code&gt; is missing, and i would guess that it is required for the computation to proceed. This would usually mean a faulty installation and would require a reinstallation of the package. You can do &lt;code&gt;ldd siesta&lt;/code&gt; or whatever is your executable to find all the linked shared object files.&lt;/p&gt;&#xA;&lt;p&gt;Note: A quick google search returned that this usually is an MPI problem.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-26T23:23:12.077" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12648" PostTypeId="2" ParentId="12634" CreationDate="2024-03-27T05:39:25.450" Score="6" Body="&lt;p&gt;EDIT:&lt;/p&gt;&#xA;&lt;p&gt;Turns out it can be extremely simple to do. Here are the ingredients:&lt;/p&gt;&#xA;&lt;div class=&quot;s-table-container&quot;&gt;&lt;table class=&quot;s-table&quot;&gt;&#xA;&lt;thead&gt;&#xA;&lt;tr&gt;&#xA;&lt;th&gt;Component&lt;/th&gt;&#xA;&lt;th&gt;Expression&lt;/th&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/thead&gt;&#xA;&lt;tbody&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Curved minimum energy path &lt;br/&gt; (path follows &lt;span class=&quot;math-container&quot;&gt;$y = 0.4 (x^2 - 4x)$&lt;/span&gt;)&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$[y - 0.4(x^2-4x)]^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Ridge (runs down &lt;span class=&quot;math-container&quot;&gt;$x = 0$&lt;/span&gt;) to make saddle point&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$-x^2$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;Wrap it up in a quartic&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$0.1(x^4+y^4)$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;tr&gt;&#xA;&lt;td&gt;And tilt it so the minima have more similar depth&lt;/td&gt;&#xA;&lt;td&gt;&lt;span class=&quot;math-container&quot;&gt;$-0.5x$&lt;/span&gt;&lt;/td&gt;&#xA;&lt;/tr&gt;&#xA;&lt;/tbody&gt;&#xA;&lt;/table&gt;&lt;/div&gt;&#xA;&lt;p&gt;Here's what you get. On left, just the constructed saddle point in the middle of the MEP; on right, two minima thanks to the wrapping quartic.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/jHALz.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/jHALz.png&quot; alt=&quot;On left, just the constructed saddle point in the middle of the MEP; on right, two minima thanks to the wrapping quartic.&#xA;&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;You can make some nightmare fuel energy landscapes with this approach, such as:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$E(x,y) = [y- (\tanh(3x) - 0.5 x)]^2 - x^2 + 0.2 (x^4 + y^4)$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;Good luck, have fun.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/XLSsG.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/XLSsG.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;Original post:&lt;/p&gt;&#xA;&lt;p&gt;Inspired by &lt;a href=&quot;https://mattermodeling.stackexchange.com/a/12635/5184&quot;&gt;Susi Lehtola's answer&lt;/a&gt;, here's a straightforward function:&lt;/p&gt;&#xA;&lt;p&gt;&lt;span class=&quot;math-container&quot;&gt;$z = (x-1)^4 + (y-1)^4 + (x+1)^4 + (y+1)^4 - 20(x-y)^2 + 60x$&lt;/span&gt;&lt;/p&gt;&#xA;&lt;p&gt;The ingredients are:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Adding two quadratic forms gives another quadratic form, and quadratic forms &lt;em&gt;never&lt;/em&gt; have saddle points. But &lt;em&gt;quartic functions&lt;/em&gt; can have saddle points. Indeed, they are the stereotypical smooth 1D two-well functions!&lt;/li&gt;&#xA;&lt;li&gt;So start with two quartics (on hindsight you could also use one).&lt;/li&gt;&#xA;&lt;li&gt;Insert a quadratic &amp;quot;ridge&amp;quot; (in this case the &lt;span class=&quot;math-container&quot;&gt;$(x-y)^2$&lt;/span&gt; term) to induce a saddle point&lt;/li&gt;&#xA;&lt;li&gt;And tilt the whole thing (the &lt;span class=&quot;math-container&quot;&gt;$x$&lt;/span&gt; term) to push the saddle point off the line between both minima.&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;The derivatives are easily calculated as is the minimum energy path -- not just for this particular function but for any combination of quartics, ridges and slopes.&lt;/p&gt;&#xA;&lt;p&gt;The resulting plot:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/Dr89m.png&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/Dr89m.png&quot; alt=&quot;contour plot of quartic listed in question&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="5184" LastEditorUserId="5184" LastEditDate="2024-03-27T06:44:40.623" LastActivityDate="2024-03-27T06:44:40.623" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12649" PostTypeId="1" AcceptedAnswerId="12653" CreationDate="2024-03-27T08:42:45.897" Score="6" ViewCount="348" Body="&lt;p&gt;I have a very small part of a protein that is supposed to be helical. However, in molecular dynamics simulation, it unfolds and gets into extended conformation. Is there any way I can force it to stay helical by applying any restraints, or any other biases? Thanks.&lt;/p&gt;&#xA;" OwnerUserId="1791" LastEditorUserId="5" LastEditDate="2024-03-27T08:53:00.607" LastActivityDate="2024-04-05T15:00:02.093" Title="Restrain a protein to be helical in an MD simulation" Tags="|molecular-dynamics|molecular-modeling|gromacs|proteins|protein-folding|" AnswerCount="3" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12650" PostTypeId="2" ParentId="12649" CreationDate="2024-03-27T09:07:37.830" Score="4" Body="&lt;p&gt;Applying restraints to keep a specific secondary structure is common/mandatory when using coarse grained force fields for MD simulations, try searching for simulations with the MARTINI force field.&lt;/p&gt;&#xA;" OwnerUserId="279" LastActivityDate="2024-03-27T09:07:37.830" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12651" PostTypeId="1" CreationDate="2024-03-27T10:27:40.967" Score="3" ViewCount="41" Body="&lt;p&gt;I am trying to run a scf calculations to obtain the band structure. However,  in the output file, it is show that the convergence is not achieved after 80 iterations.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;&amp;amp;CONTROL&#xA;  calculation = 'scf'&#xA;  etot_conv_thr =   1.0000000000d-04&#xA;  forc_conv_thr =   1.0000000000d-03&#xA;  outdir = './out/'&#xA;  prefix = 'aiida'&#xA;  pseudo_dir = './'&#xA;  tprnfor = .true.&#xA;  tstress = .true.&#xA;  verbosity = 'high'&#xA;/&#xA;&amp;amp;SYSTEM&#xA;  degauss =   1.4699723600d-02&#xA;  ecutrho =   480&#xA;  ecutwfc =   80&#xA;  ibrav = 8&#xA;  celldm(1) = 10.448522166&#xA;  celldm(2) = 1.014828084&#xA;  celldm(3) = 1.432182555&#xA;  nat = 20&#xA;  nosym = .false.&#xA;  nspin = 2&#xA;  ntyp = 3&#xA;  !occupations = 'fixed'&#xA;  nbnd = 104&#xA;  !smearing = 'fermi-dirac'&#xA;  tot_magnetization =   0&#xA;&#xA;/&#xA;&amp;amp;ELECTRONS&#xA;  conv_thr =   1.D-6&#xA;  electron_maxstep = 120&#xA;  mixing_beta =   5.0000000000d-01&#xA;/&#xA;...&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Kindly help me out.&lt;/p&gt;&#xA;" OwnerUserId="9966" LastEditorUserId="6055" LastEditDate="2024-03-27T13:51:25.040" LastActivityDate="2024-03-27T13:51:25.040" Title="convergence not achieved after 80 iterations" Tags="|density-functional-theory|quantum-espresso|condensed-matter|solid-state-physics|numerical-convergence|" AnswerCount="0" CommentCount="2" ClosedDate="2024-04-03T18:29:57.357" ContentLicense="CC BY-SA 4.0" />
  <row Id="12652" PostTypeId="1" CreationDate="2024-03-27T10:57:57.943" Score="5" ViewCount="35" Body="&lt;p&gt;I am currently studying diffusion of oxygen in high entropy alloys. I want to calculate the activation energy from an adsorption site on the surface to the subsurface. I placed the oxygen atom below the adsoprtion site which is the octahedral site. However, the energy there is high and during the transition state calculation there is no transition state even when at the point where the oxygen atom lies on the same plane with the surrounding atoms. Any idea why? For instance the energy I got from one adsorption site is -702.9264 eV whereas that for the final state is -70.6669 eV. I have attached my two POSCARS for the final and initial states.&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;Co Cr Fe Ni  O &#xA; 1.0000000000000000&#xA;    10.0453568374981206    0.0000000000000000    0.0550632930546681&#xA;     5.0062629241308159    8.6637900144891251   -0.0307447571247709&#xA;     0.0000000000000000    0.0000000000000000   24.5023355004677370&#xA; Co  Cr  Fe  Ni  O  &#xA;  24  24  24  24   1&#xA;Selective dynamics&#xA;Cartesian&#xA;  8.7766571015478032  2.1777634888882269  3.1080740310962058   F   F   F&#xA;  6.2782974601486963  7.9582629368528934  1.0190222525127322   F   F   F&#xA;  0.0274266946359444  0.0055177027200366  3.0657900259957507   F   F   F&#xA;  6.2466554474958640  6.5122750488135317  3.0610751658681195   F   F   F&#xA;  8.7627181505054867  6.4954382872392689  3.0559812109569062   F   F   F&#xA;  8.7953340244117282  7.9490487603472797  1.0418268933671475   F   F   F&#xA;  7.5451005419151320  4.3561802749796597  3.1073725012384239   F   F   F&#xA;  9.9963484714175461  5.7599382799285257  1.0248594669588107   F   F   F&#xA;  8.7618449996810774  7.9520263054541989  7.1596134241032052   T   T   T&#xA; 11.3064477104372081  5.0703329320231649  5.1497019503353334   F   F   F&#xA; 10.0511573105272269  5.7748678882568454  7.1697534960504150   T   T   T&#xA; 11.2734085310770347  3.6249672551060113  7.1877668713499805   T   T   T&#xA;  3.7476834024317180  3.6014574163070301  7.1389683868952529   T   T   T&#xA;  3.7781274372021176  5.0611187555175512  5.1174432981350799   F   F   F&#xA;  2.5071304514035702  1.4764318150220832  7.1861125931300869   T   T   T&#xA;  4.9791418842079009  2.8720082750988585  5.1004758717267427   F   F   F&#xA;  3.7607282935853994  5.0949972152369014 11.1491506911820490   T   T   T&#xA;  6.2637032412862954  2.1577927045694798  9.2340933791758939   T   T   T&#xA;  5.0612530356151701  2.9631344192881439 11.1814394828411068   T   T   T&#xA;  6.2824969032520324  0.7429695333939030 11.2080620182675830   T   T   T&#xA;  8.8079117515256051  0.7077715135484740 11.2096953029187318   T   T   T&#xA;  8.8027377709552947  2.1426254744270188  9.2388112581673933   T   T   T&#xA; 12.5403333883320354  7.2706927553702636 11.2320447392269678   T   T   T&#xA; 15.0317183647889490  8.6456670477059578  9.2260538736180404   T   T   T&#xA; 11.2794658606395775  2.1854049478835345  3.0932120682100694   F   F   F&#xA; 13.8429752095551102  8.0081264762626798  1.0400778428739901   F   F   F&#xA;  7.5062089299346431  8.5878716931148436  3.0404139188623431   F   F   F&#xA; 12.5292398688526205  5.7608791135808319  1.0195714317096789   F   F   F&#xA;  3.7534020713146861  6.4536868445706039  3.0447474010419744   F   F   F&#xA;  2.5074845499179261  1.4383185623716952  0.9638242355764692   F   F   F&#xA;  5.0081284709796794  1.4608209784853594  1.0563831099900889   F   F   F&#xA;  2.5235105240125639  4.3337415702800852  3.1074366925071208   F   F   F&#xA; 11.2753394057028125  7.9640142231110476  7.1361958144732673   T   T   T&#xA;  8.8257686223455352  5.1201964714330126  5.1156942476420966   F   F   F&#xA; 12.5303024896312998  5.6962032948874235  7.1731262765432815   T   T   T&#xA;  7.5120332816430118  2.8729491087511030  5.0951878364777858   F   F   F&#xA;  8.7921544303633450  3.5541670778287662  7.1416732646749548   T   T   T&#xA; 12.5418977243371810  7.2141785720310914  5.0637591762744725   F   F   F&#xA;  4.9971848079008145  7.2366809881447560  5.1012547576334244   F   F   F&#xA;  7.5468468348812898  1.4709631772610674  7.2248620684520688   T   T   T&#xA;  6.2808566726596400  5.1549512634835093 11.1891940802054126   T   T   T&#xA;  3.7463734285110966  2.1246516845159920  9.2749614029934779   T   T   T&#xA;  7.5626395776873174  2.8298652491039524 11.1779363858364249   T   T   T&#xA;  2.5062690459128030  0.0096842800291125  9.1805761528538934   T   T   T&#xA;  3.8259180463606159  0.8267908436997687 11.3286656317032950   T   T   T&#xA;  7.5682979533788100  4.2839857617876262  9.1269312920617569   T   T   T&#xA; 10.0114962415541395  4.3511678261842279  9.2684139888958281   T   T   T&#xA;  7.5859861209357415  7.3537074181087663 11.2142595400918204   T   T   T&#xA; 10.0406252428086056  1.4472919183804158  1.0674819665042066   F   F   F&#xA; 11.3049315964151855  3.6464452716285356  1.0584426828238245   F   F   F&#xA;  8.7550358565393758  3.6106197356729708  1.0709064491924392   F   F   F&#xA;  5.0047281251439433  5.8014588244091989  1.0209867053723687   F   F   F&#xA;  7.5159956958965415  5.8066510105756048  1.0716763870576809   F   F   F&#xA;  3.7753407655435969  2.1787215956348089  3.0762459979654637   F   F   F&#xA; 11.2809851393373037  7.9239790621965849  1.0192839404782317   F   F   F&#xA;  5.0419904075874920  0.0137745162262661  3.1010962680446039   F   F   F&#xA; 10.0296815797298109  7.2231519280398118  5.1123536141473682   F   F   F&#xA;  6.2877250092055403  0.7585152667988683  5.1340590875919307   F   F   F&#xA;  3.7378292693297657  0.7226897308432422  5.1465228539603718   F   F   F&#xA; 10.0328783754324178  2.9135288195795317  5.1516664031951427   F   F   F&#xA; 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 0.7488913776000459  0.7483211782917962  0.1243236794642684   F   F   F&#xA;  0.6650578055559109  0.1674124030264323  0.0415158212312434   F   F   F&#xA;  0.4996344114965225  0.2515395125269748  0.1247577710853136   F   F   F&#xA;  0.2510709289178692  0.4996037034576872  0.1251508454354209   F   F   F&#xA;  0.4139564407648514  0.1683785821615087  0.2936907275540203   T   T   T&#xA;  0.4192966940803240  0.6665067325999134  0.2913288929676756   T   T   T&#xA;  0.8326583135781078  0.0832934517283874  0.2086507793501937   F   F   F&#xA;  0.0831518256903081  0.0862568810490103  0.2079024427417338   F   F   F&#xA;  0.4142771789447031  0.4159838270578033  0.2914864395200165   T   T   T&#xA;  0.3317244722225823  0.8340790696931037  0.2081824878979148   F   F   F&#xA;  0.1674658319402113  0.9194780083071055  0.2913291858935960   T   T   T&#xA;  0.9186101039540117  0.1650441399360110  0.2908492879715232   T   T   T&#xA;  0.0789380280568836  0.8401892689874880  0.4570481479841009   T   T   T&#xA;  0.0637406570088894  0.3280311276366524  0.4616525072358368   T   T   T&#xA;  0.4992590235015633  0.7499621165359704  0.3757432306318370   T   T   T&#xA;  0.7481627113292969  0.7538512765965829  0.3750773488723150   T   T   T&#xA;  0.0761719562687376  0.0861958257701179  0.4575145414611073   T   T   T&#xA; -0.0101939275881990  0.5036624097263601  0.3728582540976973   T   T   T&#xA;  0.8270329522360970  0.5896211015886338  0.4587134808476083   T   T   T&#xA;  0.5870113370845126  0.8325013505290396  0.4581622644250204   T   T   T&#xA;  0.1877794975611008  0.4048523460762901  0.4351072193809827   T   T   T&#xA;&#xA;    &#xA; &#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="3442" LastEditorUserId="3442" LastEditDate="2024-03-29T08:09:23.557" LastActivityDate="2024-03-29T08:09:23.557" Title="What is best way to get lowest adsorption site at subsurface of high entropy alloys?" Tags="|density-functional-theory|surfaces|transition-state|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12653" PostTypeId="2" ParentId="12649" CreationDate="2024-03-27T12:12:08.330" Score="4" Body="&lt;p&gt;The general method is to constrain the CA atoms of the protein while you are equilibrating the structure. You can do this in gromacs by creating a posres.itp file that has all the CA atoms, and then having restraints turned on in the mdp file.&lt;/p&gt;&#xA;" OwnerUserId="6468" LastActivityDate="2024-03-27T12:12:08.330" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12654" PostTypeId="1" CreationDate="2024-03-27T14:13:05.337" Score="9" ViewCount="56" Body="&lt;p&gt;Anyone familiar what kind of software is used for drawing the atomic strucutres shown in the attached figure?&#xA;&lt;a href=&quot;https://i.stack.imgur.com/EzEfq.jpg&quot; rel=&quot;noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/EzEfq.jpg&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="1554" LastActivityDate="2024-03-27T14:13:05.337" Title="Software recommendation for drawing atomic structures" Tags="|software|software-recommendations|visualization-software|structure|" AnswerCount="0" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12655" PostTypeId="1" CreationDate="2024-03-27T15:25:06.917" Score="2" ViewCount="43" Body="&lt;p&gt;What mysterious properties lie within the crystalline structure of ψ-graphene, the enigmatic 2D carbon allotrope adorned with intricate 5-6-7 carbon ring patterns, that endows it with the crown of the lowest energy and exceptional dynamic and thermal stability among all known carbon variants? How to get the CIF files of psi graphene&lt;/p&gt;&#xA;" OwnerUserId="10003" LastActivityDate="2024-03-27T15:25:06.917" Title="cif file of psi graphene" Tags="|graphene|" AnswerCount="0" CommentCount="1" ClosedDate="2024-03-28T14:01:08.750" ContentLicense="CC BY-SA 4.0" />
  <row Id="12656" PostTypeId="1" CreationDate="2024-03-27T21:21:49.390" Score="4" ViewCount="39" Body="&lt;p&gt;We are given the IC table for benzene in CHARMM format, which can be written as follows:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;C1 C2 C3 C4 1.42 120 0.000 120.00 1.42&#xA;C2 C3 C4 C5 1.42 120 0.000 120.00 1.42&#xA;C3 C4 C5 C6 1.42 120 0.000 120.00 1.42&#xA;H1 C1 C2 H2 1.00 120 0.000 120.00 1.00&#xA;H3 C3 C4 H4 1.00 120 0.000 120.00 1.00&#xA;H5 C5 C6 H6 1.00 120 0.000 120.00 1.00&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;This is for the case where the molecule has &lt;span class=&quot;math-container&quot;&gt;$D_{6h}$&lt;/span&gt; symmetry.&lt;/p&gt;&#xA;&lt;p&gt;Assume that we do not know what the point group of the molecule is and would like to have an algorithm to identify the point group of the molecule. I know the existence of this flowchart which shows the procedure to identify the point group of any molecule. However, this is something that is more intuitive to a human being and not for a computer. In that case, how can we then identify the point group based on the information from the IC table.&lt;/p&gt;&#xA;&lt;p&gt;I had previously asked this &lt;a href=&quot;https://mattermodeling.stackexchange.com/questions/10160/locating-symmetry-equivalent-atoms-from-distance-matrix&quot;&gt;question&lt;/a&gt; where I was instructed to use libmysm package to identify the molecular point group. However, here I am looking for a general algorithm that can do this from z-matrices.&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/VZwNK.gif&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/VZwNK.gif&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="6468" LastEditorUserId="6468" LastEditDate="2024-03-28T01:36:28.077" LastActivityDate="2024-03-28T01:36:28.077" Title="How can we identify the symmetry of the molecule from its IC table?" Tags="|molecular-modeling|symmetry|algorithms|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12657" PostTypeId="1" CreationDate="2024-03-28T08:48:31.940" Score="4" ViewCount="59" Body="&lt;p&gt;How to construct a QPOINTS file for phonon calculations in VASP, and when is it employed instead of KPOINTS during a VASP standard run for phonon calculations? Could anyone also provide the preferred format style for specifying q-points in the QPOINTS file?&lt;/p&gt;&#xA;" OwnerUserId="8802" LastEditorUserId="5" LastEditDate="2024-03-28T11:21:19.993" LastActivityDate="2024-03-31T16:38:43.223" Title="Creating a QPOINTS File for Phonon Calculations in VASP" Tags="|vasp|phonon-dispersion|q-points|" AnswerCount="0" CommentCount="9" ContentLicense="CC BY-SA 4.0" />
  <row Id="12658" PostTypeId="1" CreationDate="2024-03-28T12:46:19.510" Score="3" ViewCount="24" Body="&lt;p&gt;Suppose a benzene ring is connected with copper nanorod on both side along the z axis and they compose the scattering region. On both sides of the scattering region along the z axis, the left and right leads are both iron nanorod.&lt;/p&gt;&#xA;&lt;p&gt;I want to simulate the thermal conductance through the Non-Equilibrium Molecular Dynamics (NEMD) with LAMMPS.&lt;/p&gt;&#xA;&lt;p&gt;Would anyone please tell me how to divide the whole structure into several boxes, which could contain the scattering region, for the 'fix heat' method calculation? How to set up the parameter?&lt;/p&gt;&#xA;&lt;p&gt;Thank you in advance.&lt;/p&gt;&#xA;" OwnerUserId="4343" LastActivityDate="2024-03-28T12:46:19.510" Title="How to set up the NEMD (Non-Equilibrium Molecular Dynamics) calculation in LAMMPS" Tags="|molecular-dynamics|lammps|lattice-thermal-conductivity|nonequilibrium|" AnswerCount="0" CommentCount="2" ContentLicense="CC BY-SA 4.0" />
  <row Id="12659" PostTypeId="1" CreationDate="2024-03-28T15:57:00.470" Score="4" ViewCount="15" Body="&lt;p&gt;I am currently writing an algorithm to generate bidisperse random close packed configurations of disks with the aim of calculating the packing fraction with varying disk concentration &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt; and disk ratio &lt;span class=&quot;math-container&quot;&gt;$D$&lt;/span&gt;.&lt;/p&gt;&#xA;&lt;p&gt;The broad outline of the algorithm is as follows:&lt;/p&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Begin with a deterministically disordered nucleus of 6 disks&lt;/li&gt;&#xA;&lt;li&gt;Choose the next disk diameter with probability &lt;span class=&quot;math-container&quot;&gt;$p$&lt;/span&gt;&lt;/li&gt;&#xA;&lt;li&gt;Place this disk such it touches the previously placed disk and an appropriate site&lt;/li&gt;&#xA;&lt;li&gt;The disk is moved until an appropriate position is found&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;After the lattice has been built the packing fraction can be calculated&lt;/p&gt;&#xA;&lt;p&gt;The algorithm seems to correctly generate random close packed configurations. The issue I am having is that the trend for the packing fraction seems to be incorrect and I am unsure whether this is due to an issue with the code or is inherent to the algorithm. I thought the trend could be due to crystallization but judging from the lattice configurations this does not seem to be the case.&lt;/p&gt;&#xA;&lt;p&gt;Here are some example generations:&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/ACkSi.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/ACkSi.png&quot; alt=&quot;packing configuration&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Packing fraction for &lt;span class=&quot;math-container&quot;&gt;$p=0.5$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D=2$&lt;/span&gt;: 0.837&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/SpmMF.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/SpmMF.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Packing fraction for &lt;span class=&quot;math-container&quot;&gt;$p=0.1$&lt;/span&gt; and &lt;span class=&quot;math-container&quot;&gt;$D=2$&lt;/span&gt;: 0.832&lt;/p&gt;&#xA;&lt;p&gt;&lt;a href=&quot;https://i.stack.imgur.com/S9FYZ.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/S9FYZ.png&quot; alt=&quot;Trend for the packing fraction&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;This data was collected for &lt;span class=&quot;math-container&quot;&gt;$D=2$&lt;/span&gt; averaging over 10 runs.&lt;/p&gt;&#xA;&lt;p&gt;The packing fraction is calculated by finding the largest polygon with vertices corresponding to the outer disk positions, then finding the disk area contained within it and dividing this with the polygon area.&lt;/p&gt;&#xA;&lt;p&gt;I have implemented the algorithm in Python using Numpy for array manipulation. After the algorithm has run there are &lt;code&gt;positions&lt;/code&gt; and &lt;code&gt;sizes&lt;/code&gt; arrays containing the disk positions and sizes respectively. There is a &lt;code&gt;largest_polygon&lt;/code&gt; array containing the indices (as the disks are placed sequentially they are labelled from 0 to N) of the largest polygon. There is also a &lt;code&gt;total_disk_area&lt;/code&gt; variable containing the total area of all the disks.&lt;/p&gt;&#xA;&lt;p&gt;The code then does the following to find the packing fraction:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;#Calculate area of cell&#xA;def area(indices, positions):&#xA;    A=0&#xA;    for i in range(0, len(indices)-2):&#xA;        x=positions[indices[i+2]]-positions[indices[i+1]]&#xA;        y=positions[indices[i+1]]-positions[indices[0]]&#xA;        &#xA;        A+=(0.5*(x[0]*y[1]-x[1]*y[0]))&#xA;        &#xA;    return round(abs(A), 5)&#xA;&#xA;#Calculate angle between two vectors&#xA;def angle(v1, v2):&#xA;    if -v1[0]*v2[1]+v1[1]*v2[0] == 0:&#xA;        return 0&#xA;    else:&#xA;        sign=(-v1[0]*v2[1]+v1[1]*v2[0])/abs(v1[0]*v2[1]-v1[1]*v2[0])&#xA;        return(math.acos(np.dot(v1,v2)/(math.sqrt(np.dot(v1,v1)*np.dot(v2,v2))))*sign)&#xA;&#xA;for i in range(len(largest_polygon)):&#xA;    theta=round(np.pi+angle(np.round(positions[largest_polygon[(i+1)%(len(largest_polygon))]]-positions[largest_polygon[i]],decimals=5), np.round(positions[largest_polygon[i]]-positions[largest_polygon[i-1]],decimals=5)),3)&#xA;    total_disk_area-=(theta)*(sizes[largest_polygon[i]]**2)*0.5&#xA;&#xA;total_area=(area(largest_polygon, positions))&#xA;&#xA;packing_fraction=(total_disk_area/total_area)&#xA;#print('Packing fraction: '+str(packing_fraction))&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;I.e. it subtracts the area of the disk not contained within the largest polygon using the angles between the polygon's edges and divides it by the polygon's area.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Is this trend likely a feature of the algorithm or a bug?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;If it is a likely a bug, is there an alternative way to find the packing fraction as I am finding it difficult to test and debug my code? (If needed I post the full code)&lt;/p&gt;&#xA;" OwnerUserId="10004" LastEditorUserId="5" LastEditDate="2024-03-28T16:32:54.180" LastActivityDate="2024-03-28T16:32:54.180" Title="Bidisperse disk packing fraction" Tags="|python|" AnswerCount="0" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12660" PostTypeId="1" AcceptedAnswerId="12704" CreationDate="2024-03-29T14:23:32.577" Score="1" ViewCount="68" Body="&lt;p&gt;I am attempting to complete calculations for atoms using CFOUR.&lt;br /&gt;&#xA;I cloned a GitHub repository that included a correct GENBAS file.&lt;br /&gt;&#xA;I then created a folder outside of the directory of the git clone to complete the calculations.&lt;br /&gt;&#xA;In this folder, I added a correct ZMAT input, a correct script to run the CFOUR calculation, and, most importantly, a symbolic link to the GENBAS file in the git clone directory.&lt;/p&gt;&#xA;&lt;p&gt;The calculation did not yield a working output.&lt;br /&gt;&#xA;I attempted to change the ZMAT input, as I wondered whether that was the source of the  issue.&lt;br /&gt;&#xA;I also tested different scripts to run the calculations.&lt;br /&gt;&#xA;An output was generated in all these cases however it never included a calculation as it couldn’t detect a basis-set in a GENBAS file.&lt;/p&gt;&#xA;&lt;p&gt;I only resolved the problem by copying the GENBAS file directly into the directory where I was running the calculations (and removing the symlink).&lt;/p&gt;&#xA;&lt;p&gt;Are symlinks therefore not compatible with CFOUR calculations?&lt;/p&gt;&#xA;&lt;p&gt;Many thanks for your help.&lt;/p&gt;&#xA;" OwnerUserId="10011" LastEditorUserId="5" LastEditDate="2024-04-04T17:26:22.250" LastActivityDate="2024-04-04T17:26:22.250" Title="Why is my symlink not working?" Tags="|cfour|" AnswerCount="1" CommentCount="8" ContentLicense="CC BY-SA 4.0" />
  <row Id="12662" PostTypeId="2" ParentId="12602" CreationDate="2024-03-30T12:17:52.393" Score="1" Body="&lt;p&gt;I was able to get sknano up and running on python 3.10.12 on Google Colab.&#xA;&lt;a href=&quot;https://i.stack.imgur.com/xsKVE.png&quot; rel=&quot;nofollow noreferrer&quot;&gt;&lt;img src=&quot;https://i.stack.imgur.com/xsKVE.png&quot; alt=&quot;enter image description here&quot; /&gt;&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;Here is the script in case you want to have a look. &lt;a href=&quot;https://colab.research.google.com/drive/13rDgSakZZ-J85Srj3KTpdYULvsC9i7Tv?usp=sharing&quot; rel=&quot;nofollow noreferrer&quot;&gt;Colab-Script&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;I needed to tweak a few files to get it running on python 3.10.12, due to changes in default modules.&lt;/p&gt;&#xA;&lt;p&gt;Here are the changes:&lt;/p&gt;&#xA;&lt;p&gt;In the file:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/usr/local/lib/python3.10/dist-packages/sknano/core/_itertools.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Change the import line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from collections import Iterable&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from collections.abc import Iterable&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;hr /&gt;&#xA;&lt;p&gt;In the files:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;/usr/local/lib/python3.10/dist-packages/sknano/core/math/_extras.py&#xA;/usr/local/lib/python3.10/dist-packages/sknano/structures/_swnt.py&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;Change the line:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from fractions import gcd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;p&gt;To:&lt;/p&gt;&#xA;&lt;pre&gt;&lt;code&gt;from math import gcd&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;" OwnerUserId="6687" LastActivityDate="2024-03-30T12:17:52.393" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12663" PostTypeId="1" CreationDate="2024-03-30T12:52:56.207" Score="7" ViewCount="178" Body="&lt;p&gt;I have done convergence testing for MoS2 (2x2x1) monolayer structure in the following order:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;ecutwfc&lt;/li&gt;&#xA;&lt;li&gt;ecutrho&lt;/li&gt;&#xA;&lt;li&gt;k_points&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;After setting these values, I would like to include vdW correction to the system using DFT-D.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question: should I repeat the convergence testing for the above mentioned parameters?&lt;/strong&gt;&lt;/p&gt;&#xA;" OwnerUserId="10016" LastEditorUserId="1554" LastEditDate="2024-03-30T14:24:07.310" LastActivityDate="2024-04-01T15:24:14.530" Title="Convergence testing in DFT calculation" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|materials-design|convergence-test|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12664" PostTypeId="2" ParentId="12663" CreationDate="2024-03-30T16:12:55.520" Score="8" Body="&lt;p&gt;In general, the answer is no.&lt;/p&gt;&#xA;&lt;p&gt;The convergence steps you have taken allow you to obtain electronic structure and electronic energies at your desired precision. Many dispersion corrections (like Grimme's D3/D4 models) are additive and are not based on the electronic structure (only on geometry), and thus will be unaffected by it.&lt;/p&gt;&#xA;&lt;p&gt;Some additive corrections, like the MBD and XDM models, compute atom dispersion coefficients from the electron density and will, in principle, be affected by the quality of the electronic structure. The use of van der Waals functionals, like vdW-DF or VV10, even entails switching the calculation to a different DFT functional outright (strictly speaking). However, in any of these cases, I would assume that a sufficiently converged electronic density from the base functional, will likely be good enough for a vdW treatment. At least, I have not seen a literature report where &amp;quot;good&amp;quot; settings for plain DFT were insufficient for such methods.&lt;/p&gt;&#xA;" OwnerUserId="3510" LastEditorUserId="3510" LastEditDate="2024-04-01T15:24:14.530" LastActivityDate="2024-04-01T15:24:14.530" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
  <row Id="12665" PostTypeId="2" ParentId="11789" CreationDate="2024-03-30T19:58:04.517" Score="1" Body="&lt;p&gt;You can change the &amp;quot;offset&amp;quot; parameter in ase.build.add_adsorbate to add multiple adsorbates. For example,add_adsorbate(slab,ad,adh,site,offset=(2,1)). As explained in the ASE doc site the adsorbate is added in the order of number of unit cells.&lt;/p&gt;&#xA;&lt;p&gt;offset (default: None): Offsets the adsorbate by a number of unit&#xA;cells. Mostly useful when adding more than one adsorbate.&lt;/p&gt;&#xA;&lt;p&gt;ase.build.add_adsorbate(slab, adsorbate, height, position=(0, 0), offset=None, mol_index=0)&lt;/p&gt;&#xA;" OwnerUserId="10020" LastActivityDate="2024-03-30T19:58:04.517" CommentCount="1" ContentLicense="CC BY-SA 4.0" />
  <row Id="12666" PostTypeId="1" CreationDate="2024-03-31T09:58:09.017" Score="3" ViewCount="32" Body="&lt;p&gt;While investigating 'catalytic activity of MoS2 (monolayer) in hydrogen  evolution reaction', what are the energy corrections that I am supposed to add in the DFT input (using Quantum ESPRESSO) to get meaningful results?&lt;/p&gt;&#xA;" OwnerUserId="10016" LastEditorUserId="5" LastEditDate="2024-04-01T05:58:19.120" LastActivityDate="2024-04-01T05:58:19.120" Title="Energy corrections to be added in my DFT input of Quantum ESPRESSO for studying catalytic activity of MoS2 for hydrogen evolution reaction" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|condensed-matter|materials-engineering|" AnswerCount="0" CommentCount="4" ContentLicense="CC BY-SA 4.0" />
  <row Id="12667" PostTypeId="1" CreationDate="2024-03-31T10:44:34.683" Score="3" ViewCount="76" Body="&lt;p&gt;During a convergence test of (MoS2 2x2x1) monolayer using Quantum ESPRESSO, I tried several K-point Monkhorst-Pack grids. According to my understanding, the calculation time and computational cost should decrease with decreasing K-points density.&lt;/p&gt;&#xA;&lt;p&gt;However as I tried 2x2x1 K-point grid, the calculation was found to be not converging (it stopped after electron_maxstep 80). Upon changing K-points to 3x3x1, I found that the calculation is able to converge within few iterations (~17 iterations). Similarly, It  converged for (4x4x1), (5x5x1), and (6x6x1) grids.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;My question: what is the physical reason behind this non-convergence at this particular K-point?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;For your reference, the following are my basic input and output files:&lt;/p&gt;&#xA;&lt;p&gt;Input file &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/pwscf-k-point-221.in&quot; rel=&quot;nofollow noreferrer&quot;&gt;input.in&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;output file for 2x2x1 sampling &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/pwscf-k-point-221.out&quot; rel=&quot;nofollow noreferrer&quot;&gt;output.out&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;output file for 3x3x1 sampling &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/pwscf-k-point-331.outhttps://&quot; rel=&quot;nofollow noreferrer&quot;&gt;output.out&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;output file for 4x4x1 sampling  &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/pwscf-k-point-441.out&quot; rel=&quot;nofollow noreferrer&quot;&gt;output.out&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;output file for 5x5x1 sampling  &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/pwscf-k-point-551.out&quot; rel=&quot;nofollow noreferrer&quot;&gt;output.out&lt;/a&gt;&lt;/p&gt;&#xA;&lt;p&gt;K-point convergence data summarized &lt;a href=&quot;https://github.com/joyalsunny18/convergence-testing/blob/main/k_point_conv.ods&quot; rel=&quot;nofollow noreferrer&quot;&gt;conv.ods&lt;/a&gt;&lt;/p&gt;&#xA;" OwnerUserId="10016" LastEditorUserId="10016" LastEditDate="2024-04-01T13:39:42.320" LastActivityDate="2024-04-02T07:50:25.073" Title="At a particular K-point (Monkhorst Pack) grid, SCF calculation is not converging" Tags="|density-functional-theory|quantum-espresso|computational-chemistry|k-points|materials-engineering|" AnswerCount="1" CommentCount="6" ContentLicense="CC BY-SA 4.0" />
  <row Id="12668" PostTypeId="1" AcceptedAnswerId="12692" CreationDate="2024-03-31T19:43:06.083" Score="5" ViewCount="49" Body="&lt;p&gt;My supervisor says that GROMACS can do both (all-atom) MD and MC simulations of proteins.&lt;/p&gt;&#xA;&lt;p&gt;I never found anything while searching the Internet about MC-only simulations. As far as I found, GROMACS can do MD+MC hybrid smulation, not pure MC.&lt;/p&gt;&#xA;&lt;p&gt;Does GROMACS have the capability to do Monte Carlo simulations of proteins?&lt;/p&gt;&#xA;" OwnerUserId="3990" LastEditorUserId="3990" LastEditDate="2024-03-31T20:04:46.303" LastActivityDate="2024-04-03T11:27:56.470" Title="Does GROMACS have the capability to do Monte Carlo simulation of proteins?" Tags="|gromacs|monte-carlo|" AnswerCount="1" CommentCount="0" ContentLicense="CC BY-SA 4.0" />
</posts>